From harald@alvestrand.no Mon May 6 05:01:10 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 48E4F21F85E8 for ; Mon, 6 May 2013 05:01:10 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -110.598 X-Spam-Level: X-Spam-Status: No, score=-110.598 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_HI=-8, USER_IN_WHITELIST=-100] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id gU2REC9tE66O for ; Mon, 6 May 2013 05:01:05 -0700 (PDT) Received: from eikenes.alvestrand.no (eikenes.alvestrand.no [158.38.152.233]) by ietfa.amsl.com (Postfix) with ESMTP id 9316421F84A6 for ; Mon, 6 May 2013 05:01:05 -0700 (PDT) Received: from localhost (localhost [127.0.0.1]) by eikenes.alvestrand.no (Postfix) with ESMTP id 3BA6D39E1C4 for ; Mon, 6 May 2013 14:01:04 +0200 (CEST) X-Virus-Scanned: Debian amavisd-new at eikenes.alvestrand.no Received: from eikenes.alvestrand.no ([127.0.0.1]) by localhost (eikenes.alvestrand.no [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id CSX2MROwhhRu for ; Mon, 6 May 2013 14:01:01 +0200 (CEST) Received: from hta-dell.lul.corp.google.com (unknown [IPv6:2620:0:1043:1:be30:5bff:fede:bcdc]) by eikenes.alvestrand.no (Postfix) with ESMTPSA id EA1B439E1BD for ; Mon, 6 May 2013 14:01:00 +0200 (CEST) Message-ID: <51879B7C.6030204@alvestrand.no> Date: Mon, 06 May 2013 14:01:00 +0200 From: Harald Alvestrand User-Agent: Mozilla/5.0 (X11; Linux x86_64; rv:17.0) Gecko/20130329 Thunderbird/17.0.5 MIME-Version: 1.0 To: rmcat@ietf.org Content-Type: multipart/alternative; boundary="------------010104080301020505020305" Subject: [rmcat] Sprout - an algorithm worth checking out? X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Mon, 06 May 2013 12:01:10 -0000 This is a multi-part message in MIME format. --------------010104080301020505020305 Content-Type: text/plain; charset=ISO-8859-1; format=flowed Content-Transfer-Encoding: 7bit I was pointed to this paper some time ago, but only found time to look at it today: https://www.usenix.org/conference/nsdi13/stochastic-forecasts-achieve-high-throughput-and-low-delay-over-cellular-networks From the abstract: " The key idea of Sprout is to adapt the sending rate to roughly match the current cellular network capacity while not overshooting it; by achieving this objective, Sprout can both maintain high throughput and avoid queuing delays in the network. To achieve this goal, Sprout models the cellular link using a Poisson process with an underlying rate which may change over time. Sprout models the evolution of the probability distribution on the underlying rate using Brownian motion, with which Sprout proposes a control protocol to determine the current transmission rate for an end-point. " This seems to be very much within the scope of what RMCAT should be aiming for. Apologies if it is a duplicate. --------------010104080301020505020305 Content-Type: text/html; charset=ISO-8859-1 Content-Transfer-Encoding: 7bit I was pointed to this paper some time ago, but only found time to look at it today:

https://www.usenix.org/conference/nsdi13/stochastic-forecasts-achieve-high-throughput-and-low-delay-over-cellular-networks

From the abstract:

" The key idea of Sprout is to adapt the sending rate to roughly match the current cellular network capacity while not overshooting it; by achieving this objective, Sprout can both maintain high throughput and avoid queuing delays in the network. To achieve this goal, Sprout models the cellular link using a Poisson process with an underlying rate which may change over time. Sprout models the evolution of the probability distribution on the underlying rate using Brownian motion, with which Sprout proposes a control protocol to determine the current transmission rate for an end-point. "

This seems to be very much within the scope of what RMCAT should be aiming for.

Apologies if it is a duplicate.

 --------------010104080301020505020305-- From hannes.tschofenig@gmx.net Mon May 6 05:08:42 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id CDBBE21F8D79 for ; Mon, 6 May 2013 05:08:42 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -100.708 X-Spam-Level: X-Spam-Status: No, score=-100.708 tagged_above=-999 required=5 tests=[AWL=0.433, BAYES_00=-2.599, HTML_MESSAGE=0.001, MIME_HTML_ONLY=1.457, USER_IN_WHITELIST=-100] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id bs1AlO+byrO5 for ; Mon, 6 May 2013 05:08:37 -0700 (PDT) Received: from mout.gmx.net (mout.gmx.net [212.227.15.19]) by ietfa.amsl.com (Postfix) with ESMTP id 7EDD621F8A74 for ; Mon, 6 May 2013 05:08:37 -0700 (PDT) Received: from 3capp-gmx-bs30.server.lan ([172.19.170.82]) by mrigmx.server.lan (mrigmx002) with ESMTP (Nemesis) id 0MFwUq-1UktDb0U7C-00ExCq; Mon, 06 May 2013 14:08:33 +0200 Received: from [194.251.119.198] by 3capp-gmx-bs30.server.lan with HTTP; Mon May 06 14:08:33 CEST 2013 MIME-Version: 1.0 Message-ID: From: "Hannes Tschofenig" To: "Harald Alvestrand" Content-Type: text/html; charset=UTF-8 Date: Mon, 6 May 2013 14:08:33 +0200 (CEST) Importance: normal Sensitivity: Normal In-Reply-To: <51879B7C.6030204@alvestrand.no> References: <51879B7C.6030204@alvestrand.no> X-UI-Message-Type: mail X-Priority: 3 X-Provags-ID: V03:K0:mKXQmX68CRZfls4attrAmeq4hcOKurabE12ECIbUYQF qO1m5SsHti/9hP8MXlJ4dUiP4PZVDVwnLJjV663vNDdmt6ZHpu j3TyL0SuDBQtNHFd2s1Da1ZAEZJxpmvwU7xKZ6Dj++VpEbAgAF 1801v7uMpIZIO3CGdC7z2HWTvtKZlgpOI5oH4qrCA2EkrG4d4D 6FVRvLM4oWPfOk+hMmP/Lio9kuV9JU4nyQTP1J7gEOrhQ/m0qA 675g0RiA2rtRX/kX9yp9MweMzW317elKkeb0Wqd6dfQqg5v67S J+dq7U= Cc: rmcat@ietf.org Subject: Re: [rmcat] Sprout - an algorithm worth checking out? X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Mon, 06 May 2013 12:08:42 -0000
Keith Winstein, the main author of the work, was also at the congestion control workshop last year and briefly mentioned his work there. 
Keith maintains a Webpage, which contains more information about the project (including a video recording of his talk, source code, and data):
 
Definitely workwhile to look at his approach or to reach out to him. 
 
Ciao
Hannes
 
Gesendet: Montag, 06. Mai 2013 um 14:01 Uhr
Von: "Harald Alvestrand" <harald@alvestrand.no>
An: rmcat@ietf.org
Betreff: [rmcat] Sprout - an algorithm worth checking out?
I was pointed to this paper some time ago, but only found time to look at it today:

https://www.usenix.org/conference/nsdi13/stochastic-forecasts-achieve-high-throughput-and-low-delay-over-cellular-networks

>From the abstract:

" The key idea of Sprout is to adapt the sending rate to roughly match the current cellular network capacity while not overshooting it; by achieving this objective, Sprout can both maintain high throughput and avoid queuing delays in the network. To achieve this goal, Sprout models the cellular link using a Poisson process with an underlying rate which may change over time. Sprout models the evolution of the probability distribution on the underlying rate using Brownian motion, with which Sprout proposes a control protocol to determine the current transmission rate for an end-point. "

This seems to be very much within the scope of what RMCAT should be aiming for.

Apologies if it is a duplicate.
 
From michawe@ifi.uio.no Mon May 6 06:51:47 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 526E621F8709 for ; Mon, 6 May 2013 06:51:47 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -102.599 X-Spam-Level: X-Spam-Status: No, score=-102.599 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, USER_IN_WHITELIST=-100] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id TCYLHmjZ1MEm for ; Mon, 6 May 2013 06:51:41 -0700 (PDT) Received: from mail-out1.uio.no (mail-out1.uio.no [IPv6:2001:700:100:10::57]) by ietfa.amsl.com (Postfix) with ESMTP id F3D5A21F910E for ; Mon, 6 May 2013 06:51:25 -0700 (PDT) Received: from mail-mx1.uio.no ([129.240.10.29]) by mail-out1.uio.no with esmtp (Exim 4.75) (envelope-from ) id 1UZLp5-0002Fx-D4 for rmcat@ietf.org; Mon, 06 May 2013 15:51:23 +0200 Received: from boomerang.ifi.uio.no ([129.240.68.135]) by mail-mx1.uio.no with esmtpsa (TLSv1:AES128-SHA:128) user michawe (Exim 4.80) (envelope-from ) id 1UZLp4-0005lx-RT; Mon, 06 May 2013 15:51:23 +0200 From: Michael Welzl Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: quoted-printable Date: Mon, 6 May 2013 15:51:21 +0200 Message-Id: <107C7E14-EC74-4BA2-804B-901BD509D662@ifi.uio.no> To: "rmcat@ietf.org WG" Mime-Version: 1.0 (Apple Message framework v1283) X-Mailer: Apple Mail (2.1283) X-UiO-SPF-Received: X-UiO-Ratelimit-Test: rcpts/h 8 msgs/h 3 sum rcpts/h 10 sum msgs/h 4 total rcpts 4132 max rcpts/h 40 ratelimit 0 X-UiO-Spam-info: not spam, SpamAssassin (score=-5.7, required=5.0, autolearn=disabled, RP_MATCHES_RCVD=-0.653, UIO_MAIL_IS_INTERNAL=-5, uiobl=NO, uiouri=NO) X-UiO-Scanned: 0C06A4F6FD6D762A082FA0CFD30F2C4D0E6EACEC X-UiO-SPAM-Test: remote_host: 129.240.68.135 spam_score: -56 maxlevel 99990 minaction 1 bait 0 mail/h: 3 total 1837 max/h 12 blacklist 0 greylist 0 ratelimit 0 Cc: Stein Gjessing Subject: [rmcat] Call for declarations of interest to submit a paper to Packet Video 2013 X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Mon, 06 May 2013 13:51:47 -0000 Dear all, Stein Gjessing and I are planning to arrange a special session dedicated = to RMCAT at IEEE Packet Video 2013: http://pv2013.itec.aau.at Our proposal for a special session, described below, has been = tentatively accepted by the organizers of IEEE Packet Video 2013. It's = not hard to see that this is indeed pretty RMCAT focused :-) For = final acceptance of our session, we need to have a list of committed = papers already at this stage. Hence, if the topic below is of interest = to you, and you plan to submit a paper to this special session, please = send us: - authors - title - abstract of that paper ***by next Monday (13 May)***. The real deadline for paper submission would then be 10 June. Again, = note that this is not a CFP yet, it's a pre-CFP-call-of-interest... in a = way, informing us that you're planning to submit a paper is similar to = registering a paper before submitting the full thing, I'd say. Cheers, Michael = **************************************************************************= ************************* Special session @ IEEE Packet Video 2013: LIVE - Low-latency Interactive = VidEo Several years ago, it was found that users do not like video quality = fluctuations. At that time the predominant belief was that network rate = fluctuations should be minimized, in order to reasonably interoperate = with TCP in the network. This led to the creation of a number of = so-called "TCP-friendly" congestion controls that exhibit a smoother = sending rate than TCP, while avoiding to send more than a conformant TCP = under similar conditions. TFRC is perhaps the best known example of such = a congestion control mechanism. A lot has happened since then: - The notion of TCP-friendliness has received massive criticism; the = widespread deployment of a more aggressive TCP variant, CUBIC, has not = led to an Internet meltdown, making the case that diverging from strict = TCP-friendliness is possible. - Latency minimization has become a major goal, especially in the face = of "bufferbloat": large delays from large buffers with simplistic = FIFO-queue management. - Codecs have improved; novel video codecs are able to adjust the data = rate, but modern codecs may also produce variable bit rate transmissions = with burstier packet flows than before. - TFRC has been embedded in the DCCP protocol, which has probably never = been used for anything other than experiments; instead of running over = DCCP, RTP-based applications now contain proprietary congestion control = mechanisms. The emergence of the RTCWEB protocol suite for real-time communication = between web browsers has renewed the interest in developing congestion = control standards for real-time media. This time, however, the goal is = to get things right: delay should be minimized, and standards should = realize congestion control using RTP with RTCP signaling. The IETF = "Real-time Media Congestion Avoidance Techniques" (RMCAT) group has been = founded to address this need. New questions arise: what type of = congestion controls do we need? How much feedback should we send? How do = we make this work in multi-user scenarios, e.g. for video conferencing? = What should be the API between a video codec and a new delay-based = congestion controlled RTP stream? What is the quality that can be = expected from the combination of a codec and congestion control = mechanism, when we consider better metrics than plain PSNR? Topics of interest include, but are not limited to: - Congestion control algorithms for interactive real-time video: = requirements, evaluation criteria, and mechanisms - Necessary RTP/RTCP extensions - Field experience with video codecs in a low-delay, real-time setting - Interactions between applications and RTP flows - Failing to meet real-time schedules: impact, techniques to detect, = instrument or diagnose it This activity is partially funded by the European Community under its = Seventh Framework Programme through the Reducing Internet Transport = Latency (RITE) project (ICT-317700). From dan@marketsoup.com Mon May 6 08:01:41 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id E842321F8CB4 for ; Mon, 6 May 2013 08:01:41 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -0.425 X-Spam-Level: X-Spam-Status: No, score=-0.425 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, FH_RELAY_NODNS=1.451, FM_FORGED_GMAIL=0.622, HTML_MESSAGE=0.001, RDNS_NONE=0.1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id rCGwN7TzPw+g for ; Mon, 6 May 2013 08:01:37 -0700 (PDT) Received: from mail-ia0-x232.google.com (mail-ia0-x232.google.com [IPv6:2607:f8b0:4001:c02::232]) by ietfa.amsl.com (Postfix) with ESMTP id C49F821F937B for ; Mon, 6 May 2013 08:01:37 -0700 (PDT) Received: by mail-ia0-f178.google.com with SMTP id t29so3356710iag.9 for ; Mon, 06 May 2013 08:01:37 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=marketsoup.com; s=google; h=mime-version:x-received:x-originating-ip:in-reply-to:references :date:message-id:subject:from:to:cc:content-type; bh=VlJn9SxQYQsMFetzYqfrLz6QXBrLdDxauTADVVOYeFI=; b=AEEfptVDD751ltzvN8lLz8p5QQhZYmL+BTmALr1If8NHZ6xws2Xfe526jFSkvwIs+z MjvKl0EdlAXSOKSh3rAd0gCz/oAyhppX1pLnfrP5sxQALjhZ0L+bf9+r7p87mfu7fK0s hxpY4WH7Sihhlenp6BFrVkJa8Sm1Brxm3BqaQ= X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:x-received:x-originating-ip:in-reply-to:references :date:message-id:subject:from:to:cc:content-type:x-gm-message-state; bh=VlJn9SxQYQsMFetzYqfrLz6QXBrLdDxauTADVVOYeFI=; b=Qi4NDz1mWYGLhDFkAwGXGiO1EmuFFt2bDwCVkenz77BUTy95sRH7DzAQwxJqHQv7lb Dq8HWtZGqLXUQSclFzUGPNt7hs8buhnj0cKPgUDhC1bec1d3ixyxnQfAyyj1Dk1I4sLu cD0SSXjrYfjYVFc/uX6DxKGZBsH/bFBmgbEp6tkhPxvvPKpbUzTGR4IXgX9QL8G6otx0 Qiv78FVNUlhJBBo9REqkLmJxtuwelqpQGPBfaPWJ2vss7AOYAIGHd3uRkMpgGxeyipWu aQornWipQYvSPAuWdwhiKqOVhNji8gHcPbbYo4uyxXxcM4hbH1QEu8VvD9xa1uVnkqpA lXwA== MIME-Version: 1.0 X-Received: by 10.50.236.100 with SMTP id ut4mr2591978igc.86.1367852497321; Mon, 06 May 2013 08:01:37 -0700 (PDT) Received: by 10.42.19.67 with HTTP; Mon, 6 May 2013 08:01:37 -0700 (PDT) X-Originating-IP: [66.87.127.193] Received: by 10.42.19.67 with HTTP; Mon, 6 May 2013 08:01:37 -0700 (PDT) In-Reply-To: References: <51879B7C.6030204@alvestrand.no> Date: Mon, 6 May 2013 09:01:37 -0600 Message-ID: From: Dan Weber To: Hannes Tschofenig Content-Type: multipart/alternative; boundary=14dae9399de3359f8704dc0dfa63 X-Gm-Message-State: ALoCoQnDa/3pcPd5xA+2WHhK5iHMuo5ujDeK5ToQ1878l1O8+9LCBnC7SurvemL5he9VylJ/qlyw Cc: rmcat@ietf.org, Harald Alvestrand Subject: Re: [rmcat] Sprout - an algorithm worth checking out? X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Mon, 06 May 2013 15:01:42 -0000 --14dae9399de3359f8704dc0dfa63 Content-Type: text/plain; charset=UTF-8 I've been keeping in touch with Keith on this very topic. Pretty sure he's also a subscriber to this list. Dan On May 6, 2013 6:08 AM, "Hannes Tschofenig" wrote: > Keith Winstein, the main author of the work, was also at the congestion > control workshop last year and briefly mentioned his work there. > Keith maintains a Webpage, which contains more information about the > project (including a video recording of his talk, source code, and data): > http://alfalfa.mit.edu/ > > Definitely workwhile to look at his approach or to reach out to him. > > Ciao > Hannes > > *Gesendet:* Montag, 06. Mai 2013 um 14:01 Uhr > *Von:* "Harald Alvestrand" > *An:* rmcat@ietf.org > *Betreff:* [rmcat] Sprout - an algorithm worth checking out? > I was pointed to this paper some time ago, but only found time to look > at it today: > > > https://www.usenix.org/conference/nsdi13/stochastic-forecasts-achieve-high-throughput-and-low-delay-over-cellular-networks > > From the abstract: > > " The key idea of Sprout is to adapt the sending rate to roughly match the > current cellular network capacity while not overshooting it; by achieving > this objective, Sprout can both maintain high throughput and avoid queuing > delays in the network. To achieve this goal, Sprout models the cellular > link using a Poisson process with an underlying rate which may change over > time. Sprout models the evolution of the probability distribution on the > underlying rate using Brownian motion, with which Sprout proposes a control > protocol to determine the current transmission rate for an end-point. " > > This seems to be very much within the scope of what RMCAT should be aiming > for. > > Apologies if it is a duplicate. > > --14dae9399de3359f8704dc0dfa63 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable

I've been keeping in touch with Keith on this very topic.=C2=A0 Pret= ty sure he's also a subscriber to this list.

Dan

On May 6, 2013 6:08 AM, "Hannes Tschofenig&= quot; <Hannes.Tschofenig@gm= x.net> wrote:
Keith Winstei= n, the main author of the work, was also at the congestion control workshop= last year and briefly mentioned his work there.=C2=A0
Keith maintains a Webpage,=C2=A0which contains more information about = the project (including a video recording of his talk, source code, and data= ):
=C2=A0
Definitely workwhile to look at his approach or to=C2=A0reach out to h= im.=C2=A0
=C2=A0
Ciao
Hannes
=C2=A0
Gesendet:=C2=A0Montag, 06. Mai 2013= um 14:01 Uhr
Von:=C2=A0"Harald Alvestrand" <harald@alvestrand.no>
An:=C2=A0rmcat@i= etf.org
Betreff:=C2=A0[rmcat] Sprout - an algorithm worth checking out?
I was pointed to this paper some time ago, but only found time t= o look at it today:

https://www.usenix.org/conference/nsdi13/stochastic-forecasts-achieve-hi= gh-throughput-and-low-delay-over-cellular-networks

>From the abstract:

" The key idea of Sprout is to adapt the sending rate to roughly match= the current cellular network capacity while not overshooting it; by achiev= ing this objective, Sprout can both maintain high throughput and avoid queu= ing delays in the network. To achieve this goal, Sprout models the cellular= link using a Poisson process with an underlying rate which may change over= time. Sprout models the evolution of the probability distribution on the u= nderlying rate using Brownian motion, with which Sprout proposes a control = protocol to determine the current transmission rate for an end-point. "= ;

This seems to be very much within the scope of what RMCAT should be aiming = for.

Apologies if it is a duplicate.
=C2=A0
--14dae9399de3359f8704dc0dfa63-- From vsingh.ietf@gmail.com Mon May 6 09:39:54 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 5263C21F92A5 for ; Mon, 6 May 2013 09:39:54 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -2.599 X-Spam-Level: X-Spam-Status: No, score=-2.599 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, HTML_MESSAGE=0.001, NO_RELAYS=-0.001] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id 6POLS4u6MXar for ; Mon, 6 May 2013 09:39:52 -0700 (PDT) Received: from mail-ia0-x230.google.com (mail-ia0-x230.google.com [IPv6:2607:f8b0:4001:c02::230]) by ietfa.amsl.com (Postfix) with ESMTP id 2A2A221F9298 for ; Mon, 6 May 2013 09:39:52 -0700 (PDT) Received: by mail-ia0-f176.google.com with SMTP id l27so3308265iae.7 for ; Mon, 06 May 2013 09:39:51 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20120113; h=x-received:mime-version:in-reply-to:references:from:date:message-id :subject:to:content-type; bh=t0UsfOuhhaE7lLCxBkY2jiAylycuFQYHDpblB/wPqvk=; b=pxueHCYgRpwzFdivtLkIoeN+6CK9rEfmYz2IyUYka/nISJt6Bmo2KRKgMP7xeSRHJ2 kHt4q46d1MR5q/2Q58upbV9yQd2feRr3KjRytjJ03g7KwhaNwBCYKzRkB1S9mQ+PWtQE 9xhEm4acse+UkrHTCvPNZV4lBOPmQ30oxZpurJfk7ByTPPO7UzlgK6LGX0GUoL+ixwIu 8rNIHuSkYKnvxC9LN9xPQxko/x867sp40JqCGD6K3TXamPKniMDT6bUPF3lAUjl+a9LY gDD2QqAzQCeJrNv7ZmxdooZHCk7WLoigmG67NTVJ+O4AW4/QlhqRlslVvqjiF1DgG1Uc 6Isw== X-Received: by 10.50.20.38 with SMTP id k6mr2863076ige.50.1367858391700; Mon, 06 May 2013 09:39:51 -0700 (PDT) MIME-Version: 1.0 Received: by 10.50.73.34 with HTTP; Mon, 6 May 2013 09:39:31 -0700 (PDT) In-Reply-To: <107C7E14-EC74-4BA2-804B-901BD509D662@ifi.uio.no> References: <107C7E14-EC74-4BA2-804B-901BD509D662@ifi.uio.no> From: Varun Singh Date: Mon, 6 May 2013 19:39:31 +0300 Message-ID: To: "rmcat@ietf.org WG" Content-Type: multipart/alternative; boundary=047d7bd7598a8a5af804dc0f5937 Subject: Re: [rmcat] Call for declarations of interest to submit a paper to Packet Video 2013 X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Mon, 06 May 2013 16:39:54 -0000 --047d7bd7598a8a5af804dc0f5937 Content-Type: text/plain; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable Hi all, Similar to Michael Welzl's session, we (Joerg, Colin and I) too have a special session planned for WebRTC at IEEE Packet Video 2013. It is WebRTC-related but not congestion control. Hence, if the topic is of interest to you and you'd plan to submit a paper to the session, please send us: - Title of the paper: - Abstract: - List of authors: by next monday (13. May). Note however, the actual deadline is 10. June details follow: ---- WebRTC 2.0 (Special Session at IEEE PV 2013) The standardization of version 1.0 of Web Real-Time Communications (WebRTC) is expected to complete by the end of the year; yet many technical and especially research challenges remain open -- and we expect new ones to arise with deployment experience. With WebRTC and the accompanying APIs, application developers have the opportunity to add new immersive features (gestures, real-time communication, peer-to-peer) within their web applications. Apart from the multimedia aspect, WebRTC permits sending data packets between the peers using 'Data Channels', which opens the door for innovative apps and new research ideas. The WebRTC API is low-level, which has given rise to many WebRTC Javascript SDKs. These SDKs abstract (for the application developer) from the intricat= e state-machine of the underlying media and network stack. However, the issue= s the WebRTC application developers still have to deal with are related to call management, service performance and quality monitoring, and service scalability. Consequently, the SDK providers have to deal with maintaining interoperability with other WebRTC-capable endpoints, evolution of the WebRTC API and domain-specific frameworks and SDKs. Mobile devices are a big market opportunity and challenge, WebRTC is no exception. The wireless environment and mobility in general pose some interesting problems: call setup, mobility, handover, etc. In general, the WebRTC-enabled services and legacy services (SIP/XMPP-enabled, Skype) face the challenge of interoperability, especially since WebRTC does not standardize a signaling protocol. Lastly, Internet Service Providers (ISPs, both mobile and broadband) have to operate in the tension between present and future services. They need to be able to engineer their network in a way supportive for transmitting the WebRTC flows at an unprecedented scale. The objective of this special session is to bring together researchers and practitioners in the area of real-time communications, multimedia systems, transport protocols, broadband and mobile networks, and multimedia applications to advance the state of research in real-time communication. W= e solicit original contributions on advanced topics in web-based real-time multimedia communications. Topics of particular interest include, but are not limited to - Mobile WebRTC - Telepresence - Architectures for Media Transport, Multiplexing, and Naming - Identity Management and Security - Operations and Management - Understanding QoE and Performance of WebRTC - WebRTC Applications - Deployment Issues - Non-media applications or Data Channels - WebRTC and economy of scale. ---------------------------------------------------------------------------= --- Varun Singh, Aalto University, varun.singh@aalto.fi J=F6rg Ott, Aalto University, jorg.ott@aalto.fi Colin Perkins, University of Glasgow, csp@csperkins.org On Mon, May 6, 2013 at 4:51 PM, Michael Welzl wrote: > Dear all, > > Stein Gjessing and I are planning to arrange a special session dedicated > to RMCAT at IEEE Packet Video 2013: http://pv2013.itec.aau.at > > Our proposal for a special session, described below, has been tentatively > accepted by the organizers of IEEE Packet Video 2013. It's not hard to se= e > that this is indeed pretty RMCAT focused :-) For final acceptance of o= ur > session, we need to have a list of committed papers already at this stage= . > Hence, if the topic below is of interest to you, and you plan to submit a > paper to this special session, please send us: > - authors > - title > - abstract > of that paper ***by next Monday (13 May)***. > > The real deadline for paper submission would then be 10 June. Again, note > that this is not a CFP yet, it's a pre-CFP-call-of-interest... in a way, > informing us that you're planning to submit a paper is similar to > registering a paper before submitting the full thing, I'd say. > > Cheers, > Michael > > --=20 http://www.netlab.tkk.fi/~varun/ --047d7bd7598a8a5af804dc0f5937 Content-Type: text/html; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable
Hi all,

Similar to Michael W= elzl's session, we (Joerg, Colin and I) too have a=A0
special= session planned for WebRTC at IEEE Packet Video 2013. It is WebRTC-related= =A0
but not congestion control. Hence, if the topic is of interest to you = and you'd plan to
submit a paper to the session, please send = us:

- Title of the paper:
- Abstract:
- List of authors:
by next monday (13. May).=A0
Note however, the actual deadline is 10. June

details follow:
----

WebRT= C 2.0 (Special Session at IEEE PV 2013)

The standardization of version 1.0 of Web Real-Time Com= munications (WebRTC) is
expected to complete by the end of the ye= ar; yet many technical and especially
research challenges remain = open -- and we expect new ones to arise with
deployment experience. With WebRTC and the accompanying APIs, applicat= ion
developers have the opportunity to add new immersive features= (gestures,
real-time communication, peer-to-peer) within their w= eb applications. Apart
from the multimedia aspect, WebRTC permits sending data packets betwee= n the
peers using 'Data Channels', which opens the door f= or innovative apps and new
research ideas.

The WebRTC API is low-level, which has given rise to many WebRTC Javas= cript
SDKs. These SDKs abstract (for the application developer) f= rom the intricate
state-machine of the underlying media and netwo= rk stack. However, the issues
the WebRTC application developers still have to deal with are related = to call
management, service performance and quality monitoring, a= nd service
scalability. Consequently, the SDK providers have to d= eal with maintaining
interoperability with other WebRTC-capable endpoints, evolution of the= WebRTC
API and domain-specific frameworks and SDKs.
Mobile devices are a big market opportunity and challenge, Web= RTC is no
exception. The wireless environment and mobility in general pose some<= /div>
interesting problems: call setup, mobility, handover, etc. In gen= eral, the
WebRTC-enabled services and legacy services (SIP/XMPP-e= nabled, Skype) face the
challenge of interoperability, especially since WebRTC does not standa= rdize a
signaling protocol. Lastly, Internet Service Providers (I= SPs, both mobile and
broadband) have to operate in the tension be= tween present and future services.
They need to be able to engineer their network in a way supportive for=
transmitting the WebRTC flows at an unprecedented scale.

The objective of this special session is to bring togethe= r researchers and
practitioners in the area of real-time communications, multimedia syst= ems,
transport protocols, broadband and mobile networks, and mult= imedia
applications to advance the state of research in real-time= communication. We
solicit original contributions on advanced topics in web-based real-ti= me
multimedia communications.

Topics of = particular interest include, but are not limited to

- Mobile WebRTC
- Telepresence
- Architectures for= Media Transport, Multiplexing, and Naming
- Identity Management = and Security
- Operations and Management
- Understandin= g QoE and Performance of WebRTC
- WebRTC Applications
- Deployment Issues
- Non-me= dia applications or Data Channels
- WebRTC and economy of scale.<= /div>

--------------------------------------------------= ----------------------------
Varun Singh, =A0 Aalto University, varun.singh@aalto.fi
J=F6rg Ott, =A0 =A0 =A0Aalto Univer= sity, jorg.ott@aalto.fi
= Colin Perkins, University of Glasgow, = csp@csperkins.org



On Mon, May 6, 2013 at 4:51 PM, Michael Welzl <= ;michawe@ifi.uio.no= > wrote:
Dear all,

Stein Gjessing and I are planning to arrange a special session dedicated to= RMCAT at IEEE Packet Video 2013: http://pv2013.itec.aau.at

Our proposal for a special session, described below, has been tentatively a= ccepted by the organizers of IEEE Packet Video 2013. It's not hard to s= ee that this is indeed pretty RMCAT focused =A0:-) =A0 For final acceptance= of our session, we need to have a list of committed papers already at this= stage. Hence, if the topic below is of interest to you, and you plan to su= bmit a paper to this special session, please send us:
- authors
- title
- abstract
of that paper ***by next Monday (13 May)***.

The real deadline for paper submission would then be 10 June. Again, note t= hat this is not a CFP yet, it's a pre-CFP-call-of-interest... in a way,= informing us that you're planning to submit a paper is similar to regi= stering a paper before submitting the full thing, I'd say.

Cheers,
Michael


--
http://www.netlab.tkk.fi/~varun/
--047d7bd7598a8a5af804dc0f5937-- From mirja.kuehlewind@ikr.uni-stuttgart.de Tue May 7 08:24:26 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 703FD21F8F2C for ; Tue, 7 May 2013 08:24:26 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -2.249 X-Spam-Level: X-Spam-Status: No, score=-2.249 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, HELO_EQ_DE=0.35] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id 7zPPX5p7qQuM for ; Tue, 7 May 2013 08:24:22 -0700 (PDT) Received: from mailsrv.ikr.uni-stuttgart.de (mailsrv.ikr.uni-stuttgart.de [129.69.170.2]) by ietfa.amsl.com (Postfix) with ESMTP id 0018B21F8F0D for ; Tue, 7 May 2013 08:24:18 -0700 (PDT) Received: from netsrv1.ikr.uni-stuttgart.de (netsrv1-c [10.11.12.12]) by mailsrv.ikr.uni-stuttgart.de (Postfix) with ESMTP id 0047460235; Tue, 7 May 2013 17:24:14 +0200 (CEST) Received: from vpn-2-cl195 (vpn-2-cl195 [10.41.21.195]) by netsrv1.ikr.uni-stuttgart.de (Postfix) with ESMTP id EDC5660234; Tue, 7 May 2013 17:24:14 +0200 (CEST) From: Mirja Kuehlewind Organization: University of Stuttgart (Germany), IKR To: rmcat@ietf.org Date: Tue, 7 May 2013 17:24:14 +0200 User-Agent: KMail/1.9.10 (enterprise35 0.20101217.1207316) References: In-Reply-To: X-KMail-QuotePrefix: > MIME-Version: 1.0 Content-Disposition: inline Content-Type: Text/Plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable Message-Id: <201305071724.14734.mirja.kuehlewind@ikr.uni-stuttgart.de> Cc: "Michael Ramalho \(mramalho\)" Subject: Re: [rmcat] RMCAT Testing Topology and Initial Testing X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Tue, 07 May 2013 15:24:26 -0000 Hi Michael, thanks you for writting this up. What is your plan with this document? Are = you=20 planning to merge this document with draft-singh-rmcat-cc-eval-02 or is thi= s=20 the starting point for an own draft? Two comment on the document as an individual contributor: 1) Regarding the passing criteria we should be more careful. I believe you = had=20 already a certain solution in mind while writting the document. But in fact= =20 the solution does not have to be a pure delay based approach. Probability i= t=20 actually will not be only delay based because we have to compete with=20 standard TCP.=20 More specifically regarding the criteria 2 (no packet loss): I don't think= =20 this is the right criteria as we only what to have a small (average) queue.= =20 If there e.g. is a little spike in the queue (maybe in the start-up phase o= f=20 a competing flow) that might be toleratable. While the packet loss itself (= if=20 this is only a few packets) should not be a problem for the application. Also regarding the capacity sharing: I don't see fair or equal sharing as a= =20 criteria; not even a sharing which is close to equal (as defined in criteri= a=20 1). The thing that is important is that each flow gets at least some part o= f=20 the capacity or maybe there is even something like a minimum rate each flow= =20 needs to achieve (as long as N * min_rate < link capacity). I guess it is=20 probably the easiest solution to come up with an algorithm with achieves=20 something like more or less equal sharing but it a too strong requirement (= in=20 case someone has a more fancy idea). To sum up: when formulating evaluation criteria, we should not be more=20 restrictive that the requirements in draft-jesup-rmcat-reqs. 2) This (simple) scenario is a good starting point but it only focuses on=20 capacity sharing and small delays. There are many algorithm out there alrea= dy=20 which can fullfill these requirement (e.g. TCP Vegas). The main challenge w= e=20 have to worry about is that we also need to compete with TCP. This is not=20 handled at all in your document so far. Mirja On Friday 05 April 2013 18:54:19 Michael Ramalho (mramalho) wrote: > RMCAT Design Team, > > At the RMCAT Design Team meeting on 28 March, I volunteered to document an > initial network topology model and an initial testing methodology model f= or > our RMCAT work. The goal is to have a topology and an associated testing > methodology so that we could determine if the RMCAT requirements are bei= ng > met. > > Attached is my first draft for such a proposal. It is a work in progress. > > Comments are welcome, but please be sure to raise a technology-based > objection and associated rationale with any item within it you find > objectionable. > > We have our work cut out for us, as designing an acceptable control system > (i.e. rate adaptation algorithm) to meet all of our requirements will be > tough. As can be seen, my initial testing proposal only addresses the > simplest part of our work: RMCAT self-friendliness. > > I would like to poll this audience, when should the next RMCAT design > meeting be held? > > I would be willing to review various aspects of my proposal at the next > meeting. > > Comments? Fire away! > > Best Regards, > > Michael Ramalho =2D-=20 =2D------------------------------------------------------------------ Dipl.-Ing. Mirja K=FChlewind Institute of Communication Networks and Computer Engineering (IKR) University of Stuttgart, Germany Pfaffenwaldring 47, D-70569 Stuttgart tel: +49(0)711/685-67973 email: mirja.kuehlewind@ikr.uni-stuttgart.de web: www.ikr.uni-stuttgart.de =2D------------------------------------------------------------------ From mirja.kuehlewind@ikr.uni-stuttgart.de Tue May 7 08:33:37 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 493A121F8E96 for ; Tue, 7 May 2013 08:33:37 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -2.099 X-Spam-Level: X-Spam-Status: No, score=-2.099 tagged_above=-999 required=5 tests=[AWL=-0.150, BAYES_00=-2.599, HELO_EQ_DE=0.35, MIME_8BIT_HEADER=0.3] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id aI3CeyNv+wWf for ; Tue, 7 May 2013 08:33:33 -0700 (PDT) Received: from mailsrv.ikr.uni-stuttgart.de (mailsrv.ikr.uni-stuttgart.de [129.69.170.2]) by ietfa.amsl.com (Postfix) with ESMTP id E3D9721F8E2C for ; Tue, 7 May 2013 08:33:32 -0700 (PDT) Received: from netsrv1.ikr.uni-stuttgart.de (netsrv1-c [10.11.12.12]) by mailsrv.ikr.uni-stuttgart.de (Postfix) with ESMTP id 46BE660235; Tue, 7 May 2013 17:33:32 +0200 (CEST) Received: from vpn-2-cl195 (vpn-2-cl195 [10.41.21.195]) by netsrv1.ikr.uni-stuttgart.de (Postfix) with ESMTP id 40EF760234; Tue, 7 May 2013 17:33:32 +0200 (CEST) From: Mirja =?iso-8859-1?q?K=FChlewind?= To: rmcat@ietf.org Date: Tue, 7 May 2013 17:33:31 +0200 User-Agent: KMail/1.9.10 (enterprise35 0.20101217.1207316) MIME-Version: 1.0 Content-Type: Multipart/Mixed; boundary="Boundary-00=_L7RiRdto4CMVaLD" Message-Id: <201305071733.31755.mkuehle@ikr.uni-stuttgart.de> Cc: Harald Alvestrand , Piers O'Hanlon , "Xiaoqing Zhu \(xiaoqzhu\)" Subject: [rmcat] Implemenation Status X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Tue, 07 May 2013 15:33:37 -0000 --Boundary-00=_L7RiRdto4CMVaLD Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit Content-Disposition: inline Hallo, find below the pointer to a current draft that specifies experimentally an new Implementation Status section in Internet Drafts. I believe this applies very well to all drafts that propose a congestion control algorithm in rmcat. In any case we should find a way to document which implementations exist and potentially also how they were evaluated (referring to specific scenario/test in evaluation criteria document). One solution would be this proposed Implementation Status section, another would be to have a wiki. Please everybody who has an implementation for a rmcat congestion control algorithm speak up and care about a way to document the status/availablity/testing of your implementation. Mirja --Boundary-00=_L7RiRdto4CMVaLD Content-Type: message/rfc822; name="forwarded message" Content-Transfer-Encoding: 7bit Content-Description: Yaron Sheffer : Fwd: New Version Notification for draft-sheffer-running-code-03.txt Content-Disposition: inline Return-Path: X-Original-To: mirja.kuehlewind@ikr.uni-stuttgart.de Delivered-To: mirja.kuehlewind@ikr.uni-stuttgart.de Received: from charon.rus.uni-stuttgart.de (charon.rus.uni-stuttgart.de [129.69.1.54]) by mailsrv.ikr.uni-stuttgart.de (Postfix) with ESMTP id 0242A601D8 for ; Fri, 5 Apr 2013 22:18:39 +0200 (CEST) Received: from localhost (localhost [127.0.0.1]) by charon.rus.uni-stuttgart.de (Postfix) with ESMTP id EDD7B5FE5A for ; Fri, 5 Apr 2013 22:18:38 +0200 (CEST) X-Relay-Countries: XX XX ** US XX IL X-Virus-Scanned: by amavisd-new at charon.rus.uni-stuttgart.de X-Spam-Flag: NO X-Spam-Score: -4.372 X-Spam-Level: X-Spam-Status: No, score=-4.372 tagged_above=-999 required=5 tests=[BAYES_00=-1.9, DKIM_SIGNED=0.1, DKIM_VALID=-0.1, DKIM_VALID_AU=-0.1, FREEMAIL_FROM=0.001, RP_MATCHES_RCVD=-2.373, SA2DNSBLC=0.001, SPF_PASS=-0.001] autolearn=no Received: from charon.rus.uni-stuttgart.de ([IPv6:::1]) by localhost (charon.rus.uni-stuttgart.de [IPv6:::1]) (amavisd-new, port 10024) with ESMTP id B6y786Y6wyu2 for ; Fri, 5 Apr 2013 22:18:36 +0200 (CEST) Received: from mail.ietf.org (mail.ietf.org [IPv6:2001:1890:123a::1:1e]) by charon.rus.uni-stuttgart.de (Postfix) with ESMTP for ; Fri, 5 Apr 2013 22:18:36 +0200 (CEST) Received: from ietfa.amsl.com (localhost [IPv6:::1]) by ietfa.amsl.com (Postfix) with ESMTP id 4BC7E21F95EA; Fri, 5 Apr 2013 13:18:34 -0700 (PDT) X-Original-To: wgchairs@ietfa.amsl.com Delivered-To: wgchairs@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 6D9E221F95EA for ; Fri, 5 Apr 2013 13:18:33 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -100.183 X-Spam-Level: X-Spam-Status: No, score=-100.183 tagged_above=-999 required=5 tests=[AWL=0.646, BAYES_00=-2.599, FH_HOST_EQ_D_D_D_D=0.765, RCVD_IN_PBL=0.905, RDNS_DYNAMIC=0.1, USER_IN_WHITELIST=-100] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id YOt0hCumH+qX for ; Fri, 5 Apr 2013 13:18:33 -0700 (PDT) Received: from mail-ea0-x235.google.com (mail-ea0-x235.google.com [IPv6:2a00:1450:4013:c01::235]) by ietfa.amsl.com (Postfix) with ESMTP id 9489E21F942C for ; Fri, 5 Apr 2013 13:18:32 -0700 (PDT) Received: by mail-ea0-f181.google.com with SMTP id z10so1463696ead.12 for ; Fri, 05 Apr 2013 13:18:31 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20120113; h=x-received:message-id:date:from:user-agent:mime-version:to:subject :references:in-reply-to:x-forwarded-message-id:content-type :content-transfer-encoding; bh=YcekoSY6IHMm/nLDSCl345c4Rb5cgUsKvC4r+Ev85AE=; b=vD5ON5HV33ktltkKRnL5cvQYiTCxQEvz6med2duVKMb+AWS7oxlJe+DZ3X2EnWNBap t87OnRiPArMfYfdJaICJy/GA5vasYTBAQWGKlw0Ad+SNOmao9axi7KQQQZYVgyP2/gxQ VeNBiTVRNFxbKffkCSkiilz5+Pho64Q97JYAEIaeQBgrOGouA4na8mr9byinCgUAGXlb F3VmjitkZy4B3fDww2jbmPW0K4k6Xgdt5kOZcR47Njh+BUllbZGdgCrZtQAXsGC364mQ x46WDT2wUgHjq6LK/cpkl1vMkaFb1jrQGKr4ii4m+xdJRnGpw54+fgklIK5p/c6xkkdL AcdQ== X-Received: by 10.14.175.71 with SMTP id y47mr22554431eel.18.1365193111538; Fri, 05 Apr 2013 13:18:31 -0700 (PDT) Received: from [10.0.0.2] (bzq-79-181-109-111.red.bezeqint.net. [79.181.109.111]) by mx.google.com with ESMTPS id a1sm17420650eep.2.2013.04.05.13.18.30 (version=TLSv1 cipher=ECDHE-RSA-RC4-SHA bits=128/128); Fri, 05 Apr 2013 13:18:30 -0700 (PDT) Message-ID: <515F3194.5020907@gmail.com> Date: Fri, 05 Apr 2013 23:18:28 +0300 From: Yaron Sheffer User-Agent: Mozilla/5.0 (X11; Linux x86_64; rv:17.0) Gecko/20130308 Thunderbird/17.0.4 MIME-Version: 1.0 To: WG Chairs Subject: Fwd: New Version Notification for draft-sheffer-running-code-03.txt References: <20130405194251.19607.86337.idtracker@ietfa.amsl.com> In-Reply-To: <20130405194251.19607.86337.idtracker@ietfa.amsl.com> X-Forwarded-Message-Id: <20130405194251.19607.86337.idtracker@ietfa.amsl.com> Content-Type: text/plain; charset=UTF-8; format=flowed Content-Transfer-Encoding: 7bit X-BeenThere: wgchairs@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: Working Group Chairs List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , Sender: wgchairs-bounces@ietf.org Errors-To: wgchairs-bounces@ietf.org Hi, we have just published a new version of our draft that defines a new, optional Implementation Status section. The most significant addition in this rev is proposed introductory text for this section. We also included a list of current I-Ds that adopt this proposal. Adrian and I would like to last-call this draft soon, and we solicit this list's comments before we do. Thanks, Yaron -------- Original Message -------- Subject: New Version Notification for draft-sheffer-running-code-03.txt Date: Fri, 05 Apr 2013 12:42:51 -0700 From: internet-drafts@ietf.org To: yaronf.ietf@gmail.com CC: adrian@olddog.co.uk A new version of I-D, draft-sheffer-running-code-03.txt has been successfully submitted by Yaron Sheffer and posted to the IETF repository. Filename: draft-sheffer-running-code Revision: 03 Title: Improving Awareness of Running Code: the Implementation Status Section Creation date: 2013-04-05 Group: Individual Submission Number of pages: 9 URL: http://www.ietf.org/internet-drafts/draft-sheffer-running-code-03.txt Status: http://datatracker.ietf.org/doc/draft-sheffer-running-code Htmlized: http://tools.ietf.org/html/draft-sheffer-running-code-03 Diff: http://www.ietf.org/rfcdiff?url2=draft-sheffer-running-code-03 Abstract: This document describes a simple process that allows authors of Internet-Drafts to record the status of known implementations by including an Implementation Status section. This will allow reviewers and working groups to assign due consideration to documents that have the benefit of running code and potentially reward the documented protocols by treating the documents with implementations preferentially. The process in this document is offered as an experiment. Authors of Internet-Drafts are encouraged to consider using the process for their documents, and working groups are invited to think about applying the process to all of their protocol specifications. The authors of this document intend to collate experiences with this experiment and to report them to the community. The IETF Secretariat --Boundary-00=_L7RiRdto4CMVaLD-- From mramalho@cisco.com Wed May 8 06:29:43 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 72CFD21F9376 for ; Wed, 8 May 2013 06:29:43 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -10.599 X-Spam-Level: X-Spam-Status: No, score=-10.599 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, RCVD_IN_DNSWL_HI=-8] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id rzdwkJ5jfJUI for ; Wed, 8 May 2013 06:29:38 -0700 (PDT) Received: from rcdn-iport-7.cisco.com (rcdn-iport-7.cisco.com [173.37.86.78]) by ietfa.amsl.com (Postfix) with ESMTP id CC54821F9356 for ; Wed, 8 May 2013 06:29:37 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=10320; q=dns/txt; s=iport; t=1368019778; x=1369229378; h=from:to:subject:date:message-id:references:in-reply-to: content-transfer-encoding:mime-version; bh=fn7nU9KJBPd+ZcZCARX/8NlPXgB4KG+Ku8QTdaoW71k=; b=QIMsT62ujI+GVpLqvH69u38p+TESLqHvZ1+IzOVjClA8fqIjX1nzi2+L phFX0nHmPylvzCTinKqoNsZHHMJeuN9OxQsaXS7D3fCiEOTVzwb6jH5jN /HhL6NPLgXYe85n5fzKPIK4J1hDO7vX8oNozXV0J2rlHFBmRWfcWzubfC s=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: Ai0FAD5SilGtJV2a/2dsb2JhbABRgwc3vxN6FnSCHwEBAQRJKxEEAgEIEQQBAQEKHQcyFAkIAQEEARIIE4dxwVqNZguBBiwMBoJuYQOIYZ9+gw6BaggXHg X-IronPort-AV: E=Sophos;i="4.87,635,1363132800"; d="scan'208";a="207848548" Received: from rcdn-core-3.cisco.com ([173.37.93.154]) by rcdn-iport-7.cisco.com with ESMTP; 08 May 2013 13:29:37 +0000 Received: from xhc-aln-x10.cisco.com (xhc-aln-x10.cisco.com [173.36.12.84]) by rcdn-core-3.cisco.com (8.14.5/8.14.5) with ESMTP id r48DTagQ025103 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL); Wed, 8 May 2013 13:29:36 GMT Received: from xmb-rcd-x12.cisco.com ([169.254.2.133]) by xhc-aln-x10.cisco.com ([173.36.12.84]) with mapi id 14.02.0318.004; Wed, 8 May 2013 08:29:36 -0500 From: "Michael Ramalho (mramalho)" To: Mirja Kuehlewind , "rmcat@ietf.org" Thread-Topic: [rmcat] RMCAT Testing Topology and Initial Testing Thread-Index: Ac4yHguE4ZjjqZhvQIGTw9X1W56SwwZQsuwAAAJ6jWA= Date: Wed, 8 May 2013 13:29:35 +0000 Message-ID: References: <201305071724.14734.mirja.kuehlewind@ikr.uni-stuttgart.de> In-Reply-To: <201305071724.14734.mirja.kuehlewind@ikr.uni-stuttgart.de> Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [10.117.125.231] Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable MIME-Version: 1.0 Subject: Re: [rmcat] RMCAT Testing Topology and Initial Testing X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 08 May 2013 13:29:43 -0000 Mirja, Thanks for your email. Comments in-line below (with "MAR:"). Regards, Michael Ramalho -----Original Message----- From: Mirja Kuehlewind [mailto:mirja.kuehlewind@ikr.uni-stuttgart.de]=20 Sent: Tuesday, May 07, 2013 11:24 AM To: rmcat@ietf.org Cc: Michael Ramalho (mramalho) Subject: Re: [rmcat] RMCAT Testing Topology and Initial Testing Hi Michael, thanks you for writting this up. What is your plan with this document? Are = you planning to merge this document with draft-singh-rmcat-cc-eval-02 or is= this the starting point for an own draft? MAR: The RMCAT design team (as discussed in Orlando meeting) agreed in Orla= ndo to document a network topology model and a testing methodology by which= we would compare RMCAT candidates - with the belief that some of the testi= ng criteria would be helpful in defining RMCAT properties. For example, the= eventual RMCAT self-fairness definition (to be specified in Randell's requ= irements document - now a RMCAT WG draft) might well fall out of the experi= ence gathered out of the testing methodology. MAR: I have not discussed with the design team whether the document I have = authored on behalf of the design team should be merged with Varun's (/Joerg= 's) draft-singh-rmcat-cc-eval-0X draft (not yet adopted by RMCAT). I am ope= n to whatever makes sense. Until we get a little more convergence on the te= sting methodology, I'd rather not spend too much effort on my ASCII art ski= lls ;-). I do plan to convert it to an easily group-editable form (Google d= ocs or easier-to-deal-with wiki than the RMCAT wiki). Two comment on the document as an individual contributor: 1) Regarding the passing criteria we should be more careful. I believe you = had already a certain solution in mind while writting the document. But in = fact the solution does not have to be a pure delay based approach. Probabil= ity it actually will not be only delay based because we have to compete wit= h standard TCP.=20 MAR: There is no explicit assumption on "a certain solution" during the wri= ting of the document OTHER THAN the working group assumption that when comp= eting with other RMCAT flows that the RMCAT solution would primarily adapt = based on delay whenever possible. Of course, if there is a short (in time) = queue on the bottleneck link and some subset of the flows progressing throu= gh it have sufficiently long RTT - one cannot guarantee timely adaption bas= ed solely on delay variation alone. That is why the first test scenario is = proposed to have a large queue (in time) in the bottleneck - to test the bo= unds attainable for a delay-based adaption given some reasonable topology b= ounds. MAR: It is well understood that the eventual RMCAT candidate protocol opera= tion MUST also have a loss-based component - as we cannot guarantee that a = RMCAT flow would not mix with other loss-only-based flow adaptation transpo= rts. These comments were voiced at the RMCAT meeting in Orlando. The fusion= of the information available - available delay-variation history and recen= t loss characteristics - is potentially the most interesting part of the fu= ndamental adaptation algorithm/design. More specifically regarding the criteria 2 (no packet loss): I don't think = this is the right criteria as we only what to have a small (average) queue.= =20 If there e.g. is a little spike in the queue (maybe in the start-up phase o= f a competing flow) that might be toleratable. While the packet loss itself= (if this is only a few packets) should not be a problem for the applicatio= n. MAR: Who is the "we" in "we only what to have a small (average) queue"? MAR: I agree that the eventual RMCAT protocol should admit a small queue si= ze for RMCAT flow aggregates whenever possible. Thus the eventual protocol = should never use all of the (proposed for testing) 500 ms queue for the fir= st testing scenario documented. This is mentioned in the document. However = at our last design team meeting it was agreed that at least three queue dep= ths be used in the testing: 1) a nominal network case (of which 500 ms queu= e depth was agreed, as it should never overflow), 2) a bufferbloated networ= k (over a second of queue depth) and 3) a very low maximum queuing (represe= ntative of AQMs such as CODEL or PIE set to ~ 70 ms). I think queue depth s= cenario 3 above addresses your concern of short-term bursts potentially cau= sing loss on bottlenecks with short queues. Also regarding the capacity sharing: I don't see fair or equal sharing as a= criteria; not even a sharing which is close to equal (as defined in criter= ia 1). The thing that is important is that each flow gets at least some par= t of the capacity or maybe there is even something like a minimum rate each= flow needs to achieve (as long as N * min_rate < link capacity). I guess i= t is probably the easiest solution to come up with an algorithm with achiev= es something like more or less equal sharing but it a too strong requiremen= t (in case someone has a more fancy idea). MAR: Thank you for your excellent comment. Please join us on the design tea= ms to add your voice (they are bi-weekly, the next one is scheduled for nex= t Monday - details already sent to the list by Mo Zanaty). To sum up: when formulating evaluation criteria, we should not be more rest= rictive that the requirements in draft-jesup-rmcat-reqs. MAR: Agreed - but only when the requirements draft is in WGLC or an RFC ;-)= . In other words, I believe that the design team is using the requirements = draft as a framework until work progresses further. MAR: I think it is fair to say that we do not know what are the bounds of = fairness possible at this stage. And, for some/most of the RMCAT deployment= s, we will not have any form of admission control; and thus a given RMCAT e= ndpoint cannot know if sum{min_rate_i} < link capacity ... because a given = endpoint cannot know how many other flows i exist (answer: N-1) or the lin= k capacity of the bottleneck (answer: C) or even the min_rate_i of the othe= r i applications running over RMCAT protocol!. MAR: Although TCP does a reasonable job at equal sharing considering that i= ndividual flows can have vastly different RTTs (with the proviso that long = RTTs limit the maximum rate of the long RTT session) - it only does so only= in the aggregate average and only over relatively large averaging interval= s. That is, an individual TCP session can get "unlucky" (statistically) and= stall on any particularly small time frame (that is a primary reason why A= BR schemes open more than one TCP). My intuition at this stage is to open u= p the definition of fairness somewhat (my guess was to within a factor of t= hree) - but that we would prefer the variance of the rate (over any reasona= bly small averaging interval) less than TCP (for those cases where we are s= uccessful in adapting via delay variance - I've got no clue what to require= in other traffic mixes). MAR: Please join us on the design team meetings for your valued input. 2) This (simple) scenario is a good starting point but it only focuses on c= apacity sharing and small delays. There are many algorithm out there alread= y which can fullfill these requirement (e.g. TCP Vegas). The main challenge= we have to worry about is that we also need to compete with TCP. This is n= ot handled at all in your document so far. MAR: Yours is the first comment on the list to infer a window-based congest= ion control (TCP Vegas) solution in the group, I also expected TFWC and var= iants thereof also to be more mentioned. TCP Vegas, by its compatibility to= existing on-the-wire TCP constraint, doesn't meet some of our other design= goals (e.g., lower rate variability than TCP and less probability of stall= ing). Some of these design goals have not been incorporated in Randall's dr= aft yet. MAR: As to the challenge to compete with TCP, I agree. As per the text in t= he introduction, we plan to "layer in" TCP, LEDBAT and other transports in = time as other sources we intend to compete against. As of now, the document= only specifies the first of many scenarios. As you and I both know, RMCAT = will not attain its desire for low delay when competing with TCP in bottlen= ecks with large (in time) queues. MAR: Please join us on the design team - it takes less time than replying t= o emails ;-) . Mirja MAR: I will be generating an updated version of the document prior to the n= ext design team on Monday. On Friday 05 April 2013 18:54:19 Michael Ramalho (mramalho) wrote: > RMCAT Design Team, > > At the RMCAT Design Team meeting on 28 March, I volunteered to=20 > document an initial network topology model and an initial testing=20 > methodology model for our RMCAT work. The goal is to have a topology=20 > and an associated testing methodology so that we could determine if=20 > the RMCAT requirements are being met. > > Attached is my first draft for such a proposal. It is a work in progress. > > Comments are welcome, but please be sure to raise a technology-based=20 > objection and associated rationale with any item within it you find=20 > objectionable. > > We have our work cut out for us, as designing an acceptable control=20 > system (i.e. rate adaptation algorithm) to meet all of our=20 > requirements will be tough. As can be seen, my initial testing=20 > proposal only addresses the simplest part of our work: RMCAT self-friendl= iness. > > I would like to poll this audience, when should the next RMCAT design=20 > meeting be held? > > I would be willing to review various aspects of my proposal at the=20 > next meeting. > > Comments? Fire away! > > Best Regards, > > Michael Ramalho -- ------------------------------------------------------------------- Dipl.-Ing. Mirja K=FChlewind Institute of Communication Networks and Computer Engineering (IKR) Universi= ty of Stuttgart, Germany Pfaffenwaldring 47, D-70569 Stuttgart tel: +49(0)711/685-67973 email: mirja.kuehlewind@ikr.uni-stuttgart.de web: www.ikr.uni-stuttgart.de ------------------------------------------------------------------- From mramalho@cisco.com Mon May 13 05:41:42 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id B908A21F9488 for ; Mon, 13 May 2013 05:41:42 -0700 (PDT) X-Quarantine-ID: <8y+45lPrbOEn> X-Amavis-Modified: Mail body modified (defanged) by ietfa.amsl.com X-Virus-Scanned: amavisd-new at amsl.com X-Amavis-Alert: BANNED, message contains part: multipart/mixed | application/vnd.openxmlformats-officedocument.wordprocessingml.document, .zip, RMCAT_Topology_May_13_2013.docx | .dat,word/media/image1.emf X-Spam-Flag: NO X-Spam-Score: 0 X-Spam-Level: X-Spam-Status: No, score=x tagged_above=-999 required=5 tests=[] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id 8y+45lPrbOEn for ; Mon, 13 May 2013 05:41:42 -0700 (PDT) Content-Type: multipart/mixed; boundary="----------=_1368448902-7695-0" Content-Transfer-Encoding: binary MIME-Version: 1.0 Received: from rcdn-iport-4.cisco.com (rcdn-iport-4.cisco.com [173.37.86.75]) by ietfa.amsl.com (Postfix) with ESMTP id ADDB521F9552 for ; Mon, 13 May 2013 05:41:38 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=1175832; q=dns/txt; s=iport; t=1368448898; x=1369658498; h=from:to:subject:date:message-id:mime-version; bh=nr77FPnbKMaJhzOgge0MuV0moaw5lf11+BSaE8Pl4/c=; b=i4JmjET92465ezfYgiZ5iF1BaDQpTrMHRTSTg7xL4RmgwBZbovrQDAtm DKC28u4mvYHKkNAJGG9ErSeKrIUI4yXqwMFVJEUSVbuWs7accml0QSfCQ D5n2tjL3AU/c0Sh4ssy/HXmzvP4cGQ/QubvCZZ/4AQDzrjwo1DnHoCZQF 4=; Received: from rcdn-core-4.cisco.com ([173.37.93.155]) by rcdn-iport-4.cisco.com with ESMTP; 13 May 2013 12:41:37 +0000 Received: from xhc-rcd-x08.cisco.com (xhc-rcd-x08.cisco.com [173.37.183.82]) by rcdn-core-4.cisco.com (8.14.5/8.14.5) with ESMTP id r4DCfb92006832 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL) for ; Mon, 13 May 2013 12:41:37 GMT Received: from xmb-rcd-x12.cisco.com ([169.254.2.133]) by xhc-rcd-x08.cisco.com ([173.37.183.82]) with mapi id 14.02.0318.004; Mon, 13 May 2013 07:41:36 -0500 From: "Michael Ramalho (mramalho)" To: "rmcat@ietf.org" Date: Mon, 13 May 2013 12:41:35 +0000 Message-ID: Subject: Re: [rmcat] RMCAT Eval Design Team 13 May UTC 15:00-16:00 (4pm London, 11am New York) X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Mon, 13 May 2013 12:41:42 -0000 This is a multi-part message in MIME format... ------------=_1368448902-7695-0 Content-Type: text/plain; charset="iso-8859-1" Content-Disposition: inline Content-Transfer-Encoding: 7bit WARNING: contains banned part ------------=_1368448902-7695-0 Content-Type: message/rfc822; x-spam-type=original; name="message" Content-Disposition: attachment; filename="message" Content-Transfer-Encoding: 7bit Content-Description: Original message Return-Path: Received: from rcdn-iport-4.cisco.com (rcdn-iport-4.cisco.com [173.37.86.75]) by ietfa.amsl.com (Postfix) with ESMTP id ADDB521F9552 for ; Mon, 13 May 2013 05:41:38 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=1175832; q=dns/txt; s=iport; t=1368448898; x=1369658498; h=from:to:subject:date:message-id:mime-version; bh=nr77FPnbKMaJhzOgge0MuV0moaw5lf11+BSaE8Pl4/c=; b=i4JmjET92465ezfYgiZ5iF1BaDQpTrMHRTSTg7xL4RmgwBZbovrQDAtm DKC28u4mvYHKkNAJGG9ErSeKrIUI4yXqwMFVJEUSVbuWs7accml0QSfCQ D5n2tjL3AU/c0Sh4ssy/HXmzvP4cGQ/QubvCZZ/4AQDzrjwo1DnHoCZQF 4=; X-Files: RMCAT_Topology_May_13_2013.docx, RMCAT_Topology_May_13_2013.pdf : 189582, 659123 X-IronPort-AV: E=Sophos;i="4.87,662,1363132800"; d="xml'?docx'72,48?emf'72,48?scan'72,48,208,217,145,72,48?rels'72,48,208,217,145,72,48?jpeg'72,48,208,217,145,72,48,145?pdf'72,48,208,217,145,72,48,145?wmf'72,48,208,217,145,72,48,145";a="209813298" Received: from rcdn-core-4.cisco.com ([173.37.93.155]) by rcdn-iport-4.cisco.com with ESMTP; 13 May 2013 12:41:37 +0000 Received: from xhc-rcd-x08.cisco.com (xhc-rcd-x08.cisco.com [173.37.183.82]) by rcdn-core-4.cisco.com (8.14.5/8.14.5) with ESMTP id r4DCfb92006832 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL) for ; Mon, 13 May 2013 12:41:37 GMT Received: from xmb-rcd-x12.cisco.com ([169.254.2.133]) by xhc-rcd-x08.cisco.com ([173.37.183.82]) with mapi id 14.02.0318.004; Mon, 13 May 2013 07:41:36 -0500 From: "Michael Ramalho (mramalho)" To: "rmcat@ietf.org" Subject: RE: [rmcat] RMCAT Eval Design Team 13 May UTC 15:00-16:00 (4pm London, 11am New York) Thread-Topic: [rmcat] RMCAT Eval Design Team 13 May UTC 15:00-16:00 (4pm London, 11am New York) Thread-Index: Ac5P1yuWQvo4c/qGSDab/jsQdLrl4Q== Date: Mon, 13 May 2013 12:41:35 +0000 Message-ID: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: yes X-MS-TNEF-Correlator: x-originating-ip: [10.117.125.231] Content-Type: multipart/mixed; boundary="_005_D21571530BF9644D9A443D6BD95B910315557345xmbrcdx12ciscoc_" MIME-Version: 1.0 --_005_D21571530BF9644D9A443D6BD95B910315557345xmbrcdx12ciscoc_ Content-Type: multipart/alternative; boundary="_000_D21571530BF9644D9A443D6BD95B910315557345xmbrcdx12ciscoc_" --_000_D21571530BF9644D9A443D6BD95B910315557345xmbrcdx12ciscoc_ Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: quoted-printable All, There is a RMCAT design team meeting scheduled for today, May 13, at UTC 15= :00-16:00 (4pm London, 11am New York). The conference details are in the email thread below. I have updated the RMCAT Testing Topology and Methodology document that we = used during the last design team meeting with comments I received at the me= eting and from the Varun, Zahed and Mirja on the mailing list. It is attach= ed. We were not able to progress through all of the document at the last meetin= g - we stopped in the middle of the "Test Scenario 1" portion of the docume= nt. I propose a quick re-cap of the document to that point and then to tunn= el down the remainder of the text. Apologies to Lars and Mirja in that I have not had the time to re-format to= Google docs or another Wiki (or non-proprietary) document format. And Mirj= a raised the question as to if this document should be a draft on the maili= ng list. Regards, Michael Ramalho From: rmcat-bounces@ietf.org [mailto:rmcat-bounces@ietf.org] On Behalf Of M= o Zanaty (mzanaty) Sent: Monday, April 29, 2013 10:52 AM To: rmcat@ietf.org Subject: Re: [rmcat] RMCAT Eval Design Team 29 APR UTC 15:00-16:00 (4pm Lon= don, 11am New York) Reminder that the design team meeting starts in 15 minutes. https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&UID=3D484666302&PW= =3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D Topic: RMCAT Eval Design Team Date: Monday, April 29, 2013 Time: 15:00-16:00 UTC, 4pm London, 11am New York Meeting Number: 203 451 310 Password: rmcat Host Key: 412564 (use this to reclaim host privileges) ------------------------------------------------------- To join the meeting online(Now from mobile devices!) ------------------------------------------------------- 1. Go to https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&UID=3D4846= 66302&PW=3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D 2. If requested, enter your name and email address. 3. If a password is required, enter the meeting password: rmcat 4. Click "Join". 5. If the meeting includes a teleconference, follow the instructions that a= ppear on your screen. ------------------------------------------------------- To join the audio conference only ------------------------------------------------------- To receive a call back, provide your phone number when you join the meeting= , or call the number below and enter the access code. Call-in toll-free number (US/Canada): +1-866-432-9903 Call-in toll number (US/Canada): +1-408-525-6800 Global call-in numbers: https://cisco.webex.com/ciscosales/globalcallin.php= ?serviceType=3DMC&ED=3D221585972&tollFree=3D1 Toll-free dialing restrictions: http://www.webex.com/pdf/tollfree_restricti= ons.pdf Access code:203 451 310 CCP:+14085256800x203451310# --_000_D21571530BF9644D9A443D6BD95B910315557345xmbrcdx12ciscoc_ Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

All,

 <= /p>

There is a RMCAT design t= eam meeting scheduled for today, May 13, at UTC 15:00-16:00 (4pm London, 11= am New York).

 <= /p>

The conference details ar= e in the email thread below.

 <= /p>

I have updated the RMCAT = Testing Topology and Methodology document that we used during the last desi= gn team meeting with comments I received at the meeting and from the Varun, Zahed and Mirja on the mailing list. It is attached.

 <= /p>

We were not able to progr= ess through all of the document at the last meeting – we stopped in t= he middle of the “Test Scenario 1” portion of the document. I propose a quick re-cap of the document to that point and then to tunnel do= wn the remainder of the text.

 <= /p>

Apologies to Lars and Mir= ja in that I have not had the time to re-format to Google docs or another W= iki (or non-proprietary) document format. And Mirja raised the question as to if this document should be a draft on the mailing list.=

 <= /p>

Regards,

 <= /p>

Michael Ramalho

 <= /p>

From: rmcat-bo= unces@ietf.org [mailto:rmcat-bounces@ietf.org] On Behalf Of Mo Zanaty (mzanaty)
Sent: Monday, April 29, 2013 10:52 AM
To: rmcat@ietf.org
Subject: Re: [rmcat] RMCAT Eval Design Team 29 APR UTC 15:00-16:00 (= 4pm London, 11am New York)

 

Reminder that the design team meeting s= tarts in 15 minutes.

 

 

Topic: RMCAT Eval Design Team
Date: Monday, April 29, 2013
Time: 15:00-16:00 UTC, 4pm London, 11am New York

Meeting Number: 203 451 310
Password: rmcat

Host Key: 412564 (use this to reclaim ho= st privileges)

-------------------------------------------------------
To join the meeting online(Now from mobile devices!)
-------------------------------------------------------
1. Go to https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&UID=3D484666302= &PW=3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D
2. If requested, enter your name and email address.
3. If a password is required, enter the meeting password: rmcat
4. Click "Join".
5. If the meeting includes a teleconference, follow the instructions that a= ppear on your screen.

-------------------------------------------------------
To join the audio conference only
-------------------------------------------------------
To receive a call back, provide your phone number when you join the meeting= , or call the number below and enter the access code.
Call-in toll-free number (US/Canada): +1-866-432-9903
Call-in toll number (US/Canada): +1-408-525-6800
Global call-in numbers: https://cisco.webex.com/ciscosales/globalcallin.php?serviceType=3DMC&ED= =3D221585972&tollFree=3D1
Toll-free dialing restrictions: http://www.webex.com/pdf/tollfree_restrictions.pdf
Access code:203 451 310
CCP:+14085256800x203451310#

 

 

--_000_D21571530BF9644D9A443D6BD95B910315557345xmbrcdx12ciscoc_-- --_005_D21571530BF9644D9A443D6BD95B910315557345xmbrcdx12ciscoc_ Content-Type: application/vnd.openxmlformats-officedocument.wordprocessingml.document; name="RMCAT_Topology_May_13_2013.docx" Content-Description: RMCAT_Topology_May_13_2013.docx Content-Disposition: attachment; filename="RMCAT_Topology_May_13_2013.docx"; size=189582; creation-date="Mon, 13 May 2013 12:38:09 GMT"; modification-date="Mon, 13 May 2013 12:38:09 GMT" Content-Transfer-Encoding: base64 UEsDBBQABgAIAAAAIQDh5gFFpQEAAC4GAAATAAgCW0NvbnRlbnRfVHlwZXNdLnhtbCCiBAIooAAC AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAC0 lMlOwzAQhu9IvEPkK0pcOCCEmnJgOQISRZyNPWktvMljoH17xilEpbRN2S7ZnH/+b8aeGZ7NrCle IKL2rmaH1YAV4KRX2k1qdj++Kk9YgUk4JYx3ULM5IDsb7e8Nx/MAWJDaYc2mKYVTzlFOwQqsfABH K42PViR6jRMehHwSE+BHg8Exl94lcKlMOQYbDS+gEc8mFZcz+rwgAduw4nzxX7aqmbZZPyvzCl+r iWBwRSRCMFqKRNnxF6dWyMp3qoqU7T841QEPCH2DQ175TLVssFmHRs22CNeQ+abREpSXz5YqVYUI SPcW0poKjVaQGW9o6yI9F7cipmthqU781UfFO+V25H7nHC1ELwGRzgR5d5Gt0O6jVhs5MM0NYPXn FIu4O9o/6DS9bBqQdBj7SSyWOelqYbGk7XeDlKhIu5h8bpFyZbu/FB3fI/civMLj3b9RLAXvBWmo d8fi0cAOFf9mMbrQvRCJ5hHw9nr4a442zDZL6ozb6APSfIs/SPtjGGV1SS0XICYN3Tha12KdI42h X+cHefoqUGu8eTvtR28AAAD//wMAUEsDBBQABgAIAAAAIQAekRq38wAAAE4CAAALAAgCX3JlbHMv LnJlbHMgogQCKKAAAgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAjJLbSgNBDIbvBd9hyH032woi0tneSKF3IusDhJnsAXcOzKTavr2jILpQ217m 9OfLT9abg5vUO6c8Bq9hWdWg2JtgR99reG23iwdQWchbmoJnDUfOsGlub9YvPJGUoTyMMaui4rOG QSQ+ImYzsKNchci+VLqQHEkJU4+RzBv1jKu6vsf0VwOamabaWQ1pZ+9AtcdYNl/WDl03Gn4KZu/Y y4kVyAdhb9kuYipsScZyjWop9SwabDDPJZ2RYqwKNuBpotX1RP9fi46FLAmhCYnP83x1nANaXg90 2aJ5x687HyFZLBZ9e/tDg7MvaD4BAAD//wMAUEsDBBQABgAIAAAAIQCmMWjjXgEAAN4EAAAcAAgB d29yZC9fcmVscy9kb2N1bWVudC54bWwucmVscyCiBAEooAABAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAKyUT0/CMBjG7yZ+h6V3V4YKxjC4qAkHEyIYj6S0b7fGtV3aV4FvbwGBoWxcduzT9Hl+ ef90MFrpIvoG55U1KUniDonAcCuUyVLyPnu5eSCRR2YEK6yBlKzBk9Hw+mrwBgXD8MjnqvRRcDE+ JTli+Uip5zlo5mNbggk30jrNMBxdRkvGP1kGtNvp9KirepDhiWc0FilxYxHyZ+syJF/2tlIqDk+W f2kweCaCYuCCYMhcBpiS7XEnJnEAJfQ8w22bDB4QQ3X9EWOvNCH020SQ1uCMLYpKKQ5SE0S3BkIr 7qy3EmNuNd21YVP+/mmHqcd1Af5DYf4sJXCs1uDvVRNHUsNxZt4uz8QOqtKNLUlTfK/N+N+FOOaD XoDY7J+nr/u6zid2CW5ilcH5tFACktgXYlU3r/dtAiod9vWIp0EoRrdiEoOWdQx3bTIsYTH9tzYV cd8tevIrDX8AAAD//wMAUEsDBBQABgAIAAAAIQDFoZN7PzQAAHK+AQARAAAAd29yZC9kb2N1bWVu dC54bWzsfVtz48ix5vtG7H+oo409IXl14UV3uzFDtSS7Y2emtd06Zx4cDgdIgiRGIEADoNSaJ/+H fdqI3T/nX7Jf1oUsFAsQpR4UqB45wtPdEi+JrKy8fpn5p+++TCN2H6RZmMTvttr7rS0WxINkGMbj d1v/cXu9d7rFstyPh36UxMG7rccg2/rO+6//5U8P58NkMJ8Gcc7wEXF2/jAbvNua5Pns/OAgG0yC qZ/tT8NBmmTJKN8fJNODZDQKB8HBQ5IODzqtdov/bZYmgyDL8H3v/fjez7bkx01XPy2ZBTG+a5Sk Uz/P9pN0fDD107v5bA+fPvPzsB9GYf6Iz24dq49J3m3N0/hcErS3IIjeci4Ikn+od6QrT2H5XvHO S8kB/o0HaRCBhiTOJuFs+Rgv/TQ84kSRdF/1EPfTSL3uYdY+XPm+xSOvcwaXqf+Ao1h+4MrHWZgx FG+aRoIPdL7LUzU/sd2qehh5IvQRCxrWIaH4nYqSqR/Gi495GWt05uJGfI18/zlN5rMFObPw6z7t Q3y3+Cy6mM+grHXMb57+aNmzPmDl6n6e+LNgi00H5x/GcZL6/QgUPbQPGUnklgdl0U+Gj/TnjD2c Q9kMP73barV6Zyft68Mt9aMbXL2VH14GI38e5dpv+MfcpPRHKv/4nD9GAT7m3o/ebV1NZxM/C7Ot A+9PB/I1+HMmX2v9tmd92MN57vXm+SRJz9mP4WDiBxHr7bNP/tSPJskuu5nsX+7TV+eCAP7f2VNP rz3o4fVJu3vN+aaofsGDPvuZLv08wBP5j6zdLZAPJiquaeegflQ4tmd/6S6DKSh+HR3WCrc6vfZl F2pdik/z3PpPYTTPWWu/tX9Y4Jf1AdwLu52Mo/bpcc/Gx17hNzfaSfPDEBI4K1y12zCPAnnPlKTS i7lPcJ7N/AH0wCwNsiC9D7a8mzSZJVkwZAVu4bTTJBldpSRk+eMMb8lmQRR9zv00pw/HkfMP9T79 +L53u9Z7r+Kh/k7yKVbJYbdBlsPasVuQFSXGB/eT5I7cC04GKAuH4AjxLfanIPHvf04u/MGd+Bb1 Wnzt4pU64eNHBheK/RhAaQzxVePHwpdZD+rosnt2zL+Q60tN4OVvtFNRevA6ifMMFPjZIIR9ee9H YT8NiehJL86KPxlA56sXcFr7eBlXoC15ovxTiTY6+tdAoxSUGrlBOv12ErBx4kcsGbF8EmaFo7Sr Si7DUoXXcEalF+75Fw0ysDDPUuXWT/yLLnYjlJYoklwqkg0WhZzrOCiiKhqdnbidj6QjFSunS13J FpFmFe3SvtYvrXbaw2yFs02RkidsEkQz9o+5H+fh6JFlyTQQ2iowiVzP9NasUV9q1+sly37OLA3+ MQ/TgDIfGfMzBg4KpyaMGSLhUb5nSOlGsPiXIJvP1iKs6DrVy2JvI3mVTgd+vodzNk27/SRdMqxE Jh8mIeLfuyCYkTsLQZyGpErhqMzSMB6EMz/KGPJmLICDN0eWCq+i364lEKYfXrNIvCplMEjiMdn+ JGb4a54m0SvRB5Rwnax1/C7Fe4P1wQbyajDYSPVJOmbzuLVGQu41RNyd3uFFr00R/UZkBZxE3Haj R2G4HiQYIpcqFlEe6+zk5Oi0wxOq9VovO6l6XCPcRbLHVQRfXrZ673sOCPYmQRrAYZj49wF5s/AK wpQl/V+CQR7iR7mZFivwteF4keX+HQKbeU6UT/24mFVrUDbZPL6Lk4c4I1+MHK0wDvMQKaO1ovCL w87JWbPSGnyZBWkoYpwqOXUmAB5FWgnqxCgtKW5Gj+xf//zf7CHMJ5zJKik39e+UgyuzCeYjNBWZ V975Xq99+v7KwZ0vUVKrGql+NnlZOJ1FgXk+uu5u+DbwEF8JXh+qJk6YIDqtotrdxdhnsITxrlTe DJXwO4pBxqi6ZEG2yx4CNvDjKlqb5nAVbdLfcSCJkf8YpKZDjcIHzEitmXsvrDwcZwywawWWwHyl CG5xTUOkRQjfUqnFnAm+nd7tbD6YcHcg/EJGQBgHpOUAPYKR8OEqDP0ZMneG0NlTO3rqQ9dJzh7S y5IoMN0aO63LOL0RSu3HwZAYiaA9d0x+G24kD2rqv2t2IpN4APAI3N8UqjKJR+GQUG3kthlCUiD6 qHN8cdKclzYE2uxxr+9TOZ1uJ9B5IJqXJKvpdqZQPMhpngyQEkNtBLCxVOQd4cgNgwwZ9OEaIXl5 uKs9hkIe1KemK4vgVTRyzArJtTsaGwx7bhPcGhx2EA93K++Odnj1Glf7haerPUqiKCGso0moXbuW WwJHqus3qJE7otTOc/JJhTagmOyJvIK79AcBf1AU7wcQhipt37DEmkLqxC9d1jZ5jMFIgSexjwCc Skl0iUrC66ID0qzYLWyjWcxzwMKSmwDzN0jDPgw3FzsyjwrhEAyrhNDZtSghXCaz8uALuUfwpYUS bYCz3jfiO5yetd+fXG+pC6OB/Iq/4WhM+SPNnfhlgHdyzN4A3l+QSszjb+8IAfWY3BBK046prslz t33rw7lITuPBh1/8j2kIVP5J+xRtKvjBo/zB0WGLPPP784yA6YQpZQTf/PuXFv739/zkaAs+M3oM svBXQDk77eNWa5f/d4slwIkCbU4vSQBMDUZBKho77vHKfIuhz2Tybmv6/eH3RxH+025/fyb+c/QF CPhRGEUBvmlEXTNpcif+zinh/2S/JGGcEVodnxHKE7s/p5aWeeRn9MIRC/6BVpxwxKIwDqh9Imaz 8EsQ/YB//hwOkezkAM3FK7P5lH3fYm3Lj1usxb5vk1QsXg0zPGTfd/DyjuXnXcbZIL6Qf9lTL/pL EI4nHKa7+ApJEEiyvPm45JtPqr+Zf+apfE3x+cUTFd5fRlS7pX/CASjWGE8nizOHckvn1A6V3PFz HKf+MCSwD4kS/QxCkJwjToxRIhFw5RR/o0dNzqNkcMfu6TPebQXDEC/1gWUe5Nx00lvp/mhiuZBR XT7DdqsD8ROf/d90oZWS80BScH7YOtk/neV/RMUGJ3DeOWzvd49mnDokDd5t8QsQTv1xMPRzn6Uc wZx+GHLJzgm5jddo9BD9H3+4+shrP+yWA7GvpjBTWwxXf/zh8t3WTfIQpDcQ4Xz/c4Qweb/d2WK8 +YN+KymV5JPk9vjDA2cMbARYuMXEh/MXtw87Z2fds8NDfMSCtmNOkLrj4BWPZqzYYwNPr6lODQn4 bYVdfUpACLGY4Vglr+DI2BlUwPN/0hkkfqMZkhqjsBfHztxvxANToZvbv1bv5KIriqLyXNfsRlg2 HgikPxx+SCQUNPrD8uy84HJZWVke4l+1Tg67Igv0bclaSQvHBQVKPFPG/X8FKoY6VOxcBAeq5pkF PC+llRT32c8oWZgxDfT4Gl0gNUoqgftfFfoMHBMhNSXUxlTE5yGbKP0M2Wie4pDSXYa+VOTweWVo iu4uIAILIo8rJq8Z78o7vur0Lk5gPfDz396TxP2Sn5p70XyI8j3RuCyMw+OCnyPRtQAxFn4dBhxy i3egoQbZ2jgIhmvlEeU1VY+p6cJGLvAzlYyWfPhdKJk2r+v3GHziPKS6E7q6KbVtSO2bwuhDoFdb tsrbgbJknqLbnm0bnCzc/97ZUevk2MX9R+ts6g+gm0JAaAcNpBFK8hyVmKeG6z7Uc4Z+SvR0iKOs OklNt9Wrye18RB9KP0CxhxT6cImEGob34XAOMJRB+tPXWalvgvQ5e7YXuQSNUGo/BUJ/DEOEgMJ2 ztBUS7qUewP2cuHbQeD4XtwwW659f/6zIfGI3BbeUFpPX6i3s1v40jfPQ7i0udcRTkaM0rQoa6y4 G1Q6CHivDNI3wR4HjhAmVqneBdbk9v0N9XcfFDhteNUNg6xQsDGoe94td0a+98PV5cWLuvzrNXFv F6nE1fS60lunliJRG3zw0yEbAuIBDDkAQP0kR7IR6dI7QwQLbqczg15iJpFtvxNwsesP1x/RPBvM K3GpSFwey2xUvZJXQi9qEwOkmKnfLzf56sCurGFWZCJB+UJa0K2lGL6xgNYrToIxjIAWyDciMwSX /xgj55KyaYL8yTAcob5FwDFTgtSh8SkwzQLTUaPhCoXXZzjsjUXBGImgEWW1EA1pCoZqZnc8A+mz bN6XqUd6zQh5yxXUZ0EBOTscbxuRUV6pXJz1AnjA4ny6vUWUhuF6wD0CCYmgwGdjODoxZxoFbr74 mz9GanEMX8iUFgf65uv82G9X4ditw5HKoCEJP51P98S1SQOa9EjXXpnmB2r/4ncoidFOg2YMP0z5 UEeJ9Vh9i3n2uqY4Oem0Lk4dpI7sTy0rDngQk0gHAgoUD+Zd3aHYQYBntg3WCuwz4aYQNOAXuPa/ BikmxHGU5DTBqfCOO8yUMA8Gmfw++vLGjMrRSIfjmRK8Bk77fUjF6WqgUMPnwIddERci9KC4Pwq7 cOxsCCTVQ6RY4MkzQ3LNT/7WfKfjAl823Hcyaa1fxdjluuAemUTpytmZf2OnU7MtYwSDUIpJCpUJ F66K6LPW4fVpc02Rwm5yzxM+J9sO9sf7u7L/r5JuZ8z2NKNTxcimTcLCNu+Kkm4VrQ0feuXBOkuE 2W8RF8gD7mFUcdDZaXvatZYODRQS9yiX1b1fOXAcgUUVyQ0z1jz056VHnUms93N4HRpstJNq7wd0 RqhdfCnzUFlddSYFHpICKVzzYYh+7scsD6YrnqpuPJvmG8KxJYrHOP+Gshg7a2DwpbOqOKmlABtx Y62udnmasnV2fHlVABzWmLUj2iTcqilX8hq3U6H2qLUH0wP86AV1+vrpf1FRvn6ySpSeKhjiErc5 bs3PgGcHJkIgJGQVPsNcacrARBz9JkymyBRSvxxSmMbv8Gkh2sP5C3f22Qek6+b5HOkcXtrHV4i1 GqqsudIVbDcbeqNj/Qx7Xee4RFLsYsLiF2I2OpvfcGlrjhIvR0YUJZtmOVFLJm8vXAveKRW1xcw0 osKtZmbDaER2pf7rbdeHFjND6m1ZdqWSQxe1WNgeSAH1kISjUELIgnTK79zU/0KZbRQuMAeBJxzV 60dolhrusx7LsI8jUupvASLlhV1UkOJxPqkuCPUuDk8vnAAhFenLR6UgKvAxyoTsMH883kJU6L4V zwBmDQhIvUDY8XcMeY8pR7as4aZtmGxa70+5K1l04ESryO/Mc/tA8Qs7ZNuLii5Nm6uKEy4vOodN ThsbojuOwFQmjfUrJQ93yygo7/AbdsS2F1gwLatGM2zSAMYefZhoEcRr4WOhizNIc1y6+9BXzpkq nSl3rzKgdMZ/b4JBhKRRSccuxEPqTUpq0kOtkOrgGIp6ycj2a3a7xpir3COx2ygNd71Q2aKul/Rz NJNp/PWVgHMDBZNlHoCSQoFlQKfLQviixx3tg3RJpEri4qOkTNL7aT7DHItfqORIx2y+h0YMaAVI RYz2CVSTpGmfch5GGgBelFHXK2r/AwwZos+G2OfmzOhC7sFd1jFQN5IEGA9n1EYFAgTGHy1+NPmr KGpW8yIT9hYXUkvlqwC9vrYolQV4Jo1az4Y7Ght0IT/KkV1zYFbSjPZTCvX2iOVMGPTWDzDPNqRc 41tw9tXBmUBOQbmJ0Xqq+uWnqY/h9wQWUUMmZa+H7NnjCDM+ODD4ojQLNfAh6SGSEyu2X10+Ap01 3GZD2jAAOG7AmyUacFJIgAH/WBrsBYrWJEbnmrM0tXcnFkos6TPgdlVUukvyc9Dfdrgf7MPAJSyg KRsA49BWWgiiHAuptEUVyc5iQXvILBxU7QmWfPdni8mcbFly4w11+4zcmOCLT0nFFfjL0/k/XbKc McDrXXwyTsJOqb3A5YxO+0EdXPY+/2XRITJI5hFNecLQUQrQcX4FLws61XjShtwpokomj7fh+kX+ gHQP/fTfo/yP3333nUHmyoFgSMpUzxzrkuPMK7SfyL+P8z9WstmZxGDSL+fpKBwjc2yUzyxbMImp Usit7qB0+hSvteJaI+7gy2iU1K814OPzvM/n1sjBJ8rTpVg1935KKDYiT/AjBDfVJ3wY0lu4ZJrF LBl5QdHSZ9FtW/VBmlEr+yCEfJWSKD9CHahcrLuShZzjBbzrW3TcqDEwqrHtg9g18JW0Xi02APAC k/lpgudrjE75JoSUnlZJW/2xn5O4yuNDFsxjVaLHl6Y0C71jPcTvKpUm1pNQGgvN5JibxvxpMhfz jvlwK1hWZCuQQ8EYZ56ZQdc5dABuboY13flehFQjDPEcsSKvHixbO5UTuMCnrdNoIJWG4pameTV1 8o0JjN26ii5ayj4JrIA6sHQeowXh/47gbu9hQcu//vn/eEcCDQGK0KODwIZmkmGEJDkZVVJ42u2e tMQO+SYSgarMZJLoID8qkn3gDxbyYL6SuWfOj8ZJitUn1bglZ41EdvGQxTtzgn3BAmuGs4kTZmjj FiPvoET0OVZ8OOtOAwePm7ROi8CbElJ75UUH8i00ySdYhZX18gVpc6ZPvNs0nLFbLFFi2+iw20Ga 2r0sldxKkxBlyITHqUHzariQD+chDZ2Ek6McVuwonfppGK1oifqVbAl/+NBo2qwgoVmqVrNsnCvj IDlOzkTMTr1ARJgE1s9Lb3uRorwT7fMaOAPL2agos6y79ufRnfi9EQhbw8jXUJ1508dKH5MmLsJV 2lSk4yPDdX9cVBaonE7pzHCAcW+UI+N9BKIgaSQ05X1EOVK8FYA8yq6RV4kxYjzBFtwnEWAFVBBk OVe+aKUkJ1PECahZZBQZWD5YS6RW44IaTmjBtY7Jg6aKcjJ7UYlL6XvSVs6e5kVYz0YotevVlTDF gUqFmMLxX0qzqAOIlW4SGjYG7oAgYmjND4Z785kR86r4Vjbn0AIsleql67FGZXzD9JrVPkghVtLy Ow7IV3Vvh+telB5oWeoj4Cp+LIaq8o13pD/mqKanhF/BmE2ZoxYtMRjUSyuxqIgxmCQJ9C7U8xx/ cGUqRephQr8wFSr/JWSN5s2RZvehjoPBJBb7VmQjJellksK9ez99XGQFUF0YzjHbhvUf8QEYFhgk 7M8fb9DATfsXuRV54DTJAbegUG6nC/AoChDAVSSflgh5j4cA18f5E5i4s+t2C5sE6r/XdgWD4JNv kDddNyXVpK0bjueFWKhtXlA10kE2SF6pDwHYGkVlBSJnz/TVFsgZpXYBEbsLRWfIIv1jsN4Bqnud 5SvlClnzN9xlSK1Go9ywNUKjm7Q/2QeAw2lceB74U+k3kDPZQxwesc7ZLuu02m2hZ/V8GFqXkFvp ML8P5xr7EuG2z1IAz5GGp8IW6XLVPBbG94CthxgVhFEl3Ihg4TlgP9xHEZ/M4SLA4uPdqNshK4/A gOwMf6FI91snOMHdX6LkYSCmMFhEFxK1fNDKE8ON318fX/Vajal4MT+ggSsLuy1BV8jKAzCHmsh8 Rll5BX7hTMTvaPCT+JVJpW6GGmbjkuoF5FXLPSDUpMEzJGei4E7LY6ShInHhifV1sg7lCkL+hjyF hpXY9eXx8Xu+/Yj2ZOhbPhqh0YkSs1vHVc+3S54vVygQf+7+ohRlcYGrJF3ytymfsOid77OrOJun 5NpyN5h0rtaaIBIe/Jkf/Ef9FhAM7B80c5sYgTcVUnE8TYJWKRqQ5yMVQ8PB4FPLvVewDP0gfwgk tLzwzmXzFX2oVqQS06+q+Nqwr00GEE1lSCBVzz50dvweuLcR/PJkobGKGGdcsd90JPywMSAzVDhU j26iep1Oq+NijUkJjR8qj7NpA6q3ileddMNc5INuyL37Jcxp2ifUIVlvUjU8VB4h59XH1D2VttCV YdVjNcx+mbdeNJHJpIsaA8jnTVWR3/CpyOyNQeEzg35X19Prvf+fZuXVTupVPCQs3YbpEYqtsKd6 mDzIbe8gnm99AuKGLDec+ekMoCYaZkPAqCEqH3mY8caMjO4FT/ZlO5RNk00FZKy1uU3aODbjSAsK tXvavroQ01Bk6bamnQV2hYr4cNnHKCC0Kxn5RvS/J3bbI0svoo3CLV6/Aa113D08a2+pR9BS2PI3 GxBsGABVjUZtNbG7gMhJsOHdTlbmHatDooxs0/AlqINZksG1N5Mwq3v3Vu5LU1GN2HtdpWyccdVD uERBEY1ZUBycJvgHUlvQrqgZpCu4FP34r7BR+Kq5AZWi5Q6t9CIXb7DUbufK8vDOHuWr8/DOKLWb IjZCq3+MFFMR/244Dg13MJqX/Xmy4Iz4r5YFZ5SWyEIWRKM9JRBrlNPLbaim89zZUGtlRG7aVXpO s/OrO3itviBs5pRWnPu/JOlfenEWkl8T+Fney0Jf/+WV/Bn9nq/c0n+5eOcgy7UPvAiHoXDUB6gm k4/Ku2HaJ93jo0v6IP7i9/Q7rNzGAHVsmJY//Dzxh6Dr4lq8P8OgBEqmyU84Ej+9CzDqQ/6ocypf +av6yVFH/eQ9Ji6IrxY/Ays5M4ilskuEDOzztjaXu4GdVvc9JrbgO796IzJWzeefAiqVB8MbbJK+ SAP/joc+udyVTP6EYUyI0TzHTF6P5pOWdDvhYGQn0tdpIk3iXraet0D2coV0P5Uw1JWIT/NlS57t M935a2kEzMcr5ZO37KkyLEc9lxB71/0o7Kf88vHLVfjJmoMBDGm2XvfC5774m6iL7yalsQ1wyGSR byCq3bJ6gzBYLY/kDls2CGIghxOEwsBEAdZCE0oou03JbLrYev2S0kgLAK/oXpdZsMXHFO35azgV K40bZmKgNuoPNEQ/W6FpTPUgzaNI9SDJUQBPt5NV6b6mUSC8042kGcmFOJuGOTaAoboLr5RwgGau ywHvSzwjuoqFbO0Cs6Jud2Dm8F8mzrpJbMSJciLhdi6LBrwSS1swRadHx8enRw6gDx7hsdHTgeA5 42hB2i1kXqj6NYKdX6a1fjosqp/SF8VA9ZNVwkDV4rn9gO5DJD2R+FxZJ8cLwwdajpmmlKEFCtno FF4nGfglYPTXgFpFDQF5O5c+1NpzlrsXnFJAe9aIRYshhQ4eKboQfDrDt6tZxQpTQwCb0Z0ld+4D xv+b9DWlAFBloqFCSxVvEqYHXO3jTgfRdlO0yk4Jk8KmyBGIe2hBbIx+wTym+sne1O3LJdcChke0 MsBaiJrogep3oVw+EE9xzlE+Kj/O2xDFlPxhwEdJyMS5SuCZ7sEmaQEEwYYgP20k9bvozgH89OP7 Z6/wboTSErnink3O+1qEfEmfx2C/g9BqHay9BLMoBmrZ2uJvvnErbj/LQz535JqSSgRRXI6yxSjA PMRcvOffKQdq+CUXqH6y7BwGU5GWQ0cYxm9xYJ4CY5m3RQko5Y/P2t3LkzMHfoEncnwmLU0xiycq ab2FyG9Sg5vcJCIQ6tRKZ9D6tJKv/2FeV4SqCSR6WujqC9Sz1iMgFut8Qc1fZfF9MRR0+V4DXvqy 1BQdjSoG1T857Jk09tqHp533/BK6oxG5MqUIxLgRrdzyGxQXwAL5Kbl3S6COz7JGwNrF7H6DObvn 33DFMVKdx63u1aELHN6LLn0jlJYYphsZFVB6ycyOGEp2IZPE4auT46PepQPjVEI3b2KGZVB1KfZQ Ra0zLLPHVwDESWG9gFjVVEWfVsD9De436ukQsefkxYCOy8J+tM6oA3m1lAxrnrR26dypSqs63zAa G1SjfIIl+4jiwvMV6pvLBBgM3/GR3gdbnpynw+NeNE0+OWZTTFSHWlXDaEbLIus6ftObEKtZSaJ+ d5HkOdZ5BehkqVKlPVdNE3bDxDe0mfTVf5PsxIg9biY1SnWTGW+YWxOU5PldmqHptD/HMolUrp0T zZUZRvUMeStnUn3oKwOga+q78E5aVew8OqWtHM15RVPsA0RfCyA9wxWMQ+HYnfFrlx21NpplxnE+ nUloho8rI2zthJb0Z7k6brsaouJ3B3hIg9WFeKLpm2PQZuduWVeAM+K9qUFnWr9p8UxNYufNUvLq J6lMzEZo9TAZVLiuzfoGfAsrTecKmJZmw6jvO4EBk8i7qidwJml2FvuDnCYkVFHozKPwCv6CKaQb pVxQze4/Uu4fczw3gnf208XtmRHinZYGgOKlv81FFNn4YLhO4CJTQ+riaRkCLWnkLkPQYPQthm5r kHZ0KQMP1t5lXfhFu6zdEvOiWuaNsqvYMvNzdXzYORM56nqzR1+d7XRGaYmAm5evflPlybL4Gkgz yZy3e+MtC9K4KuaZKf7wLLQzyacLyy8r7qw4Uh3fVSybWHOST2pF+VwcgaDdE6ko0daBF0TBKH+3 ddJpif6qGm87PYPWoFXjN6GlxX5bsZ0eoT/QB2KEklxji9GqmIAHbiCthuYy0qfLOelUIH6BMnWg Bp4dv9VPk53rFLCbd+5pc1Q/td6r4aBQE29cXHa88bbJ59akMHSA33WAaDVV+2ZHn1HXO1oAuzbD iC793TcTeu5ngzBc3hFY96/pCrUr81ukGqQDSrEnEFUR+uCOWv/9AP/nkJ+HRN+fvFg4giz8ODvn nSubITpk/f18E2gpNkU7MHwtwN+WaX3d2+FMoSZHHLMA4WJ3QbtVfEMVz35bXFEF7mAdjO6THjLx Wjml9QPFnOQNvGNS0RtxRHYNYrqCLhLOPyVVDHGWYCxhCOZh3GFDBB+7CB9lgLkQtFcHo+PoGqKn YrnASWvuWwyQYzzLy9+OhCBNOaTWT5YMBvNULXvUUm+8hFvFju5R++jCBUq4hB1DMWuXlgnRwqEq Up01hXvrpCmPjk8uMOZcpRO0NGVTmM/6bYn9DE+4m9hjNNd8Zd36RsR+rwrrL33b6RzI2qrrIAWw /lP3hI7CCAQMQMAdpaUBv9AAa4n5ts4CWSOlJb0Hyw0q3i2e0tKetvGU1kbI9EnPEA47Vc3XVc/Z h5xxaQ5okAbtK+IWEChXvkNglGJuOopGsGJ84jq1u8uXUOxuPGWhMKdp2iYyjOQqV5HXuWr1jlx0 5nq6h19F0UY57MVbrrfGF3/zdv8jFCsoZa93XpxcGAe9uff/5wn8AunBEhpPLSb3BW5huUkEnVr+ l3CKXSJAao6Rml/rEfW6pgNr+OPtf6xFVvOalwXwqh9XInomVrvxdRRMDhpvd1rsro8h1+9YG4g7 gTc4kGr4D1RpFn/PDgAPZH9gp6wPd+CAYAl8puviTep1WCVH8cxanNIPUHkDvDzXwf9eR2HaFaV2 D1wm6Qxmb5KpFA4ANhZiTaEcISeFKwsxnAbru28gOY9R4g8rn6LXPsWAxvpveRmfQWwVfVfNysGO ed8KItA5PmmfOnFHUEYVB0qOHvaOESTIrouqmOnMu1snuyiJUepJC/ffnBWMv6wu0Xkn742DfrXO Cvbr8ek8fPPZm79SKECtOe60FLFRoiN0f8UQo4J+c6Z8vV2TjMYMkkmI0k9u0U3k6cm01TBBWjqr zMA7C0JLjDhS7TTfkyKRbWykTxOEHLjT0WO1+XRFdsXkaPsDqZjJkAW7ii3ztV09Xe49P37ShdoZ nXZeA1P2K6o1MhjiUB1/+AtStaHB/YJmcud5QabpMmLPeJDuAY+NLaRzFO75v4H8oJQt1rsWpL6K 8Hb7qH3ZYEMa36hYRaAzztrFYZ/drga5haNvmIN08ITHpy3tYg1LQOstVwLzAs0NM5UEmKeIQDAP HdIAQSOKS6td6AWynbHay6YJ8BKrE3d1RdUwE3HltXYMOn50DYUY3ZcHu3oBZzm+3Ywdn2c/nD2u 9+zCRyOnsk5MWY7YP+12T1qHPM/xrSFWTnm1+HaSBnwmcaYtylbDWDJGhR++foBPkyPomTBcAG1X WQMN995EPUhst8JEpEytAawi1lkvnofsLW+hVVi+KqqcsdDjthPT2VZ72uqPprw1ytNP3k6pV946 LtSgjfYO+4TWimTK+K0W7RVoXlx4n39dqZc+bWQcCMOzWwN0i3J6dHR1KFR1vTrHQ2uFeXPrZ47d 710tfL/Kg1whepz6Uz1Cboq/fzOdsYKj605Hm4kuK8NkodPetiY67NSF0dLm0sX5HStRr2NeZ8Um t9m7HfYZNfco9+MgmSPkIo9MLG9CiViMrSrKgfWki+epozmKv/k9mkuvuykn/dEkpCkNB5AXZptR MXhvkEyRi8U6DYEulGMsKGA1iF3RPpgpEEVu9bX30/9oG2QtdLMYtqrFbjU4BBjMiOXjvSgcLxYo ZnOES9kgDWe5CRLKzJYXOws3AKoigKWkeigv749oA0aWB/7wcQ8KCZABmvXFUe5YqCgCLQgIH4ZN b/hJ6Kl1gNsSlad0rWaSNLzeNxZ12724MxmKF+bJXPzMKO/G09zZfDBB5ghdQYGPv4kzmiTzaMjf Cde+7Cq4tWDAlKJ9gCDJD0kK4nhbt/wRkobWLHJTio+BwdkEKxUhtejdYUk/98FIUndLIHUfYdRD OMwnaKLD6CsOzdoMVu8yzKjj9BR9ArQ7qRvl8uydd9O1ix3ExmO7a1Hpsh8JrkeTDA7FXyWS70ho Qq3nWcThpvg0Jv9oWVIidMA1CpT+GB1RmVAsHA/Gs9XLAUIm7bqkOVu5YtehfLZRFX0Nr2daaJIV VV2/AHgiaSvkcx3TvGEtnNY4p9tuXV2ebCkR1NwHbUr4N+Y+eLewTsMgI6cTPtmU+YBBwQ3DmK8e 1j9ErHO2CzvV7gpnIefJfbMLUWK64VuIi4469GBSdXOuDo+OZBGkBkdax9JjJUisfEpsB9E2r50z JDV9k8r6r45d2TCO56YWLDHTxqRLCSW3wM64Z+0xbYxF0DlpwMdux2bwU/BQ5D1ujM6MwBli9Tbc v8vP72/YNqo0og9fYqMHwAJli+1qO6z3v35kcZDDyb2T13EzJCDD7d+4azIJxxNAYGhqZhWXWkfd bsfFrg/7lRYztnWhRYccv+YG0fbIXU9+6Lff2VN5fYPOZi6Zx4d/99E/gGZ6gyI755Y5D51vTWsF dbuNRygw1dnZ2iVW+AFZ5aVyxkZPRj0pnBOaPFrFN3f+RAik3YfPN8wfDIIsQysUhWldi4bcJNGr Yp0zkfNiSgaDfUJxW7SjeoG6KVIcq6h3Jo32CyNAgkBfzgGNBhLvrycvKIM3IinPH5rXCJl2tlN2 rUoqnKmDEvIeKK9aRaCzS2cnkAtsJYHOOOjxrgJKCo3TZD5jD1g6/F0V6xq+8X+jaBhpUoNEuyNS 5sI5e4bXfcvJtFLH8huvax8HyB4CIDEHtLQ53kWUTQtWBS57n6n1v2Ec5uT+cPQmjN0rOZaXTAja JFs3fIz9aThAIP52F5yMxqQiqUhv8ymz/WDg4y+muBfiNm19Qc35TLKUMDZ5MkgiLd3qY0UjEe0P /RnqLcbVLNDqDM5v9z0WdecqGhv2j3wWUeFKRipQdV9985w90OoeIF2XOTv7Z68G0ql0dpvsEkqB HEWnVMYXsSoUQkxDDmAYAZZYyUIVrpczz7mE+G3MmazUVc5E0U4gAQ/VUlmTzud50c4exPt0e2uq VDup9syjM0LtHMds52CAUgOqeihHAEwGAFbos8MqBexMir2dSjJc7ZI2erpM7Mdy1Xu95r3kAKtY 5CyWtNNG5WORToDWfIuMH9x4qGJvOBkqwXvS+QS4Fa11QAXRWDa0gkfhQNQhVRCBscLky2I7+ryf AZmDTyCP0hAwu3JrPpvx2kM5wkTx2CJ7jAeTNIn5gKxgf7y/yy57n/9CvXyiSvxKDqR38WktSu12 sWHVpXDF7Ac/w4jSXeRAmB9lCc9BUjA1DHCjULPAkIURGiynmITydms4quI6idFH4kjZiVvDgb9R Ap8c3pgYlf7EBjBXKBm7YZz49xRAGNejECo0LP8ZtBEsBk8ZCCtBvdlzZPlYHk6DHWkrqp7AnZs4 x8yDLEx5noMP2AdATdYJoVGp3sIzmKJkCE9XsL+K9oa5jzn/DyrMPBBhZj/BU2ZFFPIzgYraQ7kD KlppLJ+qpw3/c0ejk50ddk1ALrKAgyF5Tp7aocwwIqMQjuRobPLC/GicIDqbTKnX4S7T53zQHogR pR+yJOZ3AKO09x6Af3oaBeUMuG5/ethPGvsr8OzmfawfoufxEVrm9+rZJmf88cAFkxAHDFhDn2zY XX2mPtHaBH53+kSMaD4ihRJAc1AAmFT6HJrybSKVoau8hTMnHDwaBRMnOZaOZf7wHjAAf0w4dEq7 Alae5tzvEy9t4BZtm9/ZjApJ0ko6Gs5TkRHD1CkcWbYyS9mBptuh+BnyPwmiGVwriJAwr7Cs08qx lc4GfdhN5Bxj3DC58mES8p7MgE/OoWehK6HdBQKRm8fvgK2FC2l+v34NnLFxNWnsgA3fvB3VTMPv 1I4eS8d8GAyARaOKOhQa97D37tHWy4Pkvb5Pe6Yx2WAGH1wNYHxBCtWByL4kX1o/WXYlKBaG8GRE iNh+lGLWFLF/G30y82l1zfXkGrvuXGyTKCF9NKdRrKZqbIqTO3yFoJRTLbuzFFlkS/jMUIxfAMoB gaVJuq7VG65eKtSZSWL93PUI6IYc3hqK//Lk+PKqt6XYpnWOyt8Qte6UqjWA2jAaNyQhIwKoE674 LajtpythDuTwVanxZTDHBxQPYSvhkqMjmIPpKP2FLFa0RxlmPgp4n/0n2nuAXKP9xFD7/hStFJSI xjaiBABgRLY+GycJJnNjnPuj6uUtVVliUk+9A4MfzkNjZZcc1O5eSZVYJL4BiicK+YTGPdl1ijV9 6DqFeSX2F/WaAXmol4FQUDL7kJc8wK3JSqVbXY4gKSGOxm1LTI0sr4vJ2ySpceCnSNb2YTr2+ITb NZ5DPZoQ3XprKkJ0H87n+FJgB95tZbBwUWBOl0IVCFd1ihQ0rQMliYGXQJO713ic+jViicxA1BPu M2aPmC81rSK1afHW9qz+VmO6nT3S143prle8n1Ys22r+PGbUQSsGQ0yn2+WJx/48zfJdGmmrS9E6 w02KYxAtAxI3wP3bMBpduH/PXrdyi3izUKk7LXUzyAw1PP8HVgjzIvYwWmy4zz4SSoVji3h7DkXO iO7SfA89df2AquHwvOQwMlQXlXUCUIxyjGoYqHgP5XCxcz5FdiN6FC2uVlRSWr+m97RnAgiHgPmL sZJiaB1eoKVI8ZBrpytbF8eHrebGQ8APxsNg9wX5x3Rei4mH0oV+7qBE/raiU2cNBDdsSqKVRnk2 yjPSAupvd5IjH8VUUD9ndKVlyWyQ4EJiDGKC2EigdXhpDIt2l6CAZWS1mA1W5QT1Wp2z4wZXAKV+ PN6YrBnbRhkG8666e5dskkSV9aKGNQdGmc9WFigXkGWt3slFtznVhl00caZCzSoJdMZID118AHBm lLefJvEsgudXSZgrBnr/VkmGKxPlrePmlivl4m/4HHBNBGXic/Y5f0RNRcadf8EAYISebRl5quQo uRS5d5Mm6BFC6uiGpmQBRvleda1QAukWwTX7PAhi1GQS1l5j4UeRPt1B1yRQkXAj/JoaMK5k6ujT n2nyGqHRhYNekl9p8+m5PfSxalOid7VBxX5Og3UBkKNh9n5IABGUyndRqhsBrT3cZKcdo67J1zMv ff2etD1ncrGcxHqhBhOz7YsdeNH3SMsOCZdA9MbzaR85WSSBhHO6/RNGHxEkGyGFjzMY5LiX+G13 HWS2M5yA/ZnhPsEQSOLp4XiKFMmwBk7F+yu7ONju/oHYiT8udg5+MkVD+cA84mx4aePf2Dp2Qmai FOGa867lqBrWthtGY4Pa9q9XwxC391///D8Z+ynJg3O++HLR09eVFRhMuMr22QfE4PEjgA/0U1RH kThA0MEX7vKK8jAZoFgfI432mMzRQEB54xEUhw+FQn8hwIT86FUskxIYkvTW+0776pivyWsCp7ik ltsUDD4RKXDjcj5dHmzkmTwyijEOzMQb2+lddmc1ZYbYH/cMxYILobOu6azxLc+T0aKKfoDWSuSY BnNRSaNiGmzI1A8xL3zMohC+Ke9H4feBt3SIxFyC+5KGg7yYoXFy8b2/FeT2NbifVhqlFCjB0AzL 781F7nAX+adE5EDFVOsgxkhKub+aQ4BW/BnFOF5DbbY9jncoixmQURCP8wk3KOhIRjL0q6etONMW XzdfzRmZdj+YEMYY9s7bxrd5e2VBSyBWTZNkdJWSIs4fZwFqxeZSpkYE6mvHcTTN9sI4DrIdVLEx zJ9V/cl6k2K6pv60SlTTfvVxp3NxbUPCFannOaJGyHZice03rsv2WA8uMxZ4U3g9R8iZJfOU1PZ0 Dr8BKClRoqOUBs994A/cz0Ww+gD/eWXm+dPXtH63zvvhBTNy6ifLfgxsW5Q9n63u6ieY83EtujbA aUcIyKMjpIlkWota85GxTQbAyuOn3KiQhqOk0eJfxuMV/Pymkdw/mMQ5OHIaNYfLD96ZX640Pflr TXNGYgeWC1RMYuvnlP027+wX/Vyr6SyPHIq/ac4svVKynVhTz5qjAnBlEZDHmNaixeSj5ZizDrm5 SGIhaNe2HE2DgKD9GXsM8v01omN5+9SF1Fyv4m82TH6erHvJB1qrYvd53s/DfIEVVY4m3fvco8xh tkYl7vqsddFr2fxD+Rv6OPXRb5U4yYH6davHi26mTlfyzmsPwrOvnxS7mmc9k7imKMmoH616SYoW 2DSRveb5x01hF2bN5bwTwSBoI8KWV9VaIzpRRf/psq/PYGvBnW5YDhHdRnNeOlkYamGEq9s5tSph vbfHI3ArGo9CDFeXOXt9Cg+wJiZzm9I5vMZgSRuY9OkKWzOoNbMRqIshNb9sA5s48bG7NkoGflQ5 2bV7dHx52lx9DzBKtEDNp7ydjG/ApiQcyxSoSKIDOq0/GBx+WmvpR+DsKV+Uf2mE0hLrLtbCU66A UPsiYbBQGv4QUJSVuplOvkSbqR+JTioNglbvBSh5JkN0CprZGW3cMxdzLZdlSZ62WRS1qVpcRauz hLlHNesqSpxxreREkfGCAhDQRBSqeL52GMwCDCdcToLgyS4+pFJMdJliW2UuOoxgXTh0jfwhPm+U BvnGtG8Xn0YBLCYAVm+Oahg7RRcUjVMKX7BHWCo0UBUzMEbtvuFDI8QoLQzl86OQp+TLuZIBGlwE CIzdYj8rBi8CpVIleg0znmZeypEOVVQ647WHHiFKWwIXU0VPw1yjTqY8TaIqEt2xbK0an0D4KUOm JZo0r7jh/MjvETtnT0EqLBuNvicAg48BdjSET/TkQK2POWyuSvycGdcSk3ZbRDZVkdpttY86zfns UZgj+2jkeTnKaoEoBAKZLFTRvdFR5LTXnl5hPOYzvXpXfPDSKQYMrEXrshyoVAfl7Bo+MY6GW/Hb 64+hvxW8W3my/PeHd9tj13x7As1E5PdbOM2rkIk9CZmgFRh01ZeZMvPWFwIyd9mSRTu20FbAepAX rU1/Tub5bJ6Ln/ImTz4sh6JhuDNoB6W5qNvhfoCtEfyd5IZN6SPCleCp/rtWYlaAKYdhIUSsDwxs dUzjLEvpZegBNNRpM0JQwrVpAMQ8t2br+Irl6kET5oZ9xYvDzslZZ0sZJc2fbYRGF+XqirET3uFT q6ud3YUSCfwcAkVsZpuNK/M8b8nZE3kvKeYowdyECqdorStBAgqzZpxEQXl1et324UljLTNMpHC/ NmXu7Ck2E2rnUSUKgDnZwIOVzMHgjsEuZJgwSp1VAinK81fIKaIptkokGk6/pFGIYBhpZ3hiL4Su 6vfT2dN8dTXFmRCXaHHpHb6uu2g6r3YzYw90m2b4snyFWtWisEI3eVHOWimHNuWbr4OXfH99fGWH acnfEPHuXUvMBM1vCkZPJ2f8+Veoi4d3W+1O55BjzCb4+9Ep/o5xnaB3/KNPb86TGX5+KF6SUnUG /zxt8Xf00RCfTJe/joKR9tsJel2D9N3WSYe/eJQA9bb853ie83/Kr8OGbtqRltGUOfEWTgVaZP+c hgBHn6NhMLgJ8wGo7B7zNwEEKh7RI63eT4aP/C+qq9b7/wIAAAD//wMAUEsDBBQABgAIAAAAIQAw 3UMpqAYAAKQbAAAVAAAAd29yZC90aGVtZS90aGVtZTEueG1s7FlPb9s2FL8P2HcgdG9jJ3YaB3WK 2LGbLU0bxG6HHmmJlthQokDSSX0b2uOAAcO6YYcV2G2HYVuBFtil+zTZOmwd0K+wR1KSxVhekjbY iq0+JBL54/v/Hh+pq9fuxwwdEiEpT9pe/XLNQyTxeUCTsO3dHvYvrXlIKpwEmPGEtL0pkd61jfff u4rXVURigmB9Itdx24uUSteXlqQPw1he5ilJYG7MRYwVvIpwKRD4COjGbGm5VltdijFNPJTgGMje Go+pT9BQk/Q2cuI9Bq+JknrAZ2KgSRNnhcEGB3WNkFPZZQIdYtb2gE/Aj4bkvvIQw1LBRNurmZ+3 tHF1Ca9ni5hasLa0rm9+2bpsQXCwbHiKcFQwrfcbrStbBX0DYGoe1+v1ur16Qc8AsO+DplaWMs1G f63eyWmWQPZxnna31qw1XHyJ/sqczK1Op9NsZbJYogZkHxtz+LXaamNz2cEbkMU35/CNzma3u+rg DcjiV+fw/Sut1YaLN6CI0eRgDq0d2u9n1AvImLPtSvgawNdqGXyGgmgookuzGPNELYq1GN/jog8A DWRY0QSpaUrG2Ico7uJ4JCjWDPA6waUZO+TLuSHNC0lf0FS1vQ9TDBkxo/fq+fevnj9Fxw+eHT/4 6fjhw+MHP1pCzqptnITlVS+//ezPxx+jP55+8/LRF9V4Wcb/+sMnv/z8eTUQ0mcmzosvn/z27MmL rz79/btHFfBNgUdl+JDGRKKb5Ajt8xgUM1ZxJScjcb4VwwjT8orNJJQ4wZpLBf2eihz0zSlmmXcc OTrEteAdAeWjCnh9cs8ReBCJiaIVnHei2AHucs46XFRaYUfzKpl5OEnCauZiUsbtY3xYxbuLE8e/ vUkKdTMPS0fxbkQcMfcYThQOSUIU0nP8gJAK7e5S6th1l/qCSz5W6C5FHUwrTTKkIyeaZou2aQx+ mVbpDP52bLN7B3U4q9J6ixy6SMgKzCqEHxLmmPE6nigcV5Ec4piVDX4Dq6hKyMFU+GVcTyrwdEgY R72ASFm15pYAfUtO38FQsSrdvsumsYsUih5U0byBOS8jt/hBN8JxWoUd0CQqYz+QBxCiGO1xVQXf 5W6G6HfwA04WuvsOJY67T68Gt2noiDQLED0zERW+vE64E7+DKRtjYkoNFHWnVsc0+bvCzShUbsvh 4go3lMoXXz+ukPttLdmbsHtV5cz2iUK9CHeyPHe5COjbX5238CTZI5AQ81vUu+L8rjh7//nivCif L74kz6owFGjdi9hG27Td8cKue0wZG6gpIzekabwl7D1BHwb1OnPiJMUpLI3gUWcyMHBwocBmDRJc fURVNIhwCk173dNEQpmRDiVKuYTDohmupK3x0Pgre9Rs6kOIrRwSq10e2OEVPZyfNQoyRqrQHGhz RiuawFmZrVzJiIJur8OsroU6M7e6Ec0URYdbobI2sTmUg8kL1WCwsCY0NQhaIbDyKpz5NWs47GBG Am1366PcLcYLF+kiGeGAZD7Ses/7qG6clMfKnCJaDxsM+uB4itVK3Fqa7BtwO4uTyuwaC9jl3nsT L+URPPMSUDuZjiwpJydL0FHbazWXmx7ycdr2xnBOhsc4Ba9L3UdiFsJlk6+EDftTk9lk+cybrVwx NwnqcPVh7T6nsFMHUiHVFpaRDQ0zlYUASzQnK/9yE8x6UQpUVKOzSbGyBsHwr0kBdnRdS8Zj4quy s0sj2nb2NSulfKKIGETBERqxidjH4H4dqqBPQCVcd5iKoF/gbk5b20y5xTlLuvKNmMHZcczSCGfl VqdonskWbgpSIYN5K4kHulXKbpQ7vyom5S9IlXIY/89U0fsJ3D6sBNoDPlwNC4x0prQ9LlTEoQql EfX7AhoHUzsgWuB+F6YhqOCC2vwX5FD/tzlnaZi0hkOk2qchEhT2IxUJQvagLJnoO4VYPdu7LEmW ETIRVRJXplbsETkkbKhr4Kre2z0UQaibapKVAYM7GX/ue5ZBo1A3OeV8cypZsffaHPinOx+bzKCU W4dNQ5PbvxCxaA9mu6pdb5bne29ZET0xa7MaeVYAs9JW0MrS/jVFOOdWayvWnMbLzVw48OK8xjBY NEQp3CEh/Qf2Pyp8Zr926A11yPehtiL4eKGJQdhAVF+yjQfSBdIOjqBxsoM2mDQpa9qsddJWyzfr C+50C74njK0lO4u/z2nsojlz2Tm5eJHGzizs2NqOLTQ1ePZkisLQOD/IGMeYz2TlL1l8dA8cvQXf DCZMSRNM8J1KYOihByYPIPktR7N04y8AAAD//wMAUEsDBBQABgAIAAAAIQAE609cXBoBAEBgBAAV AAAAd29yZC9tZWRpYS9pbWFnZTEuZW1m7F0JPJXZ+3/tlCYlIdu1lKUFZcotcZW1orRQE6KUqZQt 2bcaE2UpSxvRaKESbVNMtjFljxalmUhlHYqQ7Pyfc+99uYRfTfft95/fx7k99zznvOd9zvM+5/k+ 57znfa9YMAyzAeqnp+SJGJbPDRX09LMyhqnOxDCStoEOhrFgFAt27IfvMIwdb0DP1/Bj2BxhDHsE 5SlIKEM6qsyGRcmzYyAAmwNEAgJxs1koLJgo8HxArHyZLyDDNrLSCLV9BVQChNqKUzgwXuBRkqCw DfBKFFbq+TR9fDQkKVwDx6Qo7AO8AgXDZOBcISQA89GgZsP42RRsoL04hXOAl2ToW5zCM1D/OTIZ 9WFnkC8JfSMzrwSCakwJiAOIBITMh4gPCMMy+xGB5aGO8kkZ2YQPCE9SwKA6NJzIhvdAUDIQsiHR 1/c58udTsIExB/VoyWeJNnaWV/trbPs5fX+NfMaxvsaaQMZVZ+QZdfic9hMomA/uk2i80JjjKfPn iStJKx6tkIQK5CdbgdC4ojboHESQ1GnZUJ4VigBZ3E99cB7k+BhDvRIQ6g8lHO/I93r60WeVTqoZ IloJP5cLzsV5aErVm66DJpTxNMAjHZD/pQJdAxruf8PskwJNqAnsmXI8wkHrWv0vWtwUjJUCtSpA eHzwZ4cCSuoVOqgPlPAc1NLA20F1PzeFhW0OMCTUBuLLYDuoQGlqmx628pguMqoAhYUhjjDa2Gcp rTH6HuSRrC1AqkBwOjWHbCDHWFmo9ahueMLtiM6TBRICGq4b3gbVQ2iljiXi0fiha5Jmw7D3YItC yAU4aPE4TE3VSG/+jdXm88VWX1I7j0LygM/g8qBqYBzRmKIxRASsJjUbxqM+5YBw3/uHY0pm6arV MngTA2PKykoBeSpA+Fh92ZiyjTmmmZF8+tgcVxhTFl8BmCf4oB8wE9W+DNdK6Jjith5t7Nw5MawD lNKEAZhBH7t3jjGrc60b1zy3PmjU56hCyNhJgR3QOCLco3EsBAfMBPoP2BwW6/SWY9j05aPFug0b /CggmpoY+dHag98NmYu7F+1YjvlsGlU+U9pnpn6Z/DHaM14jIz/a9TK2YeRHaz/a9bJTaGOJDC0J xM2Qi9LL/3ltAQ0h4XMArTRYZsDLiGOE/Bv5Ex9+IuQThpXXQtkOfAz+Ye7gd5ANpKOoEhI7xi6l iTlgOzFL6loUezSfvk5DR2n+MQ3qZjhdtuH9vZ+XAjyiaO2zNtAgg04YEs6H4VL72eo2L+eG8Ihh R9W1qV6/HsPOPpiPfbC/bBNYmbX/Pe9sK28IktNY+6FZPxsPJsUy73qi+jV52rkPoe3li7GoD6wO eA0xdt8z63OdKM29XqiOmh4y8FCBr53BpuzsRfMxeZdcJ2QnlEShrKulv1zOZMdEIeDVNuU5nU9x nhjevYQHHf8R6no35jllgl3wOmQiK6gvV2avHatvq/1UFxiY99F504HQ+KD5ZSqdR/WojOohsYJJ qDY/AAeqgf8BLOEKPK4zahQFdAAIQhW2CogxoViC0kaoXIsZYMsxTQzJtACypeebIDcCmgmE+oXb Bx85Oo/0kaLzSA4jj2IU6o8CNFaMwn0EmkHy0cBjyDhGPsVIIPhxy+K/95/llezGxxWNAUoPn73g QWMs9NMLHjQWI2EEPwdhRRGwMhwjjZLstmP5KernSzGil/4pRiggZzhGAJ8Hxur7azDyEPrzBWwg jJRyf4qRSFYaRhDmkM8yJmRLlFygcg3EOVtsH9A2IBuMBGjZjjlCDeJsMTtqrS1mjbliCDdzgFYA IeygfDk9F4ccxWcjehnVozaI8DrUHhFqi/OawKM2vEDfBIcwd/7XcQg6wPBQr5kPcjxNAIYPL0C+ FsiOhTZXpcF4MRwamFWYNVcx4hD3Heiamo5GifEiP3rVVTYB+c1IOMTPQThUGgGHMF/Uj4UF1NGX 4vDh75+HQ4gBdmP1/TU4LAO9rcFQ3kCW7BiWBzkaWzz5AqMJJAQ0Gg494JgcthrbC8gjwV2qLWDS GdYeDpgVlJdBeR98bOAoarEN2w0oROOhAoRjjB94eXoZHVNk4FGbaUBz6XWoLaLJ9DIuQwrKiNCx cUyCESD9f8Ek7kcsNLUwnzNivMinfHpHxyR+DsKk8giYhPnJbyxcoK6+FJNW9z8PkxAPGsbq+2sw KQNGcgAsIky2wNw4HJOBbDRMysD1jYbJcDi2HlBoi5EwfWwPzIOWcD/gABxC4T7AlxZwNlDrCi1W AW8NsyYJPqjeDtpug1bbAcHyVFzieMSxRwb5OO4QDhFmGevwdvh5OFYloR0fEH4uyhFmpwKhc5SA 8GPoHEY8o3rUD8p5gb5kvjVlhbUC0FjrXsb7R0Z+NoXWH3SJKQCP7I58l3GvEvGKrCu1st+80Bqt PaNMRn609sPX4c9/XquVnVU+qvwR2x+oIbb9sqYvk8/E9ow2ZORHsydjG0Z+tPYj2hPszw4+gPwP JeTPANGBXJReJmqvAPcBcOUvWn9lD1t/pSIBkIhYf+HxiYXWBfZe4TAHwgylpnTU+yD8HBTr548Q 62EN5DhWvEVdfWmsp+R9GutRjBjhPujnsfr+mlhfB3rHQjxv4cSw34FUYA+TPjTokrCNQGSgGUCj xXofOGYAsdoSIrgTxPjtA1GeBPdHthDLUcRH0V0TyBJKtHWZMpxHYiBp4AXpZRV6jupQXJ4KJAuE ynz0HNWTgPiA0LEpQCQg1AYRKisA/ZN4ja6VAjRWvB4RnxDv/uv4BB3QGKIYwQeEp7HWYt8Sn7hP sdAVs7i7kAv5lx1X+qj4xM9B+FwwAj5hPdQ4FkZQV1+Kz/dFn+KTAnKG4xNiw76x+v4afFogvdng ORTgksSOYW6QM+LTB44jfEKTUfG5Ho6hu6Ht2AEWEvCCQCgfxwUYAdL/F1z4gC5oLHFckERKedC4 Pnw++v4dfg7ChcoIuIB7lICxfBPEfzEuuB9/Hi4Ak01j9f01uCgEvecDHhAuTsK8NRwXaF5DthQA Gm3ecoFjawAZaEdgO8xQJNiNs4R7j330WWzo7CXPKQvtScOIH8pTgNA8QwKSBkJ1KMdxNhV4dC6q 46PnqA0J6JtiENa+//W5CXT42rnpKAsYDhIRa0fcb+hdYGuWivMiHyK9rhh17w4/B2Hw+xEwCPOD 81g4QNfypXNT4NPPwyDg//BYfX8NBt+D3lvYMMwLMCgEGMyAnHFuQnZDGBQBGg2DP8ExOerctA0w uBPbD98kQOBO6hoS7aNbUncPHKGWNoeRqOtJElbGjzCE40gMeBLQJCCcR7jjo9cpQ04CQsf4gEhA jHVT6HW4PFRGskhAfEDjOAUjQPqSufIoC+0cInCK+xa9C8wldSEX8rNXY6wh8XMQTheOgFOYr1rG wgq6mi/Fqcqfn4dTiBEuY/X9NTi1Ar2FAZ8IpxEj4LQYQItwCtPpqDhdD8fsYKZE8yMJeBxjiB/H BhgB0v8XbODjiWNDDtaRaGwpf42+jsTPQdhYNAI2YB4JGss/0fV/KTbWlH0eNgCXrWP1/TXYsAO9 4+jYmAb4GD6HmcH8hrABTUbFxkY4tgNmJfSESR7QwQdlNHfg8weaU6YA/ROcfM47XYx7iYz8bMrg PqEC8DKggxDQ8H1j7BqLtt8En1H3URllMvKjyR++LxJSzKY9TeHAqPJHbF9/mGntGXVm5EfTn7EN Iz9a+xH1h+tlZ7C/JNidGwjPRellovZpcZt/7VqbyH1aHFssYAuULCA+IZzptY0ep/BzUJxSHSFO wTzqPlasQP18aZxyqfg0TmWC0sP3gSBGBo/V99fEqaOg91JwIAEI5D/zYJgJ5IxrbXRdZKCJQKOt ta3g2EjP4kjYTDY+OKYCJA1EAuIDEgRCdSQgVI/iGFpT/5M4hnSiAH3JfirVhyEO/NdxBDr8f8YR mJU69jiOhDpf8CA/WHPegHe0903wcxCOyCPgCObcj2P5Mjr/S3FEqfoURxSQMxxHgGGPsfr+GhzZ QX8IR5sBPxjg6AzkI+HoP8336+C5BnrWge5aZUEUwgcihBkSncZxAoaANNa6+M9v+FwQ6YJiJI4T vjLafKMEePkcnCweAScQ84+N5auozy/FyY+1n4cTwGj7WH1/DU7WIzsBPtwAHyKQXxyGk3twXBe1 ARptvlkDxzTh/Q50X/5PsMCLFklAY80ZjOszRn425fPWvui3SX4XI7UUoL0MdCcENHx9jLdhlDna 7wkl4TcqvCADJW4KO8c0uHhuIPTbGNzvaEdp36guYI2h7qQJMxBMJunraa2F1vnAn+RGQah3dXEE ZCyOa3WXYYlFon9Dgd1a00ATw66HTOyx5IAyj53eJkd4H+UPRCw5tvFW8MDWW19Lc72L+bvyQw6i eRF+lsGpgheO3Qlvn1qdpjK/uy/plutxVd+ywHn7Dspkvn2d4y/it3drbuJmDSHv6JSItqqALYvP shH77/3C/a/O2D9eMVnJh4XXAmMTysQ4g4VcRMQ6+4v+nOwnTq9CR8vuZ3Ybh/tO9sDbKfn4HrJ4 Vc/RJXn6TfGHP34eEKBk5xTrIX9LQsj64geaSKr0V2s5i1xrPr7xaGTv6tad1PlKdfkFLtQh7ei7 ba+ilGJaC99pdZZxpSfxef8Y9ctjtoHO3n9Utttrf8utmjzZsxJksCXK3lpo0SvZ8V5VepiYH+1v dW3rbYk6lK5spN5lkaSQLSFsfZ5BlVRPXtG5wca+iapbTitp/KZUYRLufmA32zOJAyHBC4zcBk3x 0pzTWCNB45nsHYFqE4Eqx6091yXzT5Tk5LTLL8UVx9i6F9gFvHhQcXNeaH2Iblbq4VYR96wKslEj lxl/VbTFao89GyX77/G9WlkfVtkdPmhS317h5HvvWpY2xMalb/RWky2s3XFCwoN9m0C119nuCS0K 2bOrYmZYO1xWX/rShEGnxBO+0sVXJhsnNBwxkS5sn1K9sT+KVGvl/maPlsivWX2nmtPi6m9WejLa xE1YtSW1y6L3/Tz74G1FPI4XhV8+584+RpI1Kjq0+Ptdx/jrJpwNVZvocPqRjsDHuMq0FPVF5sVt nc0//M1CGxwYxWQwRcaV7qdcDYduquZI1p4nB5NDrKy8Out2ZDzdtqWbO9tTK0XfwdBielXCd25Z OymnH2XfsvTrK292v6QoWiKY083gZJl9vKKdpp5JOW4WqUrBqkccRR0MTy95YmoZ7G18vHhmQcis fIMwd8E3ZP1oDrKB3vIdkvPebpnRFJfusWaLcNPsobavcmxLE2/wndLQYalmf7zGxcovhcdx2Z/r bqQGby38pUlkSrW0fqO/Nn/VhqNPwlfYW/bXuyi2/Xqwq8tlC8P1PY/xlY650vS0X6GkOavjtbyl emh10RyJIAu1w3Ixf1VLSdQlyrgaHIskFTuYys97WyHkvaM+kqvtanM6g5Ne02DTVTepuNK/Ib7S 71itf6tCoXCe6syC3ZfVQiwTXmQv3RjrESBnvUPG3qVGz0GK/AtZe++BKM7zU3YaXki+5u2eesLt dolz9u6hgxdf8bS93lug3sXyPDlaaFM0f03gtqjQ6mCLfcadmtqdoVxHrD5Wrj9tql+Uq509VyEv oNgx9gopjhzxZll/ebN5vftKT+9U46Eu1GXmmdS3aOK+864CNT9dPWNmvj1lUbtYkIXK2wfNEc6/ u2wC13jbOP2MfnBncWiUwLK1VSqk0KiL5zUFKn36D0Z2vVa96HWrJCSHUVULb07jkIYGN/NUxT5B 3+DJ2RP5Y7P5pQuasy8WiN3fGFbN/qt+RMVJOefiKte4I04LyRI3FjXd/xA2K6fHcW1AkXSe2E09 tsf+KheQhT9oCGec6Pp7rYZIUsQQzGxcmpjU4Nqcnuuodu2x2kTHrKcbjleeaC5kvyncZrAmMvOj 0e0jSyLkKnTDlzgor3QwZj1WFfzD+tAnRzcdfZK6rL+12alecGWvwxCDfLS2aEtOD66837nDPlFp keXe3zxWHI9UyFnCX7JXPr/1oHaNSIdhkGmVTJiMdcTDaeRJeStiD0TVCHRtCUpaV3yiq83lKkN4 eVucWW/vKZZzpPXBG1GJVY9FNVadPJ13MN/B+rhjxuZG992Xe/bB6jqlUlD3Ustv3doHXzfHvGwq 9ZxaLQ1Wb3rgLpZSl6wtkyLvoDv7tGjxVtMO7wXp3okVwaVDIZQgXlranKrnePCRnuO6mnU3yk5V F82uFU92Ne4MCmhJnVtmdtescIlZ1R/W81I2Z8408FqosNPBmHuT/HmegLIn4SqyD1Y8eZzp0383 sqtXtajt0BC8Ax6eVnYtjhasONK+4XSkUs7k2QU8GytDeEwrw3gswhScBQOLFJwNXb1+qDB7cS/t tlbnWqPG9Lzr3R4dUVqGO8RSTs5MOTf9WBVY/V5Wf05zm6n3jBFGstK1OW3TycqD+icrD0VUr5LU Ol46JZD9Bs+OO9OrN7rf8Yu0fVPwXPtJ1V62E+Sw83ln9A35F+8y0k8kxQX49RdXNpRsYYyoV3ac NRcsPtL0IEtUInCOM6/0goIzJoaXe2zW277dfbms+ciqhVY9W9Mv2RqG33TcvKt8pWuqU8aWhsAW s4AWslHRKyfbVw252oaLK0Hx4B+svp8CHRVv7Slt9qq3ZbT9hgVrklZiMyoi/cjqyfktageOrSez 2Nw+8mJF+F3vlsXnRI0a+/IMwpfElF0/8tz7cZVWrX4Y/wVZAy+vJ4GFcSr6hjcV8q6Q+j17zOsl hshVWuPdcP13azXbiOoOCI2au3SVpl7LluBP3m9M1rSZJVhTrth4M6ZFdEKIRo1XhuHM/KSV4TcV 6h6471w2E6LvjGcfXAQqvYMrVqbFMTikKQdb2x1xEZfsVqkHzemzCsT+8JdQl4gAQyeYSOefalN1 k6p40uzeGuQRcJ8/RHZWMd/+HatuKNTZOMS2ab3duSKsalPoi9wNR/u/Tx8WMr9/FeWXcqPMKmVB QfMfF/N5NvLf2jFfkn9CsY5T+5GXDwX7C63++K1VO8rpzDqvo8LVK8XNei/HRs3avv1R82Fpzb72 DnGGUAfx49n9VffJ0SfWqLwsVQ5kj+NZU7EotkxM0XDPpBNarunHklrzyhe4it/Vq4qe9SC0TOf2 772WHcUd6p8ISZsXbbIpWlcpVMHaOGVR2/apv9zdsi8y+ZxWypIt+xSrF0XL8Vf3srSF+O/+ib5s yYzc6iM3+cnq2KhJMRViT5eGl159HSpX/CLrQWue2F099gqRj8GhVf3BTYzrA4gbAh8OO6olXWpR uwLu1eilXPGwVMu1XGpe36kpr67yb49N1Ujo07QPwtdXLqs4/VvEAlpuNruXLyc7zynqll0Z3ntW vWby5YyJtrTVkG+O9Ssnfwfn9Drz/KZIrVNyGupH+6Y8dMTXQvstfeQyrGLLdI2Ll5gXtuY1zBNM e9W/oG+YGYwtk1RzWhfHqdnyCyoWFgmeUsstEnRdVrH5FLr41x8nHx28+CtKlPCZ+VP3ymsMTPiq v2NGs/K9lHoq/QdWdv4tYbKu+Xm6up42JT2Zx9a9+KPcaUHMo4n9s2s39JkE90/XoF9Br/BRuZXh V0kXuAcWeJTYOUa33cq92+pnpOjQmy0VGrnZsvJtfvWLk78bl8ZrMW63kRxp3EP+x5DVYxfQUqHj 2K9cH3PupUhbUmRXu+rFPsd1Dfn3GmRXf6AM3KE+P+bbtTmk7TcXcw/Fl+3tRs2ZGYFdrfEawV3l 8RWBXU/jY0K68uIlArsa422DurrikwK73sQ76y4Va/vbKEa0rdlIQqTtmJGEeNsvRhKplyYHVi5Z F6TY1L67L6TVqS+z53XnypYT1Yq9dQ+4Ou6peu0qsdbxbKw56LVTNGNxvci56KCul/ESwfk8fVtL Wo3IzRUhK6QfH80Ilsr3ynTuYWk/ZRdAi5YurijQx/a8a3ZX7k/AvNQUZh9I4PVaqjDbTyOw60l8 Asm/pWB5HdfGJnxqgAvrPuyQquTV8UJkS0+1at/bbOkMjeAK4bZ0/fCAGxJ/iXn/6DnLdCvtllr8 EEusR5ichlhOcUh+gt4OnflLbhx2MGbfJKyWsUk+oVLwlNGp2vAKkaSQHRGl2e6eS3KuCrr54pPd d7z7ZrlGG0TXhlV6nlLIFdoLzCHhJ0GKO2ycDcIzyC+7/4pXDOnKCvL22i96JxpNBCTnDt8Pwnb0 yeD5Id875uGOzpa8feFy1j/L3JQ5Jd/5KD7mZQLv/LioiKxL5GryhsbvhOJCq39tNs94LqY1eK91 V+lhno945b5LquaPq1y2PK4qS3rWWdVh2WjdECzYnONitdDfZWG9nFERJ/+fP269YqYovix8Nixa VGcW7q5MSxdb92hiGn73bcHFqZB9k2QSWuEcm7p3iuC2JDnrhTKb7203llkgfUosoDmnp3bumxut 2jXhN9fmigXF3Q4oSFhh1TnP0lykqe2IwOnBu7f9lqS1aiZVyQc8dvVXuVj2vO8Ec6iTN/NaX3n9 9vzx7oobHPa3pYqO3/tzObnv1NXDkXLWk6tttvfUdctlGBoZstXA/H8pqi6tW6EYNgEcRd51sKoO LkzeZlN6r+Ykm9m+jNSd98b3WJX6j1bTq22Uyw4F2cjn604W048tOxSsYhT8Z/FkMfKvrdqNFm+9 8g0i7sY5NLokzCnOKstOnNTetdCzlOHiZTnrbePYXb2mblFTCi3rDasMaL5fJCvx7pcosdLo4Hqw 5uNZ+Q3rOluwNC7X+RUFhx1u+0fa1jXwd009l3SjTKT7RmyukvNPKY+jdG5LFTOuRPt4C78zUQ6u uN+2dndoWWRHzZ7Xb0KEK5e2XTt2VZucra6RvVhHo+lCapF8O4/nJrF9xq6Gx6ULAspvXtarVHiw p2bOQ4GdOS+0/czrOPAVxRJlpSVlPU6iiuml9kdm5RXnuKecmBv9XCVlm2BxtjsM/anVRev/+K1S e0d4rRb5l6bTszIWvLzbntSj69g22dA0rUhOIsDBtq7grBNnYqRC+8X0wtPrj9dakRcU7FzvR70E hYfBd47wpD2cOLBSsrLYn9zZsOlopbdBqLV+o43DHb+Gc1dKRTpvT6necFw6P25/el2UQ8zD0nJF hztbjTn+nAhmUQ5Uv64YtOLCToHafEf2IZsghpxv9l3Kb4abyMsL8gxCKwOEU3JtHJzv/nhaNKMw 7OyS/cfEFG9M3Ny+Wv3XyvvnZPKdAxykmjwexi2SUJM9uufN1t4zG7wWphddJt2IClvNf6Na18pV /L7ezb+SN0TNHq58oq+vm1m1quZO6OqU6saZ5D4h/eDVOqE3d2pJmIk1eZyLjVIOfFnoXNpx/1Jv uCPsJhQqOLNLy0ZGaBpzH6u+WHBTSff0k2vrRYRch938bwqsdOdZuU4AvJz16ay85uxA03vScFtn yZ+9v78q0Mwq50hngEfIaTnYGKtdT77tbXg8cl5xVtSOX+2XXjzF6CZt85WO2Hsogo7yELmecPFs MNFvzL0/J6/1oM7L3Dpt27d3Gy6mu2pUb+xNjXPQVXpmRe6ebR0ZoiI1KS/fMqJG5epTncUvl11g CE3fK8O9FeV0/j7NXaDg1uy5p2Ukgkz39VetlOnU3J+WrBVeG9m1+EpqfsvpObVVT35KmK5QGFFz 2LGa/GD3r78E37H7288c37a8Js12848HW3Ka19qnz8pt/v1i7hn9ouT78kjHS3teP9M1WfTWc26s mnpxf7fTinDFUxsauXU+3lmp9RIs+6o0pVpF6qbsMSTcdXqd3oc5j/ckVM61cvtFEF/Vvr1H6d2z NLtZIbs5XdXCww403pb1zGleirRge/m7rW1lJl6982NF766eFh32442ouWpSBQ1yOo0Wq2b+sPqC ZkTtprOzH4PPTmDw2cRjvqrm95OlpzdnqlruX7X7sKhtoEaiY15zYUfN/liPvAQH9Q9zClbnNMgU HKuO+tFw8ZWDCVMf+68/HbricdQPHL9JvXO5G/9wMEi8miEcX/u0u943jp3c91z2/cyfzswk3zWz Yu8oMRQ85bOxfbW4bdrLLbtjPU7IORuTJdwiqmUKBGqCt6pYJqroRm2+Qrnj+6mKbuZpivOeTzky K1egqqNSLUw0J3X3kmQ1/cWhPfGxHjFTAhsPXM930FVWKHTMj7pYGFGSkucYWdvBKjUYEU0XsLWl /rZlWUnJnByBqnXyLWZ3TaOmVrm9bQgKy4l5ptExzyg4xdtlfeP8VR/OLI6Yl3SzwOCUib1h2A97 oion+gze99u94y1MNCEb+iwuaFbI1dVv+a3g/rnDDg+6p1omzjE5Obtgd5apZeMk751as1vUTGYw bkqnegtt9EwSF1r0ltfB9tkVkkTQ5nsaS/Yq23K0k178Lqb9+IS/Q1g12Sx4TlJWmXBN8I7zU64u jM/ZFOvpefcso5F/EKbJMb2fvG162k7bNPumklUtbvwVB4PMRWfmKy44rDzR0fA3fcd7KU85xcSs L31se8e6XPEDK3XLHbbSy4VUa52uCJVyNQRMMl3yV+Qlv7s6c8XNjm7RDq81Cox+rvZHWVhMyJ7C R/bHd22pmKf0YZniwMIhyNfR/M4EcMI4dthz2SyT1yCXvfiAvf6NKP5dV7PKOKP469atfZcmuG3u IHaTd3AaSyQoFvG0mB3wqIrTlb4/+WMf2Si6fVPjucRtPVc3nCzVEU0zF6lre/edNIPHm7KxnXCr EL0RPbXqnGeoyWpPJUn1dq4Kk5Puy64oJQWpunnu3OZZceRPscGBfpudeeHlokMJ7cLXXd5HfoQu LywoaPgoKlBN6yT91vX0pv2F2gzWOCOUXNJtbGvKX3Uu8iPEascsj1tnyhafti/xNxFoWKn4U9Nd sSMMy4BXksJwwrPMtighW9ncJIV83UnJt3zTmz6Saxh1X8Cma+7SyCL1olAmo14v+9Gq1pSqzsfZ nelDVpjJOpzz2u5d4a9ceSfkri1bYrNUd2GffRb9QQXGViucnCS492bviwt5zZ4ZTU7f34tprQoQ rxvYLLflZ2tvK7rS3Xfn762LTfpdLPGnIL6lOZlPA5ImJxD8WOcsW3tDZj/rrbdzT86MV0AP/jB9 bUOtxGUWB+BZIoWdogI1ckDomSv92XsGFDMwn/la8ARuORsUrrGVsLtxlrBfY7PhkIQyPLIf8jcT BaCMnrOxAzHyOlCeBoTarzdcs4YTHrAZAU9ahGTC3x+FE1zhudpujsEyHKamfFDmJHBrgJSAfIDO LoQvSD9jjRh+HOmO86P/VUDqaegaacy/7hse+o6nb2gBFjoUiOjyIKAA+TOzP0ToOkQmCgXjadwC /8ECvijc+xCQQCxV9n/o/58e/lfL5vZnduJGw0i8TUjMTtThJ1pvH2ZbG8nz+Qb2ZmWVYnKi2pv2 9+WpLCFf3P7+h5mbwN6g6T5CtKUJzUUZk42NxCGxj9EXQYkF5nl//8vMTvHIv58RpDMSywLyMVYp BSYnqr3voQ4ISiywHuQ+zGxzX45H/p1JkM5I7BP0JcV0vWNJSC49UTBmfnCp4N9E2NvHZ7ADArho GxAqpcBsg1P9m1WfAIUZRBLg35eRf2trM3TCZJZ9Eggk1r8pzE2DBmB++IZ44gM7PMgmBCYI34T4 N64y/PqdiR+aVDQjE+XfKRq45gTlxPo3xlz/pgwYgRj/9oFt0IEuiGEI8m/9VcSoi6RK5RDn38Rp TZdMrH8T5d4YMf5NrLWRDxIVv2t0aLozM3qzM5iDqPjN0AXT2TXoJ19E+bcPTV2iHJwY/4YddSLn SzQ3EBS/10CMJTIR5d/pFCK1BtkE+Tf9QSBR7k1Y/CbST9Danqj4jT94HY/fg3iJRNghyL/x+ZIo Bycqfg9ahyCOoPhNkLYDYomK3wMdEMUQ5N9TplAVJsS9kWxi/Bv+8hRNb0KsjWQTFb9xvYmI30g2 Uf6N602EwamyifVvjAgHR3oT498+hPs3Uetvov2EKP8mwq8HZFLvd5i9HXuZ+nyHeu+KOmLm4x3K gOYE+TfI9xnsgwgO4jezN8Cpz3eI0JVRJgH+TX1+ydgHIbyUVOxlpn5ipUiEKDooFD0HJOb5vA8m hfaUiEyszH8hAqmbsZxIpWF9wuzXTw7T3j8hUuujeiCdxHR7k5DO1GfRiCEoEfF+FcGP5+lzAyuz E0EWHiqWG16wYnKivj84tJd/UYng54Do7Vh/pn5AIJiXyOeA/6LRG6KqOMHvLAzp7F9SIHq+/JeY 4ZupSaS9CV+zfTMrMa8jwp8DMk/VIZLW5BhB+Wt/H5eN+Q/8Jk4O5I31+zhWhv7R7+PQ7wAJSZks LITIRULHZX9q2n+5Tbz7mf0Z95NPnWTcJv8lm3gTkMbj4EiDSYuD7c7MTu3t38TeFcxOyEaEzw3e zLY2kudNvN79vb3lTE7fxN7tzs5OzE1g72/gJ/1MNjYS9y3829l5A7OTybfx7/KnTE7fxN7tTsw2 9waTb+PfTNfbrIIBlxn9zPygUEWLsc5E2Nvbm/B5p7/8KbMN/m/17w3/A/6dwdzE4N/M9pINEE++ wfqkl2D/7u5n5mfQ3gTE7/8F/+5nrn9nIINTYyzzlyfIv8fjN9Wjh35R7T3u3wMBlXF9QoB7E+nf NNlDh5dpJaqfjMfvAT8Zj9+fogM523j8HnQRxI2vv0cOQVQ/6S8faiwmlMbj9xj2Ho/fgx72P3B/ Ob7+HvR1ejx5OjjAzOHG4/egjRm58fg91L/G908+2XuhugvVT8bvLwechXF9Mh6/ByPKePwecBEa 87+wPmHq452MwXhCzP7gN9k/eTpsmL+2+G9dn3yj55flZhuY+jErr6DvcQyGLqZy1DhIzPN5b1qM Zaq6A8JosnuZ/0IE9EC43u3Mfv3E6Ru9f1LBdHtXfAt7E/F+lbc38X7SDy9YMTkhABHv3/CCFZPT N3p/EJmH6Ylwe6O3Y52Z+gGB38BPmG5pmkDC7T2u9xALjNt7iDmohXGbjNvkUwt8WkOwn6A/BDsN iBsI/Z9yXCwYhurKgB4CaRvozBan8FD/PzooYgoUDJOBXAjoGmsCGTJqQvzxCActv4uRWpIUri9q /zkyP6fNBArmg+uGDAmXMpDkND7qUxZF6MlBDS8Q+p0eaosI/tTAUmo2jEdtZIGEgPDf9YFYaquZ 8I3LwXluEGQM9UpAeWxgQ3YMs+DEME0ODIN/WLRaoUG0Gt/67u2IEF9ogJ/LBefiPDSlXgddN00o 05PPAI/0QeOUKgDjAITGaTaFphNqrAA8Oh/pPnycNE/aaP21LVKLsb04hXNgzCQpHAP85449LpNx 7LkpHGxHof+fgFj5Ml8M+eF4yTQ9LPNWQu1yP92HNv062Nnf5/qcDdbFfLCrhdvL4e+mBMzxOfud HjqOcgzao3wSp7Ue9XhJOJShPeTU8yHHMn+ag45Dd/CfIYJ8tsF0EKoWUDjY0ZihxCz7SFLYBmzF TWHn6ODHsLdA6HoZ/Y/WK/yvKsAErDHUnTRhxgRgJ+nraa2F3AboLDf4Cvb3qgA0tiyOa3WXYYlF on9Dgd1a0wBG/nrIxB5LDijz2OltcsSw7/5AxJJjG2+FYfxb9bU017uYvztzyKEhd4p2qeWZg1E3 rzoVHXe8Xfp3v3ee44rUtsaPH2WUuM/qbFg3jYdPpvvs3aYPvJy2ab/2HecY7fPX9A7Knx55t996 bp9oOnV6zg/egrczL7AEiTdlaVS2ie4tyfyr6eB9lU2RS4sarr8/lXHL+vkMvrS+X1o6NzWkJbWn WPcldHu6F9s9ev89Ja200t4txj1jekzP9u+XP1WTOtBh15k6d6649bRXVcV3M8p1ffMypxS9uC+z +XTwOjaTbvN2XYv3gm2Up2ryWZ160NQgJ0DWR93Z1RQjT1jFGeErHRVyvNKte6Nr49y9pY5istGY R3TMHNb2XUvn9b0/7R/vW8/S5aLs8mwXqZIHo7T/Vmef9F0ZtxLv9KUrzlq5aHZq/Vn6QragNWFn DPe6HMfiVrvOXb5PKdtTJhz8u7DJd2rU6oj2h+pmO/9K7JWmcNW+nn84zIRfyj1TjX2rEpefSW7m 95T/Y+9L4KFc2/9nzAyTvbKWnRxJkpDMjCaFJEvGvlcqoezZwjgdUZGotMlWyhZKRSFzWiRLVESy JpR9KY4k//ueMRoddM553/f//n+/z//Ot3u7rvu6r+u6l8fjee4nYeVEtbrV/gb5RM5Tu8tHJPI/ HPDhcmE+g2czF/miIJPYeATdlVSoP9GYFvgA7/+qx9/BLlGNeLJ8SFL1gfanuwVc0ZKUXVh0bGHZ pnssi2JaDycVho0+2fbq0ChLPJFNJJ7/9yHCroOnjxfiDJYjV7jvYAtZHLt5Sdwa3isvHxx2slsZ ZQFIMbIDPr7kjE1LVR9cN3aoelWW9fTLciTfZvvyDHJoiDCP/QN/J7tVUbezzS7ezd04gLJHr393 YLFl5SvOzRm14p2ZFY8116CXPAS0Q9whTM/X6/dd6ogevQF70RWIiGjlkV1UdIPbzyxehSmzy0Je RiG5kDWbUjoshfxyyK8Pd33UXCT3Wl9v+QTiqfug6snyY4kK44bfXEO3HlvMFRX2+bapTMSGjE4L AbYrzzKcEsmIOJ9tE/1pgdn4vXpv35wbq6W0PSk7kFsdLhaGWo+S65Tziw0j2rdhfFG2m0qXyogh uiZSJltrgsxF9m9UUybUHRrtCFwstNOo+VpjydhgofTHYH4JhxOl4ZMZFbkKEiVSEW28vmeIyE1u Qdbfrk++rwmyFNnvn9VHfg+4fvn1odROM/GXSTqjnsl7qq2HtQPO5PX2uDKf10hyCCjPVTQflong wlK+9tYE2YrklhxCvg8kd6r6phbeYNHT2CLce/H6Yj6uRZnXWHlZTe6V4lcdJUYcdx86ie3m77hj F9+QXbb7df3zIEoFpe1OVIqmY9l+rj2Xaq6YaVpWH+KQH1FAnkg3TDq1jk/Snp1f4LdNVWaL+XZy Xtl9WAzx4WNNkA2UOIoSGnjUrsopIuuKWjb+IimtuGSsPWBbuOrtzWklgtEvWEPjni0BvMfYIrZ+ eJjKGry4xrXsbkt8w8CM7JV5mgae4hKOcQ62Jd3HuPN2+PWUf6tkelSA50lP6MjhFoj76GvKzLbm 9w8ColjEl8m0yST83si+XhbV5jHjiw+vFnI4LpEcvp0qcgXbNia05PwXUfxrDfF7JwxjQjW8w1OY eZk7LARM2tb8ylQtatBn0LHW2WVfMZZzUMismkdkxZY/1ImnPSo0dusp99+yk+ZajpQeKBuO3XL0 agH66MPERw91B/lCmKoTDPrWUDk3svzi6gksZRTVbZ9xhlcT+0Ij3b3unosKz32f6Hxe1o8D+aW+ clXPJI2OLOG3wD7+49cVW4NXZ7/4dsgJunWpElf0ryVdyMgqlmUtLI7hYg/29SYsXu0v7LTxwp68 4btvgeYZfvxJ0ksF3y81FmI6Yr1ZICI+dAjZRv5mG//qm7uTfz+i4wBrdP/+mMkL2GcaV9i4Q0ss NVv2fDuw/6zBpeghyeaOpFN4Jrlh1pz4bafzwchP50sNjp10FFRtZnEM3Tp8MVFndGR8ifj7dVyR WCnWJ0vEbm4uKq9WRcmNyHOcLi0QOYHkYV2ks0RQUM7vbEAMosiq+ZIyS+kEmCxXuFc6Hhaptv4t 4reSpq5bMipaZ5K65J/5eqD2ZUsdXs2zy9CDizl2XxthcU1xmbPF0i1+wtWNrwatPS5+2W/huKX7 yrLFQBjhYvm7Y7ac3peKLeyz2FcoNRaonsg13JrqYe6LaQ75fe0DYg3xozeLtKMQi2P8Ky2NK+jw MK2OW6bFvZrbTG4YCjwtKNwrUFS+pzDAzDg0ZuD9JQHWEDGxKfmpPEtmebbIwyLjiqRIWZtn5dzb Y8Ztb6Ufi8q0O+Q9dhFz7eTw5vG9Xmq5jR3NvCY7pRV5WKswJe57NSRNuBedkhkZD3xRnmzZKJyT Waqr2BmW2lJbZuN7Tq3UKLTMykLmsfN7k6mVU3kXRz0NyjUkE7SxnSMJ+i0syOQHFp8UOxTNIuKu +r6Rr3mXqhZhZFvrO+BDiBWtLbexkDHuV+MXECm7iVca9lsixhrpS1BMEFr1ZKu7Ws85ncO9nOf9 B26I8/jxt/0adMJMOVkxsyNrO68szzvl4fSp2CkrvYk98Z1Ja0+P+xJa1oyWc4qra9Xu7A1ARgyG 1Bsqq48WFCa/iBmqQ1/j9JYesbI9+oeYXL/W6pNnksPfqHdq+p5Se89y56H4TpY9fKuWXbmX0bWz Id6vwVHe2U/wxZGchLQn0damzf5vim9QsGFGYbLDJW4fVqTWDyQnXD2utcrHhu38WLn/uyMyDwee lEvhta5zW8eabmhIrW9l81f18jZnCxuWT2e/2aLZpVL2h2n/F7s3G51Xc0k+ttU4LCP3bk9uSroN cjlH2BoOuaWiFtqW79pvmr+pTUZdMjlhhursVpB9LBf8+WHSF1uD6195nxw9l6gouKYqzS/WNkr8 lafg07PnkHqhO6WCTHlME+R6tjhv+fLkifY1zjwm57TNJip7n5TcId+p2fX62Cj+Wk592W6zVcxR pX7Zwun1l56Nmx/38P7A63eM43mQn1nm3gh/80+3dVOfZC4VfvTuBO+RPMRmt9vDZhk8Hd1u2RRj qwi/io7JypDIUr/jcZ+Ub3kYZ9yPfjZuahJ0Qi0iySPD0uXZhMtzbekBVyP2B8wK0vmOxhYkRM2U mkSOao5FT1SRQI7pZHUYyalDhsN472R25iHfk2qZfuad+41OEPxaVjFXxabJq23Yd/fR12XkNAHr jGZR1vNRwbVoFuEqq8/Fzz8r8B7J/WZ+w98uY9XJGp4OsUu4l7kid8kELsk9oa1NiEs33PJbE4VC WwU+KrzyOc57wjbMT/fA2ozmfcIfVFn7XjEbDw0uOatWHVGxbmrFJUW3pVxWlPjsu294cy4skwg8 9Zqccs3eNc2t8eGjQv/s/W5vrKNUEz968o1PrlFMvJdyNJ9cdKEscERicKuO7MkQTfszB0V0SRxD cTE1KYSKid3GRoUeA6c9FbleYb0yruWTMW3uWR98P1O0Ot18RV2cdZxWpUYPra3aqa5y1OjTxV1x 7S9kmcY6ZW1dzu9RkZK3rzod6UTKdw68mRtSyReoHCWJUlH8qKVpl/DI/dmyd6+Pa5c/enc1zvxO dmVyOm9IU+ersycxvX7DVU1MpBf8XD2V7dWq5q4vK0Xw2/l1HbVyDMo23A5bbT9Q7BtYJ+6ONhfK x98P228d0fLkt7iGUs/MX2z3iHmqAAoWjNbZK7GP+pseaV1njWDPtbZZsdfMsuTeJzbzQBtZ3rr1 XNkuHMfKHzVnKrq9OiHJl9MVZK77WvuFe+mp+u6wotenzkeq1cWuv++31ZrSLLqEiy0irbJCyfLs yW8E64PXlpjt765UDMw9ezJX+szz45zZr6NeL0nQb9etGLeq/TJm2+HvDZzAaarrEhm2Xz/Mw9z5 sd+ni52Ek6pREWF7TDgrDRorfeuZRveahGQgSeyXL0skeqdkeYu3iOzTq5XvfVtZuOWa4Lomc/7h PboEOXuWC1sb7t+14L+SfaF4oC/sXlyL9UfH0Mevu5Fs9SMXLQsupFe+yfG+F+ZTFnBsLHuy+2zm Sd9RpbyLwA5VJ87vSGvxv/dCj3zP0sWm/XA/JvCcreGensOP82/33mfKjUuyXrXd7/iKsdsOL5hG rZMbvuZ9jrHQih/w5g0pKJSZjA8RPvgmbLtvReZv627llDnqDcU46xVZJWscaHqsK+fld3Y8fO2h 55y5ERUGEagLRTv52NP2v7WscXY+1t1/Tv5i2sqS2sbUFJuMLby/R5oOaIfcyToQf0++t/PEEZul 9RtWpBMQuMbhgKLj2rq+DutStep6Sk29e/zqX/PqDDiFlIvkNH896ZuQQ2AqV6u48db/j/cvbDK3 +kceD8u2yOb89Bqn4WIxrtWds979tk9YuGesXEPjjqwid2eWZW03U1CX9co2aK8+eTzS90mKHWV9 w1RDn+KHmxtjmwR/xav4K58on3Dpa7mwnCMiky/Re4Olz9H8LVM9smYZn6w9rm40LTir7drwdsXB zSY95+48LsEqdMfFbbV61HaiSXCXVnOVvuCpwrFLHRGNH27cYR7Eyqi1//bmxfJi4e69G7oQpwt/ WVnXX/zSatDjrrG3fM7q7kFN6aaIo1o2ZBWSmYsJoXDpZZsJcKUdV5/02pPwxd/Iok/BarW9kpDH rufND9t7NwidY1LxeBXXe811meSrGK3cd7tX5ZiuTD9kJtmUZOD8tcRqR2R45CVk+Zfd7l8uZe8G i3l+mZVpepmpbKQPruz1iFvUw4yaM3mGR7M4rdb7ZzSt3z7mGd8nZ+cVW5MaVsk0siLSyae7nM/1 mihPkg2r+YDp8fDEigItPuRykzCzsRzn41EuhIno6lTOOwEXA3iyM1a6LjLNuGJdblNg7ne7y8J9 4gNPf0PT3nVrTvDrKuAWId8pl2Q6pHDeOeK5lfXIYj6/VUc1Bnw+e5zbtkNexdZFNYVlsNHIRHro zq60sfL4Mv4hHbU3N9R5JISF3Ar9ng+f1Wq32bNhk1Kk3qR85eW62pVlNvIqewdKfXINBTa/c1xb r52snCNY1HvZw21M0clnqFnOIswy74aHG9P7xFuct2KPmixiNV/Lo/ik0Qw7+Jl7SN5O+tD6Mdes 0MfR1eYF2ecL2f16j+/Yvcf2lpGjsXILIRKPVmJhEXJtyIpbUTV8yaW9kmIkE5HXXdr/VigFv6td 2nO9v/igkP2b+6O2T6JquUK1RNeMHGZWGlMa5h4PZz6Vub/AIxavW+trr8N78jeN7isvCpzKDPl7 L3tzjMglNnx78cjpbJRLxwHeUO/gfTX8SdpJO9Kj18Wva0nS6c/YzYFl+YXIyZr9cF3IjZentzDn KB1ODkiX4dlW4rlrMa9X0iN5XBkhJ5eyS7796dNqrFJEyuESQdGknY6JfuFoZsNbJSqtsmjZfc9y ySlA91cBctnIDF5WnzUqEpTonfzFRxKyQl/v0fEVdGJDJlengm5HPKWxpyUwY5cZFn70przkYUph vrJvyO+i9em0hwKsdyxHD3rWbaDgz31MPhbmQQw76tAZUWIe1yaw5oj0Z5m1TFi/uFYsdzYq9hq3 jLIA4USVpNTIeLfYvnRDzWbTYmeze85o67irV5D6QQ6rlXYJJe6U20TylbouvgVrwxrNyemLeLbs bfy2E4mD1nhVf76E7HcHY/M4+VmrkJ2KCetMvLU61vGLKzuyRndnIH9lPpN5kyM/po/I8uCRRxWT qbRiTdewYf6J9MPolwHqp8tvVZ+nNq5DkN1S9lZIaBARo3y37exinofMXEFyejsNc0oz3ptVWUkm DV6r/UPkfMMoX07DV81QrYe6la+cqhWUqge58Rg3JbKMAyt31RvpqHeBrCHrcv6I9+VrwWU4KhRe LeTtu1mbZRbcEn593EE4rLPsxSPJatUeQvbiB4MqlJ2HxbCJYoAVc2zSL4HYdi+m/zBn2/m42mE5 +8j0h5fq2PctikKcrjBz9Fos4Zj+mz0+Yqu6u6PAl5tKVF4xw12vRrHb3j3c6X7rscIHid3Xkt3N 7W+wbuURJ5L0T7/nVw3dyh6575QP2gARIrD8reNwKnbb+DaTiLBba1qOGN4wlKlSu1qa6mdb+UjI PG4bN6HSc9lR1EWNq2r1nPqDaO7wmzcjSx58GpGS24V9nLvBwppDdp9mlX9Bb5dfD/eu3XxCOvde bzx9Pbq+9maJL5EULpXXeoBTfwMnllK67K1jr66vt6EIE6a81r4yl3Ol4nOkSvf+tVt22bOw4BEy dUgplQP77I6xhrxzaL0aLj5o4muKVpUcc+6OzrWpVsjE6ycZITDgYv9mJJ94245+kx339zFJHv19 c9jD1ZTk658pG/CFR5jxruTFQrZ1QUz9p6zN880i38vZN/EqIOOGbstM7D54Wia6a1FioaYfl+q3 i2JPqrsu7xRbZGx8xKfPost3WTebIxM/QX9S5dhSFuwWlrQuf4cWgVEpWYnU14ZTTf6vlSlpy8Wq PMlEF+VRk/qekGXRfQUDAtqI3CqrSaXPtVITZ986iVwf7ECEVDutfd9WxBo4LBNihK0oucNJWhWH qRnJcTn+O7uqYGPbnW9RZB7/kNvEFV7tF96gOoX7KtodBs+PONlLJIqkWmbdnzA0H6mwIBM93RTz RSQp+QSml0Neu7DVTCbiKmxy/nHstijBPG2isiGb+S/jtZTIoxXLthaJiGoTPtYefRBvfgHDx2GL eoWqHbmKydTuv13EklNHCCdq/y5HPELW6phyfG5FUVn27aXrpc+FLybXTBLqhlSOlmFcLquVM839 79LqweDHxks+20dn+IFbcAgdTf0tWRr2v4LkciKaqARiGQB43xnevwOhmIZ6DXAC3WYUyJxBPQcf fHiOPoM6iBEHeSwAbjoGtwyp9xHh/UErABeYmA6wTRhguzsA4C3A7dN14DQ6bD4bBK2gFPUW/QTV iH6EakIXodrRhagOdAGqE52P6kXnoQbQd1FD6NuocXQuagp9C8WOuYXixORSsRxzGwUhjrlDxQrM XRTESkweFXKYfBSEPOYeFWsx91FrMQUoRQAlTCEVKpgilAqmGKUKoIahAPyOwmEeofCYxygC5ilK HfMctRFAHfMSlNWh1mPqUcqYN4D3LUoB04hajWlCrcI0o2QwrSgxTBtKEPMOhQQxxBd0KxWj6BYU xDC6mYoBdBPQqwnVh26kohv9FgXxAd2A6kK/oaIDXQ/sUA/s8RLYpRrYpxLYCdoKD8wG/bAZAN4b hmZn9AW4tU4tR4OYMQ3vvfMAQF74dxNmwAh9QwZ3dc8AZwNPI6ZAfAA4i54H1dRAvdkLUoYACgBk AAS8GwzCUUQ/7WYwSMPxRKdFUnsGKeYOYHjMXfG/vJSMoJ3U+4/VxP5rBytTT9YmLySdaXo5mJuG elA0HETzBXDguNh8dWDogJPrU8PDyfNSUA+In7cWAQ5iT08PD5+fABzov9AR/NSD88GnjOftAPxA 1PwKYGkfOpizA9QBzQQ/CJMsAftHH+BEIszR8mTah1eoHaDX02qn6Wkf8JnFz1hPVT+d9m33Ofkl qB+kSRablgd555b/vX+QBgZa/6nfn5glHywM1ADr6d95gA6YWz718xU/yCfO8NO/WwAdsAD/LPlU 5ml5M/JBB+bm/5P+8BM63+WD0QMDHIBz8U9/Pwl+0nmmfk7955VPbX5+/Y9T69NTf6K/GLXHf/6P Uf8/14IS2veIqPKn62f0h/nwafnzTkDa99EkxKaZYUTXH6Zn5GNhbo7wZ/lg/BFnCL/LJ8+UzUow yUIDUf0/q3w683P53/1P52cQD5Yf2DztW+b0+lkx0/fxTy+fpT+dn175Y0ybf7PsN7d88o+ctDx1 AFKH39z1NAPMuf7QGGAHGN3/QzM/Xf/gF2jmNT8YANCD4eHzuR8MQLAAz1J/dgeo6z/1U/Kzy7/n wAbwPcOYos3X7/vPXPMX0IvRpc9dP//+Nzf99x5M14P9l6b9X6SfaYBGD3Z/MPdh+Gf8VNZ/C//3 lv5bqX/H9Sc865p+zSkDFKGn57r+ZGJQFF5/wt9RZsLgD+dT/y/Ng1OV4ZOwU1P/VL8x+ODyP+en PrkevBD/5CRsfr7+UR/Ehj2Yr//ggf6W+fmBeHCSETiqaz5+6gsY8/ODFx1MTODRmPPxNzXZUF9x maee+mIKPEppnnrqAXZUBebUb4z2IijswJz1U5PwQAgb+E7TTH1xMVSHlg+mvfgFOzBTT62l09MO OJjFz1hPVR+edUann66ktw/O84TvY8F3NGfan1v+93rG9qcma2sB/yz5EzQCanv092Dnlw/Zf5Rf DFug8tPfC5pXf9r5arPk08TT+Gfk+8zT/z/rD095+S7fG3YPjKDgufmnz5eAh5jO2G9O/eeVT23+ B/v/Wb7ZfP6f1r+FQT7sPAiz7f/X5f8t/afPb4QTYGH9x77XU3tHp6edh/JT/ef1/2QtNODP/T+v /P/w+KfPX7q+08rT/TM9/2bZjzb8aPb6a/OfeobujP1n2fdn6w+1A9D88/jnp+sfmAG10Pzz8E+v v2Pz1QP5TQutv9T1Hyx/8/KDFZQqfh75Uz/df1qg8UGY235TP9//qNzz8k+B/RdoP3/9NPu88sH2 H/wv8NObn6/9/0n1P94Thc+Sw18+2AGgHrC+F5S1Avyd58rnerZYlvjz55v/XTR/5TlpLJEZDa+X hQDgs78ggoEbgEwFGaeJSGTXVGJ4zvpfe7aa5f+pZ6t5iCxkqCz87R76WgrEEED9eZ+tXwFq4diA v0csnU6DoTHzNxETkDYEoAfYLgzwOXJRXJmhKG6xQRkuHTxHn67nQUjXE1ZfbCCsXmYorP6bkQeh mxSP7yaV4bpJorjfjCA9HvBhAdQBBABuohCIBtDhdyDeCO7TM/aB3jdA9pefxbcHxMYAcGxjiVgm IkgrAdDHQziQRQ1uJVr0353oMRCzkU4HaKZ4wTsU3CABWWCfZQDotpICaYiFbGsHalUBYPswhoEe I5jm+m2ORkPXG/LR332APmEMdBpYTrcZpKf/LWs5SHMDNKmBv4MYIhAWIC0HQA80L05NQd061KQN v6odNxDDTegb4QL1zUGZDJ0QxHRa4CIECeevb4zz0TfFeekv1GYUbol+Lq5drwF3Xw+Nv6i3UJss +HN6rPhYPQ78GT0VIIMbQBEMFLIeArEQnzI+SG8D/rAeAR8ww7cb8Ln+hM8Rf1DPBX9Azx3vMsN3 HvA5/oQvDu+olwSQAkDvZwXgc/kJ3wsgqxbIbMC7zvAhCAhEwE/40ITDeiyEID02AnmGTwHwnfkJ 3zpCrJ4K4ZzeBsJFvYV8ZE24oxdKaNRLI7DpdxG8FvT7R4KPfjfBX7+HEEj1O1B7JtDHBxaULFMf 0SeqHzEwUxcztFd/amiu7rpjkzqbkbD6RaMegiBpIX92E4RIHwmipC6CBGmhfmcRjpCOE26RdhPe kjYQJhZsU4UwSVpHmCIpEJDGdJ+xARvyGi88tlgI/MZogqAxgrBshq8BKC39E75a/C/GL/AyxhX4 lTN8KYBv9U/4kvCrjeMAzgPQ++kO+Fb+hM8FyHIEMnfjpWf4CIBv2U/4NuAFjZXx/MaKeN4ZPg7A h/wJHyt+isSCnySh8RML+qgN10rKx90jncEdJ5niJBb0kTFOlETCCZF24ASpbcrMjKzZa48ELtlo Um2JUaea9w7gQuqaTF/n9oOFb9cO2jrHzbBY0scmpA/CDe2Ix7kbVeI+GD3DtRhN4jaQ+PGWJEW8 D8kEH0Pajo8gueMTSXvxl0gR+OukIPxVUgo+lXQeoBikb4KyOlBXAWiGAO0HwAPmKEmcsJOEIxBJ XoQWI1fCB6M4gp/RA8IfO14RHHe8JTw3rCGsMywmXDVIIEgZuBGy9L0IefpEgrW+NAGnz0YQ0f+A R+kP4RfpV+A/69Xhv+jdxPfrFeOH9M7j+8Ba06cXBNIRoGwvqHMHNNsBrQngAT7UF8Ir6TPhTfSf 4fL0K3FZ+kk4IYNg3GUDJ9xqw124p4Z0OwHXUu21EcQCAJlgMa9FIxBdIN6ywL5L32fgu3FSgA8C JDdRox/ScP+BvmMHgGktgEKAHIC/824cfIcRvhuHJS5iIgJeJQD6vjyzf9ec+en+jSWyouQAr9g0 P+wTY0gM+qqDcCvRRCBRKF4i68xevwgQMegKTTgdvl9Hwbb+Hfs73b5wyDLu46YgD/teCvzzGo1A eDAjEG0gBj/gHUZfPey+iwDfwHVXox6dD7ZBbw8kZ95l/L/uu/brwHdsTETQCSWAf+Y79r/oO2QI L5F9xndsQJ7UNIAJ/uu+UwNzC/pOE8Q03+WTsPsaANSN4/FCxv8J30kA/eEchGsfnIMVYGBQAP7O HERQPLcgEP6z3k+VJdJsC9cPE5NQkKMFxvQqUAplw8BID3wBl57pQN6I3R6wBUEJnLf9/wq9/dF5 +8OoI2N6Pn0ZaRjT89HPpy+a+N2e4sB6WAB6LDSd1wUxEUABAAwzhBgAcDcV3CCmB/h8WhlsYDrQ 8wzzZU4fwbUO+pR7mg9G8FEpbpiYDkYgdgNCIe1zMO7o5TAuhIUggAfvJDYhPBD7ETupf9NCvFCk 7kW0Wtr44AFly7zTXdh/n2IngjREvGaiC6AppuHRIRo9fLILhinUqWw1LMxMuaprwlEvBoyQWKmI +OSe7hLR/vDQIPsqh2Aw0XiYIM8USrL14SHIswghgdS8maUeDtIUQF8N8AGgXxx95LJxqTdxaDKI KgL+V82QBlm6HYEN0ejnioiVvqXe02oihEBee4vOZhmzvWwCII23eOYdIXiO88wEDm4tCEdQNmn+ zJsC7EUvg/5yAOUbhdExC8l2OEQdAjPrPJTJBwD9A+flkuk0bA/mYTkITMbgvwqAQWCBcYBvwEbr wIJE7zMkAsWItQC8ANsBGAP9OsoXFGogXBFe4J8LYg/iIMBuhDNCDHDsBzmY0kCYgf8JALT1QhTE i6fBCWIhAJHpGKYh2AEgHayn18E0HJtrALgAhAFg2QoASA/SZJnpNNRDYjoN+8qYhmvgdgAiwEJr 4P+fg391DiIQEWCeDKt9PJTILj5BHzdIYF8Y7KWbF8ExZN/Zwgp9MdccpPPAOagF5iCdhz4Hm9ai vy40D6CcvzsHT4n8eQ4SQTs/zkEw/39bSPa/MgfhPJwCcw/OQQnmP8/BJWAgrwU00JZwzDIGaEsY DEGhBoKZOjf+yVxwBPzWAP9kLjCeUcFKRFCEQDvcACBQz/pYwqQC+oWZ2aN2gQp2AKgPnMsQYJ7N e11G1wfS09NYwGAK8goAcN2SQyMQksB2iiAGWUSPXalGj53A5lW7IGC6VIPOC6996WlASmbowyaQ nw7ff58B5p+1jsC1wxwA+gLaS4T4/VyOv7WXg2sLNHFmPZ6xjzhoF+hHXQNh/B/dy0EfoH7QH9wA 9PDf28vB/RTQCeAjhEuVIiLa94qLGNsUCqb3gzTsn8wzNaw9ZYq9yPvKnHs5fb7AdUQbrCP1mUnw Tx4zeznYT88tNJehjL+7jlRI/HkdgePjx3UErGGTC8n+V9aRTCDPCox/ZYA8MAlcQQx9Sw8HQWIt ADcA7BtjoK0iU1PQwDJgH3cEO7cnQgzhAGIP6n7uBVKuYDdfObNviwBauPcKTcf0vXrpdBksX8xQ B+lhnj73AO9f3qvPA6YIgIXWJ8Zrasb0fHPyx/N3dqf5bsm9mT7rep9xbfsn5+/Q25x9/g4Hir5+ wN+D4VinB7L1hDYEzFNjmwBt1SvjOojpmByK30qlocfWAVsRSBhCwDk6HH/pHB16nxjtMp+eP56j 0ygJ5hEA7DeS3mmGGJb9+RwdpkZQHE09R2dw0HUYZP72OTqS2vRzdBadc7DaEXqpTVzWsQ2FcXfk NTbM2WR44dOxL1NTMV25ztnH+Zs9ByqTbnn84X/D3OLsBeW+hjc9BQXvthQGdG3kNUT+z/jJ58M8 UHgQTeq2DOIs5prV5/xtGP2QA+qvg2UTmRh/NENIyICedl4rjDHx+4+IZchqe/XPQ2F8daK234uN W4d46pk+rOHU0U970xWMT5k8ZsLIZYQMmRAP7vtWzSgh+waF/XbAxcmUoUghUq5xYXBT3bcNk18Z SWQHpVmFWBvtRFo64rvdmn+3ag06bZdnZ8wo2YjVq7Vp223Um4QIVzcDbxkuMlvzuS8cE96M/W42 DimiNG2aWNVe0EwKGT5cSJm8VnywOJ81lUz/oaTwnA855Iq8EDI6EOHqZYApwwzoTu6dVGPskFkS hc/NNWTU7KnBjh6fpxPGxRsNH6CbKUU3VpjtZClexGDaEM+VbvLVnPZdo2Ml67d+nkC16rZy1Izx Le3ySuhZ39e1g2Hs+C7FjCLW94nqXEWVkdcpCOc87xuImngtyw3aPnyZ6BNzMGRCz6WN34SBR9Uk hJDI8ZX57ipHs3pO6+AD+HNf/DMaE6zi7U4PsDYTA0P7G3ZJ+CZ8WT7WzugM+XTKMjeW26tcWCJO O6Ge8+ZM2RcaTO6EnOS4KLbUusfLUweqD7wM3GH1xxNGG+qb2BvcarLa6p8sXJ1FnlR6sLZ7+Q2P 4INID/WsX8f4vC55JXyx+kHWNUq8w6UzfmlmBdcaQvqIo6KRUUnqB85OoN7hg5mbyJNGZavd7CpE gsQZDbebV1XqDbN/nlEfawNxdH1Cj1X7XdN+rnBUK2W9aMvp/ojFvdWBpZ9iLLLzxooDrjM7JbJ8 IotUo/yJXHHvQnZv+LRTvf+UQwDbXeReiuB55qwp35oEfF3e0wM3Gqs8feVFl37o1xnbYKmrvzZa tCdYA7B9QBKobZwPaN1JGa8W/ST07JCrqA5QlDmneMQ6WO2gc0dQPOrwyFri+oQrvzR5//rMKOCZ 0csm/o4/vk3ZiVyVdkqe6UOmX2vNiYjN45/644NPOlySush36pPjL7WcjsE++NF9VZ+72mPLJvBa yLaQfouXlz+uCLDU/fKr0JTk0MYltF7QNOkM2f37RD/Cf4DLa9utpuunPvEtiXFqFQxnvobsLfbN KhbKM27ORjwf0Sl0fsnxGDVCDJQ+V2Gpq3gF59zp/E4YMTa6x+q6ZWoozTBAQ7dwllHbHJeQcVvb ovGuyzEuqAd3IqUmG24fkQsZnXCfsiPU2UVZyQ6MmCPiapYTubxOe4m+tIwRbNJttRFvzNt4sPd2 zXdTmY9QbAUGxL4NUgJPOuBWSym/ycrhUD1tjXqJUCZPrq/6XOSu2zFJWV8l+bmzPTYRp7M+MeF1 TLzXPn8djGvrWyMUg65C/SFF/A7CFaIilKpol40c4Zi7Ogk6SfuR4mf1J7ayHEBMTFR9zoNmC3Gl 4Ko5cq5fLxBNzryxYpJ7D6eR6SDzg9XKVKPR/EhpE6m/v/UjUR01EKZTWHXBpY4vZkX9NRs0mdNx qsn3/7B3HWBNJV07IfS+uLgWmmsAFRUVBelRLEQEFASkCSpKh6hAqJIoih2kiIgUFUVUykqVGivi iiBIkRTiIiBiAkiJGMo/F4mE3dXn+3ZDns/nZ+BkJvfeOffMO2fOlHszh9md3CUwXgezYcoD7Xvh g9a1Yu+qZ7cie19ceXYnIUsh6ZgupWypqplI3iTXQf8Uh1wfhWT4J8qjIEeK55i21d3SV1nGvxpr CwoNSLkgmvSDM0PngErp+A2lgSvT6Dw8r5p2+kCUv9Vf5MsXcNt5r98v/ONcnECJs3nr/pOMqtpB d0Wipsw9XiKyAeWDmk8Yrej4/LLw+ke9CMXe9tb8FG2BxV39UTjsjYupFfNhBWxVUYNg6qBc7lmO XFXcJicpgVMeolPJ8GEvAtOsUp2m0L8PUZV7OtIRUU8YiNg8Yq5Cv+avc1JDvoCPnJvdr0lOJefG p9an8qyV9ErHf9WWFIF83XGmDxQxu7CpS8V+u6hI0ZAgxZnk42n9bgL5iGb5J3v1XR+H/KyQ9Cgh gniErpeWcDTBmi+5KkaagPiDUmYXc/OYDatp1SCM5BRy7W4ffim1Nuvo0vfWRQTG0l4Tb2xHQ68n 6Ul5o0m+ZtNTeAWS6LpgQYbJLdma0c7C7mTbA/KSLw6Jo4vUVmVnHjH9Qyw4DddjQyi8zs/WbJu6 4euf28jWIjpcu+x5upP8Gx+HaYiQ4rbkNzomvJoXCardo2Skz5IkENYnk1Ss0fmiP8rj+geqWLAA oVyTYmIxh0GLE5mVt03kq1I6tuMzYGor9BIUCl65mf3y84vAoiw9SpnPXXtmHvqWc8qIautvNnAM QdtVo6aqI4VRXBD36jzeOjIaFL4M3oNaO0JZ3B5gy2aa3uFH5AwjXyOqKNsj8ynClJyQxdbbCi/4 OCzDlPvdTaw6j85nvnkqTETnwj+EhmSGzi/IO6hfjW62t93KQ5473zDCX+lij26JfGxsT7A33tvG ZJFCyezSlgvzJhEOdCwXkHIaRKn9siwvQ8P5vWFp42zphjI6ilGVe8HO/K5xoGyTuNPYHpKVCgNB 0Qm94OPs4egQaW71QKAEXWaO+guqPM9thFYFpVRu/P2Djn0tvUz1en5cfwzzPZ6ZEUWTOZcqFuZ0 KT8SSUStRok5jn28d3jNuKF82OeMxsrO39nhq9x7ox7ZY/wx8Vf4nzRWF3XC+vbxeNfOjES+vIy4 V0GuDlvEd+xfuVsd17LDvdJWkYjDOCY8jCD4mdEUa0YH/EssqfN7+F8ggL7mPIyJb5TtMXmfWN+D x9iYBsLb/wyD4Br37MrHv5sZqVITHxXTjQLmMZQ7TUwZxnBGHpJIOGBjGOWGqMN3tZwpiFsS0WeX Mt9Qwj/tcepR7BOB2hb7N9qwF3ATheB03EEjMVbnAoDObkGExa+puZPIJ1umVhSPl04lbz31+35M inYCwftW3ttL0Z6OWpEj3a20689adbBCRejfnamJrkq+G4PtpSXOMPa8P/kXza2S87iRo9Aj2/Pi XfvSxVuDhHTJA5L7bIwyP/e8XQZk9VFg6j8hGsVWRMC7i1Y756/Su93aJRwAI0+xoR/6UBKr7+3s dH7//l27bk1pvc0D+LMXxQGhOj7xoQWRHqCwH6rH2aj4M3KL8+NfPSpeXgUvQ1BlKJfrw3svTpVr EMVTJWfXkE/J/Vh7sPaKti65NC8MEWMlRkpDEocdh3GPhkyvvUu7ksX/kwtmc8zryzS9s04ZzkFC uWOHgunXhcOy8FjvNZ3hKl2DWxSCMz67BbSM+a+tZxM5JShF4NI9w86E+11lMcLkM7PDVDs7MjMU jUpJOa6KRosZn3yymN0xTglKvocJcz0WCiubdBUNekSS1M4idYlwL8dA/uaRUcWeG1VOndv2SXXj sBc6nB6gyU6vW+i320LG9kaUsBUJxUCtf47z5+spmltCN1rQuf9qJbNDIc4ghrd4TZuJqsZujLjp Lj5M8iUP7/uD7kCjB7yxlrDhyEfaaiVq5FTV+nRHiobd59EOjcO3wgMnm5zvgjdmKXMVuk8L56gq orH5R2a9fXDRdRn6mfGnhBjmLXFTOQRpGGan6XF/8F6UZ/N6nufwd3vxQSq9mZVYhxvRs2OE35aN 3A02XPZq/ddRCOham/f3BCade8R8uCiwpLOrfYUi+afODqW2/dtNzOi3+ehzXQ4d7DO61qRrGrLq 1KKkl0tEpZSTWhDEjq35+LfizWNr6ERzeJ9uhpJvCbUhuLvMpYKhX+5vqPvK4OtNLi5TuiMizCyL 8RBwOOLldyU1LywmARO3Eu+qkr6Qp87y441WOAPGkPKI9or26IhE6jelVeu7iBvu+vU1BUHUSVN+ Y0slS1gPzm1Rk2SMtvFteH91+VeTjJKt0yGKUuJ+rm2p8imUSU1NTohJ0CTLpCDbTGyFwpXnNh1Q IyT6BKm8vrFYN9v4jMPuhBP6AsifFAWQQ9Eo+0Y9osI9n7WrqKR1zPKKDrtbcyO7+TBmAzY5AS2U ch0Be/tXG78W5J3cRb54X59DZFG5dybuaFrb8TVBtmh108Fe3AAVKSvTQ6/VoR9gBIzJrooNU4+y vivmcchiXZ1Wpbr+WisZuwDJIaumTUszd0hG3PAfdUK16litHtZcUGfYEJhfLUbKuRBtLUVZR2LE daTcPl00WfFkhBqsmlfTxjjKp7EhKpXUf7DO8sGbytv8dHNx9MG8yN7Q3PO8+Z2JQh7Auusa5TIo 5RpDSbLPSNrnajpo8uSblm7XJ4aM1JU6KxCYqG4UNrBIaF/ncYWbIytOUdU9FXP0vD7FiJ/RSg9T O5GjR3/xuDW9YwgriFGVjdqqgp5NhBEvS5K35P90qp1hHk0rdQxxu11JWbxIz3vsxKY8MxVWZxZB w+fl+ODpqSSsCClkSaWNCjrfkIe4+k65/OMVBzPXnvh8crjzdbtb6kP1Us3he7B1rgtf1+XoIt6N zZUv3xF+ZIhicFHPu8Vnjq+ZMotnYEqQo98Fes79Q7kJhLDsBYs1Si7mR8kkhS3rbKVorX2tYbLL 4kEpL8maSNFA1xYkWko9uQsj9tfBiILnY2my+RG017MLQ15+li/4OuLAEOUKg6h6qbFItYJD2w66 egZ5Kl7xnt/U7nbtgboYPe/sW6nKwaW9L0bClVr0QgOEzxTdPD2Z+abA/pMaGUroe51tdE/F+Mqq 9kqZy5fP8juZoR16D/8WxtxGpYt4vRckaMUiOwfvxIZtws6jxEXRGl0UfyoM6ZX//AdjKHDThFYR 9un01BBKc7ffjYC/dcMfjcqLRfblu6ugu4nioEHURTyUFrFaLpvPvEwzsDXMRwV1t5ZRl/cdMXf2 bYCmIUBNevzl1gpgnM2EhjXni/nHCjHmYRr9ooqoSreJh7at6ss/+bnr4PxL5KwrsRuoh0t+yRs7 z9RunMiLsZfzN6S+sKzMexjlew0Zjc4PLFCLdcqIRZ72fNd474JTkGoks6QtfQV7myNcEPjMtw0m I7dVnlGbGlV04GO7FH0vPkFRo9+rI9tJFtFkVZBlDBV2t1fpihC7CJYuF8pL6KzGhK6ixsv2+Wqh n8D1zjLdx9RVSEySZzN6/15YXGCB5rFL9ztshQpU7zIDzg8V92PTWbr7m64CRoR0WsRnOOLNb2N7 exjd3Q4sFId0FDAa1NFm/3L5i8/XEpCk5/rPP9Be+0SZa2xx+9gXb7es3mziWpycv5GEIImnQIjR Q7AtExxpfp/FukUZuEUyjGSkS9IP3eW3V4IRUo4ZjnjZkvW19rMbETxYON0jfvhzoepeuHVg9G+4 eLOouSQj8y2H1ZOqRb3SYj79SmL+2h8QyLIchJAgFFWPp1BWxL9FVXisro9x++sU7nIdQkKI5CAT mWhNSo55iUOSrGlJR6OTzzHL1rwnXivTPpVH795cfzR6rtjTpfTkc1uehZwzju4Y3pcVslzDzL5x 05JQ+VE91riBFCFwjrw6oO60tzicft2atLS88zZZLeOtcutvZZ4frVrLHCL2HN1GVr/nDD9HCNFX VR9rZQN4JSh9XBjzNhhS6HmZeX0ujD7IAKatx0ndhN7ZNuoR/KL0NOYjj+5sQghev12E1FJcjmW1 Uu9uPNCAFyclrh1e/T782lp9wzg+8uyeRafnznWoijdYv+eFwsHZ5zeeW7Hsd1nrj4abK+I2v3yz rmf4mGUruW50wPTpL/GKJOnCxvYDWbJJw705K9D3NFEB5xqk8Eyaw9LR8LbuyQnh2icIrATp/oBi z673rfxFna0vTjG2qqSXknyrtK3mtshvfFYFtoRblj5CKpeJqNv1MWF7XunbnN5RsP2TgXGNGJXZ TUnHsw1mO/oJ3gJd9cKM+7jc+Q+P5co/PMWbx5u/ApnxzMeUEKc/5/Efj60fjJztneMsKXRWNQkj jyAZhSu7qzKwT5QV29phirOMDuIOpuelMg4tRB7xewfsze7kvmO0jlpTVkeVWYGQECOBCfiqaKYr alVN1aOoO4Gm7ugnvPvJQYk2tRLbly97VLnu2d4oeunJwQ8bG4GYyeU8FhIDkxNDkwHUkfpLHo0+ CQoXlp9wOLMnTuT0z0Ke+meu2s/NRzZdv33kvqxoD85ACK/pbKi8ybiwsyHFvXWPLqnVfaSlfG/g va4ThDLBcESM67LKV1HdZ5ku+5U/Svgs3CErXZgr2XERLBCs067Wli4s3h48dl3szyMF56MC7j/l 34jlbbrBfLMcFyRW4lxKit+5XnVrFD33wlLjZW9OId5lorHi2/mLGi3Lk9U6k9Z0VI+mrlRDa5zo Dh3luyb3/spXxfcIUMDZr0sg5D30o7Ucl+1syZy1hbpVS8XFfb++KBwjRU/r9QssjMY0CilmaV1H ppQKFA5tujD7TY0/Je3CisOKKi1d6y+D9Sq6zNXhFUmhlalBIoXOoc3vjnfy945EWKWyD9ODdGF2 jTxgIQpYJ0/lSnxlMZzef5CRqr2Xp+tVlEfKh/BFePrzjhdml5t3HaSnBnUpPLKMks1Osj9Qdean o/7M3mN72Oar2W1wm01uL/XWw5t3dJMz+wrqynUTtj0YemCwH1P+TIauK8QQLXRdnVVjb2vksrX6 Jkp8e20uxaq8rmnUBs3YRd3lXmvaXVMrbaVhonEK4HJsCi7PdSQJu3g8HYsLol4dwFn7RyOiu5MN KEX9/MvJxf3tvxJKG2zurslz8tTDHqMbIcm2afuYi5uSXBrLrlxXyYxfeVCxnfa7RTr7ckx2Ozyl aDbO+OX69fvoflG05uLETmR8eeIoTevKW9fgc83lpfn7PrrhgmiS+5Ti3kq22SqSw3kYNtGHR6I3 jdRt0ticSdgj5a1ftnMp2+JHg45kdiZOzElt69E9lWLZ9sx8V8XdH2XJUjIXgAW+49NBQNKQPnYk UYyzh8Kr8lifDsm2eT7OK8V/G3Pv9/E+K98MLaXi3x++Xi+GX3xhyabewbaN12a7TarI0gBYdubj OzTcYHgvEFuYmBcb5qPdV9CZ6XiiwmxMfdlL3/VCu1flxXg9JGQNZlW37ULQte6lZh7OijYKrDV2 MD7mNSqKcTNl1DYRSnWbB5Aex8A638CW27sO+B7yueY4e+qEiw6nFs0+6YdKgM/fioTndxJvxIYd jZrL95TySy1NTxyTHsp0w2kjy/kprmDowXMo8u45ked7Lh+O/HgZjZ39dkePSVRpjAtj6JwmX0JD ZL9om+lcnE9m7h7+M9mWFx+xzUdQEh5BON5iS4WElbXSua4LF9ykZSAJfoEF0V76Z5mfh2ml85Ue 3n/zh1Vx6fXUhBitWRtro8nrgvLvLcpO5B9JfS17tyvWUoP3xrvHsX+aS3XDYdqRsjU3HLTT1bON sbyeld2bFV/zg5pBd/uZFkjYdx5eSRWvxPaYqGJpHZScOR1ror1unHSycxDoLilfbRhywUW5qv3U aox9Vu6e426CW7ef1g/Y+aelBVgmogmlflKdtlA2131+pZQHw4fpdiP6+dWPa6gUrQ3xB/AdHzr5 j+fwyzkqXbnB0Fo4rOVvVdOuWWqqnXDa7Wri6uIxzWsOrrvDfj6ePXVtSRe2VVUal9hwHtl8x0u5 vh3nZJr/+uAuW/TnD57NSc405C+yAmsRdIMo+uETUbdPipMrlMjDmsdz587JrDFWeTrPX+BRF2qA olc7i0a5nKySYbevbYvKppSIm7+0//lOqNuCfHYC2XgPKaASom8chx2aDQNb1Gf1CQY32qBXJaby MGZLlH9u9U70iV6OIMtvOoBZWWNc7RtOv+RfbRm2P1Ir2Xnxy/Zq/VJnwZuZVtYrDdbw3ph6E6Ic LDVOuFDcMXq/msfRo+dx6suQBPV0v8D8ufBPq5dUqmdXSUYkIOiSI0lJdCMlcu4RWHXucd6SaH9G 50J0fhx/erRbmrL2w1dB1dsIWt+/hdVTpZc3atc/+FlHHIy3tyLRd2Wbyj5TaDC/8tILqWDJaMe7 TCr5l8bnUZ6O2ul+8pp164p3ufoaOJ6ac1RlxZR2gLkoYJhdt0qKYHLV+Fbi7CjCoBmYyLRs7R5c SS3N4xm9qEnOPRS5NlovrTR1vQZao9I3X49u/9Mlp2IJszRf3ppMXQOj0Bfvjt+02jXn4RStlwF2 SMtRzC7ayTz33DbpXOfKQdF8MORT1ePH8DfFmRTdk0LqKhnzB7qmSPiozUXWiK0InRP7MEa2hLn/ KSUn0anYa9kzjwpQtUlX7Fwfi9ZLXrw6byE/sBuPr7LbjTsBCo72cO3IkdU7T28oPurnudD6iOeT nQiiBh8J3tNI7xT3KfeuSUyd78hfFO3XgdrXcAfRFL/+wV6cZnWiIlE6P9pFFe8X/j5+5Ypwtok9 Tg6s/kGGVPZpkmJz6bG3Kq1711r510FdU/XKtGJlcm5ADX1dkFD66gwFFPYJvxLthfBg0anECpxn UnGsB4LY+TgT2JfiUU2EwSNByq3JBfMUAfE+mGSppczx5/inWxU6T/qZ5iGIWDgpiMCU0SXnlfK+ y6QporCeK+G38F026Dw8bWl2fB6Y9jGDK/rFB8rG8aAcDt7O3lg/9EI8Cb6whO2hqa/XvNyfbuzg kSOQm5WP1caRvR2CAiuXdu4fEjXfGOVn1XPDE8nn0uikfW3s7pLVAkgVD2DJcvhHAq9LG0A94O6p PaBCYMYSR+VKccc6rahb6YP2PAzQaeTGwapcV6aXknPPpsJ6L3k49zskbnoAr/JYbnOpu/BVivwh UOwyO99b7Iu1QTqwDVkWUh8uOaVtnv/UxOLpLm2ZgEOVg9ejvZp1cHuiXG6cKJF/vK5CESxuB10/ m6pMJKh7qiA7rWdd2v0+CFWckDr/IUN/NL2CTdccswTcAsnRH5L2qyo2X1a+c5sYtPnJnUOt++mh GZ2KyGqjmsSHMZ00pfu7lkT13HExnV85z0P/bEfa5qCGy+X9ymfj15WMtVXruV2ZzRq/9ROkDBtf BXZ6UovSAJRlQTWUOpuDT/ul5tHQF+EOSkcjtdQYl34uGvRVpmVSxXYytogIVfon54g9TYsNy3rc eCfhdG1q+Svt3H2i8qFDhyKm9M/8tfD3rz3bXRn3muG0cDhdl1qKDRSqMX4mCjuEOSBUVLfnQZRM SoJ69PVbxIVgJihODHnR6lHWWpu8Ov/MH63yWVvZn0rsP+kr0DXXkfHiVLG7rNDOaq/qNaVOF3zA 88BmA8NMuPcpZLGlfb1JtZ84evmApzNlrw26oV1bzi0mHl8ytk8kZopor5bc1agsG3p43jaFLK+f mpawS+7zVbid2T5c3MsgI7TGaZclPoiXyEYcljofZnqgxeyuccIWfWT8gVBXReuE7sIB5bNeomBB 7sR99ur5HWErNPih1yBgoD051LDW+PSmY164gvVgVcJV9UrjvHcmDhohTf1+0XbmMP8MUrIrMj6v qsOwZfBD5Nsk/Hvb470HxsxfTkxhweM0gp6EjEizRJyHfLRPXdLLKwmp2tTE1KDOFYow4yBBquwn /kzze/rLkL4WzDp/SvOCyudBOk6Rn9M39ba2lJojpgxqMH2V/fdCceZRdNDcVDtdNTwXoEvQpfAe G9Lm3svCxNS2eLDGEHXY8K7cuQ/LkKObqaG8X5UEzC3nS1xOsOpu76N1dlK2FBUQtHtkQRdwSJ+2 8OcUcjTt9YJKgyha8dDGoaOTD4RxwqQbPB2GRczdz1LJsNUKiXLdoNVCPTm90i+5IGSrSqXnqOVw JvvDVboJHsjY3Ghf5yWuy/NSmoDvEm/SlHldMVZlg36/c57pQ0qi9Ah+8rEqVU+6KdqnevZbJw9H cXOlXvHgDoyiI/l0BU9zyHCLByWfEJIs159mBmc9IMWHb3O8MMfZw+QYXe8+EixuBwkR8O9tCAGB eXXr7/oa3j3X09nSbTAcNbyAXTAvK7wuQfYdPXxxDjLtiEaPHVzmZmZsxaHfKzI9oz7YnuOlEwcu tdxjPQzHCevk8oTjwEB+aWU6VRZHdyTDi48MJj1WPzJoQKxjf/bv5YA3wGmjGVL+iOo8ngbZ7D6Z FN06Q/H4ghDmKeYsdjx1UnnSjmBhWgWyBGYrKj9lJNKyL9xysmgVOxxFCrt2P6MQZf0zC9QISfjB BqXKiuGMT+a3vz6nB9WSyFNxRIOmlKcVxqjQdhR4l1gQgr3wUWASJLj0TeEPfPQkf4EU7Z3VKFtq A5b9Kf6SFT+vBY+oGsJ5/Moyy3lZ0I4LUujOJ85HL7qzv5qYU62KacnLGH4zWV0oviIeW8dgesWI GHvBbhIMFmO8UiifgyUUM/XvTKIILnoO3ozoKI24nT3l6E3CEZ4gfGBXwKnbU167mCLm1Dcy/rdO YfKEh1XtnczdQ3/adQ56aWdys9zv75WrsQG8uWUAXk+FPUIY8qXwG4J9Y19/3St3DzguCgh692cB IOidRe2JGHoXjHXOFqQ9ALEC650z6B21nwCBV9bGr/1yfur+uaK8lnwivFZ8rYhQQHi+t4DEeG8B iuU7wg+RO0hDZMkHXasDmEByGEzwhGRjl0V64jh4Re4/2j/28mqo7DCYIRAyGbxn2gRi1nfAYjyQ QEHOg9Q2QCsA4QDJgHxQgPaPZZ1fBL6z0t/+xfd4Nuj3Ol8SM58zCMwgMIPADAI/LAKsHTF/2AL8 aIJDA4CZwC0EwJazOBy3bjZzH0Foi+AfEoZfFX5EsQHakIJzLozPD7iAxDd3mubCvf/5LYB6n4I2 4Obc3z+X5b/LCbYGV/jvcvwvXA3tmH5zXMc59sGd3gDs5P6trdT/F3D9hgxfPGxwDOovjL5xL84e BjvvXwUqzrmgwFn5/p7bhEeOmxwM3BnuQI4KbnEObIjT3yPE0aMTDmQgJxQcC9wZ7Yx7trjKycCN 3oDlcIZjYANGN0/gOKoTf8ts3BEIJ6X+nlujv5XgnxycDvUG/ka4MF/94riFo4BfVZiEEMXhMMF5 wp8NR8WGvCPhJiWfntQ0qPd33HZxrAwT/rc4jff0T1enQb2nuBnisHqjJmpsuvSbYwrxLUbTot/s AxSwPxgH/1jF+GH1m+eL4zGONswZ+81Si7/G46NvjqLNlfEJ8F/GYaEhdtwYgE+DAWfX7y8bvv21 nv/tkekw4Nwafy8BVbuEg4HdfP9bXL+ZfxoUnBvqDTYSgxwXXuXohF7hmyhx7sQPvH4CrQ9yMICX fLgRxhWcs+uDXJheAmQA1FcVFGCc++MG2sBl7I+7/s2VFT2O18KX5zuQm1EOBY5L+A2G4PGOwjdO /S8fHrclnHt6CdZOcFwqLpcsLqdLI/g9/8GcvtkMP+D0mgsLejM4TyLAnfHE5P3+v6eA8f7/DsFM +WcQmEFgBoEZBCYQ2A7if/vbpCewE19/j7QI8Pveb5PYx+LQb5NYv+GahrhnGniyWM7wZiExGc9g MokFKzWDCQuJyXgGk0ksWKkfHpMJb+ms8nAi/uEx4QQIf+Ixicm4c/s/nf13Xyd5/zs+f5f7R+cd isWGhv5dwf7FsR8dk39R9G9mncCEwcBisd+86B+e4Are5JZ/KN23s3FBboA2pOCcC2OhY2NckHts hEz+NnD/8Mz0yw3U2xeLZYxx7g8q6vTLPTZGJnNewadfbizWwsJqXMc59gF6g+mXG6h3PecVfNrl ZjB8LSwsOAb1F0Zc0W8y2cIeqDjnQgs32iWk3iBYcTBAvcG06wmk3vUWnAMb4sQFvL+o9zjkHPuA RjvTjzdQbwsLe04GqDeYbrkn1JtjWEOMrLBcsN9AvTkqNGDGBbynQ71Bb8CYdj0BgxNOw21hz6bf 5RwOwFRBmIR+sd4cFp0L9nsa1Jsr+o315TDWEDtgwKfbDk6Dev/I+j3teE+LfoMBylc9YY5x8g8y JxBvMLf8MfV7hPPm+0fW79CvejJes5z9gHiPj745rCpcGJ8ABeew0BA7Ltjv6R6fjI2Vc1ZJADdI T6ZjgMKt8Xc9qNp6DgZuzC+nQ8G5N7+0t+fohL6Frb/kuHZP8P6B10+g9UEOhhEI4unud6AhyrjF 5eQKIXgcOv1yQ8vf9i0tY5z74w7ekIJbcRJtaHmQG3iPAMA53uq5oCdfnu8wOBe4oyfQ8x2g3hwO XMB7XLc59/QSKHcoV+wJGIRzGGzAjgt4AwsOFvQ4HLghN4dFHmfHDbln3j+ZrDlu4A0ezXM8cEVu jkvNHXsyBow3p0WfwfuviM5gMoPJXxH465EZPZnB5K8I/PXItOrJJvBbop8BQb8T3mGybZsAHOwO AtKQPyhIFOh8Ljh2E9BG400qciihr/6flqBgMCQ4PwdQNs8dTRCNByi9N91/Q85vtzYsQAn8V9f/ Jzz/k2tUUJN+quRQ/F9lWIDi+5oWRPHzLgISywDikSQQx4WHwSRBjBsnnPZGWIroxtVs+f9N+QVR 4oidgPFWQND9BEDMCjg75maIoO/jsX3Q5rXXhtCwiRh3TMdw/BpWbBdkCINDAQ/7GSWOkwT5eAFt y4aNQWWC6g9U2Xj9QHUEuOqOR39KQ78VUwY0BxB0/XjI3jYeKYJPFp9ZbGnWcUHA1BIcXwvoDwQM ZgH8bR0BfrdugRgq20K9AasnqO0WT1DXLKVcINps/QQF0UUbFg9wHe7veIPsOEjuCdnXgeREwH1N Q7JD+ukIaAcgSD8FURI8KJBeDYhVpyd4wRcoYJ5sYv02jhWD2+izrnuuNjYmjRIfVwAoiwSg/xZL B5AHwgPCEoqhwIphPJOexMbUnn85OfHJwgPKx6oPloysa1nXQMdZmEFplh+3+SAtCagf1DRyJwwG /sflB9F4YJkWUFWwZl3hnc26VKt+3SdW6uC7JKA4FGj7Fl/yQfixAisfqFrYLZSERQVKyIKK+tli CCVnIbROHdB2C2twbhErA4hZeaB7Ca27ZvkE5Qjq39HyezJpgPMWLocBXbNkyWThAoNtBsy/l8/C xd1aw+WktRSg78nxBHXSWmjdZkAXbSB+3yqj0LocmyHUcxsqqsGmAkW1uYUi2sShntpADUgQEAvn QRQM5moDg0H3RAJiBVbZoboJA7oeBnT+e/KHoX61voriBe2Cd1z+FSxGIGbx4gNpKRde62rnzYCg ttQOMG3/Lp5Xwfkw1FNA1ywhGZf+DV9ecCwMtNFBFM7CTA+500zviRWrnDrgHFRefUBzAJFAZZoC QcKBImSBmKWDkM4qAhIFBAKOlYbaNoTLF2wm2y04PKUNLwLXQHkhPpsALVICNhkQ1J5VUF/5wpaA NMQLkgX0MfdANB6g/sZC9uWGnPPnNrBf/y27/x0b/rc82fswQZQkYie461ZA/4kN3+bwedyGQ/H3 bLgaSpJ3Ar8/l1PzSym/9LH/TTkXoBCsOoEJonj5LgPwIgFBckNY/zlAx05uM9ksJjxPGCTF0IYb zMDVZJA+LwjqHCa/ivc5iOCHzDavh2W+kOkEX3id1xmD2vwtQmR4N9AJmBDG0PoQDCb+ECJ4hfdN J1Bp/OgN63b476IlCh1K/d1ig0AJHh4kul/tidwK/hLY0V88BisGx8akfHWeXexi3iq7Xp/RYOj8 6xIbtzwbsyW2B8ou37H1pnwy5WP3F/rDpKltS3rmt24udiq12zhcOUVs6jNhOx5S8LmxKUdRfJd4 4h4MvK4295/iQdU/T/jysQ4j+TE3vkEBq6/eXeHS/qXCH+73eYu7yuVYVo8FSjOUp5z1FRYkZ9Gt 6BJ32Dyi9uwQvuNYnNbsMKelRtE99lxCsH69d1PWNbZLMFi+F+sZv1Rgg518Ud09y3xaRqy6Ndh9 p2Lc+bT66YpEOE31rPeHp+8dy45g3jAbyl2THdjqiuolLHOMLk50kGvpPV9/X6d61ifxtyJkbA7O YSf7ZZbCH+rRPI9VmkaffXpy7o54O75HOjhLYdhS61PJFB+tGDW+5XgvmFbKiG0rrehwUEn1ewZ2 hUSY1Sf+HkYRRWPWA+VJ57cAJ7y7CkbIA/EUTkf5KmgXOMhG7B5gWknuepPwqrjReGtJ1kgCY4i9 CpK24o1Sinmw4R9a5rZodmHlLSnVnuG9KH8pTNL8m1m+0ZcCGd2MyrCPIuls7nNvEqyBXLQkDIKE fydOLNfQs7QK71n2SdxfoCwj4fII7TN7feKdrxAUa8izvAia6X4wpnurXkMj8dlIgN2xHhuDBUNK A+q9h2er9yZsY6/oMzy3X+JszbfgdqesFdKgim6wenpYm+Icci2DJD8nS/JFH6wb3y1OUaJEDBkz 77GDhjWnivpkSdGFSdL5oaHDO0KzdwaLKkBZPPBY41JGe0CLcY1pm0jW6OmHzJaS7exuor3a8PUn oz2c7HwLozHRNsr1/DcQxBYZ77E3e3pX4nQiBAgBclHdup/8jrZJPx213PQxYGThdYF+nFwNAvIV jc8T2F8jSxX3adwitCYSSZIuhHcSBuXPFoz5/x973wHW1NK1GwhdKcLBo1JVioqfBRTEUCIqRYqV plL8hGBBiFISpCUerEflSGyISBHpAopCpBlARVGKShGBJIB0SECFABG4s4GE6Oc5/73Pn/B8PpfJ s5iVvWevWfPOO7NnZu8wqYbhK2ntLUg/KuIVY2Gfdj+Zr6/kVgG0xbmhnqNl1RbJDj59sOU1TnFD F550tPeEcNZujU4FmkqDfl1axmjCH6JP19s3SF6EU3AYywL80K2TngN5CsuxSzsMjsgrtSstnLx4 wo8ef2ehev2m8hevLJZ3imLe9ZJ8kcwKIckg5oHRYaJra6DBC/6XiAB4v2weQ9uuTUqhHSvZNBjW e3f1hYk9vXcROLcKR9fAzS54RRz84KXpErkn7AEufJeRggBVLUmIiHfDITLEXYLbDwRiGh5+DjqN JkVUmLeGVOV6PLJodFnd73uZIVgZWLWmcVnBeP8ntcc75rDdpCYKozLyF4nbHVWFnbAk8tFI2n+N eqQ+XdC9Wmm+ZyYx6vnBMJz6QNvwCmzCkX8364d0jper1aeMf/ygtW1uc+/ZyOerOPb3XtWPtMyC 1++TUzeLhTesbxKKRrgHezYwbCX/zLaXLSLgdut3Ui3DyDp2t7C/fzYQa/TPyHe7teBZvaS69pMq UHVT4BOfwXG+Z3vdbzckX9shanZPRVRHVHuHwoexMSwzvb7ZYP6a8oNmTwknCdcTPMI61Xzios8z pA7Rl731zmYuN8k3qRr/865T4PMF5CAsnvi93bg6s0f4ntSgR4j8rmzJJK+TDQpEPIq68IPEofEy LNOzZKSwuPnYfEYm7jhAMRyvs/zk/Yg+/Q/9QQLeSqd7Fhz02VfWXK/ktOG73euvC+N6cL5hvUFD lsbwmkuEqk27lneSgMNN2DehHyGHocbPbLRzJ96uttSsE+gLunae4VgU6CJviUKWjx296+jz/LfM fRbNHPu4IyVvfwGDv5flpqSN91QUPHAIYTKsAXd8O5HgIZwVrKf4BXPsuNKcBcJ5fF/jyG6kCPqA tU9eqBGjZsOtgs1ZjsdaT8tsTvWYR74nxLGF+oZ2PrD3eWSnyh5dzfkZ25eLogmmBAt46Z5tMA/l RVQJ9/FRLFNpwmcJ7JehKivsHS3qaLI0XaIxheZ7/0rPtYHuahvHDWufdc0ncIJbCW/XgzkLP+Q7 FtZrHxlX3pRGslyNIIlvAd1TL6OlN9j9T6YdaQO1rOVoo4rcSsolZugeS0fL5kCBHObO2MePDDW6 a1Pu56H/fc5j7pumH3BAUnOMfK1uWmBya8y65D1wN7csQsYvMtrlIOOB20gaJfQPbn/dHAjBjPCR gd15luuZcbvs85k5TgElTBH3dsCMLIZz7vgN48D+1It43f1HJhr5VH/hpRitXcSf0V2K1wkvjNxo Flmczw+aPMzHmenW0ht14zlzJVKvL7LKfw5oqbYFH54xRbzVmxx9snbXSLozxt+9rK4plbpZ9D3M dL5dPSp1MN/566WRuUqdBnJz7ICvuQn1fLTgRUrdc6QkA0C70t2l80rotQrZJFlt9cOWfMHGlJBc W7ONE1av/dQqaSNa3NntyrL0y14JVrt0LGskdEiN748hmb8fHD3xkBgVCqeY5ftdXoj94qP1mlmt Sr6BxKAM1ZqCEAKpiIP+wcts92psVj45vw2dhJ/qMKFWV+6HE3iySrq3+jjta3Z3vJm2UU2IHDat 0xfHjCoZDRR85mexyzM6UJCcrt0v4V0Rfy31iKqJ0P2KMfOltvu0Nu85mCf3dNmNRawWDJClEoVN /+qOTddHlAZqS6+RUyOg4RXrG4UejbumBkeupLn134wjw/xJCH36xd/erKTb3sBG4WlV244U5S96 ZNAt2V90fmHyPGLz8e/99MeVGjtUGXfxnyC4t4e8MoAs20JuUl54DchKta+NI+v3tz3ho9vW9wdZ 3A+5ssqzRAydkBn5JDRlTGp13M0lqHPz8kb7TnGWH/0CrlLrw1fjc7zSUiLXvoxiFelyzQP+cXws Y+wg1Kcqyw/dUSXrYUgRi8yl6QZWfc998yqQOiZEwonavWYbG3S3PeLHjGweXi2+5b6t3ZPSC3xS lB/5gMxJk6+4Uy9PuSOj4paZTUDX0nwts/l6SIPBl7PttYbSqJZd4s8SjryToRuU+K+vFmhzOVSi rlOSW+x7/0bAgW/IzPOqj22KJPOFG/aYmj6G1+PdHU3XbtUxmtvUe3Z3JCen5fuRzjlGPvoPR0ep YvMr69s9GBvNej3UCyXQwlmGchXFpUzZIr+VUb+DTAMPN5ft0fvwpReODdb0ylOa0/iNBLJZaRof 5lJ5UtAjzVmTsXY8cm3ux1JZWwuQ1e9nzcWnb7b6kgLxzGNWF98csyL0aGVnv+sVA+09CGFeACcj A0iIpYIVauRHK/jJKc8iMl02PLuyWFng5cqiT3PFmrK0+ojdWeOoyjKdIp0aAu22Xvg8/LMR/dby TuPAypGacrs3u9OzRh7Erj2d/TSoIflk4lk2Yyv1/yIsZh7T19d8b/quLk0r2z/HIbce5qPMfPqi PvNaKF2VXOcc/iy3ot/RJ0+3/d4pBqBD+i1SqmwenCKbZ1v4pewlc1eHWml7V2xCg8Xyxa1BOvMV aNXRPu96vt0wBj19HBgVBI8mWg/skGTfLp3b8HXLr8im4Rsl6vh6NwqtiVD1x/hL5sCbZQsy3564 jq09fgoYV/AcFPfto53XYUoisIxnTFqlQ7sXwwDTiAw/r/qMuf/Y172ipDKXMIND+UW+Y4iDvo+r xdci+l8y29Q3Jf2ZM92IMv842hUYnhA5L/hxpn79sroDzKfC7cfu/2uI3IWlIPqDHsYxpTtQW5zj r2W8v3oVIaf+vgl118VKe0ndnbLAT5JbdEwhbjxAcN6ky7HOvjhxxsDwx0ABZ8qyuhQV0EPE327Q 7I+/VBii31WZ8sw/BfXZPTpCSblaeqSBEnBuKNPvYe22mzs04bS6hpIRp0WjyUe1AxqZBuOndsqs fzsx6oI6kWRh/vej2o+vOCrZF/qe7RlfeDH78eeho+rkDJSC+oaUWwJ54cRsQfJ2MUp+xcMb3kp4 j10ebWjCCa17IaKqSdd2XE+w0qxfmOtT/VjzIiNY3jh9/pEY9riup3BA0YWxyCx6+Fbl6M1nEWJe gnTrEmbPssKI7VrhmzDx16usdFy/boxi9mKjLK92emXiw1IkjAVqVmF2eWhb+lJpm2uOBh9yPWcA fweGe7/v5hzudSiKWKR7MLqW6lePUQp992mEPl3XH3/5W1CqdQmCKv6HB17HmuB2BUuRzkm6rtJq FRqx1yyn3izLzXV0zEnO37i/RclkKPH03umqa4SnzAv2z1A4VCDo7bS0H3XEUdAzuUKgWODZ3LHE 8wz3WLMXLgm9xzOf+c/JCT/80vl4m7xaZ9uRmPL2crVSz1BmeFnkWnzSdZcvLpZPtK7HX4613zS4 848h4nCqhc/O39mMhEn2HAvYX+jj7L+6zjHwm2lzvs8J1+15wWuCrm+0ygDIHxamuz148Nmx0rJU H1Hd0VFds7NliNiyWvPxLg22FefHup+vV+pHtEQWe43Iew7OsemzKkGc1zmYykc/ecSVYle3PTUg TPyaSUxEZNSoSmndpzD32C1zRxrqkOedk65Xtqq1GlNvu3sfNgv2bE9VopDtUw267rKrbo+k/Onu cTl5nX21pnkHtt6ah9P5ZlcY0XVC0HNQmp+8bhXMU62LjzxKHDI/qtaSlPZle8fg6TalfWz/wFDo /pUG/hwCthY4eLxfIAen4y+cpNVOHMK0HDtzMo6SnxyekfTZIpu58Zn+ndaV3owWSvglOzdvgvf7 zFdqpYyWYzkbFsq8tDZPVl3fWvAoLvjrkTclx+hrbJQGpvmbpZdxqiefyfS604mtfSZ33SVUWaYf 5rlItg810mhyVA2DWGfSMSjYpmTP4VmPn7NkWqgaxSTa/zqWccvMWDSeYlkW8rZad4P6QQG3iBXZ 72gRlmv9wHQI5V27+bhFTuA8ev65UaIiK2O0oeR+sfduhnSL5kDUVeeRRvk3pi2xNRZZOY3+Js+c Ar2jKwMNCUxh494B9hzH35+6Us9pZEircrQO50ZC3BUIrbEI881MCjteE9fY6Rt8MG904MHDmM9b N+k8CLaKvW25alPlm0v7rzFWjz4f8fui8LwrdhV7WEjS10cLFYRWWWiWhcRvtcztFtn0ceEA6fbt XcNxcis8w73nNBYk0odjB492G7KKXlEBv4HUuRu/8NmVtad8drv2+grnvO9FhZmtUDNiSP3xSlWt sYK+tUlpRbD6dD6P9TOS31eJX1+3eNfaJOH2HVrDrXbgWoXFL1UIG7NzbSxGDui6Jdy8mBDUYEjw cLKoDVo7HHByG3tmsGFjmYrUKm/J+PbEN7dN7du96ZarHzg2zyk3zGFnglO86Uc1LXPJijmh0Vl+ QFc3RtNMp73UxZsaXnb1oqQFcpR4M1dv552/1Nu/Da++PHDvQcFK7+2hGwYkzwUj2Tc2Pn30E+EQ j5h9LxUV+0LPcYxssr+S9KOZPR+QBI+YHctq2L3fV5J6J35pRqPOLsVIx7BLVwNPimbmZF75fLTl mLFQzaWr6xCHsJVfo/sLu9R3713dL8gwK6B6+LX2eEW8YXUb2AJFoqp3urFQwYqOsWFci9PF5wFb 21aeKJJSFw/UtpF4mXQXbrtUgB54hOBEIRSzncXf+IRPyEHaFw66HxENuHmXesD4A1gh+wQzfiE4 hk1Vury1dHT0QRfoWC4x6ra86gt901l+/qqTAuO+REnS47DtHkvvVfYqJd74KlwatdWwG+rLv5LM +0leZ2j3D1IpkodQu8ihL0YK7eIadIXGEC3HJF7UbRQaI5zyME5HD5CsBUyOFch1+0vaLtp/HL1S /dQ3l5Ux9YZWq1tDCYZnHSchwtd24M2bvpkWWdbHDIJxU1TvCfXWM+ZN728bm4E+267TC95wsRi1 0pfuxVjFyDTNOe0x3pH3wnDj2JsRx0kCON4VviOd4yXWmmpjdNM80ZxoXlrmTiO3km9VlKmVbufP GTZ+ss35U6lYznDh+eHOD5WPY7y+ZD7Y8JCAb/M+QTyxqfJjd1qjRxoWpUD/GpQX+MVYnHN2mCV8 2XFHz6ah8BD/o3vNDOcKUx2rtxUgDITQFTkNmIi9mgVRTqMI/7l5lb1/Mj+u9ojavr1zAiqcItZA kSjsHTwo9axc2kPo+I7dY52b/5qDdvviYhUdR/7mker9JOnamgchOGJFG7nrBMVlD9W+A4VRp7ic 9hhZ+w15tepJMrXr1CpxhMk8/EulA2RDkfXdPrWP5AqfvEvSOJ+drRQWzDm6Bhzs4u9YdtEJAaZZ DgnX3Ku38TeE2z2sbR1rdk6FYSTjit+EFujf8qbw5yTdzNBYT41MFu2LrF7cwDAMPhCrdiSW3Tn3 +FGXJRqqehf7g7Ue/SYhYudxrdSlpMjDqpl7zSSKh0ewAQoyG+qRfpiONjmqt6Kvj29HEIJm/s4y pMJu/pJAK5gRDKWKOiW6ZOfJ9Hzam+40qkNThBNpbpHGX8zBkj9lONcbnF/D/XfcCU2n5hUPOX5u VIpqL6tNAgW4GlfcKEPLv0QI3Psq1YYfXfzIxCo672NVWP9A0ICnRmeBmndmeNgqqxVqdTtepVXh MLs8qQiNvt7es39KceJyA+tMj3VPb/a37EgjNUo+tVdtyPQDKxFp+jTr+y4+C8pTX4+qVJYFGBVg T3u0LTjhQ9Id2PJ1y8A35O0+rYjqMgHC15zuPJoYOa7RQvMAH4UPraz3p1MIx4AX9AvhwkduPpF1 913mtGnorWW6/tqnNkWWd/+tHepf3XLGgYA27NwPpo9PIlUbTWL812uviVi+ey1ouG7rCQvB+mIe /xPP4LwNO+c8npx+QgxCKdo5pHovoHf6KefVWpUbYU73LhXV8XHBrlWg3UEXh9NfNMPku8pSQvy7 iZiu949LAgkHKWCk7nPqVX2/i88ps5ONIoUd1y3WJjXSGJJG8ZSy4MUZiREZsL6csBB/Zn+wYJXR v6Z7i7uKpn/VeSLArM//OUaQ4i+n5ZbhoGP5eWB44WVfon9RY6gf/Zq0NK168QawlpPuqPFkXeed TTqyMmmaJ+QDjIVRm1WFW9HXjMpUzraq9Me3lDVT5W2U84qx0Q31ob8v+25ppBSu/3K/YES+AxqM WrcR3UpyoyyJC+0tn4fbN8AYNS9eaT0OU//Do2BHl2p+reVwQE13+aur4bVlv8m8o+3VAstFzWVt 26gRd3SMamUXMAaLt57nqAz80omS2BainAOyKtIknnQQWgfjY1QWV7RfiRbOGt4b0JhzWFotRFLr noBvXHLeNiKfxymKSkPmW1zKJUKGh0363lDJxjancSO3mIiUCwYb/7osfhjzQhi1W3U9QYUsf2tz l0OT3INM2HFOkp2k3hY++Vc4A5HBuL7p/gjq5daoNbYlumD2ep8AZrnFIQNYDC4i+QQdrQ6aUzbq eAUul0GMinutEBK1CSNINyh00U6P0Jj7jnbbyqxEjXppx/4Y5UXNa9+q9JUJmaeh+KlI7PyiXI6u CVpbQRKcs44Qw+M3fRTK74oI9DWhMjP7B1BHr6MJHgwJxj1RjLCHleX2s8y0u3zwutHBXR1pd+EE X7cAZVtlPjpG0nZZnV14VcS4pkgAIQhOxaORDT/OUIve5BxJDL/O97sm3xfHgftuyS5F+xW68zC3 sKd7EwB2tPtvcWbEKBdFhliO13jdW3zg5tb52N3rwwsxYZ7vPJX1lCUu/uC2PvKmve2pMkW00Bv/ Rh1gkfR8xYCjgstNJv4LQMvJsij/BjZhvwFCxS0r5nMvtmivVkyDowzdPS2u3bI15BPisUyyugo1 U/DmD4b1kIn2tpIb3q9LtKaoUJMie/CMnnX9FoZJEWp8DPdbeTZnwRq3rmFSiL8gRTbHlhr5KKKp 5RtVNm/3+lfLCqsscXQVShwFiUXqrZH46wfb+sD2700oB1Hd9xtehuiG9fVkvg7RhekG0m+nvNNQ l32oxYzYuE3tat5HCbBmX2KkM7oQtIx1AaSIEwgqoCspoipCl0xiZJf8+67qHBHJc/CWQL42zknY V5KupMqH24K3D8vBqCTMioI6pxulZiNkf2rkHoTWUw10BHp1BzPMA7BFhdyJdUsW9ZGxEewD7sov oGugab0lc2S/61cr4KLa/qRXz83TmTZDaS2RlNCSsJPpXWpm+d2dN8N38Lvv3s73YTjgToJSr2M7 +ktgf35b3Ks3TWOf4q+uXMD0wgDyeucmhb+R9gQLMp67JsCRLYI3xzV973aronJVaqGa1L4Iocdd clBObsKL0qTp7g9TExzin4qjd2+v46dtPBtB/7PPZ/1ZJoGOxnSRT9HuW15TyJt3hoAnX5YdEiI9 2XvgCi5z40X4p+/Nuyp2FKo1tSV3ycGEC7TIuj6E+2AOP5CW4KDWWH7GTIa29StYL3QTbkPrBZDA wxR+Cl+fWBMOe7of+SRbafWOH7q5jkKU+Ab/ah1mTxfWbRd4UpHfEil+XbbAq9n1Xe9FARcvNYfj Lww1LU+vML/sG6xDjlfLtF7ud1yUcVCavjp0+1ipXVLEHliFmrmA+YjDYnmp9P/gyg0/ZTxKUvv9 GtMyjPYBCRHUrf1W0unWMtThUbtwd6NjKg50nDYdXq93poTGx0jpQmM+lDPdgPVL25OpjblkswI4 deHaBVJRjfw/EASCAnW6z+DAqkhAO82UW1VXTgHP8wKsiJ8O+hS7bCcmPfwr9ekIIHgjvq/uG81R Z/HAHVVKfhB/SPp8Z9p3K6j72/DWr521D6y6G5kUASNnXtbpu33lVHg7WEpsJfoZvMAjvIvMSv3v fRJBf0GcnXfAZNFvAjkZqotXH6BnbqwJvOaslP9UvdG/0qFQbtPDFTjGiKhR2vxOIkdXPHFflHZv i71nhI1aU7tdWviibYSGBhb+wR6nrTF6DBfhscFaNsxLhqYgZihG8Xkoaqtsr1CACIE3Zz63vvQ3 lgZrXW9utZJW7y9f3qzRp9ZfPu8zWFJlPNil/kSA6GRd1LgwQDLH1kcmjB5H6QyoFQgQbMGf8DT8 pnOBwyBeS9H0Zt1qGxRoFhI1po0uQmT6i5I6O/t27O7fX4leh2l7JhgXlfDX+xiZodBaht/CdBtW P7R5KFZQUaTzCvOOLkZZLxiVrw/3ojPtar+7cV/GOqc0RzTN9z+P0bbhJ9ftD3+vwdeD1I4uG02t MhuSj87n15HZvUr38MNBosyQr7bD2h51zPjODtorzFm6CjWlXn8Zo0UpBfHDLXMfs1vTflXL7aMl EVdOLVS/eemaD6ixyE9ypDbo2QR/fYo44eKquJqiWoGR7Db00+QQpvvnRp39acp6a8iejOiG0ODE Xs7F+Q+fSUeCHRR69czz8M0S5IsM866yMy9VKHh3cnuQzbvealMkjtkLRycUl22FDdwwuPfJWrWh 9hSNxLAXcSp8wghOpHOaS1TsUDb4g45jrOxv+/T6Iz3+bKQuGQ86Dahy+Nrwxww8bdRF0bUhTOuL Qvs3Dbxl2j4m5DMRIcyxCJ0j0dPPI0gH9TOOzNszVO63AmD3xxy+5oIH0uhyeboEBek7P8NSQdUk 54ufShtMT9mpW0W/iXzr+WgzoiH7DM1avPWB8Zcvowc5n/xVJIyPWsiS5D4I5mVr29QcbNEIgNf6 uGqane39ms138l2vFqlMMKQyf3Orv1m2UvAP4/9rwqhqskG5n7VW0nkdBbq8XMWnK6BIWIekMFhn gNW73qU+YXWHCUWDhSLfbITAU8eWOPYougMfKCmPp1mXxYVKzwUPYMEttikvcpGoUvp7sxVoAtqt 2CWdsOHeJ2Vn5hqOp+z49hjkU+XOzSu7+M6QPEhyUuUvSsn98UuMTpTxJ2uEtI8G5Fmp6+5VP77t 1Ze+y5TTYonsB8CkTYLlSIyVOP08ZiM5vMXy32XGL998EUplNh/Uu3xV70t26GD2E6mXQjuOqgoH vzWw4Hz0HSTWo3BoA2J9njo5c2kL/D1uwN260rHQN6r4X+6UCvUgV04XTZb1LehIsyYsxBIC0udH K3xQWx41kM08YxbDnPf0kKE1p+Exsdt4epWFzXlMDpn09Uj/TZyvYY9aRu+ZV0xmER3JmfQCSErb WCyHtGqOnOiKLNLnh77aE1ZlutG9VpzgS0wfej2YxPmYnJZCOnKw1T3ZbHueW58CkZaNG1R0Bw9B ShYO0ukFR4arrb/LgB/Cx1BP3YcgRsF3S9SZvRy+XWUa5l6RU2+1/An1RmfCNJg4MT1PwTTBiXRF g1/GRpmNnI/a9fD8bjG5irG7j6pDlvRQ190ZtCxRhsy3h6PSnI+9GTudPQ+60rEVbX7Cqd3HqHrZ JosRlIrAqr6UZHbNAYUk/ht2pTeG6FiYVRn4h9Od7UkcL0L0HV6BXh4inMw8FmlaVJ/SrtM0tm60 GXOfIwkaz28Sk1v89S3jNG1O0PKgC5zEeL3HWfJy+kD/jaQ7htc4TuDE5HdQ9+7IZ+gJF8gqxXKY i+ZP34zXxxqM9NfGXDe89901+6NJOxPJ/g2CTh+37+R4OYDzRYH/Oh2fYEMd58svdRcJtaVC7xDB zLZabUkzcj4FVDmkAHIdiJcBgd53g96bA+HphCB1tsBg8zbDwZdSuJtAgpCbQCl8SGAx+C4ChPXu owzQofenoHeY9gFxBsIKrHfoILsSQCZeU2KdhJWKEOdAMnnASchHwEnogkAHHJJHQIfkpcB5oTsC zhPnfAT0QFIo781AWHly5i87dVwAxJw69G7bb0Cga6F3rYWAszuBDu0NUQqHwdzABfHgPSsGiFnf wemJ0AicvwK0HUDWAMEBkQfXQeEMjAZjnYcwZOnTb5tOJPuPPwCX/zg2e2AWgVkEZhGYReD/VwRm d7Cb2ZoXgYYDs2GmEJjdgXSmkJ7MB+ywe25mc+RSbjO3gzQ3N3wG9P41t9jl51/CpYr7n82IgCkY lz4TO6T/igRfMmNbpE9QEqIld0JycuIvuIc0P8B7ZgguIsIdnKesXEhOTp6hHhyCiHshNjl2ifL/ 3Bf8r1OcO5fIxQDQnimC83MPa8jSiuQVM0Jw0ONOgMTNPzNC8CVLYrkYoOLHKvOK4MjpZsEDuGek B+dfsmIFNzkCbM0IwUUucNlryNxMEHwJ9/2O5eA3kruBTfBz3Hd7RnpwwG+uez4TQ5RZfk9XW+w0 wbnLbmCNRXBe8Ztln1cxL/idzDFCEYBx8zONwiy/OfjNMQLnMsHZgPOK3zh2DjxSZvtvNlESZ2R8 wvUBCu8mmMhpzv2q428YNADnYgBkmYnhCewXnl9ydUIPppccvfc0H7mtgXWmX3T9hJ+reC9ZMSP0 Bq8fTa3scSe6ANrlTPTeEO2UufdRBqsxM0Jv8KoWd4BmWZmRySW3Gzn4N2KgsXDf6k8tinAznLsA gP9pNv/lB5fMEL0BwbkZIJrjcP/l2P7MPf6fHfzvPyZy7tzsCygzWE2z75/MINhQVrPsnlnAwc1g ZjOczW0WgVkEZhGYRYDLCOwE9v63v016ATvH/j3SMmDvn36bxDmChn6bxPrdFg/iIR7YZJmctc1C YjqexWQaC5Y2iwkLiel4FpNpLFjaLCYsJKZ3sJvFhI0JW+EBJgzWFo08sM1Lv39R29M7kM7iza5C tsJ9TMAOu5hJ89y3zXZ7nAe22TtI88A22/EJ22DPUO4FADe0qTkIPPebXQpuKKOjrB3See83A2yL y6XPxA7pkwTnvd/cwJllA+xIP7VFOq/9Bj0uN4O1te0kwXntNwsprsSjAO8pgvPYbwaDm2hjfKyt rSd7cB77PT4OQcS94GDt0EiB6o7HfmMwtlwMAG0WwXns9/go97CGLFVbV08SnMd+gx53AiRu/pkg OI/9BvR24GKAiu8w0YPzwu+nUMMBAdjmAdyTPTgv/J70esLv0cbqam5yBNiaJDiP/Wb4cNlryBxE cB77Pd7Ifb8dKJMchKr1KXcDZHKS39x3e7IH5zHegN9c93xiiMJjv2f5PV1tDhDBJ/HmLruBNYje E/33dHbc08AQnNf9CS/4bQ2NUKb4zRzn5mcC7Qnbs/yeptnECHwKby4TfBJwYBsznR33NGiKOeX3 VM1yN4Jsz/bf7PqynZHxCdcHKJMTTF7w5OkU3SB++7Bh4poysYLCC79ZrQSyDQ3AuRhA4SdXUHjs 9y88v+TqhB5ML2do/YSbCygTTWRygZDHPBkHK9ZcDdVTC4S89vuXXR8cp3DvQwGrMZP0Zo0HWV0X V2OoLmfXvyFIocYyCS2v+T3O4GbA+IDl9AnHee73JDzc+ts4RW+e83ucew8vgSXo4cWv+PxyfJRV cb8WT8DdgDHp+a/lNwtt9nx++gAXNe5jMvv+yT9VD/fxBg/6pwIPbLNM876PZefEXYUHmIA+fNJH HthmF37WNhsKtjKLCRsKtjKLCRsKtjKLCRsKtjKLCRsKtjL0415KwnwwGPT/JaD9mKBU0PlH4Fgi kK2WxhqKSNGJc+AwbAUSBlMB8QIgGfypuiCaCJBurfB2S+aVy1sWI4X/Lv2Tn6X/v7H5Q5qf2tFA TpYBykMRKcT2YTFSkK2LIIUEloHz8kD4pUj1UFoQpIDgJgSH2AqLnrt1Hcf1/1D+n/rBWX4R5Dy4 HTBsAQTKTxjErIDbzzSBBPo+ETv4m+xwGjGDTcW403qmE2lY8X5/UxgfFPCw35DzcFLgOgHoYlBr UJmg+oN+BwbVDyTAqv5E9IMOpVEHsgAI63djrN2sVMExlh2ZKR3QAMY6LgKM2oDvG4C0w2Ewb+DA ebDv1isQQ2U7e6jV7JPrJpNPrgRTrAEkOuafXCE5Z8GyAdLhfmYbXI7j8H0T+D4VcGwd8hfipzOQ PUAgfoogpfmRQF8HhFWn54A/EwH9wphVRlYMsjFkpXujNT4ui5w3QQDoEmkg/69YOoFrIDwg+1AM BVYM45/eSWxc683kyam/LDyg61j1AWENBVZaVhroOAszKD1r7zY5oEsByToE9kfbBoPZAX0ZEFZg tXpQVbDKQyNmlYcqzbIOZZlpg+9SQGRQoMwmk9dB+LEC6zpQtTAYaty4xXXYuNRVwOSBq4RJjKsa kE0m9uDU3+UVA+r/k+sOUP87TP/Jpz3gvLaBBxCCKcsnbQMYTMf8n8uibbDPfI+BnzkWyD/58cnV zzwG8C8G8A/y4+/KGON61+KBa55FqesLixbXSgsY6rWFDIpoATUgESAsnB+5wmD2oDFDeaoAYQUW XlDdqKHOWaihdMz/qdxqKGlzEdTXbZ9cv26DbK1hGQIxy5Yg0LEGX7flgjaUO9GWagCmNf+Ipwiq xlQNRQRCMIXsrvyJXYjnaqhNJo9c0SZ2h37bZgf4wCqnHjgHldcQyAIgzYA4HuCCy4AI5SBmcRDi I4ubQMWxdKhtQ7hAAlR2u+XUIYyWAZkLBNKXTOlQuY2B7g6MOwOB2rYGcrpPXwF0yC7k14/3Hhju /BYY8vGWv0tvbX0aXD0ZOPW/Sw/8hSCYCjjDHMNLW2DK2X9r/6fpowv+Nj2nD5z63/nDmYZT/7v0 P/UH+C+AnMZzMSidCBBWLD/1HTQ9GBLIGiAQB5WBgOqYECkQswK072MpZGAqsL5z1P9PMYTqHKp7 qanroEgMiBSkTIVdIEaDTKG05YAXrONQnAcdBAH8D9olm2AnYIdhB2Du0IG3mhPcgFRW+X8Dxxb5 JLvPLRyfiwQ6JHe2RkPJn06KJpQYhHGoi5yIM0zWScrCFGH3IDKC1qgJhwlElwHbLVtELrYU+fbN 1XAJBg3hN37omnH4UmqRL3SNKGwJ364HaQaJQCeB9JVAOoDQFgtcitzz0gfZ/3/Y+xLAqKqr/ztJ CDPJTDJAgABhMlmAsNRvJgUFRHPfJID8hZKqIG41RfSLhUoU8IOq7fjVWurWCNatLAGByqKGVisC SlglCpiCLIpCrLi1KEEEV8z3+828O3kZZskQItH+L/xyl3fPveeec8+59755b+bkr9miL9QY0ihQ coQMExJ25Ive07dO04cpMpAfXjSiMO/yG5LTkR5yRfU07xUPpDz09fkWtlWKspPjqqeVQF6qjPqa gPKC7gmPRup7wq3+L3lR9ss+OwHUD+2svZ5me8yzHCHuMvyZA3gThFiDSbINOA4onlmJ7bgBGzAS MAbl40pR+BMxWTjFePydin+TxPXiJuA6MRHXOJcyAf72KGOinQ6WZQAOPWaaUGPBdW8e8laAfGXr afZtTFPNIwEJRPI5ak6hGoLuE2DjCTIgl4AtZaGGGSA/jFvUpsADx8dx2gEVzp5NCXEf5v2ngz+6 tcKa9bWaByadsapbDlg4J9Lfmd+WughlU4qGNnUpbErRKJt6250QH2les6tYbeqza061KYl2gm0K 9vxApL6bY1PPor9JsKnPYUvvAO7ExjZFPbsB2gDnrDFQlgxlKLwRNuSENZUiNQWpCYhv8VnVVKQm 46rfpmg7qQDbYxo245uzjJXdcc3nPCZYT11j/dOxtYdANxOIZGvGNc6YDrfeBe8HltUP96wa260o Sfr3I+no77WJE+tNiFUwW1aPGDdv7P/LQwFth9eyADMwHlBl9EEEbJ7bJD00pKmT4P37xImv+eop +bBtlUb7vjOUC2VuYBIa6Akcga6hcpEev6NnevyHN43LJpje0VPRcn+l0qjqNfCmIa+Hhn0XeRsG zAHKAcrcLDvESaT7A+ocFDgvvZ4W8bwEknqzTIsfgoRLp09AbAyUK/NKvkxTzji73tlRpvl8FGk4 r4yyN4wlrJyvBc1AgPJkzKBi41nLf6Xhr5IZ6ZSuKBtjUHVYTt6of6bPB8xAN8AO8Ee2d/SMfD6p j6vqmRz/HHT3XM9zdbpx2UI8F4Xuhuznet6cXQXsCNDdDLoPb4rc383ZJ266Ids0eRyg+kuPh5wm R6ZLjjdNro87cVN93Ic3UejGcbpBz36vQHlAxhy/HjAXMVdfwxx97aYCzNUC8Dwu+wOM+YOebsxZ 1R7nCtstYH3gHOAXkGFv4NPEBllTN0oHSAbmOee8YW6Ened5IKLO2M4wYC1QCUTyM8F+4/Dibwt/ /mFRkVl2jJOg7Q+cYiMXHmyCjXSK7wdap06PoTYKxfdePaLsJdiJzyY6BWyiI2oZxtqidqBkTd6M 830s8uT9cwgyFXOgL2Br47/XlOK0uh/Kn1jcIf/54vszr3ArOspctYfk2dDdC1/POlnYt3YxdNc5 ToKJ09ddekTd1dw3bIQ39eBwv+7SA7rrjD5bi+6+hELioTMzdDdA191zmT++dLxrf/Eo1/Diisx5 l7Qi3Q06St15fwvddWmm7rpG1F157s9GuL7Ig93Fx3eUXQO669KKdHcCuuuUgHvt0F2Crrt9mXdo d+Y/Pbpnfo/iOzI/01pKdxMgh3FALD5z6ujtnpK5PRvttYorRaO9VvnIR0Z4x/YfoXw0fU5TbKUX 6nHNCPjPymLkGnwNy5XfMcPv0He5gBuAx3HxJGR5P+QIMYrrEit6X5e4eeD2TILpit6KlmuMSqNq k9abbFTkesPlkOtNU+5bGfeyxnRf6W8LzYg+SFM2HDdY4bKpB2+BY11CYck1fcLeVwpZ/+3zY6t/ zaiw9Y08G9Ph+DfWMabD1Q/JP8abIBvkkwVpQNeBvXqGnm+pM7aSOeca9W0HVAh3xsa0E1swL1Q9 xmf2vpUQt+OM/Y9JT0xaVVVPtnyBHU7rYJ/MTIleTl5CnbH3vZbvsxOesS/DGfs46q1CmTpj497R 3EjnXPYR6xl74KRTz9glYDD4jI3zfUKkvoPP2BxjJ4CCoN2019MsZ14XkO++VTnydwNPQaFvocIR xNStCqQZBCQDI1WhHutb33r6ydG++1ROnKZvEU4xyhdfj/IfATmAE2inp7k3YNptyDuRVj4nBRM/ D3nyaQKy9TT7M6aHoZw8SSCSjw5pR/ADZ92OwANlzXHaARXOph0Z71VR9tQ9Y1+oOmDhPHA9fMBC XYSyI0VDOxoDOxI6jbIj3C+aFWkus59Y7aii7FQ7kmgn2I5gw/Mi9d0cO5qE/l4FjkGhj0AIA7DO UrcqcK5Slm0AzlljoCwZxqHwEthOodB8n+f2Qd4NMKZt0I6+UxvB2nfWbQQ8tGYbUXpVNlI57ICF Ok7HvKdOQ9mIoqGNjIWNKBplI/D3bSPNUzQfs41smtI0G4F9zo7Ud3NsZDr4rgIGwTaegMBuC7KR 83kNwP4zrI1cjWuXYnWZhnXmOtzDnYI898W0DYJri9OA07GXw6CvBSKtKcb9mzHdVwbW10Z7V9xb eQFN+gLTb8ZZhi6/fi/OeN3iJEr7A6d3byUjvh9onTq90eegSNT9qmxExZS5OOMJ0VFmBM543XBN rbGkyQLMwHjACqC64UwiLkRWhUCadNcCAwGmGTOouCn3IElH/aUD7NMYlO5Y3gEgX6w/FuCYh7fF PRkY25/M+AAz0X9PpqTo4wHDB/8t738H3503p2jdAEXHNlR7SHpVGk0YzjdwvA0hkGafeYDqn/a7 FqgEIs2RIJ0Piq/sOnT9n/YXmmX3OAna09e5I6LOy9ZOHFFVulDXuSOg8+7ok2cpAiGgR2OaYz0T OlXyDae7Uujsr7hYacFn2/F+3Z07qsJWXFjU7f7Csm5TRm2ztSbdlbybOPTnP74O9poZJyGj09ed M6LuXP0vHyG/fUDXnTOgu0z02Vp0R7ubCZ1NgQ7bwf4SwFtx4ciM4YNH5/128O159xXOyGgp3R1G w7VAFLvjMuILvKf9v/Fv43mVxxqd48M9Exnh+caQbRqfb+wrQ/v+4+MrCnR2xK4v5xRkFmwqOmfm 74pyZYLPp/CaWWa1WdFeiAqA6wDtkHItR542NAmYC0wBClHwMeItHYVY1A72Cmd4wCGEE0JhbdLQ X7ENY8BjnOKueMxdXLiQjRrCW3PMYsi+BN9nBWhOOAHK2CT9n3XakSdfJLtIRxZiTIFGa0akMnWN Y7ACDBkA21D+AslGvlmVp6C8Cy6SDtsq4zk2cL7leDvodchnmp62IYaofLQs76SnEfmex7AzoYfB iNkHz2BcI+2ACjlIOIG4lYb7UOV3FvS+8rZ1vR94Zp2yz3DXqU/j2MmXHZgHeIFLgDIwSB7tAMws ENT9krZxcdmXihloZyp2P7/E9TRRgSe7PyURwjdrHmjjRd4sxv366xMN91xq9XJ/SVbXLqLSNGdI 9bRtv8ql+EUF4unb8kXmqg6l5PNLCJll7ZEuP5QjSnEtaWKnUgvy5pk9zRd9kmNmWRXqHEYsgY7W tFLmxyE98kSH0v090kpR3acf123HEm9H+YLcrK5C3GMqQ/ohgH2qwL2ySOk7Ibewu2WTyf88EYdF 9Bce8ZMHpTgq/bVrQPeTw51KB+B0xHKGRaYZYlz8AHP6JQm2/sgf0tt+9Ooi80VigHmqaYDZWZNp CbWHNc6zPNByDrDfbD3NvbwxrepDh15jOfcGRZisAwHaj9GfZMt4X7uoIvpJvz9PZyboviYLiB7S Pw+oD4YoNL46fWT0dvNQx47abJdjDMejS8YF6pHHprTd/DqOQrBU2LidHizTwwZPfX33QqjDE6mO qeyVLSYhtzSuY7Bbv8y9aLSRnONQkCJFVTpizoFl00X9PPGkWIRdrVmKuCEocwFqr74FaX/Ac9RI KLBM1al/f1l9qhT4tN/v6xraMzXaC/j0LOkP5gKbhcdEzIWSTHemSZPXDnrWIU9mGRfnQjoXUP14 mQaoK/5V5ZAV9v6mgC5ZxyxPv+/gtozyqn+W8vKeYXmp9kyNnrXw+UeJz83Fw+Jb8bjoZnpA5Jlm iSzTTFEvZgqb6V7Kju8ImI3yw/DxnPup8jDq9rto+2OxQLwDXW8WS8XzYrF4CSeKd4CdYkWz+W7J tleLe8UW8Xvxrpgl6sQfxUfiMfEysBt6aK68W7LtnqanRFfTSsyVxeB7qfhczEd+vkg2LWw23y3Z 9jHxCObzn0WG6Y+it2k27hr9Afz+QaSY7gvJN9eqps7vlmz7E7FQ/BOebItYJlaJJXjIeCXyK8Uu 8VSz+W7JtteI+zCfZ4pDYrY4iifF/gXfshXYAz2Emt+xyLsl2+5leho+8K+YK0vA9zLxhahAvkJY TU80m+8z0bZxPxMPJ5wvhSkDsR0QojvW+Ayu81IIp6c5a60Na61av7nWzcNeeZ44LHqiZTvyCQD7 j3VvcArP3opGPAf36zFNxfp9ev1yfV4FHrES+NZxJ2JKZies6BBwBDPyK8TJJmKN6Gxaj/hlYKP4 RmzEmvgK4p3IE9tx/XXEbwJ7QLcH9NvRzh7UIN6Ejb6OeDuwEza6E9J6FfFGpIiXcX094jX6PPIt qqH+NNqngOOQfug/aVy7RJV4D6gT1eJrxFYTsVakmzYg3gpsEifFJnEM8j4Jz2g1ETtwfTfi/cBe 0O0F/Q60sxc1iP3QyG7EO4BdWId34X7ANsSbkCK24voGxGtj0lc4PxZKX9/3cRl9AX1EU3yBWcYn pKOuFVB7a/gEe3/Dua63bPAxPFsZ+0E2Wj+sIkYCEwDs/Bvd71H5v6D8NqA3fHxDOOVs03ApRCob ZRwHdT4McQZgB3hmjZP+a8j6nm9PYwLBDjBtltnmXMSUBeXAcdI3GkM3mUV35btPyr4o4xVOR+H4 +fWepO49Cq1L13tIo8r2z1vgu8b8eYtKCo38ZaGeGRgPkGf2p8ocSJMPFdR7VxwPaVQ9FU9BGdtg UHXUWR5Frf7e0+XLKwL3Ep+dM7dgsmtT0b4puJcI5olw1xNwzTh2G/J24MNE//vKlyBdBsFSTyxv C6hwZu89qVZVXB9fPOYCs5xxDJzgPhTekcnG/SFRnS/eThsxDTM0ft9PLzCDNXER6mWgnO+YlSJm MIHCqH+2wzGwnc64x8U02yhG/cc2LpyE07uNsnhoYlvbqlfzxeLDCyf1x/twrGVf4LKxfJg2YqSz 07xJjMkb22D/xqDytB+WM67Tsi2sr+rZkSAty2vR/9jB1dOC7z3xOu0vD+B85LttLJsHeAEPOqpF zMA6ZJR9ZwHsaDygyqh/ApQX+KKgNNvtBaQDin8x3e9DlA2wvAOg2jwfafYzBigGVOB4GTiPnGnS 6kwbaNvdDu4iVaT0s4qUWstAW61FWmstI5L7Wb1JItWbtLudN8mZNiKZ9YeAju1eCJCfD6D9r6CY v2PiyTaNeVC8oZrXMEYNeT14A2mOcTBA/pMAQ/2wMrkW9QYC9EeMGVQsnP77BCxb9r5P1Uz6guKL dCoN1r1jkC8G9mJM/8KYtmBMxbhwurJSbaOZgH9C802SRR4qUhbkMVa5qH45J1TajH7HIu8CqLPD us4yMT78F7WWGkutpRjzgWC6xqJoT4f/puhPtX82+VRyJg9N4bkX6qUDrO8Lz/rnlnEssdthlcWZ top2lgx7o90l11pWJdVaqqCHajPs0gz7NMNOzc60aqDKEsoO+f0VtEN+tm7kQfEGfps092Kdby1p hy9gTLRDzlO/HcYuKzX+05nHan4E26EqP+15o08fxRvbCaUzs263A3H9pxjALsjjYcT0T4iEM7XE UptaYalsV2v2tnda7O295rpUr7nGXmlWbXPcodoGeZPmQy4qEqge1hervv6TxtEWgqUfvRhxmzZ+ fdSk2JPsKTXwpOVJZcnFSbXJItmeIpKdtqokJaPWpo8fyjiSIdh/QB+jEX+IGJGoSK40l1jLzK4U p0Wk1pnLU8otZdZyS7GtpNH61prs44cyjp9AAUegh9mIE3X7KGlfk1TRzp5cm1qMvSVsJLXOUtGu zlJpd7Za+zhb42juGoNtvs9rK7/TFN98CXT1OnT2COJ/6zbkSi2z1KVWWqrawX7auyzO9uVmYS83 19qrWu0a80MZhxl6+AR6GGWwodoUZ5ITJ7USa0WSN7kkqS7ZnuxMsSe7bDWt1oZ+KOOwQg/cgxUj VnuwyuQqc5nVa5YpLos9VVgqUiosXmuFpcRW1mrXmB/KOKiHOujjIcRt9TWmrH1tUmU7Z3JdakmS PRU2kiqQF0lVdlertY+zNQ7jWS8LqwXOG77vUElHPBeYA8wHNgG5OiKdA870WfByvU91z4L3PTOg Z94vqrXItrWWqhS1vmEKxHyfJRvt8D4L74mp9Tb4rBdJRhoWVcqIz3aebRk9CwGo+zpKRrhn1xb3 C1pcRkp23GM0ZZ70Qj3OMdY3BqVLlofak5uhY97Hosy7YrztMBe8iAchdqLMaatLlil1yXUp8MCp dcmVdqIyuayd3VppLwNc1qpUl9WZWoHYacO+E6ixlrWTiCuAEltFaomtLqXGKlNKbE4bUWErsUrE NVYn/jpTnLaqlEqrMwXt2Igya4nVjrgyWfEPllrNmfuHLqvmzr1Y98mUZzcouAPm3J2IB+tzz2UT 1uIUYRWp5dbKVGGtshNVyd52TsReQFprUqXVlVqJ2GXDegTUWr3tihFXAmW2ytQym0itRTtlNpeN qMTsKkZca3XhryvFZatJqbK6UtCOjfBay6xOxFWtdu79kGU1DHMhDYBf8n0GxLXDuKYY08o34D6m V81ZrmPGOir9LSYl296GClUAP9+N8hyxF9W9faTf/6Yjczzs+wv+NQ9VhLE+37lgGQPTsbx/cYa/ kzokH8Z3NmLlO1L9+b95pahD2+KivjK0XIzvCRrT4epDDQU+Ifr+eAvmF+wo6vDypWHbD1l/+PVn rL6RZ2M6HP/GOsZ0uPoh+cd4EwzyzIIszICKM/T8xYgl4ALgRn1ruAkxYQdUUM8HBOcNe42QMofp wCE3bispKH8J8mXokHVb9vsu8i3oQvA7LcrxvRcnr1s8aSa+/3Q60um8gGCw2XWh3kEeuQGfeT9q HWoRw0zX4B1ktjXod8smqXeQ8a78ikjvAbOPWN/T3/rUqe8g0ycFv6eP95/NkfoO9Rl6J/BD/XD8 7fU0dc88yxHiLsOfcmB6It4hhoM9jDX3T4ipLxVwqUnfdzEKb9/8HE9U8D1kvofD72mdClo34DQg B+nOer6/HrOsA6D8eAomfh7y5JO8ZOtpniWM6WEoHwlIgH48JjuCH0gAoS6LgP1koS0zkKHHLWpH 4IHjIw92QIWzZ0eNv5tV6Z7zhiG9Wv++i/nh3+VXNLSjn8GOFI2yI7xP/3ikucx+YrWj8r+dakcS 7QTbEWz4qUh9N8eOJqE/D+znMdjPPxDvR0zdqlCDxCCAvngkYAyc1wzjUFiMd/n5/ay0nV4AbcOu x//fRiAIPUSykTcgS1WPsXpe68x8J3hjG6lB+9SrspGaA/t933fhgq1Qp6HWGkVDG7kWNqJolI3A 3ydHmqfoLmYbefbvTbMR2OefI/XdHBvherMTtrEKtsG15lCQjZRAiMNRh7IMZyPFuKYB3YDTWS+2 ofEqINJ6YdybGdPh1pfg/b03cUfRR5s3hN1nGts0psO1H7wP9G75R9FHizeFbT9k/eu3n7H6Rp6N 6XD8G+sY0+Hqh+Qf4z2b67WSeWter432A/MQ/Z5e0Ja25EIczhcpGvqiEvgiRaN8EdbMykj+gP3E ul5XvXCqL6JNBq/X8IPWSH03xxeVg++HsFnpDZix4ZuI2LheI/uD2/f65jD8QII8e/texUNrtiOl e9oOw0Wb/fte7+vh13RFQzv6OexI0Sg7wroa8bvW2E+sdjTzpVPtSKKdYDuCDa9sKTvivvcarOWT IQCu6SsRG+3oNVwfBHxf9r1qfibI75+NfJf7XqVXZSMVF/u/560EthJurVE0tJHxsBFFo2wE/j41 0jzFNIrZRlasb5qNwD7nR+q7OWsN970fwzb4O1lca1YH2ci1EGJT9r0etJMBnM6+144+EoCW3Pd2 eNY09OI7bsZ3QuXEl4PPuwC+D8XniwOh4DwM9aZ+93RcNOyyUXuHCe/P+olbyobj97NWLJ+3erio jX9K3FI3nNcZC9ZHPHfQA8N91wueRx71EfvomS+2/4jXfX2wfnxD+C0K02SO1444AXjshobPozl3 swDe7xkPWAGW5epAxNcxVAik6d96AekA6zPU3/CYL1a6YTnP66rNprw3slf+xbFXXufI1Po5pgP/ ALp6rgP+Avwb+ezM6UAmsFf+G3X/4hiCPsg/mSM/XZHZjHNVEeL3EBt5ULyhmtcwRg15FQJpjnEY UAJcBnDemGVunES6P0C9IhKx/DZIR5nju5eRALpcIA9Q8mGeQAjI2ZgmP9cCAwHKljGDipvy3Xqk U3pje8agZMNyJTOmld543rQDr0ohljoi/27GK/JJxyvQzatyieNcnW4H6O6PQrdD3ufYIe91vCbv CdDtA92UKHT75C2ON+TNQFmA7kPQXRWF7iN5leMjeaXjX/KKAN1J0A2PQvetHO6ol8N8UOPrjJlz XhS6dO08RxftXB8U3QDQ9YlCN0Dr4zgXOI+x8OthDOhyotCN1XIcxOWAopsOOmcUuuma0zFDh6J7 vAn9/Rn9EHMM/a1uwvjWYFxrdaj+9oLu3Ch87oMs34BMCUV3FHTDotB9qg1zfKoNdxwDFF1bD37L JQpdW8+VDjNg8VwVoEsHXVkUunTPzY4unluAKQG6bNDdE4Uu23OvI8dzH3B/gK4n6JZEoesFf9nL 86Sjp2dpgC4HdBui0OV4NjqyPZuAzQG6LqB7KwpdF8/bjnTPAeBggM4Cus+i0Jk9nznaeo4DJwJ0 x6A/c2Zk//KpZs78VLNkHgWU/t4AXXoUuje09Mx9WpfMvYCiWwu63Ch0a7UemWuA1YCimwO6flHo /qz1yyQeBxTdDND9VxS6Gdp/YZ3zQ9Fd3oT+xqIfYoyhv/NA1yNKf+diXAN8yA3w2QV0XaLQdYEc 0yHTzoDisx7+0xKFrl5aMr+V5syTgKL7F+hORJkvH8nj8NefOT4EFN0boDsYhe4NecCxT74NvBWg ew10m6PQ7ZCbsB5tBDY4LhD+fYZaBz8A/TrQX4HydBP+6IF7f4YC5N+Xax1H5C7HJ7LGcVK+5/ha vutI0Y47bNpnjh5afGaOFpd5oWbLHAJcpaVlXgHM0DpB950yH0X6YeA5XPsbsAN1t4HmEGj/iTZO aO86PtPec8R7ahxxnl2OZM9aR5JnnSPFswRYinQ5ymbj2u2o8xvU/QVoJoH2Ssch7SrHNm2kY4c2 yvE3TXM8p3kcD2vnOx4FpmuD4PsHOa5A+ipgCK5diDo5qNsDNDbQpqCNr+UkjOkXGNtvMMbbHe/L 2Y4PZLnjXbkUWBKQl9qfUR7phBl+CPuyYYg/QKz2GhSh2oMg6VXptk3cq+WBSO2lhiFdC7wORNrv B9+3fn68aWjv/96E/XuPVrZ/7xFy/x6H8TVl3xi85wveq7Mdox7ORx7qifiO99PyQffTcpT7hOzk Hq11ci8FjmqjgAeB3cjb8kcDJ6Qt/2m5G3UfdKu5cCHaTgc6opPsRPz2GWIPYiMPSv+odpp79Z5x EsT9gdPbq/cI7NV7oo08gPOrqTK/FnUH6vUZM6i4KXt19qP0ZnAvvnaUbFiuZMb6Sm/KRy2UeEfK HXktXSBnuRdANwtluftctGEHFoPuf6LQLZa3uhfLae4lcmqA7hnQXROF7hl5tbtSXgVcGaBbB7qh UeiqZJGbWC8LA3S7QeeOQrdHut17pMu9F1DjOwK6rCh0R2SWu0463UcBRWfVcJaOQmfV0tw2IAVQ dP1AZ4tC9yPN5ibOARTdaNAlRaEbrSW5i3Uoupub0N8t6IeYYujvQdBFG98sjGu2DtXfM6BzRuHz Gc3prtSy3CsBRVcNOlcUumrN5X5Fc/ug6A6ArjAK3UGtyH1QG+quBRTdEdBdGYXuiHaVu067Grgm QPcl6KZGoftSm+b+SrsV+J8A3UnQlUeh+xb+8lttlvukNjtA9xXoVkSh+0p7yv2l9jTwTICuDnRb otDVaS+7j2hbgeoAXS3oDkShO6gdgDwPug9otQG6V0H3aRS6V7Rj7mofPgvQrQRdfH5kv1Spxec/ o0PpbzboUqPQzdZS82cBD2r2fEU3BXSdo9DdonXOJ24GFF0x6LpEoSvWumCd80PRndOE/n6Efoh+ hv5SQGeP0p8NY7PqUP0dhT+LJs86GZ9/RIei2wu6z9yR9bBHHoP/PObeLT8N6G896Gqj0FXJg/DX B9zrANVfJeiqo9BVyq3uZ+TLwJYA3RLQPROFbrF8GuvRU8AK9wWi8V79JdAvBX2kvfqLcol7i3zR vVmudr8uX3PvlNvd78ta9yHw/4382P2VPOzuqH3h7qB97s7XvnW7gGLNBN2b8icj/UvgPly7B3UW a4fdT2gfu9fAZl6AvWzXtrtf1V5zv6mtdr+hvej+p7bE/Y621P2eVg7MRvpXKLsD125AnRtR9zLQ jAVtEdoYirbORZvnoe2+6KMf+urhngyM1nLAQw546QGeeoC3fuCxL3g9DzyfC96HYgxFGMtYjOky jO1GjPEG94vyDvdL8lfu1XI2UB6Ql9qfqb16BzP8eiKeN0E8FLHaa5ggX7UHQfK09+pxIB4GrAUq gRj26i/wNzFrz9mKvXqvOAnakPu8Jv0WbV58P9A7Ae4TyZMxlPS6YkTVB5P131/IC+wJuTfL1QER cMrpoSHNts7EPlDJmnJXOmDbYwHyzt/E5Hcl5cRDntATkuKfmZ4JzvyM4kr386OnZB64TtE1TXde DU3ooSHNPvMAK8A0dTcBGAfEoLtBf42v9izv+kJRkvTv7dNBX1wzK+JvYpLvpsibemF7rM8wq6bY FxtlqNJmKI4ydAEcx9Y2QnwNwjWQIZJCS7z7ai1x+cTlmQTTd1+taNuCVqVR1XBGaZAXigNypLyy AcqO9wcou0noqwSIJDvj80LGdF/pbwvNiD5IUzYcN/qk+erBW3DBY3GFy79a3eRnn3z1V2+Mrf6v toWtb+TZmA7Hv7GOMR2ufrjxJsgG+WRBGtB14LOuDD1/MWIJuADq2wlAHT7YEasQ6zsCSubUOfVt Vw0hjvTc5hbMC0PVM/7cZoTfxLyd/TblNzFpJ/z8+jp8fv0Z0kG/ifn3SJ8hs49Yn/EYefDUz69p M8HPeOCzc3ukvpvz+XU5+L4LeAuT5E307YB/oG5V4JwZBCQDI1WhHtPWGSi3lvpNTPKSDXCusS9j mn6GPEkgkp8JaUfwA2fdjsADx8ex2QEVzqYdRfxNzPYHfb+JWfVW+OdA1HyhHU2AHQmdRj0Hgmcx nog0lymDWO3o2XdPtSOJdoLtCM9KPR+p7+bY0ST09wbAe36/gxAmBNnRWFyjHdEXc84aA+c1wzgU DhEFvn+8j8i5nmMA82pdTsGkzkOec4dziNeYZjvG9DCUsT8JxGwjWPsSQMh2GbKA73ytAQ8cH3mw Ayq0FhtReuW8Z6gcpf8mJuY9dRHqHQFFQxu5HjaiaJSNwN93iDRP2U+sNrLv/abZCOxzUaS+m2Mj 08H3S0BpohALILBliKlbFXiPlzaC/WdYG7ka15r7m5jsMxvgnAplLw+hfCYQyV6M+zdjuq9ssJc+ SOeinXQg+POY3+OcMOa50kbnBFFVH/WcoGxwPNok/5x37IOASwh7Vgs+O9RX+QgC/oTtKN9iRkOc oy5gArAQZy+eHf6UoM4OPQdriRePWJ5JMN1zsKL9vpwd8nB2GDNtUti9ffCewVf/+B0x1V+++vdh 6xvnjDEdbv4Y6xjT4eqH5B/jTZAN81PNJRVnQNfQvWips4OSOe2Pc9cOqHA2/Xm4s8PRFPtq8hfL 2eGG0GeHtZF8KvuI1Z/P/Pep/jzM2SEtUt/N8efl4Psu4O/wDzw7fIGYulUBRT+4s4PyA2fdjuCL WpsdRTw7dPKfHWq18PsiNV+4L/pvnh10GrUvwt7kyUhzmfMuVjuqO3KqHUm0E+Ls8GKkvptjRyXo 7wTwDeznRgjhQqyzRjuagmuDAFwOuy+6DNcuE4W+72LPQboPwDVfrcstfV6gXXC9O9t2QR5as10o XXKuMzz57gEL9Vo+OvyZWtHQLkphF4pG2QXOC50jzU32E6tdmI81zS5gk0sj9d0cu5gOvnle8MAe eF64K8gu/pPOC77PFVY/3Oi8sO3H3+F54cfbOI0C/oTzV/mW4PPCc9ATzwtPtlHnhbEXa4m3Xbk8 k2B67MWK9vtyXvDd93780bD7+eD9tq/+lQtiq991Wdj6xj2/MR1u/2+sY0yHqx+Sf4z3bPpzJfPW 5s/DnRemdbDfQRuJ5bxwY+jzwoZIPpV9xOrPV31+qj8Pc15Ij9R3c/x5Ofi+C+BvbvC8kAz/YNzn 0Kdwn/OD+6wBfuCs2xF4aG12FOm8sLWL/7zgHN6088IvYEeKRu2LsDeJ+J1AmGox25Hzm1PtSKKd EOeFjS1lR2Xo70WAv1mzEEbz0yA7GoxrtKNEYCRgDLzfyTAOhSPFUFGE35rXcHLgmYHnBZ4bCK7P LGPMezUtfX7w+Xqsf2fdTsBDa7YTpVv6SgbnTw9aqOda2Av1GurzBkXD88NE2ImiUXaC80O3SHOV /cS63lxU3zQ7gY0+Hanv5qw36vwwBvbB88MjQXbSWs4PGWm4Fwq05OcNeDOrSDgfa7S/dMhEn21T v1myTSDtkJZAuo8M/xmGatP4HaPh9peG72gUu76cUzDtk68Kz5mJ33KUCYG+zLJ3mxXthagA1PNq 2CqIcuQ53ycBcwGehwtR8DHiLR2FWNQOz6L1w3O+DtgDhMjapMnD9TjAGDBkcVc8nqnDhQvZqCG8 NccshuxL8D37heaEE6BOTNL/br4defJFsot0ZCE2A+MB+klei1SmrnEMrM+QAbAN5WuR9Kq08XxE H9wFF0kHU/d9rqTawHB95RxvBz1NXjCtfOU2xBCVL83yTnoakeA1OxN6oL9gu0lAN8AOqJCDhBOI W2l4Fqv8zoLeV962rvcDz6zLxTUi3HXq0zh21fc8lHuBS4AyMEge7QDGHwjqu97axsVlXypmoJ2p vu+j5Cgrvqiv/5RECN+seaCNF3mzGPfrr080PHdUq5f7S7KOd8FvZs4ZUj3NelMuxS9qf5lrnr4t X2Su6lBKPr+EkFlGecpjOaIU15Imdiq1IO+9u6d56/s5ZpYJ0B9GLIGO1rRS5schPfJEh9L9PZBH YBuu244l3o7yvvlZx/GGrKkM6YcA9qkC/bdI6Tsht7C7ZZOpPh6ajuewiP5Yq0c/KMVR6a9dA7qf HO5UOgArNssZFplmiHHxA8zplyTY+iN/SG/70auLzBeJAeappgFmZ02mJdivsn0154xrPcuzAX3O NXq2QNWHDr3GOjBAUYRGBgK0H6M/yZbxvrZQRfSTDb4FTTR6tg+XvUQP1LEjQX0wRKHx1ekjo7eb hzp21Ga7HGM4Hl0yLlAP7BQ0pe3m13EUgqXCxu30YJkeNnjq67sXYnp6ItUxlb2yxSTklsZ1oss5 Dr2kSFGVjph6XzZd1M8TT4pFeMvLLEXcEJS5APpCRGIL//iCt4C0CixSderfX1afKoVMQ5kZaGjP FN8PeSfAuj49S16fC2zGb8ISc6EkU6PfWydPZhkX5wJdrk6LSHiZZkKfT4H+YfQdpf/3TdkH6/B3 50+37+C2Ugzyqn+W8vKeYXmp9kzxRvn7/KPEuyriYfGteFx0Mz0g8kyzRJZppqjHUww2072UHcKd 5jRp8toxbo4fIeTv1X/XbX8sFoh3oOvNYql4XizG/d5K5CvFTrGi2Xy3ZNurxb2Y97/H79DPEnXi j+Ij8Zh4GdgNPTRX3i3Zdk/TU6KraSXmymLwvVR8jl+q6WqaL5JNC5vNd0u2fUw8gvn8Z5Fh+qPo bZotsk1/AL9/ECmm+0LyDd/Y5Pndkm1/IhaKf8KTbcHv168SS8Q6sRL5lWKXeKrZfLdk22vEfZjP M8UhMVscxTeJ/wu+ZSuwB3oINb9jkXdLtt3L9DR84F8xV5aA72XiC1GBfIWwmp5oNt9nom3jfiYe TjhfClMGYjsgRHes8Rlc5yVWRE9z1lob1lq1fnOtm4e98jxxWPREy3bkuQaw/1j3Bqfw7K1oxHNw vx7TVKzfp9cv1+dV4BErgW9v4ERMyeyEFR0CjmBGfoU42USsEZ1N6xG/DGwU34iNWBNfQbwTeWI7 rr+O+E1gD+j2gH472tmDGsSbsNHXEW8HdsJGd0JaryLeiBTxMq6vR7xGn0e+RTXUn0b7FHAc0g/9 J41rl6gS7wF1olp8jdhqItbiu0U2IN4KbBIn8UtgxyDvk/CMVhOxA9d3I94P7AXdXtDvQDt7UYPY D43sRrwD2IV1eBfuB2xDvAkpYiuub0C8NiZ9hfNjofT1fR+X0RfQRzTFF5hlfEI66loBtbeGT7D3 N5zressGH8OzlbEfZKP1wyq++9YTEGPn3+h+j8r/BeW3Ab3h4xvCKWebhkshUtko4zio82GIMwA7 wDNrnPRfQ5b3vn33UZi262mzzDbnIk1ZUA4cJ32jMXSTvemufO9vsi/KeIXTUTh+fr0nqXuPQuvS 9R7SqLL98xb4rjF/3qKSwixcMwPjAfLJPlSZA2n2rYJ6j4tjII2qp+IpKGMbDKqOOr+jqNXfb7p8 eUXg/sCzc+YWvLj+q8J9U3D/EMwT4a4n4Jpx7Dbk7QDvJfFzyEuQLoNgqRuWtwVUOLP3m1SrKq6P Lx5zgVnOOJbIkgpr1tfZuCckqvPF22kjpvG+z76fXmAGa+Ii1MtAeU7thltLETOQXwan7y/GgPKa cWtvFbgvZsZsTb5y7a0DPe/9lpfzLr8hmbOcsjCGgXpbt9eAdvJLtxaLG4/zN7RIO75D9bSKd0uS 2f8iX73qaYzvH1w9LQGfJbNN9Xk3JVf7ar545Pxq8O0fi7q3VguasaAJvt9E/mlzeQDn4/CiEYUs mwd4AQ86rkXMwDqcu+QlC+D8Hg+oslykCVBe4IuC0my3F5AOsA1fmO73G8oGWN4BUG2ejzT7GQMU AyrQVzBwHjnTpNWZNtC2ux1cRKpI6WcV+IXhgbZai7TWWkYk97N68Xvd3qTd7bxJzrQRyaw/BHRs 90KA/KwBc3y/+Z54bG3aNOZB8YZqXsMYNeT14A2kOcbBAPlPAgz1w8rkWtQbCKDrwPf3MO8LTv+9 EqaXvV/vL9P/Kr5Ip9Jg3TsG+WJgOZjh7/w+jgrFuHC6slJtwyYD/gnNN0kWef/H3pXAU7V9/2O+ F5dLSEi3REi5pEKlW+ZQxjKV+0peaOA1oEGXeq/5pSgZqlsZkgYvKUq6XvWKCvUqaXIbJI3SqMl/ LRzdxH28er/83v+3P5a9zjl7Onut79pr77vPOZAQ+wLb2Nl+IetFnSB5CtQ7Ho6ZQCgz/GYoyqwX 3B/8wXdVy6h8qjPoAxLyZZ99x5gsB5J2qP0dkR9Z5vdsJ9nP2IaOtPkLHB5o0i3Be+kGZXUOhzwq QykXcSYDeEPcyfCpudJ8Kg/kUEQBXFIAnxTAKYWhVATEo7aFQxwPUKb4u7pgG8i2dVR2ndW3fxKH eXBPiEPU0yYcdr6vyPv/ljj8ar0BYWAg24b615bMSNyaYlroB/wOeRDE5HfIGfJsKl+eS81S4FM4 igwqXZFDqZXnUMroWRSybLzvtsqGIv8RLLdV17/xPvCFJGhHe4E8JEA/oZ+JMjm6NF2uDCxpjHSI jLM0X4aQocsRMgwar8t+h/zfch+VII/zIA9818p9iFEeXJksCls2hMKUY1AJ+VpKjFwMNUQ2hupM Y382vrWls98LH/+W++gDcngKcvgRYslmfLAVy6S5CnQZvrwz+JaAEflaKlehlgrf5O6y+Phe9/G1 Ywy4+aDCnRtjdEBWF0FmwRA/bMYQUz6EWiufReUpAH4UmVSGYgyFoMdQ+HRelx1j/i33cR1s2hOQ Q28BDPHlGNIMmKmxZbnSHBm2dK0MXYYhR5dh0sq6LIb+LffBB3mgD9YX5EH6YFkyPEqILIfCkmNS 6fIElSvHpXJkuVQ2LaTLjjH/lvtAOdSCPKZBLNU8xoQo8qWzFBgytfJsabo8YESegGNCmkdndll8 fK/7EJzr9YaxAvx0glyb3Qx8MtBWoBNAfZsJpg3/sTWZCc11kmsWuKapAXKGCNYsWFJ8Kk9OG3ic b+M8h+ThsENzmz7NeXFNjBxvQZU+W3MR1kejYOKGfYT7Ob93Hy2HhpPrOmQfwZqdFKwX/ON9RPYd zmM7oif9IJ0qEKYXDKT88Hw3IJQr8uR50M/GdSzs8yegBAoS8Nww3LcZxAw4x6DVyrDkamVq5cAC y9fKZNGRsmRCFOiyWfQQIKYsT54py5DnQsyggd8JVCYbosCCmAvEpnHl2bRauTJZlhybxqAhcWls WRbEZbIM+M+QY9B4clmyDDkoh4YUIsuWpUOcJUO2E3WxrfZDEzuklx3pQ7Ku/+999bW611k/GXXv KeheN9A5D9A982bdY9IIWWc5QpaQj5HNkidkeXQkngxHgQExB4glWybPkmXKZ0HMpMF4BMSX5Sg4 Q5wFFELLkg+hEfJ8KCeExqQhZYF2OUPMl2XCf6Yck1Ymx5NlykE5NCSObIgsA2Jel9W9f3Nf4W9A SkBglxp/AwJ16NB+Y1JncRwTHINIHn/HwrLjANzLgfA3XQNWk21VhfNgRkY2Rp94Dp7UZ31K83Ly p98cP39mocmuYlbB9K3f8UQ+HyH4TER7z1xQWJLieE8aQOTv6sDSgTiNxBlmDT8SWpvAAwxo0zEI 7lnuSDsEn9PoSHrBdgtNH9PdGp8tkWY12WZVaNughM+fTadQD9tTkgeO0YVr2H60ub2BKECTgchz n+x2+9+Kaz32NSQMghI+jXFYNmnbofyW323CYeP+aXGCmAG/hs6BC2B2iBMOVjonHBIs/X2QkLfS IfO27w8Ro7C+5tDCoy6iziUDxQChzlFY+qIs4E2ASLkuhzY0hotKNpgHAxlDc0eS6eA07HHu/9l+ XzJrYyb4h/2KPNm/jTz0MwEbfpVZ/RsVCPPoAwn2fV84RoKAP0WSoYXH9pC/S2B/mjanIOOOfOcD 85Gy+nR/TQWRfYznyXEeefJ3V3Xg6UC5DvAsgY7w97jnOljoFDiYguxMdYY05/P3gTb/Rb5gH1Od UB8LIKuWfKGQL8FSeH2hPlzLYJ800Jc0S7K+E9DOtL/IV+CQZpnrwAVKsMQJAKhgy/M15yE/1usF 51r6GHj0qzGALoKuroE611h6gq56Qpv9fVzgnl10zoPOkuUNh3RYLho3VaC5oPMnQQFCZAhiHlwg +xplQ8oAWA7Jo84L6EaLbkOaFh7lpAtEYtYGeH8gTyDU+f6sjtnHXrlq1nzpZ5/ZjTbflT2/wY6s D+sWaF+LvsLpFh7TtNa71u/KxjTkPUO3tNiITOivZdAJo6G/TOCCBKTzcho53MspeZScNxLyI4eT ebG/SB6Sdqjv+kBC7DuUK/bdf+Jd2ccSNKz5D+qs2pMNNP2z8bAx/a533yy94DsoBPn22iOYRpBv L32b7Yf7FWd90sXe0Ncg0pZxR6P5GKBHsICYQChvBpBIM9EhJgO5x6r18Sd9bKMPoQ2oayhvOpkR YulWx65wHAKVYr3f613ZQzTo06D6Dr2/AnFChV34P8HzxHshT6t3ZZ8X9kwv1tHZ54nDzdfKkc/Y TysxJj54Fs1lQ2eR57Df/OE8PMusIazu1vuQMJ8KEMpHFUixmcfzeIznIYi6w78YoDNw30kA+t5g H25AjLIlA+YxA4JLjfsXyfMYI9YxoJ1s+13ZIiMGwDUtIAaQQjPfvZk3EjhmAE/aHDlQfF04xnZi /X2aeaxLkEc74wjEAhJmo9vEEdiB744jaAP2Nd4nHYgM3xNHwt5fYder6f0VIWPbfy4f5YX6gjia DTgi85DP5cOz8TnCdBn7oLM44lt8iSMWlNMaR/Cu7AvC6v4aHE2H+hBHtwA/YSBALUrbOEJbjDor GFCvMXjCyU/vypZwR11H7JCEx//DCHQChK6KEcK9kooyZgNWUKZtvbtCECNzACNkHhIjYO97CdNT vP/OYkR8dMcwAvgU+k2Ir8XIChAcYqQPDCitMXIM7gttx19hxI0IJGYSwY17oPtBejoQOcYwgP87 GImDfMuBhI0jgj6bIN+f1TKmCl070cS5QXHuZ3ODNt+P3Wpu0BvaBebkb68p4BiDoYHXGLX0D54n +wrK/2y+cBKEgPOFnyTJ+YLhQC+n1YPkvJGQNxxI5gVxckgeivxb84XhAAom0Lfs/9bjfhzOF3Z1 /Ns6jemD2v+2jqAOCPLt6YNgGkG+vfTttf97+i1kH6LudCW/Rcj765ag1nfk/XWk/z+3bf+//Fvb 5J02X9pkxEBrvwXGA4awur/GJsdA36DfUgF4R/9fHfBO2gvsN2jOV/j/BNEV/X8S198dR2BbuhqO hPn/m/Y3fytnScd8m3mAIzIP6duAf3FYmC6jznXWt+GP+RJHLCinNY7A/78irO6vwdFSqO8+4KgX jpeAox9a4UgTrpsBQZJ2/X82XGt63zUDvgfyycdB30YfSAdIAei/yecZfE4V1ugufubztH7H7/Le e+05/5TP0+odv+35PKtBMGkgsx9Adm7g0IA5JKY4Dh08xTHOXMwHCfmhg0k/51v4PP+JNVKVvehz Xu7wmmdj+pWV3yy9oJ8jyPdnte0zC6YR5NtL39pHIu9XXKD83iBL9J/JWKP52AFiFhATCOXNABJp JjrEZOjsGinZhq5m29vzkWCNNBDvtSM+EuIE13bC2vCRwE/RFmZfsY7O2vbkcV/adjYIqbVth3Hl iLC6v8a2x0C70Uc6DPYBfaT3EKNsycAAxgwILrVr29tfI+2aPhJpB747jsAWdTUcCfpIpOzRbmBQ PdS8Rrq8fR+JAelQXxBH4YAjMg/pI4Gfcl2YLkPWTuNI3P1LHLGgnNY4AgzrCKv7a3AUAvXtBRzh psxYWAcaDbEgjsTgEvYLwKtdHHk2Xvt77/hFGfUBwnkrrs0J8jaN5TaNB8LWINocb0BH/4cTY2KL NXc6dCMu4yERgjghZUvixHlC0zt+mYCX9tZJyTyIkwjACZmHxAnY/AJhuopt6Ox4YzChYzgBjN4Q VvfX4AQ7MQ0XuAEfI2FQaY2Td3AJcYI+iyOQYMC+xIA4EZxD9INjOhDOJRjNRPqynfm97RHk5QMJ w4ig3ybI92e17fPBHrM8KLIx4H6zZ4U9rDWfBlhSWAaiLDhrAkTuH2rZZ2RR2YF9RgPEDCAvozm/ oK2BU0RtBtve9M5T+Fa8mJgya0Bj/4jDecyjCyQLhHl6A6H/OBkIz6EO920miCyAyNDCYz4/IFMg 5DHGQMYd2WuE+VBuqkBYp2AgZYfnuwGRbR0PPLZ/GoWA9wbBO6KpBDELgIT3dcSxr5Sj5Rj1GMsg 9QZHKykyH5ZBlgdsy1ouqF+H1nJ1IRNZP9pRfyBPIGE68sW+QtxvR5weLc1qqlMV8jecDfjs25Hk fjCyvo7KoXUfBpxtgNI/3bPg/VPgnrEPmUC4t24KxLi3Th46UAL4Ew4aYiccQhn+PkjIa4iRfYf9 RfKQtEN9h/2VDBQDhP1FYQ0UZQFvAvSFzndob53hV+ytM2zBwECov7P9TOo79qcpEAYy7oi+Yz5S Vqj7goHsVzxP6i3yw4BAZi17znBvnQbouyec0wUiQ5NVbMCXD8P+OxWxAgc6yI4uNgSO6UC4t47+ F/mCfehioT4qQBot+XBvXShDeH2hPuGMYJ9I0JdIBlkf7q2L/It8BQ6RjFyHcKBQBrkXTh3aSgfC vXWhjL/aWzcV6pzK8ARd9YQ2+/vowT3riZ0HnSXLGw5lYf+NBFIFmgs6z4YY99YpgM53Ax6xLYgR OGzR887aCCwHdf7v2AjcW1d4ye6ztaSusLcOnwXG38pKIUYb4eXUvYeX0xxNOW8k5Lv3IPX379iI PlAmygB1GPvuP7FuhHvlCjc4dngdqDG98qRvll7QbxDk+7Oa+gK64bPfWgXTCPLtpQcVRpVvDpyR 5P2Ksz6V3xuuIjbIWKP5GKBHsICYQChvBhDqNRIdiAydXTci24B2DeVNJwuCGN1BwWNXOA6BCrHO 77W3Dr4lexyq79C6Efnb2vy21436C/OlsY7O+vEXf/jSj2dDZ7We78Ic4piwur/Gj4+BduO60RCw C7huFA4xypYMKDszILjUrh+PdrLtvXVdc92ItAPfHUdgi7oajgTnw6TsMcbAz2/+bW1t+/NhMg/O hxcAjsg85HwY5qS3hOky1tNZHA0P+BJHLCinNY5g3chAWN1fg6PpUB/iaCHgB/fWFbSDI7TFjkCC gfT7POHkp711TetAWnCOpD7Ak2O0HAwOunCMNhj7HK8hj2UJ8jgWY30sIGFznTbHGtDP/2FE+JoR qe8kRmq9mvbWEUc7hpGFgBEyD4kRsPff/DuE7MCOYQTwefufxAjurUOM4N661hg5BjqKY81fYeSf WDOKg3qX/wVGBH02Qb4/65M/pg98XyhHFaj1+gHurYvOzLKUZn1aP+iqe+vQD8H5Ak2UnC9IyXg5 +dPlvJGQl/rsuV3SLsFtd2hNobWN+k/trYvun2vZnrxa20DcgxPd/1q76QV1QJBvr3zBNIJ8e+nb bk+u5fe0yU19kmsJavFf4f/Du3J/gaZ2yv9f1Lb/byTMLmIdnfVbxGd+aZOZgLvWfguMB536piWO RSpA6A+gHVJs5vE8HuN5CJ89WzMHLqL/fxBilC0ZMI8Z0L/J/ydx/f1xdK3L4UiY/8+sbfL/6Sc7 5ttEAo7IPKRvA/7FvW+No+E/fYkjFuhsaxyB/28srO6v8f+XQn24t+4wAAb31r1vhSNNuI44giTt +v9suPZv3FtXuIH+2XpoV91bNwoMH+6tewIx+qBTHOUVpzhO7y7mg4S8vCLp5/y3rJHiHplCD6UO r3k2pr+k/c3SC/o5gnx/Vss49E3XSMn7/Z62nWwDjqM41tKByNBF10hPYPs6s7ducRs+Evgpp4XZ V6yjsz7Sm3lf2va21khhXKkWVvfX2PYYaDeu7XiAQNFHiocYZUsGBjBo2/9NPhJpB747jsAWdTUc CfpIpOzRT8aQ9aJ5jbSofR+JAelQX3CNlAM4IvOQPhL4KUOE6TJk7TSO2Au+xBELymntIwGGi4TV /TU4CoH6cG9dEggU99bdaIUjWBZq7BdJiHHNUjAIrpE6El1rb10h6Oj/cCJ8nZSULYkT1sSmvXWn AS8o27aeQSbzIE6iACdkHhInYPMfCNNV1J/OjjfLIzuGE8DoUGF1fw1OpkO7cW8d4gT31rXGyTu4 jvbj37pOinvruGoKn62TOmcRn+2zuuKZ8o89j0NkOUPvfvqtBccf0u+nwKLceDhmAiWBLYuBeDzI aATO+4C/4fiz+A3HO9RMbyTkfxYn8/63zBmKUtWh/xntrnu2XpdsSh/wzdILzhME+f6sf2bOQN7v 97ThZBtQ17rOnGG1nBRjtRwxVYzI5TXIbgPDZBcpThBwDtZVoaURhBi8RTIGvnWPdt0K3gN0KfTU vNXy1xTxPZC5OifmzdI+MY8C6VmQD9Pg98vwHkkbDv5GyRd2FK6T4wTWQYdy3aKOzzMViWjMT5YB yQgNuIbfMEMegzscX/DJn4cxfG1uHuY3982fp2FdtYRgNdWP+fGdRWQdjMa0UFZp0/fYKM3fY/sa Gx4DtZ8D+5ACsRbYh3sQ432ToRswZkBwqV1fxx+u/TftqyDtwPfHUUCXXlclZU/qH/9N05yBWdq+ L0TmQV9oCfhCZB4SR+CPDPsCR2UfIkGFWkJnfaG4ZR3zhQDDpcLq/hocoS+UDzh6APFy8IkMoNME cYQ84uivfCFXwomwhFcpukNafSCj5hjHZi0gcoz+p/dV/A8jDbKs88YE0hYhz+KQciUxQvdr3ldR 3z5GyDyIkaWAETIPiRGYLzwRpqegBp2eL+Su7BhGAJ/DhdX9tRhJBGwgRgbBgNIaI3w43xGM/BP7 Kh5B3Vi/sL1Hgj6eIN+f1ba/1/pZnMbn96V1rCgspihkafu5hA49i2MkZgD5GUD4XIOgnYFTBN3O w56Y0hOexSEIZZZR47oueEONcwFdiGWBME9vIJgnEJOB8BzqcN9mgsgCiAwtPObzAzIFQh5jDGTc kWcTMF8/IFUgrFMwkPYNz+NYQrZ1PPB4z4EUglgPBawDWxsq1vQsjpMjV8nTcrj6Ustw9QjH60pk PiyDLA9YDsnj/EbgPkfBNTK08NhGXSCyfhvg84GygITpSCuZ5zW+w3bMJJC5sSgL8poAocwgIjr3 /NUgoTInek63J3IZtk3PXw1qkbkx1CNwry1yhNMtPN7rt5Ap2b/tyW46yA5cdGIPyG5xs+wmOD1U n2G5WD3E0kTd24mr/k/JTlUFZAn0F7JD89MYcE/Uh15nrH5OS/rsN6b23s/e0Xetk2UKvmudwjIR i4FalwKhbtAaW9D876KSHcE7sLva8mfbsunwyAK3cACH+6stwSH2nJ16w5YgVhhwuHJ2eB1jAtJj TJP80a7x+sU4OIb0EDfmh5jgLTXA6401YPlin8ISODmIZSKOeo9Bn9X+PjHyXgTtX3v905sl1ogl LJPCEpdwV4I5GhDeL+pL64DnVjiPtaVJq8GIQdDs7axcIZ4JtJ0iCf+5oW9MIBKZ7Wo7mthbolED B+I/jnICBP+2Vub9DxJwTA2x85oN32c/jiRyatZOfzAqx+ytRrmHT3q8edlPWnnK1uU/bF5y2cyn pGLj7IPlNQ2Li0xV9lU/yVx2cfpKJ2m3n2/H3OhrrXE9nmNz7OXlt4fms1/yHkRdEsuUGi+/W9Nz RNanE5PSpG5OKAhY+8p48eO3Gxte8zTL3qx++XT0iKzu3IrSvLLSiBG9hl27tWBzw/z54el+5lef PTWsPPTjw0VPx458GjkyrTzKXHPbIu6cIrvMwieLnn549eYPv8sPs7xtbe16GVSOvBAUcuf1i497 14x8HXnz8kNu4v4+KYcc4lcfeGMR5cuXPOVO8ywV33VHK0V+w9Oegc8Wvc3fecIlZgmkHpsk0T3K 2q7XwImDLtx+J75fKuvV65vy60oMa0Qy6wfOzTK3GP3Wrv7mOpXK9NJVhJadXu0lUQ2JCW6bzCfF WHhzIt55RmzJCd9yc19ppshqi9pLUUeUmKPehovYvLNKrckt6X5aIkSq24pi41i76l07grkWXiXb Fu26MMeX7cNw+SGNdfF1kOO91Rc4Kos2cc2Y5pWjFh0evpjyeHNdsopfta8ap15WqiiMyXpTcnap cZbNn8uS5L1tePaBrNm9bPpdSJgpmqovQshyLGYHbR2w1uvPUCl9jty6p7tE/NkRZbf1LN9vDpMa O3K81tDRz7nHt5llUR7MTo23WBzkp4uJS1JFum9y1aan8ijjpCHHi5q07IDRs1TYGivkBi5R8bjH SxloPjGL8+LkhYI5QX4DG/NUjeCsJnZQz13sFx6Wma/CtHkge0CNySZq+qcuenmxYLxmdtqd5DML wvcxpLmZ8s9XNAQXxtZMlxgwND13RFwaVyz2l2JnatAKXsGkSe/+yFiUPTzA6ZRZ9yyOEkuPmTiu vmBL3RPR65pjdhzn6PjpZC8ffX+6+eaS7lmn6hpmbb566MyUy3OSZ4vInFZhFfikZafnG1zNz2NX aaQWbR2RzC2KL1pL9RZ/tfmnj2HjHi+oMgo2L8ljrSaMthlv1U16urEmP7gq5/ePLlvvjYkNjCu+ 76kU7ZrCFHkXGfFYKv3V8bpNg3tW+zLqJsVRrZROs2Pq7w6TkB90jqX2LGJoRv4A/uRcw+eq24pM pNV6jq2WUeVGul9d6/DOPjV09R8RrDmcAeGbApct84gpXRX4+0SOOvXdBs8/ewyYtlPEo6xQV8LN rnrY7q0bq0f2f1y94Q8jteqpRA/ZtalFr4vmHK5YbVGaaZBjcqu2YOYfh/QmuNUE9Te5WMWLdNky 0kPt1DRO1Yj87rU7PR6c4edVuPO2W40Y76mxpc+549HXFK2LreYzo81+N4i4u/yCc1SSjbnaybJ6 Fn2338aGhl0H/CZA/uR4EatCXa/CVXG2rLu1msXPj1DGB/Ay2Abd7KXKFKJtXtxfp3XvN4nHNeKj eZFuWxoOXjC1ETOoDTfkG2113Xp8gcE+MUNJg7ow/XXPfIJ0npfV37ip43p+x8LEaPpZtZ6Otg5T RSV3V26++vSM1mP59LRq6PUerHqLwtgK9wP2u3i8lYGi9z7qON2jmOp/3Dtk6DqjaPfT+1jiDUsi 5kwzXuW6acnbKWbxr9Ld/pwtRbUitlvwHRbx3C4WcUS2uP7snWWsOFVxZ8+S8hr5II8Pi8auUXhQ rxZ5zilldKT12rpAV7Wy+yFcEWKa3IPSqojLGn3pEVsvVtf6D1HO0vVgs0TGfRx45unMYv8SzvFe J8r8cmwXrpDSkq5XXs7WlHBKUyBYYhf9xj7e16wrdxfxxCyWsGrvPleacTlauSrMoufSot1V85Yl vOphtC5R9WXtSMm+K/v0OK+5Wnec24srrmrO4g9nVTUgmpSHT9gSrSJJqVVl8txS6sPVPM/7W8SV jyh+lPHkgc5sFV93n4A+Rg5Gqr3rFuiv+XWPHk03+uXrusVXj2yrmVtyZyFxuO7u87iB/oXSYmec Anbv0nUOzHjC5HsXOI2i6lgVrFFYuZjbJ+qqauF5q4BCu3t/ppiwrdgNuvsiutmVdBs+4ebyorgH zIdWCb/t2s6y3rWKGrFRM25tRMVirQJayPvlibO0fjzj2DdAX1JrzvQXgVo8Y47cuOI72T0nBRhP iSvirdr1PP+JMz/Asa+OlluSft+9Q9b2WfHIvw9VzTnJdq1rYpKVyNsfzQ5dMpV/aV2l57muaKH5 B5pXXMaJ4W6bq+fKXt8tO2/DC7ZkspT2LtvDs2bnRCituHrfdFTs1Vp7VrDeDMlkvh47NHyPrpuO W01UZsm5qluFl+5dy9epdzbPv3fNOanf1Z3nLBdn0LZasc+7Xj1W/Gy82G73flURWX1iM3TdrAPH naVuD9r1Z/7E/oNPS5dVaRm+M3TzlUmOXh9WvNV6w4nnQyLz+9j/vvj1DB+nuyohmrsPOKZdEKs3 N/hlZdnOXyt35j/J4tvoa2vG7YxJrpqxyd56vdF7W5FNdhlrxtronU+nXjl25rfdNbmOGTcNLz3L 8+LerhHZddyY3VvTQUvtVX5Jpl72yeozxXsWvrUz6fFw/erRCfYa5rfmOM0YV7Xp3ZB9q08fmqio IdZ3l1y4rK7ohsQH7pxI3erVm8542udJm6Y9ynnip8darTNVZ4o0/ZLKoiRRxdczdloX1+gN2GXo tsU9vt58w3E7efelJe7pF3nnUt3DljO08e5sY41ujXeOpm53u5/s3bf+At/YL91V9eMm6XEqKad9 NXUOJ9PG3K1k9hwU4Jq6R9U+oID20sr6Q3r+xpyNdUpTD+rrD7qneGlN4plV8bwSkaFBOs9miQ5V jHtEK3lu7nhggptNtNLQ+KFSY7UHjhML2qC48Ocke3PbwUUGuj2ezRh8smau3r7qh5NjblPNAh1K fQMc1Pe6iqp7+O52mq/GVZyw8YheYsrduwEX+msbUgemSW6JWWsTv0zXfK249hbJaTedHLoNpzGi 9ljH/pY/WC3uRZyKcnXx86Axe37J0z48Z3YRR3PFwLBxMiUi6anU34boDarR3utDpN/fH6/iq+wb 0MdeM9t4wp6dvg5i3tp7d7tGGwdFXDNbeWfQoEt5eWcDaAff5CU+mLd2oKHIrxqng2M1nQ5e4OyI WuWhtJV9ri6v++YevUTSE2bKO3rX+9yrVHLSp6nSxthsUCkNto6vmLNWx8snMGplScHHuqDAwi38 A6rTohYMVHANLU4Lv/88u2FNmkjowaQHoxzze50JzjEuv2zCV1y54ND7zTtLguO9l1UUV5v48B3U JlvE1+euOls6IKT0zzFh8mNlJh3SuZmdLVKtP/D53ElHku1P3Nn9xqO6OkD5EO+o1+EwSohPQL5X WO6PJ/3Tdl53u/1oelRahLey0oBNU0uePeiW6XWyr07ljkE3qzceVsld4TlbJblcd0HqwK2mR+fc vpGU/rxCtD53euKp/rqhkzfsNLPZmKiw+NnLjTLXF3RXuGGSm+ve+8wt79khu1y2uD14UJ91/s4O 5bjpkz1klgcEb9TKFlc8uzR04dOMHdmiBaaU51m8EX5Ko/3N1i895eGXVLgm7vD+h5Xeq5Z4n6za bWMvYRmbHjqe7e5y9LmNcnqP0H1ef2gvcKSX/5R3+fa2iQ5+MteTZCzfX40+Ilnuc6lqwp0TJ0fF b1E2DdvIc/DzDjbbbzdk4JTcK/nXzVb68Lfs06vt+z6Lf3uu6G9Bt2WWppjeOzhpvuZMm1ALh5g9 b1dmJt05yeiRe1Pi44+lS0v1Z0YtyDYck+w81dVr5TAD04+nEzOG/y7+IEfp9eRBt3ygJ0f4lRfk lC0c7GYmOrZ7eL5Or7DuUMuDVVPk9+SWq3rc/Pm2Sq6Y/sy7+29JzIxyMJz8SHnjhzdm8RPP9eUv G7rhdUruTckhYS6Z+aeKizKJ9BUXp1sMnLnGyHxYyIv63MTb87svPpEQdbzk1ICQWUEbKiR+PRL9 p+gvFakyWtem7B7czzAr86bohEr9B09UZFz2nT14etoMu+zLHhaVu94+Wl8+3q3Cm36EN+LppgU5 VRFHte8PPhlIfXva+l1BbJlmPL383q35Ex6GrEkujXyXI+Yz8HavGzcjn88v3ggtrl50aqZospRe Ts/uNrEhlUnrzczGz584P2m1g+7YIzVG2ZXes6LfhT/70N9239oz85R2DVD15r+t4c1M25+em/BQ 6vb4Hr4Teu4TqVxgu21PsJPNXrsZM6JMs9PjV92N4R+oT3w6r4B3dKhyLiU3N9t5xtbYm/OWlfv+ HlIypyRWQsdT/kLyqQv7g+9Mmm7eb72m1+PBh0ed2/No9uhQn2tTVxssPeoVEnnpV9uNz37KvCx5 VWvY8ScJpTl1h27+smOQevCxK6OvDFipLrFMrzDFd7ahoYTegmj1vPwHt/tvCh4bevBKfs6LuTUL Zz6cKWM4l/qsYpS9U0TBDJun629PqnmoVn99fIjPmIkpotndH/vJ+hpuTbI/YVuXd/5hlXjKIedp JonTq2YNUu4WteA3tarl+9QHLLq0V+qYR0jouHvh9cxA+uUAE+XamuRMvZn+3UekSuyZWOZzrXzW ioG2jv6zQp3PVrobmV3cG+GjPOFIxdbyAcH1Gj0H/VQZFU8cKl8k5X0oMO/0vGXVVvEVjwff8L1c lzc9fVvFjRfb93uPUa/4cH1HUdLpyhKJ+AHlD2co5JyaeX/BkjPbi27+YvLmUKb2zUF8726Ze97J 3z8cAvVuz7aNj0u50mC1gHvAsXr1LPWjs6fMuvbWMkVEq953lo3vmQs+R2iXZl66cDU3YFbI0QWp r2aeW28duyPYcd5andfSrjt9XgXI7FcuqXhguH1khlxO3u0DYi6PXarFNpc6983I0a4W1654NU48 eEJeekke3/uQlttj470fzU+VzxCp1jG+5nxgXmXu5XkvC9xvAczeX7+v6fds44AFbw7vZI0IS7XO yVtxcc8pOwdP+eOMXTcyfpu7hndpZfFRvn/K/UeHphdFx4WLhWnfrd50dg/fW2f/vWsHwEKoT4gZ 4JZ75fI4n82TJWcOscu4YTj4SPXYIcG8qw6vw1aajJj2rDzlwNlDOTO1bhxRf7ZtjO8I7iD+7TUz c6KcHgfYJxSt9rGtd4oVL/1zqQLbSykh4bT3zXuHJie4XLMOjt3Bn58tUWFzLbHHPu27+hbvEuNM LZ8oK+uVioieVz81PFrpwLQ+XqGv3NVEVqwsysl3Ul9hETfbVqY4VM9u39awkRaHb7ry919zeH58 0KXAh7pDE8Sl5UpXlbEYxiki50c9yPt1GPPsjkopjzL3q+tX7B5w7LiVTeW8XG5K990vdDyDD/Hn XMr4JeMFd6rxhsptqmd1WOAHGSxJ+9DPR8c1My7bi7Pz4PmlPmKLw6zXRPLt5tTcW7/C2nrTG/N9 abojnPUMVhm7SHwc+5DpIlsswmWY230c92dohixbfLh+nx3TJqrt1nV1ONPrjBE34s3WDNq0Hd3S lokMvf2QqRWqrNqTq7d1k2ZZ6Jthxw5XZwyX2nI2bbsTx5QV9RNbQU2MNeb5KtMDdzI33gjcfvH4 YsmJ7j60xLRZe9XirLQPLpzoG7u+au4k6efX8rjm5mNrnUUKpT9KhddFrBziQqdJwBwq1djjQ+oB A9Vbs4hE/b6RC4xGqVfUvwQvf73x+vLzIls0mbuM7OdcmcJZVrf8xX1/pdHpDouMt3KK1HTWqURl GP/OYwVu+lFCy/GNKM2Bxy3+vaFisPaEoeuqwt4/9UvL1TQdmvDb9t93jp/8pHBlktOy13GE+Njp m6wS+9gm2LhrbDvJtirLH729dvGruozjHHUR3dgah0sbNNlBB9yWBMjf17Ux2zGxeMcgF9GVrB7G m3fKXyJG010mT9fYYc3eqTqymMczmaLpkiilpUub9qRcbqiLPj177YAqa79464SCc5I9B0vLv9ym JkVJvsJxiDWMLfYuCyqklHk/1K4/WjFf8e39kIYAx7S4+ATHVIqCpjSLajRt1KKdkvRoyukrpjar eM5GQZEGTlHL35nones2g3tu7DWNEqsg8Rki6bqxY0/XDVtmy7td629e9Y7QXc5Z7XTKRfXe+LRQ 8auWZn45dqOCPez269aB+0hcdgxwiNBfZf2n3kszFpvQDtbYsY25MIGTN/K4yXxG9NtUE3mbNwtm pY3uwzx6anbcqWl/LA6fak2dH2BuNEOOrsoqgrnYJu+z2zl616XUFGbIWhmn3nD/OUXKQHNkP8/Q 8DFlzwbP2XVB4j39ntu6foxprKLEX8XUY33E0lwvHw8k9OiFyQ6Be/aPf39j2dB1PryjE2+mTJWz WMW3GHc+LVrF8Ucag8lZP/jX8xzanARrSdGtPZbQ3UfKnHPwVuA/4h27Wj/4pJ7Zqco1b4fztxEX pVjut6RPGIpES8btrjGtLu4rrbo1XWPN06vSA8TCBhM+x3IlSm5tO7ylzt88mEgdrafA/A3muXkK qmLRUefFVMrXhhekBe5J8vAWn5hdr1W8qma0uKqHrvb2P66Y6kzV8777QfYXlw1rDLKPmG0d7xYg 47snrceHSTSGtMspsVEMF+c9NcOXeTyfakQpNLabejdoaMK+c4llsx1/lPVVytddFKMoknFvTF25 2QRunOOp5S68SRsCNTy2LIzWHBydzbXWNhaJE/0/9q4FLqoq/5/BYRxggFFRMa0GxEK0dtaVJJ+X h6abjMhgkmmSyQwVFeWj59ZkZVZW2PbcVSPL1uxFpWWuJZpr2pO/rtmWbuzW7mZZ0cN0S+P//d65 Z7iDM8PwUmI5H36c9zm/83ucc+659/zm/nUjxhdl5I3a3f8/0fdtvu5fxd0K3xr692WTvhj4Tb+d Dxse33liir3fquVfTP7PF90K04suO+GSiq+2/unLKMe+BSscCRWmnK4DxbWLi/55xasz7/lx+thX 8m9478FXTyiLGPHYyK6f7bt5wUPmCz59JT7i4ZyBb3cpn/rcmoeHbjoy8/vffdXlNwPG2db+5wQx 6tbTynr2neZcfv49m87utSXH3P+9dHHxKVcYvsh4dXLZKE+3nK9fMSnfX/DrD1/974orfvXZB18c esXWv/zD7yYrz51+6IPoK3tNN1rvP3fEa1WXDhh66LWTtp0/d/2BIzff+Pfhl6755ws9t+z/qdeS mANVgxf1nD3dvGX/G6eXvTjqpXdn6k/V/I7ZnjpQdaPhH1cN73PxeRs9ON8TE8Y6cp7NKloAm0WK UeF5YCqA3+nxTBuOV3UBe7Jwkze7CyLDTe8ZVwGGm66ITELcDBih+T3g89yTZ4/nATwMaI5t0rHd cwA8Xpys5fFt3LoYgjfhctNeY6np78aLTR8bLzLVGN2mfxiLTZ8YZ5v+ZbzQ9G/jLNNnxgtM+4wz TV8azzfVGmeYvjVON/1gPM/0X+M008/Gc02Rkeea+kROU8EWeZ6JMCByugoDI2eYCIMjz1fhV5Ez TYRfRxap8JvIC0yE9MhZKgyLvNBEODNyNuAi0+jIS01K5DxTJkCJvAbx35mGR95gyoi8EeVuRlu3 ov2F6Os29LvIlBh5u8kEn1BnvE2FH40LTYQfjLeq8K3xFozhFozlZhW+NC7A2BaYvjDepMI+owdj vlGFfxtvAB1+p8InxutAm2tAo6tBq/mg2RzQjvQbCVKSN9kAyRM9f3pq6Ub4+vA4xBMArFvgyMsz gYfkUwVOkYfj3Pg9VPgT/DIwUMaRrTr1cBmhPIAd4AHYePoMt1B85T18RpgyJssaVGlhicAOIhM4 o8OmqmYddKMLHPfQqaUC59c3ECTfbF5EHkPbk+vL+sVt3vTA+Z5FcB6/8t7isr2IZK3dhvW9xcyL 7kADav2xWkVZ3xtPTk62qSl1gfLR/erVq1QEAuYLdK8hEDAf3a9eHar/5OTVq1eoCASsz+6BAFkQ MD8iOQ35KgUC5ZvNdyDbi0CgfKDPfJUCMl9RVHKo/XnU7kkAT/P65/DhyADZvrd1Lc7hawSQ+QH6 X+2VAFmzHj8RkZaG+n74G7VibM87fPQPEZTty1bUuEo+LwNkvqIhwLiGvsoAmR+gvl//+nxf/yBA 4PpHjR/dK2oT4fTvZf/qtGTUkO0HHH/Q/kn+1Sv09ZvSv/DSTxVA2X+441fLHU3/Jo1f61/VQNl/ c8Zv09HPb/xe+Q/O/4g00q81+S809qv8rNe/ev7q6Qv9JQJkX2D+S/3V5fvVD0//GtF/Vfxksz5f 5YdXAdQJUPJHFvDGw5n/1O594/OvDwJo3QdsX5t/of5B6mP2XqGyL3A+5/9VoeZ/LgBejAL2L8xc v6B9wfrHftcWqr5u/Qu0Pnmrqv8D9y/McKHyfS00rO/NaPH6X9++RieZ0HC9Pt5xiVdwvzX2p1th FUjuSVPRlQwH2p9G6FDh/pTPNT532GDwhRlo9TgkVu9avf2G+DevvxvpiGeT8dP6O3jwqoOh63/M 7GDt33gV3I3B8+uO7N3L6nWHA4/v4FXz0ECI+nv37v1Yrd+QXmoc3U+ZMpUIHDV+b3/o3ovAUflq fXQ/ZUqo/vfunTJlBhEIXJ/dAwGwIPD4juzdhXxSIGD9gwfnIVtFIGA+qMd8UsCXv3EjWkOc47tR 7Z4EuNGXr+bK8o31z+HDgQGB63P4XgL4xif7J/20/qeAAYHrH9m1C/X98P/Ji6Ba3jt89H/w6PqC +q2ST2WAr/2NXgTUuIY+GeDL9xu/t75f//p8X/9XBeGfbvya/KH7jWwirP695J+ya6+OvnL8HJ++ f619DT2NHir5p8zQ129K/xr9KIA+/mkdqPg33j/Z50f/sMev4x810McfOX6Ot/H+2b1f/3V+4/fK v8r/gPPLkV2sHxb/A9O/Xv5l/saNKgUPiwif/HMC8o1PT1/oLxHA8Ovz/cYv9VeX71dfJ39yfLJ/ 4hOe/lP86vv3a9/LAE6AR+HP8UEBQYAZHyNwVL5KD3X+4/QTJJ8EULsPkq/Nv1iBAson+987g+wL Up/z/9TA87/GLywAqB2gvujC5INcv0KtP3Vq7wHqe9tvdP1jJ3RBxld3EE7N1/BVC7N8ePHg6793 fLK5cNtrfnkpn1oLYeLfgv5U/unrNzxT7YozVW66LQCWY/5+pNUA+H11S76FTlMa/964tcqE892y WTEZuZ/uB5Df7SNoBXhU8IwYKyosY4cqJt/3zS0Zv1lJb1ffgico6R4Olqcf5DVpQb6D1bp7BR7+ BILm6sN8zmh4zwNNqOUG4L9sp4cuLN/FTEFaHkA69k3Hb+MXFe/PW1Q8ZNJQ19u5ZvfbuXsAt5UM mXRbyf6820qeyN/jthSYAUNdloJFxU/ks/xI1DMDRgMSAYV4B7AHg7odfmZk/V0TjkvihqDunogn E3HN1Yc5Rsp/EaAAQPk3K2dEKAgPBUiZacpdj55Kuu/+xhloo6k0n4k6GQCOhT6d9MO5n8N6km/6 Z0W2I2nDdMk3hiXf+iJsBYwuxm8C5Xl/U2Mw4tJ5uVhXR3kaVzw+b3rxU5MWFJ8waU3xHx2FSEuV BeHLsl0QXlv8oOPl4vscrxQvcZAmVsA36MPuCP17Id8Wn+Y4UJzmOFh8quNc1AnWfm9XXe5o1/u5 F7nW5obCo9T1Yu7lrsrcOa5ncyUeD7mE+ENuaDyWuh7KrXA9kLvSdb+v3luod3sj9apdt+Xuci3M /RAg+zO4hVjQSD2T+6bcGIDVvcBXbxjqLWyk3kj3wtxM922549y3++qVot79jdS7wv1A7jz3Q7nX uP/gq7cc9Z5tpN4Kd2XuSveLuavca3PJn2Cy8pa7Ovd796HcE0pSHYUl5SFlZVrJfY7pJQ86ZpT8 UeU5dV86KVNmJCwu6T7phZLHJr1Zkpm3o2Rf3pslSyavKTk9/56S1/JnlIx2hpKD6SVZzmklY52F JeOdofA+ueRJ50/uvzl3uCMKVrlTCkK1udJ9SsEK98CC5e60Asnra0DD0ZhYQtWb584suMKdXVDq zvHVG4d6eY3Uy3TnF4x0OwuGAWR/VtSb2ki9GHdhgQlgcE/11fsQsuxspN4ul7Og2pVf8JYrz1dv JerlNFKvwpVdsNSVWfCQa7Sv3hzUS2uk3uWugQWlrlMKLnKlFITS/XGuqIJ+rhrnweIXQvL8QPFz zm+Ln3Z+U/ykU9LrFcxB452h+fNy8Vjn2uJM55ri0aqspEphhC/lkXPcrcVv5J9fPCx/XPFDk0ch bgbI+fQj9HPzZO98msgJWnOy/hjEvy625ltd5fljXF2dw11H8q90ne8sdU1xLnTNdz7qute5xfWM c73rCefHrvXOHa61zkOuTc59rtecVvdmpwGQ6n7N2ce9yTnGvdY5xL3eOdX9hDPX/YyzxP2Q8xY3 rk24Zzh3uw/n73B3df7sfjj/5JI++ekld0weVVKbl15yTl5SybZJhpIJk3a4dzh2u/c4HnPf7LjD PctR5j7Lkese7JjqHuIY4j7JMcad4ujjTnSkuvs6DO7eDitgn6uv45Ar0bHDleL42HWSY71riGOL a7BjlUtxLHZNd5S6bnFc6brOMdy1xzHGtcPRw5U56ZviqkkfFU/K21m8L0/SS67zpEciIN8kxG6j EPfAPyuyfs0iCQcALAA4jwx3DXPNJw9Zl+0ka2HyYhzCS5FYDuBeYJDi60OkIZyCfOLF+4XwVKeG Kw1jb714hd9dQ315/X1jfThY+xgGSaA5z5h73usyNuGOx4O2H7D8b59ptfJ6nPXhYPjry+jDwcoH xB/jNSr19E8CNcwA6ffT4mfDVwB2AERE2ABgnwpW+NI19TeIJM25P6KsWGVD8PlZiT6ej3gZOmW/ bfsbRK/PRxdwdZxyVH/V4SHxpyPEvjkjYU88tuId2KeBPAeyd9a/ZvN81qH9gjthv6AC4SqUl/YL YGfj/VA2BNhLU218pL55tP2CciDc0C4gbCd8HarvltgvKAfeoyBAqRCShVFCXAyfvNW7MxGJAUzU JyIs5+nZCE8Ql4oycYG4SFyJUDHe1cwVNqRbAUMB/QE2gBXQG8A0G4DpPQDdAXK+ioPgpyIeaC5K 1tLlvEScFECoeSmgHmEeOO56BBxI6/ajR/6/yQvUVNsVEEnV1dR5beUoGZ8HtRvIgpQX6tFi2srR 6kg9gi2OzFCyzPpN1aOqd4/WIwXtNNQj6PDuUH23RI/K0B/16DJOttCjyiB6ZEJ2MD0qRJ5TXC7m QYcuhA6dijj1g0CdsWnQqScgBFyo9eZvmCC8pbz/N1DR4IzCmJwJ+l6EuaqUCbCFk0hfdd79RQLS Tpi3utSyKTx7OaxKmZd6Upv5eRT5LMrC05O7oCeyjtQTzPnfhpJVNt9UPfns/8LTE+hoVqi+W6In BcDbAP24C/rRD/4rDfRkC/LPYhlAMD3JQ14WoB+gObqwH/VqAKHWDP3+TB8epNTvvdIQTkE7lB/s d1+Bpzruffl7Q2W3vg4bKcMiFKRyvWvOuZlZyQhpI8X+fv6EqpX7x5NgPZUMdX01oq9hgCSAGTAL YAGQpsSXAMdjQ+l8YarJTEAGgOXp00k/3LM2yRe2x/Wd/TN8DmAwYDEQ6wUleQ4yUAWfOI/LfdVe mrM2vTznYPoluXV2WY94yPYQDPJcAwNj9c4XZp+pADn+cQhvAFQCQvG/IT9pF/XT3z0Jfp4ZoaDu UEDz+Dk8ND8vPGvCZ48t0uwcDffx80z01154dwd4x+dO/nb4Ro13GyeOSyvKqUpfmrM//fDEK9Pa Ee9eoY2qspUfg3cjIhTQsfm8GxmSd3mGkRM8l+VAFz/7b09lpI93I9oR7+4C79aCZ/eAd126evVu 2sTojLk5P6bflvNC+qUTNw9rT7yjramyv/wE3o1qIe9Gh+SdgnnUdkch9M5wU09ltI93PINpL3p3 J3j3EnhXCd59ovFudK55zIU5tekP52xIn5P719Ftxbv9aLgG0MicyWlKdVwD198ZMbbsnWq/85Zg tpTCfb8o29TbmhqkBF6TD8yq8J0X7fzv0jHdnPtzlqe/mpOiGNX1gIialTGRT3fHXRoA53OuF0ZA OeJcd0oBywBzANlI+BL+1p6wLdsN6yQWsr+fJIQNRGFp1uFawzb0Dq9RxS1dMO8gYzQb1bk9S81i 5AdG9X0bmhM2AGlsULz7GyvixIvVxmuQBB+i4Leuh0qTeRyDBUDXD8A2gq2rMp3P4n1QjvW4pU7U wvAEhqumc7w9tDDxTNDCsfBBKrUM03tpYXiCeVYGNDccPvvgnr4vwAqQrj8CNkDE87rzv/Kbxgyc dt3GgXc/t1HqZ7B88lM/dtn3cqR7APmAMiBIHK0AqJbPyeeGrhERyU7YM56Dc41inHBwlBWH6uq+ ZSW4w3++O9KDuFkU3vDTD/XPHjVaujclqX8fUWlYOnL7PMtlKSS/qLk0xXw1bDifvK5HCfHkuQbT ujET7pohpYXf/7q00DPr8yiovXj8pSsK1QzU3496tkk9SsZOxHtahCf+0KNkIvyPBiSUsAzPbOzX fWd6FAN6NCUJZLzDUIb8+wDsUzqeh4m4QbNTsk+M2mLgGVpdFw6LMBQ77bwlimAfdNWo59jfqyQd llyZTvc4bEMXdkk3J+YbY4ci/qnW9kPTc8zjRbp5riHdbKs+OSrQc4NezlJRlzLAfpO1MOmhD8vy 4KFHnw4FFDkQ1gwA9Uc/nyTr7LQNVrzzeSLKownf/KCFPUwcoHjlgPyga6SOWiZNabzdVJSxojTb 5RiD4WhXInzliFc4bbe8zEnZQCnbv50BTNPc5qy6uhOzwY6sUGUMZW9uNQhlq3+ZxukcgV7iFFGV CJ8ysPpqUbdcrIIN7wzM0SJiJNLsALnn3oqw13nGsK4Epskydf9eXRevCCUBaWZAfXsGv72AymeF +csAfxFZBsIyMMlwU4Ji8FhRl2WIk1mJiLAjnAKQ/XgYBpBX/C/TQSs8kxl8vGQZs9L8vhu2padX 3RrSy9PK9JLtGbro6a/Oj4oQ34oHxM/iD6Kv4W6RarhXJBkWiTp8sx9ruJO0g7vJrKcfhl/XcAyk x7Fu+0vxqPgHeP0X8aR4WawUr+Fp8B+AHeLpFuPdlm2vF3eKreI28Ym4V9SKe8Q+8bB4A7ALfGgp vduy7VMMz4gTDM9DVlYC7yfFQfEI4o+IGMOKFuPdlm1/Jx6EPP9R9DPcIwYafo8T7duB7+0izrA4 IN5cq8KV77Zs+yuxQvwTM9lWsVqsE0/AWMDziD8vdopnWox3W7b9Z7EY8rxIfCp+L77Br7t8jrll G+B98CGQfDeF3m3Z9qmGZzEHvgBZeQJ4rxaHRAXiFcJieKzFeLdG2/r9TBdMwkMUYegH3woQ4kSs 8f24zitC2LJastbGYq2V6zfXuuXYKy8X+8UpaNmKuBHA/pu6NzgKZ0+FH84N+80yzMX63bx+uR6t A45YCdR13AaflNkBLfoU8DUk8kf4MQbCn0Vvwyb4bwBeF4fF61gT34S/A3HCO8j/K/wPAe+j3vuo /w7aeR8lCB9CR/8K/x3ADujoDlDrLfivI0R4A/mb4P9ZkyN1UQ30z2+fAowDzkP/S+PaKarEvwC1 Yrv4Cb7FQNggEg2b4W8DbBFHxBbxHeh9BDOjxUB4F/m74H8E2I16u1H/XbSzGyUIH4Eju+C/C9iJ dXgnzgPehr8FIcI25G+Gv6FJ/Ao2jwXi1y99XPq5gHNEOHOBWeliTERZC0DurTEnWIfqnusGKvVz DJ+t9P0g2lg/LCImAmYDsPP3O++R8T8h/TrAQMzx9e6oZ5v6rAChZKRxHOT5OPj9AFYAn1kjFG8e ogKPseo5CsNWLYy52ZyCMGlBOnCcnBv1rq8yhtOVesbNdNL4adtJ2bMeqcuKPnFAtuXJTVmsI9M+ Wv6omsf4sMeLsvX4JaGcGTALQJzZn0w7CWHiIZ38jojjYR1ZTvpzkMY26GQZ+SyPJL93OjIdNGg3 Z09Tn6rwnRWsWbpszOV5+3M+6IGzRCBPCJZvRJ5+7LGIWwEDQaSFpmN59oRO/Vxdl7wpo8zKNd8B C5x/WpJ+Ssb5kNg+ROxNmDCPZ0AfTB5lJs/Ho1w/pPMbqRL4dBGooec/22FZttMbZ1wMs408lH/4 9RWl+AotlrSY/fGvota9NUSs3L+idCjer7OU9YbIWKaPy5ww0dZreSl94kbZ9bbDUl4n49QfptCv zUyOYnmtiEpf1mV6Dfo/Z/j2eYHOnqh/qQDKI3/HjHWWAzyALHRUA5+OZYgo85MA7GgWgGnEh/wn oOYo1WsQZr1TAYkAhlV3tXcOkbLO9B4A2eYIhNnPFEAeQDqOl45yZEtQLLaEjNhd3TBdxIu4wRYR VxOVEVsTpVhqoibEDLZ4okW8J3pXN0+0LWFCDMuPRD22OxpAfFIReRkScBD+Efh6HCRuKObRjTET cc15fGHiPxxA/KMBuvJBaTIT5TIAXTQfXv17Zpv33IRpq/+tsppB1Um8WE+GI4HjFMTzAIkYC+1h dcWBaWxX71lzc2gl20YTvvkJzYdFi1QUJC2IY1PpIvslTWUYQ/Kcg7gdQJ49qfFsD/xIpNVEVUfV ROVBHggMV0fJus3BPxz+yfaPJ56SzsQhHJyP0sM1XtnSj0WvA+HpYVWULWEd9SwG+ka9i6mJWhdd E1UFPmw3Qy/N0E8z9NRsS9gOqIoKpIdcD6iHb8PX4yBxwxDDkr2myltb6uF8jIV6SDn1zllNp5Uc f3PkWMpHQz2U6c2WGzCDTuLGdgLxDOxU9TYD+fciUg467Iavzk9Is8UXRdXEV0RVdqsxe7rboqzd PebaeI+52lpplm1z3IHaRvWw5CEcvZB9/S+NYzz4wHmU3yJtppyCoNVx1mhrXDVm0vLospi86JoY EWONEzG22KpoSaP2xo+OMo6J4MPd4EM5/JUaPypiKs1FljKzPc4WJeJrzeVx5VFllvKovNgiv/Wt PelHRxnHPeDD0+DDX+G/rvGjqHt1dEU3a0xNfB72ltCR+Nqoim61UZVWW7vVj+M1jlTMJ9wDNneN wTYftZu2xvwevFoCXn0Af5XGM3t8WVRtfGVUVTfoT3d7lK07NMxabq6xVrXbNaajjGMC+PAU+HA3 fKlDNXG2aBue1IosFdGemKLo2hhrjC3OGmOPrW63OtRRxpELPnAPtgS+3INVxlSZyywesxJnj7LG i6iKuIooj6Uiqii2rN2uMR1lHOTDM+DHLvhbtPmqrHtNdGU3W0xtfFG0NR46Ei8QF9FVVnu71Y/j NQ79s548m5Jns8uwdiwFPALYAgjnOaC1nwWnav3KMwuee/4NfOaaWBOldK2JqorT76tlGNlhPdsk oyDXWJ6JpWrhhs96oWiUiQM80ojfdh5vGh0AbeS5jqQRzq264rygzWkkadfcvQpIqDrJP7YTaE+O IarPw6T5eYi8C1nYBP8H+Dak2WJrY5S42pjaOMzA8bUxlVZCZUxZN6ul0loGsFuq4u0WW3wFfFss 9p2AaktZNwV+BaAotiK+KLY2rtqixBXF2mIJFbFFFgV+tcWG/7Y4W2xVXKXFFod2YgllliKLFX5l jMS/PT3jdXRatVT2mrpPJj2nQ+aqIXOb4R/UZM8eKyx5ccIi4sstlfHCUmUlVMV4utngewCKpTpe sdjjK+HbY7EeAWosnm558CsBZbGV8WWxIr4G7ZTF2mMJlZCuPPg1Fjv+2+PssdVxVRZ7HNqJJXgs ZRYb/Kp2K3sdmVbjIAsJAIiB+g6Ia4d+TdGH5dyAc0yPlFksGwHL/wyhZNv3ocAiAN/vDla8a3Ai 0tHEGNWrD3uYmKbUlzkQ9P6Cd81jVX153rlgGl1T71+0pU24QHc2mop3qPK8m1fw+vKcaMW7Z0jE +PMqRR15I90HhY9P8FxbNz4VCRYA16ckgBkwC8A0lq/fIwW/H3kqyrEPtqG6yjzVk/LBdBlG+773 Nn/EOfgBI+5AxuAHvyO97232Tnzm1L0TY057ahqB4WdOlXW5BskwmtTth0Sm2qH3ny/MfpMBHAv3 Q5S/UgyqCED5G6QElhv9/VZ9OFh5oOInu9tX9h1b8FhFTpPKX/hkq5XX46wPB8NHX0YfDlY+2HiN OnomgdaUJen30+Jnw1cAdgBYLmwAsEMFK3zp5PcTDeP18hiY5uQ5+W2VFeFHN4jnI16GTtlv29ph EeJ62Ez5v9LHStdVed/to0t8FynEGf2sVzFcpKUTl0B2WD54b4ignkSJcYb7cC/+WZRbhzR5Lx42 HP4T6m46+2jqvfia+PI4aSui5N0h4kjh9nlFQFCmEdfZSMed/O9C9R3oG4NeqEv+cL7oroXZHuNM h4sowL9ywDscN4SkP+aHs+GTt9JxL30mAFnqd0oynT51nW42wpNgeaVY2GBF4kr8z1X9YqSfBugP sAG6aeHeWvjXurgN4QEA4hYHwU/Vwgb4yVqYfenDnGcmAhRAqHkmoB5hHjjuegQcSGuO2QqQ7njq 0WLo0bfD983n9zSS9+QB3barPo+iHCgLgtuXkHWoR/dDj2QdqUew8fDbULLMfpqqR+MTjtYjBe00 1CPo8Geh+m6JHpWivw3Qo0nQn0Vg4JIGekQ+U4+QHFSPCpGXD93JxjJL3UwDUEfoUzeoR/Q7deT4 rjV6HZF8lTpSNfZzTqWiBrrC+SrQWiPrUEcegI7IOlJHMN//EEpO0XyTdaS0d3g6Av08O1TfLdWR P0A3qCO/wUTSUEdqMK5wdMQJKzqXiUvU7xu5J7YC5BpjQ7g5OmIGPoeBW6h1RL9n04cHKb41NeRz 0Tlrvsq5ufhWv/1nS++lyzbDuZd+d/89vv1zxF3rx/S1rM2xdD2c7X8v3RD5EOaxxYAI3b306xGn jHOei0HgJsA8wHbAV9gsFqTjLPM3Qvw4Gms9iMjSrMN1nPKud4qp8146yCZ6ATiX0/EbJSsDmhsO n3kQyaD30k22m3z8PCgWjFl8f/+qzyreqQI71OfJYPlG5M8BNOzbAqQWAPKRVwafOFoBeB70uVa+ l/6zvJe++LoUMzspgq+/l85fomBad+TVfNpflOCOd/QlvUogWuLQLaeYt9X2NzPNgzK8l64AeloS ShgvRJh30+W9dI6X99KvR/qgIUk/N/de+uQlirj+LDQGp7+XznS69nIv3Y55NgXAOS3Yne/BQJny kkjEGzxfM4EwQPHKAeWGrpE6apk0pfF2U1HGitJsl7IWDMfjcy99YTbeEDS4l74jC2hq7m7cS781 ++e6qpBlDFV/22pI3Lk1HHo0XsazUc8LzqtmRXQZDN8G4Hyt8kiBbht+bzjRcLNhLuBChIV6p1x4 rCjHMi9t34475YYm3in351fL+o5o1t36MyZMwB2zejwaowHHfqFhu8ECaEiDZS+/7NcWZTDUmBpr i3f0R6INO4C8gCe28p/qgtsLaMqYOJa5hnVB+Trt2mvDHlM4bbXmmE5R/PkWjrwf6ztYDfc2Mn4J eDgB0L7vYBkESOx3B+uiPguzz7Zvyi4ftCPr+ffuUu9gybTcx9ereYwPe/zT7CTUNQNmAbhWUh9k 2kkIJwKkk+eG/ZDAOrKc9PX7C1lG7stR3CPDXXXhOIT7IJN9Y9nXn1X5zrCo7z20MsQvQQtz/9RT l97SvdUTtvq9cu8t68csTFyb8+Gyn7JT0AchWL4Refqxy33dfAx0EDLzkV8GxIm7FYBkn2vdvVU9 v1KnumLII+6ZeF+KOMl7Vw+O2D5PxuVeTCLUW4wX1001iHs2pysJzx7IYvrbPZeXJgJrppMXdDYA n3PLcOepunDDfFgPQkqCiJm2YX5G1r9uRkQQBz4Pf5p3ItHwuQzUobu+GnUvf21+nrjoAN9h4TRl /qwe2+eJT4pi2M/j2n0q+nfhXtVgnJ2yTXm+S2rW4H7X21q5QM+p49BOKoDyKO9dyT3vXDBkG5kC xzKUQfabBCDtZgGYxiJSBiCuoxDVXH2Y9U4FJAIYptu+/SXVl3LPdL0cy3T0pb63GYz8eRCONMgM v13Jgo8/UWW19anuZktUetsS7b1sfWQ9FPUEag9VPDp8MxHXnMcXJi66MkHHJPtqb7gPB/7kTXSY 45iJchmALpoPL+D9rwkTzmCWz8nxs54MR+r4NQtM6AMmjQS/nPDxF5Jfsg0UC4tHqSjIcbJ//Zhl erh8bCibL7+8DC3Wj4ntSNwwFFUe7UijPGZiUBYkLoGPsavjq7J6+tl7EWx9KJ+yLmVShlE0rDGm oCABxcOSQ9n+scZTT/9wcG5LmbODFyeBACvg40/lCXlBnpA3kkbN4Ucq2msLmbv22mlksk/OwplT uIjJ+ZDyx7FyjErvsr7tfT48lri3F9k8BIGT86GUzVD8knIKtoY1VwSTTa7zCQCIS5t8W9OvJ3Yb AJ6rNHIW4gEKnjTFO6clIhL8DNarZygi9OUbflsjz3sHoU3qJV2wM+S2/LZG4qE/d24q3qHK89ud KZFnt+pZuWxTj7Oejnp8An0DVbmrf47/WXlEpw1Xrwj61nn9GtOenueC2WhNAf6EYPlcY+YApK7F ImwFLAd4APmAY/M8lzRcPp8los+38V3IOkDOwm3z4sWtBpmGLJGHNPq0i8pnLobpDGJHFmYgQBXS FPH9BD6L3Z3FB7IM2ODg2LiLvgXt8rmQZ+U8J485OQlLCmx0BHCBbLiuwvn66idgZwM2XPOXKKL3 E6tLWfVp9DcdQBuuTKdrL2flnTZc5XmB//deYJGHoJ8bER2DNM0x3GnDtdOGa0Obt502XLl2wAW0 iTcSGXYA3xNgzeR0DJtubWcfti3trLZl221pZ7Ut225LO6tt2XZb2llty7bb0s5qW7bdGnZWg9my bo22B2BesmJ64lzGc8chSqcN16P3P949UqcN145hm3an6LTh2h5t056i1M9FEZiLQj+TSJ3stOGa AFqZlXBsuEZwG+r3/YC01xqODdck9gOYBeB5CQ8MZNpJCPOMQrqO/v1AILusz/8J54cgACFYvhF5 gc6b+A54MBbgfOQfm/OmQN8FLMxW7bZ6Ps2W3w/w/GdRzKDZQEusifD+ho/0F4hXY5hfouUnIH8k 3s/zbIjl78O3APJsiN8FMF6EfK9t2CHqNwo8l5qNtJHn4m6UvTxuG8KUsTXweV+KYabVfnx/9KEl t8fZv74/7j7E8cZ9Xg/8JzDtaaSNm4kzLYSZxvIMb0A6vyOohv/bg2/N67Tb2rjd1hmQQ9qLfAw+ aSl1vanvb9rqPVVz7LbmYiy0F/kifJ6D2pph41aOX38GjqZa9C5Lzhdoptnvw2kDZRLGRZ4tgB8J pGraqd3WtsYzVZPXCPjh0PZUlEsEsLzq2pHdVq4H5OmV8HsAuY6gh/0wFuoh5dSrh1VNtnHbFnrY YrnRxEfiRnkKxDOwU/3eJgP59yJyBuiwG746PyHN9gu129oRxkF7p5yfFsMvgc9z2+pfqN3WjjCO ieDDUPChHP7ZGj8qfqF2WzvCOGjvNB98oN3WizR+/FLtth6PcaRiPuEa3ty9iXzV35Q1hvZOh4FX tNvq0Hhm/4Xabe0I45gAPkwGH2i3VepQzS/UbmtHGAftnXLvsgS+3INV/kLttnaEcZAPTvCDdlsv 1uarX6rd1uMxDv2ZS8Oz2WVYe5YCHgFsAYTzfDwT5TIAYIXvDgXjqrM1/bd0pqIi+5VnFjz3vBGN c02s6bTbyrMbj6QR7bbK8xJJI5xbdWi7rXMhC5sw7qXwbZAJW6fdVt8dCpBFPTugDtPGbUelVSrG dyz3yaTndNBzPmRuM/xlmuzZO+22BpS9jkyrtr5bYoZgH4YtoubcLQl+Z8GrLxBjv3fmDe+WyPsR g5T68sfjbonEQ39PIw04cV+QCAgH71Dld1TvzxlR/myr3i2Rbepx1tNRj0/DO0APpr6Y80NhXoO7 JV067TCB13Dt/m5JMDtLcv8cLN+Iwc0BcC2j4/sOK0DeSc9HuAwfUeBPTed5s3StaysgqWtT7pbE nFiedfTdkgH4KYPNWfq7JYzjVU7QuyW8V4L7JRhW8+6WOJcEvlvCdLr2crfEjk17px0mcqThvRHh YaJ+bjy6zMLsTjtM3nsCpCDPeHsq9d/BcW7At10tsAHV9jaLaIuqMdtJTRlTY221ps2iYLQNx3ZS uGMKp63WHNMpOvnhuUpo/aOOejZ22mHS7pSH9R1lFwES+31HKW0uddphAmE0pz+L7Is0q8yA3x9g A1xz3l7fXcP3H9owpvvWF3Lszzh831EGyw+2t3JhtzEX6/Gx21thEJo7Yca2eSumb5vHPVFT7TA9 HMQOE9PpMt7EfeCd6WZ+b1mg+94SNzZCfm85F989Epfr4fObTn5veTXC/N5yw6xyXOH2fm/Jbyzl 95Z7ELbvvT+69urb43IsD8StQjzl9PrvLZn2NtLOgZ2mjmCHqRgyMwcyc4JZiDvhU7Z+KXaYjiXu en1OAY0IWDuCfrcY7ruDptphyge/LgCfTgO/loXBrwHAUnsG8+jwzlTRV//528pK1cp3ga8fs0zn mqprJ+j4T0W5RADL04Vrh4k8pRwegf8RfPy1SztMxwJPPf3DoXlbytw1YEQ8ZO5L+EaNJx3RDtNh yJ2cDyl/HGsouz49kE/94ko1QAvDC0vXwuGpbJN6FKgvsER9LzIY+ccS9/Yim/vALzkfStkMxS9J z3B5JOe9hvNhW5+VV4PhWwDNOSsPfgbrWwv8nosanjnL8179Ge/xOCuXeOjPndOU4Gflsrweb304 +BgijeRzPwBtFsCjswI8KnhGjMUGcuxQJVKupX72vPU4oYpvT68P68cQHk5mYyI659wicYIMWocq 5mOGg95meVPHaFTqZS0JYzADzgYgOcTvdtF2TxV+Yw4XsdWS/nHSwgqQLhkBptEOEPWxEJPwRAB1 Jhwat2R84bQ/RPHKlBW4+ZwmS23dd0vabx7vvCN8Be/33iKzNSfjDXl1PfLLAOHyqrXkXsriLPRN 2YG4qL9ZNBu+dC9jDNt1Y5D3OY+Xfez/FwAAAP//AwBQSwMECgAAAAAAAAAhAMN6HtgVXwEAFV8B ADAAAAB3b3JkL2VtYmVkZGluZ3MvTWljcm9zb2Z0X1Bvd2VyUG9pbnRfU2xpZGUxLnNsZHhQSwME FAAGAAgAAAAhAJaTY6D4AQAAEQ4AABMACAJbQ29udGVudF9UeXBlc10ueG1sIKIEAiigAAIAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAMyXyW7b MBCG7wX6DgKvhUQ7bdO0sJxDl1OXAEkfgJVGNltuIMeO/fYdyptiKFFSK6guhilq/vlmSJEzk8uV VskSfJDW5GycjVgCprClNLOc/bz5kl6wJKAwpVDWQM7WENjl9OWLyc3aQUjI2oSczRHdB85DMQct QmYdGJqprNcCaehn3Inij5gBPxuNznlhDYLBFKMGm04+QSUWCpPPK3q8IbnVFUs+bt6LrnImdbRf pXGGt9r8djBrNaon2m08qHBkI5xTshBIGeFLUx5Fk24jyciyfifMpQuvKNx7qOLM3UiaDrZ2P2gJ vCwhuRIevwtN8XLnkDsPgTJVO8oeVmpBtVUlCyhtsdAkkjXFtLozzLSQZhfEfTBBEeE3EZC2C28M xn2TNbQfxbSleR6OLgJjEcIuK41B7zQN7S6muNJX3rrQ98rshbsIlhJun4VgL9xFgHQWAa9/T1+K WqbTo/il4BrXCnrPOx6kuyjqj+erWNsFbr+LzeD0JBydHw1H/8p01vf+7IHp9QCZ3gyQ6e0Amc4H yPRugEwXA2R6P0Cm8WiIUP/zJG/cqqcf3o+6Veuy5zqWnoEf/veeg4P0Q5cZ1dJ1VUMtjIen741d 7xCtU0cFGniUsO8e2grvvUfqGp7u8KgDgNhglVC2+OZ1Qzf9CwAA//8DAFBLAwQUAAYACAAAACEA aPh0oQUBAADiAgAACwAIAl9yZWxzLy5yZWxzIKIEAiigAAIAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAKyS20oDMRCG7wXfIcx9N9sqItJsb0To ncj6AGMyuxvdHEim0r69oeBhYS2CvZzTP1/yz3qzd6N4p5Rt8AqWVQ2CvA7G+l7Bc/uwuAWRGb3B MXhScKAMm+byYv1EI3IZyoONWRQVnxUMzPFOyqwHcpirEMmXSheSQy5h6mVE/YY9yVVd38j0UwOa iabYGgVpa65AtIdYNv9HWzpiNMgodUi0iKmQJbblLaLF1BMrMEE/lnQ+dlSFGuQ80Oq8QDzs3ItH O86gfNWq10j9b0DLvwOFrrOa7oPeOfI8Y4KcdnwzxcgyJspl7Gj7qR+6PicQ7Zm8IXPaNIzxk0hO LrP5AAAA//8DAFBLAwQUAAYACAAAACEAQxrbAPgAAADcAgAAIAAAAHBwdC9zbGlkZXMvX3JlbHMv c2xpZGUxLnhtbC5yZWxzrJLBSsQwEIbvgu8Q5m6mrSIim+5FhAVPuj5AaKZtsElKJqv27Y2IbAvr eult5g/z/x8z2Ww/3SDeKbINXkEpCxDkm2Cs7xS87h+v7kBw0t7oIXhSMBHDtr682DzToFMe4t6O LLKLZwV9SuM9Ijc9Oc0yjOTzSxui0ym3scNRN2+6I6yK4hbj3APqhafYGQVxZ65B7KcxJ//vHdrW NvQQmoMjn05EoHU5Oxvq2FFSICU6Mlb/6KX8cC3gaYxqTQwfEvHLYM2S5SgzHutS5hX+hVWuicXf RE96Coe02NFMZ5w11TmymzXJzt6t+r0bLv5k/QUAAP//AwBQSwMEFAAGAAgAAAAhAD8tGZ4iAQAA ZwQAAB8ACAFwcHQvX3JlbHMvcHJlc2VudGF0aW9uLnhtbC5yZWxzIKIEASigAAEAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAArJTRTsMgFIbvTXwHwr2lnTqNGd2NMdmFidH5ANietkQKhIPTvr2k 08qWpd5wA/l/4OfL4YTV+qtXZAcOpdGcFllOCejK1FK3nL5uHy5uKUEvdC2U0cDpAEjX5fnZ6hmU 8OEQdtIiCSkaOe28t3eMYdVBLzAzFnRYaYzrhQ/StcyK6l20wBZ5vmQuzqDlQSbZ1Jy6TX1JyXaw 4eb/s03TyAruTfXRg/YnrmDaeMBHgR5ciBWuBc9pZGK8o8gCO2WnsW5SYnnxpuDFDyoUd8KKzDmQ RUoQVLKGP4RRIhun2WoUySGOH2lk2Js/QHsxi7VMieVDT0e1GSUbx1mG65QMOwmfT87YqE0ma65J rlJCWAd4BDFZvxDs4HsovwEAAP//AwBQSwMEFAAGAAgAAAAhAP3ShKqUAgAACg4AABQAAABwcHQv cHJlc2VudGF0aW9uLnhtbOyX327aMBTG7yftHSLfTm3+QkJEqNpNlSp1Ehr0AVzHKVEdJ7INgz79 zjFmCagXldjNVO4c+/j4Oz9/4ZDpzbYR3oYrXbeyIOF1QDwuWVvW8qUgT8v7q4x42lBZUtFKXpAd 1+Rm9vXLtMs7xTWXhhrY6kEaqXNakJUxXe77mq14Q/V123EJa1WrGmrgUb34paK/IX0j/CgIxn5D a0ncfvWR/W1V1Yz/aNm6geP3SRQXVode1Z0+ZOs+km1YxZGkGZSoRfmTasPVQ/mozcmMV5cFicIk TbJ4nAAnleMMxIbEn03997bL1nB9kvJork8SuyRHy72KoaKHcq8lhdv7KyLqRQxjF28e2xZkEiZJ EEA82xVknI0y+2B2HdyxZopzmWytgi63Aty2NIji8LBtEgcTfIBiu7zkFV0Ls+RbszA7wWdTinPz uXKjX3PlCYq24vLqaWHVDUPERoQdxFDxAk4UUIkRBUE/0kd5p17tuGqlubUBz1Rz4q0gIXhpvpbM YACepTt2xys3mjPjbahNhHdysnpbwaXauffi3CpUgdpfucI3BDy7P6UVdXlfC2EToNv5d6H2Z5nt 3gGQeRiFFpUeMq4oA863qqZQJ1tRpbmVDxJpzukg5lsjrzhFWDRn+mSB6Z4iSLT1OYwYD8MIiTZU PRYkGaWo/cL3bL4I1fGNe777N+rC93z/IlTHN+n5hnEaji8G/hc/EEjVAR4NAGdRBm3g4uDzHYxU HeBxDziKMjDwEDC0liV9Xrwd+vE7TS8k0DWhb/Q98LjnhQQP+u96FGJxhNIBoTSJj5vU5yWEWByh rCeEeOCP2+Al/byEEIsjNBkQGo/S4z7xeQkhFvslAghO/p3D58nw02f2BwAA//8DAFBLAwQUAAYA CAAAACEAsX0r2NQcAACw9gAAFQAAAHBwdC9zbGlkZXMvc2xpZGUxLnhtbOxdWXPbSJJ+34j9Dwg+ TMxELFu4D03bHRIlzjrC3e2wNNvPEAmJWJMAB4B89Mb+9/0yC4WLAA+JOrwuP1ggCRQShaw8vjzq 51++rpba5yjL4zR5MzJ+0kdalMzSeZzcvRn983o69kdaXoTJPFymSfRm9C3KR7+8/fd/+3l9mi/n Gq5O8tPwzWhRFOvTk5N8tohWYf5Tuo4S/HabZquwwMfs7mSehV8w6mp5Yuq6e7IK42RUXp/tc316 exvPoot0dr+KkkIMkkXLsADl+SJe53K09T6jrbMoxzB8dYukt3iy2dVyTn/z9XUWRXSUfP5Htr5a f8j4598+f8i0eI75GmlJuMK0jE7KH8rT+GOC03Bw0rn8To4Unn69zVZvfw5P8Wza1zcjTP43+h8X hafR10KbiS9n9bezxe89584Wlz1nn8gbgILqpni6r8nVWjzUhA67DxUE8qmuiiyM7xaFNkmTJJoV aaYFfvWo1cXhaV7gA8+IZY/wF2QbdB5uPPvtc3UiTUQ9JY2vcxCh3Xz5NZ1jLsP7Ih3RDNDsaLfL eP2fPNN09F901Jgx03Yc18c9MUOW71mez/TVs+foRqDjd5pCz7YCntxqYsLTdZYX/4jSlUYHb0bL OIl4/PDz+7ygJ6hPodvm6TKeT+Plkj8Qs0eTZaZ9DpegezYDR4nn7py5TLQvb0am73gOSAnBobdg XByu1uCiPLkbaeHyDgtwVmR8+233Kb723oMe4CLMF4IYHkAwUpbeJ3NmqUUUzi+TuVZ8W2OeEyzo EdG1iuYjbRnh9nTEZxZhvNznTEzPMqG5iG5vwSDlnNHKIa6i1y+ZrTpImvwA7iiXUuBu4zqny3Wg 8lHc1OAhR3dtU8dSZh4KfNfg+W3wUGBaBsgjHnIliykeen4eykuxtSmzLMk813GxjDSzYhdxKpbj +n06+5RrSQoJ3ZJOcjASTcRU60W5PgoaigZiAV7yc/JZnp8zi0sRW8lwVw9cXQhy2/Gg6sSCktLc 9R1fp9+JmQzDtugD3UMOhJuJkdenxdfzdP6NOPUGf1lwYrnlxVXxbRnxMsV8hKegGv9hGS1DUtpR Mv7nFZT2n5CIdHttHmcFboajKIOmBaPnq2KyjEIs+JK64u3HXydn10RFwbSIMfceuGdA7UOWFuks XWrXUV5o1+k6XaZ33/a6RU3x5sBirpi+m/4nH7waT1deMvhgBr+7wRFoev76exJp0zT7EmZzba/H oVexx8DnaQGGg5799B8PHZaZonh7VLKuv6Tau9U6jDO2uy5gcn3T3kd3uaZdROt4VkTzv3XojZL5 hzALP/bxZGcixOsEH4PvJb/zEqClOLzezUpbXGNlnadfNcNiqc0GBy1RjUZjO4Redr38Jwuskugs y9IvpA7zQVlAlJGKaa73fhuFblBacKbtObovlr9juYYLtcYvRa5/y3B80yqViWf5rmu3ln9tbpQW SQa1OqI7DFgkSUrmCN9DaOLqC7B7qZu/kmKmMYiK+yx+M/qfQA8u/UvfHtumezm29YuL8dl0Yo/d qeE5F9bFZHJh/C/d17BPF/F8HiV0G2nvG/aGjb2KZ1map7fFT7N0dSKMdWnzw1g3dGHxExVt4ya7 u6lMqCn/KyekcdpJmwwWUXiWziMZpq2fm8F46vre2J7azjjwdH8MC/AcMtkO7Itp+5Hew9p7/COR CRU4psNvqUE0HrT5bBD0taxvnbaKiwjSO169GZFukCqjtNb41Zb2GPFkPRVEfj0VeN2YEn7RW3SI 9iUj85NtP34X6zOY29O4tHWFoqEfpJ7h489Lo9R28+gWy5qv3GIKD5io5KwlrF1vwxks0LMsDpdQ hYswyyNY31ITypsQB9e3xqFJC3sVZu/JmDcDBwstTsCbuHbM1rXOL0Fe32W1tr1+VCKJsnKqrJpI qeAbVJo+qRg69QWoJNJKKu0GlaCILYV6Ll+USiKtpNKpqTR1x7PJnnklVBJpJZVug0rHsNmG6FKp ReH75Dz7xIbYbZoUZ+zw3YQ5nDDSScBGPtwnM14GNG6+np1Ht+XRh1kh/Dq5RFq/nt2yKMR3feeV v74Au9G8lFPkNaYo8AzIuc0X+SNOEc1LOUV+PUUWhBvpgQ1e/xGniOalnKKgMUW+7/YKrR9ximhe 2BJoam12DmnCamiJbQmezF5/0WD5esM+4lYf6NcozO8zgF9JcYCvse/oH9I4KXLtTAPsrJ13fIvH U89GlPCaBzxIdtj2oXYfj3KfccivDLPocY8qDMVDnL99SfsQzj5FQIHDdYG3ron30yH22aZyK2Nq f4W/FMWfI62IV8AdwtU61zCzEKSHMmp9ny2wyRpgbmcidjFoPe4muPFWu42X0d+6pG71p/klwqUD rlMNLVj8YK/agsYR8YyP8DphkwBKg1NF/ljlVwuDRIJpT+tNu5YpjCnAV5ZhmobDtNTIrGHbHpsS hKY5lmPb7G5jWcrISgffV940IhcNF1KEMoTrSG+2ARAob3pvbzr/1z1kDGIo7xLCk3QwIsKmBX9y DM9D/Clr/XTT+EksqB1eOMv2SqHDlL8Ob64IVtRN3yv9yZZLUDkCjgQU8JLlGTgsbapdwmoPW6DG Brti69DBt8jZq/Q+mz1MP5KHRWE9gghoMhpichsgftYR67tl8JYbPVQeg3G68tiyWuKYRXMzqtqE K4m1pCCUAGWAGCSCpBzs8gLH8jvBLkB1nukgnkIi1dIdJ3gkQNmCulqI2BDaJ3HLHiRTRhnpydJ7 wGZXi/kX7WZ5n30M5wCFhEswjymWS0CseNs4hpbkd1/bwhriE3/ExeJqEVIkS2AyLfr4EvF9uFwv QuGBm1hvlRcuAD42vStyBCRXU9pA43KK3BDty+RjdCsC5eaIJUAbm5KxZP5pEc4jce/WYpZXCMOf BqSzYUAsq7FFrJyTMobi1OX5dKmI4VYXlzMibyMokIQJjq6u4DsD1KguXsVJWoay2wMsqwg5gSBM NE2QmJg6BiBjXlpWLCcpout4k2EyW6SIYFGQnAWi9Hb4QyUd61fM3w8t3MpYaoXDeMIPRTZJf1Yh D34dh5teSAwQS/13JBNoSKMA8ZXRxcdDq3x3UML3bcfFkqYV7fmBLkIlTTPK1QlLFUvepmWDO+Kp pPDoWFHREqkYwK1osgbCEg9f9cNXlutRkNY4DYR2khCIsGo9KvFQyhtepP/PxMPBMoEmQUChgo9K Q6hev+0weiUl6LoGz+FDW671RhP2Fgy7smMoYijEQ09OlrWRHcPE1jlZkC2ck8XLmmUVcq9Euhak Qv0TBPEj07Xoxr2WRo/UMXVkbslQqGtBAG0VOrtSs0SOFbK9MNDmy9onElfKkR36eg+dytqdaGgp 4z306XMr45ppe5QxccO+2VuWt40/2Slv8xbWzyZ/Su8+mW/wpzBC22M8IAFsgD9tPbD8rlZU/LmR 1Phq+XM4U8SCryMkp8wUCV5FoogMgrGXRSaXFM5lIq8RIBHDKP0wG5kkLkv5YaNMQVsK2kIcQSTu siatUndUogicmzogT2nYQhm/QExcJYqUZl7LmH5YZpBKFGFDVyWK/AC5NCpRZGeioEoU2TlFx0oU 4cybTnAINgflMdRp7Brsjk/a+R/amwMiQ42R78vSqAqDaSG18nadOM22PIRDxoahvbNYoDHeVhr/ WizinKLziKqjWvGgdPm+ewic5GCM2YY3IVyh99FtoXEOvGa3a2UwdNut3hFPsgAmu77Alm3DNeE0 k36vsWVTtx0CnBlcNh3P2hVPWoI2Ju1h8LKunxMCJKaobWNwoVrrq1a4Zzq1rMlk88oSFsIj1TEd BS9L9FNFn5jdjxN9Elx7+MKu4sTNhf2AQHFdbdsAyixdwBMcPrI9195c4o5RxY+eYYlPpxQJ2lyo MgyklrgKMJNV0INpv3yA+aFLvIoPvyoY07Ick7MsAGPatsGlrywPKZGMuhcYlmWjuESofwVjIuzR jEQNZcCoDD0FY1Lpm6p3myJfgWyRhwGEqt6t10p6UBmmqnfbia6oeredU6RgzJ1TpGDMnVP0lDBm H8j4W6rdVN05HgY4DgKExwQaqbq+BTV2aB3KcuOCtwbSuIG8PtBrcaq0oLqgyKmzgQhbxMjDgOPO 1FbDMS3qVwb3w/CRwyP6e9XoI35H5neJPlqO4VqGBA4Gclt3pVG0wQWJgjWTo10GLpf3K7QzE9+j IFymd+Dr39HAjRuGcU66VNByJMbTWjcRiW3cYeIH6h3W46mjTSHS+pEC/ifalnEbi3bhTYByMHia ou6Gmy/JupvyF1F2U/6S3K8mlFgO5ujJMS9kuvmkQMY5+a8peuAU79Evb0bXkE1KWdHXX/8Is3XZ q6WA1/tbygUFfeC1OJdf8GafDfaaKxRR9LjAbXHwke8v0xfwnUhwR+OMug6IHxA/4Un47G3NBtiU rnsR9PUeWNJj0iOiYqiqJDKIi+XqaZ5xfsw2BTf36AZz/ZWn4+b+6s/qcIpygerDb+hdx6cU4c37 qlGfqBNvCLlP96t4lf53zHOy0R5LtCJCFAsTJ06B3BNd8fIiiz+hKiRJkW+LI7z/qm0Keoihq+Uy /jNCX0JcWtf94EOzppP9Fg46bFaytFb4PqnEjfADP/i+DlE9G8x4A9hyleg50J3PxSoZzD92mSna uZnN/E4HKXicZMyI9FGTjA0HCgD5z6QASNK7UAY8PRJ/QrGDZUNBcLs1xwx8AV5D6Q7I/11pxtte XLs4pnWm6gBZJxMP8VgVxcCa6/YdRfkK3usWHsM7PiaPcSSk220U9ccOdRjlSEiA4jidczJrc8M3 LJOWCnObga6SXqneFbO9snajyKbdItDq6iskoosIeFOguajGOCazkaIoqyYEi8FshkBD+0bXMTg+ X7MYGrf5AX4nFnMDUxcCT8mz19SNlBReO+ccjpAUX8ROdXNC/naoso/4QkqOkj/QBgF+jtB3SKuw XB64Zg8D/pCNnA7mj2P0F2xpsVbwYijTolE/Izs6VtWcje5zDatbWJoHlcB3ijwzGuJxPW2orSca XP+abvRh2ZZSBJsDFiB7EY/y8HvH2VIQf1i/1t7GPmwnlX3/eP4OfU4MsA940ftoTTtZEPJW1Pjn h0AWfUMLqh5o53pVilSPDeLVqVKlWsC92uBFpS5EF99+/KLOsui1Mhw0DfUcLGFSAYFLZm3HpvVR B16qABIHvi2qo2ph0anXVTatmMDn72pOrT8G/SYwGzNQXXP5WH5qGBIuLFXTFIYEgvC+04XGAtcR 7ejBZjgBaXo7eucoLnopLqL8ykEu8o8ulRpc1JRFpofOF90iSd830PJYejweKxohgaXhomTRM+2w gF7cpTqKZ4SEsbMMW5M2KrGqPT0+oGM3NXGjHQ+k9MF3AjrDEHt19iovaOu+6ssbdIeQcXs61rLT aHUTgYzs3RysPENftgLg2jpDnz8GSoHWAMUjviPcRnSoNv0zXQ/M8/HE0SfoUO1djs8C2xt7+iX6 wNq+MTEmsp3zfR6B7nB5sY6P0M+ZwXkJdIIgNnMkiWTx4JmI1jybUVgDs0jOYRYVswUdiiJZ/h4n Vz/ALK4nZpt5QGOU1j7a8wQGtlxhU8CDFO+aAq6lu3pp7aPdOHVE3rr6dkU3KqBS5lJWX+BRVDfx H7ubODgYAoIEy3C5tYH4Wsf3fR2d+e3A8jz0MqSlhP5Wrimsr4bnjOXlm1hrhKwAVUYpg1pLqjO/ 6syvOvOXOYj7hen2DczJ2nNSrJ+XKlOxFLYtvPFhc6kyFaHEtu+poTIVd06RylTcOUUqU3HnFO2T qZiR6Nu2j1svfN9KNeEBireNvvwdGP1QbL87Orm9IsjCpAJW2Eyn6UPjt7XY5T7yHTrFPXYNX6fc PHFP35gjO1tuJ7ztgWjDNjepSqiR9Vyvw01ydNPyTBFgtD04TXY3wKjcpE4fSFXQpTYwUxuYDW6L XPeYPIJpr9wk5SYBUz+0QfdD6weVm7TTwFVu0s4pUm7SzilSbtLw1tzP7iZ1t1yrSwiGnL6nc5MQ 2xSZD7wtgmHUQWvKo4T31Y5B05ciQAUX8uYLKrAQZw6xwy2HmWVKQhldxfZSjuUhl5dCQpQ1iSg5 O9IUhObmFSbKxcpEKxSXmZxpAU9YjtNJbXjktghuWbyAG7QUnKr/EtVSmqr/Qvkbwquq/uv+OPVf 3LlG1X/tCOhXKYylCK6zFo8hglHO4IksRWzlh+KGTq4r8tmVCE7mrJbKDeF5A3VZqIi951fRHFvP RYk44jOPk+iqSnBZ3KoSXFmN+wQluEoEy2yqXSW4ThUx6ClNEHl/zfLIDdN4/9KE/rJHIaSRkOi7 2JaiZSf7fmC7ZRZi4Jsuihfw+7ChrDLJxfwdR0xTQbXcp2c44kTvp12ThkJVZhKUH5Aif0RNmu5a 2HiX3CgbW5Y4/qYOf66atMC86O3+q2rSOgVXD47ndsahjt9/WRZ//+WXX/5yV/y9E819sahzD5XP UV62ZflVG7jJeK/Yz4dF9hGWX9kCwbc84wWX33Q6qVuENEAMtfw6DHnM5Xc9+dBZdvslUVT1qqzL f7BC0OGV6lSlMnKlopz76IoShdso7ng5RTnY7F5UphCGqoq3Syv26IlP7y8vzs+uH7douwlaUMTC 5ubF/6Mp3rIuBY0UNmvfzGpB40dV+4ZGZicIgMSz6GSehV/i5O4EtYD6ySqMk5FoTCcLX1609s1E UTIa56nat4FXRXmYDRMLH1Qi2tMlou1T+0ZteYSLXXe7DI7Z7RKb54hUYHjaVl85aKvdpem7uo/i UKEWBmKWuwpCt3FYEFgMBKmApQg6bxhMKmCpApbsXN0cKWDJ+lAFLLcHLMlmaCOdokfaEaAWDw0A KSOeoE4HccvtUOcxioiH5a+COlGb0Vty8oRYyzDU+SDM5e0BGyPu86iExl5h08WnbaI1jJ0Y1Gq7 vfbQNfhI6IlYfDLOoDvo5UojNyr4m73vnnbxKaDzBRYfgE7tZbl7I4ZGDA8ePIZqQeiM20+QajEC w9vgbtt00fUGqbR0xhH6UwyrFgUOPjV3b+nseAxwkMVi8X1qlyqWPdAm2qvMu548CJczeHk5VvkO QEYKfOA+WFhUonMvL1uKnP/2uTqxnUrc+Dqn8HhvNnHdypEUkcwrbrTe83R0lemUUKJrr0klltwl Gm34DIQc8MZUvsRr6uHrVahxDeZ47UAQC/6h3r39/NLgkhaYw1usdqyZ5tYlT4zluO5kMp2WTNjS Cyr5XCWfQ2Qm8yhRWA6rVYXl7F9NWVcOsXo7uE0Cmbttd1JYxcewtxtQjmnbvoJyhPo5EMfoCUO/ fYWd1DuQ0PastQOn4Hs2toehHLQV7i69o7m6vPQEkIPiDlcBOT/Y0ntpIMevNn+RKV5+vePL45Ix vQaMY3joMqpgHJaPB8rU70StKBgHuyDCtKuTBTnTV1Rg0/8JlxaUAClAFOpFThhM26iDr82+9KMr EdCwyrdRC8OlCDa2P+ggLwbqFCy0sH8GDFXtjvOCGOoRdsfpk0DPEH2YyUqeAfTT0LftBWGIdJ82 rNnCP6H5eOey58I/AXXaVreo1/eQ2VeuQte2XbXzyGUyf7ayXkK9JZdVB4PsVlV/96DtxIxScFdw eYvd8JKfht16d05q7nljop2Gjqo0tj5kQw9srGSgrTuLf9vAdsH0s8LdXxPujpTC0jrgdgMW5y9W eA9z24MhdxubaAflduGWF6AAg8VgI4PAdql8kPkDOyKV220MM8gjO75M8a/kwB7Q3fRpf6btab68 JbNM126MAZLL3Tpub7FFSbm5SnpfRNnVYv5Fu1neZx9DGGNwUShfah7ngHcd5IvyhwzHyDehWq6y 28isyLC7dFr8ERcL3uCaSuOZtmbWcUkOfR8u14tQpJOb2DeoolGczquuIoc/RTWlbESWjXyKb8uI xlsmH6NbIUxMcWO5Y7q4idx7l2lahPNIfI2d0up7yyv4fjwgnS32aynHFjt7dzq9y7GFsCjPp0sF zRVh5YzI27QJExdXV/CdsaV1dfEqxr7SfU+2LISyBqXifJCPKh0xMbXlXe2xGCYz7JH+ZkSvDDfF 1OXFFZ3NH3jnGopn1jso0jmiG72gkXso4eGS+YcwCz/i3Fav36pujK5r8Bw+tJ+8t/MjOLMemF/E wQ6EgfrzUkbUsTkDe3uA/EpSMHHrvXYzIo9fOCvcUQqTW7stw6FfuoEM+FomBAfWCuVlB65uOUxL U66guQmdwLkb+FkopmHBsistu9qWR67z6ot65ffsqYT+Kpf+pW+PkUtyiT2VLi7GZ9OJPXanhudc WBeTyYUh91RaxHMEfWgfp8dvqbTJKU2pQWKwTxCehIZ9WpMhpARtxyQmVmwTFeDF6+dmMJ66vje2 p7YzDrwfe5+eHpkg9l3N/3UfZhGaxbxLcnhnxKfY76bgT47h0WaFWeunm8ZPYkEdtEkrhMp1eHP1 J93L9KEFhHhbz86jWzHc7MOs6BHU5Rng5VIWYX0+dn/Xd6t1GGcrxDEfm3S5BfURReYPquzb0mR8 WxP1w5v1bblRKf9ZwchqBlbGLFil0zDkKxgVrNrnKxi1fO71FTh39GmcBWIeKapdH6IOuR0Q1baH ItwN39RFAwtkeJOktn34pspHeK2+qVH1VOjlN6eyB3r5jbbVe152MyxzIxfMN+CnllAIulsGltgp fNgyUL1zhFF7/N45O7EQo6rv6+W3utKvl98Im3sihusHQxqSzjEdE0kOYuYkGELbuSJfkiUdKoCN XTap4ryX4zzIKhEy6eU8jnIMg75UgvGqOM8nHVvutOj7LpqH0cwqmff8ONy2vgk21JJgOtU34bb4 6Xvpm+BarmujZQ3XKOooGLc7ZVJqz+AOaqWwiBfum1BpN5mOg04KTSzv4a0JmwkBlo/gj8oIwMQe Za+5V5jluQWY+X4zArapaIATHRVdOyFQ2gRrA0KLZ3vB4OUF7Sqo6st673oEGpbxWstOo9VNhBBS 9m5uM7AHx6IMNJGLIeBZ0z/T9cA8H08cfQLE2bscnwW2N/b0S89GhM2YGBOJON/nEQgNlxfr+PGQ s0AVZdgJBEn4mEmErUkPQdOTZzOKIvCyyIssKmYL+lpEefh7nFz9ADSsngnRK21npY/jm7pDnhaF B+CJebCs+HbSE3MQeJP9cy0DOUyS7Ac2bamCAVuiAzLaJgnZeHOvJ1bQjiq1g3GN+NP3Gi5oP15v 0Cw8PY6GbgZOzqaO7tmWP0YbC2tsW5f6+NyfTsZnE0BS3uX55PyyEwu6ZJ7JH782aX01wr0AZ6vA tAhEW05gwvtApBE7s1D0mDzYOmDZH4huz+PNnex8VA0uJIBkfPpUxZfKR5MyQv4VskK2RMTahywl KLz809tuzqlQcMhO1W7ue3SbTNtDgb1ym5qdAVlVtvbdU27TcYQyzAtpOXGsjay2/USNW+VBSFGj zL/X18jSQWDdQfSTQ46m4zrd7BBl/jU6kG7KmbZeV+afMIfYbi93BOLjMiCG44Zd8z5OkD0nJAxb XZVjpsy/xjQdZP6xkL7OIkzsupLcfFT6vOfngWtO/PPxuWFPx/ZF4CHLynXGU/SOsyfn/tnEuiSf dw3zc5ZFYRGnybt5aVbjyzejRVGsT09OOJ8uzH9axbMszdM2CL1Ov0TZOo2TorF6hNeLNqGO5yKB U+QuMG2sUxp6Zna1nHNWxzL7NVz//pmhglWYI0N0wl+tqTMwXzWrT0FqUYxExTu6skjYPIY1HOJi hJ+uRY8VMtzvYbhT04DbOIkLZBxlUV6EGVJMkwhNMQFaYGPG628U7yhWH9O04PhPORLmtxyajsrb 0aSD4P8TAAAA//8DAFBLAwQUAAYACAAAACEA1dGS8b4AAAA3AQAALAAAAHBwdC9zbGlkZUxheW91 dHMvX3JlbHMvc2xpZGVMYXlvdXQ4LnhtbC5yZWxzhI/BCsIwEETvgv8Q9m7SehCRpl5E8OBF9AOW ZNsG2yRko+jfm2MFwePsMG92mv1rGsWTErvgNdSyAkHeBOt8r+F2Pa62IDijtzgGTxrexLBvl4vm QiPmEuLBRRaF4lnDkHPcKcVmoAlZhki+OF1IE+YiU68imjv2pNZVtVFpzoD2iylOVkM62RrE9R1L 83926Dpn6BDMYyKff1QoHp2lM3KmVLCYesoapJzfeS5qWd4H1Tbqa277AQAA//8DAFBLAwQUAAYA CAAAACEA1dGS8b4AAAA3AQAALAAAAHBwdC9zbGlkZUxheW91dHMvX3JlbHMvc2xpZGVMYXlvdXQ0 LnhtbC5yZWxzhI/BCsIwEETvgv8Q9m7SehCRpl5E8OBF9AOWZNsG2yRko+jfm2MFwePsMG92mv1r GsWTErvgNdSyAkHeBOt8r+F2Pa62IDijtzgGTxrexLBvl4vmQiPmEuLBRRaF4lnDkHPcKcVmoAlZ hki+OF1IE+YiU68imjv2pNZVtVFpzoD2iylOVkM62RrE9R1L83926Dpn6BDMYyKff1QoHp2lM3Km VLCYesoapJzfeS5qWd4H1Tbqa277AQAA//8DAFBLAwQUAAYACAAAACEA1dGS8b4AAAA3AQAALAAA AHBwdC9zbGlkZUxheW91dHMvX3JlbHMvc2xpZGVMYXlvdXQ5LnhtbC5yZWxzhI/BCsIwEETvgv8Q 9m7SehCRpl5E8OBF9AOWZNsG2yRko+jfm2MFwePsMG92mv1rGsWTErvgNdSyAkHeBOt8r+F2Pa62 IDijtzgGTxrexLBvl4vmQiPmEuLBRRaF4lnDkHPcKcVmoAlZhki+OF1IE+YiU68imjv2pNZVtVFp zoD2iylOVkM62RrE9R1L83926Dpn6BDMYyKff1QoHp2lM3KmVLCYesoapJzfeS5qWd4H1Tbqa277 AQAA//8DAFBLAwQUAAYACAAAACEA1dGS8b4AAAA3AQAALAAAAHBwdC9zbGlkZUxheW91dHMvX3Jl bHMvc2xpZGVMYXlvdXQ1LnhtbC5yZWxzhI/BCsIwEETvgv8Q9m7SehCRpl5E8OBF9AOWZNsG2yRk o+jfm2MFwePsMG92mv1rGsWTErvgNdSyAkHeBOt8r+F2Pa62IDijtzgGTxrexLBvl4vmQiPmEuLB RRaF4lnDkHPcKcVmoAlZhki+OF1IE+YiU68imjv2pNZVtVFpzoD2iylOVkM62RrE9R1L83926Dpn 6BDMYyKff1QoHp2lM3KmVLCYesoapJzfeS5qWd4H1Tbqa277AQAA//8DAFBLAwQUAAYACAAAACEA 7e369KsEAAAZEgAAHwAAAHBwdC9ub3Rlc1NsaWRlcy9ub3Rlc1NsaWRlMS54bWzsWNtu4zYQfS/Q fxD4rlh3S0KUha9FgTQbJNkPYCTKFpaiVJJxnF3sv3eGknxLEKQ3pEDjB1uWOMMzh8PhGZ1/2tbc 2jCpqkZkxD1ziMVE3hSVWGXky93SjomlNBUF5Y1gGXliiny6+Pmn8zYVjWbKAnuhUpqRtdZtOhqp fM1qqs6algl4Vjayphr+ytWokPQR/NZ85DlONKppJUhvL99i35RllbN5kz/UTOjOiWScasCu1lWr Bm/tW7y1kilwY6yPIF1AbPktL/BXtXeSMbwSm19ke9teS/P4anMtraoAxoglaA3EkFH/oB9m/goY BhejE/PV4Imm21LWF+c0hdisbUaA/if8BiOasq228u5mvr+brz+/MDZfL14YPRomAAS7STGqLqLn 4fhx4gZDSDcsh5VfcWaNd9F1JhRcXDb5V2WJBuLtaGhmaxjNJlI2j2tGC4W3u+jzq80wF1KCs7dr Sz+1QJzixdVDDVn2LSO/P1CpmSRALcQd9tadiSFx8KLMQlDIwWXFuWGLi4G0S6UH+h5klZHviZMs 4kUc2IEXLezAmc/tyXIW2NHSHYdzfz6bzd0fBGzcIF1XRcEEeh1S2w2epVNd5bJRTanP8qYedXk5 pDfkpet0yY0oVMOrAt2ZP3J1P+PS2lCekaX5mBiPho2OYUD6mFQ4Ccn1AmfqJfYyisd2sAxCOxk7 se24yTSJnCAJ5svjkC4rwf5+SNZjRpLQC5GtV2JzzOd5bDStK1hgi1d1RuLdIJpiwixEYZZQ04p3 1wdUIPw9FR0lZqEhL7psaFO9nTbFEyK7h1+z9WjKlb7VTxyM4XrD3T5zClbeYCaeRoHli+3WSG+7 FD4ZhTVHmPwtaQ45PJEV5cTK11QqpvsNDBiHSeDyYGq49ACFVVN5mZFxGHthCCkvIO/A1vYSN/Ij Q/BgfzK9qbH/EkhE1lPl70G6bhSFQXSI0vd9J3kvlAitRxkcoIx8342gfu25fFeUCK1HGe5Rek6S jGPvP4MSofUoowOUYRQFDhxvp1xajF6KqfxqDquyEXrCVyAd7qlixMITAI746weRm22AflWbT1nZ X13nuqt+5oyDfXH0dFKayg33XhrXP32HTYG89BSN9xT5DmwBN/mgCIsb8tJTFB9QFCRJ5I8/KEKK kJeeouSAoiSKvPCF0vp/3GjIiznlD09tUKs0LXlhBPf3ZDJfxM44tEHhuHYQJK49DR3fHnvzJHRm U9eJpj/ITlxWcKqCvEQXEs5cDgUqI0zYX25BctZ6xhmF6tUrbpi9UyAXLqouKEbwDTOjNRPFNZUU RMOxk6KS2qjzU3dgCshBngyyxCgV1L6v62/QAl1LsdffHiop6EoGGY1l87n+vmmg5mJDMihx1YKC P751JM5h5B00GYuiMqNgDoC4mwSbFlyNY63+a70ysm54ChZiJ+4HWW60uAnXLOcQ8etxwxY4jdt/ U9x/re9AiQh1CRuNoU35aDSw5zTJDs1k3zt9NBpb/acaDVNBTM3CIr9TS7Axj9WRybp/sK6Y/da9 rsBt3L/ByLn8jbafN+bkgRcz0H1BdwO3WtBp/Y7fD8HdjK91Lv4AAAD//wMAUEsDBBQABgAIAAAA IQBKr3U51AAAAL8BAAAqAAAAcHB0L25vdGVzU2xpZGVzL19yZWxzL25vdGVzU2xpZGUxLnhtbC5y ZWxzrJDBasMwDIbvg72D0X1W0sMYo04vY9BDL6V7AGEriWliG8sb7dvXUBgJFHbZSfwS+vSh7e4y T+qHs/gYDLS6AcXBRufDYODr9PnyBkoKBUdTDGzgygK77vlpe+SJSl2S0SdRlRLEwFhKekcUO/JM omPiUCd9zDOVGvOAieyZBsZN07xiXjKgWzHV3hnIe7cBdbqmevlvdux7b/kj2u+ZQ3lwAmXyjiuQ 8sDFgNb3jtxLq6ss4GOP9j89QiwsB5LCeWWz6Asuwq8Zrt7e3QAAAP//AwBQSwMEFAAGAAgAAAAh ANXRkvG+AAAANwEAAC0AAABwcHQvc2xpZGVMYXlvdXRzL19yZWxzL3NsaWRlTGF5b3V0MTEueG1s LnJlbHOEj8EKwjAQRO+C/xD2btJ6EJGmXkTw4EX0A5Zk2wbbJGSj6N+bYwXB4+wwb3aa/WsaxZMS u+A11LICQd4E63yv4XY9rrYgOKO3OAZPGt7EsG+Xi+ZCI+YS4sFFFoXiWcOQc9wpxWagCVmGSL44 XUgT5iJTryKaO/ak1lW1UWnOgPaLKU5WQzrZGsT1HUvzf3boOmfoEMxjIp9/VCgenaUzcqZUsJh6 yhqknN95LmpZ3gfVNuprbvsBAAD//wMAUEsDBBQABgAIAAAAIQDV0ZLxvgAAADcBAAAtAAAAcHB0 L3NsaWRlTGF5b3V0cy9fcmVscy9zbGlkZUxheW91dDEwLnhtbC5yZWxzhI/BCsIwEETvgv8Q9m7S ehCRpl5E8OBF9AOWZNsG2yRko+jfm2MFwePsMG92mv1rGsWTErvgNdSyAkHeBOt8r+F2Pa62IDij tzgGTxrexLBvl4vmQiPmEuLBRRaF4lnDkHPcKcVmoAlZhki+OF1IE+YiU68imjv2pNZVtVFpzoD2 iylOVkM62RrE9R1L83926Dpn6BDMYyKff1QoHp2lM3KmVLCYesoapJzfeS5qWd4H1Tbqa277AQAA //8DAFBLAwQUAAYACAAAACEA1dGS8b4AAAA3AQAALAAAAHBwdC9zbGlkZUxheW91dHMvX3JlbHMv c2xpZGVMYXlvdXQzLnhtbC5yZWxzhI/BCsIwEETvgv8Q9m7SehCRpl5E8OBF9AOWZNsG2yRko+jf m2MFwePsMG92mv1rGsWTErvgNdSyAkHeBOt8r+F2Pa62IDijtzgGTxrexLBvl4vmQiPmEuLBRRaF 4lnDkHPcKcVmoAlZhki+OF1IE+YiU68imjv2pNZVtVFpzoD2iylOVkM62RrE9R1L83926Dpn6BDM YyKff1QoHp2lM3KmVLCYesoapJzfeS5qWd4H1Tbqa277AQAA//8DAFBLAwQUAAYACAAAACEAaaJf IR4BAADHBwAALAAAAHBwdC9zbGlkZU1hc3RlcnMvX3JlbHMvc2xpZGVNYXN0ZXIxLnhtbC5yZWxz xNXdasMgFAfw+8HeQc79YpK26Qc1vRmDwq5G9wASTz5YoqJ2LG8/KQwSKI5CwJuAiuf8+CvmePoZ evKNxnZKMsiSFAjKSolONgw+L28vOyDWcSl4ryQyGNHCqXx+On5gz53fZNtOW+KrSMugdU4fKLVV iwO3idIo/UqtzMCdH5qGal598QZpnqYFNdMaUM5qkrNgYM7C97+M2nf+v7aq667CV1VdB5TuTgtq +07gOx/V1fmy3DToGCTJdN5OB7vE84Hel61iylYh2TambBuSZfmSNOevGc4O8jZDb98s5FiU8eit ykOybMmAHpUFMytiyopgZnFDC6a2iZnaJpiaf+vjPa1ZGrKtY9LWIdk+pmz/J6Oz32/5CwAA//8D AFBLAwQUAAYACAAAACEA1dGS8b4AAAA3AQAALAAAAHBwdC9zbGlkZUxheW91dHMvX3JlbHMvc2xp ZGVMYXlvdXQyLnhtbC5yZWxzhI/BCsIwEETvgv8Q9m7SehCRpl5E8OBF9AOWZNsG2yRko+jfm2MF wePsMG92mv1rGsWTErvgNdSyAkHeBOt8r+F2Pa62IDijtzgGTxrexLBvl4vmQiPmEuLBRRaF4lnD kHPcKcVmoAlZhki+OF1IE+YiU68imjv2pNZVtVFpzoD2iylOVkM62RrE9R1L83926Dpn6BDMYyKf f1QoHp2lM3KmVLCYesoapJzfeS5qWd4H1Tbqa277AQAA//8DAFBLAwQUAAYACAAAACEA1dGS8b4A AAA3AQAALAAAAHBwdC9zbGlkZUxheW91dHMvX3JlbHMvc2xpZGVMYXlvdXQ2LnhtbC5yZWxzhI/B CsIwEETvgv8Q9m7SehCRpl5E8OBF9AOWZNsG2yRko+jfm2MFwePsMG92mv1rGsWTErvgNdSyAkHe BOt8r+F2Pa62IDijtzgGTxrexLBvl4vmQiPmEuLBRRaF4lnDkHPcKcVmoAlZhki+OF1IE+YiU68i mjv2pNZVtVFpzoD2iylOVkM62RrE9R1L83926Dpn6BDMYyKff1QoHp2lM3KmVLCYesoapJzfeS5q Wd4H1Tbqa277AQAA//8DAFBLAwQUAAYACAAAACEAUv+O5BoEAAB8DQAAIgAAAHBwdC9zbGlkZUxh eW91dHMvc2xpZGVMYXlvdXQxMS54bWzcV91u2zYUvh+wdyC0a0c/lmRbiF3YTjwMSNOgdnvPUVQk lBI5knbsDgX6Wtvj9El2SIlO4zibk67AsBvZog4Pz/k+no+H56+2NUMbKlXFm7EXngUeog3hedXc jr13q0Vv6CGlcZNjxhs69nZUea8mP/5wLjLF8iu842uNwEejMjz2Sq1F5vuKlLTG6owL2sC3gssa a3iVt34u8R34rpkfBUHq17hqvG6+PGU+L4qK0AtO1jVtdOtEUoY1xK/KSijnTZziTUiqwI2d/TAk vROQLQCjV5VmdNrkq62HrL3cwJfQmwAEZMly1OAaBt6DaUUwQ9YeAWJoRbfamimxkpSaCc3mZymW 4kba2debG4mq3HjrvHh+96Ezs68NmMEf/2D6rfOEs20h68k5zgAdtB17QOLOPGESziAIRNpBcj9K yjdHbEl5ecTadwtABPtFgX/RZvQ4ncilcwBKuE+vnYPBxxUnHxRqOCRscGjzJNcb59Ukb9YRJWo5 0YYPD3FZAXMtRd2s1tTC5GYrC7WLfw9QmkajOGhhigZx2h8+xCoKkoH9bhBLhkmYRIldxHmCRVrX ItPbGc93Bulf4RcINZtm7FFskm/dMqWXeseo5QNQwxmkBA8wZtgUGm1675ZQaLWeM4qhEDvu9GTO KvIBaY5oXmn0GitNJbIQQFmCy3MgR8Pe6FzSJr/BEr898GxQxRmsDHG7eG0KBtmneew/5tHsphuG CS05yyGUyGQIheAIexGlBrgDRqEsYM+6/XA6s3EyAGGx+/8YsWkQjobm+/ciFvYbYhu2Z/AbiTZw W57VA6JbMi2j8HBLWrSesbeWlHCQKUY3lJ3g3lL9DPerspKne++3pXIyXgu+lro8Ofj4ue6r4qh3 0NN/tcRiV2JvKYFj9pZRZEP9+5ICvZyXYE2nUvK7kuJc3RfLvhbNeXEgnrkGlfkIRyNmhdfVmNUa q5rG2P45lE/WtLr8lOZZYXMqZ6QNSiDspDenBchRq0D7YdjAX5tbTTxi3w09ATnKK6ndkfYSfUse g29l/juBX2jZov/bGkvQcUfACSr3PyUgfUxA+s8Hyot3P3Ss1+v6KAdW3P7TRVBAq2l6xd+j6TyI pmnSGywug14cXSx6s8FF2JslUZqMFsFoFgSfvK5bUqzKaQNJH2s4bNk+XXZ68uXzHz99+fzn/eEA QRhH31KQtu9w/TCcb1cK+hdh29S1rCC/2WyURvPhrDcL40UvvhgNetMFpLtI+nE8nw2n8/7lJ8hH hHFGJLXN+y95d4mAwUeNf10RyRUv9Bnhtd/eIHzB76gUvLKXiDDobiIbDEd3Pxr0kzgJQqvEEC9E aYXRRQtDpvO3jQ+Tr7F4s7HnFtx5oKzndkjALacVTXJvYnJ3t6bJXwAAAP//AwBQSwMEFAAGAAgA AAAhADhHNoLdAwAAnAwAACIAAABwcHQvc2xpZGVMYXlvdXRzL3NsaWRlTGF5b3V0MTAueG1s3Fdd b9s2FH0fsP9AaM+OLNvxhxC7iF17GJCmQe3unaOoSCglaiSt2B0K9G9tP6e/ZIeUmCCxgzlrCwx7 kWXq8ujec+89vLp4tSsEqbnSuSynQXTWDQgvmUzy8nYavN+sOuOAaEPLhApZ8mmw5zp4Nfvxh4sq 1iK5onu5NQQYpY7pNMiMqeIw1CzjBdVnsuIlnqVSFdTgr7oNE0XvgF2IsNftDsOC5mXQ7len7Jdp mjP+WrJtwUvTgCguqIH/Ossr7dGqU9AqxTVg3O7HLpl9hWhBjNnsAuLsVI2VKJghdLYWCSlpgYVN bgQnIIj8CuOcUUE2fGecma42inO7oax/VtW6ulFu93V9o0ieWLQWJQjbB62Z+1vCDDfhk+23HonG u1QVswsagxWymwZI3t5esYnGcIKwZpE9rLLs7RFbli2PWIf+BfDg/qXIe9VEdBhOz4fTkBLdR9WY Umy9kuyDJqVEnDb8Jjx2XXswG7OFrzLSpMBYflu75qHjw9trcOrIMru5TPY28N/w6xZpLLRZm73g jhC4TWOA4wL6BbUVzsvO+zUqvDALwSk6oCXPzBYiZx+IkYQnuSFvqDZcEecM+gGQF2DHIDktJC+T G6rouyfINj4a481w2nuI24bC54nseyIf1RS5EZTxTIoErvS+BbmWqoBIlaMJmmoPUJcoGp+ZlzBu ZQQonFqnrXfH+Ee6iKjFPdFfmQ9b5C4d+lE+Gs4d8bj4V7qgXlACa84k+lrwmosT4F1GXgC/yXJ1 Onq/YfRkvlZyq0x2svODl8Ln6VF06M437YSB74R3nOEYuoXWOlehwV40jsgKBGaRwZpfKiXvMk4T /VDT9xutrj5Rm8RADD7i6KAi9a3gJMGJjjU+UB9X56VtdNvXDZ5v9aNi5DbUInK2NE54CtVohAKd 0SyjgL12WXMnXUfs26VnKCdJroyX/n8jQ+eH5J/bOvlO5KdGNez/vqUKcusT8A9i9D9OwPAwAcPv mABMdNfb4mgOnLj9p5sgxUhmZ6o/RuPecjge9DvRsjvuDF4v+53JaIi77rDbH4znk2g1+hS044UW ecJLBG2r6Olc4M6w59vOzL58/vOnL5//ejgc4IQF+pqGdDLi50acb1caY0blxrmtyhHffD4Z9hbj eWceDVaIbzLqXK6G553VeX8wWMzHl4v+8hPiqaJBzBR3w+0vSTtkY/FgMC5ypqSWqTljsgibCTus 5B1XlczdkB1120m9pji6o9H5aDIaT4ZjW4vwF176X+ctluyE7IRCqDe0elu7cwvfBGjrhVuq8BXQ 7GYPJjZ2/1Ux+xsAAP//AwBQSwMEFAAGAAgAAAAhAG+da0DBAwAAZAwAACEAAABwcHQvc2xpZGVM YXlvdXRzL3NsaWRlTGF5b3V0Mi54bWzcV+Fu2zYQ/j+g70CovxVZtqy4QuwiUuphQJoGdfoALEVF WimSI2nF3lCgr9U+Tp9kR0pM1thBnaYDhv2RJer46e67u4/nk5eblqGOKt0IPg/io1GAKCeibPj1 PHh3tQxnAdIG8xIzwek82FIdvFw8++VEZpqV53gr1gYBBtcZnge1MTKLIk1q2mJ9JCTl8K4SqsUG HtV1VCp8A9gti8ajURq1uOHBsF8dsl9UVUPomSDrlnLTgyjKsAH/dd1I7dHkIWhSUQ0wbve3Lpmt hGjF+98D5IxUB49xsIC4yYqViOMWFq4awygCdlAhuAEkZ6DllaLUmvLuVyVX8lK5fRfdpUJNaXGG /UE0vBjM3CMHM7iJ7m2/9kg421SqXZzgDMhAm3kAOdvaK2zCGd0YRPpFcrdK6jd7bEn9ao915D8A Htx+FNIt+4h2wxn7cHo64tuoelMMW88F+aARFxCnDb8Pj1x0HszGbOFljXrmjWV2sOtfOj68vQZO HVlmk4tyawN/D79uEWdMm5XZMuoIAbdxBuBwAfoZtoVNefhuBYXdmoJRDIU/kGcWBWvIB2QEomVj 0GusDVXIOQNtAJAnwI6B5AyQlJeXWOG395BtfDiDL4PT3kO47Sl8mMiJJ3KoJnTJMKG1YCU4MX4a rU0JReGZ/wmMQgIQ69gtdU9k2JatI1h/w3DPoqMSLv6TLoxHJHVFiYAeZbSj7AB4x/Qj4K/qRh2O PrF5fAT6UqyVqQ92PnksfFPtRQcl+am1nfjafksJnCfXoJvOVdBTLwN7hAIko6jBmp4qJW5qikt9 V8W3G61S3tOP0kB7/wlnAGZVAKJri981uZMRa7yjJzYrjNvWtZ3a4/nm3SsvbkPHYmeLs5JWoAN9 60Nn9MtQwF6NrLkToz32w9IDlKOyUcaL+Y8Iy3SX/On35eSHya+M6tn/Y40VCKhPwHfk53+cgHQ3 Aem/mAAYzS7W7d4cOHH7TzdBBeOVnZL+StMiHqXL4zBOlmdhko6nYZ6PizCPJ8dJPIuTPBl9DIaB QbOmpByCtlV0/6R3ivtw25nF10+fn3/99OXucAAnLNBTGtLJiJ8E4Xw71zA4SDegrVUD8eX5i3Rc zHIIKFmGydmL4/B0mU7D5XSSJEU+Oy0mrz5CPDJOMqKom1J/K4dpGRZ3Jty2IUpoUZkjItqoH5Uj KW6okqJx03I8GkbuDsPRnYwms8l4OvN9CU469fPOQgR22LVeE6ZeY/mmc8c8zPbQ1YVbkjDN95r5 DxMbuv93sPgbAAD//wMAUEsDBBQABgAIAAAAIQADSt2WUAQAAH0OAAAhAAAAcHB0L3NsaWRlTGF5 b3V0cy9zbGlkZUxheW91dDEueG1s3Ffrbts2FP4/YO8gaL8VWfcLYhe2Eg8D0jSo0wdgJNoWSl1G 0k7coUBfa3ucPskOb7ETO2ugdcOwP7ZEHX7k+T6eC8/fPDTE2mLK6q4d297ZyLZwW3ZV3a7G9ofb uZPaFuOorRDpWjy2d5jZbyY//nDe54xUV2jXbbgFGC3L0dhec97nrsvKNW4QO+t63MK3ZUcbxOGV rtyKonvAbojrj0ax26C6tfV8+pr53XJZl/iiKzcNbrkCoZggDvtn67pnBq1/DVpPMQMYOfvplviu B295zQm2LWlGtzDg2RPwvFyQympRAwO3wsJakLrC8hPrbynGwqjd/kz7RX9D5Yzr7Q216kog6Jm2 qz9oM/naghk8uM+mrwwSyh+WtJmcoxyIsB7GNui1E78wCeX4gVulGiz3o+X63Qnbcn15wto1C8AO HhcFqXvl0bE7vnFHEeE9eqVMEUy96sqPzGo78FO4r9wrr7cGTPgs4Pu1pVgvOZVo2lR9l5SYKUzS avb6SEacRulIMeJ7wSj0o6e8JEnih8JAsOOFyWikLA69VtB9zh9mXbUTrN7Bv1QF5YTxBd8RLNkG TlAOO4cf0JYgETG4dT4sIGIaXhCMIKK0MnxSkLr8aPHOwlXNrbeIcUwtLk8PE5DnsAkOymtI3FY3 iKL3z5AFeSiHlYEOs0N4VPq8rFJgVFps7tSa/vcQim3ulFBwsuHYGW1fL5gXJF6sFQvSNIac8FSx GOSSkkrFksgX1ooEFQjSeXV+DB8nFRMykS3x4OBYDaJXMnLqtoLol4+IrEAtOHkQxQCwuYZsJ1Wu 8BJEUEtqAI3l77HCKBFbtwYAChQNGOwBMy+UB3UAoEDRgOEe8JHpAYgCRiNGB4ipn0ppBiAKGI0Y 7xF9PwV5h9EoYDRicoCYhMFQYQSMRkz3iAJuqDICRiNmB4hxlMgYGMCjgJEZwSQmAf8d8hIE9r+V mkKTmt7jEvqMFVTT8Nu5CcpJsQZrPKW0u19jVLF9/vmr2lJxyM6foDdAZAnxKtOWyiii5Eo2xcNC EisSq5asFRnAvO9z77dyjdDjZAaBLH6kmV7r0F4PvVANrKqm3BT6IXUhOiZflkxocUx9PlHBB5O/ hPQq2f91gyjUPyPAKwoH+X8KEB8LEP+Dpx9a9utNc1ID2RDACf/vBsESmm7RQf8WxJfZxSyZOmEc ek44KzwnC4rMmWbz2PPj4uIyiD/buplkojVvwWkRis8bNVnhXw47Pvn65fefvn75Y9+cwSYE0N8J SJlGzC0BWvYrBn1fL5v3Da3Bv9ksi/0inTkzL5w74UWWONN5HDnzKAjDYpZOi+DyM/jTe2FeUixv L79U+hYFg0c3n6Yuace6JT8ru8ZVVyi37+4x7bta3qK8kb6KbREZ20GWeJHveVkiey25N5n+zG7B BXEHEtsuCX2L+ndbWdng0gdhXcihHq55KmkemAjfzbVx8icAAAD//wMAUEsDBBQABgAIAAAAIQCN AHEZRgkAABA8AAAhAAAAcHB0L3NsaWRlTWFzdGVycy9zbGlkZU1hc3RlcjEueG1s7FtbctvIFf1P VfaAQj5TtIgHAZBlakqkxBlXyY5qpKl8t4CmiAgEkEZTj5lKlfeQHWQXSf6yFK8k53YDIMCHTI1l ezykPyigcXHRffo+zr2AX3/3ME+MOy6KOEuHpvWqaxo8DbMoTm+G5k9Xk05gGoVkacSSLOVD85EX 5nfHf/zD63xQJNFbVkguDOhIiwEbmjMp88HRURHO+JwVr7Kcp7g2zcScSZyKm6NIsHvonidHdrfr Hc1ZnJrl/WKX+7PpNA75aRYu5jyVWongCZOYfzGL86LSlu+iLRe8gBp1d2tKx1hfeJlE9Pf6Rv9e iOPXbFBkSRxN4iRRJ7RQPk6EcceSoXl9Y5lHx6+PVqT4dMpDeV5Iukb6SJM6IMVFfiU4p6P07nuR X+Z0FU9/d3chjDjCpphGyubAnnSrC6WYOk0hpvW2br+pNLHBw1TMabKAzngYmtjhR/rFTWzAH6QR 6sFwORrO/rJBNpydbZDGYvUDsKD6obQqvaINy+naXrWiH4ELS28Sbtj14vQdgDA/z8LbwkgzLFej kI1nkOYnQmT3M86igob14gFX9ShChB6ezwz5mAM3GcuEl3L6Iuaa1vIFEDeu799mEWTZQmYmIbOC mtvzYbAKOtt3PSdo4xfYdt+j64SiZblOFyc0s6WiXBTye57NDToYmgJLVw9id6VlsEElQs9PMzIy tUlJ2hqATj2CzcOt1TYuRDw0f+l3+2fBWeB2XNs767jd09POyWTsdryJ5fdOndPx+NT6Bz3Xcgez OIp4So+pPNhy17xmHociK7KpfBVm8yPtfpUXw/2srvZhmkXbNcTNde0YE/WvBKQhdtSehsILq1pZ kmW73ZHd70y8wO+4E7fX6fvdoNO1+iOA7vbd00l7Sedxyj99Scb90Oz37J7apcaksdDm2rDTy81u ic1jCo5JPB+aQS3EBmS5Z2mktlayONHHDSho+ksosN3VRsNsyVjJuOXDKIseCahr/IUBI4bDqmaZ +Nk07gWDxxR/XzDBTSN5k8JR+pbrwj6lOlHWbBqieeW6eSVdzMcZIhpiD0tDaB2aoRTVyVjinIw9 m+dMnqeXeUiiNBsy4auHvzKRl3YuMfl32eWM5VwJrJi7llWr1QshJUkhL+VjwhVECCRQixUmd5hQ GbeAARsIGkRAGJo87fx0iUQ1l+OEMySyUkwej5M4vDVkZvAolkaZr1RAQFrDI8hDYW/4hUr84mlA uUJXAU5wPxnO/PVw5pCtq1j98uGMcDKRGRC2q+j3AlHNQviiCKcwx56ptNAKay58oe+plQGoKj5W MesQ1pbEoOHLmikAr0NY+22GNfm7CWrktCqmFRuCmopsjTiqIocKervF0UseZmlkJPyOJzuoV3Tu GeqvZrHYXbuKQc/QPskWQs52nryrg+DOOWYST5/Q/ux0gopL8/0lO1Yz+kzpJIIHFD+DOrBkWqYV tXuY9wukFc9G2gCHaqUV23Kcmi27vmf3XpIst3hbg0Y/k45VJLtdvH09/vXFA5ViYneJRdyLs/N0 JG4VIaQaDCX8xSINwTg17Yv49EeIkR1Zbl36gLHR3YpYVZxOsbmS0tEffSfMg8gXySJVptEFE4wU tuhdFAtZFam/kqr1131L2eZn8q0pcWYChag4ioHSvzSH+vX+5aAiqqrRzQ4W9HsHB3tmgfNVHYwl NyhbVI31O/E1BwXiah7zPmNZhHbku8V8k7up7PkJ6czr9Zyn3e2Qz9Ad+/bcDfH4izrbNIlUR/cX 3x+NbHvU74yskd1xvZOzzsg/Czpn3tgZgw5ZIwstrbJ9WaDhzNGQMSk3rvY8FK8q8+aGVCqPP7z/ 958+vP/PkrNjEp+aZFVbpOpao+xQXchcNZN1F3KExpw9DkZYnzvpuKd9H11Ir9eZ9BzXHY+Ck7Fz Ri27HF3IUHDVf38TlS07DO7Whcyzey7yLFbvAapGpO7E245tBX3X71WpVpXfmHc1WxxW/f0wEW9Z bqB5PzQTiY6XfMBRdIuj6xubxmwaw1F0iyMWhnhlAInyoBrBdT1SyzjViFPJYGFaxq1GetVIrxrx qhF0yWdJnIJ0qT+mMc2SH/RAdaTDKSLfOXvMFvJNVO5EY0QZnG25vhs4ngv+Iwb0UkG8iVQJiNbW 8u6WLDj5UrZsz2+VBVa1XgX5E3qBTy1bFjZb9QK5WrYkaltlgWktWyaarbJAu5b111Bs44B9qGVV 2/+JtaEVWMv2P6IXdV4ta6kC6AnFrY2r2n6N5ZUbLx9U47RQLWJ67aFOyd9LLm40iIaQqqG6jIHY 8WmWyhPFRa5ZgeZxm+x3VQwq8nDEp6QURxeh1C5XlXCtqydT1czfIldebRQP6FGXz1h20/CY9ms2 +CJBixKg1W6nl4CpiplTFuJVzp/nf+skkiRRUrCVC5zpC2GxciEsSt16Vrp2qeoYBaNNBdH+wHgi Ypag1z9jouCybK0D+zY+BEppZs4BH7LNNj4ESomPe8BnHR8CpcSnd8BnHR8CpcTHI3zmTJwPzeqt 9IZotBLI6d5WZP7txu3dAg6hUALiLwFRbzmRxvYQEEKhBCRYAmI5Pr3Z20tECIYSkX4DkcAO8Dp+ LxEhGMBo8IK7wQ3xRRLeKK8RRR1hHNfuE1hxihoU2b9TDWgPAzF4WRaJPgseV7K7Js/ciUleL/CF kFBcZWh+eP8vzfEa/FL1cVQsfJJfaoL9UX6ZbuOXaWcLv0w7O/JLjb4P9KkOq9G3g55PA98C+v9c Q98mv3tx9Ne41ioX1VhWX2U1wLSDRmj81kwZH0V9CTBXiWsJJoBTLdGlZX5DYG6wTIo6n98yV1mu BtPu9nzazG/RMv/333Uv/zJYbmbE6J26yqk/bpg7M+QXzElfD67NfNnu+5YiQwe42vX6Zjatyc9O nrpf1rWZajtB4O2YJfYLrpqHN5h3PsjkjIuah8MeL3T9UvLX5rcQmiAvRarurk4oTYIImSt2fYlv EKraeI2wo3mveqflJx64u931Xf/EQ4WMWy7ov4zQBr945lzr2L4Uo253TMD59hafzSy5MpK6wNhb fLYQ33Y/ZZ8NaDOZtdrtlX0GaAtDVYXSIUQjZW3hpL6rP7c5xKAtLBQpV9WLB4C28E6v57c7O3ub xWqm2SSX1ACuPxTACb4j0P8z6vj/AAAA//8DAFBLAwQUAAYACAAAACEA1dGS8b4AAAA3AQAALAAA AHBwdC9zbGlkZUxheW91dHMvX3JlbHMvc2xpZGVMYXlvdXQ3LnhtbC5yZWxzhI/BCsIwEETvgv8Q 9m7SehCRpl5E8OBF9AOWZNsG2yRko+jfm2MFwePsMG92mv1rGsWTErvgNdSyAkHeBOt8r+F2Pa62 IDijtzgGTxrexLBvl4vmQiPmEuLBRRaF4lnDkHPcKcVmoAlZhki+OF1IE+YiU68imjv2pNZVtVFp zoD2iylOVkM62RrE9R1L83926Dpn6BDMYyKff1QoHp2lM3KmVLCYesoapJzfeS5qWd4H1Tbqa277 AQAA//8DAFBLAwQUAAYACAAAACEAJZjve58EAADQDgAAIQAAAHBwdC9zbGlkZUxheW91dHMvc2xp ZGVMYXlvdXQzLnhtbNxXW27jNhT9L9A9COq3Y70syULsge0k7QCZTDDJLICR6FgY6lGSduIWBWZb 7XJmJT2XkvxInMJwMUDRH1uiLg/v81ze83fPhbBWXKq8Kke2e+bYFi/TKsvLx5H9+f6qF9uW0qzM mKhKPrLXXNnvxj/+cF4nSmTXbF0ttQWMUiVsZC+0rpN+X6ULXjB1VtW8xLd5JQum8Sof+5lkT8Au RN9znLBfsLy02/3ymP3VfJ6n/KJKlwUvdQMiuWAa+qtFXqsOrT4GrZZcAcbs3ldJr2tYq3j6C2eZ bRlBucKSa49he3onMqtkBRbueEqHWyTIpfmq6nvJOcmVq59lfVffSrPpZnUrrTwjkHaz3W8/tGLm tYQYHvovtj92SCx5nstifM4SeMN6HtkI2pp+sYkl/FlbabOYblfTxccDsuni8oB0vzsAGmwORbzr xqLX5nidOfe5FtxyN1Y1ogxbr6v0i7LKCnaS+Y156c2qAyObCb5eWI3rNUG1cs1H449OXhmfdopu PBF5nu/6xh1B4IRD54VToijyAixa5BrXDz0nGphDOiQc0kDXiX6eVtmaXPqAf0SOlemiQpZq2sES ofSdXgvEGc8r4UIji4lHlJFAFrAk4/NPWFK/jWwciTMfTOBTBg8wIdpj250I9z4inM0SuAQ/ABGM 6pGXvc93qMdCzwRnOKi1To9nIk+/WLqyeJZr6wNTmkvLuBDVCx0JXZszDCQvs1smGam3i0xRYQlO hhc6641DKDJvhx/+bkrhnnLvVrCULyqBYrA8MhLV0sX5pEwg79soG+R0lzgnJYQ3dMIIyWGC11XJ fkIMHMeNozYyTZEdkxAPDeahhCiYvDYFmpcZmIYeKaYPyxvQqdFkJ01AiSailApNQpEsHj3KrQYq GEQQgz+OwHPjXTwCafH8Ld7QRaEcixfu4hFIixds8Vw/cknsOAXp6CbrYCWhtICDHcDYi8mOEwAJ pQUMt4CeF0PBkwAJpQWMdgCjwD8+JnsmE0oLGG8BCe34oOwBEkoLONwBDAfRiUEhlMPkRPCI2oaF zLmnkxVVpOEqtUdWpxBS0BHSJ/RmMCd6UkBp9s9MhO40W0CaT6SsnhZo52rLOBsKo6ZMHtlpVZkG J4PlF0zMO6Jq0roTBomUm1bXtS5RUua/3W8MOxzgFApvQxqbyqHe82aQXsobWdwTDvcAK8ul7u4N pzh/8Nr5psV+J+fPtWy8/+uSSXS9LgBHtIr/aQDC1wEIv2P2Ywy4WRYHY2Dav8l9k57/wSKY4xpP F/LfQ9+ZDC59vxdHwawXDC8Gvdjxw94FLomRN3En3vTyD7u9myqRo5nDaCqtl4xnyratsd0ybZf0 +NvXP3/69vWvLctBCQL6NwVpaKQbOsCk1wq3vdrMAkuZw77pdBh6s3jam7rBVS+4GEa9yVU46F0N /CCYTePJzId92OMGSSq5mYjeZ+1khsVX01SRp7JS1VyfpVXRb8ayfl09cVlXuZnMXKcd71YMTQLX ljiMwtCkItSFkob9OmWxREOVIWkhP7D64wqUxhLMkajqmVmqMTk2nJluRcj0bhId/w0AAP//AwBQ SwMEFAAGAAgAAAAhAET5CQx5BAAANhMAACEAAABwcHQvc2xpZGVMYXlvdXRzL3NsaWRlTGF5b3V0 NC54bWzsWF1u4zYQfi/QOxDqsyLJlmRZiL2wnbgokE2CtfcAXImK1KVElaQdu8UCe632OHuSDinR iX8SO5sWBYq82BL1cTjzDWc4nPN3q5KiJeGiYNXA8s5cC5EqYWlR3Q2sj/OpHVlISFylmLKKDKw1 Eda74Y8/nNexoOkVXrOFRCCjEjEeWLmUdew4IslJicUZq0kF3zLGSyzhld85Kcf3ILukTsd1Q6fE RWW18/kp81mWFQm5YMmiJJVshHBCsQT9RV7UwkirT5FWcyJAjJ69rZJc12CtvGc3n361kMbxJYx4 1hBMT2Y0RRUuYWB+z9CEVRLE6E+innNCFKha/szrWX3L9Yzr5S1HRaoktDMtp/3QwvRrBTB4cHam 3xlJOF5lvBye4xiYQKuBBQ5bq1+YhGOykihpBpOH0SS/OYBN8ssDaMcsABpsFgVf141F++Z0jDnz QlKCvI1VDRTD1CuWfBaoYmCnMr8xL7leGmHKZiW+zlFLuxLV4pqPmg+DF8CpJkuuxixdK8M/wb8e xDEVcibXlGhCQG0cg3D4AfopVruaVPbHGezqUk4owbDrW/LkcEKL5DOSDJG0kOg9FpJwJLVdQok8 B3YkOKcVSar0FnP8YUeysg/HsDIobTSEx4bCp4nsGiLb3YRuKU5IzmgKSnReR6v4HaIB08yCHQjb w/jgCW4VXTu7zA96EK96q3mh66pnza/ZcL7bjWDcQmrb+UEn6Idd7UAjSRPQuNlwctBram26pJ4O GxynJFP0Kv07UbMocPsIAI+dA1j/MdYAANs9gHUfYw0AsP4+1tvSwQAAGxzDGgBgw2NYAwBs7xjW AAAbHcMaAGD7x7ANQHHdhpNyjI4mmIlAwiZsXhldagfp4BJb0dVE0O6SeuO+IKBnJGFViihZEnqC eB1lLxA/zwt+unQdEC+QPmULLvOTlfebiDzZHdMiOygdTpF/NK/5z+U1zQmcp+YweOFxsZPXtP/0 UaEyjX54fGYcymuhH70lNjgR3hJb/JbYNoXQW2I7oWALTGL7QBK4Id1B9atz8PPpDOrgSQ5oMuKc 3ecEp+KhINvkQVX+7xTFqYSadaeO0w57PuHRStWjqvz83uqrqWfhyG+KsidqApVcm2qtrX/Vck+e JSgtuDQ3lOasBx1NZXgC+eE++cHxGvm7yc8kb9j/bYE53ApMIX1CJf0/dUBv3wHhv+gAaDZcL8qD Pjjh1P+PfZBBt0Bd/f/wot7l1I36dt+9nNi+N5rao243tEf9YBzBl4t+NPpitbdgQYuUVGC0iqPd 66u+fW0V8VthJ4ffvv7507evfz1UvaDEawNSx6Vpb0DhfiXgNlzrrsOCF2DfeNwPO5NobI89f2r7 F/2ePZqGgT0Nur4/GUejSffyC9hTe36ccKL7Lr+kbf8HBvd6NmWRcCZYJs8SVjpN88ep2T3hNSt0 /8dz2ybSEsOdJAi9XtjvB5G+fGrVdPYzyoIFqnejtE4of4/rm6VOU9Ctgqie6KEa+lOKzC2IMt30 u4Z/AwAA//8DAFBLAwQUAAYACAAAACEAktVrLNQFAAAGHQAAIQAAAHBwdC9zbGlkZUxheW91dHMv c2xpZGVMYXlvdXQ1LnhtbOxZ227bRhB9L9B/INhnReJVF1gKLCUuCji2ESsfsCZXJhuSyy5XspQi QH6r/Zx8SWeGXIm6BbQcoEGrF5kmDw9nZnfOzs5evF6mibHgsohFNjStVx3T4Fkgwjh7HJofplet nmkUimUhS0TGh+aKF+br0c8/XeSDIgmv2UrMlQEcWTFgQzNSKh+020UQ8ZQVr0TOM3g2EzJlCv6V j+1QsifgTpO23en47ZTFmVm9L5u8L2azOOBvRDBPeaZKEskTpsD+IorzQrPlTdhyyQugobe3TVKr HLxVT2K6nD6J24ffTYPAcgG3LXME/gf3SWhkLIUbE5HmTMaFyOhJkU8l54jJFr/K/D6/k/TCzeJO GnGIBNWLZrt6UMHo3wxgcNHeef1RM7HBcibT0QUbQDSM5dCEQVvhL7zEBnypjKC8GWzuBtHtAWwQ vT2AbusPgAXrj8J456VH++7Y2p1prBJuWGuvSiiDV69F8LEwMgF+ovule8HNQpOhz0ifR0YVeqSq cOVDiofGFxBTCpZajkW4Qscf4C/dZIOkUPdqlcAQwPUisWgA2CDks/dlaGu3wds6HJxkAzAFfmCw EoZ5wLPWh3vIg1RNEs4gT6pQq9EkiYOPhhIGD2NlvGOF4tJQFIUCDbgAdgVDWVHyLLxjkoERW8wY DTaAL4OL2h+4LAN+POzOOuw45ncJC3gkkhAssL/HCGA8TZiuMJf0gB0ZCIzWzpR0vS4kOM1Ly3M8 y3LQpM3sdDtux+qBuOAc9Z1+1yebIQwlEblfTgkdET3CBsuCSIBaPJSU9dGrBttImbymvIizEBIc L/HrD/MbUDEypJwLRvFpaNouWvqg3azNDbq0YfZUhNqrRqydfVakQjvATGfD2rdcsqAJq9XbZ0Wq itXdsFpO1/IR3IiWkNshQK6K1qvR9uwe2XAqLXJVtP6G1rZ7YMILrEWuirZbo+26Ds3DU61Froq2 t6FFzuZDdiC2yFXR9mu0vtd90ZAhF2lJPSdI0fAjMOvW0kVfP13hUHBI4IothTtFxVytYhORKcjV LSEj1YClVi8Uz1xKMLsjlswqGSslBpdVChNe1NcTHJDjMmZbXbfX9b4hY07fsyA5ENFEx0iG6gO1 t1Jt1KmkrAHgUotJXckwhdZYDQCslogalpRkjdUAwOq8r2NxVq6xGgBYncxHsRoAWJ2hR7EaAFid dkexGgBYnUtHsRoA2DJBdCVA8SWRXPv2Y2QQFQPwo5OW1t9nlCX3PBBZaCR8wZMDCbpLT3nxDPpp FMvm7NXK31hxrsRcqqix8W6Zkc3p49lBdqhNvmt15mldm+5WZ2Tx6aJW1sdldYYC98ecSSg7K42j aFOp3FjjfNfr2GAuVGLHajWrC8p3rtWG5rlWg3r5XKsNTef/WKv5WtMO1WpUGp0ua/tSRjp5spQd q9c2Unau1zDm2/XPuV470tP55o5nt6A612vYQit3g7ux+VHrta7Wtvc8gIb3IzQyGxRq0NKcRIDm l1KKp4izsNB9pJoU6i1nrb8ZKmgobm9PrXKPpcGkfLv70yTDrQr2BrG827QLdXMMnm73M2HT8+z2 J3HrTVK5NapuHSmRjTCWSjebT2kCQCOw7KRvgt9gOTk5+DMF5fL+gmM16HP+Rwegvz8APm6sapP4 QO/l5AGAs6ObeXpwDBo0af7lMZjBuQ+e4vxp2Y5te/6kBZXEVct1xm7r0nXd1mRidfu207Ft+/Kz WR1oFEkMrWhwGjN0t/NGaXs87dTo65e/fvn65e/NZh6MQKKXJCTJiD6pgvXtuoCjipwOkOYyBv/G 475vT3rj1thywb83/W7r8sr3Wlee47qTce9y4rz9DP7kljsIJKdjtN/C6jgPbu4dwaVxIEUhZupV INJ2eZbXzsUTl7mI6TjP6lRnggsGzUrb8j2nA82nsqlGtpH8aWvBBTyGo3mayHcsv12ALLIBnD7C lnhCt3I4b0QRA+gGgr7r88vRPwAAAP//AwBQSwMEFAAGAAgAAAAhAByF/VQcBQAAMhMAACEAAABw cHQvc2xpZGVMYXlvdXRzL3NsaWRlTGF5b3V0OS54bWzcWN1u4kYUvq/Ud7DcawL+xViBVSBJVSmb RUv2ASb2EFtre9zxQKDVSvta7ePsk/Sc8QzGCeyyXqpKvQEznPnm/H7neC7fbPLMWFNepawYm9bF wDRoEbE4LZ7G5oeH215gGpUgRUwyVtCxuaWV+Wby80+XZVhl8R3ZspUwAKOoQjI2EyHKsN+vooTm pLpgJS3gvyXjORHwkz/1Y06eATvP+vZg4Pdzkham2s9P2c+WyzSi1yxa5bQQNQinGRGgf5WkZaXR ylPQSk4rgJG72yqJbQnWlmn0sDENKcbXsGCZE7A8WmSxUZAcFuZpJFacGs+pSIwZKVEPKVOVD5xS lC7Wv/JyUc653Hq/nnMjjRFKQZh99YcSkz8LEIOH/ovtTxqJhJslzyeXJASPGJuxCYHb4idsIiHd CCOqF6NmNUreHZCNkpsD0n19AGiwOxRiXtYWvTbH1uY8pCKjhrWzqhYlsPWORR8ro2BgJ5pfmxfd rzUY2ozwZWLU7hcIpeTqP6U/tHwlfaoV3XnCGo5sO4C8BcvdALJs8MIrnhv4Liwa6BvP94dOIA/R SHBIDV2GYjNl8RZd+gjfEDlSRAmDTH3EHSTMKrEQ2wziDM/rzAKNDJI9QSllkAUkjOnyPSxVf4xN yHc48lFbvpOHILdxwMUkBEfAB2zNCFYiLXofFlCJuZhllAC8MklMZlkafTQEM2icCuMtqQTlhnQc 1C1ohuhCniEhaRHPCSeo1D4yxoKEcDLYrm2WbsB4HA+6o4Ouy2CekYgmLItBCRtdBMWiA9wpBaAC TSgXyGWdMN0Swbfs4dCrg6aro5UHrmVhspyaCEejnxN+J6sxLWKgFnzEUD6u7oE/5a69nHAgKdSJ KntQFh5tTKQayvWGKGWcgmc3FigQhec0eCPLlcl/Eh5K1rkBeAii8NwGz3KGFpbYaQpiEewAEUUB enuAAVRvN0BEUYB+AwhsAAp20hBRFOBwD3Doysh1MBlRFGDQACLa6UFp+RBRFOBoD9D3hh2DgiiH OQnhIQ125HOES4Dh55yxpayCOOVCdqCX3NWFblxNNw9Ywvtc42BS/SjXIMUDxwJXJyRbKtqRLCbb jnQL9uOF9JBuErprHOw/ngPdpW4vTVdu8U4wgG5UH6KRvtJ/JIEcajrfRTtWq6yxaakM6kg7VovG EEThdaQdq5XhZ6Cd0ZlZp4V3BtJp4Z2Bc1p4Z6CcFt4ZGKeFdzrhyLTqPhQhaciZqGoNRV2YyNNM 9J5G8Hb0BBOv+20KAmacJSBNrzhnzwklcdXMNbs5CSkGK2hvEI7FK16y6j6qhSVDvSSmrMBWq4mq mez0NHuMTbB66ykF939jUlXVvi+vlo71h11PqNG/e+r0XztfTnZf5//Ozl8KXnv/9xXhMF3refSE gfR/GoDh6wD4/2L2w0XD/So/GIMTuvN/HIMlXBXg6/6fjgONfjAa9kY3A6/n+r7Xm9o3bm925QwC x5na19fOJ1O9+VZZCm8PYDSW4kvGk2V7vOzE5Mvnv3758vnvhuVACQT6kYKUNKKvNIBJ7yp4qyzl TcOKp2DfdDry7Vkw7U0t97bnXoOlV7dg5K3nuO5sGlzNnJtPYE9puWHEqbxz+S1Wdz+w+Oq+Jk8j ziq2FBcRy/v1xU+/ZM+UlyyVdz/WQF0grQlMpf7Is+yRN9LECEpK9tPKggV4cSPnxIy/JeW7tWwo cFMFVT2TSyXcTSErgWgjgqbru67JPwAAAP//AwBQSwMEFAAGAAgAAAAhAMB/qelOBQAAkRMAACEA AABwcHQvc2xpZGVMYXlvdXRzL3NsaWRlTGF5b3V0OC54bWzcWFtu4zYU/S/QPRDqt2PRelgWEg9i Jy4KZDLB2LMARqIjdShRpWjHbjHAbKtdzqykl6ToV5xESTpo0R9blg+P7oP33CuevlsVDC2pqHNe njn4xHUQLROe5uXdmfNpNulEDqolKVPCeEnPnDWtnXfDH384reKapVdkzRcSAUdZx+TMyaSs4m63 TjJakPqEV7SE/+ZcFETCT3HXTQW5B+6CdXuuG3YLkpdOs160Wc/n8zyhFzxZFLSUhkRQRiTYX2d5 VVu2qg1bJWgNNHr1vklyXYG3/PbX2cpBGiaWcAM7Q/A8mbIUlaSAG2NeSmBA97nM0JhUyg6NqauZ oFShy+XPoppWN0IvvV7eCJSniqqhcLrNHw1M/ywBBhfdg+V3lonEq7kohqckhoig1ZkDiVurT1hE YrqSKDE3k+3dJPtwBJtkl0fQXfsAsGDzUMh5ZTx66E7PujPLJaMIb7wyUAJLr3jyuUYlBz+V+8a9 5HppyZTPir7KkAm/VFQNzvyp42HxtY6pNXQTCT/ow97S4ej1PTc4iInnupGHPQepyGAc9hrErseG uYrlasTTtYroLXxD4kiZZBw26q2JM6vlVK4ZpJnEbMkwGIQIu4NKYrAJSJzS+Ue4Vf9+5oBJYNOt dXyDhxzD9Q4PRJjEEAf4gKWMqEKkZefTFAqxkGNGCdA3PsnhmOXJZyQ5omku0XtSSyqQjhuULVim 2KV+hqakZXpDBFFG7TKrVJAYngzxtT7Dpcn24zmHIO5XwQ0jCc04S8GI3tt2QJ7C/rWbpH3yvaAf qISqYjiW/QBjDAiT/SAKPAxbwbhvCkq7bfahjYTNvi6t3VQ1KT/ItKd2n6HcAcBlr9mvu7si2sVa AGC9I1h/F2sBgPWPYNVu29hgAYANnsNaAGDD57AWANj+c1gLAGz0HNYCADt4DmsAx2oIViJg2BTL G2tKaaouqXqvpkzd6OKBD/tIvXFfUMZTmvAyRYwuKWtBr2vrBfSzLBft2XVBvIB9whcCul9b4321 MV9Cn8+PskOb+0fVzLdqNlOp3pUyHRBo+7ZVvaqZqQ4CEg6tICNs7sAMAAKnE6mbmpIcfTHVO16J r7r1VHfDvhdgU+fblr/X3vxwgN3wzQKHCiKu9IiRlylMO+pSmXa7uIahUGdzR9Pwnk6pnqiwUIlK 3hoq26Nb8e3p6YFGNnwD7KunolZ8e9p4oKMNH/b6OGxLOHhCay1f1IuU1LcycI/vQI8bvl4vAvNe w3eg2Zav7+u29XL7DnS94VNkrROy5++B9lu+MOi/Lh//jf4AlW2nCT1gqDH38bkqsEr0kSbw7nUH 87QWzaclCCbrcQZoei4Ev88oSevtBLXRLvVCYcabzZidyge6hM30YMFHhYmVasCwQrV1sP24tBlQ jEg80sSVehh5MfhGUB4Rf5TmQtp3ntcMteHD4AeqY32n4M+lMNH/bUEEDO9NY8AtRt//aQL6DxMQ fscEwDHG9aI4moMW3flfzsEcDiLUYcIfk2g8xiPP67jRxWXHdy+9zug8DDu9/niE/f4FdifhF6d5 r65ZDm0cnFaldfiWCVtdD7KPlJ0cfvv650/fvv61HVPBCAV+S0FqGbEHJjB+XdXw0lrpc4yFyMG/ 0WgQ9sbRqAPeTDr+xaDfOZ+EQWcSeL4/HkXnY+/yC/hTYT9OBNUnOr+kzckS3HxwGlTkieA1n8uT hBddc6zUrfg9FRXP9ckSdpvjqSWBlwgYMEI8iNzITFPaNi1/1lpwQZ0LaaFg4j2pPiz14AMHYVDW Y32rgqMvJWIA3UKU7/Yobfg3AAAA//8DAFBLAwQUAAYACAAAACEAFsdiYfACAAA2CAAAIQAAAHBw dC9zbGlkZUxheW91dHMvc2xpZGVMYXlvdXQ3LnhtbORV/07bMBD+f9LeIfL+DmmbNJSoLWr6Y5rE AFF4AOM4TURie7Yb2k1IvNb2ODzJzk4CjBYJaUKatH9a+3J3ue/7cnfD401ZOBWVKudshLoHHeRQ RniSs9UIXV0u3AFylMYswQVndIS2VKHj8ccPQxGpIjnBW77WDuRgKsIjlGktIs9TJKMlVgdcUAbP Ui5LrOEqV14i8S3kLguv1+mEXolzhpp4+ZZ4nqY5oTNO1iVluk4iaYE11K+yXKg2m3hLNiGpgjQ2 +s+S9FYA2usCsxvkWDdZgaGLxoCcLIvEYbgEQ2w9jFGJS0mpObHqsxRLcS6t72l1Lp08MbFNDPKa B42bvTJwg4P3InzVZsLRJpXleIgjoMDZjBAotTW/EIQjutEOqY3kyUqysz2+JJvv8fbaF0AFjy81 qGpEu3B6LZwLSuADWRXUCR6R1e4Ywk84uVEO44C1poBPM/CmEyn5bUZxooy5Rk5Oq/Y9hg7zZpE5 tRSJhg/xO4iKixQBnwC2a8FbxoyzPbTxytKPo4LVqeu7iPQm5snWUHYN/5ZycFJ6qbcFiAfnqug2 sQlNL2pRnpmBp+fuQA+O9vg3JsqScywxpHHgQ4GWosy9WiInyaVudYKMkAWqb2uDY0376+T7u+T3 35H8VMua/W9rLDWFSy1AK1yt1v8kQLArQPiOAsCsPV2XezXoNc3z72qQwrQ0A/DH1J+Fh/Pw0I2P wp4bdCZ9dzCYx27Q9+ezhT/rx73OHWoaXhV5QhmANh0mXzSQHXqvt50eP9z//PRw/2sIzaWhuXAE RZhEf9OQti/bIQ8T90RBamFn71rmgC82uKaD2I27wcINZkeH7mQR9t1F3w+CaTyYTP35HeAR3SAi ktq18yVp1h8Yd1ZWmRPJFU/1AeGlV+8+T/BbKgXP7frrdpodWuFihIKeH/od/6jnNx8FVGlHS1st QDDLy5RNCvkVi7MKJieOYFtDW0+tScB+bubxk4vB3u778W8AAAD//wMAUEsDBBQABgAIAAAAIQAd ZEPCjQMAAAEKAAAhAAAAcHB0L3NsaWRlTGF5b3V0cy9zbGlkZUxheW91dDYueG1s3FZRbuM2EP0v 0DsQ6rciy5ZdW4i9sBWnKJBNgsR7AFaiY2IpkiVpx26xwF6rPc6epI+UlN2NHTRosUDRH5sazgzn vZkh5/zNvhZkx4zlSk6j9KwXESZLVXH5MI3erS7jcUSso7KiQkk2jQ7MRm9m3393rnMrqit6UFtH 4EPanE6jjXM6TxJbblhN7ZnSTGJvrUxNHT7NQ1IZ+gjftUj6vd4oqSmXUWtvXmOv1mtesgtVbmsm XePEMEEd4rcbrm3nTb/GmzbMwk2w/jokd9BA67gT7EaKQ0SCqtlBmEYzoC/vRUUkrSFYeS0S1PyO 1SvDmF/J3U9G3+tbEwyud7eG8Mo7aA2jpN1o1cKnhBoWyTPzh84TzfdrU8/OaQ4uyH4aIWUH/wsj mrO9I2UjLD9Ly83NCd1yszyhnXQHIIKnQz2qBtExnH4Hp+EhfULVqFKYXqnyvSVSAaeH38Arr3ed M4/Zu9cb8gXxrV6zGfjo9C04DWS5/UJVBw/8F/wHIc2FdffuIFggBGHTHM7xA/oF9XXNZPzuHnVd u0IwirpvyXOzQvDyPXGKsIo78pZaxwwJVYAugMtzsOOQnNYlk9UtNfTumWePj+Y4GUF3EWLZUPgy kYOOyDtWouUeUFTZ35MJWosNtNncGPW4YbSyr+O4cqDgN7QJFesIhYmqSQMRgWqfkCPOPY1CNunz OfA56wCeTEEw2Ik06NK8Ymtw1dAjOjGo6jLm1UPCTui3ohcoJxU3riv4f0J+dkz+8BuSv3amYf/X LTUosi4BXXO8UPT/4wQMjxMw+oYJwOt1va1P5qDvj/1PN8Eab49/SX4vesUgnfTn8WJ+MY6z4XwZ T+bLZVxkg0G2HA/nw376IWovVSt4xSRA+yp6fhsCMnrPt/TXbdqK3OzTxz9++PTxz883IILwyv+m IcOl2L2WeLquLC5XHR6xreHAt1hMRv1ivIgXaXYZZxeTH+P55WgYXw4HWVYsxvNisPwAPDrN8tKw 8JD/XLUDBYRHQ0DNS6OsWruzUtVJM00kWj0yoxUPA0Xaa6eSHRXTaDAY9XvZeDIOtYh4EWUoji5a iPwo4MMuhXlL9c0ucIj5B21dBJHGxNOU1BcquDl5jY1wh8oWuaYwhqeV7CaFaou5iEvcnFxyxyKC kcXhyphGkmFuQ9Ooiq2aaaW+U8q1xRs8ITjXuPar9jgsn0a32V8AAAD//wMAUEsDBBQABgAIAAAA IQDV0ZLxvgAAADcBAAAsAAAAcHB0L3NsaWRlTGF5b3V0cy9fcmVscy9zbGlkZUxheW91dDEueG1s LnJlbHOEj8EKwjAQRO+C/xD2btJ6EJGmXkTw4EX0A5Zk2wbbJGSj6N+bYwXB4+wwb3aa/WsaxZMS u+A11LICQd4E63yv4XY9rrYgOKO3OAZPGt7EsG+Xi+ZCI+YS4sFFFoXiWcOQc9wpxWagCVmGSL44 XUgT5iJTryKaO/ak1lW1UWnOgPaLKU5WQzrZGsT1HUvzf3boOmfoEMxjIp9/VCgenaUzcqZUsJh6 yhqknN95LmpZ3gfVNuprbvsBAAD//wMAUEsDBBQABgAIAAAAIQBlmxQ7+QAAACYCAAAUAAAAcHB0 L21lZGlhL2ltYWdlMi53bWZ8UTtuwkAUnFkDicFAS5MUKEoqUnIF4ARItK7ooaHlCOki5RoxJ4jk SKm5BjWKtMxbGyMjwUrvt+8zs2/3fz+fQMIt1/zlFHaWcyIGokcCDfTCXVO647ZMaF7iJlgqpzy7 wb5zEKwjYRWxkwoenfcekaJntKVfW31Z3XmrAB4k/6rO8295NnMkXOHj6GwSrBbDMsPA5yVqivMH n8R7JUnlW1x0taABmM3GVZe723VmkGVf6isYRMEewgaMEcu4PslwU+bCNrmNjxr+ddcZf7NZVPiu xCt4XPAvkwx3xV31fotvvf9+V/1XbHfFFt7ovf0bcAIAAP//AwBQSwMEFAAGAAgAAAAhAAIDSIik BgAASh8AACEAAABwcHQvbm90ZXNNYXN0ZXJzL25vdGVzTWFzdGVyMS54bWzsWetu2zYU/j9g7yBo PwfXliXbkhGniJ24DZC2QZM+AC3RthDqMpLOpUWBvtb2OH2SfYeUIjtNV6f1inWNf9gURR7yfPzO hcd7T68z4VxyqdIiH7nek47r8DwukjRfjNw359NW6DpKszxhosj5yL3hyn26/+sve+UwLzRXL5jS XDqQkqshG7lLrcthu63iJc+YelKUPMe7eSEzpvEoF+1EsitIz0S72+n02xlLc7eaL7eZX8znacwP i3iV8VxbIZILpqGBWqalqqWV20grJVcQY2ZvbGkfGsZnIqHf2cJ+v+ZzJ02ugVOn47n7e2xo9OQT IZ1LJkbubOG57f29Nk3B4KpFk1V5LjmnVn75TJZn5amkh/jl5amETIh0nZxlQJgEmBfVMPOYY5gV vDF9UUtiw+u5zGhHgMfBDnGON/SNSWzIr7UT28646Y2Xr+4ZGy+P7hndrheAareLklZWo0/V6dbq POcsAUFOBYv5shDUNhgZFe08wFieFPGFcvICShMWVlegU0smAGitcunomxIwLRMJZr4duX+smAQF qyl2HHaZ305VButagX9GyO8EftcH5wmnoN/z0Ka9NLNLqfQzXmQONUau5LE2TGCXJ0rbofUQc/x2 9XKor8dFckOnMcMvDh1Gh/nLQr51HXGcq5EbeUGAc9PmIegNuniQ629mG2+0mBTgXHXGQukzfSNA MTYUl8KD0g4TCxi1MPtL+Pw1uggxD4ZXaVWNNBquS8C5gjZ5csoko2mCkT/geevNWTUTI4ByrRWa lgufZ4RfM+KQab7Bhy6J/FY+JNqtbNNskAhAjNmGCX40CLuD3n0W83/kg/xaPsxFYlzVu8PppBOG 0UErOIw6LTDVa0VHnt+K+n7fi/x+GB0G70FkY6gJjlunGZ+mi5Xkr1bWXOQdUjkq0xPBGfhaEVrv 99peB/7d88n+tOEotrB7ZgY1M89EmnDnOGOLTYL6XyYoXNfrAvZMbryYLGEu/ECVcA7beTMlkuNs UTHY2IMh7rYM9rwwqBncj8Kete/G8cOTBb0e3Am5NT+IOpFndPpav8YQ/KepELBbeJvcuSKnMsCq 9KwKwEhv6YF8YRMeEQQuKv+xNgq7ELkx1e/gLB2Wx3C6IzfWJmZg7cpzGmX+BccHx2Ij+0tKmDY8 X/BlYlFIWfONtV9bi4QUTzZDoXWE9oTrCds4wkHH61d+MAi6IJUJfg2NerDuQU2jwAujwLNc/XHC Y3PIFCAR/m79DYIFG27jliYijS8cXTg8SbVTJcCacixFAVg13oriD0zA2IH5qpc0CQ5W23bJMx4X eeIIfsnFFuLNoTxA/PkyldtLN7x6gPRpsZJ6ufXmjU08RHw6v1f6rvOXfm3G0wJ2vJnR9nZhx3M4 pI2M1pqxweNB0cDm/iFCgg9rNoyvbwA/ZD5z67JnVpnaYZP1/CdT3UFNFZtQvFxlszuE6e+CMEga IPo+zphTfxBn1nPgn5E5354Uh+HR4MifjludIJi0Avo6mI4PW0dR92Didye96bRzmxQryjRzHN62 EeDjhz9/+/jhr8b5f3UmDFo0xQj4hROF1Lo0NYKVTEfuu/E46ncn4bg19oIppfgDKNLvtaY9H0qN Q2hz9B4bL71gGEtuSifHSVXCQecnZZcsjWWhirl+EhdZ29Zv2mVxxWVZpKaEgzzf1oFMFcUP/GAQ RP7AWAn2i12aLKjeLbrq0kws5AtWOii84KKrkX3ra7SSC7Rmiy71oRKhr9FKLtBicYxqD0ZUjboH 723P7Ri/7sG91b6CYlWj7unVPUjx7Kt+3YNosRRpfgEw6Md15oV4bjvqlnUBpor22Zu7I7XJUBzO TvKxhDg493mR6wNztZ8xxbEQbhuoqJ2ucrpuVEl4GY+pAEW1lfg01rY+5XfwoXWRlqC/GXEwB8Kb Y9fGVW/vlhCcCy6paEjlBDN7PfG/UxnDsdTrro+isl1uLopz1IdG7oFMmcA1Zcmk4kYZG77Y2pjf s7zFGUljw1jdeRGrahm7WaPpbZHDhIsuJX4Zkyco8FCNBYDWdZJHtHeDNkFMpwPg/QZtU956RHvn 3CaIK7SDBm3PH3j9R3Lv3pUQxhXcvTW4w24YPsK9e7gJ4wrufgN3txuC3OvOBP7+nM3OUN6u/cwn oRM5gYk3TSTdjJz2L53vEOUoggltIxj/1tBGqFQADdYAGuCPjEeAKAQRKhVAYQMQoRM8AkQAESoV QNEaQP3eYDOA/LQmRqiYC8h6sk7X6+Yf8P2/AQAA//8DAFBLAwQUAAYACAAAACEAqYS5wTMLAABK QgAAFAAAAHBwdC90aGVtZS90aGVtZTEueG1s7Fttc5tIEv5+VfcfKL5njUAgcEXZ4kXcXlV2LxV7 az+PEJKIEegAJU5+/Xb3zCBGSEhe6273LpKr7NHQzEt3P/0247c/Pm9y7XNa1VlZTPXRD4aupUVS LrJiNdV/fYzfuLpWN6xYsLws0qn+Na31H9/9/W9v2X2zTjepBu8X9T2b6uum2d7f3dUJdLP6h3Kb FvBsWVYb1sDXanW3qNgXGHeT35mG4dxtWFboWsE2MGyULtkub7QorbNVob+Tw89ymKNoauxI8uoB B0+PvqON6K3F0whp62o1D/NK+8zyqW7QR7979/aO3QuCvOnTxfQRdIJg8WSeG48I8qZP5xr4045H BCxJYD/9uYNgZswsQdsh4s3+2BZ8PE+h74xv9das7I0PSkS8Oe7RKzzrEPGm3aOP/Fk0i5X1EBGn d3r0ZmRGrq/QE9E6z4qnHrVhePAR1C3Jssx/OkrueWFoSMbvqUD6rQ7hFMuyaAY0SkeaDftUVjEQ 4pecNVmhNV+3oK0JaK1fZSzHVbH7lHX6eVdSH3TB/Mpwm6y46tj74WCm/eZoqxt1p/9aLrMkpR0u szx/aL7m6fuaNlmXebaIoRPfIzSnLZK2a2gKMSh0q4rRO1pVNr9lzfphzbbAII7JVS2GXtXatqwB kDTx0bFxUmByw5Froxpybtas+blc8G6rC+h2GIL3ikyFnMjCAS6dzJq8brIRX9VJtqlbG9HSSHeU rbVbBhn2twadLTdB9TWGZnrkgD3FtWt1wvJ0gXznxk6KBaeW7auIqF6zRSpkhPvuy2hEQpK6QnYb dOeIjFxa+iDXOrN5OOwrZrtESN3pxiemk9J7jZSkhZKSIeYcwjEvuuDMC+3LVPds09a1hG2n+hJs EjQ3W5B6Xax0jeUrcORJU3G1PwtmYvxemp7cGGhfB3EjQ/b3NqzYgW1VNxGr11w16JFQgbzAmfj6 TRvYeq0NcE3/A6uwXFCGP20VwEdVtOlymSZNV9idHuQd/ypMablr0uphvfiizfNd9ZGB+FFVYT+L rG6mOlkE/FJNdeQ2PVKNszCMRyIlnI3l2zUT5hYhKpHMyUlV2zXQt87yYG9H106be/lWCPJX2kpX jb+zraA/SYvUWqAEEgi7K6YhXqd6WTXrEqzQdp0lcQXBDtkO0BYNrAu6aw2Cf/pbpZ/xL8ccHwNH y7PVuvmYrbQqA3/UrKs0/QBmibTvzGAj4bv4kHIg0qjOcustX/Y8/Zzmj2gDHfTturYGVSdrIswA 0R3qn/pdIGi+wiCnizfFhrS+l2Pgvx35cDDDplQ7TAGN5H+7ROKWGvnw9+l16Xu7G8EH+zBrLFEB k3VcgSdg/weX8EJXyy1Wb8emLRcHUuzvGDrbgGjLmrWGv8D/ZVWS7+Pbx/Ij2FYNckEcDNQGtPoN Dzw0NJC8cw6BE+/kyoRDcdaK6Ba5Jp31VcKovQjaeQ+YjSu7RN4vZHYbnKnTKVi8JrMFhxVe876T rAbJHkIUupYykSHBUAmiWyMo559A0KKaQKlAvYVvhIPth0qbf4EkAhITtmtKMnLPy2qDT8vlUnsm E/dVGDjwYc+NlkDnCIIE6JVBtXwl2dXNP9KSXmefwaqQ7q4WssXWspU8F7JZCT3kOgi/gSXwG1SP pMzuUek4Mey2O8WQdeJZtlygQnnNiLF5PjrFiaCP3VflrlgQV9YpW8yKBSXEU72AUpKORnyTLsC3 pOBbsEWUDcvySyiBOzykbOMOrkk1iBkFOi8XX0HgUNoCrK/L6htMCB4OouR/71gF0+f/LCAV9Ubj McqCvoztiYki6T6Zd58Uu01YghUBjWBFAqOCs5PNsOGiTMoNyPB98bBNkBDXggx6fP6NVVvhcBtQ rV/KB0ySiUCqD2xqT0sazreBg+Q1Dw6xvUiXH2BzG1a9J/WBxkdqZMUCykvU5IlADl44XT6y+cM3 sVncYINVMaj0sfdFUD1RG+sFPuUOc1Yje7DWsX+8hkwTancfdkVCw9OKcI/YqLfJBzCvVGwThogL AyLcliKQMNzTtoZtm+yf+ktehuiM2aETT+c7SCYfn0lj5ruHb20TSzXtl19Az4RSzSUAgRsfgXVP u022KT9ltPec0ui0ePPrA+TQwCh0AwKUGifZSa2tmyp7AgtSlA/UEgkEV2mo52xYnn1Lf6JxkZOQ pQM1jFZvmjBPGcVRnHv4uygxCpHcImYOpGwnANiFACjK0SqVlqxZVackPD4d5wRpGdcnau7VDJSx NZ55EUnx3azoK/PuE0K8WVE0qDcrerOi/29WVBhPsKf98BQCgYqBL3ugLA2cFLoAtRN7EklxO/ua 6rezLzzeed3ZFyjUz2yrzVejqQ5HnRABP0MLDkch7FmZ2GdiH7TgBBRCXH5sCYkTb8geeM57WhpL 9liSZix7xrLHlj1QxeavO7LHgZIOnulBzI5/dE1uFErdYsui+tQHSb/nDGxMCr7/SkfGnoM/Yofi TFmwnGLDbrE2DqLYfsGRcRx7niPHFlLDQXmTToOVY/P/9JFxHM3CQF3/4JHxbOL6dih4I9QG19+e ByurD0MLihyCuiWROtRjJrKmJd9Tgc1udQjfucFmVWjWXw42L7lpgZcDYvWmAl3H6CDiQJF69Oaf CZvQn5kH6x+ETeAF3mxyKWzQt4YSZOdh48fOpF3MDTaDF5TGr4YN3LBxYlmCu8IFpRd5m+7lKI6V Qdi4Uei0mtHBFm/2vc0sjP1YVVMi4vTjnsGmwri07x0i3uxfUDrizQZhM4kD63LYwH025wWwMQwf K0y8DnODzSBs7FfDBkUfydtjV4DNhD5CeueCNJxcVetB2KD1bRWJ6/JZbzOTe+P014eNr3iPQdiY EfobhX7gXl8c23CxRFCf9zYYwd5gAzdgRSjKiwbHSwLOAGxs33YF069yHbZzzVXclz12HRaR0F7i PAMbsKdjx1TUaBA2TuTEoQqzQdj4fmiEUvEugE3k44+yHnJJp7yN7wduoK5nEDaO6YyDsTL+AGwM A3kpqM/DBslfCBtK+qkkQMUBKglQcYBKAiA8mbhD0YDzAI/EqDbwv10SmJyEjR2O9ly8AmzoxF+q 4ABsojgyPZkmn4GNkvQKuexzFUKEktsEs4nnyDUI8e3p+0FaaPjwUdR00Nu8FDYzE1Cmjj8IGz90 IlstaQzARjFA52ETWb45kq7ssiDtu4WNexI2hmFZbdXpCrDBuL/1IgOwwaS9tZFnYIMrPAi6Br2N YQT7WzkXwAZBE6pqfVXY+FHgzlRvOQgb4ODelPH1D8AGedNy8jxs4ng2MUbCRtxgM5jbeCdhgyrZ UXNSR5G6KBYclbwVzhVym5k1CzolBnIZHUeizI3QbtfYIeogQqEfO64/DhTv0Rm/720QNgfe4Lqw 8f3oAJaDsLHiSTSWnvjqsDFmcCHuBpv0gtxmxK+uC2+i6JiSm1/B3TiuE9iREMuAu4lG0SiUun3G 3XiGZ7iquR50N67hzXyZsHXAxZt93EAG7gdqVHRV3IQO/EgLzxcxiJuJ5caeuv4BdxPHYdgGDOfd zcyLwrbgcHM3g+5mdPp/ZC0w/O3h2jVw4yj+i+y8gIWC1wP/1fEHBAmF1jFsbyIxxvVuEDewBKf1 jZfgxg3cA39wVdwEYEoCmbZfgBs7tMPLS9DKudZ53CDjW+d9w80wbk5fFID/YzZGdusfXh2n2aY1 M6XtHvI3cWi40i+d8TduOAkmMrS4ADdubMemqqcdXB7xN5Yf+/LMkI9/VdyEgJpAxf2gv3FHtm2q 6daAvwnDAP5ZRkjwPG7cEJyxJP+ecANXIdQLNnRZDXrpnzDe/Q4AAP//AwBQSwMEFAAGAAgAAAAh ALTPWBm7AAAAJAEAACwAAABwcHQvbm90ZXNNYXN0ZXJzL19yZWxzL25vdGVzTWFzdGVyMS54bWwu cmVsc4SPwQrCMBBE74L/EPZu0vYgIk16EaFXqR8Q0m0abJOQRLF/b6AXC4KXhZll38zWzXueyAtD NM5yKGkBBK1yvbGaw727Hk5AYpK2l5OzyGHBCI3Y7+obTjLlozgaH0mm2MhhTMmfGYtqxFlG6jza vBlcmGXKMmjmpXpIjawqiiML3wwQGyZpew6h7Usg3eJz8n+2Gwaj8OLUc0abfkSwlHthBsqgMXGg dHXWWdHcFZio2eY38QEAAP//AwBQSwMEFAAGAAgAAAAhALl/7nOWBgAAsBsAABQAAABwcHQvdGhl bWUvdGhlbWUyLnhtbOxZT2/bNhS/D9h3IHRvYyd2Ggd1itixm61NG8Ruhx5piZZYU6JA0kl9G9rj gAHDumGXAbvtMGwr0AK7dJ8mW4etA/oV9khKshjLSNIG27DFh0Qif3z/3+Mjdf3Go5ihQyIk5Unb q1+teYgkPg9oEra9e8P+lQ0PSYWTADOekLY3I9K7sfX+e9fxpopITBCsT+QmbnuRUunmyor0YRjL qzwlCcyNuYixglcRrgQCHwHdmK2s1mrrKzGmiYcSHAPZu+Mx9QkaapLeVk68x+A1UVIP+EwMNGni rDDYYFLXCDmTXSbQIWZtD/gE/GhIHikPMSwVTLS9mvl5K1vXV/BmtoipJWtL6/rml63LFgSTVcNT hKOCab3faF3bKegbAFOLuF6v1+3VC3oGgH0fNLWylGk2+hv1Tk6zBLKPi7S7tWat4eJL9NcWZG51 Op1mK5PFEjUg+9hYwG/U1hvbqw7egCy+uYBvdLa73XUHb0AWv76A719rrTdcvAFFjCaTBbR2aL+f US8gY852K+EbAN+oZfA5CqKhiC7NYswTtSzWYvyQiz4ANJBhRROkZikZYx+iuIsZHQmqGeBNgksz dsiXC0OaF5K+oKlqex+mGDJiTu/Ny+/fvHyO3rx8dvz4xfHjn46fPDl+/KOl5SzcxUlYXvj628/+ /Ppj9Mfzb14//aIaL8v4X3/45JefP68GQgbNJXr15bPfXjx79dWnv3/3tAK+LfCoDB/SmEh0hxyh Ax6DbsYwruRkJM63YhhhWl6xnYQSJ1hzqaDfU5GDvjPDDFfgOsS14H0BFaQKeHP60BF4EImpylzu aHYrih3gHuesw0WlFW5pXiUzD6dJWM1cTMu4A4wPq3h3ceL4tzdNoXTSKpLdiDhi7jOcKByShCik 5/iEkAp7PaDUsese9QWXfKzQA4o6mFaaZEhHTjTNF+3SGPwyqxIQ/O3YZu8+6nBWpfUOOXSRkBWY VQg/JMwx4008VTiuIjnEMSsb/DZWUZWQg5nwy7ieVODpkDCOegGRsmrNXQH6lpx+C6pHtdv32Cx2 kULRSRXN25jzMnKHT7oRjtMq7IAmURn7gZxAiGK0z1UVfI+7GaLfwQ84Weru+5Q47j69GtyjoSPS PED0zFRU+PIm4U78DmZsjIkpNVDXnXId0+Sydp+5dm8LWpk8uycq9jLcyTrd5SKg//4yvYOnyT6B zFjcqy6r9GWV9v7zVXpZPl98bZ6XY6jUuneyTbdpweOlHfiYMjZQM0ZuS9OES9iEgj4M6nXm9EmK E1kawaPOZGDg4EKBzRokuPqIqmgQ4RQa+LqniYQyIx1KlHIJB0czXElb4+EQoOyxs6kPJLZySKz2 eGCH1/Rwfu4oyBipQnO4zRmtaQJnZbZ2LSMKur0Ns7oW6szc6kY0UxQdboXK2sTmgA4mL1SDwcKa 0N0g6InAyutw/tes4eCDGQm03a2PcrcYL1yki2SEA5L5SOu96KO6cVIeKwuKaD1sMOhD5ClWK3Fr abLvwO0sTiqzayxhl3vvXbyUR/DcS0DtZDqypJycLEFHba/VXG16yMdp2xvDmRke4xS8LnVDiVkI F0++EjbsT01mk+Vzb7ZyxdwkqMM1iLX7gsJOHUiFVDtYRjY0zFQWAizRnKz8q00w60UpUFGNzibF 2gYEwz8mBdjRdS0Zj4mvys4ujWjb2deslPKpImIQBUdoxKbiAIP7daiCPgGVcPVhKoJ+gXs6bW0z 5RbnLOnKt2MGZ8cxSyOclVudonkmW7gpSIUM5q0kHuhWKbtR7vyqmJS/IFXKYfw/U0XvJ3ANsRZo D/hwTSww0pnS9rhQEYcqlEbU7wtoHEztgGiBu16YhqCCy2rzX5BD/d/mnKVh0hpOk+qAhkhQ2I9U JAjZh7Jkou8UYvVs77IkWUbIRFRJXJlasUfkkLChroHrem/3UAShbqpJVgYM7mT8ue9ZBo1C3eSU 882pZMXea3Pg7+58bDKDUm4dNg1Nbv9CxKI9mO+qdr1Znu+9ZUX0xLzNauRZAcxKW0ErS/u3FOGc W62tWAsarzZz4cCLixrDYNEQpXCZhPQf2P+o8Jn98qE31CE/gNqK4EOGJgZhA1F9xTYeSBdIOziC xskO2mDSpKxps9ZJWy3frC+40y34njC2luws/j6nsYvmzGXn5OJFGjuzsGNrO7bU1ODZkykKQ+P8 IGMcYz6Zlb9q8dFDcPQOfD+YMiVNMME3K4Ghhx6YPIDktxzN0q2/AAAA//8DAFBLAwQKAAAAAAAA ACEARNin4oCvAACArwAAFwAAAGRvY1Byb3BzL3RodW1ibmFpbC5qcGVn/9j/4AAQSkZJRgABAQEA YABgAAD/2wBDAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB AQEBAQEBAQEBAQEBAQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB AQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/wAARCADAAQADASIAAhEBAxEB/8QAHwAAAQUB AQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQAAAF9AQIDAAQRBRIhMUEG E1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVW V1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLD xMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEAAwEBAQEBAQEBAQAAAAAA AAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSExBhJBUQdhcRMiMoEIFEKR obHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hp anN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3uLm6wsPExcbHyMnK0tPU 1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD+/iiiigAooooAKKKKACiiigAo oooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiivib/AIKXeM/Fvw5/4Jx/8FAPiF4B8Sa1 4N8deA/2Jv2q/Gfgrxf4b1G60fxF4V8W+F/gT481vw54k0DV7GSG90vWtD1ixs9T0rUbOaK6sb61 gubeRJYkYAH2zRX8MPxp+MGn/BbxZ4v0DWfi3+3jLo/g2xttT1bxTqf/AAVq/wCChfh7TbXTX8PW XiK+1DUDdftA3VrpljplrdSm7u7nUDbx29rJdzSQRlkj880z9p3T9b03T9Z0b4jft46vo+r2Npqe k6tpn/BXj/goXf6bqem39vHd2OoaffWvx1ltb2xvbWWK5tLu2llt7m3ljmhkeN1Y+vmuG4WyTMsy yfNPEThXC5jlGYYzKswof2Z4g1lh8wy/EVMLi8P7fD8D1cPVdGvSqQ9pQq1aU1Hnp1JwcZP+M8T9 OnwVwkq6xGC48prDYurgK9T/AFcws6EMZRclVw31iGcSoSqx5ZS5YVJXgueN4NSP74aK/gs/4aKb /odv2/8A/wAW2/8ABRP/AOfjWHpH7WPh3xB5X9g/Fb9uPW/tGh6J4ng/sj/gsH/wUE1LzvDXib+0 P+Eb8QxfYvjzN5mh+IP7J1T+xNWTdYat/ZuofYLi4+x3Hl8CxfBDTa8S+FWo25msn8R7K7srv/UP S70V92Yw+nj4H1KVWtDC8eTo4f2ft6sOGsPKlR9rJwpe1qLN3Gn7SacafO488k4xu9D+++iv4LP+ Gim/6Hb9v/8A8W2/8FE//n41/SR/wRw1nxbN4Q/be8F+JPiP8WviTo/wt/bag8GeAb34zfF74n/H Dxb4d8Jat+xP+xb8TLzw3b+PvjB4t8b+OrvRR46+IXjTxFZ6dqPiO8tdNuvEN/BpsdpZGG1i7Fg8 qxeVYzOMj4pyTiLDZfmGW5bjqeW4XibCV8LXzfDZtisDOcc/4eyWnVpVaeS49SlhqtedOcKaqU4x qxkfqXhH9JPw78as7zLIeDKPESxmVZW83xlTN8sw2Bw0cMsXhsHGFOdPMMVVqV6lXFRlGKo+zVOn Vc6sJezhU/YuiiivLP6ACiiigD5A+MX7dH7P/wADvindfBTxdB+0B4o+Jun/AA/8H/FLWPDXwL/Y 7/a//ab/AOEd8CfEDxH8QfCfgjXfFOs/s3/Av4reH/C3/CU+IPhT8RdP0TTPEWq6ZrF//wAIjq91 Bp7WUUdzJ0HgT9tb9kf4mQfHG+8C/tG/B/xDpH7Nfh/wR4z+OXiG28caJb+Ffh18PfiX8GtA/aD+ H3xU1nxXfXVr4bn+D/jT4N+I7Px14a+L2l6pqHwz1jTtN8WWlj4rm1fwN410/QPgD9r3/gn98W/2 j/2lf2sPi74G8Z/GD4R+Kbr9iD9j/wADfsvePfh9+13+0P8As3fD3xd8ffg58b/26/ib4q+G3x80 H9mL4n+FfG3if4P6pbfEP4L+FfiHrmqeFbnxponwz+KPxCP7NXjbwT8Vl1bxR4d+X7H/AIJq/F7x H+0B4/8AG/g/4Of8Mzfs/wD7Sv7QHwJ8B/GH4G2kXwTstHk/Ye+GH7IH/BL3x3ongT4weCPhP8VN W+H/AMQfh/4M+IH7EH7TP/BMOH9nvTrjxr4S0HwJ/wAFAfj18UfBzeIP2fz4y0D47gH6v6l/wUb/ AGPdL8K/CXx0/wATfEGpeCfjL8H/AAH+0LoPjHw38Gfjn4t8K+AvgF8T9Ok1jwF8cP2jfEPhf4a6 xpH7Jfwf8TaRY+JNUsPiX+1Ld/B3wWuneAPirfXWtW9t8JPibL4T9/1n4/fBvw98ZfCf7PmtfELw /p3xk8ceH7nxL4Y8CzzTjUdQ06ODxLfadbTXaQNpGl+IPFmkeAvin4h+HvhPVtQsfFXxL8K/BP4/ eK/h9o3iXw38AvjNqngb8gf+CfnwW/bC/wCCeP7Onw/+GSfsqeIPjv42+Nnwf/Y71rXl8N/F34Ge B/Cv7NXx9+EP7AX7JX7F3j34aftG654o8fzavcfB/TdX/Zr8N+PbD44fst+F/wBqbxpq2neJfiro Nr+z0Ln4X/DLU/2jj4wfsg/t5+N/jL8Uf28fDOpfB/Tvit8NvjBp/jv9n79mXWfhq+ufGXxT8M/2 NoP2j/hL8IPgb4T/AGqLT9qXwn+zd4H8P/t0/C746/tN+Jbnxv8AGX9kn4k/EL9mmD9v3xLoWva/ rnin9m74La38NgD9H/CP7dH7P/jj9o7xF+yf4fg/aA/4Xb4S8+fxLpWu/sd/tf8AhLwJomj/AGr4 i6fo3i7UPjX4s+BeifBKD4f+ONT+EnxH0n4W/EVviH/wgnxb1jwlqekfDHxF4t1P7Naz+/8AxY+K XgT4HfCz4l/Gv4pa7/wi/wAMvg/8P/GXxS+IviX+zNZ1v/hHfAnw/wDDmpeLPF2u/wBjeHdP1fxB q/8AZHh/SNQ1D+zNC0rU9Yv/ALP9l0zT729lgtpPAPBXwt8d6R+31+0t8a9Q0L7P8MviB+yB+w98 LfCPiX+09Hl/tfx38H/jR/wUJ8WfEXQv7Gg1CTxBYf8ACO+H/jj8LdQ/tPU9KstH1f8A4Sj7LoWo ane6J4ittIP+ChPwt8d/HH9gX9uH4KfC3Qv+Eo+Jvxg/ZA/aW+Fvw68Nf2no+if8JF47+IHwX8a+ E/COhf2z4i1DSPD+kf2v4g1fT9P/ALT13VdM0ew+0fatT1Cysop7mMA9A+Bf7Tvwi/aK/wCEptvh 1d/EDTPEHgr+xJ/FPgP4xfBP42fs5fFPRtH8Uf2vH4U8XXXwl/aH+Hvwu+JrfD/xfe+G/F2jeD/i LB4Tl8CeLPEfgX4g+GvDviLUvEHw/wDGmm6F3/xY+KXgT4HfCz4l/Gv4pa7/AMIv8Mvg/wDD/wAZ fFL4i+Jf7M1nW/8AhHfAnw/8Oal4s8Xa7/Y3h3T9X8Qav/ZHh/SNQ1D+zNC0rU9Yv/s/2XTNPvb2 WC2k/KH42f8ABL+Dx/8AFb9lTxR8SfF/xg/bMkl/af0DUv2pPiH8cdf+DfgfUbj9mD4WfsX/APBR TwZ8LfhJr/gf9nT4f/s0fDbxz8Hz8dv2sNW0Hx34CHwy8W+IPjL4V+PHjfwF8eJPiJ+z5ZS+EvCX wB+2X/wTL+N/x++Hv7Ufw50z9jLw/wCKP2g/FPiD/gpZ8RPF37ZHiXUP2apNO/bE+Evxm+Gf7Zdz +wN+yZbeP9V+Isv7SPiDxB+zn8Ufix+wdf8AhPwp+0h8Nfhp+zx8DvFX7EOjeJ/hj8T5I/gb+zfr fi8A/qdor8Abv9jX4i3vx20nxH4Q/Yi/4Vz4t1T9oD9gr4r/ALMn7S/nfssaP/w7z/Yo+Bvg79j6 w+P3/BPL+3vB3xa1b42/C7/hL9M+C37XPgD/AIUx+yF4K+K/7InjP/hrL7HrfxSh8JfFT486t4N8 /wDh/wDsM/F3Sf2Z4/hja/sJf8IT8evCfw//AGY9C/bl+O//AAtf4J6F/wAPaNY+E/7Qn7OHj/8A aq0//hFvAnxH1uy/av8A+Gwfhl8Lf2mfD/8AwtL/AIKbN+zt47g/4aK/4Vx4w0zRvAv7Vn7YOqfD MA/f7Uvil4E0j4p+DfgpqGu/Z/ib8QPh/wDEv4peEfDX9mazL/a/gT4P+I/hP4T+Iuu/2zBp8nh+ w/4R3xB8cfhbp/8AZmp6rZaxq/8AwlH2rQtP1Oy0TxFc6RwH7S/7Tvwi/ZE+FmrfGv46XfxA0j4Z eHft8/inxL4A+Cfxs+OP/CH6PpHhzXvFmt+LvGujfAv4e/EjxB4M+H/h/wAP+GtX1DxH8RfFOlaR 4E8O+XZ2ut+IrC91fSLa+/MD9iz9kj4vfDP9snQPjTZfs6f8Mv8A7LEvw/8A25NM+En7OP8Aa3wT 0z/hlXR/i1Y/8EgNI8P/AAt/4Vr8CvHvjv4P+Dv+Fw/GD9k79sD9pP8As/4D+J/HHgRP+Fgf8Jh8 Std8L/Gf4m+JfCEH3/8A8FCfhb47+OP7Av7cPwU+Fuhf8JR8TfjB+yB+0t8Lfh14a/tPR9E/4SLx 38QPgv418J+EdC/tnxFqGkeH9I/tfxBq+n6f/aeu6rpmj2H2j7VqeoWVlFPcxgHv/wALfiX4d+MH gTQviL4T034gaR4f8Rf2n/Z+n/FL4TfFP4HeO7f+yNY1DQrr+3fhb8a/Bvw/+Jvhfzb3TLmfTP8A hJfCOkf23o8mn+ItG+3+H9X0rU70+LHxS8CfA74WfEv41/FLXf8AhF/hl8H/AIf+Mvil8RfEv9ma zrf/AAjvgT4f+HNS8WeLtd/sbw7p+r+INX/sjw/pGoah/ZmhaVqesX/2f7Lpmn3t7LBbSfiD/wAF N/2BvjR+05+1PpPxF0zw/wDtAePPCUnwA+HXw3/Z71D4F+If2BfDn/DLP7Qmh/EX42a78Qvjt4p+ KX7afwg+L/xt/ZQ/4SvTPHX7PM+iftC/8E2fCPjf9pix/wCFEav4i8Q+A9e8W/CH9mbTNY8A/bL/ AOCafxF+OfiP/gotZeG/2Gf+E18W/H74AftdW+j/ABW+KHjb9ljV/Dnir4i6n8LPFEX7KFh8GP2g NN1jwd+2P8SvtXxHv/hx4j8Ufspf8FE/AHiL9lj9mD4p+A/hn41/Y3/aI+EfhL9gD9mDRf2gQD+j 34pfEvw78H/Amu/EXxZpvxA1fw/4d/sz+0NP+Fvwm+Kfxx8d3H9r6xp+hWv9hfC34KeDfiB8TfFH lXup20+p/wDCNeEdX/sTR49Q8Raz9g8P6Rqup2XAfs0ftO/CL9rv4WaT8a/gXd/EDV/hl4i+wT+F vEvj/wCCfxs+B3/CYaPq/hzQfFmieLvBWjfHT4e/DfxB4z+H/iDw/wCJdI1Dw58RfC2lav4E8ReZ eWuieIr+90jV7ax7/wCE+maPonws+GmjeHfhb/wo7w/pHw/8G6ZoXwU/s/wJpH/Cn9HsPDmm2umf C3+yvhbrvij4ZaZ/wr+yig8J/wBn/DrxL4i8CWX9kfZvCOu6v4fj0/ULj8QdO/Y1+Ivh/wDZY/4J N+Df2jP2Iv8Ahtv4f/syfsAaV8Avj3+xV537LHxH/wCEf/anf4dfsiaV4D+NX/CK/tNfFr4c/sy+ Kv8AhSGi/B79pT4T/wDCx9B+Jer/ABF8P/8AC+P7N+GGjeJfh/8AEH4oa/4fAP3+rz/4l/FLwJ8H /Dmm+LPiLrv/AAjvh/V/iB8J/hbp+of2ZrOr/aPHfxx+Kfg34KfC3Qvsuhafqd7F/wAJR8TfiB4R 8Nf2nPbR6Pon9r/2z4i1DSPD9hqeq2X8wX7J37H/AO0cPjR8UPCnjL4a/wDC3f2p/gj+1/8A8Etd C8Y/8FDv+F8XXi//AIVPrH7OP7Av/BJfxj+3rp/2T4rXvhn4weD/APhtf4P6B4x+EP8AwtL4B+DP Hfjv9sX/AIT7/hVf7c2mfCT4MfDDwL4q1P0DwJ/wT3/aY0/S/wBmzTNA/ZX/AOFS/ED4O/8ADEej /t3/ABb/AOEp/Z70v/h5R+0J8Jf+Cjn/AATU+OvjD9tj/hIPh98Tdf8AiB8c/wDhXvw//Zq/bR+K X/CxP2zdC+Ev7TF5/wANJ/2f4M+HOu/ED4tfGHw14aAP6faK/lC8Sfsn/EX4A/s/6L4w+KPwi+H/ AOyt4f8Agj8APg34A/4KcfGL4pfFv9lj4X+BP+CvvxT0n9r/APYI8YfEzxrrvxBt/i+9l8dP+Ghv hl8Ff21vg7pniP8A4KZXX7OfiLx9rH7fun/D74hWeh+H/jx+0vdeAOf+AHhrUY/A/wAWf2of2MLn w/8As2+MfjB/wUfv/wBm/wDYsb4deLPCv7X/AIV1H9mr9s39iX9gj4E+PNP+Cd1HrPiz4E+OPD/7 C3xJ+BXhb9sL4o/C79n26+JvwQ+AOnf8EwPjp+wt8KPjBoH7J/hL4jfE+xAP63a+AP8AgrF/yiy/ 4KWf9mAftkf+s6/Eavr/AOE/wt8CfA74WfDT4KfC3Qv+EX+GXwf+H/g34W/Drw1/aes63/wjvgT4 f+HNN8J+EdC/tnxFqGr+INX/ALI8P6Rp+n/2nruq6nrF/wDZ/tWp6he3ss9zJ+Xv/Bd/43y/CD/g lv8Atg+HdC0OPxX4/wDjp+zx+0N8IfB3hh7hrUT6Vd/s+/FPxp8YfFU1wgY29v8ADb4C+DPil8Q4 jKn2bUtY8NaP4aaSO58QWhYA/kR/4Ka+KvC+g/FDVND8SaR4q1i68f8AxG+FfhbwVF4N1PwJo+u2 PxG0rwfpXxE8C6tY3/xL8S+F/Bf27S/EHgS0u9F0zXLrVbHxF4hj0fw3deGvElrrE+j3f436c/7I mpfGPVvhr4W1T9ozxb8YL34qfE/xJ4++HXhHXrL4fXfxM+J3gDVNCsZr3xf4r0+/+Geh3X9m654P 8S/tD/C630nx74e8P+D9aufHK6ZB4U1DXPDXwvuv6+vit+xB8JPj74g1XxT48sdW119UcpPplyvh C+0W3Z/CM3ge+FrY6/4Z1WSP+1PCmoanomqFp5RfaZres6ZKTp2o3Nm3lWp/8EpP2XtbfUJNZ8CJ q8mr2N3pmrSanonwtv31PTb/AMWSePb7T9Qa78CSte2N746ll8aXdpcmW3ufFksniOaN9Ydrw/Ie KOeeF2QeJ3iNl/EP0hPo7cJ50+MuJ8XjMg4j8f8Aw24Z4gyurmWa4jHYWhneQ5tnuGzPLsVTwlfD VamBr08Fi6c7NV6d4SX+SHh94LeOX9j4vNuHPBXx6zbKeI62fZtlnEXA+S8TSyPNK+aYutDLs0qT wuS4iGa5XgcPRy+qsLkWacOZrPMcD7fC8VYCrDD1MN/OxdaZ8M/hZ8dfH3xRudP+P3xT+IvhTxV4 e8OW/hXV7T4anQtBf9qHW9KsvC/j/wCHOoeJ4/AEeqWN5rFhD+z9D4ql8a6z4s8O+HvC4+HeswR/ Drwfot7pXzLq/wCzh+xz8LfGkvwouviZ+0Z8Kn+JWh63pM9kmo+GH0rWNK+HOlaf4b8SfEDUre98 DeIvGHgTQ/EtvqXxRiuPiZreneDvBd/4L0z46ppWsaT8DPEVvB4r/rr/AOHb3wV+wf2V9m8T/wBl /wBuf8JP/ZvneBPsH/CS/wDCS/8ACZ/8JD9j/wCEQ+z/ANuf8Jh/xVf9reX9v/4SX/ie/aP7U/0q uHf/AIJIfsmSa1qniST4aac/iLXP7e/tvXn8M/CVta1j/hKrS/sPFH9qao3gA32of8JJY6rqdlr3 2ueb+2LTUb+31H7RDeXCSfAYbjXwbpOXN9Kj6LEE6MaL9j9Jbwj/AHnsYQeHlKM+I3SgqWJdevFR pTcY1ZU+ac37c+i4a8GfpW5RLE/WPBT6SeCp1Mkw2TVY5HwZxDFZoslwNGrw1WxmFx/DNXJ8DHKO Ka+dcQYajh8pxk8Ph83xOXSxGMxz/t0/Cz9l/wAT/s5yeZbfBzxDrkmufFfQ3+L1x4U1vVtcvP7J 8NWn/CP6VZWOkaFBcXPw78LaH8OrPxL4c+C+n23gdYrCH/hXcvw6n1PX9c+EfiSPw/8A3S/8EdPu /wDBR3/s/wD0b/13Z/wT6r8YNO/4JyfBHwtEk2jQeJ9BjtdD0LwxE2kSeBtP8jw14ba+Xw14eiFh 4OiaPQ/D7avqY0TSYwLDSf7T1A2Nvbi8ufM/Z/8A4I6fd/4KO/8AZ/8Ao3/ruz/gn1X7dwHRyPG+ GvFnE/C3Hnh94i8PZlx7wlksM+8O+P8AhzxEyvDZzkXDvF2NzHKMdm3DOKxmBweYYTL+IckxH9n1 qyxUMHjcLiJU4UMRQcv0T6Mnh/xzwH48cbrjvhDj7gzMc/8ADulmWCy7xJhjocR4nLqHEWX4DD4q EcwyfJa7yjDww8cny6UaFeglldelRrwjReEwv7L0UUUH+hIV8wftd+JvjL4T+FPhPVPgTbeILrxt dftP/sReGtci8NeE4PGmor8GvGn7aHwC8HftF3Nzo9xo2ux2fh+z/Z8134n3fizxYtjBP4C8Kwaz 46tdZ8OXPhyHxDpf0/RQB/OD4P1D/g4S+GHg74g6boemf8NAfE3RPh/8HtPPib9rzQv2I734WeMv jZ4F+BP7d/iz9oLU/wBmDRv2QPil+yN460z4AfHT49eDf2FPhL8Fdd/ask0f4u/Dvw58YPEvjzx7 8Lbey8JeObbQfYP2bvHf/Bd74z/CX9mvWP2r/gb8H/2VPjHp3/BR/Sbb9oPwh8FPG/wgj8K63/wT q0D9njxJ4j1DWdQ1vxXr/wC29JJ4g8U/tByaN4OuvDPw4l8LfFDxLp1jpXh7TfFnwB8N654h+P8A 4Y/d6igD8QfDXx0/4LmzftCfta6V4i/Y7+AH/DOXw3+H/wAefGf7LGs+d4K8P+Mfj/47+HX7TEFt 8D/gR/wktj+3R8QptE/4aR/ZF06e6/4Xz8Rfgp8F9H+Cfx28Z/2h4u+EHiXwb8LE8J/Gfx/xB8ff +DkrQPje3g23/Yi/Yg8afCnS/wBmD4nazrXxO8DeLA3hXWP2uPDv7NXxH134WeE/htqnxA/a7+HX xR1/4P8AxM/aR0f4U6Lrlz8RP2dvhFrfw607x742+F8niXxZ4W+Gek/tg/Ez+h6igD+eHXdZ/wCC 9F9on/BPrV9M8J+IF8U6n8YP2w9Z/bP0DTbn9hL4ZeFdK8F237XHg/xL+xn4T+LWha54l/ad1zw3 8H/F37Llh4u+E3jy5/ZH+MPxj+PvwN07xnH8Z9T8S/tWfFb4R2Hwg+PPkHhb4hf8HMvxJ8MfG/XP iB8E/h/8CPFtr8P9D0/4LeE/h1afsjWGj3/juT/gn3/wUR1nxPqc9t4w/ad/ayuJv7L/AOCg+sfs KeBvDuu+JPiToOj+MfAng7wj421X4W/DXwl4j/aT8NWv9PtFAH8oWm/tTf8AB3Tc/Czxl4s1D/gn F+wBpnxN0T4gfDTw74R+En9seHr3/hNvAnijw58WNS+IvxF/4TyD/gpmvh/w3/wq7xB4Q+Fvhr/h EdTtpdY8bf8AC4P7Z0Ke3svh/wCIo7n3/wDZt/aR/wCDgj/hafwU+J/7cX7Jfw/+HX7PHg34f/HG 8/bE+FvwO+Gnwy8V+I/9O8R+B9M+DniP9m3UPh5+33+1b8bfj78QPA+mQap8SPHHgqP4Q/Bf/i1k Pxr+H/w18AftUftD6r+zfoVf0fUUAfMHxg8CftQeJ/jL8LfEfwc+OPh/4W/Cnwn8H/2krbxt4O1z wRoHj3TviH8ffFcHwp0f9mPWfHPh670DSfG2s/B/4V2yfGzxf428NfCv4/8A7PXjTxV4qb4baJN4 s1TwtceIotL+APgL8bf+C3niX9p/4DaH+0j+xr+zB8J/2XPG/h/UvFPxf174V/Em0+MPir4TweIP D/7THijw14A8V+Pdf+NXwp1ew+MHww1fSf2T/hD4z0v4U/svftGfBr4saj4m+L3xg8L/AB3+F+hx aF8MvDX7PUUAfzQ/Gv48f8HJXwc8F/ti/EH4ffs7/swfFrw38KPjB+2V4l/Z18C+JfhWPH3xl+Ln 7PHhL4+/Bi+/Zxtra7+CX7avw+j1DxB4r/Z8+LPxyvvCfhOx+Bv/AAtpYP2OdG8FeNdG8YfGT9of wxqlyeAP2qv+DkrxD+0r8CNIP7D/AOzB4q/Yv8XfGDwtZfFb496z8PB+zh8QtP8A2eNU+N+qaRcf FDwn8EviJ/wUg8e/Gnwn4g1T9mlfCvxZufAPxd+D3hj4tfDT4meIvEvwY8VfBvW9R+HkeueOf6Xq KAP5gvi7+0L/AMHV/g7wd8O9a+FX7FH7AHxl8W+JPsX/AAn/AIK/sm3+Hn/CtfP+BP7Onj68/wCK j8R/8FObrTPGP2D42/En9oD9n/8A4ksUH2r/AIZp/wCFrRY8JfGXwVZ2G+nin/g5U8WaV8Zr7xZ4 A+D/AMPPEifB/wCG9z8G9L+Cml/s4aN4Vb4meJ/+CaP7fHjrx9o2oWPxh+O/7QuvXHiD4W/8FHfF f7EXwNuvEus+NdL+Hvj3TvhXpXxB8NeE9J+Dfir453mqf0vUUAfyhfEv4hf8HRHgH4p6b4T/AGe/ gn/wuD9ljxl8QPhP8Qofi1+1Haf8E89a/bs+DfgTRPEfg3TfjB8E/HPgP4C/tO/sp/si+Ov+Enm8 AeO/E3hm08B3NxrGpfB342+HtGb9p34VfGeyu5Pgh9f/ALO/xx/4LzfFb9nH9srw5+1B+zj8AP2c f2uvC/7IHxB8f/st2fwN02bxDo/in47fE+1+MPgr9n3wVdeP/iZ8V/iX+zlpHxA+EHjP4B33j/4m +HH8a/F3wd4p8CftTfs2XnjS8+B8vgTx14c+K37/AFFAH8sX7Yf/AAUX/wCDg/4U/G/x3r/wp/4J keH/AAX+xfc+H/FEfwb1rxz8EtX/AGyv2n7/AOJnhz9mrxP8QPDXgP4k/Cz/AIJ//tz/ABMk8O+H /i7+0H4LuPhBofxaj0K1+Hvww8P+PPBPiX4iakdRgudJ1b9H/g58Qv8Agr18SP2Bf26tV+OnwT+H /wADv259J/4ac8O/sJ6N4AtPhRpH/CZ6PYfBfS7n9mH4i+NfDWqftO/td/B/wf8AEDxF8YL7V7Xx H4R8U/GvxF4E8P8A9kWen63Pq/heOTxZ4l/X6igD+UL4l/tG/wDByH+zN8U9Nm8KfAL/AIXb+wx4 1+IHwn1DWfjZ+1H8G/gz+0b+3Z+zH4E8ZeI/Bvwi+JmmeOf2av8Aglf8a/g34f8Ajf8A8ID4g03x T8fvDOhfs8fD34q6xdfB3x14eg8afFLTPFGi+NfCPwr9A+FH7Qv/AAc/eMbHTdX+NP7FHwA+FHi3 wr/w0b4hj+H3gDSfgDqPws+JX9h/sbfHG5/Zv8M+NfjFrH/BTn4lfEew/wCEx/bHuvg5oniPwN4H +BfgH7L4c06z8U6r+1H4V8JP438H3/8AT7RQB/MF+zn+0D/wch+MfjZ8CdS/bK/Ze+H/AOz94SHx AtvCOs/DP4EeEPgz41+EXxK0fxV8Xf2Z7PxL4i+L/wAUrb9qn9pn4peCv+FYfspD9uT4teDJ9Nj/ AGYPAlr8bPhh8BvAeq/EX9pnxb8c/Cf7Ml/7/wDt8/8AGQ37NP8AwWO/aOuP9L+HH7PH/BPr9u79 kH4ACT95aah41sPgr431L9rz4nad/wAsnWf4geHPBf7PVhJNGmp6Jq3wD+J4s520XxzILn9V/wBs f4w+KPg/8EtSb4ZrZ3Hxx+KniDw78Dv2fNPv4VubGb40fFO9Ph3wlrmr2bKxu/Cfw5gk1X4sfEGK MGaP4deAvFt1Ask1vHG/5of8FS9Q8L/sff8ABIP9oH9kH4QaBefEHxprP7AX7U3hDQtFvtVaDV1+ GHgn4BeKZ/2gf2jPiVrxg1C53aVp2r3OtapruoQzT/EP46+P/A/g271G01L4gya7YAHyT8WPhV/w u34N+L/hn/b3/CPf8JDdaNP9putL/wCEh8N6t/wj2v6B4n/4Q74i+Ef7R0X/AIT74Q+Pv7F/4Qf4 z/Db+3fD3/CyfhR4h8ZeBP8AhI/D3/CQ/wBtWP45+APhlBonxX1P4IeAP+Ckn7Xvgq60b9o6PSPi Z8F/hh+y18arS08OXGj+G/hBrfw8+FH7Olp8U/B/xb+HH7Pv7IXwK+I92vi7XNb8A+EfE3wWP7NX 7RfwJ+CH7RXxE8SeBtc+Dnj/AMefuvpWq29jbvFKkzM0zSAxqhXaUjUAlpEOcoe2MY59PHNQ+Bnw O1DxxcfEweFvEWk/EC8+I9n8U7/xh4X8dePvB+v6l4mtvB3ww8BXWl6rqPhTxjo0+qfDjxF4X+Cv wmsvG3wd1Brn4RePr34e+Fdd8beB/EGv6Tbamv8AlP8ASh+jB9MDN/pW/SezzhrwM8VOJvDTjbjP N+IODsx4a4W8NOIsnzPOMVl+RYLD5rjMJx5lebe3wMKGX8+DxOCqYDMcmzfA4DNsrdPHUI16f2v0 fvpAfR9yPwF8G8lz7xR4LyXizh7hrBZZnuAzXNOJMBjsFQp4vH16uDhUySrh1TxDlXSrU6qr4fF4 WtWwuJUqM5Ql+dXwm+Jvgw/Fe/8A22/HX/BRXxf8Vf2eZfCH7SfxL8Bfs/6H8Jvj58Nf+EE8N2vh vwz8VLz4pfFz4f2PjfV9c1rwh8J/2Xn+HPhbwWvjX4F+BvhR4n/4WX8Gfjh4P8PS/tDftMaV49+O Pwn8KP2J/wDhW+m+NdK+A/8AwXb/ALP8Ka7+zj8HtBt/HXiDSv8AhMNN8J+AfA/hP9o/w9Z6j8G/ jRp/7SfhLwNbeEPCtr8Mf237zwz8KdLvvFWi/s+eE7HXvHuqaXH8Wvg98MPj/wCG/wBi/EX/AATy /YY8SfBbRv2c5PghdeG/gbpPlS3fww+HHxE+Kvwn8J+NtSgg8GW9v4i+Len/AAw+IfhD/hdXi+3/ AOFe+Drq38Z/F2Txv4sg1LRY9Wh1lNUu9QvLs0r/AIJ2/sDaR/wlfl/s2+GtT/4Tjwh8Avh74s/4 SfUPFPjH+2vAP7Mn/Cvf+FO+B7n/AISzxVrWzwhpH/Cp/hx/wl3hq38nRfix/wAIdov/AAtuy8c/ Zjv/ADzKfor/AErsgwefQyHwL+k3l084/sjJHlGN8Fvo05/wzV4T4T4phmPCVPF5NjvYZZHNMHlm bcR5hj44HLMLDG59SwmFxWOxmX5xiMVkn6TifpI/R6xtXBPG+LHhTXjhfrWM+tUeMvEbBZjHNMzy 36vmcqWLo054h4eriMLgaFF1sTUdHBSqVaVGlXwkKeM9o+CvwJ8WfBHTfid/wkv7QXxf+Ntr418X /wBs+GtD+JmpabrGi/CjwnpNw/h7wP4M8D6ne2Wo/EfUf7O+HGneB9B8d+IviF8RPG+pfEnx94Z1 34yXsWh+OfiZ8Qp9d/Rv/gjp93/go7/2f/o3/ruz/gn1Xy5qGs2t3ZzW8cdwryeXgukYUbJUc5Ky seinGFPOO3NfUf8AwR0+7/wUd/7P/wBG/wDXdn/BPqv9GfoI+FPjT4R/Q64vybx44JzbgPjXPfpS 5nxLQyrN8tyvKK2LyGp4PcC5DgczoYHJo08BSw1XFZBmGDUqVKlKriMDiKlWMqkpVan8veKXiD4e eI30rMtzfwy4my/irh7Lvo60Mmr5hluJxWLo0M0peJ2a5licFUr41fWJV6eHzTB4hqUpqNPE0lGS SUY+7ft7f8FNvhP/AME/PEHwY8J+PfhB8evjH4n+OWj/ABV8ReFdE+Bun/B+4n0vQfg7e/C7TfGG q+JL34xfGX4N6Paxf2h8YPBdppVrpOpa1qV69xqEz2Nva2Es7fB//ERR8DP+jGf2/wD/AMA/2G// AKOavnb/AIOEf+Tmv+Cen/ZCf2//AP1YH/BPmv5kvjx8XvjF8N9ZuZfAXw01P4hadpvhqbXrLw3p ei+KdS1H4jajDdawPEnhzTvGehLe6D8Jb3wDoNhpniuz/wCE08P+JJ/jPPrsfw++HFjbeK9LupJ/ 7MqZZwFw94f8O8X8T4bi/McZxBn2b5NSwuQ5tkWXYagstp06sKs/7UyjGSvUjPlnL2/s6dnWqexo U6lSP5p4ueMEvC6tw/Qjkcc7rcRYvE4PCUpZpgMohTrYfDRr3rYvMa9HDU6U5ThGtiasqWCyzDLE ZvnOLy/I8BmWZ4P+vb/iIo+Bn/RjP7f/AP4B/sN//RzUf8RFHwM/6MZ/b/8A/AP9hv8A+jmr+PaH 9o34jfYPiFe6h+zr8WtPh8B/YvD8WpiO41PSvFvj4eJbXw1rcPhPSdI02++KWv8Awr09dW0jxXpf xU0T4X6rJr3gu08YX8Xgqy8ReG9P8LeJOV8SftI/H2L4SeGfir4O/Zq8YapqWsfEbxVpk3wj1m81 7SviMnwu8P8Ahn4gXlt4p8QW8vhmGPwL4q1HWPCulXNn4aSy8eWer2OqaP4c8PatrHibxhowsPkI 8Z+Dkml/q14nK9SNJSlxZwOoe0nS9tGDm8i5U3CzbbUYN2qSg72/DcP9MPG4irTprw0dKNXMqGTw xGI4+4Do4L+1MTlUs5oYKpjZZ99VoTlgIqpXr16tPCYCU408yxGDlzcv9mf/ABEUfAz/AKMZ/b// APAP9hv/AOjmrH8Rf8HJP7N3hDw/rvizxV+xb+31oXhjwvo+p+IvEetz6T+xbfQaPoOi2U+paxqs 1lo37bGp6xeRafp9tcXclrpWm6hqVwkJhsbG7unigk/i68I/te/HbXdF0aKT9k74tXXiqLwPbat4 mhv9I8Y/DnTpfGl1d+E/B1h4Y0E+MPClxpK/2j4+1zU9d1S4u/F91pXgr4G6anxF1DxDrXiq18T/ AA28M/SXx/vrvU/2TPj7qF9p2oaPd3nwA+Kd1caPq02nT6npE9x8NdZmm0vUJtH1HV9IkvdPlke1 u30nVtT0x7iKRrHUL21MVzL9twNQ8K+Ps7xfDuAyvxCyrHUsizzN6GJx/EXCeMwrlk2DeJ9lWoYL IliVCs3BJ3pc0XeMldNfe8E/SMxnFfHGB4Ix/BX9gYrH0c2rUMW+KOGs6vHJ1RlXc8Bk2aYrMMNS rwr0qmExGMw2HpV6dSnUpOcZI/03KKKK/Lj+owooooAKKKKACiiigAooooAKKKKACiiigAooooAK KK+fP2pvjfL+zz8DfGfxK0rQ4/FvjVG8P+C/hR4GkuGtB8QfjT8TPEmkfDv4OeAmu4w0tja+L/iV 4n8MaHqmrJHIuhaReahrtwn2TTLhlAPjfxv8W/BmsftL/Ff9pD4hXd43wF/4J36HdfCTwVZabYza 3qfj79sD406L4Wk8cN4D8PWubrxX488K/D3xf8O/2d/hLaaCbzVfE3xI+Pfxs+FttaJr2ni3uPGP 2xvhJ4z0b/glv/wVa+P3x0tLNf2jvjl/wT8/axuPFmlWt9DrOmfBr4c6J+zv8Vbn4cfs6eENWgzb X+h/DiLWtX1Hxd4isglv8Qfi14l8f+OreKw0HV/DXhzw5237DfwRh8c6Z8LfEuq66/jf4C/s1Xfi G5+FXiy9gS3i/aw/ax8S3uvaj+0b+3vr1qp+z3vh7X/iJ4r+I1j8Co8f2Jf6h4h+I3xj0aPWfDmt fAvxHoXlf/BUn9pHxf8AHr/gnd/wUX0H9lTRfD/iP4ReGf2Lv2uofix+074viv7r4Varp+hfA74g r4u+Gn7PVnpGoaZf/Gbx5dwWt74Z1X4ladqNj8Fvhbq11dTP4i+KPjvwb4n+DkIB/O5+1T+0l45+ Ct/4k1W08S3kVpc/EzWPC9rqPjH4oax8NfhV4MtzN4i1CHU/iF4+i03xPH4E8Myx6KvhPw9ex+GN XTVPH/iHwP4NS3sV8SDVdO+Yvhz/AMFLbD4jeIfBngy3/wCGo/DPjnxtqGsJbeCvEHhjxXe+IfDX hjQvE/iP4fap8QPHkPgvW/F1j4G8H2HxT8Lap8MdVk8S3+neIfD/AInNrqfiPw9o/ga4HjBav7TQ /aZ8HfEf4i+CfhNo/wAW/Gnhhx8JtO0D4h6LrX7Puo+LNF1TQvjd43k/aC1LVrr41+I9HfVfGfi7 4Sf8I1b+Gpr3wt4i8HReJdrW9t4bH9oz18765e/t4P8ABa/0/wAL6T8cYfiza/FHx5e2uu+JZP2I jqupfDu/8J/F+D4RaTaQ6RqcvgOPT9F8S6d8Fbz4xSX+jWHi6W51/wAZL8PNT1bRobW10X/Q7M8+ zqhms3hqHEX1WhhnWrYOjwlLMcNVqYfGxo1aGFzJY/BTqYjE0aVSth3FToPD16NVTVenLCv/AG44 P4e4YwvDHh1Wy3wjqY7LMH4V8H5hj8FQ+jLw/wAS4HOMXgaGVYTG0cv4onjclxmJzXO8FhsTmWCk /b4SWAzLCYyWI/tGhVyuX0Fon/BTjTPHvhX46+KPhP4i+KXjyy+A/wAHtX+LXiHVv+Eyt9I8K3e3 TvFOteDvCH9qxeJ9Y8QWniDxr4f8LXHiXy4/B9//AMIPp1z/AMI/8RYvCvxO03WPh3p/l/g//gsd 4X8VarrXhqcftB6F48h+KOk/Cjwz8K9W1vTtL+KOu+JtbufCuh6Zp+p+HNf8caFpXhnULjxZqPjn S737T4kv/D3hTT/h5JceP/E/g/xL47+Hng7xJ6f460H9p7XZPGs3hPxzqHhDQ9S+KPwel8CWOjaH 8LI/H/hnwPbeM7fwD8d7LWLzxbp/xC8Da94P1HwNZyfHT4ZamsNj8TLfWtaufCXiLSYotGtPBGo+ XeL/ABn+3dY/GaKL4e/Cb+3vhRpn/C2tS8QX3jnUvg5o+neLPsMEd58L/Bnw30rw78TLvxv4W/te 28FWXh62+JnxA1jXN3ir4zeLPGXiv4TeHvCvg/wr4F8P8eOx/FuGeFbzDOFarHD4l4PganjqOMWJ zHG4WhicNSoZ1iMTlscNhqWHxeKnj5VoxoqniJ4elPFf2dR+nz7w6/syeUynwVlMVHF08uzKeS/R K4Pz/B5zHNOI8+ynAZnlmFy/iLMc04ZpZZleFy7N80r5/UxlKGCWFzGvl+Er5t/q5gfuP4QftQ63 8bfBkHj3wf4q+MVh4dvtQv7bSJ/Gdp488F3Ov6VDIk2i+LtAtfEQsZdZ8H+L9DudN8S+F9fsPOtr vStUhtNQXTPEVhrmhaT/AEmf8EN7m4vPAf7dV3dzzXV3dftp+BLm6urmWSe4ubif/gmp/wAE7pZp 55pWaSaaaRmkllkZnkdmd2LEmv5MfgNqP7V03/CHad8efDnw/sNPt/g94e1Hxb4g0jV1vvFV78Wb 3+x9KufDhtdGS18MP/ZcHh/xV408cavpel6T4aj1H4k+DPAPw/TxDp/w58TePPGP9ZH/AAQv/wCS d/txf9nm/D//ANdo/wDBOyvzzx0xlfG+G+RVsRDFQrvibLo1ni8vq5XVqVVkucudT6hWrV6mHTba 9nKrU5ZRkoylFJv+Rvp28PcL5dwV4H5tk/BGVcJ5vjanGGFzfEYbw8wfh1mOYzpYHhGrOeIySk6+ MwlB1pyccJiMbioUq8KvspzgoTl8Xf8ABwj/AMnNf8E9P+yE/t//APqwP+CfNfhPcf8AHxP/ANdp f/Q2r92P+DhH/k5r/gnp/wBkJ/b/AP8A1YH/AAT5r8cIfg58W9Uhi1PTfhj4+v8ATtRjS+sL6z8I 69c2d7ZXai4tbu1uYbB4ri2uYJI5oJ4naOWJ1kRmVgT/ADD4vVqNHwD8OHWq06Slx5xSk6s40039 So6Jzau/JH/O79OfgPjnjzJeDMJwNwZxZxni8BnWMxGOwvCnDuccRYjBYerlypUq+Lo5Rg8ZUw1G pV/dwq1owhOp7kZOWh+Pl/8AAX9rfVfhP4T0T4WftIaHpPjDQ9D+IXhT4geLf+FkfEzx7YfEPxLq c3wx8OazH/aPjKPxpqnw41zwTqnhT4laR/avhKVL/Q/Eulf2h4a0L4eXHxK8X+HvAX014c+GPxcg 03wnpuq+O77SNY8N/EaHxz4i8dab4/8AE3jF/iglhb6Jomr6Xrnw88XeG4dB8EeFfijoOo+Ob25+ HHgrxFF4T+Cfiyy8F634CfxRIlydK6mH/gmJ8SD4l8LeItTvf2t9Zh8H654C1nQ/C1x4c8J6T4L0 +0+HN/oOp+H/AAnpPhrwt8HPD9j4Y8D3N94W8M33iHwj4PHh3RfEmq+GvDGv6zbXfiLwv4c1bSsP w3/wSY1Twn4WsvA+h+HP2m7Dwe2h3HhvxTolp4e0nT5PHui6n4vn8WeJbLxL4j0z4X2XjCw/4TS3 XQvBXji48EeIvCF34u8A+C/A3hjXZ7238KaTNB/M9XOspq04wnneXXVWVS8MHScpKu5Sre0qutTd f2bsqNGtTdF+0jBexpwjGH8+Zx4V+Leb5dRweM4H8SFVoZvi8yjUwP0V+OZYivTz+pmOLzmnmWa1 MFllXP45bVnCnkuS5zllTI5rMKGEpxybK8BRoYLufg/4D1b4d+FtS0TW9f1zxJfXfjjx/rdvqGve NvGnjy7g8Nar4v1iXwJpCav461HUdWt/7D8Ar4X0i/0+3lFgNastU1BZdTvtQv8AXNU83/ar8Z3n hz4N/GTw/q1nbR+FvG3wE+NWl6HryNKs1n47074c+JtUHh/VQ7GAQeJPD0N3deHriNYgmoeHNV06 7lkutY0OBvqn4a/sffEb4Wabr2naB8Nfjjq8nibxVqni/W9Y8aW3j/xp4h1DUr+3sNLsoLnXfEUd 9qU9j4e8M6N4f8JaHFPcS3EeheH9NOo3Opaw+patqHkn7Zfw41Gw/Zg/aB8P/EXwfqmlTp8GviB4 rsdK8TaTe6Xc/afD/hrVdY8P61b297FbzlbHX9DiubW4RTEbvT3jJcRypX7b9GjExx3idmby/MaF TFf6lcYYiEnKnavGGWqdahUpQnXlTo16fPQ9pFVJUIzhXhBzpxpnsfRs8LvFXh76QVTivi7w98TM oyLFYHPva8TcW+HnEnCOAqYvH06LhT5syoVMHhFOs50suwkswlUqYanSiqVGTlh6X+mNRXzL+yl8 atf+MXw41Cy+I+nad4e+O/wf8V6n8HP2hPCel+amnaN8VfCllpl7ca1oENyWu08CfFDwnrXhT4xf C+S9Y39x8NPiF4Sl1RYNWOoWlt9NV1H+s4UUUUAFFFFABRRRQAUUUUAFFFfnB/wU0+A37efx8+Ev wt07/gnb+1N4f/ZH+O3w8+MGrfEe++IfizS38T+FfFPhW1/Z4+P3gzS/hj4l8D3nhTxt4W8X+H/F /wAVvG3wwfWW8ZeGNd074eadpdz8ZvDPh/xV8Sfhn4F8Ja8Afo/RX4g/sufs+/8ABcP4R/s9+BvC Xxi/a/8A2QPiv8WvAfw/8TS6RDe+BvizrnhzV/GPw5/Zn8Q/AX4F/Cn4u/GDxSZ/i18Zfh/8Zfi1 P8Pv20v2i/2gLXR/hX8dvAfxT8EfET4M+D9F+L3wl+OWiXfwBPiB+zz/AMFzbTxb8K2+Fv7e3wA8 QeEvh7/wsTUPG9z48+F3grwZdftAax4f/Ye/Zh8M/A7TPHfhPQP2cPiBcfD/AOH/AMQP+Cg/w/8A 2kviP+0JoXwp+J3h/wAd+Gf2cfjmvh/4P/FJPFvh/wACaN8LwD9vqK/mhbTP+C0fiz4e/Dj4kfAL /gsz/wAE4Pi98CfiV8YPD/wxvv2stU+F3w5s/BbfD3Ufhn8Mf2VvBXiD4DeA/h9ofjbwH4v/AGn/ ABf+2H42+OPjjxX8OPFn7TGufDPx78ffhx+yz8OPhgvwd+G3jH45fs26p9wfAT4N/wDBZLwr+1P8 L9e/aK/ax+AHxe/ZStP+GmvEPxd8OfD7w5oXwm8Y6j4x8b/EXx5Z/s6+GfB/gq9/Zp8fam/wA+FH wS0P4RX9r4Gvf2l9D+O2nfHbx/8AGLVviJ+1H+0f8LfAfw78AeKgD7z+Kf7VfwQ+Dview8FeNfGu kWHi7UIUuk0GbVtB0me1sHhe5GoajfeJdX0LRtPtXtop5bT7XqcU+pzQnTtJhv8AVprWwuPyQ/bA 8f6Z+2j8bfgZ4XHjy4+EX7K/wSvfF3ij4633jJte+FHj/wAReMPE2iX/AIN0vRfh/rHie38NeFIN Uufhtf8AxA8EadqWm+OW8ZWWh/GTX/iv8PLTQ/G3wq+H3ie61f26v2Vf2mdM/aE8b/tX+HPFnwI8 W/s/2+l6R4v8aeFfjnYeCtOPwh0bwN4E0HQ/EPiDwv458ceDPG1l4ZsII/D2oeOrzUzFY6bodzJq OofYrq+nmuJPCIf2ff8AgoP468LyRaT8EfCdrrfxA8OjWvH978SviL4m8R/D+/8AH11H4I/4R3V/ +Ee8cT+P4PiNpVhBpuqa+da1zwd8LPEnhvVtM8F6dp+lX03hU654h/Z8Dw14eTweSznmc8TWxuS5 ViMwq/2nSpxwWc4rGUYZlhcSnSw39nYbA4b6zCHNRzCbqqhipVKmGk4S/m3M+NPF+nmXElOnksMF h8t4mz7B5RQWSV6tTM+G8Dltepk2OwT9vjVm+MzLG/VKlTkxGUUfYPF4GFGjjYRqU/0m+HngiX9t bw7bf8JHfeGPAX7E/haQ+DfAX7L/AMJta08t8UPDvhYJpGmr+0P4n8KeTpOk/DsWVpbWmj/sy/DW 8bwpNoduLP4veNfH+k67f/CXwb1P/BU7TNN0T/glB/wUb0bRtOsdI0fSP+CeX7XumaTpOmWkFhpu mabYfs2/EK0sdP0+xtI4rWysbK1iitrS0toore2t4o4YY0jRVHgf7LvwK/4KYfsufC8+DdJ/4ZE+ L974m8R33jTXP+E/8f8AxM+FMXgO/utH0DQI/Bng3Tfhx8E/HXh7UvClvbeHotWjuxZ+Gbx9b1XW 728s7241KW5Tyr/gpr42/wCCkjf8E2/+Cg2meOv2Zv2IIfBM37EH7V9r4x8beE/25fjzc+KtO8K3 HwG8fJ4h1zw18LtY/wCCeFppGteINI0iS7uNG8K6p8YNB07xFqNpbWd94y8L22oS32mfmvE+EyjA cQZvg8gxk8wybD46tSy3GTqRqzxGFi/3c51YUcPTqyS911KdGnTqOPPCPI03+08EZhxDmvCXD+Y8 WZbDKOJMZlmGrZzltKlOhTwmPlH99Tp0KmIxdWhBtKcaNXE1qtFSVOrL2kZJfMHiPxP4f8H6JrPi XxVrGmeHPDfhzSNR8QeIfEWu6hZaRoWg6FpFpPqGra1rWr6jcW1hpelaXYW1xfajqN9PBZ2NnBNc 3M0UMTusWg+LPDvirQtF8UeF9Y03xJ4a8SaTp2veHfEWg6hY6xoWvaFrFnDqGk61ourafc3Fhqmk 6pYXFvfadqNjcT2d7Zzw3NtNLDKjt8ZfGXxj9p+BPxT8TftpaL4T/Zn+G/gBfA/xAsfiF4T+L/8A wsPUPD3ifwH4z0zxv4H8XaZBqPwp0Kym8WeEviZ4b8Cal4I8GXvhf4h6f8SPFDab4O1HwT4qstSm 8KeIPgPSf2U/2MJPiYJE1v8AbFg1Xx3+0z4J8V/FK00bxZf/AAll+Nvxn+MfwZ8HfGbwB4r+MGk/ DGz+G/xjg1b4XeN/AmofHu1+DGk2ngj4mfsj/EX4g+Ovjp4i+DHwl/Y78S6R4x07838Y/pleNfCP in4lcL5JnWEyzIeF+I8bgcn5/DunnMp5fhMDlGJlha2JxWY5VKWa+0zKEPq9WpGrTqV8HSxNPDwx P1ij/EPBvg1whnHDOW5lm39pLHVsM6uIq5diqeOwNSUfZuUaFfC13hZ1LVYLlpYicYzlThPk9o5w /d/7bF/dk/Jf/i65Pw38SvAPjL7N/wAIf4y8L+K/tnhPwp49tP8AhG/EOi679q8DePP7Y/4Qfxnb f2Xf3Xn+E/GX/CO+IP8AhFPEUW7R/EX9hax/ZF5ef2Ze+R+O/wAC7b9ki+/aP8X/ALTnhzxv+0z8 Z/2i7f4e6/8AE/wh+zr8RPCvhXVNT0LSf2mPHekaGnjz9nq7i+HXhnw18StJ87RdA/Z3sf2rPCPx 2+J3wS8I/AHS/Bvg/wATfH+3/Z08MeBNf0T8zfA37O3/AASFWLXfCvwi/ak/bF8F6H8VPiF4j/Zb 8RaD4I17wPrOheOvFvwk+HXxBtNW8afDrV9Q+EPjOb4p6t8YPDWj6ho9tcfsy65428aajZ/tmeFf gRD4I8C+BP2n3+Et/wDD5d9Nb6RmJ/tKli+IsPQrYHC5ZW9rhvB2WMw9GviPrGJx9HF0oZtDGwoU stp0MRluOVCOFzSvVrUKU6cKVGtifraH0fuBKnt41FxDGVGnh581OliasIzqc860akVNVVCNCMJ0 K3IqeIm5Qi0oxnU/rpjuo5HCKHBOcZC44BPZie3pX2l/wR0+7/wUd/7P/wBG/wDXdn/BPqvxZ/Yp +Hf7NPhvwl4v+I/7LvirVvGngT4vfELxpqNz4hTxv4n8QeAZ7z4f+KvE3wzsdB+F3ha4ubX4d+Ev h78M9G8LWHwZ+HU3wx8MaPoWsfCL4Z/DKxj1rxnofhzwvr8v7Tf8EdPu/wDBR3/s/wD0b/13Z/wT 6r+geBPGHjTxq8AM24i46xdHGZvkfjniOE6NSlkFPhqpDCZdwFl2YVKGJyqni8a6WIoZpm2ZU+er XVepRjR9tQw1RSw9L0/B3hXKeD/G3M8qyaOLjhpeGeLxVVY3mVdYqXFWU4espQlKcqaj9WjBQlLm 91ylGEpOnH8/P+DhH/k5r/gnp/2Qn9v/AP8AVgf8E+a+Pvi7qf7fOi+AfhhrH7Ivh7R/Fr6T+zj4 K1P4f+FNZm+GVt8LfE3xLsNF1K68f+Hv2m7nxlrnhj4sW+j614Ji8F6b+ypP+zl4k8PRRfG+58Wy ftP65pPweXRL+3+wf+DhH/k5r/gnp/2Qn9v/AP8AVgf8E+a9D+Dv/JIvhZ/2TjwP/wCozpdf55/t ZOI48K/Rk+jHnEuH+GuJ40fGTxEpyyjizLama5NiI1OG8Jd18JRxWCrOaUbQqUsTSqU1KThOMrSX +pf0asveZ8TcaYRY7MMucshyySxWWYiOGxcHHHSsoVZ0q0OV396MqcoyslJNXT+K7T4r/wDBSq30 X44Xms/sr/CG6/4Qz+yfAHwbbwx8UtKuvH3xf8SWHj7T/D3ib9oy2+FviDxd4e+Hnh74Q+Ifh54h l+J/hH4B+M/2ovBfxX0PWvhlrXwp8RfEy/8A+Fm6D8S/AnnHj3xx/wAFdda/Zl+H/wAR/hv8HfgT 4N/akvPjt8R/EHib9nXxVqei6x4H8Mfs76T8P/jZbeBfhz42+JGn/FO9g+IvxH8SeKNL+FWraV4+ +Gut/CPS5fGPirwvpHi7wz4I+HOg/E7U7j3b9ojRv2WP2yvhB8MvDHjbxn8IdQ8IeI/i/wDB74t/ Def4o+HfD2sab8QtN+Ev7R3ww0PVJPh/4e+IMuh/8JT4Q+Nn/CT6V8CdA+I/hddX8J+OPCf7RPhW 68K3Hj/wh8UvDWmeNfir4Yfs3/sp+INf+CXxh8M/t1fAnWdA/ZW1j9oD4mt8Q/gJP8E9C8cfE+y0 69/ZF8QfEz4j/tUfHG98Y/FOfxh8R4vC/wAPvDujfto/HTwdZ/B7X/jD4O+Pdr4f8Uy/DT4f+LNd 8KfEz/FDhKvwtXyp5tm/A/BXDWeYDijNJ5jlGN8GvEvijAyjk/B2YZfgOHquLXG2Ly2jgeJeJMFK GZYNZblWfZHxHhauZYfM6WR0swyur/UOaQzKGJWFwuc5vmGDr5bhlh8VR4t4ey6snis2w+IrY+NL +x6VedbAZfWToVfrGJwWMy+rHDzw8sZPD4mOx8MfjH/wWt1Dwn4W8PeJf2SfhDoHi/QPhDp9n4l8 afFvx58NL3TfHnxpvdS+Gvwtsr6S6+B3xqvf7A8IaB9t+IP7XPxH1XS/hTZT+IvCdlcfsn/DfwFo Hi/QPDfx7+J3m/8AwVxn1+5+EfxMuPFemaPovii4/Yq8Zz+JNH8Pa5e+J9A0nX5fDPxJk1jTND8S al4e8Jaj4h0ew1Frm10zXL/wp4YvdWsooL+68PaLPcSabbfuzpniHQNavfEOm6Prmj6tqPhLWIPD 3iuw0zUrK/vfDGv3OgaH4rttD8Q2trPLPousXHhfxP4b8SQaZqUdtey6B4h0PWI4G07VrC4uPwH/ AOC18Xju20P4m6p4butJ1Pw7L+yN460vxN4W1VBYXNvazWfxQEvivw7r1vDNKdR023ndtQ8OarbX FjrdnaW66ZqHh/UIbhtZ/vL9krx1h+KPptYSrS8NOCeB5UfCHxhxaocCZVn+X82DzXh/B4ilRrYf OuJM6nisvw3O8XgaijWzCGHxTo0cRXwEMJhcP+YfSByeplfhXi1LP86ztTzzh+k55xicDiHGrhsV VpzqQnhMBg/Z1p29nXirUXOnzypRrurUn/ZD+0f/AMYzfGTwx+2rpv8Aonw11jTfDPwU/bJtk+Sy sfhedb1A/Cj9oa9UfuoG/Z88a+KtUsfiFrExtLOx+A/xE8feMfEt9PZ/CTw1Zwff9eLfD34l/B79 qH4Z6xfeGLmx8a+Ctcj17wH488IeJ9Bv9K1rRNRezOm+L/hp8U/h34r0/T/Eng/xRY2t82n+KPA3 jTQ9L1mzhu1j1DTVt7uF5vn/APZA17Wvhhq3jX9ib4harqGq+J/2fdN0XVPgv4p127mvdW+Kv7KH iCa6034V+I7zVLp5J9c8afCu90rVPgh8U7me5vNdvNV8IeFfib4lXT4fjJ4aiuv9qz+KT7pooooA KK+YP2yf2Q/g3+3f+zx4x/Za/aDsvEGq/Bv4h+IPhZrPjrQvDWuz+GNR8Tad8K/i14F+L9p4Tudf sYm1fS/D/izV/AWn+G/Flz4eutG8VDwrqmsp4U8S+FfEj6X4l0r8oPjv/wAG9XwT/aI+Nnwg/ab8 c/t9f8FP9H/aa+C/w/8AGfw68M/tD/Dr9oH4RfDr4u3ej+O/i78efi5rM8/ijwn+zppv/CM/ZP8A hojxt8LfDvh34bWfgTwJ4Z+CeleEfhnofhGx0XR7k6kAfv8AUV/DH+0r8ef+CXN58TP2qPhz8av+ Ctn/AAXe8EfDb9mL4wfsZ/sF/HLx7H8WvDXi74IaF8ffg98PfE3xN+H3xW8B6DffBX4k/HHQ/jBp 3xx/4Jqarf8Axa/aG+GPw18M+NNd/aV8Sal4n8F6hf8AwJ+KHjXxRZ/u9/wVd+Mv/BOPx98Rf2bv +Cff7Xnxu+IHgX4tfHf4gN4A+HXgz4UppcfjFP8AhvH9lj9vX9hbwj411qPxF4S8Vf2j8P8AUf8A hKviv8PovEfgnRPFH/CqPjtr37P+t/Gqz8OfCXxXPfa4Aft9RX8cXwh/b2/4Ih+Jdb8Z/si/Dn/g oF+2/wDtUW3/AAWt8P8AhT9gvx74t8Wand67P8J/iZ8Kv2R/hX+xroPxW8S+Fvib8LvAHxW8GfGD 9sHwt41+Gujaz+0Nf/B74ufD34sfGXwJc3nifUPBngn4QeKLDw1+v/8AwT3/AOCeP7BnhLxp4K/b m/Zg8K/GBtI8T/B/4a6b8HvGnxG8Yprfw9+MvwQufgF8KtK/ZF+LXhD4Y6zd3uueBfEH7LH7LniD xJ+xR8GfHnjLwb8HP2lbj4Z+Jf2irH4+x/GfVvi5efGrx+Afs9RX5wftc/sH+Kv2j/2uP2Bf2tvA /wAavD/wl8U/sO+IPixc29jrPwj1H4maj4u8K/HLW/gbafFbRvCeqR/FrwD4b8CeIPGPwc+F/wAQ /gVc+JfGfgT40adonhX45+JfGfhLwn4d+K3gv4d+OvDv6P0AFFFFAH84PxL/AODYX9h74ifCzTfg paftF/t/+BPhk3w/+E/gbxx4a8PftB+EvF3/AAs+6+EXhzwb4T0rxV4m1n40/CH4reIPC3/CU+H/ AIU/AXT/ABz8KPg/qvww/Zx17/hmT9ly6h+CWn3v7OPwcufBv2/+zN/wSN+Ev7JP7Q/jH49/Bn9o f9p/QtJ8e/GDUfi74q+AaXv7PGl/BrV4LP4S+MPgf8Ivgnfaj4V/Z08N/Ha//Zg/Zi+G3i5ND/Zf /Zq1H423nwa+C0/hPwXq/hjwiur6EL25i/bo/bW/ah+A/wAaPDvwt/Z9+D/wv8baUPhlo/j/AMWe JfiF4g1SG6a+8U+KfGXh3RtB0bRtO1fw0tlDpsPgTUNR1DVrnUdYOptrNnZQafpH9lTXWq/mn+0R /wAFRP8AgofpHwV+IUmp/Cz4PfDa11TRF8LL4+8B67q6+MvCF54zv7Pwjpuv+G5b/wAV+I7S11bT tS1u0uLW9k0PUjYuv2yK386CN08jEZ5l+GrToVaslUpvlmlBtKVk7X0vv0+RoqU5K6Ss9tT6I8Fy ft+fti/8FCPGPh74jxab4i/4Jq/BP9o/xzbapDo0XwqsPgt4/vfgxoc1z8KfDuh6zDqE/wC0N8T/ AIieBfjjN4T1L42aL4g0LTvgBpPxH+HHjTwbp3iLVdV8ASeF9Z/oIr+evwl8Wf8Agp5b/BP/AIJh eOv2CP2e/gd4s+Bb/s6/tTXH7UnwdDeGfCXhAat8O/DfgbxP+yx4B+GWtfEP40+H/iZ4N8e/GXxH 4C8cfATSPixd658YPAHw31H4v6x8Z/jt8NfH9t4V8O2kFX4TftFf8F9/jR+yP41h8a/si/B/4Ift R6j8H/2rde03xhodt4b8HeH/AAX8VvAmiftf/BD4R/s++BvAnxa+PvxZk8V/GDUP2g/h9+yd+0X4 J/aJ8ZW99+xf8Wv2YPi98SdD+2aHrnw98B+Lfjl6lOcatOFSF+WpCM43VnyzSkrro7NaG+LxKxU6 LWGwuF9jhsPhnHCU5U41nh6apvE1lKdTnxWIa9piKicYzqNyjTgvdX9D1fAH/BWL/lFl/wAFLP8A swD9sj/1nX4jV+cDfH3/AIOStE8P/DixH7EX7EHxM8bfEvxB4f0bxPrC+LB8Evh7+zPp2u/swfDH xDqPiz4jxP8Atd/H7xj8Y/D/AII/aw+MfirwL4gtvhFpdr4q1n4Z/sTfE678K+GtTuf2uPgz4x+D fsXhrVf+CrH7Q/xWt/2X/wBuf9jH9n7Tf2Gvj74B/bK8J/tJeMvhB40g8Vro3gXxN4k+Jvwi+Bn7 P0Hie9/al+GHxclXxf8ACDw1Y/GLxj+1P4P+AE+reLh8e/h98HF/Zd/Ze8TeAPib8U9Ds5D5Ult0 mYMxcEDb8pAGASe6nnmvONB+C/wk8KxaLB4X+GngHw3D4b1bTte8Ow6D4N8M6PFoOu6P8Oofg/pO taLHp+lW6aXq2l/CW3t/hdp2o2IgvLL4dQQ+CbaaLw1EmmL+sf8Aw5p/YS/6Bn7Wf/iyb/gpJ/8A RZ0f8Oaf2Ev+gZ+1n/4sm/4KSf8A0WdfqHED+jbxVneb8R8Q+BuCzTO8/rvFZzmOIxFq+ZV5QjTl UxXssTThVbguWzhy8t1b3pH8Z4H6PHilluEpYHAeJ+DwuDoU1SpYejhcbGnCmr+4lbWK5paNvfzZ +TmtfBf4SeJPh1D8H/EXw08A698JbfSdB0G3+F2teDfDOqfDqDQvCsunT+F9Fh8E32lT+GotJ8Nz aPpM2g6cmmLZ6PLpenSafDbvZWxi5Twb+y1+zX8Orzw1qHw++AHwW8CX/gzVvE+veD77wb8KvAXh i88Ka7420LTPC/jPWvDVzonh6xm0LVvF3hrRNG8O+J9R0t7W81/QtI0zSdVmu7CwtbeL9jv+HNP7 CX/QM/az/wDFk3/BST/6LOj/AIc0/sJf9Az9rP8A8WTf8FJP/os682GUfRcp0auHp+AmCp4evOrV r0IY2vGjWqV6XsK9SrSjjlCpOtRcqNWc4uVWk3Tm3CTR2rwJ8YFGUF4tUlCblKcFQxyjKU48k5Si laTlG8ZNq8o+69HZfmX4d8L+H/COi6J4a8LaPpnhzw34a0nT9B8O+HdC0+y0jQdB0LSLKLTdJ0XR tI063trDS9J0vT7e3sdO06xggs7G0ghtraGKCJIx90f8EdPu/wDBR3/s/wD0b/13Z/wT6r0z/hzT +wl/0DP2s/8AxZN/wUk/+izr66/Zk/ZK+BX7H/hTxj4M+Avh3xXoWj/EHx9cfE/xtd+OPi18X/jX 4q8TeOrnwd4L+Hza7q/jv43+PPiL44umg8FfDvwV4bsdObxD/ZOm6X4esYdPsLYmdpts2zjw2wPB S4K8NuA4cEZbV4sXFuOw+GqxnhsXmU8pqZTicVOLqVarxVehDAwnUc+V08JG65m2/uPC7wh4s4M4 yxvFfE/FmF4kqYnhrEZBTVOhiKeIpqtmmXZlCTnVSg6UJYXEJxtzuddSva6X8+3/AAcI/wDJzX/B PT/shP7f/wD6sD/gnzXyn4M/bUvfCvg/wp4YX4S3WpL4b8NaFoK6ivi2W2W/XR9LtdPF6tuPCFyL cXQt/PEIubgRCTyxPLt8xvqz/g4R/wCTmv8Agnp/2Qn9v/8A9WB/wT5r+d39onwV8ctRsbnxr8Lv i/4f+F8Hh34aTXWkeKvFvizV/DvhX4V69oMOt614j8U+JvB6aJrfgH4ueH/iLoUuj+DtZuPitHDZ /AHTvDtz8T/h9Y+IvE+q6jpNfTZx9GjwG+kn4EcJZX48eGNbxPynhHi/iLOchyvD8V8Y8KVcBj8X Qp4TF4mGI4P4m4Zr4udfCwWGpUsxxNXAUq06VXETy/CrFZjhv9Kvon8CZzxpxD4j18m4g4myOrw9 wzlOYYilwtk/DGcZhmWGqZhVhPD+z4ppVMFRn+79lg6vPhMIsficLLPczyTh+GaZ9lX0vZ/Cz9ji 2+Jen/GG6/ZW+KXiL4laf8R/hh8XT4r8bftn/tV+Pr3VviX8FYri1+E3jHxRbeNvGXiDTvGGsfD3 Try/0bwrJ4rs9Zi0nQNS1Xw/bQrouqahYXJpXwn/AGJtF8M+FfA2n/saeI4/h/4S0fwv4etvhxcf tN/H+/8Ahp4m0DwV8XfG3x38KaH8T/h1f6zc+CfjHo+hfFj4jeNvF2n6Z8WdB8a2UUviG80kwNoE drpVv8RXnxG+N/hvxD8SPhzr/wC1d+ycfiTd6h4Z+H3wf+F+qa/ofhX4mPp974n0eXR/Hvi/XZrP VVsPjj4/+HviK/j/AOES0v4A+Kvhcnjiy+HWv+GPDB8LXfijwj4k5/WH/aM8e/CK20Xw3+2b8DtC /aa8BfHHWdR+Jmp+EfEHhbWPh34Fk8U2PxN+Hnwz+Aq+Gf8AhFYtSfT9a8Zal4J8O21h8X9I8SeM 7TxdFr+uaZe+MfFHhTwnoE/g1/oPfQ8qxWH/AOIVeLeLq4OlhKlLBy+k79IuTpT4blXwOWYKj7Tx 5dCjmGU4GvjauVYSU6Ly3L6mIbnl9GrVP6/qfRwyynLF0cFxjx9i8zoYTOsVXy2j4Y/R4pYqpXwu arDZvkjqzxawkOIsXh8LVz2eUYvE4ef9mYP69nlbK6VOVWl+0fwU+Onwk/Zx8J6l4F+BP7Jfhv4V eENY8X+KPHup+HvBmujR9NvPFnjHUn1PXNVlgh8Ef9euj6NYqy6b4Y8J6P4d8FeGLPR/CHhnw9oe mfF//BR/4tzfGX4K/HnxPN4Yk8KNYfsyfFHQRp0uptqzTLa+E/HOoC9Fw2l6QUEh1QweT9mcKbYy ee3meXF8F/Caw/bh8S2138PtP/at/Zuv9Z+E/g+z8AeLLnwV4mh+M3inSvH82q+HfAkniH4l6R4i +HWn+JbPUPDngPwx498a6P4e1zxhDrXiz9oyLU5vGXiK5+E1+vw38B/S37WUeqw/svfHKHXb3T9S 1yL9m74mR6zqOk6Zc6LpV/qsfw88RrqN7pmjXmra/d6Tp91diaey0y613WrmwtnjtZ9W1KWJryb6 vwX+hZ9E7wo4u4h8ZPCvwUz3g7xHqcKcU4Gtxpn3iX4n8YYvHU86y+tQzvD1KHGHiNxThcbiZzoO jicbjctWJhOnzYfERcuZ/jH0g/CjNMj8BsTxX/rV4h4nJcBn3CuX0Mn4o4O8M+H8kxGJxOOxWExW Hy6vwlWnm3tsixmExGGrwq4XA4WVWHu+1hKF/wDQC+MP7NMniTxe3xw+B3iyP4JftJWmm2Wly+PL XRhrfgz4qaBpPmtpfgD9oLwFFe6RH8S/BtmZpk0DVrfVvD/xL+HjXd/J8OfHfhqz1nxPpXiL4++L PxN8X+PNT8JeIrf4b3fwv/4KJfsmQeIviP4f+BLa1b6pYftN/BO5TSbD49/Dv4C/Ea5tNB0f4u/D j4saDp+iT+GZ7m08N+Jfhd8b/D/wH1/44+BPh5LZ6dpurfq5quraVoWn3Ora3qen6PpdmqPd6lqt 5bafp9qkkiQo1zeXckNvArzSRxI0sihpJEQEsyg/hn/wUl/bw/ZmvR8I/h18PPjx+zL4t8b2PjSb xoPEza9pfxL/AOFKeI/DTaTb+FteuPEHwwfxd4y+C3i/XbfW/Ei+FfFUWl6fc6xoGhePtL0/UVki ngm/J+F+HcZxXnuAyDAVaFHFY94jkrYn27oU4YXCV8bXnNYajiK8uWhhqrjGlRqTnPlilrdf5scc cYZdwFwtmvFma0MVicDlUcJ7TD4L6qsTWqY7H4XLcLSpSxuJweEhz4vGUIzqV8TSp06blNyfKov9 pPhn8R/Bnxg+Hngn4qfDrW7fxJ4E+IfhfRfGPhLXbZJoY9T0HxBYQalpty1tcxw3dlcG3uEW70+9 gt7/AE+6Wayvre3u7eaFO4r+dTwP8ZfiH4D8R6TZeEvHw0XQms/FGpal8NfAjaZpvwZm+O3je4k8 W6xJp/gweItA/aVm8Bah4k8Taz4/8a6ndWOnfEPV/FWt3WvXltfQR6ho3i32D9kj/gp94h8Yj4h6 Jq/gf4p/tTw+CtVtJdX8Zfsr/Dafxl4d8B6drl5ra6NY6vb+M/Fnhn4meL/7TGlXcmkTeCvBvjhr TSre2HiK+sdRaY3P0uP8OsdhOH8w4io5ngMVhsqoZZicbh4qtHE06Wa4yeCwqShGvSVZVYKdfD16 tCrQozg6sY1ZKkfFZT4xZZmHFuUcIYnJM0wONz3FZ3g8rxcpYeeCr18gy6lmmOk5VZYWvLDOhVdP DYvDUMTQxOIpVI0ZToReIPrP/gp1+2H8TP2J/wBnvSfix8JvAmgfEXxdqPxG0DwivhnxFZeIL60n 0vU9K8QX19cWsHhrUNP1P7daPpltMr757dbRbwS2+Sk8H4Bf8RDn7dX/AEaB8Nv/AAmfjD/8v6+3 df8AjH+0z+2R8UfgB4+0X9o3x78A/wBmH9pT9sH9pD9jT4e/Be2/Z++Dn/Ce+DfEP7Ofwr+OvjKH 4meO5/jt8MPFnjiw8VeJPFv7LPx48NeL/BF/b6BbeHLDV/hrYWOk2Wr+HvF2reMftj/h2z8Wv+kg Hxm/8R+/Yx/+h/r8zx0cyr/VVlueYzJKdHDOliKOFyfgzM4YzEPFYmt9dnW4k4UzvG0ajw9Whg3Q o4uOEUMJCtChCvWxE6v+j3gp49+AXh1wVHhzxH+iPwr408RrNsfjnxpnHiHn/DOMeBxSw6wuVf2Z lmS43DeywDpVZQxDxEqtV4iSlGMYQifiV/xEOft1f9GgfDb/AMJn4w//AC/o/wCIhz9ur/o0D4bf +Ez8Yf8A5f1+2v8Aw7Z+LX/SQD4zf+I/fsY//Q/0f8O2fi1/0kA+M3/iP37GP/0P9cP1biP/AKLb Nv8AxFfCz/6Xvr/S1/XP+Jt/oi/9K7eAP/FycY//AENev9LX8Sv+Ihz9ur/o0D4bf+Ez8Yf/AJf1 z+jf8F8P2wPDmo+LNY8PfsNfBbQtX8e+ILbxZ461TRvAHxQ0vUfGniqz8K+GvAtp4l8WX1jq0Fz4 j8QWvgnwX4O8HW2s6xLeajB4V8J+GvD0VyukaFpdpa/ur/w7Z+LX/SQD4zf+I/fsY/8A0P8AR/w7 Z+LX/SQD4zf+I/fsY/8A0P8AR9W4j/6LbNv/ABFfCz/6Xvr/AEtT/ibf6Iv/AErt4A/8XJxj/wDQ 16/0tfxK/wCIhz9ur/o0D4bf+Ez8Yf8A5f13n7NX/BcD9sH4mftdfDbRPH/7PMy+BvHumxeCNb+H Pgqw13TzF9j1Sa9i+I3hx/G92I7LW9EGtNaeJfteuW+ha1og0eyvP7LvrGw1Qfrz/wAO2fi1/wBJ APjN/wCI/fsY/wD0P9fmx8bfh18bv2QP2j/2ivjb4d/ab8QfFyz/AGFv2B9L/bE+KXhb4jfBb9nf TbT4l+ET4++LWoW/ws06/wDh/wDDDwbrXhT7f4B+AnxzuofEOgapbao3jvUfhveapLdeG/Dup+Hf EW2HoZ7GcXieM80r4dVMNOvg58K+HMKWYUKOMw1evl9bFZbwhlGZYCni6NKpSeNwGNjisO5RcIVE 5Iyx30sPomY3IeKsrwf0COCOHsxzjhfOspyrN8N4m8T5xLA5rjsN7HL8ZOhicryydCngcS4Y9YrB YqGYU6uFpUsJOhUq/W8P/UKjrIiuhyrqGU+qsMj9DTq/NTxp/wAFWP2PbDwL4s8Q/Dzx145+K+oa R4T17WtKHwf/AGf/AI+/FnRZrrT9HutQs5LzxX4H+GeseBtF0T9w13feKPE3ijQvBukaLaap4j1/ xFpPhnRtZ1nT/wAzfCP7c/xc+L3gfx14ysf2lPC9yJZ7pvCl58L9R8ReCdb0jXLPTZddg8O+N4fj NbeGvhN4N8HQaLYa9q1/LYw+I/H17bQ3t0NS/sTQludM/R+GeBsdxLluNzaljcHgsHgszyvKqjxC rOpPE5rUlTp1U1TWFo4TCpe1xuIxeLw8aVKSlTjWleK/yd428Ucr4KznLcgr5ZmOZZlmeS55n1GO EeGVGng8hpQqVqDUq0sdiMwx0p+wyzB4DAYuWIrxlGrLDx5Zy+7f+CjvwUurvWtM+M/hv4peJNN+ Jfi/w/4O+AXwk+B/h3wl4U1m/wDjD8UINZ+Ivirwpo1jrev+fN4esltfEniDXvH/AIkawvtI8AfD Xwd4n+IesQSaV4c1Na8w13/gj94s+J/w40/wP8Yf2ttev/7UTwddePIvA/wm8HaFaXWpaBrWieI9 Sh8K32qXeq32l20mp6SY9IvNUt9Ue3iME+o6ffqs9jN8s/FD9u6++CXin4Q+N/Evj/wV4h1bwRYe JdI03W/iV4Y1jxj+0RrDarqEWmfE/QvCp8H6r4g+FUOjeIb7w5oGhxaj4UvvB8I1/Q10LxhbhfC9 xrOu/wBMMLl4YnLxyF40bzIf9VJuUHfF8zfu2zuT5m+Uj5j1ryuLvDSnw5QyjNsZLAY+hxBLMXhq 1D61GoquVYilhsWq0akY0bc9Sm6NTD1q9KtTftIy5JRlPo4E8Tsu46x/EeUYTAZhluYcLrJpZhSx jws6U6WfYOrjcBPDzo1pV1L2VCrDE0cXhsJXw1aLo1KftVUhD8xf2lP2Cfiz4l+HX7PvgT9hv9oj 4f8A7GGq/s6aH4q0T4c/EXxn+ztq/wC1t4n+H8/iRfCWmSeLvhf4S+IHx+8E/BTRviXe+CdO+Inw x174p/FH4T/Gj4iwfDb4z/FHwr8MvE/wrtviB8R5fHXx/af8Ekv2+p7r4e63r3/BZ/8AaA/4SD4b /ED9p3x/oVr4R8H/ABo8P+BH/wCFi/s4/BP4O/sk+CvEXg/xD+2X44vfit8P/wBjP4m/Baz+Ok/h z9oLxT8aP+GqtY8Z/EXSP2ibzxL4g+Kfxj+IPxM/f6ivnIpRSjFKMYpRikrJJKySS0SS0SP0Y/KD 4VfsSft5/D7xVYeNtW/4KgeIPEFy/iD9nLwdq/wsj/Z5fWfgFp/7MHwF1Hw3q2ueBfAei/G348/H b9oPTv2n/jdJa/EDw78Wv2yfin+058Z/EHivwX8VNStNa+FmreNvhl8BPiB8Jv1for4l/wCCl3jP xb8Of+Ccf/BQD4heAfEmteDfHXgP9iX9qvxn4L8X+GtRutH8ReFfFvhf4E+PNb8OeJNA1exkhvdK 1rQ9YsbPU9K1GzmiurG+tYLm3kjliRgwPtqiv4TPjB8X0+D3iXxXo2s/Gj9vFtH8IWMGp6t4n1P/ AIKw/wDBQbw/ptppp0C01++1DUHu/wBoG5tdMsdMtbiVru7ub/7PFb20l3NJDHuWPg9M/aWTW9N0 /WdG+Kv7eOr6Pq9jaanpOraZ/wAFbv8AgoNf6bqem39vHd2OoaffWnx2ltb2xvbWWK5tLu2llt7m 3ljmhkeN1Y/hmXeOVDNstwGb5f4a+IuIy7M8JhcdgcTz+HNJV8LjKFPFYap7Ov4h06tN1KFWFT2V anTqwUuWpCEk4r4LjDxr+jlwDxPxTwdxb9ITgnKeIeC+KM74M4mwX+ov0gMdQy3ifhzMMVlec5T/ AGnlvgxjMqxlXB47B4ml7fL8bisJiIU/rGFxFfDTp1pf330V/A9/w0FqH/RRf2//APxbH/wUO/8A n51h6R+1TpXiDyv7B+M37cet/aND0TxPB/ZH/BXn9v7UvO8NeJv7Q/4RvxDF9i+PU3maH4g/snVP 7E1ZN1hq39m6h9guLj7HceX2LxiqtNrwv8RWo25mq/hrZXdld/8AERtLvRX3Z85D6TH0UqlKrWh9 JTgmdHD+z9vVh4d/SNlSo+1k4Uva1F4HuNP2k040+drnknGN3of3+0V/A9/w0FqH/RRf2/8A/wAW x/8ABQ7/AOfnX9Jf/BGPXfGN54H/AG2fB/ij4kfFr4l6V8L/ANtpPBngO++M3xd+J3xv8W+HfCWq /sV/sX/Eu78N2/j34veLPG3jm60UeOfiD4z8Q2enah4ivLXTbrxDfw6dHaWRitovZ4X8TsNxLxDT 4aqcKcVcO46vk2Z55hquevhWphMThMox2S4DG06dTh7inP60MTCtn2XyhDEUKFKpSdaUKznS5Jfo nBfG/hf4n5FxFxB4V+KPDXiLguEs24aybiSlk2Q+JOQ4rKcVxdg+KMbkM6kOPuA+DqWMoYylwfn0 ZTyytjqmFqYaksVSoxxNCc/z7/4OEf8Ak5r/AIJ6f9kJ/b//APVgf8E+a/G7xp4J0r4l/DHxZ8ON duNQtND+IHgTXfBOs3Wky20Gq22leKvD91oWo3GmT3lpf2kOoQ2l/NJZS3Vje20dysbz2lxEGhf9 kf8Ag4R/5Oa/4J6f9kJ/b/8A/Vgf8E+a/NvRPhF8XNS0XSNR03wN9r07UNL0+9sLv/hJvDNv9qsr q0intbjyLjU454fOgkjk8qZElj3bJEV1YD/Rvwz4x4G4Q8H8pnx3xhwhwjgM0z/P8Fh63F/EuScN YXMJ8sHXwuFr53j8BSxVWNGTlUo0JzqQpvnlFR1P7j+hR41+D/gzxj4l1/GPifDcNZHxXwfl+R4N 4rKc+zalmU/r1WeOwcqWQ5XmdalF4SpLnnXhRpyjJxhUc9D8i00b4SQ+L9I1XXv2vv2gfCnxH1v4 w+HPFlp4d8QaH+ztF4vsvip478E6d+z38NLnxR4T039nfU38C+IPiX8IdXsLzwf8OPHNj4b8RyeC YvEvjrXPA2h618PfiTqPg7O8M3X7D/ivwP8AHD4h3/xj8YeNPgt8QtP1/wAYfEzS/iD4Nm0bwPB4 Hj+Jnxf8Sw6LpFxffB7wr4wtNP1D44fHLxnqfwt1bTNfuPiZ4o+JngF/DPwx8Vaxc/C7x14ctP0o 0n/gnz4V0DVdM13Qv2OfgdouuaLqFlq2jazpPhL4Labquk6rptzHeadqemajZ2sN3YahYXcMN1ZX trNFc2tzFHPBIkqKw0LX9g/SrK88LajZfsmfB601DwN9n/4Qm/tfD/wft7zwd9k16/8AFNp/wi11 FCk/h/7L4n1TU/Edv/ZL2nk69qN/q8e3ULu4uJPDp+Kfg/Gpzy8bfo51Iy+vTqRxXi1kOYSq18ZT pYedevKtxfSw9eOIw8sRHNMNLCRhmSjh6UqlGCvS/qDDfS1+jdSxDq1PFrwkxFKp/b1WvSzfhf6R PEVXFZhneGwuXV8fj543L8Nl+PpZll9TMafFWV1MopUOJo0suwtXE4GjBTwvlPwW8QfCLxfffGHx h8IfHmn/ABCtPE3xRsr3xpq+harY674YsfGenfCL4UeHRpPhrWtLtY9N1LT4vBui+Dr++kstS16O 28Q6jrdhNqdvd2dzoejeGftzeAdK8R/BX41eJL/WPG9rcaB8AvibPZ6ZoPj/AMaeGPD11cWHhPxT qFvJregeG9c0rS/EUbTHybyx1221DTdTsQNP1SyvLH/R6/RrTP2f/ipottJZ6N8K9P0m0m1DVtWm tdM1/wAF2FtLquv6re67rupyQWuoxRPqGta5qWo6zq16ym51LVb+91G8kmu7qeZ/jb9ubwv4o8J/ s/8A7QOneLNG/sTUZv2dfitew2n9oafqXmWUngrxdBHcefptxcwJvntrmPyncSr5W9kCSRlv03I/ Efwp4wwGbcP5D4leFfGWdVMiz/MZ5NwnxpwtnuKqOFDE4zE4ujlGX53mmPlSoVKvta+IcJQjNurP 2MZqnH5L6WX0rfALxS8AanAfAXiTk3E/GuJ4tyjPMRluScJ8b5Bgq3NnGNzPN8Vh5cR5XGlBRq42 VSs62Zuriq06lelQoqosLR/uU0r/AIJg/wDBPfT7+21nVP2Qfgd8QvENmzyWniv4z+DLL47+Mraa WN4ri6t/GPxnPjzxRDeXaSzC9vI9WW6vjPO13NM08zPyX7THgf4T+LLPSv2L/hF8EPgxr/xC8Wab beLr/TdX+HWgX3wt/Z2+Hl3fXmkj43/ELw1pkGmWd3fXuoaVq2j/AAd+HiXGnat8XfG+ianb291p ngTwN8T/ABr4H+i/j78b9X8ATeGPhh8KtE03xz+0V8Vo9Uj+GPgrUprqPQNF0jR5NPtvFXxg+KFz pzC/0T4QfDY6xpM3ia/t2h1LxJrmq+Gfhz4Ukk8Z+NNAhbo/gT8EdI+CXhnVLT+2tS8cfEDxvrkv jX4u/FbxFDax+K/il8QbyxsdNvPEutJaKLXTdPsNK0zS/DPgvwnpgTQPAfgbQ/Dvgvw5b2+i6HZx j+CMNicTg69LE4SvWwuJoy56OIw9WdGvSmtFKnVpyjOErNrmjJOzZ/l5jMHg8xwtbBZhhMNjsHiY OniMJjKFLE4avTbTcK1CtGdKrBtJ8s4yV0nbQ+ZNM/4Jc/sW6dp9hpMnwotNS0ez1Cz8QXGgX1wk fhPVvGtpo8WgD4han4J0y207wW3jqbRov7LfxDZ+HrK4t9Nkl0ywSz05/sg+u/hX8F/hR8D/AA63 hP4RfD7wr8O/Drzm6l0nwno1lo1nPdMuHup4rOKJZZ5Dud5GBJkeR/vSOT6dRXXXzjNMTQlha+YY uphp+ydTDutNUajoczourSi1Cq6LnN0nUjJ03OTg1zSv5+F4dyLBYqGOwuUYCljaXt/Y4tYak8TR WKUFiVQryjKrQjiFSpqvGlKEaqpw9opckbfgp8Zf2K/2vvhT8drb4zfBr48/sx+Ef2a/hH8a/jR+ 2B4X8KftDfDT4heIx4J+NXxx8A674C+JmtzeIfA3xc8B/wBpeGVsPGvxU1vwpozadY6ppniX4x+P 1v8AVfFNldeENK8KSeFv21P20PFfh/S/EVt+2J/wSi0i31a2F1Dp3iP4LftDaJrVtEzuiC/0q7/a zFzZSyKolSKYLJ5Ukbsq7sD9Sv2vP2dtO/ai+CPiT4Uajqd9pRv3g1PTryyuJ4fK1bTknNi11DDN DHf2m6Z1msbsvbShhIohu4rW8tvxW8Jf8EPZLzw9pk/ijxMtnr5g26nBZajctaC4R2UvAZbJJNkq BJCGRdrsyqNgWlh6eElhnKaws6vtUpfWs2xmWShHlnyqjSwnDPEKxMJ2vUrTnhnRnGNP2TU41Knv VP7Qjh4yyzJ+Es0bnH61W4m8SeJOBMThan772VDL8Bw/4J+Lcc2wtelFVcRmGIxOUTwleEMJ9TcK lLE4v37/AIaz/bW/6PW/4JD/APhqvj9/9FpR/wANZ/trf9Hrf8Eh/wDw1Xx+/wDotK/OX9qL9i/9 hv8AYp1j4a6F+1h+1r4G+Al78YP7U/4VxP8AEXXNU0TR/E39g+O/hH8OvEHkeIm0aTw/Yf8ACO+I Pjj8PNQ8Rf2tqdh/YHgS48XfFHV/sXwy+GPxO8XeD+g+MH7AX7IvwC1H4o6P8Yv2j9G8Bav8HPhB p/x38daXrL+JTqMfwz1Twr+0f46tNU8J2Nl4du7n4keID4J/ZD/aT8Y3PgD4cReLPiFY+FfhH4m8 Q33ha20htLu9Rv2WD/ky3/xJs4/+lqcnPxJ/0S3hf/4v/wASP/qMT76/4az/AG1v+j1v+CQ//hqv j9/9FpR/w1n+2t/0et/wSH/8NV8fv/otK/IX4K/DP/gk9+0F8M9Q+Lvwy/4KS/szT+CdD8P3Xizx VJ44+M/h/wCEXinwH4VtfiFpXwpHiX4k/Dv4unwN8Q/hr4f1D4ieIfC/hXQ9Z8e+FvDmneIdR8Y+ CToNzqNt408LXGr/AFB8GP8Agm7+yt+0V4i+JnhP4GftMeBvir4g+D//AAq+f4g6f4K8Xxa3/Y2j /G34WeGPjX8HfF1ndWts1l4k+H/xR+GXi/SPE3gD4i+F7nWvAniz7P4j0bRPEV74g8G+MNK0I9lg /wCTLf8AxJs4/wDpahz8Sf8ARLeF/wD4v/xI/wDqMT7a/wCGs/21v+j1v+CQ/wD4ar4/f/RaV8ve N/hl8bP2qfjXqX/Cy/26/wBgQ+G/2kfg9Yfsh/HzwH8C/APj7SvEXxR+C9944l8S2nhPw3e+Of2g PF1vovjXVm8ReOvh5Y62dP12zXwl8VvG1hF4Tv8AxNd+Ftf8Mejf8OM9E/6HCf8A8GE3/wAi16L8 Iv8AgjZpPwx+Kfw7+I8Hi+6a48B+NPDXjC3jS9Lmafw5q9pq0UDrLaFTFO9osMwG2TynfypIpdki XTo5e6lNVngqVFziqtWjxBmuJrU6TklUqUsNU8PsFTxFWELyp0KmMwkKs0qcsTQjJ1Y9uWrM6uYY ClnGReH2XZRUxuFp5rmGVeNfH+eZpgcunXhHHYzLclxv0S+HMHnGPw2GdWtg8rxfEOQ4bMMRCnhK +dZXSrTx1D90ksYDp66bcRR3VsbMWU8M8aSw3EBh8iWKaJwySRSxlkkjcMjoxVgQTXxX4k/4Jw/s YeI/EKeL1+BfhLwz4vg1lPEtl4s8E2x8H+JtL8TRjUFTxNpGuaEbPUtK8Qomq6giazYXNvqCLcnZ OpigMX3AOgormwmZZhgFUjg8bicNCs6brU6NacKVZ0pc1J1aSfs6rpy96m5xk4PWNmeLmGS5Rmsq NTMstwWNq4ZVY4atiMPSqV8PGvHkrxw9eUfbUFWhaNVUpwVSKSndJH4qeB/gx+xZ+yV+1lq/w2+K /gL4BaU/ijStS+N3wB+MXiNPC+n+JPDsMusmLx/4E+K13q13jS/FMnizVdQ8U/Dr4m3qaTa/Fnw/ qXiHwrfxXXjn4V634i8d/pRf/tbfsqaVZz6hqf7TX7Pmm6faR+bdX1/8Z/hxZ2dtECF8ye5uPEkc MMYJA3yOq5IGckV+AH7cnw6+A2r/ALaH7R+s/EjwJfap4k1HxF8Ntmqp4Y+IN6l9pNp8BPhJaWfk 33h6xl025htriK+tv3UrtDcR3MMu2VJFH5lftCfBb4Z/EA/D74WfszfDLWPEnxn8RfEHRLceDdD8 O+NRrk3h7WvC/wAQLPT9Q1G38TQ2+naV4ePiTTbSaXxHq0tho+l/2Pe6ne6nZ2Gj6nd2vyWacY5x isVLD4mGLxywdSth8L7etXrRhD2snKNCDvClGtUftHClFKU53fNJ8z6cuyLKcrjWeW4HB4CWLlTq 4qWFw1GjUxNSnTjSpzxNSEVUxE6dJRpU51pTlCmowi1BKK/pL/by8Hftw+Ovjr+w58Uv2Gf2w/gl 8EvCMHhL9rTwz4h+HXxS8axv4O/a6+JPjD4O+GfjN+yr4G0rwifhp8S9M8e+ErTxb8A/EGu/GXxP 8PNQ8D/tAeDf2WNR+OWp/APxzomp614g1Sz+TfhN+zr/AMF9/HH7I/jX4Q/tG/tdfB/RvjH4n+D/ AO1bpd78YtDufDfhX4hS/HPVdE/a/wD2fvgf4W8Dah8A/gF4G0j4a/swahpHiH9jz9tfwT8d9GuU /bC+HfxM+HnxJ+GPjPwBqnhv4qad4U+A/wCgHx2/YCu/2mPg38EPA+pftN/tNfsn+Lvht8II/hjr Xj79jvxD8Gfh58XdQ0fWJ/g14i8TeF9L+PPi/wCCPxJ+MXw/8M3Xi74J+DrzWdL+Cvjn4Y6Z8RLX T4NO+KFr450jTvD1honw/af8G6H7IAuvh7rOt/Hr9r/xN4t+FHxA/ad+KXw28Y3/AIr/AGf9D1j4 eeO/2kv2cfgn+zNoeu/DPTvA37N/hLwl8Jf+GS/CX7O/we8WfsR6Z8J/DXgjR/2afHfgHwdc+DdP fwl4L8E+D/DfvRbcU2rNpNrs7ar5HUc+37MH/Bxlo/h/4caB4Z/4KRfswa7q/iXxB4ftvjv8Q/i/ 8JfAfifUfhn4VvP2YPhj4M8X6z+zp4H+FH7JXwL0Pxr4g0L9qPxz+038X/CXhr4y67Z6dr/hX4Mf sTeG9e8WaJpGu/tVeEviL5B+3P8ABv8A4LJeFf2WP229e/aK/ax+AHxe/ZStP2AP+CsXiH4u+HPh 94c0L4TeMdR8Y+N/h1+0FZ/s6+GfB/gq9/Zp8fam/wAAPhR8EtD+EV/a+Br39pfQ/jtp3x28f/GL VviJ+1H+0f8AC3wH8O/AHir9Hvg9/wAEh/g38IfiZ4N+McX7SX7b/in4ieDfEHwnEM1t+0RP8C/h nrnwa+Afw91vwR8C/wBlPWf2bf2R/Cv7Of7LkX7MHwn1zxBrHxU8NfDLw98E9Bn1L4ha14sh8Y+I PFHw7+IfxJ+H/jHwv/gsz458X/Gz9jX/AIKKfAf4TeIdT8N+BvgV+xL+0h8Rf2oviRoFwYLmTXbH 9nzxr44+Gf7L/h7UUDQrrvjaOHRPHnx0XdPNoXwRuvD/AINvtNB+P2ja/wCHGB/I5+258Z/h/wCM dRttfbQfHep6P8YPiV4D8OfCmTw/c+BPDniC98UeH9NHjP4WfEDQrr4meJ/DXg59O1y++HGleNfh 9beIbnULfxeuqeEtI1DwlrUWv3Xh+b8tdOf9kTUvjHq3w18Lap+0Z4t+MF78VPif4k8ffDrwjr1l 8Prv4mfE7wBqmhWM174v8V6ff/DPQ7r+zdc8H+Jf2h/hdb6T498PeH/B+tXPjldMg8Kahrnhr4X3 X9a/xF/Yi+F/x21W/wDEPi7Rr7W4Lo/ZW0mePwddaFZ/8UhL4Iu4bHTde8PagYE1DwjqWpaFqIEj pd6TrWr6VJnTtQubNvONT/4JU/s662+oSaz8O7XV5NXsbvTNWk1PRvhZfvqem3/iyTx7fafqDXXg 2Vr2xvfHUsvjS7tLky29z4slk8RzRvrDteH/ADP4T+mB4CcIcN5Hw3mfFNTKcxybJMtyzGYB5hgV VwWLwmX4bDOhiJVcRh6uIWG9jBc8IYGtWlTVaFWhzxUPxnxB/Z2/SczHxe8cOK8pwWULA8feK3iz xrleY5V4s5Rw48X/AK5cY5xmuR5nnGR4ijVxkMPhsrr5Ri6mSZZmfDudUcywnNh+LMHVp4evh/57 brTPhn8LPjr4++KNzp/x++KfxF8KeKvD3hy38K6vafDU6FoL/tQ63pVl4X8f/DnUPE8fgCPVLG81 iwh/Z+h8VS+NdZ8WeHfD3hcfDvWYI/h14P0W90r5l1f9nD9jn4W+NJfhRdfEz9oz4VP8StD1vSZ7 JNR8MPpWsaV8OdK0/wAN+JPiBqVve+BvEXjDwJofiW31L4oxXHxM1vTvB3gu/wDBemfHVNK1jSfg Z4it4PFf9a3/AA7k+Fn2D+yv7M8Qf2X/AG5/wk/9m/aPAX2D/hJf+El/4TP/AISH7H/wjH2f+3P+ Ew/4qv8Atby/t/8Awkv/ABPftH9qf6VXDv8A8Elv2YpNa1TxJJ8KtHfxFrn9vf23rz+G/hI2tax/ wlVpf2Hij+1NUbwSb7UP+EksdV1Oy177XPN/bFpqN/b6h9ohvLhJPcw304/o+0nLm48UE6MaL9hj Mr/eexhF4eUo1Ma6UFSxLrV4pUpOMa0qfNOf78+D4a/ZzfTMyiWJ+sTyfBU6mSYbJqscj8XOForN FkuBo1eGq2MwuPy+rk+BjlHFNfO+IMNRw+U4yeHw+b4nLpYjGY5/26fiD+y/4n/Zzk8y2+DniHXJ Nc+K+hv8Xrjwprera5ef2T4atP8AhH9KsrHSNCguLn4d+FtD+HVn4l8OfBfT7bwOsVhD/wAK7l+H U+p6/rnwj8SR+H/7l/8AgjF/x4f8FF/+z/8AS/8A13j/AME/a/Faz/4J3fCTwjbrdaXYeIPD8Fno eg+GI5NIl8DWH2fw14ce9j8M+Hol07wtG6aHoD6xqQ0TSY1FhpP9p6gbG3txeXJk/an/AIIxf8eH /BRf/s//AEv/ANd4/wDBP2v0TwS8ZOAvGHxZo47gPN6uc4bJuAONKGYYidWjiI06+M4h8NZYegsR h5zpudOjhXek3z0qXsZNKFWEV+3eC30UfFv6NnB/jVnPidh8NSw/iXx74Lrh+quOcv46zGrLg7hz xrp5jQxuMy/LsuhgsPl+C4jyHAZbhpxrN4ehJ050qMIYah8Ff8HCP/JzX/BPT/shP7f/AP6sD/gn zX53/GL4Mftb/ELwj4A8Qfs0/GfSfhtrlp8BPCunfD7WNe8VeKtI0L4V/EXTtM1PU9Z17WvhRpXh Txb8O/2kdJ+OWj3/AIX+F+ow/GayEX7MNn4Ym+MXwd0Xxn478Q6p4eb9EP8Ag4R/5Oa/4J6f9kJ/ b/8A/Vgf8E+awPhh/wAk1+Hn/YjeEv8A0wafX9FfTAzWvk30efBbHYejg69SHiXxpH2WOwtLGYap GWU4duFWhVThVpTsoYjDz5sPjcNKtl+Po4rLsXjMHiPA49xE8NisJVhGlNptctanGrTa9mnaUJJq UXa04O8KtNzo1o1KFSrSn8Oahon/AAUI8HeG/jFqXir9ob9mZob/AFbwZ8J/2fbHXNEufAurPpOo /Fbw/wCGPD/xS8f/ABmuPC2ueEdK/aZ+KvhHxdqvhL/hAtE/Zq8dfBJPjbp3wi1DwV4Kbw1f+N/h x4x8n8SeBv29/id8Afhz4c8J/txfBLwn+2ivxt+PXxT1vWvAlzoGvfCK28F/D3TPiv8ACS8+BvgL wY3w6t9Y8Z/D34d/ETxh8H/CPxLvfjDoHxB8W/Czx9fax4m1bXvFXjbwn8OfCt9rePL39hTx78W7 zxr8QPHHiz4efGH4z/8ACnvgV41+H3ii7fV/F/iHwvrfxp+GWu/BH4I+PvA2vaX8RtW+AvhP9pLS bKbVtT/ZmnHwa1H40fA34jfHTxj8evhLd+I/hf458R/BHz2Txf8A8Et/j98IvHfxS8ffErVviv8A Aa00n9oz4t/Ei++MHgf4g6T4S1SX4s+PvC/hex+Jt9c+JPhf4U8Sy/EL4dQ6BP8Asr/sS+NPDGoW 3xFg8F+GPid8D/glqXjPxF8L/Gtv4L/gLAwxcKWDxj4bqubzPBzxGJwnhhgcZSpVa2TSwOEyqjRc pZVmeDx+NhiZ0aMsXS/txxp4nEQg6+Ip4P5SkqqjSqfUZX+sUnOpTyClVjGUsK6VPDxjd4fEU6tV TcYOpH637tSolzzjS1vhv8D/APgsNpvhfwz4O8VftPfs+eGo/CXwosPBFp4u0j+3PjJrfiPxzNqP w7+H8/xH8YW3xJ+CHhzxHrX/AAh3we0nxv8AFbw/olz8SZtY8dftZanLqPxF8aXfwA8S2Hwg+Gnn X/BWbxPP4R+DXjbSvGuo2fiHxx4g/ZV8W+HZz4Q8P3ejWniHxG3hbx8viXX9D8K6h4i8Tah4e8Ka aq6h4kvbXUfFXiKbw54fg+yXGva9qSW0mp/rF8Bvi38Evit4Sv7f4DfE3Sfi14R+F2raf8LdQ8W6 L4z1b4mWb67pHgvwj4kSxm+J2ralr83xF1aLw14r8N3OveK/+Eo8U3l1rt5qNj4i1yfxdp/iK1tP zE/4KxaHpP8Awhfxv8SHT7dteH7HfxK0NNUdC93DpB0n4j38thbO5b7Nb3N4Iri9S3EX26S0sDeG f+zrEW/9QfQdzfNsz+kVicNWynJsjxFDw88Rqs4Yfh/D5PilDFZPSq1KmJp04PF1qs6X73DUcTiq mHoTr88Oago0pdmQ4qrXz6jCvhaGGcFVlyUcHTwlRup7OSdW0XUad1NRlOSipNQtFxt/dB8Avgfe fDCHxN44+IHiC2+IXx/+Ksumal8XviVFYy6fZXjaSL9vDXw88BaVdXF5c+E/g78NYtX1XTfh54PN 7dTxNqWv+MvE9/r/AMRPGvjfxV4g+iKKK/qM/cgooooAKKKKAPyg/aC8HftD/HiD/gpX4O+JX/BP H9mD45aR8Kfg/b2v/BNTxJ8brT4S/E/wr+1ZqPjT4NeBfit4q+CnxV+Hni/xUdR8D+H/AA1+2h8E /hzL4j1XxR4h+EvhX4gadYfCbWLDT9J1f4LxfFTWuA/ZssP2wv2ivjf4n8Jf8FKf+CVf7MGjeCdU /Zg+C2rv+1PbeI/gZ8Q4Nf8AiZqv7NXg/wAH/Gb9k/Wfg1qPiP4xfES98P8Agz4iftRf8FCPA/hr 4iXfjNPh7N8GvFXiz4eWuk+J7b4qeJ/iD8T/ANnqKAP5YtB+Evx58KfD39oLVPD3/BqN+xAbnxj4 g/Z28B+HPghZfEr/AIJufC/UfiD8GvEvwzs/iZ8f9N+KHi/RNL+J3gPx74f+A/7YfwZ8HXfgGTWL HwPP8WfCvj74N+OovhJ4E8bfBPxfcah9f/8ABMTw7+1V8IfiZ8fNB8Uf8EWv2YP2BvhT8QP2n00b wL8Rv2edT/ZR+FXirXP2R7D4e/tGeJ/hd4s/aD+GvwF+IHxhtvG/xg+F/jbwz8Mvhl4httB8e2mi ajqP7V+p+KPAXhrRfC3wg8e3/jH93qKACuf8WeLPC3gLwr4l8deOvEvh/wAF+CfBfh/WfFnjHxj4 s1nTvDnhXwn4V8Oadc6x4h8S+JfEOsXNnpGheH9C0izu9U1nWdUu7XTtL061ub6+uYLaCWVegrx/ 9oX4KeFv2lPgF8cP2dPHV/4g0nwT8fvg/wDEv4KeMdU8J3WnWPirTfCvxU8F614F8Q6h4avtY0rX dIs/EFnpGu3dxo11qmh6zp1vqMdtNfaVqNsktpMAegaN4s8LeI9R8WaP4e8S+H9d1fwF4gtvCfjr S9G1nTtU1HwX4qvPCvhrx1aeGvFljY3M9z4c8QXXgnxp4O8Y22jaxFZ6jP4V8WeGvEMVs2ka7pd3 ddBX4A/AL/g23/4J9/s3f8Lq034b+M/2v4fAvxn/AOFj+H5PhPqX7Svif/hVnw9+EXx1/sbRP2kP gV4N8G6PpmjWWu/D/wDaK+GXhP4f/CX4l+Jfi9J8UvjZp3hz4WfCfx58MPi38Ovj18MvBHxh0T2D 9pL/AIIX/sj/ALUvgv46+EPiR8R/2n47n9o/xB8fvE3xW8a6f8VtE1vxpq+o/H74+/sY/HK4ttKv viJ4D8daR4Z8P/CXSP2Bv2a/gB8FPCfh/RNO8K+DfgF4RuvDmo6N4i8bX0fxBtAD9nq+XP2lPgz4 q8aR+Evi98F7jSdE/aT+CU2p6r8L9T1i5m07w9458P6z9g/4WB8BfiNqFnbXd2vwz+LunaVp9peX gstWPgTx7onw++LmnaHreufDrS9Jvv5hfjj+y5/wQr1H9p/9rr9i74o/HP8Aaf8A2Xfjj4Q8P/FD w1q3iSD45+EBpVj8Pf2jPD/7G/xW+JNz+y98PD/wt7Tv2W/g/wDs3fsX2HwX/Y28XeLIPgR+zn8M 4/8Agmjo37QPgjxtrPxq+B37L3x4+KnwC8g+G/wi/wCDd/8Aai+EXwh8S2H7b/7X/wAJtT+Nnw/+ GHxS8Y+Nv2ofEWp+IvE+p+GP2cPjZ8QPiT8U9d/ap8c/tk/Av44fs26N8AP2gf27P2irW5/aB0zV dZtP+Cff7Vn/AAUE+DvhDwn8FNP8WfG3wB460PXgD+rD9mn9vj9mf9qrxL4g+G/w18by2nxp8CaT d3vxP+CPi3R9V8OfEb4caroGtW/hTx74Z1q1vrRdC13V/hl43uYfA/xCuPA2ueK9E8MeJ7rTLG+1 ZU13QptS+zK/KH4ifs4/Cb9if9pW7/b5+EXgFM/E+bxD4I/ao8H6ffeIfEmvyaD8VfGHhzxLrPxo +BXgy+1PVU0fxbB8R9F0DxD8cfhn8LNH0eX466Hc3/jqTRfF/wAZPAfg/RvGX6EeLfjb8MfB/hLx N4xu/Fen65YeFvD2seJbvSfBj/8ACa+LNUstE0641O4svDPhLwx/aniHxPrl3BbPDpOhaHp99qur XrwWVhaz3M8cbdNLBYytD2lHCYmrT1/eUsPVqQ0396MHHTrqY4/M8kwuIjRjmNGhejheanj8ThKG I+syw1F4tRpqrrR+tSqrCt/vJYZ0ZVFGpKUV5n+058ZvFHgHS/Cvww+D1tpWtftJfHS91bwp8GNI 1i3mv/D/AIY/sywS78afGz4h2NpPa3f/AAqr4M6Rd2uv+JkW80s+LfEl/wCCPhLo+s6d4x+JvhV5 PkT9vH4NeFvgF/wRp/4KJfDrwxdapqy2v7BX7buueJ/GHiS4hvfF3xE8f+LPgV8UPEHjn4jeNdSg gtIdS8YeO/Fepan4h1y4trWzsI73UDY6Pp+m6Paadptpxfwc+O3iK/8AH3xJ8c+EPhlc/tK/tzfE v+zvD/jDwV4X8U6ZY/AX9iX4aaRNdat8Pv2ePi1+0XDa+JPBPhTxH4at9abxb8aPD/w3sfit8avH XxT8Tal4i0r4aXXwi0j4eN4P8z/4KafsoeKfG3/BNz/goP8AFX9sH4ny/G/xv4V/Yf8A2sfGPgb4 UeFrG+8DfsufCLxVoHwF8fax4a17wt8MjqOo6v8AE3x34U1W00/VdF+KHxx8Q+N9U0PxRpkHi/4W eGvg9cznR7bnaabTTTTs01ZprdNdzVNNJppppNNapp6pprRprZn5yWd94T/bL+C3xP8Ah74D1XxD aeELvUPDEum/FC/8Iz6j8HfiZPpWu6V4nuvBr6Vfap4euPjj8D/FC+GrfwT8c9A0S90bwX8VvhT4 08T/AA80D4kW95rGs6l4b/N/wB8MoNE+K+p/BDwB/wAFJP2vfBV1o37R0ekfEz4L/DD9lr41Wlp4 cuNH8N/CDW/h58KP2dLT4p+D/i38OP2ff2QvgV8R7tfF2ua34B8I+Jvgsf2av2i/gT8EP2iviJ4k 8Da58HPH/jz9tPDXiLT9F0+SznguSTctKgtooDEsRhgiVAHniKlTEflC7Qu3B6geVah8I/gLqHji 4+Jg8J+KdJ+IF58R7P4p3/jDwv448deD9f1PxNbeDvhh4CutL1XUfCnjbRp9U+HHiLwv8FfhNZeN vg7qDXPwi8fXvw98K67428D+INf0m21Nf+YKnm/FGS8T+ImCoZDxXHg3OquKzHIMHluT+H3FWHnx HUwuU4KnmOc0uOOG8xpYqg6OB+tYfE5b/ZeMyXOMNgc0yeFDF4anVpf6y8W8DZxnOY0Mwp4bC4vM aeJhTxWOdXO8phUy5TrVZUsAspzanUovnq+ynSxU8XTxeEnWw2LnUpVJRl+f/wAJvib4MPxXv/22 /HX/AAUV8X/FX9nmXwh+0n8S/AX7P+h/Cb4+fDX/AIQTw3a+G/DPxUvPil8XPh/Y+N9X1zWvCHwn /Zef4c+FvBa+NfgX4G+FHif/AIWX8Gfjh4P8PS/tDftMaV49+OPwn8KP2J/+Fb6b410r4D/8F2/7 P8Ka7+zj8HtBt/HXiDSv+Ew03wn4B8D+E/2j/D1nqPwb+NGn/tJ+EvA1t4Q8K2vwx/bfvPDPwp0u +8VaL+z54Tsde8e6ppcfxa+D3ww+P/hv9dvEX7BP7B/iT4LaN+znJ8DNR8N/A3SPKlu/hh8OPiD8 UfhP4T8b6lBB4Mt7fxF8W9P+GHxI8If8Lq8X2/8Awr3wddW/jP4uyeN/FkGpaLHq0Ospql3qF5dm lfsCf8E/NI/4Svy/2atB1P8A4Tjwh8Avh74s/wCEnvvEvjH+2vAP7Mn/AAr3/hTvge5/4SzxdrWz whpP/Cp/hx/wl3hq38nRfix/wh2i/wDC27Lxx9mO/wC7ynjNZBg8+hkK8ZMunnH9kZI8oxvhB9Hb P+GavCfCfFMMx4Sp4vJsdgqGWRzTB5Zm/EWYY+OByzCwxufUsLhcVjsZl+b4nFZJ8JifC/i7G1cE 8bkORV1hfrWM+tUeJ+OcFmMc0zPLfq+ZypYujiZ4h4eriMLgaFF1sTUdHBSqVaVGlXwsKeM9v+E/ wJ8WfBHQPir/AMJL+0F8X/jba+NfF8es+GtD+JmpabrGi/CjwnpN6PD3gfwZ4H1O9stR+I+o/wBn fDjTvA+g+O/EXxC+InjfUviT4+8M678ZL2LQ/HPxM+IU+u/o3/wRi/48P+Ci/wD2f/pf/rvH/gn7 XyZrfivT9S0u6soIb1JZvJ2tLHAsY8u4ilbcUuJGGVjIGEPzEA4GSPrP/gjF/wAeH/BRf/s//S// AF3j/wAE/a/qL9mXT4n/AOIhcdYvi7CPCZzmHDedYqcPqGAyyFTD08Z4b4ChVp4LK6GGwVGPLgnT bo0KbqVKdSrVUqs51J/L/Sayv+x/B3I8CqFXD06fiLgp06darWr1OWpw7xHNydWvUq1Zp1HO3PUl ypcsbRjFL84P+DkLx34I+Hf7Qv8AwTu174geMvCvgXQ7j4Nft8aRb6z4x8Q6R4Z0mfVrrxv+wLeW 2mQ6jrd5ZWcuo3Fnp2oXUFkkzXMttY3k8cTRWs7J+Teg/wDBUv4TeHtD0bQLL45fsry2eh6Vp2j2 kt18TPDT3MltplnDZQPcPF8QoInneKBGmaKGGNpCxSKNSEH+hRRX+6c8+4OznhDKeDOPPDLhfj/K 8kzXH5xln+sFXHp4TGZjCNKvUpQwtSlFSdKKp3bd49E9T/OLM8hwebVFPFrnUbcsXFNRaVrrVO7W 5/mp6D+0d/wTn8K67ovijwv8Ov8Aglv4b8S+G9W07XvDviLQfCPwL0fXdB13R7yHUNJ1rRdW0/XL e/0vVtLv7e3vtO1GxuILyyvIIbm2mimiR11rL9q39gTTdR8D6vp3hT/gmbYat8Mfsn/CttUstC+C 9rqPw9+weKNU8cWH/CD3sHiKO58J/YvGut614wtP7BlsPs3ijV9U8QQ7NWv7u7l/0lqK5J/8QYqN up4A8EVG48rc814lk3Hlqw5W5Zi7x5K1aNtuWrVjtUknyPhXAS1lOtJ2trOo9Emra1NrSkrdpSW0 nf8Az1tF/wCConwT8N2c2n+Hfir+x1oNhcatr2vXFjovjnwlpdnPrvirXdR8UeKNamtrH4gQQy6t 4k8S6xq3iLXtRdGvNY13VNR1bUJri/vbm4l+Rf21P21Pgt8cPgt8bSfjb8BL/wAUX/wE+JPhDQdB 8IfEnwpdXmsXl14U8VHS9P0/S/8AhKtW1HUNY1DUdW+x2lpZ75buV7a3t7Zp2/ef6cdFelwvnHhf wLmeLz3gjwN4G4W4gxWWZnlTzvLK+bLHU8Lm1CWHxsVOvXqxl7aMrz5otyaV3uGG4Uy3CV44ihHk qxd+dRXM7tOSbbd+a2r367sKKKK+EPpwoorwD9rH4Gf8NQfssftLfs0f8JR/wg//AA0R8APjJ8C/ +E1/sT/hJv8AhD/+Ft/DrxH4A/4Sn/hHP7X8P/8ACQf8I/8A8JB/a39if29on9q/ZPsH9r6b5/2y EA9/or+YLwH/AMEyvEf/AAT5/wCGmtT+PP8AwcI/tAeFfh/8c/8AhaHizTbn49+PPhZ8PfGOifCz 4jf8KE/Zn+LHxO+KHx2+Jfjm9+IHxN/aA+GXw/sv2Svhb+zL+1B4a134P+HP2Wvjs/gPUIPhZ4z+ H/xv8Zfs5/Efv/2vfgxrHj6+1f4M6Z/wXD/aA+Dfxg/bc+IH7aWmfCTx38PtB8d6n8OvhJrHhv8A bJ/4J/eCPD/wt8H6/wDAr4hfDv4ZfA//AIZhsvgdoX7A9rp/xS+JHhvx38bv2p/2zvjEmn67F8YP jJ4l+B3i8A/o+or+YL49fswfY9Hmv/C//BxP+0B8LJfjr8P/AIwXvwE13UPiV/ws34RfBX4WfGfw Jd/FL4MfF3TNT8MfFfwprGtfD/wj/wAE2P2Df2pfAOhftF/tafGb4i+HPHvxsh+KX7eXwm+Inwt/ a6/4SPUPHPP/ABZ/ZY8VaJoniPSZv+DkD4wa/wDGTTvD/wAKvFPxU8M6l4l1Hxj4q8T6J8Ov2uPj doP7TngD4S/syfsU/tB/s7fF7w34f/aQ/bd8V/Cv9mLwHpfwcm1j9rj4Maj8IZP+CdfwT+O+ueG/ iZB8GvDQB/U7RX8oXxv/AOCZmj6h4c+M3gv4Y/8ABaH/AIZAsv8AgpR8QPi34u+JP7Pvx0+CfgTw V/wkOsf8FJ/in+0Lr3wR8O+Fv2dte+I/7MPxgtP2gPHnwf8AFP7Rn7L+twftVp8evHfxm/4V5pF9 4T+HXwg+Jv7D37NVn+zR0H7Onwk8K6J8Zf2YPFcf/BzP4f8Ajd8FtQ8Qfs3/AAR8K/CnS/2jNO8Q +NP2j/i1+ztB4D+Ifxd+FXhb4qeKv21PixofjPxB+1B+1H8Rfh38Uvjv4cuPhJ8Sv2h/DvwC8c+A P2GvhT8Wfhp+zT4uPhvxcAf1O0V+QPiP4tfsnaR+2T4/+O2l/tn/AA/8DfHr4gfsAWep/CnxPqVt 8SZf2KNX/ZO1ax8a/Gf9n/4pfHHxHL8TdI/Zy+PnxA+GnjP4QftxfHD4Uah8NfjL+z58SdX/AGRP FH7RsUmhan4F+GmtfHvSPzg8f/s8/Bv9o/w/8d/2c/CP/BfrxAnw28feIPFP/BOr46fBP44/FOfx j8ZdZ+MujfswaX+xJ+zh8J9fn8XfH34XeMfBPxguv2sP2bv2j/2tfHelfB/wH8K4P+CoEHjvxv8A Dj4i6R8UPgTpOmeItVAP6naK/KD/AIJ0fsH+Fv2a/i1+11+1f4F+NXwf+Mvgn9vjxBp/xh8Haz8I fhHp3gmDUvCvi39of9sH9qjw94y8Z/FfR/i18SdI/aR8QajpH7ZNp8OPCnxY0vRvAGnXHwa+Efwr 02x0S8treK5h/V+gDwD4pfsnfss/HHR9d8O/Gv8AZp+AHxg8P+KPiBpnxY8S6F8Uvg38OviBo/iL 4p6J4E0/4W6N8S9d0zxZ4c1ey1f4gaR8MtI0r4daZ4y1CC48R2HgTTNP8I2upReH7K20+Pz/AEz/ AIJ7fsC6JrHwt8RaN+w9+yBpHiD4Hf2f/wAKU13TP2afgxYax8H/AOyPHeu/FLSv+FW6na+Cor34 f/2Z8TfFHiX4i6f/AMInPpH2Lx34i13xdbeX4g1fUNQuPr+igD+cv9vXxV8ZvDf7bt1P4w+Gv7SN l8HxH4Xtvhd8W/gV4v8AENjoUNje+BdBsfE9t4z0vQPAnxE1bSRN4w1LxF4e1O/0CDQtY1nQZraw tbe4aJ76X5XX48eFtH0fxb4h+Hvg/wCJWj698WNEn8XjT/gL8NPG3wx+K+hWmmy+DfL+Ht5q+ga9 8QbzwwPEGvazO+qeC/jZ4W0LVfFIh8ZeKNLMhi8A+Jpf615oIbiNoriGKeJvvRTRpLG3+8jhlP4i sZvCvhh0u438N6C0eoJJFfxto+nsl7FNG8Usd2htytyksUkkciTB1eN3RgVYg/r2G8VatLDZLQnl aj/Y+S5TkbVHEtxxeGynGUcZCcJ1oVKuW1sRVw9GpXlgpK+Ig6y0m6cf56xvgPQr47iXFU89c/8A WLibP+KIyxOCSnl2Nz/LsRltSlOnhq1GhnNDCUMViaOGhmUJL6pVWGkuakq8vxg/Yd/au8a/A34D WaftQfs7ftbeCPDWseKdX1TwT4z074TfFH9o6DR/AzaT4dis/wDhZMXwn8P+LfiN4P1WbxGvii7n n1X4XeH/AAb4c8MjSBqetwLY397Xdft9ftZ/sxftE/8ABLb/AIKcWnwN+Pvwl+KOr6X+wD+2Wmue GfB/jrw9qvjLw1cRfs5fESSex8WeCo74eLfCep2yOj3Wl+JNG0vUbVXRri1iDrn6M0+7uv2GtV07 w5rNzcXX7E+sXEWm+E/E1/NJcTfshazd3Nta6R4H8UX8zSTP+zBq805sfBfim/fb+z1frZ+D9eu2 +DOoeHb34ReOf8FnfgF8DPij/wAE1/2+vGnxK+DXws8f+M/h3+w/+1Z4q+H/AIv8ZeAPCviTxV4G 8S+GfgT8QNb8Pa94Q8RavpV3rHhvV9G1a2h1DTtQ0a9s7m1uk8yKRSzZ/PuJs8q8S5/m2f1sPTwt XNsbWxtTD0pTqQpTqu7SnP3ptv3pzajzTcmowTUV+u8E8L0eCuE+H+E8PjK+PoZBluHy2jjMRCnS q16eHjyxlKnS/d04pe5TpxcuSnGEXOck5y/lZ/ag/aK8Y/BefXdXtdeljtrv4jan4Yt9S8ZfEvVP ht8K/BsDP4g1GHVPiH4/j0zxPH4F8MzR6KvhTw9fJ4Z1dNV+IHiHwP4NW3sV8SDVdO+aPhz/AMFI 9H+I3iHwZ4Mt7b9pzwz458bahrCW3grxB4S8T3viHw14Y0LxP4j+H2qfEDx5D4L1nxdY+BvB9h8U /C2qfDHVZPEt/p3iHw/4nNrqfiTw9o/ga4HjBav7SFv+0N4F8fePvAPwM8HfEvUvACQ/CLSvBfiP wfrnwN1XV/BL6B8a/Gz/AB1hkvf2gvGUes6x4j1z4Of8ItpXg648QaV4z8PR65BA8k2jT/2tfyfP 2uXv7eD/AAWv9P8AC+k/HGH4s2vxR8eXtrrviWT9iI6rqXw7v/Cfxfg+EWk2kOkanL4Dj0/RfEun fBW8+MUl/o1h4uludf8AGS/DzU9W0aG1tdF/ong/hThGPCvBNXDeH2X4rDQ4G4axNeEvCXJMwjja tLBYCnWUMx58PUnjcfRp1cVD95Xo+yxNOr7eVeEsPL/pKzXiviPA51hJZbw9xxPLMBw7hsZj8owP glDifKsfi8uzOhgsbgsp4pec5BisVj81wWFxOOy6apTwU8tzDBYz2kMwo1cpfveif8FLtD8e+Ffj r4o+E+tfEvx5ZfAf4Pav8WvEOrf8JZZ6R4Vu9uneKda8HeEP7Vi8S6x4gtPEHjXw/wCFrjxL5cfg +/8A+EH065/4R/4ixeFfidpusfDvT/L/AAf/AMFhPB3irVda8NT23x80Lx5D8UdJ+FHhn4V6tqul 6X8Udd8Ta3c+FdD0zT9T8Oa/420LSvDOoXHizUfHOl3v2nxHf+HvCmn/AA8kuPH/AIn8H+JfHfw8 8HeJPVvHWg/tPa7J41m8J+OdQ8IaHqXxR+D0vgSx0bQ/hZH4/wDDPge28Z2/gH472WsXni3T/iF4 G17wfqPgazk+Onwy1NYbH4mW+ta1c+EvEWkxRaNaeCNR8u8X+M/27rH4zRRfD34Tf298KNM/4W1q XiC+8c6l8HNH07xZ9hgjvPhf4M+G+leHfiZd+N/C39r23gqy8PW3xM+IGsa5u8VfGbxZ4y8V/Cbw 94V8H+FfAvh/6THcA5HhnhW+DcgVqscPiXg/Brh3H0cYsVmOOwtDE4alQxWIxOWxw2Gp0MXip4+V aMaPs8RPD0p4r+zqPLn2K8SssnlMp47iOKji6eXZlPJfo75dn+DzmOacR59lOAzPLMLl/GWYZpwz SyzK8Ll2b5pX4gqYylDBLC5jXy/CV82/1cwP258IP2mNS+NvgyDx74P8RfFuw8O32oX9tpE/jPT/ ABz4Ludf0qGRJtF8XaBa+IksZdZ8H+L9DudN8S+F9fsPOtrvStUhtNQXTPEVhrmhaT/SX/wQuuJ7 r4fft13V1NLc3Nz+2z4NnuLieR5p555v+Cbv/BPOSaaaaQtJLLLIzPJI7M7uxZiWJNfyc/AbUf2r pv8AhDtO+PPhz4f2Gn2/we8Paj4t8QaRq633iq9+LN7/AGPpVz4cNroyWvhh/wCy4PD/AIq8aeON X0vS9J8NR6j8SfBngH4fp4h0/wCHPibx54x/rB/4ITf8k3/bk/7PU8E/+u2v+CeVfjvjXw/w7ldX w8xuUcL5TkGNxOVcXUMdWwXC2D4YxWL5K3BlR+2wlCDrwpe0k2qNWvVjCopcjaSk/wCZvp7YyWZf R78NcwxOW4vAZjU8QcupY+eYcLVeDsZisRDhDiGdWvLIcTisdicvpzqTcfq9XGYhU6sKsadSdOMJ y/dCiiivxc/yACiiigAooooAKKKKACvxh+Jv/BdD9kf4Q+OB4L8bfDj9p9Y5fjB4f+ANh4i8J/Cn RPiPBrnxl8WfttftWfsQeGPh74a8DfDnx54r+MnijxB4h8SfsR/tOfGrRofDvwx1SDUfg18OLbSr SeX9oPx78NfgL4x/Z6igD+YL9rj/AILEf8EwPEUnwX+Kmi/AL9oD9tv4wfE/4f8A7Pnxu+Cfg/4L aF4/8d6xH8Cfh7/wVX+Cnw++F3i3wPdfDrxB4p8GfCn4gfFb9o3wt4e+KelfBrXm+F/jH44+O/2c fg5+yL+3i/wi+MGm/Av4O2Hz/wDGv9pj/g33/Z//AGcfjJ4i+AH7EP8Awtuy/wCCbP7IHwC/aB+G knwt+EPxN+Duj6Pff8FH7X9nLR/gf400L9pDWtP8P+IPhv8Atf8AiXw/4M/ZN+Iup/tTeI52/bJ8 C+BP7Q8XfBLxb47+Jvw4/aF8EeEv6/aKAP44vCH/AAUm/wCDf6f43/s6/FHx3+yh+2/+z/428R+H /hz+278I/hd8VPgV+1lB8Avh14V+DX7NXxm+F3w1/a78Kfsd/DPx18RP2Ybzw/8ABb9mH9k/wfB4 M+PvwQ+C/jjTvAngvxp8IfG3hLxZa3Pws/aC8Rfs8dB8PP2o/wDgg18FfAnjL/hnD9hn9oDTPEGt /sgfslnxP+zp+zP5Nl8bPHPw68Uax/wTg+In7Hnjm5+EXgT9qLSr3xN+1/pvxN/4KY/B/wD4UT+2 BqHm/tT2fxd+D/7Rn/Crv2grjxB8P/C9749/r9ooA/kin/bu/wCCLn7XHjSb4PeNfhp+2/a65o37 b/w9/wCCdVzF8YLP4jar8Qv2hPiF8TPgF8fv+CamifCf4o+L/H/xQ8e/tLfAT4P+Hvgt+0v8e/jP p+lftFav+yP8TPHfxMT9o/4s/CjSfip+1HoX7ZHhWfn/AI/6z/wb7/smWPxM8K+J/wBmD9oD4m/D /wDY5/4b1+E/jT4h+Cvj58TfjL4c8Bfbf2Nv+CeP7G37Q/w0s/EHin9sib4gar/wmHw//ag/Y6/4 J6+APBtvpl7/AMM+/FPw14jgvNN/Z4+H/wAMvFfxps/63dG8J+FvDmo+LNY8PeGfD+hav498QW3i zx1qmjaNp2l6j408VWfhXw14FtPEviy+sbaC58R+ILXwT4L8HeDrbWdYlvNRg8K+E/DXh6K5XSNC 0u0tegoA/lC8Q+M/+CNvxC+O37fPwt8S/wDBLP4geCP+HXH7IHwg/ag0/wCOPwa+Emu/s8f8Kz+B PgPwdoH/AAUM+FvhT4I6joWu/s4/Fr9hP9r/AMR/Fr9oD4666/ws8P6f8IfGPxM/4Vv4t1P4t/E6 4/sPU/h58PfP/hn8CP8Ag288RfCzwv8ADbwL+zx8QPCPh/wL+0B8GPhDonw9s/2svjN4K+Isf7QH /BZDw58L/gD4p+H/AIcm0j9syz8Z/Gr4f+Pf2cvA3gLxt41+JHw21z4o/sgfHH9ljTfH/jn9kH4n /tG+H9O+OkFh/W74s8J+FvHvhXxL4F8deGfD/jTwT408P6z4T8Y+DvFmjad4j8K+LPCviPTrnR/E PhrxL4e1i2vNI13w/rukXl3pes6NqlpdadqmnXVzY31tPbTyxN0FAH8wXxY/4OTf2Hv2U/2cf+Ca fxC+H37O3xA8J/s8ftbfED/hVGgWuoaV4S+HfgT9l39nH4O2vwn0rx3450zT/gdB8cvCXxG/4VX4 S+K/w9g0L4JfAObxFa6DrHh74pfAH4h+Kvg5+0P8E/G/wU0z9fv+CeP/AAUE8Cf8FG/ht8SfjD8M fh98QPh/8P8Awl8QPh74R8Jp8UtD1nwl478UaP8AED9k79mj9qC28Ra74L1nRNN/4Rn7J/w0Q3g3 TJ/D+t/EDwJ490fwlp/xY+HHxF8W/D/4geGr5ft/wn4T8LeAvCvhrwL4F8M+H/BfgnwX4f0bwn4O 8HeE9G07w54V8J+FfDmnW2j+HvDXhrw9o9tZ6RoXh/QtIs7TS9G0bS7S107S9OtbaxsbaC2giiU0 bwn4W8Oaj4s1jw94Z8P6Fq/j3xBbeLPHWqaNo2naXqPjTxVZ+FfDXgW08S+LL6xtoLnxH4gtfBPg vwd4OttZ1iW81GDwr4T8NeHorldI0LS7S1AOgooooAKKKKAKeo6fp+r6ffaTq1jZ6ppeqWdzp2pa bqNrDe6fqOn3sL215Y31ncpLbXdnd28slvc21xHJBPDI8UqPG7Kfwl/4KZ/8JB+x3/wTa/b++FGp /wBseJ/2VPGv7EH7WHgj4MeK5ftusa7+zt4s8QfAL4gaT4P+CHjm7b7Te6n8H/Eeq3Nl4W+CXjm9 eS98Ga3d6F8IfFdxdWWp+BNYP7zV8Af8FYv+UWX/AAUs/wCzAP2yP/WdfiNQB+K2t6xovhnQda8U +Jta0fw34Z8N6VqWu+IvEPiDUrTR9D0HQ9Hs5dR1fWta1bUJbfT9L0nS9Pt7i+1HUb64gs7Kzgmu bmaKGJ3D9B1TR/FWhaL4o8L63o3iTw14k0nTte8O+ItB1K11jQte0LWLOHUNJ1rRdW0+S4sNU0nV LC4t77TtRsbiezvbOeG5tppYZUdvj74m+FfAvwi+APxXtvj/APFZPCv7Nvw7l8G/EfwH8SdR1a5f 4jfCLV/A3jXSvHHgWyjm1XSPEunePr74c/Erw74Bvfg3Y6xpHjPUfH97/Y/wu8aeAviGYpB4++Gt J/ZT/Ywk+JgkTW/2xYNV8d/tM+CfFfxStNG8WX/wll+Nvxn+MfwZ8HfGbwB4r+MGk/DGz+G/xjg1 b4XeN/AmofHu1+DGk2ngj4mfsj/EX4g+Ovjp4i+DHwl/Y78S6R4x07/Ffhnw24YzjJZZji8wzyPI 69WljcuyWrjsFi8PQo4GrKhFVMZgIUc0X16jSng/rVRUsTVw1KpKOHxKxsP6A8W/pbeM3CHiVxxw xlmLynLssyDO6+BwVCrw1hc2nToUMPg6kqUscsVh44mtz4j3JPkm1Ogq1Kg6kvZft59lk9U/M/8A xNcn4b8Z+CvGX2b/AIQ/xr4Q8V/bPCfhTx7af8I34j0nXftXgbx5/bH/AAg/jO2/su6uvP8ACfjL /hHfEH/CKeIot2j+Iv7C1j+yLy8/sy98j8mvgXbfskX37R/i/wDac8OeN/2mfjP+0Xb/AA91/wCJ /hD9nX4ieFfCuqanoWk/tMeO9I0NPHn7PV3F8OvDPhr4laT52i6B+zvY/tWeEfjt8Tvgl4R+AOl+ DfB/ib4/2/7OnhjwJr+ifmb4G/Z2/wCCQqxa74V+EX7Un7YvgvQ/ip8QvEf7LfiLQfBGveB9Z0Lx 14t+Enw6+INpq3jT4davqHwh8ZzfFPVvjB4a0fUNHtrj9mXXPG3jTUbP9szwr8CIfBHgXwJ+0+/w lv8A7DLvA3hzFf2nSxeL4woVsDhcsre1wvCGOxmHo18R9YxOPo4ulDHRxsKFLLadDEZbjlQjhc0r 1a1ClOEKVGtivgqH00PHmp7eNTNsnjOjTw8+anwLTqwjOpzzrRqRWMVVQjQjCdCtyKniJuUItKMJ 1P6wXgdFLErgY6E55IH90etfdn/BGL/jw/4KL/8AZ/8Apf8A67x/4J+1+LP7Hfw7/Zp8N+BfGvxH /Zd8Vat408CfF74heL9RufEKeN/E/iDwDPefD/xh4i+GdjoPwu8LXFza/Dvwl8Pfhno3haw+DPw6 m+GPhjR9C1j4RfDP4ZWMeteM9D8OeF9fl/ab/gjF/wAeH/BRf/s//S//AF3j/wAE/a/UPon5LgeH /HXifK8BLHyo4fw2zSFX+0sG8vxscXT4p4Xo4ulWwTxGKnhnRxFKpRjCpV9tKFONStRw1Wc8NS/R c18VeLfF36OEuIuM6+FxGaZb46Lh6jPCZXDKIxwWD4Blj1Tq4SFavatDGZnjU6kpqcqfs1OFNx5I /tLRRRX+lB/O4UUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABXwB/ wVi/5RZf8FLP+zAP2yP/AFnX4jV9/wBcD8Vvhh4F+N/wu+JPwX+KGhL4o+Gfxe8A+Mfhf8RPDLaj q2kL4i8C+P8Aw7qPhTxdoTatoF/pWu6Wur6Bq2oaedR0XU9N1ayFx9p06/s7yKG4jAP5q45njBVQ uCc8g+gHYj0rgNB+F3wt8KxaLB4X+GPw68Nw+G9W07XvDsOg+CvDujxaDruj/DqH4P6TrWix6fp9 uml6tpfwlt7f4XadqNiILyy+HUEPgm2mi8NRJpi/r/8A8OYP2Cf+gJ+1Z/4sh/4KQf8A0WNH/DmD 9gn/AKAn7Vn/AIsh/wCCkH/0WNf5x4b6GHiLg6Lw+F8Tcow9CUPZzpUcFmkKc6aUlyTjGSU42lJW ldWlLuz+qs88UPo6cS5vmOfZ74FLM84zeu8TmePxGLw7r42vKMYSq13CvCMpOK5fhSsttWfkBrXw u+FviT4dQ/B/xF8Mfh1r3wlt9J0HQbf4Xa14K8O6p8OoNC8Ky6dP4X0WHwTfafP4ai0nw3No+kza DpyaYtno8ul6dJp8Nu9lbGLlPBv7OP7Onw6vPDWofD79n34H+BL/AMGat4n17wffeDfhR4F8MXnh TXfG2haZ4X8Z614audE0Oxm0LVvF3hrRNG8O+J9R0t7W81/QtI0zSdVmu7CwtbeL9qv+HMH7BP8A 0BP2rP8AxZD/AMFIP/osaP8AhzB+wT/0BP2rP/FkP/BSD/6LGu2H0QPFSnRq4en4tYKnh686tWvQ hRziNGtUxFJ0K9SrSjUUKk61FujVnOLlUpN05uUG0eYuN/owqMoL6P1JQm5SnBYymoylOPJOUorE 2k5RvGTavKOj0dl+VWiaRo3hjQNG8K+GdE0fw34Z8OaTpug+HvD2gabaaPoeg6Fo1pBYaRoui6Tp 8Vvp+l6TpdhbW9jp2nWNvBZ2VnBDbW0MUMSIv6Bf8EYv+PD/AIKL/wDZ/wDpf/rvH/gn7Xqf/DmD 9gn/AKAn7Vn/AIsh/wCCkH/0WNfYH7MX7JHwI/Y78JeMPBXwC8N+KfD+i/EDx9cfFDxrdeNviz8X vjV4p8S+Ornwd4M+H767q3jr43eO/iL43uWh8F/DzwX4bstObxCNJ07TPD1lDp9hbE3DTfrPgV9H jibwq44zPi7P+Lcu4iWP4YxuQRpYbDYyliY1cVm+UZmsRUq4huMoR/s6tGS+OVSvGV7KR4XH3iN4 c5rwDh+BfDvgCpwRgo8Y0uLsXTp16NTCYnGLJcZk9eq4QnOr9ZrUqmCi5uXJ7LCJNczuf//ZUEsD BBQABgAIAAAAIQBEzrz1ywIAANgHAAAUAAAAcHB0L21lZGlhL2ltYWdlMS53bWbMVE1PE1EUPXem oMiHC4k2akwgDeii/gdLYvwF7v0PLlyyswQiBhKNCIIYiDRiqDHxo8QCLS2K7aKFNoFVVUw0qFUX GkTHc2c6TUgKLTsmOXPum3vefffdue/lU4kh4B660SUFXII+G5cFDYBZMAEPLtrf6vhuNLqpVKvJ uIIJ+uiXZpvPi9dmQ8RWNBg6TbViWJYFhsIZHOG7o/4omd8sDvhU+naI37c1wrUQX7qOX6A5Ycuo B02EPlpoL3kEqvd6CtzDQ2bo6HRt6DplnWHri8ywhR6fWUftCLGIgCjUHtnTV87rqSbv5CWlqLvn h1J+L5ifVrDSjit9K6+mGymtZpb34Kzu7glopcZnHsYP3MI/DOGU3MBZGUCbBGEhiGbptX371X3B fRRYl0VM4Rn/+ivMcDyDDB5BfW68WnUv0YsEruM9BlBEPz7hDpLEKvNWnxuvVl2HTOOkhLnnCcab wi+McjyKRhmH+tx41XQ7/4D22N696TSwhyrtTXeVn7jNat/FaenHORlEu/TwCPSgRfqgvv3qvmIc 79gzCYTwHJOIIsxxGFlMQ31uvFp1EfSx2kF8wCC+4yY+s1OWiBxzU58br1Zdpzxmpz3hnicZL4Tf GON4DE3yAOpz41XTVa++80d2vwOcG0bPzHFPnD0wzJ7VO6DVuMr6qXXM2KTlodUplrVT3yXDuCCu PmBbqg+Iq6+eIQPzUb1fnHPqF/d8in2P+sw2npsoqx/FN9Z9i9woighOyDw5ScSwjRjP6htyhmNF iv4V8hqR47wc56cYJ0eFYo0dskJOERl2SAabWCbHaCmS9M+TI0T0QOXi1AvlnLKYwwZRxGv8ITeJ YhZeWSAvEXH8RZynaZmc5ViRpn+VvE7kOS/P+WnGyVOhWGcFVslpIsu7J8u76y05TkuxRP8CeZaY O1C5VO8752S4fap9DfwHAAD//wMAUEsDBBQABgAIAAAAIQABcj94yAAAAEcBAAARAAAAcHB0L3Zp ZXdQcm9wcy54bWyMkLtuwzAMRfcC/QeBeyMnQ1oYlrMEnQuk/QBBpm0BFiWQyuvvS7T10C0bCeIe HN7ucEuLuSBLzORgu2nAIIU8RJocfH2+v7yBkepp8EsmdHBHgUP//NSV9hLx+sFGASStdzDXWlpr JcyYvGxyQdLbmDn5qitPdmB/VXBa7K5p9jb5SPCX50fyeRxjwGMO54RUfyGMi68qL3MsstLKI7TC KIr5Sf9T6vW5ieNwKj6orgk3B697VQYT7uto+86uHfTfAAAA//8DAFBLAwQUAAYACAAAACEA2P2N j6wAAAC2AAAAEwAAAHBwdC90YWJsZVN0eWxlcy54bWwMzEkOgjAYQOG9iXdo/n0tQ1EkFMIgK3fq ASqUIelAaKMS491l+fKSL80/SqKXWOxkNAP/4AESujXdpAcGj3uDY0DWcd1xabRgsAoLebbfpTxx T3lzqxRX69CmaJtwBqNzc0KIbUehuD2YWejt9WZR3G25DKRb+HvTlSSB5x2J4pMG1ImewTeqgiCi tMCny+WIaUgDXHo0xnFU1tW5qf0qLH5Asj8AAAD//wMAUEsDBBQABgAIAAAAIQDCMWTIowEAAJoD AAARAAAAcHB0L3ByZXNQcm9wcy54bWysktFu2yAUhu8r7R0s7gnYuCS24lQ2DlKlVurF9gDMxgmS MQhI22nau4+kSdeovujFuAJ9OoeP87O+e9Vj8iydV2aqQLrAIJFTZ3o17Srw4zuHK5D4IKZejGaS FfglPbjbfLtZ29I66eUURIilTy6JjSZfigrsQ7AlQr7bSy38wlg5RTYYp0WIR7dDvRMv8QI9ogxj irRQEzjXu6/Um2FQnWxNd9BR4K2Jk+PJxO+V9Zdu9ivdPr7jSmkTH9mN7tEdNmtRerf7yUaXPIux ApwXBSEAfQKUMsb5DMCYMUpnAOeUFsUsOKIZQCkhGM+Ao9MsoBTjWV3OCWFsphXnOK4jQP+GYEv5 Gh58OA4m7pKDUxX4vV1Sti3yGlJMGMzTPINNsW0gbVOyxDjFdbb8A2JNmpe98p1w/b0WO7ntVWhF EOfkI/6UlladM94MYdEZjd5iR9a8SGeNOiWf4vP3OcVyEY5y144tSWtMsxoui1UNc5IVsG7aFjZN vbqlNMO3KX53lIM4jOHk2Fr1H/Wy7EowTvYyz7j9+A2f3OYvAAAA//8DAFBLAwQUAAYACAAAACEA wAs/bEgCAAC4BAAAEAAIAWRvY1Byb3BzL2FwcC54bWwgogQBKKAAAQAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAACkVN9v0zAQfkfif7DyNCS2tKUgqFxPo9U0pJVWNBvPxrmk1hxf5PPalb+eS7J0 HUw8QJ7uV+7u++7O8vyhcmILgSz6aTI8GyQCvMHc+nKa3GSXpx8TQVH7XDv0ME32QMm5ev1KrgLW EKIFEpzC0zTZxFhP0pTMBipNZ+z27CkwVDqyGsoUi8IamKO5r8DHdDQYfEjhIYLPIT+tDwmTLuNk G/81aY6m6Y9us33NDSuZYdQusxWogUyfFPkdQ07q/SeZdpK8qGtnjY5Mh1pYE5CwiGLZNi5WuIOw QuujTI8DmQwgRtT+dtkCVkt/SiYAeLHe4E6cjCfv3sj0hUC50kGXQdcbUqMhhzypcu1sDqTY+ijJ rxg7QyfIK5vn4B+9jO2ZLheLmbM1NaB7Ua6NdjBjdlShHQGnPhjkFehm8ittAym5jZMtmIhBkP3J sx8n4ocmaDidJlsdrPaRuW3COqWVXU0xqIyXgHOzr9Nb8TjsWLbjBiLHsvDXwC5Xi1ZkNjqg/y/R 1O1gcu3nBHQllgWPJL7Ax+iYj7a1jo2uyzkU+t5FMQeypT/u80DKt8XsIhO8qRENOpEBRZFhjQ7L vThZehC8TDsdcvEZI6P1YO7eimyH4ktV84zaK5qD03txDSUJrlVbEyHnTTsU6Qht58gAf4M0Q07k 92pmyaBY7ylCxZz2Znlt/R3d1BnOdYR+YZ4b5XqjA+R81b3/ySCveFeCa5LMNtqXkPcxfzqa07vt HiI1HJ8N+GuvrLc1x9M/OeoXAAAA//8DAFBLAwQUAAYACAAAACEAg1sBPKMBAAAOAwAAEQAIAWRv Y1Byb3BzL2NvcmUueG1sIKIEASigAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAnFJda9ww EHwv9D8semohtuw7Wlrjc0hyHBRyNKQuLX0T0sYW0ReSGsf/vrLvzr3Q0oc+rnZmNDu79eWzVvCE PkhrNqTMCwJouBXSdBvytd1lHwiEyIxgyhrckBEDuWxev6q5q7j1eOetQx8lBkhKJlTcbUgfo6so DbxHzUKeECY1H6zXLKbSd9Qx/sg6pKuieE81RiZYZHQSzNyiSI6Sgi+S7qdXs4DgFBVqNDHQMi/p b2xEr8NfCXPnDKllHF2a6Wj3XFvwQ3NBPwe5AIdhyIf1bCP5L+n3/e2XedRMmikrjqSpBa+ijAqb +/3NVQspp2i5VdBiiNBaZ5XtRnjz2SDsrB+YF3BtYyIY5I8X0A4WPmnHpJ9mpFtUbIRb7ALAFp3k EcXbmi6fTN9xjyxa3+wl7xkquMrhnmmmensBd32+zWf8CTUtULEQ92nXDxLF9fgv4p/gie/xSU6H 05Q1PS+TmznrgyUUkNKrDlmfOt/WN9t2R5pVUa6z4l1WFu2qrIqP1br8Mfl8wZ/SPDzoo9v/VjwJ NLPjlxfc/AIAAP//AwBQSwECLQAUAAYACAAAACEAlpNjoPgBAAARDgAAEwAAAAAAAAAAAAAAAAAA AAAAW0NvbnRlbnRfVHlwZXNdLnhtbFBLAQItABQABgAIAAAAIQBo+HShBQEAAOICAAALAAAAAAAA AAAAAAAAADEEAABfcmVscy8ucmVsc1BLAQItABQABgAIAAAAIQBDGtsA+AAAANwCAAAgAAAAAAAA AAAAAAAAAGcHAABwcHQvc2xpZGVzL19yZWxzL3NsaWRlMS54bWwucmVsc1BLAQItABQABgAIAAAA IQA/LRmeIgEAAGcEAAAfAAAAAAAAAAAAAAAAAJ0IAABwcHQvX3JlbHMvcHJlc2VudGF0aW9uLnht bC5yZWxzUEsBAi0AFAAGAAgAAAAhAP3ShKqUAgAACg4AABQAAAAAAAAAAAAAAAAABAsAAHBwdC9w cmVzZW50YXRpb24ueG1sUEsBAi0AFAAGAAgAAAAhALF9K9jUHAAAsPYAABUAAAAAAAAAAAAAAAAA yg0AAHBwdC9zbGlkZXMvc2xpZGUxLnhtbFBLAQItABQABgAIAAAAIQDV0ZLxvgAAADcBAAAsAAAA AAAAAAAAAAAAANEqAABwcHQvc2xpZGVMYXlvdXRzL19yZWxzL3NsaWRlTGF5b3V0OC54bWwucmVs c1BLAQItABQABgAIAAAAIQDV0ZLxvgAAADcBAAAsAAAAAAAAAAAAAAAAANkrAABwcHQvc2xpZGVM YXlvdXRzL19yZWxzL3NsaWRlTGF5b3V0NC54bWwucmVsc1BLAQItABQABgAIAAAAIQDV0ZLxvgAA ADcBAAAsAAAAAAAAAAAAAAAAAOEsAABwcHQvc2xpZGVMYXlvdXRzL19yZWxzL3NsaWRlTGF5b3V0 OS54bWwucmVsc1BLAQItABQABgAIAAAAIQDV0ZLxvgAAADcBAAAsAAAAAAAAAAAAAAAAAOktAABw cHQvc2xpZGVMYXlvdXRzL19yZWxzL3NsaWRlTGF5b3V0NS54bWwucmVsc1BLAQItABQABgAIAAAA IQDt7fr0qwQAABkSAAAfAAAAAAAAAAAAAAAAAPEuAABwcHQvbm90ZXNTbGlkZXMvbm90ZXNTbGlk ZTEueG1sUEsBAi0AFAAGAAgAAAAhAEqvdTnUAAAAvwEAACoAAAAAAAAAAAAAAAAA2TMAAHBwdC9u b3Rlc1NsaWRlcy9fcmVscy9ub3Rlc1NsaWRlMS54bWwucmVsc1BLAQItABQABgAIAAAAIQDV0ZLx vgAAADcBAAAtAAAAAAAAAAAAAAAAAPU0AABwcHQvc2xpZGVMYXlvdXRzL19yZWxzL3NsaWRlTGF5 b3V0MTEueG1sLnJlbHNQSwECLQAUAAYACAAAACEA1dGS8b4AAAA3AQAALQAAAAAAAAAAAAAAAAD+ NQAAcHB0L3NsaWRlTGF5b3V0cy9fcmVscy9zbGlkZUxheW91dDEwLnhtbC5yZWxzUEsBAi0AFAAG AAgAAAAhANXRkvG+AAAANwEAACwAAAAAAAAAAAAAAAAABzcAAHBwdC9zbGlkZUxheW91dHMvX3Jl bHMvc2xpZGVMYXlvdXQzLnhtbC5yZWxzUEsBAi0AFAAGAAgAAAAhAGmiXyEeAQAAxwcAACwAAAAA AAAAAAAAAAAADzgAAHBwdC9zbGlkZU1hc3RlcnMvX3JlbHMvc2xpZGVNYXN0ZXIxLnhtbC5yZWxz UEsBAi0AFAAGAAgAAAAhANXRkvG+AAAANwEAACwAAAAAAAAAAAAAAAAAdzkAAHBwdC9zbGlkZUxh eW91dHMvX3JlbHMvc2xpZGVMYXlvdXQyLnhtbC5yZWxzUEsBAi0AFAAGAAgAAAAhANXRkvG+AAAA NwEAACwAAAAAAAAAAAAAAAAAfzoAAHBwdC9zbGlkZUxheW91dHMvX3JlbHMvc2xpZGVMYXlvdXQ2 LnhtbC5yZWxzUEsBAi0AFAAGAAgAAAAhAFL/juQaBAAAfA0AACIAAAAAAAAAAAAAAAAAhzsAAHBw dC9zbGlkZUxheW91dHMvc2xpZGVMYXlvdXQxMS54bWxQSwECLQAUAAYACAAAACEAOEc2gt0DAACc DAAAIgAAAAAAAAAAAAAAAADhPwAAcHB0L3NsaWRlTGF5b3V0cy9zbGlkZUxheW91dDEwLnhtbFBL AQItABQABgAIAAAAIQBvnWtAwQMAAGQMAAAhAAAAAAAAAAAAAAAAAP5DAABwcHQvc2xpZGVMYXlv dXRzL3NsaWRlTGF5b3V0Mi54bWxQSwECLQAUAAYACAAAACEAA0rdllAEAAB9DgAAIQAAAAAAAAAA AAAAAAD+RwAAcHB0L3NsaWRlTGF5b3V0cy9zbGlkZUxheW91dDEueG1sUEsBAi0AFAAGAAgAAAAh AI0AcRlGCQAAEDwAACEAAAAAAAAAAAAAAAAAjUwAAHBwdC9zbGlkZU1hc3RlcnMvc2xpZGVNYXN0 ZXIxLnhtbFBLAQItABQABgAIAAAAIQDV0ZLxvgAAADcBAAAsAAAAAAAAAAAAAAAAABJWAABwcHQv c2xpZGVMYXlvdXRzL19yZWxzL3NsaWRlTGF5b3V0Ny54bWwucmVsc1BLAQItABQABgAIAAAAIQAl mO97nwQAANAOAAAhAAAAAAAAAAAAAAAAABpXAABwcHQvc2xpZGVMYXlvdXRzL3NsaWRlTGF5b3V0 My54bWxQSwECLQAUAAYACAAAACEARPkJDHkEAAA2EwAAIQAAAAAAAAAAAAAAAAD4WwAAcHB0L3Ns aWRlTGF5b3V0cy9zbGlkZUxheW91dDQueG1sUEsBAi0AFAAGAAgAAAAhAJLVayzUBQAABh0AACEA AAAAAAAAAAAAAAAAsGAAAHBwdC9zbGlkZUxheW91dHMvc2xpZGVMYXlvdXQ1LnhtbFBLAQItABQA BgAIAAAAIQAchf1UHAUAADITAAAhAAAAAAAAAAAAAAAAAMNmAABwcHQvc2xpZGVMYXlvdXRzL3Ns aWRlTGF5b3V0OS54bWxQSwECLQAUAAYACAAAACEAwH+p6U4FAACREwAAIQAAAAAAAAAAAAAAAAAe bAAAcHB0L3NsaWRlTGF5b3V0cy9zbGlkZUxheW91dDgueG1sUEsBAi0AFAAGAAgAAAAhABbHYmHw AgAANggAACEAAAAAAAAAAAAAAAAAq3EAAHBwdC9zbGlkZUxheW91dHMvc2xpZGVMYXlvdXQ3Lnht bFBLAQItABQABgAIAAAAIQAdZEPCjQMAAAEKAAAhAAAAAAAAAAAAAAAAANp0AABwcHQvc2xpZGVM YXlvdXRzL3NsaWRlTGF5b3V0Ni54bWxQSwECLQAUAAYACAAAACEA1dGS8b4AAAA3AQAALAAAAAAA AAAAAAAAAACmeAAAcHB0L3NsaWRlTGF5b3V0cy9fcmVscy9zbGlkZUxheW91dDEueG1sLnJlbHNQ SwECLQAUAAYACAAAACEAZZsUO/kAAAAmAgAAFAAAAAAAAAAAAAAAAACueQAAcHB0L21lZGlhL2lt YWdlMi53bWZQSwECLQAUAAYACAAAACEAAgNIiKQGAABKHwAAIQAAAAAAAAAAAAAAAADZegAAcHB0 L25vdGVzTWFzdGVycy9ub3Rlc01hc3RlcjEueG1sUEsBAi0AFAAGAAgAAAAhAKmEucEzCwAASkIA ABQAAAAAAAAAAAAAAAAAvIEAAHBwdC90aGVtZS90aGVtZTEueG1sUEsBAi0AFAAGAAgAAAAhALTP WBm7AAAAJAEAACwAAAAAAAAAAAAAAAAAIY0AAHBwdC9ub3Rlc01hc3RlcnMvX3JlbHMvbm90ZXNN YXN0ZXIxLnhtbC5yZWxzUEsBAi0AFAAGAAgAAAAhALl/7nOWBgAAsBsAABQAAAAAAAAAAAAAAAAA Jo4AAHBwdC90aGVtZS90aGVtZTIueG1sUEsBAi0ACgAAAAAAAAAhAETYp+KArwAAgK8AABcAAAAA AAAAAAAAAAAA7pQAAGRvY1Byb3BzL3RodW1ibmFpbC5qcGVnUEsBAi0AFAAGAAgAAAAhAETOvPXL AgAA2AcAABQAAAAAAAAAAAAAAAAAo0QBAHBwdC9tZWRpYS9pbWFnZTEud21mUEsBAi0AFAAGAAgA AAAhAAFyP3jIAAAARwEAABEAAAAAAAAAAAAAAAAAoEcBAHBwdC92aWV3UHJvcHMueG1sUEsBAi0A FAAGAAgAAAAhANj9jY+sAAAAtgAAABMAAAAAAAAAAAAAAAAAl0gBAHBwdC90YWJsZVN0eWxlcy54 bWxQSwECLQAUAAYACAAAACEAwjFkyKMBAACaAwAAEQAAAAAAAAAAAAAAAAB0SQEAcHB0L3ByZXNQ cm9wcy54bWxQSwECLQAUAAYACAAAACEAwAs/bEgCAAC4BAAAEAAAAAAAAAAAAAAAAABGSwEAZG9j UHJvcHMvYXBwLnhtbFBLAQItABQABgAIAAAAIQCDWwE8owEAAA4DAAARAAAAAAAAAAAAAAAAAMRO AQBkb2NQcm9wcy9jb3JlLnhtbFBLBQYAAAAALAAsAGENAACeUQEAAABQSwMEFAAGAAgAAAAhALnf 3XK6BQAABxEAABEAAAB3b3JkL3NldHRpbmdzLnhtbLRYW4/TOBR+X2n/Q9XnnamdeyI6KGmS3UEM IAo/wE3cNiKJI9uZUn79HucypcwZhBYtLzjnfvnsnjOvXn9t6sUjl6oS7XpJb8lywdtClFV7WC8/ f8pvguVCadaWrBYtXy/PXC1f3/35x6tTpLjWIKYWYKJVUVOsl0etu2i1UsWRN0zdio63wNwL2TAN n/Kwapj80nc3hWg6pqtdVVf6vLII8ZaTGbFe9rKNJhM3TVVIocReG5VI7PdVwaf/Zg35K35HzVQU fcNbPXhcSV5DDKJVx6pTs7Xmv1qDFI+zkcefJfHY1LPciZKfSU7pnoQsnzR+JTyj0ElRcKWgQU09 ptuwqn0yQ51nhp5KfQulXo2+V8YUqFMynC6Rq/qZPtLtsYtvq51kcmwzAMBE0RTR/aEVku1qANWJ Oss7QNQ3IZrFKeq4LKBJAEebLFeGwZsdL7dnpXmTi1argQgZiv1WM81BR3W8rgfQFjVn4OEUHSRr AG7r5UgZdJQ+1/wDa3k+YDKvas0lyD4yyMfOCTWKrK63Rk5BBOa76JUWzUyCG3KKADgQ4RVpMK3u 288KMhqEjpyZe3Ql1faQivyRqk0druTKSvJCj1GaW/a+/di3c0DPmR+YZJBvd3xZ5N3secrquZFP JorZgCmavPiflLTo7H+u0xpK9Fip6scUmKltC4UaEnvHGmN7amjJ96yvNXjcgsm5Ab41sYsj5FOA +rZjBWS/gaZLUc9ypXgn9AaeEAkIHxEyPigGK+NpOz5OoNGCY8DA9w/Ogyi56WIvq2cofvEWGIUB JgDWAUu4IwGPqaxKPhRzyNwgdlt943FbvgEkVfCEDc/Ob0TwswB4a9r4Hp7eT+eO55zpHsr0Pzkb OpHXVfdQSSnkfVvCtfhdZ6u5iaad8MtUqvnwUQg9t4EQN7VDb0KMEbtwiGvbVjxW6QeOZzshRTmh nW1cnOOlGW4t9hMb5ySeQ3DOxqKZh/pJHd8NMA6lLk0tlONZVpJjHIvYm02GcjyfBriOTywP58Q0 tdGordimjo/6iZ0kRmttZSR2UT82oa6F+rEpyVLUj+1SNwmxCGzXSwPcWkCzBO2PndpxmmDWHId6 eYpzLA/HgZP71EYzhTQTH+2p6/lJjOLaDQD1uM6Ld8EjduagmXqZFSdoRX14iRMUiX4O1d5gNQhs 2yfT03h95wLXzZwXOJ4XoHcuCOnGR+sWEicPUFyH1E59FAehDxcLrVuYUxKgmcbECj1UJ6ZOYKE1 iC2LWGhFY5cGHtqFOHSJj2I0Dn2ao3WLYxrgdztOnCBBrSWO5YdoPhtC/RzF28aDIqC13uRehmM0 pST30FuSUst30J6m/ksvbJpYDp5pmpJ4g1Y0I4RkaNQZ8R0brUFmwT+0p5njujiuM8+xQlzH99wY rUEGweE4yEPywq3PU8/bDBiFX8bp97CJzL7xQd69Gk9myFg044CyYc1OVmzxYDYSGFWaaCe/JFU7 83ccNjL+PWfb72bmzc3IUA2MwTlMYTNjAEgTlZXqUr4fzNYPTB4udicJiVJh4nvzZMuM91z+LUXf jd5OMLuOw8PsjjrOZK9q9duqmemq321nrRa2iu9YfVu+f5TG4OpSnlOkYRmFeR+ssPYwzwi8vfm8 NaIwa9RyaxZW/sC6DoZNENkd6HpZV4ejHqZbDV8lLK7Dx+5gTTzLDFUavgxv+GCFyQykp4MRGI8g NR0uNHum2RcarGWjnHOhuTPNvdC8mQaL8yk6wqQnYf35AuPsfDT0vahrceLlPzNxvXxGGoswDHL3 bVH3JQc0lKKAVcYsV+OupY6s49B2M7TDNCaigTBN8WrxGPGvsK/xstLw54KuKhv2FTYGGCaM9Um6 ZmfR6ytZwzPC3RV1UTLNzMJhOnmlDN+w6l3HcopKXlSA1u252V12hNsxr7pSess7WCe0kFCRYYL/ a7B8+QvG3b8AAAD//wMAUEsDBBQABgAIAAAAIQAXoBZOAgEAAKwBAAAUAAAAd29yZC93ZWJTZXR0 aW5ncy54bWyM0MFKAzEQBuC74DssubfZlSKydLcgUvEigvoAaXZ2G8xkwkxqrE9v2qogXnrLJJmP mX+5+kBfvQOLo9CpZl6rCoKlwYWpU68v69mNqiSZMBhPATq1B1Gr/vJimdsMm2dIqfyUqihBWrSd 2qYUW63FbgGNzClCKI8jMZpUSp40Gn7bxZkljCa5jfMu7fVVXV+rb4bPUWgcnYU7sjuEkI79msEX kYJsXZQfLZ+jZeIhMlkQKfugP3loXPhlmsU/CJ1lEhrTvCyjTxPpA1Xam/p4Qq8qtO3DFIjNxpcE c7NQfYmPYnLoPmFNfMuUBVgfro33lJ8e70uh/2TcfwEAAP//AwBQSwMEFAAGAAgAAAAhAJAW+pR3 CQAAPjoAABoAAAB3b3JkL3N0eWxlc1dpdGhFZmZlY3RzLnhtbMxbW3PbthJ+PzP9Dxy9O5Z8t6ZK x5e48YzrppEz5xmiIIs1SfCQlBXn15/FAgRBLgkRdj3NSyxe9gP28u0CxObX374ncfDM8yIS6Ww0 +TAeBTwNxTJKH2ejbw83e2ejoChZumSxSPls9MKL0W8ff/nPr9tpUb7EvAgAIC2m2yycjdZlmU33 94twzRNWfEiiMBeFWJUfQpHsi9UqCvn+VuTL/YPxZIy/slyEvChgtCuWPrNipOESiiYynsJYK5En rCw+iPxxP2H50ybbA/SMldEiiqPyBbDHJxWMmI02eTrVE9ozE5IiUzUh/aeSyIkWHeMqyWsRbhKe ljjifs5jmINIi3WU1Wq8Fg1UXFdTenYp8ZzE1XvbbHJExjMqD/HBdc624IoakMB1GGOphJJY2UH6 t/ZqG3EydimjPSIhzByGTKE5ZjWThEWpgXmdaWzjAh/eEt+/52KTmelk0dvQbtMngyVp6TGz8Qky z1at8AIg1J2vWcZHQRJObx9TkbNFDDPaTo4CGZGjj5AqliK85iu2ictCXuZfcn2pr/DPjUjLIthO WRFGYJ6HKIHscs+3wVeRMPDkdspZUV4UEet8uL5Ii26xEPRro+3LIWOWPgLsM4tnI57ufZs3BzG3 FtESkFm+N78YgeA+alD9tTTJjF7qrZbakCAgXcxV2gSj8NWdCJ/4cl7Cg9kIUi/e/Hb7JY9EDrms vjfnSfQ5Wi45JGnzXrqOlvy/a55+K/iyvv/XDaZIfSMUm7ScjQ5OTtETcbH89D3kmUxVMFzKEhj5 XgpAHtlO/1fJTqSiYKGu19ecyfoQTLwlDqREYemCEJuWIv64h++Ee/ROuMfvhAuF713se/pOuLC4 eJf5nv/DuCFDwvzDqA9RGUPeHMi6+WZR+gmUuZDFfCD+pyRbsyKCtctAgS8xC/laxEueBw/8e9lt nahOZufnjqRyL4J5xkJcfmynG0tseDq4ix7XZQDlSKYnOR0b5mTsGF1J3kUFatEQc2VCJfZ7HsF6 pTXagWO0P/gy2iTVRFUebYx5OFwYU2pD+Gi3sFS0Y9jjgZJ0zJPdktJKHWOeDpSkY54NlMTi0LCQ Kw6vYU8RdAXCqSt+rkQs8tUmrnzaDodTVxQZ4c5hXYFkJLtC8NQVRQ2qBBdhCCuTDu+4dK450y/v UrsmT7+8S/k2i/pRXIZooRz0owzmVT+Ei2Bf+XMkd+FvS6PI7C8sZ485y2AL2cxKh7igGbTI+2sj SixONnMOsLAOkr9NYbFb8KAT5xDXsINwtH9QL4dzBiegfucMzkT9EINTUj/EoNzUK+6VpPpRXLQ1 OQdd0pc5Tl3MNRBYE3ohXLTtzF+0RvjlLyrvMgTNX1TeZYVW5plU7qAoLkO0UAxFKIp3/qIQrvzV SVQK4U1UCuFNVArhTVQK4UVUIv4qolIUV3waltlEpRCuEDUQNlEphCs+O4lKl2R+RKXyLkNQolJ5 lxVaFDNEpSguQ7RQDFEpijdRKYQ3USmEN1EphDdRKYQ3USmEF1GJ+KuISlFc8WlYZhOVQrhC1EDY RKUQrvjsJCquF+0V4MBddFXLqLzLEJSoVN5lhRbFDFEpissQLRRDVIriTVQK4U1UCuFNVArhTVQK 4U1UCuFFVCL+KqJSFFd8GpbZRKUQrhA1EDZRKYQrPjuJil+U30BUKu8yBCUqlXdZoUUxQ1SK4jJE C8UQlaJ4E5VCeBOVQngTlUJ4E5VCeBOVQngRlYi/iqgUxRWfhmU2USmEK0QNhE1UCuGKz06i4hHN G4hK5V2GoESl8i4rtChmiEpRXIZooRiiUhRvolIIb6JSCG+iUghvolIIb6JSCC+iEvFXEZWiuOLT sMwmKoVwhaiBsIlKIVzxKY/WYh7YJ2A2Qyf+Xz37oA6GH2bpSX3lK55DSxYn33KHQ1XfYvuxcE8/ 6HvspRBPgTm5tM10iPuNYSDRIo4EfqJ+2fm9+xBPn2mTQH+DwsOfV8Fn1aSwGx2dS9HJKSh0fdgN HLI7Ajvg4MXyJYMuisz+6g7NHbLdBVrqcAay5+MWejR0p4UUlq0XIIvNJ/o2aqQNiL+hUUa+mrtb Y4JLOISVw3S3wJjHHX0w6hmOtcB/ix/VnA4wF1u9LqjtDrXxHamoNv8Em05sVevmETUqg96VP2Ur CjFECmfKXffjKH2q7lfDXK1Zro4DG+Yr4MhRI4/HF8eTs5ML9RZ06khNnjjP7mEYnIq8uItSXihD qMNoEF9w6DkE/x6d6Y9UYlPCHPjdc2zAJSqYSsN2uu0BmiIBJWF/i/yz7FWSHqs6muyHn3SXk/Go /dBIhkVpAV5Ch5LSbNGYE8z+SukTyhPK6tnhyfHNOUYmgmAKhQYnPAWsb8uDdJjx5Y1CtkJDl6bi x5Vs2ELPHeC93eESgqdYWPJcqtfDEt1SZY6xZPiTQNIvBeatAF9D59VpqZqeLkJ175F6r9F5pHzY E+albGtzzPlBPnfSO8BXlC3pBKvmiF0zhGyziFX0wo/bVAb4Vvd6qTy0/M7UIPD8isfxHwxjvRRZ /6sxX0muAdBkjE05LaiFKEuR9Mvn2HnRCwBhYU9GXUol4FePvdNNsuC57uPoiZN7IZcNJDKglQTv 94TCUEv3z60Rw+GmANPMZYZvZ/tGdmrnfP0wmAR18lo0s2EnD1CrrhyonA6d3D0571/NSj9ZFmrU alO0TItV21fmARq/5SW7eA+pWRVY7XavmgXEUPSP4roAYXqDgNUP4ddPUIoitFbU5fqjm7PJ5bVM p10FCOUKU4Cxvkz0vq5RcwYuUYbyteGZvhh4K12rQX5quirPvY//wOlqxaA3+6/xaDd/L1kcC5Fi M2LbffqZ6lRExRw0ttOrBVoz1jPLQv85W0MXuwz4apFubuCyXF2pwDdL8In+EGFbSN0DgmM6f3uN aqvnsttbQ98a61XR72XGxXsZ05QLs8lv28w86Iqz/qLuKAPnp5MbTRddxu3kujsauvmitvHt2au7 XVP3rXSIVJNmmH66cGWXS1y2mpUn5gz5P8XUMrz4MRup9nGoE3J3JrmFmxz4vau6yPqo8esyw1aw K5mNDsd6mxfCrgP2hhsW68ZkMIkUVNX331xNNfZyk1PYzZFSKmeOH3Wwvs5bO7lmadWV9YnnZh+u dnOwODe56Fh/g7Nzkbq3O/qG1t86Xjpj8q3pxwrsVv6m9Gp+cnmwttpmB/4Oe3ck3c/uXfA3psDi 4/8BAAD//wMAUEsDBBQABgAIAAAAIQDwrP5d9ggAAE03AAAPAAAAd29yZC9zdHlsZXMueG1szFvb cts2EH3vTP+Bw/dEF19ke6JkbCduPOO6SeRMnyEKsliThEpQcZyv72JBQiCXhAg7muYlFgHuAbC7 ZxcgNm/efU+T4BvPZSyyaTh6PQwDnkViEWf30/Dr3dWrkzCQBcsWLBEZn4ZPXIbv3v7+25vHM1k8 JVwGAJDJszSahquiWJ8NBjJa8ZTJ12LNM+hcijxlBTzm94OU5Q+b9atIpGtWxPM4iYunwXg4PA5L mLwPilgu44i/F9Em5VmB8oOcJ4AoMrmK17JCe+yD9ijyxToXEZcSFp0mGi9lcWZgRocEKI2jXEix LF7DYgZ6RgMFBeKjIf5KkzBIo7Pr+0zkbJ6A8h5Hh+Fb0NxCRO/5km2SQqrH/FNePpZP+OdKZIUM Hs+YjOJ4Gt7FKSj7lj8GX0TKYG6PZ5zJ4lzGrLVzdZ7JdrFIUoGBGjJh2T3AfmPJNOTZq6+z+iCm aR4vAJnlr2bnIQgOcAXVX2sla7Mu/VZj2WAwMN9MexEohS9vRPTAF7MCOqYheCI2fr3+lMciB0/Z ts14Gn+MFwsOPmvey1bxgv+94tlXyRfb9s9X6IBlQyQ2WTENx8cTtEQiFx++R3ytXAeGy1gKI98q ATDe49m/lexILRQ01Pb6ijNFl2DkLTFWEtJaC0JsGgvxxz3YE+7hnnCP9oQLYWUv+p3sCRdi7V7m e/qTcSOGhPnJqHdxkXCF2Yt1s8288BMocpHd98b/kK5XTMaQS3pO6FPCIr4SyYLnwR3/XrRrJ94G s9NTR1C5FcFszSKIKwpnY4n1Dwc38f2qCGYrDE9NmOOhY3QteRNLXIU9+rErEmqxP/J4QUYbO0b7 ky/iTVpNVMfR2pgH/YUxpNaED3cLq4W2DHvUU5KOebxbUmmpZcxJT0k65klPSUwONQ25/PA97NiC NkeYuPznUiQiX26SyqZNd5i4vMgItw7rciQj2eaCE5cX1agSnEcR7ExarONa85Yz3fKuZW/J0y3v WnyTRd0oLkU0UMbdKL151Q3hItgX/i1WhxLlOnSLZMVDZxhFZn9iObvP2XrVdMMD3ND0SjefN6LA 5GQzZ4yJtZf8dQabXcmDVpwD3MP2wintg+tyGKd3AOo2Tu9I1A3ROyR1Q/SKTZ3iXkGqG8VFWxNz 0CRdkWPiYq6BwJzQCeGibWv8ojnCL35ReZciaPyi8i4tNCLPqDIHRXEpooFiKEJRvOMXhXDFr1ai UghvolIIb6JSCG+iUggvohLxZxGVorj807DMJiqFcLmogbCJSiFc/tlKVLol8yMqlXcpghKVyru0 0KCYISpFcSmigWKISlG8iUohvIlKIbyJSiG8iUohvIlKIbyISsSfRVSK4vJPwzKbqBTC5aIGwiYq hXD5ZytRcb9o7wB7nqKrXEblXYqgRKXyLi00KGaISlFcimigGKJSFG+iUghvolIIb6JSCG+iUghv olIIL6IS8WcRlaK4/NOwzCYqhXC5qIGwiUohXP7ZSlT8ovwColJ5lyIoUam8SwsNihmiUhSXIhoo hqgUxZuoFMKbqBTCm6gUwpuoFMKbqBTCi6hE/FlEpSgu/zQss4lKIVwuaiBsolIIl3+2EhWvaF5A VCrvUgQlKpV3aaFBMUNUiuJSRAPFEJWieBOVQngTlUJ4E5VCeBOVQngTlUJ4EZWIP4uoFMXln4Zl NlEphMtFDYRNVArh8k91tZbwwL4Bsxk68v/q2QU17n+ZVU7qC1/yHCpUOPmW2x+q+hbbjYVn+l7f Yy+EeAjMzaWtpgM8b/QDiedJLPAT9dPO790HePtMiwS6CxTu/roMPuoihd3oaFyKTm5BoerDLuBQ 1RFYEAQvFk9rqKJY21/dobhDlbtAhRHOQNV8XEONRllpoYRV6QXIYvFJ2YwrKhWIv6FQRr2au0tj ggu4hFXDtJfAmO6WOhjdh2PN8V/5o5rTGGOxVeuCq92xbHxHLbRU/wiLTuylbotH9KgMalf+UqUo RBEZ3Cm3tSdx9lC1V8NcrliurwNr6pNw5VgiD4fnR6OT43P9FlTqqJU8cL6+hWFwKurhJs641IrQ l9EgPudQ0QX2PTwpP1KJTQFz4DffEgOuUEFVJWyr2e6gSAxQUvaPyD+qWiVlsaqiye78UFY5GYva nUYykoUFeAEVSnpl89qcYPaXej2RuqGs+g6Oj65O0TMRBEMoFDjhLeC2WV2kw4wvrjSy5RplapI/ LlXBFlpujG273SUCS7Go4LlaXgdLypIqc42l3J84UvlSYN4K8DU03jYsVdMrk9D2Yk2/V6s80jbs cPNCVbQ55nyn+p30DvAVrUs6wepWb9cMIdrME+298OM6Uw4OZX94oabj0OI704NA/yVPkj8Z+noh 1t2vJnypuAZAoyEW5TSg5qIoRNotn2PlRScAuIU9Gf2oFgG/OvSdbdI5z8tykA4/uRVq20A8A0pJ sL3DFfpquntuNR+ONhJUM1MRvhnta9GpGfPLzmAUbIPXvB4NW3mAq2qLgdroUNjaEfP+16j0i0Wh Wq42ScuUWDVtZTpQ+Q0r2cm7T86qwLZm98pZQAxN/zjZJiAMb+CwZSf8+gVSUYzaittMf3h1Mrp4 r8JpWwJCOWkSMOaXUXmuq+WcnluUvnytWabLB15K12qQX5qu2nL7sR8YXe8YysP+cyzazt8LliRC ZFiM2DRf2acrFXFhDhrb4dUC3TLWM8pC/TlbQRW7cvhqk24acFuun7Tjmy34qPwQYWtItwHBMZy/ PEc1l+fS20td3xrrWd7vpcb5vpRp0oU55Dd1Zjra/Kw7qTvSwOlkdFXSpUzjdnDd7Q3tfNHH+Obs dWvb1H0zHSJtSdNvfWXiWl8scNtqdp4YM9T/WNHbcPljGuryccgT6nSmuIWHHPi9K7uo/Fjib9MM W8KpZBoeDMtjXgSnDjgbblhSFiaDSpSgzr7/526qdpYbTeA0R1Kpmjl+1MH8Omuc5OqptcysDzw3 53B9moPNuYlFR+U3ODsW6bbd3tc3/279pdUnXxp+LMduxG9Kr/onlzvrqG1O4Hs4uyPpfnXrgr0x BMq3/wEAAP//AwBQSwMEFAAGAAgAAAAhAN1n3GBWAQAAnwIAABEACAFkb2NQcm9wcy9jb3JlLnht bCCiBAEooAABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJySX0vDMBTF3wW/Q8izbfoHRUrb oY49ORg6UXwLyd0abJKSxHX79qbtVjsUH3xM7jk/zrlJPtvLGu3AWKFVgeMwwggU01yobYFf1ovg FiPrqOK01goKfACLZ+XlRc6ajGkDK6MbME6ARZ6kbMaaAlfONRkhllUgqQ29QvnhRhtJnT+aLWko +6BbIEkU3RAJjnLqKOmAQTMS8RHJ2YhsPk3dAzgjUIME5SyJw5h8ax0YaX819JOJUgp3aHynY9wp m7NhOKr3VozCtm3DNu1j+PwxeVs+PvdVA6G6XTHAZc5ZxgxQp025FKyiUKO7ED1RSetKX6FVFc7D nExU3UZrat3SL38jgN8f/jL+FHd+AzvRvWSZ5GR69Gn68kMk4MjXyYbyp8lr+jBfL3CZRHEaRNdB nK7jJEtvsyh673Ke+bt6w4U8pv038QQo+8TnX6r8AgAA//8DAFBLAwQUAAYACAAAACEAIz3HNB0C AAD2BgAAEgAAAHdvcmQvZm9udFRhYmxlLnhtbLyU327aMBTG7yftHSLflzghKxQ1VJQNaTe9mNgD GOMQa/4T+Rgy3n4ndqBVW1QiTSVCSr4cfzrnl8++f/irVXIQDqQ1JclGlCTCcLuVZleS3+vVzZQk 4JnZMmWNKMlRAHmYf/1y384qazwkuN7ATPOS1N43szQFXgvNYGQbYfBlZZ1mHh/dLtXM/dk3N9zq hnm5kUr6Y5pTekt6G3eNi60qycV3y/daGB/Wp04odLQGatnAya29xq21bts4ywUAzqxV9NNMmrNN Vrwx0pI7C7byIxwmjR2lnRUuz2i404okms9+7ox1bKOQXZsVZN6DS9qZYRrFtdQCkifRJr+sZiYU NMxYEBnWHJgqCc3xuqVj+o0W+M/xriBp58Rr5kD4cyGNcsW0VMeT6oJvqG+k5/VJPzAnu8biGpA7 fLGHDS3JD0ppvlitSFSykixRmUyLrFdybCr+7nplfFYwQdhY8AklWfRBBX36VaHPNEboIyLJo1Xb gIUp/4TMTv2/JhcnfAfdFIFNENxnoOsGHC+mk2d055EjzGd0ARQCv4yODkW3ZHqDH/VCiLrwxBB1 Yco/IUQ0fxmiokNRnJUhJLK7EMYBIWI1xv4CiEfcTUWPohgIAloJELeMsX7t9mJ9bMSQ3dUHYvx/ IkLDnrwezJIpiRm5QGYVNkl33nR8hkXkBZlrz5kMWbyJyGL5TkSuOGc+jEh/4MD8HwAAAP//AwBQ SwMEFAAGAAgAAAAhAD7WRKfyAQAA8AMAABAACAFkb2NQcm9wcy9hcHAueG1sIKIEASigAAEAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAnFPBbtswDL0P2D8YvjeKm6xbAkbFkGLoYVsDxG3Pmkwn wmxJkNig2dePshvH2XaaT+Qj/fT0SMHta9tkBwzROLvKi8k0z9BqVxm7W+WP5ZerT3kWSdlKNc7i Kj9izG/l+3ewCc5jIIMxYwobV/meyC+FiHqPrYoTLluu1C60ijgNO+Hq2mi8c/qlRUviejq9EfhK aCusrvxAmPeMywP9L2nldNIXn8qjZ8ESSmx9owjl9ySnmVSOWhADCqUj1ZSmRVkwPCSwUTuM8iOI PoBnF6ooWfgMRB/Deq+C0sQWyqKYFwsQIwQ+e98YrYjtld+MDi66mrKHzogsMYAYtwCbs0X9Egwd 5RTEOIWvxrKYxQcQfcTqgtoF5fcs6SZpHFLYatXgmj2QtWoigjgDcI8qzXejDGuGAy0PqMmFLJpf POHrPPuhIibnVvlBBaMssYOprU+6uPGRgiwNNczNtT7vwnHbODbzZC73cnDZmMBeAxcu1XUnxIea 70b/EFuMxXYaeqkjOaNwOOMP1rVrvbJHuTZRu2x7jIRt5Dm+wcn4n/HRl+4urdCboZfgaA2eDe23 XmmeVTGbLXgw54UY1WDLi4MVT/jEeAbgnt0PTTqW/7U7rE49fxfSij31D1gW88mUv26nThjvxfCy 5G8AAAD//wMAUEsBAi0AFAAGAAgAAAAhAOHmAUWlAQAALgYAABMAAAAAAAAAAAAAAAAAAAAAAFtD b250ZW50X1R5cGVzXS54bWxQSwECLQAUAAYACAAAACEAHpEat/MAAABOAgAACwAAAAAAAAAAAAAA AADeAwAAX3JlbHMvLnJlbHNQSwECLQAUAAYACAAAACEApjFo414BAADeBAAAHAAAAAAAAAAAAAAA AAACBwAAd29yZC9fcmVscy9kb2N1bWVudC54bWwucmVsc1BLAQItABQABgAIAAAAIQDFoZN7PzQA AHK+AQARAAAAAAAAAAAAAAAAAKIJAAB3b3JkL2RvY3VtZW50LnhtbFBLAQItABQABgAIAAAAIQAw 3UMpqAYAAKQbAAAVAAAAAAAAAAAAAAAAABA+AAB3b3JkL3RoZW1lL3RoZW1lMS54bWxQSwECLQAU AAYACAAAACEABOtPXFwaAQBAYAQAFQAAAAAAAAAAAAAAAADrRAAAd29yZC9tZWRpYS9pbWFnZTEu ZW1mUEsBAi0ACgAAAAAAAAAhAMN6HtgVXwEAFV8BADAAAAAAAAAAAAAAAAAAel8BAHdvcmQvZW1i ZWRkaW5ncy9NaWNyb3NvZnRfUG93ZXJQb2ludF9TbGlkZTEuc2xkeFBLAQItABQABgAIAAAAIQC5 391yugUAAAcRAAARAAAAAAAAAAAAAAAAAN2+AgB3b3JkL3NldHRpbmdzLnhtbFBLAQItABQABgAI AAAAIQAXoBZOAgEAAKwBAAAUAAAAAAAAAAAAAAAAAMbEAgB3b3JkL3dlYlNldHRpbmdzLnhtbFBL AQItABQABgAIAAAAIQCQFvqUdwkAAD46AAAaAAAAAAAAAAAAAAAAAPrFAgB3b3JkL3N0eWxlc1dp dGhFZmZlY3RzLnhtbFBLAQItABQABgAIAAAAIQDwrP5d9ggAAE03AAAPAAAAAAAAAAAAAAAAAKnP AgB3b3JkL3N0eWxlcy54bWxQSwECLQAUAAYACAAAACEA3WfcYFYBAACfAgAAEQAAAAAAAAAAAAAA AADM2AIAZG9jUHJvcHMvY29yZS54bWxQSwECLQAUAAYACAAAACEAIz3HNB0CAAD2BgAAEgAAAAAA AAAAAAAAAABZ2wIAd29yZC9mb250VGFibGUueG1sUEsBAi0AFAAGAAgAAAAhAD7WRKfyAQAA8AMA ABAAAAAAAAAAAAAAAAAApt0CAGRvY1Byb3BzL2FwcC54bWxQSwUGAAAAAA4ADgCqAwAAzuACAAAA --_005_D21571530BF9644D9A443D6BD95B910315557345xmbrcdx12ciscoc_ Content-Type: application/pdf; name="RMCAT_Topology_May_13_2013.pdf" Content-Description: RMCAT_Topology_May_13_2013.pdf Content-Disposition: attachment; filename="RMCAT_Topology_May_13_2013.pdf"; size=659123; creation-date="Mon, 13 May 2013 12:38:22 GMT"; modification-date="Mon, 13 May 2013 12:38:23 GMT" Content-Transfer-Encoding: base64 JVBERi0xLjUNCiW1tbW1DQoxIDAgb2JqDQo8PC9UeXBlL0NhdGFsb2cvUGFnZXMgMiAwIFIvTGFu Zyhlbi1VUykgL1N0cnVjdFRyZWVSb290IDY1IDAgUi9NYXJrSW5mbzw8L01hcmtlZCB0cnVlPj4+ Pg0KZW5kb2JqDQoyIDAgb2JqDQo8PC9UeXBlL1BhZ2VzL0NvdW50IDcvS2lkc1sgMyAwIFIgNDQg MCBSIDQ2IDAgUiA1MiAwIFIgNTYgMCBSIDU4IDAgUiA2MiAwIFJdID4+DQplbmRvYmoNCjMgMCBv YmoNCjw8L1R5cGUvUGFnZS9QYXJlbnQgMiAwIFIvUmVzb3VyY2VzPDwvRm9udDw8L0YxIDUgMCBS L0YyIDcgMCBSL0YzIDEyIDAgUi9GNCAxNCAwIFIvRjUgMTYgMCBSPj4vWE9iamVjdDw8L01ldGEy MSAyMSAwIFI+Pi9FeHRHU3RhdGU8PC9HUzIyIDIyIDAgUi9HUzIzIDIzIDAgUj4+L1Byb2NTZXRb L1BERi9UZXh0L0ltYWdlQi9JbWFnZUMvSW1hZ2VJXSA+Pi9NZWRpYUJveFsgMCAwIDYxMiA3OTJd IC9Db250ZW50cyA0IDAgUi9Hcm91cDw8L1R5cGUvR3JvdXAvUy9UcmFuc3BhcmVuY3kvQ1MvRGV2 aWNlUkdCPj4vVGFicy9TL1N0cnVjdFBhcmVudHMgMD4+DQplbmRvYmoNCjQgMCBvYmoNCjw8L0Zp bHRlci9GbGF0ZURlY29kZS9MZW5ndGggMjMwMT4+DQpzdHJlYW0NCnicjVlbb+O2En4PkP/AR6mI GfEmicXCwO5mW5wCAdo9QfuwPQ+KoyTq2nFWcrqbf39mSFEiZVFxHmKZHs6F882NIpe/k3fvLq8/ /ueKZOs1+XD1kXy4OT+7/IURxsnN/fkZIxnJqIA/wojOaMYlKbKS6pzc7M7PMvKA/349P/uSvH85 PKYrnuzbVCY/k+u0SJrNY1VvyXtKPsNala50skuZSKotUKpkf0Fw6feUsQQWREKvaPo/cvPb+dkn UANVCeTzQtJC+PK/JMTbQD5dfyTEM4p5Rs1ZkmtFmew5XVWHVCW1UT5d5ck1qvxKmFhSiSlNeR4y uiA8e2NXqalk4a5FQ/hbhpSMCsfpzzrNE3RC1+yf0JKfgT6jqUjkolI5o1keslpUSrylVF5QdRIn GYCPE57TTI7481jKDHU00KOZzjgI5Qz/i1yR9mF2+TPC810GPlmvCvjUcq3wg61XjOEDX6/yYEHB QwYPZbFeCfzM+4UMWOBe5ihY5n7JLfNMrgvkwQpLiTu0/V4UHstBhu43lh/WqxK/Z/az1Hajx6Bk i2qXnyzluNCz0B+sTGA143/vdDNNVWkdhtvFRCP/FLRvPBpV+La877VwhxfVMw/VXMCICjAiZjAi sowWOrDiGHbfDEQyxhVZZZRxBljPGYcnUmjz0dbnZ3/9RJ5ggyc+78UDpEAeVYBCkAZBjKArS5Ao idKQmIgUkuoSftU5yDHs7n86P/tjxqYisEkGSXd0iyo4VUfpdjGgymloetxUQUuXPW8wYUPqlUlN MCM/YCre42K1Jbi8hyx+jw8EcsoBHwx1081lEpNEJM3zUAiJ0hZU8pD2M5aHaxTx8f0NgXxscnJ3 QOWaJ1x/iLHjkkPsh+wOzoZn+wCGbfcPr1EW4MhMhSyqVCdG8B1oQrBKGaZ1B+vmqUlZljjVQMCu BnnjUaH0u4l0f2UDefkFv+2AYZ2WltXBnvm8mjJXiPBATfAIuC66o1BHbhnOxhj1iOe8fcZyEWPi ACQF5bxn8g2ZGPWrp7RXuzGAeUVPGtbdfoeGom3muzH7fjxN5SPw8zWQge9jHhJYZUIdot4UwgDC p21rFP4NZBqlm7beAbBrUyaN8v0xgmJVh5g3wGn37sno3tV3qbREgMneDuPRtgLt760DI56AJJVN DFhFaQUtVEj7jzGgezEKRbZxTbU8UQScEQIjOKPdBg+hipqQcyQ+jT9AdapLiwFigNOZgPnuENBs LUaW4cdLKkXP6iuitsbjN95pvDAcw9K4Z9fMxPGIPNk7ukEUY0g25nu17QzpvYuV1mTF+t9qC+ws 7m1umiSBkbexKAdcI6jhF8MPJRgo2S2QTGC7DZ79E9nsnw4tCLMZgwzmtSDTrPlQhLW7wUrf6OVT ZAJrpT3FHrr3qYjCljEJ+8JtMZ8zVkBlDGk7dI2w9eUxtg9AIk+VIQtsnQNawG1lzzGyB5IgjA+n 8S+gQ1c+LbYLmYDkufmSbDaxbdDYq0AELOOOqBwNgaFCnQBd4NTt7CiEaY3lpkj5WxabAR1vBqTW lKmTRqlsgUspqWKRlsKUtUMqXDWEXzEC36zFrCjRWwFvrxb7LQnGGLYIYkwAxXziNvEcq/2KljqU Z83AmiGD0MrtL6jOv/VQLIKU0rSushrJt7j4Dx7FxiqK+3JXgyO5E+KBTU43WuClohPlUZfqa+r8 YNR4saVJuQoX4wawgKpwkmSHgVzTsuhpd5UpqK8LCYJNtkRhwDQa5pO+gP7GEV/dw96VkaexqoT+ GvuxoQ0xpbuxSRe7XeW8YRLsCQjlhZniA92OEVr/eEZpddsAIHbYaRRBpzHPW0AfDYEZ8u76UtDr 1nXNrdHRN8kh1dmFderIgstf1HTWkNAaFmUg8F0mCrme7jyaUmQupjsXOtccrwQC2u+DGx7nKvMy 6pSi3DUDD/tqLJhhk7mDQAiywyDP1P6+o/crOc5C8fwLOT4QHYUIoJfrkLaKpyDBqZxQd83O5C9w cmQTIOVkdWDimlMnyJEOVXgONnXcunb54EA9Rp3t8BvEMiqqQNE2hmktsfUNpNOU9Ty8uuGGoAuX pUCTuVnhu4uE9mv6ZscjJUztrl664oAtSVt3Xd1dmMbuu7kBLMcmDRJZrNJzqkXINZrDoLTkOqTd Vq812hU7LI63GEW4J9ZEcGgF+IR/E1Occ26y1imKc66w1Qho97a9deHTmrvSoZ/Fam/x2pjjG0Nq bHej+Bcgjk3E/Z3gHAnzTu+Qx6HX7dPhrvnRIIi85ns2o/T9M3S50rbzRitkORIMVf0wSnH9dRWt ldCnTNHV15KopQ6TYLB27Ve335pJ5pUYXA6D5XbfdX+nUWypkrIy5ISDijkOtG4MFftUtYBv++hN Iao/k7sgAA+nJ2S8OsH2ydfDMtuarBzrBQQDn0/2xXAuWIktb0B761yGQ/lKTcarAY4j+o6N8+64 AlMXZlEpGc6zgSbhiDb2EoMytjAtX9Q4YDCG94xexD3bVrRyvUxfy4LbCnMLgddlTVsPVxKxMYJp mwd8ScsTwNHblFFfoXOazxX/Yy5HrzI8LpBTM1cZTD0YS8zglsa2d4MbjZEXtkTEZkWNDUrAPZz9 78f7ue3QS5r+0CaUcHjH8La14+AKkO/jfGwnPEjFmnwhGOa8QLnpZWVhUV6jblijYuXV+CDgFM20 0OBLEdI249XX7OyEv2KM5QklN6c2aAI6DjEM6FgOcrziqLY1cTnHVnCIGz8Pxxszg/pYzYRwLEKZ 0XyVlTRnIe2YNp6HiWmaM0zjHuuuTMk+TXzB8R4zoLXpstu0ppuyLr9z9enW3M/uXZPSpxJix+kx 1TB3mVw/HWqgu4veERY44Z2kqxQZ3ssEtJPbtTCcrNd+mEE3HL682roMG8Vx+LeyZqMz+gICe4gy ZBBNgbw8ol1OXkevPD2VRYm3zadwca87L3/9LxSRh+787Nv5GV7QQx+PPAUFlUrCMo4vO7WgUpIN 8L28rg8VZ+RqT/6Ab8PuYwlqRk8FHaUukZ0o7VtZ5CAMh7c0zuN2l4yW+dxb3nCykdhIRmmNxP8D EE649A0KZW5kc3RyZWFtDQplbmRvYmoNCjUgMCBvYmoNCjw8L1R5cGUvRm9udC9TdWJ0eXBlL1Ry dWVUeXBlL05hbWUvRjEvQmFzZUZvbnQvQUJDREVFK1RpbWVzIzIwTmV3IzIwUm9tYW4jMjBCb2xk LEJvbGQvRW5jb2RpbmcvV2luQW5zaUVuY29kaW5nL0ZvbnREZXNjcmlwdG9yIDYgMCBSL0ZpcnN0 Q2hhciAzMi9MYXN0Q2hhciAxMjEvV2lkdGhzIDIwOCAwIFI+Pg0KZW5kb2JqDQo2IDAgb2JqDQo8 PC9UeXBlL0ZvbnREZXNjcmlwdG9yL0ZvbnROYW1lL0FCQ0RFRStUaW1lcyMyME5ldyMyMFJvbWFu IzIwQm9sZCxCb2xkL0ZsYWdzIDMyL0l0YWxpY0FuZ2xlIDAvQXNjZW50IDg5MS9EZXNjZW50IC0y MTYvQ2FwSGVpZ2h0IDY3Ny9BdmdXaWR0aCA0MjcvTWF4V2lkdGggMjU1OC9Gb250V2VpZ2h0IDcw MC9YSGVpZ2h0IDI1MC9MZWFkaW5nIDQyL1N0ZW1WIDQyL0ZvbnRCQm94WyAtNTU4IC0yMTYgMjAw MCA2NzddIC9Gb250RmlsZTIgMjA5IDAgUj4+DQplbmRvYmoNCjcgMCBvYmoNCjw8L1R5cGUvRm9u dC9TdWJ0eXBlL1R5cGUwL0Jhc2VGb250L0FCQ0RFRStDYW1icmlhLEJvbGQvRW5jb2RpbmcvSWRl bnRpdHktSC9EZXNjZW5kYW50Rm9udHMgOCAwIFIvVG9Vbmljb2RlIDIxMCAwIFI+Pg0KZW5kb2Jq DQo4IDAgb2JqDQpbIDkgMCBSXSANCmVuZG9iag0KOSAwIG9iag0KPDwvQmFzZUZvbnQvQUJDREVF K0NhbWJyaWEsQm9sZC9TdWJ0eXBlL0NJREZvbnRUeXBlMi9UeXBlL0ZvbnQvQ0lEVG9HSURNYXAv SWRlbnRpdHkvRFcgMTAwMC9DSURTeXN0ZW1JbmZvIDEwIDAgUi9Gb250RGVzY3JpcHRvciAxMSAw IFIvVyAyMTIgMCBSPj4NCmVuZG9iag0KMTAgMCBvYmoNCjw8L09yZGVyaW5nKElkZW50aXR5KSAv UmVnaXN0cnkoQWRvYmUpIC9TdXBwbGVtZW50IDA+Pg0KZW5kb2JqDQoxMSAwIG9iag0KPDwvVHlw ZS9Gb250RGVzY3JpcHRvci9Gb250TmFtZS9BQkNERUUrQ2FtYnJpYSxCb2xkL0ZsYWdzIDMyL0l0 YWxpY0FuZ2xlIDAvQXNjZW50IDk1MC9EZXNjZW50IC0yMjIvQ2FwSGVpZ2h0IDc3OC9BdmdXaWR0 aCA2MDAvTWF4V2lkdGggMjQ4Mi9Gb250V2VpZ2h0IDcwMC9YSGVpZ2h0IDI1MC9TdGVtViA2MC9G b250QkJveFsgLTExMTAgLTIyMiAxMzczIDc3OF0gL0ZvbnRGaWxlMiAyMTEgMCBSPj4NCmVuZG9i ag0KMTIgMCBvYmoNCjw8L1R5cGUvRm9udC9TdWJ0eXBlL1RydWVUeXBlL05hbWUvRjMvQmFzZUZv bnQvQUJDREVFK0NhbWJyaWEsQm9sZC9FbmNvZGluZy9XaW5BbnNpRW5jb2RpbmcvRm9udERlc2Ny aXB0b3IgMTMgMCBSL0ZpcnN0Q2hhciAzMi9MYXN0Q2hhciA0NS9XaWR0aHMgMjEzIDAgUj4+DQpl bmRvYmoNCjEzIDAgb2JqDQo8PC9UeXBlL0ZvbnREZXNjcmlwdG9yL0ZvbnROYW1lL0FCQ0RFRStD YW1icmlhLEJvbGQvRmxhZ3MgMzIvSXRhbGljQW5nbGUgMC9Bc2NlbnQgOTUwL0Rlc2NlbnQgLTIy Mi9DYXBIZWlnaHQgNzc4L0F2Z1dpZHRoIDYwMC9NYXhXaWR0aCAyNDgyL0ZvbnRXZWlnaHQgNzAw L1hIZWlnaHQgMjUwL1N0ZW1WIDYwL0ZvbnRCQm94WyAtMTExMCAtMjIyIDEzNzMgNzc4XSAvRm9u dEZpbGUyIDIxMSAwIFI+Pg0KZW5kb2JqDQoxNCAwIG9iag0KPDwvVHlwZS9Gb250L1N1YnR5cGUv VHJ1ZVR5cGUvTmFtZS9GNC9CYXNlRm9udC9BQkNERUUrQ2FsaWJyaS9FbmNvZGluZy9XaW5BbnNp RW5jb2RpbmcvRm9udERlc2NyaXB0b3IgMTUgMCBSL0ZpcnN0Q2hhciAzMi9MYXN0Q2hhciAxMjIv V2lkdGhzIDIxNyAwIFI+Pg0KZW5kb2JqDQoxNSAwIG9iag0KPDwvVHlwZS9Gb250RGVzY3JpcHRv ci9Gb250TmFtZS9BQkNERUUrQ2FsaWJyaS9GbGFncyAzMi9JdGFsaWNBbmdsZSAwL0FzY2VudCA3 NTAvRGVzY2VudCAtMjUwL0NhcEhlaWdodCA3NTAvQXZnV2lkdGggNTIxL01heFdpZHRoIDE3NDMv Rm9udFdlaWdodCA0MDAvWEhlaWdodCAyNTAvU3RlbVYgNTIvRm9udEJCb3hbIC01MDMgLTI1MCAx MjQwIDc1MF0gL0ZvbnRGaWxlMiAyMTUgMCBSPj4NCmVuZG9iag0KMTYgMCBvYmoNCjw8L1R5cGUv Rm9udC9TdWJ0eXBlL1R5cGUwL0Jhc2VGb250L0FCQ0RFRStDYWxpYnJpL0VuY29kaW5nL0lkZW50 aXR5LUgvRGVzY2VuZGFudEZvbnRzIDE3IDAgUi9Ub1VuaWNvZGUgMjE0IDAgUj4+DQplbmRvYmoN CjE3IDAgb2JqDQpbIDE4IDAgUl0gDQplbmRvYmoNCjE4IDAgb2JqDQo8PC9CYXNlRm9udC9BQkNE RUUrQ2FsaWJyaS9TdWJ0eXBlL0NJREZvbnRUeXBlMi9UeXBlL0ZvbnQvQ0lEVG9HSURNYXAvSWRl bnRpdHkvRFcgMTAwMC9DSURTeXN0ZW1JbmZvIDE5IDAgUi9Gb250RGVzY3JpcHRvciAyMCAwIFIv VyAyMTYgMCBSPj4NCmVuZG9iag0KMTkgMCBvYmoNCjw8L09yZGVyaW5nKElkZW50aXR5KSAvUmVn aXN0cnkoQWRvYmUpIC9TdXBwbGVtZW50IDA+Pg0KZW5kb2JqDQoyMCAwIG9iag0KPDwvVHlwZS9G b250RGVzY3JpcHRvci9Gb250TmFtZS9BQkNERUUrQ2FsaWJyaS9GbGFncyAzMi9JdGFsaWNBbmds ZSAwL0FzY2VudCA3NTAvRGVzY2VudCAtMjUwL0NhcEhlaWdodCA3NTAvQXZnV2lkdGggNTIxL01h eFdpZHRoIDE3NDMvRm9udFdlaWdodCA0MDAvWEhlaWdodCAyNTAvU3RlbVYgNTIvRm9udEJCb3hb IC01MDMgLTI1MCAxMjQwIDc1MF0gL0ZvbnRGaWxlMiAyMTUgMCBSPj4NCmVuZG9iag0KMjEgMCBv YmoNCjw8L1R5cGUvWE9iamVjdC9TdWJ0eXBlL0Zvcm0vUmVzb3VyY2VzPDwvRXh0R1N0YXRlPDwv R1MyMyAyMyAwIFIvR1MyMiAyMiAwIFI+Pi9Gb250PDwvRjYgMjQgMCBSL0Y3IDI2IDAgUj4+L1hP YmplY3Q8PC9JbWFnZTI4IDI4IDAgUi9JbWFnZTMwIDMwIDAgUi9JbWFnZTMyIDMyIDAgUi9JbWFn ZTM0IDM0IDAgUi9NZXRhMzYgMzYgMCBSL01ldGEzNyAzNyAwIFIvSW1hZ2UzOCAzOCAwIFIvTWV0 YTQwIDQwIDAgUi9NZXRhNDEgNDEgMCBSL01ldGE0MiA0MiAwIFIvTWV0YTQzIDQzIDAgUj4+Pj4v QkJveFsgMCAwIDM2MC4wMSAyNzBdIC9NYXRyaXhbIDAuMiAwIDAgMC4yNjY2NiAwIDBdIC9GaWx0 ZXIvRmxhdGVEZWNvZGUvTGVuZ3RoIDI3MTM+Pg0Kc3RyZWFtDQp4nN1bW2/cNhZ+H8D/QY+jYs3w Il4EdLeImzbIom3SeIA+bPfBO3Ecb2Y8ie3dov9+v3NIzUiiZMdjOc4mgBWRInkuPHdyPh7MZCGF lEabqi6Mk4X2srg8PZj99k1xcTBTxdluiKxMZ8jbbw5mv2KMUNoWfxzMnjw/1qY4u6IZzw9mhSr+ XcyUcqKqCqUqYV2xPpjVTriAtheAuDqYHR/MZlpr4QsaahWNUXUtDA2q0oiPWyyUx4cc0aMF4P/o CmVF7YrFW0IdM4BD5YQBQK2D0HWxWNNKZwnFf8xf/1wemvn3T8vDar4o/1ks/n4w+2HBdN0DppJe eDUG8xWBvNxcb8pDPV8S5M2KnkXp54vTq/LQza+LxeYDDYtfNmf0/uee+AUhqy5LDLYMLAG/Q47e 7/PSzl9enJYOGB3a+Y+MR1nNL9H/R6nC/CQ13pSE9KGW86Py0POYa5rBj9XpBVY4Rd+SKHpPj79M RYEykCIzRsGCMGZMNxFDO39BjzXj+gF9RMH5JdrKM4oXDepP6PGMplL36uTPssYCpp7/hCZ1neGP t6jgLzSaOEWLnoPQEJehkcSd38u9KPaFy0RKKeFsYaVQwWcUQ4qVYqgnjF81/08ZsEeHkbx183JR EoKWEDeKBBGyha7zi1JJ/kBTi6el1TRExeVo0hv8xZ6j/SkKvU0k02CLSgmPveyTdAKuXkZeTgYQ +libMYCvSB0J6rIkcSXZhSJCJ4lu2IgTvH6IfPJgL14SeqwnRsYFNvThvDTzi2bo1Z5Cn4uANMKp whgYtBx9VlvSSlY5epz/95S0s55fn6+38nF1TSTGNgnt1W6fm8mx5/yimAzx4IWpxxAnLJYE/8NU 8OCpBPmqYXhvz1en0EuS54l0U1sYVAujFOi/PrwXa1KzD2VIVodaAwo5MS66Fj7H5bjR+K15WLJd 2w94RZ68A9w78uNQM5nbqKdjULLAIkIJlpbnheFGKYQwAl6LtAABxRKrP3mxPjk7Rd+zTfFrClaa eEMGYW3ha1GpGhgJELMNWj7uhmkpguGQAwFKsE0HwbIUkWBHq12rom9LGpw6lLC6aKYCJE/dItAM BjvM7jNCG72bmlq7lVNHAhynNki1ccbgd8RCYhrwb/i3iq87xq66fF41c1Y8P4V5msSIWV0LQJe1 qDVzWrcYbWTD6A4/1q2OhHWXlT2s+0R1CR7jR2JXl5UZp7sb0d2k3h6+i7KgKHL9aihCqCxJ7yNN fRGvvQieO2xoQu8uyNYoUqBwt/Ab5qjnbxUTV2lS3L49ONpwpLt9rE7JncJtkqNCALekx3t6IAAL CMAOOVCpU9/Rbyn6VPO/8tueBrTnqSqh/SjGXRj8iWdgMypKg2ARsbVgb41/bXOzFy7wX7QRxgqZ 4wJ33zDuHbHs/Iq4V7yB75bkZHyLiTzqfMOfmL8DYanS8Jmk846kdp3kFMmNVGTMV9sRyN9ASbsD gmLiCKRtwDjr4MClNSNvM9DVhBYNEQeCP2YkEk0oCTuTWnJE0DJpOpk0WtDVeBggcnnWJ389gGtG TJ/YjBsZv/ocbdskiIEgWQrF6+esp4+DT9R+VTP/SCSTdDQdstlJ2WtoK2zEKw3NOxiGlmyxUtCw 6sOaWCgaNxeFwvHTE2NbMlFt4wkaSsLQxXE9gON0/Oj4pc8M+B6m3nCpI+BpVWasfmFTX/yLLdAm Zck3m/1JrDlMZwBSUJkBpNiXRAeyjxntugLSm/QI8AMkNK6wnhXJSWYPvGzjEWBmopNmVMZGHrdq azOHVwX995bqZq06mhXaJTfdGg00LH2F+MSqm4buu9uGV6YZnhbnglwcnVtIjVfE1phcI4sPwte+ QNohg9rD9WU5I4yQBcLYPJPnMS85u94lq5smnYnNWA7Z7EogUyVX8O9khL0mkodqiYqLiUHvWUwc gmmEpI13FSU0n5rQVf2yw26ztcOKyJoR3CNwwXoaZOl2tXWmaSfJLvJnG0RdMwJICpoRTSdvfmcR iiPjKCoIay4IE/kgnv5ZY5KddrBCOSMgYFUVNFMvBaJRANWQNRVjUugNm+qfT69PsBXRUncB7Vsd qkmEQZISVSve6lW1udYWuOpDhZQr/HVrQWsyFfSSCkBTiQHJAWJppPcyF4OskjdVQl+RvgMqtPAO Gf2diZPY31B4qNdA4eBuxc3J+O0g/g4OJAyWCh+I3YaSLmialjnUXvpBAWJFRjmGKFUd5UNTrWTd 6jBk8TUVjhEc2krIGi1FldfUWpKOa5b95jMyj7Cbmlq8Mg9OHYoyn+1USTW+7crc4sEJcPzcIBWn dnDe5eRb9/jVUHVMmAeKD3wtnKwjKdwRsIM6rgFfGwhQJAzmKbUSKdCQ7WdDaWozNbbSyokU6qAM vi7SVO+56p1WTq1l5CgAN58TlmlqB+fdBn01xAxFQZgcNAfbCI9j0NQOg4T1hqM8142FpFONT71/ LNR3TVaQGwywDgNxx8vSzlM85NJhxWbrkmKbfdam5acmqzYjCgBPLdxzHmF/+x0w+w5mkv7+Np1l RhCgC+eEH4D56QFRQamVSRle2kAqm0+ygW5o/xSk0+nHC2Z7UgXyKh9LVzrHakFIff9q4l1TBonI /TYtFkVam4ZkZRqtG940aL/7YhIQLRwVjxEI5zv2E8D9QJx8dkQxKNKQfe80jO9fXYMp90hDOpH6 YZMTKK3unBOEKs8HfJYPKA6QSGg4SKrpFBXRRUy1FXEzT8p3Ef/4hFFPgNSJsisq6yMIaGSSS8IT yKSRkioakPFg83sPjySUDVLkznOkHsYJGKRDbhQmi2OMzd/fZvnThiGlf8ANC2Ywj3i0DasonaNS 0gBSC8CD3QdiEYvbmbmzyLo2dHGrssxM6wSy6fsws+exiJvQSKw7KP6PGAdBiCqWniFxfFDDbLRP IcsemrArCiHW1ZSAairjjlR9Yr6JHGlnTLHTkKQbjOn4sFtNqH0wdWSq8tjxce2nspxmfFb7OQJz D/uppX8wb6f42tYXs1tsPDXCAvsgxlMFOYHlzDlJelirL4iTyWgqSmtzpD6H0RwBffOmZQchje00 iiwmFWilnXLrUlXJiLr6craupjKMNnyU+HkOQoy2AjnACMxPd3RRyegqwPjpRvJAzowP+ti/UMOn s47cZ+pQSJTodJlsO79W1Lvkc1e+xEM3TdKMeNume/dmGc/sK9d0NKfBceq21Sy77Ugg49QGlzaq k94do0ti6eoYXSSCieFbepoqc61T9e4tvR0/1k0rYd3lYA/rLlFdgsf5kTjdZuUAp7sb0ZrXXrM5 nd/K0/8zJXc67s/LR+mmqbRUCs9uvZYmHoXxlWk6KqNL0ZfpGn7nhMxPfvsVHPB6xK4/9O1XOAPS ldsOb1oGiW1N0MLIaGw657Nbi8Q+hn5YkuLz4VFs3Ky9Za0YsYWbRg0Xaqq7H91ayb9biChtSzWV zEo1Y34Vm1lT0vcwfpUvPrbypuy49/Gqs+xiFVS/ys9EX3MmSx7W38fD9vPr6GJHYB7T7xu2P214 z6ff48W9RmSMvU1mpNJbmfEa3NcapDsuxtuqJTMqk5mbpbS2Q79pu0FKFfx8W0j1JwKUyu9BpAci dCVRat2CaTKY/wOKv6UNDQplbmRzdHJlYW0NCmVuZG9iag0KMjIgMCBvYmoNCjw8L1R5cGUvRXh0 R1N0YXRlL0JNL05vcm1hbC9jYSAxPj4NCmVuZG9iag0KMjMgMCBvYmoNCjw8L1R5cGUvRXh0R1N0 YXRlL0JNL05vcm1hbC9DQSAxPj4NCmVuZG9iag0KMjQgMCBvYmoNCjw8L1R5cGUvRm9udC9TdWJ0 eXBlL1RydWVUeXBlL05hbWUvRjYvQmFzZUZvbnQvQXJpYWwvRW5jb2RpbmcvV2luQW5zaUVuY29k aW5nL0ZvbnREZXNjcmlwdG9yIDI1IDAgUi9GaXJzdENoYXIgMzIvTGFzdENoYXIgMTIxL1dpZHRo cyAyMTggMCBSPj4NCmVuZG9iag0KMjUgMCBvYmoNCjw8L1R5cGUvRm9udERlc2NyaXB0b3IvRm9u dE5hbWUvQXJpYWwvRmxhZ3MgMzIvSXRhbGljQW5nbGUgMC9Bc2NlbnQgOTA1L0Rlc2NlbnQgLTIx MC9DYXBIZWlnaHQgNzI4L0F2Z1dpZHRoIDQ0MS9NYXhXaWR0aCAyNjY1L0ZvbnRXZWlnaHQgNDAw L1hIZWlnaHQgMjUwL0xlYWRpbmcgMzMvU3RlbVYgNDQvRm9udEJCb3hbIC02NjUgLTIxMCAyMDAw IDcyOF0gPj4NCmVuZG9iag0KMjYgMCBvYmoNCjw8L1R5cGUvRm9udC9TdWJ0eXBlL1RydWVUeXBl L05hbWUvRjcvQmFzZUZvbnQvQXJpYWwsQm9sZC9FbmNvZGluZy9XaW5BbnNpRW5jb2RpbmcvRm9u dERlc2NyaXB0b3IgMjcgMCBSL0ZpcnN0Q2hhciAzMi9MYXN0Q2hhciAxMTcvV2lkdGhzIDIxOSAw IFI+Pg0KZW5kb2JqDQoyNyAwIG9iag0KPDwvVHlwZS9Gb250RGVzY3JpcHRvci9Gb250TmFtZS9B cmlhbCxCb2xkL0ZsYWdzIDMyL0l0YWxpY0FuZ2xlIDAvQXNjZW50IDkwNS9EZXNjZW50IC0yMTAv Q2FwSGVpZ2h0IDcyOC9BdmdXaWR0aCA0NzkvTWF4V2lkdGggMjYyOC9Gb250V2VpZ2h0IDcwMC9Y SGVpZ2h0IDI1MC9MZWFkaW5nIDMzL1N0ZW1WIDQ3L0ZvbnRCQm94WyAtNjI4IC0yMTAgMjAwMCA3 MjhdID4+DQplbmRvYmoNCjI4IDAgb2JqDQo8PC9UeXBlL1hPYmplY3QvU3VidHlwZS9JbWFnZS9X aWR0aCAyNjkvSGVpZ2h0IDQ1L0NvbG9yU3BhY2UvRGV2aWNlUkdCL0JpdHNQZXJDb21wb25lbnQg OC9JbnRlcnBvbGF0ZSBmYWxzZS9TTWFzayAyOSAwIFIvRmlsdGVyL0ZsYXRlRGVjb2RlL0xlbmd0 aCA1OD4+DQpzdHJlYW0NCnic7cEBDQAAAMKg909tDjegAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAADuDY3bAAENCmVuZHN0cmVhbQ0KZW5kb2JqDQoyOSAwIG9iag0KPDwvVHlwZS9Y T2JqZWN0L1N1YnR5cGUvSW1hZ2UvV2lkdGggMjY5L0hlaWdodCA0NS9Db2xvclNwYWNlL0Rldmlj ZUdyYXkvTWF0dGVbIDAgMCAwXSAvQml0c1BlckNvbXBvbmVudCA4L0ludGVycG9sYXRlIGZhbHNl L0ZpbHRlci9GbGF0ZURlY29kZS9MZW5ndGggNTEwPj4NCnN0cmVhbQ0KeJzt2ll2olAQgOFomLkM BkHjwBBbjYCNA9gOGKdk/1tqQGlvOHY2UPUt4T9QD7fq6QmhH9XgetSi/gxSvVKjKMGwHMdDw3Ec k+egemQpWI4XJZkQogBCiCxLAsfSX0fegpeI1jCapmkBYprGi67IQl7jX4yshay+WJ2e7TguII7d 67aaGslq1MqBUWd4STVe7bfhxA9COIJgMh44HVOTeeb2o9SyD0MgjbY9nPyeL+MEjjheRMHI7RiK mH0a9xiK0R34s3i93aWA7DareTjsm6pYTo0sBieqZn84Xa7Tj8MJjuNhv0misdPSJY65x5A0yx5F ye5wOn/CcTkf0z/zidtuyJUYzngGM4bvPYyxSo/nyxccn5fTfr3AGAWMQcEYFIxBwRgUjEHBGBSM QcEYFIxBwRgUjEHBGBSMQcEYFIxB+TkGwJeuxzHwDbTyOr7ZA3sd/9gm0Xvldfy6NwlmyWaX7uFI d9vVYlrdmxQbNWfkR4s4WcGRJMtZOPa+b9SKXWvz1RmM/CCcAhL677/crqnne/hauXrOt/Ca0er2 Hdd7g8PzXLvXNnUicOUW/nqfIciKbjQtqwWKZRoNlYjl+LxfqwiSTBRFBSW/3RH5bHrSMbIhyrDX iy4BkOKqi2WeKxd/t2M/BprrtV/1+PF2ElmH5X+HoAh98xfL2dJ/DQplbmRzdHJlYW0NCmVuZG9i ag0KMzAgMCBvYmoNCjw8L1R5cGUvWE9iamVjdC9TdWJ0eXBlL0ltYWdlL1dpZHRoIDQwL0hlaWdo dCA0Ny9Db2xvclNwYWNlL0RldmljZVJHQi9CaXRzUGVyQ29tcG9uZW50IDgvSW50ZXJwb2xhdGUg ZmFsc2UvU01hc2sgMzEgMCBSL0ZpbHRlci9GbGF0ZURlY29kZS9MZW5ndGggMjg+Pg0Kc3RyZWFt DQp4nO3BAQ0AAADCoPdPbQ8HFAAAAAAAzwYWCAABDQplbmRzdHJlYW0NCmVuZG9iag0KMzEgMCBv YmoNCjw8L1R5cGUvWE9iamVjdC9TdWJ0eXBlL0ltYWdlL1dpZHRoIDQwL0hlaWdodCA0Ny9Db2xv clNwYWNlL0RldmljZUdyYXkvTWF0dGVbIDAgMCAwXSAvQml0c1BlckNvbXBvbmVudCA4L0ludGVy cG9sYXRlIGZhbHNlL0ZpbHRlci9GbGF0ZURlY29kZS9MZW5ndGggNzI0Pj4NCnN0cmVhbQ0KeJzN ldmSokAQRZVddgS0BRQVXBAX3BtcQND//6XJUrtB2zYmYl6mnk/cWzcrM6tU+i9OOT/vIAzDcAId HMd+JUEDJ0iKphmapkjyN7KM4ThFVzheEEWBqzAU8QoET4KkWV6uanqtpldlgWWQ5E8OpxhOUuum 3e502lZdlTiGwp8VwZSs8LJu2O5w5Pter23WZL7yDIIayfByzXKGk/lytVpMPbdZU3iwfuQwgmIl 3XJGweoz3EXhOvDdpi6xKEyRw6mKqJnd0XyzO8ZJEu+3C9+xNOnRGeRoTvloD2eb6HhK0/QUR5vA 6zSqPF0URHKS3uyNl4Bl5/M5Ox2j9aTXrD0IQgqaBTkv2O7jFHHnFJznIKiwBUGwZXjVdPxFiOQu lwsIxtFy7JqqkEeGpyArYq3Vn613cXpG3CVLk/1mNmiBMbxK/hSsVLeHwWafpFcMCR62gdf+kFFp co5TGp3R4vOQZF9cegwXfrehcN8XRFXhq4YzXn5dDzhIAhd0TJWnySIHMcYrVJXLncviaDVBQR44 QbPcyTqCqnxzyW497VlaHvjO9V5xTV1E3fUXnPDM/ZUv5HAhR/ycAzg656B+VaPrF+uSpXEIdTGq xbq8r/M39+u7DR/erYT6QID2m652qK3ufQAx+qgs+YiUy9DO6IKLEBkDeE4TZHt9tkL/oT6Vr21/ E7z16c222PhgzIia5UDiQwJgliUHSOtayLa4PdAcyXW7P12Fx+SUntB4zAb2B+qq4qSjQRJUo+PN 1uHhGMeABV7XUMWnjXCdc1E3u950uQ2j6HM1GznWzzm/TbCsm52+P5svFsF40LV0maOfsNse4iSt 0XIGw5E3cG1Dh4VFvlxYNCsoutFs2XbL0KsiS//ErkUkYE9KiqrpmqpIAlTuxZ68S1IMy/FwWOYq 9npBow1NUBRFU7DGCeztxgcUR78C9vYHKeU/zVvo388f3V2NOQ0KZW5kc3RyZWFtDQplbmRvYmoN CjMyIDAgb2JqDQo8PC9UeXBlL1hPYmplY3QvU3VidHlwZS9JbWFnZS9XaWR0aCAyNzYvSGVpZ2h0 IDQzL0NvbG9yU3BhY2UvRGV2aWNlUkdCL0JpdHNQZXJDb21wb25lbnQgOC9JbnRlcnBvbGF0ZSBm YWxzZS9TTWFzayAzMyAwIFIvRmlsdGVyL0ZsYXRlRGVjb2RlL0xlbmd0aCA1Nj4+DQpzdHJlYW0N Cnic7cEBAQAAAIIg/69uSEABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA8G6LFAAB DQplbmRzdHJlYW0NCmVuZG9iag0KMzMgMCBvYmoNCjw8L1R5cGUvWE9iamVjdC9TdWJ0eXBlL0lt YWdlL1dpZHRoIDI3Ni9IZWlnaHQgNDMvQ29sb3JTcGFjZS9EZXZpY2VHcmF5L01hdHRlWyAwIDAg MF0gL0JpdHNQZXJDb21wb25lbnQgOC9JbnRlcnBvbGF0ZSBmYWxzZS9GaWx0ZXIvRmxhdGVEZWNv ZGUvTGVuZ3RoIDgwMT4+DQpzdHJlYW0NCnic7ZrpdqJAEIWjrM2OCKigEvcdFfcVl7z/K6Uakolm 4sz8mDOZA/09Aeeeureqq3h6IhAIf5NMxHd/xX8EqJGNIKq8A4JQNAPQFFElJpOlaZbnEUIsQxNR nrBvsgzHi7KiKoqIOCIKLhKKAUU0w7RMQ5MRS1OZVPBYEfANhyTVsJ1y2S2auow4hko8cTt5IAuW RJB1s1StN5sNr2TqksCzSQd3k6idfKFKJkMxnKAYxUq90x8O++1n1zY0RUo4oigKYIcvmyxECYtE NV/ymv3xdBaMB+1apWSbRsLJ5XKaKuN+QmV/9g2LJM1yntvD6WK1Xi2mo16r5lXKCcd1nKKdj/pJ 9q5QMnGU5OxKvTeerXb7/W67mk/9Qa/X7XaSTbtV91xbl3mWunVP3IJVo1AB38zX+xA47jfr5WwW BME00UzGfr9dcy1dvJvGonQVVdPxwDfL7SE8A6fweIBq2W4Sznq1DEbdWsmQeeajULAkvKhZbq0z At8cT+fL9Xq5XLAuUC8J57DfrqbDZtlU0K0mkCVQJW6964MkIVbk5eWKuaSA8+m4nfvtqq0KH4GC wwQpeafW9XGUnCJJMNdUcDmHu8W4U7U18VYTmhU1u9oaBj+qJEVcL6f9ctL1CveaMJyUK3gdf745 4Cz57q/8tzzURNRxncxIndx4B/LEhWkNCoXkSSxK3IrLDRhhIWRJ34nnE3jq6Ha5jjvPLjydYz3S Mp/sVgHMJ5Yq3MwnkSi8FA9t0HuOaZxjnfs5Fr8AI/vkS15rMFlAqISn9Lx3Jv6gUy/bn947749A xShWm/0J+GePJ9554A/6qX0Xv+3rBTkKlVGwXG/Ssz9x4/2J8Hl/El26aE6QNNN5Bv8E82AyxHu2 Qqr2bJ+XjzhUWB4vH6uN7tAfxftYPR37WP7Rfe8tVHKW4zVarYbnWLqcjr093lA/uO6BfxgOyVq+ 6FaqlRKWJA33HepX951oLYtLRc9btpXXyR3wwz9IUlRNVSSB3IsjolLheCQIiGOJJDH4hxyaYSB7 aIoikrwR/aaEo+c3PksZf5A8BAKBcMcreKITLA0KZW5kc3RyZWFtDQplbmRvYmoNCjM0IDAgb2Jq DQo8PC9UeXBlL1hPYmplY3QvU3VidHlwZS9JbWFnZS9XaWR0aCAyNzYvSGVpZ2h0IDQzL0NvbG9y U3BhY2UvRGV2aWNlUkdCL0JpdHNQZXJDb21wb25lbnQgOC9JbnRlcnBvbGF0ZSBmYWxzZS9TTWFz ayAzNSAwIFIvRmlsdGVyL0ZsYXRlRGVjb2RlL0xlbmd0aCA1Nj4+DQpzdHJlYW0NCnic7cEBAQAA AIIg/69uSEABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA8G6LFAABDQplbmRzdHJl YW0NCmVuZG9iag0KMzUgMCBvYmoNCjw8L1R5cGUvWE9iamVjdC9TdWJ0eXBlL0ltYWdlL1dpZHRo IDI3Ni9IZWlnaHQgNDMvQ29sb3JTcGFjZS9EZXZpY2VHcmF5L01hdHRlWyAwIDAgMF0gL0JpdHNQ ZXJDb21wb25lbnQgOC9JbnRlcnBvbGF0ZSBmYWxzZS9GaWx0ZXIvRmxhdGVEZWNvZGUvTGVuZ3Ro IDgxNj4+DQpzdHJlYW0NCnic7ZrZkqJAEEXHZgdZRARREFFxV0RwbxVQ//+XpgrssW3bjnkaJyjO cz0QN27dzMrk16+cnJycv6YAefVH/E8AOd4SclmuAEEwjADgOJarkgBMguEkzTAMTRE4louSuoSg WF4QBb7I0ASwys/HUeANJ2hOlMuqWpGFIkP+YJVCmjtY5iFIuigp1bppGnqlxLM08fa9VaAiGI6D 4CGzDs1woqI3Wo7TsQ2tLHBP7k+iCEExLMdxxYwjiLJas7rDyXQydJp1VeJo8pv6AxWhGI4XJVmW yxmnouqG7YzceeB7k17LUEtFlsIf7g/IHZLhJUXT63XDzDgNy+70J16w2mzWgTvsmNUyz1LEF6eA gg0kkTWj2e72+hlnMByOJjN/tXk/7PebpTd2mjXlIVRgeaK4kma0eiN35s2zje8HwRIqcozC8LBb +eOeXVOkYiJK4ZNNCJov11uDqb9ab7YZZ7fb7Q+HMIriOA6P+03gDpJQAUl7rwkjVExnMl+D48eM E4aJHqfT+XyOo3C/XcxAqGgyD9q3P9cHxgkralbPXeyOETiMAECP8+VyPp/i8ABEGXUaWim5Pp80 4STN6s+W72GcHEeACwSIEgFRlh5wSkVib0ZJNak2B95qH53Sw8gAnBKB6+P2bV2GRsk1uSSiHHfL 2bBVU0Ci5JpcUp+ARHEHtl5+8AmqeRJHx91qPnJMVYItfgH1ugNccopgxI4dqyrz93WHYEUV9Cf+ +h2t/iQJ2KU3chrVssDe9yco9rHxtY+FLVvjo2W7aZK+d8x2f+x6CL13QGuyWwfTftLa30mC4Lt4 OgugKgdwb+aTnl2vSI/DNmgUNp2fGKjMTxbr7XYNunrH0hWBpYivk2r05mzd8cxfBPPpoA2jBBTh x5FsMuEnaXTmsc3ucOJOR13bgG+/+yj5JAqcUqMxty9Kim61u12nZVYVGCX4k71Xut959fLlH5Du d/R6w2rU1NLTVcZNFgSAe8CiWK5omiqLoAQ/pCt6fOyLRUkSeTZZ7bz6k15PIgrJsCzD0Pl/BVfS pSdJEkCRJ6tiBEn+ysGgILlLblzz9tWfkZOTMX4D2sUUfQ0KZW5kc3RyZWFtDQplbmRvYmoNCjM2 IDAgb2JqDQo8PC9UeXBlL1hPYmplY3QvU3VidHlwZS9Gb3JtL1Jlc291cmNlczw8L0V4dEdTdGF0 ZTw8L0dTMjMgMjMgMCBSPj4+Pi9CQm94WyAwIDAgMTY1LjExIDk2LjgzXSAvTWF0cml4WyAwLjQz NjA2IDAgMCAwLjc0MzU3IDAgMF0gL0ZpbHRlci9GbGF0ZURlY29kZS9MZW5ndGggODA3Pj4NCnN0 cmVhbQ0KeJztV8tuGzEMvBvwP+w5QLYi9f6CAL21PvQDij4ObYGk/w9UK43INffQ3GwEAYwEOx4+ NKS49PP59Nw/n/rHLW4NmdrflPLy8uN8ouTXkhcuawq0/BaA/Eq5LMR5pbTxA4W0FGrfsTx+PZ98 WmOJgjy6tZkknvbyjADNQqAQVnJxgYeYOgER8NToyAAAsoPpdfKN/PN8+v5wPn14urBffvxtB+4H dWt1LaXl89P51P59XN7esS+7CM10GIUluOXl2xDlP19vrZFdavLs2iJZfeKVPsHtk8eTqgNAAkcj TjqKU67EqVfiVCtOvRKnXImTbE+8sSNdtoq1QhXfHeUwT1XjAEaivzbPoftiAXzegFwUcJ0hQMti 86EA0WDECUDU20ZvPjZiUwfR07BMeRL9YESx7Nk0oAoDhZZg8KFAxNXku4rOeYgUZ3RfByC+04iu QqPn2j8AeaSTBQjOADHs63sv0cnHfnFJbjKP8SjKow1V6DlfpRQF1RMAPnaAKx2wyt84er/0EEZa D1cmVfXXk1S1qTfjkrMC1BmaNWqqDCIMIXPpbxo9j06DMNu1G5YpyaUajCiWjHpIL3oet0yCwYcC cTAi3VV0Hm1TZNziyuioTCO6Cl2GqyIDOdsJHcgAMe7rey/Ryad+7Zxeu/5mCaI82lCFRnQtRUH1 BICPHeBqB6zyt43e9vdH6uvEXPp4rm5fHpY/bbnRBdRthC1DgR7bTfKxbv4u/VfA87b78G6FtN7m Miy+ABw89RUEryivL8K6B7aTj0ZhOWglw8C4OwI6D7gvAZ4Mg+3IZBlDdWwnCmBdYTYMCsbHEagm D2LD6I0Q9ybOnFYB6KFOoZgyojUBoFEwZzSPaVItIGfBnFEgD4DJMNj6OAKiOvLQusx2kMqhid/b 5L1NXtEmfcHBC9DLaza7PaArFUsnVDYMDNMjkLRGfcXwzjDYDmTW3yZj91EAy5BqAwZ54+MIFJMH kWHEXa90oAqA0yoAPdQpFFNGtCZzyxAA73PNAwx1OgE5C9Z8BfCriJ1hsPVxBER15KF1me2QTK+8 t8l7m7yiTdqi8g9KOOhYDQplbmRzdHJlYW0NCmVuZG9iag0KMzcgMCBvYmoNCjw8L1R5cGUvWE9i amVjdC9TdWJ0eXBlL0Zvcm0vUmVzb3VyY2VzPDwvRXh0R1N0YXRlPDwvR1MyMyAyMyAwIFI+Pj4+ L0JCb3hbIDAgMCAxNjUuMTEgOTYuODNdIC9NYXRyaXhbIDAuNDM2MDYgMCAwIDAuNzQzNTcgMCAw XSAvRmlsdGVyL0ZsYXRlRGVjb2RlL0xlbmd0aCA4MDc+Pg0Kc3RyZWFtDQp4nO1Xy24bMQy8G/A/ 7DlAtiL1/oIAvbU+9AOKPg5tgaT/D1Qrjcg199DcbAQBjAQ7Hj40pLj08/n03D+f+sctbg2Z2t+U 8vLy43yi5NeSFy5rCrT8FoD8SrksxHmltPEDhbQUat+xPH49n3xaY4mCPLq1mSSe9vKMAM1CoBBW cnGBh5g6ARHw1OjIAACyg+l18o3883z6/nA+fXi6sF9+/G0H7gd1a3UtpeXz0/nU/n1c3t6xL7sI zXQYhSW45eXbEOU/X2+tkV1q8uzaIll94pU+we2Tx5OqA0ACRyNOOopTrsSpV+JUK069EqdciZNs T7yxI122irVCFd8d5TBPVeMARqK/Ns+h+2IBfN6AXBRwnSFAy2LzoQDRYMQJQNTbRm8+NmJTB9HT sEx5Ev1gRLHs2TSgCgOFlmDwoUDE1eS7is55iBRndF8HIL7TiK5Co+faPwB5pJMFCM4AMezrey/R ycd+cUluMo/xKMqjDVXoOV+lFAXVEwA+doArHbDK3zh6v/QQRloPVyZV9deTVLWpN+OSswLUGZo1 aqoMIgwhc+lvGj2PToMw27UblinJpRqMKJaMekgveh63TILBhwJxMCLdVXQebVNk3OLK6KhMI7oK XYarIgM52wkdyAAx7ut7L9HJp37tnF67/mYJojzaUIVGdC1FQfUEgI8d4GoHrPK3jd7290fq68Rc +niubl8elj9tudEF1G2ELUOBHttN8rFu/i79V8DztvvwboW03uYyLL4AHDz1FQSvKK8vwroHtpOP RmE5aCXDwLg7AjoPuC8BngyD7chkGUN1bCcKYF1hNgwKxscRqCYPYsPojRD3Js6cVgHooU6hmDKi NQGgUTBnNI9pUi0gZ8GcUSAPgMkw2Po4AqI68tC6zHaQyqGJ39vkvU1e0SZ9wcEL0MtrNrs9oCsV SydUNgwM0yOQtEZ9xfDOMNgOZNbfJmP3UQDLkGoDBnnj4wgUkweRYcRdr3SgCoDTKgA91CkUU0a0 JnPLEADvc80DDHU6ATkL1nwF8KuInWGw9XEERHXkoXWZ7ZBMr7y3yXubvKJN2qLyD0o46FgNCmVu ZHN0cmVhbQ0KZW5kb2JqDQozOCAwIG9iag0KPDwvVHlwZS9YT2JqZWN0L1N1YnR5cGUvSW1hZ2Uv V2lkdGggNDEvSGVpZ2h0IDQ4L0NvbG9yU3BhY2UvRGV2aWNlUkdCL0JpdHNQZXJDb21wb25lbnQg OC9JbnRlcnBvbGF0ZSBmYWxzZS9TTWFzayAzOSAwIFIvRmlsdGVyL0ZsYXRlRGVjb2RlL0xlbmd0 aCAyOD4+DQpzdHJlYW0NCnic7cEBDQAAAMKg909tDwcUAAAAAAD8GxcQAAENCmVuZHN0cmVhbQ0K ZW5kb2JqDQozOSAwIG9iag0KPDwvVHlwZS9YT2JqZWN0L1N1YnR5cGUvSW1hZ2UvV2lkdGggNDEv SGVpZ2h0IDQ4L0NvbG9yU3BhY2UvRGV2aWNlR3JheS9NYXR0ZVsgMCAwIDBdIC9CaXRzUGVyQ29t cG9uZW50IDgvSW50ZXJwb2xhdGUgZmFsc2UvRmlsdGVyL0ZsYXRlRGVjb2RlL0xlbmd0aCA3MzQ+ Pg0Kc3RyZWFtDQp4nM2Vx5qiUBCFWxGQpCQFVIKKWVrBgAlJ7fu/0tTFVhGnw2IWc9f/V1XnVLhv b//LKz3eT1y5jMErl79BEYVVCIKER+AVrPwFijCcICmaYVmGqpKA/jVqqYRVSIrhBFFuNGSR5+gq UYEKXsEyTtIc39A6hmkabUXiWQrIIgh58Spdk1S9NxxPJmO722mKHEVWCoUCVyGZmqyZg+m763mu M7ENReRoshATBaRqkmYNHW+7O+x3G3c+MFSBreIFEAKyomqNnPXuGITh+eh7QCo88xwSOILmm8bA 8fZBFCdJEp58d2p35BqFY7kqkWJWavWmrn8CLk3TKDxuFmNLFegn5SWMoOpNc7TYHMIk/YCXxMF+ 7Qx0mUNV3shSCSQLGgTcnWLgLpdLmkTH7XJsKXWawO4hkYes1Lbnq30AIHCXjzQKdt6spwk5OVdv GsZosT2GScYBmJwPkLstcQ+HoMugWbEmSz+IbiCEPG4XI71RpyD3LTNGMLzahRKDKH2AJ385NppZ kXm3Wz0o8Rynl8tn7hiKnFgqz9zVZKDU7jsrZE4O3K+m3bwaBHIg2lk/g+f9agYg+wK+/xLs/yoi K15rfBKz96ZdVWCIZ/BXqsFHQevOwMe44KOp5H1EnakrJnTmFD1aGEJnhnojm8hvex0eNs6gI+d6 nU0PV5ye+HV6PucRNds/Rtk8XjNDiVmrH7twnXBj+J6bcHAxm3DqCYSdYUS0M1uQAysDbh+ynSmu IZwnCKkP5t4uCOMkjrMt7LflWvWu+TM3LIOomsP5Cu31OTj43sw2msWAyEqc4gTVGszdjb/b+evl zNYVHi7Fze0HCbdM0gx74ixddzkf93W4PU9KHmNOcWKzbdnD0WjYN1sNdPdeuEw5QbF1WWl1dL2j NcXa9T6+gugAVWm2zouSJPKAVXOr/4pmN5y53vCvrz36FXACPRxH9/vrvyZjf/xn7uyP/9a/eX8A m6OTrw0KZW5kc3RyZWFtDQplbmRvYmoNCjQwIDAgb2JqDQo8PC9UeXBlL1hPYmplY3QvU3VidHlw ZS9Gb3JtL1Jlc291cmNlczw8L0V4dEdTdGF0ZTw8L0dTMjMgMjMgMCBSPj4+Pi9CQm94WyAwIDAg MTY1LjExIDk2LjgzXSAvTWF0cml4WyAwLjQzNjA2IDAgMCAwLjc0MzU3IDAgMF0gL0ZpbHRlci9G bGF0ZURlY29kZS9MZW5ndGggODA3Pj4NCnN0cmVhbQ0KeJztV8tuGzEMvBvwP+w5QLYi9f6CAL21 PvQDij4ObYGk/w9UK43INffQ3GwEAYwEOx4+NKS49PP59Nw/n/rHLW4NmdrflPLy8uN8ouTXkhcu awq0/BaA/Eq5LMR5pbTxA4W0FGrfsTx+PZ98WmOJgjy6tZkknvbyjADNQqAQVnJxgYeYOgER8NTo yAAAsoPpdfKN/PN8+v5wPn14urBffvxtB+4HdWt1LaXl89P51P59XN7esS+7CM10GIUluOXl2xDl P19vrZFdavLs2iJZfeKVPsHtk8eTqgNAAkcjTjqKU67EqVfiVCtOvRKnXImTbE+8sSNdtoq1QhXf HeUwT1XjAEaivzbPoftiAXzegFwUcJ0hQMti86EA0WDECUDU20ZvPjZiUwfR07BMeRL9YESx7Nk0 oAoDhZZg8KFAxNXku4rOeYgUZ3RfByC+04iuQqPn2j8AeaSTBQjOADHs63sv0cnHfnFJbjKP8SjK ow1V6DlfpRQF1RMAPnaAKx2wyt84er/0EEZaD1cmVfXXk1S1qTfjkrMC1BmaNWqqDCIMIXPpbxo9 j06DMNu1G5YpyaUajCiWjHpIL3oet0yCwYcCcTAi3VV0Hm1TZNziyuioTCO6Cl2GqyIDOdsJHcgA Me7rey/Ryad+7Zxeu/5mCaI82lCFRnQtRUH1BICPHeBqB6zyt43e9vdH6uvEXPp4rm5fHpY/bbnR BdRthC1DgR7bTfKxbv4u/VfA87b78G6FtN7mMiy+ABw89RUEryivL8K6B7aTj0ZhOWglw8C4OwI6 D7gvAZ4Mg+3IZBlDdWwnCmBdYTYMCsbHEagmD2LD6I0Q9ybOnFYB6KFOoZgyojUBoFEwZzSPaVIt IGfBnFEgD4DJMNj6OAKiOvLQusx2kMqhid/b5L1NXtEmfcHBC9DLaza7PaArFUsnVDYMDNMjkLRG fcXwzjDYDmTW3yZj91EAy5BqAwZ54+MIFJMHkWHEXa90oAqA0yoAPdQpFFNGtCZzyxAA73PNAwx1 OgE5C9Z8BfCriJ1hsPVxBER15KF1me2QTK+8t8l7m7yiTdqi8g9KOOhYDQplbmRzdHJlYW0NCmVu ZG9iag0KNDEgMCBvYmoNCjw8L1R5cGUvWE9iamVjdC9TdWJ0eXBlL0Zvcm0vUmVzb3VyY2VzPDwv RXh0R1N0YXRlPDwvR1MyMyAyMyAwIFI+Pj4+L0JCb3hbIDAgMCAxMDUuMDkgNzAuOTA2XSAvTWF0 cml4WyAwLjY4NTE2IDAgMCAxLjAxNTQgMCAwXSAvRmlsdGVyL0ZsYXRlRGVjb2RlL0xlbmd0aCAx NzI+Pg0Kc3RyZWFtDQp4nK1SQQrCMBC8B/KHOQvGbNIk2xcUvGnfoPVgD9X/g8m2FhURhMAykNns zGbIpNUkdZCyJjFjRWpwG7TaWkMtB4cQjGOPUSuKhi0hkRDXTFhv+OXM84VlIhMXrc6bulq7rnce w73s7ThiRXI4dlqBsEc1x17ioTmYgpHiezxl3LXghJCDO308+Gv3R1v8mlScZvTBi9+y3DIwPrcn /je/akJ1lHr5gg/VY3lVDQplbmRzdHJlYW0NCmVuZG9iag0KNDIgMCBvYmoNCjw8L1R5cGUvWE9i amVjdC9TdWJ0eXBlL0Zvcm0vUmVzb3VyY2VzPDwvRXh0R1N0YXRlPDwvR1MyMyAyMyAwIFI+Pj4+ L0JCb3hbIDAgMCAxNjUuMTEgOTYuODNdIC9NYXRyaXhbIDAuNDM2MDYgMCAwIDAuNzQzNTcgMCAw XSAvRmlsdGVyL0ZsYXRlRGVjb2RlL0xlbmd0aCA4MDc+Pg0Kc3RyZWFtDQp4nO1Xy24bMQy8G/A/ 7DlAtiL1/oIAvbU+9AOKPg5tgaT/D1Qrjcg199DcbAQBjAQ7Hj40pLj08/n03D+f+sctbg2Z2t+U 8vLy43yi5NeSFy5rCrT8FoD8SrksxHmltPEDhbQUat+xPH49n3xaY4mCPLq1mSSe9vKMAM1CoBBW cnGBh5g6ARHw1OjIAACyg+l18o3883z6/nA+fXi6sF9+/G0H7gd1a3UtpeXz0/nU/n1c3t6xL7sI zXQYhSW45eXbEOU/X2+tkV1q8uzaIll94pU+we2Tx5OqA0ACRyNOOopTrsSpV+JUK069EqdciZNs T7yxI122irVCFd8d5TBPVeMARqK/Ns+h+2IBfN6AXBRwnSFAy2LzoQDRYMQJQNTbRm8+NmJTB9HT sEx5Ev1gRLHs2TSgCgOFlmDwoUDE1eS7is55iBRndF8HIL7TiK5Co+faPwB5pJMFCM4AMezrey/R ycd+cUluMo/xKMqjDVXoOV+lFAXVEwA+doArHbDK3zh6v/QQRloPVyZV9deTVLWpN+OSswLUGZo1 aqoMIgwhc+lvGj2PToMw27UblinJpRqMKJaMekgveh63TILBhwJxMCLdVXQebVNk3OLK6KhMI7oK XYarIgM52wkdyAAx7ut7L9HJp37tnF67/mYJojzaUIVGdC1FQfUEgI8d4GoHrPK3jd7290fq68Rc +niubl8elj9tudEF1G2ELUOBHttN8rFu/i79V8DztvvwboW03uYyLL4AHDz1FQSvKK8vwroHtpOP RmE5aCXDwLg7AjoPuC8BngyD7chkGUN1bCcKYF1hNgwKxscRqCYPYsPojRD3Js6cVgHooU6hmDKi NQGgUTBnNI9pUi0gZ8GcUSAPgMkw2Po4AqI68tC6zHaQyqGJ39vkvU1e0SZ9wcEL0MtrNrs9oCsV SydUNgwM0yOQtEZ9xfDOMNgOZNbfJmP3UQDLkGoDBnnj4wgUkweRYcRdr3SgCoDTKgA91CkUU0a0 JnPLEADvc80DDHU6ATkL1nwF8KuInWGw9XEERHXkoXWZ7ZBMr7y3yXubvKJN2qLyD0o46FgNCmVu ZHN0cmVhbQ0KZW5kb2JqDQo0MyAwIG9iag0KPDwvVHlwZS9YT2JqZWN0L1N1YnR5cGUvRm9ybS9S ZXNvdXJjZXM8PC9FeHRHU3RhdGU8PC9HUzIzIDIzIDAgUj4+Pj4vQkJveFsgMCAwIDEwNS4wOSA3 MC45MDZdIC9NYXRyaXhbIDAuNjg1MTYgMCAwIDEuMDE1NCAwIDBdIC9GaWx0ZXIvRmxhdGVEZWNv ZGUvTGVuZ3RoIDE3Mj4+DQpzdHJlYW0NCnicrVJBCsIwELwH8oc5C8Zs0iTbFxS8ad+g9WAP1f+D ybYWFRGEwDKQ2ezMZsik1SR1kLImMWNFanAbtNpaQy0HhxCMY49RK4qGLSGRENdMWG/45czzhWUi Exetzpu6Wruudx7DveztOGJFcjh2WoGwRzXHXuKhOZiCkeJ7PGXcteCEkIM7fTz4a/dHW/yaVJxm 9MGL37LcMjA+tyf+N79qQnWUevmCD9VjeVUNCmVuZHN0cmVhbQ0KZW5kb2JqDQo0NCAwIG9iag0K PDwvVHlwZS9QYWdlL1BhcmVudCAyIDAgUi9SZXNvdXJjZXM8PC9Gb250PDwvRjQgMTQgMCBSL0Yy IDcgMCBSL0YzIDEyIDAgUi9GNSAxNiAwIFI+Pi9Qcm9jU2V0Wy9QREYvVGV4dC9JbWFnZUIvSW1h Z2VDL0ltYWdlSV0gPj4vTWVkaWFCb3hbIDAgMCA2MTIgNzkyXSAvQ29udGVudHMgNDUgMCBSL0dy b3VwPDwvVHlwZS9Hcm91cC9TL1RyYW5zcGFyZW5jeS9DUy9EZXZpY2VSR0I+Pi9UYWJzL1MvU3Ry dWN0UGFyZW50cyAxPj4NCmVuZG9iag0KNDUgMCBvYmoNCjw8L0ZpbHRlci9GbGF0ZURlY29kZS9M ZW5ndGggMzg5Nj4+DQpzdHJlYW0NCnicpVtZb9tIEn434P/AR2tgtdkkmwcQeJDLu1lsMLNZA/OQ 2QfGpmUilOSQsh3Pr9+q6ptiUzIGAWKJ7i5W1/HV1Y4ufo/evLn4/P7Thyi+vIzefXgfvbs+Pbm4 yiKeRNd3pyc8iuEfj6qYxUkWFXHJ8uh6fXoSRyv87x+nJ1/PosX/out/nZ58hL3Rx8/vo8ghzD3C SZTkLM6maOdlzPJEEmdxFSdRzBKO/6e5iPrV5OMvyMCbOObp5bKAn1V2KfAHv1xyjh+Sy2XuPRDw IYYPZXG5TPFnrh7EQAL38uKyKNSWXJGgBYZG+fFymXkPqstlhQ/eSS40qRhoJ97b48tl6XJR5YZv JFCm8vflO7UulkyaZWof/5hezsg88WSeTsg8KwqWJK7MJ9T4g0Qe80REy5jxhKegJZ7Ap6io6Eff nJ788Uu0gQ3O61P1elARvI+JOIf/i4yTEsuSiRLo5BUrkyhLM1aV8OsqJ2J3v5ye/GfiRNlR5pln KcuSPft8t8jOmm67WGZnzwsB51ymZ3Xf4A/6vIOH9/jbZlHqJ/BtuyjOHuSHZXLWbVcvEX64WfBU PtrgL4cdbujrFvbSA9o7LDiXpO4MhX5Rjd8XAWct7WoXPJZb27qLDIkGHuVyF7JDxKJFftb8fMBn Td+u6af/crZQJ/sDqZqjbfThv3x+//YaWXJVjqIdyzMpWVEq8yBR9Ft9gK2UhRJFR3Rv4XkztKuN ZpNeXQ/40dm+wpOh/JOzYWhu9WI63CMtA0nRSe6RYH8eoRC6Wj9tenrwrLnA5d/12da1VJMU603g gGkhWF74B+zo3XQGoCBI4A4X0cLYBZB/WMgF0izmpcgzxjN6CRh6jKZ78xXPP72LxzG5pruLdpB8 WlRis0YWmo3maKATo3w2+gjKZOCxtbYe+I08/XnmjRbcDJFVmTo8boUzFtZncvketClUX67+ZyFh i4QVwj3RgZghHG8fCVNUFRPH0MhnaJQZK3OjkDQn8fKxGi+uxB7OlKyKRwRw85s4LbLL8fY9mOIx oJ27+2vQA3lcsDz3177VALJ+RPvsLGSQHul7iy7Z0tOXaKu9Sns9Oh56voKHYfvY35DPktb/PAsw kwBYZ8JnBt8j3buvb3baHPp22Bk4wyVDyCbSCh3wKFmkWcKy1F+7Da4Fjx7J2KCmY9BDo53BFcI0 zSzZU5vxICLxDbfr2HGrZaH9VX29NYog4WwmmCISs1giCgIHyUSrvB1f89TewoEIwVT8+IJx6jN+ ArCPJBhC3Nss9BaEiXqHluR5/YNUKvCyMxw7sQe+WeD9vthfkDugSTjqRBsMSf8IaQ48G7VsT4hZ h/bOPxfnIe3EglWeZBRezsJDMQMPQkCKMoaH5BXw4BJ4PTzY3YfhwV37VuM/6sDCO5pqu4VfAIB3 r0cQSmFUPDHhfv2AKRXlJtaYVyFmk4ozIXxm+1obWCgOppyzrPB3LYNrBeMj0WE4JEPHDw8mOWqf Gun2iIV0GJly3DQyigIIwi8f5XG5wjiZMpJ7kCW//10+Mc50ETLOMker9BhDX+kP+XkWo1HLDf/+ +AEljWksOFLAIJKCFe6245wHUnqWetuO8J1yxneg1EiKse+kr/Adl8DrfcfuPuw77loTWgcEVUhR u0Y/uTNo97xAYLyVGXmuULTHQHKjMzHlaPjrb7qG2Bnb60ye3tx8DzkLFEhQKh11EnQsPjp1J6OC yYcRrFuTA9Kjq09Xv0U/gOVHHXUeZx0R3yKO4yitUgq/7lqZ+Te6XpC5ogcbmK5LKAp4keBj5Qaj gcgwow8yu2fM1YwxAwLlqSKShRw2h6R2tPYV5u5se52lz71vbOnu2t8WXFWutsrpKfyvCeyxmKK6 VJo3Wv+drB4a+IjVh0oLAibJSxaP2At6kEw1dotMG6dyqgZqPVj+EmG8alaDBNs7ZHfn12J+2f5N v2in2eyoSEJvU1X02D0myvNalt+P2oeHRheeB0A7A1uoKoPyQHMq89TM3pmIS0vRT4MZKBcxVD0e fYpTth41LwmWldjxqXwakKsrsXy5vtZUpAYeqKzTcEVF8QYfkQejeajzhUAsYeXoZUGLKSE2pv5a qYJV+4Rv2+huxoTEZD69sTHaojau3T5HZEmrVU/dlFW9k+cKgAcUJR7XR2agWc7S0tt3RBTlcRh5 MpBfko7DqDgeVzwCrw6jzu6D4OKttRUq6kRIVJe55jpEJs9YPCITSvN4XiC4e2s9wMCEjd4vw80T Yl3TD7bVd2uKUxuQVOAGHLR29Ow1Tcjgxy6cO03A7kXbaLvW2Wbd9rJN4/XmcF87rv10pUTY+wSv xM5YcwhtQBiicqUAucjN3mFCeV+OCalHw4bkVjUigZ2uC7a3eJGR43o0ZBKN3bEaQLdwG5jddhi0 fRB6WSFv7CLj3sMQ9bqttbPxykVjt5WF4vxLamyL686RkN9uVcyttzbOwBMxBc7KftB2DqlBJKwS B9VA9YNhieJKY1rGMgVqfiJG7VS2VJytG5S9buMBL1h0yQ7qUztgkbbdQDIVqoggYnCfu2DSxlNM 8Ly1trSxupvt7nm7uya8HOr0svCX/7mA05wH2StjdHefPdvrDCWiJVaPwfPvwzGfgeO0xFGGpJLP J4Le2lcAtrPtdVg9974xVrtrj0wEQ76fsGxE0EmldJ6nQHEvzwtkAim1GT2iIzwtFFbsdOxfNdoS mr7WiCqZsN2sJlhug6DJttxX+imoeb3DvsapZqX7pnIEw1bwgZ1HQ7um/Kk7CB5Jil1Qp06aRs2A ErIUDcClEdQXpChoAO5aD+8Fzp26l/NouweIfTDVz1haHPf+hBeMp/5aT84XGGvgqEECecUSPjrA XKwVFBGkKbtgf2AeB44gO9vCaWxjDtD+pawA0xoH2PP5TDirBOPHySirCmwwe2tpgNdetYfsKK4g S3QrD+nJoS45h/UY/t1tjtLNoKivb9ut7Iu8LPSsE4W8DtpkBSl04VMO6jSGyJH6a1szpOxUb9ow 47adQ0aSYe/EIegn8KEBVVJwFvv7jkngk3DESCvwjanKZ59KOkOlqDC0SipXEpVJr5MzY+W3zaAT pOEcqx+QZGcSD+zF4xfbjw8pMkkEi4XPgt8uNSNuqzNOg1kaHkhfqgeqo9FRG1P2+1XrN+V52XTJ rHPjoV6bkU1L/eduPAZVzmkyyNkMWIs4B//UyL9XUytwaAaiPMGVhSDNjZfty9xV2LbgaPqDX4ct QGAxrkIoJWLRJ4MyajqulGzG5JKNiYkMSB6SMNXNlHkvLKd9nR3R2bb/3qxmXmwixlBtR4E11Xt6 sGSOTvZ4LrMKeND+1AK2BxgUUjkDJH9iRMFUDSsmVG6artYg9R2Ab15O72jSzONCiJDFKWap3jHn 3TibceNUsHIqRdunMjP5ThPOePF3wGB3ry3UtoHhyw+jD9sKjownWUtNXSBuu86OPqWDPuC9lJv2 zhi59vh9o5ddPLq6MuDNAtfzUX/AdP2zXdMUZo2H8XOy2val3IKdeJo32zjHklXK0AKPnNT+NM1p Fr010+F13XXGfqfdxwy7p6dmP7TnNo+6qSYDnMGKFcVVir3KiEOFWoaltncKXxm2TEY6MvmdUkk+ lQc1tW6J3GveR0Y0mnodkDaOJ0odBHvZegNfrTEtDiRiHrh6Asqd5NtaEzKr7+0sXzdnnzqd7gsM N9QvbJ2xoUHm4C2XPMYpp3foeWefuaKSFJQvH0NlZpKd5FClaV4+7RoyY9lNz7SBU8wL9PrN4etQ tlemeFjvPUEf5GWF2Zm3uL41kwaLX0/BsilJ+R6JA9MFe5VsOTFhgDArFzvxC78KSmRINua618gO JMoGijaZgxTYxKJ7hxb6KObt9PCt3ywOu1EGdYHwikRTi1KaIL3SudBoDX9ozEWOxpTjT20deXfb VCpDYbZugcF+TcScaQ9dlNHhwQzLg02eJEag8ji/13p61rY1Sh5dfoLjJ1Pb2bIOs6eXqKOO3Soy 9x58zYc4FXGMvXuP05CHC0gKxmtDuhMxtoP8tVfAkS7O5jWepljsurd8dEu287DSC+9WpcvgBadl NhswtAmbHF2R2MpsSllD3W50lmldNwge5F230ruEPsdTY0oSzx+HhVNTT1qGyTLlS5cZvXn/pfMC 5iUThQEQG4hC5TLekvA2PVODwGBNZ6aUtjGpLVyhSOFeQnFqFKDTdQhErlW3MyfL50HHbZ3LZNd0 3cdS9doek8BEacpqYNgrpG+UlqMqaJVEAdvH1/H6kPjBkaqJvoOOy/75UtsIIwN2rg5J4LKJ/1HD gexvCQPevcJcGsU+zib2b9UalaxeNAnq7dMSdQXadDB3VqRmjkm11cEhBIbWpHJM8157oiuK+5lL QLz0iYwmITutcc8uMACqoQraN40oUHjejELHSxt/7jS2yPoFzN8DNdKvsn90BRRBMOmS1z091ufT pZnLSzjQCv81hEdl5tYIFxX+SYNqsm/MtRdTqMtPj9qrJf71gzZqN72ezFrpdy+b+RTJ46JetzcY Hkw9LC/uPrXbXnvHqAJTl0eFuTuq5+nDYi/HkJ73qK3V1A7qHkW73ms0zNtyJliqr77VfV/LTASr gAbSktzxFTvjs3I1l1yd4EL2JPRd3Gjycv8yl4NBae/G97a6c6KaPD9NmHVdnf4OoG1MPet3uGQr Jtj2TRNW+Kf2/0CkuUPmZGy9MSNChWGmazIv0zRmhcnDpO51Z6g4JtWausxGytzokjb0lxbY+U+E x8F3edVFG5zTr96L7Ep7UimjdBRFQZi0d0tnOb6x7As01KtPoawoU49V1+IpjresYYj+qdMibNb6 6nU3GlajBUk0DOtfq4jneA/CiYl9fbdIHQy0/ZZ76rKS+4YuSggg6tNUpYItdcQobEWmuS8vB9em VbaX6jm5yTJTeglfUcxSn5PwdcYMrzN6a83lXdVqIfee6KraP0fA8oUGN/TnUQZWaaf9yyjTQJMn xN5PrYd2wUm0VlXM9Z+ZfT17+w62frn4gLJ6+99/yrJoS50er0luwEQayq3nWWSWNkm2odJPw30z Nr9z8o3tCg7zEsnbN8E2kkjwcqR3jIk4c6djvg3+FhvJGWwq09U3LYW6lTnwKGl/8+uvwPOvl3MF E5qsy5SqDWeVUeasKLO5U6DyVwYs5Blkez04LM1YkvuU99KB/wMKqZ0ADQplbmRzdHJlYW0NCmVu ZG9iag0KNDYgMCBvYmoNCjw8L1R5cGUvUGFnZS9QYXJlbnQgMiAwIFIvUmVzb3VyY2VzPDwvRm9u dDw8L0Y0IDE0IDAgUi9GOCA0OCAwIFIvRjUgMTYgMCBSL0Y5IDUwIDAgUi9GMSA1IDAgUi9GMyAx MiAwIFI+Pi9Qcm9jU2V0Wy9QREYvVGV4dC9JbWFnZUIvSW1hZ2VDL0ltYWdlSV0gPj4vTWVkaWFC b3hbIDAgMCA2MTIgNzkyXSAvQ29udGVudHMgNDcgMCBSL0dyb3VwPDwvVHlwZS9Hcm91cC9TL1Ry YW5zcGFyZW5jeS9DUy9EZXZpY2VSR0I+Pi9UYWJzL1MvU3RydWN0UGFyZW50cyAyPj4NCmVuZG9i ag0KNDcgMCBvYmoNCjw8L0ZpbHRlci9GbGF0ZURlY29kZS9MZW5ndGggMzcyMz4+DQpzdHJlYW0N CnicrVvrb9w2Ev8eIP+DPq4OsSKKoh6HwEDqJEXv0GuRM9APzX1QbHmtVrvrSn7E//3Ng6RIaSlv gCLIei2RQ85wHr+ZoaO3v0bv3r39+eKnD1F6fh798OEi+uHy9au3n/JIZNHlzetXIkrhn4jqNEmz PCrTKimiy93rV2m0xY8fX7/6fRPF/4su//X61UeYG338+SKKHMLCI1wFCBe1TOqcKScSXiYqLeCz zEU0bI88/Ewr/yc+U+XmAJ/15h4+1aaNz8p0M9LziJ439LmPz4p8cw2ftX7+Cz3hWbf0BOYW6WYA ClKPuTD0C0OBKfMsGFlITb+j5zCmNDRHRyrIvOE4K7IkUy7HvgT9sSophD/24PDDu/wvfK/08wez M+DhivZkJHJ8BSlFksrTdiNlnsjaH3tDq/LaLI/gbKWSqvRn/wTzKs0LSLAwkmVpsmT7EL06T7Ly xJ3XZVLMuPxI632DNYrNHe3Dnj9wwTvYkRz5+d7Rl8ZoXGH2ak7l+Pp5XSd55q//z8BYlcpkRT2O moeVbZbIKpJVksPLuoiG9vWrm38cscrsJHMvyjqpv8/cpUN4Tg2UOWPvAbtLJXy9+n0j5mf29pNa bKdK6nRGACe/S2WZn8+nL7gRaQ5sOLPDiiJSUJTCH/u+j0ELwdTkZjzEFZpYvhmu2hEeZeg68k3z 2MbkV8Ad7OOcv3X7WKF95PgNP2ORos7kmxbtdtPsYrLaDCiqDQ2ht1Fc8OMbeEyUrkNqnbLxurtt 4prJNBFMp29EDKmO7R4XvuZVgPCXTSw3TzCOd4Tfur7HoTSmvWkHGneIS94gSyEWAvhWTHi4Dyl9 AXo4k+VZaGyZJaLyx/YdSBVEprd7fKLRLZUmRaYnfsUJfEojCYA2rBlx5XoV6ye7Ozi0Fu2ZT4l4 3dL53sPgobmBkTitwynmdPFMiX7X9P3zlxjevwk68jxJlb/NVTvKV+xIgrEv7Cj7DjtyCXy/HU2z l3Z0ZFE0KeUtCuulRX5+lr1LhXp/fpbDzx8U/6zTFJzZuRAwJpXnZxKepVkqik/0n57xOBojyg9M x8yvLlIhUvj/kWjR+Iyen9fOsLI4V7xCAcwrGJxV52fwnRbCBev3Lwskw+CpfInMNfyIRDKIo2U5 k4jLiXpH6+NOpWKmA2ql6kTIGaWTzhKRxWzmCgopk2p28O23O/ASbd+jHRSbrbUwslZ2Qgp9EP6G QZMcEFnLLfubgEsrU4rq7lq75lu3Q7Mkm96FpuaZSMrKnzo04GPZ547sDxV77LYb2CuuuxUgmRl7 td6CvUPLvqXzfSMPKh13PhyAcQ4fTb9ll9kZJ0172QWhoiyStPZ3ETwkiPqV8seS37sjdq+6G9zB c2g2+N/i1JVKleSzlSiQjA/AKTnfP1pkE2Vxb3ytjkQl6YEvShSkhKPq4sqRG5xXydTa/oA/MDqB kw0dfkrBxt3UGxZ6XDPVUBTN83wxddU3qxXfnBaJqua+WX6Hb3YJfL9vnmavYxyV+2MvLZRp4RBI bp8PFpasRmAB+QzY25Lc0N3FK9MqcILyyLRu12otIaX6fElP4eBN4A1aS16SS1uTwdtP9cIT5jV5 N3cabhyMVILrwfCP3/q56RxzqgDa8/K0U8jqIslmu3XxyJmGV2N7zd5Tw7AbAxEn/2GP7MbY2PAE DDQDprsbi+a6ob1Cc+wOmKYGN5YX9UI9GA32DW7o+QWfqWoxZS50hF8tCL231t2jP28pdrRXf8YF M/AXbO/BsPSgoXI+X75GkO3hWGvj9PbGrmfloHXnbgpORniR8Vmo7f2fE+R2lgTlKzZJMGJBjl76 bK+6jyLsPlRZJvIUGuUKDbDHoljaNSH8AYVH4XiKW03PBucpEAVuYZ53o8XCt54IOR+4NcoZzAWy XGAhw9tbKBfIcpVI6Y/FXODanA3tsj88jeZYmwHUhRm8tpnWjc2+0KxImfpj0Qh+2x1sxtO/QYVz cQoQRQLMNy7UgBWBMNqhGzljwNcsIMdA120kr+Cn5s0x5NE/CTISUmSMfbwELsbqT+O+2k1qRHZF wbS1Ku9z2j4SuZ4zqyklegx6qTSRyt8v5oSarvHVJpVsxmnNSXx4cKx0jcmSGRk1JuCPBE7awRD7 +wUuJfKhU2TyruQLeqKlLcJKe6/xRyByKYGe0SM5PIDW0LT9lPBvnbTTxYj3JnW+s48cPjD0/nzx HjdzuQZRs7IiM3G3McnNOMRtG1lv+BiLjDwrW7c9wSm8Fly+mBzrk2cDU21DQ2rPDeCa26ZzIN1L hyKqpBTmULZD267BNJHJpK78SSEXIrKSjsgdSx7gzoh+Uc2wIYN4CmEWgQjjtC0AvgE87o2dVTQK YwZcXTCuauGSxmjpc60l3ZiQeW++DNYm3RMOhq+CKorePldDT7USegCEpuUpROowkbyqk1z+LfEr OxK/bDGM8tM/Y0P5udUq68KJgxf1Jv/UN8/oBZWpJ+njfLAOAM+RhnMprtuboPIcdY4RGcIhKCYA g/kCCaI2UWPlzBs7PsfGEtHqdwkJ4bfJnnXx0USaUwpteQmwvZ67mwP7YoKry7IjrcAvrqd6gNVg rerKavqTkYulqCWKIaUZKBzkFA5Mcu9EBKBm4Ru81ok3rn1nA8o0h5lvBhv026tb2M3eHG1/2D4T WQpvbbJN3rwkILAnoZah3WB0a5MBtyEFdgo8KkEXI1UiZis+NsNzt99OsnbKwdr/oQ0Rc9cMe426 wg4nx0+Q+DkWxiJo9mN3DSrdHuyoH3+Bib9+id84KFq7Il/D4cidiOLonQPqjPvCoTN7myVGbtRm wa4fCQBK5YUBndXC7IEhhVMkMPjRqQG/nHcpQ9eIHZ2upN9Z+n24uJYmtfT3eKSIZM4sTKeusMXl 0Zk7AGNxE/ggEc8dqtOA8Hk2WADxyWW8kkKqIin9rTSUxTZ3xs6sXkI2+tLxyTQpLXazJTTaNO5p FzSPkkzJnR6KgiJPF2PX29rpSgQDty1OiqVCrFBJBRYTjsRBkxCP3XbvWlpL2eqO0cKWYIDOA4o5 6HkP4icFGLoefUVWozTJjLMUv2LqJyzOP5L0eTq6UsEDIgv7omXs86k88NjiG8KcQ2tXujMG8GAJ tNM66iXrl1WRVCYkOqUBG6d8W5736rqGBMSPH7HoCwnItpnVfpPot3aCD/1oUwl+YA9D12NCQiUs Smx+5Zj5V5xPBRGH4yUE5+g33pqzXoR1jWv68RCx5Zz5fcuXxIgdOhP4xwcbI8bWunY/iXHQjVue snm7DhjsUXSlWtlCdTdlsByKop1VrnlZVwtk13yLDILXsYHxBMTu0JUESBOUz9rRGH+kXisr8Nv+ XO7aqKmX43Ww6pT/686U7k5h88nvaOnGD82pLs6rd6f1onKFBWCPlRNaUbmqsCE540K3oKraa0HR pj7x5pAJ9f7c8HYB/KgPyDft2fC+rlAofGnXRDJlcX6GCwsWgdueU3qFC5LgCfVwwEaQLbqLnCIP IWuIXLOtLcRxwvJAQfo8hivhql5s9asxHG2m3WEwaNqiY66eBiDJV5MJvVRy1akRv4TZ4xgRIvLL CIFV2A/snExoDvzYvBF5dJPtul25L3EoJud4m2VFhstomoWjqcwzrPKfQmXlCovMKry79XfkpnKW m0LQOHh5u/+byVTz6cbIFDYwd9XHSSWaedpKoZZOmPPWkDesEK95PPqnahtCnN7eYxuh6YyOcH6b mMEfbXEP24JDRzXL6U7FkejnKs266xASq8m69NbazsKDQQpWZ+9s8nHrqbFTuLTyp17Bsy0q9+04 +tuayl8TgoAIrbNIxgl+5hsqJMmM7mt5fEzwOtjGWXCjd6dLPBp89JQrlE7NmLM3rwn0goQxm6hL Lx1BjoeWqx9HEgb2WOQ6CMC1lEYfyR/yY/0Zj8FFf8bv/9iq8XXA23jQNNCntzefrEPT7wK+SBYQ XT2pAPrGeirDxal619hSz0sirnKs3y7uFoSbtmXlT5qxFspsJLbzvInBSJQXifSHtt+6EdlkjPkl BuaCORQgIlGeuFKVYdbrjI3OWCzYL/8pyAyEhKz2plGTPLxOrfCGjrenoxVTYz62PDH8udK8zpTC mOSR7Q/j6F0CnHD3H/a+x71Nuo8gZicsLvV4UQbQdYe25XqXYgtsILIbx2arGAsjya3XNBLYr3Br FLao8Y6I6ZDPXFFA/kLhpQpvqt9JsEjHyb7G1lbp/KrUCksYgNupyzGMOh874jUDZ1pVpCruVl+u +klgMC39We8vcAv/Zt/rODujHU82n7y2L59Wbi6Xs10FL1GmAltB3lhWirH1W+CDDhFTtLIOqB9f qnCi8qdehVPHH64C0LXWuyklnSDPXL/R0V9zWo3nOnBUGdudjR1OZusefbFAOOCZaJTOFYGwAc57 3NM2MszOkn26+Nl0w44ajHtT76CX1L7TeBm2XjjSGoLNQSMjrCfZMtytxQxPBkEZbT8SwXSA7LYE rvGognhIVHTlxVsN5T2v7bG8vXg9K+lp2+GDGPnZHfdt52gD+1UgkynkBVtLACjr2t/dOvReufWa AWQqT+otiZX7WZkQSSqWAD4YdSvsqnizwq4uRYjgDmVbOxgfxO2Mhu5XH3ELM282Kby+ZEz4vY/Y Qd57UNQidLwEQJ30Ds561+7vg4qKjquc7VfftjPX0p9WcKLMK2w0edNtl22Rvbid4iJQhDOayA0c KgjZWtfw4N/tCLZP8lokyt/VVIMfQrcflSjx9vlJx6wVSdQAlYw6Mj698a+PO6fmFl/nd/u5lq7z BZIMuCMDRyEFCf2ZSCYzzB28fYTvhioc5I2davgo7ba/CfYVBAY4b27w5k5NzUFvrGYJzn/Yc00O vo5BlwE7LVe4Whr7ym0qbNefRqT0/hxGBP4cRiiZlCdd8RKVRxDspEjSfHEJHKKoQxMWqdMsSpNM 4KcslP7Tt8Xjz8f/Duf/b2rAGw0KZW5kc3RyZWFtDQplbmRvYmoNCjQ4IDAgb2JqDQo8PC9UeXBl L0ZvbnQvU3VidHlwZS9UcnVlVHlwZS9OYW1lL0Y4L0Jhc2VGb250L0FCQ0RFRStDYW1icmlhLEJv bGRJdGFsaWMvRW5jb2RpbmcvV2luQW5zaUVuY29kaW5nL0ZvbnREZXNjcmlwdG9yIDQ5IDAgUi9G aXJzdENoYXIgMzIvTGFzdENoYXIgMTIwL1dpZHRocyAyMjAgMCBSPj4NCmVuZG9iag0KNDkgMCBv YmoNCjw8L1R5cGUvRm9udERlc2NyaXB0b3IvRm9udE5hbWUvQUJDREVFK0NhbWJyaWEsQm9sZEl0 YWxpYy9GbGFncyAzMi9JdGFsaWNBbmdsZSAtMTIuNC9Bc2NlbnQgOTUwL0Rlc2NlbnQgLTIyMi9D YXBIZWlnaHQgNzc4L0F2Z1dpZHRoIDU4NS9NYXhXaWR0aCAyNDg4L0ZvbnRXZWlnaHQgNzAwL1hI ZWlnaHQgMjUwL1N0ZW1WIDU4L0ZvbnRCQm94WyAtMTExMCAtMjIyIDEzNzggNzc4XSAvRm9udEZp bGUyIDIyMSAwIFI+Pg0KZW5kb2JqDQo1MCAwIG9iag0KPDwvVHlwZS9Gb250L1N1YnR5cGUvVHJ1 ZVR5cGUvTmFtZS9GOS9CYXNlRm9udC9BQkNERUUrQ2FsaWJyaSxJdGFsaWMvRW5jb2RpbmcvV2lu QW5zaUVuY29kaW5nL0ZvbnREZXNjcmlwdG9yIDUxIDAgUi9GaXJzdENoYXIgMzIvTGFzdENoYXIg MTIxL1dpZHRocyAyMjIgMCBSPj4NCmVuZG9iag0KNTEgMCBvYmoNCjw8L1R5cGUvRm9udERlc2Ny aXB0b3IvRm9udE5hbWUvQUJDREVFK0NhbGlicmksSXRhbGljL0ZsYWdzIDMyL0l0YWxpY0FuZ2xl IC0xMS9Bc2NlbnQgNzUwL0Rlc2NlbnQgLTI1MC9DYXBIZWlnaHQgNzUwL0F2Z1dpZHRoIDUyMS9N YXhXaWR0aCAxOTg0L0ZvbnRXZWlnaHQgNDAwL1hIZWlnaHQgMjUwL1N0ZW1WIDUyL0ZvbnRCQm94 WyAtNzI1IC0yNTAgMTI2MCA3NTBdIC9Gb250RmlsZTIgMjIzIDAgUj4+DQplbmRvYmoNCjUyIDAg b2JqDQo8PC9UeXBlL1BhZ2UvUGFyZW50IDIgMCBSL1Jlc291cmNlczw8L0ZvbnQ8PC9GMiA3IDAg Ui9GMyAxMiAwIFIvRjQgMTQgMCBSL0Y1IDE2IDAgUi9GMTAgNTQgMCBSPj4vUHJvY1NldFsvUERG L1RleHQvSW1hZ2VCL0ltYWdlQy9JbWFnZUldID4+L01lZGlhQm94WyAwIDAgNjEyIDc5Ml0gL0Nv bnRlbnRzIDUzIDAgUi9Hcm91cDw8L1R5cGUvR3JvdXAvUy9UcmFuc3BhcmVuY3kvQ1MvRGV2aWNl UkdCPj4vVGFicy9TL1N0cnVjdFBhcmVudHMgMz4+DQplbmRvYmoNCjUzIDAgb2JqDQo8PC9GaWx0 ZXIvRmxhdGVEZWNvZGUvTGVuZ3RoIDQzMDY+Pg0Kc3RyZWFtDQp4nL1bW28buxF+D5D/sC8HkAJ7 TS7JvRykAhLFLlI0PWma4jwkfdjYa0c9kuVo5ZO4v74zw8uSu8uV1BZFEO+NHA45M99cSCUX75OX Ly/eLd++Sdhikbx+s0xef3z+7OIqS7I8ZTL5ePv8GU8Y/ONJxVKWySSvVJrlycfN82fwomJZwtKM 41+Rq2R3N/r6wx+fP/v0kjEuFucFXCu5UHjhi3PO8SZbnOfBCwU3DG5K6FHi9XJxXsGVwTN2LcvF P5KPf3r+7BIYRqYtmxkXqeQ+m58CwlLTQzpEb6mfK2bGeW2ec82pfR7hY3x8AStXqf743M6HM3PD zABMLgpkjBceweTy3TJJPPHwQDxiRDwS5l3mwbizZD5BMjta4rlMi7KbCjDOUVhlYZbILEkgksFw 4uAMuJBpFYw2O5+agDw4AS5FjyIueLUQypeolbjsaYKZnlNFdxOVfaayFLS9P2BplPuVXidUdq3b hbOGc+Hr2lWPAxbqpGWEX4qpFVdH6IxKeRku+UBnvpFFM56p5JylHOwLVIJncJcUFV12zfNnv75I 7qGDN3xuhgcEgPFSxXL4W4BpIkaUZapKoKNAQGUiUfIlfK5yGIjo3b54/uyvI5MqgknJBIYfU9ms APoapBKEpAQBaPZ+Nz8Xs9WWLsk8n+3n53K2nZ9n8ASv2jnnswd811yvbqnt9VzM6nmlW66298l2 rma3+EA99vD0lTrAo5qt5pzN7vH5htr/vrqZF7NHvK/XCbQlMk1rCepRr+fwDnrls3o3LzURYqo9 S7431OZeM1oYAtBqMLzUbFHH9Zou3+Hz6h7+3CX4iHOh90St3SOFXb0CYvSCSNMS+Drg67ddXZB+ JY2+1Pc48Rs9m9zMe9dcI2uwXvPzwtKE0ToOd7AE5pXSC7S3N7tGCyQPV2a1Jf5+jvCW5TzNqpC3 SfwrPU3qTVBVZSqOoVFN0ChFmmsgBsVmAm6vP814f2kvrtRAh8u0Yj0C2PklE4Vc9LsPTIAzhFGv 96eoPDkrsFHQ9tUaJLPWirkF1dAiuT7MNpcVLJpPCxCKXzJeMe1uJTyXS8ZfqwXeFjm9ok+AfkJd LgDkeFbqltCKrvkV/j887YxlaRGOH7iPCNcZy1Op+mwXbxaFxwMit0QWr1wAIorLBXDN1Rt4XdJE 8SqUoiY4E6V7cZYxvmTUBD8p8wrnr7r5A6UFgbpZF7cQ/fcwIjKkXjqKdpBCEefB8kEv1c0AW+d6 fudZN4Z9zT2OoYe5dcIzo0Lng9KQGUeXcpQWykymSoZt2wa00ACpIizo4QyB1a622NVuVntqOAlc Kq/gaoZYdQhct0iSwKluNR16GzMbKZFMQC1qYjInE/Pb0sBfAyDf1fumj9GKIHG3xe/aIOv1nQbP lXUgRGVjsbR9wL/guxBwaTqrpv08TyO8CVj4vIjPYxiFsgm8UzIVZR/vshPwzidwOt51vQ/jnd/2 7Zwbh6gVYlWvaTkjFMSQQvNDLztIpZhtmvt9i86YcLNFoUrP6a6fYu5L8rRUx00jA/3Ledj2w7vl q49dIOMhd9OSYn2ezbnQEUGnOdQYw4p7F0RoBSO2N1uwis4ba9d+a+OfBr4oL3I4RtJGVUQFgWDn IwzqoK9AtGeZBqdlAVq01IBXKILUsuoACl+jO4FP1Jxr/2FhUoOVQ1ckjAMAPKNDEsUVwncMfN17 C5TlclH1WIWxsZno0NW4DdcZzEX0/AAyjFfOfBCn1zif5ZIifDMX3zUeNAORlWlWBGvbU4q/kSTX tzE0KMGOeEjgCAcqIJTPRU+mLMt9IZEztYIxIQFJARwqeM0j3IkAL52FvE0jFZ9AqkylrOgjlTgB qXwCpyNV1/swUvltO6Qica5jXbOM1srv6jKYBixbeIi1AbvWAfbh6D9jJcGOTxjxRKc+lCiRj47D lkrLXv91/dRosOlSJ8Qa0trl+zOa6Z8vAc3ewEivAZ9QoYUFLgdVLjX6igzRJCmP222DLM9513V7 QT3Av9a3OH3tLfG7CwW8PGU6quAslTZd+IY9dcJ3PzfISJipM8k9ZYkOcR3+dhllbQOfp+TWupGR 1IjAuCHWu5VbmaQroVTp1gYyOrDBmGFHAmraNjYlIShdD6ZE69AxqEGl0A++P1G9nFSnsA2mvXSr P2jxANvt9hHSCuQmwouCiL4KWYlFMoqpftNpeMji8CArlRZVHx7k8fAQEDgZHrzeB+EhaHsF8rUW ocZiTFLAVlvrd1c42IEo9TsMI0nL1ntnkGREa/09ELwxd1vooL8dysCQOupofqzafRJqaa9yQexF tLHK0SUF04y5L8kY+qGg7aNdCLwB24nlHwUCZtDzzGk3BUWb+omm4wJsKg49JfUE81adSp5yZchu Vj/2j1gSAWYKD8Ru48YD9x8wcnuHdyAAFG6HtaOr32IbDX8ryh5csWVvbXFMBvDmS2erNqxbo9y0 i2iufwPkoYYQTQqLq4WlhpR+oAfZWxg3yLPT3bHspdWivt5t4yBkVy7PU8XNyh2acjzLwboE2opP bRocxAQ4KMhr1VFUwvI0Z5FgWEJGwS1fH7U0hCnO6bDtugENvKdlg5udts18tiWj5LD8/ZLYGLbk 4LuzcLAjEI0XHFMMvxsEd+oVY1JiSRi3LxjLpQ17scytCgr5gvDZC5B1rK4jY1Nmya/8UBcoXNqI nko/pip0uAJU5GlZhXM8pgJUMgxrenPsAlideCxdwaYXwB4TmatUVNNr70fxTIRtCZNdLcR4z9rl /L0aqbKOOQZ2LC1C+l+7bA5t9t6riecaRmowfPASexxEx55gvYcDI4mRqI30LIR+0Soei13Rjwf9 oi4QVkr1xnjokLNdfaE4j9ArCg1GvWPjDY1aTUAD+OTyuOgjj1MRlUj5IPo4oWwcEDg5+vB6H4w+ gra/uORk/TQXfqRoFIlcwXr7vbVfx0oRLvilJxMyHLZgWWIN1+fnpPrpuSvJ6gKq+h/VTw3dReXV BCKlgkrXh3E42RFyqDhZbKb6AFExVYoe793Eewth6vJmIv6sjy26y6JKuQw14QjIlWWGe9U9gQ2L 7krX3EVxZJlAcZ6yPK7EQ0ssJiyxAIBR/0VBMyBwuiV2vQ9bot/29dxLh3UI19gyuY3gItTyDMsr AbWrt1e/RNuXEDj3OP1mU9XmEQsN0VpABpLqdf2q6+9dsd8HAfj04O8UunD10aa6t7a+AU7KBq1i dkeBVIcwrgKAMbFOp3VQ73Lym7AacZfYtTQ+MeJXdYVqXGkKFusFyBXKT2tKfBiIP0W4bJvVer1q m+stxQA3uowTSZPBPnpM0pY+DXl2wJuLXGAy1psagEhUN0t0rkG3yblx4I4H48DkWhSEV+2xYU/G UEMYyCY6fq4w5A3IxTW/zysMHQ0aIETjYdtuhztM526mgp2MM9yxDgita0wqbQLmNrqiWZqyFo66 7uVn6xUp72+WkV1NwZsjQfnbKm3SqNQFhMWZCLmrr/c4LGbTeJwhoqI8I532O44Zqs0bvQQTjDXX c41pMGbTLD9OqLIUadlTADoNYRYRa2x7WJDmUCIqIIPMOqM29lJHCwocq1Fl2G1a88FUimCcTzrW f7BC65Cp6Y5rKE/l7n1M7CtHH/5HFMRUNnA5bnDQz3NQkFjcnMHCVCrkd9rPThy2EIJ2s/7zcnxA 4HQ/2/U+7Gf9tpc/utNCWEg3yzc4SjNeJeVnWKMWZ+Su1Jk1Bs7mNhR2xTWNd4h0UW8KVlHykL2u WhfLNBkmPUGfdvuI7OCeYXTPOGdYJYuu2lD0E2dkBK/SarATc0KpNSBwuui73odF77f1S60gIH42 sc5clOTV/P7CyVu5ZN477BDogSuTU7lnsHNj6m7xY1GVxN2W6FSHx0LH9vg5nh0EKAVgEzbFfUVz bxFHIMxaN9Yza5RakxeDlL8C/LnTOzxtYg/DtQAycuxYx+4RH+8Pmo9zKOvfQl/rjdvbt2B2zTft GQ6lmIsxvSijZ3ZYXrMNc2inQ9KowzDrhPiYd0VoM2FD5CF0f4PTA1HQFQyz3ID2tCQn9kCxVsYG cao63vICAidbntf7oOUFbX3Li4sAQrmgF9fgOWppmba0WKxXpLwIiXUgqZUmD4xy6AWilglElYgv xVCeY5tWVuNyjqfeXRU580+lkiVtdeR27h0JqV0KlISnX9crF1woXJ6f4OnCPAG9n7rdisEGwPdu h2H6xIg2hi9uu9Q3ZNXZ8Zr4u4NVDPKAe42IsSQpT4twSQCDLD7pTYN4yChk2PWQreMBLys/rWQu IwsCN0K/wXzzELdwp0fHZwY0PYUNEwLrEbydbxMd7lzHfYBjzPkUL2UU0xmjBNDhZTjJGEBJIQZt pxV6YqMlExlmWT2Ayk8AKJ/A6QDV9Z4GKDVgVZbE6l+2Ub3hqJ199ib0TJJO+hxFqvLdwfE2QScF jbDeoW282yy7sSVYnQMlwWFClyLeWkvefQe9qXc3ehy7JbCf+4VbqpdsHlAh69VuQ1u/g0TlrtHH D1BHdT6KyqvV1SWkyVqf824NSLmN5gNJWsaLVNgIJzhw558WQWr9s8xdpAa6HtLReOmQYz8fOfYv 9TKO5lzKT7m6oyG6NhY9yM5SVYR8RAN/yG2zHs83bhg6JmqLWMAdsfh7g/Mx1XhY/thGkZC0n+6R xlqRNcSJQ6USOqig31C/h1AgJ6BAn+zu19ROgAKfwOlQ0PU+HKv4bV9Zvblb/Y7yvh/ZF7Fu1/fO uJNiTmQ8Ovc9esSy2wChxQ5GHzP8xP1GZe88kt2XSdpHq8r/bKyphFWo0NN/tYcjYj87Qb1zMbyu uxaTPz2JRUqyooOuUUEMtWlsm874a16WWEHSVIpXyMjPtC5v9y5BGCw7RnUb+LxyC1InuiTt47AR b7iBuqbTVgZPtUC6GrnL3wxM+eW+0IGHh3TH8f/BbA/H3HOFxd9g/txVUQ9EObwQ2PnkijMvcwyg g+7R3diywkg4aDst5rF9VMuwKu1v2nzQeD2Rpee9XtRD68avzjV2u5N37icKza62kuurvXdMRRmd 0WcAOx2iHzF49qnroUZpnKMxLhC9EPXaYK8f6DO1tm6SsNRn9z2M630HNwQ5f08afNZe4CnhlBmz qWObdkGlxDrGhAb46XqHZ2uXadUED/idK68K3aR36ZlmJHMRKgbHX5yF6UjgDzYy4QqaWaZzqgU8 7Wla7cUDnq7qW+QLtBnOggzctx7inRIcmFPyQh+9mV6NrEptjFtS0E/ceth68QU5oYB+7+x25Pdv MBm7kYEVQVOWbubOpvu8fp4DobNeGDJ1iI7TuTaf44kfC0R3AwosI/lE4hsHFZ6D8Ju6k4XesaaN zeRvXClHW0bkx40jkDctIS5xj9nk7Kt/EYaTgZHWffj4Pjzi8rTeokndTGzWQLYeUI26Yy5wY2fA QR6P+QQlnF6PMNiKjiSKtCiCfhq2wm2owWR9fUr0SUN3WpkqGogPto5mnIRJbbGgZ21fHkgeIRME yAjWIZo8ymrQdhr8x7burewZSzPrQorl/x/D73YE4t1OXpeXjyG6xYJN/YPgXFo497bGXDTy1QqJ ToQaUMd9G/gPYns6YBelol9eB/5/QrSJDeg8REeuuhJpTd1M4BdLU0r8cVMw9Fm0LMYHbaPqX9Au RNC2Vx4JwM2Vl4jbRmfIbSxRF7nCXa6jOBEwQ1WFbU123TauyrLykjFCIVy7B+fmdhYStV/vtmwp OqQduYFJ/BuDswgyDQplbmRzdHJlYW0NCmVuZG9iag0KNTQgMCBvYmoNCjw8L1R5cGUvRm9udC9T dWJ0eXBlL1RydWVUeXBlL05hbWUvRjEwL0Jhc2VGb250L0FCQ0RFRStDYWxpYnJpLEJvbGQvRW5j b2RpbmcvV2luQW5zaUVuY29kaW5nL0ZvbnREZXNjcmlwdG9yIDU1IDAgUi9GaXJzdENoYXIgMzIv TGFzdENoYXIgMTE2L1dpZHRocyAyMjQgMCBSPj4NCmVuZG9iag0KNTUgMCBvYmoNCjw8L1R5cGUv Rm9udERlc2NyaXB0b3IvRm9udE5hbWUvQUJDREVFK0NhbGlicmksQm9sZC9GbGFncyAzMi9JdGFs aWNBbmdsZSAwL0FzY2VudCA3NTAvRGVzY2VudCAtMjUwL0NhcEhlaWdodCA3NTAvQXZnV2lkdGgg NTM2L01heFdpZHRoIDE3NTkvRm9udFdlaWdodCA3MDAvWEhlaWdodCAyNTAvU3RlbVYgNTMvRm9u dEJCb3hbIC01MTkgLTI1MCAxMjQwIDc1MF0gL0ZvbnRGaWxlMiAyMjUgMCBSPj4NCmVuZG9iag0K NTYgMCBvYmoNCjw8L1R5cGUvUGFnZS9QYXJlbnQgMiAwIFIvUmVzb3VyY2VzPDwvRm9udDw8L0Y0 IDE0IDAgUi9GNSAxNiAwIFIvRjkgNTAgMCBSPj4vRXh0R1N0YXRlPDwvR1MyMiAyMiAwIFIvR1My MyAyMyAwIFI+Pi9Qcm9jU2V0Wy9QREYvVGV4dC9JbWFnZUIvSW1hZ2VDL0ltYWdlSV0gPj4vTWVk aWFCb3hbIDAgMCA2MTIgNzkyXSAvQ29udGVudHMgNTcgMCBSL0dyb3VwPDwvVHlwZS9Hcm91cC9T L1RyYW5zcGFyZW5jeS9DUy9EZXZpY2VSR0I+Pi9UYWJzL1MvU3RydWN0UGFyZW50cyA0Pj4NCmVu ZG9iag0KNTcgMCBvYmoNCjw8L0ZpbHRlci9GbGF0ZURlY29kZS9MZW5ndGggNDc5Nj4+DQpzdHJl YW0NCnicrVxZc9vIEX53lf8DHsmUCWOAGRxbLqXkK0fFyWatJA/efYAkiEZMilqCktf59eljThAD 0qmUqywePYOenp7ur49h8vLH5NWrlx/e/Oltkl1cJK/fvkleXz1/9vK9TESeXN09fyaSDP4JeFum WZ5UWZ2WydUWaP7wMc+T9fD8WZas+W2h3/7h+bNPi237W799XK7kYpss1eIDvrparvLFP5Kh/89S LrrbZbFIlqti8YDftTdLkS++AGl3WK7KxZAgcXsPlLf4PVG2y4bf/RtmVovhgB/2y1+Sqz8/f/YO OEfuDctFrtKs8Fj+tLjHsetkWS0O+Ooz/tcta568v4eH0+fdPjZlnY+nXEVJVVqGpMR59wDLbvcH +J+ks+9wncncQqTMUiGPF3JAYe2f2k2ylMz4jucqF9f0qCQyod7MsinSRuoZ2weUKG3Ffofc/AYc 9tsWpMMy2XyLzdaUqWzC2aJPbppUFCFt9yvu9yMspt1EhuXAcK7CYWlyxXuo4gvNVZ7WI9a8bb6H JR6scu1ALe74XenpRz8shWAKLeOK38Fw1FP81uxkFV14UVZpMeLk4PEPsr9FCRzwFao5awSfgqG7 NztMH+/h+27T4lf0Yf/ULUW22OB/305tetWkhWZg2JLC7OxEyEx8nyuRqmB89FGVTPMmICWpuwPA ssMVxzeBBK70IUUVJ6Xu8bN9Szaie2HO7vBolP7fdJ5uljx4YtvwK1oxnSE2Ifu2h5nsoSK66hL/ T2NnMm/SPI9KI3n34U2SeOZVeObVzNFksCEyKUuZlnywE/ikgJc3nxb1WLgv36uxUW7qtMlGE+Dg V1lRyYvx8GObnsm08Ucf7+jEQ0VWpSp4KDwvK+XFKn+VCXV5sZLwt36TCfHuonqFf7IsKy5WCthS 7zLRZBcNfNxoyixnanh/muOyJKn7LI8N8BTLZYOnLmRZvFYXCjltiI9CvbdsAovAdnYhmXtRlReF x6l6Cx+9Ze6BkkblPJPSI4AMPy68dYp3PC+8h7c0CL+Gx5i56alOWPZ5IMfSGwET4LfAQeV9mr23 j8HPzB7AIvElrOCkcNFEgXOb1QdH26TVSHfu4OTQwdon1sIOZM+cBaXD3D6BNYA3a/445vSqtAof IOAIZwkefPeYPFvK6BzmgCn8a2ze7hFn2N90Q9RQgqkejfKdzTdGJjGMgMo2Ht5FDaUiv+bT/hCl rdOiCmlnTU4+YXKMEyhUWtRGrD8vaW9+ArAFC7u1QGJr3BAbSVixxgLslb6CMHprocnAaxgDbkjb UgJTgFCMnf7E2wWvtjHxFyJPRROy+IKGqCjQA6eqwhFZhoqHnnw7/BLVYtWkavyoqMbnqaxC2lnx FzPiz7O0Miggj+13kSPqC2h/XhrM/JHAdck+n+SMu6cIzdLmPbqNouPHNKMt5CNb4VHCbzcbPFLk fje7rwM8KyaNvKlSWYTMzUpDzkgjK1Oh5yhOCMMjdbL42xkeQAJGDR7FRtE3mdZBle8vamOSL9kU gwk+7ZxqcKdVwOM5vqkGVN+MONNOAZ0MOpZKaadTMjcqQ3eFXtSa/7zmtQDvIrPeQbwR6CsMVVG9 o3lhrkLVtHD8WyiFJLza0nPizpdkUtEMsoCh795OCKNOAYkE7kQA1IdTKURasr1KVmi6NL4Bm3La I+UgUeHJhuFN3CuB5VYq2AGjzAk8TxKw3pNL6l0o2N4tralKLKTnD1prEWOoWII9FrOb7iiLtA7V XRtW4OpgUS76mHY4geJVI9DJ8Cw7g3hvbFCJUWVhAueSpcBO09j0EFp3v/XDAWVSGa9cLv6KZETL QkRLszOGf4DjJ6PoOEf2RMjlrHlQcXisqhKAwAgdN+ejY3/8d4NjN3gm2mFA7JNSoiPMLlybIORg PSNJlCOh7uYLSJwIX4Nc/6WjP4ubMGWCISfM5rIhEPToeOazC3X0rrYH42hZhwMqfSiAma/mo+Ez R1/Gc2xu6ZuTQi4qUOrKX/yZ8i0gcgoHxo91nWMqxSd1GCM6qJEYcPuDbFj9QImTO9T27sYedvrq qwWxIIGVch86pHMCbSoACpmBrA9sVu66GxPlQnitTxVu5q/40SM73yieLDDmCaaNqmKp0qYOaZ0+ 8R63exvrrs/Y4BxscFEEU565w3mRjUdGGc/Bv4PvDGhpG65NKNH298vJrICzbZuNNU/avNvzc60R kk4mEsmtCfdpruEHHU7ApmcmV4DpSBpK+xhDrFIKsOgB7y/QgNYYr2RWi0aTxaCVbAqEKmeJzagc xEoyH9tIEbPOmIOTo1E0oiD39yHkk1zkvUlQ0Uqkkc8RKYj/5wXmd1I8oOv0RaJmvQiN6H57oPOw 77cgNZcQokfrs0fBV+Sky5qcjVvOjClRIs2qkLa1ilVjdMIRJm+WTogOL8lWhLy71BKhijWnrfmg od59tnr5aBd+e479gKNQKQMQtN23Gd6YEEROrjYY/J2+JzIxo9pg4o0zv18m3IQ91OBC6yYcijI1 2uQOovLyrdHZyizNRThbmNm7DhyuTJYFlx3cPs6ClqIQaT5a6SxoKWdAi6hTIc6ZpJqZJCsw5DyC FIkxY93Qr+9918++fsvR3JoS0rrMUno5TyK/BKXlbH9PUV/e4KaQ3WIjiNmWIjFn8bNRdOcq2XQq XcHgHPa1cZ8Hs6cbOs8evtEuD5ilANbuFxOuDzZN5AWv/+tZkhBc1YVVPRYesMloKKLwgkLFYOjO ZOF1TmEWTw+dqcIYwwZLBNtGkNzlRWhhPxA7JgPTxlS/klg1CViKHhMAPHDoAtqnbv8t2ZjMgDVe t+a8bNpo1aCQBNOC6RxowcH6RQy6ZWklzuO8qEndA9rwgLOmPVidM3WRmFuWCJzOeraUJQKngJY2 qHtAJW33rbGe/e4+6e/pTM2rHu5Zo6d6iyM/vvmRDiY5SJfBtMflswlBbUX0C55f51ZQa0n122Ho 7yhCwI+4ZtSjlEi7XGLk8u8fWBVjUVpJm+Nzem+29WDMM3P6xfhIz/BEtrHK0cUGsw4v0JXnJ9Rc Zhni/GBkdMPANgK8D2hRzbGI7DLN/Tp2yiWABoBXwfh44C7Sqg5pWQxcg4seHonaH46btH7zioRJ ypHDMxVjKgSShpoDAR+EZayWdI4LhGAFrqOFWZE2RfgwOtl3JiNIVuwaVW2za63DsUX8ecWJKWBD J95/qNUvhhiEEWP+uj4arcEnAk9OgQwI89kEa7nE9ElhciaYrIeYTFv3P338kSx1ewPxIix7GOiU cV56hI6LE2quREWq5z/qlA5ISoR5R5QT9D092bFJBVWjlL8ujZV+XPoQ8rvUx3+Y+bIlwPA9lmIm eCpqQuTBCrHa4kI8WCFWEEyZvRus1bxbsjv+VFHURsB9O6DinBHYyhqUrwwefGZgKxs1HnlyAyEW zg2U++olaVZx+CxAT1Q4EuSAhe54YwenuYMxt0ZaLLiJxpf1Hn3Ho43jbM6jtW0Hv482WBSETPwH /vICXZiLpLPo8YcdKEeDt4Nt9CG1udVbrLLjLdZcdqi80rnIz2bBGrC9sNRay1GVODFzww1ET93m W2o0/v3OHI1Teyqowyfo5fDFyjmI3hZoej43tjBqOx6sJmMR7sObyyvCO6XOO98zpu9vBmtwVJhY 8OShG0YORgTcC2Q6TLgm1JkmKtcodNO6r+IetyY4NbFqxdaFw4md8Q02Lc3JmSDNWAVZxjB2mxc6 YITGONOW3dGUabOdYu1D0DoTLfqWVGAKpicWWaNW464gLxSKBb8Ku6JCfo2d3rT7tY0SQiixM+GF p/UG/26jJdMCSy3Bs+Ll1QohbkAbr6dkWB8NaIMuqYlIwCushAvrnZay63giREHwhCLV9uYzmanb KJrCjPxZjMu6wraBgBaggSj8yC02WIGii3q0c5vNaYNQ1GWam6PxYB8EYP2aToC1DD9dUTTvBbja HGlUH6b5/Vy3NnH7/sDF3lg2tca2goCffd+SDZBRSw6B3mgMYJxYLgZCtRFxtBZUlke08RxPk2ZN SDtRSyE3qFHdhA0NXA/5C+oDaLlxI8wShf1mzr+ulFEVUx3fuDLd3qZFwgaXee3A9rlmDAE4BWdN 1oN1whsT23HIeYtkxhcAISkFUrASES33xHac/UlsjuGRc2DGvp9seGTZlNoVGYPqdwVYemdvh2/A 6D0bTKEt5h5tGTvB/wRC91D6CZmpEqMSL4i+/PjHxPYs2uTLOIY2BvPyNTzop+SOoxbgHVgj4J4m fyFRcgGWajIvHKBgqL8ZdqQ+IRIar93Y74MJ5/aEyr3EVm8Vc9htycJ5XYvG9XGywaDp09szLzaZ Y/8li21uGydqWygOm0pYk6x/QrHRFG4e2sI+7aKnXlLaOOAkutu5gji5CIlNpxjKZbpY5WAkIBIV jh5giaAGxuG0t0upO5xtxt5mc6gflSv/jyau6cPmUTpt204HdqTh7rTNb0VeIXMeoLCwFkKjfWst EifkE9bUwcU490YD5uItg/om0IkHkoO0n42wV9LliEftebFOKIl9gsHK4n2CJfYJBrQTZZRRVsR5 vPVLbsDgsLZaYAJjpUwqWBlh4gGKdupikiGPs3uUka/jGXkEWtlZaf0mPkneUCPfRFofVoYmbZzQ a11bVmj2JClttEFdJ316Mn/fksNS2rBzopJKJm9t9wYhhqbnesJXTHyMVa53G4Cq+WBehB+7pLeu fpcjj834b9hRA4pG9e48WEHE8I6CmKQuQ8HGknlmE+oCTY7zxoAOyMeeyukJiV3wwXCdhunRL/ON Fz+IVfOVilxQvj6cEO/ORA1rk1ZVSK8fGq0IZKkU4Yio2a4KNKIB7Xxfezaj6Izmzpllpj0+VxLx 4/ccl86cgBGEU+ZzHSZ3vTGnFMOyD/Bi5zi6BjUL+Hrq9pgeo+dNnrTNzm+u0jFAFfHJLZyH0oRK tkKg/QBpUz+09Peptf7ROrZ15zpXaCgwdzp4yQvA/7YvzXUD7e0SdNRi61+W41hEXWOnWjAvoIZY czN1CXrEXiPDLtpqXedYEg5GzTYIYjEbgpyAp4nMDTl4531BfkM01JLV0YyuAONUL8jI8NM2D4bs 16XOzTiY2WtVMo48ZLDd7qLp1BrrIgE/GnYoDxIQ5PiGy7QIgQsmo26y1ajn3erlfAhtdCpXqbDd V5yQN3iMsroj5SXv093aiMirlM0osAD8p6rwYeaQcKEYH3Xv2jXWHF/HsCjdZgtmm4mDM7RwAXE8 Di6OaOeN4lQDv5GsyFJ1noGe6kPXs4hGoe/5f5jWcmRaA30n/HbDFy84uLWaHPZyBRmjmaJRoULe o5cwswKLCwHtEzbAYRGV12YBT7SeKUtMT5/3PK6WB7Tceja4SplNiW4fRujGR0ojkHQcAdpk8Yyr MvtcC9tybK7OJeai4ShL6jbbGnpO6drbIH7SF+bgvFo7cDC7jabvciWwHdDnJR4PSjwqPumdiRAO 5sU+apLByIM98Ec7i4yxVVRZGrzT4I+L7jPGASGp3uaRBZsQ8LHeraSvGNUpvVgVfnwXuaqqO8vX Z2QL8FKdDJou7+YAq8hyBNvBKBew9abUMWewixydfTADFZM5maYzyDE7iriiqcPR8xZw6u6JWTso ZX3WbSox06Iuigozxv8PO1pN2NGJkN6ViabxI+w6P9277UxqZC7hWms010I3US+6i1aHSmyCDyTh ely48BZtcZZYyS/DwdFmDEl9sQGtn6NJ+GKxL7E2PXUC8hyZ58n+SXEtS2lnuygsChb2BhvbxnaL TToDbd6DiyI4n3ezs/ec/U3l5CzFAu4CtiV6cDYX7+ATBhxpiW+Cx+Xq5qjTXhWYeA4WuW1hMN/w R1s6Djanit4ZXcsLZomXCiVeyAtoW+rO1nXlcYR/xk8vyKrCO7zBnFEdAbusRrQk1bClal4nMnie aaSltG0/DP3OtgCyzm1JseOmClxeMFM8WKLfBfBJr6KkDZosn1Qb/+SonISv7yyuH1uhJOiMYf/t lchZ8V2rR8vXIkAfa20nju5w+SqHCuDxGHWlqkrLKiAlXocpzzWl3bDXVROMf6RShImhdlgv25pD S7cIzG8EBOldpLt3RfnCKwtR9tj679NnRcFZie87/V6KZVvhBUqBhVaIeOuiaapk3z1/dve7Sa1s ijQvWaVpmk/aW4ZWfJTWo9oMAwIUaiyzhJdHwC17j5jT1xqvwQa0J36DwcYDq4nfYCjxJxjuD8Qu usDLeWw3y+PUJZa6QuzpD3O3IYX9IYLx7xLQvUnJFybNTf+KLonSBVH9ywF0UVTw3X0zGf6aQKEU ktkrmua6qb6aqZ+DX5fe/f3X6owGJNAvUJ5ACvvBNppwJWt0Dfsc5SAzx/WxaG0cfElc/MeoaaZH vqpB3aKz/BcnqiNHDQplbmRzdHJlYW0NCmVuZG9iag0KNTggMCBvYmoNCjw8L1R5cGUvUGFnZS9Q YXJlbnQgMiAwIFIvUmVzb3VyY2VzPDwvRm9udDw8L0Y0IDE0IDAgUi9GMTEgNjAgMCBSL0Y1IDE2 IDAgUi9GOCA0OCAwIFI+Pi9Qcm9jU2V0Wy9QREYvVGV4dC9JbWFnZUIvSW1hZ2VDL0ltYWdlSV0g Pj4vTWVkaWFCb3hbIDAgMCA2MTIgNzkyXSAvQ29udGVudHMgNTkgMCBSL0dyb3VwPDwvVHlwZS9H cm91cC9TL1RyYW5zcGFyZW5jeS9DUy9EZXZpY2VSR0I+Pi9UYWJzL1MvU3RydWN0UGFyZW50cyA1 Pj4NCmVuZG9iag0KNTkgMCBvYmoNCjw8L0ZpbHRlci9GbGF0ZURlY29kZS9MZW5ndGggMzgyOD4+ DQpzdHJlYW0NCnic3Vvdj9vIDX8PkP9BfbMPWWVGo9FHGyyQbJKixV0apPt2dw/KWusVaq+31u7m 8t+X5HxS9sgO+lIUh8vKMofD4XDIH8lx9vpz9ubN61+u/vY+E5eX2bv3V9m765cvXn8sM1lk17cv X8hMwH8ya0UuijKrRZNX2fX25QuRrfGfv7588evienlRLO6WF+Wiz5YXerFftovuEZ+G3bJe3OM3 3SZb6sUtPu6QHGmAWC2abPl7dv33ly8+wMw4u5tS1nVetNGUvy6GcSmlGfaInL4By11ieCGqXCk2 /CJJ2uYtJw2Cblb4mGf/WEphlmIWOZUFVxo+9SOsj56yZWUejIKWjaEaH+F9t39MiKTKMpfyLOlV Wec1J33CqR7c7F/dxCRB9zzs9rgwEmPwq0rIaVSMGzamZC2rOtdniVrWMi8KRnqzVItu7FNGYO2u alXelnYIimSE3PdGcpCz22ycRdHebXbfRmBtdI07RWtDhduXODEt7B7Y4QdS2h5ZKnpHAzbf4Zs8 uzaK0Xbvca+5rvapBSgJK1B8AcOYOQZpq8HNuYUZzeoyEqZzX/ep2UBfVc1nS9pNW+aq5bReKdvh Hhe6RkGtPuHpm5MHVzC/YXWbK8u0WyGr5+7erFMvunW/ynb4aY9OgQ7YMHb097nDzSKLdKSpU6tK 9A/xTCmhClXnQjNS2OcaFGq81HOPx+DoWdbescE/fwxwCOrFQOKBbkBRRjk4nPSGGhrpi+4WWSOD 9GZVec0XsKd9Dvbad8iKFPM9daaUzpuCcUkeP9Xmmu8NrAfNy9sVLtO4iZM7XJV55U4xrR2NZ3qQ Vs61HPH8R5SLmq0Xa+NZK3aS89TeljKXiosTi559+OUqy6JIJ6NIN12Txr/nMClmmMCGqMYy+a9C Ywv/VnGgee734BPAFrKb3Z6ceH9DG0jfIsMH4xc758zDLJYExhhrp6Nn/ApuFRjsGCT6ihJufBCw BJuUXckS3TpbeNIGZY3uhtEaSbewbKOkrygZ+Z+Vi/LDynnkuxTjVuc153vKgguR187z7XHCarFO HVaJcjd8TBK5GCJG+9uCToZ2rg1XvPFeR6U4aZ3LyawpzUrd5C0nfe9O312AMym8JEErjebj13uU sHtwTiHpXwuZV5O5aYlk7rST43YYR7DG1lljglNT5eWEE5pDf7Pbkr2PmQ3XJkxtd8jt3uMdUml3 k9rFUhS5nLD/U5K2mug+u8BYDk7mBvZzmXJIpSzymo8TNGTWoSiGvwH6wZkS5TEMrhth3bfIC4Dp 8KlW8K+GHdivj739Qij98xL3A8zgYTeiRlfZ5w4fxuF+nV3RMV/KAhChiYIK3MhSKvO5y253dnh2 3Y/mLILb+Sd4jBval/ulCSNIQkN2mfxzKvBVCnchLOSEbsqzchNdaRcB4uRklrNOu3GtpYsFWdh2 OTXc1x/1gTxwDsWEAQ5+I1RdXk6HHyxHihLOcTR6xtGIGpfMaN8yCPlDUEJqhc6TsUt7mzqXnHSK JV5RWO8cNLhz4NFF9axzKNhg88E5BwOgKDV5DJ9pGHIfLEq6c9Ohl8HZXMDAuEXUwz0ZOjr2JD6v YbcmC0HsM8EnqaNO+Qwb/G5Zhvzg0fskOiD9zb+WlVECkh3GODfE6Go2emlVhUhH0QVZ/rZ0+Y1B 1c/ItPA6sMng9+zRuXTCXqR1gm0YhMnf7gl77Bz8jzbuCNal6T8hCc3/ymeOQ8iS4kzT7ptlCsEe UUxh0U/mEPiti16KZKFJhrzPXyW3Q8i8rLlmAAo1LrnKvKbN1mqL5I+g0cFnIP3+GQHa/F5A/IMU 3Mz4K0mLm/GaNIJiq5+Q3VRD5itY6U/v4K029J+S5ZAmB4/Opkr6hUZiFGW0v7uchgRIBS8JSWGp 07MceNBqxoNCAG31OUxq5uAPHarhV7ZFrqxQ4EsbIYS8urwo3wgp35q/+v2lFPC3tZ/r95cXBfxt roTS7+A9jBHqsnojRKkvL1REAkM0cvoAlDV95Sir0lBoy1R+uGzMt8TgCsQQhZDVRyHfWaYTEjdH 0eAc7rX68NE8VyQ5SncpZTQMuNIzrUwQ98qIiAvB/5VGLSghio/EHUlxyMkgU0DuKSVTKR1JMvvv u3tWAxrMKTf+fdgE2GrzAhi3su7W5MVxdSRKX1Yehd4gskA0vO0p4yPyV57v992TCxZUHyI/eeIM lnWNpY8oHyX/cRtVaDB+hILDrUu6AOfUxj+HuAln/gk8jyv3+KwsgVoB8gHOYiK4SUgGTbWqGPyj XzsIVs5N2tTtPts5GYOrxCi5J4X04zjOICytuUDJCFhVaAOM9i9J2jYvFadN1pdqQHlMhvPws6rb vObjDvEzG9AUuZ4sIMq7aXdZXQNUSTGuhz0IAcCWoW6WNhSek6442wN1CxXb3lxJddsNmwE+RFWk zUD1YB6IOgzS0SvtDuJXFyGffPKziitzvrZIMbX2BWc8sYMJtUnlQ9qhW76g35O0DcJ4Rjvr5pt0 rCjLBouRZzBpZ5gohZYzgezF+ZCdMfhhyB6NnofsuuS0n3xpJi56ZVRA+wPc0gP5j8E7EPSJJhGm nLcDVAkm/mggHozZ7MZk9a6A0y4msn6z5tXfO5T4bwMI4dUTvvKm66AsVkoeXV2BxYj+oO9hF5aC bCQHE0cL9G7CGe529NUtqlmt9yanePSnO4CpCeY8dWxli0HQzPrlmnyGXcYDJcA36L9tkyRA6GF6 uF1bgODi+OhgeLJiCecGtyCefb5iKWZsHkyvPObiD7nMFD5V0+aNmp4cldSfOS5sFI1IZosCAmQR D5g7ITovKk77drPJeBIR0hvrBrtNqJ2TyZky9E1PDnH7REUoWyx1PTHTyDvWAoONHEKXjJxznEBn ow/TpprL+mWJrKcKTUtzhB4Nr5+/XMOhMdbnsZI354NO189oqfUp21a1RuccGk5O9gnewI+rkJWN R8zazUffB/2iFxrs6lcu64yXr48lVt67fQOyJnIggSwVbrTGMM8WloQEusmLmtP+PIOV1IQvVRXW 5iyTdKiDdPG7rM4TC4vfRTHZm9kOLJjdH8YX7Yct/XXAIdWN1aI8mMO4o5RUWqrZFRx6kpnuh6pE rs9CA1KdlfWpUudN+7+Q9SHDy9o8Ul6mzdenky0h8H5BvJKAQ3GrIyBqHzwaOIZK75e+nROXZ/BA 7gdfftsPnfN2hS/mmCxIufNMBbKAfvtxWPMyDYU0rNNtaeC2710fxiZ7p9qESsm8cJH9e08OOE8h Sgl5lORD5k2onDFEWeXVeeFVM0NsUoYoJDZITOEdHAbYuagyLPJLW3efvDRldwB3usb91LQxGmPF RS3A1eP7VIlcFjV2daM5Ty2iOqtIXjTAV/5YkVzWaS0XmOTVU+DwA1VyxuCHIXc0+mSVnNG+TVpg iUCF0WLMs3Bi2yftHYvnsuQjgzfvAixOlfcIl7PhvkYaKutfQ0HZxOZfrt5eM1/RbwinpGr8RSNz XfN5kveiGo1EjParSaJDxO9WWMl+MPg3Xin6qVSGLzA6n7V5WEWA7JJvyG7z5Ko1cYO7OkzxIVqG rMb7uAj5pIKo5tZFpQuwd7TuZCB1ZwLAh2awOFQjQk4/jK94oaw7yJx42aDbrE0hyrt4hFjGL8eX B1JXYBTGoEi2uesyFZazGG2M4hhodkAcz8jKpI2Exr3t7iiFxPKZy1tT99g0Xodhs4YuDrG2N2to yQCQpXL3He6wiIgKfAhkoVFBNcQNgKAEKtNF3lTnqaYEEIr+IaalOR58ZY8uMhhvcexex7zplCpA hLh1xuLx+GjqoahdBAYeE3b7YecC+vFExH5ZUIr9E6USLmkyRobXSyaZ9SQd2HQh+TH1Ck2A/g63 mZfX7E264CdW4eDBQ7KDrgq8I8KUkdwQhdc+GOknB40evczdZtxlS/UjDtntSNEGMBJXtfHwmuXc Dku1OFq8vTC139A8M9XbZNemRaNiMxpPlazzFpIuP7Eh6SI16YjR2sSQjBfNM5jyzldz/BWuuJoT 3Sp1QNJWIfsHPOXkc/1u+2ZauIR0eyI9RMvUx1LhgR+I7bC+c5D01FZibJexYnemjmTn4SsiT20b 01RuD+G3fxVn+8bCtthn/J6Zwnzvgo1f4TE8H6oU96kVHMFNCkKTlGwxUepzvEel9AdqD9mmEjWb IDkCzGGaT6GjdBp4qaqm4B0rcwogjokNMb9tp2KjEKJAUf0KKBX7SCnYOY0sBThSc77O5bpsx5jN OulABF7zYQyCeX25xiN97StB1r95azzXjci2zVvWneK3JcdjPhvthaa++oyPvNrfJ68cF5g0tHxK GwzrRdqVFAJdCRuVBIaFwrSE0XJgmBiH0XMyLrqHjflkP8Y+NAUVRJuLmvNJX8CWWEdMzWmqtvud qW6nkEmF1emIxZmdLLxPw8edcRNMzrRJJCDy84or7VnFFQmn0t2a/f9oqcNcH64uy4jSdNbN58I6 QHB85aGgvNRDI5R1UjC7H4yesn6PTOg9acdqK0wqYsnjfv0ZLq2WZDbR3symR+BWGe2ZvU8PzlJI V+I1RsaZvMgQ3Wwy0XLe8+kqXI46Xs0iMFulcIHFKJOOfO0vCqXBhIVndIna5yt09+cQnpkUm0pd s3fk8Ic5EG/YqtK/zGmwJsRoDy/c2+XMdYz325vOwxTbK06CZ0hNVMMnTdXbygrrbYx0/tb7TCNK lvL4zetDLjONKFlUmF+dauFOikhs1DmNqGjAyUYUo/242blAbZNR8zuH1HWOqL1yHEAftKCYFQ97 3r4/bZ9FS5chmNDJMN5WeaE4rfldWtTTqqIulK+kHCtPrBxIDqlwVAsKFp4wxaI5ULar4Bz53Rq7 H3jYs5v3SIAI2nA/kPrmNk0EeTdrM83gd4HSeAvWLU5/MIUOj9rp8nRrcoboztBzTx1rWxbo3V5a Z+yvO3EIBIPWvCsX3Xwk0aJpwi/Ghm246ZjZHygmVA0uTE3UkNwWgD5AxGhXPNW1kWZwO7w+of62 htnd5XvzSxOu3PTPKmSuGz5+3G0xxKVGgAOWfEC6fCuwCMRot33HbghBCMJCCUWu/rclPqd7/JRs J6c+dIozPbWmyGuR5PIfXghuZg0KZW5kc3RyZWFtDQplbmRvYmoNCjYwIDAgb2JqDQo8PC9UeXBl L0ZvbnQvU3VidHlwZS9UcnVlVHlwZS9OYW1lL0YxMS9CYXNlRm9udC9BQkNERUUrQ2FtYnJpYS9F bmNvZGluZy9XaW5BbnNpRW5jb2RpbmcvRm9udERlc2NyaXB0b3IgNjEgMCBSL0ZpcnN0Q2hhciAz Mi9MYXN0Q2hhciAxMTYvV2lkdGhzIDIyNiAwIFI+Pg0KZW5kb2JqDQo2MSAwIG9iag0KPDwvVHlw ZS9Gb250RGVzY3JpcHRvci9Gb250TmFtZS9BQkNERUUrQ2FtYnJpYS9GbGFncyAzMi9JdGFsaWNB bmdsZSAwL0FzY2VudCA5NTAvRGVzY2VudCAtMjIyL0NhcEhlaWdodCA3NzgvQXZnV2lkdGggNjE1 L01heFdpZHRoIDQzNDIvRm9udFdlaWdodCA0MDAvWEhlaWdodCAyNTAvU3RlbVYgNjEvRm9udEJC b3hbIC0xNDc1IC0yMjIgMjg2OCA3NzhdIC9Gb250RmlsZTIgMjI3IDAgUj4+DQplbmRvYmoNCjYy IDAgb2JqDQo8PC9UeXBlL1BhZ2UvUGFyZW50IDIgMCBSL1Jlc291cmNlczw8L0ZvbnQ8PC9GNCAx NCAwIFIvRjUgMTYgMCBSPj4vRXh0R1N0YXRlPDwvR1MyMiAyMiAwIFIvR1MyMyAyMyAwIFI+Pi9Q cm9jU2V0Wy9QREYvVGV4dC9JbWFnZUIvSW1hZ2VDL0ltYWdlSV0gPj4vTWVkaWFCb3hbIDAgMCA2 MTIgNzkyXSAvQ29udGVudHMgNjMgMCBSL0dyb3VwPDwvVHlwZS9Hcm91cC9TL1RyYW5zcGFyZW5j eS9DUy9EZXZpY2VSR0I+Pi9UYWJzL1MvU3RydWN0UGFyZW50cyA2Pj4NCmVuZG9iag0KNjMgMCBv YmoNCjw8L0ZpbHRlci9GbGF0ZURlY29kZS9MZW5ndGggNTg2Pj4NCnN0cmVhbQ0KeJyNVNtu2kAQ fUfyP8zjbhWWvXltSwipIWnUqkhV4rekDy6Y1CoQySat8ved2YViG6xGFmZ3PJez58wsTL7BdDpZ zD/fgJzN4PpmDtd5NJp8sqA05OtopEDioyCTQmoLiUyFg3yLPncPWsNzE40kPIetOWzvohGgu0HH 5SOzwL9D/iUa3WLmkD0+y56KTLazoxVjp9IkdtaPPsOmpBVZK/iR9UuePBPhXMf1oeIZ2/GxZUtu WAncsj3tftKr5CnmGhtW7XjMVmSqflcrnrBXWhcboL97rgxb0Gr+MR+orK0SUr0LpLZGJEnHdU3J N1xJ9sLHmv1BMA3Qaos4cL3nLuD8gV/wDGjziL1tj4twmqqmGG9suFLhoGVBRn+2twFEJrXCdRGN B11TYbpiIDosWCDNod5ApFX6nSpaFfdVpOyepP1RttpLo1Eq+YFWX+/zIW1saoSxnXxXgIz2++By 9GEyXGZEZtt6FVWNfeVY2TSknKedeixkXP46arYlBVCRVzTUJQLelhiXeN2CQxD5n2Le6BuB0tHP d2ONHPhPvptfMJHfYfYBqZQTznSB1xsah5LIc6fGKXbcHnsJt9R+CPGwewNPre+pAX51Rvx2Cg1q a7RQXdcnhqUqURKJ4go0FW1pijQ0/9MmQQDHTlkTmaFN6iNHpxGh+S9W5BKmnYp654oI3bXoT4LK lxrFsU3RnKS6ML1PfGj441iopIUYxuEMdJWKwSvDSZGZdpS/Pzssw+1iDtC68VXrxu8T5ixN2LlU PslfUl9G3w0KZW5kc3RyZWFtDQplbmRvYmoNCjY0IDAgb2JqDQo8PC9BdXRob3IoTWljaGFlbCBB LiBSYW1hbGhvLCBQaC5ELikgL0NyZWF0b3Io/v8ATQBpAGMAcgBvAHMAbwBmAHQArgAgAFcAbwBy AGQAIAAyADAAMQAwKSAvQ3JlYXRpb25EYXRlKEQ6MjAxMzA1MTMwODM4MjMtMDQnMDAnKSAvTW9k RGF0ZShEOjIwMTMwNTEzMDgzODIzLTA0JzAwJykgL1Byb2R1Y2VyKP7/AE0AaQBjAHIAbwBzAG8A ZgB0AK4AIABXAG8AcgBkACAAMgAwADEAMCkgPj4NCmVuZG9iag0KNzEgMCBvYmoNCjw8L1R5cGUv T2JqU3RtL04gMTQyL0ZpcnN0IDEyMjIvRmlsdGVyL0ZsYXRlRGVjb2RlL0xlbmd0aCAxODI1Pj4N CnN0cmVhbQ0KeJzVml9rWzkQxd8L/Q567D4s1oz+QymUbUuX0hKawD4sfXDTu2loYhfXgfbb75mr 8cYkJrl38rAtxJHsq3M0Gv0kW77OzXlX2CVyJTjy7Ep0lIIr2bGPrhTHKblSXWA8Sy7gUZqLMbnq XWzZVXIpFldh0qqrweXkXUVjmFU0TtFVXPZoicsJj+wa45XmWvMOf+Qjuybdt+jwRxTRJDlikqYo c3XoiUKApqBs5NAXxRjggVIaexhJIOQJFXkZAVDGyMjDu2A0JI+SpA0ElaRr2NYsfePVhv7Iw7hl kTekgOGBduwxbiJyTIzrxKhg4IjUMQfIKaFSpQ0SFwLMCKkLGCRRdRyjNIZhlHEyDFMcB4iKjAjd cI5ozMFxkREg3Sy5I4ZzlegYzjUjZiSPG4kPnFtGzNxc8LCnQKhgPimwC6Kg4FGRZIWIOcwwDNmF QJLGgkqVS5jeMULkNyQMjiJUKSNCvBpyGHOPigwHcxWKJBzJD1USHuFcx3kAH00SjvmLXpKNy9FL wmN1URKJuUJFEg5KokwwQRBZEp7YxSAJB39RQMN8gjRJOBiMURKe4JyCMArnBLAIRMUcZfLhnCW9 yFEsCIEynIsEluFck+AA5yaTj7GBGsiRvuS9tCmoQEGALZGkFzElaQh2XGLJWAHrY6iyZAJmj7Bq UpClg3WTIkvjJOsBMWMJpRSkDZxTFfTgnIUNrKCUhXysoVSQSIEpFWEcCwhtIYcgNYEaVKUmwWPh ZD+SW1CR4DF5WTglTEyW4RJMM0vwWCKZJXgsoDxON1KDzmGIJZYjS5uECsIE71i1gIjAYk5YykJM zkHkcM7ohxFKLsCBQWcu8MDicFkAYKyvLKHKjpEbZo8RZfFe9pCCCqYISS0y/1n2DXCSZeMAV8h6 DchmkT0D042wa5LsYQy1SAB41Cq7QJarknPE1xhTyuigReDz9OniSHrw7v3ieHG0OPnxdVgcbzdX p9uXF8Pl4s3fzn9wi6MzF6TNs2ePH02Q0HwJz5eEQxIw1CXHX5erW6pd88UbFydKnp9ur5YXJ8P3 7RP3m5N+04P6zRNHB7hwVd5GxmJsOz9HZb6kzpc0AyIWrAxckQEsOkhWzRNnmNJtzZ+ri/PVcPx5 CdXzi+0TkHSo42iYrg5INQJCeb5Gpw5vXvsabDR356e3lwRN1NxeevzAnsNUoMd0yCeqsUjXub3R 9d020aBJBk02aIpBUw2aZtDQYcKm7Q7zRIeJmrY/zBNZYCALDWTBgSw8kAUIshCxAyLP/xQyS8MG TTBookGTDJps0BSDpho0zTKnJhAsJJAFBbKwQBYYyEIDHcZBTrr3vIHm3Vt3maq6/eZNFkjkXC7v wXIsv34Tvhl/uCf+xBq/nyo6EH7vu1tZ+mZD37/3vsND+472caeH9j31xCPfs/SpzloWLauWrZfR a0nXSNwIb9ION0tTDZpm0Ox2uHmiw3BO2+HmiQ6jOG2Hmyc6DN60HW6eyMIDWYAgCxFsIYItRLCF CLYQwRYi2EIEW4hgCxG7aTJ8Rp2lYYMmGDTRoEkGTTZoikFTDZpmmVMTCBYSyIICWVggCwxkoYEs OOwyXg1Lb46G79a8prvW3pyOokGTDJps0BSDpho0zTKpJhIsKNA9LNy99maJLDCQhQay4EAWHsgC BFmIYAsRbNocLERodHnWp8jDmt0dqKPlZntwrffjU+Fe9K+4Sz9z9dtX8vsEKWo/YNV+9K5dULug dkHtgn6DQ36RIEXruv59vPzuYCz6Ka71Q1zTM5zXM5zX471nLYOWehb0SUs9E3o9E3o9E3r1I/Uj 9SP1I/Uh9SH1IfUh9SH1YfVh9WH1YY2L1Y/Vj9WP1Y/Vj9UvqF9QfVS/uHuuflH9ovpF9YvqF9Uv qV/S+JL6JfVL6pfUL6lfUr+kfkn9svpl9cvql9Uvq09Wn6w+WX0UKrnR30v1UcpIMSPljBQ00tub pPc3qaifEkiKICmDpPSR4kfKHymApLfBqKqPEkmKpNzU76XGpXd4SG/xUFM/hZaUWlJsSbll5ZaV W1ZuWbll5ZaVW+68fnC6TPeW5clmGN6v19vF+/XF8Hb51fUUy/IdVuNV15M9rt3abfauvhu+b98M P9zuG7lX8Fqtt8Pinfx7ufp0/US+zvm4/r44Hk63i9fD8tOw6XXR7Or7tyjHF56v4LDcnq9X+nyz Pf9nicr47K/15svH9frL4sX69OoSMY2vfPs8DNu+A71dnm7We8//+Iz/e89fnC8v1md7LxxfnH8a 9tr2ftDsbLO8XLw6P7vaDDrWd1eX37B3uh11TqeXx18/SC2MP3+QWhx//yC1NP4AQmp5/AXEfxNz z9544E68Yafsut3t2tZ7l753u+aBe47/5x7ag/t5NtIb3wOPwdm+MfxVdmEd5M+xFWswv+Z+3IO/ tSk/fvQv6jAo9g0KZW5kc3RyZWFtDQplbmRvYmoNCjIwOCAwIG9iag0KWyAyNTAgMCAwIDAgMCAw IDAgMCAwIDAgMCAwIDI1MCAwIDI1MCAwIDUwMCA1MDAgNTAwIDUwMCA1MDAgMCAwIDAgMCAwIDMz MyAwIDAgMCAwIDAgMCA3MjIgMCAwIDcyMiAwIDAgMCAwIDAgMCAwIDAgOTQ0IDAgMCA2MTEgMCA3 MjIgMCAwIDAgNzIyIDAgMCAwIDAgMCAwIDAgMCAwIDAgNTAwIDAgNDQ0IDAgNDQ0IDAgMCA1NTYg Mjc4IDAgMCAyNzggODMzIDU1NiA1MDAgMCAwIDQ0NCAzODkgMzMzIDU1NiAwIDAgMCA1MDBdIA0K ZW5kb2JqDQoyMDkgMCBvYmoNCjw8L0ZpbHRlci9GbGF0ZURlY29kZS9MZW5ndGggNTA5NTMvTGVu Z3RoMSAxOTA2ODA+Pg0Kc3RyZWFtDQp4nOydCXyUxf3/v/M8zx7JZrObhBzkYDfZJIQNIXHDZZRk c4KEQICoCaIkHBEEMQqiKJVAxSNetFoPvPCoWrWyeeIRwCNV623Bq+JRQMF6oVBbbavC8/vM7JIE hT/h/2pYW+f97Hzm+s7Md57n2SfP7BViRJQE0ai1YuoJY88c96SXlNemEyUuG1tRWTXbefpEUsw3 Eim3ja2dNHWn0xdBSsRoogcvGTv1xLLnbp13KSmPdBGlXDB+al3Vmd55ZrQ/Hr0OmlA3dZxn7rWo y9pFZD9l0tR8X0Jj42voy4r6xtryCXXLEi/+Fv03Ij/ypIqa+qkPLYwlKhxHFHPdrDObWs67Ztc8 YqsuRptfz1qy2N3y1d9OInZHLZE1u7nl9DPnupu+I3ZZEpHpq9ObFrXQAIJ/ZtST8/QFS5tX1ry9 gNjvzkef2tzZZ57/wV92Xk9U8T4x/31z5zTN3jrjj34idiUffy4K4jT7auSfRT5z7pmLz79/jRVt lblEnovnzzlnoXG90ULsn0NRv3PBWbOarCUD9hB7fxlRcuDMpvNbEqrj1qP9J6h3L2w6c86Q+h3P EvuXkyh6UMtZixYbmfQM/Cvg9S3nzGmZv/C46cSujiKKKyV+LEwxu75IvSRphuP4r60D+W4iunPH iCoev/B04aTvLt97pZOsI2AbIew5iC3p+yrpZCd9d/m325zUXRNCm89L7CfTWFJEgUJOyqeTsBev wLgcVT1DeZxMZDWtMRWig6xgrK6lZiWWmRTFqlpMJkXVtpPX6KLzeasI3rCuptxN2Mx+0/x9VazQ ks42+okZhoHW95om8JmSZj6WpQYHDoX7aZ12NgWoD8C+LBRPE7MhGo9wKYIPIR2h8KDtMMah+jQ9 jz3Qk045nA+Wq2jI/rS2g4aH2mUfqs/DAZ+n81i9iiZqi2gS4knddYuoSjmWvPvzSOea76cJvJzP fX852lSraTQZ88xGXckP+o/pqy+S/056nyMSiUQikUgk/2nY9caGcPvQV7S//vf4KpFIJOGEkbHB iuAked2USCQSiUQikUgkEolEIvnvxn6yhTH2G3N3gQWbmSNyA4KFWUTdFnVEUygRiZU9vUygpAlJ iPKJRlw1YQI02cw/5nPT0ZjCwcgK18CSnzrs8Cb7GXJ4E0kfwVUm3C5IJBKJRCKR9DsqqYxjUlWm 4P4nybTL1kX/shpkpQhjH0VQJDRSqI1s0CiKMvaSXWg0RUMdQp3kML6nGKGx5ITGUYzxHdZnsdB4 ioMm0ABootAkiocOpCRoMvRbSqGB0FRKhqYJHUSpxr/JRWlQt9B0GgTNIBfUQ27jX5RJ6dAsyoBm kwc6GPpPyqFM6BDKhnppMDSXcqBDaYjxDeWRFzqMcqH5QgtoqPE1HUN5UB8NgxZSPnQ4FRj/oBF0 DHQk+aCjhI6mQuixNAJaRCONv9NxQo+nUdAxNBpaLLSEioyvyE/HQUuFltHx0HIaY/yNKqgYWkkl 0CryQ8dSqbGHxgk9gcqh46kCWk2V0AlCa6jK2E0TaSx0Ep1gfEm10N00mcYjPYWqoVOF1lEN9ESa CD2JJhlf0MlC66kW2kCTodNoKvQU6C6aTnXQU+lE6GlCZ9DJxufUSPXQJmqAzhQ6i6ZBZ9N04zOa Q6dCm4WeTqdB59IM6Dzop3QGNUHn00zoApoFPRP6CS2k2dCzqBnaQqcbH9PZ0E/oHJqL9CKaB10s 9Fyab/yVltACpM+jM5E+X+hSWgi9gFqgF9LZxke0TOgv6BzoRbQIupwWQ1vpXGMnraAl0JV0HvSX Qi+m86Gr6AJjB11CF0IvFXoZLYNeTr8wPqQ2ugh6BS2HXkmt0KtohfEBXS30GloJXU0XQ39Fq4zt 9Guh19Ilxja6ji5F+jd0GfR6uhwlN1Ab9Ea6AnqT0DV0lbGVbqarkb6FrkH6VqG30Wro7fQr6Fr6 tfEXuoOuhd5J10Hvot9A7xb6W7rBeJ/uoRuh99JN0PuE/o7WQO+nm4336AG6Ffqg0N/Tbca79BDd Dl0nNEB3GO9QO92JtE53Id0h9GG6G/oI3QN9lO6FPgbdQp10H3Q9/Q66QehGesB4mx6nB6FP0O+h Twp9ih6CdlEA+gdqN/5MTwt9hnTos9QB/SP0LXqOHoE+T49CX6DHoC8KfYk6jTfpZdoAfYU2Ql8V +id63HiDNtET0M30JPQ1esp4nV6nLqTfoD8g/abQt+hpKEaDvk1/hG6Bvkbv0HPQd+l56Hv0AvR9 etHYTH+hl6Bb6WXoNqHb6RXoB/QnYxN9SJugO4TupM3Qj+g16F/pdeNP9DG9Af2E3oR+Sm9BP4O+ Sp/Tn6G7aAv0C3oH+qXQ3fSu8Qrtofegf6P3oV/RX4yX6e+0Fel/0Dakvxb6DX0A/Sd9CP0X7TBe on8L/ZZ2Qr+jj6Df01+he+lj40XaR59ADfoUKq/p8pour+n/e9f0W+Q1XV7T/+ev6UP/B6/pu+U1 XV7T5X36T/Ca/nYYr+mEKy7Zp9sSIkhVNXPvV2p6veutBQut4hEkkr8zbqVeJfwtcRNvYIG5FmlB ymTSLNTrrfKjjRaugSU/dZS+m1r6z4ufHcyWEG4XJBKJRCKRSPqbqCSxtuq5izzU2ipiv4FNrq0k /8XItVVYUKKSwu2CRCKRSCQSSX9jT4788drKwhG50Bol4sC1lVXkInp6MZP5wLWV2SzXVpKfJGrf Ta2HN5H0EcWeHG4XJBKJRCKRSPobx6Ao0jRTz12khs3KETlTsNAmHqEWfFXFc5E9vVjIwhtY+doq iqfMFtFl2F74l2srySE4grVVxOFNJH1EcQwKtwsSiUQikUgk/Y3TLdZWPXeRh1pbRXW34PecUdRr tcVf4D/42ipsL/zLtZXkEBzB2iry8CaSPqI43eF2QSKRSCQSiaS/icmw/3htFcERudCH+n6wtrL9 eG1ljeDfyeKfBozmTa0WcwSFcW0Vtg8jSn7qyLVVWFBiMsLtgkQikUgkEkl/E5ftIJPJ1LNOMmGL 5IRyAjtR9H6DWL7Oig4W7ieSIiKxloqEucnBm1qtZt5B2D5UZQrXwJKfOkfwlmbU4U0kfUSJyw63 CxKJRCKRSCT9TbzXibWVpecukq+tbByRC31hyiEeQeL4OstBvUr4W1iRNqylbHxtFcObWq2WH3wl 6+gi11aSQ3AEayv74U0kfUSN94bbBYlEIpFIJJL+JqkgjsxmS89dpBlbFEfkQh/qixGPIIl8VRVD vUr4C/w2O9ZSdizFLHF2NLVFWO0Uxhf+5a9nSw7BESy7HYc3kfQRNakg3C5IJBKJRCKR9DcpI+PJ YonouYu0YIvmiFzoQ31xRAP2Gwzkq6oBwcL9RFOUA+soB/89iwQHmkbZRJdhe+Ff/nq25BAcwdoq 5vAmkj6ipowMtwsSiUQikUgk/U1aUSJfWzm7C/jaysERudCH+rCUit9vkMq/chVPvVZbfG1ld2Id 5eRrqySnWFtFOqnXl7SONnJtJTkER/AzJ7H958XPDi2tKNwuSCQSiUQikfQ3bv9AslptPXeRVmxO jsiFfuMiUTyCuPiqKpF6lfDfDoyOxToqlv+P4ZRYNI2OEl2G7UNV8j8TSQ7BEaytBhzeRNJHNLc/ 3C5IJBKJRCKR9DfpZck/XlvFcESuZ22VtN/Aze85k+gHaytHrKN7bYWmDrvo0tn/Ezg4cm0lOQRH 8FU8ubb6z6Gll4XbBYlEIpFIJJL+Jmt8GkVE2Lo/8YdVSQTFcUQu9GMUKeIRJJOvqlKoVwn/6pUz 3kkUH0kUmRaPVZUzOop3GbYPVcn/TCQ5BEewtko8vImkj5iyxofbBYlEIpFIJJL+xluXTjZbdM9d pA1bPEfkQl+YGiQeQXL4z1kMol4l/MtYcYlYjCViKRaVkTgAiy1ndAL1+pLW0Ub+ZyLJITiCr+Il 958XPztM3rpwuyCRSCQSiUTS3wybnklRUY6eu8gobIkckQt9YSpdPILk8nes0qlXCVECDRiIFVUS X1tlJqHpgFjHDz42eHSR/5lIcgiO4OOiqf3nxc8O87Dp4XZBIpFIJBKJpL/xzR5MdntMz12kHdtA jsiFfoU6UzyCFPB3rDKpVwl/IyshNQH3otFoPyQVTePjRJcDj8IMDkrYfqBQ8lPnCD4u6uo/L352 mH2zw+2CRCKRSCQSSX8zcoGXoqNjez7fF40thSNyoS9MDRaPIIX8HavB1KuEv5GVlJZElOYgcuSm JRMlxcem0QFfyTq6yP/6KjkEtr6bph/eRNJHLCMXhNsFiUQikUgkkv6maHEeORxx7u4CB7Y0jsiF /j+wVzyCjObvWHmpVwkWVZTsxorK5SRyFrhSiZIT41yiPEw4wzWw5KfOEXwVL/PwJpI+YilaHG4X JBKJRCKRSPqb8kuGU0xMYlZ3QQy2DI7IJQQLC8QjSAnREJHrLiHKoEFZg4iysBSLG5mFpoOSE7JE eZiIC9fAkp86R/BVvCH958XPDmv5JeF2QSKRSCQSiaS/qb6+iOLiBva8BxWHLZsjcqEvTI0UjyDj iIaJ3IieXrIofUg67kXjieKPH4JVVXraQH5jmn00pnAwwvYDhZKfOkfwcdFh/efFz46I6uvD7YJE IpFIJBJJfzP1nlKKj0/puYuMx+bliFzoNy6OF48gtfwrV8dTrxL+8cCsYVhRDUskSiwfhqZZ7tRh dMDHBo8u8j8TSQ6Bs++mhf3mxM+PyKn3hNsFiUQikUgkkv5meuc4Skx09dxFJmIbxhG50C+llYlH kJOJjhW5sp5ehtGQwiG4F00mSq4pRNMhmaLLsL3wL/8zkeQQHMH/sx7df1787Iia3hluFyQSiUQi kUj6m9kvTKSBA9N77iIHYvNxRC70S2njxCPIafwdq3HUq4TIR0NHD8W9aCpR6pTRaDp0sOjSdzSm cDDkfyaSHIIBfTcd039e/Oywz34h3C5IJBKJRCKRHAXUUEglJvJvIocUe5c04q81e8mNVCRl0FAa RsOpiEqpgmqolqbQSdREc2genUXn0lJay44x+w0DbdzCtuBHtrNoLi2gc3psjR2H3WYZd38fCPnW R5iZuhswRSFSfmiAKWum7qyDYihuQHxC8KOEoV83zOz1M/MF/ANi/Atmx/b0UUFVY7G+rJ5ANKl2 8hSiE086uR7l//H/kar23fStXun/2qPnLzuxzl9SPOb444qOHT1qxPBC3zEF+cPyhuZ6h+QMzs7K 9GSku12D0lJTkgcmJSbED4iLjXE6ou1RtsgIq8Vs0lSF0dBKT1WjO5DdGNCyPePG5fG8pwkFTb0K GgNuFFUdaBNwNwoz94GWflg2/8DSH7T0d1syp/t4Oj5vqLvS4w68WuFxd7Jpk+uRvqrC0+AOfCHS NSK9WqTtSKeno4G7MmluhTvAGt2Vgaolc9sqGyvQXbststxTPicybyi1R9qQtCEVSPS0tLPEYiYS SmJlUbtCVjucCiR7KioDAz0V3IOAmlXZNDtQO7m+siIlPb0hb2iAlc/yzAyQpyzgyBUmVC6GCZjL AxYxjHsenw1d4W4f2tV2ZaeTZjbmRs32zG6aXh9Qmxr4GDG5GLcikHjBzqSeLDqPLa+/tHdtitpW mTTPzbNtbZe6A2sn1/euTefa0IA+0FbJqmpsq8LQV2InVk91YzRlVUN9gK3CkG4+Ez6r4PzmeCp5 SeMZ7kCEp8wzt+2MRhya5LYATVmaricn+9cb2ym50t1WV+9JD5SkeBqaKlLbB1DblKUdA/3ugQfW 5A1td8YEd2x7tCOUiLL3TszprhMpYc5T1VO69yzjHnlOwAkRcM9yw5N6D+Y0msuc0dQ2azTMQAND q8BsHJF5gYjyxjZnES/n7QOmLKfH3fY14QzwfLHrwJKmUIk5y/k18SQ/T7pPNdTvTwdycwNeLz9F LOU4pvCxWORH5A1d0qnc7mlxuhFh91Et9m1TQ1E+dn96Oj/AV3T6aSYygdbJ9cG8m2am6OTPz20I KI28pmt/TfyJvKZ1f01380YPzuSHxXM9PmDN7n44nAlxlXOLAizh/1E9J1hfPdVTPXlavbuyrTG0 b6vrDsgF60d314VSgbjyejVFCaWUFFXU4qSc3m3MM/VRAS0LD7M4qWd3Wqw4K0UJc1cFnI3jgtoQ mZ7ex0adxh7eSkQ9zUJuBopyD8wfd0D+APei2lQ4rGUr1XXT2toiD6irwhWora3K465qa2xr6jRa Z3rcTk/benWwOritpbJx/xHtNDZckRKourIBk5jLinC2KlTW7mGXTW73s8umTqtf78TV/bK6el1h SnljWUN7Jurq17tx0RWlSncpz7l5jqoZznRdsYqqlPV+olZRq4kCkZ/VyUiUWfeXMZrVqQTLnKIM 8Cd6eV1970MonhcNeUTtde5OLaojKtrHYz0u0dep2Tpy3C5HqVOLpVYEhRzQEoQZCKpQRn4tVj+/ 0N+J6JxgtDAYnRGM6gr9j8NwPBUaXVpsR2KSjxd3REb5WnlsjeD5GH1aob80QovBnzluF0NTg7Fe Wyiqa3gvMTQ2WNpRURlsVRYsLg4ZFxW6SjORdyP4EVoQ1iHsQTDD+xjKR1iNYCBoIsftliNcg7AW YTu3Fb1ZCx2lKZoTNU4xdye5EPIRVGrUIjD3gFCHZsVesdIkhNs1C2lapE4LXOvRidpRKTxVO3KH iVjPGeITFXpyqu8J/KW8Cfc4LhQwPSFF1JBeVhZKjBwdTHR483zbSiM1ot0IikYao5xgq46cYb49 TyHP1H3kYIyXqt93OAdgNHVvhyPO5y91qv+mWgSFAmo7dSEodJb6NS1HUGC+Ts87hg+kruuIjPY5 Yb+b3AitCCqthTKR9yNw+90dcQm8+491R4xot00vGB5MdDiTfLWlA9T34c+L6uvkIZf6IeJBiJ9H nIb4OfUFsgs/7+5wOH2tGO8umN+lLqUhqP6tegH5EN+nXkQpwuwdPTo4zjt6jtdXGqneqy4TJovU s3FD5VIXqPN1n8u9Ub2bn4/qro4IG/dvl+6M9z2hfqrOpwGw2gmrRJfjCXUh5SPwmXR2RNh9q0uj 1E5MsxO7xQUfGd0u1K++rqMjjPc7tZUSULdJXUHxiO9XV+rxrq6N6j+F2Te8F4x3J84YHnXYo31d pRHqnfwMUb/CHv9KjPaPjuzRPirNVq+kAgQFO3UHUjuQcqpfIvUlDtOXODRf4tB8CS++xElL6heo +QI2+epWalHfo9UItyOtoculOvbgepHIzPGtV3+hLsOecG7EvmMovagjIpp7tkyPjRNmy/gTvOQJ 9W2ahKDA+S38GXnWRvVqMZXVHUkpvMGbekQUdt2FwWOBhhfwY/CE2qquFHtihdgDgSeRxfmv/lI0 NjqiYnzLcfTrkD0Leg3CZoTdCBrM6jCHOpqBoMK8tiPa4XNsVKeJxifo0YWuJ9RxmPo4sbfG6fEZ wuexoYTm0FMG+Z7kCcrDHzGfFq2Z9XzX5I1qNc6fSepEfbYLvk/W0S9vOLFjdJGvYKM6UeyLibrL EyzW4waKRJUeETyvyjsiY7gnFcIwV7dGi+Lc0FNS9XYMSPS5cJ4WidkWitXLKBy+UTg0o/A8KRQH w9fhjMXZP1v1iRn5qBFhLUIAQcMx9sHch2Pso+2ixKGOxHRHkoGg4tiOpD0IuNSox1AJwjUITyFs RzCJ0kYEBeUFGKERuhpBQY/5yDuhfoRGhFaEtQhdCHsQLLRJzcM4ebAugLYiBBC2IWg4VkPhx1DU xapu2mvlH5dcrtzkL2LLaTlbrixXl2vLTcudy2Os/hFZQ33+M7gM45IDGdUY0RLRGqEWRPgjaiNU Z4Q7Quk0unRLUSEif6y5qPDdms9qvq1RY0etNq+2KJtKo1gMbUPYjaDSJuZEzomc03+puql4W/Hu YnVTzbaa3TXqpq3btu7eqm7K25a3O0/116QU+UbNYGex5ewaprlYPithk5g2Qz1LXa5eo2ouNV8t wbmgNdpabK02tcDmt9XaVKfNbVNW29baArYu22abKWDuMm82bzfvMZtqzY3mFnOrebV5rdnssuRb Six+s7antFx5Dzt1LTSAoFArdLVIOUVNF3SzyK8W+UZoi8j7obUi5YEW8BSCB329C7tW6GoEbsfz HmgBzyN4cHV/B2Ut0NUIivKOPzWjINOfqTgz3ZkKZbI9mWxz5vZMJZDZlal0lRYpW4SXW+DlFuHl FrTcIsbegn6RQvDA27eF3duwe1vYvQ07njpYWSO0RaT80FqR8kALeEp5W/eMcpQmKjejxxnQ2xG2 IaiUDy1BOEvkXNxCuRnqV9Z0DB6KP/jKGj0b10hEGcFoUDBKFVHHwGTfjFKHsgZdrkGXa9AJz7kQ SnjO6FJu0iu47U36mGBUVLitdBT+inJXbqJ1CApNgt4uUvnQEpFaJ2wc3fkAdLtItUDXdrebIVIu 6P62qrIG201IOZQLUHqB36ZQAv+R0dgYa2ynskGfF+vqVB7Wc5yIOoKRzqPSOEXFvrezL4U+JPR2 odcJPVmow2/z2P/tsf/RY7/XYy+NVMZTJor3CP1U6Bn+6Ez7J5n25zLtd2Xa78y0b2Q7KAMV6f7k DPtHGfa/ZNgfy7Dfn2G/NsM+PcM+OcM+IYN3lUNusitpXNlpQlP9iW779277B277y277C277HW57 g9te5IY5+wp/T+3sFqE3CB3x2HC7a7g9bbh9g4IrEztFd1DERkVhp5BdjdS9xa5ONUJESrpek4Uo Va8pRZSi10xBlKzXnIMoTq+51lUaoThYO25WXEo0a7fyOEr3rkC1LRhZde9piEy691hXJ9unez2I vtOb0xB9qzcPQvSN3jwc0dc8epz9nZoVdMP+pjffhu7ZZ5TDu2UfU7byAOJOvaYE1o8FR2cPUzHL QjGWVdwL9qDuhXPsPt2bg+he3ZuJ6J5gdJfudSG6Q28ehug2vflaRLfqzTsRrdFzFvD+bqIc0c+N lC3iRXpNCqrP1mt4Dy16TT6is/SaEYjm68WvIpqnF+/kTU9n7QxnNmsmr/C0SW/2onpGaCKnUo6o nk4jRM9j9Rq+S6p4J6V2VhmaSAUr5/d8rIy1i178urcAZsW6NxvRmOCeO15vzkU0Ws/BPmaj9Jzb sOdGhgYYwo/P4ywTbvCOPLr3ARi59OYhiAbpzZWIUnhLOBUXGjWWioVTMbqXWzl1r9v1JLNRs+gx krLZmkdde9Hvd8Wd7CTd9a2/08p01z9zED3q2lUz0/V5TSfueF2f4Sn8wKOubTDdWoyk3+Z637vT 9V5zhuslLyz8Ka4XvcNcz2QvdXXmbHR11AxytcOxQPNM17pm0cND2Wimu+7L6VQYWq9tnuC60Zvr uiG7k/vwaxhfysdAR6u8S10rs1e4zsWpsLjmctcib5qrJec01xk5fKBE1zzvFNdcTOR0tJnTfLqr yXutq3GE8Pg076uuqSPEHKqbxYxOKBYV45qnuKrgASpKeAU8OA7npQ9Nh43YyPcR7lTKO151nTjq cQV/hVkrwjn+YZYnLBdZZlrqLGX4ezPYkmVJtwyyDLDGWp3WaGuUNdJqtZqtmlWxkpWUAZ3Gdn8u f8l0gNnJI7PGVRNpp8KVv7qKexKFWRUstAJxarVSPbUsMCq3utNiTAmMzq0OWGtPqW9n7OoGVh3o mkXVM92Bb6Z6OlkkVsEmTxkLxFZTdV1ZEowDymVYTtbVdzKDt1iVwl9aWk+MDV11VQqPq1Zd1dBA CUtKkkpii2OOrao4iDSGtLIit4ek3NwDcmmB66un1gfuT2sI+HjCSGuoDgzhLz+tVxYoZ1RWrFfm 86ihfj2bqyyonMLL2dyKBpgdJ8yoWJkPM6rhEcyU6VTMzVA+vZcZa0dxRXtxcdBoEmvnRnjSTBJG 04JG5b2N1CtYuTAqV68QRrcFB/TCDwzo5xHMTAvIKwb0mhYIsyRu1p6djZ6as7lJuy8bBu3ZPlE9 uac6J1j9+2D173l1J2M99SOyg97mULYYIVvJgU1uGJlT9v/RiHWMWbKwnr9s2OipnIPQGLhiydyk QOtMt7t94ZLQ64nZjTNnzeVx05zAEs+cisBCT4W7fUz9QarrefUYT0U71VfW1bfX++dU6GP8Yyo9 TRUNHRNXjD77gLEu7x5r9IqDdLaCdzaajzXx7INUn82rJ/KxzuZjnc3HmuifKMaqnlLGqmvr261U 1lA+PRh3KLZIPFsaU9IbyhKcLcXiqXNcetJFKRs0YveRLbchEOUpC9gReFVeaV4pr8JTmldF85eG Q1VJFx2XnrKB3ReqcqI4xlNGi5Mq51XgsQgsXnwuwD5etCi4r5OCFYtzK0U9DBYjtVgAS6R5WCRK Q/WL6dwecnODtrQot7y+vaamMmleRQpu4jv4fXduwyLKzQ0OmJtLGBOzFjf6CeJG32ZOKHyr5qOa r2vULnGHvxlhu7jD78Ld/WaE7bjDH6R2FW8u3l6sdtVsrtkO262bt27fqnblbc7bnqeOCnnAh2pg 8LBnOzd30bm8OJeJ2Yp5c0fgNBJ81vt3wyJRsVjsGBAsF01z0VFud/PcnsSiYOW5okmwdFHPOYwK 3v3ic3N/TKgUl2DT1eQyTRAhVb2O/wNk4wOEnQif7BtvfG+aT559Zxjb1ThcrjODIUQWXYwbvU/o enqKTqWXcd9YyYZRPWksiQbiwn4sVWP3JZIJf15zcNdYTbUUj2v9R8xO6+gY+oxV0Qr8cZ5Et+C+ cCIW6aX0K1rLxhqf0gp6g82jB9D6PuanwTSBjTO20WSqNR5j/Ittx9ENtIZF44/VBBbJPMZW9LCI LqUN9GcyaBrdaFqLXvh7UAuNx2g6vcamsVOMVDqBFtJFdCPdQU/QTnYZ69JMRiONoJl0DrOwOJaj rjTuo9GmLRGPGM8am8kJ+zvQ6y4lV6syviQ/faIxYy5OjzgqxLaQ7qRH6X2WxEao5RSN28/p2BfL aJ2aAx/H0eWY2wZ2IVunRht3YzajaBYtxyl1PutS0k1bTHuMCygW8xsOT9vobvoDPUOfo7cqVqee ua/EmIi/kVbKpUqMdDFdQg9hzz2N7VnmYOnsBPT8B7aVfaAuVP+Knu+lL+gb+hfLYfPYRUqJstLk 27vCeISyMUM/+jiBTqYF9CDLZn52CtreopynXISl8qPq+1qOttsYbTxDZsKSnFbS/ZjXn+gNehvH q4rVsD8rF6kdpkuMC+FvPs3FLC6m39J6+pqZWASLYgOYmxWyUZjZhayLfaCkKR6lXp2prjNdaSw1 rqJ0nCun0hy0PIN+SavoMdpEH9Ln9AVLRst8tCxhtewqLJGfVTapJ6vT1es1v3a99oD2tPa9Kcb0 9L7X9m3HXuf9FFANtlOpmS7Avu7E9gy9y1SWwgahpzFsPHqawZrZMraa/Ybdxe5hj7Ln2Wb2KdvN /q0kKVcq1ykblT8qm5TNaprqVSvU29VXtHTtXe07S9PetH1P7dtt2Ixco9BYbdxivGd8IY5CKs74 EirH2TWfWjH71fQbuhX7/GF6ld7CebdNbDtpD47Bd8yMs2kgPMpgHjaYDcXsTmb17DzWxq5ld7Pn 2AdsJ/teISVKycDmVUYq45Xpykpll/K9Gql61FL1fPUG9XX1W22pyYftAdMjpj3mnZYs6yvf37x3 6z7aN2/f9ftuNkbgXDTjzIvDc244leGcG4+jPJvOxnYOLaHzsI8uwB6/BWfOOtJpI71Ar2Dfb6L3 6H3hL98+xZH4B+2lfUzB8TQxK7ag7wU4MuU4WxrZHBzb4HYhW8kuZzdiu5ndxu7A/n2Nvc7eYNvY DvY15kRKnlKqjMWMapVTlFOxzVBmKSuUK5SHsf1J+bPynvKh8q3qVGNUlzpYrVRPVy9T29SA+rD6 pvqWlq2VauO0+drz2muY+TjTCaYZplmmK0x3mO4yPW16ybTTZJivNd9p7jR/Yom0jLTU4rb0csvv LBst71sM62CcTzXwvvd/FbiWnaLlK6uZoXRi3k8qi9WXlevYA73fQTa1wYPZWEx3qk8oty5brX6o PqisJNIqRPUYXMVeocfpFdMbWrzpE3peSaYvcT28Tm1SnsRSO4mNVI/TVmmv4KqzFH7epWxTLMo6 WHyOozGDTmQD6SvtJNqN/b/J1IZ9WqVsZQ8oz2HpfCptobuVjYRFPc1ho+DdbHqEvqVfsfWqmz2K 8245baZdtL3XG/X5e8uUEnOSssRchCO0nk02nleGGJ/jWf8BW0Xvqd/i3D+JTWT5dA/twFF/iw1n Lm2flkKv4co3iG7GWfsxdeA5+JKWiWfQ17ReHU7TtO045vl7X9xXYVqs/pJ9o5TicCaKK/ckfjXG NfhGXKv4dTSa1uFMwFVEPKM/p1dZBvbiG+Z3aQ1dQxvUeMpSf6u0Kob6guamX9N2dQJG/QWuT/9H 2JeAx01d+98rjZZZpdEsml0jaRbb8ngce8b2xBOPnNVZnLiFhCQwZIMQIDSx2ZpQmoQtLC2hlD3t I6VlKdBHikNiQmnS0tLyHiWm7Wvp8tq81l3g1a/w4aYL8fh/rmYSwuv/+17y+R5Jc3VHOsvvd86R nMRwAVa6Cl0O95Gc+X3tK7DCFagH9eCNeC2aD58MoMTMVXDlTwAWmTMXzTzMrGEM9AZehgPoGKBX CLT4AGOvTcLMQxCHv0AD+C40WrsEHQdeCeE07gBvmmSuY+5hnmYOMd9kfsDOQp+EqN0PVvwNmgLW SOJNoIt30F/B1+dC9LRC/PTDVQwAh22l1tAvo3k4grYDBjYBbs8FHawFS14Nq9yEPgPx9DhwyBvo XSxCxftN9BZEjgxxvgm+n4d1lqKVYPWr0ROAjjfjUThyCUqgFtDTP7AH91DXwPcRnH0AcPY4XNMv 0e8BOWas62rFvVAmr4K1/kpiGb6hCw1BPYBmDqMSMOV8+nX0O5QCdp0LMfoVOG89+IYHxVGJ+S2m UGtt+UwPdTn9Mg4CG3rAq84HZp+Dh+EqBLiPaRTAK1CxtghWewawbIh5HNjXAGYIUAHbBcxKuO6f A5O9gUZmVuNHOBIBFI6BdWMMebWEQ3MPUfgVlhujedOHGNsrNHJwtlcwCvMs8wpFfwP3IzsYYRUK GeKp8nR5uThVHpwuowpsi6dhmNWuelVvGgYcs6HTSfr4aZNBH6Ck7Th58+a5md9hknuIgLqffpk6 SP5XUerzKEHdOxq3YzRGh82Id7HsvCdxIEElZDni8i+OIDOsFNC3MbZauLCNXUJEiVCRVsGluCjX GPaZ9mMsZsPxt06EDLim6uBkdaIqlYz8pCFOLhcXXDr/91VUGZz+fWVWO144f+H8xfOxnslmM8VC V2dHMODnOJYmktU1cgxvbeWyhfxFSwbWdRRj2rx16+bNW3cxfnHksZ9/Z+XgxesWLxv/+TW1N9fN tz5ZbzXx3qSPwp25wOPWmVGKl/wFio/GCwg7bG6P7EWYYz1BD+UZwzvNsN/PYe/ebfKjMiVHoo69 SRu2hSMfXv5y8VR1cBr0Kk4Oe0sl7JVKJfIDlw9Jp05/eOEf3anO2uK/YM7C5SG8u+PS0Jq+RUsj 1Jt4z9JS3wUXFnMX1/bg3avbZ6++eJa+hdTpc2sP45dxJ8lgTO/fKczZbfjb6HVpscthWxoYwwtN J+5UBCz0h772WbD5VHVqehJVJqcmsde6mKqv2NVVLGQzusY1dGddCbv5mss5UKorbvRecMmiVTu/ Vnu4tePR87x2nvNe1Df3kluv2fcrcgVrZ/6AnwTccCLtEFrMOmliTWfS3m6n7GHXtjuIQk6DQuBL 4evONRFauGHjggUbNuCCJRYs2Eg8bMnMBP0Cs4X4PV5ihu1RVmHT9maZC0UDyUA61GzneHw9Hx/D juclJgtilHVL8hjtMNPITGUKyDTaYOjsgqF3TsGEuDoAsRHJSYKmAKeTmZ59buw2fYGCO9z6l/fI JZ4yRsDn5q02Zc1MZQsaWUQji2hkkW0aHiaJ+RqYaG0MTpI2hgzVDEyWSVUD8y0JpxD5Apy1Xm6c BfdO7n7eDnMjbkmqikqxgkf0UGxKT+sU63Q5XHYX77KxgaA/SLHhUCQUDdEsBamTDdNsi9FsUGzC q21EGQ6GmE/eiJsYGFRPfCPWXdmNKBSELQPDllUnk6Gl8WcPGsbD2M95KFB8NkNipruLWFkOMiLZ J6ZnvaIcDHZ2dHd10y+UtKvvXbXxX+a0qkZf5/g11/2gfV7tdZsjE+4xwumIX+hp6wi3sNQT/35w 650fu6Q6f/jhL//niw9/+Uu3v/RLfEnvXbOSIf3r03+undy4qD3Zcy3xkr0AT5vAqjK6+RvIg7+G i4jHjx/W1nHbOAr3u60jHP47lCNB/DgS8F8BCosoSFGmR+ARw3MuOKgAlo/RdlP0eIaEbcJzAi2C a4dDnm9SCPHUqyhEyfjXFrZNkDCslgfF6SpBt4pU+svkafwXA1cNcEOvH+61M6AWOzvA+72FDNFB Nk3tDy4cVKa7UhcsiUizkp2LJfw+s+WDZ25c0JpONy3cTR27OK8mUxPkjjrgjr4AdxRDfzRTt1P/ Sj1L01nX/TTlcDqcGDFR6UDwUJAKxii4JoeTj43h9YelvHwQAGMMa89jiSfu4nQX+DE6dcjDYBeE zpQZRYzIUMwvpR8JMXwshmORhIDxMYxxOH4UMtV7EHHXieowAMzw4NR0dQJVKpOkfDZ9vBl0V3hT 9sAQFmBwlyz/AyXMu6jhrzDD8lOYZMmoaMnnY96KNXfCawEVAayqtySVYFd8jQAFqqpqEUnFgqUr y4EIYrFYBR12d9JDp3+Dt33xposfWZnu+uU9lz29fsmltWdxemt/i5YK4hdw2z2X3/WI+/jY+icX 33rHi7UXJGMB0aM681v6TtCjgU6YCifIwhZjh3Fr4Nbgft/9wa9KTwSP+py5WCVG+Xk8hu837eRf AgRzq85+O14P6b9KvY4y1Bsogni4Hbe3YOlVCoCk3jhsepiIG/nHKN+hJMaM4yi+Hzlx5HCirmYA gyPeH6FmsZlqJsDgFWQsR3JCAicIPCTCrefo3ACdDwNKTE1WxalpbykfjkyWUahSiUwahjg9IU5I pXx1UirV1YWLfdS52gLk44jKkKo1eMuKOEDfDM6PrDZ3rP3MxvTAf9352SMrL7z2htoParVnV5Tm GmpcfGXlkiuOU0/pauna8nnX3+d+8qlnr156V7H05Kd/XPtpqanS1u/hH7127R1/AMV0gl9+DfTp QG70sBmquKH6wzSyUZzdwfBuF7LxbrfTOYYvMkWE/WACJzAb73RjG3oJn0YMclCi6eIxw7vciBd5 in+JtsPCHF5vhvK2io0SbIqNskUERFSEwp46gk5A1FWrg1NlK+IqkFicKjeYTyrtbTNsN4rfEQSh rhsf7vR2BnRINdRu1dtJ3bLzU5+qTdYCG6AOm6EvP/3gido4bj9ByVbO8Qd8mv42MIyMOl5EYUgi wpKvwC5GnGux5BToxfbWYwEcCIfO0u8USWkszAVMPIdzfOfyzyqLdDZsmN/gIfrbG+o8tGF65FxG EiG/OggahQoXt5uf10SnVNksXider+8Vb9Ofdh8RuQfco24Kp3QKabquOjzOuENWQ3HZacd2io/b g95APIhTDqQFr9YFMakjVVQpVafUnFf0e72iTukq1eQR/B6PQF3nwR7HTi9WvaJgC+qq10PZsKwL WqoJzIXxhGiKAg3O43DYeSGIg0fxTUjHbaaedITbM9szuzMHMuOZkxk2LWaSGTMzBEfuyRzMcPuu AgUNi9WpcGRwerIKvlsW4W+lHCE4OQ328koyMZlcguyrWtrraTN4sBvIENmofscg8FAqhZA4icXj 9bF67g4nlstcGfJICIAqaF/l2IBfDsoAtgAT4IzB+g6hGpJ3ZLM0TZ9fU0uxtugVtTmLL16Af+fD by/MaX3T26MrkkGWil3xb+P4plvmGqWoyKfTzk37bbM/eOpfmhUmnQ6KCclnn/s+/lGNvJAQBVsN M8tAGthpXhTZbXcUdDKIZDDIcJlvS+iy9CPNY03MZd7LYedB70PBr/jYTR4uGUeaxifjHk2PtQke SitGo4iXcjEhrsSpeB/fzuEhDnM3ts55oe5pw5A9E5aBxEFEGTFDZQaRX/S3+2l/FySAb1ejhzOD 7X5s7U2usfLBShngYlb70vN2fP1iHnKCJbohRiSf10exTdnmbEuWZj/co9hgQA6EAuGAjU2lDTGT xi1k0CMwZH0xMhhwzEgHtDQyxPK55L9nDzEC2e0kTNfdoDq9qAL0SAG/h4KcjwYylC3m91rZQDTX WxHswXmlHLXu/fteeOmie4/dOefmtaIv2vnk6k9+vH/zQDqdDFxOf2pLIZue+7Ha2Il9731xXcRl m/ngV+dnHMLII1AjMV/Y2aoAukOtz20Be3ThFeZIgkSOM4HtiRsSVHvPgq6hniehXmTSsS58Pbo+ dn38NrQ3tjf+cPyp+Dvxf8Rd23tO9lCKpPgUv5gS04wgCT7Bj1Iobe9iHck4pWmRZFzStLbZ8Yym OZNxr6Yrs+NpTc8n40VNH5u53ZyH4rEkRqgpFvXHYlHU1YVQLp7wx+MJhLviMVqBarKrSGEqk47H JC+PUHdPVIzgSJ/jhPPXTsoZ6SGFiz2WKFgXBHu7TXsgWOhJKE35NvKZl3zWdrKNOt423ka1hbt7 xvD5o+qc60JjuPVWw1g+VR0xSKG1XDRGjFNVy2vCgIz5ELgE+UNGCyrlEg9gyUDQgQxZG2eedRHo rI5Uh1EVDRsYqwGSuEF4nZPNdFtGxjpkOIRcyLFg17mGp8fxdqqptZwKC87g/FLrdLm+Pf230PS7 jPuCaq3dk1ve5KTgQ4NqwW/Qn04HPGro0tM3EXvDthbaTE9+YNheP73gErmjkk5jpZB3Xkivvawz myZ4WUDI9jjYPAKGOvEiSs787XlXKTk28zfzImdpRQY/GDoln0r+XbO18DGEXck4p2k4GWc13U2M qUfbJNQWi7E+CdyTF1Ws/mp9cHfw0SAdvDOfwZloPRHMuZFLdFFDrvVQQt6YznwDCmwVimkOyNpS eCM0qyTyqiQHLIO+J0UIPoMWGQJREHwJRfdHQnJYpljdr+axEoFBC6TyOCkn8ghZ4dQIJLJj6RrU ejZvLKpJi9lZ2tsgc51qji64aHrFxfOi0flVagVO1b5yz4Y/qN6dt9xyM7W5dvsnSlo6rfd8gt5O tsa/cMs3tBD10PRh6nMPPfgZosEMoNjPQIM6yuFPmpWVkZHIQwGa10P60sii2CJtQ2yTxklA1azI iKytPX9Z9Pro9drt+uvRf9fH8/zDwR9H/h76IPxBhMnzrjHqPw5ZOrY2iJphwywRVUM4RMUoFc3p ml/XtV36XUBEqCWmRndrE9qURovakDau0eMa1uSWmKZn0m3RMfwbU9YRYlO5Nh8YKflDVdU0luX4 pDqGGdPuQi1iC9XyKyjKKDPoSqXBLRo2c7mGoPK6sW3Oizhs5enVMmEeQkIiEJJotSKsPYBJ2AOL lSeBl+oJ6fBItUQoqlQlxFT1QGyErLgAQyazrf5IIB3ONKVb/S15nI3AYARzedwcyuRRJHoWGo26 NespcRO4pdNVMnhXKRbyBfqwYT0sIunb/8fUjZSXa5AYpr1WAUFsngRbTy9p2Py6UxP3bF3wKSi/ o81dtZW1pWtKd9254nNfoq6o3fJR688/csMDG/uUWnFNUKHT1BXUw9P/2nnrlfvvs57Iz/wX8zz4 gYrjLyIdcGZ2JFUY13Gn7cEAJeq4R8Yl+XL5q/KYbAvKQBPhMHmsE0dhUHLAE3e7eGfcpYaTcdUc m/mM2SVzbJJHnMhRHJeTgZflAMOyTXIYtsIBnmNtLiYMwRDgGYZTIVmECLQDih4/kltc0GU5go7i NiTjm0wp6TLh2HoXdoU1fasKmcVZqDMi4cHp6dBy0rUxrMArl0laQVogcmnvYJtBLMcQePNYOUXk I+nER5KKvaKnTH6+zpLXzY+Ekry34JAxqhprIMUYHsGAhwYOsMQoOs5kssU6LAaA1DC2bAMFbpF5 fsnslvNqObWWP7+0grozuDopi21Yxa72YFIxFjHL0q55HS9+MGXremW+HdIKIS7NunK6Sq25akkk 0ebyWsh20cz79K/oV9AsVKaWmAFWFEu2pFjqMMvzC3cVP8/tL9J9hA42LC0eLuFPc0/kni0fyb2a e0v9ae6t4u9z9iK3gFviWyIvLq6WN/P3o/3Fx/FhfJh3dXJ4d9/DtkdyX5hlQ31DfZuC6/tG5AcC z+HHZx/DJ/scfHCo75peeoCnAlKA6iXf8h259Ode3NHJ23nOaG0yWtNGa3O585nOlzppW+eczsHO Gzs/2/lo59c6X+58o/M/Oyc7nds7cWevn1f5S/lreRvF9/LL+J38Hfyj/BP89/mf8XYnH+W387Rf 4umQO6MYsGLz5nzvANXxIKrm81TIbDYKQkgJrQttCz0aei50LMT9OvSn0OkQHQqZHrEQohSOcgqt Smu+tdJqa53fPE9IK2kq/Q5CeXvFvst+zG5LgqCQXbRT9jH8kimafbv7KLNvfR/V9xQk8uQpsdk0 1FSZieKogbrFbqq7gzH1dGEb8y5DtTMmM8SsZ2xMeE7PSnC7WbfWczFjcHJ4atj4VlWsDkPxP0Kg 5dQEQH+FdBLhc4CVKSAAcXpqQpwEV6wOj0hkONOgE1/jxbKnXAbvwiN1jzvkCsVDFKqusUCmo2d2 THeItE1IxzNq2pkpZTwJbwK5kvYE1vTZdHcCiTF3Ajs0GHpsvQlkPWS28rIG9uzZg0eGqwh+8LCB SIMo3ahI0sV6I8JKmM/WKfVOTZ3kO7pllhzOetn6rM4OavEztw9dMYaLstnU3xKJZRb3VlaOvP6J W/fLHoffHYkmOq6cP7TWsaM3q4ZzHXc+ePmKK5+5++IrupvjUiigGE2zFizrHLh54fDclgdr95uq mA4tmbf0flxa9LGu7jY9SnBo+cwEvQ78XkfvmVf9hcUpO15jfyLxXeq7+lv4HfwbinPwuJVq8V+g bLZfplxnv84xknjQ96zvWSi8j/oPJ47q302cSHsRDvgQ7YmNo5MQTeP4JIbCxg+8oPoAu0LverH3 v0MZJ6cO2JwCFEEG6RiPdoQrVuc4avcWBIwP4INwRuS59J/Bq4SYEqNiHVxjHpGHm4zCOCTpVs7m 8hS4cKrnbitbN6qkcVddTlIC0PvgxIhVJE4Oi2WrqqkOl4at2qfR8AALjQynLY1TpGfWeaZ6PNM0 C9Qz5y7aVOZ+d9tLJzff8NbnnlnQ0ztoZ2VZadcK5y/uXjpr9XuhT+3AkVePfe65e9eW5i+/pBIO dw4+est7vUYbQZUVMxO2BYDyCWD7nab+kPsp94vuI0GbJHXzKCEmKFnJ2fnQY0riu7rAQXhxY/h/ DuHHWAU2LjzCG7e4AOfJC39mWN6hZvwcLIXqpXsLCokhKtRiKdADGhLwCkwdhCIykiddn6VFIkZ7 5xSINP2gr6H8eJ7anj+Qp/IKZFumSD4IkFNF3A6V55A4LtrEcFvPntDZsCM6HQFPPlXfm6z33Can CIlPilbnrWrQHpFkurhqhVKT1uL2pdJ6mmKlTL3S8aQ1XyaLWtwwpL1qFmcFI9tIwYwWkoVBmZXf 7t7u265tbzmYP55nt3t2SdfJu/TtzTfkbpPvzD3kfjC4v/WJ4DOtR1s9u4U7vBSxYnWNxfV5uNOw WrHuOJS05POyUsFWi7ZaT5mBEIvE4NmzoeeFIhUYxFdvkzZM3k3/kOVzPbVrF21bOLrl/C0vbJm3 pdfuap+7d8mV6VA6X8jJTauXM8s+eP0qv5q0qYP3reo7cNPLD/55Z6EfR64MxmMt07fd7Ve+8KWv P53x3Vn3AroKMRZASVw0V7PSUn/Vv82/JXBpaIefSzuepF6lXvO+Sb1Jv+V+K/A+/Te3Y1cAa6QF s4reTG/Trqd3aTfTt3necf8xYG/hZ4KYt9sN4gZJnuarTDKI8MLgGG46FM34OGYMJ0ZdTnvQetsG rBs0w1oheDkiEUSMDWFv9Sc9BSLNkLeIInmtoq3T/qzZtGRzPaHrEBuRZ8mEVJeZ9oLlNS5wp3ER i2G1EYFWLQpp+QSJQcMgzmIY9VbN1DTJ+qaqE1h8bbiemnsT8XQ9NY9JSgJF/MEETnijCSwHYGik 5sYeqHCJkYexWo/GOkYSA0pgP65wJlgDdHV6xr52wYbyxh5t2diO8StXTT9995v/o6cDekHtxX85 uvW8eRcE9+85sOfYOzjw9mNf+qQida7Zr4MqFkJN0wMx2op//SJiZ9593lmyCr/80mKBWUhRQ6Tu 4xiGDbIZ1ia4ya9oK25RE1tZ6TnPMQ8VxciXUjxj1C9Mr5ZNKZqu2VOKW9djKUUdo35ubtKbUkqr ruMo+e3u0GYbp6mqx+N28Iod21v8PlPtr/jMBYsKPnNO0WfOg5/SbNhpnwVDtgkGIweDloIhocAg egsnfFjw4aTvhI8SfdhHyFY63oaVtoNtVL5tO5SqZl+R3MgoLGVJWM2SsKAlYSVLtrZZ0vSAv7Wh Ouy2NGWtQ3Bh72ZxPns8O56lyaHR7tkFS+Zn1SVclDXVHlcL2XBueR06iDMAYFh1mtjgR2BjoO7h kXNeiqo3FOuNKgAUgGrrMA1ZIYCJFdkq6fg6K6r1HX5XxQNIVt/zBd2wJ3tgCAswRMWKh8S96q+c WX8NQSRcHQEIgOQfexutbdIWIU2rM8WzxnLeM42s+rFsEb8yuHvB6hubm+bUMh1hSTKiTctaBV9v LdMb9mb7mGXTv/3YvEv2Hqh9/soil0pxauRS/KVretXuBTXnJWGNT6XYZPBK+vAVBT4NGNACdKAz W5ETxdAvzGBit1euCF4koZjiFSUxxsopRSLgr7lTipds6KGUEnvJ+qUAlvQhCl2F51jMmlBXx1jJ 67ATHcTgaD3bMulml0twK27K3RKSTVje6v3PLlqPApJ6/RGWT7akmc+1Fw7KeB+k27IoU/INZmIo QSmJ9YkDiYMJWz5RSeyDjeOJkwk2vvw4lHNguFPV6vBZs0G6Va1XAJVJK/YtVX+0JftRPYNOM/1r LzTNtWtfb5tX4/oS/ra5zFbrgGleWOudjm7qtqVSlCZvojTYTEN0GqC3FESniOBmJaK19RI+KGEB KmQkKlAjiyLrTCmspTucUhhLd66UIsKGGdThTJZxNIrUFpeTaMZZ1wwRo7lCwdnQEJGmDio66MT7 nBg5RSflvEGRDkgHJTovVaR90nHppMRIZP6sQoHIw7m2gtdSEHHwj2jIUs4ZxZBS5p/UMfqhGpZ9 cN3Zm6e/v5HcPNz9MijFrwXmWEgtN5VFFJYkxXQkunnBh8pooeKDwFnI4q7ucEqBdOynh7RcSmmC DdOv9aeUsq4JKcWn62YWayklO0a9dUQ3e3F3SumFbbNFn5tSFuo6p+W6VA7bEuWOzbbEZofDxqGF bLm3Kev3OQZMoIABopmVCa2ABg4MHBw4PmAbgIrRIwiKQAktkTDAVphg1KPhY+ETYdoM7wtT4bdV raUtBx/lrI9yx3IncrSZ25ejcm8joVuB1L9lbj9ZORLXCuv7T/ZTB/oP9h/vp/MwjPfT/eFFA2PU eaMqARVSfQ6P1BHFyvHK02dktWzVo7B9tuNWKQ9CdjLZaHmXiBGMeru0gS0WDaXys6Jxp5th2zOx zCymLYFZLu6MJLDLnWc7EjjqStTJCHJ8K80nKT5afP4OU1KSvD3JJ7KMYlezKKnyHCYoBihjpTKp 9QMnByjWlXIVXObAT5zMCmYFv9y+wnl8gOmhVrArXP9gbaRVMTxST2AGyPO7uKXoUTFQYcdm/jYK QGdJgD/X2My7Z6XXXT8O0toXnPV9ofG52DgPJNn/urOEPoRcXM+IAvUM6P8GxD7qzENUcux/OfBr gzcvX7tTHfr80Iarc9m+WrwUlfxG3Fid88r9tVg2J/jz0SY1X4TPEhZu0k/ecP6881etHVpzxwO1 PVsLgJNMNroB33vjfLVSqTkujaRJFOizPo7v3WWmAsrSmmNThbXQdCslWmha5+xuiAuDshHO/uML zpKdxTniSz1Li0M5zABfp1n6Z9RP6P+I0AG2CExO/wT/OkpJggepyFA8oioazwnHBB5HY/6UItT5 OwOcrWsO4HOLv5OEvwM6sLqh62oyKQgeR3gzQ9u4KCTlo+OYvPnygrkqVMQ7IJ1lHRajBwJ+Qul+ 8H3Bj5P+E37KT+jdD9TuJ9TuN4tdMAAj+0ls+AnJ+wm/+wm/+wm/i37sJ6QuKLmDOSqf2w5hA4ye azC6JWGRXIPZcw0mzzUYPtdgeEsnAjB7LiYghRBRNps5S+0ZnM8cz4xn6EyD2jMNas/UKT1VyIRb P6R0i9HFcyjdINX4h75lhWPjsTycMAyUXp6s0/s/8XqyzuvJM7wuEF5PnuF1gfC6QHhdILwu/G9e n9WORkheCKUJaZgHzimlP+rI/+yzrwzcsuzCT/pFcMlsURYlI7JqSbZYyzbcc8fyRZcuLT1Wu2+r Revp8CZ84OqyekPNeXkP9xE3bLzRcgT80I1UfL4Z+l4EZ11YuoD3ZNwYcXKGs/POuGk7U6HZzIxR EGzYFtHrFZolFtVFxRKjpTkFIs0U1LrH9XGdQrqpr9fJJmPqj+qULkiKREnmuBM7Gxm6JWFpIg9D Yu4Mk+cjuw9liz3DBDnrxqvXco38i7zrQt7csQxUrr/BMh+rIhTeSiKZoFi/L+CjWDYTjUVi4RjN Cm4pS7qVCRy0SwkU4uJZ7HV5sjhBexLY55ATKMbI2XPeUTFaWgAxAQxnNeESXowXiztczHZ2l2uX uD28m93n2ifuDn+felVx7OKg8hN2hfZxu927hX0hnjRph9dgSP0bbVmrTJdkjbVaI/WXWbqIPTO4 tvOHV12686c/mnj7ROdi2eMcaMslsm5/Jh2hX/n0H+/83m2P4aZXXsPGosHf/tuV1UVLwtqcdVh9 elc8QBh2KUL0J8CCzThrOpwZZ8npd4l1hUI4gvzDaFQpGA3GB7n7eaVo7cYT9cOCaEkz6w8WRAM/ 4LzHoJxht7cgxKFYb1biYkJsZnEgKMtIg0rfSlTkV5W4lajoKaWZJCpx3dEhmIky+HusuyJcRiAG NbOJuEOoIsdRvA7Z8Loj93Dj3EmO5sbwUdOJmgVZgdytRdfq3qRZWFAoWDKatKTpl4KF4xrermGk iRql/bxl+UqrO1/PVIA9p6aqk5PiRD2XK5MnmOQ5CmeV9IQoIXFuZDXWb1E0gu1Mu6TxoCog10ts 8ii4aNXVhB6qn+nvmdffVlzOOdzxSHMgiTlXvqfGzTF4R6adfvLHn1u3oDJvyXwbG9QqG679aU9J jIZpoITSTooZCsYiDEH7j81MUD8GG3VQT5sXOdsDYsUmupv9YrzZxvqD/lfTr2Z+Jr4j/l3kmsV0 S4/Y1bLXeb9+f+qrzi/rY85DupNxMW6+OeBa5FzqYk2n6aKkDgXtpxSMCepg0ylVHiVQjheYPrRf ysOBQv59I6SE90eVSISEFUy5J4IjY/hKMxHeH3xfkpiMwUmJjOSU6smlKQUK+EIJapOTh+x+diXZ MB12P7Wy/kqAVY47hUJ9TyO1ijkbolfxYE9EKOB8YUVhXWFbYVfhuQJbkPgkWYSM1EqBV3iKN+Hk +pYWaW46U8034aYz/bCmcCcJeBLvUH9PQF4OdgO0fYFPAoiSl2dMGU7hTb9a4csBHYZgGnbh3hq4 SgDi1Ahp9Jw5VU3W662Tph3WUC+G88mdjMISloRVLAkLEfn82bWMNRPGMHl3KYzNphAoOeaFQYzC 4JFhcAfrE8krdOSLEomEUEmMzfxm1OWvS5hB5PMw3ZpozXsRMUC4EsxlEjCRScAsxn9mivgnUpZg cXJqEol/sl6dEvKmw1vJm3YBBrgXMo1Mqs8i35zOwaVBqI+P1iXcKhBPOgcUBHs/Mu2wkc4BK6XH Zt4blRUiJ46EkhVXLKxWPsyt1qBh8uCCPICCmPHpViJF8MpGosVqXEC06HTnmXeD6m/sWW8LkeYG dZ+gzbm5v3m2P4kz1eV3r5q3PeFUg6qo5b64sH1OecvDubn3f3bZoqhXCobob9W+dfeW7lQ03Py9 u1Ytf2CoxdmBh265pbelfeGiK3o+vmnrc2lB0AnGZWbepx6wTaMwesj07HPuc1HW4HSh8Bg+DPax +f104GYKs0kn+ZcQaOeI/VKPk6LHsMeMM/+Pva+BiurI8617+4OGbj4URMGvVglBJIhIiCJxCCEM Y5AYRIMMIXw02Hx1t923Gy7dTaC7A+hkjOs4rMtxfJ5s1iGerMewxufjua7jqC+TqONxHGPUcV1H fcY1jmGMYxxDv1/VvQ0dNWN239s9752HdX5V/6pbH/+vqlt1ufbV7tHFT+aUShKpmq7iVcnRsRPE mJjoHGg/mrpUFHbvc6MPRJ+IVkTHxdPVRXochK3CbbYbwO2/KOrO0s+RJd/7+vKr9I1k9kQom2OP Y9eQNRx7ZSjwHJwtLE+Pm8VeK9l74UJkYtRzWdNe3rPKOS6srf39XOXXwztqvv6nl+dOrYk9UPPs zF7uq1mrDolU1u/5LyvnKX5OZnIb/xtJAHfbsR9MOJHAh+om65J1P9ApF+r6prw7Ze8U5R9Cbmr4 mTna8IwZNMKJMhrnyWjlP4dw/hCOHiVnzZLOT9PoQ51ZKpwj42pDtWFaMnMmFKAm6mT5WDlNTbd3 auz31NjiqekWT013d2q6sVPTjZ2a7vPUdHenZk9v1FykmtOrf63miTpKzavpVi8sge4aE7DLS5B3 eQny7i5B3t3RdCBZuoyeE+RNHk1z4rDJO5DATU/YlcDPTbAk8Akx0ydwE5Ij6ULzD+g4Qt7jRch7 vAipM7YORWOrdyuCmxtxIOJEhCIiblbRyCNgdpdgz3GCn9088CQHt5HPR57k0D0F2/G9ukZ6KMAe 4mGrFjgBsz90JEr7sRmy1TOfYVnF0aRnh73Pdy1/yZn85GLOHT17csLUpAV0Z/Z1An3S4l72gyrP 25yNbsG+7jRkTYuOf4m7LZ8Lxg3nKz6H9edyNR+wZyE6Opt3Rk9YTP8YsYQsCS+IXxVfNrk0tSG+ YbIxde3kvZM/nByRFJ0Us4AsiM8n+eGr1atDVus2z+0n/fGfxIXDp8LnhuvmRqh1IdPVE+Jip0+I ov9bRzkdi0709JjkCU8mJcyJmDs3Pz4uJj4+ThcePgkrUngFfQEvPIJw3Iy58XER4ToSMuHJuSSB kjidxCdcn7NhWmTC9WkTYrA0qNTxRFs57+K8W/MU86g9wmOSMubhiB05Ye4EfsJeTpEzUTV7tv7J jCfznlQ8+asZc4jqBOZiXNo8XPuHGb9YIR2Q2UujmHLS32et7JZOTYLD8Pc+Z6dh6c/tE+l7e5rU OeyvtewNMEoQ+W/xf+ENME1Utiabvawyh7yqkv8oyzZl0dFsRWPZEI4PeuN8ovwO0jPc0PDJvOdS uS/mJaVva140bzG3MDUrb/jL2nkvGJev/n5G+rMcp9FETpqclJnIf/CzgognnuBnTkq0DG/kJv/1 oidS+CeeUD37/tcvDt/PLnnt+azCnOcTtdqpyb103rPna7B8FPmbnJh//s7Ph6bMIlHq4OdD9Adh eOn5j/RYaKb0WEgbHZshPxAaz/5qgt3e9PGVo0+GFOPkx2Rz7rzKnnU+/Ajo4QdAAyMPgODeDz/9 8g9yT3C9PP3/ZpP+kSgUJ7FZbQROv6/i5kbdlt67p/+fo3c4gTuPulFSG+XVx7dRXr13SpUy2oYj 39bmy9FxyPAglz/aRvMd2mjInwY1QW2ivrXN1yNtosgfBqOkNoRkyuFvyfDDgfsewmpuNV/M/3fF a8oQpSUo7AoOqi4a1EUPhpACFj4L+UzzuRRCP3hU0M5DuKj7ffgADRFXIjtpiCLj3hx/Ivp9GmK8 sbNi/2biZilM+un/byGOjIWxMBbGwr8pxP+HhIyxMBb+LwxFccY4z1gYC2NhLIyFsTAWxsJYGAtj YSyMhbEwFsbCWPh/NUi/sE0u0i82kANERegXkBL8byFe6D9HYkgM6ASiYPHC4buIy/1GMp+VzCeR /jzE41icgPKn0Wov4nLEC1HnHOJItFpIxrF4KmouJAmMzmN0AYsL/bsRFzN6BfpZSEoZXY54Betn BRtrBRtrBclnJQUsfhH8r0BbSr/CaPqlxHLUfwvxOMSELFdcJ4EPHjawWMEkn8ZylOaJhhtPAl+t bGK/o0hpJUkiQzKtIpPoL9wxWk1SuEKZDiGOkX40JI3slOlQ0sW1ynQ438cNj3yv8GnlZpmm31k6 JtM8UapmyLSCZKo0Mq0kMapxMq0iOlWiTKtJrGqxTIeQRSP9aMgk5R9kOpQ8ryqR6XBuqeqv6Vc4 lQqMFRGilGklSVVfZrQK5WEh6TKtJMkh4xmtRrk6pFymlSQxJJvRIVRvIR6Zhq5CqhmtQbkuZIdM K0lKyDpGh8r6l2hJ/xIt6V+iJf1LtKR/iZb0L9GS/iVa0r9ES/qXaEn/Ei3pn9JhTPbTMg3ZQ/Yw Wks/FKNRyrSSpIdIOtFR3jSZMg1+NLGMjqC/x6MxyrSSpGkKGB3F+smUafQj14+mOtRslmnoUCPx FkP50eyXafCj2croCSiP0dyQaSXJ0BxldCytH6qXadQPlfQZR+uHFsk06oemMnoytWmoR6Zh01DJ RlOZTT0yTW0qlU9n9d+TaVr/TUYnUJuGnpZp2DRU0lsy1U8YL9PQT+glRtPfwAkLS5Zp9BMWRmlN kP41QfrXBMmlCZJLF1RfF1RfF2QXXcAu7xI9SYcHzAP0pIQYSS3SpcRMTIBARGJhJc8jZwVN4yqU 17MaqbjyHHyvCWkxylajvUBsLFeLtJb9Wm4tMaBmCa43s1I9KULawmqZUVaFnvS4Sq9UAQIbw4A6 9JqVNKLMTOr+Xfw9WDPrsXzkgm7C6FlkJePfJvelxypNv8X6DKgk9FtPanDVjOuUN4HMDupZ6ne0 12VkOXlqpOelqPmwBCUjVB6ToQW9maBRPXkJ/dex8ejVp4DlaEf7bUKJKOvDyjRIe01ByUpWX2Dl elLI9Eg1akKZHtZeiPtPOlnFvjirZ1zSfuzMZtQCRtkedaxHgVmG5i1MJ/RXZgUEalk9qWZtBdk2 L+B+UgivkNpag65YmL4MGKWG9VjPtNrCxqJftH30uFKe1q2BvHYmhYHVNSM2sOsWXJEkoFoxyGPV yz3UyH1J0lOf1T8kuZlpU2S2rYct9cz7qkfGehRfpof6/u5aGu3dMGJnK/MdgXFeM+LDj5ZeGv1h vhYF6YBKIskisPECs4P2L8lqQEkLk9zMZtyjJZU0XfUNrdYyy5rlWJJKou3IWVisZ9w6RjxX6ofW bEKNv2ijd/XpafPS9CXGWv1Ss8ksiJZa/fNmq8VsrRLqzaZU/XNNTfri+tVGwaYvrrXVWh21htSS +uZam76otkVfbG6uMunrbfoqvWCtMtQ2V1kb9ea6b+8vUJj1YB+55iZD1spaqw219E+npj2jT1pa X2M128x1wmxWGXVZ1WXLn6KVl5aMDFBCozxrVUu9abX+pbq6+ppa/VP65UKVqalWBB/WepvZlKJf WV8jmK36wiqrodYk6OctnJ++ymzXN1eJerutVi8YIUedGVeqbHpLrbW5XhBqDfpqEVdq9S+sKHwO V60sY7GaDfYaQV9v0rcY62uMQW2R1ptqmuwGNBXMekO9zdKEAapMBrSqR4Ua1MLwqXp9YHCzqUnU J9XP1tc2V9NWo32ZArUfyRKrbqAyW2ttghXSQXdBw6P5SF+LGAdJ9RhFqG2m5rDWY1SDucXUZK4K HhRMV0ms1lr1kNeMoRDbBYtd0BtqHVS5qGOsbbI8INFjV3xatprNPrqqPq62QOxcOKjPHluzjs3V x9XKZ+MKj6un6FH8o+KQ4p8Qv/+dJar/ThIV4roRtANltIX9sS2+z9YRG7tbCGxeP17KzzDrG8kd jPIZWj+u/krW8+NqFSBtQo9136n2MtBUK3asvNLa+njdBGvysVIqpysXKxcpn1dmKhcoc5TPKl9U LnzsCCXf2Z9epNJy80A/vib1Zgv0/VieuXHkkmIWco/3EjO7V1WNnAuJfwb5JXn0PwX9YhUJJ5zf T/ebhCzlr+Zjy/tzQnJVKpwDl+qlpTbXoGf//PhHvucfLllalJuWpiBdRD5p65Ac5U7R/4uHA9+b hON/HPgYn/xVQQW/hd8C+mc8zgH8f+Fvgf6Cvwv6KwVOgYrxCpyTFNGKfNDfV7wIupB+F1XxuuJ1 wis6FLdBf6m4D/prpQ17b0EpEIXSrhRBtynbQDuVfwV6o/InoDcpN4H+qfKnoHtVKYRTPaXC+U81 XzUfdIZqEehsdR7h1C+oMZa6UL0UdJH6FdCl6lLQq9Q/BF2uFkDb1XbQDnUL6Fb1G4RXd6m7Qfeo 14JeF/IO4UL+LuTviCJke8gHoPdoniO8JlezhSg0P9PcxM7/D5rboL8MRc+hq0JbiCK0VYuTojZM G04U2ghtEujZ2vmgM7Q/B92v3QX6fe0vQB/UHgJ9WPsx6KPaY4TXHtdeA/2ZFqco7efaIdB/1H4J +o72Dug/af8E+q72K9D3tLCsjugO4jTxS90R0P9D9wXoId0fCa+7HR5JuPCo8ElEER4XvpJ+p0y2 J09mMA1LupW0KusTchVDohINdKUp1UAiTZmmAnSVpgZxncaC2KEREbdpXLj6uqYTsUeDM5nGq/GC 9mm6QHdr1oJep/kR6A3QFdXSkKwTHtqYAzpFOxeypGnTmLzXQf+r9l+ZLIcQH9YdhkRHIBeVYgLi 2HCcSsMnhk8EPYnKJcsTRnq5fURVZa2qJvoa0dpEFq+21jaSImNttZVUNFUJJpy1wwi3ojhPT2Iw a/z0uQXRypSK6JhuCJsp9BlFeFCew1k9YiRPv5iCngpLCvQkVq7B49QeKdMKXI0i4xprrSZiZLGJ xQKL2+g2iHSwuIfFG1jcy+IdLD7O4kvNjc1Yq1k8TGNOzeIIFseyeBqTX/nImB+xtZRy9APG4J2+ sh8CfsMgvQ5y0Z+Dpj+REQ29TIBEEwn9ylE8mUymEPp/K6dj3Xl0u0eV0Y+kKL6RRtLf//2WlJ7X yrGiNWFldxEfeZNsIlvIO+Q9spvsI4fIUXKKnCeXyQ1ym9znlJyOi+eSuEwujyvkSrhyzsr1clu5 7dxObg+3nzvCHedOQ3aOcNw68IZUK4BDpOGHpDSyn56/CRdVIGlKnyylGe9I6dMOKc08JaXPDEjp C1ukNN8npd83SmnREaKkX/17aRlRQ8ncqzOJGmJzr62T+KjKo6MRrnqSlK/Ok9MKOT0lpYZ9rJ6y 7lTdtbr7q6Ok3Or21RtXb189KOWMScZs4zKjQcrVJ9Zn1RfVV0vtGxKktDFKTq+zWpqmQ01nmm42 K5vjm9Oa85vLWWmkKde00tRgajdtNG03DZqOmy6Z7pjDzNPM6eZ8c5nEsYU+r6NpodSjpURK16RK qdUgpbYzUj17oZyWQMM0xV0iNDvUQ5+/kAv0N02dKUA64ZwHkS4AFoP+kBB3Eeg8pCVIcX9xLgNW AuVyvlqGEfWPIzUBgow2Oe2QgVuW800ZlN6INqeQbpbzXYRzTJFS51mkW2W8A+wAdqH8ItI9cn4f IR6DjAbCeSxIHTTPT2w5I+aLWWJxK2/nGeJFA8Ni0SOjh6FDHGDoEtdT2FPsPEXrLhld4jUxQ7zZ ckEsbLksFrdcR3pLLBaTxAGKljtiact9sYLWA2636luOUKC8EOXB4zcwpIOm/WtkJKI+RQRoihTQ FCN8CpcljPC9niEPtIT1DCZxO4Mgo4vJNND6pgxe3MuwGXUpAvmtoLcG5WU9PJR/5zEwgZfNwD7h aOtBYAfoXcCHoI8DZ4WTDFS2i8A+cT/DVdDpwDD6GB7VvxgmXKawQ5cUYqx4WoJwgWGKeImCtaWI pzpGu5lID9ojxFTYJ5XpgNkP6U2WBuwg2cTSegNthyR+ArYdSWXbBmw50mdAp7A36zMGfcUE2e5B W476gIPh22y/APSCv9jexbAEeqWohs4oloGmMII2Mv8I+MomGYF8H8NK0OWPrL+NoQ3+0yb7k4T3 GNpkBHxMLm+pE7c/Cq0boaON39DXX0agXmBOjvgoZKcY8WHQm4PyD15/nA/vgaxtwCn45Sm0C/gm xQ3hTusQMOKvoC+O5u3UXneBkfpYU4aAYP++G+TfAWxlc2T9g+uMqBTXU7TuAB87gvKB9WdYPERh T2kroRiRZXR9kvJy+9YuVlaIaxEM7Dqti7a7gtoHxpPnGeMZEKOQjwrKP3g9TPwIOGHXiwYKzMFt DPfEBgro+xJF2zQJo9fRFmhLQDkQtH71ULQR8IO1sS1ZmsdsLsvzbQRJ30RbtoxcCSPlBRKC5j5d m2+2EbGBIsgfbwavDWIGZM0QbrUVSenj/KtNJ61xbePFwrZJ4iGsT+cxP/e3JY/queWkmNOmFrdT BMZtS7NHtGXKc5rN65YDDKPz/gDDg/NeXjc6d4guitF8ywGKh+41o9ePMIBXGespAvO+c49wi2Ff 50GKVpMznSEwL2W5Oz9Euw+p70BmNdphXe88Ja31nWeBi8hfBW7gum40PzpXwOMQ8MDcge3WU3Se Ba/Ao/N0vkhzoHNIPC1BuEAhxnbelWDPY5gi3KII6KVzWLxE4VG2HGEIAx02mn/wXuOJEgcoHrx3 BuTHrknLzs+EnZw17MwcipNtBolQLcD5NpKdbKNxpl1O4tUrcbLVszPtTHa2fIKdDFPp3/T4P+As ThTTFTNxtn5SkYb96XxFJolSdOLMHaNKwum5R5Wt+g35seq3qt9yT6g+US/iEtWL1c9zP8L5eDX3 V+p6dT33M3Wjuonbqraqbdw2bag2lHsb59fd3N9q92j/K/dzHaczce9i332Lzxzd8a3JAnKwZzyB NB/AHnHNaUJs2NmtKUaKXd2aUqACwA5rTYOct8hwoP55pC7AI6NHTtfL2AT0yaD0NrS5hHS7nN9E uKZkKV1zDel7MgaAvcB+lN9EekjOf0RIq1VGK+Fa25H6WH4CSSFZJI8UkVJSzZ55dZB1OLFsJf1k AOeVI+QEOYuzyjCnIYo1i9ekr8lbs2DNkmacOSzXLDcbbpurQV23XG64ZbaAumg5a7lqLgJ12nLC ct5cDuqo5Yh5ewNtcdCyz7zFcgrUXsuAeaM5EdROS7+5x5wBapdlq7ndPB7Udssms2DWg9piWWdu MA2D2mjpMFeadaB6LA7zStN1UO2WJnOh6S4oI67mmm6CqsDVBabLRGnZbXnbssHSb+nFGFua7qGk 31IJug5Xmpr7Gyahdpol2Rxm2goq0aJvmdJ09P+Yl6rYcyDCngBx6nb1GySUPQsZx55kRMOvJnEe nCp0ZD9sQEywrwm2hAzEdBs2w1nMdA9pGCFmHMvMOOlCegL9SPlJMnBeNicAyTLS5DRTRjaQK4PS BUCRTAdQIqMMqATqgCaZhs844mXg1OxIYXRKY3ZjbmNBY66lorHIYmgsQShjqMSVysa6xiYEK9JW xO0ADU2NPtDrGEXDBlYPsA/Va+x37cP19OneOOh/CMfp2/yXhOf/BFsomS3UzBYhzBY62GIhCVct GrFIFCzyMpmoXg67TGZ2maIuU5eRabDLe2S6dieskwDr3CdPaodho+T/xJE4kkMEZutUnERJM05y zRsBnOCacVJbfRUpTmvNOJ0JWUTTkNWQs9qCOL8hf/WAwM73/B/5P4LTO/wdwqmyVFmEVxeri4kC vreKKNU/hAeqtH+v/Xui1n6t/ZqE/LvacBGD7BmAgZzklFwYl8blcpWclevhTvJR/BK+h1/Pvgq7 m9/PH+JPIlxThCn0ilSEDEWFwqjYqTivuKPMUIQplygNygblLVWFyqjaqNqiGlIvUNepWxWp6rdZ /VT1CfVVhBshmSGtIQOaBM1iTYHGodmsOam5FsqHZoRuDD0alht2Xstr9dpEbYo2U2vR9mk/1F7Q 6XS5OoPOpOvRbdcd1d0L14RnhpeEt4XvCh+K0ERkReRELIkwRqyP2AKN03eonqHvPwFZQLZ/N/eF /y3uK+DP/rd4Dgj1n+PD/Lv5SP9uWIm+aRXK3qt6hr4BNXwX7aaiXR5ZhXwZQN+82uOnz0sUaEHf h6JvQ9H3rkLkdnkYLw/t8li7cpTt8eex+m99o74Kdfeyd7WygGyAvrE1nr1pFYnrUayukUwFpgG0 TTqu0Xe28gH61lYh8vSNLfq+1kqk9I2tAJeRUk+QIQo5+u4XffNrGh0ddLr/E9aT1MvukV5KGc95 JELmIw+tdzOep4L/afQdNGgkD2kBII3/FlqeQ8tzaLmbjbtbbpknt5THBfLQugCQxpxKlqOsBGkp 0/FU2GAPWcNs8M3R6dtmBWy0c6h/jtCv7fLs/TL6dhlHPmBf+1YwPexmFlLxT/nn85lAIfDy8Ot8 iX8+5qDEnQbtNNxd8iPuq+EheIOO54aH+Hj/IFHBPxpQMgj/aIBvfAzf+JgoUFqE3BXkrhCOT/D/ TxJGbcql+NdyT6Gmyr8W3rSQDxu+x0cCsf7XedgNNXdhhQn0M45L9U/n5gLzgPnAXdIMHm5ixPHg 4SYf5Z/Oj/f389HwyklI44HJwFT0rce12f7pRMu8CVJ+p9HVMp8fo9avUWsNuHkG3DxDIlHaj/bl 4OpTcPUpuPoUXH2Kmv3g5FN+IhAHTAf0QCIwG5jj/xSawugPjiyNBg3nQ8P5kOw3kGwuJPsN7nvp /q1kRpCH5wd7OHo7B17OgZd88FLOpSGdB8wH7pIWWGAh+mqGXRZi1HN8OIA+eIwDeY3QVi+0dQ6a 6mWy61E+y/8T6MDIP4GyJGA2ypL9vWQy41DiIB8c5IODfHCwBxz0P9ZGKv8ejP7xN2wVCytI9tr9 kL14pjeqszD0vRZ9r0Xfa9H3WvSxlmlYjzQRmA3M8a9lPiN524T/Lb6+zYeoJw6it0H0NgjL2NHj IFoOouVhSLMWLQ+Ds0G0/jVa/xo6XYvWg+ByED0MgstBokUvh9HLYfRyGD0cRg+01e9R8zA/E0gE ZgNz/IeJko/BlVlAEpDs/z3TRz/a96N9P9pTr+sHB79hnjcJqR752f7+bxlpuv+XjxxJhZXvCla9 K+Rd/+tkh/8YGfDTdzP3+Puwxu7xF/LP+Y/xBf4+/gdIX0RaiLKlQBFmzsvDv+JfQXkZLPBD/2b+ NdBGpI1Im1C3GTD5B0gUn4Uai/0DfA6uvMB6HEJvQ+jtCnrbi97+hX8J5S+jRQnqrfLv4yuQr8X1 ZnAUgR5eD+phQG5ZFtTqJ2jVx1o145oZWIOWU+DBcfDeuGAJ0dsM9AbpyHz+heGP+XzULmASXkEv dZCokC/HKBWgX/Mb+GrQtf44vg7pasCI6w3gqBm0HakDaMXoor+OqFmvS0kcpLrCvwL6NdBVZD58 9TlQL8BXtbJe6YjHIMvvIMvvIcMNjHwMuuzDqJsxSh1GMGCfstjvheRX0HY7alKJqY4GAjqCfgJ9 LfV/gnGNqEHHjmO2eQ01q5Aa0a9kG6qjY3wLWqoYlz9ktYZQg12BDEWshLa5wvS5Bn20kDiig+76 wE+fbIk+/kWMstT/Y74I6Uv+Sox8TLbEFb4SLSbCAgQWIAT3MzIN2AGdZGEdXOx/Ar3slbQyfAxW +BRy3GY9FrJej4GP36HXgG0HZJ7AO/oQcaeIGOHnBSb9FdT+mPFQQuVCL1T7jUCT5EuQ5AqTZCr4 om+Ez4dn9MEzPpZ7ep1JJXnEFYz/G6ZpapdyZpcBeMMx3sA03wePoD7/Dl+P8gagEaB+bwZszDv6 grxjgCRixg1gxg1gNR3AajqA0aER+Cbzy2ERHMyDd8DWuNPSmUet+Qrzy0LYaQBclPKvAhX+ReBm Fl+J3quQrwZqcN2AVPLVUvhqKbibBe5KwV0puJsFzkp5C2AFbEArIPoXkVB5jhVC/jq+gNqAadQA bb7O9A95SYjsuZvhbQPgbQ3jzej/BZ0LuOMXsPt+M6Hv+O5h7d7ALolSWVihFmP1zwH9HNq+4N8J Le8MmgV1sF0zRpssy/sTEoYWJczTpJnzOuOrCOUvgYNV6C0wA7TofwC161B7DbNgQIKXcC97WZ4r 8EdWW8XXkvHQyhV4xcfgfDO8Yif6oHWoh1WyXo9Bh5/IM2AAehtgs0BAuYg5Es5mDesVqyldqerg q0bMIsnb6EwaxPp3O6jVFeys5PUILfvYWLUYvU72atovj7Uijvo3ZiGdQ7Q36rcmpGbwQ1e1EHnG XmF1actG3NFxBeNcgSUrkKsE6NU6rCxGcNHs/y24GUKtT1Drd9gdvQvZy7Dy/pBJfUxeI66wNaIZ rUxstuxi64QCNYfYVTp3tPDCYxjlsKwpKvun8gyjmqLtPqY1IdGn4LZC5lTS6b/INaUVOpQvw5XA TMU6ya6YRtbwT9iI4dBbHfRWx2rLa8tIn5SvBnmeNzMe5zNtR43M8anITQPo2lMmr3gV8KfX4LmV zArHRqzQiDKTbA2V7GHH5LXjV6xfndzHQJDe6Nw/LNt9gN73ULsPmh5g+uMor7BtEys3MJ30YuQf o+9zGPkm8xQztC3KFvxRkBeif3kFC9SCT2EnH5BuB/oOQe5p5J6GrMcg6zF5ZRlg93SepLP3FAj9 nzK4wycQ+pb8bAQFmYughL/Nx37gaQQ1eQYhhCwkOGuTbIQw8gMELVmBoCOrSBnsUU7/5wr5AGeM KPJLcoiM5+ZwT5EYbi43l0zk5nPzySTuC+4LEsd9yd0h8dxX3FdkCvdn7s9kKk94jkzjVbyK6PkQ PpzM4CP5SJLET+Qnktn8ZH4KSean83qSwifwCSSVT+QTyVx+Nj+bpPFz+DlkHp/Kp5J0PoN/mt5L sDo8zefx+eRZvgDzPgcn8WXkOX45X0IK+JV8KVnCl0H/S3kDbyAr+Dq+jqzkjdDpK3wDbyGlvINv Ja/xXXwXqcYZvofUEG78zehi6EbH7SdNhAgNgAVwAC7CN55H6iGk/DYhjfsJabgrgeaFHmA9sAn5 Q3JZH7BNygvbR8C5ugj/SomExkvANZS/h/TmaHkwgssbb8vpvUfXX3lCKvee/8Z1xgfDezJvlJcB wjepCVn50WhdpEwmYS+rx8Zh7SGvQOX4CDgBnJbz52X6EkDlQHvhtlQnoBv0z9AgoPweK+ebdJIs DGhjJ6Pj29VSXYCNTfto2PpIsOu0v1dK+N/ZytrOetJslW0XPZm2urarnmxbU9sNT67N2jbkKbC1 gi5C+V2U17UNe0ps7U6lp8xW6QzzVNp8KKmzrXNGeZpsG5yxHqutzjkFdXqdMz2ttlZnEtqCrjWi fqqn3bbFmeHx2d52ZnnW2XzOHNTpx4gbbDud+TXFtn5nIeh+lLfbdjuLPb22QWepZ4vtgLPC87bt iNPg6bcddTZ4doK2gD7pdHh22844XZ5B2wWnx3PAdrm00nPEdt3Z4zmKVus9J22XnZtQcsvZ5zlj u+PchjpnnNvR533ne54LAu8c8FwWNM69nutChHO/59aKXOchzx2Uf+S5jzonvLwQ4zzt1axIc573 RqD8EurHO695YwS986YnTUikMdVb7S4hxXnbU4CSeyhPdxFPq7DApUbc4UrzbPlG3OXKHIk7aEyl 8yYKb7qyPf3fiDe6sr0pwmZXrueIsNVV4E2X6XdYvMNV5Dkg7HKVoJ/geE9QvM9V5rkvHGSxRH/o qvQuEI676ryLhcUunTfe1su4PeVq8ubZztBWjly34IsV8lzjAzLKEt1wrfNWCzGoaRTOuqzeJcKQ S+01CUtYHUkDEr2M0Sudt716odw1yVMmx9UyPQ2x0ZWAPoNjkysZsRAU33VtgAUlH2PWFIZdvR6f Xena4rllD3O97cm0R7n6vYLkt8JFV6t3mdCGtu2Q1wp7XXW1e1dCXp+33B7r2ults09x7fYM2me6 Br0d1Ce9XdT6K5ow+gHvm/Yk2CIlQLuOeFMkr5PlYhaks8aYSP3Tu9Ge6jqK+XIUo+8cnTvezdRL vVvB4UlwmETtaM+gUtizXGeoRK4LVCLX5VHpXNc9R+w58J8Sez6z7BLqSzJtZPpn9rUXum552u3F rjue6/ZSRldQWtaMgWqGzjLvO9SfvTvsDa77nnV2i5v33LE7mFb3uSrhCSbmn4y2u6DJXrsHmoyx 94BeZ1/P6E1ujXeXvc8d4d1j3+aO8e6zb2d66KJ6sL8HLRnhq0c8/fYB1wFPtn0vo/e7470H7Xvd evhwijseniD58zK6qqAOaMkWkIja4hBoIzyW0h+13fV+aD/hTgSd406BNk670z0H7OfdC8o19kvu xeV6+zXqRfabrlzvcfttRt+jtORXDoKZcoquVN6zDnVppfeiPcyd56l06NxLsDJg1ao9TteH2pWO 8e5l5Xqq/7oe6l0rKukKVruLrhXeq2w1y2b0Dcckpn9pTkm26KA0XdnqPHQN8Q4Fe6Zjmnul964j wV3uHRYSqZ4dyUzP20dpYcmo/ul66FPSlcfb5UhzV/vCHJluo2eD5MmwNeaaI9tt8kW1Nrir37jV aqFXWx3u6priVpfb6NW0elB+p7WHla93Jb9x3+7pyOvibb3uNqy0Z9wd4NbXXogR+fZijAgf7tLA S0u9W8HJ+IBvt25qG+qKkLxXSIH3FqA8G1Ivo3aUbcr0DI8tgPcyPdO1941Mutr7lHSN7Yqx52BG Z0seS6Xriscq+lGXHt474oF0te9KlNZVyjOVtCMPdB800966jc1fxptY5krrGhYrqa0datj6lLxi MCswLcl9OgrcXb4pLTHtfb79jiL3m97FjhL3Rt9MR5l7sy8JJVtRUuZ+h9H0aqV7hy/VUefe5ctw NLn3+LIcVvc+T66j1X3QcAE1P2Q1j6Nmu/uUL8fhY5Zd5z7ryxeuui/W3HRscF/1FTp63Td8xY4t 7iGsopfddz1HHG+7h32ljv52ZblGON4eVq537GyP8lU4drfHeiMcg+1TfAaHtX2mr8FxoD3JW46a qT6L40h7hs/hONqe5XM5Trbn+Dxom+8tp+uYr0e6h0p3K8eZ9lLfeseF9grfJsdld7mvz+FrN4C3 6+0N3mFK+7Y5brVb4G932h2+7Y777S7fey18u8c3YNvd3uPple5lLZr29b69LRHtm3x7xbqOU91K sanjbHeYaO242B0ltnZc7Y4V2ztudE8RfR1D3TPFdR13u5PEDR3D3alib6eyO0Pc0hnWnSW+3RnV nSP2d8Z250v3aHFn55TuQnF350xfqryLYPdreR1OovNdHHSndBeLBzqqu0uD/YfOOMwIzLiuGPEI 9gMXsDJfe8Nnu05nsXi0M6m7QjzZmdptEM90ZnTPDF5PxAudWd0N4uXOnG6LvZSuqCjHKipep2sX Vjl6Fw5az4WV1LfFW2yNCl6v4OfdDurn3a5gn4cPYwVAP6OrgbQyh9HVWLzjutPtEe8HrcwCnemQ F/4pDrJZf5DehYNX6Ta+M7+7p03TWdi9XjC6U7o6Ws9j3TvZFtFZ3L2pLaaztLuvLb6zwvcRtV33 Nmq77u3/i7zvD4siuxK9VdU/aH4NIuMQYhjGIYRxAFueg9iP/kHHNVhDG+Iy2HR3GMM4hrCGMI4j bYdAg9ASl2EJzzHENcYYYowhhs8lLmGJYQjhEZ/PEIfxscbxMw4hPMNzXUJcH8uH75xTVU3R4miy eflnv/udc0+dOvfcc+8999x7q38UxJZYJRqr1p0UWK+TlXi1Lwdq3AUxB2ZTVULN8f0FVUk1JxsG AXc2DJJ3WaT5Avgszpqanv2eqpSa80F+Ws1gw4WqzJoLDSOARwBn11xpuFJlqbnWcK1qY83NhiNV Ys0k7MRofKsKam433KwqqplpmKzy1Mw23N4bW8vAhy/hPg0x6C+t1TWUVJVVtzbMVFXURu4frdpT G9swu/cM4BLEjazKVxvfqKvy1yY2RhKOxb0cYIrJEq4K1CY3xsvtaq5d3ZhY1VZrbEzeu7s2q3F1 VXttDth/rNYOuL02r9FYFVe7pTGLcE5VR23h/syq07WuRntVV+32xjzAOxvzcH69crvqXO2uxi1V fbW7GwurBmq9ja6q4dqaxu1Vl2obGndKowbtOgi9NFrb2rir6mrt4cbdVQm1Rxu9VTdqT7jn9tyo PQX0RO2Zxhocr8YGwgdVdEPVVG23JxNwL+Dp2n6w817tUGOrtIuumq+92HhY6mevpvZy41FveO3Y ft4bU3u9+CrUPr7f411Re6vxhHdl7R3o1anau4o276raucZT3lQ/33jGm+EPa+z2rvNHN/Z6Tf64 xn6vzZ/QOOTd5E9qvOjN96c0XvZu9ac1jnmd/szG694Sf3bjOK0R0bjPCaR5T/rFQObr/f4C2I3D eQHWDtiZB7JhvbgRsHg7gd7oPVt9MSBK+yVvj28qUOA9/8XyQBzITAUsyA8U4R4p4EF6/5QkQ/xS 4E8Dn9Yd9ORAmUR7B0FnhfeCv6i+2zvi98Acb6vuDux54yzuDby0N8CzScCHp4D9U3syce44dwX5 AeQHmpGGlR1lJtRr1p4K0LPTe81fWn/ZexPkE0CmBWybBPl23CcE2rw9X4wBO2GH0Jj1xnl/WaCg 2FM91phF/HbkB47hLiLQIcl4b/sr6nd7Z/x76se8s0jvY0jjKUnxYThBzO6vgFm5JXD6ddcXVwa6 ZK9G+hzS0Fcq/p4iv69+yz6d319/HcbCF8jcF+n3f7Z7XyzGGegTiDO4Gwkk4G4k0Ef0ANHD++L9 AdyZ+JthZwgrSCAbPTxwac+8v62+wdnvb6+/o6ZRPpCN8iBTAOe1vH2J/mP1d9XxCunAKNIvHV3E x7X+Kq31N4hOofPUuJr2HvF31LfuS/af3s/jGTCQgqetQJK0h9m3+ktlgYl9xi9uCkzh+QtalOTv 2l+xL8t/ziPuy/F3QYy1+/sC0xDZcJ9/DvYMvbATDu5g8fwYCKPV7TTR95B+qZA8oWhfnn+g/u6+ Lf7hwATE7d31vdIqsK/Qf6mhpCmnyd6U52uru91Q4muum6y/uHdL3Q5Ync/UlTeyvf11lfs9vqS6 vQc6vTv8lsZbEval1FUfOOtLq6s/0PO6q67pwHlfZl3LgUFfdt2hAxfkHf6JuiMHRqTYIs19n6Xu uEeUT7jS2VY61apPrNJZlU6pvo11J0POqrSC+8S6zgNXfAV1Zxt3+orqehpsPk/d+QPXfKV1gw2z vrK6C7BPIz2+irqRAzd9e+quNO6S5q80E7HeA5PyaRp9Plvy5EXxNmjJgdvqCIljV38dz8iBJKld FDHipPO1FJekuYwryIEZXEEOzMgzneagz/fFHQdmff66a01M8hBfoO5mk87XXjfTFCk/naAnBr5j vqtNsdLTCV9H3Sz0rfQsgk79vtP1rCne11WvgxrpmYPUb9JTBWmf6btUn9yUpT5RyrT0vIJmkO9c fWRToq+vPrYp2TdQH9+02jdcn9hkxP8Hod+GMdVvw3j6bZgmzB7mZFr6PdhK+j3YM/R7sOSwvWHV bE1Ybdjfsiz6rdfH6bdeBRHPRRhZYcT/jvgd89Dv016mX6O9Qk8gk5mZMbaRfZolsFJWx9axL0Mq ZK3sK+wldpx9k21jJyEVs07WxVzsR6yXvcyG2LvsM+wG+w17jf2WTbEqdpfdZ1/Ct4qwA9xBrpl1 cYe5d9k/cO9x4+z3mnLN59m/azo032H3NX2atzlBc1HzDmfQTGp+xy3T3NUK3JPaZO1HuWd1B3V9 3Ed1/bq3Oafup7qfci7dsO6XnFv3v/Q67lW9Qf8U95b+I/pErkP/jL6WO2moNQR4reHLhjY+yvBV wxH+KcPXDZ38hw0/MFzgnze8Y7jKf8LwnuEu/0nDv4fH8Z/D70zy+yOiI57gGyJiI57iAxHXI37L N0d+IfLr/OHImSiO/1lUQlQC/07UyqhV/GjUc1HP8b+KSotK468xDvqlnL4TlYjfORJXAqwCSAXI YAniKjFVzBDXiSbRJm4S88WtolMsEXeI5WKluFesFuuBahJbxEPiEfG4eFLsFCvx91k0tizs42Ef Z3yYGCbSL9li+TQ+jTE+m89mHG/iTYznrbyVCbyd/zjT0FNVHe/gHUzPv8S/xML4bbyLGfiX+ZdZ FF/Kv8Ki6XlqDP95/vNsGf8G/wborOJ9bDk9VX0K+juZxet+qfsl+xC0aYxdp5bF4q/U8g+y0vyD +a35h/OP5p/IP5V/RowTE/K783vz+/OH8i/mX84fy7++eS5/PP8WXF3Mv5N/N/+u6MufA4PCHNGO OEeCI8mR4khzZDqyHRbHRofoKHAUOTyOUkeZo8Kxx+Fz+B0BR7OjLX9uIUE5KaXJqSCY9sip3XEM oNnRAXDa0eU45+hzDEAadlxyjDquOm44JkBiyjHtuOfA/0zi9N+G3lyxyM/xnxbWsUrwWhPbBz5v Jz9/Efy7iznAw3/EtoB/v8s+yW5BKqA++pT+Wf1H2Vb9x/QfYy/pn9c/z4r06foMtk1v1BtZsT5L n8VcepPexNz6HH0O8+g/oc9jn9a79R72sr5EXwLzhWNHYSZhL69iWsY29wEMyDBMec7mns3nNw9u vgB4ZPOVzdc239w8ufn25pnNsyITdWKkGCvGi4mbz4vJ4mrRKGaJOaJdzBO3iIWiS9wu7hR3ibtF r1gjNogHxVbxsHhUPCGeEs+I3WIvXPWLQ+JF8bI4Jl4Xx8Vb4h3xrjj3Iv8ifoeRC3st7A36TWD4 ot7aB2kd+wWkF9j7kLJg1v+GrWeTkLL1BfoCtkH/kv4lZtLv0O9g/5VxMIvC6dvHq5mesW3rAEyM c2FuA9jEOOtNxtl2CZnbMlwrt61zraJcoU2u1G02VwbBJte6bfkuE9F4b6vLRnJ4rcjhtdO1aZGe Elf+Ip2oA2V2uLYG83KXM8ivdJXQtULvde0gWrmvlEF7FDm8h/oxR8D71XBdraoX6XqwsVolFwpY LhTQBjUo9YWCYpsasO1Kvyhyil1oi9I3iv3Ib5JtxRyhBdqpBiyngKILAW3DdmJ+COrG/sHy2Aal DqXtOF5oH+rAa5R1ymVQVuk/ZYzUNip6jrjKg32Lck2qXLHluKuS8pOuvVQGdSm5Und1SH2K7VgO xxf1dbqqHyjfFFLvWVf9th5X07bzrpZFdqp1L2Ur5ootSm5TXaM9eK30D7ZNyVtCrrEM2qzIK3MB 7ylzY9B1iHJbSF0ZD2m/0t6MkPYr14oPKWMLdRVnSrzQPCiDdV5wHXEmum47k10zD/jHB+TF2Y93 f5FcaH8/Rl5sUV2H9rMtZLw+ICc71Hxo90NzuV9C+7p4o9RPj8of2Y9KO9S+j/WMuI4H59oV18lt 11ydRCu5Ej+VuXzTdTZ4b9LVQ75y23V+URyecQ1um3VdoD5T/BHqdjLXiFPnuhJsI9xzRrquOWNd N53xrkniKfEByjpXu2adRjcjX1R8EnJnllvnzHFHOu3uWGqLPLecee54hOJS91xxmYdH+eIKT1jx Hk90sc8Th/5a7PckkN9CPcUBT1JxsyeluM2ThuWDvrrUGB9SzRuZX9wO9V10H6V6ji3UEbzf4cks Pu3JXhQ/8j/AN1tC5naoT4XGlNC4pPQR+FFxl8ei2F18zrOxuM8jFg94CoJxSLFhXUgcUq1Rzi3u RITguqf4iXztLHQnO13u1QTb3UbnTncW1u/c5c4h2O22kx6vO2/R2oS+UOPe4mxwF6rXN+dBt4vW XAVkeWerezvpOeze6Tzq3hX0xxBwnnDvJlDsRh865faSTWfcNc5udwP1j7x2O3vdBxXdyvxx9rtb SdeQ+zCOLY2vuo7L7hPkt2PuU9hebKPzuvtMUOe4u1vdX85b7l7nHXe/8657yDnnvljMuy8Xh7nH iqPd14vj3OPFCVu9xUnuW8Up7jvBOYz+oIynOg8d94xH5KH+tS4kl/nFIsyFArBf7W/KOqGsl+q1 KHRNAn8tLpL9dSk5ZR3C2Fqk2ivIebEH9nMw3kpO+zvMH9XOD4q1OP9EKZYoebD/QvcZoeuf0ja8 bgnJlb1NSExalD/MXvV8PaSKB/K4B+NP6Lr6sLgROp6oW6lfnsPY37tNu20P7G2xX4Y9RcVp7rsI tIdBUOK9EhsQsM3oJ5c8nuAcRl2qOarMv+DeGO1R9iSwThSPekpxvuO8p7qvespw/qn1Fd/wVDyw 91btuYsnPHsW7ZflGBWsX45Fwb0z2jzl8dG8hHlcPO3xK+eD4nueQLDfZDuL5z3NwfFS7V1dMZ5j i3wW1yilj6CcS+Npc4V72vEUH/Zm2N8xFrGW/l9oKmKK4f/epvxln69oBXafnqO8TM9RPqPr1/2U O0RPUNrpCcoJeoJymZ6g/JqeoLxvqA2P4+30XGSMnov8Mz0X+RU9F/k1PRf5HT4XERLwuYiQis9F hOfwuYhgxOciwlo40Xaw0wtPDzZ0srwNnRvObujZcH7D4IYLG0Y2XNlwbcPNDZMbbm+Y2TBrYiad KdIUa4o3JZqSTatNRlMWpByT3ZRn2mIqNLlM2007TbtMu01eU42pwXTQ1Go6bDpqOmE6ZTpj6jb1 mvpNQ6aLpsumMeBj6oXEKCVTwqvDBEgD4JOAsGL8pWTI2dYHI/IlVgun2jOQNtA518R+yS7DSXYU kpn7OXeBWTQjmneYDZ9XQUmOOVnJQnuNF9iq9fHrE9cnr1+93rg+C/IcoHLW29fnAXfL+kJIrvXb 1+8k2GWcXL97vXd9DVxtB1yzvgGkEtdvJxt3gI1P0XcBGXgP/vtLKiQeztL4b7hpkDQsg61hWraW ZcL5+gWWzQxg00YWxTZBimZ5kJ5gIqQYlg9pGdvCPgmWfoptZXHgc062gv6pLoHthfRhVgNpJfND +gi7CCkR2v4Oe5qL5qLZM/RfXDULbV0bLmSabeZN5nzzVrPT2GYuMe8wlxuLzJXmveZqc725yVhm bjEfMh8xHzefNK8wd5rPmnvM541Ta03mQYIM8wXziHHUfMV8DfBN8whITZpvGyeM7eYZuFOWNWy8 Z541TkM9NpB1olbzSePUQrLozINSMo4aRy2RlljSoqQRKVniLczcZEk0r7CcIF1NltUWo3kW7LGB VgSnuVxOTZROYgKr9gIcAXvOgxVbjcegxKw5xpIMrb1gLrdkWXKg/YMI0CIb2GO35Jm3Ar3VssVS CFoHSYMC9WANQhPYdsg4QQDaLS7LduilGahzhABrQ7C9MGTZiXqVWkijAmgDgGUX5DugFEI51CKD ZbfFC+NxxVyZxZuvWRItNeZ6S4PloKWV6icb1pyi1qnrBrActhw1d2YNY2uhR5FSANuPJVHSZs0k 2x6ApfjWTMtBK7/IfhXQPbDZmm05YbVYNwYtVMFSfORZRRqvkVBAvrWARlkCtAP7RrbfcsrYvtZk OWPpBozQC/00CCPXvzYfroYsF2E8L5tLLGOW6+YY8IxK8tMRyziM4W3woVuWO8YO86TlLvWh0zIH bYCetIZZo61x1gSoEcbQmmRNyT2ce9Salnsi91Tumdzu3N7c/tyh3Iu5l3NduWPkifJIYg2513PH EaxJubfMV6QSeC/3Tu5d8h2lR5XeK7dEBlul9iu5F3Ln7Lw9zB6N3mGPW7vJOJ01ZU8gXz1oT6IS 0Ddr163dZO5ZazK2247Yjq812U7aTho7KE3bOqENSbazth5jhzXFPPLCEMy1MpxvxlHbedug7YJt xHbFPGK7BtFgBfRVvaXVeMx4DO7ctOXDbG62TYKW27YZW6exwza7Zi6XgW1bc3W5kbmxAPG5icYp 0HQetLbnJueuNjflGnOzzMdzc3LtuXlrU3O30J1C6K/tuTtzd5ltubtzvbk1uQ0Qe9DbNq01WYus HmuptQzmgw5nIFxXWPdYfVY/5AFrc9DThqxt1nbrMfC4NmMbxKASZfZYO5RZZD1t7bKes/ZB38bi mJgrrQPWYesl6yh4J8JV6w3rhHUK4tzNINDctk5b71nnbRpbeKinQjScRMCxscXYVhCstK1C37Gl 2jLIhxQavMi2zmay2WybbPm2rRaXzWkrse0A25uDHg4abeW2SpyVtr22cvNZiJUIPZLf2apt9bYm W4vtkHkG5u0sREux9DBGW3uKPQ0gM/dgbqstBjzZZs63Z0PUPm7Lf2Eod2ytCVKG3QJ1TBonLLEY jY3T9o120V5gL4JRbzNPgqdM2T32Ujv0t73CkmPfYxkzT1rb7D7bDHD89oC92d5mu2Zvtx+zdxgD EMdy1pywn7Z32c+Bl5ykmDuI0cneZx8gf+2hSC9FyjLgTJln7MP2S7QWvvqfaAdVxirpmTn+kz1b Y2EcQNwaEyQbpE1rNqUOpw6vyYe0FZITUsmaktQbqTfW7ICEvPI1h9ZUrjnyXPlz5Wv2QqqGVA+p CVLLmpbnTM+ZoB4+7OWw7fRfi3/FPgH9upm9CPsKB+wOdOyvofcioJ8/jf/1EDkZOU0W0WddOQOM s3ogH4a8VMjM6bMW5QwA9MmA9DDAJRlGAa7KNN67IctdUsnh9USInqkQnVdlmWlVfk/Fn5evZdqs kWnlvlJmVCV3VdZ/VYZpVZ3qdl0KkQuF6SVgPgQmHlJ2YgmYWqJOxaZLqr5R8wdU+YDcTjVcUoG6 jfOyvGLjqHw9HVLHVXm8JmQdV2VZpUyfqowyRqHlITeHq+ycDsllW8wxcr7CuuAbfSF1L1WfYvs9 ufzKJcqH1GteBZAKkBFir1r3UrZOq2xZKp9Q5aNy2x6WX5VtVuQVO+cX7DavC2l/aD+Etj+03aG5 en5dletSeKF530KdZlhZzS0Ah5Ye3z9r/rB+f9w8tJ8/aLwekWO7H5mH9LHST4/KH9kPofYr+m0L Y2/eBJAv0/kqO1S+bN6qknFK/WQusS6Kw7APKjKXWxdihhJPKwH2qtqIba4GqAdoknlKfICy5iMA x63BuRickycBOgHOLh5jc48EsLsqspyS5C1nALoBeiVftPTLPgn1wF6oyHIR4LLcPsVXP2guqvhU V45cj6oO5b5lDOB6yJh+kG8+ytdCY8pSceme5EeW8QW7LbcA7gDctT4Yl0PjkGq9MJ+XILjuKTFC vjYPAlyQYQTgilz/NRluynomVeUUX7gNMGNdtL6ZZ6U1VwFF3sLk/tQBRKraHwKWWAmCdkM/WuLl 8UkESJZ9SF67LasXdCvtthhlXVnS2NL4quuwS31lyZPai220bFHpLFzcXxYXwHaAnQC7AHYDeAFq ABoADgK0AhwOGZOJJfKHjfvD8seNccPWhbVjqbXnYflS/rqUnGpdXjK/IY93aP6o9j0q5iqxZNj6 YP8tlSttelSuikVL5o87PqHx4GFr5uOuaROq+pU9H/Svq9n6wN6WfHUO4KgEtIdZFVKveh8I+q28 dWEO31s8R5X5F9wbT1uDexJcJ6xh0nzHeY/y1mhp/qn1WeMW7AvVjXqtCap2yfrV8UmJRcG9M9qc JLcV5rE1xRrc41rTVP0m22nNXMJP4J51o3Wxzw6r+gjLZQNYrEX4vSf6L3z2n+esybXif6WzSC6a 2RhLDwOIBogDSABIYuyZUshTANIkeHov5JkA2QAW6Zp4GyFvkuXFBcB3Q6YXSIC0ch9l04vk3CPz EcoAKgD2APjka79MBwCaAdoA2mUZxaYiGbCuY7LeDoDTIbYXPQS6mC2tO603rT9tKO1i2uW0sbTr aeOQbqXdSbubNgfpzofLgEcpnU8PS49Oj0tPgKs76UnpKR8uSE9Lz0zPTrekb0wXIS9IL0r3pJem l6VXpG9MbE7fEz8fP5/uS7uV7k+79eGy9EB6ALjq5MPvej74TV96/4OG3vzwJL3hYQW94eFD9G6H lfRWh4/Qd3yT6Du+6fQmh7X0Dod19PaGF+jtDVn03oZsem/DBnpjg/UvXh/HxXLSt2Z72fOMpSUz 9tRRCdJWAxgBshZ4alDz03Lk3P4Q+XiJn5YXUm7LwjXdt8t0oaSTIOvB+gCef77z+bMhqUdFn1fR gw/hL5HwnYT0TW5G7/eQ3uyhpW9yh9M3uaPozR7x9DaPlfQej4/QGzyS6E0dq+gdHSn0Xo5UehfH c/QWjtX/3/Ry7AzrXvgMaGULczw5qqRnjQs0XK1WXy2dpBLPrkbZZ7MkePD+B+lTSdwLlcQnh/xh fD8lf5z/MYT1t/mfsUT+v/MT7Fldla6KfRyjJ9sY8aOIfvZX9F6ReIBY+f0czwTLa6A8xBL+JN/L tHwf6EqgMitBYgVhuT/iLjAubpDKfZ3edoFvJ81mFpXEKRYb1/8kn9SdcCdpPO5MXDekMUin4nrj +uOG4i5Sukw68NPkcP47/Heg7u/z3wfOD/gfMJ4/y59lAv9D/odg2T+BNVpo0zALo9aEg2U/ZhER PwH7YmDGNXHD9OxuK1sGtcMseybuEZDw0HtcXDxzxImQJuImniyBtOPJHUSXP1m+fHz5ONJxZXFl eI336D4PaaOUkq4mXQ3K8R+QpiD5IG1cSFh2kU5FTp1E4CkwAZIlUhmUTZpKmlo+njQN9vFoH5XP Tron28fDvauKVaoaeCpP9jxZSeUmFCuAj3bdgDSRRO2OC4NUJielDdNx0zSO+FYmRu824gwuw6cZ b3jZsJ3pDDsMO1iYYafhs8xg+JzhcyzC8AXDF1ikYbfhdRZl2GuoYk88tg9zXCd3j8Z7L+xbWKzp 8SGxHFZIF8D2BwHvISzfBdeFUg7X3NMNlDtis5bdjr28vGC5mDgUW7i8YNntZbfhqmjZSOL12Mux xthCuFu0vChxbnlBbHLieOwcJGNsZKxx2e2n+cShZSPLRkAOEpbD0qBvTM6BF5sH1EzsWOzO5R7I jQosL0gcejoOSoyA3jmQm5Pk1EC2KfCAjYljZGMh0GDfchFkyD7IwTa4N6S2acEe4Mj2YDtRb2yy BGhX7M7Ei4mXY8eeDgPNM8AphAS1QImxp6Njd8ZefzoJR4l/k4cYzX+V/yoz8F/jv8bCDcWGYvCA EkMJeMArhlfAA8oNFSza8JrhNbac3k0VF/H7iN+zpyL+EPEHFk9vn/rQHxXjnAAFABUU5VbRb0xc 9F2GHDnyrSI5H33jgGObVHKZbCf+x2xQjoNo9Pfg0TzEI6qfakuk2vANwGHk6Yw8XUOeriNP15On G8jTw8nTI8DT97Io0oRtYNQGLbXho1Q3vo0ILZfqfpZs9JLVHKsM8njmkS1Xy0lWcyxP5v0plj2q rUvbzbHDcn93Ut3JxKuX7e5X8S7J/a2W65XtrpR5+P/e/xGfQW+Jf2gLdKSJkSaONPGkSSBNYaQD 37GtfdAGqiWC9Ed/wBgeZj2qMZR4vaxD5XsSr0LuDTWvTe4Nhffn6ovHac1/pLeW6gv8j+CLtCtI wP/9io5kLLKNwBEVFjkeeSZaQ3Ai8gzm0ZqoQHR45JmoMKCk+zHRMVFdUQHgdUV1wZWG0grCK6NX AneeIAzTYo2KPukOaVLpiRyHq3GUxtoASzV3ReEvgwTDZwyfgTZXGsAjDW8Y3qD3ij3m2sTO0gjK n2xGHCNwRGVGZUdZojYCFqMKooogeQBKgZcZVRZVAdwyuLsnyhflBwhENQM/M6qNkkjyFpJVp8Ua FX1lcJ1JmlBPEdBFwMmGez7Q1RzVDpz2qGOEO6Lwe2y8odSw509tYXgfgSNiLpKP2A4wF9EfGRbJ QwqLjMYEnKGISDg7DUUMIV/O4yIToEwSJigRLacEKUGZOdK4k0pIGhV9Q6hL0gQ4mqRziOJBGw/l UwgknEAtfNVQ9kesHzzs/69QlJLmYQr+cx2XyWWzAbhuX8RN5TIomtUv4iZyyRQTdy3ixnEJzA/X RYu44VwM/c7StojLOB0rhOvVKi7P7tI+Oy7IWxi9R8/wWP4E/y2Q+DZ/EqL8d/nvws66k++Ekl18 F/RND9/D9NA3b7MwfhB6yMD/gh+B+HOZf4dF8e/y77In+DF+jMXwV/mrbBl/g78BOt/n34eY0xvR CzHnx7ArfxJ25T8B38C9/VcIv0n4aw/QX1HRbSr6kIp+S6ah7Vwh54K9X5rc9o8RL5/biu9pWMTb yInA0yzi5XB2uLqziLeOw28IXFvES+My4Wp4ES+ZwzNh9yLeSg73BccX8XB0OVi/1bxILpZWcDVP w4XD1Q41j81xvGrNkHgzbFa1Zki8KTatWjMk3ji7pfKJj5Gf4/gzit0cxW6eYrcAsXsX7AQqIILr Q0fCUP7ASLSp+P+N6FIVXaIara+o6DcfoN9SybylKvuWSudbqrok+m8WeYBEY3tX0TdE8UwqtTh1 QRpaJ51nEZ8FHI7/MI1vzpS5i2KXDnb5+kzm0JXqCnRlABWAkyDfo/MB7del6AJAN+va9Bm6duAf 03UApxTundZ16c5RKoOrCpBMAZ6USimpNS7o26NrAw2oaUEPyvmBcw7u9gFgGoDUrutjC/uxx43O N7kV1EL8bizT2gHgvKOF8412p0xDTNLulnOvTNfI0EC5Q1ugtWiLADyAoyEv1ZYBXaGN0+4B2qf1 Qx4AfrO2DagCuNeuPabtoFQEVx6QjAOelAooqTUu6CslXahpQQ/KVQCnA+6eBsDUBSmgPf0n7rcf 92QZzRVS7+2G8wbTwo5FuLEAeK1NXAwK/4l7APMSxEDsiQmXeDExACsAwFu1yQsg63QIE8KEZi/g UeG0JgbwPcBTkE5rwuFOtaZeEw6pCVKLMKqxaQ5pMjTrNCZMwmlJEmQzpITaQjUu6CNdoGlBD5Sd EKaAZ4J6bZojwj3IN0E6rrH92faef1Lf80egf4wLgNf8zcVAfIjfQhYAxEkBvF3IkwHpLQAwxwXw ev72AuA13Hfw5ZBmAZx8Bn8IcDXgSkgZfAtfDouwDvIWIRJSLNwdFOL5s7BKnqeUIUtm4JMqSuVy UmsM6kNdqEmlJwP/+xU456HeQSERcDV/gb8gJPODf+m+p7evzqp2E/iMMGy+cj5y3kJQCWD5I1YW PM9xNJoYk4fvZwdjNNMcRXwfIj3Xcx9obgIxn6Kpwc9qiDOA8lwrRCeg53HHM0GcgflRwIkkkzZf SbQOJYmeQcwmdK2EZ4BToovGunToV4z0MN1ukh+llYOh1+G5FbQzwjuAs2oeT6yH6S7tNqS9BFeN mA+jVUfaDRwhfJnuLieaVnVuhmhpFzFBpYzEbyV8kThOuks7Em6AOLSeSXsZjvaC/EaibxDtJ3yQ cAph2lvy44T75BpTaVeSSjankv5EqjeVLEmlFiHuIHnav8CsQ9yDWGggbfeIziM8SZK0q4F+kex8 guETE+RUkswFwjtJzxWi6f3PwjrEmi7CGYTzSZu0f6Fd0f0xomkXdr+JdM5R2aT7o9g6xNwM0U6i OwinIRZ4onfT3WOE+wivpLudRPsJnyJ8iPhbCFcSniTcQJjq0sQgZrP6lYTxOdIsedSwxAlLIn4f YT951AxikmTaO0RL/FbipBJnJWEsNUG+Rz4PPlmJ7SI/b9VSP+hxJnYTvkY6uwlf06UhjZhP0ZIP YCk+RVeCmOQnSMME8gHj/7dMSHzy/wndFexJLfkncgCnIdYbCW9EPyQ8g63gWrEsV6LFGVFCMiWS jK4HMekZIMkBWZIR9lKPSbNPwq3UV1i2mrTFk2Q13Y3XVSPGu/xGvAt29hC+Qa0YJkx8qXZtM46+ rgM1azCqzCLmqhFDn0j6d5DkMGINxROS7AZf5vjPkpd+l/r/GuFumc4gOoPGSIo5OsJdxKHYMu+B smw+D2uZP0GRSopXMRSdKgmjTAnxS+4nk69ijIonnEilEimaJUoRbP4zOMeJc0PSQJITEkZLONln yAcmqM9LaBRKqOeriY7HfgZ/mCFMI049E0/y8dSrs9R7A9Sfs9LYoX+CDdje+7C7gniIMnBXonHP /FMa0z8Q/w7xlxM9QfgyxdhfE07UvAo4h3o7lXAcYSbjBMKvEtbR7Ogm/CJhegar/QrhHSSTTBGs gPDLaAmD09n9m4zk6TM6hqdsoRLHGmb0UcRSL+GsESoRcyXzNN+xb8OSsP91rYi1m7CHNUepVCRi TTb2iRAprSDoOdpmiU9x7xTS2mHs27BJvKujOau5Sb09jJZAtLkE+P37/wr4exTHViLNUWzkZ+S7 iDeQzJvkjaSfGyIOI/+htQBkLlH0Qw2VhF8iyQ6iW+TIXEHxH1Zcvhp7RngPIzx/cb6BaJR/iVoa g7SWIq1Qxb4N+Jy0btKKMIBYOEf10plKE0GSZdjPwnvk//dpxO+TP9yhuHcf4+H8KPb//DTNVgaR nrv/rzi+/Pd0/wb4X/RrsdU6PIN9T3sT+0TC+ljEuiSUwbvC/0E+fw45mjriv08cpsFxHNLASZHf olmNWFtOfJg7wtPI4XqJjkbMr5bktTaUgXMP9DxqY4lw/gF5bRno79ecg954RXsQ6P+JtKZLmw+4 CbH2MEpqv4U0fwCxUKOF3Yv2beKYEesjSPKTxGean0PZvyGdb2vWA/0jpIX3tH8LnBiSrCCdVSiv v0SlPkk1jpL+F4UAYLPwZcCrhNeoLNgpaIU6wDZtLuByAXGXADZzx4RvAb4nwBld+K1wHuizVMtd IR04PyecJLyBegQLcXAWvCLUg/1/L/wPkO/T/BY4PxM6Af9Q+CGUPSJArBO+KhwD/M/CDwB/SsCz PuOPEcYTNePOgIZSDvds3+NPgowb9pacwCHNv0acPH4IRxZproX47Tzo5+qwFq6VZI4R/xfIB0nQ wP+dINHnkY80v4H47/PnCANHk4gYaCz7Poczbh/RjEtGee4bOO7cb4geB/o2j8+HXufRQ+7yuM6u F/4v4Ge444A/x30e8H8hq1LIqpe4X1PZX5POfyEa1hp+HXcLd0rI51qQz+XyGuCHk+S/EY7j3kEM uzO04R3S8H1q0TiV6iZ+J/FPAb2OtL3A/wrwu7B/5NiHqN+eRN/QdFH82aG1As7U8BipyFvepFH2 Il/oRFqnJ5/8Kvnkq3T3LcLfpVK15JMD6JPgUchPJslLRH+DfG+nAP2j0fL/CPRa4a/RozAmCx60 XCjRagHfFGB/LnxT+DTGCgFHn6HvabQCRGyO5oV2jLzuJ4Rb+N8Dfod87z3ysTeRz/9I+CbgZvL2 fqEFNHwItWm/gRj8EPH7hL9A/LfIhnbUxr2N8nA+QjuPCjg7BoQfg4Yo4WM4CoiFDcJTQP+e6G2E 5wSMct8SvgP4H0nnl4R2qh2w5rwAM5RPF34CUeso7UJjMPrdTyCcjftn2BMAnu8kTgZhnby7PkwR 7xLh92g9+imtX6/Tel1CuyzErdJeCHeGsB7RDoHW32q6G0+4BHeJXLXeRDuilcQx0a7pDu0NRmmn Z6LVzU/0Stp9kSStek9of/D/2PvyuCyOZt1+p6f7fYEBUXANKO4KqC8KCu4LbgiouMS4C4qiiArE GJeoRNGYiEaNiX5GiUnccIt73I1r3HfjvmCMEneNu3C6npm8n+ee+51zzx/33H9u/OWZorq6urq6 q7p7Zhiw82yO3WYYYUEDWE77auznC+5apx7CVHCwP1crDa0muAOZj/28aq8KduPUU9yFVGc2Wh3w 7gidoymjQnI5o71WT8g0heYQ0Jux4uCcxXFS0KGBY+VS5z2cCGgtEzhNaGGQx7lAx1hInLD038wT BEnyDQU002pCT3dgQ+A96MGpTX8GzkjQ66F5lylPqxjHKcY2F/RptGiewhbQvo7vJNTqmussydjN 01YQ1sqVZl1oi4P+G5akqmUvA06eeV6D/FlCUTp/pJJfTKjPI9TuAF9gJmwhVPFMlmTQDkeLpVLb YWBt0qCXot7pe8xzFsnze9B5BTI/0H6GYxz5X8B6QOxA9IqgDZw1isLaldDwBrZ1hZ+nE9qTqRei L6H+W0EkdghKUhtO+vVoovWmGIXlQPOkFgpPHoRkbXBO0/N0rRKs2kCoTQH9IXAksBX4N0HHYW6/ JdQRa7wh9mwaODuws8o1z0pAB3wi1TwlmYOYRbSjeAtt2ONp+4ivtUJpJObGbfNcCc1NILkc9xN+ AKcYxqsj9O9D6R7wSwEDwO8Fj7UzowB7yGUFz1StTbD/Atr1Q92GoH2Bz9DKn5bMUMgPxSiTPwuh F/2AiZCfD2/PA15AW4Whswk0dAf+ZWrD+B6F5/H8yZaJXV9JM0LRylaMzm1YjnsRAqcYkQ0f3rDs IUs4asWDM5702MpB83HoOQ7v4Y6EQHSrPQG1vgilZiRqkN+BUjPSr5n7TzPWMOsuE0rcV5FexJer oAfPxNSsIDsvmeML/nvQds+8kwDLl6GVfeDHQP/T/LXM5t6LaMdqcyYDcVdEPrVaV+hAdrIPh83D zayCSNwKjKeZL89a2WABxr07ohgextntIMblLc6Av1szgfRnoTTVROzDDfjqFfoViBadWml4iXqN SFQZgHrqbZaCDkcp7m5ps6B5OdAPnqkPPADJ1cAZGK/14GeABl9DxpY/YGT3oBfPYQmyrtqrZys0 xHbK3oQFpQjVKmbD+pVNSH8XveAZncIKNoN+pM4EdL7D2U3NCJL3Bq5W6E58W5AtX6EbIVsPuiIw BhgLfI7SA8Dz4NQEXYi0qVZMnb1hw21ag+yDyFp7kMKFamxtBS0JlZ1XgCFY9bJAbwB+D7wN3Av8 DXgOkqeA5YFpwP4o/RH0F6Cxmstt1COd9rFuhGw9ecZWEZwYYCxOxDHA55A5ADyPuxA1QTOco5l4 Dp0/gYa3ZTFme4N7cQU4qbme4pUG0mn3EUpvYB+yxyptQbXy8Z6PhbifSXNP4QackujclIw95H67 GinRmVDPJZQRhNwfHEZonwo6jdABDgdHWwaEvAQtrqB0JzAQtYJQ+hXoQZA5A05lcFLAuQOOO+go 0JNRasqY+pugrXRovg+rMmEPrJJoS2SB7olaR8CpB7oU+APAqQO6A/iLgXPA16EZFurbQS8BnQTc AqwAG0YBY8C5CHRCpw/0nEfdMMhAm3YMCNv0h8BI4HuQzAG+BicOOA/oBZ3miLxCf4dBfw2UtgG9 FKWHwHkJ3AMsCZ2wRHQCxw0cX9B7CT0wvm4dgRh9N8wEB1qxo9S+GxrgWy0f9FWg6RMOPizUm8IS yOu9gJDksFC7BXoz6m6FJHzOH0ASmjlmRcENmpkFe8ynAKgbT5Gu5upAoDdlZrXTUfOW7vKJzoR6 LqGMIOT+4DBC+1TQaYQOcDg42jIg5CVoFQXJmPnJiIVkzP9kzHniXEHdncBA6AxC3a9AD4KGM+BU BicFnDvguIOOAj0ZpaaM2XoTWJIOzfdhcyashc0SbYks0D1R6wg49UCXAn8AOHVAdwB/MXAO+Do0 w0J9O+gloJOAW4AVYMMoYAw4F4FO6PSBnvOoGwYZaNOOAWGb/hAYCXwPkjnA1+DEAecBvaDTHK9X 6O8w6K+B0jagl6L0EDgvgXuAJaETlohO5phijIAqIyUj9pORx5KRnZKRnZKRwYjvBg2+0LaX0AOj 7NaRaDfMJTfMKwessptzaTHJeIC270brGBctH/RVoOlPDj56pzdFLyCv9wJCkqN32i3Qm1F3KyQx XvwBJKGZY0bZ2mKfsB97m85Yr3OxR4rAfskfHNwVtE8FnUboAIeDo5k7IshL0OIKSncCA1ErCKVf gR4EmTPgVAYnBZw74LiDjgI9GaWmjKm/CdpKh+b7sCoT9sAqibZEFmicc/Uj4NQDXQr8AeDUAd0B /MXAOeDr0AwL9e2gl4BOAuKspFeADaOAMeBcBDqh0wd6zqNuGGSgTTsGhG36Q2Ak8D1I5gBfgxMH nAf0gk5zRF6hv8OgvwZK24BeitJD4LwEloQ22CA6geMGji/ovYQeGFm3jkCMuxvmgAP67Si174YG eFXLB30VaHqDg59rnstgA+T1XkBIctimYc/PN6PuVkjC2/wBJKGZYz6onaHaq+QXozvzame4DjvD ddiJPcdusBR2g7dpZ0IcVp92hqr0MfaEW7Fzm0z3GcBxJ1R7wjzsCfOwJ8zDnjAPe8I87AnzsCfM w54wD3vCPOwJiS5k7jzNVvRo2jPTsy1tPiEvBvo4cA1wCqEtE6UNwbkAOgsYCE5d4BJwDEK9Ojj7 UDefnkRrXdTO3WbLA+0gWtUiLAJOJEqDgT0JeSuTD4wF1gU6zefahDwU9DXwb9IzNe0FcI09Absp J9lDqHeGPTeJr2QSIEOSU4i2ZQKnQz4QdRsCNaCB0nxxEjiGegH6Kehg2uXaygGD1VmW+jKG+kUy Csegp0RXsnAMVtKidBqC5X7gMOJow4Q6/+rR8KSGp4TBenvSYFoIDfNBHyaax4H+HfZMlxdhFckc Rx8voDTYHksjC04kSu+D9gO9DzJnoeEHcJZYbakduPYEkvtgyTWr1KSVzSKCrOXNaNet4y6r9oJs 4KHwWzFI5qF3Wy0+eTgOY1FE0s4kErb5kR4tQnyHsaBaOkWNLRM90smrthKYSyUwQ6IwcyLIM2p3 oWS0HNTtJOLg7TF02jXHDv1aA/nDwKfws2m5QLs/AnMxIh9JdUrVyur5xIHMcpT66IPRCtF+kNxC krwBZAIIbVmg/aSbos0eVYLkbrN3pEE3x70otO0H/1vUjZItYT/dU+0EmUCU/gx6JOnUEuHh1vDe KHhjH/QwYDQwAjI2om3rgUuAp4GdMJdCIdMD8tXAKYJSP7FLoT9xbCWAldCjyrinbdYFnyfo9JT8 LjREgh+JXsyFntGWPaQhjey3zQGWAU4GdhLfKJkRlk6SzwWWQ6198OE+6HwLflVInsW4xELmI4yj HfwcPP2pTHNA1AGGEfJsmg/cJnYqfEa0vgv0KJR2JtQMtHIX3l5GbfG9ZuzQzNGrYxaFgvY28wnm 81XIjMNYXEUm8QR/HGgnZtpE0FvNHAhOMjh16Skzj8O8HU601oWiQLuPqA8wsyvanYkYz0K7iYi+ WGA82ppvaaN4qQ09ZYnPNXP+o92nYgHi3Qkb6GnOALSuQY8f2nWY2QM90uGNKfBqPHnDAUvs80lG wgaHRjJyC2bmCkJHGnHs9YgWfwCroHe5sCcAmuPRViztDB1TZCbdNaJn5UonPSctBU9+hXm+Ffnn F1i1FHYOh4Y6mDljMR8eQHId0Ab+MIodjszAo7A6FJOVkX9GwDN0P+Eu8i3TP0AszEVcN8Cunt6X q0S0yrcKtRrAEeDswypzDq2cAacnZqAf8DJp0zbB23limmo3Gk9mI1Arnzgql07D3QxqfSxazyM9 BZu1CxhlZaGeTigyQB8FbgZnGfAherGVkN9G6SeE9niUbgf6gh8NnAf0Br8F8AvILwGdgtIb0NaK diC8j/ClVY9ovQL4AeBfMVsEPYFkNLTI34BuBG2XULoFGAfcCXwMzCLULgBbUy1dopXqhFKHzBtw wkEvBz1DliMPEIrtwJmE0oPQvgj2NyBa5WHCRMgkAa+D8y2deZUNhB8Sasf1jylzEure4C8mVPYQ dgOmIZPshw1TwWF4epir013KNF1lSPvX5ptCtIPS+6GtGjhf14HNNtAFoBuglVQZojjnIDkTpeVh ZyFCbRbozvDqTmj+Hr17BPlcyLcA/T7d45JfYYcwiHK1OEN2igiULoC1nURJJdMcnPMkL25SllOW k/390eJGer6mOGr2CqybKu+9Vf16Cw/rsLkW5Umd3mm2yQnoywG0NUvQWl+atIkbwkbnGjxFdQf+ BX4qycgXtD7qr0QH4uhqZytrEYoFpj3IwCd5Cq2JpoeJY/emWtIPOfwuadPKQNKfUBamnbNurino F4/EiIyH/ANTM9+NXrsr/q/UC+WlEtirRMPyXXQHGz6vjVG+BT0BohVGgegPqJYcAJ3lQS+hdsV+ 880EjA7GS5+BUQunXvAc9CWS2tIjyQbeD5zSaDdNKI4uIBkHLAbcAexAqC3DjEqCZCJp0HHHWK8A nWOItj0R9DQ2hmiVYZ7TSQ1xZNZ1EopzusqKYgLpVJ6nJx1Tic+nonfhJk06+RRgGNqK5LQ+zoHm QWSDtgzYikZTyzI5+hzqEVppDj0XoaEzPOwPOxlmSKTVohoFng4MhyWvIf+W2hL9aDXX56HFTqiV hl54wZJS4hjVoroyF318BURsihoYuzYY3466mmNyOI2s/hL8PcAUeL46nqS3g23hiJF0M28g413B nK+KGd6e4kU/hQwTjxlyCfLfobQoaG9E0AXQ/eRhin1BYzcfsWmD5KeI2d1o5Q0k2yP/HIDMB6Bz 5T9U6TrsOnZQJOp7aRTc11Ett44k46hG6IaZZl+P+baB0G0/oSOSUF5HaQ6sTSV593WQ6UgeUBoU 2pHtRaDoBZ8oP3NPzI0pxFGrhkK+EjGIdVydWZ4hj9E62452TeIu+UrFYymsVhRfown5ehGJ9WU3 9smkJwyeZ9ycLW3pXgedWGVRrBcxRGtYZ3VfovWH4ByDhhzQ2GfabmKfOQRxNJXecJOx9CRCr6J7 Kc404mi90OIDtDgAtmF1LriB97Ve4O2v+XiuWqzgD8r/4KwBTrH49N5XJvAlOA1RegF0FjAQde+D Hw96CfgGOHjHzJYPfhdCWx7oSNADIFMET8DxzNQWTMhOgtMFelpBJtZ8So6nYI0h+QM0TIe2usBY yIdCvhJkfsFT7M7gzAInz3wDDXXLWZJUN4KQB4D2Q1sM9DDIROAJdTRkQsG/CW2H0WKcZckjWDgU XiJOPp6LrUGLedC5BPZPh7ZZ0HMI7wCMRd2tpjbI6NBfwvS/9f4nvASdkaYfQOeY7+nBtkBoluD4 AGuhFvrLBVr5Ee3mgvMR6LJAH0j6gb8F2ACtYJRteKuQ77ZqEQ1JHZ7hRVF3P/QPK1AnNe1b0MOh oRNKc4A/Q8NIlCaCsw8y+2ADPKzZ4L31wCXA0+D3AFZDrSLg+8M2c6wxarwy0PRGK0jChzwBde+a fUeL+4HBwEGQdMAqvB/CnoPvDfwcbQmzL5AZAT0lgAyccuZ8gx5P8oANT2y1qig9C0k7ZuNJ4A28 +RBGkjwbFtpg+TN4dRfoUeiFOXsRTba7oJeh9Db0eINzFaXX0OJ84DhYmw/6PrAS8Cb4Z00Z1O1i yZ9m9ESYcKI5G635RpzjoJ3ANcBktPgUlhQDBpoZA28URAK7oO5WvI0QbL2NgCiG/hegX6B0tGWn SRPOteLlNGweCvspsjT0Wpq9MzMYZBzwsI6RmgIa4+XA7LUjy8lE0E4qlYgyjjhSpcRBzhGfIIL6 oS8BVk57RCcy1B0OPt6N0SrAhrnwQxSwI/h1wB8L+x8A18GeHDypx5setmEY2SgTTT8ULEK+nYdc sRBZFO8Zwp4t0FzDzJlW7BOuN2MH2A14BngZ8ptgbbQ1ExYi8xA+R+lYKxsT3Vu/qVoZrtMJtLc5 A/HUYBfu1u4yn7oyZj0NdmfzbcuY6JPaJ54FJHycmsw69k/tN4j1HNAvPpUNTO6TnsJG0O9AdoqL DKA3tgoK6C9VMjfmwQozH+ZJPymeg+7XMoMVYkWYL/NSP9PvvVAJc1E2+lKQRWtMMk56ozu2CqAv CqFct8oE82ZFExIGD2XjgJnAL4CzgfOBS/omJ/VnaxKTUvqwTcDtSSlJ6WwP8GBS2pBkdhx4Vgn2 YZeAN5KHJCSz28D7g/v1TWJPga9SVbGNAfH+CPsn4v0W+r1P9EH8O84/KRvzBLq9gx7voOMd9HoH 7UBTj/s7aFhYmFVgwSyU1WeRLJp1ZN1ZX5bM0tlofPNjFpvHfmCSXq9lk5n5+0ZFzCv+Hom6OujL 5OoE46jA6P0Lm9tB82d3J6G6ZsNem/tm63rAvHr7mlef6UpeXYtXMOuViDJ/LkG/Va30l1hj8fdZ vSii/i+HtgvhCwjRLIYx/M1X7X/+q2piIM0oWzktlLfQuzA/Vpc1ZVEsjnVl8WwgS2UjWYby3HT2 DctmS9hqtoFtZ/vYUXaWXWE32V32lL1Rm0TDvoFx+3L7CvtGXFfaN+G6yv4zrqvtm9V1haK24LrC vhXXlfZtuK6yb8d1tX0H09R1p/pppZLehesK+y+4rrTvxnWVfQ+uq+17lfRKu/Ks4i2378d1hf0A rivtv+K6yn4Q19X2Q0p6lf2w+mm1kj6C6wr7UVxX2o/hukplAbqutp9Q0qv/F4/Q9/VHsHH/Rx45 iZ4vt5+yPHPa8swZyzNnLc+cU+0st/9m+ee85ZcLll8uWn65ZHnksuWRK5ZHrloeuWZ55Do8csPy SK7lkZuWR363PHLL8sgf8MhtyyN3LI/kWR750/LIXcsj9/4Lj8xm89kitvJfeuS+5ZEHlkceWh55 ZHnkseWRJ/DIU8sjf1kz5pnlmeeWZ15YnnmJGfPK8s9ryz9vLL+8tfySb3mkwPSISjTwiMNmesSh mR5xcPKIQzc94hCmRxzS9IjDbnrE4TA94nD7b3hkDzvMTrNL+K7AY/ZKbQDdHe6mRxwepkcchukR h6fpEYeX6RFHIfKIw9v0iKOw6RFHEdMjDh/TIw5f0yOOouQRRzHTI47ipkccJcwZ4yhpesZRyvSM 4z2aMQ4/0z8Of8s/pS3/lLH8UpF66giw/FLW8ks5yy/lLb9UMP3y3/bIXZdHKlkeqWx5pIrlkaqW RwItjwTBI8GWR6pZHqlueaSG5RGn5ZEQeKSm5ZFalkdCLY+EWR6pbXmkDjwSbnkkwvJIXcsj9awZ U9/yTAPMmIaWZxpZnmlseaaJ6Rn6QizZjRVohloJDJailgCHWg38WCXmVP6KZLGsi3FSZfpmjvb6 DOOURc00ToOKU7wzFjXTOKuo5pA7Z1Ezjd9Akdx5i5qJrwRVYNVZuBqPaNaZ9VZZPZ19wiYbF1wt XXS1dMnV0mVXS1dcLV11tXTN1dL1v1sy8hTV0tFM8f60qJnGXVDNFe+eRf1nFt1wWZTrsuimy6Lf XRbdcln0h8ui2y6L7rgsuu+y6IHLoocuix65LFKxb6tuq642MKU0uj9dXiuPtVjt3DxrYReQrkZt HCv5H21mc9X+YiXbxE6qefzCRl8mKWYLsAXaQm0Nba1sw2nn5vEL0/ClDd1jt4va8zelHVHUN6CO uqhjLuq4izoBinaHhnaSaC1X4WyUnXJJnXZRZ0Bx1Qsv5qudRQ2yZKpGVnwFmXPvyBSj34/XZmt7 GVeSs7XfXJrOu6gLLuqii7rkoi67qCsu6qqLugZKqPH3VXO+HKuiqfVZ+1a1pdZnbb667lcS32oH FM7Xrrvq3bD6bdeytOlqjLK1RUp+ibacuWsrtZWskLZa+4l5a2u1dayItkHbrPRz7EZ9Ge3hGmOv 5W19i/M7VZCj5Sid65Q817Zp29T+TI22NgvfBaAvLdLYq0yPvaw7fQVOm6vNZf7aPG0eK6107GBl 8Hv+jfB7/qQ/RY3Ku5Gs7OYtlc7noFq5qNYuKspFtQEl8JXPEuocUQE1H6PWE9R4Cum/IPmMMon2 WHuOHqr1Qk6SmRqdDDhHt7k7p/usBjfQDyXB70h/TrPcJsvIslTP1pUt43k8gFfhwbw6r8lr8ww+ gWfyyXwKz+LT+Sw+m8/l8/lCvogv48v5Sr6ar+Eb+Ga+nf/C9/GD/Cg/yc/yC/wKv8FvKV13+X3+ kD8WVUSwaCAaiSaimWguWorWoo1oKzqI90U30UskiP5ikBgi0sRHYpQYK8aLT8VEMUl8Jj4XU8U0 8aWYKb4SX4s54h/iW3pGIH4US8UK8ZNYLzaKzWKr2Cn2iAPisDguTorT4py4JK6Jm+K2uCseiqfi hXgjmdSlQxrSWxaRvrKELCVLy/Kyoqwsq8ogWU3WkCGylgyTEbKebCSbyGayh+wj+8k0jzUe6zw2 GJohDXfDyyhiFDNKGaWNckYlo4oRaAQbTiPUCDfqG42NSKOVEW20MzoaXYzuRm+jrzHAGGgkKx8v 5Q5Om4syvAzdp+GVmcaDeJAahWq8mhrtEB7CBA/jYUzy8Xw8s/NP+afMwSfyicyNT+KTmDv/jH/G PPhUPpUZfBqfxjz5TDV+Xvwr/hUrxOfwOcybf8u/ZYX5d/w7VoT/yH9kPnwpX8p8eQ7PYUX5Cr6C FeOr+CpWnP/Ef2Il8JuIJfnP/GdWim/j29h7fBffxfz4Xr6X+fNf+a+sND/Cj7Ay/AQ/wQL4GX6G leXn+XlWjl/ml1l5fp1fV3Pzd/47q8jv8DusEv+T/8kq83v8HqvCH/AHrCp/xB+xQDUHqrAgNQ+C WbCoL+qzaqKhaMiqi8aiMashmoqmzCkiRSQLES1EC1ZTtBKtWC0RJaJYqIgVsSxMxIk4Vlt0Fp1Z HdFVdGXhoqfoySLoizWsrkgUiayeGKjOLvVFikhhDUSqSGUNxXAxnDUSI8VI1lh8Ij5hTcQ4MY41 FRkigzUTE8QEFikyRSZrLiaLyayFmCKmsJbiC/EFayWyRBZrLaaL6SxKzBAzWBsxS8xi0WK2mM1i 6Gs7LFbMFXNZWzFPzGPtxHwxn7UX2SKbxdHXeVgHsUQsYR3FcrGcdaKv6rDOYp1Yx94XG8QG1kXN 3S3sA7FD7GDdxG6xm3UX+8V+1kMcEodYT3FMHGO9xAlxgvUWp8Qp1kfN7HMsXlwUF1mCuCqusr4i V+SyfuIP8QdLFH+KP1l/8UA8YAPEE/GEJYnn4jkbKF6L12yQKBAFLFlyydlgaZd2liI9pAcbIgvJ QmyoLCwLs2HSR/qwVFlcFmdpsqQsydKlv/RnH8pyshwbLivICuwj+voSGyGryCrsYxkoA9lIGSyD 2ShZXVZno6VTOtkYWVPWZJ/IUBnKxspwGc7GybqyLhsvG8qGLEM2lo3Zp7KpbMomyO6yO5soe8ve LFP2lX3ZJJkqU9lkj588fmKfeaz1WMumeGz02Mg+N9Qiyr4whCHYVMPNcGNZhqfhyaYZhY3CbLpR 1CjKvjRKGiXZDMPf8GczjbJGWTbLqGhUZF8ZlY3KbLZR1ajKvjaCjCD2jVHDqMHmGLWMWmyuUceo w/5h1DPqsXlGI6MR+9ZoZjRj842WRku2wGhjtGHZRlujLfvO6GB0YAuN94332fdGN6Mb+8HoZfRi PxoJRgJbZPQ3+rPFRpKRxJYYg4xBbKmK/FtsKC/HA7mTh/Kn/As+g3/D5/Fs/gNfwtfxTXwr38n3 8AP8MD/OT/Pf+CV+jd/kt+krQqIqfyqqiiD+uYgR7UUn8YHoIfqIfiJJDBbDxIfiYzFGfC8Wixyx SqwVP4sgsV38IvaJg+IoP62uZ8UFcUXcELdEnrgvHotn4pXIl5qU0l168dsiRhbj5aSfTJa1eVnZ SybI/h6bDN1wGIbhbfgaJQw/I8CoYFQ3ahq1jbpGQ6Op0cKIMmKNOKOz0dXoacQbiUaK6uUQZDaG zGZDTtOQ0zhymo7cJZC1JPKVHfnKgXzlhnzljnzlgbxkIC95Ii95IS8VQl7yRl4qjLxUBHnJB3nJ F3mpKPJSMeSl4shLJZCXSiIvlUJeeg8ZyQ8ZyR8ZqTQyUhlkmwBkm7LINuWQbcoj21RAtqmIbFMJ 2aYysk0VZJuqyDaByDZByDbByDbVkAeqIw/UQB5wIg+EIA/URAaohQwQigxQGxmgDjJAODJABDJA XWSAesgA9ZEBGiADNEQGaIQM0BgZoAkyQFNkgGbIAJHIAM2RAVogA7REBmiFDNAaGSAKGaANMkA0 MkAMMkAsMkBbtTsow9ohltsjfuMQsx0Qsx0Rs50QoZ0Roe8jQrsgQj9AhHZFhHZDhHZHhPZAhPZE hPZCPPZGPPZBPMYjHhMQj30Rj/0Qj4mIx/6IxwGIxyTE40DE4yDEYzLicTDiMQUxOATf8UvjZXlV XoPX4k/45/xL/jX/B1/Av+eL+Vq+kW/hO9T82ssP8WP8FD/HL/KrPJf/QTNGxeATFYOBKgajRTvR UXQR3UVv0VcMEMliqEgXI8RosVAsEsvESrFG5fZNIlBsE7vEXvGrOMJPqesZcV5cFtfF7+KOuCce ib/ES/FW2qSQbtKT/yGiZVEVfe/JQbK26KionjJeJorrHuvVZs1ueBiFDB+juPGeUcYob1QzQoww I8JoYDQxmhutjRijvdHJ+MDoYfQx+hmDVV9T/38k/rcjkVbkWojHUMRjGOKxDuIxHPEYgXisi3is h3isj3hsgHhsiHhshHhsjHhsgnhsinhshniMRDw2Rzy2QDy2RDy2Qjy2RjxGIR7bIB6jEY8xiMdY xGNbxGM7xGN7xGMcVtUOiMqOiMpOiMrOiMr3sZJ2QWx+gNjsitjshtjsjtjsgdjsidjshdjsjdjs g9iMR2wmIDb7Ijb7ITYTEZv9EZsDEJtJiM2BiM1BiM1kxOZgxGYKYnMIYnMoYnMYYjNVnZ8l/gpo b7aQLWcb2E52kJ1mV9ht9pi9wX0QnH1YoDpB1Wb1+V9qNmfw5won8JcKJ/PXCrPkZKaJBnKEwkZy pMImcrTCZv8bDc+g4QU0vIKGN9DwGTR8DA2joGEMNKizmPyEJECNdVHjXNR4F5Xhoj51URNc1MS/ Kfrbpxb1BJQ6vauMc40x8VbkM03lBnUqVflBHVpUjnBnDhXbifiuZhFmfj1O1/5Qp77ldBdCoycR Ubh3VImF4k6At8dhFelKI8/7m1Jzhu4vHFE/PVFnucuQ8+JjVV5QZeaV5+G8SCcMhrOCTdW8+vd5 kZ3xKOTh9R+eTVDb9PSpHAtW/m1s3Yk4hJPzYdcdhZv0ZU1Qv7uoW39T8iOS/k9P4uazNxueuhl4 vqScpT3k7+n99QF6kvV0zmZKMVZ8gLr6gsuK93ZmFO8u3QIzW2U+97TZteyM4jGK1Vqz2UI8nG5S BHlxrZRgzj7SPUjadFtGHc2mZ3dwtncGv8PxW1h6nB+rj39tWTxLU0tLMuvH0tX/Demfs+w7ynTf Va9ff7Rn+Qnv4YPa9fl8cZj06sVTszOKhDgzdGURj87mmk3T3KvnFL7UrqD7t4d2/l3bX5kyNCTI WVXyTrqHT7lmQ4Z+nJrUf0B6QJWEqgEhERF1AmKSElKHpA1JTA9oNiR1aPWQ0k4/U7jovy8Zkton PWlISkhZZxkq5z4l/lkeN2RIekCTD9MHDElNSv/YWbq4p7OOM7ym+q9WiLNm1+KeITXVj2GKqf7r 6vwYvlJKpI/WqUOIj7Mw/eDwcX+/T9qApJT+6aoZb6cXMe0+9rh+fQcPSen7t2Hu/8qw8s6ypmGl 3i3v2y+gQ1L/FKU1oF2zJs4MWzmnp2sAbTbBeIatEFN8dy3DZmMbPx5ztsfa5hFLQpeHXHhZMaz1 Rztfl5m/v/mwByda3D79xe5B0XHxT+dou2N+a51co0LDfjuOlt/o0Wrj2A8vN9+2bJpXu70Vgx5n /+FZvsyJJhVexc85VrL5jzOjysw5srZGud1R1UYPOV+0dL0vIrwjLm+r+jSxXjVbzYL8yq0WrU+2 TZr3evOahLEZL7tnj58wMWv1402zvj8WvqjdxOKVJ8Vedj5jDZ7ue9lg/PbMe8kRi6uHPltXfZX7 mPgvRyTO+ybNM3PV4z1PAn5uW2RqwqHg8zWbl7y/JWp2vXYdShxNbP/xshWTDnRuuCCj3eQU8VPY rlEVtsUlNpgTezjok1opE1rKE/OPR2VqKZnsh52TrnbQ6PvV349/5Rz/3Omj3OlfUTec7tKhpq4Q ds6d4xcS16aPn+sc//U4727Hhz5ISp1fvv0nvmtisgoOfZf6Pz/fMgqxXezz+vUnFz7R8FnC3auN nYXIRh+brUAXTq4uTn9ieOnFdN/D/keHs6HdVj26sCd2bvvI6t9HJjx0elBxIV1XYZT5TuhwmhGj clZ+ElXp8dGtsekLu1ROD/xwbebbnOhZI1jMnYN/lriUtNdr4egnWrN9BycdftHh8C8LtnUe8jAh cmkkuz/7wNwzfps8FpT0nHXuQukVVcc8uLcobfm0KxFZDb4ZuDV88MnJq8q/vXrnbJLbl5O35V9n W0KfPB/90rtIdfFn1dkzmw6qMmxj+LRrds9feww4sm1ck0GJS7Zs3JIVevAx9x498q+T15peHZV/ /fry/GdXz3iuHXp2Rm7bDeELR1c73eBiqEd8HW3B+IHlP3vWPWHa6q5bIs71/qLThFK1/qr3TXaG sbDX52uDN37346GcCwEbdjhLTgzw9QzcGve0ybWeztwZVZIm7Rp648ninKPjmqYO91I5ZqTKMfFW juljO9YQubDQu3EkVJ75fxjVlHAiVI6pU7NmqLNmBCWcEGct14/O8Z/+X7HNExNHTV09pm27uL/F +b8Q/y9zzzbnZ6+bpy7pMGj+Z21Z+Z3bT/s3+OmDxuFP0r7MqHRrdhHW4bxfhlf9o/5btj1vOvXr 02/CS938+WXu3VN9+I7sU2c/jOneYum9ng9P3kjqViotb63fVP1I1cjsvh/UKP1Nj5T9OSUiMvrt Wbw158PJJfMmfe1bae3YSsN/OB0eMSF3baUzJV4G3Tn5a7GuHcs+/nrqpMyq+U9bB9/6/IXeaMyR I7NnZHoO4zeO5xtNwwrObWp0Oau5+5hn59qs6PZweKr/R+XHfBa2x6/Hmna8TcvB9sWdJn8jxy0a v6Jj7G/jz77a0XRnyPZOnnPOdGhdxPnn7z9OHt1zz8iuvpMc6+okZf9bNeYd1VSWB+A0miAgRVE6 Aob+EkoIESmRLk0YRMoKhhZaQghBESmhd6WqFCmOSlGRLoyAKAgDiLiLA0oijDAiVRCkChus6LBn 95zdM579673ffe/el5v7u9/97p1ASiayTiz/g69+aK17/Ar/J/YsAeEL27Pn6yxWP8Xk3y6IzD6R Gv3Trbj6tou3yckfhk+Ya3PWMyYyS9gHbgjvhwkAu8O2n/aHN18QhWkCGACdj8pXjVb2IJOJGkpK OJK3os/nMVTEEXyUiF74zVIlIongEoAj+ythrRiJp8goAgw//0IwGHYQ0ADUP8cAJFr+U4OBgYHb NehK2tIS+bsJ9YE+cGhEKe/O2fVdBF1KP7a0rk13RdJV5WZAuR+QnFkTsUIaWe9GvdIgXrAU46z3 q+qY7xuJH4MT/fumhlvOTM/aqNiFUSe4fyNBx3nMJmk7E88cNudwDnjvm8NCeyRnJ7ATXe70/tkG rARS1L+SXNRw956nNQZxYkTet3PWVFZoToRyJvpWW8zT27JTZV2czSOXQ8d6xiJJ1lQBX9n2vIyq fSL3CGnPT169Z+J1o2NKM/VlhVJpUCDa3RN0hpoL5abjMoykdekZEvdi2B/zFZ0Y9EeS1EQ22mVa JY+auxl2CAsXt0qj8RZm1yZbmL0VSYKz4s98JA3Dwvm1gy93kdWNzRn0yWXQJ+ojfbg92S+aN4Ok Snc91xO1DXIv/J5BP8Z11BjwUQMQgIoKahM9aEb4A1zHGu/j6k929iH+p64ziPJdvdWua+wn0P7I 8JBV80opX708soHH/Gh7xNQh5QEjRCq85rzLkKhFZH2LSW8o09JMQGPCw+t9N/FEt1MH3MZqamei 7nRPl7znucJ+XEJGqUd7wAYmSKn2cfExtn5Om6U3XY54GPYi9AgElb7QnMdqI+Jh0D3QTHFQOlsj BauysfcUwm2EBR+c7oNJmaIDySyOLQ790Sj5gA7OcRE0WzBlPdfbN2ho8lBKVp4f5wlZc4GTTsi8 JxFmchIOHnoJdKVIbouK5ep9Sd7TUtm8S53cv0VxzlMp/mptGUGFXU7Mk0zl0cq1S+n2kTqRtlHp vuWi8oZdhBzskOdYqHSy10feUMFwxj8iuR1xWP8/bIebme3TzoIfvKkwoC2gJIyZaWXdUSk1iU75 JWe8DKODbXsM7P1SgQ8C4xDZAbICBTB2IViQzrcm9CeN2gZQ6aa7EC3BFg27kgucWcCciUS9pBl/ 67tabEwKG3WWVlFCU+jztUU27PTEGoxg72rZtY7a25biggRWfIgXtFBCf8q7yidYok7/75Fvk7ga WeLV7k2EvCY66l1OfdL1iJbcPNwk2x082XET2RdzpxP3QK1XQLyJQsdcqhT0zxOP7a+q4rFOnM9p cTW+BJfOcYrnwjzkdT1l2NBzI0LDvPykLR14/Rot/DJu7hk6fJlXPNElDMcMy5y7BMEqndGPrd+A DLguG9OfQclplUy+HF25g3DnYMPZPTm7xNUhQjFlzK2ZyLpR7TYrzbvFcfQxN1TSvERmTld5oLWl xlPS4Yr97xiAKmEAKvWzHjGnK3zQI7Yfp0d/AsEmo9QZNqTKQBMS8YFRyh9DxGYIhFf+FXp0AJD6 GIr4YvFED1eS2GErPTE9KzMNlI46UkFNXV1HAa2PRiKkgP0f+yT0bZ8UrDY7JWblSqLgca7/Fm8Z 4TvEdAUsgwYyprLfD8b0rnKm8I6XoOA8lHVTi1JKlmyawVCxDR4ymh5iGvU81G8mAPS8Aeu9Sijz eyPXG5z6KH1PbkFr/fJiCM15WAEQyZFWoGj9oZ+ZfLM/DtXfNfO2x/7+msfQnEtK9th9nuWixsi1 pwmPmDTvgikWB6BLkbW7o5OcGh1l5A/2/Pz+gp2qsPnuZvV+EWctTbVKGz7+wAwM9wqoPO13R1Tp gQacvCFf+E8vvceL5TKSYjlDikA/B0qyXJAlQutkJc9dorcWSpg0HTnOHGhNwpYfcqGlRbLa1qy/ jjFiU6usXFIuDjlSeDoUeVyGM696YehgntakPmarTn0FAjwjtgmCmXiWXn9Wn2ulcz4kd6P3G1Pa lhj/jSmR/Yk45/+JKX1uibw9rL/xP+bm7WgFmi5b+/1JrNuvMi/t7nSDqCF7HFolj/M0XF/0+i1m PamzmiIqKPFucfjXqjs64H2oG4aoTOJKl/I1eGIdew2ZF15bGTAsy/Z7gvmLC1pZtSo84ePcNOHB epceMwvMkfj3e2lSN/syY8ZNHoy+WdbZ4wieOBZ7lhI0SliPEStLy0m81HRiXz4/IDlUGOJ8XlhG 5r7ROQ1sRNw0vS+CZi6vinmlowMuAXGwzz01Enykm3Sm/K1CkqPMcGNS6Hl+SpXTKt+BEgIPThdu qxGPSdAeqW3tSj0mpG/jldKZamrDBPp1CdDWM3uxN/buAvcb2r4XcJEqy7nAIemXDWzhPIMiGo/1 EB90CnYRAgYD4TE/cMv2zUby61FXfnj75ur0adjYoAiOredojO9+jdgRnMDWp/wManypCEMwUv0C /mEsvUJG4GBrEG9P1ihlIWePOOCxpQoHwg6wzVcMkwdZg/AgH5AryB8kBjJjXAMZ16MgAqPMGeTL uDcCkRl33oy3cAXSYZL/MlfJp4kEd5Iz0eO02HdsglHBIG0T3RaqkCjR/ZhQgJbkCXvRmmn7lLZa Dpm51TEEU5Ra91k2fqFj2uU6ntDbU78oyvcHxz5ebDx7KzBrV8VRuQwxkpFDpo2hHHNMZKwfuBMq hjWCZ89w7I+9nJj/Cu+oQKh4K8SiFfuzp8O6GvTCCNPTKlI0LeDcbAXNl6onyoVjsw5ZzkQz+44b V1Yo1BRiM+WyM9HjbfIjlml8Tlc79XOe6K6muj12X0Ea9407+dYaTNgODU8tZ9VArhldDLp+zf2B TB+fgaOZNPWm+Eg1lm/WuSBjZw8BLJRyLb7SxuIU16jRDGSK+sJrp3Zc8myjBqZKf57tQYaQQpJD bYL1jL9KARUiClAhgl/HiRlBhXAwilj/8oT8fpH8Zulm+ZSQ+Y6AwNZsZP969AtmfPPLEyYEF2NN BQA0UgWhrqqmirb7UzI+11vQr7xRbIeY/cPgdFFoQX2CVeR3hNpMkZCuhSx5lYM2BFxBk7UjE8b9 zbrsQL/ccvuobHp20UWh130KsITLqZQWJcq+tEZoDb99EBmv1lE7wY0SmEOaThpcfWIi7TXNJKqK m19zjq+qwv4BXtRaJL2DDq2Lvq4OKEw49GpgvD50cdZg7V56cU3AxGLfcGOMSOjs8b+FytofSd3o PKfRtxfQjOxdFH4Vra2s+Cp3r9SoC9MOd85nj6/AVCth9OJiTfxVj9PcLiQBb4ifLGv75I631VKR IPwNqAMNYr52JbTDdCgurshi4vbxTOTt6bruYL6O1PueL7ncBkvO0eS5oovJheI9T9lT54cHTd1P vatT3QCJ2qkagk/2/BMPO9LLDQplbmRzdHJlYW0NCmVuZG9iag0KMjEwIDAgb2JqDQo8PC9GaWx0 ZXIvRmxhdGVEZWNvZGUvTGVuZ3RoIDM0MT4+DQpzdHJlYW0NCnicfVI9b4MwFNz5FR7TIQIDCSAh SylJJYZ+qLRT1YHYj9RSMZYhA/++xi8lUVPFElj3fHecxflFuS2VHIj/YjpewUAaqYSBvjsaDmQP B6k8mhAh+XBC7s3bWnu+FVdjP0Bbqqbz8pz4r/awH8xIFhvR7eHO85+NACPVgSzei8ri6qj1N7Sg BhJ4jBEBjTV6rPVT3QLxnWxZCnsuh3FpNWfG26iBhA5TDMM7Ab2uOZhaHcDLA7sYyR/sYh4o8ef8 pNo3Z3pk6XaLGfmwexg4GFP2Ocl/ibOOf9XGydbIixjS3Pwf9xTdM2Sv2KVpdGVaIC1jE6KnKFtE mHMV3P4gXTkaTZAdspu3SNF0TS9N4yvTFC+b3iM7doHSnUNZiMPCDbMYhyhIQhxucIjyJL2Zie4w U7S5zDT9yalwc0340RjbENdKV42pFFLBXFzd6Uk1PT+eWdooDQplbmRzdHJlYW0NCmVuZG9iag0K MjExIDAgb2JqDQo8PC9GaWx0ZXIvRmxhdGVEZWNvZGUvTGVuZ3RoIDEwMDQ3Ni9MZW5ndGgxIDIx MTk2MD4+DQpzdHJlYW0NCnic7HwJeFTlufD3nTNrZjuzTzLJZCZnliQzmUky2clymMxkIQGSkGCG sEzIAAFRQYSiyKIGgUCrotgUvS69v6TX2nqwauE+rWJLsb1X/l/rUtvbKi5d3P7SRWtFJvf9zpwJ SYqIvf9z79/nyZe87/m+99vf792+cwIII4TMgCSoK7qovTUcPtqEaPcuhKxbY5Fo77I1uXkIHTqJ kOr9WKSz+X9X+nYjdIcbOjzQGo21MO/Y1yM6vxAh6eLWroWLtnyLykLoQR5RquWti/oixW8ejiPq WwxC11oWLgqV9zz9s+MI4Vdh1sTQVYMbzLG6IoRYGI86NbTlOueSxr7nEapZCuUFqzesueo1R98W hDzvI6TuXTO4aQMyIRbmN0F/Zs3661ePvfzdxxGqewTGKBheNZh8c/3cHTA+9EdVw0BQfjdLB+W7 oOwevuq6rfs2ZcVg7BqEnO9fueraq9sCkU8Q2tqFEL1j/TVDg1//p8NGhJbBGnJ2XDW4dYN+v/p1 6H8M+juvHrxqlTLv9XKEtkG92bXhmk3XTRxG9yJ0+59J/YZrV234Ub10LkLlHEKyXER4K/3wh689 /gqzQlf/IVIpEEnHfzPWQJ7PtgyP/CX//L1Z5xQJaKtEFEon6Cc/nKoFnmdB/Z1Z54SRpiS6hlA0 jWgJnBtJFGJQCK2Gmp+qe9NNJM9R30NSpJAeloahfG/6if+CVuMUpaMkCloqkdGU5AyiJjgkWZEZ e/4ipxM5YTuMrDZViwflh/GzToTvFwY9I+0jO0W0NIqeEpb6wzRIqyc+JmXJ3WiN8LwfJSRrUSIz KvXchTxJsh+hZZm85J10nbQD+thRrzQPRdBs+odJkjZUP5l/Fs6wCQ1Q96JGSRFyS06hOmoEtWfq qS+hOnk+ape8BPAVNADthb70UdROP4K6qfeRZ9rYFYiB8Yz/fbuZTbNpNs2mf5xENaCxyfxjaL3w /Db6zv/cimbTbJpNs+kfL9GDaPv/9Bpm02yaTbNpNs2m2TSbZtNsmk2zaTbNptk0m2bTbJpN/62J Ev8Cw4RokqMQkuH3BcofZv5tBpRp8S856M8ZNd2Txr+jqy5a/ZvP7PjWtCL5GxAZgAIphbJapDMC Jt/OzciCrJ+5jlsEfCvag/aifWgU7RfKX0G3odvRHegg5O9Ch9DdYuvD6J7P3tL/J+nzOP/FkgSd AhxATsgR3iqRBhWgElSH5qJm1ILa0XzUhXrRIFqLNqDr0PXoAfQtJzMxIfQmrZ2TrWNi6x5onUTr 0bVo62RrPPHJxEdwusfxv0z8cOoPzCb+TAzh2jdemZQ57+VxIy1h3JJVyRXLly0dWBLv7+vtmd/Z Ma+9rbUl2hyZyzU1NtTPqautqa6qrAiXl5WGgiUBf3FRoc/rcbMFLme+Iy/XnpNts1rMJqNBz+i0 GrUqS6mQy6QSmsIogG28rbk/to7Pbk7wajbKMk5eveDs/BCPDHYXq3eGQ/ESsRUv9fPI2MGbuvqP Iq4mzsv8M5ss4GkP80cXdJ5vd8Z4iQd+2XmDSb6wp9/FMq/YJ+vj0IfPae53uew85YHfdqiC33mD ziTPdAHdZU9T2nnU1U/g2MSbNUBENa444J5+3pEpxuMXW+RxhCZOzFjmAjzKHFVnN0d5ZDqK1G/y yEyana1BPKrnC/2wEAZywmgoxGPTH3ls5LF5Pix5+hSk25mai/AgllzHxpJrgaPJxAWenk1z1OUc dY729OvDkBUW3cH/uLv/qCqrmW1elQUEJBDQ0SwVUFSEAENsOIrVjVjIUOpY3VEKKTTAPgNZbozA Op7bn4AMGwW+QY3xQs2xiRMHplYh6JbJGdO59CJ4WTMvTy/CuZbnBnm033k0cGL0wDEGrUz41Uk2 Obi0n6cHocFRRHtiw718bkfXEiDBVACJYSc57qiAyOE5Y8POUSiTtgnAbJQc+jR6cnhVgogJTrBR qFM29+9xnbDzBnjGeL2f10AzzQ1v2+nRmG2tkxRHR/c4+QdguVNqXQSDENhg6aMxFmaDwWLrIuRI QpPHJkhje1I4HG7/oJPftXJdWvYGD2Tk3zXK8OqPXHA6cD7QU+gosjKZWEeWvG6QbDO2zjm6f5Ww 1QPC1kBenbF1UQKkI0g/6oPeS/pjw2zswoSwccjQnpl9XS4+2086jo7GyBIHk7D69JKh4sL6iU7Y /RjW08xzvcID9QpnADNyg9G4SBIbLCHdSE0iGo+70ucOTXm5Z480yDpHyYhyD2/yM66TUHeiJNDR 0x+L2oXd81Rzf8MHNvsHkO/omiRjG7QZDX1gT/OoYxHb0Z2WguEMSvSmFZiaPHloKrYXRj1ts59O 55f2t7AtidHRFtbZMpoYHTw2sWsl62TY0aNq9eiGWMIpqD8G+r/ut/MtB+I8kxjGdcIJkeGcRPZa ejp4Y/cAOaoW5/Bg2nA0sa4au0s/2abrs6pFnQPpBx0gOjfKvA9rU4N1sjtbiKk5BhbCzjM1RGVh QX39oBNDgvwKCHRlEQxuJ1pDxz2xtYtEZoFkisJDbGC3SIVBXC6iT/uPcWglFPhd3f3pshOttD+G uJAfzjFBak5kasx9pGZXpmaye4KFc7N1LPoc+Z4q26N61uCsDQn8F0xvkj/RC3v8uIZX1IhHb2zu p+2UmKPsNMll+cGU1fNWv9CR8AQs5ijDOp9necbPS5v7T9jr405GD6YOQ5s2P9EgsKjPsz/BxI4i E8Pjeh5bCB2BXRXMO22tgcpJQXLGRhOipE3dlugMksMX3xu0YVjYnj3dXm9gyQ6fE8ybaLU9LUSv 7K50i3lxXktsM699X0CwXntzvxMsEWhut5BxxpzD5LB5ZyIqmIS4fSr52MSZRJSYQFgyaWIXRRxw mrXTZa0kcLmCvgsE/aYD8eE6GIUrhh04K2FaQVt6+0Uu1dhFjSJztZOtTK+f5GKmDRw+KJ6LL835 iQ0ENcf2QfxiLO/onVaaMplQVzNpGXr7+RZ/ZvB0udVvn1psm1HdnqkG87HdfgNxIxSKHGXx3u6j HN67aEn/cQYh597e/scoTDUnIvGjbqjrP+6EIEigUoRKiKTgJAXUgWG0xyiF0N5+nENol1ArEQhC eegYRgJNkaFhNHSMStOYDI0CmiRN4wRaOqqI2YaBBf0sHHqS57r6b4wPjybihNnIkhZAkGy2EfEU 23gUUzI1n8WuivAqNkLoTYTelKbLCF3ORkD8QTmcRNVHEyyoPxjgfmTHcSLCRFwoj/PYxARY0NNg eV28zLMUAAys0h93ghTPg3atBBJAbuV3DQ2SdRAxpYktbx+K84rJAaFJO6+EEZTiCNCiRehDvAB0 GgJhHWSFLJBBOXbF+bifTNq/lgzgdEI81MbW8TJvekypl0wUio8a2HLBncg8fJZnD3koYW3EEAoU OxRhsniaSXI1rHyIhaqhhBO4LUFDi0AYJV7ym2VPU1aBV5d4VwmQZRcrUVqDVJosXhkkvkou5FVB GBB+5fF4evFCaY/YAOZmeBWsyDuFlWIH4A5UtZO1wO8eWCpp+gwZpvsY6mG3gg6SRQsjyaGa13ja B8HgpPurgMLWZDrDWAqBRMY4mabKyc7VQkDbe2xinL3eNSWVBFjwzv1EMJEdYkgOxUdnEvgBMJyK mVSNQB4dVWgu3iHNL4Vm8kmIzthakFXkBJ8CbJR52wf31xgqSo4jJ3Y8rrThec5jOC+Tyc1krJmM JZMxZDL6TEaXyWgymaxMRpnJKDIZWSYjzWQk3DtC7pyAPxHwuwJ+W8BvCfgNAb8m4FcF/KKATwv4 OQH/RMA/FvApAZ8U8A8EfELA3xfwUQE/KuADAt4v4FEB7xPwrQLeLeARAd8i4JsFfJOAdwl4p4B3 CHi7gLsF3CXgdgG3ERyaG8Je1ASwEGAFwDUAOwFuA7gf4FGApwH+D4AK5WM3CgE0ASwEWAFwDcBO gNsA7gd4FOBpABUcJMttxa+fsVhzX3oZ0LYbLfZtN2a/8FPIb/kSoKs2AFp/DaArr7bYr7x657U5 1202mXPXrAO0ei2gVcMm+6rh3RtzsjdZbmjOdl0PIH/W+iz1299h/3XfwdansO+VxFMbntr1lORr hyk/dxivuBPfcZDyQwzAMe/Z82qVQ7ahZ4do55BGV0uIgdZ8Ty3z8KodtfeNsfm2r3qLa786hv1t Y/juQ5SfOdTE1f78EFbxdn6Ep+dqsBxLQZz9WCY+JeJTyrWPIv9+gH0Ao7tl/pt2Yv/2HVL/jpGC /L27sX8PwMhuqf8WAHu12VZlNleaDRVmXdisLjcry8yyUjMdMqOg+Rh2cruaG11en7bQp9MV48KP J/wf/1X30V+0f/5QW/pR6cfU2Y9xsV8b8OsKWK2b1Tnytc58nY7Rq5VZKrVMrlDTEqkaYUoto5P5 Kl2HjlKhOShKr1ZeR+9RfhMdUf6HTqlCKlqlm4PmKOP0gHILfZ3uHnSP8mu648pfIO1x7MIFnEFn x3kamzxHY2asGoPEpMmfq8Uu8oIAMAMQAmgCuB/gaezivLJAfXF9Yb233l1fUO+sd9Tb62315npD va5eWS+rp+tRfVe4F/OGDtTRG+GNGJ6LInzY33GMdvbw5f4OXtk10H8U46/EgcpTe8Et9vKSveAJ e+HCtWSg/xjOJtW7wapgjPiOxO4vx/3+PD5JwrBdeXG+nGRuz4tDwFzezdvZiH9m2nSd+Ng8jcr/ OcZ/HFs7yH8MN7aP4Dr0cSzBf8RGN6Vri2N8IDbIFwLRy0anDYhnjI9ggvQc5LFpE0y1ieR4G98E +525nqNKsvGungi5aXTwSbgn2LsGEnwOG4GgH0pVXQMQP0Y2bdp0FEGUcpQiSAZoYKB/bh52oCTO A8gFsAJYAAwAegAdgAYgC0AJoACQAUgBJNz85LnkJ8l3k28n30q+kXwt+WryxeTp5HPJnyR/nDyV PJn8QfJE8vvJo8lHkweS+5OjyX3JW5O7kyPJW5I3J29K7kruTO5Ibk92J7uS7cm25N8w+nJS/O/q JR1FWoSkfYhBfgEjSbn4TpK8lDqTzk+cnfgngtN5hFI96fz0JNuOGLph4iwFvSYegBb6y3nxpRBB +Edy29Fr6McC+S60Cw3DcwztRw0ogTZecpAPL2em6Qk34ipcAlb1n9E+XAqKakMHRHo5LkTfnmy4 A21Gz6P70L3oDrQJDYPW/hGdQTdDzUp09WQrsr6I8G/iliDF5BxaHER/RojqucgCXkLPQQsD1D+P lqOtaAG6G+b6JXoT6hLoXZjjwloDk3gU1vEAPL8M8KRQuRLKtwo0HiVhdoQeRteiedMnkz2FFNR1 cD43wbmcQa8AaTPqQ42TM9ThYpD/bwDf34aV3U1J0C/xJ+gEzHEWa4HyJOz4DH4NLaFlsMq70Vm0 Bdb9y9SrqV9NnJW0gykfl3cgcoxPAbpV2osKUQCVogpUyJnRiC77Vpv9kJn5aoF6TGq2SHMLdKip qYn5DfM28zYOfRB6u6wUV1Y0UtWNdGWFly3QUnK2sqoqXO6gzCYoaGmz2WpmK7HepSdAVcssxW6r 166b2+gsdWcrE/X7mluGGnN17vqA02uWG27Hn56X0YOf1uDfWiye4kpfdihcy3b0mNzljpsdwbxw S5G3saGlxBXwFebKrn7wwdTbksPnVkv+8skjsHqK/FtJaYF0KXIgFxqHqL65r58LOxHcDfOx1CVl dC6X3WJhpUqXUpeP6fyDcNXAdhpjpY6Wm210llWpzDoSVSJbyK9HYb01bGsy1IZWLF+W84Ffb0C1 pdgWKtfXwqr04TCz58QJAmV2Lv/vHjCOXXKZzGyyml2VwEoQagdF8lVVwFOfx0XTvlSfS2sYTvV5 aoI5+EGswvMsjlL/+VcryrVMKoGHH8DjKwo7ilfKIxFJoLNVcsW5BzqafMpIRBYszu+s+xlF/oEq WgNnPle6CnjzvTRnhPeqXKXW3AbS3kUlKFpJU7m5Ulp6kMuV6Bmo0Ot0WEvrTCZwmAdNRgrrOIZx KrbbgA1vwD5yTr90GjV94Ec25iTsqdbflDOlUFZqT88RuOw5OJMR2aYNMmPEONazXpA1Ss8YwuVV VdVhvUzGFripygqDO1xukczdaxvuve/rd93WvrTatO/qJ1c+n/rr9jux49lV/0talXpt45WpF1Kv pN5LvVW2Mp56Icd2Nw797ud47rcthEcJ0IN5YFODWJ3hkWbiBNepVLdpFAwHD4YxK8y0+SCnCLoU B0tLEYVhR8GgnJYfDHLBkiPRIO1wuSy05aCLcxUcibo0jE5nobCDy88vVVh2+AjrygXevXIaHqfL UciPcmxMeptNU/KwZXiG0gw4FfIzp9IsJUuq/68siUjjF5iS8DxIsaxeZHim0CipDtMgtXSlviJI +Sol3D5XkJv/i5FAuUu3caO2IBQa+Tlb6mXtDsM+46dFHr9ZJjX7vdK+1A9WNPtSzuy6htS6uoac 8+8qLd5AW1PqzkiWtaiplF4e4gqzsyLiifjgRCDyFPW5B7EM62R5VsI6dN58b8j7tFeipL1ev8NP Ow5yEBApkK3LlrBtsAHdZjbn0XkHzZzZdCRqpmVKhfJIVMF6PR5k46zWEgfaob1wJJkDAV21zeCL njQQ+QJF5tQyOAwu+v9iNaJ1uJwZ4x6TgxZsRYbrroscDoVljLWIPf+bDMvpZ4WjeWZXKOxSbdyo LigP7jpXWV1g1ksjEaWtiCull6V5nj4aOi/amOpsiuWKWkFdBWeQi3rFMzBbTdM3sEOrdeTpDbgW ODnJPsCERbqZjW3TGlxkR2bwHBSWqK2Feef/lNkCpSnymRTn2HpvjhEsXVpQVpQ2FtmyIhFVtruu hqx1GfjNJKy1Bn1TXGtFlZ1Tmtrs9opCFK52mOmKivCRaAWtVHvpIlVhYdGRaKE9p6qqoNos3anX 11XmF9wUFCSCiMQb4bCB2Hp0wX5DxhrWh+F0YCPCDtnLmGKqB5g5QhxrKbPeZLFMsqGqmpXJ5JjF Xh9rmV7l9QKHMHbJkpVendpTe34iUGBUymiz2u5J/ZlP/SbbaMjSFlekbvX4LVKNtwb/AZtxAL8s NerYOR2f3t/Q6tFFImpD3pwofrf7l8HC+UPng7Q/Fn3ojVTFvDqvBphrK2wspQc7a9xM5NN/pyvJ p3miifcBZx2oGN0m8taX66SdYMlzTXJTMV180AT2+0jUREsVcsWRqNy2w+0O5KMdmoyCvTFDtYgH FKwN4aLj0oPNVJIpfYkIUdNFqNxiNhHH4KskegGuFHyGnMJZVn/JBa2gYuc/3XLmG4ONi5Nbamuv Xtzi/SRS7bIoItPN0BPf231ylWRj7Y1rh7dVUCIvpAuAF2UQ5/5I5EW1PScQDgfoMMQAAYgBAgEt 1pbT5Qe1nFZzJKqlywooN8bUkSi255TU7rC42aZwyQ65wBvm5fKXwKHWimIWnrnNCwFDLWFV8eXP lZG7Sw8Zd01nnpWEcCCBZhA8qyB8Xp9PMDNEFGli/Ckh5qOumqKhrVseaqxo88U2r5w36GsqXlSb 2lnXvoAtr6yu0xZWrR/qGm6w7tqxeDp3XQW5fRs7Vh5YVpTlvLJn78BAVqTrvm92crbUUx31bq3k 3vMv+ecPN+7dC9rdO3GWfhFimDL08zTXH1d5PCVW8kKjHkIJK8ruyk5kQ4yRbTIRO8uZJKUkxijV lUGMUVZSQtP0wRJjts1W5NrFMKVFu+TyMOJIVCfYfhLTvAHh3SWCGmIN4AguTBy47Im5kksGN+mR 40aLJSOyviAE1iSgtlgFu15AAkVL5nDYAq9P/6vszRvnLK8Nrh5YsCNedsNvx+JfH95nnNPfXLuk omTdqm1fbr72F7et/tUg7v7S5sJ4c+NAT9DXu2prx7ZH4kZb6rWFywKFC2vq+roruG13JLY9MWi1 4ApiR+FWJPkPkPACNCrKt9eAQMhorY7LketIbMHpaBdG+EgUGfR2Dae175DJ3KzoBF7JOc28cjqj 7kTQUBiE7zTstJxIcM5njzap6DN7xdMymr5o6InfkxKBJN4Dbysus8m667lQgWqf5Gv7jBa7oyBc 1Ca4wYjcWjy3lP51bv2qErwi9WCUK3EYlJ/aRf8H+lwPsTFDn4X7TxidFfc7X1VEF93HcaouFbVB hVUqic6cb95pprNos93O0MwYZ2cKveNg2nGYDqEQE6JMEkmIDt0tsSCsKpQ4R8LhSoWJMwd2K4iW v5Rzmrj0N6xhQbyIhwdvAKHYVKGABss2ihax4e9fAgdrSA/7edPEPT5BlryVFW5P2lCC4rPAapA7 4nsE70wLoicIJvWQrueeKxbvnAt3FW9xJBhsrtJ8f+kNX1oeuv6ONpnGlFeYOmC751C0PthTeou0 q61pQ/ud/2JZsWxVkTO+8MmiQJ6au31n6oZIG2vWZEXwq5L1w41zy3qCxK7COYxKx5AThdB3xHOo dOSNRx3IiU1u2j3GmRiZglY8LJNJx6MymTIrRPs1ftp/iNNYFEorjUZCobLCWxjxgiLwWpAjwgLC A+bXk4xoahK4XHTZEyDbpceKY8EPSdnqNEszylspmFVPGFd4RR0WGCnJlRoKQ6mz1yt1bfe3P/nE 1T//WqCvTmb0lmPz9tTrPX2N8ZLFA/6+OuzubCm2ZzUrb8ftCz859/A7W1XMwJXxUE5Ws/Y8umFL /BubfvQDf7wOODgAFvKvIMnZwMOnRQ7WOY20c4zbYMQ6Y75xoXGFUWKhjcYsOgtM1RiXxaBsrKKz aRquCIc42pKNDCM5OQVO44gs47j/cKocTZGeppwpXmSZKK2hLzjNNHm8yIhxz1QmWqzkxyUYx2pa kFI5/frqH9/8znvXv3bnwL6VTq/RhM/finfe3HlD6/clbV3zB5RPrl8yce7r711f3FHZ1L1oyxPf rG3DHV+7+947wcI1IkR7pfciDzoi8qncSK5TRt0uHaxwjNNhh3w8KnW0cnYdC83Go568vHwjZ8i3 58vU+SMSic8rWrvwKX2YeUVwIRdMXnlGOIgFEzjk+twJpti+md3j1eBy9UQvqwlDrGY2rapmc9jM ihFib8jD3BDy2LQ0897PFjfv1Re5/EH9M88wRRUpbURb0NBJDcfk+ryg+/Hj2ueqK2rXrujcfn6s o9GtjpC/7nOnOEkeSA8oDVqIXSJf4pxzgS9LEVJU09VjHK1QhBiMysuhfStXrgs10A1jXIhhFtC6 BfkLQgtoK72A0xraFnCMrYVuGbPltpukzXlqlstjizFVThcj6e66uu6KkWJRS/9wymCtZU6ezGFO w0/mlQK4ZH/6PiqqmCgiQthcm4ldILAhrJ37X1sjZ8vNTPMFpo1jn9xCAk2IMwXPHA5n4s4ghEdV 1V5BeoVHI0UsgQsLui+ETrJJmypYXbZAkvdNSa7nxdNDTeXZ9dUfjx+5/s17Nh67ubVtbrHXN7di QVfz5vuXhhd48Nrzy1o7Y+2t7fNa3W7P9j07brG1cI+000uMqtzB6LcfN5RUOJz6m/ddebjbVLm0 tTZR4FhQG+ppLgzclli2u9eXJUs9vWPbtZu33bTp04dzI/62WG9nQamT+P068Pt7wALPmfT7hT69 li4uKh6PMkXmOQ47DT+gvkxN9Xi0BtVhxYjZ3DDHOVJ6IcgHY5gxlSTsDAsmk5xS3iXHQraL94vj tAXI+KJKoggVYjwENIlAkxAaTcysHj8/cFvH1VurabXZa0/ZQ6xGk19W6F1UTctUhoLclMVRYNRK 6CyTtxgsLb20u7l77PrUnYH5wTwTXC1VxfNWYGnymgZHqDuYurGmwZVjMQBdbsz2xThavbi72mVS RLTnf0TuAu3kf4qRXgOSZkePizyrpSmaHuJ01EKKmqCwjnqaeh0yEiWiGIpiaEr/sE6nHY/qdNkS u2Q8ascGyjCiUOTligblJHPywlUJ/AyxisuXbbxWNLWlX3T8KZenmaPFMXCPFlkqsC/NUfxC6v+u K/NolNn+AmzcLrLOJr3mww8/eVFT3LYCv1BW7zbKo4rztRkWiRJElYIEWVFX5m2B2TQeNSMrlshl YPBkaESjybbNeFuQ9sW6mU1tU6rBvYr34AtnjZ9Te8KZA1WahQPFrhVtfs3fnhdZHZyW7AxYuDj6 qbg6TuFWgeM/xKkYhKM0J+Fo7hAnYeIPX3HF4vHoFTprTllFu7QznN3R0Tke7dCPOBSBkRpHTY1j II5iI12ZdwW1oRADNzlxR+JNn7B7MmgQRVtwll9wVpERlxw1jq2iqxRfwv+NvmglhEZdoElEHRL5 ekEI8L+pBw52zlsZNa861N21Npqf1iVHSYFGXRDy5gRKnEa5lGE9KXeQVUvVZrsn19NdrXKXpFyl Ho3U6CvFhh10P93X4m2fs7yzuH9k6QwNUy/ZyOUyroLiijmpf422BfLIe5zi9gRWRwZqinO0wZ5Q avvyDr8qEhHE7Z55rX57VlSRPkXJITjFWnRIPEW/laqlc7JzxqM42+x72ONxgzfVFeq1JXDJOMSV MOERmWyOo9BnHHGQAxPevhBTNWlt0ky9YKucnzfiVFM1vbNwm740f+VW4hAyZyQ5lLIH3RqZxprr zvX21Kg9oVTeBTbq1I3L19T2rG/OE04hovK3r8Cq1oE6X7Y6tCiU2rli3t9w6Xa6uskTWnLz4tTB NNdROjqUhIFvOuRAV4icsyEjbRzjkEUJxniMUzLqW2w2J3OLJBNCowt+kPCFmdl+qqOEvUsLJt0d cYWCwxNfFshk1Jw7X946b+S7V/7xoxveTD2+IlHZ6jesWBbt8TJr3nr01pO7GiY++vZ711K6l16s Wn1b/GcvL36ErLs+1SNZA+tm4eb/ROa9HjERtHyck9nNDxuNBtowzhl1pdaSnBK65BCXw7h8tG+M c1nybikuDpstbrgbqMierOUzdpU+wnQs+uspOlp4uTNMCxUuOlhcOk0E6LQICNoqvqfSTwkMZGb8 nBCyQThHq0w+LzZv06kXH1r42GNrnx9bM9QXXzp4xdKSvqrvCJGbENjRV7bWF9tNiqjiDnpR+7lP vvXO5hzcuG3zM9959kSwr1K0fTTRGi86IfKwRo9VSMEoKCWtkHCUyqAqUNF6iURFq4gx8j7sdrPj UbfOkm3LHo/aFJxcXuiF20He5PvRnNPT/FTmxile2sXgLPjFppnurC42pGjprOlvQVr6ohbs3zXt h5c0ND+hrw5aKkuMMm1xeco4xTZ104s7Nan36xrtZeGKitQzKzr9ypmmBrjWDTeqJcC1EHox802I nfjdd5VMWxbLGtljE7/jytIF2mrkjLl07piRQSG46oQCXICm6bGAxWa1+vJ363RB326ZrAxxwYu/ cBK3mMmSF0J+PUHCZ5+Zs7ouPSsXsEy5QHzGsOLbphkvm8zpl02T75q0FHmR+jPb8BUd89nuldWD bcXDz9zYfuCaEWt1JBhZkNu2ZvmWxvr1Xx146N+wdmAgOreortJvq2tfUr1kpEVteodrsddXeavC fl/fNfO6N3d6Qr8HznqAs5TkFygX3SXKY8CoHI/KjTodVtM6YyvH6HI5NdOWm2uj4YdcGg0GZGJM WoUpfTc9FYaL10m4dTVNfrKCXFpOxCvX5404eQ2d0Tdz/UxfucJml9lFpEz4zEJT/bd3HbpzewNc raW/x3mpt8zlntxAmX1rR8OD/0yFYlmFzeu7P9meati4PpyVYyNyxIDPctJnID7KvNmoQ7q8EonN 46uopt2VooORKix0ttwmKEIJkhXl6bLcOlRtLMkrs5VVZ8lk9UVuI/n+Gj5J9A8wOLLaqTD9UwXJ 6OF6Jbi0z5twxkeKC33j2Ch+lhZExSd8srakv1NXV9NBCflqI5Cs1ekv16Qsk1N3vesKl+Wlshtl asPGtQV6ty+1039F4wvvWZwFdqsKv91kMK1ZbTMWsXh7SWcb5U49HmooUEDwVqI2m3O+flOR12Yr kEQiypbWD3Cns8hjVmLQUr/ek3vnTkeRJZelIGxougI4bEx1SGLA4RL0jMjhepunkDZ7DfaCgBTu D+NRi86BGJ0chEEONghrVHkqKm2IJHawbmakY2iHw1xQGLKbCY+ZU+WgKVbhco+aTguGaFn6jUUo HBY/5KTjhZLLn4uT2InUXWK4uDStc2FR4Fic/jAm/KWA0TjJYi0tpxbM3bR7qGPuBo2P9TbMr6lN nct1FTnwn0KBnNvvN5lKA3h3Hpsf8Jbc8VCP8dchtnjTtdTvF87JlwFT3e7S+akOvLO0nS2ulkea lTnFi3rJm4AxENmHgJc0kiMFcj9G8fSxiROcVqtvoxU6OS/DlPRRWeiNcDkKfdD0iv+DstLMn3kY 8UOpP2FN6k930w+lfoqD5/cRTD0GJ7QeH6daqP0wKvMEhRGS4pDwyuQ09HZVuqj/ZO9c4KOqzkW/ djKPzCMBBENQilNsMVoEipRGTMFXUSnaFEHrO5PMJBmYzAwzk5AgxoHEEBBBEDECIj5q1doeaqu2 XE47h+aqpTRtESxFpBGVWKUhIA2olH3+a+09kwmmvZxzz/n9zu9e5uO/9trr+a3vW4+9Axmmnhyl 7dF+vkOe+T8hsFpnKQ3OudydnZ1Fr8Karbp9deCrYuzfX51Cvezzs9U/LrHe9uy3tYtOfmyddSKQ /chnf5Kdynbuyd6U1cP7iGyn4HInczKZzeuFyB779pv49Jzfyt/Lk61YZUvN3155YVb9DasKra0n h2mdmgyMf27jM+WIOKI1aU1Z12cPUOI3xHKWklZLq3WmzWFL/L8p9quVvJ8z32FxWp0bXKOU1Li/ 6z6aW5L7ce7HecsHXDbgRUMGlg9ynJEz8j9IJiiZhoTOyBn5Hyorz8gZOSNn5IyckTNyRs7IGTkj Z+SMnJEzckbOyBk5I/+/iPHr3kJkzydclS2EXQSFRdj0XYT5+l8Ih+q3ETbrBwgXq3ClClfpPYRr 9J2E6/SnhEU7oO8WluyJ+pXCRgv7CfP1jwmb9SOEi1W4UoXryM0RFv0woU0/SNhMazmUkeFKFa5R 4TradFByBqFNxRv1Zwib9fWEi1XYQgsOsUTfTLhClXlQhStV7ioVX63Ch/WXCNequNTBob2rtxEe 0DeJwfRyFaENDQfTSzths/5bwsUqXKJ3EK5U8YexzGBV62zK75Df1ooOZ2OrFwib9bcIF6twpQof VrlraOFs+m0XZxt1sdWvRT79viO/7VXvJGwUAwibVbhYhStVKO0wlJLDCW36q4T5eGEoepYSNuvT CRersIVxDUXbOOEKbDIUa8hwpcpdpf+ScLVKeViVWaviUquhWEOGB/Qx6LGOko1o2IY26/RtaCPt tpj422KxSm/RPhDPi5bsiYRL0OSQ/C5arLdELCdcqlpYqkrer1pYrsIVKn2FSn9QxR9U8ZW0v49w HTNqpUpZpVJWqZRVKmU1vbxN2MwYVzNeGS6hr9X020O4XIUrSX+Yut2E65hjayj/HuFiFS5RKSuJ r6U1GTbrvyFcrMIleGEtuTIuvbZWeWodJXcSNmP5dZSU4RI0WUe/nYTLVbhSpT+Ml9dRa7/2Ljrv 1lgr+u8J8/U2wqH6GMK1ehtWs5z8QK2/sVmTzC9eyM1K/7+QIk8E1Z3xzbi+bIsZ10RedpUZzxI5 zlSZbDHJGTXjFlHgbDHjVuIvmHEb8TYzbhefOvea8RxxkWuGGXeIqa43zbjT7kz35RI3uYebcbco dKf6SumcndY59V23491rzbgm7O7tZjxLWAb6Ut+kLL4w8Dtm3CLcA28341biITNuIz7fjNvFPQOb zXiOOHvgv5lxhzh/ULYZd2bfl+7LJb4yaJQZd4shg1J95WrTB/nNeJ6YeNaP5bdEWxymnY24YWcj btjZiBt2NuKGnY24YWcjbtjZiBt2NuKGnY24YWcjbtjZiBt2NuKGnY14rjkbZNyw8y0iLGqER1QL r6jnWiNiws81LqpEgLhHVFAixL2HEvI+Qn6U8gHS4sR9pJWpurKOrPtNMUtMF1eYdaMZORHuwtSo EeWqxQAte8Q81Vc5Yf/9GveybDknSw31jV7jlPAQk/kRcowReCnnM/sKmC2Um235VTiGlFPHLfOD KlZIrQu5+skrS/fUn1ahz7V8+jbqbd2nWqokLcp9jBJRZY04oWy7/7EbvX9er8syLCBHYowlrvqL KG94VfvGWH2kzFMjD6tvpu5/pIadvX1s6ld+DZuhMSojXsNdRIUepW2tGo0/3Y4sGaTEP/dQlbJc REwSY5F5SsYoi5arORSDClVS1qymjPwGbjnCSjXGCC3Uk5oaRYy41KaCvBr6lzW9at7Uiefof7wY h1xK7PrP9eERV6mRpuyX8oycR1fQVpDrDNIqldYxdedX6yjK6KW/xtCCV3lcjtirrGDMFDkH/MqX PlVHthIyfVyRtm9IXExeuZohRmkZ82bMnZTPDRtLf4bFHGKVKuYzV5lRN9OLPlVXjjGm1oIxGqnH fKWPHON1Kj+lca0aV72aw7Vmi9KOXvQ7VRtjvRt2653Pss2rlR0qVYpX9ZmqY7QfV14wcqrUd6xH iQeUbWIZpQ0rB7CVkRpVMy2q5pjhqVoVr1dl40ofqePo9L4TVDWqlI5y1MZ88Zp26K/1TEul9Aik Z2+vF4w1Z9jNsGevDnPMXSCU9mFM6e3NWEtxVTdk1kr1FDbXllGuWukYVKM0LDszvYJTfi5X31Bv jNPIqVazW7YSUqvXWKFeZmOqVEj07lUB0x6yVCw9k6Lpc8Jvzrh5KrVcjdev1nSVsplX7WYyr68V a+hPngWZO1pMreNgxn5RpuLejDEHlHXKzN0ytef6Va1qcweJKUtVKG2lZ32soIDyW2XaUjenV8Sp q9OwknEWZq7EcrWzZO7MqbWTWi+y11rTf3JP8ajZb8yO0Rn26p0xUTT7vKU+v6Ziao7KvcuXtkpM ecXYd4w5HlUa1yh/Zmreay3jlDH2wN4Z4z9lBzJsEBIXqDqzlS3iou88P7WHGlXbWKEx83QpJ7XX J5MyepN6VCo9vKr+POVZYyz97Y9+duq+Pc9TM7PKPJuMdipNu/hVK8YMqDZXVeauIe3qV2vDKF+v /B+mlb42ucbcc+dk1L6K0sYZaqyJ09vNa0zNjXkUVCswtQ4i5lkRUHXCqgVDd6/pi9RcCWWcP8Ye FVcrtzpdQ9opYu6hsfQ+Z5zgAeWL3h0qZSfjRAooH4fN5w+jdan9vD47kFetptR6rTZnUiB9Qhn/ G4bHPI9PnVdj+jlfJ/WzAq9UvvCpPONsnihuMveQlIW+RmuXkt637sXpuv2var85awxPeNMz0Ri9 31xBHrVPe5Xu1WrMc0Tqecf7D3Ol/U//+eHUfXYWd4H0qXyjsni8z3k3tp8nrnK1K4TM50Zjb7te tR/O8MF15t536gk9U+2mYRUzyhr75Ry13/zXPIPJPa33Oaz/Vnvzzdae84wfN+5Sz/WB8mg4Fq6I e64KRyPhqDceCIfGeK4IBj0zApVV8Zhnhj/mj9b6fWOu8laXRQNeT5U35inz+0Menz8WqAz5fZ6K cNQTDl0cK4/K5Kjf6wuEKj3ekM8TD3uC4fAcT2U47PPMqyI3Eg2E4tTxxj2xai/dxALz/bExnuvi quFaf7Te46+lYCziLU81E4mG0U2qRsmrA97KcMgbVDmUjwfKuanyBqLBQMgfU8moHKggGvWjTpBB 1fqD9Z5YPBoOVY5GkUDQ76kKRwPzw6E4lTOKG0rJNqSexhD81RF0Q0/Vwhy/h3RUi3kwV5U/6olX edE3LiuFa+Lc+qtj/mCtHNbMqkBMjbk8EKFPbqrDsbgnFEZrv7dMJoVkBU8APQLlMWkktJApwfA8 f7TcG/N7yqu8UW953B81Vawp89X4pYJ0Wk8TqFjmlxalWiBKnB6wpT/or/aHcGG4wjMvHPVdHKj2 VkqlbpaOSLkTlWpiphPLvRFlZOUd6RdPGAMzUzyRMOYYrfRSholenFYq7alYVbgm6JOqxIJy7mDx qN9XU242rtSK+mM1wbgyjN+cQGgQuiDumV1DtmHzVIWamHRozOMLl9eokUxS1aL+ypqgN+qZ55e9 9M5Hf51ZeV4gXuXxeihTiS7+uDRAtVemyalRHvCHykmvry4LB01NrmHmzlHZV9VHA0E80c80r6Fx bBQMx6QPIqyKQAxrydbxv7JKSK0fZlTc762WGf46ysVjcs6FPd5AtV9NKKkTCykQizMH5ewN+ecZ E8gbVX6txkgBuaACEbxaH0nZakx6vU5KO/DKcNA3Sa7miTcxQ6RCXxtz6UQz92KZm+Fqf0DNWK80 It0z11Ao6vX5q73ROZ6wzMm4reh/f0jN2VmhgFzKN8a9cWPdjZUbgeqgPFwTikcDzLbrw0x2OYLr mH2pBT0zEA17ZpLKvJwTq4rHI5PGjp03b96Y6lR/Y8rD1WOpF66MeiNV9WPL4xWs1cyi6l4WuyVc g3vr5TRGLQYpc+QCwPTVgbhUsaxeKfzNWdOvUFNL3rCpMDnlnJMbQnlVRl2urNhgjc9wly8QiwTp wNiKcDTDkxM1PsaT6jscYrYXBi5kryiTlXqbCqUK96uRKq62S1YGBis31l+6d2Vps63LlAKFAXqJ syXhDKZqPatjXigY9mZ2is5ec6eNetI+YW+KsD35/LXsPbJMlT8YOWVAp+MKZfixPn+Fl1k6xhuL 1KV+tshHf0SsF/195P/g5hBO4RJ2XRcDRJb5k0OhFQr57cEi/TPJ/j+W7Ilut0YZbcvpls/NleWz Sk63/IABqvx7p1t+4EBZPrvudMsPGiTLW9ynW37wYMpb1P9jlyMsqrz8CfN55v9Nl0vqOdj0AuEW E8RAcYUYzDPc2Zzv+Zz/Q8U9olEsFc3iYbFYPCVaxI/EErGFlG3ifrFbLBcHxApxVDyoWcVKbaBY pZ0rVmsXioe1CWKNNkWs1aaLddrN2ruaXzugRbQPtNrsiVojat/fVydtRYZOeaQOR6eL0KkInaai 0x3oNAed6uXff6DTw+rbjxejT4v4OTq9hk670OlddDqMTjo6DUSnc9FpFDpNQKcp6DQNnW5GpzJ0 iqDT3ei0EJ3oX3ukr07ZozJ0GkZqITp9HZ2motMsdAqh0z3otAadvodOP0WnJDr9Dp3eQqcP0ekT cb92lliufVGs0Mah01XodBM6laHTXHS6B52WoNMj6PQUOr2ITv+KTm3o9AY67e2rkzXrP6nT79Fp LzodRKfP0Ckfnb6MTl9Dp2vR6TZ0qkSnWnRahE7L0Wk9Oj2LTq+g01Z0+jU67Uand/rqZHs3Q6dz Sf0KOl2GTt9Cp9vQqVb+XRk6PYFOP0an7dz9CZ16RIuWLZZoQ8RSdLlfuxKdZqBTOTrVodMD6LQW nV5BpzZ0+gM6yb9z+av2bpZTO5CVr32Q9YXsiVkXs94m9tXJMSxDp/NInYxOd6DTAnRajk4/RKft 6PQROv1dNGrDRbN2iVhM/y1aKTpF0WklOm1Cp63otBOdjoqVWS6xKmukWJ11hXg469tiTdYdYm1W tViX1YROT6HTJnR6BZ1+jU5vyP0pJ4c/BQWjR09tmHooxyZy7MW+JB9fsbo54SutKy31nci4Ke3O sYgcS3ep+nTnOESO892EfAS/TclVojORY5fFKyoqFsgSsgt1E6w4lmMVOba615PddQWtRo7+aIH8 FNtswmaLtBbU7V7gsGkOe1EBUT4LbFaZsft48vWIwyocliLaVF07ZI0Fu3dHEscXNB132IXD3lFa Whfk0+WwULK0VHQYJeVdR6mpss0pbK7PRHXCkL8mbXZhsx9X9aQW9rrtfOpk80ZqnawkOzsYV/Ut Ggr9viOyqUMOh26Ok1w1zihSNW7cd/c6jCjxcZ6NSVuWsGUnk0Ikk1qWZrEkc7K0HIs0c5Kk7GzN Yd24caMjRziUK0Y3TJ16SNnA8AXOkIPLOVlW6lvgKy07qYZq3hmDs3anBudwCYero2Nucm7yVmQ6 cnnynQ7VgOkRCtGVw3RJxTGHla7wSUekCKcoNUynSK9oNrvpFbvmyBnudi/AOHtDNqvM6NcrZJhe WXZctYblg7UVsqd/5hW3sLkPJueVVig5FrHlCFvOQVUv0yv2VOqCf+oVa6ZX7KZXpJ+7fL6iooED pVc0myXTK44szWF4xXSLU7rF6RROp5u1ma/kfDFFXJG4IvFu0mnXnI7JFVtl+a0Vk9VtykUVJ+Vt ymNo57QIZ9pJ3Lo0Z25fLxl+Uq1IzxiOcjo0p/Mkx52UCraHCqRcfJxw2mh+wfY2fDZ82fbjzhzK 6Y+mvGa3a/acumXSVQ0yy5FnszW8yqd9nt0ms7ZvP5Fsq3NaUaqoynAcneUIe86Uiori0oYpV/2q wcmjjKNDlCIh9YMZQ44l1FhSXjSH1pEemt0t7Lm9fpSetDuE3dHVpw2poWOBVOnVBbJfR1esnE+D bMAm7HblU+JWzc7UZJRMTKaZ6VXcapfKHiubUDB66iGnES+bMKGgYOCDHRmOzcrWrNaODmcWvkym XWuxai7b7t0PPvif9a00qV7uTftWc9oyfOvWnHkdkUhHpOOW0ltKb0CuLr28tKNbOemkOUzDt65M 3waVbw+fhm8dpm9dOZrLiW/TzpV+x6onk1sXuGzCZS32mQb7nHddDuFyGt79P/jXZaGhtH/xSZ6w 53VFYq3lBYYc2yId7PznDnb+AwfL+IK2jrrh7BU42PZf5mC7dLDLJVwu6eA83DsYB+NiHHxF8t0O Zbsp5V5Vx1s+Rd3jVOVkb7ku7x2pe2UGJk13rxlcbs2V4eZbMxytmko7mqJOzeXSRXnCi5SLBvxc Kc2UOJx02eml4dWtHZHiPFvzqydcvD249OT25LLLpdq9MoITVctx1G13FwfxvNsh3E477xtSptDY r0ypFJclVMniCqZBsqzYbRNuW+88KO12c+o6psgtRk6FX/3KaKu/qSD9qLyfngzUtgh3xmzgeOd5 eEDmdJATQj0VdJ3SVE6OluMsrvgVn4pid6qEN+FN28VQoVvI54ecrlqzA5uWk7OgLdld7F52XG5Z qTnCJJFPEA4mSdFwZols0vFxwiu8YjwyHCGbJ6pNokPYszS7Vc4ZOWnkUdHd7crKctmSfWaNW82a XLfIdduFnVc4V8KVODcxKDkoOSXp6ShFDnfnOrRc13mJuYlIokNkSoS084TK1lV2RP0FWoP6wW1E ZesJme3sNxs5LnKtWq79eKT3czw3T8sd2F1cV1THJ/gzKZVFUsqKSou6F+Q6tVy3LmIJeZhIiSXu zWzPreXmnpodS6j7juPduTloMyX2Tkd3XfGIAfbF7SdyXdTRO9pLl3vyxKlyHs8NmsM5WXTySmPn tpLYITEvIbVw2RPZSqbQ/LtpmZe4LOnIoVZxRWenzqE3Odcucm0jJkYiJ9JjdAqHc0pS6iVlCrPg 3sQUTsRk8h30lTq5us0xzUvUJ+dmyGcduVbai0SE6E63J1O6M63oGCQcg45tEPWdYu5rp/757FBC PTcd+1zTcriuyTzcZoyHp3Wpr+uYuDvRW7bX7MeFer46dm/M7JoHJ0fDgf3dC0Ysbz/hsguXPRI5 aegVLXbIoX+WnJu4jDUu1/nX2RiOJXNTyXMTl/K6co7KdDOdW4X8z3JysrUc9r0OIQjM+ZybreXa OlIfmWG1aXk58rHJ+JdITt4I9ons8vpoUAypjPrniIlBbzzE25lTaDfOuNLDJil03fx3WXlmXKPT AcZ/haTus3hXGUjJ7OtKSq4VI2d8+3qPGDNzxrc88psRVYls2htkxtk+xFlm3MoABptx+W4/RJw9 xx8NiYQKm1W4TIWrVNiqwg0qfFr+uE48r8K9MtTyVDhZhREVPqnCHdVzqudkZanQrcJ8FXpUeJEK J6hwcvonFKcTDuWapUbEC4n61hjjZz1sFthqADYZxEgHy1HJf0f5n6qR/9/ew3+/Tv/R8tmiQAxj gv/fxM4VReJ2HqAWiGVivXhBbOHtea84KE5obm24Nlor1qZrt2tBbYG2TFuvvaBt0bZrezX573Vz aMONNsOVXYT2M+P6rE9dtezvCoeaAfJbGXl3H31n3/sJ+/veF7X1vS9O9L2/9sWMe6vQZub3zZ/5 dN/7O6b1LR/o6ps/p6lvfnxg3/x4W9/8RLRv/sKz+ua35PXNb/lZ3/xVrX3z14zqm/+Y6Jv/WEvf /O+dov8zC/rmv4g+Wal7G/drhUPLuH/lA+HIzrj/RavQNr4udyfbCPdUd8Ld7G51b3D/1P2h+3ju ne7W3Dpozt2Suy33RN4Neevztg4YQrnPywakOS2tqpVT5UNTaHnAyNw7Zfv9yAb6a1Z9pmSbFHo3 ZKshA4ZIcbcO2p7/cn4yf1v+zvw9+QeHvsndzgJ3wVncv6xykgUTCtYUtBW0k95R8OmwgoKOYaNU 3qmyB9mWkmGjVYunyLCpQ9+UosrvPFXol55l36p2b8vJfmQPWq1RmplybpNnwxeHSz37aflTUzoM GTZKygUXXfBCfvKCA4U5hXmFBYUjCwsLxxcWFU4jXgUNhW2F7YW7Cz8sPHGh7cKSCw58Xqgzkrop KVCtnCrjTZEtT1Otf15G0luD6jEl7VIuvJPelaCBISVSCgsuGq2scDBlyV7b5e+8eMbFtyMzkLJL ThSNKSoqmjxptUSmFR+YvOWKqVduTF2/OeqaNNdtvm5vimljpj09bf9097SnS24qKS3ZUdI97emZ a0t2zPLNap61+tZ9t7Xc3nDXl2SuN69kx637bt3nnekt8wa9Dd6N5TPKv+uL+nb6jlSIiryKIRUj K8dVzaiqqpof2BLY6p1ZPiOwM7CzQpCGBLYG9gSOz94X2BOsCoaCbcE3A3uqg8G2UF5oSOic8Ljw xMg4lddGfFxkaeTZuSPnrp775tyOuV3Rn8ZmxCKxhhpRk1dTWvNkbbB2ae1SUiJzV9c+Wz+ivnv+ lXdvmttxz7TYjHtW15Q2TGq4uiHa0NKwoWELshV5vWFPw9F7p917+723q/uWeyvuPZqYloiQvyfR nGhN/CixN/FhojvRAycWZi0cuDB/oWfhqIWRhfMXzk+cQPYuTCzct2jIohsWBRPdi+Yv9CzajuxY tHfRh4uON2Y1FjZOaixpLGsMNtY2NjWuatzY+ExjW2N7Y0djV+PxJlvTkKZzmjz97gyp3SFT+qz4 prL+xVjn/a7U1GrNFLlO+qywpnivyNzMe2MV9bci0qsiU/rM9abm/sWY300P5m4rYObn72Q3bW1a k9rV3D9t2pR7wn1c7qlNm2c1525ramv6VO5hw0bJuY+VWk1bqT1S1pJ5xFMWbFV7cTPtJtQunLZj 3lbumtlRt92XQy459+XlNqvUhJLmzP01LWqXlyL34sz9OLcOae5/H5YngToL5GmwPrUPq/rUcR+X e7K0/n3blT8ONo9gVTM+9uH25nhzw7BRzQ82bzXGrFZ+MmOfSxqelTssOwGtNHcUuIeNMvfblzP9 LPdOGW/uyX9Z7eem1ws6ZLjYsvicxRsp09HSm7cto6fUrDnY5Em3nt7T5T5k7ERK+s67jBlm7uAZ e3hBuyEZO7ecaZ/Kc8c4eaTkv0wZ9vL8lz0b8l9uaeH+LCyiNGcvL2h50pxreYWFSzaxgxepHb19 6VlLPcb+yRwtMGeqsTNTWu2r49Pzt0CdAA20l2OUN+RCG/E8dvH2whxZcumLhQ0qLUdJXp893RDj VClK7/+9J0AV0tD/zq9Ont1q7z9hnD9Kv3Z5EtCbbEXWLZJngRz30rb7Kx4ozE8+MJlQ2jz5wAvL 85eXNHfk75zVzK7dbOzRt+5bXit/irt8E/tsm7Gjhsex05+msLOfIpwOfaSfEjv6yiyfoUmvfL4O Z8l/UIwzJbAzdU3dpe4rxCkypGKIcf78Y+Fk+o/IntMXTrO+0tZXOPvyDN/0J/35pXbp3NWchabI O3kmGuehOhNnpGK1SzlDl3J6dshzUp2fSjg/EVmzdunyzdSk7twOeSKqs1IJZ2RLw+vGaUl8i3E1 T07jPJWyR0mLLE3ZaStyOCmzOEWNM1QJJ+dedZKqU1SdpN3pWHOiWa4QVf6EIZy4UmSt+SvyqEU9 88zaKffCAveKwhU75L644riRmr/zwUXG/rLSvapiVetDIx9a/dCbD725Wqz+0erk6ldX736g8OGT q5PsHW1rLI88WdA2bNQjrz9CicznzPxk67Wttxp7l7lbtQ8b9ei1j85Qu9nO/IOP1vU+Lxe0Pfoj 9qpRj763dtu6kvXTHhOPbduw8fHxjx/c+CLPHnsMS2MbZaeFHmNsvJu26k+JXXqR+Kt+ULPoPdod +mFttv6M/H1SrVPflF0C39E3OTeKYucT8KIodt0lxvMe0qof5A2kVd+vTRdDzHqdpO/SD/FO00p9 C2m9eYd5F5alNb2dnE3aAEp8lfh0Uah9h/gd+i+0cu5no0kCDlCmU98tv7VW30+r+8nZzXtvq15v attB3WLtZn2vdgvcCrfB7XAHzJa/86e/QBvTLaRZSLPcCXdBKXjBB36o0PdmjpB3rFb9OWkXWmmg hWeww27sgDb02077H6nfTZQjaqfcZkYlNdpPTid19pvay3rt1Gvv03q2so60TCcjc6s29ivLtNHG KiyzK8Mysrf1yjIH9DGyTd7bWwn/SoqmrPw4Nd6gxhZlj+9wvUN/hRpbpMWwZQ8149TcbPuW8NkX 6zc5n4Kn4TV4He8PpsU206q/pLVOs/9is/9XTM/0mJ5ppLX2f9iaQ+pHS7vVCO7gOpsRHIBOfTa1 xqsZJEfRQJ+7Tds9Q7/P0O86s9/15rg3UXsTtQdS+5E+fZr9uSbpm1136bNNu87GG516j3he2PQO 4YSzYAjk60fEUGxdoO8Tw/DlOTBcf0NcRN5XYDRcDGNgElwGxfANmAU3wc3wXbgFboXb4Ha4A+6E u6CcfnzghwqohCr6DcBsmEP/QaiGEIQhAnMhCjGIQw361cI8qIN6dJ0Pd8MCkD57lBm0jutxrp/A p/AZnCDt73ASdOYV/tK6sM4hOAIf67uzssEKdhjK/P4aTITLoETfz7zdb3Hr+yy5kAcDYCAMgrNg MAzR37CcDflwpd5muQquhrjebp2id1ivhmvgWn239Qau34aZ5M2Cm/V91u/qb1j9pFUQr4QqCMBs CJEehrkQhVpYCIvgPvKbYTnxFfAgrIRVtLea6xraf5T8x4g/TtrTXDfBq/AavA6/ht/rR6x/gB3w BuyEXdR9E/4Iu+FPtLMH3oK98DbsYzx/hg54B97T37BZ9TbbJJgGq+AhWK3vtz0M+Mq2gevjXJ/T 25yd8IG+33UjvpkkLPoyYWU/tcvfx5e/UQ8ucEMeDICBMAgGy99nB/lb70P1zczmHmbzZmbzLnGu 3sSMbhVf0LeIEbR5HnjgizASzocvwZdhFFwAhaycC2Es7Y1jVX6V63i4BCbA12AifB2K4FKYDFPg crgCroSr4Gr4JkyFa+BauA6+BdPhergBSuA7MANuhJlQCl4og3LwgR8qoBKqGGMAWN+soB5WUA8r qIcV1MMK6mEF9bCCelhBPaygHlZQDytoFytoFytoFytoFyuolRXUygpqZQW1inuwUwPcC+xsYiHj X8RuZNNf0jzwRRgJ58OX4MswCi6AQrgQLtKna1+Bd/RS7T14H3rgmF6aXlF/0ZdlfwgfwUH4K3TB IeiGw3AEPoaj8Df9YHYPHIPj8Al8Cp/BCfg7nNQPsjp7WJ09rM4eVmcPq7OH1dnD6uxhdfawOltZ na2szlbLN/WXLFPhGrgWroNp8C2YDtfDDfBtKIG4vtlSTx/z4W79oLUYvgGXiyGs5s1W/GqdBvjW im+t+JOVvZmVvZmV3cPKbrXeom+x3kH6nXAX4GMrPrbiY2u5vsyKj1n5Paz8HlZ+Dyu/h5XfY51D XhCq9dnWCGXiUAPzoA7QyXo3+QvgHuINcC/gQ2sjNMF9tNMMLcSXwP3osozyDxBfhW4PEV+DrjzH sFP0WNdyv4744+RtJP4E8SfhKfgePAPfh2fhOXgefgAvwA/hR/Av8GN4EX4CP4WX4GV4BX4GP4fN 8L9gC/wr/AJ+CUn4N9gKv4I2+N+wDX4D2+G30A6/g9/DH2AHvAE7gacRdq/N7F6b2b02s3v1sHv1 sHv1sHv1sHv1sHttZvfazO61i91rl3W/3mR9F95j7O9jpwPQCR/R3kHgycDapW+x0ZeNfmy74E39 Jds++DN06NNtH5BGeVsX94dA11+ys47suTAUyvWXRBZn1i95XlqvYjuJxYnJZzsLZ6R8ptymninf Fr8TTpX7V66TxC4Rkt93oX0kns/SRCh7HIyHS8Tz2SXwHQhDPdxDegPcC43wPXgGvk/es1yfg1fh NXgdfk36Nq6/ge3wW2iH34mQ9RGxyHpSlNjGi6k8eXxqmy6W2UrEePvd4qs8hbQ77xfjncvEVOcD wInjfASegqfhObHD+bxY4/wBZX4Cr3D/M+7/jbJb4TXKvK7/0XlAlDg/Ej7nQZ4McrHDh9bjwmf9 hOece2ChqLMvEnXOxyixATbSwhPwoljjmiHq0s/ib8u/JGUH26WepXbI50/KllC2hLIlqlwBJbp4 YjjCE0MXTwxHeGI4whPDEZ4YjvC00MUJ3sUp1sUJ1sUJ1sUJ1sUJdoQT7AgnWBcn2BFOry5a9tGy j5Z9nGRdnGRHOMm6hIu+d+GREXhkhH2h3m5fxCgfgw3yGRie0NtdM+Aucw4clt4XFvnsTL1C6hU6 n0RXmzmK/dizDXu2Ya827NUi7OoJnBw80Pa53GzTAr9Tz+ca4UH1NN/CE/Zunjblk/pPSJ0unyTF CvXNKU36UfXdKcvEIPEAV/kNKo+RvgEeh43wBDwJT8HT8D14Br4Pz8Lz+ifiB7AJXoSfwE/hJXgZ /pU2fwHbYDv8FtqB5w/xJvm74U+wB96Cvfonci5oVv2o9o4Yob0H70MXbw2H4Ah8DD2kHRMjLEP1 Q5YCGAbnwLkwHL4AI+A88MAXYSR8Sf/E8mUYBRdAIVwIF8EYGAvj4KswHi6BifB1KNI/sR7Rj1o/ hqPQwz2zyHqC2aHpR20urrn6IdsA/RNbPld0s6Gb7VzSzxODbOcT/xLQv43+bfRro1/bOPInkE4/ Nvqx0Y/tUriM9Bmk30jbM2EW3ET67XAH3Al3Ac/cNp65bTxz23jmtlVBEKohBGGIwFyIwnzq3A0L 4B5YTxq+tuFf2zPEv68fsYf0o04Hs/sS/ajrGvgW8elwk35Im8rMeV/cxxxuhsXQwjrkrFHfTHM/ LCP+AFf5HTUryHsQVlJuFXP+Ia6ruV8D7BvqvfZR/X6xVv8d67NerNffEs9R5gX4IfwI/gV+DK/A z4AzRHCGMLs6mV2dIgmvwmu0+TrXbfAb4tu5/hba4ffwB9J2wpu08UfYDX+CPfAW7IW3YR/8GTrg Hcq/C3+BD+EjOAhd6H4IuuEwHIGP4Sj8DXrgGBxnbJ/Ap/AZnGAH+DvjPMlV501P6G9pWZCtv82s f197nOtGeAKehKfgafgePAPfh2fhOXgefgDowhtOO2847bzhtPNW084zWDvPYO281bRbztcPW0br nZaLuY6BsTAOvgrj4RKYAF+DifB1KIJLYRL1ZRvF8A2YDFPgcrhSr+fNZz1vPustNfrblnvpI6G/ zSp5n1XyPqvkfevf9MOslMPWY/Cp3mnlLY0V02nV9bdtQj/MynnfxtjZf+ttNv0tm5M0l95pc5M2 gPhA3rgHwVkwGIbAMM7bcykznPwvwHnce7iOpM6FXC+Ciyk3BsZRjnHaLqFtxscqO8wqO8wqO8wq O8yby3pWWqetmLrfgCmkXQ5XwFXU+SbXa+E68qah443oOxNmwb8Tc+/hcdWHmcdHY3suFkkIGZJA MITYXATIwVYJJNhJgIAFiIsMMRcBEcHicriIizAI3wBlCAkIJUMSta7aRq06bWUt1baVl4g0tPVQ oiYYCDQzLgxggRkuwtwNJMS//YwYNi5PNn2efXaf/ePLb+acM6Mz5/f+3vc9I+EzbD8TZ+FstKEd 5zt2uffswIW4CBfjEkT2XWa8HFegE1fiKlyNa+zvguuZWIHrcD26cYP3XolVWI017qzWwjVP3IQe fAvfxm24Hb2uwR3ow3fwXeR8jjvxvXCbjLst8YPwYKIf1mLij3zmdfhjDDifP/Eef+qYP3OdaDJB kwla5BQVTlFJ/LXj/sbrRkKZa2xNXhleTV6Fq3EtVmANnBdHqcx2/rOd+2zbZt+Mb4CXzK72Cuc5 m1/M5hezc7bxitnfwx/Kw3x4bPZfYdTzMWzAjzCOe/Bjr/lH/AT34p/wM9ut9dlPe99K6JbXt81+ PjxWv1ASN4Wt9TRfb97rj8ISz81zvXmuP8F4YqhwvEr9SZ6fjFPctZ5qPC10158eHqz/qvcx//Xm v97817db6/tMN7n/T62trkeqz+PL1X/9rvpv3yX48ihfnseTx3nyOC+OeHHEixO8OOLFCV4cxb4f 5vPjHD+OfIKIH0f8OOLHET9u1woirWCeVhBpBZFWEGkFkVYQaQWRVhBpBfO0gnlawTz+ndAMIs0g 4uMJPp7g4wk+ntAUIl6e0BYibSHSFiJtIdIWIv6e4O+J2I/8zHHc471+jHtje/P48dg/G/8FG1HA ffhX2+/32p8aJzz/mccP4xd4BI/il96r6H1Lxs34DzyGx1G2/Qk8iaewxfGT3utp4zOuy1Yd6llU PH4Oz7umL+BF12sKL2Gbxv6y418xvorX8DrewJvYbt9beBvv4Ff4Nd7LgminLGjX0/LyoF0eRJpQ izwYlQej8mBUHozKg1F5MCoPRuXBqDwYlQej8mBUHozKg1H35EfUTXq9z+De/Aj35kdMf5O43fgW 3vb4HT/jXeNvQns8Ho6Iz0QiHKFRzdOoIo0q0qgijSrSqCKNKtKoIo0q0qgijSrSqCLZktCqIq0q 0qoirSrSqiKtKtKqopkHa2mHuKdudNz80C572mVPu+xplz3tsqdd9iRkT0L2tMuedtnTLnsSsieS PV2yJ5I9kezpkj1dsqdL9kQ7ZU9O9ozLnlF5k5A37fImIWsiORPJmYSMycmYSMa0y5iEfIm0tSjx 4djecqZdzkRypkvOdMmZLjnTpcVFWlykxUUyZ15iT8ft5bVzsE8YlzmJxL62uQ7aXaTdRdpdpN1F iQO874FosP8guA6JQ9Dofedjgdf67JrfPLmUkEvtcqldLrXLpfbpXPK5ZVJOJiVkUkImJRJHh/ly qV0uJeRSQi5Fcqn6/fJybXGehhjJpYRcSsilhFxKyKWE1hhpjZHWGGmNkZxKyKnRxAXe6xKfJbLt Uud3jbEL12IFrsP16MYNjl2JVViNNbatxY24CTd7fY/xG84xi1vCrYlv4laPv+VzfBu34Xb0Ou4O 8CS51CWXuuRSJJciuRTJpUguRXIpkkuRXGqXS+1yqV0m5WRSNJ1JP/SZrQ25NKrBzpNNOZnULpMi mRTJo4Q8SsijhDxKyKOEPErIo0gWJWRRQhYlZFFCFiVkUUIWRbIokkWRLIpkUUIWJWRRQhZFswfC fHnULo/a5VFCHiXkUUIeJeRRQh4l5FFOHuXkUU4e5eTRqDxKyKOEPIrkUSSPInnULo8iWZSoPzLM l0c5eZSTRQlZNCqLEjIokkGRDIpkUCSDIhkUyaB2jXyeHErIoYQcStSfG9tbFkWxT3PyCU4+wcmf 4uQT3GeC+0xwnwnuM8F9JrjPBPeZ4D4TVtSEFTVhRU1YKRMUOEFZE2ZlwqxMmJUJszJhVp4yK0+Z lQmzMGEWJlztCZ9owieacHYTzu6p2If95G3uSwv8qMSHSnyopKtu01W366rbdNXtPKnEk0redZt3 3eaV22Kpuo+4/2vBe79F6ar9NmfTjFNDfkZryLvDjdy9xqd/x+ae2KMoVBxVsedcdwbv7ylNH/lP 7rTPDZur98bv3227n/6ILS04d/p3bEur7/P+7/1is+zdXrcgvOaI7XWtqP5246N1Z9hyFs5GG87B udDqqq+f6flMz2eeh6+hHefDPdpM92gzq78XqZ7rs9XfKE2f5ZNeV5g+v+rdfeH9bxGmtzz+3meu bake/XfV3yfFdnMeG5zHBuexwXlscB4b7N1gb/79T+hcNjiXDc5lg3PZ4Fw2OJcNzmWDc9ngXDbE ZnjV07Xf3E3GmuoS4Z66fXyeTxv3xWcwF/OwH/bHATgQDThIWh2MtV5zoyt+k3GLd3sGW7Edb7ku x4Z7Zh6HJWjG8TgBJ6IFJ+FknIJTwz2Jn7sP/aXxCTyJp0I+sc34MnbYF8I9Seea/BA+Adc96bon XffkBZ5HrvOETzNSlwxTdWnMRj0+hA9jV3wUu+Fj2B2fwB7hgbo9zfenwn11e4VH6+aEv6zbO4y7 KpOuyoirMuKqjLgqI67KiKsy4qqMuCojrsqIqzLiqlznqlxX9wfe7ws4EkfhGJyAE3ESTsYpOBVL cRqW4etYjogmLnU+l+EK53QtVuA653U9unEDVjpulXNcbVwD9wRmY9JsTNZVv9f/BrZYh89gK7bj rVAwKyNmZcSsjJiVEbMyYlZGzMqIWRkxKyNmZcSsjJiVkZmtYWrm2bg4bJ8Z4VJ04krZe5X7waux Ijwwc5VjVmON+7K/xT3hvsRPjPeG7Yn7wwOJn+LfPP6Z3Pm5+5eH7PsFHp3+fnUksdm+/8BjeBxl PGH7k3gqXJeoOO4FvDT9vesIVYwkXvX4bce9g3c93uF9QxhJxsJUclYYp5aRZDo8QDEjSfOf3M22 T3j8SY/dTyb3xF6Yg73hnjL5aczFPOyPA9GAg3EIGnEoFmAhmmDOk4fhczgcR+DzoIMkHSQXgRaS R4Mekl/BsTgOLc7vJJyMU3Bq2J7kPcmlOA2n46vhvuQynBEeTZ6Js8JfJs9Gm89zTpi0Ciatgsnk 17xfu/c43zFft+8Cn/Ui2y7GJbDmk5dXPSh+Z+zi+F+EB2N18ZNjDXX56r8dXP2Xg6v/bnBsD167 Z/h57FOhL7ZXaInNcZezt/374NPYF5/BXMzDftgfB+BALboBF3iv5ejAhbgIF3vvSxDhWu+/Atfh enT7OTdgJVaBqmNUHVuLdZSbwB74lGzYi8LnaM57e27GrNCCFVqwQgtWaMEKLVihBSu0YIUWrNCC FVqwQset0PHpv5a4FJfhOu91PbpxA1batgqrsQZra3+hcVOYiu8VHo7vg33Dg/H9jfNDY3xB6HMF l8aXxpriy8N98YvgSsevMK5AdxiIrzL2OX7Q8UOO/3vP/9HjkvHtcN+M2fhQGJixv/H58NCMF/Ai pvAStuFlvIJX8RpexxvhoZmZ0DJzd3wcx1rdx2EJmnE8TsCJaMFJOBmn4FRciatw9fTvsOdbxYVZ zSE/6/Qwf9ZXcWZomXVW2DTrgvDQrEtxGS4P47NWGlfhNvtuN+Ycd6fxB16zzvhnnv/Q+JD3exi/ wCN4FP/umF+iiBKe8POexFPh57O2YDL0zXoaz3iPrd5fFs6qYFvYpC0UtIUCZylxlAJHKXCTAjep OkiBWxS4RYFbjHOIAococIQpjlDgBgVuUOAGBW5Q4AQFTlCw+gpWX8HqK1h9BSutZKWVrLRJK23S Shuw0gastIKVNmWlTVlp1VVWsMomrbKCVVawsqaSlVBJPhdGk8+HfPIFq+/FMJGcCh3Jl0Jrcpvx ZftfCWPJV8PDydfwOt6w7U3Hb/cz3vKat8MjyXcc+6uwJPlr47uO+Y1jdnjfEPKpWBhP1YWJVDx0 pGaE1tRM46zQn0rYl0QqdKXSoS01OyxJ1du+S2hPfcj4Yfs+Anc8KXc8qd0c8zHHZMKeqd3t/7jj Phl6U3uEgdSe+JT9ezluTmhJ7R0Wp/Zx3L6O+4z3mAt3Pan97N/fcQd4nwPtb7BfN0jpBqlD7HfX k5pv/2ftP9T+Bfa7+0sd5jN8zjGH44gwmPq8Y77gmCNtX+QcFnvdFz3/ku1fNh614+nU0V57TGhK HeeYJV5Hp6njHXuC7Sc6rsVxJ9l/sv2nhJ5Uq3Gpz3EaTnfcVx23zHFn+CxnOu5s+9u8xzk41/7z 7P+a/e3e53z7Hwv3pR5HGU/gSTyFLZjE03gGW/EsKngOz+MFvIgpvIRteBmv4FW8htfxBt7EdrwF XpB6J9yXviA8nO4I+fSFuCiU0tw7fUnoTEehNX1pyKUvs//yUElfEUbTnY65MmxKXxUm01c75prQ nu4Kt6ZXhP70dWEgfT3cxaVvAG9NrwqL06tDfXptGEzf6LU34Wb73MGlvxHa0tmwJH2L/beG8fS3 vPbbuM173R7Wp3vtv8Pr+/Bd+3Neeye+Z//3vd8P7O/3+rtDY/on+OfQl37IuT6MZz2u4OXQOHtW uG/2QTgYx+H4MDD7TONZuMLjTlwX7nNXUKjbRTINS6V87a+YJqVSJJVyUmlSKg1LpWGpNCyVhqXS sFQalkrDUmlYKg1LpWGp1CWVuqb/5uNi73UJIlzrPVZACkihSSmUk0I5KZSTQjkpNCmFJqXQZPXv JSTAsAQYlgBbJMCwBMhLgIi7D3P3PHePOHueiw9z8WEuPszFh7n4MBcf5uLDXHyYiw9z8WEuPszF h7l4jovnuHiOE+drf3dQ4sR5TpznxDlOPMmJhznxMCce5sRdnHiYEw9z4klOPMyJc5x4mBPnOfEw J85x4mGum+e6ea6b57r5nf6iZ5LrTnLdiOtGXDfHdSe57iTXneS6kzVXK3O1cs3Vxrlajqv1cLW2 mqsNcrVhrjbM1YZrrlbiaiWutp6rjXO1Hq7WxdXauNpwzdXKXK1cc7Vxrpbjaj1crY2rFbhamauV uVovV8txtR6utomrdXG1Alcrc7UyV+vnar1cLcfVerhaA1fbxNW6uNo4VytxtRJX6+VqPVyth6t1 cbUGrlbgamWuVuZq/Vytl6vluFoPV2vgagWuVuZqZa7Wz9V6uVqOq/VwtQautomrdXG1Elcrc7Uy V1vP1XJcrYerlbhaP1fr5Wo9XC3H1XpSR3HEo732GI4otblamauVuVp/zdVyXK2n5mqbuFoXVytw tRJXK3G1fq7Wy9V6uFoXV2vgagWuVuZqZa7WX3O1HFfrqboaZxlOLw9l7lLiLiXuUuAuj3CXHu7S xV26ucswdylzlzJ3KXOXAnd5hLvkuEsPd+nkLuPcpcRdStyll7v0cJce7tLFXfbkLgXuUuYuZe7S z116uEuOu/RwlwbuUuAuJe5SqrlLP3fp4S5d3KWJu2ziLmXuUt7JXXLcpYe75LlLnrtE3GWYuwxz l4i7RNwlr9suizXEp2KH6bbV/34/Pl8/uzMcFi+G0XgF74bzZuwSRhMnxn6QrMQOTz4XOyr5PF6M LUpOGV+ybRt1vuzxK7EDk294/qbH2/G2x+8Yf2X8NfX+xrjD8xA7KlUXW5SKG2fEDqfgSmpWrDGV 8DyJlG1p42xjPXaJHZj6kP0ftu0j+Khtuxk/Zsx47e7Gjzvmk47Zw/Y9sZdtc4x7G/cxw/va9xnP 52I/2/Y3HmA80Osb7DvI84PRaNt842eNh9q3wLjQex/mmM/ZfjiOsO3zxi8Yj8Qi+xcbv4gv2f5l 41Fee7TxGPuO89oltjfjBNtONLYYT3LMycZTHNPqmKW2n4av2rbMeIbxTOd+tn1tnp+D82z7mrHd eL5cWx47MN0ROyp9IS6ONaYvMUaxw6mznL7cvis878RVtl1tvMbY5XUrHHud59fjBttWGlcZV3vd Wvtu9Pwm9Nj2DWPWeIvX3Wrftzz/Nm63rdd4h7HP675rX87zO/F9235g7I8dHvvetKI2avfFsJqq VlPVYb9DUYfvpKgSRS2iqLm/Q1GLKKqRokofUNThOymq9F8oau7vUVSppqi5H1BUI0UtoqhGiir9 HkWVfo+iSjVFzf0vFDX3dyiqVFPU3N+jqFJNUXM/oKhGilpEUY0UVfo9iipR1NydFHUgRS2iqEaK KlHU3J0U1biTokofUFQjRS2iqEaKKv0eRZU+oKhGilpEUY0UVfrfKura+L6xxRrF6E73Dnkpm5tO 2Vek6FvuM94J/VL0Vkrp3uleIC81c7XUrKZlTlrmpWVOWlakZbe0rKbkqJTMScm8lMxRRZOUrEjJ bin5iHTMS8dbpWO/dLy1lo7VVByVijmpmJeKOWpokorVNByVhjlpmJeGOUpokoYVadgtDaspmJOC eSmYk4IVKdgtBXNSMCcF81IwRwFNUrAiBbulYDX9RqVfTvrlpV+uln4V6dct/R6Revla6vVLvVtr qVdNu1Fpl5N2eWmXm067i6ztS6RHpA9fqsderkf/tivnpVnOLPdIs0ekWF6K3SrF+qXYrWa4QYpV 02tUeuWkV1565cxuk/R6RGrla6nVL7VuraVWNa1GpVW/tMpLq1zsz6e74vzQoieOx1eELfrUhD7V o091m+l+M5030y1mer6ZXqxPPWK2e3WoR3SoHh2q08z361B5s99i9ueb/cX604T+1KM/VZXQTwl5 SmihhPmUsJgSIv2pQ3/qoIhWiqiniHqKiChiMUVE+lOH/tRBGU2U0UoZ9ZRRn8rseIkyIspYTBlt +tMy/WkZhTRRyBIKqU/tvePd1D6O29dxn/EeczHP/v28z/72H4AD7W+w/yD7DsYh9jfaP9++z+JQ +/VnillMMT36U4f+1EE5bZSzZ+oLfsaRZnuRn7nY677o+Ze87svGo3bcSTmtqWO8x3E+/5LQqT91 UFAHBUUU1ERBu1NQPQUNUlArBfXrT536UwcldVBSREkNlLQ7JdVTUr/+1Kk/dVBUB0VFFNVEUbtT VL3u9IjulNOduqlrve40TmFtFLaYwjoobEJvyulNPZS2ntLGKa2N0hZT2jJKi/SmZXrTMoo7muKW UFx9etWOd9OrdzxBcV16U4fe1EF5R1PeEsrbk/Lq07fYfytlfUv/+rb9tzn2dvRS6h1hdwrcnQIH 9aZOvamDErsosYsSmyhx99gyCnyQ4koUN0VtFWrrmf4+4i095m1N/x3bf+Xxe95SoqgpaqpQUw8F Vain6iVj1FKilgqlVHhID5WMUUaZMsqUMcU7yryjmxpK1FChhArP6DH7JbNfMfMVXtFj1sfMdIU/ VL1hzAxXeEOFL1T4Qg9PGDObJbNZMZMVM9ljFsfMXNnMlc3clJkrm7lus1UyWxUzVTFTPWanbHZK ZmfK7JSnm+17679kVspmpDK99rs9vgEr7VtlXO24mx3TY38WtzjmNttvR69j7jD2OeZ7jvm+/f2h EhusrfEHXeG11nfJ+r7X+h5ztfOu9nrru8sV73DFj7a+y7X1XbK+x6zvqrPnzcB6M9BlBtrMwNHW d8n6vtf6HjMbebOx3vruMiMdZuRo6ztvfY9Z32Nmp9v6jsxQm/WdN0sd1nfe+h6zvqsz1mnGuq3v yKy1mbVdre+8meuwvvut7/XW93qz2GkWO81im1lsMYu7Wt9563vM+h4zo51mtNv6jsxqm1nd1frO W99j1veYGe40w93Wd2SW28zyrtZ33kx31L71GbO+q7Pea31HZr6t9q1Pp9nvNvtt1ndEAW3W92vW d36nb33GrO+qInIU0Wt9d1FFG1U0WN/3UkZn7Vuf9db3eirJUUkPlURU0lZLiuq3PmPW9xjF5Cim 1/ruopo2qmmwvjdZ32PW9xgFjVHQWO3eqIOC2ihok/V9r/U9RkljlDRmffdQUyc1tVnfeet7vfW9 nrI6KauTstooq4WydrW+89b3mPU9RmXdVNZpfUeU1kZpu9a+dVlvfa+nuhzV9VJdRHVtVNdQ+9Zl zPoeo8AcBfZa311U2BH70+nfHN0Ypqjx6dp30+99F72CMrv1iuf0iufxgh7xonSZkiwvUds2Y9UH 3nTMdlR7xnvfQ3ZSYys1dlLiOCWOU2KBEh+hxE5KbKPETkocpMRxShynxDWU2EGJrZQ4SIkRJQ5S 4jgljlNiFyWuocQOSmylxHmUOEiJUU2Jo5Q4SokdlLiGEpdR4hJK3J0SBylxnBLHKbGLEtdQYgcl tlLiPEocpMRxShynxC5KXEOJHZTYSonzKHGQEiNKLFDiOCWO1+7UOyixlRILtTv1NZTYSokdlNhK iS9R4iAlLq7dqY9T4njtTn2QEjsosZUSF1NigRJ7KfFeShylxNHanfogJXZQ4hJKXFy7Ux+nxPHa nfogJXZQYislLqbCUSocnf7+7xJKiSig+t3fFRTQiaqPXW37NdTRZfsKzn+d469HN0XcgJVSZpUE WS0Z1lLUjV53E24Oayivi/I6KK+V8nav3ZGPUt7oTt/3dVBeK+W1UF6B8sYpb7x2R76e8joorzV2 C8VNUdz4tP+9QEkvUtBUGKCuXupaNt1e35Aub0qZ7XjLMW9Pt9kcha2hsGWUNUZZBcoaoKxeylpG WSWK6qeoAYrqpagSRa2hqBIlDVJSPyUNUFJvrc2WKGkNJRUoaZKSJimpn5J6KSlHSWsoqYmSShQ0 SEH9FDRAQb21VluinEHK6aecAcrprbXaEuWsqbXaMYoZoJheiilTzCDF9FNML8UMUEyv9JpHMSWK 6aKYEqUM1pQyQCm9NaWUKGUNpWyilElKmaSUwdo31TlKWVP7prpEIYM1hQxQSO+0QpZLow5N9kJc xJculkyXUEJkdn+bdptq390MUEovpXRTSoFSJillklL6KaWXUnKUsoZS5lFKiUIGKaSfQgYopLfW ejdRyCSFTFLIIIUMUkiOQtbUvhEuUcb62nc1A5TRW/2bjtjCupbYwvjdsSPjL8YWxKdiR87YN7Yg eVNsePYPYzfHMjsdsWB6zwuxhcm3YgtTMeyKT2EeDsHxOB3nxhamL8KV6MbNuA3fiy2MzYnvFRri 7l3i+6PPXfpPw+b4w3gURTwbNidfDQ3J1/A63uWsF+AyPBQOSz8cDpsdC5tn1+HT2BeHoBELw+Zd XsVreB1vYHvYHPtI3bOhWP2/yK2Ds+OHhh/FF4aV8S+HdfFjrY0Tw1B8qcfLQjF+BuRE/Ppwd/yG sLL61yexE5zzVue81Up6zXlv9S6vxT+rVSwIT8aPNOo68eXh+fhFuAIrvMt1uAGrPL/Z2BOKyXF3 GGXjE3gSr4atPudWn3Orz7k19ZWwJXUsHgvPpx5HGU/gSTyFLZjE03gGW/EsKngOz+MFvIgpvIRt eBmv4FW8htfxBt7EdryFt/FOeD79+VBMfwFHYhEW44v4Er6Mo3A0jsFXcCwuCFvNz9a63eq2hNl1 z2ArXow11L0cW1r3OrZ7/hbeDnfVvWP7u8bfxBrin4gtdXUzrm7G1X0gPjfc5Qpn4gcZ57tqh5qX Jo8XU4ufHj8qZONHw0+OL7G92WtOMJ4UzomfbDwlNMVP9bjV/C513Gm2nR6ap+f2TONZ3uds29s8 P8e+c93Vn4eveU275+fj67jAsct3bI9fhEsce6nXXOHx1cbq7F4fOuMrvWaVbTfZ9o1wzowjY0uT /xDuSm7Av4Vzkj9HKWSTm/EYXg0Zs50x2xmznUmdGu5KnYWv6z4UnlqODlyIi3AxLkGES2EFpC7H FejElbgKV+MadOFarMB1uB7duAErQza1CquxBmtxo/Rz7qmbQZ2pbyCLW/BN3Ipv4du4DbejF3eg D9/Bd5HDnfgevo8foB9/iD/COp/xj2OLUwOx41J/YvxT/Bmf+GFseWrQ4z83/gWGPP5Lx+aNf+X5 Xxv/xnHD4ZzUeozgv+Eu/C1G8d/xd3z47+Hap8bg+qf+B+7GjzCOe/Bj/CN+gnvxT/hn/As2ohCa U/fhX3E/fooJ/Bt+hp/jAWzCg3gID+MXeASP4t/xSxRRwmb8Bx7bsT31OMp4Ak/iKWzBJJ7GM9iK Z1HBc3geL+BFTOElbMPLeAWv4jW8jjfwJrbjLbyNd3ZsT+/Hew/AgeDT6c+GbPpQLMBCNOEPcBg+ h+PCOeklaMbxOAEnogXWWfpknALrLN2KpTgNp+OrWIYzcCbOwtlowzk4F+fBeku343x8HReEDAfJ pL8Z7kp/J9wVi0+v/hXu3/aq/hsKPGMpv1gan8FpZyGJuZz3oOl7uwes4wbruMErxq3BLdbgFppr oLkGmmuguQaaa6C5BpproLkGmmuguQZ6a6C3BnproLeGWJITleONfv788DCP/3H8eI5QdYHuUIy9 ULfFuUzysKfxjMdbY0vf//c96rZ7/BbeDg/W/Sp8s+7Xxnexw+Og6ce1/hnh2vhM4yxjwpg0zjUe hEafYX7Yzvfuii/weKGfyoGns+oon/NYLPG8Gcfbf4LrcJKzPdXzVvuW8r33PO+9LDsTZ017XdE1 anKNmnhd+QNeV4x3SP+LEeFS+y8zXo5OXImrbbvG2IVrY5laRt4l4a6Kr7ZtLW7ETe6f5+sJ/xDu Mwf38cEyHyzzwTIfLPPBcvIp+5/Gs7EFvK/I+4q8r8j7iryvyPuKvK/I+4q8r8j7iryvyPuKvK/I +4q8r8j7iryvyPuKvK/I+4q8r8j7iryvyPuKvK/qP0VaaKKFJlpoooUmWmiihSZaaKKFJlpoooUm /lOkhyZ6aKKHJnpo4j9l/lPmP2X+U+Y/Zf5T5j9l/lP+v+A7Rb5T5DtFvlPkO0W+U+Q7Rb5T5DtF vlPkO0W+U+Q7Rb5T5DtFvlPkO0W+U+Q7Rb5T5DtFvlPkO8XUr1zjX+Nd/AY7EGIL0jHUIY4ZmIlZ SCCJFNKYjXrsgg/hw/gIdsVHsRs+hgx2x8fxCXwSe2BPfAp7YQ72xj74NPTJ9GcwF/OwH/bHATgQ DTgIB+MQNIK2+FeZf5X5V5l/lflXmX+V+VeZf5XThzvmiNgCzXVL2KKNbNFGtmggWzSQLdrGZm1j s5ax2dp+Q2+r6G0Vva2iq1Wk9GYpvVlKb5bSm3Wxii5W0cUqulhFF6voYhVdrKKLVXSxii5W0cUq ulhFF6voYhVdrKKLVXSxii5W0cUqulhFF6voYhVdrKKLVXSxii5W0cUqulhFF6voYhVdrMIVN3PF zZr6s7rrgvAKDxjiRlnr/S7r/W7rfN20K83gGAWr/65q06lb6pPvWjfJd57GMx5vxbOhsfqv9uzU yXZ1RXblVS1173jVr6a9qqXuNx7vmPaqRl41zqsaedU4r2rkVeO1zjbHVZzDKbfxrvtdzTn8635n 0ec8q57VzLOyzrdPX1sZP8a5fsW5L7Gt2eMTjC2OOym06G3rdupt59Q8LFvrbX187K5ad2vW3Vbq bkP8LLtTd2vhZ1l+luVn2fe6m57X4TPoUfGLjREuDQPxy4yXQ4eKdxqvhPuv+DXGLqwIv5xu7tc7 n+7p9t4QX237WtzIb29ybK3NT/e9+eFBXnc/r7uf17XwuhZeN8DrBnjdwH9q+0851nwkn8WrYQ6V zaGyOVQ2hw8288FmPtjMB5v5YDMfbOaDzXywmQ8288FmPtjMB5v5YDMfbOaDzXywmQ8288FmPtjM B5v5YDMfbOaDzXywmQ8264ArdcCVOuBKHXClDrhSByzogCt1wJU64JAOOKQDDumAQzrgkA44pAMO 6YBDOuCQDjikAw7pgEM64JAOOKQDDumAQzrgkA44pAMO6YBDOuCQDjikAw7x4GytAy58rwO6r/7P HfBsHnx2rQNmf0cHbOHBLTy4hQe38OAWHjzAg1t4cMtOHTDLi7O8OMuLs7w4y4uzvDjLi7O8OMuL s7w4y4uzvDjLi7O8OMuLs/9vO6Ae/jjKeAJP4ilswSSexjPYimdRwXN4Hi/gRUzhJWzDy3gF7pY5 SQMnaeAkDZykgZM0cJIGTtLASRpS1nZKF0npIqnfwPpO6SPpGOoQxwzMxCwkkEQKacxGPXbBh/Bh fAS74qPYDR9DBrvj4/gEPok9sCc+hb0wB3tjH3wa++IzmIt5qPbV/Y3vd9YGjw/Cwaj210ajdScH BuTAgBwYkAMDcmBADgzIgQE5MJA+3DFH4P/sjnYO550TO6huiiO9fyd61LSTVe86V3Kw5mkHO9l4 Kpdo5RhLPT7d3asGzLUu5CYjnGS2VZyzciMrN7JyI6szZ0VGVuKoVThqFW6yMpZbEcutiB+kBsOk FXG9FXF9Ku/xeyth4fRK+NswKjkX1lr9Ildokatyamwxz1/H69fx+nW8fR1vX8enh/j0EJ8u8uih Wqu9K/5Z+xbgSBzPj5fzzYuq97i1+9v3vC+bHA/reNUQrxriVUO8aij1lbAudSzc09Jzlp6z9Jyl 5yw9Z+k5S89Zes7Sc5aes/ScpecsPWfpOUvPWXrO0nOWnrP0nKXnLD1n6TlLz1l6ztJzlp6z9Jyl 5yw9Z+k5a36GzM9Q7G+08aad2niTNt70/r/wpo03aeNNtTa+dqc2vrbWxscl3FoJNy7h1kq4cQm3 VqLdLc3u1sYz03cXh4bvSK5q0y6a4wul08bpdn2Obec65jx8zfN228/H19Fh28WIoMFq1BmNOqNR ZzTqjNQpatQZjfq3bXq1x2txI26SGPNjGelyt3S5W7oUpUtRuhSlS1G6SBT7n8azsQyHneKwGTrK cNiMlpuhpww9ZThshp4y9JThsBkOO8VhM3SVoasMXWU4bJHDFjlskcMWOWyR1ooctshhi5x1I2fd yFk3ctaNnHUjZ93IWTdy1o2cdSNn3chZN3LWjZx1I2fdyFk3ctaNmmhGE81oohlNNKOJZjTRjCaa 0UQzmmhGE81oohlNNKOJZjTRjCaa0UQzmmhGE81oohlNNKOJZjTRjCaa0UQzmmhGE81oohlNNKOJ ZjTRjCaa0UQzmmhGE81oohlNNKOJZjTRjCaasZ4ymmhGE81oohlrK6OJZqyvjPWV0UQzmmhGE81Y axlNNKOJZjhQkQMVOVCRAxU5UJEDFTlQkQMVNdGMJpqJ3fCfvvVcrNMcNf2d1TrOsY5zDHGNrI7T p+P0UdI6HaZvusNU+0u1q+ghFLCOAtZ98NtR3aFPd+jTHfp0hz7doU936OM6fbpDn+7Qpzv0caA+ DtTHgfp0hz7doU936NMd+nSHPt2hT3fo4059ukOf7tCnO/Rxqr7/ldV/HjuOio6jnAOpZm+qWUc1 66hmHdWso5p1VPM/uTsX+Cjqc+//5z87s9nJEqFioWpRvBEFjxoaXqor9RpFvKwYb6vGC6NB1Kh4 i7VAWX2bekqbop/m1ZxoY/VQi5ZiTN+uqDlKgsajS7wmrIJxE0lA1iUsnIiRZs53/rsJmxC8tPX0 /bzJ58fMzszOPP/f8zy/5/nPhp1qoqaaqKmmnlZSTyupp5XU00rqaSX1tJJ6Wkk9raSeVlJPK6mn ldTTSuppJfW0knpaST2tpJ5WUk8rqaeV1NNK6mkl9bSSelr5z6ynREggS30LBu5QizHez2BJgNHg AHAYmAJmgmJwhbB9peAWcDcIg1+ASnWH3PY9JAro5k92eomLhCxW/x9oNnpCXy88bG+jV15Nv7Oa fmc1M4Mk3XpK3SGIUovaMsdGdWJQJwbFjcTbikwv/oScxXz9HGIrPX+o5OgTUbNSrrMCRfs5MVhN DK7IUrVKVK0UVStF1UqJy2risNLr+u0a5q5zgA2uBdeBUjAXXA/mgRvAjeAmUAZuBreAW8F8cBu4 HdwB7gR3AZSQuFtB3K342oq2p5pVEpeVxGUlcVlJXFYSl5XEZSVxWYmalaJmpahZKWpWipqVomal qFkpalaKmpWiZqWoWSlqVoqalaJmpahZKWpWSlxXE9fVxHU1cV1NXFcT19XEdTVxXU1cVxPX1cR1 NXFdTVxXE9fVxHU1cV1NXFcT19XEdTVxXU1cVxPX1cR1tdDkTDSjaKCqqfs/J6u5UtvgfZ7irHs7 buWZQzXIVIj/kXsqX1UtvsV7GmI8UbwiM0tsG/zU5ipwNbhG1ao2vNuGd9vwbhvebcO7bXi3De+2 4d02vNuGd9vwbhvebcO7bXi3De+2CS89UaObZxm+3TxsG8y5U/FIFI9EMh5xZ+HRjDeiI3gjijei eCOKN6J4I4o3ongjijeieCOKN6J4I4o3ongjijeieCOKN6J4I4o3ongjijeieCOKN6J4I4o3ongj +k/1ho62JPCG8gSxe5I4Um2LZrZFB/lqzPAVzfAVyeIr8v8YXxH4isBXBL4i8BWBrwh8ReArAl8R +IrAVwS+IvAVga8IfEXgKwJfEfiKwFcEviLwFYGvCHxFxJlKj09GZ2epnHY/s3pY9QEuX+79nDQz K2BmRYaZFTCz4n9Eb5eDp8DT4I9gBfgTWAmeAXXOw+TAw98qQ4aKqJmD9SyaqX3peEpQ2SJUtogI wmQEJlfLU5wtHF8Nm3GY3ELGboHJN+RFYipstsJmRIbYdiX75zitMBqH0TiMRmA0AqMRGI3AaARG IzAagdEIjEZgNAKjERiNwGgERiMwGoHRCIxGYDQCoxEYjcBoBEYjMBqB0QiMRnLucbbk/AQsAAvB IvBTsBiEwXLseAo8Df4IVoA/gZXgGdDktMJ0K0y3wnQrTLfCdCtMt8J0K0y3wnQrTLfCdCtMt8J0 K0y3wnQrTLfCdCtMt8J0K0y3wnQrTLe6lcZZAbO7e4dIJotnitnCyzyqRduiPvvoZY5yB3OUtsyn 4svED+lPk/SnSfrTJHt3SLKMeWNn5lPvpAzz+l4n6t0APgTtZN4HTpKeLUnPlqRnS9KzJenZkvRs SXq2JD1bkp4tSc+WpGdL0rMl6dmS9GxJerYkPVuSni1Jz5akZ0vSsyXp2ZL0bEl6tiQ9W5KeLUnP lqRnS9KzJenZkvRsSd8PnajveHACCABUyTcD/AjAgO9kcAo4FZwGTke7rlGfaLvfw9AJBj7Z3vNT 7bbMp9ptg59qD3Tv6U+PG1UXP59l+tPjiLyHbsy9u7iYbfc5T6i7ieucRuZ2jcztGv+p3e0xTiPz mkbmNY3MaxqZ1zQyr2lkXtPIvKbRV8Ts+wxwJpgJzgKzwNngHHAuOA8EAbMb32xwASgGF4KLwMXg EnApCIHLwOXgClACrgRXgavBNcz0NZc5sR8xGR/8NFCSzx5gghuIvPngTtYXO51w2QmXnXDZyXg6 GU8n4+lkPJ2Mp5PxdDKeTsbTSQZc73RLqoX7iSMx/II4fPCegvv9+Un1lwzHaT3q+y6PxPfHaTtY 3+mswuersKMGO2qwowbfu/P9GLbE5B1iAr4mK4iJHyu7YnqhOE6fBk4QY/WgOBI7Y9gZw84Ydsaw M4adMeyMYWcMO2PYGcPOmMgnGhNEYYIoTBB9CaLP/cuTOJEWJ8LiRJT71yNxIidO5MSJnDiREydy 4kROnMiJEzlxIidO5MSJnDiREydy4kROnMiJEzlxIidO5MSJnDiREydy4kROnMiJEzlxIidO5MSJ nDiREydy4kROHC/d7X7ji6sU4nSsPXr3vRnWN4IuZw1cXgeH1zGCoxnB0fAYz+RPXOWPdFrgswU+ WzK5FGKEIXhtZ5QhuG1XOfQT1hc77ZncaYfHdnhsh4EQDIRgIAQDIRgIwUAIBkIwEIKBEAyEYCAE AyEYCMFACAZCMBCCgRAMhGAgBAMhGAjBQAgGQjAQgoEQDIRgIAQDIRgIwUAIBkL4sB0ftuPDdnzY jg/b8WE7PmzHh+2Km2oxA27a4KQNTtrgoQ0e2hhnlHFGGWOUaFyb+TsiV1UbGWt0L4oaZaxRxhpl rNEcd9tHIA46QCf4GGwEXaAbbAKbwSdgC0iAT0ESbAU9YBtIge1gB/gv0As+AzvB5yjk36Ko383K rBo8vRJPr8TTK/FuHZ6tyyjkCjxbh1fr8GodXq2D2TqYrYPZOpitg9k6mK2D2TqYrVP1Kv1XXo87 z8tnnc0y4vTId5xe9VdcE+QjqEMtWMZ161i+R4ZuICP9YrK+Dxn2AmrQ6NT4msBa4CrHerABdPA6 yXKXE7MkMAHZac0CZ4OLwDwn5u9wOv2d4GOwEXSjLgfKSmejfMxJySeI22XE9B9Yfwa8CFrJ4BTY 6Wz2RZyUrwG8TKysZtnotGBNC9a0+N50NvreAh2sd7G/G2x1UtahTsI6DBwOLnE2W5c6m8Vo+aDj h4UaucJpko3OVfLV/k6YaJJtzlnyIxjqcG6R3c58uUUUyq39SdmDiu1yxul+x6+Pc+YKKSNiokyI ifTyD8LTFjg62P1OflhsgcUWxbE7ljrQCt53SjhqLmNp0WFH97nMsr6P06EfoNhtGTKeD8B6sAG4 Y0o6LZbXKbFywBhwKK8PA4eDI3h9mmK7A7Y7YLvDmsNrG1yrmO+w7lTst8B+C+y3wH4L7LeMEk5s lAbw2igdGOjoJEaRZBRJvOLGQxMeieGRGKNJ4pVO3VKWx/TvgP2B+3lEBP+/QB/RwHI1I2p0mhhN E6NpYjRJRpNkNElG08Roknin0zoJ64oYwVl7xop1FxbS82BxEouTWJzE4iSzz8edZ+B/nGzColex qA0rt4iz3P8Xq/yxlMhO4q+14iot3t+tfQw2ArdW9bL8DOyuTWvUX5uY6ntOTuPdk+VvOF8VqMbz jxCDteB3XOsJ8qWO9efZ3sBr/MX1J8tmdGcty7dYvgvaOBdaQgRtlmiJREvkVmccMTwX3yfwfQKf J3zPwlS9Ys2N6R7fa6y/3p8klk8jlk/ztfKasfmo1TCYgsEUDKZ8H/K6HYY/AnHQxXu7QYL3Jtm/ rT9pCSdqaSDPmWyNY3kQOBhMBFPA0eBY9hWwLGR5msqPueTHXGInQewkiJ0EcZPACym8kMILKbyQ wgspP/rnR//86J8f/fOjfcRSglhKEEsJYikxyn1Sho631qA2O1R+jB34lB2eS9izjAxcxt6N6SyE w3echkwWVpCFE+HwDnx7JPxNJAuX6gc6q/TvE30HiyP1ic57bi7378TfazjDOPJ4KWco5gwTZQde 6ma5hUjZyvYetu/qX+X/wJnn/8SZ7k84Nf7Pnenq7yAWUGsWUGsWUGsWUGsWEAuujbcRCy3EQous Zv0xFON36psSlpIRNWREDbbHVLQ9z/4Xed3A/ldZ34r9u5yVuo7NhzlL8XULvnazpIYMqcHfS8mS Gnze4nvduQ2fL8Pny/B5Cz5vwect+LkFPy/Dz8vw8zL8vBQ/L/UlOH4r793m3GZd4Cy1bgd3O0uV wqtPdmB2KZbF4SIBBwnFvVc+CBMRFC0hfiR3icm+jWK5daSosm4SVeIRWdkfU1ymo76YqC9mxDFG 7KrZOKUBK/BMWgeKGXVMZcKLLBs4ppH1Nc5U+Qp4tX+lbIbz11l/A0TB2v5VsoXlm+At9r3N8h2u 9y7r73HtNt6/DsTY/n7/AvkBy/VgA/s+ZNkOPnKkjLPs4PydLD8GXby/m2M2YdNmgBbLT9meBFu5 Zk9/XG5nfVd/p673x8jAqWTgVDQsrOcyW/M7FjoW1sexf3+WB7DvsH5X08L6JOcePOaqczFeiyld UxnaH/O9BT5g+3qwAbTjrY9AHKQzsRgvxdxs9KWcqb5e8DnoA7t4719Z9gPHmWqJ/qWWBmR/zDLI XpOlt3+BlQNGsT+vf5W1D8vRYAzbxjnF1vdZnwAOYv1g3jsRHMG+SWzLB0c6NdZRnGsymMK+o8Gx nOc49hWwPpVrFPL6JCdM9k9Fh8PocNi6gO1zeG2Da0Gpc481F1wPbmffnWy7i+Pu7ncrSjHKUIwy FKMMxShDsX9b/1J/CmwHO0Bv/1KUYSrKMBVlmIoyTEUZpo4KOFPFD8gxN7cSRFohkbaWalNMpE0m yiZn8ipBhBUSYWvpSNK11K2hllOD9xJUoRq8txLPrcRjNXgsgccK8VYh3ppMFSqmChWTYwkqkeul tXhpLV5aSyUqJpcSeKmQXErQubTQubQMqa1TwUnOStipgZ2VVKkaqlQNVaoGZhIwk4CZBBXL/d6X GmY3j5APtSpHYgM9lKtBxJAbLzHiJUa8xIiP2PB+CT5j8BmDzxh8xuAzJi4jo+PaTmFpu4SFLsXh qhsN6oarGNx0y0aRJ5vBW+Bd0EqH2MVyE9gMtmCV+xnI5yz7wBfgr8yvBNCABB5gAC/IAXlgNBgD 9gVot/5dMB58D0wABwGURT8UuJ8JRpxueO9G27rhPQbvMTiPoW1xtC0O326t6kbDuuG82xIiz9LA OHAQOBhMBIc6bfDfBv9t1hReHw0KwDQx1poOjgcnghngZHAKOBWcA4JgNigGF4LLwNXgGnADuBHc Icb6t4k8fwpsBztAr8gbxTnFdTCcwocJfJjAhwmqey+VvZfK3ptmluUmsBl8XVZNJzXIrI91y+n+ SoYP4LgRWCbKu4mlBKymYDVFTCWIqQQxlSCmElT+Xip/LxrRizb0UvV7qfq9Q1nl9dGgAHwVq6fR RRfhra9idw7H2eBakMU0epEiM7qJ7QSxnSC2E8R2gthO0EX00kX00kX00kX00kX0ohUptCKFVqTQ ihRakVKe+Q6eeVl129Vu5VG9X4y+q4Va20Jv1UOOu7H2Mqy8TF6jvGRVHvl7LCgElzg99Dc9dBMP UqWreddjqMzjLJdRh/5Ar/AMSKtOC5k1mQreQgWP4a8Kt7tEbZaiNhWoTQVV3a0RFUT9ZKJ+Mmoz 0dfYv9PXBF53u3iWHSDB+lb2b1NKUgGXFShJBUqyFCVZSgV3e96lKIhbyd2+t4JqHhPSVXC3SxG5 jHSlfG23nvg+G6YdfrB/WkOEwVyD6gFywBhwhNraqBibq7rlDqcD1grpCd6nB06IQo5fxfGrOH4V x69y+wLm4m28U+NdNcKjupr0exNudyNM914TZ303c9YYnUY7e+aK/bQknTZe0VIst6suuWXQ/nXw 684rC+FzmrNyyFgMJzlkPEfxejJwx+VRf+XZiAXpa7mf/LqWHymWi0Pp4fz0cH56OD89nJ8ezs+x HVy5mAxeSpwUksVLyeKl6rt0Oqgn9FNkcg2ZXJOe6an/O0UlBnmsj0PTDwIH83oimAKOBseyr4Bl oVNIBFPtwHawA/TSh7njjzH+GOOPMf6BcSdgew1j/3Rw7LucTzPjTqhxe501eGENXliDF9xvGksw /oQavw/1SXGWHlQnxTt6yOgUGZ0io1Mc2cORPfi51dnAERvYu4G9G9i7QXHXQu+comfeoe5PG+78 bfici0jb6SSJ9h36KGZ5Rzg7iNYd1kxmapfghUtBGes3g7ucHfT2u5jR4CvmxD1Co49cLjRer1H/ Jogc8kfo9Osp/WB17V71pJ+4kO59LuxJHzOZ3OZI2a+ybSXXT5JlSbIsSZa5dT1pnaCyJ4k9SbIn aZ3P6wuoxyUsb2d5F9vuZv7nnrmGM+9wzywm0/Hucoo5qx8NrkB73TwuxN4a9NXNYb9eKC7Xp4nL 0bkKzuhHxyrQsQp0rIIz+9EvNx/96FIFulSBLlWgSxXoUoUYpZRhHzCgCijCsCyvgOEKGK6A4Qo3 u0Ve1h2AmDv7V7P37Bk7s/URZ+Ze/LORa27kOhu5xkb8shG/bOS8G/HHTifOljhb4lSj3erlfmfU Kuwswc4S7CzJqFcJtpZwnhJsLcHWEmwtyShSCfaWZBSpRCmS5n4DlZD6JcTGZc4WPHsJkXKZ845+ hRsNme2f8KpXHdWljvLpxU5cv9DZol8ELnY69EudTXrI+Yi9v9Mvdz7j+FeFh6M62bqVre+z5T0i 9CJeXUzcEHtsbWJrSh3Xy5Zfcuyn6rrulT51r6vWPmYNJvR5vOdGquzNTgevbnReZW2tfqvTpV6t 0ss4t/s0Qo1XnwqvPtfZpl8Pr/OcN/QbnPf0m1i/2fk172jjvDez5VZnLVe/Ht7mMcabnZ+xpZWz zcWeG53bOGMNR96Ive55XQvc7e5ZmAXrj3JNukL9MTGJaz7hhNW/MTHanCUazLNFkfm4KFDPKvsN 2PMZZcut5cK2/sIywjL9TLK16llkHvX81S71NNV1nC3oPpmNuvsLMSHztK0a9U3c6W/M1jiiCO1O ClvbKqq0FMvtooosqCILqjhyKzPi7aJAyNzpmSfAjvraT76NZz39Vne/4Z+rm7nHY4F73QJxjLhf 1IolXOcBYYvnWF8FngcviFophG3s1EqMz8EXwja9osr8nqg19wcTxHLzIF5PZP0Y1mewLBJh8www h/WFHL8IPKfNNV/SzvLuI8LeBVqJd7E23xsGP4e5e0XYegibHtFKrEdBrTbXegw8KWqtOm0u4y3P nSHs3PPAbG1+7mWiKrdELIWDt3Ovxuqx4j8Yw8tgNWgETWANeE0UeCaLAjMPTAL5wH09BczCwhtY hkUBfnR9aLs+zL2C9+2nbVF+CMN4WI4TYf0Ejv57I0KyN8geIoG1EMe5r0IcFxR+Y6dYYnwulpjP iSXeBWCxqPWGYeARscR6FNQ666zHQJ2zLnc2nvHyjgBHBTkqOOT50rM5n+H+T2i2hNkSZosNW/lC z37ynDpm8BXHhDimXEwU/8b7d4G/gn7giKDnFHAqOE0E3etiacA0RNA8HpwFHgAPgofAbwEjZRS7 7fuNMw+u5sHVPEYUYEQBrh7i6iGuHrK6RVBZcIF61l4ZVtw/GI1VRGMV0VhFNFYRjeVYUIUFtSoa v0f07Q8mOL1EYRVRVzUQdVhQiwX1WFDv/Tk9tYoyUcXVq7h6PVev5+r16cgSy4msciLLfSpgM5EV FuO5+hKuvoSYL+cqS7jCEq6wJPvMnLGWM9YOnvFJOgP3rNM56wzGc5JYkhtU43OvEB5yBTfjy4m0 cjK+nGgrV888jDDWU7WpxGAhmAb+F+B82g/BKaJPOw2cDorAGeBMMBOcDS5DKeaA6zi2FMxj/SZw M7gF3Armg9vA7eAesAAsBD8VAW0T+vMJ2CK6sK4P6/q0HrFc2yaasbIPK/u0Hbz+L9FMbvShUc1o VDM50qevEV0eos1zASgGF4KLwMXgEnCp6PNcT1beCLDJUwawx4M9ZpvoM3vwHNcwuYZ3Ih48BBxO FIxn1FWMuopRVzHqKkZdxairGHUVo3atDWNtlVJPzoK1NtZWuSqKtTbW2lhbhZVVWBnGkiquWMXV qrhalXqCQTtK2aueo3CYZjrztIPBRHAIOBQcBg4HR4BJIB8cCY5ypmuTneme0515niJwBjgTzARn gVngbHAOOBecB4LOPLMVfAjawUfOdDPJcitwnHleru8dBcaBOc486gnayUjD5kvE3z7kSL7KEVe1 R8gR6RfL5WgwViwfyJesXElkVLvKPIb1GSyLiPAzAPnjfpMCkb2cnEmgzuV75MyT5NLQCC/Pyp8y orue6C4Xt4j78N2/oiG/QFWXgF+y/iuwXEwQT4HnwCrwItsawH/wrpeUmpej5uWoeTlqXo6al4tX 2N6sVL1c/CfHvgGiYC14E7zHtTqoohs5potYNvD6JpbZkZGJCNiph5162KkfqLEqKiaLcg/VwbNI FBjUYGM7IHqMPnQPTVRPM9WI0VyWeUoTJpgHsH4Q8TuR9UlsywechypTbh6rnn5aYJ7AMv0E1Crz fN5Pfpjkh0l+wPgE02b/teA6UArmAvKEClVu3sj6TaAM3AxuAbeC+SDM/p9xXAWo4fUy8Hs0twyl 86G7SwCcU2/WDz5N9S+sp5+kGrRWq6enluWiNblnAPqU3LPBFaLc/1N4NLC6eXhVEweIFsV3FXwH 4dhGL2z3OWVwWGv8VY3ZNmdp4xlvvXku6ygs466i+xmLTTY22Zy1j7M2Y5NbgYo4ex9nb8YuG7ts q0nY2GCL/TlzFR5sxoOuAjXjweZsD6q8HvAi+Z2++m62R2ChaCQWRB5XCmZ6sHCmB3PrfxFntzm7 zdmLOGtoD0Z84mH1FPkm8TnoA1+op5c3mb9RTy53n1beJPKG/H+Z34lwzuPgCVGeg8/c/yfjO0wU +Q4X5b5JosyXD6aIoO9fREBI9X/Qfs/avn/Tp6Q7nenZn5QyG5nObGQ6s8MjySmT/TXZs0b217C/ Rhz1DTWmSlXKvevMEnSmDJ0pUzqzYA+tKcvSmuVozfJMNV2O1oRUF3iSuNvtf4bV6nLhw4IiLCji jCHOGBrWAbndzQRxiBrPnmMJDxtLrdLLoWMZ7C/26CuGdwB14lnsnZOxd8mw3qJB2TuiJVqCKjXM GqzY3eUMMDmCWn+JSoe+1JKLUOkAKh1AnQOocwA1DqDGAdQ4HyXOR4nzUeJ8lDgfJc5HgfNR4AAK HECBAyhwAAUOoLgBMqhsBLWtZTS1jKZ2eK6iGGWobj5qG0BtA6htALUNoLYBlDaA0gZQ2nxUNoC6 5qOu+ahrPuqaj7oGMuoaIN+7yMzyjLoGUNcA6hpAWQMoawBlDaCsAZQ1gKrmo6oBVDWAqgZQ1QCq GkBVA6hqAFXNR00DqGkANQ2gpgHUNICOFKAj7nyhOaMjrgI0u8+fRkEDKGgABQ2goAEUNF/4B/UE LYGFMCyEYcHVFFdL7D105JBMvtUOj4y9xKSbX7UqKnbPuobHZ+IrOtQyoqI+05mGB2dVB2bq5tdW Xbd+Uh+LlEeGqu8Aa2n13a28BShvgcueqjWjuWLRHurrR2dGg7HAZW23Ervs1WbYq1XsWcyIm76W Ek9mlhNilhNilhNilhNilhOSfi1PjgZjtTxmPCFmPCFmPCFmvx5mvx5mPCFmvEXMdN2ZT4iZT4iZ T4iZT4iZT4iZT4iZT4gZrofZ7Xjvvaz/nFqzRM07+pjZjmdmuy8z26D1tFv1tO8z8wnhh2b80JxL f8sMKIQv1uOL9blXaofgiy7miwNq6CrhlWSbpp6/7Rk2gysSMzMdl00u2+SyTS7b5LJNvtrkq02+ 2uSrrSr4mywHqni6WxpayYd2QDY5aavqnu6AbHLSJgdtVW9PGLniD+l0bHAtYGZCLtrkok0e2uSh TR7a5KFNHtrkoU0e2uSgTQ7a5KCd6Wjsb9pBZHU2NnmZ7ig0dT+mFK6CSvd2d6fD9S+Y6UaDaGAQ DQyigUE0MJjVjQZH0kJ4DQ/pRjUxFo6De+lGB9V+eFahjcGsjjSIP4L4IzigkSrjNHyS1smg0smD 1P2OIFoZRCuDaGVwmFZmd6JB/BPEP8ERtTLdhQa/Qi+DWV1otm4GM7oZyCjA2xkFeDtbAfBREB8F s7QzKHzZme92oVgc3CPjdTJ+w0AWiANHqqmDypldQ7PVcu/z+HT93F076/eYv3vUvaPlu+8fiRP+ Wc/tNf6P0l+39y7KeHiJGcQj7v2qe8Rx6p4VkY43ivBG0Qj3ruoH5wjPqnlCfcZLRXipKHMvq83q Ut2ynbmnVcuRjxHjPqqODZdheLTh0WZPLXtq4bAW7sLpe5YD97lGvseVdU9mevo+F+8KfuW7GnhX A+9qQEmDg+/6IdHQJx4Q9Wi9ex+pj6joIyr6iIo+tN9G+22030b7bfTeRu9t9N6925lnfIGOGepu 59tETh+R04f2h4ievoz+2+i/O3vrMxdy7CLwAK8fBA8BunxqgU0tyPMuog4sph6ka0IZNSGEF9y7 nkSdlmc9Cmq1KdSGKdSGUKY2TKE22Izojdzz4GM2tQAtzaoN04jAHnW/TlUxt2INq1QhZenwKjVQ odJW5WFVXpZV5apSPaqq1SFYdIiyqI6lW6lma3nDKtQUVaFmwG8YfsNopo1e2uiljV7a6KWNXtro pDs7LxjQQ/eucrbuDZuF2xmPVyl982J1HnzuT8ZOBJNYzwcch7bZjDJMRttktDvv26m0bY66v2uj TfaANqn5RboWhxlheDBC07rUrOaFRGtGn+oH9Wm6uqtaxajL0CY7c4/D7Z7LxNFEWBgfBIioAH4I EFEBIirACN1+qYsRdjHCLvwTIMICRFiA0a1ndOuJsjC+Cpg5LI9neRZYyPoi8ADrD4KHwG/BH1DU BWI98d9D/PcQPW6urWck6xlJHyPpw/o+/BRArxqIGnfe04O/Alhej9Vu79CH1fX44AHUceQeyEMP 5KEH8gztgUQfFvdhcZWKLjcvsvughWxfBEbqh+5wOrIjTUXZQyhLOtK+yPRFh2T1ReMzfdEr9ERh RlKVFXnvM5LmTG/0jijMjCSYGUlw90hEH9z3wX1f5v71kG4uM5LgsI4umDWS7HvaIXVP+w5nHT7o I3eCw3LH7fLKskY10O2NZ1RFWaMKqm7vNOpJelQ56p738Hw6jFHVqhENjEaI9UNGtOdoajM+KVIj WcjrReC3max+SCnmcMsG+caq1RmuaxXXlzEPKAFpnteLf/myT1ky3U5+VrczgfpX/g1nguXupzUq 40f6xMata5lPbAYzeom6F/N2pm4FsjqLIjUrcz/NOS4TIXYmQuy99Pv2XmLdzihpKBMhdlaEZOt9 KKP3rrLaGa0vz6jq8MjYraxP45u0zmdHxfiM1nfhgy5X64Wh/g6vwVmb/bdyQjImD/MeIfLEPsIr viPGCZ/4njiRV7PEeeIH4kIxj0p4h1jEq8V0pyHxlkiIJ0VS84smbbQ2RnRqY7XviY3aAdqPxBbt HO1ctga187XvaBdrN7HvLm2xNlm7V7tPm6b9VntKm67FtW7tdG0zv2drCX7P0ZLaVt6X0rbzzl7N 0WZLKb3a5TJX5mrXyFFylDZH7iP30Ww5Ro7RrpX7yn216+R+cj+tVI6T47S58kA5UbteHioP1W6W h8sjtFtkvszX5suj5FHabXKKLNBulz+Qhdo9cro8QVsgT5QztMXyJHmydq88VZ6q/W95hpyp/UzO kudp98vzZbH2K3mRvFR7QF4ur9eq5A3yBu0JeZMs0/5d3iJv0X4v58v52pPydnm39gf5E7lA+5Nc LO/VnpGVskqrlw/Lh7UX5CPyEe1F+Vv571qDfFI+qa2RT8s/aq/IP8k/a80yIiNai1wlV2lvyhdl g/aWXC1Xa+/IJvmq9q58Tb6mrZNRGdVi8i35lva+fEe+o30g35Mxbb3kV4vLj2Rc65CdcqP2seyW 3Vq3TMiEtkkmZVLbLFMypX0id8pd2hbZLx2tR5e61FK6qZvadj1Hz9N26GP0MdoX+n76d7Vd+nj9 QK1fn6hPlLp+qH6o9OhH6JOkoRfq06RXL9avkD59rn6r3Fd/Qn9Cfl+P6lE5QW/R35QH6Zv1XXKi 7nhyZaEnz3OJPMVzmadU/tIzz3OnrPYs8iySvzdOME6QTxozjJPlH4zTjDPlH41ZxixZZ5xrnCuf NYLG+bLeuMC4UP5f4xLjUvmccYVRIp83rjKuki8a1xhzZINxrXGtfMm4wZgvXzZuN+6Urxn3GAvl G8Zi4z75plFhVMh3jX81HpLvGdXGv8mPjUeMlbLLiBgNss94xVina8aHxhZ9rPGpsVU/xEgZKf1w Y4fxuX6EscvYpU8xHFPTj4aeHP1Y0zKP1aeZU80f6FeY08zj9SvNH5kn6bZ5inmqfp15pjlLn2vO Nq/UbzSvNh/Tf2w+YS7Xnzf/aK7QV5vPmPV6k/kX83m92WwwG/So+bL5sr7WbDQb9RbzVbNZf9N8 3XxDf9t803xLf9dsNVv1VnOduU5vMz80N+rrzG5zs/6RmTS36Z3mDvMzvdvsM/v0LeZfTUdPeDWv T9/qzfXm6ju9o7x5+ufe0d7v6F94x3kP0/u9R3gnefzeY7x4wnui9zzPft4LvSWefO9V3lJPgfd6 7w2e471l3ts8J3rv8N7pOdX7E+9Cz+nexd6w50xvhfd+z1neeu8qzznel7wveYq9r3tf91zojXqj nou873rf9VzsXedd57nE+773fc+l3vXedk/I253j95TkHJyT77kvpzDndM8vcy7N+bHn0ZzqnB7P Szl9Ps0Y5zvGd7pxkG+O7wZjmu8p31PGj3wrfCuMk3zP+J4xTvY963vWOMX3Z98q41Tfi74GY6bv ZV+TMcvX7HvNOM/3uq/VON/3gW+TcYWvx9dj3ODb4fsv40bfZ77PjDLf575+42ZLWtK4wzKsHONO y2/5jR9bedYY4x5rvLW/scg6yDrcCFuTrMnG/dYx1jHGr6xp1jSj0ppu/dD4tXWCdYrxgHW6VWRU WzOts40aK2idb9RaF1gXGb+zLrEuNZZZl1tXGk9ac6xbjKete6yfGKushdZC4wXrPus+40Wrwrrf aLCWWL82XrYetB42XrFqrMeMqPW49YTxjrXMWma8Zz1pPWm0Wsut5Uab9az1rLHO+rP1nBGzXrAa jA+tl63VRtxaY71qdFpvWFGjy2q12oxN1gfWB8YnuQW5M4wtuSflnmzszD0j9zyjL/f83Nmmnluc GzKN3MtzrzD9uVfmXmXm+T/wf2CO9sf9G80x/m3+HeZ3R4lROr2vnPEDtF6c1Ht2k5gtrhb/n/04 63b/O7DmbOP3dud11lz83IXTm9l/1T/4+g+AR0fYvhbEso9zlmHTSuds9epTZeenX3rmHYNrHWl8 Oz/OJyAJOr/Zu5xV/H7ytY9/V/277ZtaN+K5Eu6vWutKn9P5GOBhp/1vPOO2odbtaaeT+kdZv7fr j3T23XG913cmdp9h8BxjVQ6oiHG6v+S9qZG2jbx1qLX8bnI6BmLS2f5VVu7Vgm2u/enczHg0Mbgv scfRiZG2/qN+1Nn/ppEMeGkEH6TH1D0QPXuOYECXhm4beeuQI/CT85GzLqN/2wZH8I35cRa6muQs 3GMEmTWu863F/df9GaqAzinD9s5zTGesM0+tM9eBFffftWKCer3OXUcxenjVM/iehLMZRV6m1mtG uGINWp1wNU4oX7pe5rcmw/efnSbXIn63qX9dtZ/9JfY3caa1nHGdOp9wDsvat24gW/fOs/L2S2rN Vev/BK/t/Wp/3486+5tg0zd6Vy8sbMiK0bEjHJNVpeFjXXo0f/+PunZa7Vx2nsdvTYCK42z5yvcm vnFt1f5GM7/1H1h479vsFL79H2er8wr+2/pPtuKlf9B50lox2AVmrY0c9yPkzLfx4+pdWocyP/lc uYBlwR5Hbtj9ryhApTa4useWZax1uNtdBXXVjx9L3VH6b/K+BD6KIvv/VfV09XRNLkIOQm7OBBII JNwJR7gvATnkktMTEf2p6KoInqvuoSuKouK5yIruCrpe4I3osuCi64nropwCLqIgIgqk/996M7kn ISGgu59/12dq3lRXV1V3V733/Va/qS7NXaWcCqlplUsvy/EBwkLvynJtjHH9JOLXwpS3Flh6IyP7 jcc5123lcUXJO917F7H5DAt+QukLay+vvps3Dp8La2pXhd9dQ2HaccozdmILS/Oh49az/lroZXq/ Lcsxv4Et/pu33Fsekg94Ed5vvWLvYS8MczR9qMKVbRf6FAfbyfr9f0gXVUVOQG1rvTW14eefY6vI Ifl3LQi1Wp/a6D1zvBFSfn5mnHmvnarzLe0N3iu15tpbivRCunMXNM399ajlbY7DaKCGbN6zIURk tMWO2s+h/GqHNE87LzY4LsLrImay0WWHx1FFK5B1ss4gtCWFStdV2lzaoiDO7RrKG2oHdFJMyVGj x0qRcgUNPR99rHKvi4N+D5azBPqhsAZ0zbiac5TWuo3RdpAvreS4nAlu4+u4l8s2tiqLqtjKIJrk zWD+mFIpaGtgKzqaOJT3QDAOz3R/rq12dO2pKr/PKzlQ4nnnsfyf8jgo1XwezILM9z/C7PuHSQWH 3FI5NfS9x9tT7Yi+VX5/W+nX2oqooqSW8wvdgf0Vf3vfeQeBAUIM1lsX/Jyajdnah2HSa+DO1Wdh glqyVFfiGu7y3mfJ9OI3g5zCe4D7bfBcjfRZmJI/C59a2h4E5vjel0EOG0r9M+r7I7DyqmpHrizl mOXzovxhtujt9D43cfizDJXwZZm0m/XvKZpv4WtU73kFb5JBF94klr8oj0ul0nnBX3Lj3lUJFVXa +xIj5pfqVeIvqKfCoIp3ofVvNbawnuWc1HvjLarye0steavYa+8cr5+JWX6e49fL9j3P46TmMZJW 456TunEvWVn2q0WZNWNMAJusvJjQnN1C4NQlwWAYnDfLe8y7jWebnsOv54JaGb9X876gXhgWpsa1 CJu8YWyvCznlFk5jRuRNw/3bxCnzEbYZawqbvCVU+tqKrQ0dW4xjWuCb66w041WFoQSfPJQ/fzAS 675tpfPiZkbg1M0K1Dj73gD24m3leDU/lThEJ/EZTujKbKo4mpiJh0Xup0x/H/fJxHGOXwOuEYbZ H/e4jaHP2obVHyotDJsCEgmbejLqO3kbNEAQi8eE2WdG6DLkuAV3Kcv0C/y+A+PwxtCRy9AvTZ5b EJYcd8ZhYekMSWiGvYLuaPBcQwNHBEbCZoR6aoYKzGJtQ/sxPXECR4Q7pr7lPFHhc8IbMKTRrAeP n5ManWQUklaF6/6CG1Du5pM9Z1DvNnxdw7zpB8TPWyulflDxN8+b7q0buvrvnZPDOaw3T57+P9zO Cn0avjVQF5Xdg19EF3ELGmoPPvI+DMfsj3PU3jKevNYw5IZu4UZicHxWfbJf5r1Rnh7Hoe5bfTVo YT3zV93SmIV0rLWcjtWfJJ3E7VSW/d+y3V2HPCMr/eL5JxpwEuot/ZzwBqv1OaWZp/Jh9m0rnxXj 30Hfn5Nkk7yu/0Wo4lBVu13vEr5tYBPS0IIdYcrdwU8xqqKKMDlPrFZ+vtDgexDU5N63wWc6Vfa9 bVLRz0pnYIPzsaGcVee061BXJVzkFXPrGzzT4/3L+xdj7DBP4LyNPPtedg9Cc7uls+87G9hzxp+c M6i1jrC9O5znWh3Lq/NMRWUvNVzf/cbvxcyZQXqWZ3MWerPLn+R705D+ZZhyvqwhtewc0Ac/Aipa 7v3R+2MoZY83yXvEu9R7zbur2pHGq2l7hSeA0/AZSmX+at6uqk9zeathpJT5hEWHng9Gh8kUXeXZ IYXP6e0u8xTcGhwtZVev+qyRrpZSWkp2yVFPhWbfl/ATCY7NnCSkt0M+XbsqlwpmMy3kZxdu1nEh wjbvMp7NCM5tGr/ihcG5IaQH5y43AplxjF8p4e5aqLSNXjscPcz4APLvmAr7VnNPyKOQD3joyVj5 3TKzSp/Xgv9+rpnftRVnt2DR0kJPPINXp6jkQMmB0D14mq/LC97L3st8D27na7cpeK/LP9yPrgp5 Hp4dpsZl/NToRhy7P4gqvCchrww9h72aPSrNzO8yhI3s8d6bn4VXelZfVtpCXP9lnP9B3htbYd8S vqeDKfQ01vt3eVwqeVuDc6dht5/rHmyseFYYv5Vn32d4Lbwkbx7LLxjvT8RmHJin3Su9ddAY22D9 S59l7i1D/4tD3lMLwtRo7twObxHfpeDs+7qg1yjLt4Wej28MzdKbPnIaj7RDFMbvt2ymfm1oBjq7 wr4qM6fGR6Q0LpW8g3WaEzqlW+XnCbXmrPgfkDg+e34yil74AbDAB1XHVIXcVcqpIbX0uWtw3n2T 97yZQQ3tNfp0WfWryvtWs3/EfDqul9r/2ha64mvR202PfMv7pMac5fp1NbTvalzDsDjTe9fLPfG2 QOsb3+xtrLW4Pfh+y3ur1uNCdyykiZbVqa7gE7ea/ARWh08/bqnLqPwp2t5gLZwWRk80dDM+k1W2 tuVx3cdcmJJxrHnSGg6vH/fYYH+qEwI8cYRZa6l7q3xvDN2LOjznBmpYyZZuczhvjlCeUr/TyWX4 oxLn9aaEvreGQ0l12dh2DsMYMONgEY83bg++/1brcaWsKfg8qdYxU3ZMMG8NrL3+vgGh49ZS2bM9 Zqjzg+05FeMgbP2JiK5hKeIkFz2lQi0ry/r7LIRp+AQ1kCr5sGQ30JEK90yvrpsXUfJp8B5Co4bx vDvu8dXqrrk9FZ/p8+9xJUcNWgr6Cv73bDW3p+qzT9yD3SUfYhSpkm8bUF9Eaf+BXphSe95wW/W6 a25PmHuw+3/7HpRvJb+g73U4/8Xw7TEa/eRswP/G8+WA+ddytX0b+L/Muyrz9dKcIX6xre7zqIw3 arLUkuaSj4wdOo1G0GAaRdfRULqBFtI8uote5NXNN9LT9E/aTW/TVwif016EL2ifkLRF2CKCvhfR ohEdE41FL0FiqDhN5PL6IB3EaDFb5Is54gYxnFcGmSm2ip3iYrFPeGIurwByM68A8nteAeQ2XgHk dl4B5A+8AsgdvALIQrM+hbjT2uMbLxb5JvkukbbvMt/lMtW3wHetzOBVJ5rZPe2esrnd2x4gW9iD 7EGyrT3EHilz7DH2WJlvT7AnyE72mfYlsjOvKzHMvsq+W46wF9v3y9n2g/Y38mKzWoRcYx+0D8o3 7UP2YbnWrBkh/2bWjJDrlKUsuUFhk+8orVLlP1S6aie3qjyVJ/ebVSTkAbOKhDxoVpGQP6rBaog8 YtaPkMfUdDXdCqiZ6lErQi1VS61hapl6whrOa0mcrp5WT1tj1F/Vs9ZY9YJaZZ2hXlIvWRN5XYlJ 6nX1hjWZ15WYwutKTFXvqHes6eo99bE1Q21SO63zeS2JK9TXar91lTqofrIW8CoSv+ZVJG51Ak6U tdBp5MRad/P6EYvN+hHWMrN+hPW4082ZYq0wK0dYH5mVI6zNzhznImuLc6lzqbXNmevMtbab9SOs Hc6tzq3WLj1Zn2ntNusjWF+Z9RGsvWZ9BOtrsz6CtU/fpm+39us79d3Wd3qxvtf6QS/RS6wf9XP6 OesnvUqvso7ol/XL1lGzGoJ1TL+l37I8sxqCj8xqCD5pVkPw+QIdA/k+O9ApUORzAn0CfXwxgYGB wb5GgaGBEb64wKjAKF9SYExgrK8pSfEDerCPepCNYJFCsMlBSCA/gkMuB/OfpQBCBEIkQhSHGJ5X i8V3DNIbIcThVyyObYzQlJ/QJVA8Qgq+E8DXExGKqAlCBiUh9EKuptSHkhH6IlcKNaNUBOPH1xqt yqJstKENtUOr2lMeyuhA3ZDSHaUEqCcNQr2DaQjaMhQhBmNxGOo3ozEWo3EM6h8LTJFAUxEcmkYz UMNMOhctOY9moYwL6DK0ZC79Cm24EqO2GXDNAtR+LUIcRvN1OPYGhJZ0I0Ie3YTQin6NkEs3I2TR LQjZdCtCG/oNQkv6LUIuxv7vwBV+j5BDtyHk0u30B+y9A9ohD9rhLupEixDM+0fupi50D0IuLUbo SvcidKP7EEbR/QhdaQlCd3qAlqGEP9HjqHc5/QUteQqhNa1AyKWV0DhZ0DgvoyWv0KvI+Rr9Denr 6O9oyXragJa8g5BL/0BoDc20EfI/6SPk/Bg6KY+2IGTRVtqOtu2AzurMOqs966wutI9+QP7DdARt O0oedYW+ktQdWsymPKGEIiEwaNCn/MJPPuEKl+KFFpqUCIgA+UUE9J2GvoumSBEj0HtEI+i+RtB9 6C8iTsQhPwIliQSBfiMSRSIliyaiCaWKJJFEaaKpaErpIlkkU0+RIlKot0gVqVQs0kQaZYp0kU7N RYbIRkvaiLaoN0fkoSUdhHnrSL7ogZRC0QttGCqGoQ3DxXC04TRxGtoAnYt4tBiHlpwhpiH/dDEd +WeIs9CGs8X5aMMsMRttmCMuRxuuEFeh9qvFfNS7QFyHeq8X1+PYG8QNOPYh8TCuySPiEcoWj4o/ UkuxVDxGuWKZ+BO1FY+L5ZQjnhBPImWr2EpDxTaxnfqJHWIn5H1iHw0T34hv6DTxrfiWhov9Yj+N EAfEAaR/J75D+kFxEOnfi++RfghjeKg4LA7TQPGj+JEGi5/ETzRIHBFHaIg4Ko4i/Zg4hvQSUYJ0 T3g0BPZDUn9pSYsGSJ/0QbalDVlJBdmRDmRYF+porAvlG+sCGdYFMqwLZFgXyjfWhUZae6yD1MP6 3jpKjnXMKqEIy/PZlOBTvgA18UX4IinDF+VrDDnOl0DNfIm+ZtTS19zXhrJ8bX05lOvL9eVTnq/A 1406+Lr7eiCl0NcHcrGvH3X19feNJOEb5RtPCjZsOsX7ZvjOpUTfeb7zKd03y3cR5It9l1AmbNtl VOSb65tLXXyX+y6nNLO6Ekq71ncttTPWjixj7SgB1q4P4mK7L0XY/ex+kPvb/cmxB9gDyDVWkHrB Cg7B3qE2dIs9zB4Gebg9nOLMmkzIP8IegZSR9khqaiwlFRlLSS1gKc9EPMWeQt3tqfZUijKrNFFb e7o9HfIMewbkmfZM6mGfZZ+FEs62z0Zp59izKMO+wJ6N9AvtC9GSOfZFFLAvti9G7f9nX4I8l9mX oeS59lyUfLl9OfZeZV+F9lxtz8NR19jzcdQC+1qUeZ19PfLfYN9IKfZN9q9R8s32zTj3W+xbsPdW +1a05Df2b5DyW/u3KPN39u9Qwu/t36OE2+w7cOxCeyE1s++070T6XfZdZNuL7EUUa99t340zXWwv xrH32vei5Pvs+5Dnfvt+HPug/SBqfMh+CMc+bD+M9EfsPyLnUnspSnjMXo6Sn7CfQs4V9gpc55X2 SpzF0/YLaNWL9mqc6Uv2q6jlNfsNpKyx38LZvW3/HUettzfgOr9jv4vy37M/pEL7I3sTWvKpvRlt +Nz+Avdri72V+tjb7O3U195h70Abdtq7cHa77T0o8yv7K5TwH/s/KGGvvRflf21/jRr32fuQ5xv7 G9QCHEN5BscgPmQfolz7B/sHyIftw5RtMA2ZdbCI2kLhCcozyIa6GGRD3YFsNOKAisDeSBVJLVWU iqJcFa2ikTNGxUGOV/GQE1Qi9jZRTShLJamm1EYlq2TKUSkqFXvTVTpKyFAZKC1TZWJvM9UC+Vuq VsjfWmWhnGzVBjnbqhzqpHJVO6QASyFPvsrHUQWqAHJn1Q15uqvu1NXgKsiD1WDkH6KGIOV0dTry jFZjkT5OjaNW6gw1CeVMVlNRC1AXZQN1zUTtZi3plup8dQH2zlZz0M6L1CWQL1VXIv0qtQAlXKtu QMk3qluos7pV/Q7X5PfqDuRZqO5EXXepRdRN3a3uoVFqsYKNU/eq+9HOJWoJSnhAPYD8D6oHkech 9RD2PqweRvoj6hFqrx5Vj1I7g/yQskzBAqo/qT+hDY+rx1HCcrUc+Z9QT6ANf1F/QfyUeoqkwYUU b3Ah4hfUC4hfVC+ST61Sq8hvMCL1NBiRooERX6fGZgUy5AFSpCSDFCnNIEVqblYgQ/y++ogizTpk JMw6ZMj5qdpM6epz9QVStqgtpNRWtY202q62o8wdaify7FK7cewetQfpX6uvUcs+9Q3yf6v2I/9B 9T3yHFI/ULI6rH5EaT+pn9DyY+oY4hJVgmM95ZExqj6Kd2zHpkxHObCzDjbyOX7HT40c13Epzax2 RtKJcCIo3Yl0IpEnyokiBeTaiJKdWCcWxyY6iUhv4gD3OclOMkpIcTJQcqbTAjlbOa3I77R2WpMG uu1A0U5HpxPK7+YUUmOnyOmNnH2cYkpy+joDUOZAZyilOsOcEah9pDMG9Y51xlFP5wxnPPV2JjgT qdiZ5ExCvZOdKdQcKHkack53pmPvDGcG0mc6M9Ges5yzUcs5zjko+VznXJR8vnM+ap/lzMJRFzgX oF6gasozqBoxUDUVAFXPo1znGucaaunMd+YjHQibcg3Cpngg7Kshz9PzKM/gbMTA2Ui5Wd9MbfUt +hZqqW/Vt0IG5kZ8p74LeRbpu5EHyJs6GeRNnQ3ypgKDvKm7Qd5IeUO/gXiNXoMU4G8cC/yNY4G/ EQN/Ux7wd0fKCuQHYNGAwjtRdqBzoAu1DHQNdEVKt0B36hToEehBnQOFgULqEigKFFF3g9SRZ2Bg IPIMCgyi3MDgwGAcOzQwlHICwwLDkDI8cBryjAiMQB7geJQwJjCGRgXGBsYCH0o5hdF8P8bxMYza Y0J4PZZxukHkMYzF+zMWH8BYPJ6x+CDG4kMYiw9jLJ7EWDyFsXg/xuIWY/EYxt8xyGuQ91hg6xhG 1f0ZVQ9gVB3PqHoIo+okRtUpjKRTGUlnAEffTJmMnnMZPbdj9JzP6DmP0bNZMf42pBjcXADcfAfy L0ToQnciZDKGLmAM3Z0xdCFj6CJGz70YPU9j9Nyb0XMx0PMDOJMHEVLpIXoM8jIg6VQg6eUo7Ql6 Eij5z0DSmUDSK4GVn0bIpGfoecgvAFtn0iqg6/b0EhB2O0bY+UDYr4GRvI6QR2/QW5DfRsgD7v4b 2rYOIQ/o++9IX4+QDwy+AenvAHnn03sI+cDf/0TK+7zW7ocIBcDiHwN5f4KQSZvo35A3A5dnApdv xd7tCAVA5ztw1jvpS3CkXUDq3WkPkHou/QdIvRBIfR+40TcIRfQtfQ/5ELB7EWP3XsDuR8F2jiH0 phLg+D7CLNVSLCTQfLGwhEUFjOkzKmD6AGP6aGB6sEDG8dEiUkRBjgF2DzB2j2bsHmDsHs3YPcDY vRFj98aM3eMYuw9k7D6YsftQxu5NGLsnA7tnAK9nikzU20xkQc4uQ/MSaD4HJeeKduSI9kD20aIj kL0LZJ8PdlEgClBjJ9ENcndg/QCwfhGwfk8g/mjRW/SmCNFH9EF6sSgG+u8r+kLuJwZDHiKGQh4u RiI+XYxGPEaMRf5x4AMB8IEzUM54MR7lTBCTIU8BN4gGN5iBvWeBIQTAEKDFxDniXIoV54EtNBIX gC00FheKCykBnGEOzv0icRnkueAPccwfBoM/XE1NxTwxD1fgGnCJpuASC3AdrgOjSGZGEWBG4Yob xY2QbxIPUl8zGxRiDhOZOZzOzGEiM4dJzBzOZOYwmZnDFGYOk5g5nMnMYTIzhynMHCYycxjLzOEM Zg7jmDmMZ+YwlpnDGcwcxjFzGM/MYTQzhzHMHEYzcxjDzGE0M4cxMkJGUFcZJaOom4yRMZBjZSzk OBkHOUEmQE6UiZQuU2QKKZku0xG3kq0Qt5ftKVH2kD0Qj5fjaYKcKWciPkueRbY8V56LeI6cg3ie nIf4dnk7nSbvk/dRS/mIfISy5FK5lEbK5XI5NZdPy6cRvyRfwt5X5CvYu06uozZmzVjEH8oPEW+S m2iU/FJ+CXm33EPZ8rA8TMMtbNTCrAdLrSzXchFrS1NrK9KKpBFWrBVLzaymVlPEyVYy9rawWiB/ K6sV8hheNNXqYfWgdGueNY/6Wtda1yO+0foN4lXWKsSGNfUDO2oMPmN4URJ4USKl+pqAHaWBHTUH n2kBjpQDjtQWXCgHTCkPTCkX6e3AlzqDL3WC3NnXFXI3cKdMcCfoZl8PMKieYFBFkHv6ekMu9hVT b19fsKk+YFP9waYGgFP5wKlGUcB3OpiV3zfBN4EifRN9E5EyyTeJon2TwbU0uNZMyGf5zoF8LnhX NHjXeRTnOx/sKwHs6wLIs31zIF8EJhYHJnYxmN7/gY81ZT42gPlYIfOxxr55vvko37CyPGZluXYv uxdQuOFgMcy+ouyB9kDIhoMNYsYVBcY1AimGZQ2wz7DPoHh7vD2ekphxpTCb6sc8KoZ5VDzzqH7M oyzmUUEGFcOsKca+0r4SZRrW1I+ZUgxzpHjmQinMhfoxC4phFpTELKgfs6AY5j8DmPnEM/PpZy+x l6C0B+wHsNcwnyRmPv2Y88Qww4lhDhPDvKU/85YBzFvimbcMYt4yhHnLMOYtScxbUpiZpICTHATD +d7+njKZk3RmTpJp/2T/RPn2EfsIdWFmkm97tkcFxvhTJvOTDOYnhcpWNvVmllLMLCUTLCVA+SoC XKWAuUoac5UOzFU6g6vEUJFqBMbSE1ylCfYmqSSg8KbgKu2Zq+QzV8lkrtKRuUomc5X24CrNUGZz MJY0Ziw5zFg6MGPpzIylAzOWnsxY8lUH1QHHGt5SzLwlVXVS6NXMXjoze+mjeqgeyFmoClFykSrC GfVSfZCnWBWDA/RVfXFsf9UfKYPUIMSG5xQwz+nNPCeVeU4G85wc5jmZzHNy1DQ1DbJhO7nMdtoz 28kH2zkfXGKWmoVyLgDz6QDmcwnSDecpAOe5Bm2bD+bTBcznOqRcr65HnhvAggrAgm5Cq36tbqYe 6hYwou7MiArBiG7HVf0DeFFP5kW9mRf1Yl40jXlRb+ZFxcyL8pkXFTIv6sW8qA/zolTwokfRWsOI UtVj6jHzThgwonxmRMXMiHqrP6s/oyUr1AoKqGfUM+Akf1V/JZe5ULRarVYjNixoILOggHpNvUZx YEFrkG74T2O1Xq1Hyga1gZowF0oGF3oPOd9X7yP+UH2IOMiIPlGfgB0ZXqSZF8VV4EUSvGgrytxW xo4iwI52IGUnOJIGR9qFcoIc6Sv1FWTDlAJlTOlbsLX94EsBdUB9h1oMa9LMmiKYNcWpI+oI5KPq KPIY1pQcYk3kEAWYO2nmTk0qcKdoZk2NKzClgBPjxCDdMKUmFZhSgJmSZqYUAFNqBo7UHHwp4LR0 WkI2rCkQYk1ZTjbkNk4binDaOrmQ2zvtIeeBQQWYQWkwqAGQDXdqxNypMXOnOOZOA5k7DWbuNJS5 UxPmTsnOVGcqjjIMqjEzqMHMoJqEGNS54EsB5kvJzoXOhZDnOHMow7nYuQQsa65zOWLDkTKZIxU4 q53VlOjsd74D6zvqHCXl7+cHH/Cv9f+LJvg/8/9ItjvTnUnKne3ORvyi+yJlua+6ryJ+w32DRrpr 3DXU3N3gbqCW7nvuP+k090t3F9L3unuR8o37DXLud/eDZQEsURtta5tGaVe7lK8TdSJl63SdjjhD Z2JvG90We3N0LuSOuiPi3ro3NdP9dD9qpQfoAdRaD9aDaYQeoocgfbQeTS3MutM0XM/UZyPPHH0R 9l6mL0P65fpypFyhr8BRV+orkWLYYKa+BjwwU1+vr0d8o74JsWGDRWCAtyG+XYNl6IXggZlggIup CzPA7nqZ/hMV65V6JdKf088jXqVfQvyyfo0K9ev6dTDGN/Wb1Fdv0BuQ/rH+GPF2vR1l7tK7qLfe rXdTL71H76FiZoZFzAwzAgWBAspkHtideWAhM8BCZoAZzAAzmQHmBoYEhkAeCgaYzwywgBlgl8DI wEjIowOjqTfzwGnMA4sD4wLjKDVwRmACjjozcCZ1CEwLTKMis941tYk4FHGI2phVr6lVpB1pUyuS yXlm7evUdc0+pq5gC/8Fm7c36Ct3outQB1etqJLG/jaVVpu+w1vmzS1dbbpC+gHvI++mE6vb2+nd VC0x2/uEnyRvL/P5yWevd/NvcbNSi/mPQ+i/Pr/MyiyoPY7P+0RrjztRf7MT9YKqUsrSOuTZy16o 5hPyw/R2mTXL6l7CiW/lZ1nqte0tPpX11b55c+lnWi2n6gpdSDnPrCrDd+OEW8Dj5alqqUF/rlKP 46UV/VCCY9KL8wbx96ATudveZG8yne4VmeOr7Mnn+L7SNnnZlTzJ9fF8X+p3Jfju1bZeebVrfjJr r3JsjR7NddrioHG2Vj0Xo6F53blPa/mHQ4M2L7O0npNWYp09IUs+LTHnN6air7vxcyzZxz6olxrf 1GqlZ5TnK0u7uazEemrQ+uj4k6wlzP3eG67vBv/ZXbU3NbT2ynf4ZN7vOtS9saJlQ1+u+GtImfQu /0PoJLfMu6Ni/+CUm2vKe7I3nNEQ9OOy8eDt85ZUHh2lV+LkWP5q9X9KFVcE21W3q8t34eVa9lfD DjXke8/826/s1z85Ps7aOUEU4r1c0/8iqmOH45RXj7d7eBPD1VVez3H/bTImlM9c9bbGl9p40Zde cW8FPon8f887oNferXzHYSVTQ5L5P8q7Xi5jZJMviP1j6n4eJ3279HgZMKJPlT6p88oNJfV6F02d Sjzuf3Mqr2bNKT/TSjnHGXlVWu69Ws/SS9c5r9M/O2os5Rf5R2DQnoBd1rs/lBxuUL08Soy1CX43 5H9RYUqvF/qraWWq8L2mwtpmJ3C/K2jkd0+NFaulbr7apTYG+rZB/bVa6XW45mX/iQ+tJxAmx+Zw ujE4p8OfE2xz6NxPQPN6Y06sxtDR+xpydMO30IrWdVizKWQ5y+13cI2OdCqz1PXc2lYqPcw/Lk7V Vn9dVq/STxGz5LKr9fNS/l99zuIk1Vi2bvlxZxqmVfn9SXA+4YRqrfN8anndhnmXjkWeZV1WFYFS aF3h2mdoqs2njqk4n1qHtj9z/Dw1HrvyBI8L9oY4tP3FcP+jRrq5G7X+wxpIeQFbnQX14U/epd6n JXcE5wm8+82vckZYYrhiJ+/ScEigNC38v/NKqs9z12OrYIE3HF+vhFblqPUfuvWou9x+nzoUf4q3 cO8qOOV1luq1Bt35BrbhzV+g0tJ3fASvuaQ57LdEMl1mkDDv1SaLvZd85o3aZMscmRPyZHLMe7XJ L7vJHqRlP9mPIuVwOZyi5Ag5gqLlaDmaYtjPqZGcJCdRrJwqz6LG8lx5HiWZ92pTMns7pZg3alOq vExeRmnyCnkFpcur5FWUYd6uTZnm7drUnH2hWsmFciG1lnfJuyjLvGmbss2btqmNfFg+Sm3lUvkY tZOPy+WUJ5+Uf6GOcoVcQZ3kc/I56ixXy5epi3xVvkrd5ZvyTeoh35ZvU6FcJ9dTkXnfNvVm36k+ 8gP5MRXLTfJTGiD/LTfTIPmF3EpD5Ha5nYbL3fI/dJrcJw/Q6exNdYY8Io/QeHlMejTBvGmbJrNn 1ZmW3wrQFCvSiqIZViMrls6y4qwEOsdqYjWh861UK41mWc2tljTbam21pouc55zn6GLnBWc1/Z95 +zLNNW9fpsvNe5fpCvPeZfqVee8yXensco7QNX7bH0ELzXuX6T7/Df576Un/E/5vaY1577JwzXuX RSPz3mWR5T7lrhAdzBuXRb5547IoMG9cFp3MG5dFD/PGZVFk3rgs+pg3Lou+5o3LYoR547I40/3O /V5McX9wS8R0LbQU52tbR4gLzFuWxaU6TieLK8xblsUC3VrniF/rzrqb+J15s7L4g3mzslhs3qws 7jNvVhYPmjcri4f1eD1JLNVT9FTBb1YWT+hf6V+JFyO2RewUq8zTXPFKRElEiXjDPM0Va9AvP+F+ KdmfTsoM9E4f986gb53k3qm4d7rcOzV6ZwHSO6GP+tBHu2Fv97KeWsA9tS331M7cU7twT+3EPbUA PXUq9k6TM5BufPQ6sY+eYB89Ic9DD7a4Bwf99QT3YJt7sJ97cA73YIf9+IS8Bv3YQj++DnmuR2/O 4d7cjntzNPfmRtybG3NvTkRvfhhjyXj8JclH0bM7sN9fnnwM/TvZvE8esfEBjEcvfxLxn9HXE7mv R3Nfb2TeLY/SXkKPj+ce34F7fBr3+Az2E2xm3jNP+XI9en8b7v3Nufe3NG+bR2z8B9PlR/IjjLqP MR6y2Jewo/wUo6K1eQs94s0YG5kYG18g3oIR0pJHSAZ7GjaTX2GcZJs30qPkb+S31ELul/vRhgMY OVk8cnJ55ERh5ByDpiiRJdARHkZRKo+iWB5FCRhFfgqwl2IEeyk2sQIYVynsq9jeisLoamreZo/Y +C3GYYzFIY7HSEvgkRbFIy3GvNkeZbbAeIvj8ZbC401hvL2A+EWMOs2jri2PurY86mwedTZG3b8R b8bYy+GxJ3ns+TD2Ckn5i/xF5Pp7YhxqHocFGIdPU1v/M/6/Umf/s/43qQt7oHTyf4bxKcz4JAvj szPZbhe3K/ndbm5/yjFjlaR5OzoluyvcFRRvRixFmxFLjTFiX0S8yl2Fvavd1Uh/xX2FItl7JYm9 V/LcNe5a7F3nrkP8d/fvyL/BfRey8WRp577vfkCN3A/djyjR/dj9GHs/cz+H/IW7lTq429xtyLnd 3Y6Sd7g7IO90d0I2/i957m53N1KgEVDCd+53lOkedA9SS/d793vKMO9jp3z3sHuY2rg/ukepuXvM PUat3RK3hDKgNQSlm/e0Uyv2l+molfZTa/aaSdNaB6iZeXM75RudgvQ4HY/0BJ2I9CY6iVrqprop 9ibrZGoDXdMMKc11S8qCxmmN8rN0Fo7K1tmQjcdNR52jcyjbvOmdmuouugvF6a66KwV0N92NoqCb elCsLtSFlKqLdG/IfXQf5CzWxdjbX/enCPbNacK+Oe31ED0Me0fqkYhH6VHIDy0G2fjp5OqJehLF QJdNQfpUPRVlztTnUII+V59PKXqWnoWcF+gLUPJsPRvyhfpCyMavp72+WF+MFOg+ioHu20ZZEdsj dlIiNOB+yAcicIWNHiTH/NWBUiJFpEUJJHFBjY90Z/aRzmUf6c7sI92FfaS7sY90V/aR7s4+0l3Y R7ob+0h3ZR/p7uwj3Zl9pDuwj3Q++0h3ZB/pAvaR7sA+0vnsI92RfaQL2Ee6HftIt2cf6XbsI92e faTbsY90e/Z/9lfS19U1dRBBGF9oRxbJIuiOYlkM3WG0c54cKAdCpxgd3Zx1dCHr6KKQjp4gJyD/ RDkR+Y2+zpOT5WTkP1NOgd4xurs56+6iSrr7bHk2tHBFDT5LzirT47PlhZCD2vwieTHkoE6/FDrd Yp3eQl4tr4YtqajTF8hrK2n2FvJGeSPyGP3eWi6SiyiB/bejWLM3Ys3eiDV7Y9bsbVizZ8tlchks k9HpEezXHSGfkc8gp/HujmLv7sasx9vIt6DBk1mDp7IGz5EboLuT5Ua5EdbiXfkeZKPHU+X78n3I Ro+nsh5PYz2eznq8LevxZPkv+S9Yjs+gzZNZmzeVn0ObJ8ut0ObJ0ObQAnKn3ElN2Ic8lTV7ivwa Oj2ZtXkT1ubp8jv5HVKMTm8lf4ROj2adHs06Pd7CJaJo9jmPtHyWDdlo9hjLgWaPZs0ew5o9ljV7 HGv2LNbs0RYCuVYM9Hs06/eA1Rj6PdpKgH6Phn5PQmw81QPsqR5jpVnpSDG6Ppq91iOtltD40ey7 Hst6P4492HuwB7vfaee0I8t51nkWNuB553nExofQcdY766m5847zDuJNzqfQ/p85n4VsQAtni7MF R213tiP+0vkSsfE5lOxzKNnn0PHP8F9FLf1X+6+nDLYKef77/PdRpv9+/1Jq5n/M/xjkZf7lkI21 aM7WopCtRVGZtfiRrUW7StbCYmvRwh3gziAfezNK9maUbCcS2Kexsfuy+zI0tbENjdk2ZLNnY4T7 JiyEZtuQwF6OUe5GdyNSjIVozVYhAVZhM441VqENWwXNNiCbfSCj3H3uPuw1npCN2RMyyj3gHoBt OOQeQmwsQQ5swE+Qj8ISNIUl8CiZvSVT2QaksQ1oCxugIDuwBIms/XN0pI5EzigdRUk6WsdAbgR7 kMh+lSlsA3J0qk5DuvGxTGEfy1S2BOm6lW6FnK1hCZLZBrRlr8tUnafzUFoH3QHpxgMzVefrfNTb SXdCurEQ0WwbonV33R2xsQ3xsAo9IRtfzQBsQ1/IxmMzhq1CLFuFLPbYDOihsA2uHq6HI4+xENFs IeL16fp0yMafM1KP0WMhj4PNcNlmtNKTYDOi2WbE6+l6BmTj7RnDNiOObYYLmzEb6cZOZLH/Z6Se q+cixXiBxrAXaCx7gUYa1EyNInZF7EJsPCFT2RMylT0hY9gTMiayMLKQkiOLIosomoRvrW89CYqg WPMHqUWL5fh72twz8Z7597y/uN/iyfcsWbzwnk2Ln1i8ZfGBxXLxefeOv/f/sfc1XnEcV75VPd09 0MKEEBYTQjBRiIJlmRCFECJjTAjGmGCMiRYTRUtYFiOslQGNCELDQNAw093zPcxMf8ynZCwThchE UXg8orAy1sMKxkjGCiaKlihEUTAHE0XmEMISRftujbJn97x/4L23x9xTM9TUrbpV996q+dU9XTWN yi1/m5KjVCr1So8aD582AFcvcNzz05DbH7QHI8HR4JXgZmh7KDtUGmoMGUPO4FToXOhCaD60HpoP J4Yzwzmhm+G94X3BpXB9+BDUUaHOHNSpDh0MGUKB0ElIC6Hl+5yhC8HrofVwT2BvYJ9/MFAfaAoc UoqhL6FAT8AUsCr7Am4lxy9CiUzkhwfCp4Ob4UOh0vAIyHcG7UR6eAJkz0APEsI54WvhGyD7VnhF 2ekPBAoCN5SewIoyELgbjAlUBjOCO5RQsARGv08pgBE3+s/5zwTbgfRKZbDXv6zag3zgWrBGXQym Bnf7z4EOCkHy2ajs4uBmZEdwKpIfKYk0gOTS+3KDoyA3JXIF5MZF5iKLkaXIamQtNBkKnKBPcJGM yBBwZBJ9RdojvZGzwHUxNB+ZgrYpaKFA3QznKJnAPxmaVlOVQ2CfDfWUul+1KwPqpv8g2OWScl4d VdzKVSWkyJDvUfeDVXarvNKkLkL+jmJS88FKZ5VbwLmk5Klr/jZ/hdKpzCh3/WJwKHg23BmcCo4H rwcXg0shGnTPgR1zQ3tCHaG2kC80FrXi7TAKp4OFiCZzwpXhsnATaDs5lBbWBddCZ0KzYPn54Gqo LsyC5SdDg2DjzaAneDG0PZwXKgqeAh3Zg/dCYjgunAIeYApbw+6wHKoI7wRpg6EtsFJFyAm1pkJZ oVron1uRlVtqkpqh1kT9cijAQt+3+4v8e/zVykggFBgIDAdGwANM6mjgNEmB8+AfnYGJgA76Mhqc Cm+EAmD3gfCl8N3w+QgViQlfDdSHQ+Hh8J0g5a8OVgVmApeIFwTjA51qQ3BHMD9YHiwETy9Qm4kX BJuDLVB2K3DLfwa8ZEdwB3hFBswFtzICsgoCV8EnhwN3AhvBpOCu4P5ggyIHKiOFkXuRSCQpEh/Z FQqAT1RFaiL7Q6URPqJG7MHRyCnQQH1wKTIOXnE9shnxRDyhxkh5pBl0UBGZC50LqmCHZNB7WiQ1 uBRcOpFwIjmyO1QUaYnoQ9mR0RAXaQY/LVbKoK9W6M2AcloZVvOVa/4LfoNK+WdBa+XgC1sB5Deq 14FG1YvqlUAizNs5f4K/LrAT/KANRqHzB5SQf9I/rRb6l/1p/mQ1Ro3xO/0+Za//pH/QfwZmwpgi q7v8C/6b/tv+df+Wf0vZp7arLape5QN54Hkhf8DfEYgLpEBZlj9buRXIDOSo1+GzAr8zUAzzrSxQ 6c9Vq9RmNaKOq1Pqqp9Tx5Ubyop/Xt2hqoF0fymsO7ACqZ7o6tMMM5CsOsWwMskwOrfSqVLKRLAk PAPrFqb/DVHo5ejZWxS9vwZHb66hoqduNciFQohGg+j7sMq9BpSExoD+LnqCNTl6XvVB9B5QCroB 9MnoHTGp6H2gT6EPgNLQH4A+jf4MlB49PfoQZvFDKAM/jHcCfs7BOaggek7zcfwYfgwVRs9gPhE9 cVmEn8XPomL8HK5GX8ffwd9BT0ZvXSnFzbgZPYUP4UOoDHfgDvQ0NmITKsev4dfQM1EkXEkVUUXo 2Sgerori4ecAD5ehaqqc+gbaC6h4L6qhgFBdFA9/B/BtF6qP7vA7AR++jY7Bfn4e9QLSu4ms1C1A cRLgt/eRHN2Hq1G0FqD+RG2gILWpQSgMcP5BNKj5pCYNjWseAgQ1ofmM5jPoDUBQO9BFTZbmEfQm nUvnorfoAroATdMNdAN6mz5IH0Qz9HfpDnSZ7qQ70Tu0gf4emo2e55qLnuR6j9li/oLmo/dKXIMt ggZdZxk2Fi1Eb4v4bfTs1U02jU1Dv2O/wH4B3Yqelvp99JzUElvAFqL32SL2SbTCPsWWozvsM+wz aJ3lWR79iT3Fvoo22NPsLNokJ3fwZ8jJHbydnMrBnyUncXAmOYODP0dO3+Ad7Cq7ij9PbiLAWexd 9h5+mJyjwbu0rDYZP6p9RPsILtQ+rX0aP6Ft1L6Ei7St2lZcrj2ibcff0B7VHsXPaI9p9bhSa9D2 4iptn1bEf6/9X9pJ/G3tJe1l/A/ad7Sz+AXtVe1VfEA7p53Dzdpfan+NXwSsuITbYpwxTnw05sOY D3FnbHJsMj4Wuy92H9YDdtrCXbF3uRhsIjth3A8oKBF7YfebjP2w+03BAS6NS8NBQDsZOER2vDgM e91HcITL5qrwy4A0nseTsAvdh6e5/dx+/DZXz9XjGa6Ra8SXyc4TX4E9p4Df4aycFa9wTs6LP+Ak TsIfcgoXwmvcCe4E3uQGuFfwv3GvcqfxX7gz3Bn879ww92MKcT/hRiia3BFAsdzr3OuUlnuT+z0V w73PrVAPc6vcGvUoOf1B5W7L21ZIfXlb0bYiqnBb8bZS6glyvoMq2fbMtueoJ7d9c9vzVPm2b23b Tz27rW5bHfXNbfXb/pHaC8jkcfBlTFXDTotgku2IQchB/58JPyh3ylZZlk/DK3nfcNUqlGxVkpRd zogcUhog8YqqRJSzykVlSrmizLllqGMCXqjhLnAXKDFKEqkhTwCvqpwCznzI65U10ranWtkEPmhZ nnDVQp0e0rKaLIdAUoM8o0TULDVXuaLuUYvkTuWeSqucmqZmq6XRnkF9tUO2qgb5ErSwoZ5UdsH7 /boy1J1VF6BPSeqyuq5u+ZGfBYqDlAL1LqgVikrGo56EmheAa1qeUC5CL8/CeEqAymU39HRVHpBD 0MdheVg+r1TBOKzyLXkF9LABpbtBDxNKjdKieJRF0l+gcWhhTrkuX5WvKUvyiDwC+kpSCpVC0EqI 5OW78l2lXb4EMva7iaY6QWqqMiTfgRZH5R54jVd6FbsyJ28oGcoOpVnhiTTgHZBvAD9psTDazoQs q9VqhVqrZoEetqt1aoLaqB4EfXfCqIr+9rqhrKrniL7ua0r1qU41QDSmtKtnoIUxZU6dBy1PgqZu +1l1UB0Ea2wQzcDrMmjV5E+E8UyobdC3K+pNf7o/XTWqYpRDVi9AyUlXLXwPMPQUPYUQPU3QLj1D zyCKvkJfQRp6lp6F7wYKPQGv5Em9z6MsWPuzgdJQDtCn0VeB0qH8CfQQKkNPowz0DNB29CyqQp9F /wD0uejdaztQE9Dn0UGgLNQO9DDqRUa0E5/BZ9CjVBr1FZRNfZXag8qpAqoAVVAuSoGV3k8Nwyp+ lvoJOkSNUqOojRqjxtBh2PH/C9JRr1MX0XdplmbRMTqejkf66GnjLvoY3YUMzGNMA/oe08K0oO8z h5nD6DTTznwX/YA5yhxDP4zehjTMWBgb+lH01qNzjJc5gX7CjDAjaIJZZj5Eb7Dvsu+it9lfsL9A M+x77HvoMrvMLqMr7AfsB+gd7U+0Y2hW+zPtG2g+uqP9dUxGTAa6EfOtmG+h30T3mouxPbE96Lex 7lg3uhk7HDuFfhc7HfsOuhd7NfYqpmPnYucwE3st9hpmYxdiF7CWxBVxTOzvYz/EsQ889sBjOBlm fClVGZ3xyWAJZEkkCT8oFTrPSzVOJPVKEWlIGrXpvGnSdWlJuifTcpZcCqnWe847Jm93XpLb5A7Z 4DgpFUolUo3UIPXaVZtOmpOWnBvSKnDm3ueUaanBuVd2Rttekk9KvVBn1ImA9zrUhZZtN4B7Vi6V PMA/76uEdm/Ky1KhPCiPyRfkaXlB3pIK7fHR+rTUq8RJdiXTvqbkSPek0b/VrfGO2VMVWe5QBqTr BIsBsjqvTAA+nwFOFvCsznuOjAcQDey2JMDscpayU86WG0Fqmq1S3i5VgYweaX90NM32eImXsyQ7 0YQ9VbpC+uvoiOphj1wh18ki6a93zKmTD8pGGJMKdEpqkdqlNds1mZMTpLNQn+SnpIvWMckOMoqA rxdGXePcgLrnpHKQWij1etPkaocoG6RRaOGUPVWulcalReDdL52yIUkvbcrJkt5OQXs10f7tl+el iJxlXZcnrScVZF+VffIZ+bYckM/J69KiMiF32DKdI0qiZJcHlRw5TcmTxgGpHlKaiKZkg2wA1Gh1 FNkq7WvypDxp08EutEDZq1SC9sqkEpCkylm2TFumYwt0OgH7mxQlXZqCfhQqJskOo54F/6FgZs9+ NJf/785ltjGmk8xlfA69CGC89KP0/3aias27BZ1H9JzzIm+iudC70+ITZrz1Xp1n1rzoPe3ZMud7 Bs27PR1RrnmLz5sCXIhweDs9s95ES8B30Tdnveq7J233XZGKpGrpoI2XOqwhByv5pDOSzzZqz5Lm Ibcs3ZbWpS0ZQZ1x35xvCeqUAn8jcCdKHcB98j6ng/UtSResd4S8/iTPmGDy7bD4zGtCvbnQt8tc Y/H5dvvyzUPeS4LOV0jkyzm2Ud89GUlFjjip2sZbAkS6nCf5HCnQg2RpXi6wLEjr1gG52LzbXeBL 5RM8oq/BleUc97ULOf0UL5oL+5O8O6FFHka85fN4030ASXwR3ymL0zfkO+sbFUbM+d56IYcXfR5z oTkfJF8hsuUmkH1ISrDOEPxnDYEOonJ9cyAX8Jm0Lg/YYgAVTciXbKvwCWAwR4pcL8375mC8oC/Z CnXm5QFpXvLJI+ZCzyy0wHp10rx5tyQS8sx7jGK++6p3J2g823vIqyN28ZzxDHrPe3yec2CTEciL 3kSw3Lo3T9B56yE/6RH5BYuvvwa4p71N5t1QOugdEIfEK8KI95JvyndFTvQt+q6DLVZtOyRaCsCG YLuULeVKdVKt9ZZkjFpxUBqTcmWWaBLoJnwGVrSmS2lynG/Ttyo5wfI+35pUYWuREiTRNycj3z3Q z5xkAP49tgxpAXL3pDZpUpqGuilyupwp74RRz0oGy7p0zjYqFdl4qLUoZVl3ikMwJh/0ecFz0xtH /FKYAd3rxGbXbQ8nwMjc6b4ST5uv3DllrvEE4H9IvipzofuGr8a7An2Zg1FBkgvkHMu6XGYNWYfl StuiYLIEpCK52Nci1PvavVc954gX+Np9evcdsGtvf5Loue8DUS+we9OFMt9+oHZid170pvdTng7o 3SD4YirU3wKuZl8zKfWu+HiPT8iRdY50OVHeax0hXgE+0WNbkk0glSDlEPEKaQtoXT5ti5Gm5Rnb qm1Vqia+A/oossVYQ75xuQC06wPf2gczZh1844ZcBuSG8l1Qn5Otgs7i87TBrHR6fK4sV5bnJLG0 u8BzEmblDdAamc9D3rveCe8+oAJvmXcv5Ou9ex2XvMNiEngHkHkIagS813jRs+W947V6TY4Vx4oQ 8s54DELIXeCc4g3eq9D6be8t74p3w7XlqXOng++kkxnpzRR3wEwodPf4KNBnjHlIKPO6Yb7E+5K8 la7bvlQh1J8EpRlCjlf2su5r4J/F3kox1dsDfjvmucAveJa9ObCqhCBBj2EGwuojlIFeYdWBEYpk dB4feMSsZ7A/yZEC3/C1+Cw+ixAewSMI4zE8hig8jseRBr+B30A0fhO/iRj8Fn4Lsfgyvoy0+F38 LorB7+H3UCz+Ff4V4vAiXkTbKJ7iURwlUiJ6QJOtyUbxmnnNPPqY5prmGkrQXNdcRx/XLGgWUKLm huYG+oRmUbOIkjQ3NTfR32luaW6hZM2SZgk9SAfpIEqhw3QYfZI+QZ9AqfTL9MvoU/Qr9CsojX6V fhV9mv4B/QOUTv+Q/iF6iP4x/WOUQb9Hv4c+Q/+S/iXaTv+K/hX6LP2v9L+iTPrX9K/R5+jf0L9B O+hb9C30eXqJXkJZ9DK9jB6m/0D/Ae2k/0j/ET1Cf0h/iHbRf6b/jB6l/0r/FWUzHMOhLzBxTBzK YeKZePRFJoFJQLuZRCYRfYlJYpJQLpPMJKMvMylMCspjUplU9BUmjUlD+Uw6k46+ymQwGWgPs53Z jh5jMplMVMDsYHagx5mHmYdRIfMI8wh6gnmUeRQVMV9gvoC+xnyR+SIqZr7EfAl9nfky82VUwuQz +ehJrVVrRaVau9aOntI6tU5UpnVr3ehprUfrReVaSSuhCq2iBdyk9Wv9qFIb1AbRs9qwNoyqtCe0 p9Bz2kHtj9HzcW/FvYX+Ke7tuLdRY9zluMvohbh34t5BTXHvxr2LDsT9Iu4XqPmj+N9H8b+P4n// PeJ/7EFW95/RgGM0SZqH7YX2cj7JUGZvseu7U+0eQ1lfVV+V/ax9nE+1z9mX4P8106R9U9xpv+eg RVNPtr3EPGFX+5Kg5FRfFXBNmSbhkzlBdCSLKY4sM+w4nTcc1cY7jjpLoSvDla9XXS0uu0sVB1xT riXXmuuem3YnO4cdWUDVjiJHkSvJUug4CNyFwLvfOOAo0nscoqPapZorXSohvUfI7U8k//VnOnK7 FvoT+4tdqqWla9Ky2l/WX2mpEZbd82KTo1SoMBQAV7pL7Vrovtc16SjtT3QkdLfbC8nIuhb6qmAM HscsGalQ55i3j5u2O246liG3ZZrsHjUVOWjHbce6vdCU7Jg2JXdNd99zbAkGh2gpcTfqPZZd7oN6 tfu6PQL9PNN91nRGr7oNbmPPsgEBh+hk3U5nnCWV9B5oCPqyT8gVN/rGXaqjmvReWO5aMMgu1XSm a7K/iU+11PQf6tfd7x8hfpeIDBN9Vc6d0DvP/b7xSd1DzibTMt8Anx+CxZg1IKeur0qUoQbU7Gnj k+xrhjJnnmPLubdn3nGTbxHEnmXjgHHAbLWMOy+5x4wD7jq7xz2pVw0mV4uYYll0c06r657T7V6w rFnW3Dfdy5Z8MZ0/5b4NtWT3uvGOu84966gWbutVkTXM/G1MxAo9VrqvEN6t/ZkC2EO44FK7N2E8 w/x1GM+IO9ud3X++fwI4UvovmfNcqrDevWlp6Rs3XOoP9Q90e7oWxL2OIvCfTbD5VNeCZVUPPmI2 OYrsVfZyQ04PzSeZJ3qW7fv5UeBqB+/ke2hiNTvJX+n29FU5OGIzvqRbTzyTh1f9KXuDvTnqwxft F6EO5OwRoEXQqdteCFo6Bf5sh/JN8P1V0WT32IeArkdbrrH3GsocyUDbwZf3uMot+S7eUedodJxx NYMHVHXHuznw3WsicmRbCoVq5wT4erY7oXvT7BY4l0dMEdPN1p46N2c6Y7jmuMCXi3mONGgPPF0c cHSAd9U66kCXOXyJc8OSIca5VLevO95e5SgV49xb5qv9OXqP+Vp/XH9KVyNobyf4ep6lwaX2ZImJ QqPhhmWVeHr3DnGv5Ww/sje7VNBDrv2i3nM/Z4/0F/Sz3S2O6u6pvl6wCGtv6boJ0vOE5f695ksu ylkAdujtqibtg9Xi+XbnhiPNkEPmo3OiO+KocFQ4V6CUcsWI6a5dYJ8kZ4/Zyq+5Vp0z/H4+idim h+4e7asyz/DljgUn6quylHTHwEiuuwPOkNtoGDbeIQlmw0l3hzPR3eZMcaZ3LZgru+NJ6m+C9eCQ uLO/vr8T+lwIfr7uPgielktmAsn9x1wAq6x2D4HXF0OqFHeKO531XVDqLCMWcxbYS5ydvB78fYez x2lyZjpzyGxx7rO3GwdcSa4W96BlnMwCp9tytvts96pzxbkCK8U+xx73GafsHAYLzuhVPsMZcg64 z7kvuKe7aMtSdwRmaylJYk/U39PNMGOFC92pwrKwbLE7e4Qz4p2+cbGpv6nf1LXAzxmH+2f4SL+7 X+6+3n9a7+nJcp4Wywwz0P6E85Lzkr3dUSEmutMcTke1Jd/R5jC4dvNX3EXu7Y6AeKin1BVxnXIN QZ9HXZsWtTvivOo4aUh0DDrPOyaNA90tUDfblQprjhOIlOQ6cl0XXeOwctY5xhznnHfFHlOdc6Qv 3iwbB/riYcSXXPFipSHPneveYy5zZ7mqDBuuGldDd69e1auwGpS6K/R2w3nXFdecw9jd7q5213bv sNvNOlgFegwm44BF765zXYfeZoEudrhKXHp7ub3Fdda15LzlvOPwGfKMble7pcS16Khz9YI13C41 GjEco38K3zLvAT4k9zfEA8qLRVlAn4xGDFOjscJPoaeB0qKxwk9HY4Xp0VhhRjRW+JlolHA7Oo5s 6LPIgSSUjRRAnF8BvPl99DgaRj9ChegCUBHgzSn0tSji/Hr0F0pK0DtoFj0ZRZ9PRdFnWRR9Ph29 67gc0zgeVeAEwJrP452ANQ9EUWZzFF++iL8B+PJgFF/+cxRfHoriy5YovmyNIss23AeY8jA+A5jy SDRq+d1o1LKfKgBM6QVM+Q3Af89QVWiAqgYEORhFkK9RLsqD3qR8lILeisY0L0djmr+LxjTfj0Yz l6kJ6hL6gJoClLkGKPMm2iD4EscRfIkfoFaoFfwxQJkf4gRqnfoL/gT1Vw3CnwJ8+QB+SPMxzYP4 EYIycS5BmTif4Ev8Vc3DmkdwgWZWM4ufIHFSXETipPhrBHHiYoI48dcJ4sQlBHHiJwnWxKWANQ34 KbqH7sFl5LZV/DTzGPMkLmeeYirw3zOVzF78baaGacANJLqKW0lcFbeRuCrWkbgq/i75lQjcwXiZ AD7KRJgT+HskroqPM8vMCjYyq8wfsJn5I/NnLACKvYfdLGIpLEEHWayyMWwcDhIUi08SFItfJjeF 4gGCYvEr7G52Nz5F7vbEr5L7PPEgW8I+iX9Afv0J/5CtYJ/Dr7HfZL+Jf8I+zz6PR9hGthH/D4Jr 8Sj7CnsK/09y7yX+KfsDdgz/jD3Pvo7fZt9gf47fZd9i38PXohj39+QWfrwE6HYVL0dx7Qfkhn28 Coj2AfwH7ccB1/4pimj/Aoi2Cd/VNmtfxP+u/WdtK4W1h7UGiiV3J1KJ2l5tL/UJrUkrUkkkXkx9 Uvsz7evUQ9o3tD+nMrVvaX9BPaKd185Tedpr2l9TXwFEe4t6nDz3SBWTmDL1dRJTpkpITJl6kiBd qpQgXeopgnSpMoJ0qadJrJkqJ7Fm6hsk1kxVxP4o9sfUM+SpRaoqdjR2nHou9vXYCaqWPKlI7Yud jL1EfZs8y07VxV6OvUx9J/ad2HeoehKVpv6RRKWpBhKVpv6JRKWpxtj3Y1eoF2JXY+9QLwKq/hPV Qp5FpHTkeXTqCHkSnTpKro2nOjkNR1PHyPOHVBcXw3GUgfsE9wnqewRzU70Ec1PHCeamjARzU33c I1w2ZeJyuFxKJKdbKAd5SpDq5x7niikPeTKQUrmnuDLKT54JpIJcBVdJhcjTgNQJgsupkwSXUy8T XE4NEFxOvcK1cjrqFNfOdVKnOT1npF7jTJxIjQJGt1E/4xyck/oXrp+Tqdc5lQtSbwI6f5V6izsN iPwyIPKfUr/kfgaI/EYUkS9yb3BvUr/lfs7NUkvcVUDkdwCRP6b5+LbHtxVqPgWIvFTzaXLbviaT 3K+o+dwDjz3wOOzsMLIj339i7pfc0fRA9LeqdsI6mAcrWAmqQNVoH6qH3XYLoo6f5YuR5viQOY0v g9yAvhFeQ3wFfCabY/g9kHPyVZATTVvwTr2053gv0ryUe1xvWoUyHZ8FZYdMN3iQeLzRfBdydaZZ PvW/rMo4egs4QpiepVejvUsndzgeWvuviarVTRlLzettbX2JxzMM08fS+ILWcf1efuNYmnldqBJq zOutS7opniVc/D5DLS8bpvlL+r1CjJAE3KfFRrFNFEWfOCYuiMsW1pJpKbCUWfZaOi0mS8hy3nLN csuyYaWsMdYM6w7rLutuaz7UOQh1AuKYJRH484C7ybIPuE/f57SYxIDlqrW8a0g4e2xSGD1e3jfc lS+MG6Z7V4SLwpS+U7hybF5oEezCXFQ+SBbHrPkW1toO7ZWJjUS6tdcSstot58V5aFO1RkD2KeuQ bqq75+hdc6153XiQzxM2+QJhqLeza8gw3W09lmYsPXwJxl0j7jFUiKVihVh9/GJX4eGQWNdVY0g4 HNLvFRPEtG6rYdrQAZKNRLb1OsheFGetmzbaWg6S2b/JFa2UzWc7ad1lS7ON2aZts7Z524JtULxp WxY7rHO2DlG0bBB92fbYqm0G2zmb0xKyBXT5wi7LgDWeB12Y10EvVoub38endMXzezsO8qf5q/wd /q6wv3Xp2KR+WGgwedraQDM3WpfAQiEhntfxN/hE/V5957EOPr21nC9o24KSSv6WeUugWpeEcsNC F6W/IbSIBhjBbbCEE2xxUhwUJy0hcRq0uS5uWXIsO8GOPVErDlsuWe5YC6OapCz7rKmQ8sVZGHOJ eM6is8jibah5xpJumRFnob8jUDoG+hEt9cCPYLRJkLtgKbbcsKyAB1RZa6z7rQ2gqbuWesshywT4 SJylEmqJ4k1LimHB5Dl8F/pcf7yKtxK/bB0/PsdvCLsNjfoR87rOI1wXrh/PFxZNc8JFQ5s+naRj C+CZOd3FfcPQl7/9WVWwD28dteqt49aLVo8wam22tljPCvfE2m5r55CwJKzyea015jFjQm+xuP34 WaPzvg+Y13ubxGx+WCzSx+njRFoYarsJXlLR28mzJo/OY5g+erdzSMwVaoS1w9dETkzWh8Ssw3cN RdZ7tpu2g9YroLElcdbG2ZLB/tstcbZaW6OtlHgFaGC3bdAm2i7YJi1WW52tzpJpS7Bl2UqBa8xW JB6EEcyCF01Zp2xnwH8Gbbetq9Y1W66twtZmM4rTtmweGSoMFYfv8pn8Tj7PnNtVRSytHzDM8wUd Iu/me/hh01zrKaHZkNAZY0gwDrbMHJ/T79UNtdwSqrr0rUt9t3Qe3f7uHsO00Ns1xHe2rgk7hAzz OfO5rv1COx9nWhT0bQeNTn4FpBwSeLOzrcOUaprrrtTn8Of5EX6Cn4FeTEN9+7H5Dp/g6Ro9LAv5 MH8ih08L+s6So3e79ndbYZaeEoaEQt7ED/DDbR36a/yKkHp0p36AL2vL5pv4a4IqlPDFZAU6lkZW HzIDyapjqDCvg+w8PsewACX2bqvVDisbTX6KECGGYmCVY+APUYyW0SLNR3HMj+KYH8Ux/3vEMWPG YzOiqOUiehShxoL/35Lmrm7ziLHtZHOxcVLX0nayLbdpro9tXWxrPHKwL72zRVfSl9d8tyWntapp d/u+PlNz4pGEw3eMAeOg8UxbrXH2QLJxqw+1Nb7Y3tbY2dJX3NfUWtXX05fZVtvU0n5Ixx+ofVGv azk6Y97TNf6Soe/Ogewj07ol3eYLmeZAX+jAuSOl5nnd6EuNh0d0p8ylOrtprafdTL+of1FvXOga h7V/vG+F1Dm6AfXumUXdknm6dQram+86Za42G15IN6UeqD0c0vV2y8cqdPYDxhfz9ZlC0pFlIUPY 3Vzf3HnkttDc3nkk6/CdtoQXco5w7SmHTV0N8J1w1bTWMsDfOTAIGDEeuOFbRSg/ekPoPXxHiAj5 LQNCQ/O19kSinwNbOt44CS3kdu5vmmtdhM9AOy3DnS2HK3UlR1FrVbupZaY5sVPftQllhp4rLQPd +166bco/kNZ348isueKFdJ1qKjdXm6qOLPOZoJMIn3Og1lTzQmZ7Ip/3gtu01p7+gpsvNmXwZab9 7ZlkTMIOfd6xiq6GF/OPGPWZR5YP1JIR6dqbO3WFR2635h++09zUNtie0rXZdpL0kvTT1GucbPvf 7H0NVBvZlWaVVBK0TAhxiEMTh3YchziE0MShbYwVGmOgiY0xVtMgCRlkkEoy1k8hJCHVPyAJwng8 HC/LeryEEMI6LOMQwhAPIY6XZRnGQxhCCKEJIYQQmibEx8N6fBzisJ697/VM9/6cze6Zc2bP7J4+ 75TELb2qeu/de9/97udXz6Mwnr323Lr++lpoMW4j0+MuCTx0e+37Q7OMzn3NfYO5I3YzT+xEaE1o tz2rCzA9rnSk+7p+Zjp0N7QQuhdweY1eh7Xd092QEKE9Lm+hO9bV6zXS1UI77bIeAbx2y6b3OsIF oU1PXz3FxHlFr8iPets8a5Epb6f1SENC6KE1qb4AaZ6upl31c5ExD2s94rTYCmx6WxPqY8tCsIjX eNthBKHNLceuZL7TPw/owZrOVHoT3Cahkx1jx5xz9XydCAhm3vaoJZmHGvVHka7tuXCNp1UD4xGw pjfMBFz0MesRz117gIlrdoRXWq5ZE+pKm9PrSr2ByJg30DzWMMNFwOpX6nVg8fqm2/Zce1KzFnS8 wvQ0bQVSkY6bE5D9NxfyPc3mOjXScbOHmXM/QPZfp4ZPkT7bNNoc0xzjn7NvMD3Nx5Hc9CRwt7nY aWlOB823NU039TQNX/E2BxoSPNn0Mc9u02KzurmUSauPa3rEHGYO11PNRibDvWZNt480rXuhDZ6I 3ezV2s3h682DzYPMaPiOLa1hx9Md5sMdocR6XXgFsCV4SjgjFKnvae51qQWjhw1nhZuae8PPmjvt oYg6fDAUHfaHt8KWus7mmHBceC4U8QyEDzc/Ddc2d9VpwwXNS56btjuh5FCqZ6Kh3xO5woK3rdbr AorQ8/A6d88GyA20ZLGP2G7V34nM25pCJZEp2zPwmNXIhtXD3bMmRQjmcGSPG/BM1G+JrhbQW0tJ 3ZEW1j6CbLPlhq2WiUO+Vqe16T19ke2m+y2pzftbsptTbE2ApECu2+++1mKKmMEq5Ja+8MFwXGSJ 9bTc5G547tJ2mx6wdCLkT164yxrkWNdb7rYoWiKsx1PWUhYZA7/YahmITNmJ+sNMnM3S3IXmDQ+U 5q7mrnCBdccz4XngGfA8hnniSHjYmtQ81jwWXrEXuxfsYzDfpAVgxkM2UK/zhmzPGH0oO3TMHgrl 8QX1c7YOeqB+y1PmTY9oI8dtz+gBdIB/FoebQtVNWyF7pLR5J+SKpIC9ypEpdNjplmRPmWeALab7 Wu7Vj3p2mQxuN5IEs2Am8lEkBfKYJ5488FSWGQ1F7LmBvDqCizAZdat1/aGB0FCzhzbRJm9A2GZ0 DFhmYCHURy+EblifhrqZudByfW3T7SBVpw64Ql4oD0IT3v1BjdMSugaeC97uLvFEQjcjok0fvhUx h7O8hZEA+LHZbo60eSJeun7OHoDsbBAsJstOREbqKc9dTyTiAMMLAR7vjXRFxu29wcOiF6wqzXok YgyVhYs8fcgy3bH00Dt+DHM7G+lkVsBHE2wZLQ94TcsyzJhr9lx+8kqmt81tEuWW5y036kJ1Ia+j zih0uk30zXq+ZZc9EhG9+1setzxsjasbjMzXb9VpwXImWmZbKW+CLU0sg7mgHfk09xjuntSyiWNI WVjjgRa5Y92xngiyYuawPSmsw1Y72bAXim021h0PM6Dp9vr1+tuhQ/U5tuHwZHjUm2Ltv+INzzWP N4+H7zdPNc+EH3niPX32lFAkEgM2kEp3ewZCDwMlnm6PzBymXc17oYf1i8iG0G92bXO/XcsWN201 bcGsP+JJtO9dYZmDkJvr3ZmR/Z5q5MdWiAb1o+7YcGUkoX6ufgViRB5Dge9ALLMu1WvsMdYjMNcT 7ufw6yNrO8Q0fyjePuKJrX9mG+ZuuBe87Z6bzDMv4VXT1fU87brC+p95HjL3w7frj9qG7QQ9VN8T zgkX8ZX0hGc23HOFrW9qbodWDjZ3Nd0JKSAy8uE7kBfNgY0/CReFIqHdK+AJTSvho+E08ImN8IHm ec/dUKSumHnmyYaMI45cIVcIgvwF+QuCVG4ptwgF9U1qiFBSf079BRFFjVFTRAz1I2qBeJH6JfUr 4uPUNvUb4hD1d9RT4jD1e2qPSMY5zlEVFOIzqhOqE0SKKkuVRXw2ajhqmEiFZ9z8Z1qn20Wk4Czp NciRvgVXoyypCDPw54kp4gFRjHOli5iB12EG/nWcN72B86YynDeV47xJT/wa8iYDzptMOG+6BHnT S0Qlzpg4nDEJOGMSccYk4YxJxhlTI86YmnHGFMIZUwRnTC04Y2rFGdOXccbUhjOmP8Is/XXM0rdj lv6OQgvZ0CDOhn6AVxj/CrPxDxEbTyoQG0+q0QpjMgpx8mS04j8ofkDuQ2w8mQBZ0ttkGubhjyke Kh6SX8BsfIbi75QEeQLlR2Q+ZuArMANfhfIj0ox5+MsoPyItmIe3Yx7+CubhazEPfxXz8A7Mwzsx D++ivJSfdEPGJJMetI6Z5DDT/nW0jpnsw3z7v8N8+zcw3z6A1jGTf4bWMZODaB0z+S3Mt99Tbalj yO9jLn0dc+m/QpkUuYEZ9bcwo76p/rz6C+TbKJ8it9Wn1BfJ3yD+XKFA/LlCifhzBaW2qW0KFcqq FGr119U/UUShHEqRhXIoxSnEliu0iC1XZKPsSXEaZU+KXJQ9KfJR9qQoQNmTohxlTwo9ZE+tCgPm w8Wo70X9XBFCGZDiG5jxHsSM97cw4z2EGe9vY8Z7GDPef44Z7xHMeH8HM953MeP9F2h1tWIUra5W /Bjz2D/FPPYy5rF/hnnsFbS6WvHzF97S7FOsQg71YaUK5VDKGJRDKT+AcihlLMqhlB9EOZQyDnKo EuWHUPakPImyJ+WrKHtS5qDsSXkaZU/KXJQ9Kc9A9vRYmQc5TrZyGrKby8o3MQ/8O4IkM8mu93KW 8tb/544/yFnX7nFFhLL2ac0ofCtqH9UMwecWVwLn1mv6OJj3ape5UpAWuEJ3F0gzuP4Ul4Xr3+dS QRqtYblEkIaujoI0wCW56f9L8+W7fLjqkTruvTfk3lj/Hw/FW3wS222IZgf4QrOO72SXqybYh+wy +/zKM2egyiskC8eETHpRsFvjhSFhQpgVJizzfBKfAtcMsUN8IbtWNVE14Qzw8+xzLo47qu/nnwrx 9CJ77+qmYBdYazzcZ4Ltk7RSqeSQRKlL6hKzpHlpA6QuaUOOlw9JDrlErpZdsixH5GT4bV7ulvvk AbimGGqFoN4S1IciK+DIhPqyfE1OhitDIE9UsdwwNywy3Kjod9Qaorn73CStE3lu2lErNnFz0MKI IbrKWzVBWwyJYiu3KF7nVsQO1CZ5U34sdcGz5uVdeEKXVIha1EjBczfkEmlQjjTGNR6QuxsPNh7m k7gn4mT1jasLfKG4yDv4KXFdrBUf8VNVXkO0kGyIpoeFCe6ZMOuolRLoSXpSSpISoKSIk9Lx6hvs Gh+gF9EIl8M17Jqjlif4bWGIV0NLaNyWTamrsUDql+YbKxsZOR7G4p12OKAdPY3DMC4wPo33oUw2 TkM52rjSuC5vNl6Xd2UZjWkjA79fl5Mbb8E4zZt1VV5rPFydLNjlCJ8AY5Ysp1ZNXN1k+1BBWuT3 zDqzzpkupLK7nIardQaEQ2wfnSPYuSzQ+FqQ5kPCQ3bIGXBo+FK+s8rLDgkL7ADHgCUUss+hvrc2 hSuyVvNaehHODcLZx/wMWE62MMEucH5+hOvgbnE93G145hD0f5le5GA0BRdY2rJlXrirH+Hb+TGR kswSLd+TAljrbVK71Ctn/4PFTEk70jZoKlE+JGfKebJJZuW7SD9yBPUP7GVIGpHGYMQ6YcSOwRUO +GsVxqQffj0LGu6SciWPtCffkGYko3xTKoQzT2W77IVrH8iz8oK8DFYgy9FyrFwmu+BOyC4C0rg0 z/bpR9gBbPGlPM3sMDt8L7vJj1dNcAesmWD920KmmGW+Zb4l2OEsC9ZwzzIPNnlLvM1NisPiKEz7 YIGGIbFHvAP2dx+uXBdzuC0YzYfcI5FHVi0F5F3QaJz8sFHTmCY/b8yQq6UNQ7S8Bjo9zE9JR5wB cVo8iGwPLG+djxG3+Cl+yhAtPkG2J6mlGGHW2Y9sjl0W56CsI0uDKxPASvfzKVI66Ge7+oY4LcxK +6FHA+KKuILqiM8kgqfLH8GT5hqbGnMasxoLGovACisbLY212CeTG/3YDm833gF/6EDnwAL5Rl7a QNaKZKgVLxU3LkojoKPNxhyoN9q4BUXXqMeW2dp4HSyc4Y8Yoq8U8cf5Yt4IfuThA/wMnSUeFXaR l4KfariDHMUuWzPRPFS+CDPRc65AMHFpgknIFM4KZWIOzDET7AOhzK0HC4wID7gmsQhsCeyJ0xkG OAufy90R43haPMrDDMQvVXlrVmpWOD1XifrNDgg3rhy8clC4xqQjK+Suc61GnVEnairS+XTxQJUX RumgeJgXoTVxYlrVmphhaatijQeFaEEhxAqJoo7X8jtiFpQcOgPmx5tCN5fBL/FLdI6o53jhcW2C WAm6yRItYq2A/G2Ivcuv8htCqpAnlAjVgixs8l18P5cD/Z8SksUCYYDtZgfMOmPaP87BUBfmX7Cr IWEWzbzYYwt5GkbNXDUBVjlrjefbDNHSBn579a+ovyII6q+pvyZI6gfUDyC2/A31NxBbfkj9EL+9 6iCaCbRbOkK9iRj1HsSo9yWMeg9h1PsJjHqPYNT7KYx6kzHqPYpR72cw6k3BqPezGPWmYtT7Mka9 6Rj1fh6j3mKMeksw6r2IUa8Oo97XMeotxai3DKPecox6DRj1GjHqrcCo14RR7yWMeivxvxNcVnwR kG41Rrqi4j8pfkB04jUlX0UolvgOQrHEdxGKJcYQiiW+h1AscR+z/DOY5V/HLP8mZvnfxiz/Fmb5 f4NQLPG3mOvfwVz/f8Zc/2PM9f8d5vqfYK7/KcVTMvFb1WN1DLGHMehHMQZNwBj0RYxBEzEG/RjG oAcxBn0JY9BDeA3HCbyGIxOv4TiJMCiZhVdynAIMOkdqMadfizn9q5jTd2BO34k5fRfm9N2Y02cw p1+HOX0P5vR9mNP3Y06/BXP6rQiVkl+Omoj6OTmIGflpzMj/CDPy85iR/zFm5BdeeKzZR/4EIUjy bzEL/xSz8L/FLPwuZuF/h1n4ZwhBkr9HCFLxSbxe4TN4vUIKXq/wWbxeIRUhSMXnEIJUpCEEqRhB CFLxHzHr/StAJTeJsfewyfmC/+n4gwit/FbwOKEs7whqg7kgXQtmwGckeBjOycGjwTSQAsYQSJ5g YhAwUXmtdQIkSzAmeAQkU2AXpLLA8yB4RXlxYAekwsBOYO//yIvexVfR8dEpuA+JBJhZUdM/Hsq9 q+uGDIs9sF0zHkwOHgtmuyaDrqA3KAdvBvuCs7bZ4IJDbeyy6owJ1snAGJtmHjT2BsYD84HVwE4w lh5zTQftQflSoCIxOBtcZjVWHXs4OAC/PdaZrHOXl/VD1la2SbBUrFkfsYvsli2x+rZ5xFTJWtii CyWGreIAqkFv0NtCzgVWOGy9ZSZYnX5IyKlYY+esjxy9FQ+NDnPphWw6RRiljcJ68AHbYXh0oZu1 CLcrStgik15SGDoMt0sow/U6/dV1845kss0acyXZ3F+zJN2THpQsWqf5a9Y5Iy09vpwq7RaPiU/r jkrR1iLBUjUqlUhlUNsruaQ+aUDQ89fYIumataiixJJZkYjGJyhzpTXjxt5gNueB8fEGZtDoWOeC s1zINkuXWnVcG9fJpnFdXO/Vdc7IOUqecCLXzo1UZHPjhlpRW6c36LkpMddQax40r9bksjliqa2E mzFVmkVuw2YS023VUM/IHRfN3LzNjvsEvSmhisegR6J5xzYL56BH+ns1S1ypdM84z18zHrnsvZxq iwQfXF03qlE7eUXNOB8dTNSlXgzw2dDK7HfaaLFbdZZs/i6bxj8Ievk1frPuMP/QSNTp+d2LAWMp fxPu1uWa5J/zJSzPdwfP8kPBWWuBziRoLu0vbxcD1tbLz63TNhhFW7Y5piLbVHkpibVcXr5oFHKE OHqbya5Ysy2LO7bNy2XG+YvptsfG7Yo+4cDFdMMW0rytzzZUsSaucqWmSpPG2GvSGyyoj3JWCSXn SKmXN23XKhIl+er6O/0zdPDX5HVd/OVU+Ukj0bi/MeFyNW02bl9+3HikYuECG9gxdFinka7l6/Jt eVp+Jq/ULJWss022x+zBizP0uHRTesjGCVvSsrXVmBScCD6QXEyq7SY7x3YElozqmrGKXbD8ncBT o9q0DtYL/gcekBmsRjoOdiP7D64FN1mKzUE6ZuPocfYomwF2cCh4SL8Q2AsqgpHgteBQ8G7ZaPAd uSxYEnwId5qgj7NZwdjAVGDjUoA9YOyy3TMmgN3Eg3ft6hLNg8Gz+gX9giU7+DyYF2TZrIpd/cLl x9Y56xxbIGSB/d9nm9gm65Ywx25xBJsj3BYmuSQ6JDwqmRNjwFMqHUn0U7aW288lWJIFizDM1or7 Wb1xQzwi5DhooUd4xi7SHmFRyBDWxXSDRihgV6AUlVwXcthRa6v+4YXHFwlOy+Va5/SgG3bSAE8S jgpP2Gn2kZgkEibG2Gn02BRGs8GiQz7WYS2S4g21bA74VbJ0rE4vZZYftz6xzUoR6RqcG9Kz0oJR i2xTWpNcwceSq3hMSpVSbclSYjBaYoM3pBvBezqF1I3ls0GTNCGlMqnSXem5YBH3pFhHirRpOFCx UH0A7P2QVC3201ppV9ZcbJfj5ANSnnXakWI8bvFKs1K2ZJcpQ8flxxf7TbyJYS3mEVu2Jfli+9Vn 7H0hx/rE+sS8wanpJLbSVOkOXba7ihzzwhY9VbFrLLS2uneC4BfIBip2uTaY/Wbpp1ygfIkbqz5g qLW5bC7w1RmbN7DKbZgowzA6wD9pYZhbEoq4VdHBLnIbYnHNEhoZVIxHDNcrHl6KsXSXd8lp8mFr E2fm+sVC+SBXLB/lijmaGwyyRgJmiqfcDh/Lx/PJ/LGLM3xmMI938TLP8hH+Bjx1kL/HD/Cz/DL/ mAvwXvDLVP4sX82b+AW+LDAPdnkI/Hqb2+Mn2DQjIVB8In8oWMbbAzN8XzCRzxM7bQ+5cX226BFD YpvYZS2CuaJP7LfdFceqD4vj4hR4bY44L86IG7aFijVDjyiKvey0OCIOitt8nrndesuS7N6BcXM4 zOISvQ0WedAWEdtt3bYBY7rt3sV2V6Wsrxmv2K2I5g/JBXKRXCnXyozsl7Jtdvm+fEeeBBvYBd1t yYuNalNPY5I8LI+ad2SLzMu3pOzGGLmj7ihYTWrNkpwB5dHlVON2Y4r1lqyTW+UeZ588JyXLTdaO irWKNSHNOmq9b522PDBuICs2HjfVskWGSrao7KAuk33GxQi3hOvCHYv9Qia9xx2v6IPZZ8WVU51V bL5sF9bZW2yPM5O9zd4BC9iwtlbEigliinunTGcpYfKuPuIKL+03VdLaimx2XWi9EOGOsPfRb6yf ZVieHuNSHL30CHvdmEAvvfG8JiDwAm/csUVbeyxeW+yF59WHafFiu9AkHrceLtHUDFrspnXDJF1M F9KltNnaAbNepe2QobbsqC254uzFFHrG0WlttR27qLXF0qHypfJ2486lJNshW6Ytm56/lGQeZFvp BPq4cKdEY3TQojGl7L7ACH4u/cKE9ZkwbUull9giiKJNQi07yT4ROliIqe6QsO7qAM2qxQThMJyv BD3rBL1QxM457ewwa3E4uNClJK4U0IGS+nvq7wmAESqKIFUvqF6Ac+9z2O9z2O9z2P/COGyiHTzn XfSeM/nu8Qczj9JNXxmhLF17fRW+FaVLDsi8S+d9pXBu5vVpXyFIkxXbIN1//Z5PRyhcAV8JoXR5 fCW4fr8vHX7rfb3HlwDSLUM3SB2v3/Ad/l/OHO9mG0q7MvTe6uac+P/2IPuqmKKJ8qeOQHmxY8Qx 7pip1p0LORXOWGey85jTVGFymqo6ilP0a+dvG3SOQue9Um1xehXjMMM1YnmxsbBad7bDGXtRXdzv NDnt79R0HnOITtln9Hl8g/5of7w/2Z/pz/MFfB4sHfKf9Vf7vb4p37j/ns9YPoXa4Ix1rZcXF6c7 ZtxEtc6pcBhRCwyVTpN7f4XJsK5fcye4jzjvuVPc8HzXlutZXpM7xp3kzvU5Gg40HGw43HDA1+5f aDjqExvSqpjzHeiep++XF7s7Hf35Y/lq94wz2THzzv3Kn+rXymeYPOe9hiangnE1XLcMMez565ZN JpKvbihgkpnE4hQ0Fu5Vl4ZJdcw0+J0m/UJDR8Othh4Db+jwR7vWG277Bitk5wD0+Y4v11nmG3fQ 5zvKCy9EfIRDdITOd5QwTpOj3zHiSyqfceygfjlT0bj6Cp3eMxHnLOqXfs1Y7LzrnIC+DzoGi6p9 MY5235H6WV+67/jZAri+zdHu2HCs+ood/b5cw2Rxenmx95lPfVGtXytOqTh7/rbD6Es4F/KV5veX ah0zRdVF1eUzVR1ltfrZ4vQLkaLqN5AujD4a6QM0kuk3+Rd8Zv+Ar9N/zX/T1+kT/cv+Ev9df6pv z7/m3/U/b6AaNEh/oK9ov8nX5s/27fel+LSOTse2zwz3CcE5BRyJfrtvxjfvhBG9EEGHO8Ex4jQZ Q271Ofpc4Rt9SCugkQzHiKGjIcsQ53rkPu5acT1xaxt056+DPkMNOQ1Fjn7Xlns83+ieKqt17zXU MtFIQ6XaUm0D38A0tDJ2Rnar3epqHehA32CpZ52KhkqHGUZnEDQacoeKjc57568zN9z9xjHHhvup w8gcc/S/fqvhjj+6YdjnaRj1x/qMfpe/zM9Cf2/4lnyrvg3fNvR3wv/AP9sQ5z/m74YegeTr9XX5 +v19/kO+Mb/sj/gf+x8Wz/g3fQ7oy4h/6F3LzvPt+EL+eN9T93686pZUkeCHShWED5VapSYUqmhV NF512/nPt2cUEYLyOSICJY1ohfIy0UZch3ujN8NewTH9BMT0KSIT4voDeBqK6Vk4pp/C74F9kaRI FfEq3nvqNI6tuTi2VuK9p8yKbMWrxGXFacVpokZxRnGGsCjyFQWEVfElxZcIm6JIUUTYFW8o3iCu KMoV5UQtjsJXcRT24ve62vB7XdfxXlV/gt/uasd7Vf0rxaRikvg3ijcVbxI38e7vf4qZuFuYifu3 eN/3LsUTxRPiK4rfKn5LdGOu7at4h6sevMPV1/AOV714h6uvo3eziNt4n6tv4H2ufoj3uZrD+1z9 CO9z9WO8z9Ui3ufqTbzP1TLe5+pneJ+rLdWW6gnxa9VT1VPiqWpX9Tvit6o91XPid2pSTRJ78FiK +C9qjTqGeI6jLQlx9hipwG9fUepX1a+C0gvUBaRafU5dREapiyHyvoCZuw9g5i4WM3cfxMxdHMTc r5Mfwm9f7Uc7a5HxaGct8iNoZy3yANpZi/wo2lmLTIhyRbnIF6OYKA+ZGOWL8pMfjwpEBciXorgo jjwU1RjVRH4CRV7ykxB5J8jPRP1l1F+Sn4+ajZolj0X9KOpH5Beifhz1YzIj6idRi+QrKCKTJ1BE JjNRRCZPoshLZqHIS55CkZfUoshLfhFFXlKP9+aqxHtzVeG9ucx4b67LeG+uarw3V80Lv3/h9ySD /pcNsg694UR60J7oZL2mVfNl0qf5I80fkw2aDk0HyWo6NZ0kp/mKppvkNT2ar5Gipk/TR8qaf6/5 M7JR803NN8mQZlgzTIY139F8j4xovq+5T/6xZlwzSf6JZlOzSXZofqP5Dfmv931h3ytk577T+06T f7rvtX1fIm/tO7eviPzKPt0+HfnVffp9erJn36V9l8iv7avaV0X24t3Dvg5RsIMYei8Wnoz+744/ GL9dEaYT4rHMdDG9KDozHfDpYW7DOQfTiiULMwBSJcPCt8JVxvSDVMI44FvhKmSaQMplKhkGpCwG xfYMpoTx/m/mjffeUWpX2/G+ZwWAzYnM949/wkH2GRNei8tLOzVXpjtJn9s7M5FVffqols6fL3l0 xnVuT19ybu9Uhrs4d1Ubk9/vLtW25a7mi8aEnOW8tDObZbqsvqzqPH/+fMGN/Plze2Vz79Q84zqz qZ13G90eiENGiD0jbhoODxQkDcLfS3C0u0PMIfeelkZtOElnPS/T5YtnJs5tZ1VrafcR1IJc7bm9 vBV9SUF87urJUK5R21YUfSEC9TU6U256yZZ2u3zKVcB4wcJkJuIeZI4x15h45ga6I7qnTlGmyyso 3stPfy2r4BrcceKd++Wl5a6+1nNGoW1j7jETZxLPHMrL0qVq2wuO6V3Mg6Ll3NW8NHcxGouc7jw9 9HmQuQujYWJmmQVmGfWIWWbWmE136NyeNiZ3tewOKu7QhXh4bo82150Co5OBRrVsuiD+JO0uLCk4 fRT167QejetpvmD3VEZeB+oXPKvy5Dga18z7Bd35Me7jbq1l07J5tlLrObd3bu/kUlnBhb6ivJOh 4r2yO1kD+WKZDlBeesENZ7V2NX9GG+M+4s49ffTcdi3c7czEme4z3dr5UxlnJkCPojb3zMBr06AL I+iARrjAPeWeZ465zUy0OwBnnsKnh8mEHiW6x9z9TDZTxpiYasaO9Yeu20DXlhWcKy0bLSs6k+g2 Y03i4sx297s73Z0wqmnaXHScDCE70u6vLTu1XtB9qofxglbimZuZd+AJ3caEMxNIf+iTGdC2a+dP 0mB/oKHXspih17IuxJ+ZyHfkH9dnIg2hom0r3mYmTo7nXUcoLqsa6RH6OMFMlDzKWS6bzrwPI0Sf pLVt2ra82qKbr6UxfQUy0nPuakF8wTXoodE9g/thhrIKf28z8e5ePBJd7i7mLCDbVOi3yz2OeoQl ERVGwSjcbe4d9zacLdGamTy3A3rsYmL/wbKRTXe6PWANvXkrMDMVk98mvw0T03fI78As9V3yu4SC /D75fUJJTpATBEVOkVOEipwmpwk1OUvOElHkPDlPRJOL5CLxArlMLhMa5cvKl4l9yjeVbxIxyp8q f0p8QPkz5c+IWOXPlT8nPqj8hfIXRJzyl8pfEh9S/kr5K2K/8i3lW8SHlW8r3ybiqS6qi/gI1U11 EweoHqqH+CjVS/USCVQf1Ue8SN2mbhOJVD/VT3yMGqAGiIPUHeoO8XFqmBomkqhFapF4iVqilohD 1DK1THyCWqFWiMPUKrVKfJJao9aII9Rb1FvEp6i3qbeJZOrX1K+JT1OPqEfEUWqH2iE+Qz2mHhMp 1C61S3yWek49J1LxHP45PIen4Tn8ZTyHp6v2qfYRn1d9QPUB4pjqg6oPEl9QfUj1ISJD9WHVh4lX VB9RfYQ4rvqo6qPECdWLqheJTNXHVB8jTqo+rvo4kaV6SfUScUr1CdUnCK3qk6pPEl9UfUr1KSJb 9WnVp4lXVSmqFCJHlapKJU6r0lRpRK4qXZVOnFEdUx0j8lQZqgwiX3VcdZwoUJ1UnSRei5mOmSYK Y2ZiZogvxczGzBJnY+Zi5ohzMfMx80RRzELMAuDO95Hq+0j1faT6LwCpkveUHe/hvbTK949/wvEH Eb01QK8RSquH3qQfglRLr8Knhd6Gc5X0PJbK6EcgldAr8K2wFkI9pTWXnsX1s+hxkDLofnoEpFT6 FkjJ9DA9+n5s/P82Nr7HqZqU1e/9v1Yp42Tf+fv52lNz57ZPzb08esJ0qdCaZi0wpJ0MnF3MH09v O3E3ve1zhNWfmZN5J3/c2mRtLYh9Zf38/Qz51NypA6fm8tuhfs7JQFbmyYC10mpBNU8k5o+fyT5x t2a/tcc6XT1JJ9Dp1Yt0uvW29TYdQx+hU+h0uhRk9C/v/TX9Lx9EbThxM63v1Nwr65cKcwetaYa0 6mnUglNUelsW3Ovl1syck+2ZFmurTZE1cf5+Vkl+cWrTBS+9V7ZlO2RLtqTajlVvWUw1SzVtdL8t E90R3bMy+9RcZaY17nRr5nVbydnFS4Xv3O/U3H9l7+ujqrrOvC/nnHshFCml1lq9fFQv90s493Av 8i0SJIgEiTIULff7E0qsQymxGYYaxlJDGEOJscZYSokxhBrDWGqsNQy1xFpCKaXUOo61DKGGGsNY 61hrHAPvs3+bSdq+fTuZP961uma5zjq/+5zn7M9nP3vv39733Hsy86ubszzB1oxja+uDxurd1Xuq 92bmy42hW1W5OXUFsSlRwR3MFoUnq33Vjc7iQJfSVtBSfbj6iHcqtLR62CtUHws0BMeVtpzBzPyN 3ewIjufnPZCbH50REZjKWZLpyo9epy+LVVrkxuASV00wO5hWuKswwOwarA3WyTdKk1m96Nj6wOls K5UpO4tWBIEbgbkt8fdrg6XB8sIYpS0wG7gdXBHU3j8YjNnYrWxbPZ0zHrgYmMnODDZt3BfYnrHM NxKYCRbl9OdnrrvtLM4opGN3iiqn/9O0YsyIyChZV+iP9V8me1N7BMdDBaEy/4Vge6gz2B/aGWoL nKN2OU1t0hdKJwJ0NjTJnqMJ6aj9WHtFhUJ0FgQj7z8Y3BqUgsZge7DHWxk86q0MaULxoargdPAK WWE8pYXllj0sNypt1YszezIqq5dZIquTAw5qkbysierh6sLQLddYdYRrt7u1Orq6JHsqY7fcuLrW lZnXn9meomTe2dLiLF63qbqhejtroaLoomhnfVHm2vr7j1YfqK6prgnKrB1z+p3Fa+udk2nNZbGZ 2Uqb3Cg3OuuDrZlbq7sykrMd1ZXVjgyHPVNpsTdXn6CWGgj2VA+FYunwhIpD22jsayFLXPO0BW/S iHk8dMpzOXQ9lOs5HTzKroKDwZPBM6GO0P7gpVB96NHQBW9JytnQaPAg+fD50CFmGfJs5tPTntMh XfBOdh7et3TnHg+9x0Pv8dC/Bh5KvaP9/Zlu5fm/zKlcI55hlegZdg16xujqhOeySnBMeyZId9x1 xHOars55LtFVj6uTPgXHWU8jXZ1ztXuGKPweTx9dtbmaPZ0qwV3icdFVk6ve0/PeqPD+b1Sm1Vff /0eplXnsFN5cH6OP9EzkdMszWWVpy6wBa+2ai6TpXCNYe3Sk10cmbZcHMqZYCFuFrVOesZ5fH2NZ 4ZlIbWQ6FsNaa2y2SsaGjK6iBvcd3UTeEnlAKUu+ZCtLv5zTnVObNKeP9CZ6k72F3hJvjXeP94D3 yMbS0nPeKe+sL8Z7wyf7Sn2yN8+3Y+M1X5Nvn++gr9sn+Xoojp7ibKI4JzaWes95Z71zCJ3NQ3pv eDf5XL6TyqG0CIOiv5l6w9nmOZtTa1CUXs9lpVc5btSbVnhGdRP6kYL67GXW7NRkg+KN8HQYTsmN tgqUiZWmhvI64i2hPKa8iaxEZdsolyu+Uu9uyuem746v26/ya9bHpHbZRtPPwha3rOflTfpIfYyx Szmkm0iLyOn2TFiL6M51W6dSbw18asg2Kc8V+dZLzjalyrLL08vKJw8wC1tjvGTrtAiFypZWYhil kuSxsvjN3hq/4m32F/srfCepJEcWylG48VrZ3YeWUTm2+a8+pPffDQi+fP8F795AtNfq2+E/7S0k m5BN/W3+Q/6z/sv+CbLosawypdjY5Uvz7cqY2nhNniHraX0rrLXJl6jkkVbJtjOn2zCaVZZV5pm0 DJKmTjmeU2tbKjtsLfrazae9gvW8s82mSkrM3mOMzqrXTaYt001k79FPezpybpIFZmxtuWXpZ6lG I3RkU+2yk2p0Z/U76IjMuirPZCyWZzwXPKfWXcxo9pzWR+Z0k8cEKFydITfjoj6msM563nIy/WyS 1dDmjfBmkh26qM1Zq1d6Hd4GqkUja6Oyu94x77B3yrcEHpDv2+qr8x1l7bPxGmna6ezxNnubff1e ny/SZ/R2UUyfd2hjK+m0viK6W0NWLvTepvCHyWatdLXde9EX8NX6pLIC36DvjG+E7L3De5t8r5zK ccw7Q7EKvXu9A7KDtbq1Rx+jm1w3m1aijyHPr7PWeS4bJjZrWE9J2p6Ul+HIHMmY0qdZWo018kxR tEGxTlunlV5rjy3Xsqug3ujgB/lfn27C1mu8YRkxeNZcLKhXeqm0hfzw3fTu8U37Y32X/Ev98b5r ObW+cd95f5S8yZCbFmFr018xSdQHV9gU/SXjsCUybXF2szGa+548k9RsjTR0GjqtgcLawlr9En2M PkY5ZA0Yu7ImLSt0k0XRuon0s7Y23VlbJ/XNtNx67+Kck3pJf9Oyg2oW4S8LRHgT/TpfnT+d/LDK HyKPq/ce8/f6j/v3Mz8k60j+C76D/uv+Wz6tv8/ft7HU7/E/SneP+a/6O7x6qksztdGgb9A/SR57 IbDYn+sv8Lf4O/2n/KPeRv9OazvzgnWz9u2VJ63ns+7m3GT+YtUaFxOm6SMzR9Ivew7lhgoqnFcN nZZd66ZsE54OTy8dtzy91q1JmUl58oC+ruSg7m5GI7G5KVuFPJMSS740UhSd5PD0eY5n701bbKP+ lVOrHPLsL6iXfdaAPobdy4nccjp1t/5M0V5js0mb166UFdZaBi0jqZWplQaNMTEvJr0voyRNb4x2 t6+b9Vz1dKaW5Axm3LDssvQXja2bMwqWQc91a7tuQjdhOGVQdKO2q95opd4xrhySZ9Iy15/JKLG1 6GikMGhoZDplO66P8dyl3t6b3pKnVbYZOnMGjQ3udn1TRqFVuz5tzQH9jpQ2m5JaQi1GPSSrzHHF GuBjcE43G3+T9lBP62QjL9mtR55ZN2s9b7xhraV+U5LTXXQuLcJ3Bf/T9yPpJ/d+fXLv1yd/Rb8+ +aP/sVw2jPMvMiLlyNpMlagctu+iT0HptDcS7l+bS7oO+/a1ZrpqXZtPV7tMy2ytdNVoJ9ajNJii 6FNQtq2NpauQvXCtiq5clsN0tdV43Vb+B/3j/d+VREXEvs/VlpnFuyk15kRDnvmiZWlCWtypDdNx VfY6+w7zjD1g36U/az9qP7khTdbaR7TjxnbtFUOywVGSa9faV9iNeSp7adxVe608bp4xD5lnKHSP /Yx9xH7e3kr3jq6pM+lMBXK5/rhuRomQm3TLHLmr95trlBLFtypSOaycUIbiitceceW7tiYY9bGu Wv2os9JywemQy+VyZ4Pc5FDkWrnWlmyukfdRvJrlJ5TdxZvMy3Qza4/YZVeRc2z5gHJEbtoyl7Ai fjghxp2+fMDosua6K7KG0watZatjzQN0tdOwSbvVmK3vk7OdN7bMmqIsUe6l7vjcSt2Y22zc4S6L C6UN/s1E2qB5YGOVe78x233I7dGNWXPt0wlGZh9tpC3RsrQkd8O0fIfssyOlZkOppdfUuzre8Whu g0llH5Gnk2oNyZalxUJKjSPk2BZ/LnWJpcLRYuwx7DZvd+1bPmCuzLngOrh8KEFKGc4qNPXGX0y4 lnNhVWTqHdfRxFjXyTizVnYNOvY/uN3RmapldTJ5bHPxM4ZZoys1UjeTNSw3sRo5S8wDcaetuTaf MTuhzlC4ZVZ/IWGElZKV09BoWWqzrhksPZMykDKwoXTD9Or4subcBkOefcTSYWg2JBtPVt5yJjut tmZnZlKpucGZpzdrI80DhjxZy9reMem45Vzs1Cf0r45P2LqmLjHWlG72xSfqj69WLNdTp9dP5uxM 1dpmVkXG9SmHTQXLT7hqLcfNQ9bLVo19xSqtsTTtaMI1U/Fmn3Wp2ecsNOXGFbOWd91htXJT+VdF bhmKuyU3GQRWR2sVtduoVdHVGFutx61lRpd5wHjFmpuwwphtbzVKW2aT7lgnLZ2pVBbr1TU3Pcs8 iXqPyWNsT1ih3aqbcVeUl7qveyI8i43d5gE5TUd+qB1fFenKNw/o+3KTs3flHNJK9n32g4bEtIPu kL7PoehmrDry+ka7bMjLUxnz7WmWpRQr314ed8q+NUFmbWxvKjumP5tyO8tnl+U01sb2ccN2fYj5 v+GwqW/5mD3bnp89nj1u6bW3U7xudk29xmXv3zKUMrYq23DYXpRSQ31ryD5i7jJe0o6n1FiWUu8a tGwzODZMpy5JbTVd2JAWV5UyZr+U0mwoiauiHqOLn6NeE3BetN+x30k46pJW75fbTb26Zcpe5UiC 7MpOLUdP2ePcbTLbb5prjE2Wq0qE85z9mqsupZmsUu7crj/lHKbzWMJRZcBU4EpzNZmK9ccdBc4T rsiEVletQ2eoiRdSzxgcqQFLh0lHPa5JboorlrvX1K09Iu+SW7VFSUfjqgzblUT9hK1Gf9p8Lj4z Plk3Zii06vR34xMNgjuXzoKUMW171rC1IqmW+prHvMfdYbpOvtnu7owb1fexvha/yXwxvsuts+fH H84eX222ty8fcNeza3ex3eV+1Kq4t8Uf0LrcityUsMKQacy2Kglb4zR0FeOucres3m+KcvcmnDdV ufuKprVbDZmGGW27u003o5vRuuIzDV1Uxj6yYjMbNyxX44cdZofZeUDbriST5YqdQ2y8cZG1HVF0 lKXs1h83aql/3k3oNuSZLrNTnqa+M5tT5ah3tDk6HDvN201RqYMJ0uoWy6ir33XUuEK3jJ2O/a4z rh7HodSDjl7XCI1n8S7yOhp9MnHWmTym/aad1jb3cfcpJZHGieliwXVQbjK6WB9lV3FVSaW5DdpI x3HHacfZuCpta8qQ3RVX5bibMpZQ5IxOaXAuoyMxrbX0UtaUbo9TcEbEVVk6jLscV+Oq4k84LttX 5O00HKaxp89xypmYN2lpSdQ4RuOPOC44rlui0q7FDzgmtlw0pdMIm+eisdk1veVi1gnnJtc1yynj tZWj1rvuKNthJVqJdgXWlK9aYmqRA6nnXZdcVwx73SrLqewVpl7LacuFNWcsd8lu467zrkCq0XI2 7UrqVsv1DZFuTWKsdX/8sOtmnEd/inpqq/u0qdc9YS0u6nbdcU/SiHsrdyhl1iPE5ZqiTFGeaMPt hPPUS3al1rnv6ma27NFPuK9SHzzu9rjjEyTyjwH3afdZT3RC/8oLy2fcF8xdWZUJg/pOs5U87HIC tarxZtwty1U6rluup3Q5BxxmU65JcR6mOUJn9skHHWWOisoLcqtumc1X4rHEymfiohLqXCtcMcqY cs580WVkvcmldcQ6lipTqSvMQ5ar2nLXDmezPBKXm1ru9MnXTOnxB0y5qVsdsZYOW6V8kg66V9q/ pau0X5l1eBye9TqHxngyxyNPy5cSphOmTb0JlyyTVJLcNYFVcppsue484trlajUfS3VZdfHWgiHn jHPKOeu8oSP6sCpy5ah5b+qONTdpvC91lTuqTJezpuILXe1WJX632WfqjetbOWo5ROOrFBcll6cc UDYp25WulIaUA2uTtZIh07nX2SUPxnlSe5y3tXJqpP1KSrND5TDLrY5iU4utyznnULlkR5TL5QrI O+LSzSUpzaal5kxno+WqI91Z44hP2OFsJG+iVmP7JWGT934/cu/3I/d+P/JX9/uRP9pRjW75y+uH JJX1tkrU3VkeoE9Bd2O5g3DWUEi6meWbDFa6mjQU09WF5QX0KejGK2g1oRtZnkafgm6oIpmuBpbr KxLp6rj+Jl31LV9qiH1vhHhv9RA2IR7AEwfZqgdVqkWz/81540+ub3+AOP8V7s+FnVs4F+Ro6f8O A90N/okzks4Y/on7S/7g3v/g/CDl/rPl0dK5QvVg1B12LFIt0tARRZ+xdKWhM3bRUhzxi3R0mOkz apGySKE76bjLDoXO3EUFSKF4UcGiskUVdKQvqqJTQ9fpdHiA7JNLOmDxomKKw9IPUSohOiqQbgEd FJPa9sF7zyEsPIdwR7qjSsbTCCl46kDGUwcWPHWg4KmDVDx1YMVTBzY8dZCGpw5W46mDdDx1kIGn DjLx1EEWnjrIxlMHOXjqIBdPHazBUwd5eOpgLZ46yMdTB/fjqYMCPHWwDk8dFOKpgwfw1EERnjpY j6cOivHUwQY8dVByrxX/V7RimLBHwq8Gw04Qj1JFtP/xeV8unQV0Fi/o+t/X/2nYD3Iinf7/Jhy7 301hy/5Ef3DhZHLPH6TT/355UN7/4fmByt7zAcr8l+rc/ufL94FsVvAH14N0nlHVhjtwVIYfCdfT kRheQ1fHwn3hJ+jYHj5A1+yYxXGDTj3pGymML3wPwgyED4UPhzcspDIWfo7kIcT3UdiS8It0TAHZ J5dmgI73jmY62OcQUmTHEeDtP8AblNp2+pzjR4S0cETyA+WmcBExEWzn8tP33m/8Z95v/I70jkrG W44teMuxgrccp+Itx1a85diGtxyn4S3Hq/GW43S85TgDbznOxFuOs/CW42y85TgHbznOxVuO1+At x3l4y/FavOU4H285vh9vOS7AW47X4S3HhXjL8QN4y3ER3nK8Hm85LsZbjjfgLccleMvxg3jL8Ua8 5bgMbzl+CG853oS3HG/GW47L8ZbjrXjLcQBvOQ7iLcchvOW4Gm85rsFbjj9zzzPuecb/wzPCwsxh u7BqGVFZyD/G+Ck00efU+9eihp9Mzz7f00W9HyZsZiHe2F84WZqzC+fUnw//Xl6tC+eu9+X/uvfe /V3vlcciVCwcVXR46AgBtwn1wqN0VAg7hRahjSQP3X90QVchdCBcCPr9dHbSsR9HiI6dFIPd30l9 KHrhv1on3/uvVhH/1SpJ35bOqiLwL61a/EtrIv6ldSX+pTUJ/9Jqwv+zrsL/sybj/1lT8P+s8v+3 dGkNylZ/KtX8z4DTwFngBeAY8Bbwl+QJ8Qi/i8cKawK6gBXAfGAfsIOhUAZUgIXQHwaeBE4BR4G7 EUYL+SZwCJodkA+itIuB8UAjMBd364E1wKvA88A5pOADRgCzgVh/CxeBzcB9wDbgZYaiGegA3mV1 R0138ZKrImET9n90qrlDwHJgHjARKABPAOuASHNuCRApv3sNchTk29S2Hjxj/ASwFbiX1VSsgTwH /D6egqoDPsZQuAL8NfAtFp40NIozvyf5dcT6FLACqT0AuRR3ZyG3Qx4GIn3xc5DfBL4N/A3wLu4u A34Bv0+FF4mfBXYDIxDyIEr4O8gvImQY8N+x5zAIvAj8Z+AR4A+A3wL+E3AMaSId9c8XkFpQfZXJ mhLc/UekzJ/Q/gYQKYgvA7+DWL8FXgb+DfSvAZGm+GPgKZT2OuQPQ/4VZBEyt9IAcB/wq8BfAns5 Mr8VJiDnqLoJczky/xSKIH8OmIKSxKLkqKNkQl5noP84cAYaWFK8H/hF4DEye5jYgjCwpHoD9PAK aZjdFa5B0wf8D4QJASOheRohpyD/LRD9WkBI8SfAaWhuQ/7EAk5QLFgjDHWn/sxwD+4iNQF2Fv4T 6aNlRbSsGv4mfh6YB4RfidVAWFUNFL+MFNC+YhFktD6tW1maXH8D8grIo8BnUJK9kPuBX0OYVUCF 2w3yRyF/CTkGIAvIZQT4CjRod80nIWuBxcAOIHxemAe+oaIxTfwuUtYjTfQFGmnZXZ7jRziGVVJI +DytxFn6yFcN3yM+wzAc+iXQw57qCoT/N+AlaHgKPwJKwI2IixZU10MDj9J8DHpe8kbgIeAJ1Wbg lyi8DfK3gKcZSg2QXcAYjmFqwo+w8NS7WZj7gLHAxcBRhOxhGBHHMewGaVZCn4K4uZCTgPcD1cBE 4MeBkcB1HJHva0wmz2S5ZANzgEXQ9zPUfJ0heSPDF4CvAAcQci3kTuDL0FiAvDyoC/X3zehfhOpd QBEpO6C/AhwEfg/6RyH/cgFZ7SYR62vA30L/PPA48qqB/DZkGTJKK34biDLTuAEU7iPNS9C/hJR/ CnkW+GtgC/AXKAmsLb6KlA2QP4F0rkF+HfpM1H0vNGtwV4FmH1LgPrAE2AsNSiJJwHegNwF/Bg1v wUeAN6BBLYjNMnk1w/Bw3P0I8voG8KvQoNVEJ3AVMBn4UdUvKIXfI53bQJRN2syRZoMwCV4hZQEP AXcgZCpkL9CH8u8GooQaWF5TjpDdCGMEwjKaB5A7vEI8Cv3PgQeBY4j1HcjHVHbCxyBfBcJDpA8h nb8F1kHzTcR6C2nCP8Vh3BUgw7Yi0lf/COH56DE230n6pXzcCEtmY/LcOZLboAEfkL4CuZ+P5Oyu GmOCVD93moVhsaQKxklEPsedVA0TrmcoFTM2InB2cWpuktAMTS+LpX6GodCF9DFvCl3QYAYRTkIe YjyNkGTNEeSO8Vl8F+XpRhjM2oT7SfN11R3CKmiaw9KRGmmEb6OEzQyF53H3m0hhN+RDCHMUeEi1 nUI+hFzGObJ8xZ/Or6e7GPOFF5Av50I3gWOqAJtTGHcVX5o7wMYNWIbPwvsRvh+23cG4mfQ6LD8I m/8A+EOMn9uR19eRL9ivODe3nPAy6v5phuSBzP4HWTpUZsavPgkO1oYcO3irIccnGIcU2xkKjzDu KoBviHyuVzO9VMNsQq15CCU8hNZh88skSuVF+J3I91OMfwp9cy0YH5j+p3NsvB2C/Prcq2w8Z15B FiDOKWGWF0bRgj0oTw9j6epNyL2czzKwST9KjvKrW7mtGKOQbqEMYDsS7CO+AZn7AOcAT0KDGklN sCHYphoeouEz71PA/cDPAOF14qNA2FNEa4r/AgRnk3RAK1I7AExHjcD0JD4PctaRCvkRINiIBKYn gSlJYCziO0ihEigDC6DnbOcWQt4HfBh3Y3gb4e73FuZQdjcBiLsiGLgIFiGBXdDIwGJxtvwq8CiQ s2gXwmQgDJiM2gD9z6CHv6lhH/V2aDirQXgJPUVCz5LAVEVwdQmWlDjzyUHcZiA4lfT3CIl2Ed3Q w25qWFXizAe8ToJNJM4flgP5+BOH8JxT9QBRZikReuQoTQI3QwNmIvLS7gTy9Hnd7wD9wG0ICdYq rURcngLKKYElqtEiIti1iFFRDcYlodeLvDzwHAn8ltZvbByA9UTO9GAx8XEgRh4RdRE5f94CRIuL 6BG0nmJ4G3wbniOgZYXngEhZgOcLqJ3AvRdMWxoHcu89Cz3/Rx++IsMKQsIIJiI1EfaX4Fds3wQz I0Osm0SsFwTe0xcBwRLFNGExQ9w9Ceb/GvA36LPoKRJWLhK37bcRC2s98SDCnIQefiIagWuhAVcn 5sDsjDUdsTIV+iZZVeAsnfsSchHhA7RyZrG6IWMuEO3QYIQX0YvFLGjAqwXeLvAZsQEIL5UgC1gt Snw9snOhTZkmHxhEGL4u/iHYNc8Fq0iJM2f0cYnngjWaxFe4WDVLnC1zD+cjQCfqW4w5GoxF2gr5 aeDjwM+DlXGG80OE+QfM5uBg6hehdwM/A3wCCM4pgqWI4Ak0RzPMAz6GNMF5yIYMLwGnkeYKMCjw N/I9hrwk/wa5DfgsNGBfYiFK9SZkcGA1Z4nHgCihxLkcZylPAsGQpU2QnwGC/xCLYFgifBZ9mcnf B/YB/xGxOC9tBT4FLAByS4J9ibz8nFFbIYPlCpwN8nwDwH8C3gIuB4L1iZ8CVgE5i0sAwibiFcYS RdRa4usUcF0J+RJ32owWZyEvAM9D0wy5A4h1hMT5JLioBAYrngKCXUtgs9KXYVX0CDX8WcAKTvw7 yHyfAeu7cKy5wtGvBYxRImdxmAskPuacBiNKQiz0HTVWzQJH8EMBs5gGHh7OV/QeIMZSYs5M3zzX yPgVwmP1LXydadQ1mNnR00WM0iJWrxrsLKmxUySiT4l8VuX7PxiTBYwM0gUgX4OfB57DXcz4Qicf B9i+loT5S0AvFviuAmokYGdGAF8VYBPJzMKL352PIU094o4xDOeWsTNZGEd47OEInFfUATGrCnwG BNfVYPeAVqNMht00fN7Ejof6HyDzXSmMPGrwEOkVxv2kcuT+BZQncW6E8YR5mdJ/mGnUmPHVGOc1 YD5qjI0CtzzaVA3eLmGXRoO5Uv0R3rII6YOmDG3E5zuMqBLnReshP4j6cg7M64hdAjV4hYTdGDWs rca4J9ahtJsQHnxG+A1S+AX0nwRagF7gFmAxwjyLdL4LGbOSgLlY2AkeC/+UhtAW4Abh4HjhYDvh S2ErcD81vEji+zPVSL+N7dMSuyPUoI3Ub3C/RV6PAZ8GPgFsAn5xofXLCV+FZi/3Pch87wI2FLFL JgzPayjlvdyLgHwf76AqAzMdoQZ7KbT6VmE8ZGHQN9VgnhqgVMsw7PdznwOyus+iFgpifY7VQv1N tt8rYL9FQi9Tg3MKPDWwTQm+LaE8alhP5AwKbFksAqt/G74E/xRbUS8wUqEGdc9iGDYIzo8Vh2AB 1nKLITWwKTUsoEbt1NhDk7AbpgE7lcB4RcxlEnyP1toqrEyZhrNuzuvQZ8P5zh731Wa2KhQwmwvg 3gKYpBp8OBx8TMRerubXrI8IbegpE3NXSP9phAQ/ETBHi/BqNd9h5rtbuUDOPcbnv4dxm8mc72GP WoM+pcEOoRpsRM15C99fTWRtIXGW3oyQYA5q7I+pUTZ1NBBMNRzjQCQ04WDg4Zjx1dyT4Rtq+E84 WIHEmQ/nGNhb1oC9aDzIESOe1IfV9BrI8CsNvEXNVzd8bEReauwiStjjpTnxEoUE8xewcyugdQSM qAJ2sAUwT+kYyoOxLhw2DEcK4Ril1bytVyMkUpOw/ynB8hIfOfnoitWlBulrsDrQYF2vBnvU8H3U o2CP8GqRe+MsK6dwiyGteRneZd/sEGNksgjMQF2QjnocCP9XY2dYA8towNLVWJtID6mOkIaPe2Cq 6i2wIdpXA7aswXio5jzwrYV6URiBf8uA3WOJ15p7IB9ROWdG60t8jcP7KeYvCfxT4isjrAc1nAdi LtNwv0L6GswOaviVmq/aPhTWQHfRCzRoKQ34vwY+oMFMquHzdT5kzlrhtxIvPywQDvYeDoapToSe exTmLOLnVSRnMJSGgOMMab3G5EHgfQt4HSvQKng4w2HoDzO8T82Rff8lmaC3AbOAScClwM0MiVlV YQ5i+BTwhQWZcpG8CPMvyAVlUz8IXAd9B8PwHoY0j1fBk6uwG8PCpEHeCzyGNN+CPh1x34TmEuSb wFloqmCHLwBVSB8a4hsM3waiPOGfhfxLpIl8Nd8AzkDfAnwS2IkwmyC/AXx6IW4A3IzJ/wwcBb6I 8pznSNwnTGqD/lWk8yPI/wq8Dvx75Psa5Drgp4EoP63Kq+CxVVjDMmvAkuKvIJ8DonXCk4FIn5hY FcZbFrcI+Do0KyFXAvuhQauRxzKsRQpzSB+lIh7L8HvAy8BrwJ8jhd+j5D8DohVolGP6CqRWBvSx b2apL1Rhh6QKa22GDwPXAt8BokWoR7MyIG54KdJcDL0FmlSgGfoA9CPQIE0JniM9C/1R4DTwqwh/ BvLjCOODjPTVU9AgjOSBZhUQ9ld/DAgPD98GhGWIB1ZhPKzCrM30IjT7YJ+XsOP3EvvuW8I3ceJB MPNbTKMBN9agv4tgUOIu3H2WIwsjbofMdzNOYN7Xgatg30boxd1/xSy/DXd5mNMI8yDGhEUcmV6N +UV8E2EiERd7HWq+H1IFzQ9wdzHkixzna9m6CfJJ4E85ooS/Q8p8P5Ovf5/H3UO4ewh3+Wx4E+V8 Eun/BvKXgM8AO4BfBf4W+BbSeRHyE5CfglwCxN6m4AI2AftYjkLdXDFbBXC7Ia/NuMtXRnyHje+o 8G91bcDnEH4jkH/rZ0HcR6D5CLOn+AjssBOazwOHgZPQr+L75JBvIO7HeHvBAqmQwUkkfMsv8Rbn uzd8P2cAeqzypJWQJSBn7Pcj/RZgJRB7KWIl7GyGpg47z3WwwzVoAsDtCMPb9+PADcAtwIeBXmA5 8DDwXdgN9RUKgT6UZxx3X0JeL0Fu5YhcPocwL0Dzd0C0r4h2F9Hi4ieAUUgT3ijCP4XLkJdABg8R RrmMGo2yHIU+bmcg99JVaJ1VvBWw/uKrzhLoD4OHc6Z6AOG7gV8Gwq+kTMh5wAJgMV9BIwUwZ/FF lr6EFbqUz/TC1fllpP8hwnwT6fAd3W9B8y2k8B3I3+G2hVzJUOK7073QdAH5+qIO6WyF/DjGDXAJ EWtwNXaixE1IbROsvQ9xL8FKe6F/GWXbCqzGXfAckbPlh5A7r1E/5LcR5hjiHkOOb0GDtYz4BGS+ QjwG+QyQr/33oUXuIC5/dgLfNYi7EWY3StjFrYrWKYAea0AB6wgxi2uAXwQWAV+Fd2kgL3xHD3mC 1xclH4LcDWwAngcOArGTrAEDjwBrjUA/isB+ggZjo4bvlmMXUZ3EuRYrbTh8Q3hZeIwhe5ZJeorW TIzPqLB7MMNWtaxGtPZkOyHtQKy+RfA94buI+wSLK7w4n6li39Ew/UG0y3dprma7nTPQM3yOPSsl dM23wq8YTiHWcwjfxJ4yEp9kIaU3wqLBkWJZOqo9pNnE8pJeQY7Y2xR+grjXODK9uJc9VSU8IehV 7HurITYO4OkL67yH9PvYU1JCudCPcXIG4yQr1ddpVcp2D2Ywm3+f5E721JPQhm+LnmbPXAkvzb+C 9M8zDwx7h4237Dko6RGGFOYm86KwHpYLNG3zZ9hoxmSxakFzTMV2mzuwNme5e9gzY1IBGHszY/vS w/NrGOOCNfaprCwW+05Q2DdfwPJlKKUB8YSMdADyJjwb04pvLX8yryP8FUNKgeou/hLPNa3Ct2wv M1mSsFqpRspt7+7DCFnPRiq2chf+A7mPs7jCy8AXgU8DnwXuw/eMbbDtNfYNGnnIDWguoaalbKbG jvcTqiJoWLu3MiRPJpQuzleCK7KWxTcLQse7hQzhSx3QvIJYr6AuryD9Z6B5Bt/ZrUVqX8HOyX+y 1bTwGrzltfk+yDuAF1XsWaxrzJ/nCWmVZ0WYGpIvsBQ0ySjPL1h5hC7U7imss74MW8nwrp1Mowky WSxGvtdVj7L5BVZ9HhZ+iz0+R2tSZvM9KOHzzMLS5+d3slZG/9qM8n8FuTwP/BZa/yvcbrBYM9Ys RxZ84Dhan+2q7UHKG1HTZqwoX0AJK1mpJC32Fvh+Tg17ao68hcVqC1uqYs9ZsRoVoeTlCN/A/JNW HMPIhaX2Q/jPCyjJOYT/yfxe1D0A70JpWZqiHV4XZCmTp2ngG8yf7Syu+musJDSKnkHKw5gL2LcM le+y/lg5x9qlOWwFcp9AeVj7Hscs8wY8Kpf1BcpxkJVTlULYgz2TBozDR9jTjNQHP6xi38YSio/O Z0GzFDZMQa3ZdzRhkL8HfF01r2LfLLDUEJK4dwpixZHGBIxgKK5Dm36N5S6qgbdRtrb5dayPzCdh JPkoamdh3zJA3ovUnoP8OORnIZ8A9qhWqtjzCQ9TCpFhORTrN3PvqtgqO4XNUAi/bwG/RndzwjJQ Fyqz9GPV28xXF+oVBz1phKPzH6K4DoZkK1av3/Ia8bvAvapPURg9ctnNcd4GfIZ5Oyub2KD6BKEf dSxFmDOq31Fq4WwHg3xvDevLyMWBu1bk8lLYF1RsdmP5InfhlQVkcR+bfx2lpfTVb7KaigFeflY7 8RssL1qbs7i52D17GnIYbPUEs4/44TBmsVegeR2j4nNhD7A2mjcRKkAtQ2oLA2H//McoViNacAnK OT3/e7CLNRh/wpD771D3IJvBF6yRwGS0rJ95keife1nFvstIwaj+Waz7WMgvM7uRhpXnB+hBP+Y+ EPbg/2HvO8CtKJJ/q7p7us/MOZecM0hUcs45XDIi4SKZS46XS04LIrooiNl1FUkquiYUCcouBhQk iaKAOaOCqKssiwgqr/vXo+u96/6Xfe57+973LffjNz09PT091VVdXdU1p9F+99ZX4n1rOE0UlHAS EWD90exzOeYJl2MwtzGYkweNEBHRyM0fAsxyDbSqhu9d3YY50m24ilXXAH4qDQ0bwfMTYn4V4qpa jfKrMbfphRzE1KlxHjE/x9qowrw9wGw8+AA21C6HCXi6DPwwCcwWxPsoczXmCdtwF1YYg/cwM8E6 iMHsXb8KPOvyNd4x4ePxpnh0VxPVMOuAtZVgPHcB6sQcLLjBI8pgRd78Fle9VxBzbPUV0nchvyuw AOarsNqC0h5hdfpIRf/WftXYr/6Aemop2u9XVH3swR9RErNxXR40PIQnvoDWeq8vbASDtXXjY2ZW gjKwj0xPpL3tth6IdgrMxoW3FmETiTOo+T3gLp/GKAqrR8BOEd4eXIirPs4zQplZyB/trD/hYyr8 in9llPwQLWmFNGxY5e1cWBxmpX871OBX1uBd1JU9l6Ie71XG2lkCXJTAapH2Kynem4doKO2jSn5c +XU5uEujN7X3EoNKCaxBJ7C+o/36+Ey06iXQBLSS14N/xiO9E70zDj27ASWHgluaI9/HNgxFf2W5 HIPVHwNOVr3AgX6d+j7c9STQp9Eq7deDvK2BeXXwBOrxXsq9yNkH3A658CuSTfy7o37Y14lieOJt QB9ZURpXscahvccVEa1mKvK939vHzwzAXe/iKc8BlwAxww88xcoBm6FtWB8J0F/Gx9xuQ7638dEj wQ+gFewj7SNtYN+pQbBQPoKtcQi8jfg05fmkBUaYgqD8R8AjQHgnFGQ2QL6CZa0KIMfz5zLkwKoy sLhNWaBGGxrASoVtq+BLUSs8og2wpvXDqA12sYI3Q3+Gp0N25EN4yufA08gpg3fZjZoR4abqowZv 458HHvYI++gwuGg83h1jlJgFysP2UftizLKIu9S7aEMC6W6o51ug50NIn9rt6gzyoU+viC0yp9EK ou+SqP8L4Gtom0D6FPB91A8fiIT/SsGu1/OQ7g9s6aUD6YNAjM+mJNIYT+zM39EQcWsqRE6IfsQ6 UehXteqhjLf4sNIqT6OG4d5v5j1s6C+sxgrvxaqPceYmIGzhoCHuwhq0xMqUBg3d0gp8zoT5s2vh JJR/BjnvoFXvYDTGSof+BPVgHUf5mDcvs+8AIWtWZl3PXot7r/WShffC6KR9TBpWzRShZwnt9H5C v7YOOTVe00HWjI91eRo9dRR1foP2exvZ94uX5T5o/whgTWBloI9ng5Ud+Cg4/6boL+NXqLHaogsh vxbyscppsFIWwBcR7PWIq6jZ9pqG55bguXU1wPMQwCZSWK9Rt6LkMOS3AoJnAtA/KOzTqBMeVON5 Caucxq8uQQMa+AZDjMkhaGJQv4EfxmDdx3hdY8AJTcAb0FxBI8rrxjrYBbe5dJRwsZd27jHSzTpc jp1d7HbzATwRK+MJrLoaxN4nsKYTLPCa3et0r829/kX9TwD3Al8CvoCa9zvU5ZFzCPge8IhDq53z Ou0MHAo85VAgX+xGTk+kb0Rt45FGeWufwo4A3gW8HXi3Q3kdkJBzBk/cAtwFfA75S4DPIOfPSE8A 3gdciPw/4bkRcmahzvnAg8gZDXwauB35lwIVcBnurQwcB8yLOj/E1Xvwdq2QsxN4FPWcQz4ooD9D /s0ofxmwLRB0sLMgh6CGQj3yKaT91SdRWw3k4y0EKGBnDnkxc3Bl0AYF2kpQ0lrleTETcGnfqg1o uffONQOf+FiI99yKYeBXBr10bPe61etN5LfHvX6tHCNAsMRrxlj3uas/4Ck3AZcCN6KdU9EStNny vytZAIi3DsEn4XngX1FmBDAD6NtcDmnfgwZp8IYKgD4K6DRiJk/jWV2cXGj/lc3vUSbCVejuwPs8 PXetAqKdcitwHZ5yGHeB58WDyEnDVbRQ/A74GHKKI30cac+N4CtxB/AG5D+MdBZwDRDSKt4G4ony TeCXeO67SK8F+r72754HV8GZajOuetnx9xYEgvPllUBQW+YH4ulyJsr7/LJI4yliIur0nAk5kp5X uwPRp7IWysxAGn0ntwEx9qqaWHceBtruQUkf5/mV14NIr0B+G9wFGZeXAyG/GpwfFAMOdJh4C/gp rnZFPt7dbEK6EtLPIl0S6a0xV7Rxsxd4VFa6dIiYirC044oE1lwSNzsfVAKRAxadHwmzRPmau8vA YtKIgjCIuWLodMYaCvsvFxBVxdCzBjEzBl9dGcRsqMWufo0oFO2jWP2XeuBJ1ci1yuRD2sex4I0k xjS5D28hgAy8I367Gpj5O2rMBs5B36GvBeRF3Ip8jE5iCrADEHQWw4BfA/14dScQMqWkQ8bIw6A8 Yzy0fZcX3zY6fBmI8URCchmjDUMLMPSCKAOEjLOXozrAscBqwCooAz7XVyHHl3wI+YOR3wc9exHw E+SDD4XnTLy7xFXxKNLTgd/huaCSLIqrhVBDQ9SJkS0ATwYHvKYG+th+RIDIbzFWoCUS45j8LeqB Ngx8GjwpH/UtB+d7yx1RUsb7HHz8HiKNA8RFG2+PY31WeavER8tjDqAXIR8ltY/FwugRQAcpL4mv 4O0WIR/akNEGDclV6JEENGAC40NYHVcxRmlfG6TeWmeuPKRMY8y0trlDHz2OlSCBeYLwsc2IERL+ y0pEVQmMosJ/F+ljw3yUu//20PtPYB0Lv5bhZ1M+qs1zPmKcpI+U9t/2+hUov5rsv165Dl4p+Ljs yOzwD8hRSK8Bdow9Zg5342olpOHRCnx+P+BA4BBgH2B34Hhgc2AHIHyYEv5AWQP4DvBT4EdAeM+C Qt7rCERr5Vve94j0FuDbwPrADcBmwEbAyWjzAmAb4JfIh7xb3eFyziD9KNLlgTcCNyH/SiB8gFbv OzwOXAbcAbwPeCuwOnA1aqiC9CPAJ4ELkX830nOAaJXsDPQeSPg5ZT3vhwSCquo10KSK9yuizHrg q8CJwDtwNQK2QM5p3NUa9ZxHTj4g3lQ2Bm5HeTzLzlQdTkH+BOAx4EngC0B4a+UhoPcffoC7WiLt 6fkFcnCvQs+qrsh/A+k3gUeA04Dw4ipf5wqkiwLhj7WSWwPax11dDpwKBE3ks8D9wJ0oiTe147zL 8b35HBC9FiDaKkD8lfFfgrdDXKtf+cW3cgKz+gCjioZNYfz3Ds1hu92ByMzvYOd6m9r71nyUNaJV +X34P7GWl8C6sPJfByPCTcFCUf5LN/8l/mtog4+dRkSxuAVx2vtdPdZmz3I2IJ6I7+6tRT/XzQ8R m4rvGoJDfvblcjQsRO2/EEEMg+iE/BmIHWXk5AHCN8Lfo543gA+hzHKkn8a7wAfIn6B8Q+S3RYRq kTha29mexxDLii+S9MtA+G8DH8cIW14jFlptgL8CXlNVFvWA/rIk1kHWYmUH9pSAn5a/gY3mtblE Gt/IKO+V9XYlvMHCzwHgS9HwAmnE8gWIe1T4dj6AP0HCl6j9tzY+Kh6WnQrgEYWmCBC5Z3w0IOY5 wscMe+vbe+EyQCvvWVqBdA+8CzxFyiCnA/AF5KcBGwC7A/2710eZ3e77RDHd9TXDd8rwbTLiK4yP fUXsovwad+HpshVoOMytK9lxICL33ZzFwH93eRdq9v0+F310J9LX4t6+uBcx4WoO8gf7GHvktECZ BNKQCIV8O87UxVhqUfpY1sGe59FfiDYXrwNBN9XfRzLDcoeOk17WROy/dfVPR81X4q5MpK/Bt4qd UKYu8kcjvxL40P/mwGrcWxDfuu4Aeh+v/xrxC7wvvjiQ4PAAXhFbg6t5kUPLRU4usEKhMTtVtfGU MniK/8ILfgw5EZLotTO+a2B4Vnk/vDTQ0QK8Ifz3hvPQ5qscVwcV4MfAmCBnYmTQWLX3sV6oWZVB ef/dlv9Wd7dbo5c1UL//usH75Xxs/xuu/YH/vsBbiwNRTzO003skaiP/d3jf2SgPvmV8jSL/AIp5 WxWzrAh2qIFEKMQdaed3Jf8bJzw+kU4yc072RCo0JnvUBJo5cfj0ybTecdtlvduWo4ZE589TQUqR puJUjgrQJZZHGlIL6kQukpCoBw2j0TSRsq1l4MumkaESVN6mqlM9akQtKZ36uu+qqScNpzE0iabR HMKPiqB8HkpQSapAbnZQnxpTK+pM/WgQCepFI/BLqdNpLhUh2blXr3Rq37tn93I0qE/vruVoOWpw c9aQStFFVJhqUhNqTe2pC/WnwSTJfc2TSeNoCs2geSgdUmmqaGurRU2tZdGVqtJ85BemfPaty1Al Kkq1qQE1o7bUgbpRBg2xba1Gve1Mdzxl0UxaED81PyWpLFWmYlSHmlM76kjdaQANpYAupstoFE2g qTSLfkMLM+tOyxTfOZQKmAIWApYCVswcPnG6rA5sCGwN7ALsAxySOXzaKDkWOBk4HTgXuAh4dWbm pCy5HLgGuAm4G/g28CuHSo2cPGWSKgIsBawArAqsCawPbDo6e3imag3sBswAjgRmAecDl04cN2a4 ugW4EngP8KGJk2dMUpuA24DPAHcB9wNfAb4+cUrmRPUu8Cjwc+BJezFbnQH+4DBQwAiYD1gEWGqK PQQVgFWBNYH1gU2BrYEdp2SPnBx0A/YGZmS5/CHAkcDxwCzgTOB84OJptkeCpcAVwFuAdwDXANdP Gzd5dPAQcCPwCeBTwOeBe6dNyswKXga+CTwK/BJ4xqEW06bVrqNTwELAUsCKwOrA+hbr6ubAtsB0 YA9gH+DlFuvpYcCxwCzgbOAi4NJpM7Km6RuAtwFXAtcB7wc+Mt1SQG8CbgM+A9wF3A98Behi8IWV j+L/wlHakaMCXfS/lXK/YfbPMGGlObCjmbGp0Ep88v9SnrF5OXOY8lwgOqs2nx1vCvwb08KOgpX+ hyNT0QtGgfsEQYNDs7j/DtMuGItcMJb7Oyx8wVj5ArDgP0Vp9Vsp/Pb+hadK2lQZ0Mn9Xv+FH5mq /VMUVuNc8i8cmcpeABa6IGxitfMSuoXuoU30PB2io3SKK3Bdbsu9eQRn82K+idfxRt7Br/CHfFII UUBUEHVFW9FbjBDZYrG4SawTfxKfyWKyqmws02WGHCtny6Xydnm/fELulq/LY/KMSqhiqqpqrNJV BsH6ooTnNfl5znNFuc4vznVe92fntrCqTe4DHn+uiYL5Oc/Ntp+Vt+fhuzhXVjKL2B6t7HPznvXH fCo+5omPxXLeXeCRnOcF03O2pmiu1pZakfO8dOtc531ynY/NWX/p+bnOV+R8XukHct2fi5plSuU6 vzbX+Zmc52XTc53fnvN5lar+7NyOG5V25TyvnMp5f+XeOc9rVMh1XjHXeeWc5zU1zoUdcwt4CtRs HB+f+aV+rDUyPk6Oj7Pj45JfKl17R3zcHx+PxMcPc751nTI5e6HOyJytrPtErvO9Oc/rrcx1virX +Zpc5xt/xsPufFOu8yO5yr+e87xhLi5s2D5nLzUcnfP68Htyna/Ldb4l13mu9x2+LWf9I8vlvD5K ud/ItJQcQ8fsbP5z6Bq3dwlhnxFra6oZ0EAFSIcrzQ3hnWaFudYstzmaH+FHbFXut2/ZjkMbSeAX cCV+WVbhl2UDX7usLmvImrIWdk7Yh18lFK4F4hvXCvG8za1pz4tY+yCbVtIuep/OciHbkoS9u1B4 D4nwzvBeiyvD9Rbvsu+Qz85qytlx3O3/0Nw8QpL32JZtwPEG86g9vmjPH8PxBrOahD1bY/EGs9bi TfaNHd+WoApmPUn7RivMfTjeYO63x+X2/A843vCzkg/EJR+MSz4Ul3w4Lhm319yMp92Kp/0OT/vx yu9x5U5cuevnV8JVeMfVeMc1eMcfr6zFlXW4cjeuCMtzz/Fzlvbul4UZvyws8MvCEr9vq/D7tkH4 +/AOKxN+7uBktL7rcWs7Ctsvy8h5m9x+3ayqK5unx+lx9v7ZZjap//6m8X9/0/gf/Kbx37ipBLip BsaV5brjf3nmvzzzD3mG+XVwjbdfamJ/jl/NK+CMJDgjBc5IA2fkAWfkBWfkA2fkB2cUAGcUBGcU AmcUBmcUAWcUBWcUA2cUB2eUUPep+yyvOP4oBf4oDf4oA/4oC/4oB/4oD/6oAP64CPxREfxRCfxR GfxRBfxRFfxRDfxxMfjjEvBHdfBHDfBHTfBHLfBHbfBHHfBHXfBHPfBHffBHA/BHQ/BHI/BHY/BH E/BHU/BHM/BHc/BHC/BHS/BHK/BHa/BHG/BHW/BHO/BHe/RrB/RrR/RrJ/RrOvq1M/rV7bLypNUV zme8xP4tpKvt3yJaav+uoGtphb3yCG2g32KHs2uga66l3fZvGXY4W44dzq6j4/QZXc+KA7qRV/Pd dDPfzw/S7di/ZSX2b7kL+7eswv4tq7F/yxrs37IW+7esw/4td2P/lnuwf8u92L9lvSglmtN9oqVo RbtFG9GG9op2oh3tEx1ER9ovOovOdEB0E93oJdFX9KWXRX/Rnw6K68UOekU8L55nLV4Tr7ERH4uP OSG+Fl9zKE6JUxyJb8Q3nMQ+ZCm3Pwynuf1hOI/bH4bzuv1hOJ/bH4bzu/1huIDbH4YLuv1huJDb H4YLy+OqCBexs6vp3F7NUfO4g1qkFnG62zeGO7t9Y7iL2zeGu7p9Y7ib2zeGu7t9Y7iH2zeGe7p9 Y7iX2zeGL3X7xnBvtVvt5svUXrWX+6j9aj/3VQfUAe6nXlYvc3+3qwxnuF1leIDbVYYvd7vK8EC3 qwwPcrvK8GC3qwwPcbvK8FC3qwwPc7vK8HC3qwyPcLvKcKbbVYZHul1leJTbVYZHBxwwjwlkIHls oAPN44JEkODxbrcZnuB2m+GJbrcZnuR2m+HJbrcZnuJ2m+Est9sMT3W7zXC2222Gp7ndZni6222G Z7jdZnim222GZ7ndZni2222G57jdZniu222G57ndZni+222GF7jdZvg3brcZXuh2m+FFbrcZviJo FpzixcHp4LRoHpwJvhUtgu+CH0QrzZpFW620Eu10pFOivdvRTXTSdXRdka6b6Waii26lW4muuqPu KLrprrqb6K576EtFT323vltcptfr+0QffVAfFP30q/pV0V8f1odFhj6mj4kB+oQ+IS43k81kMdBk mWwxyMwwM8VQN8sSw808M0+MMFeYxSLTPG52iFFmp9kpZpgD5oCYaQ6ag2KWedW8KmabI+aImGM+ TQwXc8PM8Hbx1/CR8Gt5SXguPCenRGEUyqyoYFRQTo2qRzVkdrQ0ukZOj5ZF18mZ0S3RLXJOdFt0 m5wb3RWtkvOiNdFauSC6J7pHLoz+ED0oF0UPRw/LK6ON0Ua5JNoc/VFeFW2PnpLLo2ei5+WK6JPo E3lzdCI6IW9J1ks2kLcm2yTbyNuTnZKd5e+TXZPd5Mpk72RvuSqZkcyQq5ODk4PlmuTQ5FC5NvXH 1LNyndvtR/7B7fYjH3C7/cgH3W4/8iG324982O32Ix9JvZH6VG5Ia5bWTD7lNIaLf6H0WGPUiucd De3/3j/lMG2x/yvmKuPmJvfEOYJUQG4BLRCBtT0C+49EYAJjywoq6EcvjBMLIfdrnFzSIcilgFxK yztfs3Y9zNtdD/NTrof5adfD/IzrYX7W9t6zvMP1Dx9E/3Rz/SMWu7cXu9ybiRfdm4m37VP7YrQk jJaM0VJgtJQYLRMYLSOMlkmMlimMlmkYLfNgtMyH0bIARstCGC2LY5QrjVGuLEa5chjlymOUuwij XEWMcpUwylV24xtVceMbVXXjG1Vz4xtd7MY3usSNb1Qd+6TXcOOS1Ukng1NWJ1kJsnrISpDVQ1aC qIGTIGrsJIiaOAmipk6CqIWTIGrpJIhaOwmiNk6CqK2TIGrnJIg6OAmizk6C7LzDygh1czJi5x1W Ruxcw1kivZ2M0GVORqiP2WF2UD8nI9TfyQhlOBmhAU5G6HInIzTQSQQNchJBg51E0BAnETTUSQQN dxJBmU4iaLSTCBrjJILGOomg8U4iaKKTCJrkJIKynETQVCcRlO0kguY4iaB5TiJokZMIusJJBC12 EkFXOYmgq51E0DVOImiZkwha7iSCrnMSgX72ltiPs6Hazh5TL7hfhVV71B5rj+1T+0ioF5W159RL 6iXYY/8JXv1JnmQWWlrHtuN6+GiIqtmZf2glrJblyTrUmPJSU2pJRak1daJSdm5g+Y162D+3TjjI 2ulD7F99GkajqAGNsXPCZjSBptk7Zth5Qye6i+61cn0/PUQD6VHaass9SdtpLD1NO2kS7aG9NJ32 27+ZdMD+zaKDdIhm0xF6h+bTe/ZvCX1An9BVdMz+LaPP7d9y+pJO29nFGRZ0G5fjqna2cAnXoge4 DtehDVyPm9Kj3Jxb0xPcljvTdu7GPWgn9+JeZLUoD6E9PIyH0WEewWPoCI/jCfQ2T+IZ9B7P4ivo mGgsGtNfRDPbH6fEAJFJp8V8sYRZ3C5utzOEDWIDJ8UmsZlTYqvYynnEk2Ib5xVPiac4v9gv9nMB 8ZGwswJxTBznQuKEOMFFxBfiSy4qToqTXFyyZC4hi8liXFKWlmW4lCwny3EZWUFexGVlFVmFy1sO CLiCMiqNW6m8qh53VA1UM56gWqjhnK0y1Tj+nZqgsnlVkBlM4vXBlCCLHwuyg2n8eDAzmMmbg7nB 1bwlWBos5eeC5cFyfj5YEdzEO4M1weO8N9gcfMrv6jRdSOTXRXQxUVyX0CVFKV1alxVldHldU5TX tXVtUUvX1/VFbd1QNxV1dG/dWzTUfXQ/0Uhn6EzRVI/So0VHPVZfZbXqb/U6MVof0e+LxfpD/ZG4 Tn+sPxHX6+P6uLhRf6G/FTfpc/qcWK3P6/NijWETiLWmqLlYrDfVTbrYZrqYTPGaucZcI742T5pt 4qR517wnTplPzTlx2nyfKCuTifKJDFkzcXniOjk6cX3iK3lH4mRYWH4XFg0HqHLhwHCCygwnhQvU 9HBheL26KrwxvF3dFu4J96hV4cvhQbU6fDV8Va0ND4evqXXhG+Fb6t7wnfBDdX94NDyqHolSUUpt iApFhdWjUdGoqNoYFY9Kqsej0lFZtSUqH1VWT0ZVo6rq6ejS6FL1TJQRDVDPRgOjgeq5aHA0VD0f DY8y1QvRqGi82htNjCaql610FbZW0WOwijZbe+gJO+tV1irabm0gK7PW+tlpZ72RtYr2UspaRQco j7WKXrH64LCd9RawVtGbVh+4/W6KYL+borCji8OOLgH/W0n5qjxm7Zg71Qmqp74ImtISawlupFfs fP8QncM3EYGtr4KoLzuqDCvJTamtlWa3t+oIGk/ZNNeOQtfSTXQHraMHaCNtox1WOl+hN+lDq5lO 0ll2ARWp5BMkk48nNyWfxHFzchuOW5J/xHFrcrs9brKpp3DclHwax83JZ3DcknwWx63J5+xxsy33 PI6bkjtx3JzcheOW5As4bk3uscctttxeHDcl9+G4Obkfxy3JF3HcmnzJHrfaci/juCl5EMfNyVdw 3JJ8FcetyT+RsFd3WNyc3G1xS/KAxa2/giKH8eaPJ4/ElHktpszrMWXeiCnzZkyZt2KKvB1T5J2Y Iu/FFHk/psgHMUU+jCnyUUyRj2OKfBJT5NOYIsdiihyPKXIipsjnMUW+iCnyZUyRP8cUOWTf//Hk u6DIUVDks19Jka9jipyMKfKXmCKnYor8NabINzFFzsS88m1MmbMxZc7FlPkupsz3MWV+iCly3lMk xZ4iKeEpkpKeIinlKZIKPEVSxlMklfAUSYWeIqnIUySVjCnyFShy2nFKihxFUvrXUSSV5imSyuMp ksrrKZLK5ymSyu8pkiroKZIq5CmSKuwpkiriKZIq6imSKu4pkirhKZIq6XklVcpTJlU6pkyZmDJl Y8qUiylTPqbIRTFFKsYUqRRTpHJMkSqeIqmUo0iqAChSzHFKqsKvpEi1mCIXxxS5JKZI9ZgiNWKK 1IopUjumSJ2YInVjitSLKdIgpkjDmCKNYoo0jinSJKZIs5gizWOKtIgp0jLmlVYxZVrHlGkTU6Zt TJl2MWWqgiI1QZH6oEhTxyluJcS1GyshGVSNP+XP+As+y+f4Bz4vpDVXjIhEmsgj8osCorAoIq6V jeVYOU6OlxPkRDlJTpZTZJacKrPlNDldzpAz5Sw5W86Rc+W8YHZqtq03P3/i9o3j43ycmD/nz61O OcNWevg7/t6aRPYfGaGEooTQQlMo7B9FIilSlBR5RT5KEwXdlwviGnEN5ZeNZCMqIPvIMVQwmBXM oiqpWalZdm4nqARFcpd8Qe6We+ReuU/uly/KA/Il95a2ffPwlq7MHfJOuVLeJVfJ1XKNXCvXybv/ rsz/XI+bPRf72ey5LlaQCCV2Ye8lV6LUz0rU+9k1QUIgqMK25B6sgHXBCmb9v63yyPUk7QCx0h3l PfZ4L85XuaM9X+VWviiPvC/OvS/OZRK23XsQ5ZFX3i5/L5fJ5fI6uUJeL2+QN8qb5M3yFnmrvE3+ zlmloDHhnYR8QD5IKfmYfMzOpYWdE5eSrWQb2U52kOmyi+wue8ohcqgcJofLETJTjpSj5Gg55pf6 3b2LbOl2iJKtZWsXeyzb2vrby/a2lZ1kJ1Kys+xMgewmu5GWPWQPMrY/B1PCctZU+/7+6S3t3W3t XZ1s6W62VB/ZV/aT/WWGHCAvlwPlIDn4lzgRT2/lfv/ett59/dROtrNP7yA72Keny3T79C6yi316 d9ndPr2n7GmfPsRyUwJ0+NvTW9mnt7NPT7dP7/6LT/8Fejgryra7jX16e/tEYdvexT6xh32Ktq2d Zy1rX78t40q46+7qhcoU6m+Jt2uL9+qEN+qGd3EyYesPyojldtQynOCQI05yitM4D+flfJyfC3BB LsSFuQgX5WJcnEtwSS7FpbkMl7X2SXmuwBdxRa7ElbkKV+VqfLG1V6pzDa7Jtbi2tVrqWpulPjfg htyIG3MTbsrNrP3SgltyK27NbawV047bcwfuyJ04nTtzF+5qbZru3IN7WqvmUu5trZo+3Jf7cX/O 4AF8OQ/kQTyYh/BQa+kMt3ZOJo/kUTyax/BYa++M5wk80Vo8k3kKZ/FUzuZpPJ1n8Exr/8zmOTyX 5/F8XsC/4YW8iK/gxXwlL+GH+Sv+mk/xX8VIMUqMFmPEWDFOjBcTxEQxSUwWU0SWmCqyxTQxXcwQ M8UsMVvMEXPFPGs9LRC/EQvFInGFWCyuFEvEMnFGfCvOinPiO/G9+EGctwqbpZBSKhlILY1MyFBG MilTMk3mkXllPplfFpAFZSFZWBaRRa31VFyWkCVlKWdBybLWgirv7CdZUVaSla0NVVVWkxfLS1QH 1VF1Uumqs+qiuqpuqrvqoXqqXupS1Vtdpvqovqqf6q8y1AB1uRqoBqnBaogaqoap4WqEtbJGqlFq tBqjxqpxary1tyaqSWqymqKy1FSVrWaq+foRvUE/qh/TG/XjepPerLforfoJ/aTepv+o/6S366f0 0/oZ/azeoZ/Tz+udepd+Qe/We/RevU/v1y/qA/ol/bL9e8X+HbJ/R/Rr+nX9hn5Tv6Xf1u/od/V7 +n39gbOn9FFnT+lP7d9x/Zn9+9zaVF/qP+uv9Nf6pP6LPqX/qk/rb/QZ/a0+ay2t7/T3+gd93pC1 tISRRpnAaGNMwoQmMkmTMmkmj8lr8pn8poC1w4qZ4qaEKWlKmdKmjClrypnypoK5yFQ0lUxlU8VU NdXMxeYSa6vVMDVNLVPb1DF1TT1T3zQwDU0j09g0MU1NM9PctDAtTSvT2rQxbU070950MB1NJ5Nu OlsLr6vpZrqbHqan6WUuNb3NZaaP6Wv6mf4mwwwwl5uBZpAZbIaYkWaUGW3GmLFmnBlvJpiJZpIp aAqZwqaIGWqGmeFmhMk0r5s3zJvmLfO2ecfZiuZ984H50HxkjpqPzSeJtxJvJ95JvJt4L/F+4oPE h4mPEkcTnyQ+TRxLHE98ljiR+DzxReLLxJ8TXyXOJs4lvkt8n/ghcT6kkK26lKEKg1CHJkyEYRiF yTAtzBPmDfOF+cMCYcGwUFg4LBuWC8uHFcKLwophpbByeHF4SVgjrBnWCmuHdcK6Yb2wftggbBg2 DluELcNWYeuwTdg2bB92CDuGncL0sHPYJewadgu7hz3CnuGlYe/wsrBP2DfsF/YPM8IBUcOoUdQ4 ahI1jZpFzaMWUcuoVdQ6ahO1jdpF7aMOUceoU5QedY66RF2jblH3qEfUM+pl7dLe0WVRn6hv1C/q 7+zT6HJrnw6y1umQaGg0zNqnI6LMaKS1UEdHY6Kx0bhofDTBWqqTosnRlCgrmhplR9Oi6dGMaGY0 K5odzUl9kzqT+jZ1NnUu9V3q+9QPqfNplMZpMk2lBWktnHXrfVj8ED9EC/lL/jMt4pP8F1oMr5bb P/Zauhe+rfXwbb0J31ZCzVFzOIRvK3KeQ35Wr9RreCc8WXud1c9vJIJEWf4yUS2RIUL4s5qk3kh9 JBakPk59KpbCn7XM6uirre4uYGcHlSndzkXnuxiixMeIw7CpMPVTZEg+KkKlwir2fHVo5zdmTVjN 4tqw+k9lG9nUMmsrp2x9xagMVQybuJzQzu7MLWEzi7eFzS3eHrb76Z5eSNn5g33fUnYyUkFUcF/u iIp2VlJd2BmtqCVq2blBPVHP1sx2zqx/rJ2q25mOsHrDzqqtXkkCrZXg0vbozvLHZ/nd/IKO2z/i tbzW7ezH99oSD/CDpC6g1s5xPZ3/hVpFMFY89nea7z+h9/5DWu//J20nvv0/q+/0Qf2qPqyP6RMm Cb230Wq8J6GJnjIJq2+clttpNZzTbV6zvXKBOu34P9Flf6/JjNVhf9NeP2qG/9e02N801Uire8Of azM7d3gMswY3Y3Dzhe36T2aUny+YMXa2sEvvNik3VzBp+kXLhWMt901yHPejzhOzc+q7MDMcGY4K R4djwrHhuHB8OCGcEc4MZ4Wzwznh3HBeOD9cEP42XBpeE14bLguXh9eFK8Lrf1FLfvwr9GTqAjRl lbBqWA36svovasxGVmc2CZuGzcLmOXRnu3+oPXv9m/RnTu3Z69+hP/UWM/qf6tCWdCW53xhbTrus xbGb9lI72k+HqCMdoWPUk05wQCOgYReIFqIl/Ua0Fh1okegketHVorfoQzeIfmIw3SyGiuF0p8gU mbQK9v1q8Zz4htaooqo9HVYz1AyWwZBgCKtgWDCMg2BEMIJ1MCOYwcZZ/5wITganrV4+E5zhPMHZ 4HvOG5zXggtqpQ0X1aEuxCV1EV3mf7H3LeBVFde/e87Z55x93u/3+5FzYqDxQDA8DBRjBKSAEZCG lFKMkYaYAsYISDBCgAQChIAhCSFiTPkjRaoUESMCBYQEIqRIacSIiJQipZQiUkREvDO/s6nQx9f/ 7b299373K/vjNytr1qxZM3v2zOx99lqbxOQBeZzE5b3lA8h9cnqQ4fIs+RDyPfkw+XAyiq7pj5KH 5Y/Jp5DH5U/Qlb1I/lP5BtIi3yjfRDYopiqeJK8onlI8TV5TzFTMIlsUsxXzyFbFfMUiskOxV/EO 2avYrzhA9ik6FMfIAfY7IPm14nO6Kzgm2Omu4CMhW8ghZ4U8YSb5k1Aq1ElkQqPwtiQo/FJ4X3K/ 8rLqHskEVZmqTNKszlJnSV7SnNNclrRormiuSn6uzdBmSDbjGYGE3snp8LbbEq5d5Dx4B+cA9yg/ jy/n5/ML+IV8BV/JL+IX81X8En4pv4yv5pfzNfwKfiX/PF/Lr+Lr+Hq+gV/NN5KFpIJUkkVkMaki S8hSsoxUk+WkhqwgK8nzpJasInWknjSQ1aSRrCFN5AWyVrpYWiWdI31WWiZ9TjpXOk9aLp0vXSBd +L/Eq5BWShfh+QYP34r5XBPnwpOKPvQOt5RLx5OKiXhSMYnKDeBc/4rt7HkMdCee1bhue1bDfheV 0B1REfvFU9JHcg/dJfWX0D0VWy/pzoiulZxccU5xnhMUFxSXOLUgFxScQVAKdB8mpAt9OZvQX8jg HMJ3hfs5D52xTnJBOl+d4SJsRuLuEm4qCdeDzSLc3XQWSed6sbmDu4fOHfdzff/Gnntgz92SmezZ FLUnHfb0pzu1DLpj5alVZZyMWjWPE+gKvoBTwjYVbNPCNhNsswg6wUCtMgk2zg07A7AzJAwVHuSi wveEh6htzNpUWNsL1qbD2n507pRxGXTm1HDfheUPwPKhdHZ7kPsenduyuVHib7Uj6P9TsDwdbbmK /R73Fw6j6H6W7s5Mf+FJ6M6rJ3fL74TxJJyDtrWv2Pc82iqnbX2OU+AMqNFWreItxVucjt5PneT0 dBd+mTMorii+or0uo62MCA7BT1twF23ZIOFhIYd7nK4gn3I/oWvFJW62cJ22ppzO/1ZuFZ31+3Mv 0POQzbXSuXk810nXpye4LromPcudpOvQcu6suGvOoDbl07qDbO/PZbK7Oe5h9ls2N0b4UNnAdf63 5dizP+m/Sfrbc5GHHk2Mq+zbzkXfb88FN5bO6bd4EjqPp9x2Lvqy9/EVNwSe44SAkMwphfG0Hvak TJqwBDYEUXtctPIWjsIc5cH1rMFefR3dq9MdO3t+SWtwcQF6H9STNFOJBYQ9h61iUtwS8jJ7o5f8 jOIyVoKrxhy3iO76v33DZiLs60f5GrzDwnHn6UHYasBJ5I/KH+Wk8pfkL3G84knFk5xM8bTiaXrl zlPM4xSqF1QvcIKqWdXMKVVvqN7gVKqdqp0cvfvgeojvxlShzp10jZNjjTPQNe4IZ+ZO08NBR8NZ zklkdKVz8T34npwbb6d48XZKgK5E17mg7GvZTS4kV8vVXESuk+u4JLlb7uaicr/cz8XkMXkylyzv Ie/BpbDfr7keeFOlJ95R+Q7eUUnFOypx+Rj5I1wfeb58CteXrk3F3EB5ubyce4DegTZxQ/AGy1C8 wTIM76sMx/sq31MtVS3jRqh+ptrIjcI7JNmqN1Wt3MOqPap93Bi8PfJ9dZo6jctRD1UP5cbjjZFc vCUyAT0qlXxXMkTyCM7zILqKc5IH6CpOJGPp+s0eYG+gI+6G4mvFTcU3AicQQSJIBZ6OkKAQEsJC REgSokJMSKajJVf4gTBB+KEwUfiRMEl4VPhMuCx8LlwR/ixcFb4QrglfKm1Ku9KhdCpdSrfSo/Qq fcpc5Q+UE5Q/VE5U/kg5SfmoMk9ZpPyJcqpymnK68kllsfIpZYmyTPmccq5ynrJcOV+5QLlQWaGs Ua5QrlQ+r6xVrlLWKevplSCh8yFdh+nYpeswHbt0Habz4Tl6/bvp3s9K75kfplf7d+h+9Akune5B n6XzWyW92oclVld63z8HI28uKRc5s/lnb+P8835iZUr5stvKGOiddTv/nGKxvFDxzH/LE4LqkA+S D73tPfcm7nvkF+QN8hbZSfaSNtJBOslR0kW6pXdL35d+IP1Q+pH0Y+kn0t9Kfyf9lG/i1/LNfAu/ jl/Pb+A38pv4LXwXf5zv5k/wJ/lT/O/4T/nf8xf5S/xl/hp/nb8pU8u0Mr3MKDPLrDK7zClzy7wy vywoC8uSZDFZiqynLFUWl/WW9ZGly/prOjSHNJ2aI5qjmmP/ea/6/5P3qnUcT6c3qUwuE/7JO4x0 PPMH+A7+EN+JN0j+2ZtkJHaJf0+5Qfmqcqtyu3K3sk15SHlUeVx5SnlWeUF5WXlNeVPFq1Qqg8qm 8qhCqmRVqqoPvTMaTO+CRtB7nhx6d5NP72Sm07uWOapy1SJVtapW1Uhn8/WqTXSua1XtUu1TdaiO qLpUJ1SnVedUF1VXVNfVHJ2KNWqT2qH2qSPqFHVcna7OUGeqh6lHqceqc9WT1JPVRepi9Sx1mXqB ukpdo65TN6lb1BvUr6q3qrerd6vb1J3qY+pu9Sn1WfUF9WX1NfVNDa9RaQwam8ajCWmSNamaPpoB msGaIZoRmtGaHM1ETb6mUDNdM0MzR1OuWaSp1tRqGjXNmvWaTZotmlbNLs0+evUc0XRpTmhO013/ Rbrnv07vt+RajdakdWh92og2RRvXptO7gEztMO0o7VhtrnaSdrK2SFusnaUt0y7QVmlrtHXaJm2L dqN2s3abdod2r/aAtlN7TNutPaU9q72gvay9pr2p43UqnUFn03l0IV2yLlXXRzdAN1g3RDdCN1qX o5uoy9cV6qbrZujm6Mp1i3TVulpdo65Zt163SbdF16rbpdun69Ad0XXpTuhO687pLuqu6K7rOb1c r9Gb9A69Tx/Rp+jj+nR9hj5TP0w/Sj9Wn6ufpJ+sL9IX62fpy/QL9FX6Gn2dvknfot+gf1W/Vb9d v1vfpj+kP6o/rj+pP6M/r7+kv6q/YZAYBIPOYDG4DAFD1NDT0NvQzzDIkGUYbsg2jDNMMOQZCgxT DSWG2Ya5hgrDUsNKQ4NhrWG9YZNhi6HVsMvQZjhkOGo4bjhpOGM4b7hkuGa4aeSNKqPBaDN6jCFj sjFuTDdmGDONw4yjjGONucZJxsnGImOxcZaxzLjAWGWsMdYZm4wtxg3GV43bjDuMe40HjJ3GLuMJ 42njOeNF4xXjdRNdSEw6k8XkMgVMUVNPU29TP9Ng0xDTCNNoU45poinfVGiabpphmmMqNy0yVZtq TY2mZtN60ybTFlOraZepzXTIdNR03HTSdNZ0wXTZdM1008ybVWaD2WH2mSPmFHPcnG7OMGeah5mz zePME8x55gLzVHOJebZ5rrnCvNS80txgXmteZ95o3mzeZt5h3mvuMB81d5tPm8+bL5uvmW9aeIvK YrDYLB5LyJJsSbX0sQywDLYMsYywjLbkWCZa8i2FlumWWZa5lgpLtaXW0mhptqy3bLJssbRadln2 WTosRyzHLacsZy0XLJct1yw3rbxVZTVYbVaPNWJNscat6dYMa5Z1uDXbOs46wZpnLbBOtZZYZ1vL rVXWldZGa7N1vXWTdYt1u3W3tc16yHrMesJ6xnreesl61XrDJrEJNp3NZvPZIrYUW9yWbsuwZdqG 2UbZxtpybZNsk21FtmLbbFu5rcq20tZoa7FtsL1q22rbbttta7Mdsh21HbedtJ2xnbddsl213bBL 7IJdZ7fYXfaAPWpPtafbM+xZ9uH2bPs4+wR7nr3APtVeYp9tL7dX2WvsdfYme4t9g/1V+1b7dvtu e5v9kP2Yvdt+yn7WfsF+xX7dwTnkDo3D5HA4fI6II8XR2zHAkekY7sh2jHNMcOQ5Ch3THTMccxwL HEsdKx0NjrWOdY6Njs2ObY5djjbHIcdRx3HHSccZx3nHJcdVxw2nxCk4dU6L0+UMOKPOns7ezn7O Qc4s5wjnWOcEZ76zyFninO2c66xwLnWudDY41zrXOTc6Nzu3OXc49zoPODudx5zdzlPOs84LzsvO 6y6JS3AZXDaXxxVyJbtSXX1cA1yDXUNcI1yjXbmuPFeBa6qrxDXbNddV4VrqWulqcK11rXdtcm1x tbp2udpch1xHXcddJ11nXOddl1xXXTfcvFvjtrg97pA72Z3q7uPOcGe6h7lHuce5J7rz3YXu6e4Z 7jnucvcid427wb3Wvc690b3Zvc29w73XfcDd6T7m7nafcp91X3Bfdl9z3/TwHpXH4LF5PJ6QJ9mT 6unjGeAZ7BniGeEZ7cnxTPRM9kz1zPCUeSo81Z46z1rPOs9Gz2bPNs8Oz17PAU+n55in23PKc9Zz wXPZc81z08t7VV6D1+b1eEPeZG+qt493gHewd5g325vjneQt8E73zvLO9VZ4l3pXehu8a73rvBu9 m73bvDu8e70HvJ3eY95u7ynvWe8F72XvNe9NH+9T+Qw+m8/jC/mSfam+Pr4BvsG+Ib4RvtG+HN9E X76v0DfdN8M3x1fuW+Sr9tX6Gn3Nvg2+zb5W327fAd8R33HfKd9Z3wXfZd81300/71f5DX6b3+MP +ZP9qf4+/gH+wf4h/hH+0f4c/0R/vr/IX+Kf41/gX+qv9Tf51/k3+bf6d/j3+g/4O/3H/N3+U/6z /gv+y/5r/psBPqAKGAK2gCcQCiQHUgN9AgMCgwNDAiMCowM5gYmB/EBhYHpgRmBOoDywKFAdqA00 BpoD6wObAlsCrYFdgX2BjsCRQFfgROB04FzgYuBK4HqQC8qDmqAp6Aj6gpFgSjAeTA9mBDODw4Kj gmODucFJwcnBomBxcFawLLggWBWsCdYFm4ItwQ3BV4NbgzuC+4KHgseCJ4JngheCV4I3QnxIEzKF HCFfKBJKCcVD6aGMUGZoWGhUaGwoNzQpVBCaHpoVmhtaFKoJNYSaQ+tDm0JbQq2hXaF9oY7QkVBX 6ETodOhc6GLoSuh6mAvLw5qwKewI+8KRcEo4Hk4PZ4Qzw8PC2eGc8KRwQXh6eFZ4bnhRuDpcG24M N4fXhzeFt4Rbw7vC+8Id4SPhrvCJ8OnwufDF8JXwjYgkIkR0EUvEFQlEopGekd6RfpFBkazI8Eh2 ZFxkQiQvUhCZGimJzI7MjVRElkZWRhoiayPrIhsjmyPbIjsieyMHIp2RY5HuyKnI2ciFyJXIjSQ+ SZNkSfIkRZJ6JvVO6pc0KCkraXhSdtK4pAlJeUmFScVJs5PKk6qSViY1JrUkbUh6NWlr0vak3Ult SYeSjiYdTzqVdC7pUtK1KBcVooaoI+qLRqIp0Xg0PZoRzYwOi46KjotOjE6OTo3OiJZFK6LV0dpo Y7Q5uj66Kbol2hrdFd0X7YgeiXZFT0RPR89FL0avRK/H2E2lJmaKOWK+WCSWEovH0mMZsczYsNio 2NhYbmxSbHKsKFYcmxUriy2IVcVqYnWxplhLbEPs1djW2PbY7lhb7FDsaOx47GTsTOw82/WRXwDf AL4F3AtsA3YAO4FH6V6QImSTgXIR3wLuBHbDc5zRAnQLkBEgI4j8NmAHsBPISqkgowJHJXI+pqgG XwNtGmjTiJy9wDZgB7ATyMpqIaODBj1K6UEbQRthiREajOCboN+EXBPKmpBrgn4T9Jug30S6KP4Q klYRdwKZHhs4NmiwgW8D3w7aDtqBuhyQdEDSgbocqMuBuhyoy0F7nSGr0YVSLpRyoZQL8h7wPeB7 wPeA7wXHi3q96JP5ZDNwK7AVuAe4H3gQeBj4Hj3bFCH7MnChiK3AHcAPKFZCayVyK5FbidxKaK2E 1kporYT8YsgsBmdxgsOzp0FVsL0d2tqhrR2S7bCxHdraoa2dlZUPQu4y9Gg12loNugZla2BDDcrW gL8CmlcgdwXKrkDuCmheAc0rYNUKep8q4U5CslbEHUCmZxU4q6BhFfirwK8D1qOWesjUQ6YetdSj lnrUUo9a6mkfM2R1rUap1Si1GqVWQ34N+GvAXwP+GvCbwGlC7U2sD4mcSVLcCmwF7gHuBx4EHgbS c8sQsilAQcRW4A4g06oErYJuFWRUkFGJ/P3Ag8DDwA/w5LcVeBiY4NC+IVrwddCmgzadyNkD3A88 CDwMZGX1kDFAgxGlcMUSM2gzLDFDgxl8C/RbkGtBWQtyLdBvgX4L9FtY35MfQdIu4g7gx3hjYSuw FbgDyPhO0E7QLtTlgqQLki7U5UJdLtTlQl0udrYpsho9KOVBKQ9KeSDvA98Hvg98H/h+cPyo18/6 RBJhV7jkbmCapILiQGAmMAs4NIFMA6UXURwJzpgEgj8G/Bxw8oEFwEJgUQIhWQx6ZgLBKQVdzyKu SFay609Sy2YiisyqbcB6cFYjtwWS70pTKbaxFkkOsPZS3H/r+pa8C85h5HYxSSkH+a/Esbf51qiT +oEc40glLFeqZpIcLz0HfB/4AfBD4EfAj7GKvSVKfQL8LfB3wE+R34l8QUSmS8AMLUCjAI0CNArQ KIgaNZDVgDaJ+D7wA+CHwI+ArJwpUY7HSkrxFwxZCUrvBc10OERkfB0kdZDUiZy9oJmMR8T3sQow i+eDM1/aBTwOxFogPQE8iXm+VZQ6BTwNPAM8i/zDyK8UsQtz+R7Qx4HdwBNAprFS1NgO2SWgV4jY BTwO7AaeALJyKxLl+D7sjFLczJCVoPQe0ExHvYiMnwHJDEhmiJw9oJnMGhG7MHNiPmQcil3A48Bu 4AngScyNraLUKeBp4BngWeSjP4hKxC6Myj2gjwO7gSeATKNK1KiDLM4VsYjYBTwO7AaeALJyFrE/ 8tDKPLQyD63MQyvzoMMlIuMXQrIQkoUiZw9oJuMTsQtzCzuDPPYHGqAJ6KAoZXsRug9JpG+I6S3+ L3CNJPJ50o39SjJQBQ06hrInGUeWC45K3HVht8m3ANezqwe0AFoDWgPaBNoE2graCtoB2gFaDc20 flxHCWvonk3cqSW4Cds8iX0s/zZFGXZCMowLGb+PYipsUyR2ruArwFdgPVfwu3F9d6DVLMV+lnIZ vkNbuAw7NaW4Y+2AZYxWQ5caezE1vwdte4fq0KBHWS8BIaVDjXpKS+k+tQM8fYKHmgyQNUCvAblG 0MYEDUkjLGU98IaYtiFNWG4SLTeLyEpbE4haKcJ2K3TZkGNDDqWhkaU7EylqtUPGnqBRyg5bHfx2 4DvA3Rgze8Ux1IHecGJmcqKkC1owgjk3aLe4q2W0F3tCL3K9qGM+9jztwBXAevbLA9tf0dU2kW4V 01v8zZjDDtIVI5Gyufhl7MQWQ8MyNpLkHsZh73tgb7kDuYmdJHbN/EtA9utlJehK0O2g20GvAL0C dC3oWtD1oOtBV2HUzqc2sNkuYTPdh4q7zwT3A/y1JrEfx6hdgB5YgB74OayqAKcCnAqM1Ar0Nd1v o70sxY4c56SSnQ35Pdh3LmI9Kz2C/l2MOqqgqwr9XoWRugRnrx3jtR09ynqJjZxlkF2GeqsxPqrF kVOd4KG+5SixHD29HCVqQNckaEjWwF7W9q1iuh/pZrFPEvavFJGVrk0gaqVI2tHDTNcq5KxCDt2T ox/pX4Stg3XIq0PNdZCug431GKf1aGk9bKkXbanHWJFwDZghG1ByNbSsBt0IulHcoTO6CXvzJuQ2 oY6qRE2QWY2d/hrgfP4LiudZ7/NzCVYe7Ot0QAvQhd/SXInRwXaXrGfw9y3+ZqxCiXx5YrzQnfxB 7LR3YLfMRvEZxpEfBkcj7pZxl8DGI0X2e70KtAq0DrQOtAW0BbQdtB20C7QLtBaa5ay32e4a1lgS Y5mmCW7CNl/i/oONZaLArh4zLcFMS+KwTZm44wBfCb4Se2wlOzfsLgOtViXGBbV4N5CePQWHHbZa vNM4CMsYrYUuLfbQWh73GGxEszsN6DAkEFIG1MjmUylDNraIMcFDTSbImqAXOzval4w2J2hImmGp JTGKkO5Hulnsma2wzQpNVpS2JxC12slB6MJcSu81WI4DOY7EiGY8SDiR50zQkHbCRhcb0RTfAe7G WEnY4kqMaOLGLsWNkh5owY6ReEF7xbuQD3Cfwe4//Mj1ow5toibIeHA34wPKMaLbmaTkbtwTJO5L br9X8CiWAGuBdcAG4DJgI7AJuBa4HLiCIZtdKHaCs4W9laLYQvUl0loxrRPTBjFdJqaNYtokplS7 4gazhmItsA7YAFwGbAQ2AZk1AVgfgPUBWB+A3QHYHYDdAVgcgMUhyIcgH4J8CK0NoVQIpUIoFYL+ EMqGxLKshSGxhSGxhSGxhSGxhSGxhSGxhSGxhaFECwVYLMBiARZTbAAuAzYCm4DMgggsjsDiCCyO wOIILI7A4ggsjojyy4ErcC/aAWTnJwV6UqAnBXpSoCEFGlKgIQVlU1C2J3LvFrER2ARcC1wOXIEx 1QFktaShljTUkoZa0mBtGvSkQU8a9KRBTxr0pEFPGvo3TezfNLF/08T+TRP7N03s3zSxf9PE/k0T +3c8+nc8+nc8+nc8+nc8+nc8+nc8+nc8LBioqAI+D1wFrAcuBa4GrgG+AKwG1gBXMmRzB8XD4LA2 DERUBZY+L6arxLReTJeK6WoxXSOmL4hptZjWiOlKmkokmbA1E7ZmwtZMWJkJKzNhZSbsy4R9WZDP gnwW5LPQtiyUykKpLJTKQtuyUDZLLEvbJlQzDRSfB64C1gOXAlcD1wBfAFYDa4Csd4bChqGwYShs GAobhsKGobBhKGwYChuGsmitFJuBLwGrgTVA6ESPD0WPj4T+kdA/EvpHQvNIaB4JzSOhYSQ0PAT5 hyAzBvQYlB2DsmNg2xgxdzVwDfAF4IvAZuBLwGpgDZDZNga2jYFtOdCfA/050J8D/TnQnwP9OdCf A/050JYDbTnQloPznyOOpxxxPOWI4ylHHE854njKEcdTjjiecsTxlCOOpxxxPOWI4ykf9uXDvnzY lw/78mFfPuzLh335sC8f9uXDvnzYl4/W5qO1+dCdL9qaL9qaL9qaL9qaL9qaL9qaL9qaD1slwmcY cZ9hxH2GEfcZRtxnGHGfYcR9hhH3GWwqQBsK0IYCtKEA1hfA+gJYXwC7C2B3IeQLIV8I+UK0uRCl ClGqEKUKob8QZQvFsiuBzN5CsZ2FYjsLxXYWiu0sFNtZKLazUGxnYaKdShuzg+LzwFXAeuBS4Grg GiCzowh2F8HuIthdBLuLYHcR7C6C3UWi/IvAZlpnEdkPy4vQliK0pSjBwfkrwvkrRg3FqKEYNRRD dzF0F0N3MTQUQ0MJ5EsgMxP0TJSdibIzYd1MMXc1cA3wBWA1sAbILJkJS2bCklJoK4W2UmgrhbZS aCuFtlJoK4W2UmgrhbZSaCtFX5eK56hUPEel4jkqFc9RqXiOSsVzVCqeo1LxHOXiHOXiHOXiHOXi HOXiHOXiHOXiHOXCjlt7oCViWiumdWLaIKbLxLRRTJvEdC1qLWIrGMVaYB2wAbgM2AhsAib2KIl9 yRIxrRXTOjFtENNlYtoopk1imqi1DLWWodYy1FqGWstQaxlqLUOtZeLKnVitl4hprZjWiWmDmC4T 00YxbRLTRK01qLUGtdag1hrUWoNaa1BrDWqtQa2r8KR6eQKxl61ltPIY6FXAOvH5dgeQ0S8A9wA3 AVuQ2yLSXRTXg94IPIgn2+8kELvkA4xWOUBjvy7pEJ+KHwQy+j3gn4GngF3I7RLp31DsBn0SeBP6 ryUQnK9Ry4RELvAb8Vn6QSCj8auRNAVoBaqRqxZpWotUD9qMO9z/RGz7T8S2/0Rs+3dFbBM4kogk I/lnMW5uRaBR0au6n2TubZ5OjHOvZP63vkbkNHdR4pEEJCEqkUJ5aZJ8SYGkUFIkKab37qWKVsVH zIf87x2Kz+88qJY7j9DfHoL9zoP5pP/dI+Wvjp7MY/2OI+1vDyH7zoO25R8cwrk7D9rmO4/Cv3co tXcetJfuPObi+Pbv4r86Sugx8x8cpX/vUD78V8djf3U8/VdH5Z0H9/+ihxXhTnJuLoPL5IbRVYB9 g/Db7w+W0fm6iqvh6rgmroXO+q9yW7nt3G6ujc7wR7njbOeDKAb/sxj6lzDtX8F/4Efl4zTSI/xc 2ZfyPHmLolgxQ1GuWqt6SbVNtYv73+nblPDn0tDER6Ic+94uR9ayr3LCJ2sTeY19RZv9GkS2kNcp zSJASsk28ia8ON6i9HbyNqVZNEgp2UV2U5rFhJSSdwj7fgqLDCkl7eQAvgfSQel3ySFKsyiRUvIr coTSLFaklPyaHGPfRKd7Hil5n8XlR9xIKfmQfMi+K09OUPoj8hGlT5JTlP5EspDObiySpFRSKamk NIsnKZUslrJvBrOoklJpXHqUfV+ZPRGlK1wj+6Y7/wdOyl/gL1CaxZmUyu5VLOZIYj+ueF1D7UTM SanmN9qBHL7lgx6ScFvEL8qw+O8S0Y/lDTEeZiulWSz4hE8LQUR4CTxbCOLCS8QvorDo8BJ4uRDE iE98HYUgUrwEHi8E8eIl8HshiBovgfcLQex4idgPLIqmFN+kSPRAou0EHjJEejfbecJPhrAo8JRm 3jKExYKnNPOZISwiPKWZ5wxhceEpzfxnCIsOT2nmRUNYjHhKM18awiLFU5p51BAWL57SzK+GsKjx lD7Hehg+NoRFiuck8LQhLF48pZm/DWFR4ynNvG4Iix1PaeZ7Q1gEeUozDxzC4shTegO/gSLzwyEs mjylmTcOYTHlKf1zfjOti3nmEBZfnnJe5+kY49/j6VmDrw5hMeUpn3nsEBZZntLMb4ew+PKUZt47 hEWZpzTz4SEs1jylmScPYRHnKf0J/1uqjXn1EBZ9nnKYbw9hMegpzTx8CItET+nzGFHM24ewqPSU w3x+CItNT2nm+UNYhHpKf85fpZLMC4iwaPWUw3yBCItZT+mv+Bs0l/kFERa/npPAO4iwaPWUZj5C hMWspzTzFCIscj2lmb8QYfHrKc28hgiLYk9p5jtEWCx7SjMPIsIi2lOa+RERFtee0sybiLDo9pRm PkWExbhn0cJkPkr7ZX5KM/8iwuLdU5p5GREW9Z7SzNeIsNj3lGYeR4RFwKd0siyZXlPM+4iwaPiU w3yQCIuJT2nmiURYZHxKM38kwuLjU5p5JREWJZ/SzDeJsFj5lGYeSoRFzKd0X1lfqpl5KxEWPZ9y BrDrF18MIfhiCMEXQwi+GELwxRCCL4YQfDGE4IshBF8MIfhiCMEXQwi+GEIUW9gMAD8owuLCcxJ4 QxEWHZ7SzCeKsBjxlGaeUYRFiqc0848iLF48pZmXFGFR4zkWyo+Dx6v4bUR7Pk0t4HL2CfFye45c mVIxrOILLVFImsvtD1LWAxJCeqnjSrmsh04qccm4+KNyVQ854Ul5Xwm9fsbEH473vI3jafHN9dCF kR0PcXn0JmgaXRYfpzc4j9PbIXrEg7cp4y1/Hnu3vOG14gGPl0/ILnc3TVva9p6qudzUK17OT4qX S0c0SyVEIlGlvmI8kf3NhBfe3X2rtJeaMr1Xj/hdcukjvNocun/a9GeKp/y4oCSQ/NhdgV79+/cN jJzyWPG0p6ZNLgncP614emovX9yTELbemTOt+NGSKdOm9grG/SxfanZ8mz962rSSwH1PlxRMK55S 8kzcZ9fG+8b79ab/0nrFe+fatb160z/voUz6Lzf+DPqKKpGbJY+M6WWOG9kfgln1/UefKpgy9ccl tBpDXMeYCrNi9OP5P5k2Nf+WYap/ZFg4HkwY5ro9P//xwJgpP55KtQay778vXk5Cce1fTiAhMk5a TvQc5ask5YRwbz7zbNcPX3+g/4Y+m3p1f5l0z4Mzd3/lX9v+wJN/em/IuWNL33lixOi8K6sl74w8 /mDR3ZFBj/+yM/ymetibzz390QM7Ny7XZe9P6nG5+VNt2P/efZHreat/5Xzgv54f7l99+PW7Q+8M /86caR9Yffcu7W/o/9HOu65Mvvc7pPc3N2PD1r9RRCqbvtq+5bHnyr+c0DxvwcLqzZdba3/6q37r sxfaY5WjPopf5QZeafty4LxdFX8s6v9yap+rW1NfUz2bt2LW5KaGp7QVr13e93ngrYdMyx57t+cH vR9wXnx7eN292WMcnZMffmbjzysPjBv0Ynn2oqmyX9yzpzSyc/TkgatHHepRljZ1wVD5e2uPDK+Q TK3g1u2u/HiMREoH/k/nXY/P+yJupt3pTeI1cZVcoENXJlPQZXleC+MSfl5jfF79XMMPjkz/05Ti teGHyyxbRlZ/8+5Lxf/nx1u5ntvDLcnIWGR8b9DVxy58PDiuZzaaCfmGl8XpHfQ3cS9j6Hgbbznk 7ZzBTf/Ba5917xvV+HBW6k+zHrsUV7NsPc/Ty6jitktHykZE6Suvlg2PXu7cMaqkJSdWkvL06xVf vzKidhY38vcdf3CcmLJf1zLnc8n9bR2Vh66NObT3xZ3jpl16LOtnWdzFugONv/G0ql90amvf7/b9 /K5n//TH9U9tWn6yf/XAhsId/X5ydNFr4a8//n3XFOWKRTtvfsK93efzL+Z8aTClyv5wV93zmU8k P/lmv+WnFNqDPyw4vHPufU9M3vD2m29X9+m4LDXMmf3no6cyPy69+cknm25e/fg32tend6387UPb +rXM+c6xgR/2Uef1lbw4rzC8+OqEx5Zvzn27//uTlj6ywJX253sbmss1LT9a8nrPN1/6r3df6Q5s +2XcuTBg0absGH3lvlMT479dmTylcs/005+//Ern3MziGTo6x8ymc0yeOMc8Ko/Nw1wo3H4dyeg8 83/xqmYTTj860/Tu3at3n3vuYRNOPN6L/ZnG/ozPm/9vsU2LgUOHLj/yoezRt8Sl/0D8n849O4u3 Lv7U8+LC9pLWSROk6QObvl49u/GuIaHNL1eO+ePFIQPafyBTf3/Dmx2yQ78eMXPo9IWv/+7dj3/8 6U+/Lok9/+MX36+SZsXbvji4/eAArzAu6yG7oP1yq7NgY8Tzlez7C3+/f5Qi2PflP3T2vHtb5uGg 7OWus79O/n67e3bnXemKw2sfOfT2Z6E/bAiv096196sj7+QOemxge88H1aXPLLy06E//oxozj4d6 6+P4zNiz72TfMsY2gwzGzkiW0GhSKBr7OsaYiaxjXyNrQqj7lCXp2rmWFBUi3ESy54YUl2Qtz9Cm ruf1PK/X87xur+e/3/ec3znnd37n+31/P9/j06h3eupaBePyiU2J8Unh/lfZZ9J+UZQFh5zkO+HG oKC/4OThvaiSswC6lV0wkkXDwqTO4zrpf8yAY7wu4YmfZ04pIEdWd8Wi9vS788jwWblA6Qbbx7z2 4Ftpegfa3HS3qxTKrkuJjnLN9H9mzxo0bGV/9nyLYrFeX4hJ4+a0yIaP4GXOXu71+/+I2z0+Aead qCcHMk3oLjcExCh5oFyh+4e9/s4LQpQaUARUNR+efzhK0QWPx6rJy2NwHnKeX85QDuPtKY91d91p lcfivB38MHhfeT0U2fHkyE1Qwy9fCARSqkPVoCpfbCgoSubzhEQicb8JHXF7ZsL/EFC79NGT6sE0 ekz5et67/MyTIQbRbugbINEtMwm/kKt0tVGsu2ls0Maf1Z3dQhiIqcOt0k61B1lAuMC/9766Aunh Yexj90mRmkc3rg+0McrfdpT1NEVKoXERZlp9bgI654r8bZIWHxDjOkFgudwHOdLTdRC6kfnMyemA xDMsMaiCETszYpaP3U1r1ZT+EjYhqtl7yKL+Vou627UvtqgjAO/w14a3uwTyxahoXkoebs1M5i0m 2UnObEZIC/ZSdib1kBif3TTV0/brGx0hLsTZuDNHO1ysrK+pL3G2FEEWG7m8sjwTz2HjfH4+2YaC JYU2V1w4c2YMwIotWv8Vh60pm2y9ygUi0yeXTJ/IT/RhcaO/bNYCkChhHUYKWQU4F/7IoJ+jdZSh qjBlKAyqpATfQY8q2fwJWsfS1dPRF2/vif1Ptc4LuNfm7Ye6Rj48D7sNNVEtGyUc9TIKDWxmxx+G v9FUHDoKuwSuTnEYFzKPqG817g2hWlvwa4p/cPNpmSvW6byk00x1zUJk3eO3xR/YrtOfEpWS79Ee QlPyEao8HTyNLIdH/hxtvhr+IHQsxAQET1tpyaNFC7oceTzUQrCRD6qWoKxEW7vxY7ZDA9XfPqWU MFUl4mlsW20Go+Ayfo+Y5gRV6QIJH3M9vALG5zUvZub5MJ2FmPGcs1PI6ws/Ji1q44KMH5WPYDH/ db3qYKLHW4kr7GudLM8imd6RCL7K7ekBhV121PNU5VGKNWtp1hE6EVaRaV7lQjKGXd45euNuMyGH ktw/8YYEBJP/iPh+xKH9/1A7LNR0nysLTuCOhAHsAaX3zDGtzDqlEuOoi7/lzJUidPTan0B5vw7g AFEyCB4AoAB+5CpED6DzvRL6i4zaB1Bppqyw1kDzBtakAnsaIFMCFpm44GvZqEVHJbtda4GK5H+j mlJzDU0/mlCN4OvdLL3xqOaOhQifN61rsDtFoajBG49Kz0DRWoP+iOVE5iaaOOW7r4NnsbbIq5f6 urpHklommiGPA+cflSk8ja7rxNxX7uURaSaMIrIr+HzzRGIGKyvZLBPe5bQ6GmWDD+XYxTEjHrA7 njds6LkVrmZWfs5qFDo7qyowFbv0XDVsnV0kwSEUQ02ZsZQN0pO/YBBTvw0aclw3Gn1OgU+toPJi 6Mp9AbYPNPyTO4dVRAXEH11K3ZahUDut3Y7SaCyKHZ1xgie+E83I6SonWlqoDeD0fxV7TwZUMRlQ l77KozTZXXlE9/Pk0V9AsCuPoHCFw2Q0KcB2GaX4yYTtmNCwir9DHklCJT6Zgl56rlgXR5ywPgop jEQdU4PrqCjIKquo6MiqGqgqwCSgYp/2xP/9nmRRO5sSRjniCK4Yx3+Lt/SwA8K6PBYBQ+lvrnx4 Ed27yXSRfa4YDmYjfDQ1LyFkQlKPjBehXUHTacGmkcMhPgt+gOEGPY9N71KfRenewEvdady5BW31 66vBI/YTslDBnEOyBK0/DDKSygZj4YNdC8s91ve2XMaXHC5embnHtn6tKWJrIL6bSqMRSDCXpFiL qOGKSrRrspWSUe/55UPW6cMCZlwtKoOC9loayhVoDk5iOoJlA1CeOmkLL5FswMgYcoSdmPKYK5JO T4xhCr4G+IUoTpMFwVLUQsSTs0fbCkWNm01OURMtcXrlmg4jqRG0VtUfZ6OP0ilXVKwpFgWbFPqH KJySYsqrWhlXz9OaN0DslVPfgABOj2kGIV4/T6sPMmDe6HwXnLvd+51S2pcY/41SwvtiMfb/E6X0 ZSb8/rD+Tv9Rt+xHK8Db0q3JvhinDqmp03WPAaRgbps28VNsDTdX3Z9Ff0zsrCII8Ym+X53oqKzT AR6E3zKEZ2A3uhRvgBNq6avx7OCaCr8JCN1kvNlYllZmjRJb2BzLiMCLeoeeY+YIk7gPvCMSZU8z oueM708vrutw2wJfn4wJIgRMe3+MFi5NzUnIbj57MJ8TKj5eGGyfIiAlde9osppeeOzb0afhI2Yy hxGvdHSAxQAG+qWBo3zduokXypdlE22lJpoSQ1I4CZV2mxySxd5sGF2wlVocIl77ZU1b16WT/AZo 94udl0zRVICONag28tgYb0zjCsviyMExsGClxRJx/NBUA10Y2wtBtSdIGInyMplY6SAgEBoW/RNL tu8KyW9XXflh93ey0+djo6OAMey9RyOv+82ihzFB9/ZykqnxdSAljOzqqLu37wl5etH2IVOwPZQh 7+9ydnRAHfYMYYChoZb5kFAwwBTgCsAAcADv3as4JwAeIAywBPgDsGTLmdxuT35yAfgXHAoV/5d+ ivfHejvj7LEu/vI/cImSBARkuw3golw1ZIIkhNrWOHKV7qSG9khaRwJDmq+v8ZzyO1ysg+5rjwwq yVps4xaL6D5iXcjWUT0ZXZ8XwutZlMfY4hd7wD7c/86ENL4lfRwpfnPz5f2hqq2R4gzd1xq+RPFH 9CX0hohxX80rM2WhDwYvWCWRZGkD0m0d4lX4Z9UMzt0stw5akOTiFuUhttxxQS3npiY+F80c3Zil uW/NIoN2syDyl05of+hf89YYkJwk0Ycpt6SyQRoFFhvUU8PhS2Gs1Fs+ySgmihsNzCsNTjNZHCfh HVEpiyzCVm8QywMnKrsLYjBjDjiI3GmE3xRDksjr1ZoAo63HFYaktGW9an/WGwUkkBCUBOL7dkbU MBKIgdxE+7c7448J8ru0TfPZGfNtoTx7PZH+27UvkLzm1x4qGDM5ve5kUiiMnFMVyPn0R0c8n9w3 nIhipG+oyImSRp2Nw+g32fxApx0XSXA1+P1JuwCNx0uWKM0DJIonzdf/qF8/DsOCYoUWkl0faXPc NV+dWza+Te1ay9uDuq6rSQRG9oocz2cwfS+nyFt7C5Uhe0aX8wLa5w8mLJcmG6plyCTcrUYpRmCr VFtuI3EYgb9lcRalf9f6AhevKBBCbTz6iBdzoHdKnvWD1VBpIO0IE+GGPgWLhXkRrl5D946U9FXG KDd6CH0/U15BZps2fHUl2KkJO+SVt1RVePKp/sMrLhbHC3gKU9SdRPm6fysQRLpUyJUgZnpm3ovG Vl8HD/IrO78UXEGftInbNvHMIqmLPxveNDJWEgyjefM+cNDVhyrI0CfYaJH5ib1uqJCE8z8Bokbm hw0KZW5kc3RyZWFtDQplbmRvYmoNCjIxMiAwIG9iag0KWyAwWyA2NThdICAzWyAyMjAgNjUyXSAg NlsgNTczXSAgOFsgNTc4IDU1MV0gIDEyWyAzNTBdICAxNlsgODQ2XSAgMTlbIDYxNF0gIDIxWyA2 NjIgNTEzIDYzOV0gIDEzMVsgNTM1XSAgMTM0WyA1OTcgNTMxIDMyNiA1MjAgNTk3IDMxNF0gIDE0 MlsgMzA4IDg5MCA2MDQgNTY5IDU5N10gIDE0OFsgNDYxIDQ1OSAzNjVdICAxNTRbIDUyNSA1MzFd ICA0ODNbIDI4MF0gIDQ4NlsgMzM3XSBdIA0KZW5kb2JqDQoyMTMgMCBvYmoNClsgMjIwIDAgMCAw IDAgMCAwIDAgMCAwIDAgMCAwIDMzN10gDQplbmRvYmoNCjIxNCAwIG9iag0KPDwvRmlsdGVyL0Zs YXRlRGVjb2RlL0xlbmd0aCA1MTE+Pg0Kc3RyZWFtDQp4nIWUT4+bMBDF73wKH7eHFdjGNpEiSwkh Ug79o6Y9VT0QcFKkBhAhh3z7mnlkN7BSipRYP3lm3vPYmjDdbXZ11bPwW9cUe9ezY1WXnbs0165w 7OBOVR0Ixcqq6Eei/+Kct0Hok/e3S+/Ou/rYBMslC7/7zUvf3djLqmwO7lMQfu1K11X1ib38TPee 99e2/evOru5ZFFjLSnf0hT7n7Zf87FhIaa+70u9X/e3V57xH/Li1jgliDjNFU7pLmxeuy+uTC5aR /yxbbv1nA1eXs/0x63B8D5c+3C+xZb/8KiLCmNvfQ/o9ML7nFX/ybkjjAnHSEqUgRSQ0SIO2oIVF Qarw0Ucc30vQsrGP8mourwyFqYgk1AokQBkI1jTqqnggHsG25k/N8Ig8c45maDExY2ZmOIe8hgSH vKZecJGAqBdcjQUNaMxLQBvQgkijazp9btRQu7hBx/W0a3pu1IwSW5JIFkQmAuEKDfWQL2DUSBCM GhxwjSvy0k+tpVSCpxzRemJNzq2luFCD06ejmdVAUkFQPO+FxJuQKsFLljAtsulL5jNlqdY+TvhD /qd6hupbRKeT44h5UY0DCOq0NDGS5KOE+CBhIJGg94KehcyokszwHmRknx0mlrhhsX5UGsbAMK3e Zkxx7To/Xmik0VwZJkpVu7ep1zbtkDX8/gHx32tXDQplbmRzdHJlYW0NCmVuZG9iag0KMjE1IDAg b2JqDQo8PC9GaWx0ZXIvRmxhdGVEZWNvZGUvTGVuZ3RoIDk2NzIyL0xlbmd0aDEgMjAyNDgwPj4N CnN0cmVhbQ0KeJzsfAd8VFX69jn3zmQmUzIzyUzaJJlJhiRAAgFCCUUykEKJlJTBJBBISGgiAqFK E7sGUVexN+wF1MkgEsWCir27qLu6ttV12V1Q7LtAku85970nBHT9y3+/79vd3y9n8tznOe8p95z3 nnPuOybIOGPMg4uBTS2unDDuyKrvejHlyHzGvBeXjC2uSn99wM2M/bifsZSMkrGnFo2snGlj7Mvr GIueOq64pPTPz357lCk/rmZM/XLc1CmVC5pGnsu428b4TbZxlaGxz330WSdTwomMjZs5pTJv0D8+ /30KY/x3uGt946KGJffeGnmfsT7o07C8ceVyf/jGvW8zVrudMWPK3CXzFv3wwySU9duI+yXPa1i2 hKWwAO5/Mdo7551x1txRK3ZtYWzWi4xVmufPaWj6IrPjFPQ/A+VD58Ngf8CEuhx1WK/5i5avLj2U kcCYUsBY1tsL5zSfeauydS1jb2F8jqFnLG5sWPr0rKmMRd5kLK10UcPqJelDMs1o34b2/jMbFs3J Wln+HWOfoE5M/JLFy5Z3etmFGM98Ub6kec6ShQ8pHbj1TbidkwnfGm9ps9obFs1yjPqeJaErpN1/ W/eq4Ocyrltz5HD7pugDpkeQjWYKo4R2UayD8b2WrUcOH94afUDrqVsyjBMWRwarZ0Y2F1CYk+Wx OYy5rsB9VZSqhhx+BUrMxuuN+egyjVh9k12oMDNTHEZFUQyqYviUKZ1Btr1TGwHSpEq/nwUxnWIa g+kWJcvP+K2iTN1ljBEzRe8xx0bD38CIbhPP5eSSoZZtNxSzhp8tO8C2d8+r+4/P/7OkPsC2G21s +k/6O3qsvWL4dX0d1743tVHrfr5t1Hu4b9+fLzOeyhpP6l4Z1I9xNms0VJ/ghwfYuJ9ro37BHMfd M4Pd/6vv18IyTGnslJMZY0/qSSKp77AZJ9vGMJhdr85mtb+ybv1x9zvC6n5NO2UpyzzZcf3/TOpe NuTX1BO+kpq/yy44mXvwv3a+03W/O47r5/qfqx/VxK7vfr+fjKXg1z2zrvp6X+IZKi8f36+azsp/ TR/Kgyz9ZO75rySMc8uvravezDKMbT99huoq1ke9lWX8xN6H1fyr4+tJPakn9aSe9N+TlBu5RWp1 5y+/v3kn66v0YuOB3YqRXdvd3tVHDbsYyDnZcagJJ36H1Me3jJVo5Uc7f/g1/SiL2AXAGmU5ewo4 qXiA7sNu+R/rDGGbTrbf/9SE78kLda74N49jPPAg0AzMAwYAc8T4gEYxvn/nGJWbWcH/1f5aO8v+ 1T4Q343vnsfaLT0hP7ObLgHm/Kv37Ek9qSf1pJ7Uk3pST+pJPakn9aSe1JN6Uk/qST2pJ/WknvT/ JKk6Uui3JbxC+1s6po5mBj4Uhl7Mzwz4MGZnGSyTFbIJ7DQ2ndWxNWwre8Dv9Mf5k/yp/uLOTq0/ O+pnst5sDCvTajV0q5Wi1eKd3zNmcOu3z1R7MdbZqDz32ezPGj4bi8/n+u9t/EAGm6r/Nczyn45c naheq25Qz1YvM5yihtRmtVo9Qz2gHlS/VL9SD6lfq9+o36rfqd+rp6nTDMWGMYYSdRJm4mKxLBHz zWLZLJflsVFsNCtmJRjvaayG1bKZrInNZ8vYcq5wB3fyZJ7Ge/OpvJbX8QX8DL6Yr+Ar+Xp+Cd/E L+VX8Bv4Tr6HP82f5y/wV1kUP6CN7uuf/PaJM0X/e0eF/XLix+YnhGG4lj3ZmbKfmSv757PVnboR OEcfxv9m/v/ZSe0mMWN1pjoL166/nTT0PqneenbI/2KFBMc1zZpZN2N6bU11qKqyonzqlMmTTi2b OGH8uNKS4qKxY4KFo08ZNXLE8IJhQ4fk9e+X2zsrs1cgw5fodjkddqsl2myKMhpUhbPckkBpvT+c VR82ZAXGj+8n8oEGGBq6GerDfphKj68T9tdr1fzH1wyi5twTagapZrCrJnf6R7FR/XL9JQF/+LXi gL+N15ZXQ28uDtT4wwc1PUnThiwtY0cmPR0t/CWJ84v9YV7vLwmXrpzfUlJfjP5arZaiQNEcS79c 1mqxQlqhwr0DS1p579FcE0rvkhGtCjPbxW3DamZJQ1N4anl1SbE3Pb1Gs7Eira9wVFHYpPXlXyDG zDb5W3P3tFza5mSz63NsTYGmhhnVYbUBjVrUkpaWi8KunHCfQHG4z5rPEzHlOeHcQHFJOCeAzsoq um7Aw8ZMZ8Df8j3D4AMHDxxvadAtUZnO75mQYopdbkK51Axjwwgxv/R0MZZNbUE2G5nwxvJqyvvZ bG+EBfNyasJKvSjZI0s8IVGyUZZ0Na8PpItHVVKv/6ycnxjeONvfLxfe134y8YNyf1jNqp/dOF9w w5yWQHEx+a2qOhwshgg26HMtaR2Qh/oN9ZjEAuGG8upwXmBJ2B0YSxVg8ItnsKCyWmuiNwu7i8Ks vlFvFc4rKRbj8pe01BfTAEVfgfLqR1l+5yetg/3eHflsMKsR4wjHF+GhZJW0VDfNDfvqvU1Yn3P9 1d70cLAG7qsJVM+pEU8p4Az3+QS3S9fuqLXC3E6oLSuLmZsyzf5qxavWiKcFg78Ul8DYUShw4nFp WfFEx47yV3Mvk9VwF72GUMf1g4yaWTReFKmiadF4b3pNOqVfGJJXH5MxM2zu1pcThq4x0X3+6dCo thhQH3/JnOJuAzyuU6M+QL23nx+nInyh3xgtzOJxjpdFaiZ2LmwKutFM4ikm+sNsqr86MCdQE8Aa Ck6tFnMTvtaeb1lloKy8tlp72voqqTouR+UFlAuzdBTLjFKENVia45WPVcuP0/Jd2fEnFE+Qxf4W c6CsskV0HtA7ZH7sIEw6KmtCw6aC2MHYmqU43QKlDQG8ZEpbGto6N85uaQ0GW5aU1M8fIfoITGhq CVRWj/JqY62oXu9dI24Vy8p4WdXYfrk4e8a2BvjF5a1BfnFlbfWjTrx7Lq6qjihcKaofW9PaC2XV j+J1FNSsirAKo8j4RUb0VIGMWavvfTTI2Eat1KAZtHxjG2eazSxtnDW2KWRzSpsCm4FsQc0mEh5S 4ny4GMdtib9JPJ51NfNb6mvE5mLxeJT44WEeGM3CSmB0K1eibGFLYM7YsDUwVtgLhb2Q7FHCbsLC 4PEczhFnUkt9AOcUFlQ183Jaiqro0t/W2VlVnf6a92BNOpbaDKC2Ohydg7PfmDkR9cYJ1MM8Lryx sUGMg4WqRVtT5oTGGixb2SGqTAhHo4dovQfUKNXaiOWIRo14NniAWvuNyIQ31oRrcsRNqxfUaMvZ GWbjAyPw2KlPY5a4UV5NS2xgkLY3sRUsmRcJisbYWGU1WbzI4mY15CSTDSNvDKCosd4PbxtYYyWW Op2lFi9Z5uBINGTN0WDx6oVMTEvNtNot4ej+6BA/Qlv7iy1pzDTV1NDgtdxFegXc2xm2YkRZ3Vyp N4B3UDRBjAU/F2GoourTopvyNlYRWI2TRQxa68mE4rA9c0IDDn9qb4UlUCAbm8UZYdX72EtWk5i5 DX5XM6vaOu8JnJXeLfXLDYiXg1iYzPsoFjaraTnREJ6e0y/XfKLVrplbWsz2n29A/jLbu1gY/SV4 azAWiVb9bcr5D0cn8okQ50lxrhTnSLFRirOl2CDFeinWSbFWijVSnCXFailWSbFSihVSLJdimRRL pVgixWIpzpRikRRnSLFQitOlWCDFfCnmSTFXijlSNEnRKMVsKRqkqJdilhQzpaiTYoYU06WolaJG imopTpNimhQhKaqkqJSiQopyKaZKMUWKyVJMkuJUKcqkmCjFBCnGSzFOilIpSqQolqJIirFSjJEi KEWhFKOlOEWKUVKMlGKEFMOlKJBimBRDpRgixWAp8qUYJMVAKQZIkSdFfyn6SZErRY4UfaXoI0Vv KbKlyJIiU4peUgSkyJAiXQq/FD4p0qRIlSJFCq8UyVIkSZEoRYIU8VJ4pHBLESdFrBQuKZxSOKSI kcIuhU0KqxQWKaKlMEthkiJKCqMUBilUKRQpuBRMF7xTig4p2qU4KsURKQ5L8Q8p/i7Fj1L8IMX3 UnwnxbdSfCPF11IckuIrKb6U4qAUB6T4mxR/leIvUuyX4s9SfCHFn6T4XIrPpPijFJ9K8YkUH0vx kRQfSvEHKT6Q4n0pfi/F76R4T4p3pXhHin1S/FaKt6V4S4o3pXhDiteleE2KV6V4RYqXpXhJihel eEGK56V4Toq9UjwrxTNSPC3FHimekuJJKZ6Q4nEpdkvxmBSPStEmxS4pHpFipxQPS7FDiogUrVKE pXhIigeleECK7VJsk+J+Ke6T4l4p7pHibinukuJOKe6Q4nYpbpNiqxS3SnGLFDdLcZMUN0pxgxTX S3GdFNdKcY0UV0uxRYqrpLhSit9IcYUUl0txmRSbpbhUik1StEhxiRQXS3GRFBdKcYEUMuzhMuzh MuzhMuzhMuzhMuzhMuzhMuzhMuzhMuzhMuzhMuzhMuzhMuzhMuzhMuzhMuzhMuzhzVLI+IfL+IfL +IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL +IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfL+IfLsIfLsIfLsIfLaIfLaIfLaIfLaIfLaIfL aIfLaIfLaIfLaIcX7RACUXMkbbQPMXMkzQM6l3LnRNJGgDZS7myiDZE0G2g95dYRrSVaQ3RWJHUM aHUktQi0imgl0QoqW065ZUTNZFwaSR0LWkK0mOhMqrKI6AyihZGUEtDpRAuI5hPNI5obSSkGzaFc E1Ej0WyiBqJ6ollEM6ldHeVmEE0nqiWqIaomOo1oGlGIqIqokqiCqJxoKtEUoslEk4hOJSojmhjx TgBNIBof8U4EjSMqjXjLQCUR76mgYqIiorFUNobaBYkKqd1oolOIRlHNkUQjqPlwogKiYURDiYZQ Z4OJ8qmXQUQDiQZQZ3lE/aldP6JcohyivkR9iHoTZVPXWUSZ1GcvogBRBnWdTuSndj6iNKJUohQi L1FyJHkyKIkoMZI8BZRAFE9GD5GbjHFEsUQuKnMSOcgYQ2QnslGZlchCFE1lZiITUVQkaSrIGEkq BxmIVDIqlONETCPeSdShVeHtlDtKdIToMJX9g3J/J/qR6Aei7yOJVaDvIomVoG8p9w3R10SHqOwr yn1JdJDoAJX9jeivZPwL0X6iPxN9QVX+RLnPKfcZ5f5I9CnRJ1T2MdFHZPyQ6A9EHxC9T1V+T7nf Eb0XSTgN9G4kYRroHaJ9ZPwt0dtEbxG9SVXeIHqdjK8RvUr0CtHLVOUlohfJ+ALR80TPEe0lepZq PkO5p4n2ED1FZU8SPUHGx4l2Ez1G9ChRG9XcRblHiHYSPUy0IxJfCIpE4qeDWonCRA8RPUj0ANF2 om1E90ficV7z+6iXe4nuobK7ie4iupPoDqLbiW4j2kp0K3V2C/VyM9FNVHYj0Q1E1xNdRw2updw1 RFcTbaGyq6iXK4l+Q2VXEF1OdBnRZqJLqeYmyrUQXUJ0MdFFRBdGPA2gCyKe2aDzic6LeOaCziU6 J+IJgTZGPDiM+dkRz1DQBqL11HwdtVtLtCbiaQKdRc1XE60iWkm0gmg50TLqupmaLyVaEvE0ghZT Z2dSzUVEZxAtJDqdaAG1m080j0Y2l5rPIWqimo1Es4kaiOqJZhHNpEnX0chmEE2nSddS1zV0o2qi 02i40+hGIeqliqiSqIKoPOIOgqZG3OIOUyJusbwnR9zngSZF3P1Ap1KVMqKJETfiAj6BcuOJxpGx NOLeACqJuC8CFUfcZ4OKIu6NoLGR2FLQGKIgUSHR6Egs3u/8FMqNirhqQCOJRkRcYmkMJyqIuMaB hkVc1aChEVctaAiVDSbKj7hyQYOo5sCIS0xsQMQl9mYeUX9q3o/ukEuUQ531JepDnfUmyibKIsqM uISXehEFqM8M6jOdOvNTLz6iNGqXSpRC5CVKJkqKOOtAiRHnTFBCxDkLFE/kIXITxRHFUgMXNXCS 0UEUQ2QnslFNK9W0kDGayExkIoqimkaqaSCjSqQQcSIW7HTM9gl0OBp97Y4m31HoI8Bh4B+w/R22 H4EfgO+B72D/FvgGZV8jfwj4CvgSOAj7AeBvKPsr8n8B9gN/Br6Imef7U8x83+fAZ8AfgU9h+wT8 MfAR8CHyfwB/ALwP/B74nX2h7z37QN+74HfsZ/j22bN8vwXehn7LnuN7E3gDeB3lr8H2qn2R7xXo l6Ffgn7RfrrvBfsC3/P2+b7n7PN8e9H2WfT3DPA0EOzcg+tTwJPAE7alvsdtzb7dtmW+x2zLfY8C bcAu2B8BdqLsYZTtgC0CtAJh4CHrWb4HrWt8D1jX+bZb1/u2WTf47gfuA+4F7gHuBu6y9vPdCb4D uB1tbgNvtS703Qp9C/TNwE3QN6KvG9DX9ejrOtiuBa4Brga2AFcBV6Ldb9DfFZbJvsstU3yXWeb5 Nlvu8l1qucd3gZrpO18t8J3HC3znhjaGztm2MXR2aH1ow7b1Iet6bl3vXV+2fu36bes/WB+MjbKs C60Jrd22JnRWaFVo9bZVoceUC9lc5YLgqNDKbStChhXuFctXqN+t4NtW8OIVfMAKrrAVzhX+Fapt eag5tGxbc4g1T23e2BxuNowMN3/SrLBmbmnr3LOj2ZtWCg6ua7Y7S5eGFoeWbFscOnPuotDpGOCC gnmh+dvmheYWNIXmbGsKNRbMDjUU1IdmFdSFZm6rC80oqA1N31YbqimoDp2G+tMKqkKhbVWhyoLy UMW28tCUgsmhybBPKigLnbqtLDSxYHxowrbxoXEFpaESTJ6lOFP8KapTDGByCkbCvHzsAG/Q+4n3 kNfAvGHvHq8a60j2JSt9HEm8aEoSX5x0dtLlSaoj8Y1EJZjYJ7fUkfBGwscJXyUY4oIJffqXsnhn vD9e9Yi5xU+qKtW4sJh44BBtrpPiA1mlDg93eHwepcTn4cz1ieuQS/U85XzDqTgc3OHodChBB6o7 Ynwxirh0xqjBmIHDSh12n10Rl067Gh+0wyJ6zLZNrSp1WH1WJVRonWJVgtbCotKgtd+AUqZyP+eM O0GqWYyCe3yl2Nc74rmR433eWlWZk1PWZmYVZWHz1OlhfnE4s1Jcg+W14aiLwyxUO726lfPLalq5 UlQVdovf2Gr5CzZvZmNTy8KpldXhrak1ZeGNEEEhOiFYams8G1uTM3PZimU5Octn4jJz2fIc7Qc5 vkLkcoRR/Cxbjrz4rNDyLOcXE1UDzVqGtFwal/9yq//0xP/dA/jvT61M/JHBmE7lfNaknAecC5wD bATOBjYA64F1wFpgDXAWsBpYBawEVgDLgWXAUmAJsBg4E1gEnAEsBE4HFgDzgXnAXGAO0AQ0ArOB BqAemAXMBOqAGcB0oBaoAaqB04BpQAioAiqBCqAcmApMASYDk4BTgTJgIjABGA+MA0qBEqAYKALG AmOAIFAIjAZOAUYBI4ERwHCgABgGDAWGAIOBfGAQMBAYAOQB/YF+QC6QA/QF+gC9gWwgC8gEegEB IANIB/yAD0gDUoEUwAskA0lAIpAAxAMewA3EAbGAC3ACDiAGsAM2wApYgGjADJiAKMAIGMZ04qoC CsABxpo4bLwDaAeOAkeAw8A/gL8DPwI/AN8D3wHfAt8AXwOHgK+AL4GDwAHgb8Bfgb8A+4E/A18A fwI+Bz4D/gh8CnwCfAx8BHwI/AH4AHgf+D3wO+A94F3gHWAf8FvgbeAt4E3gDeB14DXgVeAV4GXg JeBF4AXgeeA5YC/wLPAM8DSwB3gKeBJ4Angc2A08BjwKtAG7gEeAncDDwA4gArQCYeAh4EHgAWA7 sA24H7gPuBe4B7gbuAu4E7gDuB24DdgK3ArcAtwM3ATcCNwAXA9cB1wLXANcDWwBrgKuBH4DXAFc DlwGbAYuBTYBLcAlwMXARcCFwAWsacxGjv3Psf859j/H/ufY/xz7n2P/c+x/jv3Psf859j/H/ufY /xz7n2P/c+x/jv3Psf95M4AzgOMM4DgDOM4AjjOA4wzgOAM4zgCOM4DjDOA4AzjOAI4zgOMM4DgD OM4AjjOA4wzgOAM4zgCOM4DjDOA4AzjOAI4zgOMM4DgDOM4AjjOA4wzgOAM4zgCO/c+x/zn2P8fe 59j7HHufY+9z7H2Ovc+x9zn2Psfe59j7/+5z+L881fy7B/BfnhJnzWTMdAtjHVcd91fdU9npbBnb iM+FbDO7ij3FPmCz2XlQ17Ot7G52Hwuzp9lL7L2T+lv2/yF1nGVcxGzqLhbF4hjrPNx5sONuoM0Y 081yFXJxBv8xS6ez88sTbF92XNXp7GiLimUWra1deRvWb3l752G8X5HvHCryykXQDq3F16ZbOh7q uOcEH5SzWjadzWB1rJ41YP7iL9IXwDML2RlsETtTy52Jsnm4zkVuFmrhLNH0sVqL2RKgmS1nK9hK fJZAL9Nzomypll/BVuGzmp3F1rC1bB1br19XaZZ1KFmj5VcDG9jZeDLnsHM1JZks57Hz2QV4ahex i9klv5i7pEu1sE3sUjzny9jl/1RvPi53BT6/YVdiPWxhV7Nr2HVYFzeym06wXqvZb2C3sFuxZkTZ 1bDcqilR+jh7nu1kD7KH2COaLxvhNfKI9MtczYdL4IN1mOF53UZM/lvV5a0NmLuYW4s+09Wwn9ut xUrdj6LmeahJvdBzEL2sP8ETV2AOpI/NiHJXa/M/Zu3ulV+ySn/c1M0zN2o5oU60/jN9DbsZO/A2 XIVXhbodmtStmu5uv6Wr7lYtfwe7k92FZ3GPpiST5W7oe9i92Nv3s21sOz7HdHdF/CB7QHtyYdbK ImwHexhP8hG2i7Vp9l8q+zn7Dt0e6bI8yh5ju7FCnmR7cNI8g4+0PAHbU7p1r2aj/DPsWeRFLco9 z17ACfUye4W9yt5gzyH3unZ9Ebk32dvst+w9bod6i/0F13b2pvFzFsPGMGZ8DH6+ic3Ex4hTaZn6 Nk4RlZnYcDaJTWbTH2d2vO7j2Qi+c6enuNjcz/QkXuUK8yMYMDPOi4IOg2LflZxcGNg1JGqz6prQ xvs9XGjajDC3sP2j9tfz2j86GDs87yDP+/DTjz51fv26a3he/qf7Ph04gLvSXRrcMYrJ5I4KZPRX hmRnDc3PHzRaGTI4K5ARo2i2wUOHjVbzB6UpqltaRisiz9W3j9aqU9qjlA2Bwmn5xrRkh9seZVRS EmP7jcp0Vk7PHNU/1aSaolSj2dR72NiMsjNKMt43uVI98amxZnNsarwn1WVq/8AYc/gbY8yRIsMZ R7aoUSNnFPZSr7OYFUNUVFtaYlLfkekTpjninAZrnNMVbzbFumy9i2e0X+hJEX2keDzUV/skuCXQ ediwwehmGSyL3fwo69W5/2Gbk58aaNNFVlvnoYetEFYpLBDBZKEyneJq16427RrszTNFca6VT+oV yMr8zma1JWakBix2Hm+wMZvTpjwUeCrwRkAN2AK22NSK2JAxxAoLC2OHD8/Lq6tzJQx3QbrynQcH ufLh8Zw6ehWynJzM+PgozeXZaroaowYysrKGDuPk5wRTQE03rDBzZ6bPlxkXbVjc/sXpqiUukJKa 6eBmHjHYk7LT/H2TYwxr+cf8mVPivTEG1WSL5iM7Xoq2RxuMMd54Q8QaY1ZVs8O6uX2t+Jdi28U/ 8MLqSmM5rIC9GEz2JTr5JJ/TIS52XBJtuPgxV/E74mDvZE8Q5Z4gyj0ea66onCsq54rKuaJyrqic +xi+E7LOPTuhWVY+PL0DNcGHdjh0tmv8ww6bxvt3WAUrzqB9q3WPVbEmZ383cKCpl/ZfpcsHt3Fr q6mKFR4s1NbtcJ5X96nmtEH7ckjAnJMznDSc6o4xBNIzsoa4Bg/NT4f3PGI9p6l8cH8lEHCJxRx3 TBq4r2BK49IJHQ8m9OmTwLOWb2kcFJ8zpu+QGSW9O9qTC2onRvYWVQxNmpw5bmH564dHVhdl8WWn zKsY3dfjyzacm+3LrVozqX/VuIJYy5CKMxWed+qQlI66wMgp7R+OqB7l6yhIGVbBOGvoPGSwGdOw i2fvSGEjc3Sv5OheAR8QXgF/KbySo3sl50l8x45hiTyPpbMsnhuJqzTs5n3ZEDaA92+NnoYtve+g AM+j6Tvf3TtwQKY7Jqrbtozy6NtUbGCPO00R8xbLymBTjGZ3cNbaCRteuXxS5TVvnV1wem2p12xU DWarOWbQlKVTpm1uGjak8Yrpk5aVD3aYLFHqLmdibIy7T7a36s6vb77t6EMzPP6+3pi45Fh3Slx0 dl52yYVPr1v7xNljsvKyolxp2IFilV2OVRbLfGxVMLUwnceJlRMnVk6cG3OOi8WE4xIx27jdYuWw ZPJNsu6bZH3FJOsrJln3TfJufO+Phm9skZhybxvPajXSKpG+2CdXRJ040Y5bEqZuC+DyaXcdurvj S+3xZ967/+bynYMX33/hQ63r7m8ertxw75G7KuhBn3bH/usX7Dx/4lHX6I1Pi3/Dipmp6zCzXLay NTlbf6LZ+qiz9VFn66PO1ked3aa4gtHRcf44Pwaf3MbNQfvGLL4ni7+ZxbOyopLEL2js5dmg1qiu VV+3tBnTytOOEae++rXnrPxkpQfSXSdIdZ3BYje3XyVmqMw1281GIy4dUTxixtFgiIaerHCz3WIY F+uNNdNszbFed6zXZe44PdqZEheb7DR1DDS7vNq8Ow+rVZh3NpvRaorT5x2nzztOn3ecPu84fd5x mPdOeypLSzVhajvi4pKi2njvHRnlSeKA1N9IeXtdw7tmx38yGfm2kdNVqzAxUwe8Z8LgNR00u/3J iRluM6Zaqln3xqVgFuNNTq8nzuuKbv+TyW4yGnExPChmmSpmNL3zS8Nqo58VstuDqSkpjkSxQhPF Ck0UZ1uixSYUZpEonp6dPZXN/dnB7PpsNduhz9+hz9+h72SHvpMd+vwd4q/D8wbzwYlt3PJwRsbw vNG7uQXveAvvExle6W7jua1508Tzxm52kTv0c25fXd3eroNO98txu3noMJdYBWK3a95yiRPw2P43 GFYbzDaTrWDmebUL719ZWLLmvjmj1g7p2OdyGaLxjrjRGh9riR0xY3bTwGsO3DGt7r6DV0w8d05J ssUwMy41zpzVP2tyy5OL1+05vzg1lZ+V0QtuNJudKbEdcclZqRmJtrrth7bccDjckBzok5xB68Mw Fe/cPNb2cOFAHrDpLrLpLrLpS8SmLxGb7iKbcG5KQi+r8L5VeN8qvG8V3reK88Eq3hEJLOjBiyUY Jy5OFz+VBVHOEsQvLVAg+BGUJfStwAskN+jYY+Nv2rjt+LcxNtTBQo63xj7hVn3JHdtYdZldS637 qqNT0wOblIapZnd6YrLfbW7fAZUkVp7ZnZGYlO42K5O0tQiVDO9jydnMyuj2Z6Q2vC9V+2ElSmp9 f/Fq+M/Dpu4qTJiS8FCCynQXMt2FTHch013IdBeyx3AmWjr37IInLM4KbbqYZtdBmPmTyfBqOe5o T3pCUvfRHhuh3PV/x6jy2eyga6DYDAPEM8kTKt2ij8+ij8+ij8+ij8+ij88iHrHNk12RbnF6K5zH oqNCeWjD+7jSOLOysvnPuF8PijzuKBPn8fHq303uDG8gN97U0evEZ8BfjnImpCcn++NM9tiOSv66 y5QiDsAop0W5qP2srqPg2LN4WimMtpkMRhjsyQntne03JMfpZ30ZZp/Mxj/KPDRZjz5Zjz5Zjz5Z jz5Zj/h3DizaUeFp4zn6Yc7zXpMPo9vp3bWwxKFWhhM5un1vQp+uSbwpQrgytzcuGmfzg3KoR26L dqXoTyYqB+fxKLY96KwfvWS0Yh8wICEvz9I/MTG57Ve+TMWDSes10GaziN1nEbvPInafRew+i3jS FrG2ENcFk8RC6zW03JqYYM9LHNg/yte73BeSm6swFkFuPiYqozNEus4u5Rp+Sl5+voh9u63FABfx LiJfHjjujNdCX54vnrfmn6gcs9uXlJAeZ1Y68lWrJ9XtSXNblY5xHDstKREPOdc73z+gV2I0X2Xk F1qTfVlJixzeONuxJT3vyBaTxaQaEMrgy8X1Xfa7+/ayJff2Hj1NvTutb5I1Oi7Vo59kG4wudgq7 YEe2w+HWnamxQ2e7xoeEM926M92aM9Ms/fsPEs4clOgQF1Qc5LQJhSqDRBUnSyuosPR3ZBuSxHtQ rBDNfcJ5P/FdXr6+ZMhT2BuB+HjPz/grTU3Iz+q2qgwb7J5k+7Dk7EDA0zHfPyZFURRznC8x0Rdr zk2uSM32pbr4iNShgwYmcoQBcb6keH+seZwb36asqYOylU+Grx85/pqJR7/t2i33986wJPTxtb84 uLG+Lm/KtinKk/iugUjCZhL/74/GzoOG/cZ0FocIYV0w2S184BYLyi3CPbcI99yJ5Kb8YLSfDWAb 8W0kTXdumr5S0/QXaZr+Ik3TnZu2GyGxhSXhtemoDIidZZx2fNhX1+2bwHFfT7Wor1sMbNg/8aqP tlz5zqbiiVs+2nL5vs0lO7OnX7dkyXWz+mTVXtu89IaZvZVrbj7aOuu0u3/Yev3hh2ZNu+vb+858 YtPkqkt3z2ves2lS1eWPiwgXJ+P/oexLoNyoznTrVqmqVFpr0b6rtbdaUi9qdas3Vbfb3a1ebLd3 G7eN99iAF4wxYAYMGAIhDIEAcyC8hEnyIMkkgPHWNuHhnOMJSWaaRxK2vJdkmDMnD0KO3wyZeWFt 9bt/VUmtbptJRnarSqWWdO93//X7/6t+Beufj0gRN52IMtpEGG0ijKZyjKZyjDYRBkTAKfgBHj/A 4+dNZjTuhxzKDw27hBDDscJJhjHhaRpP2idNdaGSKiD8wmgpsjhE0tUFutQr8pEf3PRVTgq7wao0 epC9cWLPdeOp093rppq+8bVlu4ei1Fe3Prmvp5Kt6QVeatZZ2nTzuuV785bZj5PD29UV7qe/iFc4 QXQTfy37DWExCbNIwiySsMhJWOQkLHISz0Q2ECFfs++Yj/K1auC0auC0aqvcqq1yqwZOK+yqE8MG c2YapU45V8V0HbDUZljq12cAhOL8eteio2JLM60hkGDqUyAtB6TRIgnAszCYGNuGG473tTy2vSoJ 9//ywREp1ddY3jeStOkr318sFNc7gwITLm3sCTStffrDp574GCTjj/9t8pHjBzI9SxqsUoR8Z98P 71+26oHzX7j+5S9jMXmJUOVEZ8RyUiAGiYfkAJ8VOvR4qh2AWoey9h2AYgfA1oHnfzYF+XaqJABW +EzQMBM0gRI0gRI0zARof/ZleZxTnDkgI1l29mK5OR2edGqmWckkLtWAq8ufi5ptUeiHLHWZIDmc AUpLo52Sw4Hy8UQ8Xk2gjIwtGvCEbUbdEXumb3X3oaqI4YRKaun3jB1alogMbCqG8pmk7QaLvjI7 uMJdanvoO4PbB4LYNOux5cCGsSW/rhSZ/VVN9HB4TlPmzrX7l/TvXt5ls6R7lrVU/iXqp+4e3+Nk mcp4uHsFttHDc5eo7VgWy8S754j+ufdOWXk03q9B1K9B169Z6H4Nqv5psklOt8qSDY23ygKaiLZG W01eF7zWC27Py/Nwh1/iheXwnidbwPed9Cqx1oWTbu1oU49nrBCImrIvogTRgUP6uGwUQh2oQzaa 0LgAvTcGOOsQOgRHD85/Tvd76dQqB5ZtzXrhJbgkQHaXTk/xl3hQ8PnIVFSfWGTWdFXZVum5LPM5 6T5DbV9y5G+n+vev63YacSKgt7StODjaObUk2rpyz74vrGzr3vPQ6vS6iR6J0ZEUY2SNucGprsKK vKd11d59e1e1oWuu+uvtrY5QgysWdPhFtiEZCXSsaOtY1t3S1rf64PLJ29dmrO6gZBRckuiTOF/E 728eiBWW9bS29a46iNfIii3kW1jyG4idZ10yZFQCoHYKIti/2FxC+CHMXTgNks+IkDz6NYvYikPc DxRw/j7NX0zXUsf5IL5qCZQA6y0l5X2kGiviMy0lpo4rCbGSMX769ZogbtMLPklSSUWIt76H/dvN OBZME4/L/qszKARaGwItDoHohCBiCoHUwP5WWajPV7CkEQ5twg5twg5twg5twg5two7zJA+xPGQ1 0AQnc/gtDPGV/ErvvNwoSYxmB9PzIjKFLg+bNZNXFxjcvPTY9OFrnr9tUE2aJX3TqsPlscOTaQWa sMSh39547thA381njlCRKhyf/XHjPRsyTevvXEc56/ODBmzdvoBRiRL7ZH8UDFsyijxwjHtQ0oni ZtTkRk0u5J7WlFQ5AbPnql6BE1mES26X2xWPBVe6aFHNYsRiSRCRqggwQ2JqCk1NTaWn0jEleNRB SFQo1IWMrQ4Hw5JndRZ3wu8IuwQTS1U26JGYbPCFRU6HDiG0h9Jj0xWMmil9AMhRhON+o173gkKf 6s2GT1/WleA60Kcwx14cab+D59hD7D4Z70HYWX0kLwHFjmER1MNJModivHIlhhpccJJqQK4QnGRa UKYZZaIoE0EdKxtXRpqNVH1SiuO+El45fANaWPsXq0XGVPVs8TQXTpi+S8f7UoFg2mfRVT4gP6Es nlQo3OSzUpXvMUiIh4JRiSVRBCEbxdliAV/YxlEoRSI/xUgRfyDCIzpuESCaEyzUzz/LVc91f+f0 ACoW46cXdV1GK7baeqvx0x/rug34nLZ44I/wEpuwNS5RP8NZokw8L4esA8GB3ABl5Jx5ExbtPOhH HlQjz8N656fRh7KFSCSsBDIRoEFEl2apu7TYukvThq6qjHRNk3rZJjj/nsjzebL7Qh4ReZTPZ/sb p5FXtr7WgBoadP73s6O9vzZN6IhclUFTSJWpg5unqoHixfTmqaLGprViB7gZZyQQNODYub0ueGhr 12IG7YpO0R1WNa4OIF+oEu/zeoKW7ocmhw9NZvpu+M6eWx0ty4q9W8stJj0OjFnvwNpd+a33ro5/ +4HBHQPBDSv69/e6TCYc2Zk2loZiQ7v6xw+MxobyK9q9/ohfz7utbr8n4pea1ty2+qIzU0oNrRoY xOg+jtF9gz5INEJGchorvyFc0KxGQbMiBQ0veKzgVZhGH8leexoisnQIOGbAPw02K80r1DNpkDnC bii0h3V08zSiz8RHvUP8eBGfnqAnFCuDIXQWa1nJPGY1O5OwX25wVOGsBt2s4HAoYegbbdu/MpUu Dw0l9KLXjtMMhpVCLjfOOZJjIyPJbfevSz5rz6+VQ33y0sTgrUv61ne40buHXzw+JMS7UvuwzdHp sM2hO5XIAd/N/i7VGeGX3fX84aV37ugVGwdaK4+vWtez/SjW2I0YsRD1U6KduO+ET/HYKovyjsae vHcKktkrkLf/dyFpO/e+SuaSRtmcsyCL+92gbDCPBKPTiDwljVJ/aAF/xplHWpqmEXOCmwBmPn1J uasReRdrtO0iep5R3TVTT85TIZJm3T1j63NbH9vZ3n/w8Q3pycF2F8eQotma6FnTdeT2sDzVU1xb Spsgpf2m4BbM7phflI+ePHz3y7d0854Gl0VyiYlgOBk+++y6u9ano+mIXvKDnl6NcXmSvo6IE0Xi fjlY6kZGbxG0swjeqwjRTxGkowjCUnwRfUwQRE5FLaeBldPAymkam9PAyoFAGaTwkLGY8OosjbCB wDWKVV130jJBj4PDVsSptIinV+SpRgrUqyAOP2tSRcXj9QF8B/UkK/hsUPobfvyq7V9el2zd9tCW 5XfJrC0IMsU9veSvBktYgrBE9Yd75aGEuypARybWTtx1YtsNLx4fXrqENFaz29mlWHa23SoP3rkT y9KSFkBrCqP1OLZqaSJPPCs35gqlwv4CJYE2SSEgvaVwE8SKTYCWWg5T7BuWhY9PD6a/nSah0HMa tC2v04RPp8mY8tioHFUDpwP8wuGmV47pvqIjL+jQazqk0/lyv46Put6/2nLAQlq4932KgE3VVwdU pfxNWhU2pSamKCgTCdeJlX2h8JH2REEBlKUeT7hnXwgMHZiUd5RzJtbIUCTFGgtrD8r7n7m+q+fg U9v3Pnp15mnq5iO9m/oaSJJMhMduWpu1e+ysxS2aJavJ6HZJfbdM33LDuTuWDh762nrpzkey4zs7 wHPG5j4h76Fvwp5zxwsOHhRQUTyvZrW8VWvl1cyZVxMmL2yVbG6MTc+9JovA9sYMlwrDnvil5pHQ OD+iZDWtkPunL7Z9oOpY28VFHLldYwvrs5qIxpe3VTly8h7s+xnWHkh5Y/mQ5ad6I0eL1p/qsWly hST97TwPpub2yMh1o5GBqAnHBFbJaaE5I+dqm+zaxgoeKRr67A8QPkDxjLKHopJHYKc2f3Ftymw1 SV6ouLZXvkrdR/2E6COWEVuI12S7mBkGLRvW4ykPh3gJjQ+3lXBUARCUNP3Cx3fOwFMldjk+lc1W EY0v9+qszVQby4L08ApeF2QzPsm0sV4v25bRAcZyHkBeDx+xPsTjl61vjMlGfIxZm1mqc/R/mVa9 Z7df3Un9vmekMTTwq87Rq34VWq4VnUpqGeJN1fSn22YAXCcOwCAEE/BFfiaN/6erd4A6xtjhUF1B HGfg2EE6tcyxKnMd2L3mC8q9qtk4uUT5eM2dQnE2nkhYKO0RdZ9kvSPia506tqxju1d09hf+sOTA ymz+mqcPXvf4tiY+3BJqybXGgtH8pjvGU8NBxAtCpbJzqnk459x5VctIzrlqy+TvQykXd/zGsZ19 XuqGSDC6LrfsplVNfoeYDUSypIEM927o7juwpiUmb8iH+zrb3O7xpt6r47GpgYlbVmc4fbjywabd oc5ycsOuYMfI7OauEql3Z1JJe/8Sf3MfyPfjOMN5CnvmVuLmU6U8apwve2mCXVcP0+pj2C07A2px QylzKBUOxWwY4TmDWtcINLpxQs+czYxGh9zjivlUEnmU02h91RkXF5L7ijdhr8Cdq6GjnXpKL6o+ 15UtN/fdOogfKgRq1RUPf6W88eh42F2VZ9I6sXkwun7N7P3VK/X+d6zcu+u+rWAp7577BE3SOcJO hIkvny1Flkf2RyiHFsstyHAk5fjOokxIzXxeJA8SPsL+ebS6Bqkdw3TGEIR+BNg0eMrNlxV83ryU 1qyh5lmuXPmQwO2CMGIpRH2LAZCaurvS8FODgDrOqhNmUXNXY6qIf/CM596ofBXtwDOOEs3EPSeX t0KHiBIs4OMfYdyxqmGH1hGYQAy+PyFtIrTfq6vhqPOqFXOw7ZMNbjfRmoU5ZvEcTyaDZRv2pCdo RUvxTIW2tmo8q84Wz5VeQBA4FmZ9C6Y9GZB3DIcyLpwOUSzHMhFnOBewVI0eYNCY7u5utO44ujqt N5gF0QyVYNqWGSlTf3c5HKoe3Ir1IE88KptKBZRqQS2yiCZwePSaMrkWzf21wOxNylFxfy0vkgmi gTBpGHx+jRCrhseRyRAAiaoijgYjnSz7hoSqeijkIA62cHSv+ITWd6pSUBODv6iwdKteavB4Iy4r Uzm+WD7Qar3obnC5G+yc2Vo5j/aZjQqVRbFmDv2xYr5cTT77BbrRYOYo7FQ5k4uvnK/EBLtmO1Af xsxOyEq9b79S77tyfW9eRtBHpwz8kDJjTQCuXN+7TLLdlw9NGwX9Go5xVhDvy14RqnpKT0ZcyWYT Sip7YCUauryurzJsdfX/92v2LRBwAIMfaFWrSEo9SSklKWbOgOX77ArgRFb0Xd4mob7tZe0UL6KP sJHlEfPC2CgOvhnZ3D/aN5TpLGfG3XXrX18QKGo8p1CsVkLBWiqbx/4zk/l5NtSupd+asNCvqaZU 0tuaBrPFQ0tBe5xhiXU0LckWb6hZVkb0OR1+nh1/sNy5YbCZz0yODUfX3VgOztvYSHGRjb38CnUc ByYUxRn1R9Ys9+T6ky2DjRI2vuNVH4RXsJV4RLaqKwh3mjtavEqf06UByWLAyPNVr6SU4esq8Oij s5pjArckGzKjje5ouQo9RA01z1StTmho/wXuyf7n3FMNxL+Z+DPuaQFQGKCrwTtBNvhbjBBUpr4j +0oplBRRSgBuKm5CcT2Ks6hRYUOuUI1654rVKAjWAzkDMtSVuUILy1znSQNwx2etxMQBvExu2DVt HY3gzFFLryFD1CDL1YpXU9Xbn6tiUb/tOvSD6/f/932F4qHvH8LHjme9fXuXl/cMhr2lvctH9g6G 0O/2nbtnbOC2U9fj4yg+3lq+c1sxv+XOidE7txbzm+8EbqHyCPUGxga4hWPALYQLV6jiq9ZnvpwP QYxdpRUUgkFh0FWG4Yq8Qplf/rm8wpVohSvIyOfTCg9vTg72y9E6YbHZvSKbGp+YzGz7EtAKbQqt MJQYvGVJ34YOD/r9jT+8a5hvyEcqfVVbqPs9lhmKwtJzc2Nfyj5+/LnDS+/Y0SOllrRUnli1vmfH rUr+jNF6UkPrHtmL4Qoa06AwaYOpSrEoRi4NuXMj0aaKTV0X5PtaF2S1O7LaBYlzZ3usbOxNB3V8 FnJnz2gn5M78BPj8K+fOCzBrF1SmsCovzvbPz505ULOgjU2NjpQTAFHr9oe2JIeWDjdCI63NJ7CX 5c+VU1Wk0EyqGLFWc2gh1p26rgpd5f+pSbRKyOAkWrFO5DMKM7j91IF2FLdqQjXfIKUJl1WTOisI l1hHnIOUER4sczGZS4/GrfZQ2T5OaOZecfjpWixcnwBeydAoQsSQz5AMp9c7/VG7u7m9K7LYzMT6 u4p+czjqN+koRG1zBASO4/S27HjH7POXG5q7CoMJK6U3GDiL0ic3OXeJfBXPuEy8KptyY6Wx5WO3 jz03RtcVp/6kFaUUoegHekpaVLRSilXo13JQrVAptSkQMa1ABSky2BzvefQnpTnDAGGRSVZCJfww jt+vZHrORJqyv+kw/EFYIVwtHBAotRD1v6EKNep4T1XGWglKK0BNQUmhrgA1H0v/VwtQ5Kttm+9c 1rxuabPDoIMCU7q0trNxsNWbkFesmZQTqZVHV0ZHulJ2lsLRkYHhGgrlXKOcsifllWtWyQlkWXot Xm+n2xYNSjj+9Ia8YqQQi+eTwYZ039qe9q3lJpNo501WBy+4edbhdkiRZl+iPRlqaOxZDWsRnvtX 8jrdD4guYtOpFCFEMhrmGW0tMtpaZDSFzGhSmQEhNDnNmUuREb/5knOkBaJvVjXbMyB2bRp7NXNR pfZ0VyYYFtIQjiodQ16n50OprHNoh+y/zSpCFeqvqoHau8Adi9Z3O4adUZ9NT3O07ip/A2/hmNjY oWWkRWUY3qy2XrypchAVw9QWzsDRFhfM+xHg+agf4pjgYTmIIwFjAiQoARKUgNpMQjFSCV4JudDH Z1RNC2qoBDVU8PEjRTfh5KTSEK4pa1CT0SDkKpyUKSeMtLuMAzN6nuyrb++qidQVyb5FxapCxzzt 9yQr+u1Ov8BMPKa4ftam5ijO3Ehz39GlrC2INVfkahHBkTXLenbft41sqGrn7H8s37Iktn4Nebh6 RataUUcxPk3Ev5wjInPYm0GgG1RqObEgCqgnAeTQ5mnXjrb58Fc5irUa/Ny/yR1QwMdRhYASPErS qCGJL/Q2oGgDCsNpKYyiYRRSroZQNIQSVnRjGIWB5OIE+0g4hLU2DLUwDotiGBhGeAQrEYb3N0HL XbIcNnrKRtUAKmXANOwjmFIih7T6Hypk2g4DqCallZ0dtWarOhchOTskbUvHUURSZGVGZ/YkA4Gk 26KrvKqjoS3I6Y9InK6ioz4lDVLY6wwILPUNHWcwsZ99F4pkOr3FQK0ziRyFc0IS33GzHpOJ/D+c SU+ReiOg3Y5zjOMY7aXEb88Rw9g89eKpdQL5lepEHXCMZVE8jOIhFA+ieADF/SjhQ0kdSlGoqxt1 d6HuDOqBv1FiRxO8Rh/AUTZgceVD+B14q3YZjrIJHAlctvaXld8DMEv8cn4/fzuv42XRMcK3lWPl rq80oSZ4rgmsJi85RnY3HWkil+KrznEOQH4DkJy6WCrNYCRVvOdLkWoxUr2pQDM1nKkEW1e7uwLk daf0cR1d+ZAyO5OBYKPbRL1Eks9RZk8qEEzgR5WPaR3OLpy+BlFP/YokXyE5EYt9UNSTb5HoTZKT wh6XH5aFtVnnF4V8gONmD80vkdXGcka8QjhTnfVwHF4hMza80Pzoqj4i9QZYrxTWjjG8XjninnNE CwZGAH4f7EYWLEZ3FrmwPJ6Bep4LOTXb4KheciAOpLUR8lZ4TQ+BOiOoYETGEKQXsCpGY0tzqhwx Cv6yUEsh1EpvrlblBeFV5Tcdc9iqm2Tm98jMV0QlqVoGRdQSvZQIBiJ2o+7tt3RGe4PPHxMQh1yV D/VISoT8EZtBN/OaziAEvf6YSHKVj5sskonG2TmLdla+hg8UbZIs6Cx6xiKZdRRjYCsn0HIGugeN NmtlM1gPHAXeivGJEivPEV4813bQfC9KeZFLSZ5dKG4pWMgEhzzgkrs8yN0JwLlRsOw2SGXDmG45 MaYlrVD9TatKC8obptSpdkjQBxvP16q+ksLqOGws2XYT09LqCQkkcyvHU5WX9Xw0EGiwcTRC1EeM 0BDyRQWmcpoXaJPNgoo60UBtsrssNKW3mmez5JuSkcZ+QsQz2YCD2reos0Sa6D5H8HgmDqjCx5Wu pBx+Ps8NciQXE3DSctI9Yk0oyQseOJDvrThWmJmCvt1aS6vC9KIFTelK+xCCU/ItRm/Rz75p94I8 ogcqt/MS9LySOqNgYuFa5TB6Wm/mmCHJK7C+cIPF4XDz5N5wTMSPGYtDCFlcTg8/+xjL40iLRIa5 P6Ff05sJO5EiLKfpmHeCH8Kg/ubVuh5AKl4jwBZtWnuJhU1jPpEVkN4e8Xkjdr2FcyeDwRTWB1cq GEy6OXS4GvVS502iiWZMgunTYjjtNRq96XA44zYa3RmF//wTtQ6PJE+MEHHZEo0GOdtJmm7mBrvA R6ITzUMQOvwGdt0p/Lo6wtp2O2WUWjx1WdV5cSZIrWvdeNsEG0nYA6KeQZzoEx39m4qekLx1oGud nDKw2BkytuLk1vw1T+xorlzEswmE8Gzw7EIBPDvqn9bfe3WB/sBqBfVH2L9KbGpwU2txy9K4O+Bi BL/D5ZaCHrH3C1/+rHvxbBHRWPktOkS8Q3gJwwtGp4/gX59RG8lYVrV4HVIN5UOMxSncR5sltyQ4 DUh3t9EV9bijTuODwXw2436VNegVI4SkY94QzzB8CPKskco/oQeoR3HGniPCJ6K2F8nlRBw/cfS0 IZhupq1EbgZ/KI4uXv/nH1/e8ClceSgPwOqGkrC6yRCsLmN2CvfSZtEtKkO7y+SMul14aFQo1ARz bgo1ZOCYmZ1QBvuPegOrgzwHCbXBksSLcx9qY00Q3hOEbZo8etYQiLjHaesIUZopzUCw2HrlUS4Q yMvGt/jx5eNKhtULeHGw0/VkwHr/DR7PPrw6RsJ5AtqsLpyBdiqOwmYWDyX9I1iqOi54X66vJws/ 1w3nskvxD7xHI3UYHaJvwivM4RUexq+sCuxfvsB0PNiWy7heZU2Km+GQdLsnJDKMqKzwvdQRKqt8 QgdhPsU0OFrxp7TNAE4L6kballP2ClcVW/i00RlxuRocRryY/BdpE15M3mFAdMV5hSewV9AN36aN whNow2s6o6wpFsDKpc95Akabpo6QP6+N1phwttVGW0MlHs/Pw0JfESzy5zCYe3Vm0QWDoY4bnBG3 M+IwVp6oewIPX6c8A6OnE0E8GteM3giih1EUMIoCwwghz+c9gdcPVd6lDPT/wJZRf4KniRy2N05t MBrbzX5HZ7b57e6wqGPIKZ1ZCthx8qGjPzBb9TrWLJmZo2Yrh+dvM+P3W4pOkVmyl7ASllMEa7yk I6AZWav9hVVZUmx8VhQqm0V8Q9/ElpxGHycCwXg8wAgeAmFrfUlHkrfhdxFewO9yDvmIz3sjHSlJ n5UkUZSoH3FWjiYL8UgkHotw6l60uyvPoH+n7yciRINspyAooSAdphTHRdmDxruJUg7rndo4yeD8 S3TWNtpmKUWGVBzQv26Z2nIVjSx+t+iRTFRhZacvWFzZhjje53D6eJLe9tPKhjffqmz8B5NgpElG T+/6+du/OXjw17/6xW4dw+AAgYcR3YJH9C4eUZhoO0eIarYgatkmHE/DyESladSo8BnqCNOttd5O thrZFMT2PJnQ/JbTIaJ3fZ2TBcokeUSP34zoTZs3b9aRvM9p9wl6cvdh0n3wN2//fBetZ0gau9Kf oWfeehM981OON+DRMbqZynI8vpcrF0gvfYQIYk/p/onV8wogn7tUBb6ahYVryaoir16rZY4wOUSj UXSYEMFgx2K1fOtbcKx8FvZiP2xj0uCtGd4phHyf9DBWJ6CxsXIBndE+jf+J2/oKo30arW5l0JLk +XRZqVmcMYpO05zFik0s+61vqcc5k1M0fmLz4vQ/LDitDH3RFxKcPMMKXgk+6evkk9jz3ov9hEu2 BJLBRM7JWnnGYIwYsdiLTpxwIhwYMkwiITnA7HVILANtzB0dCcC64HRScTCELNVRcGAhYVmqbCGd Tr/pDR8VymZDlO91U8DpRJYPPrAgpzNger16/Q2T3+kkLR9QzzCRRFLkvlb5xMpjOWS+xonJRIS5 Zi920gmRewLRPL5VPn0CX49H2L3YotxP7SKfoA9XYxdvfJjHJqU0U+8oqCr1u+iKw07ehQEXRZeV cRpsYacrbONQ5YsLrjXHqXtqlN3/rJ5VWhZe43k8lmvmLlEv0SElenn8HDGKI36nlZy4ehSlD5fQ rhJaUkL5EoqWUGmaXCLbTD6f6ZZ2tLcdjbWjrnaUbkft+IkzBwgExgcSMXWz2ntn8dsQzSZkmp77 RDbgB6auueZmOj6NiBekDYPTyH6C3lLb443VYep1HPNP/bOSUYnQpqecwd68dB39pFtMN7GL2OEq R/5S/tqnD07euqk3xovZ5Uee3hcbl5ssrI5ErJEzxgsTbVP3rElRnv6JtS17vrIh/qyzsHEgNrq0 5AmXNpfkzX1+9K0137i5nBy99kvf3rzqe1+/f3cPZxWNZqtkET283iJYxo99d5M14LIWd953ddeW gajZGRTveHZPpnlyJ/R+rMTYnlf2THQQw+jOc0QBKBQBGvTwCRiF9mntSnv1Sr56JV+9ohDIwjyR XFaaz/ESlVFz9Xeaq+RM/RWlyNo8Tbplty2pWMekQv1o5yF1q4ZL9gSskUAAdizZlLuALWDoVH6n E+gJux8n7MoLtYvwws7z5BKCmHv9JCzy/KLXuuO1nrsLWkXzgtL6MwC5oQHeY6AZv+lAddAD1UEP aIMeAFETDJA/Gdp76cyse8PS2ZqwFGvbG19XiY4FLfP4wNfVFkB6al8aWR+GdaiuYH6nCEXlax15 zkIBvjCg2pNSoM73HHz6mh1f39eVHNu3tGeTHG7Z/viubQ9ONUFD3vD+scTb/s5V7dfu9xbX9ey8 trFh6e7B0pbe4N3Hj92FxlfftTHbuPKmid5da8cagksnNxUGj6xvy03uK7VtXl0ORUbXbCG3NA42 u7etSSzpKQbzt81+MzvW3xsO9g2Um7buvQaiYixLryg7rNLE+7J7URErVi1iZYDLiIF0ZFBdeQpq sjZgAG2weDb44gYcV+OQkQip5GdIE66QVqUIaTQgPr4HMWQ0hODvV8mcATZvyQSlfGcGB72AhuUG klB4LGUDoSoQFxSNJwyEIdPkha8ctq6CnU3VjVvzfd0478WKXl87VJbsP6mE6eoKGjrqldx1z99x yzO70s3XPn/sKD4+b/Gmeyaa1+ztdQT6d450runFUTT5pUf/dGLruu9++NQjHyrH72994sY1He4V X/7htQ/9w7Gu6JLN19+NzdezWG2/QTuJLPE7ORoNoKgfRX0o4kVRD4q6EST3TpRSsBeB0WhWerAA 7mZEALRESmOTUxqgKY1XTWmApjTKJAVbwSwBF7zIZYR7o6DpET4qeiVoelR3/YK2+QdDj1/xlIAE SZxGpZORlSl+GrHqjtPW0uyMwuXDbQba46o7JVRlmOetprTsvbpVAvtyRuWrOmJarVuJBahvMAYz O7uJNRkZhjPrkeUT6ISjGJwONepMOHB14fD5fZxD04PA1rO8RxI9Ake9/ahBZw44BRdvYl6mdDqk Y43Mpw9yOCTEaF+P0X4Sy3Qf8YhsThVQOoBSfuAA5emqG5KRA6TYoVgeR0jhmsjMmbYY/kcUNayL 58nbCaMKjhEYPyNUsIXOYihUxMKXPdPmYLKr+OI0SlYRUisfOdWYYAMyU/uaBQUjhdtbAA7QdYsS dKZmO1hlk8mTNI5WZ9stditLGaymT9ftKYq+9hV5pSmcxaE6Setd3Ruu6d78wFTWMXzP/hmyTW81 0qOwg4blAw4bDjXMyLDp4Zu2pdMTXQ0NyQa9GLBbHbzFHo242jfdsrTv6IPPXf8mJyqR8G5sEx7G +K1H9DliI4bMB5BtRC16DEoLKH6LglsL4NYyTbbLhmWr4suWuSQ0IQPXHMe/EgcKVMZX4zJl8er5 anVJeaU3pDRkqiLrxcifVmg9pYsa9NuiiaZFk3YLLJyEl8HSDc063bJCJnUjRXQ1EVY9QLfQLTgK 08goG8qrmv49FKLLsDnKWNsclbtU5Gv7o7Dpzqn2XrP1SlMiNHiIxXk7rxkLRsluazUqdfusFmpe xrLML6Ide4CH+2743jX9B9d3WfUMZTFz7av2Dw7sGGxIr7p54iheK5YxWriDA3vKCU9+sr1r63ir AVhDnBlIXWv2yxvvvSoT6tvYvWT/igy6fsODuzrs/qDFgnOtqC8UCzX0rWntWC83YPWwS24r2yBv 6EiWC8FIMkJbvQ6rU7BIeJ2zqw8P9+6ZLBpJtn0F2P7muU+oX9I2ohHbpU/lLiDMMyjRhKIJFI2j mA/FvSiiGKiYC8WcKO5AcTuK21CcR3iJozSK6lDaixRrJarWKuNw4RNHiNd68tRevHfOQq+eL5vl p+c+k/34N3hQPwhs8R3w7eBEeEi6ePgulgShU22VDjuAamuzbIDeZl1zLuHNKgusS4d53hBeaVB3 9WCta7vU2qoxvmmtmgYbn2eU47wGLrqhhQ29NdVE87bKgSIoTP3SJj5c3R8++76JN+PczcCiX9BS oCkQbgnwDwv2yt+SlavQM+hAOF75t2oJCfEMH3BJAbfTTInA/NE4k/3sxxHy97NdoHE7scY9Rluw xfqRbE50oERBaSGhFIt1RjVYHZpV6lC+Xgq2eMI2tiSGPgkbZkEvkpblrftbb2+lWq+8Ffg82YaD q/e04OrCaaXvTZqGhhLoK5VcBfieC1NT13+EYO8L3TTpWqA6U5dAdXJpxL+paczFqddV5VHBBXTn tWVBSRdCoMiCL5jBOaLWREo9NnTsxLU9164u4GSMhBTN0Di8Z2TJgclsYvLWtb3r4z5X0E/26q0G 2iZW/JFy8/6n9xfRU1/45v4uwe2ymASPKHgFvdvvCQ3uHu3bUgqaPDHSGg5x2AhGk5VHabJ965fm 5qp5CclQPyMA+e1YB57DyAeJt84RArZdBiGMxgWe1zbDLtwk+57mJz9SZPEGpTDHT1dfxfNqCUl5 Fa+9SnnaCLW/wzwoDqOV/cLVlQ2jusD2bSWgtWseua5P9T3t6yHeOY1fY6eFaZQ56Zk01jYtKi5Z WYW0VqerluvmK3VKiaOeSaeeo2iOqWRpqzPqaYgLJIPen/2qJNEGC0f+0WI3MrqLot/rtnz6qsnK UYxZMutGk1EJ+xVG9GE0tUwEo/mPBHBa8Php7DmaiQHiJVlKZVHj/2fvXODbKO59P7OzklYP27Lz wHEcZwmQOEAdE0iaJgaUEAKpoRhoXjZYViw5FpFtVZIdh8aJ4rrUIT4geimFtL0nocAp7bk8C017 eotcpzZQ00KBNuVR3AdQKA/zaPE9hOz9zX9XshwcSh/n3vv5XO8kv8zOzM7/P9+Z+e+ubMc2vpC+ 5nbqfD7fxVfLUKHLYa/G7SQvcyeZc/UZ/FNnrD0jfIY47Qx+hvyRWifLz9dZlCnma4D5OvBduWJX yPsGLl0hn1foR/zaV/ClK9asaFohTl7BVxxUTvPlLzqFn+J7W9cdS9899XKsYu1ex/qcl0J6HaQf o7nSeiNcnLuGaRWrx35jwicn/CC4OvG7p5aKO6ZXXvr5O6OnXbry9OmA5dbc5WdfdmZg78bTlSU3 NkT+26YFi6+6LXZp1xW+BYV3z1vVcO7KK1aUzlpWu6q6T/nBZ//9X/c2r3B7i4rmlswsybcVFBVU 77zjirmVK5r6Ll//tY41Cy9uufbAmuTdkcpFlwSXrNi8+pRPSOLLjLeUkHITfVI8z1c0nZW5vLP4 rLsLds09iZ90t60bg/4c/vBF/U/1//X/x0AJzVuz9cK1zavmnrh669pLtvpK+rwnLj3lpLNO9E47 acm88jPn5vELLt65aXHFhq6atTtqz1pad/XaZRuWzylddvmy1XVLZpStuJxxo9p4TrTalshPIr7P puE1zfq+dXpfmyZ/K8ADWO8afYyIxUtfoMt+VpX9AcR5tvzppdNnznYLTfTY8mfMnjFjtkdomtPp EFreNI/NqbntwpE/3c2wFi80nrNFYXOBOp15lS/Jf4Ubq9KhlvMdtNfXsIh4UJ3JFrHp9516cpn8 77E89iK26MzHPnjszI/6Ud9j/luVB+2ufO3oQa2wdMb0OYXIOfNcdjzJanytVjhnuvwIDbk8t03x TZtdJH8q2C1/Khi3gYhWNHua/J+xkMtz2mzmTw/Lpy6F1fNl4htiLctjs9mc77J8xwz3D7mLqawQ Wszkj0/wRdbnwzmfa84snHAmvnFCwQeegpnTC5V3i6bn5oUonzu3/OR5845ukF+OP2XePMnkfHal +Ko6n81hnvtPKJiFCXnM/MoLntgzX2T+JF860/yaG8ezzFdVV4H7yGsuj3A47aLwhELhyPN8sENJ 5hVo4tZZc/MQRa6zzT/ZW1qUp/A+d/GiOfMQSY7+5OijDveMk+TdjtWLg+qJiLme+4tKvXbLphmo sm8KnMs36aVLZ54gv4H6oGp32Y+86fY6VcWR71a++MEu2FNUp9ctprvylHMKZ093i6MJ+anrCaXz Znhs/Gy+xO6eedKckjlw6WjctkD+b7gHzMQXHTe9qGzOST83k6ieJH1Xrcum92WyrTlu+ontJ/Zp OSntqMtJT06etIuQXnZ+2UyuYE76qZnc6ydND3s2TaXjpTztuOlA/icmSYfMVBCaJP3xn5u8T384 FW6i9IvJU9EmSu/ING3peJp+wvRv5aYZS4+THpvx2MymmS+Y6YTbP5yKT/y70r2TpVnNJb5senz2 kmy6cSpNpf9P069lKq05Ju0u/dWcuXNWUopReqTsxOOmtTkpgnTDJOmZuafODcy96bjp7WOTvuz/ SHpJf2me5x9MD53UcfLMU1yn/Hx+z/y+BactOHPBa/9IKv/kx0yf+6up20pPmGmhh9KahT1TaSpN pak0labSVJpKU2kqTaWpNJWm0lSaSlNpKk2lqTSV/t9K9FtVOWMFixlXrvEw5hQnM5UVGW9BF5BW G69AN5EGjQZoszECjRv/Bk0Y9zCV7zOGoWnjGeiQ8SumiouNH0LXsQLoRuaB1hn3QeuNaqif8jH0 X8hU4zVo0HgcGjdehiaMP7JCXi7L0bPUNOmgbI/+kRfrjD9A66FF8PMNaDXpJtIgc7EitHkPWsc2 QevhQ5HwI18Mi7+DBjGiYlj8IzRhvM2K0f4R6EZ4UoyrBLTeeBPqR74UV70KLUL7UliUWg0OpbAo tR5elXLF+A3UC69KeQmslPIy41louZGGdlF+L5Xvkz1gXI9D++mqIZkHkxfZfNj6F2gRxjKfRjef RjefRjcftn7P5sPWI1Bpaz5svQYtQ8/zYUWW7KWSlPE8m49xnQXdaJwLleOaTyOaLyLGQ2wBOPwF GidNgNgCePV7aD/GuwDM34YOoefTiUYVvLoPugDzXgWv/hW6ibQevlVhbfwemsCIqohGFTw8DC0x XoBKGlWg8TK0HdyqeAdpF5XvofxeatlH+ZTsE6yegT5AJWnja9B+4wB0yPgOqwKx37Bz4NWr0AXG E9Bq40noJtKgcRW02XgKGjdaoAnjWnYOfHgFKns+B33eB+03DkKHjHvZOVi3hdA62R6jXgH1I4+V i6uq0ecjULlWq9Hbq6walN6FDoNhNWg/Dt0IYtWg7YFKMtVg7mEb0EMYGgTnDcR8Ayg9BfUaT0NL MJYNoPQraLlsDzIyv5fKUyCwge+j8iGpsKVANx59H1rHKqH1LA/qp3zEuBEaMwaw6oMgs4l83gSf 32WbeA1bAQ2zS6CDbC7bhFGHoevljKI3DeonjbBe6C5WBt3NdFZLK7MWtF+HVmOl1YK21Hqs3lrY kvk41mEtbKElRvQctMv4JTRtvATtxyzXgjYU8cHF6kHmLWgQ660e10pNyBK0fwXaj7VXj/Yvs3rM C2qF3HH1mBeZj4FnED00QItgJQjffgKtNgahm0jrQTuIVMqCYC5/p7zXkL8ZvsSQv5O+zJC/Fb7G kL+Pvt2Qv/W+g7SLyvdQfi+17KN8ypC/sf4ByqeN26D9xrehg8Yd0CHjm9BhI8aCmKMK6HrjOugG 42roRmMJVM5XEPM1E+qnfMT4CjQG35oxlidZM0W5ZrR/jsVRsh8qyccxupeh1aAdx+ik1mNO40hO FsforoN6jVugJcad0DJjH7TG+Dq03fgZtIO0Cz7HMTqZ30st+yifwijiGJ3MDyGGxDGWu1gc/mBe MZYboRuM70E3GmdC69gSqJ80YtwEjWGfJuDzN6Fybybgs9Rq0k2kckYS8Pb7UC/2YALeHoSWGQ9A a4xHoe3GIWgHqfQ2AW9lfi+17KN8Cp4k4K3Mp7FTEvD5pywBb8uh640gdKOxGFrH8qF+0pjxLa4g DrwL3We8DsW10H7jbegglQwZz3AFK+1ZXoCWb0JTxl+g+4z3oGnK95MOGr+CDlF+2PgDL8BVr3Iv RvcmtAtahh7egO4z/gyV15bRtWW49rfQIeMd6LDxGi+TEYOX49rDUK/xJLTE+Cm0zHgMijsjtMY4 BO0ynobupdqU8SI0zfKg/cwOHWIuqOyzHDS6oRuNTmgda4HWs1lQP+VjxiNQ7HFeA7vPQL0gUwO7 r0PL4H8NIsY0aBf41MCiLN8Hz2sQN06A1rHLoYg/UD/lI2wtryXCtUS4lgjXEuFaIlxLhGuJ8JXo YSbUDw1TPkz5CPx5Huo1HoeWGA9Dy4wfQbuM/4DupZIUeovAyl+gDxgv8QhGdD9vJ+vtZL2drLeT 9Xay3k7W28l6B7XsoJYd1LKDWnZQyw5q2UEtu1D7HrTfGIMOYo66UPtn6DD4d4Hzs3wPrZY9tFr2 0GrZQzO+h2Z8D62WPbRa9tBq2UOrZS8Iu3gfxvtLqNf4HbQEtX0Y74vQGsp3GS9A91Ie93doGvPS hxl3Q+WM98GHGijWPLSO1UHr8YTRB54yH8PKScHD16H7jFegacxjinxLwbdXoUMYRQq+vcFT8O1F vg9evQz1kpbgqn3w6lVoF1bXPvgjS/YZv+f7YPECaD382QeLMh8z+nkaPfwOKntIyycWaBlpOVqm aXRp9PY6dC+Vp8AtjfudC5pmHmg/6RDpMGY5jZEGoBuNjdA6+XwAu9iZsCvzMeMJ3g+7r0C96LMf dt+AlpGWY4/0w67MS7v9sCvzKdJ9eJbtJ7v9sKtBhyg/jJntJ8L9sIt1QHb7yW4/2e2H3af5IOw+ C/Uav4CWGE9By4xHoV3Ya4OwJUtSWHWDsGWHPgAPB9HbmVA/acz4MR9CP7+FejHeIfTzR2gZGA7B fxe0hsq7qHwvqdwLQ8RtiPwfIv+HaG0Mkf9D8L8VutHYDq2Tzz3k/xDsynwMMWdYPr9BvZQvwSiG YVdqOdbJMOy+Ce2i2r1UnsJ6GMYoZG0aDIflMyR0SOZhpRTqxzPuxcifBPVD18lvCoYGjc9D40Y7 NGFcJdZhLT0t1uFejzgu3xqgfsonjEfxxKAyD7TIeAa6gBR3Fugm0qCxBdpsvAGNG2FowoiKjfD8 MLSGzYTuM56Cpo37of3GD6FDlB9mLrERdq+C1htnQ/2UjxnXw2/16Bi0CO3rYPd+aDXpJtIgKxB1 4LYV6jUi0BKjDVpGWmPgTsmvZBo0bPwF2m48Ce0g7aL2eyi/l9r3UT5lfAH6AOXTxovQftJB4wno ECjVYU5fFnWY0+XQjfBZPk19FrrAeA4qydQTGTxfsTponC2DJjDSenj7M6jXOAAtMb4JLTPuhNYY d0G7jB9A91J5ChbrYWUVdKOxEvMnafiJhp9o+ImGn2j4iYafaPiJhp9o+ImGn2j4iYafaPiJhp9o +ImGn2j4iYafaPiJhp9o+ImGn2j4iYafaPiJhp9o+IlGBDS+L+R95Fkh7yNSy0hrjOeFvI9ITRm/ FjF5j4amSQexrmLyfVPslJEZGmbnqmer8v/5kMcnlHlM/gy7PIKkgt6m8+lM0E+R5AvVygtWKYqs vJrTxoY3zFVW3p5T7mD/KWqtvMZOFY9beSfT1c9aeZeyP9vezdarCSvvYaeqj1r5POVm9V0rn88i jj75vk/HYseYlefMoZ1q5RXmcF5t5fEO7Nxt5dWcNjbmcd5i5e055Q7W5bzdymtshnPEyjuZ1zXP yrt4Tba9m53mWmzlPWyG60orn8cvcsWsfD5b6v4RPOGq0+Js5k3OZt7kbOZNzmZezWljcjbz9pxy k7OZNzmbeZOzmTc5m3mTs5k3OZt5k7OZNznfiXelxXiyr2TLkLsYb1eNLMbasPvaWBN2n87OQy7G oqQBlISRa2UVqFnJIkg6uwxlW/A+kMBV8iyEf0No3QENouV5uC6CNptRFkaLMLUL4G8L+gpS21ac xVHWSnXm9WF4oONvAO3C6GE7zrYhl4At2aYdPSZQHsKZ9LkdVwdR3wpvZC9tVq8JtGixbMoWOsbY RjallTiNZS2NtQklcoztKA/RFTEqiZDXCWscjag5nXpuoZII9RgAI7M8Y6UF/USIWNTyshUlLWTV 7FOOM5HjgbQYpbGYvDO0Td+lpTYQ0DF+k7j0qgVtA7CfoDM54kR2PkxmphWdfG+1xtVGbDdTy3GP c0ckqXXSdeaot+K8gtZD7mwuoN5aqIftxKHdmvlc3nLGzPGHyH85fnNeYrQa5L+mRTnXOvqIZkdj +rjFahPH2dVW7wmMwpyhjuwsBWiNBFDaMmFcmdXcCE8CZL/Rsl9BK3YLzZWs+fAeWP6hUS/P7pol bL21isLWeluCHpeidvJVH7LWrzmagOX/Fqo1/QlZxKSPQVq50qutNGeZayavbfqbdvD4ajHnZh3O wuSDtH85rfbEhHlcZHnQljOCRmvfJWiUIVrLF6GkkZXTHC9EmyD1fwF5ZV6bQIqC4iKkbZQqaI9P 9LyCem9BmwTWlvR/C40gih62o1TOYBONRe6cib1mymX0MGdga7a/TeSzuWq302qLk4cJ2ldxigPm 1TqNQe7JEK2oMNkwCW2mazP0zge/ixARzWtjOTXmfg4Sk/E9uo1sNdIensyueS7bNmIVtRPDYHbN B6k+Sit2e846j9JIW62VbvYVIpU799hxy3ozQpTjqoW0OlswrlB2z37Yq9YP9fzxGY33nonSuhVn zdXTOCHefXjs4+t1ol8rcgjIkZhjMaN+ZtXHsneQIMXQVoqlgeOO1OQcmMA0ZK3+Y/eApCpXXjtd GaR4JEcTyvYjW0Yopn3UDP2z9sX4nlhE3sg9YN6JKmiuoqzzTn1xZeUy/eJwY6wt3taU0M9ri0Xb YoFEuK21Ql8ZieiXhbc0J+L6ZaF4KNYRClacF4iEN8fCejiuB/SWtmAo1qrHA61xHfXhJr0p0BKO bNe3hRPNerx9cyIS0mNt7a3BcOuWuN6GpolQC65sDeqNbbHWUCxeoa9N6E2hQKI9ForrsVAgoocT sNEYP12PtwTgQWMgiry8pKU9kghH0WVre0sohpbxUII6iOvRWBv8lm6j90ikbZveDMf1cEs00JjQ w616Qo4DnuESPRJuha22Jn1zeAt1bBpKhDoTuDi8NVShW8NcENdbAq3b9cZ2DN70O9EM+6FteiyA scTCGDYuDLTo7VFpBj1uQUk8fDWaJ9owoA45pIC+LRBrMW1JzI3NgRgcC8UqLgttaY8EYtkZWJ4x vVxOzZL1QIRB6Usqli7OQR8CX5gJoP8tYelHCI7FAsFQSyC2VW+TNTmnTZNPMGHBaNa1hhO4/vJE IGGOcRE6aCMDjZi7RCwcildc1N5YHogv1IMh/YJYG2oTiejyRYu2bdtW0ZLpvKKxrWVRYnu0bUss EG3evqgx0dTWmohbTWW+KYABbJXtNrW1A+12vT0eghMYkqzWA5jJUKwlnJAObd5O7p2/7qKVqI3R CeY52G7O6LbmcGNzzrX4N9zaGGkPShZtejAcj0ZgQDKPxsJo0IhWodZEhZ6x3daKBVEeXqiHWjbL i8a7as00ntQjai6XNPDHgafRXHdZ68TV6msFOVAehhUsfYk+JjdIsG1ba6QtkGsUPgdMTwE+OwNt 7YloewLYO8KNIdmmORSJHjOgjzMXNBOLgqGmADZRRSAe7cy+DzKjmF3DJjs4WuCNgk1jDsPAm6Ri vUUxXo6/V5hfj/2IQ1XP93g42ig9H7d9Xp5sL0Y+bvuCAtneVvVx23u9sr395o/bvrBQtne8+3Hb T5uG9viXybdKldrLt+pLSQtZHitiJawYz8ul7Cw2H08KC9hn8LZQhxjdzKoQn89h3Ww1ux5PEl9n 1Xgv28AexB17gNWyJ1g9+w0i+Z/QcozFuY0leBFX+AJewBdzLz+Xl/BP8zK+gZfzzbyGt/FavoNf yffwML+JR/jtKLmPt/OHeAd/lHfxp1Ezwvfy13kf/0+eUmx8n+LlDyilPK0s4P3KYj6onMeHlM/w YaVOfFppEhcrcbFOSYr1Sq/YoHxFbFT2izrlDlGv3CX8yoMiovxIxJSfiYTylNipPCN2Ka+IpDIm dguHuE7MFF8VunhNlIvXxRLxhlgl3hSXiFFxhXhLhMXbokO8I74g3hUp8WfxDfVT4tvq2eJ76krR r64Wj6jniyexLp6fyFb89u9kexvY3gu2PwLbn4Ltr8H2JbB9hzWj2zjPk1/hAdtFYLscbC/E2eVg GwDbCNheDbZfAtuvgO2tKLkXbB8C28fAVn7K/nuwfQNs3+d9iga208C2DGxPA9ulYLsSbC8D2yvB 9iqwbQfbL4DtDWB7C9jeAbb3gu33wPYhsB0C25+D7Qtg+yLY/gls3xdJ4Qbb2WB7GtguAduzwfbT YLsBbINg+zmw3Qm2e8H2ZrC9HWzvA9uHwPYpsB0B21fA9h2w/GAiW8dvctieALangO2ZYLsSbC8B 2yvBdivYbgfbL4HtV8D2m2D7A7B9GGx/Cbby66ofsHruZkE+C2zxnsiXgO1FYNsItm1guxNsrwXb W8D2drD9LtgOgO0vwHYEbN/ibQrj7UoB71Dm8S6lgu9RlvO9ylqw3Qi2QbCNgu1OsL0WbG8C2zvB 9gGwPQS2j4PtC2D7Bti+BzI2sVEUijpRLOrFicIvThURcaaIifNFQlSD1qVil2gE23awvQZsv4p0 AGy/DbYHwXYQbJ8C29+B7SjYHhXvqB7xrloi/qyWq59Sl6pnq5eoK9U6dbUaVM9XWxECOiey9azP YTsLbMvB9pNguwZs18nvdABb+dzWDbY3gO1+sL0bbB8G21+B7SjYGqyWl4DtQrBdBrYXgO16sG0D 216wvRFsbwPbe+TX8OTX1sD2ObD9E9i+z8OKk0eUErA9FWyXg+3FYLsJbENgmwDbL4Dt9WD7NbC9 E2wfANt+sH0KbEfA9k2wfV9cjDW4DmtwvTgZbBeD7Tlgez7YfgZsN4BtA9jGwLYTbHeC7Q1gexvY fg9sHwXbp8H2N2D7OtgeEW+qbjEKlm+pC8Xb6jKwvQBs14NtCGwTYPsvYHsL2N4KtneB7Q8msi30 5rCdDbange0K+T0wYFsHtlvB9hqwPQC298r/+wlsnwDb11g1d7ANfB7bxBeD7SVg6wfbNrDdBbb7 5FduwfZxsH0ebN8A2/d5meLh5cosXgOOteB4pVINtrVgGwHbLrC9Dmy/Cbb3gO3/BNvHwPZ5sH0V bN/jDwg7T4tpvF/ofFAs4UNiFR8Wl2EX+8E2Cra7wfZakLwFbO8A2/8Btg+i9iGwfRhknwXb34Ls y2CLmKAWiN3qSeI69ZPiq+oq8ZpaLV5X68Qb6law/TzY7gXbr4Htd8D2P8D2p2D7LNj+ST3bZldX 2orU1bbZ6vnyP+6wnTmR7czzctjOAdsKsK0G22aw3Q6214Ltv4HtIbB9GmxfAtv32Pl8OtieAbaf AVs/2CbB9htgexfYPgS2z4Ht/+KKMpMXKCdzL2JkibIabNeDbRBsO8AW8Va5BWy/A7ZpsP0F2P4B bN/nXcLJ94gT+F5RzvvEp3hKyK/krQPbENjGwfZasD0AtneD7TDYPgO2r4HtUbFe1cQGdZbYqC4Q dWqFqMea84NbRL1IxNTNIqE2i51qm9il9oDtLWB7F9gOgO3PwfbXYPsq2L4v3rR5xKhtjnjLtly8 basW79iuEO/aWsSfbTvVT9muB9t/B9sfgO0A2D4Bti/I5ynNgT9eb3n56h3d3ZqNa46RVGq0t7d3 VJ7Yo71JHL1Rzc41bbS3BwdqVNSMJpP4k5xwkqRmy1Ynk1/vWb2MTnDBEXmVxrmmJq2Duu5N7U/v T6V6ZQc2q2JU07jmGhi4Hcctt1AHhw7ddtuNN/b10UlnDx2d1AF5iYucjpwaO42BqlK91Le9IZX0 6d5Ug2Zjmn1MN4+Mc2Z3EkJ39+rV5eVer+ZmmrtH79E/7fu071IkPakn7TZud4xqnb29ZNsBV3ul DbvK7baodD1K5ZpsgkbUPto7lkx2airT1ErfqE8eaGS3d6ZSDcmoSRg93fOwvMQExEwOLmFoQmeW r2kaRjIpge1PTSBp17jd9eAje3CQSbMvyzoO6ZXdYfpK3O0O00FNswtuV0fMXjAKezSZrvSOOFTm UE1nK6kb2frmZruN2W29vTU1um53MruzN9mbXIc7xTwksw41Nb3aeDOfTxqwjSCTHMnxmSVpNCNe b4PPx3wCt1aBJprC7MInH2JxYufcLpLyJMlxIF4rTJOthFwrNfv3CzC11dTsd9uY06ZpXq8uDSaT XCBejHA7U+1HXApsykJ5+Hx0KjPyAGF5ms5gTJunPutI2+RS0b8V/ZYuBCzu37+fFg8hJag4adhP kzNm1cAL3Zc9iWqa1ayysqYmNYZlRauPlrhVs8xHi8g8GaNByAVi2olma6I0Xd4RTWOac/ONNzbP XLhwDRy022Fc14WN2exjbIxKtMp0pUa5ZENxQ/IjNjeWv0Nu1GTS2qj/1M3tmHxzO7nm7k/2J29F uhFJrqKJmxxb2blsdTcOmMjuZLnJtfGaKvFP2eSej9jkTht3OpK5u9xu7nKq0LLbXFY0pEZlhcqc 2OaT7fNMZ8fZ6Or4Rneq3ImNbu10J+fOLNZ/aKvLKHVP+pitToHJN/let3/EXreP73X7JHs912uW pBE1pP7W3e60drvT2u3Ov7bb3QqsZnY7djmdZ7Y7iuk8u9+TafPcl7vjndkd7zR3PNbY+I7HyfiO p5rMjjdPrB2Pk/Edj5PxHS83XHbHy5rsjjftRLM12R3vxI4PsC+zG/F842bTkycnz2MOG3PYddr6 uiqnYIxNvvmdTuZ0amw6kpy5lWwXrTmnnTs16cUYNsUY7p1OrWoVMVlVJc+cYz1yk3WjTi7bsaS5 +8fPxpLmPdfplNdd191tXScvOipl4rIlez1mPOjtkb3YM1VjThd3etI4DvgO+L5MqQ8Je93p6j9w 4IY9e774xS/QWdWq3fKAKdkduU7bxynr2Cq2O5tW4amPJ8eb9SKuke/yUYYmyelgTsdRr3VkfaeY Q9BkzysBTGKT+DTmdHNnngwX11oB44ykDBgOG3fIue/ErnHZuUvDhQcPweqhg7LKfHrqjVKVqqqJ PlT1JRx27pDPK0eSyR0ulbls2ajhQ0uHY4dcCEk06JzQJ4ZBYK3IkfQIwzkeOhA8XDbukmHGYu3i 3DU+DUmHkzs897NhCrpmIkesvjNO9ZhmrfJDByVkeWr5jlE4VO6wgklS5mVgbPB6R2QAtGVGUkn9 UXcYsMQkIwVChcPFHO7VvtW+U5MyFeI53qxGZU1NryunKfYG9T/qlbt91MUVV+ZWAgY0WrkJK3UJ QVWYosqd7lTkA4yPQosv6eDcAQgytiQVzhXkVQVcZJ2KHuwXplIpbCNkLrwwlWdnbruqTggxXLWN 4LXM5jiaJ7jLpufEGJ1KZMY8UOWRJSPj1EfMguwk6SM26TcFGlWFfZhPWcvTCjV0ZoUafcyqI5d8 42fmQsYidxSXl194Ye8RTctsUIQbzeoF8cYMONTyCA0MI8vai2brzJCDmONyMZc7gHd+GXWCzJl0 +Yp883wnJh3ms4RXbhzVweyOo4wdtcnpsuIOchR3XE7mQtwZjzy7sJVoszq4y0l7UkaYIy4Np+es NDmtPEeeuo500zbfjVq59I9kws0Rmu1s9ElSY7r2+t27rWvldQZdfczKp656Mk8kPfLUka084nJz V166Id2AkL//Bv0GbPFrdbnVqVMZhcwwhFDjcp9jDSVzrESwoe7lsMyQ5HZN2u5cxtJZAIhKPT3d 1gqWu0fOmMvBXFo2LHmzYzLjHlH9cGDSmPQ/v0fPPMvkBCdzR6s7sAPddu6WgSQ3Ojms6ER16uTh ya0ytwxP2fjkQN1OGSOSeKLcMbHbvxqg3DbuJvJWhHJz7s6Zp/+iECWH2kmhf/S/OkS5ueLOhCiJ gQYst+vfE6TcmSDldphBSmY+KkhpzKYZ+YK7c4KUDE5UNB6lZCUV5YQpBCqzSM85RvBM6NYQqsxY 5aZYRavdetmW82BTXJqejVZWLXmn+45kTzsxKdbtrDgbsOh0BwaZU1vlsxaTeZoNWb6s3c6ebG2n Nd/a6EdGLW08ajk0GbUc8rVARahqKFYpLzM4dbuY2+VhRZRORPIldyXhkC/pczu429q6FLzcGs7L AiZmX6BMnrvGrjHDV/c1Y7QzZPiy4tf4OUnS7eRu91zWkPQxLBR2vdlPsiE5l1HV+MQYOZN07IYh r7qzD1fd0sp4aIPVPO4uSBeni/eX7y9PXZi6UN5gvqh9UevWyEo6uR8phdSb7EHqRtpt+lbKGifE sJU4L2UWBno8pC3uOk7TOQh32cZmuCPvMGcYZ6UmJ9ztYO6cgOc9ZuDj3Z3DaGbkPOBP8kSaGzlH HiQaYzdGdL7XTOVysPu9Pq/P+sgIERDLxOPgHgqgBw/JR71DBye8AlOtgmP5Glm7Zrn1siujIGpt zGNbNh4G5XLQxuNg945jOu/uNm9BWSh5wnDlhkI97bFzD4XOzOR5OPfkzm1Sc3Mt//vpQb0nJ9EL csbIhLdl93gNhUQ6z4wGA6O3ZCsmJq3XDHnnwY1HPgf5fGPm0JZRr6YBYJD7Z9KX5kxoNF/3ZTBE bHTnNse2zbzoYAMnxzxc8WSf/SUbYhDtxe4/Nj7Kj2NsPusFEa+LXJGfIrBjIqQnEyE9mQjpoQiZ 72Aeh6JkYqQVIm2ZEFkguEeGSJ/lCXI6lVEuEyN9SSobmbAWR8yy3ChJYdIzHiY9Dhkmae2bU5OZ HbezsiZlLfWjdN7Zg3lRZaQcP0eoVBTsDRlfPNOnn7x6dY8BQFRvxkqF6uW5GSzH+z9qDRljztpf bcq4P3IxqGNuN3N7or7e5B52LVJ72qW79CJ9nr4y/TeFTI+bedz5LJ/NpnRG8oxkQ3oXHqfkE5VH 4x7XkcHBwUNHBgcGBgaPeJwomMuiyQaWzkkNKJnLEEs8nqNsINmfTOcc/cmB5FFGG+yoPD9CpUfH C46a7ejyucmoz+x7yLq8IR1Nz01S5XifRq6BtEfBupxQIP0eGBwePjx6+PDw4OCANKblNDjqyece 70jpSOlo1eOnH44cjjx80fDwob6hvgHPgIeMjaRH04+nDyMNIw0i/Tg9kO5Pe9zckzeXfc5ClEkN 6c+lgcAERqzIUL7n+K2TbIRVEtEjbJANUBpkMm+e9SeJUVVTOj3SWZpvtw93ejTmcRrF48cxXMaP QPJcRnNrmpNJzq05y3K+PQXcU9hv77cPXNPY19jXNNw0vPTwWRurOosriyvpnXrHoN2+c3DwZx15 Gs9zyU6fe2lAHi89Z37q0ESWmqqoXuBYsYXqt6yQr/xwfHAQc7u5Ks/O8+xVDQ0NYw3W4ZH1u7Cw Bnekd+KKnceaGBjIU3iemk7jNpQ5vKqRZ6usZKxy/BjJc/A8p6wdxGSPHh4eHrQuzDmcHu4seG7k 5crBCYk+l8jaMz+laKJ8U5Unp+6l58wl5XRlx4ex0jvY4ZGMCflxRechOVGevk752GgfH+4y6tuy AzjyIwr5KWojk2kpUimSMx9/5PJrLN5yc/Dms+6pGi3G6xjexJzaQFNTVXFVU9OAZ/Jri5EqGTlx xFNcXIkZP5KnKHk5uwIciVVnn91u9ywDO3C0Ca7Y4GFavvc6kaPvQqEC3EydNsmfySmQd1acoX2e 2d6GvrR5TcPDwzYHy9OampqGewsdLN+Bzj1woVjOjmyZ5iq32Ue5/CDSSHpVLAWz3NreDQ2VVEg5 65D1VDg6cVGPmoWVE45Rh8bynMW1RrFRW2zDUtOG5UFb0ZrPzJR6XMs6D2e2jkEFOwYxl/AZzMYL 7FV2lA7uoM2Zz8rYTHCez5rYGmxNI2lnMlHrnXJ+d1itZUEZsR8ct2gIydskkvWpiRyzWlC+8Vzp xZgH8SI/qvdSYN/DYkwdcXqd3kLviV7fiFO+fnqtyI7Qzh1OGdqpWPF4Edu9HoXOKCdLrO84crFb lY1MNG6PRdj0LbHQVrY8Eki0sotQwy+/bJWO9SN/F4f8uqyd5eHN1DzjDFPKZlC5WaLgjbUAPGYy sbam5kJ28mWXXKyzys9eVq3jMc9sI7/ny8tOoDMBC4XZ3vE2iqe+WdYZHsrYNFbCZjdG41F2G+m3 Se8hfZD0h6Q/3hqKtbKHSX9G+hTpM6QjpC+Rvia/Z5G9LZXbSUtIK0hXka4nvapla8tWvpP0GtLr SG8i/e+kd5Delf3Orb+m/GOqBpICDOwgjB3O3P8XyxTMQ97f/K/cF/JnHuR3xXfjve1Wdt//5u1M wJuq8r9/c5MmaZNWKGWpoBg22VFEcWBYVFQ2S8VlEGc0Ii5BRXYKWCgWcRdXRMdxQQcRFR2jzrhl ECtLESzYtLVBSltCQrwtbem9jRU87+fchlrQef7zf5/nfZ/zfLhJ7tLz+35/53dOKh6Urco+pUpp sKhKshmpMxGtpsj/38jKfRlUK4v879aWES3Hh1a3HP8Wb3MP+Va7/pT3FvfxU9+n9Tn1ffv0U993 ePHU971/OfV939PO9z/z1PfDqKdq2/eNbc7bFcuVfzz1/eRHOKaQ032VbPn/aHHP/Uh1npqtrFDf UEuVV61/s/5NKbYtsL2mBJO+sz9ksaZck3KL5ZOUB/lauMPdzn25epn7RvfL6pLUmamz1C9SV6Q+ phakqWlOdV9aU1qT+r1iyTOkNvaS1I9/txXRylMPtWmxRCv6ndaY1qO19aWNoI2jzTLbutNbalHa +rQP261NtFfbtE2yyS8Tv9NS2me3tkfaP9vajJaW3u132mDasIwX27Q3Wpp55rSW8UHGjta2p+NB 2mHZOtl+r6UP7pTeqW/nR9q0Z8229XdbUefmk61LRpczW9u4RJv4uy3bbNcnjqe2vMSf8rptZitu bS13H+hSl9k/c2bmy5kbZTv96Zmbf6+1PD3zX5lVidb4a5M/JbPZ/Fl5krMm9xzR2ib3nNraZiba LFpez1m9htLG9h7ce1zPWfw5uPfWPjvOLTFbY9/ptDn9+tAG9qvqF4eqfr/03zHgZdn6VQ34fEBs QGygbWDawIyBn9KKB4+mZQ+ePuSlRAucn3dBnwuiw56+aBht9PAuw6cPz7n4g0T7/OJtFxeP6E+7 eMTqkftH2c325KitZjs++qLR7yTax6OO8/6d0XXmu7ox6hh19DtjBo59Yuznlwy+fBrtwJV3jnqy 5WqOdS1XTRgtr5sweWKPiedNHD1x46Q+ZsueNMtsOZNWT3qJP3MmFdIOTl46OW/ygavm0NZmebkq O2tP1p5Jhfy5X76iVWVpWc1T8sy2Yco3ZjswRYMDU4xs2xSD81r29Oz92VVXL6A9PfUcrtswxWg5 M3XpFGPqoam112Vfv23atL+k/6XbX/rcYbtj+h1ldzSfPN45kPbB7Haze8zJmXP/nC1zquZoc4y5 trlD546be/vcOXOXzn1o7tq578z9eG7B3H3z5sx7et7GeQ3zlfnp88fPnzH/8/klC4YtmLHgpYXX L3xoYWBh4yL7ooGLrlj0zqLDi8ctbs7plnNFjjdnXs5LOZtzypb0WPLnJR8vKVvSvNS9tNPSi5de unTm0g1Ly5b1XzZu2U3L1i3btGz/MuO+sfctve/zXHvu2Nx5ue/nbss9vvzM5Xcu37BcWzFiRc6K zXnZ/6FWfXx6PTq12uQt+rXJOmL+pivRWirIfxh7E08fcaeOk5ZM/92qc7LytGmn1o68bb82WR3y in9tLXVB1tB2m7ps6/wsdbh8dB1V06zB5pF62z6b+roubX27talFrTWTa9sbPWfKe1M/Tlv3a+1s UYnqPM6svy1X9Uhbf1I9+amsxea15fK8eX1CQZ77ceohKvl67ig3n1ZE79ZyLDfbr7ND7LRZYVyb eeDXmWC97Pdvqv+m31T/lETNf8Ss92aVN5/D3WnjeL3uZCXEj40Jv6hNLfWnpb4lfKQmUgGlazNb q+NJR6lxXSbmVck7fvW459S8qrwqniavauRcdmZVz6m/zQnqYHGbivo7dbZtXf1tTU1U7m1mNrVU 0ckn66es63zCT83TMjfyydQu2RcNy9rTydYyj5lH5qzOzR0PklXpJ2efk7NKerdOtl9noJaslHOb ebVNXsG9WzulyzPyE3mV/Dy9W2rRyUztcmZ6N2bAdHm/fN3y6a/zaNuZVPbFnDUT82abmTOdJ5w+ Tz57yuxYlJgZM072nvPNLT9d/vxJ2R0PdhlHf05RX6omNcapNiP2pMYtI1Gq2ZIpPWei90TpplSi S3bGi6bfG6U3bUb1iMzNxHpyhi1ueWqe1iUvT2tp8ifIY8+p0hX5qiXT5DFP6z2419AWWma4XkPN WalNkzNcy+xmzo//l82cU9u0315hzrRtWmLGbW2/vUPOtP+7Zs7F/3VrnbH/QztdKdla5/H/0MyZ /b9u5mrjv2ynq2OuUdq03+pnrl3aNJn3LU7/79pvn/w/9+6/ay06y7VL2vpR9ok9Rh1PLZerHrM9 aX5ilysd892TE3vINVDiHI0V1MVy1dTyqaz98pVs5upomrmykmuoutF15vqI1RGvto560lyd5LWu YmTbMCUva/+UPLmCMd9tSKxzWl5vYBVUJT+RKxp5X1aimSueBebaiGvNsxvkn5mbuXqDXE1RLfpk 7TfXXTmJlm1+0keuusx32Vn7ZV1KnKOxcjuPtZpcocn7VpuvaOY6bY65nuNac6XWul6blD1GNRU5 LrW4ekGLEqPsZjz0uKWnkwrNZ8uftNp8lvncU0fibx1tmwfnlrS8U+xyt1C5S6jcI1TuECp3A7UG lOGK3IetyNwHU77SzD3wLOZenqrcodPcn9OlvC2OKwXiuMWrdLDcoky1zFAyLbcqHstMpb3lLnN/ 0GFyx0tzj0uLuaOljWvdXNuea91cm2I+L8xVtUqyRe6P5VV6cv46zp/F+Z48qzfP8sg9J81dJl1y p0i5N6T1PvqRK/5Jf0dYq8Xz1kPKedawMtQaUQZYj4i91hjfduXTi8x9IG1yn0a5S6PckdHcjzFH OUOZqLSDEUo/ZSTI/Rlvg9tB7tIo92hcCItgMeTAEsWtLBX7lGVwH+TCcsjn/lXwAKyGB+EheBge gUfhMfhEuVT5FOK8/gWE0s+igAWylZGWq2EqXAPXgk+ZIneGlPtCyl0h5Z6QckdIuR+k3ClO7gVp zVfOtr0i9tlehddgn9LP9h0UQxBKoBTK4HsohxDshx+UfkntxN6kg2Jf0o+KO0njdQ3UiX32JGWi vR/HC5R+9os43i322u+B2XAvLBQR+yJAGzva2NHGvhTQxv6eMtL+PvwTmpSRjv5Kd8cAuFnp5/DC DJgL82AJ5MFKQCPHk/AUvAKvKZc63uZYA7VQB/XQAE2Ahs5bYSbcBguV7smKMjI5Q+lu5u5hc2dL +eqIuUNlR7LWT9b6ybY+ZNslZNv9ZNs1ZNsMsm0C2TZW7iYp94yUO0bK/SLlbpFyZ0i5L6Q1IDZY q8mzsGK1HiYHjyg3mnl2yNwjsn3rqLhJGdLm+eN5/iKefznPHy73cJQ7OMr9G+XujXK/RrlbI8/7 nOddr6TxlKM85ShPacdTzuUps3nKEJ4yhKcM4Clyj9gDcn9Fubui3GdO7qZoRrqTV+8pXXjGv3nG v3lGX8vN4lOeM4Tn3MxzhvGca3jOGItPfMuzhljWiX9x52c8z8bzFtGz23lmB3qWz9MetVaJRnpX aI0yWo8og6yxxIhtz1P781QfTx3OUy/nqb14Yl+e9p3cw8zch/if5K8rUWFOUElkZXlByReasgoe gNXwIDwED8MjIPfPfQwKRVzZBd/AbtgD30IR7IV98B0UQxDK4AchlANQAQehEqqgWuxSDkEYGkRI OcY4bwQdDGiCONXtJ843w89wHE7AL/RFCM2igMWsitXW6WTYn8VR600cveKobZ/QbN9BMQShBEqh DL6HcgjBfvgBoiJuOwIx+BE0qIFaOAp1UA8NcAwagb7YfgEhdiWli12OsSLuuBwmwiTIEhHHtRyv g+mcvxFugpuF5vDCDLiLc3M5zoMFvF4MObCE9/dxzOO4Elbz+kHAB8cajk9yfAqe4fWz8Byshed5 /it8vp7Xb/D6bV6/x+vPAI8ceOTAIwceOUJCOPYDHjnwyIFHjoPcUwlVgEeOIyLkiMGPxKJBjShy 1MJRztXx7HpogEbe453D4NjEezxy3goz4Tb8UpUnlAxz5rIqT5C718md6/A3iXfv8m4i7yaQ5QXW b5UBioVPDWUcmRkiM0NkZojMDJGZITIzRGaGyMwQmRkiM0NcHSHT4mRanEyLk2lxMi1OpsXJIo2M McgYg4wxyBiDnyf3SQxZ/6IkWW+BGWTQraKarAmRNSGyJkTWhMiaEFkTImtCZE2IrAmRNSGyJkTW hHDSwEkDJw1cDOFiCOcMXAvhWgi3DJwycCqEKyHcCKF6HNXjqB5H9Tiqx1FVQ1UNRQ0UNVDUQMUQ KhqoGELFECqGzBFbrjjQ8hJGspO59wvm3o+sRcy1e5mFmG1MfWNEuJcIK0197+Od3Mu7G/rezxNK lWnMkx7mSQ/zpId50sM86WGe9DBPepgnPcyTHuZJDz/pIubKXsyVvRizxYzZYsZsMWO2kjGrM2Z1 xqzOmNUZszrzaTpjNsyYDTNmw4zZMGMWv5VJzJvDGKeVjNMKxmkl47TCOkPpY71V7r+trGIe7c48 2p15tCtzp4e508Pc6WHu9DB3epg7PcydHuZOD3Onh7nTw9zpYe70MBbDjMUwYzHMWCxm7OmMuWLG XDFjLswc52GO8zC/eZjfPMxrHsZKmLnNw9zWi7ESZn7zkP/F5H8x+V9M/heT/5XkfyX5r5P/OvNf OvNfOvkfJueLyXmdnA8zB3qY/zzMfx7mP4/Md9GA1g2sz54QD+DAeOp5JfV8IU6Mx4m/c/Yxsv1y 6z5WUsXiF2tQmWG6F+Lqcq4qY8Z8Qizn3Qzu3ce93/HpWO59gnu3c+9E7i3mvhsUe2Ic/Ykrg1xZ zJUTzfWVzJk3zSfdxvkxnN/D+RLOj+RJD3P2fZ50KU8q5Ennmdd/b64TD5h/GkqK5Qylu2U63A33 wL0wB+bCPFgAjzDTt5c77srddeXeunIfXXNt9KrS2fqZcqH1S/yvUnoya1/DKjGdmftMVok9rVEq wxF6EOOzH5ULmc/niS+5oxNryh5yTuf+u5UJzGDT5X6RygTrTebqa4KSRs+60rOu9KwrPetKz7rS s670rCs960rPutKzrtyZwZ2zuTODO2ebd6ZyZyp3pnJnKnemcmcqd6ZyZyp3pnJnKnfKneLP5065 V/z55p1u7nRzp5s73dzp5k43d7q5082dbu50J+4clrhzGJHcqPTnVX9TY7+5RmiSe+TKfQDhapgK 18C1SgprtxTWbims3VJYu6Uky/9Oa5M73ModVxMrjQLTo0ql2NJXVFn6QX8YAANhEAyGIXAenA9D 4QIYBhfCRTAcLoY/wAgYCX+EUTAaxsBYuAQuhctgHFwOV8CVMB4mwESYBJPhKsiCKfAi/BVegpfh FXgVXoP18Dq8AX+HDfAmbIS3YBO8De/Au7AZ3oP34R/wAfjhQ/iI1doWjl+KcstW+AoK4GvYxufb RdCyA3ZCIewCuX/ubtgD37KCmM63lZtEke1rVhLbYDvsgJ1QCLvgG9gtgrY98K0IJrUXVUkZ0BE6 QWfoApmiyr4GXgA0sL8sDts3iKP2N2EjvAWb4EM+/4ojq03717wuEkH7d1xfxmtDVDnOgrOhO5wD HnHU0QN6Qi/oDX1E0HEu9BXljn5ALjjIBQe+O4by/gLOjRSHHX/kOFUcdaqiymkFGySBHRzghGRI ARe4IRXS4AxoB8TrTIcOQNxO4nYSt5O4ncTtJG7nmdAVugH9d9J/J/130n+nB3pAT+gFvaEPfRoq DjsvgD+IoHMEjOSzsXAFXAk3c90Mjrdz7g6uuxN8MAsWci4XlsMKyIM1fP4617/J9RtFufMt3m+C Bj7TRVWyBYg1uYMIJhNHckdxOPkccmiZuUcz6lhQx4I6FtSxoI4FdSzcYUEdC+pYUMbcybk9pEMH yICO0Ak6QxfIBLnXs9zpuTucAx7oAT2hF/SGPnCu3Kecb9n9oD8MgIEwCAbDEDgPzoehcAEMgwvh IhgOF8MfYASMhD/CKBgNY2AsXAKXwmUwDi6HK+BKGA8TYCJMgslwFWTBFJC7VF8NU+EauBauo9/X w59gGtwAcj/p5bAC8mAl3A/5sAoegNXwIDwEcsdrud/1U/A0PAPPwnOwFp4HuaPzX+EleBlegVfh NVgPr8Mb8HfYAMyAlo3wFmyCt+EdeBc2A7XWQq21/AM+AD98KHfblvtcw1b4Cgrga7mPNOyAnVAI u+D0KnKduEXuxs08cIbcF1vuKi33xJY7cduoeDYqno2KZ6Pi2ah4NiqejYpno+LZqHg2Kp6Nimej 4tk28x3lPXgf/gEfgB8+hI/gX6LG9gl8Cp/B5/AFBODfsAW+hK3wFRTAbsVt2wPfKu6k9kpKUobi SuoInaAzdIFMxWV/TNTYHxeafQ2v1/J6nYjYX2BOwgOzmr3KOWKx/51z9NlOn+302U6Vtr8nDtnf hw845wdZ5T7m+n/y2Sec/xQ+4/3nQD/t9NOsftt5X8i5XRy/4bPdsAe+hSLFbf+On813Ozvf7ewl fFYqmsxKWU7f+D5nj3Av31nsGq9ZXdtZXduPAt9Z7HxnsfOdxX4MGkEHg9iaxCFHmqhxnAHtoD10 EU2OTDgTukI3OEtJcZwN3eEc6KO4HedCX+gH5/PZUI4XALOsg9m1peoqbqequJxWsEES2EH+NXkn JEMKuMANqZAGZ0A7aA/p0AEylBRnR+gEnaELZMKZ0BW6Af100k8n/XTST6cHekBP6AW94VxR4xzA d7SBMAgG856VgvN8Xp+sxMN4fREMh4vhD8QxAibz+irge65zCvdliwLn1TAVbhBNzpvp5+1cd3qV 5vuuk++7zsWQSx+WwwrI4/qH+dmMf7Nqr+W4jue+AC/CX+FNnrcRTlbxt/kMD5069/4smpIVcSjZ Iv//NKElo2dyCsf2fN5BcZuVnRkquTOfdYFMoB4nd5O/l5QjPbGuypV71ptrtK2tn8+W+8Obv0eR 661aJUkdL/5svUp8xeo0Rf5ui3M1ykD1PBFTh8FwGAPjxV51gtilToKrWJVfJw6wutjP6mJ/yjSx K2U6PChiKQ/Bw/AIPAqPwePAd7mUNfAkPAVPwzPwLDwHa+F5WAcvwIvwV3gJ/gYvwyvwKrwG6+F1 eEPE3ANETLHSU0OdxnfieXyHHkn/dfqvqyNEmP7r6mUcHxaV6iN8d7lRGUT9GsSVu1KuEeGUa+F6 +DPcKipTZsHdMBvmwAJ4UOjEphObTmw6senEphObTmw6senEphObTmw6senEphObTmw6senEphOb Tmw6senEphObTmw6senEphObTmw6senEprsmikrXJJgMV0EWTIFsuFpUEruOh8NFKQ59o5o+ih3m bw67E/tG4t6o3ig2qzPhHnhYbEED+a8olBP7RmLfSOwbiX0jsW8h9i3EvoXYtxD7FmLfkpIjNqcs gWWwEh4Qm+nXFvq1hX5toV9b6NcW+rWFfm2hX1uUS3DAhwM++laNAz7610QGNZJBjfSzgp6U0ZMy 63W/NFqn/aIzu6TizBD5r43gzpDEd/wCsquR7Gqkd2X0rozeldG7MnpXRu/KcMaHMz6c8eGMD2d8 OOPDGR/O+HDGhzM+nPHhjA9nfDjjwxkfzvhwxoczPpzx4YwPZ3w448MZH874cMaHMz6c8eGMD2d8 OONDgTIUKEOBMhQoQ4EyFChDgTIUKMMZn3IZKnhRwYsXO1HBix871fHKWUSfRfRZid+3Ppr4Pt0f FTrJfy1C/htC8t+LSPyW+Aa82olXO/FqJ17tRI0s1MhCjSzUyEKNLNTIQg0vanhRw4saXtTwooYX Nbyo4UUNL2p4UcOLGl7U8KKGFzW8qOFFDS9qeFHDixpe1PCihhc1vKjhRQ0vanhRw4saXtTwooYX NbJQIws1slAjCzWyUCMLNbJQIws1vIqDXGgkYjcRP0XEi4g4nQiXE+FiJRONCtCnAG1K0KZE/psM 8l8i4OwzxF9A/AXEX0D8BcRfQvwlxF9C/CXEX0L8JfSjhH6U0I8S+lFCP0roRwn9KKEfJYwVn3jz tHrXqAxSr6bGTQMfdW4WNe4uuBt4Nj0+2FrrcqkZK8Qu1zIRc90HubAcVkAerIT7IR9WwQOwGqiN Lmqji9rooja6qI0uaqOL2uiiNrqojS5qo4u66KIuuqiLLuqii7rooi66qIsu6mJaMqSAi5onK3vM 7LvOGA8zxsOM8TC6ye/pfTi7j7EbZuyGGbthxm6YsRum7zp91+m7Tt91+q7Td52+6/Rdp+86fdfp u07fdfqu03edvuv0XafvOn3X6btO33X6rtN3nb7r9F2n7zp91+m7Tt91+q7Td52+6/Rdp++yZk0T 36P2Nyj8ZWvNkhFVKEOJyM/5Ks434cZx3DiOG8e5toJrnVzrYqSkEOlgRkoK0Q5O/A5oGw4dx6Hj ROknSj9R+onST5R+ovQTpZ8o/UTpJ0o/UfqJ0k+UfqL0E6WfKP1E6SdKP1H6idJPlH6i9BOlnyj9 ROknSj9R+onST5R+ovQTpZ8o/UTpVy4kkny82YE3O1Sf0g1/dhDBrYyAnxgBBpGsIpLOid/MdJa/ mSGS5+Vvs/BuB97twLsdeLcD73YQVT5R5RNVPlHlE1U+UeUTVT5R5RNVPlHlE1U+UeUTVT5R5RNV PlHlE1U+UeUTVT5R5RNVPlHlE1U+UeUTVT5R5RNVPlHlE1U+UeUTVT5R5RNVPuN4mjmOLyaKbxP/ zekKev0Mvf5AcRHvbuLdTay7iasjMXXkzHPEs5t4dhPPbuLZTTy7Fbu6EF8XiZ/UxeKwuoq8eFzU qs/J37TzabO6ShiKhT9/UvpxhaHmkBFLYJUIqqsVp/ogdz8moupa+W81iJ/VF8TPLta3Lta3rrPg bOgO54AHesBMrrkNboc74E7wwSy4C+6Ge2A23AtzYC7Mg/mwABbCIlgMObAEloqfzXia6Wm1misi xHJIfVYcVfmmp0xX55Ht82Ehn+YQ5RJYIYrUPFgJ98MqpaO6WrynruG6J8VB9Sl4Gp6BdeIT4vvE pYpvXFawQRLYwQFOSIYUcIEbUiENzoB20B7SoQNkQEfoBJ2hC2TCmdBV1KJhLRrWomEtGtaiYS0a 1qJhrWuEKHKNhD/CKBgNY2AsXAKXwmUwDi6HK+BKGA8TYCZx3Aa3wx1wJ/hgFtwFd8M9MBvuhTkw F+bBfFgAC2ERLIYcWAJLxSeKjcw5gIrfoWKlulbUk0urRAN50qRk40IcF+I40IwDMsMqmXEMZhyD KwxUjqNynBnGYIYxmGEMZhiDGcZghjFQP476cdSPo34c9eOoH0f9OOrHUT+O+nHUj6N+HPXjqB9H /Tjqx1E/jvpx1I+jfhz146gfR/046sdRP476zajfjPrNqN+M+s2o34z6zajfzCxnMMsZzHIGs5zB LGcwyxnMcgaznIG6cdSNo24cdeOoG0fdOOrGUTeOunHUjaNuHHXjqBtH3TjqxlE3jrpx1I2jbhx1 46gbR9046sYZc4vIbjkWc9F0Odm9SklD7WrUrkLto8ocNA6gcYBMj3LlDrSuRutqdSnvc8UR7mog 8zUyXyPzNTJfw4cT+BDAhwA+1KtPiO2MgFJGQCkjoJQRUMpY+obasA2PgngUxKMAHgXwKIBHATwK 4FEAjwJ4FMCjAB4F8CiARwE8CuBRAI8CeBTAowAeBfAogEcBPArgUQCPAngUwKMAHgXwKIBHATwK 4FEAjwJ4VI1H1XhUjUfVeFSNR9V4VI1H1YwQjRGiMUI0RojGCNEYIRojRGOEaIwQjRGiMUI0RojG CNEYIRojRGOEaHgcwOMAHgfwOIDHATwO4HEAjwN4HMTjIB4H8TiIx0E8DuJxEI+DeBzE4yAeB/E4 iMdBPA7icRCPg3gcxOMgHgfxOIjHQTwO4nFQ8eFgGAfDOHgMv7fi4lGcK8e5H3GuFudqca4W52rx 343/H+Cehnua+iifPY7Ta8S7OBjFwSgORnEwioM1OFhPnnyBixW4WIGLGi5quKjhooaLGi5quBjG xTAuhnExjIthXAzjYhgXw7gYxsUwLoZxMYyLYVwM42IYF8O4GMbFMC6GcTGMi2FcDONiGBfDuBjG pVpcqsWlWlyqxaVaXKrFpVpcqsWlWlyqxaVaXKrFpVpcqsWlWlyqxSUNlzRc0nBJwyUNlzRc0nBJ w6UKXKrApQpcqsClClyqwKUKXKrApQpcqsClClyqwKUKXKrApQpcqsClClyqwKUKXKrApQpcqsCl CuU8XDJwyTBHY4sLjbhQjwv1OGDggPzeVI+69ahbj7r1qFuPuvWoa6CugboG6hqoa6CugboG6hqo a6CugboG6hqoa6CugboG6hqoa6CugboG6hqoa6CugboG6hqoa6BOPerUo0496tSjTj3q1KNOPerU K/2pDMepDMcZ/RrzeYr6KFE8RhRm73m9FtYx37/AvN2VVV03OAvOhu5wDnigB8zkmtvgdrgD7gRW kGjdhNZNaN2E1k1o3YTWTWjdhNZNaN2E1k1o3YTWTWjdhNZNaN2E1k1o3aTcidZRtI7SY40ea4yC GKMgxiiIMQpipv4nRwC6/ybzWcGr8jcb/znbo/gRxY8ofkTxI4ofUfyI4kcUP6L4EcWPKH5E8SOK H1H8iOJHFD+i+BHFjyh+RPEjih9R/IjiRxQ/oiiooaCGghoKaiiooaCGghoKaoyGGKMhxmiIMRpi jIYYoyHGaIgxGmKMhhijIcZoiDEaYoyGGKMhxmiIMRpi/8VoiOFQDIdiOBTDoRgOxXAohkMxHIrh UAyHYjgUw6EYDsVwKIZDMRyK4VAMh2I4FMOhGA7FcChmzvF15n+FvAivNLzSqDYa1SaM9hraS401 NNbQWENjDY01NNbQWENjDY01NNbQWENjDY01NNbQWENjDY01NNbQWENjDY01NNbQWENjDY1ljBox asSoEaNGjBoxasSoEaNGjBoxasSoEaNGjBoxasSoEaPmkrmwEBbBYiDfiFEjRk1pRy3WTx0zZNqj 5kg3qKnG/zRGWLsvYo3KN1NGm5vRZme0VTLSOjLSUpSs1oqykNk4F5bzvXwVP+thUUdm13F1nLFZ x+zcyF2DUdhA4cY2q6Y6sruO7K4ju+vI7jqyu+7/U7WpI/vqyL46sq+O7Ksj++rIvjqyr+7/6apI fluJo9T21u8tjYo18Vkcl35WrkPbQrQtxL8a/KtBW/nNphwnktA3gr4Rs/6t4f2zfEd4jpXSOj57 QUTQNYKuEXSNoGsEXSPoGkHXQnQtRNdCdC1E10J0LUTXQnQtRNdCdC1E10J0LUTXQnQtRNdCdC1E 10J0LUTXQnQtRNdCdC1E10J0LUTXQnKqhpyqIadqyKkacqqGnKohp2rIqRp0j6B7BN0j6B5B9wi6 R9A9gu4RdI+gewTdI+geQfcIukfQPYLuEXSPoHsE3SPoHkH3CLpH0D2C7hGXjHMhLILFkANLYKmI mBr/lBgJcaWD+pHSSf2SFedW8vIrkaduFxvVY6wzdLFG/UkUWamc1kF8ex0i3rMOE+HWv618vdLO +ifz3x+Vf6cw6g6JPTj2Bs/dDFsZAV+JYrWATP8atvMzd3DcJULqHr7pFvPTghxLIKokq0cYqTpr XIOVUBM0i3qrIg5aHeCETL79DxHV1vPFMetQuAAuFIZ1pKhye4Xmvk3sdt8F1Aj3vRzniJB7LlAT 3Ms45nJcDqyh3fnAjOl+HBiV7jWcf4bPqH3u53m/Dl7iGW+In9xv8fz34H1xzP0P+IDP/Lz/hCMx uYv4bC/sg1Lel0GI1/vhINfViIPuY9AkDqZmiNrUjtAJ+HaYyrfD1F58PkvsTmVNn0q/Uh8UjamP i2Opz8EL8LqoVSYmVC3HpziqlqJqDarWoOpxVD2EqmWoWoqqx1C1FFVLUdNAzQbUbEDJBpRsQMkG VPwJFXVU1FFRR8EaFCxHwVIULEXBchQsRcEyFCxDwXIULDtNwXIUrEHBGhSsQcEyFCxHwXIUrEHB GhQsRb0a1KtBPR31dJSrQTEdxXQU01FKRykdpWpQqgGlGlCqAaUaUKoBpRpQqgGlGlCqAaVKE0qV o1QNSukopaOUjlINSg91k1imfiTeR6kAOfgzCm1AlR/VA+IO8myhekS8QnZfrzay0v5JjCbPtlmt osBqF09Y3WI22R60ZgiPtbtyu7W3WEDm97AOFpei2utk/xXk3F+to8Vy6yXixsTfzqqw/km8ap0m Zll94gv595eI6lNq0pfMEl/BdvEDP/EwfhzgJ4b5CUd4ah1PrOKJRxlLIxlLo/hGuAnHvhR7uUuO l2/MMRJVzubufdy5kzsP0bcwfXPxhGJzPAwTxdz5pdjJXYe562Pu6MAdlfy8CnP88q3aHMPdGaeD eD9EHOCug/SyQDmLzDpm3llAZn0NO8iYXdy9h6wqZhUZ5FgiDpEdh8iOQ2TGITKjksyoJCsqyYpj ZMUxsuIYGREnI+JkRJyMqCQT4mRCnEw4hHOHcO4YrsnKH1XS6I+dnr/Bz9vEz/0XsX4CO0Qzuu5H z7A7Rxg8v4HnN/D8BvcLvH9ZGDynQbFxVyM9n8cdVTLvWQlvopZ8RCxfiSI+Dal7qSNSwwMihm57 eW4pzy1VpvFT13B1HmOq2syWf4lcfnoud9ajRDNKNPOEapQQKNGYGFeNKNGolonNPNFPJhWpGtmT AhniNmsn3OgMXaCnmG/tBb3Fj9a++NwPBuEeulvHcP4S8+8un09vzmfsVaNuI+o2MvaqUbgRhQUK C8ZeNSrkorRAiTUosQYl1jD+qlG7GbWbUbsZtQXjr5rxV43qzajejFq5KN+IYrnud6lEm+EzMd9d wPEb2A174Hsohx84V8GxkmdUifmpitiWmiQ2p9rBAR7e94FZVKiVYg1jsBo3m1PXiqrU52EdvAh/ E5sVFxnZQDZW4fQFVJ8TVJ8TVJ8TuD6ckX6CkX6CkX6CUX1C6YYf0ksD7evQvo677NSoempUPTWq ntgbib2R2BuJu46464i7jljriLWO+lJPfamnttRTW+qpLfXkdz21pZ6+NtLPOmpFPbWinlpRb0nh J64kA9bi/hbcfxr3n1a/wNEAfCm2qwXMil/DdvE6WfCzuo/Pi8mtMrFQ/V58rpZDCPbDD3BAPKhW cKyCap55iGMYIhBVVpItfjXG6x9BI/NqONbCUTFfrYN6XjfAMeGjNhVRucuo3GWM4OupUXvUnzl3 HE6IL9RfOApmYQuoIOuXjWxL4rWdOpUi8qwuXrvFPWY9O4NjO2gP6ZAhRpKt48nW8WTreObW1dYz xWJrV851g+7KDVYPxx7Qk5rXC3qLP1v78P5c6Mv7ftCf1wNhkLiMGnkLleVdXFuJaytxbSXZ/n+I OxPoKKq0f9+q6iWprrCGsMq+CG6Ae1wyOhF1BBxGcRAUdEQZmETZIkIIi+MusrhAEBAQxACySERl E2QZcAlk6YRKZ5mYEEJ3OhWWhCQk9P2eauP8df7zfXNmvjnnO57nVFfVrbr3vve97/t7c7B7GPHy Le0m2twMt8gXtVs5xsJtcq52O8c74E75OLviPu1XfL5LTmVnPNL8L2a3sENmaKNFB20sTJQniK+f GBNlpjEJJstGdkkjO+RtdkgjXjIfL5mPl8w35nP/RXgNXoc3YIGIMd6ChbCI9u9xbSks4zwVlvOe FZx/wHG1TDTWwjpYL18xPpIzyGZzjU2cb4ZPYIscwq4aQoabiwfOxwPnow9eIcvNNT6TLxo74XPa 7eLaHtrt5fM++Irrhzk/yvVjvPdbrn0H33MtA45DJu/KgmzIof1J2pqQzz0fEL3x7vns2iFGsdzL zh1CFp3L7r2P3TvEKOMaPmjgg8ZpwA+NM+CXBwz80MAPjSDgg0Y1nIVzRIDzcJHP9XKf0QCX+HwZ 8DkDnyMqzIvC76LwuyhN7otycHTKJKJEElEiKSqC80iihw74YJQhD0RFQQs+t4RWXG8NbaAt16Ol SaY3yfRmVHve14E2HaETdIYucAVtu3G/O/Sg/55cI8ISjeZFzZWZ7PD5Ua+KmCjWOoq1jmKto96E BfAW996RM9j584lUQ4hUQ4hUQ4gC84lWQ6JW8J5VjHs171zH+9dz/hFsgI/lNNGDKDGVKPFpODMf DOfzI0SCCnb8Inb24+zsnezabezab8i5tezY/ezYMnZlFrvxW3bhPnZhDrvuHnbWWHbSNnbMW+yY I+yYCnbJe+ySHHbBV3j/R3j/g3j/Abzf/j8VbsLjT4g/EK82MpJPyFjZ6jay1E5iwpdc2wUHyXOH uHdY5hE988hcB4hZVWSuneTAKkbrJ3vtJHvtJH6tZ+RHiFN+Rn6cWHSYUZvEm1LiTSkjryBeexl5 NTHbS8z2Ek8OM/otxIItxIItjLKRUf7O1jxkr2zjSSLt03InGWwnGSybDLaTvVnF3qwig2WzPzey P6vYnxvZnxvZnxvJYNnGSzz3MrwJC2QeUT2PqJ7H3qwim2WTzbKJ8HlE+Dz25kay2U725kb20hb8 fgt+vgWf9pNPvOQTL37rJ6d48VU/fnoYv1yPX67HL9fji358rRRfK8XXSvEtP77lx69K8atS/Oow uciLTx0mw+3EpzaS4bLJHHn4x3r8w49/lKIg9+EHX8HXKLSj8kssfYrskIUv3E00LySaF+IP32HV EqyaiVUz8YkviNzFWPYYkboQyx7DssfwjUp84zTROIdonEM0zsFHrsZH6oiyPqKsD1/Jx0/KiawZ RNYMImsGPpNLNM0nippEzhwiYhYRMQurn8Lqp7D2KSJgFhEwiwiYRQTMIgJmYdlTRL0sol4WkS6L iGYSxXxEMR9RzCSKZRDFMohgJhEsnwiWT7TKJ1r5iE4+opOP6OQjOmUQnTKIThlEp3yiko+o5GuO ShlEIx/RyCQa5bA6x4gshUSWQlbpGCt0jOhSTHQpJoIUEy0KiRaFRIZCIkMhkaGQlcpkpTJZqUyi QjERoJCVymSlMtn5hazUMXZ+Fjs+ix2fxY7PYsdnseOz2PEZ7PYMdruP3e5jt/vY7Rnsdh+7vZBV zGSXF7LLC9nlhezyQmriM6hjW1ffIJvEjewyu876EzsqlR2Vyo46yDrPY9c0sK4bWNd01jWd3RJg XctY162s6VbWdCs7op5dUM9azGMt5rED6lmPeXh8PV6eipen4uWprMU8vLweL6/Hy1Px8lS8uQF7 bcVOW/HmBmy1FVuVYasyvLoBe5XhyQ3YJx37pGOfdOxThjc34M0N2CgdG6Vjn614bz3em4rnNjDn dOZ4SL6Fx9Yxg32cXWDstXITvlksOjGzC5yVMzM/M/Mzs7PMKoM4EGBmGcwsg9FdYHQZjC6D0V1g dBmM6gIjusCI/IzIz4j8jOYCo7nAaPyMxs9oMhiFXcv6RTd6qqWnfHoqp6dyejqDDe0aNZPeaugt k94y6a2W3jLpLZPeauktE1ucxxbn6bUWW5yn51p6Lqfncnouxxbn6b2W3mvpvZzey+k9k97t+rCc GqGYeHlBnmDWJ+i5hh4LiWW7iLgnibh2ffBFOOK6aFXTXEMFmv8fpuu0UWJw2HIl3CnkTkn4zK7t GsN2dDY/dZ6zIO/P4/3nUMMmmjaIhS8xTx1LCHCiSV3ghh6c94VV8izvKA6vTBatC8gi9hhrRF/e cYQ7X2K/87xrNy1O/1Tfh/ONIL64IQJ0uZtZjWA2T2HH89ixGDsWY0e7vi7GfucZw27GcIQxHGEM R7DlL+vuztDlZ/V3D9r3Zi/25biK9qu5ZtfcCnO2RHvGd44xnWNMlYypsvkvONWM3s+4qhlXNeOo ZhzVjKGavs/R9zn6Pke/lfRbSb+V9FdJf5X0VU0/5+ijUvTm7XuY/V+Y+bGfRVkvdt5CTxfDUVUP /0uRl5vXMp/ZT7T/Rc9P0YcZH6PXPfS6h173/MPIY0eaHrSzo0xfjnbEWEXbv48YkeEsegEd0EBt 7WJdR8rJzf+64wQ9Pxr+F6ODGXcxLb9g1TKoC/IY/36stO1nEcTODCaWWsVa23n3NNZahbVWMZ/9 vPVN3raVVcxAu+VhwVVYcBUrmYEVV7EjTHaEyYpmML/97AqTORYzx2LmWMyqZqDB8tBgeeitvL+L HCarnMEqZ/wtcvTgHb3lKua+n3kXs8oZ4ejRGasXYPWC8F8jaokiDfIQo67C8gWMuIoR23/DqcLa BVi7gFFWMcIqrFyAlQuwcgFWLsDKBVi5AAsX0FMVFi7AugVYtwDrFmDdAnZVLVH3EtkP78HDauV+ oZIFL6GUGoSGGjnK2TnOKkQPzixqmHr0iYU+sciUdWTKOjJlXfPfCANolrPo+HoyXoBMFyDT1ZHp 6tDr9WS7ABq9Hl1hocnryW51ZLc6slsdurse3V1PZqsjs9WhOywyWwDtYZFp6sg0dWSXOhFJLm9g JCvJ3RY529Z1p+nVYgXXsYLrwlElkmxfo0UTSa6RQWbgp1VQu1G0JMJQ84hB9GMKB+85xXvsv7nW 2zNgxkb4LwgBuz2WiGY/3SjruW7/VZYWPFcq2nFmz76G2dcw+5rwzEejFcbK3J/NvIaZ14Rnnckx C7KhAAqB2TGzGmZWw8xqRHd6O459a7HvSex78ueVOX0H6aUc29bSQzk9lP+tGt8R/otfObatxbYn sW3tLyr0k5yb4b8Chit1bHuS3sux7cmfV+tCYea1orcWxadouRq1ZKGWLNSSxZg+Z0yfY61aFJMf xWT/da0KO1WijCxWoIkV2MwKbKaObEMdaf/rSFv1+FE9fsb1OerGj7rxo278qBs/asaPmvEzns9R Mn5UjMWYPkdR+FEUfhSFHzXhF25G8yk9X6DHenq8QG8N9PYdvX0nenH3B+xWwRjzGWM+LS82/w37 /63QjSi72/Dru7DDelmBDS9hw0t/W6UdXEvnfBfHPSitoxx/vmonOTfhp9Urok0J7Utl/i9WMQar lWC1EqxWgqVKsFQJ4/5r89+kSrBICRYpwRolWKMEa5RgjRKsUYI1SrBECZYowQolWKEEK5RghRLR iXkWMcci5ljEHKuZo5c55jDHHOaYg1K1vS6H+eSgKgOoygBzKUJZ2h6Yw1xymEsOSjLAPHKYRw7z KGIORcwhhznkMIec8P9F2UsbJ3qJVDFeLhdPwzMwTa4Rs+QSkQyzIQXmQJlMFaegHM7TpkEuFpeg EZrgslysXCkzlf4wAK6Cq+EauBaug4EwCAbD9XAD3Ag3wc1wC9wKsXAb3A53wJ0QB7+Cu+Bu+DXE wz0wBO6F++B++A08AENhGAyHB2GiaK8ckPuVr+UXykE4BIfhCByV+5Rj8A18C9/JfY7VcoljDayF DM6Pwwlgro4QSLnY2Uoud7aRqU5UthOV7URlO9tDB+gIJXKJM0ibKjgrl7j6w02QIJe7EuFZeA6S 5BrX84DdXYtkpitT7nNR8bj7yn3ufnCl/MLdHwbD9ZzfDqNlqnsMjJWL3ctgPZRw/gOUAmvm9ss1 7gBUc6+G84tycYQqMyM0cIATXIBSjEApRkSCDh4wIApaQEtoBa2hDbSFW+W+iFgYx+dnOM7j+DHH NPlFRK3MjORdkW3Rx4+LNvK4aAtEP9EOYqA99IMroT8MgKvgARgKw2A4PAi/hRHwO3gIHoFHYbxc ieeuxHNX4rlzxHS5SiTB8zADXoBZMg1vTsOb0/DmNLw5zfGGPO54ExbAW7AQFsFiWAJvwzvwLrwH S2E1z62BtTKNVV/pPCmPOwuhCP4KJVw/zbECgtyvgrNcuyyPu1zghkjQoQN0hD7QF7CDCzvgHWmu GzjexPE2jvfC4zAWxsETkCBX4jkr8ZyVeM5KPGcOnjPHxXxdzBcPSot4zraNWCIzxdvwDrwL78FS 2AAfQxpshE3wLXwH30MGHIcTkAlZkA054IVcMKFM7iAm7CAm7CAmfCMuQA3UwkWogwa5jTixjTix jTixjTixzXFGZjr8EIBKCALVicOCajgL5+A8ULE4asB+LgRSbmO/7XATC9zsfTd73c1ed7PP3cPl N+6HOY6E0bQZA2PlNvefOJ8OSTADXoDZ8Aq8Cuw3NzZyYyM3NnJjI/bTNveHHNdz3MZxD2AHN3Zw Ywc3dmCv7WCv7WCv7WCv7WCvfcNe+8ZdCUGo5tkarmMP9t025VrhEK2FE1z2jyXZvwoCkWB/e7cH DPsrJqEFxIoYcRuMl8n4eDI+noyPJ+Hjk/DxSfj4JHx8Ej4+SczkDbNkIn6eiJ8n4ueJ+Hmi+LNo KV6Cl+EVeBVeg9fhDXgTFsAu0VXshjI5ixWdxYrOYkXfZUXTWNE0VjSNFU1jRdOE/Q3SDTKFVU1h VVNY1RRWNUV5X+YqK2AlfACrYQ2shQ9hHayHj2ADfAxpsBE2wWb4BLbAVtgG2+FT2AHp8JnMVQeK luogEaPewDEO7pPJ6v1ymvoAjOB8opyvTpIJ6p8gQSag2R7Qxsjp6LYHtHEcp8tvtSSZpWUKp5Yl orUcVG8uVXme0LUymaadQouUiyu10xwr7O8G4lgp2jimi9aOJHgeZsALMBNmQTLMhhSYA3NhtUwk XiQSLxId2aKlIwe8kAt5cBJMyAcfFEAhFAH2xNtT8PYUYk2ys7XMxetnEWMSnZVCJ74kE1+SiS+J zkbR2qUBvuVqA22hF/SXia4BHAfB9SKGmJLoupnPCTKZ+JFM/EgmfiQTP5KIH0nEj0nEj0kufMk1 C/Al13KZ63o//H/Q57qvgK7QDbrDIBgu09hps9hps9hpKe4poqV7KsyD+bAElnF9Nce1oiu7KcW9 mc8ltP8BSgGfY+e8y855l52Txs5Jc1eJSLcF1bSv4T7+xw5KcdeJlhHRMjeiHcRAe+gAHaETdIYu wFgjGGsEY41grBE9oCf0gt7QB57iXePhaUjhfA7MlbmRiszVR8lp+mhIkQn6XGDf6OwbnX2js290 9o3OvtHfgoWwCBYD89XfhnfgXXgPlsIySIXl8D6sgJWwCj4A7KOvgbXwIayD9aKlJxlmQwrMgbmA bT3Y1vMisL897G8P+9vD/vYwTg/j9DBOD+P0ME4P4/QwTg/j9DBOD+P0MEYPY/QwRg9j9DBGD2P0 MEYPYzSuEi1bRIIOHuKDqp1gp5QRjexP9nePtFdnEM2M8K8LuMANERAJuv17U+FfnbK/wd6wfwYF BeBDAfhQAD4UgA8F4EMB+FAAPhSADwXgQwH4UAA+Il9bIl9blEAAJRBACQRQAgGUQAAlEEAJBFAC AZRAACUQQAkEiJITiJITiJITxB+lJSbCJPgTJEAiPAvPwWSYAlNhmpxIRJ1MRJ1MRJ1MRJ1MRJ1M NI0nmsYTTeOJpvFE03iiqU401YmmOtFUJ5rqRFOdaKoTTXWiqU401cm7heTdQvJuIXm3kLxbSN4t JO8WCvvvHWmwETbBLtGRyNuR/GuRfy3yr0X+tci/FvnXIv9a5F+L/GuRfy3yr0X+tci/FtF6CtF6 CtF6iqiglj0DfghAJQShCiyohrNwDs7LZUT2DUT2DUT2DUT2DUT2DUT1mUT1mUT1mUT1mUT1mWh6 E01voulNNL2JpjfR9Caa3kTTm2h6E01voulNNL2JpjfR9Caa3kTTm2h6E01voulNNL2JpjfR9Caa 3kTTm2h6E01voulNNL2JpjfR9Caa3kTTm2h6E01voulNNL2JpjfR9Caa3kTTm8pvRYwyAn4HD8HD 8L70kom8ZCIvmchLJvKSibxkIi+ZyEsm8pKJvGQiL5nISybykom8ZCIvmchLJvKSibxkIi+ZyEsm 8pKJvGQiL5nISybykom81BLp1BJ7qSX2UkvspZbYSy2xl1oinVoinVoinVoinVoiXfle6EoGHIcT QieLGWQxgyxmqLH2/6PK8dcc75NzyWbDyWbDw9lsjAyq42Ei2e1nWU1NlEEy2x1ktklktjvIbJOo xRdp0+QWbY88qH0lWmhfk/1OUM9nUafniPZkuQBZTtNOUt//mOmcZLre4e+YDHC9kswzXRhkOYMs Z5DlDLKcQZYzyHIGWc4gyxlkOYMsZ5DlDJR0ACUdQEkHUNIBlHQAJR1ASQdQ0gGUdAAlHUBJB1DS AZR0wLFMWo5UWA7vwwpYCavgA1gt48mc8WTOeOqudOqudOqudLKoThbVyaI6WVQni+pkUZ0sqpNF dbKoThbVyaI6WVRHZ1roTAudaaEzLXSmhc600JkWOtNCZ1roTAudaaEzLXSm5aiVQcdFqIN6aIBL 0AhNwJ4gM88kM88kM08gM3vJzFOo/0zqP5P6z6T+M6n/TOo/kyrBR5Xgo0oIUCX4yODxzlPSolLw USn4yOQTyOQTnIzJyZjI6PFkdIOqwecMcS6l5RKggAqaMMj0BhWFj4rCR0Xho6LwkfkNMr9BZeGj svC5utD2CujFtT6c9wViLVWGD2UQjzIwXAO5jw+iDtpSdfhQCPEoBIPKw0fl4aPy8FF5+Kg8fFQe PpTDBJTDBJTDBJTDBBdx1EUcdRFHXdNgOiTJiaiJiaiJyaiJyaiIeOpZEyXhRUl4XR+Ev5EpxrUd Pgt/K1OM6wjHTJmOyvC6WEvqXtNVJ2JQHF4UhxfF4UVxeKmF06mF06mF91IL70WBeKmH91IPp7tv Ezo1cTp1gUVdYFEXWNQFFnVBISplA3WBRV1goVamoFamuB+TQffjMFbOpD6w3Al8Zk+5n4XnYDJM 4Z1TgXlROxRSO1jUDha1g4XC0VE4OjWERQ1hud+g/ZvhbxW0UD069YRFPWFRT1jUExYqaCYqSEcF daSusFBCM1FCOrWFRW1hUVtY1BYWtYVFbWGhkKagkKagkKagkKa4T/HucjgNxHo3sR7VtAzVtAzV tAHVtAG1NBO1NAW1tAG1NBO1pFPrm9T6JrW+Sa1vUuub1Pomtb5JrW9S65vU+ia1vkmtb1Lrm9T6 JrW+Sa1vUuub1PomqsuL6vKiuryoLi+qy4vq8qK6vKguL6rLi+ryorq8qC4vqsuL6vKiuryoLi+q y4vq8kYMZkzXw60yPSIWxvHupzgfD0/DM1ybwPGPMBEmwXMygELzotC8KDRvxDyeWcT1j2mbJvdG bOTzJqiVZqQQMSg4byRzi2wr0yPbCV1/SJbpD8MjMEoOR9kN1x/j8wsyqM+EZPhJ6c3n88vwqjBQ fAaKz0DxGSg+A8VnoPgMFJ+B4jNQfAaKz0DxGSg+A8VnoPgMFJ+B4jNQfAaKz0DxGSg+A8VnoPgM FJ+B4jNQfAaKz0DxGSg+A8Vn/B8qPuMXiq+dWChvV8aKYcoT4iHlSfGC8gdxj/KUuF0ZL36v3idG qRPFI9pIebc2St6l7ZYbtK/kMK1UfoM2jNaIcNppuUQ7I49qftFZC1BvVcqLoptYGDokNstscVhm 8/Y7m78N9ibefhVvv4q3/0qZKC+SW8vphWqOqmykjKWXO+glSdsr92j74KtQUDsgd5LjTmoH5RHt kFxI7y/Rc71WLivoPZbeF9G7Ru8f0PshEaEdl+u1TMZEJa9ly6e0HLlL8/JUniwgKxahUzfLvzC2 v9DyUXLncVovo3Wylh0K0Xotre8nj+7kiRk88X74ux2vY7QpZPMryN73q8PI5BPlRPVZoamb0MmH 5B/UozJVLRY3qrVk5GjRUrtOfqTtFQZZ+jpm8Ck9HaUe1bRsas1c+RlZ2snbQ8zIS6ZObs7UWnNN qjGzCs3PrAJcr5RVyu+FQ+4STnCBGyIgEnTwgAFR0AJayj2iFcTKAnEb/FluFy/By/AKvAqvwevw BrwJC2AhNtwls8RumaWoskDRwAFOcIEbIiASdPBAFLSC1tAG2kI0tIMYaA8doCN0hW7QHXpAT+gF vaEP9IV+8FtZpIyA38FD8DCkwByYC/NgPrwIf4aX4GV4BV6F12CxzFeWwNvwDrwL78FSWCbz1YFy u3oDxMEI+aX6uvSpb0gfXj6SVQniZ0342HZWIoiPPYiPNWkXQ2e0OnZEvXRrDaE67VKoQGuULq0p VKFdlnFaiOtSdnQ4Q2ccLnm3wy3djohQnSMyVODQpcvhCVU4DBnniOJ6C9pNl7scSfA8zIAXYCbM gmSYDSkwB+bCh7LAsQ7Ww0ewAT6GNNgIm2AzfAJbYCtsg+3wKeyAdPgMdsKXssixC3bDHtgL++Ar 2A8H4Gs4CIfgMGTL7Y4c8EIu5MFJMCEffFAAhVAktzsb5S6XBvivyyn3uNpwbAu9YAAMgutlgetm jgtkkWsppHLOPF0f8Zn5uJiPi/m4mI9rG9e2ww5Ihy9gF9d3wx7YC4zdxdhd3/L5O/iezxlwHE5A HpyU+S4f9yqgEs7BebgANVALdbLI3QJaQitoDR1kvrsjdILO0AVukAXum2GK3O6eCvNgPiyB1bBW Zrk3c6yT2yP6yaKIq2RBxLUcB3IcDg/y+VGZH/EU98fD0/A611O5vhzehxWwGRplfqSQRZGtObK/ ItlXkZ2giyzQn5I+fRIkwLMwGaYD+11nv+vsd539rrPfdfa7/hYshEWwGBiv/ja8A+/Ce7AUlkEq LIf3YQWshFXwATBHfQ2shQ9hHayX2z2/kT7PAzAUhsFweBB+CyMgWX7pmQ0pMAfmwjyYDy/Cn+El eBlegVfhNXgd3oA3YQG8BQthESyGt+EdeBfeg6WwDFJhufzSuEpubxEpv2yhg0d+KRzkiu1E/oCW K64lLjeJ98QsuUIkw2xIgTnQIH3Uzz7qZx/1s4/62Uf9bFE/W9TPFvWzRf1sUT9b1M8W9bNF/WxR P1vUzxb1s0X9bFE/W9TPFvWzRf1sUT9b1M8W9bNF/WxRP1vUzxb1s0X9bFE/W9TPFvWzRf1sUT9b 1M8W9bNF/WxRP1vUzxb1s0X9bFE/W9TPFvWzZX8Ll/IXxnlUBqlZg9SsQWrWIDVrkDo0lTo0lboz h7ozh7ozR10vz4T/feSP/+roB7VO/kA2M8liK7QTohv5soQMtoAabgU13ApquBXUcEFquCA1nF0/ +aiffNRPPmomi5rJomayqJksaiaLmsmiRlpBHbSCOmUFNckKaogV1BAWNUKQ2sCiDghSBwTdA6TP fVX4+ziDaH9by/vQ2T60tQ8t7EMD+9C/FvrXQv9a6F8L/Wuhfy30r4X+tdC/FvrXQv9a6F8L/Wuh fy30r4X+tdC/FvrXQq8G0atB9KqFRg1GJPHueXz+2P7WNGmhNy30ZjAymv00SqaiMVPRlDloyhwj RZ4x5sBceSYqWv4Q1Q5ioBt0h/lcXyd/ECpZ5RPyOjpO2y1u1faIx7X94gbtgOiAfb/QDqKkDol+ 2nExHFsPp653ohjupLZvo3nFYOz+V5RDV3ROKVfLxAD0wnD0Ql/tjBjCew82/y37Knr6Wm6m/Tvh PrdzbxKqYo9owbVvODthfy/l//9duspEEfePv0+X8Qxid9xOr0PJh/czhh+vDCJb1nH1brLlHrJl IPwdxZX2r1FytQtnd4b/ptietn0Yg/1bBKfFNbS4lrMTIo4ZRnOvK3O1v/VtlMzQpotYxn/QcQd6 TeXKMc6+ozW5CU1YzVkRZwkiirNLnB0T/YRDxAknuMANERAJOnjAgChoQY8jRTttNBpvLCQwpz3o wAPozK9llmO6iHMkwfMwA16AmTALkmE2pMAcmCviqOXjqNnjqNnjqNHjqNHjqMnjqL/jqL3jqLfj wr9/EYW6raGnImZxWtvPStq/ZvK1/Bx1W8ncp2OT3YxrH62YLXOPEm2UTNFLyRIDscxY7PBrbTSt xogx2tjwd8yN0RLk1/a3EmnPy1JtqbhJWyZuph+Lle6DktnquFUMdsSKgVhrjOjKE13p5wZWc7ro Tk9Vdv/hnqKaf9fkqPYYTz9O+yc4PslxOh6WKfPRyEH0cUPYf/JEBE9pwmX/EgqtY2gZQ8tIWlq0 qBYxoowoioYS5eimqfRkr+nzMgfdHWTVWxJxs8Lv87KCuTzFO21F7Gwjm6jhm6jhm6iRm6iRm6iR m6iRm6h9m+hzpDxj/x9PvHEAO8UdfluurBHtf9HnY8SsJyCRuU1HiZ+Q5xhdNfOw8Lh29F3LU0fo 10O/9f+0Xw/9ltq/zcLb2tCvkzfW8sYgb6zhjZG87VzzLJrYZyO5an9f4GMo+SdgKnemi448GcmI XTx5kSebeDKKsYRsq/FkI7uiTNwrTkE5NODZl6ARmuAy0WEklcsoOVB7jGjxuBinPcHxSY6J1D5T Gc/zcp02G79YKm7BH27H4pn0GBtem2y5KtybV+ax56Kpci41+8hgB+92hECKfs424l73aBgDY0U/ 9zJYDyWc/wClwDjd1Vyr4XiRsdnf/1jNyBqYcwMjG8C8GxjZAObdiXnbESOC+erMtUI7KVqFvW4v TxzkiVM80YknTvFEJ564hdatGPPpsOdly0bGXc+Tp8JPecO/SzCa/sbgyWM5juOYRFQsFT2JeNXE GJ3I2JHI2Jp4tzf8izr2+vlopXGlmnUYyadR4b1hfxtejDYNr5pBvjvNuM/Qo19aYX8r4blTPKfz 9gjerHLHJzqK8fKceBqegWms/kjWczTjGgtJeKbdugwvOY2lKxiTn/oywFsqyZN3iPbOVvKcMwhV 8pwrARLhWXgOkuB53tui+TeBTN7s480+bRqzSiLml7KOZXjRKXZQeLbE4TPYyC+/D9fi7RlfI+Nr ZHyNzbO3/6ZczFuKeYvKWwYwxla8pY63hHiL/U3zEbzhB/v3iBhfI+NrZHyNjK+R8TUyvkbG1yiu EePFUPE0PAOzRLxIhtmQAnNEPD22pMeriVlOLDyCmOXEyiOIWR9j6R1Yeh9+ehQ/vR8/HaptkkuY 03dkiL4/joa8ZY/mDGriVhGLj8Y67pCmY7WId6yBtSLe2UoMdZZwDHKsgrMi3tUfboIEMdSVCM/C c2CPL4JRXWz2G7XZb9TwWtkW9MuK8F8jtjLuDc2tYppbxTBui5aDw3+B8MscPCMhdIhasIrar4Ra r4rarsRxZagcX0sIWVyt5kq140p5J29NCBVrF7FzI083ERsuy+MOp6yjLqx3eGQNLY/Tckj42a+5 m8WVLK7o4Wct7RL9NWKVyzKXGjPkiBQung3RKpdaMkTLOOJSQug0vYSoUmsYWVBr4NhIr0145o9P NtFriOq0hhEHHREcdUbh4fqPb2piBrV4XQJ1bZ1QeEs1bwnxFskbzoT7dgmFp6t5OsTTkifPNI+h v22n0GLGUMrTvXi6gKcvapfYsfbom/Djy3hcCJ0g5WXGUsrbevG2At520REpveFZeVhnQ7SiUg7w 5suMaYudRaXKG+sZR5EWEipP1dN3kSOKz1fKHnaL0AlaVNCfbSkfLSp4p20lH+84i3X/br1Y/eZ1 4ul/sj7htuF1oe0/WQ/m+L9cB+Lpv2h/osx/2O7M8b+xd/jOP7SzaOGIFpGOdoyvg9AdnXhbZ57p gma4gs9dudeNez2515vzPtzry71+5AOHI4YeOnO3O8c+rInhiOaMGsLRnv470UNnerLf1ZXr3bje g+u9ud6H67yHVbBb2z13bm5h92S/qw3jUrlb7ojhSnvoILoyvja0LOedXRmfyvhUnip3dOd+D+jJ 9d606cO1vnzuZ/8qOW8pYqz2DFVHR8baSTib32I/XcT47Rmqjl7c6829H59WmW80tMP3YhhzB97b ibl0ZvW70NcV9ry434373bnfk/u9udaH+32534/5MQvWph3vjeFqe+gg8xhDCOuUOrqwllcw5660 6Uab7tzvAT1p04s2vWnTlzb9yGz2Ohlhu3YQ0YzDtlg944hmHB7GYYRt25Pz3mEL1jOGaMbgsVdF aOG5d2q284+jt62nhef94xPVzaNWRct/1yfYtRb2+zu/YLdfJ6L+Vd/gqYHC/d/5B3f7iLb/KR/h bVcz63/TT3j6StH6f+srvOVWe0b/GX9hJb4Nr+O/5TPh3BD1r/pNOKpfqV0M+YmkTxBxuhDVhmmX QtVEtXu0plCA6DOeqNadqBbrcIb8RNQniEZdiGrDHJGhaqLaPQ5PKEBkGk9U605Ui3VEhy5ikWuw SH8s0t/RgfOO8mos0oJRDcIqfbFKH0dXrnejXXfa9ICenPeiXW/a9aFdX9r1w2siqdwMaq44zf5d n0OiLWo3GqXbG1VxC1rhCGqvZfi3hXYrY8VtyhNiiPKkeFP5A8enqNxHypXaI9Qiv5e7UR4rw79U 1/9/aHUk3Mr+DaST4as/nW3/25lKJf+VckBuD3+yf92ulE8tqZKvEULEUpMOEHfx30DxgHhIDBKP iN9z9VG03O3ij2KB+I1YKDaJ58Ru8RVnB/hvifhW5Im3hcl/q0UR1ckaUcEbNyqdlc4iW+mqXCNy lKHKMFGmPKg8LMqV0cpjolIZp4wTlvKkMl5UKwnKs+KCkqSkiovK+/zXSVnJf52VD/ivi7JR2aRc oRxQTijd1IHqYOU69Qb1ZmWwGqvGKjepd6pxys3qr9V45VZ1iDpEuU29T31AuV0dpg5TfqWOUB9S 7lIfUUcp8eoYdYxyrzpOHafcp45Xn1buVyeoE5QH1Inqs8pQdar6X9R9B3wVxfb/2Zndmb33ziYh CZAEQpciiHRUQMH6BH3YsKAoNrBhQUREioBKVZoCPpAiYMMHVlBQsICIBRGkSm+h997m/525NzEx gRDg6e8/97Mns7PT7t4z3/memd2T9s5NrAPr6dzGerNXnNasPxviPMaGsTecdmwc+8hpzz5hs5wX 2Wy2yBnKlrB1zjtsM9vqfMJ2sl3OZLaHHXQ+Z4fZUWc605ycbzjj3PmOSx44s3g8T3R+5sk82ZnH i/A05zdempdxFvFy/DxnCa/AKznLeBV+gbOCX8gvdFbx6ryGs5rX4nWctfwSXs/ZwBvwS50M3pA3 dDbzy/nlzhZ+Jb/S2cqv502dbfwWfruzkzfn9zv7+GO8jXOCt+XPMuKdeCcmeBfehUk+hA9lPp/I J7Iw/5R/yiJ8Cp/CFP+Cf8cCPpcvZil8Ld/KyvADXLMqrufGsTpusluRNXQbuA1YM7ed25Pd6vZx P2OPuJ+709kQ9xf3V/amO9/dwEa7m1zNPvXCXpj97ClPsV+8BC+RzfUWeEvZb95ybzVb4q3z1rEV 3kZvI1vpbfI2s1XeVm8XW+Pt8fawDG+/d5Bt8g57h9lW76h3lG3zjguPbRdSxLEDIkEksBMiURRm WqSIEpyL0qImD4vaojZPF3XFNbyEaCqa8QtFC9Gd1xEvipf5XaK36MvvEf1Ff36fGCgG8fvF6+J1 /qAYKkbwVmK0GM0fE2PFWN5GjBfj+eNigviEPyEmiy95BzFDfMu7iu/FbN5DzBEL+UtisVjCB4ll Yhl/TawUq/jrIkNs4UPFbnGMD5ckGX9HSlmKvy/Ly1p8prxYNuALZEPZkC+RV8hr+FLZWP6br5Q3 yhv5OnmLvIWvl7fKW/kG2VzewzfK++UDfJt8WD7Md8hHZQe+U3aUXfhx+YLs5jL5suzpurKP7OsK 2V8Oc335H/kfN1GOkCPcJDlSjnKT5Tg5zi0iJ8hpblH5nZzjVpS/yUXuhfIPucetLffJI+718pjU 7i1+eb+8e7tf0T/fvcOv6l/o3uXX8mu5d/sX+5e49/j1/QbuvX5Dv6F7v/8vv7H7gH+df53b2v+3 39R9yL/Zb+Y+4t/h3+G28e/3W7uP+0/4T7lP+x39jm57v7Pf2X3Wf8Hv7nbwe/q93ef9vn4/t4vf 3+/vvuAP8ge53fwh/nC3u/+O/67by5/gT3D7+BP9iW5ff4+/1+3n7/f3u6/6h/xDbv8QgM8dEHJD rjsoJENhd3BIhYq6Q0OpoVR3bKhYqIQ7LlQqVMp9N3xzuLn7XrhluKX7UfiB8APux+GHwg+7n4Qf DT/qfhZuE37cnRx+Mvyk+3m4fbi9+0W4Y7ijOzXcKdzVnRbuGf7AnRH+OvyDuyG8MLzc3RFeGd7g HggfjqS5JyJlIwO8UpFBkTHeq5HJkeneyMivkT3eO0qqFO8nVVld5a1Qt6uHvEPqUfWkCKm2qp2I V+1VB5GoOqqOorDqpF4SRVQv9aoopQaoAaKCGqReExXVEDVaVFZvqbdEHTVOfSDqqknqU9FQTVHT xNXqK/WVaKJmqBniOvWN+kFcr35W80Uz9bv6XdylFqklooVaplaJlmqN2iVaqb3qkGivjqhjopM6 EZDoGrCAie6BGwjRI/CDQLwcJARFRL8gJUgRg4O0oLh4LSgRlBNDg/JBeTEy6Bp0FaOCbsFLYnTQ K3hFjA8GBoPFhOD1YIiYGLwRvCE+DIYHw8VHwZvBGPFxMDZ4R0yJY3Fx4su4xLiiYk5csbh08Wvc wbgjYj6xMPg7kbq80A1UkUrROQp6ql6nN1I1vQnxP/LMcUIP15Pw2an74OwGfSfKzEJsU+z6Jr0F ck3s7ECu8ubqFr0Pnz+vyTza2YvjtXz7+zyOr3KkrEQLRUwrJw2wvJBvqT6KuMJMfhcFOF+Xs4+Z 3yaPNn/Wq/UO/QtqWItvm5FfH08j+Kh1SKz29XqbnqU3xM725Gp9K44VepVeoA/pxhTCvTufSme7 fiK/xvR+/Hb7UMOfPcf9B2OJXh2vx5PCkfUb/qX0dhwb9DLUsRKnHnhWeboUsZL26kw9Vy+C/kB3 YLfn3f77+i09En974bhMV9XP6HaIZbuPmd8esW25Sp/Q3+sMaND3+if0A7+DuXs5S2Xl/TmfW0Gw U4nibOzVWMoO1P1Lpm5m14pYyj588z2493/oveD78UiqhV8hq3W91f5CWzNz5yq/TW/GGNuRecfN yqj9uzx7nvz6Hcu3LMfZUznOfji9OhCq2/wxTdOL8fv5enE+LR/MNrar00X55P5Av2tGtP7+tPuU s/xGox1GZ3NdWXgapfHN9Ms2Nvmv41nfdxrloSP6U4tbK83vVtCg37No+h7ua+7gn1YNO/VUi5qn qRd51LDn9LUqj9IxhNXzz6j0h1YuNshxzkPN02h/Y3Qu00ehR3sL3II65dUKOG6yrWTOeGuin9j1 knmUqYRPSXwq5ejl27G/v0Y/pyhfPc/ysbsLLdkPdNp/sg4DP7fr3UCw1XZMGa0+ZNMH28sl9Nd6 uv7dzOgnKX8sW7wvpQL/b6OmZoTE0lZgbpiWG4uzyhzNFh+AmSeerqWWiE+Mpa3D3fvt5LNqZvtW o99A+RDQp20MyU36x3oScT3lpOX/qoUe2FNrpL8Su/6Dno37/2PsLDd+H8kW74PSqXQ9GSZ0WSzt K/0FavjvSdtfn3f6CfxiBh/1jfrf+gHdNJZ7VK7y3YFi4/V/9Tz9e7ZkRi2oB/VD7FXqb96ZoQ+g uRNpCtjhNJpONeyqQh36jhZRXVpKG6gJZTgO3e60dFrS07Dob6J2xpan9saKp2fZI6wNPQd7fAl1 Zn+wddSFbWKbqCfbwrZSL2ObUx92gB2kfuwoO0qvGtuc+hvbnAbCNo/QYF6Sl6Rh/C7egt7gLfm9 NNyd7E4mY9VqGukleon0s/hMfEa/iK/EdJor/hDLaZ7QQtN8Y9PRAmPT0RJ5g7yRVhibjlbBpruN VhubjtYam442GZuOthibjrYam44OG5uOTsCm6+sQrLmBjpCD5TAnZGw6J97YdE6CsemcQnKsHOck GZvOKWxsOqc8bLo9zgWw5rTT1Oe+59zp+37YudtXfpxzr1/IT3Ie8Av7RZ3Wfppf3HnEL+GXctr4 Zf3znCf9S/3LnKdhtT3oPAPrrJfTAdZZX6ejsb+c541N5HQyNpHTOfJ8ZIDTzVg6zlCVoFKcaeoD 9YEzU61Tu5xZxtZwFhhbw1lqbA1nubE1nFXG1nBWG1vDWWdsDWezsTWcXcbWcHYbW8PZZ2wN56ix I5xjxo5wjhs7grG4UFyEybjCcUVZOO5Q3BFm9hQWW41xrMYwaMwQWBRD6T/Q6eE0Dinj8ZH0Nr2P WWoC9ElYfRLQpy8x6r6CVoWtVoWhVXOQ/iP9ThFaiA+Dli0Cq15Ky8GuVtBajLF10LnSlEG7MeL3 4FOG9tJBKkuH8ClHh+k4nUcnoJGFrEamW43kViOV1UgFjXyMElgb6KWyepkIvVxBRdhKtpKS2Cq2 hoqytWwtpbB10NfiVl+LWX1Nsfpa2OprmtXXJKaZpiQO+k/J0FoGiUCFobsScfz4lMpD0ONkq8fF oMd3UXneAtpcAdrcEvF7odMVrE6nQ6dXkOOudDcQcze6GSTcTe4Oirg73X1Uwt3vHqB496B7jEq6 x6H951ntL221P91qf7rV/nSr/enQ/isoWV4pr6SIvEpeRa68GuPBw3hojJQmsglSrpPXkZTXy+vJ l//GOCmLcXIDyt6I0RKyoyViVkAokLdhzMRhzNxJpeVdsgXFy7vl3XSevAejqJAdRYXsKHIwih5F qcfkk8jzlGyLlKfl08RkO/kMWmkv26PmZzHSIhhpz6NUJ9kJ6Z1lZ+TvgrEX2LHnmPUU5Okle6Pd PrIvrvaX/ZEyQA5AqYFyIPIMlkOQMlQORU+GyWFIwfiksBmfqGekHIlSo+QopI+VY1HPODkOOSfI CUj5QE5E2UlyEu7Dh/JT3JnP5Bfo51Q5FfdkmpyGXn0nZ6G338s5qPM3Cc2UCyV0Ui6Wy1DbH3IV lZKr5Trck/VyE9raLLdQGblVbsOd3C53UDm5U+5Ei7vkHvR5n9yHnPvlflw9IA8g/aA8iJ4ckodR /xF5BDUflUdR8zF5jJLkcXkcrZ+QJ1BWS23+v6rvUbpBE0igCSTQBBJoAgk0gQSaQAJNIIEmkEAT coAmPSF7+b2IGUwh12AKOQZTSAFTOkF2DnelBIMsxIEsi0hFFkeWUBBZGtlDCQZliBuUoVSgzDpK UuvVekpWG9QGCtRGtZGKqAyVgaub1CZKUZvVZiqutqjtiO9QO5B/p9qJPLvULuTZq/Yivk/tpzR1 QB1AnoPqEPIcUUdw9ag6RhF1QmlKCYxpnWTwC9INXEgvEJQIFPOpaBAKwlQ4iAQR5FRBQMWBa0lI SQ6KUJpBNyoCdEuDLBYUR54SQUlKDkoFpVBP6aAM4mWDsshfLiiHOLAP6cA+pLwZjEQro4LRKDUm GIOaxwbjUOf44B0qbNCQuEFDSjBoSAlArI9iaDgAH27R0AMaDkN8OHCQWxwUQMEPEJ9In0N+QdA2 oOHXiH8LDOQ0CzjIgYMLgZiLgK/crt/7Fge5xcHCFgeLWBwMWxwsanEwxeJgqsXBNIuDyol34ilw mjvNIR9z2kA+4bSFbOe0g+zj9KEAKHkjMYuSIaDkA5AGJSMWJUMWJeMsJiazbWwbFbI4mGhxMIkd Z8cp3iJgAne5S4nAPh/xMA9TId6cN6fi/E77JJvBvnSLfSX53fxupN9jn24zOJhucbAkv4/fT8Wy cDCDOBBwH/nAvmMUtqiXZlGviFm1xfhsJBth9F4uLyduMc6X1wDjXGBcE8QNunGLbsKiW4psKpsi xaAblzfLmyFvkc2Q02Cca9GtiEW3sEW3NKBbS1LyPnkf5P3yfuR/UD4I2Vq2hjRI51ukC8eQrp1s h5RngHTCYpwvn5PPoWxH2RH5M5GuK+JRjOsueyBukM63SMct0oVlP9kPpV6RryLFoJ5vUU/FUG+Q HIR0g32+xb40i3rcop4r3wTq8RjqjZajER8jxwDR3pJvIb/BQW5xMC0bDnKLgz5wcCriUez7Un6D +HdyHqTBPh/Ytwxxg3qFLeoVsagXtqhX1KJeikW9VIt6aRb1lNwr96KUwb4iFvtSLPalxbDvGDCO W4xTvuM7xKNoFe4Qfo5C4efDz0N2DnemSLgrsCkS7hbuhpSXwi9RyOIUiwyKvEHMIk6y2g6sSVC7 1R5KtPiSYJElGchyEPFD6jDFA1NOYJwbTCkU8IBTPNBEUpzFkUSLI8lAkETEDYIkBUWDoshjsCM5 SA/SkV4yhh2lUYPBjkSLHQkWOwpZ7EgEdryJOkcFo1BqbDAW+ccBNRItajBiNXaZlde6G6+oQ43p 9pPx/P8/gt6kN5sjdrY6L7vLrPPYtb6C1r3erHBZy/tre/5HZptWzotZn9uM/Wlt0WV6rc7IuaKT f7uZK3T6yYL38NwG3QSWp/l7Uts7V4lNsLRnn/m6TFY92/56pndbGUuHrbgPd3at3oEja2UvmyWa nK30MuRaQmbdoyhisRXGTOv6bwrhrN5kb1fRHTZta16rC3pL7rU5vUev0UtxJdcuxJmGzFXynGdm /MS0Ott6AfrOs+LbTvYr61W5VzXPVch7ByffUuP0GPv3mF0N/8EcZn1Iv4fYnFieTM0yI3i//jUz vUDtrLc6uvbPc7MKpldky/GKXQ8ya+WrbGw9epMdoWL393R/X7tqvTb/fAUP0LRs9eoD+hiOI2at Sx/Pke9U+1L/x8LfPOZPI+gRZ1H4hjzqW0sVoYMlzqLWU4eKZLHV4KnF1DwDsOG09xDPfq74S305 epV97J1m+Y/1dP1hbH8gWY/S023qOjO7Z5+9z4g/LAE2rrb8IcNyE4tmZk7Sq/F3QizXDrvf9iOO Wfhk5Fy5tkiWSplrszMxF8zRv+EYgdTGeoH+yab/HmURdkf7joL3NFfPN+c4s3Oo/ihbyiN6rG6j e5tVft02K7Ue0j434y73riOZPdfce6Fb9Nf4LsvO3UjN1AczjwHBMnnhHIrtz2bvA3A5a2/E7LHk U/Mv56qPZxpwlwL7d6DZb851tZ2emSNv9O8KzG7rjIacQXsLjdZbvmXvk4lhflsdu2uQ+mE91/7e B4nnMYcFVC1XnTswDrbHdpc4kCNz1+lg9OrZz29/7kPn3K/MZCmGe9l5ez0+O3Jxz1WWe+Yx2jGa zzF25RX+gmcLcl0/9teUWPpTeadTQfbRCxx0qwIWiD5j0Uu/ZP/utAjwiTkQe1dPjsbstUx+Zvc7 8Ut9cQa9+1h/DsT8LHY2U79P5vmgKSaOA8gJFJsJlMhkwTuBvj/FcCK6fxaXq87Z+jM9I1ZnsjmL pedAB60L3ltbDqNUL806y7Rd1phYpl0ZZeIW0eYY/Yg+IxIbP3ssIrfQN9izGWR2857E8SxiA/Qw zHXPxmrJ9mwL7sA03fEMenuv7qzf0m0Q+xaj+i3d2uLDK5iN3sJ9nqFH6Icwt+40e4D2m03VE/Xo aMuxWSNNf/uXOjP0IliV0ZFbOysW4536cPQ4fcaco+59drxnPRWUc5ay83SW5WuZ72r73EP2Jy6q 5nxi5e8KOXdx7RNM2/Pvif1GuZ6/+jtCTkvW3FXo8N788NP+OufM0i1IyM4/MBqMlbUYf0+y052V c8vZ91e/qTvpF/VQG/8V+j7GPCkTm4eifHG//hTH9LNrx9ZULfoky1nVsU5vxExo50f8phuhh1mc O/qr613gHLvyYoAFbusMOHe20j9Ff1X0xeDgL7GzVbHxE+v1PzOe8wq6lX5Qf6knE7NnnXV7oHXL KCPQU/QhnPXTT+mLdVngaC39rH74LNqK8sdSZ9XfGCZFbdqs5w3H5Lx6LoMedw7qMNq7KIrq4Le5 fn17fa2e/+cs/M8G9OYPjDm75gkdNpZilqUSZbq4OhvHSZ5V/bsD+vtq9pELfjX1n+zPyQNGWzvD naJPuuqnwY5+x+iLXpth5R/6C32n7o1Yf708mnaGbc0++/4WsMV92Z/z+r8bsjjunrN/ujKvZ93P ZYiyQ/DvDZj1zsGKRX7PKJ+y7GlqlJ5k1/a3nnlL2ULqOanltAK40FkzVz3wXPQknzZiSAd2e9br 8ufoV8qvlXVgtv/jkXLuAljPvnN2ZxLPoh/nYrz/jfsRZ6KN4D1royVjb3ZkrovMtfsMc09Z+PFY 3g8L3u7fHc7kHYhcdZx0N+QUZexqvVkpilrC0RWdrL3g8KnsY7u2m0ptSBS8XVv+DN7y0hl27vjz XbLMNbnTte0idE3BW/1HQ5EzLVjwnScyTzWYfeksy15Ps3I78Dnf3Yj/awG8f//J35nIlu/Q/74v pxdODyHPdFbP812pfNuyTxD8+e6g3bHI0qxwnoUy85q1quJ0J8bcPxBycvcoasB6ygdn7U7MP7De p3efw7rWUGxFOc83jirZt5zMDvqveVzNr27zHtWazJKZMbvCvyaWktlmPdvWX/qV7aznn3Vm9sW8 r5WrV+atrOpml+ZMrHY9Qr+tp2a9BxaLGUYQW9P8Nasf1XP19+2Ct5ej/Bk8KaTn212JH7PO7TNA 4JvitHf6TuPtvZO0nee7yfmU2WhXrcxMbrHAns3E2IsiQ/hU/NLOKPF06em9r5lH+TN5/mGBed/S Hgei51bGVs1PjQ6x71I85/NG0K/d+jd7jKCi4KSbY7tJq6Nj2uraIwXvaT7fI7rDls1a1y31s/od PdL6Dch6pkc30R8XsOaZfw9jNn08eTv6RF67ytEdxb+k7c5/F+dMg31GJobMeg/4xB7woyV62Z9I pLchzewZX6RvteefQAMW6RZ6ljnXM/Rr+nuzYm6vDc5R94rM9AL1qKluo7vpxrEzG4MGtrbxt/VY 3RZ6MAJsbSpmXpNjsv5Mfxqbtc3qfBGqZvecO+jHbFr0ecSR4NVvmt/DeEnIegoox1qQPpz5Nn+B +vuGfg+22n9iZ3Nt2yMszs+198Dsvn6o9+lvbIboW/uxJwxiWly74K3+U+F/8jZ27lbWZCJWdN/5 nwpnsk+FX3o7ZVt1yPKQcDpzTxKZ53dutvHiVAu2ZylbdgNYxwY7mxSjmnohRqj5rNAr9cUYL61J 6ei8HrNTMTqjNlXR2PnHsZ0KRllvTNv0D07xPeyzFboj5rnYCqRupO/B0US3oiQdnYMzfWh0xnGV rqeb6dibDfoHvdw+LWFG7BbMSWti9mtlqmhnzso216lXN/Lu1xg9FvK9rPOpxpbL8WTFLbHInXQT XUQ1rJ+Y8+yV7N89fGK+jpw4aGfKL/Wj+hMzh+kuuoeJodY+OZqNPgP26Bn09zH9BL7/E/bER+wx i5s97Ez9G37LjBPRN+mnWK8gmcHeWf10rI7TsPHybHtz/nlyldlmnwgwPMFqk9XmmTh37WV1Sr5j SsVTffSe0YJ8/Ng1j/mx607XOswpTA9Y73QdrHe6XtY7XR+nudOCBjgPOw/Ta9Yv3evOM04fGub0 c4bSROOdjqYa73Q0zXinoy+Ndzr6yvnG+ZVmsGqsOs1ltVgdmme809ECdhm7jH433uloIbuWNaHF rC17mpaxDuw5Ws4GsMG0ko1j42gte4dNpHVsMptCW9kX7Avazr5k02kHm8lm0W42h82hvewXNpf2 sXnsNzrAFrAFdIgtYovoMFc8oCM8gSfSMeNhjrT1MEfWw5zHy/FyjrQe5nzrVS7C6/A6TmC9ysVZ r3IJ1qtcovUnl8Sb8zudZH43v8cpYt6Vc1KM1zcnzXh9c6q6U9zpTnPj9c25z3h6cx40nt6cVl6C V8hp7SV7qc7Dxt+b84S33FvjtDf+3pxOxt+b09n4e3O6GH9vzgvG35vzsrffO+r0ND7enFeNjzdn qPHx5owyPt6c0cbHmzPO+HhzJhgfb8504+PNmWF8vDnzRAvxsrPYeHdjjvHuxlzj3Y15xrsbk8a7 G/PFaDGWxRm/bizR+HVjScavGytu/LqxssavG6sg5oglrJLx6MYuNh7d2CUiQ2xl9Y1HN9bIeHRj 1xuPbuwG49GNPWI8urHnzPtxrIvPfMa6+sKX7AU/4kdYdz/eT2A9/GQ/mb3kp/ip7GU/3U9nvfzS fhnW23hcY32NxzXWz3hcY/396n51NtD4XWODjN81Ntj4XWOv+w39Rmyo8bvG3jB+19gI43eNvWn8 rrFRxu8ae8tv5bdmY43fNTbeb+e3Y+8a72vsPeN9jb1vvK+xCX5vvzeb6Pfz+7FJfn9/APvQeF9j Hxvva+wT432NfWG8r7Fp/if+dPal/7W/gP3gL/IXs+X+Uv8PttJf4WewNf5mfy/bZryysYPGKxs7 5OuQww4br2zsmPHKxo4br2zcCaWGSvDA+GPjSaEyoYo8OVQ5VJUXC9UI1eAlQ7VDtXmpUN1QPV46 1CB0OS8fujJ0Ja8Sujr0L35BqHGoCa8Wuj7UlNcI3Ra6ndcOPR5qy+uGS4XL8frGuxtvZLy78WuN tzbe2Hhr408ab238OeOtjXcz3tp478gtkfv5BPPWHp9mvLXx75RU8fxn46eNL1R3qof4LuOnjZ8w ftpc1/hpc6Xx0+aGjZ82N2L8tLmFjZ82t7jx0+amGz9tbinjp82trMapCW4V46fNrWX8tLmXGD9t 7mXGT5vb0PhpcxsZP23utcZPm3uD8dPm3mj8tLm3qDVqrdvceFlz7zJe1twWxsuae5/xsuY+ZLys uY8aL2tumzgW57uPx6m4OPeZuMS4ZLeD8azmPh93MO6g2yWe4h23KzFnLVAvDhZfPCWQQ4Xw4ZSI edilFMzdHmb185BeHh9JFTAL+lQFKBkCHtYjBTw0/+fhUvsfMAxixlnEjAdi3opSt+FTCLjZAjXe TfdTQ3oAGNoIGNoWzOFpfC6ndtSBCtNz+BShjtQFLXcFwqYAYRWlOoETR2n2DeFiTgIw9wJgbgWk VHQqUjWnknM+0is7lRGvAixOtVhcHVjcFPIGIPJV1l9oqtMCuFzD4nINi8s1gcudkN7Z6Um1nF5O L9TZG0hdDEjdn+o4A5zXqa4zBKhd3aJ2dYva1S1qVwNqv4f4+8DuasDuWZgPvne+p3rObOcnqu/8 DDRvYNGcAc1rQdYGpguL6QkW05nF9ASL6ckW06+wmH6hxfSLLKYXB6a/RyXZ++x9SmcT2H+pNJsI lC9jUb6MRflSQPkvIb8C1pewWF/OYn06sP4XyLlA/FJA/HmQvwH3S1jcL2FxvyxwX9F5PAD6l7fo X9GifwWgfwqdz1N5KlXmaTyNrjQzAeKYCagSZoIKkBV5JZTCfEBVzHyAUpfwSyDr8Xq42oA3gLyU X4o8mBsgMTcgxbxrfY191/pf9v3qa+z71f+y71RfjXmiK13qvuD2JAezxQCKdwe6Q+hid6g7jJLc N9yRdIk7yh1DRd233P9SqjvR/YzSMKNMoRrGmyjVMvMK1TfzCikzr0AmeAnUyCvkFaLqZnahGphd fifuLfQWUilvkbeI4r3F3mJyvSXeUvIw6yxHygpvBVJWeitJequ8VeR7q73VVNhb462hiJmTKDBz EnJu8jZRIW+zt5kSMTNtJcfb5m1Hizu8nZTk7fJ2UVEzV6HF/d5+SvEOeAeogXfQO4i+HfIOoT+H vcOIH/GOIH7UO0qXese946j5hGCUJLhw6VLhCY8czHCSMFkInwIREmGKFxERIS6UUJQiAhFQAxEn 4pAHs6D5r+4iCWWTRWGUTRGpyJ8milGiKC7SUXMJUYKMB9TSkGVEGdRQVpRF/nKiHPKfJyoifyVR iYqK88X5SK8sKpMrqogqFCcuEFVR/4XiQpStJqqhtuqiOvLUEDVQtqaoScrMuGirrqiL9IvEJchZ T9RDDfVFQ/JEI3EVcl4triYprhHXoM9NxY34XjeJZqi/hWiJ1u8V96GV+0Ur1NNaPEoNxWPiCWok nhTt0OIzoj1dLp4VQA/xnOhIRcTz4nn0tpPogu/SVbyAerqJbqihu+iOGnqIHhQRL4oX0cpL4iXk eVm8jFbAAKiYYQBUDQxgINUSg8Qgqml4AKWCBwzF1WFiGKWJNwRwQAwXw6m+GCFG4G6PFqMhx4i3 qIbxAYv84AqoYYKYAPmBgJaKiWIiyk4SH9JV4iPxEWr+WHyCq5PFZJSdIqYg/XMxFTmniS+Rc4b4 Gle/Ed9SHTCM75E+W8ymquAZc5D/R/EjUn4SPyHnz+JX5Jwn5qE/v4n5yLNALEAPfxcL0edFYhFd IBaLxVRXLBFLUBYcBaVWipWoeZVYhVIZIgO1bRJbkH+r2Ir8u8V+5DkgDuBuHBQH0bdD4hilGh5D NcFjAsTjZCGqJRNlEhWTybIo1ZEpsjjVlemyFFUHy6lA9WVFWYmulefLylRPVpFVkHKBvJAayGqy GmqoLqsjZw1ZA3lqypq4WkvCdgQ3uphqy0vkJWirnqyH/PVlfVxtIBugLeNTwDGciWoYzgQJzgQJ zgQJzgQJzgQJzgQJzgQJzkRphjNRMcOZIMGZ6ALDmRAHZ6L6hjNRqvFVS1X9Rn4jlAJzQgqYE/KA OUGCOVEdw5yoLpgTLAG/td+aGoA/PUHx/pP+U8gDFoWyYFFIB4tCzhf8F1BPN78b4t397kgHo0J/ wKiQv7/fn2r5A/wBKAVeRTXBq4YgZagPrfOH+cMRf8d/B229679L1xqmhRQwLQobpgUJpgUJpgUJ pgW52d9Nl/l7/D1oZa+/F/WAdVE1w7oQ1742/3srRHRVyAk5lGoYGBUDA5OQfsin2iEEqhYKh8KI q1AcZHwI828oIZRAdUKFQolISQolUf1QciiZaoYKhwpTg1CRUFGkp4ZSqVYoLZRGF4SKhYohXjxU HK2kh9JxtUSoBFLA7RAHt0NPwO0gwe0gwe0gwe0gwe0gwe0gwe0gwe0gwe0gwe0gwe0obLgdXQZu dzMlhG8J30Ii3CzcDPFbw7ciflv4NsRvDzenZMP8kNIzPI5YeHz4A8TB/xAH/0Me8D/kORxxiEVY JI2uMCyQLor6bjAskJhhgZBggZB3qjspXd2l7qJSqoVqQYXU3epuKqnuUfdQWdVStaQy6l51L3F1 n3oQ8VaqFfK3Vq2R5yH1EPI8qh5F/DHVhsqpx9XjyPOEehJ52qq2uPq0akclwCyfRXoH1QHp4JeQ nVQnyM6qCxVXXdULVFp1U92Rs4fqgZwvqpfQYi/VFyn91KuoGRwUrQxSgyAHq9eQZ4gaij4PU8NQ zxvqP4gPV8ORf4Qagfib6k3UOVKNxNVRahRVUKPVaKpkmCtVBHMdR5XVeDWerlRvq/cQf1+9jzwT 1ARcnaQmQX6oPqIq6mP1Ma5+oj7F1SnqczpffaGmImWamoYU8F1I8F3Ib9S3dJ76Ts1Enlnqeyqv ZqvZyPmD+gGt/Kx+Rco8NR91gg2j/kVqEeRitQR5lqk/cHW5Wo56VqiViK9Sq6gWWPIa1LZWraUK hitTCXDl7lQ86BG8SGWClwLcJfDmXlQl6B3gXgX9gn5UMngleAUpA4NBVDkYHAymKw2fRgr4NFUx fJqSDZ8mZvg0JPg0JPg0JRs+TTXA7BpaPn215dPMMukob85kzIYfx1l+HEd34BNnmfG/LDNubJlx omXG11lmXMQy46KWGadYZpyazX+PZ/33+NZ/j2f993jWf0/Y+u/xrP8ez/rvCaz/Hs/67/Gs/x7P +u+Jt/57POu/J9767/Gs/55rrf+eJtZ/T5L133O99d/zb+u/p6n133OD9d+TBqYeAW8OnMBy9FSq 7aQ5aeDQhqlfBKbelC6xXPxmp5lzB9INF6/ntHJagWE/4zwD2d7pCN7cCYy8Lhh5L2oALt4b8b5O X+Q3jLwuGPlQagguPoIagYV/CvmZ8xld7kx2ZuCqYeG3WRZ+hWXhV1oWfhVYeDXiloXzbPybg39f Yfn3teDfTSwLNx6GXOthqJD1MFTIehgqbD0MFbIc/UbL0S9mvVkfutR49qdbYkzd8PLKbBKbRJXY 5+DlZS0jP88y8grsJ/YT+Lfh4qXZfDYf6QvBv0tbr0XpbClbAUa+iq2CNB6Mqlivbuez9WwDUjJY BqTx7VbCejYqx7azHYgb/0bl2W62B3Hj5agiO8qOIW58HZVkJ5imEtbjURnucIa48XtUnnvcQ9x4 PypjvR+V4xEeQUo82H9Vy/trWN5fy/L+m3gxXhzphv1X5WXB/i/k5cH+q1r2X42fz89HvAqvAlmd 16SasATqIn4Rv4gu4BfDHqhq7YHqvD7sgar8Mn4Z6jf2QFVrCTSzlsCt1hJoZi2BW60NcDXY/xCK A+8fSYmW8adYxl/MMv6L3Mlg/PXA+GdSA3eW+zNdbnn/ldl8MnnWJ1O89cmUZH0y3WAtgcbWEmhk /TM1sfbAJbAHFpCwNoD0lsIGENYGkNYGiLPsX1r2n+Kt99aD5W/0MpBieL+wjL+oZfyNLeNPtIw/ xTL+VG+ftw/ScPqrLaeX/4+1r4GK47rSfNU0RRm1EEIYY4QxxhhjTAiRMWEIIhhjTDDGBBNZQwjd NE1301XVdFf/0DRN9S8tohAGaxSFaBVFkbVaDZG1Go1Gq7CKQjSKRqNwCEdmtIxWYYmi1TA6OoRV CMPKGrz33W5hZGcSzzl76nxfPb366fq59e73caquUNMnoaavRk2vYFnQ9HGo5uNQzT+Jqr0a9Xoc KvUkVOpPojqvRl0eh7o8FXV5NWhx8L1sAShyFrV4Emrx6qgKL2KLYP1ithjWp1q8GlV4RHPHoc6O Q21dg9q6FrV1EmrrOtTWKaitn0BtnYra+klUz0+yg+wgaMpvs98GNUnVcykq5jJ2H7sP+qlifhkV 8yvsQfYg6EiqlYvZw6CVy1Arb0WtvJ09yo6Cjv8RqOStqJLfRn28nT3NnoatqEouRpX8Nqjks7Dt j0Erb0WtXIJaeTv7d+xF2MPP2Z/D+lQrF6NK3ooquQRV8nZUyVXsVVDJZaiSX0GVXIwqeTuq5ApU ya+hSn6Z/RX7K1hK9XFEGb/M3mUXoYfq4xLUx6Woj99mV9lVUKhUGZehMt4OyvgJaFNNXIGa+JW4 Z+KeI5WojKtQGb+DyvhV1MGvoA5+B3VwFergrXFfjPsiMFXAr6ECror7ctyXYZ+0otgmrCUWi7XE NmEVsU1YRSwWq4jFYxWxeqwiFotVxGLjGuMa4ddpLbFYrCW2CauIvYFVxLZgFbEGrCKWhlXE0rCK WCxWEYvFKmKxWEVsE1YR27KuitgmrCIWj1XENmEVsTSsIhaLVcQ2YRWx2HVVxGKxitgmrCIWi1XE tmAVsTSsIhaLVcQ2YRWxtHVVxGKxitgmrCLWgFXEYrF+WOy6+mGxWD9sI9YP24T1w2KxfljDuvph sVg/bBPWD4vF+mGbsH5YLNYPi8X6YZuwflgs1g/7CtYPewPrh23B+mFvYv2weqwf9hbWD2vA+mFp WD8sFuuHvYH1w+qxfljDuvphsVg/LA3rh8WCh9lCSsGxPEdeQX9SyT3PPQ/eIJfLBa3/IvciKeHy uc+B3yjgCqC/kCuM+pZibhv3EnkN3UsxV8yVAFMPU8V9ifsS7Id6mEqumnsduIZ7A/ZWx70J69Rz 9eRl7i1wMtu5Bq4RHMI73DuwlPqZCk7NqeF4tJwWtopUYqQOpwocjgl+izqcBM7KSbAfG2eDrRyc g7zKdXPd0NPHeeEsqM8pRW+zFSs3FqPDKeOGuCFg6nNeQ59Txn2Hg1ECfU4xOpzt3A+4H0DPe9x7 8OvU7VSh23mH+ytuFLainmc79z73PqzzX7mTwH8DzmcDN8v9Bvh/g+fZgJ7ndfQ8ldwStwR7pp6n lPuQ+xDOjnqeDeh53kbP8wp6njJ0O8XodkrR7RQ/thEcThk4nM2kAh1OFTqcV9HhvAYOJwVc0BOP pcKaT4LDKUFvsxX9TCX4mefhV/LAz2wAP1MEXPxYKfB28DAb0MNsAA/zFjB1LxvQvWxA9/I6uJem qGOhXmUn+JBmdCwt8S3Q0x7fTsrjTfEmYCFeADbHm4Et8RZge7wdmNai24y16DZjLbrHsRbd41iL bjPWotuMzicGvc1XN2zdkEX+bEPthq+S8g26DW7ShJXqlOh2lOBwXgQXQT3Mi+hhXlB1gId5RtWp MoFSp77lGXQsL4Jj6YK2RWUF5+BUOaGHepVnVb2qXujpU3nBpVB/8hz6kxfRn7wA/mQ39HwLXMoL 6FKeV/2F6i9gfepPXlR9R7UPln4X/Mnz4E++B3uj/uQ59CcRZ/IsOpMC1Q9VPwR+T/UeMHUmRehM GlV/Bc7kC+BMjkP/+6oTpBCdyRfQmbyEzqQInMnfQM9p1d+Sz6nOqM7Amj9W/Rj6qT/5vOoc+JMC 1XnVeVh6EZxJIXqSIvQkjaorql/A0gnVJPRTZ/KS6gPVB7Am9SRFqn9SXYf+/wme5CXwJL+Cvc2C M8lAZ1KomlPNwe9Sf7IN/cnnVb9RgcbD6oD5WI80T3VHdRd6aKXALNWCahHatF5gDtYLzMJ6gflY LzAL6wU+jfVIM1T/pvo3YFo7MF/1kQoUIFYQzAZhDgoQ6wg+jbVJM7Ca4FNYmzQDawrmYE3BfKxN mrcxYeMm6Kf1BXM2btm4BXpolcFcrDL49MbUjWmwlNYazMdagzlYazAXaw1mb8zamAVLacXBHKw4 mIUVB7M3mjaayDPoxJ4DJ+ZHJwbxsHHXxl3g0AbAfT2H7usl9F2N4Lu+A+19G0dIIbqvlzbu37gf 2rRyYQ5WLnwKKxfmY+XCXKxcmIOVC5WE2Xov3QfiVxWzm/wvQjTNAA1ADxAAEsC1NmcsozCXASHA bsAwYB/gAOAw4BjgBOA0YAwwDrgEmABcBcwAZonCdwVBNLcQCt8U4Bq07wAWAcuAB4S0KQAcIAGQ DEgDZEaOoS3n35nnR/bVti0Kuk0JoByXkbYqQG3keHGbw5FzbGsA7AC0RPqjc4XvBoKxnAScgfbN tb4I5gEL0fY1wFK0fT8CP4mCBagASYBUQEZkXX82rk/atABj5Dq1mdeueWTdPFyPtNkBboAPEI6e w2Dk9/yF0XPdAxgBHIwuPxJdXhxFGfTBfWyj53MOcGHtXCLnfAZwDnABcBkwCZgGXAfMAW5H53fX zR+ufw+wEp1fj263sm75KiFaJSAekAhIAaR/PKf3T5sFyP3Mc4W/8uN7Rc9NWxC91/9RpD0KjO/d kd/BuEqLrIe/ux5FgNKP52v7iOxX4a+B/gpAdTT+YJm27uO5thGwU7m5dU6s7ZvShLoIMousAt7d lQQ83JUKvK8rA/hAVzbw4a68vim6lbdFc6yr0KttvS029F1rvSvu6LuhOdFVjFy21j7dVdl3gy71 GlvviS19NzVjXTV9NyPtKK+I2r55zXhXPXIT8CVsX8L2RFcz8NUuDfBMlx54tkvom6dbec3ARmiv iua+Bc2tLgn4TpcLeLFL7lug/V67Wina+5Y0y10h4Addu71udbzo7rvfpugaRt6HfACYa6sCTug6 DJzcdQw4resEcGbX6b77dCuvry2na0w+oE4UfTJc2a5xmahTxLDMUvaG1enioKxq29Z1Cbika0JW 0R7vYKQ/ylniHjlJnSuOyKlt5V1X17iqa0ZOpf3ePVEuEA/KGW21XbPIt4AbsL2j6w5wS9cisLZr GdjY9WCNzRaFd6TNbuG8B9VF4hE5u81tSZCzcW950R6fJfkh0x7vEXWpOCoXtoUtaciZD9u03zuq rhBPysVtg5YcuZi2vSfVFZZ8aFeLZ+Sytj2Wbcgla+0RSznwQUsV8BFLLfCopQH4pGUHtlvkMrqt 94y6TjwnV6obxQtyTdsZi3aNz1m03nNtFyxGuUa9U7ws16tbxUk8BjOyfa192eKGI9GJ03JT26TF t8bTlrDcpDaJ1+XmzvEeH3IYeRD4Us8e4ImeEeCrPQeBZ3qOAM/2jMrNdKt+d+etnpP9PrVFnJM1 aqd4W9Z33uk5A7zYcw6Ztpd7Lsh6urQ/rPaId2W280HPZZk1KcS7/YMRVgfEe7Jg4nomkaeBE7Cd gO3knuvAaT1zwJk9t4Fzeu7KAt2qfw/wCrQHxFVZMuX33APe1rMCXNIDPbS/f0Q9ZFbKLlO5m3KV O77/oHqvOV6WTbXuRMqmMLZTgBvc6cA73FnALe5cYK27ANjoLpJlulX/EZPZXdo/qt6vvimHTHZ3 hRxSHzInyrsp+7PVR80p8rDJ7a4G9rnr5GHa038y0h/l4+Z0eZ/6lDlLPmAKuxvXeNC9E54d6O8/ E+Wz5lz5sGmPuxVZt9YecZuAD7otwEfcTuBRtwf4pDsAfMY90H/OdM495NWqz5sL5GOmC+69/Rdw byeiPZfd+4EnKdOe/svqi+Yi+bRp2n0I+ejDNu3vn1RfMZfKY6br7uPyGG33T5vm3Kf6r6unzBXy uOk2XHlg99m19l33eeB77ovAK+4rwKvuKXmcV7qvAce7b8jjdNv+OfU1c7V8SX3DXCdP8Inum5/g FPe8PKG+aW6Ur6rnzTvlGT7dvYC8tNbOct+XZ9QL5lZ5ls/tJWtc0MvKs+ols06+1XbdMoi8B3gO 27ctI8B3LQeB71mOAK9YRoFXLSflW3Qr7wWt0nLGe1l932yS72iI2SIvauMt54ATkVOQ0y0X5EW6 1DupYc1OeVnDWi5Tpm1tlmXSm6BRmT3yA22uZRr5+ifaBZY54CLLbeBSy13gCss9+QHdyjutSTIH vApNqnnAy2mrLSvAdZZV4EarEninNd7LaTLMQ94EbSuyzprova7JNu/1JmtN1hTkdOQsb7Im25oL bYu1ANhpLQL2WEtpP6w/pw1YK6BnwFrtva3JM+/3pmmHrHXAe62N3jRNofmQfJWy9652v3Wn956m 2HwU1j9kbYU9FFt1lKFnLtIf5TLzcW+mptJ8Co7tqNUEfBz5lNUCV4b2r2jPWp2QPbGtqTGf9eZo z1s9yIE1vmgdAL5iHQKesu4FvmbdD3zDegj4pvWod1U7bz3uU8J+znvzNRnWU8CV5ovA9eYrcJwL 1rPAS5SxZ07TZJ7ybtPet55/lGm/D2yr9aI3p521XvElaprN17wl7SrrlLeEtn0pmmYr9Gg05ht4 XhG++bDdnmSdB061LgBnWJeAs633gfMkAlwosXDudNsVjd5801uuEczz3qr2Ykn1CS6TkrxVGsm8 4K3VuMxL3ob2SsseylLqGtdIGd4GjWy+793RXi9lAzchN0t5wBqp0JdONYkvq10vFYM+AW3gy20X pLK++XZJqgR2STWRDO4roHnQV9QuS/VyRntIapIzaCbylbbvlpppVpI0wJBrfBXtw5JeLm7fJwmQ X+B58VW3H5Ak+RaNW19d+2HJJT9oPybJwCekUCTGfI30/vp2tp+WdntzNDXSMDBcB19r+5i0j14T 6QBw5EzHpcPAl6Rj3gbMOLf5ol4VZB868t/lS3uTZIGv6E0Fru7NiI7P9+go17/C1/Vmy4fVZ3vz gOk4s8o39hbSMae3GBhGkrCS39lbBqNHa2+lPIORP9c+IZ3w6dqvSqd9pvYZacxnaZ+Vxn3O9lvS pb4b7Xekib6b7YvSVZ8H1pmBdZalWV+g/YF0yzegU0h3fEM6Tlr07dUlSMt9C+o66YFcqUu2KXz7 dWk2zndIvdOWINfrMm3JvqPqXFua77i6wJYpZ+hybDney7p8W77vlG6bbZvvbERv6EpsJb7zunJb ed8UVRS+i7oqW5Xviq7WVkvvgq3hYWbXNdh2ILcA74Bjm9K12LS+azqtzei7oTPazL6bOrPN7pvX 2W1u34LObfP5liKatk1hC4OKi+goVCk6n20QtCvqRl3Ytgd40DYCKo7Gxv02rQ1Yt8d2xE90I7ZR P6s7aDvpV+mO0DXVStuZviXdqO2cPymi3DQHbBf6pnQnbZfhGUeNqjtjm+ybb0uzTffd152zXYdf N9rm4DpcsN0Gvmy7K2frJm33QION2lbgeKZtq8DX7UrfkGbZHg/7n7Mn+lN1t+0pvil6BfwZurv2 9Ehs+7N19+xZsJ8Ve65crFu1F/jzOpT2In9hRGF2xNtL/cUdifYKfxl9LvyVHSn2alDpoNX9NRHu SLfXRRS4v34dNyE3469okPUdWfbGvvmOXPvOvoWOAntr3xJV1H6ho8iui7YlZBd9vvxy9EqCHvaH kHfTo/IPd5TaTf7hSBt5X0eF3SIndVTbnaCHQRX7D3TU2T0RDew/vI6PgVK1y9kdjfYA8E7KVLX6 T0S4o9U+EFGq/tMdOvuQXNhhsu8Fhn7osdj3R1Srr+Jj9o/Rp94/jnwpwh1O+yHQoqBI/RMdHvtR UJ6gS/1XOwL243J9x4D9FLDFfhY056T9PGhLel9mItwxZL/on9Vm2a/A001H5oSOvfYpyJ5Z9mvQ 3m+/4b+lybDfpBnBPu+/03HIvuC913HUvuRf7Dhuv+9f7jjlIP4HHWcdbEARHdtx9NY0O1QBruO8 IwlGY5cjNZAQGQk7LjoyAskdVxzZgbSOKWt1ILPjmiMvkBPRAFqToxByAWaZjht03I7k6I6bjuJA fse8oyywrWOBZtuOJUclZD0YtQIl2ilHTaCk475lOlCu3euo96bpiaMpkBbNy0cdzd4EPevQUC3h 0Mu39CqHQHO6Q5If6JMcLm+yPtUhw+/ecIRo/nLAGKjPcAxDf7Zjnze5vdBx4GGm0Oc5Dgeq9IWO Y3BsoCX8SfpixwnfFD27QK2+zHE6MtJ6p/WVjjHYT41jHLIA5NxAg77efCqwg+apQIu+yXEpoNU3 OyYCRr3GcTVgptctYMf9uPV6x0zApxccs+BxYAwPhCNqh7KvNcIPVY3ZGRikHOkJ7EEeoccQOIh8 RC85bnkVepfjjpfTy1SNUGXia9WHHIuRNuQ7YNgKckFglI66gVH9bsdyRFcETkYZzsLXqB92PIB8 gW08r1H9PqfCm6k/4ORAUYCuCJzRH3YmRFQEHNUaB0a0R53J3nz9MWca8AlnZiTjw36AA+f0p505 kSwfuKAfc+Z7t+nHnduAoR96LjlLIlk+cHkdT9I8FZhGHkG+rp9wlkPuhgwemNNfdVZBpoY8Hrit n3HWemv1s84G4FvOHZDF6p0t3h14ze8i34temTtOrbdEv+g0eqv0y06zt0H/wGmXbxkUTndghdf1 1oTjeVNvfaiet/Q2ATt7m+Vh3tOrkfV8oFcvs/xArxBOhHUkWDrU6wqn8Ht7ZVi6vzcUTucP9e4O Z/FHe4fBDR3q3Sfv5o/3Hgjnqvf2HpZl/lTvsXABf7b3RLiIP997OlwKGXNMPsxf7B0PDvBXei+F K/ip3olwdcQdqK/0XpXH+Gu9M+E6/ob7VLiRv9k7G97Jz/feAh8333tnTYcv9C6GW/ml3mVo3+99 EDwlEI8irBNYDxc2CSpPQtgiJHmSw04h1ZMW9ggZnsxwIOJATbWeHPBcEaeDnkLI9uSHByIuT8iD Hkko9GwDzwW5PjxkOuIpCQ/xuZ7y8F6h2FMV3i+UeWrDJlM+XVM95GmQXUKlZ0f4UMRndY57Wh76 2YjHFGrQV9aablPH59Gu/fqoxwiMXkmo95jBMUU8zip4zHGhqXfRX2Yq99hh/80ed/iooPH4wGfB FQgfF/SecFSr7BEEz6B8WJA8e+QZweUZCZ8SZM/B8NmIHxRCniPh88Juz2j4ItU54SvCsOckeGpw 1uEp5GvCPs8ZyBrgoCFfAIdvUPaipw7fpL8Sno+wcMBzDs7oMHguSTjmuSC7qP8NLwgnPJej7SXk +1Qv7SLRKwnudRcbZTiqXSrhtGdylyrSRk4SxjzT8j5h3HMd3Ct42F2pwiXPXMSx7spYx9mmy57b cMUmPHeBr1KmHtO3M8LCjOdexFfuyhNmPSvyaeGWZxUY+qHnTp8y4jF3Fa7jYqridpUhV0ZYWOyL B+cI/nFXjbDclwg+EVzkrnrhQV+KfFVU9KUDc31Z8oyY0JcbbqX3ZVcTcrN6qK8gvCAm9xXJY2Ja X6k8IWb2VcCaOX3VcrOBc/oCq+gdMB/h2AWexZDgDAeVhmTnYDBewzr3+JMMac4RmjucB4OJhkzK 0D4STDHkOEeD6cAn1zjfeSaYZdjmPBfMNZTAVlzE0xnKnReCBYYq5+VgkaHWORksNTQ4p4MVhjQ6 fiKvGHY4r/sX6WgZrEau0wacc95kQ4vzdrDRoHXeDe7UFDvveecMRudKsNVgdq4GdcgmOk4GLVFv BRx0GuzdyqAn4rMM7u74YMDg604MDhjC3SnBIcNgd3pwr2FPdxbwSHducD8dM4OHkI8aDnYXBI8D F3kVhiPdpcFThtHuiuCpSE4xnOyuDp41nOmuC543nOtuDF40XOjeGbxiuNzd6i/DUZQzTHbrZL1h utsUnDJc77YErxnmup3BGxqh2+OtMtzuDnjLDXe7B+TTkQxFOXhTI0M2hHb3UMAdUW4did17g/OG e937gwsa0n0ouGRY6T4avG9Y7T4eWDXkd58KZhmV3WeDBcb47vMhYkzsvhhijSndV0IqY3r3lDxs zHKOhJLW782Y230tlGos6L4RyjAWdd8MZRtLu+dDecaK7oVQobG6eylUbKzrvh8qMza6SKjSuNPF hmqMrS5VqN6ocyUBm1ypoaQoW1wZ8i2j05UdajJ6XHnBgDHgKgw1GwdcxSGNcchVFtIb97oqQ4Jx v6smJBkPuepDLnp/Q7LxqMYVChmPu5pCu43pLhjzjadcmtBw5N4Zz7r0oX3G8y7BN2S86JJCB4xX XC7gKZccOmy8BpseM95w7Q4ka2pc4LCMN137gOddB0InjAuuw6HTxiXXMeD73aWhsU7iOuGf7WRd p2W2U+UaC413JrnGQ5c6U12XZKEzwzURmujMdl0NXe3Mc82EZjoLzVP+ss5i12ywtLPMdSs0C2ve gTUrXYuhW5Ff6axxLYfudNa7HvimOpt6FKFFDWvMlZc7m3u40LKmrCfBm9mp6UkOPejU96T1KzqF nsx+rlMyevo5TVMPZOdOV09+P2i5nm3eHZ1yT0l/cmeop7w/rXN3T1V/ZudwT21/jmFbT4N/kXJ/ fsT1d+7r2dG/rfNAT0t/CVUv/eVUpfRX0b+i9NdGnjj8C8Zg9C8Vjz4d56N/K8C/DPQ3dB7u0QZz aX7v30E9eH8LjcZ+beSvQzg+rHQec47A/lGJdZ7oMXqnDTk9Zu909K83+HeVztNmS7/RcK/H3m+O uP7OsR53v53ea18jUZAnmEXm/xDC/J5ZJgrmPvMhUTIfKRjCKmIVLHlMsUGhIhsUiYrNZKPicUUK 2aRIU2wlmxVZimfJFkWu4gXyuOL7iu+TJ2JqYr5CUmOrY18nabFSrI2kx/4s9mckIwEm8nRCZsKb JDOhIaGF1CeoE/rJ1xPeTfgpCSRcTrhL/jphIWGZXIOj+SpR4v9+kEA2kcfIZtJENpAdREveIjry LdJCvk2GSIgMkw9ImPwj+TW5Qn7DxJP/waiYjeQjZhPzOMMw9Bsnjr43yTzBNDMGJp3pZMJMHjPA 7GVqmBHm+8zXmL9lfsl8Peb9mPcZp9KudDDdSp8ywPQoB5TfYjzKd5XvMj7ld5XfY/zKHyjfY0LK E8qTzDeVZ5Q/ZgaVP1X+lBlW/lz598y7+D3mXuVV5QfMd5Wzyjnme8rbyn9hDih/q/wtc0j5e+W/ Mj+kb9ExR2K3xG5h/kvsB7GrzDE2ls1mptnn2eeZJfYFtoD5PftFtpT5kH7hwXzEvspWKZRsNfum gmXfYlsUCWwbq1Oks3pWUmSyDlZWfI79Jjuk+CI7zB5QbGd/wB5V1NIvJxSN7An2F4q32Ul2UmFl p9gZhcTeYG8oetk5dk7hYf+ZvaPoo+9jKfzs79glRZhdZlcVA3EkbqPi3bikuMcVP4h7Iu5ZxXtx OXEvK07GvRInKMbjbHF7FHfjvhP3nRhV3HfjDsRsjPtR3ImYLfT/VY15Iu6/xZ2NSY8bi/tZTAZ9 HygmJ+4f42ZiiuKux92OKYn7l7h/jXmNy+FOxTRxv3vsmZhfJ3yY8KGSfi8nkAFgFcmgXxtXnoyC A+STHEFbsyIYq2q+cq2qUDALdsFdMyf4hHCV0DAsnBHOCReqxoTLwqQwLVwX5oTbdfF1WcJgnVPY 81rta0ZhRDgoHBFGhZN1Wa9VQVQpIcYXMcZ/TxjmI+YjooCITiQxsOwpfBOVKH6k+BFhFO8r3odl JxV/TWIUP1H8hMTim6is4peKXxIOvwR7TPGBYprE4zuoKnz7dKPi14pfkwR873ST4reK38LTQd8s TYphYpi1/zU4NoYlKfjlWGpMSkwKeTImNSaVpOGboltjcmNyyVP4VVhGTFlMGcnEb8CeiamIeYVk 4Vcx2fjOxnNw/ComCa8cZcJfJB7+In+Fn+Kv8Tf4m/w8v8Av8fcFwi8JrKASkoRURIaQLeTxC0Kh UCyUCZVCjVAvNAnNgkbQC4IgCS5BFkLCbmFY2CccEA4jjgknhNPCmDAuXBImhKvCzPpJ3CHMCreE O8Li2rQsPBAVIrduShCTxTQxE3pzHplaxBxYN1/cJpYIDx5OYrlYJdYC06lB1AqLohHWNYta0S66 RZ8YFgdhnzniHnFEPCgegfNnHhOiowb9Zn0zXpNUmGJIOkxKkkOeJ7EkH6Y48nmYOFIK02OkDKZ4 Ug7TBlJFXsO3y9+AUYd+d7mJ/DlpJomkFaYkGHd0ZAsxwpRMbMSOX1y68VtLL75RHiRpMB69S7aS 78L0FPlPMGWQ/0yOkqfJj2B6hpyAKYv8GKZnyX+HKZv8BKbnyN+Ri3B8V2DKxf8N+wUyQ/6J5JFf wZRPfgPT58g/w1RA7pHfwbGvkP9LvkBWYXqJUTBxpIiJh7GvFN8f/xKMfYmkDN8fL2cymGfIl5ln mWfJq/i9ZxWMhg34RWczqWa+wWjI64yW0ZI38F3yOvy6801GYARSz3QxXeQtxsE4SQPTxwRII4yd YbITRs9vkj9nvsUMkq8zw8ww+QZ+3dkKI+lZombGmDHSzowzPyM65hLz90TP/APzD8TI/IKZIJ0Y vzyMArlE4PK4PNKFb+dZuC9w24gV38izcaVcKbFz5Vw5ceCXRE58/66b03BtpIdr59pJL9zb22QZ Y7+YVpYwnQaMAcYBlwATUVyNYgYwS94xjZnGTZdME6arphnTrOmW6Y5p0bQM/IBX8BxMCXwyn8Zn 8jl8Pr+NL+HL+Sq+lm/gd/AtvJY38mbezrt5Hx/mB/k9/Ah/kD8C0yh/kj/Dn+Mv8Jf5SX6av87P 8bf5u/w9foVfFQYEpRAvJAopQrqQJeQKBUKRUCpUwFQt1AmNwk6YWgWdYBIsglPwCAGYhoS9wn76 P4jGamM7IQl+I6EV6yu89v8tvt+EaRNGeSJG+WaM8i0Y5ckY5Y9jlKdglKdilKdhlG/FKE/HKM/A KH8aozwTozwLo/xZjPJsjPLnMMpzMMqfxyh/gUzAlIex/iLGej7GegHG+ucx1gsx1r+Asf4SxvrL EOsKUozx/UWM7z9jnmIyIO5pZJdhZG/HyC7H7yO+jNFcgdH8CkZzJUbzqxDNffAMeBkvPAP0K4nX MZprMJprmb9k/hKeBxrTdfh9xJsYzfUYzQ3MBMRxIzPJTJK3ua9xXyNNXDPXTL7GdXKd9HvtRF/i brhPKrj2GwhjbYW42wYoAZQDqqJ9tYAGwA5AC+1TbjYVWYv5q38cuM6MNG0qtZaZKqyV/OyjoH2m amsNfwtwR7pOYaqz1vOLfxx0HVOjtcm009rML38M+m9Tq1XDP7BqBIU0Z9JZ9QL3x4HrJEi3TSar ICRbBZPFKiGcVpeQBsiUzNjOke4K+dI9k8cqmwLWkLDtY+C/S6QV04B1t1D+J1AlrQq1NqVpyDqM 2GvdZ9pvPSA0REDb9NyEHR8Dz/WQ9bDQYj1M54ij1mOC9k+Drmc6bj1hOmU9LRgfhemsdezhftfD dN46Lpg/humi9dJngaXVud90xTphmrJe/YO4Zp2hsOichyhMN6yznwk3rbdM89Y7n8KCdZHCYrIN mZasy58FFovzqOm+9QEFTyQFgpU4CovTeZzOu8yOUV4jaXmVlMAnScmfhMXjPMWnSml/CpaA8yzu I0PKRGRLOXyelP8ICqVtn0KxVPIIyqTyz4xKqYqvkWo/hXqpgW+SdnwKzVLLI6Dn/Rkg2G3xvF4y 8oJk/oOAZYLblij4bCm4niTZPxNckpuXJd+nQPcXBgza0vmQFP4sEPbYsvjd0uAahqU9a6DLRwAH bbnYPmIrEEZtRfw+aQSP9xMQTtpKsX1AOvinIJyxVQjnbNWP7OOwdOQRHJNGPwW67QVbHX9COilc tjXifNK28w8dz7+L09IZfkw69ymMSxf4S9LlT2FCmlwPYdrW+nBsXz8WPxwr18a46zbd2hg0ZzOt H0fW4mT9fX14Xx5eo9s2y9q1vWtzrj8mHEsGYEyBZ98yFBkDLHsjzy8+V/ulNMwbEO+WQ4CjzvMP 49lyHObwO3S5cM/mEVZsAWHVNiAqbUM0v4jxtr20n56bmGjbL6bYDtHxVUy3HaXjpJhlOy7m2k7R HCAW2M7SsR3PGeJdLLKdfzg+i6W2i2KF7Qo9b7HaNkWvhVhnu0bHTrpPRKPthrjTdlNstc2LOtuC aLItiRbbfdFpJ/T6Yg6i1xKuoeiBPBnNZ2IA8k/0OosDsJ8hO0v3gcv22lXifnsSzTtruXbdPVrb J0U0pzzMBfSYaG4UD9lT8diO2jMe3mdcn479cO8xL0POw3M7bs+mfeIpyOGlEdB8Ta/vI6iL5GWa rzAfw+88zMV0joD4wXP7RI7F3wKIZ60yBc2xD/PqQ4jnrcMUazmS5sxoblyfKx/JkdE8+RDiRciD cI8x90E+FK9YxygwbmmeOx/B2pgFEKfseTi/Zi8Ub9iLsR/GD/GmvUyct1eKC/Yacclej/30Gaa5 hD638BzR50m8b28yE3szHYvMrF2Dz8X/Y+9roKOqrrbvzNwZIj8j0pSfGGhMEWMICAFpRAqUxpDM H0gBeWkKMXPvnR9xMuDMgJRGoJGmlFLgU0oRIx+lGFOgSIFCDIi8/DVvGoEiIMW8+ZAihTRS4A2U D8K393POhBji0q73+9b61mrXWfu5m3332fecffbZ5ycxxueBzIuILbLDeS7UmXKTnCMYL8pbXD+e A++ZW23mVUt+ibefbHDeDHWLGDzmoZ6RGS31WZ/mW6hPZFaob2QOtzuUHikODYqUIIdzf6gPoWGR xaERkWWo90X5R7YrNEbm8fgcX9RKR7YZfW2Tj1v6w3k4Tp/3rc/Jp6Fc+fTM2sJ9aqG2ebJ1ruT8 GM+RrXMi6cIO6/A78kFo4guu8NbY/vDOWDUT7214vLGv2RM7AhnlrNCxqD28P3Yivn8JV8fOhEoi e5HHaN8RPhI7iz0F5bTQ5sjFUHGkMr4nCJ+IXUBO4/Wf9w2c687EGnmNDp+NXQtfiN0M7Y3cCjfO VsLXZtvCN2d3nqnM7jbTNrvnzM6z+2BPJvMl6vLeTO6bsOeJ71HYlrTB72Z2m92X8yW3q2VvF9+H Xbubg0HxPYzce7At3o/N7Dk7nfc7M/vMHhSvD33qD/5N/sI8ob7N7Dt7GGS8b4yT3Cd+htruBeXe 7zMk/dp2X9dCvBeLU9t9XXyP1s7ebGa6oC/cm/Heq/X+i/dc8X1Xqz0WtxV1WUf65J65RfMvNDWy 8p55VRBZE99jhYzIutCMSDnnorheaFZkM8d1aE5kG+IpngdYh+ccxR+eiyMHQ8siNeBXRo6F1kRO MbWeb6F1kTrOEaHyyDnE57bI5Xv2MUShykgTiOKRCfOQ89bBqBnPmmhCfA7ynAidiiaG6qJJLfOP c9C5aApyzcVov9DlaEaoKZrJa0+cuL98xsL8oz6HbkWziszRkbBN+aMoIZqNfkr9InvUUZQYHV+U FJ1clBLN51xU1C9aWJQR9RdlRkNFWdEIr39YAzk/0Z6gaGR0blF2dD7n4yJHdBHOLLQWFo2PLima HF1RlB9dxf4qKoyWFfmj6/mcUBSJbmE/Fc2N7mD9ovnRqqJF0X1FS6KHeQ/I+T+em4tWRGuLVkWP g8gerzMc20Vl0dPs96L10fqiiuh5jrOiLdEG5DAax6Id0St4VxW9ARv7os2cy4sOx9Si2ljHouOx rkWnY92L6mPJRedjqUUNsbSiK7GB7N+iG7GhyGPc/+bYcH6G1dhojodwx1hOuGvMFe4emxBOjk1p iR/ag/P+I5wamxZOi2nhgbEg5DLnhofGwuHhsRjGj+ZJeHRsXjgntjDsipW2xGr8HBBfo4gPT4gt ZZ3wlNgrLFPMism+yL5MUf71E5R/op+gNChX7v4cQGtSZuhJeoreT8/QM/UsfeREVc/WHfp4wsl6 vtYkip7CpBfqfu2WKHpIj+hz9fn6In2JvkJfpZfp6/UKfcvEpfoOvWriHn2ffliv1e2yrAAd10/r ibLU6+f1Bv2KfkNvNlSjo9HV6G4kG6lGmjHQGGoMN0YbObo5XkjDZUwwphjT9ARRDM0IGmHSi6GF 3CLW5Hf8PfoC3/N3qaDYzvu/cg/qprkxjsoDuAfthnvQr+Ae9Ku4B+2u+JWg0kOZQSUJt6EP4ja0 N25Dv4bb0BTchj6E29Cv4za0L25DH8Zt6CO4DU3DbeijuA1Nx21of9yGZtCcq1EGKrVUBuM2NBO3 oUNwG/o4bkOHKZ8of1G+oVyiMhx3ok/iTvSbuBMdhTvR0bgT/RbuRL9t6mPqo2TjTvQp3Inm4E50 LO5Ec3Enmoc7UQfuRJ24E3WZfmB6SfGYFpgWKE/jTnQC7kS/gzvRSbgNnUwz/XfKM6Zdpl3KVNyJ fhd3ot/Dneh0dbH6E6UAf2mwUN2p7lI0mtcHFUO9oP5F8dP8bSJfmpQ5SvHdWPVSj70nvGe8Z70X vI1UrnlvkuNtWmetm9ZT64NiaDO0WdocrZhKibZYW6at1NZo67RybTNKXy1dG6QN00agjAHmah7C idpUrYALx425P8XNABk33fB9jhgzjdEjFD0cKyr5P5Oih2PFhljpQJHyFMUQ35nfR9ExlWKI46MT 4qMz7sm7UL+eo0jiaOhKsbCc4onjoBtFwQaKJ46AROVtKl9FBHRHBPSg8d9Pccv34b1ozD+kCONR fxCjnow78N408heVPhjjFFNXGuOHMLqpGNevY0T7mqabCpSHMaKP0IiGlTRTjEY0Hbfc/U1LaBQz MIoDMIoDcaf9mOl3pp3KIMWUMCxhRKvxSFcf8Ka3Ldpcbb53kHdYvGj9vCNkGdO2aIu8uV6PKNoS 70TvRG0FSdoUbZVW5p1KpYCKwUVbj+cM76x40Sq8c+4t2hZYmOMtlqVEFG2Hd7F3sVZFuOzeou3z rvSuaSnrWFeWclk2ty2BzYFt3m3eyngxLnv3ynKwbQlUemvi3wrs9R6jso4kbYo+1NvkPUWFv1fH xZ+m2el5DjVQ9MZ7rXsP+nNg4WDcs96LogQOei97LwfKCZvuLYEa6t+tluLRzC0lQZR2PHVYq9Xs WmJLOa4loZy+64l40eq1FK1fvGDEz2sZbUoD0RUtEyWLyg0pb9ZVwpEtPfJ4i/WOWva9Re+qOfTu 2nhtMhc9WcsXRU/VQiQp1Ar1NK2wlZ2Wog/0XtT8LSWkReJFeN9bRyNC8a0PR+zm6qP1HI4x3cWe 0CdwfOhTiJuG3mbomh5Ei4Loq7DEkXIMo1QTOBWoQzScg/cvwtMNepjmziDy3zDvCD3mLdfnkZft +kJqX6m+lGK5QH+F4n2Ovloz62splpcVluobtCz67lKKkxLS3ahv1Xd6b+l79P16NbWY43+ZfgS9 LKARO+wt0U+Qhkc/o58lWzxr0SNoirnCo1vinahfoPY3Up+vkXwx6Q2jWbdYv0ncIH2aoXhHGDaj s9HN6Gn0MfpiLk8UxUg3BvF8NYYZI6iMMXJpts4QM9bwGBPxNfqSMdVbYhTwnDTIMmnOMGYZc4xi o8S70lgs5x/PwHJjmTGDYs2OeEuitys1h5ZlrNGSjHVGubFZyze20fjSaOlLjUpjr3GQPJehZVOb Vmq1Ro1xjLRPUanTMo1KRCD3EmPFelQoYthLxjmii1o2zeFlRhPJI8Ytn9mo8yX46Nu+RF+SL8XX z5dBvg76MjnefVm+kb5sn8M3nmOcPIsx903W0yjasnz5xgxfIRW/L6SN5ELvIr5M31zqgUObTG/m a/m+RRynhIW+Jb4VvlW+MqOvb733oq9C8/u2UDyGuG++Hb4q+mYhRWiE+xe47N0WaPJrlBn2Bm7R +NRRf7IpXpYFzcEEygLlQTtlioPGSl9DMNHb01tZWO0bH0wKpvC8ppghbwX7BTOCmUZ5MCs4kiKU M0cTZTP2TnmgMlApNLzL/EeC2WSL8x0iGJoiy1AEk61jQYd3ZXC8d3NwsvegZia9SmrP5WA+cdt8 +cFC7159uC/TPzzoD4aCEWRBmcmCcwPIrL6swLHAseD84CLKc+dErgsuCa7A1+hLwVXei8EyzmaE l4NlwfXBiuAWf/cgZXRfvshcyF0JgYvBquASLT+4j1vi20fjxLGT7zvsq+X4EUVfSu0+6DvOOcl3 msa4XhtPo3Oe4iqD8kGGr4F8vd53RRvpu+Fr9nr8qp/yjvecv6u/e2F1YbU/mUZwPcXNZe8cf6o/ zT/QP9Q/3D9aKzTq2O/ebVqWP8fv8l72T/BPMc75p9HsWUwJJqiF6Pt1tD6e94+mGWynnFVIb8L+ mH+eluRf6C/1L/W/4i3WEvyr/Wv9G7zH/Bv9W/07Nbt/D1m1+/f7q72nyHKd/wi1yU5tOeE/4z/r v+Bv9F+jNtaQ7QTvZdK8GVACNu/iQGfKNt1oLnkobnpSnQyKlaxAH4rfhkBf72Z/mq/B16Av9dV7 64xjgfTAoEBf8oM5MCwwIjDGqAnkBjyBiYGpgYKAEcjVHPScYTQFZgXmkHaxf6mvNlASWKxFAssC KwNrAuv8SwPluobd1IB/nTD/iU6YfiWM32rozv83mYJyxfSsWUksWE+lgsoWKjuoVBVUTaVSsK9g 3/RT008VHKZSW1AL2XEqp6mwrJ7KeSpUb0rjlMaCBipXCvgMa7Z77OPoG11xolFwojHjLGPBnlfF WcaKU4wNe94OOMUk4BRzH04unXBy6Yw9rx173vux5+2KM8sDOK18RTF11bqG0Cf83mHBUMVU4KLn cHpOUB/I3VCQ82XI4aDnRqKtn0M7BTnyBeXu+ZK0n6i6HToiyBGh54kvR4759Dwj6aykC4Ly6sTT sYqojPhGomv3kqOCnje/mBw7iKrIriLJRtT5s4S+taG8bm2o5z9AfYj6tkPp7dhlGtSGhn058pDf 80YQjfkcyhXkOSEoz/MlaSLR1HaoQJCHxi3P+HLkobHNmyFplqQ5gjwXxNNdT89jRMVEJfeSh2Ig b/EXk+eatLFM0kqiNW1oXTtU3oY2/wO0jaiyHdpLdLAdqmlDx74cOc7T81QB5ke7RO8cDURXpN65 L0kXiS63Q6ekzWZ6Nn05cqr0vHWXHOa71KLTVT67EyXTu4S732pNzlT5ffsXkzONaOBn6zsS21BS O8R1h9IzhZ7D5XN0++35PHL0I8pohzKJstqhkZ8lZ06r/N0638bzpcxjTldBS35xTij4bP6Ix0nr cZX+bvHRlFa+nfbZNrXklNY5ID6H5dziNSMe8+N6tonpJvHeqREFicIiR/D64pwn5Nwn50KiUpFf C3i8KE86XyFaLdYA51qZ32+KeHeST+L52UlrmnOr6K9zp/QD2eR8yTZBbJfG00l50Um+c1IbnGz3 gvSv9CfXxToZX8POtvIz2XEpwga/c9F64eos29V2nNqMUcuaEh+nUrE2urqJtrl6tqp/U/QF/94q 1z76t6uPlG1sRTvbobbr8pF26ESr9bXVGttCja2ozfrasl7+d9bJPgWfXQvTC+6uga3Wu5acReQa I5+0brk8co5R/nDRmuSiNchF64/LkHKaw7x+YN7miPnkonXGNUvkItccOS/kPIjnRY4ttsN5Dvkp PkdKRd7i+i05sO3cajOv4vmlZW6VyvaXyDFffLc+9Gm+uWhtcq0U7XbRmuTiNahO5iTuA61Brs2y 3hfloLZ5vD2deJvbycct7xLu0ufmui/KpymfpXvyZOtcmdkqR7bKh9BNkTpZwgeco8dR/IxLF8R7 Gx5v3tOMGyRlFCvubOI5j8n9yzjaG7maZB6jMR3HsVUi8pmbfc/+knuCcbkyl/H6v1LmOY4/WqPH kb1xZM9N7R1HcTOO7I2jOBvHNinGxhXL/BnPl5vl3iy+b5p1N4/ClrSBNpaIfIl2tc3DbXJwyx4m noe5n2yL31FMjVvWqv5i2Z9hwl/Yc1Hfxq2UshGtKLcdarsXLGiHpF/b7utaqLgVtd3Xxfdo/529 2baCz+6/9hbc3Xe13mMVyLqVrXzSdm7R/HPVFNwzr1zHClr2WC6e13UiF7Xkq3Mirl0XZTzF5azT JOOPn5RX3HLeuWmOue2CWs83d6LIEe4kEZ/ufu3sY4jcGZIyBSEPsv0s+Rx5dw7ynHDTWuce32r+ kZ57sphvblqj3YVEfrH2xAn5qEL4ifvsDhFFpG3qh3uu7KfUd9OZzr2IaAnRigLkIvcqIjrDudcT VYj1jwl5kvYE7i1EO0Q+dleJOOW10L2P6DBRrfTXcaLT4pzgPi/85G4Q+m5aO9w3iJrFHpDzfzw3 e2gN8HQUxPawzlBse7oKv3toD+pJFnHmSRV+5HH0pMl3A6WNoSKXe2iP6KH9oYdzD+3HPLQP89C+ ykP7KY8m/OsJyjxG/feE5TMm4sFDeyEP7YE8tEZ4lt6NH87dvB/w0F7IQ3shz1oplznXQ/sBz0Zh n+eJh3zkoT2AZ0+rWI2fA+JrFPGe/ULHUy1k/NsYXfZ1OfCv38b4Z7orU9PV/fwTVXO18htF6ZBC 1I8ogyiTKItoZKtnNpGDaDzRZKJ8okIiP1GIKEI0l2g+0SKiJUQriFYRlRGtJ6qQtIVoB1EV0T6i w0S1RMeJThPVE52X32z4nOcVohuSWL9ZURJUIU/oSNRVtq1BPqkPCd2JkolShbzlmUY0ULQ1Yejd PicMJxpNlEPkEnYSJojvJUwhmkakSXmQKEwUE3YT5hEtJColWkr0CtFqorVEG4g2yufWVs+4/k6i PfK5Vtbb0+r9fqJqoiNEJ4jOEJ29+2T/JFwgavwHnnFfXBN+/EcJY9Caxgti+xiveql7oQ3dFP/b +fgzXj9u9z4bUWc53iS/r9vd5309ifoov3HmOj3Oic6pzgKnAZrhnOWc4yx2ljgXO5c5VzrXONc5 y52bnduclc69zoPOGucxKqecdc5zzovOy84m5y2X2ZXgsrsSXUmgFFc//DuDSqYri2ikK9vlcI13 TXYuc+U7y12FLr8rBIq45rrmuxa5lrhWuFa5ylzrXRWuLfTvHa4q1z7XYVet67jrtKvedd7V4Lri uuFqdqvuju6u7u7uZHeqO8090D3UPdw92p3jdvF7kk9wT3FPc2vuoDvsjrnnuReCSt1L3a+0S6vd a90bnDPcG2XZSqU9fieVPe797mrij8hywn0GdJbKBSqN7mvumx7FYwN19nSjNaFXu39xQZF/cSEB f3GhI/7iQmf8xQU7/uJCV/zFhW74iwuJ+IsL3fEXF3rgby30sqfYBysP2ofYs5UBdq/dr4yyz7DP VJ6yR+wvKk57sf0l5Wl7if1l5Tv25fZ3lEn23fY9ynz7YfslZSH++sKG/49bZjJ1M4Xx+yqV/H+T T82URJkldaSkbEmOVjwTzZrUyZJnvXzJF0ryS6Ksm0pZN5Wybipl3dRFUneJ1GfZilb/XiWfZZLW t/pmhfz3FqW/o5rKEccJxxnHWSoXgGcdjVSuOW46FafN2VkUR7Wzm7Ons4+zL0nTSd7HOcg5zHHW OcI5huYkZqXjGs1Lj7OAxup+/KUNBX9jw4y/sWGxZ9ozFdX+lD1Hsdrz7G6lA/7eRmf7dHshjUPA /pzS2z7L/oKSYp9r/4GSal9o/6HSz15lr1LS7O/a31UetTfYG5T0/8fWTc3fVb9NOJWiw9TcCXxH 8IPBDwY/RM0lHGqNQF4I+c/BLyHMtL4NPhe8qDsY/HjUfYxwIORD1RDscN1M2M9XhzBav8u/+2Sd S3yiOobRGiXcCp03+Lu3wd/ejTYshPw58EPADwE/VLRW4lzgTOiQzdv/S+1PWC971B9vv4tWoafq E+hXAC33M285BT4BbxXUeguS51HXCcn94Eeh7mxYux8tGQW0QmcYdAzCQeAHgc9Uh0MeBD8MFiAH DsHbTLz9hvoko/U5tGQ4NJkfYrkCHeGHJbBWBWs8Fo+p5ZALzAJOgI4Gmztgk7xhfpq/aB5gLSB8 2Uqz2xwDPwp4yjqLsJh1TGbgq9BHO80Ko8WA5qtWL+EG2HyAJaaTzJuu4u1y6D8F/Z+BT4S1q8B6 6N9U/4PkZvUA4QT1OH+FedOnkBjqScIRrKM0MZocwL8DdzNaLNDMg51JrG/6GBbKwW/C27HQvwP9 dPDngfuA26F/SS0iTZf134m/wXFrtlnfJb6Z5aZCazXhWZUiwZzEOsol6wLC/2I0nZcSQksm7CQB k1FXBy4H9lDv4O2zxL/PaD4Dvgp4BPiqms9jZLsE3AGsAJYCGxk79KRvDRUjCM2Xbfw3VArBjwJ2 kVgBLAVy3R7Q3I+3WyA5BUkxJGvFuDNPuANYASwFNgJZPw+a81BLEWj9BUcF+FfR8g3gK4EbpKQC WApsBGZTX/ZaSxFFfkZ8/STwKuoul7gDWAEsBbKF5fDGz1jHsgr4M7T5KrAeduq5zaZL1hrCa8BL 1teBYeB0ICLB2kAWemC8bkCzHnhR4gLEwD6ODUiaYaEZFpphoRlRcRZvz0JyVkoqCS3oy0PW/YiZ GmAYOB14lBGRUC9ijHmKNLZ2FPwl2tNzG0hiHi6R+mI+xFFqToYkGZJkzO5ktkx4AFiJyNxIfZwr 4hOWlwGXy7o8L15AzPfg/xM3fet1YBg4HXgA2ABkm2dQ9wy8cQTWjoB/FfwbEtl71Wjn0x3YWheB ItLAbxBofQcjG8Y48tur4C/ZvskeFsitUiChMy1jEuRHMLJHINmKOdIPmIIsNBj57WVbGuFLkH+C XHQN/ApeQUx/Rk7rIvIha5o6Wn2EX0E2KwH2gDc2QycDc+ED8E8Dy2UOpPXFBPvmDoy2ozz6tp+w N6zIpWoB+8S2k3lbBvOWC4jtcsRJJqK3BrV2WrdyXXUzWsVvgyKf2zhz9mekuXkcc+o45hHPjofB L8fbP8s+voD2GKj7a+j/Gn5GhrFeYP8wUq5mFOM1wEbrozkG/S7g90O/WGaPCuSBUl4dMAcNyF8F PgB8GF85CbzTIZdHs8NGfJffPsWjTDOX+USJbPNxmZPLiO+JmDwKSQrwtO1BHl/k2zcQz88gb2/j LGo9hpg8wprWNMReAkto7DiGEzmfm2rELKazMq0IGJdj7GHKA5WIsUrMSoEHMF8qgQewgnCuTuK6 5M93UWsBZtACxCF/JcqtsuTxW0ueyCoq7VVMvTHHx6DWTtt15AfWz+LWUiSz5DzPdIrwD3hlQcsz Zf5ZAE3+ynrgcuA+2yPM236KmTuOVxnM3DN4WyVRzFDmJ9r6420DJA1oP3t4mO0o5zq09nVeDU1/ wJqYhNbehvxt+Lw3+BT05SzvlMzjVbZfq9oJL/Du0dyLkcZrAbIKj9pq9LGM55plMNbBRxktKSpJ zL+H5degeRWW/xP8f4IfC/s17HlCtuxAm0OMyhbwF4HPWDsqvK9g+09ipNJhoVasv7yPon3Cs8h+ HOGLsXu5qAbRC463r+PtarT8KL61G9aSuKfqH9kbVvhEvY7xjfH6bunO1iwfMK8+CT4H/W1EL64j V1zHTExCO5HtzVXcQstQ9P0+2VpuSSr4DJX2rqZD6PXvVNoNmkajbYdRF9FuHq7O4DmOWhN5D2ye aPkr4SvqU2R5JMZxm6pxfJpfI/44rH0ika29ATuPw2amqhJ+zEhR11vhXRl5wNIBfngTtWYBlyEG Lqjsvc2wkAb8Oex4wEfR99fh5zHoYxC1PgGeAQbYY7TL4l4s5F0r8fdxVGANeh7WCtHOibBjs67k DCCjkXv3Dtpz09aX0XoV+AFwN+SpQAfnBLHnZE3zIOBw60msI8zniF0o7BwFHoKdQ7BzCHb+BH0D +gZLzGFIRkDiEbtW5pUmbgnhB8DdkKeCZ/0uYmeLr+wWiH1UHuzkcV3zJPCTBM92CHdDngrsDUky 4gf7Ddj8GNauAcuBm4AbVV4Bx8LmWNgcC5tjYXMsbI6Fl8ayZUs6a1rS4YF9sLAP/Hbw27kX5NUy tJ/xt6K/zFPbymCnDLWuwgJLstDO6xKrMbO4DROsj2G28ugsUHm3uVeeDvgrB9QTmLM4HbCmInby 57C374VTQC7w97DWC/abgCeAG1F3CjAHdXdC/gmwRqUotaVyv2wVjGqQddRa6y6a6fiWbZaV16l8 +CoMD/wd+nb2qq0C83owWnsUcfIxcJk8p5zE6BxETJ7EqJ2EZxCfPMvIA/14pKw9CNfgTGSGZh9o HgVfgq+PEPGGsXiLJRYLRsoCeR70PwZeB5YDD2InX247j6+w5A6PC40v8+clYqzB7xSRwxKKBAdG 0IERp3O0UmL5I50rPdZOjDY6t95+n2fi7fetNMqW17BTqmafqE/wuqPqzFveBv4PyMt5P6a+gawI fdob877oa6jrxL7oOWi+x+dN9RBnaQvOj5ZJfF5Wu+Ltb1HrV4wdHoS8OyzcAm6EfgHipJjHwrKd fWupAz8WOIRRTeExUlMRG6XQfxcR9SGjdT10hiAqkljT8mOM7F/BB/H2UbztiWjJhgVxVt0IzMW3 RmFX8AZWwBz2mOVjrCClyI37sWoc5P2JZS12pEuxBq3D/nAeJC9jV9MIO3uAx4EfAD+EnXPAWuBs rE0fYp3dyWh9D3wxcBeyaxPWoB/x/k3tj13ch5LfAawAlgIb+S2fvKwX4f88aHYGPmH7N0JxIsMJ 0bJLYgWwFMgW3obmHNTazhJCloxniXUaoiIfe93ZQCcwjJ3hLOw/c3AmxQ5W7Yf4eQffgqallHOp Cgkh9+ICLD8scQewAlgKJGvWR/lMansXMXPI2p1qdYK1tUAvEOdTNRF9fxH8Dok7gBXAUrzlfr3I vlJ3M9+ht+0XwClsH7VUiewfnBEsG9kPllHY9c2T+DowDJwORCzxzs3WEeP+PWjmcG60Pmw9RPyn 1vcIfwH5CYlh4HTgAeBjHG94exCSg5D8mPe6lt/wDDX9AHvpPsBvAmdjb5mCc9AT2LtmYFe8FBE1 GxG7lPeB5hxY/i34F3F63Ya2fQT5R2xHdaL9dSxRH5T4OjAMnA7k+fUIt0r9Gp9hbW+KmOcZYT4H a52Aa7FDmI95lIj9w0zE/xq8/VDi68AwcDrwAHTIn+pD/BXre3yvSMg6u1BrF/hEeKAJXjptrcBc 6MNvBeLEep5PrOoFllh3c0vUHeA/Ba8iTlToz7NewigI5NPr+3x6JW9wVNSq89E2jlgF/C60fBfe iiw6EtjJmkio8HhZe9meJn4dy60PIZI/Ar4ocylnnirk0uXQWQz9tzDj/op51AkZNQsZeDX4dzgD U1xRLetejMtB2MTp1bIClp+Htf7gd/D5l064/DYMzSrGhN0c4QkKTls/h2XcmXQQ2f4/cLopxQy9 iBm0HbPjcSBOx5ZNsPAmrCnqy1SrCnZ+x21TcU+l4kRMY8FrqI6z8AvMk4VG4HHM60bgcczWRuBx tPa3xP8UX9wJL93iPYDlNWSnQ0AVbXuHz8jqL4ERRgtuTizVtkW83mEWLwe/HfpvoO5PMdNLWWLz czawPQf5e9CvB04CrrU1MXaYyisddH7FkdPhQfDdgUNg7Rb0X0GbO/LqoHbjeyr1MWsS4od5M7fN 2sCjr3bD3JknzpuIh43WwxwnLFc/lmdqvrGswBnnCczrsbxGdMjF2H2AkXqSeVtHaxd6ewNr1i4+ EVP0ck7I5rcdcrGyrOXZRPmqEngAeakSyGuoA/dI/SGvg7wO8k8hPwf5h5Dnw9pH+Io4ec3Dyngc uIu/a63nHtlwH2vZihP3Oqxxq1jf/O98vqYsNx0evo42c156gs/ati6Y9Y2Y3XsYyZM1yDOPoSWM tXjbCfuiTrzzoXx4G3PhdWQMflsMLJXZg2udRN54l8/dpLMa8tVoP/KV7SXid6DNT6kPEv5PRjUF /t+Cnv4JoxODzjNSkyV9cA76PfdRfYDPyBbcKlvEqe0UTm2HkZO/Dz8kY9wH4Fz2C0RLTyvlIlsC al3HDuE3fB63BlU6WahLkWNDqBtC3SXgy/lb5m/gi4UYlzdw6tfQox/hhHscM0KF5Kd8Klf7o53f hf5lfBGtspaAn8dnc0sReKHzPCwMA36P90u0b+RZuUvtwesCWvgJ4lycpr+FSBiLvj9mqaJ+TWU7 tghwLqO6Vt2EzMkz4tvMW+dY56BV7M+J0BE/79iNbGblt5YXeBWzmmCnK/y/Cy38FZ+7LafBf8qn dctg8GP5tG75NfpyP7fEihmkPqP2IkkZ2j/f8inhSxaKBPUi/5TH9kvsCZ/l0zr1jtvzIJ/ZLYth 8wWJ7MMuwGf4nG7dBfw3PkdY/jf33dYdHnDgDH4WtQr4nG75Kvg9eHsN7fkLWrgV8r/hZxkp7Blb Gr4+Ejgd/Z0BHCb3lryq9kKtGj65m//IJ3fLj+CfXrg/rEcLnwU6MDo/xjg6edQoegnNmyBJRjtX 4xSzHDhK8DihLMdcW46TznI+VdFbOolYH8GOei80fwjcbn0Z+ZB5O9ApEBacsOCEhbHQbMRZrz9L 1P6QnIRktUojbkJdc1/gIpyXv4Pz8ndwCnsC57tf8FmJIoH0zX5ofogvdsf+cwCsDeC6ajb4BQIh WcDWCHdDngrsjZWdPGM9it4FVToVWtbA5hOwL3o3Evh9PntS+9EL2OwPm/3R00b0tJF9pT7Dlm3Z 1mPAH3IUwcIWgfBPIfhc+GGUzQVfMY7D+f00n9+pFy6++1KP4rsuzKA/wcJVWHPxasWtoszD+Jr6 MOE0dSHJ5yCj4rxM52t++2NgMiQj1RLiwyq3bQAkyLdqb4zFX4F/Y7RUM1prGdUBwAVc1zoQX/kq bOYBhwPXw1qp8BUsfApMg4dfBD7PGa/DIfZAggf+vIFz33O4pX+e+Q42rHrP8lvrI/BwNTSzwevM dzjE1hI8vDOxNuM8+AT6JWIjC6OcjXFZAz4RFkZA59d8P2ApYP+rSRiFLYiNh3gVs5zn3lk2ge8K vhg6dcABqJUKTMRodue61nU84tb1kA+B5psY5R8zb/4rJE/YhgFf4XiDZi8eTYqTl5EDGY/A5kbw D6PNifDh91lOmjfQ2huYofhJ/Z23FJNiufN78Jv4Z9nAzDtvgn8UWMo/JZdv3wKug/5c8AJ7ApdD LupuBr8Z1jYCP4LkI/CnoENy89N3+EZ0APBlYAw4CngKWMxoMjMq1yDJBCqMFgP8q8ANwAckzz81 OIm6VyFZDnwKtX4GPhFv64E3IcFXzBMg+RS8sD8CX28Cfoi3fwfuhjULdPKAkyD/WPLchnJINkEy Fvwd1EoHfx64D7gdeAmaLvA3wNvANwN7As82p/POEO2BvvJfLLEIzyQDk1hiQq9NzwDfh/wM+Crg EegI7z3d/C2yMFSMBfPmUcAy4FoxCuAzgQrwVeCGZt6d7hX+Z4npN8CrePsHWF4lege+h/A8dJqh 85DoCyT1aNV58EdlX76FfiVQ3bmoO48lCvxjegmamc0e9GI1Wr4arV2NtjEuh+Qq8BIkDzEqgk8G JgHP4Yv9gCnAwcBP8C0RgSvA/xmY1DyGcCL4r2BkS0RMsty8GXxGM5++PwA/HHJEhbkDow2RZpvN qO6ChdvsAdvzzFurMdYbhGfuvMY/bYT+T0RswNoKtOE6dP4OXz3Ns5LmVE/EP+MyMcq3r/CMQ09j Es3AFMIewFHAYrwthrVilpA/WZ4DeSZQkZjC6wL4VyWypgfePik9n4JRKAMy/xTLLT/D22uo9Tha KCL8GnoE/5tOixFBT98Q8Qxeg842eOmYyB7sK/U4PCbmbyL4ZHhmH/T3NY/mWynwMdiJgn+d0YJZ bMlDBN6A35bjLUbT1BvyS+xD0y202QbvJaFHCfBSMyPFleC5j/CV6SdAEYfPSkxB3TLYYf33YfMY 3r4FhD+Vy+j1ReDrwD/c+QrhbfSxIyRvg+8NPgWjNh58LVp+AW97MU8Zo5wko/H2BeBqvC2DBxDt lsHgxUxPYo+ZH4VczIjfA1+DZR0WdFg+Ib3EvMhsNZjX+zFbP8EoIKuYVHj+SdgRmbAW+Jc7Q9iT 4KtFDoTmYmh+XeRAfOUo5Jh96nzMnUPgr98ZS+0U68g6ZJsP2Ffqk+BzIG+EnevgkQnN9wH7A1PF nIXOIeDvZHZ6nBArhekwdLaJGQ1EBjC/Ai+NhM5xoMgbiFsz1gXyKp0pLJj7pjeBs4AiV6QBfw6M Qh4BPwYYRAS+CPlbci3geF4oefaAWDvyoY8cYi4UawpG0wb/9wQuB74PrAIin5vexnjdAf8O8Cbq HhHjBR6eNH0K3gB64KUm8F3wdjf4POCk5iZuIeQfw+Yy4CbgRjl/xbc48g8h8pswIyYBx0K+D3wW 9BfAGtYd0wF8vRmxgZXRhExu6QXN3YgW8KYmZOMT4DdCPgW8yKsYfVsFIqor8IfIMNif2PrAmshI k9Da7XfW8M+YYOFO80/QX0LTQeBN5OEJyCSbgNOgeRN5uDP6ItapRJlXUxDbnBlGQDIC3huBrNIE eRf4YbdEzr0WaOZJZAvleLtJYgrWnRnwYQrayXkpBW9rgNtRdzzuGK/hDj8ZN43Jtt+SZmf52zX8 2ylZ+J2c27hbfpR/y9H0PqO5Aj//PYCzJ26oTH9W+Tdz9uJEhp+2mLNtnXim4yc4tcyb3wN/RT2F syp+5sX7c2WquR+PC99IWNLVAH9d/SXvMZg3N6p/42hktFxRNyh8v0SayhlGkx+1chmtFbjTsAEH qvN4bsJCuUr7Xks+LNzit7aJqDUBOBS/n3ADmKAm8Yhbvs8es+xnHebN8/m/cDHPYLSELXWwRprK YUZTqqgFyTFGtYGResG4zvJT7gXsZPOtgvmgsIO3UxitC2HhBrAOuBi41cL3OemM5v/D3ndAWVFs 7e6u3X1q5nSfYoABYUBEMogwBJEkCqICIklUJCk5SBKGICIgGURAkkgGSQJiQkGSSAZJIhkkS84M iMOEV/V1ey+g713vf+//r7feu2vW+nr3rl27dn21q6pPnTAr2Ly6z2le14vb0GRw6iNO8ykyz2ho l5HpsEFtb+RNxt4pDz85USuezef38vEEM/o8E7EtNGfaqPUlsCw0BYy9swq1TgWRmNJ60Ezlnma1 gb5CgOZzRHbgbaZhCbF9Y2TrGOJhYRl0Es2v3kAWQhiNtQql5hPIJawT+MSs+VRbLTFM46Pm1EWs ECPNqisGm8jFbDOvjSwGiUEaewvz7rYw9tYHwDoG+Q3YjBP4rKMYpbEoD9X4BeTCPBd+tGzdgCXq imdQdyTkjPB2w2SpdRStJ4mMZi4LkxX1RBbEGWPyX+BdfhHSmooinZnLIr+Zy8beqgGsbZBuGmSG hyrw9pLIatZMsQM+jXxLnDS7BuSFsKwOD6mo+xDk08DvLcPwYsRw3sqtLYtY5oRTr4tak2yZd5lT rESzF4h4s66KvnjX3vyy7AXrmInHoFVRZDYasdTsXNYvZs8FZgcWMai9aaSTkEcBM1hHYHnEzHTI h62eZjeBzx3WLI1jrUNmPzKR0Bl4uGkiEclE5lPo9lWDoVjIxyFH8Ol0F/Lj0H8GjfZjzwhpn3Z9 YGXgRYN8FvipQceDPtmgsIHvQ1MANo0MhvbBshCwOkpzQW4KuR4sT0MDvT3MoMwBOT9KvwMmQoNW +AfILSD3BdaCph+wh0EL0YoKKN0M+RjiCcHmA+B8lK6H/AXkS8CawFehR484BXV9b1uB/YFtgHtg WRIy+sV30OKbkNchnr3A89B8DG/NUas0LLdA/zDkRZCngJOlkLsDpwELotYMqXefUDZ/dIxsXwSm +WNkZMeDJhnyU/4YQTPaHykjcyNgU2AneGvsjxdqSX/UIIOT0BV/1GD/KfA0SnMZlDmg+Q6xFYXl cGBbnx+0/jQiXO1zYjR6TzSyzxh4tmcCy6NFsG1dQymYFCvgAVnnjAVugP104C7gC0D02vYzbQri 7A37vPAAzh2FGJA/Ih9yLxr2p2CzAPKTsPRzrBJQGYxaYOpGZUKcDJvn4GEJMBb6bOh1ATCzBfbj UIo5Yu9GrTxoC9zyWH/egcN9qAtu7WHA/PDzFWzi4R98ioqouxh6zDLHz9XWaMufiTn83IOfbZBh KYai1gXYjAH6GQL2uLOfyWj3YXC1yKB1DZpJaMvPw8eA5YC1UXcn5BLwUBx4Bvgb9IPQVjPIL8IP +uWgdacULEfAzwTIYF5gfbBnAbsBX4KN3+JPQD9DlqP0DSDGhbOixY5AMC+hsW+gxZ7Q+2sa5qDt z27MXCcdNBmAWBkYWcHwJvyVCquKuAp71LUTgJ8A50Hvr42QeQc0GyEfQevIK8bcEddRC1nn+LPJ 79FK2IRhPxkaf9xXQV8HGAdEzIw1MzQEPv2okBX2ISDmlI3csBB5qA9qvQ37JMiYiXYv4H7oMaYM /p2G0GONsrFq2cgHgVXdbglcBvtE5Exf5I+/Xs0HYi1yMI+4PzT+ynkZdf0xxbgzRiqEXOIGQMw1 HgVE9srtBqOQFQ72LwfZHgLbEn0PodSGPWON4jLAmqZ1IvMaxJ6Rat4tqg+sDLxokM8CPzXoeNAn GxQ28H1oCsCmkcHQPlgWAlZHaS7ITSHXg+VpaKC3hxmUOSDnR+l3wERo0Ar/ALkF5L7AWtD0A/Yw aCFaUQGlmyEfQzwh2HwAnI/S9ZC/gHwJWBP4KvToEaegru9tK7A/sA1wDyxLQka/+A5afBPyOsSz F3gemo/hrTlqlYblFugfhrwI8hRwshRyd+A0YEHUzYa6abB5CvJolHaC3Bh6CURfQleARVE6HNgW +DRqrUa72RGhHzn6a88Elkdd9Nq6hlL0SKxAXYy+Mxa4AfbTgbuALwD9CP0R9/vVG5gXHtB3R8En xlHkQw5Ew/4UbBZAfhKW/lhXAqJWFEqjMiFOhs1z8LAEGIvScZCRmfZu2OSBZzDDiJ+/Qmk8/IAZ URH6xdAjex0/B1rDm5/hfq5ugx42Yig0F1A6BojREeCBOwMnwZs/jo8BywFro3Qn5BKoVRx4Bvgb 9IPgsxnkF+EHkTtoxSkFyxHwMwEyuBKYWfYsYDfgS7DxW/wJ6I/pcpS+AQSTnBUtdgSCPQmNfQMt 9oTeXw2QvbY/L5DzTjpoMgAxpxjjyPAm/DmO+Siuwh517QTgJ8B50PurCmTeAc1GyEfQOjKBkeHi OmohTxw/5/0erYRNGPaTofFHdhX0dYBxQMTMWG1CQ+DTjwrjbh8CYhbYGH0LkYf6oNbbsE+CjLlj 9wLuhx5jyuDfaQg9ZreNTBBYCe2WwGWwQVbb/kpyGbI/UhhNBv8hZAg3ACLneRQQuSe3I/8x1g7W cwe5GgKHEj0KodSGPWN94DIG6ZA4QOZUZLsuzeOfY/AIramC190tzWkDz8RJQlWUTjXfjeWc5vNp PAFnKcJoxDnoRxi9+YAFmW9bGE1Dg84ug3YR6BNRtxNKzxoMdYbcElgF3i77lmi3XnCakYfMGYV5 bTgVmoHBiUcRfLfOnKJUw/lJEs5DYnE2shD6Waau2AlNS5SOhyzg4TKwG3Ae+u4ZFH3BQF1zQiI2 4NSiJOSSvMTUNTaUhvOKjMH5iUY6bmyc4vBTB7Uq44SkrNFYGe3JWp85OBtZiDOQhTgP0Zg6Os2c U9VK227WXsj1zGtbsdPI1jOQ66O0MuSVkPfDshfkKMhlUboWtc5Dk8H3Bs2JVPNKvzBsMqBWPLAp Svf6iNI4yEko/Qge8kA/G/pSkAuhNAS5FeTBfgxGtg74MaC0h5FT66Td0pmQD5ovKavGg5CnGpnT 4bV8mkGuALwOTRLkCbA8atDZZdC2oBfAhSiNMmglQr4MjIc9wWYEsBBwAEq7IYaxkJtCnocWL8Cm J+RNKG0HP2H4XwOcFURuImkLzVJoVgCHAdFTroJSBU3f1OX4L+zG86pUcxKYE547BDEY/WEzRlzB IB1G3UXAUfCGEw9xCpq6xsbOl2o+q/YkSiumztWYStW1PgY2xYxGXPVjhueZJobQg9CsNLI1Cvo6 qV+Y/DT29jqU7jWluu9mdDx4rgN9FvgcifizpSXpOPsh2puI7aCp5XRCX05DPx1Z19vUskqhrZ6Q c8FPfGoy3kFINnwChxnUT1MGj0GTHTanIWcwyE8jqpIYtQ1oqwc8t0SExwyGbHBbwM+QtJdM1hkb kcFozO/v6BUSs8yOMX0JZYH9aSM7z8LGg6a+n4dgOzta8cBMBsOYNQi9rpdqzmbbIcJ5kMOpr5gc SzWnnRmBNdD6BrDxDOSmxtJKRK14yLdguQEeRkEeDv1esLEV+nzQ3EDpB9AchLcPoHkSllcM6hUH 4+XnIeKvjr4cRwzHkAl+Jo81vdavAo6AJYw7sC9GKhH2qfBQBG2VRWk88ucY9KUN6vXdjEvVwMbg KeTALnje6fMfsGEir4y+HANXmaGPAOvBsl3QbjLmRTJy7zoywbc0vOUwss7t68hkY9MYOAqaV2AZ h7biYLkdtTbAZiJwKUprBPO3uO5LCDEvRh+3QZ8d+B3iae1bor8d/F4bS51FOLVGRoUCVmciq8GG YcZqDc/jsQ6sAntrgraMn+IYqcz+SoVal1FrDSxTke3xsFyMzIw1cigXpUOmLceIm/gn+zM6mCPG W0OMUR7g64jwYrDiZcVeY1rZGszZCbr0c38uG296tRyPqIqjlr+uGs8DcEp8mZojr5qbPT2ttpZf Rtadhw3WAfbn0XDUrSF+QOYvx2iaPq7210ZY9oG+Lpgfa1CvS8uxVphVxR+RecAolOZEryuhv0eA I4DJ8FwZ4/UUMBewWmBjVrnewTialW2MWTN1PizHbJqLrEjGO7nJyNVk5HMyxsLIt8Fb32AXywqN 6fVE9LS8v4thzbmM0VlhUCKLJHYZPgvL5kDscXTV5KF+Bv4Za+B1rIFmhamLOMsiS+ORwzuR1ViL tOVMWBr7z6BvB8sqkJ+HfhYi3wt5IfTPpu4GdsLsu26eyU0rqRPSTmC86pjZijF9Af3K5e9rqWvx fn0mEy0i74e+5IRlnVQ886BudsqhfcYFI6vllE+NZyL8zhvZ5ns6wUmjQQpDHzZ6IqNJbWA+ZZ1a 33wSPhXfB0kNQy4GuRjkEuZz2qklzWfptb4T9PMhv2Y+P2Y+ma/l9ZAvQ75oZPMtHl13mfmVG+hL mk8Daj8L8NssN/H7NisMmu8REJnvuafGmm9zpMaa74OkfhlqZ37lRr5rfuXGyCkrjZzaLzTS/MqN vGr8h04ZlFcgHzL+5VnIdyD7NrWBJWDZBNjc/O6NiS3lmB9z6EPYz4Ts1zqPmBOhzwN9jEH5FHpX BHgF/R2A0sVACf3jsKyEti5CvwU+i0NTFsz4miSUNoD9MLS4BSwlAfug9YqwfAR1jWU85HjIxUOb oL8N+RH48fX5EMnLkAtCfhV+9hmMkpDxSz5RUShtAM1QePvW/AYOPDwOD8UgF4NcwnxfXtv/CDkz MBNqPYOYiyPmphjlKejpTZQittAcaF4DrgcmovQBjUXlZ5A/h89VkIfD5ivgGOgXQ94F+YaJ0PwK h47W5GEJvC/PKWmQwZt5Jz21WMo5E08KxsK88641101pykrDpK9J7QPMCUQteCiWsg6WqJuCXqdM gXwKPtdC3gv5MkqRUSkHoDkDP+YTOERha0jUeeJmb3VuR7GtOrd4g3q3a5LQgb4k/crvxTqVcpJ+ ZZGWRpnIoxBlp9yUgYrQY1SGnqJq9Ao10j5q09v0LjWjNtSRutLgwD5Ckh6kPJSRilIp7aUiPU/1 qLFutQ71on565WhLnagbDcH/GPTrKIrSa0ZeiqV4epzKUSW9Or9Kr5GgF+kd6k8t6A16k7rTUMpM XLVWrSpUrU7NF3JS07p1ns9JE+DlAfxm6EN6bc6nPRaj8vQ0PUcvUH16nZgKUV3qTQOoJbWjztSD hqFONOWk/GR2uieoMtWgR+g96LNQjObhYYqjAtpvCSpNFegZqkI1qQE10XEXppeoDw2kVtSeutBb NDyIID25lIuyUUHtoSQ9Sc9SVapFDakpOfQovUx9aRC1pg6UQD3Nb5k2K96lGb8MbAxsCewA7Abs 3axJuwQeBBwFnAicBVwEXNqsSZcWvAa4CbgduBt4EHisWbP2nfg0MNGgLYAxwBzAwsCyzdu1aWU/ C6wOrNO8Q8f2dj1gY2BzYFtgJ2A3YK+WnZs0s/sBhwPHA6cD5wMXA1dpx03sTcDtwN3Ag+06dG1v HwOeBl4EXgfeBqYadOx2HZu1c8LAGGAWYA5d2NnJAywEjAeWApYHVgJW6Wj81ADWBdYHvg5sCWwH 7Nyxc/MOTg9gb+CATkY/DDgKOB44GTgTOA+4qIseI2cxcBlwDXATcDtwb5c2HVo6h4EngGeBl4GJ wKQu7Zt1ChEwDIwF5gAWABbv0iW+WKg8sDKwOrAusCGwucbioXbABGAv4ADgcOBYjSVCk4GzgAuB i4ErgOs0lgxtBe4C7gceAZ4Cnu/StWmX0FXgLWCyQSmAUUDVpWunLjIWGAfMCcwHLAwsnqCZlKWB FYCVgdWAtYAvA83TuNBrT+w/cWU9z7NR9v+SZOGHQ//P6OgVw9GrqKSof9udjTtftvSqdz9G/iKy Xudc/ObyvyJZevX+c8zwl1FgRIT2au5w2mP2B/OU+Jcx/V/GB/+AMX8ZcyJSxtW6C00P7tapf4is d6rMlOWflB6AJPT+lOufuuamPP/UNS/l+yeult5J/zH+Y04svYP/Y0z3l7CYftpI0Lv+WJpFi2kd 7aZTlGjZVqyVxyppVbbqWs2tBGuANdaaZS221lm7rVNWorBFDlFd9BTDxEQxXywTW8RBcV4kcZjj uBCX5Wpcn9tyTx7GE3m+noOmrSg/Z7nGffdN77sfft/9iLvu7fvKQ3qa7ydp3XUfLnnvvTfz3vrq 1r3+Y+vfe5+J7vWfKfa++3z32Ve5777hfff39SfTwXvvMxe4777Wffc97o0/+/R7yx9cce993sL3 3Re5617Pv7zx95X3w73Q60MGv4f5a/nXAn7PbZ1zmfValS/Q7gyuB4PrqeB69c+sC30ZXFcE1w3B dde9UTyi7u3lI8vuvS/a7177oofvvS+29d774t/cd7/03vsSde+7f/m++0733Xe+7378XVmmhVIT 7rtfdq99qftG6Q/l2++733nf/a57R7HMdo1KM9PMGkctrclYbZvqP9IzdSxZToyTHntFBgp5VdUG r4pap1arNVoTsi5Zl7TdVesqWdZ16zoJ66Z1k1hVVBXJVk+rp/W+afJB8DNcxbQnMohMWmO+QaRM PBzRNYvo+8z61Uhnmkwb6BglWbE6higdVaxXm4RXxaujsar3osZqOvoYvSbn1K8W4vVrnvLqLLGI 0TGdw3WD0q+0RCZ9fwHXDWovCX23X+MGdVDjJt1Xk6FxlEsd07Gu1qXHcd2gTujrGn1/EtcNd1me Cix/CSxPB5ZnAsvf430e8VZHvC8g3t9LaqCkJkpq3V2itiDCrYhwOyL8vWQnSnahZDdKBEmh//Q0 c4X55HaMiNGsZtKssves95xmfbVaTSEd0xrNFGsL826kv+vrqaXrN8F4EUbKspKsJD1qaVaaZssR +rkHfh34DcGvFHEijqJELpGLokUBUYDCXEWPpus0dZqS5zR3mlPEaem0JOW0dlpTOqez05linAQn gdI73ZxulEHlVDkpo8qlcuk+5VF5KJPKp/JRZlVA6dd8qpAqRFlUYVWYsqoiqgjFqXgVj9/lLkHZ 1WPqMXpQPa4epxyqjCpDD6lyqhzlVE+oJ+hh9aR6Uo+OybfcyLc86jn1HOVVjVQjyqeaqWaUX7VQ LaiAaqVaUUHVTrWjQqqD6qAXik6qExVWCSqBHlXdVDcqonqoHlRU9Va9KV71VX2pmBqgBlBxNVgN phJqqBpKJdVwNZweUyPUCCqlPlAf0ONqjBpDpdU4NY7KqA/Vh1RWfaQ+onJqkpqk83OKmkJPqGlq GlVQM9QMelJ9rD6mp9RsNZsqqrlqLlVSn6hP6Gm1QC2gyupT9Sk9oz5Xn9Oz6kv1JT2nFqvFVEV9 o76hqmqpWkrV1DK1jJ5XK9VKqo7xfgHjXUPnyjqqqXNlA9VSm3S21FZbdHbVUVt1dr2otuvsqqt2 6qx6Se3SWfWy2q2z6hW1V8+Remq/niOvqoN6jtRXR9QRaoDfxG6orqgr1EhdU9eosbqhbtBr6qa6 SeZ3vvvp+dFPZ1I6Kx31seKsB6kv/jPqAKu+1ZAGWu2s9jQE/w11mPWmlUDvWcOsYTTSmmB9RKOs a9Y1Gm3dsm7RGOuOdYfGmkWGxomQCNF44QmPPhTpRXqaIDKLzPSRyCay0USRW+SmSaKgKEiTRbyo RVNEguhKq0R30Z1W6+eInvS9eEf0pjVigBhA68RgMZjWi7FiLG0QH4oPaaOYJfbRJo7o9SeZS3JJ SuVKXJnSuCpXtQRP4SkW2wn2DMt2mjnNrOJOC6eFVcJp5bSySjptnDbWY04Xp4tVyunqdLUed7o7 3a3Szk+hIVaZ8IvhJtaV8GDXslK9GO8Z8ZbXwJsqPos0j7QVNyJ9IsNFkhIqiqPUw+phTqdyq9wc o/KqvJxe5Vf5OYMqqApyRvWIeoRj1aPqUc6kiqqinFkVU8X4AVVSleQsqpQqxVlVaVWa41RZVZaz qfKqPGdXFVQFflA9pZ7iHKqSqsQPqcqqMudUVVQVflg1Vo05l/nn1JxbtVQtOY9qrVpzXtVeted8 qqPqyPnVm+pNLqC6qq5cUHVX3bmQeku9xY+oPqoPF1bvqnf5UTVQDeQiaogawkXVMDWM49X76n0u pkaqkVxcjVajuYQaq8ZySTVejefH1AQ1gUupiWoiP64mq8lcWk1VU7mMmq6mc1k1U83kcmqWmsXl 1Rw1h59Q89Q8rqDmq/n8pFqoFvJTapFaxBXVF+oLrqS+Ul/x0+pr9TVXVkvUEn5Gfau+5WfVcrWc n1Or1Cquor5X33NVtVat5WpqvVrPz6uNaiNXV5vVZn5B/aB+4Bpqm9rGNdUOtYNrqR/Vj1xb/aR+ 4jpqj9rDL6p9ah/XVQfUAX5JHVKH+GV1VB3lV9QldYnrqavqKr+qrqvrXF8lqkRuoG6pX7lh8FrK PPmUxFpbUKezYzWyGml1C6sFWfYSewmJUEoohTiqQlQFPXv+Pauxztz/rMb/n6/Gf8++OGRfIfO0 ZbUJHfpPjv0nx/5NOWY5bfXzfIyVS5TkZ+16lJ3KUiWqRnWovn690FY/v/fUzwPDaDRNpJk0n76k ZbSGttAuOkgn6Dxd10/2ZIUsL7oHcXSX6ITot3DtGt0T127Rb+PaPfodfU3QUm9cE6L74No1ui+u 3aLfxbV7dH997artBuCaED0Q167Rg3DtFj0Y1+7RQ/W1m7YbhmtC9Hu4do0ejmu36Pdx7R49Ul+7 a7tRuCZEf4Br1+jRuHaLHoNr9+heJHRpP41do4do7BY9QmP3f4GRceh5l+jxATMfBsxMCJj5KGBm YsDMpICRyQEjUwJGpgWMTA8YmREwMjNg5OOAkdkBI3MCRuYGjMwLGPkkYGRBwMjCgJFPA0YWBYx8 FjAyVve/S/RUMDILjMz/Fxn5ImDky4CRrwJGFgeMfB0wsiRgZGmQK98GzCwLmFkeMLMiYGZlwMyq gJHvAka+DxhZEzCyNmBkXcDI+oCRjQEjmwJGNgeMbAkY+SFg5HMw8g0yZTUY2fAvMrItYGR7wMiO gJGdASM/Boz8FDCyO2BkT8DI3oCRfQEjBwJGDgaMHApy5XDAzM8BM0cCZo4GzBwLmDkeMHIyYORU wMgvASOnA0bOBIxsBSO7wMh+ZMqJf5GRcwEj5wNGLgSMXAwYuRQwciVg5GrAyLWAkesBIzcCRm4G jNwKGPk1YOR2wMhvASN3AkaSA0ZSAkZSg1xJ85kJk89M2PKZCQufmTAHzJwFI5fBSCIYSTKZYv5P o4kbp2n1qKC1S0zj6lyTW3IrbstvcBfuyt35LX6Hh/BQHsbv8XB+X792OcEn+RT/wqf5DJ/lc3ye L/BFvsSX+Qpf5Wt8nW9wIt+MlDL/R8naae3UDUw1387l5/l5ElyDaxBzc25BNrfmNhTiztyZojiB Eyiau3E3/STQg3uQy724F3ncm/tThCfxJMrIy3gbxUYeizyGU4Y4Cts57IfsnPbDdi47t53Hzmvn s/ObnumIbuJ03aIsd51NPILzoHbGQtfMH1hkv8ui8F1lmklup63JjrXNb4EVsAuQG7Qba2eyM9sP 2FnsrHac+e07bfH3dgXloXR2Bjuj7dghW9pRdrQdtl3bsyO2stPZMbY577J13/roEEwdYT9hVyDP rmhXJKXLSlEWnsPzeCF/xut4PW/gjbyJN/MW/oG38rY/Y9yclvFsnq09zjXfa+YFvEDzvYj1OqqZ W6vbO8EX/uZ9trZaoEuX8XJewSt5FX/Hq/l7XsNr/2yM4X0Oz9He5/E884lMXqi9f8Z6ddYRbtPe TT+M9yIU+6de/6Qf4OxEwJmp9xezC/VMNuh6TgexmPrTABpIg2gwDaGhel6/R8Px30VH0ij6QM/y MTSWxtF4+pAm0Ed6zk+iyTSFptI0mk4z9ArwMc2i2TSH5tI8+kSvBwtoIX1Ki+gz+py+0KvDV7SY vqZvaAktpW/1WrGcVtBKWkXf0Wr6Xq8ca2kdracNtJE20Wa9jvxAW2kbbacdtJN+1KvKT7Sb9tBe 2kf76YBeYw7RYfqZjtBROkbH9Ypzkk7RL3SaztBZOqfXnwt0kS7RZbpCV+maXo1uUCLdpFv0K92m 3yiJ7lAypVAqpemEtkRtUUe8KOqKl8TL4hVRT7wq6osGoqFoJBqL18TrooloKpqJ5qKFaClaidai jWgr3hDtRHvRQXQUncSbYrrYLw6Ig+KQOCx+FkfEUXFMHBcnxElxSvwiTosz4qw4J86LC+Iih8Ul cZldcUVcFdfEdXFDJIqb4pb4VdwWv4kkcUckixSRKtL0EmQ+bc9ss8MhlhzF0Vyb6/CLXJcbciN+ nZtwe36TB/BAHsSDeQx/xJP5c/6Cv+LFvJS/5e28g3fyj7yLf+LdvIf38j7ezwf4IB/iw/wzH+Gj fIyP2+Xs8ub/ttq77T32Xnufvd8+YB+0D9mH7Z/tI/ZR+5h93D5hn7RP2b/Yp+0z9ln7nH3evmBf tC/Zl+0r9lX7mn3dvmEn2jftW/av9m37NzvJvmMn2yl2qp3mRJwMsqKsJJ+WleUz8ln5nKwiq8pq 8nlZXb4ga8iaspasLevIF2Vd+ZJ8Wb4i68lXZX3ZQDaUjWRj+Zp8XTaRTWUz/ddC/7XSf21kW/mG bCfbyw6yo+wk35SdZReZILvKbrK77CHfkj31Xy/5juwt+8i+8l3ZT/aXA+RAOUgOlkPkUDlMvieH y/flCDlSjpIfyNFyjBwrx8nx8kM5QX4kJ8pJcrKcIqfKaXK6nCFnyo/lLLlALpSfykXyM/m5/EJ+ Kb+Si+XX8hvzv1/lt3KZXC5XyJVylfxOrpbfyzVyrVwn18sNcqPcJDfLLfIHuVVuk9vlDrlT/ih3 yZ/kbrlH7pX75H55QB6Uh+Rh+bM8Io/KY/K4PCFPylPyF3lanpFn5Tl5Xl6QF+UleVlekVflNXld 3pa/ySR5RybLFJkq06IoypKz5Rw5V86Tn8j58oZMlDflLflruEf4rXDP8NvhXuF3wr3DfcJ9w++G +4X7hweEB4YHuW+7vdx33N5uH7ev+67bz+3vDnAHuYPdIe5Qd5j7njvcfd8d4Y50R7kT3UnuZHeK O9Wd5k53Z7gz3Y/dWe5sd447153nfuLOdxe4n7qL3M/cz90v3C/dr9zF7tfud+5q93t3jbvWXeeu dze4W9wf3G3udneHu9P90d3l/uTudve4e9397nH3pPuLe8Y9515wr7jX3BtuonvTveX+6t52f3OT 3DtuspvqpnnkWZ7w2LM9xwt5J71T3i/eae+Md9Y75533LngXvUveZe+Kd9W75l33bniJ3k3vlver d9v7zUvy7njJXoqX6qVFKGJFRIQjdsSJhCIyEhWJjoQjbsSLRCIqki4SE0kfyRDJGImNZIpkjjwQ yRLJGomLZItkjzwYyRF5KJIz8nAkVyR3JE8kbyRfZFJkcmRKZGpkWmR6ZEZkZuTjyKzI7MicyNzI PLz7jBNZnIz2EdOEXkFx3jmDq+n9fQ+/oPf3fVyfG9ABbsyv0SHsoT9zJ+5ER/SO9y4d5dE8mk7y BJ5Ap7Cz/4J96zT2rTPYt85i3zrH3/ASOo8d4qJdxi5rEc5NhRN2wla8E+PEWMVwMlo8dDx02jor 42VJ6zJOSW+EB4cnCRGeHf5OPBDeHL4tiuOstClOSefo3f46Reung1x6z6+hn4Am6h1glV6ddRPu QBJqM6SFkMx7NDGUmbK7G/X9PneTxgPuZo2H3K1/s92npe8pSj9LZKEc+gmgkP/ukXvA6N1DGn9w f9a4zT2qcYd7ydRUmYxHldl4VA8Yj/CVAq+/v0cTre/Wq7DGjcq9pyQdSmJQkv6ekiwoyYqSOJQI itajFq/HrrQw/y2pnChHQjwrniUWVUVVskVNUZOc8JjwGAqFl4SXkAxfDV/V/oQzT/z437TH3rvD /r+9v/7P7LBmD/2r++Z/556ZQTaXLWVr+bbegczO+YzeM6tjN6utd6YR2Cfr6T3S7I7+3tjiL+6K vf7BfvjH3fAjvQ/+fQe8e3f5v203/Ntup/fFCXr/vntXrKifPsyzh//kYZ47auknj9+C5447+qnj Vf3EMRXPHNP0E0eSztqXdaa+ZvLy971TtL933/RivPReBi+jF+tl8jJ7D3hZvKxenJfNy+496OXw HvJyeg97ubzcXh4vr5fPy+8V8Ap6hf50tx345/utilZh5f6lXXfhH/ddlU7FqPR/2H03upvczdiD t/7pLrxP78MH3EPuz+7R3/djlVk9gD350v92V075476ssqisKu6/tDvfszd7Kf8Du3MNS1iZ9EvZ OKsAxVq1rLqUG++UFrAaWy3oEauV1YpKWG2sNlTSesNqT49ZHa2eVNrqZY2jytZEawo1tr62dlBT 0Vkk0Duim3iH+oo+4l0aIvqLwfSeGCrep1FipBhN4/Ce50divNCrPV7jT2WPM9A0juVYmsOZuRDN 5cJclFZwMa5Mq7Hj78aOvwev3vbaM+0ddN5J76S3sji3nFtWVue2c9uKc5KcJCtbSNNlZQ8NDb1v PRgaGRpj5QqNC02w8ocmhqZYj4SmheZbRUMLQ4utcqFvQhusyqFNoZ3WS6G9ob1W49CB0CHrtdDP oaNWU/1skGK1CKXpZ4N+spQsZy2VT8gnrVVRBaMKWd9HFY4qaq2NKhZVzNoYVSqqlLUpqkxUmf/V 3nVARbFs26qeaRh6hiZLFEkimR5yEiWqqKCCYkLJAiIgICZUQDErBkyIipgDmAUDAkZUzNesmK8Z FUwY4J8uUdHr/ff99/77d/21HrWoU90909OnTtU++1RVd+Pj/PwZPiHqKOqIT4o8RZ64WuQr8sWn RF1EXfBpUTdRN3xGFCQKwmdFwaJgfE7UX9QfnxcNFkXgC6JYUSy+IgdhP77KhDMR+BoTxcTgG0wc k4pvM2lMGn4KfnYpfgZ+thy/AT/7HjeKKfEASlYcIh5DhUlWSO5SE+RnyedRh76sb4FotJjMuITg 6OY9u1vswcgFyTRzD2PgNHZwfA0kPi8GVrCGSH6rrHmrDLZuQuJX2Zhjc2g1VtgK3J0TdoJzdsKd wLl0xV2REC/Gi8kqmyoURmvR2rQO3ZrWpdvQerQ+bUAb0kZ0W9qYbkeb0Ka0GW1OW9CWtBVtTXO0 lLahbfEF/Bu+iC/hy/gKvoqv4ev4Br6Ja/AtfBvfwXfxPXwfP8C/44f4EX6Mn+Cn+JlQIBQK3gre Cd4LGgQfBB8FnwSfBY2Cpn9lnxBUEVJkpEFI7lZQIrNZGpAESAeSEGquHWhqgfh1adaQRFCrLsAT 3SAxyB2SGHkjHyRBXSGxKBiSAuqH+gM/HARJGUVCUkExkFRRCkpFamg0GoPU0QRImtA7KaSFFbAi 0oY+qoVaY12si3TJmoY20F97ID3or/2RPpnVNSA91RDH43hkRFY5tMUjcBoyxuPwOOjT0/A0ZIpn 4JnIDM/Bc5AF9OA8ZAk9eBeywhW4Elnjo/gYkuJqXI1syXiTHel5DoRT+5FRp0Fk1CmUjIVptRgL sySrqVypgVBjrSkpJQXm6EA58PeIUd5wxI/yA+bYi+oFzDGYCkY08J8oJAPMZygwx6nMdCRiZjJz kJhZy6xDiswGZjNSZi4xl1Er5ipzA2kwt5h7wKnTxeORPniRSciI9xDIFDzESmTO4zmyBjy/hKSA 4jeRPSD5LeQAWH4POQKeP0BOEGM9RM6A6Y+RC+D6U+QK2P4cbPWzLlZEly5UHOii+4MuzpQzHOE1 ElA9IKYREo1oopEM8Lz+SJboJQIWNxzJEb0Yopc80UuZ6KXKFDNbQaPtzG6kTXTUIzoaMA+Zx8iY ecq8AL14Ta2IplKiqQPR1An84BqIE9ZBtNGBaO1DtO4E/ukt6gre6TNEKF9mX/m7HCOJRta8jvyT 9pBLs47WzZ8xgd47By/8to/CG/FW2FL99jnoAb+oAzcK6o3UhJDYlib1IUPqQ5bUh4jUhxzw3hDE kFoRE2tLSN3IM/2YfoiFyHw8UoDoax7YPJdZinQgBtuNjJhSphw5QCT2Arkzr5j3KAo4xBQ0DNjC HDQG2MFmlAW+fxdaAL7+KlpGbF5KbL4HPPgdtJdYfh+x/H5i+TJi+QPE8uXE8hXg2V+gSvDur9BB 8PCf0SHw5zLoNHAcDXQJeI0+qgEuY4Z+B1YiRrXALpTQK/DxWhABABJChDQcIT6CRJ78KAPqya+2 QYHisRIfdBq+0xov+Yc/R552+W/69Lf2gMKJVTnS5nu0aA/c9/aAgpD7t30U8iVz96rfPkchAZPP rIbfrGCqoI03iPmeA3tJlP/lSvTJNXDNV/n1Wl0Azf4JdIdvqhEsRAQLMcFCAcFCIcFCmmChDMFC WYKFIoKFcgQLGYKFYoKFEoKFLMFCBYKFigQLlQkWqhAsVCVYqEawUJ1gIX9v80HQQEJ1FuxFHf9y LojCDFaGqzTAZtgGu2BP7Id7wdWF4zichNOAP2XhqXg2zoVfLcBr8Wa8HZfiA/gwPoHPQt3cgHp4 hGvxa/wBHJAMJaGUKQ1KlzKizKCOHbAZaG8CdWFJZH/wwLwMwc5EDsIuRA7GrkSGYjciw3B7IsOx O5ERuAORkbgjkVHYg8ho7E1kLPYlMh68Oi8TcQCRebQ6L4W7aQ0iS2hNXrIfRWJe0ioiCS9lVovk iSwTsUQeECkQ+VmkSGSjSInIJpEyL4FBqRDZQQGT34nDpoBGCsA1KNiygLw/MA6evwAmgZbQEkFH KeSh2AbyMGwLeTgGLgO62UMeiR0gj8KOkEdjT379CfaCfCj2gTweOAsFWnWGPAl3gXw49oM8GXeD PA93hzwf+0O+lFZFFOirBnkJzY++fBSBYUBTaNWgpxDyMhFwHtBRhl9RJZKFvFEkgrxJJIco0A0Y mKgDMoW+NRB8fjz4+nQ0Cc1EuSgfrUab0U60Hx1G1eg3dAPdR88AX5rnFKElaUBbN4K2xGEH7Aat qTP2x0FQG6GgVTzeCLWVBzW0icgQvJnIQbiIyMG4mMhQvIXIcEB3XkbgbUSG4e1ERuIdREbhnURG i1rzEnTU5SVo2YbIMpEekQdE+kR+FhkQ2SgyJLJJZMRL0LgtkR3wcmK/FcRyBcRyK4nlConlVhGb rSY2W0OsuJZYbh2x3HpiuQ28PUSqpMbVSI23IjWuTmpcg9S4JqlxLVLj2qTGdUiNYyRUQGRluYBg BSI9HSvwt4nwTxP2J+v6TZAN4QFkNAy3Im1NnbQRDf63+bNgzW+lGL4l8dgLeLKQtBWS87N0WBEQ CmE1iKswQSKK4AvvVzXQNNwbB+N+uC/ug2OYvuAB+38Zm6ZGUOOpqdQCQZ5gg2A7+4n9zDayTYCy y5jlzAqmgFnJFDKrmNWAuJXMQeYQc5g5whxljjFV7DuWYgWskKVZGVaWFTENzAfmI/OJ+cw0Mk1i gD3xXPE88XxxrniBeKF4kXixeIl4t7hEXCreI94r3ifeLy4THxBfE98Q14hvi++K74t/Fz8SPxE/ E9eKX4rrJLISkUROwkjEEolEXsJKFCTmEguJpcRKYi3hJFKJjcRWYiexlzhIHCVOEmeJi8RV4iZp L3GXdJB0lHhIPCVeEm+JDyth5VmWVWZVWFX2PdvAfmC1WR2Wnwc1JpEnItEmDayrK/i0OCoemEMq RJUSahxElfJk3SxLYkgFEhkqkvFfJcE2wTakLLNFZitSkSmRKUFqMu9k3gFnhHgJqfPxEnCrGuYB MuWjJmBSU4E/uIiLgDl4QcR/FXWDqP866k74gz/hDwGEP/Qg/KEn4Q+9CH8IJPwhiPCH3oQ/9CH8 IZjwh77iRmAO/SSKwBbCCVsYR9hCBqsGbGEi6LkX9f9HLPrPWfDfYqevFmJIbSJSm3KkHpVJPWqT ejQimlsSzR2I5j2J5kGEJwV/iT5p8rZBKPshfmzZE+m2bP8/t+I/b49f2g6cQYm0FERaioBYWIbY kyX2VCD2VCT2VCL2VCb2VCH2VCX2VCP2bEXsqU7sqUHsqUnsqQV2U0fazVcvptkWV88C523usXyf J+0UkXaKSTulSDsVNH9XQiu0+K4GsJJvKPC1pxPkIL2AtGSatGRZ0pJFXyJp/Aq/xR+b2YAS1YrS pgwpU0EXOoKOoofQsXQKPYIeyeqzhmxbth1rypqzlqw1K2XtWAfWiXVh3Vh3tiPryXqzndlBbCQb zcaww9hEdjg7gh3JjmYnsJlsNjuVnc7OYnPYeWwuu5BdzOax+exytoAtZFeza9n17EZ2M1vMbmN3 sLvYEnYPu489wFayh9gj7DH2OHuSPcWeYc+xF9iL7GX2KnudvcU+Z1+ydexr9u1/7vT4z7rP/7U7 PRSB80fTKuxH8Pkd/qF17dATcZzMjRarkEX8Kp1va3z+m3U631b4wDmo9tSgFiMd/J6ugEDfxgvw a/QOOLo95QSf8IJ9AVRPqg/VjxpIRQJWJQHqjePn1X6V+Lm0lgnO8mNy+mPiZ95aJn6e7pfJ66fk y8/i/ZAC/pj4Gb2WCXT5kwT+4IcEOv+Y+v0qgf/4IUEt/ZgGkfR9O/KnNARS3J+kpF8lceOPCbzW j0nzp2TwY2rW78v1kjP8Z3zkT8ZHMKoB/+kGvr4zsOwg8iyWr09g4Z/GMh3NQQsh+ilE61ExxD97 UQU6ChHQeXQF6o8j883/09zpn8oD/pn8l6MgX8ZIJCAW8nEP8uBjAfB1rUj0wM+zYGwKcTQF3n4B lBfiRVBejPk3iC+HyIvCu/AL/im0+BXEK3XkPRxv8Fsov8MNxGd+hPIn3AjlJop/CwpFCaHN0ZQM lGUp/smtYgrib0qevFNEkYIYm1KmVKGsRrWCsjr/jhDwq9pQ1qH0oWxAQeRGGfFvHwEfawplM8oM yuaUOZQtKAvEv1XFEspWFP82oKXUUijnU/lQXkYtg/JyQSfyJNkuSCDwo1X4Z9XRoC+tRfvwT1ek OyEB3ZkO458VTsdCOY5/MzH46pFQHsU/tYrOprOhPJmuQPxbliuhfFAEyCyiIIqkRMZyQxGWi5cD pic3TH4DwvIb5SHqld8kXwnlg/JHoHwUmCpmdYFnCIBNNpEID1BZgVLQ/3KfNbEMhcKb7w7+zkEw 4SCYcBDc4i5WTDgIJhwEEw6CCQfB5N4TTDgIJhwEEw6CCQfBhINgwkEw4SBfrpAiTAQTJoIJE8GE iWDCRDBhIpgwEUyYCCZMBBMmggkTwYSJYMJEMGEimDARTJgIJkwEEyaCCRPBhIlgwkQwYSKYMBFM mAgmTAQTJoIJE8GEiWDCRDBhIpgwEUyYCCZMBBMmggkTwYSJYMJEMGEimDARTJgIJkwEEyaCCRPB hIlgwkQwYSKYMBFMmAgmTAQTJoIJE8GEiWDCRDBhIpgwEUyYCCZMBBMmggkTwYSJYMJEMGEimDAR TJgIJkwEEyaCCRPBhIlgwkQwYSKYMBFMmAgmTAQTJoIJE8GEiWDCRDBhIl+fUfLtiSXaKSBVyV6k PZTL0h4iI2c2ufPkd/JYlirI0u4Lu4IojKViTk6GNmcFlBaNuDAZxlwGC3GWI4WFBYFcT86ixR6d Qt0MHTKl5IYCUDhKQYkAolEoFf75KSZ3Tr/FyYSq7WRXBTjVW0577Ik1hj+dfu2x176zBVmtzLgs oTKXRX0oEFCYAnCoRDPc3KYqnXN/G/HsVkdO/tuVYiFcU5LUnDOVEfQWilUMvBKTRifHDolJ1TOJ MNWTOjs76nWPjUhOTEmMTtXzSkxOspLqcjpfPqz245HE5LDU2MQEqT7Xhj8uUNH4frxXYmKqnseI 1JjE5NjU0ZyuuryzIyeVcpwjB3/91eVtOKmNrbR582+4oixs0LJa+DdVZQGswH6GysIYbaDKKpN+ d63z1zZZsWjUIO5J4YZZbQe/b1zQbVVJ47JCPff0noVLC3NCbYae84wcXbs57XjQtbqn+ZN1clZM it5xZOiYcMNLrd1qFPC8RwsPl1tG5+XFGC8562JRLtnV17jS9yHj7rTQYoOJ8/pnXSZ63puksC8v vnfY5qz0laGWI7s9XrIz0jWvh45UZKS6YsPDueYav7dfHKEa2peOWtHasdeUd+te5FJHtS+U9/bZ MS2j3OVZUK5/8ed1Y4al+m/RqF4oZ6KPgueExjru66os69anacDH1dGMaO35zD7BL3a7DmqVOVJ4 7e2B4owFjVtPTbi0Tit5oNuJ/S9Fqwy4HTLZx3fojVTJvkUJoOGvylzPZa7hMguhNltjYWYel7ko Q3HA2aQXscnLDXuOV93efXbTyZXJ//f2y/qLNi7gbbjgkbhiVv0iDfvnpdjoykil+oGhNiuWi0+6 03On5hx3+V2/7mXwfItdBZ2qwl98ulzt6tp/g0NQbKPRsA7HqzfW0Ok3pbPar1BMitvXqBygEVvx 6azXPaX+egFPwsdu2ahZZe7Y1vJA1Erl6W0VIla9C9Jp0D9+Sa2+1+YELxvZz1nq7x8MiZfv+bbs Va9jZQ8Pc5/0pHJTWy8w1ep+sTW15lXGbcHOAa+33awKro3qcqxX0O6dAhPlpjmXXopyxpcuOrLJ 0eL+mPvrR95LK0Bn4zpUnneYfttDeb19nHbcdfs7v+kI76/3EVb1t3VK6K4jH17CFM68cDGog+8p nd5rk64ru0yZP2LFuvMFgAqhXJag2xdUYKw2Kd3o0TRw2cmKr5jS+u8CA+j3TjbwBwhgA2AgtYFN +69gMJogKJxERoXqHShV4ZT4DZEKExyWEhObMCQVfkaRY/mdsiqyvaIihyUmRH69MObPLsyQ0/9y YVotj0dG6QXGDkmAs+r18PL4S1QoGT3uUsgOH+f1dpul1xra2ncZWfGxzfJjPsNfnPN99NvMQ0O7 9Qp/vYQ61P1Kl3hrI/eo8tOGJeLOJRNG3PQp25jD9jjS1ryu4KG8YZtzHkYfwpec0fRZM9+vzZJT O6wNDvlZpideVdN1nems6HyzzPR1tKsltmlqbNd57a54PCX/497tEROyGgYWZE7Knr21rjR31Rmn tT2y1dtN8b/JvUXtXx9taJ95YPLzeOd1VnZvd1ptYcaFzx0Vnb84RX7ylrrD9Xp7ApRnRZy0uGrj o1m7z2+ha49AjdPRPUdvLJpS1cd9RVaPqQn0NvvKsUZlvaLbL/GvNh9vmzCpk8y55Wf9JlMJk9Hq iim3AptR4QOX+Y5T4UGhrVDCMTIicGg0LSsQ/P+ACgX+GlX4107SnAAE15rfwQpbCVWrW59OQ0kD try6dtg/r6e31SrviJecmD+sIBRCN5rcousQjBm7qXi8n3Hd6f3+qYV926Wajdgx+fOmbrmjUPfH J55q3Ig9wham11NeR09MqX4fWH1wRVmfxJcR3hu8Ue3CqryLOqXiFZryuZev6RaZjnvxfG3K5pwa 59ntF8ftdxp2fuoWw8+3Hl+KlZs7tazxDtpnV/8uvUFR2Yp+arpwvudQk+ElTjm3ZeWPh8ScKsvw GBq9fl/Jvtl2J+oEiulj3py/7XlrbOOdO5sb3966KL8j6dK8ewG7nQrTLX9rf91OHO5IrciMM5z2 dmBEztb++5wvh87sPUnL9o3r4oIsSeHgGTssSlauObnpmt7uck4zW09V3mx/r9cetwdx9+aZxE6p TLpbv27T6QzP5DQWMCYOMKZXM8aEKYzqThiSoGU/ogFn/sZe/RVwbDkOEMcWAIdz5mz4TVt+k0v9 t1xa83HBnxz/S6wpvM7MOnOwssvSUxtd7IoM+w29Hn9A36Akt+pJcfnRi8YHbZRm7L8WYvHRoY+u mnlxjvxN1VUJJt0mtOrgsXlWx22+U+WvZuYWLZI5G+ydNvDJq0/s3Qmpq2xPpj54cS9s5XhBiU/T RXfli1tPDJI/O7auREX+U2icSfaImSVF+7Mfqe+cc+BNq93hIc+VbrnU6g+YsSUj5ZDPvQXTRoYu fVg0stJxlq2qtcr18OPFWhsCFg8p+k3PmRt+e9YQ37tHdV7L90j1sH5EG8XpD+2ydd7h7c7HPNcM G6jhtynn8uyJ7qOYTldWb59keOhu3djobX6pZcYeXfPDVEP9uaqs+rPipPTa3t1Hnhf1Tstsxpr3 XOYbUvetFfgeC51QpqJFh63X7zg7vef7oK6LH6hfjptoR1sZP/o1NPE40dpQqMG1yvh1N/fmP9BG 2J5z5ZwLHAvsJ9vGpKYmuVhbRyTHWw37akOriMRh1klDY/m91knJiZEjIlJTrL0CoaFZwS6u89ef BB7ixrlwTl+3OWqyRfMJR44c+asTRiW3OFPqTx2IoE3H4MTAIcv1Jtph9nf1rm5FT69kTqiVH506 MmBRJ416pBY7/nr4nMLPQ1bm3zcx/dD78pLGHuWD5HbsWfs8q36xbmK/D29e3ZFcmCFyb6Wud65i l08nkXFosFzX3Jei6r3dE17e7axsYj9DP/nW4N1bYpWNcmsf28ldH5+QOI/pdcKsW5eNNhaTH62s DjHev9/t9oDtE8V77XUCJvl0atqXu7Kf7IaFN0eVBU9Ys86/uq4oP8/j7smBRu43Jth18n97pmrs sqe7j+dHqAZuKcp7cbn8TMHKTQtOjDGfYlFx7OqneMG1cqeiV+cGaqorVLw7kbFWUaR1c47hw60r u7k/2apkPIqttNizeuixHDdAm2WANtlf0aZL+nOCNvTfhzZBscOiUlLDhiW1RBsHzlnqwEnt7W0I vZGSTRuO3+Qy1/5brq0d1/aLo9RN8IpNiolK1vMO9NHzCfR3kXLeTpb2TnaOll6evk5fPyhQ0f0T JQKjktNiI6L+EqCe7KUjqq6OLp7k7b5mx+Hn3ZYb3XJO05W7ZOPXd9R586trZOe8eNj+Y5lx+qqP D8aNtzlztf0MZ8e691dc7Vr9Ni/ro92zmOxkrZzbpd1ul2bX2zJUZWFain23kFcld/zGtS7NHXW9 STdbzdN3+OkJ7YKVz00McD3zoebtjOcd0L2LNWEN6rO6rs50exPb8cmdaeWyAXtTxz6WPOj0ZFP8 q4tDMkXvW50Yp7Iv5a5ctw/hH58XOOe5ND5VqgrTDe97hQmaeNG1a9e7vcusQ7Vmz6O9roU8zWIM F8kV0NKoGfP9dT30C+fN+ezj7ZNov83HsSh2Q1SDndc29YOuzncUZ9ZpTbkX1KON6zJpUUuA+g5I 45NfWnXoY3q77buYUvyp653xZ+65/4A9iY/8OyzaY7ep6+Sc/flPNrt6eB09+y9hT2pKUkTY/wr2 fD1T6q8QVPQHFP4FQMWOyZKTtDpXc8Z3mlX5ObsxmRPamXiY1V/Qn8cuKhocOMi04XllkN/6ce9U zopVG7rXTVZDCfcmtjbxWWfhbHMzMc+xf61hr5wgwawO6/Ijnd46VKl67XZxX3xc/tDwTJP66HXS uwNDchp69boz8On8Octi5bpNO3curZudfNyddO915gMmBk3wMdJse3i675G29zQzYk1V36offWlg kek7yPx1w9qjI90NExvWRmbPLgyX32Cpu/7BHPcJTVtnf1r07NVn4ZZTXU73T938oV6ljbbz6VU7 L+1/vbO2qqiuj+5Ht1dVl8y895fndxgXrXFqu14Ec6Jj+ygbzfTtpe0rjTv7G2guSZjJVb6a+yNA KcaJlwRUoLablK77tOk7ZkjhzzD19wRfzejE2dk58ujkDJt/Q/D1B+D8K7y54ZjwcUuVp99wjarT nd0DKz5sUt1rYbNPOaBX1cTn7rZXu0jnmeyeG3m7TY9Jew92PTeBfv9ixIEZx9ZfLI5Nih7VLvrR 7pIX2XtO1W78rLxa3M/A1PpMx6t9hNppu4ZFDvMLun7zVU35ionHMm5N6EY55r6pWC7qoxvT6dTV irSB1uN2txXu7DMgTieiKSPdrfaisG1355GpsiEHB16Z7Ggx4jj7RNdZLj2tcVl8wpjbz9xzFi0f zg42C9AID7VZfn6iv7nBwBifGTXWkxR7bG/YpTUrvrbtUpX3JxUvZ7Ovs9JSHI4uGFNYHSrzjN46 2bbkfe6ASR6T+mbnJmxtY9G5OjHf63bcownGs4d+wZssbAI1YvTrHvr/IvxSlJFrHgBVw3xMhVqg 5y/BUfPbF1QpoUSXQYFoBApHXsjjx9DsD3HdLwAqt7uS9GB6j31Ks1eGyWJ2ZpLPrBcpQWUd5GjL ptKegdk6z53nlqzqI66ZudtV+9zHzeuOl2zrqa+dKIodP1RQaOD7PH7nsHSDUt8Lk+pnKRyQne5Q +XT846QQnxXzzlefvjm74k652an0Z8eLbS5O2XMy4rDDOQ398rQa17wd2inL9ade2blTOWjm6/yD UX55Jsb5odMVXI+pRI3qvO9M0USXgK3hfWu4x4+dW9+bVnfNObNBRX9mZEaEjHBhXR7lZT3Wd+re JupqVINfzTVB6vwddIKketkNk7D0zq/U85X0nSidKZtljiy0KX3Q8Whg+7IN02oeRTvOem2wML96 68igni6Xkr23G76VZgm3AEhtojDmMqf8jVHZD7Hi9zHugsxrnOo3e5tgqayAJquX+VbQbEw5gVTS clgdrub7lljKci2PqnGG378olEIbe5fjJ5vZdW7NLlFej63Tyj+bBMzdxUW2+IpE2ocLKjDLMEHd USyKQMkokYzMR6NUpIeC0GiUBFtDYH8YlGLQ6JXGGUZ/6l5TRyclDkkOS4oZrfcTvAmzMNIr/720 nyZyUc3Tmtr9dP2CrfnzOxY+YW2DhbVOKb6fPm0rXvLiNndv/PQ3T18Lxr65OLDhTeqyDHHCjmvF 1oIEYdITwaW36tMsKyYtcFxzxn1SSDA7+vgVzSvln21nLL+xQ6+wxPfpnvErnm+pcD/6pNz71jmP /e8fq2pO7/pqPvY5M9hWMmNC8cxVXrOqPvk3RRTNO3RK2q53ys7QkrnCd8fl04o7jyqm8jJOFM+1 czA++nukpGA2dXxYm3HF4/vYH76gkr7d02DBkjNj/JPSVhWbHzF4OCblckhBzsoXwQFSylwxzftD rq9OeK7K2Jz0+5MMb69a6u8oPNoteuOjNdfW9DUcN40710Z1ZRbVhsuitL/bSEaaRUlgl+j/vIn+ 7JF+CDBkm5toQQin0bIlir/PAmH4zW9HaKkCuFonKWcDjtbG2da+/x8aItVkxN7aHTYrxGowN9VH 682W28/e/4RZfBO5teiQn8jyVulx7bVX9eljkmfRk42aPKkzXi/LqlbqpS28u//O/NnKHe8amxWu nTsjbKZGQ7XZth5aU96Pnfsk8EjHR/ssQ3JOe8+LTOgT2tZTfGwyleFRa7Bk7BGbMT1q46fe/+Cg /ubojHnhrYPyfnugorzy0rLid03BLoJOjy/W9q2PdvcY0nVQyYGyq9mW94NLq+ZuCh8e12Gdiujg GfPqETVLpo8elTSxyDfv4I6J0/w7uZhPDNS3Wd/45FiH1DSqonhjcmBIacyx8U+l7WPy2mXU75TZ +vBCqZJF1vn48i23hm9/NDF8/W6cxl1jOwZuH0DXv9vpEEkH6qvNGOKboBg3rJ9Kr4Sd8ui/APzk LRsNCmVuZHN0cmVhbQ0KZW5kb2JqDQoyMTYgMCBvYmoNClsgMFsgNTA3XSAgM1sgMjI2IDU3OV0g IDE3WyA1NDQgNTMzXSAgMjRbIDYxNV0gIDI4WyA0ODhdICAzOFsgNDU5IDYzMV0gIDQ0WyA2MjNd ICA0N1sgMjUyXSAgNjBbIDUyMF0gIDYyWyA0MjBdICA2OFsgODU1IDY0Nl0gIDc1WyA2NjJdICA4 N1sgNTE3XSAgODlbIDY3MyA1NDNdICA5NFsgNDU5XSAgMTAwWyA0ODddICAxMDRbIDY0Ml0gIDEx NVsgNTY3IDg5MF0gIDI1OFsgNDc5XSAgMjcxWyA1MjUgNDIzXSAgMjgyWyA1MjVdICAyODZbIDQ5 OF0gIDI5NlsgMzA1XSAgMzM2WyA0NzFdICAzNDZbIDUyNV0gIDM0OVsgMjMwXSAgMzYxWyAyMzld ICAzNjRbIDQ1NV0gIDM2N1sgMjMwXSAgMzczWyA3OTkgNTI1XSAgMzgxWyA1MjddICAzOTNbIDUy NV0gIDM5NVsgNTI1IDM0OV0gIDQwMFsgMzkxXSAgNDEwWyAzMzVdICA0MzdbIDUyNV0gIDQ0OFsg NDUyIDcxNV0gIDQ1NFsgNDMzIDQ1M10gIDQ2MFsgMzk1XSAgODQyWyAzMjZdICA4NDVbIDQ2M10g IDg1M1sgMjUwIDI2OCAyNjggMjUyXSAgODU5WyAyNTBdICA4NjJbIDQxOCA0MThdICA4NzZbIDM4 Nl0gIDg4MlsgMzA2XSAgODg0WyA0OThdICA4OTRbIDMwMyAzMDMgMzA3IDMwN10gIDkxMFsgNDk4 XSAgMTAwNFsgNTA3IDUwNyA1MDcgNTA3IDUwNyA1MDcgNTA3IDUwNyA1MDcgNTA3XSAgMTA4MVsg NzE1XSAgMTA4NVsgNDk4XSAgMTA4OVsgNDk4XSAgMTA5MlsgNDk4IDQ5OF0gXSANCmVuZG9iag0K MjE3IDAgb2JqDQpbIDIyNiAzMjYgMCAwIDAgNzE1IDAgMCAzMDMgMzAzIDQ5OCAwIDI1MCAzMDYg MjUyIDM4NiA1MDcgNTA3IDUwNyA1MDcgNTA3IDUwNyA1MDcgNTA3IDUwNyA1MDcgMjY4IDI2OCA0 OTggNDk4IDQ5OCA0NjMgMCA1NzkgNTQ0IDUzMyA2MTUgNDg4IDQ1OSA2MzEgNjIzIDI1MiAwIDUy MCA0MjAgODU1IDY0NiA2NjIgNTE3IDY3MyA1NDMgNDU5IDQ4NyA2NDIgNTY3IDg5MCAwIDAgMCAz MDcgMCAzMDcgMCAwIDAgNDc5IDUyNSA0MjMgNTI1IDQ5OCAzMDUgNDcxIDUyNSAyMzAgMjM5IDQ1 NSAyMzAgNzk5IDUyNSA1MjcgNTI1IDUyNSAzNDkgMzkxIDMzNSA1MjUgNDUyIDcxNSA0MzMgNDUz IDM5NV0gDQplbmRvYmoNCjIxOCAwIG9iag0KWyAyNzggMCAwIDAgMCAwIDAgMCAzMzMgMzMzIDAg MCAyNzggMCAwIDI3OCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgNjY3IDY2NyA3 MjIgNzIyIDAgNjExIDAgMCAyNzggMCAwIDU1NiA4MzMgMCA3NzggNjY3IDAgNzIyIDAgNjExIDAg MCAwIDAgMCAwIDAgMCAwIDAgMCAwIDU1NiAwIDUwMCA1NTYgNTU2IDI3OCA1NTYgMCAyMjIgMCA1 MDAgMjIyIDgzMyA1NTYgNTU2IDU1NiAwIDMzMyA1MDAgMjc4IDAgNTAwIDcyMiAwIDUwMF0gDQpl bmRvYmoNCjIxOSAwIG9iag0KWyAyNzggMCAwIDAgMCAwIDAgMCAzMzMgMzMzIDAgMCAwIDAgMCAw IDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDU4NCA1ODQgNTg0IDYxMSAwIDcyMiA3MjIgNzIyIDcy MiA2NjcgMCAwIDAgMjc4IDAgMCA2MTEgODMzIDcyMiA3NzggNjY3IDAgNzIyIDY2NyA2MTEgMCAw IDk0NCAwIDAgMCAwIDAgMCAwIDAgMCA1NTYgNjExIDU1NiA2MTEgNTU2IDAgMCA2MTEgMjc4IDAg NTU2IDI3OCA4ODkgNjExIDYxMSA2MTEgMCAzODkgNTU2IDMzMyA2MTFdIA0KZW5kb2JqDQoyMjAg MCBvYmoNClsgMjIwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAg MCAwIDAgMjcxIDAgMCAwIDAgMCAwIDAgMCA1NTIgMCA1NjIgMCAwIDAgMzQxIDAgMCAwIDAgNjYy IDY3NSAwIDAgMCA1MDEgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCA1NzAgMCA0NTIgNTcwIDQ5 OSAzMjAgMCA1ODAgMzAyIDAgMCAyOTcgODY2IDU4NSA1NDAgNTcxIDAgNDU2IDQ0MiAzNjQgNTg0 IDAgMCA0ODNdIA0KZW5kb2JqDQoyMjEgMCBvYmoNCjw8L0ZpbHRlci9GbGF0ZURlY29kZS9MZW5n dGggOTYzMzYvTGVuZ3RoMSAyMDIyMDQ+Pg0Kc3RyZWFtDQp4nOx9CXwUx5X36+45NVfPjObS6OjR 6EIz0giN0IWQGml0ITAgDms4jAZJIHEIIQlsHIOxMUcEAZvYGGMnsROvcbxJtrGz+SCHTTb8cA6z X+JN8osdZ0Nib+wkZpd4fX0xjL5X1T2jEcbOsd5kj6lS17y6Xr3613uvqlpiAAYA7JiooCKypLP9 3g1fDAAb7wdw3dIeaW1zfEooAdj/EwD18vZFC5esPfHyYoBPVAATf7R9ybLm1nPr4sAe/CHA6N0L l4Qqu585HQZgTiPX3r7NsRGrxnEBwJ8NwD7Wt31caPhpLQswS8C8sG5k/eY7HSFsX3gOwLhgfWxs BDLBj+N9G/vz6zftWLf1xVldADUiQO4/Dw7E+n+5Y+4+5N+A9dWDWKB/SR/E/DjmCwY3j9+y7ZD6 EeTtBvCpNg6MDvtOFqwBGJGwjbRpS1/sN8++chZgOY6fdXhz7JYRnjM+g3XHsb8wHNs8cMsP3puH c+kFcHSMbBkbn/zEiWqU53FSPzI6MPJCxY+/AVCZCcAZgWCnfutbfPs3omssDW+BQQcknPnV8Tnk 89m2wUPv5F19yKDR9QIHemBBDthPeyJeB2DwvJN35ZMGDYyDZ/J+SAaugbQxtcFcXBcSWOAhBOuQ aDYukJuovsR+HdSgU59QI4LwkPzJvAPrmDhrYVU6Tq3SZLCqi8BOiqBak+C9YIkggA+JhzV18Tom pj3BPCsA8xnK9KJ6GZkpcOoIPE1F/Zb8JIJqA+ygn7tAAymB/dr0vOYQsOouUKvXy+2T/dnJdyEd /lsF1RHoJJ/cp2EBobmrMJ+9e1JL6z4HYXYjNCXasr0Q1vwrNKn+Dp9umK86Ovlz2vcxaOImJq+w v4Ytqi/CeKI997PJ5/7S80mHdEiHdPjvEtgAlL+v7GGI/TVkSYd0SId0+J8SuCq49NeWIR3SIR3S IR3SIR3SIR3SIR3SIR3SIR3SIR3SIR3+KoGlf+MBkAkcoVgADfM6LfmdUjMVGGwj/4UH9we4yj05 5jWu/k8Th3n5fUXkry50Cm1UPnmwgk2hnR/Cbg8+e2Ef7IcDSE3AQVp6GI7A3XAPHEX6XrgPjoH8 lykn/jRZ/yrhDyH/pwUVPIZpAQhIkb/D0YMJ8qEeWqAVOmEhLIEYrIMhGIFtcAs8PDlJe5FWQrLV AtqqDwZhE4wqrZjJ30++jav5+clvJSLyTcbJvqRu5X74bGUNEqMDa25avWrlimjPsqXdC+Z3zevs aG+LtDTPFZsa5zTMrq+rrameVRWunFkRKi8LBkpnlBQXFRb4831CXm5OtjfL43Y5HZl2m5W3mE1G Q4Zep9WoVRzLQJBxS+6WntYNkqelVzL6I35ekIw3XF4QksDm9fmtQjgULVNaSeqABPYuKXNRzykQ a6OSJnBtkxskrpB/w4edF3iFVklViD/+ebF+qaS7x+fnf+xN1kexj5TV0uPzeSW2EH86sQp/5sWE folfhOU+r1zSKcGiHvKcnvxlLRZCrS+KaXePlJvIRqPXE/IMwOTZa8S8gZngTxk9LREJMk+B8ZcS OEizy7UgQYNUEkBBeKQoNwhJTOYbEmOXGMcCFHn6EKTbxdrrYNDav8Hf2j+EiPb3TmF6WUbUJ0wI E9091jCSVOgu6duLe04ZMlr8LQMZWAC0AE5lGLDEQAqQxcgpxtjIUII1ttafYkFnQvhsRNxW8myQ xIO9SPgjiBvW2KdqTk+ePZRaBdgtQdllShZC0rRIWlkIYUgSYxIcFE4Fz04cOs3D2t6Asd/fH1vV I3ExbHAKuMLWwaVSdteiFViEQ+HTOyiQ5Y7QhCye0DooTGCetO3F1B8hiz6tvH9woJeoCdPrj2Cd vqVnv++sV7LhZ6tkDUgmbGa69RUvN9HqHhJIdmJivyA9jOKm1PpIikrgRtEnWv04GjJr3dBMliSU XDaqjZ39dHHEgzFB2r12g6x7sUMJ/fdN8JLxbR+uDq4P9qQdFSj7ezcQkTfEyDRbNwgTBwfoVA/R qaG+Cq0bIuQhHVH7YRn2XtHTOuhvnRoQJ44EV3htX59P8gRIx4mJViJirB+ll0XGiin5iU14AwzK 0yKJS+kHLKVrgCOKsUhUKVIarCDdSE1vJBr1yeuOTSVt4X51uV+YIBy1hVJmgPedw7qzZcGu7p7W iJfOXmJbeuZccnsvId21KFnMuLHNROiSV8aoa4m/a7GsBYOJpHepbMBscuWxqdKecr3g9l6Q6VU9 bf623omJNr/QNtE7ETs9uXutX+D9E6eMxomR1l6Bmj+D5V896JXaDkUlvneQqacrRNgJRPfaursk ++KVZKnahMGY7Dia/L5ar8+abLPog6oVm0PtRxsgNjfBv46yGdE7eYU24mpOo4fwSnwtMVkUaFkP 2kQf1V+aoK0sQeZeYjVctLB1aIkCFmqmojzEBy5WSpGJz0fs6eBpEdZiRtq9uEfOC7DW+ySIoQCu Yy+pOZuocSwjNbsTNcnuvX5cN3fXkj+g36m6PWH124S6EMWfut5+6exSnOO7tZKuVll6e0sP52UV ivVyhMoIoCtrkFwB2pFggh5zgvcL3/dLfEBSt/Sc9TZEBd6Kro7BNh0BYkHoUb/v/w5D/Chk8hLT IDFOUg7oV6l751y1WJlUJKF1olfRtNRpKZtB/+D154ZteD9Ozyu3t9r8ZIbPUfemeO3CNmJXXp/c Yl5UMhPfLJlfpwnK623pEdAToeUupoTQKgySxZaE3gh1CVFvavHpyYu9EeICUWTSxKuoOKYytNN1 rSz4xyr6blT0Ow5FB+uRi1iKMxBm4bDUWpb2KCjVehWLImN1kqlMr0+imGiDi4+G55Mqsr7jRkXN cl+KXg/yrqXTcimD0brapGdY2iO1BRLM5Xx7wJua7bimujNRje5jp/dWso2w0HzKzxxYfEpkDixZ 0XOGBxAOLO15kmXYlt7m6KkCrOs5I+AZiJaypJQUkoxAMtDFILcnWR1t7z0jAuymtSpaQPN9pxmg ZbpEGQN9p1m5jE+UsVimkstEWiafKlrdgwhBjx8XvV8SF/XcFh2c6I0SsMEpKyBqtr8RJNbfeIph NUYpwz/QLBn8zaS8iZQ3yeUaUq71N6P6o3EIxNQnev1o/uiAe8DLRIkKE3VhC4XTk5PoQS+g5/VJ msJV+KCD1QeiAmrxPGzXTp5eLG6XdvfFiBxETTniyzv7opIuyRCbdEp65KBXOGCLNtqH7ALYqQ+V NeanJBajceyOStEAGbRniDAQBDwPdfjrJU2RzFNdRAYKRSds/kq6nWgKpYzC/eRDj7IRR0hLvJjF waIySFojSt7nx6q+XgHRVkHfElRGVRH5yfDKJQO4q6uKBuiT4VUqQbYggylD0peTvUpLaUM5MsQf bTQqC09z+5UGODYvGVCiohQolQ6IDlZ1ElnwZz+KSpp+k7BZfBq6/begDRKhKSctVkumws4YOhy5 vwFL/LWJzshLR4sIj3NyqZbM3EgPtEtPT5707/ClhLKgH3fnHqKY4MUzpAjRiWsLpJXoOHXXlppo 8cSEznT9DjJeOlPykxSCgLsJAqgp6owdrLVVlWEn8Y6fX3S6sn/4I0w+dpvT+7HbPD94HuntN2Oy eQSTTVsw2Tjs9G4cvn00a3xbpiN7/QZM1g1hMjCY6R0Y3Ls1yzPmvLXF49uBj/ZZ17PsyNO7n2b3 S8yrrzEB8QRT8YD4gPTA2QdU9xxlA+K9jL7P3fdsHyf0mSx1uHc81Z5XWHeaMYprjjOBmk8zx+5j A+77Z5TWae933c/y9zWJdS/cxzx6H3PH7Uxg5y51YNdd+XkH9jKB/fjctVcd2IOPbq++Blq8NQ53 tcMxy2GrcljCDmOlQz/ToalwcCEHlDtOMxliuKXRV1RsLim2WEqZkncnA+/+P8vb75jffMvc9O7l d9mmN5nSgDkYsOT7zQV+S26eWciz4MFZXKzWZ9RZeKtRn2EwarQ6I6dSG4FhjRquP89g6bKwBpgN EW6dfpzbr/9beEz/U4veAAbOYJkNs/VRbqV+OzdueRAe1D9gOaN/EcxnGBNjFm0WL5NjcmuzTA7e ZbKpMk15c82MidwLMeXxCeHThM9n8HmGMYlFmmBDaUNJQ1FDQUN+g9CQ2+BtcDc4GmwNlgZ9g6aB a4CGReGljGTrgq6lzZKdwc8lzVI40HWaE7qlykCXpF+0sucUwxyOYqnEHkC3uFRSHUBPuBQP3CtW 9pxmPKR6L2oVw4DU1bv3E9FAIEfqJ9vw7pyoVEmIu3OieGCqXCx5/c2Ba8PYuPKxbXrxmPRmq/Ru 61BMehfP7G/jgfjd1l7pbX+E1kqlrVKwNSaVYFmRXJYMTIIA5I3cyQDjY8gRf5CW3FITzvNaOU7p yYQXdTeTE2aX1I/nQ++ilb1Slr8ZD3uYq160Es8NzeoJMAOolwEPAZqCqpKkygX8okxPXp78FEll GiDeLdPTg2Yn8Nycycss9pp8GFtY/5iXEDrlof8Q6JkPaNQLWz+QwTA8Dm/9MSNND8xNTBn8Ar6N vfcwHsbMqOANWu5mKpkS+V8H0bALtsH34Pfwefgk7IRBVNE34CLcCS/Bl3HsKSluh2aMACsgI2WU xF82f+U6Ipyj6Us0HYcFcAz5A8pEwm9wjOuFCXgoSSd4Pgz78AG8wvfj6HKYN72b5mnQseO4Pnfg ulyE78KTKPEyaEzKWc+UMrmIxb24uj+BQzAa/xldYxVBQrVPvRRKIAgVUAUx0Z6Zac7XaMwQDAQq zG53RZUYQisSvRUQ5sNsOMdQAlAasGdWZgYMXLisrLoiHLpgqwvZXHUXQhjrSAKh1ReyfpZFyi9Y 60I/+0drnTWMmZkVzKyqRramkZtVVeTPN7Na/6zq6nBlLuvIxIyZczhcDv8sxuqzkoet0ThLC1xF XsvcRqGiwKPvbfh4S1tfY7aloCEoFDm0truZK1c1XOxKLfOq01lYOqvYEwrX+bu6Mwsqc+/MLc8J t80oapzTVuYLFpdka4YfeST+iurEe+tU7/z+Czht9Ek7Ji+rXlAPQAD+AY8yLct6xHwWPB63u4zf JQpZvNnRkZVjcTNOzp2Zk8llHhVz7IAuXszEGpgBLNawmhkaTnNUnKECd1PWpQC4+fNrblptrQuk 5Gx1gQomlHUJUQjz5ytnVnhF10fMPspw/nLWn6/RajRaM0LqdIYrq6trwpxG488vmlVVU43Ihyud qhfEPVyuWBO8qXzWmqLcsCNvQaRr44LCPWLs7PCPXjFmllYc/cqPdqz6G3VV/KXoirLi0pkP9C/+ xy+0LB1uCPcujb+Q7fn1T5tv3Ldj4rk9ogdR1KAevYI+Jsg4FRQF3mRmITc3J6e80KFzajEWcYU6 B8eLemMH7zCRLSiMpMlxVNTpgk7IuZjDmjjByeU4jwqi4HssIlhYhufYYFDLaY8GxWDgsUiQQwwC kOXm6czP4cxDNHv1fAAIKLY6N4J8PsCfR/1l3CFXmN9/9qzVxsiwn6+kyBv+woIoK+PnlPXwVxUV 0VwjhzlfDZqEvRpNorhG9Ur7bnVW9cz3NhwsqQm5hnvXm4vKD2//RXDmjOpZ2QdWXek0l5YJ/FdM xUGzeln86TXz8+NC1pzq+Ib6xuyrvzFm1d04J3682Vi6oJOrm11fWqxplteH43F9vLBCWR+31p7J aTIzczRevJA8FmEsRpPxsYiJTssKYXeIpARBVFirK0xQs3xo06gvdR4+VEAtR5XQxVyN66ekZt6R aY2KKw5OE5RmrjyblevPwiyxTvJLC/LvOhvhlCJ3HZ5QsgvU+jxBqNHpvZzLJRbOqOVqGEHUZ3YI QmMlb6/gwrbKyvBjkcrC7EbVnMY5j0XYRiJtmAhqDSsS46zoKgVwmqgnOE+aYHkdmW3+f4xllLEz qSBoFXSqa/waLePnioqK/Wim19RS7NhXb2BeZH6QApNZAXCVpbYwM1Qdb/xss8mk4s1BW0ypvydV La58g2uZDqaMLfNo5OXblq++8hYbHX1iyapLi+Od0+pTNEaNJ4fPI/JhOKYgX8aonFmqzDJ1poPT 6WZ588q5MpXK6SwpmlEy47FIiRd4U9iMWyiiBAndINBYE+BQagprq00GOuvP4RJlfHanK1w9Xd8o rMXXhxU3/9u+ubDclBNqo2o4QhH73SuXs4N5Fl1ZXoeC5N1JJNXLrn731VNffJ6Z21CXxOi9M+zX uo8MMy2//Xj8q9dDj/yqDXcVdTvuKnZ04SsV/LJMu/Lz8wOZu0QOXJzrqAj2jEKu8KiYkfTrJCUm R3eJ0KWZXpH/0KZRNfHqjSp06bh/qphM9Pfo41HHqslvTXCH1bAs2/rKa8L8fX//z7e+8tsZqw88 eSH++qIVFcGaysbB/GyHcdGqGx/d28H/22sLn3v5u0fa//Xl3t9eOv2xOubWiY85vbWtP759/cfn z9t324PxX8UfAWbyXdwvl+HMZsIvlHnNADwnOAt3abXh3F1mg8/nrSDbWoXKAoyZgzKxTMWpjopl difZ11xY5fSix3SzZs5t3233ct6joj0xL3Sgz8m72TVZcoBA1SHAXD1fyZ+jbjz7P3W0qD2XRX+N OBYVFxGcMed0cf4igivRLnJq0WpIxN212H6Gq+jp2LyrZMm6NbHI3u/u7388OmcPs7x36NbY2mhv xczQovauVUdWfWd1I7OgZyCwc6Q+urSr7YnVC49vbXB44y+PDG7ta9vZ3jy0ff66VcvrKp3ZQg4j oDZ1IuYruMuQDeVwr4J6EFjOaBI0BkNF8V2iw2gKcqUZ+pORDGspV3pMtDoZ8Hu9fs5/XPTy8nSt NqgLK+pDTMkVTuqa7N9z/0wuUabGhUcMxeCKzXgEoXjh/sZVJ/TQkSkfRri7V4ycMBqCtYb47mpT ZNvWeW0bGmf2Hj2z+b5yrb6ybvXdPYGy5o8v9XGPd/BX22eJzrISdfMFVU+spPnI8NCPz9zVGt8l LCxsjnwtfm5nZ8cdX7qf7BQLJi9z30OMCuCbiZ3C5WCYIuEuUceI7pwORvg7cgXlQcAzskrPQb4q n8s/JqqcDpvFxVg5V7Ytm8s+Ltr4accsW52S+TFmVmd5LkxZqHyKq/io2UcZFz2vyQc2PLJRvdP6 p5BEINl3Fg89v2v90U6HxS0EwkeeWt/yUEPtl9lgYN6+FR9v/Rijv3Eo2vO54RuXN81Z3NC2bpbD /qbD2TH3ifjzo19vBEWrvq4+DkVQC19RMKs1WBzOolI8F9TPvEvMLSooKOPKjosFvN3G2W0nI3aH s5qryqriqo6JWc4MRq/j9LqTET0QR028EtUQ1AlUDcVJKaeIFDUr/ajYRhmiXeVscU1h+AP0z3Ud BVyj4fW23CDPBLZeMRivUcQ1qIjRJRFNRoomqjZ4bnI7PbxeM5d/78jMFtf7NDIv/qnchUUtKSrJ wnzUyF+jRvqgFK4kdDLf5QHbvsLCoOcuUevK51zHxTX5W/LZpvyF+UdQYfItuSB6cjpAWOPb4mPB x/sEH6fnfOSU6sh0dfhyOYzHRM5pKeFKjosWPnVHIHoUQEXaShSJnkSQTNlTrp7DnZSsQfAvN3a0 MEWbqS47MjUalRbXi/rXmsLEEnGHB359YNujS8z24pmf/tHtxx6aczh+9f+YzAUNoZ7DvfHm098K la6+7/ujw92PjFQtHl6+4Xj35pH54zfVq2Y3FbZU5bWvvKLec0t41mncp7Txudz/VT+E99oXFOxL wB8wZ/HZnhx3TjCgCWjcOVyA58sD2czJSDD7ftFjKSjyFXFF5MWdV/Rlm+0G4Hme9chXBYOd4+3H RQNDpktO+QHlmJ+wZvysDEydmPHeQa4eDH8+zJ87T0DnP9qRona8zckXOvQORfJ9WhvW+jliAcU1 qO7k8HPAPGNGbpbFM//Wz60tXllfdodKyHcV5OdZPU97n/l7/+3fPRqq8GYXldWVl7i/zfU1q4yu qto1O1cHNMZvN1bZym9cOLzzytcfeX6jabPOM2f7Rm4H8bdhvPHVoPcIwGcVfKu0Jidns5UJuQzk BfLyfAFOCDAzSrgZJScjM3Dz8qg8nAc9Im/lOSt/MmJ1CA5i2ykmHVbsnR4SCXryzQ39BsL0ZzND h0peMqDeaZNuwq4oHTk1+uxJN8L8u2nR36xbtz2zO0NbVmOMx3Z6jUUFwvybaq3D8V9cdSYcBzdL tXb12MDcFfHD5ZW2sgJNMyuM93jKghXrRpddnVRtWFumOAz0BE3obnept+Bx1glSwhMwHIisSYWY GTmW4/pEC7uQZSdZxsI+w/4cCZUeWJ5l8d5pyDgZMTieyMy0n4xkWui9083/S4hswKgYaHGjio0j Zj/MulBJLbz8o+EaZdCl2qejRoBid1XFr9Z4DJqyGkO89yFTRuFsC1M4qt7y1lvvPVRZwQeKEJKv NrS4in2aZoOiMewnUGPscIOCgZMxsFyGTufIkL09Q/cCkEVpCgWm3z5NH9AoyoSZKfnkhWSzt8bj ZAVRNmXR1MffG8OlInJNrQ6RC1dHcyf6aRGeVeRqqq8rqy0L1ZZxkFfICUK5U2OxWpvLecvJCJ9X hspXV1/KlXBUAzm+EZ3hMbGRr3kC0TkZqU5iOeUbyd5FL4mh5KzCYfkW5Kokek4mWPIR8Sfb4rXa 3simaLuSIdeklBXVuqhzVjUte2LD+rGkAUwYDOrCwtwbVhILuHh3ho4rKA7t6cxEc/iU2hqqtDD2 oTpj27bx9v4xzrepb7pRREMNQVtZKNy/Fa2CHSupyDdXhW69vR8z/+CO5pbmqZoNP1Etj5UOyyuh asGVCMCjCZ+izi/hGKbM4s0ymj1mM+/hLJ4nXC4n53KejLgsXoMuT8fpjol5PAQ4CJyMgAPhCV3H DfD/cl2n8udzi/qudSLXIDm1AKqCaxxJCnKt27e1r1f8zTQfkgrQslggFVf5dKEyIVZuvGFGFbQ8 mXv8/oBnD3pF3FyOizwP9MiJbud6F0x6v/zQluR+OXUKrSFahbNiNRqOnKUaVcrJijk7fHKNRpfp 8hf1b2vtXnHb44t7HvzhpTnNhS1zq0JZc8SlH4vyCx8ZD1ZH2rvFjqFWm2PlZzfeFX/7y8sZ/02r 87rGPv/Ztv6bPhf/W3QRkz+Pd6sW05N8HTyjzKzBdpdYWTm7oLYoK0Pv1XlB5+UKdE9oNGpOoz4Z 0VhqMmaZZ3Gzjolm3o1Xl+Oi2+nP5/z5JyN+b+IQmWIt11MKRS2yCCwlHw3vqP0alSDXdOxZrE28 nmA0iWPplFG+6C6tsTCWzXXGyPhoyqG0jFOz1KMx3+Jn1hc2zckrnp1PTqjd+eyZTaUzfGqiKjfG ZiRPpf/E53gMxONxwrz2TtFdM6v58TML5rXf8cSDiufjfotI58AXFJxr3C6j05jDGM1OzsQweSaj y53BqViVTZWv4qwqr4oDhmdYG8eo7sMroYNP3T2ayGkF9w75BahLftkjO3BrOOHliv+jLKOMn9qc Stm4FXyJz3Nx0lM5ft5f1lSabSRm5qRWtrXLuPSrm5rnsd9vqTL55rUtmE2sqy9Ijes11c234nbC TF7B8/oh6n1eVNBog1KzM9N/l1Zblr1XNBsEwVNarCpWcYsSV70R2A1qUB0Xi52ZHusaJ2Nx5jlD ziNOvAFaPZzTc1y08olTHDkby6e4q+dXb6UXaRt9q5E4nCffa9T+Zw117SuN6qmzI1FEp8tJD+fk dUbNU+qZHRULl2eLHf0rXzq/4FRn1e36BR0ti/MiLRtWbf7Gjo2nF9cy7o4bfQvaSutrgg13LPrk pz2Of1vd0zq7sLa2pGnfinV3t2U53yWatgWxLVK9iDZ9NmHRJoMToMjgdngyPfZMD2cAMQvvHgUC FPAFQgHeO1Q+rsB3TOW02BkjZ3eIbvPJiNF9v0h8Mj0Bkxc2F3CqTcqUszz8hWtf+p/n6dE78FFx jxYmrpfVNXY/OYCH5SM3JxtyDftS+8itixZvrDA71+83N7bNDHov1/+7960tWqOOy/eVran5yoLu 4tl9jaFlMebJZpVPHOn9/c54TW79LL85FBBbCF7j6N1v5i6iLu5N3F6yvVk8b7VxWVllDFvCFRiz E5uV0+M+GfHwQDcsy9RL+SmHJGNCjxuKFbr/pO5Ru0/eyYjTr0lk6GU78ZslZff7JPMZ3OgKCzLL y5srfeZhJk/e6uL7q42rvzg8QDe6YC138epF3OpCpfbC5q7lzSxztVHZ7C6oxjeTrY4Zxa0uWKAl lvkcngssiEYpfEZBoxJMznyVPk/DcXq73VFakufJcziCebQ4Z0aePTsnG51Ijl5Top1BrwyJidFT Ulh+qWxz1SWOmOR3QzThzydeS3v/dGbyCwnyNtqFRwJ7LocQJbEqroaa4nIOK9mFK6qzfBamxRM8 dt+cg4787ByPJX76E8OiJ98S/0aWyHhWDApFQl6ehZnP3tm9qtzjVzU3h+49VBP/XrAxz6ZpZm6J 9YW8BVgaYUwLX+/oLLDrmsm/IShHwK4iVhxoQQcVYjYrcYu4Xm6E4zidRSvt1qC75VhWq8LtDfXh XMhVCeh/ms6vxgNBBcP57XZ8GOZqZLJlHB+G4R6NP8+UX50gKfsknj1iuE2fUi+jY/hFK/LjWJUa Dzss5c9BUwj9Dt1Zz7nQoTGMzJQ9FX/liV2zkal62ZUh7v73XiAsybuoS5zEfRrvBoRjiWhVa1Ua vB/hQUPPahgth1tV+EKlvJnweL/h6R2HyKombMu+fKiZ3fLU4Rb18biHeZUhifyr7zumIlOA8U05 sovkyJm4L6g8Svyn/6lRPYAxrvmSdrMuB+NT+moa78xoz/iZYZ5h0jBp3GeqMj1nXkLjr9MxHf8r RYs3GSPpmI7/xeOWdEzHdEzHdEzHdEzHdEzHdEzHdEzHdEzHdEzHdPzfFuV/iok/X8C0ldkNGsjF RzP5S0xtNN1D07003UfT/TQ9Mvk6pnfT9B5acpTS99L0fkx1yIekNpo6J/8NU8JNR7npKDcd5aaj HHS0l42rn/wJOOEg0k46ipOO4qT8nZS/E45N/g7T+ydfhb3I821M99J0H03303SCpodpeg+m+7Hk d5gepul9k29iegLpA8xr8AQc4OoxvQdLfgFHaXovcn4d07003UfT/TSdmHwD08M0vQdLjmHLNzDd S9N9NN1P0wPI/xi2IfQJcOFDeJ6gPE9QnicozxNU2hNU2hOU5wk6xxM4x0uYnph8nXmZIgMQYhPf cmdijyf/wa0ZNtGc/I1t/ZxKoRkwc4MKzYIzI9GGg46MUYVWQVHGAYVWgzvjqwqtgYKM5xVaC7/P eFuhdVBq2KTQemgzXFboDG1GciwDLDdWK7QRSoyHFDohM5eUOfHdbJXGLys0A1rjrxSaBQO/K/EN f1DAb1RoFdj57QqtBiN/RKFRb/kHFVoLO/kvKrQOHPxrCq0Hv7VUoTO4vcmxDBCwLlBoI2Rab1Fo EzPfekihzVBt+wn59kKVXsFZpmWcZVrGWaZlnGVaxlmmZZxlWsZZpmWcZVrGWaZlnGVaxlmmZZxl WsZZpk2KNhBaxjkKW2AbCLAZYrADP7fBGAzg5zgMwhDSAqzDFsOYF7DFGP3zngEYxfZDWDaOdD+W raV9SR/StxWWwXyYq/QdTakZwdwW7LEN+ijHIeQswM10LPLtfdcfV86Ttn2wCfv2K6OOYwsBKVI/ gjXyDGLYrl8Za0jh0KfwGqBpOZZcO29Sv4lSJdhrBn4OYN3a5EjXk2r4fZz/eIymuPdTTuuxbBTz Y9hilKIxjinhff25y6O/X67ZKQiQmchzGafjjdDViFH+8lz7seRmOvMtWP5BM5Vxjk3DdICu6xYl lWcl09swN0JTgUq7nc5mIMmHtNyELT58hQYpciNQDyGMN9NYThHtozo0hs862pL03IxtxnFGZIbr 6RxHkMMO+r+5ynzHkCbSrMO6bTg+6RmjenMLfB7Hr4QKjHVILXjfGAK00Jkm8EusDNGjuchrE352 Y9l6KvUYzQ1QOxrF2ZP1KkcOMbriZMYxioKsKUQHBuha9tM+hMuwssbrkvgOQxnW9VENkVsTKpai O4k1lzEm67kFNiK1nlL9ipXJfVNXsZ/2JXMco7Ygz4bIcSuVh8yxk9YnJN5O57WD6vB2hSPBkXz/ 5rXSyPYu4zalz4RnhOKwnpbE6JiJPjL/cboKcg0ZeQjLNlH+A1SKRGsZ5SHESi4dpZo2SnVMXqnt lN5B245TeYiMwaTf2UR7DFIZyaxlfYkpOFyPeypSCTmGkto7tQqyzcm4yXhOybBR8QLDyTUco3LH UmxpnPYdVnolRtqi2JbcbjOVcROdpYzs0qQFJ9a5j357qjxPuWYz1W7CZZhar2yhMdTGRKthmPJV QwoepNVYUpNGk/vEgKJxN9PSPjrfAWrTgxSzGPVmpG46ittwPLIXpHq0MWrHm1L8xVpKx1LmPETR Wat4y4TPHaC9NiseZIwitY5KS1a2Hy1oiK7b+iRSNyYt4lrrlFGS98JUS+yjniXVMydsJ2EvZNTt yvoRnyJQ7Ze1I5iC15TGjKJk70fq/TY1RnWU+K7+JCpjdFVkvyPr+CiVeBtdz1TJp9CSdxnZB05p zMA1HkjGYBiKaZ8NFItxmK7n146wjfaWLXRM2V36sHRqTepTRiNyrKdyxGj/m+nKynO5nn8cQE89 feSbqWYOKnuTzGe9gssA5SJrwGbFqlK9BsF1gNqG3H4HXf8tyGU6Ju2Kz92Y0rsFW8t7qGwTf5w3 36ZILuvRJmqBCTsYUfaKIdpnC+Ugyx5T1iKhK8Mp+4/so8ap5W5O9iA4jSg+dCzp5+QdfIiuxZSH SuAk70hDdI23KOcPmTuR/uZpHihGrSlhr5sVTRpK7lBD1EIEZT++Vq/Kr7O/1v9/9s48PIpibfTV me4enISAioKExFERIoaAuBzECAgYQVGRTUVUJslAhkxm4syELQTCIgREQEREzAEXCIoRRw+HoxH3 RBExKotGxSgTIIINYYkBFen7655JSCTfvefc73ue+8+1nl/X21XVVdVvVb1vVQ9gCytwgDkWRjtD mlifPqLBU18vRkcsSoO+rqfuG8UNf6mpe2NNTetpeb07I/MpPEaOxjka1oszsrbspgV3mG+VbWoj SzTshBz/Za4xMv/+zuKvFngUd65Gfz3CfJNAM0/Yo4W9WLppLzyRHWXY6t1p1u9tMjpDIlbxr757 pGlnvaYULhu2pFmmJfqf2Z0Z1u7sDq3lWs/mR2p72d6rZ88b7Xe60n1ev3d8wD7Q68vx+hwBl9eT bL/F7bYPd03IDPjtw51+p2+SMyN5oCM7zedy2DMdfnua0+mxZzj9rgkeZ4Z9vNdn93q6+9N9RrLP 6chweSbYHZ4Me8Brd3u9WfYJXm+GfXImuTk+lyfAM46A3Z/toBm/a5rTn2wfEjArnuT0TbU7J1HQ n+NIb6gmx+elb0bXKDnI5Zjg9TjcZg7lA650bjIdLp/b5XH6zWS67BqP6HPSHTcvNcnpnmr3B3xe z4QkOuJyO+2ZXp9rmtcT4OEmxcOdMuow+hl+BWd2Dn2jn2YNWU476XTNb0ddmU6fPZDpoL8B4yFv boBbZ7bf6Z5kvNbITJfffOd0Vw5tcpPt9QfsHi+9djrSjCSP8YDdRT9c6X5DSfTCSHF7Jzt96Q6/ 056e6fA50gNOX6SLuWkZuU6jgzQ6lSroYprT0CiPuXzItIAunW5nttPDEHrH2yd7fRndXdmOCUan 7jUGomE46VKuPzKI6Y4cU8nm6BjjYveiYGaKPceLOpLMfpmK8XVv7FTjSPkzvbnuDKMrfrcxd9C4 z5mRmx6p3OyWz+nPdQdMxTgjE4geeLoG7BNzyQ7rvOGBXL8xoH57hjc913yTPuZjPueEXLfDZ5/s NFo5Ox+dUyIPT3YFMu0OO2Um0BdnwFBAtsNIM6ZGusvpSSd9anaa1x3pyW3M3Cwze+BUn8vNSLQw zXOpHB25vX5jDHJYFS4/2jJqZ/xNrXjM9cOMCjgd2UaGcwrlAn5jznntDle205xQRp9YSC5/gDlo zF6Pc3J4Ajl85rhmoySXsaBcOYzq1JwGXSU3rtc+jQM4wIvSh5jTp4+xqK8fzUQx+nV98o03RAp1 NwqFyzQZd6fLnL4OQ6P0hYlH73yODGe2w5dl9xo5TW7Ht2wsGibwKI/LWNcjAo5AeBH2MKyC2UC6 N9cT8LmYend6mfnG6wxhKjas7pEun9c+klQmaZY/MxDI6dOjx+TJk5OzG9pLTvdm9+A57wSfIydz ao/0wHgWbtOi5r1R7H5vLmM91ZjTdIuXNHKM1cA4ZLsCRhfTppodvnXU0FvMeWbcYGGYqcYENKxD emaTZ4lZvu7cjPDYZbj8OW4aCNslRp3XM2ZtINne0LbXw9RPdF2F4UgzHjpblaehcIs9MoubtpNl gsLSw4uxsXVT05G6bjI7kOiilQD2icFg3k5lqUz2uL2Opo3SZ0fE7PrsjWOCocrBVmU4J2GIjDKZ TnfOX17o3xkKU/E9MpzjHUzZZIc/Z4rx/VE/8cwq/ekm/75h0/+M//vIecImooVV10Ub8+tfDMkJ UhcRxV5DSKuFJK2RXhFRUon0GnJQel1YpDekfyBvkv6JvFn6F/Kb0lvIpdLbyFukd5Dfld5H/kD6 EPkjqQy5XPoY+RNpK/Kn0jbkz6TtyJ9LFchfSF8ifyXtQN4p7ULeLX2N/I1Uifyt9B3y99L3yHuk Pcg/SD8gV0k/Ie+NelRIUfOi5glL1Pyo+ciFUYXICyzXCMnSy3KtsFius3yN/I1FQz4svyAk+UX5 hLDIdXId8q/KAGFRBlqfEJJ1mbVUWKxvx9CfmK9iaCvmh9a3ohs5/DsCmnkDPQRp/XW0EYUeNiH/ E21EoYc3kd9CG1HoYQvyO2gjCj18gPwh2ohCD+XIH6ONKPTwKfI2tBGFHj5HrkAbUejhK+QdaCMK PexG/hptRKGHb5G/QxtRET1UST9y/Qk9hDUQfnfjrXtxvZZ3j7J8Z/kO+XvL98h7LHuQf7D8gFxl qUL+0fIj8k8WarDstexFDllCyNWWauR9ln3I+y37kQ9YDiDXWGqQf7b8jHzQchD5kOUQ8i+WX5A1 Q8Po9kW0ulZeK6LkdfI65GK5GHm9vB75Jfkl5Jfll5E3yBuQX5FfQS6RS5BflV9F3ihvRA7KQa6v y6+T8ob8BvI/ZOaevEnehPxP+U3aekt+i5RSuZSUt2XmkvytjGbkH2RmiFwlV5H+o/wj8k/yT8h7 5b3IITmEXC1XI++T9yHvl/cjH5APINfINcg/yz8jH5R/oTZN1kg5LB8m5Yh8BLlWrkU+Kh9FPiYf Qz5uzqhf5V9JqZfrSTkpn0Q+JZ9C/k3+Dfl3+XfkP+QzlNRlXUiK8U++RSmSIiFHKVHIFkVmNvIf KaqiknKBcgHyhcqFyO2UdsgXKRchX6xcjNxeaY/cQemAfIlyCXJHpSNynBKH3EnphByvxCMnKAnI lyqXItsVO/JlymXIlyuXI1+hXIHcWemMfKVyJXIXpQtyV6UrcqKSiHyVchVyN6Ub8tXK1chJShJy d6U7crKSjNxD6YHcU+nJW1yjsAaVXkovUq5VrkW+TrkO+XrleuQblBuQ/6b8Dbm30hv5RuVG5D5K H+SblJuQU5QU5JuVm5H7Kn2R+yn9qLm/0p+UW5RbSBlgrF9W7jLW73Lrcq4rrCu4rrSu5LrK+izX v1v/znWNdQ3X563Pc33Ryiy1rrMyP63rrSVcN1qZS9ZSwwKw9lmDMTtiWIMxO2N2Iu+K2YW8O4b1 GPN1DOsx5puYb5ArYyqRv41hbcZ8F8PajPk+BksVswfrERWxGjaxImqfsKRP9blFuwk+Z5a4ge2w R6SSI40YPsBu/F+XsMLh36FiI7IkWmGXzX/G17yPwl63paRlyLBhg8Xlw+++0y6SRw6/w/h/B4VL WKjv/IgsY9kviMgKlv3CiKyK1qKduCiLbZIoMK/zzOsi87rMvK40r6vN61pj3yE2mNc9xlWKNa/9 zavPvJplpK+zs7KzolqZ1wvMayfz2sW89jSvfczrICEafwn7P1/bm/8mpfFGCr03/oZl2G/F8Cax aCj8f6+60HgrtNP+/z/xHz1hER3EJaLjf0uKE73FWOEW08UidhslYovYLvYITZyWYqROUpKUIg2V xkpuabq0SCpiN7FF2o4H04TxC6DF+CVSdAr/u6OGBzXiF8aG4/qN4jxzHrQyfbCUMK/5fddOze+7 nWl+n1za/L5P03wsbOq45vmpPzW/v3tl8/JjhzbPfzDUPH/8jOb5E3o1z/cdbZ7vX9o8f9qK5vl5 /ZvnP9qteX7hm83zlxQ1z1/auXn+ylXN859JbJ6/tkKcF9Vwrwpp3WhxnqXJ/Ya14jypyX2JR0jP xho2Su0ZMzFmbcyGmK1YzaOt72o9tvXYmLWt01ovIt7auhg2tT7Q+lRsQuy42Bdit7aJpfy5AYtL HQ1hq1nbXwJ1h8PYlgJ9MFtt04GWF5k1/DXsoCebzN40hFNGoF/hsDUc2sQaIWbrRcvignGb497n WhG3p9O2+FZxQa6xcUHjL/aSszm+Z7wnvii+mJQt8TvitfgtCSqlzw0VhPcbQkLbSEqz0GlbOJh1 n1ODmRNrtG08ndAlvlVDMPpxTqigXx6zb5FgP3rFjs4j44uv7tJS/+h9s5CgGuHqkUkXxG1Oykia kTQ3aXHSyqTipGDS5u4CeXH3jt07d+/WvWf3ad3LktXkdpQ6N6wkzG0Mi806/hqCkUC9yQndRbj2 c8JK2utottkQuhmhRwfaNwN9CId2Rkha3OO4qYc9Ddo8q7+44LUZZvD0adf3rv5jDYz7AeMHBW6L HdwY337ozoIG7j4+rG0Dw9LumXJP6XBxz5RRO0btGz17dNE9U+5X7/9y9OwxHcf0HnP7Q9sf9owL pvc18p2Jo2c/tP2h7U6PM+Cc5ix0rpowdMLwzHGZH2bucR1ynXKdYepfnNU7666sgLvCvcvpIZ/g OkQawb3LHXKfzh7uDnk2eT70tvUmuEPeIm/bnL45g3Juf2ToI6N9w4w8b1vkob6Nvl2+en9nf7J/ MCHN786Nze2cOzq3YNLmSdsJRyYdITXNVz+pbmrf3NipaymZPK3CP9jIyWuXO9qfljcvb2nehryt eRV5u/K+y/sp70BeXd6ZvDPTW01fzV1FXsX0faQfyJ+YPz1/Rf7a/A35QcLm/C35H+d/mf/1jP4z Umekcr85f8WMoTOK87fM2EOZDTPq84NGzsx2lNo88yFCxkzfzEUzX5hZMnPbzD0zjxSIAltBp4Iu BdcVpBYMLfAUTCmYV7CyYHXBSwWbC7YUfFiwtaCiYFfBdy1ajwYL0tRaGDah2fqf1anlEF71La7b YAsrNWhahSZhVrezwchteh9eTy2ujoYV0jQ0m/WzUloO4Zk+a0DrU/HF3WkRy7d11mDjDSPvjB2e lRabwF1aOIVr8Sx361OzJs16zrBtCWrM2k7bTCaaT5j6M21rmlGPUaL1XQ1abdCkYTuxsaalNa34 jgbNxho1bMDunpq1kVxyZlHWTF1rhg1NrXBjOHqOLU8zw6JIGNt0DFsXEza1bMFN75Jg2vAXwj7G CGYdxjPUa9hzY6xm9zVHb8/spfGxhk3AhhfPPjL7VII6xzand4IatsBmmbMzYLNpRSrCNsSoZc7o TtuMshEL3GRWGFbXkOe441slqGetc/wW87lpc5bOOUKZLXMzGvPeb2Gu7Sn4rqH2s/7AsF9hC2be tWoams7HiO1vYv3ji8OhBYuvhb2WEain2ExrdcWO+FZzv+aeeRDuOT5g8dyj5rycm1T86JnuPZM2 4wW6zRs3b2LE5maQF57Tpj03yprpwcaZHvYbHalrhlm+cb4nq9zNxfp3I4/0eae7dzTTZphhblNP 0BhMb2QEw2s09RwRX3GOtzD9VU/TX5SFvZYRSJ1mtGXW0TFps+E9jDeeHzu/YEFy3OYFgxa8YWgb aevCXgvdc0bHBcf0xtr3Dtv2hT4s+aGFJVjntmE7/MhQPMS/GcL2vmnAqzQL55bA5zQLYzoa/Wga zn0GD/QfhnPraB6Mt24WzrjOhL3Wfx3wZ/9JCP37Af/YLIRH42zAY/YNj01LoaVxMfwl3nRwQ5i0 3Vdv+NOILyUYaQ0B37vR8KaGfzV9rxnwvQTjyUnbF26eZITt/mTTs4bDGXyq6V8JFabPPdPs7oAZ zlCmbuFR/OoK09uGwwrD587ojzSRsMH0xJsj4UszrFhYjz/un78h4rGM3WurTtsea/vYCsOWPbYl nBoXXHR52F4sWvT4gcX2xfMWn1rSZ8nSJUeWBmYNWDpv6coFbzzx7hNl2IKiJ7Y9mRlflKA+ufjJ 7Uv6NN1xxm1enrC8Z9gWRaxPcYL61OVPJZnWKRi356nhZ/fO8UVPFcZr5FesGLui9Om1KxNWljyT +kzZKs+qU+xBDrATOWDsFIzA+fULvV7s1pNFSNfEYb1GkmGi7pUO6KVSjV5kGakvs4zSl9leEsNs L0OpGBY9QfTirLJbr+Q0zHOSpId4LiQNFQk8W8OzIZ4Ncdr8gvPxbr2Ccru5P6zXR8q1o9zOxnLt I7VUkFsmtdErKZEo3au/K90PY+ABGAsPwkSeKoADeoU8Tn9XdkAapEMGOCETXDBRf5fT8Bechukt T1aa/a7g/B4y+1NJixW01ou8Mmosoj/jeNcM3jWDd83gRLZb70zpekoMJXcBGilFI8afwz0sbOb7 oCtO3Lv1sogWNVK/j7xhBc9U8ozGM1qzmuXIW2tGvyjFOTHSqxCppdTxKLo4aOqigFIH9GRKFYu2 kVIVkVIzKLWTUqlmPWHNzDDqU0eIYdYl+kTbK1ACX8CX+tBmNRg6L6SGmogWGnS77H9bQ0NPvzJH zOjhRHR3gJpq9Ik81Ys5kiLOp1QlpV6hnbJIO6WUTjG1HW6nI08EmrUTaSN6gF4aPUE3vt6H9VMp rRaqfkzY4AJoZ/x5fv24aE9POuhV4hLijtBJrxHdyLsakqA7JEMfuAlS4GYYBaPhXrgP7ocx8ACM hQfhIXgY0mknA5wwHiZAJm25AJ2JLNp3QzZ4wAs58Aj4wA8ByKXsJJgMU2AqfZ0GeTAd5hp/twCM v3XwGCyCx8H4+wdLYCksg+XG3xHg+adhpR4Uz8Cz8A7p78L78DF8AlthG3wG2+FzqIAv4SvYATth F+xmfu0lDkE1HIRD8AvtaHAEauEoHIPjcALq4Feoh5Nwir78Br/DH3CatD+JzxDrjLtFPyYpcAmz piNzME4PSp0gAYyZlAVuyCbPA17IgUfAB34IQC5Mgsk8NwWmwjTIg+mQDzNgDW09B8/DC/AirIV1 UAzr4SV4GTbAK8D8l44w62rhOJzQK6MsoIAV2rOub4Q+0M9c4yHWeEhuq1fJ58MFcCG0g4vgYmgP HfQa+RLoCD31Y3JfnukH/eEWGAADYRCk6kH5NuLB4MbeoQ8ZfcjoQ0YfMvqQ0YeMPuQAZXNhEjC3 5KkwTS+S59MGc0q5DYbC3TBMDynMfYW5r4xFfhAe1quUcXqNkk0ac1hhDivMYYU5rDCHlUmkT4ap MA1mwAJgriqPk78YViA/DSvhGVhFfUXEq6n/efLRt7KetBLiN4F5qHwBzEWFuahU6seVb+E7+B72 wA88WwU/wk+wl3pCUA37YD/gSRQ8ifIzHASNNn6nvj/gtH5MjQLmnCqDFc6DaD2kttaD6oXI2BK1 A/fYEBUbosZBJ7iC9K6APVGv5/4G6I3MGKkDiQfBrcj3EA+nLmyHiu1QsR2qC9yAPlUPeCEHHgEf BCAX0KuKXtUpgG5VdKvmwXTIB/SszoQCmAXzgDFVGVMV/avYCfUJ+rAMnoTl8BRgH1Tsg7oSnoFV 9A8boRbB3+E5YA2o68grRl5PzPxXmf/qq8gbiV+D18nbRPwR8Sf4hC/0IvVL2IG8k7S9xCGohn2w X6+wCsC3WNGv9Xy9yNqReCTxKBgN98J95N8PY+ABGAsPUu4heBjGQTpkUtZFPBHQlfUJ/ZjtfFii h2y8o435ZmO+2VjftjLuy+Fj+ASwfTZsl61WD9qO6sHoPnooGh8QzdqKHgKshWjGLnoEjAR8QjTr Ipp1EY1PiH6AZ7Dz0nwh628LBe9uNf5mGpwH0RADsdAG2sL5cCFcZPydM3033smFd6rDO63BO5WI OH0uHson4vXVIoE6LwU7XAaXwxXQGa6ELtAVEvVCcRX0oM6e7GWuIe4F18J1cD3cAH+D3nAj9IV+ 0B9ugQEwEAbBrZAKt8FgGAJ3wFC4E+6CYXAPDIcRwA5GjAMHpEE675YBThgPEyCTd3XBRMjind2Q DR7wQg48Aj7wQwBy0ckkmAxTYCq6mQZ5MB3y0dMMmAnsgsQs3n828UqRKJ6BZ2E9u4yXILzPKxWn SPsNfoc/4DT8CWdAZ6+i6uvxPBpeR8PraFI8u5EERtmuF0uXkXc58RXQGa6ELtAVEuEq8rvp06Sr YSLPZoEbJsMUmArTII/6pkM+zIC9ekDaB/sBL4pXCeFVQniVkFRP2kk9gDcpxZuUWg7rb1uOQC0c hWNwHE5AHfwK9XASTsFv7C5/hz/gNPwJZ0DXNVkAe0w5CtrqdXimOjxTHZ6pDs9Uh2eqwzPV4Znq 8Ew+PJMPz+STU0WifBsMhiH6evl2vVi+A4bCnXAX3A3D4B4YDiNgJATwPOx08EQhPJELL6TJs4Bx k+fomsIcVJiDymDRDk+0RmGeKcwzhXmmMM+U+2Gs7sIrufBKdXgln+LQVytO0sfDBMgEFzAGSpb+ tsIY4LXq8Fp1eK06vFYdXqtO8ZMXgFy9UGF8lOmQDzOB+aTQJ2UO+XPhUeR5MB8K4TFYBI9Tz2JY ivwEPElfllP+KeRV9O1Z5NX09Tnun6fcC9y/iLyevJeQX0beAK/Aq7ARXoMgvA5vwD9gE/wTNsO/ 4C0ohbdhC7wD78J78D58AB/CR1AG5fAxfAJb4VPYBp/BdvgcdsBO2AW74Wv4Bir13Xje3Xje3Xje 3Xje3XheF57Xhed14XldeN46PG8dnrcOz1uH563D867B867B85bgeUuUQ/pc5RfQePfD6OkI1MIJ 2qiDX6FeX622FonqABgOq4B1rBbB3+E5KIb18DrwfngdDa+j4XFC6rfE38MPUKWvVw9ADfysT1OP kkZbaj33J/X1Viu01kPWWGJss/UiYjy89VJi5hoeScMjaXgkDe+j4X00vI+G99GsDr3MmgbplGe+ 4YU0vFDImqWvt9WKRNtRkRj9ADbFOFMu47S7mxOixG7ZYp42ZfPMppl3RUY6KZxAxG7hQaoz/gax 9IvYECUJj+U6uAH+JjZYRsIo8EM+zCJ9NsyB+fAybIBXyCshfhW2wWewHT4nvYL4C/gSvoIdsFN4 lDVihaqKKWofkcGZ64A6Ujyn3id6WeeIFKvhT58UqbblIsX2FKzWK2xr4BXSS+B1scf2hlhh+4fo ZXsb3uP+fe4/pew2+IIyX8IR8k5wxq3j7Gac/gt5d+O7wjFViF6qRGuPwgJaXMhT69AjY83JOIWT cQon45ToMWCc/Ay9jhatzC8N4W8HlWi0rOkpmnPmsP+olSk8OYUnpzS2Es3T9ZFzfMi6gF3IQt56 HRTDS/CyXhHNLoXSReYol9LWcaEgcX4X7Xj2OM9W2jaIXmZqJTorQ2dl6KQMnRSaXxEq0XBZyzm8 3THqPEFNu403NL+wREVmUYg6z34XqCB/HGM3RrwhCvF3j8EiWAJLYRkshxUiQTwtbPjJFPxkilhF 2rPE7PLwlSHxHvfvwwfwIXwEZVAOH8MnsBU+hc/gK9gBO2GX6Wc1sZc4BNVwEA7BL7SrwWHkI7Rf C0eBc7s4DiegDn6FejgJp+jXb/A7/AGn4U84A7pIkSzoeA08B8/DC/AirIV1UAzr4SV4GTbAK6Kd 3APYL8l9hU3uB/3hFhgAA2EQpIoU/FwKfi5FnioS5PmUR68qbapWiBYJ2KoUtR3yxdBB2NRLoCPE QSfoSno3oD2V9tRr4Tq4nrwbYADPD+L+Vuq6h3g49y7iR8AHfsiD6ZAPM2AmFAD7HXUe0C/V6NcC WAiMu/oE9S2DJ2E5PEVbK4BxV1fCM7CKthh3bGsKtjVFXc1z6BIbm6Ku45li4vWA3lT0pr5K2uvc bxLtrE+IdrYlwmajTtvTyCuBMbCViQRbOXwMnwDzxPYLZWpZaUdZVX2ELXqQSIgeArxv9CgYDffC ffAAZcYSOyGT8X/T/ObR8L3j3O8cmnharxIr2R0+A6t44lni9yLfOT6AD+EjKIPyv3z7+DTy7eOv 3zpa/s6hCc38hlcvjtBmLRyFY3AcTkAd/Ar1cBJO0Zff4Hf4A06zA/2T+Ayxjq0wvnX833x/2Cu6 SvtgP9TDSfiNmf2naNfw3UHuwdk+/A2hSu4H/eEWGAADYRCk6iXybXqpPBjYnTZ8DzDPw1bzHKxx Di4xz8AXm+fgKs7BVZyDqzgHV3EOrmo8A9OeSnvqtXCdeSau4kxcxXm4NHIW1iJn4RLz/Ntw1vX/ h2fahY3nWo1zrca5VuNcq3GureJcW8W5topzbRXn2irOtSWca0s415Zwri1hhtuY4TbOtyWcbTXO tiWcbUubnG01zrQlxpnWPEsu0as4R1b95RypcY7UOEdqnCO1yDmyinNkCefIEs6RVZwhNc6Qmnl+ PPfcWMIMt0U7kTOZI3bTx0Q81P8Lzy9tEnP0cWIuvvJR4nkwH9jligXEC0k3/vUUdrviceTFsEQv Zh0WiyfIX0b8JPFy4qf0iazJCtZkYeO3x1Xsf4zvj0X6dPF30ldTdg3xc/A8vAAvwlpYB8Xkvwwb kF+BEuRXYSO8BkHSXid+g/gfsAn+CZvhX6S/CW8hl8LbyFvgHfr8LrwnUrELGp4tFc+WimdLxbOl 4tlSsQsadqEYu6Dh2VLFNsp/xv124s/B2LF8CV+RtgN2wi74mna+oY1K4m/hO/ge9sAPpFfBj/AT 7KV8iLVfTbwPXe1HVwegBvlnOEjbh+AX0jQ4rJdha4LYmkJsTRBbE8TWBLE1QWxNEFsTxNYUYmsK W/iuqkW+q2rYGk0S+nRmWZEURWzhtGp8c1dEG+yPhv3RsD8a9kfD/mjYHw37o2F/NOyPhv3RsD8a 9kfD/micWIukEHXwHpxcizi5Fpm/LBzhBF0reknHiU8Q15N+Ek5xiv0Ne3ea+E+9NCpKXxYlgwrt RaKlHyfJOH2c3EkvlOMhAS4FO1wGl8MV0BmuhC7QlfKJxFdBN7gakqA7JEMPkYr90+RrKNeL+2vh OrgeboC/QW/yboQ+yDdBCtzMfV/ifnoQm1mIzSzEZgaxmUFsZjDy3VXDZmrYzApspiYbJ8LfRRvl DzgNf+rjlDOcKnX2Y1GiDfa0WJWJrcStSDsPOVqvML8xxurT1QtIu5C0duRfpBeym0hV2xN3gEso 0xHioBOgGxXdqOhGvYzn0I16Bc92Rr4SumLDEonRC3a5WEUvKnpR0YuKXtiJpLITSVWvQUYv7EhS 2ZGkYq+D2Oug2pu60Il6E/1KIUYfKvpQ+wH6UNEHNl1TB1JuEPXfynvcRpnBMARu1yeqd/DsncjD 4B7KGN8/R4hh6hjuH+C5sfAgPERdD5M2DhyQBumQQboTxsMEyCSNE5aahezmuWzwgBdy4BHyfLTj 5z0C3OfCJJgMU2AqTIM8ykyHfJgBM6EAZsFs6p4Dc+FRmEfafCiEBbCQuh8jXsT7PQ6Lee8lsBT5 CeJl8CQsh6d4fgVgB/FFQXxR8JxvrKv1ZeoaML61Po++XoAXYS395IQR+e6qqS/x7qw9/JOmYgvx URXqRsq8BkHKh7/BFlt5X+sUfZx1KkyDfJgB2HN8WbHtfNHGhp23YeNtpNkWwiJ4HJbohfi5Qvxc MX6u2LaKtGehCJ7jfq0+0bZRn257DbCvtnfgXfgAPoSPoIzTUDl8DJ8AdtS2k3TsH/6xsOE7q+2Y Ph0fWRh9k2gTzfyKHqhPxF9W4C8rou8mjTmD39SihxOP4H4kjNKL8aHF+NBifGix+e11rL4s+kHq Yv5EM3+imT/sGlPxqYUimh1SIjukRHZIidIBqIeT8BtW6U/RKypKJEbJoHJG74GvqsFX1eCr9uOr avBVxu9UNdjTGuxpDfa0JmJPa5rY05D563aU+VtMTYNNYE3XsKZDrJ+QuU7uIB5O2iqgbsa/hvGv Yfz3M/77Gf8axj/E+IcYf+N7e4057kHk1/Ua9B5C78Z36hr0V4P+Qrx/De+/n/c3zlir2JEWmb/V F9IrYy9RT6/q6UU9vainB/W0Vk9r9bRUT0v1tFRPC/XUXk/t9dRaT4311FgvVKmNfkgaCpFf+y0j 9ULLKPQqkfKD+aur8f2ixpQ+lQp4xhL5fbjeOCmTXhD5wmE88Z64QLqX0+v9MAYegLHwoHmiLWZv k8jeJlEep++WHZAG6ZABTsgEF0zUd5t90+ib8cv4AOM39IY/hWD25QOzdaPNo1w5LZsta7Ss0bJG yxota7Rs9K6MlhNoOYGWNVrWaFmjZY2WNVrWaFmjZY2WNbOmWmqqpaZaaqqlplpqqg33orGmWmqq paZaaqqlplpqqqWmWmqqpaZa0Zaaqqmpmpqqqamamqqpqdr4UwbUUE0N1dRQTQ3V1FBNDdXUUE0N 1dRQjbab6M18c/MLhegrtdIrpRhoBxdDEnSHZOgBPSEFboa+0A/uhfvgfhgDD8BYeBAegodhHDg4 VSDTw0rZkNMgHTLACeNhAmSCCyZCll6plsJ78CF8CtvgJzgIh0CDw3AMTsOfeqX1PLBBNPA+1jbQ Aa4A3sN6K6TCbTBYrxQ3SKq+U4rXD0qX6sclO/JlcDlcAZ3hSugCXSERrgL8o3Q1zOQZzhvSLOK9 6HIf7De/vofYv4TkIfpO+Xa4A4bCnXAX3A3D4B4YDiNgpL5T3aUfV6uID0AN/IzfqCc+qe+0qvpx q5U4Fi6CS8GhH7SmQQZ5ThgPWaT79ONiD29WJlmZseeBDTiVSa0hFtrC+XABXAgXQXvoAOwcpI76 CSmOseukV6Ad41f0UjRUiYbK0VAZGipHQ+VoqBwNlaOhcjRUjobK0VAZGipCQ0XSddTXB26CW2Ag 3A53wJ1wF9wNw2A4jIDRwIqSWE0Sq0kaDxOAVSW5zBUclLLADR76mQuTYDJ9nQLsrqRpkEefp0M+ zICZ5p9lqWS0KqXZ1DPX3JGWMWpljFqZdIRnaomPE58groeTellUe1b8jXoRp+MiSz+9jFEtY1TL GdVyRrWcUS1nVMsZ1XJGtZxRLWdUyxnVcka1XB6FJXgI3PoJmf7KXvBDgNNzLkyCaewO6Y/8KMzD iv8LPmJOc7pQP9FPqF/grb+EHcg7OXnuIq+SvO9gj/nNukzdS14IqmEf7AesFTOpjJlUpNZS7jj8 an7LLmNWlam/6ZpV6CesEsjIKuvCqpdZWyG31kuZbWXW8/UgM67MejFpHUm7FNmOfBlcDp3hSugC 7CKtiXA1JEEysJu2XgPXAvPBej30hhuBuWFlblhT4GboC/2gPzBfrHhCK3PGysnYysnYytyxMnes WHIr88fK/LEyf6zMHyve38ocsjKHrCPp8ygYDffCfbzf/TAGHoCxgJ36X8Tdf5zcVX3v8e9OfuxM QA2aiAYkKhFYMVGyINFmlY01WdyI2ZCNP7LAIskAixB/bIAA7orr1rVtSllage1Wm+522l5607Ua C6M17U7Suq27qcbMTNRVMwMOyhCQH4FA2NPnTEZveh/38fDxuI/e2z9efme+3+/Mzjnndd6fc2aX WC+n6q8KU/WduNp9H63+hjhtRuXNqLwZla/nXv11zl/vni7XbtD+rc59HFaQZlu+fpukj8Xuia6L jYTr6v46mh2ORK9WR04Py6LX2rUtCg9GZ4T7ozPDquh1dmhnub4Yr8cb8EacjSV4E87BuTjPrq8B 13ivzdiCJK7Fdd77enRhm/e/GbfgVmz3c27D7bgDn/Yze9CLIV7PlVCvDYO1OV4wx4fN8b3meNkc 32uOF8zxveb4XnN8rzm+1xzfa47vNcf3muMFczxtjqfNx0HzcdB8HDQHC+ZgwRwsmIMFc3CvObjX HNxrDu41B8vVGn9nKMfODEdi+iD2hrA/pr2xZWFp7IIwFNscDseuhbkeu8nx5nB3bHsYjt3h8V3u 2+m+Uff9teNX8NWwL/YPjnnH4+HwrJeHu2edZq6+2vEsvBmPhyOzjuAJPIlf4ik8jWfwLI7iOTwf jsx+TVg1+7VYhEsl+fvM+VasxftxGT6AdWjDelyODejGNtyMW8Myc3twzrqQmtMRls25Ap1h1Zyr w9ScG8KROZ9CN+TAnD7Hz8FuYM4fOQ65708cv+Q1f+74l57/lWM+7J1zCD/AD/EjTLvnx/gJfgp1 fk4Jj4YH5/wcvwj3z3kMZe/xuPeXdXOewFG7gi/JgS+jkjf77Sz+HQc8/341VwoypCBDCjIkLTcK cqMgJ8pyoiAj9sqIgowYlBEF+bBXPhTMv0Hzb9D8GzT/Bk+aawVzrWCuDZtrw+baXnOtbK6VzbXK PBs0zwrm2V7zrGBuleutYOufDPfW/zLsqH8qPFD/dNhT/0xYW/9saKw/GtrqK5/n+bCz/lg4Uv8C XsRxr3nJ/TOhrz6EB+JRmIjXhbXxWGiIzwqb4uZnfE4oxeeGe+P1YUc87p5E2BOf555TQmP81NAW f1noi7/ctVdgftgaPy0sjr8yzI+/KvTEF4TO+ELXX+3a6XiN5691zyL3nOGeM8Mp8de57yznX+++ N+CNODtsjC9x35vCwvg57jvXscH5N3uP8/EW9y91fZn3eavrb/M+F7i+3LVGXOj6Ra6/3fWLXV/h +jv8nHc63xTS8Xe55924RLuaw4r4qrAo/p6wO/7b3uO9Xrfaa9Z4bYvjpTNfidt1x1tnnotfFsbi H/C6dWgLA/H1YTB+uddv8Pp2fbZR/3wwdMc/7L6PeK9N6HDfFe670n1Xua9Tv8nP+DXeYzPsxONJ 1691/TrXr/c+xXA4/jAewc9QwqP4OX6Bx1DG4ziCJ/Akfomn8DSewbM4iufwPI7hBbwIGRB/CTMI 4XAiQh3Mt8THQilxY9iRuCn0JbaGBxIfDxOJT4S1iU+GhsSnwqaEuZi4OexM3OKeW0M6sd09t4WN idtdvyM0JXq8rhefwZ3OfzZsTfSFhYnPhfmJfsfPe90AvgA75cTvhS2J3w+LEztc/4OZ44k/DGOJ u712EPeEgcQfhcHEH4cViS+GRYl7Q2Pifj9vyGv/BMOhJ/GnPtOXXP+y6/8Ylib+GRNhKPGvjnmf 9RCOeP4EngtL570s7Ju3HI24LNw9ry0Mz+sMh+ddjZs9vgW94W57tr11L1el0ipUSoWaUqGmVKgu FWpAhcqrUGkVKq1CpVWotAqVVqHSKlRahUqrUGkVKq1CDapQg9W/IrrOe12PLmzzfjfDqkxFmlKR BlSkARVpQEUaUJHyKlJeRcpX/gJHNUirBmnVIKcapFWDlGrQJfHTEj8l8bskfkrip6R9SqKnJXpa oqclelqipyV6WqKnJXpaoqclelqipyV6WqIPSPQBiT4glVO1vxSZksopqZySygNSOS+V01I5LZXT UnlQKqelcloq56VyWioPSOW0VE5J5bRUHpDKaQmcksApCZySwCkJPCWBpyTwlASeksBdErhLAg9I 4LwEzkvgvATO1xJuQsJN1BJut4TrknBtEm5NLeEGJVxawqUlXLqWcHsk3J5awu2RcJ0Sbo2Ea5Nw 6VrCTUi4iVrC7ZZwXRKuTcKtkXC7JdyEhJuQcH0SrlPCtUm4ByRcl4TbLeEmJNyEhBuQcH0SrlPC tUm4xRLuAQnXJeEekHB7JNweCdcj4fok3EYJt0bCLZZwuyXchISbkHADEq5PwnVKuDYJt1jC7ZZw ExJuQsINSLg+Cdcp4dok3GIJ94CE65JwUxJuQsJNSLgHJFynhGuTcFMSblDC9Um4NgnXKeHaJNzj Eu6BeKtkusxn+4DXrUObe9dLqMvdt8F9JxJuTy3hdku4PRJuj4QbrCXcRgm3RsI1SLg9Em5Cwk1I uEEJt0PCdUq4tkrCSZl0LWX2SJk9tZTZI2U6pcwaKdMmZdJSZkLKTJyUMl1Spq2WMg9ImT1SZo+U 6ZEyfVJmo5RZI2UWS5ndUmZCykxImQEps13KdEqZtsQfSJo/dP1urx3EPRLmRMpslDJrpEyDlNkt ZSakzISUGZQyW6RMp5RpkzIpKZOSMl1SJiVl0lImLWW6pEyXlElFfbF7wgYr3f2xUijOisL5cy+P Ntc/Ea2rfzK6qv6XeDpaXf9M1F7/bNRa/5zj89HF9ccdX3JtJroqHkWr43XRunjMcY7jXOfqkfB8 XtQePyVqjb8ML3fuFZjv8WnOv9LxVe5fEF0cX+jxq107Ha/1eJHrZzi+zvWzXH+9x29w7Y1Y4n3f 5Pw5jg3Ov9m587HU42Ve91bHC7DcuUZc5PHbnb/Y8R1e907v1+Txu1x7Ny7xuNn1VY7vcf23XX+v x6uxxvkWx/c53+r8ZR5/wGvWYb3Hl7u+wXGj6x90/cMef8S1TbjC57vS+ascP+r8Nc5tRtLja73u uqg18bGoPXFjdFXiJnw8Wp34RLQu8UnHbc7f7Nwt2O6+2zy/3bEHvc59Bp91X5/7P+f4eecHnPsC fs/j33f/Dsc/xN3ODeKP3PfH7v+i4/3ODzn3J/hTj7/k/i9HrdFn2XB+rPJf9kThopNMaGdCOxOa mdDKhGYmtDLhPCasY0I7E9qZ0MyEViasrJnQzoR2JjQzoZUJzUxoZkI7E9qZ0MyEViY0M2E1E5Yy oZkJ7UxoZ0IzE1qZ0MyE1UxYyoRmJrQzoZ0JK5nQyoSVTGhmQjsT2pnQzIRWJjQzoZkJ7UxoZ0Iz E1qZ0MyE1UxYyoRmJrQzoZ0JzUxoZUIzE1YzYSkTmpnQzIRWJjQzYTUTljKhmQntTGhnQjMTWpnQ zITVTFjKhGYmtDOhnQkrmdDKhJVMaGZCOxPamdDMhFYmNDNhHRPamdDOhGYmtDJhJRPWMaGdCe1M aGZCKxOamdDMhHYmtDNhJRNambCSCc1MaGdCOxOamdDKhGYmNDOhnQntTFjJhFYmrGRCMxPamdDO hGYmtDKhWS68IWpQuYerFe0pe+anreOfsQ5/NvSoZJtUslJ1rf6Sdf0MQrVq9ala3arW1mrFiltD JsJelWqHStWjUm1SqaZVqB4VaocK1aNC5VWoLSrUtMo0pjL1qEw7VKYelWmRypRXmbaoTAdUprLK VFaZUipTt8rUpzJ1q0zzVaZpFWlMRepRkXaoSD0q0iIVaVolGlOJelSiHSpRj0q0SCXKq0RbVKJp FahHBdqhAvWoQHkVaIsK1KMC9ahAO1SgnvilXvM+11pdu8xr2rznej//ctc3uH6i8uRVnq0qzwGV p6zylFWelMrTp/L0qTzdtcozreKMqTh9Ks4OFaenWnFuDGWVpqzSVKpMnyrTrcpsVVkmVJYxlWWH ytKjsqxRWQ6oLGWVpayypFSWbpWlT2XpVlnmqyzTKsqYitKjouxQUXpUlEUqygEVpayilFWUlIrS p6L0qSjdtYoyrZKMqSQ9KskOlaQnStV1hXRlt19d053Y3aeru/qbHbeH/SyZsu7ptu7ZxJZ72ZJi SyNbFrKliS0TbOmz1skzppsxmxiz01onxZpG1ixkTRNrpqxzuq1zNrHnXvak2NPInoXsaWLPRuuc NdY5a1i0Nn7azI/jr5w5xKJNLGpk0UbrnDXWOWvYtIxNa+OL3HOGe86cKbJpE5sa2bSRTU1samLT Mjatjb/Jfee471xrjQbX3+w9zsdbXF/q+jLX3+r627zPBa4vd60RF7p+ketvd/1i11e4/g4/551+ TpMRfpd73o1LvKbZe6+a2c+y7SxrYtna+GqvWeO1Lc5fOrONZQ12ct9g2aB1Tpt1zhq2bWFbF9vm xzfMPMW2uWwbZFsb2wbZ1sa2JrZtYVsX2+bHr3Jfp+NHXb/G9c3eZ4vrSdevdf46168Pc61x8szr Zt4m5u20xkmxr5F9C9nXlNjGiJutTW5x/Vbrme3WGbc5f3s4hYkNTNzIxCYmNjFxGRPXJvpmfpz4 3MyhRP/M40zstMZZY42zhpFNjFyV+H3nd7j+BzNFRg4yso2RTYzcwsguRs5PfHHmKUbOZ+SANU6b Nc4aZm5h5ipmzk98eebRqJ2RR9nIwGgB80rMK7BumnXbGTfGsjLL8iwrsOzAiWyKFrCrxK4Cs6aZ tZ1N0/JomkVjzCkzZ1oGTcug7YwZY8gBeVOQNwfkzVZWlFkxLWem5cx2FpRZMC1fpuXLdqM/ZsSn Zcq0kR4z0tPyZFqWTMuS7XJkzKiWjeq0/Jg2otuN5pjRO2D0CrLigNHbasTKRmxaRkwbre1GqGyE 8kaoYIQOVPNhW7TAyJSNTMGoTBuV7UbhgDwoyIMD8mCrni/r+Wk5MC0HtuvlA3q5YN4f0Mtb9WxZ z06b79PRTr26zzy/W8/ebW7nze0xczulh3fq4Z3m9ha9vFYvr6iv/E7jeb19Ym6nzO2dtbm9U69v 0utNen2FuZ03t8fM7ZTe36n3d5rbW4zAWiOwwtweNLdT5nbKaHSpEGuNyApz+16j0mZuD5rbKXM7 ZYS2GqEulWKtUVpR+5bmXiPVZm4Pmts7ze2d5vYWI9dl5FYZuUYjV2duD5rbKXM7ZRS3GsUuFWOt kVxR+5Zm0NxOmdspo7rVqHapHGuN7IratzT3Gt02c3vM3E6Z2ykj3aeCtBntFeb2WK2CdBnxFSrI WqO+wtz+vrm9w8gvrH1LkzK3Uyzoq1WSNiY0MWGJuT3Ghi21b2l2mts7ze0+dvSwo40djexYWPuW JmVup5jSV6sobWxpYsuS2txOmds7a3N7J3M2MaeJOStqc3vM3E7V5vYOc3sLi5pYtMzcHjS3d5rb O83tLazqYtUqVjWyqs7cHja3U+Z2imFbGdal2qxl2QqW1dW+Jdlpbu80t/tY18O6NtY1sm6huT1m bqfM7RQD+xjYZW63sXBF9BfV/9rzRNX5LhtXsXFfreoMqzpjzCwzc5CZA8zcXVujtDFz2UlrlBQz y8wcZOYAM3czc4qZbcxcxswtzCwzc5CZA8zcXVuztDFzWW3NsoOZA8wcYGY3MxuYuZCZfbW1yw5m DjBzgJmbmNnNzAZmLqytYfpqa5jK94c9zOxh5iZm9jBzMTNPYeYiZu5g5gAzB5i5iZndzGxg5sLa WmYHMweYOcDMTczsZmYDMxfW1jR9tTXNHmYOMHOgtrtuZOZCZqaZuYOZ3cxcyMwGZi5k5t8wc6uq c7xm5iAzB2q763uZ2cTMJcxsrJnZx8w0MweY2VPbXe9kZiMzlzCzqWbmIDMHarvre5nZxMwlzGxk ZpmZg8wcYOZuZk4xs42Zy5i5hZUPsHLgpLXPJlYuq619Kt/d9bCyh5WbWNnDysWsPIWVi2rf3Q2w coCVW2pWNrByISvnsjLNygFW9tR21TtZ2cjKJaxsqlk5yMqBmpWdrGxi5cJouLYG+jwbP8++PPvy NfvS7OtmX2ft2+wy+4aZN8W8qZp5aeZ1MW9T9buduTKxHiesS7Oum3WdtW+t06zLsy7PugHWdbOu k3V7WNfNujTr8qzLs26QdQOs62ZdJ+uWsG4P67pZt5t1U6ybYt1A7TudLtZtYt0S1qVZl2ddnnWD rBtgXTfrOlm3hHVp1uVZl2fdIOsGWNfNuk7WLWHdHtZ1sy7Pujzr8qzbzbpu1nXWVtT3sm6AdZ2s 62ZdJ+ueY90eebiGdXtZl2ddnnXDtW+tu1nXWbNugnU9NeumWDd10nc6XazbVPvWei/r8qzLs264 9q11N+s6q9bdyLKbcMK4NOO6GLep+l3OzbLyFtxq9b1dHt1mTXS7kT/xPc5uxk0xbopxA7XvcboY t4lxSxiXZlyecXnGDTKuj3HdjOusrborxk0xbuqk73G6GLep9m3xXsblGZdn3DDjtjKum3GdUX3d K6LllX+BIfZg9FuxcrR51puiC+q/ED1Z+S9WogUnXb2geuWpaHl9iJbH43gNzsZbcCHa0IEt0fLE VtwaXZC40/F3cQ+Go+XRe2NnhmRsMc7B5tAYuxY34Q7cFa6MZcKh2D58G9/F95HDz/BsOFR/LCTr X8CLIRmfjaKReRiP4Gco4VH8HL/AYyjjcRzBE3gSv8RTeBp2E/FncRTP4Xkcwwt4EcfxEmYQ9GgE O4vEDSGZ6EY+XJk4FK6cFw+H5iWwGOfiPDTgQlyEd4ZDpx7DC3gRxzETDkXzf/WvntQ9FnaZ/xti bwujseXhitgl4a7Ye2VCa5iMrQ/9sY2uf9Djm8PW2K0e3xbumrUh3B2dFjszmhdbjHOwLByOvTU8 JEWe8S7l2G+Fh+rHcSyaV/8CXozmxWdjbXgo/v7wUOKGaF6iu/Lfx9Qdnjlc9zAewRNRQ93TOOrx c3g+9Ncd9xnODC1GsEVWTcbOxjkev9lxmc/5tpCJNfpcTaHJZ98Va9aOVViDFtffF8Zi7/cel3n+ gbA+to4Fbdq4Ptweu9z1DeET2jipjbnYh1z/sPf5iHs7cEXUELsSV3l9p+tX46O4xn2bVfBrUang N4T7GbUq9knHW322291/h+d3ev650F//zTBZ/y18z+Pv46fh/vrDKOJYaGFXC7ta2NUS/1DYFb8a XarLDfgYbsRN2IqP4xOw5onbz8S7sQ034xbciu2wp4lb98TN9/in0QP7mrh9TfxOfBZ9YTT+OfTj d/B5DKh0X3D8Xfw5RqKG+Gi0Ov4Xjin8pd3GX0Xr4n/t8f9wfAB/4/H/dO8ux7+NVsbHHL+Cvwv9 8a/ia9iNr+Pv8SAeQjqsj38D3wy5+D/gW9iDf8Q/YRwZ7MU+/DP+Bd/GBP4V/4bveI9JTGE//h3f xfdwAN/HQWSRQx6H8AP8ED/CNH6Mn+CnOIwCitbaD+MR/AwlPIqf4xd4DGU8jiN4Ak/il3gKT+MZ PIujeA7P4xhewIs4jpcwg2A9GqEOS2XYW6PzEm/DhdHKxMXh/sQKvAPvxG9hJZrwLlwW+hMfwDq0 wfxNXI4NaMdGfBAfwofxEWxCB67AleB6ohNX46O4BpuxBUlci+twPbpwQ2iRSC2Ju8KuxH1hVzRb shyWLIermXBzOBCd61mu7li0vu6laL35WzR3i65mfj2/bjCHPlldCefMmbL5UjRfiuZJ2Twpmyfl mocNJ3nYwMOGmocNPGyoenjCwYZfOajPyvqsrM/K+qysz8r6rKzPyonKvxwwV6qUYktD3if6pvzK VD/F9pCLhn71ryTJoXTdC+Huuhe17LjHMx4HrYvJlllhW2y24xxH+8FYvePZ4eva+PXY0ug873pU Rn0idkG0QEblqvnaLKfeK3PWeN7iJ18aNcqoSdmUk02V3F1fy6Z0NXs/5H0/7HkHrnDvlbjK+f+c SWP6Ma0f07Ftrt8cUrKoX17fr0/T+vTr+vTrMmhSBk3q27S+TevbtKzJyZqcrMnJmpysycmanKzJ yZqcrMnJmpysycmanKzJyZqcrMnJmpysycmanKzJyZqcrMnJmpysycmanKzJyZKcMWw0ho3GsNEY NhrDRmPYaAwbjWGjMWw0ho2yJGccG41jo3FsNI6NsmRSlkzKkklZMilLJmXJpCyZlCWT/wUZMiZD xmTImAwZkyFjMmRMhozJkDEZMiZDxmTImAwZkyFjMmRMhozJkDEZMiZDxmTImAwZkyFjMmRMhoxx MM3BNAfTHExzMM3BNAfTHExb8Rxm1sN4BEfxHLvOtP5Q11W7Q9W6utmsuRY34Q6zQ11XOQ6pHIdU jkOSqiipipKqKKmKkqooqYqSqiipipKqKKmKkqooqYqSqiipipKqKKmKkqooqYqSqiipipKqKKmK kqooqYqSqiipipKqKKmKkqooqYqSqigFDkmBQ9Erubzg1/N6m1rxfzlvrROtULT7QHW2XBqyZkem Ojs2mJuzzamHzJNRtTvH82zd6/XhGXWFsL+uiIc9fgQ/C0sr/5KYPj1Dn55hJm+sOyaNXsBxj19y nPEOsbDUTE6byUvN5LSZvNRMThuDTmPQWU2tcxwryfU2n+ECs7opdNRWHLusOHbF7AzM6Ltqq45+ M3pbbdVxrc/+CZ/9d3ziXbWZPXTSqiNpdndYdewyw+86adWx7X+b4cnqqmNL9e/QVsWuq/0tWpfj DeG+2Mccb0RlJbLV8eP4pPOfcuyuZnGlp5LVlcmnPe/FZ/ycO8N99W8Ph3+dut8L2yTENglxn4S4 T0LcV/+o64/hCI7ZEb6AF+1CZqMrdEiPDunRIT06pEeH9OiQHh3So0N6dEiPDunRIT06pEeH9OiQ Hh3So0N6dEiPDunRIT06pEeH9OiQHh3So0N6dFip7LJS2WWlsstKZZeVyi4rlb1WKrusVHZJl7tq pi0/YZod019G5zFtc8201UxbXVup3FWzbXPNtgXSZZt02SZdtkmXbdJlm3QZli7bpMs2K5VrrVSu /S9ImaSUSUqZpJRJSpmklElKmaSUSUqZpJRJSpmklElKmaSUSUqZpJRJSpmklElKmaSUSUqZpJRJ Spnkf+tKJRYOJ2ZhNuZgLuoRRwLzcApOxcvwcrwC83EaXolXYQEW4tU4Ha/Ba7EIZ+BMvA5nYTFe jzfgjTgbS/AmnINzcR4a8Gacj7egsqqyNrGyWm5ltTxxgcfL0Qi7ysRFjuaD1L5Pat8nte+T2vdJ 7fuk9n1S+z6pfV/i3e65pPr3W52yr1Otr+yhms3gShK0mN3v8/gyM3udPUGb43ps8Hijo3VYbUY2 mimDZkeX2dFldnSZAYOs72L7GNPHmD7F7JWsLvwvqz3+1fp7l8cnbD6LzcuZO5Zo0JIT68fVWrla y9ZF62TkqGwclY2jMnFUJo7KuEkZN2kdlJFxk9ZClb9y6refS8q5u+zlkvI3J3uycicrX7LVT36L e7fLnzs8/6zHfVYV4/bJjzj+DCUcwwt4UYWejbU8fX/V1SxXs1zNcjXL1SxXs1zNcjXL1SxXs1zN cjXL1SxXs1zNcjXL1SxXs1zNcjXL1SxXs1zNcjXL1SxXs1zNcjXL1SxXs1zNJprDZGIV3oPfhpVY YjXWwKglLsX7YAecWAsrM2M8aYwnoxEV5fOVf/lRJdmnimyzJtyvkuxTRbZZE+5XSVIqSZdKklJJ ulSSlErSpYJ8TfX42klrwsHq+u/9YV/Vi8s580Ej8J/XePtUgLwKkFcB8rEt0eLYdehCZa33Mccb sRUfR2Xt9ynHbmyT7CfWgKOxT3vei8+gshZ8e7RY2n9N2n9N2u+T9vtOXg/WP+r6YzgSLf4vWLft k6z7JOs+ybpPsu7j5z7Juk+y7pOoeYmal6h5iZqXqHmJmpeoeYmal6h5iZqXqHmJmpeoeYmal6h5 iZpPxKLFiVmYjTmYi3rEkcA8nIJT8TK8HK/AfJyGV+JVWICFeDVOx2vwWizCGTgTr8NZWIzX4w14 I87GErwJ5+BcnIcGvBnn4y1YimV4K96GC7AcjbgQF8HY/Kb1YuLd7rkkWhzdZu72m7v95m2/9ci4 9MnUdhIPSpzKOqOye8hYX4xXdwzXeLzZfL4WN1XXAslf7wiOhX5ztd9c7TdX+9X1cXV9XF0fV9fH 1fVxdX1cWo2r6+Pq+ri6Pi65xiXXuOQaV9fH1fVxdX1cXR9X18fV9XF1fVyqjavr4+r6uLo+LuHG mbScSTf9Osn+Vrp9RYr9ptX+d0JGHc2ooxl1NKOOZtTRjDqaUUcz6mhGHc2ooxl1NKOOZtTRjDqa UUcz6mhGHc2ooxl1NKOOZtTRjDqakU1J2ZSUTUnZlJRNSdmUlE1J2ZSUTUnZlJRNSdmUlE1J2ZSU TUnZlJRNSdmUlE1J2ZSUTUnZlJRNSdmUjFe+RzyOlzCDEJKyKSmbkgxZyY6V7FhZrUU32GF3h/7o tPog3+N4Dc7GW3Ah2tCBLdHmxFbcijvxu7gH90YLEsOOfxadFdXFKv8+Xp28mYxmWZdOWtdMWtdM Wk9fwpbLZExlhWpNHX2MT6O13Wom1urs+61Z1znX5vF67lzu/AbXP+jch/j34eo3Zk2Sq4lrQ5Ir I7kykivDu36eDfFsiFejvBrl1SivRnk1yqtRXo3yapRXo7wa5dUor0Z5NcqrUV6N8mqUV6O8GuXV KK9GeTXKq1FejfJqlFeVb62aJFaTxGqSWE08a+JZk8Rq4loT15okVpO0auJck7Rq4l0T74Z4N8S7 Id4N8W6Id0O8G+LdkLTKSKuMtMpIq4y0ykirjLTKSKuMtMpIq4y0ykirjLTKSKuMtMpIqwxv+3nb z9t+3vbztp+3/bzt520/b/t528/bft7287aft/287edtP2/7edvP237e9vO2n7f9vK38/xheGq2M 3lP9lqG5Ol4543XYGJWNT676DcJV1X1EzljkjEXu/8vO/+/wVXwNu/F1/D0exEPVNXFOn+T0SU6f 5PRJTp/k9ElOn+Tilc95EFnkkMch/AA/xI8wjR/jJ/gpDqPA4tcwt5OtLWwdru24hpk5zMxhZg4b 0WEjOmxEh43osBEdNqLDRnTYiA4b0WEjOmxEh43osBEdNqLDRnTYiA5HcytzyvqoHFuLk+dUZSQm Xc3VRqKSxrnaSEz+H0Zi0khMGolJIzFpJCaNxKSRmDQSk0Zi0khMGolJIzFpJCaNxKSRmDQSk0Zi 0khMGolJIzFpJCaNxKSRmDQSk0Zi8r91JGbJknIleYzCiQw6cS5XO5eLYvInU8mfqEXPjVTvb67u oyf1665qTVtf3f9n9OJdenGkVtPu+lUN04sjenFEL47oxRG9OKIXR/TiiF4c0YsjenFEL47oxRG9 OKIXR/TiiF4c0YsjenFEL47oxRG9OKIXR/TiiF4c0Ysjv7E2pe1Hv4Hv2GdOYgr78e/4Lr6HA/g+ DiKLHPI4hB/gh/gRpvFj/AQ/xWEUwl3RHL2TqVp3WbUHK5k9GSXqjoRc3RN4Ck9Xv22sXH2w0r+z 3hF2zXqn3t2od7O1by1K1ZV9xc3LrUs3RitrfmZjH3Gtsqe5Gh/FNVVHs3o3q3ezejerd7N6N6t3 s3o3q3ezejerd7N6N6t3s3o3q3ezejerd7N6N6t3s3o3q3ezejerd7N6N6t3s3b6JTv9kr1PyU6/ ZP9Tsv8p2emX7PRL8W9aIfwDvoU9+Ef8E8aRwV7swz/jX/BtTOBf8W/4f+l4XaU3q1ZP/rqOzq3+ pq3yW7YTv0F7KHZb+MSsDeHz0UJnpu2iMnZRR+ygMnZQGbunjN1Txu4pY6eSsVPJ2Klk7FQydioZ O5WMnUrGTiVjp5KxU8nYqWTsVDJ2KpnoQ/Z48+zx5tnjzbPHm2ePN8+ar8War6X226qMtV+L3UKm tgMdj93u893h3J3OfS7sshvI2A1k7AYq66EW66EW66EW66EW66EW66EW66EW66EW66EW66EW66EW 66EW66EW66EW66EW66EW66EW66EW66EW66EW66EW66EW66EW66GWeOU3X8fxEmYQQov1UIv1UIuV cMZKOGMlnLESzlgJZ6yEM1bCGSvhTOKysCshGxLrYF2S0OuJy7EB7diID+JD+DA+gk3owBW4Eleh E1fjo7gGm7EFSVyL63A9usyfyr9WcLj2lzuHo1dVn8UwG3Or38Ud1bdHK1f151F9eVRfHtWXR7Xn qPYc1Z6j2nNUe45qz1HtOao9R7lzffWVE5w4GC2u/LsIdUeihronogvqnowW1D1V/Q3pBXXPePy8 a8ft8GIq2WzMxenRAj//oJ9/0A7wvOpvbO8MB2e9O1owa0PU4LMc9FkO+iwHfZaDPstBn+Wgz3LQ Zznosxz0WQ76LAej85hUZlKZSWUmlZlUZlKJSSUGlRhTYkeJHSV2lNhRYkeJHSV2lNhRYkeJHSV2 lNhRYkeJHSV2lNhRYkeJHSV2lNhRYkeJHSV2lNhRYkeJHSV2lNhRYkeJHSV2lMy37WG//1UDo0t8 2lU+7SqftvIvaezziVf5xKv0U+W3NpUx2q+f9uun/fopoSW9WtJbHa+bHCtjdqsWVmbjHZ4bO/2W OHn8tLZXa3u1tldre7W2V2t7tbZXa3u1tldre7W2V2t7tbZXa3u1tldre7W2V2t7tbZXa3u1tldr e7W2V2t7tbZXa3u1tldre7W2V2t7tbb3N7oTi06ptiAbvUtf5PRFTl/k9ENOP1S+vylob4FhBe0t sGxI+gxVftelvQUJNCSBhiTQkAQakkBD2lvQ3oL2FrS3oL0F7S1ob0F7C9pb0N6C9ha0t6C9Be0t aG9BewvaW9DegvYWtLegvQXtLWhvQXsL2lvQ3oL2FrS3oL0F7S1ob0H6DUm/Iek3JP2GpN+Q9BuS fkPSb0j6DUm/Iek3JP2GpN9QdHr1d3bPV7/dz1V/P1f53dzc6u/Gika4aFacVUu9USNc+R1j0egW jW5RDxf1cFEPF/VwUQ8X9XBRDxf1cFF9rf3VRGzE+uOrXHkwPBn7Fz495nE5lKt/GRF3tRhLhXRs OhxK/Jv9+neQxS9Cet7scCg6JXZPON1dU7FdYbfXfzr2UxRCV6xkPj8WnTormjkya364ctYZIWVd 9GB0fqwcnV+tJSd+t3qPn/lVP/sx8/r11d9ijoSB2N6wz7vtrZ6NQt47dFf+6/+Q8iwVXVd3eOZ4 3cN4BJWWHHV8Ds9Xv8Pa/59myF1aeE94d+yPPf6itgzNFGN/Gs2P/Rn+XH+OhgOxv/P4G85/y/N/ 8jjjk+1DpUe+7TgVGmLfdfw+stHFsZxjJS2fcP4pz5/1+Kjj8XD7rHl672VYjGWhnPhG2J/4pj7b G81PTIQDie96fmCmmLBKSlglJX7s+U9c/ymK7nkYj0C7EqUwlngUP8cRr30Cz3jtUdePzRTnxcPh eQm8OjTMW+x4Ls5DA86PLp73FizFhZ5fhBXue6djk6NV/rzOcPu8q3GDxx/DjegJ5VN/Ec0/9TGU 8TiewPPRxace+w/qzgW+iuL8+zOzN86eAEGRmxYqikREVCwQEUSxRUBE1BQloGIbUUGjctGogDWo BE0roMaq9N94Q4y2jTZtNSpKDRq0BOVSSV9UbgJKCOGIXCJm3u/OOUlObtztZffzOzs7Ozvz7DPP /J5n9pw9q9clVILvAEyUUKXXNW+my5qHANfdPAy4duHU9O9z2FjQi4m6SCRUf4tFf0wzT7f9kXn6 B+yv1XOwmpkxqzkVS1hmddFfCd/Y1wccWc8Zmym1VZyIDYiEDXp8QkQnJ+zU85pLnSwugSlKYYpS mKIUpiiFKUrp+43UkE/fF9L3JeopPVc9o6fT73Pp90L1EulXwZvsv812Idv38DyLQTEogU0+YbsS fAo2AZhBfWvs8k1L6XLL03OsJD2Hfi6kn0tC7+rpoffBEvY/ZPsJ2xV6Lv29kf7eSH8X0t8l9HcJ fVxCH8+lj+fSx3Pp40L6uDC0k/Ruzt2r5/rNRGs/BNro9X4ntl1BEjgV/AT0Askc68u2P9sLdbk/ CozWc/xxbKeyvU/PSdgrWidUgu/APlAlWpt+MneB6Y25sXF4FuP+UXGiGfuviwFov5wxmxLaJgr8 s0SeP0Xk4ameY/TPRb8nmh4yY0rPVrngGfr1WVjkOf0T9Bv08Wx0vEy9xjYYY2+TXsjxRey/V7VY La4Kxvo8Vcx2qe6nSqrWqY/ZfsL+crYrwErSq9h+yna1Pk/9q2qP+oy61laVq3Xkr68qVRvZbuL4 ZtJb9GT1Ffga+yonfzt1VrDdCb6tWgwrrbQ84GuXsepaLUBLPQwrda024HjQEXQCSZTrxvY0jvfQ Lv27LFSkZ9PHy+jf6rF8In17YmgD+RvBl2AzY38L+AqYMUvebsozbkOVul+oSvfzJVDAZiw7bF3g gWZVi/0Q8Ek31+f5Ldi2rNrjJ4LjSLepWue3ZdsOtCevE2W7kD4FdCWdBE4FPTh2BnlngrP0PL8n dZ0NfsKxXiCZes7hWF/S57Ltz/4w7frDweiqlfCCCy+48ILr36qH+beB28FUjk0n715wX9XKhK/1 7IStoAxsA9vB3qrFCZXgO7APVFUthitcuMKFK1y4woUr3OY/1f1Ee6xoA5YzAG+TgtUMwGIGYCkD 6JmZ1rF6Mb0ykx6ZSU/MpAcGoP0BaH8AXikFr5SCV0rBK6Wg4QFIP9O/Qi/2U8A1YCK4l3nKUCx9 mYS/JLylLOAAz/zryS5a/8Jw0vOk57N9if1XwdtgKfb6MVgOVoBVgHkVtleG3RmPiZ2VYWNlihkr dlamiFaQ/lOrFX6gDduOoJv+FOm/QPov4IddXMEXXMEyrmAZV7AMO9qFHe3iSpbBBbvggl1c0RfY Sxn2Uoa9lGEvZdhKGbZShq2UYSNl2EcZdlGGTZRhE2XYQhm2UOafpj/1u4PTwRnsnwnOAecC5tv+ ZWzvAHeCe/WnCcQbzYO3jbRCI6vok1IYswh2LIIJS2G+UjxcBWxWhKSrkHQVTFUESxXBTqWwUCkM VIpXqcCrVIgTqGE9ek1Gr/noNBGdJqPTZKKNneg1Gf3MY8ytpoeL0NE8dDQPHc1DR8noKBn9JKOf RPSTiH4S0Usi+khG9nn0cBE9XEQPF9HDRcg/T6jAygOfQByxBGmDuEUjEbGK3xp0hrU89S8Y7TOY 0QYtQSJoD3rociHhuJ7w22a9k88PiJWCz1Lzr3VlzJi2ciUf6B0c3yNUEJ2bowqGHMqZmaILfqg/ fqg/fqg/fqg/fqg/8QQ8Z8ouJp5YjDYTiCcWE08sJpZYjHfLV0FdW8BXAB+IthOIKxbj4+EC0EYn 4OMX4+MZ3+BU8BPQCyRzrC/b/joBH824A9+BfaBKLxatZLnOl9vh+gjbb/Cnq+mZqB7WW+foaVZf PQ19rIdt1tfXCayxHtZYj094T0e4jgjXEEH+CPJHGAcRriFCjRGuIYL9R5A7gv1HkD2C7BFqjSB7 BNkjyB5B9gi2GcE2I9hmhBYitBDheiJcT4RriWCLEa4lwrVEuJYI1xLhWiLmd3mFRAiRIEIw9x9c bGgHNlSKTZRiE6XYRCk2USosvHQyR8tg9BL6dopYaHpynZDkfsanQDtBP24OSkV7lLp3mSNniw70 5gZ6cwO9uYHe3EBvBs/jz8fzl+L587HgfDzHBqw3H+vNJxLIx4Lz8RYb8MSlWGo+3rgUb5yPNy6F RTfAohtg0Q145nysNh/vnG+kmmekWi3a0IJL7S7+KQv/lEXueK4gC3+URQsufigLns6iVheOzoKj s+DoLGp04eUsanTh2iy4NguuzYJrs+DaLNGcmkuROYUay9HYNOROQe4UZE5B1hQ0OA0NTkOD09Dg NORLEYF/rKBkBSUrKFlByQqOVDCW9lEfDGeYZCzXdx2IMYo4htaWWZ7oxfk30mI+LU6inhup50Yr ifxu+kbqupFWJ9HqJH+06EXLk2h5kj+V9L0cu0/0MuOxkN4cTftj9D+ta/VWpBqtt7O33rpab7Ou 0d+Q+4l1nV4rHHI3kFtG7k5yv7YCNlLkbjJnetZVeiNnb6XMTsosJfc1a6zeTblVwuboFnL/H7mf k1NKzhjKX21aeJ2cclNml5XKFY4GY/QTpvZt1rXC59hoah2DbV5NmWsDdrBuw74m6S1cwW36A1Kf WVP0DkrehiVPhP8mUXKK/pb+v01vE82sm7HnW8hLp5du1aus25FoItc+SedRbik1TkILU4yFpzPL iuZ/RI03U+o2tHw7Vz9Rv2pqjBgJvqTUF5R/ljafp9deEF05uiD4No3P5uazQ/CpXzTpY026VCS6 V4hiN0Wkuy+Ljt4jusT/Hah900iJ/wp4lejwNZHhv8P2XbbLyPuYWWLwRhEr9pbJ+cF/DZvxW+Y/ KnrG3qcxz9g+o9McdWW5SJPbRbGMsP1GFFvniAKrryhgbG43OWlChc83bzQdUfNO0MbfvrnOvHkj +gZOK/jfBFpzwwODFtlrLTqLWSJXZMMJc6mrUOQqIdJcIWe7ErQkfYpY7vYBg8RCd7jIdS8Fi+RE t1j29tqKXO8BOdubJZ/3HgKzxXL/YeLjF+Rsfz5YIIr9l0Dwb66FotjIPEikhVPlU+Ffkh4nMrmG 5eGbzLtAgn9Ab+zfz5eIQcE/Zpt/nq7+h+jqf4a+QmSaf1Z+SAxC/4HuM9B9WvBvu6Kt3Cr6octM tJaJLjPRXKZqKzKtAZx1pD2qOJrGkTRhk0qPlUsPyomwK4XvLhIF3gPC92bRwkOio/+C8P35YAF9 /xIo1GXhVGzPc4V5g0uZ91DwrlW9mqOrObo6nBrMI9HicrS4HA0up/xCNJYkLHLzyM0jN8+USWcv nb10ygRaTRNtxdOcH/w3cOx/gWv+B1iIDCTMMP8B/CLtPiAykDITKbPRw3j0MB49jEfidCROb6T2 dPEjLCcPq0kTT0ctR+xjWwW0GIEV5dgXiRH2YDGC1tbQ2hosKXinyAj3RTGCFtfQ4iZa3ITV+LS0 nJaW09IaWlpDS2toaVMDKzmBlnLMm1Zib1mpfguK2xwraEntA6NvBqGF5bSwhhbWUHsxtRc3Yo8Z xh4Hs71KpNLiGlocRIsZtFhMi5lmNGZgQRlYUAYWlGHeJvQuUlwoz2Y09gK9QR+QDM4BA0Wl/Cn4 GRgELgKDwRAwDIwWPeUvwTjK0lNyPOlbwK3gNnA7mAgmgcngHjANTAe/EiPkFpEjvwZbxSakq0S6 SlkBX+wwnFGJlJVyJ+lvRTH2Xgl/FMMfxdh9pbVEbLJHijT7SnAVGAVSwWgwBlwtKm1ksZHDRg4b Oewp4A7R0/1CVLp74IRKtt+JSu9UkeZ1A6djBe246hyuOoerzuGqc7jqHK46h6vO4aoDaTORttgw WwVXvQNESMNwSJuGtGlIm4OUOUiZiSQ5tJhDazm0lgP7rTP/4VwkTpauHi9/DE4EncFJ4GTQBZwC uoIkcCroppPlaTrZHqLH20PBxWAYuAQMB5eCEeAycDm4AqTo8e7nYBMI3g28RSe7u9ju1uM9D7QA x4FOYIIeD6O3FLlcZa5bzFhqayx1FjIHzBpl1RyVQG8kgtYwj4BRpWHVAlg1B1bNqbHWh7Gv2vEQ tdhg7EetNdVYa62l1o6NCeJ++uEh8DDxezb4NenfADgOKTqKt0kvBLCkeJfji9j+HbwHisBi8D75 xWAJ6Q8p+w+wFJSAj8EqsB52/ZIym7BHh57bwnYrPVwOtoMI+KbuFWODOdhg0LM5sHmGfSY2NVP0 dCpFmvMd2IddKWADF42E2B4L2sBTJ7Htiv1xHuyfAftnwP4ZLuPNvBPsQvNesEr4fKE7inOxZRdb dq8GN4NbQDq4FdwGsGu8RoY7mfQUcAe4E2SAu8Dd4CGO/4Zyj4Dn2f8j+BO2Tlm/FXgMPA5eFZUw QrF5v9g7pN8lvYR8dOd/I7LD58IvlwJ8bzjFeKaMhCx06CBxHmfncXbgR/ICvyWOF8vQa1THwThP Y5ynBboN9OY6yIIO3StkC651jcs4dhnHwTX7j8JpDWUybxtrIBd9igwjjAzFMS+XFvNyaUT80b4s jsUgZoTG96UZpbWckhN9L5u0kanYyFJXjgLkGBR771q8bnJEC1oaFIt2MmPRTuChB1F7GrWnUfsg as1uIKMUT8IDLcxvxPEnzRaI7GZ5IrXZy+AV8v4EXhU9Q93FoNDpIjN0hhgROhMQM4R64zkUZyZR qo9ocaD798T3yfH38Inxk4nxk808OY9Z9j7zr1Q1cyyOz+P4PHFiLLYqjjFALjpcjg6Xo8PlMa+4 PBZj+cRYPmxQDBvkwQZ5Mf9V6yFNXGX82PI6EUGUFdJhhRmN+q8QLeXRUh61FVBbQRynFHNGgXlr W3tkzUbObOTMRs6FyLkQORfWMFVL47WLm/SpUX+ajiyD6jFUrSwdDCeiDVkm0htoJPDegRZiUWb1 1cdxYWNXnRmLE+q2NLKGC6s5sJb7UuG9VHgvFd5LhfdS4b1U+C61Mb4z/LZVZB/EeIjy24Aajktt lNtqeS3V8Brl4LRUOC0VTktthNOKD4rTJnHu/vkstQkeG90ojzXOXal1xmxabMymoY1stJGNNrLR xgi0MKIBt7WPGw95NVFh1P5bx9l9EBlW0PMV2H1ren9Nvd5fQ+9nmt5PFRX0fCo9n03Pb6Lnc8UJ deKMpnsrl97KrY41jMfpW9eLNGDThuyeY5g8kRZHNGCxBJAIWhtGS4tjtLQGmjlO/BY2CxjtabAH 7AWV4DvwvS6yB+kitzm4HDwFKOfOA78DuWA+eJW55HZQoYvCo4P/BT9qtcZmOnVqP5G4P5tIPJtI PJtIHNaQ7VQiaC3bEZVnE5VnM5PszEyyMz0cjO0gOs8mOs9m1tiOGWN372FYZTa28phIZdbYzl8A XgL5eIwCLLFQ/ojeLqa3c8PD6PVf0tPjgjmQbEFvFzP3iuefG2D2ICeTnExyAm7IEUOa5IL64z3w vbUxzohYbFPHBzc6pgO/XD2ugzEdHcM50THc0FcfcCzvbxw3NoYP0ffXH9cmFgjuB/Qzn2nihiYj yVoWTYtFkGkwaRpMmgaTpsGkaXERZEMNR7WbWSeCDN5FGmXZxsZtjSeqz7IwbNoBosjsOLZNi4si 02DcNBg3DcZNq8u4tVHMQUaR++8tdHhIUWTd3hrdCAOniVA8t8TuY2TERUhRTjmUt8tWj5fad9i2 jnnqHM7cZHj6YLxy7eykoUcO7pLkImE6EuYiYTrW9l/4TmH3ZTHoEN4rnBn3XuGCA75XWFXrWoTo iQJ0uRA95qHHvHpR2UITlTVH++Vov5zSFZSuRPOVnLGJMzZxRiVnVHJGZfh8vcd4wxvw0K2Ct+bG +m1T9ZtTqWFTrAYdV0MFNVRQQwU17DI1BG84DWo5ScyStpgrCuD5PFFIeh/bKqBFHvyeB7/jxeX5 ePAC+D0dfs+A3/Pgd7y4PN+jh7xZMgWeT4HnM+H5dLSZCc+f788HC8BLIJ/8AnxAoTwfrv86nCpT sJ4CrGcTPN8b66kI7mWZ1nrjTXrTWkbQGq30jrUylFaGxlrJoJUMWulNK71ppTet9KYV+JDaUuVQ as+j9jXU3p3aN4m+5q5SwGmN8dkS4w16VvNVbC5fE7fGzWyzA06qiZiDmKIlUVcbE+XV5Zy4OBfO UVjfcsMlcXxBxJ9r+KFupL08juEHBdZSn+FNbByNvvsFfBE3CrNFR3q0Al1W0JsV9GYFvVmhhEzB ez+I934Q7/0gvVtB71ag7wfR94NuIuN/IPsvYoUPyAfR92z0PRsdT0XHU9HxVHQ8Ff1ODQ+WndHx bFrfGh4n26HjieGbZFfsKWpLBbRcQMsFtFxAq0NpdSitDqXVAlotoNWhtDoU3S1ET5m0XEDLBd40 2YKWr6Hla+jpbHSTHbOlC+JsKSNmS0PRwx5ihhykuQZp3kIPjA/yb8KWT0GaHKQJ7lrmIk0u0jAb kZ2RpjPSdEaaXKTJRZruSNMdm0tFmjSkyUWaXG8a4+kBIpiZsPksrP0h8DA2OZtIJmp/nZGsM5J1 R7LuSJYai2i6I9lyE82kyr4NIppOSJYbP9boHRvJeiNZbyTrXWfsydj46yPuqh57TVp/QWAvjIBg jEX10nAkdNvfXfiY507CY3eMeev693ua9Nbmjl5w996lRxu7k9/XzGGid/IfMx6xIm4+sgkLLzAW HsxLgrv7nWu4qW4PdkdP3dFT97gerGaNgKPSa3ow2nsZMebIiOOn7uiue33dobc16C2vvt6Eo57V JWqh+R1TSWgL+CrgerFd2CJRCHEM7NWc2c+l4ljxczFeDBVTxL1irLiPeHOC+EQmwK6JspXYJVvL 1mKPbCPbi73yeDlAfC8vkZfJzvJKeYvsKu+U98nz5Ax5vxwify9flhfLdaxXyY1ysxwly+V2ebWM yG/ktXKX1PI6pZQnJ6iwCsvbVXPVXE5ULVVLOUm1Uq3kZHWsOlZOUcep4+Qdqq1qK+9UJ6gTZYY6 SZ0kp6su6hR5r0pS3eR9qrvqKe9XP1G95MMqWZ0rf636q/PkHHW+ukA+qi5UF8rH1UVqiMxRF6sR 8kl1uUqRv1cj1Sj5rBqjbpLz1QQ1QRaoW1S6/Iu6Td0m/6YmqonydTVZ3SXfUFPVNPmOuk/NkIvU I2q2LFJz1ePyffWkelJ+qH6nfic/Ur9XL8h/qAXqJblCvaz+IFepP6m/yNXqdfW6/EIVqoVyrVqk /i6/VEVqsdysPlBL5FdqqVoqy9RKtVJuU/9U/5TlarUqldvVGrVG7lAb1SYZUVvUV/JbVabK5G5V rsrlHhVREblX7VPfy0qlLSX3Wa5FUGn5lq+k1dxqpZTVxmqjPKud1UE1s06wOquw1cXqoo6xulqn qWOtHlYP1c46x+qr2ltXWdep462brSmqi7XAWqDOsEqslepMa5vdUvWxj7HHqFT7WnuCesFOt+9W r9kz7ZnqHedC50L1rjPIGaEWOZc7o9Q/nDHO1WqlM9a5Tv3Tud65Ra12Jjl3q3XOVGe6+sqZ4WSr MucRJ1ftcp51nrOaOS84SyzfKXHWWmc4m5zd1kCn0qm0Upx9rrR+7tqubY12PTdkjXHDbqJ1rXuM m2xd757r9rOy3fPcgdZv3Ivcwdaj7lD3Yutxd4R7hfWEm+reYD3t3uS+ZL3kvuK+Zn3t/sX9q7XD fcN9y/rGfdd9z9rtvu++b33nLnGXWPvcZe7H1vfuCnelpd3Vbqkt3c/dz23LXeuutW13k7vNdtzt 7g67ubvL3Wsnuvtcbbf2lKfsdp7jtbLbe8d6x9qneMd5beyuXjuvg32q18k7w+7u9fH62/29n3mD 7Z96F3tX2oO9q71x9s+9G71b7Gu9W71b7eu9271J9jjvDu8e+yZvmjfdvtW733vQvt2b5T1kT/Ye 8ebYd3hvee/Yd3mLvL/b07xir9i+11vhrbB/5a3yVtn3eWu8NXamt9Zba8/w1nvr7fu9jd5m+wFv e7PW9qxmSc3OtP/UrH+zS+zXm13XLNNe0uzZZnvsrSEVCjkDQ31ClzhDQxNCk5zrQn8O/dkZH/pr 6G/OhNAboTecW0Jvht500kNvh/7u3BpaHHrfmRJaEvqHc2fo49Anzj2hFaHPnWmhDaEKZ1ZoT2iP 80RIh7TzW1/6jvOkH/JDzv/5zf1E5/f+MX5r5zm/jd/eme939Ds5eX5nv7Pzin+af7rzB/9M/0wn 3+/pn+286vfx+zh/9gf4A5wC/wL/Aucv/oX+hc5f/Z/5g52/+UP9oc6b/iX+cOct/zL/MmehP8of 5bzjj/V/6bzrj/PHOUX+BP92Z7E/yZ/k/MOf4t/pLPV/5f/K+dif4d/vfOI/6D/orPCz/Wxnpf+I P8dZ5T/m/9ZZ7T/tP+N85j/vv+Rs9F/2X3G+9v/o/9Ep8/P9fGeb/5r/mlPuv+m/6Wz33/YXORV+ kf++862/xP/Q2eMv9Zc5lf5Kf5Xzvf+5/4Wj/Q3+BleG+4YHuSo8ODzEbRm+NHyl2yo8KpzqdgiP Cf/CPSHMLMk9KXxD+Ea3S8KGhA1u14SvEra6SQl7E/a6pzVv1jzsdheqTz7sLPqmDLKZ+44S/+OL fqfxlN7BeqteQCrA/VGYo8lH1N6vwW8ayS8Ey+L257JO1vl6YGz/i4Oq/bOa1PoojnzRZeBrsO2Q zzzE9vVHh9pCzdKaNVj82JWjB70FfHN41QXX3FSqNueHXw6sQb0rtq3t+WiqdZCKnq83H0KTwXll rOvj2w5y4uVpWgfBeXXPrXN0h7GmXdF0bW79VO35pnzZ0dB5tKbGJD6Qnmt6fl1NTjQV6Gqd0VaZ XqE/r9b9AfXdurrlxnQc29vO0V16M7k7RIOFY03qRM/QI4NPk95ak1snFbBbU1f5Qyy1vW72xtY7 er3uoPvpW016ebX9RFPMu4PULl1i8tfV6YVAC/lNNJkUs+N39ApTdnVUjpgdl4Cs+hLG7RWZEvnR knz2qF/y4LQV9SmGPT+M4sgXXQQ+jvLbIZy1y2hrV1xW60bLra5NoTv2dMVhiRmtAyvTf6Dl98FH 8SO9yTPKDstvycMS7ygv+l96VfD5H5XhkEYxLPO+fk9v/6GkaaLVVUepno8bSdXUHYy6BkujNn/E cswTwZOFtUsS7fRk27NBycJ6qSSYuFD/1eTM188wSt6JxYJFJq/R3iR3kBmfq/VSvbQmdzU1rYjn Q8Z8fpTFGtSQT2xZqOceeKzF80H9lB6o/8xngGFRmNxh+6/xAO1dBC5tJL+krqw6UZ9s0OEg6txW 45mH6Q/RcsDFYzl3bOz4yAZn7EB3u6KfdfKj0c28oMfNfkS7Ok130+MbmxUENhHtx2Cp2heFPtkc 22Ku6JA4/N+71Lc9vQEL+7ve8G+WorTe/n4i+vq2rL8JRtaB5wB6SU3qvQB1+/zwlqBO08Mr91uq rDr6jMUnm4k8Xj/Ell6InnkYQnYMoqtY+2+Bd6MRi/77florqUlFJR4b2HN0JMVF7XVS9SypfQxH vgS1+PuRsWVUwnpHL9OdGPujTbqGtWOpINqcR6z5WZ1TOtLSSabUvKjGGixJschlerSe2Ofm2Pyr pIYVg5p844XqeCKdVSNJIMHA6lTs6DPBNehnGm250aWpuc7hL7X93uhRt97+3XDzNfpuk66eebSu MwdJbFBH9dxydf0j9cvFjXPTw6IPa3DkkXolV9TZK4m/ioCJm2xhZ+Mp+GSnXlQ9B9HFURz5Ysbc u43kNzWLbqChBrN/k4r5vBWk3jZ3RNbrnJhFljVWt7GaLWbW9FlcPWavdr6JT3wVy35eb2wYWcBe dWamZv4Q4G+NX0kT11dRk9pymMzWsM4d4iBmHw3Omh6MRT3dpGvnr3VS9WOEo73Uv+9WNxKqvj9Y s7/CRB0rxCEuOnJ40jVa11f7PVrfSy/Tr+gX4+99/juW2hlDbH/tfsrWk01P0T8NPk26xr/XTekv 9ZcN6tFm07gHOcLF9Hp+zV6yaSVAUnSfODU5ZsdZRP9FZmYwl1S+8V3jdTH5JWY/eoehyPBFUOvo RloroRdHsL0fb3l5MI8gPZLy+fo3zCvyo2OG2ODrWE2Fou4MKZBiJK0OY5tleCf+DkudkvsZedH7 lLGRHcxij85MtimuOPj7Eo3fP9YbzXZ1tXc+yvfoj0pNP9zyQ/Pk4S+x+9G79Lf1DviNRZf/vqV+ 5GryAnvqF4x1xmCPWJw53oxVxq6xg/kNz6pTw1wTTU4W1fcYJscdK2zipCNe6o4n4qidTR07knoP a8k7iBLxZZIC/R/EWQ1bqcYRLQe64ob39nWE9QiiqKOg4/3XHx8xbie2PEhZa++t/M8uaTEc8UIf 7deyjFXUseOYVRy2Hf/QVtFwYcbRIKb6t7Z/yP4LWy4/InZbd+Ay+z2/rKk73jGft756PlhzIOkg 640upvZoXHnQS79DKv3fsDS4j/8/v+Q0mjsiLr3cfA464laqcURL07FtdN7ayLfhHQ9mnlW33uq7 +v+55WjOwo/GEs9dgb+odzjQ8QG/Uau5WxXtj3h+aXuE0jVtFWYeWD3j0Lv1niNoJT8uXX+GcKh1 NekLqn8T01jsczTnTbX1V6dMxPUXk7pV/0U/HqT1ZJ0SnRcwshp8nxf7xcvm2Gdtjf/SRawv65dr yl2hf63T9Rx9V4M6gnsNy8x9gejvKYJvEC+ovZ9FvbsP4mpW197pbvT73jiZqyWvk7sjkD+opfoX KvoLfOLXIFLv1xJi//N1PVB30Cfr6036iZrfsJiUucPyBNFLSfW3IXXvDzT5jWmSiH7LO6X2WwWk Wh375iXQ3XX1pIiT2MwPC/XImvJx35QaObLM74Syqvdrj8RJ1nDMVy8/zF2s2J2nWFyRbPglYIzo XayRuh3XFJU4sLSSaHmustDMiefTe4Vcb0n1vf6ovk2psY20Fugl+CZ9HraYGdPxXKPh4A7ZiqhH 0DcYu6j+nq7OnCOYS1N2LqUXmKP17mJR88hqv1Ibu8altv8HdFx9/ziq47H17hTegYaviklcZKzP XLXRaZKI3uH/wNj35iiHVEeS4N5GWgtaCnScH/zeIKbjp9Dxv3QBdQXfSjzTQMd1vt9Agt9Rcl7w +wbz+864b9qjvBW3/2EjqX/zN9amzfz6V9Fkyfq/CAm+/yuM8fF8vUT/03w7dOA7hcSo5nuaoloL Nb8IKYz7drsCjxiMhXcbkWO+Hs+5k8UBvun7719ibLfa3CEr0p/u/3vQ2pjPcGUhlvlx/NH6368c oO0y4wlWc9764D54tH22i/Xi/Z5XFC/Nwd+Fi/nouuNl5iFJXBj1AcYuVsfShYdayyG0Fz9XbCtO M3nRPjj1AKcm1caOhpffFuZXC4csQeyXoAddPho5HEEMVv+X44aBA0s5iO+89BasJxj9m/d/76Pa ZvTZ2NwwUBZvFdji6Yck8abAlxk7LiEiLOF82g/itf3fkag3n/r0oNuLfjNV17fOOSSJA9udG2Pe 92PpTw+1lsNeJgW/U9InHu1qa/0I7DyeWGN8bMT3qFpZtYUo/XTd5bDqHVBV4xUPftYb/eVanZwm 269fVo83v30bGHxX8Z9cmm6/we+EOlRtqVrJWDpeH9avlXSvqhjn65n6moM+q12DnCbbb0THW/63 dBx3JPGHkOTg22q8ff3UUW23yV+Gx2Lo+O9Bduht0V9+HMTvF4uaig6Df6UWtwlbBDPM4eJSMURc Ju4TF4sZokRMFZ+ILaJYfM26VpSxrhPlUon10pEJYrdsKVsJLY+VA6SSF8vh8gw5Ql4mz5ZXyJtl L5kuZ8hLzdPU18t18ks5UZZLLe80z07PMs9OP2KenZ5tnp2eY56dnmuenX7UPDv9WPCUr3zc2maP kU/Y19p3KM/OsO9WneyZdpbqbJ7jPdkZ5AxSXZzBznB1ijPCGaFOdy53rlI9zDO9vZzrnOtUH+d6 526VbJ7mHe5kOv+nLnNynedUujPf2a0mBs/uqiJnn7NPLXaqXKHeD57gVUuCJ3jVh27YDaulbgu3 hSpxj3G7qGVuV7e32uAmu8nqm+CZXrUzeKZX7Qqe6VXfuZe5l6vvg6d5lXZvcm+ymrsT3DyrhfuK +4o13P2j+5p1qXmyN8V9w33DGum+6b5lXem+6y6yRrnvue9Zo81TvmPcYneJdbX7kfuRda151nes u9Jdaf3CXe1+bv3SXetus8YHz/daGe637l7rHnefp6xfBU/2WjO9Y7021mNee6+D9dvgmV7rqeCZ Xutl7wJvnPWad6N3q7U6eILXWuvd4d1pbfDu8e6xvvSmedOsTcFzvNZmb443x/o6ePrU2ho8fWpt C54+tcqDp0+t7X6O/4QV8Z/2/8/a6ef6z1h7/Of9561K/23/bes7f5G/yNrnF/lF1vfBs6ZWlb/U X2qL4FlTWwbPmtpW8Kyp7YT7hs+13XD/8M/sZuEh4SF2q/Cl4cvsY8JXhK+0jwuPCo+yg+dOr7aP F0pGsFFbnCMcVku4rI7wWNuIZqyeCJk1+D4+zJrA2py1hVkTRUvWY9gmkt+KtTV7x3DusawdzLOB bcRxrCewbSP6Ene2FeeKdqw/Fu1Z+1Oqgxggjme9gFIniM7iR6wnMxvrilRJxKae6CZ6INUZ4kzq OItcj5r6I815YjDtDhFDkeVi1kRG2zDaD8bbMYy3FNr/ubiGs65l9cRY8Qta+KW4gfNvFOORZIKY jCRTRAYy3MW47CymiXtp/VesrRmv93HuDNYu4n7WM8QDrKeIB1m7iJmsSSKL9VQxi7WbeIi1h3iY tYvIZu0mfs16mvgNaxfxiJjN0TliLvU8ytpNPMb6E/E4ay+Rw9pbPMHaRfxWPCn6iKdYLxVPs/YR 81iTxe/EfI6+KBbQ7kviD0jyR9au4k+sXUS+eJ38N8Rb1Py2WEhb74gPyC8WS8j5UHyEJP9g7SKW snaFh0pIfyJWUfKf4gukWsuaBBdtQKqNMFQvw1CnG4bqLcrFbsrvEVr0kQK2Soat6BXpSldI6UkP a2ommwlbhmRIHCd96QtXhmVYNJMJ8JoPr7UUzWWixG5kKziuFRyHpZj/kDhOsor2so3EYmRb2VYc L9vJduJHsr1sLzrKDrKD6CSPl8eLfvIEeYI4T/5I/kicLzvKjuJE2Ul2EifJH8tTkaSbDN5U1V2e iSRnyZ7UdrY8l5x+cgAyXCyHIcMl8hJkGC6HIwPcyucVciSSXCnHUv46eR3lfyHTkOF6eRMyjJc3 I0O6vAMZ7pR30/o9cjrt3ivvo91Mmcm5M+QMzv29zEUnz8hnxKnyWfmc6CGfly+ILnK+fFF0kwvk S+I0mSdfDt44IdeJIXK93CAGyo3yS9LlslwMldvldjFMVsgKcbHcIXeIS2SEUTpUfiO/IX+n3En+ t/Jb8nfJ3Zy1R+4RP5N75V5xkayUlWKQ/E5+JwbLfXIf+d/L78mvklXka6nFYPyEEhcqS1nip8pW NmlHOaRd5ZL2lEcaLyLOCryI6Bl4EdJ4EdJ4EdJ4EdEz8CJiuLXN2iPOsfbaQni2tJVIsC07JNrY vt1StLMT7Vbix/YxdlvS7ewOorN9vH2K6GJ3tXuIJPsM+0zSZ9l9xBl2st1fnGmfZw8g53z7Z6QH 2YNFH3uInSKk/XN7jHDxVdeL4+xx9gTR1r7ZvkV0stPtSaQn23eIE/FhGeJc+y77LtHbvtu+W3QM /peC2rLsLNE98GrCCryaaINXG8LnUOdikeAMc4aRvsS5RHjOcGe4CAXeTvTH213O0SucK0Sik+L8 nPRIZyQlr3SuJH2Vc5XoEPhCcW7gC8XJ+MLr+RznjBPJzg3ODaKFc6Nzo+jm3OTcRHq8M570BGeC OMe52bmZGm5xbqG2dGei+LEzyZlM/hRnCjLc4dwpwk6Gk0G7dzl3U2aqM5WapznTqHm6M52jmU6m aO3McO7nrAecBzlrppNFnbOchyj//6n7Evioimz9c6v71u1bnTRJSAKEJIQ9hGyyhBDCFgIiympg EBEQGWAAURERERV8yPgQCTLYfXsNMojKKCLPQQZRETfEZRAQkUFEVFRAREVEZZL31UlU3HEZ3//f 9evipOpU1V2q6nxfc6rqFnMhpZu3motQc6VZibtebC5G7m3mbbiSJeYSpPzF/AvqXGouRQ23m7ej Br8ZRNmQGaJmZtgMIz1iRsg0o2aUksyYGcOdLjOXoewd5h2oebm5HDp/Nf+KsivNlWjxLvMulL3b vBvp95h/g+a95r2o4T7zAdS81lwHzYfMh/CE15vrcRf/MB/DVW0yN+NOnzCfRivPmM8iZav5Au7u RfMllNpu7sBz3mm+gvp3m3upxHzN3I8recN8G9dw0HwHb+pd8z3qbh4yD1NP84h5BNfwvvkB7u6Y +SHq/Mj8CDV8bH6MGo6bx1H/J+YnaPGEeQI6n5qfohUgFSrQSAVxtVlNLc0as4YKtDGkNhq1UFug Fg/lSFvaSAd2oSKNXagY2CUJcX2ZjNwUmUL5MlWmUkvZQDaAZkOZDjlDZkDOlE2QmyWzKFs2lc2g 31w2R80tZEvktpatkZIts1FbG9kGco7MhX6exEiRBRIjRZ4l20GzvexAHWRHWYQUoCXodJFdUKpU lkLuJntCp0yWUSeNnCAPloOhP0QOQcoIOQI6F8qLkD5KjqJWcrS8BPWMkxPQCnAV7neynIzWp8jL oXmFvBK50+UMXOfVchbka+VcpN8o/4wabpa3oOaFcjF1lLfJpXgmt8sgdEIyirZisooGymVyGeQ7 5F9xhSvkCpS9U94JzZXyLqTfLe9Gyj3yHsqTq+QqytV4Dimr5WrE98v70e4auQZlH5APQH+tXIt2 /y7/jnidXEdCoz1K0WgP8Sa5idzycfk4eTTmo1KN+ageMN8Wqq/3d4EOkB810siPMjXyo+Z6lxfE e+RrFK/3eiFD7/UCzTfk29REHpTvIOVd+S5J+Z48REoelodR5xH5PnQ+kMdQ9kP5IdI/kZ+glRPy U+iflJ9B/5T8N3SqZQ01BqQyqIneJ4YE0KSJGF2Kmlv4kGF5LA9Jy7biKMWKt+KpqeWzfEivZ9Uj t5VgJVCihUCZencZlE22klFbipUCnVQrFWUbWY3QSpqVhrJNrCZIz7KaQbO51Rw1tLCyUXMbKw+a +VY+eawCq4AU8GtnqmeVWF1Rf0+rnOrr/WmgeY7VjxpZ51oDUOdA63zKsCqsP6D14dZItHuRNYpK rdHWGOpmXWyNpR7WJdYlaHecNR53NNGaCM0/WX9C7iRrEtInW5NxPVOsS9HKVGsqar7Mugw1X2Fd gdanWdNQ6krrSrQL3EwFGjcjBm6m9sDN86ildZN1E+Vb8635SAeGppbA0EBlap4CKtNIGjGQNFIq VSXlqMUKWEvdpm6DDFSNOKwi0ImqGHSAramDxtbUUWNraq+xNRVrbI2UZ9WziLeqrUgBwkZZIGyU BcJGDIRNBUDYJZTt7eLtArmrtyu18Xbzdqd8r94NsMDb01tGHby9vL2oo7fcW05F3t7e3lSssTh0 BnoHQmeQdxC19A72DkbZ873nU1tvhbcCKUO9w6DzB+8foAOkjhpGekfSQO9F3ouAAIW4hPF6KSP1 JMblSYzIExh5JzHmTmK03ZXRdjdG2w0YbfdgtF3GaLuc0XZjRtuZjLZLGW27GG0nAWsXAmFrnJ0E fN0P9Q8Fhk5i9NyV0XM3Rs8NGD2XMXpuzOg5k3Gzl3FzAePmXKBmzBenYeUCxsq5QMq1KHkRZI2P 84CPb0PuEoQ8RskFjJLzGCW3Z5TckVFyEaPkYkbJwxklFzNKLgFKjuLaYwgFVEV3Ql6JUMC4uQlw 8z2QV9HfkH4vcHMBcPMayA8gFNBaWgf5ISDpAiDpDZAfBp4uYDydCzz9GDD0JoQcepyegvw0Qg5Q 9jO4wi0IOcDazyJ9K0IuEPdzSH8eODuXtiHkAm2/hJTttAPPeCdCHpD3LrTyCkIB7aa9kF8DCi8A Cn8DuW8i5AGLv4V7f5sOApe/A1zent4DLm9Dh4HLOwKXHwVD+AChiI7RJ5BPAKkXAal/gWdyCqEz /RuhmKqB3Tsbesl+iSGA4EsMl+GiPMbxuafheB/j+ETgeC9kjd0TjXgDjA/YvT5ijdcTGa/7GK8n Ml73MV6vz3g9hfF6KuP17ozXezJe78V4PY3xegbwehYwelOjKdptZmRDbvMVghdA8LmoOc/Ix9RZ ADSfCDR/FrhEO2B6BUzfnmyjg9EB7XY0OkMuAcr3AeV3pTijG7B+otHD6AGs39PoifQyowyIv5fR C3K5cQ7kfsa5kPsbgxAPBgfwGEOM8yFXGENRahj4gA98AGjPGG4MR20XGBdBHgVukAhuMBa5lxiX QHMceIIPPOGPuPfxxgRKNiaCM9Q3JoMzpBiXGpdSQzCHqXgalxnTIV8FFpHKLKInWMS1lG7MNmbj mVwHRpEORnEDnsxc8IoM5hU+5hXKmGfMg3yTARymf/sBu9D8YQjzh37MH4Ywfzif+cNQ5g8VzB+G MX84n/nDUOYPFcwfhjF/GML8oT/zh4HMHwYwfxjE/KE/84eBzB8GMH8YxPzhXOYP5zF/OJf5w3nM H85l/nCeiBNx4Ak+4QNnSBAJkJNEEuRkkQw5VaRCbiAaUJZIF+kkRRPRBHEr0QpxgSigRqKL6IJ4 uBhOg8UlmPUGi3FiHJligpiAeKqYini2mI24UlRSHxESQK565z1qLpaJZYjvEHdQS7FCrADnuUfc A/kB8QDitWItch8WD0P/EfEIUh4XjyPlCfEEtRZPiacQbxFbEL8kXkK8U+xEvEvsomzxingF8m6x m84RB8VByO+K96iV3n8PuZ+IT5ByQpyAfEqAfbksl0VNXT6Xj1q4El2JdLbehQ9ypisTcbYrG7k5 rhzImk39wdXd1Z2yXHNcc6iLa55rPuKbXYsQP+J6BLHmWqXgVJjXmU01BptqDO6UDk5VCE7VGnI2 mFUhmFUBtXUXgl/lgF+dhfR2YFmFYFmdIZe4SyF3BeMqAOPqBr7UHbyrE3hXT8hl7nLIfdx9qNh9 NjhYZ3Cwc8DB+oGJucHEhpLPPQx8zHZf5L6I6rlHuUchZbR7NCW6x4ChxYGhTYA80T0J8mSwtUSw tSnghJeCszUEZ7sM8uXuaZCvBH9LBX+bTmnuq8Di0pnFdWMW15FZXIp7nns+6tdcLoe5XBvzbPNs IPu+Zl+wCM3fkpi5JZgDzYGQNX/rYQ4FZ0sAZ/sDUjRP62aONkdTA3OMOYYaM2fLZD5WykwsiZlY A2ZipczEXMzEkpiDJTHvSjLnmnNRp+Zdpcy1kphlNWA2lclsqpR5VBLzqMbMo0qZR9UyqG7MnRow dyo1V5grUNud5p3I1dypMXOnUmZNScyRkpgFJTHz6crMpxsznwbMfHow8ylj5lPOzKcxM59M5jaZ YDWnwHv/bf67jtUU1rEaDFTgbJfEzM/cJhdA1ILsAcMpYIaTywyno4yX8UDemueUMM8pAM+pj9xk sJ08ZjuFzHbaMtspBNtpCGTfCJynE9hOFlKayqYo1Qxsp5DZTu532E4Bs51CsJ0c1NkWbKeQ2U5b ZjuFzHbaMtvpxGwnV3aW6MPMeUrAedCHmfMUMufpLHvJXtApl+Worbfsjbs4W54DnX6yH7WX58pz Uaq/7I+UQXJQHTvKY3ZUzOyogNlRLrOjQmZHBcyOCuVEORHy1xypkDlSLjjSFbiXaXIa6rkSfKkt +NIspGumlAemdBM058v/hrxALkDuLWBNeWBNt+J6FslKMKjFYFDtmUF1BIMCtpEOeFQn5lHFzKOG M48qZh5Vwjwql3lUR/ColUi/C2yqM7OpArCpVbhCzaMK5H3yPuisBo/KZR5VwjyqWD4oH8Q1PCQf Ip/cIDdQIhjUw+Awj8nHIG+WmxFrBtWdGZRPPiOfoVQwqK1I19wpRW6X25GyQ4KfM4/KAI/aDc09 cg/ivXIv4lo29bp8HXxJc6o45lSpp3EqAU71Huo8BGYVx8wqHszqCFLeB7+KA7/6APVofhUnP5If QdYsy/cVyzpJtvwMXMsn9ele9ZhxxTHjimfGlYoJ2AXZbbnJx4wr4zTG5WPGFceMK+00xlXLtVJO 41c+q6HVEOmaX6Wdxq98zK/imF/5wK9yyLbaWrmQ88C1bOZaPuZacVahdRbkdlY7XE97qyPkTlYn yMXgXT7mXXHgXQMga8ZVnxlXCjOuVGZc3Zlx9WTG1YsZVxozrgxrgjUBpTTvSmHe1ZN5V1od77oM LMvHLCvDusq6CvIMawblWjOtWcyyrkf8NbPKszZbm8HQPrO+IOlxe9yIz/P0p0ae5z0HaLDnTdsg 055sTyZpT7enI95kb6KW9pP2k9Tcftp+GvKz9rPU195qb4W8w95Bzezd9qvUx37Tfhs6R+0PkHvc Po70E/YJpHxqfwrNz+zPqJnyKJtaq3gVT+eoRJVIuaqJaoKU1qoN4rYqj7L17qDI7aA6IqVElSAe oAZQC70LKJ2tLlQXUlM1Rl1MvdUMdTVSZqvZSLlB3QCduWouZM0eC9RNzBsXqAXMHm9FrNljERij H3FAOZSnQswbl6llkDVjbK9Wq/upRK1X4Ahgj48iflw9gfhJ9Qx44xa1hdqo59Rz1EXtUDuYN+5D fFgdRp0fqGNglR+qD6mEOWQRc8hcb6m3FHxPM8b2zBg7MlfsyFwxl7liQR1XHOIdAvl8cMVccMXh lOe90HshuKVmicOZJZZ4R3svhs4fvX8Eq5zonUhFcYfi3qfmcR/EfYD4ZNxJ0juLnqLWcdVx1WB+ otEYvbNo4+qm06jo/36VCHuPPMpSp59dduT3pLGHzjf2+LwN4aqv9/j8uuWad2oerOn7c3dSQqkh 35P6T/Yi+bavdVndV9/lV/6nv+kuAG98Hf/Ip9YL9Y1fsFtJmx+qm3fn+JE9I09fe/rLPjUrzkDn yFc7hdT5QeH9nHbFZ1LHd+p84Qx0vuphX7X7m3oxnPmnZvnv0or8Tsq1X+4Egz6Q8Atq1O/sie+k /vPrWL+J03eQ+fa7xAg+Y9+3X//BTDGhThry3ev+0ZJX1FyLcXQFpG95X9as5vimmpu+aqPJabld a/N/i4/uJT/mCfnd9/ujtf3inY/q5qtXf0rvez/JmK/X6xUx37wWfV8/NQNi7nvjy/jnfGr94H+7 XZ6qz9BPvvpk9avs0/bWt9PZB3NUTb9vl6jpzvGr39i/7yuPuOqfteeAtlBn9qS+bcvO0B59/yeZ 9/nd8X2lf7rGn7JHP1DqV6xZ+6Wf2vVULK053Qv9NC/5lcAsP/jGfumK/JrrvvHXGXtL/tpPTaSm x2l/XVnzrRWJ/8m1EF+vS+G9An/Sv5x3IPuRnVO/izd+QG/3aTt5sv/8d3wHm3xD/51ae/hD7/a7 eONHWz9jP3q9mqjm6LfbOW33559emRFXp1mB0et8ex1QTfva663dx+m09DLeH+UEz8kh4OY8Rs7D vrTpNY3P8PqP/rTOz/pUnEmb/4Eem3tmajXtf9tma+LOQOcbPe5n7M/0q9/NN9fz/ADq+vbaaL16 7XfY8fX33GfpGzty/Y67JZ0JU/0pnV+4xql2z9Tf5EyCM/18uadT3drXH11L9h9p/yDHP7AvD+bJ 70XN/LvDyl9jz+vWvvzCFZy/pN2aY19ikR8eRd+fc9ruez+bQ/xC1vH/yOdLLlgT/CrlP3mWxE/a mdN/r9O/4NWeLPGz2znj3+u+yte/q9WtAeNf8C6r+cpm80rpI3U5P75T04/+XveTV/2LVzvX9t9f +LtFk5oNuN+VdSOj7lfIuv1nn/p6BfL3truS9697SuOwn7MLaI2oZawoWbuqPEL87GsUP7+bar6D l2o61v37vSvefh4P/U7dJ75crf8jvzvWvk2evX/tzk7fqfvV///mkC9/W/rd2ltd9/29232l7vt/ 8Dss/x5WOz8Luoz9XEg0EVlk6PMqycXeLm6RI3LIFLkir87zxaNPrSRbdBZdyCvKRTn5RH/Rn+qJ gWIgJYjzxfmUyH4xSeJCcSHVF6PFOEoWE8REStOnVlI6e8dk6PMqKVNMF9OpibhaXE1ZYpaYRU31 2ZXUTJ9dSS3Yd6a1uE0soWyxVPgpR59gSXnsR5MvlonlVCBWiDupnT7HkjrocyypSNwv7qfO7EdT Ih4Uf6cuYoPYSF3Fo+JR6sHeND3Zm6ZMbBG7qZfYI/5FFeI1cYCGsdfMSPaauUi8L47SaHFMfEIX i8/EKZogqkUNTXYZLhddqk+wpMv1CZZ0hSvOVY+muRJdSTTDleJKpZn6HEua5Up3pdN1riauJnS9 q6mrGd3gau1qQ3NdbV1taZ4+05Ju0ucl0nx9XiIt0Ccl0kJ9UiLdqs9IpEX6jESq1Gck0mLrA4+L lnriPcl0jz4jkR7w3OK5gzZ71npO0qv6jEQjS5+RaGTrMxKN7vp0RKOvPh3R6Gc/bG82ztXnIhrn 63MRjaH6XETjAnuH/bpxoT4X0Zioz0U0Zthf2KeMq+0a5TauUbZSxg36fzuNuSpRJRs3qjSVZsxX 6aq58WfVUuUblaqd6mAEVTfV04ioXqqfsUyfeWjcrQarCmOVGq4uMFarC9UoY40++dB4UI1XE4z1 arKaaWzQpx0aW+IOxR02ntX/42c8Fy/jpfFPfaKgsS2+PL7c2Ine+S73TsFeWEJkoY+6uY/WemQJ 7qMSfTQX/TIPPVVxT/Wip3ZAbkf0Vzf6a2folHzVa9txr23DvbYD99qO3Gvbc69th147GrljxFik a/+u9uzfZbB/lyEmoje7uDfX+noZ3JtN7s0e7s053Jst9gEzxHXo0y706bnQuRE9O4d7di569m3o /UvQvxPQv5dizNwubsdo8aOvN+G+nsx9vSH7jPnYZyxNLK/r9yswBu5E709H778bsfYiS8UY+Bvi ezESGvJISOCR4OORkISRsAF1PozxkMrjoYDHQ0MeD1nsV9ZMPCuepbPEVrEVo+458TzSXxAvUHPx otgGWXudtRTbxXZqJXaIHZC1B1pT8bJ4GSnaD601+6G1ZD+0Qh5dWRhdr2E87xP7IL8uXoe8X7wB nQMYdVk86pryqGuGUfc+Uo5i7DXH2DsGzQ/Fh3U+bK3Fx+Jj5B4Xx5Gu/dlaYmR+gRTtz9YW47Ma c0oNRmk9jFKDEl3CJai+Cx/K5BFbn0dsA4zYOIpzxbviKZ793xq56mEMZ7AXXJ4rCSO5MUZyCmLt EZeC8dwQcSOM6gY8quvxqI7nUZ2IUd0aNWdjbKfw2M7gsd0AY3sjKesR6xGS1qPWo5Afw2iXPNq9 PNrb8Ghvw6Pd5NFuYrS/hfhtjPkcHvOCx7wbY76cpKe3pzfZnj4Y/14e/+0w/v9BbTwbPA9TB89G z3PUkX0h2nvexLxg6HmBXJgXupFpd7d7kMfuafenHD1HkMAcsY7S7YfshyhVzxSUoM9RpWR7o72R mtiP2JsgP24/Dp3N9mbkPmU/RT72o0hjP4p8e6v9PHK32dsQv2S/BP0d9iuQtU9Frr3H/hcl2Xvt 16ihvc/eh9zX7ddR85v2QaS8Y79HBfYh+xD0D9uHUf8R+wjk9+33IWtPjHz7mH0MKZibUM8X9hfU wj5ln6KW+vxWOos3Ys5WhnJTc32KKzVV+FAr9tAoZA+NVipJ1admKlklQx/zF2Vh/spAnKmaID1L NaWW+oxX5DZXzVFbS9UKua1VDtK1R0drla/ykaL9OgpVB9UBcjfVjRrrs18pRfVQPShOnwBL9fQJ sFRflatyytTnwEI+R50DzX6qH3L7q/4Uz94gjdgbJE8NURXIHa6GI75AXQB9zJWQtX9IWzVWXUKJ +qxYpE9QE1DnZDWVGqjL1BWUoaapadC8Ul2Jmqer6ZCvUldB1l4leWqmmokUzLCUiBn2ELWOOxx3 mBrqM1shfx6HZ6hnW7Iw23ooI96O91IDPecS5lSjPvvvdmD/3bbsv9uB/Xc7sv9uJ/bfLWL/3WL2 3+3I/rud2H+3iP13i9l/twP77xaw/+5Z7L9byP677dh/t4D9d89i/91C9t9tx/67uey/m8f+u7ns v5vH/ru57L+bx7659jesgrYH1mn2wKpDK+1Fe8y52lvXI7qKrphTykQZ5ghtA/LF2eJszLPaEjRl S1DClqBLnSW4QFwA/RFiBPS1VcgXI8VI6F8kRmHG0RaiKVuILt+wEH8Uf8Rcf7qdmCQm1VkLKaaI SyHX2ozLxOWQteWQ4kpYDhdbjmbiWnEtLNbpluMGMafOfki2H83EPDEPOtqKtGSbkcIexvFsLRLY WiSwtUhia5HN1qK1WClWwv5pO5HE3sZJbBsS2Ns4nr2Nk9gqZLNVSGCrkM4+x+lsG9LZNuSwPWgE e/AiLMc2WIVGbBXSYRV2QNb2IJ3tQSO2BxlsD9LZHrSBPdgD26PtQZp4AzagkXhLvIX4bfE2NWBL kM6WoDHbgEbiA/EBWtGWoBFbggZsCTLYBjRiG5DOPs0ZbANaiH9j9vfx7O/j2T/Z5ca872Nf5ziX x2VD1jagnssLG+BjG1CPbUAi24D6bANasQ3wueq76pNyJcMS+NgSJLoawBL4XGmwBD5YggzE2ls6 ke1BPdiDFkhpBXvgY//pOFcbWAUfe1Ensm2o78p15SJFW4h67Ffdmf2qbavIKiIX2wyLrYXFvm4e a7u1nZpaOy1YWdiJN2A/3rTeRKwtRDPrXetdlDpsHUZ81DqKWPvGCfaNE+wb5/EM9wwn03Ox52LE kzw3UnPPf3kWUCbbj3zPcs9yauL5q+deyvLc57kP8mrPA5C1XWnKdqWE7UqXL+2KbbBdKaqzK5Lt iovtSjN7gD2J3OyBJ9gDT9iVdiVsj2M7iLV1SWGfvCT2yUtgW5LEtqQ1++Ql2c/BonjZlqSwf168 vcvehRRtUVqyFUlhX70Eth/ZbD+8bC1as99ePPvtJbDfXhL77cXbn9ufUyO72q5GrC1HDmyGwCzs huVIU6ayIGvfvnS2H43YfrRRPgVkoOqpBEpl+5GjUlQKUlJVKjVUDVRDyAjI1V6A6WxFcth+NGKP wHS2HxlsP1JVgSpEurYibdg7MF0Vq2LU01l1Rrr2FExXXVQXyF1VV6RrG+Nj6+JTZaoMsbYuybAr fSCfo85FfJ46DzO+tiiJbFFaqfNhUZQaqoYiV9sVH9uVZDVCjYCsvQ/j1Eh1EeRRsDSKLU0LdQks jY8tTbL6k5oEebK6FDVrS1OfLY2CpZmOdG1dWrHPYpy6Tl2HlOvV9dDU/ouJ7L8Yx/58CezPl8D+ fBnsz5fO/nzpGt1TvXh8EGt70yi+d3xv8pHh3ubeRQbFUZJeBOTPFaMCB5wkp8hZ4JwKJjsVwX7O 4uDYoBNc5WwIZoUSQulOJJQdeNeRTkNoPY3UNGgVQ2NdcCP+So4Mi0yMzIk4kc2RI5GT0YRofvS8 6PDIkujs6M3RZdFH8d0bPRr9PHpvLDPWIrImlhMrQpmxKBOLbI6mRztE+0THRSfhuzK6tlYzenNk RfTRWN9wXDgpNCrcMJwZbhH4HNdSES4Kl4bLnKRw38C7oR7IGaDbj02JTYtsjhVFE2LXo/3hkWG6 9diC6LKYP/poZE/089jy2N1oe3XswcCB0JDQ8bDfKQovd0aEHwxvCsvw7vA+1H0Kd58UOI47Tg9N Co2LtEPo5shIeWhZsDzSL7w44gs64e3hQ6FJToVzIjLIWRBpFSnGFczia4jDNRyLLKkSVb6qXFxB Ql37c3BPB6qcyJrorqpY1aqqNVXrqjZGF0XHVb1YtTN2qGo6NI7q51bVrapf1SxoLYwuq1qCNjag BhlcE/08sBfvoAJlFkWXOtudFnhXq4Mjg8nBcmdEcE2oWSjbud6ZFpzq9MWbrHAG4O8i5G50DgW7 OZlBB3/f7ZQ6x/DGJjoRaMYCR4OrQtkht1PozHMeDPWITI/MipVFlkTmR1ZEVkXWRF6M3hvZiXda HXVHe0RLoqOiN/IbXR/dGn03Ok4/VTzXhrGkWCHe6P7IwVhpZGN0RjSEXrAssi6aHd2GXrAoejly N0dGRhZGjsQoqiJT8ZyGRbZEh0R3RQ+gNwyIVcRGxMZEU6PHI0eil0efRJ9JjQ5HqSWRj6LNcH19 nQG45ued3UEf99GxoUeDq4J7gieDH4WUMyVcER4RHh+egt5QGpwaHqO/4Wl4n4XhmeEcXMucyJLY pug49IEpscWxp2PzYs/Htsci4Yax8bGZsQ3hDSEV8YTnha/nHvF0uDCYFt4XPhYR4RNOw8DxYJbu EZGsSC7yIuFIaBx6zL7wPvy7G+OirzPFqUCPWoD+OT58d3h1+PnwW5HkSJozICyrPFVbqibG9sV2 x07gffuq0qqyqlpFE6oGVY2tGhaZUzUVTyAnsqZqPnrGiqrNVSOrRkbzq5Kr2uEZpFbForMjY/Ee 9uMuDsbewltZU7Wnan/sVFRVFVeVR05WzYnsrGoXOB743CGM0DJczQhnjDMeb3pxaEaog7MhdDOe mggmh9aG1odKgksQpgZnBeeHtmIMLwxuCaWGDqAfZOMuckJDcCezQzc6J9DjdwZfdDY5m0J9Quc5 caHhoVGhcRgVl+NdvBVaGgqFVobuRZ1rnaRgbrBVsF2wW+goel4FRld+6MnQttDa4P7gQTy5vaF3 g0uQdhw1fR4aEqawDB4JeoJZwWHB6cE5wRXBzcHpjt9ZHlrk7AsOCu0KVjuL9WwU7MczURZGI2Yg 3GER2h6BOyx0Njgzw6difsxhhmmQoOW81pR4dxaD92URvMrURZUUITetpLsw492HkEzrEVJ4xWYq r89sQC8jNKR9CI14B5Q0egehMR1GSKf3ETLoU4RMXi3ZxJBGE8oy2hg5VGIUGoVUyisSuxpdjC7U jVcbdue1hT2MgcZAKjMGG0OolzHaGE29eWeRPsZEYyKdbUwxplBfY4Yxg84xbjTmUT/jPuM+6s8o eoDoIXrQQMbSgxhLDwaW7ktDRD9xLlUAUVfQMIFAoxhLjwY2vpbGMJ6cCTz5HF0DDLmL5gATHqAF jABvB/Z7h/zAe8fIYZ4fAro7QWFx0uWmKNh7Y1rlynBl0SZXc1dzetLV0tWSngLKyqGngakK6Fl3 sbuYXnD3cPegF93j3ePpn+6p7qm0zX2Nexa95J7tvo52uOe459DL7nnuP9MuXn20h9cd/Qv0wkV7 eR+FfVJJL+0HOUqkA7w7wju8Uuhd2UK2oPdkJ9mJDvEKn8Oyq+xKR2S57EPvy76yPx2TA+UQOiGH yqH0uVwkF9EX8l55H52Sa+RuqtbrT4zWev2Jka3Xlhht9HoSI0evJDHa6jUkRq48Lo8beXotvpFv uS1pFOjVIEY7y2dlGu0tBKPcGmwNNnpbU6yrjD7W1dbVxiDrWmu2Mdi6wbrBON+aa91oVFjzrJuN YdYt1mLjQus563njYutF62XjEusVa7cx2dpj7TEutfZae42p1uvW28ZlQJJHjRkev8dvXOf5zPOZ cb2daWcaN9hj7bHGHPtzJYy5wEsJxgLNqI0AsFCaEQSLzjSqwKKzjGWqhWph3KGyVbaxHGinwPir Oku1N1aoIjXcuAsIZLSxFZx2rLFNjVPjjJfURDXR2K6mqCnGDs1jjZ1gsJXGy2qJWmIcU34VNj5U URU1PlVVaoVxUt2l7jKq1Sr1N6NG3afWCEM9qB4Uplqn/iGkelhtFEqvkhdx6hn1jIhXL6j3hU99 oD4SBeq4+ly016saRIm3m7eP6OLt6+0ryr39vANEb71uQfTzDvVeIM71XugdLQZ5L/aOE0O9473j xQXeid4/iRHAKr3B/wwxBFxNo5RmZBLdOv/bX6NBoDBQFhgQGINY/7u6sjqwAdLzgbcqywMVThq+ 3ZxBzjBnojPLmePMdxbeVooypdBFicUHFh8IbIK2LjETuoOckc7EwLFAmdPOWaXrXnLSWRMoQ5nV gZmouyxQpGt2XgxUVFaj9nmoeb9zBPV+5JwMFDrrnI3OZmenc9Cp5itD+WB+oCzYIXA9algdHB54 C//Wlh3gDAveHFzqzA88H1wWvDe4Nrg++CjCk/huQ7kZQbczSN8PSq0OzoDWjYGZzixc5URnWOBU 4JQjAn1xpSsCIwIVuMaKwPjANMeD+ygLRALL8RxWQzqE5zDT8TmtnH6Ow9c7zJmOGhY6SwILAoud WGAKwvMIJxAGoCb994OBB51cXPMpJxn3XoZ7qQhsd8YG7kZ7U/EMygJPO8VOubMQbewO7HOynG66 NeiOCPiRO4Xr0/XMDAwIqqA7mODsR9k9wVRnSzA92Az5hYHV+plxvNpZEZykn1ftkwqeF+wTHKKf mJMbHIcaLncWBhc584Oz8aRW4vmMCo7Ck9HPUz/VZXiqpcGtuJ+ZwWy0Mj8YCu5CKAn2YI0BeHoz g8Mrq2ENTCDfbUTu7e7tQME73TtJuHcBC7vcu927YSEEdUecARvSmrJhAfIR0nkPhAzqjJCJ/O7U hPrSOZRF/RGa0UAaRM3pIoSWvL9YKxqP0JomIWTTdIQ2NIdupBzjXuNeyhPpohPli86ihPqJUlFK 54lKEcB8HxSrMZevEf9DU8Q6sY4uF+vFerpCPCweoWniMbGZrgKJUnSNO8mdRLN4hey17rnu/6LZ Zi9zEt1gzjBn0F3mNeY1dLc527yO7jFvMOfS33j3n9XmbeZf6H7e5WetGTbvov8xN5obaZN5zPyM HpevylfpOfkv+S96Xr4mX6MX5DF5jF6UH8uP6Z/Ww9Ym2mY9YT1Lu5jvvubJ9mTTPma6rzP73G/P t+fTG8w+D9jr7G30pr3dfoWq7T32HsNt77X3Gqa9395vSPst+y3D0r9DGh77ffszw47vFd/LSMWI 7yMG8IhPxZug/16qv0aDypzbT2GyTPYX39LHP9E/yx/zr7r14K1T/Tv9+wPupXsD7kX5gfyFGwId IKcvKgn0CQxBmRMok+Yv9s+H/gpob/SvC7gDqbWa/v3+tEUzAuO47rH4FgeG+Gctutwfu/VgZQ7X fGPA7U9butc/aOEG/0cLr0e9SwOhypzK5YEZtwwP3Ox/MbCyMmfRqNtP3brxluMo/6i/X2BbYBeu b6d/VsDtxKGsZ+EG4O2yRSX+WUBFGpFNcaZVjnFmOtff6gTWO5mBUYF8fT+BJ8E4WgDZFAWUf04g 4S/Tdav+k/6PKpcvGlU5xu/ju8nCtXVDajk/iam3PKmv178HV6tw50v9EwPD9fXiDnsESgLn4Z6G +UcGRvlb+XP9m/1b/Acr4/Cs3Pz3Ev/CRSv9/fzVgWbQK0bNnlv6oNXpfhHogL+K/asWXR7IDvTx z7pl/S3rK6csyvfP8a+B7v+y9/1hcaR1nlXV1d3QwyCLGDGDyLIcsogsxhiZiBEZBjPIYJblIkEW MZKm4RCa7p6k6a7+WdVV1dXd1dU/YZHFbIbJRAYjYi5mWA4RMWJEzLBMRESMmEFERI5BZDmOue9b 2efc55779+5275nU8zb1Vr1v1ft+v5/v25/v56lUJ8cvQqsT8bn4Jnz2wogT5PElx3d8FWDj4R5K 5KPrPWJPW4++52pPW1AFn/eDTeLlwHjPaM90vDKIQT29ZxXmegCZpwpZCvxWgXhd/GFvvW8XmCwW H+hZjluCGLJefAE8uh8/36MJjIvDIi+eDub3Mj33etxiRs8WsN78eDlkR0mAHwIie/HtWP5/G8sq fQKDYhkfxVqBks+8Xf5tF6KRy46cDG3DZ19kODLB34S99SgWTeLyoiXRs9xutDpSB8cKUSuxXTqI jEYmIvdQi2gqlxcZjlUG2mIX/R0xNuaPDfqY2FzsYeB+bCee4s+N58WroLTFL8cuCm1xXrgeF+PR eF+sMnYOjjRDn3FovxTbiR1Bj8L46cct/blCc7zRdyN6F8bUFj4enRUqvGFexZeFpGBCVIjOS1d5 VVQLZRHdP37HJ8TYeJ+PiU/E5uDulejuvvZ4XmwzXhULxy4GpuP34N734w+4bL5MSAltR7fFU1xe aCV0GEvgCvmyyDB/M3Iylhat5na5vKAzlhvLhdmdEEpjxbEz3uLoo+jNKBY65Aq5PNQ+djxWzmXH smIFMJsGNAb/EYxhN+bvwfzHe1LjKTCax/e/GLvYU+ZLjYvAfM4C3wLG5R/0LQKD1Qbux7fQeZg3 2K0nFex3sacI6nm+xcgElxfPE9qiSbGLkWzPYigpnoE2sT1yml+JuGG8w5EH/CR4AnwERxrFU5Ea 8NVEtDZSF9qODEeT2MHIauRkFIvURS5HKiJROFsFramoKuiMJkXqomWRUq+Jr49qY+djDcKwfzym A790xExgvZOxBvDpUGzEPxVbgJkckz1aGq+L62O3kVXROMHW0fhV8GRvbCDmjGvi2bFBOGqJzcQz Yn4Yb4V8thJa70O5DddwQ42NrcWb/Weg7/XYQHw4PgrWomL7cTJeE2/zMWCXqzCWgdhUpDRSE6kS UjhKrI5cRxiNrPNlgM8qvjZ6ik+PNEq70RVeG56JCsGEUG10BRVAchnfFDkpVMBYLsKVoAAG7sSn Y1PxlPiysBsbCR+PVcJdH8QIodSbJWnAv4CJ0ArfFLrGFcaSI8Pe4seIQJjwrgWd0v3oRnQDYQZQ UAgYSYC4qIk0wnjGJA3gZje6Fz1EZ3lVLC1SFTrsUcWne07FV2GegAzARZKP8R/5mJ5MwEKObMEo bCJkJ2cBEfU9+T35sTmEHx8Drc7GU2LnwA8s2P1OfB0QLEKr9vhB/KAnHTwyDVdo6EkVSsGveZGT kapIDT/Lz0JcgqejBq4wkhIRwWoQ29JB9Ea0KXIA2xbrjOwKFYCKXdEeHODHAB11kUY4YvDmRu2e w1BSVIrmRDPFaxEecNIeAbxHDUEnXNMMLcUoAzEYj/ZHr0m7fD0/Hz4emY7cl66CbyaiN7kK9hxf LR1I2dF8oTRaFL3FnoDrjgWdgMib0cnQYbQocjVyJ7IcJPgNtjyaHq2PtEX0XJQdCS9EhfDC49UI 8I1WohJuN1LnWeSyAdFV/CzYuxTm1wyxid6yXYeP4CMYht/Cb2E4fge/gxH4OD6OKfDv4N/BSPx7 +PcwJf4D/AeYCv8R/iNMjb+Gv4Yl4K/jr2OJ+E/xn2Ia/CH+EHuCYAkWSyJ4gseeVJxQnMCSFUuK JewdimXFMpaiWFGsYH+meKh4iKUqVhWr2DsVjxSPsDTFmmINe5diXbGOHVNsKDawd5Mvki9i6eRL 5EvYe8iXyZex4+RXya9iT5GvkK9gGeTXyK9h7yW/QX4DyyS/SX4Tex/5KvkqlkX+nPw59ufkL8hf YNnkL8lfYn9B/or8FZZDvkG+gf0H8tfkr7FccpPcxN5PbpFbWB65TW5jf0n+gfwDlk/+kfwj9gHy n8l/xgrIt8i3sA8q4R9WqExVpmJ/pUxTpmFFymPKY9iHlOnKdOyE8rjyOPZhZYYyAzupzFRmYh9R ZimzsFPKbGU29lFljjIHK1bmKnOxp5V5yjzstDJfmY99TFmgLMBKlIXKQuzjyg8pP4SdUX5Y+WHs E8qPKD+ClSo/qvwo9knl08qnsTLlx5Qfw55Rflz5caxcWaosxZ5Vh9VhrEIdVUexT6nj6jh2Vt2r 7sWeU/epv4xVqv9e/fdYlfor6q9gz6v/Qf0PWLX6RfWL2GfUL6lfws6pX1YPY3+tvql+Ffts0mtJ r2FfTPqnpH/CmpNeT3odu5T0k6SfYNqknyb9FGtJ+lnSzzDd24rg/0YRvIt1EzPEDzGrrAs6ZF3Q K+uCUVkXjMm6YA/xJrGH/d3biuDbiuC/JUVQ1aG6/Cd9oNuEiuIDkO/e5QqsA/4N/yGXFkiGvVn/ bCA3cMKWGagMNMC+jgt7Dmw5AVPAYi23O/2T3pJAWuA4nMnyz0KrM1wYjlQGawN+XgwMsmVBJjDF FATmAgvBST6FzZQSpFy6XjojNfB9kkViJb+XCTYFBmGbosdg2wssBB5C60U2M7jHnQkcwfF6Sk/X o407w83xy2jPkcfXUH38cmidrg9thXa9SWGMosIqW3XIHbpKTYcm7INw5j707WPbQ7vUNL8cYKVN mCPMierzz9qdgWSxCs3RvibWBE6IjWKzqIdzIhcWL4tUwCK6Rd4/JpaKFVDa2HZRDGkCR2JfKIU7 EzoWymAzxav2AWlcLLQxbD6bGSoMnbSdok5Di9Pi9VCpOByqQKOn6239dL09jZsTksOpdH1gCo3e Vk31hTPpejY/tBvOsWWGVeH8cNHj8aFNnPbviffh7zKMLvnx2LgC8UEwla61b8L+OWulo5k6Hczx zwbzwfp2/ywb5woCOuuAuC6KQSyYJDbbzwdrbaekcWmcLeN0trFQszTONweSbalsJr8uJfAi55fC wVMSGyyxSdwSt8RXhURPW2AtFPXmS+NUc6iPKeCbQ5dh1Dyb6Y3bwZ9BRmrglh7PDW1CR7jEZqfr w2cdedwc1Uc/gnmlw7zMYTvMS7Dl2/KtD8MSeGSaTRLOQUstnN8Kp4Zr2bFwe+Ac1ee12zI9B4CQ BthPClbzJH0rcDvYTtfzGZ51/92A0z/PFXhLbKf8i3y2LdO/DRhN8M8jDwYKAHvlgXP+WWsW8p/d EuhA+OTbrOXWAv+K/5GM5OJAMZeGavYB+0DgvH/Ps+wfA4tlcWEr65/1HPjHAhet5YFkahS2B+jK jpoAYR0I+GHrBUSPBB8FBqQswPOSWCgRgSOpXNRIYcCw3b8XGALs7tuaAPNDUi+bzpaIGVIB9Fpj y6QTUpjND/aLpx3Z1sFAGK4HiJfOsHaREtICc954wGm3sII0ZJ0DK1WJGs86NW2d86aGhplx7oxn K3QnNB2YgXMPqL7QMptD11uLqTpe79B7kxDqpSOvnSsOXfeD7f2zfA3M9czjmn0gtBoatQmBKepy 6F5oNzTq3wgdBKasg7bqcBI3HrwhbkEM3fP2o+vT9aJGSGAFGKMTxaWtia0NjAfGg1JgJnjDOhNY C86ymfQe3wizMnGmoMFu4gqQb/zz4mWw4q4jW6wTo4DcPocIM7kaqgmWhU4yM0wBKhAZdaE8cTSU Ld4RJ6g+Si9qUAnDjBxVtpxwevgUzGAMMM+HMgJT3ByKClT7n3ExG7goPoC9XSiwGsG2EsyEiBhE HhO3/JNsPd8mNgfT+cZgkXhPXEWRE1T5t6Vx+xkpIdTI6VBEBEu4YhvDnAtKQQlWDT4wwmu8s8Em 8KABooMMlgXP2upDbSG9zRCi2FpYS6ZRkUaQlUL3qWb4+4hLs1Xbqr0bfGM4Hm4Kp4auhnO8kxDb TLg/fC1cFq4O14tXwwbujLU4WE/fsk/Z4A62MduYfzswTtVJAyIZmAoMWKcCm8F5aYnbkQbFY44q h0Yqtm7a+mGklZJTPMnWBs3UdTFbzAu2CxZp3CZQdbb84BisP6RIojN8DV8jnZfOAQrnWMlDBq9J I9LtoFaaoiDqpSnoMxa8Jc1JM9IC/8A7b70d3OByg9vBQ7afzYTIG5ceSmsQeXXSRUkX2JE2pR1p XzqyslQboH4E1ovxEMk3Sx2BgcBg8G5wRUrz3/Vv8Ff5vqAQjIsp0kzwppQs9nmxwJwE3wpCGl0v 64iT5Hfgm2YBmCL6v9DJwPcS5V/Be4+sIx6XFcSnsOdgy5AVxPfKCmKmrCBmyQrin8vaYTbmAu75 F8A8ffJ7jmPYB7EeYKCngH++jJVgN7GvYx/HJmD7BPDPGaxUZqBl8i90PIP9GLuPlctstEJmo5+S 2ehZnMSTgSGmAOusxfOBdTbLfPOSzDS1+KeBabbITFMnM81WmWn+J5lptssc80s4DeyyAx8GdqmX tUyDrGWKRAmwSwnY5aeBCT5PnMO+QtQAl3xR5pJDRJAIY1NElOjB7spK5z1Z6XwoK52PZI3zDWIS mOa6zDR/D0xzFXsTcUw8EXFMXENsEBt4EjDN/4o/SewSb+EpQKBJPAOY5p/hWYp3Kp7CCxDfxD+C +Cb+NGKa+GnFBxV/hX8c6aZ4KdJN8U8i1omXIdaJP4NYJ16OWCf+LPBNJ14BTJPBP02yJItXKZ9R Po8/r/yMshavU55XNuCNykZlG34J6ay4ASmsuBEprPgLSGHFzej3EfBu5ZeV13CL8rryZdyNFFac UW4rd3CPclf5B5xX/lH5Fi4Ae1XhEVWCSoP3qpJUyfiXVSmqNHwAsVf8RcRe8UH0hkv8JcRe8euq 06rT+Mvo/ZT4DfROSvyrqirV8/gw+mUj/KaqVnUBH1F9TvU5/Lbq86rP499Stava8TuIz+Kvql5R DeNj6D2O+LjqG6pJfEI1pfo+Pqf6gerH+ILqNdXP8Z/J3HYdvZEe/w2w2l38tzKf3UJvm8d/D0z2 Xfi2+j3AZ/dlJnsETLYDf0utV3cRhNqovkKQ6m41QySidwES71Lzap44pvarJeLdSDkmMtTfVX+f yFb/QP1j4v3q19Q/IwrVK+oV4mn1Q/UbxGlgsptEKXo+kngWqctEBVKXiU8hdZk4ixgu8RxiuEQl YrjEpxHDJaqQ6kw8j1RnohqpzsRnEr+V+CpxDj3FSPxN4kTiNFGb+P3EGeJz6MlF4m8TZxPniEb0 LDzxhcTXE18nLib+JPEnxBeRPk00I32auIT0aUKL9GmiJfH3iTuELnE3cZ9oTzxI/O9EF3o2kXgB Pc9OXNZA0kFYNAmaBMKqeUKTRFDoeUTCrknRpBIOzVOapwg34toEjbg2wSCuTXgQ1yZYzYc1pwhO U6wpIXzo/+YQEnp2kIhqntVUEjH01CDxZc1nNOeIfk2NpoYY0NRqzhNfQc8LEtcQHydeRHycGER8 nHgJ8XHiuuaKxkK8rKE0TuIVjVsjECMav0YiXgVuHiEmNDFNnJjU/J1mgJjSXNW8SMwAK/8aMasZ ASZ+H5j4d4glzXeBif9SZuK/0vxA8yPikebHmkXiN5olYOJvAhMvUaQBE39G8e4nnn2iQvFe4OPV iveh988rctE75xXvf/KZJ59V5MEaaMAsf2LcHY+LBmoZWA6sZCewYlirKrBqrBYjuCzXOUzBHecS uFyopXJFUEtiD7hMqJFcHqZgj9hN+Euwe9ZeqG2zK1wC1LaoAaitsvfZrX+16irk39DB8Gv4SxiB 38BfwVQYTi6T+/J4MtGbCr9k+NeFaGQXOqctadZjXKHRzNVxeirHtkOHOdFo7tJx9y3FXbruFXbB PY9acSlUkXUdWjVDiyh3FXpU8Rv8oTfNm+ut9HZ4Ld5e74j3tnfKO+d96N0UNEKhUOF1Co1Cm3dH cAu8IApR4Sr02YM+BdBnANqPQ+sFrx9aZzxu6d30FgilwoRz39rcOc2X8WcNpXx1dxNXZxliF7oZ Wy+1x9calqlU5p58/w5h3VspXPX2CrtwvSl+G93dhwkaX5JQ6L0otPnSfZmC6Mvx5bMLfDu7Zknj 7Z3HjGZ2iU/n43w/Vwdz0XdOc4VdOksxm8XncKX8Xauen9cXdWbzi/wKb+icpsP0HD0HvS5yddZd /pH1GD/Jz/Ib3mT+UBj1HnkrfdXeBl+Tr91nhxH0wv1vwf3T4P4bvm1B9BP+ZP9xf5Y/118g3PFm +U/4i31nfbO+SaER2c0n+a755v0JvkfQk+EaOw+EFEHPiUIbO8cuGUiwzL53h0thH3beY/cNFdbT HIl8xT0AHzVYwt2PZE/Wsce7VyxphmWuj8vmLqNxd690PdTHuTwqh6O629kdjmcXOLF7hbtnuGNw s0eGZW+CNxmNyXsc/HLCW+w9Jxzzngefsl4/eBSs6l2TPZotnBTqhGFkVdgo4bLQB5bXeXVggXLv kkCCvzXeM94h4bS3wXsk5AnXvZVgozTvHPg27CW8O+CfSu9toUqoATRMC/eE+8IDsFYzoGAB7OUE FM3ANbO8Ju+g4Y4lzbPnquCOcRlcKcKobYfP5EQ2i5twz3bpjEznNGCkiddaGsC39Y+3Lj9YwdTp NpTCWNLgSlB86cKqTwV3O/Cd8pX4UvkyYVnY8hXxApWPfG+4ijCBEHEli+93FfI3+RuPEYEwwY/x OZYF3sybLQ/5dDvF9/PtfNw9b0kzMlwdBS27ygE5UzzDS/w1uNYtzx5f4tMKdyAGRn1lvlpAhsFn 9rUjZPhu+MbAl4AMsEDUt+dbAWSkef2+m76b3hFoZ/fFvb3+ZO9Dfg/8oAO7j8JVDgFDZ/zlvnrv eZ/g6/fd9S3CHmPVsAuP47grAWZgoYq4POuxzpPcquU8r+IquJNcDXOVG+XWu05wbtvOlYLOZT6H DncueyZdpOVE94peMDLmUfesZY474DFDqbWQqeGGYQXSGA66TO55bos6dJdxuzaCXeNS+FSL31ro 0vPp3Ja+2jZgbTOmcm36IlgZ6rrbwU5+awafb1vjRqFW1Jmhr+eWXY2Gk9wy1E/xJdwd7rQtmaty NXpuMKe564BV0ljGJ3EZxlqPgZuGFQ+tRnq0EiHbA7qX2AWEA5hdluGO0WyeMJp9t2DFI5UJygQM U2qUGgxXPql8EiOU71C+A1O8rWS+rWS+rWT+/6RkJswmFsk8ZgoyQax56N9bIUnzutHe1aCfNw0a c7oqHYYvzdOV9nVjSddRdxNtMiXQFsP11oqOJd0CdZMeh32N4Zh7hcp3b5vv0WnmLfoMXW4sadkw llzZtw3QAx1L9G36ovle14inWn+tZbEt/dIQvea5ZUroyGKyDQdU3GjW3zXsegyeMbbBNGOu0e23 pVrbtHXsoHHWU2vc8zS1pbelewRTAkN6NpgMwyoVN5dS8a4T7An2DGsyHafXzDUtBraXLbg0wtTY LIZdw65RMI6Zo5dudyxx97ktw0FnXTfWNaO/YUrm7unWzPquqdaqzmWr3rRpzGGdwE+izDQH3z/w rfyAW++se0HTWcfnUBt8ddcUfIsmcVcvDXVj+nlkH1OWbsQ0aDjmMGj5L83b183rXUf2GlM5bepu AgtldSzp5w16w3XmKnMd2u8Z8vS3mCjTxwxr25gJ/ayn6dKIyc9MswvmlCsW9mFburGEXWvZYO61 zJoa2J2WRQ9jKtDPsvtMG3vE3DcNoTnxce0x4xjr7FhqucndNxzYLGhGV5z6G4brpmRTZdeULrcl 3bSpf6QrNq8brqNxMgemQfNJY76hwpPkSe86chgej7GroWPJvaHfMFzvjhum9UX6U/Dtetidb9KZ lmiTzt9lcWDg5Sy60pNuuGzc9pzSL9KmzgpPtTbb5Dfd5govDXGnuVKuSrvVWcM1t2AtszAvQ8si d5kd9JRp6+gsvdm0b9q3jxp4/Qo790KKaZDLY2o6a0wzyPOdNS1Y9yLnbq2BOW+2pXZkeW7poL3N oktDc+VvGceAz0y2Rjt3u8DyYFN5nobdriljuqHGtNlyyA4AUyM6TN6ES1NUiTdZ5zSOdTUYds16 5POuoY6l1jZ+r2tKf6NzmV6DeS0YdnX7+hutVfSgp5+vN7HgU3PHvmeS1tEdtE4/yafqJz17gKcJ o9294T7sajDfs5bqFnQjul7tAZ3bVUkXWMaRzw11KB5op/Uk3WuZQz6nh3QLLemGA8Ox7lv6Metl 7TJN0Ofo8xTWehn6WVCdukEX06wxn+4A5CfRye5H7r2WDXrkBY17Q7dgXqeP05W03xhv1dAnTE6T E0Yadhjs6/SU+9CRbizTX9Nf0+20bOh22GKY0Zqxlj1nODBnA34K2HKmxqTz9FtOyJFz03PDWEQv MTVMoynZc4tZpZfoAXpOl8WOeBimlM1l/Wwyo2fPe9pZi+em8axHYvLYNIjCi+wgkwK8a565zFCM m+H119rSIfqOtZaa6zz1LGtKMBywQyaTx9xaoSswVNgeIp+xc4ZdiCBAfMtd7ZapnJsGj9/jVrll wwGv4pP0N/j81hT+bGsFwirfZFg1mYw5pjlPNawWZdwwncBjdAOf3nr50m1gz1C/clFfxJ/SFfCp hmzewN3xSOwJ4H5aXQHXp92yWbgJbpcvobaNObwdOK3AS/QQX8sd0Fl8EV/WsQT3NbNzJp3uDHjV TC+gdcSUbMykF+gFplnr9mx7Do1nIVcqgNHrIH536B1Pf0u6/m5rlX7Fc402dTUgDLgPYT3MMvUy o4zYeoy5A4iahVgruWKBMZDsOXZH528pQYVp4zTsJvOAaWaWuRQmm1llKwG3sm3YOV0uH9dPWsbZ mUtrfL8FotRhYK6zSzYLrKf/Uuu6CFGYAJG7ZT4JpDDphRTIoUodBiOj5V9I8RTRQy2HLYc6Z5fT MG0AZAIbzYfYSdXynpxWtwfWaSrfMNF9izYx68wuHTbGjYJhy5jvUXnSHYauyo4l7YEnk6tpS/UY II4zIIortFvd+bqdrn39NdPDlsVWDafnKM+kZ9J6VVulXYWIuWvTAT+v4xrpQa6N47k8z1njHqDq Wsss5DzZnkltHUJm56i5BsW1qYG7bMxkmq9YjOla0jPP34BIvtu5y8/bR1tudCzxGy2H8FnGNxlz AAHJ5gl2oMvfkq9d57e5+/ysJ4l/BNns4aUZLnrFAt8bN/hrKNMxbXZNMSLks5NdQ+yA5ahrylTO L+pXAH0HHq1pE65UY67RGxCKTeXak55FhFqWMGuYCqbKqmez2IKWRZPFUcS0GWd15Z6bTArboT0N 65OF3qf3GQ19xJBsuFNvLNONe26ytz3XLOMtRRAbBt2RETwMVz1gCtnjposIQ+icbo5+qJszb4HH m43b9KZe2yrCGlfgWfE8MvkNpynJVG4qvzQCxyq1p9kEdgpGoGNnuhf1d3UFjnRttiGb0VM56DvL yrfMarMdqpZF61VrKVPXWmEgL+3rOky3W2bZudZV/ayVN4U7a3SW1gdt6RD97Tone9ysb61hnZYZ y4znrmfWlsaOswSgbpYdoGdglGueMeYkcxqhHJCqg5nuMM3g3ZuWYl0aveARPHFPvykZvlvtjEa3 77nW3aSfNVyHPCQFX8aXMQz/Bf4LDFdsKjYxgvzP5B1MQf4j+W1MTU6Rc1gS+VNyGXsP+Rvyt9h7 yR3yTSyL/G/kEZatVChJLFfOfPKURcoi7C+Vn1B+AstXlinLsA+ox9RjWAHco/f/0LO8/Vi+nDt9 CjKnr0NvlDtVyUr889hdbAarljOov5aV+BpZif8bOZv6j3I2dV7Opj4rZ1N12G8gm7ogZ1MNcjb1 t5BNvQ9rlPMoq5xH2eQ8yi7nUQ45j3LKeZRLzqNoOY9i5DyKlfMoTs6jeDmP8sp5lCDnUT5Zsxdl zV6SNfthogRypJtyjvRD+SnkX8na/CbS5nECafO4Cj2FjKuRQo8nEN8mfog/gbR5PB2ypl/jhbIq f4LYJDbxD8va/EniTQWJfxRlTfhzsh7/eVmP/yLKmvBmWZW/hLImXKdYUCzg7bI2/yVZm++QtflO WZvXy9p8l6zNG0gzacGNkEfx+GX0rDNOyxr8K+hZZ3xYVuK/JivxX5eV+FH0rDP+TfSsM34bPeuM f0tW4qeV26o0/Huyyr4hq+y/RZkVvilr7b+TtfYt1dOqj+G/R/kVvqN6RnUBfxMp64QGKevEE0hZ J5JUnapO4kmUZRHJqldUPyfegXIqogzlVMQzSEcnypGOTlSgbIp4DmVTRCXKpojnUTZFVKNsivg8 yqaIJsimJOILslLOqr+rfoPwo4yI+Lqshd+WtfBvyVr4HVkLf1XWwsdkLfwfZS18XNbC/4ushU/I Wvi30RPYxCR6Apv4maxw/1JWuFdlhftXssL9CD2BTbyR+DvNO4k1yKmeUjyJcipFGsqpFO9COZXi GMqpFO9GOZUiHXKqOsV7UDal+CTKphSfQtmU4izKphTPoWxKUYmyKcWnIZs6UFRBzlOhmIdsp1Xx C6QNkziG48V4/59ymM+u/bsrT8Iakg3xX4Sdws5g5RD3NVg91oTpsA6MoE5SpzEFVUiVUhVQy6WK 4TOLqoRjx6kCuZbaXgW1JKpMXws1kirFFNYj6FeKEdY9Khdq2xRBpUFtV98OtVUqXZ/0f2m9xOVf h4SbKI9UWX/6X3TnS//XQvzOlm4NXxCsA7azTWu2uHWh6bx1zbpg3W9us041JdiLtX57eXef3dRW Yx+3z9mX7HOXtLZ0W/4FQavT6mxnrUtN56HPlO2RdZ/SUNkX8u0J9tzuPuuIdchusrNtNXCd89Ze Z5PT7JSc15yTzklHnXPPlQC1SVeCq9hV7pRcJhfrCrsGXUOuSucenJ1yzbjmoI8BWt2APofQEm25 UBqg/aBrxFUJPW9Afa0pmbpOXXeI1LAjSo1eEKg71MQVu6OPmqZGHVepezDC4xeEpoSm8xcfXeh3 XKfuO4apB45RNCa3xn0MxjHn3HNnwJgmne1oRO48uEeCy+Scdw25T7pPu6bcpe4KWzq15Vh15Dm2 bGcdB7Z227xT5eCdqbb5poQLgr34gtBWYZ+jdu1L1KizpKWwpdBZ5iyBrdqx6qx35FmXbObuPmTh Or1t3gqtqAPboX3chjWdt8XbaqB9k1OQx6RxTrrbnLMwKrc76ioGmzwejwTjmXY/APuAndyrsK27 t2CrojFaBf1GYRaDyLbuKJwfdVW6J8Bee01rTQltNdC70m5yDdlSbelwZM3WDzasdJ2DEQ1Ze9GG vGpPls9N2s9YdwDXjdYp+wlrr2XWbqJOAgI2O+ptjH1fq7NONffZam3xpgTo89A6QDUDMs5a96G9 07ZIVVzasJV098GxW3B007YCSKq0z1lnqDbbGMVTIhWl+qy9Wh3cfaG7j8qwpdstgLyFS1r71IVT Nsl215HiZJyC66GzX0bBTect513XxX9B0IYrzZUMnjvjKnc1uHQup2vAtYT85RpC8wT8LDgXnStg uTGw3HnoIcEeAbaZhbMd4PFJp9YZd2W5bju3nXbXuLMdrnbc5Xf1Qt9N145r33UESBx0FbhOuCyu MFwJ4aTf+ci5B5Y6ZR2QI6DWprXOWedsN6wPbbNN56mUSzchGg7t5Y66LxR+odBugqPJgI6ZS1rA 6B3HNDXhuO94cEFAiKw/4Zhw3AM8LkPPZUcjtdqUYF2j1h19COXOfneGuwrwl+IudNe4s911ECWA NDcJvq0A9J21TjnWHYUIi06VU2VTOZNs87b5C4IzHWHRme8ssi9pxxEGrQuO/8He9wC1kZ15douW YGTOSwghhGjAw4AQjBFCMLKQZIxBaBiNEELDCP0Dq1vqbpYBqcdrCaw/LVmhOI6iHOLlHC/hCMs6 FOujKMI5FOEIRXk51sd5WUIIIYSwXtZhWYc4LOEIp3ORe92TzOzW1c39qbuq1JXpepK+1nuv3/v+ vO/H168/HYePIzxG80BLFdDaxFB+pB7I5yXQ6H16KwJmFBiKAFjE1IlkRLJDALCDKx1HR6OuaFO0 JUpFmb/u6G3WRrXRAVYfl6OrwD5mmHNAE4ejw7cSGK1laFBLHrkejUU2b9mBdrpAve2vJH4lMeqL BlkNHY9OAU3vD2VYekLZIVlIH7ICu7oe6gD6Ig8rwghjtQ5TuDyYGjgDujHBrEtmsyMhzA+W081B Ed1Mq2kTjYWbwJozHZijMf8C0MA79HrQF24BurSHE3/Ya70YNIcqgsNhQYgIK0IdwN6eOxJ8o77R oC5oZOYdGKKHWppamuh7zmlGC4PRYNC6bl0Pp9qmQpJwFriiCHC6JEQ7TO4nYY3jRlgXNjrOW4fo dDqFvkBfDFMhFc0Jm8HR1CIC6+V9+kFQHHoeeu5/EvYFKfqspT8ctPSA76PhbnqS0f3A/dBh6IQu ow20nXbTvfRRaCQ0EQQjDK3R8rCLng7cCQw59qyTv1uTQV2wHgO9mqO3mJWYsdhQdYgAXHM4TBbZ TaTFGAK6dSuBfeL1r5G/hiDk+8j3IRj5AfID4Gt+iPwQ+JofIT9in3hthb4CMfl4GRSczqJgAYuC M1kUfIFFwW+wKDibRcE5LAoWsihYxKLgPBYF57Mo+C0WBV9kUXAhi4IlLAouYlGwnkXBBhYF17Eo 2Mii4PdZFFzPomATi4IbWBRsYVGwlUXBNhYF21kU3Mii4Cb2bgLKuQyQL8YiX5rzF5z/BN1ld5x8 k0G10HcYVAt9l0G10CyDaqF/z6BaaJ69F7DK3gvYY+8FPGfvBfycvRdwwN4L+CWDaqFfsXcEjtk7 Av+ZvSNwwt4R+DV7R+CU2WsCxZBOpBv6DTcGMCnCYtJMFpNeYDHpGywmzWIx6ZssJs1mMWkui0lF 7G6PK+xuj3J2t8dVBpPCFeyej0qASTdhNRvzv87G/P+IjfnfYGP+Xjbm72Nj/u1szL+DjfnfZGP+ fjbmH2Jj/jQb8/8qG/PvY1Aq/LX45fifwdNsxH6Njdj/mI3Yb7ER+5+wEfvt12L8z8M/ZRAl/Gs2 Sn/GRul/w+6BgNg9EDCDKDkcBlFy4hhEyXmL3dlQxO5skLI7G4rZnQ0lDKLkvM0gSo6MQZScOQZR cv4jGxX/OUAp96DZT7FKTf9/Vz4TsZkz/ACdmdP8Br8JUEn+avDK98vAOcSv8ldAnIaXOMB0DSd+ sR9gtIYXdoDRGvb9F/wAzTU89ScCasuf7E8D1JofAdQTP+JP+l+yok/wVkJ2goKdQzoUB0G61d8V BGkru7mHI/ZlbJxY82c1OBqz/U34jL/FH7WsYgM2k3/GFDXaqRtWfZvbv4hHSb+14ub6zadtZzeP /EmOZL/Rk+1vIWSWGDbgX/QQ1A1/zH/75hH5iJDVPakVktMWX0AWoMle4npgzPIisED0GbeIWb8g yGmsx47xLOOWYZmUWgboMUt5aB4rCS0HEsnptmmyNzAI2ozY7rgFgZ3aBJuWJoglui9QH9DXWT+6 TevpenQlwLOlEDLzimtdfxc9sqnrqsPr4QPQ52747KNtHKkbCYnQOdu60UA+ssoirjqCcttutKow Ef0QGw8/sGvCW+E9w675gmX/5kEkK6IxGiLmCB8bN6w2qPBthj/ktGsIG7dWNDiCpsZsfKatjOGO i4MNNKhsJkJG3bBTQQzw5s7N6bayYFnQYNE4x4xu10WH1S+wbNObtRdrhW6K3nFxgn7yQd2IfpB+ bn7k2SRmrYmhefMefWI3k9P0y2BKmHM9zXWRmRN6ZNnW37XdqKsmh8Lrxi2jnJmRkYMjVqhuBA8a DcSsIVpHRIYjo21l6NbNPetgEIwzeN+iCz4KrgDZRBsc2IA12WbCEeqGw2roxqOhFldZKBiKhrpD t61QqCTUHxow3guVh0qM9sbs0HDwKMQPaUJUsAwbCJkJWe0dcoWoDqdYfORTfQeQnIr0k6fkGTFr 3PILaoVEHz0WGrcMhJrILmIkfMe61lxSe0ff2axoLifXQ1O1QuyYkbxT4pSQveEIvkjM2kx1O+Ac DXobsaW03SBkntZIqv5uZNFutsSIhZt74bO6ahyxiOtGzCtGQ+2dBkcdcUt2q+KW/lb9LestB2mo W7hFNE7YHt/KsChs64zMI7FbibbpWyp8Bkc+2gjI/FP+Y2Kh1u56ahvy77c+iegICaEKgOPDef+o f9w/Sj6KJJGPAoMBGT6MblkhchJHbh7dPEW30HX/vEXnF/izgFWaGZn7uxl78C9blv27dTJG5v59 NAETNC5ZK4x+u8jmvnkG7JLy+/z9/gG/yD/D0hp/uX8V9DRuXw1A/qSbWzcPCJn/hb8ESEsP9CjV 3+TfMAGr8iuAzbUAe9sGn1wBMBZiDcj+Sd0Ty771OjndWg+sSEZY6evAhjaB/jjoDL8AO259gmfR s5byj0SeHYsmkOHmB14Ci6NbkwMZrc8CyeQFeqltOvCErqYHA2PBdLojtEH3uV11FaH9wASdH+QQ O/TDQId1lk4OXsA14H/Ki3VPSMb6erDjwPPQIn030BeYpRf0g8b0umeEw1jW+LDtBiMB8woGuGhN s+Y38oxYeNqmDs+FnzK6GkEifByJiNrckfLWPkZXI0bSFGmKtNhufDjz4YynNXzfzw+f+oMRgX8Y nWs7Y+kVvy4itpsjqXVjESr8IHwvPGTY/XBR30lIyEdA/yeBlEvQ+5Q7EoxE0TuR7vBj27r5gvlC 3UhEEX4UPor46hbqruOauifG9NZOcjqQZvHh5gAd6HQ1B+4SHQTtXiVGaD0xS9NkJGANOAD/ouQF TGxYDoEVDEcYHSAn7RSxhg2g00F7mz94o3HNsl0rrBUC231EPnZPhebJuY8PYK8JrcnBCH0Y7HIH AX97aQmOmFcY3tQtAPtcdtkj0ciA7VFkymYISoPqYDP9LHI70h8ZD8qD2qA7+NgK2UzAcu8FHwQn g+uGjeCKccWvCCWFskKCkCikAPbmDzWFjCGfjeOSu7Sh1Mbs4FZwL3gGavmCpzef+ueNfmwgeMcv CLnwqD0aGg1OB+eCByEkJA7pwGrwNNRk62Ws1T0avhAWhqWkn1CZomGDoy9sb+aHsXAzPUaPhW+E 3eEuq4zsJbfC6WF5uCxsChvCvWFtYAErsfhCMWI2fD60HPZbBsjp0AyRHb5IHjUjRk5zKm4OqyPb QCtGgC3PR5Yjq5Hdj1aJhfBZ+JHFdSvNuUOZIkbKTblv5d/KvlVtM1n2HZJbyeH1yG5kP+QLP7pV fQvCRI28D4H9RmYiM7ckdYStN4hR/shG5PgWr24N5RixyAtrKwHsL7Rq8Rla9B34tu0OnR+g9XdJ NZ1GglmSzYFngbXAIV1By2iri0OmkNpgiqHf0E/30LTpdm0Z2QW8CJA93RkgAq2tTxyE84ml3+2i n4Ri+ueOzbrk0PaHG5jYKml0kFjASkusfUFOMIH5LpAfyA5InA8BfZ48H6gm/TbMdr9ti86gs412 wwZWQhrsTeh90mR3EdWBQXrN8sLa51gDUjTUTjZC1ifGG8ST2jvELDFrXiG7wLfANzZWkymBE0Df 0dO1c7VyssyxUHeXLANn7pFDZDohA7pcQQzaKbresYDznYO15y2+D+fpRAdNugmabnWtk8IAr7Uz IKN5gYeBJVpF6/0Cmqb7zPeAbCfcrjZhaL61s206dNy2EnoRGAztBq7TIzRkTTZuWcTM3kZuPDce griJ3EQI5n6O+zlw7lWM+1WM+1WM+/csxg31Acv5BM1f5XxSPvM/EY/OG4XiPBpvt/c2oMq8EfAq 994B56TeGyyV770LqGwvAd45HoGuA1CpXrM3CKjzXjegErxarx1QkFcFxbljXpXX8T9cOT757yOu Na770/3R5cZ/WuBRx1ybyxw1VJvyrYa2Ye2OYcRrt8ja9t1Qjd6Upl83pWmhqi3nUc0Tx4G7wgJZ T2sWQJsmc7SNMuW/32cYaZC27Vse1nSY0twVH9es0bdRtnJvr3fIu+LL8pX4ND6jz+y97x1iqXJf k8/nu+3d8z71bXt7tbPMGGwlZoEpv2ZBu+NZN4xYZI45ZgQNEXD9Wf265aHzqPaF56kFsiW1lTjm PHOeFd1ig7DqoOGBT9Suaq9or27Xt9f7jtutvtV2h2PuA3ObS59eW2LKp7J0y1Q5pXu/zw1pd0xp NX36dXPUefT+pppngRwJDXNUjIp9xPsosYampj5K/iit/To1T01VbTG8oCiqm1r8YLv9rimN2mgf 0Q+1j7VPWA6tHF9W+0Pvilvivu488q6AT9l6vzvbu2LJ+MBcQ9vEXmkb1eb7wPyB0a3SLVsNXoPX 1LbBzM3NY3hrkdRU68vUD5m5OY/quz4YqFPXLFSd1o7qD7xlbVEv5m0GmuFvGzWltQXbom2LbfPe Lt2y3m/Q1yyY8r0XvXKmbdtUmwtIZ47RDdNDLZCQdqdtv21fv64F87XIahZsYqtBfwTk0eu9w8gE SMXoo3zHPpFv0TvtE/vGvdPeB76Yz+Xb8Ol8Se1Qe0Z7dnt+u4SRIZBZlq8b1DJ61V63N9LW3bbM ynbIO+lL9Ql8Cl/Qe+A9MqWZozYxU2pfWA2mtA9KPFuO08rjOgOQTz2QClFzYuW0t3omPY88e55p z2PPQXtnDa1f16d7Te0dumWLQ11P6TQ67Q51u72HGmCkZD21nlqg9r6GOX2kYbrhccNjw4hj7/0+ 7ax2pwHoSFuTW1V1CjQ13WpoH7QA5/dRNlXSTlMtVJQap5Z1y7Wp7bNgBmbvUPsCeBf5or4WX79v 1TfKjNp76j1rT/Tt+vZ9L9pl3gPflG+GobyPvHPex4Ca9275BnzD7WntyQ1d7TzvPTDvdd/yb7Ub 6LUPATwq8fFr+tj9uq9xXwO2eI57Dtjiee55iMNN4iax+3W//v8u9xTUCY4CqAscYqgbHIVQD3Qb 9M08RfY269cvAb++BMmBb38Mrsb4dQXr15XAfz+HLsMIzIWusDmsrrL+tYL1r01sDisHp4xzBUI5 VzlXISenklMJuThVHA2Ec97lvAuRHB1HBzVzPuB8AP0hp4HTALWwnvhD1hPfYJ8E62GfBLvN5rz6 Kvs8WB+b8+qPOYucRejrnL/k/CV0j81V/ydsNvoBNkb3DTZGN8jmnv83nF9zfg0NsfG3b7KZsobZ TFl/ymbKGkFoJAz9GZsv61tIN9INjbFZs/6czZr1fTZr1hqbNesHbNasH7JZszbZrFk/ZrNmbbNZ s37KZs16zj3kvoR+zj3jnkGnPIgHQ/+Fh/B40H/lvcZ7DTrjJfISod/wkoEnhli/Gwc8rgJG2Ce4 eLx3eO/A8Tw9Tw8n8N7n1cOv8UzAB59jY3p/wMb0ktiY3ufYmF4y8L7/Fv48+wRXCpOnC05l8nTB X2TydMFpTJ4u+EtMni44Pd4X74O/HN8R74cF8aF4Gs6Mj8RH4DfivxL/FTgr/l/F98BvMj4YzgE+ eBl+K/6v4v8KLo7fiN+AS+J/HP9j+O34n8T/BJbF/zR+B77E+Ga4lPHNsILxzbCS8cGwivHB8GXG B8NljA+GrzA+GLaymb4cbKYvlM30hbGZvpxspi8Xm+kL58fx4+DrzG9/wH/EPCUF32CyrcNefh// a3A7/4/5/xq+yR/kD8JB/hB/CA7xv8UfhWn+GP/P4Qh/nD8OR/nf5v87+Cv87/C/A3fxZ/mz8L/k f4//F3A3/z/wl+Cv8h/zn8Bf47/gv4Dv8n/F/xX89XPKc5fhe+fePfcu/I1ztefq4MFz75+rh795 znrOCv/pOcc5BzxyDj+Hw392jjxHwvfZXGTfAv6wH5r81CuWqv5Z+UxP7h6k+oH3vUsNUMOAuk1N g9du6j44F6W6qDuA8lMTgLpBdYB3jruVGgcUAVakfkA1URFAmSk7xfRloPSA0lJ6quN/snp84s+R fl4rm0WNecYKkkdflf/9Ao8qTRXiytm60aqYct1Y79FpH+uHNRPvPPY0KV6qT01l6tNSgWHFclTF txx5fJ5gZb06XWnyZFXOqueqYmq59rG59Z3H6pR3Hlf1G44+rglazim73Oc9tz0DbS89q55dzzEF Aeo2S21TEJUM6HHPAGX1xNRuZgzKddUG6C/do6sa1T7WTNiFnqaGmI5Wn3p0prLKE8vRezpqzBNs OKYmlKaq7lKRVVBzofa6dpqapRaoJaBjT0DPrdQaVU9tKk2WI6bPun3Q57rySF2mnlb3epo8ut/2 N2s50uxoIE9QV6HhVXZW9hj7VFmqfbW0Wtxy+A5mOTLWG1beG9UPX01oiFmO1Grqufq0cpY6rBil Tih2TtRL6tAzoD5lOTPgGbAKmMMzUDVfIVYLVQMeEeBQt0pUuXT1ceWSct2j0axdvcPM7eojhree liqFXahpZeYGrnCmcqlKAG9TrC+UKZ4Sj0Kz+U6Cx6VaNtarTxUSk8ljNPUaE5VHVoGyV51eFfMI PGJ1ioe6LFPtVvEBv8r1w2q5erISSLHyZeVLZVepwKPTTKjTVQNVLWqp+zyQSDc4wFg9MSqRavVE qWr3JCWhVO5Jz23qOgW51z37nkWqo62P6qPuUoOMDNtetr2kMoDkjsEYzJoMk72y0xNlpPnbY8Oz 6JnyTDH8UQ0w5T2dcl19qmqxn1cpqIeaNWoBSKaeaq0YBVzbAdqjY2TIvFLPVPvKLuW65jkrpWlG TvgWGPWm4mXdMiOlynownyCu1vAUaUYefhG/+N4oK0sdqMUDEs26+liZoj5VrpfOe4KeIJBqhYau dWieAFkPgfZLoG43kBXEzn/Zs0ylUTwqG4xHxnJixjPjxigHRYB5j3heMDNiqX7moCqoCs+o+wGV T/VQnaoZima1epjSf6zdrF5PgU+rnnmPDqxOevjb8LfB4vQd+Dtgpfou/F2IA38P/h4UBz+CH0EI vAQvQVx4GV4GznQFXoHi4TV4DUqAN+AN6DV4C96C+HHFccXQubifxP0ESoz7adxPoX8R9zdxfwOd j/vbuL+F/iDu7+L+DkqK+1ncz6DPxf193N9DyXH/EPcP0Ofjfh73cygFuY/ch76AjCKjUCoyhoxB X0QeIA+gNGQcGYe+hEwgE1A6MolMQl9GppApSIA8RB5CryOzyCyUgewgO1Am8hR5Cl1AdpFd6A3k GfIMykL2kD3oTWQf2YeykV8gv4BykF8iv4SEyD8i/wjlIifICSRCTpFTKA+JITEon8vcoHqLy+Py oIvsOl7AruNidh0vZNdxCffz3M9DRdwvcL8ASblf5H4RKuZ+ifslqIT7Ze6Xobe5r3Nfh2TcTG4m dIn7BvcNSM59k/smVMrN4eZACm4uNxdScvO4eZCK+xb3Legyt4BbAJVxC7mF0BWulCuFyrkl3BLo KlfGlUEVXDlXDlVyFVwFpOaquCqoilvGLYM03Kvcq9A7iWuJa1B14nriOvRu4kbiBqRN3EzchN5L 3ErcgnSJ24nbAIG+wqyvMOsrzPp7g1nhubj+T5GfuPtV+T8on4ntiQPiCIoj9ohT4gxQO8QheN0k E8C5Q+IZcQKoZTIZUIskBN45xBwJ0DkxTRyBdw4xQTwD1BgxS6wBapgAuJ8YIDaI7Vce8v9bD/lp nNURR3z6C1r5z+FRCVSaX0ipdwsp+bjWjOtwc8EEdnxpDqfkuzJaMiij1ds1FD6Fz8t38eXSCqWo 0i2BCpYKKbMatBHg5vf6Ls0VJYAWt/F+pmYFJN9Vp0oGXSZ83zGBGQmC6CB6iA78Bf4CjRDXHUuA HgH0hmOC5KD3rjxjxiDhFXQUUpVuXFdqxc3YcdV1ZgSlz8EY7koGy5bxKdJA2ksrSp4qmiXQJQOp rdGZU0gT2ezykzfICNnlEpK95HnyDnFC3mN6ZPp8jy6kyAcSGTlJzlWe4RSu+7i/QjBOyUuJo7Si wlFVbX5g3ru4eGUNn1JESHlpp7rF5hYfgLkAXpAr5NOqelxHnsnoa+XOjGZ+cxJBNJc0p6JHzQIi W0bji/gUkU1kVwqZg8jGkdL82i3xJM43q/HU2i35cMlK2a4igpfbTLgLb1LYcR/DW3wAH5VcLxxn 5oZPlY7Jdw3dhZQmodJfdYJn4WK8RaPFg3j0kgnUFeAiqxU34uMSWaUQH650F1KuMzypKAGfwTXq 1QoI8CupYEK+Kh9Vb+A6JTiuHKq35avYcSElnlScVl4E8tjFNxiZgNH2EYPkeXyVeE4kEk+ITYKH vyBTgFxeEjRRT6aTF51WdJ24DtoAmQGpPQSlD1dIDvFuvMT8AF8F0jzGY/gxYSVawWoiIWQywOtL GHu1PUVERpdR5Zi+h3SXd5F+shdIZajS31xC3iflZBmJNR6Sakc2OV21dOVQEbn0iHygSCfnrmTL s8hHuK6pizyo6GSkpBQpRRIreVpVbTx47yW5R+7hZkaW8lVcV1VNrhcslaxoEmS0IqKISKylFaVj zYgkXzlPPia3tGbyCHC+tzmrObVZhL9oFhMOcEwQd8Hqd0KsAU6oiAqiGuM7x8gE1xApJToJCI8x FJFGJBMZYHV9RuQTC8QSKXRmF86QF/Bt/IVTTxwynAHtgV6DuUPEdUIv+fgXnTivEOlnIlIGi95j seifsFh0gMWi32Cx6CD7q52vEOkrRPp/M4raDezjE5/35slnoys0H5VAcagKrUCrAaVAXeBVhxrB OREqRhWAKrMuACodvYCaACVBEwGlR5PRCojjOEDFUJzjDEXQVEA9dxwC6tBxggo/WRs+fcLliBv7 NEfVm01M4fyieK5IpE4unlNCWr3KUKTL2RA+FFYIHzalihBNTGiVWlFdlfQSX94j7URdBc3STtFo 8VzdA3Wy6SXTimmRs1GhLRJoFgsTLx2XSTSxBnmVVBK5FM3xoWZ5jyRdelgkQn1oFB1Ah2uN6Aa6 i8awZCwfk2HVGIFGsU5sEJSH2BK6i61hh9gJ9tLJQY9BmyBoM1prxCBQPxvTowNYPdZZK/64Juhx FBtxXsjFREahVdGkaJKOoOIinbBD3qOYqtBKUsSjuqBwRBOTZgvrlc/yKoR6MOa71klRkqr58jE7 pg3UB8Z0jMacanANGepjRoS+wDqdBmwQXQbXqXfawXgwZ3PxXOFa4ZpoVNGkhOrTc7XynqIkVFM5 L+VpYiJEaFUnN6VKO6vdBc3yHsBXqojKEReUFUVzqBJXUVJDClOjSspwuEhTDHgt71ECbuV1FAly NlQG0BsFRtTPjilWa3T2oovO+85J5zoYUQzrBGUQcGMXXXSVYC9dGuyZftqlq3W5jM50TO9qAuOv dqUCDi0xvHU+dR65BGjMJcI6XWKtXpqNNmE92OYlPrqbK8+7rtVr9cVPsetYBSbL2Si4XyQqEgnr 7QvFc6KkmjStHlXYF4QV0iVJiiS9qElqVewr09As0bFoVLWVQ+XMoPzc8w0HSkhl0MTAZ2FZYu4F 0agSEgmK9kUC4UPFgGKAma1oFBXnZBWoC9RSq0gg7RQO5kY0A8Zgcbpsr0BaJAJ80hUBDVNWF8+h Rnl1UZJoNGdRuZnjqtxW3kVvo/3OdDBroAXoODqFzgM+LLIa9ALLwNLA6FtZ/enDxrAF53lGXkBi z7Fn2CyQ6Sq66kxBZzAHRqP7oOUMlohNoItYB3bXmQCk7gPcsmJPQM1ubAf11WxiEtDjrJPjFDov OqVOOeD5EmYF50eAdkKYCtQcQLcxntSq3CyeK56TyJXQZUplkPKkhHRJulSgFkWLKMZyUJ1yR6y7 1K0ZBjzziaeknTkUsKa70rvynsKlokXA3fqqpx8f1skclyam2ioyK5oap4F26Cq0YLQDHx9YPZhv v/OGU+v0OyNOU5FOf8dZ5nTLe3IvCq3iEk2M0UXAt+MikUQt5VUeOy4K6z/WRWlnQTNKAZkai3S2 blu30IFqhA4wWmvlvPBh3QMllENpYjmUuETac8lYPKegqrXSQVtLsaG4GW25TEl3nA9cZmBjXWAE d4A+TjsfOR87VzDIeeriO88YfQTc4gB9zEKHsQ6924W4ECzZOQesVQXKM+ceGgRzWQVlA91wlbsU znSXy3nPOQQ09MCVhPWAXreK7xfP5doZ/Snrkw6qE4X1BWqVIWdG6Cg+X3xeaL00I0otnkYFykO0 XF4NrLDj8nGJQJ2s7Cy+gOo03TnmwrUqqepOwWSOuVSomLrElx0UqnL4otFceQ5VuZ1jzplCSyRb lxQ5y/JOYWfxmbCiuEtqlciZ7+oMaJKhuiwjz5qXrzlGU+ULohcqQ0VErje9LJVfLq97IFosfiB0 5Iil9GWKWe+A7B+LFIVruRdyhdKTHHHVWYNcckET08SKovYFcF5buCkS1e3J84t8ReOKXWVrQ4rI XLxXKhd2FEVzE/JkjovA4nSySfOAWCEyKjerHhXvlSQV9xY/zT1DRaLt0juoRrkjkTMWotWXVf9u TRay6/E7zxjJikbzrjNaWHoPSGpQ2JGzodwU9oEVt0yEoDE2R+APkB+9enbl1bMrv0fPrvRC/Z+i kPRNtnwmQlL7rmxCcWqqGLryDFDN0lPwil3ZB+fs0oMrG4CqL3wOKH1ecvERoDS2e4Aqz0PAO0ct vzIPKKn00ZVxQOUXdwEqW7Rf/OCf2MenT6UIErI+xW7pCgTJnM7fzD0RcUQHGSfC0YZksdZ23/ZA JLXdE6WU5guEtvWM52Jp7ljNdl6J7SiPbxbWv7SZbHYblnFo6yocsA2Jj0RS8ZlIWppfP2J7mjtm OyjZyjgUCBv7Xje/LRa7LxjtSRK9uNdurtE1QBKepEe09bZYsiM5zM5+PSrokhrzE4sOsjOaHuch jXclksYRsVvsbpwALZryRvOGpUYJr2AJtBt5W9wkb7pRnG9PEnS919k01JQuSpA8E/e+Pyzczc14 W3dtG0Dye3mj115k2kWRzKNrsUx53qgjrXA3MyKMifbEhvoFo1qAFYqvzVybv7aY4bi2Ku22N2W6 RZHcEdBC7khsuiGMOVQOKMORN2o7zZUVdOZv5nXrkwt1uXRDcmEq4M+Dgk57f56oyF88YR8W2K9U 547lWgs1efxCnWmgoLPkvv124bCorHC0obpoPbOs0NV0JkooeqqCriHC/cKWzGYVXeTP0AvuqyCR SVp+LTUDupb1OpKhuiayz1wT2+eL1MycBO5a7VuGd7bBjJal25l2cS8zo/yOTLl0P2+06UAYy1x/ fd+ofjtJe5sZJTPO+sNCnX1XoLYfF2wWbNr7G5KLJ7QxgT33JHescFs7nMcvuWg0NVpzK+pPGh2F osbWxuuClLzuTHnuiVgq1jZ2NPIaMxplStc75uKJTG39ywxIcE/cnHuYm3hNl9EpFV8zN50WqXOX RKa8KclOnlmSdm1YAonPBA8yrPZV0X1z2bVxwX3x5LWpvGNxs7L79azXo9kn1xTXKGZW10YbO0Wm DF5mb/aJRP/uY/uquFc4w8w1p+ttnYOQBjOqMyeLkzOPRPcy5dkTeaPCXWGsZKu42vjf2DvzKKuK 69+fU6fOuQ0CEkScehKRHqBvDzTIPMlkMwhtC0jfvt0iIiIiDiFIUIkizyhBRKIEEQkiokGCEyJB RESCSBAJGkRERESDSJAQRIJ9f7U/u58ZVt7vl/zx1nrrLddd99u7d9WpqlO1q2rvXfvc0ytzUpuK wsMZxypOtRlxcaLjmqy9rc5NH5/XsaUb3ZLd1YdrpmVNrplfs7TUXXnewUTjDvkDd7eNp2/Nap97 oEtJckZNUdW9VfMzlrQ4XrVz+LndjuS80Cq7bXrugarjicZ5u/N3VhzpPy3neOaR/FOVY7oN6pCf c6pyRssl/bcXzJcxr1xRubJDfuWmrMX9p513UMa88kDuipxBw1sWbMkrzeh43vHK8ZW35M7InZGX W7mm5ZLK9fJ/5dzK2ZVbM6OCg5n780o7udnm+rk2Z+nwpllNB+7OWpl7yM22XYVrh7cc1iS3a148 c7mbbWUFB/P3Z6fnbo2XZQzPGN55T9t4q5bJlolmiWZtRyUHD/OyxhRPbnE82bVof8H85Oz0qcmt buZsqVpXsC5h4wvi60umFA1KZne7PbkjOz29UcbETt1zRicb5URVp9qOKjruZtH05N74isyz+73Q 74Xk0KJTyU2JPm0WFY0uSc+2eQsLd2cMdzNwRnyGm51jqmalT0+UdzvSaWbnRRkTsnrlVOSuKFuS Ec/x4js61GTWZHyet7tkYs6Rlquq97nv5wUH47OzEiULC/s4OV3S8nBNvqvvUF7HmnYZY3MPyNwr 3pRrildWb66cGm+fO6PLgco1uWk1kft/8qBxlbNrmpRMGdgns6JVo+r3nGzsy1ne8mTJlKyyjFHx GW6GH6vJLNucPrKmZ+nRFkdq+mVuzJqaszxndXx2TYuS3SW7WzWK78jf7tp4IGNCdrqsI/lLczIT AxIDqvZ3Xt5m+/CS+I5kmqw/yZF58YR8JiYXZ1bklebtK+qZmJdzfOAxviPy7um7u+WyQe0SyxLP JZYUjkofWdKscOylk4uaVKdXN8uf1uK4fN18La1unNhQfCixecCh6o5tllfXz2rfcl98h3yzdqSP z26W369kX82gmoqcioJpw5oMnVdt4zNy58qclf/iZYW56Ym8exLvJT5PHI6XZXcv2FM52/1tXHCw qqj/xoJZXfZ22VvVr6pnTn5VRdXoqhZV+e6a3bmbqtxa3aKoqkFiW869eaVtlrc5ntjt8g0q3FZ1 e9mqnNFVXtXZhfGqzvFzEyfT16fPLdrTYl1199yS6vL09WWl+bdXJ6snVt9TPL16ZvWc6nlFFUUV yfX5RXnvlZTHJ+fuqO7T5khWWvWUoqjjruLJ+Q8V5ef1KeqZO7S6e3JTcn3x4KIGGfUzjmVOqx5b fWemV3IsJ7N6VPHsnChvSdGpmhHFk2vGlcwrnV49oWaSm8MTEsPjpuah+KH0kW7sFhUvLj2al5vb tPjpmlklu2tuyl1Rc2/J7jZNarzqtYVjize5dXhETU3NIrcGja5ZXj54eNO+xzr0zCjNX91yVc3t 6aZq1vCWWTPyl3boXDIgv6ZkQ9JUbc9onl9TdSQ+o3J9i3WdFyUmJqbkd47PdbPkUPJoYcf43pIN +TuT45OJ9JWZo3NNcnKiNFGaHJPomOhY3LTiYLy2ZEDGxOSuqtUZE1wrpyYGtOqVPrdNkVu9jiXG Fu7u1iS+Nb5V0hL1O61K1C/OTtyTuCc5N5HrZvz6nBEXbs3cmbmzS6/SxYOauGuad53TJsoZlN7r wvHJA2Xd09OKF+TtzmmQMSFZkmydLBleltu6bbxtvHh6zqTiFRcnMjsnn06uSNxZNLq8a4ZtVVYy pcfm+JhBZ+c953K0SJ5IrizZEB+fSC+aVbS0aGfBrIIX8iZU3ZuzvGpP1cH4royZ6e2TvbKyM2+q rM1OTzSv2t7tSGJCSXmyabIs0Tw5NRFPrkmuj0/P2ppzMDs9uzxretULHTonRlUtTXRv26xqY7ys emKeRLf7/p7vnz75/umT758++X/u6ZN/8Lg2mvbf2xM9Jre5xwt63FKxu80c99+4igMOR+c87Xg1 FZtynM3QY3jOIvdfecUW99f0KCuY6f7rVbGsYoP7r3PFCvdfu4oFFYs9c+nRjPruv9yKRTkjvlsh vrMm/O3BXGITOnr9Pa/hof/he/Tv6BPuW/tvXHOoLt+/yNvI6vc7uv6/yFNf65W/fBu7bzP9S3r6 36X9B99/p93/sj3N3TfX69/Q4xM1bOA+Tdzfs91/DRpmur8t+OQ3LOKT71LbuY/XsLP7ns2nXcOe Dfs1HEQJFe7vCJfWuWEN3wbu/xr3GQ3KX6XGgRXu41H+Ta6Um9xHrvHcNYMaTmp4uxvb/t9HLNRF LJjQeK2JWyggPiFOfEIh8QlFxCcUE59QQnxCG+ITSolPaEt8QjviEy4iPqE98QkdiE/oSHxCJ+IT OhOf0IX4hK7EJ3QjPqE78Qk9iE/oSXzCxcQn9CI+oTfxCX2IT+hLfEI/4hMuIT6h7PtR/P9iFH0/ 37+TVX+zV+h5aTP1W6/C/V3yd//vrPtW6F94e9x3/9/lOei+R/72/7/8SpnP1X2X1NXzT3m+q6um 7jvi7+id/5Q+4rv2FNZrX/fp6j693KcMHFxvaL2E+7R3+/GYeuMd1culJ+p47d3+XEZe4U9236nu M5lPmfuMdFdI+kgn743qfklvz3e/pBfwS3rW/sZu9dL4Db10fkMvm9/Qu4Df0LuQ39DL49fzWvHr ea359bwCfj0v/n+tXN/MsDxN6q90GrIXvfCP39hk953qvtPreHv+xv/nvP/OV8qJzfgf8kkdW1y+ 2f/E31j3FXr739oif/93e2jvf/j9t9q+/d9o839zz//Qn/9h3dL//8QbGy7jc2d4OCx3nwHhPPff sXBOONN9FoYn3f/uE3nyCSe6b7nj3+PyzAnXkudkFEUNoiZaSnR2lBk1iSKun+PyrhKtOsoH5a9S RYJ1NbtP1C5qx9+IEuVzWDDq/Dd0Wn65a8/MqGfdp1/dZ5B+aLfkKw+XORm/4vv3Zf+L92X7oe/2 CnlrdiFvzS7irdnFvDW7hLdmt+Gt2aW8Nbstb81ux1uzL+Kt2e15a3YH3prdkbdmd+Kt2Z15a3YX 3prdlbdmd+Ot2d15a3YP3prdk7dmX8xbs3vx1uzevDW7D2/N7stbs/vx1uxLeGt2GW/N7s9bswfy 1uxBvDX7Ut6aPZi3Zg/hrdnlvDV7OG/NHsVbs6/mrdmjeWv2Nbw1ewxvzb72e8n4XjL+D5LhbFCx /lJfp37v+bWHoE+m9jk8lTrk8ERqp8Pjqa0Oa1PHHX6T+tBd1V9yeqPAAf4Uh338pMNefoXD7n53 h0P95S5/e1IH+7Mc3mnudTjJyPOPFf5iKcE/5nCkf9BhjZMv30v4WxwO8qeTc7jD4U5afe92I++J nmDkHSvl/jyH91PXOvJbr6nDyMt0mObJW+48aa3TuDo7LPNvctjPH+Mw6fRi35tm5GRvtF/rcLIZ 6XCcSXc4xqTJG/KM/N7bWCM2+myzy+FUM9XhCKdx+94cs9/hoiDf4bIg4XBLcEpO6Lz69CeYWg3u hOPallpdu8jh07XlDpfUdnW4sDbb4bxaZ4Wn1taudLiidoLDRbWu5NSC2mYOl9W68lMPfXvY4fza Bg7nfntCYpWJWP4peA/4iNx1MAa6FnyNSKoJ4B2C5nPwM/Ao+Rt7bj0IIjhvctXlYBWpvaEHkIps BDOhN4GUH9wI/Sn4Bfgn8BSp54I/4rlXJC24HlwIppFzHi38C/ST5PTBL/FLrAV3ga+AT4NvgM+C vwa3UiblhO+C74uXJTwodFRG6n2UrPHej4GUEDwDvsRVX4H7wcvgvw5SZvA7cDWtPQJ9OvQn0AG0 9tIacA74c/BDcCk5TxNZMtvhJL2FDqvB+0RKzbXQc8ACWtKElnOPNo8SNsA/CzwAh54MeoC3gX90 3e4H08hDT4aXwFep8CXVHIazHPwz/NFgfTgPUuNe6BvAO2kzOYO3wX1wTkCfA/b1trur6A2fe3ez XXAGqZRm6GfzV8pnZANGNkTegpvBriByFVwD0qshGNxNCYxv0Aea0Xd2rpSp/KPQzaG3gA/TktnQ z3k6dyRPK7AIzgroM6DvokbWusBQy2bwRTiMe3Q+dDrYD5wFIvMmBR16bsULXqbklpTJXHB2peTR Gn8AJvyhLicyH7xP+dQbIntuxxSMwW8Gn/4MK8j/EbgbjpbwFmjBgVzLCIY3QXfxWzs+chWdCVYK x+pdTAYX0cIzybnJG+Lw995droTe0K+D2wXtdOgJYHPwEj90GJf8bjWQPOeBLcCW4B5yrhJMKwTv 9Y86Tlv4ZVw7CPoi8DLwLLAEzAPTwcvBKdT7LnRILQPAgeBwQbNBMPq1oLPfBF8CfwtuJecQ6OXg q3B6gNoe7iU4H7xfMJwDnknJ4+GfBLeB78C/F/pPdalyd0e46hlSA/gvghupazL0t9DdoWlt8AZI m92eJHRvU8/hK9CbKPkT6FrwG/Ah8EvqorfdmiYld4BuBXrgB/DLuPfFcC6lrp5wllCCykAuuBoO LbHNuKPT4HcCP4WvI/i/oC3IXYTtofsKxs4hzwXU9Sz4JBxGza1Cgl3AruDF3geu3nrUXp/SaJu9 Clzh9gffIhW2P/gCeA85L4a+GbyFEuaCtDCi56NR5HyOPB1BeiYaRu1IRbAW/mfgMnAvV70JvcGr dPgA9CkQCbEZlPMT8E44v+Gqv1Im8unWAUltCq2jTPnhh+TX9WRVar7jn808Pco87V67w9H3wkFD sPdDs+LZTZIaskrY1rXrZE1j1sdESwl019vvbWIdFkyJfmJU35hcu8fRH8M5KFeF7wuaBZTPTmr2 wmFPMSdpz9mi0QVW6GgMtbNiO6mWtWgf+dnHzTbvIcfZ4Z10OALOBr8dOobjmNG0sI2geZzUpyhh OvT75PkEXO2NR2I9Zp/gTKk3WJrq61LZBcxn1Kva0TFwv9NqnSSL9hgkaue6PplCz+i+vJP8E+jb TNHW7PPS824bpfe409+yiramrkepN1N30trzZC3l3s8StBPp/55SjttNROPKFzRbKI0dxL5Dje+J dh18IGjuFJ3WoIEEuvuXC9+eJ31iL6RnrqaXrOjYNptWXUn+ztTbR7RTM6J2GiuS8B+qlfV2ve7v tb9hlJ1UBN1EC7W67zeXETSf055a0efDwVo7qY/SJ8doOe0PkSjzhXRO2B7+hjq5Evwj+AsQDcHt C4JZICMSdaZ8ds9ItRFGPFAN6sfgT0DdixfovYBzwT3gqyBajc0F24OqWal2xA4eJpEB+sHSt0bn F3u0W6s91i7hsC+7lUQQzdmq9sK+aWltWA0igRZd1zYG0Rgts9WiL1n22RB+qFrEeyC6dHA1edAB bAYYh/88NDpA8AA4BXxKd3ZKoz/D8XDQ1ux88qyERoNyu7nQjIVbMyW/loAkB0hpgLYWTCKVuwi1 D3eC7cB6YAuQ+WhzyIm16FZa4XwMog3aXmA2qUMoHz3WYlNY1dVVR1KLgNEJ0GPtEugj0K2hkROL nhMOAofCuQI8Th7qDbUPWXmC20FKs0iIs+gEk6wDDaDRlALWokD1QNWi0RiDbuB1IHPBqGyzLIQh JVOOoYfNKjjoZhbd224k/zpoldgdoOqoWFsWjdfeCqKvBip7jGPATAkKKV9ndENQ5eQ14yxQcxxb AJ0/qC9omSMWayWkDy3jHjB2wWBtAzl1ll0LMoOcheixo3loVlICEh4wcwPG2s1r14dmFvQykLF2 q5xcpToz9pFdCP1DsCc4DL7OBbVb9a5vgQ8aLMRAdWYdcfrEqP2rc7bWv4V9WfKgIVt2vYAZ4ewj WZfUUjbQandcSE5aYtbWachDWOuG0BuyCz8BLgLvFl3L3gatOzg6VfhyXaqgpqIDBOz1AXqFszUE n0Rbmw09glpUB+tDOaVoQeje5g+kotM6G3wIO6bkPAEmwevBq8G3yf8oSKr9Gv5OSv4B9GZwPUiZ VrW1r+AsBZ8GuSOr5aMVB+g5wVvg8+CV4HFzvcOPoVV7XAguAEeDCdqP5mzQZwx6V6Aar9oF66iR Mu1IUPX8S8A7wGmg6mbo2E5Wh7AicZX/Omuv0GNAesaqVnkUmvEK0M0CLAK3Tg5hHxFE9wu1NPRS Z0sOYcYJBx3VorGHun6y5hh8FEZtZCzQEIyxv8RY4Y3OfTSfgHXSYKVafCZOZ3D7eMjKEKrViQ1o 1Cpk30nDSg2ngqxmETtXrKx2ssvJ2h5gM5prhBP2Yadm3Q4qqes0rkJLDLFMjc4R1k/DHDdY7oZ5 atQCxd63ar+r7qQelYT4rCz+AcMOYtR+ZN8x3IvRHZn9Ijgs+YPFqcbuKmauaUcJs+FzdzHtkyz4 6odpTM4/gBeRqp4WtViZ75Hqt6XQ9F7EWhfgbbC6CmEdh7+EVh8L+oNFvwpVA8FHZF9Fx2b1dnNc OM1oTydBc6p2s1ybkjPBQuGErCEh9nioqzp9FbISRrQwxLtiGLUQSbDoaREaTlis/UMetdmLQNao GH6JgHU7wjdiT6clupd9Ax8vQYBs2Bm6yoFo6aHu/qVc9Tz4GPgp+Gf6/0LwPLAB2IhrbyOP+hbQ BEwf9OHpwo+xD8bYT2PddCyEH6k2gp8haEVpy8U76ixHhxErdsReH11P+ReDw8CBYHewBz1/v3hT 7R1wttGGXpSpOwseP/NsKsJ2kx6AY9VHtNG7yPHPFYzQUgLkM2Q/jVQ7wnryX629EZwgXhrK/7m0 NnxLPL12ODnxHNoV1IgeaNBSjO5HSFTIvmxVe0H+rXqf0GpCXQHYxYIOpKrsqQf1HPR51hb7a6QL qQ4GcO9Il2lN274V9B/AFlDpQtoNWqiJ61hTMncd6dxXWdWdFH04GAl9hNRZpOrcaQsfPS2m7VTN TWW1RmzDkFXFfA3iOzXMlxh6XfS6zBRnx8l8eaH2c3cVemCgXllmdKB6zjquRac19HCEHhUy3wNW V4u2ZtEQgn2pVz3xNkgebNUQjSLS+YX2EtHbVldFvM0R8mzVp92TMdVVkTaHaOkR61KYp/0PrSsb 64b5GXfHWNentJjeL3pjyDoTQ8ewzAVLHwa6fl6PfT0WWn3m5d5uV6Ouw+wRIbpQyBw36JyGcgxa lkHaDWVGaKcRulmE1EVNQTyxFs+wZZexetfaA2oHoQ9b+jZiRgc6siXat6JDBudJ24I/y/mO05mF vgi8WDDEIgtZqyPVsTlZsPS/01iedql4vO0HctdWrRLOLELG3dJaq5bCOPIwggaryiCZBom1yGdw qq5kQXzFIScRFrvJsgpZ9Qyjo1q1CFRWVRukzZH6ItRG6At/MKPGahmM07kgmmSIzhniabeclYR4 9S1jFGHBxWhV2lSVYTwe6MzRDOxi5n6oNhfzzjxe53EdwRo1An+v0FeAVwm6WxyBRurQWUlCN/eO eGInCr0UXEHOS6HjgmkDwS/lfM3lF35rSvgWPAH+ETwM7gb3krMXOAicKnU57VFSl8H5GDwIZ4xg LBQ0PwSvJnUlOA5cQM6XwNdoJ7WHT3C/z5DndfAxcDn4FCVbaEoOm0JP4KoqOKvh9AGbgWvBGeBZ 4K1iidjZ0MPBAloyFbpCTiTdrJTSJsP5GXgN2Ia6ZkGfDvrgMErYB6bAKeBxUtuDH9Eb2fBHQNMP hlZF0+BvJ2cn7jQDeiItWQMdA2vAnWB9sIQ8XBUiIXY9ZdZS5iJQ+3MU9GZSKTMiZ8i4WyQhfEBO UZ0uJJxtcM6D1jx/4KrHwflwkLpoMTgPvICrdBQ+h6O93VB7mNQWYA8wizy5pH4NngP/dmjyWJV5 JNOtGIL3gz/n2t+CSGzYGBqJjVT+J4Haqi/pgR/jkXtOzrIDtMGgml31WziqJeLHiLqT2pjUHHAc efCgBmfBuQ08jHahunEXOHcK+in238vB23QvlpzBcvKwRgVzodklg6fJ8ymcW8DnwRvBJ1NjRZeG HgveBb5Bq57ARtBTP7SRYCipD5NKG0LdfZ7EN1hKXYug88Gu4EVgZ5C2mfmU0wHsxX19BH4L/hn+ FeQsVH+s1GhOr+0nOzipWdp7WiNtGwxtQbx2Bi0iQOsz7PsGLciqTqs+NNZ2q6su3lSrY9RGV3Jq GQF6tGQf5edCL6Xnu0sfBsXkSQd/DLYEX6GHd0BnCm1V7/od5ai+uonUnXDe0f4Ht4AvgfOoUX1E 7EpmFfxG9MxX0OOxI25ldC4gPx5R8zCp9cAzwGryNCTPZHAzuAdcB64gZx8wX9sPhqCeFA+D1py/ 5Cr2XKM+c/zGBp+/0dP8Zozv70FtM7JhdUyn0v5LoG+mhS1I3a/7MvweYAH8aylf91b2d/MUHHxc 5g7oZ8lfBGcNffWs1GKuhD8IRHMIkF7znoypOcSofU1Odls/JXyL78uof+/SOumd4MkJu3A6al3a P+AfKPNDWovH3nwM56/gNq0LegP51ao6iET9FenCB2s4dzY/Tp3rid9D8iwmtZyrRkPj5XZ9KHSh oL+Nlv8CzjgwCWbQnhryo2EGqmlwchGqb+FPlByAxfTbbq69kTajX5nzaTnxAEZtxpHUe4o8p5G/ QHVCek9Xp5vgXwNnO3QltTwhtdg1cLQ/+0L/DKypq11G5F5dP8mDjAW961JFZi6Gcw59GNAS9PYA G9zg+zUaf4I/2ZwgzyeUcBH019A3c/7CfRlsbaMr7TwQv0SgOe8H6WerPvm74NwHPgKf1diqXx1v hukr7YxU357OiHwumMZYp2HFp6HLRejVkfoimKGW9TPWXldRc4fY5hJbFTY3D3oSt3DAE9+XlDwe SR6CZ2YAiO0WqK6rNlFvSrhTSnAy1h5dS669iva3c+uonKBJmUvBRyWCy0xL3YMMC77AVWPpva8k uilYJznDdL+RyLZEy5id3gxX426pK+xBjY9z1XrBYLJwgg8l8iowpqX0ksSxBL2J9zg9VSN8ieky B81zIgNSvrNoBHPd6i5ndo52FsFrMvoSZ+XuZbXD2TpnJQbMPJJ60aV+I5Fage9/I/0p8VehEXQc V35wwF/i8HzhmNtSG1yeraR+BmdSaoWjG8splXmG2odJLJazOJxNYZ4QS8Qs030k1cVhgj55zCtx +Cs5f3S91FPWSUFbHyQ+x46HvpnInBew3R5LtXD4vKBZTz+ERFWVcqL3rtC2VOwjcw8lTwTNt3Mc pmpvknaKP8Ewp0wtJXxYt5442rwLvgZirZjfQr/FKecq8j8v53dmOLiaukamBoi04IGf6/UR6a2T B4fBfEH7YmooOraMOKda/vFve7k8P0XGniX/3dzXZEp+EE6Cs8JOlPMg3ptXxIp3rWrCVctlLfUm ehIjtMulZnmHHf18yqF9hh5elBrj6B1SQpRLS1ZKS8wW7usV7L5n6DeD7D0tnKgDEtiL/PW9SciV 9PBb5Dzfl555WUoIhtDCDdLPdmjqdtGu5Y7sQNr/CrW8A+LZc60VqXiVfltIj2lk0Yti9YQ3M7/0 JH2N1GVG4+VbTV2nc+8rsIJ/R0vyaedOvBzqq/Qlos+M4qpN/tme7H1yjz3pw5aS314jMmzW0pIN amUjXe9Ce+R/KTXbk6gwaeFK2n8XZarnpBjJfFzKD5YhSxuR/PuwzYdJe4LHqWUdJRfT5zu/XY8c ynit85uTKvfVnHH/iexlzuoRGbuSWfOct5b5W8Be78q0SVb7ZyX20mz1T3e4TzAYkJIVaRv3O0fy m9c5SzoN+k1Bp/WlZA2nNHKGV5L6jp/hOGPAvoLBAMb6Dak9KATfYJ+tSV3sya53IXWd4YmFVSgn udDzKe1D6Aeg34U+Ci73LpC+9a8TPcHvJN6/2m898R5I29aQfwG40nvEpd7hX8QcT3Ei+YXLuU/v RVroxu4Lmd2p0xjT01jT5L7+Sp6NpO4Fn/AuR9uRWmaBV6TaOLwh9bBL3SVtC271zpE83ONQ8pz0 /iIyLL4Xc62sWqYdtYwmtTO1fOv/yOE11EvtTqoFv+Dam1NvSkuk/HCZ3GkwntRlcndO95CxPoPS ThHj8SjldKGvtkr/uF66QPYO7WdWzs/93o7/fipP7GLB4EtB1885Dm9Pnek4LzOC2ZS8N/W1wwTt L0/5yJtrWzAqdbUnFrTkuTyV5bCfjKzb650UBWfXPoONLK39xL+e/pecw6XfzNu05xcyj8J60B/6 /ZExuetXud+X2dEGst+h7aQNE07sC+HE0KZi6ufvQozEL0VLifCTW/U0dhFOiDcsZPevh7WYRmoa 0YYW68NOQsP5FTQxMFbPfNuhCWi0wHGZoTH0jRgevBief4NlZDhn99+nhBvQTDjbjdKw5tBCowbC j/BoxfQsYzv6Brp6hHUW64R9qpGNy7hWTweup2TO9GOcIIRca4musT8FVXu/BGvoNOi76AH1uakF +iJr42OUTCRDSC9ZIhZieubCtRH6Z8Spiv8W94jHzN/PtWpXLqEWzqH8BXBeA7Gt/A+4yoA+tWPD BujtwXPgR6x76Mw+rQqwkvyfg7vU/gIfIifncf5DcFpIy/0xYr0aRtbgWzZ6lqcxACdpYSvarPUu BGlb8DqpOjqMiNHIaj1H4+wjwlMdaYwxdxpT77F6a9XyJc4kwksZIi0x7iim5++PUstY1avp/6No 0fSVm4kRa7Lgy8iYenS/IudLyIyekW1FNohbCGPQWDH2Ba7dBR4Esapi2IwxfMLhUfj74ONtjuFB jfaS2p/SOKOPNaHeL8lP9I7FOrZtyLOC/Bp3/ahq0fC700J0/uCPXPsh+DtwEPVymhMdID+ehIj4 ophKu9oCPvfLGUSoNvI0xk4jurFD7fnYTV+Qeim27VXM305wmI/BEjjbkL0v4WAjBz+ghAnQ3UjV GCHmmkXOLbLhP6U2ILXjPQjxJIQ/AntT7xqdU+CroNrFJ6n9uMot+SnfrASngMwdg/fJ/Jr8LSnz MFc1BxuAugrhoQra0sNVyM8zkt9/Eg5WT7Ba711s5wDPQ/A25dN+i40clMD5RO1irv2C0g7R8wvg WHaxNOg5ai2SvxZ6I3fUDlqllPsKdYU5g3I8wbR0UkuZuSdI3Q/nl+BsJGEDEtKYHlgumKY+kJvI fxB+BfnxIdgrQPxCETa7QcJ9fDtGT0zi2Msqgc2oZQJIVEzESZNlpbUtwfNp8xQQ71ZYAt+C9fWu wY/RnZCr4G7wGfjY9VZPrPT0QT1dj9G3I9R+h8NK5XPaHrFKRJz8hsT2hHreRFxcpNHgtDMYD+Ir iMgZdYTDfQU/pJ2K/cAr1Womv8bmaSRYBpypcDSacS0c7lEcYA4XUiZrUTCJcvCE2MtA1h+L5ESs DxGjY3neJMoGmdERflGrvsSEYD3mZj38sWnsXxEWeoT3KcJ7Y7kqhofE/sY7XXZ2dOlhQtdbL5GT 9ZrUnQ5Iai2pRGgYdrGIuIJoMDiBFYbVI0Y/xPASWH3KoJgSuoOdwIsEwyyQGt39OoxtE4weBe8C 1wmaKnAinBuh23PVTOgi8DLwEvB68GtwDvgg+UvBG8BeYBdQr6KdTm8UTjl0DjgOjgedKxicBnaF kwl2BkeCPwKrwUngF5QwAxwD3kwJfbkjbU8JSMvt5Vz1Jqlv00tDoblTezapR8F9lENPBr8ltQH0 GnAJuAh+Nqit0jxl0AnwQsrvQ54MMCIPqTYJToBDy0Ol74ZPz9vWIiExzv6saoMpORmMIf+Rng4z XpanLYK/Us5OOM3AcyizFr7e+2vwV4GHkcwh4CiQu452gLPI8yVS1A+aa2ODoV+i5OOUrBHCJ4lj /IxrHxZpj/RZmLV1fSiSfwFt1jtCZ7Oca4dopCGRJ84OlTL15Fpjh35JXS+CT1AaI+jsYsGt5G9M 6gk4jJFBzgOkyxyCXg+NzDhLXzgboZkdhjnrrEvhPwUuhnMHyBiZx0FG33wE0p7gK/BDkH4O0mkn UhpsJ+ertDMGvwK+tkSvYryclSQ4D6Sfg6YgK0agbWbWmy3gzyjtdpBIHjuirscEN5H/dfAh8B1Q 5wXzKHgF+l6Rq+A9OA/AWQD9PLUgLVFP2n86yIxL20Pqy9DITJrKGOtPFCcncu7WLqGZBTFKc5aR 0OS353s9PHmCQ9r8AV6IVXCITKvHmlxvkkhU2kKh05aJbyeN0/+0A+KfsWdyFXHIdhurJVaAT1SD j1fT16fziLIIiZSLsebHiH6JYfXEiAK1j0j5ERGqkcYwq82lT3uxH1k8xm6e9hArBpq9KaYR+G/Q e38Ad4O6Rp0BNgHpbfsrkJwxxiv2ttibETLgdnzBe+nna6FZc8xUkBXMsM4b8htW8sBA6zxdBiJF PrPGZy747As+M8L/GNT2qHyGcJjjPjPa/5QyC8EL4BwgJ1JhbwU7guwj5k+0FqmzmhNJM0h4dDUy wN4RsqcEyJthxjnbXJC7DshjdNVqSL3caajrPFFhMaynGDtmyG5usXRCjaUhqiemUTp4/t1qLCvV Lyh/Lqjzei/0LmgkPyTVsKoEtCHS2CqexQvbEvGLdzfkjCnGihcRbxPypFuMGmMqdXj2YpwyhBqh pOseu2GEVRKeSV0LQWZ3wNwJPuHemZtRPWjaYyrhqCTU0Es67rpTT2dWsq+lMe/q6QiO4CrWqIh9 PGwOzXrl9DopQdd2Tg1CYt2tPh1JXIpBgw2J9glY1QONfkdjsRpVrhGnWIUGvcVo1L2OAuMSauyT ntnhQ7P4lILfgOvhnAX9FFgG7gB3kqrercWC4SvQPwWngXeDk8Fq8FpwJjgXvA28DDwMHgPjlNkE X9Cz4DrwaVKPQ9Mqt0IWoC0UsFYUsNIK9gEvAbVtg2jzfWB/8Ev4m8Ft1OhBP0/qeeBLcPAQBj8H 54FfgRtBWhhoS5aBF4F4I4OVlNMT+g1wC7gW/BmpK6CngpPAEWA/8AZQ730Xd60+tHJoSjM/pP2l 8DdRpl67H1Qv3+XgELAx+dXr2Ba8GOwNjiKPjvKnoPbAIvAEHO2r3eDn4FH4jeo8mULT54H6Wv8I 5zOQlluucmuU4MPkYQW2tMd+DOdB6AywDaj92YzUDdAdoe8FJ4J/4e4Mqdrbv4Z+DVxCKqe0MY3q /IjIVT0VbaS2KqsETz3HNLKLc8aI+WL7EIGJpRypFcP5oCFO1T/A81/Ep6Xp0zHsd6HuUNcRPdtd nswySaK1nyb/Ns6vsf3tY8K3RHtGPN8R6rNC18DRODfa5hMx4mNN+3uxZ08jdpQ78vEh+Oof217n bZMI0kfBciJF0WkN0bCGuO7gLq4lUsJYOBG4C1wk5xHBTFpyhHvXNUdtUs4pDG2zL+Od6InN+wnR vDFq/JozhQelnJhGxxEd6uN/iOn6hk1t3mMs8KdZvB+ReoHYZQzPbtg34evTzXpurhGJu9VOhK+j zNNDoT5Bo3sB9Yaci6XhI41pCeo968616Db+WhmjCN04RA8JiN60Gus4kbtjHzSP029n0Ve/4H7L wPvAd8B64DfkmQD2A38Aai+dAA/IU4qmkhHBi+ITQRQjWjLS+BOeeApeJP9xSghoD2egbv3pLN48 8l9FnivBDmBXpKUaehDXngMSGW67wL+OOzofeg58v64E4W+hBH3Gh9SwYZ0m1gePscNIn7LXEjz6 k5b4V8CZD6oOSRS6/wb+AY1xVfuLeAzzLrNjKW1oTzv7cm0O9FU8z3gu8kY/WOIZTD5lPgKtO+aX kjPSyN75Qof6hAVn/cGz3AXPX4T6XAN+zoC5E+rvJxDlEjI3TYqna/dyX0TXByMon9ibUKOXH2a+ ELtl8P5FGml2jPbjJzT4Nn38rkGZyJuP18vHA2/19yXU09WN0ogydaO5WXR4vDFIaVDBehLISb3B 624pLdhHXcTEGn0G6n05lw/wdxki8/1v8Lvi5zfPc1/qs9V46Q7MAp1353CGciN9Xs796m996K8Q 3EWvqueE2Jj6aCkxfS6DaKUIj6L7v74/Lq3CC6669aZxXtNrbrr6Om/iuCtvGe8tkUjty8p7Zntu NU6lvDO8Bl7kneNle028Vs5SuMjr6vXzLvekbZd6V3rXeNd7N3u31uVt6MW8c73zHdXaa+O197p5 l3hDvYT8Uo03kt9evcWb7PGTJeRv5KV553nNvaZudyj1OnjdvTJvmFflGW+Id5V3rXeD90Pvx14z L7hk8OB+Xq/ySwdme8mK8v7Z3kxKEE2/npfuXeCd6cW9js4+6e3194Z7SS/wcrxyp/mO9SZ4E70p 5K7vZXgtXGmFXluvk9fTk7PP20g502vsUjO9C72z+MXYzt7Fbg4N9K7wql1r87zLvKu96/6Lve8A 06LI1j6nqrqqq7u/OEMahpzzEEQEJGdwiCIgIjDkzBAEJINIElERWURERBaVBWXVRZZgQEREFhER EbMiKgIiIiKL/6maVplZ75Vd7332//9n6Ye3prrr66o+dWJ99fWB0XALTA37TYAPxaAsFITqcC00 g5ZgdvT2BgcqQhcYAMMgm2K1aTA9q8aYLM4sehaTFtMslrRYMavPsLG8hsX6FltY7GCxh8V+WX3G 9OcjLI61OMnidItzLC7Myho+it9tca3FzRb3WvzA4lmDgvUbMXK4SLWYZrG4xbIWK1usYbHOgOw+ WaKBxTYWu1rsa3GExUkWFw4bPLCPWGZxlcV1Fp8YNmLccLHZ4naLOy3usbjf4iGLR4eNzBomPrJ4 3OJpi+csXqQm2Q6z6FqMWky1mGaxuMWyI6lwKlusYbGOxQYWm1lsY7HDyOx+I5yuFnta7DvKnB9k cYTFsRYnWZxucY7FhWNoXpy7LS6zuNLiGouPWXxizOARA5xnLG61+ILF3Rb3WTw4ZnjWKOeIxU8s nrR43qBkFoMxYzKqy/wWi1osa7GqxdoWGxDWkC0strPYyWI3i70s9iOsKYdYzLY4yeJMi/Mt3j1m 3KgxcrnFVRbXWlxvcZPFzWOJAnK7xZ0W91jcb/GQxaMWjVfCSH+k/RMlJ41QCkr/S38hRH4TXZJS SZrKJd3hkRybX7+o8NwvZ36t1ZWec8Jzv9w793WE2BWiIM2UIN2b8i/8/VOfv36VkbYr+9+UCAWv GLn9HLea3byxy6DdeQzW84DoFWOBK8YS/4D5rxjLXQGm/iZysl1FoOg/9Vc6/VXMUqs8VPgnSoSK v4mMLHTlf6JEsuq/jfmuCOuSlZ0DS8l/eAZ2wSE4BudQYi1shl2wH47F2bgE1+BTuBMP4id4lgmW ykqzWqwZ68L6sbFsNlvC1rCn2D52kVfkdXkb3oMP4ZP4fL6cP8a38D38CP+CXxCeSBMVRV3RRvQQ Q8B6qODmcBu/mLtO8Xbueuk89cw89a6X1YmTRTYo/KlO8Y2zPXddXd4f1b3iti6Ik/PTbJfNORtv EpbtwrJrWPbO/elknrulLM09mgITco82/WjuepFFeeqr89SfyX3/Invy1I/m7q/I+dyfL1o3Tz0P 9Ysezl0v1iJPfWme+rHc/ZUZf1mdNEjZ1Dz1Hrk/X3ZV7nqVUXnq2XnqY3PXq3axdfN2wWQOBarO ySmrRX9tHqttCsutYbkrLA/8Wuvq8bBMC8vSYZmR+6mrD8s9C9U35R5lzSBPvWie+uk89TN56mdz 12vJy3jY1N089Yp52lfOXa89NU99We5Zqr0l9/U+ebioz7nc9b5ennqe5+0bzX3/fnlmsX838w5q ouRAOE7xwglrhUxuFbB5UFBMEBOB5bQRU8RUMV1Ms21mgdnbPhfmmfVVfpDOMOIDqdeoZfphtVTd rZbQGYkbcAN1Z97yirgJNwGz73rl9h2qwr5D1cm5O8/g1XkNXtNmf3jVvjWRkbV12HfsPPueXWA/ UF3YjNTAdrGXKWo7wA4AZ2+yN2n8iFXpmfJT9JENK0iDfgAXMJVG5dK9U/V6YPph/SfCNXoD4SNE hTjZ3uJkHWy8op4Bjq/QuP9iy2VqM5WvUf1ZWy5TfwRGtXWEy9SjhMupT8P5aVBSbQBOz7tUbbTl MvUElUuo/qQtl13WclPY8s9hy6fClk+HLcPxqvttbw/Y3h60vf105SF75WF75ZHLr+i19hn/aJ9x nX3Gn648aq88Zq88bq8w4toX8UWaGfOGXbRv2GX2DbvcvudV2Pe8OvohvZqkyq7bWymvZXiGYk1G s7YAzK8hTN5yFBkiA5gcLUfT56er6fTE/3m373/e7fvr7/b9hZvSLDdVtZppocz8D8/8h2f+S55B PGy5JicmqmYzkPxuXrGc4VvOCCxnRCxnRC1nxCxnxC1nJCxnJC1npFjOSLWckc9yRn7LGQUsZxS0 nFHIckaa2Cg2Eq8Y/ki3/FHE8kdRyx/FLH8Ut/xRwvJHScsfpSx/lLb8UcbyR1nLH+Usf5S3/FHB 8kdFyx+VLH9UtvxRxfJHVcsf1Sx/ZFj+qG75o4blj5qWP2pZ/rjK8kdtyx9XW/6oY/njGssfdS1/ 1LP8Ud/yx7WWPxpY/mho+aOR5Y/Glj+aWP5oavmjmZ3X5nZeW9h5bWnntZWd19Z2Xk0emS1kK8xO ntl0TKMIaA5MJ69iLsyA+bCIrmyAjXC7zeE2z9qa+bCbjgU2h9tCm8PtDvgcvoA7UaADd+GD+DDc g+vwcVhmM9SssBlqHrAZalbaDDUP2gw1q2yGmodshprVNkPNwzZDzRqboeYRm6FmLUtn9eGPrAFr CLtZY9YY9rCmrCm8ypqzFrCXtWatYR9rx9rB39j17HrYz25gN8Dr7E7zeyvjqaBkL7OXUbG32Fvo sk/Zp6jZ1+xr9Mir+Q59m2ktMBlwMGIy4GDUZMDBmMmAg3GTAQcTJgMOJk0GHEwxGXAw1WTAwXz8 K5GG+ck/m4DNyC+bhs3FDDELW4q5Yi62MflxsK3Jj4PtTH4cvM7kx8FMkx8H25v8ONjB5MfBjiY/ DnYy+XGws8mPg13EfrEfrxcHxAHsKg6Kg3iDOCQOYTdxWBzG7iZ7DvYw2XPwRpM9B3ua7Dl4k8me g71M9hy82WTPwd4mew72MdlzsK/JnoNZJnsO9jPZc7C/WeLBASZ7Dg402XNwkKMdjYMd3/FxiBN1 ojjUiTtxHGay6uBwk1UHR5isOjjSZNXBUSarDo42WXUw22TVwTEmqw6ONVl1cJzJqoPjTVYdvMVk 1cEJJqsOTjRZdXCSyaqDt5qsOjjZZNXBKSarDk41WXVwmsmqg9NNVh2cYbLq4EyTVQdnOU2dizjb ueRcYg0kqRXWUAopWWOppWbNZCAD1lwmZSprYTLXsdbyGlmXtZFNZVPWTraULdl1JjsGy5SdZRfW XnaV3VlH+bh8nF0vN8iNrKt8W77Nusl35Dusu3xXvst6yNPyNLtRfiO/YT3VeDWe3aQmqEmsl5qi prI+xtdiWWqWmsX6qXlqPuuv/qr2sIHqNfUau0UdUofYBPW2eptNVO+od9gk9Z56j92qTrmD2WQ9 VK9i3+ln9Pe8isc9zkd7CS/Bs73CXmE+xqvlXcXHeou9u/h47x7vXj7BW+Gt4Ld6K72VfLL3iLeW T/HWeY/yad56bz2f4T3p/ZnP9J72nua3eVu8LXyOt817kd/uveTt4ou83d5evtg76Z3k93rfeN/w pX49/1p+n9/ab82X++39jvx+v7Pfha/0e/g9+Cq/t9+bP+T39/vz1f5AfyB/OHgxeIWvMVmN+OMm qxFfb7Ia8T+ZrEZ8g8lqxDearEb8ieDD4BR/MtI00pQ/Z+yG2b0DrUK7kRF6H7Xpf6efzyA8Q/9L 52ljPJQ14RmKPBzXvEnQ8RzPfFvoRIA5MSdm456UHB1mtcU0K/2rjHTCQSudzMolJ975HqWZYdxm Zhi3mxnGHWaG8Tkzw/g8zd4r+IKZH3zdzk87Mz9spnl6tss8GXvNPBk7Sr12tToTrM5EqzOZ1Znc 6kzX6kzP6kzf6szA6syI1ZlRqzPjVmcmrc5MtTqzkNV1RayuK2Z1XXGr60pYXVfK6rrSVteVsbqu rI3HyhktB+WNloMKRstBRaPloJLRclDZxodVjI6CqkY7kU264Fwkm0RyZAJqiXCVkSO42sgR1DVy BPWMHEF9I0fQ0MgRNDJyBE2MHEFTI0fQzMgRNDdyBC2NHEFbI0fQzkgK+R0kKeR3kKSQr2Giki5G UuB6IynQVe1Re6CbkRTobiQFehhJgRuNpEBPIylwk5EL6GXkAm42cgG9jVxAHyMXkGXkAvobuYBB Ri5gsJELGGLkAoYZuYARRi5gpJELyDZyAWOMXMBYIxdwq5ELmGLkAmYauYBZRi5gtpELuN3IBcw1 cgELjFzAHUYuYJGRC7jTyAUsttxb6zLPqLqJzcTfzDtVxevidYrN3hBvABNvijcp6n5LvGVjs38H x/4sVXyUHWkNGseddsUHoALFlJq8umrEmdXB7AmsCw2gADSClpBOfgJxHWTSUQ46Qk+K2XvRUQt6 Q3+4CgaSf1gPhsIY+sQ48iFawgPwCEn3OlgPN8IT8Bdq9yxsg0GwA16C4fAK7IGxsJeO8bCPjlvg dTgIE+AQvAuT4X06ZsOHcAxug+N0LIATdCyEk3COPI3zyGApFsfy5DlUwmrwGFbH6rARa2JdeALr YyPYjE2wNWzDdpgJL2EH7AC7sTP2glewN/aGN7EvDoRDOBiHwlEcjuPgfbwFZ8BxVofVgW9YPZqP s6w7y4JzbDKbjciWsWXkLWxkG9FnT7GnMWB/YX/BKHuWbcEY2862Y4LtZXsxyT5mH2MKO87IQ2Bf si8xP/uKncQC7Aw7g4W4wx1M4+k8HQvzErwkpvPSvDQW5WV5OSzGK/FKWII4QGNJ4YsENhQp4mps Ia4RDXGoaCz6Y7YYKIbjfWKkGI8rnaHOOFzr3OJMwCedSc6t+GdnqjMVn3ZmOovwGWexsxhfdJY4 S3Cns9RZji8565y/4h5nm3MK35P5ZDpLyKKyOCskS8pSLF2WkeVYUVlB1mYlZB1Zh1WT9WV9liEb yCasuuwhe7Dasqfsxa6WveVQVlcOlyPIwo6Sd7BW8k75GBsg35PH2Uz5hfyS3SG/kifZnfJr+TW7 S36rkN2tuOLsQUX/2CqlVYQ9pIqpGmytqqU6sC2qkxrK3lJ3qbvY1+p59QI7o46pz9hZ4mnOzpHS L8d9t4Lbm1d1+7r38gHufe55vty9oIvwi7qY7iOK6yw9RmTpcfo2MVbfru8Tt+k/6FViqX5dvy5W 6sP6bfGgfke/Ix7S7+r3xWr9of5YPKI/1V+IdfqEPiE2eKleqtjopXtFxBNeMa+Y2OSV8EqJP3tl vHLiGa+CV1U862V4GWKH193rLp7zent9xPNelpclXvT6ewPFTm+wN1S87A33ssUeb6w3Vuwn6cpH EdKTNkJ6mmKjzeQBC4qQtpHCfZ48YJcipF0UL79CHnBAEdI+iFKEdICswpvkAScpQjpCVsFkp8tv s9MVsDF1IRtTp9mVusL8LX6CYpqHxTdQU3zrNIHZFBVugQPk+x+FH8hODiEnL44lWS3eQnQjSa4L TUiaTSbZvjAEsmESaaH5cDcsh9XwGGyiaOAFks4DcAQ+Ivt0Bi4goMTAJ0vu/9Xf6j9vy23+C7bc 7r9oyx3+S1Rupb922XKr/7Itt/m7bbndf8WWO/xXqdxG7fbacqv/mi23+ftsud3/my13+K9TuZ3a HbDlVv8NW27zD9pyu/+mLXf4b1G5g9odtuVW/21bbvOP2HK7/44td/g7gdHVPYTbfJoZunKIcMfv oMi79sn/6r8XUub9kDIfhJT5MKTMRyFlPg4p8klIkU9DinwWUuR4SJHPQ4p8EVLky5AiX4UUORlS 5FRIkdMhRb4OKfJNSJGzIUW+DSlyLqTIdyFFyIOhVscsRU5Yipz5nRT5PqTIhZAiP4QUuRhS5O8h RX7MoUgAObwSYA5lApZDmYDnUCYQOZQJnBzKBDKHIoHKoUigcygSeDkUCfwcigRBDkWCSA5FglgO RYJ4DkWCRA5FgmQORYKUkCLnLUUuGU4JXEORIPr7KBLky6FIkD+HIkGBHIoEBXMoEhTKoUhQOKRI ekiRIiFFioYUKRZSpERIkZIhRUrl8EpQOqRMmZAyZUPKlAspUz6kTIWQIpVCilQOKVIlpEjVkCLV cigSpBqKBGmWIsUNpwQVfydFqocUqRFSpGZIkVohRa4KKXJ1SJE6IUWuCSlSN6RIvZAi14YUaRBS pGFIkUYhRRqHFGkaUqRZSJHmIUVahLzSMqRMq5AyrUPKtAkp0zakTIalSG1LkfqWIk0Mp5jvTMy4 7Xcm3aACfoZf4Fd4AX/AS/gj4xRkK+axCIuyBEuyfCw/m8/r82F8OB/BR/JRfDTP5mP4WD6Oj+e3 8Al8Ip/Eb+WT+RQ+lU9zpgfT6b4JPIbHyJp8jp+b34UgSS2eR5I6vIh/B4fRP1BMMAEuk0yCZnSA x3wWgM9iLA4RlsJSIcbmsXmQ4PV4PUjybnwopDjTnGlQLpgWTCPfjkEaeHwPf5Xv5a/xffxvfD9/ nR/gb5inpPFNs09p2qzkD/JV/CG+mj/M1/BH+Fr+x39o89/fx3jPBS/znmuab8UY2BZ7bP4B0yL9 sha1LrvGgDG7WYNGss5+n9bGfh9a65dvfPhjwEmxrDIlX0flo7a+2pRUX22+I4Mofzw8+3h4FoHR uF+jq6UhxlfwB/idfDG/i9/N7+FL+L18Kb+PL+N/4Mv5/fZbMUNjsM/E+Aa+EQL+NH+afGlGPnE6 b8qb85a8NW/HM3lH3pn35Vm8H+/PB/CBfBAfzIfwob827+ZZeBPz3nvejDczv0/gLej+rThxKW/L 24Lg1/HrwOEdeAeQvBPvBIrmsw+4xFnj6Plzem9Cn25Bn2pLrTtQq268O+/Bb+Q9+U28F7+Z9+Z9 fo0Tbe9NzRv7afTmXR4teUvqvTUn2aAnaUe9Z/JM6r0j70i9d+adqfe+xE2upcMvvTel3ltS7+2o 946/2vuv0MNEUTTu5tR7K+qR0dgzqcdO1Iuk0U6j+Drn/tTGtDDXzdUrlSl7/yb26VrY52prn6iD fRYjE3R/pyhbSFpLoYsaPfQxwAhGMYZxTGASUzAV82F+LIAFsRCmYWFMxyJYFItRfFICS2IpLI1l sCyWw/JYAStSvFIZq2BVrIYZFLXUoJilFl6FtfFqrIPXYF2sR/HLtdgAG2IjbExRTFNshs2xBbbE Vtga22Bbimmuw0xsT1FNR+xEUU0XvB674g3YDbtjD7wRe+JN2AtvpkinD8U5WdgP++MAHIiDKN4Z gkNxGEU8I3AkjsLRmI1jcCyOw/EU/0zAiTgJb8XJOAWn4jScjjNwJs7C2fgnPI1f41n8lvVj/dkA NpANYoPZEDaUDWPD2Qg2ko1io1k2G8PGsnFsPLuFTWAT2SR2K0VPU9hUNo1NZzPYTDaLzWYL2EX2 d3aJ/UgGHjnjnAuKiiQFBy7XFOj7POARHuUxHucJnuQpPJXn4/l5AV6QF+JpvDBFT0V4UV6MFzcR FC9FEVQZEz/x8rwCr0gxVGVehVfl1URr0Ua0Fe3EdSJTtBcdREfRSXQWXcT1oqu4QXQT3UUPcaPo KW4SvcTNorfoI/qKLNFP9BcDKMoaJAaLIWKoGCaGixEUb40So0W2GCPGinFivJgkZstn5F/kZvms 3CL/KrfKbXK73CGfk8/LF+SLcqd8Se6SL8vd8hW5R74q98rX5D75N7lfvi4PyDfkQfmmPCTfkofp OELHUTrek+/LD+SH8iP5sfxEfiqPyc/kcfm5iafkCRNPyVN0fC3P0HFWfivPye/kefm9vCB/kBfl 3+Ul+aMChYpRpCWUoySFWi5FWp7yVaAiKqpiKq4SKqlSVKrKp/KrAqqgKqTSKA4rrkqokqqUKq3K qLKqnCqvKqiKqpKqrKqoqqqaylDVVQ1Vk2K1q1RtdbWqo65RdVU9VV9dqxqohqqRaqyaqKaqmWqu WqiWqpVqrdqotqqduk5lqvaqg+pIEV5n1UVdr7qqG1Q31V31UDeqnuom1UvdrHqrPqqvylL9VH81 QA1Tw9UINVKNUqNVthqjxqpxqrBKV0VUUTVQDVKD1RA1VH2gPlQfqY/VJ+pTEyuq4+pz9YX6Up1Q X6mT7sfuJ+6n7jH3M/e4+7n7hfule8I96Z5yT7tfu2fcb9yz7rfuOfc79zyZR66FdrTUSrtaa0/7 OtARHdUxHdcJndQpOp/OrwvogrqQTtOFdbouosvp8rqCrqgr6cq6iq6qa+ia+ipdW1+t6+hrdF1d T9fX1+oGupFurlvolrqVbq3b6Hb6Op2p2+sOuqPupDvrLvp63VXfoLvrHvpG3VPfpHvpm3Vv3cdr 4DX0GnmNvSZeU6+Z19xr4bX0WnmtvTZeW6+dd52X6bX3OngdvU5eZ6+Ld73X1bvB60ZxaQ/vRq+n d5PXy7vZxKdeX4pP+1F0OsAb6A2i+HSIN9QbRhHqCG+kN8ob7WV7YyhSHeeN927xJngTvUnerd5k b4o31ZvmTfdmBD9GIIIRFuEREXEiMqIibkRH/EgQiUSam+g2Zw0L1+N6mIYn8RRMxzP4Dcy0q1qz 2Xw2Hx6xa1tr7drWEbu25YoZYgZqu7blmZVDfF6ukevwJbuStcdE/fi2G3HL4Um3utubabuedU3w YfAlmxJ8FZxic+161gKy0XPIdifJOygLrcgXnWx2JLlf2T0Z9JdO/XmXSBzyQ7quRvU/avLg1Dpd nfBRXevntg3pr3soVg7ofgWhKJTWjc0ZTd6dWqGbEq7UzQhX6bY/f6ab/Yv8B3redHJGSrKS5jdC rDR5JZUZ+dasGqtGvkFNVtN81UI+s/zp7lDZrL6R3ShI6KNvMUpq0belqSXCWsL4F/A5HYAP4UMm 4x4+Qi0ew8fNrpvfvGvr8D6t/4m7MmcQe/IfLN+/w+79m6ze/0vWjv39f9feybflO/JdeVp+o1Ks 3dtCFu95a4l2kVUR1sq9RhbO2LYcy3bkCm3a179hy/7RksXIhv1ivX6yDP+3WbFfLNUwsr2Jy60Z +Q7PWq/BeAzGX3hJ7lTDc/wFNZK8hX1yv0o1voLKJ98kLhxE3DfccNxPNo9NyG3v9FA9TA/XI/RI PUqP1tl6jJ6ip+pperqeoWfqWXq2vk3fqRfru/Td+h69RN+rl+r7ftVKfvU77GTqFVjKajpDV7f2 stavWsyGZDMb6ya6qW6Wy3a2/S+tZ7f/IfuZ23p2+5+wn3K7GvGbNrQBzALznoGFsIsijt2wB5rC XjgILeAQHIf28CU60Nda2CnsWtYAprJGrDlMZy1ZB5jDOrEusJh1ZTfBPexm1gfuZ1ksC1ba+P5B 9iL7DlaJwqIVvCkmionInQHOABTOIGcQOs4QZwhKZ4ozBZWJ/tF1LjiXUEsyJxiVTDoYk0p6mCID GcMCMiHTsbAsKkmvy/KyDmbIurIJNpatJcUmsp3MxLayg+yEmWTTB2NHOVSOxv5yDFn2YfJx+QSu lpvkU7hOjVcT8XF1q5qCG9U0NR03qZlqHj6lFqjFuFXtUa/iC+o1tR93qgPqKO423wPiG+oH8goO usXIK3jX7eb2xmPuEHcannJnuSuZ4652X2Ql3Jfd91lTfcG7lvX05nhz2Cq/nd+OPRScDi6w1cHF 4BL7U6RZpBl7wq4RMIrkonbn2wJ4OTzTOteZ3dBHzBPzxQKxUNwhFok7xWJxl7hb3COWiHvFUnGf WCb+IJaL+8UK8YBYKR4Uq8RDYjXehnPwdpyL83A+LsCFeAcuwjtxMd6Fd+M9uATvxaV4Hy7DP+By vB9X4AO4kt/BF/HpfAafyWfx2fw2Poffzufyeb/r3Hy+gC+06xsCTNaVWbAC0uxKRS2KcKdBbbtS 0cuuVPSmdnUh7V8Zu1mPsffOWatJu2yt5ipDTfKIhplvPFktk4uGXcPq0jmyl+QZka0EqU6rM+Cq s+o8+G7UjUHcTbipkHQbuA0hv9vYbQYF3ZZuW0gnjXUMSpC+OkH+GWkkqEAaSUMlo0WgGmmRBlDd 6A64inRHW7j6H8ZT246nGrvFrE3ReGrb8VxDnlp98lgFjWoqODSqGeCSBZ8N2o7Ns2OL2LEl7dhS 3fxuQRpVmlsUCttxFrfjLOm2dztCWbezewNUsKOtakdb3Y62th1tHdKdEahPmjMVGtqRN7cjb0na rSO0Jd3WDTLD72rNLy4+sCPPeZZz1t+Dn8+Yv8oT3waY/PkcI8+rMvz0Kx9zjkFBetarQ9oL+6yS nnUaKDsDvn3WiHpePQ9RiqeOQUydUhcgri66nKgeoacs7RZ3y0Ft8shvgAZud7c39CcLcgqGk604 D5PIQqTCTNL/ReBe0vqN4QGah26wmXRzH9hH9mkMHCKbdBu8R3boPjgWes31aUz9qO8SxveHJiaa g47mu2zo7H6sV8G+K25n1v74/1LrX+air6VoHTsXHS6bizq/zAV0IZ3+0zlGerziZXNRx+zcd4Ub ALjl3QzQbh/qx6yU8ZyR2DGUsL1nhKP8CTOtjkq38hxYX30N+erksZv1S+ohDYpTHFQZV1GL2fiw 2YtiWsECNGuyC/FRwjvMJ2CR1XFzyev/ZZ9NPzu+a+h8xO5kAfiCDhRTxVRgxiYAl4PlYBDyUfko OGqimkiSO0VNAaXmqXngeo94j4D21nnrwPO2edvA917yXqJ4yvxWK2efzHzb8zaydNJaujhZuv2Q Ah/RUZB44hgUQofsXZqoJjKgsN2jUsTuUSlO9ohBCelICSVlikyB0jK/zA9lZClZCsrKcrIclJPV ZAaUlzVlTahovsWGSna/SmW7U6WK3alS1e5UyZA3ypuglhwmR8PVZKEmwbVyvpwPzSkOXQMt7D6W lnYfSyu7a6WN3bXS1lvi3QvtvCe9TZBpd5J08HZ4z0FH7xVvL3S2e0hu8Ov59aCb395vD93tvpEe dq9IT6JCQHPckLVg19vZbkC2HFhzsuXIupAVN8vY66Aj8YbjSle5rqtdz/XdgPikglvRreRWdqu4 Vd1qbgbxTF83y+3n9ncHuAPdQe5g93v3gvuDe9H9u3vJ/VGDRl1UF9PFdQldUpfSpXUZXVb31Vm6 n+6vB+iBepAerIfosXqcHq9v0RP0RD1J36on6zn6dj1Xz9Pz9QK9UN+hF+ll+g96ub5fr9AP6JX6 QW24SxtrTBxM1pg4mKwxacXTpAUKkwdYhDRzd5L5KuSVjiGNN4VkviF5n/dRhG5tLEX/sy3/TceZ 4ZmZ4rbLzvw2ncxnZok5l30mTvH1y+J2dZfMVjOu6LcRdA/ZQra/bOf7CmiLT+LT+CxuwxdwF+7B fXgAD+ERXpO/w9/l7/MP+cf8U/4Z/5x/KdaItWKdeEysFxvEE2KTeEpsEe+JD8RH4hNxTBwXX4lT 4mtxTpwXFxwyKY50Upx8TgGnkFPYKeIUc0o4pZwyTjmnglPJqeJUc2o4tZzaTh2nrlPfaeA0Dg4E B4NDweHgSHD0Pzut/z/ZaR0F4WjHd6JO/Df2MxI/i/3igDgoDonDV7CfDMudFq/rdXqDfkpv0c/p XXqvPqAP6w/0MX1Cn9Hn9SVPeJ4X9/J76V5Jr7xX1avl1aUoqQVFRJ0o3ulFkc4QimrGUwQz05vr LSJtt9xb5a311nubvM3edm+nt8fb7x3yjnofecdJ2531LvjgSz/wk35Bv6hf2q/oZ/i1/fp+E7+V n+l38Xv4vf0B/jA/25/gT/Vn+/P9xf5Sf4W/2l/nb/Cf8rf4z/m7/H3+Qf+I/4F/zD/hn/HP+5cC EXhBPMgfpAclg/JB1aBWUDdoFLQI2gWdgm5Br6BfMCQYFYwPJgczg7nBomBJsDxYFawN1gebgs3B 9mBnsCfYT9JzNPgoOB6cDM4GFygKkxRzJSMFI0UjpSMVIxmR2pH6kSaRVpHMSJdIj0jvyIDIsEh2 ZEJkamR2ZH5kcWRpZEVkdeSxyBORZyJbIy9Edkf2RQ5GjkQ+iByLnIiciZyPXIqKqBeNR/NH06Ml o+WjVaO1onWjjaItou2inaLdor2i/aJDoqOi46OTozOjc6OLokuiy6Oromuj66Obopuj26M7o3ui +6OHokejH0WPR09Gz0YvxCAmY0EsGSsYKxorHasYy4jVjtWPNYm1imXGusR6xHrHBsSGxbJjE2JT Y7Nj82OLY0tjK2KrY+tiG2JPxbbEnovtiu2NHYgdjr0X+yT2Rex07FzsYpzF3Xg0nhpPixePl41X jteI14k3iDeLt4l3iHeN94z3jQ+Kj4iPjU+KT4/PiS+M3x1fFl8ZXxtfH98U3xzfHt8V3xs/ED8c fy/+SfyL+On4+filhEh4iXgifyI9UTJRPpGRqJ2on2iSaJXITHRJ9Ej0TgxIDEtkJyYkpiZmJ+Yn FieWJlYkVifWJTYknklsTbyQ2J3YlziUOJr4KHE8cTJxNnEhSYYkGU2mJtOSxZNlk5WTNZJ1ko2S LZLtkp2S3ZK9kv2SQ5KjkuOTk5Mzk3OTi5JLksuTq5Jrk+uTm5Kbk9uTu5J7kweSh5PvJY8lTyTP JM8nL6WIFC8lnlIwpWhK6ZSKKRkptVPqpzRJaZXS4f+0dy5wNabr319rtTofpHU+n9eqkFWRsyFJ jIhoGmLrIEkqSVENScqZ0lmSnA9jGkJShqhIchgMIWEcp8HQUI7v8/zWYw+zzWe/7//9//d+389n ez6f732t677u677uw7qf61msheXHCmAFscJYkaxYVgIrmZXGWsHKZOWxilibWTtZpawDrEpWNaue dYHVxLrNesR6xmpnvWMz2RZsWzaXLWYr2fZsJ3YPdl/2ILYneyR7LNufPZkdwg5nR7PnspPZaexV 7Cx2AbuYvZW9m72XXc4+wj7BrmefY19ht7DvsVvZz9jt7HccJseCY8vhcsQcNceRo+e4cfpzPDgj OD4cP04AJ4gTxonkxHISOCmcZZxMTgGnmLOVs5uzl1PBOcqp5TRwLnKuc37mPOI85bzgvOEyuGZc Gy6XK+WquY5cPdeN25/rzvXijuKO407gTuGGciO4MdwEbgp3GTeTW8At4W7n7uGWcSu4R7m13Abu Be4VbjP3Z+4j7lPuC+4bHoNnxrPhsXlCnpyn5Tnx3Hj9eR68ETwfnh8vgBfEC+NF8mJ5CbwU3jLe Gl4Or5BXwtvO28Mr41XwjvJqeQ28i7wmXgvvHq+V18Z7RTw2mfCt+HZ8Pl/KV/Md+S78vnx3/gi+ D9+PH8AP4ofzo/lx/CR+Kn8FP5Ofxy/ib+bv5JfyD/CP8Gv5DfwL/Cv8Zv7P/Ef8p/wX/DcChsBM YCNgC4QCuUAr6CpwEfQWDBR4CEYKxgkCBCGCCEGsIEGQLEgTrBBkCvIERYLNgp2CUsEBQaWgWnBS 0Ci4KGgStAjuCVoFzwSvhAyhmdBWyBWKhUqhvdBJ2EPYVzhI6CkcKRwrnCAMEoYJI4WxwgRhsjBN uEKYKcwTFgm3CncL9wrLhUeEtcIG4QXhFWGz8GfhI+FT4QvhGxFTZCVii8Qipche5CTqIeovchd5 iUaJ/ESTRSGicFG0KE6UJEoRLRGtEeWJikSbRTtFpaIDokpRteikqFF0UdQkahHdE7WKnonaRe/E TLGF2FbMFYvFSrG92EncQ9xXPEjsKR4pHiv2F08Wh4ojxXHi+eI08SpxjrhIvFm8U1wqPiCuFFeL T4obxRfFTeIW8T1xq/iZuF38TsKUWEhsJVyJWKKU2EucJD0kfSWDJF4SH4m/ZIokTBItmStJlqRJ VkgyJXmSIslmyU5JqeSApFJSLTkpaZRclDRJWiT3JK2SZ5J2yTspU2ohtZVypWKpUmovdZL2kPaV DpJ6SkdKx0r9pZOlIdJwabQ0TpokTZEuka6SZkkLpMXS7dJSabn0qPSk9Jz0irRFek/aKn0mbZe+ kzFlFjJbGVcmlill9jInWQ9ZX9kgmadspGyszF82WRYii5DFypJkqbIVsixZoWyzbLesTFYpq5ad lDXKLsqaZC2ye7JW2TNZu+ydnCm3kNvKuXKxXCm3lzvJe8j7ygfJPeUj5WPl/vLJ8hB5uDxaHidP kqfIl8hXybPkBfJi+Vb5bvleebn8iPyEvF5+Tn5Zfl1+W/5A/ljeJn+lIB5NFFYKOwVfIVWoFY4K vcJN0V/hrvBSjFKMU0xQTFGEKiIUMYq5ivmKVMUyxRpFjqJQUaLYrtijKFNUKk4oGhQXFdcVPyta FW2KN0qm0kppp+QrpUq10lGpV7op+yvdlV7KUcpxygnKKcowZbRyrjJZuUS5RpmnLFZuVe5W7lWW K48oTyjrleeUl5XXlbeVD5SPlW3KVyoa8ZBkpbJT8VVSlVrlqNKr3FT9Ve4qL5WPyl81RRWmilbN VSWrlqhWqbJUBapi1VbVbtVeVbnqiOqEql51TnVZdV11W/VA9VjVpnqjZqjN1DZqtlqolqu16q5q F3Vv9UC1h3qE2kftpw5QB6nD1JHqWHWCOlmdpl6hzlTnqYvUm9U71aXqA+pKdbX6pLpRfVHdpG5R 31O3qtvUbzRMjZWGrRFr1JquGhdNb81AjYdmhMZH46cJ0ARpwjUxmgRNimaZJlNToCnRbNfs0ZRp KjRHNbWaBs0FzRVNi+aB5qmmXUvTmmlttXytVKvWOmr1Wjdtf6271ks7SuunnawN1UZq47TztWna VdosbYG2WLtVu1u7V1uuPaI9oa3XntNe1l7X3tY+0D7WtmlfkQ+VOiudnY6vk+rUOkedXuem669z 13npRunG6SbopuhCdRG6GN1c3Xxdqm6Zbo0uR1eoK9Ft1+3RlekqdEd1tboG3QXdFV2z7mfdIzLr o38P7gcPgdVgLVgPNoIXyN+jIZ5BSFt70ITiIbAKbMJ3yUnZDL7NYGMGGzNKXwvWg40g2coCNhbQ WFCamwQtobeCNyt4s6I01WAtWA82gmRba9jYwEMntOoEuTPkzoikMzx0ht4O/u1Qa4e2dqi1g387 +LeDfzv6ZYKTYMmhWAWSfrjQcOGBCz0Xeh5kHmQ++uLDkg9LPvrioy8++uKjLz4x6yTJHoVoJUQr IVoJYS+GXgy9GHox9BJoJOhXgjlZRC8Fy8By8BhYA54Cz4Dnyd90IJ7bSNtt4GKK5WAleJVgOrym ozYdtemoTYfXdHhNh9d02C+FzVJolho0xLMa+fkQGXsdvNXBWx0s6xBjHbzVwVsd2dbEE7UrMaOr MNZVkNeg7RrEsAZt10CfAc8ZqM1A2wzUZsBzBjxnIKoM4jmVQWuGZRbFSpD0kw1NNjxkQ58NfQ6Y i15yYZMLm1z0kotectFLLnrJJeaYJNlXPlrlo1U+WuXDfh3066BfB/066AuhKUTvheQc0k1IS4Jl YDl4DKwBT4FnQGJtScLWETSjWA5WgqRXc8gW8G0BGwvYWFD6GvAUeAa8is9/y8EzoEFDzA3dGnob eLOBNxtKcwysAU+BZ0CybSfY2MJDZ7TCO5bOgsxCJCx4YEHPhn82atloy0YtG/7Z8M+GfzY59/S/ wZJHsRK8iX+3UAaWg5UgqRdAFkAWoi8hLIWwFKIvIfoSoi8h+hKSq02Q7FGMVmK0EqOVGPZS6KXQ S6GXQi+DRoZ+ZeScMNTkO5zRHXRlpBEcALqDHuAwA0kPhLyEoDc0vgZC7wu9PzQhYBgYDkYYCMsY yPEGQpMIOZf8hRZGJvn+Y2SRJxFBMqoDYC40+agtgeVpIxeCteSIGCfJ8RKs+fD+ZpyG5gxqL5OW RkzYv6f2XumHXWekApmkxgi73qgTaUljGrWC18Ab4E3wFngHd7FDlNVd8D74EPwF9Y2oN6NI+jLD CW0Gj2bwaAaPZvBoRnm0gq0VZDuK18AbIO40aGeHdnaGdkwLcoYIfk+SbEHI1ZBJH3yKpB53KCbu Vkw7SlMNmbQRU7yGuwAZ8SJoFhnh/De6DjaDLeBtnPPllNXP4D3wAfgI9WdQn06xCWf5McjXwWaw BSQ9plMe62C7HHIGxSbwOtgMtoBkuwxDO2ZvckUJlpIkWxDyMcikj1yKpH4QLAfBchClOQaZtFlH sQknJ85DUkOwCbwONoMt4G2cjeWU1c/gPfAB+Aj1mA+6BcUm7MpjkK+DzWALSHq0oDzawNYGMpti E3gdbAZbQLIdm5qPUIwyFKMMxShDMcpQ+BBSJPWRsIyEZSSlOQaZtJFSbMLZQq4gE/mBFWgH8gka kbkIkYcYyv1U+UH/Pd4jhnomvQn5ij1oAQ82JI3nkRrjIGgsqKwL2SZzJ7iHfPdANoNsBdkKsh1k O8gcyBzIfMh8yJbwTPSP95EhGuK9QGVqBq0hNrEhj2UeJ2iMTMgY+8KY2UDQCbGZGjJX6E2hN8X9 3JR5Eu/veoyaLJHPElqSp4kRZiNTM6cy1npERsqW8GWJXMySeQpjO034sMKMkrMEwsoGPXYiZCMi T62HrpNBh55sYWsLv7ao7Qy5s0GGZWdESs7AfqqsRWmI3I6KnEWRbM0xEL0SROwc+OKihosaQoZH sqwylOiVBxueQUYrHmLlM5HLknND8CT2TDW1h+oxGwKcTAK0FMILdjBNBFlEZbWkLEFOKEGtBH0s Qs5TB2aAueTfPJD5FXG3NZRlVPlBX4oz7BRxxzCUZM65DZnYUnhYSe4kEzWpMUXeSOSWlag1ZJLI mpk7wG/JMw5yOuQ6yHWQMyBnQM6CnAU5F3Iu5GXYtYuIGMjTzhAzkYdS2adBexWv1hnycezaVMxA KmbgW0SVBk0aNGnYqWmYayLfxnjJEhk51iSdXA2TAcg7l5Aza3QR87sUfSyDr2WY92XYqcuxenXY r3WYUXKWyJ2zErYr0e8q7I9V1M5ZZdChv9VosRozvRot1kBeY5BhuQbxkmMvo8oalKXUnBjiz6RI ts4yEL0SpNdhhklf2ajJRg2Rk2MeiVf0n2hkXk7W5aDnHFjnIMZc7NNcjDQXseRSseRirzBoeTgh 89AyH17yIRdALqAydFIuRG5eiNpC9LHM0BNs8pHprwMXMd8TfETOPhMrQdxNKpHrViIjrUSWSP5d mtCwO8jskpwZvP6gL8VdyFBvYtgvRCZ/Cpl2JbJlche3khqTS9BYUdkynhLI/UjwW/L+BNkCsg1k G8hsyGzIPMg8yELIQsjW8GxCzjaZXSMatmEvE6VBa4hNanj+IPcy3RRZPU5aOk5auh6xmRueOKA3 h94cObY5uTbkUwZGbWHYF0TEJ0Fi9UzNkGFbUk8apxAZKVvDlzVyaGsmnivIHU0+acCHrYGwskWP 5HlqRJLcW/TOBh16soOtHfwi1yLmkpRZBhmWLETKNuwilDUoS6mZKUNsHHjioDXPQPTKo5+CL5yl xLMGWcNHDd+wo0kdLASoExhkWAsQo5Dc0QRPgyexVwyxCA07mi5CliJCSzG8IGOkSyBLqKeQq3jO IJ8/ZKiVoQ9rQ0+wEeNpRgqaYEfXkZaM7ngmMDyXfPysIDZdCxaCRWAxmA2WgJvBrWAumE+SPF0I NkJTQf7bFNMKwp+hLKTKIqospspsqiyhys1USXg3Y5LRECwEi8BiMBssATeDZDRyRC9H9HJEL0fc csQtR9xyRCxHxErYK2GvhL0So1WilRKtlGilhH8l2iqptuQIldQIldQIldQIldQIldQIldQIldQI ldQI7TFCe4zQHiO0xwjtMUJ7jNAeI7RHBGpErEbEakSsRsRqRKxGxGpErKbsc8F8PIvWg+T6OMKP I/w4wo8jPDjCgyM8OKKtI9p2RW13iiXgZnArmAvmY0/Vg2QvrujFFb24ohdXROsKP67w4wo/rvDj Cj+u8OOK+XWl5teVml9Xan5dqfl1pebXlZpfV2p+Xan5DcT8BmJ+AzG/gZjfQMxvIOY3EPMbiAgG mGaC68D14AYwC9wIbgK3gDlgHlhAkjw7GLiDExpyDAPw2wpkuY4q11PlBqrMosqNVLmJKrdQZQ5V 5lFlAVEyGO6I1R2xuiNWd0TpjijdEaU74nNHfB6w94C9B+w9MDYPtPJAKw+08sDYPNDWg2pLjM0s h/RAcB24HtwAZoEbwU3gFjAHzAPJ2RmGGIYhhmGIYRhiGIYYhiGGYYhhGGIYRv5+K8Ht4A4wB8wD 4RMzPgwz7g3/3vDvDf/e8OwNz97w7A0P3vAwGvajYeML2RdtfdHWF7H5UrUbwU3gFnAbuB3cAeaA eSAZmy9i80Vs/vDvD//+8O8P//7w7w///vDvD//+8OYPb/7w5o/196f2kz+1n/yp/eRP7Sd/aj/5 U/vJn9pP/tR+8qf2kz+1n/yp/RSC+EIQXwjiC0F8IYgvBPGFIL4QxBeC+EIQXwjiC8FoQzDaEPgO oWINoWINoWINoWINoWINoWINoWINQawMsw7suA7suA7suA7suA7suA7suA7suA7EFIYxhGEMYRhD GKIPQ/RhiD4McYch7nDYh8M+HPbhGHM4WoWjVThahcN/ONqGU20LQDLecGqc4dQ4w6lxhlPjDKfG GU6NM5waZ7hhnOZSMg6C68D14AYwC9wIbgLJOCIQdwTijkDcEYg7AnFHIO4IxB1B2W8DtxN9RtBr EHkExhKBsUQYNFi/CKxfDHqIQQ8x6CEGvmPgOwa+Y+AhBh5iYR8Lm3jI8Wgbj7bxiC6eqt0IbgK3 gDlgHkhGEo9I4hFJIrwlwlsivCXCWyK8JcJbIrwlwlsivCXCWyK8JWKuE6k1SqTWKJFao0RqjRKp NUqk1iiRWqNEao2CsEZBWKMgrFEQ1igIaxSENQrCGgUhjg850FqqLKTKIqospspsqiyhys1UuRW9 xpJ3MIKFYBFYDGaDJeBm0JCjGPKStVRZSJVFVFlMldlUWUKVm6nS0Gsaek1Dr2noNQ29pqHXNPSa hl7TqDu34W69lioLqbKIKoupMpsqS6hyM1Uaes1Dr3noNQ+95qHXPPSah17z0Gsees3GJ9WrDUQu m0XK5tchZ4M51Ofb9SAprwePgbvBEtSWUPJlglsh7wRP4ZPt4wYiSz5JyhZyyMjXGfXUp+KnQFI+ D/4OtoCXUXuZki8RbILcjE/IGfD/xkBo6OglxFALGlGfpZ8CSdnwGbsTiIzfqBNqO1Ey0YsRCzIP T7j/+d22//xu239+t+1/6nfbzGh0w+/JMP7ZL918+B0aC+Ld3puR/NH3nUhNP8aiP75xRL9Ne8wQ M+QMJWHhSOhcGSGMMEY4I4IRQzy7J5oeNb1LfpP8c5fp608vwsunl/IfLzPZpxf5zfTPXo5/urqS 31v/5HL9x8vM/9OLGMtfXGZPP72IMX96hX/uMud8ehGz9OmVjOuP1zF/umKJK/4vrsTPXeZf/+ma 8afrmz9dqz+9aP8vfs+KTmumiWj9ae40L+IuMA7/w9+H/9tvPnFeL6OtoeXQCmklxKm/h1ZGq6Ad pdUSJ/wF2hUy88FvGfyfUvlfout/hX/xbSo5zdroInMJc4EJ3STcZKdpgul802UWWy12WByxID9z /+/+jhMN39Ki/r8wXghRkt/4Iv7wAvQpPH8Tc8c0r7SX1nTiHE3hDSdUQxl0urOl3tzEuIuNEUNo TNMHmlh0MaEz6Sm9GHRmsa9+jL7rRxpxiTRZTCwjeY2mBRG37ChiEacSt+OpxM2buPSKj5wx2V0G f2l/aL5LycldWuMf1t9d1LGhcltxip2zPoU5RZ9iNLKYSEQYDAunXZ2v+7wPWH/66IfWEiKUaOcu egcTo/FMS5ZySFT0vJjp08Ji5fbBDnLnPn16yb2nB8dEzY4KjZUPiYqJdnKW6sUGY86nNVExgbHT oyKdFXoZWW/E4v9RPzYqKlY+eE5sWFTM9Nh5einPWt9L39uF+OPqrHeZwLN2diFe9iSUxJ8J+nmY K8KJCYsx3teZpe9MvjBjWXwVODtseuS0WKIbW70NqTRlmY6dGjIzKjLkQ2AWfxWYSq8wBCb8uD5k qtx3+rRIwqvcZ8hgfQpdqbf++wLS6cY0oxR6Jxqht2Ck0Om0g/O+uTxp39A+23vsdm7q0PQcHn/0 tayobuisJ+c9H1xccXzGyLFBbfmM495Xhkd0Vw+c+kOj6qCl18EFc24Mrdq52sanRtPlWfF9a5Xs /GD1q6D8s4KhW9aOkOWf2dddeXxEt6SoqxxpvxV9bPvcqHJoC+3Xje7y/p3Oa+v+CHp64euKvcEL UjoCihemLl5V+qw8a9PZ3lt9FvN06aNu6F/QBrTVdgxYeCTt14g+25x6vChz+s7im6CMuaGFebOt 0757duK5/NBou5XBp7tedRkqeHx4RE4/H19+Y+iYeTu/TT/pN3BDis+SSOPvex5LVFeNDR2QP6qh y3zXyNRhJueLzo1IY0Sm0TYfTb/pS6S3NPqmha/0C1/qWcR0SjRMK72FiRmxdY2NTY2M9AtLSC2d ubBAvzA32Xbiuegn02OKVGPms/d6r3p/emPMv36/pXSiHaMt799/SefzA18Et94cpO9Exsii098z jfVGRKGXkAobJpfJbpA0xtGiJ373W9OJUQVjPJw2eQQ/1VuS1Z2YTOJtlPbRW8eI3BGJu/bMH6F9 1lg5KrbEXxfrOGdf2ttdI7Pm0rwf1v/Cvz69xqYk6TljSG19ekO7b0P1hiq/qKfBHjs8aI9zThZc EpdbbhBYZ/3UJP3W4Zsnv26dvXt1c59VA/LCK3vPvLDkO9Xbmw8vTzfPWFL17hbtcI/nL5M6bO2c jH9xyFnrPsN+1sHeq1tMrU9NCjtTlTx4Ruj2wwcPr+pR/8zINinh9wst7jcT3926tfvdi5uXrPdF X868M/pA75KkbhcHXOthGdSLsWFhuGrpi4Dg1aUTDvf5acqK8alC19/75RWnWJX8bfm+rgc3bjm9 q0l+4Ae9YLGcbe1YObZtcMtk/Z1M++npx6JvP9+2qzHZPSbOhjhjEogzJog6YwJNdAtxFpp9/D4y Js6Zf+O7mjxwehMnjYuLs0uPnj3JA0evdyZfupIv9QsX/Y/EZo2NQ2xdpvdon7EfzI3+wvyfnj1V MWVL74s3LK6LLZ8SYOQ2oPBtfkKBg6eydFu676+PPfvWTTS2/Gr7wXrjhh9Hxg+LXrzv7umb0+5v ehurWzttw0/LjDz0tS9PVZzqKzHz8xjNM7PuKBOE7VSLXxt/tfhhzShTRa9tvzR27X7A/YzCeNvl ez/af1UnSmh0cDM9UzS+4fBvyl+2qzZbO1S/Pnd8wsDgAXVdh1smzlv8dMmTWVVDJtzZtM/6+fjX mpbb8h/vF0zO2uLazX7BV6Lx4VYuHk9CI6Ke9i58wvi2YOONPFNbm/786bfnjfJktxxacW7OzMLd tMJu7r+PKZ/QNnfooodOSV0OTzojCLT/NmuIRU24+/v9Lns2OyibuQ9+pM6edv3C3z9/9vzxLlad n+04sur1XcWrWdJ8znlex4mty7B8kk7ku554I5sm49yQqJh8PTf58297D9JAxhyg76fvU9yruGea a1hsbHTf7t2DYyKcZn5YQ6fgqJndo2dMJ7Xdo2OiQuYEx87uPsSX2HhOhErv9SFCOp3ZX99X3/vD az0jrSvlMD4+/nMOp8Z85Cn2T28onD5DHM4GV0XcmT3zeP5PM62W9Kv1mp2gaex6u1fi+h4bqlSN R25eCZjXeQZrjJwefCjmpdmd2m/GOHLtL56/v87xLN/6AmtWhkOrX1XH5Rrr7t9N7TbTe6iDX0zq 6C8uhEsGB+2YF7DqaV38stMMe6f1dYVd7h5yNL/Rmnv7bsLKybZLfDfemDI6Pm/WlO0T+2T8uMtO Zvzw+NAdP1aPOfRd+fU3Jqm0tthN1943SIpVxqY/63pW564R7EyZonvwOrWL9Dzz9KqzKdY/bfce MmjOheYb8U+WBczolB6yuqziYMWuaeMUQ3eOCLs/bvJydsC0ua1rAoxsM8zWq+W5D27SOkfv6Ngb E31wz+3qDVwGcfqsJ06fxYbTxzbcMn/0UZpmV+drQ2X+CdNK/nwG/XtyHTd9H2c3vbO+R49e5NHT h3j5b8h1xk2fOXV2bODM6P/dXOd6r8jX3510HzGLf7LRa6Dv0Ve72BVdXQ7bjR57ctGvA12vDnfO tD+QEdIi80mtqP7y/ALj9idzjiyv235pz/To0Lm60AcHDj5ZfOjM451v7TZbfq106H520FU/pihu /8yQmSPGXbvxW/MPGxbVJd9cMJLRK+v3o0VmftKwYWeuHo0L6P7NAQ2zzG9iuDj4fXJS/8eXmBrv PvGxppOqA66k9eo655TNI2kf86S4d+sjIhNaWgeuzi2aZfM3x9H8oCkuRRcWjeqiDAgbury5e6qt z96O/cKVEY8161jtp21/WmzTlhI32602O6GkYYpJq3FpmuvB9qyJqYNT/RdnRZbKuno1RBUOaQl/ sEC7aobhvEmh2xMzov7ciWP2/0e2Y2tiTj1ZcOhkCkP76KCMejDqi9xDPXZ9mba6svDR7n6Dh9Se 0wv+3oDNYFpJLWi+tDnEU8gQ2uBPM6F/SKM+c0BleXd2rk7yOdx51cZAU7rNiuihK5/MHlf1hblx t/flY3wXi3/tk3Fwk59l84oD/UTnX+/edurg92MUoiiz6fNnGJUoPX+NKJuZpCz3/DH1+cpOR0yX uR37Zf7D6ElDN2ReaGi8serorR8czyS1ntrjcin90OngE27n+Yof4pr7FewTzS5SLLlSVmY3bkVb YfXUEQX22sIpyzr1q2NNnet1+Oy3i/qOLg3yb9Y/fNhHcmfps6Y+CztYihUhycEmzJxnBYwh3RM9 l1S8Z1yd2jGiuckodu0+40irhvXX7QOTvH7jFXZW9GaI03eb1OS4lN8dVOs7oGrH0uYHob1Wtilz ChtK48eN6Xs5xmOv6gVxQO0kDqjMv6dHWd2QHpn/+9KjfzgIkB7pe7n0JI4mF2ecUa6Gl87kS/3C ff+K9Ein1xheSiOHTI8Omxoj9/AdKh/qO6pvr8G9Xbq59e49uFsfzz4uzhq9yjAm8adj6uZLDkru OzUmbnrw1H96vGUvtJC788ckXM3+dd3b6+nnX9usZj3a2cveLu6dt8+uuFzHtcNadvhNZ9zNmu+9 +NqCWU/m0K4dHhLxOmr3rKddzidlNmbx1m+sqeh4Of9G4K1uemmhtlvcF/c8c1btubK015WGJ8/P Tjz+JqzlWcjqdQ+O23VsOpL65vLyRuMBVfQ4H51Re+pBbtrKKUcmOXTtf3bL27wJPSWjuUd7X5EG fjHAbZ8fmxOf3c/2Fa107e1JvXbpDgd39WIvHH8n4tGOLtkrl9jM30TbEq82zXOMNip3VK8paK4p UX75w8ivTeLHxQwpHRhyY22qmf+Bdw/Th5u77dvX7rpj/siSeQtcvnawKdr/e0v/oi9aPft9nE79 cSDYZy/5gdHvl6asim88O7063TZ//fvzn2RKnz0x/m8ypdjZ0cGB/y2Z0gdPsZ8/rD/J/0yOfu60 oj3e/eb2hSWh9Q53Jhw6Q0uZzwuoUX9td3j7yxk/pb9beXp/nEykfPHyVn3ZocF0Ya9vvXrlRL9q cN1mv6Lc8kAsy/7gvjm3HM1vLx99M++L3IM97BY+sr0huV4RcnaUT7+Ry94Kbmj2XMpJf/TlibtP OwbzJtF/+WrJN3EJd6Pepct3ry1cUfDD34TFHL26pWR+YIbEweH48DV9hyxa+rj50qIbo7v27Hd/ 8GD6TpqV5bPLw0WN7isTS593WznJ4daRlQsyOHFlU16zdTuj7ILd7f37Luu3fNDPB2saMr8Se/rN WH0609vPmFbfrh80dNRNwZKq322f3hDetJeWjXkW36K9c9h8od11ad9zQ51TmPnEiZXNoNP1C9P/ jY9snzxI/vFRV/HCE+TdiVo2cyNnq48/RyP6/eOVpbON/uNaDnFq/L0h05nY6rocVo3b1bMJN788 f81GlrbD5rnwmj7koyZWzn76ccWOyfY0b9p0WjAthhaFj+JCabE0OW0cbR4tmng1jdAHElIYbd5G bbL6L/dp7LzoqGkxgdFh87r/6VxiptBpyQte+8ybJKqR1VinFnc8nzjPnpb2tKlTZcWLmXvLHt+x lESGpX2Ven/dS7fmJ2Gyg6O9y+8lPXy8j73b/tRv7w8aS7w2Xl1UPvItr8fXC1/uUOtuKH48Nfnr vh2+o10cf/Go7yhQuXNMzj74LpjO+UZ2b6cbPzf34UWLigO0d4frjgw83+PRvuNjrfYuf1oeua6L 3dH2Qg+nMsXC9uaM/uEzS+23nBs3sdPhjecSD57eMevNi5k3+yZZdz2a0jZu8yrr0dXLXc86rxng 2O9vl/arz66YUdQxvdH6/cZ7npmqV1UDvnEyvd9/QO+pFc+2bq2ZFMt0fvutcvud8vgAn0CW5xHP Gl56UGvWzNS2yI0pDJk+hSH6Y41MnFMYVoTK7F++Gf98g/zktm1KbcbiSXr+xzvR8o+PfelEn3+v MXbuRNxeyTup3pm4p7q4TfiHjThrw/rwoNaLVT8NPK4d4VmaNMl2bNKfTidyi/j9uudclPSA/NaQ tnbpi1uek2Z/2UvqcH+8T3evQ6dH3spe1D788vNXiy8E/br/y7m5TKfLinLhyB/mxv325vtdDe1B NJ62rzDz98sbAoe31K/ZN3Fd/rSvJ41oU8WOH7I0Ub1u+9n47zbxvv9yfH4X4wRjK6uWoGfnBl21 ez3qRlVmaZ9D5u6q4ZvG7Xi7b/ygGTN+LLss2jtuZtvVLq/v3VnRa1Pr4O8fmzi3b/S+fWCtxmFg 6Bjf3QmD6YN/3bfNu/uR3+40xzuxj7yceDxxdbvgWUvltqlzVny33WnEb7d8/LhD46x6zvsxqNxt z3bHirh2ZxP3NQ61ybWmOarTEdwBg8+3PK15/JOx+6U5e1//L97VBdINCmVuZHN0cmVhbQ0KZW5k b2JqDQoyMjIgMCBvYmoNClsgMjI2IDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAw IDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAg MCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgNTE0IDAgNDE2IDUxNCA0NzggMzA1 IDAgMCAyMzAgMjM5IDAgMjMwIDc5MSA1MTQgNTEzIDUxNCAwIDM0MyAwIDMzNSA1MTQgMCAwIDQz MyA0NDddIA0KZW5kb2JqDQoyMjMgMCBvYmoNCjw8L0ZpbHRlci9GbGF0ZURlY29kZS9MZW5ndGgg Nzg1MTkvTGVuZ3RoMSAxNjY3MTY+Pg0Kc3RyZWFtDQp4nOx8CVxc1fX/ee/Nvu8zMDALAxNgIKxh CRAmbAlbgMAkQ1YIkM0kEAJxJaZWjeJu1Grcq61arJ1MtBK11Vo0v9a61l/sFpe6VSu1tq7RML/z 3pkhBHf//Xf5dO6dc7/nnnvudu55997HMsAAgBkTEbTWtNcvWhCRHAG2/24A+3m1VTUd7Gtvfhfg ChWAVFxb1VSdePYNYwCXDgFwVy+qqa3TJyVfD+xJ45g/uqi1pf3JM975HcC1JmDOMSxqD1Tpnun9 GFhXOkDjxS3tOfkfvX6wDoD5Dfba1bO1e6C4rPggQHo51i/p2Tnkum/XE4cAai8EEJvWD2zYevOb VXcC+LA/uXFD944BSAIP9t+L9XUbtpy6/rQVT5wL0HATgHX9xr7u3lfOn/ottr8Ky4s2okB9h6YG 81dgPnXj1qFTmrO4KQC2BMDLntQ3uG3hC/7XAXb/AXW8W/p7urlPIkqAdTIAxzNbu08ZSHhMfwmW 4fzAta17a9/DNRVPApwlAtD4B/p3DEV0gP1fWsOXDwz2Daz9eeRFgMLzAPQs8LYV3zB+6K43Stdq y9+DBGwWw/1/PuNXPD6ScvXA0cJjjylMsiRgQY5EAetJYAqYCcVNRwuPKrEcmH0wI3DX8DrajbAK xIKABR3kQBdaaVJPrXAiH3MplsrE14gLsEkHIfcUnMuCDFitmGVZkYIVvQRsxA93RrCOnK/Y3O5y CSO/icYgvYH1ouBGodGfiPX8TLF1zfHRME/Cf32QPAdL/9VjiId4+GcHUTK0fZN6XAc0fZP2uWeg +avUY7dHKr7JuP6dA3MYKr+W/puRsq/TjqQDKtHen9uHyA5Lvk7/ouTIhzGe/enXG/t0vbtg+zep 900Czn3g/7UN7uTIU9wVYP4HDCce4iEe4iEe/oMDey3c/68ew39a4ObBB//qMcRDPMRDPMRDPMRD PMRDPMRDPMRDPMRDPMRDPMRDPMRDPPwXBy5KScJfjAHcjTnk2JtABFdjPhF0KFEgp4YUaIZuWA+b YQAGYRhOhZsiEaGWGlxCWQ9sgi1YNgSnCGVM5D2AyAdwM3XGJCItifRE+7JE0yRwIKbGRsQ1cN9h dEwi42DSmdXMJqafGWZ2MiPM+cw+5h6QMG8Jeu9EWzkeGGCjf4HHwhcH5nhP38hqXxZqvpoag+OM zVTI42wxnZ4v8hci8bPmSx9lDv1/Ge0/MnD/0Nb+TX3QX7d2zepVK1d0BgMd7UvbWluWNDc1NtQv XlRXW1NdtdBfuaCivGx+aUlx0bycudlZ6d60VE+K02bS67RqpUIuk0rEIo5lIKvWU9flCnm7QiKv Z/HibD7v6UZB9wxBV8iForoTdUKuLkHNdaKmHzXXz9L0k6Z/WpPRucqhPDvLVetxhR6v8bjGmRVt QeQvqvF0ukKTAt8s8CKvkFFjxu3GGq5a28YaV4jpctWG6nZuHK3tqsH29isV1Z7qPkV2FuxXKJFV IhdK9wzsZ9IXMALDptfO38+CTM13G+LSart7Q61twdoau9vdKcigWmgrJKkOSYW2XJv4McMFrv1Z D41eOK6DdV0+Va+nt3tVMMR1Y6VRrnZ0dE9I7wtleGpCGae9YsMp94WyPDW1IZ8HG2tcOt0BExKn 6Tyu0fcAB++ZfOtESXdUIknTvQc8y09x2kxYHuMBx4YjxPm53fxYLhj3wzrMhHa3BSnvgnX2MPhz fJ0htosveShWYg7wJbtjJdPVuzxufqlqu6KfnRttod3rXNlZaH3hk4YfLHeFOG/Xup6NPHb3jXpq ashuHcGQvwYZf3d0rrX7c3NQv7sLJ7GJN0NbMJTjGQiZPFWkgAIXvwab2oNClWi1kKk6BF090Vqh nNoaflyu2tGuGhog35anLXgQCiIv7i902Q8UQCF08uMIWapxUby1o8He9SFnl70X/XO9K2h3h/yd aL5OT7Cvk18ljy6U8SJ25xZ6FGrh3GZpx5T5mUvTZK4ga+c6+dVCgasOE09VORbocLmELL+iVeWu IGOHmBr2EtXguRPawQyXVr2YL+L4qtWL7e5ON4UvGJI9OiZxWkg2oy0dCqbHRP187tBImx9Qhqu2 r2bGAE9oVBwdYLS1zx4ny9si2jHWkPHLuThWxKXhk4syFpsRRPwq2lwhaHUFPX2eTg/6kL81yM+N t7Wwvo3tnsa2FUFhtaNe0nFCjspLKBcCNxbHMmw1+mCdzx5bViG/SMhPZxfPKq6PFbtGZZ7G9lG+ cU+0QXDhE4STlnjruy8oMRTio1mHu5unrtvj0rnqRrvHI7vXje73+0cHars2zufb8NT3jnrag+V2 YaxLgyP20/iuDNDINHZUZWfh3lO138Oc17bfz5zXviJ4UAfgOq8jGGYZtrqrqnN/KpYFD7oA/IKU 5aW8kM+4+Azf0lLMyAR9+0E/wG6hVCQIhHzPOAOCTBaTMdAzzpJMF5OxKBORzC/I+ICLZNuIJsbt ttbVyy/PGZ0bR7s6+YcLLLiU+GFCjGcBhFjPgv0MK1GFFJ6+qpDSU8XLK3l5JcklvFyKjsFYGDQO vyeNdnlwn0KHCoKdIVfk+CZd45FIR9D9uH2y042utgppRTAk9+HeL05rQL1FPHWheFFod083Pw4I BPm60rT6nk5021iDqFIfkmML8mgLqFEn1OHdESv14NrgAgr1d2MmtLsz1OnjOw1u6hTcWReCxZ75 uOzUptjLd5TTOWrw5AvPJj4KirQ9PMhxbNAeJIkds9hZJxlJqsKR93iwqKfLhdYWQU87ujrtpQo7 SfpwSxR5+wRS2KOFwE+LS1OqFSH5XGwQPzyvnMs/kuI0aWcnDV7I7YkqYN+6kBJH5J1hymgFtA4W 1fNjwc8eHCqv+jO+mbZxWOo5BXcWftBCS1IsDqnT6rtx86f6SpR4SmKVZfweoYy2MUFSKT9zFdqd S+sYj9zmOdU9I2RnefjDgXdMsB9Ex4bO0dmC0EpfdpZstlQtiEdHZerPrkD2kqmnEYWwX86Ns6eF HQuc4+ypBKeEHUqEkwl2hh3zEYYJhkhlR9hRhjAYdpQjbCcYIOgPOyoQthFspQpbCE4KJy9E2Eyw KZxchbAxnFyNsIFgPUEfQS9BD1VYRxW6CbqobC3BmnBSLcJqglUEKwlWEHQSBAmWEywjCBB0ECwl aCNoJWghWBJOqkFoplwTQSNBA0E9wWKCRQR1BLUENWF7PUJ12N6AUEWwkMAftjciVBIsCNubECoI ygnKCOYTtBOUUpslBMXUWBHBPIJCarOAIJ/q5RHkEuQQzCXIpsayqLqP6mVSWQZBOsEc0vQSpFGF VAIP1UshTTeBi8BJ4CBIDicuQUgisIcTWxASCRIIbFRmJbCQ0ExgIjBSmYFAT0Id5bQEGhKqCVQE SgIFgTyc0IogCye0IUgJJARiAhGpcJRjCRgCEICJEEwRHBMqMJ9Q7mOCowQfEXxI8AHB+2FbO8J7 BO+GbR0Ifyf4G8E7BH8llbcJ/kLCSYK3CP5M8CapvEHwJ4LXqew1glcJXiF4mVT+SPASCV8keIHg eYIjYesyhD8Q/D5sXY7wO4LfkvA3BM+R8DDB/xI8S/BrUnmGck9T7imCJ0n4BMHjBL8ieIzgl6T5 C4L/IeEhgkcJHiGYCFtwX2J+HrZUIjxM8LOwZSXCQwQPEvyU4CcEDxDcT3Af1TtIME7Cewl+THAP wd0EBwjCBPupXojG8iPK3UXwQ1K5k2CM4AcEdxDcTvVuowrfJ+H3CG4luIXguwQ3E9xEcCPBDWHz OoTrCa4Lm3sQrg2bexH2hc19CNeEzesRrib4DsFVBFcSXEGwl+DysLkb4TJq81Jq8xJq82KCi6jp C6nCBQSjpHk+qZwXNgcQ9lBj51Jj5xCcTZrfplbOourfIthNcCbBLoIRgjMITic4LWzGPZk5lXo4 hZo+mWAn9TBMYxki2EH9DVL17QQDBP0E2wi2EmwhOImmspn620SwMWwuQthAsD5sOguhL2zifbc3 bDoToSds4uutI2F32ORH6CLhWhKuCZt2IawOm76NsCpsOgdhZdiIhzCzImx0IHQSBMNGBcJygmVh Ix7zTCBsxPOd6SBoJ1gaNuIxz7SFjXiwM60ELWEDP+olYUMdQjNBEwkbCRpIWE+wmGBR2IDnJlNH KrUkrCGoDusXIVSF9fxDuTCsDyL4w/pOhMqwfgXCAoKKsJ731nKCMoL5BKVhvQ+hJKzPQigO60sR igjmhfV8R4XUUQFBfljPWzCPIDes5w2ZQzCXxpJNkEVD8tGQMgkyaEjpBHNoEF6CNIJUAg9VSCFN Nw3JRYNwUn8OgmTSTCKwU/VEggQCG2laCSw0QDOBicZppI4MBHqqpyPQEmgI1KSiopwyrFuNoAjr 1iDIw7q1CDICKYGEQEyaItLkSMgSMATgjyBGUG8K8RjSJ0gfIx1F2UdY8UPkP0B6H+k9pHe165x/ R/qbtsf5jrbX+Vekt5H+gjSJ8reQ/oxlb2L+DaQ/Ib2O9BrKX0V6BfmXEf+I9BLqvYj5F5CeRzqC 9Aek3yP9TrPB+VvNRudvkJ5DOoz0vyh7FvHXSM8gPY35pxCfRHoC6XGkXyE9hvRLpF8g/Y/6JOch 9Rbno+pM5yOIE+os589R9jDyP1NvdfojD6k3Ox9Ub3L+VL3R+RMseUCd57wf6T6kg6rtznHVoPNe 1Q7nj1VDznuQ7kY6gPkw4n7UCSH9COkupB8i3Yk0hvQDpDuUu5y3K09z3qY81fl9xO8pz3Deqhxx 3oLy7yLdjHQT0o1INyBdj3Qd0rVI+5TZzmuQrlbc5vyO4nvOqxCvRLoCaS/S5YqNzssUZzkvVVzr vERxvfNixY3Oi1B+IdI5XJrzbK7E+W2mxHlWYHfgW2O7A2cGRgK7xkYCyhFGOWIfaRw5fWRs5Pcj foNEcUbgtMDpY6cFTg2cHDhl7OTAfez5sJ49z18e2Dk2HBANm4aHhrl3h5mxYaZmmMkdZlgY1g27 hjnVUGAwsGNsMACDrYO7B0ODorLQ4IuDLAwyivHIQwcG7Y46RP8Zg2pd3fZAf2BgrD+wbf3WwGYc 4KaSDYGNYxsC60t6A31jvYGeknWB7pKuwNqS1YE1Y6sDq0pWBFaOrQh0lgQDy1F/WUlHIDDWEWgv aQssHWsLtJQsCSxBeXNJY6BprDHQULI4UD+2OLCopC5Qi5OHJF2SK4nT8QNYkoQjwXffqly73/6i /a92EdhD9ofsnEGb6ExkM7QJTHVLAtOfcGbCJQmc1vakjfXbMrLqtNYnrS9Y37aKjH5rxtw6sOgs Lgtn5udmae6oE7CyhjBvnjDXZovHW6c1M1qz08zWOs0M6F/U/1XPmR/UPaljtVpGq41oWb8W1bUa p4blk4iG82vyiuu0aqea5ZOImrP41SjhW5yjau2o0yqdSjZQqWxRsn5lZXWdX5mdWwcc42IY/jcd LoaT8aNgzM46fK4PWBgxg+f5/o52n69xXBpZ2hiSta4MMeeF0tr51N+2IiQ5D9+6V6wM7meYizv3 M2x1R8jE/7RIyJ9z0UVQldwYSm4Phm5K7mwM7UbGzzMRZCB5vwWqOn1rdgzv8PmG1mCyZseQT/hg jhnmcz5eyH92DGGej8NCHnxfGEgNYe0ODEMx4dAX1/qPDcy/egD/5sG2dg3/iyPpDQBTe0/4HVYr bIYdsBvjuXAR7IUH4fewDr6N3DVwE3wf7oAQ/Ax+Ac/9435thmM4VbwVVNy9IAEjQORoZHLq+0jj Ys0MyV7MGUWu45KILvKXWbK/TO2N6KbGJQZQCHXV7DMo/TtzLHKUreTzkSI+z+5BXivUeEd6w9SP pm47YTgN0AQdEIBlsBw6oQWWILVCGzTDalgr/M6uF/pgPWyAjbAJ7XUSbIGtsA1pPfTDAGyHQbTh EAzDTuSHohLKnwKnwmkwEsXT4QzkT8X0NIHbBWei5b81jWdN43HJt+EcpLMxPRf2wHlwPiKfnig7 MTcKF8CFuJ4XwyXT/CWfKeX5S+FKpMvgclz1K5C/Gtd+H1wL1wnSvXAVfEfI3QjfxfKrTtDly47r Xw83oNZNcDNq3oLec9ssXV7zRngAfoI+9Sj8FL3tQeQehoPIPwwvwIvwCrwOf4I3GB9TxCyCv8G7 8CRan/+NKm/zASHlf4O6YdriJ6NtY5bdhRY70Q47o2Vkz7MEO8XKTkbNPbgaZ82oMyqsU6wtXjvW 1kx78XPiZ3RcRjPcOy05Pu8Ta5HeTJudaMF9guTE0tmWncnf/Lklt8D3kG7FlF+H2bkYdzs+4Tz9 AMbgTuQoPZ6PcT+Eu+BHuBfshwNwD/wY7oXx6fzdmDteHhYkMZ3Plt8H9wte8CA8JKz/z2FCkD2I 3MFo6YPRkvsE/mE4hLvQY/AreBweQd85JNBj8AT6x9PwDO5af4Dnox50WPAgD+ODp+BpkRd+I9Yw Yu4heJhdAqdg/jn2GlwJEL8CGv77jaZ2cL/D3YMDKZQJu0DLPdmWbIusfKGCmYR6kDK9wIKLuRBk wDC9foOITSuWcG12tX6gjWmrkbIdUHnk+SOrnz/yOOLjTM6RycOTumOHJw2lpTk5ebmM3q0XyKRh pVKJxJMyly0uLioqKMhfwM4rnMt6UjRI3nmFC9jiBVxBvoMVVElTkKIyL+V+98lKruWYhD3dWbtt SSrrtGtMKjHjEjutsoqWuUate156uj/HKVVIWLFMIsuYX5NSs2Z+4tQ9nFQpVbgslkSNWCRVyeSu BGOCRjRVJ9Yc/ZtY83G1aMvHV3B5hRuWFomvVshYkUTygN2aVlbnTvC5jFqjTqURGy0GidRoUHor Go5dILMmWqUKhVSlU8htNotMrpCodMdKgIGlkaOSCbTnfDhwHzvC7oKgj78XBYL+qiy3ST13rjEb FGaTK1uh0LkuyWZysxltNqPksrPn56jwaljYNjdbbQSFxZWtMpuyctzzNXZvmz2gC4gD6T5bJQaD tVRfUMnkFPgmmPz80oSctWtWr16t95XacvRocz1ToC/ADyZ5eFdN/sot5uV2pmk4YXmMHoY3v3cO 5+FiIlwafhWsxgImykrFv2YVJneCzWUQsy+xx1pkmekZKcxzyJNYL2YnRQabXdPr8iXrRPeL2Sqt Iy07aVBr04tFCVKVVCzGRLTh4ys1aq0KV+HqadltJodRrk5MT/qkk7vNPseukRuTzfxfD7VFJrmX uF+CF/31ovvYM9nd0zY+IE+WOcaZH93tneMtk40zd90LWi9j5Lx546zDbzWCvGxOslfCueszP0ps KPrQr2nmmgQbJDZPVk7ydmByJp9Fex6ZRPvpJvWlpbwNLV+hIm+9mHOTydB1RQX5FmvUfaVSrxdd XWQ2OVje9Yu5LFFqpilRh82qa1YPlrVuWmA15zRuvrCz88x8o8ibbrLrRMyvc7bWFC2vznPi9b3I V9zf1WBI0GtEUqX8B64mf2bJqqGKkouvuLC/enHlSp2Gk6mkb9XWFnScNLgty1Nb6qnYcnmQ/5uq JrTaMu4XMA/2zLJZUhLoefMkpxd+kO4UM2LF+zkNrvfTIUGXwCq4BNNRf1ozP9fE5mPPAtrGN1mJ DALaaqI0hzdQ0tetitbiH3LeTGQTC28StJbZpJHQZoC2c4i4ZVKNUaVx5DXO9/fU5zrUKzoXrl6Y qZPJRXK1rbxlVd7NN5rzlwxe1Z3esHBespRbYvC6LcmpjnmBLds2eDdsdmW4tBqV2+NISE023vrd isv2jp7kV1vciYaoL4lK8TaWBZWz7eJXuLMrU7BAnlLMmyfRnJLFzalDoVwGEk3uR0kN82f7AbpB JT6BZJeC/JE9mokJ3jwJX7nqp7xIFLUEPne0N0qZmBtZyIuyudRMc6JOzLoELypbXpZmllpyGzdf EPQ1LSg0r2cUJleCzYnP6NRhdKZ5gZo8l66qfqYr3e5urMxwFtbWNzjnX3rZBSdVGd1zE5gpqZp/ GNXSY+tqF+ct3bx929zuDeWbL1+OlmtGf7oen8K5UD7bcj/OzC+WiEA+zmr8co9e5eBMJk/OOKv2 m8Ej+WlxcaZDr1flP53ZoHrB74j6B5pAX8rvXznoVs/i2ZFjLcXnzyo8f8avUCvmUR6J5ARvYqUz n0a0XyFvPlbKa3DX+8979orNUnFPv399Y65cLhfJ1DJVRUdvfue5nVkJRctOvm5dx3Bjyh2tDQt7 m4v16zddFPCwr+Lpk+leYO/dbLQY1SpFUnKiXGU1qtLbz+hYeOXl565fkFnVVlxQmd3UV5KYXQ5M pGJqL5cnPgXP14tnPX0Gh955P/Mq7mV65lW/p758sb++zF9vsdT7y0SQqXp5ySJH+ctlzlTD4sVF L/tTW2ITn0BvOTZRidaasOI5myPs/brJ6T3L+OVVyWSi6EOIGxRZTOShTR830dhzSBuWMfZgFkTP aavFwuWxnESmkEjNSV6rryLLodT/QqkWSeRKjfSXY/r5Hdtqs0ulIhEnQi2pVK016zIrfMmqW3cr lHhIq9SKXQm68kB/tSU3wymRSMTFIr3ZasIzWpZY3FG6QqtX2qxmneKTOztOb5ujkYhVCpGRV+A4 DhXKuHy1QWa1WQzKkaWnt84Ry1USsQH9szJylHlbnINvShmw+USb353hNDlgnF3nVyqcDofJmSFK TdCOM4t+LPan1idEH8rnmyf1wnlw+NlJ/jBFm977Jbq8PaOnZfQeM+PsFB7dN8T6pExHstfAiiUG O3JpRnbqA/60tCU48bQ8wAgHJ7KM6FdoUIXC6k1KSkuQyxPSPs6TKWUiESbc2XiHQU4lxT0sUja1 l2WFmZbBabNmasoty8OZdvtVijxnbq6poiyvqJwfvl8uLqr3fehPmHaK5yeFy0NBATrUkeNT/mp1 Pnvmn3agmB0+kejtGTh7EyOW6JLTHQ60yNQb2tymLQ0ZxeQtCpVUqlDhna5wTpLyQVZhdtusrs+y y9H3l5weyFbxnoGXNJtRxTKscW5DEffAcSsxgj+8I94OZlg0a5/XmUHpV+ClTCkS6+rEtKTCyic+ XpDPP0rKTxfihKOnfDETndRrx5eRUbBys7COIiYhtmriEhmNRxYdj/h13D9Xwm2zxlNak509t9Rq SXEvSVkJK7FzvMEoSlKU7Q369I/89Q0lc91WBViylSkrl9SUagoW1Bc0JTVFxyaMjj9vJ/CGmJMz gYeuviAfl2kC4VHkhEuh++u2NfNuWFQ0L7qHcl8gilpFGt0pCMwmiVS8geEXE40jYfvF0ryK/JO6 GvStLAl1EqZfKs4vL9hMwphJ72Hw/mcy27UiJkVbu2prafmy4kTOVLdqS0n1ihKbTDptZzYruTDR 31Rx0t5lU9uOCx3zEyrqTxRy56CHcPyV6c4UvEq5S1tyPE2Vmd6qYKGnJjW6SlwIV2k+nD5rlbx5 iYl2r0jDgZYxcVpNmvkjf1FDml0jStTmeWUuX72rSR41I1mR36n55cAlmF4Hy5fXEjZpydcwNReS Sbej/7loH0FrFlbM61/b+LnWrFmzvYK3IXsYZ33sieMmc863VDR+ockyqoO41y7Bu8DTaCUr5EDw RDsdxB3K6ZeDTWdjjZwtlb9JKVXJ7xkbMl72S4+f4tFr9yRvFMWni2ecVMfP8djVUdhcRNzTSaXB k7+zuuv8YKZ9/nKB68y8y5zXUlK+rrk0zWDJW1JS0c1z7I6GfZfsWlM8N7i7rWHfxWeuKc4J7l6R 31rs8NWv6x8uyW8tcfga1g0M4e764dQV3FM4t0y8IV4+ywfU7nlFKvU89Tyb2moDfmpJPquqaJ5b JM39yNtgVdtcIoO93tBS+uGMyQgLOylsMM9O5vD7rE64KOJ7Gz/7xK/ewAyrzJnhHzOdIWolzFss gpWeopthdsOCQkuAleNpY8WbIXOMFS6R6A6aarxENm3wJ/0QX6fnFA10NerdOVtq5uEriFvLnj3/ sisu2LLQ4PIlTrXG9jPRm/jigX4x5m5cmFm4/OQW3+LCpPIte5d/r642v2Pz4AA9Sezf0I4FsGX2 PTtdr082JEFykmqcsfl1/uwGQ5I+PXmOxJpSb53ecekJypnQF0SPpoOg+hL12febz9ubLDgynIda JjNaHaaUzmWL9C0nnsnRZ8VtrWxom6P3OKwSCXedyOpw2Q1ShbRs48XtU/2ffkRuzWgqTRFL5RIJ v5dsj7zNPiL6IdTC6CwLZBRl+Yp9VTL5QvnCYrnPl1tsLbZCbtXi4oXlsqyX5T530WLth373tAfg oTuZ/3hpKW7xj/M/ZDGURt1oYkK3h145jF+hdsw+Hu7z78zTtz52+tYn3BPZR1iJQqmRv9Ynkvhy 7enJFplMjvc5qcyVmWMtWVpiZ8Virm9EqZKojOpdPkZpEvZ8MeN7Tavg9srNFoteMaUwF+oLcuQK uVKrdjpsUqlGKbEVNBepkl0uDXNUbdSkuSyHpSq5SCRXSQ9b0I4DuNv8kXsA3zuGZ9kxRWmDvPL8 PE9qgg2UttS8BE95vlxcXO+oz/rQr2sWH3/fogMez/eJCdyK9cKN2foV6sw4B6ff8oumHUqw46y7 DpfFKAzJZpNdK2bdutrV/aU1q0sT5NL+6IGHFtkmkSjtPue8/q5GQwujjIkT0Joi/sdVd6Q0+tPT FnbOc9d62MKYdx17JrEk2ZGXaqrYcmWQuTgmxreNp/DUug4tlDP7PvgAeFgtJICSdfvVDKSqbHg/ wWhNu5/VoLqa9fg1fmtmfarK4Kg3NEliR5HgamiDHPqhnsEqvGnwRlN9pjLvWUYLvd/P4egy6C0q Zjgv72L8y6xwa7JYJFI2e0LCWeY4k1wGCXfV1KsStS3NkZyq5xTMzoMS1ujFEr2Uu4TRSFQWtx1v ipyaeWVqscaoEvM/1mN6pq6XKiUiscqgYR5gbkW5iJMopFMhphWBEymMGvQaM+7jt6BNcmHjrDcw j8mYcT+rA4AU5tgBm41/ceXNYJxb75GZkutNjZqWWWbAt/vjL1qqz9SLHtu4L07P3sh56UGin6It 4ITnycLdIhK7l2y8oGvqmMSQmJZg9xhY5btXsqwUnxi7Uy9lhtkFvR2LnKzSnGrPdnC3Kq2KlY88 9+a3pm6U4YMhVpk0TCnXrzJJlVo5x0k1imMpy+8++JNufjNS4fl8f+R99gzxGrz75kCZ32RWWjxK u8eSLvI5lGZQiHRi3ziz9G5Hs64uPWYcX2XlsSfw9ZvegXKELXf26wz32T+mvYPfMM2WRK2IvZNT 2VIT7SlGEfeCRKlVarI8iR6jVKzQKXSZ7uRUI04udopw96kNSjEuo+rjrZo5czwKrUamtWnV3vQ0 pU4p19lwJh9w67ml4mF815kD5QuVYGJ2gQOc6NRzcIvdBQowslq/XDlHnJC6SLdo5myOTOCr3OSR Sd2xI5OzpmKRzsqyv2XkepvBYFWLmMWM0ppizfWIptIZuS4RhaoZQu7c2PCZJ3lOp5vKmy0Rfst2 +79HZDrj8V8W3/38iH76qcglReOBT0fRln9afOmzo3hoRnzgeJRcIk05IV762VFWKMR7Pj/KO79R fPPLomJI8bd4jMf/9qhc/m8bD8RjPMZjPMZjPMZjPMZjPMZjPMZjPMZjPMZjPMZjPMZjPMbjPz8K v9Nm8JOC6Vx4CMTQwegYNvJ3THWRv/DfzyrwDiEdibzNf1trZArTfZH3MH00chjTQ1iajrVex1QX eQHTRIF3RF7ENB3EmI4IkkOgYoax7luYPoqSYaz7e2anINkpSHYKkhGh5RHk32XOxx4j/LfCRj7A 9NHIc5geirzPXIitKZl92O8rmOoib2CaKPCOyJuY8j3uw1pvY/po5BjzKGo+jalOSBOF1IG9PIqa z2G6DySY3oMjOYRjVmG6DxSYHop+13E2mwKxb9/tFVJOsJ5GyPE8CyouE2Lf+LyAE0V5ESRxiVFe DDauKspLUL4iykvhKLczyssgk3srysvBJRqI8gr2pum+lLBMdGmUV0Gm6LUor2avFuuivAa2SG+f /g7nfJkpyjMgldVFeRYk8jti39YMTvlVUV4EGvnNUV4MKvk9UV6C8p9FeSmMyJ+M8jIwKxRRXg46 RVOUVzCt030pwadYFeVVqL8nyquZJsV1UV4DRco/8d+QLZJH7Uw82Zl4sjPxZGfiyc7Ek52JJzsT T3YmnuxMPNmZeLIz8WRn4snOxJOdiSc73wEuyIdcjCXC9yRvgh4YhH7YgbQehlBWjdwgDAhpN0o2 IbcNnzsXLIQtGF2wFGX8f2gPYS0+14fYh9o7Me1FzWqstwV11qFsE2psEvS6kbZiW72C7jbM7UDZ NqGM6m/CEbiQuqP/eXwq5k5Gbgj74nWGscUhlPdhjh/zMNbuxfJtwv8ou4RxuoT/Vu7DFqhPXsOF c+wX+uwT/n+cn0u9MNf1KOkW/rt5UJiFS8BuYZZ8vzSPHizJElreKki2CC12o41IHutl6/8Rdybg UVV3wz93ZjJzM1kICoJE7YUAAkIICAqICBgkINgUheLSSiYLJGRrEta6xDFFtiKl7qWCtDWIC4hK VJSJCqgBMURIghmYKCTKEBGRxLiU+/7Omcmmed+Xfs/3fB/n+d31nPNfz3JT09BPpvJYblDLbJ5k KamBPqWdBe00kBJzlS0Bf7d4O6C7lJSDBwz12/BzlRfS1e9my9+UL1B30uKC1ngEfBaQYijds4N2 5SjfulTNNo3bWyS9tli1C1g9n/tYlQ/to3ml6i1L9bBE+WFBMPLt/S0jFrA/Vekv7Q/EJU9lgzwH JMpYG/SR22pNQMe5wTr53C0N9l6AFYEILWyNUpLKkSSeZnWwqyWbk9EkSclPDsqP7STrx/zCzkB8 WuI/pnXUjBSzglmUHsy3kfR4DW87th/SoX3nIyI1mNsBS5OCts1VbwO6pga9KfVPUVktbZmv4tnS pvO3af/R6G7LpEDcZnKXrnSQ8m9VlhR0iPHQoAY57SxIDo7JAmVlqsrzaTxJFgNU/AdSJ0X1P1lp FWhboP5/HMbQ41AiKUusGv8dNY9VvWdRp4C8k/rPVRbk0sMSnsropilb5Kjq2GvLczmzBCIwv7W/ 25XOgYxeojIxX2lYoMZcvpojAq0NZYMcr6kq29KVjICHXKpti/cm4b9pzJaBtnnt3gTGeorySdv4 XaRkJavx3ZncwL2sm0wWLVA+TGkdDynqvZxxAha0jIFcZWl2cBQE+kpVRzmqf263fB+YPQbQaqDK zizsSm0dz7/UKvsXPV+4j9p6b5nBjeAcHMie5A5z4S9tb8vXjnpd184D0pKALYEVoSXr81pXlxQ1 v2areTbpv7U04OekDj5NDWb/z8eA9KrMvAWqZYqaq6Q1qa39yJqZar77nyL0f2tctI2JocH/b5Wk 4CoVq2KVKxY/ZwyPixtlTE9PzsvJz0krMG7MycvNyUsqSM/JjjUmZGYaM9LnzivIN2ak5qfmLUxN ib0xKTPdlZdupOcbSUZWTkpqXraRn5Sdb/A+Pc1IS8pKz1xiLEovmGfkL3AVZKYaeTkLslPSs+fm GzlULUjNomV2ipGck5edmpcfa0wpMNJSkwoW5KXmG3mpSZlGegEykvMHG/lZSWiQnJTLtWyStSCz ID2XLrMXZKXmUTM/tUB1kG/k5uWgt1Sb3jMzcxYZ81DcSM/KTUouMNKzjQJpB5rRxMhMz0ZWTprh Sp+rOg4IKkhdXEDj9PmpsUbQzCvzjayk7CVG8gKMD+hdMA/5qYuMvCRsyUvHbBomZRkLcqUYepzL k/z0pVQvyMGghdKkJGNRUl5WQJZ0c/K8pDwUS82LbXX9mBaZ2CPtHyNDM3IWLsIoY2TsNcOD74cE 3rcLRCreRmgS0uamS61SUTMvKSU1KylvvpEj37S7Tes83MpJ2DYzO72A9rcWJBUELB5KBzlKQDKR LMhLT82PnbYgeUBS/kAjJdWYnJfD24KC3DFDhy5atCg2q6Xz2OScrKEFS3Jz5uYl5c5bMjS5IC0n uyA/WFVepyVhwHxZ7/acBTh6ibEgPxUlMEm+NpKIa2peVnqBVMi1RKk3aea0CbzNUzdEPWVBIL6L 5qUnz2vXlnN6dnLmghTpixwjJT0/NxMBMgK5eelUSKZWanZBrNEiOyeb9BiQPtBIzXLJRm1dZbdU 7lQjVV0mOO7Pxz3JgSxsla78GuzrOqXAgHSkMBCk6/PkcEnJWZSdmZPUXig6JwU0xfGtEchZUJC7 oAC3L0xPTpV15qVm5v7MoAuJhYrE0JTUtCSGVGxSfu5i+T2m/kpKT7Gs0/87KY0aofK/fBcO0xRd gt+c8leO5N+tmSdE63dc5//irY+Hh2vU0dZeaP2ICFW/+ULrd+ki61vmXGj9qChV/4MLrd+1q6xv jbvQ+hdfTP149feFdL79ZH35xd1N/m0gzSK6a1HC0HqJq7QrxCi8eKP2OzFDSxd3a8zb2gLxR22h WK3dKx7XVohN2mqxle/9N7XXxF5trzjIV7/XOlWcpPcm+jzfUY78q0KdyhmNnHjk3IacJOTkIuc+ 5DyMnKeQ8y/kbEfO28gpQ85h5NQi5yt6/5HerB3lWELayemBnBjkDEXOOORMRc5dyMlAzh+RsxI5 f0fOc8h5DTm7kVOOnGPI8SOnyTpVC7E+rnWjt8s7yrH2aSfnUuT0Q84w5ExAznTkzEFODnIeQM5f kPNP5GxDzlvI2YecKuTUIecb5PwbOeHIuYze+nWUY5vcTk40cgYgZyRybkLOrciZi5xFyFmJnL8h Zxty3kZOGXI+Rc4XyGnS9mpW7X0tCjkGcobR25iOckIeaCfncuRchZzRyJmNnDTkrELO35GzHTm7 kVODnJPI+U5brenaU9ol2mtaf+SMQM7NyJmHnKX0ViTHpR6q6c6kwqTCGZRHxaNiBcUeotntoxKW r12bKy9D4hIKC9fO0UM03a7rbc/tcQlnCgtznQ5Tt9n1sVFRUYZhlOoWTbeOF+PHjy8sLHTaTN0a JQKvWt6ND7yzh2p2550ipTC+cEWb2NyEhLVr1wa7X75ciVVPl6+tpY1Ns9tyVXOHTXPYxp+R13NU 9QTZMtdup5/4AXFxict1dZmQkJhojC/ULRbdFpAsCq02ix6SmLhRd2p62JzSpPG/GT9j/LrCRwqX U+x2ze4YG1+0/Il57awPtWuhDpvN1vYiaH6YwwzF/AuyP9SihQbs79wBUvLslPjly5ery1HxRUXL c/Xg06LlZzo4QLdp0qKgB2Sl+Ph4qRtm29s8YJceiMMDoRZLaNADAReESheEhmuhEQaVE+ckbpxi TDGmGkXji8Y77JpDHyvlPzHPEaI57NILuMHp0Jy40tbyimpSzebCwsURDtMZEnREe3NFUGa4DUcp X6i3RqnTqjmthtHiDodTc4TfXpg2Pp6yXIVCaYHp0iPqWnoElzgdwqEPHt6nz8T4xTSVCobMnqN6 CbVpoSGGcUb1OUc1ig/4xUEjx8S+A6IGJBQ51fXEeNyEAoVSExopVURhoc1mcdrxzUZnhOaMNHrG DUgckJiYuDZh7ZSolVHLjCKjg3sCPkD2cpJBC8M9HfyjB/0TqZthIQ5d18e1OkjKtRlGi4ciQkyn TdfbuSjMqoXZjHY+CtMcEXeVJhsTKTJOwUj9P/CRVKXFR0EnhSknhUVoYV2kk+KkkxKlk3ATTioy dIemh46bONHtLlpdQB7r+Gm8clS4roWHappmaX1LVX3sxIk/FRYWLe6im+Ftropq7wrR4orIEDOs xVlBb4VbtfBWb6khEqbpre5qcZhS6i7XxIkT8ZO6Gat0KFoc1vZm9+uyuZzxpM/UUA7RnHbDaA50 nasaTpT/lPJCV26TfgvTha5PmDCxT98BA+S4C7dawu2tWknPhVjCHXKyCu+ihUeNumLUFWOvyRyb Kf/tz9yftXrPE+/3fL9nqK6FOm9ITn7vvff2HlgY6tBC9ctcc0r5t3txRKgW4dQKZbGKG/i2Sxbv qbJXHOBLUlYOvSwtbe9PsnKU83yEXSu1sgGzi18VhouW0jNY4kStiLBpEbY4titz1D+kRNnNiJDw cCF6qn9x8l9tsFrcnNZqoRFaaJfs3PwnknsGyt44WZT22fnJ/Nu7d6+6uyJgy97F4e3e1XtlH3Ju zcwN9hhm18LscXE/BSXkqsbJgZ5wRKgI1YcVXq3+CF9PGMHH6l4RzuNQuY5JX/SnjBWjKHFijigV ESFahD1oA32K0tIQhyVCT0vbv3+5CO7OnGKTZbawJi/JyxTd5ualzhdjMpMKssU03mi3zphoIEyw m5W7MruIYEUO3GnCISJFd/U88MTCyt0F9S4R1ikMB9F3xq+nGyLuthk3G2JcsI7cH0eJHupO/q3C rq2920SYuEhcGrwLIUwXi14iOjk3P1f8Ux23qOM2ddyhjm+p47vz+cAWH6jjAXU8pI6fqmOtOtar Y4P8uhNn5VGzq2MvdYxVx4nqOEsdM7LmZ83X7lPHZeq4Rh0fU8en1fFZdXypdZf7vx21CzzqeNKK D+x4WBfyf734//fMQhwi/uNzpLhCxIoZ6qeJbrFObBLbxbuiQnwuzrKXC1WW6kFrG4T833CstOum /rqqRe0E1XlpfOD88C3t2pBvhzZ1vP/W0vH+3OCO99/17Hj//cYO91q4s+N95LMd76P6d7zvNVGE WtrdR9vbvbcLbchtHe+Hb+LsJKcHiETsiaSNG1fFWRLF/ZZ/WqrERuvfrX8Xh2wFtmfE4ZCj9nWa 1fmks1h7w/lR2GTtg/BZ4assN4Y/E37CsiRiS8Q2y9sReyIqLLsjEyJvsVR0ub7L9ZYjQsvbLG2z 54Wf7qxE6JQ+EYPbleHBondSxkYsbS2FlHWU9ZQKWSLFz0uEHumMHNylPljOtCtNskTd1WlJi3qr pXS1d+3ZWlYGS2knpYJS3W1cu5IQKOrNz0q3Wd0yW0te9yLKSlU2d1a6VnTf0f2DHoNUmd1pSeux trVs6bGttXwaLLWU+h4N7UqTevaz0tOgVn1Po+fCngsv/VIWedVzYS97r569ZvRa3Wtvr3JZAk/b Sq/6zoqSWd/rTKBEO9uK7Dk6SvVvSC6f2ntwa5nYe3ZryQ6WQspjvQv7JFBm9Hm9zwGuX+/zesy0 vjP6zVFlab9aSlP/Fyjbr5x35X0w78qiAVMHGrJcOW/guIGZFPfA1QPXDYqi9L9qNeXpqzZf9VKw lA9ZN3TU0B/iug3bQSkd/tRw7/Afrr4nWJZdvfbqp0ecoZwfmXjNpmt3yzJq1qhHVKkYHT56ZbBw x/3K0QfU3YHR1ZSVo89ft/y6HWMHjH9s/GMTBk/cPmpWoDbnA4Fa8a/LevF7J62ftGXS6zf1uWmj KmU3nVDl7GQx+ZLJxk1nubqFkjL5fEJ4QsYUG2XQlHPUK5vqmuqafAvHXHlFWTi18Gb7zX1VGTSt 27RelFHTxsEjlKem/TT9kunGdGPaU9MHTV87fS3PeXNLGtwz/ZJpo25p+rX4jWtG9W0Ztxu3D7p9 RNIB1wjXmy5vyzk5kvLEvHHzEtOfTd+WfjojKqNXRt+M4RmjMqZmZGYszCjMWJOxPmN7xlsZZRnV 8xfOf2L+S/ObM+2ZPTNjM0dl3pE5L3Nl5guZBzLPZNmzjKwxWeOzbsm6K2tp1vqsN7MOZR3L+jLr h2xbdv/suOwZ2Y9k782JyhnU2bOc+Jz7ctbmvJvjze2fOyd3U27DH/p39uwPs//wQ+fzUHAmalc6 ziR5RluRc0TerLYSmB1+PpY6joVAPnc6c7TMHu1Kx/Gft7qtyNGe91RbCYxzOQ92abr0yx6DmEv7 jD7AzKfmUXVmzox6K2I9Vji71EfoLfNe154Rfbqu7J0t24afjhRt81/QG0tVGxGstTTS2eIl+VTO p7KulNd1pXze4qmuPbkbzGzsjHRG9JG90WZdl3rOfVRpm+GH/2xmX982l7ebzZ1S71/M4E2/mMHT AvM2M7a9Za5W/Uir13ddGSnkbCRnN+JRzlWtnH8Cc0xgtmJmk5HKbo0es5a8a4shHpZ9NEQ71fMz vWcH+mQ+bTeHBubI1lmw0zkwMLsq+bODs97ElvmOp4N7z+5VzjX9D9sx1dV9c2A9UWfWjh5rWTE2 d9/RuiIEZ/qupd03t60KgcySa4yqvVnWoO3s7jvkG/WEWvJ519IIvSXbemzj3Ur6pr26Vk/b1rP2 K5rURa1eLetX2wq2I6hdxzUrLbhSbVGrVGBtGsR9QCZSbyrrXtTjU7SoDXo24F01fnq082W0MzBy pM8Cke2dLf3aO1va3KO227ge0vvl0v/txuDgXvVYVSuzoCUbZI8Bb1O3QdZjZUkIEFhb+iSo9aBd kWtLYF1RK9P/YVGrWbvSSY3XO5bgWtdaftlCrXH/UVGr4IWXl/7n8nNPydK6gv43Ra2pF1zUOn+B 5efeUbuDduWX/lO7hnZF5nEg0v9Z+WXP/7t2F1YCfpa7hkjntbsnrR9VEdFH7jdUmSWfXLtb7jHk 3ahZk9bL3UfgnSwjzo84L/crgadqtagOFNlm/GNqTyN3LwdGH1A7E7l7OUCLWewMegV3EJSpuWrf 0EvuLOS9Oss9hazzSKDIGrIOJfikV/3NfeUuhXG+cWqu3NHI3YwqZerJRrmbUXdlU3PlPBJ8R2FP tOWmE3Lno3ZCQu2BKGr/Y1M7JerKXU/bPuimstHVyuIKaet0I2DptbuDWnULaDj5FtW33FcJ2Veg 35+NtV9ErH2c+80J3Am7Vmq+YZ1urrLOFF2ss0W4Nc9837pLXMObCPOoFgnRZo12GZSaB3l7Uli4 8ltnmseFxvE7YeH4jnW2+YHoIp43fxK7zZ9ou4+2+2h7grYntDniYi1JTNFc4nItWfTRUkSENl9c RMsxtIy3Zpo7hEa/dcJG3XDqXkzdcOqGq/7rqHWaNhGml3699PsJ/X6i/V70pn5f6s+kfh/q96fv vvTdh97Wo+8xEcbVc9jX1XqPudZ6r/k77BttPW4+Zj0h4qx1YrD1CzHIetKstvr5qpTSKpD2mdCR VoW0qhYP8OZS3tjRdhU9V4lsLL5JRIH87yeuk//tg1khUiEN8k2fKDAbxAJYCItgMSzhW3ap+aH4 I9wD98J98KAYLYrgT7AMHoLlsAJWwipYDW+ISeJNaOY7+LwwhCkMTQj5J68MLV38RtsrorE23TpL XGe9Uzisd0OmWG69X/zK+gA8KC63bTA/tG2EZ6BCjLZ9AofgMFRCFVTDEfgUasALR8XokG5mRYjf /DCkUdhDmrj+Dn4wP7TjC/vVnK8XQ+3jOS80K+yLYDEsgftNn70QHjAb7G54UNjtRfAn80PHSBHt uAYyhOGYD1lwjxjtuBeKuMZ2B7Y7Huf6b7Ce6y3wgpjk2MEZXzi+hx959xP8Wxi6RYzWQzk/x5m6 +vOwU0SH3iGiVQ7Xk+9OlXX14lIy9xUy9xViPpeYzyXmM4j5DDIslgy7jQxbRobNJMNSyLApZNjU QF6ZI62zzDXW35pLyY1ryI1HyY051l3ms9bjYhj5ZbXWm2etJ8WdKrdqqHVUdG83Uh5G3sPIW4+8 9ciLQ94NyMtFXjzykpF3HfKuofUdyHoEWSXtZK2j/7fof6a4iF6/ptev6XUbvW6j1630upVeo+l1 IL1m0uvV9DqcXgfT6wCsOEbPqfS8j16vpsfNjMJo8zAtD/P2Q578VVxG36X0XUrfS+l7KTUWUGOB 8tDdjJA5aJ4k8ul/JP3PoP/rtXTTh4w47QnalZpvImcccpZhwTJkjcQCN72vsn5u/oQV56xfmk1Y Emv1m+fVaD+HpHNI+gpJXyHpYqQMRkoGUoYhZQJS+iFhIL0foqdDwsZs9iz5H0F0I3hyjlkqj7nj SfEgxyL4EyyDh2A5rICVsApWQ5nZLPbBfvgIDsDHUA4HoQI+gUNwGKrhqPm9OAY+qIXP4HM4bh4U J6AOzpqV4luzVpyDRmiC76DZ/Eh8b+4UP8CP8BP8G86bJ4TJ3ClAM0+oWfAO02u9i+vfc55jnrBV mKdtn8AhOAyVUAXVcAQ+hRrwwlH40my2nQQ/nIIG+ApOw9dwBr6Bs/AtnAN0sZ0H09wZcol50HGz 2exIhJkwC243ax13c54DqbxPg3RzpyPDPOGYD1mwkHf3mKcd98L9XLvhQSji3UOc8b0D3zv+wvU6 eJznT3H+G+f1PH+a6w2wEZ6BTfS/hecvcr2V6x1cv8n1XvDCUTgGPqg3v3d8AV/CSfDDKXRsgK/g NJwzKx2NQEwcxMRBTBzfAzFx/IgOP8G/wTQP6sKs1TVzp24xT+uh5gn9Oc7ooj9P7ljEGtFNrYpW scY8yVUZeV4uQriTc8Vi7uaS9e9ZPxaDhMbTJhFPZvrITB+Z6SMzfWSmj8z0kZk+MtNHZvrITB+1 /WRaM5nWTKY1k2nNZFozmdZMFjWQMU1kTBMZ00TGNLWsm9bfiRBrErjMz63J5udkjY+s8ZE1PrLG R9b4yBofWeMja3xkjY+s8ZE1PrLGRySbiGQTkWwiij6i6CNyTUTNR9R8RKuJSDURKR9R8RENH15v xuvNeL0Zrzfj9Wa82oBXG/BoEx5twqNNeNGHF5vwog8v+vCiT41Yr3DgywlqX3KP+UfW7ZnWcnGl 9SAr2CesfNK/chdyCAuPCxt3K7i7hbsR+He9mM16GsN6GsN6GsN6GsN6GsN6GsN6GsN6GsN6GsN6 GoOUcayp/VhT+zFeyxmv5YzXcsbrccbrUcbrUcbrUcbrUcbrUTxtMl69jFcv49XLePUyXr1omsaa O4oxWs0YPcYYrWaMHrO6RH8r+xLW4CLW4L6swb1Zgw3W3RjW3RjW3RjW3RjW3RjW3RjW3RjW3RjW 3RjW3RjW3RjW3RjGoZdx6GUcehmH5Yy7o4y3csZbOePNy3oZw3oZw1oZw1oZwxoZwzjxsk7GsE72 Y5x4WStjyP1ycr+c3C8n98vJ/ePk/nFy/yi5f5QomUTJJPe95Hs5+X6UfPeynsawlsawlsawlsaI MHy+Fp//gxn9A2b0g/j+AXz/GtHbRX5PslYwox8yz1sPi2QVr8+ofYJaJ1h318hZ2syg7X7avsZT N23XyB0bbafStol2d7BXWmNup+Y6alZT8xNqZlHrY5Ulz6me/sr7FWr9+q3KhyfVCMszD9DTRKXF YfZmsn6FWu+/VccmdgHR5resLN8Kp9ZFXKHdAZmQBTmQC3+APCiAleIK0Z1VqYJVqYK2X9D2C62U XfNMcwNyn0BCvdpnbRQDrDvFCOs78Dn73OPiVnab3dgN9GK32c/6Jdcn0c0voqynxAhxl/qtr7/B engaNsBGeAY2wT/gn/AveBaKYTM8B1vgeXgBXoSXYCtsg5dhO7wCr0Ipu+d3OL8L78Fu2APy983k b5t9AB9CGexjt3IHq/bvzTdtH5k1tgPwsVkT0p3dG/rY0cf+qVljP8qYHgADYRBcBcPMGsdwuJrr ETDS/MJxDYzl+noYx7vJZo1umA16b+gDMdAX+kF/uBLoV6dfnX51+tUHwxCIhaEQB8PgfvoqhBdg p/mFjm06tunYpn/Fs9NmQ+hkuN2sCb3D/EI4iOMR4nik5RuF2L1DzC7h66APu4g7RCi75ynW33O+ W0wRkWRINBkSTYZEkyHRZEg0GRJNhkSTIdFkSDQZEk1Lg5bzaWnQcr5qGUnLSFpG0jKSlpG0jKRl JC0jaRlJy0ha9qflQFr2p+XA/7jlyGDLkew07+S75m4xWIRgZw121mDnLuzchZ2vqv3vd3I3qr7z 9vN+P3l8MU/SyOPZ6utGjhG/WENm+slMP5npJzP9ZKafzPSTmX4y009m+slMP5npJzP9ZKafzPST mX4y009m+slMP5npJzP9ZKafzPSTmX4y009m+slMv/Ya+9ZS8zOy8wjZeYTsPEJ2HiE7j5Cdx8nO KrKziuysIjuryM4qbb/5jfYRHICPzW/I1nKytdy2x/zathfehw/gQyiDfbAfPjKryOYqsrmKbPaT zX6y2W/fbH5j32Z+bX8ZtsMr8Crs4vlHnA8Acsj6KrLeb//c/IbM95P5fjLfT+b7HYPNrx1DIBaG QhwMM6sYDVWMhiOMhiOMhuOMhuOMBj+j4QijocpxE31N5vw782tGhZ9R4WdU+BkVfkaFn1HhZ1T4 GRV+RoWfUeFnVPgZFX5GhZ9R4WdU+BkVfkaFn1Hh1zPpa7H5jb4E7jerGCFV+gM8Wwar4c+wGV7g +YvUeQm2wjbYaR5nFPkZRX5GkV8/zLOT1P2KuqfNI/rX3J8xvwkdZX7NyPIzsqoYWcdD7+RZGt8h zWTWZ2TWZ+o3SAfCILgKBsMQiIWhEAfDYDhcDSNgJFwD18IoGA1j4DoYC9fDOLgBxsMEmAg3QjxM gptgMiTAFJgKN8M0mA63wK/hXvM77T64HwrhAXDDg1AEf4Jl8BAsh7XwF1gHf4VH4FF4DB4H+buy f4P18DRsgI3wDGyCf8A/4V/wLBTDZmA107bA8/ACvAgvwVbYBi/DdngFXgVWHu0deBfeg92wR/62 LnwAH0IZ7IP9Zj0jpZ6RUs9IqWekuxnp9zJzOJgrrmPmkD8puM72uvmd7Q14E3bCW/A27AIPMG/Y 3oF34T3YDR+JcNsB+FiEh3QXzpCenC+FXhANl8HlItyOf+xPct7IGR/Y8QEjrt6+lXvk2JHDSKu3 f8i5DNDTXsm5CqrhCHxK+6O0q+X6M/jcrHcIEe641PzO0Qui4TKIgb7QD/rDlTBAOB0DYRBcBeSc g5xzkHMOcs4xlmfklYO8YjTWO8gdPQIioQtEQVe4CC6GbtAdegA269isY7OOzTo269isXwG/AkM4 9d7QB2KgL/SD/nAloJuObjq66eimD4YhEAtDIQ6GQZb5nV4Ai816RnW9fj99FwL5p2+Af3H9ArzI u5dgK2yD92i7G/bAXt4f5tkx6vsAX+r4Uv+K56fha96dgW/M70IZb6ETOE8WzlDGSuhvub6d851m vVpb/IxwP5loJaOWk1Gb1NOvePoVK85BVhz5U8OP1NPjPD0erLuCun8XNp6e4OmJlp+xiRBLgjmP b/hX2E93C/5E8lsx2MKMZhkB15oNlhs4J5gHLVPMfZabYbp5mB4/Y/avY/avcz5t7nNuhI9Mv/MA fAzlcBAq4BM4BIehEqqgGo7Ap1ADXmCGdx4DH9TCZ/A5HIcTUAf18AV8CSfBb/rD/8C6abHMZgeb x1fZpZYx5peWG2GFedyy0jzOeBvCWBvC24POJ80vnU/BetgEz5nHndtgO7wKO+BN83jYWvgLrIO/ wiPwKDwGj/OlEoJnTuEV6Y19eEPuxmvFr5C9AdkbLHdCCmTBCrMaParlVxbyNyB/A/I3IH8D8quR X438auRXI78a+dXOXbzzwDvwPuwzN6BTNTpVo1M1OlWjUzU6VaNTNTpViwlEzU3U3OhWQ9Tc6NdI 1M4RtXPoeQBNatBE/mR1CPp2ZzYKwTtxzEYheCiOffwKuRchoueI6Dm0q0G7GrSrQbsatKtBuxoi 7SbSbiLtJtJuIu0m0m4i7SbSbiLtJtJuIu0m0m4i7SbSbiLtJtJuIu0m0m4i7SbSbiLtJtJuIu0m 0m4i7SbSbiLtJtJuIu0m0m48UIMHavBADR6owQM1eKAGD9TggRoywS1uxAsuvOAiFmV4wUU8yiwJ xGaFmYj1iVg/ia+XVXy9rMELU/HCJXjharxwCV64Gi8U44UHiVUZsSojVmXEqgxvJOKNRLyRiDcS 8UYi3kjEGy684cIbLrzhwhsuvOHCGy684cIbLrzhwhsuvOHCGy684cIbLrzhwhsuvOHCGy684cIb LrzhwhsuvOHCGy684cIbLrzhwhsuvOHCG4l4IxFvJOKNRLyRiDcS8UYi3kjEGy5hD371PYm1T2Ht LKxbiXVPqnGyB9/swS+V+KUSH1yE/Rfx9hFs34Pte7B9D7bvwfZKbK/E9kpsr8T2SmyvRIdKdKhE h0p0qESHSnSoRIdKdKhknKTzlTpd/ixSzS/d6P0bMcTyG/MkI/YEb0stGebblvmQCdlmVfAnb7uZ W3Y73zPfdu4x3w57xzwZ9i68B7thD+yF9+ED+BDKYB/sh4/gAHwM5XAQKuATOASHoRKq4Qh8CjXg haNwDHzmychfQyKgr/qi9SvdGxnfdYzvOsZ3HX4bht+GqfllF/OhB96B92GfWYfujejeiO6N6N6I 7o3o3ojujejeiO6N6N6I7o3o3ojujejeiO6N6N6I7o3o3ojujejeiO6N6N6I7o3o3ojujejeiO6N 6N6I7o3o3ojujejeiO6NxGG2eQRvl+HhD1p/jiMt2iqGYVEJ72t4/zXROEs0zhKNs9StpG5CcJTI uSIkOFeEkEdPEZ2zROcsFpZgYQkWlmBhCRaWYGEJFpZgYQkWlmBhCRaWYGEJFpZgYQkWlmBhCRaW YGEJFpZgYQkWlmBhCRaWYGEJFpZgYQkWlmBhCRaWYGEJFpZgYQkWloiRWFFMXMqIS5klXVxGbMrQ fjXZf5DsP4kVxVjRIzjWewTH+nZ88CxxKyNuZcStjLiVEbcyrCrGqmKsKsaqYqwqxqpirCrGqmKs KsaqYqwqxqpirCrGqmKsKsaqYqwqxqpirCrGqmKsKsaqYqwqxqpirCrGqmKsKsaqYqwqxqpirCrG qmKsKhYO4vITVqzCio+xohIrVqH1XrT+TIRh7y7s3YWtu7BL2tSDN8XYswt7dmHPLuzZhT27yIGF 5nnLIiji+s+cH5U/leHpaUsRma1xbGaeXGQ2c3XIskzYLA9Riy8Xy2Oii+UJ80fLk+aPYVvgeXgB XoSXYCtsg5dhO7wCr8JrsANK4HV4A96EnfAWvA27wAOl5o/otcistdxr1qPfZ5ZHzK8sj5vnxO2W PPNdSz4sJkuXwP1muaUQHgA3FIlLLMs4P2wes6w1qyx/gXXwV3iCOY75LCzBfDdsCkyFm2EaTIdb 4NeQCL+BGXAr3AYzYRb8FmbD7XAH3Al3we/g93A3zIEkViIXJEMKpEIazIV5gM5h6ByGzmEPQhH8 CdA97CFYDitgJayC1fBnWAMPwxbseB5egBfhJdgK2+Bl2A6vwKvwGuyAEngd3oA3YSe8BW/DLvBA qbmHaC/Ee8vMT/DiEctjfFNayIOzxL9J5UaD0KnxORFqIkJnLffJvBEGLY7Tola1yCVSHiLlsSxg 57gIzy/mvASWsiOTcb2PlvezdyqEB8ANRabJKuRhFfIg7ZxlDVFba/qIoo8o+oiij1yoIF8riaaX aHpZkTysSB5WJA8rkocVycOK5CHKHqLsIcoeouwhyh6i7CHKHqLsIcoeouwhyh6i7CHKHqLsIcoe ouwhyh6i7CHKHqLsIcoeouwhyh6i7CHKHqLcQJQbiHIDUW4gyg1EuYEoNxDlBqJ8iiifIsqniPIp onyKKJ8iyqeI8imifIoonyLKp4jyKaJ8iiifIsqniPIpVlUPq6qHVdXDquphVfWwqnpYVT2sqh6y wEsWeMkCL1ngJQu8ZIGXLPCSBV6ywEsWeMkCL1ngJQu8ZIGXLPCSBV6ywEsWeMkCL1ngJQu8ZIGX LPCKdCJYRwTriOA54r2TKMrIVRC5KiJ3msidJnKniZyMfyjxf5no+Yiez7KKuUKO3IfNfxDBWiJY SwRriWAtETxKBL8kT94lipVEsZIo+oiijyj6iKKPKPqIoo8o1hHFOqJYRxTriGIdUawjinVEsY4o 1hHFOqJYRxTriGIdUawjinVEsY4o/hdvdx5fZXnnffzOOSEJ4T7iVrdWrSva1l1bq1Vrd6vdxpHa 2qnV6YKO0z48WJdWiqUyFkrrUrcyVG11OiNdoO7FiGJAMBqI4ZDkwCEJgUByJ7lDIBzCej3vk2Jf nXk9fzx/PX98XvdZ7+u6vr/f9ft9rxhityh2i2K3KHaLYrcodotityh2i2K3KKWilIpSKkqpKKWi lIpSKkqpKKWilIpSKkqpKKWilIpSKkqpKHWIUocodYhShyh1iFKHKHWIUocotYhSiyi1iFKLKLWI UosotYhSiyi1iFKLKLWIUosotYhSiyi1iFLLuLK/egl1eBmL8Ape5avOFKWSKJVGd+Nd0UGiMCwK I6IwIgIlESj79xHqjlB3hLoj1B2h7gh1S9QtUbdE3RJ1S9QtUbdE3RJ1S9QtUbdE3RJ1S9QtUbdE 3RJ1S9QtUbdE3RJ1S9QtUbdE3RJ1S9QZoc4IdUaoM0KdEeqMUGeEOiNRlV0/oMfkMj/TW2aXZ+yq z0STrK3H2nr+VjumOYHeiR9jOu7ySfvHWvvK65RpPTKtR6b1yLQe2ZXIrsT6+6y/z/r7rL/P+vus v8/6e6y/x/p7rL/H+nusv8f6e6y/x/p7rL/H+nusv8f6e6y/x/p7rL/H+nusv8f6e6y/x/p7rL/H +nusv8f6e/4fakQi+xLZl8i+RPYlsi+RfYnsS2RfIvsS2ZfIvkT2JbIvkX2J7Evo20ffPvr20beP vn307aNvH337ZF8i+xLZl8i+RPYlsi+RfYnsS2RfIvsS2ZfIvkT2JbIvkX2J7EtkXyL7EtmXyL5E 9iWyLxn36uhp+64wNPrz7A+KVSpWqd3db3d30z6lfUrjlMYpjVMapzROaZzSOKVxSuOUximNUxqn NE5pnNI4pXFK45TGKY1TGqc0Tmmc0jilcUrj1BpTa0ytMbXG1BpTa0ytMbXG1BpTa0ytMbXG1BpT a0ytMbXG1BpTa0ytMbXG1BpTa0ytMY0OVPu2y8C9MnBvufuN7rCfee0eufqQT10X9orwXhHeK8J7 RXivCO8V4b0ivJd3u4WfUftl+fj9Wd4tyw+T5Qfpm+/s4KnRKZkfRUfpeiPePZ2K2/9/7NBR51d2 estGH5XXOBxlPdrp0U6r3RP9ozkWzbFIhxIdSmWfaDVj7L7U7kutKmfOB4n+BvNORX9I9IfsvNTO S+281M5L7by0duFoVhStq2hdResqWlfRuorWVbSuonUVratoXUXrKlpX0bqK1lW0rqJ1Fa2raF1F 6ypaV9G6itZVtK6idRXFpSQuJXEpiUtJXEriUhKXkriUK1Nq56R2TmrnpHZOauek48oxfXg0q4Zk 1ZCsGpJVQ7JqSFYNyaohWTUkq4Zk1ZCsGpJVQ7JqSFYNyaohWTUkq4Zk1ZCsGpJVQ7JqSFYNyaqh UX13UTGl70h0aOY555TF4fXMa7x1fbg1syz8V2abXrk93J/ZGZqycUiyuVDMjg992UNxGs712ufC H0b/W/3E6MDsl6N4/0/u+kXsSff+k0x9jXOv5+OWhB2ZpVim2i6XxW9yzys4ZSfJzGrXFvTI1d7o YKO2ZkrYgV1GiZzGq1GDI0Mpe1bYlD0b5+C8sDV7YVgR/y4Mx78PTfGf8azHz7k+H9bGL6DO88Wu 9SGNl2Ap3vBac9gRr0Ieq71f8NoarPO8HV3ukYRSPOj+21EKm+IdGPHaTs9DKOVyOCxsyh2OI3C0 58fgOI+Px8lhRe6c0Jr7MC7CV3ENvoZv4du4EQtCU25ZSHPmlWsMO3KrfHctOtAbWqPPUHQrRfup uZqaA9QcoOaO/Wrmqbliv5orqLmCigNUTKhYVnALBbdQcAv1tlFvG/W2UW4D5fopt4JyKyjXT7kV lMtTLk+5fsrlKbeVclspt5Vy/ZQboNwA5QYol6dcP+X6KTdAuQHKraDaBqptoNo2qm2j2AZKbaPU Nkpto9A2Cm2j0AYKbaHQFgptoVBCoYRCCYUSCiUU2kKhFRTaSqF+Cg1QaBuFtlFoG4WS6MTMvPDd zHOhTiYvpsx/UGYfRQYz7TK6J5qa6Q2Py+pvZIbD72T1J+XW69lsWJqtCg/K8CtkeIsMPzV7YJif PQiHenxs9L3sSeEaGX9q9vTw2ewZYarMP1vePZC9OEzLXhqu1YF+6Vy8wbm4/Ht+T2ZvCK+O/pbC eDMpx6vHbDYYeVBMNhu522iDRkuNlholzR7rdH2a67m4KrrQfrrIt+epdIvti3r7aFlYaS0l6zje nZrd5Q13We0u692l1V1azXWcu7S6Sz46wDeX++Ym33zetw7xrZXGX+ebr/pmwTc7fLPgmwXfPNA3 V/tmm5P3k8ap1yOWqMtLsVzmvclNr4C9IsPWy7D17jrGN7OyZ73sWS9z1suc9TJnvaxZL2tKsqYk a0oyZkTGjMiYERmzXqaMyJQRmbJeZNeLbClX/r27jLse4K61VlDO+HnW/qL5/AXLZexV1ne1vbrI Pf8+Kzs83+geMsQ96sNN5X3hVDCP8s/ZCfWhwSuNmbdFIe+e7SJwVVjpXiuj6400xyen2V+dPv2M EWcbcbZvDVBhNxV2+/ZqKpSo8Nc7rHZtQVtY4G4vyq6mTH9oyNYiDptpu5m2m7OH4XAcgWMpdkJ4 OXsiTgo92VO8dipOC120785eGFVnL/H80jAw+tOW8m+XfPWvP+2yTzspPUjpQfu0k9qD1C5Ru2Sf dlJkNtXLqsyhyhyqzLFXOym/m/K7Kb+b8iV7tdNe7RSB3SKwm3KzRWGQerPjwag63hY2x8PY7vHO qDpXEV7O1YbNuYNxCKwpdyzeC2vJneR6ss9NcD3F80+FhtzlYUHuCnwO3/H8JiwIg6Izx/7tFOnd uaLPr0M7OrEhLIjGydp1MrYt8+ZoJpxDsQ+N/tfKr5vN81EmfgGLsTrK6Fl/zdTNYtQvRv2+UaW+ 9apvvepb7//IwH469NOhXKf6rb1fbepVm3rVpV51qVdd6lWXetWl3v0Z2a/O9KozvepMb8W7K+4N cyvuw/34JR7Ag3gID4e5ZjRTJj0oi96SRTNl0czMy3JvERbLvyUc1lIsC/Nl07ZMs9fzoV0W3Zkp qF1rsBZFrEN7uDvT4dqFDdiIbmxGT3SNrHs2k3jch/5wT2bANcVgmJLZgiGPt2JbuEHda9IR2nSE NlXgavVvaWa39/Zgb3g5s881hLpsBTLIojJMyY5xrQpPyOx7suM8jsOVqsdqGX6lWnm3Wnl39uDw c9l+pWz/mmz/mmz/ml59X/ao8Kvsu733HhwbXZ09zvV4nBBusgtusgtuyZ7s+QSc4vun4n0efwCn hX9Qc29Rc38uqtNFdbqoTrdTLlN/H81+0OsfwvnhruyHXS/AhWF29iOuF+HicJvd9LXsRz2+1Geu Cg/t/621F+2se+TVUfLqKPX6efX6yar1YW71CTgRJ+FkTAhzax4Lc8deii+HufH80BAvwPM62gtY FGbaddtk2kyZNlOmzYyXeX85VmAlmtAcHRWvQh6rfX6t14pY53k7OnxvvecbXbvDz+PN6EUS7ov7 wq9009nxFs+HsBXbwpV26ZU67GxZPF0WT+dL7tNlZ8e7wl3xbuzxuRDus4NvymXCz3NZVIa77OYr +Zb7cgeEX+UO9NpBONhrh0AM7YbpdsN0u2F67kifP9pnj8Gx3nsvjvP68RDD3ImhTgW4UhefrQJ8 TQW4KXeq196H9+MDOA2n4wycibNwNs7FefggPhSm5M7HRzy+WBW5BB/1+OP4BD6JT4V7cp92/Qwu 8/5nXS8Pd6o0d6o0d+Y+7/kX3OOL+JLH/4Ar8Y+4ChO9/mVcja94/tXQxmm0cRptuX9yv6977Vp8 A9fhevyzz37L+9/Gd4w/yWs3eO0mj5eqasvCzFxjdFROrHNinRPr3Nuwr1WO6bkCjde6Fmm0Du3o 8LzTdb37bDBv+5mDacslnvehHwNhSnSSSnK7SvKiyrF51Ekv04OWhz37Xc0MFeBbKsDLdvcLdneb /r7dzl5gZ3fZvQ127Vq79fd26wq79T67tdFubbRT77Mbr7X7nrPL7rXLGuyyl+2sf7ez8nbOG3bM c3bMvXZM/f5/ezBz9Dcwr1PjFprZ87rlyoyzvBmuUOsWq3WLzXK7ivxHFblVRW4125fUuU265hN6 7+ZRD7Pa4xa0hWVW0ai27bCKgvq11gr63nGtVrGGc+22ihL32s29dqtBa9WOotpRNMO9Zlj+LdLF uuPK+D9DokM+oUM+oUOu1CGfsE832aebdMiV9upie3WTvbrQXl1ory7UIVfGDb73Jt5Gc2jVJVp1 iVb7dJNuuVK3XKljtOoYrfbpYt3yCft0sX1VtAeKcr4ov3dwsd1cbLcc3sHJdsvbHXJ2rRxdJkeX ydFl8nLHf3O413l+Pd5xut/x+Rt99ybXBeEJ+bVQx1ypE7XKlWVyZceo2/2xrtKkqzTJjbcovkdu vEzpNkrv0VWaqLyHynvkyNm6QbNu0CxP3hz1gCXv78BOXWgvRxWJd2VopvIbVC47yzflTEHO5OVM Sc6U5Exedc+r7nnVPS9/Tpc/iaqdV7Xz8qhRlW5UpRtV6Ua51KgyF1XkNlU4LzJ7VM8m1bN8Stsj OntEp0102kSlTdVsUjWbVM0mVbNJ1WwSgTaVskmlbFIdmyi/RyVsU/3yql9e9WtT/RpVv0aVr03l K6p8RVWuqMrlVbW8qpZX1fKqWqOq1qiqNapqRdUsr5rlVbNG1axRFcurYm2qWF4k31CRmlWkZhF9 QzTfUJVaVaVWladVlWlWZZpVlGYVpVlFaRbVJlFtEtUm1aRV5WgW1SZRbVIxmkX1DRHdo2o0qRZN qkWTatGkWjSpFk2qRaNK0ahS5FWKvEqRVykaVYq8StEs6k0qRLMK0axCNKsQzc7xPdFBIpGj9nB0 nh2ZyoXb7L65dt9cu69LTky1w0ri/jtxf1HcX7Sz+sW9IO7zxHyemM+zg1K7JhWTqWIy1Y5JxWWq HZLaFXPtirl2xVwxmWpXpHZFalfMtSvmyv4SzebRap7sL9FrHr0K9CrYBSWaFWR+iUYv0uhFGr1I o4LsL8n+Ep1epNOLNJon21PZPleml6z5RWusDz+V3d1W8IJn21ST7eExuat3WtmwZ91W1mNlPft/ XtCoZiRW1mhljWY3bHaNZtdodsNm12hWw2Y0bEY9ZtRjRj1mM2w2w2bTYzY9ZtNoFsNm0eNU1KWy bR91UO1Gai/XWBqmRmsy2rDRmozWZLTtRmsyWpPRthutiRYpLVKjbqdFauTtRm43cruR22mRGn27 0bcbvd3o7UZvMvp2o7dHterkb6w8b9UtRh424ma1r051blWdC2pg3Wh1rtp/zuzwyV5nySucJc/M Xh2dPapch3eK3un827Nd5TtGYzwrr67LswH3X+H+A1GGQyr/N+pz+PI2mdVP611hSA0eVteG1bVU XUvVtVTdGlazhtWo1N3aVfHtusMuez+rdtAnOtk9OrxT9rJb3GuhT2yi5lZqbvXJdZQsUrFIxaIx yv9ubL51/ZGiWyhapGiRouWfEhQpucUcFppDhzl0mEMHVcs/PdhK1a1U3UrRLRTdQtGtFN1qjgup WjTPhebZQd0t1N06qkWXtWasNRMdbp47zG3I3FJzS/fn1JBV9JnfkPkNmc+Q+QyZy5A57DCHHeZQ ru2p8VPjp8ZNjZsac8h45bqdjqqwhArLKbBcXe5Sl7uM30r51UYaUYe7rL782xGr/i66q8yv0vwq y/+eQW3qUpu6KLDc6EuMvsToS9SlLnWpS13qUpe61KUudajLyperQV1Wvlwt6TKbJWpJl1rSpZZ0 qSVdzsr6m5kMmEmPtW41g/v2//f+8jm5/K8OV+klbc7I7Tp9l+sG/aY/1FNrPrWeodYz1rDYvmij 2KNi3+JOm6j2KNUeta76/b+l1iyqnRxhGyUfpeSjIttJzUftlTZ7pU2EO62v3n5ps8ZOa+y0xk5R 7uTs2ji7Ni6ujeLPUPwZij9jH7WJeqeod1L/Geo/Y+31IvCotddbd6eod4rEM9G7qV+gfmH/T0Z2 jv5kJAr9IlAw434z7je7fmoXqF0wy34z7KdygcoFKheoXKBygcoFCheM1E/hAnUL1C1Qt0Ddghzb rh7vCu3lLIoqPPu1fCv/POC80B0d56w0yNds4ms26aIjuuiILjpSflcHbc1+VQy+zockTuqDfMh2 lMKIzjfC9w/qfq28/iBPsom3H9TtRnS7Ed1uhH8f5N8HdboRnW6EZyn/XLKVb9mk64zoOiO58r8s qzaDl8zgpf077zfu9pJPv+STL0UV5jIQXeAEXHICLjkBl5yAS07AJSfgkhNwyQm4xDukvEMP79DL OwzyDoO8Qy/v0M879PMO/Va7h2/o5Rt6+YZe3avHKjv5hH5ZtsZJrOQkVnISKzmJlZzESk5iJSex kpNYyUmsRImyF+jkBXp5gV6KdFJiDyU6KbFH/++lxB4eoJcH6OUBeimxhxJ79P5evb9Xz++lRKee 36/v9uq7vfpur57bO7reIZrEYYO1bLKWEWsZsZZN+3/+PTD6mc3Ru3jnfaJWErWSqJX2R2yViK36 u2iVRKv8k+NW0SmJTkl0yj8pLolKaTQiq1zXoqP8uw6jmXGEmHSKSaf7D7n/kPsPeafTGEX3Lrp3 0b2H3HvIvYti1un+Q+4/5P5D7j/k/kPi2GmMslvtNM6QcYaMMxRVWc1g9vxoTLwLu6MxuUocGY0p 139d5utWWP43zPUyYmF0JD066dFFhy4x3SimG8V0o3h2iWeXu3XQZoNYbhSbLrHpEosucegShy5x 6KJ/F/276N9F+42076J9F+27aN8VnWeUYVm01UjDRho20rCRho00bKRhIw0bqfTfVDnX8/NH1e82 +rDu9zHd73SrWGMVa6jVbUbDZjRMte6/U62bcyxxjiXOsZQr97eDcQiM/d/UPNL7x3rtvXhH2ZM8 Pplnn+D6jrJFj9ehHVS2qmF7/f+m8jF2w7Aot4tyu/V0WE+H9XRYy6AsHzbPDvPskN3D5jlonoMy fFik2813UJaX59hhjh3m2GGOgzJ9WKaX59hhjh2i3y7y7ebXYX4d5tQx+u+FJmSvjSZEj0TfDI9E 38K3MSVMi34Qvhf9EHdgKn6EDd7biG5sDY9HO8O90S7sxh7sDfdWnBIdVnEq3of34wM4DafjDJyJ s3A2zsG5OA8fxIdwPj6MC3AhPoKLcDEuwUdxKT6Gj+MT+CQ+hU/jM7gMn8XluAKfw+fxBdwQHV7x ani5YnF4oeI11GMJlmJZWFSxHG+gAW+GRZWPhe9VPo7foNHzFVgJa63chxDuHXNoeGTMYTgiOmzM kTgK78Z7cDSS8L0xJe/vwK7wvapz8FHcEh6puhW34XZMC9Oq7sQM7/0qOqxqTVhUHUWHVZ/lejbO CS9Un4uLcLHnn4aYVYtZ9Q3h3urfYj76PO/HAFIMh8ert0OsqkN4pKYi3FuTiw6rOQDjcSAOwsE4 BIfiXTgc1lRjTTXWVGNNNdZUY001x+BYTAuLau7Ef3j8B9fXXQdc0/DCWPEbS/OxXwmLon+KDuZO D8GheBcOw+GYgFNwKt6H9+NyXIHP4fP4Ar6IL+EfcCU4k+gr+GaYK3Pnyty5o5l7s876fdyCW3Eb fhCeks1PyeanZPNTsvmpyllhZeXPMBs/xy9wD+7Ffbgfv8QDeBAP4THfexy/CU+J+twx68PKMZuw Gb1IvL7FdQgl7+/ArvBUVXVYWXUgDgINqmhQdTxOwBk4E2fhbJzj8xe7ftT1k67WXPUdTMINuBG3 hLkyZ67MmStz5v4tc34cfl01HTPCUzXPlbWJ7gtN0f34JR7Ag3gIv8N/4r/wFOahAW/iLTTCKTVy So2cUiOn1MgpNVqFPFajDRvC02rC02rC02pCQ7QNw9iOEnZgZ5ivTsxXJ+arE/PVifmVPaGp0om2 MkEf+jGAFIPYgiFsxTYMo/y9fQhhvv32dPXloan6i7gKE3H16L+Pbqi+1vUb+JbPfBs3hPnVt3g+ DXdiOn6Cu0GfavpUz8GjeAyP4zf4re/90XW+60LX11HEOrSjA33u348BpLB2e62h2tqrrd2em2/P PV0ThQb7br5aWBkdqOofGFWhGjUo/13fWoxDjBwOgCoY2UVyfLIcnyzHJ8vx78rx6+T4dXL8Ojl+ nRwv/5+WxsrzSfJ8kjyfJM8nyfNJ0U+i8dFdmIF/w934KWZiFn6G2fiLcRZiQ3hYRB8W0YdF9G4R nS6i00V0uohOF9HpEa8oqlNFdaqoThXVqaI6tYKKFf+OuaBmBTUrqFlBzYrf4gk8if+ADKyQgRUy sEIGVsjAit/jD6B6xZ8wHwvwZzyNZ/CsM/iZ0fiMLpI51/USfCZMzlwWbs9cji9Fh2RuCPdnbgyz Mv+C8r80+Gr4bPaacDMX8Nnsta43h4Zsk378dnRodlV0fHY1/9YS1WY3hN3ZjTxfd3RqdpPr5ugD 2cS1Lzq48ubowMrv4xbcittwO36AH+IOTMWPMA2PhUlqxSS1YlJlczS+chXyWI0WtKINBazBWhSx DrSU6VNl+lR1ZvKYd4UmGf+w+jJpzPZorNoyWW2ZrLZMqpJLVfKlSr5UvQdH4zSc471zXS+EDqqe TKq61ONbwmS1Y7LaMVntmKx2fFft+K7acZ3acV3VT6KxVXdhhs+LV5V4VZUz/hScivfh/fjI6G6b bpc9bJc9bJdNrb4jGl89FXKqWk5Vz8VvvT7P9Q862XyPn/e4z+f7MYAUw+Fuu+Zuu2a6XTO9Wn5V 74T8snsetnum2z1TazLR+Jr3hqaa43A8TsCJOAknYwLMs8Y8a8yzxjxrPoDTcDrOwJk4C0+5l3nV /B71ni/B0tA09tOhqfbRcHvt46gPs2qXojEaX7sCK9GEtyGmtWJaK6a1YlorprViWiumtWJaK6a1 YlorprViWtuODnRiPbqwARvRjU3YjB70IonGj1scHTLuNdRjCZbidSzDcryBBryJt9CIFdBpxzXh bTRjFfJYjRa0oYA1WIsi1qEdHdEh8eRo/AFfiA454IuwnzjFlVE2u2H0TLAyOtGj6szJKlk8+rfG q1CNGpT/H6G1GLf/z8XncAAOdgY+BIfiXTgMh2MCTsGpeB/ejwuMeCEuDwkXkHABCReQcAEJF5Bw AQkXkHABCReQcAGJCjlFhZyiQk6JJoU0ugE34l9wE/4V38X38L8wGeW/EDQl3K6azlRNZ6qmM1XT marpTJV0oko6USWdqJJOVEknqqSxShqrpLFKGquksUoaq6SxShqrpLFKGuu5BT23oOcW9NyCnlvQ cwt6bkHPLei5BT23oOcWVN2cqpvTexO9N9F7E7030XsTvTfRexO9N9F7E7030XsTvTfRexOVepZK PUulnhVt9rwH5f82kKAP/RhAikFswRC2+vy2MENVn6Gqz1DVZ6jqM1T0ySr6ZBV9soo+WUWfrKLn VfS8ip5X0fMqel5Fz6voeRU9r6LnVfS8ip5X0fMqel5Fz6voeRU9r6LnVfS8ip5X0fMqel5Fz6vo eRU9r6LnVfQ8T/4sT17Hk9fx5HU8eR1PXseT1/HkdTx5HU9ex5PXVbwV1VY0YgVWRrW6QU43iHWD XOaCsFlHyGU+7vqZ8CNd4Xpd4XpdIc5cE5LMN3FDuFt3uFV3uFV3uDXzryHRIc7TIW7UIc7TIW7M /u9wT/YlZ95FUS67ONyUXRm26BYH6xZH6RaJbpHNtjprbnBG3aiTdOsi5b8ol3i9T/W/OYp1i1i3 iHWLWLeIdYtYt4h1i1i3iHWLWLeIdYuYG0240YQbTbjRhBtNuNGEG0240YQbTbjRhBtNuNGEG00q Hw5p5SP4Febg3zEXv8ajeCxM1IEm6kATnV3qnF3qnF3qdKNYN4p1o1g3inWjWDeKdaNYN4p1o1g3 inWjWDeKebWEV0t4tYRXS3i1hFdLeLWEV0t4tYRXS3i1hFdLeLWkcjtK2IER7MQu7MYeyC0dbrIO N1mHm6LD5XW4WRx1gaMucNQJR13Q8SaOSUPKVRe46oLON0XnmzJmxGs7sStM1AFjDrtQVRPSqrGo xTjEUH90xpj7LnDfBe67wH0XdMq4qvyv04/3+ASc7LMTcJrXzvD8TJyFs3GOMc71+gXev9D1ougQ Dr2go07UUWMuvcClF7j0Apde4NILXHpBp52i007RaafotFOqfuD7P8QdmIofYVq4Xfe9XfedqfvO 1HUn6rp5XTdf9V9RbdUiyHFnwTpdOF/VFdXqxHmdOK8T53XivPNhnfNhnfNhnfNhnc6cd0asc0as q/6Uz3/aVS3llRNeOeGVE165oHvP4JUTXjnRxWfp4rOqv+PxJNwQJvPMSfWtuA234wf4IeSuLh/z 0wk/XeCnE3464acTnT/W+WO+OuGrk2q5Wi1X+euEG4h57ITHTnjshMdOuIPJ3EHMHeR47YRDmMwh xPx2wm8n/HbCbyf8dsJvJ5zDLM5hFucwi3OYVS3/quVftfyrln/V8o+bmMVNzOImZnATM7iIyVzE LC5iBhcxmYuIuYg8F5HnIvJcRJ6LyHMReS4iz0XkuYg8F5HnIvJcRJ6LyHMReS4iz0XkuYg8F5Gv uS2qrbkd00Kdc3AdVxFzFTFXETsP19X80Xt/wnwswHMh4Tby3Eae28jXrPbagM+lGPR4S1TLgeSd mevGXhPV1v4qbK6dg7l4NFzPlVxf+1uPF4Wk9hUsRn24lUu5tXaZx3oIt5LjVnLcSo5byXErOW4l x63kuJUct5LjVnLcSo5byXErOW4lx63kuJUct5LjVnLcSo5byXErOW4lx63kuJUct5LjVnLcSo5b yXErOW4lx63E3ErMrcTcSsytxNxKzK3E3ErMrcTcSsytxNxKzK3E3ErMrcTcSsytxNxKzK3E3ErM rcTcSsytxNxKzK3E3ErMrcTcSsytxNxKzK3kuJWYW4m5lTg6MvpF+MTf/cWmxRXvwdejiRXfiK6q uC66o+L66GMV/xx9suKb0VWZz0TXZG4Y/fttn8heHT6WXRh+l10Ursh2OSNs8PrGkGY3hXuzPWF5 tjd6dzYJzdm+UIqOM8rY6PehNVoSWo12k9FuMtotRrvFaJcZ7TSjnW+004x2htE+YbSDjHaA0T5s tIuN9v1sXViYfRmL9vVlXw3P6zet2dfCkmx9+IVZzDCDkWx32GQWHzaLX5hF1ix+bRb1UU12RXgy 22RuTujZ5vDP2VXhL9m8b7WEtToUrczxeXN83ie/oo+t9OmHfPqObPO+fT79G5++TE97zjdu8405 0fHRL6LzKnJRdcUBeDVM012P1k0/mvmcs5bKkPmuDjsvOjFTHy7NLAtXZNqj8zLbwzezFzs/1UWx rnm6VfzZaMuds7LZZmeo1eFZXXOMEfZZ1Wqd8479nTO7/6yVtbpN2V4rS7zeFwYqTo0qw8JoDKpQ jRqMRS3GIUYOB2B8qIsOxAVhTXQhfhJej+7CDPwb7sZPMROz8DPMxi/o+JewLloY1onjGnFcU3Eg DsLBOASH4l04DIfjCByJY3As3ovjcDxOwIk4CSdjAqaGYsWPMA134seYjp/gLszAv+Fu/BT3hvUV 9+F+/BIP4EE8hIfD+syZ4YXMubgEXwqvZGaGrsys0CVz/3H072puHP3bmgso2i9fvihf9mRL+3qy O8LHsyOhJrtz347srn1rs7tDVXbPvs3ZveGS7D6vh3BE5Zh9PZVV4eOV5f9FX82+HZVj962trA1V leP2ba6MwyWVOa8f4HM3h4WV38ctuBW34Xb8AD/EHZiKH2Ea/hTWVM7HAvwZT+MZPIvn8GIoVv4F C/ES6vAyFuEVvIrFeA31WILm8HrlKuSxGi1oRRsKWIO1KGJdeL1KLlXJlyr5UiVfqt7jejROw7m4 EBeFNVWXuj4UilWP47eez3c1nyrzqVrq+et4w+MGrPa4xdVuq2pDAZ1YH9ZXbfTeduzGHuzFPoSw pvrIUKw+Cu/Ge3BCWF99Ik7CyZiAO8Lr1VMhV6vlavVczMMfwrrq58PrNRn8ayjWTA5ram52fcD1 QdfHwvqap7znszW/R7vXOmBeNesxFIpjLw3rx34Z14Y1Y78R1tQ+FbpqF+BpPIvnsRCN4YXaFViJ JryNZqxCHqvRgla0oYA1WIsi1qEdHejEenRhAzaiG5uwGT3oRRJeGHdv6Bp3H+7HL/EAHsRDeBiL wyvjXkM9lmApXscyLMcbaMCbeAuNWIGVaMLbaMYq5LEaLWhDAWuwFkWsQzs6wivx5NF/8//KAV+E vRdVqrsLVNEku1rdaw17oqucH+c4P85xfpzj/DjH+XGO81WD81WD81WD81WD81WD6ppWvB4Kzjn9 zjn9zjn9zjn9zjn9zi6POLs84qzylrPKW84qb2WeDDtV3bxqu/6d353IHulssjjMcTI/Rm3vUGnv 5/3n8P5zeP85vH8/79/P+/fz3Q18dwPf3cBbz+Gf5/C3c3jZObznHD6z/Ff8+vnJ8l/vK1R/cPTv lPXzkP08YQO/1sCjlX+uWf55ZgPf08/39PM6/TUvhQIvU/5re/1jvxoK/Moj/Moj/Mlb/MlbcX3Y GS/BUiRhSzyCELbkcjgax/yP39945/c2loWdo7+nkVHV/qA/zIzGZxdGH86+FP1T9pXo3Oyr0RHW /3z2Nd25PpqQXRF9nhafd14bo/PEzmwHZvPRWXRp14GO0zO7oov09rH6zuf1nQnZnuhT7lu//2d9 HzDSYiOtDg+NjrnVezfqTuW/E7iaK+gNK6KKihuiS0R+Zfm+0YXudoU6e5l7//WVs1ThHV79mCo8 oApvHf3Lj31hpztuMEpvdP7oz1KO8NmTR3+2cpbZnGL00z1bGX3IzI/03pj/w9x1wHdRZP83M7sz +/tlNyGQQKih9yJSpIXYQIRDRAXpRbGgWE6xnHeK5+nZ651gQT1RUVDABigighiQXoTQS8BAQotS Q8v8vzO/X0IJEAiW/+5n5jf75k3Z2TffeW9284J76IZ+99ALxFDc8ww9w0mx/tF7YG2doeeDG5gE vSEHV2txNQTaxXSswzP0HKpFDnrpIkgEheAhhBDCCDEIPkKAEEupohslwg6eCBt4ImpJgf27CDWt QE1LYc+mwp5NhT2bCns2FfZsKuzZVNizqbBnU2HPpsKeTYU9mwp7NhU2WSpsr1TYXqmwtVJha6XC tkqFHZUKGyoVdhP6Yvs6Re9FS2txF1vEd5De6XoVWpwIDWg77n0o1cezTkTuXnO3uPdYKskWU3W2 hBphZPpana0XuHpTb9HP+j/sLYboNFjwc8T9OkMMp+ZiBMIUPIdvqCZWyHFOS2rsGO/tAqVqoEQN tNMET3MoVUFLO4002ZZczKdV0JV2QE86aJ99uvlPb6DuwlWO1b524GnFAQGWgucIUOAIcnYZPqPp oIWFeNqLIIHLgQuQDv0rSuegzp14wqVQZj9y0qL8uaZGtLoI1MWoeQnueiloy9F6hOOI5TBSJsGx HxxHIjJuPK6i3hX6sO3VYnC0sv1cCn3K5C7T6ZCnBGh5h9FCpA4vWvsWscK8kbD9XIyrJXo7yh2O 3vVm5GyiqpgJOZDRMGZMOcyYEpgHU4khzrHeznMh5XnCfOMkwO2Bk+NqFe7eXG1GX7cgZyvqyIbO uQ25240vB8yTPOQeRO15kdoxb7JQWzYk3ujZpnwJcByIchhfqh5yN1rP/eiZno/ZUyuSCxw2uVlo l9vasvUWO4dNfcZPeC7G/ajeAN1mJ3QZ8w78qM5ByjzL/eA6jHAEo35UL3JcnQu9J9eJ0XvBscjy LkXKjNkhXB1Gi0cxqlrnOSHi4M1Dbjp0ozz0eD9yD+Dp5OI5HkSNkZpNieUocQS150HLOoKe7HA8 tBBpydSwHDUcwTM9gNHNxXgdRKnDWqNklm1LEkOpHJTKQymNElm2zZJoM0OY/82QC93/IEb8kF5m e3kEszhPZ9vSrs5ADRw1rEEN+52QXmZ7HqNXQLPLtjVJ1JCL9taLPMuZizbWO4Ed71zIxyF7H6uQ swXlTZ9XUayTQCEnEf1KQplyVMKBXuNUIM+piHQl5CUjryryquO6BvJqIq8W5M5xSqOF8sitjN8a eBa+k4CrRL3LKWPqQgvl0ZKpqxLoyaBXMfWAXgN01EPScidR2NZjOKoibeoqiX5x5GY6pUEpg5BE yehfSXBmos5k9I+jfxylMp3KyK+CUBX06uCpAVpNpGuZ/z2IWtair5E7LIu+liM3WospvRb9j9xh NeRVR16kNMf9JiAkQuZKo89JqLcc7qW83oOSYbSP+0J+MvIrI78q8quDVgP5NZFfC/eHu9DbUEMu atjrlEFIgqSVBXc5PM8KeI4Vcc+VwJMMnsrIr4JQFTzVwAOt0qkJnlqYneY5+XZckygB/TAjlot+ JKAfMeiHb8e2Kq6r2xHMRR8S0IcY81RIRJ9uZJwjvTejJ6JP1o55tNcc69n+vGzMgv6QmgqQyM6w OXIgke1gc2yDBA2CVCZDKlvD5sjGbOgPiaoAqewMmyMHUtkONsc2SNcgSGYyJLO1k5B3CKPQAKNQ D6PQwEnKy8UoNMAomOd5IUaiFkaijlMJfMmgVwZfFfxWBV81/FbX5pleiNGohdGoAx0ANiTWhVRo EbHQHkoBGY29WgPo0QKYMQvrQBwFsAkXwbZfBNt+EWz71rDt28O2fxa2fXvY9u1h27fHajRSdAeW Xw9bvoceaUtNQakpKDUFpeoUUSrNljI+s1dYav7VpwVXnMVjRW9ARK2wftalS3BeQJ3oWmpM3el6 UHvSzdSGbqXnqCOs+LF0F02habiajvNlmkvp9AqtxPkObaZM+h9tZYzeYwFLpGmsPCtPs1kl1oB+ ZH9hnWkl68K60GrWi/WhNaw/60/r2UD0eQMbwu6kzew+9gxtYc+x1+gIewNniI3EGWZv44xhY9hY 5rPpbBGL5RfwC1kl3pRfxKrwVrwVq8Hb8lRWk1/GL2e1eXventXlHXgnVo935p1ZI96VX8su4N15 D9aE9+a9WXPen/dnF/FB/CbWgt/Cb2Gt+GB+J2vN7+H3s0v4g/xJ1p4/zZ9n3fmLfDjrzV/jr7Mb +fv8M3YT/4KnsXv5bJ7O/s1X8s1sOM/i29konsN/YaM5dGj2ET/ID7PxXAtinwkuBPtCKBHDJopA BGyKiBNx7BtRUpRkU0VpUY59K6qIqux7UV3UYD+IWqIOmyXqiwZsjmgkGrF5orG4kM0XTUVztlC0 Eq3ZEpEiLmY/iUvF5WyF6Cy6sNXiOtGDrRO9xI1skxgi7mA7xD3iAbZL/EP8g+0Vj4hH2D4xXIxg +8V4MZ7lii/Fl+ygmCwms0PiazGTHRYLxQqO9U9s51hthOblHNeJ5dWdBKc2b+ikOCn8Mmeo8yS/ 3HnGeZf3cMY7E/ndzlfONP6gs8BZxIc5S51M/piT5Wg+3I11Y/l4t4Rbgk9wE9zS/FN3nbuZf+Fu cbfxKe5Odyf/zv3F/YVPd3e7e/gMd597iM90j7hH+BxXS8bnSiEFXyBd6fKFUsk4vkjGyyS+UpaT 5fhGWUEm8wxZVdbmmbKeTOE7ZKpM5VpeIrsKkj1lfxEvb5HPiST5gnxJtJX/ka+KS+Tr8nVxuXxT jhTt5LtytLhCjpVjRWc5QU4QV8mJcqLoIr+SX4mr5TfyW9FVTpfTxXUyTc4S3eQcOV9cL3+SP4ne crlcLfrIdXKTuEH+LH8Wt8osmS0Gy91yn7hdHlYk7lIxKhD3qbKqnnhQNVatxLOqjWorXlXtVAfx muqkOomR6ip1jXhLdVM9xSjVR/URH6r+qr/4SA1UA8UYdZO6TYxVd6q7xKdqqBoqPlf3q3+JL9QT 6mkxQz2rnhOz1MvqFfGjelUNF3PVG+o9MV99oD4Q6epD9aFYocaosWKlmqAmiNVqkpol1qiFapnY odaqDLFHbVdHxUGlPdfxPeWFnVLeEG+IU8a707vbSfKGevc55b0HvAecit5D3kNOJW+Y96iT7L3i veJU8f7rvepU9V733nSqe+947zi1vDHeOKe2N9Gb7DTwpnvTnQu8md5Mp7E32/vRudBb4C1ymnpL vKXORd5yb7nT0lvprXRaeWu9DKe1t9Pb5Vzi/er96lzm7fX2OpeHWoRaOu1CrUOtnStCbUNtnQ6h jqGOzpWhzqHOTsdQl1AXp1OoW6i785dQz1Bv56pQ/9BAp2toUGiQc1349fD/nG7h0eHRTt/w2PBY p194fHiC0z/8WfgzZ2D4i/CXzg3hSeFJzqDw1PBU56bw9PB05+bw9+E055bwgvBu5/YYGRPrvBxT Pqaq80ZM9Zh6zqiY1JgBztiYwTHpzvyYlTFb3VYxR3zH7egn+i3ca/3Ofj/3Af+v/rPu0/7b/nj3 ff8zf5I70f/Kn+J+40/1p7nT/On+dHeG/70/z/3eX+gvc+f76X66+5O/0l/tLvPX+j+7K/wt/hZ3 o7/Nz3Ez/N3+bnerv9/PdbP8owG524NQEOvmBCWDJHdfUDGo5B4JKgdV3LygWlBDUlArqCVFUCdo Lp2gZdBWlgwuDi6VScHlQXtZPugQdJCVgo7BX2RycFVwrawadA/6yNpBv6CfbBQMCG6QFwSDgttk k2BIMES2CtKCNNk6mB3Mk22ChcFP8pJgRbBKXhGsCdbKjsGGYIP8S5ARZMjOweZgq7wqyA52ymtj O8ReJ3vE9ojtK2+KHRh7o7w9LiXuYnkn8dB08x+RY3bHE9WmZPpNDr1Vb6XKCAQd+lT5efp+PUZ/ gtQ/EK7XnfQ0/QFS22zuJr0a8cYo775CpbeZoHfg3FVAjCvcB4QHi+xpJ4RPj7ter9cTdOAzltmP sErvQdLHut0Tdj3pzILcnIJU1inKztYb9Xb9rV6J34V6XlH9K/LwUOfMSGs4P8tv81gvClreibBO b8Co5eruFCIXekWVgty8ohrSOXqv3oPxySggKVDtlf5Yf4xRM09wzSnLmrYz0XqOXodLl8IYsxSk 6kR7voRaIpAJpyw/TJtvNUj3Q2irG+n79F0njPSWglSh9iFrcyGPWXq+noc+7NILSUZzsk/iXFDk GKy3vTepL6Njsl1PhjUfyV1biH8/zlx9WC8CZzvzX9qhvzkR2bQjknlMciKyf0LpTL1Zm7+zItiv 5nqh/Y/pkL0Cjl0nlzlNv08YFf3hSXd0dkfkWe238c/6Z/IQztzqYYSD0YtGdNEZeUfojxDv0D+e dX+OL71Ff454b2ScTsg5Jf6cwHFAf21kC6npRk5PyOtRZOlfET63iLTq5NJFH/oVI0167ClnjXcW 5XP0FPs0dpxry/nlj+HsOZd9Pvo7qxhlp9p4xSlHTBavP9GjepFtm3XBrC+HMb+2n2Pt/hlzayNc Y9uIoGJG5IzmnmptrYMzGWedE3o42saLIucZSjc+Zek9NsYKrI8UxpQCrjydDUzMxozLHw+7Auj3 bbwKmLkeeHMWhx5OZYBLTelqpL+ylN1YnbNO3/YJpV/CKhJHV9AApO3cR9lt+tdTrZ0nlTSr8EiU DlFpureAOlN/Q+7p19VCM8XFfd8K+jiba9aIw/k4ro8UKn34uPRzmLtlqSo9g/RllvIdtJgf9YTT tp15anoe2tGTdAfdTg/SV0R53ylU+rHo74lrJKe+9C/Y/UQv0ItYV1+mTyCl42kypPEbmkYX2h2B 5jST0oHAqyiTOtm9gB5sABtA98ICv4aGGtub7jdWNz3Ab+N30N9gP6+kh/kavpkegRWdRU/ybXw7 PWVsaXqG7+cH6Dl+mB+mF4wtTS8aW5peNrY0/Ucki2R6TfQRfel1MUAMpDedSc4kegtWqKa33dJu aZovv5Pf0QI5W/5IC2Wm3EKLVViFaamxu+gnY3fRStVb9aF1xu6iDbC7bqCNxu6iTcbuoixjd9E2 Y3fRdmN30UFjd1Ee7K7hjGBxjWRSva3eYyFjd7E4Y3exEsbuYvFqvJrAShm7iyUau4vVhN11lDWA xRVmXbxYrwTr7ZXyElk/L8krxwZ6Fb1kNsir4lVjt3g1vdrsNq+uV5/d4TXyGrO7vce9J9i9sLI+ ZvfBmlrIHoQ1tYQ9ZOwl9ndjw7B/GBuGPRwzIyad/dNYJmyE393vx74xtgT7wdgGLM3YBuwnYxuw VcY2YGuNbcA2GNuAbTS2AdtsbAOWbWwD9ouxDdivxjZge41twA4bvZ8dMXo/O2r0fs5ju8R25Sq2 d2xfHo5rG3cxN3u7K6zEMCsxHBIzHDrJCHoD8vwmvQ/KBzgVjaaxWIM+hjxJK08S8jQVs+1bSFXY SlUYUjUH9Lm0jGJoORlfTek4A8jZWoqldbSJKtv9pyq0lX7FPN+NsyrtoQNUjXJxVqeDdJRqUB4k Mt5KZEUrkcJKpG8l0odEDqES/A7IpW/lsiTkch2V5uv5eirFN/AMKsM38U2UxDdDXitYeS1v5TXJ ymuilddyVl5Lcc01lRJQ3CkBUssR46BEyK5C2hMelRUhyHGClePykOM+VFP0hTTXgjQPQHogZLqW lemKkOl1xJz1TiZxZ4uzlaST5eyiGCfH2UuVnH3OfopzDjhHKNk5CumvYaW/ipX+ilb6K1rpr2il vyKk/ypKUF1UF4pRV6uryVFdMR9czIduoHRX3UG5Xl1PSvVQPchTPTFPqmGe9EbZPpgtITtbYswu BQXqBsyZWMyZm6mKukXdSnFqsBpMNdRtmEXxdhbF21nEMIvuR6kH1N/B8w/1MCiPqEeIq2HqUbTy T/VP1PwYZloMZtq/UepJ9SToT6mnwP805l5g5x4zex7g+Y/6L9p9VQ1H7hvqDVDeVG+i1Eg1Ejxv q3dBGaVGoSfvqfdAwfyksJmfqGeMGoNSY9VY0Mer8ahngpoAzklqEiiT1dcoO0VNwTh8o77DyExX P6CfaSoNYzJLzUKvFqrF6O0StQx1rlUbwL9RZaDmTSoTtW1R26iy2q52YUxy1B60tVfto6pqv4JM qlx1kKqrQ+oQWjysjqLPWmmq4hllrJrHPEY1PO5xYhATh8Ke67kUeNKTFOspT1EpDweFPJwU74W9 MMUYNKGKBk0QA00QA00QA00QA00QA00QA00QA00QA03QygJvAeKF3kLiBlPIMZhCzGAK+cCU7xHP DKdRCYMsJIAsFcj3K/qVKPCT/RZUwqAM6EAZKguUqUOlgrpBXUoI6gX1KAjqB/WpdNAgaIDchkFD SgoaBY2oQnBB0ATppkFT8DcLmoGnedAcPC2Dlki3ClpTuaBN0AY8KUFb8FwcXIzcS4JLKQbI1Q70 9kF70IFfiDsGHRF3Cv5CJYFiV1GZoEtwNSUGXYOu4LwmuBYtdg96gtIr6IOagW5oZUAwAPHA4Abw DApuQp9vDm5GPbcEtyI9OBgM/tuC25AG9oEO7ANlc/AzWskMtqDU1mAras4OtqHO7cFOSjRoSMKg IZUwaEglgFjjomj4Ek5RgIavIf0mcFBYHHSBgp8gPZ6+Qvw1TbFoOB3p74GBgtKAgwI4uBy4mQ58 FXbvXVkcFBYHEywOJlocDFkcLG1xsIzFwSSLg2UtDsawOBZHPuvFeiEewoB67C52D+KhbCjiZ9gz wMGuvCtxi5IeUHIQYoOSYYuSnkXJwGJiKb6D7wB6GhyMtzhYkh/lRynWImCccIRD8cA+D+mwCFMJ 0Uv0Aur1FsAUi30VLPZVEv1EP9D7i/6gGxysYHGwkrhB3EjlCnBwKwkg4F5SwL4jFLKoV9aiXqLZ WcUs7aw6k7DopoBr3REbRBMW0VyLaGVUL9ULFINoQvVTkGDg2gBwGixLtFgWslhWFlh2O2b4HeoO xHeqO8F5t7ob8T3qHsQG15TFtVAU14apYaA8ClxzLaIp9bh63OLaE+A3uKaAa88gHUG059ULSBtc UxbXhMW1kBqhRqDUa+p1UAzGKYtxMVGMe0u9BbpBOmWRrqzFOKE+ArqJKLp9rD5G+hOF9VWNU+PA afBOWLwrexzeCYt3CniXhrTBOKVmq/lIL1RrEBuMU8C4TKQNuiVYdEu06Bay6FbaolsZi25JFt3K WnSLUXkqD6UMxiVajCtjMa5sFOMUsExYLIvxfM9H2qJSeFr4O/LCM8IzEM8Mz6RwOA0YFA7PDs8G ZV54HnkWj3jMypgNxC2ylAqaAFPigouCFhRvcSTOIkgpIEgK0m2DVIoFdlwOisGOEsGVwZWgdAo6 A6cMXsRbvCgFpOiBtEGKkkHfoC94DEaUCm4MbgT9JmBESWDELajBYES8xYg4ixElLEbEAyM2o87M IBOlsoNs8G8DOsRbdODE65YwezQNP29xDV1M151Om///fOiNsDu3RPaJ9IbCuyJR6+mUe3VF1Jyh 1+gcay/OtPsPqy010+4kLInuy5q6N1srMkMv08ssR7Qt/dMZa4/u4+nB596z3+7QnfQX9rfQzvMp uTfCSv/h7KzdM9bz84lpjOnP+buCegFGdSVGc51eolcUcB17fgkFtCV6l14EDTwJJaKWYmS38Q85 wgX9OH7/2aeeEVqh/bUtkd2KE2i79E+415z8XdXf9ojsdumV+bJ2fPvH9xm9KLSDfrq59Bv17Jxn o35fv2t/j6C3c2wYocfgd240P7rXYXcn9+nFRe3XnrKNzfpnSGJ0DyuSMvsjBbvW/0X+9sgOtd4E 7jnRcT2hLX3gLFo6kL9v9tseeu+xvuj9GKt9+pDdmT5hd+ecdwL/hCNfIjGzs8/Mmc/3O/al0LuO M3J/rifqT80ePZXW7+iJlrZRz7e/6wq4zrg2nKbmFUCLHL088gSRWmnn7mq7Ho21HLtszkKzU41z a3SXMdqWnUHl6bLo1Xd6rv4WHGWpI36/t7QPoyvYowi9z72HZ+x9ZIX+tOB6oB6l79RP2Tdpfy+g tgYNPPrXk5Ec87HQM8YKPFPPM6v0b9zX/Xb+WMkzCFN4nutdx/bHzyyh5yY9v8Nh3xbrV05+P6wf ONXbDL0emLG5mPrSClPKrtlB5NqSg/xYP2KpB0lE3qwVlDNtxdIFJ9W2C/XtsnW4+N2YT7WxeZeY fu49PKH+gudyfE3Rt4+Z0Vm0MPpO8gTJs/ifc/LbRPOO/vx6dK7Hye/7Cu/hR+nPnJJajCd8tod+ 8hyYK9kST+uH7a95y/wlxvJL4OgU8xutMX99j7yT3Xz6Nw9n6NU4PQFr9vjo1Rz9cXR2z0GYb3WM A0b2o/3YoudH532krZO+utDfo4czLM43AAp9HqX+cAKPNmhdjJ4up+PffEeQM8PKna0vImu23wss 7+L8UmTeSC226HqrvZquZ+u/6h/1g/o9/QawMoq0kRLR9H6M9H3F6OVQfZ9+S9+N1DydhdRfkXoe VtBbejJGZpS+HSj+DmjL7Gh9qf8XkdhoW+Uja05BbVk6HXhu5mJTrFzRORm1CYwOc8imzvm9sx2t ncejdP4ztmlj3UVtH9vKBvM2LvJGLtpWg2NP4o86jv9CxfQOI7OniFXGSMHe37tfhVrVBan9Vqdd gd/NZywxI38OF7PFt3QvPUyPsOkFkJdReppNb4nMZaMb6ccRPit+G7aWDvqf51V+s96JYNcIyJ9B tQJrKqKtYE1bg3BW2u0Z2llW7JJLom/PM+y3aesjX69YjDEr3sYo1x8u+ycf+jZ9k07L//JI/x16 y1yzZ2K134k6F3nP64d1A11Hj9UpePZ/O2UtrxfZTuQbj6rn3d83T7j6/HzrO00r/z3P8pnA6fTI uopZu7pQ/hZQt+nlx3Zg/pxDL8Is2RzpBbSxVadYF1dBAjKKPw9+mwN9eJaO+z4I693UP7M/hQ/Y VS9Edkfs1UOYO1sj2FmgP2yCHfi8flkfhCa05tRfpRQ9zqf7rvG3PSzeQyow/8/L9iv45uh3OPSm 49s5v9VZX3i+vSmi/g0RvQjjeV4r0vnvDRfZwhasrEV+MfVnH2fWgs7hKPSt91m2X2iv+SzK7DKl jpU825lVnLb+6ON89zyL814BtsTWqCbl5tdRsNPvn350bVtl6W7zzfk5t1mcfe/sY29fCtqPfC97 tMi2OF1x7i3+KUfp4hTKXyHPqcwMU+rY+m+/W94Jy6iIPd/itPX7HLA3957uC87juM7DjvvNjpgi 8ktT72Nv6v6Mw6ynmGFrzvz3C/Y90x9sv5/tX1ScpvSU6G9GNKSdgqmO/WI7oXh6lv0mPCO/ZCRl Q/4X55EWWxOd9FX4CW3l70UWlB59it6YL8sbm+/O8+/qnPo5Uk/BOTp6ZVP2HcaU6F1EetC4UD+L 0VZB2WJo2bD4zVcLBbvdVn/eR7KofetoW7+zBnrK4/i/QYjMYl5ECUUp5mOvcz2K9b5jk33fUaDp 2Vmwveh5FW2r4knUxXg+i/VcKkN19KzoTmladAcJEqSvPvcenrEXs208seC6h34QNuKr5q8D9J0F 1Mv0i6epwD1FnTvPZt0ozmF1p4jluluvwNxfjHjtcWvsDtB/IbNvd4e9/gKI21fPx13Nxj3N1zdF +d44oda1+ppi9KWnvka/ra+NXtmUvs2mPtGj9VC7OzUl8nz1ZJxfRp+iaas0NbJvPB/SQyzNfM/w Nizxt/WneOqZ5p2EpZ+w76IP65HF6OcIINPM/DtGagxi85dn5mumTD1Bf4SnNcNm2r+/yrfto201 PfcW/+ij6L/kPO8WtkXmK57AwaK5z+IoC3wqS+XNaENCEXBVCfN8Ps65CGt1M8y5PhSna5zQj855 EdSI/hWrnqoXW5wzf2Fp3utH7cRj87nQnXxr44eAqeVtqrnuhbauwnwppVuewDkMobfuhrljvwEA Lq3Xq/U4/T5kdZvOiVoK9aiWxef6lmfGuQ+F/g6acr4Emm9XZuBcf0wP0r3sTy/qTi2phW2r3slt 6XhNuqJWQIOZ+nH9DcIw/S/7OyX/3WH0iLX89xejn/fp+/UL0ffnPlL34nwe9Bds7mcaloWehCdw zFYPitvWb3TwQumi1kQFPUqAN60IXyy9or5YHqMrrYeVQawSq0d3WN8qf7e+VR5mfVlfeoQNZoNp mPWq8ih7mD1D/2LPsRH0svGqQm8ZrypkfKq8Te8Yryr0PzaDLaJR/ALemD7jTXlz+sJ4VaFJPJWn 0mTjVYW+4lfyTjSF38PvpW/5g/xv9B1/if+HZvD3+fuUxj/k42kWn8Qn00L+Nf+aFvOpfBot4T/w NFrG5/A5lM4X8IW0gi/mS2gV/4n/RGt4Ok+ntcYnCq0TJURJWm+8oVCG8YZCW0R1UZ2yjDcUyjYe UGiHaC1a0y6RItpSjrhYXEy/isvF5bRb9BK9aY/oJ/rTPvud+AHjp4QOGj8lLDB+SlgNZ7IzjTUw fkpYM+ObhLUwvklYSzfBTWSt3CS3ImtjPJSwS42HEnal8VDCrjIeSlgX46GEXW08lLBrjIcS1sPV 0mU9jVcSNsB4JWGDjVcS9lfjlYTdY7ySsPuNVxL2sPFKwl4yXknYy8YrCRtlvJKwMcYrCVtkvJKw pcYrCVtuvJKwdOOVhK2UY+UnbL3xSsIyjFcStsl4JWGbjVcS9rPxSsK2Gq8kLMt4JWHbjFcStst4 JWE5xisJ22e8krDDxisJO2K8krA845WEc+OVhHvGKwmPMV5JeCXjlYTXNl5JeD3zRTlv5AVewC/w 4r2SvLFXxivDm3jlvQq8qVfZq8ybe9W9Gvwir45Xh7f0GngNeSvjNYS3MV5DeIrxGsIvNl5D+KXG awi/zHgN4Zd7T3pP8vbGdwi/wvgO4R2M7xDe0fgO4Z29T7xx/CrjO4Rf7U3xpvBrjQcRfp3xIMK7 GQ8ivLu3yFvEe3hLvaW8p7fcS+e9jAcR3sd4EOF9jQcRfqPxIMJvMr5D+M3Gdwi/1fgO4YON7xB+ m/Edwm83vkP4EOM7hN9hfIfwu4zvEH6P8R3C7zO+Q/j9xncIf8T4AuHDjC8Q/oHxBcLHG18gfJLx BcKnxbwRM4ZvNN+e81+MLxCe63f2uwlmvICIsP+uP17UMF5ARBPjBUS0NF5ARBvjBUSkGi8g4mLj BUR0NF5ARFfjBURcY7yAiG7GC4jo52f5WaK/8QUiBvi/+r+Km/19fq64xfgCEbcbXyDiLuMLRNwX lAvKiX8EFYJK4mHjEUQ8ajyCiMeMRxDxhPHkIf5tPHmIJ40nD/Gc8eQhXjGePMSrxpOHGBHbIfYq 8VrsNbHXiXdie8T2EqOM9w7xQVxKXIr4KK593BViDHGghwMsbw60LUGM4nEKKgmt2aEkrGwuVaAa oNfEqbBC1YNuUx+IFgJ2tYYN0Qbrbwy1tV4iDbr5Ft0CoFt3lLoeZxwwri/q7kc30kU0CHjXAnh3 D9q5F2dLGkoPUin6G84EeogeoUQaBjQsDTSMpTL271mSWAkgYy0gYy1QarPaVIfVYXVBrwesrGOx sq7FyroWK+tZrKxnsbI+sPJJasCeYk+h7NPAzSTg5ovUkL3EXqVGbDgwtK7F0LoWQ+taDK0DDB2D 9FggaR0gaRqlsllsFjVhs9k8asrmA1ubWWzlwNamiJsBYaVF2FiLsNwibKxF2JIWYVtZhK1tEfYC i7BlgbBjqAIfy8dSOf4xH0eV+HhgbrLF3GSLuRWBuVMRfwvkLW+Rt4pF3nJA3gWIFwJ/KwJ/FyNe AhQub1G4vEXhyhaFq1oUDgGFk6i6KCvKUg1RDojc2iJyDYvI1YDItRDXBi5Xtbhc0+JyNeByCuK2 QOeqFp2rWnSuZv/SJ8X+pU9b+9c9Kfave9papG4DpB5GzZ1HgdcMeP0SBc7LznBq7IxwXqN453Xn bbrQecd5lxINjlMZ4Phkqme8TpFFc2pq0JzCBs0RJ7gJ1MJNdBOprsF0qgdMX0/C3eBuoIruRncj BW6Gm0GOu8ndTC6wfgsoW92toGS5WaTcbDebPHebu41KmTWAYswaAJ7d7m6Kc/e4e6gEVoJ9xNz9 7gG0lesepHj3kHuIEs3agLa0q6m0NA4GmkkmGYUll5zqGX9WSDvSQdqVLjXH+qEokJ70KV4GEjNL xsk4YlhR4smTJWVJipGlZAJ4EmUiCVlalkbNZWQZ1Jwkk8CDVYfisOpURNlKMhllq8pq4K8ua1AJ WVPWQs21ZW2UrSfrIa4v66OGBrIB+BvKhuBvJC8EfxPZhBJlU9kU9GayGTmyuWxOvrxItkD9LWVL lG0lW6G21rI1eNrINiibIlNwR1jh0NYl8hLQL5WXg7OdbIca2suO5MpOsgs4r5ZXk5JdZVf0uafs jfvqI/uj/lvkbWj9djkErdwh70Y9f5X30UXyfvk3aiEfko+gxWHyUWop/ykfo1LyX/JxSpBPyCfQ 23/Lp3AvT8tnUM+z8lnU8Jx8DjW8IF9A/S/KF5H7koREmVWWkswqS3Wwyr5JDeRIOZLqY619F/RR chSVke/J96mu/EB+QE3laDkaIzxWjkX8sfwEzwsrMUphJUaMlRj838hvUMNU+S0oWI/BifUY9Dly Lijz5HxqaFZl0JfL5aCny1Wgr5arUf86uQ5trZcb0PpGuZFqyQyZQY3kJrkJ/Fi5wZ8ls1BDtswG /265F5z75D5wHpaayijzgqKOWcupPtbyCtRAVVSVKEklq6rUUFVTtaiRqq3qUV2s8RdSU9VENaVU 1Uw1pybqInURKC1UK2qGtb8NeFJUCnLbqragt1PtUGd71R65V6grQOmgOqBm87dmzGgGVM9oBoih GSCGZoAYmgFiaAaIoRkghmaAGJoBWX9iZP2JIYZmQLWMZoA0NANqajQDcEIzAAWaAWJoBtTQaAbU CJrBJ+AZ542jZtAPJlLgTfImgwdaAkpBSwAdWgI4Z3uzEf/o/QgKdAW0C10BnMu95dTAS/fSwQ+N gepDY1gLyjpvHXLXexlI7/R2opVd3i5KNToENYAO0YLKhFqGWlKS0SSojtEkkIYmgRiaBGJoEqB3 C3VDunuoOzWEPtGTmoZ6hXpR/VDvUG9qBt2iP2obEBpAtUIDQwORhp5BDaBnvE6x4TfCb5AMvxl+ E+mR4ZFIvxV+C+m3w/+jkkYLAWVBeBvx8PbwbpJGFyFudBGKNboIlYQucgUoHWIGUCujkdAFkb+G MxoJcaORIIZGgvhd/10q54/yR1FF/z3/PYrz3/ffpwr+B/4HVNkf7Y+mZP9D/0MS/kf+x0h/4n8C /nH+OPCM98eD5zP/M6Q/97+gKv6X/pfgmehPAs9X/lfI/dqfQuWh5XwL+jR/GujQdRB/73+PeKb/ A5X10/xZVMmf7f8Izjn+HHDO9eehxYU+1iN/qb8MNUMfQisr/ZWIV/mrwbPWX4c+r/fXo54N/kak M/wM8G/y/4+1849q47oT/Z2RNBJYwpg4mBBCCCaEUOJgQgnFhGCMCaWEUEJdx3WNwEIIIc0IIQlJ 6MdICCFcrw9x/Ryv67g86lLqOi7LcVmHUtelLnUJpa5LXepS16Wu47I8h1DCel2WvO/9irju7nt/ vHNe5nw/urmaGUmjq5nPlzP361lo/0n5J9jnLeUteBbMiWym5kQiwJzmyNPKf1P+G9mmnFd+AG2w KOj/SPkRcFn57yRVeU95D/r/U7lKUpQfQ+r4NHhVJElRrVMpSbIK/oOeKFUU2Qam9Sj0xKriSCr1 LRIBvpUAfEKVCOuAdcGzm1UpwKdVT5PnqHvBfsC9yOPgXpfJY6qfqcbJk6r3VPB5wcMmYT+/UMGn Vl1VXSUJql+pfgU9v1FNw95+q/otvCL4GfSAn5FU6mckhvoZYamfAcHPCEv9jMRQPwPbYtnn0M92 oJ+xaGbcmoeFDYz6lhJ9i86VegNITasYTasETSsaTasUTWsjmtajaFqxaFqbHprDLMM5zHKcwyzD OcwynMMcgXOYZTiHWYZzmNfhHGYZzmGW4RxmGc5hVuEcZhnOYQ7XcpDhHOadOIf5FZzDvAHnMH8W 5zCX4Rzmz+Ec5nKcwxzHsMw68hj4nwoYzTwG1hXPxIN1Uf/LAf97jeQylUw1eY35AgO/THS+zzBa Rks+zVgZK9DGOEke42Jc0HaD+W0D8+uC9leYr8D61P8+Df73FnkJzO8EKQDnOwf8HvM98Lwh5ofw LHW+19H5CtH5tqPzFYHzZRIJOp/kIduTgO3tQNv7LNje59D56CxrKc6yXo+zrNfjLOtHcJb1ejTC V9EIX2S72AMkn1YjJZXohfFogc+y32W/S55hz4MFPoX+txn972n2PfY9MEVqfk+yV9mr0P9rsL0n ceb24+xv2d+DU/6B/QOQzuJOx8oWaewt9s/Q8z77PpDWt0jA2d3J7P9i70KbzvFOYT9kF6FNZ3qn sn9jV6BN53s/wa6yH5MEnPWdJGEkLLTp3O8UiUwC+QHOAE/CGeDJknWSddCzHowzA40zE40zC42z QvK4JAH6qXdmSDaDdz4nSQXvzEDv3CJJl6RDGxbgVskLZKskR/IitHMlueRTks9I8qBNrfR5ST5Y aYbkZcnLsH9qpRnoo59HH61CH/08+mgVmugOcNCjRAn2eZL+m5vgnbHSXuk75DG0zxzpENjnZ8A+ L5Ft0p9IJ8jL6KDbH5qXLsN56Sqcl74B56WXo5WWoJUW4Bz1V9BNc9FEOXRQDh1UifbJoX3Gyu7K 7oJrLsg+hB5qnI+icZagcUajccaicW6SrcpWwRioU+5Ap+TQKaPRKXegU7JcNDglhzbJoU1uQmvc gb7IoSlGoyluQjvcgV7IoRfGohfuABd8EZ6lFhiNFrhjzf8KuAJYs5ArhDWpBe5A/+PQ9jg0PA6t rhitrgStLhqtrhStbiNa3aNodbFodZvQ3jZxR7mjZBv3FvcWOBC1t1zu69zXSR7Xw/VAP/W2F9Db Crh+rp8UobFlc2fA2PK4dzj41tDbtnED3DnyMtjbeeh5lxsmr6G3beMucBdgK2pv2dyPuB9B/yg3 Ctv+mINrFfpcDvrcNu7n3CTs4Rcc/K65X3K/hPWnuClYh7pdDrrdNnS77dwMNwN7oIZXgIaXjYa3 DQ3vJTS8IjS8F7j3uffh2Q+5D2E/1O1e4Ja5+9BDDS8HDS9XzspZ8po8Qg45tDxGHgektrcNbC8Z 2tTzXkLPK5BnyDPB4ajtbUfbex1trxANrwAN73U0vO3yl+Uvk8fkRfIiIPW8IvS87fIyeRnsk1ZP UGH1BBlWT1Bh9QQVVk+QYfWECKyeUIbVE2RYPUEm/7L8y/DqtIaCDGsoqLCGwitYQ2ED1lAoxxoK cVhDIQ5rKMiwhoIMayjIsIaCCmsobHiohoIKayiEq8KosIZCHNZQkGENBRXWUJA9VENBhjUUVFhD QYY1FDZgDYU4rKEgwxoKKqyhEPdQDQUZ1lBQYQ2FcqyhIMMaCrKHaijIsIbCOqyhoMIaCjKsoVD+ UA0FGdZQUGENBRnWUFBhDQUZ1lCQYQ0FFdZQkGENhZ1YQ+EVrKGwAWsofBZrKJRhDYXPYQ2Fcqyh EIc1FGRYQ+EVrKFQhjUUyh+qoSDDGgpxWENBBqb+KMkFR38SmKTYSgrQxV9WGBVGsg2MnCd5imZF M8lRmBUt4L4WhQX6bQobeQwdPVthVzgI/g0P2i6FB0h9fbvCp/DBfoKKIPCg4p+AhxRvwt4OK74K 6xxRHCEvKP4HePw2xduKt6GfevxLim8qvgnvpF/RD+uHq85Qs98OZj8Ar0LNXqn4V8V52MO7indh q+8rvk8KFT9Q/AB6fqz4Cbz/McUY7IGa/WNYpSYb/T5PMaWYAlLLL0LLz1P8TvE7koeWn41+v03x Z8Wfoecvir/Aq1PX346u/7riA8UCbEWNf5vir4q/wjofKZZJHtr/yxF5EXlg89T+cyO2R2wnL0WU RJSQ1yJeiXiFFGAmkBdREVEB69BMIDeiMqIS2q9DJpAX8cWIL8L6NB/YjvlAIeYDRRF7I/aSxyK+ HLEP1qyBrCAnoi6iDnq0EVryMmQFx9cyAZoDnIQcoAczgd7IXuj5duS3SX7kQOQAcDByEHgu8hxw KHIIOBw5DKRVM9Zj1Yz1WDXjEaya8QhWzViPVTPWY0YhwZzh1XW163TkxXXd694i+etOr7tIKrGm hhSzCClkDs1g5zQ3eBZzg2eU38Hc4LvKAfBsmg88iZnAs5AJfA/aQ8p/BRcfUY5AD80BnlL+SPkj 6Pmx8idg59T7N6P3P4ve/wx4/xXo+SXY/zNo/08rf638NaxPvf9Z5e+UM/Ds78H7nwbv/wPsjXr/ ZvT+J9H4n1L+WflnkqF8X/k+8C/KvwCp92eh91coPwDvf165oFyE/r8ql8gWtP/n0f63ov1nKf9D +R/Qc1/5N/Ip5YpyBdb8WPkxyQKpZMDjWZWEZKikKin5lCoScoMtmBVkYVZQoYpWbYBnY1QboZ/m BltVj6kegzVpVpClelKVBP1PqZKhf7NqM+wtBTKEBMwQtqhSVankecwTMlVpqjR49lnVc/AsrWOS jhWS0lSZqizooTVNklTZqhxo08omKVjZJAkrm6RjZZMkrGzyBFZISlDtUO0A0ion6aqdqp3QprVO klWvqEqhTSuePIHVkhKw7snjWC0pAaufpGD1k3SslpSmqlZ9AWsm7Yb+N1RvQA+th5KK9VCeUO1T qeFZWhUlHauipGBVlFSsipKs0ql08CytjZKCtVGSsDZKsmpANQBZEM2LNkNe9FMSD3kRjAfVz1U/ h8xnEnKhzZgLbcUsqAKyoN9Be0Z1A44YzYW2qm6qbkKb1lhJwRorj2ONlXSssZKKNVZSsMaKlDCP LyaIoKJKyQHyB0LUZgg7hAciAHEAovvBI2NWw+NRiBMQvRD9EGchzkEMQ1yEGIOYgLgKMQ1xA+IW xBzEAsQyYf0iBlGvYLD+IMRBQmpZCDh110ZBbISIh0iCSIXICL+v2qzwe6jN/b88FsC+DsNjcThw mzKISohdEHsh6sLvt1a39shDWCCcEGJ4X2uPrP8YxEn47FoIA7RPPegLx2mIgbW+IYiRtf7Rtbi8 FpMQUxDXIW5C3F5bdx7XJ7XB8Pugx6mWHovDeMzD6y5C3IO+YxB03VMQpyEGIIbWXnt17bOOQIxC XF77bJPh99MuXYtI6JuCuA6fxwxhX9ue7vsmxG2IeYhFCPqasN86KQRsVxcNEQuRAJG89pj29/Xr tkBkrz1Grm2X/dDzeRCFECUQ5RBVELv//ki/v7p9EBoIPYTp//D///jIttP3ZINwhT9bnR8itPZ9 /z8EjvmHou7QWhyBOA7RA9EHcQZicK2fPp6HuABxCWL8oe2vYLDt9Hhdg5gJx397nVka0g01eoF4 T9YqTEPAKNMIchS40XQZGG+aBCaZpoCppuvADNNN70m6lS+9Nst025dZYxI476kam6D0nq7NNc0j Fx+0C0z3vKfps76cGpcQ4x2oLTategfC7TX6hTjvUG1ZsxRY2Rz5oF2G7V3N0cC9zbHAuuYEoK45 2TtEt/LlAxOhHRJSvCO1fHMa0NK8BehszvaO0H5fUc0hId07Wis25wGDzYW+0pojQqb3cu3B5hLg 4eZyZBXwWPNu4MnmfcBTzRrg6WY9cKDZ5L1Mt/JV1A4120R9zXEhxztZO9Ls8k7W9Aj53ilKXzWw yHu9drTZD7zcHPJepz2+PbWTtD/8bE2fUOq9WXNGqPDerp1qPgS8jrzZfMR7m/b71EhtzaBQ7Z2v vd18HDjf3ANcxPa95j7gavMZ73ydtHkQGNl8/gGjmy/4DHWxzZd85przwh7vYl1C87h3Efd2b60n ufkKMI2S9vjsNRcEtXe1bkvzNWB28wwS2rTf56m5JGhFaV1e86wopW1foOZS8x1ojwsGMbKusPku sKR5CViO7arm+8DdZgLcZ+aAGrMSqDfHYDtOjKTb+g7UXBHMYnTNNcEuxtaZzIlAG9JlTvR11/nN KWJszYzgERNqZoUAvIeQOR14yJyJpO0j5hx4J3eEA2Jy3XFz/gP2mIvE5Jq7QreY1mRry0HmI4uA rrZSoL+tAhhqqwYeatsDPNKmFtPoVp03mo63aTtv1SwJR8UtNfeFE2J2U0+bAdjXZkbS9pk2u5hN n+2cUxOh1zvVNNjmAZ4XejsXwlRzQr+Y13ShLYA8ALyE7UvYHm/rBl5pOwq81nYCONPWK+bRrTqX gWehrRTOiYVNs239wDttZ4F326CH9neuqGOEYbGkaamN8n7bxRCrjhMuiuUG0jZGacjH9gSQa7sK VLZNA2PabgDj2m4BE9vmxHK6VUhhSGlbCEWpE9VascqQ3rYsVqlThDFxN2V7tDpdmBD3GTLbVoA5 LlbcR3s6x8L9a8wUrooadY4wLeoN+S7FAxa5okQ97Q9tRMar84UboslQ6tqIjH/QrnAlAatdqcA9 rgyg2pUF1LpygQZXQSjJYHYV+zLVRcIt0Wawu8pCqbg311qPx1UJDFDSns5hdakwJ/oNB1y7kHs/ adP+UIa6QlgQQ4ZuV50You1QluGoSxfKVVcLy+Ihwwk48kAX/6Dd67IA+11O4FmXCDznCgKHXQeB F12HxUN021CBeo+wIh5Rq02seNww5jr2XzjhOikeV2tNCrFHbTBFiX2Gq65TyNMP2tOuAbFPbTZt FM8YbriGHvCWa0Q8o7ab4sXBuj5zKfCMuQI4iO3z5mrgBfMe4CWzGjhu1gKvmA3iIN3Kd7Tumtns O6H2mJLE8+qAKVW8UDdjtgNnkXeQd80e8QJ91terPmDKEC+pD5gDlLRdt2Q+IM6ou01Z4njdfXM3 8ihwFtuztL2fmE8AOXMvUGnuB8aYz4rjdCtfv/qoKVe8oj5hKhCv7Y8znwMmmoeBKeaLwHTzmHhN 3WsqFmf2ZyJzzBO+s+p+U5k4uz/ffBU5DSwy3xBn1f3mW9AuNc8BK8wLwGrzMu03lfnO7d9jXoEe dQvrG1afNVWKd/ZrWxRAQ0uUeEd9zrQLvgWg7+J+c8tG35h62LQX1re3xAM9LUmUpr2wHw/2I9UX TXXiXfWYSQfvLdCSKs7UDVLuP9CSAUcG+n0T+7tbsnxXsT2tnjDx4tL+oy25yAJxCdYH7j/RUgzs bSkD9rdUAs+27AKea9kLHG6p893Yf7FF57sF+7GI99W9LTxwzOQEXjWJ8H7GWizACUra45tTT5uC PrL/aosTOP13Yv/C/hstom95/62WoG9FfcN00Mftn2sB0rafVd9oOQztW6bD+LmOIU8CF7C93HIK uNJyWpzRsC0DQEXLEDCqZQS4sWUUPjtsC593znTMp1QvmE76YjTxLZeBSchUZEbLpC9GvWw65YtT r5hO+xI1WeYKYG7LFLAAWdxy3ZdYy5oGfCmaspabwErkrpbbwL0t834FdRJ/lKauZRH8BNzAv1Gj a7nnHdLwLatAi0UavoL74+l10J+kcVoivfMa0RLtnadXIn+qJmiJpVclSwIQrjX+DM1BS7Io1Ry2 pIlS+nvxZ2mOWbbAbwfGrT9Xc9KSLY5rTlnygKctheKsZsBU5i+g36+/WDNkKRGX1BOWciAcB3+Z ZsRSRY+JZTcw/ElHLfuAly0aXyK94oSKDXOuUTGNnvlDZYYF12Uxz7DsmgSuuKbWzs+V9CwX2mVk XddFkzrfdRNIzzN7jQrXbXrOcc0D4UwSqjNGuRbFPuNG1z2xTzNpXvGd00xZ9P5KzXWLyb9Lc9Ni 8+/V3La4/HWaeYvfe1qzaAl5BzT3LIf8OljnCKyzajnu5+ullh6/pT7S0ud31kdbzvjF+ljLIPjV Fct5Mbo+wXLBH6xPtlzyH6yZsYyLCfVpliv+wzVnLNf8x2oGLTPe+fotllnfifpsyx3/yfo8y13/ qbBv1Bdalvyn60ss98VD1Cj8A/XlVuIfqq+ycvRbsCo/ubLX77bGAPdZ44AaeG8j9Xpron+03mRN 8V+ut1nT/ZP1Lmumf6reb83xX68PWfP9N+sPUaetP2It8l6uP07dqb6HWkp9n7UU3BW9sf6MtQI4 aK0Gi6Nj43b9eese4AWr2j9ff8mq9S/Wj1sN/nu1i7jmFavZO1p/zWr3r9bPUHOrn7V64FXuWAPA u9RR65esB4D3rd3ey1piPQrkrCe881qltRcYY+33LmrjrGeBidZzYqQ2xToMTLde9Du1mdYx76g2 xzrRLtXmW6/6R+gRaI/UFlmnw2O7PVpbar0B+6mw3hKl2mrrXHusdo91oT0hbJhatXW5PVmrta60 p9HfRfsWrcHGgqWDq7dnI/O0ZpsibODthcgSZDmyCl9lN3Kf1m6L8g5pPbaN3hFtwBbvHaVG3a7R HrAlrbX1SBP9fbXbtN14JMGH211IP31X7SHtUVtqewjbh5BHtCdsGd6b2l5bFvgwWHH7cW2/LTfs wO09yD7kmbo0cyYcq7O2AuA5Smqt7YPI89phW3HYVNsvaC/ayryr2jFbJRD6oWfCtitsre2XkOPI K/RX334NOROm9qptL7goGGn7rHbaVgfmCV7afkd7w6YTE7S3bDxwzmYB5zxuc4Jb0u/lLnJJu2AT 2+/XLdmC8OumZ+YZ7bLtIFw9l2xw/tSu2I4FiLrXdpJeEWynAlwDazvtG2tQ2AYCyoYo21AgpmGj bSQQ1xBvGw0krp3b8ezdkGS7HEhpSLVNwtl4xTYVSG/IoGfChizb9UBmQ67tZiCnoaCFDeQ3FNtu B4rCDtBQZpsXZxsq6VWmYRc9bzfspdfohjrbYqC0QWe7F6iAqzNcbRt42ypc9eCsFaje398qDVQ3 WMzdgT37i1ojxTsNztZo2L+I1+VAayzsJ9iaAPs/2JoMPNyaBlfzs61bYM/HWrPhFU+25gFPtRbC 655uhXNgw0BrOfQMtVYBR1rh7NcwSq8UDZdb9wXUDZOtGjgm4BL+1YapVr1/hH66gLbheqspfKYN GBputtpgP7dbXb5EekUOmBvmTbqAvWHRdDDgabjX6g8EGlZbQ4EDOmnroUA3PW6Bo7ifE5rJ1iOB Xl1k6/FAPz2HB87qotF2wHkC55DDn1iNKSNwETmGnEBexfcwHaYutrVHvKJLaO0Tr+mSqY1QMwnc 0KW1ngm34XpHe25R3wjM7deaVwJzui2tg2GvCCwgl/FTrOiyW893sLTdocCeOV1e6wXxrq6w9RIY BXhFR5SupHU8bBGBG8gx5FX4Lq6I93XlrdeAVa0z4St+YIWyY6Nud+ts+CrfEa/b13rHR3Sa1rtA 6IcefeuSj6NHryMJmYrMoNepjixK+NRInan1Ply74Qrekauz2QlcqeE63lGgc9k5X5zOb1cCQ/YY uIqV2eN8KfQa3VGMLMPjMKY7ZE/0cboj9hRfjO64Pd2XqOuxZ4qDuj57TkelMd61GtIZk9zSYI8x 1R0JzHBHi/uMWe5YMduY607wThkL3MkhHtZJg2eL3VtCFmOZOxuerXTnQc8ud2HIadzrLoFsKMVd Lu421rmrQqI6zr1bLDfq3PtCQSPv1oQOGi1ufeiwOt9tEk1Gp9vWcd0oul2hY8ag2x86Gc4O1BXu kBgyHnQfCp0yHgb/P2085j4SGjCedB+HPM7g7vnEw42n3H2hIeNp9xloD7gHg5HGIff50IhxxH0h NGocdV8KXTZedo+HJo2T7iuhKeOU+1roejgDNRD3DORc4UwHcwrjdfds6GY4yzPehJ5C4233Hci5 6LX+tmGP+y7whnspNG+cd98PLRoXPSQ02jRL11THeDixxHjPowzdC+dZTTZPzIN8FnNM4yrNKyET PEEzPk/cg1dXexKBmCvxUk8KZEzhHOcc5JiH+Eh3X3ta05InXSzhoz2ZoVU+1pMDeRYcgS4pn+DJ D7tKVySf7CkSTXyap1Ts47d4Krqi+WxPdVdsOB/k8zx7uhL4Qo+6C/PxrjS+xKOFnBoy664ws/ly j8E7RTPorjxkIaWvGtsl+CrlYfJVHrOYx++GnKuQ3+exiyU0/+2q4jUez1p7N3If9aUuzdqRhOy1 S0/p30jfVcdGXu8JdJlou8uGdPEmzwFRw9s83ZC9Qg7b5eddnqPhjLUrhDyEPGLweE7AEfN7eoEh Sppjti9Rdh3nD3n6w3llVw9/xHNW9PPHPeeA0A89PZ7hcI7Z1Yc8gxykFtd1HnkBeYnv81yEzBHy x65x/oxnDPJEyCK7rvCDngmxhz/vuQq84JmGY37JcyM0hN/LNeQMjIpb7S5+3DMnhvgrngXxOH/N swxrznhWxDTdGXt+xy7MHfB6hOeuJHFGN2gv6tirO28v7ahTH7BX+Fd1F+zVNL+z7+nQ6S5RQlvd wevG7doOC9DwgFfs5g6n7prd3iHqZmCra+GcTjdr93QEdXfsgY6Durv2Ax2HdUv27o5jugv0/Enp m9bdtx8NKGl21nESeWr/HvsJcbaR2Hs7Tjdy9v6O0+ph+1nfXKPSfq5joDHGPtwxhBzB8+ToWm4F 7LjcGGe/2DEZzrMaE+1jHVONKfaJjuuN6farHTcbM+3THbcbc+w3gJn2Wx3zeM5cRN5rzLfPdawC F4LSxiL7cjCysdS+EowMX1MaKxxsMHqN1Q5FMLZxjyMqmNCodmxsT2vUwvUopdHgiBezG82OpGBy o92RGkxr9DgyglvUC44sX0xjwJHrUzYecBSIfnqeDJygDGbXsnA1hLajOHAibG5araMsmNfY7agM FqoDjl3Bksajjr3B8sYTjrqOXborDl2Hs7HXwXcEG/sdlmBV41mHM7i78ZxDDO5rHHYExX2NF+3V Qc0/7G3McTCob5xwHA6aGq86jgVtjdOOk0FX4w3HqaC/8ZbjdDDUOOcYCB5qXHAMBY80LjtGgscb VxyjwR4967gMVDgmg5o1RjmmxEH9Rsf1YJ8+3nGzY0qf5LgdPKNPdcwHB/UZjsXgeX2W417wgj7X sRq8pC9wSoPj9PsNXtEXq1eC1/RlzsjgTOOwE875+kpnbHA2/N3pdzkTgnf0e53Jfqe+zpkWvKvX ObcAeWd2cElvceYF7+udzsJApnrCCY6hF52QZ+mDzqpOoj/o3N3J6Q879wGP2Zc7lfqTTk37ff0p p947pT/tNHXG6Aects44/ZDTJebpR5z+zkT9qDPUmaK/7DzUma6fNAXb0/RTziMdh/XXncc7M/U3 nT2w5m1nX2fO2qvMO8905usXnYP+Ef095/nOIvWBxjHxkn7VeaGzVH3ReamzoknqHO+sbop0Xunc 0xTtvNapborVx3eq1dPOmU5tU4JzttNQyzrv+FKakp13O81Nac6lTnvTFuf9Tk9TdhvpDDTltXEB ZVNhG9d5IJz1N5W0KTu7m8rbYjqPUnvpPEEtpbOX/hWlsz/8i8O/YFRTo/DN/ZdfhyX8t4LwXwY6 zzZVtcV1nqPX985hmoN3XqSjsXMs/Nchen7wTTfttlfD/vFvNU372hJ9/brxthRf/9pfb+jfVeaa NKbUzonG7rb0zqvhrL9J35bZOd1kgt8yS1iyiVlgPiSE+YhZJixzn/kbkTIfswzhWBnLkQh2Hask 69hodgNRsY+ysWQ9G88+Tjawyexm8gibxj5LHmXfZt8mmySlks+SOFml7PMkXuaSuUmC7D3ZeyQx ShOlIU9GaaO+SpKijkb1koqob0a9R74U9Zv1MuJfH7U+i/zL+uz1+eQavJsqIsXZk1FkPYkgG0g1 WUd2kTryGtGQr5C95J/IIRIg3eRXJEh+Tf5IxsmfmEjyG0bJqMjHzHrmUYZh4pk0RkHvYmQ2MXuY BiaBaWSCTDoTYo4wpcwx5m3mC8z3mF8wX5K8I3mHsUktUivTKhWlfsYhDUm/wrikb0rfZETpW9J/ ZnzSr0u/wQSkZ6UDTJd0SPouc1D6Q+kPmW7pT6Q/Zd7E+XFHpFelv2Lekt6Q3mT+WXpb+hfmhPQD 6QdMj/Qj6b8z/5Pe08ackm2SbWK+Jfs9p2D6ufXcFmaK28ptZZa4F7hc5iNuO1fM/I3OAGA+5l7l KlgpV8l9keW4NzgtG8U1cTybwJk4F5vEebkQ+xz3Ve4Y+yJ3nOtjX+K+zQ2wZfRee7aKO8/9mn2d m+am2WbuOjfLmrnb3G22jZvj5lgX9yG3xLrpXVOsj/tPbpUN0rum2JCclUewXfJ18jj2TfkT8iT2 6/Jk+Rb2G/Kt8kJ2QF4ub2Uvyj3yt9l5eY+8R6KU98q/JVHJh+TvSh6h/96TZJN8VP5jSYL8J/IJ SSK9d0eSKr8p/5MkW/5n+YeSXPmSgpXsVBgU9yTVEZ+JaJD8cf329duldE6UgYSASpJIZwcXsRBR EPEQBSSVv1HsKakqHuNvFZ/l5/gFfvmzs/yKwBbPVRUKWUKuULAzVygWyoRKYZewV6h7tf/Vi4Ji 500hauflnbeFjUK8kCSkChmvXtw5CmNLCiN9AUf6R4RhPmY+JiyM62icS/oE3h1K2O+w3yEM+w77 Djw3wP4LkbA/YH9AZHh3KMf+gv0FUeBcoAj2V+wUicT7QpV4R6iK/SP7RxKF94KuZz9gP/jk3/WR MBLmwb9mJpNwJFailChJnCRWEksek8RJ4kg83r35uCRNkkaewDlCiZJ8ST5JwtlBT0kKJdtJMs6m SME7N56G969kYvDIURK+kLj4Qr6EBwfjd/P7eA2v5028jQdz4v18iD/EH4E4zvfwffB/ev4MP8if 5y/wl/hx/gp/jZ/hZ/k7/F1+ib8vEH5J4Pi7gpIfF5RCjBAnJAopQrqQKeQI+UKRUPoPy5hQIVQL ewT1g0UrGASzYH9o8QgB4YDQDb1HH1omhKtAg3BC6BX64fGT5axwThgG0uWiMA1blcJr3BBuCXPC Amy1DHtcEY6aWMFgUpii4PMzEYPwHdI7GGAUwVmDHpM4WCQkARYpSSXPEBnJgEVOnoeF3t+dB+eX fFgiSQEs60gx2Ykz7D4H557w3Lo3yB6cW7cP9qeB5RGig2UjaSEW8ihxECfZRLywPEbaYYmHs9Kb 5HHyFixPkK/Bkki+SfrIk+Q7sDxFzsKSTN6FZTP5Piwp5AewPE1+TC7B+xuHJQ3/lb5nyTT5LUkn v4clg/wJlufI+7BsIYvkr/De75H/IFvJKiwvMCwjJ9lMJJwB8/Ce7m1wBowm+XhPdwGTyDxFXmY2 M5vJDpzZVwznxEqyE/8FqxLmy4yavMLUMXXkc3h/dznO7HuVMTAGUsEIjEBeY6yMjVQybsZPquAM GiS74RzaRd5gvsIcJF9iuplu8mWc37cPzqfnSQ0zzAyT/cxF5kdEw4wxPyVa5mfMz4iOeY+ZII04 fpvgLMATgwK+OCLgPXQmRavCTprxvrkWhagQiUURUASIFee52PAuuVZFn+JbxKH4tuLbpA2+29tk Gcd+Dq20YkyESIFIh8iEyFmL/LUogiglXzSmGNONmcYcY76xyFhqrDBWG/cY1UCt0WA084tGu9Fj DBgPGLuNR40njL3GfuNZ4znjsPGiccw4YbxqnDbeMN4yzhkXjMvGFZ7lFXwULBv5eD6JT+Uz+Cw+ ly/gi/kyvpLfxe/l63gdf4/neQvv5EU+yB/kD/PH+JP8Kf40v8oP8EP8CD8Ky2V+kp/ir/M3+dv8 PD8vSIVIgc5HYGUGWQtcCr8RdQpGLAvj8//X+H4VlvU4yqNxlG/AUf4IjvKNOMofxVEei6M8Dkd5 PI7yx3GUJ+AoT8RR/iSO8iQc5ck4yjfjKE/BUf40jvJUHOXP4Ch/lkzAko5j/VM41jNwrG/Bsf48 jvVMHOtbcay/gGP90zDWWZKD4/tFHN+fYZ5gEmHc05GdjyP7JRzZBThn4WUczYU4mrfjaC7C0bwD RrMbfgNexgu/ATpz4RUczaU4msuYrzJfhd8DHdPlOGfhVRzNFTiaK5kJGMdVzCQzSV5XfE3xtf/N 3teARXVe6+6Z2TPgT0ZDDVGClBJiLBpjiKXGUPUYgqiwZ7BEPYYqQdmz5w/mfwbrscZaS6216jHU EmO8HmsppcZQQ5CqMda/Uo9VS4ix1Osl1lBjiDUeY73G3LXevQdGII19zr3Pc5+n7fe87158+9tr fz9rrW99G0uEovit8VuFZ+JfiX+F/z+5Q5cPXU3rNJjmfpCg87cKgquWsJOwm9Cs1R0gHCEcJ5zm OvFeV52/vjzvbwNtpOBM1y5/g6vR31RedCe4zrXXv798PqEkaGW4DvoPlct/G9zGdczf4jrhP1nu 6gH/7Gr1t5X7CJHgHNdZf3v5sr8NtFkZLHad93eUr/Z3uC76O4HL/q7ydYTqwAXIm4Ol5duCiuuq /5rrhv9meW0P8PPOYLnrdkAo3/05aA4Gyg8El7jFgAkYGBjsHhpIKD+igmUeW/nxHvDP7sTA8PLT geF8BZIDKeVnPh/czp0WSHePDmSUn7sT7nGB8VG9sXBPCGSVX+iBe1Ig+27ga60c6p4amObODeT1 i/yAxPCdrUxkuGcHiu4K8wLz3QsCJX2wOCAzfOdDotsRcN0NfBcrk92egA8IBSLA0sAyhu9yZRpf vRciqe62wBn3isBKd1VgdW/4rlaOdq8NrPs8+G5UjoOOjYFqoCaw2b01sO0O7AjU9kF9YOcdaAjs vms0BZrd+wMH+uBQ4Ii7JXC8D04GTt8BHvddoPxScLm7PXDO3RG40C/oXvmV4Kry68E1aNcZuHRX 6ApccV8LXO8D1ncrcK5CH9zgvhm4dTeoiA9uKheC+m6YgvFR4L6ZMCy4BXJScHtFarCufHDQjP72 QsWo4C70ISE47PNQMTbYWJEZ3Bv7fPnwYNIdSAmm9gE/OzF4sDw9OKpicvAYrjnBE/3157NQnhEc Wz4+mNkHWcGJ5dnByX0wLZgTi4qZwdZobL8jFmuxMhrjKqzBs9EYVDEneD42jnTbSey6amvSPUfF wYvdc1savBzbJ8SS2xRTyPf9ohoD/AM1Hya/8g8NrON9g+3dn0hIrpwQtWd/Gl3pPXy/QglerSgP 3qgIBG9XLAmJvL9ULA8N5HoeW8Wq0NCKNaFEjq8VG0LJHCcrNoXSKraERvMeULE9NI5jO8ZM9l5R F5oQjc8Vu0KTKhpDU3ncFXtDuTwXFQdD+Rw7WSdwLDS74kRoXkVraEHF2dDiivMhR8XFkKficiiE PZL3IN4TeA6v0j6p7WcVN2j/ic7z7VCiRwwtZR18zzMwtMIzNFSFvSe618asUbdOhranRPcC7hPv jZ7E0Frumyc5tLF7nbk9rR2vPfZl2vN4bJ60UA3XeUbTHr5LBe/XPL934KC6L2PP4v2Y3hPdi/kK kP1gbL32WL4yPOP81xi8x0b31Sg8EwImRnSPxJ6p7Y2xe+Ude6S2T0bhmUT7IK0x9j7aDz1TA+MZ sFve5yao6I5ZBE9uaCuu+aEdntmhevgYxQ/PvFCDZ0GoybM4tN/jCB1CPfkw7x/wW/Ij9iePJ9Ti CYVOcizyLA21wS80P4jGRbYt1sNxzrOC4lPUR3i9KG7x89EY2Me3evlVNL50+xbroLjpqQq1Y83X hjqiz6M9+ZtnY6jTUxPq4n57toaueXaEbnIMR0ziMdSHBU9D2ITnPi8Gaf3yNGlxPBqXbsW00fqM sfaKx93joTgcxWfGus+Ip5792vVQcBSPKYo+cTI2VnJ8jMbImHiItWc93IZjE82BpyV40D+6cpJ/ XOVUBuc2vN6c0/gnVOaijmKWNy+80j+pMj+av/inVs723AxnIY5R3uHPrZyHnIJimjc9XOK5Fh4f zQn8+ZULENN4/+e8gWPd7MrFvEf751U6/AsqPd6ssM+/uDLkd1Qu9XsqV/hDlVX+pZVr/SsqNyIn 0+IlP4vcLJo3cc6j5SjQpelAH6sqazheol/R3C6ahzl6YjAQzWG03IN1cT7mX1u5lfMd/8bKHd3P c3seD//MuSDnXDQ2f01lPeo4b4xCyxPvQO9cUMv97oA2r73zum5wLhZF77wumqP1k5v5t6r43NyM c6/Y/ItzrmjeFZtjcV/5WW4TnZPevkX+5zkZHtzHr9rCCdEcy9MeHu7pCKdwLOqOV53hdLZrT1c4 A/YUrec27HNsf3T1CuFsryk8DfLgcJ43ISwxYv3NOzxcxDHCmxKez/bpzQjLffIYgnd82AWQPTLg hxS3vNnhCK7TwsuiPsg+4ZXCq71F4XXd/kd+5Z0frmZ/85aEN3vl8DavK1zLe08UiEd0xoL/0Zi9 vvBObyS8G7opfniXhZsxTq29d2X4gHd1+Ih3Xfi4tzp8mmORd3P4jHdb+Jy3NnzBuzN8ifc/BuIk 5QTe3eEr3ubwdY7H3gPhW2ynvBd6j0T03uOReO/piBnzdSYyzHsuksTnBO+lyCieJ++VyFhu770e yfTeikz06SOTOQfk+B+Nzb74SI7PHJnJYH3YZ/g8NCxi5Xn3JUXm+FIjxWxnvlGRUsQwWkff2IiC e5mRcuiYGAlwLPdNjizx5USW+2ZGVvmskTW+OZENvuLIJl9pZItPiWzn+fWVR+oQx2j8vkBkF65L Io1sD77lkb2+VZGDvjWRY74NkRNR++EcnPMP36ZIq29L5Kxve+Q86rWY66uLXPTtilxm/ewnvsbI Vd/eyA3fwcjtbluNngOiexTJvmOVIrfxnagcyHWCXtCZj5vb8HcU//l7lH+s36NcFq72/DbAJgsu 22rbOlu1bbNtm63WttO229ZsO2A7Qnzcdtoma2UdcMZ2zubSygXbJdsV23XbLUWvxCtmZdjcCUqS kqqMUsYqmcpEZbKSY1tpW6YWJZ6hzFSsVIcy57wyRymeO1optUUURSlXAnPrlSXKcmWVskbZoGxS tijbFcXmUwu1qFN2KY3KXltELdTioHJMOaG0on/cI27J9/iN9Ab+2n/PFbLwGf9XvoYWkIdYqNyL r6EJ+Br6BXwNvQ9fQxMFRXAI9wsuKkn4JvoAvomOxDfRL+KbaCq+iX4J30QfxDfRdHwTfQjfRB/G N9HR+Cb6ZXwTzcA30TH4JjqWPO+4ME44QeUxfBPNxDfRx/FN9Cv4JpolvCf8Wfiq8D6VSfgy+iS+ jH4NX0an4MvoVHwZ/Rd8GX1Kl6JLEXLwZfRpfBnNxZfR6fgymocvozPwZXQmvozOwpfRfN2/6b4l SLrndc8LhfgyOhtfRr+OL6PP4JvoHPL314W5uj26PcJ8fBl9Fl9Gv4EvowvF1eL3hRL8JbpSsUnc Iywm7z4iyGKn+GdBIS++TnOpEyLCsh5blScImfIEeZI8Vc6V86nMlufJC+TFskP2yCF5KcohuUU+ KbfJ7VQ65E65S74m37QJNpNtMBd5hVwlr5U3yjUoW8E75HriBrlJ3s+F7UY/huzmEc1uEvB+thg9 rdHDZD1sKyLNfyZZD9uKCbYSR5byNNkQfzkfQNYxn2yI7WMQ7GMwvpbfQ+NykiWxNQwlW1hP9sR2 kEBWsIPsiS1gmPAqlftgAYmwgPtp/Q+R3fJX8RG05u+QhfGqP4BVT8aX8JG08peEFKxxqm4orfGX sLppWNcHsaLpuoW6EuEhrOjDtKIeYbQuRCuagW/dY3RraBXHYhUfwSqOw5ftR3Wv65qE8YIuPis+ u2c9yqrEe8uqehf5jHyubG3ZxmiRL5TVaGVr7yJfKttRVq8W+UpZQ1mDfJ1qehX5lk1f1kRlP5VD XGzxNjNdW8pORottWFlb32JLgoa2snatdKjFllrWWdZpiyfu6ltso8quld2MFlngtmqRTVoZ3Lu4 hrtS5AR5eLS40uUUraT3Lq4MOSP6Ltd4mYsgZ/QurixnmpxFhd+XzcWVLfvoOk3OixZlcV/tpH8a NKR3z6ykFleeXCQXuSTi+X2Lq4jGVxIt9FTP/1xaMfUutrG2TOpTJFpsE7X6yT0zES22HHmZvLK7 UCt6x+o7i20mwSqvQ6mWq21ztPpiWyldN0dHRKXdpsjb+hZbuVxLZae8m4stIDerxbbEtty2Sj5A q75GPtB3JNTnDTRHR7rLcfl0d8lWi20T27dtC2x3h227rQ42tgs20wiL2kt6DmK8q23HSOIeHYR+ VRNZiq0Rq5Thmu8qwWqV8OwrbTzRtpm2E+Q7a22t5Dk1trO287aLtsuyz3aV5irPdoNseb/tNtl7 myIqA2cmki13KUOVRCWZrmk0ox2yj34erYyTS5QJyiRlKvWY7b9LycWs7VfylfyyDm5RVq/MVuaR LvZajAgtVV9h2+woa1AWyNuUxWVVioPqO6ndRvK6TsVD0lolpCwtq1FWKFXKWmWjUqNshS83qEXZ odSzvyoNtkZbo9Kk7CdvbVE9VjmktOBt9CblJPWmjX1SaSfNHUqn0qVcU27ahbJrdpPqf+yBssk+ 2J5AtuaDvZno7nBa52p7ij1d3mnPsI+nNZ4oH7BnydlKmj3bPs2eR7O+mlbAZJfIStnmqu1FVObL 6+zZqgVSwVqh3TbYDNXZSwiyvM1OFm/3Uf1pe8S+zL7Svtq+To7Yq+2b5XVKon2b7LPX2ndSm932 ZvsB+xH7cXs1bNxkPw09Z+zn7OfIihvtF+yX7Ffs1+235M1cyuodevtORzxsdbf9ksMsNzuGsZ0S H3AkKe2OVMcox1hHpiw5JspHHJPJepezJTpyHDMdVrLgI/STybbKJcsJLpeDbEROcfko2ma7IvI2 17KyLrJgmaKAydlEkSLdtbIs37W6LESjbbZXu9a5qtmvyWZotlybXdtcta6drt2uZrJQihwUDVLY BmST64DrALU44tpW1uWcajtGujjewYLRElEGFpwmj3cdL7umVFE0PE13ZGo3nPymyHWGpASeBTlF CbnOuS7Yt7kuua5wFJTV+Dee5wpz1uy6rrS5brn1FOemqbHOHe8289v4Te5hsuRO4mhGXOROcqe6 R7nHKonuzLJO90Q1ciF2uZQ292RlqdzsHM09ccwh7Ww7zY5iR6lscihcqLdp1O90RznbhyPgWGKX HMvp7irYhCSvdqyhsoFWfLNjk2MLrdt2R528zbHLnuFo5GcdjXKtYy/ZTVFZm+OgPctRTmWv45ji cZygN6bTuM8rou28XORodZx1nHdcJO/pcFx2XLUtL7smZ5dttKcr85RE6tlO3LnhuO0U7enOgc6h zkRnclk77QLV8k7Hdnm8c7RznHPC4mO2VtppfLYbzklyFmnOdk6l9rmy5Mx3znbOcy5wLnY6yGoz yBpcFOt9To8z5FxaFnKukNOdVeTHFHeda+27aYTD5WolmWxko7NGznNude5w7iDvkUhnvbNBvkC2 s5pmr/aZi8798krnIWcL8Ulnm7PdeUiudXY4O+0uZ5fzGrVOdN50lFLqa7JnuQTylSzXYFeCPct+ BdnUI/88Z/7DnTMVwYN/4ZDI/62GRSmCblGJMGxREpVUKqMWjSqWiqVFYxeNfbbt2bZFmYsy+Vo8 v3j+c1XPVaFuIpXJiyYXryxeuSiHykwq/FwWleri6kXWRVZ6j9680fwCvWMozjUCzjV6nGgMyHxF nGiMOMuYkPnG4SwTj7PMAJxfBuH8MhiZrxmZ7xBkvkNxcrkXZ5YvCLqhi4eWY0z4N4ilGwRdaR1d N9F1l3jvrKGl2+8G+bvpmkhI/gykqcg/omLW6LvEOMKEfjBJRf45uk69O+RfomuuhnwNs1Xk56nX Aj0hnuR5hAV9UTCMros/HwWphFEkOzR4CKFeGNcPlvbCir8DVYS1/WBjP3oZNb2w9e5QyHO/g1D/ GWhQUThVxaymu8R+wqF+0KKikNft5N2hkNe2TUO7hg4VhbPVq3UmrXs2yZ2Err4oZBu49vkoXKDp uKkiXyCYemFwP0joheF/B1II6f0ggzC+H2T1QvbdocBK12mqf/QLulcwh1CstZPuEkWE+f1gmqZT oWvJ3aGgnK5yDFwxiLZZol2XE1aR7Ot5VywK1mhy5PNRsIGwqZeOZb2wsh/ws1voupqu27VrXf/9 +UysI1T3g82Ebf2g9k4U7Crtid+x8TYaL6NxrLEnvhTsvTN+dNtJ7LpG1yU6Rwdj5vbYnX3qjimx MSDqw1H/4j1Ds/lC6sMdNl2i3i84QWglnFVjBO8vBRfVeh5TwWXC1VLE19I1apwsuF26XRJLsQdI A0vV+L5YtXeJ50SLzxLtaVKyOl4pTZ0HabQaL1knQ2K9ZAsSxUWJ5k6iPkisd7Y2v9H55P7zPhnd w/Jj5pn1OFQdfE+i/UIKaf3qvU691qh7P4muE4+V+7JU7Zu0Iub5xdr68c88rtna2Kq0usQYpPWD 3vvypH4wtbRnf43ZY7sxLwa999jofvnf2SerSu/cCzeW9uyBMftdd8wiSPXalfYtqUmrp/gh0Z4k 0R4k0f4jndTqyYd5/4Df7lL9SaJ9RmpXY5HUoflF1A+0uAjbatHinCvGR66qcYuf746BvX2rl191 x5eob13V+t+lrfm1mOcjqr9JtDdZBLXfFtqTLLwH5WkxicZgoT3IMlx77vPiT+843l+baJ/7icfd 8MXgs971efF0dS/0jpOxsXJzaU+MjI2J07Rnq7V72WqMLiT7KdyognMbXm/kNTVaHdmKZSfJHMe0 /KWQciNLiRbHaE0LOSfqUuOZheee50vLCQobtFjG+7+gxTm2P9qjC0lfIemzUH8LOf/hvIbsrJB1 ch7TqcVPLV7i2UmlPXlTe08chS5NB/rYpcZL9Kt3HO4Vg7tzmGgc5nGyLr5PNlV4M+b5a+p48HO9 5ic0ttmCVrcjBg39oHcu2NIPtHntndd1ozMGvfO6aI7238nNUkrvzL8ySnvyrpgci/uKZ9N75qSP b5H/WbL6+pUlu7Q7x7JQvSVPjUXRdhZJtWtLkWZP0Ti2X/Uri+ZfFoorFs3vLORjloiKWH+zsF9x /UrNPteV9s1jCJZqDZtVwPdY/zbtWtvjg+wTFtrrLM0x/kftLAdUf7PQHm05Tjit7j1R8Hj5jMXz xGO2nCGc03TTOCwXtHFq7S10prNcIVwn3CpFLLLqCXSGs5oJw9T9j4E4STmBNYmQqsZj6yjNTmkv tI4lZBImqvNlnUzIUc8JVqs6T9Y5ansr7R3WUoKi5oAc/6Ox2Up7gDWgIVPdZ9i2rUvUebdSDmpd pdqZdY06j7yO1g3avU2aji1qLLdSjmil/NBKscdK+ZiV8jAr5VVWyqesJ9T5tbZqcYzHf1a7nlft wUq5kJVyICvtEdYbMfZD7+R8wEq5UCHlQoUDtXot5hZSPlCYqK0f+UkhzVEh5QCFo2NsNXoOiO5R JBeOU9sUTlDr8C8z4s2D/vkvM/7xvpiJGeIh/u2qvkV4RRDiUgmjCGMJmYSJhMkx1xzCTIKVMIdQ TCglKIRyQoCwhLCcsIqwhrCBsImwhbCdUKdhF6GRsJdwkHCMcILQSjir9eG89s6Ln3G9TLiqgdvf INwWhHiRMJAwVO1bfKJ2TSakEUYTxql6uq8T1Pvc1/hJhKnqmONzCfmE2YR5hAWExer74h0EDyGk 6V9KWEGoIqwlbCTUELYSdhDqCQ2EJsJ+wiFCC+Gkdm2Lad9O6NCuTdpzHTH3OwldhGuEmwI5K8HU c+X5GUCePCCBMJyQ0s/Pva/phAzCeEKWOpd/F8beiQHZGqYR8ggSoYgwn1Ci1fNVJrgIPkIk5vll GlYSVqvo8451wCsFWwt2FNQXNBQ0FewHDhW0mEwFJwvaCtoLOgo6C7oKrhXclATJJA2WEqThUoqU TiVDGi9lSdnSNClPkqQiab5Uwr+2BnxSBD8vo7JSWk1YJ1VLm6VtUm1Bh7RT2i01SwekI8Bx6bR0 RjonXZAuSVek69Iti94SbzFbhlmSLKmWUZaxlkzLRMtkS45lpsVqmWMptpRaFEu5JWBZYlluWWVZ Y9lg2WTZYtluqcP9XZZGy17LQcsxywlLq+Ws5bzlouWy5arlhuW2VSQMtA61JlqTrWks4+fR1nHW CdZJ1qlUcqnkU+Er/8zybCr88zwqC6yLrQ4qHioh61LrCmuVda11o7XGutW6w1pvbbA2WfdbD1lb rCetbdZ2awftDCP6/UsMgvaXGOLxlxgG4i8xDMZfYjDjLzEMxV9iSMBfYhiGv8SQiL/EcD/+BsMI s2wOCw+YK82rhUfMPzPvFKaYG8yvC0+bm81vCLPMh8yHhUJzi/m3wtfNbw/RCc8MMQwRheVDzEMe E1bgrzLs+P+4Zzpdgs6Df7vSzP+97QdPaiAvf5C8+kHy5gfJix8kL37wWozMII8mZ0RdOnlz+mC1 Pj1Bw3AN5LXp1DCdvDadvDY9S22bnq215zrysvQ8TZek1RdpmK+9l++VqD+ny8KYghoqsR7F3MQ+ FeNRaun2q4J2aTD5hcDeVdAA/4r1rixJorUagr/AIeBvb+jxtzcM5og5Iojm75vXCEbzD83/LsTh 73AMNv/EXEvr8Ir5VWGkucm8R0g1HzD/WkgzHzP/Rhg1RD9EL4weYhxiFL48JHNIppDx/1i77vaz 4lPEK4x+4kGQrZAHQH5Mq88jnmAMoL4U9T+CvIY40/gq5DzI6rOPQbbi2UeJx3H9JzfEcujhZwdC f6r4OHGx8Vn+d1DGJaifRpxrDBJvRJuX+b2fNLD8yR/Qh2rUvwT5cfAEvPdxjVnPdKMXb58Gmd/+ qTiG5By0mQx+WhvdGLSpQA+fQv+fQP99eIrlAYbr6FUyj502Ypo3Iz81EqOeb3QTf03TNgTyV6Cf 6wejJs84BfJTkNWWWXgvedPteMg5kAeKk1DP4xJQ/7RWz3I25FzwILTMxfz8RXyS5EeMTvR/Ep5i eZDhKtqM45nBehUaXXh2DeaK5cGGP6NXI4iHYUT38bzR2Eshc0sd13/yAVbhA8yqDvXTwXFiLY8a fC94OvhxtBwkTgTPJv4qj11faJT5t9nGEuLv8Fj0IchTwGd45vXLuI1OD34B7TOZDTLavGBcRLwD 2u7lGt3bLOs+wt31aP802v8Q8jDo+Qh8Hu1vir+ler14mHi22Mr6WdZ9iBpZfJs4m9sI15l1M8F/ Be9jNhjQcgb0PMPtde9CQy3kX+DudLT/FO0zIF8EHwS/hvbvi2R7+nzjr0mGj+hNxjdIvs31ulJj C3GHSLakT+I2wvvG54n/i1l3UashNmRCTxI4Gc+WgdeD7xc/xd3nSP4ds74d8l7wSfALYjGvjul9 4h9o3AiuA1eBu5jjhtMbb2G2X0fL1038d1w2Qp4C9mpyHbgKzM/OQMvruNvBNYaBqNmFmq3qurOs m6BxI7gOXAXuAvNTM9B+J54VwJnGHxPnYt3/ipqjGvNYdkA+A76syY3gOnAVuAstc+g0kW6sgo0p xM+h/VPgx8ADwA+B14P/C/xrjRvBdeAqMGv+X5i9H3Ibw5vgFk3mMX6EZ+dqzM8mQE7m8ereNx4n eSR4kia/BPaAF4IPgy+Tzvux+jfQMoFZd0nj52FRB9nSUHMbGhJYA8mHIT8P3zkOPgxWa5qpzVfQ qy8ZD8ECWcMAZpI94IWoOUXyT2Bd52G3r7BM1nscfsT1bjqT6HQWtmHqjzouHtFRtnx9MmqSUZOM HiZjjMnoj8Q9IWuvp5EuwUi/Dc07wevBezQN7HF+eNP9pvuoZiLqk6A5CZqToDkJmpN49sgrWX8d WraDr2gytddtgf6T4C5N9iBeYXTgX2LGWjCW1+L4LV7wFFi1zLJhIGp2GH/F9gP5IVjOQ5BHmr5G PJ6Z1oV6q0ON8Ck0S7ibj7t7cfck7u6BjzfAQ0eBU+ERjyG6fsc0mvhbqH8P8fAa5A28b+r+hLh6 jxqNuaVw3Wij+i8goq4EfxMzthRtxsIH34L8RXCtFoftVA/9+hHgOOY4WI7pZZ4fI6K6uIzHYjrO smkqxvUj+L4MvxgIS/tPZjEffnQDNRHNi6vgHayzydhA7BZ3cjzBeE9gLC+gZSG879smjvb3QP4G yxRtOJ7MRv0OLSKxfC/azIW8XvVctP8TxnIIOjdAfxze9QNEpA7wo+hVobGTZ5uZdh9m1RIWms4Q b0HLKZCvo/0uLRKy1y9WoxnXGzZhHjbh7lHwU+C54AHgkXF54Hq8nWvCbEUUVVjOBWdD80OQv6Lt OFtIHg6/OIWaVPBZ0wNsOdhNXoZn3cM7iG4u9qYw7xS6FczGm/CIG/yUMRs+/ilqJPAoeME11mC4 H/41DHvZ+LiJsDq2gd1YLwEt34fHPck+SNbejEii8mF4Md/Nwd0yRKGfa97K9eNQfxC7WD7rp3V5 A5GQLWo8dswG9OFejMjAIzLMQJs/oeakSNmjbhpq5mAeLpk+Jr6Op0oQo+ag5iKi1sOmt3jn5Z4T qxH1ecQWftd28HrwQdPDxL82/YB4Cv8X53W/Q+Rpx929GnvQQ5aLTGNw9zKiCsciC9ZIMZ3iXqG3 L3G2oPtP5AxJWJdPUP8qVm0ks6Du7x2ci+qtIus/IZqJOzm7049gFrrwRj/G68MYt3AcMDyGGPJl ZkOqSDX630Dzi2j5Y2j+n5CnQ/NxWMVx1qmbyb0VdqHPl8BzjQOp5q/IQ2ZD85NYqQzoOaFmJpzN UgbF8jp4ymrkdZdEB/rPtvog7tagz6fwrlPQlsRjFH/P82DEbIgfMxtCWOVE1mZ4i2XxSci5GGkX +v8xItjH8Osk9PZ96NzLPTRMwKgHaL3lnqRBHivSyUV3FKN+XaR8W7iCvh3Ds7vRZpLo4oiBp4o4 H9YXGT4g3ig+TZonYwV3i4vZtvUvktwKbe9pzNpehp6vaLMkkvwuM9nbSIHzVZoBQxzm4ad4ygde B0voFHn2dqLmZ1jx0dD2LHooQQ5iBl7CbE/DSB149j1wO3gWfL8DY1lhXAx5AFsF76QC1kvYAp1u cCl6WwSdJmM1xxPNMnm8QX6v8CLa3DSlMxs/Ar8F3of6NPBM0nBSzdK5Je2DzJOMbyPms5yr5u3Q cwp8FHqOQs9R6PkD2stoL3ON3oOabNRIap7PMu10H4HfAu9DfRpkbn+PehbAW/apjGxzBvTM4Gf1 z0B+RpVZD/E+1KeBR6ImGXZ1GDPJOt+FtmvgWvAvwPUi79fToXM6dE6HzunQOR06p2OWprNmQwa3 NGRgBg5Cw0HIr0F+jUdBs7oF/Wf+pTpelqlvW6BnC576CBq4ZiL6+bHG7B37RO7DbOOj8GJenedF 3kMPaOcpfsthsQ2+jPMUtxTUs88FnIZG4NyUB/4NtI2A/uvgNnA9np0HzsWzTah/D3xcJLs1pfG4 THXMooPbiCeMeygC4F0mn5F3wGLMlQcz8Fe0N/Osmurg74+ht6dgJ++C12knu7exOkdgk29j1d7G zMA+2ftoBkbxShnvJ96MU6QeLVPQ8hTklXh7tmpvWIufcY3BgJUyoH4G2r8L/hhcCz6C806t6SLe wjWf8rrQ+rJ8UWOsNeQm1XK4hixhJlZwJlacTu6CbPg9ncHHGwcRh0zfp7M8/PGTd40bqf2LyOta eE7EJ3gnEstYNrwK/nfU13L2KL6MaIn2lP9z/vZFPDsL+ZsTLd/kE7p4lKO3ASduwzNGioHiUNz9 JZ76CXPcA6hPhIZb4Hq0L4GdLOO1MLzGc2s4B3k6+HFmMZXXSEyDbVSh/RuwqHeYjdvR5nFYRRK3 NHwPK/sBZAfufhl3h8NacqBBPd3Xg/PwrinIXl7GnpjLM2Z4FztLFaLlIewmRzirMWxF/rwWe9M2 ZsNS1HwH2VEX9OwHt4LfAr8DPRfAJ8Bh7FnvYOdtYja+CXkZWM3tr2Nv+i6y4jHID9/R5EZwHbgK zDntO3zqNF7C/M9Ay8HgJ0z/SqyeRpeC92hcB64Cs4ZX0RJZt/ga1xBzjZVrjAtgFcXIWsPgWeAX cJbxIPP0IcvNRb69g7NQcRSs6Fd4I9obqjiiiqgh5rF0Qv9DGjeC68BVYNJm/DKf1k1vwHKOGhPp qUHQthW8CPw2dA7DDFRCbtS4EVwHrsJdHl0lz5i4j+W4kaYfg+exfjwlasyzdAr663k2DFOQDS7V +CWwB7wQDIvijM40EKv/DbTM5QhpfMh4lOQPjW8S/xj1bRp7wAvBh8GPstXh7hHUHEHN9zgTNrzC fqr7N2TgKeCvgcPIOVNxdnsCOe1Y5MxrYVdh2O1azg/1udD8S8iVnOvqd6Nvf0T9H1mPOAv9P8c1 4gMavwT2gBeC2cse5l6JX+RzuumnquWzX+gvQNsg8FZkC8vhTcNwQvfCCzbj7jsavwT2gBeCD6MN zaf4JX6L8U3+AkzMbXD2J2ZZ/Y5xHbN01lgHj0jhuyrjPH6RT9xiJ9cY93FPxEbIH0IWYSci2i81 vo9VUJnP3b/jczfNBlvFCXE5+sYWK0Deg57vwV01lk4GDzIOIxZ4vYwjTIUkb+N645dgyX8EV2oR lePPXkTU9WizGu1/Br/7AH40CHF1IuJwDeRfcRwmu6KnjAewLkegswmRdgM0u6FtDORGPrOLJbjr Qcu9zPH72MLjcUYz/giab7O1xKkx/7c49VTBQy/Bg16Dd+CkT/7LMeQX0PBTaBPE79BTe6Hnde6b iDM4RapWrAXvpGU4cftZJg1d4Fb4dRe4Fd7aBW5Fb39JMr5bik2YpVucCRheRIw6ChbRt1/xSVz8 D3CA2YDvQoYW0yre9eDF6yG/hvYv41l8BTVUcY1J4WhgcqL+TbQ/D34GvNV0nTluPu93aPMTtpy4 ByAngh+Htltoj6+m4kDeI8QE/iInPmpMgv2wrOe+GS/z6osJ8J2l2rcyL/bKY2wnXC++q53W+YRV hxPQE/Dr6bxTxOVh7d7CSj3Jsmmg8R66ewM71x4+L5P1ckzI4btxedhftrI3UbxqBh9GXGoG8046 E+fuMag/h/pzqP8Q9RdQ/w7qi6Htj3iLei5biv2xFbyH32s8zyMy4Tu2oQEn8W3Y6TbhPP5rPndT lFuIGf4Yfea49ASfwU33wOu74N37mUV87aQ48yh6wnwCdwchOxpkehLx8BP4wkuIGHx3GbhKix78 1NuIG2/weZza1KC+Bv1HvDJ9i+RG9Plp8QHi/8EspmL+d2Gkf8DqhNBmrtaSa1JwJvoNj1G8l0/Q BpzWDeqZ7gzOdMcQk7+JeUjGuj+inr5hLcONFItM8XjqY+QJr/A53egQ6XwhrkWMLcez5Xh2DeRa fpf+q3hjKdblZZwNv4uTbyt8QcTofsBndnEMevgsWuKEa0B/jCshL+Uzu6ECstrGDQ1Z4G9wvkR5 I/vjHvF+3hHQt/dg4eop+19gA9Mx6kcNe2lE81mPKQBewixuFX+BmMm+8BTLxogxgl7xTBahjYCo tQ9xzMh3DX7ev4w66BmKmd+DHv6Ez+OGs5A/5FO84THI0/kUb/g5xjKEe2KE74hzxRFUswX9X274 kPhbBrIB8RL/fs30H8gJn+NTPI2O+/MAn+UNq6HTrzHP4T3guXx+N+4B/yufIwz/m8duSsQMzMSp vANPlfD53XAf5P24ew39+TN62ID6v+C3P6k8M6bRePtk8EKM1wXO0nJL3k9H4KnjfJbX/57P8obv Yn5G4PvkefTwOfBMrM73sI6zeNXIbon1v0BNMvpZg1PMevAUVcYJZT28bD1OOuv5VEV36SRifBgZ 9QG0/Db4NeN3EAlZNoNnqQwNs6BhFjRMR8sunPXGcI04BjVvo6ZGjPCXCpyU08GrcF7+Os7LX8cp 7Amc737MZyWyBGqvV9DyHbwxEZnnI9D2CD8r5kB+XmXUPM/aiPehPg08Ens6zYzxFEbnEOlUaNgM nU9Avzq6yeBv8tmT+o9RQOcY6ByDkXZhpF08V+Jc1mzKMZ4Gf5utCBp2qYz5KYWch3mYYsrHXDFb cH4/y+d3GkU+fxMTT+G9+fCgP0DDR9CWz/sU94piDvOL4kPEC8QVVB9BLMV5mc7XfPd74GTUTBZX kuwRuW+PoAaRVhyJtfgA/BdmQwuz8QSz+Aj4eX7WOA5vuQ86Z4AngbdDW5U6V9DwIXg0ZrgS7OZY F3eUZyBewnzewLnPid8muFmOM2G/e47vGh/GDLegZQ7kMpbjjrK2eIlzEuNtnAefwLhU25iIVc7B umyGPAwastHm5/x9wFDC8/9/2Dv3OJ+q7/+vs9c57zPzNvYZjDHGYMg9uZOQkKKS3BNSrqHBuAsh JCTJpVRIkiSppE9iSOVSckvuJOSWu3FpDPOe716vcz6/L/Pt8fj0+fX585NHz7PO2muvvffaa+/z fp/3eb/HTsQsfIrcKCbXLz4ho+OPIcdCHgmbQ+BdqFUcjMNsxktdZ77MuLMA+qqw/ACzPFFkdQ6a e0I1QHnn3guWBWU2TZ68iD1QuB0+l0AuiT7HIYbDRW8sM9DbDKxQeTKhb/aHZFGZ7B/kCYfsj+Vz fLA3+ARYJ/sDwy7ZZaGfIE8UQN85sPwQnA8Pw1BrGDQJ4GuG7wYelqLFpdCflucospeAv6CusE/2 XsPHRK+aZ8sd1LvAF8HB4H3gXnCk0FJCugJNFZCE3B3yTHAhmCeQ5ZOIPah7GZrXwAdQ61XIcSg9 DGZCg1ZUC2guQPb910Hr18B9KL0OroY3hs1DYGvofwtk6cMiaD6GphHkbNQqB/kE+C34BXgGlk0g Z0AOQY6ACRH5hOJopJy8VkR/YE+viYb9yCSBiaKxMGrrcXAb9Achp4HbYeNHr3mkvvFQDXJLkdV9 YAo4D61sh0xC0weRu4AzwYURedW6Fp5/h83z4DcofRv+Z/ljhFwA8lTYRGBTDK18BTkJfVuO0p9g eQr6scHoYJMdZfwM8+MAy4eDuiZKlIFYjYK+SqQpxmiu7yq3kI5BngD2FFq7wKvgddh8BzkC3oTl MrReCkwGK4Mn0UM/P6dBPg4mRhoYtoKcD/M+zs9Y0aulkMtH5N36Lsi1oEfOKFcYQh6Ghgjtr+Ah SyIT6i2yswmZMAFjPJz9tnxaCvuX/cyBt2nowx+w2Yj4NJeVa1ZcAlaHcCrsi2aZVz7WDYz0brAp mAI2jCgwWUYnNJEUNkHpSHhuIhqTJ6IvA30VRG8veA08KqVcDqVdwJngENQqFbQllu+D34CXA1ls norIHewBkPOJnvuhdDN4BR6qY0QJ/rwgApgva78/g4jMO/7qgNwVNssR1R3+XiSxtXciwv5uEAc5 CpH8FvbfRurJXS/Iu6EfDG+DoJkjZH9nuI58zkC0X0MpcsBku/jMg7pnEP9D6H8IY9kEORHyKYm/ yUOJ/2HwVKBPhp9k9OEt9FCy9xPwK/AM9H78XwZbg53AUYHs+5RPCqbDfjn0vUHMEV3EmjqNuM0B t2TnM8zCGMPQfAa5MFZlGrKiGfRbMepTKC2IsZ/JXmQ09VA6APq5iBjWFFeGXAUeEiXOqiz0/rr7 AXwKPrvBQzf4XAFNYcj+7urnwGb05yTijJ3NsjFTteHH3423+ntXdlWJIeRN/j4My0mwvCPYh6WV n6DHGrdHY4VuhPxHdiPTT/9aNh973S6Jkl0b8oPQn4efPyBjN1bRIHZFVdzfGWCzEfwS/f8kUt0Q Vyvre9gs9/cNEPuMmoEo1YXNTtDfnZDtCtcmE1Xzfoexw1gfgP1Bf0cqA74BDoJ+oMw7t4OmDdgL +fwcSr8DPwSPYkWMCWSJhn8t64Ba2LVUZ/8ah5kNYS4SwNfAZHAbiPyxcH2xPhNSNuRVYCY8bA/m SGTE1roAuRrYFHFbBzm3H2HID4GtI9ekn6jVET6Hg0tg2RDyQeT/T8j/rVgXd4FloV8AuSbsX4Af XAEpggzBNdo6hpgXhM1q5Axksx/iczHIS6BvC9nfw5EDocXIq1gQ1z4Hr5RCReDN383uQD+/yJ4t n4LBQ3bkZYzR0NqA0tV+xLDzt8Au9DHY0c8l7Dz7MRYFhsGuwR4uO8Pn2G/joKkDb9ew86xD6QFE 4x1wdbBjiD3iZmL+Fvrjy8m4RovNaHA4+GYg+6UpiLDI+eF/C+pmwOYt8AtomuEe6VXcXUyC3DT0 uYl2TPCpkzzJMxJPQ2XhDnlZJ02yS6gW49Pq9Xgfjfts1nFbnolai3eX+ORINQzlkp0Bn0ZtFVl9 Aznd3ov33fj8Tt5rZF9TlUjudYfl6mb3lGu9/Z68IoIcb1+S/gvtkL3QaNLx7ESm0BqPWt2Fzg7c n0kEY+0RspbhoZpQzbV/wLuzS/gkVGqlgi3AeHiL2InGchkPN9zAR2XPhDxYvkul2gq5BR+S95hi SWuElkatDUJ7r5A78CtGswh1k+SuiFqGuh1QWkroNEOt/eAmcBJ4jOUTov0sMe/Mw6T/cl/CeBNN LacdbORdQJpoaJ7ItByaGZAzxd6+BvvtQusKr5XR8SzZz2E5V2ivhDwaTILmKGqdFzrtIE8C84Jt A43plaokMsdLb+l11O0l5GFCawF6wsoSOlfkN5UgK6VEY61BqTzZXtUycY7cwFM9zdQk2SXkfpFK U6/KiNRL0n/1vqx3kdV4NV4yU8nVNlnsrU/AKUKeCJvVCs+PqamG03mi4WeQp/IH8CNyHlh+hRa7 oO57kCuDrpLPsrPQeqbKJ6tbIQdUAvoZK9mu8HyCChlNfeXJ6lal5f2O2FtNweZCuipkhofG8NZa FZS9Qm2DT1/+Ta4pIltLYNkEHiKoWxTyCfAby7yjtJajD6ct+VSxgiV3Zc1+aTQ3Lfl8PMu6IlcH WVnWFcgP23HyysE6LP0RWvVVvGE+tUKua9Zx4yERzAtWEBpvhvQb5KlgXusQLA/JuoZ80BomVxb4 3KbMOwtrhnXA6BciziHpj0qCn5PgVaz3WURm3lNtUxpZEoqDfARybpHxufz80N3QfyJ6R+40vhta YNgObAieFfIp8GOhEwP9TaGywVegKQObJ4WhPbAsBzZBaXHInSG3heUJaKC3JwndIpBLo/Rr8Ao0 aIV/hNwN8miwGTRjwKFCC71VdVH6A+TD6E8INq+Bi1G6HvJnkM+Bj4FPQI8RcRbq+t42g2PBnuAu WFaDjHHxDbTYD/I69Gc3eBqa9+CtK2rVhOUm6ItBXgp5DmKyAvIQ8B2wLGq965qrT6iQPzsi22fB bH+ORHZioLkJuZ4/R9BM82dKZH4S7AymwltHf75Qy/VnDTJiErrgzxrsPwZPoLS40C0CzdfoW0VY TgZ7+fFB6/ejh2v9mIhGJUH2I4Y42/PBOmgR0bYuoRSRVGnwgKxzZoAbYD8P3AE+CmLUtp9pc9DP kbAvCQ+IuaPRB+SPKoXci4b9Mdh8BPk+WPo51gDUwqiPpG5UfvSTYdMIHr4E46AvhFGXQWQ2wX4m SrFG7J2oVQJtIbY8w193iOEe1EVs7Ulgafj5HDaV4B/xVPVRdzn0WGWOn6s90Ja/Eov4uQc/WyDD Uk1ErTOwmQ76GYLocX8/k9FuMcRqqdC6BM3baMvPw+pgbbA56m6HXBUeqoAnwevQj0dbXSC3hB+M y0HrTg1YToGfWZAReYX9wV4ADgZbw8Zv8WfQz5BVKH0WxLxwQbTYF0TkXWjsy2hxGPT+noY1aPur GyvX8aDJC2JnYGQFw5vydyrsKuoi7FHXHgh+CC6C3t8bIfM2aDZCPoTWkVeMtaPSUQtZ5/iryR/R atiEYT8bGn/e10DfAkwE0WfGnhmaAJ9+r5AV9gEQa8pGbljoeWgUag2HfSZkrER7BLgXeswpI/5O B+ixR9nYtWzkg8KubncHV8L+CnJmNPLH368Wg9iLHKwjHguNv3OeR11/TjHvjJkKIZe4PYi1xlNB ZK+7VRiFrHBw/XKQ7SFE28XYQyi1Yc/Yo/ge8DFpnUjep9jvRuQzr3ZgQ/CskE+BHwudGOhvCpUN vgJNGdg8KQztgWU5sAlKi0PuDLktLE9AA709SegWgVwapV+DV6BBK/wj5G6QR4PNoBkDDhVa6K2q i9IfIB9Gf0KweQ1cjNL1kD+DfA58DHwCeoyIs1DX97YZHAv2BHfBshpkjItvoMV+kNehP7vB09C8 B29dUasmLDdBXwzyUshzEJMVkIeA74BlUbcQ6mbDph7kaShNhdwRehfEWEIXwIoonQz2Au9HrbVo Nwk99HuO8drzwTqoi1Fbl1CKEak01MXsOzPADbCfB+4AHwX9Hvoz7o9rJFgSHjB2R8Mn5lGVQg5E w/4YbD6CfB8s/bluAKJWFEqj8qOfDJtG8PAlGIfSmZCRmfZO2JSAZ0SG0X/+HKWV4AeRUfWhXw49 stfxc6AHvPkZ7ufqFuhhoyZCcwal00HMjkIcuD/4Nrz581gdrA02R+l2yFVRqwp4ErwO/Xj47AK5 Jfyg5w5acWrAcgr8zIKMWCmsLHsBOBhsDRu/xZ9Bf05XofRZEJHkgmixL4joudDYl9HiMOj93QDZ a/vrAjnveNDkBbGmGPPI8Kb8NY71qC7CHnXtgeCH4CLo/V0FMm+DZiPkQ2gdmcDIcJWOWsgTx895 f0SrYROG/Wxo/JldA30LMBFEnxm7TWgCfPq9wrzbB0CsAhuzb6HnoVGoNRz2mZCxduwR4F7oMaeM +DsdoMfqtpEJCjuh3R1cCRtkte3vJOch+zOF2WTEP4QM4fYgcp6ngsg9dyvyH3PtYD93kKshxNDF iEIotWHP2B/4HiENUeeMnG5vJflWZhh3A6YYTYy8H+e6cs+Bx+F+wkMones4JM9FxEnu4S6KEo36 HfopeO4uhHsgtmist6DvIHR2CO0KsE+Ch1SUnhKG+kPuDjaGzXl4uILW2wZ3NkoYZsidE9UPmgy7 gvjBXZQjuItSw7/7Ac0J3Es5Cv1m1E3DPZOhsDkPDvbvn8ioVQruPLRy5Ls/1YQci7so26WUskW2 8kGT5sti48QhYsnQRwWUd9b57NnSOjSLwA1gKWFkWrbcj2qWvVW8QW4r72TVdpGtByC3Q2lDyKsh 74XlCMhRkGuh9DvUOg1NXt8bNEcj0pPysMmLWpXAzijd7ROliZAzUfomPJSA/n3oa0Auh9IQ5Gcg v+T3QWRrn98HlA4VOdIi+5qJQClolpHcndgPea7I7IlM2UKuC6ZDkwkZ7+vVr0Jnh9C2oFfgEpRG Ca0rkM+DlWBPsJkClgPHoXQw+jADcmfIi9DiGdgMg/w9SlPgJwx9d7TyLbgg6L/0pxc0K6BJAyeB GC+NieyUWYiskjyEZmhE7vglw3OfoA+inydzpI4J6SB8LgWnovWbsMzw+yY2fDgiT9bdB31D8a8u RT4w+gg1Mb2KheUR0aiL8NMK/n+Htw5iHyoM/csis4p8Zhgv9vY6v134TEF85oretCveWqL/hbIz jaYOenvVH7XYOy3Q7mTkWwXYH4Omj8SBLqLnMaK3NBiJ3DT6LUI1GGwrtL4FD4OnYbNcyPejP22R OdXAeLS+IZh9o6F2EVmVmxHheWAZjKi/n//+zPo9gf6wMAp+XKw+8+rXjDGUgLqLRXYe9OdX+uy0 w4iWB7MwH/pVeO33mdxD9rMxGEs6Zucm4pOOlZgKjdxHPQK5EjzMQMTyQe6MWnlhvw42adB0hNwH +qmIzFTIS+E/CfI3sBkA+2Xw9hQ0DPvPYRklpfYE9BNj5MbIZKxoehs9sYWhERh1U4mAPVuokvz1 hbnbHVmC2Vki+zlqRRCHwwHny9UE+itCs9fL3B1Hr0qBi8BKiMZm9K2S9M3MrJ/V6fiUQUqPgRvB 3bCsBc868JaOFSR5shgjtaFZDvsD0JyFvAA+60HzMPg49DeDmZoPWTQj0cpc2HQEV8CmFtg0WO9V TG/n+6MIck9WzRZ/r4B+P9gXnnv4eehHA/H5FKtvCXKpA2ZhITy39e1RtxY8D4VmBTQZsI8nD9GY jxyQmEcQ4Sj4fx3ezmIeO4ql6fkqmUfps3ldLR5awH4ZLJ/27YP9UFp8PTJLehjsmYR9G+Ol19G6 +NnqZwhW4j9w3/g8dZVX0UI+ld3cyG0w6tOwSUWOHZTdwJkMfXH0/+EgryR6y5Q8adYVmtHIz4rQ J4H7/b0Uu81QjFpDPxiMAhdhpBMwxlQ/ttipFiPmNaFpjL1upN+3wIPsn9Nl/zQ9lAxPQCSrwKYH 2s0MVusH+EzfX3c3sTMXRG/9q5t/fZEYNpO9yF6JUSRnj0Sph8wxDOGa5S7y9xzEvwn2nDpgZrAK TFsu1h23DeZa9pl6fnyC3UD027HSkyCPCHZOKX0b+hTkbTzkR6DvAZvNkFOhL4OrVRzyf0WwA6fL rwllH8Vu2cKUbsfMVvSvXBH5jZTl2flxResqsy+7gXmt0gJ7RRHExDBSUjwQ4fcDyZbvFgV3F4UU hj4seiLRRN6QJ8Mja+Tp/UgjyJMhPwC5d6CfI/fz5fl/o1mM0qfk2Tb5HoGR10M+D/msyPKdo0hf eWY+Mg36avIEo/HwEX7JZwvJLyalGc6SzzGpmXzrP/KgfPckMka+vRJJC6UYHnBNrazzkAuIbPr5 quE+96L0KnRMWnEvQD4g/t1TkG9AFpu+8u2SSPuQ/EbTG24nsKv8LhD61tDvc0h+zWmYa2Yz8kII nlE6NnQaPT8Mb7GwFL7g1pNn/Fz5PaIxUfKpR21nHCKzHBH4FaPwRAObN6LayTOEoU2Grwe9NSs6 8pxbC22J/rlQJvy3h/9J+C0j0Y+DvrE8nx8Z576PundK39z26L/IoyGPCX1v+LWbYdgM+pnQPxgq ZTjUbQO5LPr2BEa3R+yjXERJnlFcHBWFeZS681C3UWgi2vrK8C746Qk/T0CeCbmR/A6A8TkEfkRe jJlqFIqHxmRs5JXQVYlDQNF8AbkR5L6QGztbMd4r0n/kW3OwkSOl7cFG7p3IK5FrhxbCRvLwXmRg Wfm80sxvAcS2AHoufNb9BPpPDQdBHgu5b2gN+rAGWTQZ+slo8XNwOjgNre8Af4JmByjyAMRnAFZB VTwbQFnZRi4qTwtEcsnn9ZHKWfLLVIVBypLVUVo+649U9pll1n4kf9Zqw1LQFI6MQmky/CRDAz/w WTnLrN9IN99PlvShbNYc6GUtFMn6Dm3tNozLOg+NsChYOWsfKPtMlayThvkiDXCVIApbr0c3Ie7y XP8Uinumf7dnaUxKp4F9aAWZ95YtWzRIJrNTZmdTPMVQiJLoDspLFag61aL69Ai1pY7GRwuzL/Wi VBpMI2gMTaApQY3c5FJhKkH5qCLVoNrUwOz7T5CZN2pJ3ehZ6kdD6HkaSxPpVfyNTb+Wpiizn5Wk OKpEd5vW76dHqR09TYpaUXdKof74i6DjaBJNNdb8ULNmjalJi8ceTaburVo8kkxz4ScBv5db1Fwh SlF+qkz3UkNqTE2pPXUipnLUmp6h3jSAnqNR9CK9TK+hVpiSqTTJdbcm1aUH6DG6k6ahpCDFmtJi lEhlqABVpXvoPnqQHqJm1IE6m96XpzbUg/rQQBpGo2k8TabpQT/yUC4qToWorJGrUT1qRA9Tc3qS upBDd9Hj1JP60iAaTi/QS/QKzaCZXaoM6MKjwQngVHAWOA9c1KVTykD+FFwJrgO3gnvBo106DejG Z8F0MAOMCG0bDHfp0jvVjgWLgOXBWmBjsA3YtWtKz2fsVHAwOKJrn7697THgBHAKOAN8C5wHLuze v1MXewn4D3AtuAncCR4CTxnHnex0MAOMCB07pc+g3k4YjAXjwSSwOFgGrJDSt0uKUw2sBTYAG4NN jUl/pxXYDnwa7A6mgP3BoX3F20hwHDgJnAq+Ds4G5/ft37WPswhcCi5PFf1KcC24AdwM7gD3gocG mJlyjoGnwXQwA4wIQ6EBPft0D8WAecEEsAhYAiw3oHeX1FAlsBbYEGwKtgU7DxhQqXIoBRwIjgDH gZPBGYZVQrPBBeAScDmYBq4zrBraDO4ED4LHwLPgFcNqoZtCV4FRoAbjwETD6m4yWAosD1YBa4J1 BwzqPMBtCD4MNgPbgB3AzgMGpQ5we4B9wIHgMHA0OH6gibY7GZwGzgLnggvAxaC8Fldm78n/bxzZ rO4kKvz/JZnXZP+SjvkXMntpFH5M+D9zZuPMly1K/j/Uf5FsdrcYs9P/PckyO/WfM99fJmNGGFcS i3D3Clc4+V+Y6y8z719mkf/DPH+ZxdBfG0frFkrPb9V5/5JsrlgFzBXq35MSIClzbbrj3zqWMNfm f+cof1/9rx8tKvMXWPYv8F/HzTJX83/N2L/EqubqP9S89plFi8xrp+9pL52iDCvKSrDKWDWtxlZb q4c11JpgzbIWWSus76291ikrQ0WpBFVFPa2mqLlqqVqjtqpD6ryKsOYiXIHrclPuyH14JE/hubyU 1/BWs36lvSg/t7lPjvMxOc5n5Dhfk+N87S3nZt3w0VvOQ2bLqECudct5eNLt5zEZt9f3mtzuP+7T 28/zt7ndf/5eOc5H5LCfm+N8WY7zo7efx1fKcT4yx/nCHOdbb+9/0rXby4vkvf285IQc55NuOTfr tuTkHOWHcK7MLp7XH2HpJf6xTCpKbLOHxpudo5SvLVs+ONYIjvWCY5M/s75TB8eE4Fg8OFa4vRd3 9rp9lOXjbz+XPyxwq32VdrefVzt8+3n1TTnON99+XqNHjvNeOc7H5Tgfn+N88e3nd9e7JeuMUKtB jvOut9vX6p7jPGf50Bznw3Kcj7h9Vu8daqhNpLpYM6m7NRtXmc7mH1kzrBlyn9HJb3TyN0HZCTsx Tm6xsJRl6uJvkFr4G6RikZdCMa96MTFTvLAX8qKMJmSds84Zu4vWRWOXbqWTsq5aV4n1S/olsvVE PdFcqSWDFD/AjaVHKq+S9mLJMftEPs7Pd3Ilc+5wbjbXUo7lWLI4juNMjXJcjpgrckXTe8uqYEYU b95V9afZtIEOU6YVZ0YSZcYWF/MGqZgpMbMMX41503CqiUGsuUYkmx23knn3VserQKxiTb8r4hjj VTLH/Oa8Mo4xXhIpc1bEMMZLNpSISd4nUnGvFLEZb9grjWOMV8Yco8x5WRxjbrEsF1jeGViWDyzv Ciz/2d/X0N9p6O909PefJTNQMhMlr99a4sWih3nRwzj08J8l8ShJQEkiShS5yvwzizeXkmfhY5Wp rfKbyHPM5JhXyDa9C5GZQzOLrvFjKfmU139VQPjt806YU8JsWlamlWlmNtvKNtFylEM2/DrwG4Jf VyWqRIpSxVVxilZlVBkK80P8EOVyUpwUinH6OH0ot5PqpJJ2zLsU8pwRzgiKdUY6IymPM9oZTXl1 d92d8ukeugfF6V66F+XXKTqF4nUf3YcK6FSdSgm6v+5PBfVAPZAS9WA9GL+p/xwl6eF6OBXWz+vn qYgepUdRUf2CfoGS9Vg9lorpF/WLVBw5eQdysoR+Rb9CJfV7+j0qpT/UH1Jp/ZH+iMroj/XHVFYv 08uonF6ul5tt6h/6H1Rer9Qr6S6dptOogl6j11BFvU6vo0p6g95AlfUmvYmq6C16C1XV2/Q2qqZ3 6B1UXe/UO6mG3qP30N16n95HNfUBfYDu0b/oX6iW/lX/SrX1EX2E6ujf9G90rz6uj1NdfVKfpPv0 7/p3qqfP6DNUX5/T56iBvqAv0P36kr5EDfVlfZke0Nf0NXpQZ+gMaqQzdSY11jf1TXpIR3SEHvbk ZcIjHntMTTDfj2K+m5pcCdNjJldiqJmnTbY092JNdrXw8prsaunFmexq5cWbrGrtJZisauMlmqx6 3Esya6StV8SskSe8ZLNG2nklvBLUHr9n38Gr7lWnJ727vbupo3ePdw895dX2auO+xxizPsaYTPIs j0ZZiVZhGo19ZZzVzupAL1opVm+agL9nPMnqZw2kl61J1iR61bzWeJOmWpesSzTNumZdo+nWDesG zZCNiGaqkArR6ypGxdAbKo/KQ7NUvIqnN1UhVYjeUneoO+htVVaVpdmqkmpGc9RANYjWqCFqCK1V w9Qw+kY9r0bSt2qcGkfr1EvqJVqvZqgZtEG9od6gjWqB2kPfmz1J002uxtUowg24IWVLTluK5/Ac i+2B9ruW7fR2eltVnL5OX6uq08/pZ1VzBjgDrOrO887zVg1nlDPKutt5wXnBqun8Eppm3RN+M/yB dSG8JVcjKxLTJuZl9VzMuzHH1Ce5F+f+VF3OvT73DpWpG+umHKWf0c+wp3vqnhyrn9XPch7dW/fm vLqv7sv5dD/dj+P0AD2A8+tBehDH6yF6CBfQw/QwTtAj9AguqEfqkZyoR+vRXEiP0WM4SY/T47iw Hq/HcxE9QU/gonqSnsTJeoqewsX0Ar2Ai+vFejHfoZfoJVxCL9VLuaT+XH/OpfQX+gsurb/UX3IZ vUqv4rJ6tV7N5fTX+mu+U6/X67m83qg38l36R/0jV9Bb9VauqLfr7VxJ/6x/5sp6l97FVfRevZer 6v16P1fTB/VBrq4P6UNcQx/Wh/lufVQf5Zr6mD7G9+gT+gTX0qf0Ka6tT+vTXEef1Wf5Xn1en+e6 +qK+yPfpdJ3O9fQVfYXr6z/0H9xAX9fX+X59Q9/ghjpLZ/EDOltn84MmAS1u5NmezY0913P5IS/a i+aHvVxeLn7Ey+3l5iae+Y8f9fJ4ebipl8/Lx495+b383Mwr4BXg5l5BryC38Ap5hbilV9grzK28 ol5Rbu0V84pxG6+kV5If96p6VbmtV8OrwU94Nb2a3M6r5dXi9l4d717ugPd5Fl5PVcNee6dc+6wn rSeNupvVjSz7S/tLUm6UG0UcNS5qnFk9/92N/7sb/2d24//NvkRkn7xiV1bP0PH/5th/c+w/lGOW 08u85o+1iqtq/KDdlpKoFjWgh6kFtTPvOnqZ1+/DzOuBSTSN3qL5tJiW0Ur6ljbRDtpPR+k0pZtX 9mSFrJjoNcTRX0WvjP4ax1XRa3FMi/4Gx9XR35njSiOtw3Fl9HocV0VvwDEteiOOq6N/MMdVxm4T jiujf8RxVfRmHNOit+C4OnqbOaYZu+04roz+CcdV0TtwTIv+GcfV0bvMcbWx243jyug9OK6K3otj WvQ+HFdHf0vKlH5vuCp6q2Fa9E7D1X8jIgcw8q+iDwaR+SWIzKEgMr8GkTkcROZIEJGjQUR+CyJy PIjIiSAiJ4OInAoi8nsQkTNBRM4GETkXROR8EJELQUQuBRFJDyJyOYjIlSAiV4OI7Dfj/yr6GCJy GhG5+Dcj8kcQkYwgIteDiGQGEbkRRCQriEgkyJVsPzJh8iMTtvzIhJUfmTD7kQnbfkTCjh+RsOtH JBzlRyQc7UckHPYjEs7lRySc249IWPsRCXt+RMKxfkTCeYKIXENEbkqmhEMSkXDM34tIOJ8fkXCc H5Fwfj8i4Xg/IuECfkTCBf2IhBP9iIQLBRFJCiJSOIhI0SAiyUFEivm5Ei4eROaOIDIlgsiUDCJT KohM6SAiZYOIlAsicmcQkfJBRO7yIxLOKxEJJyAiRSRTwmX+ZkQqBhGpFESkchCRKkFEqgYRqR5E pEYQkbuDiNQMInJPEJHaQUTqBBG5N4hI3SAi9wURqR9EpEEQkfuDiDQMcuWBIDIPBpFpFESmcRCZ h4LIVEBEqiEitRCRepIp8pdWpd+4R9eWylo71DvchB/j7vwM9+JneQAP4iH8HD/PE3giT+KXeTK/ Yt67HOXf+Bgf5xN8kk/x73yaz/BZPsfn+QJf5Euczpf5Cl/NPUL+Bpq13dpuGpgr34DmR/gRUtyU mxJzV+5GNvfgnhTi/tyfonggD6RoHsyDzSuBoTyUcvEIHkExPJLHUm5+m9+mfLySt1Bc7uG5h5OZ VfMqJGwXsYvayXYxu7h9h13CLmmXskvLyEyPruJev0UJt9ybuEvucnGKWJiapQOLpFssKtxSZlYz pxhrsuNs+aW4MnYZyhW0G2fnt+PtAnaCXdBOlF9GNBb/2658AuDZee18tmOHbNeOsqPtsJ3LjrFz 29q8hYi188jnH2Zso0wXpI6y77XrUoxd365PcgemBiXwQl7ES/gTXsfreQNv5O/5B97EP/Jm3vJn EZc7avw+v288fiDfHeeP+CMT76W81IxjJX9n2jvKZ/6f9/eN1UemdCWv4jRezWv4a17L3/C3/N2f zTG8L+SFxvsiXiRPFfIS4/0T/sR4X2fmxcY4xHsFivtTr38yDsTsaBAzqfcXswv1JBtMPaePWk5j aRy9SOPpJZpAE826fpkm4+8Dv0pT6TWzyqfL0wX0Or1Bs+hNs+bfptk0h+bSOzSP3jU7wHu0gN6n hfQBLaIPzX7wES2hj2kpfUKf0mdmd/icltMX9A/6klbQV2avWEVptJrW0Ne0lr4xO8d3tI7W0wba SN/TD2Yf+ZE20xbaSttoO/1kdpWfaSftot20h/bSPrPHHKCD9Asdol/pMB0xO85vdIyO0wk6Safo d7P/nKGzdI7O0wW6SJfMbnSZrtBVukZ/UAZdp0y6QTcpiyKUbRLaUs1VC9VStVKtVRv1uGqrnlDt VHvVQT2pOqqn1NOqk+qsuqiuqpvqrp5RPVRP1Us9q1JUb9VH9VWpqp+ap/aqfWq/OqAOql/UIfWr OqyOqKPqN3VMHVcn1El1Sv2uTqsz6iyH1Tl1nnOpC+qiuqTS1WV1RV1V19QfKkNdV5nqhrqpslRE ZZvLoMWKmW12OMQuR3E0N+cW3JJbcQd+kp/mTtyb+/E4fpHH80s8nd/k2fwpf8af83JewV/xVt7G 2/kn3sE/807exbt5D+/lfbyfD/BB/oUP8a98mI/Yte068peX7Z32Lnu3vcfea++z99sH7IP2L/Yh +1f7sH3EPmr/Zh+zj9sn7JP2Kft3+7R9xj5rn7PP2xfsi/YlO92+bF+xr9rX7D/sDPu6nWnfsG/a WXbEznbyOPFuE/dRt6n7mNvMbe62cFu6rdzWbhv3cbet+4Tbzm3vdnCfdDu6T7lPu53czm4Xt6vb ze3uPuP2cHu6vdxn3RS3t9vH/Es1//qbfwPdQe5gd4g71H3OHeYOd0e4z7sj3VHuaPcFd4w71h3n vmj+veROcP+Hve8Aq+Jo255nz9mzw9lypCioiCAWEJRDr6JIUVEBEbsi0pSioGKJYgF7LBhjJVbs vUaNvUWxl8Tee29o7OWbfUSDifmT//3evPm///qcy3lmy1l2nmfmvu+ZnT1nhPC1MFIYJYwWxgh5 wljhG2Gc8K0wXpggTBQmCZOFKUK+8J0wVZgmTBdmCDOFWUKBMFuYI8wV5gnzhQXCQmGRsFhYIiwV lgnLhbXCOmG98IOwQdgobBI2C1uErcI2Ybv6u83CLuFHYbewRygU9gr7hP3CAeGgcEg4LBwRjgrH hJ+En4XjwgnhpHBKOC2cEc4K54TzwgXhonBJuCxcEa4K14Trwg3hpnBLuC3cEe4K94T7wgPhofBI eCwUCU+Ep8IvwjPhufBCeCm8El4Lb4S3VEO1lKc6KlBKTaieilQSVggrhVXCamGN8L3wTnhPCQXK 6bfot+q36bfrd+h36nfpf9Tv1u/RF+r36vfp9+sPiNvFHeJOcZf4o7hb3CMWinvFfeIB8aB4SDws HhGPisfEn8SfxePiCfGSeFm8Il4Vr4nXxRviTfGWeFu8I94V74n3xQfiQ/GR+Fh8Ij4VfxGfic/F F+JL8ZX4WuIlnSRIVDKR9JIoSVIpyVQylyyk0lIZyVKykspK5aTykrVkI1WTHCUnqYbkIrlKnpK3 5Cv5Sf5SgFRLCpRqS3WkIKmuFCKFSmFSPam+1EAKlxpKjWRHubrsJDvLNeSasotslF1lN9ld9pA9 ZS/ZW/aRfWU/2V8OkGvJgXJtuY4cJNeVg+UQOVQOk+vJ9eUGcrjcUG4kN5Yj5Eg5Sm4iR8tN5Ri5 mdxcbiG3lFvJreU2clu5nRwrt5fj5A5yvJwgJ8pJcrLcUe4kp8ipcpqcLl+Wr8hX5WvydfmGfFO+ Jd+W78h35XvyffkBw127DzOyODM6gJvBMQTF+c5ZmnDG78c1jRm/n9S01rQhpzWxmvbkLHLoeU2m JpNcYIyXQy5qxmnGkauayZrJ5Boy+3XkrRvIWzeRt24hb93WrNWsI3eQIe5pfbV+QHDelOMVXgEj b8FbgCvOjLrp7uoewS3BX6gND3CW9In+oP4yx+nvijxnKRrEQM4N50rjcZZ0HmP7ImLC1EEl4kwi mALKZwywhaEz+xPifsIZDFgqwpL6jKYUKUOsJZltV5AYyxkqSgaW20lmH8+VmAIwqGtMzNhVbZgC qP7h6ZFUUd0v2bHcVLJnublUheWlJXf1k0ob9YpKW/WKSjv1initYLxq8TMaJZJtiUoUy2WlyWdH muGR5nikxWdHYvFIezwSh0c4YsKiZmSx8+HU39jy5/wJx4VxTEFyDbgGRMtFcpGE15/WnyY6/Vv9 WyKIXqIXux7HL+CO/k0c+znD/v/Nr/8ZhlU59K/y5t/JmWWEDKGr0F0YyhhIZc4oxpktkM3aMmaa gjyZwDhSZccP3Jj5F1lx2J/w4e/ZcA7jwV8ZsCS7/D/Ghr+yHdUwDp/3GSs2YupD1R4flIeqO9oI ran2g+6gOqY6EpniWIiaY5GQRnnWapuzltpebZcfuZPr/DlvSs2lFlJLqZXUWmojtZXaSbFSeylO 6iDFSwlSopQkJUsdpU5SipQqpUnpUmepi5QhZX6Rbfd/mW+VSCVKafKXWLfo97yrNFOaKy1+x76y pEgG5GCzL7JwBcbDFSU7yV6q8pGPlbZKO+Rk9z9k5eDf87ISq7RX4v4ldv6cm4P/A+wcCRyUZkPZ cuBALCAKYog9Pil1gFhIIk7QEToSd0iBFOIBadCZeEIG9CE+kA0TSAjkwzQSC9/DYRLPdeOySD+u J9ePDOQGcDlkODeIG0ZGciO40WQsl8eNIxPwmecUbiLH0B7H+NM1ksaMzMAVGPM0ZTTVyXyNs8aF bNK4akLINmT8n5Hxj+Po7YS2QHuY3OFL86XBSkd0BMrqOB0H5XRs2AzldZY6S7DWfaubBBV0U3TT oJJuhq4Aqunm6OaDk26hbg246NbqtoC/bpvuCITojunOQDPdJd0liNVd1V2H9rqbutsQr7srEEgS OIFCX0HPFEKuECSEwXqhvhAOW2gGzYTttBvtATtpL9oL9tBsmg2FdAAdAHvVp2iwjw6lQ2E/HU6H wwE6io6CgzSP5sEhOo6Og8M0n+bDETqNToOjdCadCcfoXLoQfqLL6XI4ZRJuEg6n9Qv0C+GMfrF+ GZzTr9BvgEv6TfpNcJex7WW4p38r8vALY9tAeCfWF2dxgjhb3MZ1kK7LDtwA+Sf5Erfzw0oYNiZd hs9d2kFy8Z61JfYA8WNu/KBAqjJl48GOz2VJzZcxbTAXrbq1uXhrM9s6z5K6HscJnFjbqQk1Gen5 gA+7Zj2oxyimITQkWpgMk3E9TiHpwFfmq/BV+Wq8A+/IV+edeGe+Bl+Td+GNvCvvxrvzHrwn78V7 8z68L+/H+/MBfC34CX6G43ACTsIpOA1n4Cycg/NwAS7CJbgMV+AqXIPrcANuwi24rX5bHNzTarRa zTPNc80LzUvNK81rzRvNW807zfv/zj4tq4qWw/kGLa6YNcVnWlYsaYg1S1pcj8kz7zkTgbiwRJlX /ZhaDGBJTwJZEkkICSUSaciSQlqwZCCtSGumEmNZMiOJLJmTTixZkO4ki5QmX5E+xJIMYKksro8q BwYoRcqznlqOVAAbsCE2uLKhIq6YsmW9tjWxw2e7lbC/2kM6pJPKuNahCvSAnqQq9IN+rGePgBHE EUbCKFIdxsJY4sz6cT6pwfrx96QmbIPtxAV2wx7iCgfgAHHHWScP7H9eqKzDce4pFuee4nBGrFyJ GTEXXHflzzGFSipwrpwr049enJf6Hh4Xwo6Ec+FMP0Zz0Uw/tuBaEJ6poCSiY/onjQj6Q/ojhOqP 6U8QUX9Pf5+U0j/UFxEz0VqsQMqIFcVKxEqsIjoSa8Ymu4gd45J9pLLKE8SR8cRN4qSiOnFhqG5N XBmW2xNPhudViBdDdEfizVDdifiwkVYN4suQ3YX4MXR3Jf4M4d1ZrH5bFyPWpQGXyupi81ldfDlf dkStkYaLYiMbLdaIxxrpmNprTQSsF2VarisxwXrpsV4y1ssM62Whf6p/Rqz0L/RvSHmsoy3WsZJY Q3QhVUVX0ZPVS61pTaypK9bUC2vqw9jwLglgXFhEamOtQ7HW9RhLBZCGjKOC2TjlwzPYRqx/JmKN XNU6qt9pSPyK6+hafI4D671jYeKnfRwsghVsy+LTeawHfMEHARzzG3pCi7Hl0R869IeA/qDoDxOm ftsRPXpFxGhL6BtZP0M/gyhsfL6LGNgY7BSL+Rn9ZWKtv8u8Uln/TuRZjQ3ME4GitxhIkpiSOEg6 M81wgvRhGqGI5DIF8JpMYIxfkUzDmK/HmP/AeLwa2YCR34iR34SR34yR34KR34qR38b43ZNsZxzv TXYwng8mOxmrNyKHmNKJJSeYuulILjBFk0luMG3ShDxgGqMFecyYPo6NAxgSsnFSV0LUcSSpq841 kCbqmhvSVNwujSSH2GcSYMpfPg+/V/RvOvtTeyDxGFU3bPNRJdqD26/tgcSQwE/7OBLGRqi/tgc3 db5bf0V/hxBRJyrERKzN/pqZuhfH+h/uxA7vwVh8lx/v1Y+h2b+A7uyTpYvXiqpYCIiFGsRCLWIh j1ioQywUEAspYqEJYqEesVBELJQQCxXEQgNiYSnEQjPEQnPEQgvEwtKIhZaIhWUJ8KdUvuQiNNv4 Tfxu/gip86fPhTjQgxm710pQHdzAD+pCOESze4yHVMiEnkxL5cJwGAPj2d+eCfNgCayC9bAFdsE+ OMI8dI554xY8gKfwitGQjpM4M86Ks+Eqc9WZp72gOvOBA/NIDbStGQ+rth34oo0FP7TtwR9tHASg 7QC10MZDINoEqI02EeqgTYIgtMkQgjYFwtCmM25XbQZEos3ny6tWu5a3RruOr6BaQxC1VC1vSa1U q1tGy6LdQ8uhLaT4OTZcwc8JJhQ/J+ipjWqZjqqIdoihHv6dVHBkmGRgioNjW84sb810h6piXFge C0aWtweGUqyGrG2y+rmzPB6YomF182R5InixPAm8WZ4MddW1KBDM8jQIZXk6Uy4cq1V9lmdCA5Z3 hXCWd4NGLM+HxiyfChEs/463Ihyrb1mWr+PVNbBBVCYcq6nCwrOMGli+h5ZieSE1VVdXUdYrWP3M Wa6nFoRjdSvN8iHEkfWwtoz50xnjZ5PBZBQZT6aSOWQJWUM2kV3kAPmZnCPXyD2GMsXPF1lLsmIt vjJrS0bwggDWmupDBMQwb8SxWqXDIuatfOahxWjbwRK0sbAUbXtYhjYOlqONZxiv2gRYibYDrEKb CKvRJsEatMnUUbWsjmpry2e1dEK7hzqjLaRq68tnda2J1oS6oNVTo2pZjV3RDoHpGL8ZGLmZGLlZ GLkCjNxsjNkcjNlcjOI8jNx8jNwCjNxCNR7UFj1uhx6vhB63R49XRo9XQY9XRY9XQ487oMd9/4Kn 34CW+dkCrJmXncHjCz7uBr2hPwyGr1XGZK2iABbAMlgDGxhi7GZIcYxh2gWGX3fgETyj7kTDi2Cg Xmhb07po29FgtLE0BG17Goo2joah7UDroY2n9dEm0Aaq5cxoOG4n0YZok2kE2hQahTadNkObQVuh zacJqmW+SlQt81YS2j00GW0h7aha5rNOaE1oClo9TVUt81wa2iFU7VUGyvoT21L7U2uq9qR2VNX9 sdRXjSL1U6NI/dXI0QA1lrSWGksaqEaR1lajSOuoUaRqr0qhaq9Ko5Fq/6NN1P5Ho9X+R5uq/Y/G qP2PNsd4t1D7H22p9j/aGmPfBmPfFmPfDmMfi7Fvj7GPw9h3wNjHY+yBaGkZ9Y6xFPSxZAjDdxd4 ZBCC+A/MXyL7vPryhMYQxs7g2TkR+FaJA2O+gI+zplAGccgS8cNKvU/1ilD2U6mTWkuVnRnjTEQc wVx9mgulGIcRKM3G34BcxSEDqcprKtnPfOxG3akH9aRe1Jv6UF/qR/1pAK1FA2ltWofWpcE0hIbS MFqP1qcNaDhtSBvRxjSCRtIo2oRG06Y0hjajzWkL2pK2gmbQAlpBS2gOnfTTmeaa+eGZCNeD688N 5yZo8jULNat4G74ib8vb8ZV4e0NdQ7AhRABDKG1N29C2tB2Npe1pHO1A42kQTaCJNIkm0460E02h qTSNaYGr+mv66/ob+pv6W/rb+jtMFwgiFU1EvSiKkiiLiqGWUl9poIQrDZVGSmMlgmmGOmKQWFcM FkPEUDFMrCeeFE+Jp8Uz4lnxnHhevCBeFN+Ib8V34nuJuVDiJI2klWylSlJlqarkIFWXnKWaklFy kzwkL8lHaixFSJFSlNREipaaSjFSM6mr1E3qLmVJPaSeUi+pt/SV1EfqK2VL/aT+0gBpoJQj5UqD pMHSEGmoNEwaLo2QvpZGKtFKUyVGaam0UlobAg21DXWUDkq8ksDi5sjaSQyLmzozUoONDRoyVZzK pRNXLovLIh5cP64f8cQ13l443+GNsxg++KzCV7NSs5L48VaMI/11P+g2kCDddt12Eiyor9GEqK9R kFAqM+YLU8f5pJU6zifxYmXRiaSpo33SXTzEdG+2+IQp3iFSRaZ4x0h2kh3JQ907FnXvN6h7x6Hu /RZ173jUvRNQ905E3TsJde9k1L1TUPfmSyFM8X4nNWcqdw6q3K2ocncobZjK/ZHVfANp/Vdi/C/G 9G+I3KeY6dGbBL1pgn40Qz+WRz9WxprXwJp7Yc2bYM1jUN+3+DBrwiu8KeJEONnL8rrEpmQv+m27 /uMW+qE1sSuYYtsh2HY0GGEdxlPBeBownqUwnqYYTzOMpznG0wLjWRrjWQbjaYnxtMJ4lsV4lmNx a0fKF9+9gTcrcfcKG6sV93sVibDlEmy5gC2Xw5arKf5sKd68xGetmJr+hCUfMMIQinimzh4SbNU8 tmoB27P65tbXpO6/G89KIpUAfw2h8C4dmG4l2AMdsNfVxP7m8mGeCh7DM3hdrLJNuTJcec6ec9Q0 4DvzGXxXvjvfjx/A5ygdlRQlTemsZChdle5KD6WX0kfJVvorA5VcZbAyVBmufK2MUeYoi5QlyjJl tfK9sk7ZqGxWtio/KnuU/coh5Yjyk3JcOaWcUc4pF5RLyhXlmnJDuaXcUe4pD5RHSpHyVHmuvFRe K2+V9wYwaA2CwcQgGmSDwWBqMDeUNlgayhrKGyoYKhrsDFUM7gYvg4/BzxDwv2ur/3dt9b/tbapS TBUl85aGIKanhvyld0cYXkCq7kaJlf5UXQn3aR3d/2Et3KdVdOwaXC0utsQ8orqnIcPJT7Nx8JQ8 Z2NfT86HnRHM9kVyTbjmXCuuLZfIEDWTYfNO9dn1l5L6vLpkYlf5PPn8PqlPt0sm9Vn4F1Pwb1KY +qT8sxT5+6Q+NS+ZWF3+IDHW+iyxOn+eWn0pMZb7LDEvfZ5iMf26nfib1JGl1D9ImV9KjFE/T81/ k9r/JnX6PBXXD+/2wxX+d/bxD2YfgVxgLB/AFIn6nU0x+P1Pv/3up4lsrFtAFpBlbLS7gWwju9l4 9xg5xfxnxDUd/7e5z7+UR/4r+RfnGD/MQErMFMAidk6wOo5iXFcGR17l8D1yR1BHlVEwgZUnwiRW ngzTWHk6rGHl7+Gh+g3a8JhooAh/Q+gXeMbKz+ElcuZrVn4D71j5Paf+mhPHaVmb4zkdKwuc+q3T Iiexsoy/jVSKM2VlM86ClUtzZVjZEn/3qBxXnpWtOTtWrsTZs3Jl9VeUGMc6snJ1rjorO3FOrOzM ORP116FqsHJNTv0Ns++471h5KjeVladx01h5ukb9BcH6jJk1mnDeko1SVRXDMSUUqX5DPd+EjdOj +TRWTue7s3IW35eVs/kcVs7lx7ByHp/HymPxt9X38/tZ+QCVCDAFpM5HlWGjY6CW1JWV3UxWEjBZ ZbKKaExWy8xX8iP5EdHIjxWBgEIVkWgUiWlrUBKZ5tAYajENCGykXI9whvqGjgSKv1tGxfP44jf2 f9UjgHoEUI9AibfGAfUIoB4B1COAegRQjwDqEUA9AqhHAPUIoB4B1COAeuTDHXKoSgBVCaAqAVQl gKoEUJUAqhJAVQKoSgBVCaAqAVQlgKoEUJUAqhJAVQKoSgBVCaAqAVQlgKoEUJUAqhJAVQKoSgBV CaAqAVQlgKoEUJUAqhJAVQKoSgBVCaAqAVQlgKoEUJUAqhJAVQKoSgBVCaAqAVQlgKoEUJUAqhJA VQKoSgBVCaAqAVQlgKoEUJUAqhJAVQKoSgBVCaAqAVQlgKoEUJUAqhJAVQKoSgBVCaAqAVQlgKoE UJUAqhJAVQKoSgBVCaAqAVQlgKoEUJV8/IaiT99XVL47sxa4l5RPM+aW76gzqT60/tDnMgjczNzy LdmuGA7AVTSa6HgnRcOV44mxg07vpAMt5HpzoJ3Z1NjE6Fxij3WBzUBrfHgbQCJJPOlOMhigJpEs 9l99mBtotCtxMa3F+RH6FS8sfhjqXfbnEelX2miSGofdmplbproxV2tmzOVezdRwwDGg2E5GBgQM Nz0a+Czh3sU6RvnTnYKW3VOmq5PRUadpphXNKwVnZH7VLaVjpyxbhwRHW1dfX2/bxikJ3TK6ZyRn 2QZndMus6WpjtP5wcunPj2R065CVktHF1c5YUT2uMbf69Xh0RkaWbVCPrE4Z3VKyvjLaWMq+3kZX V6PR28j+tbaU3Yyubu6uxZv/wB3lQqWSbgGeaHJZs2P79VwuAFnIbd6eecO/KKK8w4xJvWONdwoW jq7S/sW7CY1mr3s3rcA2MLtJwXcFeXFuaUfrJn71YEnPvTFniu5OHWqdN2Nw8uof0/rE25+oEHDB AONuTdy1tUZyfn6nqlOO+Dlvlb5vWXV72E19oM9E54UOvgvuNRhU9+pgw8b89GYdluRmz4qr0avR 7SlrEv3zo6xdaWWLGQtvfuNkdaPW5ASLuJZ80owK3tHDns9/OJ7bXf6nrc1CV48YuNXvXsz4iGVv 5/fpnBWx3OrARBMHO9JibFyK98aGZkJA8/dtXs9J1tN5x3Kat3i41j+2TE4v7ZlnW5YNnPBuxcEB J+aX69Y2YN+mR3R2JeNq3ZC9q217mQ+5yGlYw5+ds8CYM9eYU8C8WQG0OfnGnEkDS7U5kvkwpdt0 +yb9LVY1HvN+/6xu//n45f5JG9eoMZxwS9w2+skkK8/766HyqV6mT9rGuc2YLu4P5L8ZnrfX74Zd 0aMW3zp/P7NeYfzDNycP+Pu3XugVk/Kucufaew8susBnn3cdXWtGqczUje/MIq1Str05EnzVtLVt 5J34vssXlS108q5SY0vSLLOvqxgSZj+PsX5pt/dE6SfRS7oEuwlvcy1fXO+YLjd5tvlx9J7NN3cZ 39i6mgyvMMGxXOPjFbi5jwde0qxp83Tl+cIWD5Ia7ImOWbtG42D2fuyJRzSv//pJPy72dr7W59qC Xld7ziRHUmtvP+b19aUgswWeqeVTz3pe/tlae21BqLawtbtPl8bWcvw6fcGon47H1A47aN1sXuZZ M79h3/aYMf/YTIYKccZcTaMPqKCvudj0XNT7ttP2b/uIKRX+KTBg/d7Hjf1jCODGwMDVjW16fgSD rxBB2UV05lyzpq7mRlN1g5rrW3To3imlS8cs9mdKGRV1p2AuRCclds7okvjxxvR/dGP2RrsPN1au 5PHEJNumKR27sKvaRgUH/SkqrPuq34l2q0N9F3gscT3zsopng17bXlecvie068OjYbd+HrUzrVF0 /NMp3M7Gpxqku1QOTNp6yH6dWH/dgB7nQzcvylOifqziVDTzpmxf8WhQ5VfxUw6XDZ37bXjFKQdX u1TaGV4jO+N0aRv/Ub6lfM9vdnya7F8D3N6/q1Z/3vfpMGzq6w2rEgbkvmw7M2fwkDEritaPn33Y Z17UEMtqwyLOG5+RWk93v6yVs2Xo/XTf+TU9nq2puVzfL/6b3slTJ3eXhy4v2vXE9odIs9EJ+51P u4WWfbAxfKJ/VFOrQ8lNvlq0dFhh88AZuVHDu/ArPbf3rbw5OrnWlIgDTv3duwyupzs6/Uj4UK7L UDJn27CLTYtR4ZUx57nRXAWFKlrJqNdRRmg8L2g0/zOgwqDeo7n6w7m8UcOMsYK6Q9GW0VocqHCo J8lss/zxmV0R+U1Cas4OSXhkFNXDBq2WdaOhJboOYkzfxcv6h1ctOrQpIqugZbWs6j1WD327uNH4 3qTx7X13rc6l/KgUZD/hgnfvG3bgRdMDO2Zsbp7xKCFkYQh5MLEw/7j1enFGWXn8yTM2Sx37Pbw/ r/uSvAu+Y2pNTt3k0/nY8OX2by/ePpFi8s3wze8uk40eT55nvyxlVpO/6zjx27ppDl3X+eRdEuS9 7Tod3DwwKC15wcZ1G8d47CvSlMru88uxS3Uv9n13+fKSd88uHpdXZ54YdzVyrU9Bdo2fa531EOO9 uRk5qfYjnrVNyFvReqPvybhRzQaXc//Ff/LMXKmg/cjVzutmzd2/+Izt2q3GskNsLeTqm6KfBl2K NV4d55AybHvmlSfzFx8aWLdbT4VhTCrDmOhijOlg6N0YFZKmZD/iGc78g736I+C4G40McdwZ4Bh9 jW7qpru6acz6W26t+LjmD47/KdYUnNWPPrxje4PvDi7y81hq3yrtbPoWu0rrxhfeWbZ19/GqO9xM R2460875tVdzm9JOy/Lk8xazuzg0GlCmdtCS0XVWhg2XT+eMXzpJd6RFSM+2dx6/Ua4MyJrtvj/r +sOrHWb116wLfX880Oz4in2x8pG+RevM5TdxqQ5Deoxat3TTkFuWa8Zu+aXM2vh2900v+j2wazNy +cDuO0OvThjRK+67m0t7bfce7W7hYn42fu+ycgsjJ3dc+rOtr7HrpdEdw67stn4qR2UFudziK6fa pTVYMW7XKt89ded2bmsVvjjv5JhBgb319U7NWTXYfueVor7JK8OzNlcNaji1g0VchLEw98kRMTP7 QbPGvY7RZj1zirHmhTHnF/R9BYPaY1kn1G0r0WGf2NUZk93kRUzDydctT6YO8uBrVr31ZWhScaKC vdbKWGbgl7t5iHpCRW0to7/Rd6b3TM+h7p2ysjL9XFwSuqXX7PwxhjUTMjq7ZKalqHtdMrtlJPZI yOruEtyUNbSabJex/sc/yXRIgNHP6PNx28gNdS6+YK9evb50waRuJa6U9ZsOhGhTp0VG047TbQd5 gHLDsmHA0runcgY8kL/K6hU5qZ7VE1I6pf/Z+LEFbzvOmnrNwfFVs5NT3kVtjTVZ/cO8+7lPJttk tHr1y+PL0k8jaWAZS9uj274PrUerxrUwaTj+ET2woXGXR1fqmzl4jrTrdrH92uUpZpXHP7jtYXK2 f5eMcfrofdUbNVjk5jz01qwD7apu2hRwqc2qQeIGT+vIwaH13m8cP6uVsHDi+d6bWwyYOz/iQNHS qflBV/a3rRx4boBHvYhnhwv7Tru7du/UBIumy5fmPzy59fDMWYsn7OvjNMx5257Tb9I1Z7b6LH18 tG1ZS8O25/sGzitFy50fa39zxaxGgXdWmFbtrWx3/mFO2p68AIY20xjaDPmINg2y7yPa8P8c2sSk dE7qntWhc2ZJtPEy+rp6GV09Pd1Q3rjipptR3TTmzPtb7q2ascoHorTpEpyS2Smpm21I01Db0KYR fq7GEJ8anj4e3jWC64b5fDxRY27zB5VomtStZ0pC0p8C1J0NfELh6a+WDQ4JnLt61/1G0ytf9O1p Y3LCLbxl72NOp+cKYx/erPV6c9Xs2a+v9+vvdvh0rZG+3kUvTvl7lPl5XO5rj3udhnQrl3dpfaNL 64c8cddz2wt6dvds1O7xusvh/SqsH9/77HubIaXrhnU9NKBaC7OjgyL9D7+68Gzk/drk6vELHV5a jm44Jyfgl5Q6dy6P2CpEbsjqe1u6Xu/O4vTHxzvm0Bdl9vUz39j9ikmjV/Gv78/0zfd7d9e0sINN fMtT+phBx/0bNrzSbLNLXLkx4/jgM+3u5urtJ5nM5F2TRn4bYRNkVzBu7NvQkNAMz5Wh3ktTFia9 9AheabnD3/dyqVFF5YZdjYmq6D/NdWlJgPoVkPp3e1SzdnPHS1Wed1oPbxpe7n/4auBn2JNxK6L2 pB88Fjccmrdp6p0l/kHBu4/8t7Anq3tmQod/C/Z8vFLWlxCU/g6FvwBQKX1yTaQyRy8cDhtRc+tR jz45A6o5BFV/8pPdOGXS0vZNYx1f3t8eE76g33PzI6LFy8ZFQ0uTLlcHVXAIne/s63Y+I9+79QP7 6LwYzeja86cm+jzzKrQIXusXOHmvvLNrjsOT5PmuV9q2y3sZHX257d1vx05LMWk04ujRno085NTL 2SHzndoMihkQWrlslV1fh/1Y5WrZgSmOFs8sdz+q5JwTFuv09OW83b0C7TNezkscMqYgXl5Yw2bB 9bGBA96vGPNm0r3Hb7XLDzY41Dpryasn5hXL+x6avebEpqdrHhQuLWpu8zrgceGJ6iGbtk6t3S/Z 6uAq2wT9vjq1ktzKZq9aX2t71foRlcpO6TLKuP3xN58DVKlUcUrkNlJlsenZ0Iot+3Qs+C1M/TOD r2J0Mnp4eKvo5Ms2/4HB1++A88/w5px3l9fLC+uGd7UqPFQ/sOm2V4stNji7bTSLjC4cdD/Q/XQD 13EOa79JvFQxavCGHQ2PDuBfPOyxZeSeBceXpWQm966WfGvtuodDfjj4YNFbszliq0qOLofrnG6u Ld/z+86JncNjzp5/fGHrjEF7Bl4c0IjzHv/Ltum0uU2negdPb+vZ1qXf2iraNc3bpFonvB+YHfDg uLZKY99eWUK7HW1PDfV27rFXuWPja5Ld89209C59Lt0LzJs0vavSvnqkVXyc2/RjgyKcKrXtFDry gsvgUlGrXn5fbnT6gyrfmb/YX+rkEOVpbs/uXrsn9Ck4EKe7x68Y6r7uxfg2g4MGtxwyvsuKis71 D2RMDb6UemtA1TFpH/AmFxyYRyp/uYf+jxh+ldKZFE+AlgZ1TEVKoOcXwbHspw9YcFrJRk+akh4k ngSToM+HZr8b130BoMY3NnXdkR210XTMrA4CKKMyQ0c/7B6zubYJX+P9+iZNh1jf9/1m3ezm4oVR a/3LH329ZP7edSub2JXPoCn90zQFlcLup6/pnF1pfdhPg5+MNmwRvvbafrf/7cx2oTPGHTtw6PyY bZe3Vj+YfW/vMrfjw37Yn7DL66iV3daeF/zzV5fvPt1u+Kk1a8xiRj2duiMpPN+h6tS4rw3+e8yT etffeHjpIL/IFfEtLxhv3/atcHVE0RnfnJfmdqMSBybotBOL8rlgl75hwze8504nvQy/cEaT9e1q vot0YNo5hw7Z9R9bTjW18+Gshy3R/TjRbf31Orub1tq8cMSFW8neo59Wmjj1wIpeMU38TnQLWWX/ zDVXu5yB1GIOwJgz7B8clX02Vvx1jntmzhmjxad4O4CroOHxPQG1FRQH00TjKpWcVmd38+uW6KoY Sx4tbbT/9YNaV9bGriwf8V8rXXbfcvKy/gMrot5nCX7u8pQ1SEHSwmMYZhCyQKtBg8GXIZMhmaGI IR88Mp/GUMKgwBDCUMlQAOSlA8UTgawMhsqFag0qOKvXksqC/PSixIKMSgW04o2liZGh2Tqw9bTO 3vkHu18vcFrkc0f7zXWlbQ0mgfvXRGxdNmWthet8nyqZB89XpfwyF01M+5fdnxGwwq9oI++UF6Vf +z3nfXm+PiL2ySWBrSK6m+yvvPjFMPF12QOHXOvILakRoZ2zLDlE2nQ8TjaZ/X60W+RAbj0jt6Pa pp8BDktsrAOlKxbE18a8c61cdeGDYB1fwtvZ7R4tbTp+bNFHAsxeh39f4aaw+dOW0nr2pxoOP3Tz 2g47LFsZ1tAYe2v+EkaNj5JXLk8Ln7e5LMHgYVh9hHSHC8OFzboqW4uCl8i01PzM1XrCzCzQNUNp 2V3h4/tPzfDrvj5N5KPg27+8/sl8O7TuXHoswjz/dXnIm+ULm5jkDZqYpBFxxGbYxMQDFOKgexJF r5FQOhjs0CS6INZAAjklciNmgRiBdsJlWA35gVWthaGBEbCiNbI0Adat6Amx7/NOx0kysZfrP949 9Ux/1jNT1Tmf0cosUBK5kJXJn3HpxXH1iOKQp0Zu/nePTtuppmE0s+nC1pJ9Jf5hOjcWPzP/9fhn ++u40gOXribvzHJXcjzTs4T9y6LeYPeD5TLTVHL1GBX5Tr25le0e+vP91Fv3jtRafNoRxM31yYjd qP6zenJCc8XdPz+nbde+4shUpam59Yx8mbhK5wyp7pUdUQ+W6V1xcHD7p35BIFygdfEmzpLOoB6z R3IPmT6/OJ/pIHZWKWzDKolVJ/ilXqUVSrS5dB95ZLo9nUXLMXye+4IVIU1s8+/MOLm0uvxNquI/ r4NfxG1N1vrZ7Nm840lk0LdULdFIBpfnq5UDSqWUI7fy2Lx7UfLz8TKnitZFOq/v7AnqenJtAy8D AM4unskNCmVuZHN0cmVhbQ0KZW5kb2JqDQoyMjQgMCBvYmoNClsgMjI2IDAgMCAwIDAgMCAwIDAg MCAwIDAgMCAwIDAgMCAwIDAgNTA3IDAgMCAwIDAgMCAwIDAgMCAyNzYgMCAwIDAgMCAwIDAgMCAw IDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgNDczIDQ5NSAwIDAgMCAwIDAgMCAwIDAg MCAwIDAgMCA0OTQgMCA0MTggMCA1MDMgMCAwIDAgMjQ2IDAgMCAwIDAgNTM3IDUzOCAwIDAgMzU1 IDM5OSAzNDddIA0KZW5kb2JqDQoyMjUgMCBvYmoNCjw8L0ZpbHRlci9GbGF0ZURlY29kZS9MZW5n dGggNzk0NTkvTGVuZ3RoMSAxNzExNTY+Pg0Kc3RyZWFtDQp4nOycCWBU1dWAz31v9n2STLZJMpNM 9mWyJ4QtQzayEAgkowkQSEjCokBiFjaNolalEdC6ixXQ2lqLymRADYJLFbWtolattW7FiguWVNxb MJn/3HcmIeDyt/5t/fv/c2/O++49dz/nvvveJDDAAMCCFxnUldVXzWzI69aBcLEOwLqpvKSsQbv1 xmMA1zcCyC8pL5lVqtl02XUA16gAxLqZZeUV7z3+yZcg9Edh/i8z6+bUH2liNwBsex3Ytjdn1rtL njh8hIGQfwBg5qI59Zk5Xwbt3wvAXsFRW9pWtXblXFC4GCB5Ibaf2ram155ZlV8FUF0JoFAt7Vq2 6rYPSu4GSLsJQB28rLWnC8LBAfCjv2J707KV65fm/Tb9KYC6OoCQsuUdre3vKkYrsH/sDwqWo0K/ RRmKeZwzxC9f1buu9DPFdgBhEkBi3Lkd3attEbE41iWvY/mTKzvbWne2bI8BaMf6MRWrWtd1WU+G 4trYEJbbV7eu6rjq4OZbAC69A8CQ19XZ0+urgwdxPnw99q7ujq6njvc6AfJwzpYfA7etfPvQQ/fc c/di49TPIALNhmH/ny94hvOJuJu6T746skV9TPkE1lWDABSwnQJGgR3U7Dz56onL1cekniYE8UOu McbBHJBLCgFMkAktALo2HFeqIqsWDmCpSn6zPBe7jCGKz8ODAqhAMCoFUSYTBdlbIPhccLcP26h5 w9p6ux3smNhJc1BuFxLtwHZInT4qN/CVYu+GU7Nhz8H/+6AYhS3/jnHEX0Hx1+o/B92/Y/xACISJ QfwEZn6ndk1Q+ffUk9VAzWl5JVR/l/H+LwT2BZz7rx4D7X3hN5bV/n0++7ogvHJ6v2I2VP1d7Z6E sO86ZiAEQiAEQiAEwvcVhFvg3X+4TT7s/BdM5T8miJfA+u97Dv8XA35mv+77nkMgBEIgBEIgBEIg BEIgBEIgBEIgBEIgBEIgBEIgBEIg/J8Iol+i/P+C7X7MYUq4HWSwTdKbUMP/5ZIe4iAbJkMtNEAr dMAK6IRe2OnzSe30YPeX1mNpG5auhm6plPk+wyEOiNG+L7DebSif8ga+Nv+I4f6ZhPolHCJpZmK1 eCMsgnZmYpEshq1h/Wwzu5ptAwU7JtX46Mx/dYd5wf9v9AT49sAmjPFt5hn+iubs/6ZnCmUT0riG b5wGzpPW5883j5fgeiXSmv9zgvhP7e1/7S50VSxe1LxwwfymRndD/by5dXNm186qqa6qnFlRXlZa MsNVPH3a1CmTiyYVFuRnOjPSkxMT4h1xtvAQs8mo12rUKqVCLhMFBunljooWuyexxSNLdFRWZvC8 oxUVrRMULR47qipOr+Oxt0jV7KfXdGHNpWfUdFFN13hNZrJPhakZ6fZyh91zqMxhH2Lz5zZiekuZ o8nuGZbStVJalihl9JiJjcUW9vLw5WV2D2uxl3sq1iwfKG8pw/4GtZpSR2mHJiMdBjVaTGox5Ul2 dA2y5OlMSgjJ5ZMHBVDp+bAeMaG8td1TN7exvMwaG9sk6aBU6sujKPUopb7sK/ic4Ur7YPqjA5uH TLCkJU3X7mhvXdjoEVux0YBYPjBwhcec5klxlHlSNhwJxyV3eNIdZeWeNAd2VjNvfADmkSeYHPaB zwAn7xg+drqm1a9RJJg+A57kSxw3E5aPpQHnhjPE9cXG8rlcOeSCJZjxbJzbSHk7LLF6wZWZ1uQR WnjJo2MlFjcv2ThWMt68xRHLXVXe4v9Zszzcs3GJPSMdrS/9JOAPlts9YmLLkrblnK0dA46yMrJb Q6PHVYYJV6t/reWDWZlYv7UFF7GCm2FuoyfT0eUJcZRQBVTYuQ9W1DdKTfzNPCGlHmhp87fyZJaX 8XnZywdaymiCvC/H3MZ9kOs7PJhnt+7JhTxo4vPwhJaiUxLLBxrbl3psLdZ23J9L7Y3WWI+rCc3X 5GjsaOJecpg8KYdxuFhpRKkVru2M2mOV+cqVCSp7o2AVm7i3UGGvwIujZCoWmNBdUpZ7tGSqvZFZ YawajuKvwVOn9YMZMaG0kheJvGlppTW2KZbCt0zJ6p+TPMGjmtCXCRXjc6JxvnFqVJtPKMVe3lE2 YYKndSr3T9Df29fPU+C28A+MLVTcnZVjRWIC3rmoE7AbScW9GG73QJ290dHhaHLgHnLVNfK1cVtL /q2pd9TMnd8oedu/SxpOy1H5JMp5IBaLxzJCKe7BijTrmFul/EwpP56tPKO4aqzYPqBy1NQP8M4d /g7BjncQLlqRWNV65aSgPLw1K/B0c1S0Ouwme8VA65Bv45KBQZdroKu8Zflk3oejqn3AUd841SrN dV5jv3UDHyoIalhNQ0lGOp49JYMOtmnuoIttqp/fuM8EYN/U0OgVmFDaUtI0GI9ljfvsAC5JK3At V/KMnWd4T/Mwo5LqW/e5ADZKpTJJIeXbhhhIOtWYjkHbkEA605hOQJ2MdC5JxwM6KXw5mhiP23J7 O3fPBU3LB1qa+M0FoehK/GEe5pgOHsExfZAJCp1H4+go8WgdJVxfzPXFpFdwvRI3BgtlaBx+Jg20 OPCcwg3VCFZGW1HkXdqHfL6GxthD1uGmWNxqC1HmN3rUaXj2yxOqsd5MLi2onunZ2NbK5wHuRt5W mVDV1oTbdqxDrFLlUWMPan8PWKNCasO3IzZqQ9+gA6X2GzHj2djkaUrjgzauaJK2s8kDlY7J6Hbq U57IB8psGghy5Ej3Jt4KmoQrONQ4N6hvJI0VszhYExlJqcOZtzmwqK3FjtaWQVs9bnU6SzVW0nTg kShL7JBEY/UXAl+WmKDVazxqJ3aIPzytdfJbUp6gbGqiyUu5K/wVcGyTR4szSpxgSn8DtA4WVfG5 4M8VOFVe9Ze8m7lDMM+xDk8WPmmpJyUWe/QJVa14+FN7LWock8Yaq/gZofX3cZC0Sr5yHdpdTGgY 8t3pWB87IWSkO/jDgW9MsO7DjQ1NA2cqPAvSMtJVZ2r1knpgQKX/+gZkL5V+nKiEQbU4JPzNGxNt GxL+6o1JQ3zhjUlHfE74jPAplX1CuY8JHxGOEz4k/IVqDhOOkfLPhA8IRwnvE94jvEt4h3DEG6NG vE25PxHe8kYHIQ57oyMQf/RGZyLeJLxBeJ3wGlV5lXJ/ILxC+D3hZcLvCC8RXiS8QPgt4XnCc4Rn aRKHCM8Qnib8hob9NdX8FeEpwpOEJwgHCY8THiP8kvAo4RHq82HCQ6Q8QNhPeJCwjzBEeIBwP+E+ wl7CHoKXMOiNykF4CLu9UbmIewn3EO4m7CL8whuVjbiL8HNqdyfhZ4SfEu4g/IRwOzW/jbCTsIOw nXAr4cfU9S2EbdT8ZsJNhBsJNxCup3bXEa4lXEP4EeFqwlWErdT1Fmq+mXAlYYDwQ8ImanAF4XLC ZYQfEC4lXOK15iEuJmwkXES4kNBPuIBwPmEDYT1hHWEtYQ2hj9BL6CF0E84jdBE6vZH5iNWEVYSV hHMJ5xBWEJYTlhGWEjoI7YQ2whJCK6GFsJiwiNBMWEhYQJhPaPJGFCIaCWcTziK4CQ2EesI8wlxC HWEOYTahljCLUEOoJlQRKgkzCRWEckIZoZRQQphBcBGKCdMJ0whTCVMIkwlF3vAixCRCIaGAkE/I I+QScgjZhCwJIvOGOzGXSUonIYOQTkgjpBJSCMmEJEIiIcEbNgURT3B4w/iGjvOGTUbEktJOsBFi CNGEKIKVEEmIIIQTwgihBAuNEEIjBJMyiGAmmAhGgoGgJ+gIWoKGoKY+VQQlKRUEOUFGEAkCgRFA AvMRRgkjhC8JJwknCH8j/JXwhTQs+1xaEfuMlJ8SPiF8TPiIcJzwIeEvhGHCMcKfCR8QjhLeJ7xH 473rDXUg3iEc8YbiBmNvE/7kDZ2EeItw2BtaivijN7QM8SbhDcLr3tByxGve0ArEq4Q/EF6hrn9P eJk6+x119hLhRcIL1Nlvqd3zhOcIzxIOEZ4hPE3tfkNd/5rwK5r8U4QnabwnvKEliIPU4HEa6DGa 9S+ps0cJjxAeJjxEOEDYT3iQut5HXQ9R1w9Q1/cT7iPspYH2ELyEQRrWQ9hNuJe6vodwN2EX4ReE u7wWPHfZz72WGYg7CT/zWmoRP/VaZiPu8FrmIH7itcxD3O61uBC3UZWdVGUHVdlOVW6lsh9TzVso t41q3ky4iRrcSLjBa6lDXE/NryNcS7iGpvQjqnk11byKsNVrmYvYQjU3E64kDHhDGhE/9IY0ITZ5 QxYirvCGNCMu94ZUIy7zhixA/IDKLqWal1CVi127kceN5bYPDZW2w7rZtsdQfonyKMoj2rNsXpRB FA/KbpR7Ue5BuRtlF8ovUO5C+TnKnSg/Q/kpyh0oP0G5HeU2lJ0oO1C2a5bbtqHcjHITyo0oN6Bc j3IdyrUo16D8COVq9XLbVShbUbagbEaZoRa+FE7AWWATTiKXg41d5A3mt+OF3iC+tXoJPV4z31rd hPMIXYROwmrCKsJKwrmEcwhTCVO8Jo7JhCLCJEIhoYCQT8gj5BJyvEa+T7MJWYQggplgIhgJBoLe i04ZYjqClqAhqAkqgtKr565WuBYg/4IyjHIM5c8oH6AcRXf+EeVNlDdQXkd5DeVVlD+gW15B+T3K wygPoRxA2Y/yIMqt6IofowyxjWTpDV4z3/LryTjrCGsJawh9hFJCCdlhBsFFKCZMJ0yjJVsIIYRg jn2iKApel+2Oh0UB9qIcRBFFoLmcT6gnr8+jmc0l1BHmEGYTagmzCDWEakIVoZIwk1BBKCeUEeII sTR5O8FGiCFEE6IIVkIkIYIQTssMI4S6bkGOoHyJchLlBMrf0MF/RfkC5XOUz1A+RfkEvfoxykco 76G8i/IOyhGUt1H+hPIWevcQyjMoT6P8BuXXKL9CeQrlSZQnUA6iPI4yhPIAevx+lPtQ9qLsQbmF e18YIRv3Ey4grPCa8VWILScsI7MsJXQQ2glthCWEVkILYTFhEaGZsJCwgDCf0ERoJJxNOIvgJjQQ MglOMnUGIZ2QRkglpBCSCUmEREIC+Sae4CDICTKCSBAIjO5IcN2O9KGMoryPhn0Z5XcoL6G8iPIC ym9Rnkd5DuVZNPQ+lMvEBNsPRKftUua0XVK50X3xro3uiyr73Rfu6ndr+6f01/SL2n4r4vz+Xf2v 9SsuqNzgPn/XBrdsQ8gGQbO+cq173a61bu1apltT2edu6DvS92mfGNLX0Nfe19t3Xd9LqFDe0be3 72CfOOR71BXUN2lKxca+q/uEECwXoI8ZuTq2T2uo6K3sdvfs6nbLuvO6hSmfdrPD3UzI6mZ13S3d Atba0x2fXMFr53eHRlaYurO6Xd3ieZWd7q5dne45nZ2dF3Xu6HykU35R51Wdwm5MCa5Otb5ideUq 9x9XMTgg+MCE8qjg84qazv3CKDD4UBh1+di5aIBz0BArnMvcy3ctcy91trs7drW725xL3K3OFvdi Z7N70a5m90LnfPeCXfPdTc5G99lY/yxng9u9q8Fd75zrnrdrrnuOc7Z7NuprnTXuWbtq3NXOSnfV rkp3XSWb6axwl4sFNnyCQAz+dMVsjDkeI9O2RHdFC13Rh6OPR4tdUcejhIuszBh5UeRVkaIRLwJd ImwRV0XsiNgdITdKCVHXFbQxSOgybzQLWWaX+XnzYbMMzDvNgvEq4w7jbqM4x7jY+KHRZ5TtNrLd hkcMzxnEOYbFhk6DaDTwvGhyGZzZFUa9Te+amakXp2bqi/Vz9OJVeubSO3MqXPr4pIpi3RzdYp24 Q8dcusSUig81Po3g0mDBh2qfWvCpGYjMzhj/s6ediSruI2axVeB+3BPK5AxfLQYb6tPSaoaUvnk1 HlXdAg/b5Emo51fX3PkexSYPuOcvaBxkbGvTIBNKGzwh/BfHUv6yLVugJLrGE13f6NkZ3VTj2YgJ F0/4MAHRg6FQ0pS2qKevp6c3rScNLyiLelDT24c/EhhekX29vKS3B7BK2jcEXqOHo0+q1NO3uA/7 wAJU90hqnlskVfmmPv6t4RtX8u8I7Psc/P93CF+8CEC5HWD02gl/W78Y449hF9wHD8Iv4TfwInzC NNACl8Ej8DZ8AB/DSbxNlczColjKP+9P+qOXyleBXnwUFPybI3wnfEdH7/IdBZAbJmiuxVyYLPGU xhfkGz5TN3rt6NDoswotmKS2JuFp1B5nw74TQjHP+wp4XriCp6UWx5XbR3eP7jhtOl3QDX2wDtbD Bjgf+uFCuAguhcvhCtgEP0RbXITpK2EzbIGtcBVcDT+Ca+BauA6uhxvgRrgJboZtcAva8VbYDjv8 ZTy/HeMNUikvuR1+BnfB3cifwB3wU7gTfo75X6D174Z7UUcayt+Dmp1wG2p/hlpei+t2Y/TAIHhh D+xFn1F+LDcEj8L98AByH3pzPxyAh+Bh9OOj6NnHJB3XjOW/uSZdH4eD8AQ8CU/Br+DXuDOehmfg EDwLz32nkifGNTz3PPwWXsC99hL8Dl6G38Mf4DV4E/4Ih+FPuOuOfaX8FazxKtZ5w1/rLaz1DhzF msNYk+pRndel0velHl7CtofhCFPBZ0yAk+DDFPfeDZKHbpb8yL3HvXOHZGfuj92Y5x66c9w396CN 70F/8hxPb/N7416sO4gWHLPf11vtWb93yN4HsA63BS855LfFU35P8H4eHm/7tFTmldo9Nt7rKYvS Cn83wTqvT7DhO/CuZBmyHpWesh6vcQTrcCvzPk637Z+wLVmft+X6iW142auYP4qnwzG0NOefJU/8 Gd4bT7/nLx+Gv8CH8Jl0PQ4f4XnyCXyK+c9RcxxzX9WeqfkC41/hb3ACPfgljEzIjZxRMgKj6GNg jAlMhNFTqVNaSWT4iqHAM03F1EzDdEzPDMyIryLKM0q04yXmr5TovqZMLWmCWDALwfMyjIWzSGbF czOaxTAbi2VxE8oixkvsWOJg8SzBXxYqtYwYb2vDGmET6qawLLYWr2nMyTIxnc3yWD4rZEWoycB8 DuYnY1mWxBKogyWwEk7I3xeewf5D8FQZ5N9HN9ojvoYnpghKKIJamA0NB0DPbsVjdTJ7em9ZmSpD +TBmBbCzp0GF5rvVFSwT9FZrsSNfsVmca64qVm4WGqB45M03nsTLoaCizEMs843hl4dNI0+aizKH XxrOzmLmWLMkIQZBqVQoHHFOIT8psSA3N2e6kJ+X6IgzCJIur6BwupibEyOIIWOa6QLPM/G1L+eI 5SPxwvrYKfXZcpaWEGYLVqlEW4w+IddurKl1FCRHymUqhShXKZMKShzutdVxz2rCk6Kik8I1yOgo 5MhjcsOJj+WGk2fLyk4eEN4vapwer1iv1wpyterW5BhLfHbUtBq9US83WMMio5Qqs0GTWtk6cnNk QphGE5YQGZXA+0oYmYLv/lt8JxTnoe2mwh/4y6e70aXVZ2WFZWZqnOHhkUNC+974bJ1Og4kHIL5g boROG76fZYALnL7je00OYVb2kO+4y85TYSZ+1dM1LDMr26mwJc+1uYPccjeEF2MICiviT+/I2uGc nJxilvnScI4518Qv5qJpmbm55tzsLOt9/9xRsrOaEsbcYHYwg8hTScxhHlfmcQ/GCGEsl6HbeNKi OE8bnZUQnxWlE0Z/KAuyZcXFZdmCxNEbBG1MJuqjtQUZdztLsuw6Fi5jcXpbyqSEQWtShD5eY9Io FHiRRZ88ojdrRLnWpJVFnXx7XH9xboHRUZT65YjIUifHGw3Yiv/rzWLfUXGzPAGqYD/5YR/MEG68 Lz4nPkdn5X/5A52Tm6QQNCzjfnMhxtCpQ77392qNbNZU/LDt0s2wylPqQ8O5IpR/XHfJz0KDoBnS ioOKiobTzEVFmZmmYdMwN3wQz+Cmth4A5z+pW7Q0I6PKxjY83RlOhT+vsPiNzm8VS0iMQtw865J7 20p7GqdEamVqo8aQW9dZlTUrPyqrdsnyJbVZ5X07mpwL66aHKOWCqNRrtVkVCwvTXGmWzDnty9tn Z7EfLN22LC/UFheZ7bSlRmpjk2PDUqcnphdnp2VNc/fObd7S7DSEx4QYwhyR0cmRuqhYqyUhLzqN ynvQ7jrfCfED3P9x4Ca7D4JiSLhuT7hZETRmh6AhtmCvK3quTtpgfOU5LPPgyCG03uC31hqzSOyp zRY7dhzE8vPhA7nGqB49oI/JTUzMjdGPHtAYNHI5XsSr0Rpy2e3RKRG6k8PjmydYF5ESHZMaodVG pPJ/EzwTd80a8feQCy6WQvP3qsPyhoQFeyEpCSYPCeUuk1kMY5+EsbAhXR77Mo/l8d8eqHV6Nisv zzkjdYiFu6yH45jYH7clTnDF1cW1xInGOFucoJPFxcmih3yHXQYdri863MRqo084q6fhil1qzEw7 4tLVyiA8k3bDcFoanpuLFzU3Ny9uHjZjOq35vOHm81jm8MEi3CE5RWgwl/F7no10HvDDOzExP99/ iHN/5OI+FU4d4dNl0kGgpJ0amptTUCiuCUlLzUgxF245a+bas7Omrd+79mxz0oys4rZZuSatWavQ RFUs6pyy4vqW9C9app1VEDGzOL/JaTOYlEqTYeaUkoSqlZWze2riC1KLU0Oi4qIMkYlhtvhoR0xw ivvyha8GxefGTnIV5PHToNL3gRgrvgz5cKvfq1GQ9LDQCwYIZzawQbx/08XzX4EGV8seZJWQjZbU alltdrp0s6bz36O61LXSzTqS9lLacDFeh7k3cqT7/n/aE52sigkPOLy/FXR7Y4rufukxGCvKleGT q892LtuxsrB03R1LkmtL80PVcjHEZE7Mq8xZsjwytzY3r2ZSol6tU8o8kY5wY1hspMnVv7f38sc3 TsdbONQY7oiYnIlmu/GaytXVCbZEm8Yq3QM1eA88g5/AEvHZf73fWlpr0X4BPyJCptDt0gTHVmiL kqwyQ+rYvYr7rMqlDq/Ok9aXh7m9LkOtfNbYnYu7B58i+ITCBz9tW/V37WPi82fifssJDTP7T0mL mJjoPxElmxWKz2jCU2LsyRHa8hsXLt3SlJy75JrFNRum8odSAj6UThS0FWTPTLMEpZTlRWbnFtjj tEaNTKYxatuq5825fE/b2ocvr5w2heFTR6tQaE2akbyyyux5HfmTzqnPMcYVJnO7VaPd7sezIw3y mJzstic4ODad/90/LU82xC0XK6YHpwvW9Mdl/DYN07NakJlkwqw6WYtM2CnzyASZLCoTLbLHyGo5 XXask3kksTr8czCYDIJZNKjDdaxWHY4V1H9zRY1torSX8NYc9t+lzectak4bXtSM9s55Ax9NmZLF /71jS2e1whE7Yd9aTt/dgiWpQPKTUrw/JX7kLeuU5hkl7VVZRrVOJQoylX7y/N6StXvWTZm+5q5z unYszfpUXLA4a2ZmhMBOONOLmmfEBYcFK4NiI0JtoUZDeJh56oYH+9c+cllFSd/ORfZz1sdPq89E v5zrO8G2yGeDBWKhnPzyCIQKj0AUWIQW0ICNnX+fK8JURVvtZdxrjF5Qrfu+puy095+xhQTz+zQR X1RxG7INOmlbRevGGDy9wT1lmrthapzGyB9HRo24AfcW7iSjhmXNmjypataUIjylLsRn5wu4g3Lg Yv+zMzV4P04xBrTCYi/EmPClbQ8eIyZ+y/BD2zTEal1aV0Z1akR8VcQsmiS+RUj3Sxp/LTENF0nr MP1DLU9fo3T+KM1fWbSloIDuthd0UdnxCdlRuuD4osSsJflj69ZEptjsqWGa6pvrF/TXxo2vno3M qM6Prigd2T1ujwvGUsvq6qYuG2hFv1X6jspkaI1gSILzxvwWIvThKRSDVw1E+A+OiCEW6VIbqx3S weHgf69yyWvH3qmG00558+9tcerNa3yvyvPG37Kk/SyTTd0wdP5aT++kaRseOH+dp2fS6Iglp754 UkOBNTS7YXpRQ0EkO9p9YFN1yYVDa7ofuqJ6xoVDF5d0znOmzOmcicxImd1JPhf2S28cXX6fJxqH hBaXDiKNGpsmUyPqRQ2/KdF7miFW79K40qoTjRZ7lUXyGb4ySrNezO/2g35va/77+hOWKN2CX+Ne 6TOXQtiPd6JGFRIRE2RJzUAnn+Fcx/RJk6L0MfZwrVwmiDXxzkiNUqU0x09NH3npq+7tzJmRaBSV ao3Okoqrr/IdFT7G1VfB0VNv6c7xt/QyVxzoZE7mPFKo1TDNe+ZCF9/EhfZCQZRerY1T2VT+ScYq vV4f4a/W1aEm/vYDocwkC/143K1oH//7dbP0gr24Oc003Iw/p728u+z/4tG+wzu98HHR8q31OQsq s0J1MpVOrU1zuQvi8pNCEqbVzq2dlpCz6IqG1Dmu9GCVTBSVOpU6sagmKy7HbkqcPmfunOmJLGZW 7+wkY1i4JSM92mFRRsREGiKTI2PS7FFx6a75xa5zZ6XqgixGo8UWZo0LUVrCLYZIR4gt1R4Vm+5q Qi+F+Y4JW2WDMBmuJS89YDbrp6SAI4P/u7wwfcbYIzwD33n2OCqj9WMKPX8JCqvM5n+Jdin9xsEb 7JB0W+aO5BzMMdPjaR9kfJdO6KSS+T+N8iOYXj3H9jA9dhQO/HgaOvYYErZqgxyZhVE1qyvjzg0O 4dvyHG00nWCP8Y0aEvy4c0qIPcKsVGgV8g3pmcF4WCfOWTeP/TqzMDo5TPMUvgfI8ZMoJsKSowsz R5urqpRqpdISj+fWu76PBJAvx+dNCtgO4JNmCOz4pNl6v1aeYK01VUBx8RvP+s+ksY/P4qkHyRm/ 4XiLaSLS8EaL0LBInS0/OTnPppfrYwtSUgrter29MCWlIFbPfj72YiJu1ofoFUp9sP7knJRJcUZj 3KSU1CKHET8i83eUnb5P2IPibulMtQ5CyJAw9IAmxoEPAGMlFB8qPoROGca32TNPP/OZ03rQwKdQ EKvTEQ1n5sXQ1EnxRmP8pNS0yfEmU/zkkcrUIq4oSk2dwjmFz2e92C68Kl87ZiuLoAAtxAqK+1Pk 1sSZpploq0P42XD45eEJcxo31pgmSUyUXgAtwuNqS1yk1RGC7ynWdLs93aoZXakOcURa4ywqFsa4 cka2uHXs8x97ZMyRozNO11ksuO+vAxA98jBwwn3+3+Xo1SlMncxUSYwFsSzpo5ZRqHVlMRFShoRr 9sSEa81DvjfvQ6U5GD/A9rvUjnkpRhPTyk38T/YuRcP4AZFTPILmTjt0MJd/8sUTApoZfriyusJT klkKjjNhKD7C39MfWmlxM/XT3EzP8PEPyLm4nRWJ0h1SmEC/T7OYpY8THoXWoB4pUBlwt2Pqo+fD os0KQWXQsVC5MTzJlpgZrnpRbdTK26OS+G+8pN+eacXqHq3cnJoYbgs1qPbK5CLD00d98kVteBI+ orf/74hsyT8ehZgJsT8Qv2sUV3xL9H01ym6hKF/2vcYD/2hUlJ4W7/+2qMynqPq6sCMQAzEQ/2Vx +JuiOv97jj/4z4mauEAMxEAMxEAMxEAMxEAMxEAMxEAMxEAMxEAMxEAMxEAMxP9JlP73Hf/23cfw GgMtIIMG/k27vmPQDot8n+O1HSKgnQm+Dv79u77ZeI30rcRrjG8OXtf4bsRrv5TeLKWv9q2DdvFs 3y+YwLb5hpkJ236K137f5ywGNR+zNZJ+M+pfxKvJ9zZeI33v4TXGdxSv/VL6arxejTWPsm1Y8xhe Tb538BopaWKwdBvW5PptvveldWQIfD303cf0bc+itDqDlONpAVRiKox94/ZkUeZPyyBcjPSn5Zie 7k8rMH2WP62EE+Jqf1oFqeIRf1oNdtlyf1oj7BwfSwtnyTb50zpIlb3pT+uFm+Qqf9oAK5U7x79B O0el86cZKFXT/WkBZOrbxr4rG6LVW/1pGejUN/vTckzv8qcVmH7An1ZCv/pxf1oFFvWoP60Gk8bl T2tY3fhYWkjT1PnTOrBozven9WyW5mp/2gAF2tf5N5TL1H47U5rsTGmyM6XJzpQmO1Oa7ExpsjOl yc6UJjtTmuxMabIzpcnOlCY7U5rsTGmy811ghxzIwjgJU7WwAtqgGzqhB2Up9KKuFFPd0CVdW1HD v9l6NTixZAasxGiHeahbBsuxrEfKdSA7sPYavLZjzVJstxLrLEHdCqyxQqrXirIK+2qX6q7GXA/q Vktl1H4FzsCO0or1VmAP6zG3FlO9OBav04c99qK+A3N8zn3Yul36bu1lUi+d/l57scYq/5i8hh3X 2CmNyUfpkdZSJa11KWr4GvtQ3yG16JY0K6VZ9/rX0YYl6VLPqyTNSqnHVrQR6cdGWYX9rJQs1uWf 5WrUrJJGpT75OnsnzICP2CWthew9Zm2aOx+pEy1gx/WTxfmsVmFd/p3ivVKOr7h33B9kMxrFLs19 tX9dnZJtl0g1T8144oq41dZJ7WjV52LeKe2Hid5MknpbJfWwXrJDn9/zE+3NPUbr75Dmz9dPfumW dgMnjch9bcc+usZXQ3Nc5q/Tg7kN/t57cRXkoTXjXmqV9kgraledtq6x3dyGM2mVxm/zj+/8ml0/ +SvrtEMJluEZL5XRHZMPZ/l30Ar/XsvH3gqw9PS2GeNt/4u4MwGPsrob/XlnJu9sWQAHSBBxBJeg EBBRUoi4o7IGEAvYwoQkQCAbk8mQwbApxaWoSKmiVUSbukA/RGsXtbUJmwQEUiExscIXggaxISb4 Eijw8d7fOTMJCdBbeu99npvz/N71nP/8t/M/Z+KSS8+EzEhOhy1Mi9g0S70N65gZ8aLUO0Nls7Rh ropj65hLv535H83q8xkUjtck7rKUDvLzJ6oZEOgQ2wERDfLaWZAemYsBZWWmyu/RPEkXiSrufemT oeTfr7QKjw3Q8vHuANp81ZLUvO+oeZKSnkOfAPkm9Z+lLMhHQoinMqozlS1yNnWU2vpcVpRwBOa2 yZuidA5nckhlYIHSMKDmWoGqDeHRXmWDnKeZKsuy1GeEPTRDjW313n34bzRVMjzW3+5NeI5nKJ+c n7fz1Welq3l9qc8N38u+6WRRofJhRts8yFDvZaUJW9Ca+/nK0txI9odlZaqjnM0X2i3fh6tGIqP6 quzMwa7Mtnl8sVa5F0m+fB+dl95aub2R2hvOnvQONfBi28/na0e9hrXzgLQkbEt4JWjNen/bqpKh 6mquqq9p/9LSsJ/TOvg0M5L9F84B6VWZeYVqZIaqUdKazDY5sme2qnP/uwj9v5oX5+fEAKWNnAPh 1SlJxSpfFL3jHTRwYLJ3TFa6P68gb2bAe0+ePz/PnxbIystN8t6Vne2dkDVrdqDAOyGzINMfzMxI uictO2uGP8ubVeBN8+bkZWT6c70FabkFXt5nzfTOTMvJyg5552cFZnsLCmcEsjO9/rzC3Iys3FkF 3jy6BjJzGJmb4U3P8+dm+guSvA8GvDMz0wKF/swCrz8zLdubFeAz0gv6eQty0tAgPS2fazkkpzA7 kJWPyNzCnEw/PQsyA0pAgTffn4feUm2kZ2fnzffORnFvVk5+WnrAm5XrDUg70Iwh3uysXD4rb6Z3 RtYsJTj8QYHMogCDs+ZmJnkjZt5Q4M1Jyw150wsxPqx3YDafnznf60/DFn8WZjMwLcdbmC8/Bomz eFKQtYDugTwMCkqT0rzz0/w54c+Sbk6fneZHsUx/Upvrh7Z+pvfuvOyMoTIwtz6MgzDJe2vSbYMi b/vLt+2CkImn+cA0PmlWltQoExX9aRmZOWn+ud48+abd7cxLh1o5CLsm5WYFGD8xkBYIWzsAAXnq A9KJYsCflVmQNLowPTGtoK83I9N7vz+Pt4FA/tABA+bPn5+U0yo8KT0vZ0AglJ83y5+WPzs0ID0w My83UBDpKq9npmHAXNlvSl4hTg55CwsyUQKT5GtvGjHN9OdkBaRCM0JKvfsmjb6Lt351Q8QzCsOx nT87K312u7Gcs3LTswszpC/yvBlZBfnZfID0fr4/iw7p9MrMDSR5Wz87L5fUSMzq683MmSEHnReV 29r5khqp7jK5cX8B7kkPZ2Dbpyu/RmQNUwokZvEpTALper+cKhl583Oz89Lafyg6p4U1xfFtEcgr DOQXBnB7MCs9U/aZnZmdf4FBlxMLFYkBGZkz05hOSWkF+UWtfyfHHCM+uuT/JkejB982RJywmyZH S+QbltASOf9EiLbvbpf+udd6LDpao4+27HL7x8So/rWX2z8uTva3pFxu/06dVP81l9u/c2fV37jc /ldcQf971d9scvB9T/aX37I7q7/GNE10pSL31ixigNZJDNV6iPu0XmKCJv99+qCYqy0UQW2FWKqt FCu0l8WL1pHi19Yfi03WF8XHSNyChIoLZO//N7InInsasrORPR/ZjyH7GWSvQfZvkP07ZH+CxO1I 2NdRtvZWO9ndkX0dsm9B9h3IHoXsqcieiexCZC9F9jPIfgnZv0H275C9Gdl7kPgFEr7pKNuyop3s BGQnInsIsu9B9jhkT0f2XGQvQPZyZK9C9lpkr0f2n5C9A9n7kXgACQ0dZVuL2sm+Etk3IXsYsh9A 9iRkz0R2AbIfR/ZKZL+K7PXI/iOytyP7C2QfRqL8C19nO8q2BdrJvkp+40X2Hcgeg+xHkJ2D7EeR vQLZLyP7bWT/Adlbkb0f2fXI/gGJ/4N/Y+V8cvAt31W25DDt5JLKJQeWlNMcUcKh5+8obSqKX5Pv 0Lk5OzD8o0cJXW+KL6quLtJtQo/KL+UnX/WPl0/lc9klv/pUaWmR0yKc1tJSUap+wmNln+pIH37y davQbbXhDmGJtfkDa+02027zNfn4GeiwaA6b6oAg3SJ0KZJLq1VzRK1bt04pODB/k9TvrMOpOdz/ t/Y4deG0R0dHF3/GT7GuC91e9NnZ0tLiCwySL07JPp9F+vATltN0oUEOm3BE+SIWOS2aM2xRq0m2 iElRwqnjFamjvdUkp1tzxtTy01z7N9/faTt9e2jOKM1px6ja/GSsUiq3WjXQrgu7vWiFNKDYHqXZ pfGlpTvyXbrmcrQaxitdszvQ+mzp1iKXRXPZ2kwrVa/Ctn3W2k1aZ7dp9oh1pfJaV+YNrHWiOfad kvb5kqWwqNI2C+0Wza4s5NoWpbnsMvJK44iNA8+6ojVXbG1+Ez81m2TbO3DvwO00pXLR2a2lp4qj V5wtcjmEy2Ga8ZGfsJpnMeisMtReRN6Vnipy2zW3U+cneG779u3ngmETzmLp2eILLbVrdudXstv2 7eq6WA0J+02mcZulTaW+gU3KUh1LpalFyW6L5m619BKmupWpyoaBTU1hU8+6YzR3XG1ybXJTUZOa M7vX7F6zd82n8Z/Gu3XNraytLeopzXU7hLudufEOXXPwfgUBPJstb+yyc+nWs0XRdi36vMWY7LBr DmnLudLN54qlmu1sLlUvvzpXr6xu7anMdkRpDswOz0h5I13KxDnV5IoSrlbDsTzaYonWSy8wPeq8 6dHKdLducTtbTcf26FgtunNtz9qeTSlNKdXZ1dkyqz5d8emKLdFbopUNKYs2Y31KrL4coxwi2tnO /HinXXOi6nJ9kTTRqWtOR3Lx13z+18XJMQ4txmXlZ9jiI1u2bDmyeJjToTldKYuObDFLDy0eHm3R oqPa+aBUvT5oHt6ifto6M3RRippdrW4oVR+Ep4mKDIqMa6sj8ESMxRJz3hPyA2TJCruCm6goLcah yl60Q4t2xRedWhM2Rv3FPrmKusQblsnCmh7yZwvPLH/mXDE0Oy2Qyzd6l9AmTrjbK/82H73lSq6L GOGJ3GnCLmJZd+Xz8BMLK0Wc6EazPpia+oC4dsK4MV4x8KEJo7xieKSP3FN1Uv//QJNrF+tJq3Sb cIsurIfhuygRLa4QPcSV6fkF+aJEHder4yZ1/IM6/lkdN8/lC5nYoY571HG/On6pjrXqWK+ODfIb gTguj5qujj3UMUkd71bHh9VxTs7cnLnaInVcro7PquML6rhWHd9Ux41tO6N/d9Qu8+jAk1Z8QB3l Wv6W+//fMwtxiPmPz7GiF9+3J6jfPj0mVok3xPtis/hc1Inj7BmcylJHxNoGIX/XL/+6pEf9FVT5 FzmHhs9P7g+fX3253Rjy7UiPDvdaVKDjvb62473z6Y730V063vcKdry/5oL3vVd1vO/3tnBa2t33 z273XhfaHR90vL/PwtlFTieKVOyJZcxjuGqgJVUstpRYvhDrrK9aXxX7bQHb66Iyap/+pGZ1TXSl aR+6nnBr2o7oTtH3We6JfiR6rSUUkxEzx/KXmMUxKyxbYy2xDsvnsSdjT1pqhLY0VfpG3xez6ZJt J21/zMF27etI23mJ1hjbs631pg2mDadlqLbqwhazM/aV2I2dVkbay+1aiWqnL9U62zqPbGvLOj/b 1prCrUu3S7REWpJndbu2NtzUmwua57eezW1tR9cvabWqnbtU65LYLbpb7+7LIu3pdm21apsv2Sq6 n25t8Z74Hm3t3kgbecmWqtrDkXPHtiRylP22q7a/rYVHH4xvSrgxISNhbcLbsl0oPWHjpVpYesKf EuoizTjf5KcknFaftURy1eg+SW3tzj4j2trkSJtGC/SZdu31tMHX9b4uuc80jr2v+8P1f75hp2rf Jo6lZfTtQfP2rerbAFV9j9/455tWyda36qZNNx2knepn6efot5G2I2kQ7d6ksQNWRtr7Nwdu6XHL V4OX35ZIGzQkesjYIdnJb0bapuSPkncM7UXrNzQ47LOUFtluL759o2rfDu81fHWkrb39W+5XD69W d9XDv6OtvsNzZ/DOkru63Xcnbfv9qbcXh3tzrg73evB62e/BwSNdOPX6kStHxaqWPGqCasZoy+j4 0b1HGVyl0maOEWP0MRljWsa0jO05tp5+yeMeGvfQ6FSOM+QVbfY4/7glqbpq/VLHquZLzQVfalHq Y6lFvPenVo+fOt43/vj44xM6TVhLv368U28mnEotmjhjYvakPT++d3LVT1f+9OWflsx6bFb17Idn F7WeZ6+fvT5rYO6zuevyW+aJecPn+ebNmReY99i8TfM2z/t6XuO8U37d7/Hf6B/sv9uf6m8s6FRw fUF+waKClQXbC2oDQwMPBd4P1Bb2KNxfeDo4MDgzWBR8OfjB/B7zH5r/ftHsoqeLPijaU1QbcoV6 hkaEVoZ2Lrh2wYgFsxcsWLBswZsLNi34/FHPoyMeXfPo+4/y/aU4vnhkcUbxxuJvF964MLBw48La Rb0WDV40Z9GTi6oWexZPXfz24volPZd88i+q1qYLK1PHurPk6/NNVpSlsedbuJb8i9k38sI513Gm hHP9kvWntQa1ax2ryNLB55usD0vvPt/ClUFW004l8du7r6Yi7x9eTf1U1VidqbydR1JpV8W+0mll zM7W6tn52Zj9nZv6TJZjYzbFrjpfRcNeok4PV5U43Ktn7Cut3pNPVVWWfffL96p/xIPI3RRzkJr+ CiP2K2k70W4l5/2qnV8nvr5gfRjebkU4vya8IvW+aB0ouXAdoPbbInV/WWvFV3IYHTuc61WttZB4 vB2JF9UpXIHCFS4SR6oiNVBGbXJbfWyNKFUufqTsfz7CfUYgR743eJ6aUMf9RdlADdzfrppeosa2 r6kX19NI1d6u8ihcQe9srZ2ypvNkhJTL/Yj41NsSxz3U9Vx4JVNnVq3up1mrznWLZh2KrDytK0qX bl3PnV99wvko1zfZv+s52YPRm7tFyzfyiVrLeCLfdekWs7M1T+N78L6WT0BG92XqTj0/v6K2X1Ol Tmr9bF1B29ZQ1szoS6yZqy9aMyvCKyVrpKfVFt6fDuuhNFk2Krnrl/H3oluHaEgvXjhzWz0enpHS t+GM6TMZ74+UsZV+iU/1rFaRf1tGqt3sTkrY2KVb21q7PyJ1STgfZFzC+ZWw8bre114fJryqXXu9 WonaNbmqhVc0tSb+Hza1jrZrF/dQq2u7Flll29rFI9Tq+h81tf5edmtbpf9Fu9BTsrWt3f+iqdX8 spvaYVxmu9A7al/Srl3sP7Vfaddkpocj/Z+1iyX/e+0ur4X9LPcrsa+ktIx03f5tzH6501GtWD5J aZG7G3l3e/FIl9z3hN/Jxq6pn9wphZ+qtei7cFM7ojvVbkrum6qHV6s9kdw3VTOiWO1H9LZ9i2z9 UvVxM1J1uWdRd/0iO5vwdT/2PbPlE7W7YZw8yyb7M0JX0nzqbT95TNhI735y/9QtelTsuBlyryX3 Waolqyexcp+l7pLHzZCVKPKOJsuE3JGpHZpF7c1osj8j5A6OnnI3dn5/Nip5+HfKH99KT4w/HvZD SouyBn3Deo5OlZLVfs8iZYXldpyHF8ezfRbcsDN8J3St1NxjHWP+1jpJJFgnizir3zxi/UT0FRbe 7OKuWl01WCeZR4TG8Z/CwnGfdbK5j+/mG8wWsdVs0Xyij5YmJmkzOKeLRC1D9NLmil70HE/P6dZs s1xoyPlG2OgbR99e9I2jr0vJa6BXs3Bq00QP3vfn/XTeD+B9f2QNQlYio99S+ri5eh99e1mLzTLr QvM19L3Feth83fq16G/9RgyyHuHdUbPa+h3fdlu1rRM2rq7mqhfabEDSPlEk4sStohMMFdeIYZCB /EyYCQXmARFAq0IIwnwoghDfcBeY28SjUAwLYRE8LhLEMvgZLIcn4El4Cp6Gn8MK+JBv4B/BKa7P gSkSNAEapIpkbTxMgInwEGSJcdp20R2Lp1sfFinWR0S0dTpki1zrYixdKvpYHxe9bK+Z22zr4HX4 XCTY9sF+qIQq+AKqoQa+hL/DV3BAJER1Mqujas1tUf8QtqgGro9Bk7lNjxK36n053yKu0W/jnG1W 6zmQC3lQaB7Qg4BvdHyj4xt9AeAb/V2RrG+CP8JJkWy/UXS33wTTRYLdBzNgHvghBEtgKeAj+0p4 Hl6D10WifQPnY9AITdAMx+Ek4ENHOmRAJhSK7k4hkp0e0V3lbiN57VJXR4n6KdGVrN1J1u4k2/qQ baPItsfItqlk23SyLZVse4DepeTL3daHyZUfm+vJm0nkzZNICFg/MV+2HibPvhEua735V+tRMUrl 2RF61YvObbNimkhpJ3868guQPwn5d9F7RkT2Vkbdjux1yN4QkZcqYttJcSFlCFJykZKClJTInBiC lkeQNBFJzyMlFQl/VZb+UV3FI+MvyPgLMhK16eZHyElBThZyRiFnKnJGaFnm58hK0daYv2fkx8jr grwQmhUgsweahZC2ylpnNqPdVuu3zKyj5Nx3kRkb027G9kfqoMjslzO2kpEHmHljzFfJX3e4wsjf 6fK8RrwkHjcbxDL4GSyHJ+BJeAqehp/DCthpnhG74DPYDXtgL1TA3+Bz2Af7oRKq4YB5ThyE/4Za OAR1cNisEF/DN3Dc/EL8YB4SBpyAFjgJp8xK8U/m9Gk4A2fhf+AcuphmgyZAU1Wx3jrVbLL+xGyx TuPsM1tsn5sNtn2wHyqhCr6AaqiBL+Hv8BUcgG/NM7aj8B38AxrgGDTC99AEzXAcfgAD0MV2Dkzm bBezwn6necZ+H4yEUTDWPGR/iPMkmMr7R2Cauc0+3Wyw+2AGzOXdPM5+CHA9H4ogxH0x5yWcl8Jy rp8A4mB/jvNKzs/DL7heDb+EF+BF5L/G8ze4LuF6A9fvcv0xECM7MbITIzsxsv/dPGf/CoiRnRjZ iZG9Fh0PQR0QI/tR8wv7d/APbGmAY2alvRG+R3YTspvhOBj0JXb2Fp6f5J4YOdIhAzKJl0U8KzxE 6rSwimfNmrbVK4q7D7lbwd1Csrzaulf0FhpPW8S9ZGYVmVlFZlaRmVVkZhWZWUVmVpGZVWRmFZlZ Re+DZNoZMu0MmXaGTDtDpp0h086QRQ1kTAsZ00LGtJAxLXzebj6v1vpTZkIazDC/saab35A1VWRN FVlTRdZUkTVVZE0VWVNF1lSRNVVkTRVZU0XWVBHJFiLZQiRbiGIVUawici1ErYqoVRGtFiLVQqSq iEoV0ajC62fw+hm8fgavn8HrZ/BqA15twKMteLQFj7bgxSq82IIXq/BiFV6sUjN2t7Djy2Rmss7a +ypr7xprhbjG+jfRxcpqo/x7JOLfQ8q/T3H3I+7uwb9Fcm8hJrNOelgnPayTHtZJD+ukh3XSwzrp YZ30sE56WCc9fFJ/1soerJU9mLMHmbMHmbMHmbMHmLMnmLMnmLMnmLMnmLMnWE/jmLM1zNka5mwN c7aGOUu8qbYPi0Tm6THmaQPz9BjztME6Q/SzpkO2yIiso1ezjnpYOz2snR7WTg9rp4e108Pa6WHt 9LB2elg7PaydHtZOD2unh7lYw1ysYS7WMBcPMvdOMOcOMucOMudqWOM8rHEe1jcP65uHdc3DXKlh bfOwtvVgrtSwvnnI/4Pk/0Hy/yD5f5D8P0D+HyD/T5D/J1j/4lj/4sj/GnL+IDl/gpyvYQ30sP55 WP88rH8eIjXZPCazHhuZ2+zSnqV6T2Ltetg8SFX/Fe+fJB6/5+2b5Pwg6+dcMyutlaxjMoZf0PsA vaqp1M+ai7gLMbaGsfJpRmQd3M3Y/ozdw7gRQqfnm/RcSM86ev43PeeoXZbMnPVK0iO8H8P7PbyX OXI3klbw9nUkJSJpK5L6qf4Nard4WB1bWP/i2AtOhWzIgTzIh3nghwA8LQaIzlqpmuuvIH2V/HQV 2XXwsRhsLYM69rmHxQj2inGs3x72ignWbzkfZWf1Hc/+wc7Mysg9jOjGzjJBruyMzxYprGNT2Xc9 IlKt09QejFUazRLRLBHNEtEsEc0S0SwRzRLRLBHNEtGM7OMzHmHHNo3zdJGrRnoY6WGkh5EeRnoY 6WGkh5EeRnoY6WHkIEbexchBjLxLjYxjZBwj4xgZx8g4RsYxMo6RcYyMY2RcZOSoyEi5R3mEiE1n Xkkff6R2CqfxVp38b3BYy8fDBJgIDwknOzgnOzgnOzgnOzinU/53OzY83IUxc/DwaLUflzH6WuzX Es3DWl+4EW6CftAfkmAADISbYRDcAoPhVrgNhkAy/AiGwjBIgdthONwBd8JdcDfcA/fCfTAC7ocH 4EEYCaNgNIyBsTAOXjbrtF/BK7AWXoN18Dq8Ab+GEvgNvAlvwdvwDqyHDfBb+C/YCO/CJngP3off wQfwe/MHPFKnlZkHtM2wBbbCNtjO80/NKm0HlMNO2AWfsZ/YDXtgL/N2Kpk7zdxn22b+YNsOn8IO KIedsAs+g92sBntgr1kV1dmsi/KYh6O6QjfoDvGQYB7Wn4OXzDodH+hrzQb9TfMH/S14G96B9fAB z7dw3grbuK4wq/R99GfforeYh+1XmXX2XnA1eOEa8wd7b+gD18J1cD0rxw2QSN3qCzfS7ya4GQZx fwvvhrHapHCeYP7gsJiHHVawQRToYAcHOMEFboiGGIiFOOgEnaELXAEes87RFbpBd4iHBOgBV0JP QH8H+jvQ34H+jmugN/SBa+E6uB6dBrFvuAV+xMo3FIbx7E4YAffDdD5vBueZvJtFv9mQBXOgEBkL YREshiX0fY7nv6b/W/R/2zzgeIf79XCcZyfMw07NrHNiq/MKs8qJHc6uZoPTSw4VaRayxQo2iAId 7OAAJ7jADTHQyTyidYYucAV4oCt0g+4QDwnQgwzrZR7TrgYvXAO9oQ9cC9fB9XADJFJr+sKNcBP0 g/6QBANgINwMg+AWGAy3wm0wBJLhRzAUhkEK3A7D4Q64E2Q9uxvugXvhPhgB98MD8CCMhFEwGsbA WBgHqeZRbTxMgInwEEzCvofhxzAZpsBCbFkEi2EJLIXH4HFYBj+D5fAEPAl869BWmqe152EV/AJW wy/hBXgRXqZm/gpegbXwGqyD1+EN+DWUwG/gTXgL3oZ3gNVQ2wC/hf+CjfAubIL34H34HXwApdTy MtgMW2ArbINPYQeUw07YBZ+ZjVSRRqpII1WkkSr9BFU6j3UggcqfwjqQQPVPoWp/YaPi2ah4Niqe jYpno+LZqHg2Kp6Nimej4tmoeDYqno2KZ9toHrO9C5vgPXgffgcfwO/hT/AhfAQfw5/hL/AJ/BVK oQw2wxbYCrtFnG0P7BVxUZ2FK8ojYqO6QjfoDvGQIGL1FeYx/Rmq0HNcv8D1GvOI/pJw6cSAatao r+Mdtui/4R066+iso7NOldbfNY/qmwB9dfSlyjXqf6D/H3n2Ie8/AvTV0VdHTx09qX6N+qf02cm7 Xdx/BrthD+yFChGn7+Oz+Yan8w1Pr+LZF+ZpKmWj/iW68a1OP8LYf3DdwDV7bJ09tv498M1Fb6b/ cfgBDDgBLdh20jxqjzWP2eOgE3SGePO0PQF6wJXQE64SLnsvuBq8cD27whsgEfrCzTwbxPkWGEzl HQLDzEZ7iohzWESswwo2iAId7OAAJ7jADdEQA7EQB52gM3SBK8AjXI6u0A26QzwkQA+4EnoCejrQ 04GeDvR0XAO9oQ9cC9cBdcZxE/SjIvaHJK4HUjlv5nqQ2UglbnQM5vo2GALJsjJjx1AYzfUYGGse cYxj3BTztGM6us3k3SzGzYYsmAN803Wwr3TMh4V87iJYDEvo/xSfx5ynUjc6XuC8BlkvwcvwK3gL eW/DO7xfDxt4ZtDvBGPPmKedwjzq1ITL6aBy40Oni3Nnnl8h4qjmjU5WJWd3nsVDgnnM2QN6yt9I ytkd2Us9xaysU/uyv7Y9X8bzx9VvUOQeq1lEWR4wH7aOkb+ZEi75Wy31rp9loFlvGQxDzCOWOzg/ YO63PGhus4yCMWYFkqrZUdSzo6h3TTa3uabCE1w/CU/B0/BzWAHPwLPwHKyE52EV/AJWwy/hBXgR 1sBL8DL8Cl6BV2EtvAbr4HV4A34NJWZ99E1mvbCiaYtlMt+Gpf7D0N9Af8My1KxGf8NyD+enzEOW p81D1C0vNctLz22uiWa16yF4GH4C6eYh1xzIhlzIhwA8YRrYZmCbgW0GthnYZmCbgW0GthnYZmCb gW0GthnYZmCbgW0GthnYZmCbgW0GthnYZmCbgW0GthnYZmCbgW0GthnYZrhHmofco2A0jIGxMA5S Ybx5CNsNYjjE/IIIVVtUHM2P1e8irsb2Ddi9wfKI+bElA3LgKbMcH5TLbyPYvgHbN2D7BmzfgO3l 2F6O7eXYXo7t5dhe7ioyP3aF4FFYCj8zP0avcvQqR69y9CpHr3L0KkevcvQqF3cRgSARCKJbPREI ot9pMqiZDGpGzy/RpA5N6qyTzp1E37jIt5n+kW8z/SO/I6wmu5rJrma0q0O7OrSrQ7s6tKtDuzoi EyQyQSITJDJBIhMkMkEiEyQyQSITJDJBIhMkMkEiEyQyQSITJDJBIhMkMkEiEyQyQSITJDJBIhMk MkEiEyQyQSITJDJBIhMkMkE8UIcH6vBAHR6owwN1eKAOD9ThgToiExT34AUfXvARi714wUc89loe ED2wfgrWTyFaSXx7fT3yHfqWyLo6ILKuDoh8L/YRq73Eai+x2kus9uKNKXhjCt6Ygjem4I0peGMK 3vDhDR/e8OENH97w4Q0f3vDhDR/e8OENH97w4Q0f3vDhDR/e8OENH97w4Q0f3vDhDR/e8OENH97w 4Q0f3vDhDR/e8OENH97w4Q0f3piCN6bgjSl4YwremII3puCNKXhjCt7wCTu50IzFfbF4ERYvxOKu WJiHhY+IBHz0Hv55D99U4JsK/BCHD+Q/P1qP/e9h/3vY/x72v4f9Fdhfgf0V2F+B/RXYX4EeFehR gR4V6FGBHhXoUYEeFehRwVzJwtMd691x0d8yniydTK3Los7NocbNhWzINSvVby5aa91CasZic5v7 UbPeXQwLYREshiWwFB6Dx2EZ/AyWA7XRTW10Uxvd1EY3tdFNbXRTG93URje10U1tdFMX3dRFN3XR TV10Uxfd1EU3ddFNXYx1ggvc1DxN/fZL6m4wx2uY4zXM8Rr85sZvbjV7iswa5m4Nc7eGuVvD3K1B dwPdDXQ30N1AdwPdDXQ30N1AdwPdDXQ30N1AdwPdDXQ30N1AdwPdDXQ30N1AdwPdDXQ30N1AdwPd DXQ30N1AdwPdDXQ30N1Ad1mzJptf4e1qPPxxW82SFn0lBmFRCe+/4f1potFCNFqIRgt9v6TvQPqm MFNcWJrITHFhbSJ59Iys/USohQi1YGUJVpZgZQlWlmBlCVaWYGUJVpZgZQlWlmBlCVaWYGUJVpZg ZQlWlmBlCVaWYGUJVpZgZQlWlmBlCVaWYGUJVpZgZQlWlmBlCVaWYGUJVpZgZYm4FUtCxGY3sdlt yRLdiM9uLMhkBjQwAw5jyTNY0hNLbsSSnlhyI5Y8iyWbiN1uYreb2O0mdruJ3W6sCmFVCKtCWBXC qhBWhbAqhFUhrAphVQirQlgVwqoQVoWwKoRVIawKYVUIq0JYFcKqEFaFsCqEVSGsCmFVCKtCWBXC qhBWhbAqhFUhrAoxjyereZyMFZ9jxQeRfx4r9xVvCjf2lmNvObaWY1dXbOrKm3expxx7yrGnHHvK sadc6JZCYhwkg+ebRy3LGP0M68Mv5e/YefpPyzKzRWgcT4q+9DhpKeJZSD3fa1kunJYnGM1e3vKC 6GRZw/OXzH+6r4SecBX0gqvBC9dAb8iATJgJs2A2ZMEcmAvZkAO5kAf5MA/8UAABKAT0c88HdHKj k3uB+U9lzz/RtN6y0PweW45YVpuNlhfRf6rFT10rgEKeFmFlCBabn1uWwFJ4DJaJqyzLzU8sz9Fv pXnA8jysgl/AGnMH9u1wW6hlVrBBFOhgBwc4wQVuiIYYiIU46ASdoQtcAR7oCt2gO8RDAvSAK81m fNiMD5vxYTM+bMaHzfiwGR82u4ean7uHQQrcDsPhDrgT7oK74R64F+6DEXA/PAAPQgZ2ZMJMmAWz IQvmwFzIhhzIhTzIh3nghwIIQCEEYT4UQQgWmDuEjcw5hBdr8eJRywvmGXJpmfkdeXJSpBIFgygY 7TKpkhWnkRWnkR6NeNmwyF1autnICtPICtPICtPICtPICtOI9w28b+B9A+8beN/A+wbeN/C+gfcN vG/gfQPvG3jfwPsG3jfwvoH3Dbxv4H0D7xt438D7Bt438L6B941/m8Ej0WMUjIYxMBbGQSqMhwxk ZMJMmAWzIQvmwFzIhhzIhTzIh3mAb/CugXcNvGvgXQPvGnjXwLsG3jWEA+/+NxneQoY3WBaRw8uE B2/X4e06vN0s8vFxGT4uI9Pr6bkHX9fj63rLAmbqQiKxiJGLzSYyv4nMbyLzm5CiE4ddxGEXcfje 8iwVc6V5mBlwmBlwmBlwmLm0n9pQTowqiVElMdpFjHYRo13EaBcx2kWMdhGjMmJURozKiFEZMSoj RmXEqIwYlRGjMmJURozKiFEZMSojRmXEqIwYlRGjMmJURozKiFEZMSojRmXEqIwYlRGjMmJUT4zq iVE9MaonRvXEqJ4Y1ROjemZIEzOkiRnSxAxpYoY0MUOamCFNzJAmZkgTM6SJGdLEDGlihjQxQ5qY IU3MkCZivIsY7yLGu4jxLmK8ixjvIsa7iPEuYlxJjCuJcSUxriTGlcS4khhXEuNKYlxJjCuJcSUx riTGlcS4khhXEuNKYlxJjCuJcSUxriTGlcS4khhXiiwi2EAEG4igQbw/JooGkfuKyH1P5JqJXDOR ayZyMv7dif+HRK+B6DVYfs6zZ4j0c+ZGIniMCB4jgseI4DEi2EQEfyBP9hHFb4nit0SxgSg2EMUG othAFBuIYgNRbCCKDUSxgSg2EMUGothAFBuIYgNRbPhfxN17nNT1fe/x3+4Mu8swyySKRo3RWIy3 1Hg3TUya2p6WpsZEkyalpjFpg2kwVnMB4w1v4AUvIMrN4AUiorBUrRFTlgSCIOJtWFlchoRhF9zM zLrDjr9dWGSJfM9zJsRjctrHOX08zqPnj9fjNzP7m9/v+31/7iMzsmKZFcusWGbFMiuWWbHMimVW LLNimRXLrFhmxTIrllmxzIplViyzUsxKMSvFrBSzUsxKMSvFrBSzUsxKMSvFrBSzUsxKMSvFrBSz UpmVyqxUZqUyK5VZqcxKZVYqs1KJlUqsVGKlEiuVWKnESiVWKrFSiZVKrFRipRIrlVipxEolViqx UomVSqxUYqUSK5VYqcRKpehUVhpkpcFaNE6JMqwQs8IAKwywwCALVOemAeoOUHeAugPUHaDuAHUH qTtI3UHqDlJ3kLqD1B2k7iB1B6k7SN1B6g5Sd5C6g9QdpO4gdQepO0jdQeoOUneQuoPUHaTuIHUH qTNAnQHqDFBngDoD1BmgzgB1BqKTZIYhmWFIFu5Wz1P1d9rFXTX/sXqPZ2Ouv98fhkTckIgbEnFD Im5IxA2JuCERNyTihmg9ROshWg/ReojWQ7QeovUQrYdoPUTrIVoP0XqI1kO0HqL1EK2HaD1E6yFa D9F6iNZDtB6i9VD0bVp30brListWXM1fRVFQFAVFUVCs6f+7CJjOy++RDWfgXtwHHXx99ZON/9zb u9ijiz262KOLPbrYo4s9utijiz262KOLPbrYo4s9utijiz262KOLPbrYo4s9utijiz262KOLPbrY o4s9uihYpmCZgmUKlilYpmCZgmUKVqOhKBqKoqEoGoqioSgaiqKhKBqKoqEoGoqioSgaiqKhKBqK oqEoGor/F9FQYKECCxVYqMBCBRYqsFCBhQosVGChAgsVWKjAQgUWKrBQgYUKLFRgoQILFViowEIF FiqwUKFW4yu60u3R2e9mr5kyjl6S9mXa//dklHG4BN/CP+PbGA82t8eyPZbtsWyPZXss22PZHsv2 WLbH8oiqL0zElfgh+Js9lu2xrMe90o7+V8yURfwu+bYa6YNy6uD/KUb07lfqsafw41v5650e36VX mm76nh0dFH2ecn2U66t15ZNwvbOmOE6V9++AuU9sVqtz7F0n1rrbWR7PDf0U7ufdFd5d4d0V3l3h 3RXeXaF8H+X7KN9H+T7K91G+j/J9lO+jfB/l+yjfR/k+yvdRvo/yfZTvo3wf5fso30f5Psr3Ub6P 8n2U76N8H++r8L4K76vwvgrvq/C+Cu+r8L4Ky/SzTD/L9LNMP8v0s0w/y/SzTD/L9LNMP8v0s0w/ y/SzTD/L9LNMP8v0s0w/y/SzTD/L9LNMP8v016aVPZR6+d25JY4StbnGJM1K+6Iv07aDth3sV2G/ ilq621+3ssQI+pboW6rlv+msNFNGmaVTmquDvT/00LVE1xJdS3Qt0bWUqtaG+tBB1w66dtC1g64d dO2gawddO+jaQdcOunbQtYOuHXTtoGsHXTvo2kHXDrp20LWDrh107aBrB1076NrBpyp8qsKnKnyq wqcqfKrCpyp8qkL3Et1LdC/RvUT3Et1LdC/RvUT3Hrr30L2H7j1076F7D9176N5D9x6699C9h+49 dO+hew/de+jeQ/ceuvfQvYfuPXTvoXsP3XtqGld176Xx29FB9ct48urwfP1z/HJNmFD/QnikfiD8 sn53uKN+b3gt0Rx2JE4OvYlTwuOJM0PXu/9O+SvREYm/izIH/r3yDtZayBpPiLDneP8aPexalnge L4i09SzzssdZvegmlnzdsQOl6JD6HlVst/cNev8eDLlbFDoTjWiC2ujuxcRpXj8dZ+Cs8FbinPBG +huhnL4kvJj+DuSH9BWO1EhTIy0fpK91nBRK6etxAyZ77S6v3Y1pMO+k7/PaTMzxmPekH3CNhWEw vdj1n8RToTf9b3jaaz/xfLmjPaXbvPYaNmKz5zn8yuOt6HLeztCZHsCe0Nk8KpSaD8GhOBofxrFe vzS82HyTx9bVfFvoab479DbPwv14RMfyNwdU3c5G+6i6map5quap+g5Vt1K1SNXNVO2n6maqbqZm HzXL1CxTskzJMiXLVNxDxZiKMRVjClYouJ2Cmym4mYLbKbiZgkUKFim4nYLFP1BwOwXzFMxTME/B IgW3U3A7BfMUzFNwM/Uq1KtQL6ZeTLkKxWKKxRSLKRVTKqZUhVJlSpUpVaZUmVJlSpUpVaZUmVJl Sm0+oNR2SuUpFVMqplRMqXJ0TP2SML5+WVhKqXV88DcUeoIqpfpt4fv87Mb6nrCIZ4+v3xVaefZF /CyfSIRcoiHMS6TD7TVPHxVOSRwdXZr4SLiN1/954mPhm1R7jud/js+tSPxpeCRxbhh34BOp/IF/ lXxpYnxYJQpWRGl372CnDnd/xd262SLrbjtcveyKA67W4WqxGDpHDJ0bjbTuQe/a6F17vasaH4PW e7p35w5EYMm6dlrXka7Q4QoFV3g9aq7tdI3O6YXwlHec4R3b3W+rd7Xb0T7v3O5dRx94V867OqMP 8aiKd/XxpAGeNMCLennRLl7U4967eVEPL+rhFT28oodH9PCIXTxiF2/YxRsqvKHCGyo8YYAnDPCE AZ6wiwcM8IABHtDDYj0sVmGtATm+FB1rLc32u1Bft8R9/90almN9eLv2b3jH8oCrQp/rF1y/4PqF 9P2ePxT6XKcQJb1rr5V/yzter1pW3lgSXmLzTq++7tVsPe+q6bdNvhhFuy+H11339Wisu05z9o1i qeAdT7n7JHef5J17KLGbErtdYXP9y2bzrPtsosjrjh3IhRZXXMaDNtaXeUMKo8JVCTU1oaYm1NTE 6DA5cSw+wsYneH4iTtZfncnun/H43LDLaj5rNZ8VcwXq7qXuXjFXoPDe9HejUenvQadGhUnpaz2e FKZRYholpom7ArV3U3s3tXenp/v7fV6biTmez8X93veAaz3k+K+UewIrwuT0WsdX8Cqy2IJfIu9v nY7bsSNMbo7Cc83DQktzAxpxjOfH4dKwlwWmib0Ca+5uns0iczAXP8KDoUVFXl3zxB0s/Veyzn5Z Z7+ss5/V/0KE7xfh+0X4ftG8PzqSPWLal2lfoH3Bu5rfm5vsPbb32N5j+y7Yd8G+q3st2Gvh3bzy H+QUa42ts/DeHFGXcseJPOAW1m9l/cmsP7n+5yy6EqtF69ro0Prn8YIc8jI/3ej1av7IqYpbTN+/ xK+wFXlsC7fVdzruwBv8r9vx1yiiFN3EW56uf9PjXpRdY6djHyru+xZij/sxEK6Sk9pl7KKMXRS9 46u5qX6f136Dd8Km+v2OQVTXoR7VvJXkbcM8bghP8sgJiRG1qL9B1HclMmFm4n14Pw7CqHAub72I t17EWy9SU5cmjgjzEx/0tyNxdPS1xDGOf4TR4XyefD5Pvj5xnOfH44QwlkePTZzk8R/j5PBFuXGC rPIqqy1htSWstoS3XyBPtibOds7H8SfhJ4lPOH4S54SFiU85fhp/GqaJiosSf+bxueFGkfEt+XS7 fFr9l9nXJC6KjkpcjPFhQ/Uz8vT4sDF9Kb4bjRQlI0XIZBEykpdM5CUTecnE9E3+fjNux1Tcgbui Q9N3YxqmO3+W12Zjjudzcb/rzPP8IceHw8z0AjyChWFp+tEwXxVbmF7ieQuW4l/DWFE1VmVbyAOX 8MAl+oKlqtvC9DPhJ+lleNZ5y722Ipyf/pnHP8dKr6/1Pr6VXu+6L3ntZbzitVeRRZtrvYaNaHf+ ZufmsMXffolfeX0r8q67LbSL3LGq50LRe5HoPT/9htf4YJoPpgvgh+kSesLraX6Y5ofpMvhguoK3 ENt3PwY9fjtsSu/FkMfvgM+l+ZysMKGZ3zXzu+ZE2NScdBzmtQY0osnz4bJHCnywOR1eb27GSI8z eJ/X34+DcLDXR4WiCl9U4YvNH3C9w5xzOI7AB3EkPuTco/39wzjGPf7IazKsbDSh+YawUYRPbL4t OrSZrZvZupmtm+/EXbg7LGm+L8wX+UtkqrEy1ViZaqwssES2Gts8z3UedJ2HXfMR11/o+aNYhMfC 5Fon8W1Z4ieywos6iU4Z4ecywa9E/FSR/QOR3SJql4ra1ertLhH7UxHbLSo3i8a1ovApUbhR1H1W ZF0ikh4RMXeKmJ+ImO2i5E5R8rIoWMn75x34jtOzvP/Z2n/T/n7YEP2TfLXIShapWOvrn1Sjl4WX 5a1H5K1HrKqaPf9d9lwje65RuRYfqOGr1cCS1XarXqtVr9Xy12Irf16eKlh5tlrBrLoo33TLN91W vk2+zlv5oJydl7PzByrcY3LBYrlgsVXutsorqt/SUL3Wp/9Rj3tJWK2CrVbB1qtgq9/tEa70/Krw yIFeYZH4XCQ+F6lg69PmjvQtuBN3hTWy+hpZfU2td7jP32dijudzcb9rPOC6DzmuCIv5/WJ+vphP F9STvHqS57cFNSXPVwsHqtdifrmYXy7miwW+1s3XuvlaN98q8K0Cv+rmV9216nasTvK3FW41n1qk wq1XOdbwj8X8o8A/uqOJqsQ6VWIdf1jFFx6ldEV1WMcXviCbt8vm1Sz+PFXzVN1I1Y184mmZu5Oy bTJ1O2XbKNvGN+Jahj40bJKNN8nGm/jI6Xxkryy7RZbdcqBfa5NZV8isK2TWFXxmg2z6miy6Xubc JCOukxHXUb1C9Qq1KzLgOhlwnQy4TgZcJwOuo2xF1lsn662T6dbJaOtlsS2y2BZZbL0stkIWWyGD rZfBXpPBXpOtXpOttshOW2SnLbLTFtlphey0QnZaITu9JittkZW2yEorZKUVstEW2Wi9bLSJddpk lnaZpZ2V2lioTXbplF06ZZBO2aJdtqhmhnaZoV1maGepjSy1kaU2ygqdMkA7S21kqY0iv52l2kT+ OhG/TsSvE/HrRPw6Eb9OxK8Q7StE+xbRvkW0bxHtK0T7FtFejfKNorxdlLeL8nZR3m4OLumMqz31 mWEoOkuU7RJR3xBRs0TULBH1AjsvFDV72HURuy5i10WipciufezawqYtbNoiInaJgl1ssZAtFoqA aqe8kMfv4uWzePksXj6LLRby8l28vNopz+Lls3jzHnq10KmFN++hVQut+mjVx6v30KuPJ++hzyL6 LKLPIvr08eY9vHkPjRbRaBF9WnjvLt47i+fusedF9rgm3Mpjd9vBk54NWPvu8BDfzEVH2FnFsy12 1mlnnXZWsKuX5IGinb1kZy9ZXXU6e8nqXrK6itW9ZFUVK6pYUacVdVpRp9VUrKZiNZ1W02k1L1lF xSo6o6PdaaA2lwy62x4M6RLf0SdHte4ldrd2d6tWqwF3q/pMu7sNuFu1Kg3QYsBdB2gx4M4D7rzF nbe48xZaDLj7gLsPuPsWd9/i7u3uPuDuW8wI28IDdr7Brje4c+yOBbnsxzLuZhl3s5z2oIz7ctTg rMED81N84BtLJyfGRqOjE0R5UZQXndHpjO7fTdfO7LSTQTvJivKqblk7ydpFVgQURUDRbrJ2krWT QTsZtItBEVAUAUURUBQBRRFQ/L3J9wPO+ZDXfjcBj/b42JDlzcXqtMubi7y5yJuLvLlYs+2vrOzt mm2HedZf+0xlL4Zkkobqt5F0VWfrqs7Wq+fsoRx2+ltZrt8pd+6UO7vlzm65s5obd8qLO+XBblfb VvObTbUrJWoKxtFxrrHMX5azbq9rtTrjrXd10UPQpJcevfTodY/WA//G8mpW7qVPL116WbmXNr2s 22sNrdawzBqWWcMylu79PU0+6PmR+J0mxzj/WM+Pc3zQ+Q/XPjMpR3V2H0cfsL7eA3VuqzVtrUau Ne2w+l9b1w7r2mEdO6xjhzXscO9e9+517+p9t7rvVvfd6n5b3W+re+1wn+o9tkbHuvpjdt9q5yve UwOqs36rO/XVcn6q9i917jvgaVtrne335ccDudGOV7jrY+76mLs+9h/mxWoePMZ51Rx4nGM1nz3o 3D/MZ8Ot5qdWsK32aUND7Xuxl7rzBnfecOB7Quui060758w1rJY1tRSsfz2VVlGplUrVtf8bj64q 9QxbV7uCPmo9Q61n7Ge9qy5wtVZWzOosq5X4GQo+w5JVL3+Glxd5eZFFs/a3nrcX7TFnjzl7zLFq VodY0CEWdIPVCt1K6VZKt/L6IitnWTlL9Vaqt9r7eso/Y+/r7TvHylkWaI0+SPU2qrfZ84t2ULHv X1h1Vfk2K+6z4j6r66N2G7XbrLLPCvuo3EblNiq3UbmNym1UbqNwmzv1UbiNum3UbaNuG3XbxNfu cC9tNtKjh4epCOLpFDX7rPB2lNArvVr7dO2ssC06xrPdtU8tR8txx+K00K+O96vj/c4YVMN7dVSV A58y9qrDvepwvzrcf+BTxt7ap4wr5L3fftLYr/b2q7397/mksV/d7dcVDai7vTqjAXWwXx3sV/v6 o+E6jT1W8oDOIq59gntmKLlr9RsJj7Pg47VPbZv0InFilDWfXPt88I3a5xVnefeXo7+U/46Kkq7x Ru0ap4R91c9d7Zb9nL/DudupMMqOzgp7anqs9KgvOsSj+A8+aexLXKTzvThst+M+O+57zyeDff/J J4N9753gow+7U/XT4J107aZr9x98Ilxyl5003ekOO91h53s+ud3pLjtpupOm3TTd+Qef3u6k6c53 P73NO6fL8x0y4Xs+kY3q7HpXdGyiuWbxR/VwA3q4AT3cgDU9a03PUmqPPq6ij6s4u7/2Wd9n/P3c 2rf8llF+mTz8YXm4+u+pi3qxil6sYl3P6rkqeq6Knqui56rosSp6rIr1PKu/quitBqzpWX1ORZ9T 0edU9DiVqNFqnnbnXbVPGKsWPNedvxxWu9vqaLS/bqfbNmvcao1bnVn9RP1N+vXQr4d+PfTrot+e 6udUNNxGwz003EPDHhr20HAbDffQcJu1bqXhNhr20LCHhj003EbDbTTsoWGPNW+l4R7r3UrDHhr2 0LAnOpRqnVTrpFonpfKUylv3VuvOUaqTInmK5KmRp0aeGnlq5KmRp0aeEnlKdFIhT4U8FfJUyEdH 2GfJHkv2WKqpcYorn6Yin44z8Cfi5Sl56t/wjMfLsCKU9Lv99pK1l6y9ZPW3/faRtY+sfZTsoWQP WXvI2kO29h3O6r82PjyaG42TCS7Bt/CD8Hh0TbgnuhbXYRKuxxvh0agbv0a/c/aG6dEQ9uE3eCdM rzshtNediJPwUfwxTsbHcApOxWk4HWfgTJyFs/Fx/Ak+gU/iHHwKn8af4jP4M5yLP8df4H/gL/FX GIO/xmfxNzgPn8P5+Dy+gPHRUXW/CC/WrQ5r657DGqzF83gB6/EiXsLLYW3y4XBPcj4W4FXPs9gA e03uRwjTh70vLBp2UHh02KjQPuwQHIoP4DAcjq5wz7Cyc3birXBPw4k4G5eFRQ3/gstxBSaGxxuu BN0bpof2hrawtmEwtDceF9Y2Ho8TcCJOxxn4FC4KjzZ+FReH6Y1zsBBdnm/HDrBZY094vPFNVPxt l+eDYXpTfWhvSkB9bxqGBuhfm/SvTep3k/rdNAJpNGMkMlDTm9T0JjW96WB8Iqxt+iS+7vG3HG90 fMzxcewO7cNda/jBYW30teggHncwRuEQHIoP4HicgBNxEj6K8/A5nI/P4wu4ABfii/gSvoK/x7iw lOcu5blLee4d0QQzwkRciR/iKlwTnuDNT/DmJ3jzE7z5ieQdIZu8E3dBVCSnYTruwQzci/swEyIm ORsPe998LAhPsPrSYZtDdpjoGpZHJ7q8XnAsouzvO/GW194J2YYG6KsbhiOFw3A4PoLjQIcGOvCO JxrOdDzb8RzHMfgaLsbX8Q1cFpbynKU8ZynPWcpz7uA5dzTYb4P98qAnmq6oahPN0FPdi/swE7Mw G/qtqNpvPY7FWIKX8DJewavIYgPa8Bo2oh2b8DpyeCMskxOWyQnL5IT2yMwT7QLbR3w3MvvIE6vk iVXyxCp5YpU8sSpZCu3JHryJXpRhZkr2QR+a1Icm9ZdJ10y6ZtI1k9X37UcIq8Tbska5oFHsN4r1 RrHeKM4bxXnj3+LLuMg5X8XFYVXjdzyfgIn4Ia7CdbgVt0G8NdKokUaNNGqkkXha1fhjx4WOTzqu AB0a6dBIh0Y6iLVlYm2ZWFsm1paJtXax1t5oT432JOZWiblljfQQd6vqPhYldSPD0IBGNGE4UhiB NJpR/c3pT0YnR+dgXJjHx+fx8Xl8fB4fn8/H5/Px+Xx8Ph+fH10dHcTPp/DzKfx8Cj+fws+n/Bd+ S+r0qBVvhNksOptFZ7NoC4uuZNGVLLqSRVey6Mro7ej9rDqNVaex6jRWncaq0/67vhdff2p0eP1p 0cn1Zzp+Bn8d5tV/NsyuPw8XRofVjw9L6i8NN9d/B5eFm/Vslye+Gm7Xt12e+LrjBJPMRHW6Lcok XotGJdrxuirbER2VeCOsSnR7/uvohESh9qsOoxNvOvZGmeSE6KjkRFyJH+IqXI1rcC2uwyRcjxtq v6M1Rb6YIl9M+a/+jhZvn8bbp/H2aXLNvNp38g8Ks+WYKcN6o4Pkl3nyyzz5ZcqwfdFRDQnwrYaD cDBG48QwpeEkx9NwRnSynDKl4eMeXxbmyR/z5I958sc8+WOe/DFP/pgvf8xv4EsN14Avvftd//aw 43/73n71u/ifDytF2myRNlukTXv3d7h+9xtc1d/emuP13/7+1umiaVrtN7i6nL8dO8DnRE6LyGkR OStFzsrGndH7G/tQcf4uf+d/Imha9Xe6/p99R/+9v/X1nu/aV79HnxobZqfsKzUp3Jy6AeImJW5S 4iYlblLiJiVuUndjGqbjHthv6l7ch5mYhdmYg7m4Hz/CPDyAB/EQ6JOajwX4MR7BwujwEddGh424 DpNwPW7AjbgJN2MypuAW3IrbcDum4g7cibtwN6ZhOu7BvbgPMzELszEHc3F/dFj6o9HhI4dHh41M YUR0mG5xgyh4o/YrJhtqv3xyVP0PZbOMbJaRzTKyWab2f0wYjur/Z2oE0mjGSBykuz0Yo3AIDsUH cDx00DqAvA4grwPIy3yjZb7ROoGiTqCoEyjqBIo6gaJOoKgTKOoEijqBok6gqBMoypITZMkJsuSE 6NsmrfG4FN/BZfgXXI4rqv9WHd/D9/GDcPV/mFGvCWNk0zGy6RjZdIxsOkY2TcmmKdk0JZumZNOU bJqSTVOyaUo2TcmmKXW3oO4W1N2CultQdwvqbkHdLai7BXW3oO4W1N2CzDta5h2t/sbqb6z+xupv rP7G6m+s/sbqb6z+xupvrP7G6m+s/say9QzZeoZsPSMqhnJUQg/eRC/K2Ik+VPAWYvSHp2X25TL7 cpl9ucy+XGZfLqtPltUny+qTZfXJsvpkPX1OT5/T0+f09Dk9fU5Pn9PT5/T0OT19Tk+f09Pn9PQ5 PX1OT5/T0+f09Dk9fU5Pn9PT5/T0OT19Tk+f09Pn9PQ5PX1OT5/T0+f09Dk9fU5Pn9PT5/T0OT19 Tk+f09Pn9PQ5PX1OT5/T0+f09Lm6C6LD6y7EF/El/C1+FLIqUVYlyqpEWZUoqxJlVaKsSpRVibIq UVYlyqpEWZUoqxJlVaKsSpRVibIqUVYlyqpEWZUoqxJlVaKsSpRVibIqUdYs0WqWWGWWWGWWWGWW WGWWWGWWaDVLtJolWs0SrWaJ1rpXolTdq8hiQ5RSxTKq2EhVLFNv3lHJMvVmGtVsuWo2TjUbV6tm Xw3l+nEYH+a8t6rV/0vt113GqGyXqmxjVLbqryQ9mfhBeCyxQhVbGTUnVofbEhvCU6pcRpVLqXJF VS6V2Bx2qHQtB3676Kja71y+6fXeaJgql1HlMqpcRpXLqHIZVS6jymVUuYwql1HlMqpcRpXL6KSL OumiTrqoky7qpIs66aJOuqiTLuqkizrpok66qJMu6qSLyTkhTs7F/fgR5uEBPIiH8HAYo3KOUTnH mLtazV2t5q5WVTSliqZU0ZQqmlJFU6poShVNqaIpVTSliqZU0ZQqmtJnxvrMWJ8Z6zNjfWasz4z1 mbE+M9ZnxvrMWJ8Z6zNjfWac3B3KyUHswdvYiyHsw28gJlTmySrzZJV5gsqcVZlnmP9y5r+c+S9n /suZ/3Lmv5wpIW9KyJsSiqaEvAo+Zlh3iE0KeZNCXiWfoJJPGGZNw6xJRR+jomdMDflh+z0PIW6I UId6JKKMSp8xUeRNFHkTRd5EkVf5Myp/xmSRN1nkG4507ocw2msf8fw4yLWmjLzOYIzOINNwqr+f 5nhGNNrUkdchjNEhZEweeZNH3uSRN3nkTR55k0de5zBB5zBB5zBB5zChQR5tkEcb5NGGH2ACJoar dRNXv9tNyKHm2ZxOIquTyDY8FKUanowOb3gKz3j8U8fnHdtCqy4j28CW5t5cQ/UXOT8UsjqOrI4j q+PImoVbzcKtZuFVZuFVOpCseXiVebi18ZwoZSZuNRfE5oLYXBCbC2JzQUGXstxcEJsLYt3KDN3K jMZ/COXGr+HiMNl8EDde5rGYarwcV+C7+J5rfh/2ZXYomB1is0Nsdoh1OCkdTsoMEZsh4sY7nH9n 7ZcNY11PyjwRmydi80Rsnoh1QZN1QSld0GhzRawTmqwTSpktYrNFbLaIzRax2SI2W8Q6pBk6pBk6 pBk6pBmN3a79axQg1zfK9bqmp3VNT+ualuualuuWJuuWZuiWluuWJuuWUmb9nFk/Z9bPmfVzZv2c WT9n1s+Z9XNm/ZxZP2fWz5n1c2b9nFk/Z9bPmfVzZv2cWT+n68rqurK6rqyuK6vryuq6srqurK4r q+vK6rqyuq6sriur68rqurK6rqyuK6vryuq6sk2nW9MZ+ERobfokvu7a3/R8HC7Bt7z2z47fxnhc iitCUYeW1aFldWjZphu9Z7rXH3Pu42FV02KPl2B3yA2PosN1cNnh9jb84NA6/JAolfpSaE+ZC1Nf wdgwTmc3LvUPHl8VyqmrcS1+1+nd5PEtuC3K6PgyOr6Mji+j48vo+DI6voyOL6Pjy+j4Mjq+jI4v o+PL6PgyOr6Mji+j48vo+DI6voyOL6Pjy+j4Mjq+jI4vo+PL6PgyOr6Mji+j48vo+DL/Hzu+zO91 fIdE08Jf1V0cXVT3DfxjdFXdP0X/WPfN6IK6cdG4+r+O/rx+fPSpxJfDVxJjw4WJ1tCaWBnGJXaE dr3hqER37TdeFyRKIZvoMUu9ad7qDYPR0dG0/aWoJXRHa0O3q3/6wC/SXuDq57r6uQd+SXaw+lvR 7nK4u6Tc5dPuMsZd7kn8LLyU+DlWhlTiF46rwxuJ51x9TXjY3Re4877Er2t3/4K7P+DuKXdf5u7t UVMi64w2azLJJzZae3t4MbHJax0q4mZnpK3tZWt72ZnfUDuzzl7g7NudfYizW5z9FXV0lXdc7x2T o2Oqvy9ptfNV8z9WvcfXn6+Sjw931V9e/bed0TH1a8LE+hfCgvpt0Tn1u82jo/TPp4RnEz9TfVdG p9rBendqNY+mEhtrs2hWlc64+j476lKpbz9QqVMHZtKUncWJHruq/dJgqNT9XZQMi6JhaEAjmjAc qeq3s5FGM0YiY7J/Hz4ZstE5mBymRlNwC27FbbgdU3EH7sRdmBZ+ES0Pz0St4Zm6ev1PAkkMQwMa 0YThSGEEmvE+qJN1B+FgyCV1ckmdXFInl9TJJXVySZ3cUSd31MkddXJHndxRJ3fUyR11ckfdcTge F4T2ugvxRYjtOrFdNwnX4wbciJtwMyZjCm7BrbgNt+Oe8GLdDNyL+zATszAbc8KL9aeGqfVn4jO4 kPWmhmz9HSyzMnyRVcr8bJCPPcUS5d/+5qPng/ufS+wJoxJv788n9u5vTwztX5LYtz+X+M3+5Yl3 wojEfq+H/eXksP3PJRvCqGTj/nyyaX97cvj+JcnU/lxyxP7lyXQYkWz2+kjnTQiLkhNxJX6Iq3A1 rsG1uA6TcD1ugN42qbdN6m2Tetuk3japt03qbZN626TeNqm3Teptk3rbpN42qbdN6m2Tetuk3jap t03qbZPL8O+hPbkcrViBn+HnWIlV+AVW4zmswVpsDFOT7diE19GBzchhC36JX2Er8mHqsH1hUUMC /LdhWGhpOMjxYIzGSTgNZ+gLPu54V2hvmI25nttnw6Me20+D/TTYT4P9NDzptafwNH6Cn2K511ux Aj+DtTdYe8NLHr+MVzx+FVlsQAc2hxcbfulvRfQiRj8GsAu7sSe0N45EBu/D+3FYeLHxcByBD+JI nKlP+Ti+F6Y2fh834ibMwMNYEJ5pbHHcE6Y2HR/amz6qxn3M8VTHz+MLHv99eLHpm/4+DpeAPzbN 9fr9+BHmoQX7wovDo9A+/P2O4mu4uBquRg9Xn1PfxKW4DJfju5gA8Z4S7ynxnhLvKfGeEu+puzEN 03EPrDd1L+7DTMzCbMzBXNyPH2EeHsCDeAj2mJqPBfgxHsHCMHXE34TsiPPwOZwPex3xBVyAC3Ft WDDiOkzC9bgBN+Im3IzJmIJbcCtuw+2YijtwJ+7C3ZiG6bgH9+I+zMQszMYczMX9YUH6o2HqyOFh wcgURoQFUVL2f0rmLyZeV8s2q2Ozomvkz2txHSbheuyVS4ewD7/BO3LVCSE2P8fm59j8HJufY/Nz bH6Ozc+x+Tk2P8fm59j8HJufY/NzbH6Ozc+x+Tk2P8fm59j8HJufY/NzbH6Ozc+x+Tk2P8fm59j8 HJufY/NzbH6Ozc+x+Tk2P8fm59j8HJufY/NzbH6Ozc9x9ffA6taFvJm1bGYtm1nLZtaymbVsDn3U HPqouTNv7sybO/P1C8MOFW2RSlaqHww76/eEnbVvNq02d25QjdpCXgVbZIZrMcO1mOFazHBlM1zZ DFedn7Lmp6z5KWtmis1MsZkpNjPFZqbYzBSbkVrMQS3mlBYzSYsZosUMEZsRqr8gGpsDyuaAcuNJ Id/40dqvgVZ/CbTay2f12Vm9dVYvnNUDZ/W/sf431v/G+t9Y/xvrf2P9b6z/jfW/sf431v/G+t9Y /xvrf2P9b6z/jfW/sf431q+W9atl/WqsR63+QmdeHxrrQcv6zli/Ges3y8NHhbwe81E95qN6yrye Mp+eFHakr8cNYUfzqLCz+RAciqPxYdzk9Udq/7qpOyxS1/WYidbojMSK6JuJVdGxiV9ER9D3lcRz 0SGJNdHxiWx0Hq3Pq831G6NzzfaZxKbodLqXq59i63N2ePWN6GT9wnm1z7Cr32fo0bX89rPs091p dVju/OW1ez7lb9dHCfc7wWvt1TOjEXUXRKm6C/FFfAl/i/HR6aa3lOmtOrmlTGmp4dX/62rSeo4S HZ+q/SayemgNv33lKNWy+D+p+xLwKoqs7VNV3VWde7tvQggkYQn7pqISUUYQd50Zl3Ecl3FAEVdc cHDYRARRRwTcWFRAQUVBHUXRUREFAf1QBBdWWUTCkgAhGJYACUsg9b1VtwlhCZCA/N/f96nu6upT p05XnXqrTnX3uUhtitFyPEbLhXY+CGscJedgJpRHF9k1RUObCRnM/yGsg8Rx/8nWq7SZE5nnJtb/ 3E16vuiOuvkaOtTW/JM9UhbgbDmop2Iu+JUuxFk2zjoj31d6F84WUBNywN1FkAgKwUNIQIggRBF8 hAAhhhJvoCqinf5OdEDojFqcoheD00pwmud0p0ynB0JPhIcQeiE8jNAb4RGEPgh9ER5F6EeZsOUz YbNnwmbPhI2eCRs9EzZ5JuzvTNjembC3IYuVdTLmdFNQV1P1ajEdvegr/QtKnILZ7Sbce3c6FTpR BVcLjC7g3lMomc2j2mw+NQrfS7tLtANV3FPzqcZTs+hsv+n6QfTE/HY4NRMjECbrPLR0fcxkPnbO pVOc1tQItdWeYsgRQzlnoDW7owWm6k0o6QdbUoASfkMJc8TNKP8WzEA74ngbjt1Ryjy9HHPkfMyP 91j9WUwuckVImn9jAXU6KNNBmQ7KAlAUUnXKAYpiDkVr4977bIk9cQROoNVdIO5S8NsO1C1EjgLD 08yI3WRdBBu+CDZ8EWzkItjIRbCRi2AjF8H2LUKZN+BebwKX7mi5OchluJkV09QDyrwZ/DsiPEDM lj0XNT8P6fNR3gLU80JoziLMzBdT9JjKjYblZoNbIu6iGByzwTEfHAvAUYarb64dP2KgLhA3WTmy IEeW6GrbuAEkVsJ4bo7LUoScUchSjNzGQimg0ymHWtEahLUIu6gx7UYoRtiDsJcag3NHay3djH52 C90gOuJ4G44PwJLpCs499QzRBy05HJo+Aj0Wsx7UUUPbNgv0x7a0n/US9LkUWDl7oCOZ0JFMB7yd EgRNjd1kaqXaIbRH6ECN1QiEcQircL4aIRsBcqrNSNuOYxFkS4BkRZCoOaRpjntNCVsHoyt6gGnj JdAZo2nTIf901EwuqFNQO7nIkYIcmaBOgJwbUTPbIGsBZN1p6tXmmmP1E20EXW6AvlsEfW4gegAJ syk1Pl+Hvuaidcx3Wnl6hv0nH9NmWaCKIKUQcuzzEBe+HSO6QUceQv9fD33IQ/3L0Kd9LvIA23AH 6xDydBal052Q5C6EuxG62X8wKII8cyDLHFCnWOoclGitOFzLAyLadVeMi20pw03SuW4+wkadKzsj PIDwT4QuCD0QeoJvLPxfBOOJMwucs0Q33FEP3Gk22i1Hb8Cd7orfqd4BqYtRymxre6dCvgLIVwD5 Ckp7STtw6oDQDbL1QLtkI2cOZDd2dNzaNHe3yvwHEuQrgHwFkK8A8hVAvgLIVyDNM5XmBMud7kK4 G6E3zh9B6IPQF+FRcI7/a1IzYFQs9ENvEOciYNQI1PJE1PI30MvJ0MvzoJeXi/egr9mQLAf3ZqXB OJWLNluvs6CTraCTrZy2eqnzOjV3xiC8Qc3dJLrcXYVjPo4bEbZQc9nMPPtE6EyXywcQ/onQBcHI 54VtZHTGDXXGtW21zmpEgV19GA+53w6p0kOqdMhdAMpMK5tpfyk6l7wjdurNsPWyHKU3w5bLcpqW zILMnUtWIbUIKUVOU30auHYuWSKK0FLFyL0HnPbqbMfVu5yILnYwHwFlNihb2LwTcHUpUpaCW6HN O0fsBk6YvHuhDRp5EkjZvD5ssBiOTXUGJYNyFkophlVaAMnyhXkrvBil7tG7kXM+chah1GJYowWQ ON/BrAhcdkGC3eA0H5wgb8lqtFRn2LFxLoXgUgwuJUZmW3Y8dyFyFyN3iZU9LoNL1ZGzM2TIFjtQ Zztx3IX6wyw5vPOlYi/6dIleC067IEu2Iykd3LLBrchJwCgfrxHcPyU4gV4Lzrsg03Nm1CzJBkdT B7miBGOOsvef6wSIN9VkKT60LbLbUsVbJcFSmZZZgNo9qL0wnwjbCbmP0j6W1rYLaI/SHpR0vO1A fkXrH1p8gusdOl5Ofdsrh61nijkp5DnVwDWNIk4NhJrIUwv5ayOO2apTB9fqI94QoRGuNca1JmZW 6VQHj5q4WhfHRqYOnBScwWZwUkFTw14tsLwykF4H8XqIN7TUBYYPSUudZksttBT1bSmFlAy5XFzN d6ojJRUhjTIgXyIo88EzA/KBL0IdnNfF9XoI9ZHeEDSNkNYY8SYoIwYuuZDV3KHrpKP0GiRCLiZ3 LuQ3d+g6DXCtIa7Fc7uUBBkiyL3R3mka+NYAVU3UXi2kx8uPgMNGWwP1cb0h0hrhemOkm7JxF+Bf DVer6y1OqrlXaJyVAW1ZC+XWRloGaOogrS5o6pk6AI2VBTSNQdMESGfaKdHWaxqlhO1UDDlSIEcM ciTauq2P83g7FUOGFMgQM61ia88Nc20/QHpz3/Ec20ulTqysTqDX/ozYQXqB3l6HgorqBnI1QC8t Rz9wlVPVE6Uj4FYNKZXUE+T2qcrx6gq4VDd3dGL0BS0xzrZjpXTG3lFQUb1BmTsxmy0qmQ8sbA7E cYBqLcTukmlAtZpiT8kMoM+5oqSkGKiW5Lgl84GNzYFGDlCthZNQMg2oVtOJlswAMp3rBCXFQDX0 wZJfUCM1UCMBaiRw0kpmoUaqOTVK1kGqhqgVB7XCnQzQ1QFdXdDUQ6gPugagawi6RqBrDLom0JoE WGqJsLEuF+ZfhGbYWX0KZrkZmFVkmnV7zPbS7T8ZTWYdqA3rSJez2+gZdjuOdyCX+d+hG/W34u+Y Dd2kR9t/x2t2BKpvLdW+f1waXXr2UekZZwEs4OZE1JouoFNgc19EZ9KVdB21oBvp70j9B+Zt59E9 9CxdQc/Te9SFJtM0nH2F31D6nhbTMFoKm+N1ymWJ9AGryWrSYpbBmtMSdhW7GqnXsOspj7VjN9Nm diu7lbay29idtI11Zv+kHawHG0m72Sv4ZbDR+NVhr+FXl73L3mP12FdsLmvAz+SZ7Czekrdi5/DW vDVrzc/nF7A2/BJ+KWvLL+eXswv4n/iV7EJ+Nb+aXcqv5dexy/iN/Cb2J96et2dX8lv5rewqfie/ i13NO/FO7Bp+L/8n+yvvynuyG3kvPoC154P4c+x+PpgPZw/ykfxl1ouP4/9lvfkn/Fs2kH/HF7NR fCnPYeP5ev4bm8Q38y1sCt/Kd7CpfBcvZjO4FsRmCi4EmyWUCNj3IlEks/kiRaSwRaK6qMEWi3qi PvtVNBSNWJZoIpqxleI00ZxlizPEGWyNaCEy2VrRUpzDckVr0YZtEG3F+SxfXCguZJvExeJitllc Ki5lW8TV4hpWIK4XN7Htop24g+0SncUDKLqreIi7oo/ow6PiUfEo98VwMYIHYoKYwBPFp+JTniQm iUm8ivhCzODJYo5YwmuLbPEbbyKKhOYtHNeJ8TZOitOUX+a0ddrydk53ZwBv7zztTORdnM+daXyU 85Mzl7/pLHDW8rec9Y7mX7gRN8Lnu77r8wVukpvMF7oL3V/4Yne5u4pnuTluDs9217nreI673s3j a9zf3C18nbvV3crz3UJ3B9/o7nJ38S1usVvMC9y90uVbpZIxXiyTZJIQMllWE45MkxnCk/XkWSJR ni3PFvVlK/lH0UBeI28QLeUt8gnRRj4pnxK3yUHyGXGnHCwHi05yqBwm7pEvyZfEfXKEHC3ul2Pk GPEvOVaOFV3lW/It0U2Ol5+I7vIz+aXoK6fL/xFPyplyphgoZ8t5YpBcKBeJoXKJXCpelMvkMjFc rpArxQiZKzeIl2WB3CNeVaS4eFcpVVe8rxqrlmKmaq3aikXqQnWh+EVdov4olqkr1F/ESnWtulas Uder68VadaP6u1in2qlbxXp1h7pTbFL3qnvFFnW/6iUKVG/1qNDqMfW446in1DOOVIPVSMdXr6hX nOpqtBrtpKrX1OtOmhqrxjk11Hg1xamlZqjZTnM1X211WqrtALkbvcZeY+d2r6l3inOHd7p3hnO3 19Jr6dzjneu1du71zvPaOvd7f/KucB7wrvKuch70/uJd4/zLu867wenm/cP7h9PTu8Pr5DzkdfH+ 5fTxenu9nX5eX6+v85j3mPeE87g3wBvkPOk94z3rDPAGe4OdQd4wb5jztDfcG+U8473j/ccZ6o33 xjsveBO8Cc6L3lZvm/OSV+gVOiO8nd5OZ2QCwMx5OcFJcJxRCSpBOaMTsDmvJiQmJDmvJVRNqOaM SUhPSHfGJtRMqOWMS8hIyHDejlwXaee8E+kY6eh8GLkzcqfzUeSeyL3OfyP3R+53Pok8EPmn82nk wciDzmeRnpGezqRI70hv5/NIn0g/54vIgMj7ztTIV5FZTk5kUWS5kx9ZEVnrbI/sitZw9kQbRIe4 GdFh0TfcZ6OfRae5o6Nzo1vdt3zlp7mz/VP9y9xf/Zv8e9wi/37/Qan8rn53Gfg9/V4yye/t95ZV /T5+f5niD/Sflxn+EH+IbOQP81+Ujf3h/hjZzH/Tf1O29Mf578uz/Q/9T+X5/iR/irzUn+pPlX/2 p/vT5RX+1/4seaX/o79AXuf/7P8s2/mL/aWyvb/MXyk7+Kv9LfJOf5u/U3b3d/t7ZG+/JCDZN+AB l48FTiDl40FCEMgng6SguhwUpAVpckhQI6glhwYZQUP5YtA4aCxHBf2CfnJ08HjQX74aDAyek28G Q4MX5H+Cl4LhcnzwcvCy/CAYFYySE4JXgzfkh8HY4B35aYzHYvKLWHIsVc6M1YzVlj/GdsR2y7nE E57AiELRyUlfUhOqQydk0yv0SmoOy4r0/MNeL9bP6wn4FeleOLtV36Xf1xMRy7ZXs3Uu9qtD2qJD cpuruboAv/3XUg6h2ozw5FElHYjw3zLnS8G9mimh3C2idxvp9DbEzTuyf6TGOM8q5bC+NJZ9mPLm 6+U6T/+AX7begtn68W6p4DnGcs7R+Xr2vtJ1/iEl59tay9dZqP3bqCZqrJmRPLxafLSCdKHepLfq 9XptaVJVpG6y1z5F6yXqzxBbc9i8oNIbUXqRziNTaxnUgC6MS48ri/ViaMtKEyun7Nf0aHOXugfC X/TF+nE9ALGVpdd/K3uXB+UtRl2vQNlf629x9wVoKTe88stBlDOPWgfbKdQ0PcTuC/RmcA+1sEzN 7KMvRI1t1Tv1ItBdYe+2DWo+lFJv0Buwzwtpdx6SezPqbJ3RkbBfFFENe1xY/t2WI3fWAWf3l4l/ eWwcsJ2+v0S02EJy9aKjlGp64Ibw5BRqeUTat/UrRk+MDlV802vNHUK7lh9yZfVR825B+LeNvX9w Cxp0OkruHITJFpGW7e/5x7pBqwvtfuFhLiYeE4etCKsqWm6Y96vwOLESeV+1+5nm/k/w1vqoZa+P t6veBSzdVEHuR67VVgg32DJWx/fxX3j1cKNjM/zq4NfsAAnftvu58d8Rcrc4bO51dr9Rbwd2bS9P VFwzqLZB/2r6ockTx/D4mAe0+0Z/r78rN3eZUVUPonpA5KvpGsTftSkLMU59qZeWm7vMuKWHYRxI p8tgeaIH2ZRf0Re+2Y/O5ZVtRlDokcndElZrmK6/0JMwxpaLS/uxPtwSUX/tkP6wvTpVf66/0tNC 2o2H5C4zsqOmEu04ZEaVq2zKNyh9sp5cbtnlzAtKzIzgB/0Pfa2+X98Q0h6CZHoQ6nWW/kmvPABn OHWgf8NCJ9jrg81XJ/Q++TSBJlFTmgLbPdPa7ufQDNjuregX2O5XwkpndBPryDpSN1jPf6Puxm6m nsZipof4ffwBehi271Lqy3/lK+hRns1z6AnYwevpSb6B/0b9jTVMA3gR30GDeDEvpmeMNUzPGmuY noc1HKUhwvgkekncLG6h4aKjuI1GOp85n9ErsCM1jXKT3WSaLSfKifS9nCqn0Q/yV7mcfpJaappr 7CeaZ+wnWqT+qq6lZcZ+ouXGfqIsYz/RSmM/0VpjP1GusZ9ovbGfqMjYT1Rs7CfaC/tpKBPqBTWS SWNFMd9YUSwwVhSLGSuKJRkriiUbK4o1MFYUO8VYUewqT3guu8nzvAhr7/lejHXwqnhV2W1eNS+V 3enV8GqxTl6GV5fd5zXwGrEHvPO9C9iDsJzuYl1hIQ1kPWAhPcMeMjYQ62VsEfawsUVY7+gj0SHs UWNhsBf9JD+Nfe6/77/PvvZz/C3sf8wcn80zc3y22Mzx2S9mjs+Wmzk+yzJzfLbKzPHZWjPHZ/lm js82mjk+22Lm+GyHmb+znWb+znaZ+TsriSXEolzEqsVSuYztjO3mCdCbRVZvmNUbDr0Zjpn8CHoF 85tRNA4pb+Gn6G16jzwaD62SVqsktOpLSqCp0K2I1a0IdGs20r+nnykKrouQdzF+AbRtOcUoi7LR x3KgeXUplwrQa7biV4+20Q6qTzvxa0C7aC81pBLoZRWrl7WsXgqrl77VSx962ZmS+APQTt9qZzK0 M4uq8xXQ0arQ0WxK5TnQ1JpWU2tYTU21mlrNamq61dSqXHNNVQVBX1Ogrxx7bFQNWqsQR7NTmkiA BqdYDa4BDb6ZGolboMeNoccdEb8N2tzYanMtaHMWMWeFs5a4s87JJemsdzZR1NnsbKfaTqFTRInO DmcPZTh7ofcNrd7XtXpfy+p9Lav3taze14LeX0Ip6lJ1KUXVZeoyctTl6AkuesIVSLlSXYmUq9RV pNTV6mry1F/QQ+qjh/wVea9FP0mw/SSKfnIjBerv6C0x9Jb2VFfdrG6hRNVBdaCG6lb0nyq2/1Sx /Yeh/9yPXJ3Vg6D5l+qKlG6qG3HVXfVAKT1VT3B+CH0sij72CHL1UX2Q3lf1Bf2j6HWB7XUMvW4A aAaqQSj3afTARPTAwUgZooYg11A1FDQvqOFIGaFGQJKRaiRS0DMpYnommZ75GnK9rl5H+lg1FnzG qXGgHK/GI+V9NQF5P1Qfoh4+Up+iZiaqLyDnZDUZdTJFTYFUM9S3kHammg2e8xV0Ui1S0Ea1RC0D t1/VSqqjVqkc1MkatR5l5akNVE/9pvJRkxvVJmqgNqvNKHGL2gqZt6vtoCxUhbhapIqQvkPtgCQ7 1S7w3612g3OxKgbnPWoPVVV71V6UXqJKkFcrTVGDI1TL4Aj2wBHsgSPYA0ewB45gDxzBHjiCPXAE e+AIMeDIAOwHegOJGzQhx6AJMYMm5ANN+mDfN9KPkgymkACmLCY/uiS6lILoL9GtlGTwhYTBF0oD vuRQVX+Nv4ZS/LX+Wgr8df46qu7n+rm4ut5fT6l+np9HNf0N/kbEN/mbQL/Z3wyaLf4W0GzztyG+ 3S+kdL/ILwLNDn8naHb7u3G12N9DUb/E15QaoPtTVYNc2DuBg70bSEoGfkWoWhANoqDxg4BqAsuq IiUlqE7pBtGoOhCtBvY1g1qgyQjqUEpQN6gLDvWC+og3CBqAvmHQEHHgHdKBd0h5NXgN/F8PxiDX G8Eb4Dw2GAeebwXvUDWDgGQRkJIMAlISUOqDEAGH4CdKEXAk4qOAfcJinwvkex/xCfQ59l/QZIuA XyH+P8A9Qd8C+wSwbxGwcjEtQXwpfspin7DYl2Kxr5rFvgSLfdUt9qVa7Euz2JdusS/KElki+awd a4d9ZwakY11YV+y7s+7YP82eBvZdy68lbpHRAzLeib1BxohFRs8iY2DRsCrP5+Z/IwwCVrEImMz3 8r0Us9iXKBzhUBWgnod4REQoSbQT7aimaC/aU22LerUs6mWIDqID0m8VtyLdIGAti4AZ4nZxB9Uo RcBcEsC+7aSAensoweJdusW7amZVFP3zYnUxCYtrCoh2JfYGy4TFMtdiWaq6Rl2DFINlQl2nrsP+ enUDKA2KVbMolmBRLB0o1hF9+3Z1O/Z3qDtAeZe6C/tOqhP2BtGURbSEENG6q+5I6QFEcy2WKfWw etgiWm/QG0RTQLR+iMex7An1b8QNoimLaMIiWoJ6Vj2LXM+p55Fi0E1ZdIuG6DZMDSNhMU5ZjEu3 6CbUq8A1EeLaGDUG8TfUGyTVm+pNUBqkExbp0ssgnbBIp4B0kxE36KbUl+prxGeoedgbdFNAt2WI G1xLsbhWzeJagsW16hbXUi2upVlcS7e4FlXb1DbkMuhWzaJbqkW39BDd9gDFhEWxqMc8RiKOR5Fe kYfJizwSeQT7vpG+FIn0A/pEIo9HHkdK/0h/8iwS8eiw6MvELaZU9TcCTRL9Ah94ahEk0WJHVWDH DsR3+rsoBtQoQU82qJEUiEBQDHihKLB4UcXiRVUgRTLiBimSg9QgFTQGI6oGtYPaSK8DjEgGRtQD B4MRVSxGJFqMSLIYUQUY8Sp4vh68jlxjg7GgHwd0qGLRgRNvfpNZzWyx+7wnYZFcX948/v/yprfq bBNsvODAlZtSmiK99ohrlOXxNiuyKxBm27MV+9KM9WJXB4vNCll8vQhSFBy4glm+PRheXxAe7664 ZCdq0+31aHvcekzU2XqOsfaOdR2tXD75B8bNOmvpWtlWWH3ZOsvUpl5SSrW/9cKVa1vnxhtABiUa apt2yNr377pFQknKlppI59u0VQe3vt506HoXtOcnPVvvqIxuHn3T88JjTqjJW8pc27ZPeivFYdpT Lz98XzohklWYsx6jR9hjkZ4HzZiLMEG/qBeE7V4qv11ZnAcdmlWp/p5PZZ5CxJ+blLn6rN4CHMkP a3S9kaRM5n3aUHgM5eykwz7tON4NLblf+u2oq00IZtVoxwFUGw7N+X9tK13zyjs2XTleRDoi78Ot NpdPPVNP1N/ojwxOIR5f2VwYrlHmlVKt249tFeD9q1m/DLFvg30CVAAEMU9FJsT543wGjt+ZgPgB 65l6PBl8ytx3V0DdhUCpC6ieXhJ/EqBz9Bx7fH7fCt/xbWWfbsWfHukPSs9f1ffpQbqjno74zaWp F+vO+gs70hxU64dDKdzBZD0dOl7u2mkl5d5qkSaU3khia7zsqFVQdmVcLzsit1knVrqKbECj8Pmb 7n7QlW90/9J46QgGjTB4sQYj6xHvqZzSDGKatrB1Y/VzQ1hP2OsethxlnwcfPFKn2Le0yvIyM4AV GLMihlM4N9gVXis4Wp0fg6z7kbLMU7B92BifjwDjc21ZB2ie7W+5h4zv+ZV9rlTZLT4rLXNe7uyn 7BPMMqlTTqw8ZTjfUAFi+5xHDwyfKRahR68zTwj1R3p8/EnhAeN7Qahln+mPKyHXl5gXTArjs4DR 9nmu6Z9GBzDHyA6fqRRZZF0azi7iKBocxGu6xZ6JFuenx5+B6O8PoNhbcQnDnAuozNP2EDkXWAya buPAQoubX8e1IP5EMt47wiuX6Uvt2VR9N2ryPoQn9HM4fmJTvzmgtE9Q69313yohZxc92mA37n81 Yu0RexwWwmj9HsbAIfpaPcxYDEg1NsOHemy8z+hONnPKvuepIa+F6O2Y+VNTG49bWeHsyzzVs++P GP2oxDsgVmtKn2zHx+IwnkWh7bPfjqMD52Z1D37v4fffys4hzTM5vdGM+kfMcdD8/uRsBzzXtE/W 9cYjz8RsLZ9cK43K1if0Z6edRxUe2T6wGFMJOct//lwBHie1fvRr+kn9vO5p49mwRt/WL4dX8vXP 9rgRSLxx/8ytUqVcrF87Tjl/he01J1yJWaMX6x/LvENm59WweObqbaXvD1SulKOs2Rwxb46Ze+NY gvAj5ufhaGDfNzDv9tgZf3nvbJ28DajdURufxmn27CGcd4OlYi1nUwO6WE/SQ3VrjCFzgOFjKtdy eqQ9NDguSePtOiM8C63Y+EoAlbGmjn+rwHtd5XHYYmvQ4HAe5quHtDKuLzNW34m2VSq6YWaVByni 9ugG6OmWMtfsKAM9/hE97PvDZj9pG+QcX/bdFeDSjP930hxu03fpmw1CGnsG++dx/pH+ycZDiw96 MEn/VT9Lxv5aVTkdO9ntAO3YdXJLrNi2D/X1b4e+P1oBLr/rGlg4o8zHmLX5+Nb5Krt2YJ5PHCPl h/Zt44PfEqvoVu848x/zhjH+ONb69NATJ0k5JYT4rjcdT8ufyLGt3DKy9O6TvWZR8U1/bm2G462P JidEmN9tO94vGzDSVOJpjV1LLl39su8I7+tbkfJ7mZ0jN6B2pCpRYn5lUNu0/n57LVwLPLa3x337 jvL/D1t6ZTKZNfxK5FpQdmQx33FgnCr6fZ5C/h4b5q/bjz5i6T2V4LywMm/o25l/3gFn++oy4Qi5 jAan05XQ0ZO8GWu0NJ5n7YDVR0Ygux5+ktdtykp5XHxWh+HbQy41C78lSCnz3UFFOM9Fvc3dV4qJ 2bDvW4h95bWxJR0gT5mzAfu5heHt+LHMZr55aGGOenL8fY0Kyvk28r0dxm3Mrn1PDu9hnwQtDpLz 7YqXVJp31eG/ZDxKrl/K3rnhcOjTl3K3Sq00oJXWHZ3qkFx5YX+3z/zt86B971NEjvAFirmPdLqo Mv1drzvaCvBhcy0LQ/yphlnd3kTh040j5IqvlqYf2P/0Ur3efu3ZjGrhaJ+NYvSxsw6rTf+ouHxH lP1ruy+1+XVv3VG/oUfYp8P7+0x7/aY9Fh/63sVhvhAs0Bt/n9V8+0ZI/FnVUsxxFsI6XYr5demX MfaJjVnJv1DfaM+/111BdZ+ehTuapB8M1zUPeKZlx5G79F8qIU1ncL0mjNuY/W54hJ6ov9Iv6Vv1 N1Yj0u2T7QX7LCr9gEmjRubpkO6mu9i0ItT5Sj0G9zJRf6TfDZ/gHLCGZceGwfqFSsg5Ts8sXc2b qd/A/r1wPpKjP9YvIG1LSJpQxvKPI2DDipd3sreT8UTGalX8fYVD9P0klJ5VqedxeVRmBSbUvqPz qYKQTJfbeEPM6xtQfXP/6FnmH37+QE2BR9kIueh9ueg5VwEnEvVZlj5aWlpffXkYjT95/qb0e04V f/slpPu8HNnjiDcCeG9HHN1PX6v/hdCf6us2liTEd/sFdlt9se6kb0FsqgmQb4x+T8+2797ES6tL jSmGo/22HBo//qj1cKhMH8VDeDYZ91TmOUb4dk0mZpp1yPwX377vyKeVoaleslX7+hK9Brg0XXcB j5H6edzXZP1c2Vqhfd9zPxHHhwrK+TD0Jf6NsItYF32vfs7q0FL7xmcQx/wylpD98jz+ZsAxzwMO LHHDod80HkOugrDvWgvXPrvZRtJeSjzC+G5ypNN5aH9O3x7F71C70O/QE/Rnxlk1utP6FOplfQoN tD6Fnmbt2C00hN3L7qUXrTehl1gP9jSNZM+yETTB+BSiycanEE0xPoXoS+NTiKayr9lcms7P5C1o Dm/Jz6F5xqcQLeQX8AvoZ+NTiBbxP/MraQnvyrvRMt6LP0zL+RD+Aq3g4/g4yubv8AmUwz/jk+g3 /gX/gjbyL/k02sS/4d9SAZ/NZ9M2/hOfQ9v5PD6fivhCvpB28sV8Me0Svghot0gSybTH+AUibf0C kfUL5IqGoiFT1i+QZ30BRcU54hwWWF9AMesLKMn6Akq2XoCqinaiPUsRHcStrLr59oKlGV89rIbx 1cNOdyY501g746uH3W7887C7jH8edreb5FZhndwUN53da7z0sC7GSw/rabz0sEeMlx7Wx3jpYX2N lx7Wz3jpYf3dQreYPWU887DnjGceNtx45mGvGc887HXjmYeNNZ552HvGMw+bajzzsGnGMw+bazzz sMXGMw/bYzzzMG0883BuPPNwYTzzcNd45uFSjpFjuW988vAk45OHVzE+eXgN45OH1zM+eXgj45OH N5YL5VJ+uvHGw1sabzz8bJkrf+OtjDcefp7xxsP/ZLzx8CuNNx5+l/HGw7ubrzF4L497nD/sSU/x 3l7Ui/I+XqKXxPt6KV4K7+eleen8Ma+2V5s/4dXz6vN/G/85vL/xn8OfMv5z+CCvhdeCP2O86PBn jRcd/pzxosMHexd5F/GhxpcOH2Z86fCXjC8dPtz40uEjjS8dPsq72+vERxtfOvw1r7vXnb9hPOrw N41HHT7WeNTh47xB3iD+jves9yz/jzfYG8LfNR51+HjjUYe/bzzq8I+NRx3+qfGlwycaXzp8kvGl wz83vnT4F8aXDp9ifOnwL40vHT7V+NLh04wvHf5VQnpCLT7DeNHh3xkvOnyW8aLD5xmvOHy+8YrD dxivOIKMVxzhGa84Iil6ffQOkWm+5BAXG6844gpf+YniOuMPR9zst/fvEQ8Zfziiv/GHI54x/nDE 88Yfjhhq/OGIYcYfjhht/OGIscYfjhhn/OGId4w/HPGxP84fLz4x/nDEFOMPR3xt/OGImcYfjvjO +MMRs4w/HDHP+MMRS4w/HLHU+MMRv/qr/Wyx2nizETnGm41YY7zZiDzjzUZsNt5sxFbjzUZsj/GY Jwpjfiwm9sSSYylCGw82Do/tiO1w3ERKZI4kzr4GQsWARImURAxjaxUSGF1TkZpGNYG8tagR0hvj p6gJnUoenQZES0CONhj7zqO2GFPPB7r5Ft18i24B0O1G5Po7fonAuFvAuwPdgRx3hnjXFeV0w68t dadeVJUexi+FetOjVI36AQ2rAw19SmUBi1Ga/TosnSUBH2sAH5sgpSlrSs1ZM3YK0k9lpyJ+GnAz 1eLm6cDNa7D/K9DzQuuRLZXdAgw9w2LoGRZDzwSG9kF6XzaAWrCBbCB4DgKqpgNVB1MmG8JeorPY cCDs6RZhT7cIe7pF2OZA2HcRfw842xw4+y1dymaymdSKfcd+oD+wH4G851rk5UDeltifDfyVFn9j Fn+5xd+Yxd9ki7/nW/w9zeJvS4u/NYG/71IGf4+/R7X4eP4B1eUTgMj1LCLXs4hcB4j8JfZTgcu1 LS43sLhcC7j8E/ZzgM51gM7zsJ8PjK5tMbq2xej6wGifGooASN3IInUTi9SNgdRp1Eyki3Q6RdQQ NegCg9qIA7WpKVC7CfZNRTPkAnbTqQa7kau1aI19G9EGV9uKttifL84HDXAce+A4Usx3dhfb7+wu sd/WXWy/rbvEfk93ETC9H7V2HnMGEAOyD6HAGeoMp7OdEc5IquK87LxG5zivO29QNedN5wNKdSY4 EykN6D+JzjD+2qiFGQPoD2YMoIgZA7BPcpPoPLeKW4VONyMBnYGR4GcS7iJ3EdVxF7uLKXCXuEvI cZe6v5CLEWI5UrLcLKSscFeQcle6K8lzV7mrqKoZOShqRg7QrHfXU6Kb5+ZREsaP34i5+e5GlLXJ 3UxV3C3uFqpmRhSUVegWUnW3yC2ic90d7g5ItdPdCUl2ubsQ3+3uRrzYLabW7l53LziXSE5VpJAO tZaudIlhHFIEGJceRWWCjFAgozJKQvrSp+oykAGdK2MyBhqMVZSIsaoq8qbIasibJtNBX0PWpCRZ S9YG5wyZgbz1ZD3s68v64NBANgB9Q9kQ9I1kU9A3k82omjxFnoL0U+Wp5MjT5Gnky+bydPA/Q56B vGfKM8GthWwBmkyZibxnybMoYsZFlNVKtkL6H2RrULaRbcDhPHkhufIieRkoL5eXk5J/lH+EzNfI a3Fff5M3gP8tsiNKv03ejlLukHeDTyd5P7WRnWUXOk8+KLujxB6yJ7WVD0nghnxY9qYU+Yh8BNL2 kY/iXvrJx8Dncfk4ODwhnwCHJ+WT4N9f9sfVp+RT4I+xmdLN2EzNMTYPpRZymBxGZ5oRmlIxQo/A 1ZFyJKXJlyX6vhwlR9Ef5Oj/peyM45o6z75/5yQ5CXigVC0iUkYppRSVUmSUoUW0jlpLqbXOOecj AUIIMZyEEEIIITkJIYmWOcscZY5ZZ51z1lLGmKPOOeec47F+nB/qnI+Ps87H1/r4+Dofx5yv9aHv 776CzO396+35XL9cvc6dOycn4dzfK5/kp9iP87xT3An9vriLPcud9TAeqzhmeE98D7pfxDtTHBAH cN8PxEFWJv5Y/DFmHhJ/gr0HxAO478/En6E+Ih7EyJ+LhzDyl+IR7P2VeJQV8LUf9X8V/xUjT4gn kH8kfoQxJ8XfYcxp8TSO5GPxYxzVGfH3OM6z4lmWKv5B/ANbIJ4Tz+FeYAWMvyhexGyfiJ9g/Kfi p5jnmngd4/9L/C+M/2/xrxhzR7yDM/A38W84nrvifTaL8wTLB08kIE/UPcqe003XzWCzdTN1s1iB LkWXxhboHtdlsDzQxtOsWJeje4Yt0+Xq5rLndfN081CZr3uWfUmXr8vHDM/pnsPIAl0BxizQLcDe Ql0h6iW6EjzKQt1CjFykW4T6C7oX8Cj8N6QqTi3sWU4tUFALFNQCBbVAQS1QUAsU1AIFtbAUTi1s NqcWKKiFpXJqQQ5qYcWcWtgsTi0YD2pBDmrBXlALFNTCCji1sAWgFhPG1+vr2ZfALjaWoLfrmzAG BIP7gmBQB8FgpKJXME9AH0Ae1AdRB83gSEAzGP9N/TfZc/qt+q24F5iG5YNpelF5W493l75P/13k P9T/EI+1V7+XLeOUg8pt/W3M8Bf9XzAGrMPmc9Zhs+P4Bx9lcao4FZvFiQcVEA8U/7H5IB6sj3FJ cUmsANwzgxXHzYybyfLjHot7jH2J+wmy5+JS41JZatycuDnI0+LSMA+oiD0HKnqDJcavjl/NxPiv xH8F+Zr4Nci/Gv9V5Gvj17HpnJlQicTvZkL8D+L3Iwc5IQc5YQzICWP+zzQVE6YJ01JZKecnVhj7 JSznJyZwfoKCn6Bfl77O0qT10nr2BelfpH9hj0gbpA0sXaqSqlimZJAM7AmpWqpmaqlGqkNukkwY Xy/VY4xZMmPMRmkjcqvUyJ6UZEnGGJtkxxiH5MDeZsnJHgeTtaLultyog8ygXskL7ZB8bI7klxSW IQWkIEZ2Sp0YGZK68IhR6U1UuqUtmBn0hkfpkXqg35K2YUyv9DaOuU/qwzzfkbYj/670XYzvl/qR f0/6HubcIe3A3nekd1i2tFPayXI487GnwXy7Wa70A+kHbLG0R/oR8n3SPox5T3oPez+QPoAOSj9m c6UhaQh7fyINY+/PpBH2jPShdBCVn0s/RwWkCAUpQn8lHWVZ0q+lYxjzG+k4e0r6rfRbjByVRvEo J6XfoXJaGsOc4EjMf1Y6C/2DdA5jzkv/jr0XpAuY54/SReSfSJ+w58CXf8Jsl6XLLJtTJnsclBlk cxI6E0LsiYSuBJwlEGeUzU3YlIBzldCd0M3SE76R8A1U3kroYbkJ30r4FlvMSRQVkCiby0mUTeck ygROolCQKCMSZdM5ibJnwUTziERfJBIViEFjxBljzWkPkWUC+xq2BGLKLxNTvvQQU75MTDmTmPIx YspkYsqUh1wPtOR6IJLrgZZcD7STji/c9UBLrgdacj2IJ9cDLbkeaMn1QEuuBxK5HmjJ9UAi1wMt uR4sI9eDcnI9SCLXg+XkerCCXA9eIdeDCnI9mAXGnQbiTFAlEN3OBt1iY4XEuEVg3NdAk5xiX1N9 RfU11DnFfkllUpnYF8GvLVCXysNKVF6w7BfBslG2EBS7CfmbqjcxnrPsF8Gyb7MXQLH9rBT8Ogz9 qeqnbLHqgOqX2Mv59Q3i1zLi1yXEr0vBr/lMQ/yqIXJ9hMhVA3LFKwRyfZnNEF4Bv84gX4aYY00i +TIkki/DdPJlSCS6fZXo9nlhk7CZLeKuw2wlMW4aEe1c4QPhA/aMMAKifZJY9ili2aeFj4SPQK6c Yp8QxoQx1H8Pcn2CvB7mCP8m/BEs+4nwCZT7PuSSC06OcEX4X6h8KnwK5V44j5MfRKbwv4WbyLkr RJbw38Jt5NwbIlv4TLiPnDtEpAsTwufscfKJyFCr1AJy7haRpdaqtci5Z0QGeUZkqqepp6HyCLh5 PhHzc0TMC4iYK9Vz1Gmoc26er34S3JynzgY3zydufladq85FPk+NTgoMvYAVgKGfR16sLmbz1F8C Sc8nks5XLwJJz1cvVi/G/Jyk5xNDv04MvYoY+nVi6FVEzy+Cm3vBzW+DlR8lVk4mVp5NrFykOQBW /hJY+RhbqPmN5iRbTMS85CEnCy05WUjkZJFEThYVxNAvEUOXkqtFOZF0MXGzjohZR8ScQKysI1ZO 1l7RXgEHX9V+igrn48eIj196iI+TiY9TtOPacSgn4BeJgHUPEfCLRMCCKIKAdcS+OmLfFGLcF4lu dQ9xbQqx7ItEsTqi2GSi2BdBrvOx9+/M+iLR6jSxUCzEyCKxCCM5s75ItBpjUx3xqI4Y9MvEoC89 xKAvE4POJAZ9jBg0mRg0hVgzRewWu0Gu3xC/wQqJNYuJL0vEXrEXdc6XqcSXpeIOcQdbSmRZKO4C WZYQWc4mslwo7hH3scXgywFUOFO+RjS5UBwWh3EvzpSFxJSvgSlHcN8PQZaziSyLiCwXir8Wj2GG 34i/wfjfir/FeE6Ws4ksi4gsFxJZLhHHxDHMwPmylPiykPhyIfHlC8SXS4kvU8U/in/EXk6WD5jy hngLFU6WRUSWxUSWr4kT4gQrIaYsIaZcCKachZzT5AtEk6W6J3RPscXElEuIKd8gpiwjgiwlgnyD CHIJEeRs3fO656GcIJcSQS7RLdYtxpzcb0UivxUt+a1I5Lcikd+K9iHvqBXkt6IlvxWtbpVuFR6d u65oyXVFIteVcnJdSSLXlQpyXZlFriuzyHVFS64rWnJd0ZLrikSuK0kPua5I5LqiJ9cViVxXZpHr ipZcVyRyXdE+5LqiJdcViVxXtOS6kkSuK7PIdUVLrisSua7Mesh1RUuuKxK5rlSQ64qWXFe0D7mu aMl1JZ5cVyRyXdGS60rFQ64rWnJdkch1RUuuKxK5rmjJdUVLrisSua5oyXVlGbmulJPrShK5riwn 15UV5LryCrmuVJDryixyXdGS60o5ua6sINeViodcV7TkujKLXFe06AFAsSD+p1gp8f1i/dP6p9lC UH4OK9HP1c9lRfp5+vmsEMSfh3q+Pn+S+wv1BfoFbCnRf6G+SF8M5T3AEv1C/ULMU6Yvg5brX4Iu 17+C2Sr0r2JMpb4SPcNr6AcW6r+q/yrqvB94QV+lr8KR1OhrMD7mTcU7hCXoECx4lFiH0KR3YIZm fTPu1aJvYWX6Vn0rKh16P46f9wnF1BvMJi+rQuoQSvRb9FugvE9YSn1Cif7belwfqE8opA5hof4d /TuovKt/F4/Ou4Ul1C28of+Rfh/uxXuGhfr39e9jzAf6QSjvHxbrx/XjmIH3D8X6z/SfsReof3iN +odS6h9K4vRxelZI/UNxXHxcPPIE9A8lcY/GPYrxvItYQl1EGXURS+OS45LRY8yKS8HI2egliqiL mB2XEZfBFqOLWM0eoc7hEfQMa9mM+HXoHGbEr49fj0ptfC1bFG+Jt0Ct8VaoHC9D7fF2qDPeCeUO O4nksJNIDjvTyWFnOjnsJJLDTiJ1IBrqMV6dNmdaJnt+2oppr7NF04zTPGzlpBMY7zrU6DTmMg31 EnOpl3hGqqNeokGygHR5//AEdQ5z0TnYkNulJhC8S3KhwnuGJ6V2qR2VDskPmud9wlPUJ8ylPuEZ 9AmbUXkT3cIz1C08LX1T+ibG8z5hrvRtqRd730af8DT6hO9gNt4nPEV9whPUITxJHcJ86fvS96Hv Su9CeYewgDqESulH6BDy0SHsR/19aYA9Sx1CPnUIBdQhLECH8BNUhqWfsnnSAekARn4ofYg67xPy pEPoE+ZLh6XD2HsMHcKz1BssoN6gUjohfYS9J6VTqPMOoUD6WPoYI3lvsED6N+k86v+O3qAAvcEf MdtFdAiPU4fwrHRJuoTH5X3Cc9Qn5En/IYG1yPMol3zUcqTr0g1UuP9RhnRTuoWcuyBlkQtSBrkg 5ZILUga5IKWTj9rj0v9I/wPljki50ucSSIx8kTIByCAxckdKJ0+1x8kjaU6CPkGPnDslZZFTUi45 q+UkJCY8gjp3TcpKmJEwAxXunZRN3knpCSkJqdjLHZRyyUEpixyUsslBKTMBG/ZyH6Us8lHKIB+l zARLggX9D++InkJHFGBp6IjwfkiIJETY0+iIulHnXVAB9T+V6H++jbw3oY89S11QQcL2hO3IuR9T FvkxzSE/plzyY8omP6asmFsbU825nabgVlJvZp8wZliHMCBMCCvCgXBP3aqa9uDWN1kLITYjtiJ6 Ef2IXYi9iAHEMOIg4gjiOOIkYgxxjglBmYIZLlIIQSfCg/wK4jriFuIO4j5j1QJCj0iMPXb1TEQq IuOh2+yH/n9ebK7qAkQxohSx7KHbFYiViDWT9+G36xE1CDMCx1XtnLoVggqFqmk/Ygh5eKoWi25E z2TuQfRN5jsmY/dk7EMMIg4gDiGOTo4dpfGsmh8zvw0juhE9dFyxsadoHKvuQ+xA7EbsQwwiDkw+ 3hnkhxBHEXzsKQSvnZ/cf34yLqHG4yqezwji8NRzYdU3ELcRdxETjNVoEPGIpNh5r0lGpE3eZv79 dmp8Tuw9wG9pfFLs/6f25yEKESWIMkQ5ouLvt/z1q1mFWPvQ7QaE8aFbC8I+dSsEr8aOu8YVe241 3sl5gv9/Qe/rhyMUC34c/zDfqn+KKGLL5G30/5lHCPJj24bYHnttanYi9jx0ux8xpHm0qkQu9zsN F233udoFUj30ij0Ret0+E3rLngq9Y8+A3rdn+538Xsp4tWCfp9yrKpMr/J6qcnmVX6nW2wtIi6fy RHupX+F7A6yqQl7rD1fPtC/zh2P5pK6SN/i7q1PtK0hX/lOeYV8Dzbavh86z10AL7GZ/N79XQKxa Kxv9PVUbZIu/r7rYLkNL7U7oMrvH38frAanKKNv9O6pX2BXoSns4ML3KIrv8u6vX2LtJe0j7oOvt O6A19t1Qs30fVLYPQp32A1CP7AqkVCv2Q4H0Krvs9e+rDtuP+vdVueSgf7C6Ww4Gsqq8ctR/oLrH Pgrts5+C7pCjgdzq3VTfwbUqKG/xH6qKytv8R6v32c9M6aD9vP8orwfyJ3WLvN0/Wn0Ae7lemsoP 2a9Cj9pvQEftt6Gn7Hen9Ix9IlBUfb5JE1hUtU3e6T9Vfakp3n+KZjszWbnalAS9wZVXAkurtst7 /Oerb+Occ13xIOf1wPKqnfJ+/6Xqu03J/ks8D1RWTzSlId8jD/mv1miaMklzpvL4pjxoUlMhNLmp BJrWVAbNbCqnvAKaIw8FVlftl0f8N6qG5MP+2zV5TasC6/5BC5vWBtZVjcjH/HerDssn/BM1JU0b SI1TeVmTxT9RdUw+rWhqypvsU1rR5FI0VSfks0q8ZdBzk3Sc9B70QDuDHmoXoUfbJeho+3ToqfYU JZ7fK1RpOdOeHtlbdVq+oCRVnZUvK8mW8+1Z0EvtuaQ8v9qeryTzvZGBqgvyNf+g5UZ7kX8wlk/q Zfmmkma53b6IdOk/5Xfbl0Mn2iuVtI2a9tXQ+PZ1Shq/V2S46po8rmRW3ZTvKTkbk9oN0OR2EzSt 3ark8HrkYNW4jSl5GzPbHdCcdnfkSNU9m6gUbsxr95GGSDdDC9u3Qkvae6Fl7f3Q8vZd0Ir2vUoh v1fk+MZV7QPhywZmWK6UbFzbPqyUGESbpJRxjZw0SLbpSvnGDe0Hocb2I0o5r0TGYvVJnW5LUSoM KbZ0ZdVGS/vxKbW3n1RW8Xrk3KSm27KUtRtd7WOk56Zyb/tFaLD9CjTafh26pf0WdFv7Hej29vuR ixt3eoXIFUOWLVfZsHGPV69soNmMk5X93sQHyiuR64ZcW75i2TiE1w7qnfkg5/XILUO+rYg/L28q jh95ZGzjiDcDeZFtkWLfeNibTTpvKj/mLYCe8BZDT3tLoWe9y6AXvCugl70rFTu/b+SOYZFtqeIy LLUtV7wbr3nXTOlN0nHvesWLc1uJM7zctloJbrznrSE1P8itzCsrwaprtnVKplX0OqdU8nqUTEOl zaBEa1Y1eUmDU/napih0Q9MWqLFpG9TStB1qb9qpRPm9AoYaV9OegMmw2mZSthjW2azKthpv035o kDRKuqVpSNnG9wasBoPNoWw3GJpGuPK8ZlvTYWW/wWRz+3tqtjcdIz3xT/nOptPQPU1nofubLkCH mi77e/i9Ag6D1eZTdhoctpCyp2ak6Rr0cNNN6LGmceiJpnvKHoPbtlnZX3Oa9KyDBdwGn22rMlRz wSGSSqTTlSGDz5GC/LIjHXrNkQW96cjlddvWgK9m3JGPyj1HUSBkCNl6lZFa5lgEFR1LlRHDZlu/ crhWsvUHNtdOdyxXDhu22nYpQ7UpjkpoumM15kEl4CPdGttr6LXtVY4Z+m0Dyv7aLMe6Kc11GHBm UA/01uY7TIH+WG7YZRtWTtQWOaykjild5HBDlzp80OWOELTSsRm62rEVus7RG9hVa3D0B/ZinoPK 6VqTY5dyGvkR6F7bcRyh1bGXdABHhQqOc8B2Ujlb63AM/6PyemCg1u04GBiu9TmOKIWGYduYcqE2 5DiuXOB54KBh2HES+UHbOXpGY6R/z3MdF6GbHVegWx3Xob2OW9B+xx28Rtsc9/HccV883yO2i/7z huO2K8rl2l3NwpTuJR1o1iuXDSdt15VrhjHbLf4eaE4knflAa4ebU/EeOGe7o9ysPdicMaVHmrOh x5vnBY7UnpTLA8drx5oLwCecDU7Wnmsu9nfXXmwuhV5pXja5go/xdTBwrvZ68wr/aO2t5pX+UVqJ LtbeaV7DV6Xm9f6rtfflE4ErRqG5xj9h1Deb/RP093LdmNgs42+Hv29vGWc2O/09xtRmDzSjWZl8 j93hr2/gvjG7OaycMOxq7obiPAQF47zmHn5Omvug9EyNBc07oMXNu5U9fMWJ3LdO9ypYfXDljwrW FG9YSbOme7uhWd6e2PU5qudXuWiiNdfbp6y15nt3KGv5dSY601rk3c2vOd59UFxJoqnWRd5BXD2W eg8oQf7OD/iMpc37lArjsubBoN64ovlAMNG4svmQ/5JxTfNRv2Jc3zzqDxtrmk8FZ2LMGYwxN58P phrl5kuB6UZn81Vlm9HTfCOYYVSab/v7jOHmu/4bxu7miWC2scepCc4z9jnj/YPGHc6kYIFxtzM5 WGzc50zzjxoHnZnBUuMBZ05wmfGQMy+4IsYbxqPOwuBK46izJLiGE0Wg0njKWRZcbzzjLOevgrMi WBNb2Y3nnaugl5xroVedG4Jm4w2nMSgbbzstQafxrtMe9BgnnK6gUqdxeoPhunhnMNgdY9rqNc4o Xn1ipxil1CU5twSnuNG5zd9Xl+zcjpUa741gX/Woc2ewry7NuSe4oy7TuT+4uy7HORR01uXRyELn iP9oXYnzcHBfXZnzGPJy5wm/s67CeRq6ynnW31231nkBusF52b+7zui8BrU4b/pH6+zOcajLec9/ qs7bwqDBFhHHE22RoFtapgcHq1e0pPh31G1rSQ8eqNvekgX2wBkIHqrb2ZI7+d421O1pycc8+1uK /BN1Qy2LgkfrRlqWBkfrDnPCrDvWsjx4qu5ES2XwDP+7CJ6vO92yGpQOVg9eIr1ad7ZlXYzAgzdI b5PeJZ3gj9KpiWndhRaDv6fucosJz/1aixXHdlO2d8bXjbc4JvMk0mT+99WZVnePn0nOw52ZpDmc ezvzTKzF3ZlHeSFpiUls8fkPmaSWEHgYVNxZZpresjnGwJ3lpBWkq6qvtmz1nzKltPRC07lyau1c S7rBlNXSHyPVTqMpt2WX/7wpv2UvFHVUiloGYtTaaSG1k7r4X32nlzQYU9OilmH/DdNSeaQzalre ctB/21QpH+7cYlrdcsR/17Su5TjU0HLSP2EytYyBLfG6dG4j3W6ytpwLJtaaWnBVNDlarnTuNLlb rnfuQQVXRZOv5Q6OPNRyv3O/abNL6BwybXXplcOmXldi54ip3zWz8zDqqZ3HTLtcGZ0nTHtd2biq 09XbNOCa13naNOwqwNV4zFXceTZ2JTQddJV2XjAdcS3rvGw67lrRec100rWy86ZpjBjggmsN1oLY KkPX7dgabTrnWo8VH6tt57jpIl9tTVdcNVjpcNXqvFe73GXuvGe67pJDzHTL5VRGTHdcns7LsXW5 Nsul4Lncd4U5S7i6lWi94Orha7qrz99Tr3fteLDa1ie6dvP1y7VPOVE/0zWISqrrADTDdejBSlGf 7ToaEuvnuUaRF7hOhaT6YteZ0HT+7EIp9aWu85NXWkf9MtclzLPCdVXZU7/SdSOUXr/GdTuUhTNz N5Rbv941Ecqvr2nVhIrqza3xoUX8vIWW0jzLa1lrkjJSL7cmhyr5NTy0epJ2oKF1pIYHVGNzhEyk xDkhB6mbH0PIRxqqd7amKTvrV7Rm4kg8nEbqFdvmoFAfbs2J5aHNpFv5WhDq5VfdUG99N51h0EWo n3QX8cOd+p7WPKwXyEN7SXvr+1oLlWP1O1pLQBTgitBA/e7WshhFBAWuoWHSrbVZreXKaeytgO5r XTW54t/hGjpYP9i6NrbKh47UH2jdoJytP9RqhKKOytFWS2yVDx0nPUk6xtep0DnSraQX60db7Vi7 sYJ3GutPtbqwUmMdD12pP9PqVa7Vn28NKtdqjrVG8d442LpFuUnn/DrpLToPw/WXWrcpF+qvtm5X LtffaN2JNZ0otP526x6l0LrceyiaYa30Hg3dt672jkazreu8p7pGrQbvmeg8q8l73j9otXov0Zir GOPw3gD3ur23owVWn/dutNga8k5ES62bOzTRZdatHfGYobcjKbrC2t+RHF1p3dWRppRZ93ZkRtdY Bzpyouutwx15WDcPdhRGa6xHOkr8N6zHO8qi5lh3YD3ZUa6UW8c6KqKy9aQ3IzJmPdexKuq0XuxY y1fVjg1RzySHX+kwklqg1zvsUcV6q8MVDVvvdHij3db7HcFoT6PQEY32Neo7tkR3NCZ2bIvujnWg G/M6tqPninU61FM0zuzYGd0X6/IaUzv2QDM69qMj4Gv94MZox1B00Cp2jEQPNGZ3HI6GG+d1HIt2 b0yikQUdJ8JDjcUdp6OHYn2WZbADPW9jaccF9LO3Oy4raY3LOq6hr8zruKkUNq7oGH/w6I0rO+7h GKhLalzjY+iYYsez3idCa3xS9OjGTN90Ja/R7EuJjjbKvnR/Dz8D0VONTl9WjFUiw40eXy5mU3z5 SrAx7CuKnmns9i2Kno/1g409vqXRS419vuXRq5xzojcad/gqsa6hs47eJr3buNu3OtYvRye4duZw DWRx3aThj7KJHmtTklXy4fw37vOhF24c9JmUPN7/bkpuPOCzTuZppJmclzY9OJPoXjflkRbyo9pU 0njI59hUQnkZaXnjUZ9bqWgc9fnQvaKH3VTReMoXinWsm2K6lhR9pW8zztgZ39YHynvMwH2um4yN 5329sb5yk6Xxkq9fsTRe9e2Coo7KDd/eWI+JR+daRkqd5ibqGTe5SL2Nt30D6BzRP24KNt71DaNP RBe5Kdo44TuolMka3xFovO84GE/0nVQy+euyaQvptqpx39im7XKS75xSLif7LipeOc13RQnKmb7r Snz93db9StS0uXUIV62J1hEwqhtXxf1mTevhzgvm+NZjoTvmpNYTgV5zcuvpgNuc1orebUovhO6b M1svdwnQa6Q3oTmt4116c17rva5Ec2HraRA79XSmzW6GmUvcYtdMc5lb6ko1l7und2WY9vLrJ1c8 SoU7pSvbvMqR3zXPvBZaUDPuRgdn3uDO6io2G925XaVmizu/a5nZ7i7qWmF2uRcpx7h2reTXya41 k70VqdnrXuq/aw7ahrvWm6Pu5V015i3uyi6zeZt7dZds3u5e1+U073QboNvdpi6PeY/b2qWQhs37 3Y6ubqgbOuT2BQehoeAgv5Z29ZhH3Ju7+syH3Vu7dpiPuXu7dptPuPu79plPu3d1DfKraNcB81n3 3q5D5gvuAcVuvuwe7jpqvuY+6D9vvuk+gmvgCvfxrlHzuPtk16nYCsW164zhnOto13nDOfdY16UY udWdcJ/rumq+577YdaOBua903a7a4r7uH20Q3be67jZI7jtd+obp7vtdEw0pbUJwTUN6mz6sachq SwzHN+S2zQwnNeS3pYaTH56toagtI5wGzQ5nNixqmxfOaVjaVhDOa1jeVhwubKhsKw2XNKxuWxYu a1jXtiJc3mBoWxmuaDC1rQmvarC2rQ+vbXC01YQ3QM1hY4O7TQ5bGnxtzrC9IdTmCZgaNrcpYVfD 1rZw2NvQ29YdDk5qf1tPOBp7t9SMt/WFtzTsatsR3tawt213eHvDQNu+8M6G4bbB8J6Gg20Hwvsb jrQdCg9hnqOY53jbaHik4WTbqfDhhrG2M+FjDefazgf2NlxsuxQ+UT/RdlU50XCl7Qb0etvt8OmG W213/ZegE9A7Hk34bMN9T3z4gkXwJIUvW/Se5PA1S6InLXzTMtOTGR63pHpywvcsGZ48xWLJ9hRG mGWep0Q5aynwlHXdtRR7yiOipdRTERy0LPOswrHRo1hWeNZGJMtKz4bIdMNqjzGSYjB4LMp2yxqP PZJu6PW4IlmGfo83kgsNKqct6z3RSD50SyTfMODZFimy1Hi2K5mGc56dkUUWs2dPZKlF9uyPLLc4 PUORSovHMxJZ3bDLcxhnCRpZF+v6LYrnWMRgCXtOROhzmwixSsRh6bb5Iu7YXxxnjEDu5CcV//jX cTD2WUHsk4GuHkuP53TEx9f3SIj34JHNk+9J+nSIf7YQ6LX0ec5GtsZIzLLDcwG623M54Jj89IY+ VzFrbNZIL//riPTHun7LPs+1yC7qOu8wgc1S3VL9N2Oqv6rwf6p7qs+YRvW5oGKioBVEFidMEyQ2 TUgSHmUJwmNCMntESBXmsEeFTOFJNkPIEZ5hjwnfE77HZqmXq19mKdpy7UssVevQNrM07a+0v2Lp idjYFxIzEl9lGYkrE9ezysSqxC729cS3En/JgomjiTfYjxNvJt5hZ3E0rzMN/X41kT3C4tijbDWb xtawGvYaM7I32Xr2DbaFhdhW9jELs9+zP7ET7D9U8ewPKkmVwD5XPaJ6TKVSpapyVHr+/UXVLNU6 Vb0qTdWgCqtyVVHVNtVyVZ/qe6qvqH6q+p3q6+r31e+rXBqnpkXVqlE0QVWbJqp5U+XVvKV5S6Vo 3tZ8RxXQvKN5VxXSDGgGVZs0BzQfqro1v9T8UrVV8xvNb1Vv0a//tmnGNB+r3tZc1FxSfUdzVfOf qn7NnzV/Vu3U/FXzN9X3+bfZVLu1M7QzVD/UfqydUO0VtWKW6oz4tPi0alx8RsxT/VV8XixRfcZ/ qaD6XHxRXCZoxHLxVUEUXxPXC4litWgU0kST6BAyxBbRJ8wXN4lbhOfFrWK/8IL4jrhHWMF/ByCs EgfEj4Q3xFPiKaFJPC2eExziBfGC0C5eEi8JXvFT8brQwb8vJQTEv4jjQli8I04IUR3TJQhv6abr HhPe0c3SPSm8q8vWfVEY1C3RWYUjumZdj3BD923dt9X8uz796gTde7oB9Qz+78GpZ+l+phtRp+kO 6n6lTuff11Fn636vO6cu1J3XXVUX6/5T9zf1l/XZ+iH1av1f4p5Q/ynxs8TPNPwXX1YWhUosnf8i eMktxH3GlhYgslm2vOtli7xXHpCHX94vH5SPyMflk/KYfM6mf91pS7TNtKW+fsCWYcu2zbMV2Ipt pRX3Xk1/aVflIfniq0y+Il+Xb8l35Ps24dX0V7rxrtLgPX6L3uN/ZSrV56rPmYB3dBJTY9/j9I1Q JrwnvMdUwvvC+9g3KPyYqYVfCL9gWvpGqCj8Tvgd09NvmeKEj4UzLJ6+CyrRt0AThD8Jf2KJ9P3P R4Q/C39+8K9/qVVq1dS/dqhViyyZfvuUok5WJ7PZ6hR1Ckulb2zOUeeoc9jj9LumdPUi9SKWQb9i ekJdpl7CMuk3Hln0nY2ncPySajqdOa5MTmPgBzlTzpHz5EK5RC6Ty+UKeZW8FrpBNsoW2Y5wyV45 KEexb4u8Td4u75T3yPvlIXlEPiwfk0/Ip+Wz8gX5MvSafFMex75x+Z6N2UBlNvCWDbRrAzX9w3bE BhaygXumtkrbats6m+GhzWSz2hw2t82HsX/fjttOQkO2zbattl5b/9S2y7bXNmAbpu0g5htDrch2 DtlF2xVk1223MGeR7Y7tvl2wbcbzV8VZJ68a/Hflj9I5ScGmZmnYNCybPc20bB42HXsWm56VYItj i7DFs1Js09gy9mX6/eAruOrEfjn4NbaOfjm4AfMZsc1gZmwzWTNzssdYG/OwWcyPbTbrxJaK69Fb bA57G9vj7LvY0tkP2B72BfYetifYALZM9iG2J9nPsWWxX2B7iv2aHfu/7H0PdFTVue85M2cmMU3H mEYEjBExphgxYIgRI40UI6UYJjOTGJEGioHOnPlzzpxM5n8o0pSmXMriIeViSnnIYyGXx6NIKUWk SJFLMaU8SjGXUh7FlEtzESlSSmmKMX3f9ztnkiHESte9b623Vrv2+v3Onn2+/Z395/u+vfdhMlD7 DlMag/+/80HhpPAroVj4NaWxwr9Telj4D0olwhXhD9T2HuHPwiNCH6UJoknMEMrELIp9Ffge9xMU +3KESfged6VYIN4nPCneL94vPIW/WKyiaOgQnsb/czdVnC3OFb4gNoqNwjP4Tnc1/j5xhhgQA4Jd DIpBoUaMiFHBIX5VbBVcFDvbhJkUPf9JeF78lrhM+JK4QlwhzMbfJ86hSLpb+LK4R9wjzBP3i28J 88VD4tuCW/yp+FNBFn8mHhG8sF8/RYExQiCzOLNYCOLbc1rmI5mlQhO+MdecWZFZIYQzKzMrhQj+ XiaK78fFMudmviAkMudlzhNaaG67hWuw/XL+vRsllzCcUEAoJBQbGG+gnDBJeE4ZrhQohUqxMl4p VyYpU5Rpil2pU2YpcxW3EqAUIsSVhcpiZamyQlmtrFU2KJuVbcpOZY+yXzmkHFGOKyeVM8o55YJy Wbmm9KomSpmqTc1TR6qj1CJ1rFqqTlQrlUNqlTpddaj1apfaoDaqsqqqYTWpLlLb1GXqSrWd0jp1 o7pF3U5pl7pXPaB2qEfVTvUUpW71onqF/180S6PFS4vgbNscslgT2ed/lX3PoHQ7rDwHVn4HrPwz sPI8WPmdsPJhsPLhsPKRsPK7YeX5sPICWPm9sPJRsPLRsPL7YeWFsPIHYOVFsPLPwsofFI5QKoat PwRbHwtbL4Gtj4Otj4etPwJbnwBbf5Rs3SSUw74fg30/Lt4jFpDds2VPgmV/DpZdib9TeBLWPBnW /HlY8xRY81NkzV8lH3hRfJF8gP9a4Quw5mmw5unit8Vvkz+wTVfj7xRmwJrtsGaHeITs2CUeFY8K tZnPZj4r1GXOypwlPJvpzfTyXxznLMpZSvOUTWP/KUEM7xCEwFLCCsJqwloq203XDYTNhG2EnVS2 T7ojsCy8Wi3864BMcbQksDK8NtAe3qCOvxFcFlgX3qyWEyZFyxiBjeFt6pS/DpYJbAnvDGwP71Gn DYA/B3aF96t2Ql20IrA3fEid9dcBmbnRyYED4SOqO3wk0BE+DhwNn1QDhFB0KvLxaLW6MOoKdIbP BE6Fz6mLB4DPS6MzA13hC+qKT8Dq6Bzo6A5fBi6GrwWuhHvVtTo4H+iJmNQNA+DPgb5Ipro5kslX hiJFbOq2TwbLKVmRPCUnMlLdeSOUYZFRSn6kSN1zI5TRkbHq/gEoYyKlt4LmVckjSklkolIWqRwS FZEqRvOa5HGGMjky/ZYwNeJQqiP1H4fm9cmTiivScCsIbUycVmZGGoE5ERmYH1EZzZuSZ/ga6kxm N29NnlN8kbCiRZKDEdqeOK9EI4s+Cc07kheadycvKwsibUBrZJmyJLLyBiyPtN+EVZF1N2BNZOMt Y31ki7Ipsv0mbI3sUnZE9t6EwWO9O3LgVqAeis5X9kU6lIORo0OC7qlHoj71eFSD3OFI5y3hWOTU kLbD+k4SzkSjyolI161APRddoJyOdPfjbORiP/j+BcLlaCvy16JL1N7ocuV85AraOwhBU3QV8pci PZ+EYGZ0TdAWXX+DjquRvhtwPSoNRjAvuik4MrpVFaJZwVHRHbgWRXcP1Z6Pg2qN5qjZ0WE3ITea rw6Pjr4JBdEx6QiOje5LxfYbYrERK1MxLlgaPZiKQcGJ0cPpcaTfTtLnNTUvqTGqjB7rH9uq6In0 NiGW7KOYQvbYfFC3y+bDhg+zXx0jnEheY3tvPk04m+xN2XPzebrSc4LTo6eDjujZYH30fLAheinY GL3K60tQjl7ncvSN1oigGhN4LQmGY9ZgMpYdXBTLDbbFhgeXxQqCK2OFHNu5z8H2WHFwXWw8x+fg xlh5cEtsUnB7bAriMsV0Hovgrtg0jp3BvTE76w0eiNUFO2Kzgkdjc4OdMXfwVCwQ7IqFgt2xONZI XoN4TeAxvBgtCV6JLeR1LNhD609qnPtidk2KLWYdfE/Lii3VcmIrsPak1tq0OerXyTDWlNRawO3i tVEbFlut5cfWaqNjG/rnmeVp7njutTGxzVpJbJtWFtupVcT2oGwyreErdfB6zev2Ddior8va1PBO rMf0nNRazFeA7Ad9G7TG8pWhVYfPMHh9TK2rKWiu8GVG/xrJa6axNqavlelrZGqdTEGbSesgrYVY +2g91OZERjFgt7zOjdahzY/tZ7vUfLFDmhY7gnw0dlxbEDsJm6X4obXGzmhLYudwb3nsAq6rYpe1 NbFr7Lfa+lgv+xP6tSlu0rbGM7UdcRv8IuUHRlzkWKrtjudxnNP2UWwyfEQ7GB/JcYvrp2LgTb41 yK/644vhW6yD46Z2OHpVOxYfxW3sr0/y7G/aiXiRdjo+VjsbL9XOxydql+KV3G6OSdwH7Wq8Srse 19eGT4pBRruaBCOOp+LSyTQZo83o66B43N8fjsMpfNyzPiaeNlmNa3Y0i+cihZviZHqs5PiYipFp 8ZBloYdlODbRGDTlRrc2X2ox8Rw3X23J5H42X2+xhYWWvLC1ZSSXI2Zpyc3h7JZR2L+Q3bFsOLel CPsN2neEh7eMxZ6CYlq4oKUU+zRjTxAubJkYLm6p5PU/PL6limNduLwFsTA8qcXBYB8NT2mpD09r aQjbWxo5DofrWuTwrBYVezKKl+G5LWHUdbck+/dMvOcx9ijQZejge+FAy6JmV3Ip2pXa26X2Bq6B GAyk9jDG3oN1QUeopS00MuFCnVR9lucYzZ/ZLngMuG/xlmUo431jCsY+8Qbcyl6Q25ba06Xt6/rB +7kUBu/rUnu0IfZm4YU6PnFvxnuv9P0X77lS+670PRa3leuyTGpMDN9qGh534FoQr28qjDfAVnnP k/Kr4nhj0/i4DJTH1aZJ8XDTlHiyaVp8UZM93gbUxZc1zYqvTLf3prnxdsAdX8f+1RSIb2wKxbc0 xePbmxbGdw3pb3Q+aFoc39u0NH6gaUW8o2l1/GjK35rWxjv78xvip4DN8S4GfG9bvLtpZ/wirnvi V1I+2LQ/3tN0KN7XdCQh9fsf+VXT8UQW2nMykcMxq+lMYhivPSnwnrLpXCK/6UJiNPp8OTGm6Vqi hGMXx4+m3kQZrykp+ZApURHKTEwO2RJTQ3mJarbH0KjEzFBRYk5obGJ+qDTh431BaGJCYz08fqHK RDRUlViAvS3Nf2h6ojXkSCwB6hPLecx57EINiVWhxsSakJxYH1ITmzh2h8KJrZBPJnaEFiV2h9oS +3gPGFqWOJiKzaGVicOpdSnUnjgWWpc4weeR0JbEWT5ThHYlLoX2Jq6GDiSuhzqSAo9j6GjSyucR XrtDp5K5rCPUlRzO8xzqThawX4UuJgtDV5LFoZ7k+FBfsrxZSk5qzkpO4fWd7zXnJKexz0GO2t08 LGlvzk/WNY9OzuK2N49Jzm0uSbp5zpvLkoHmimSI+9U8ORlvnppc2FydXIyYYMRcjpPNM5MreK1s npNc3Tw/ubbZl9zA8a45mtzWvCC5k22Xx4vzza3JPbBnsoXmJcn9zcuTh3gcBZMg2tpsKwThH/+C 8nf0LygXhSsD/w7grRYCXs0b9S7wtnqXeJd7V3nXeNd7N3m3Eu/w7vZWGykK7PMe9LqMdNh7zHvC e9p71nu+fq/3kveq97pP8Fnru33ZvtznhvmG13f5Crzz9UQSBF+hr9jr01N9x3M5vvG+8vpdvkm+ Kb5pPruvzjfLN9fn9gV8IV/ct9C32DszlUhiqW+Fb7VvrXeOnnwbfJt920huJ9rHLWJJvsdPpCfw e/5PbyHb/uJ/yXvQGeQbNZTuwHvQXLwH/Qzeg96J96DDBFnwCXcJAUoj8Tb0brwNvQdvQ+/F29BR eBt6H96G3o+3oYV4G/oA3oZ+Fm9Dx+Bt6IN4G1qMt6EP4W3oWPK5I0KJcJTSI3gbWoq3oRPwNvRR vA0tF/5DeE94THifUgXeiT6Bd6KfwzvRJ/FOdDLeiX4e70SfEgvEAqEK70SfxjvRqXgn+gW8E52G d6JfxDvR6Xgn+gzeiVaLXxVfFOzi18SvCU68E3XhnWgt3ok+i7eh9eTprwvPiW+Ibwiz8E70S3gn OhvvRL8sLZW+JczFb+U1SrulN4T55NeHBLd0XnpPkMl/rwk8f3Fh4YCtynlCqZwnj5RHyUXyWEql 8kS5Uq6Sp8sOuV5uQFopt8vr5I3yFkrb5V3yXvmA3CEflTvlU0iNsiyrchj1x8pJ8CK5jbiR0jJO bDemh8huHjbsJhfPZ4sx0Rx9lqyHbUWi8S8l62FbscJWMshSniYb4nfmt5F1zCIbYvv4FOwjG+/J P0398pMlsTXkkC28RPbEdpBLVrCJ7IktIE/4PqU7YQHDYAF30fwfJLvl9+EjaM5/RRbGs343Zj0f 78DvoZm/IBRgjkeJOTTH92F2R2Ne78eMFopfFucKD2BGP0szqgljxCjNaDHecj8kLqNZHItZfNj4 HUl+pz1OfF3cLYwXxMzyzEkD8+Gpl+7w1A9Ocqu8xNPgafQs05O83NMgr+LkkQcneY1H9YT1JK/3 JD1JeROVDEryVs86zyJKbZR0nTtwXelpTyV5N8nclOR9no2kYYtnu5F26Uk+CD5MvPfmJB/zHPB0 9Kc296FU6tfcNjgF9/uXe456OlMpeMhzykhdg1PwCLWqW0/B456LnotyFpUMSsGTwTOeK8Fznh5K fZyCF9Rjnj5ZkrNSKXhZzhmcaHSWeDZ6J3k65WF6ch/XU/CanC/nBy/I+QPtTGtxr3uFPDqVPD3y mFQijbruEvnEoHRaPkvPKetP5+UKTu4VN/davuQZKU/uTyw3TJ46KF0lXJerkVyyyyvo5V6rN5uu M3XtnLy53uHynJuTt0Ce7y2UfbCXRd5i7jEn73hvuXeSu9c7xTvNax/Qk6axzn08zZ40OeqdpSd5 gZ68c9m+vW7YruoNeENsC94424x3IduHd7F8wrsUvZ3qXeFdjRathva1clSOsqVoJozHRi1Ts/Go ank8+tpIHmnvBu9m7zbvTu8e735Pg/cQ1TtCuo97T3rC3jPec94LnjbvZWrfOu81b6/P5Mv02Xx5 vpG+Ub4i31jPOvd+X6lvoq/SV+Wb7nP46n0N1GKVWrnX1wgva/PJPtUX9iV9VZ6wb5GvjXSx16JH kFwHP6Ee+ZZ5kr6VvnbfOk+9byPpPkRyjeRLu3xbKNfg2+7bRbzXd8DX4Tvq6/Sdgi8n9eTr8nVz b30XfVd8Pb4+v0Teyqndn+XP8Q+DjdOT/PmeXf7R7I3+MYQSf5m/wj/ZP9Vf7Tngd3k6/DNZC3ue f45/vm6pcpnf59f8Uf8C2eVv9YT9S/zL5flyvn+Vfw2N8gL/ev8m/1b/DrLXqTQDFf7d/n3+g2Rz Lv9hSsfkav8JWGCJXKLPFeTmsMXwXPlPE876z/svySX+q3Qn6r9Oi7o1kB3IlcsCw33rAgWBwkCx pzMwPlDONQKTAlMC0yjZYeMV3qUorQvMCsyVXQF3IBAIUYoHFpINc6oILA4sDaygVs/3LAqsDqyV 8wMb2E4DmwPbAjsDewL7A4cCRwLktYGTnvbAGbJHjfsWOBe4ELjsnUIWGpVLAte8+2lsdnmnkMed 0kZR7JqjHtOKtLGebq2U7LnP06NNpEiRo1V6z2lV5Mud7kPadPWYeoz92lOlOeQxWr3WoDX6pnsL gtk02hvZKimacXzq4ceSFEnQpw5NpUjF8Q4WrEtyhMG8VHkuamH3Ci1JNr6IyseQXCfFq3yNaxzV lmkrqY3t2jpto7ZF267tQhS8qO3lCKgd0DroaUe1lVon0imKc5Ie63y7NDyNLVhrdx/Xujmaad2k mSUvale0Hq3Pc0BbpkcuxK4czUSpncZ0NLfEfz7Qq/BPvGUqNiWPItRmZaQy0r2ZbGW9Mkop4pjk aVTG+sJKqVyhTFQq/a1KlTxVma44lHqlQZ6pNCoy3VGVsP+8klQWKW3sscoyZaXS7lnkX6OsUzYq W5Ttyi6lXdmrHFA6lKNKp3LKKyhdhG7lonJF6VH6VMk3Vs1SczxblFP+85696jCSbvB0+ZfgDr6T 4wnzt3L8O7yb+Zs5nnX9382Zo873dKk+fDvH+G6Op4+/m6N0es8Z389Z7jkw5Hd0zquXlE71Kvla jzebv6XjzQ5ayU5dZK92mvntcjSYS7FxjPvQwDd3vLRaBMvlnOBwf47xrR3j2zry/GCdWmJ8U6cA 39UZ+GZO6hs5ewIh7KYe/scJ8+/ohCkLGr7VMIxYcJ8TRE+pkOfuotTt7p7dMLvBfZFSu7sd+Svu K7O7Zne5eyj1ufu4zCNRyvJkcVnDwoaFnhxKwzzD5pTNKfPkUxrtGU3PMdnsthp6Rg5ONAJONCac ZczY80o4y1hwirFiz5uBU0wmTjG34eTyKZxcsrHntWHPezv2vDk4s9yB08pnBDFnfo6KPuF7h+75 guheQlc6o7iXS3dM73O33gqq17pbn5EIWR+DHB3V23Q8M+wWkU8YPQTG6Kg+RNeSW0P1cbqWGagw MFmHe45+rb5AuEz5qYTqm1HdS1fXJ2NGpqFjpgHWP38QfENAG4To34AFhNYhsISwfAisGoQ1twaX la7rCZs+Blt1uLJ1PLPjFrGbsO/j4cql68Fbg5Nt57CBYwZO6HAN169Omh9XAeVPE87eDCfb2flP hquQUEz5SwauEq7fiGphCFgHIftvAI1F9fAhQP2pLrwZg8e6uvjWMGMiXccTyj8GdG9GJaHKkJt0 i5gytO1AB+t00HXarWFGPV3twBJc69KQkmk0rjJBpfysgWelY0bYyM/9ZMxIEhYN0uEehMDNmNFG WEb5EMWd+fp1RvvQ7flYxAkLh8BiwtIhsOJGzFg3ELtviLepeJmKYxsH4suMLTfGj347SZ/X1Lyk xmh72tjuurFN/TEl3TZTPpzyLdZl2LyrbpBd83zuJRwgdBCOultruA20vsw4pZdzn3iNmNHlxlri phg74yLhCqGHQP2387pVrffXTmuVndcqmhc71bVTHTvHAc2I6TQO9jF6vLSX6HrttJ646b6d1g87 xRQ76bKzrpnG+KbGk+ryOmnn2M86KwbGmXXZo7oOvmenWG5v1dt10zwNmqP+9cSYJ9bFa6Od4r6d 5sm+Kq2+S587/mynsbdTHLeT39m3GjJSGnKGwOB1ecwQKHEPrK9pa2w/pqZh8BqbWi//M+vkAveN a+ES98AamLbe2U/odmmn+G8/a+TJ5uyXDJsle7NTLLdf1z/XCMaVYnVNtu63Nbm6P3G/aij+1lD8 rSk0/CLlB0Zc5FhaU2zEuboBH6kp1+MX1++PgYN9a5Bf9ccXw7dqjFjM9l8zRW9jf/25ur/VUP0a fg49u4biX81cvd2IS9SHGtJXEzDqfVL8GRTHh5RJtXmIeNyPWWn4uGd9QjzlebgBg+NkeqxcnBYj 02PieKPuQuNesR6jXXP1OXa59X666HkuknPF9XKOWU6yHRfVw/5lgS7romdgv0H7DhfHurNGPFth 2KaxJ3CtJlBM4PXftcGIc5t1va5tOthHXTsJewj79TjsopjmOmLET4qXruNG3ZPugT3TsbQ4um1A B/ZSZ6jdB412DY7Dg2Jw/x4mFYe3GTrOuVsdy4w6qfrn9diMz5v0MUDfLhhl69OwdQjcyl7woHtg T3fM3b+v68fpNAze16X2aP+ZvVmu+8b9V4G7f991w1q2z6g7fGBMUr5Vs9S4st+tdg/seQy/qiGb qNlggOyhhsa8huavhuavZr8BsoGaIzfae81xAyd1/6qhea6heaqh8a+5PLS/cWysuUags43DRMgc 8DeHLS2fZ2CkDvY9xyhCkXEdO+CDjlICxTtHZZr/UZ8dVXp7HNP1mOVw6GtPCryndNB+ztGg99lB +zaHrMcujh8OVV9TUvIO2q85aB/moH2Yo023R8dKAu2nHLTHcWzU9wWOLYYeGj8H7Ukcu/R4zPPv oD2E44CBDn3MeewcXK+TQHsJR5ceux3dhjztIRy0h3D06HtAR5+7PzY7pYF1yUn7CWeOfh5x5utn CietkU5aI520b3BW6OPonKyfR3jtdlbrOpwufZ6dM3W/ctIZ0knroZPWPyfrprXOuUBf33GvVfc5 znO7nTSvTlrznKv0tjvJ/pzr9Tl3stxWvV9OjmHkb859ekzoj7kUw5yH9bXSSX7m5DPTaT3eObk9 l3Tb5fHivPOqbs9sC04aV5egjyN/G+PTBz79k398G+Pv6V2ZVCwd5H9RNR0WXhOEjFGEIsJYQilh IqEy7VplXKcTHIR6QgOhkSATVEKYkCQsIrQRlhFWEtoJ6wgbDWwhbCfsIuwlHCB0EI4SOo1nnSJ0 EbrTrhfTPl8h9BD6BCFTImSlXXMIwwj5ujxfM0cTxhBKCGWEirTrZMJUQjXBRZhpyM8hzCf4CBoh SlhAaCUsISwnrCKsIawnbCJsJewg7CbsIxwkHCYcI5zQ+5V5mnDWuJ5Pu6bkL+ljiuspo56cdv8q 4Tr+i2/hNiuB/PW23IErj89twwkFaddCQnHadTyhfODKbb5tEmGKUX/a3wbMWTqm6+Dn36Bv+CDY CXXG1X6znttmEebq432bmxBIu4YIceE151LnCudq51rnBudmhjXu3Obc6dzj3O885DziPO486Txj DTjPOS84LzuvOXtdJlcmJZsrzzXSNcpV5BrrKnVNdFW6qlzTXQ6g3tWAz40u2aW6wkDStcjV5lrm POJaaQ242l3rXBuBLa7trl2uva4Drg7XUVen6xTV63J1uy66rrh6XH21Um1WbU7tsNr82tG1Y1zh 2pLastqK2sm1U2ura121M2vn1M6v9dVqhCjXqV1Q21q7pHZ57araNbXrazfVbq3dAeyu3Vd7EDhc eww4UXsaOFt7vvaSNV571UjX+3Ocv14nGMlKKdvVU5dL5af1VDe8roAwvK6QUjGl8XXldZNqr9ZN YdRNq7PTmjBiyF9cEIxfXMjELy5k4RcXsvGLCzb84kKOiX9xIRe/uJCHX1wYhl9cuAu/tTDCNsr2 iHC3bYKtSnjYNs8mC0/aArYm4Wlb2JYQnrEttL0oOG2Lbd8Qam0v2X4kPGt707ZPWGTrsL0vtOLX Fzb9f9wyUcwVNXxfZY/wkCDcf8IAefr9Zw2cN3ApLc8g777/upE/y/9xu54vtBrINkCeXkgeVEje XUhChcW6bOF4Q57LytM+TzKuUwxMG3hmoV3/XFgnPOS0Usp25jqHOwsoFTqLkcY7y52TnFOc05x2 Zx3SLOdcp9sZcIaccSpd6FxMuaVUo9jwRt0f2RM3OPfQXN2OX9oQ8BsbJvzGhtlWaisVJNvTtqmC xfZF2wwhA7+3kW37sq2R5sFr8wv32EK2ZmGULWn7qjDa1mr7ulBk22vbK4yx/dj2Y+FB20XbRaH4 /7F2se9L0hPEsyw+4k8hn4V8GfJlyE9A/hHJzmxZhHyYuNTyMvJPIO9D/iHkn0GtscQlhrZaaFvI dyHfII1htrj4W0+WJOXzpEJmS4R4B2Re4bofIf/Rm9DTinK/3iqjbZXQ3Iz8NJQjb3mB2foyyj+H knmk5zfcwo+6LDPR2kr0SK/7EGS+hNY+Cp3zkH8ceS9a/hR6J6Mu5x8x/wUlDyP/G2j4FO5OQ7kC zU+hvAn525F/EjIleHoDnnI7nvIk8k8hr8uXQ95NPB758ciXShXgcmhACXgCyh/DKD1m8eMpFZDh /ARzO2odgmQYmjcgvx75o8gvQ34vt6FvMuQrUf4oeDHxOPAEzNcE6Wnw46g1H8/1gt8QRFPAspy4 0rKE+BsWeropivxdYDP4pGUNcRtLineA16BWKVhgNr8IyQ2WbxHvtHyX+D4uEc9xXvwQd9dCfjbk 1yNfBs6Dzvcgc7/0M+J86SfELqmTn8J58Rfgt1Huln5JbGdJMRM8B7VMyL/JbC6E5DyUKywv9kHD 68i/ibv1uDsS8k+jbjf4z1KQyqstLNkjqZS3Wt7h0eBysdFymPi3ElmO6QGWET60vEklNvD7Rgmx +fPQ8wC4CHUD4HbwfZbP4u4LPErMpg+RPwH+LfhlqYHnKOMesInZ2gvuRMkD4Nn0rIX6DELyG9aP eB6Rv0tn1LoLte5Crbsgsx13t6PkJEraUPI/2BLEOzhPbGJmDcSdKHkA+Y9gD2SfpvmQX4C6pSgR kBcsZ8FcMga8AeUb0JedyO/U82jhTrRwJ9qz00rRw/xz9Os+WOB9kH8UrToH/lBny0q2LtxdC21r oW0ttK2FtrU8SmSB1AYznmvWn5iHWnno3XvQ9h769Wda7ogt58Ad4NfAvbhLvmYegXnsgeQp8CVw j+U4bOMa2wyXkB91gF8D94KP8yxD/rfQ+Vu9hGuJn0arxnNe+JBlyKI6wK+Be5kligYmUbc9zos2 aHvf8q/MXCJ8mDEL8r/h9qAlD3CPTL1oQxFKilBShBYWoYVF+l20v0i6RD39sm7Jlqtsw3hKO+pO RMt94PusUch0gF8D9+K5j7Jts7zZojPG87fgl6HtZYzYYfYsikgbYNX7YKs6wwKR36kzNK9FPg/y eZj3PC6h2VEw8mDuHY2hgv7CZ5np6ecw/lyyFfbzOPiLiIEjLP9C/J61mng5yv/ALILJO/4Fs/w/ 2VtRchKSs+EFeeAy6CllNi9HfoNlNVpOtcyPQv9/Q93JkP8N8iXgN3R7RuR8HVH0XXhBBpdbr7Nt WDfzuFnu4bqSn0fP+i7nrXbOm3fD8qfCnv+NOUPi/lpXSV3cWljXYoxbM7eH/NGOMR8HHoExHwce gZEfBx6B8R8HHgF/HAcegbkYB2b5P6L9L0FzPvoeQGzZCc7TY5f1IUSqMuICbon4IefFtzCzlRkP cgSDvBn5k6jVpscotLwN/luqxxm+a34Rfv0iZDaA7wM/CY8+p3PGD5nprM5P5LuzYTmzERnWcwmt Tax/Gu6W6VECdd/LeA4WQl5gGgeukH6F6MQyn0PJA9K78ME/EU+Gv1yx0spr+lcuJ4/4EyI/eYQ4 D/nvc4S3dMMvBJa31CEOfICSEYg5b8PXbsugeCj+GP4iYfav82xSRPoAdv4BPP0DeO4H7KcGwweR 75Tgm6zHpFh+T3w7M2k4jlp6/OEIcwl9WchtNtstPyau0WMd1kcF/WrMoB2U6UW91xxzSPMXue+s nyLPA7wCohefN+LhcbSHuV1n67fBVxE91mO3wLHoQ9w9YTBHiVrr1xFDHoXPMj+VMRor9buIUe9i JGmlFg9KZ/Cs3yN+/olHBnd/CMm7kS9G5Bxn+SblL0jTiS9LfswdR9FH8dxHkc8Afxv9PQo2Wf5I Pcq0aFjfWU8ZdimFGKsqPOUd8BHI/wwafqZHTjzdAf4jz4U4BpFzNuL5T5BfCZ5noR2maSb012PW RkHPOZQg8ounwC2Q38q9Fq9LzehjC3GxdILjCWReRY/e53aK66BhPffd8iiPkqWI2fwy2yTFJdJm /oDzUgz5GLfc7MQsj0Ck+pMRqdiuPsPazPdyC2k15F7nol+/lk5T/hHpp5TfjpJytOT34K+iDafQ rwrk61D3aWkHcZXEK/UqztO6w2N1GpJF5jsp/zto+xC8BeVPQcNjUhvx78HPWMjHTRLadg+e+Drk t0lvs71B53VwG8r/CA0V0HYc+RdQfshyBm1my/8G79ZoVxYjXs2RnMqrSP9z1gkk3ySxT/mYaX/I tZ7G+Gyy/BR+1wILZP4J795N91ufAz8BLgZngZ8Hv0Ss73VdkCwDu6xjOeJxXvyFwcXgLPDzYJZx Q345tC1HiR0lcy0cYzNRN5OfTlwMzgI/D2b5xyA5B5Jv6oy93DzomYeWK8grRr4YnAV+HlyPODOH RulJ7L37oLMP2l7XdUpb2MKhpx566qGnHnrqoaceo1HP2sxPs6S5Bvw8Wt4NPd3Iv43822j//dZ3 MBo66z19B60CW7Kh8x3UfQLM5S0WOvGZbOA76UzP8fApRDmKEqYalH+HWXwbea+lCt7NvBUlJyB5 J3qaL20nXsh5k4nZPA35eWCFa5nvYKbVh+vmotab0H8RJRp7oqneMhE2zGO4gkfMOpl7aj3ILP13 riX9iXfIlvc5b12MXcdjGMMkxtYE+cmoexL+W46zj4PPszRW8zBK8zBK8zBK8zBT8zBKnP8J2vMC 5M3I349xVphp9GC9lhq2Uj65Uy94LfiOtJ9K8g271S0zC9ao22QxrCuLz2uY00KUz4POPvDrBvNK 93pGFPIsM5JnjexhLHqns24PYyFTjLsvoeQltDZCMXaxmfyxz27+A7PlPkH86Of83uOjn1u+RvLf 5RO6+bBlLo3n4xzhpa9w3vx98LdRvtkSIn6FJUXI0+pPLN2Lus8wW/2QfIvfTkhv87sLcxc0PMvv Q6Qc3P0Bar3KnHE3yodBQy94K+Tn4mS6kOfd/EOO3uYzyH8BPIFZGsXnWWk01uUlkP8xZvZXzJaN kJnAeWkkS5r/CVHld8j7cPdB3B3ObK2CBv0EvRU8Dc96kmOg+RV+42Geyuus+d+xK1iCc8FB3reb D/GJmPZOJCMu5/EUN2BUF6DkG7xDsFyCnn3gTvC/gX8FPefAR8Ex6S8of4F3s8yWt5BfCH4D5+Vr OB3/gHd90pPY+/3IyJuYeedG3ImSB3CXVhbrYxh/BZLZ4MetCeL90LAM/DudWQNxJ0pYw/ch+V3U 6uUSqRcl2Hla/hnr4z9jR3oQ3AI+hR3mL7CTPIh97Cs4QffxrpJsiXfI3XhiHfiHHGktI6BzBNe1 JJFP6nnWQ9yJEtJj+TqflDNM6JfZMox4BvRcQDufYX+XvgcNNoNZjw16bBif76Ev3+PxsTzO+YyI 9TvgONsG9CR0xqjeBv1bue/mKPZ4v9SZ92/EHeDXwL2QoThmfQpz3QrJqRY6cVhett5L2j7HJ03z Li6X7tKZNRC/Bu4F27l3uIsTtPkQl5g3oO559krxNPbJXwWvBh/AfnIRzqTfxJn0a9gvLcfeAOd0 8RLvAE3roXk48sf41GyutPSx76B8AuuRznL7Jey9pa/ojPKvoLVfQWu/gtYu51ZJzXx2tv5v1BKw Y8xH33HuNteCd2Of8AP0aDVO0C9hJ3YE+h/WGU95GE95GE95GPJHeFSlb/KzrGWWBeAOvNngWnfq jJIajMY1jFiP5V34QgWsWme2zxI+O5O9UYlVs8A2kPeiRwn4VALyv7S8hxnRmUe4gM/RksQllkZp L1rI+UXI34n234mSXFhjO3imJY+0neOzsOXz1uVU8g6XW9bi7tPM5h8h/weWke7A2fkgZDpZ3pIF 37kX/DzOwt/DKfgys2UE79MsSa5lrcRTJkPnT7E+/hqavw9trWAbn7ilXbj7KrwpD/wZvnsb3hRl zsLJ6y8cpS3zOL5lvIUYPpXzpv+Ds/lj8Kle+MsruhejxAoNH7LOzFnSOqp1B1aBP3MLaeR5dj7i czTFqxGYl3FgPl+vw/n6f3GeJMeBR8DTx4FHYL7Ggbnuq1aOA11oA95USHXWfF7jEK/eBicQQwr5 JC79hk/f0g5mWgfZug5bX4Wds48fRL4XvXgFdbsQG3/IJdbjHCusfpS/BZ6P+NCFus+Cf5fxCLiN V0AusWSwRWXcDflh4FehExHVvJnP2tIX+NwhvQDOw4r8nOWV/8veuYf7VG0Pf64511r7YpsubZIk 9xBi265JEnIL7bSPhGIjRO57S0IduSVRQqIcOSVJkSS3n1RIJWknqVSSI6JyS8p3v3N81jrPG+f3 vKfznvPneTzPZ4015phzzTnmmGOutb7f/UV0nUR29mEX9D15/lrHE18Oa+2b8BL2PqcPeJJ1a1Ce j97mnuoHsfTvJw9MkLv9pHmsxzMyj2F7ZvNx0YTXB+KfMvJU6yJcchrv+vTTwqR5sgeZXbL6TK48 ZTvKKFYjr2Z1TxbZ1Y0opTUpvZyVFcn3SB/8unIVt7e6JzK/Cc9ln/A+J1/oVtBL7KQn2UPliSlP xhLskB027Ex2/Yk7gUU8xfTjqe0XeU73efdoFsoTup4kGT4cIH0OjpETNpJde+KBj0XWB+AOSm8O i8AhckWJIjcXB2RHpnQsPEaeeZ1avAU1F8szu8tIK+j5CslyoYt5vzBzURP2YtbG+JJv34YFjP1b ZqcsNjzdm5lwCrwJfTZPcPkyUr8NmorI9fwPaF+e+/Cb9xneSMMbl/EkPkGe4v17/e9dD/tQq53c XwWHiJa3/NvIRTLeddRdR912REsZPH8ETqY/a5m7S3l+fJgZf51dZglz3RTNS/Ic4fM06m/EvhWt vSIMPkJeRW4PkcfyTB210Bg+IM/4/hes5YvkrtXvJP0MgmC+ZAz6OY9oWcu94jizxekPiCfDjyVK 3U4knCj0v/FlXv5Knr9X5OC7QPb6V9mtvsSmH5nwLHmyF6XFheYJ2SWDqdLD8EY88AW93SNP/X4h eeo3w3mCPkqvOjDqyxlXS+lV8C4e+BP6lTIKs9l3Tw3+AvnEzZ9vPqUPTg4/of3d2PdhlvvIewAX 53LFD9FXRH4ytpE2p8l7gFAJ/YXyNsDPEn2YRx9mYl9G3gboH2m/B8xC/zUtdBI5eAy5cnQV3s7V ZFWyP4af4au1kDthsxSOgdF6LMF97Ab8afzPnFxddiXzFt6bw/vP4lylPWyGx7aTGc6Rzc7gnynw BmKsFs9Ka2H9WL4aVoep8FZK3bNP8DD38N9j+RB8NVji2m+MXBNOj1kdpkJp4QYsy/KkOU40/jg0 JdEc4wl3Ks+YC+GtcCfP8vRHP8cT36O8WzgpT2durbla+lksT3Ld++SO119Em4ukrv8g8sGYV8Pq MBVKT36SdwLuybeH82RNxviafKJt/kab1eEd8A158vWr0tqUmFfD6jCV0luh85j/gbQcbpJP/Ryf dS28Sa1KMcVLK2m5tXjD+bkjHhM+wtjLyvsENwqnCb6Qtw3uKiJ/jlyJq1cSjb+cvjURmhO+e742 Q/3/kXURTCOzSekZSk/BAWjukydrsxzeJZqgBfaj8O3l8KTQZYaXZXdGXgQPSq3gnNDfTZs5ojeT aLkc/J78MMVf5diV0np4eCGcKTbJVcQDyfgheITnzRPsnrtFThrMHrqc0ofx8Di8dw18kBibTQtV pM3klXJHFD7K0+g6f50rHRXHtnuONi/F8ZnDM5REziSRXTs5zHgOHha5nryd8PO4ylPSjrtvrCWR QNyWhpXoz9Ncq3dQzDFDaDrgz7HM6T54F/bjsK+AnMfs3yKasJJESLAYfV1Yin5OEVkfpYWHwm7w uMwdNvfJ7IctKN2ApgltLkNzEz3Pw+dviD7cFBamz4Xxhnz7om6B2wWUKXgH+UX5/gDMKHgOuRqc LN9GiEufh3yXoGA0csRScCb6qO5y5OW0tgx+geYL5D3YOL0eWCDvPJvCB2EuvBgauAdOFHrFhCqB JgMqoRmHvAiuguUjOSHvqw9Q91c082F3ai1EzoTp2HyHXBGWgVnoP4Rb0fSFHdAk05+jaDSaDbRc CU0OHIQ+6vMg+vMacjYsjX1LbA7CX9C3Rz6DHCLXgN8mJB9W5rqMyLOi8Y7QznXYV4GV0c/FJupJ ZL8bzkEzMNFAYjXyv8j6YrgH/iXyOXLvyOfICi6CqxKylj+IfC4abxb8ldL5tL8qGhfyJcgrKTWw djQWZC8aCy0UiUch+q+jcSXedy3cTgt90TeMRod9RqKc0/RKZDOKbHqeTQ+z6YkwHf0vyOWF7rrZ tJzNtYSNuFYb/Hkp7Z+ApblKFCfEjJkOqzGuetR6BDZLuPsTL+pzLfg6LAqThEmlhOEsof8+bCRj D59BnyyyWRPHcAMis498AhtFZkI+tzqFPDNRycmnE/WZzYPM40H8L7w3muVze2WVMbqmiaGyypBz I/ncduRC+E04kdKJiZthITwp+k7oM6ilkFUsF5I1iGZRzKFQat2M5mbReAfw/68xh8JCzE4rKHJ3 KTULsfkuprR2FZ4/yYiuidZOQt6ANUN/PI4W5xn9ZhQV5351ch4RtUI0wVls1oomKMU6anOO7y3g 4TmJonK3n2go6/Sc3KsTgd4C8a23Gs1YoWtZnp7IAKYj7Z/B23OxnENkVqTNX87JJwK1ErLXtGcU Id4IIxnPl2bUhaGBlRNtYCHiUzQp+OGI1FL4zVwXR6z48HY4F5v7YQ6avLg18e2lyJHn58QUm7cS bk/RlpG+in+imK9O/w/jkx9j3zZyMnHuKG/RiWTvMbgDasa+WXzoetgIioZ8aFrQzkfwPVoj/3uf io06RiRXTFR07IR+Lvq3RaMOoS8C05iFx+O1L/PVhTbLRRkS7oWHE78x0oZQPq9hB/HegMvQR1ER 5cksWj5CT55CX1tizCd+/ANiH1QpcD4xUf78UPpjfhAf+nnIeYz0JkqjXPdzlAdkvI7S24uwuRx9 cWy+QK6D/HKcD11vvfpofoJRDmFcujHsDNk7dORb8on3OWRX8paivx42gLSm2yXcnZImn5jLsFwO 2Wf1LtgTTkY/A8uoD+vQzIS/wXfivUlmZ3bUZ5H9F5HHUGsoHBDtbkRFSIzVgCF1DyDvprQe8oo4 BkSGOtqFy6H5EE1TeAfXSka/F25Az+7gdt6drv9kdS9B6b3os+PVmk1r2bSQTd7IplQ0B5GjXbsE jO43+tPauzDaE4chc+fgrcVjrbH8gj2iWDTjsjvosshDsPwSfkXm7we55/HvguytAZ4PuVMy0TwO YhRbC/qyuluKf6JZi/TxuGRHyCI7bYDXYlPx3CH2kWw4lKwuciuy/bfwQzJGB/QdEtfCQvinEP4X fXVyyAa8tCGWZS+4itKcmEPpbSFWk9i8Fvu2FRT9HbA0mb8jrW2NKXWvhwP5ZOQEn4A8ydvaJ5Nk x6+NXDs84urWQb6Ce+Dn+O5Qez6pbBwUyLh4n/OtyPpT5P/hmT36dkeC72BU5PPTrTx1duEz1i7h LZIT0B8RWUfyiaCl5DQ+e71Eng5Uhm7s5KmBvLnK9PvLM77/jON2kfVOX75PslJojvvyPJgvluqg 0OtHrdbCYKPQD2EtX94Ktqa1LNpZwruRprTzm9iEnambFV1XqPfCFn5pxzPmXujuuk1f5Fz0XYRm iNknepHVLqFXg9K9wiAdmwlwmXnYUdNCC99jLKIfDWktmB1dEe6D4+FKI29Tqwv1LORyQVcnHxDZ OynfKHY9dE8EJk00aptxT47qc6FeL3q1TeyDVtQtGbUgep1s1smaMqsl25tF6KXWMSkNUrFZAo+h ryJ0emkhUxgspFdnYGM4XtrRXeI+O3vPF/p7hCYLLqOHRntCeaujNLLWWjTeRkp5zvL2863p7yWG 9VTJV3qSjEvLZ8pPieyd0PI9vd1a3i1P02MdJ2qXn71iYu/NhvOgEZpxtLBIT3FcpSXCyxv59lEz M0WyqGi8X7GZzxW7U2shciZM18nO5jtsKmqJ9jL6IplZLZ82thbZ2wqXyf/hqDvoVFhSMgAcBmdA KzSVaCFHZD1Il5U1pV2s6sEi6+L6C1n76DdgmY1laeq29OROTNPaQe8FuXfyqjhNZe+wk/M9t7p1 MU++eWhE9mro2vTQjUWd9dNlx5RSL4BTdX3R6DWu5XbUrQyrxPJexyShOkVrc2Ft2q/sfYMPnX/0 r94YmRc039LyHGyShOqY1FI/S0/0p0rxNw51hGF3oXx/3mleRn4H+RRyf+THXUR9Gi52HAObCINC QvM3uAzNJTBNqCvAZ7G/A5tewjCBTUvYn9LmyPch34/lNngafSP064RJzZD7warYfIR8A2yI5l3k mciPwC5o5tOfojC6boD8G71qjWYr3Eutc8j7YGU0g+G9aBivX4+6U5F9St+HJ9C0Q74VOYlrTRZ6 PyNH3vuEFh7A5kb0e9DXQd6C/A5+wBvmRbgd1qLWp0kD5XOHaF5EDgrBy6LZQb4EpsHro9kR2X8n miORTS84FObS2thopqhVPpov5GHRTGG5DZ5G30iY1IyWq6L/iL7VxZ6x+A9HnsGmJ7KJfCIaPZz+ lKHnUelZ2BUvbUQegk0xeIhau7GP5rEsvJjeMtcBXgqiGIh6/hiMevUZPY9i+Ccsh9O3tbTfF0bx 1psIpG/hACy5lvkAbsamG+yD5giyFSbvkzaTieSwGnUH0Ro2SZ3QZ9KTatF6wXtHqPU2NunoD1K3 IjKtme+RWyE/iJyKHEXUGNpZxiwkGFdzuA72g49ieTu1ViMTIeHdjD1ajwe47iTkxuiPYok3ku5B 1tTKRh4RxTZXfz7yM7ycuouRmS+N98IF8Gk0Ua6YGa0XWqjDLG+Bxehze2xyIGsqqITMvPgdYQNa uAW5B2yLTT78itK7YKS/ApJDNGvZfwG2of034HNwLjbkQ72QWoeJ4WNomAvNWPwVkDXrX4flKvgx XE5rNZFPYdMZdkdDjg2xD8lFSbdhT171Q2SuEpJX/ZOQNWJ+QGZEQR4a8qePpcHDmgg0+5FZZcGr 2CyBUU6bgj7KtK9D5tFEXp0IyYrBN8hzYAq9uhpLosiwLgw9NOwO/khqRZHwJXr8kEQGCLLQr0fP GjTXQNZ++BJ9HgiJHJ9R+Mysj1d1NIpoftkdQjKtH80XdX0yg4mutQbuglEURRkmyoTRfvQQfWNP 8aN9jagwhZFLQFZKGGXmG4jeR4jbosTtXtY47fisygA/m/cpJcP7V8IoDzC/AfFsZtOfUbQ/AxIJ ZjSMduevkX+BtJxMdk2mz8Er1GLFJUU5bSl6Ziek1H+TuuRGM1h6pVRBY1gKvig7TkI+3RsDmwiD QkLzN7gMzSUwTagrwGexvwObXsIwgU1L2J/S5sj3Id+P5TZ4Gn0j9OuESc2Q+8Gq2HyEfANsiOZd 5JnIj8AuaObTn6Iwum6A/Bu9ao1mK9xLrXPI+2BlNIPhvWgYr1+PulORfUrfhyfQtEO+FTmJa00W ej8jR977hBYewOZG9HvQ10HegvwOfsAb5kW4Hdaibiall8HraQd7MxTmohlLaXk4jFp10dO+/zDs CQ3XHQ7L0EKkPwu7Uncj8hBsisFDcDf2kT/Lwou5Ij4P6G0QzQV98B+DUU8+ozSKpZ+Q6YO/lpb7 wmjeexMJ9C0cgCXXMh/Azdh0g33QHEG2wmRmM5mICqtRdxCtYZPUCQ365LfRpFP3IPqKyNQ13yO3 Qn4QORU5msdH4e1oViMzL+HdjCKK8AO0OQm5MfqjWDKupHuQNbWykUdg+Tzy5dgvRsbbmrGHC+DT aKIVxyrw2yPnQCIwqISM9/yOsAG1bkHuAdtikw+/ovQuGOmvgKw4TeT7L8A2tP8GfA7OxYbsoRdS 67DQO4YGH2r67K+ARLh/HZar4MdwOa3VRD6FTWfYHQ0ZKcQ+ZOUm3YY9WcgPkblKSBbyT0Ii2fyA zIiCPDRkGx9Lgyc1cWL2I7MWglexWQKjDDAFfZSXXodEtYm8OhGSQ4JvkOfAFHp1NZZEiCF6DT00 5FJ/JLWiGf8SPX5IYo0EWejXo2elmGsgKzR8iT4PhESIzyh8ZtbHqzoaRTS/5NKQvORH80Vdn/Vr omutgbtgFEVRHoiyTZS9H6JvZGA/2gWIClMYuQRkFYRRZojsI0+S6/wrIevRZ+4CYtXM5lqjqDsD MstmNIz2qa+Rf4G0mUxmS6Y/wSvUYtUkRVllKXo8H1Lqv0ldspP6wBgl78TkuyuVglTexsjfd7fm jVBfI596L+I9UhtKnwoCJW+Q0h3n8iZNi0Z/h3666P1QLN0mFMibE/TdhMEuoV8L/UlaGELpIWE4 DLkvbE2bxyJLrj5V/hbepMkbM/0Umgfj913y9u8Ub8/a8ibtbPTGDM1iqaV3otHYH4NLGGOaUI9n pJ15J7aFt1WZyJnmNaklNqpA9N5F8VsyR/U178QyaCeLWi14c9VYNN5F/nwl78qWyaqh9CnYRZgY UiB/mdupQL4ptL5A3kx2kTcYeqfIXg3krpS2QN6AvAfLMSJ7CVqoQumb1NqNXDxqDc3+xCI0Urc2 7IU+IZbeWTRPYF+Jun+ltD5ydUpD5DuRJ2HZmKt/iuVhSkeJnMiS/vjto1Eo+b7rGZFNEa5VAXmI 4s0qGh/Nduz3CkNfSWzQE1Mdm1LIGu7DMhk5DbmD0MWQyEu44krkWchLsCwJF/F26CByX2xyqdtV rmhWx32W0tFc9z36uQf5ZHxFicbayN2w75VYJ2/eRK92JeQtbmvanE3peOqmiP9dxuO9KJoZzMhA 2m+feI4+iH1PkfUW6bmpIbKL6QayG1KrpWhc3QWudEFitfMVEeKtScjb0eVS6nLXc4xXRlSdFvar VN7hryYHyt9pVoiuIt+CcL2Vni9FXwrPl2CMO6XNYBTt28TjzmYVNjMSEvmX0qaldDOsI73y5kXe k9F5E2GG2OsqiU1cd7vMjsh6PXIVmAxrC9211iNv4lpPSxxyxQkqXdaOXFevV0XkzSQeO8YVs9Af gFuY5YXUWkbfvoLNiC5iKeiNJiH2Zl+BfJpQpuB7xxO0OTC6SjRfrK8z8SoTz0xFThLKb3+57EoU +ZNhc4mBsL6UBp9IH4JOBWeZixVwGStR6l4a9URk5xnx1amC77g7msUK5br4qozMnTeRvrVAkytz p6fityXIjRNNxT+Jvtj0pXQCo5gg7Z/7Ac0hPneTFtJgC9HoavLJjt8QDx9DsyUxWqJXxuIdZi6+ wj4ZVk7IrxAEfB40X/pm0hPPcK0hrIh8+YyA3ip6eFlCPhXqWyDfBEhmjC8z6hSJK68tsdpXPOC/ HM2XXN1bE0WXWIbEmBvdJnZ28WEl8sz+KG/IGnSjEx+elNJwuVzFy6fN9vSqC/4sTt3arIXiondP bXziIAxSpYemI2uzi8yXOisecD5ZxizciKWMqEPiE/g1V6xOJEs79yYeoa74fJj4xPFF6u6j7iEi XOK8tPjEK5XgcxxKb0ucQpbPYnx8vhmb5dgvjohP5vH9pTmUPk4LjRjRFK7VKP6OxyburKSdldH3 nWg/hz4n4/M/MSNLhN4M/POeynI+KUp+qI1mvFBtE284j00njz0ua42c00zacXP0K30L2H2E72F/ TDwZLIQZzF1pstMdYu+8LZEQcpW9+HwW+c2X+Hc5jWzG/HYh20wUjeK7ZOpzuApfLWdVViEOp2O/ PqrFVXrTn8OMt2mcgZvgW7nKBmJmRjQK2kkWvduhAr6pIqu4lVw3fFR+wclFuPyd3duqqTwDcpUD rO4hRFol2l8m13UR/ivxWYSslc5ek86uxM5C/FvixCcL9cD+NNlsOj3ZqzLIe9Pos8hz3Y7k4hxv lCJWtbRvuuH/NVF2irNiK3bhBmSwhuzX0v58LE/ijbtoYUI8CieHUT6fEa21eHeTvzEcr99Flh1h G76qz0jzEx+Qpbez+tbhB/nL1s7C4Ee+k7aaFmYR4QPRNMWHk6U1t5ZX4DeZ60NwOnE1Bn1R1t14 omK0yOpndrQdaMZgnx+v6GXsWVHOz5CsQjykic/V54yrRzT77NeLo1Ly6m5WRymy6Hg4EE2C/bEk dxGN2VM2oiHnB0uJkAw8OZpP83OJ4TLsCNytJXE/43Zw7iu4VinxlcmPoz2f7LGaHKgYRZTJ88kD wh7YbErMU/IZ/RB6JXnmZlrogM0SYrgfmirYvxdzCPMyhGjPZ6RDGN1qduFF9NlpEr8U7CcSshjv 3c7y+WjHpNaw+K4sunOTOHybuuNVWSdvYoxr6f+XwkQdaa3gtPwWlmMvZzOU93uHeCPHW9BkPntS qWLj2ItP60SjaOG2QL6b2jU8Jb+ThpyKXAe5DnJmuBfNQjT5yJPke63hMuR85HOUFhY5qZ78Qhqa TDd70sLH2Pj8NtonwvCM9CFJ2kkPWwqTZssvpMlf8yWeTloiv5Am8rkNIiceCOfJL6Ql/SCfLCdd DM/wS2jfSvuRLL9u4eRf0PPrZ0nPIzdH7ie/kxZsld9Ji8YYHhD75OIiJ6Vi+Ru9rUs7PbEpTWlr xtUQ/sKop1O6HvkM+ipodkD5W+mM5PK02YSrD+Az8Xxkjc2faXkFXsrnipqrT0F+jbqN5dvIEaX/ zodfiT7ZIjemhUifQR/uQG6EfCctfI19EfoD6U9G1J9wFv3ZLL9sxqgbxKOuS8s9sbkN+ynIDWES ta5F5jfoku5CZrxJHRmFXCVT0RN+da1uGFDaBdnnKkfxySQ0dSl1s5O4CtZNMnAaNt/Cj7AsQF+H Pq+lz8wd3x40544hN4DZcpVzW6QP5z5A/lKY6AW7ojkkludWiYdj/UhYCJagnRLI98IG1FpLrW+Q t6LHP+ee5lqvo39X5ISmBWY87sNxbPZRq3z0KbpK9SYnH1Ym555hA1X6ncP63KXGDuw54m61Unag m7Oal1MuLxYUqBIqTYWqjKqoiqtaqp7zbzPVVv1JdXdt3KTuVferHNVfDVYj1aTYvrBKUpepSuoi dZWq71q5TrVTXVQPd9UsNUY9oHqrAWqIylWT+f9rozpWJbuMU9ll9NpuX7taNVft1a3qdqXVzeo+ 9WfVR92lhqo8NUWVVKZNp06tVdusjjeWU706Z7Urp+bSysX8HvXlLqdXcS3WcXcC16sb1I2qq7pD GbfDd1Zj1QTVVw1Uw9QoNZU6KaqcusK1maGuUS1UB3Wlegh9KVXU+aG8Kq2qunbrqoburqClaq06 qttUT9fvGuoWNU49qO5Ug9RwdY/bx6MeFFOFVAV1qarmWshU17qduo3qpLqpXm4vqamy1Xg1UfVz WXiEGi2/k52TMTzHZMMesC+8G+bCsTk9B44wE+EMOA8uhsvhmpyew/uYzXAb3AHz4V74VU7OoCHm IDwp9DUsCsvCGrBx74H97/RbwfYwq/fdgwf5XWAP2BsOgENgLhzTd1jPHP8BOA3OhgvhUrgKbnQN 9/S3wR0wH+4dePfIQf5X8CD8Hh6HZ2BCGPgDB+cMDFJhUVgKlnWFw4JKsDqsDevDJrA5bD1Y2ukA O8Ou8A7YFw6EwwYP6313MAqOhROGiH4qnAFnw/lwEVwClw93cxSsgmvhZrgN7oC7h/e/u2/wOdwP D8Fj8CQ8O3xQzpBQwVSYDsvCqjBj+PDadcImsAVsDzvDbrC3Y0Y4EI6AY+AEOA3OcqwbzoeL4TK4 Cq6Hbzlmhu/BXXAP3AcPwMPDR/YaHv4IT8PfhEkaJkM7fOSQ4UnpsDQsB6vAGjBjhPNkUkPYFLaA bWEnmA3lzY12uSf9Xzgat84vVWX+vySPH9n+fzNQ8t4rdHkx+T925nMWyZ66/B9Y+A/SuDxXiN/z /3ckz2Xv/53F/zA1M6Jdq3LmxfuUMPUPs9gf5mX/wKJ/mOXoqeHo/Y4ygt/r7D+lcTtVSVXqX5Qu RtJuf6rwLx0r8vPPf/xYWVX5F46e20n/Of+5Tzy3g/9zFvlDrOPuNka4XX+WWqxWqbdUvjqgTnq+ l+5V8jK9Fl5nr7c3wpvgzfIWe6u8t7x874B3Uvu6rG6vR+upep5eqtfq7XqvPqzPmlRT2lQ3jU1b 09UMMKPNVDPPLHVrUK6VHMWs6XDBea8LzqddcD79d+f+BeWhW+Z7VJL3u/PUzPPP0xadX9+ePr/9 9K7nn5dQ57dfIv2C8yoX2Le+4LzbBecXjKfE3vPPS1a94LzTBeejzu9/mYXnl1+2/vzzyjUuOK/1 u3O3/irXvqD8Ac61yw/FoxFe0Sk6Vo1G7ruYK+lyVZVYuzM+7o2PB+Ljj/+bdfWV8XF9fNwSH3ed 34sr7fmjvHLt+edXPXC+/VWfn39e573zzzNWX3C+5vzzup0vOM++4HzIBefDLjif/bsoc0L9uRec rz3fvv4Fs/QP5TsuON95wfmu82ex0Q5H6zyT4z2u+nrzyba93D/lVuos+UZGUIy9orgK09rYLWmt 7Vt2k93sNKF31Dvq7H70flSed9w7rrR3yjuljL3OXqd8e7293u2bEg/atDSt5Xq6uC7hNO7axkp/ TGFXs5Y7L+meRoap+WqL+kqd9dJdH5Jdr9LTblI6rXValmObtJsd27reF3U5uZx7Wqjtnnma2EPK 6KKuT99x3GLdk5Yu4c6PcNxidyvtzvY4brF7HbcpnwgtrSrYr1xfN7nSrzlusfvdcbM7/4bjlt9Z Hogtv40tD8aWf4st/97fdvS3Pf29kf7+vaQDJR0p6fT7ErudHr5HD3fQw7+X7KRkFyX5lGiVpN0/ t8wKafkrk6K6qPNqCedVk9Yq7Qbn9U12kwpdnzY7T7mnbC2fSUe7vltarn5P5ksxU5531jvrZq3A K3DeCrS776HdgHZD2k3SpXVplawr6AoqRVfVVVWqaWPaqEJBr6CXSgt6B71V4aBv0FfZoF/QTxUJ hgXDVNFgRDBCFQtyg1xV3Jaz5dRFtoKt4MZUyVZSJWwVW0WVtFWte+az1W11VcrWsDXUJbaWraVK 29q2Nv/nQ11Vxtaz9dRltoFtoMraRraRutxeba9W5ew19hpV3l5rr3WzI/FWkXirZG+wN6jKtrvt rqrYHJujrrB9bB9V1d5p71TV7EA7UFW3d9u7XaIYYoeoGnaEHaFq2lybq2rZUXaUusqOtWNVbTve jld17AQ7QWXYSXaSqmun2Ckq006z01Q9O91OV/XtTDtTNbCP2cdUQ/u4fVw1snPsHNXYPmGfUFfb J+2TLj4X2AXqGvu0fVo1tX+xf1HX2mfsM6qZ/av9q7rOPmefU83t8/Z5db19wb6gWtgX7YuqpX3Z vqxa2ZV2pbrBrrKrVGu72q5Wbewau0a1tWvtWtXObrAbVHvm+0bmu4OLlbdURxcrW1Qnu81Fy012 u4uuLPuei66b7Q4XXZ3tThdVt9hdLqqybb6Lqj/Z3W6NdLF73Bq51e51a6Sr3Wf3qdv4/xa62R/s D6q7/cn+pHrYE/aEut2esqfcc75WD7j18YCLpCJeETXOK+1dpsbzv25P8Lp63dSD3kBvkJrM/7Q9 1RvqjVAPeVO9qeoRb673hJrh/eT9pB71Tnun1WPer96vapYkGfW4DnWoZus0nabm6GK6mJqrS+qS 6gl9qb5UzdMVdUX1pK6mq6n5urbupBboEXqk2qjzdJ7a5O4jRqs39H16rNqsJ+gJ6i09SU9Sb+tZ epbaoufoOWqrXqw/UdtMYZd/fjOZJlMlTHPTQhVITHvaLDALPOOP8P/i+UFOkONlBH2CPl7d4M7g Ti8z6B/09+oFw4PhXv1gZDDSaxDkBXlew+CjcLLXKPXm1J7eD6mTCnleIq1oWkt9T9ptaU/plwr3 LjxAnyg8rvA0fdZqm2ySbXlb3hSxFW1FU9RWtpVNMXuFvcIUt9VsNXORvdJeadJtTVvTlLBX2atM SVvH1jEX20ybaUrZ+ra+ucQ2tA1NadvYNjaX2ia2iSljm9qm5jLbzDYzZW1z29xcblvYFqacbW1b m/K2h+1hKtjetrepaPvavqaS7Wf7mcp2kB1kqtjBdrC5wg61Q01VO9KONNVsns0z1e099h5zpR1n x5ka9n57v6lpH7QPmlp2sp1srrJT7VRT2z5sHzZ17CP2EZNhH7WPmrp2lp1lMu1sO9vUs3PtXFPf zrPzTAM73843De1T9inTyC60C01ju8guMlfbxXaxaWKftc+aa+wSu8Q0tUvtUnOtXWaXmWZ2uV1u rrMr7ArT3L5iXzHX21ftq6aFfc2+Zlra1+3rppVdZ9eZG+xGu9G0tm/YN0wb+6Z907S1b9u3TTu7 1W417e079h1zo33Xvms62Pft+6aj/cB+YDrZD+2H5ib7kf3IZNmP7cfmZvuJ/cR0tp/aT80t9jP7 mcm2X9ovzZ/sUXvUdLE/2h/Nrfa4PW662pP2pLnNnrY/m27xs5Tc+WSSa6u5cA687l53p+7j9VGe /5r/mtLhufCcMslNk5u61fPfbPzfbPyfycb/N/pKE33V5W7L6x9+9t8Y+2+M/YdizAsGuPv5ol4F nWla+V1UGdVYNVdtVZbq6p4XBrj799HufmCqelTNU4vUUrVSrVWb1Xa1S+1V+9Vhddzd2Ssv9NJS RimTMjxlRMo9HEemjOaYm3Ivx7yU+9xxhJPGchyRMo7jyJTxHHNT7ueYl/Jndxzp7CZwHJHyIMeR KRM55qZM4piXMsUdc53dVI4jUh7iODJlGsfclIc55qU84o55zm4GxxEpMzmOTHmUY27KYxzzUsYo 7UofcByZMtkxN2W6Y96/4ZHHGfnwlNmxZ+bEnpkbe+aJ2DPzYs88GXtkfuyRBbFHno49sjD2yF9i jyyKPfJM7JG/xh55NvbIc7FHlsQeeT72yAuxR5bFHnkx9sjy2CMvxR6Z5cY/POUpPLIYjyz9Nz2y IvbIytgjr8QeWRV75NXYI6/FHlkTx8rrsWfWxp5ZF3tmfeyZDbFnNsYe+Z/YI2/EHtkce+TN2CNv xR55O/bI1tgj22KPvBN7ZHvskXdjj7yMR1YTKZvwyJZ/0yPvxx7ZEXvkg9gjO2OPfBh75KPYI/mx Rz6OPbI79sgnsUc+jT2yN/bIZ3GsfB575ovYM/tiz3wZe+ar2DNfxx75JvbIgdgj38YeORh75G+x R97DI7vwyB4iZf+/6ZHvYo8cjj1yJPbI97FHjsYe+SH2yI+xR36KPXI89siJ2COnYo+cjj3yc+yR M7FHfok98mvskd9ij5yLPZKIY6Ug8kyqijyT6kWeSdWRZ1JN7JlDeOQYHjmJR85KpMj/ASz95m1a F1XN26WfNu1NR9PX3GkGmLvMcDPS5Jl7zH1msplippqHzDTzsHt22W++MQfMt+ag+Zs5ZL4zh80R 8705ao6ZH8yP5idz3JwwJ82pwvXl/+jzdno73QWekr/NN+1MO6VNB9NBGdPb9FG+6Wf6q9AMM8NU shlhRqgUk2ty3Z3AKDNKFTJjzBiVZsaaP6vC5knzpLrIrDXvq/TC9QrX4y1DaZXql/Uv98v55f0K fkW/kv9/2PsOsKpyrt0ke++Tw25UARERFBUE9YCoIIoVexd7B1HBAir2gmAf69jFAqJiw15wVASs 2MvYEBV7b6CiiMBdO6KDM86dud//z/fde5/fPGZll5OzV1byrnclOZuyfDm+vKYZPNF7NruOkXWR uQkXNh80ULsDPlm+8A7bIne4FrkGLckNhLsRb8Frb/R14p2QVPi9Fnwx3pK34q354rwNX4K3hTt+ +16CHJExb8ab8wKv4ymv5414kZd4mVd4lTfmTXhtvosH3cLhEbTPEL4W74Nkvi5fF6lwrRqy5uK4 DVw8t407yh3jjnMnuFTuJHeKO82d4c7+qMW12TJuHbcOalzPafutNnObob23coCj0HJH4Pvucc+/ 1b4O7toMV/dzB7iDXCJ3iEvikrkU7jB35Ec2ZrXHcXFQ+wZOe1tIPBcPtW/jAJ3hCc9C7ZoeWu2V kMUPa/2BHqzN7hW2mfa5v9m72Oe03gCfEwaT3WgSmoymoKloGpqOZsC4nolmsb9cPRfNQz/DKF+A FqJFaDFagpaiZTDml6MVaCVahaJRDFoNCLAGrUXrUBxajzagjYAHm1E82oK2om1oO9oB6LAL7UZ7 0F6UgPahXwArDqCDKBEdQkkoGaUAchxBR9ExdBydQKnoJODIaXQGnUXn0Hl0AV0EVPkVXUZX0FV0 DV1HaYAx6egmuoVuowx0B90FxLmPHqCH6BF6jJ6gp4A/z9EL9BK9Qq/RG5QJaPQWvUPvUTb6gD6i HPQJ5aLPKA/lowLo0Ji0IW1JO+JH2pMOpCPpRDqTLqQr6Ua6kx6kJ+lFehN/EkD6kEDSl/Qj/UkQ CSYDyEAyiAwmISSUDCEx5DpJIzdIOrlJbpHbJIPcIXfJPXKfPCAPySPymDwhT8kz8py84ETykrzi JPKavCGZJIu8Je/Ie5JNPpCPJId8IrnkM8kj+aQAIEj7LQbH8ZzA6TjK6Tkjrg3XlmvH+XHduO5c L643N4gbwk3mpnBTuWncAm4Zt4Lbzu3gdnG7uX3cL9w57jx3gbvIXeJ+5S5zV7ir3DXuOpfG3eDS uZvcLe42l8Hd4e7y3nxN7W+C85f5K/xV/hp/nU/jb/Dp/E3+Fn+bz+Dv8Hf5e/x9/gH/kH/EP+af 8E/5Z/xz/gX/kn/Fv+bf8Jl8Fv+Wf8e/57P5D/xHPof/xOfyn/k8Pp8vEBTBjNal9Wh92oD60oa0 EW1Mm9CmtBltTlvQlrQVbU3b0La0HfWj7WkH2pF2op1pF9qVdqPdaQ/ak/aivak/DYAUCKkfpCAa TAfQgXQQHUxDaCgdQofSYTSMDqcj6Eg6io6mYyCNo+PpBBpOJ9IIGkkn0cl0Cp1Kp9HpdAb9ic6k s+hsOofOpfPoz3Q+XUAX0kV0MV1Cl9JlNIoupyvoSrqKRtMYuprG0jV0Ld1M4+kWupVuo9vpDrqT 7qK76R66V/u74vQXup8eoAdpIj1Ek2gyTaGH6RF6lB6jx+kJmkpP0lP0ND1Dz9Jz9Dy9QC/SS/RX epleoVfpNXqdptEbNJ3epLfobZpB79C79B69Tx/Qh/QRfUyf0Kf0GX1OX9CX9BV9Td/QTJpFP9Ic +onm0s80j+bTAj3SY7qOxtH1dAPdSDfRt/QdfU+z6QdxlDhaHCOOFceJ48UJYrg4UYwQI8VJ4mRx ijhVGiuNk8ZLE6RwaaIUIUVKk6TJ0lRpmjRdmiH9JM2UZkmzpTnSXGmeFCUtl1ZIK6VVUrQUI62W YqU10lppnRQnrZc2SBulTdJmaYu0VdombZd2SDulXdJuaY+UJCVLKdJh6Yh0VDomHZdOSaels9I5 6bx0QbooXZJ+lS5LV6Sr0nXprnRfeig9lp5Kz6XXUqb0VnonvZeypQ/SRylH+iTlSp+lfKlARjKW iczJvCzIOvm+/EB+KD+SH8tP5KfyM/m5/EJ+Kb+SX8tv5Ew5S34rv5Pfy9nyB/mjnCN/knPlz3Ke nC8XKEjBClE4hVcERadQRa8YKaIiKbKiKKpirJgopoqZYq5YKMUUS8VKsVaKKzZKCcVWKanYKaUU e8VBKa2UURyVsko5ZbmyQlmprFKilRhltRKrrFHWKuuUOGW9soGtPrMZWTYzGk6iCSAom+9czTUF /36FawH+/RrXheuK0rgeXE+UznzoLS6UC0W3weNFoAxuPjcf3eeWckvRA+bZHzK/9Yj5rcfMbz1h fuspt5dLQM+Yh3jBe/E1MGLzpkQQBREbBBPBBLuxmVF33V3dI/yEGqgHfsVmSd+K08TlhIjrxCRi JZ4UPxJ3Nlfqz2ZJ48DbZyEjYAelwee3BAYUBR7gEKAzfIU0BRH1JCvFs5K2RmOCLJGtdAKOr0mp kKdJJyFPl858u/calFKQHriENbIDBlDhy+qRlKadl9IhPy3dgvyslAH5eeml9km1mFajaqnVqFpp NbK68litX9dojODomCpCfkKVvrtizK6YsCum312xZleKsys27ApBRmA1A9jOk2j7zL2JNyKkIWmI ONKENEE8aUVaIUFcIC5AOjFBTEBUfCO+gfqIsIFc/Id87Pce9v9v//rv8bCaD/27fvOf9JlmtA/t S/vTseCBNM/pCz6zOfNmbcAzzWF+shP4SM07fvGNgX/TK477C3/4R2+4DPzgbx6wqHf5v80bfvN2 4BeXgv8u6hXrAvvQuMcX5qHxjtbAPHIKeUcusI7OwDhWMc4RDYzjE/TaDtBTe2r98qvvJIO+95uy iWwqm8nmsoVcTLaUrWRrubhsI5eQbeWSsp1cSraXHeTSchnZUS4rl5PLy06ys1zhh952yo/9rWqk iqr0t7xu/B/9rmqsmqimf/C+J6RU6STzwWd+6IWvgR9Ok9KlW1LGV3+sWqpWzCe//FOvnPdHv6xa q8VVm3/JO3/nm+W8f4N3bokJLgahrA12Qha4NfZDZdhKqRPugQORC+6H+6EqOAgHIQ88AA9CVXEI HoM88Ti8CDXAUXgl6oH34PPInwwlYWg8GUHGo4kknESg6WQSmYZmkhlkNppH5pL5aBFb81xGFhNA exbjr+JkzgxFcxacBYrjLLkKaD3nylVGBzk3rgFKZh7/MvP4V1j0dpWP5c+jZ4KpYIqthWwhGxcX PgofsY3wSfiES+igubCtboZuNi6pm6tbgEvrFumW4vK6KN1K7KKL1m3ClXXxut3YW7dXdxw30KXq LuD2uqu6q7iHLk2XjnvqbukysD9wgzwcqCsAbhBJq1FvvI/WorXxIb2zvgJO0bvqK+Mjeje9Gz6h r6avhlP1XnovfFJbP8On9HX0dfBpfT19PXxG31DfEJ/VN9E3wef0zfXN8Xm9n94PX9B31HfEF/Vd 9F3wJX1PfQD+VR+kD8LXjSDsx2mivxiAb4iBYn98UwwWw/AdcYQ4Aj8HP7scvwA/m4Tfg5/9iPMl InUlVOoujSG95Wj5HglXZitR5MiX/S0QjW5lKy7dcd/CM3uLnMGoBtIVco9ywGk84Po6SFq+FVjB Oia1o8TCo0Q4ugVJ22Xjgl2g11TC2l9B9MSeUGcj3AicSzPcDPF4KV7Kdtmkot6CjVBCsBVKCnZC KcFecBBKC2UER6GsUE4oLzgJzkIFwUVwFSoKlYTKgkFwE9yFKvhXfBlfwVfxNXwdp+EbOB3fxLfw bZyB7+C7+B6+jx/gh/gRfoyf4Kf4GX6OX/Acz3PZ3AfuI5fDfeJyuc9cHpfPFfxXzvGgCk/YTAPP fq1gylazrCFxyBYSDy1XHjR1Rdq+tMqQ9NCqNYAn1oQkIh9IEmqAfJGMmkFSUUdIxqgz6gL8sAck M9QHkjnqD8kCDUNhqBgajcYgKxQOqTiMToJssDE2QSVgjNqgktgO2yE7tqehFIzX1sgexmsX5MBW dUuzkVoGD8QDkSPb5VAWD8cjUDk8Ho+HMT0Dz0DOeCaehSrgeXgecoURHIUqwgjegyrhZJyCKuPj +ARyw2fwGVSFzTd5sJFXjXHqpmzWqQebderF5sJsisyFVWS7qbxJN2ixksSNuAFzrKa9J5I0IA3g SlPSFJhjW9IWmGNH0hEJwH8CkQ6YzwBgjtPFn5BenCXOQ5IYJ65HJuJGMR6ZiVfFa8hSTBNvImsx Q7wPnHqcNAE5gBeZjBw1D4GcwUOsRi4anqPKgOdXkRug+C1UFZA8A1UDLL+PqgOeP0SeEGM9Rl6A 6U9RDcD158gbsP0l2Or3ulRiujQhwaCL3Xe6eBEvuKJpxJHWENPwTCOBaaQDntcFUaaXHljcEGTE 9BKZXgrTy4zpZSFuFbeDRjvFvagE09Ge6VhafCw+ReXE5+Jr0EvTtBLT1I1pWo1p6gl+cB3ECesh 2qjNtPZlWjcC/5SNmoF3yoMI5cvqa3MYn32YRpU1HQG7tXGPvp3RSk4weufhxd/OEbwJb4cji2/3 wQj4QRvUJNBurCV4ZluBtYeOtQdl7aFn7WEEvLc7ElmrSMzaMmsbRewsdkYqROYTkDFEX/PB5gvF 5cgWYrC9yFHcJyahahCJvUY+Yqb4EQUCh5iGBgFbmIfGADuIR5Hg+/egReDr09BKZvN9zOa/gAe/ i/Yzyx9glj/ILJ/ILH+IWT6JWT4ZPPtrlALePRMdBg+fh46AP9ehc8BxrNFV4DUO6DZwmQroEbAS Cb0CdmGKMsHH20AEAEgIEdIQhLQIEtXTZhlQG223DWonjZV90Tn4TEm87G/fx951+w/d/a0/IPab TIg1tT7fukh/MPzWH5Cf9jvownMENWRr9xbf7iOIE1eIa+E7k8VU6OM5kjZy4CyL8r88iQN7BkPh U3591hqAZv8CusMnizEsRAwLMcNCjmEhz7BQYFioY1hIGRbqGRYaMSwUGRZKDAtlhoUqw0JjhoUm DAvNGBaaMyy0YFhYjGGhFcNC7a0dh0EDmTTm9qM6f7kWRLCIzeApS+MK2B3XwPVwU9wWns4fB+NQ PAL4UySejufghfCtMTgOx+OdeB8+hI/iU/gCtM1NaIcn+BV+hz+BA9IRmZgRa2JHHEkFaONquAJo 7wRtUZHJLuCBNdkdezHZA9dgsif2ZrIXrslkb1yLSX/sw2QArs1kH1yHyUBcl8m+uAGTQbghkwPB q2syBLdiMkqw0iS/V7BmMkEorkk1Vy9pUjDXy5rUrdUrTCbqVSYP6Y2ZzNObMJmvN2WyQG+mSWBQ 5kzWNsbse4KxM6CRMXANAkeukHcBxqHxF8Ak0BJ6IujoBnkv7A55b1wFcn8MXAZ0qwp5H1wN8kBc HfK+uJ62/wTXh3wA9oV8IHAWAlo1hjwUN4F8CG4K+VDcHPIo3ALyFbgl5MsFC0RA32KQJwja7Euu HgwDmkKvBj15yBP1wHlAR522o0pPIc/X6yEv0BshAroBA9PXRs4wtrqBzx8Ivn4c0t4BsBCtQGtR PNqNDqKj6Ay6jG6iB+gF4EvhmiL0JGvo647Qlwy4Gq4Jvakxbon9oDV6gVYD8SZorShooc1Mdsfx TPbAW5jsibcy2QtvY9If0F2TAXgHk73xTib74F1MBuLdTPbVl9Qk6GinSdCyFJOJensmD+kdmMzT l2YyX1+GyQK9oyZB47JM1sarmP2imeVimOVWM8vFMsutYTZby2y2jlkxjlluPbPcBma5jZo99Bas xYuxFrdkLW7FWtyatXhx1uI2rMVLsBa3ZS2OEW+M2M5yjmEFYiMdG2s/E9HeJd6S7et3Qu6MB7DZ MGzJ+poV6yPW2ndrteDi30r9tZ6kYS/gyWLWV1iurdJhE0AohItBXIUZEhGGL5pftUYzcHvcEXfG nXAH3F/sBB6wy5e5aTKcTCDTySIuitvI7VQ/q3lqvloAKLtSXCVGizHiajFWXCOuBcRNEQ+LR8Sj 4jHxuHhCTFU/qETlVF4VVJ1KVb2YI34Sc8XPYp6YLxZIAHvSz9J8aYG0UFokLZaWSEulZdJeKUHa J/0i7ZcOSAelROmQdEO6Kd2W7kj3pAfSI+mJ9Ex6Ib2S3khZMpX1spEsypIsy4qsysayi+wqV5Qr yZVlg+wmu8tVZA+5qlxNri57yl5yDdlbrinXkn3k2nIdua5cT64vN5B9VVlVVFU1U81VC/WjmqN+ Ukuotqq2DlqORZ6IRZsCsK5m4NOCyUBgDmEQVcpkPESVCts3q7IY0phFhiZs/teU28HtQGa6bbrt yFyXoEtAxXQfdB+AM0K8hKy0eAm41W3xIXLWoiZgUtOBP9SQtgBzqA8RfxpqDlF/OmrB+ENLxh9a Mf7QmvGHNow/tGX8oR3jD36MP7Rn/KED4w8dGX/oJOUDc+gsmwBb8GdsYTxjCxPVYsAWJoGe+1GX v2PRf82C/4idvlpIZK2JWGsasXY0Y+1YgrWjI9O8ItO8GtO8DdPcj/Gkjl+iT0EUFDYKmyJtbrke siva/3/fi/+8P37pO1CDKespiPUUjllYx+ypMnsaM3uaMHuaMnuaMXuaM3taMHsWY/a0ZPa0Yva0 ZvYszuxpA3azQiUKn14S1CJPrwLnLRyx2phn/RSxfopZPyWsn3KFn5UF4yKftQZW8g0Fvo50hhxs FLCeLLCeTFlP1n+JpHEmzsa5hWzAlFiSEqQMceaaCAFCoNBPCBKGCcOFkaqDWkYtq5ZXnVUXtaJa WXVTPdRqqqdaQ62p+qh11HpqA7Wx2kPto/ZV+6uD1BB1iDpcHamOVsPVCHWKOl39SZ2tzlXnqwvV xepSNUpdoa5SY9RYda0ap25QN6nx6lZ1h7pL3aMmqL+oB9RDaop6RD2mnlBPqqfVs+p59aL6q3pF vaamqelqhvpSfaNmqe/U7P/Z9/k/+z7/237pYQKcv69gruaCz6/9t/a1w0jEwbqbRXYh67VdOt/2 +Pxv9ul82+EDdZBapEeRmQ7tTDNAoG/zBfid9hcrSFXiCXfUh3OtSBvSgXQm3UgfwKpQQL3x2rra j5K2llY0QS3fJ88/Jm3lrWjS1ul+mOr/LjXUVvG+S63+mLQVvaIJdPmTBP7guwQ6f586/yiB//gu QSt9n3qw9Ntxn9+lfpCC/ySF/ihJ+d8n8Frfp+K/S6W/T4X6fXleVsP/zI/8yfwIRrfBf9YEX98Y WLYfexfL1zewaG9j+QnNQ4sh+olFG9BWiH/2o2R0HCKgS+g6tJ+BrTf/n+ae/1Le6l/JfzgL8mWO RAaxWIt7UF0tFgBfZ8miB22dBWNniKMJeHvtHYmL8RIoL8XaOzZXQeRF8B78GspvcCbEK1mAJhi8 ZTaUP+Ac5jNzofwZ50O5gGh/A4kQXntnI9FBmbK/IiQRiL+JQozZrzEhxiZmRHtDXTFiCWUror33 zIaUgLItcYByaQKRG3Ek5aHsRJyhXIH9xSIX4gJlV+IK5YqkIpQrEe19ZcvJciivICugvJKshPIq rhF7n3ATxHFNBXPtra0C6CvYaH/DS2goNEKc0FjoDWV/IQjKwcIQ7V3uwkgojxImQ3mKMAXKU4Vk 7f3bQgqUD+sBmfUEokiiL2c0AGGjgUbA9IwGKRsRVjYpEPUqm5UUKB9WjkH5ODBVrNoBz+CATRaw CA9Q2ZgYO3z5nTWzDEH+hb8O/o2DYMZBMOMguMivWDHjIJhxEMw4CGYcBDMOghkHwYyDYMZBMOMg mHEQzDgIZhzkyxMSxkQwYyKYMRHMmAhmTAQzJoIZE8GMiWDGRDBjIpgxEcyYCGZMBDMmghkTwYyJ YMZEMGMimDERzJgIZkwEMyaCGRPBjIlgxkQwYyKYMRHMmAhmTAQzJoIZE8GMiWDGRDBjIpgxEcyY CGZMBDMmghkTwYyJYMZEMGMimDERzJgIZkwEMyaCGRPBjIlgxkQwYyKYMRHMmAhmTAQzJoIZE8GM iWDGRDBjIpgxEcyYCGZMBDMmghkTwYyJYMZEMGMimDERzJgIZkwEMyaCGRPBjIlgxkQwYyKYMRHM mAhmTAQzJvL1HSXf3lhSYhhIC3YWlRhgiCzRT2dUYWrjqR8UTElMZIlOcMqPYOwmGYx0govKERsB GXrrRBcd5nFkdYL5mHaGNgbXImdsY+0m2rIlpZqoFfJHw1AIgGggCoP/2hKTj8GhSGW8Ra/JPjtb 1Z6eW3Vwox66j3Oa9IhO6hQTaVnBEMmbGSLJpxiOYALgkIJm1qw53fSiT3bAi4w6BuXbk2IeninU zcXgrOPa85J56fohoaOHBvXrH2bvFOBs7+blVd2+RVDA0JBhIX3D7OuHDA2t5GZnsP1yc7Hvr4QM 7R0WFDLYzcFQSrvOmVv/dr1tSEiYfd3hYf1DhgaFjTbYWSle1Q1ubgZDdQP862KluBvc3Ku4FR7+ B54oEpcu2ixYQFwkwAqcF0kkxmgjSUwJfeSd1bKEU/SSUT0Mz2I3zi7b82P+ouZrEvJXxtr7jGsT uzx2bi/3ARfr9Rn9Kn7ESb8bWc9XTLWdGz25765jA8b4l7lasuZtYzz/yeKjSRX7RkX1L7fsQg3X JHlPp3IpDR+LPp6LXTc6eW140WRSvfuTjQ9EDWzfOz5y3OpeFUc2f7psdx/vqNa2bnpHi+iNj392 sX5Ua2mARa9OQmB0yeptp31Y/3ohOV7i16T2vrtmTEyq8cJvYcuteevHDApruc36zGIjJwfUcV6v oOoHmpnRmh0Kuuau7Svq4y5FdOj4eq93D8uIkfyN7ENbJy7K3342/Op6m6Hdap46+Ea/prRhl27K yV32I82nZBAOOv6aiA2GiHWGiFhozZKYj4gyRCyZaNL1QujroKGryrSZYLGzxZyC06uH/vvtF/kX fZzTbLjoiZQ8++0S66ov92HH6yNN33br5R69SjrtI/w8fe7JGo8cst50XOC6J6ZRqv/rz9fOeHt3 2VjNLyjfcVDtk2c23RbG3XKbXSvaJDT4QL5ZK+ug5M8X6t837WLf6pn/2G2biqe6VC9b8VDgarOf yhoHrPngZ5vjcPJqsbdt4wfXd6d5kVYfH/YbqLTJTsxseyLx8VHDZ3s3o+klFznbtLhSkqzLnHiH 29313Y5bqR1fBTY50dZv727Oyaxg3tU3+rkT9i05trm664MxDzaMvD8iBl0Irp1yqdpPd+qabaga XCI4verdy7b8gw2+fGqXKp6DW9gq/gli7Kxfr/jVbnjWtn1caLpZjWkLhkevvxQDqNDLEMk1/4IK YqXNpjdbF3RbeTr5K6aU/E+BAYx7T3f4BwjgDmDg5g6HVb+CwWiGoFCJzpy0b+dmbjDVDvTmYsfe w/oHDe4XBl9jYlC1k9Sctg3sMyhkcJ+vDyb+2YOVMTh8eTCbotf7BNq3C+o3GGq1b12/7l+iQsLo 8Ve77/L12uAR73Yjp2zVJiOTc0utOuE75PXFhk8uzzoyoHlb/3fLyJEW15sMrOzoE5h0rkyC1Dgh fPgt38RNc9XWx8q6ZMU8VsqUuljX8ZP/svPFfdctaFpq2dldlUsfaVpxXEhaMTvvWV4mXrcSnd/1 9a6I3QvyyzeO2zMQT1uRu39nQHhkTreYiMlT5mzP2rdwzXnPuNZTrMpPa3nLkI1qvTueUyvi0NSX A73WV/LI3l1pmzje/+dRfVcsHaZM3ZZ19K39L63MZgecdk1z9y3+6kDTxd6t21mf69tm9KYt01I7 +ERHtp4+WNhRNWWsY2LbvrWWtTzjMqHK4MmNdBdXXWg6lQyeitYmT8toV4gKnwwRHwzmGiiU5WWD qNODQxMEynH/b0CFsfaM5kANecHAgTCU1E6ovCVvcabkuREotOu2zBtHW0a1aVBpTYOANwZJu2zM 8zCMphYZOgxjxm7eOqFpuaxzB1uGxXYqH1Zh+K6peZubLxyFWjw99dz6ZtAxNXbcW1L/+KlpZz62 O3M4OrFDyJuABhsboFeLU6Ou2O6ToosrC6/dsNviPP71y7hh8XNve82ptTT4oOegS9O3lcnLeHo1 yOjn6Yn5d9EBj7cfxuWYmFUSnjsvXlBvgNOQBM+5d6hysnv/s4kT6w7ou+FAwoE5HqeyOJNxY95f ulMvY2z+3bvx+dkZV5RdoVfn32+11zN2XMXLtdI9JP/qJDoiuMyM7G4Bc7d3OeB1rdes9pNtqrz3 XhoTKcf2nLnLNWH1utObb9jvTTIUn2JvoVQ42PZd3Ts9DPfnOwVNSwm993b95nMT6w0doQLGBAPG tC3EmN7Go1owhsQVHUcC4Mx/cFR/BZwqBgMgThUAHIOXwV07rKIdGsL+kUcrvM79yfW/xJrYdHH2 +cMpTZaf3VTDY0uZzgPSBx5yKJ2wMPXZ1qTjV8oddjedefBGd9fcah3sirlsnavcslgz2Kl5uGXt uvGz6+xoOF1Ji1i4ZYnuQscGI7o9y/ys3gsPW1PldNjD1/d7r57AJfgWXPExu7L9VA/lwtisBHPl c69gpynDZyVsOTjlidXueYfeW+717/7SNKPGK4euM7dNHHbE9/6iGSN7LX+8ZWRK9dlVLCqbp/uf 3GqzsdXSflsu23sZhtyZ3a/hveO275TWYXUrPxEcgx0GNNk+/+hOrxP11g3qZt1089xrcyb5jBIb XV+7c3KZI/eyxvbd0TQssVzdZit6W/RqaUiNfHtBCh33qn2LkZf07UdEFGLNR0PEe9b2JY21EQuD UJdcZMC+dagzZ1ybj37Nlj60uhY8yUOoVO7Jj6FJw4mSZXhrg+XEHw/zBtoNpfhaBm+DV0z1mKpT q/QPCwutUblywNCBlQZ9tWGlgJBBlUMHBGlnK4cODekzPCBsWOX67aCjVYJThsZfvxJ4SE1DDYPn 12MDmepaWOHIkSN/VGHg0CI1hf1uADG0qdMxpF2/VfaTPLD6yKpZzS3Pr0eEv1JGh41staSR9VtU LGhCuv+82Lx+q1c8cHL+1P7asvzWST2Mdv0S9zLy7VK7kM6f3mfelX+dqfextLK/mLzHt5G+XK+O Rs0WvtGf2d9i8Jt7jc2cqs50GJrRc++2IDPHha+eehilTxgcMl9se6pC8yab3F2nPll9pnu5gwdr 3um6c5K0v6ptq8m+jQoOLFzdmW5cfGtUYsfwdetbnsnasiKq7r3T3Rx9boZ7NGqZfT517Mrne0+u CLBot21L1OtrSedjVm9edGqMyzTX5BNpnwdyN5I8t2Re7Fbcyjj5w6mJcSZ6m1vzyjzevrq5z7Pt puVGqSmuv6wdcGJuTUCblYA2U76iTZNxLxnaCP85tPELGhQ4LKz3oNCiaFPN4OVWzeBWtao7ozdu 7NDdoB0aIuL+kWcrbyj7xVHaDa4fFNo/cKh9g3a+9r7tWtZwMzTwrFjV06N6xfr1Gnp+vZEzt/sT JdoFDh0RFBD4lwD1bL8QkJo2euvkBj7rdh192XyVY4bXCDujq+5NO4265JK2js57/bhWbmK5cWty H46f4H4+rdZMr+pZH697e1henh+Z6/Gi/5ShNnPv7Gt+Z9+Ut1VEkhI7YljV5t0zE+42HV9y38JR 6QV2U4rVazjkXHj5jmYXJ7XyPv/pdvbMl7XR/Su3e+dYzW62NqLm+6A6z+7OSKKt9oeNfSo/bPRs 88DMK/0i9B8tT403PzDsnlHzT/65L2O8omrkPzdN7W3n3+m66DfpinezZvfaJ1buZTNnvlD/Rvfn kWKZJUYxglvgzAUt7eo6xM6fl+fbwDek6g7f6luCNgbmeNTfYXXY2+uuyawsm2n3/VqX8l7ptqUo QP0GSBOGvqlUu4PznbIf+u/Dn5vdnXD+vs932BPypGXtJb94bG42de7BFc/ivevWP37hv4Q9YcNC A3r/t2DP15rCfoSg+j+g8A8AKmhMpJFsefH2+YYzKiVd9BgTEV7eqW6Ft786zFeXbOnZrodzzssU v6Ybxn8wvyBZ5LTImloMDb4/qaST73pXL/dbIVHVu7wq03auHze79voVfTyzq6Va1N9bw2fpSeXI kAint33Xu93r1n1uTtu2d7s9XzBvZZBR8xkXL45o7qEE3x3XYL1L10l+4b6Oxcse/anhsbL3i08M crbItjr+prRrRMMeLu9y4o6P9CkTkhPXZ8qcWH9lY0W7DQ/n+YQXbJ/zecmLzDx+29km57qExX96 a16qhNe5NbuvHny3+1XqlqwOdrk1M1OvVmhwMGlF7fF9rc/utA8QT9WpFehefNzOfbVSyjVuWbr4 ssGzDCmZP38PUCbB0rJWyajsZtN031KdxvSL/T1M/WeCr0J0Mnh4VNfQyQsO/wPB1x+A86/w5mb1 wbnbUus1HWKdeq6xT7vkT5st9ru6HzBr1TZ10kufKmlN3OY77f25z51SrSfvP9zsYrjw8fXwQzNP bLiyNSi076jyfZ/sTXg95Zezrzblma2VOpd2rny+TloHvsSIPYP6DGrql34r83ZS9KQTEzPCm5Pq C98nr9J3sOvf6Gxa8ohulcfvLcvv7tA12DagYOK4mq+u8GVbeI38Xythjz0Uc6PNXKf0JN8rOUvO mrJ/c3Pyqh68seufPq+QL17LXyIpwWjepWY/baWYDNfue/otAgGbfm6V6s15pzpb+MdpgeutfF+a yorNjk2tWnQmge0N64Y24+0/pkS3OLZEtE7J2yCv43Emf47zg6wX9Wp92ZDypolRAxgiKthz6JDo fgmwcUIHQEUZQX0qBqTSE2vhKAnXIMLEwiPHxRDMUMqQxODM4IjaNcPo12EpoKb4ChoeqgnYLdi3 MJGdka+nwLX3fXHIXntOVt3/OwKDW2XeWk7cvjiM+17PNmvpi7/XLD+5fWOgonQ+R2ZdNvMiJbe3 OVtya5R2uF1u+dzLv4+9y+zg67qXBbGu8yddOnPubt+Bh/u1zta8ObnO6Gr7ztPJR8wuSijuL7tn PWuzdPE8xY4bW7YIhfR8mXMo1WuWhtqchC5+6+PCqRUeu8+vbbby35AUcc/g5UtL2cedn25ZNv4U VuxJaUhmY5n2aRaTs361W8eu/0w3U3963bvFXDJ5M2sez5m5dzQSazw+is8RVLRgkmlfw3Z0mtGO pw7Hgm33ruy89yLNvPeL0rQ5ZzaUhwRaXSty2aT8zbCJZT2wkFrNxMho0Ng+gL0ylL4iYox7QeMt AxF4fGswGrIzs4JXL4NSATQyOZkNeZCH1YGuQfC4DfkMkGVFDZQRGlkMgWnsbU6Rf2R3el62mA0b 19/5IimnmlYapCBp4TEMMwhZoNWgweDLkMmQzFDEkA8emU9jKGFQYAhhqGQoAPLSgeKJQFYGQ+VC tQYVnNVrSWVBfnpRYkFGpQJa8cbSxMjAnfSisaL38pw+qW9eXnNeXZ979cw89yRNpyO3HF6zhHzz Ozn14Jc//5MXvn7AUHlYebH69LQjXY6tcjEzX1ffUmV+fb7g+d5DUV4H3CIeJXwyneL261Wdqdny U6kHVldJRR3IsprHNVMkUSL26ZevDsfOKZx2cL7w75PMvoy4Oke+Ve7+jMlPzdSfXs9v89/fajed qdbSu++uRtxe8b3ePpNPKMjP/fR4/5ZVZ96GTFk64Yh4fftb6YbC7xf4DmxzfGHh//jMjqTZ95zK ambJsx9euX3HKv1ctxv32Hl7tlU+jorOPf3648tzZq93eaS9rzjxx2b+tmPCOmsELR52/Vohkcae +LC7hTE+0nO338ImJnmDJiZpRByxGTYx8QCFOOieRNFrJJQOBjs0iS6INZBATonciFkgRqCdcBlW Q35gVWthaGAErGiNLI3NojAS4marWdP9Wl8GCnN0e31ZZNWnliSdj1ZmgZKIo9NlvmlHam/rLk1k tJHkKzqvVxESna/c5vOWa2KQrlS9S+rPuQ8Xn5su7bb7Q5iJsvTG2g1ZE1gmBrd+98k6YnTKl7u4 5611HUvbhgpJqWds9k7z7zfvbbkhu1SLVSJcLeeQ+eSqe3t2rZJ6XLTv1NQ2/6JZjxZ8E9T8cs3w YN306Uwv55WWT2LYXrPZzf7U96WbbrCpeZ85nO0TMHnP94WqS6/meRa49K6sv/7qqcAZOYlFUVdK U3iKy4udVTV3Stx/0PFzu6qXIef/C0rLb2+Vm7fhl47FHm7J1hXzNm2J9A/xa53y+c7ph18s/lrE nN7jc+h2bGJrxuq2PS/TF29fWXWIdaWl6M/tujVJDACvMjtaDQplbmRzdHJlYW0NCmVuZG9iag0K MjI2IDAgb2JqDQpbIDIyMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDU1NCAwIDAg MCAwIDAgMCAwIDAgMjY0IDAgMCAwIDAgMCAwIDAgMCA1NjMgMCAwIDAgMCAwIDAgMCAwIDAgMCAw IDAgNTY4IDAgMCA0OTYgNTkzIDAgMCAwIDAgMCAwIDAgMCAwIDAgMCAwIDQ4OCAwIDQ0MSA1NTUg NDg4IDMwMyA0OTQgMCAyNzggMCAwIDAgMCA1NTggNTMxIDU1NiAwIDQxNCA0MzAgMzM4XSANCmVu ZG9iag0KMjI3IDAgb2JqDQo8PC9GaWx0ZXIvRmxhdGVEZWNvZGUvTGVuZ3RoIDk5MDIwL0xlbmd0 aDEgMjIyMDY4Pj4NCnN0cmVhbQ0KeJzsfQtYXNW18NrnnJlhGGCGGebFEDjD8AoHGGCAMMkAh2Eg BPLgmQAxCYRJAjEmxJAYHzFoQhLJQ6PGdzWtibl6ez8PRCvxWkut2miDjdra1j5MfFSrwaDV2lgD d+0zM5hoav2++39t7//NYtZjr/1ea+21zwADQAAgDgkHYqXX16R9dc1tAC/FAaiOVXrnVhyfK/0S 4MW5AOzx2b7Kqpd+9e5TwPwJy1zu7LoFjd5zr/UB/PIkMIZrZjc2exU7k9uAGbsOYONfFjQ68xtc j68AIMdxlvbOKzp6pj3H/xWgTMLxfJ2benmWNd6FVV0AEfev7Fl1xR8SmzcBeD8BiGpa1bGhByKA x/lF7B+1as3VK73FuqcBuiNw0QVdKzr8H+wQj+L4uB4o6kKF/hnTf2F5O5ZTuq7o3XyZQo1zMxkA JbsuX3HlWtvDSYsAjv4O25SuWdfZ8ef3/optt3iw+8ErOjb3pKbGHsK6/8D+/NqOK1Z8747GGoDH EwCMbM+6Db2TO6AX18PT+p4rV/Q8yo+huKAaIDYJqC0Vn/5k/fMxW5ZpPZ+CDZeJcOyPd5VQ/tOq rms/KThTa/rIchaLamAgANhPdc+EG8Dc9knB+UOmj+SRLgB2I9XYFkAT+okCAzpwwkocZDHOKzfh zpBbQAERinsULizfF+DkM1hJJhgtwylYBadkGe4UMJMicJOhsec18jxQ+x5UuifcpEN1D/kpD+QB edCnFM10p8AqfPC0vNSfBDAEXB9cBd8ClDtg41Sf3XD11M7+Cj3c0+D9NmOE4d8D2PegTuY7oZvr gW72Xehi1sAC9hMoo3rGDY1f7cNdBY1cGbbfAHPkvgugke2BpczjkPpPXXwYwhCGMPwfBiYBHvma bg6M/AuWEoYwhCEM/2eBTYX9/+o1/LOBWwtD/+o1hCEMYQhDGMIQhjCEIQxhCEMYwhCGMIQhDGEI QxjCEIYwhCEMYQhDGMIQhjCEIQxhCEMYwhCGMIQhDGEIQxjC8P85sEFMCH5K/EksocQ8BBzcj+Vk 4FGiny1XQzSW8mAmVMA8qIMm6IBV0A090AsHJwOfAKdt+AvaNGKbTmyzFq6U25DJzyf/ghN6ycOT Pwl84ZjBr8nOqU+qJ3zTisl7bBEoyRm59LVPtwf3cyH/BxaQx/umBhu+qiFvfa2R8hIddTI1yNQE 5r87wTbEftgBO2EX3ITy7qmaW2A/3Ir8djgAd3zTGv/N4NtZ/tvCv3Ukim0r/MuWLrlscVtrS3NT w7y5tTVzqmdX+Sq85WJZaYln1kx38YyiwgJXfl6uMyc7S8icnpGelpriSLbzSYnTEmzxVovZZIwz 6GN12pjoKE2kOkKlVHAsQyCLWCRLRUvlasla0S5FOXwOHS9FzR+f55RAb7M7YnmXszU72EpSCBIY aqW4upZBEItbJaXw1SbzJTZV97EdO8+z8ZUSl4ovR02HX8poaLE7dK/ZpupbsY8UX9Fit9skJhVf c7AKXzUdvF/S1aHebgto5khQ10JxePLNYlRCsb0VaUOLlBgqtrZeapHHACZHvrLM+WRANxhlrfBJ EDcIUW9KYKTNxotBAo+UIeBCdCjJo4FTInEfS8QgEeM8XPLFU9Bup4ovYYNK/2pHpb8bLepv/9Km 4wGL2vkBfqChJdaForzoWul4fcugJrLCUbEiEhUgK2AwUoMaDVXgED2DJKqUyAITVTlzkIGIaDSf ni63kuJqSdzdjoLDh3bDGsOXNcOTI3surALsFpIMASmwCElZIakCi+C7JbFDgt38YNbIwJ5hHSxv F6L8Dn/HZS0S24ENBoFNrexqkhJq69pQhVMhtnfx1N0+mVDn8ZVd/ACWadt2pA4fdfpFen/XinYa JqTd4cM6dUXLTvuITdIjr5RiBSkam0Vf87aNHai0dPO0ODCwk5cO4nIvqLVTikFgwaUPVDpwNhys crWXusQ55TY5Guf4ZeeIuzt4qW/56kDsdewJxb99QCdF/cWO3kH/YE+5Y9CU/vbVdMmrO+g2K1fz A7tXyFvdI28N45WvXO2jSDti9EMz9m5rqexyVH45IW4cBTb1q33tdskq0I4DA5V0iR1+XH1gyVjx 5frpmbAJBNdTIYlNMoMm2Qc4o9jhaw2qgg3aaDda0+5rbbUH/I5NJVXqTkWOgx+gI6pSpThBZ38W 60ays2obWip9Nnn3ElPRUjJmsY2hXFs3pSYWbDPgHLMFbFTb6KitD0RBV4i0NwUOMDPleWwabC+P OmqxjQbky1qqHFXtAwNVDr5qoH2gY3iyb7mD1zkGBqOiBnoq23n5+BPUP7nbJlXtaZV07V1kpuwh OhxPY6+qoVYy1C+mrqriuzoCiaPMYS+22WOn2tT9vergmcPoxzNAz9yA7gyuLQqzk42voqlmGDOE TdIV0yOLC2puwTPRKcevTPCsNOLgNnpq2NbUyu7GoLEwMoPBQ3NgfVCLg9jt9DztHhZhORakvvqW QJmH5bYhEJ0C+rGd1oyEaozNtKYvVDPVvd2BfrPUNv6D+L4wtgdiHXre7ZTtL6devzTShHv8a7EU URx0vaGihbUxQYmxsVSKFDCVeSSzIHekNsGMOaBz8Ccdkk6QFBUtIzZPK6+LxVRHsE21QE8QZtST jhcIzaMQp5OIRyImqgfMq3J6Z83FWDkVSHzlQHsw0i7cVvAy8Hddem/YRufA7dkC7WP1DrrDE3J6 C2bt1Cp6rmz2QIuaVimG5mYp5oxMcL22ihYeMxGe3HpZ4Cv5LupsiW/3ySmh1XahenjyVLuPpkBc Mm1iC4Y40oBpL4617KxvG+h9GOg37GntmomjiJm4A74Qp5VPS1NL0ErFtuCJonPNoVu5uH7KiqE2 6Hw8eHYpN/4FCwZqvGWs9VImr226qHTBZHJd8VRmaGqRqoTQ4IHybMF2YbH6K9VzQtWYPrbYrqHX CAPeQQfZVT8okl2NbS3HdAD8rqaWIYYwFe3e1sEUrGs5xgOIspahWqqkBZ4WoJbgaENMhNzedkwE 6JNrOVkhlzuHCci6iJCOQOcwE9DpQjoGdVxAJ8q6wFNFpaULTdDiQKf7JbGu5brWroH2VmpsMAUC ECPbUQoS4ygdJIwySop0rPBKGoeX6suoviygV1K9yuHF8MfDwdOjPtDuwOOPCbgFbKSVhjANFyaV H56cxAw6ipnXLilTL0PEBKsWWnmM4hpsN5tiO6pnS32dHXQdNExZmsvndLZKEVMDYpM5khpHUAdH wBZVch96C2CnTgzWDocsohoPR1+r1CrQSVu66QA8j89D1Y6ZkjItMKYijU7kbB3QO/Ll60SZKkWm 7qRMjWujiVDW2LCIk7UGjKSKwpV3OrCqs51Ha3PQ2YjByKXRV6QtoFmBtzqXtkLGSFuwEgInSBMd Kalz6F2lkmVNDg6IL1Vra2DxcmlnsAHOrZM0uKK0C0wZ7IDWwao5dC342olLpU1/TIepH4YGx2Y8 g3TR8kgqrJaiU+d0YMIJ9NegxlEc6oxjRcgqOsazAa2K7jxKfqBtGp484rjafgFkZznwdm6hgQk2 fIYUoXXgqwppMSbOiK9qo2X1wEBE9KU7BOwVET3FqZKv7MZYBR7vFDSjMm1Ox+5ifUH2MeDJxGNq C6nhh8nnIeFcSPhrSPgsJPwlJIyHhLMh4cOQMBYSzoSED0LCH0PCOyHh7ZDwVkh4MyScDgmnQsKr IeGVkPBySPh5SHgpJIyGhBMh4WBIuDkk7AsJAyFhV0jYGRJ2hITFIaEtJLSGhJaQ0BQS6kLC3JBQ GxJqQkJRSMgNCc6QkB0SskKCOiSoQoJCnJSlT2T6sUw/kum4TM/KdEymZ2T6vkzfkenbMn1Lpqdl +geZvi7TX8v0VZmOyvSETF+U6QsyPS7T52X6rEyfkemITH8k0x/K9KhMB2X6qEwPy/SQTA/KdJ9M 98p0j0x3y3RApjfJtF+m22W6DalYWsP3yaWtMr1epltkulym9TKtk2m1TL0yjaFUW97JlUMSohOx DHEB4jLEdYhbEW9GfADxUcQfIf4cMRqWse/j1dHHfgK3IB5ElBBHEE8inkIcR4zAUV04qgtHdeGo LhzVhaO6cFQXjurCUV04qgsicQ0F2LoAWxdg6wJsXYCtC7B1AahwVge8gXgWkQUt0iTEMsRliA9w DtGhGH+TSOdHzjMj50+eP3V+/DwXYOzI5MnJU5Pjk1xPeSSXisseQXoS8RTiOJcqRnGnnh5/mpGJ tjyWs+PAdvqXGpkWbK1FegqRwWkjaZmLeIxo04i23Map5LIS6VbGLLe9D5IQnYhliAsQlyEq4Q2k ZxEnmfvERvaNUyZzwi9+ieTa60y2a6+zvvwKypuuQnJFD5I165BcvtZku3zt1ivjezfGGRNWrUay shvJiq4424qu/vXx1g2mayqs9qsRreV5zK1wNyIDCUizqMTczdzD3AtRzF5mH3Mz8gFmN7MHosDG 3A27EXFLSB9A/G/E3yJyzGFscwSimQew73eR34d974foyfeYfUNxDvcxFO6hQnk8cyOzBV0sMDcw 14EC+fXMNXh3CcyWIL+GWSTrr2JWyXwVs2hIIfDDTM+QjXf/kLkS62m7tajnqH7R0TyXW11ezqwH K+IjWD8st+nG0usovYfIMtuZq9GiAtOHnPbfipyu49ogv5pZKNdvZlbixSAwm5BT/cYg3xDkK4Pt epGDrA/wdczCIZUwvbwOywR2UMosYZYyy9CE9UwD04h8PrOAqUNTapj5iPUQySyBWSi3orwJcSOW 78Xy48h/gzyS6cYel6NBO3GkFcjbcaTlyLvBw3QitiMuQaxHnI/oYzyy1SqYWHSUgI9igXIplumu S5hYtFpVuRH1BKqQPo/IMLOwXoX1buR0dzOC7e3YXkWt7BoymNzlJsYZrMgJ8mzkdIKsYFkI8kzs qBBml3uxTECB9LC8pFmMC2oR/VjqpW0ZL6OTpy5HTkcqQ06XPjOoLw7yoiAvDHI+yAuC/fKCPDeo nx7kGYwOtzBQvhbLBOKRHmPycctmxsJY0SkaJoqJRh7BqJlI2TkRiBo0vhlXG4HO0aBzNOgcMzon Ap1jRudEYL0De6SiM6bhSEnI43GkBOQOdMQ0xHhEM6IGMQI8pJHMozsj84N8IbmM2oo0B/ki5FT/ OvkF5jaB/DrI3yGn6M7I6SA/RT6Q+VnktP0Z8gHaWsTnhSF1JB62EcIN5eUFBTw0w5Mjj/00iXdj C3YoK8v9JGEJmmIoKdlxjIpHRxITHSHltGkhZULClNJmCynj4oNSn8YQlER1JEoMIUfFut0oEapD qTwSlQALIImqKMcFwVBds7wyOOpw0BXBE9MS3eJ7Npu8zHdTUt0Lh0mEaCC//7VCmPVa7WuMKGmi 3T8eUQjYQJzxgMHgFu9z5rrvu4cI996jEO7ZzwkP380Jd9/KCuJzWXnuW/ezwq79d+1n1J2Wzp92 snxntBYHH39sdlKq+2fDJFJMIHcdIMKM+8kdBxjBcmdaptt8J9EdKBPdvzlAniJFJAvvC4HkDo1y Aj5cDJ2gLHtolEWWRZVPkbmkRm5TM7RVIRwji0kTnittuZU04XabgCE7yC7ZOTuRU+feFOS7yM1y x33Iafnmo/0Koaw8ihwEQl4iJ+TKV5DjMSQvkxNDSupZ1VB+vpuyR1lqhqN/SJTdKsb+zhLvfuFF VnjxOCeIx+3JVHv0uNEs8+fRmjI3xcutHT/KznPX1aOd6tHe7+C23n4LC29lZrpHT2AEnfD65PYn 0tMpf+KEOd79zPsEd60eel2eWHS9n5rqfuN9Ij5rm+Y+OqgQBtEx4khJiXvkUU549VGF8OgWTNev 603u535I+H1Et4/QIXcXFctD704X5KXk78ax9+xVCHsHOOGmAYUwgHb85CwrfHxWIXzUxwjjBznh LJpGPJNf4BbP4Gy0+8H6hgCvnB3gxR55OM1BdPwbB8lB7En1t2P8U/0v+tA+N2wlwvW4qi04xRji r7eSrf2pSbv6ibATcTvOsg1xer+7f04/u7KfVPWTon6S1k9sM4yWIqOx0KgvMGpdxqh8ozrPqMw1 sk4j5BjPfa7lz+WeY9LSYzLStZlCTJagTXbEpDi0iUkxfJIWFDoF4ymJ0Xh6PXd7WK0uNkodqYlS qiKiWE4RhRdElJL1J/VkEm0m0WhrtZgpZoGP7WX/E36rVWpAw2q0s2CWupVdrN7E3gv3qu/W/gai jhENiRIztTYyLdqiio826szRei4u2nlu3bkHzh089/NzJ88py86J5x49J507dU4Bw0Qz5DznfJJo oIxoxBzub55zns88n3qyPJmeDE+aJ8WT7OE9iR6bx+IxevQerUftUXpYD3jqXE1E0tdCbZNXMhDk jV7JJdQOs3yDlC/USuq6xS2DhOxrRa3E7MLz3CRxu4YZZPqKtsUtw8RKq/vxnRYmAam2vX9vqyBM k/z0W1N901qlfCrcMq0VaqX8esnm8AqXgg29G0N8Q29QhV8yDGakVUqZlR1SVmW7TwhpZSAbEALt g72m+AWAY07Nc8nZL6yijMgS9NLBeqmmt/eihpeYg7b/OyV5xA0X94HQhoNNer9dn6+tuTfUTrJI Zei7rzYYVFMn1jV46XeSayV/Q62UWLe4XYp3eGul41gqqlssRTm8OPaGAPTS18YN1BFB3SAwFU2D DCVKJIsXt5R3kgnwk88RzyH+FfEzxL8gjiOeRfwQcQzxDOIHiH9EfAfxbcS3EN9EPI14CvFVxFcQ X0b8OeJLiKOIJxAPIt6MuA9xAHEX4k7EHYiLEdsQWxFbEJsQ6xDnItYi1iAWIeYiOhGzEbMQ1Ygq RIXY7f/E/7H/I/+4/6x/zH/G/77/Hf/b/rf8p/1/8L/u/7X/Vf+o/4T/Rf8L/uP+5/3P+p/xj/h/ 5P+h/6h/0P+o/7D/kP+gf59/r3+Pf7d/wH+Tv9+/3b/N3+ff6r/ev8W/3F/vr/NX+73+GP8lI+b/ ObT+c6YBxV58cAFFM+hACP6I2Bz8aTv9sexTARnfXn2H0pB+ouFLGXsPQjRbAtF0FMY4Oc6cAt3k wQtbXOIHvqdCs0QEUf4D+l7YEmzQOcV7ZL7wm0aDZ76x9tLwErwA/y3/xgDAU3AUvh/Ufx8eh34c 8SnYLJdb8YFoOxwE+lf+N0MbzIFmWArdWLMeDsHhYK/l0A55+AVQihYdCGpfhPfgB+QLbHfv1+a/ DWe5EoZxpnuhBscrhf2429vhP+EBqIUdF/39y9dkeorpgNWwAY6AhH390CVr58ENUA2X4dqq0Err YS3O3gaPwmOwAgbhbtQ/BQ1wv/JpiGB6qacm/8zMnPyz/LsRd+C7oxuYfWwf9MJ1cD/8AfAtP9w8 8cw3e+9bwC1wF+5iO+xDn7axJWwd2z7l238ET6C9foy22YxeeQj9cT/cQlLhHtgJW0gUfAeeIvn/ 678O+gTswbEvhp/AMbTbYfTvPrTYBvTLf+Dq677alWSQSIyb1dBGYuBzWPa/XMmloQdjYTNG3I04 z5W48xZYidG1EXkX4tT/bMBH4FLYhV5/EJPi26j3wvWwltgxVT4Pu4gFrsH230Ht7fAkycW2G+Ax kgHncPzFuMuvAeYDXTAfAD2XxITnBM8m+zkts++H8kGIkhQ4fmE+IA4SjfH2BDyC838P7iU2wsKn cBomiJMkoOemw8uIz6PdnoQfo/3OYAsL/Ip8/XePvrYW7LFbsYIL1n59LRjtey/KTTfgSbkPz9cW jKHH8Kz/GG6FHyDfg6WDeILuhP/CGHgIY6kP1/rlvG3gQrqKUtkGMRgZMDXvCNVPvjw5Ks87Guo1 sW9K/iWe5t/iea4L/E+FMIThnwWM6ou3FG8wcxRaBZn8gHtExU0sJp9ixWE88bchvRa/Vl26L3ue fU/x6OSHiicnvIpYRcrE+onr8C77FfwGfg7PwVvwKkb2i/Aum8s+x55mP+baOaViVPE9eJzLgau+ /lt13Fqui6vnDnFtXI4iHcsJeFc1wCK8q9rxvrwc8xooblHlcbcqFir87Mfs54q7sNsazHs7MDfd hpmMHrunkexQNEEGZEEuFECtmGp0FmRMz4KsaZq8nIIsTU6OJquAKyyC6UKuS28wxFgsOXkslI3m O/FV9vvXRvNj9cTsdiLoRnWjsS7daL7u98/n5ZLCglJmRilbWJDmSI5hVI7CoiJXfiJjjMNCDGs0 mo2OQhJrj6XIzFCaMlPMaTZteSmfm2JVt3tuqqjqLE3Qpniy+DSjSn8L+eK8ku34opi8azKlZham W50ut6O2IS4lP/HGxJxprqrpaaUlVdn2rPSMBOXa73534m3unr+t5D77/Pu4QSBw1eQ4p1esAB7W ibo4XYyxOk6rX6Zfp2f1ZhieHBdzUYVermPamZMMp2aZRHMMG7NfNBsSlaxyfyKXSJRKJpIYDjF6 fXLk9fHO03q303UaDeDGF5SNCWApi6dU9+yypUvcgu5ZJGiJWEcO40hW4tb1Jld+UdEMV6xS6UiG 2AJ9iivfxOk7LTXLK1d997K5t69p6JrNdy59btPExBc7ifIHi+9RFE98sGhV1k0TYz95duKDvc6V nRNvWq2khTS/RvDtKO4MbywlfUIsgpXirAKrqNZXW62uVE1MOpuSmvKQLzoV8lx5D/kKzTbWxVot BRYtmVdQkKQcM5kLWb2+ON7mYpP6BOdpcz7uyOyi+xJcLigzu4RYcFmclJlduEkL6nFD6L7YuETG bLQXljKFuI0ZDrydHCb9xeocJr3QTohdGZ2VbtaojdNzJpa5s3RqZexE74aJW2IVall3W2lmdKQ5 LYesIMvIjaRBkaIx2b2VXzxQUZpiicrLi0mpqidb7ySF7i/s7NmSiZGHJ24NVunSq2vYjsoyhzE6 7wsXOwoM/T9LXDFaIxGfun1iagLP8vvFhASDShGhinjIpzLoH/IZprPT9xtY8/UpKdlJsDXKiU50 O09TF6L3nHTT8mbRmXm5qV/bUr6JBrEjOb2QerOwgHpXRR6OtuXkTcwJbWb8/Xeqtz/Wua6kd/1t 83Pqe7yd+ednVU03ay5e9dEnuh5ancM1zrpp/cINVdM49GfP5Dh7ACM1F/pFrZNGqjPbSX/XU8OZ aKB6UGMyYJRZeEufhYthLZYETUoKl5DNsdx+MdtgSGAT9hs4y6EFZmI2Z/BjWm1uxphKlQ+HcuWg lRF3vOT0l1Ebqwd3rIvuGmNX78Yy1utp/BoSGdwnnuO09BymsIAeY5M5GNNKY5zJZA6cajRI7C/i fGuaN24p2HT1xl0V3T/bNnf/FZ3mqqW15as8rjWr+/Yu8G58sOM7o2RGy8q8azbWrmzzzFx347ye w226hImPW5an53ZUzF7eVCCu3bu0e//i6YVET8+uF316HfqUh2YxW6uPRRfGstokEs0mJcWqrWBl rftFYJlDbExkksWbdIjn7ZFbLZZke2xotwLRfXw6uFMIbdMluxp3aMftsA7HVPRyhbGBpOXlZi43 CbkzZmyVvTsDM41Bc72zpEAwdCqaJw4t9BeYvoCgX1U6c0qphwO9u7sOI7EO/ShhTKZBPvzxGJDJ 9x7T6vCN9/Dke2IklZgcMo3LGJ48JfrU2uoMjSadTb9D7NH0aSTNiIYDjU5Tp7lFc1CjiGI1Gmsu yeFy2Jz7Rc6UmnLEl2rkDbmGgwbJwOUiYQz0e33p6VnVnCEOS9Zo4zRjtpFVs0adVcfq7rLqDHFx EYn9RJPG5tNJ1ZgG8vMLMvsjsHQUCxFOQT76gQwwSmMDzYN2woS2XliyvkyYMmDIgusDRQHFvFxB SE2niS0trbAgJZUGDEYIJv5SjB+TieYGFq3LBoJGPjrMg9pFdy+c21uKj9X2jIXV85dZtrX39Xk7 N3uYyLj0rIkPo372Yk5Vrm9d6c1ca82sy6tufSC6vGtzcUPDjflOW9mN2yYO1ZQUJJmi8shxpqvb 7bV6V+ZjxHSj7RvQ9na4SvTx+HjOSISQpD7DbB70Oj2vZ9VJeqLVEyurF9OmV+u1Fi2rvVO0mJIw 2R8Qk3Q6XaSeNxgcDCGOyG02+byMolniraN07xDI9MF8/xo1wJVLl8Rbx+ItutEl6zFJGqdOiHx+ ZuBtgqYJnh+2Zmtsvjevak2ZZWb77MqrRLdrfusi1w+P97y4vWE3e/jl8trEtuH+5r3+4iKft7hk uuFvY7e/c52B/h883BsnKO6EZMz4q8Sc2Ed0Ou0Rn87oinNanKyTbiJ5elIS5ji6D5XyiE8FESSy Xx+XzDpokFDHOxzFWXRXQX9DWdkFeWDKyxaq1b2DuynIYdML8eKST4jKMSOdnve0qWyA1bhX9Ksr Hw8Py7HR5nTXx7OUcULRGU+UtmxJt+fQUO9z13rXuGPsxRXOvh1re7JmFs+0xXBl7XMLE/Xqgsi/ XTO/IsOqKYg8xFVUZJz74NA7PUbLxOD8pWJW3OjIyHGtfWZuaR61QBd693b0rhX9u1n08gZToj2W jb1DtNs1JpjNv2E9a2XAqrPy1nErXuVWE2diTXfiwdEksokHRA3WmPVg1+u2xcc79NtVsh0+0rtf i3Wjf0NuDTlXjnPrWOhKoBZy471wgQXQKPZgUM9gZber2D7x8r55L71y+fM3rNjX7GTPDxRe3dGw rfxyZWaTb9W1mkcq5gqffXTg7evEdQ/v0m/67uKSStK85qY5h++mGW8BbvNdxX34XLZG5CNVEaoj vgijTo9uNpEPBS3wOp7nR/iTvCKa5alPLcmp1fw0cVoKm3LHNPrZGPthXmD6LVr6kwAdmafFm/uj /F/Qfco5n4YpDdqyMVc+3WogEZIvUyCLKRATIT7BufLxUY2eZfrU5mI6z0Zbp2dPrMpKM0ZenWY1 x0Zz6pKN/W0LZnQaXDn27DRb9Fl20fkHK3wOY2ReXpQpWaxklriUqph4V84Vu9rTNY/PytOnicvm dtPPYJRNlLNvoi/zoRwaYVxc5LU3pKdHRjgjitiIAyNFRFuUVOQsYtVFRU5tA2kQQUeMmD21uiSd U3dWN6lTOFidzllNcAgWPhTztdZqtvqAaE1wlrFlB5y69Mio5Lkp1EjT0RApKYl2r3duJa8zkLmV iYlNjDojj8uctV2hw2OhUBjxLWjzXJofNVpsMddobHZtz5QDZFRAQm8UTJNmN80HQizemShgxWh+ /oWPgMETFBvKk5gbRvE6daIYjCCswigi6SpMjXGYNdMDaVFOlXE0jcqX7QyaTAOUplGznchnjAlm V4MycOiCjyGOZPbNY+qklBeONXrmTqvwja/e4V5zYteKI1eVN81zFon11bXuFQN11bPJ8vM1K9td 1dnG/IXFy/xWl+vm29pu8MWkV888UM8uUmmSLi99cNA4szg1TeddV7P0tgaLe0lV2ap0Q02+e1lJ 5i2XLdzaOD124uSWXem+1ryWTTOu/2IsrbmorTm3zZNQmGnFU9qIgfwnhQ+dYoWFYqaZs3JHfFZj KF9pmc4elmjZN1hGyy5DxrJkG2PoZyKD11FkMHQjnYLw7GndaXAuWb9kLJCRQvGK7yFYGqrygxlN T/g0YrSTrcMr0+3maM6Sl/2nEl22a2KzwvfMM5+PRel5bxV5TJzvNEcUqs8XLqxwROfR84Zr5Zzs CfDAJrEkh0ZCdgaSLEoESqwJHpYhzBFfPDFOfyQjI/2IL0Obpdfm0msjV1fUHxFRmpUZ1588PHmS Lj6Z/iRXF0vmJuPqT+fTB+vTwQs1lFXLAo/V9N4UBHvgyBXkcPTBwxjcSOEFe1OZaQAkBh+9OefE pvRkc3SEwZaam55e1ZQmbzO06/dLNDE1i5cUFDWXZxoj4tKcebj1Ch9RVl05Z/q02KS5NbkTu+Xd 511skwe5WtFhLZi3pnFiZ2UpThC8cdjX8IxGQwLMEZMAc+0BEUyqeDb+gEpn0mnIPNO2SD4KfRWZ GIPPqI+jJmYbSx2JShYPjCAfG+HLI5KXq5i6P2i8XxzXTNzJ32443vfa79a+OLFr2zUVS2fFl/dU X32D7tPxw2+vO/enh95eTz5/6ffla/cvuO2Zxa/gGudMNHAa9GAGFEOfmKlWyhefDdJy0vCh6YCY ZiqKdyW5WNedeCmaH8FDdsRn0iZvywtGWx5NENEYbnl5M8ESzxb3a+W7kuZOGg9a6kf5DRJyCHpw 6pqcujgDcZlqvCCNBq9O9B8b3CveG2zgqaBQJ7ub9KjNQu5EV0q2JYKLMqdnf1ASrS2tnjc74/Cg /0fbazbnW0oafVdf805xfZ098dVyMdWCqTXSOL1qJttWXZIRr1dT15W503SffXj49HorWdbeVc6/ 8CzZ5Zg/JzMY4Ww2+jAd/GKiyWqxHvFZ/oe9s4GOqjoX9j6ZZP4ygZBMwgSRjhiRIgKCpREpBoiI FS1StNYqZJJMyIQkM85MSFCECIEERRt+RaT+VEVFKtT/S22NSCm2GG1tMbbIBbRALUagNtKKnPvs fc5MZoB2edf3feve9a2Zdz3n7LP/3r3fvfe79wkhkyfPkYM2XtC7t+YS9mx7mttiz2hyyZeMnOz8 yRw7XRnZDrv96xdqOYsHmDN7wHA5n/uoA+JbF4mL5E6Ch+szatQVf07YSdRsjW0cZ53QWrDXN2fU Xjlm+G2e0cMLr5pQgPM7VTvoPI/LmMGWfMvEa4dYD46+ZMjUSSNO/fgHV3odydP1Uqfs2Qxmp5Oe XSIeKM4f3u+Kft/pZ3mtnyb6ZffzMkP7DTpX/ut78eSc/MnDOQRqGYNcc1xLXGkXuL7hSrMIV7ar 2DXVVerKcGS4zh2Wd67l3NXFefnDMiwZq4dl93uioGDISO0JgX0WDxw4yr54SPz1aX+f2KruOTph iZm33mq8SN1qvETdGpYbqzoVJL0tDeL9MT8+6RPerdL00vyxU745deagqf7K4BWjy1qmTn/omrJz qm8tvHK0d/D06h/UXfH9p26bcMetafvHXtn/mvHDxl560dBvl5V8p6ZkQIH7t7d8t/f5Yy8eVfyN iwdNLps4bW5xVq600wX60bRt6c+zhm8svqRvtsXtzS0eNHxybrGr9+Tc7Pv75qc5e1s1l8VqK3aK J0vOcXbZeue6HY4BtozMxf2G779MDvpu+Vow0jg/yFG/7Iovd190EYcm+aI4zvLNUXnn5Z3XJ3bk VVOdg8QFI8ed7868T5t46ufZQ4uGDp408OKrFpTcNX+V5W774Ctm/uBz/6mJvsj4/ud9bfSV4x54 LO0i6XU20uiwpYX9wyZGFX8tbYuwZFu8lqmWNktGb4vFtqXYqqVlbLbaHdbNg0fwgrd/1EghT2hy w/3E2Bxy5Q+Zwjt37rS0fPzxl77Dh6m3nXpX8jYp6x1a3C9NVsTmI9K0wWPEu5YJSVUe3y8Hd3i/ Lzuo0HK+RVW4crzvkjd3Ztxw8hrLi1+spFJqXW7ZnraBU7msdXBxnlVo2fL3gezyNx03W9I322wO u5ovv2fGSDdy6yijxvNAm14c6JeWd0V1Qcb9py7W3pXI3zlizXZk+EU/Ma54QE5+Xl5fu9VhdzxQ Yu+b3lf0ys93WIVD3N2rV/9zVNU7snf0GTVc/TCq54cYo+Qpw3j1Mlafeiu7UBtlzUt7Oeu8cTOu /fLc4MyRffuf453zvaHa779p1TLGXH5BXmba1Vdn9Bk4bpLlosEXTBhzrda3VH4H55wE+fBM0aqV /EZK2vS0zf9/iqUW+VP6LelvZUywDkcWx8TmtlXaum3d9nL7547vpCQl/yvljrhsSElK/pfKO/9T 4uyXkpSkJCUpSUlKUpKSlKQkJSlJSUpSkpKUpCQlKUlJSlKSkpSkJCUpSUlKUpKSlKQkJSlJSUpS kpKUpCQlKUlJSv5fiZD/z1FoY4T8YwDtIkPUCKuw6p9xzdf/JnLFIr2T62L9j1yXqGuLui7VP+a6 XIVX68fkN2Hqh0Rfyn7EdZFeynWxfjPXJeraoq6t+gGuS/Uo1zZ9K9flKn6F/hrXVSpmtT5f9NU+ 1DvEIstofbtoUddW6jzMdTFaWqlTXlvUdal+hOtyFZYtadUOi42i1TKa61JKfSraVA3L1XWFuq4i /gOui2nPKmqT1xZ1Xaof57qc8BpSu7guUdcWdV1K/WtI7dI+pJ5O9afFhqeNMf/IWFba2vgfHOsl atST8Z2ZFZZ0M6yJXpYqM5wmejnDIvZtrSOcTWY4PSFPhvA4t5hha0K8TfzTudMM28WQzHFm2CEm ZW4zw06bM54/U9zospthlxjsmmGGY222xNsc++uHI11LzLAmbK5XzHCasGV/ywxbhCe7xAynJ+TJ EK7sW8ywNSHeJu7MrjLDdpGX/ZgZdojzs/9shp2WxfH8meKiPnYz7BLuPqPMcJY2pc9VZriXGJ2z Un67bbrDtLMRNuxshA07G2HDzkY4PSGPYWcjbE2IN+xshA07G2HDzkbYsLMRNuxshA07G+EsczbI sGHn74ugqBdeUSt8Yi73ehER8q+tRUWVCBD2ikpy1PHsJYd8DpEeJn+AuCjhCuLKVFlZRpa9Utwg pojxZtlwQkqIpyAl6kW5qlF+Z6pXNChd5VzPrtd4lnnL8Qz1lDe0RsnhJSTTQ6QYPfCRr8LUFTBr KDfr8qvrMGJO77dMr1GhwZT6Onc/aWVxTWdrVd0ZNX91G/XUXqFqmkVcmOcIOcLKGlGusu6z993Q fma7Lk+wgOyJ0Zeo0hdSo+FT9Rt9rSCmQfU8SPy/6qlhZ1+STf1qXIPm1eiVEa7nKaSuXtXaOao3 /ng9MmcNOf79CFUpy4XEGDEcaVAyTFm0XM2hCFSqnLJkLXmi9Ej2cJbqY4ga5hIb60WEsGxNJWn1 6JclfWreNIqn0T9SjEAuI3TtGTq8YqLqacx+sZGR82g8ddVwn0bcLNXqiHryq3UUpvdyvIZRg0+N uOyxT1nBmClyDvjVWFaoMrKWOnOMK+P2rRMXk1auZoiRW4Z8CXMnNuaGjeV4BsVsQrNUqMJcZUbZ xFGsUGVlHyNqLRi9ke24XbVH9vFqlR5r8RzVr7lqDs8xa5R2jH0HcmJrjPVu2K1nPss6S5QdZqkY n9IZK2PUH1WjYKRIzQHialT9ftWKWG7DygFsZcSG1UwLqzlmjNQcFZ6r8kZVe2Qbh8b9To0qUaXa KHttzBefaYez1Z5oqVg7AvHZ2zMKxpoz7GbYs6cNs00vUBcfw4hqty9hLUVV2TqzVExT0FxbRr5a 1cYa1UvDstPjKzg2zuXq+6uNfhoptWp2y1rq1Oo1VqiP2RjLVSd6fFXAtIfMFYnPpHB8n/CbM65B xZar/vrVmq5SNvMpbybTkq1Yjz65FyR6tIhaxzUJ/qJMhX0JfQ4o65SZ3jLmc/2qVK3pQSLKUpWq tXJkK1hBATVus+KW+l58RZy+Og0rGXth4kosV54l0TPH1k5svUitc8zxkz7Fq2a/MTuGJtirZ8aE admZljpzTUXUHJW+qyJulYgaFcPvGHM8rFpcr8YzseU91jJ2GcMH9swY/2keyLBBnbhQlalWtoiK 5Hl+uoZ6VdpYoRFzdykntmdMxiRok+2YpdrhU+Ub1MgafTmbf/TjqZM1N6iZWWXuTUY9s0y7+FUt xgyoNVdVoteQdvWrtWHkn6vGP0gtyTa5yvS5sxNKTyS3sYcaa+KrefN6s+XGPKpRKzC2DkLmXhFQ ZYKqBqPtPnMsYnOlLmH/MXxUVK3c2ngJaaeQ6UMjcT9n7OABNRY9HipmJ2NHCqgxDprnD6N22fqG JA/kU6sptl5rzZkUiO9QAbVCvOZ+fPq8Gqb2xp5xP3O3HXPGehwjYvvzaHGj6UdiVvoGNV5G/NlX sN+cIYbVffFZZ/TUb64Wr/LJPtXOWtWq2SJ2tvH9y1Rp669+Vjjdp97AUyC+A39XWTeatLcNP8vp qlx5gDrzjGj4sWtV/cEEe19t+rnTd+PpynMGVcjIa/jG2cq3/N85b0n/1XPmOnutPelmbU97R44Y cZn32kB5OBgJVka9E4PhUDDsiwaCdcO842tqvNMCs6qiEe80f8QfnuOvGDbRV1sWDvi8Vb6It8zv r/NW+COBWXX+Cm9lMOwN1l0cKQ/L6LDfVxGom+X11VV4o0FvTTA42zsrGKzwNlSRGgoH6qKU8UW9 kVofaiKB2/2RYd6ro6riOf7wXK9/DhkjIV95rJpQOEjbZNPIWRLwzQrW+WpUCvmjgXIeqnyBcE2g zh9R0TQ5UEkw7Kc5NXRqjr9mrjcSDQfrZg2lIYEav7cqGA7cHqyLUjghu9EoWYdsp9EFf22IttFO VcNsv5d4mhbxYq4qf9gbrfLR3qgsFKyP8uivjfhr5shuTa8KRFSfywMhdPJQG4xEvXVBWu33lcmo OlnAG6AdgfKINBKtkDE1wQZ/uNwX8XvLq3xhX3nUHzabWF9WUe+XDUTpXKqgiWV+aVGKBcKE0YAt /TX+Wn8dQxis9DYEwxUXB2p9s2SjvicHIjacNKk+Yg5iuS+kjKxGR46LN4iBmSneUBBzDFXtUoYJ XxxvVHykIlXB+poK2ZRIjZw7WDzsr6gvNytXzQr7I/U1UWUYvzmBaEHdhVFvdT3Jhs1jBeojckAj 3opgeb3qyRhVLOyfVV/jC3sb/FJLz3z0N5qFGwLRKq/PS55ZtMUflQao9ck4OTXKA/66cuLn1pYF a8yWXMXMna2SJ84NB2oYibNM83oqx0Y1wYgcgxCrIhDBWrJ2xl9ZpU6tH2ZU1O+rlQn+RvJFI3LO Bb2+QK1fTSjZJhZSIBJlDsrZW+dvMCaQL6zGtRYjBeSCCoQY1bmhmK2GTTP6Hl+2Y2LjOEau59E3 Mkdkk74x7LLRCQPsD6h56pOmQykzjGaEfRX+Wl94tjcoUxIeK8/uFWIz9Ya6gFzA3436osZqGy6X v1JQHqyvi4YDzLFrg0xx2e6rmXOxZTw9EA56pxPLbJwdqYpGQ2OGD29oaBhWG9M3rDxYO5xywVlh X6hq7vDyaCUrNDGrepbZvh+sZ1DnyslLs+ikTJHTHoPXBqKyiWVzVYOvvGHKeDWh5AOuhCkpZ5p0 A+VVCWW5s05r6iuMQaoIREI1KDAcEMNL9+T0jA7zxnQH65jjgwNfx0OUyUI9VdXFMp+1RSq7cpKs BwxWbqy6uHZlabOuy1UDBgfQEsURMRhM0LmsiYa6mqAvUSlt9pn+NeyNjwkeKYRTqvDPwePIPFX+ mtBpHfoqQ6EMP7zCX+ljbg7zRUKNsZ9xCn0RO8vZPppIE3bRW9dFb0LGTwWFNlgI9X1K2lnLxD5W S8Tlkt/Ioq39qvmzsmT+NPtXzd+7t8rf+FXzZ2er/Ie/av4+fWR+y01fNX9uLvm5C/lT0nSVX/70 OF9aTWSLLJErBvI0XPQVY8UizhyLOVUsETNFC6eDVs6gS3m6R6wSbeJRsVxsEivEyzz9UqwW74g1 4k/ah+Kwdlgct4wWuiWi2WiSO1mf5knQ1wt9F/A0Cn3j0fcd9N2MBj/6Iuibj75l6FuHvqfQ9zz6 foG+Xeh7D30H0Pcp+v5pGa3Z0ZdN/QOS9aWNTtDXG32Defom+iah7wb0+dBXi7556GtF3/3o24C+ F9Env0nnLfTtQd9h9H2mfailaYe1LPT1R18h+kYl67ME/o2+meibjb4G9LWgbSX6HkPfc+h7HX1v oe999B1G32dijSbQ1wt9BegbjL5L0FecrC/96QR92ei7iKfL0XcN+irRF0FfE9qWo+8h9G1GXzv6 3iHmA/R9jL4vxGrNjr489BWibwT6itF3Nfq+n6zPmpag72voG8fTregLou8+9K1H30b0vYm+99D3 F/R9Idq0LLEce63QRopV2vXom4m+WvTdib670bcefU+g72W5ju1WYbeNLWniUzLW7hB254dN5QzX DUzJq5kqHzapHCdKSkoai4v32TMo0djaVJptbz1qt5FyakW2/BRZM4TVWtqWHWo7YU0X1oxQW1NT W6n8U402j93e2NraurZG5Qm1nmhqDTnShSN9BDUW89nnkAmNbW2lTUdbW0N2i7BbikW7SrJahdX2 TtXkyZOPmMX5hBwytrPCbJVS+E6oOBYMtRV72/bZ04U9vbj4KNFTvRmalmFpahJNTXaNGSz7Kx8s Fs2R8cgjj9gzNLvNu88rPyccVs1h2gSjOByaI/N1jJJsFpXJNAsdSNccVrpc7M3ObtvnsAmH3TSM tIzWYxmCMctoiZZJV3mOygRlmalxy2gJlnFYSCuOm8YWM0KX1GE7q2mwWUZnlWEapfwM01g1zSpN gzkcmuZIbzrdOLTBETOO94TTpjntYycslJkWThjrdGpO1/52X9M0JVOUFDftb5f5HCcn8JkntTsz NKdsoZo6rSGVempFzEY2q2YjFWusrbFlEGaONTUZ2eyu9PR5zXyWzVFJVCJnkDNDODOKJqtOyPpl DfOkAZpONDc3Oi2aM26p4n02u7DZ95TJ1hySuuyNskKy2eLx82S2DGGzKmsRTtdscqxK5YAyJhmG vUyDpRsGc2qoaUq0mNOKxZwZaU67t/SRBJM5EkyWqTmz9u0rbb+++PribyMlCBr3nW4yK52noU2l nnTZVodwOvSmVsQueqS/UB1KNF7RZBRNHpFp0zIdGC99bAl9nTJa5SsqaT7ZVFKUmaFlSuvFzWcj bb40SdPJhQvnnW4+Uh1qTpV0qXBRycKFC0uKnEY8DVaTTSmPmc8cxRCOguUtzXdCJkwekWS+NGdG j/nS07VMaxsfaT9Hj/0y7Vqmc9z48Srf+PHjMjO1zF4xAyabUPbZGTdh8b5Mq5apbFg8wi6NmOkQ mc4zjSjNaLdqdmlGZUf1YPrFIpdNc/UYEkuqVGVJmZqhuRJMWbyP7HZlS8OYC+dlWjB23Jp4UTKY 5izpUg/KnguVJrth0AmGY1GOyTCp+RDzvs505lpM6VSvTdNsyqrYMVNLy4yb1bCryybtmpmRltlj V++JLIeWlfk1cVtTaVO7SJTSptuaviayemlZ2fvGhopCRTfxmbJ2ytqrPFd5JiDFnn1jVelT8mdd TVLKOUWUxuWoyLJpWY6xldva20NFLqt1ya7GLKfIytTbd7UvK3aJ02UAPlNzOObtsFrHVe7oaJAO 0j62ol1+KoqULhunVClXoPONuMwSlzc5bBQdW7ljx6n29rKxWVYtyzq2orT0RKnxOZolq16wg8+8 9vb5E994Y35WupaVUVoqxL5YHuXou9SP4Xrk8ybZKufYyjfkp1L22chk9Dm530eFbIe9KxyrUXZh 3q7t+xr7L9t1Qi45a7xNVSPsaZo9o71dHhjb27PSaE678ZGD1t6enqFl2To7O9uybGlZmZ7GtZ7Y R36NmTpROsWatI+EpXxuuEa4Z4X9s8XoGl+0jhOQU2jfnTbBy4lBcGI3fteglxnW5Dne+PpB9Zwm HJww8oXl6qlTJ4uB075zrVcMmz7tGq8YY+awUF8fM5wuMkWOGc5g2HLNsJUzrVvkzebFWTSp6xJ1 XaauK9R1rbo+pK6PyxdUsVFd98ir1ktdi9U1rK4qj7a7dnbt7DS7uuaoa391HaSuI9R1jLqWxE/m X+XaV73TyB5lyN9wwCo4WHrnoie9sFA2fc6hf/RK/mZMqsR/q4RFeESB6Pd/FDpHFIlbRA1vDMs4 7W4Sr/I+skccESc1l9ZfG6qN1aZot2g12jxtmbZe26S9qu3S9mhHhPwtD4v8bRO8umy30F4x7s9u UXfNWSUcah7I30zhtH3J8eTnMa3Jz+MWJj9PqEt+vi474TmDo3xTcvrNvZKfy7Ym5w/OSU6/zZWc Pvel5PTbpyWnL/Ekpy95JTn93heS0++bkpx+f2ly+rrT+vPIyeT0R5uT0zd6k9M3Ppuc/tItwpEW e7by/JFwaAnPWzcIjrY9z+05Qttwt/RRGWszx2RWZYYzGzOXZG7JfClzD+HjcNI1xHWpa4brKVdX livrRnKdKY1IVVzCqpbTZYsp1Jx1C7XvUflOl8bMk1LQGZNLlTxlCC0w5EYpmeE+A/M9+QPyC/OH 5Bf1leHCvjdxlXED+s7pu8fj9GR7hnhKPGVcoyrldBmCFMbEc7t6TpK+Aw1RuQulhr43ka+nhgFn kSF990hBf0za+h88t5TWlJgyxJSolPPrzj+aP6BwSOHkwmmFNxXOKKwhNLlwSWFb4brCRwqfLXyV uG2knyky302myHI1ZtnTZYmStrisU7KLug2ZYco2JZMvWKf6UZTY68Htg3cj7ci+4eFRj4zaMGrL qJdGe4sWFi2M3WVqUeuYjd8qHvds7D6+aOLeGJOqJt0d4yrv5JGTW6++ffLIa5+69qXr3NeNnjzy +n3Tnr3OPe2VabunHb1p3E0ffX/3rSNk+sx+17l5HjezdGb1zOaZa3wlvm+XzStbUb6lfGv5zvKO 8j3lx8tPVFj9t/jLfCX+Kn8VKcel+Mv8df62ytH+ulm/n7W36tKqSf66qiOB+6ouDayqrpz9zuy9 NZ0yrepSwu/U/jH4Sqg6FA1tC+0KHQxXRMZFQpH76u31A+ob67fN2dPQCylqKCI2FIo2TLq95o4d 8265c0Bo1/x5kXEyZf7v6hsXNC5YuGDLgr0LPmua0DS9qRIJNS1serzp1F0eZOBdA2Xcgr13Db6r Y+HQhQcXuZD8pukqZeGiEYt+3expHtZc3DypeUrzzc0VzeHmpuYlzauaHyp8dbEXGbR4EHHh5mGL RyzeumT6kjXknLRkU3OFTFnyXPOqlnQkp6V/y8CWoS2jW6a3VLY0tixpaWtZ1/J4y3Mt7S07Wj5q 6Wo52epszW4d0Dq0dWRrUev81lfOur5jazxRktZt67azi7Faz7ruYmsvUZLWUOs7Zxdj3Zx1LcTW Q1yM1XWmGHO9da/rUk924Tra/1Hc/yxpPeWagZfC+y21T9vtunRpztJi6W3wH6wDLBE27WF4M0rJ NMIxK8l68GHKV8btlOVS/nWP69LWvTJ+6XXkcJk+t8f7xcTwwS8pP7wnyVseR07+Cy8p/fQM5Sm7 DG+tvKQsLcu8JD2mtOzdLphxz1R8pfR6AzzZ92y85wVP9J4d95wweml6NTVGyvvdJJ+X5eMho6Yn 9MRGTPq5ZUPzPcq/mmPnUSnLxiybuuwXeMEh90bv7Y6nFsbHu6i1KF4bIn2M6b/P6l0Nn5rkVbNN GaK8vPTzZTGfSouktx2S7+l/UGq/r1hqIEW1rXDyfTerOTLth4fxsDMI4Q/bvm36PzmP5GwyvKrM J2Nvis8w6Uu3Jcy2GYRrqGFI2x5SZiTNQ8Ojz4h755rTfPKZXln6/EeUV37V9PxS1ikvPUTVsETF TpY9aeta3rZyWv6AlVUrd0t7rTyy6sZVbcvyp+3Gj+42vCa+cAue71LDx81+B7/7FQU/e5rgq5Pk zBx48iSZ9opsQ6KcWcbw2f6q2D32FHuWPUiSncjxfy94/v+O1H11YSdJEsO2PWJY+WxyNgvLHSUU jYwLVbPbKGnoFYrKPcfcbxAZFxN2pl1y/1ElQoawOyGyXEOvVS/N2SNLhnbJfWbBXrUHKbnLw1PI 3IU8TROMOyG5Q01QVykLpbA7ydynmk4tcq22yz2HPWiYuR8pWezleYm5IyHNU+KhSebOFTZllRSZ f7F3dS85qxd7TV/A6WJ14eoO6XVWfybj1sw31vj96WtnrG17oN8Dyx7oWJe97uZ1Rx9Me9D+YK8H vSt3E0pjJTvXT/rRR3iB6EPOhzwPdCSev/IHPHT3Q+sND2L6jGxP9OG7H16lfErRw1tjJ0WP8+Gj eI3oI6MfTX80/OOax5yPvfr47U+4ntixIbqgsWlhRO7cyi70QfWmodddnsVe3sr+oBdp6Xq3Vq1v 0A7qndohfYtlKlyvb/H8VIz1PAdviLEFITFSpGlThJuchzh5/0H/VFgoecyMOyacmqZ3ELNd6009 lxCeIgZr1xMuJ1ytH9CauB/UtwuNp05O/Z/oR8i/m3wjidlO2lb0T0nUyxvBH/QbSV1PygZa1knL OmlJOvUd1LeoHmxF8xEVU61iO8jbQd4O8nYk1ZYmNZN6gDfSA+TV0JpOz3vrf0hocYdq8UF9mNTJ u+onPGmUS9efJ+e75Nyu2nw993KQdTYpzfOlZnejqMh7Qb/RI3kROuF9vYj3XqPHH1DLIWrpNGuR Fuo0LSRrWfFva7FRQ6dqqbTKQWWZanKPZIzGqtZ2mvaQ/dqAngfNfq1HzxZKbaWUlVLRJB1m/QXX 6FsLQvp6NUpbxTFhlWMLOeCW//NHPy766h3Co+8VBYxFP+ivvyuGkHYRDIWLYRiMgcthLHwLboAb 4XtwE3wfboYfwC1wK8yAmVCOngrwQyXMgir0BqAaZqO/BmqhDoIQgtsgDBGIQj3tmwMN0Ahzaevt cAfMg7XMyAeYEQ9yP8H9H/BP+AJOEvclnAKdkS5gbPoxRudgy/7YcgD2reY+m/gaqCWtDoIQgtsg DBGIQj3MgQbKNMJcuB3ugHnUdSf3+cD4a12M46dwHP6md6ZZIANs0Jd18A0YDZfDVP0Ac/1AzjP6 3pxN8BN4FjbDFvgpPAfP6+/mvAAvwn59e84B+FDfnmvTD+TawQFOyAQXZEEvYB7lZutbcvtArt6R m6evyK3Tj+VGYA5g29w7uc+HRaQ3wxJ9b26L/m7uKuJWE14D98NaeAB+RPxD8Ag8Ck/AFvgpvED6 i/Bzwr+A16AdXqe+N7j/kvp3kr6LcAdx73L/T/g7dMPncAJ0/bhbgAZpYIF01lYGWMEGdn2v2wFO yAQXZOmd7l6AJ3NnQ67+rnuUvt1dBQ3wGrTD6/oB9zb4JeHfcN/FfTcc1te7j/D8mb7C/Xf4nPAJ fUOeVT+Qh63zsHUets7D1nkXwCAYSfpofUXeFdzncr8d7oB5cCfp82EB4CPy7oKF+vq8RdCsb8lb DK2Uu5e89xH+ob7Bc0Lf7mEuF1Qwb78l0vUnRYZ+RNjADg7IBBf0gt6QDX0gF/IgH5hprPRuVnoH K71bnKOvZbVvEufqb4sB1Pk18MJ5MBDOh0K4AAbBhTBYj4qvw3DqGyHc4hLuI2EUXArfgNHwTSiC y2AcXAHFMB4mwEQogSthElwFk+FquAamwLVwHUyF62EafBemQyn4oAzKoQL8UAmzoIq+BkDuTrPp aw3UQh0EIQS3QRgiEIV6mAMN0Ahzsc3tcAfMgzux03xYAE3ouIv+L8Q7WxmVc7l7uZ8HA+F8KIQL YBBcCIPh6zCEXfAi2K+Xah/Bn6EbPtdLY54gp1V/Mmcp3A33wDK4F+6DH0IbLIcVsBJW6UdyVsMa uB/WwgOwDh6E9fAjeEbvxqt041W68SrdeJVuvEo3XqUbr9KNV9mEV9mEV9mU8xEe5c/APp9zCA7D X+Bj+CscgU+gCz7F8+TiOfrqR3I9UACzoQaCwo1X6chtJDwXboc7ABviYTrxMJ14mG48zKbcVv3t 3GXE3wv3wQ+hDZYDfc1dyX01edfA/bAWHoB1pD0I6/Vo7sPkeQwehw3wJDwNG0l/BjYR/gk8C5vh OXgeXqCeF+Flwq/AVtryM/K/Svh12raN8C9p66943km+N3n+NeEO0t4m/A7h38Lv4PfwB9gN70En vA9/hD/BHvgA9sI+2A8H4EP4CP4MB+EQHIa/wMfwVzgCnD5yu+BTOArH4Dj8DT6Df8A/4Qs4CV/C KdD1I3jRI3jRI3jRI3jRI3jRTrxoJ160Ey/aiRftxot240W78aLdeNFuvGgHXrQDL9qNF+1299HX unMgV9/kdutvu/MgH/pR3znQH/ArbnTmoS8PXXkWfXteJrggS78xD7+Ux1zJO4fn/jAU8Mx5Y6AE lpDWAm3ynMnZMKqupep6QFjE25z8ZOwn3MeIP4g6zklH5P8g1v4qNqZpos4yAkbCKLHRMhWuhyDM hTuJnw8LYBE8ARvgSdKe4v407IBfwU54k/hfc/8N7IK3oAPeFnXuoeJmd6mYxBnsoHuuaHTfKUbm PQUvcGZdLyZ5fiQaPQ+JCs+TPD8FMv5F2Cp2en4m1nheFSM922Enz2/y/Dvyvgud5Hlff8/zOWkn ef4Sz51FLz92DxJT3ReKqXkbxTV5z3Ly20zqs+Iaz2b4qVjGKXkZp+RlBeWiQp33bVhKniN/J0/m 5JhEjknkmKRSCzg5dXFyOsbJqUtZlx2X09MxTk/HOD0d4+TUxSmji52zi12zi12zi12zi13zGLvm MXbNLnbNY+yYXdQ+ldqnUvtUdq4udq5j7FxdIlOe6xmHAYzDgLxn9Y68zfSPu0fefwrP6R0F5fp7 xpmVdnQIq1lmMGUGS7u638EWz9NmmbKf3hzAmtux5nastR1rtapT9QcyJU+mnJ6ablribfnOQe8H czpmpfF2coC94hP1BvI8MVPkiVrLE828HS3GAkugBeT/Wb+b+z2wjF3iXu73wQ+hDZbDCvKs5L5K /p9zwvfznrWWPj3AW846dT5dL/DI4mnSN8FP4FnYDJyZxMvwCvyMPHgfwdlJcHYSnJvEDvgV7IRf A1YXnJ3EW9AB78Bv4ffwHnwAe4EzldgH++FDwJMIPInoom2fwlE4Bsfhb/AZ/B264XM4Qdv/Af+E L+AkffgSToHOGZpVrrHKNQvvkRn6p5x5OzjzdnDm7eDM28E5t4PdrYPdrYNzbkcOsyaHtufQ9hzO fDm0N6cT3tcP5fwR/gR74APYC/8J+/X1nHPXc85dn+vGm53LjPPqn7rPg4FwPs8XwGD4Oh6I9xg3 7y9u3l/cw0nntMIMXu/mpOIuIu4y4L3GPU4/5L4CimE8TABOJO6rSfs2XAPX4vWu4z4VfkD6LcD7 jZv3GzcnEXc59yrqDnDnHdrN7ueu4V4LnK/dIZ7D3OuBczaraL27iTbdBQuhmTjmmZt55maeuVuB ueVmPrlXAPPJzXxyr4Y1cD+wYt3r4EFYD5zD3ZzD3Q8DZ3E3Z3H3j+ExeBw4l7s3wDO0hV3Qzbxz M+/cnNXdL/HMzudm53P/B2ylfz+DV+Hn8At4jTa3w+v6Flb9FvcbnIW3qzPzevcOyrAzunfCm9TH zohH2MI5er2bHdHNGLsZYzerDy+x3v2+fizvQf3TPNqcR5vzaHMebc2jrXnPwEv6MU8/WAasLw/r y4MNPPTfQ/89a/VDnoeBfnrop4dyHvrooY8ednsPffHQFw8eysOa8bBmPKwXD3POw5zzvEVaB7wN 7NyePcQdAuY9Xms9XmuLhx20YKJ+qKBE/7TgSrwYJ9ICTqEFN/HM+24B77oFvOsW8K5bwFwoYC4U cDIt8CmPt77Az5mdE2lBFc/MiwLmRcFtrKUBarf6H9iptEVikT4Bf1aEPyvCnxWJVtbyUn0Y/mwr /mwDfqwaP1aNHyvCj0XxY0X4sWqxmjxr9BX4sii+rBpfVo0vq8aXVePLSsWPuD9E3Q9zfwQehR/D Y/A4PAEbSH8SnoKnqXcjdT0Dmwj/BJ6FzbCFuJ9yf4778/ACvAgvwcvEvwL/gc6t8DPa9Sq8hlXb 6cPr3LfBG7Adfgk7iP8V+ndyf5Pn3xD+LfwO3oXfw254j3o7ub8Pf4Q/wR74gPi98J+wD/YTd4C6 PuT+Ebr/zL5yEA4RPgx/waYfw1+x1xH4BLpo+6dwFI7BcfgbfAZ/h274HE5Q5z/gn/AFGH62OsHP lrJDbcDXluJrq9nJqrWH9S3aI/Ao/Bgeg8fhCdgAT8JT8DRshGdAvn0coCx9iL+FHNSzY28i2gne UP6hz9dOcv9Sn5+Wpk9JSwerPiXnJX1Czst6dc4r8B+wFX4Gr8LP4RfwGrTD67BNL8p5Q4/m/Bdt 9x4fV13nf/xkCuUWubSTOdxsjRRsiS3QUohALRSlAcolJRZoMFRoBAakSMIlSFoguK1IQYJSxfES L1E3v92dXZddd7zgJd21u9osjm4y6ohNKNNAdkRAWgR6fs+ZnmKW1f25f/z+eD2+55zv95yZ+X7f n/fnc76hOojN+Gf8C36ILfjXYIZckJMLGqf92PitGMK/wzpNs05yRKMc0TjtZ46t1bRhjDgvuP/n +AV+iSJ+hSdhnSbli175Ijd9Bk86JmpMzorSckWjPNEpR6TliEb5oVd+SMsPq+SHRrkhnTwdZwQz kou07zR2Mc7EWViCd7n+bpyDpdG8ZJN7z3Pv+bgg6pczGpMXuXax/mYsxyXua8F7PHcFLnXtMlzu eCVa9V2BK937PvdeFS2RXxqTq41px/txDSr5Jq293ve+Qf8HcCPW+B43ue9mx7fgVmNuq+4srk6u 86wez77XdT4g3zTKN43yTWPyI67fh4/ifmx07QHz9THPeiTKyTnp5Cd9P/Ett6TllrTckpZb0nJL Wm5JJ7+Cr+Jr+EuIb7mmU65JyzXp5N+4P6v9W9/x7/D1aEPy7/GY43/wO/4R38A/Iee+b+Jb+Da+ A7qSg9JyUFoOSstBaTkoLQel5aBVctAqOWiV/NMr/6Sr+efHfvNWv2MITzj+iT5vEvJQWh5Ky0GN clCjHNQoBzXKQY1yUKMclJZ/GuWfRvmnUf5plH8a5Z9G+adT/umUf9LyT1r+aZR/GuWfRvmn8/C/ iubJQavkoFVyUKMc1CgHNcpBjXJQoxzUKAf1ykG9clCvHNR7+BNyzi9dL4EvyENpeSgtD62Shzrl oMYjlkXz5KFeeahXDmo8YqUqtlXbFqXln7T80yn/pOWftPyTln9WHXFNtEQOapSDGuWgxiNuDGbI Q5V/d/vJqFjdMX20WvsX/8iuaZH7FLlPkfsURVRRRBVFVFGkFCmwSFlFq1K0KsXXd9F+INMPVt8L ivFuWtFsF/2iYryTVfTtfhsc7JMrbxyD/GiED43woRG1Y1nt+JLasax2fIknjfCkEU8te2rZnWVV /iHRizXLkI56a+4y6unqXwoyU5o5ZeWvAyVXS9XqfrS6A+6d0XH/3rcJbxCHqFeXQQxV3gH2/rUk vrtyX+Xo6ZrKbk9N9e8dlScM7n2HqZ5tff2sMmLPJ49W711QMzXaXDMzer7mLdp6vBXHYBaOxXF4 G2ZjDo7n6w1Y55671NF3a7d52lPYjpewMxqd9lS0edp2PI0SdmAcz+BZTOA/UcZvos3Jl6PnvX1v 9va92dv3Zm/f/d66N3vr3lzXoO/t2gU4De/CR1y7Dx/Fx5xvip4Ptvg1uZr9oh01B+BAHIQ34WAc isMwDdNRhxBH+MZHRi/UHGUFj3bMgWtmeCOYWd0vy5mVnFnJmZWcWcmZlZxZyZmVnFnJmZWcWVlr VtbWnOx5p+F0nIWzcR7OxwW4EBfhYizHJViBq7AalXW5HjdUd/ZfqLkFt+I257ejC3fgQ77fnejG WqzzXSnAakzU3OM592IbxT6F7XgJO6NBq5KzKjmrkrMqOauSsyo5q5KzKjmrkrMqOauSsyq5ac9F O6a9HO2Yvl/0wvQDcCAOxiHR1umH4rDq7vzo9CONOQpHRzuSv8QOkfCsdiJ6Ifmi2PoddjreFW21 0hPJ1/RF0Y66GkyJcnVToxfqfEbd/vA5dT6HEnKUkKOEtXVJ46xVnc+hihxV5OpmOD7WuOMwx3FD NEElubq5jud7c1/g+BRv2KdprUfdYtfe5fjdjs/BUpwL61NnfeqWwRrVWZu6ZlibuvfA+tRdhsux Eu9FG67EKrwP1q/ualjDuna8H9fgWlyHG7EGN+GDuBkdsJ511rPuQ7gT3X7LWqzDXbgb90QjdT24 V/+H8Rd+w3ps8Hu86YuCCVEwUXe/523U/wAe1PcxYz7u2ifwCDYZ82i0I9g38XDQkvhi1JH4RlRI DGI4SASJxIVBQ2J50FDzpWCf6OdBipOE6sQj1NtHRj8KjooeDI5WE7852hrM0D8Tb0E93opjMAvH 4ji8DaIjEB3B1Z61Gu14P67BtZ59HdK4xfNvxW24HV0+5w58CHeCygMqD9bhUUqeWv3b2OCkiM2I 2ME4Yv/cHe6ciM1V/xJ8PW7Af4+yQVE2KMoGRdng5ChL8KXETNRHmQSPTMyL5iZOij6cONnxhcFi M7k4sdrxNbjO+Bu1t6LL+Du1D5r3Pvd8KXow8XXn33Y8ot0VbZ5yIN4kS3jutA3Rz6d9BPfho7gf G/EAHsTH8BB68TC+ru79ezyG/+3u+CE4FIdVd8rniezB6bdF/dN7HN+L9dGS6VQ33WdNfxSfRka9 +pfaAeT0fVP7PeO+r93sni3arc6HtFE0mAxQgwSmYB811b6Yiv3A95MH45DoR8lDcVj0YHIapquJ ktyjDinQoVw7KNcOVt3mRe3vsAsv/7ed3NzrO7h7XGKQQ+zZyT0l3s1dHO/oduEOWHsROfhHoi8j +jKib/C/RN9G53sib7CyG1yNNpVE3cvy2O/ximsqlbrXova63dHSuihakwqiYqomyqUS0eaU3Jfa B/u6NjXqT+0XZVL7R4OpA5wfGLWnDoqWpmrd8yZjDnbtEGMOhbVKTXM+3ZikMXXGpKKNqVDf4Tgi 6kkdGS1LHRUtSh0dbUq9OVqVmqF/pr63oD5Kp95qzDHGzDLm2OjI1HHGvc24OcYd73s04O3GzTVu XrQkdUK0IHWicfP1L/CMk7FQ/yn6T/WcRs95h/7T9J+u7wx4N0m9U/9i/WfqP0v/Ep9zts85x29Y akwTzo0GUucZc74xy1y/wJgL3XeR84tdb9Yu3/3T1CWut0SzUpdGj6Uuc9/lWOnzWl2/wrj3Gtfm e16pf5X7r9Je7XesRrtx7zfuGuOuNeY6XK//Bs/4AG7Uv0b/Tfo/6Dk361evpNQrKfVKSr2Seg6/ xfN4AS/id3gJOyGOUy/j93gFr+I17EYUbQ4D1MDah9Y+tPbhvlCPhfthfxwAXhB24paoGN4a9Ye3 RZnw9mgw7HJ+R9QefihaGt4ZrQm7jVnr2jpj7sLdxtzjvMeYe435sDHro43hBvd/BPdF6fCjUU94 f7Qk3BgtCB+Ijgw/pv8h9/biYf0f1/+JaFn4SLQo3KT/U9Fj4aPu/TQyxn4m2hR+Vv/n3P95fEH/ F937JXxZf7/+r+j/qvu3RHPDIfwkejDciV3Rg4cH0dzDU9Hmw0/HGbgUK6PM4etwFzZEm9XRgzUH yUhZ2ag//i9ARmWjtGy0QTYakY2yslFWNsrKRlnZKCsbZWWjrGyUlY2yslFWNuqVjXqrfxO+1rOu Qxq3eN6t4P6yz6jss0H22SD7bJB9Nsg+I7LPiOwzUvl7KufPcv4s5x/m/FnO38/505w/y9WzXL2f q6c5ej/3znLvLPfOcu8s985y7yz3znLvLPfOcu8s985y7yz33sC9N3DvDRy4P/675AgH7ufA/Rx4 Awce4cBZDpzlwFkO3MuBsxw4y4FHOHCWA2/gwFkO3M+Bsxx4w/TKm+U+nHVfcBhu2z/pvzwY5baj 3DbNbdPcdgO3HeG2I9x2hNuOcLM8Nytxs1LsZo9zs15u1sPNWmM36+NmWW6W5WZZbpbnZkVuVuRm OW72ODfr4Wad3KyVm2W5WZ6blbhZKXazx7lZLzfr4Wat3GwrNytxsxI328jNerlZDzcb4Wad3Gwr NytxsxI3G+BmG7lZLzfr4WZzuNkIN+vkZoPcrMjNitysj5tt5GY93KyTm83hZlu5WYmblbjZADfb yM16uVkPN5vDzbZysxI3K3GzAW62kZv1crMebjaHm41ws05uNsLNStysxM0e42a93KyHmxW5WR83 28jNerhZLzfrSS3nhJe4p4UTXuozLnPf5VjpM1qNv8K49xrXxomuNG6V+6/yW672PO+o3KyPm/Vx sx5u1hm72VZuVuJmJW42wM36uFkvN+vhZos4Spaj5DlKkaMUOUqOozzOUXo4SidHaeUoWY6S5ygl jlKKHeVxjtLLUXo4SitHGeQoRY5S5Ch9HGUjR+nhKJ0cZQ5H2cpRShylxFEGOMpGjtLLUXo4yhyO MshRihylyFH6OEofR+nhKJ2xo2zlKCWOUuIoAxylj6P0cpQejtLPUfo5SpqjpMPKTkQgnmsSE8Fi 9exyVe6KoKF63hA8mpjn/MFoauLhqFb1W0h8w5jhaH2i5HiX669GbVNqo/VTjgsWJ28PHqnbFcyo ezk4te73eDWYW/eadrc2sgZBcEyqJjgitW8wIzU1ODW1Hw4I5qYO1B6krTXmYH2HOD8U01ybrk1q xVQq5f7Q+eE4wrUjtUdpj8abPXeG/pmuvQVvde0Y7Sztse49Tvs2Y+YYc7zrDZjr2jztCdoTjZmv b4Hzk3GKa6dqG7Xv0HeavtOdn4F3urZYe6b2LH1LtGd79jnGLHW9Cee6dp72fO0yXKD/Qu1FuNj1 Zu1y916ibdF3qXsvc/1ytLp2hfa92jZjrtSuMuYqY652fTXe79o12mu11xlzvb4bnH8Aa1y7SftB 7c3RSHhLMCO8NTg1vA1dwdzwDu2HtHfqW6tvnfO7cI9rPdp7tR/Wtz44Jtzg/CP4qGv3azdqH9D3 MX0POe/Fx137hPYR7SZ9n9L3qPNP4zOufVb7Oe3n9X1B3xedfwn9rn1F+9VgbvDJxIO7n6OyhRTW kPiBjDDsuERpe1RWT2H1f0Rh8ycpLP9nKCz/BoXNn6SwPIXN/n8obPafUFj+z1BYnsJm/wmF5Sls 9p9QWH6Swmb/LxWWn6Sw2X9CYfk/Q2F5Cpv9JxSW/x8Uln+DwuZPUlj+f1BYnsJm/wmF5f8HheUp bPYfVVgNJS0JNiTqOdo8+nqYk30jqE28GoS01VLN1K/Izq9q/5Ch0zL0SPV9Y6qssB/2d/6HbNxT zcSHyb7TtH/IwGkZOB+/R0zOvO0yb17GzcbvD3sz7sw447bLuFtk3JKMW5Jx+2XczkkZ91AZNy/T ZuP3hr2ZdqZMm5dhs/H7wt4MOzPOsO0ybF5m7ZmUWUdk1vb4PWFyZp0ZZ9Z2mTUvo2Zl1J5JGXVm nFHXyKhbZNSSjFqSUftl1J5JGXWmjJqXSbMyac+kTDpTBi3JoCUZdGRS9uypZs67Zct7tH/ImGkZ c4uMWZIxSzJmv4zZOSljHipj5mXKbFx7782UM2XKLTJlSaYsyZT9MmXPpEw5U6bMy5BZGbJnb4YM vlytUedFy9SnucSt0Tb57xe087Mpx0XbqGRAPdejnktTS4Za+qilkVrmUEsjtTxGLT1quMcoppNi 0hSTUcP1UU0j1cyhmkaqGVC/9ajf0tSToZ4+6llKPXOop5F6WtVvzeq3Zipakjpy987UUTja9Tcb M0M7U99bUB/No6YlqWP0z8KxuwvU1EpNc6hpGTUtpaal1DSPmpak5hlzwu4dqRONm2/cAs84GQv1 n6L/VP2NeIf+0/Sfru8MLNL/Tv2L9Z2Js/Qv0X+2zzkn6lK/Navfmqmslcqmps73Gctcv8A9F+Ii 5xej2X3Ldz9AZUtSLY4vVZtdZh4ud99KqmqlvCuo573U3uY5V+pfpe8q7dXa1T6j3bj3G3eNcddG NdQ2ldo2qt/S6rdWqltDde1UN5PqDqW6qWq3xyivk/LSlJdRu/VRXyP1zaG+RuobULf1qNvSVJih wj4qbKTCOVTYSIXLqHApFS6lwnlUuCS8f/fOcOPuHeEDuwtU2Kpua1a3NVPjPGpcEn5C/yPYpP9T 6rhHjfm0/ow3y894y/wsFX4uqqHGqdS4Ud2WVre1UuUaqmynyplUeWjQSpUvUeQQNVb2SCpvE3nq G6W8IuV1UV6J8rJVfzqg6lGj1Jav7n8cXH1LyFPZKIUVKayLqop8qUhNWQrKU1CRFxV5URflZKll hFryvGeU9+R5zxoKyVNIkecUeU4XReQposhrirymixKyVr/IXypVe9aqF3lLka8U+UoXT8la4bwV LlrdotXtsrJZqzliNfNWc9Rq5q3mGiuYt4JFq1e0el1Vr+iq+sWoFctX39/XVivsvJUatUpFq9Rl ZUasTJ4/jPKHPH9YYzXyVqPIF4p8ocvsj5j9vNkfNft5s7/GjOfNeNFsF4MvmO3K7uSQGV9nxjeb 8cfE/YC4H5gU92mz3xrH/eNmvyuO+wFx3zcp7lutxLI47h8T9wPifmBS3KetSmsc95VdqAFxP2CF 2mWPZqu0JN6FWhbvQg2I+wGrtsaqtcsizVZuiZWbGu9CLYt3ofrEfZ+VXGUl263k0ngXamq8CzUg 7ges6hqr2i6bNFvZJVZ2arwLNSDuB6zyGqvcLqs0W+klVnpqvAu1TNwPiPsBcT9g5bvEfbPVXyLu B+Ls0k4BS2SXZipYIu4L4n4jJcwR9wPifkDcD1BFD1V0iftWylgWZ5kB6mgX933ivk/c91FKD6V0 UUozpSyhlEPF/YC4HxD3A1TTQzVd4r6VcpZVs82euB8Q932T4r6VipbFcf+YuB8Q9wOT4j5NUa1x 3Fd2gPrEfR91raKudupaGu8ATY13gAbE/QClraG0dlmomdqWUNtUcd8n7vvEfR/l9VBeF+U1U94S yjtU3A+I+wFxP0CFPVTYJe5bKXFZ8LWadLS1sn9OkU/E++V79sZvpc6u6u7JcHX/+7hoqOoLL0fZ eO90K5WWqHQNlTZP8ohBKi1N2i/dSqWleL+0mUq7qn5xiLjcs1e6lUpLVLqGSpur3pGy+n/YK934 hr3SNJVumrRX2hnvLuzdK50VqzT9hr3S9nh3YRGVzqPSWVS6adJeaWe8u7B3r3QWlW6atFfaGe8u 7N0rnRWrNP2GvdLHJu2Vbp20uzB5r/RX8V7pzDfslW6KdxdWxHulld2Fx+Pdhcl7pZvi3YXKXuki Kl30hr3STfHuwop4r3QRlZYm7VVupdJSvFfZTKVdVa9bp1bZs0+5lUpLVLqGSpurvvdf9ynb412F RVQ6j0pnUemmSfuUnfGuwt59yllv2KfcFO8qVPYpF1HpojfsU26KdxVWVPYpq35ZqZlysV/2x7v4 E5Q4Ee97bYmr6rWU2B7vew3Ee12jlDga79xvmVRdt8e79hOUOBHvc22Jq+y1lNge73NNUOIEJW6K q+21b9jnmqDEiXifa1Ncda+lxAVv2OcapcTRP7LPtSDe55qgxIl4n2tTXH2vpcQF8T7XBCVOxPtc m+IqfC0lLpi0z1WkxAlKnKDEx+NqfG28zzVAiZsocW1cja+VNeviajxNiSOUOEGJE/E+10Bcla+d tM+1iRK3UuIoJY5S4sAb9rkqShyhxAlKnIj3uQbi6nxtrMTKHtcoJY7Gu+ZbJlXp7fGO+QQlTsT7 W1vian0tJbbH+1ujlDj6R/a3FsT7WxOUOBHvb22Kq/a1lLiAErdS4igljlLiwBv2typKHKHECUqc iPe3BuLqfW2wf80hwfzKv9n0bnd64tngpMREcPqU+uCkur8OHjn8b4PVwbGTRpxU7XklWF0XBfNT +werU7Xaw7R12nrtsdq3a0/ULtS+Q7tIe5Z2OVY6btO2a6/T3qi92Vvu7cHq8E7t3doPa+/TPqB9 WLtJm9F+Xvtl7deC+cG7EkdHbYmZOA4nYzWuwY24Ew/iG0GY+GFUSDyBn1b+Bi0XPK3dEZUT41E5 lYjaUlOwD96ECfwnyvgNnsNv8TxewIv4HV7CTuzCy/g9XsGreA27EUVtYYAa+JzQ54Q+J9wXU7Ef 9scBOBCd6I7aDj8sKhw+DbOj8uEn4iTH87EI78TZUeHI7fA7jixhB56JCkFdzdPRcOXfOtc8K8vN Der5y/rEiX7tSUFDYr7jM/36d0e7EuealfNlw+VRf2KF9lKzcYsx3DRxu74ux3fs+TfTwRk126JC zVPwmTUvYacnHh1tN/fbudjz5n+7T3o+cYInnxSNW4vtidMdrzButfNrcCO65OA7o/G6X0e7zPt2 877dvG8379tT73FtBSaicfM/bv7Hzf+4+R83/+Pmf9z8j5v/cfM/bv7Hzf+4+R83/+Pmf9z8j5v/ cfM/bv7Hzf+4+R83/+Pmf9z8j5v/cfM/bv7Hzf+4+R83/+Pmf9z8bzf/22sO8osX+sUL/eKFNc8G i2t+E7TUvICXnO/Ermh9zcvOX9W+FrQkwuDa19VYH9QmjjGfFVUer51nLk/AieZ5gfOKUk93vsh6 nOXakuihRJOZOs+aLbNmF7h+oXEXaS+OOhLN2kuMb9Fehsux0j3v9ZltuNL5Kv3vw1W42vnqqNas 1yau892ul2NudHxz5d08WJy4zbXbfYcPGXen63e7fo9rPbg3Wj/l9ODaul9E5boifh001G2P1teN R7m6ZzCBctBSZz7qngta/lv0vCdoSK3A+0RWGh3R+lQnbsGtuA23owt3wHdI3YlurMU63IW7cQ96 4DulPoy/wHpswEdwHz6K+6OHUhvxAB7Ex/CQSqxX+zD+T3Bt6q+Cc1J/rf0bZIPZqb8Nbkz9neOv Bxen/h6POf5HfIMX/ZM2x5e+6dnfwrfxHTyO7+J7+D5+gEFs9nv/Gf+CH2IL/hX/hh/hx9iKIfw7 nsBPkMdP8TPP+A8MYwQF/By/wC9RxK/wJH6NbRjFGJ6C9Uk9jRJ2YBzP4FlMRLWiqVY01YqmWtFU K5pqRVOtaKoVTbWiqVY01YqmWtFUK5pqRVOtaKoVTbWiqVY01YqmWtFUK5pqRVOtaKoVTbWiqVY0 1YqmWtFUK5pqRVNteAqvbgxmh+/AouCM8MwoF56FJTgb78K7cQ6W4rygJTwfy3ABLsRFuBjNWI5L 0IL3YAUujdaHYiIUE+FKtOIKvBdtEBvhKrwPV0FshKvRjvfjGlyL65DG9bgBH8CNWIOb8EHcDHre 69LhJ6Ny2BeVgykivJbv7eKepSDkC908oZsHPCn+nxSnLeK0RW9OXD0prp6kyRaabKHJFppsockW mmyhyRaabKHJFppsockWmmyhyRaabAn2r1aNc6tv2mM+82eJcznHdRz7Fo5xa1AbPFOzjS+NYgxP YTvi/w2Kmpcc78QueeL3UabmlWgbDxuu2e04irYlEvxoSnRLYh/tvtqp2v209T7hGLnheOzJKy/x s355pZ6PjckrOV5WyS1jiaW+ScXPztV3nvaCKM/HhvjYZvkmk7jE2JZqzunnZwV+Npa4wj175+lK 41cZ8z5chauNaQ/mJK5FGte79wbtB7AGN+Fm1zq0nbjFd63mscp/BVXNY+sT3a6vw12421tfazDH WvRbi37+ludvQ/xtiL8N1f1W34vYGczhX2P8a4x/jfGvMf41xr/G+NcY/xrjX2P8a4x/jfGvMf41 xr/G+NcY/xrjX2P8a4x/jfGvMf41xr/G+NcY/xrjX2OpAT755+rhH4x9gyb4VJ5P5flUnk/l+VSe T+X5VJ5P5VObo1zqn/Ev+CG24F/xb/gRfoytGMK/4wn8BHn8FD+LCvypwJ8K/KnAnwr8qcCfCvyp wJ8K/KnAnwr8qcCfCvypwJ8K/KnAnwr8qcCfCvypwJ8K/KnAnwrhQcGcsBZvwsE4BIfiMEzDdCRR hxRCHI4jcCSOwtF4M2ZgJt6CerwVx2AWjsVxeBtmYw6ORwPejrmYhxNwIk7CfCzAyViIU3AqGvEO nIbTcQYW4Z1YjDOjIT43xOeG+NwQnxvic0N8bojPDYVNxpwbzAkWqDK2qTK2qTK2qSy2qSy2qSIK qoiC6kHVFr2oWqjUUCXZvCSLl2TskqxbkHULsm5B1i1w+RKXL3H5EpcvcfkSly9x+RKXL3H5Epcv cfkSly9x+RKXL3H5EpcvcfkSly9x+RKXL3H5EpcvcfkSly9x+RKXL3H5EpcvcfkSly9x+RI3LHDD QpAIDgoO5EZjwX6Vf03quz/HEfpdyYr+ftFfifpsMDUxR3xWatJzxfxyvZUq8YNBfc0l5uOomtFo qGYMTznejqejuZX/vRoVWIMKrME8HWWejuJgy2perrrYEAdbVvNa1cWGONhcDpbjYHM5WI6DzeVg ORVa9+sV2jEcZ091Nsa76+PqrFIlh5Oqsw7fP6s6yyTO9k3fpW8pR9lbqV0QrUxc6NpF+i9Gs2vL nV+CFueX4XLPWKltde0K9/7B4Vaq2EIVW6hiCzlcxho3Jdp9/2u012rTuN683aD9AG50fY32Jtzs eoe2E7f6rrdBVcXt6umjKdHt+jrchbuNvUd/T9Cgsuuua+Vwv4jGON9YXN2t5H793K+f+/Wr7hpU dw2qu4a63xr7InZGQ3+y0uuIOjhkB4fs4JAdHLKDQ3ZwyA4O2cEhOzhkB4fs4JAdHLKDQ3ZwyA4O 2cEhOzhkB4fs4JAdHLKDQ3ZwyA4O2cEhO1R4GRVeRoWXUeFlVHgZFd6gCi+jwsukPh6EqU/gEWzC J/EpPIpPI4PP4LP4HD6PPnwBX8SX8GX04yv4Kr6Gv8RAtDl25/l73DkaiSvI1bE7n8Odz4ndeXPs zqtjd65UkSu580ruvJI7r+TOK7lzhjuv5M4rVZEZVWRGFRmqIkNVZKiKDFWRoSoyVEWGqshQFRmq IkNVZKiKDFWRoSoyVEWGqsiQS2e4dIZLZ7h0hktnuHSGS2e4dIZLZ7h0hktnuHSGS2e4dIZLZ7h0 hktnuHSGS2e4dIZLZ7h0hktn+EsTf2niL038pYm/NPGXJv7SxF+a+EsTf2niL038pYm/NPGXJv7S xF+a+EsTf2niL038pYm/NPGXJv7SxF+a+EsTf2niL038pYm/NPGXJv7SFB7EMWvxJhyMQ3AoDsM0 TEcSdUghxOE4AkfiKByNN2MGZuItqMdbcQxm4Vgch7dhNubgeDTg7ZiLeTgB3uTCkzAfC3AyFqJS 8Z6qbdS+A6c5Ph1nYJHzd2oX48yoX4bolyH6ZYh+GaJfhuiXIfpliP6wyZhzcV7QoCJuUBE3qIgb VMQNKuIGFXGDirhBRdygIm5QETeoiBtUxA17q9NgTs1EtJC7Vbz2oaqTnc25mrTncZsLq651Htc6 jwev51jn8eH1arJs5d1Q9PaK2LSITYvYtKjsFYlpEZgVfVnRt1VEnCEaRkXDxaLh/tTfOd77PvWP jvdEwYxqFHw3ysqn8+N3gjPMzhlm5OLq3kItr6/l9bW8vZa31/LpIT49pNat5MEh9W6/irOQOMEv Ocmx+U6c7vhcx6t5+zXVN9wc78vV/dobnyqWVw3xqiFeNZR6j2sr4O2VjnN0nKPjHB3n6DhHxzk6 ztFxjo5zdJyj4xwd5+g4R8c5Os7RcY6Oc3Sco+McHefoOEfHOTrO0XGOjnN0nKPjHB3n6DhHxznr MhRW/ldz/iOuzxvU5w2T6vPq/97ZpPp8SGZbpz6vZLchmW2d+ryS3XKy2zrZLSe7rZPdcrLbusTR nH8mjomeSBynPV5brdOrmS2bONlxJXtd4O2hsudzidm8FHuyUpus1CYrDau7C+rugrpb1REsVHcn E9dor9Wmcb0xN2g/gBtdX6O9CTe73qHtxOv7SLLmncZ0u7YOd+HuaFjtnZSBnpCBnpB9hmWfYdln WPYZVnsn1d5JtXcylQjqU1OwD96EPU7cRndtnLhNndxGe22018aJ22ivjfbaOHFb7MRtNNhGg200 2MaJhznxMCce5sTDnHiYLoc58TAnHlYnF9TJBXVyQZ1cUCcX1MkFdXJBnVxQJxfUyQV1ckGdXFAn F9TJBXVyQZ2sCgsWpv4TZfwGz+G3eB4v4EX8Di9hJ3bhZfwer+BVvIbdiIKFYYAaJDAF+2BfTMV+ 2B8H4EAcFCTV0Ul1dFIdnVRHJ9XRSXV0Uh2dVEcn1dFJdXRSHZ1URyfV0Ul1dFIdnVRHJ9XRSXV0 Uh2dVEcn1dFJdXRSHZ1URyfV0Ul1dFIdnVRHJ9XRSXV0Uh2dVEcn1dFJdXRSHZ1URyfV0Ul1dFLc J9XRSXV0Uh2d5AFJdXSSDyT5QFIdnVRHJ9XRSZ6QVEcn1dFJLjnMJYe55DCXHOaSw1xymEsOc8lh dXRSHZ0MO4P6sDuoD+7gGx18o4NndPCIDjVcplqDXhB1c7v13O4hTtehNutWm2Uovlvt1c1DFvKQ hTxkIQ9ZSJXdPKSDh3TwkA4e0qHOyahzMuqcjDono87JqHMynDKjzsmoczLqnAzXzHDNDNfMqHMy 6pyMOiejzsmoczLqnIw6J8NRM+qcjDono87JcNcMNc+n5ttfrym+oc7IcdBv+j7fwrfxHTyO7+J7 +D5+hv/AMEZQwM/xC/wSRfwKT+LX2IZRjOEpVH7v0yhhB8bxDJ6FLMIzqRq/wXP4LZ7HC3gRv8NL 2IldeBm/xyt4Fa9hN6KIqlGDBKZgH+yLqdgP++MAHIhTZIk/ZIv5PLSDh3YEh6X2l2MOQz3ejoWQ T1Ir0Y4bg4vD23E37sPDyODzwYzwy9qvBTMq/+Uul1vhjWUqlZSr/y7tIleW85ofiOdBbzX7JM70 jnBh9U2lXNkpD66nqrKrQ9V7zq96apm6xqjLvfz4EuctqPjrZdrLq3sb3Ty2m+LKPLbMY8s8tkx9 ZWqr7JOWqatMXWXqKlNXmbrK1FWmrjJ1lamrTF1l6ipTV5m6ytRVpq4ydZWpq0xdZeoqU1eZusrU VaauMnVV9hi6eWc37+zmnd3U1k1t3byzm+K6Ka6bd3bzzW7K6+ab3dTXTX1l6itTX5n6ytRXpr4y 9ZWpr8w3y3yzzDfLfLPMN8t8s8w3y3yzzDfLfLPMN8t8s8w3y3yzzDfLfLNMvWXqLVNvmXrL1Fum 3jL1lqm3TL1l6i1Tb5l6y9Rbpt4y9Zapt5yqzN/TKGEHKn/VeQbPRuWgJnFusDBYJud2y7ndcm63 nNst53bXPI2XsNO6LApqE2fh3GBxQqWVUGElmit77rgMl+u7srK3Xnljqrz1BLWpTtyCW3EbbkcX 7sCHcCe6sRbrcBfuxj3owb34MP4C67EBH8F9+Ci+6XO+hW/jO3gc38X38P3KvjH+A8MYQQE/xy/w SxTxKzwJb3qpbVB3pNQdqadQ+R1Po4QdGMczeDZoCPatzBt1515/Q79UnCw1T6GqK5dYZj4uUFNc pL3YtebKW6/zPXMVmqv6eK7qzVVorkJzFZqr0FyF5io0V6G5Cs1VaK5CcxWaq9BcheYqNFehuQrN VWiuQnMVmqvQXIXmKjRXobkKzVVorurNVb25qjdX9eaq3lzVm6t6cyWezecg/n/OWYIrVPxkczAl cSYdVXYHllf+f2OqHlO51pA437UVctW+zhZykF2uNFT3DVbEIyv7yeZ7ykKcwoHew292GVlILOEX ld2US8ztCnfv8ZZdiZUVT3HtfbiqMu9VP9nFT3bxk138ZBc/2cVPdvGTXfxkFz/ZxU928ZP/y925 QEdVnX1/n30yiCGAZs7hnARFQOVitGpsEHUUL7xjvY8WxY5ArY4VUSMKaKyOl6iNtVgbq6mX2MYb rYAQFVsJilWIBLkMFxGDWMQRAjIcQsAYKXC+394zCQOkfdfb73tX1/oW68/ec86Zc579XP7P8+xJ Mm3wSRt80gaftMEnbfBJG3zSBp+0wSdt8EkbfNIGn7TBJ23wSRt80kZX7tGVe/QEHl25R1/g0Rd4 dOUeXTm8gN4/AgtAA1gIPgaLwGKwBCwFCbAMLAcrwErwCfhf5gW/Vuu7UXPECNGVGjxhYE95k9+a qWErM/vHdepvKdBR8QR6FY9exaNX8ehVPGoHj9rBo3bw5N1kAcXSKbAVeGAbaAbbQQvYAXaCbwH3 IGd65EyPnOmRMz1ypkfO9MiZHjnTI2d65EyPnOmRMz1ypkfO9MiZHjnTI2d65EyPnOmRMz1xo/7s smP/P/MZ5jZ4bofiu/bPLzmnP78E6c8vVRUUZyVxeRNrLmXct7PUKO8B93Iss5MkH8Y71W5S1m4R q46z6jirjrPqOKuOs+o4q46z6jirjrPqOKuOs+o4q46z6jirjrPqOKuOs+o4q46z6jirjrPqOKuO s+o4q46z6jirjrPqOKuOs+o4q47/W50y+dm5GvwERME1YBQYDcaAnwL6IYd+yKEfcq4HMXAD+Dm4 EYwFN4Fx4GZwC7gVlILbwHhwO7gDTFC7pFqreJX+rH69toHSv/TX09Otp59bT4+VpJ9K6p+jftBP 0h8l6Y+S9EdJauIkNXGSmjhJTZykJk5SEyepiZPUxEnqlZv8JjkJa93JeLe/SHltds7zpxgex7aJ k41mYRktzHcwp+dqz4X0nlPoOacgUyUyVSJTJf5hab+4mb7yDjAJ/lF+cTey/4LjD/rLzRJxsjkE UMubETEYuZcj93LkXo7cy5F7OXIvR+7lyL0cuZcj93LkXi4G4bUpvDWFt6bw0hRemjpo3/s/uM8N S5DrxQ91V6w64ptVlDDezniHipK0XXXH+yARAZPYZAY7pSLjP9gZknWcc8C54DwwHPwXCIPz8cMo mj9h334E8w1go1+f9TMPJ2CNE/CL9ZmfeVif8dmE/pxQfUaY5o8Y1orhI+qvEMTwk9R+HKK1w3H1 Vw2yd6Q3+yn8JIWfpA7gkxjWjmHtGNaOYe0Y1o5h7RjWjmHtGNaOYe0Y1o5h7RjWjmHtGNaOYe0Y 1o5h7RjWjmHtGNaOYe0Y1o5h7RjWjmHtGNaOYe0Y1o5h7Rj+msJfU/hrCn9N4a8p/DWFv6bw19S/ wzfCNFL0nHdqbdSKs9B7NfquRt/V6LgaHVd3ZBP1ia7KKOpT3buU7tReCihn/pDfaHtgG2jWn/78 x7KNcyG8dhG4GFwCLgX0UE4E0A85dFjOj8EIcCVQ+fZsGGls1g7YWJhprN4B26K8jfl3YizeVYt3 1eJdtcRcETGn2GcRMUe8MU5Sn6hrXapdJsVAi/CkRXjSIjxpUS8Vd1sBHkXMFfVSHrUdtIAdYCf4 FrSC70Ab+B7sAv8Au8EesBf4WFAAA0hgghwQAF3AIaArOBTkgrP9RXjPIrxnEd6zCO9ZhPcswnsW 4T2LxF1ooChLA0VooKjjZ7c8/2Jjm3+u0cK4gxEJ0UgR8ZfMfNqVzHzStTrzSdfqzCddq9OfdPnX yt+hkafJNs+BF/x1sga86FfIl+lXp/hj5Gto9Q3wJsffIs+84zfLOVz7HtcsEBfKBl4vxAeXguXM PwGf+tPlRsZNYDPYxrkWf7rZxW8xDwW5/hSzN+MAxhL/XKrXc80z/GvVz5A584V0FvoVzhJ/nZNg XMmxT/wxziqwhnNrwTrmTYwprtkKPLCDY3s45vvrXOFXuFJIt6tw3MP9ZjcfHMn8KDCIeRHjSYwn g2LwQ3+6WwKGgDN5fRY4h2vOYwwzXum3uCP9Ke5ExkngTlABHvWnFH7qrytcDT4DjeBzsMFvLmT9 hU0AHRR+A3b6LYXfglbwHfjebxHHyxeowmvAy2hoCuObgGpWfiHyTPzFxE/MPNAT9MZfqIQdKl5n FVgHUmAr8MAO4It+bneR5wZ9z3XAcACruKPAaEBsuBMBVatLTLj3gApRVPip6Fe4GnwGGsHnAL8v xO8L8apCvKrwe925POFvkG3+ZhHUPzOpfqf0ZbxpBl72DpWI+t3SBRxbyXw11QDVtvxK/0ZztSRm 5Tb/QtnMXXb7FWaeX2s6VIcD9H3f4az6Leku3LcFr+ynfxuabsnsS5UwgLz6005jIePz8gk0+Dvw NHgOvAD/1QD1e9WvaO06cgZ4M/N71nOYL6AnpdfAd/vhs43yM46toZ7RknLPFo7t5the4eC7Hr7r IXUj1nBMR1mE1yUil1omF7918NlGZwXjJ2AVWAPWgnWgCaQ4vxXAyVjLcb4DbWAP8P1GfNbBZ/u5 vRhd/K0AHMnro0B/5kWMP+Q6Oj58tdE9lWNncG0InMO5MLhY+6uHxR0s7rjXgRvBbWAix8kT+K+H 5R182MN/G/HfRvy3Ef9txH8b8VUPX/XwVQ9f9fBVTwxBowk0moAdlFaTsIMHO3iwg4dWEzBCIz4r 8Vlp5oI80BPkg0LQGwzQ0d2IphJEdyPR7RHdHtHtEdUeGkqgoQQaShDRHlpJEM2N7uVE85VgJLgG jAKjwY1gIpgE7gT3gArwqJCsLMHKEqwswcoSrCyBT0t8WuLTEp+W+LTEBxQHvswKZjCq31qdz1z5 xmpWuQWO20aPTmWF7T1ld3GI+q0lfL9avqU8l/VTP+LTdawvT4wx1u/dbXwNNoCN8HQr43egza+D k+vg43q4uB4eVn916XbuNEZzcJXyXaLnBeY14CWgmOEVOPTNzJPmcH4u83lE3QJ/gv6J5aX+2Kyf Wm7UP7XcRBRtYtwMtnH/Nv8hfDiFD6fw25Tm2Xrls4wr/OY0t/olmlc3cXyz8lfmW4EH4HCHyHW2 gxbwHe9pA3t4j4/GpV/S8dPIR/lj4dlGOLbxoJ9IPodz5zGGGa/0U/hkCp9M4ZMp/DEFE0mYSMJE EiaSMJHs7CeY8dEUPprCR1P4aAofTYmA1tZb/k4VwR280av9J0MyjDVBe+8MdK/0OY8cuABWWunP RXcTYKwkjFWJ/u7nLoPR3QjNWG3+j8wjsPCRfoI7Dzb7+atEPneEdUD6TiXcSXKnau50IXfpx12G cZcSuW1vm2zm6bt9B5kaCxP+uMK/+0MLv/SrC7f6Q0WYGm8YNd4warxh1HjDqPGGcfdq7j5WPo3P VKkcTV/9IvOXOP4KMr7G/A3wVodvxInCOjmX8/N4rfxjG+y7G1aGwyTViWnCurnwVzcdmQ6R6ZjH cGwA40DsOt+vwy9UlNYRoXX4RiVRWuesAWvpn5sYN3F+s/YJ6TT71c520AK+49o2QG9O1NbhE3HN R9S9RLBD9DpEb5qTYn6t5qTxnKMzcsvwobvBL8AjnHuUc49R/eapnxZq/9STSL1QVyZvkYVUpK6k Q2gCW8SwjL2niNxMPHv6J/oXACo8XYPsJkO2iqh7ugi794moMPGXNE+pv8izEH33k7/lukrwpMon WPQpxt+DZ8CzKj73evJ5xmqdYyrkHxj/CGqYv8hzXtLPniBf5difwJ/Ba3jAVMZp4HWVhzg/k7EW vMG5N3nv28z/Av4KlNx1YA7PepfxPe45F7zPfB6eVY8nfQQW7G2UDXuTchHzxWAJWOrnyQTjMrCc cysYV4JPmFND6b/88BnPa2S+hnt9zrgWfAH+DqitiIExcj34CiTB12Aj729CP5vwsc1gC5X3Vo57 YBtyNnPfHdrDJT7m7JcJuuFfeX6JCTeQ8ceYhYwqGxyjooFxIDUea3M+APPARwC7OQupeD5mXAQW 6/xa4SQ4tpJu9VNeN4LPVY7d6zlfMP4dfAm+Bt+ALTrnVpBRKsgoFfBXEfxVBH8VOTs5963Kvbx3 r86/FS6Vuyv3eq7pj3EPAbmgG+gOeoCe4DD1Wxd7k24+CDLvxftYE/n6QvL1hW4f5kf5eW5fxn6g P8cGEQc/YH4iOIn5yby3GJzKuaEcOw2c7le7Z3CvEDiTc2eBc7jPuZw7j/lwxjCv6ZX2ZULmMd/Z LwPSMbp3g1+ARziXyYbEkkNGrCAjVpARK8iIFWTEisINe5OF2LawCWwC34BOsmRv4rj3Jf4YcZWu sp6jYmrPUi/CUC+RMYklagLFShNgpQn7MhbXvsc1c7lmFexKXqayShCNeAro8BS8opuOxzyzJ5k2 32/DU9rSnqJjtFEz1EJ/rM5aCcaV/gTqh0rqh0oqLWpixuys1UwdsR206HoCZtI1soSdxlJt9cOC SayXpKpKUFUlqKoSaDqJltvSWkbD1zAfRcU0GsRUzcG4n8azmOsezj3SXoPw3sdUHdJJRuusDjnW oLM06CY7NKs0qrS4Cnyhq+G8Dm3lpSsqrYnsFavVdQdB4IDhmcopW+KK/4FUJ5GZkmSmJJkpCQer nz9Nkp2SsKUHAyZhviQ+0KSz6iuMU3SVncTmTdh6NbZejW1Xm92pPAb4q7FfE5GcxH5NZJemjmp5 nY7WJNGaJFqT6QqZ89RWRGcSmzVhp9XYaTV2Wo1tVrtRqob7wQPgUX81Hp7Ew5N4eBIPT+LhSTFS dxQNfis1Uis1UquWaiPjJrAZIKH8XlhyF/gH2EMmEcAAEuSAAFD96yGMXUG6j20yezA/DBwOgsAC vYALCoDqc/swHgVUhjoaHJuuTKiXWqmXWuGHVnihlVqplVqpdb9Vnsnrs8B54HxhuReAi8Cl4DJw BfgxGAHSfWqTO4b5z8D14Abwc3ALuANMANl97L28joNfgnRP20S91Uq91Uq91Uq91Uq91dpZ/9ob GYSNf9TjH/X4Rz2+UY9vqKp2FdkzQcVSm+62GNMVSZIMpSrShFTV41qYfw9MJcFRujpUlWEjddfv yIuKZV6klnmZTJ9mlkqYpTLTvylWqYZFqGlAru7NPJgjCXN4MIcHaxShZw+Pq8bbqmGLyoPYIsMK eFe1ZoTLieCR4BrVQ+F1o0FMdc6M94BHmD/KucdU16pYW9Vwohsrq6eXzMQq57uqOGRsj8MjQVE6 HrlaXbUmHdX7RasLCkB/cGrm6oCcx5ULdFVJbcp8m18pguK31D1LYYs1aCeFNraJftbpfsqKgJfB K+BVMIXYcEUe982jkyzi3nncO48qKELXWETXWCRyjI26VurHMzzulKeP5OnqKX1E9ehpORIih/+n qL/RS4XQqKXpqj+jUH3zPCy/ABupdzX5m9VZuV1X4WRgYxvdUAvjDuUP+m51ciFXrlLdN/gC65X4 FeYQsmBXtNfdV1m2kSzbCE83ukdyrAicwTwEhuMrXfRPkc9DN+3SqoqQeo/7p6giWacw9F8UHrzf b+tlPuHK+GUchqjFN+OwRC0sUYuNHN1NUVmwzjqpnpL5XVC1L6Eqa2yndphqieJabOhgQwc/jmf9 PmYtEV1LFNcSxbX4d5xIrsWuDn4eJ9JqibRaIq2WSKstVN9/4aCpWjTViKZq0VSj1pTKnJ/x5DVq d4h5KktTaS0l0ZKns5nLWAD6g1O1tjy0pXaDkuIHVLiSCldS4UqqW0l1K6luJdWtpLKVVLaSqlZS 1UqqWEkVK6liJRWspIKVVLCS6lVSvUqqVknVKqlaJRWrpFqVVKnSUfgAIDnVnKSak1RykkpOUslJ qjdJ9Sap3iSVm6Ryk1RukspNUrlJKjdJhSap0CTVmao+pDgU3m5BB83wdQtrVft2LfBkCzzZwhqb WaPq1DZgG6o80YXrm9CTx/UqczRxbRPXNokB+hNcz69Ey5OMZsbt2i8r0fYkYyfjt7xuS/9E5f6f XvjnkgWaYP8mGKcSdm+iK2yhG9wJ01Rm7Waeqz4JhpGbYJNKGLcJxm2CcZtg2SYYpBJGbYJRm2DU Jhi1CUZtEsH98nvPdI7X+fu/2fHoNHcH4FjPVN4RBfeDB/Qnf7v96sxehq6/hUE3VKb/hlcLPZH6 m115eJfa6ZD6ugH6Zw3ontrfxas2fyX3qdcdtnrnJP13/dVfi46hkVRmj2+AKBF9ibpaoq6WqKsl 6mqJulq1W0JPinJ5mqn/wrRHn5DF3freHr1Bkh5S0kM6+3HzdRyL+fX0kJIe0qGHdKh9k9S+SWpf eJpzmqf9euRD9o5Or17017KZfhxbJrBlgi5lGLWn2uFJ0BUP0/uShYy9eX0M1w1gPlCU0MUOw6YJ qu9hdLLDkCCObRPYNoFtE9SCJdSCJdSCJUgQx9YJqu9hSBHH3gnsncDeCeydwN4JMSBTBWf1S/4U 9OCl7Y8O8kEhSFfBjt4zH8i6Lmd96Qp1CvqoJ1fVk6vqyVUOuar+gJ7AQy8eevHIYfXksExfwHsf E06nvnMY1eiFVKMXIlkekuXpurw3eeNKMBFMAneCCpHHHfK4Qx53yOMOedwhT3vfBtazAZk3IOcG nrdB+0qKGkt5k1p3bsYXe2KRfOaFIL3OatZYzfuqWV8166tgfRWZ9VWwjgq9jkc595j2yCf2UoPS /Tep76Iwr/Y/Na/xtwiD/7/Ur5PMvtGzjfrMIeYIf4t5lb/HHEn0Rv0vOVpnjvK/M0f7i0QOZ7dz dBtHN3HE48hV/g6u3cEdvubofGFyTSuvfs91W/WdN3Q8Q90NZjNvgSFuU9+iwWwBs7Wm+gZV9arO LPW3mup7VQ1ebUWesTzxJu44jvvf7K8zb4VZbvOn8g6yF7PtzHbw3lu55jZ/Oq828Wosr27x7+Bu b+g7EcPcYRezDVyV4tUf/KVmDR79ohjIFa/4T+r/G8XhVpmYZd0tIlZc9LGWiT76uxengIO/c7HK nSPK3AbGhYzp71is09+t2EP/xkv7z/bv+y2Xsl7vcLxOFDslIuwMEeXOUBFxTgNniqOdYerbyHnn IK46Nf0NIep7ydW37QhTf/9j+rsHq4WhvtubLO+JYmObiBktjDtEzCwBQ7haclQdKRay4AL9zY0x 0e2//Xbz9VnfcG6qp/KsLgUX8bwTxa+4w2RRJZ7knrOZ14E54F0Rk0LEuuWJKmuA4VoDjf7WYFFs IYl1PvgRuFiUW5dw/jLmo5lPYJwootZvGadx7XSwkfduFc12SFTZUw3XnmEMsWeCt0W5+xSSvCaK 3RmG684Eb6DxNwFyuPNEFSu0Ci4ToYJrRXHB9caQgltY8W0iyqpXFNwBi1vifREWH4APwTwwH9SD hSKc/7EIWyFwJbgK/ARE9XdwVlnPMM5E76wWO8ewc6yglPeFDvyWUPRdhb6r/r/9ttBerBJf833q AV86osw8gyf+v4gV2a5dkaNnc/bpWuRZA3jKQLBRlNpTxW32DDHZnikmuzNEqTsTvEEl/yaY56cK rsdDD+EdIa6KcFUk+xtEORsRgQO+0zSiv7XU5GiUo1GORvU1fXjVh1d9uMbimpDoLZ7n/bvBXuCL SP568BVIsv4BYhBSDrJOYT4W3AXqwWL9zaqDkCeEPCF0Mw7djEM341hBH1bQZ7/vUL0eLx6PDCfo eHuSJz0vcg+MN6TIRYpcpMhVsYckuUiSiyS5SFKOJJOJwQjS5O4Xgyr+xnLsLpCOvQixpyTNRdJc JC1H0hokrdFx9xqam8E4E7THnIq3a7U2a7LirEHHWd8OSXcTc3uBLywks5DMQhoLVghradKSWFqK xcLKfnLWE2fxxFnubLr8eWIWUR4hyosLLhelBT/jqZ1JkA9DWWILIJ8GLZ5wMrgZ/AX8FbwDZoOP wQr6+yVgKUiAZdj6EnAF71fcWkZUl8GtZUR2mY4YokRcb5wC48JvBkxrnAqGgtNASISMM8G5osEY Dv4LhMH54EfgAnAxGMk1PwFRcA0YBUYDrG/8nPvcCMYxvxXcBvA/43ZwB5gAJoJ7QBzcBx4Am3jP N2CLmIXks5B8ltEMJ20HLcx3gJ3Mv4WjHDGLTFFFpqgiimeZ9WJW/nb8qAWQRfJ3gm9BK/gOtImG /H+IUP5usAfsBb4IBQUwQQ4IgK6gG8gD3cFh4HA8P0c02Jy3e4J80AscKWL2URzvC/rxuj/4ATgR nAROBj8Cl3Id3mJfAUbwGr3YN4NbAPoRLtouR9vlaLscbZej7XK0XY62y9F2ORqJoZEqzdDNIoJG ImhEszUaiaCRCBqJoYkYmlCrLUficqQrR7pycYzRxR9n9AX9QH9wNDgGHAsGgIFgEBgMjvOHGkX+ 0Pyv/XH5G8BG0AQ2gc3gG7AFpMBW4IFt/jjbBN1AHujuD7V7Mx4BjgengNPBcKC+UTPH6IlPXgwr bkULIfx+EHwRhf3KiMAoERiFK6JwRVTxg8wTk+VhwBKTydNlHZx6PvnjR+BiaoxLeH0Z89HMJzCm 83O0nW/tt/2vdB7u4N32HMzxdA4OZ6JTcUMVkRkhMtW3Qs8lMmNivHiY/x8Dv4ZxJ4PHmf8GTBV9 xDQwG9SB9zg2F7zPav7GdR8wfgjmgfmgHnzE8QZALhEfc+1isAQsBcvAKvAVeXoD12wkbwXwgU2M W7B5uy9kfADtrEU7a9HO2o6oqBdVgWNFMbVBWf4iURw8kgqlL1zVD/QHg8Bx4HhY9URGop8aogxt 9rGot9BmMdrsQ01RRk1RRk1RRk1RZo3hHOxp3cRYRsVzN/nzPuYPgAdBOfgt76tkfBL8DqB162lQ xT2f4R7PMn8OPA+qwQuALG/9Eczk/FtcNwuQPy2yufUJkcO1biF4AUb/A6gTu+CzBioAlWt3wWsN ZP8I2T9Cxq8qGA6vXg1GgdG65ikTAZXtM5k8lsnkMfJiAh2vIk7IhVks1IAOG9BhzCpClmv1eo9n vQ3WPczvBaybKiWCTDFdpdRR2c0RG7VM5EK3gdcLed0ul7KpkmHqQTIU6grMg1m3gRawQzRg1xXY dQV2XUF8N2DbBmzbQJw3aBuUGT20PPd1qpdIJ3opFz14UpgnxXhSOU+K8aRyXQ1lKm9dFd2t77S/ jIeKZ+mO2sD3YBf4hz/f+gB8CBZR16vj1v/VTxC1+UMP+ikiwz2dnKX6zuqD9jiO66jqO6no0V8N +qtBfzXp6l5XFuX7V/Z+al9lz3wCVelE7cMxcnqZ+ht46WqCCi3NHmWwRxnsMRX2mAp7ULmJqVns cU2n7HEoT+/D0/twx2LuWMwdyrhDGe8u4x3FXNlH9Nfr6XwtVaylirVkryOy3zouO0juKi13ZxXQ PnljGXmjyBvJyFsq+v0LSTq0up8EnWkwI0WW1mqQoCajtZosKcIZKfbve66Cc8NwbhiuDcO1Ybg1 DLeG4dYovBqFV6NC1bzzQT1YCOiH4NMwfBqGT8PwaRj+DP+TGGtgNQ2spuHAGFMcCn9G4c0wvBmG N8PwZhjeDMOZYThT9V1R+FL1XlF4MgpPRuHJKDwZJkaL4UnV3ewioqZmeDIMT4bhyTAcGYYjw3Bk GI4Mw5Fh+DEKP4bhxzD8GIYfw/BjGH4Mw4+ql4vCi2F4MQwvhuHFMLyoOqUw8R/OxP+sDC82E/Nl cGEYLgzDhWG4MAwXRkVeBw+0aJuWooVStFCKFspZfflB8d8/E2vlB3pFlj+GD4irdMX+r2Jqn2e0 Z+P9PeNg34yJI/6JJTuyYGeW1Ex+vM5exZnMlc2cxR3MuY81i2FN3T+Kw3TveCBr5qG5w4AFnH17 F6oOO0h7h4lnYMdOGFTsgT3fB3/bn02tT2HUtjSrFqhvNcz/t+5Qp/IQyL7TsfRkpXQ4ZXQ4ZXQ4 ZTLPyJGHAcvIoRcrpeMpo+NRdVYzlm2m8yml/wpbo3V3WEb/VUrPVUrnU4ZFN9ozjRy7Fuu+rT1R sWSz+wbZ700j6M7m2HvocZ5xJFadhVUnF1wpyrFqA1adWzDeOB6rrqV3budUxaeqYzX0vpHBPFef ze6Ei8UFcEMEbojADRG4IQI3ROCGCPEfIf4jxH+E+I/o/L6MsT3HB/5Jnu/L6vqB/mAQOA6o3H8i 42mA/o24juha4Cadfw+qB4jvCPEdIb4jxHeE+I4Q3xHiO0J8R4jtCLEdIbYjxHaE2I4Q2xFiO0Jc R4jrCHEdIa4jxHXkf1pfEOsRYj1CrEeI9Yi4MaOlEFUr1TN4nPlvwHtgLngfHf+N4x8wfgjmgfmA ToIqFV4EyoM/5trFYAlYCpbpPaTy/apUQ1hau+kqtYZoqSFaaoiWmgOYdmpW/zYVlo1RpVpUqdYB VghhhRBxW5qxQgjGjWGJEOxiwboxWDcG68Zg3RjWCWVYN5SpjqZ2YpUQVglhlRBWCWGVEJWpBfPG sE4I64SwTgjrhLBOCOuEsE4I5o1lVaYhLBXCUqGMpUIHVWAH8EiWZUJYJgQLUxVkc4iqDJE4fBB3 mGIVPUrG/8URnWXmDg7OzsZZu5Sd7E201y+tOt721QIH70moXa1iJFL7bMVIVCzOOHD38D+9a2gt +1/cOZRoqxhtFYtDM3thYfQ4CD0O4kw5Z8rRYXlmN66P6I41HsAaD/zLXSG9I+S/rzOc2t0+XDyH Fw4Qk/Xu1zzm8/W+0mTuMJU7vModJrtq5/ANMZc7zOUOczN3mFpwg97li4pT8A5LPElF/DzRPpt5 HZgD3gW7ObYX+GIyPD8Znp8Mz0+2BhArg6ksT2FeIgbhRRZeZMH5pXiSBe+XwvuT4f3JeJNlTePa 6aCe14uRcKrRw54Oa80wXHKBm8kFpZq5XtP13y4k30VOGEJOGEJOKCUnwOXGEHLCpwXXooPrjf54 3go8r4GcMATP26j3LMuQNDsTlWUyURhpypBAZaBmnl7M03vw9B48PZLJRBGdiWbqbNSfJ/fnyeqp Lk/LOSgDndURVYoTO+PDhborL27nu0w93MFr2d234rSOfYrjgaqVQ1nReSB3jeaa9oht76zV7uIz uivu4B66kGhmZTFWFuuoqbM7Yir8g/gHzuzoTEp1hKvuZJauqAbiMeHM/nAYDwnjIWFWV5NdVWX2 i8N4TJiVNbCyBrwmrPeMh2gPCet942mM00F6/ziMfebiw1QJ5KrXdOzMRfK5SN6M5M1I2wz3qF1Z 1QWsRcIapCMqsNEdYqo4PrOPHEW6KNJFkS6KZLuQbBeS7UKyKJJFkSyKZBuRbGNm/ziK3qei2xDS RZEumrVnHEW6qP2S/1lGumY8pxjdhjL7xg1IuRDPycFzcvCcULqOEbvQZQ01TDizj7wLid9E4heR 2EXiueJEJI5lqqxSJC5F4lKqrB5UWT2osnpkqqxSJC7t8O3BWDldaUW0f49lriqtaRyfDtIVVykS p3TVNV1xEZVXuvpSPh/RnvGarsBWHOD30UzE9ddVWFp6xfd7kX4u0s/qiINjkH5/yYVYsV+NuE/y jRnJS9HzrEx9qCQuRWItre5MYHckWotEa5GoBxL10JGYrgtdJHoHiSJIVJqJzHaJ+iPRCvGDf/X5 V6YKGZRVhfT5J/tk2RVIVVYF0h6xYb0f1tlnadfq3kx/ltYRiS/8032okNpr0Z+zFaHLMsVi/6Le Lsuqt3ehz13osyzDdO2eUKbZbhqYnma9TO2tmC/UiQeUZTGfqsNd/VkjHoCu56LrGLouQ9c9sllQ BORL/lI511/qNIPtoEXlPyMocvgnRBcqcUP0ED2Z5QtHdBUF4kxeXyQuI/NcKcaJoWKSuF9cKh4U j4ifiAoqzzHkm8fFdeIJclJMPCNmiFtELTHyEJXlIrSzhH9VYrlIid+LNqOLeMs41DhUfGh0M/LE POMw43BRb1iGJRYYvYwCer3exmCx2DjZKBafGyFjmPjCuMS4VKw3IsblImmMNK4VG4zrjFvFNuMu 40HxD+Mh42Gji/FH42WjqzHFeM3obqw3mozDjc38c40tRsooMDzDN3pLKQ8xTpDdZDfjFNlddjd+ KHvKnkaJPFwebgyRQRk0TpW2tI2h0pGOcZo8QvYzTpdHy6ONs+WxcoBxjhwkjzPOk8fLYiMsfyhL jEvkUHmGcZk8S55l/FieLc8xRsjz5HnGVfJ8eYExUl4kLzKi8hIZMa6RV8gRxk/lVfJq4zo5St5k 3CBvljcbE+StstSYKMfLO4w75SR5t3G3vFfGjfvkg/Ih4wH5hKwyHpLPymeNX8sX5AvGZPlH+arx uPyzfM14Sk6TrxtVcqZ823hWviPfMWpknZxrvCg/lB8aU+R8ucD4k1woFxrT5BK5xJgul8vlxuty pVxpzJCrZKMxU66VXxiz5Dq53viLTMomY7b8RqaMudKTzcYHskW2GPNlm/SNelOa0lhidjG7GEvN rmZXI2Hmmj2MZebhZr6xyrTMXsZq0zX7GGvMfmY/Y715tDnQ+MosMYcYTeYIc7Sx2Rxr3m7sMF8x XzH2mEvMJcZeM2EuM/zAoYFcaeQ/mv+8NPP/kD9VOvmv5y+Ux+Qvzv9MnpP/ef42eWn+rmAXeX3w 0KAtxwdvDY6X8eCE4F3yweAvgr+QvwzGg3FZEbw/+IB8NFgefFg+FqwIPiofD04OPi6fCPJPVgYr g0/KJ4NPBZ+STwWfC74onw6+HHxVvhCcGnxd1gRrg2/JV4J1wY/kn4MLgx/Lt4OLgwn51+DK4Do5 J9gU3Cobgt9ah8iE1d0qlF9ZR1h9ZLPV1+ord1j9raPlTutYa6BstY6zjpPfWydYJ8pd1snWELnH GmqdYZrWmdaZ5iHWedYIs6s10oqahdZoa4zZx/qZdZ3Z14pZY83+1i3WreZA6zZrvDnYmmSVmUVW 3IqbJ1r3Ww+ZJ1m/siabJdZvrKfN06xnrefNc6waa7Y53HrfWmqOsZZZq81Sa421xrzT+ru13rzL 2mhtMu+xtlhbzPssz/LM+62d1rfmA1ab9b1Zbu2x9poP26Ztmr+0A3bArLC72Xnmo3YPO998zLbs XuYTdm/7CPNJu599jPmUXWQfbz5j/8A+xXzOLrGHmDX26fbp5kv2mfYw82V7uD3cnGJfYF9i/sn+ sT3CnG6Psq8zZ9jj7FvNt+3x9r3mbLvc/rX5kf24/aS5zH7Kfsr81K6ynzFX28/bNeYa+yX7ZfNL e6o9zfzKnmHPNL+2Z9lvmxvtz+0vzU321/bXpmdvtDea2+zN9maz2d5ibzG321vtZrPFbut1pNna 6+Rep+Uc0Svc66qcY3uN63VHzpBe0xwjZ5jTzcnPqXLOds7P+YNzoXNVzhRnonNvzlvOu867Oe86 7zt/y3nP+dD5MOd9Z76zKOdvzlInkdPgrHBW5XzsNDprcpY6a50vc5Y5SWdTzion5Xyf87kLseRs dnPcLjnfuF3drjlb3Vy3Z47nBt1gzk63l1uQ8617pHtkzvfuUW7/nF3uYLcoZ697kjskYLhD3TMD Xd2z3bMDPdzz3QsDPd2L3R8Hgu5Id2Sgtxt1RweOcH/mXhfo68bcGwP93ZvdWwID3Nvc8YFB7kT3 wcBx7uPu44Gh7hPuE4HT3Gfc5wKnuy+4LwbOdF9xXw2c6/7ZnRoY7r7uvhk4353lvh24xP2r+9fA Ze5sd3Yg4s5x5wQud+e58wNXuB+5HwdGuEvcROAn7gp3ZWCU+6n7WWCM+4X798DP3CZ3U+B6N+Wm AjcUnFdwWeDnBZcXXBGYUHB1wdWBSQXRglGBOwvGFFwbuLvguoLrA/cW3FBwc+C+glsLSgOPFIwv uD1QUZgoTAR+VbiqcHXgscINhZsCjxfuLPwuUPl/uLsS+CiKrP+qOiRAIMd01UzP5IBwBgIBQoIB RDAg9yEiiICIeMCioquoq3KsgoLrsYrouooruhoVdGXdT1xR1wtUQEE5w6HcEBUREAU86O9fbyb3 weQA9/uqfl1T/bqu6a736v2rX1clDEwYXOcRkucsMWPOuS8MGkhD6XL6f+jc/aXP3P3uYfi57gbE t+OYYw73x1CKnNPUjsU43ipFW41jTbHzufBT3MXBNrjfunkmDLP8XcHj9Dr3AI7jOHaHneNrdyn8 12Gmzne3ufn4PVzdFpZT5oGg5/g+UzZq2WOeN6hfVaWc0G9R2xSXdjRIKeppfJcO1ErjQzXC70Kr dxU8Yff76tSCUkyeH8NMXcv/opJavq9yrrzQb6lnUUABjx8JnYf5L9wfy78vJek4OwKf5+7AkVfU gmo8iznuiKDs+e92JeWKm13q6iQ30lXuJI5/7K7GXVkNqZbMZ4eZshq9difOdxbcJZZ6kAmV1LnY XVaYRjElj/1i+OBdX8Zl7WJ/mENT6hS+dqD080DqpSEJzLW66cXqymO+2HUqmRO8B0aOcY68U9+5 mjluUX748p/7prkPRb1VlZMmryjmruN/cqhm7SxR+q5gGzhueG8PnvZ+HD+e8u4eqPLoJWrQ0NPu 8J93nQnpeXqd+537ofuB+91v3Y6gM/pajcv4rPRZAaUCDaUcHjpdzp2LI7cYIRW1Z+A3o0zK1UVp ILtWu7lBCn5XgP9WhMqqRMIWlrTOXVd4klwB3Zwtg78V2umt7vwQzfB6btla0JopkC3zT83PJbmj SGJjTFmP0BwjgkcoxdxT/5/qOPdKHFNL0Uq13c0O+XGnLC0k59z5kAEr+V/NddOL2l47Iz7GwdVm NAydHUENS90RoJUqncfRotE7PXQE8UU+y//82mjPmXOlZSrGl2XusyVR3m/n3M2lzivQbMv0r3Xu EhNWWnYRvjAcvuJ0/2fGygZnrKwwxYEC7TCkle2HBHq+CjV8xuFp0qW47++hIMb/MShRyk1XKE1D mstMd6gJOV7O7AFH/YXEkhLaT6fHmRpSS5ZfyAlBDZnbS00LRix3qNvIbWZkW4lRJYPlkRkxFhcb RYzsz6BkfpLzIdFTK2oGci0NpQn965BmDkqoD+QWUAvzGCkzwny7yLUEx7TCcRXcW8AL/kJpX3R1 ipFVQb3+/45zI0udzzr5i9vEncXxb0pc+aY0pcTVvMp4w93ibjF6S2nNJUjn2OHytG7396XODxXG lhUfz0/+Uknd5Yzd7vfu0RDuNsfHweP0OiMxy8jcCvSOsveyOHe7X6Htm4IU6DYH3LUhhLmAueKI eyiIEisoe6u7le9B6dGJ6Rwzc1A8awDu28e4+ECorndR88vQtT8okdNoXEFUu6ug9Xy8zmd73S9N WFF7OM2+wlg+y+bTjEb4flVv3i6llptyRp17JcuooKQtjy/K9IrfxhX1JT5LL3V1OWvzy6tU4pHa aVn1XRk9ao073b2n+Jx6mOWclmfkvlrqfEcF6Uq1173K7WVCjr9b4sq75gD3V8z5yRVeqXXHPWZx 4VkzrtscrD+42Sfz3YA7neNzIc3mG89zg1PcV/hsNY7c0Lgzn2WeOZtU6ahn5GKeO5Bx6NlMmQO/ DJRlQZTljsPTzGPadPa7jP4AhPR1qJbc4G+ovDluDrSTAH7HMYcUnxucXqru3aXP3N3M37sKZp7N XMnpny8pmucuRqv2ux+jH/Pv0sKZ09XFteKaO75HS80sbPFS+anXYi2V1J9d9LzLuWr6SC7SzEG/ S2Ud31AecuPQE2eF8uei7YY6h/38yuYB0NcHIjRHcF58YPG6avhPauUNX8G4VM3cy2oyZ+Dmo+cu rPDq4eA7m3JQvunvC2lhuTptheWV4xYWO6rtoK0ZTj8aZurffJw83S70Xv03mYUJ9ZkK3pO4XzBG KNNrDD307i6Y/zdqfe07oJgvcGz6rdvxm7kraqWU6sqHhcVzFnsWZ1xGcf21MrcGbWpv5XMR5eZa VnTUsP7aGfWKvZ2sQq7Cf1HjVjStsI4KRuJyx+hUaNCp8PXDqpPnC0PaT3IRpQJ3dlhlVu6SuZ6M MMrKKPtmq1bc6Sn1v9GFN79WVh4GZ4Z617huczxak0IgHb+k5IoskoLcWqQ9FdroVZmLKyg/+9Rp zqyDLvJj+bO2YeY/VMMGJFdUt3vQPViuHsX0WnC1NG/hruc3x4cquMqjGHpdSNcr/C0c3crOp5+i vrwSs2rB9xc1/i+huf0KcIO7L2THWPCu+UBxOse+q4kFZRC3nsmZpNpx4SPa4nfH3Ct3ewgL5CL+ GeOBue41xd7aj6uQLw6V39dK0iGxdsO/7L6N4+VC2hx3kTvbXeG+UCJnnrsUaYveSpqZhHOp0DIZ uKXUG48ydRe9e9uF/lzLVsFoX36h9eNBRk6hWoy1V5hl9Dn5ixtX8HaS34YYu8FUPtvDsy0F7ztK aJ14Drnll8hXzZziLncK6zvBOcil7EeB/g6fT+d2ButbxqGZERxbQXmr2a5ioLFr5PNAsWtLubSc gjmdku/uGXOuM7aiFTb2TM7TGv11ceFZNupWfH+C92jgySNuZMh2chnfF/jQs1jGs3Z5hh6aFwzq wiY2p1IbTvOGOQ9cZJ7X+UwJPospwXfI/LRW8zyteRudy73AWC1dyPOqxWoLlTcXz34xzyO/wM+w +DztfL5urIWCM8B7SrTE2ADs+a95FiXfwuSUmjO/2Q247YP6Or//28Wclspn5imsY1rIDiFofcFh bmUzqfwUmauoYM48yAFmjjzYsxcx9wafdHCG3TznCXythI0HU/LcJ3l2PS/0JLOL11Wq7pWlzyq2 JznTrognTpmySAop/v+fFVg74InsYG4PE+lWhKP5zXDwjXDwjYI5z3WXhJ6aoZsxP7ecO2xmplcb KXRmZtPPrCu0917Mkml5xfNaxUZMYwu3FHfxs3LTrXHb1rxNGBnyeLRZaqzVcSyv/N1pwVML8XYl o1ixPFMKaiv3ahj2nZWWHrLe5J57IDiOuTNqVma59ZR+53EhpVEKDo6HeLB7jWpAGe7bOD6sYr5g 3wpLawzxZpjfzlTVFWrwBb+lvgyrMN969DwjmzcU2JmUk6bgm6HZ6Kcj+GkX9Sjpzi5Mt7P4m6rq OHeb0SZCfPFIqHctdT+qNE+JZxae/UHB+FjB1Sq//S+Vf1kxTWfP6eOLcmrOIsMdwf6cRRK+dt2N xepaXNj/J8GPwxGUNpEn15/Mh5YWWdqKLUzXHTyddXK32UuA44uLeljVXbhtcJuVOs8x1mtuzun6 mvP0uNJvlfEs8k+uB0dFnjxUrQKzcP8buA04nsLPIqv6rQu3DeU8i/z/+8+iyJ38L3hPeDKsN/A1 4bxSJe1hVFbRfBR/LVL2DWrRVyTBNxnhz9vyyFHRaC5pGkWQGasG0xDqR0PpDhpAM2kWTaW7aS5N p3n0At1L/6DVtIA+p3x6j76G30wH4LfQQSFpq6gjouiQqCca0PciVsTTMWGLNPpJdBDdERsgBosm Zr0T0UIME9eIVDFZzBQ54imxSIwUO8VecSWvaDKJVzSZyiua3MkrmszkFU1m8Yomd/GKJnfziiaz ZVvZVszh1Tju8czxHBP3en6y48XPtm1radtJdrL02pPsSdKxr7WvlX77OvsmGbBvsW+RKfat9gzZ hNfVaGXPsefINvZ99tOyLa+f0dN+0V4ue9sf2Svl5fanKllO4FUx3lBNVBO5VDVTLeSbvCrGf3hV jHdUB9VBvq8yVab8QGWrAXKZGqTGyDw1Vo2V+WY9DPmVWQ9DfmPWw5CH1M3qFnlEzVB3yqNqlrpP HlcPqAcsoR5UayypPlefWzlqndpk9VRb1Farr/pSfWn1VzvUTmuA2qf2WYNUvsq3BvNKGEPUt+qg db46pA5ZF/B6GMPUCXXCGq5+1ZY1QtfRHusSXv3iah3QydZknaJbWjfq1rqNdRuvfjGNV7+YqbN1 V+sufY7ubt2je+k+1r26nx5q/ZlXv3iMV794XF+l77We1vfredZHvNbFGv2Enm+t1Qv0Amu9fkY/ Y23QL+pF1ka9RC+xNuutequ1RX+hv7C2Ovc591vbzBoP1pfOI84j1naz0oO1w3nKWWDtdp51nrf2 Oi86C62vnJedl61vnA+dD60DzkpnpfWt86nzqXXQrOhgfedsdDZah82KDtYRs6KDddSs6GD96O/p 72Ud8/f2D7ZO+C/wXxAh/SP9oyIs/xj/uIhI/3j/+Iho/5X+qyIakBSHeHWgLlQH3qJI+AiKgtdU Fz6S6sHXpfrso3nv34bsY3glIePjKQ4+Gr/xZJMHXuPXJj8QrULc+ATywncls1PV2eTAN8Z1P51D AfgeuJ5AOZQI34SS4I3FX0u0KpVaoQ2tKR2takftUVIH6gxKF+qG9pxDfVFvP+qP9gyAjwXvDkQr DPfGg3svRCuG01jkuhQ+ksbReNRzOU1ASybSJLTkapqCltxEf0AbbgWXN4EEmIHa/whvg/vvQN6Z 8OmQAbPQgrvh02g2fAuaA9+S7oFPpT/Bp0My3Iur98G3ovvhW9MD8Gn0Z3oQVx+CBGkHCTKPMukR +Cx6FL4T/QU+jR6DP4v+Cp9Nj8ObNdOeAGU+fGd6knJRwvOQPi0gff5BzekV+DRaTP8G5Q16C214 m/7Da219BPrHtAJtWEmr0IZP4NN4pabmkFurEf+cNiDlRtqO9uyAb0E7aTdatQcSLYslWluWaJ3o IB1D+uP0M1r1C7l0liDIuM6QcXWonYgUkSREFOSd5HWflKgv6lMdES2iKUo0gASsBwkYSw1EnIij GBEPaRgHGYhewqtCKaGFJkd4hRdxn/BRQDjCoUThF35KFgERoEYiQSRQN5EoEqm7SBJJdK5IFsmU IhqJRtRUNBat0IbWkLB1eF0pJTqKroib1aXqQdoORO2DxCDUPlgMRu1mpak4SN4RaINZb0qJy8Rl SD9emJXcrxS/Q+2TxDWofbK4GbXfIm5DvbeL6ahxhrgDNd4p7kTemWIm8j4lFuA+PC2eppbiGfF3 ShfPiucoTeSK56mVeEG8SK3FQrEIlJ1iJ/UXu8Ru6in2iL2IHxQHaYD4TnxHg8Qh8OFAcVgcpsHi iDgC+vfie9CPiqOg/yB+AP1HcQy5jovj1FucECeor/hJ/ER9xM/iZ+onfhG/gP6r+BX0k+Ik6K5w qR9GEUm9pCUtOk9GyAjE68g6iEfKSMSjZBTiGGOogxljKMOMMYhjjEEcYwziGGMQxxhDSWaMoSEY Yx6mLp55nico0jPf8yRFe/7meZa05znPQvJ5Fnleosaelz2vIv4vz2vUxLPE8x6le973rKAWnpWe VZTm+cSzltp51nnyqL1ns2cLKFs9OxDf6dlNZ3n2eL4j4TnkOUZ1MJIRKXSZSPLaUXZdamTXs2MQ j7XjKQUjnE1n22avlU62tjUlY7RLojQ72U6mNmbMI8uMeaQx5l2P8Pf2DRRt32jfiPgUewpF2jfZ N1FdMxbSORgLb8XV2+zbKNa+3Z6K+DR7GlJOt6cjPsOeQX6MlHdSkj3TnoV6MV5SM4yX9yG8376f OtsP2A9QQ7MmFbWyH7QfRPwh+yHE59pzqYv9sP0wyplnz0OZj9h/pcb24/YToM+356MlT9p/o/r2 U/ZTqH2B/TTS/N3+O0p+1n4WJT9nP4erL9ovkm0vtBch10v2y8j1D/sVlLnY/ifSv2r/ixLs/7Ff Q8lL7CX476/br+Pqv+1/oyVv2G+AstReijLftN9ECW/Zb6GEt+13kfc9+z1qYr9vvw/6B/YHFGEv s5dRvL3cXo5/+pH9EfJ+bH+MklfYK5Bmpb0SeT+1P0WNq+3VyLvGXgP6Z/ZapFxnr0MJ6+08lLzZ /gIpv7S/xH3ebm/Hv9hh70Or9ttf4Z9+bX+LWg7ah0A5bB/Fv/vBPo5cJ+yfcLd/tk+ifFdZ1FVF qCg6W9VVDaixaqhi6BwVq+Koh4pXHspBF7CpiVLKS82UTzkUr/wKI4wKqAAlKHiKVokqkWJVksL4 opJVMmmjzVA7o80gbKaaUZpqrpoj3kK1oJZGs6HW0GzSqZVqp9qBDv2GOhn9hjpDv8lG2Fl1wdWu qiulK7O+cZpZDQwpz1E5iPdUPRHvpc7D1d6qN7VQfVRfSlX9VD+U3F8NwNVBahBKGKwGo7Qhagiu nq8uQPph6kKkH65GoJyL1EikvFiNokw1Wo0BBRoV0lymLkOu8Wo84leoCUgzUU2ks4x2hfjN6mak v0XdAsoMNQNp/qjuBH2WmoMS7lH3oXzoW/inD6oHUe9D6hGkMfuOpZlVyNDC+eopxBcojD7qefUS 8r6sFqPMf6rXKEstUW/gbixV/0Gad9S7qOU99T5lqw/UMrNGp1oOyofqY7RwhVqBElaqlUi/Sq1C mk/UJ7j6qfoU9NVqNbVVa9QaamN0PlDWqXUI16v1aMMGtQElbFQbkX6T2oQ2bFFbEG5VW0kajZCU 0QgRQiOkKKMRUjejEVIMNMJvyWNWSMNV6IXkGL2Qko1eSE3NOmkIXS2pgVktjYRZLY2UjtT1qZFZ Mw2Uhroh1dExOpbq6TiNUUzHaw/SKK2pqfZqL+gBHSCPWVEN6ZN0MtKn6CZI01Q3o4BurlugtJa6 JUnomq0Rpuk05G2j2yB9uu6AlBk6g1J0R90RlCydRXG6k+5EydBEs5G+s+6MErroLrjaVWN0g24K zUl3192Rq5fuBfp5ug9S9tODUNpgPRRphulhFKUv1BeihWP0WLT8Uj0eJV+lf4fWTtLXIuVkfR05 +np9I0qbov9AifpWPRX1TtN3oMY79Uzqpmfpu6i7vlvPpnP1HD0HNd6j70X779f3I+UD+gFc/bP+ M+gP6gfRkof0XNTysH4YJc/T81Dyo/pR1P4X/Rfkekw/hnqhK1M7oysjhK5MHaErv0hpeqFeSOl6 kV4EOvRmUKA3U5LRmykJevN9lGZWSKN2RntGCO0ZlMecx6iV81fnr5TuPO48jjg0aYTPOs8hTa7z PNJAn6ZMo09TltGnqaPRp6mz0adBWeusRbjOWQcKtGrkhVaNvNCqEUKrpnbQqntSC38vfy/Ee/t7 U0t/H39fSvf38/cDpb9/AGX6B/oHUpZ/kH8QdfIP9oOjjf6NNCP94F//xf6LKc0/yj8Kecf4x1Br /yX+S0AZ678Uacb5xyENtHOUcKX/Sjrff5X/Kuh+Uk5kHb0va+exrInHhrRwo23Hsp4dyxp2P9aw +7OGrVnDHsga9mDWsM9nDdvPGnYia9h9WcO2WMOOZa06FrmNPj0cGnMs68r9WFfuz7qyZl15MOvK ftaVE1k/TmL9uDHdBc04mzXjdNaM27FmnMmacQfWjDtCL34AlD/DZ0EvfhBa5kPw2dCOMUbSw/DZ rCVnsZbcjbXk7qwl92AtOYe15J6sJY9nLbkXa8m9oSU/iX/1N/gkeoqeQzwXGnMSvQifTQtpEbWh l6A3Z0NvXgwd95/w2fQqLUH8dWjS2dCklwJlvAl9uh3r05nQp9+hDHoXvgPQ/nLEP4TvAC37I7Tw Y/gO0LXNuuor4TOhca8C/RPo2Zn0GXwmtO3PQVlL66DNr4fPgua9Ec91E3w25dE2xL+AFp4NLXwn ru6Gz4Iuvgf/fS/tA8rZD728G30FvTydvoFe3h16+UE6l76D70GH6AfEf4Sm3oM19Z7Q1H+h8+hX +Bw6Ca39PGEWtektJHT33sISFmWxBt+4mAYfLeqKutCS60F3j2bdPUY0FDGIQ2NHaPT1GNbXo1lf j2F9PZr19XjW123W1xXr6wNYXx/E+voQ1tcd1tcToK83pgiRIlJQbxORinirQg1eijaiDUpuK9KB H9qJ9ohnQKevB52+I9UVmSITNWaJzoh3gZYfLcyOd3HiHOj6MaKH6EH1xbniXNBzRA70/p6iJ+K9 RD/E+4sBiA8S5yO8QAxDeKEYjvQjgASigQQuQjkjxUiUc7G4BPGxQAUxQAXjcfUKYINoYIMr8U+v EhOg/U8ETogXVwMn2OJacS15gRYm479fJ6YgfhOQg2LkMAjI4XbgiqliKu7ANKCIAFDEDNyHO4Al EhhLRDOWqCdmiVmI3yX+Bt39KWCGdMYMYxgzXMiYYQxjhksYM1zKmGEsY4ZxjBkuYcxwKWOGsYwZ xjFmGMOY4SLGDBczZhjJmGEUY4aLGDNczJhhJGOGUYwZhjNmGMGYYThjhhGMGYYzZhghG8gG1FXG yBg6W8bJOMQ90oO4kgpxr/Qi7pM+aiQTZSJFykayEcIWsgXCdrId+WSmzES8q+yK+Eg5kkbLy+Xl CK+QV1AdOUFOQDhZTkY4VU5F+Lh8nJqZdXKphVwgFyB8Wj5NqfJZ+SxdIF+UL1IT+U/5T4Svyldx 9U35JtK/Ld9Gmo/lx9TarJCLcL2EViE3yo2UJvNkHg2T++Q+UPLlV9TKrIpLaRYcNTXr4VJzq55V D2F9qz61tBpaDWmo5bE8lGIFrADCBCsBV5tZzZDeoKPLrK5WV2pkTbWmUh/rj9adCGdZf0L4hvUG 9WHs1BcY6VXgJYOO/EBHSyjJ8zowUjIwEvQnzwdASm2BlFZShmcV8FIH4KVPQP8UqKkzUNN6xDd4 NiGeBwSVDQS1mXp4tgBHmRV1tyH+hWc74js9O6mXZxcw1XnAVHuAqfYCWUUAWUHb9hwGvqrrOe45 Tg08JzwnQPnJ8xPFeH4G4ooD4pIUY1t2HcQjgb5igL6igMTqAoN5gcHqIx5tN0Q8BnhMAY/FkmPH AZUFGJX1Z1TWnVGZbQfsROj3Bpt1YGyWbk+2J0P7N0gsljFYQ/tm+2bEDRIbaE8F+moI9DUdFIO1 +tt323cDFcy2ZwMVGNyVyJiqL6OpWEZTmtFUX0ZTFqOpII6KZewUa79gv4AyDXbqy3gplpGSZkSU yIioL2OhWMZCfsZCfRkLxTIK6s/4RzP+6WuvslehtE/sT3DV4B8/45++jHxiGefEMpKJZfTSj9FL f0YvmtHLQEYvgxm9nM/oxc/oJZHxSSKQSRPgnKaqKXRlg0w6MzLJVqkqFfp3K9WKujA+yQQ+aQtd PB0oJZtRSmNGKd1VR9WRejFW6c1YJRtYpTPSdwFi6cSIJZkRSwYjls5ALOcATXUHbjkXiKU3rvZR faBn9wViac+IJZMRSzYjlo6MWLIZsbQHYjkfZQ4Fbklm3NKWcUsG45bOjFsyGLecy7glU12qLkVe g156M3pJUpery0ExGKYzY5jz1O/U75BykpqEf3e1uhr/6Bo1GWmuU9dBv79eXY+8N6gbQLlJ3YTQ oJ0sRju9GO0kMdpprGaqmWiPwTzZjHnaqvvV/Ygb5JPOyKc9I59MIJ9HqYP6i/oLynkMKCgDKOgp 0BeoZ0D5O1BQJ6CghWjhImChLsBC/wD9FfUKUi4GLsoCLnoVbfuX+h+g09eAkboxRuoOjPQW7u3b QErnMlLKYaTUk5HSeEZKvRgp9WaklMlIqTsjpZ6MlM5jpJQEpLQGbTYYKUmtVWuRZh0wUiZjpN6M kXLUZrUZLdmmtgHxblfbgYJ2qB1UT+1RexDfr/YjNBhpAGOkaHVAHQA6Oqi+A92gI1sdU8dAOa6O Ay8ZpJQApPQrUrrKpWioAAJhEC9F6AhgJ4Oa4hg1qWKoSQI1xUDvjwV2imPsVB/YKR4UDxBUHBCU QjkGQcVpn4YuwTgquhBHJVFdnQw0Fa0b6caoxWCqOMZU9RlTKZ2qUxFvpVshjcFUCSFM1Va3BcUg qzhGVk4IWWXqTNRukJVdDE1F6266G+gGTTnF0FS07qv7ogSDqaKBqYagPecDWUXrC/QFiBt8Fc34 Kk4P19Ai9EX6IrRnpB6F+Bg9BvFLgLWiGWvFAWvdiLhBWfGMsmxGWYpR1gBGWYMYZQ1hlOUwykrQ 9+n7kMtgLZux1iDGWk4Ia80DsopmZJWgH9ePI/6EfoIa6yf1U5Rt1t1GaNBUNqOpLL1D7yAfBucI ivQ29DZEONw7ApQN3m9otPeArz7V8U3xTaFI3zTfNIQrfCso1fep71Nq4VvjW4P4Wt9ausC3zreO mvi2+bZRM98B30FcPeY7Dvqvvl9BcX0utTAQhFId6Uhq5sQ7HmrteB0vDXMCTgBILNUB8nDaO+0R dnAycDXT6QSc1tU5G2m6OeeA0tPpiXCoM5RSnOHOcGpu1tGmls4oZxQNdUY7o0G/wrmCmjpTnJtx dYbzR9Dvcu4CZbYzG5Q5zhyk/5PzJ1AMesx2HgBuzHYedoAygB4fRWjQYw8gxqcQLnCeBg78O3Bj NhDji9SFEWM353Xn39Tbec95D/QPnY8QrnQwIgM9fkbdnc+dz4E81zvrqY+zzdkG+n5nP8KjzlGU edw5TjnOCecE9XR+cn6i3owkezCSbOw/z38eZTNu7Ma4sTsjxu6MGBszYsxmxJjuH+0fjfgYIMZM RoxZjBi7+C/zX4b4Ff4rKIdx43jGjb39E/wTKMk/0T8JuSb7J1OG//f+31OPwMbAZmoR2BrYinBv IJ9aB74OfI3waOAYNQ+cCJyg5iT9eWb97sRJKdcAtdTG11s1cz4KfVFRnXf9Za0xg5Y8xex5prkP wd9UsEJ2ocuiBu4Rd7s7+9Tr85Wp41AZm6M0dxO/f95dWPOFbIOfEzqOV/wm/PQ71KxCv9VxadW0 YEurVq6au5TfpubKV+ILs4xTfhflHihcGTlk1eruL94bq2fhafrnKVIUcpSpm3/DsketfefedEZq KWNF5s4sWAWt2qtgbC5714LPrtBeO7f4CmqhdfFS3P6h89lVW2sJOSYixzSTv6CMgpI4XFzwFQvS FbPycsdWtZ7quypbDCpI7aMhq6GgBXCBxaMs6JmVuKpLhrRCmygZOnxVLqOYC9uaLg1yd7abwk9p sznjlux208jnbjZPrlxZkVZShvD4yP85ZNEXrvOZ+1wwMlNh3uDK9mXs6atWdllXkJ/vbBW/Da1o HbhwnpIMpUoxLXAPFn4jl+ZOC7VlqeGEMt/OpYTK95XTn8LoYcH1MIu39MzwG/rNNBwFX675wDGL 3aL75yv1W7t1Hyz+ZLlfncJS2V1V6dUy42AFrgF4Zmnh3TZnB091t90NFacoOw6eylVvtAjpsYV1 hPH9yYWh3zSW52vcXF57LMj9B41tOP77fHcUfktbu/OTQK+U5jsX7p0DEeP76iaUKLv8th4s+Vsr buKpk6C+oOTwldNnw+vFZftg+PIZd7nKuSpsV3jjAj/REiWUp9OXXlGysh1rwvpixDzXojsla/lJ V1RrJXxdUiJXbd0ilujLqytzIUkMR5nvLKqkS1T0vXDYtQZHDMkyu5KV6apRdphyrCJJdqrvt6t1 n1OC4/opVoooD+nVCPvxfV5MBfe5VkflU93ngpUiIaXLTenuLP9e1Lg/B/VaWagNhZevZv057L3A atvh6Rpdz6yvVanWGhr9zJPgsS+0SkcjOsVYGFYbztg6a6dTTocvN6pYbqn+DF284Eqt/5uicaRm /TlsVwszU5XrxRXmWlztCk2buwMPbnI/d3NDZwWl8jp1lcwEpUH3nmG0jGBIYX+1azCv28AtQGGb CzAXI+LZ7o0V6UtIW+4XTCfDmRcr8XSqKKMqkp01Q1MNglKq5N465bnQqgqVfjdbBZdSgMVPMf72 L0Or0VfZteFq0NOrV9/80Mzema43JLtC9Uq6lu1xSDaSjUmY/a/JYqucCNlatqY6so1sE7LQiZId ZRbVlZ1lN4qWvWQvipOD5CCKl0PkEPLIkfJisuVoOZq0vFReSl55ubyCfHKCnEh+s/81JbD9TqK8 Qd5ASXKKnELJ8hZ5CzWSt8lp1FjeIWdRM/mQnEupcp6cR63NXtiUxjY+beQC+Qy1lc/K56i92RGb MsyO2JQpX5Gv0FnyNfkaZcul8i3qLP8j/0Nnyw/kB9RNfig/pHPkx3IldTf7YlMOW/30NPtiUy+5 QW6k82Se3Ex9zO7Y1M/sjk0D5G65mwbLfPkNDZEH5REaJn+WP9NIeVK6dLHZHZtGszXQGLM7Nl1i 1beiaazV0IqhcWaPbBpv9simKyzHcmiC1dRqThOtllZLulpv09voGv2l3kHXmp2O6Xqz0zH93ux0 TDeYnY7pRrPTMU3Rx70N6A9erzeJ7vf29v6OHvHe6L2X3vDO8y6ktd43vcvoK+8Gn6Dvza7HorGv h2+SSDX7HYthvsd8C8QYs9+xuNLsdywmmP2OxUSz37G43ux3LG4w+x2Lm81+x+IPZr9jMc3sdyxm mv2OxUNmv2Mx16nrxIpHzE7H4knH6ySJv5k9jkWu09xpIxaaPY7Fq2aPY/GG2d1YvGN2NxYfmLey YpXZ3Vh8YnY3Fp+Z3Y3FWrOvsdho9jUWeYGNgU1in3nfKPIDRwJHxAHzvlF8ix65gXukZAsxKRuj X0Zwv6zL/VJyv6zL/TKa+2UD9MuO6KPGfkzKLPTRCPTRzkjTRXbF1bPl2bjaDb22LffaTO61adxr O7GlWZa8GH23LffdTO67aWx7lsW2Z4Jtz4SciH5scT+O4n4suB9HcT+uz/24DfrxbVRP3i5vD1mp CTkNPdtCz74DKe+UM5FmFnp5HfTyh8ADc9HX47ivx3Nft7mv+9ieLYbt2fzyGfT79mzV1k4+h96f gN7/AkJj4abBA4sQvgRO8DEnxDEnxIMTlqK0N8EPmvmhPfNDI+aHxmz/1sTsFk8d5UrwRmvmjabM G82ZN5qDNzZQC7aLS2W7uAy5GXzSEnyyDeEX4JYUcMt2hDvAM82ZZxqz1VwT+TU4pxU45yDK/E4e AlcflodRu7GmS2VeigUvnaQO0gVHJTNHeZijvMxRDdm+zrGiwVeJbGWXbsWAuwLgrniExuJOgccU Qg1O8zKnxYLTmqKcZuA3xfyWyPxWF/z2JcLt4LoGzHVpzHVpzHVRzHVR4LpvER4E77Vh3pPMexHg vUFU1zvYO5iivUO8I6iB9yJwYyRzY1vmxkxw4/uU5v0APNmJbSeyvAfAmcJwJllmP3KK8vX19aP6 ZldyauO7yDeJLSumkjS8SpHg1Xcowfeu713ShmMpDhy7jGzfct9ySvJ96FuB+ErfSqRZ5VuFq6t9 qymGbTD8bIPRzrfOtwFXN/s2I9zi24L04G3Ed/v2ULxvr28f+Xz7fftBz/flo8wDvu9AOeQ7Qu19 3/u+R8qjvqMo+QffD4j/6PsRcWPF0c53wneCEoxcoHjIhQhKceo4dai5E+lEUmOzJzp1dOo59ai1 U99pSE2dGCeGWjqxTiyuQnZQC7b0yHB8jh90Y+/RyElwEqmJ2TcdeSFTQG/utAC9pZMKeiunNcpP c9JwtY3TBiW3dzqCYmxCUiFxslFyZ6czcnVxuiBurEQynG5ON2oFSdSHAk5fpy8pp5/Tjxo6/Z3+ ZHZeH0gdnEHOIEp2BjtDyeNc4FyAlMOcYbhqLEkctiRJd0Y7l4B+mXMZwvHOeOSC/EL8Ouc6xK93 rkcJU5xbyOv8wbmNEp3bndtxdaozFeVMc6YhPt2ZjrixP0l37nDuoADkHfgosCmwiXyQensR3xfI p+ZG9lE9yL6jlBj4IXCMvCRFFFv6ZrKlbxpb+maypW8WW/qexZa+ndjSN5stfbPY0vcstvTtxJa+ 2Wzpm8mWvu3Y0rcDW/q2Z0vfDLb0bceWvh3Y0rc9W/pmsKVvG7b0bcuWvm3Y0rctW/q2YUvftmzF W6+EjDbSOaqYdI5iuVyX5XKdkFw2dr11WQo3kzkyB7LAyOJ02Uf2gdQwErkJS+QucpgcRl1ZLndk udxMjpKjkN5I53Q5Ro5B+kvkWMgdI6mbyHFyPNIbed0xJK+vlFdC5haX2pPkpJDsjpTXyGsRD0rw 6+T1iBs5HilvhBy3WI43ZQkeUUKCz5B/DMnxSJbjTVmOR8hH5CPQdIwtcizLbg/Lbg/LbsWyuyXL 7hYyV+ZixDJSuyHbJTdku2QP2yXHsl2yYkndUi6HjA6wjE5kGd1aroJ0DsjVcjU5co38DHEjqRPl WrkWcWPBnMjyOonldTLL61YsrwNyi9yCsWErpHaApbZffgmpHZA7IbUDkNp7EBqL50SW3QnyW0jt AEvqZPm9/B7xE5DXcfJX+StCI7VTLdwKimOr6BgrwqqDuJHd8VYUZHccW0jHswS3WYJrluDNWYLH WbFWLNW34iDH41iON7BsyPE4yws5Hgc57kdobKkbsC11vJVsNQLFSPY4tquOsZpDvsexfNdsY92Z bazr6dF6NFn8hVAUfyEUxfZtdfVevZeaQNZ/TZH6gD6A0Ej5pvqwPoz0R/VRhMf0MbLYEk6yJZxk S7i63su8l1Ed7yQv5DVL/Gbe+7wPUyOW++neRd5F1Nj7kvc1SvEu8S5B/HXvUsTNeNCEx4Mu3uXe 9dSVR4WObFFnRoXuoVEhkkcFi0eFphgVbqQItreTbG9nxobHME48/b/sfftXHNeV7jnFwxhjjPpB FwhjomAsY5kQosFEITLBWMYYY4IJYRiCCSEKxhjLGNNNQ6Chux5d/aruevSLEMIwWGFJCiMThmCM CYMVmcgEK5gQhVEwVmSGyFxFS0N0iaK5u8o/5K77F9x7V7RXNVXV57n3Pvt8Z2uf04YfwacyHySq EXg6NQJPo1p/nWr9M9QIvHsNKzAH3KNa/0Q1Gu8+w+8Nv4c3it1PVCPzNKrFf0i1+Peo9j1DjdK7 T43S06hRejo1Su8+mFIjwJbdRd4Fn4qVV+z7PXB/L1j5JLDyCXCvRPKlqFb+ftXKPwxW3gD3JNh6 g2rfM8lUMhVSPkA+ABY2jfwc3B8Ai29QY/72q1Y+k8wivwDvlfi//Wr8X4pq61PJx8jHIGUe2Ppk 1co/rMYCppBfI78GpRWShfBeiQtMIYvIIqj3GHkM3itzQIJq/RPIZ8hn4FOx/gfB7j8H90oEYRxY /0q4V+II96nWX6ta/wfVOMI4shbmgFiyjqyDNMpMkKDOBAfJ75DfgXslyjCe/C55HO6/B3NDLNlC tsC9MkMcJNvI1+BeiUHcp84QenWGiIUZ4vvwXpkVHlSjEuNJmqThjRKbuE+NTdSqsYnxakyeRo3J 06gxeSlqTF6KGpO3T43J27e/bH8ZSkA4ciFyEWFY8WuUTT1enqgWUoRSoUNYFSvh4sULwmFxW0qW coTDkk8akcaFHWlGOCAUCBVCh5gqFottkGoaUhRJ5cJhISWQFsgLlAeaAr7AZGA+sBGMDB4IZgVm gs3BjqAYnIVrM7gXig5pQpmh7OBqsBvSpQVyIE8r5LkRjA2mBAuCFcFjwaHgqc9SBjsC7cHVUKG8 IC/Ky/KqvC5vylvyTZGX9/zIHyeP+jVCorQhb/pJpf7Q8VCbWv9GqAfqzwrZlNpDPNSdFZwNjISi g6OhYSjxZOiMkCLdkE/Ji0KHv1g45a+XK+RZP+evF3n/Geh9qbwKPR73X/Zf8V/37/pvBwghMRAf 0AWSBw74od9+m3hFnhUHhMNQcwnUzYe2A77Q9cBYOD6cHD4abAYefFZveSg6PBmeD66Gl8Ir4avh qvC18I3wrUD5QOxAQuhKOBCmg3sKv+CbpvBgcD08HhTDM/5cRRL+fPmUP9sf7U/3pwqnhESxUJSF zWAoyEp50J9uoH4xU2gUh8VocU3kxHPSISlPmgRpDQkLEiGwSinCEDx3iCapRLwi1IHUzgt7QreY Ll6GVDsiktKEg9JRaUYKCCeEZTFO2ggUBUqCbKAhUBVoD5gDlsBgcDQwArxdCqwEE4MJwSPBE6pk zwYXgzdDuQp3gdJDqcEUSDUemAzlB5zBxqA7cD4oBujAneByYCzIBqfgW18gI1AbLA3FBS4FjobI wKFAIHgwuB7cCXaHikNlocpQTeBaCAWrg3XBheBW4GrwMORqCMwEbkH73Gqb08Vs8Tj0bUDclpul HKlVoiWLNChUgGZkArcy5R2otzzQAPKvALm3hOTQdIgLzYXOhQbk1VB9yBSa8B8PxEgrAykDif4y AbTBH+dv8/P+Yf+E/6RQIa9KPmHHf9F/QXb7t/2FQC2gJbK/HrSCg7HgFirEAdCiAv+aHPJX+mv8 Pf4B/5z/nDDkN4V1A5HBzdBa6GJoN3Q7nBY+FM4J54Vrw61hS7g9UB72KdILnw+PhS+FN8J3wuaw ORgZzggXBTYCV8MrIS6QAzwHXQhdCF2GEbMavBk8FSbCMeHycEPYGR4JjIRLhCwYfUeEaqFfEEE/ zgpTYrqwLifA+NXIB8QWsUa0yaVynXRJipd04nXxthQjbIIGxEi10pgcApnPw5hulm4Io3KinCKW yUekJqlBJEVSuipdE44JB6Rb0h05Uo4VZsV8OUs+LBfIx2C8VIu74hnxpDghzslDYA14YUo+IXfI 3XK/eEZql92yKMzKo9IKcOiszMqN8pQ8K5nFerEHcu0CCMqQqqQlYUu4KR8Uc8WLMis5hU3VAl1Q rY9PGletzmGwTEPQuxBI/7Cw6D8TzAK7hbVfgZX/iLp3FCEKCKunqhDqrtEI5EEDKBKNojfAyp0G 0qEpIL266zJR3WNpQB8CkegyUJJ6ikky+gRoP/ojUAr6FOh+9GegVHXH4wM4Gj+A0vDDOBMdwdk4 G+Wrewu/ir+Cv4KOqvsGH1d3CRbg5/BzqBB/HVegJ/AL+AX0pHpGyDHchJvQU7gFt6Bi3IE70NO4 H9tQCT6NT6NnVaxbRhQQBeg5FfGWq4j364B4i1EFUUI8gyoB91aiKgII1amI9wVAsF2oXl2rmwAH /hJ1wsp8FVkA0W0ijrgCaE0CtPYJktV1dUBFaCHiv4hdFCZuRSD0AwDvBjQakRSRgmYiHgDsNBfx uYjPoZ8DdspA8xEHIx5B70ZFRUWj96JiomLQL6Nio2LRhai4qDj0ftS+KC1aikqMMqAPoneid9Cv 74m7Jw6taH6t+TX6UPM7ze/QqhZrMfqN9m7t3WhNq9Pq0W+1ydr70e/UvUm/V3clbegO6h5GH6kn JXysy9Z9Ef1B9yXdY+gT9fyDa+o+ok91JboStKP7lu5b6H+oO3+uq3t+/qRr1r2Ebuhe1rWhm7p2 nRHt6cw6M7qje1P3Jvpv3Qe6ixjpPtT9FRPK/hP8iLL/BB9S9pbgR5X9JDhL2UmCv6DsIcHZ+iR9 Ev6istse5+gf1j+Cv6TsBsG5+i/pn8CP6av11bhY36HvwE/rvfoQLtEP6AdwpX5I/yP8Df2IfgR/ Uz+qfwNX63+sP41r9OP6n+IX9B/rP8HfBTy5g5sBQ/4Zn0j8YeIPsREWRgQ2GR4yPIQ7DS8ZXsJm QFD34C7AS0nYpqx4sRew0OexAKvch3AQVrkP4xD5KPkoDgPm+SIeUFa2+Aewps3Hg+Tj5LfxjwBv NOEF8iXyJbxIvky+jH9Jvkq+ii+Qr5Ov4/eVNSdegtVmAP+KDJNhvE3+kBzBfyRHyVH8J/IkeRrf IMfJcXyLfJOcwP+TnCR/hv9Cvk2+jf+bfIecJxC5QL5LRCq73olocplcJu4iV8ldIoa8Rf6FeJj8 a1IE8aiyP4E4nPRU0nPEPyR9PenrxNGk55O+STyu7EAgipLqkhqIJ5Mak5qIkqTmpJeJ55JeSXqF eD7p1aQ2onL/s/vLQLsxUQHrNgWlHEBRCLHb/+eFDUKbYBNk4aRwQdgVCTFNLBGbxFbRLI45p8RL 4h3xkpQoHXTJ0hFXtFQhVUt1UjPk6YE8Z4QL4iGxSmyA1E7RIm6IDZxJypKOiJPw3YDEKmVLQ9Ko cEFqFtOkBSi7VTApJTsPQNmD4h3hCpS8Lm1BuTvSTcktnZJm3ZOuSmlTjobcnGCTs+Vi4YJcJlyW j8ttHOSGNn6WV3bJ8pq8LVULA/4Yf7I/zZ/hP+TP8R+Vc/0lcqE8LZ+B9NAfmZNlec5PyBfFDfkK 1LcsZwq7cqqcLm4It8WrUoFLdre728UlgRc4qV8YFgaEM65zwoRwUbwmrAFn4kWdWCuWA2fGgS8b 4g0pVjogdSjtd8lQQqnUKJ0QtoXrUrcwLcxB+5rEGXFejBEvqc9HxTxHkXBZXBFvAf8uQN8GRFo6 LCZDfccEE3CyVUqQUqQ66J1PDEiRUqKYIbZD2mExRzgnjojn4bNIkGWNHCeT0qK0KonSWWlPCklT MpJb/HnySTlfzpUrgVMtco9skm1QQrlUKg9DrgmpTr4sX5cv+OP9OuDkgDwglsjHHRvycTHNHyPz Qo+/SNgWN1xxUMpteddf7q+Sa+R6bk5sF2Pkc8Ia8HIQZgasfVj7qPp/GE/B3HA/3D2EDoLVzwJK QdlA96MvA6Wix4EeQMXoaZSGngU6gJ5D5ejz6FtAD6pngWWg40APoWagg6gd6GFkQf0oE5/Cp9Cj RArxGMoivkwcQSWqP7mU8BB+sPFB4gzY73HiTdRCTBKT6AQxRUyhV2FN/zZqI94h5tHrURFREagz 6q6ou5A56u6ou1FX1D1R96DuqHuj7kXfj7ov6j7UE6WP0qPeqCeinkAWzb9o/gX1aU5rTqN+dees VWvQJiGbtlnrRYz2B9ofoJ9oh7RDaFz7z9oR9K/aUe1J9KZ6vs+kdko7jf5NPcdnWjuvXUJvaT/W fozO6wy6B9B7uju6O+iicvwa+rWe0BNoRQ//0Id6Uk+iVVg3X0a/0X+k30S/U1fA/5H4xcQvosvq 2vf36np0w+AxeNBH6np00/CO4bfoY8PvDBvojuFjw8c40vAHwx9wlOE/Df+Jow2fGj7FdykeRRxj 2CUJfPf+0v2lOBEswTGiTLUEiUoMiW1DubCBixXq7COACVhmXahjp/lSvllYZNY9I8KWqAF8qOEW vJmAmIvFSsBB9Wy6eJyLZTX2Ea4acPEoXyosMOuOSg6wkpjKbCophS2uWswX25SyPQ3MTYEVj7PT ogbSLrJILXkYyk0Qs31LYiET8m4DnpkQp0UTYG9elAHZwPoBcjcLdcyWuAb1TAlucVtBXp4RpSQl r31ELATs0yDWc26pXTIDWSSa2XNkAwJaEC9KeWw6s6n0B1BbsnRUWJbKRY1Uy4REDd3ArHMFXKmo YdYBpZVBqxFg/zihUWhm9uwjau86hGZHrqgR3ApnhBCfpbRf2FT5ki4i+xKzqbRfLOSOAC0AX7IE UWxhpoRuYVVYF3aEm/YVqEF5nhLOirnQh2gxExA3y8XaR6DmQtos1InFLBJYvtnexC2w6ey0/Y79 jpjNLQBaWxaPg2xOCf3Asz1Ap7NKyxQCxJ4p9gh74pxos2eI58RtZk/MBl5VwmrEDZhyGng1ASuW NED1hxROQcnpgElLxFypnesG1JjBl3KbkO42pGrnVlkNcDULWrvFbEmtYj2zx0WKV+x3AOPq7Bap SHBLBAerXkRoH4HR//ex///U2I9uvGtVGfv4LHoRIcuVv1//d19EtWeP1/S19Jfwc46V/ipqieet N/kab05/Tn+e1+kN8G3eEUgTzWv4dK6tj+PX+qv4XUhx1FvSn8NfplZ8o8yAb9a37tsTou0LQq5Q LJQJNYA0bMw0W85M04cBo00zuUK0MAcIZZiugDxDzAB8rguZkL5QqPFtMXHMNGCiz1LaqBVhmC1x +3wHKCfP+w56myyLlLO/ypflieUv20jfYfuiR7SlutT6hXNshm+drrAvMGVQXhmbp9QuXIcSd9ly 35ZSq3AbPk1MsWevj/Mlusf7WnwVfL73BpSe4s6z7PRX9Tuh9xpbNvQ44G31sf0ZXl8f73NbFn2i L+Q70IdcuXwNVUQF+oZtXH8R1HzKNyrGsA2+dTHNXsBcBOxVJZigFWq9zADUGCcGhGnAVGMqRjsv LomDdIe4Yl8APNYiWqC/wC+mB9AeLexC36eZNd8xr6W/ypbaX2I95jvg2vUdsZ6wLPJn+G1vk9DC cN4cYdp+yn6Kyefa+NS+Gt5mDUHLb7vveHOoGe8IX89X8vl8Zn9Jf5V3EJ7TrYe9RW6nZRmkNsib PEf4CZ73Enwb3+PN4JE3zzvipa2z1iM85xHZq75TwgXflO8s9G/Bt+jbZDjfKMhWI5BCPrS2EhA5 SNZeAcj1pG9H5e40IzMm3yZdAc83hXO+VRVRg0R9y0I2dc1eAGUp365TK8CVesiRygwwudQGswa9 zwepDQsXhTW2VbgMGjQhHBdaBBn0Jp0BbfFNCYiOtM569qyN0OYBfpi/6FixcaCnx0FPa70Wa4G1 gi/zxPoKgFsFNhm4OOCbUi4o94r9GB0JawHCt8WW8zybAdi5zNcInGp168QNXzWf319lPWbL953w ddsmbNOf6QDQtq/Ce4nX+Ep9pfxlX4qVtez4WHceHw3jocymaJHOVukN+Or62nzNvg6e9PVbG20m MU8cY8tVHJ9hLxCLxBKBFMuFdHaDKRPbVa0YBqw9COh7XJxkZFjTmIGvu2ItWyKki2P0jm/Ifsy3 w0yL8cAf4C6UdgnWPzmw/mliM0QnaHybrYxacqzwpMPHZ4O0C20T/IQrF0bFKsh2xprCn+Ov9A17 V7zj3rT+MW+MN96b7G3ia2w2b5XX54sEmY/xZf05MKI13knLDj8Nbxq8tbzMy9aQu4SPs1bY0l25 UF46X+wo8s5bK/pyvee9S65d6w4V4K+7fXycLxbGTZX3kveqLdt7zdsK1O695b1j3/IlwBhKtB3v d3o33O2+FK+Zv+D22eJgzOm8h7zlfC7fAm0f4E+6rntvQFnHFQtELSnWx70CIxCsDmh1Osg8n8+1 zoKtqel3CruACL6Kx/E4QngCTyCMp/AUIvAMnkER+Of45ygSv4vfRVH4Pfweisbv4/fRXfgD/AGK wR/iD9Hd+Lf4tygWb+ANdA9BEzSKI1iCRfdGZEVkofjINyLfQPdF/jjyJyghciJyAhkiVyIvITJy PXIdPRC5EbmJ0iKvRm6hz0d+Gvkpyoi8CYvdhzSva15HhzVGjRH9g6ZT04lyNV2aLvSY5vua76M8 Ta+mF31Z06fpQ0c0Vo0VfUVDaSiUr31c+zj6qvZ57fPoqPYb2m+gx7XV2mpUoK3R1qCvaWu1tahQ W6etQ09o67X1qEjboG1AT2obtY3omPZ72u+hp/Q/0/8MFevf0r+Fnta/rX8blejf0b+DntH/XP9z VKr/d/2/o2f17+rfRWX6X+h/gZ7Tv6d/H5Xrf6W/hL6RPJs8i76dPJc8hxqS55Pn0XeSF5IXUGPy ueRz6LvJ55PPo+P7v7A/G33v7367v/vt/u63+//VbxfdHN32t9X66znKFfEwt2xZsVVbVhzIoTHT jmzLWJ+776ajzdFja7RYHCd7bxsPWWMcZ4xOx7Rjjk03x3c1w/t8yySkqu+9bmt0cNYYeDPsWnac 6+t2rJmTHS1ujeN235Az3pnmrnG3mQrcw+45R3HnmpMw6jyEg/TEG9McPdSaY81x2xhwxrjLnBm9 1526Ljek5R3bzGhnqrPc1Wgs92RYGjxF5lumLL7OfYE/aJmxrvD9ngxHJT/Ej3bVmS30JVMif4o/ S6VTV/hjnnlbgmvBMsN38Cc8GbzbbPHMW8bpDDqPW+69bVli000L5nhHNm1ReuqcdI47ekwdtMU5 Tw92TVljjFf78x1z1qPOJafPTDvHu2J7d81XnZfcJuc16rbHxzTTec7a3onO1N7rnoCznRqg75gK HMgzxrZ1ZnfaPOPOG55J5x3PjNJ6yy3zuKeo/zJfZ+vn1vmD1IDSelMitGzB0mDUmS29E7YD0PYe fpFbpune265E04LroPmo63B/pusItC77s7bZql0dLtZ61NpuCrlEa6u1vbPNFTLf6kx35LpGXQdc 3VQcm2oZcx1zVbv6HXG0hU13LXdMGAOWSXMym9+55rnquUYN8JF8rKnA43QP93Wbkz0615SD5A/y WaYEpruzjD/sqGQz+SN8ATNqm+o82TfkucMnOm6b88ztljxm0dVoqTWW04OeInqeX+dW+RPUcehR nSfDiywNphSzxUsyZ/mz7jZvpje7Y9qb6803DnqLnUSf21hEm7vquPW+SFusN87YDnlSHS10rbnc eNV5y7NkNHtGLEueFeeGK9J51RXrOW+2UJldo6ZRB9kxYUukztErvbumg9Y0z3zfrGWGSufWHcOd J0F7LXQ8t9W7a2vsYkGH0ztrFNk6TKCbPLNoWaFHFMk6JswZzCbIPtoRZ5vidriblkHQe1vXWUeq +lTlKHYMmI86ZG7ZVu2ogRyZNO04w62apth0R7bjuOO4acqR66jkNh2FjnNAF5lEesPdA/o77YwH /W13DzhL2B5jrSfZmOaO66ru23QepWdcN92avk1PGlPhPNR10H2O6acbOnn3BY+OXnFnOy22Ucu4 k4byYDR0rvVuu5b7jjiT3bddO44Jdy7VQ5dYavkpY4653DPPIlMCX0EvWTeYCr7a5FbGBN8N+iSy LY5i8yX3bXM7U21Koa5QVzrPdPLmGL6U2+s74mjhWVuB4r3i9vhGRxkfoosc0a5G21nTKIyhW8Cl Sx6nZZJKdy1YrzmGnZauOtOUsclVAXU3G3NsFcCrC64dasBxmdp27TmuO3bd6TDqS52tjmH3cXO7 p5bbMud1naCQG9mqFbl0nnTOOM97xjzzyij0DLoSPBmeDGOOcvVOwJju6Oo3VfPLwLmAc8Sx5qyl x/hZGHuDzjHnivmWZcaV4sqyDPYddG7Qg646y6SruXMXyOYSe6+DLo65Sh0XuppdQ45o2uJyu065 zhpvuApcFa4T3FYXC/JscV+0rLCFnhuuBdcCt0i3mkfc6e50OoeZdc16LgHXe6htNzK38wfoSdei Z8Nzi08wJ/Mprj3XumXcG20Z41f5TdeCu4yOB07c7NwGO5NuPORa9RbyezCmj5kHey+CLqfbdrxl 5qv8Fr9D13o11g06zbXqWqcJ4yHzTOeaabF3wk3S5Z5D7nwnwYxabjhz3C30mKfKk+NsMg+aD7kv GsuZCk+re80T4zR7zO5o83lnq2nUteV0GgPMKliNEnelZcVZ5axVvnFc6c/vynJfduY5M2zrVKq7 0JNnSnBtgs2Jd+daJmGM3nAXOy007Sl3tIAEjrptRqebc8vMTVOBCUa4p8HT1FnGxrmvuLedRdS2 p91joZPNPsW6emiwEbm2OmrAfd1xkRrove6ud5vcZ2BcFbI9bIs71Z3pbKDp/gH3SfqSe9epc0/Q g2Cflf8bIiLfipyBWeY3gBiV/SvxgPvuRgeBklSPXrLqy9uPngZKUX1596u+vFTVl5em+vI+p3rx DqA+5ECfRy4koSzkBwz6GCDQN9BX0Rn0E3QUzQIVAAI9j76mYtAn1F/DKEK/QsvoSRWPPqXi0WIV jz6tnrRbgiNxPCrFCYA+v4kzAX1+T8WdTSrifBE/A4izWUWcL6mIs0VFnK0q4nxFxZonsBVQ5qv4 FKDM11Sv4uuqV9FL5APKFABlPgOI8FmiHA0TFYApR1VMeZrwED70LiESfvSe6nN8X/U5fqz6HD9R vY1bxBxxDv2ROA+48wbgzk20qyBOHKcgTnwvsU1s4/sAd/4JJxA3ib9gLfHXCIT3A+K8Fz8QcV+E AT+i4E58WMGdOE9BnPjLEQ9HPILzI5YjlvHjUTgqChdE3RUVg5+MuidqH34qShulxWVR+igDfk7x XeIKBXfi5xUPJq5UPJj4Gwr6xFUK+sTfVNAnrlbQJ/5HwJ3JuEabok3B/6Sc/olrtc3advwtbYe2 Czdpv6+14lYtpfXi1xWPJ+5XfJ3Yqvg6MaX4OjGr/HYBtmvnte9hTvu+dgn7FF8nFnUGXRKWdPt1 KTigS9U9iEOAaA/hYV2WLhu/ocvRHcZjulzdEXxaQbT4rIJo8ZvKyZV4QkG0+Ke6el09nlTOmsT/ ppwviad0r+ra8FvKLxPht3Wduh78js6is+B3dTadDZ/TwXIV/0LBuPi8bln3AX5POYER/1K3qvsD fl/3ie4a/g/dju4m/li3qyfwtop3/6ycFo9vAdJNwnsqxv2rchI8vgPo9gj+b/1R/RPEXQq6Je4F dCsQ8XpJLxP79AH9AKHVD+p/TJDKKX5Euv60/jTxoP5f9T8lMhQfLvGI/iP9DvEFQLf/RXxViWkk ChV/LvGE4s8lihR/LvGkgnqJYwrqJZ5SUC9RrKBe4mnFz0uUKH5e4hnFz0uUGuYM88SzSuQhUW74 heF94uuGZcMHRLUSbUjUGD40/Ib4JyXinKgzXDZcJl4wbBg2iHrFI0x8W/EIEw2KR5j4juIRJhoN twx/Ib5r+CuJiRcBYUcTrUpUIdGmRI0Trynx4oSR3EfuI0ykjtQTnUokIdFFJpH7iW4ynUwnehX8 TVgU/E30Kfib6FfwN2El88nHCRv5NfJJglV2ohAuJd6P8JJl5POET4nxIwJkNfmPRFCJ7iPC5LfI F4gBJa6P+KGC0YkhBaMTP1IwOjGsYHTin0kLaSVGSIq0EydJBykQp0mJDBKTgNcHiLfIQfKHxNvk MPkG8Q75Y/IU8S4g9UniPfJngM7fB3S+SPyGvADo/LKKzjfIi+Qq8RG5Rn5EXCU/BnR+HdB5acS+ pLKk5yL2Azr/ZsT9yhnwEenKKX4RD+4v3V8G6z6MnEj8G/5+8ax63av+LlIm2MRcsGZFqBRVoBpU j5pQKyKo5r48FEE1UkPUFDzVtsTBZxU1A+/Ke3OoMXgqpqbhqZDqgb/Ei7XUERTxYhV1mDoB3x2i AvBdBtVA0fCUSrXAE0lVwt+/WWisnkeNEI5cjtxQW5eqnA74ou5/v4jq7gSqwzxHTVE3qVgjSTXS hR17rzTQ9V3z1CI9YRqkFo27kKZZSdVFG8lXDhlJOg5StNE9XfNmmTnPXGJusJHsAbaAPcY2st2s mxXZIXaWXWS37HH2dHu2PddeaC9mluz19uP2FrsJ8qxAnljI0wzpWUh9ih1lt9i9z1JCzlh7qp1n Mqy7L9W8ft5msRaaZhiomcnpSOw7aqrq2mCO0uc6E5kipX77hH2aPWA3Qe1bUJ5oP6fUbr8IT4v2 OPYIlBlnvwJ1b9uvdyfQaz23qFjzHNNAjTKtL22/NsTQ9BUoOw3k0cGMUIumQabcSFo4C9czzsxY b3eyzLyRNA93sq80MBbGx6TRqcw41HyNucTFczr2AJfMHuZyuKNcLdTc+Fm9zA17ITfDnbcf5y6x IrcBdJW7Zue4W9wdR6Q9lxtks+y5Cr+4Vs7MjbCL3CS7xc0zVa3bRrKvqqWIKWfyWtKYEqbESPYO 0STNsTv2MrreXsgus6vschdN9dPp1Cqd/wpB55on6OP0tHG3r6QlgzpFuakpI9l50LhrnqM1tIku prpfaTDudp03z7WM0IUvL1OL1DJdCfxoMe7SZ1qqqLPUOn2OucpAG5k7zC2QTwJzjT3I3mSzQLYV bDXbr3CXXVAli+wakFGPyt1Ce4290t4GEjjMHrbb2BR2it1kS4EPiWyHnYS36/Zo+PYA8OwGOwTt r2M2FI0ADXDbM0FDWuyyfcA+bD/JNtrz2bPsWZBYNnAyBNpyB2o/Ae0TqRC12DJiQXQ0FUunduwx BF3fM08P0wPUYl9JR2JLmkKdCewWcwN6ABdIv8C+Zr9tv8ARXIz98uvn7Wfsc/Zdph3yNFJnTWbb eWqU2jTztqa+JibADNL5n+kAkMiM2a51VTG1TC0V+9rQS7yqJTSMBbGvhE4FLTrLTJoGX05hmhgz 4+zs7jxGhbpjuTw7Z4/j4u3TXBpoRRFXDnpRxTaCOvk4WtEK6G0Lt8SNg6aS3A3OyTnZbq6Ea+DK occiO8usAM8Pgy7EA62A3nKOWC6DO8Q1ce1cgBtjs7ijVJ31JNX4Eted0JtIjTZPvXK0ZYSapYbM NmrTZqHjqD2zrXed3qXnjHOd6y8nmjO7ikzmVxq6llpa6Qmq27jbWd1XQrH0GjVEX6avmMz0dp+O tlFb1BZ9gb5InbCtdB6AcTJtnaBO9WbZiM5lSBFPX6fzW210Zn8plUVn99wwkmAPbjMxTHznidZt 4BFv3WV0xnOdQ50JPbeYZCbNOtFb/doQLdOov6KrnC57uY6uoVv6zNT/Yu/7o9rK7vzeEzJlCWFZ LBPZyxKWZR1CCGEpYRhCGCwzDAOy7MFCkmVbRtKTbMvw9PQG68f7/UPSsNRlOZRlGUIIZR2HQ12F eBlKKaWUcCiHcLwscRxKHEIJYQnlEEooQ1iW9r6720zTnuac/rE9Jz3je57Eld597/74fu/9fD66 7+sxsbKRiuyGu+mS6GBkRpmBIpgy+ygeqMw68iCYmXoiT/ixRhM9Hep8L7NlXolmod5V/wxB1P9F vQ9jW3ysbH6sbH6sbP5/qWwmTPxWJsQu08jnEaTB8pt2xJ3gRlcYX8K7sB5ntyPXGX2QLaX5cxyD 9DUpnzi2T0p6TP/gsElyxXvzmrZcJ2Sfc1QcDqyK04xeXMNJKVFKcQy6M719xHEgQ/I3SVKbVMTo vTiBOboIv7vQvvhwMyz4dI0X5Ayp09/jy24scYyH12QEsxCTwXvgrEUK8TwLd5AJ4Ty2LFzS1OMu DJt8OjnV81LWgjL9Ho+/zVcWfuGzRlLsdWRmJMupknrkJGe3bPQt4FaXFlsH+COXjBJFvqSoEVyz x3uEFxOl/ifRVm8JqcJ2vXlkOTlEVtqrCFvkIApWaceGrA1Yo9VRA9Fjb2tKiwbpnegAtivZog2O DXuVy4rplf5xjJA1oH9GnVHi+EG2P8e3pPSOY484xl7ZJ7HjJokoahx1nTSN4SPg0zQ56Ao3roUW GRt+KLcS/ojHt+FKktsjhPMUa6EzfQtES4QBn3Q5xsmO8BreEM4juz35kRa5UfLLA7hOaRPR48qN agkbUYSf+JIcXVGt0iJHO1HqmPI/sbdhu45evJes9B7Zj0Etp1xh8pY8i/UEBhwD3lEugTPR15Qa K3XEl5okx3bTGBi/5+x201bTrreZSAOltsMX2G17qbfZG7VXKWMvb3sf+2bDyd484ti3RGBkzUPB tRzpsS+So0Q/aSIOyD5XvL3OMe7YC68Rfqwz3BHO9DxzDNonHa2+Q0cDuY91RnbJU/tuU1r4YlMP MamMPBijE3dmZB17hu0Gm7Fd34KzG7eS3WBt1/rKaJPrkNl1THmPiKK/ax8Y0V2M8T4nK7EnPh39 mB6ST+hHBBPEiXxQtxkix6cjVcpYM7uYx/v8vWRslyh9T/Vwk3gZ6ieK5F5ySB6xH4Sfy+FIp2Mk 7JA5eZCskWPOoYhkL5IziGN3pt1D+O354SEmHev3GXwLvg1vocRE0qKD9gOpwn7gHIq68ZNw34Ni ccI1Rb6wt+FLjN5vIzuIUqkOLxZ3HLnifqBLsQonpXiMZCFSJMJepViFJPnzHdvkLefoQ+Fh1Fct PhdfSOlSFj4rlQa2Jb2SDwxIasnmGJCq/ClSp7gijopzjkGp5eFjLM0V71sSN6U0CXvYTfaJp9g8 Nu8YlzzikV3vfOyIefscXSDFk5v4CfCTSWmS2Ao/kjo9HqJFehpekQ0Aq6Q588Im4FlUGCf6pWey zn9AtIWF8HPpWaRU6vctRPTha3JxeCKS4xoI70v94eaIhXgVviVnh4dlxOcOd0jHDyvD3f4KrO5B bgBxdLkLgW8m+YIeLFwYSW/qcbRHqhwxrM7ZR+x6jygwso4RYsyT79jwzbpOHgq+atwaLbDvRotD VYol+4F/EaVRjsiJ9rqMiiVHY74lbJ5oA9be4xgAdp8azItapZxoYzATmwdcDuQDgzQeDfuCkXVw pfFoRuQ4mkRg0REf6QKsz74YzY4ao+34ib0qWI5Z/OkPRqJlwWaizbfx4DDaRWR5C6NTxJgrKaoD XlgnPSVr8BPC5pwD4Cw+3OFP9yG+ePBaHJ7GdsNHxLw0Ly1G0hxTvg2p02cI38OXlNG3t/lmnaPh tUibvSjSFt6UR4hSlxZcFxzAH4POIYcWML/j6IL/iWPcrmeqIn5XLkCLu7jV+9irkZdxI8E4BuWp wKC8gLeTwM/wQfHIuyOfMADFSpKvWumvcALZwW6zrYFVwDGz5dXgBXkP7w1r8MEA+PuhQBzL4/K4 OI0fYnrHqv+JvBS84Ariqz4jXixvRJ4STGTmvYvvZZITEVAP5xBxIJ9gBLnmyXdlKMwq8jLy0tlH dZHlwG8OwFn9chJgWJOAaW+RHQGELSNs4XvYLkDIeZFXnmfkCvDZRucLexG5QjDkpnMuPOdNsE/6 n4T80SVmPbqBERj4B2acLP8B1oL1RE+iMXsVmG0Xo0jEBlq1RDdHD31JkfVQf3Qv8vQ90BdRBNSs B9jCQnT5vQSykqyhiu1jWEqo32ckV5xzwG62sWfuwsaScPmDQ6KT6CfAzBAeDkc9+XgDsM4lMI6Z DxrlMnHa0RoeDc8BbyghNXKjL4xZIonhU1DnNUd7uFl6Kb2KqKV1aSuST3h8htBBpCJSF77n0vm3 gLVXBuJBn/p9C/Y6OVc2kAmyVY5XvvPtSWP0NdeguCM3+KakGdLkTZZJslzSS3p7FVNEEFInaO1u xEa0EE/DjyOYc9TeQ+aRhbgVq3OdgPE4JAgSB/PlOJlAMPZ88ppvCaRluZqwebs9etCqZ2Cm7Sds jj2vA18m+3yroBU1wBYL8MPwJtFPm3ztzjWiB/ipTnYDO02SraQJP5R6pKfSZPiRXCDN+7LD0+Gd 8BFo6W74WqQoUkE2uwulJ2HTg+Wwg+iRU8M10oGjK9yMvXLsOaYAB0lBX6GvEAT9EfojBFUPq/8C MJdR9TgSr55UzyOfUC+qv4to1T9Q/wBJV/9Q/SPk99Q/Vm8gmeqfqneQLMBxdpGLqe+lvod85uyX z5YjOWfNZ81I7ln3WTfyubP3z95H8sA9ev+Bdtb2IrmQN70FWNM3QWmFN+mhJn8FmUXmEANkT+9A Tb4OavLXIZOqh0zKBJmUGTIpC/JTwKRuQCZ1CzKp24BJfRqxQQ5FQw7FQg7FQQ7FQw4lQA4lQg4l Qw4VhhwqCjnUe5BDtUAO9ceQQ7VCDvVPoG7fBnX7dqjbP1WVAX4Ug/zoO3BP8I+hPr+j6POoStHn 0XhlTzD6jxSVHk1Q/TvVd9BPKPo8qgW86a/RfKjMF6p2VDvoP4b6fJHq53EI+prCmNA3oSZ/E2ry dxTGhDZAZd6uMCYUg8r8vTPomU+h96ECL0AFXlT4ESpBHV6GOnwY6vARqMNHoQ7/HtThW86ePXsO /eOznzqbgT5SdhijnVBvn1B2GKP/Fqruk1B1n4Kq+7eVHcbojLLDGP0Pyg5jdA6q7t/TfEpTir6E ivoxVNT/RmFS6AnU1f8W6uqnmjsaO/rfFD6lUmnuazhVnKKiq84rKrrqgqKiq35X06npVKUrrEr1 e5rFcypVhsKhVO8oHEpVp2jmquuKZq6qV9iTyqKwJ9UNhT2pbinsSXVbYU8qHCrnXsCePlARUBX/ U6iKv68wI9U3oB4eg3r4N6EePgz18G9BPfwZ1MP/AurhI1AP/wDq4aNQD/9Xyr5n1Ziy71n1Xahy /0eocq9AlfsHUOV+pex7Vv3wU4fadNUq4FbZcWcUbhWXpHCruE8q3CouWeFWcb+tcKu4FMCt7HG/ o7CquNcVVhX3hsKq4ioUVhV3SWFVcTqFVcVd1nLn4+IqAfe5GjcPWA8Z932oEv8CQdEStPcjLnP9 0W/c8WsVbbybqkHi8I56HXhX4a31peA1TBnAZxwhUWUg53+QDnKE6QDfQlT35qhykHOYNsG7CrdS uSBnrFdTWpDTO0dArso0j/f8P5pHf6mWn9k9c/TRM3DvbP6vh+ontBRqf9AcGqTH7h8w2tC2rdpT QCVQmUzj7UTMwEyBY5nVsJm31WwzG2U72G6smJbongfN94ve3abHQnu2alCmkWmgLlLllAlDmC5m hNWElm4nsnlsyW313T3PaqiLH+Sn+GV+W0gQSoRKwSQ0C4+EbuGxMCe8EPbFdGFIrBDrRIvoEVvE NrFT7BGfgDLjoMweKOMA50fB2aPCkHAkJoIzbaJHeMHviUXijK2M2qeOOA+t5ojGxSYtnUinYOOc n07nJK6NzuI67xNKPRoXsVlnFddD53D9dBGnXH9KXBd3hQTxiWASj8E9uiVEqZGUJOxLWlCri6JF ypCyxU4pVyoA7dbLz21LdCc9xr2id7kD7rie5FN5LWa4bWGmHjSbptluuo7tuJ3INxrHsGw+yHN8 mG/ne/mB+gbawhezGqWHbb18bmivqYG2MWHeSGOgJkv8lGSVgkKCxAmZUq80KC2Ampj+rh78smiR y2WT2Cnfk5vlqPxItMkdcrc8JI/KExIpZ8oasU7pU2lDOpQvyrhcIhzJ1+4fUKd0Gp3PzXMM13n9 iFukS+kKbsZYcdvmKeCecmM009jJcI0VwqlIsJmiRVgBac1Wfas71KWkJu2720zv/QNgHTpmiUqm Sqghz2rDfKj3TiWbSVFsHzt8fY2JZydCI55GrJ2eZ0BvhEbYx6EYNQxsZYzKu5/DFlKP7Bn0U1aD FTDF9CSlYqzAslbZbs8yNcqUUS+oFWqN2gx1vbvdBKyQ1VDX6Bb2YuiQuoAVs5Qng0llqtkX/AK/ JE7yG4pV8If8iaAR1cIFaFE1giBQwKKeA3s6ElPEHFEvPlPGDyRJZMR+8amQJxSKY4IKWNIOlybs g79wMV/IFDbFNGABCXyMXxWGRUy4xs+Kfn5ESBY6xFKxCtjivLgovgTlTKCXJ4RpMUusEG4JfcBG N4Ry4V6o15MRGrTHmqz0Ir3uqPQeMLmhE8bQ1EpVOrHbiUyYWeay7lHAJzJZU2Nn4yIrONZuqy0F 3DNukmuhq4Qj0KYNqUzSSRnilpQqVUvxkkEy8stNWvGVeCAVcwd86+1EeUV+wa3TuzxCbdIePonP YHGuky9QbI+v5g281bHCkzwZ2uZeci/5+Ov7jJHX8o18Kk3QPXyXY40J25bkFb6BdwOv93Nb3O7t Kj6bL+N19Pq9ZGlAfiwnS26xRQpLrVJMGpempFnhluiXE6QTaIeVco18Sy6UKVmQ+2SVrBKapRFp SdoWbsnNUjw/Lg+Dnj6SGqRGYK8OeVqek9qlLmlV2pMvyHnCBWmZbmsyAC96Qs/QL+ld+oA+ZqxN HLvPzjVpb78EfmqgaqhC6lZ9rPGJrdpYdLuffU5F2QQKZ5OZDWaPOeGKwByzHFplVbdfPmhmK9lH 1DSnB7Yy5FijOh5sUo/pZ9QOu0ZvsUfsKWZk3LcZb0rjE6qb6gtNhcZDs+y1+/lNMbbmYSfloO5R z6m5u7G7MXblTjndzxjrdbces5vsDoMYKzAjl3j/gEvBGjyrxixmkBlgYsw4V8e0Mu1cGpfD5WPc 3VX2FuugmrkKruoWxVmoCXba3M/Zblu4dA6rJ9l7oQF7LLTAkEyQWWC2mUP2AlvOjjLZTAElcGrG yMxypSweag8NAl/LoDR/NweDc8H8G9oAs2+HMvM2GewxeowGFkC/AjNJhvPpbTWTdNsiaZV5X/0d 9V/C51MfIjKiRF9XUO8FiHrTIer9NES9mRD1/j5EvdkQ9f4hRL0XIerNgaj3sxD15kLU+zmIevMg 6v0CRL0FEPX+EUS9Boh6r0HU+w5EvXUQ9V6HqNcIUa8Jol4zRL03IOq1QtR7E6LeWxD13oao1wZ/ ObCrvgyQrgMiXU71bdV3kC64y+RrCopFPlBQLPKvFRSLjCsoFvk3CopFJqHuvwB1/3Wo+29C3f+v oe6/BXX//6ygWORnAMWqkL0z6jPxyD78DeC/wt8ADuFvAB+eST6TjBydSTmjQX4Bfwk4hUgXgUgX hehWBdFtHES3aohuzyi/BKDxZy8AdJugyQQI9ZMQoeZAhPpZiFBzIUL9HESoeRChfl5BqGiBglDR P4L7PN6C+zyq4T6PtxWEitbA3R61mkXN36J6qPhTUPGnoeLPQMWfhYo/BxV/Hir+AlT8Raj4S1Dx j0DFPwoV/z+Din+3glnR98/9+NwuOgl1/Hmo4/8V1PGXoI7/Xajjv9DGadPR7yn4Ev0Z1O4PoXb/ IdTuj6B2/wuo3R8r+BL9GwVfqv4A7nX4LNzrkAv3OnwO7nXIU/Cl6vMKvlTlK/hSNaLgS9W/h1r5 jwFm6UYGPkIub+f9b8evxW/mRDoRiTNnGSbpFET1cJhOBq9DtAaJM+3RKuoE5HppLRL3sIs6AO8q 0wqdBnItYE5NA98J1B7IUY5lahV894qaAblGap5a/xUf+yXKStAk5MK6XkCAEVYL/+OIO3EdU+vU FnV8J4fOtQxfYRwtdCNN0rl0O91LL1gResnRT59gCQ0DWA1zkcmzTzgWwX1eUbuOSVpLV9MNtJvO dUgNCL1ALzMqLIG5QA84Jp3tN4XrFdimNclawDTzF60x6yHzwp3qGHNhGGVq4fs8+yaPYal29Wah q9SdbUnmC81ubgNb4faYSmtS05A1xsyBMs9NLdYMI3nllaGXf+Ri+FHqJRO9ssg/51/wzXdeMuXC 4t1MYcutvauxnjgWLcPX58VqZ7V7WbQaDfYEVyfXbo2ZG8SphhhWKW6znTen3b3CS7db2MWmxXiz VSwTde5lQ/WNYzEstorj4pS4LLqxaewWUyLC/iGnjIY7OY7FKwy9APqHpF4qvdMQoxdYzIrUD2MJ liGWYPJYv6PHUGxYZusMDayN9bAt7i7PDtspJLo6a+bZHiHF9cyS59xzPLMWCFnuXlxvanEPCPkN MaHo5jV3TChls4QK9ol7RGmTK/FG6V2Nu9cybE+4Pu+sts4qLZIu2BOMBlenqBWnXJ34OttpWHUO uo5dLdS6pYRdvJPDvqwvwUzOMFNJtys1VupIbWEJN3K4MJPHdRkKuEEuxo1w46bJhgxuiptl57kG 95RL7WjhFjgtV8C56SAXpBc47qbgjrmrbfeEOmuBe8mV5l6ttV5PcR+6jaDm7XwftnlXwxdyy5Zk 4Zmp5c6xMG/LvJvnbLQc3S0E45bKrVqODEtw5PfuqqwxYawBcbXdzbTUCIvm4N1Mz5xUclcjlYup kgmbkHDRqrRWaZ+wJU6xOQ8ktlNacVbbh6VNaUfav1EhHUmn9glzgzRhRswNylhLUanPaRDd0nN7 wp1EptnajlFgPPrds0I6vcBH2TZBT+cKVVcO8JYbB+xT9xTbVtvOvKAX3OPucTrX1MK88DxmNK4W 17FhW1xlEppWxFl6nJ6yzdkzxUZ7JjPHNOsdrhbTJPCULWD3iKuFzqYX6kvoAsswXWwbUqyC7lI8 hl4FJQ9dasUqmAQmk8ls2HMseh45W6/k0/F0Es3RYXqQjpmt9BLMG2kDvQGuNOvWMoW0lloE/p7L JN+MUusNA8DSMoA/bjv67RO0zhw0B4FH7tFldJAppLasJ9crrldYkyw11iS+g2lmml1V/JA71Uha C3iB72aGrdn8RO0qv2Z2N8b4TFc6c4tVsynYKX+RjzK3+E2mxs3xR01DzA5/j59zjdGr3Ak/yu/c LOGTPSv8Nc/+lQq+kBm6+ciSwObXBm2CvVu5I/DNCcOSkeS2+Wlmmlnj983btbOuLJfeXSysm4M3 KrBTYQubFo7NQcuKZdOMiBmORTHbqFMsWWwQ3fYEsV3sFUcMuYoliwvixpX++jx3r5gqpjqzRYRO FY10qxikR1xPRQ7mi2mrOAC+J8UucU+MF14JB8DLlwxdV/KhbyeJ1eKgNXZzWlLdNDFHUoJYYG64 or6iBt4SE3NFg3iInVpPbg656mpnGRO54VxwqV2JzDAzyhfqNXrNHYI5cvl53NXWZHKTzCOmo2nF VuhOdSe5ShtjytgribW4tUJ+bbuShBz2mT0BtFRp7amr03pyR2/ONWc8yJIuukm2lK1iGSFNSpY0 UiZbwepZid01TVoR4KmT7Ct2nT1w9DjDHEKXUTNcNafjDJzVPmGf4Fo5kus1FFgcXDFX5mhhj7kk Lpsu4wa4DOoVveB5BPx6jJ3h2pk80yS3xG55Z7lULpczco31JVy8QLiT+D5XFm8SbAIm+K2I45lz WWi5myB0up4KPUI/X8gXCk+FJ8KkddYacy8IFh4XmMZZoU2YESTHGLbiUjfGXG1yopzSOGJJtia5 w/pHgse97T6x7FhGXYlsmnTrRoWrE/hwoVQp1UgOyyg2YdeIudJjabgWkUbFhZvTN6fZdWlOWnMu WQRjTBq6Pi/dk5qlDnDWmvTI7bZsiqn2BCkPpBds540KWY2VSNckQeo2tUjTZkSisOdOLfaCO7wp 2KKutJocQ4y/xgy7Um4c8OXADoede9ermH3mlHfwt3jqjt7tdhewWeYCcwHbww/f6LGOmLf5Uaab 6WtEmCjT3LTiznaVYjv8Dn/aGLuebi02ZPMqtshd7UoBFmhkHvEmt9Wzz4wq3zH3GAeDN4SvM2ya 64AR9DV3cmoRNoev5CvdZW4dtoZVWjowyprrzHal8zWC+kaF29rAuRtcT68cuHrsE1ifq9/mMLWA GbPRHXRzljWDtRZxI2yi0+0Om4tvpJgHLYLtnrvV3e7Mts2B+TX+ZuG7yQzlIuzT/GPXpP65a15/ 1LANvLaETa/ddtmYBOsgmC/KGRNYW/OYFWaTEXic72sygZY+BmO7wu9wG8RF5lrTEK/hL9BaZo5P YIb4F94kFnO3Gw0AHcSp99R7CKL+ufrnCHr20tlLcHfPxwr3xwr3xwr3b4TCjbQDj/olqi8b+uXx a5lHtSqQjcTVdeKr4F311gH+ErzumqfAZwI+HwDs4q01SyvIkfgEYURUtrFAKhJH6AOpAcBD3prx jYHvTHi/fx9R1RnMdSBXjXf4t/+PM8ovWUjcvTjyo53RXzr+nw/08Q0Ct+A2nKjrw/v1Fyv260+r t/EtvN8b70316q74vTpTmpc0c0atecrb6x2oLzRVgTJ1uM1UBMpM1p+SZXh//dF1cKbXYKGUM72p piJzfCAlkB6wBZ4GxgLzgZeB9UAOyCu5mcBW4DiYFPAHiKA1kOKNKXVwF781U9dnqqrY9+rqT0EN 9EoNjNleHbFyxf/2RTOnzyQ2vQPEjinl0lOdgZi79JJ4QawRp8GR4HhwNrgQLAguBcngatAQ3L5B WE5xS20spKrr8+mrY+YF07F33BuvXF25Hm4D1+vzHXsHQhcvPSEzQMolC2qKrneSxWRZ8MT30lps oZS+8LX5nvheOSyhTK/OdxB4FcoLFRoa66KBp9f9oZKALTgVXNZnBje8OmsG3n/JE9y74rmRUxf1 6vB+2wVvq5nzFvgL68oDtjeWLac1RbjNP20qwv2gfj1eXXUMjOia0ViXqbTZm6T0+Y18bwGeaKGU NoPSXd4uo9tUZVOZkYrH/ue45N/x7/uP/Kc1i+AeDC7h8/jMO+3VsUDijTZTVV2ff8I/h/ebOcMJ bjFqcb1/pXr7+rEprb6wYr9mt2b3it+U5t90WExVuM1AglFSxkkZKRsYpeMgGegP6gJVwYxgbqAq kB8MBnaDxsBioAeQk97gQKAlOAhLPAXpOPAs8Mr/whsfUOMt+GIgDXxeFCgN9AeeBCaDSIAJSMC2 YCKe32gLHhLDxASxT4wS08RRKLmm6Iq/NqZ/FEqojr1zYkoxHfv8/k28NHTBN6aMUH1hfeF1m//R O+2XntQu+576ntafNhOmMe+4f/PSk5AGr/PqbCqvrjZWGzNy3oGaIrLaZzN3+Vp8/b5533p1zHYU Kgf1XA+khyrBe38wPnAQTAUWkh1oCbQFCDB+rcGGoDvYGIwFmGBB4ImSC9QF9AFLsDhYFvAEtf6V YFew/XpbMBzIClQEsGD131u2YtOdoL1jgR5iBUaB0519EyoA7//DRYJCwiB9HomClI+0gPQFpBVp A9dWnif7IlzZXwMr+yxSAlb3OXA3ZWUvhSv7l+DTY19G1egZ5A0YUeoSXGF1cIW1wYhSDapy1RuI XXVJdQlxqi6rLiOY6k1VFeJSva16G7mr0qv0yD1Vvaoeua8yA5P0wLX4AVyLm+HTYK3wabA2GIHq T+AzYe0wAtU/U82oZpA/U31f9X2kW/UT1U+Q96Fa1wPVuq/A/5WjV3WgOkC+qvpQ9SHSB/W4r4E1 V430w7hVj2Hcqq/DuFVPznzyTAryjTOaM+eQfwEjVv1LGLEqBiNWfRNGrBqGEau+pTzXhYzAuFUf wLhVP4Rxq1Zh3KofwbhV/wnGrdqAcat+AuNWbcG4VT+FcasOwZqbhXyoydZko3Gai5rPoGpNriYP jdd8QfMF9Lc0hZpCNFFTAtblT8BVOBmsvw3ob8Mnt35H06hpRFM172reRc9qgpoQqtHQGg5Ng4re Bajo/S5U9NKhogfWYs0imgGf3Pq0EikL/X0lUhaapUTKQv9AiZSFZiuRstA/PPeVc19BL5776rmv oZ85N3Duz9Hcc18/93U079zguUH08+di576J5isrMlqgRNNCi85tndtCi5UVGX1NWZHREmVFRl9X Vl60VFl50S8pKy9apqy86JeVlRe1wJhaNhhT6w6MqdUAY2rZYUwtB4yp5dQmaZNQQvnfNFCf8nQU SiqR0dF3te9re9CH2l5tHxrQfl37dZTSfkP7DZTWxrTfRBntt7TPUE77gfYDVNCOaydQUTupnUTD 2m9rv41GtLPaBTSqfa79S/Sfav9K+z30T7Qfaj9EO7Un2hP0T89Xnq9Cu87Xna9D3z9vOW9Fe87f On8b/ep553kn+rXz98/fR/vP4+dx9J+fJ84T6ACM+vXnYBXsRPo+WguLdn/l+LXrN1FMZoH1uICo JnNALoeoAK9ZZB74LJ0oIi+AnIYsALlk4iKRAHLx4Lw4AiG0yvneIzIBifPuE4m+Q5Db9r0CuQ3v ie/4V+aNj55maj/TCqOTVQGEjhRVfXz83x/o45L1kl1dmQ4pUZfoL3cU75W3lfeXzFQ+u6a/eq8S K1FXYq8XvBmr2Hlz+xp2v+GqUGx8LbNknRjVlV0dLVFfelXednW08tlrmqLHlVhNS2WRcubVe+C7 XWLfp/YVgXWmB6xKk+BIBHkl9wTv99l8W746XxWZ5EsrmVHqUKJ/86RE/Vpm8V4lVt5WMmN2KzUo toI6VJWoX++t2HnHWJF5VbiUpcvQFV8WTKBMRU1Jz9U5MkhyZJhsJY586WQZ2QVwykDJ+uu5JbvV e43WEnVtUnH25cx34msHrumVqyvX05VV7FztuJR1VXg9tWbmUt0li271slBrrT81h8nxiuliq26v skjpizerLye/tqIrI0cqseIGXxo5BdoFWkTOkgvkkq8I3L39HSPZW4l9kQBtKCYNJSlfJHxPwX0s V6NmN+iPLiX59PUXX88ldoq1xMTV0bfnlNbWT1zqL9ETa8UN5Z1Km8u3lD5/I/dazhcXi4aVNlfs vN19eai24bXMN4ur9yqfEXPE88sTb8zqCuof66orsfqS+nLdYT2uQ4qzdXtvU2Bs1AA/TL+2QmwW a18T3tw2u4mV8n6zscRTbCze0y3rlosmXi+od7zdAfpaezkBII194tSXDkaqyDfjs5FloB/1vizf DBkPXlNInW+RzPY980lkNb5LuslGkoQj2wLSuq/TN0+8uKqpba3tMiyDkmpfGrhWC0CE/SBZfDZd WbFWOQyHxQVkUBcrGr06fOn4crKOIwdrwehUTlZO1qaCEXLcy7/ap0utd1w2md1Xu5URAjU2AutM +iJWM1Nr/O/snQ9UHFmd76urqivIMIjAZkPTIDZN0zR001RDQ4AQhhCSIQQIwzAMZPp/N90NxgQj MshDzCCbF1nMRjZmEWOWZSMvj8XIZlgmYsSYwRgjZjHyIiLGmI1sHDFGxBgjs/d+L+OMHvXpO+ed 574NderTv/rVrVv3z+/e+7u3mq5dO3ftLOh9qv/pm82j1null8pH948/O7ndWuyhcVitFZ3ZNdad Ffy2me1Xc26R0rnw1KldgzSdzc3NN0hdhZLULhyYO7BMLIQ74DkQJPv+5mrq1TZb39NxYIKkv5ce HdC/hztgag5rjjxQeGDlwMNmR3Pd023N5aScNh7Ibd60btmXiE23EE3/gfacEtIzpSg+q/gs6Zhe VrxMeqlXFK9wvOLzis9zguKi4iInKqYV05xScUVxhZMUM4oZboNiVjHLhSjmFHPc2xTzinkuVEgX 0rknIlsiW7iwSOKEcU9GtkW2ceGR7ZHt3NsjOyI7uIjIzshO7h2RhyIPcZGRXZFdXFRkd2Q3Fx31 zig99xdRpqhc7p1RhVGFXBrpM6s4Y1R1VDVXEFUTVcNtjXo+6nmuMKo+qp57KuqFqBe4oih7lJ3b FuWMcnLFUe4oN7c9yhvl5Uqi/FF+bofqC6ovcDtVX1R9kXta9SXVl7hS1auqV7ldqi+rvsyVqb6i +grxzB77co99uce+3J+lL6eYJLb5ax8pVfN4/z/Y/6DP6zcETnJC4GTgTOAsxweOB2YJjwamiG4w MBwYJUeHAtfIUXvgWmCOHB0MtJGjfYGzgXFy5AsMkCNHoClwhBzVBmzkqCrQF+j/Lz2evLkut1dw vfm2JL1LMWSSMwuMA1VnTG15ovW2cZN/2f8w+0wuX7hWHBqILxwKxBcsBcwVnTmZgaLAzrKh4uWi OpPsk4wD/tOmtq1W/7LpRC6f5klZCWgDhs1NJORScWhR03bOLwYcvmFSF4+C0UFdMJrUiS9wLxgS DA/KQVWwMnA+MOpxBQ/meWga5KW8MlNbUZ1x09Yp/3L2mbJxmoI0TyDeVFw4ZLxR0ZnbWT9eNlTo 33Ynu3trWPDOZkfwfvBBY2jgfONGj8s35atu1DT0uB8FexozTXL2vsyC1H3bakxtjSUGbmuYaW/u /cI146b1+AaId3OysKdsyH86d+aF2cZDaSM7NuaqsscbD+eYTEOFbaltm5toWWx3bC8vGs6939ge iM857Svy5zaEBx41jjScaexriA4MNKob9dtXG02B+MaIzaPbrY25aROprsaRQHzK0raaQH5FZ2AT tnP14dn76u8YDf5+/+m0dv9Iatv2jrzTm0f9C9s7/Cv+layNgTBa5jvEbbxhtOImzXNFp8mVcyn3 fvb9gtyUZdMZ/4T/UoCzJQQibZPF1wLx/jH/Bf+S/9ZmycBtlqy3Sd20+fv8p4yGgDUvMzstZ6ls 3D/nf1h8oeRioNy4KUefo887XLC0jc92Zd83GiwSqaW6QDVqaiCYFixo6PEtBjsDR4L+4L5AV6A5 eDKYEzwWVAXuBoeC48HJ4MXgZXINqUlSl6rAaqDafy0gPdXvv+LS+xYDPo/OfSTQ6j4S5IPFganA tHGA1OmA0RB8bVdYY2Hw+va64FpwPnizUWysygsaRvP6ytK2m1NL/ae3jaflFq5tXm0MNu4vPkxr qHi5eLnwemOLaaZEV3KxcL5w3r+87U5a7jbZuCl3ptHmk7Z3FOQG4vP68vqySV2aoht7G8vyxhpr Gz3Z8wUiKd17jf2kpk4FfI2niSV2BEuJ7dUEe9w3AlcDs2S/4XN40vxlwRPBmWCCV++Jpkek1znq N3mig22B4eDeoCt4tmEmNSF4hpRTR2Aw2E3z7xv2DRKbXgy0BkMCt03FeItP/mPf7bHv9th3+/P0 3Uh76X1z7HuX7w/7IZ5+zylO8Jz2jHjGyNGQU0U46blIdEMOyXOGHI16rpKjLs8R8sl7TnmukKMr nnbPNXJ00jNEjto8+zzdHL933lNHjpo8Ds/xX/cTb/5fxC3l3Td/4yhhhu78v5naTJOeSdljarO2 WuITJ1If7G6xSNmTcomxLnFBXrEMp9Z4rpcUJ1dr7+aJGZ3auxatqS0jzTNpvkuvolekPsh4kLig 6UntkU89H0xcMEd6ricub57VTnnmk6vljZpK06Q31Kv2ZnoLvbXe/d4Wb2+Fv6LTO+a94F3wLpFu SEt2qy+/ssy77I3wlfuqfXU+H7lmI7mmhFzTV+H3jpDQV7yXSMjI9ZBL3hKf2ddhNuhyPSc19zU3 LceT7qS3W4aTEoz5iRGmtqSEpHnPUOLClhxLh/loxkzGWV2hczxvOfeE52xeLU2T77hvwFtL7tXr 48g9xnzDNEV7SMdI0qX1BivLfNo9m0h6zvumTG26Qk2N7qGRjH6eB3J/UnhykWVqa2txX+KCpVpe 8UwmpWnvpp0mpRSZuJA4kjiiW7KesxzNDHl+iRybzNWZIZ7rtISTOflW4oSlWqfRRehytedJSkwk LYu+2yQtd72eBr4hpCGBpKR3PR2ZlWUNbVWlvuqKy96xqraqtoaehmO+1j1cw4mGk778hr3eXF8+ LdMGuaGgweVdajjo4xo6ra3aG8Y6z5n8KVpDnuuecc+4ZVgbqanMuLi7xTptnU5c2N2SXpv0wCf5 ikqKUaor3uXUB9ZW06SJ2IX2vOzR3LS2WlvzrpCSlVJ7SKmecfhKOjPmjUdLirfss2it0/mtmklP j7nawmXcJ1a04OnJOLtjyXKU2kpi6LbKpIPmSHNkntpz3aLdcpbamqyxDO+I0N5NPSHv3+HJdiUd zL+xuZXeMXEicYKUErlPNi+v6AotWnk5/7zF4LnoHPfqvSZfqzcXVlFGysxGv0kFizrkPU3rz3sL 9rTJZyCW0UTrj+RpzLfT5yB17PF6fM3eKu+c96G3nZRslfeUV0O0K754cpbaQ6b3Agl/mGiJHXpr iY2OELusq7xQecnX5TtC6iPfe817jdir1dvrnSBX0bv3l3Tmk3Iy1llWE69lTJZ0Wla1d2WNrPEc yy7wXDbW6SJSaxIveY7l3ygp1t2ySNvGtXet05aOjIt0szySN5LUZCJfuaS295McXPWN+mZ9N3zn 0tt9R32Dvumk8G3jpD0a5OUtPTK5ozk+MUKnN5u94q7I9HZme9q7idc8d3TqxLnECblFbiEpmkqa pPa5tTV7MiMt8Zp1mljcQ4tBczajU/Y4uz1rmovyUsaxjDPasIxJS1MD72sluVv0DfjuETsMb4gm lqjy9jYUE8sqpXZIWmadt71hHylrjfdSQ2VDZYWfhNM1RJMSGSM2u5HUiYfkYNG32NBNWk5rw5Bv 1feoIa0hp6Gmwe/NbQhJGpI98oo8Zmoz35b7E8sSL8maks5t47rcks7EiZJOY37Ocr6kJTZj6dLl Zuz13PfcyVtOCiHbHc+MtUPulZc91/NvyLla8+ZZa2tJcZ5I+ie1RWvcZJ32nHi21ELiNc1ramiZ Ffd5jsnLmuuWYcsqPbe5Lk+fv5hUk3jB0uQ5K5ck9aS3JE1aHOa75rtJaZ4zBbb0Q5qzxjrt1aQh zWTqmmVnaqXmuue1pMvp7TqTuVwbKbdoBz0nSZtesDRr9hI7b854kDTpuZkUrrnv7N5yMuO6XGh5 pHtoHbRUJw2lP7RMpR5LriY8IVeZN+VezLiZ1KaZzOZJicdnX85u0/WZZLNZJ5o30RZgbc0ufaMP lldo/2u5rb2b0UlbE7Uy0v9Oyv3pLakP8s+nnkiudp6wVHuX8MtxXxO//vg/IR7/J8R/+v+E+I3f Y9ykwf4H/SjbLdsSJ6jijePkk7dcNY5yvCpi9y1OsF22PLLNE92E2cYJljHLcqaBhB+Ti8jRkOWm jfhRlgFrPCfE3LTM2sY5PlajXyXnDmes2kbf0qre/N+HsJDINz28v+wSHlUsxzl099SnU6TEDssD 2wXVI9tCqaTy2ZZsK3GD9jD7Jrs25tCzNsOxmI3PluxpSw7JOmfrtfXZ+g0624jtkm1OM6fyaYtV PhKasxuetdmtpnaDzh5WP6ZqNiTIWp1VLnLqY/emL9oHLJ2mQmeLJUHdm6F3TsjTxhx9X0qkfr8r zDDp2hQ36HjNoXPcTzkva52hhm778YxL6YvqEXlnzLK8c1exuteq2xJqqTSr6nsNlc4V5+HYg/ar 6edjIlTNKU1lc+mtqi75XIbGnaMbUEk6g6XSoDKecbsS69QmnTU5pGCxrrNiIfaOIcQdvithy0Zz qVul87lls0olpa/qIwwqd427TWc1h7uLzaWJkqo6btWoi3PETOgzK+89ddURop+LTVDtNKY9/yh5 PPOCatgRbfRb/Fk+dYT2WPLZpD6HzrTk4GtDdVJWtSPBkaZzZG7UV7mqU6birjpyXHWa0NiD+kN5 q6XW5Mv5Bx0F6l5LtKsppt/VEWMytLm6HMWuI45KYzfN01NFKQOW+fQp+ZzaY5R1A8n3aY6eSzOo LCRXunKdVb2ia61YqJ9IniepHIhzqPvV+sp7joNxV+s6y/bn9j7/yBGiGq6UjH7daJYvfdESknw2 rsm24rhs2ph5wTIZO2+4uLvIMRM7nlGV7DIcjE1wXM9qTr/hGC/XbT6hGjbk1I/FhKqaNCPqhzqr a1htkvPzbmeerjqV3qXuy7iVISbO6mtdi+bwlMGUYbnL9Shltn7CzWdUGTodM/JxzYjjDsl9UeKq O8Sc45o1VblWZbOuOqXIkJB+Pm46JsJ4Ij68bM59Rt9vTIsrSp7UGeRzJH81xjOqZp3VPW8IqVhQ HzJfdr9m6ZabLT3qWvWp3UdMtRn9KVP6a2qTUXbnxO7LKo894b6TfNOg0u+Xi/Rj6tPqCEep66jL oY5w+bZccw3ETLiOq6YcNQ7Zsddy2dVcX2sfUE3HhMaU1J8yHHTa4gYzM9W9sXvVS8nhW045F3Kr UqyaKnWELsx+TxttPy4XbT4RN2A4a5F19wy6rOPmtBQpblB11TZG2szEliuqR6WSbTl2hrQByVBq D9M/TK4hLcFcMKieoC0mKdPoSmrJ3J95SOVT+WJnbCvkuoeZ+22nbFdqg/ZIdZ98Ve2Jm7adrljW 3VP5ktcMF2Pvy+aK5RTJdssen25ODrFdqFioWCAtUqup0sylGCyy6pGqWdUcc4u2MrPfvtO+M3af fdrSGbNsaTPLztP26S1XnLf0/a54dbv5oFOtb7cXmQpTOHOpU+/stRe5tLVVKcOxk05RdcR5KEYT N+y8YEhwhrqs2tc0ofZBp8fWG3PatclUknXb3G2/t2XFvmon95S1hm5DtzHHOFQ/pj9sKiTts1B/ 2JgT5zDLydczQ2M7DaUxhw055lLDGZVPHk4Oj4lwJ6QMu0mvkKHRDciz8nGDSr5ruOg+mDGnK1df cXequtSnYxYMIWoxuU3f4o62nYpzWELkVtuKIcdd6Y7OPOROs11z79X3u0uNew2Vec3p51XNWbd1 1pRyTWhySMat+qC7wO2XrbF33N3ps+aercd2O9Qm/ZzhRPqwe1/Ko/RFQ2XMYd1woiF23phTW1V/ SNbqC82V9i77EWdh+nD6sLNKv+Rst6ape52XMifsdXaHcyklzJCm9mRcMNfoRuPO0d2hqu9ztapW 62tVq8aC2AcGFamDw3RXrzi6VVfJ8ai7x31MM2dadoSX3nDVpXCW6Mw+04ojOv2oozt2Pj3edMnh T+YdbY5uxwnHsaxIzUpdZ+LtZwsdZ5NGSEsecEzm3Vbfsq3sCdGUOc6QdtljmHQMpcdXTzpOms+q x4x7Sd/jcuxzXMwadcw7bjo6VU1lLWUe3XlLp+pqVaFmjNTomPGie81wwjXqOrfHlXHLeShxNUub MZZ1w3Wjvt11m2x35WZDjiHaHC2bXYOu8+pDrmnjUNZdXZdpwaFLuW3eq6t2P/CIrnvGfSlhjmhT ZpzZNeW6qh+pjDdX2h6aWmI7NSOxCe6TljT3WbPsCI89uXsqcTV3o2kuPcx9fUsw9g6pjZtbFnS3 zWmWy5mn3DNGOWNZ1+y+nPKI9LwXdyXEzqtF0u+ecA+pNmmLk4vd9+ui61vck8/qVUeN+4jdjBtK 6w+pL+jyYw7pc9UmtUkT6gw6CWP6nWVkjDiacUkzYj9nPx8XJp9PX9x8wlW++4j9rnrOkOO8lhFq mosd0gedY3af3ee8Ym+yNzuXraqMiYL42EmX2bkxaaS+vbDQ8cB0S9VkSEsZzmqyDzv3Z4r2WfsN 48X69qwbGdeybsR12Rftt43X7dW6nfqxZNkwkxmaGZoy68pP3xTbGXvMkGa4XH86Zaez1rUzxZqp cUSnnE8ZdhU5+519zlOaoKFU3avujVnOOp61M2YhZdT5cHOBfUp7f/NN1XBcZIGUEqYZMd2yJCSu pk9rC1xczC1Zm1guD2rUzrHE25oRfZ+xM27QmesssUyqODL2jRjkFK09P+aSvdyZKe+0j8buNXnS fU6Nc87e6pJckS5DnJbUbqXpUMqiM0JfaCpzrNk7kmecGs1K4mriKl1lUSw+/h+Hx//j8Ph/HP7T /I/Db6zPPjH9h+cVGxctmZyw8UZ4GvnkN14L1xJeSb5OdJdSmpIvkqPJ5FlyNB4eSj75jaO1YeRo +MlH5JPfeOq5B+So/8nl514jR8eSu8hRz5M3yecbPcevZxWKWX4Wz/xzuV0kXab/zd73W8fBP+Ka N8L9rrC29f0Nef/vCLN//b771/d+steuf9Lzp95y7k/Z/5h0/65wLWRv53aFOrCFhVaTrZV8dpCj arJ3hHZhOxJ6lGzHyWdr6ADZHKGROEu3AbIPhtYhhmHyORp6jmyRoefJXk2OI8k2BdJPJh0Fh8nm QPzTJJZpsp1DvHVkI1eSujX8GX0TID8qn0vD9wGMUSVRVZwJ3wfIw/cB8vF9gC34PkABvg+wFd8H KMT3AZ7C9wGK8H2Abfg+QDG+D7Ad3wcowfcBduD7ADvxfYCn8X2A0v/y+VfwPaKIFj1OxnRuw97f 2g+SvY3snevH3W/R/3bYzrec/307Pd9D9mO/5/yJ9Z3KJ98SX/f6Pf/U/Q+l5a15/GPCvZGm35Wn 3xe+8y33+FPT1fYWeYjsZ359HFReoptULnUoLygvSJFSGDnqkqqlI2SrI5ojko9oqqVWaI5Kx6UB yYFrOshxuTQoDUsOoqVXVEujZDsH0k8mnQePSmHYprBNS1Mk7iJ2d8TWJDXh8zjuQ7erb+E0CV0n za5vN9a3xfWNppmGui3dpZ+kLRb8f/K+1ryoPNJS6VtbC/DW1q14a2sh3tr6FN7aWoS3tm7DW1uL 8dbW7Xhrawne2roDb23dibe2Po23tpbira278NbWMry1dTfe2lqOt7ZW4K2tlXhr6x68tbUGb211 4a2tbry11YO3tnrx1lYf3tragLe2+h+X+/+jclcoDIrD8PKucOmk9G+u7w/elIV4tlMdPt/Qad8M w2t+85rftfMRZC9b3yN+f/g37seLbFesvSlDH/GbYeh5Iqcr1Nj0Cj3fRLZmsJXv4Lv4LoWaP8If 5Y8TuYmc72I6oh1AuGZyfIR8DpJ9mGyD2JrJ+WaiP07DEAt9+/qvMy7++tcZBXFcnOQ24NcZw/Hr jLH4dcZ34tcZE/DrjIn4dcYk/C5jCn6X0YDfZUzD7zIa8buMpv/LsRP/fY3+YhL9o3IVpcIGTkAf DcaDesrXV8HXoMmHfAu8QWwmHvEcYrEpqsGrYDvCfAOcAb8DfSE4Ch6l5MtBM1gM/RB4E+yGXg15 BbwITQvkfrAZ9IN3wTlwDSFdYAiYC2Iew8+DnWAfeAS8TSkYwL3gI5pTlNKh9VIKRY7OowwLwASQ B8fB/SDiWdsIIrZfLUMOg/yAUwhb8P1PK5i1TlLyQizks+D78H0UDYgw/P8Ah8Ez4GfoVXwPR3pN /qvQfALXSuukZ1egfwi+Dn4J/BF4DiFzIH8U3AFNEuR/Aj8O/h14AWdzQZwV/hr8S9CFMF8Bt4Oj SP9RyKUI8xn8f9sIZnMtIOJXIL8KhCG9EuW7wQZchbsLPYjt/eB76dxU+TeQXwPvIuYqhFSDz4Cb wUywGFSBT4EFYCcIqxaOILZPg8cR599Cj9QKHwF94GcR5hhyNwAiPfzLYD2IOHlWMv8d/DDYwEht m8cd+Q8iv7/iThGugQ/Af6d2rvgelfknwHdB/2OkDaUtsvR8B/JlpOqT0OQjZpSPoAed4PsVxOsW ShDyJTAcetib2E3P8mO4Fvnl/xn8AsK0IfwGhJyEZjfkQcgGhLwE+UMgK5PrIFLIX+HILF74IvJb Ce4Dn0b4XoSZAl9FzB+AvgNEagUb0hAF+V1gDIjY+O9DTgEPgqwGvbiKxZMIhiE8zvIT0CANIixN QJ0K/woihfxJyHlIbRHkQpC1O9S7wIM/BZ8Dd4JfBt+ONEQgNmj40yCsWkD8yn+BrARnoEGcIuIU WRnacfZVRkUNYTvOPg9NP676KxC2IbqhvwhegR5tXxnK7AGEtSs/vF5HlEu4Ng36EIRB/y9sBGH5 QgDcjzDIixKtVXwScjTOolfhkS/lJmiqwRZuD/gSYSOVlSI0PvC9lGI85A2U/E1GhZLwe/Qq/gbO vgJ+EfwSrjoAeS/lhlFGxX0S/ueI4RHu+CTkO+BV8CvgbXAGXAN/wWR6X9LvUfks4v8RiPDCMvgA Z5sppSxKhRN0gW6Q5foa5HKwEppvgK+CLKdfBz8DzoHfAr+NMOEosSjk9wJkXCWcB98PfgBsRXpY Sf416FmXaTkcxbVecAv0ZvAZ8AXEj7IiFkL5PMhKvhZ8DrSDe5DC44z824jGAb0D9/o05NPgMdAE nsTdf4irpsH/Cf0Sygf1yLMS+3ewDuFnof8m+H2EfxY5RV6EU2AQ6T+HMN+DphdETkVmY9ehgQ1I HQiJ8uFZGaKEyUi6B2PoHoynVM9BvsF9m6MjFE0PUk7aL9V/DbIR8gDC/xL8ieIzhMiFMA/i7qIV 5MF/hf7HIEvzLcT2E/AeNMiv8lcg7FPJ6vQSYkCtKWFR/HfBn+IsrFHsBmGfIspHWQTZy9WTME2Q I8AuXMXKk6XqE+DfgIO4Fm1KRO0r26B/H8isGhrlpyB/FNyG3mAa/DhHfD/xRdbPvz5AND+A3qNI o70cpZCydp3Ie6GvQ0iMYjz6NN5Bw4iv0DBKjDhK9PnKD7DxC2d3r00ROQA5i/rDgoj+p5O7TBhJ yXfg7JPUl+NZCtHP86yf//jaIu09cNaJtNWALCUHqaxMBc1gBs4GcbYRciPkchAjJl/LiLNPg/8N GvTh/CGmAXuoV0xIZfS3/B5KyU9zLbLRdgG53ou714HPIPz7ueOErbgqlxF6jIDKCu4hLT3oMxVW lDPR8C+glDSUSuYf1kBfD5Zx+9AuMC7TNAgffH0H0WO847NBL+7yFMsL56EjBZ1ZCN61E3ScBVGb wkPU8i+on8O/F1fVocbjqUctojbFMpCVGEZw8f3UWoRjCJ/J7oV4DkBGLUgmpO3sWiytI9zrIyix n4OoWXErvQvxe6m3rAJ14FdBlKfoYlaHmK10XiDspeStdH7Et7Naw9kPgc3QfBtXXaMhxfNgAi1P MZmSf4HlFHw3uwp6N50NCR9HXiJRyw0ojRKE+QVytExnIvxza13UxhAS3qPgWyNjnGADD4AV0Des fQ55n0L5k7kJ/w8s7zhro/XCv0htTGiCDM+ZL8Udt4Hb6dxNnMVVzJPpQqpMOOtiRKkiPUpmY27q SYqnUYa9SOdRXPsjFgMI6xUTYI3wxJTwqwW0F4HNGtbbIPhd8Bb4NoRPRQxfB1nMQyDyKDAPmdnM syB8G+F/4dp3QMP8nJ9BPwXCixbYfOdzOAt/TPwm6IH+vSCTT4Fo7wJasTCOkMzPxIxGnGF1AWJ+ JKBPExbBEwgDr0xE3yj8BDJ8Xf6HkOGxC37IESD6KLEQ+jnIyyDmeiLmcQLKVvg8NHdAzK0E5icz v/caCC9dwFxSZNaLXkVESPFb4N+DHEKyORdLG3oDkXnja5Dhf4oKaOBVCph7ipiVCJhvCg7wU9B/ A4RPLiK8+DWchScpCNBkgGymAFmwgBx6mHdChqfKw2/nfwmihHnMich4TYlS4mEDPOpUYOlMB/8C 3IWzfeDnYMmoZR5+ssBmmpgB8ayOMIfi0eJ4E/gC+CukGX2CiHmEiFmVyOpxP+KpAZn3znzmAzjb DZmNiagL/jwIW+IxI+BRejzrw3/KRxOuQm7DPO59oBd8BjwMfgrE3UWkWdThXmYQPa3I6oVZNXp1 wYlygIWLzIbhz/P3QMxJebQdMXo9NlIvPOyTZzNxVtoYu0XWFtB+hWQQ45oQB7J5H/ookfUGaK2C EbH9G/gIGliOwMZWdl9YqYBZqsBm4mzlAXNAAe1dwKqIAOvlWfgPYCaFVQsB9SWwHiN03cYoUbMi ZkDEn6Qy7qKMgW9TCuav+zkvwcaovA8+kg5yAB5RGZgDjQXMBSVQCWaCCSA8QwHzBTJLZeGpR838 1R9A82GwD/fCLIBY4x6MwlS/HzJL27vBD0HD/FIBDAGzEUMk5LuQkWYB3qDIZlifhGY7+DNwN1iI OJmPGs6/m6PzZRr+ZWjeDiI9PEqDx3yHeCN7UO+U7wHVYCfI5mXwfoVYUAu+E3rMwkTkTsRcg2fe Pjxh4TD87Y9AbgeZN/4dhEfZiu+Ahnn1bOb4EngQZ3dArgHfBWqgfwLyV0EW5kUQNSvAoxZQ/uIH QTab+DLkYhB1ISIXAmxMyXo51powR+bZOIIxcQPm0Rtg5xtgmTxbY2Ett4m1eoRnK2AfAz8Jv+I+ 4me+JXobJfOf2VVYB+OxPsZjvYLHSguP/ofHKh+PHk9Cm92A3kmJtqnEepoSPaH03bU2js43afit VOY9LAz8FraChDFOQgpFtrKEUYPH+ieP/kfEmpiIdQyRebxs5WEnXVMVnqcUsbYmwovgE0CkhEfv zcPD57Hux7Nx8Alwkl7Lw3PgsRojtL4eQdMAvQYxvwh+lHID+j3xCZxFehRsfMT6La8FmQeCMhTZ 2MfGYngpSrZ+gt5PYn0+eh4JPYmSzTWw/ilihURk6zAY2QWMPuJLmBklIFU8SuA+ZKww899cu0L7 5NdNND3QsLlPJ8jGkWsgxg4l/BYlfAkJta9kuUDa+EpoMA4qUfIis6J5EOuiAlYySTulMbDSRp8s Mh/jPrMEhMEdxZ+DWDFWMv0PkH5mY7BeJTxYEet4IhtzZejZqngW8sXWBlHCAhttx6A/CX4NRMkI 20HUmhADvg1n0Y54eCBiO9UoW6HPxSwAY5AI65LgC0nwJyWsVUoTSPNRhMFqvKBCzHb6DIX06oRK lLMSJab8IWKWwafBfDAdTEFsHfSJjBiAhrVoE+Qjr0skBubn1HLZGIsJlcwjZat/EbgLRjcJVLyy dgAkeVG8jBydQwrhh5CRi6awlD7LEDHO8vA5ebZCiNVLJepUfAA9njuImMGJbE7HLJldextkPipb AYaXyy+ht4FXILL10gLk6O1ICcpE0YB5ELw1Hl6WgnmSuDsvISS8cfEqCA+ch6fH4yrlfuixJq+E 9yWehczmNYywEBG+BI/WKmK+KcFDUCI2EX2diJmFhKcqIlu/DdL5vsj8RramjfVzns2F4UVIbC4w zGwJcaJFSxbaHvkstMpDa0tEZivtzJticys2n0VtimyVm9Xp2OtfIDL6Zx4thcc6thKzGCXzkFlZ YSwQ2bo6nigp0SpF9OH0mThHVzupBuOFyNoXVnolVs5srZs96WDpZ3X9j5QbMB69jZUY/EyJPXGA Fy3i6cAGtuoOb1NEryJhliQxPw3+v4DYyDyFrrSwVgPfW4CNCfBaRfZsAuUvsF9HYU8T8PRKhG0r 2WydrULv5RbIXdgow0oDMyklW2NBjiTUi4S1aAl9l4RVeok9RcLavsh6cqyKiMwe8LRCwtxECesS saZB/AqqZ09/2OxpP/W0BTzJ4l+m6eG/AH6HUvgEfe5JPECq+QalEn2ICH9VCd9VYnMc1uegrxOZ BSZyZ8hZ1vvF0HJTosSUKHMRLUvJrA69tHiQhhHhJwisdjBeS2zEZLMPNkIx3xV6CW1ZxAgoMstB byCweR9mTyLsSoQfIrF2we6L8pFgsSJb82d3Z+PXBKPiIAmD+CX04Uqsokjo5STISoySEptr4Bmi Ev2tiDFLwIxeiRKTMI8WX+DqYPl1yF0dQlJ+gFLJNM9SCj9e5z3YWx3Ktg52S0M+RxnSxEifIJO7 07PvwlU/Au+A3wO/ibO7wefWZRKz2Iazx6H5PsiuRRo2qCl5J7gHZwcg50FuAYcR/l8g74P8KvhF pHMR/Bzy+2mEuQT2gf8ADuHs65BfQvhoyH8F/YvQfAkaM2gBb4LtYPH6tWSmJn4CchBpGGIkHqJC 3Az9xxCbHXIP+D7cBSHFWHAjeBDXfhucAX8G/dOIQYlyiIC+HDJi459AbGehfwXhM1CSVsjbce1n cfYRNF1gKvQ14N9Bg3LbgGvJjIzyNPgpcBZhUGvSODiBa7+Bsz/E2R8w0u82kB6Pyn8PDoLfQvgP Qp4CkWYJ5Saxkkd46QKIlIgjuCoHmsPQbIXmGdAGRuJsAmSWaxX4z9DUQa4Fw8CvIjyzFhlyGfTv Rl5+CQ2sgvgtVA6HvhHeeCP9noYI/1NownrvZapRop9XstUqtg58kJGeFfIhfwzEeqDwHfgqCegJ G6F/ET6ADqP8AdABumlIgT2Pfg0a9PDCP+GqUXASRK8ivgIZ3oIwDfaCXa8H6ZwXsg/8ICNS+DJk 9J/CM5Ct0O+BXI01bfYcoR3prEJKWJozwRKwDPSCW8HnwDgQJcB/FHEiBsEN1kD/FGQtZB5kq77h 0Bshb6OpIh77TqKJgr4VjAXV4G6wHClkz1UVrIQhoyT5m8ipC/pnEfNPwO9DA1lYg2Ya5V9OS0/I hr4YRB0Jg9CHQQ6BDO9L+DQ0X2e1AM23/oO9c4GyqjgTdVXtvc/pPu8+71efc7pF5C0iQWweImCL 2CK2CC0SREBAROwAIiIiwxhEJMggYQghhBBFQhAJUSRqCCISREKQECRIHK4xDIOMIssoYQh9q77d uSN9Z91x7pq7Zt21RpbfqV27du3afz121V///pvybCCGFZx1gBh3x3w38euIWeS2EGKQoWVRkj/z 7B8RcyWa/BuI305MAhZhiZTvc/YIfBf+lrOuNLLwZng5vIQ07ryxB+EaQ3mecHvKNpmUPbn7cMK3 w94uaTNuG+sA+7htiWvHks+b8BW4GdL21A8hbVU9QfmpLzWedVyjuwPF2aPwE5emdjRN295NytOk ZK6ovJz9jJgBzWzU7EWYp7NOkg8zLsshZgT1eIJrf9KU1eGHaQN3wAfgTFK2gTFi2sIMuZ0lfjQx 3cnH1cp2Jr4zY4hra0F/t4Yxhrj6TNaVVne3NpGDu7I4S26zIT1I0dLUzc2SN3fxcfYYfAzeZWj/ HWHGE2sUd/8aMV3deDgZjoB9kOQ20tMHrR7E96B+g8gnSAyzMstDuAizcAI57CE8BS6iJEMJN1La P3PtZcTMgZxVSN7y8YysaNSfGH/YQyljjV/GzLMM7YTjWu+wFrPvNyk973Ht19WjhsYST42ADYZ2 P/W05qWQdYqdIdzK0PqLoXpAHNe8hHY1wN1Lhcze1QRy7k6edxEe29Rd83bKfwsxt6irzXhIuAfs Sp6XwgrYFt5h7Ab1tfPNyAnvIzfam0oYSzx1IznUwhGG1tXmWnu1DAmjvzJp+ouFOkaYs/YYUjIb V9PJbTn8DtfWGitE1U211uFPsKf6DPuiz5pGmTWOsSFUbdVmYbRMpoTb4UDdI/VKnPteI14npkbz a/Bm2J1dtkHGLlHVNb3Ec73EHQ+Z8ss/m9HY2BNan8ILhmqAuaM1Wq7V4ZuIualppxkDCfc3crYu IXxt0yZTj2ZnTa+1TUnaUmu9jKWlnrvupk2avekrzYpAsQaxK5t6mXkU8hwmugijsVlG2fryTunL XTStP8CTxlpM57bazPaJ+RQrssHk3IW7LGtqJcz+bCtTfqS3CqvCd7FLHGbCeuZv1jLtzL1sduVU 178sZZSYwphg9h1WUaqnTQ62uzobbMJqLBwKR8MO7CNXkdLVWH7b7Feq66GrXe/FHfvwdH2a6jSr 2U3oKWp53lP0CE1rqqG9uGmoMDrVhUYOf+lv6gj2o233dFs4Vw3nSccQHs8dx7q5sWcaJM8A7IFu 5yqeztWA/ZQV/TdppXOaNprxnPBIMV1zvjgijB3mx5oPNWnat1NHdzSZ3e07eN5lJmfn95R5iSmz XokbmdzKOq4OaZ+mhfczMZ52hM9Rwj7UWk9qbauYIYz9kqmj8Vz1rDGC1XVkarCBZxlFfcWbZtMj zIjhJ5+B3HEUud2LnAch2x6wnrMjYSez0nEmULMDaRW1sAZ2g1eje+wG7+aqm2Ed/KhZB2LWxV83 6e2AeSJrm9GQ6LGxnalrrk3LtOmtkLWtKhBfQznd3eqzlP9fTA52yfQs3Qt2Q5P/QiQznid6Cnne 3bREGM2w2R+0aP/nTP7WR3Ae4/MSnu56StuT8aEN7GNolbN+vx2tzi2kGQSvgNch7QGUZDgxl1MG YWrWSv9lh+GF6UjDlPNzyv8x7CKr6Qvmqrbkk6JldiPmNvggb+3nOPsJ48BNxNeIbfrpuoqOmuPQ NbXlPfWwseVW18uw6SOGVnWTGb17INXhJr0ajv3nO4TvhzNEkzA6VZPbAJPSPkH8OFlpeo2hlpsJ 30p4L+ETtL07TUnUW/BOzr5myqzbgGmT05r6mbNNl1KqmKlrWCsu1xxiwvYrxNzMHW8mfC3hS2BP l8R3475tYAPx3eEDnG0UlwhjjXOv6YOyh6619Rf+IswOQkcziyDlTXCw+C71aJ73f8irkGdHqOWg 32gm/lHxkSkh4Vac7cV9a4i/rcmv85SGeqQyZweQ8ruEa0nTAHuL24TRU3VkPIFNV8K/N2MO6YnX 74IY7dyEqVk1jJjRhtZlIsPMJMvoZJgit6fEnzR3Go2TuoX0/cw7QuUpW2vyeROOlQ8Ko3Ey4Wlw rrnW7tD0lg5fxrWtqZE2pi05q430rDwpr0NifbhjL+7+FuGTWEa1I42vuXWZ0r5DboNMLahP5SW0 Z3N2DnwCLqec34MziRmNDBvldWbNaGjtbWpr7gXfNFS9ybkrrJGXabaHl8M2sHdTwszfqK9nyPnb cBn8G/h3bk2RT1vYg5LPbvpCM0epqknztSZJb+KOSPuqprs1q2C1ofpLc80WNdubNq9r6mrDC8/r s5eS89ukudLUo77vfcLYSnWkhRh2IP9q2J5aeBRpPMjZVsQPhFfABxlFD7spm+NvpG2bOq0hvtJt D81v4d1c1cnYJTKzWmPGN+81hNG7etsT/g38haHXZmbC7rkXPZ6NHtXr2sOcx+bnPPNwLCs8rv0J uwP2HJesmOawLkDb72Fvrhx9Yxnpy9kDsleQcgW5YcNj3+iS+DPMnOeibWDt4LDjUMaunxdLPC87 Dmo5KVnJKnQXjmspxJzcwxrTcx9k/Pewy+lF0+tMcWnOeo9DVvre57kj2nUHrYLjahLQHjusv7xY d3ieJJ51roMmwWYNZf+YtcY/uW8xYra5NM/rcUvI6tVhN83r6lexsrZv4u6uPO8ijbtztwhZoTew WVeWYYfj+Q1Ph6WTF228QsOjFhDP2lyhyVGXQldv4OouZrNK8rirV3K+A6IHsCfCabwxrybM2llV Ee4Ch3C2edXMui9mtBxqoas9Jg2aDftlykN92WhaPOxZOL8kxt3P5XsWD/p/L1prL/YqXuw0vGiq PUjGQ7yDtZLj7tFQOx52eTxourzswnixhPdgWWSzgrbdfcYrkS1P6rxO/ChTa7a7Y1XLuu830K1Z WrLTy8R40Wl7F3O2gXbl2vM/Qd2h+3KGEe+2ouHEsH70oh/wsm/rcff+JhGPZt7rfg200yVn2bHy fod7sd602S3SbcmcpY15kJvDnrvnHeLR3jjM3j2u5dgHXPu3nGXt7FhQcXcsf7wTiWFfwMPa3+t+ f+F+PUFL8HDWeRiZoK2yTrhklf044RfQtDxLzI+I+Qn8R2JcXd96OBei63D6kmcZMeh/7BHEo2lU aEIU2j8bnY/nO3AhaVaaO9oPcnYCpF/baOrsa1zSg9x6n07MVPgIRONnUdcW/Uv9Av6eMvdjxuXu yrmaT/RUDpoT6yD8oUvmmT9kBDjJVd2QPPpAu6GZjWa9QHgkZIyykYBFqRy0TJar2aO0FloC+0Fa 6VpqivZprecd/TJ32QrRh9gPkQZ9jv1zuIUapAzW48SkSPPP5IOuxn4K0pLt/vAarmJdYLO/bKMr tr/OOO/uPX3ikpw/IZ4xtoyxy06RPoUksUu0sKeyfkueM+EfXDK6YjGiGP3slYwwaHLsdZT2fYjG z8MOoE1PsZG8/QylbXJbOzn8LaMu/c55g/jOXHUMziLmu3Bi81Ob1vsM12LLYbuj39WcvZpWxJvC ccdt+qzHtUR9j3p/jxLy3jRfsgqz3yHY7xDscZiU7HZ5XcvG7yP/A+R/BVzGU7DX5qFOrePwI85i JWj/I+EfwDVwO/GbCH+PHOjXHvf7oFeJ/x3xWMF52JX2UAYHjZ9nPndBP+mwf+24lsklYty99QD5 vA2nc9XrnEUP70GHaWGN6cHqw+N+cfY0Oa+hzzKSl7PnWM5OdDl70F7GWPtbSPswKd2353kRZo6x G4bNjMJYWeu5hNnJWsHZP7B/iqWQBzl42L310t682Gl4XbuUIe67latGwEZ4r6F+2xouImYGXAdn Gup3bti8c+EeQ/3ONesvrlILiCe9XsuYqw4TvhTeBofC2YaWh/ATpLwDPgcnwmmcvRo+SsxwwlWQ 0tpd4BBiOpBnHPYhhtIqnkK/kQ3HcFZx1VPwLXgT8X0p/3JiRsGvwbu59iXOfoF8fkn4Sc725uw/ wqPk40Bi7ALhj+A2YspgFm7gKuRg9Sd8GTlTEvsbMAdvhleSEtoj4YPE9KJUSM95nZgHODse2rSN Xu5b231Ts2e9wH23ErOLa0e5bzeuGgR7wKsoFRLWrdfEIKVy7qvbcJg2HMZWJMx8IEx7Nimfhd8i /ixle5N7ufYPu9FX7CbmE9OqHdd2y7WepQ1Yb5CGNmC5dsK3EnZrbTSkDVhIyeoGb4FjyXkyZbgT dkfOtHn1CDF/Txh5qulcRZvU61xDt9XRHtRDcCq8Ar4KaUtWPXTb2I3EIxlFGSy35XeFt0NaqTUQ Xgfds26fagXvgfRTlSANfc2ijizKr5CnPYEY+p3l1t13oISUSq8HDX8Ol5KyCDtDalB9TJieZbWH 7lNvh+Ss3HjkYPEslvuknxKm3ao/EHZjLsBjptVZWNdbtEyL1ZP1e8LXw0sgrc5ixHD+SG738xSr iaHMZe6z0ALtfyamLWR8cOhrDn3WYWxxkJ43QPrniaGFeFPNbfJaM8dAtzbZhO3BlO007/EdLk37 LGP3oay90XaWMR/QnCHMd4gmh8UmBy/WrR5sjSS2NJIVgXS/KcYOysEGxkN/9Li2Pbwl7a7N1Pl7 6I/KnTP8kVLxPrKxWPO430OxjrDcduuFL8Kfwo3w2zw1Y4K1iace3MyOWDGZvulHnpWQ/uXQfhS9 Sbn14vaFEmQcU25vagOrYTl82lBSd9YW+AIxlFMyekh37GLkkbRzST+Sbjl5B1mM25L7ylq4GFI2 +X3o9qA34J/gXvgKzxUmPA4JuGMsNe78AzG8yxz6gnL7b2vChyCjlkUaiUzUVsKMsZK3mEN789Ba PKypPbz9Hff7er4dsNGoO+wRe1izeN265rsMXU4zvpGPVQN5A1rIx+a5nAh3X0k8svKQm+Nadj3O eI6NmcM3Cx6sGjzYG3vcL6Dd+d6fuZb5gAeLZY9rl5Uk5yk8F73PceXMqKKQicO1FiO8/Rnx9Nky t3UhGS/vxzKkrXhzOe6bN0/4HHd3xz3GBz1fMuED5PAyMe67zLVCZG6m3O+vWRErLG8tLG8t188D 44nCAlnxXLZr6Y0dmsLySrnfJbnfQLnfvKDDsdE/WO6episftBMWulM9H+hIGhMeBkfA5+ENMAkT cCpEi2XtMXTQqVroDK3LIRpXKwzL4XVwILwDDdg/EV4MXW0eGkg9W+iIzDvyFujI2NuRWjPx5wij e7QkMU1cFSTmPGFSWmgmrQmwkfhVhEfBddDVT1IePS3tyFvVEC207puGro70Vu51mvA+ONbVbRLu ANtC9NhWADowA/vBH7iaW1cHSA7TCf8LZ9Ef2j8jjM5cj3sdeWMafgS/RZqXueoN+Cn8mLNeiIbc fgiiidXzMRMfh0vgfZD9AutJ+D6cDSmVzVPbrpRIaT8CKaeFzln3a0N0nnqGY/gr+BwpOxF2n6g9 nAF5doun0ONVR+aiHRnBTPhSnoi5k4d9ojJ0QWVYJpTh18KL3a/X9UtQwMbb9YeABsyDbb/ViZXF ZKyU32Hdeog1Hda2jvsFBN8SetyvyRaRkq+P5SuGHqyjvYwwjuuJ5dt8R4D2yTOebyKwlVXdTNjh +1nnNGHXX8f65lX/Y2a2iS30y1iqs36R87CmrqD8Qe5+L7wf/j18Ei6A2JbLN8iHNBZPZ+0gH/KX q8wddRrDhcRc4OxbpMTG3hrMDmyK+Dy266PhGM7OhI+4ltvk4H6f5X6L58qcOarD+svpA7Eb92BT 7TB/cPi6xHG/KHwEPcm/UAt++Gvy/wXcS0n2s/M10+i0JdZoEg2VxAbJy+xCfUgNut/luX48XFtT VsHOJtK72rMfI/nHuNeLtAosWCTWaJL3hdd9v/C1oFyB9psR1WEVKZvckZOysaq1xhPuCtEoWmsJ t4Pr4M9gDp7n6e6D1KwliT8Hka3axVe66BZ0Xeh2IldSd2/DvZDR24MdtQdNu4NGwtpHniHq7g6z n6jHRj2nsu40dPjyRdXC7s31W695GzHHufYD+AkxLtGgqhOED8Bvogfg2S3sbB3XVvAOWjK9UmJL LF+ltbzOVdtI736RIagRi/Tu90c8i0QT5WEmqXZQX3WUcyLXIkP5e8IN5ntn+Q/Nz2skz73sK2gP fGMiP+Zef24+q9N7XNuDJ/AYgMZJ7kd6rqeg7ZTH/frJ/U7qOHf5Hne5hLsvcvsp6WvIky96PGgz pLsb8jT9131Gm6sOuVZD7mhAzshcon2S90O0rJLeYbUnB/fbqM70AjRFzgJsO9vRMjdjA8N+hF3F GOV+O7Mey5Zz5Mn+i+TrLfkhssUGSX2Pr8XfozzohSQrUOufybk9Zwfw7GjtpPu19a08LyV0sC+S 6Jwl3ynIH5gyl2Nj7+WbLBvLKI/RZAr8bAX0z3A5WihxlQ6tavb9q+QG8xWf3CR/Iiy5Wf7U9Eb5 kg5vkS/jM/BnOvyKfNU8Cd5Tt0lTstflDh1+Q+7U4Td1SSz5S6nX/PItuUeH3zbWvfJXcp8O/1rX sh7x9Rhiyd9II6nfykM6/K40Xs9+J4/o8Hta/hJfbZb8vfy9Dr8vj+nw/1Df1PIyvgct9bh63Myr 9MzKUk9Y5v3USc9wLKuzvdboceznhGWvs9fp8I/sF3X4JfslHTbe3iz75/bPdXib/aEO/9H+ow4f d4SwHBn9hpDRKdHHhRWdHysIGSvG7hFWbGJii5CJlxO6bIn3svra7LbsW8LK7snp0RAvf1buipzx tmY3S1eJB/G1KPE6q5o9Lhrfswq/i3/1QGu8L0r80Cp8MEq80So8MUp80ir8MUo80yq8Mkr80yp8 M0q81Co8NEp81Sr8NEo81qpmGRp/d5Y8hn2VkZ4rN4nnRolXW4XEJP4b/+oZz3hx/KvEjH88C/94 Fn4dJV7yLLw7SnzlWfh4lHjMs/D0KPGbZ+HvUeLvUeLvUeJBV+H1UeJHV+H7UeJNV+EBUuJTV+EH UuJZV+ENUuJfV+ETUuJlV+EZUuJrV+EfUuJxV+Gvz8LvrsLvrsJvpMT7rsKPn4UPSYknXoUnXoU/ SYk/XoVXSYlXXoXHPwsPkxIPvQo/kxI/vQpvkxJvvQqfkxKfvQrPkxLPvQr/kxL/vQovlBIvvgov ghYeKSUefRUeBS28U0q8U0q8U0q8U0q8U0q8U0q8U0q8U0q8U0q8U0q8U0o8Ayt8VEr8Ays8VUq8 BCv8VUp8BSu8Vko8Bit8V0r8BivatnT98smJZbXCGvPQlEkiPn7K3feK6ZPumjZZrDXfP91a37ck ugnR1CRiemTxiIwoiagwOopuope4XgwRxg58kBglxolJYoqY0Zw2KLwiK6p0qIO4Uo9EvcUAcZvx jSNuFneJ8eI+MVU8RK9y04dEmciJamFmy11Fd3GNuEEMFSN0fxssRuMlfZqYKZLCumHw4AGif/3N N5XEiCH1N5bEQnIw2tlykReXiIToJK4WfUR/MVAME18XlrhM3CLGiHvE/eIB8TCpy0WlaKVzu1zU iGvFjaKNmEV8QkT0UxfEpSIlOouviR6ir7hO1IkGMVKXta2o1+vpiaJRTBePNN+1QvhFUbQWaXGF 6Cn6iVpxk7hd3Ckc0U7cKu4W94pviAfFbPHomC5Tx6jzhpYNAzAO87DVmLsmTbM6wG6wDxwIh8CR Y+6aerc1AU6G0+BMOAfOGzPmvkZrIVwNX4S74VF42tBWYyfff58dh1lYgq1hB9gFdh835a4xdm84 EA6Fo+FkOBPOm3TP+LvsJXAFXAPXT5r8wH32ZrgVboM74R64Hx6adP+YSfZR+AE8CU/rk1Psz+F5 Q0fBMhiCcZi9X/84JdgadoBdYHfYG/a/f8rYyc5AOBgObTTxI+BoOAFOhtPgTDhnqq4RZx5cCJfA 5XAVfGbqPZPHOevhJrgFvgZ3wN1T7xvT6OyDh+EH8BT83NAjpk7tfIXHB6MwC6thO9hFs4unBvaB tbAO1sMGzSs9I+E4OBlOh7PhvKkPNE71LIJL4Qq4Gq6FG6ZpCXg2w61wG9wJ98D98BBvzbTI/Ad+ LT1yVItL/q9Cxh/vv8cy3ZsdPZp5dahc93j//4M475fi/jXm4jRShL4izY5HRI820f/EsNJj4KX/ h18pUl+ZiuuUYFXBe8X8bxj8ykx+ZZb+Nya+Mlt/Bcb+XVr67Zbnr/F89VBOhwrIyfwFn6/+K0Xb f5dKv2/a/wd+pSh+Bca/Envot/58sVysE1vFbnFYnBBnZWvZTdbKoXKcnC7nyWVyrV5n7NLz2OPy c+VRSdVadVO1aqgap6brmesytVZtVx9beauD1dOqs0ZYk6xZ1kJrpbXBes3aax21Tlnn7YCdtzvY Pe06e4Q9yZ4l8Bojytz2ZgdaHJdaHPdvcVz3pWM9D7EHCq/867FeVjqLLz72dvhSen1ctpFjW/fO pK7V1m5ssHfz74Dm3/rm3xEXXx2JfOlY953IjotL01NcXNprx1583DfZ4rhdi+PeF9+vb32L47EX 36/vnBbX72hxfObi436jWhzvu/i4f6HF8eSL7zew08XPP3Dvxcc3Ri++/saGi4/ra1scD2hxPPDi 41td+Sg97kZdCdw6ovn3w3+rHofMb/5d0vy7svl33b+Veuii5t/lzb9rmn83XvzUw+IX18Kw4ReX smFji+PtFx/fvqTF8dIWx8taHK9rcbz+S8d6pB7eok+M3vWlNq8DYya2OF54cfoxiy4+vruF1O9u UWt3j25x3KIV3T2txfH0FsczLm4l49+/+PwEvcLWNWPr9cUJPd8/xfvI/MUzwV8nk7FYLM5bKio8 qecTr6Y2JH5mb9QrYyUcuVFu1Fm5a/vNcnPz2t5ipWS7+erRqSPaCGU0hXIfLUrfW31h7q+MjqST Pk7qtcMUsVLsEsfEORnXZSjTV8dTLwmV2pDaovl86mVNU9sRPeMp6VHe/F2onol39Wr+Lb0+PMzv q4nf6d9f6eMj/L6a0Cs3fbRH89XE23pt/ztdMtOis6I68Wu9It+oz+7n99XEO/r3BX18gN9Xv5Ty N80pDzan/G1zykPNKZvLq1em5m6/4G6vc7e/nnmDM29y5pdfPpN6gWfcxDP+hGf865nNnPkpZ17k jBIe+YZ8Q0vd1YoYfYirCbGoFTu1PvVj3U/cOYXpt11NLQsjf0c8Kcz+9y79T0bfjmppxJfFl+nV 9bOJZ6mv//6bGP8VfxPjX+sqS111pqcujE/97xr5L6sR42ldMuM3NXKFroku/1k1gfQDSD+opf+8 rgkj/ZiW/mERR/oZpJ9F+pVIv4T0q5B+J6R/OdLvjPSvQPpdkP6VSL8r0v8a0u+G9K9C+t2R/tVI vwbp90D6PZF+L6TfG+lfg/T7IP1rkX5fJNgPCfZHgtchwVokeD0SHIAEb9DyWqxHFGMB+Zj+96iY p//N0TPe+eJvxAKxSJ/ZKF4Qj/MXM59gRFqg58G79fhk/mLmQv5i5rfEP4mT4ilpS0f8nfy+/KF4 Wq6TPxbL0SOvRIP8PXTHq9Aafx998Wo0xT9AR7wG7fAP0Qs/g0b4WXTBa1Ve9RTPqd7qGrFbXauu FXtUP9VPvK2uU7Vir7pB3SD2qTpVJ36tblO3if1qmBom3lFPqR3igNqpdkqPele9K73qj+qPskx9 qj6V5eoz9Zn0qS/UF9LP37UMONKxZdDxOl5Z4ZQ75TLq+B2/jDlBJyLjTsJJyDR/9TJjtMAya/S/ Mmc0vzJvdL6y0mh7ZcHoeWXRaHhlyeh2ZZXR6srq6PzoS/IS/YaOyVtiqVhG1scKsRp5m9HqyilG kyunxvrG6uU0o8OV3zTaWznPaGzl40ZXK+cbLa18wuhn5QKjmZVPGp2sXGi0sfJbRgMrF8Umxqvl U/FW8VZqQLx1/DJ1Q7xdvIO6MX55/HI1KN4l3kXdHO8er1GDzd/KVLfG74yPUkPi98TvUUPjk+KT 1LD41PhU1RCfEX9I3R5/OD5b3RHfH9+v7oz/Jn5QjYpfiF9QoxN6qanGJFRCqbEJ/Z+6O5FOpNW4 xHcT31XjE99LfF9NSKxJ/FDda95W6r7EusQ6NTmxMfGCuj/xXuID9Y3EicQJ9VDibHKKmpmalvqR +lPqF2lltU8H0gHr/nQ2nbUa063SraxvpHule1tT0t9Jr7CmpVemV1nT08+mn7UeSj+Xfs6amd6Y fsF6OP2T9GbrkfRL6ZesR9OvpF+z5qS3pbdZf5t+I/2G9Vh6V3qv9c30vvSvrYXpd9K/tRalv0h/ YT2dPp8+by3N9M/UWt/O1GfqreWZhsxw6zuZEZmvWyszYzJjrFWZezL3WN/PTM5MtlZnGjON1g+y m7JbrDVGQ239yOimrfVGK2392OijrQ1GE209b3TQ1sbsr7LvWS/k6nJ11jYzSokG/f+A5lGqS/Ob pJv+v/Z/xUjzbbBo1SKNedvsbo7Rszv7Y/sTPUX/1D7DXC/n9l16yaO0+tWO5VjioGnL4remLYtD pi2Ld3VbDorDTtgJi9+ZFi2OmBYt3jNtUxylbfpom37djooyZGpb7jS1Ld80tS13mdqWvzS1LXeb mtSzOF2H8h3qsM7UoZprJKR2madXvzJPr47qUg5hbBGMLZKxRTG2WIwtZYwtPsYWP2NLgLElyNgS YmyJMLZEGVvijC0ZxoRKxoQiY0KJMaGKMeESxoRWjAmXMia0NqOBuMyMBqKNGQ1EWzMaiHZmNBDt zWggOpjRQHR0zF/U6OTYji06OyEnJK5wIk5EdNF9tiCujJfi1aKr6WXiKtPLRHfTy0SN6WWil+ll orfpZeIa08tEX9PLRD/Ty8R1ppeJWtPLxPWml4kBppeJgaaXiUGml+n3oe5H+k2o+5GoN/1I3Mas b5jpR6LB9CNxu+lB4g7TX8QI01/E101/ESNNfxF3mv4i7jL9RYwx/UWMM/1FjDf9RUww/UVMNP1F TDL9Rdxn+otoNP1FfMP0FzHF9BfxkOkv4mHTX8Qc01/E35j+Iuaa/iK+afqLmGf6i3jC9BfxpOkv YqHpL+Jbpr9Qw1Lkv/R+vtKsLuy38cb9/0frlZedtt8pX1e+sfzF8lfKt5fvKt9bfqD8cPmx8uPl p8rPlJ8tv+CzfT5fxJf05X3Vvja+Tr6uvhpfH1+tr85X72vwjfSN9U30Nfqm+2b55vrm+xb5lvpW +Fb71vo2+Db7tvq2+Xb69vj2+w75jvo+8J3wfez7zHfOL/wef8Af9af9BX8rfzt/Z383f09/X/8A /yD/EP9w/yj/OP8k/xT/DP9s/2P+Bf7F/mX+lf41/nX+jf4X/a/4t/t3+ff5D/qP+I/5j/tP+c/4 z/ovBOyALxAJJAP5QHWgTaBToGugJtAnUBuoC9QHGgIjA2MDEwONgemBWYG5gfmBRYGlgRWB1YG1 gQ2BzYGtgW2BnYE9gf2BQ4GjgQ8CJwIfBz4LnAuKoCcYCEaD6WAh2CrYLtg52C3YM9g3OCA4KDgk ODw4KjguOCk4JTgjODv4WHBBcHFwWXBlcE1wfXBTcEvwteCO4O7gvuDB4JHgseDx4KngmeDZ4IWQ HfKFIqFkKB+qDrUJdQp1DdWE+oRqQ3Wh+lBDaGRobGhiqDE0PTQrNDc0P7QotDS0IrQ6tDa0IbQ5 tDW0LbQztCe0P3QodDT0QehE6OPQZ6FzYRH2hAPhaDgdLoRbhduFO4e7hXuG+4YHhAeFh4SHh0eF x4UnhaeEZ4Rnhx8LLwgvDi8LrwyvCa8Lbwy/GH4lvD28K7w3fCB8OPx++MPwyfDp8Ofh8xEVKYuE IvFINlKKtI50iHSJdI/0jvSPDIwMjgyNjIiMjkyITI5Mi8yMzInMiyyMLIksj6yKrI1siGyObI1s i+yK7I0ciByOvB/5MHIycjpyNnKhwq7wVUQqkhX5iuqKNhWdK7pV9KzoWzGgYlDFkIrhFaMqxlVM qphSMaNidsVjFQsqFlcsq1hZsaZiXcXGii0Vr1XsqNhdsa/iUMXRig8qTlR8XPFZxbmoiJZFQ9F4 NBstRVtHO0S7RLtH+0Rro3XR+mhDdGR0bHRitFHPbmbp2cv86KLo0uiK6Oro2uiG6Obo1ui26K7o 3uiB6OHo+9Hj0VPRM9Gz0QsxO+aLRWJpPS62irWLdY510/OZvrEBscF6/jJCz0onxCbHpsVmxubE 5sUWxpbElsdWxZ6JrY9tim2JvRbbEdsTOxA7EvsgdjJ2JnY2diFux33xSDwZz8er423ineJd4zXx PvHaeF28Pt4QHxkfG58Yb9Tj5pz4vPii+NL4ivjq+Nr4hvjm+Nb4tvjO+B49jh6OH4sfj5+Kn4mf jV9I2AlfIpJIJvKJVol2ic6Jbomeif6JgYnBiaGJEYnRiQmJyYlpiZmJuYkFiSWJFYnVibWJDYnN iVcS2xO7EnsTBxNHEx8mTiZOJz5PnE+qZFkylEwmC8lWyXbJzsluyZ7JvskByUHJIcnhyVHJcclJ ySnJmcm5yQXJJckVyTXJdcmNyReTryS3J3cl9yYPJA8n309+mDyZPJ38PHk+pVJlqVAqnsqmSqnW qU6pbqmeqf6pganBqaGpEanRqQmpyXp0mpmam1qQWpxallqZWpNal9qYejH1Smp7aldqb+pg6kjq WOp46lTqs9S5tEh79Dshmk6bvwSebpfukq5J900PTA9OD02PSI9OT0w3pqenZ6UfSy9ML0kvT69K P5Nen96U3qLfAHrcTx9IH06/n/4wfTJ9Ov15+nxGZcoyoUw8k82UMq0zHTJdMt0zvfU7oC4zRI/7 YzOTMtMyMzNzMvMyCzNLMsszqzLPZNZnNmW2ZF7L7MjszuzLHMwcyRzLHM+cypzJnMuqbFk2kk1m 89nqbJtsp2zXbE22T7Y2W5etzw7Pjs5OyE7OTsvOzM7JzssuzC7JLs+uyq7Nbshuzm7VK5pd2b3Z A9nD2fezH2ZPZk9nP8+ez9m5QC6ey+eqc21ynXJdcz1zfXMDcoNyQ3Mjc2NzE3ONuem5Wbm5ufm5 xbnluVW5Z3Lrc5tyW3Kv5Xbkduf25Q7mjuSO5Y7nTuXO5M7mLuTtvC8fySfz+Xx1vk2+U75rvibf J1+br8vX5xvyI/Pj8pPz0/Oz8/Pyi/LL8qvyz+TX5zflt+Rfy+/I787vyx/MH8kfyx/Pn8qfyZ/N X6i0K32VkcpkZb6yurJNZafKrpU1lX0qB1QOrmyoHFU5obKxckblnMp5lQsrl1Qur1xV+Uzl+spN lVsqX6vcUbm7cl/lwcojlccqj1eeqjxTebbyQsEu+AqRQrKQL1QX2hQ6FboWagp9CrWFukJ9oaEw sjC2MLHQWJhemFWYW5hfWFRYWlhRWF1YV9hU2FrYXthd2F84XDhWOF44VThTOFu4ULSLvmKkmCzm i9XFNsVOxa7FmmKfYm2xrlhfbCiOLI4tTipOK84qPlZcWFxaXFl8prih+GLxteKO4u7ivuLB4pHi seLx4qnimeLZ4oWSXfKVIqVkKV+qLrUpdSp1LdWU+pRqS3Wl+lJDaWRpbGliqbE0vTSrNLc0v7So tLS0orS6tLa0obS5tLW0rbSztKe0v3SodLT0QelE6ePSZ6VzVaLKUxWoilalqwpVraraVXWu6lbV s6pv1YCqQVVDqoZXjaoaVzWpakrVjKrZVY9V/U/qvgU8qiJbtx67QwjpQLp37drdBEi6O92IyCvI SwSNgQASQIMaEREwYgwREYEA4SUgL+UpEF4iMIKOo4geH6iIgpBAREY9ioIoiAwiIiqCIqKeqn+X j7njvTP3es537rE//1q9atVaq9aurlqr03szO2t+1pKslVlrsx7J2pD1dNbmrO1Zu7PezjqQdSTr RNbprPMRK5IaCUTcSMNILNIk0iLSJtIxkhvpFukV6RvpFxkYKYkMj4yJTI7MjMyPLI2sjqyPPBZ5 KrIpsiWyPVITeSOyN3IgcjhyLHIycjpyLkqiSdHUaCDqRhtGY9Em0RbRNtGO0dxot2ifaFF0YLQk Ojw6Jjo5OjM6N7ooujy6Oro++lj0qeim6Jbo9mhN9I3o3uiB6OHosejJ6Ono+RiLJcfSVGoZjmXG 4rGmsVaxdrFOsbxYj1if2LWx/rHBsZLYsNjI2LjY5Nj02H2xhbGlsVWxh2KPxjbGno1tjm2L7Yzt ib0d2x87FDsaOxE7HTufbWWnZtvZGdmx7KbZrbLbZXfKzsvukd0n+9rs/tmDs0uzR2SPy56SPTt7 Yfby7LXZj2RvyH46+4XsV7Krsndnv5X9Xvah7GPZX2afjZN4crxe3I03jMfiTeIt4m3iHeO58W7x XvFr4wPiQ+LD4qPjE+PT43Pji+LL46vj6+OPxZ+Kb4pviW+P18TfiO+NH4gfjh+Ln4yfjp9LkERS IjURSLiJholYokmiRaJNomMiN9Et0SvRN9EvMTAxJFGWGJEYk5iYmJaYnZifWJJYmVibeCSxIfF0 4oXEK4mqxO7EW4n3Eh8mjiSOq2zS0r9ZU/gM8HngNmAVsAa4B/iWykwVQrYxMMng88CXgPsV1gKd DN3JkEmGTLLhVwFrgHuAelQKZFLASTGcgwrrgJ8KbanQlmo424BVwBrgHqAe64dMGjTUxai6oNNB p8OTdGhIBz8A/QH0BjA2gN4A9AegPwD9Af3bO3IjJIXBl4BajwOOAw0O+A74ErQE7cKWC0kXki5s ubDlwpYLW67+zZ9CbTGMUWGMCmNUGPIZ4GeAnwF+BvgNwGkAuw0Qk6l0I/Bp4CbgVuAO4C7g68A3 1dVWCNmHgfcY3ATcDNyncAa0zkDvDPTOQO8MaJ0BrTOgdQbkZ0FmFjizDOeQrm7hezW0VUNbNSSr 4WM1tFVDW7UeWycVvXMQ0bmY61zQ8zF2PnyYj7HzwV8AzQvQuwBjF6B3ATQvgOYF8GoBfUfhh5Bc ZHAzUOtZDM5iaFgM/mLwlwArYaUSMpWQqYSVSliphJVKWKlUMdaobS3DqGUYtQyjlkF+BfgrwF8B /grwV4KzEtZX6hjSJC2p8GngJuBW4A7gLuDrQHVtNUK2CTDZ4CbgZqDWWht0CnSnQCYFMimGvwO4 C/g6UI/ClVH4OtDjqNhQP/hp0JYGbWmGsxW4A7gL+DpQj60LmXrQkI5R+MTSIOggPAlCQxB8G/pt 9NoYa6PXhn4b+m3ot3Xs6U2QlAY3A7UeFxwXGlzwXfBDoEOgw7AVhmQYkmHYCsNWGLbCsBXWV1uh tpiBURkYlYFRGZBvCH5D8BuC3xD8RuA0gt1GOiYspj/hrDkwh01XeCkwF5gHzPdQa1D0TIUF4BR6 CH4h+EXgFANLgKXAMg8hOQJ0uYfgVICu1H/9ZAv1548t0juRQu3Vs8BKcJahdy0kX+PNFFbpGbGd er4Kd/z8+WavgfM6evdqSU4g/71Zext/XnW8EZBoDme6l9fRksQKzACOBo4BjgOOB07EKfa8kZoM nAKcBpyO/j3oTzaodSVjh06GxmRoTIbGZGhMNhpTIZsKOmBwNHAMcBxwPFCPC3jjAut0hBQ+qRG/ mV6n7Sla63ANav7jkHwcko8bzjbQWibD4GicAtrjqeBMDYwClgPHAiuAE7DPbzJSk4B3A6cC70H/ 6+ifYXAU9vKtoMuBY4EVQK1xhtFYDdl7QS8wOApYDhwLrADqcQu8cYF/11dU4UaNeoSit4LWOioN av77kHwfku8bzlbQWmaFwVHYObEfao7CUcBy4FhgBXAC9sZNRmoS8G7gVOA96Ec8aIrBUViVW0GX A8cCK4BaY4rRmAbZNNC2wVHAcuBYYAVQj7O9cUF9p5TGjRr1iKC+M1jTWkfYoObXhmRtSNY2nK2g tUxDg6Owt+graCE/SAUGgK6+20PnIvqODrTPmPZn/pP4jHj9Ft2PfKUxMAUa0jQGV2tOcBY4KSbr QrYZjABj+tMDOhl0KuhU0AHQAdACtADtgnZB14FmS99HorM0eKNyNpOpeVzPtwwvj7VeJvp3HToT 8mFd+KydCpvBt1pe5gp+LfBr4TyvZW3H57sGs9Yt8lnF1VitZrgZmVptk7HWwDNN14GuOsjF6lh6 j0tV8lxnrNCR5iGk0mCxrr6PQeWpNeDV9XiwVA+y9aC3HnrTQad7NCTT4amOwDOmrULreR4wngcN 6tHCQ1hVCN8FdDnocdCjaGjU7UteC6sSMtKjMUrCV9faAqwGbsea2WbWUA2iEcLOFMLIMLRgBZP6 oOubrFbTDZATNkBvA9iYipynGrgAWKn/Tq3zK3Xaeu3Tpv2ZvxF72C51YnitzjkfRiY2Cxrm6JVk 99Ac8YzmqNxyM3q9TBJZs/UX4ON6jwM9A3Q16GrQC0AvAL0I9CLQlaArQc/Gqp1K92G383xWeajJ Pj3uPrxb4eXjWLXTEIFpiMDj8Go6ONPBmY6VOh2xVvk25qtbZOS4JjP01bBvRt45U0eWv4H4zoKN 2dA1G3GfjZV6L65eNdZrNSKqo6RXzhzIzoHduVgfc83KmevxYG8eRsxDpOdhxHzQ8z0akvPhr577 06bdgXajiYnn/0KDevQiD2FVIa1GhLWuxehZjB6VkyOO6h19l+i8XPctgeUlkF4CHyuxTisx00r4 Uml8qcRaYWQpdsilGLkMWpaBXg56ucnQNb0SuflK9K6EjdmeJcgsQ6a/AjjV+lzhcR39YEPcuZWE vC4NaAPD+OVF2FsdOrvUkcH7n/kbcQp5/UneelGZ/C5k2puRLSsU6ZpjnwMn1WTLqBL0elT4uD6f QKeATgOdBtoGbYOWoCXoMOgwaD80J+lo6+wa3tjeWlatx/V8a+jVH3ot01rI6rHTUuy0tAV8q+1V HODXBr82cuza+troKgOzTvHWhfJ4O1BdPXERMuw6ptLYBc807YcuP3Jov4XqQq9oXWlARz0PIVUP FvV+yjXqtUXTPR4sBSAbgF5kdiqWmg56NCSD8NT2VhHaHWg3msg8Dd8ENAmMlh7CqqS7oAt7qao1 dI+LHtdb0ZoHiRD6Qh4N6RB8DOsVrbAauB1rxfMl7K1oWh9ZSn2MzIAWZIy0AegGpgrZhzpD1x+N 0NsINvyeJchkoJppCEzCiq7Wkqw5agKvLvltrZAhngNuAb4C3AbcBNwOrALuBL4A3KxR7y4K92jU 9yJqVPq8dotpXzHtNtNuMu1201aZVml3/NobhVuArwC3ATcBtwOrgNqbTHifCe8z4X0m/M6E35nw OxMeZ8LjCOQjkI9APoLZRjAqglERjIpAfwRjI95YzDBiZhgxM4yYGUbMDCNmhhEzw4iZYcTMsCVm 2BIzbIkZtsQMW2KGLTHDlphhS3gQg8cxeByDxzF4HIPHMXgcg8cxI/8CcDNq0Rqgvj5NoKcJ9DSB nibQ0AQamkBDE4xtgrFN0dvc4HYgKltYaQ7J5pBsDivNYSUHVnJgJQdWcuBtDvTkQE8O9ORATw70 5EBPDuKbY+KbY+KbY+KbY+KbY+KbY+KbY+KbY+JbiviWIr6liG8p4luK+JYivqWIbyk8uNTaoFH/ glbhy8Ct4D8B+lXgDmA18Hngi5DRFf+leu9Q+Do4eg5Kp9eKl0z7smm3mv4nzPtXTbvDtNWmfd60 Lxr5faplLBe+5sLXXPiaCy9z4WUuvMyFf7nwLw/yeZDPg3we5paHUXkYlYdReZhbHsbmmbFqbs6D WoPzoNag8GXgVvCfAP0qcAewGvg88EXI6Ojkw4d8+JAPH/LhQz58yIcP+fAhHz7k619OK6wBvgZ8 HvgiRkEnIp6PiBdAfwH0F0B/ATQXQHMBNBdAQwE09IZ8b8gUgi7E2EKMLYRvhV4vNBRCQyF8K4Rv hfCtEL4VQnMhNBfCt0L4VgjfiqC/CPqLoL8I+ougvwj6i6C/CPqLoK0I2oqgrQjXv8ispyKznorM eioy66nIrKcis56KzHoqMuupyKynIrOeisx6KoZ/xfCvGP4Vw79i+FcM/4rhXzH8K4Z/xfCvGP4V Y7bFmG0xdBcbX4uNr8XG12Lja7Hxtdj4Wmx8LYavTDLtk2TaJ4UvA7eC/wToV4E7gNqnEsyhBHMo wRxK4H0JvC+B9yXwuwR+l0K+FPKlkC/FnEsxqhSjSjGqFPpLMbbUjN0H1P6WmnmWmnmWmnmWmnmW mnmWmnmWmnmWmnkmMM8E5pnAPBOYZwLzTGCeCcwzAT/K4HcZ/C6D32Xwuwx+l8HvMvhd5sljrZap tcr194TwvAxzKcNcyjwOrl8Zrt8IWBgBCyNgYQR0j4DuEdA9AhpGQMNIyI+ETDnocowtx9hyeFfu 9UJDOTSUw7ty6CmHnnJ4Ug5PyuFJBbRVQFsFtFVAWwW0VUBbBbRVQFsFtFVAWwW0VSDWFeYaVZhr VGGuUYW5RhXmGlWYa1RhrlGFuUZDcY2G4hoNxTUaims0FNdoKK7RUFyjofDD5EDiOdNuMe0rpt1m 2k2m3W7aKtPuhNUJ+gRTuAX4CnAbcBNwO7AKiBzFy0uM1YixGjFWI8ZqxFiNGKsRYzVirM6D1Xmw Og9W58HqPFidB6vzYHWed3J7p7WxmmOs5hirOcZqjrGaY6zmGKs5xuoaWF0Dq2tgdQ2sroHVNbC6 BlbXwOpifFM9z0Pksos0Lf8GejFwifl+uwao6QeAW4GPAdeid62h9ypcD/pR4C58s/2qh8iSd2ra vQA08nVWY74V3wXU9JvAM8BDwL3o3WvodxTuB/0h8EfoP+shOD/Ayu1eL/An8136LqCm8Vcj3gQo gHXQW8fQygqvCzqICnce7n0jRD99rTZprl5ppCXRT2zsQDoRSS4j+SSD9CA9SYz0Ui/9BIb+pDEZ oF6tyUByC7mY3EpuI5eQoeQuNWIUmaRGPEDWkavJI+QxcgPZSJ5Tcs+Tl0gJeZnsILeTXaSGjCS7 1Ws02aNe5eRN8jYZQ/aSD8h4clC9ppGPyFFyDzmmXveSE+p1HzlJviFzyFmqa/NM2pisoRfS5uRR 2pK2JE/QHNqBbKQd6WVkE82l3clLtCftRXbQPrQP2UkL6QCyiw6kA8k7dDC9leylt9Gh5AC9nY4i B2k5vZscY+1YO/I1u4R1JKfZ9exm8g0bz6ZRypaypTSFPcGeoHXY0+wZmsqeY8/RNPY8e4HWZVvY FprOdrPdNMA+Zh/TIDvGPqU2+4x9Rh32OTtJJTvFTtEQp5zSMHe5S+vzBrwhzeCZPJM25BEepY14 gidoVmBm4CEa0b9Do50DGwJv0a6BtwP76dDAgSChI4IsmEwrgynBdLoquDC4kq4Prgo+SJ8Mrgmu pf8WXBdcR58J/jn4DH02+FzwOfpq8MXgi3R78KWgqmaDfw0epjXBI7ZDP7QvsXNZup1nd2Uhu5vd nWXYV9oFrKHd2+7PsuwB9gDW3B5sD2Yt7GK7hLW0J9mTWBv7bnsqa2vfY89nHeyF9v2sq73Yfop1 s5+2/8qGCC78bIqoK+qxOSIggmyecITDFoiwiLOForFozB4UTUVTtlo0E63YGpEnrmPrxfViFHtB lIv57F3xrHiWfSUOikPslPhCfMlOi7NOKvvGSXNa8DpOK+c23swZ6qziQ5zVkvLlkss4Py8by1Ir U5bJ8dbNcqKca42U8+Vq6x65Vv7ZWiL3y/3WKvmRPGw9KI/II9YaeVQes9bK4/KEtU6elF9bj8gz 8oy1wW3gNrCecLPduLXRbew2tp5ym7hNrX9zm7ktrGfdVm5b63m3vdveetkd7A62XnFvc0utrW6Z W2a96g5zh1vb3RHuSKvaHe1WWDXuBHeC9QaequYj9WiEteZdrSL1OepActVn6WrSjwwmpWQEGUem kNlkIVlO1pJHyVPkBbJNfTbeIvvJYXKcnCLnKKFJNDW0i/DQ9tCOUA3aqtBraKtDu9HuDO1R7Q5F /RXtjtAbaKtCb6KtDr2FdmfobdVWKbl30O4I7UVbFXoXbXXoPbQ7Q/tVW63k3ke7I3QAbVXoA7TV oQ/R7gwdUu1OJfcR2h2hw2irQh+jrQ4dQbszpE5t1fvvCqtC6vxVPQcV7vwDETmKmW8PfWIic8xE 5lMTmeMmMp+ZyJwwEfncROSkiciXJiJfmYicMhH52kTktInINyYi35qInDUR+c5E5JyJyHkTkR9M RH40EfnJi0iYmIj8Tc1/e+gLROQMIvL9H4tImHkRCXMvImHLi0jY50UknORFJJzsRSRc21sr4RQv MuE6XmTCqV5kwn4vMuE0LzLhul5EwvW8iIQDXkTCQS8iYduLSFh4EQk7XkTCrheRcMiLSDjsRSRc 30Qkw4tImOqIhGvplRJO1xEJyz8YkYYmIo1MRDJNRLJMRCImIjETkWwTkbiJSMJEpLGJSBMTkQtN RJp6ayV8kYlMMxOZ5iYyLUxkWprItDIRaW0icrGJSBsTkbYmIu1MRBogIlFE5AK9UsI5fzAiHUxE LjER6WgicqmJSCcTkctMRC43Eck1EbnCRCTPRKSriUi+iUg3E5HuJiI9TER6mogUmIj0MhHpbdZK HxOZq0xkrjaRKTSR6Wsi0x4R6YyIdEFErtQrReUxVPuN+yyKyAX0E3qcfk7P0e/pj/QnxpmP1WIp zM/SWDoLMMEcNpu34yX8Nl7Kh/Iyfjsfxu/gw/mdfAS/i4/ko/hoXs7H8LF8HK/wZQYfxt/tjtKj hNBP6aeE0hP0BGH0LFWff3qe/kB8TP1HajGLWSSZJbEkUpupF0lhdVgqqcPqsnrEz4LMJnXZLDaL pPO2vC0J8L78VhL0NfI1Iong+uB6lVkxEiYpvIpX8518F6/hr/Hd/HW+h/9Vz1L5V4FZapnlfAVf yR/gq/iDfDVfw9fyP/2DzP9Zj75jxf3NHSutcfc7gUQV/s35//Welot/08dUBkr042KUJw/hvv0e RD+XofWvd6jz9SqbJ8pL1fKHVLsO71fpVr1fpeSTSBp/2HAfNly1Fyi/9V+4YqQuX8qX8Xv5fXwO n8vn8fl8AV/I7+eL+GK+hFcqGQsxJpgT44/yv5BU/iR/UmWyTGWkGbwzv5xfwbvwbrwHL+C9+QB+ Ex/IB/HB/GZezG/hQ/itv3fd9Vx4J95Jab6MX6Zmnctzlf48rlY/z+f5xOLdeXfi4z15T5LEe/Fe pJa6njeSZLWy7lTz96x3UqNz1ah8Jd1TSfXl1/Br+XW8iF/P+/EbeH9+4++tRFjvzDsr65dz/dT4 K/gVynoX3kVZ78a7Kes9eA9lvYAXKOu9eW9lfYBaTcmIw6/WOyvrVyjr3ZT1gt+1/jvxUKN9yu/L lfU8ZZEp33soi72UlSTlbQVJNvqVjJbQ/br3X/1MQX8nzC4X88rHjHpiLvozofT7GrL71K5ViybT 2jSF1qGp1E/TaF1aj6bTAA1SmwrqUEldGqJhWp9m0Aa0IW2kqoMsGqFRGqPZNE4TtDG9gDZR1UJT ehFtRpvTFqpmaKUqhtb0YtqGtqXtaHvagV6iqodLaSfamV5GL1c1xBU0j3ahXWk+7Ua70x70SlVR FNBetLeqKa6iV6uaoi+9hl5Lr6NF9Hraj95A+9Mb6QB6k6ozBqkq42ZaTG+hQ+ittERVG6V0KC1T 9cYwegcdTu+kI+hddCQdRUer6mMMHUvH0Qo6nk6gE+kkOpneTafQqXQafZx+Sb+ip+kZVsxuYUPY rayE3cZK2VBWxm5nw9gdbDi7k41gd7GRbBQbzcrZGDaWjWMVqnaZwCaySWwyu5tNYVPZNHYvO8u+ Y+fY9+w8+4H9yH5SiQLljHNucR9P4rV4Mq/NU3gdnsr9PI3X5fV4Og/wILe54A6XqnYJ8TCvzzN0 /cIbqfolS1cvPMazeVxVMI35BbwJv1CcFKfEN+Ir8bU4Iz4VywJHAn8LHA18EjgW+DRwPPBZ4ETg 88DJwBeBLwNfBU4Fvg6cDpwJfBP4NnA28F3gXOD7wPnAD4EfAz8FSVCVU0EetIK+YFKwVjA5WFtV P3WCqUF/MC1YN1gvmB4UwbD9vn3A/sD+0D5oH7I/sg/bH9tH7L/ZR+1P7GP2p/Zx+zP7hP25fdL+ wv7S/so+ZX9tn7bP2N/Y39pn7e/sc/b39nn7B/X6yf5JqCWlahlL+ESSqCWSRW2RIuqIVOEXabq6 Eem6uhG2ejlCqldIVTj1RYZoIBqKRiJTZImIiIqYyBZxkVB1zwWiibhQVT4XqbqnuWghWopWIke0 FheLNqKtaCfaiw7iEtFRXCo6ic6qKuoiuop80U10Fz3ElaKnKBC9RG/RR1wlrhaFoq+4RlwrrhNF qnLqJ24Q/cWNYoC4SQwUg8RgcbMoFreIIeJWUSJuE6ViqCgTt4th4g4xXNwpRoi7xEgxSoxW9dYY MVaMExVivJggJopJYrK4W0wRU8U0cY+YLmaImWKWmC3uFQvEQnG/WCQWiyWiUiwVy8Vl4nKRK64Q 94k5Yq6YJ+aL4+IzcUJ8rms2cVp865xwPndOOl84XzpfOaecr53TzhnnW+es851zzvneOe/84Pzo /CSJpLKOTJV+mSbrynoyXQZkUNoqpI6U0pUhGZb1ZYZsKBvJTJklIzIqYzJbxmUL2VK2kjmytbxY tpFt5SWyo+wkO8vL5OUyV14h82QX2VXmy+6yl+wt+8ir5NWyUF4jr5XXySJ5vewnb5D95Y1ygLxJ DpSD5c2yWN4ih8hbZYm8TZa6+W43t7vbw73S7ekWuL3c3m4f9yr3arfQ7ete417rXucWude7/dwb 3P7uje4A9yZ3oDtIVYU3u8XuLe4Q91a3RFeH7lBVHd6uasM73OHunao6vMsd6Y5S9WG5O8Yd645z K9zxqk6c6E5yJ7t3u1Pcqe409x53ujvDnenOcmeHPwufCH8ePhn+Ivxl+KvwqfDX4dPhM+Fvw2fD 39XvpX9V491PSh+jj5FJ9CT9gkymp+jXZAruMJ3GZrPZZB3uM12P+0z34z7T93Gf6QHcZ/oB7jP9 EPeZHsR9podwn+lHuM/0MO4zrRdUl4Wm4z7TgL5/l+60d9mv0924q/RNXaPTfY7jtKAnnQ7Obaw2 7i1tH349/C6bEN4Xfp/NxL2l96ozfbo66wMqm4iTbip3Ha+fpOR8g2fOKEo2+OUpOPWIQzJkO8LE LqkyPlEjOyh8TV76i2w39f45VVunKn0uaUhisofmSJUNii2yp8JXZIHCbbLvL2MGgVL5hopPhkpe Iiyi/xUBFlNZTFOmcnnWnDVXuUQOy1Gaqcqxk37WTprq+9Gp/heZ9a8V6gBVXaRp1ep36eZdus5H yKfqRegaukZlig/RdUriUfoXxf/nWrsbPd3/L7QyXwl78h9Oyv+Oc/K/6ZT8n3Q6Kiu3KA/HsLt+ PSWVtyPFcVbyX3tS2j8KIpgQwhXtcGIeVGflUX2G2Z+p8+gCnI+n1NmoT0XvTPzpXzwNnX9yCv7j GdhanX6/nns/nyr/v51/v55yC9Sp3eaXc3CZWK6yjg+Rb+hcQ2cax+1PxUIv0xCLVJ7xtX1GtNdZ huhgnzNnpDof5Ug5So6W5XKMHCvHyQo5Xk6XM+RMOUvOlvfK++QcOVculcvkcrlCrpQPyFXyQbn6 d0/Vb/7AudrgXzhZ28n2sgPO10t/94Ttps7YHvJK2VMW/N1Z2/d/e9oO+k86b//+tB30n3He2h+L +//pmXsFmUr0v9l0H6lSFcpOUqM4u8nbpCvZS46R3uQz6iODcSJPYJeyTmQiu4x1IZNZPutDprOr WV8yn13LbiT3s5vYILKC3cxuJqvwfcCD7FX2LVmNp3G847N8PvKuL9mXTPb5Unwp6uxO9aWqs1s/ n+OAr54vqM5ux+eok/rZwMfqpLaDtjqp5wTnqJN6XnAeDQQXBBfQYPCh4EPU1t8rUGFn2jHq2HE7 Tuvbje0LaYZ9kd2CZtqt7ItpzG5r59LGdp7dk7a2e9kD6KX2QLuE9rKH2cPodfad9l20yB5ll9Mb VA4wlw6w59tL6Ah7qcoExtpv2O/QJ+x37X30GbFCrKKbxGqxlm4WD4l19GXxsNhAt4qN4hm6SxwR x+hfHUvlDG87jVXO8IEzyLmNHnXucmbSL5z7nIeZz/mLs5tlOW84x9gVLne7sv7uPHceWx26JnQN WxM+ED7K1oaPhY+zx+sX1C9gG/GNg/4VZhqeT3YvqTac7n/H2UkG8Tf5W/zf+dv8Hb6Xv8vf4/v4 fv4+P8A/4B/yg/wQ/4gf5h/zI/xv/Cj/hB/jn/Lj9B46nc6gM+ksOpveS++jc+hcOo/OpwvoQno/ XUQX0yW0ki6ly+hyuoKupA/QVXwWn83H8wl8Ip/EJ/O7+RQ+lU/j9/wh3nQ+g8/EtyUWnkE7lawk YXzv0VrVyxWkDb73GIDvPQYquQ4k/P/iu/52B7q9b37Cv/nmRz+/h6l8qUzJBFlrdrHKodozlZnp 01TlTeokJUniO/E9SRY/OJTUcaTjknpO2GlAAk6+0404Tg+ngLhOH6cvyVD72RckS+1mZ1T2pvYr coHarwLkQr3HkOZqj8knLfXOQi5WO0tf0vYf/GkLf5ozfT9KWPnTBv60V3lcR5X/WsqricSnvLqb JKvzfRqpDd9S4JsfvgXgm+00crKUV1EnQerDz0z4GXGKnH4k7vR3BpIL4G0zeNsS3raBt+3UzuqQ jmpfbUA6w/Mu8Dxf7X39yJVq5xtEeplnG/VU/x+C5+3wJLdMZIPkF46mGqt1O5AO+YXHVJ73KPn5 +byax4ir5trWxN7CXJPUXCeRWrgCdTBXvzgoDpI0VZN9QeqqHJ2r6+BzUlXUHTXLmHOB04K0Ufn6 QNLJGezcRm5R58tZcrtzTlIyTp0fDcgUdTrEyWJ1JvQgD6jrMIhsUjt3KdmjTq/xZK86seaSD9Up tZocVT75UXMQlYdNI1moNnJRbVyBaiMP1UYXVBtdUW3ko9ropmsI0l2cVF5epZ9PQwqdE/LPZM9/ gUaK56T+z9H765oZjCvfHuu/z2/WTPtf1wyZSDr9wmNkOGnymzWjKijCHb8jCHFaOu1JbadU2dHf D6Z4PsPbLHgbgbdReBuDt9nwNg5vE/C2MfxsYWb+M/bCrpuBHSoVtclD+LdqHtXf7ypfwiRT1X1N 6Wp9NwT9E+5aWKd3Z6q/W7+P/hn3Kei7LeZi156pqpxfnwk2ADNRe42q+PQTtQg5rl5Un2aE2XPt uYTbe+w9xBKrxCriE2vFWrUXbRAbSC13g7uBJLtPuk+S2m6VW0VS3D3uHqKqLXKheVLXbNh8SZ3p STjT66kz/Q0SJIfVy1Xr+ygJUXUwk3CgJvAaqY9nYjXAM7Ey1UnamGTZF9pNScRub7cnMbuj3ZFk 293t7iRuF9gFJGFfY19LGtvX29eTJvqv6+RCPB+rKZ6MdRGejNUMT8ZqYU+2p5DW9gJ7CWmrztYH yaX2E/YTpIuquHeRrnhuVj6em9UNT8nqgadkXek+4K4iPd0X3BdJLzzXqo+7091FrnLfct8hhXii 1XWhvFAeKQqpF7keT7HqhydX9UdEOevMurJr9DphnVTWQlgXlbVQ1lflK/oL/kfIVWr9pDl1nXpO uhNwgo7tCLWWWjk5TmvnYqeN09Zp57RX62qoU+bc7gxz7nCGO3c6IySTXFrSJ5NkLZksa8sUmZCN 5QWyibxQNpUXyWayuRwqy+Ttcpi8Qw6Xd8oR8i45QU6Uk+RkebecIqfKafIeOU/OlwvkQnm/XCQX yyWyUq6Ra+Wf5ENynVwvH5aPSL1+auvMQq1ylVkoWmUWaof/Tu1o9VWuG1enzGC1f12k8u/xavee rvavzirPXk26eflCUAbDWHmT6RTDcYP1f8P553HSY0LBjN+M6UoyAzLgBNxAKBAO1A9kBBoEGgYa BdoF2vvf8+/z7/e/7z/k/8h/2P+x/5j/U/9x/2f+L/1f+U/5v/af9X/nP+f/nui7x/7AMz79HfyX kBT/2/53Sar/gP8gqec/4v+E2P4T/i+I6z/t/1b/fafWUXKe/sgslsLqMUftCxHWmDVTJ00HlcF2 ZT1V7lrEBqjdrVTV1KPVeTOFzWRz2SK2nK1m69lj7Cm2iW1h21kNe4PtZQfYYXaMnWSn2TlVRyep mjmg6uOGqhZuwlvwNrwjz+Xd8LeQfnwgH8LL+Ag+RuU801TmNJ8v4Sv5Wv4I38Cf5i/wV3gV360y t/dUlnaEH+df8m/4eYtZyVaaZVthK9OKW02tVlY7q5OVZ/Ww+ljXWv2twVaJNcwaaY2zJlvTrfus hdZSa5X1kPWotVH/e0nWNmuntUc/WdY6ZB21TlinrLPWjyrvTlHZtePL8EV8jX3NfK19HXyX+br6 evqu9hX5BviKfaW+4b7RvvG+Kb6Zvrm+Rb7lvtW+9b7HfE/5Nvm2+Lb7anxv+Pb6DvgO+/6jvTsP jqrI4wDeM2G6M+lvBzI9gWGAEJIQIIRDwg0iAgn3FbORU4QIRkBUDFc4DIdxCVdEBVSUFVmWZSUc Ai73JQSQBYyIiIqKuCIqEm4Qdb+TrS0Yjlq1/GP/2PpWfSp5OarmzXvdv+73pt9J12nXeddVKaSU kB7pk1EyTibIurKhbC5byXayi0yTveSDcpAcKofL0XKCnCLzZL6cI+fLhXKJLJCr5Xq5Ve6S+2SR PCKPyRPylDwjL8pryqlCVbjyKr+KVvEqUdVTjVUL1UZ1UN1UuuqjBqhMNUxlqWyVo3LVdDVbzVOv qkVqqVqh1qqNarvarfarQ+qo+kw4dTLupiloQdviHtoOLWl73Es7oBXtiNa0E9rQzkimXZBCu6It 7QaeR7o72tNUdKD3oSNNQyf6B3Sm6WAvoe9HV9oD3WhPdKe9kEp74z7aBzyXdF/wLNMPIJ32w/30 QfSg/dGTDkAvmoHe9CGwDdMD0ZcOwgP0YfSjmWAVrB9BfzoYA+gQZNCheIg+ioF0GAbRx/AwfRyZ 9Ak8QodjMH0SQ2gWWO/qEXiUjsQwOgqP0dF4XDhR3UTz63vBPla3AvsnvQpL6ZtgT6ZXgq2SHoMn aDaG07F4ko5DFh2PEXQCRtKnwCpW52A0nYgxdBKy6WSMpVMwjj6N8TQXE+gzeIr+ETl0KibSPLC9 0dMwmU7HFDoDT9OZyKWz8AzNB0cQ+llMpbORR5/DNPo8ptMXMIPOwUw6F7PoPOTTF/EsfQmz6ct4 js7H8/QVvEBfxRy6AHPpnzCPvoYX6UK8RF/Hy3QR5tM/4xW6GBxj6L9gAV0CVgP6r3iN1kcibYBa tCFq00aoQxujLm2Cu2hT1KPNkESboz69Gw3oWhTQpVhI38AiWoDFdAWW0GVgnaGXg3WG/htYeUQU R5yl5yLO0wsRF7m9NZrRNmhO12MV3YA36Uasppuwhm7GWroFb9GtYBust2Ed3Y71dAc20LcR+Azq Tmyiu7CZFmIL3Y2tdA+20b3YTt/BDroPb9N/YCfdj130ADha1Qexm76LPbQIe+l7eIcewj76PgKr qBwG62T9AQ7QIzhIP8S79CiK6Ed4j36MQ/QTvE+P4TD9FB/Qz3CEfo4P6XEcpV/gI3oCH9Mv8Qn9 J47Rr/ApPYlAK/E1PqencJx+gy/otzhBv8OX9DQ4EtDf4yt6BidpMb6mZ3GKnsM39Dy+pRfwHb2I 0/QSvqeXcYZeQTG9Cr47+geco9fA90j/iAv0ZwTeqZ9wieedwGXqwBXqxFUaAvaUKIVr1IUfqcRP VOFnGmrYWcNt2DMjzLCvhjaslAFTihrjouFG0tJG0TImlEYYN/UY9uuwhhUjvAY00hha1oTTcqY0 9ZkytLyJoH7D2hoVjKUVjZdWMpE0ypSllU05Gm18tIopT2OMn8aaCjTOsIJGVVOJxpsoWs1UpjVM FZpgYmhNE8v90AIN6T1oRFuC40L9FpbT1XiDrsEy+nesoOuwksf5pQjuMfb0N8weiEKmfskcQoOS +1MaOX1On2jC3j9JNC2Zv0otmb9Kc7ZlhdPLme7sITJL7i4YErIhZKMY4XK6nGJUyWzVaFeEyyOy S2alxrH3jBPjZX/ZX+TIDJkhJqpYlS4mqS3qsliroSHOaKu9otgkmxRxznQyncUF09WkiksmzaSJ QNXTQcSIQv5uaV1GR2iPNjo88Dc6UpfV5bRPl9d+XUFX1JV0lK6so3WsjtNVdIyuquN1NV1d19AJ uqZODNy5I6YFni0XmP8QzlKmVLgopSKUR0iVrFJEqBqjskWYWqYKBEJnheaL8NAfQq+JMu5a7trC 4+7j7iu87qnuPFHWvcm9Wfjcxe6zwh9WNSxeVAzrGdZLRIXNCJvJ8Q0rNeEShbZS5Frv3MjF4pc8 24DHloY364a19eeLjo6VjjWOdY5NgZUAHHsd+x1FjsOOo7ZqSB1b2UbbKjbGxto4W93WtnVsXXuX rWeTbH3bwDa0jWxj28Q2tSm2rW1n29sOtqPtZDvbLrar7Wa721TPSM9oT7ZnnGeCJ8czyTPFk2ub 25Y2zabbnra37Wv72f42ww60mf4t/m3+Hf6d/kL/Hhtvq4n/rzb/a1eb55FmW9nWto1NFreuZ82j xdawCbamTbS1xI1rBYcKx7/vqHL+t3u9/nMnFo8jZ2Nnzg1zdIEtzZyTr8+SOY6L0zy3o1nbxzkT uC2J9XwmK/qhzuHOUc6xrpDIwM9vG46sgsL/EpyYW8NxWFAC11pvm4Sbkhi4EhuUpFvD8V1Q+Fru kLJXgsPXHJzBtwvHjEHhXgpOTkmufz/8pmQxo+6QsbcLx6fBybopuTdlXnD+J+cGHeKYqCCai1Yc Z3cpecbo9eeLThBTRJ7IF3PY5i0US0SBWC3Wi61sK/eJInEk8Impkqvzv9aY32TSb/EOM2tRAiEH bZS3mneW90DkgsjXI5f7lvtW+Qp9B37XOSzxL3BHG6cNCmVuZHN0cmVhbQ0KZW5kb2JqDQoyMjgg MCBvYmoNCjw8L1R5cGUvWFJlZi9TaXplIDIyOC9XWyAxIDQgMl0gL1Jvb3QgMSAwIFIvSW5mbyA2 NCAwIFIvSURbPDkwQUVCMDBDMTU5Q0MzNDc5NjUzRUU5NjY0QjdERDQwPjw5MEFFQjAwQzE1OUND MzQ3OTY1M0VFOTY2NEI3REQ0MD5dIC9GaWx0ZXIvRmxhdGVEZWNvZGUvTGVuZ3RoIDU1Mz4+DQpz dHJlYW0NCnicNdRHTNNhGMfxP1ChQCnbAS7KkCpDmTJqtYhFRFBUBEFQETejDMWBDIFWEcV4EuPF o1sv4smDJxMTV+LFg8aziQdP6gHb31ffw/vJm7zjyfvkeQzDP+bng/xzrGEEGIIvIjhLRPYLS6GI qoJ38F1Yb8BnEf1BxIyK2EERlyriE+AWPBcJjXBXJN4UKa/gl7DlwnuR+kykNYl0p8goEZl/hP2T yO4UOR0ir1rku0RxkShLF04ic/4QFTPCPSyqfoqab6K2QdS1iNavou236CLAbq/o8QlPqegtEH2V YrxdTPDsZITwZotZ/vq2Q9wjK/ft4kGyeMhlj1/78+TPmNsYhwmYhEvwb4vXf+DJ3P9VEARDCISB CRZAKJghHCIgEiwQBVaIhWiIgTiIBx8sggRIhIWwGJZAEiTDUlgGy2EFrIQUsEEqpEE6ZMAqyITL YIfVsAayIBtyIBfWwjrIg3wogEIogmJYD2VQAqVQAeVwBRywAZywETaBCzZDJWwBN1TBVqiGbVAD 26EW6mAH7IR62AW7YQ80wF5ohCaYgn3QDC2wH1qhDQ7AQTgE7XAYOuAIHIVjcBxOwFU4CaegE7qg G3rAA73QB/0wAKfhDAzCWTgH5+ECDMFFGIYRGIVpGPOX75xLZf9CXTho5JEYqwsQEqkGEWJJgnph vRPA5HsjpmbFtCGuqfeYrmeIGVuAUPNbEf4yQFj5R+F4GsDc7xEDzYbxF5V1kZANCmVuZHN0cmVh bQ0KZW5kb2JqDQp4cmVmDQowIDIyOQ0KMDAwMDAwMDA2NSA2NTUzNSBmDQowMDAwMDAwMDE3IDAw MDAwIG4NCjAwMDAwMDAxMjUgMDAwMDAgbg0KMDAwMDAwMDIyMyAwMDAwMCBuDQowMDAwMDAwNTU2 IDAwMDAwIG4NCjAwMDAwMDI5MzIgMDAwMDAgbg0KMDAwMDAwMzEyNSAwMDAwMCBuDQowMDAwMDAz NDAwIDAwMDAwIG4NCjAwMDAwMDM1MzYgMDAwMDAgbg0KMDAwMDAwMzU2NCAwMDAwMCBuDQowMDAw MDAzNzI5IDAwMDAwIG4NCjAwMDAwMDM4MDMgMDAwMDAgbg0KMDAwMDAwNDA1MCAwMDAwMCBuDQow MDAwMDA0MjI1IDAwMDAwIG4NCjAwMDAwMDQ0NzIgMDAwMDAgbg0KMDAwMDAwNDY0MyAwMDAwMCBu DQowMDAwMDA0ODg0IDAwMDAwIG4NCjAwMDAwMDUwMTcgMDAwMDAgbg0KMDAwMDAwNTA0NyAwMDAw MCBuDQowMDAwMDA1MjA4IDAwMDAwIG4NCjAwMDAwMDUyODIgMDAwMDAgbg0KMDAwMDAwNTUyMyAw MDAwMCBuDQowMDAwMDA4NjQzIDAwMDAwIG4NCjAwMDAwMDg2OTcgMDAwMDAgbg0KMDAwMDAwODc1 MSAwMDAwMCBuDQowMDAwMDA4OTEzIDAwMDAwIG4NCjAwMDAwMDkxMzggMDAwMDAgbg0KMDAwMDAw OTMwNSAwMDAwMCBuDQowMDAwMDA5NTM1IDAwMDAwIG4NCjAwMDAwMDk3ODUgMDAwMDAgbg0KMDAw MDAxMDQ5MSAwMDAwMCBuDQowMDAwMDEwNzEwIDAwMDAwIG4NCjAwMDAwMTE2MjkgMDAwMDAgbg0K MDAwMDAxMTg3NyAwMDAwMCBuDQowMDAwMDEyODc0IDAwMDAwIG4NCjAwMDAwMTMxMjIgMDAwMDAg bg0KMDAwMDAxNDEzNCAwMDAwMCBuDQowMDAwMDE1MTQxIDAwMDAwIG4NCjAwMDAwMTYxNDggMDAw MDAgbg0KMDAwMDAxNjM2NyAwMDAwMCBuDQowMDAwMDE3Mjk2IDAwMDAwIG4NCjAwMDAwMTgzMDMg MDAwMDAgbg0KMDAwMDAxODY3NSAwMDAwMCBuDQowMDAwMDE5NjgyIDAwMDAwIG4NCjAwMDAwMjAw NTQgMDAwMDAgbg0KMDAwMDAyMDMxNiAwMDAwMCBuDQowMDAwMDI0Mjg4IDAwMDAwIG4NCjAwMDAw MjQ1NzAgMDAwMDAgbg0KMDAwMDAyODM2OSAwMDAwMCBuDQowMDAwMDI4NTUxIDAwMDAwIG4NCjAw MDAwMjg4MDggMDAwMDAgbg0KMDAwMDAyODk4NiAwMDAwMCBuDQowMDAwMDI5MjM2IDAwMDAwIG4N CjAwMDAwMjk1MDkgMDAwMDAgbg0KMDAwMDAzMzg5MSAwMDAwMCBuDQowMDAwMDM0MDY4IDAwMDAw IG4NCjAwMDAwMzQzMTQgMDAwMDAgbg0KMDAwMDAzNDYwNSAwMDAwMCBuDQowMDAwMDM5NDc3IDAw MDAwIG4NCjAwMDAwMzk3NDEgMDAwMDAgbg0KMDAwMDA0MzY0NSAwMDAwMCBuDQowMDAwMDQzODE3 IDAwMDAwIG4NCjAwMDAwNDQwNTkgMDAwMDAgbg0KMDAwMDA0NDM0MCAwMDAwMCBuDQowMDAwMDQ1 MDAxIDAwMDAwIG4NCjAwMDAwMDAwNjYgNjU1MzUgZg0KMDAwMDAwMDA2NyA2NTUzNSBmDQowMDAw MDAwMDY4IDY1NTM1IGYNCjAwMDAwMDAwNjkgNjU1MzUgZg0KMDAwMDAwMDA3MCA2NTUzNSBmDQow MDAwMDAwMDcxIDY1NTM1IGYNCjAwMDAwMDAwNzIgNjU1MzUgZg0KMDAwMDAwMDA3MyA2NTUzNSBm DQowMDAwMDAwMDc0IDY1NTM1IGYNCjAwMDAwMDAwNzUgNjU1MzUgZg0KMDAwMDAwMDA3NiA2NTUz NSBmDQowMDAwMDAwMDc3IDY1NTM1IGYNCjAwMDAwMDAwNzggNjU1MzUgZg0KMDAwMDAwMDA3OSA2 NTUzNSBmDQowMDAwMDAwMDgwIDY1NTM1IGYNCjAwMDAwMDAwODEgNjU1MzUgZg0KMDAwMDAwMDA4 MiA2NTUzNSBmDQowMDAwMDAwMDgzIDY1NTM1IGYNCjAwMDAwMDAwODQgNjU1MzUgZg0KMDAwMDAw MDA4NSA2NTUzNSBmDQowMDAwMDAwMDg2IDY1NTM1IGYNCjAwMDAwMDAwODcgNjU1MzUgZg0KMDAw MDAwMDA4OCA2NTUzNSBmDQowMDAwMDAwMDg5IDY1NTM1IGYNCjAwMDAwMDAwOTAgNjU1MzUgZg0K MDAwMDAwMDA5MSA2NTUzNSBmDQowMDAwMDAwMDkyIDY1NTM1IGYNCjAwMDAwMDAwOTMgNjU1MzUg Zg0KMDAwMDAwMDA5NCA2NTUzNSBmDQowMDAwMDAwMDk1IDY1NTM1IGYNCjAwMDAwMDAwOTYgNjU1 MzUgZg0KMDAwMDAwMDA5NyA2NTUzNSBmDQowMDAwMDAwMDk4IDY1NTM1IGYNCjAwMDAwMDAwOTkg NjU1MzUgZg0KMDAwMDAwMDEwMCA2NTUzNSBmDQowMDAwMDAwMTAxIDY1NTM1IGYNCjAwMDAwMDAx MDIgNjU1MzUgZg0KMDAwMDAwMDEwMyA2NTUzNSBmDQowMDAwMDAwMTA0IDY1NTM1IGYNCjAwMDAw MDAxMDUgNjU1MzUgZg0KMDAwMDAwMDEwNiA2NTUzNSBmDQowMDAwMDAwMTA3IDY1NTM1IGYNCjAw MDAwMDAxMDggNjU1MzUgZg0KMDAwMDAwMDEwOSA2NTUzNSBmDQowMDAwMDAwMTEwIDY1NTM1IGYN CjAwMDAwMDAxMTEgNjU1MzUgZg0KMDAwMDAwMDExMiA2NTUzNSBmDQowMDAwMDAwMTEzIDY1NTM1 IGYNCjAwMDAwMDAxMTQgNjU1MzUgZg0KMDAwMDAwMDExNSA2NTUzNSBmDQowMDAwMDAwMTE2IDY1 NTM1IGYNCjAwMDAwMDAxMTcgNjU1MzUgZg0KMDAwMDAwMDExOCA2NTUzNSBmDQowMDAwMDAwMTE5 IDY1NTM1IGYNCjAwMDAwMDAxMjAgNjU1MzUgZg0KMDAwMDAwMDEyMSA2NTUzNSBmDQowMDAwMDAw MTIyIDY1NTM1IGYNCjAwMDAwMDAxMjMgNjU1MzUgZg0KMDAwMDAwMDEyNCA2NTUzNSBmDQowMDAw MDAwMTI1IDY1NTM1IGYNCjAwMDAwMDAxMjYgNjU1MzUgZg0KMDAwMDAwMDEyNyA2NTUzNSBmDQow MDAwMDAwMTI4IDY1NTM1IGYNCjAwMDAwMDAxMjkgNjU1MzUgZg0KMDAwMDAwMDEzMCA2NTUzNSBm DQowMDAwMDAwMTMxIDY1NTM1IGYNCjAwMDAwMDAxMzIgNjU1MzUgZg0KMDAwMDAwMDEzMyA2NTUz NSBmDQowMDAwMDAwMTM0IDY1NTM1IGYNCjAwMDAwMDAxMzUgNjU1MzUgZg0KMDAwMDAwMDEzNiA2 NTUzNSBmDQowMDAwMDAwMTM3IDY1NTM1IGYNCjAwMDAwMDAxMzggNjU1MzUgZg0KMDAwMDAwMDEz OSA2NTUzNSBmDQowMDAwMDAwMTQwIDY1NTM1IGYNCjAwMDAwMDAxNDEgNjU1MzUgZg0KMDAwMDAw MDE0MiA2NTUzNSBmDQowMDAwMDAwMTQzIDY1NTM1IGYNCjAwMDAwMDAxNDQgNjU1MzUgZg0KMDAw MDAwMDE0NSA2NTUzNSBmDQowMDAwMDAwMTQ2IDY1NTM1IGYNCjAwMDAwMDAxNDcgNjU1MzUgZg0K MDAwMDAwMDE0OCA2NTUzNSBmDQowMDAwMDAwMTQ5IDY1NTM1IGYNCjAwMDAwMDAxNTAgNjU1MzUg Zg0KMDAwMDAwMDE1MSA2NTUzNSBmDQowMDAwMDAwMTUyIDY1NTM1IGYNCjAwMDAwMDAxNTMgNjU1 MzUgZg0KMDAwMDAwMDE1NCA2NTUzNSBmDQowMDAwMDAwMTU1IDY1NTM1IGYNCjAwMDAwMDAxNTYg NjU1MzUgZg0KMDAwMDAwMDE1NyA2NTUzNSBmDQowMDAwMDAwMTU4IDY1NTM1IGYNCjAwMDAwMDAx NTkgNjU1MzUgZg0KMDAwMDAwMDE2MCA2NTUzNSBmDQowMDAwMDAwMTYxIDY1NTM1IGYNCjAwMDAw MDAxNjIgNjU1MzUgZg0KMDAwMDAwMDE2MyA2NTUzNSBmDQowMDAwMDAwMTY0IDY1NTM1IGYNCjAw MDAwMDAxNjUgNjU1MzUgZg0KMDAwMDAwMDE2NiA2NTUzNSBmDQowMDAwMDAwMTY3IDY1NTM1IGYN CjAwMDAwMDAxNjggNjU1MzUgZg0KMDAwMDAwMDE2OSA2NTUzNSBmDQowMDAwMDAwMTcwIDY1NTM1 IGYNCjAwMDAwMDAxNzEgNjU1MzUgZg0KMDAwMDAwMDE3MiA2NTUzNSBmDQowMDAwMDAwMTczIDY1 NTM1IGYNCjAwMDAwMDAxNzQgNjU1MzUgZg0KMDAwMDAwMDE3NSA2NTUzNSBmDQowMDAwMDAwMTc2 IDY1NTM1IGYNCjAwMDAwMDAxNzcgNjU1MzUgZg0KMDAwMDAwMDE3OCA2NTUzNSBmDQowMDAwMDAw MTc5IDY1NTM1IGYNCjAwMDAwMDAxODAgNjU1MzUgZg0KMDAwMDAwMDE4MSA2NTUzNSBmDQowMDAw MDAwMTgyIDY1NTM1IGYNCjAwMDAwMDAxODMgNjU1MzUgZg0KMDAwMDAwMDE4NCA2NTUzNSBmDQow MDAwMDAwMTg1IDY1NTM1IGYNCjAwMDAwMDAxODYgNjU1MzUgZg0KMDAwMDAwMDE4NyA2NTUzNSBm DQowMDAwMDAwMTg4IDY1NTM1IGYNCjAwMDAwMDAxODkgNjU1MzUgZg0KMDAwMDAwMDE5MCA2NTUz NSBmDQowMDAwMDAwMTkxIDY1NTM1IGYNCjAwMDAwMDAxOTIgNjU1MzUgZg0KMDAwMDAwMDE5MyA2 NTUzNSBmDQowMDAwMDAwMTk0IDY1NTM1IGYNCjAwMDAwMDAxOTUgNjU1MzUgZg0KMDAwMDAwMDE5 NiA2NTUzNSBmDQowMDAwMDAwMTk3IDY1NTM1IGYNCjAwMDAwMDAxOTggNjU1MzUgZg0KMDAwMDAw MDE5OSA2NTUzNSBmDQowMDAwMDAwMjAwIDY1NTM1IGYNCjAwMDAwMDAyMDEgNjU1MzUgZg0KMDAw MDAwMDIwMiA2NTUzNSBmDQowMDAwMDAwMjAzIDY1NTM1IGYNCjAwMDAwMDAyMDQgNjU1MzUgZg0K MDAwMDAwMDIwNSA2NTUzNSBmDQowMDAwMDAwMjA2IDY1NTM1IGYNCjAwMDAwMDAyMDcgNjU1MzUg Zg0KMDAwMDAwMDAwMCA2NTUzNSBmDQowMDAwMDQ3MTcwIDAwMDAwIG4NCjAwMDAwNDc0MzIgMDAw MDAgbg0KMDAwMDA5ODQ3OCAwMDAwMCBuDQowMDAwMDk4ODk1IDAwMDAwIG4NCjAwMDAxOTk0NjUg MDAwMDAgbg0KMDAwMDE5OTcwNiAwMDAwMCBuDQowMDAwMTk5NzYyIDAwMDAwIG4NCjAwMDAyMDAz NDkgMDAwMDAgbg0KMDAwMDI5NzE2NCAwMDAwMCBuDQowMDAwMjk3ODgyIDAwMDAwIG4NCjAwMDAy OTgyNDAgMDAwMDAgbg0KMDAwMDI5ODUxNiAwMDAwMCBuDQowMDAwMjk4NzkwIDAwMDAwIG4NCjAw MDAyOTkwNDIgMDAwMDAgbg0KMDAwMDM5NTQ3MSAwMDAwMCBuDQowMDAwMzk1NzExIDAwMDAwIG4N CjAwMDA0NzQzMjMgMDAwMDAgbg0KMDAwMDQ3NDU0NSAwMDAwMCBuDQowMDAwNTU0MDk3IDAwMDAw IG4NCjAwMDA1NTQzMzEgMDAwMDAgbg0KMDAwMDY1MzQ0NCAwMDAwMCBuDQp0cmFpbGVyDQo8PC9T aXplIDIyOS9Sb290IDEgMCBSL0luZm8gNjQgMCBSL0lEWzw5MEFFQjAwQzE1OUNDMzQ3OTY1M0VF OTY2NEI3REQ0MD48OTBBRUIwMEMxNTlDQzM0Nzk2NTNFRTk2NjRCN0RENDA+XSA+Pg0Kc3RhcnR4 cmVmDQo2NTQyMDANCiUlRU9GDQp4cmVmDQowIDANCnRyYWlsZXINCjw8L1NpemUgMjI5L1Jvb3Qg MSAwIFIvSW5mbyA2NCAwIFIvSURbPDkwQUVCMDBDMTU5Q0MzNDc5NjUzRUU5NjY0QjdERDQwPjw5 MEFFQjAwQzE1OUNDMzQ3OTY1M0VFOTY2NEI3REQ0MD5dIC9QcmV2IDY1NDIwMC9YUmVmU3RtIDY1 MzQ0ND4+DQpzdGFydHhyZWYNCjY1ODk0MA0KJSVFT0Y= --_005_D21571530BF9644D9A443D6BD95B910315557345xmbrcdx12ciscoc_-- ------------=_1368448902-7695-0-- From paalh@ifi.uio.no Tue May 14 11:27:56 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 7F3A811E810E; Tue, 14 May 2013 11:27:56 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -0.81 X-Spam-Level: X-Spam-Status: No, score=-0.81 tagged_above=-999 required=5 tests=[BAYES_05=-1.11, MIME_8BIT_HEADER=0.3] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id V7icqfgrbcST; Tue, 14 May 2013 11:27:55 -0700 (PDT) Received: from mail-out4.uio.no (mail-out4.uio.no [IPv6:2001:700:100:10::15]) by ietfa.amsl.com (Postfix) with ESMTP id 9EE7211E810D; Tue, 14 May 2013 11:27:38 -0700 (PDT) Received: from mail-mx3.uio.no ([129.240.10.44]) by mail-out4.uio.no with esmtp (Exim 4.80.1) (envelope-from ) id 1UcJwj-0004vX-Nr; Tue, 14 May 2013 20:27:33 +0200 Received: from [148.122.14.90] (helo=[10.10.1.180]) by mail-mx3.uio.no with esmtpsa (TLSv1:AES128-SHA:128) user paalh (Exim 4.80) (envelope-from ) id 1UcJwj-0002n6-7u; Tue, 14 May 2013 20:27:33 +0200 From: =?iso-8859-1?Q?P=E5l_Halvorsen?= Content-Type: text/plain; charset=iso-8859-1 Content-Transfer-Encoding: quoted-printable Date: Tue, 14 May 2013 20:27:32 +0200 Message-Id: To: bloat@lists.bufferbloat.net, iccrg@cs.ucl.ac.uk, rmcat@ietf.org, rtcweb@ietf.org Mime-Version: 1.0 (Apple Message framework v1085) X-Mailer: Apple Mail (2.1085) X-UiO-SPF-Received: X-UiO-Ratelimit-Test: rcpts/h 43 msgs/h 15 sum rcpts/h 46 sum msgs/h 16 total rcpts 3746 max rcpts/h 73 ratelimit 0 X-UiO-Spam-info: not spam, SpamAssassin (score=-5.0, required=5.0, autolearn=disabled, UIO_MAIL_IS_INTERNAL=-5, uiobl=NO, uiouri=NO) X-UiO-Scanned: 67A55365DF2BE3690FBA58E0CDC496E8052261AB X-UiO-SPAM-Test: remote_host: 148.122.14.90 spam_score: -49 maxlevel 80 minaction 2 bait 0 mail/h: 15 total 22 max/h 15 blacklist 0 greylist 0 ratelimit 0 Subject: [rmcat] [Packet Video 2013] Submission deadline in 4 weeks X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Tue, 14 May 2013 18:27:56 -0000 Packet Video 2013 Sponsored by IEEE Communications Society December 12 and 13th San Jose, CA USA ------------------------------------------------------------- Call for Papers The 20th International Packet Video Workshop (PV 2013) is devoted to presenting technological advancements and innovations in video and multimedia transmission over packet networks, in particular wireless and Internet networks. The workshop provides a unique venue for people from the media coding and networking fields to meet, interact and exchange ideas. Its charter is to promote the research and development in both established and emerging areas of video streaming and multimedia networking. PV 2013 will be held in San Jose, CA USA on December 12 and 13th. As in previous years, the workshop will be a single-track event and welcomes paper submissions from both cutting-edge research, and business and consumer applications. PV 2013 will be immediately following the Picture Coding Symposium, which will be held also in San Jose, CA. There will be both regular and special sessions. In general, the workshop seeks papers in all areas of media delivery over packet-based networks. Authors are especially encouraged to submit papers with real- world experimental results and real datasets. Topics of interest include (but are not limited to): - Cloud and peer-to-peer system architectures - Media streaming, distribution and storage support - Multimedia communications and system security - Multi-core and many-core architecture support - Networked GPUs, graphics and virtual environments - Networked games, real-time immersive systems - Operating system, middleware and network support - Web 2.0 systems and social networks - Next-generation video like multi-view, panorama and 3D - Wireless networks and embedded systems for multimedia applications - Content-centric networking In particular, we are interested in soliciting papers that discuss system-level support improving performance with multi-core and many-core processors, as well as papers that focus on multimedia applications on mobile devices and/or in a cloud-computing environment. Prospective authors are invited to submit an electronic version of full papers, in PDF format, up to 8 printed pages in length (double column IEEE conference format). The proceedings will be published by the IEEE Xplore shortly after the workshop. For the Technical Program Committee and details regarding special = sessions, refer to the PV 2013 Web site at http://pv2013.itec.aau.at/. ORGANIZATION General Co-Chairs Ali C. Begen, Cisco (Canada) Bernd Girod, Stanford Univ. Technical Program Co-Chairs John Apostolopoulos, Cisco (USA) P=E5l Halvorsen, University of Oslo Publicity Chair Christian Timmerer, AAU Klagenfurt Publications Chair Zhi Li, Cisco (USA) Steering Committee Chang Wen Chen, SUNY Buffalo, USA Tsuhan Chen, Cornell, USA Reha Civanlar, Ozyegin Univ., Turkey Pascal Frossard, EPFL, Switzerland Bernd Girod, Stanford Univ., USA Jin Li, Microsoft, USA Fernando Pereira, IST-IT, Portugal Amy Reibman, AT&T, USA Mihaela van der Schaar, UCLA, USA Ralf Schaefer, HHI, Germany Eckehard Steinbach, TUM, Germany Ming-Ting Sun, Univ. of Wash., USA Important Dates All Papers due: June 10th=20 Acceptance Notifications: Sept. 13th=20 Camera-ready: Oct. 18th Further Information http://pv2013.itec.aau.at/ From steing@ifi.uio.no Wed May 15 08:11:50 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 53DBF21F8F83; Wed, 15 May 2013 08:11:50 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -2.598 X-Spam-Level: X-Spam-Status: No, score=-2.598 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, HTML_MESSAGE=0.001] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id iGIrVo0PEbGg; Wed, 15 May 2013 08:11:45 -0700 (PDT) Received: from mail-out1.uio.no (mail-out1.uio.no [IPv6:2001:700:100:10::57]) by ietfa.amsl.com (Postfix) with ESMTP id E8FA821F8AD8; Wed, 15 May 2013 08:11:44 -0700 (PDT) Received: from mail-mx2.uio.no ([129.240.10.30]) by mail-out1.uio.no with esmtp (Exim 4.75) (envelope-from ) id 1UcdMl-0005Wl-5S; Wed, 15 May 2013 17:11:43 +0200 Received: from 1x-193-157-202-195.uio.no ([193.157.202.195]) by mail-mx2.uio.no with esmtpsa (TLSv1:AES128-SHA:128) user steing (Exim 4.80) (envelope-from ) id 1UcdMk-0004fY-EU; Wed, 15 May 2013 17:11:43 +0200 From: Stein Gjessing Content-Type: multipart/alternative; boundary="Apple-Mail=_4CA7AC64-6758-4240-93E4-84B414877C93" Date: Wed, 15 May 2013 17:11:41 +0200 Message-Id: To: aqm@ietf.org, rtcweb@ietf.org, lmap@ietf.org, tsvwg@ietf.org, rmcat@ietf.org, multipathtcp@ietf.org, video-codec@ietf.org Mime-Version: 1.0 (Apple Message framework v1283) X-Mailer: Apple Mail (2.1283) X-UiO-SPF-Received: X-UiO-Ratelimit-Test: rcpts/h 8 msgs/h 1 sum rcpts/h 13 sum msgs/h 4 total rcpts 2607 max rcpts/h 28 ratelimit 0 X-UiO-Spam-info: not spam, SpamAssassin (score=-5.5, required=5.0, autolearn=disabled, HTML_MESSAGE=0.001, RP_MATCHES_RCVD=-0.551, UIO_MAIL_IS_INTERNAL=-5, uiobl=NO, uiouri=NO) X-UiO-Scanned: 45A26AF8F0515C0711EDC4E4402EEAD2BB95E78D X-UiO-SPAM-Test: remote_host: 193.157.202.195 spam_score: -54 maxlevel 99990 minaction 1 bait 0 mail/h: 1 total 36 max/h 6 blacklist 0 greylist 0 ratelimit 0 Cc: Stein Gjessing Subject: [rmcat] CFP Packet Video 2013 - Special Session on Low-Latency Interactive Video X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 15 May 2013 15:11:50 -0000 --Apple-Mail=_4CA7AC64-6758-4240-93E4-84B414877C93 Content-Transfer-Encoding: quoted-printable Content-Type: text/plain; charset=windows-1252 Hi, Here is an excellent venue for discussions and publication of results. Cheers,=20 Stein __________________________________________________________ Packet Video 2013 - Special Session on Low-Latency Interactive Video Sponsored by IEEE Communications Society December 12. and 13., 2013, San Jose, Ca, USA Call for papers. =20 http://pv2013.itec.aau.at/call-for-papers/accepted-special-sessions/#ss1 Several years ago, it was found that users do not like video quality = fluctuations. At that time the predominant belief was that network rate = fluctuations should be minimized, in order to reasonably interoperate = with TCP in the network. This led to the creation of a number of = so-called "TCP-friendly" congestion controls that exhibit a smoother = sending rate than TCP, while avoiding to send more than a conformant TCP = under similar conditions. TFRC is perhaps the best known example of such = a congestion control mechanism. A lot has happened since then: =95 The notion of TCP-friendliness has received massive = criticism; the widespread deployment of a more aggressive TCP variant, = CUBIC, has not led to an Internet meltdown, making the case that = diverging from strict TCP-friendliness is possible. =95 Latency minimization has become a major goal, especially in = the face of =93bufferbloat=94: large delays from large buffers with = simplistic FIFO-queue management. =95 Codecs have improved; novel video codecs are able to adjust = the data rate, but modern codecs may also produce variable bitrate = transmissions with burstier packet flows than before. =95 TFRC has been embedded in the DCCP protocol, which has = probably never been used for anything other than experiments; instead of = running over DCCP, RTP-based applications now contain proprietary = congestion control mechanisms. The emergence of the RTCWEB protocol suite for real-time communication = between Web browsers has renewed the interest in developing congestion = control standards for real-time media. This time, however, the goal is = to get things right: delay should be minimized, and standards should = realize congestion control using RTP with RTCP signaling. The IETF = =93Real-time Media Congestion Avoidance Techniques=94 (RMCAT) working = group has been founded to address this need. New questions arise: what = type of congestion controls do we need? How much feedback should we = send? How do we make this work in multi-user scenarios, e.g., for video = conferencing? What should be the API between a video codec and a new = delay-based congestion controlled RTP stream? What is the quality that = can be expected from the combination of a codec and congestion control = mechanism, when we consider better metrics than plain PSNR? Topics of interest include, but are not limited to: =95 Congestion control algorithms for interactive real-time = video: requirements, evaluation criteria, and mechanisms =95 Necessary RTP/RTCP extensions =95 Field experience with video codecs in a low-delay, real-time = setting =95 Interactions between applications and RTP flows =95 Failing to meet real-time schedules: impact, techniques to = detect, instrument or diagnose it Organizers: =95 Michael Welzl, University of Oslo (michawe at ifi.uio.no) =95 Stein Gjessing, University of Oslo (steing at ifi.uio.no)= --Apple-Mail=_4CA7AC64-6758-4240-93E4-84B414877C93 Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset=windows-1252 http://pv2013.itec.aau.at/call-for-papers/accepted-special-session= s/#ss1

Several years ago, it was found that users do not like = video quality fluctuations. At that time the predominant belief was that = network rate fluctuations should be minimized, in order to reasonably = interoperate with TCP in the network. This led to the creation of a = number of so-called "TCP-friendly" congestion controls that exhibit a = smoother sending rate than TCP, while avoiding to send more than a = conformant TCP under similar conditions. TFRC is perhaps the best known = example of such a congestion control mechanism.

A lot has = happened since then:
=95 The notion of = TCP-friendliness has received massive criticism; the widespread = deployment of a more aggressive TCP variant, CUBIC, has not led to an = Internet meltdown, making the case that diverging from strict = TCP-friendliness is possible.
=95 Latency minimization has = become a major goal, especially in the face of =93bufferbloat=94: large = delays from large buffers with simplistic FIFO-queue = management.
=95 TFRC = has been embedded in the DCCP protocol, which has probably never been = used for anything other than experiments; instead of running over DCCP, = RTP-based applications now contain proprietary congestion control = mechanisms.

The emergence of the RTCWEB protocol suite for = real-time communication between Web browsers has renewed the interest in = developing congestion control standards for real-time media. This time, = however, the goal is to get things right: delay should be minimized, and = standards should realize congestion control using RTP with RTCP = signaling. The IETF =93Real-time Media Congestion Avoidance Techniques=94 = (RMCAT) working group has been founded to address this need. New = questions arise: what type of congestion controls do we need? How much = feedback should we send? How do we make this work in multi-user = scenarios, e.g., for video conferencing? What should be the API between = a video codec and a new delay-based congestion controlled RTP stream? = What is the quality that can be expected from the combination of a codec = and congestion control mechanism, when we consider better metrics than = plain PSNR?

Topics of interest include, but are not limited = to:
= =95 Congestion control algorithms for interactive real-time = video: requirements, evaluation criteria, and mechanisms
=95 = Necessary RTP/RTCP extensions
=95 Field experience with video = codecs in a low-delay, real-time setting
=95 Interactions between = applications and RTP flows
=95 Failing to meet real-time = schedules: impact, techniques to detect, instrument or diagnose = it

Organizers:
=95 Michael Welzl, University of = Oslo (michawe at ifi.uio.no)
=95 Stein = Gjessing, University of Oslo (steing at ifi.uio.no)
= --Apple-Mail=_4CA7AC64-6758-4240-93E4-84B414877C93-- From mramalho@cisco.com Fri May 24 07:38:11 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 914D021F8FE8 for ; Fri, 24 May 2013 07:38:11 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -9.998 X-Spam-Level: X-Spam-Status: No, score=-9.998 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, HTML_MESSAGE=0.001, J_CHICKENPOX_63=0.6, RCVD_IN_DNSWL_HI=-8] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id VcAl20-uE06e for ; Fri, 24 May 2013 07:38:06 -0700 (PDT) Received: from rcdn-iport-1.cisco.com (rcdn-iport-1.cisco.com [173.37.86.72]) by ietfa.amsl.com (Postfix) with ESMTP id 5D49721F92F5 for ; Fri, 24 May 2013 07:38:06 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=11941; q=dns/txt; s=iport; t=1369406286; x=1370615886; h=from:to:subject:date:message-id:mime-version; bh=YECmFW7S0dnhtkNY0YQzesX6rItbEhtZa5efge0sHNI=; b=kG+2g1+eUFi3J5TpkHU7JA55orH20fhJWUSQ1B4E3I9UX4hLZGcFaS0l oA228zt3s39Py6AQTPZWDxcaY30iNRiYdJ6+EhXzOIoSU9VL2mwZsSRZY 0N2ulDYzo+bYthQoCae8LaOvsAluNqj7op6NOnN+PW1NWZ0bPoojDBAOv g=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: AuYGALJ5n1GtJXG//2dsb2JhbAA/FwOCREQwwiWBBBZtB4IjAQEBAgItOQIjARkDAQEBCwoEDAM5FAkHAgEBAxMIiAUMM5lckn2Nao1bDg12IAEMChIHglthA6h7gj9QgXE1 X-IronPort-AV: E=Sophos;i="4.87,736,1363132800"; d="scan'208,217";a="214424970" Received: from rcdn-core2-4.cisco.com ([173.37.113.191]) by rcdn-iport-1.cisco.com with ESMTP; 24 May 2013 14:38:05 +0000 Received: from xhc-aln-x12.cisco.com (xhc-aln-x12.cisco.com [173.36.12.86]) by rcdn-core2-4.cisco.com (8.14.5/8.14.5) with ESMTP id r4OEc5rJ007303 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL) for ; Fri, 24 May 2013 14:38:05 GMT Received: from xmb-rcd-x12.cisco.com ([169.254.2.54]) by xhc-aln-x12.cisco.com ([173.36.12.86]) with mapi id 14.02.0318.004; Fri, 24 May 2013 09:38:05 -0500 From: "Michael Ramalho (mramalho)" To: "rmcat@ietf.org" Thread-Topic: REMINDER: No Design Team Meeting on May 27 - Next Meeting on June 3 Thread-Index: Ac5YjEkg8jde9UoAQVSn+ILXfcklqg== Date: Fri, 24 May 2013 14:38:04 +0000 Message-ID: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [10.117.125.231] Content-Type: multipart/alternative; boundary="_000_D21571530BF9644D9A443D6BD95B910315567E66xmbrcdx12ciscoc_" MIME-Version: 1.0 Subject: [rmcat] REMINDER: No Design Team Meeting on May 27 - Next Meeting on June 3 X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Fri, 24 May 2013 14:38:11 -0000 --_000_D21571530BF9644D9A443D6BD95B910315567E66xmbrcdx12ciscoc_ Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: quoted-printable All, This is a short note to remind people participating on the RMCAT Design Tea= m that there will>> NOT<< be a design team meeting next Monday, May 27 due = to a major US Holiday. As agreed to at the May 13 meeting, the next RMCAT Design Team meeting will= be on Monday, June 3, 2013 (same time at UTC 15:00-16:00, which is 4pm Lon= don, 11am New York). For those wishing to join the May 13 meeting the conference URL will remain= unchanged (the URL is in the email thread below). Henceforth, the meetings will resume their bi-weekly schedule until further= changes. Michael Ramalho From: rmcat-bounces@ietf.org [mailto:rmcat-bounces@ietf.org] On Behalf Of M= o Zanaty (mzanaty) Sent: Monday, April 29, 2013 10:52 AM To: rmcat@ietf.org Subject: Re: [rmcat] RMCAT Eval Design Team 29 APR UTC 15:00-16:00 (4pm Lon= don, 11am New York) Reminder that the design team meeting starts in 15 minutes. https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&UID=3D484666302&PW= =3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D Topic: RMCAT Eval Design Team Date: Monday, April 29, 2013 Time: 15:00-16:00 UTC, 4pm London, 11am New York Meeting Number: 203 451 310 Password: rmcat Host Key: 412564 (use this to reclaim host privileges) ------------------------------------------------------- To join the meeting online(Now from mobile devices!) ------------------------------------------------------- 1. Go to https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&UID=3D4846= 66302&PW=3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D 2. If requested, enter your name and email address. 3. If a password is required, enter the meeting password: rmcat 4. Click "Join". 5. If the meeting includes a teleconference, follow the instructions that a= ppear on your screen. ------------------------------------------------------- To join the audio conference only ------------------------------------------------------- To receive a call back, provide your phone number when you join the meeting= , or call the number below and enter the access code. Call-in toll-free number (US/Canada): +1-866-432-9903 Call-in toll number (US/Canada): +1-408-525-6800 Global call-in numbers: https://cisco.webex.com/ciscosales/globalcallin.php= ?serviceType=3DMC&ED=3D221585972&tollFree=3D1 Toll-free dialing restrictions: http://www.webex.com/pdf/tollfree_restricti= ons.pdf Access code:203 451 310 CCP:+14085256800x203451310# --_000_D21571530BF9644D9A443D6BD95B910315567E66xmbrcdx12ciscoc_ Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

All,

 <= /p>

This is a short note to r= emind people participating on the RMCAT Design Team that there will>>= NOT<< be a design team meeting next Monday, May 27 due to a major US Holiday.

 <= /p>

As agreed to at the May 1= 3 meeting, the next RMCAT Design Team meeting will be on Monday, June 3, 20= 13 (same time at UTC 15:00-16:00, which is 4pm London, 11am New York).

 <= /p>

For those wishing to join= the May 13 meeting the conference URL will remain unchanged (the URL is in= the email thread below).

 <= /p>

Henceforth, the meetings = will resume their bi-weekly schedule until further changes.

 <= /p>

Michael Ramalho

 <= /p>

From: rmcat-bo= unces@ietf.org [mailto:rmcat-bounces@ietf.org] On Behalf Of Mo Zanaty (mzanaty)
Sent: Monday, April 29, 2013 10:52 AM
To: rmcat@ietf.org
Subject: Re: [rmcat] RMCAT Eval Design Team 29 APR UTC 15:00-16:00 (= 4pm London, 11am New York)

 

Reminder that the design team meeting s= tarts in 15 minutes.

 

 

Topic: RMCAT Eval Design Team
Date: Monday, April 29, 2013
Time: 15:00-16:00 UTC, 4pm London, 11am New York

Meeting Number: 203 451 310
Password: rmcat

Host Key: 412564 (use this to reclaim ho= st privileges)

-------------------------------------------------------
To join the meeting online(Now from mobile devices!)
-------------------------------------------------------
1. Go to https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&UID=3D484666302= &PW=3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D
2. If requested, enter your name and email address.
3. If a password is required, enter the meeting password: rmcat
4. Click "Join".
5. If the meeting includes a teleconference, follow the instructions that a= ppear on your screen.

-------------------------------------------------------
To join the audio conference only
-------------------------------------------------------
To receive a call back, provide your phone number when you join the meeting= , or call the number below and enter the access code.
Call-in toll-free number (US/Canada): +1-866-432-9903
Call-in toll number (US/Canada): +1-408-525-6800
Global call-in numbers: https://cisco.webex.com/ciscosales/globalcallin.php?serviceType=3DMC&ED= =3D221585972&tollFree=3D1
Toll-free dialing restrictions: http://www.webex.com/pdf/tollfree_restrictions.pdf
Access code:203 451 310
CCP:+14085256800x203451310#

 

 

--_000_D21571530BF9644D9A443D6BD95B910315567E66xmbrcdx12ciscoc_-- From mramalho@cisco.com Fri May 24 07:47:49 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id D978021F8EA6 for ; Fri, 24 May 2013 07:47:49 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -10.298 X-Spam-Level: X-Spam-Status: No, score=-10.298 tagged_above=-999 required=5 tests=[AWL=-0.300, BAYES_00=-2.599, HTML_MESSAGE=0.001, J_CHICKENPOX_63=0.6, RCVD_IN_DNSWL_HI=-8] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id oHmEnuedqXup for ; Fri, 24 May 2013 07:47:45 -0700 (PDT) Received: from rcdn-iport-4.cisco.com (rcdn-iport-4.cisco.com [173.37.86.75]) by ietfa.amsl.com (Postfix) with ESMTP id DD9B921F8CA5 for ; Fri, 24 May 2013 07:47:44 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=12735; q=dns/txt; s=iport; t=1369406865; x=1370616465; h=from:to:subject:date:message-id:mime-version; bh=Nh35XS/G1kh0rMCIdy/bDMIuQl1Nko4e2dDDl880qso=; b=IeTPMf2rP0S0upXYAQmUCQvFIbwMT95aHQEXpKZlmzaaRZm6f78LpWsJ pm3a+Iq4NnneI5RaZh8x0MFFk95hYxHpGBR60uvCP+gYIA6XE+SvNH7Zs Bqfn3KuWp9eGuO3hxJqNfMND5fSQ15cuoPSS5YYFZKu95ross28Y7lLbz Q=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: AuYGADt9n1GtJXHA/2dsb2JhbAA/FwOCREQwwiWBBBZtB4IjAQEBAgItOQIjARkDAQEBCwoEDAM5FAkHAgEBAxMIiAUMM5lSkn2NaI1bDg12IAEMChIHglthA6h7gj9QgXE1 X-IronPort-AV: E=Sophos;i="4.87,736,1363132800"; d="scan'208,217";a="214712698" Received: from rcdn-core2-5.cisco.com ([173.37.113.192]) by rcdn-iport-4.cisco.com with ESMTP; 24 May 2013 14:47:24 +0000 Received: from xhc-rcd-x14.cisco.com (xhc-rcd-x14.cisco.com [173.37.183.88]) by rcdn-core2-5.cisco.com (8.14.5/8.14.5) with ESMTP id r4OElO1i002592 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL) for ; Fri, 24 May 2013 14:47:24 GMT Received: from xmb-rcd-x12.cisco.com ([169.254.2.54]) by xhc-rcd-x14.cisco.com ([173.37.183.88]) with mapi id 14.02.0318.004; Fri, 24 May 2013 09:47:23 -0500 From: "Michael Ramalho (mramalho)" To: "rmcat@ietf.org" Thread-Topic: REMINDER: No Design Team Meeting on May 27 - Next Meeting on June 3 Thread-Index: Ac5YjZljopC2ctKNQV6fvqZadw9AAQ== Date: Fri, 24 May 2013 14:47:23 +0000 Message-ID: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [10.117.125.231] Content-Type: multipart/alternative; boundary="_000_D21571530BF9644D9A443D6BD95B910315567EC5xmbrcdx12ciscoc_" MIME-Version: 1.0 Subject: [rmcat] REMINDER: No Design Team Meeting on May 27 - Next Meeting on June 3 X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Fri, 24 May 2013 14:47:50 -0000 --_000_D21571530BF9644D9A443D6BD95B910315567EC5xmbrcdx12ciscoc_ Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: quoted-printable [Correcting small type in prior email] All, This is a short note to remind people participating on the RMCAT Design Tea= m that there will>> NOT<< be a design team meeting next Monday, May 27 due = to a major US Holiday. As agreed to at the May 13 meeting, the next RMCAT Design Team meeting will= be on Monday, June 3, 2013 (same time at UTC 15:00-16:00, which is 4pm Lon= don, 11am New York). For those wishing to join the >June 3< meeting the conference URL will rema= in unchanged (the URL is in the email thread below). Henceforth, the meetings will resume their bi-weekly schedule until further= changes. Michael Ramalho From: rmcat-bounces@ietf.org [mailto:rmcat-bounces@ietf.org] On Behalf Of M= o Zanaty (mzanaty) Sent: Monday, April 29, 2013 10:52 AM To: rmcat@ietf.org Subject: Re: [rmcat] RMCAT Eval Design Team 29 APR UTC 15:00-16:00 (4pm Lon= don, 11am New York) Reminder that the design team meeting starts in 15 minutes. https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&UID=3D484666302&PW= =3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D Topic: RMCAT Eval Design Team Date: Monday, April 29, 2013 Time: 15:00-16:00 UTC, 4pm London, 11am New York Meeting Number: 203 451 310 Password: rmcat Host Key: 412564 (use this to reclaim host privileges) ------------------------------------------------------- To join the meeting online(Now from mobile devices!) ------------------------------------------------------- 1. Go to https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&UID=3D4846= 66302&PW=3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D 2. If requested, enter your name and email address. 3. If a password is required, enter the meeting password: rmcat 4. Click "Join". 5. If the meeting includes a teleconference, follow the instructions that a= ppear on your screen. ------------------------------------------------------- To join the audio conference only ------------------------------------------------------- To receive a call back, provide your phone number when you join the meeting= , or call the number below and enter the access code. Call-in toll-free number (US/Canada): +1-866-432-9903 Call-in toll number (US/Canada): +1-408-525-6800 Global call-in numbers: https://cisco.webex.com/ciscosales/globalcallin.php= ?serviceType=3DMC&ED=3D221585972&tollFree=3D1 Toll-free dialing restrictions: http://www.webex.com/pdf/tollfree_restricti= ons.pdf Access code:203 451 310 CCP:+14085256800x203451310# --_000_D21571530BF9644D9A443D6BD95B910315567EC5xmbrcdx12ciscoc_ Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

[Correcting small type in= prior email]

 <= /p>

All,

 <= /p>

This is a short note to r= emind people participating on the RMCAT Design Team that there will>>= NOT<< be a design team meeting next Monday, May 27 due to a major US Holiday.

 <= /p>

As agreed to at the May 1= 3 meeting, the next RMCAT Design Team meeting will be on Monday, June 3, 20= 13 (same time at UTC 15:00-16:00, which is 4pm London, 11am New York).

 <= /p>

For those wishing to join= the >June 3< meeting the conference URL will rem= ain unchanged (the URL is in the email thread below).

 <= /p>

Henceforth, the meetings = will resume their bi-weekly schedule until further changes.

 <= /p>

Michael Ramalho

 <= /p>

 <= /p>

From: rmcat-bo= unces@ietf.org [mailto:rmcat-bounces@ietf.org] On Behalf Of Mo Zanaty (mzanaty)
Sent: Monday, April 29, 2013 10:52 AM
To: rmcat@ietf.org
Subject: Re: [rmcat] RMCAT Eval Design Team 29 APR UTC 15:00-16:00 (= 4pm London, 11am New York)

 

Reminder that the design team meeting s= tarts in 15 minutes.

 

 

Topic: RMCAT Eval Design Team
Date: Monday, April 29, 2013
Time: 15:00-16:00 UTC, 4pm London, 11am New York

Meeting Number: 203 451 310
Password: rmcat

Host Key: 412564 (use this to reclaim ho= st privileges)

-------------------------------------------------------
To join the meeting online(Now from mobile devices!)
-------------------------------------------------------
1. Go to https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&UID=3D484666302= &PW=3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D
2. If requested, enter your name and email address.
3. If a password is required, enter the meeting password: rmcat
4. Click "Join".
5. If the meeting includes a teleconference, follow the instructions that a= ppear on your screen.

-------------------------------------------------------
To join the audio conference only
-------------------------------------------------------
To receive a call back, provide your phone number when you join the meeting= , or call the number below and enter the access code.
Call-in toll-free number (US/Canada): +1-866-432-9903
Call-in toll number (US/Canada): +1-408-525-6800
Global call-in numbers: https://cisco.webex.com/ciscosales/globalcallin.php?serviceType=3DMC&ED= =3D221585972&tollFree=3D1
Toll-free dialing restrictions: http://www.webex.com/pdf/tollfree_restrictions.pdf
Access code:203 451 310
CCP:+14085256800x203451310#

 

 

--_000_D21571530BF9644D9A443D6BD95B910315567EC5xmbrcdx12ciscoc_-- From mzanaty@cisco.com Fri May 24 13:22:57 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id BFD6B11E8108 for ; Fri, 24 May 2013 13:22:56 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -9.998 X-Spam-Level: X-Spam-Status: No, score=-9.998 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, HTML_MESSAGE=0.001, J_CHICKENPOX_63=0.6, RCVD_IN_DNSWL_HI=-8] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id 4BB9dubTmmlm for ; Fri, 24 May 2013 13:22:45 -0700 (PDT) Received: from rcdn-iport-5.cisco.com (rcdn-iport-5.cisco.com [173.37.86.76]) by ietfa.amsl.com (Postfix) with ESMTP id E594411E80FC for ; Fri, 24 May 2013 13:22:44 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=9634; q=dns/txt; s=iport; t=1369426965; x=1370636565; h=from:to:subject:date:message-id:mime-version; bh=gdXCV3eAVYKcSOqhjcRdf+fHKlvktSodONlKGYN1FmI=; b=gS/fuB0ynnKgG4LRq+NYaAandFkYNZ9S71FRNvmcapbhEI2O5rTTojgg hR3N/zuQM4l0qweaS9VFNwMcWoWu6uypC3jXAUF56lsut/7anFAxPsi8H FhXI6Uoko3V4kMa3K+JvcyLHrK7UILXsPdkS1WvDaiFAq36BKTYNqQlGz 0=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: AugGABjLn1GtJV2d/2dsb2JhbABAFwOCREQwgzu+cw16Fm0HgiUBAgIjCjkCIwEMEA4KBAwGAgQwJAIBAQMbiAUMM5kojmmEFI1XjVsODXYWCgEMHAeCKTJhA4hnoBSCP1CBcTU X-IronPort-AV: E=Sophos;i="4.87,737,1363132800"; d="scan'208,217";a="214771662" Received: from rcdn-core-6.cisco.com ([173.37.93.157]) by rcdn-iport-5.cisco.com with ESMTP; 24 May 2013 20:22:44 +0000 Received: from xhc-rcd-x15.cisco.com (xhc-rcd-x15.cisco.com [173.37.183.89]) by rcdn-core-6.cisco.com (8.14.5/8.14.5) with ESMTP id r4OKMita006211 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL) for ; Fri, 24 May 2013 20:22:44 GMT Received: from xmb-rcd-x14.cisco.com ([169.254.4.194]) by xhc-rcd-x15.cisco.com ([173.37.183.89]) with mapi id 14.02.0318.004; Fri, 24 May 2013 15:22:44 -0500 From: "Mo Zanaty (mzanaty)" To: "rmcat@ietf.org" Thread-Topic: RMCAT Eval Design Team 3 June UTC 15:00-16:00 (4pm London, 11am New York) Thread-Index: Ac5B3p6ixOOnnvu2TeOiuvliKShvmQW3dHhA Date: Fri, 24 May 2013 20:22:43 +0000 Message-ID: <3879D71E758A7E4AA99A35DD8D41D3D91D47C0B6@xmb-rcd-x14.cisco.com> Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [10.82.242.79] Content-Type: multipart/alternative; boundary="_000_3879D71E758A7E4AA99A35DD8D41D3D91D47C0B6xmbrcdx14ciscoc_" MIME-Version: 1.0 Subject: [rmcat] RMCAT Eval Design Team 3 June UTC 15:00-16:00 (4pm London, 11am New York) X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Fri, 24 May 2013 20:22:57 -0000 --_000_3879D71E758A7E4AA99A35DD8D41D3D91D47C0B6xmbrcdx14ciscoc_ Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&UID=3D484666302&PW= =3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D Topic: RMCAT Eval Design Team Date: Monday, June 3, 2013 Time: 15:00-16:00 UTC, 4pm London, 11am New York Meeting Number: 203 451 310 Password: rmcat Host Key: 412564 (use this to reclaim host privileges) ------------------------------------------------------- To join the meeting online(Now from mobile devices!) ------------------------------------------------------- 1. Go to https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&UID=3D4846= 66302&PW=3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D 2. If requested, enter your name and email address. 3. If a password is required, enter the meeting password: rmcat 4. Click "Join". 5. If the meeting includes a teleconference, follow the instructions that a= ppear on your screen. ------------------------------------------------------- To join the audio conference only ------------------------------------------------------- To receive a call back, provide your phone number when you join the meeting= , or call the number below and enter the access code. Call-in toll-free number (US/Canada): +1-866-432-9903 Call-in toll number (US/Canada): +1-408-525-6800 Global call-in numbers: https://cisco.webex.com/ciscosales/globalcallin.php= ?serviceType=3DMC&ED=3D221585972&tollFree=3D1 Toll-free dialing restrictions: http://www.webex.com/pdf/tollfree_restricti= ons.pdf Access code:203 451 310 CCP:+14085256800x203451310# --_000_3879D71E758A7E4AA99A35DD8D41D3D91D47C0B6xmbrcdx14ciscoc_ Content-Type: text/html; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable
 
Topic= : RMCAT Eval Design Team
Date: Monday, June 3, 2013
Time: 15:00-16:00 UTC, 4pm London, 11am New York
Meeti= ng Number: 203 451 310
Password: rmcat
Host = Key: 412564 (use this to reclaim host privileges)

-------------------------------------------------------
To join the meeting online(Now from mobile devices!)
-------------------------------------------------------
1. Go to https://cisco.webex.com/ciscosales/j.php?ED=3D221585972&= ;UID=3D484666302&PW=3DNNmNhZTJjYTI1&RT=3DMiMyMQ%3D%3D
2. If requested, enter your name and email address.
3. If a password is required, enter the meeting password: rmcat
4. Click "Join".
5. If the meeting includes a teleconference, follow the instructions that a= ppear on your screen.

-------------------------------------------------------
To join the audio conference only
-------------------------------------------------------
To receive a call back, provide your phone number when you join the meeting= , or call the number below and enter the access code.
Call-in toll-free number (US/Canada): +1-866-432-9903
Call-in toll number (US/Canada): +1-408-525-6800
Global call-in numbers: https://cisco.webex.com/ciscosales/globalcallin.php?serviceT= ype=3DMC&ED=3D221585972&tollFree=3D1
Toll-free dialing restrictions: http://www.webex.com/pdf/tollfr= ee_restrictions.pdf
Access code:203 451 310
CCP:+14085256800x203451310#
 
 
 --_000_3879D71E758A7E4AA99A35DD8D41D3D91D47C0B6xmbrcdx14ciscoc_ Content-Type: text/calendar; charset="utf-8"; method=REQUEST Content-Transfer-Encoding: base64 QkVHSU46VkNBTEVOREFSDQpNRVRIT0Q6UkVRVUVTVA0KUFJPRElEOk1pY3Jvc29mdCBFeGNoYW5n ZSBTZXJ2ZXIgMjAxMA0KVkVSU0lPTjoyLjANCkJFR0lOOlZUSU1FWk9ORQ0KVFpJRDpFYXN0ZXJu IFN0YW5kYXJkIFRpbWUNCkJFR0lOOlNUQU5EQVJEDQpEVFNUQVJUOjE2MDEwMTAxVDAyMDAwMA0K VFpPRkZTRVRGUk9NOi0wNDAwDQpUWk9GRlNFVFRPOi0wNTAwDQpSUlVMRTpGUkVRPVlFQVJMWTtJ TlRFUlZBTD0xO0JZREFZPTFTVTtCWU1PTlRIPTExDQpFTkQ6U1RBTkRBUkQNCkJFR0lOOkRBWUxJ R0hUDQpEVFNUQVJUOjE2MDEwMTAxVDAyMDAwMA0KVFpPRkZTRVRGUk9NOi0wNTAwDQpUWk9GRlNF VFRPOi0wNDAwDQpSUlVMRTpGUkVRPVlFQVJMWTtJTlRFUlZBTD0xO0JZREFZPTJTVTtCWU1PTlRI PTMNCkVORDpEQVlMSUdIVA0KRU5EOlZUSU1FWk9ORQ0KQkVHSU46VkVWRU5UDQpPUkdBTklaRVI7 Q049TW8gWmFuYXR5IChtemFuYXR5KTpNQUlMVE86bXphbmF0eUBjaXNjby5jb20NCkFUVEVOREVF O1JPTEU9UkVRLVBBUlRJQ0lQQU5UO1BBUlRTVEFUPU5FRURTLUFDVElPTjtSU1ZQPVRSVUU7Q049 cm1jYXRAaWV0Zg0KIC5vcmc6TUFJTFRPOnJtY2F0QGlldGYub3JnDQpERVNDUklQVElPTjtMQU5H VUFHRT1lbi1VUzpodHRwczovL2Npc2NvLndlYmV4LmNvbS9jaXNjb3NhbGVzL2oucGhwP0VEPTIy MTUNCiA4NTk3MiZVSUQ9NDg0NjY2MzAyJlBXPU5ObU5oWlRKallUSTEmUlQ9TWlNeU1RJTNEJTNE XG5cblRvcGljOiBSTUNBVCBFdmFsIA0KIERlc2lnbiBUZWFtXG5EYXRlOiBNb25kYXlcLCBKdW5l IDNcLCAyMDEzXG5UaW1lOiAxNTowMC0xNjowMCBVVENcLCA0cG0gTG9uDQogZG9uXCwgMTFhbSBO ZXcgWW9ya1xuTWVldGluZyBOdW1iZXI6IDIwMyA0NTEgMzEwXG5QYXNzd29yZDogcm1jYXRcbkhv c3QgS2UNCiB5OiA0MTI1NjQgKHVzZSB0aGlzIHRvIHJlY2xhaW0gaG9zdCBwcml2aWxlZ2VzKVxu XG4tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLQ0KIC0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0t LS0tXG5UbyBqb2luIHRoZSBtZWV0aW5nIG9ubGluZShOb3cgZnJvbSBtb2JpDQogbGUgZGV2aWNl cyEpXG4tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0t LS0tXG4xLiANCiBHbyB0byBodHRwczovL2Npc2NvLndlYmV4LmNvbS9jaXNjb3NhbGVzL2oucGhw P0VEPTIyMTU4NTk3MiZVSUQ9NDg0NjY2MzAyJg0KIFBXPU5ObU5oWlRKallUSTEmUlQ9TWlNeU1R JTNEJTNEXG4yLiBJZiByZXF1ZXN0ZWRcLCBlbnRlciB5b3VyIG5hbWUgYW5kIGVtDQogYWlsIGFk ZHJlc3MuXG4zLiBJZiBhIHBhc3N3b3JkIGlzIHJlcXVpcmVkXCwgZW50ZXIgdGhlIG1lZXRpbmcg cGFzc3dvcmQ6IHINCiBtY2F0XG40LiBDbGljayAiSm9pbiIuXG41LiBJZiB0aGUgbWVldGluZyBp bmNsdWRlcyBhIHRlbGVjb25mZXJlbmNlXCwgZm9sbA0KIG93IHRoZSBpbnN0cnVjdGlvbnMgdGhh dCBhcHBlYXIgb24geW91ciBzY3JlZW4uXG5cbi0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tDQogLS0t LS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS1cblRvIGpvaW4gdGhlIGF1ZGlvIGNvbmZlcmVu Y2Ugb25seVxuLS0tLS0NCiAtLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0tLS0t LS0tLS0tLS0tLVxuVG8gcmVjZWl2ZSBhIGNhbGwgYmFjaw0KIFwsIHByb3ZpZGUgeW91ciBwaG9u ZSBudW1iZXIgd2hlbiB5b3Ugam9pbiB0aGUgbWVldGluZ1wsIG9yIGNhbGwgdGhlIG51bWJlDQog ciBiZWxvdyBhbmQgZW50ZXIgdGhlIGFjY2VzcyBjb2RlLlxuQ2FsbC1pbiB0b2xsLWZyZWUgbnVt YmVyIChVUy9DYW5hZGEpOiANCiArMS04NjYtNDMyLTk5MDNcbkNhbGwtaW4gdG9sbCBudW1iZXIg KFVTL0NhbmFkYSk6ICsxLTQwOC01MjUtNjgwMFxuR2xvYmFsIA0KIGNhbGwtaW4gbnVtYmVyczog aHR0cHM6Ly9jaXNjby53ZWJleC5jb20vY2lzY29zYWxlcy9nbG9iYWxjYWxsaW4ucGhwP3NlcnZp DQogY2VUeXBlPU1DJkVEPTIyMTU4NTk3MiZ0b2xsRnJlZT0xXG5Ub2xsLWZyZWUgZGlhbGluZyBy ZXN0cmljdGlvbnM6IGh0dHA6Ly8NCiB3d3cud2ViZXguY29tL3BkZi90b2xsZnJlZV9yZXN0cmlj dGlvbnMucGRmXG5BY2Nlc3MgY29kZToyMDMgNDUxIDMxMFxuQ0NQOg0KICsxNDA4NTI1NjgwMHgy MDM0NTEzMTAjXG5cblxuXG4NClJSVUxFOkZSRVE9V0VFS0xZO0lOVEVSVkFMPTI7QllEQVk9TU87 V0tTVD1TVQ0KU1VNTUFSWTtMQU5HVUFHRT1lbi1VUzpSTUNBVCBFdmFsIERlc2lnbiBUZWFtIDMg SnVuZSBVVEMgMTU6MDAtMTY6MDAgKDRwbSBMDQogb25kb25cLCAxMWFtIE5ldyBZb3JrKQ0KRFRT VEFSVDtUWklEPUVhc3Rlcm4gU3RhbmRhcmQgVGltZToyMDEzMDYwM1QxMTAwMDANCkRURU5EO1Ra SUQ9RWFzdGVybiBTdGFuZGFyZCBUaW1lOjIwMTMwNjAzVDEyMDAwMA0KVUlEOjA0MDAwMDAwODIw MEUwMDA3NEM1QjcxMDFBODJFMDA4MDAwMDAwMDA2MDI4QTM3M0JENDFDRTAxMDAwMDAwMDAwMDAw MDAwDQogMDEwMDAwMDAwQUMzNjUyQzJDMUJDOTk0RTg1QjlFMTBGRkUzMjgyN0MNCkNMQVNTOlBV QkxJQw0KUFJJT1JJVFk6NQ0KRFRTVEFNUDoyMDEzMDUyNFQyMDIyNDBaDQpUUkFOU1A6T1BBUVVF DQpTVEFUVVM6Q09ORklSTUVEDQpTRVFVRU5DRToyDQpMT0NBVElPTjtMQU5HVUFHRT1lbi1VUzpo dHRwczovL2Npc2NvLndlYmV4LmNvbS9jaXNjb3NhbGVzL2oucGhwP0VEPTIyMTU4NTkNCiA3MiZV SUQ9NDg0NjY2MzAyJlBXPU5ObU5oWlRKallUSTEmUlQ9TWlNeU1RJTNEJTNEDQpYLU1JQ1JPU09G VC1DRE8tQVBQVC1TRVFVRU5DRToyDQpYLU1JQ1JPU09GVC1DRE8tT1dORVJBUFBUSUQ6LTc2Mzgw MzY4Mw0KWC1NSUNST1NPRlQtQ0RPLUJVU1lTVEFUVVM6VEVOVEFUSVZFDQpYLU1JQ1JPU09GVC1D RE8tSU5URU5ERURTVEFUVVM6QlVTWQ0KWC1NSUNST1NPRlQtQ0RPLUFMTERBWUVWRU5UOkZBTFNF DQpYLU1JQ1JPU09GVC1DRE8tSU1QT1JUQU5DRToxDQpYLU1JQ1JPU09GVC1DRE8tSU5TVFRZUEU6 MQ0KWC1NSUNST1NPRlQtRElTQUxMT1ctQ09VTlRFUjpGQUxTRQ0KQkVHSU46VkFMQVJNDQpBQ1RJ T046RElTUExBWQ0KREVTQ1JJUFRJT046UkVNSU5ERVINClRSSUdHRVI7UkVMQVRFRD1TVEFSVDot UFQxNU0NCkVORDpWQUxBUk0NCkVORDpWRVZFTlQNCkVORDpWQ0FMRU5EQVINCg== --_000_3879D71E758A7E4AA99A35DD8D41D3D91D47C0B6xmbrcdx14ciscoc_-- From dan@marketsoup.com Sat May 25 16:04:58 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id B862521F8A54 for ; Sat, 25 May 2013 16:04:58 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: 0.48 X-Spam-Level: X-Spam-Status: No, score=0.48 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, FH_RELAY_NODNS=1.451, FM_FORGED_GMAIL=0.622, HTML_MESSAGE=0.001, RCVD_IN_PBL=0.905, RDNS_NONE=0.1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id XnE4xMrvXZUE for ; Sat, 25 May 2013 16:04:54 -0700 (PDT) Received: from mail-ie0-x234.google.com (mail-ie0-x234.google.com [IPv6:2607:f8b0:4001:c03::234]) by ietfa.amsl.com (Postfix) with ESMTP id 4804621F8551 for ; Sat, 25 May 2013 16:04:54 -0700 (PDT) Received: by mail-ie0-f180.google.com with SMTP id b11so1316513iee.25 for ; Sat, 25 May 2013 16:04:53 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=marketsoup.com; s=google; h=mime-version:x-originating-ip:date:message-id:subject:from:to :content-type; bh=waL4YUt3tU388wckz6foFfUsYF1mYDqFMOh2aF7+2Uk=; b=VlLC/mRZCdXa9K9IftLvV/ua/5Kq4vCK/MoJc3VNUwla3k3CP6fdv/qOlBP11Gq65b PIMcVrbzceEtvUwapCvJJGNkACQLte02FQC0gCHigGGq1uK9FBYAUDQMr/EJW+rflic4 m8E8T5eAl1fELmg21UmYvN/5wU4mwYGyf7xV0= X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:x-originating-ip:date:message-id:subject:from:to :content-type:x-gm-message-state; bh=waL4YUt3tU388wckz6foFfUsYF1mYDqFMOh2aF7+2Uk=; b=XRgKAUZtzHX2AeVKIi19+pu3BAfHxJC9ee12IPEV/1FFr2eqBWhaZFsb4+oDjagi2B rSnKHyux5aEFVaoS1RvEJEEEfrXtDCdPBSej/2J3sPjQ1YTKIIkSz+LvFLWnfl8PVNHP kTclqacM7q84Wb3JGIY6iQLobEWQZokfWfF0Uc96G6+XaTR7ZTwUVvpoY/YfUXy9/hxb 40JHfU5kpR7kpERrPPYq6yGILKZwOjkjVLs50vjBJpnKC8kFD/Pro+T0JgvvhIxzbLu1 AIfhqo+Paj9xWO/KISx6vCBI7scwie6fHgmoIYiupIW2c+h9bfzporUz//FY3TzEdXJs LTSA== MIME-Version: 1.0 X-Received: by 10.42.144.2 with SMTP id z2mr15271309icu.50.1369523093763; Sat, 25 May 2013 16:04:53 -0700 (PDT) Received: by 10.42.254.74 with HTTP; Sat, 25 May 2013 16:04:53 -0700 (PDT) X-Originating-IP: [174.51.153.161] Date: Sat, 25 May 2013 17:04:53 -0600 Message-ID: From: Dan Weber To: rmcat@ietf.org Content-Type: multipart/alternative; boundary=90e6ba1efd30840e2c04dd92f17a X-Gm-Message-State: ALoCoQmXkNso7lPSgSCpjogHQfocQLz0+koEKHn2UIKBIa5ZHEnEPL/u1RYw7yJlN0PMaS2i/z1G Subject: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Sat, 25 May 2013 23:04:58 -0000 --90e6ba1efd30840e2c04dd92f17a Content-Type: text/plain; charset=UTF-8 Hi guys, I've been reviewing CoDel, and it's clear how it works reasonably well for TCP. It's only slightly more complicated than an implementation using a fixed timestamp per packet expiration. The minor difference occurs when it goes into its dropping state which uses a square root scaling factor for the time based on the number of previously dropped packets in a sequence. This takes advantage of a known behavior of TCP congestion control algorithms which expect congestion to happen in large bursts. When applied to RTP unknowingly, the behavior could be pretty disastrous on video content. Although I doubt it's any worse than actual competing content with no AQM, a particular case does stand out. When CoDel is in place where there is no competing traffic and the RTP sender bursts the wire without pacing in respect to maximum stream bitrate, CoDel is likely to burst drop packets because of overflow on the queue time. I think *this behavior is extremely desirable*. This will bring awareness to all vendors and implementors that their implementations were working despite the fact that they were improper. This kind of behavior can be enhanced and augmented in a way that can be used to expedite the implementation of effective RTP Congestion Control. If we were to implement *receiver side CoDel* *for dropping "frames" or "messages" of RTP packets on new implementations*, we could become the "Soup Nazi" and start effectively identifying improper implementations as well as rendering them inoperable. *If implemented by one of the major WebRTC browser implementations, *a *chain reaction may develop that forces implementation of RTP congestion control up the pipeline*. If useful feedback is delivered back to the sender, which really needs to be net translated to *frames processed and frames dropped*, an application with its encoder could reasonably adjust. *This may solve fairness related problems because the receiver could identify if the sender overflowed the queues by evaluating actual arrival time compared with frame presentation time (converted RTP timestamps).* If the receiver enforces this constraint, fairness on RTP streams is effectively in force because implementations are rendered inoperable, and it works safely within the scope of CoDel. This implies that TCP would be only at most affected in the same way that another TCP stream would. And finally this leads to my suggested solution for sender side congestion control. Based on my assumption that CoDel implementation for AQM is on the horizon across routers in the next 5 to 10 years, a reasonable suggestion for RTP Congestion control may lead to CoDel over CoDel. An enhanced version of CoDel for implementation in the RTP stack (or at the codec encapsulation layer) provides clear frame demarcation and packet mapping (frame no == packets n..m), and drops entire frames based on: an assumption (or determination) of targeted maximum bandwidth and (optional, but highly recommended) some form of ECN. Notifications are then provided back to the application as to which frames were dropped, and the application can make the decision on how it seeks to change its behavior if at all [This combines well with the receiver based notification. If it chooses not to, the RTP stack enforces "fairness" by degrading the application performance in full units. A good implementation of this should *use FEC to maintain a constant bitrate despite the variations of the bitrate in the underlying stream. *While it does use more bandwidth than *immediately necessary* it provides great stability for the stream in *cooperation with both long lived TCP streams and short lived bursty streams*. It also *prevents unfair competition from TCP*. In addition, it *provides additional resiliency for handling intermittent packets loss* from WiFi and other wireless/cellular transmissions. I think the benefits of this solution outweigh any other that has been proposed, and solves many of the difficult challenges presented. While I have not yet build a full working model, It should work in at least as many places as CoDel works, and much research has been done and continues to be done on how well CoDel handles fairness. I would love to hear everyone's thoughts on this. Please send me your feedback. Thanks, Dan --90e6ba1efd30840e2c04dd92f17a Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Hi guys,

I've been reviewing CoDel, and it's clear how it wo= rks reasonably well for TCP.=C2=A0 It's only slightly more complicated = than an implementation using a fixed timestamp per packet expiration.=C2=A0= The minor difference occurs when it goes into its dropping state which use= s a square root scaling factor for the time based on the number of previous= ly dropped packets in a sequence.=C2=A0 This takes advantage of a known beh= avior of TCP congestion control algorithms which expect congestion to happe= n in large bursts.

When applied to RTP unknowingly, the behavior could be pretty disastrou= s on video content.=C2=A0 Although I doubt it's any worse than actual c= ompeting content with no AQM, a particular case does stand out.=C2=A0 When = CoDel is in place where there is no competing traffic and the RTP sender bu= rsts the wire without pacing in respect to maximum stream bitrate, CoDel is= likely to burst drop packets because of overflow on the queue time.=C2=A0 = I think this behavior is extremely desirable.=C2=A0 This will bring = awareness to all vendors and implementors that their implementations were w= orking despite the fact that they were improper.=C2=A0

This kind of behavior can be enhanced and augmented in a way that can b= e used to expedite the implementation of effective RTP Congestion Control.= =C2=A0=C2=A0 If we were to implement receiver side CoDel for drop= ping "frames" or "messages" of RTP packets on new imple= mentations, we could become the "Soup Nazi" and start effecti= vely identifying improper implementations as well as rendering them inopera= ble.=C2=A0 If implemented by one of the major WebRTC browser implementat= ions, a chain reaction may develop that forces implementation of RTP= congestion control up the pipeline.=C2=A0 If useful feedback is delive= red back to the sender, which really needs to be net translated to frame= s processed and frames dropped, an application with its encoder could r= easonably adjust.=C2=A0 This may solve fairness related problems because= the receiver could identify if the sender overflowed the queues by evaluat= ing actual arrival time compared with frame presentation time (converted RT= P timestamps).=C2=A0 If the receiver enforces this constraint, fairness= on RTP streams is effectively in force because implementations are rendere= d inoperable, and it works safely within the scope of CoDel.=C2=A0 This imp= lies that TCP would be only at most affected in the same way that another T= CP stream would.=C2=A0

And finally this leads to my suggested solution for sender side congest= ion control.=C2=A0 Based on my assumption that CoDel implementation for AQM= is on the horizon across routers in the next 5 to 10 years, a reasonable s= uggestion for RTP Congestion control may lead to CoDel over CoDel.=C2=A0 An= enhanced version of CoDel for implementation in the RTP stack (or at the c= odec encapsulation layer) provides clear frame demarcation and packet mappi= ng (frame no =3D=3D packets n..m), and drops entire frames based on: an ass= umption (or determination) of targeted maximum bandwidth and (optional, but= highly recommended) some form of ECN.=C2=A0 Notifications are then provide= d back to the application as to which frames were dropped, and the applicat= ion can make the decision on how it seeks to change its behavior if at all = [This combines well with the receiver based notification.=C2=A0 If it choos= es not to, the RTP stack enforces "fairness" by degrading the app= lication performance in full units.=C2=A0 A good implementation of this sho= uld use FEC to maintain a constant bitrate despite the variations of the= bitrate in the underlying stream.=C2=A0 While it does use more bandwid= th than immediately necessary it provides great stability for the st= ream in cooperation with both long lived TCP streams and short lived bur= sty streams.=C2=A0 It also prevents unfair competition from TCP.= =C2=A0 In addition, it provides additional resiliency for handling inter= mittent packets loss from WiFi and other wireless/cellular transmission= s.

I think the benefits of this solution outweigh any other that has been = proposed, and solves many of the difficult challenges presented.=C2=A0 Whil= e I have not yet build a full working model, It should work in at least as = many places as CoDel works, and much research has been done and continues t= o be done on how well CoDel handles fairness.

I would love to hear everyone's thoughts on this.=C2=A0 Please send= me your feedback.

Thanks,
Dan
--90e6ba1efd30840e2c04dd92f17a-- From lars@netapp.com Mon May 27 08:17:41 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 26B6D21F966B for ; Mon, 27 May 2013 08:17:41 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -10.127 X-Spam-Level: X-Spam-Status: No, score=-10.127 tagged_above=-999 required=5 tests=[AWL=0.472, BAYES_00=-2.599, RCVD_IN_DNSWL_HI=-8] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id pgcozfIy0ZXu for ; Mon, 27 May 2013 08:17:36 -0700 (PDT) Received: from mx12.netapp.com (mx12.netapp.com [216.240.18.77]) by ietfa.amsl.com (Postfix) with ESMTP id 71BC021F922A for ; Mon, 27 May 2013 08:17:33 -0700 (PDT) X-IronPort-AV: E=Sophos;i="4.87,751,1363158000"; d="scan'208";a="58410680" Received: from smtp2.corp.netapp.com ([10.57.159.114]) by mx12-out.netapp.com with ESMTP; 27 May 2013 08:17:32 -0700 Received: from vmwexceht01-prd.hq.netapp.com (vmwexceht01-prd.hq.netapp.com [10.106.76.239]) by smtp2.corp.netapp.com (8.13.1/8.13.1/NTAP-1.6) with ESMTP id r4RFHWvk026211 for ; Mon, 27 May 2013 08:17:32 -0700 (PDT) Received: from SACEXCMBX01-PRD.hq.netapp.com ([169.254.2.208]) by vmwexceht01-prd.hq.netapp.com ([10.106.76.239]) with mapi id 14.03.0123.003; Mon, 27 May 2013 08:17:32 -0700 From: "Eggert, Lars" To: " WG" Thread-Topic: Send agenda requests for IETF-87 Thread-Index: AQHOWu1OqpElHpoK4E2Ttuxvmdw0lg== Date: Mon, 27 May 2013 15:17:32 +0000 Message-ID: <809B822D-0777-4BED-99E5-484FCF233624@netapp.com> Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [10.106.53.51] Content-Type: text/plain; charset="us-ascii" Content-ID: Content-Transfer-Encoding: quoted-printable MIME-Version: 1.0 Subject: [rmcat] Send agenda requests for IETF-87 X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list Reply-To: "rmcat-chairs@tools.ietf.org" List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Mon, 27 May 2013 15:17:41 -0000 Hi, we asked for a 2.5h slot for RMCAT in Berlin. You may begin sending Mirja a= nd me requests for agenda time. Note that we will again prioritize discussion of topics related to our next= milestones, which are cc-requirements, eval-criteria, rtcp-requirements (i= f needed), and app-interactions. [1] The authors of IDs targeting those milestones should submit revisions soon,= so we have sufficient time to discuss them on the list before the meeting.= We should ideally wrap up cc-requirements, if possible, and make some majo= r progress on eval-criteria. For any topic *not* related to those first milestones, a request for agenda= time is best motivated by the early availability of a related ID and an ac= tive discussion on the list. Thanks, Lars [1] See http://trac.tools.ietf.org/wg/rmcat/trac/wiki/RearrangedCharter for= which milestones are meant with these short tags.= From kevin.gross@avanw.com Tue May 28 11:40:47 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 73A4721E808C for ; Tue, 28 May 2013 11:40:47 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: 0.786 X-Spam-Level: X-Spam-Status: No, score=0.786 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, FH_RELAY_NODNS=1.451, FM_FORGED_GMAIL=0.622, HELO_MISMATCH_NET=0.611, HTML_MESSAGE=0.001, J_CHICKENPOX_44=0.6, RDNS_NONE=0.1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id yOamqzR5+Z76 for ; Tue, 28 May 2013 11:40:43 -0700 (PDT) Received: from qmta13.emeryville.ca.mail.comcast.net (qmta13.emeryville.ca.mail.comcast.net [IPv6:2001:558:fe2d:44:76:96:27:243]) by ietfa.amsl.com (Postfix) with ESMTP id 2EB7F21E808D for ; Tue, 28 May 2013 11:40:42 -0700 (PDT) Received: from omta24.emeryville.ca.mail.comcast.net ([76.96.30.92]) by qmta13.emeryville.ca.mail.comcast.net with comcast id hTqk1l0071zF43QADWgiGv; Tue, 28 May 2013 18:40:42 +0000 Received: from mail-ie0-x22a.google.com ([IPv6:2607:f8b0:4001:c03::22a]) by omta24.emeryville.ca.mail.comcast.net with comcast id hWgh1l00J09Eadw8kWghPL; Tue, 28 May 2013 18:40:42 +0000 Received: by mail-ie0-f170.google.com with SMTP id e14so3853534iej.1 for ; Tue, 28 May 2013 11:40:41 -0700 (PDT) X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:in-reply-to:references:date:message-id:subject:from:to :cc:content-type; bh=c9qvo16e6nPieb6YLd6fiEoV2hzF9eCGvCwkDDg+y9Q=; b=I4bk7kHdORnKhziiaWCXcPL0TOfp0t8IAcxwiNUrjVJbwffFuQlcaCUYVnnVAIkABj O6Uzhjcr6WTDBHD1zcsPQzF+Rt2tJzlm4gzctQi+wJK+IrSALX4lTA8MSFkuh5uGjhDr /VEBhm53HWwLG+OR6Gz0bmLu/ENL8Zwsz6t10TBkIwV2G2W3EDk4oQMGyCgkwJj2ZFU7 zT2zn963CF1XVpscyRljMBwAJvN9INJ5sniUVpoSqr3xc4NVFSLXXGSS2BM8D6bqhdLJ /chBxZJ/QHx9563gqqLdOnq8UEr3v5r7W775Jj4R4ydr8/rLpDvF86qJg09GHJd+1zMR Ezww== MIME-Version: 1.0 X-Received: by 10.43.162.7 with SMTP id mi7mr19653209icc.34.1369766440327; Tue, 28 May 2013 11:40:40 -0700 (PDT) Received: by 10.50.65.69 with HTTP; Tue, 28 May 2013 11:40:40 -0700 (PDT) In-Reply-To: References: Date: Tue, 28 May 2013 12:40:40 -0600 Message-ID: From: Kevin Gross To: Dan Weber Content-Type: multipart/alternative; boundary=001a11c2124219e5f204ddcb9a7c DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=comcast.net; s=q20121106; t=1369766442; bh=c9qvo16e6nPieb6YLd6fiEoV2hzF9eCGvCwkDDg+y9Q=; h=Received:Received:Received:MIME-Version:Received:Date:Message-ID: Subject:From:To:Content-Type; b=BnAOCNLmerXfZ0dWuoj8PHLNljgzoh5p+Ey8+1BUlTIjIgqlVoNvgY+J8UPWFW2Qq HyqgpSHUTJGfFkNtFKvz6ps/9yr+rjCXWUjgyD4z7hZXc86RpgK6pJC7ATEUrgJrKb FSdgvYLQk7sTTWVZNjLqeVDXwZW/8551ntvWFqsIlu6gwLUc8G7x7dVlH8pz6FZgxw 7tjkE8GfKFtkaLdfWQfli34qXOqdJOQnnpRPGbJlb5eslJvLKxnGV/MMnqucLD57m/ 7q7nfSEEX3tKumWyEec7rPnrEH53Ngbt+R3sQonom93TU+kbq6jUKYfbzL+brqbdk7 1mlmLXucEwgUg== Cc: rmcat WG Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Tue, 28 May 2013 18:40:47 -0000 --001a11c2124219e5f204ddcb9a7c Content-Type: text/plain; charset=ISO-8859-1 I don't know where you get the idea that codel drops packets in bursts. It drops one packet per "interval". "Interval" starts at 100 ms and is reduced slowly (71, 58, 50, 45 ms...) until congestion abates. Codel is effective on TCP flows because the loss happens promptly, not because the loss is substantial. Codel is designed to be applied on a per-hop basis. I don't see how it can be applied at a receiver for an end-to-end connection as you are apparently proposing and still behave as generally intended by its inventors. Kevin Gross +1-303-447-0517 Media Network Consultant AVA Networks - www.AVAnw.com , www.X192.org On Sat, May 25, 2013 at 5:04 PM, Dan Weber wrote: > Hi guys, > > I've been reviewing CoDel, and it's clear how it works reasonably well for > TCP. It's only slightly more complicated than an implementation using a > fixed timestamp per packet expiration. The minor difference occurs when it > goes into its dropping state which uses a square root scaling factor for > the time based on the number of previously dropped packets in a sequence. > This takes advantage of a known behavior of TCP congestion control > algorithms which expect congestion to happen in large bursts. > > When applied to RTP unknowingly, the behavior could be pretty disastrous > on video content. Although I doubt it's any worse than actual competing > content with no AQM, a particular case does stand out. When CoDel is in > place where there is no competing traffic and the RTP sender bursts the > wire without pacing in respect to maximum stream bitrate, CoDel is likely > to burst drop packets because of overflow on the queue time. I think *this > behavior is extremely desirable*. This will bring awareness to all > vendors and implementors that their implementations were working despite > the fact that they were improper. > > This kind of behavior can be enhanced and augmented in a way that can be > used to expedite the implementation of effective RTP Congestion Control. > If we were to implement *receiver side CoDel* *for dropping "frames" or > "messages" of RTP packets on new implementations*, we could become the > "Soup Nazi" and start effectively identifying improper implementations as > well as rendering them inoperable. *If implemented by one of the major > WebRTC browser implementations, *a *chain reaction may develop that > forces implementation of RTP congestion control up the pipeline*. If > useful feedback is delivered back to the sender, which really needs to be > net translated to *frames processed and frames dropped*, an application > with its encoder could reasonably adjust. *This may solve fairness > related problems because the receiver could identify if the sender > overflowed the queues by evaluating actual arrival time compared with frame > presentation time (converted RTP timestamps).* If the receiver enforces > this constraint, fairness on RTP streams is effectively in force because > implementations are rendered inoperable, and it works safely within the > scope of CoDel. This implies that TCP would be only at most affected in > the same way that another TCP stream would. > > And finally this leads to my suggested solution for sender side congestion > control. Based on my assumption that CoDel implementation for AQM is on > the horizon across routers in the next 5 to 10 years, a reasonable > suggestion for RTP Congestion control may lead to CoDel over CoDel. An > enhanced version of CoDel for implementation in the RTP stack (or at the > codec encapsulation layer) provides clear frame demarcation and packet > mapping (frame no == packets n..m), and drops entire frames based on: an > assumption (or determination) of targeted maximum bandwidth and (optional, > but highly recommended) some form of ECN. Notifications are then provided > back to the application as to which frames were dropped, and the > application can make the decision on how it seeks to change its behavior if > at all [This combines well with the receiver based notification. If it > chooses not to, the RTP stack enforces "fairness" by degrading the > application performance in full units. A good implementation of this > should *use FEC to maintain a constant bitrate despite the variations of > the bitrate in the underlying stream. *While it does use more bandwidth > than *immediately necessary* it provides great stability for the stream > in *cooperation with both long lived TCP streams and short lived bursty > streams*. It also *prevents unfair competition from TCP*. In addition, > it *provides additional resiliency for handling intermittent packets loss*from WiFi and other wireless/cellular transmissions. > > I think the benefits of this solution outweigh any other that has been > proposed, and solves many of the difficult challenges presented. While I > have not yet build a full working model, It should work in at least as many > places as CoDel works, and much research has been done and continues to be > done on how well CoDel handles fairness. > > I would love to hear everyone's thoughts on this. Please send me your > feedback. > > Thanks, > Dan > --001a11c2124219e5f204ddcb9a7c Content-Type: text/html; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable
I don't know where you get the idea that codel drops p= ackets in bursts. It drops one packet per "interval". "Inter= val" starts at 100 ms and is reduced slowly (71, 58, 50, 45 ms...) unt= il congestion abates. Codel is effective on TCP flows because the loss happ= ens promptly, not because the loss is substantial.

Codel is designed to be applied on a per-hop basis. I don= 9;t see how it can be applied at a receiver for an end-to-end connection as= you are apparently proposing and still behave as generally intended by its= inventors.

Kevin Gross
+1-303-447-0517
Media Network Consultant
AVA Netwo= rks -=A0www.AVAnw.com,=A0www.X192.org


On Sat, May 25, 2013 at 5:04 PM, Dan Web= er <dan@marketsoup.com> wrote:
Hi guys,

I've been reviewing CoDel, and it's clear how it wo= rks reasonably well for TCP.=A0 It's only slightly more complicated tha= n an implementation using a fixed timestamp per packet expiration.=A0 The m= inor difference occurs when it goes into its dropping state which uses a sq= uare root scaling factor for the time based on the number of previously dro= pped packets in a sequence.=A0 This takes advantage of a known behavior of = TCP congestion control algorithms which expect congestion to happen in larg= e bursts.

When applied to RTP unknowingly, the behavior could be pretty disastrou= s on video content.=A0 Although I doubt it's any worse than actual comp= eting content with no AQM, a particular case does stand out.=A0 When CoDel = is in place where there is no competing traffic and the RTP sender bursts t= he wire without pacing in respect to maximum stream bitrate, CoDel is likel= y to burst drop packets because of overflow on the queue time.=A0 I think <= b>this behavior is extremely desirable.=A0 This will bring awareness to= all vendors and implementors that their implementations were working despi= te the fact that they were improper.=A0

This kind of behavior can be enhanced and augmented in a way that can b= e used to expedite the implementation of effective RTP Congestion Control.= =A0=A0 If we were to implement receiver side CoDel for dropping &= quot;frames" or "messages" of RTP packets on new implementat= ions, we could become the "Soup Nazi" and start effectively i= dentifying improper implementations as well as rendering them inoperable.= =A0 If implemented by one of the major WebRTC browser implementations, <= /b>a chain reaction may develop that forces implementation of RTP conges= tion control up the pipeline.=A0 If useful feedback is delivered back t= o the sender, which really needs to be net translated to frames processe= d and frames dropped, an application with its encoder could reasonably = adjust.=A0 This may solve fairness related problems because the receiver= could identify if the sender overflowed the queues by evaluating actual ar= rival time compared with frame presentation time (converted RTP timestamps)= .=A0 If the receiver enforces this constraint, fairness on RTP streams = is effectively in force because implementations are rendered inoperable, an= d it works safely within the scope of CoDel.=A0 This implies that TCP would= be only at most affected in the same way that another TCP stream would.=A0=

And finally this leads to my suggested solution for sender side congest= ion control.=A0 Based on my assumption that CoDel implementation for AQM is= on the horizon across routers in the next 5 to 10 years, a reasonable sugg= estion for RTP Congestion control may lead to CoDel over CoDel.=A0 An enhan= ced version of CoDel for implementation in the RTP stack (or at the codec e= ncapsulation layer) provides clear frame demarcation and packet mapping (fr= ame no =3D=3D packets n..m), and drops entire frames based on: an assumptio= n (or determination) of targeted maximum bandwidth and (optional, but highl= y recommended) some form of ECN.=A0 Notifications are then provided back to= the application as to which frames were dropped, and the application can m= ake the decision on how it seeks to change its behavior if at all [This com= bines well with the receiver based notification.=A0 If it chooses not to, t= he RTP stack enforces "fairness" by degrading the application per= formance in full units.=A0 A good implementation of this should use FEC = to maintain a constant bitrate despite the variations of the bitrate in the= underlying stream.=A0 While it does use more bandwidth than immedia= tely necessary it provides great stability for the stream in coopera= tion with both long lived TCP streams and short lived bursty streams.= =A0 It also prevents unfair competition from TCP.=A0 In addition, it= provides additional resiliency for handling intermittent packets loss from WiFi and other wireless/cellular transmissions.

I think the benefits of this solution outweigh any other that has been = proposed, and solves many of the difficult challenges presented.=A0 While I= have not yet build a full working model, It should work in at least as man= y places as CoDel works, and much research has been done and continues to b= e done on how well CoDel handles fairness.

I would love to hear everyone's thoughts on this.=A0 Please send me= your feedback.

Thanks,
Dan

--001a11c2124219e5f204ddcb9a7c-- From fred@cisco.com Tue May 28 12:16:52 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 34C8411E80BA for ; Tue, 28 May 2013 12:16:52 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -109.109 X-Spam-Level: X-Spam-Status: No, score=-109.109 tagged_above=-999 required=5 tests=[BAYES_05=-1.11, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_HI=-8, USER_IN_WHITELIST=-100] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id nDC0MqB1BdoE for ; Tue, 28 May 2013 12:16:47 -0700 (PDT) Received: from rcdn-iport-6.cisco.com (rcdn-iport-6.cisco.com [173.37.86.77]) by ietfa.amsl.com (Postfix) with ESMTP id 1255F11E80DE for ; Tue, 28 May 2013 12:16:47 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=17368; q=dns/txt; s=iport; t=1369768607; x=1370978207; h=from:to:cc:subject:date:message-id:references: in-reply-to:mime-version; bh=97YJoTTO5gCHNzaWEqfprw1AMRFewFzSH/+/QH34bmg=; b=Mm2Lwoo6Ru0gsWZ0IxCV8BkrEcy3rCLpSoo+/01mzAHBZ7zn7iqA3aqs p9GJNxtOuXF/HXUnn6WG9Yr26BCQFNmZzosBx/m7qo4eZU1ZDL1yAJ7xs NBk9pQrcy3hS/HyZwXLMadcEH4HoXJO05SXJ+QBagRC/MD9HjXZBJW0Ie k=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: AqYIAAgCpVGtJXG8/2dsb2JhbABPBwOCREQwhFm1EIg2gQcWdIIkAQEESTAQAgEIBxsdBzIUEQIEDgUIE4dyDLwWjVARgQshDAQGAQkIgmJhA4hnj32QF4MPgic X-IronPort-AV: E=Sophos;i="4.87,759,1363132800"; d="scan'208,217";a="215887744" Received: from rcdn-core2-1.cisco.com ([173.37.113.188]) by rcdn-iport-6.cisco.com with ESMTP; 28 May 2013 19:16:45 +0000 Received: from xhc-aln-x07.cisco.com (xhc-aln-x07.cisco.com [173.36.12.81]) by rcdn-core2-1.cisco.com (8.14.5/8.14.5) with ESMTP id r4SJGhaT010246 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL); Tue, 28 May 2013 19:16:43 GMT Received: from xmb-rcd-x09.cisco.com ([169.254.9.220]) by xhc-aln-x07.cisco.com ([173.36.12.81]) with mapi id 14.02.0318.004; Tue, 28 May 2013 14:16:43 -0500 From: "Fred Baker (fred)" To: Kevin Gross Thread-Topic: [rmcat] "Soup Nazi" RTP Congestion Control Thread-Index: AQHOWZxL6IEBmtLbYkSjConjeG2EKJkbRk0AgAAKCgA= Date: Tue, 28 May 2013 19:16:42 +0000 Message-ID: <8C48B86A895913448548E6D15DA7553B8FADD8@xmb-rcd-x09.cisco.com> References: In-Reply-To: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [10.19.64.122] Content-Type: multipart/alternative; boundary="_000_8C48B86A895913448548E6D15DA7553B8FADD8xmbrcdx09ciscocom_" MIME-Version: 1.0 Cc: Dan Weber , rmcat WG Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Tue, 28 May 2013 19:16:52 -0000 --_000_8C48B86A895913448548E6D15DA7553B8FADD8xmbrcdx09ciscocom_ Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable On May 28, 2013, at 11:40 AM, Kevin Gross > wrote: I don't know where you get the idea that codel drops packets in bursts. It = drops one packet per "interval". "Interval" starts at 100 ms and is reduced= slowly (71, 58, 50, 45 ms...) until congestion abates. Codel is effective = on TCP flows because the loss happens promptly, not because the loss is sub= stantial. Codel is designed to be applied on a per-hop basis. I don't see how it can = be applied at a receiver for an end-to-end connection as you are apparently= proposing and still behave as generally intended by its inventors. I was scratching my head on that as well. In context, you would do well to also consider PIE: http://tools.ietf.org/html/draft-pan-tsvwg-pie "PIE: A Lightweight Control Scheme To Address the Bufferbloat Problem", Rong Pan, Preethi Natarajan, Chiara Piglione, Mythili Prabhu, 10-Dec-12 It has the same caveat, of being designed to operate hop by hop. CoDel spec= ifically talks about dropping, and Van will tell you he's not fond of ECN, = but IMHO it could be applied to ECN as well. The PIE draft explicitly menti= ons ECN marking as a possibility. That would feed into https://tools.ietf.org/html/rfc6679 6679 Explicit Congestion Notification (ECN) for RTP over UDP. M. Westerlund, I. Johansson, C. Perkins, P. O'Hanlon, K. Carlberg. August 2012. (Format: TXT=3D148560 bytes) (Status: PROPOSED STANDARD) In short, ECN is intended to trigger a TCP/SCTP sender to reduce its effect= ive window a bit. RFC 3168 says "do the same thing you would in the event o= f loss", which for loss-triggered TCPs (newReno, CUBIC) means to either set= it to some value (used to be one), multiply it by some fractional value (1= /2, 7/8, or whatever), or reset it to the last value that didn't result in = such a trigger. I would expect that in the RTP context it might insert some= form of seder traffic shaping/pacing (if one presumes that a codec has cer= tain mean and maximum rates, it might default to allowing the sender to sen= d at its maximum rate, and might when told to reduce the rate in the direct= ion of the mean - and if the mean is still too quick, ask the application t= o reduce its rate by changing codecs). Kevin Gross +1-303-447-0517 Media Network Consultant AVA Networks - www.AVAnw.com, www.X192.org On Sat, May 25, 2013 at 5:04 PM, Dan Weber > wrote: Hi guys, I've been reviewing CoDel, and it's clear how it works reasonably well for = TCP. It's only slightly more complicated than an implementation using a fi= xed timestamp per packet expiration. The minor difference occurs when it g= oes into its dropping state which uses a square root scaling factor for the= time based on the number of previously dropped packets in a sequence. Thi= s takes advantage of a known behavior of TCP congestion control algorithms = which expect congestion to happen in large bursts. When applied to RTP unknowingly, the behavior could be pretty disastrous on= video content. Although I doubt it's any worse than actual competing cont= ent with no AQM, a particular case does stand out. When CoDel is in place = where there is no competing traffic and the RTP sender bursts the wire with= out pacing in respect to maximum stream bitrate, CoDel is likely to burst d= rop packets because of overflow on the queue time. I think this behavior i= s extremely desirable. This will bring awareness to all vendors and implem= entors that their implementations were working despite the fact that they w= ere improper. This kind of behavior can be enhanced and augmented in a way that can be us= ed to expedite the implementation of effective RTP Congestion Control. If= we were to implement receiver side CoDel for dropping "frames" or "message= s" of RTP packets on new implementations, we could become the "Soup Nazi" a= nd start effectively identifying improper implementations as well as render= ing them inoperable. If implemented by one of the major WebRTC browser imp= lementations, a chain reaction may develop that forces implementation of RT= P congestion control up the pipeline. If useful feedback is delivered back= to the sender, which really needs to be net translated to frames processed= and frames dropped, an application with its encoder could reasonably adjus= t. This may solve fairness related problems because the receiver could ide= ntify if the sender overflowed the queues by evaluating actual arrival time= compared with frame presentation time (converted RTP timestamps). If the = receiver enforces this constraint, fairness on RTP streams is effectively i= n force because implementations are rendered inoperable, and it works safel= y within the scope of CoDel. This implies that TCP would be only at most a= ffected in the same way that another TCP stream would. And finally this leads to my suggested solution for sender side congestion = control. Based on my assumption that CoDel implementation for AQM is on th= e horizon across routers in the next 5 to 10 years, a reasonable suggestion= for RTP Congestion control may lead to CoDel over CoDel. An enhanced vers= ion of CoDel for implementation in the RTP stack (or at the codec encapsula= tion layer) provides clear frame demarcation and packet mapping (frame no = =3D=3D packets n..m), and drops entire frames based on: an assumption (or d= etermination) of targeted maximum bandwidth and (optional, but highly recom= mended) some form of ECN. Notifications are then provided back to the appl= ication as to which frames were dropped, and the application can make the d= ecision on how it seeks to change its behavior if at all [This combines wel= l with the receiver based notification. If it chooses not to, the RTP stac= k enforces "fairness" by degrading the application performance in full unit= s. A good implementation of this should use FEC to maintain a constant bit= rate despite the variations of the bitrate in the underlying stream. While= it does use more bandwidth than immediately necessary it provides great st= ability for the stream in cooperation with both long lived TCP streams and = short lived bursty streams. It also prevents unfair competition from TCP. = In addition, it provides additional resiliency for handling intermittent p= ackets loss from WiFi and other wireless/cellular transmissions. I think the benefits of this solution outweigh any other that has been prop= osed, and solves many of the difficult challenges presented. While I have = not yet build a full working model, It should work in at least as many plac= es as CoDel works, and much research has been done and continues to be done= on how well CoDel handles fairness. I would love to hear everyone's thoughts on this. Please send me your feed= back. Thanks, Dan * Make things as simple as possible, but not simpler. Albert Einstein --_000_8C48B86A895913448548E6D15DA7553B8FADD8xmbrcdx09ciscocom_ Content-Type: text/html; charset="iso-8859-1" Content-ID: <60757A57DDDA484FA2F3A6A7FB3CFD3A@emea.cisco.com> Content-Transfer-Encoding: quoted-printable
On May 28, 2013, at 11:40 AM, Kevin Gross <kevin.gross@avanw.com> wrote:

I don't know where you get the idea that codel drops packe= ts in bursts. It drops one packet per "interval". "Interval&= quot; starts at 100 ms and is reduced slowly (71, 58, 50, 45 ms...) until c= ongestion abates. Codel is effective on TCP flows because the loss happens promptly, not because the loss is substantial.

Codel is designed to be applied on a per-hop basis. I don't see how it= can be applied at a receiver for an end-to-end connection as you are appar= ently proposing and still behave as generally intended by its inventors.

I was scratching my head on that as well.

In context, you would do well to also consider P= IE:

http://tools.ietf.org/html/draft-pan-tsvwg-pie
  "PIE: A Lightweight Control Scheme T= o Address the Bufferbloat Problem",
  Rong Pan, Preethi Natarajan, Chiara Pigli= one, Mythili Prabhu, 10-Dec-12

It has the same caveat, of being designed to operate hop by hop. CoDel= specifically talks about dropping, and Van will tell you he's not fond of = ECN, but IMHO it could be applied to ECN as well. The PIE draft explicitly = mentions ECN marking as a possibility. That would feed into

6679 Explicit Congestion Notification (ECN) for RTP over UDP. M.
     Westerlund, I. Johansson, C. Perkins, P. O'Hanlon,= K. Carlberg.
     August 2012. (Format: TXT=3D148560 bytes) (Status:= PROPOSED STANDARD)

In short, ECN is intended to trigger a TCP/SCTP sender to reduce its e= ffective window a bit. RFC 3168 says "do the same thing you would in t= he event of loss", which for loss-triggered TCPs (newReno, CUBIC) mean= s to either set it to some value (used to be one), multiply it by some fractional value (1/2, 7/8, or whatever), or = reset it to the last value that didn't result in such a trigger. I would ex= pect that in the RTP context it might insert some form of seder traffic sha= ping/pacing (if one presumes that a codec has certain mean and maximum rates, it might default to allowing t= he sender to send at its maximum rate, and might when told to reduce the ra= te in the direction of the mean - and if the mean is still too quick, ask t= he application to reduce its rate by changing codecs).


Kevin Gross
+1-303-447-0517
Media Network Consultant
AVA Networks - www.AVAnw.com, www.X192.org


On Sat, May 25, 2013 at 5:04 PM, Dan Weber <dan@marketsoup.= com> wrote:
Hi guys,

I've been reviewing CoDel, and it's clear how it works reasonably well for = TCP.  It's only slightly more complicated than an implementation using= a fixed timestamp per packet expiration.  The minor difference occurs= when it goes into its dropping state which uses a square root scaling factor for the time based on the number of prev= iously dropped packets in a sequence.  This takes advantage of a known= behavior of TCP congestion control algorithms which expect congestion to h= appen in large bursts.

When applied to RTP unknowingly, the behavior could be pretty disastrous on= video content.  Although I doubt it's any worse than actual competing= content with no AQM, a particular case does stand out.  When CoDel is= in place where there is no competing traffic and the RTP sender bursts the wire without pacing in respect to maximum st= ream bitrate, CoDel is likely to burst drop packets because of overflow on = the queue time.  I think this behavior is extremely desirable.  This will bring awarenes= s to all vendors and implementors that their implementations were working d= espite the fact that they were improper. 

This kind of behavior can be enhanced and augmented in a way that can be us= ed to expedite the implementation of effective RTP Congestion Control. = ;  If we were to implement receiver side CoDel for dropping "frames" or "mess= ages" of RTP packets on new implementations, we could become the &= quot;Soup Nazi" and start effectively identifying improper implementat= ions as well as rendering them inoperable.  If implemented by one of the major WebRTC browser implementations, a= chain reaction may develop that forces implementation of RTP congestion= control up the pipeline.  If useful feedback is delivered back to= the sender, which really needs to be net translated to frames processed and frames dropped, an applicati= on with its encoder could reasonably adjust.  This may solve fairness related problems because the receiver could iden= tify if the sender overflowed the queues by evaluating actual arrival time = compared with frame presentation time (converted RTP timestamps). = If the receiver enforces this constraint, fairness on RTP streams is effectively in force because implementations ar= e rendered inoperable, and it works safely within the scope of CoDel. = This implies that TCP would be only at most affected in the same way that = another TCP stream would. 

And finally this leads to my suggested solution for sender side congestion = control.  Based on my assumption that CoDel implementation for AQM is = on the horizon across routers in the next 5 to 10 years, a reasonable sugge= stion for RTP Congestion control may lead to CoDel over CoDel.  An enhanced version of CoDel for implement= ation in the RTP stack (or at the codec encapsulation layer) provides clear= frame demarcation and packet mapping (frame no =3D=3D packets n..m), and d= rops entire frames based on: an assumption (or determination) of targeted maximum bandwidth and (optional, but highly= recommended) some form of ECN.  Notifications are then provided back = to the application as to which frames were dropped, and the application can= make the decision on how it seeks to change its behavior if at all [This combines well with the receiver based = notification.  If it chooses not to, the RTP stack enforces "fair= ness" by degrading the application performance in full units.  A = good implementation of this should use FEC to maintain a constant bitrate despite the variations of the bit= rate in the underlying stream.  While it does use more bandwidth than immediately necessary it p= rovides great stability for the stream in cooperation with both long lived TCP streams and short lived bursty stre= ams.  It also prevents unfair competition from TCP.  In addition, it provi= des additional resiliency for handling intermittent packets loss from W= iFi and other wireless/cellular transmissions.

I think the benefits of this solution outweigh any other that has been prop= osed, and solves many of the difficult challenges presented.  While I = have not yet build a full working model, It should work in at least as many= places as CoDel works, and much research has been done and continues to be done on how well CoDel handles fairness.=

I would love to hear everyone's thoughts on this.  Please send me your= feedback.

Thanks,
Dan


  • Make things as simple as possible, but= not simpler.
    Albert Einstein

--_000_8C48B86A895913448548E6D15DA7553B8FADD8xmbrcdx09ciscocom_-- From kevin.gross@avanw.com Tue May 28 12:52:10 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 0CF0D11E8101 for ; Tue, 28 May 2013 12:52:10 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: 0.186 X-Spam-Level: X-Spam-Status: No, score=0.186 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, FH_RELAY_NODNS=1.451, FM_FORGED_GMAIL=0.622, HELO_MISMATCH_NET=0.611, HTML_MESSAGE=0.001, RDNS_NONE=0.1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id nBTo+NXH9999 for ; Tue, 28 May 2013 12:52:04 -0700 (PDT) Received: from qmta05.emeryville.ca.mail.comcast.net (qmta05.emeryville.ca.mail.comcast.net [IPv6:2001:558:fe2d:43:76:96:30:48]) by ietfa.amsl.com (Postfix) with ESMTP id A8E2111E80D5 for ; Tue, 28 May 2013 12:52:01 -0700 (PDT) Received: from omta18.emeryville.ca.mail.comcast.net ([76.96.30.74]) by qmta05.emeryville.ca.mail.comcast.net with comcast id hVp31l0091bwxycA5Xs19u; Tue, 28 May 2013 19:52:01 +0000 Received: from mail-ie0-f178.google.com ([209.85.223.178]) by omta18.emeryville.ca.mail.comcast.net with comcast id hXq01l00K3rZRp58eXq0Cz; Tue, 28 May 2013 19:50:01 +0000 Received: by mail-ie0-f178.google.com with SMTP id f4so6464650iea.37 for ; Tue, 28 May 2013 12:50:00 -0700 (PDT) X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:in-reply-to:references:date:message-id:subject:from:to :cc:content-type; bh=gtncxHUG/TqSt+XU2GqjV5AmJq0gJNbTv4PwZH4egMk=; b=E85YCbw4CwjPMo7k3dC5yT1CrKUDKfE68xYTuLbyhRpDO+/7zi9GuqRiSFQ5SSamNV EU+EVnB7or+dn8hnD/BEf6irEP/7cFU1VaFA8scsjT5XT3zyzPEochKsfiDqC5irm636 S/xuzoh/dxMOZJ2/chgUpkNI7Nw1Uz4pu57zAPw+Xxca8RxPJQ3JVml8pwbqmQfrsrPM OHzXk/RqK10nQc5Jhtxzr90aIHedF4XNUcs1vusFK5GQAQwZORjO4jK+KHpOogj7Zzlg JitPmZUzmLG1U+VQI5VIuoKXpdmPCxojIM5XFKJbSA4NqD+CAMI0JUMg6DCNhpmt05gJ iKhA== MIME-Version: 1.0 X-Received: by 10.50.126.1 with SMTP id mu1mr7903545igb.5.1369770600007; Tue, 28 May 2013 12:50:00 -0700 (PDT) Received: by 10.50.65.69 with HTTP; Tue, 28 May 2013 12:49:59 -0700 (PDT) In-Reply-To: <8C48B86A895913448548E6D15DA7553B8FADD8@xmb-rcd-x09.cisco.com> References: <8C48B86A895913448548E6D15DA7553B8FADD8@xmb-rcd-x09.cisco.com> Date: Tue, 28 May 2013 13:49:59 -0600 Message-ID: From: Kevin Gross To: "Fred Baker (fred)" Content-Type: multipart/alternative; boundary=047d7b1637b709a60404ddcc92b2 DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=comcast.net; s=q20121106; t=1369770721; bh=gtncxHUG/TqSt+XU2GqjV5AmJq0gJNbTv4PwZH4egMk=; h=Received:Received:Received:MIME-Version:Received:Date:Message-ID: Subject:From:To:Content-Type; b=O9jtI1nKYMngVeYDC8uTOE2cwPdwn8P1wx/LdIYW9T0MqV0N9npkoyLiTKu8t1+cU eisWKVXEb24HtpRaCaY66vVPYkiJh4xK7ziRJPfw59GqLvMljdp6VQ5Wedx47FOR6I xJif7wbv4AIjFsPIekq5obNmTpQw/SCRmnGBdIk7sMGaWruM4DWOgohZFc/JyXRVcp mUNT0ka9PYg3kImxwZb+F6rdmFBHgnv50PU88GwWB1yHlCE7LGHLH1ozXSmUvWr3Mi 0kDYfsOc3UbAhryE7wqH76+eUHRDSZ207fgpiqbunFgeMJiROgIqpr5TmYrZ6sg4nW AcT2hpabWnYoQ== Cc: Dan Weber , rmcat WG Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Tue, 28 May 2013 19:52:10 -0000 --047d7b1637b709a60404ddcc92b2 Content-Type: text/plain; charset=ISO-8859-1 We should definitely keep AQM (including ECN) in mind in this work but I don't think this is the right place to have a PIE vs CoDel discussion. Kevin Gross +1-303-447-0517 Media Network Consultant AVA Networks - www.AVAnw.com , www.X192.org On Tue, May 28, 2013 at 1:16 PM, Fred Baker (fred) wrote: > > On May 28, 2013, at 11:40 AM, Kevin Gross wrote: > > I don't know where you get the idea that codel drops packets in bursts. > It drops one packet per "interval". "Interval" starts at 100 ms and is > reduced slowly (71, 58, 50, 45 ms...) until congestion abates. Codel is > effective on TCP flows because the loss happens promptly, not because the > loss is substantial. > > Codel is designed to be applied on a per-hop basis. I don't see how it > can be applied at a receiver for an end-to-end connection as you are > apparently proposing and still behave as generally intended by its > inventors. > > > I was scratching my head on that as well. > > In context, you would do well to also consider PIE: > > http://tools.ietf.org/html/draft-pan-tsvwg-pie > "PIE: A Lightweight Control Scheme To Address the Bufferbloat Problem", > Rong Pan, Preethi Natarajan, Chiara Piglione, Mythili Prabhu, 10-Dec-12 > > It has the same caveat, of being designed to operate hop by hop. CoDel > specifically talks about dropping, and Van will tell you he's not fond of > ECN, but IMHO it could be applied to ECN as well. The PIE draft explicitly > mentions ECN marking as a possibility. That would feed into > > https://tools.ietf.org/html/rfc6679 > 6679 Explicit Congestion Notification (ECN) for RTP over UDP. M. > Westerlund, I. Johansson, C. Perkins, P. O'Hanlon, K. Carlberg. > August 2012. (Format: TXT=148560 bytes) (Status: PROPOSED STANDARD) > > In short, ECN is intended to trigger a TCP/SCTP sender to reduce its > effective window a bit. RFC 3168 says "do the same thing you would in the > event of loss", which for loss-triggered TCPs (newReno, CUBIC) means to > either set it to some value (used to be one), multiply it by some > fractional value (1/2, 7/8, or whatever), or reset it to the last value > that didn't result in such a trigger. I would expect that in the RTP > context it might insert some form of seder traffic shaping/pacing (if one > presumes that a codec has certain mean and maximum rates, it might default > to allowing the sender to send at its maximum rate, and might when told to > reduce the rate in the direction of the mean - and if the mean is still too > quick, ask the application to reduce its rate by changing codecs). > > > Kevin Gross > +1-303-447-0517 > Media Network Consultant > AVA Networks - www.AVAnw.com , www.X192.org > > > On Sat, May 25, 2013 at 5:04 PM, Dan Weber wrote: > >> Hi guys, >> >> I've been reviewing CoDel, and it's clear how it works reasonably well >> for TCP. It's only slightly more complicated than an implementation using >> a fixed timestamp per packet expiration. The minor difference occurs when >> it goes into its dropping state which uses a square root scaling factor for >> the time based on the number of previously dropped packets in a sequence. >> This takes advantage of a known behavior of TCP congestion control >> algorithms which expect congestion to happen in large bursts. >> >> When applied to RTP unknowingly, the behavior could be pretty disastrous >> on video content. Although I doubt it's any worse than actual competing >> content with no AQM, a particular case does stand out. When CoDel is in >> place where there is no competing traffic and the RTP sender bursts the >> wire without pacing in respect to maximum stream bitrate, CoDel is likely >> to burst drop packets because of overflow on the queue time. I think *this >> behavior is extremely desirable*. This will bring awareness to all >> vendors and implementors that their implementations were working despite >> the fact that they were improper. >> >> This kind of behavior can be enhanced and augmented in a way that can be >> used to expedite the implementation of effective RTP Congestion Control. >> If we were to implement *receiver side CoDel* *for dropping "frames" or >> "messages" of RTP packets on new implementations*, we could become the >> "Soup Nazi" and start effectively identifying improper implementations as >> well as rendering them inoperable. *If implemented by one of the major >> WebRTC browser implementations, *a *chain reaction may develop that >> forces implementation of RTP congestion control up the pipeline*. If >> useful feedback is delivered back to the sender, which really needs to be >> net translated to *frames processed and frames dropped*, an application >> with its encoder could reasonably adjust. *This may solve fairness >> related problems because the receiver could identify if the sender >> overflowed the queues by evaluating actual arrival time compared with frame >> presentation time (converted RTP timestamps).* If the receiver enforces >> this constraint, fairness on RTP streams is effectively in force because >> implementations are rendered inoperable, and it works safely within the >> scope of CoDel. This implies that TCP would be only at most affected in >> the same way that another TCP stream would. >> >> And finally this leads to my suggested solution for sender side >> congestion control. Based on my assumption that CoDel implementation for >> AQM is on the horizon across routers in the next 5 to 10 years, a >> reasonable suggestion for RTP Congestion control may lead to CoDel over >> CoDel. An enhanced version of CoDel for implementation in the RTP stack >> (or at the codec encapsulation layer) provides clear frame demarcation and >> packet mapping (frame no == packets n..m), and drops entire frames based >> on: an assumption (or determination) of targeted maximum bandwidth and >> (optional, but highly recommended) some form of ECN. Notifications are >> then provided back to the application as to which frames were dropped, and >> the application can make the decision on how it seeks to change its >> behavior if at all [This combines well with the receiver based >> notification. If it chooses not to, the RTP stack enforces "fairness" by >> degrading the application performance in full units. A good implementation >> of this should *use FEC to maintain a constant bitrate despite the >> variations of the bitrate in the underlying stream. *While it does use >> more bandwidth than *immediately necessary* it provides great stability >> for the stream in *cooperation with both long lived TCP streams and >> short lived bursty streams*. It also *prevents unfair competition from >> TCP*. In addition, it *provides additional resiliency for handling >> intermittent packets loss* from WiFi and other wireless/cellular >> transmissions. >> >> I think the benefits of this solution outweigh any other that has been >> proposed, and solves many of the difficult challenges presented. While I >> have not yet build a full working model, It should work in at least as many >> places as CoDel works, and much research has been done and continues to be >> done on how well CoDel handles fairness. >> >> I would love to hear everyone's thoughts on this. Please send me your >> feedback. >> >> Thanks, >> Dan >> > > > > - Make things as simple as possible, but not simpler. > Albert Einstein > > > --047d7b1637b709a60404ddcc92b2 Content-Type: text/html; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable
We should definitely keep AQM (including ECN) in mind in t= his work but I don't think this is the right place to have a PIE vs CoD= el discussion.

Kevin= Gross
+1-303-447-0517
Media Network Consultant
AVA Network= s -=A0www.AVAnw.com= ,=A0www.X192.org


On Tue, May 28, 2013 at 1:16 PM, Fred Ba= ker (fred) <fred@cisco.com> wrote:

On May 28, 2013, at 11:40 AM, Kevin Gross <kevin.gross@avanw.com> wrote:
I don't know where you get the idea that codel drops p= ackets in bursts. It drops one packet per "interval". "Inter= val" starts at 100 ms and is reduced slowly (71, 58, 50, 45 ms...) unt= il congestion abates. Codel is effective on TCP flows because the loss happens promptly, not because the loss is substantial.

Codel is designed to be applied on a per-hop basis. I don't see ho= w it can be applied at a receiver for an end-to-end connection as you are a= pparently proposing and still behave as generally intended by its inventors= .

I was scratching my head on that as well.<= /div>

In context, you would do well to also consider P= IE:

http://tools.ietf.org/html/draft-pan-tsvwg-pie=
=A0 "PIE: A Lightweight Control Scheme To A= ddress the Bufferbloat Problem",
=A0 Rong Pan, Preethi Natarajan, Chiara Piglione= , Mythili Prabhu, 10-Dec-12

It has the same caveat, of being designed to operate hop by hop. CoDel= specifically talks about dropping, and Van will tell you he's not fond= of ECN, but IMHO it could be applied to ECN as well. The PIE draft explici= tly mentions ECN marking as a possibility. That would feed into

6679 Explicit Congestion Notification (ECN) for RTP over UDP. M.
=A0 =A0 =A0Westerlund, I. Johansson, C. Perkins, P. O'Hanlon, K. C= arlberg.
=A0 =A0 =A0August 2012. (Format: TXT=3D148560 bytes) (Status: PROPOSED= STANDARD)

In short, ECN is intended to trigger a TCP/SCTP sender to reduce its e= ffective window a bit. RFC 3168 says "do the same thing you would in t= he event of loss", which for loss-triggered TCPs (newReno, CUBIC) mean= s to either set it to some value (used to be one), multiply it by some fractional value (1/2, 7/8, or whatever), or = reset it to the last value that didn't result in such a trigger. I woul= d expect that in the RTP context it might insert some form of seder traffic= shaping/pacing (if one presumes that a codec has certain mean and maximum rates, it might default to allowing t= he sender to send at its maximum rate, and might when told to reduce the ra= te in the direction of the mean - and if the mean is still too quick, ask t= he application to reduce its rate by changing codecs).


Kevin Gross
Media Network Consultant
AVA Networks -=A0w= ww.AVAnw.com,=A0www.= X192.org


On Sat, May 25, 2013 at 5:04 PM, Dan Weber <dan@marketsoup.= com> wrote:
Hi guys,

I've been reviewing CoDel, and it's clear how it works reasonably w= ell for TCP.=A0 It's only slightly more complicated than an implementat= ion using a fixed timestamp per packet expiration.=A0 The minor difference = occurs when it goes into its dropping state which uses a square root scaling factor for the time based on the number of prev= iously dropped packets in a sequence.=A0 This takes advantage of a known be= havior of TCP congestion control algorithms which expect congestion to happ= en in large bursts.

When applied to RTP unknowingly, the behavior could be pretty disastrous on= video content.=A0 Although I doubt it's any worse than actual competin= g content with no AQM, a particular case does stand out.=A0 When CoDel is i= n place where there is no competing traffic and the RTP sender bursts the wire without pacing in respect to maximum st= ream bitrate, CoDel is likely to burst drop packets because of overflow on = the queue time.=A0 I think this behavior is extremely desirable.=A0 This will bring awareness t= o all vendors and implementors that their implementations were working desp= ite the fact that they were improper.=A0

This kind of behavior can be enhanced and augmented in a way that can be us= ed to expedite the implementation of effective RTP Congestion Control.=A0= =A0 If we were to implement receiver side CoDel for dropping "frames" or "mess= ages" of RTP packets on new implementations, we could become the &= quot;Soup Nazi" and start effectively identifying improper implementat= ions as well as rendering them inoperable.=A0 If implemented by one of the major WebRTC browser implementations, a= chain reaction may develop that forces implementation of RTP congestion= control up the pipeline.=A0 If useful feedback is delivered back to th= e sender, which really needs to be net translated to frames processed and frames dropped, an applicati= on with its encoder could reasonably adjust.=A0 This may solve fairness related problems because the receiver could iden= tify if the sender overflowed the queues by evaluating actual arrival time = compared with frame presentation time (converted RTP timestamps).=A0 If= the receiver enforces this constraint, fairness on RTP streams is effectively in force because implementations ar= e rendered inoperable, and it works safely within the scope of CoDel.=A0 Th= is implies that TCP would be only at most affected in the same way that ano= ther TCP stream would.=A0

And finally this leads to my suggested solution for sender side congestion = control.=A0 Based on my assumption that CoDel implementation for AQM is on = the horizon across routers in the next 5 to 10 years, a reasonable suggesti= on for RTP Congestion control may lead to CoDel over CoDel.=A0 An enhanced version of CoDel for implementati= on in the RTP stack (or at the codec encapsulation layer) provides clear fr= ame demarcation and packet mapping (frame no =3D=3D packets n..m), and drop= s entire frames based on: an assumption (or determination) of targeted maximum bandwidth and (optional, but highly= recommended) some form of ECN.=A0 Notifications are then provided back to = the application as to which frames were dropped, and the application can ma= ke the decision on how it seeks to change its behavior if at all [This combines well with the receiver based = notification.=A0 If it chooses not to, the RTP stack enforces "fairnes= s" by degrading the application performance in full units.=A0 A good i= mplementation of this should use FEC to maintain a constant bitrate despite the variations of the bit= rate in the underlying stream.=A0 While it does use more bandwidth than immediately necessary it p= rovides great stability for the stream in cooperation with both long lived TCP streams and short lived bursty stre= ams.=A0 It also prevents unfair competition from TCP.=A0 In addition, it provides= additional resiliency for handling intermittent packets loss from WiFi= and other wireless/cellular transmissions.

I think the benefits of this solution outweigh any other that has been prop= osed, and solves many of the difficult challenges presented.=A0 While I hav= e not yet build a full working model, It should work in at least as many pl= aces as CoDel works, and much research has been done and continues to be done on how well CoDel handles fairness.=

I would love to hear everyone's thoughts on this.=A0 Please send me you= r feedback.

Thanks,
Dan


  • Make things as simple as possible, but no= t simpler.
    Albert Einstein


--047d7b1637b709a60404ddcc92b2-- From fred@cisco.com Tue May 28 13:57:47 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 0EE5A21E8097 for ; Tue, 28 May 2013 13:57:47 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -109.853 X-Spam-Level: X-Spam-Status: No, score=-109.853 tagged_above=-999 required=5 tests=[AWL=0.745, BAYES_00=-2.599, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_HI=-8, USER_IN_WHITELIST=-100] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id Sw1UORyiFY9M for ; Tue, 28 May 2013 13:57:41 -0700 (PDT) Received: from rcdn-iport-8.cisco.com (rcdn-iport-8.cisco.com [173.37.86.79]) by ietfa.amsl.com (Postfix) with ESMTP id 4825121F8E12 for ; Tue, 28 May 2013 13:56:42 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=21420; q=dns/txt; s=iport; t=1369774602; x=1370984202; h=from:to:cc:subject:date:message-id:references: in-reply-to:mime-version; bh=SHM7YfyG0M5+RsYRXURSOL6S4Nt4ES3U9PaPMCkh9yg=; b=jFU6ITo9D7ZY/xoDmrRcUjhW6PIybKHAKUt6uc2W3XLZ0hns9nyeg4At PQX0Aw96x0QIdiOHSX9k036fJV0+ajztvx34COYzHQqsH2SFzmBGUH8BB +Go1ADHZebB0ttOkiLLrnYDEQ9EdJ0vO9/ArUTQiSlbqGiXp6w8q8SOMb I=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: AlwGAFYYpVGtJV2Y/2dsb2JhbABPBwOCREQwuWyINoEGFnSCJAEBBEkkDBACAQgHGx0HMhQRAgQOBQgTh3IMu2aNUBEFgQYhDAQGAQkIgmJhA4hnj32QF4MPgWk+ X-IronPort-AV: E=Sophos;i="4.87,759,1363132800"; d="scan'208,217";a="215911149" Received: from rcdn-core-1.cisco.com ([173.37.93.152]) by rcdn-iport-8.cisco.com with ESMTP; 28 May 2013 20:56:41 +0000 Received: from xhc-aln-x12.cisco.com (xhc-aln-x12.cisco.com [173.36.12.86]) by rcdn-core-1.cisco.com (8.14.5/8.14.5) with ESMTP id r4SKufsv007475 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL); Tue, 28 May 2013 20:56:41 GMT Received: from xmb-rcd-x09.cisco.com ([169.254.9.220]) by xhc-aln-x12.cisco.com ([173.36.12.86]) with mapi id 14.02.0318.004; Tue, 28 May 2013 15:56:41 -0500 From: "Fred Baker (fred)" To: Kevin Gross Thread-Topic: [rmcat] "Soup Nazi" RTP Congestion Control Thread-Index: AQHOWZxL6IEBmtLbYkSjConjeG2EKJkbRk0AgAAKCgCAAAlUgIAAEp6A Date: Tue, 28 May 2013 20:56:40 +0000 Message-ID: <8C48B86A895913448548E6D15DA7553B8FB058@xmb-rcd-x09.cisco.com> References: <8C48B86A895913448548E6D15DA7553B8FADD8@xmb-rcd-x09.cisco.com> In-Reply-To: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [10.19.64.122] Content-Type: multipart/alternative; boundary="_000_8C48B86A895913448548E6D15DA7553B8FB058xmbrcdx09ciscocom_" MIME-Version: 1.0 Cc: Dan Weber , rmcat WG Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Tue, 28 May 2013 20:57:47 -0000 --_000_8C48B86A895913448548E6D15DA7553B8FB058xmbrcdx09ciscocom_ Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable On May 28, 2013, at 12:49 PM, Kevin Gross > wrote: We should definitely keep AQM (including ECN) in mind in this work but I do= n't think this is the right place to have a PIE vs CoDel discussion. I didn't intend to introduce a "vs"; my point, if anything, is to not limit= one's thinking to CoDel, and to suggest a way that hop-by-hop AQM would be= effectively used in RTP congestion control. Kevin Gross +1-303-447-0517 Media Network Consultant AVA Networks - www.AVAnw.com, www.X192.org On Tue, May 28, 2013 at 1:16 PM, Fred Baker (fred) > wrote: On May 28, 2013, at 11:40 AM, Kevin Gross > wrote: I don't know where you get the idea that codel drops packets in bursts. It = drops one packet per "interval". "Interval" starts at 100 ms and is reduced= slowly (71, 58, 50, 45 ms...) until congestion abates. Codel is effective = on TCP flows because the loss happens promptly, not because the loss is sub= stantial. Codel is designed to be applied on a per-hop basis. I don't see how it can = be applied at a receiver for an end-to-end connection as you are apparently= proposing and still behave as generally intended by its inventors. I was scratching my head on that as well. In context, you would do well to also consider PIE: http://tools.ietf.org/html/draft-pan-tsvwg-pie "PIE: A Lightweight Control Scheme To Address the Bufferbloat Problem", Rong Pan, Preethi Natarajan, Chiara Piglione, Mythili Prabhu, 10-Dec-12 It has the same caveat, of being designed to operate hop by hop. CoDel spec= ifically talks about dropping, and Van will tell you he's not fond of ECN, = but IMHO it could be applied to ECN as well. The PIE draft explicitly menti= ons ECN marking as a possibility. That would feed into https://tools.ietf.org/html/rfc6679 6679 Explicit Congestion Notification (ECN) for RTP over UDP. M. Westerlund, I. Johansson, C. Perkins, P. O'Hanlon, K. Carlberg. August 2012. (Format: TXT=3D148560 bytes) (Status: PROPOSED STANDARD) In short, ECN is intended to trigger a TCP/SCTP sender to reduce its effect= ive window a bit. RFC 3168 says "do the same thing you would in the event o= f loss", which for loss-triggered TCPs (newReno, CUBIC) means to either set= it to some value (used to be one), multiply it by some fractional value (1= /2, 7/8, or whatever), or reset it to the last value that didn't result in = such a trigger. I would expect that in the RTP context it might insert some= form of seder traffic shaping/pacing (if one presumes that a codec has cer= tain mean and maximum rates, it might default to allowing the sender to sen= d at its maximum rate, and might when told to reduce the rate in the direct= ion of the mean - and if the mean is still too quick, ask the application t= o reduce its rate by changing codecs). Kevin Gross +1-303-447-0517 Media Network Consultant AVA Networks - www.AVAnw.com, www.X192.org On Sat, May 25, 2013 at 5:04 PM, Dan Weber > wrote: Hi guys, I've been reviewing CoDel, and it's clear how it works reasonably well for = TCP. It's only slightly more complicated than an implementation using a fi= xed timestamp per packet expiration. The minor difference occurs when it g= oes into its dropping state which uses a square root scaling factor for the= time based on the number of previously dropped packets in a sequence. Thi= s takes advantage of a known behavior of TCP congestion control algorithms = which expect congestion to happen in large bursts. When applied to RTP unknowingly, the behavior could be pretty disastrous on= video content. Although I doubt it's any worse than actual competing cont= ent with no AQM, a particular case does stand out. When CoDel is in place = where there is no competing traffic and the RTP sender bursts the wire with= out pacing in respect to maximum stream bitrate, CoDel is likely to burst d= rop packets because of overflow on the queue time. I think this behavior i= s extremely desirable. This will bring awareness to all vendors and implem= entors that their implementations were working despite the fact that they w= ere improper. This kind of behavior can be enhanced and augmented in a way that can be us= ed to expedite the implementation of effective RTP Congestion Control. If= we were to implement receiver side CoDel for dropping "frames" or "message= s" of RTP packets on new implementations, we could become the "Soup Nazi" a= nd start effectively identifying improper implementations as well as render= ing them inoperable. If implemented by one of the major WebRTC browser imp= lementations, a chain reaction may develop that forces implementation of RT= P congestion control up the pipeline. If useful feedback is delivered back= to the sender, which really needs to be net translated to frames processed= and frames dropped, an application with its encoder could reasonably adjus= t. This may solve fairness related problems because the receiver could ide= ntify if the sender overflowed the queues by evaluating actual arrival time= compared with frame presentation time (converted RTP timestamps). If the = receiver enforces this constraint, fairness on RTP streams is effectively i= n force because implementations are rendered inoperable, and it works safel= y within the scope of CoDel. This implies that TCP would be only at most a= ffected in the same way that another TCP stream would. And finally this leads to my suggested solution for sender side congestion = control. Based on my assumption that CoDel implementation for AQM is on th= e horizon across routers in the next 5 to 10 years, a reasonable suggestion= for RTP Congestion control may lead to CoDel over CoDel. An enhanced vers= ion of CoDel for implementation in the RTP stack (or at the codec encapsula= tion layer) provides clear frame demarcation and packet mapping (frame no = =3D=3D packets n..m), and drops entire frames based on: an assumption (or d= etermination) of targeted maximum bandwidth and (optional, but highly recom= mended) some form of ECN. Notifications are then provided back to the appl= ication as to which frames were dropped, and the application can make the d= ecision on how it seeks to change its behavior if at all [This combines wel= l with the receiver based notification. If it chooses not to, the RTP stac= k enforces "fairness" by degrading the application performance in full unit= s. A good implementation of this should use FEC to maintain a constant bit= rate despite the variations of the bitrate in the underlying stream. While= it does use more bandwidth than immediately necessary it provides great st= ability for the stream in cooperation with both long lived TCP streams and = short lived bursty streams. It also prevents unfair competition from TCP. = In addition, it provides additional resiliency for handling intermittent p= ackets loss from WiFi and other wireless/cellular transmissions. I think the benefits of this solution outweigh any other that has been prop= osed, and solves many of the difficult challenges presented. While I have = not yet build a full working model, It should work in at least as many plac= es as CoDel works, and much research has been done and continues to be done= on how well CoDel handles fairness. I would love to hear everyone's thoughts on this. Please send me your feed= back. Thanks, Dan * Make things as simple as possible, but not simpler. Albert Einstein ----------------------------------- "We are learning to do a great many clever things...The next great task will be to learn not to do them." - G. K. Chesterton (1874-1936) --_000_8C48B86A895913448548E6D15DA7553B8FB058xmbrcdx09ciscocom_ Content-Type: text/html; charset="iso-8859-1" Content-ID: <799717B036046B4EAAF89CD89DECD460@emea.cisco.com> Content-Transfer-Encoding: quoted-printable
On May 28, 2013, at 12:49 PM, Kevin Gross <kevin.gross@avanw.com> wrote:

We should definitely keep AQM (including ECN) in mind in t= his work but I don't think this is the right place to have a PIE vs CoDel d= iscussion.

I didn't intend to introduce a "vs"; m= y point, if anything, is to not limit one's thinking to CoDel, and to sugge= st a way that hop-by-hop AQM would be effectively used in RTP congestion co= ntrol.

Kevin Gross
+1-303-447-0517
Media Network Consultant
AVA Networks - www.AVAnw.com, www.X192.org


On Tue, May 28, 2013 at 1:16 PM, Fred Baker (fre= d) <fred@cisco.com&= gt; wrote:

On May 28, 2013, at 11:40 AM, Kevin Gross <kevin.gross@avanw.com> wrote:
I don't know where you get the idea that codel drops packe= ts in bursts. It drops one packet per "interval". "Interval&= quot; starts at 100 ms and is reduced slowly (71, 58, 50, 45 ms...) until c= ongestion abates. Codel is effective on TCP flows because the loss happens promptly, not because the loss is substantial.

Codel is designed to be applied on a per-hop basis. I don't see how it= can be applied at a receiver for an end-to-end connection as you are appar= ently proposing and still behave as generally intended by its inventors.

I was scratching my head on that as well.

In context, you would do well to also consider P= IE:

http://tools.ietf.org/html/draft-pan-tsvwg-pie=
  "PIE: A Lightweight Control Scheme T= o Address the Bufferbloat Problem",
  Rong Pan, Preethi Natarajan, Chiara Pigli= one, Mythili Prabhu, 10-Dec-12

It has the same caveat, of being designed to operate hop by hop. CoDel= specifically talks about dropping, and Van will tell you he's not fond of = ECN, but IMHO it could be applied to ECN as well. The PIE draft explicitly = mentions ECN marking as a possibility. That would feed into

6679 Explicit Congestion Notification (ECN) for RTP over UDP. M.
     Westerlund, I. Johansson, C. Perkins, P. O'Hanlon,= K. Carlberg.
     August 2012. (Format: TXT=3D148560 bytes) (Status:= PROPOSED STANDARD)

In short, ECN is intended to trigger a TCP/SCTP sender to reduce its e= ffective window a bit. RFC 3168 says "do the same thing you would in t= he event of loss", which for loss-triggered TCPs (newReno, CUBIC) mean= s to either set it to some value (used to be one), multiply it by some fractional value (1/2, 7/8, or whatever), or = reset it to the last value that didn't result in such a trigger. I would ex= pect that in the RTP context it might insert some form of seder traffic sha= ping/pacing (if one presumes that a codec has certain mean and maximum rates, it might default to allowing t= he sender to send at its maximum rate, and might when told to reduce the ra= te in the direction of the mean - and if the mean is still too quick, ask t= he application to reduce its rate by changing codecs).


Kevin Gross
Media Network Consultant
AVA Networks - www.AVAnw.com, www.X192.org


On Sat, May 25, 2013 at 5:04 PM, Dan Weber <dan@marketsoup.= com> wrote:
Hi guys,

I've been reviewing CoDel, and it's clear how it works reasonably well for = TCP.  It's only slightly more complicated than an implementation using= a fixed timestamp per packet expiration.  The minor difference occurs= when it goes into its dropping state which uses a square root scaling factor for the time based on the number of prev= iously dropped packets in a sequence.  This takes advantage of a known= behavior of TCP congestion control algorithms which expect congestion to h= appen in large bursts.

When applied to RTP unknowingly, the behavior could be pretty disastrous on= video content.  Although I doubt it's any worse than actual competing= content with no AQM, a particular case does stand out.  When CoDel is= in place where there is no competing traffic and the RTP sender bursts the wire without pacing in respect to maximum st= ream bitrate, CoDel is likely to burst drop packets because of overflow on = the queue time.  I think this behavior is extremely desirable.  This will bring awarenes= s to all vendors and implementors that their implementations were working d= espite the fact that they were improper. 

This kind of behavior can be enhanced and augmented in a way that can be us= ed to expedite the implementation of effective RTP Congestion Control. = ;  If we were to implement receiver side CoDel for dropping "frames" or "mess= ages" of RTP packets on new implementations, we could become the &= quot;Soup Nazi" and start effectively identifying improper implementat= ions as well as rendering them inoperable.  If implemented by one of the major WebRTC browser implementations, a= chain reaction may develop that forces implementation of RTP congestion= control up the pipeline.  If useful feedback is delivered back to= the sender, which really needs to be net translated to frames processed and frames dropped, an applicati= on with its encoder could reasonably adjust.  This may solve fairness related problems because the receiver could iden= tify if the sender overflowed the queues by evaluating actual arrival time = compared with frame presentation time (converted RTP timestamps). = If the receiver enforces this constraint, fairness on RTP streams is effectively in force because implementations ar= e rendered inoperable, and it works safely within the scope of CoDel. = This implies that TCP would be only at most affected in the same way that = another TCP stream would. 

And finally this leads to my suggested solution for sender side congestion = control.  Based on my assumption that CoDel implementation for AQM is = on the horizon across routers in the next 5 to 10 years, a reasonable sugge= stion for RTP Congestion control may lead to CoDel over CoDel.  An enhanced version of CoDel for implement= ation in the RTP stack (or at the codec encapsulation layer) provides clear= frame demarcation and packet mapping (frame no =3D=3D packets n..m), and d= rops entire frames based on: an assumption (or determination) of targeted maximum bandwidth and (optional, but highly= recommended) some form of ECN.  Notifications are then provided back = to the application as to which frames were dropped, and the application can= make the decision on how it seeks to change its behavior if at all [This combines well with the receiver based = notification.  If it chooses not to, the RTP stack enforces "fair= ness" by degrading the application performance in full units.  A = good implementation of this should use FEC to maintain a constant bitrate despite the variations of the bit= rate in the underlying stream.  While it does use more bandwidth than immediately necessary it p= rovides great stability for the stream in cooperation with both long lived TCP streams and short lived bursty stre= ams.  It also prevents unfair competition from TCP.  In addition, it provi= des additional resiliency for handling intermittent packets loss from W= iFi and other wireless/cellular transmissions.

I think the benefits of this solution outweigh any other that has been prop= osed, and solves many of the difficult challenges presented.  While I = have not yet build a full working model, It should work in at least as many= places as CoDel works, and much research has been done and continues to be done on how well CoDel handles fairness.=

I would love to hear everyone's thoughts on this.  Please send me your= feedback.

Thanks,
Dan


  • Make things as simple as possible, but no= t simpler.
    Albert Einstein



--= ---------------------------------
"We are learning to do a great many clever things...The next great tas= k
will be to learn not to do them."

- G. K. Chesterton (1874-1936)




--_000_8C48B86A895913448548E6D15DA7553B8FB058xmbrcdx09ciscocom_-- From dan@marketsoup.com Tue May 28 14:58:40 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 8EE5711E80FA for ; Tue, 28 May 2013 14:58:40 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: 0.48 X-Spam-Level: X-Spam-Status: No, score=0.48 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, FH_RELAY_NODNS=1.451, FM_FORGED_GMAIL=0.622, HTML_MESSAGE=0.001, RCVD_IN_PBL=0.905, RDNS_NONE=0.1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id ebo91pDz+hjg for ; Tue, 28 May 2013 14:58:36 -0700 (PDT) Received: from mail-qa0-x235.google.com (mail-qa0-x235.google.com [IPv6:2607:f8b0:400d:c00::235]) by ietfa.amsl.com (Postfix) with ESMTP id 12A8221F8C03 for ; Tue, 28 May 2013 14:58:35 -0700 (PDT) Received: by mail-qa0-f53.google.com with SMTP id bs12so1813376qab.12 for ; Tue, 28 May 2013 14:58:35 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=marketsoup.com; s=google; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type; bh=XEPpQuLwDFfUIz89VUk3ZgSx7jZM9Guta6Lspg65pmc=; b=jCX/bKyOC22s2FRMAcaSXzIjqikIRW/afJWM9Bxy87i1hJvpGNmWOY+XqX7/DhSOPk PD6KDZXwwIsHl5VvIpf6W+zoyszANmyHiPaulYpCNZq3F2pE2j7bpSnRro3FcQOWyOOr DYhIQJLFLJZDBN8xwPbrgEQKaP/PE+KjI0rfk= X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type:x-gm-message-state; bh=XEPpQuLwDFfUIz89VUk3ZgSx7jZM9Guta6Lspg65pmc=; b=HytRO73CEB55g/oXgbwh8q2dsBb03KmHbsY7e/fBvblt7E0XIvZr1dKVlU0Fa7PX0o P5gqB2fcDrM52ZuvVX3FnQ22g213xsUh+D1zq+bg3YCvrHglSjZcbmxZQ1cTngp4Fgf2 ztfn2yBjplodBVhBukYYKOqBAGoHyvfGUsyIATsJpEiWIrXkxZo8ybE4JV6YS5lH5Fwl BMxWk64HCf+IuvI/zkacbKhbLmEVKutzlAcI+7qD+wpbXkhgwoREhObX4xMmrMIaKI9h 0TTIivEagLOImIRq5Wx05CONevnotDJLtvZWj7l/i8KmcELin6+XBF20g6vQlbF4IbmH IYSQ== MIME-Version: 1.0 X-Received: by 10.224.7.195 with SMTP id e3mr473598qae.5.1369778315133; Tue, 28 May 2013 14:58:35 -0700 (PDT) Received: by 10.224.209.66 with HTTP; Tue, 28 May 2013 14:58:35 -0700 (PDT) X-Originating-IP: [174.51.153.161] In-Reply-To: References: Date: Tue, 28 May 2013 15:58:35 -0600 Message-ID: From: Dan Weber To: Kevin Gross Content-Type: multipart/alternative; boundary=e89a8f923b36e515de04ddce5d82 X-Gm-Message-State: ALoCoQm7A/065tohbduP2EwxKOwMSoDdffBShLgRKVpddlqjop0XJvW2kU9GR3ixHA3UIe/GCUbH Cc: rmcat WG Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Tue, 28 May 2013 21:58:40 -0000 --e89a8f923b36e515de04ddce5d82 Content-Type: text/plain; charset=UTF-8 You're right. I made a mistake in my interpretation of this. I missed the part that the next drop is a solid step into the future. drop1 = t + 100, drop2 = drop1 + 100/sqrt(2), drop3 = drop2 + 100/sqrt(3) ... I'm scratching my head at the words I'm looking for with regard to fairness. Though I would say the following situation would be unfair utilization. The frame rate is 30fps. Which means net effect that media needs to be delivered every 33ms. Now let's say it sends the first (an I-Frame) out on to the wire which composes of 15 packets, the expected presentation time is 3000 (90Khz clock) or 0.03333 in relative [delay adjusted] absolute time. By the time the frame arrives completely, it's 18000 (90khz) or 0.2 [delay adjusted] absolute time. The next frame arrives has a time stamp of 6000, it composes of 6 packets, and arrives in total at 23000 (90khz) or 0.2555 absolute time. By the time third frame comes in (ts=9000), it's arrival time is 28000 (90khz) or 0.31111 absolute time. Isn't there some metric we can use to qualify this behavior? I was thinking the CoDel control law using some comparison between expected arrival time and actual arrival time, but I seem to have lost my thought. Sorry on the CoDel mistake, seemed so clear at the time... Thanks, Dan On Tue, May 28, 2013 at 12:40 PM, Kevin Gross wrote: > I don't know where you get the idea that codel drops packets in bursts. It > drops one packet per "interval". "Interval" starts at 100 ms and is reduced > slowly (71, 58, 50, 45 ms...) until congestion abates. Codel is effective > on TCP flows because the loss happens promptly, not because the loss is > substantial. > > Codel is designed to be applied on a per-hop basis. I don't see how it can > be applied at a receiver for an end-to-end connection as you are apparently > proposing and still behave as generally intended by its inventors. > > Kevin Gross > +1-303-447-0517 > Media Network Consultant > AVA Networks - www.AVAnw.com , www.X192.org > > > On Sat, May 25, 2013 at 5:04 PM, Dan Weber wrote: > >> Hi guys, >> >> I've been reviewing CoDel, and it's clear how it works reasonably well >> for TCP. It's only slightly more complicated than an implementation using >> a fixed timestamp per packet expiration. The minor difference occurs when >> it goes into its dropping state which uses a square root scaling factor for >> the time based on the number of previously dropped packets in a sequence. >> This takes advantage of a known behavior of TCP congestion control >> algorithms which expect congestion to happen in large bursts. >> >> When applied to RTP unknowingly, the behavior could be pretty disastrous >> on video content. Although I doubt it's any worse than actual competing >> content with no AQM, a particular case does stand out. When CoDel is in >> place where there is no competing traffic and the RTP sender bursts the >> wire without pacing in respect to maximum stream bitrate, CoDel is likely >> to burst drop packets because of overflow on the queue time. I think *this >> behavior is extremely desirable*. This will bring awareness to all >> vendors and implementors that their implementations were working despite >> the fact that they were improper. >> >> This kind of behavior can be enhanced and augmented in a way that can be >> used to expedite the implementation of effective RTP Congestion Control. >> If we were to implement *receiver side CoDel* *for dropping "frames" or >> "messages" of RTP packets on new implementations*, we could become the >> "Soup Nazi" and start effectively identifying improper implementations as >> well as rendering them inoperable. *If implemented by one of the major >> WebRTC browser implementations, *a *chain reaction may develop that >> forces implementation of RTP congestion control up the pipeline*. If >> useful feedback is delivered back to the sender, which really needs to be >> net translated to *frames processed and frames dropped*, an application >> with its encoder could reasonably adjust. *This may solve fairness >> related problems because the receiver could identify if the sender >> overflowed the queues by evaluating actual arrival time compared with frame >> presentation time (converted RTP timestamps).* If the receiver enforces >> this constraint, fairness on RTP streams is effectively in force because >> implementations are rendered inoperable, and it works safely within the >> scope of CoDel. This implies that TCP would be only at most affected in >> the same way that another TCP stream would. >> >> And finally this leads to my suggested solution for sender side >> congestion control. Based on my assumption that CoDel implementation for >> AQM is on the horizon across routers in the next 5 to 10 years, a >> reasonable suggestion for RTP Congestion control may lead to CoDel over >> CoDel. An enhanced version of CoDel for implementation in the RTP stack >> (or at the codec encapsulation layer) provides clear frame demarcation and >> packet mapping (frame no == packets n..m), and drops entire frames based >> on: an assumption (or determination) of targeted maximum bandwidth and >> (optional, but highly recommended) some form of ECN. Notifications are >> then provided back to the application as to which frames were dropped, and >> the application can make the decision on how it seeks to change its >> behavior if at all [This combines well with the receiver based >> notification. If it chooses not to, the RTP stack enforces "fairness" by >> degrading the application performance in full units. A good implementation >> of this should *use FEC to maintain a constant bitrate despite the >> variations of the bitrate in the underlying stream. *While it does use >> more bandwidth than *immediately necessary* it provides great stability >> for the stream in *cooperation with both long lived TCP streams and >> short lived bursty streams*. It also *prevents unfair competition from >> TCP*. In addition, it *provides additional resiliency for handling >> intermittent packets loss* from WiFi and other wireless/cellular >> transmissions. >> >> I think the benefits of this solution outweigh any other that has been >> proposed, and solves many of the difficult challenges presented. While I >> have not yet build a full working model, It should work in at least as many >> places as CoDel works, and much research has been done and continues to be >> done on how well CoDel handles fairness. >> >> I would love to hear everyone's thoughts on this. Please send me your >> feedback. >> >> Thanks, >> Dan >> > > --e89a8f923b36e515de04ddce5d82 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
You're right. I made a mistake in my interpretation of this. =C2= =A0I missed the part that the next drop is a solid step into the future. = =C2=A0 drop1 =3D t + 100, drop2 =3D drop1 + 100/sqrt(2), drop3 =3D drop2 + = 100/sqrt(3) ...

I'm scratching my head at the words I'm looking= for with regard to fairness. =C2=A0Though I would say the following situat= ion would be unfair utilization.

The frame rate is= 30fps. =C2=A0Which means net effect that media needs to be delivered every= 33ms. =C2=A0Now let's say it sends the first (an I-Frame) out on to th= e wire which composes of 15 packets, the expected presentation time is 3000= (90Khz clock) or 0.03333 in relative [delay adjusted] absolute time. =C2= =A0By the time the frame arrives completely, it's 18000 (90khz) or 0.2 = [delay adjusted] absolute time. =C2=A0The next frame arrives has a time sta= mp of 6000, it composes of 6 packets, and arrives in total at 23000 (90khz)= or 0.2555 absolute time. =C2=A0By the time third frame comes in (ts=3D9000= ), it's arrival time is 28000 (90khz) or 0.31111 absolute time.

Isn't there some metric we can use to qualify this = behavior? =C2=A0I was thinking the CoDel control law using some comparison = between expected arrival time and actual arrival time, but I seem to have l= ost my thought.

Sorry on the CoDel mistake, seemed so clear at the time= ...

Thanks,
Dan




On Tue, May 28, 20= 13 at 12:40 PM, Kevin Gross <kevin.gross@avanw.com> wrot= e:
I don't know where you = get the idea that codel drops packets in bursts. It drops one packet per &q= uot;interval". "Interval" starts at 100 ms and is reduced sl= owly (71, 58, 50, 45 ms...) until congestion abates. Codel is effective on = TCP flows because the loss happens promptly, not because the loss is substa= ntial.

Codel is designed to be applied on a per-hop basis. I don= 't see how it can be applied at a receiver for an end-to-end connection= as you are apparently proposing and still behave as generally intended by = its inventors.

Kevin Gross
Media Network Consultant
AVA Networks -=C2=A0www.AVAnw.com,=C2=A0www.X192.org


On Sat, May 25, 2013 at 5:04 PM, Dan Web= er <dan@marketsoup.com> wrote:
Hi guys,

I've been reviewing CoDel, and it's clear how it wo= rks reasonably well for TCP.=C2=A0 It's only slightly more complicated = than an implementation using a fixed timestamp per packet expiration.=C2=A0= The minor difference occurs when it goes into its dropping state which use= s a square root scaling factor for the time based on the number of previous= ly dropped packets in a sequence.=C2=A0 This takes advantage of a known beh= avior of TCP congestion control algorithms which expect congestion to happe= n in large bursts.

When applied to RTP unknowingly, the behavior could be pretty disastrou= s on video content.=C2=A0 Although I doubt it's any worse than actual c= ompeting content with no AQM, a particular case does stand out.=C2=A0 When = CoDel is in place where there is no competing traffic and the RTP sender bu= rsts the wire without pacing in respect to maximum stream bitrate, CoDel is= likely to burst drop packets because of overflow on the queue time.=C2=A0 = I think this behavior is extremely desirable.=C2=A0 This will bring = awareness to all vendors and implementors that their implementations were w= orking despite the fact that they were improper.=C2=A0

This kind of behavior can be enhanced and augmented in a way that can b= e used to expedite the implementation of effective RTP Congestion Control.= =C2=A0=C2=A0 If we were to implement receiver side CoDel for drop= ping "frames" or "messages" of RTP packets on new imple= mentations, we could become the "Soup Nazi" and start effecti= vely identifying improper implementations as well as rendering them inopera= ble.=C2=A0 If implemented by one of the major WebRTC browser implementat= ions, a chain reaction may develop that forces implementation of RTP= congestion control up the pipeline.=C2=A0 If useful feedback is delive= red back to the sender, which really needs to be net translated to frame= s processed and frames dropped, an application with its encoder could r= easonably adjust.=C2=A0 This may solve fairness related problems because= the receiver could identify if the sender overflowed the queues by evaluat= ing actual arrival time compared with frame presentation time (converted RT= P timestamps).=C2=A0 If the receiver enforces this constraint, fairness= on RTP streams is effectively in force because implementations are rendere= d inoperable, and it works safely within the scope of CoDel.=C2=A0 This imp= lies that TCP would be only at most affected in the same way that another T= CP stream would.=C2=A0

And finally this leads to my suggested solution for sender side congest= ion control.=C2=A0 Based on my assumption that CoDel implementation for AQM= is on the horizon across routers in the next 5 to 10 years, a reasonable s= uggestion for RTP Congestion control may lead to CoDel over CoDel.=C2=A0 An= enhanced version of CoDel for implementation in the RTP stack (or at the c= odec encapsulation layer) provides clear frame demarcation and packet mappi= ng (frame no =3D=3D packets n..m), and drops entire frames based on: an ass= umption (or determination) of targeted maximum bandwidth and (optional, but= highly recommended) some form of ECN.=C2=A0 Notifications are then provide= d back to the application as to which frames were dropped, and the applicat= ion can make the decision on how it seeks to change its behavior if at all = [This combines well with the receiver based notification.=C2=A0 If it choos= es not to, the RTP stack enforces "fairness" by degrading the app= lication performance in full units.=C2=A0 A good implementation of this sho= uld use FEC to maintain a constant bitrate despite the variations of the= bitrate in the underlying stream.=C2=A0 While it does use more bandwid= th than immediately necessary it provides great stability for the st= ream in cooperation with both long lived TCP streams and short lived bur= sty streams.=C2=A0 It also prevents unfair competition from TCP.= =C2=A0 In addition, it provides additional resiliency for handling inter= mittent packets loss from WiFi and other wireless/cellular transmission= s.

I think the benefits of this solution outweigh any other that has been = proposed, and solves many of the difficult challenges presented.=C2=A0 Whil= e I have not yet build a full working model, It should work in at least as = many places as CoDel works, and much research has been done and continues t= o be done on how well CoDel handles fairness.

I would love to hear everyone's thoughts on this.=C2=A0 Please send= me your feedback.

Thanks,
Dan


--e89a8f923b36e515de04ddce5d82-- From dan@marketsoup.com Tue May 28 15:15:50 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 8B4B611E80FA for ; Tue, 28 May 2013 15:15:50 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: 0.48 X-Spam-Level: X-Spam-Status: No, score=0.48 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, FH_RELAY_NODNS=1.451, FM_FORGED_GMAIL=0.622, HTML_MESSAGE=0.001, RCVD_IN_PBL=0.905, RDNS_NONE=0.1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id aO0CaVV43l61 for ; Tue, 28 May 2013 15:15:46 -0700 (PDT) Received: from mail-qa0-x230.google.com (mail-qa0-x230.google.com [IPv6:2607:f8b0:400d:c00::230]) by ietfa.amsl.com (Postfix) with ESMTP id 7C3EC21F901F for ; Tue, 28 May 2013 15:15:46 -0700 (PDT) Received: by mail-qa0-f48.google.com with SMTP id o13so1818209qaj.14 for ; Tue, 28 May 2013 15:15:45 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=marketsoup.com; s=google; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type; bh=S6tDLQaWB4Vs46fZND7crj6wDHaiO7kKvy5XF++WGLY=; b=e8zX0968d8kmMxz6etIWCbnXVOksnpPoVpFLbZUWj6eY611KUpiDOJijTb1jTqZ4+j NgNdVcbiUcbPJsDMDCaB7Aqze6EnfTeiGWj66Tpd9OwnfyZrbaKUvPQLYdq7+C3aZ3kO QXX3V0UJJu2vDvFfANA6nS0Vq0giWrhgjY3rA= X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type:x-gm-message-state; bh=S6tDLQaWB4Vs46fZND7crj6wDHaiO7kKvy5XF++WGLY=; b=PFAQopgYlIlZAdtcoFunW1mcKsvDGry31EB8p2iCsXKDX6o2iLXAQZE+r02rqcJowW A1+suwoyYtQtIHpkP5Ev856UGnswNhbwE2vIWy12tLtxuYJgswZLmXSIgQ9OrPD1raIk fasMIbOm8dQEyL3qaY/t2UOpoanAYlN4KjyiDyeRjaowPpiRtiYXl1tG9RpqMc5yFN6h 06bH7S9BQ39hSBCSmj1JHHezBSLCVd7vgjwcBfx0JeYdfoNWKzpZwrP+Kb+mPb68Xl5y vWw6eLi2OPvKhss16IiWE+4Jn95qtNAmKeBehs706h99QDCu8sfmcnashST+nunpCB92 0TJQ== MIME-Version: 1.0 X-Received: by 10.224.78.69 with SMTP id j5mr527562qak.0.1369779345787; Tue, 28 May 2013 15:15:45 -0700 (PDT) Received: by 10.224.209.66 with HTTP; Tue, 28 May 2013 15:15:45 -0700 (PDT) X-Originating-IP: [174.51.153.161] In-Reply-To: <8C48B86A895913448548E6D15DA7553B8FB058@xmb-rcd-x09.cisco.com> References: <8C48B86A895913448548E6D15DA7553B8FADD8@xmb-rcd-x09.cisco.com> <8C48B86A895913448548E6D15DA7553B8FB058@xmb-rcd-x09.cisco.com> Date: Tue, 28 May 2013 16:15:45 -0600 Message-ID: From: Dan Weber To: "Fred Baker (fred)" Content-Type: multipart/alternative; boundary=20cf3074b246539e0704ddce9b4a X-Gm-Message-State: ALoCoQkUATycPad7A3DCG1yrUYOiwmUoN4xzypbAYz4n9Wbs1Te0iTYC9Uvpm0Pr+ptodH9Ro+gH Cc: rmcat WG , Kevin Gross Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Tue, 28 May 2013 22:15:50 -0000 --20cf3074b246539e0704ddce9b4a Content-Type: text/plain; charset=UTF-8 I think the behavior is right if the RTP congestion control mechanism drops the entire frame and notifies the application it wouldn't be delivered within the appropriate time frame. The mechanism by which it determines this is still open for discussion. I particularly liked the thought that if any one packet of the frame would have to wait in the user space RTP packet queue (i.e. while pacing) for sending and exceeded a certain threshold (e.g. 100ms scaled down), then the entire frame should be dropped. This could potentially give enough benefit to the application encoder to be notified that those N successive pictures weren't usable as references in addition to the fact that the frames were never sent. The encoder could update the state for the next available encoded frame leaving a better user experience. Dan On Tue, May 28, 2013 at 2:56 PM, Fred Baker (fred) wrote: > > On May 28, 2013, at 12:49 PM, Kevin Gross wrote: > > We should definitely keep AQM (including ECN) in mind in this work but I > don't think this is the right place to have a PIE vs CoDel discussion. > > > I didn't intend to introduce a "vs"; my point, if anything, is to not > limit one's thinking to CoDel, and to suggest a way that hop-by-hop AQM > would be effectively used in RTP congestion control. > > Kevin Gross > +1-303-447-0517 > Media Network Consultant > AVA Networks - www.AVAnw.com , www.X192.org > > > On Tue, May 28, 2013 at 1:16 PM, Fred Baker (fred) wrote: > >> >> On May 28, 2013, at 11:40 AM, Kevin Gross wrote: >> >> I don't know where you get the idea that codel drops packets in bursts. >> It drops one packet per "interval". "Interval" starts at 100 ms and is >> reduced slowly (71, 58, 50, 45 ms...) until congestion abates. Codel is >> effective on TCP flows because the loss happens promptly, not because the >> loss is substantial. >> >> Codel is designed to be applied on a per-hop basis. I don't see how it >> can be applied at a receiver for an end-to-end connection as you are >> apparently proposing and still behave as generally intended by its >> inventors. >> >> >> I was scratching my head on that as well. >> >> In context, you would do well to also consider PIE: >> >> http://tools.ietf.org/html/draft-pan-tsvwg-pie >> "PIE: A Lightweight Control Scheme To Address the Bufferbloat Problem", >> Rong Pan, Preethi Natarajan, Chiara Piglione, Mythili Prabhu, 10-Dec-12 >> >> It has the same caveat, of being designed to operate hop by hop. CoDel >> specifically talks about dropping, and Van will tell you he's not fond of >> ECN, but IMHO it could be applied to ECN as well. The PIE draft explicitly >> mentions ECN marking as a possibility. That would feed into >> >> https://tools.ietf.org/html/rfc6679 >> 6679 Explicit Congestion Notification (ECN) for RTP over UDP. M. >> Westerlund, I. Johansson, C. Perkins, P. O'Hanlon, K. Carlberg. >> August 2012. (Format: TXT=148560 bytes) (Status: PROPOSED STANDARD) >> >> In short, ECN is intended to trigger a TCP/SCTP sender to reduce its >> effective window a bit. RFC 3168 says "do the same thing you would in the >> event of loss", which for loss-triggered TCPs (newReno, CUBIC) means to >> either set it to some value (used to be one), multiply it by some >> fractional value (1/2, 7/8, or whatever), or reset it to the last value >> that didn't result in such a trigger. I would expect that in the RTP >> context it might insert some form of seder traffic shaping/pacing (if one >> presumes that a codec has certain mean and maximum rates, it might default >> to allowing the sender to send at its maximum rate, and might when told to >> reduce the rate in the direction of the mean - and if the mean is still too >> quick, ask the application to reduce its rate by changing codecs). >> >> >> Kevin Gross >> +1-303-447-0517 >> Media Network Consultant >> AVA Networks - www.AVAnw.com , www.X192.org >> >> >> On Sat, May 25, 2013 at 5:04 PM, Dan Weber wrote: >> >>> Hi guys, >>> >>> I've been reviewing CoDel, and it's clear how it works reasonably well >>> for TCP. It's only slightly more complicated than an implementation using >>> a fixed timestamp per packet expiration. The minor difference occurs when >>> it goes into its dropping state which uses a square root scaling factor for >>> the time based on the number of previously dropped packets in a sequence. >>> This takes advantage of a known behavior of TCP congestion control >>> algorithms which expect congestion to happen in large bursts. >>> >>> When applied to RTP unknowingly, the behavior could be pretty disastrous >>> on video content. Although I doubt it's any worse than actual competing >>> content with no AQM, a particular case does stand out. When CoDel is in >>> place where there is no competing traffic and the RTP sender bursts the >>> wire without pacing in respect to maximum stream bitrate, CoDel is likely >>> to burst drop packets because of overflow on the queue time. I think *this >>> behavior is extremely desirable*. This will bring awareness to all >>> vendors and implementors that their implementations were working despite >>> the fact that they were improper. >>> >>> This kind of behavior can be enhanced and augmented in a way that can be >>> used to expedite the implementation of effective RTP Congestion Control. >>> If we were to implement *receiver side CoDel* *for dropping "frames" or >>> "messages" of RTP packets on new implementations*, we could become the >>> "Soup Nazi" and start effectively identifying improper implementations as >>> well as rendering them inoperable. *If implemented by one of the major >>> WebRTC browser implementations, *a *chain reaction may develop that >>> forces implementation of RTP congestion control up the pipeline*. If >>> useful feedback is delivered back to the sender, which really needs to be >>> net translated to *frames processed and frames dropped*, an application >>> with its encoder could reasonably adjust. *This may solve fairness >>> related problems because the receiver could identify if the sender >>> overflowed the queues by evaluating actual arrival time compared with frame >>> presentation time (converted RTP timestamps).* If the receiver >>> enforces this constraint, fairness on RTP streams is effectively in force >>> because implementations are rendered inoperable, and it works safely within >>> the scope of CoDel. This implies that TCP would be only at most affected >>> in the same way that another TCP stream would. >>> >>> And finally this leads to my suggested solution for sender side >>> congestion control. Based on my assumption that CoDel implementation for >>> AQM is on the horizon across routers in the next 5 to 10 years, a >>> reasonable suggestion for RTP Congestion control may lead to CoDel over >>> CoDel. An enhanced version of CoDel for implementation in the RTP stack >>> (or at the codec encapsulation layer) provides clear frame demarcation and >>> packet mapping (frame no == packets n..m), and drops entire frames based >>> on: an assumption (or determination) of targeted maximum bandwidth and >>> (optional, but highly recommended) some form of ECN. Notifications are >>> then provided back to the application as to which frames were dropped, and >>> the application can make the decision on how it seeks to change its >>> behavior if at all [This combines well with the receiver based >>> notification. If it chooses not to, the RTP stack enforces "fairness" by >>> degrading the application performance in full units. A good implementation >>> of this should *use FEC to maintain a constant bitrate despite the >>> variations of the bitrate in the underlying stream. *While it does use >>> more bandwidth than *immediately necessary* it provides great stability >>> for the stream in *cooperation with both long lived TCP streams and >>> short lived bursty streams*. It also *prevents unfair competition from >>> TCP*. In addition, it *provides additional resiliency for handling >>> intermittent packets loss* from WiFi and other wireless/cellular >>> transmissions. >>> >>> I think the benefits of this solution outweigh any other that has been >>> proposed, and solves many of the difficult challenges presented. While I >>> have not yet build a full working model, It should work in at least as many >>> places as CoDel works, and much research has been done and continues to be >>> done on how well CoDel handles fairness. >>> >>> I would love to hear everyone's thoughts on this. Please send me your >>> feedback. >>> >>> Thanks, >>> Dan >>> >> >> >> >> - Make things as simple as possible, but not simpler. >> Albert Einstein >> >> >> > > ----------------------------------- > "We are learning to do a great many clever things...The next great task > will be to learn not to do them." > > - G. K. Chesterton (1874-1936) > > > > > --20cf3074b246539e0704ddce9b4a Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable I think the behavior is right if the RTP congestion control mechanism drops= the entire frame and notifies the application it wouldn't be delivered= within the appropriate time frame. =C2=A0The mechanism by which it determi= nes this is still open for discussion. =C2=A0I particularly liked the thoug= ht that if any one packet of the frame would have to wait in the user space= RTP packet queue (i.e. while pacing) for sending and exceeded a certain th= reshold (e.g. 100ms scaled down), then the entire frame should be dropped. = =C2=A0This could potentially give enough benefit to the application encoder= to be notified that those N successive pictures weren't usable as refe= rences in addition to the fact that the frames were never sent. =C2=A0The e= ncoder could update the state for the next available encoded frame leaving = a better user experience.

Dan

On Tue, May 28, 2013 a= t 2:56 PM, Fred Baker (fred) <fred@cisco.com> wrote:

On May 28, 2013, at 12:49 PM, Kevin Gross <kevin.gross@avanw.com> wrote:
We should definitely keep AQM (including ECN) in mind in t= his work but I don't think this is the right place to have a PIE vs CoD= el discussion.

I didn't intend to introduce a "v= s"; my point, if anything, is to not limit one's thinking to CoDel= , and to suggest a way that hop-by-hop AQM would be effectively used in RTP= congestion control.

Kevin Gross
Media Network Consultant
AVA Networks -=C2=A0www.AVAnw.com,=C2=A0www.X192.org


On Tue, May 28, 2013 at 1:16 PM, Fred Baker (fre= d) <fred@cisco.com&= gt; wrote:

On May 28, 2013, at 11:40 AM, Kevin Gross <kevin.gross@avanw.com> wrote:
I don't know where you get the idea that codel drops p= ackets in bursts. It drops one packet per "interval". "Inter= val" starts at 100 ms and is reduced slowly (71, 58, 50, 45 ms...) unt= il congestion abates. Codel is effective on TCP flows because the loss happens promptly, not because the loss is substantial.

Codel is designed to be applied on a per-hop basis. I don't see ho= w it can be applied at a receiver for an end-to-end connection as you are a= pparently proposing and still behave as generally intended by its inventors= .

I was scratching my head on that as well.

In context, you would do well to also consider P= IE:

http://tools.ietf.org/html/draft-pan-tsvwg-pie=
=C2=A0 "PIE: A Lightweight Control Scheme T= o Address the Bufferbloat Problem",
=C2=A0 Rong Pan, Preethi Natarajan, Chiara Pigli= one, Mythili Prabhu, 10-Dec-12

It has the same caveat, of being designed to operate hop by hop. CoDel= specifically talks about dropping, and Van will tell you he's not fond= of ECN, but IMHO it could be applied to ECN as well. The PIE draft explici= tly mentions ECN marking as a possibility. That would feed into

6679 Explicit Congestion Notification (ECN) for RTP over UDP. M.
=C2=A0 =C2=A0 =C2=A0Westerlund, I. Johansson, C. Perkins, P. O'Han= lon, K. Carlberg.
=C2=A0 =C2=A0 =C2=A0August 2012. (Format: TXT=3D148560 bytes) (Status:= PROPOSED STANDARD)

In short, ECN is intended to trigger a TCP/SCTP sender to reduce its e= ffective window a bit. RFC 3168 says "do the same thing you would in t= he event of loss", which for loss-triggered TCPs (newReno, CUBIC) mean= s to either set it to some value (used to be one), multiply it by some fractional value (1/2, 7/8, or whatever), or = reset it to the last value that didn't result in such a trigger. I woul= d expect that in the RTP context it might insert some form of seder traffic= shaping/pacing (if one presumes that a codec has certain mean and maximum rates, it might default to allowing t= he sender to send at its maximum rate, and might when told to reduce the ra= te in the direction of the mean - and if the mean is still too quick, ask t= he application to reduce its rate by changing codecs).


Kevin Gross
Media Network Consultant
AVA Networks -=C2=A0www.AVAnw.com,=C2=A0www.X192.org


On Sat, May 25, 2013 at 5:04 PM, Dan Weber <dan@marketsoup.= com> wrote:
Hi guys,

I've been reviewing CoDel, and it's clear how it works reasonably w= ell for TCP.=C2=A0 It's only slightly more complicated than an implemen= tation using a fixed timestamp per packet expiration.=C2=A0 The minor diffe= rence occurs when it goes into its dropping state which uses a square root scaling factor for the time based on the number of prev= iously dropped packets in a sequence.=C2=A0 This takes advantage of a known= behavior of TCP congestion control algorithms which expect congestion to h= appen in large bursts.

When applied to RTP unknowingly, the behavior could be pretty disastrous on= video content.=C2=A0 Although I doubt it's any worse than actual compe= ting content with no AQM, a particular case does stand out.=C2=A0 When CoDe= l is in place where there is no competing traffic and the RTP sender bursts the wire without pacing in respect to maximum st= ream bitrate, CoDel is likely to burst drop packets because of overflow on = the queue time.=C2=A0 I think this behavior is extremely desirable.=C2=A0 This will bring awarenes= s to all vendors and implementors that their implementations were working d= espite the fact that they were improper.=C2=A0

This kind of behavior can be enhanced and augmented in a way that can be us= ed to expedite the implementation of effective RTP Congestion Control.=C2= =A0=C2=A0 If we were to implement receiver side CoDel for dropping "frames" or "mess= ages" of RTP packets on new implementations, we could become the &= quot;Soup Nazi" and start effectively identifying improper implementat= ions as well as rendering them inoperable.=C2=A0 If implemented by one of the major WebRTC browser implementations, a= chain reaction may develop that forces implementation of RTP congestion= control up the pipeline.=C2=A0 If useful feedback is delivered back to= the sender, which really needs to be net translated to frames processed and frames dropped, an applicati= on with its encoder could reasonably adjust.=C2=A0 This may solve fairness related problems because the receiver could iden= tify if the sender overflowed the queues by evaluating actual arrival time = compared with frame presentation time (converted RTP timestamps).=C2=A0= If the receiver enforces this constraint, fairness on RTP streams is effectively in force because implementations ar= e rendered inoperable, and it works safely within the scope of CoDel.=C2=A0= This implies that TCP would be only at most affected in the same way that = another TCP stream would.=C2=A0

And finally this leads to my suggested solution for sender side congestion = control.=C2=A0 Based on my assumption that CoDel implementation for AQM is = on the horizon across routers in the next 5 to 10 years, a reasonable sugge= stion for RTP Congestion control may lead to CoDel over CoDel.=C2=A0 An enhanced version of CoDel for implement= ation in the RTP stack (or at the codec encapsulation layer) provides clear= frame demarcation and packet mapping (frame no =3D=3D packets n..m), and d= rops entire frames based on: an assumption (or determination) of targeted maximum bandwidth and (optional, but highly= recommended) some form of ECN.=C2=A0 Notifications are then provided back = to the application as to which frames were dropped, and the application can= make the decision on how it seeks to change its behavior if at all [This combines well with the receiver based = notification.=C2=A0 If it chooses not to, the RTP stack enforces "fair= ness" by degrading the application performance in full units.=C2=A0 A = good implementation of this should use FEC to maintain a constant bitrate despite the variations of the bit= rate in the underlying stream.=C2=A0 While it does use more bandwidth than immediately necessary it p= rovides great stability for the stream in cooperation with both long lived TCP streams and short lived bursty stre= ams.=C2=A0 It also prevents unfair competition from TCP.=C2=A0 In addition, it provi= des additional resiliency for handling intermittent packets loss from W= iFi and other wireless/cellular transmissions.

I think the benefits of this solution outweigh any other that has been prop= osed, and solves many of the difficult challenges presented.=C2=A0 While I = have not yet build a full working model, It should work in at least as many= places as CoDel works, and much research has been done and continues to be done on how well CoDel handles fairness.=

I would love to hear everyone's thoughts on this.=C2=A0 Please send me = your feedback.

Thanks,
Dan


  • Make things as simple as possible, but no= t simpler.
    Albert Einstein



--------------------------------= ---
"We are learning to do a great many clever things...The next great tas= k
will be to learn not to do them."

- G. K. Chesterton (1874-1936)





--20cf3074b246539e0704ddce9b4a-- From kevin.gross@avanw.com Tue May 28 16:05:43 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 2327521F9128 for ; Tue, 28 May 2013 16:05:43 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: 0.486 X-Spam-Level: X-Spam-Status: No, score=0.486 tagged_above=-999 required=5 tests=[AWL=0.300, BAYES_00=-2.599, FH_RELAY_NODNS=1.451, FM_FORGED_GMAIL=0.622, HELO_MISMATCH_NET=0.611, HTML_MESSAGE=0.001, RDNS_NONE=0.1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id arkZ13iFi2ef for ; Tue, 28 May 2013 16:05:39 -0700 (PDT) Received: from qmta14.emeryville.ca.mail.comcast.net (qmta14.emeryville.ca.mail.comcast.net [IPv6:2001:558:fe2d:44:76:96:27:212]) by ietfa.amsl.com (Postfix) with ESMTP id E7D3C21F9123 for ; Tue, 28 May 2013 16:05:38 -0700 (PDT) Received: from omta16.emeryville.ca.mail.comcast.net ([76.96.30.72]) by qmta14.emeryville.ca.mail.comcast.net with comcast id hUb01l0051ZMdJ4AEb5ecm; Tue, 28 May 2013 23:05:38 +0000 Received: from mail-ie0-x236.google.com ([IPv6:2607:f8b0:4001:c03::236]) by omta16.emeryville.ca.mail.comcast.net with comcast id hb5d1l00a251pGM8cb5eTZ; Tue, 28 May 2013 23:05:38 +0000 Received: by mail-ie0-f182.google.com with SMTP id a14so23295043iee.27 for ; Tue, 28 May 2013 16:05:37 -0700 (PDT) X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:in-reply-to:references:date:message-id:subject:from:to :cc:content-type; bh=8CyLBHNI1profgjT8gVRRn9zNcGjbawgdPrSjH81GR4=; b=FbuNo9dpygA14NQXqds/5VitiCwoqOM6l4SjgNR7W5mUVcT9u707TOQpGQxxrS9pZN gMKNxmfZbcWTQkl8TTWsPNuoD5ezSayoiStKkweU7OcFJD6rfe0Xl//GZTIz6ix1XpOI jkX+SQcDG5TnuCOzw/HV6d+3v3cqZ0sJZE3DSuB13VW8uKXhSLx2wNnPLhgxQEBx0d65 I90qOVsMI+W2DeN6mu4TxJzJX7+VSABiBrOUptzJ9bkc9I+gcY1P3mBh9O+KHKwpNd/j 6pBKBeMl9KVswkrV9PIJEf6bHBLJYjgrx9kICYnCbd8iZiwA8V7SQG1Tr3cC9p3pWgqa w3/A== MIME-Version: 1.0 X-Received: by 10.50.126.1 with SMTP id mu1mr8240764igb.5.1369782337600; Tue, 28 May 2013 16:05:37 -0700 (PDT) Received: by 10.50.65.69 with HTTP; Tue, 28 May 2013 16:05:37 -0700 (PDT) In-Reply-To: References: Date: Tue, 28 May 2013 17:05:37 -0600 Message-ID: From: Kevin Gross To: Dan Weber Content-Type: multipart/alternative; boundary=047d7b1637b7a705dc04ddcf4dc6 DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=comcast.net; s=q20121106; t=1369782338; bh=8CyLBHNI1profgjT8gVRRn9zNcGjbawgdPrSjH81GR4=; h=Received:Received:Received:MIME-Version:Received:Date:Message-ID: Subject:From:To:Content-Type; b=EHTSMEmq5+6xNfzdfrmOODmHZv/6dsz7fP/e9L58CwWaVggtLTknBXGy+awAPKM5L mO8JcpIqNgywk/aK7ze9rTLWfzDm8IGWhRnxEFv9g9YLkEvjGPWb6a08kDtp1HNKl9 iopQa37xfC9AogWkq4aNG4iAnnc38r/riZlq/D1A672vsF3R9yxTYMjHTnM7BrQijN 1p9O+PSPiggeTEJlX0T7tgYRIiN97pd6NkVnyHiGsFAvywD5ZlTJ1rJs1uAnenP+nU GPdjskjNY+c11qtypnRafTir67c5pwGLEq4yBGmVoyYeGp7aDj0vc/WuxwUT13Qo59 cc2T52EJMQ55A== Cc: rmcat WG Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Tue, 28 May 2013 23:05:43 -0000 --047d7b1637b7a705dc04ddcf4dc6 Content-Type: text/plain; charset=ISO-8859-1 Looks like an oversubscribed link with bufferbloat. We've discussed detecting/addressing this with a *delay-based* approach. CoDel and PIE are delay-based. Maybe that's the thread you lost? The other class of congestion control (e.g. TCP) is *loss-based* which wouldn't work here (wouldn't start working until it was way too late). Kevin Gross +1-303-447-0517 Media Network Consultant AVA Networks - www.AVAnw.com , www.X192.org On Tue, May 28, 2013 at 3:58 PM, Dan Weber wrote: > You're right. I made a mistake in my interpretation of this. I missed the > part that the next drop is a solid step into the future. drop1 = t + 100, > drop2 = drop1 + 100/sqrt(2), drop3 = drop2 + 100/sqrt(3) ... > > I'm scratching my head at the words I'm looking for with regard to > fairness. Though I would say the following situation would be unfair > utilization. > > The frame rate is 30fps. Which means net effect that media needs to be > delivered every 33ms. Now let's say it sends the first (an I-Frame) out on > to the wire which composes of 15 packets, the expected presentation time is > 3000 (90Khz clock) or 0.03333 in relative [delay adjusted] absolute time. > By the time the frame arrives completely, it's 18000 (90khz) or 0.2 [delay > adjusted] absolute time. The next frame arrives has a time stamp of 6000, > it composes of 6 packets, and arrives in total at 23000 (90khz) or 0.2555 > absolute time. By the time third frame comes in (ts=9000), it's arrival > time is 28000 (90khz) or 0.31111 absolute time. > > Isn't there some metric we can use to qualify this behavior? I was > thinking the CoDel control law using some comparison between expected > arrival time and actual arrival time, but I seem to have lost my thought. > > Sorry on the CoDel mistake, seemed so clear at the time... > > Thanks, > Dan > > > > > On Tue, May 28, 2013 at 12:40 PM, Kevin Gross wrote: > >> I don't know where you get the idea that codel drops packets in bursts. >> It drops one packet per "interval". "Interval" starts at 100 ms and is >> reduced slowly (71, 58, 50, 45 ms...) until congestion abates. Codel is >> effective on TCP flows because the loss happens promptly, not because the >> loss is substantial. >> >> Codel is designed to be applied on a per-hop basis. I don't see how it >> can be applied at a receiver for an end-to-end connection as you are >> apparently proposing and still behave as generally intended by its >> inventors. >> > >> Kevin Gross >> +1-303-447-0517 >> Media Network Consultant >> AVA Networks - www.AVAnw.com , www.X192.org >> >> >> On Sat, May 25, 2013 at 5:04 PM, Dan Weber wrote: >> >>> Hi guys, >>> >>> I've been reviewing CoDel, and it's clear how it works reasonably well >>> for TCP. It's only slightly more complicated than an implementation using >>> a fixed timestamp per packet expiration. The minor difference occurs when >>> it goes into its dropping state which uses a square root scaling factor for >>> the time based on the number of previously dropped packets in a sequence. >>> This takes advantage of a known behavior of TCP congestion control >>> algorithms which expect congestion to happen in large bursts. >>> >>> When applied to RTP unknowingly, the behavior could be pretty disastrous >>> on video content. Although I doubt it's any worse than actual competing >>> content with no AQM, a particular case does stand out. When CoDel is in >>> place where there is no competing traffic and the RTP sender bursts the >>> wire without pacing in respect to maximum stream bitrate, CoDel is likely >>> to burst drop packets because of overflow on the queue time. I think *this >>> behavior is extremely desirable*. This will bring awareness to all >>> vendors and implementors that their implementations were working despite >>> the fact that they were improper. >>> >>> This kind of behavior can be enhanced and augmented in a way that can be >>> used to expedite the implementation of effective RTP Congestion Control. >>> If we were to implement *receiver side CoDel* *for dropping "frames" or >>> "messages" of RTP packets on new implementations*, we could become the >>> "Soup Nazi" and start effectively identifying improper implementations as >>> well as rendering them inoperable. *If implemented by one of the major >>> WebRTC browser implementations, *a *chain reaction may develop that >>> forces implementation of RTP congestion control up the pipeline*. If >>> useful feedback is delivered back to the sender, which really needs to be >>> net translated to *frames processed and frames dropped*, an application >>> with its encoder could reasonably adjust. *This may solve fairness >>> related problems because the receiver could identify if the sender >>> overflowed the queues by evaluating actual arrival time compared with frame >>> presentation time (converted RTP timestamps).* If the receiver >>> enforces this constraint, fairness on RTP streams is effectively in force >>> because implementations are rendered inoperable, and it works safely within >>> the scope of CoDel. This implies that TCP would be only at most affected >>> in the same way that another TCP stream would. >>> >>> And finally this leads to my suggested solution for sender side >>> congestion control. Based on my assumption that CoDel implementation for >>> AQM is on the horizon across routers in the next 5 to 10 years, a >>> reasonable suggestion for RTP Congestion control may lead to CoDel over >>> CoDel. An enhanced version of CoDel for implementation in the RTP stack >>> (or at the codec encapsulation layer) provides clear frame demarcation and >>> packet mapping (frame no == packets n..m), and drops entire frames based >>> on: an assumption (or determination) of targeted maximum bandwidth and >>> (optional, but highly recommended) some form of ECN. Notifications are >>> then provided back to the application as to which frames were dropped, and >>> the application can make the decision on how it seeks to change its >>> behavior if at all [This combines well with the receiver based >>> notification. If it chooses not to, the RTP stack enforces "fairness" by >>> degrading the application performance in full units. A good implementation >>> of this should *use FEC to maintain a constant bitrate despite the >>> variations of the bitrate in the underlying stream. *While it does use >>> more bandwidth than *immediately necessary* it provides great stability >>> for the stream in *cooperation with both long lived TCP streams and >>> short lived bursty streams*. It also *prevents unfair competition from >>> TCP*. In addition, it *provides additional resiliency for handling >>> intermittent packets loss* from WiFi and other wireless/cellular >>> transmissions. >>> >>> I think the benefits of this solution outweigh any other that has been >>> proposed, and solves many of the difficult challenges presented. While I >>> have not yet build a full working model, It should work in at least as many >>> places as CoDel works, and much research has been done and continues to be >>> done on how well CoDel handles fairness. >>> >>> I would love to hear everyone's thoughts on this. Please send me your >>> feedback. >>> >>> Thanks, >>> Dan >>> >> >> > --047d7b1637b7a705dc04ddcf4dc6 Content-Type: text/html; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable
Looks like an oversubscribed link with bufferbloat. We'= ;ve discussed detecting/addressing this with a delay-based approach.= CoDel and PIE are delay-based. Maybe that's the thread you lost?

The other class of congestion control (e.g. TCP) is loss-= based which wouldn't work here (wouldn't start working until it= was way too late).

Kevin Gross
+1-303-447-0517
Media Network Consultant=
AVA Networks -=A0www.AVAnw.com,=A0w= ww.X192.org


On Tue, May 28, 2013 at 3:58 PM, Dan Web= er <dan@marketsoup.com> wrote:
You're right. I made a mistake in my interpretation of this. =A0I = missed the part that the next drop is a solid step into the future. =A0 dro= p1 =3D t + 100, drop2 =3D drop1 + 100/sqrt(2), drop3 =3D drop2 + 100/sqrt(3= ) ...

I'm scratching my head at the words I'm looking= for with regard to fairness. =A0Though I would say the following situation= would be unfair utilization.

The frame rate is 30= fps. =A0Which means net effect that media needs to be delivered every 33ms.= =A0Now let's say it sends the first (an I-Frame) out on to the wire wh= ich composes of 15 packets, the expected presentation time is 3000 (90Khz c= lock) or 0.03333 in relative [delay adjusted] absolute time. =A0By the time= the frame arrives completely, it's 18000 (90khz) or 0.2 [delay adjuste= d] absolute time. =A0The next frame arrives has a time stamp of 6000, it co= mposes of 6 packets, and arrives in total at 23000 (90khz) or 0.2555 absolu= te time. =A0By the time third frame comes in (ts=3D9000), it's arrival = time is 28000 (90khz) or 0.31111 absolute time.

Isn't there some metric we can use to qualify this = behavior? =A0I was thinking the CoDel control law using some comparison bet= ween expected arrival time and actual arrival time, but I seem to have lost= my thought.

Sorry on the CoDel mistake, seemed so clear at the time= ...

Thanks,
Dan




On Tue, May 28, 2013 at 12:40 PM, Kevin Gross <kevin.gross@avanw.com> wrote:
I don't know where you = get the idea that codel drops packets in bursts. It drops one packet per &q= uot;interval". "Interval" starts at 100 ms and is reduced sl= owly (71, 58, 50, 45 ms...) until congestion abates. Codel is effective on = TCP flows because the loss happens promptly, not because the loss is substa= ntial.

Codel is designed to be applied on a per-hop basis. I don= 't see how it can be applied at a receiver for an end-to-end connection= as you are apparently proposing and still behave as generally intended by = its inventors.

Kevin Gross
Media Network Consultant
AVA Networks -=A0www.AVAnw.com,=A0www.X192.org


On Sat, May 25, 2013 at 5:04 PM, Dan Web= er <dan@marketsoup.com> wrote:
Hi guys,

I've been reviewing CoDel, and it's clear how it wo= rks reasonably well for TCP.=A0 It's only slightly more complicated tha= n an implementation using a fixed timestamp per packet expiration.=A0 The m= inor difference occurs when it goes into its dropping state which uses a sq= uare root scaling factor for the time based on the number of previously dro= pped packets in a sequence.=A0 This takes advantage of a known behavior of = TCP congestion control algorithms which expect congestion to happen in larg= e bursts.

When applied to RTP unknowingly, the behavior could be pretty disastrou= s on video content.=A0 Although I doubt it's any worse than actual comp= eting content with no AQM, a particular case does stand out.=A0 When CoDel = is in place where there is no competing traffic and the RTP sender bursts t= he wire without pacing in respect to maximum stream bitrate, CoDel is likel= y to burst drop packets because of overflow on the queue time.=A0 I think <= b>this behavior is extremely desirable.=A0 This will bring awareness to= all vendors and implementors that their implementations were working despi= te the fact that they were improper.=A0

This kind of behavior can be enhanced and augmented in a way that can b= e used to expedite the implementation of effective RTP Congestion Control.= =A0=A0 If we were to implement receiver side CoDel for dropping &= quot;frames" or "messages" of RTP packets on new implementat= ions, we could become the "Soup Nazi" and start effectively i= dentifying improper implementations as well as rendering them inoperable.= =A0 If implemented by one of the major WebRTC browser implementations, <= /b>a chain reaction may develop that forces implementation of RTP conges= tion control up the pipeline.=A0 If useful feedback is delivered back t= o the sender, which really needs to be net translated to frames processe= d and frames dropped, an application with its encoder could reasonably = adjust.=A0 This may solve fairness related problems because the receiver= could identify if the sender overflowed the queues by evaluating actual ar= rival time compared with frame presentation time (converted RTP timestamps)= .=A0 If the receiver enforces this constraint, fairness on RTP streams = is effectively in force because implementations are rendered inoperable, an= d it works safely within the scope of CoDel.=A0 This implies that TCP would= be only at most affected in the same way that another TCP stream would.=A0=

And finally this leads to my suggested solution for sender side congest= ion control.=A0 Based on my assumption that CoDel implementation for AQM is= on the horizon across routers in the next 5 to 10 years, a reasonable sugg= estion for RTP Congestion control may lead to CoDel over CoDel.=A0 An enhan= ced version of CoDel for implementation in the RTP stack (or at the codec e= ncapsulation layer) provides clear frame demarcation and packet mapping (fr= ame no =3D=3D packets n..m), and drops entire frames based on: an assumptio= n (or determination) of targeted maximum bandwidth and (optional, but highl= y recommended) some form of ECN.=A0 Notifications are then provided back to= the application as to which frames were dropped, and the application can m= ake the decision on how it seeks to change its behavior if at all [This com= bines well with the receiver based notification.=A0 If it chooses not to, t= he RTP stack enforces "fairness" by degrading the application per= formance in full units.=A0 A good implementation of this should use FEC = to maintain a constant bitrate despite the variations of the bitrate in the= underlying stream.=A0 While it does use more bandwidth than immedia= tely necessary it provides great stability for the stream in coopera= tion with both long lived TCP streams and short lived bursty streams.= =A0 It also prevents unfair competition from TCP.=A0 In addition, it= provides additional resiliency for handling intermittent packets loss from WiFi and other wireless/cellular transmissions.

I think the benefits of this solution outweigh any other that has been = proposed, and solves many of the difficult challenges presented.=A0 While I= have not yet build a full working model, It should work in at least as man= y places as CoDel works, and much research has been done and continues to b= e done on how well CoDel handles fairness.

I would love to hear everyone's thoughts on this.=A0 Please send me= your feedback.

Thanks,
Dan



--047d7b1637b7a705dc04ddcf4dc6-- From dan@marketsoup.com Tue May 28 17:22:20 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 4FC6421E8087 for ; Tue, 28 May 2013 17:22:12 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -1.248 X-Spam-Level: X-Spam-Status: No, score=-1.248 tagged_above=-999 required=5 tests=[AWL=1.728, BAYES_00=-2.599, FM_FORGED_GMAIL=0.622, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_LOW=-1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id 4YOKX2gcnNif for ; Tue, 28 May 2013 17:22:05 -0700 (PDT) Received: from mail-qe0-f48.google.com (mail-qe0-f48.google.com [209.85.128.48]) by ietfa.amsl.com (Postfix) with ESMTP id 42AB711E80A4 for ; Tue, 28 May 2013 17:22:00 -0700 (PDT) Received: by mail-qe0-f48.google.com with SMTP id 2so3994156qea.7 for ; Tue, 28 May 2013 17:21:59 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=marketsoup.com; s=google; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type; bh=th6gW9QKYqcZfzeQwNKXJN5MGEHF9xGHZVDTmoET3eE=; b=AWmeCX4n2en7XWJJKoCOI6DrvqA29jMtCw6vkSH3tSNZo70yVBW9MFayz8yhjj81GZ QmZam529aQJMZDeLqK+jpj2Kq/YMykmIz34uUrCfl0A+O0644NVAxc3clRr/Xx+6DtiC +K1ct1Ddn4yorECEHvvKUgibO7aoXkT6mioRo= X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type:x-gm-message-state; bh=th6gW9QKYqcZfzeQwNKXJN5MGEHF9xGHZVDTmoET3eE=; b=WJCYn6ehNhKPlew0M9d673Qbr1zVLpz+RD9d8ok2urfPART8te5s4UqemTjwNwA+Z3 9ohGVL8q5jEh10+94zprgAOXHz0FyYJAg45XKPJiVWeSM/gLiSB2Knu6ZwsmwmBU85hc vYygFSTQ7sS3t0yPZTL+LPOJu45tdD0tqgl/0Fd1SldfaazKNXG+oHAw1qwx1mtFTl49 Zbi4phOJ5McMKV3XHxCTZDXr3JShto70UGlLuHKrH0DFOmtlXxPO1ON/Vco8FrMeblDi webkSUbExcNSpAjL120SESVTCnKummWQjYA1PDFBQ+N1nJOIVYpRaUwia/RMzT4Cucs9 YKyQ== MIME-Version: 1.0 X-Received: by 10.224.7.195 with SMTP id e3mr844702qae.5.1369786919367; Tue, 28 May 2013 17:21:59 -0700 (PDT) Received: by 10.224.209.66 with HTTP; Tue, 28 May 2013 17:21:59 -0700 (PDT) X-Originating-IP: [174.51.153.161] In-Reply-To: References: Date: Tue, 28 May 2013 18:21:59 -0600 Message-ID: From: Dan Weber To: Kevin Gross Content-Type: multipart/alternative; boundary=e89a8f923b36bf47c104ddd05ecd X-Gm-Message-State: ALoCoQlnJyXzOHZB3IgrmFhrx7eeYq4pHNv5MjMLInJuopMAZ8j+MVd1+DeZUFL2bgj+fEqSI4KZ Cc: rmcat WG Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 29 May 2013 00:22:22 -0000 --e89a8f923b36bf47c104ddd05ecd Content-Type: text/plain; charset=UTF-8 Well, that's probably it. A delay based approach seems necessary for measuring queue performance. You can't have net queue exit time be any longer than the intended duration of the frame otherwise the frame won't make it there in time for presentation. Can't you just use CoDel's method of calculating queue performance as a metric of fairness or maybe even something more dumbed down? e.g. last packet of frame arrival time minus the first RTP packet arrival time of same frame >= lesser of 2x frame duration or 100ms. It's not a wonderful condition, but it says that's it's clearly within the scope of congestion. Yet in light of this, you might be surprised at how many current "working" implementations can't meet that spec, and actually depend on buffer bloat to support their poor behavior over multiple frames. And to be clear, my definition of congestion is "Anything that won't let me get to the place I need to be in the time for allowed." So if there's heavy traffic we need to leave early, or consider getting more occupants to ride in the HOV lane. Thanks, Dan On Tue, May 28, 2013 at 5:05 PM, Kevin Gross wrote: > Looks like an oversubscribed link with bufferbloat. We've discussed > detecting/addressing this with a *delay-based* approach. CoDel and PIE > are delay-based. Maybe that's the thread you lost? > > The other class of congestion control (e.g. TCP) is *loss-based* which > wouldn't work here (wouldn't start working until it was way too late). > > Kevin Gross > +1-303-447-0517 > Media Network Consultant > AVA Networks - www.AVAnw.com , www.X192.org > > > On Tue, May 28, 2013 at 3:58 PM, Dan Weber wrote: > >> You're right. I made a mistake in my interpretation of this. I missed >> the part that the next drop is a solid step into the future. drop1 = t + >> 100, drop2 = drop1 + 100/sqrt(2), drop3 = drop2 + 100/sqrt(3) ... >> >> I'm scratching my head at the words I'm looking for with regard to >> fairness. Though I would say the following situation would be unfair >> utilization. >> >> The frame rate is 30fps. Which means net effect that media needs to be >> delivered every 33ms. Now let's say it sends the first (an I-Frame) out on >> to the wire which composes of 15 packets, the expected presentation time is >> 3000 (90Khz clock) or 0.03333 in relative [delay adjusted] absolute time. >> By the time the frame arrives completely, it's 18000 (90khz) or 0.2 [delay >> adjusted] absolute time. The next frame arrives has a time stamp of 6000, >> it composes of 6 packets, and arrives in total at 23000 (90khz) or 0.2555 >> absolute time. By the time third frame comes in (ts=9000), it's arrival >> time is 28000 (90khz) or 0.31111 absolute time. >> >> Isn't there some metric we can use to qualify this behavior? I was >> thinking the CoDel control law using some comparison between expected >> arrival time and actual arrival time, but I seem to have lost my thought. >> >> Sorry on the CoDel mistake, seemed so clear at the time... >> >> Thanks, >> Dan >> >> >> >> >> On Tue, May 28, 2013 at 12:40 PM, Kevin Gross wrote: >> >>> I don't know where you get the idea that codel drops packets in bursts. >>> It drops one packet per "interval". "Interval" starts at 100 ms and is >>> reduced slowly (71, 58, 50, 45 ms...) until congestion abates. Codel is >>> effective on TCP flows because the loss happens promptly, not because the >>> loss is substantial. >>> >>> Codel is designed to be applied on a per-hop basis. I don't see how it >>> can be applied at a receiver for an end-to-end connection as you are >>> apparently proposing and still behave as generally intended by its >>> inventors. >>> >> >>> Kevin Gross >>> +1-303-447-0517 >>> Media Network Consultant >>> AVA Networks - www.AVAnw.com , www.X192.org >>> >>> >>> On Sat, May 25, 2013 at 5:04 PM, Dan Weber wrote: >>> >>>> Hi guys, >>>> >>>> I've been reviewing CoDel, and it's clear how it works reasonably well >>>> for TCP. It's only slightly more complicated than an implementation using >>>> a fixed timestamp per packet expiration. The minor difference occurs when >>>> it goes into its dropping state which uses a square root scaling factor for >>>> the time based on the number of previously dropped packets in a sequence. >>>> This takes advantage of a known behavior of TCP congestion control >>>> algorithms which expect congestion to happen in large bursts. >>>> >>>> When applied to RTP unknowingly, the behavior could be pretty >>>> disastrous on video content. Although I doubt it's any worse than actual >>>> competing content with no AQM, a particular case does stand out. When >>>> CoDel is in place where there is no competing traffic and the RTP sender >>>> bursts the wire without pacing in respect to maximum stream bitrate, CoDel >>>> is likely to burst drop packets because of overflow on the queue time. I >>>> think *this behavior is extremely desirable*. This will bring >>>> awareness to all vendors and implementors that their implementations were >>>> working despite the fact that they were improper. >>>> >>>> This kind of behavior can be enhanced and augmented in a way that can >>>> be used to expedite the implementation of effective RTP Congestion >>>> Control. If we were to implement *receiver side CoDel* *for dropping >>>> "frames" or "messages" of RTP packets on new implementations*, we >>>> could become the "Soup Nazi" and start effectively identifying improper >>>> implementations as well as rendering them inoperable. *If implemented >>>> by one of the major WebRTC browser implementations, *a *chain reaction >>>> may develop that forces implementation of RTP congestion control up the >>>> pipeline*. If useful feedback is delivered back to the sender, which >>>> really needs to be net translated to *frames processed and frames >>>> dropped*, an application with its encoder could reasonably adjust. *This >>>> may solve fairness related problems because the receiver could identify if >>>> the sender overflowed the queues by evaluating actual arrival time compared >>>> with frame presentation time (converted RTP timestamps).* If the >>>> receiver enforces this constraint, fairness on RTP streams is effectively >>>> in force because implementations are rendered inoperable, and it works >>>> safely within the scope of CoDel. This implies that TCP would be only at >>>> most affected in the same way that another TCP stream would. >>>> >>>> And finally this leads to my suggested solution for sender side >>>> congestion control. Based on my assumption that CoDel implementation for >>>> AQM is on the horizon across routers in the next 5 to 10 years, a >>>> reasonable suggestion for RTP Congestion control may lead to CoDel over >>>> CoDel. An enhanced version of CoDel for implementation in the RTP stack >>>> (or at the codec encapsulation layer) provides clear frame demarcation and >>>> packet mapping (frame no == packets n..m), and drops entire frames based >>>> on: an assumption (or determination) of targeted maximum bandwidth and >>>> (optional, but highly recommended) some form of ECN. Notifications are >>>> then provided back to the application as to which frames were dropped, and >>>> the application can make the decision on how it seeks to change its >>>> behavior if at all [This combines well with the receiver based >>>> notification. If it chooses not to, the RTP stack enforces "fairness" by >>>> degrading the application performance in full units. A good implementation >>>> of this should *use FEC to maintain a constant bitrate despite the >>>> variations of the bitrate in the underlying stream. *While it does >>>> use more bandwidth than *immediately necessary* it provides great >>>> stability for the stream in *cooperation with both long lived TCP >>>> streams and short lived bursty streams*. It also *prevents unfair >>>> competition from TCP*. In addition, it *provides additional >>>> resiliency for handling intermittent packets loss* from WiFi and other >>>> wireless/cellular transmissions. >>>> >>>> I think the benefits of this solution outweigh any other that has been >>>> proposed, and solves many of the difficult challenges presented. While I >>>> have not yet build a full working model, It should work in at least as many >>>> places as CoDel works, and much research has been done and continues to be >>>> done on how well CoDel handles fairness. >>>> >>>> I would love to hear everyone's thoughts on this. Please send me your >>>> feedback. >>>> >>>> Thanks, >>>> Dan >>>> >>> >>> >> > --e89a8f923b36bf47c104ddd05ecd Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Well, that's probably it. =C2=A0A delay based approach seems necessary = for measuring queue performance. =C2=A0You can't have net queue exit ti= me be any longer than the intended duration of the frame otherwise the fram= e won't make it there in time for presentation. =C2=A0Can't you jus= t use CoDel's method of calculating queue performance as a metric of fa= irness or maybe even something more dumbed down? =C2=A0e.g. last packet of = frame arrival time minus the first RTP packet arrival time of same frame &g= t;=3D =C2=A0lesser of 2x frame duration or 100ms. =C2=A0It's not a wond= erful condition, but it says that's it's clearly within the scope o= f congestion. =C2=A0Yet in light of this, you might be surprised at how man= y current "working" implementations can't meet that spec, and= actually depend on buffer bloat to support their poor behavior over multip= le frames.

And to be clear, my definition of congestion is "Anythi= ng that won't let me get to the place I need to be in the time for allo= wed." =C2=A0So if there's heavy traffic we need to leave early, or= consider getting more occupants to ride in the HOV lane.

Thanks,
Dan



On Tue, May 28, 2013 at= 5:05 PM, Kevin Gross <kevin.gross@avanw.com> wrote:
Looks like an oversubscribe= d link with bufferbloat. We've discussed detecting/addressing this with= a delay-based approach. CoDel and PIE are delay-based. Maybe that&#= 39;s the thread you lost?

The other class of congestion control (e.g. TCP) is loss-= based which wouldn't work here (wouldn't start working until it= was way too late).

Kevin Gross
Media Network Consul= tant
AVA Networks -=C2=A0www.AVAnw.com,=C2=A0www.X192.org


On Tue, May= 28, 2013 at 3:58 PM, Dan Weber <dan@marketsoup.com> wrote:=
You're right. I made a mistake in my interpretation of this. =C2= =A0I missed the part that the next drop is a solid step into the future. = =C2=A0 drop1 =3D t + 100, drop2 =3D drop1 + 100/sqrt(2), drop3 =3D drop2 + = 100/sqrt(3) ...

I'm scratching my head at the words I'm looking= for with regard to fairness. =C2=A0Though I would say the following situat= ion would be unfair utilization.

The frame rate is= 30fps. =C2=A0Which means net effect that media needs to be delivered every= 33ms. =C2=A0Now let's say it sends the first (an I-Frame) out on to th= e wire which composes of 15 packets, the expected presentation time is 3000= (90Khz clock) or 0.03333 in relative [delay adjusted] absolute time. =C2= =A0By the time the frame arrives completely, it's 18000 (90khz) or 0.2 = [delay adjusted] absolute time. =C2=A0The next frame arrives has a time sta= mp of 6000, it composes of 6 packets, and arrives in total at 23000 (90khz)= or 0.2555 absolute time. =C2=A0By the time third frame comes in (ts=3D9000= ), it's arrival time is 28000 (90khz) or 0.31111 absolute time.

Isn't there some metric we can use to qualify this = behavior? =C2=A0I was thinking the CoDel control law using some comparison = between expected arrival time and actual arrival time, but I seem to have l= ost my thought.

Sorry on the CoDel mistake, seemed so clear at the time= ...

Thanks,
Dan

=



On Tue, May 28, 2013 at 12:40 PM, Kevin Gross <kevin.gross@avanw.com> wrote:
I don't know where you = get the idea that codel drops packets in bursts. It drops one packet per &q= uot;interval". "Interval" starts at 100 ms and is reduced sl= owly (71, 58, 50, 45 ms...) until congestion abates. Codel is effective on = TCP flows because the loss happens promptly, not because the loss is substa= ntial.

Codel is designed to be applied on a per-hop basis. I don= 't see how it can be applied at a receiver for an end-to-end connection= as you are apparently proposing and still behave as generally intended by = its inventors.

Kevin Gross
Media Network Consultant
AVA Networks -=C2=A0www.AVAnw.com,=C2=A0www.X192.org


On Sat, May 25, 2013 at 5:04 PM, Dan Web= er <dan@marketsoup.com> wrote:
Hi guys,

I've been reviewing CoDel, and it's clear how it wo= rks reasonably well for TCP.=C2=A0 It's only slightly more complicated = than an implementation using a fixed timestamp per packet expiration.=C2=A0= The minor difference occurs when it goes into its dropping state which use= s a square root scaling factor for the time based on the number of previous= ly dropped packets in a sequence.=C2=A0 This takes advantage of a known beh= avior of TCP congestion control algorithms which expect congestion to happe= n in large bursts.

When applied to RTP unknowingly, the behavior could be pretty disastrou= s on video content.=C2=A0 Although I doubt it's any worse than actual c= ompeting content with no AQM, a particular case does stand out.=C2=A0 When = CoDel is in place where there is no competing traffic and the RTP sender bu= rsts the wire without pacing in respect to maximum stream bitrate, CoDel is= likely to burst drop packets because of overflow on the queue time.=C2=A0 = I think this behavior is extremely desirable.=C2=A0 This will bring = awareness to all vendors and implementors that their implementations were w= orking despite the fact that they were improper.=C2=A0

This kind of behavior can be enhanced and augmented in a way that can b= e used to expedite the implementation of effective RTP Congestion Control.= =C2=A0=C2=A0 If we were to implement receiver side CoDel for drop= ping "frames" or "messages" of RTP packets on new imple= mentations, we could become the "Soup Nazi" and start effecti= vely identifying improper implementations as well as rendering them inopera= ble.=C2=A0 If implemented by one of the major WebRTC browser implementat= ions, a chain reaction may develop that forces implementation of RTP= congestion control up the pipeline.=C2=A0 If useful feedback is delive= red back to the sender, which really needs to be net translated to frame= s processed and frames dropped, an application with its encoder could r= easonably adjust.=C2=A0 This may solve fairness related problems because= the receiver could identify if the sender overflowed the queues by evaluat= ing actual arrival time compared with frame presentation time (converted RT= P timestamps).=C2=A0 If the receiver enforces this constraint, fairness= on RTP streams is effectively in force because implementations are rendere= d inoperable, and it works safely within the scope of CoDel.=C2=A0 This imp= lies that TCP would be only at most affected in the same way that another T= CP stream would.=C2=A0

And finally this leads to my suggested solution for sender side congest= ion control.=C2=A0 Based on my assumption that CoDel implementation for AQM= is on the horizon across routers in the next 5 to 10 years, a reasonable s= uggestion for RTP Congestion control may lead to CoDel over CoDel.=C2=A0 An= enhanced version of CoDel for implementation in the RTP stack (or at the c= odec encapsulation layer) provides clear frame demarcation and packet mappi= ng (frame no =3D=3D packets n..m), and drops entire frames based on: an ass= umption (or determination) of targeted maximum bandwidth and (optional, but= highly recommended) some form of ECN.=C2=A0 Notifications are then provide= d back to the application as to which frames were dropped, and the applicat= ion can make the decision on how it seeks to change its behavior if at all = [This combines well with the receiver based notification.=C2=A0 If it choos= es not to, the RTP stack enforces "fairness" by degrading the app= lication performance in full units.=C2=A0 A good implementation of this sho= uld use FEC to maintain a constant bitrate despite the variations of the= bitrate in the underlying stream.=C2=A0 While it does use more bandwid= th than immediately necessary it provides great stability for the st= ream in cooperation with both long lived TCP streams and short lived bur= sty streams.=C2=A0 It also prevents unfair competition from TCP.= =C2=A0 In addition, it provides additional resiliency for handling inter= mittent packets loss from WiFi and other wireless/cellular transmission= s.

I think the benefits of this solution outweigh any other that has been = proposed, and solves many of the difficult challenges presented.=C2=A0 Whil= e I have not yet build a full working model, It should work in at least as = many places as CoDel works, and much research has been done and continues t= o be done on how well CoDel handles fairness.

I would love to hear everyone's thoughts on this.=C2=A0 Please send= me your feedback.

Thanks,
Dan




--e89a8f923b36bf47c104ddd05ecd-- From dan@marketsoup.com Tue May 28 17:41:06 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 5F2AF21F86C4 for ; Tue, 28 May 2013 17:41:06 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -0.096 X-Spam-Level: X-Spam-Status: No, score=-0.096 tagged_above=-999 required=5 tests=[AWL=-0.576, BAYES_00=-2.599, FH_RELAY_NODNS=1.451, FM_FORGED_GMAIL=0.622, HTML_MESSAGE=0.001, RCVD_IN_PBL=0.905, RDNS_NONE=0.1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id l3mdOaNECh8v for ; Tue, 28 May 2013 17:41:02 -0700 (PDT) Received: from mail-qa0-x22f.google.com (mail-qa0-x22f.google.com [IPv6:2607:f8b0:400d:c00::22f]) by ietfa.amsl.com (Postfix) with ESMTP id C259A21F86C3 for ; Tue, 28 May 2013 17:41:01 -0700 (PDT) Received: by mail-qa0-f47.google.com with SMTP id n20so17942qaj.13 for ; Tue, 28 May 2013 17:41:00 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=marketsoup.com; s=google; h=mime-version:x-originating-ip:date:message-id:subject:from:to :content-type; bh=kadbkJj0js0egCpXZHhKmZm4W6FEpo6XNc5W5vtXO5A=; b=NCSTcLqOJZoJ8elBi9GIXDngcoIUOs8TllNvuFXyuHaFipCmb53I6dPrtocatgqM9y SqD6v2zyvfDYWaiapi09enRYnrcnrqHm4lnG5p7i3cGvHwaqoxsxmJJWDYSZAoGFvpkK sFRIB4avk65MVPpo03XUbErYBEbBLOJLjln10= X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:x-originating-ip:date:message-id:subject:from:to :content-type:x-gm-message-state; bh=kadbkJj0js0egCpXZHhKmZm4W6FEpo6XNc5W5vtXO5A=; b=Z8n1iSCPsi24JpzkJOino2Mr4cjktgwKPkcW2eg8BoFETolBR2docWb7aYvUzB5mbH t+LrbXodrFN95/N2DSeE8Qd9JT9HCEkYyr+ZVincFgJrFquZ3qaZJkU1b2TqLZSGLPbB s8tsVPu1HhDzehhwW93F2r7Ere14iPgVefj8ra2u45sIoPhNzizIOw1NMcduyambdgGE bMdDLpLx00Qt++AeCzwD7UXexyKpvFf4c14IGKPoZgjWsV22LS/muP8El2YBATlzJJHb IDRhFw42+ctQK1kmkEmm4tqB61ueS1Q8/AGda6ZpSDxHfB9L2L28oRvIimPeSZU7aNaO oAkg== MIME-Version: 1.0 X-Received: by 10.224.74.8 with SMTP id s8mr769206qaj.60.1369788060830; Tue, 28 May 2013 17:41:00 -0700 (PDT) Received: by 10.224.209.66 with HTTP; Tue, 28 May 2013 17:41:00 -0700 (PDT) X-Originating-IP: [174.51.153.161] Date: Tue, 28 May 2013 18:41:00 -0600 Message-ID: From: Dan Weber To: rmcat@ietf.org Content-Type: multipart/alternative; boundary=001a11c3c27cc8a11504ddd0a233 X-Gm-Message-State: ALoCoQmrVSHDQfcyFj2YYbhzRruSaNGjXvee9jAbkNUuKp4nlEAjdeVaZmzifJabM1TGajZBfjef Subject: [rmcat] Variable Bitrate Impact on Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 29 May 2013 00:41:06 -0000 --001a11c3c27cc8a11504ddd0a233 Content-Type: text/plain; charset=UTF-8 It's important to note the role that variable bitrate plays in congestion control. I know we've discussed this on some level, but in reality, any decision that's made when the underlying medium continuously changes characteristics is an unreliable one. If used with any sort of instantaneous measure, it can give you unrealistic expectations of capacity. Just consider a large file transfer of TCP over the network. It may sawtooth up and down a bit, but it usually stabilizes to a certain level. Now if you've got a 3/3 mbit link, you have a video call going with a *max rate* of 1.5mbit/s bidirectionally, and you're uploading or downloading the latest DVD iso of Ubuntu, your video call may deteriorate somewhat randomly, and you may see a good bit of bounce in the TCP download performance. Your file transfer over TCP is like, "Mmm.. Give me all I can get." and your video call is voluntarily leaving food on the table only consuming what he needs right now. The TCP guy is baffled by this behavior, but takes advantage of the food as it becomes available. Then when someone walks across the back of the room, the video bitrate spikes, the video guy is like, "Who just ate my lunch?" This creates an unnecessary race for available resources, and makes it difficult for all parties involved including other congestion controlled streams to make best use of their available resources. Variable bitrate in real time seems like a good idea in theory, but it doesn't work in practice for the problem described above. This is true for all cases where it has to share itself with other congestion controlled algorithms. If it's on a dedicated link or contains special QoS, there's a fixed number of streams allowed, each with maximum allowable bitrates, then it can work fine all on its own. But in that case it doesn't need congestion control. It's congestion controlled by design. But to be clear, I am in no way suggesting that we use average bitrate or constant bitrate settings from the video encoders. I used to have this wonderful demo that demonstrated this. In the very first demo of my video conference bridge (~2006), I had all of the participants displayed on to the screen, and I had the encoder tuned to 768k/s for QVGA. And when the first person jump on, he would take up a quarter of the screen leaving three quarters black. He looked perfectly sharp, and then another person joined. Everything seemed okay. The third person joins and you start wondering why everyone started looking fuzzy. Then when the fourth person jumps on, it looks like everyone's face is covered in vaseline. When you're targeting bitrate, you're ignoring quality. A few solutions come to mind. It may not be feasible on anyone's real network, but you could try using something like RSVP to perform bandwidth reservations. You could also fill packets with zeros to target the bitrate. And while this solution maybe very CPU efficient, it's not really doing anything for you. To me it makes the most sense to use some form of FEC to fill up the difference. Variable video bitrate + variable FEC bitrate = Video Stream Max Bitrate. Maybe you could even do something fancy like span it across a bunch of frames or focus on your i-frames. Whatever rocks your ride. On the plus side, in the event you do hit some intermittent packet loss or you do hit some congestion, you have added resilience to protect your stream while still having wiggle room to adjust for congestion. Dan --001a11c3c27cc8a11504ddd0a233 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
It's important to note the role that variable bitrate plays in con= gestion control. =C2=A0I know we've discussed this on some level, but i= n reality, any decision that's made when the underlying medium continuo= usly changes characteristics is an unreliable one. =C2=A0If used with any s= ort of instantaneous measure, it can give you unrealistic expectations of c= apacity. =C2=A0=C2=A0

Just consider a large file transfer of TCP over the net= work. =C2=A0It may sawtooth up and down a bit, but it usually stabilizes to= a certain level. =C2=A0Now if you've got a 3/3 mbit link, you have a v= ideo call going with a=C2=A0max rate=C2=A0of 1.5mbit/s bidirectional= ly, and you're uploading or downloading the latest DVD iso of Ubuntu, y= our video call may deteriorate somewhat randomly, and you may see a good bi= t of bounce in the TCP download performance. =C2=A0Your file transfer over = TCP is like, "Mmm.. =C2=A0Give me all I can get." =C2=A0and your = video call is voluntarily leaving food on the table only consuming what he = needs right now. =C2=A0The TCP guy is baffled by this behavior, but takes a= dvantage of the food as it becomes available. =C2=A0Then when someone walks= across the back of the room, the video bitrate spikes, the video guy is li= ke, "Who just ate my lunch?"

This creates an unnecessary race for available resource= s, and makes it difficult for all parties involved including other congesti= on controlled streams to make best use of their available resources.

Variable bitrate in real time seems like a good idea in= theory, but it doesn't work in practice for the problem described abov= e. =C2=A0This is true for all cases where it has to share itself with other= congestion controlled algorithms. =C2=A0If it's on a dedicated link or= contains special QoS, there's a fixed number of streams allowed, each = with maximum allowable bitrates, then it can work fine all on its own. =C2= =A0But in that case it doesn't need congestion control. =C2=A0It's = congestion controlled by design.

But to be clear, I am in no way suggesting that we use = average bitrate or constant bitrate settings from the video encoders. =C2= =A0I used to have this wonderful demo that demonstrated this. =C2=A0In the = very first demo of my video conference bridge (~2006), I had all of the par= ticipants displayed on to the screen, and I had the encoder tuned to 768k/s= for QVGA. =C2=A0And when the first person jump on, he would take up a quar= ter of the screen leaving three quarters black. =C2=A0He looked perfectly s= harp, and then another person joined. =C2=A0Everything seemed okay. =C2=A0T= he third person joins and you start wondering why everyone started looking = fuzzy. =C2=A0Then when the fourth person jumps on, it looks like everyone&#= 39;s face is covered in vaseline. =C2=A0When you're targeting bitrate, = you're ignoring quality.

A few solutions come to mind. =C2=A0It may not be feasi= ble on anyone's real network, but you could try using something like RS= VP to perform bandwidth reservations. =C2=A0You could also fill packets wit= h zeros to target the bitrate. =C2=A0And while this solution maybe very CPU= efficient, it's not really doing anything for you. =C2=A0To me it make= s the most sense to use some form of FEC to fill up the difference. =C2=A0V= ariable video bitrate + variable FEC bitrate =3D Video Stream Max Bitrate. = =C2=A0Maybe you could even do something fancy like span it across a bunch o= f frames or focus on your i-frames. =C2=A0Whatever rocks your ride.

On the plus side, in the event you do hit some intermit= tent packet loss or you do hit some congestion, you have added resilience t= o protect your stream while still having wiggle room to adjust for congesti= on.

Dan


--001a11c3c27cc8a11504ddd0a233-- From abegen@cisco.com Wed May 29 03:41:11 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 22EC321F88D8 for ; Wed, 29 May 2013 03:41:11 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -10.599 X-Spam-Level: X-Spam-Status: No, score=-10.599 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, RCVD_IN_DNSWL_HI=-8] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id BHz+3uGOwFgC for ; Wed, 29 May 2013 03:41:05 -0700 (PDT) Received: from rcdn-iport-5.cisco.com (rcdn-iport-5.cisco.com [173.37.86.76]) by ietfa.amsl.com (Postfix) with ESMTP id 918F421F88BF for ; Wed, 29 May 2013 03:41:05 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=1582; q=dns/txt; s=iport; t=1369824065; x=1371033665; h=from:to:cc:subject:date:message-id:references: in-reply-to:content-id:content-transfer-encoding: mime-version; bh=dXwinWKesGe+UQcEuNG56id9t2bVqJdl8trHwQCvzKY=; b=gzpWuZLios8qgNdI/HdKTYY/11TigouPahhUdU1kAUfm7xl4geoUP+A0 +/+VXg2QTKodHydfzNsXSamWUXhx+QRhhsAhMtgaF6EJEupJTQ5f67twJ nSs92hr63DICrrOTN4LIVicyyLU7r+R5xnC8QpCvoYqT1k2lAC+oL5KqT w=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: Ai4FABXapVGtJXHA/2dsb2JhbABagmghwiuBCBZ0giMBAQEDATo/BQsCAQgiFBAyJQIEDgUIh38GAbpCjVSBDgIxB4JzYQOoe4MPgWk+ X-IronPort-AV: E=Sophos;i="4.87,763,1363132800"; d="scan'208";a="216171696" Received: from rcdn-core2-5.cisco.com ([173.37.113.192]) by rcdn-iport-5.cisco.com with ESMTP; 29 May 2013 10:41:05 +0000 Received: from xhc-aln-x14.cisco.com (xhc-aln-x14.cisco.com [173.36.12.88]) by rcdn-core2-5.cisco.com (8.14.5/8.14.5) with ESMTP id r4TAf5xK002039 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL); Wed, 29 May 2013 10:41:05 GMT Received: from xmb-aln-x01.cisco.com ([fe80::747b:83e1:9755:d453]) by xhc-aln-x14.cisco.com ([173.36.12.88]) with mapi id 14.02.0318.004; Wed, 29 May 2013 05:41:04 -0500 From: "Ali C. Begen (abegen)" To: Dan Weber Thread-Topic: [rmcat] "Soup Nazi" RTP Congestion Control Thread-Index: AQHOWZxLNJY3y1cPlE+gbu/SBSn9ZpkbRk0AgAAKEQCAAAlNgIAAEqEAgAAWGYCAANBOAA== Date: Wed, 29 May 2013 10:41:04 +0000 Message-ID: References: <8C48B86A895913448548E6D15DA7553B8FADD8@xmb-rcd-x09.cisco.com> <8C48B86A895913448548E6D15DA7553B8FB058@xmb-rcd-x09.cisco.com> In-Reply-To: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [10.86.252.243] Content-Type: text/plain; charset="us-ascii" Content-ID: <1EEBD9CB798737468CDC884E0FB5A9D0@emea.cisco.com> Content-Transfer-Encoding: quoted-printable MIME-Version: 1.0 Cc: rmcat WG , "Fred Baker \(fred\)" , Kevin Gross Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 29 May 2013 10:41:11 -0000 On May 29, 2013, at 1:15 AM, Dan Weber wrote: > I think the behavior is right if the RTP congestion control mechanism dro= ps the entire frame and notifies the application it wouldn't be delivered w= ithin the appropriate time frame. The mechanism by which it determines thi= s is still open for discussion. I particularly liked the thought that if a= ny one packet of the frame would have to wait in the user space RTP packet = queue (i.e. while pacing) for sending and exceeded a certain threshold (e.g= . 100ms scaled down), then the entire frame should be dropped. I dont think that is the right move. There are so many skilled receiver-sid= e concealment algorithms that can deal with the loss of a few packets. but = if you drop the entire frame, until the encoder deals with that, you will l= ikely be in serious trouble. And you will likely have wasted all the bits y= ou already transmitted successfully for that particular frame. OTOH, it is true that if you miss certain header info, the remaining bits a= re useless for that slice/frame/GOP/etc. but do you really think that the m= iddle boxes should investigate the bitstream in that detail? This looks to = me as a non-starter. > This could potentially give enough benefit to the application encoder to= be notified that those N successive pictures weren't usable as references = in addition to the fact that the frames were never sent. The encoder could= update the state for the next available encoded frame leaving a better use= r experience. >=20 > Dan From mramalho@cisco.com Wed May 29 07:12:42 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 5ED2421F8E49 for ; Wed, 29 May 2013 07:12:42 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -10.598 X-Spam-Level: X-Spam-Status: No, score=-10.598 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_HI=-8] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id YPHzAqb0x5NG for ; Wed, 29 May 2013 07:12:33 -0700 (PDT) Received: from rcdn-iport-8.cisco.com (rcdn-iport-8.cisco.com [173.37.86.79]) by ietfa.amsl.com (Postfix) with ESMTP id 395FA21F8EF2 for ; Wed, 29 May 2013 07:12:33 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=36516; q=dns/txt; s=iport; t=1369836753; x=1371046353; h=from:to:cc:subject:date:message-id:references: in-reply-to:mime-version; bh=d5hAFs7+XBH0Ft1wLPqyGFcLC8bxu7JekQNJReN/6+w=; b=PjdNsokdaDPZXvC4KAE4zS5lP6RVCuLWZFVnJawfbnugNw1lKIxxix9t ZhxenQdzDHXB3zdNPK9EDuSQrEEX8/deV1ICZiG8O1mjhIw8XLhZAlOpJ HsdF8W2FngOxN5Px7mPlOQezoS2uR+L4nNiZiu8w1VvvSu0Dk9I0d033m 0=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: AkcHALULplGtJXG+/2dsb2JhbABQBwOCRUQwgzu+QA18FnSCIwEBAQQjChwwEAIBCAcKBAEBCxYHAwICAjAUCQgCBAENBQgTh3KoUZISjVmBCxYLEAYBCQiCMDJhA6h7gw+CJw X-IronPort-AV: E=Sophos;i="4.87,764,1363132800"; d="scan'208,217";a="216244284" Received: from rcdn-core2-3.cisco.com ([173.37.113.190]) by rcdn-iport-8.cisco.com with ESMTP; 29 May 2013 14:12:32 +0000 Received: from xhc-rcd-x05.cisco.com (xhc-rcd-x05.cisco.com [173.37.183.79]) by rcdn-core2-3.cisco.com (8.14.5/8.14.5) with ESMTP id r4TECVM6010669 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL); Wed, 29 May 2013 14:12:31 GMT Received: from xmb-rcd-x12.cisco.com ([169.254.2.54]) by xhc-rcd-x05.cisco.com ([173.37.183.79]) with mapi id 14.02.0318.004; Wed, 29 May 2013 09:12:31 -0500 From: "Michael Ramalho (mramalho)" To: Dan Weber , Kevin Gross Thread-Topic: [rmcat] "Soup Nazi" RTP Congestion Control Thread-Index: AQHOWZxLv0AsRQlc5UyHgkMHksoJ1pkbRk0AgAA3TICAALXuAA== Date: Wed, 29 May 2013 14:12:30 +0000 Message-ID: References: In-Reply-To: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [161.44.43.45] Content-Type: multipart/alternative; boundary="_000_D21571530BF9644D9A443D6BD95B91031556C061xmbrcdx12ciscoc_" MIME-Version: 1.0 Cc: rmcat WG Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 29 May 2013 14:12:42 -0000 --_000_D21571530BF9644D9A443D6BD95B91031556C061xmbrcdx12ciscoc_ Content-Type: text/plain; charset="utf-8" Content-Transfer-Encoding: base64 RGFuLA0KDQpUaGFua3MgZm9yIGFsbCB0aGUgY2hhdHRlciB5b3VyIHBvc3QgcmVzdWx0ZWQgaW4g Oy0pLg0KDQpPbmUgb2YgdGhlIHJlYXNvbnMgd2h5IEkgcHJvcG9zZWQgdGhhdCB0aGUgaW5pdGlh bCBSTUNBVCBjYW5kaWRhdGVzIGFyZSB0ZXN0ZWQgaW4gYW4gZW52aXJvbm1lbnQgd2hlcmUgc291 cmNlcyBhcmUgc21vb3RoIChpLmUuLCBwcm9kdWNpbmcgZGF0YSBhdCB0aGUgZW52ZWxvcGUgb2Yg dGhlIGVzdGltYXRlZCBhdmFpbGFibGUgYml0IHJhdGUpIGlzIHRoYXQgZmFpcm5lc3MgaXMgdmVy eSBkaWZmaWN1bHQgdG8gcXVhbnRpZnkgd2l0aCBhIHZhcmlhYmxlIGJpdCByYXRlIHNvdXJjZSB3 aXRoIGFyYml0cmFyeSBwZWFrL2luc3RhbnRhbmVvdXMgcmF0ZSB0byBhdmVyYWdlIHJhdGUgcmF0 aW9zLg0KDQpOb3RlIHlvdXIgZGlzY3Vzc2lvbiBiZWxvdyBpbW1lZGlhdGVseSBmb2N1c2VzIG9u IHlvdXIgZGVmaW5pdGlvbiBvZiDigJx1bmZhaXJuZXNz4oCdIGJ5IG1lYW5zIG9mIGEgMzAgZnBz IHZpZGVvIGZsb3cgZXhhbXBsZSBpbiB0aGUgdXN1YWwgR09QIGZyYW1ld29yayAod2l0aCBhbiBJ LWZyYW1lIGJ1cnN0KS4NCg0KU29tZWhvdyB5b3UgZXhwZWN0IHRoZSBuZXR3b3JrIHRvIGFjY29t bW9kYXRlIHlvdXIgYnVyc3RzIE9SIGlmIGl0IGNhbuKAmXQgdG8gZG8gc29tZXRoaW5nIOKAnGlu dGVsbGlnZW50IHRvIHlvdeKAnSAobGlrZSBkcm9wIHRoZSBlbnRpcmUgZnJhbWUpLg0KDQpbTm90 ZTogQWxpIHByZXNlbnRlZCBzb21lIGNvdW50ZXItYXJndW1lbnQgdG8gdGhpcyBwb2ludCDigKYg bGV0IG1lIGlnbm9yZSB0aGF0IGhlcmUg4oCmIGJ1dCBJIGRvIG5vdGUgdGhhdCBBbGkgaGFzIHBl cmZvcm1lZCBhIExPVCBvZiB3b3JrIGluIHRoaXMgYXJlYSFdDQoNCkJhY2sgaW4gdGhlIGRheSBv ZiBJbnRTZXYsIHdlIGhhZCBWQlIgVFNQRUNTIGluIHdoaWNoIHlvdSBjb3VsZCBkZWZpbmUgeW91 ciBmbG934oCZcyBidXJzdGluZyB2aWEgYSB0b2tlbiBidWNrZXQgcmVwcmVzZW50YXRpb24gKGku ZS4sIGNoYXJhY3Rlcml6YXRpb24pIG9mIHRoZSBlbnZlbG9wZSBvZiB5b3VyIGV4cGVjdGVkIHJh dGUgdmFyaWFiaWxpdHkuIFRoYXQgaXMsIGlmIHlvdSBjaGFyYWN0ZXJpemVkIFlPVVIgQVBQTElD QVRJT04gYW5kIHByb3ZpZGVkIOKAnHRoZSBOZXR3b3Jr4oCdIHdpdGggYSBWQlIgVFNQRUMgKHZp YSBSU1ZQKSDigKYgYW5kIHRoYXQgVFNQRUMgd2FzIGFjY2VwdGVkIGJ5IGFuIGVuZC10by1lbmQg SW50U2Vydi1jYXBhYmxlIG5ldHdvcmsg4oCmIHlvdSB3b3VsZCBoYXZlIGV4YWN0bHkgd2hhdCB5 b3Ugd2FudCEgSG93ZXZlciwgbm9uZSBvZiB0aGlzIGlzIGJlaW5nIHByb3Bvc2VkIGhlcmUgKElu dFNlcnYvUlNWUCBhbmQgZXZlbiBBUU1zIGFyZSBzb21ld2hhdCBvdXQtb2Ytc2NvcGUgZm9yIFJN Q0FUIOKAkyBhbHRob3VnaCBJIGFncmVlIGRpc2N1c3NpbmcgdGhlbSBpbiB0aGUgY29udGV4dCBv ZiBSTUNBVCBtYWtlcyBzZW5zZSkuDQoNCkdpdmVuIHRoZXNlIGNvbnN0cmFpbnRzLCBpdCBhcHBl YXJzIHVucmVhc29uYWJsZSBmb3IgdGhlIFJNQ0FUIHByb3RvY29sIHRvIGV4cGxpY2l0bHkgYWNj b21tb2RhdGUgeW91ciBpZGVhIG9mIGZhaXJuZXNzIHByZWNpc2VseSBiZWNhdXNlIHdlIGFyZSBu b3QgYXNzdW1pbmcgdGhlIGFiaWxpdHkgdG8gc2lnbmFsIHRoZSBuZXR3b3JrIGFzIHRvIHlvdXIg YXBwbGljYXRpb25zIGJ1cnN0aW5nIHByb2ZpbGUuDQoNCkkgdGhpbmsgd2UgbmVlZCB0byBnZXQg b3V0IG9mIHRoZSBzaXR1YXRpb24gd2hlcmUgd2UgY29uc2lkZXIgZmFpcm5lc3MgaW4gdGhlIGNv bnRleHQgb2YgYW55b25l4oCZcyBwZXQtYXBwbGljYXRpb24gKHlvdXJzIGlzIGFwcGFyZW50bHkg c29tZSB2aWRlbyBhcHBsaWNhdGlvbiBydW5uaW5nIGF0IDMwIGZwcykuIFRoZSBSTUNBVCB0cmFu c3BvcnQgcHJvdG9jb2wgc2hvdWxkIGJlIGFnbm9zdGljIHRvIHRvZGF54oCZcyBhcHBsaWNhdGlv bnMgYXMgcG9zc2libGUgKHJlYWwtdGltZSAzRCBob2xvZ3JhcGh5IHdpbGwgYmUgaGVyZSBiZWZv cmUgeW91IGtub3cgaXQhKS4NCg0KQXMgYSBwYXJ0aW5nIGFzaWRlLCB2aWRlbyBlbmNvZGVyIHZl bmRvcnMgYXJlIHF1aWNrbHkgcmVhbGl6aW5nIHRoZSBiZW5lZml0cyBvZiBnZW5lcmF0aW5nIGFz IHNtb290aCBhIHZpZGVvIHNvdXJjZSBhcyBwb3NzaWJsZSBhbmQgdG8gcGFjZSB0aGVpciBvdXRw dXQgdG8gdGhlIHdpcmUuDQoNCk9mZiBTb2FwYm94LA0KDQpNaWNoYWVsIFJhbWFsaG8NCg0KDQpG cm9tOiBybWNhdC1ib3VuY2VzQGlldGYub3JnIFttYWlsdG86cm1jYXQtYm91bmNlc0BpZXRmLm9y Z10gT24gQmVoYWxmIE9mIERhbiBXZWJlcg0KU2VudDogVHVlc2RheSwgTWF5IDI4LCAyMDEzIDU6 NTkgUE0NClRvOiBLZXZpbiBHcm9zcw0KQ2M6IHJtY2F0IFdHDQpTdWJqZWN0OiBSZTogW3JtY2F0 XSAiU291cCBOYXppIiBSVFAgQ29uZ2VzdGlvbiBDb250cm9sDQoNCllvdSdyZSByaWdodC4gSSBt YWRlIGEgbWlzdGFrZSBpbiBteSBpbnRlcnByZXRhdGlvbiBvZiB0aGlzLiAgSSBtaXNzZWQgdGhl IHBhcnQgdGhhdCB0aGUgbmV4dCBkcm9wIGlzIGEgc29saWQgc3RlcCBpbnRvIHRoZSBmdXR1cmUu ICAgZHJvcDEgPSB0ICsgMTAwLCBkcm9wMiA9IGRyb3AxICsgMTAwL3NxcnQoMiksIGRyb3AzID0g ZHJvcDIgKyAxMDAvc3FydCgzKSAuLi4NCg0KSSdtIHNjcmF0Y2hpbmcgbXkgaGVhZCBhdCB0aGUg d29yZHMgSSdtIGxvb2tpbmcgZm9yIHdpdGggcmVnYXJkIHRvIGZhaXJuZXNzLiAgVGhvdWdoIEkg d291bGQgc2F5IHRoZSBmb2xsb3dpbmcgc2l0dWF0aW9uIHdvdWxkIGJlIHVuZmFpciB1dGlsaXph dGlvbi4NCg0KVGhlIGZyYW1lIHJhdGUgaXMgMzBmcHMuICBXaGljaCBtZWFucyBuZXQgZWZmZWN0 IHRoYXQgbWVkaWEgbmVlZHMgdG8gYmUgZGVsaXZlcmVkIGV2ZXJ5IDMzbXMuICBOb3cgbGV0J3Mg c2F5IGl0IHNlbmRzIHRoZSBmaXJzdCAoYW4gSS1GcmFtZSkgb3V0IG9uIHRvIHRoZSB3aXJlIHdo aWNoIGNvbXBvc2VzIG9mIDE1IHBhY2tldHMsIHRoZSBleHBlY3RlZCBwcmVzZW50YXRpb24gdGlt ZSBpcyAzMDAwICg5MEtoeiBjbG9jaykgb3IgMC4wMzMzMyBpbiByZWxhdGl2ZSBbZGVsYXkgYWRq dXN0ZWRdIGFic29sdXRlIHRpbWUuICBCeSB0aGUgdGltZSB0aGUgZnJhbWUgYXJyaXZlcyBjb21w bGV0ZWx5LCBpdCdzIDE4MDAwICg5MGtoeikgb3IgMC4yIFtkZWxheSBhZGp1c3RlZF0gYWJzb2x1 dGUgdGltZS4gIFRoZSBuZXh0IGZyYW1lIGFycml2ZXMgaGFzIGEgdGltZSBzdGFtcCBvZiA2MDAw LCBpdCBjb21wb3NlcyBvZiA2IHBhY2tldHMsIGFuZCBhcnJpdmVzIGluIHRvdGFsIGF0IDIzMDAw ICg5MGtoeikgb3IgMC4yNTU1IGFic29sdXRlIHRpbWUuICBCeSB0aGUgdGltZSB0aGlyZCBmcmFt ZSBjb21lcyBpbiAodHM9OTAwMCksIGl0J3MgYXJyaXZhbCB0aW1lIGlzIDI4MDAwICg5MGtoeikg b3IgMC4zMTExMSBhYnNvbHV0ZSB0aW1lLg0KDQpJc24ndCB0aGVyZSBzb21lIG1ldHJpYyB3ZSBj YW4gdXNlIHRvIHF1YWxpZnkgdGhpcyBiZWhhdmlvcj8gIEkgd2FzIHRoaW5raW5nIHRoZSBDb0Rl bCBjb250cm9sIGxhdyB1c2luZyBzb21lIGNvbXBhcmlzb24gYmV0d2VlbiBleHBlY3RlZCBhcnJp dmFsIHRpbWUgYW5kIGFjdHVhbCBhcnJpdmFsIHRpbWUsIGJ1dCBJIHNlZW0gdG8gaGF2ZSBsb3N0 IG15IHRob3VnaHQuDQoNClNvcnJ5IG9uIHRoZSBDb0RlbCBtaXN0YWtlLCBzZWVtZWQgc28gY2xl YXIgYXQgdGhlIHRpbWUuLi4NCg0KVGhhbmtzLA0KRGFuDQoNCg0KDQoNCk9uIFR1ZSwgTWF5IDI4 LCAyMDEzIGF0IDEyOjQwIFBNLCBLZXZpbiBHcm9zcyA8a2V2aW4uZ3Jvc3NAYXZhbncuY29tPG1h aWx0bzprZXZpbi5ncm9zc0BhdmFudy5jb20+PiB3cm90ZToNCkkgZG9uJ3Qga25vdyB3aGVyZSB5 b3UgZ2V0IHRoZSBpZGVhIHRoYXQgY29kZWwgZHJvcHMgcGFja2V0cyBpbiBidXJzdHMuIEl0IGRy b3BzIG9uZSBwYWNrZXQgcGVyICJpbnRlcnZhbCIuICJJbnRlcnZhbCIgc3RhcnRzIGF0IDEwMCBt cyBhbmQgaXMgcmVkdWNlZCBzbG93bHkgKDcxLCA1OCwgNTAsIDQ1IG1zLi4uKSB1bnRpbCBjb25n ZXN0aW9uIGFiYXRlcy4gQ29kZWwgaXMgZWZmZWN0aXZlIG9uIFRDUCBmbG93cyBiZWNhdXNlIHRo ZSBsb3NzIGhhcHBlbnMgcHJvbXB0bHksIG5vdCBiZWNhdXNlIHRoZSBsb3NzIGlzIHN1YnN0YW50 aWFsLg0KDQpDb2RlbCBpcyBkZXNpZ25lZCB0byBiZSBhcHBsaWVkIG9uIGEgcGVyLWhvcCBiYXNp cy4gSSBkb24ndCBzZWUgaG93IGl0IGNhbiBiZSBhcHBsaWVkIGF0IGEgcmVjZWl2ZXIgZm9yIGFu IGVuZC10by1lbmQgY29ubmVjdGlvbiBhcyB5b3UgYXJlIGFwcGFyZW50bHkgcHJvcG9zaW5nIGFu ZCBzdGlsbCBiZWhhdmUgYXMgZ2VuZXJhbGx5IGludGVuZGVkIGJ5IGl0cyBpbnZlbnRvcnMuDQoN CktldmluIEdyb3NzDQorMS0zMDMtNDQ3LTA1MTc8dGVsOiUyQjEtMzAzLTQ0Ny0wNTE3Pg0KTWVk aWEgTmV0d29yayBDb25zdWx0YW50DQpBVkEgTmV0d29ya3MgLSB3d3cuQVZBbncuY29tPGh0dHA6 Ly93d3cuYXZhbncuY29tLz4sIHd3dy5YMTkyLm9yZzxodHRwOi8vd3d3LlgxOTIub3JnPg0KDQpP biBTYXQsIE1heSAyNSwgMjAxMyBhdCA1OjA0IFBNLCBEYW4gV2ViZXIgPGRhbkBtYXJrZXRzb3Vw LmNvbTxtYWlsdG86ZGFuQG1hcmtldHNvdXAuY29tPj4gd3JvdGU6DQpIaSBndXlzLA0KDQpJJ3Zl IGJlZW4gcmV2aWV3aW5nIENvRGVsLCBhbmQgaXQncyBjbGVhciBob3cgaXQgd29ya3MgcmVhc29u YWJseSB3ZWxsIGZvciBUQ1AuICBJdCdzIG9ubHkgc2xpZ2h0bHkgbW9yZSBjb21wbGljYXRlZCB0 aGFuIGFuIGltcGxlbWVudGF0aW9uIHVzaW5nIGEgZml4ZWQgdGltZXN0YW1wIHBlciBwYWNrZXQg ZXhwaXJhdGlvbi4gIFRoZSBtaW5vciBkaWZmZXJlbmNlIG9jY3VycyB3aGVuIGl0IGdvZXMgaW50 byBpdHMgZHJvcHBpbmcgc3RhdGUgd2hpY2ggdXNlcyBhIHNxdWFyZSByb290IHNjYWxpbmcgZmFj dG9yIGZvciB0aGUgdGltZSBiYXNlZCBvbiB0aGUgbnVtYmVyIG9mIHByZXZpb3VzbHkgZHJvcHBl ZCBwYWNrZXRzIGluIGEgc2VxdWVuY2UuICBUaGlzIHRha2VzIGFkdmFudGFnZSBvZiBhIGtub3du IGJlaGF2aW9yIG9mIFRDUCBjb25nZXN0aW9uIGNvbnRyb2wgYWxnb3JpdGhtcyB3aGljaCBleHBl Y3QgY29uZ2VzdGlvbiB0byBoYXBwZW4gaW4gbGFyZ2UgYnVyc3RzLg0KDQpXaGVuIGFwcGxpZWQg dG8gUlRQIHVua25vd2luZ2x5LCB0aGUgYmVoYXZpb3IgY291bGQgYmUgcHJldHR5IGRpc2FzdHJv dXMgb24gdmlkZW8gY29udGVudC4gIEFsdGhvdWdoIEkgZG91YnQgaXQncyBhbnkgd29yc2UgdGhh biBhY3R1YWwgY29tcGV0aW5nIGNvbnRlbnQgd2l0aCBubyBBUU0sIGEgcGFydGljdWxhciBjYXNl IGRvZXMgc3RhbmQgb3V0LiAgV2hlbiBDb0RlbCBpcyBpbiBwbGFjZSB3aGVyZSB0aGVyZSBpcyBu byBjb21wZXRpbmcgdHJhZmZpYyBhbmQgdGhlIFJUUCBzZW5kZXIgYnVyc3RzIHRoZSB3aXJlIHdp dGhvdXQgcGFjaW5nIGluIHJlc3BlY3QgdG8gbWF4aW11bSBzdHJlYW0gYml0cmF0ZSwgQ29EZWwg aXMgbGlrZWx5IHRvIGJ1cnN0IGRyb3AgcGFja2V0cyBiZWNhdXNlIG9mIG92ZXJmbG93IG9uIHRo ZSBxdWV1ZSB0aW1lLiAgSSB0aGluayB0aGlzIGJlaGF2aW9yIGlzIGV4dHJlbWVseSBkZXNpcmFi bGUuICBUaGlzIHdpbGwgYnJpbmcgYXdhcmVuZXNzIHRvIGFsbCB2ZW5kb3JzIGFuZCBpbXBsZW1l bnRvcnMgdGhhdCB0aGVpciBpbXBsZW1lbnRhdGlvbnMgd2VyZSB3b3JraW5nIGRlc3BpdGUgdGhl IGZhY3QgdGhhdCB0aGV5IHdlcmUgaW1wcm9wZXIuDQoNClRoaXMga2luZCBvZiBiZWhhdmlvciBj YW4gYmUgZW5oYW5jZWQgYW5kIGF1Z21lbnRlZCBpbiBhIHdheSB0aGF0IGNhbiBiZSB1c2VkIHRv IGV4cGVkaXRlIHRoZSBpbXBsZW1lbnRhdGlvbiBvZiBlZmZlY3RpdmUgUlRQIENvbmdlc3Rpb24g Q29udHJvbC4gICBJZiB3ZSB3ZXJlIHRvIGltcGxlbWVudCByZWNlaXZlciBzaWRlIENvRGVsIGZv ciBkcm9wcGluZyAiZnJhbWVzIiBvciAibWVzc2FnZXMiIG9mIFJUUCBwYWNrZXRzIG9uIG5ldyBp bXBsZW1lbnRhdGlvbnMsIHdlIGNvdWxkIGJlY29tZSB0aGUgIlNvdXAgTmF6aSIgYW5kIHN0YXJ0 IGVmZmVjdGl2ZWx5IGlkZW50aWZ5aW5nIGltcHJvcGVyIGltcGxlbWVudGF0aW9ucyBhcyB3ZWxs IGFzIHJlbmRlcmluZyB0aGVtIGlub3BlcmFibGUuICBJZiBpbXBsZW1lbnRlZCBieSBvbmUgb2Yg dGhlIG1ham9yIFdlYlJUQyBicm93c2VyIGltcGxlbWVudGF0aW9ucywgYSBjaGFpbiByZWFjdGlv biBtYXkgZGV2ZWxvcCB0aGF0IGZvcmNlcyBpbXBsZW1lbnRhdGlvbiBvZiBSVFAgY29uZ2VzdGlv biBjb250cm9sIHVwIHRoZSBwaXBlbGluZS4gIElmIHVzZWZ1bCBmZWVkYmFjayBpcyBkZWxpdmVy ZWQgYmFjayB0byB0aGUgc2VuZGVyLCB3aGljaCByZWFsbHkgbmVlZHMgdG8gYmUgbmV0IHRyYW5z bGF0ZWQgdG8gZnJhbWVzIHByb2Nlc3NlZCBhbmQgZnJhbWVzIGRyb3BwZWQsIGFuIGFwcGxpY2F0 aW9uIHdpdGggaXRzIGVuY29kZXIgY291bGQgcmVhc29uYWJseSBhZGp1c3QuICBUaGlzIG1heSBz b2x2ZSBmYWlybmVzcyByZWxhdGVkIHByb2JsZW1zIGJlY2F1c2UgdGhlIHJlY2VpdmVyIGNvdWxk IGlkZW50aWZ5IGlmIHRoZSBzZW5kZXIgb3ZlcmZsb3dlZCB0aGUgcXVldWVzIGJ5IGV2YWx1YXRp bmcgYWN0dWFsIGFycml2YWwgdGltZSBjb21wYXJlZCB3aXRoIGZyYW1lIHByZXNlbnRhdGlvbiB0 aW1lIChjb252ZXJ0ZWQgUlRQIHRpbWVzdGFtcHMpLiAgSWYgdGhlIHJlY2VpdmVyIGVuZm9yY2Vz IHRoaXMgY29uc3RyYWludCwgZmFpcm5lc3Mgb24gUlRQIHN0cmVhbXMgaXMgZWZmZWN0aXZlbHkg aW4gZm9yY2UgYmVjYXVzZSBpbXBsZW1lbnRhdGlvbnMgYXJlIHJlbmRlcmVkIGlub3BlcmFibGUs IGFuZCBpdCB3b3JrcyBzYWZlbHkgd2l0aGluIHRoZSBzY29wZSBvZiBDb0RlbC4gIFRoaXMgaW1w bGllcyB0aGF0IFRDUCB3b3VsZCBiZSBvbmx5IGF0IG1vc3QgYWZmZWN0ZWQgaW4gdGhlIHNhbWUg d2F5IHRoYXQgYW5vdGhlciBUQ1Agc3RyZWFtIHdvdWxkLg0KDQpBbmQgZmluYWxseSB0aGlzIGxl YWRzIHRvIG15IHN1Z2dlc3RlZCBzb2x1dGlvbiBmb3Igc2VuZGVyIHNpZGUgY29uZ2VzdGlvbiBj b250cm9sLiAgQmFzZWQgb24gbXkgYXNzdW1wdGlvbiB0aGF0IENvRGVsIGltcGxlbWVudGF0aW9u IGZvciBBUU0gaXMgb24gdGhlIGhvcml6b24gYWNyb3NzIHJvdXRlcnMgaW4gdGhlIG5leHQgNSB0 byAxMCB5ZWFycywgYSByZWFzb25hYmxlIHN1Z2dlc3Rpb24gZm9yIFJUUCBDb25nZXN0aW9uIGNv bnRyb2wgbWF5IGxlYWQgdG8gQ29EZWwgb3ZlciBDb0RlbC4gIEFuIGVuaGFuY2VkIHZlcnNpb24g b2YgQ29EZWwgZm9yIGltcGxlbWVudGF0aW9uIGluIHRoZSBSVFAgc3RhY2sgKG9yIGF0IHRoZSBj b2RlYyBlbmNhcHN1bGF0aW9uIGxheWVyKSBwcm92aWRlcyBjbGVhciBmcmFtZSBkZW1hcmNhdGlv biBhbmQgcGFja2V0IG1hcHBpbmcgKGZyYW1lIG5vID09IHBhY2tldHMgbi4ubSksIGFuZCBkcm9w cyBlbnRpcmUgZnJhbWVzIGJhc2VkIG9uOiBhbiBhc3N1bXB0aW9uIChvciBkZXRlcm1pbmF0aW9u KSBvZiB0YXJnZXRlZCBtYXhpbXVtIGJhbmR3aWR0aCBhbmQgKG9wdGlvbmFsLCBidXQgaGlnaGx5 IHJlY29tbWVuZGVkKSBzb21lIGZvcm0gb2YgRUNOLiAgTm90aWZpY2F0aW9ucyBhcmUgdGhlbiBw cm92aWRlZCBiYWNrIHRvIHRoZSBhcHBsaWNhdGlvbiBhcyB0byB3aGljaCBmcmFtZXMgd2VyZSBk cm9wcGVkLCBhbmQgdGhlIGFwcGxpY2F0aW9uIGNhbiBtYWtlIHRoZSBkZWNpc2lvbiBvbiBob3cg aXQgc2Vla3MgdG8gY2hhbmdlIGl0cyBiZWhhdmlvciBpZiBhdCBhbGwgW1RoaXMgY29tYmluZXMg d2VsbCB3aXRoIHRoZSByZWNlaXZlciBiYXNlZCBub3RpZmljYXRpb24uICBJZiBpdCBjaG9vc2Vz IG5vdCB0bywgdGhlIFJUUCBzdGFjayBlbmZvcmNlcyAiZmFpcm5lc3MiIGJ5IGRlZ3JhZGluZyB0 aGUgYXBwbGljYXRpb24gcGVyZm9ybWFuY2UgaW4gZnVsbCB1bml0cy4gIEEgZ29vZCBpbXBsZW1l bnRhdGlvbiBvZiB0aGlzIHNob3VsZCB1c2UgRkVDIHRvIG1haW50YWluIGEgY29uc3RhbnQgYml0 cmF0ZSBkZXNwaXRlIHRoZSB2YXJpYXRpb25zIG9mIHRoZSBiaXRyYXRlIGluIHRoZSB1bmRlcmx5 aW5nIHN0cmVhbS4gIFdoaWxlIGl0IGRvZXMgdXNlIG1vcmUgYmFuZHdpZHRoIHRoYW4gaW1tZWRp YXRlbHkgbmVjZXNzYXJ5IGl0IHByb3ZpZGVzIGdyZWF0IHN0YWJpbGl0eSBmb3IgdGhlIHN0cmVh bSBpbiBjb29wZXJhdGlvbiB3aXRoIGJvdGggbG9uZyBsaXZlZCBUQ1Agc3RyZWFtcyBhbmQgc2hv cnQgbGl2ZWQgYnVyc3R5IHN0cmVhbXMuICBJdCBhbHNvIHByZXZlbnRzIHVuZmFpciBjb21wZXRp dGlvbiBmcm9tIFRDUC4gIEluIGFkZGl0aW9uLCBpdCBwcm92aWRlcyBhZGRpdGlvbmFsIHJlc2ls aWVuY3kgZm9yIGhhbmRsaW5nIGludGVybWl0dGVudCBwYWNrZXRzIGxvc3MgZnJvbSBXaUZpIGFu ZCBvdGhlciB3aXJlbGVzcy9jZWxsdWxhciB0cmFuc21pc3Npb25zLg0KDQpJIHRoaW5rIHRoZSBi ZW5lZml0cyBvZiB0aGlzIHNvbHV0aW9uIG91dHdlaWdoIGFueSBvdGhlciB0aGF0IGhhcyBiZWVu IHByb3Bvc2VkLCBhbmQgc29sdmVzIG1hbnkgb2YgdGhlIGRpZmZpY3VsdCBjaGFsbGVuZ2VzIHBy ZXNlbnRlZC4gIFdoaWxlIEkgaGF2ZSBub3QgeWV0IGJ1aWxkIGEgZnVsbCB3b3JraW5nIG1vZGVs LCBJdCBzaG91bGQgd29yayBpbiBhdCBsZWFzdCBhcyBtYW55IHBsYWNlcyBhcyBDb0RlbCB3b3Jr cywgYW5kIG11Y2ggcmVzZWFyY2ggaGFzIGJlZW4gZG9uZSBhbmQgY29udGludWVzIHRvIGJlIGRv bmUgb24gaG93IHdlbGwgQ29EZWwgaGFuZGxlcyBmYWlybmVzcy4NCg0KSSB3b3VsZCBsb3ZlIHRv IGhlYXIgZXZlcnlvbmUncyB0aG91Z2h0cyBvbiB0aGlzLiAgUGxlYXNlIHNlbmQgbWUgeW91ciBm ZWVkYmFjay4NCg0KVGhhbmtzLA0KRGFuDQoNCg0K --_000_D21571530BF9644D9A443D6BD95B91031556C061xmbrcdx12ciscoc_ Content-Type: text/html; charset="utf-8" Content-Transfer-Encoding: base64 PGh0bWwgeG1sbnM6dj0idXJuOnNjaGVtYXMtbWljcm9zb2Z0LWNvbTp2bWwiIHhtbG5zOm89InVy bjpzY2hlbWFzLW1pY3Jvc29mdC1jb206b2ZmaWNlOm9mZmljZSIgeG1sbnM6dz0idXJuOnNjaGVt YXMtbWljcm9zb2Z0LWNvbTpvZmZpY2U6d29yZCIgeG1sbnM6bT0iaHR0cDovL3NjaGVtYXMubWlj cm9zb2Z0LmNvbS9vZmZpY2UvMjAwNC8xMi9vbW1sIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcv VFIvUkVDLWh0bWw0MCI+DQo8aGVhZD4NCjxtZXRhIGh0dHAtZXF1aXY9IkNvbnRlbnQtVHlwZSIg Y29udGVudD0idGV4dC9odG1sOyBjaGFyc2V0PXV0Zi04Ij4NCjxtZXRhIG5hbWU9IkdlbmVyYXRv ciIgY29udGVudD0iTWljcm9zb2Z0IFdvcmQgMTQgKGZpbHRlcmVkIG1lZGl1bSkiPg0KPHN0eWxl PjwhLS0NCi8qIEZvbnQgRGVmaW5pdGlvbnMgKi8NCkBmb250LWZhY2UNCgl7Zm9udC1mYW1pbHk6 Q2FsaWJyaTsNCglwYW5vc2UtMToyIDE1IDUgMiAyIDIgNCAzIDIgNDt9DQpAZm9udC1mYWNlDQoJ e2ZvbnQtZmFtaWx5OlRhaG9tYTsNCglwYW5vc2UtMToyIDExIDYgNCAzIDUgNCA0IDIgNDt9DQov KiBTdHlsZSBEZWZpbml0aW9ucyAqLw0KcC5Nc29Ob3JtYWwsIGxpLk1zb05vcm1hbCwgZGl2Lk1z b05vcm1hbA0KCXttYXJnaW46MGluOw0KCW1hcmdpbi1ib3R0b206LjAwMDFwdDsNCglmb250LXNp emU6MTIuMHB0Ow0KCWZvbnQtZmFtaWx5OiJUaW1lcyBOZXcgUm9tYW4iLCJzZXJpZiI7fQ0KYTps aW5rLCBzcGFuLk1zb0h5cGVybGluaw0KCXttc28tc3R5bGUtcHJpb3JpdHk6OTk7DQoJY29sb3I6 Ymx1ZTsNCgl0ZXh0LWRlY29yYXRpb246dW5kZXJsaW5lO30NCmE6dmlzaXRlZCwgc3Bhbi5Nc29I eXBlcmxpbmtGb2xsb3dlZA0KCXttc28tc3R5bGUtcHJpb3JpdHk6OTk7DQoJY29sb3I6cHVycGxl Ow0KCXRleHQtZGVjb3JhdGlvbjp1bmRlcmxpbmU7fQ0Kc3Bhbi5ob2VuemINCgl7bXNvLXN0eWxl LW5hbWU6aG9lbnpiO30NCnNwYW4uRW1haWxTdHlsZTE4DQoJe21zby1zdHlsZS10eXBlOnBlcnNv bmFsLXJlcGx5Ow0KCWZvbnQtZmFtaWx5OiJDYWxpYnJpIiwic2Fucy1zZXJpZiI7DQoJY29sb3I6 IzFGNDk3RDt9DQouTXNvQ2hwRGVmYXVsdA0KCXttc28tc3R5bGUtdHlwZTpleHBvcnQtb25seTsN Cglmb250LWZhbWlseToiQ2FsaWJyaSIsInNhbnMtc2VyaWYiO30NCkBwYWdlIFdvcmRTZWN0aW9u MQ0KCXtzaXplOjguNWluIDExLjBpbjsNCgltYXJnaW46MS4waW4gMS4waW4gMS4waW4gMS4waW47 fQ0KZGl2LldvcmRTZWN0aW9uMQ0KCXtwYWdlOldvcmRTZWN0aW9uMTt9DQotLT48L3N0eWxlPjwh LS1baWYgZ3RlIG1zbyA5XT48eG1sPg0KPG86c2hhcGVkZWZhdWx0cyB2OmV4dD0iZWRpdCIgc3Bp ZG1heD0iMTAyNiIgLz4NCjwveG1sPjwhW2VuZGlmXS0tPjwhLS1baWYgZ3RlIG1zbyA5XT48eG1s Pg0KPG86c2hhcGVsYXlvdXQgdjpleHQ9ImVkaXQiPg0KPG86aWRtYXAgdjpleHQ9ImVkaXQiIGRh dGE9IjEiIC8+DQo8L286c2hhcGVsYXlvdXQ+PC94bWw+PCFbZW5kaWZdLS0+DQo8L2hlYWQ+DQo8 Ym9keSBsYW5nPSJFTi1VUyIgbGluaz0iYmx1ZSIgdmxpbms9InB1cnBsZSI+DQo8ZGl2IGNsYXNz PSJXb3JkU2VjdGlvbjEiPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5bGU9ImZvbnQt c2l6ZToxMS4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90OywmcXVvdDtzYW5zLXNl cmlmJnF1b3Q7O2NvbG9yOiMxRjQ5N0QiPkRhbiw8bzpwPjwvbzpwPjwvc3Bhbj48L3A+DQo8cCBj bGFzcz0iTXNvTm9ybWFsIj48c3BhbiBzdHlsZT0iZm9udC1zaXplOjExLjBwdDtmb250LWZhbWls eTomcXVvdDtDYWxpYnJpJnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVvdDs7Y29sb3I6IzFGNDk3 RCI+PG86cD4mbmJzcDs8L286cD48L3NwYW4+PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNw YW4gc3R5bGU9ImZvbnQtc2l6ZToxMS4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90 OywmcXVvdDtzYW5zLXNlcmlmJnF1b3Q7O2NvbG9yOiMxRjQ5N0QiPlRoYW5rcyBmb3IgYWxsIHRo ZSBjaGF0dGVyIHlvdXIgcG9zdCByZXN1bHRlZCBpbiA7LSkuPG86cD48L286cD48L3NwYW4+PC9w Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5bGU9ImZvbnQtc2l6ZToxMS4wcHQ7Zm9u dC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90OywmcXVvdDtzYW5zLXNlcmlmJnF1b3Q7O2NvbG9y OiMxRjQ5N0QiPjxvOnA+Jm5ic3A7PC9vOnA+PC9zcGFuPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3Jt YWwiPjxzcGFuIHN0eWxlPSJmb250LXNpemU6MTEuMHB0O2ZvbnQtZmFtaWx5OiZxdW90O0NhbGli cmkmcXVvdDssJnF1b3Q7c2Fucy1zZXJpZiZxdW90Oztjb2xvcjojMUY0OTdEIj5PbmUgb2YgdGhl IHJlYXNvbnMgd2h5IEkgcHJvcG9zZWQgdGhhdCB0aGUgaW5pdGlhbCBSTUNBVCBjYW5kaWRhdGVz IGFyZSB0ZXN0ZWQgaW4gYW4gZW52aXJvbm1lbnQgd2hlcmUgc291cmNlcyBhcmUgc21vb3RoIChp LmUuLCBwcm9kdWNpbmcgZGF0YSBhdCB0aGUgZW52ZWxvcGUNCiBvZiB0aGUgZXN0aW1hdGVkIGF2 YWlsYWJsZSBiaXQgcmF0ZSkgaXMgdGhhdCBmYWlybmVzcyBpcyB2ZXJ5IGRpZmZpY3VsdCB0byBx dWFudGlmeSB3aXRoIGEgdmFyaWFibGUgYml0IHJhdGUgc291cmNlIHdpdGggYXJiaXRyYXJ5IHBl YWsvaW5zdGFudGFuZW91cyByYXRlIHRvIGF2ZXJhZ2UgcmF0ZSByYXRpb3MuPG86cD48L286cD48 L3NwYW4+PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5bGU9ImZvbnQtc2l6ZTox MS4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90OywmcXVvdDtzYW5zLXNlcmlmJnF1 b3Q7O2NvbG9yOiMxRjQ5N0QiPjxvOnA+Jm5ic3A7PC9vOnA+PC9zcGFuPjwvcD4NCjxwIGNsYXNz PSJNc29Ob3JtYWwiPjxzcGFuIHN0eWxlPSJmb250LXNpemU6MTEuMHB0O2ZvbnQtZmFtaWx5OiZx dW90O0NhbGlicmkmcXVvdDssJnF1b3Q7c2Fucy1zZXJpZiZxdW90Oztjb2xvcjojMUY0OTdEIj5O b3RlIHlvdXIgZGlzY3Vzc2lvbiBiZWxvdyBpbW1lZGlhdGVseSBmb2N1c2VzIG9uIHlvdXIgZGVm aW5pdGlvbiBvZiDigJx1bmZhaXJuZXNz4oCdIGJ5IG1lYW5zIG9mIGEgMzAgZnBzIHZpZGVvIGZs b3cgZXhhbXBsZSBpbiB0aGUgdXN1YWwgR09QIGZyYW1ld29yayAod2l0aCBhbg0KIEktZnJhbWUg YnVyc3QpLjxvOnA+PC9vOnA+PC9zcGFuPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFu IHN0eWxlPSJmb250LXNpemU6MTEuMHB0O2ZvbnQtZmFtaWx5OiZxdW90O0NhbGlicmkmcXVvdDss JnF1b3Q7c2Fucy1zZXJpZiZxdW90Oztjb2xvcjojMUY0OTdEIj48bzpwPiZuYnNwOzwvbzpwPjwv c3Bhbj48L3A+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48c3BhbiBzdHlsZT0iZm9udC1zaXplOjEx LjBwdDtmb250LWZhbWlseTomcXVvdDtDYWxpYnJpJnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVv dDs7Y29sb3I6IzFGNDk3RCI+U29tZWhvdyB5b3UgZXhwZWN0IHRoZSBuZXR3b3JrIHRvIGFjY29t bW9kYXRlIHlvdXIgYnVyc3RzIE9SIGlmIGl0IGNhbuKAmXQgdG8gZG8gc29tZXRoaW5nIOKAnGlu dGVsbGlnZW50IHRvIHlvdeKAnSAobGlrZSBkcm9wIHRoZSBlbnRpcmUgZnJhbWUpLjxvOnA+PC9v OnA+PC9zcGFuPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0eWxlPSJmb250LXNp emU6MTEuMHB0O2ZvbnQtZmFtaWx5OiZxdW90O0NhbGlicmkmcXVvdDssJnF1b3Q7c2Fucy1zZXJp ZiZxdW90Oztjb2xvcjojMUY0OTdEIj48bzpwPiZuYnNwOzwvbzpwPjwvc3Bhbj48L3A+DQo8cCBj bGFzcz0iTXNvTm9ybWFsIj48c3BhbiBzdHlsZT0iZm9udC1zaXplOjExLjBwdDtmb250LWZhbWls eTomcXVvdDtDYWxpYnJpJnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVvdDs7Y29sb3I6IzFGNDk3 RCI+W05vdGU6IEFsaSBwcmVzZW50ZWQgc29tZSBjb3VudGVyLWFyZ3VtZW50IHRvIHRoaXMgcG9p bnQg4oCmIGxldCBtZSBpZ25vcmUgdGhhdCBoZXJlIOKApiBidXQgSSBkbyBub3RlIHRoYXQgQWxp IGhhcyBwZXJmb3JtZWQgYSBMT1Qgb2Ygd29yayBpbiB0aGlzIGFyZWEhXTxvOnA+PC9vOnA+PC9z cGFuPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0eWxlPSJmb250LXNpemU6MTEu MHB0O2ZvbnQtZmFtaWx5OiZxdW90O0NhbGlicmkmcXVvdDssJnF1b3Q7c2Fucy1zZXJpZiZxdW90 Oztjb2xvcjojMUY0OTdEIj48bzpwPiZuYnNwOzwvbzpwPjwvc3Bhbj48L3A+DQo8cCBjbGFzcz0i TXNvTm9ybWFsIj48c3BhbiBzdHlsZT0iZm9udC1zaXplOjExLjBwdDtmb250LWZhbWlseTomcXVv dDtDYWxpYnJpJnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVvdDs7Y29sb3I6IzFGNDk3RCI+QmFj ayBpbiB0aGUgZGF5IG9mIEludFNldiwgd2UgaGFkIFZCUiBUU1BFQ1MgaW4gd2hpY2ggeW91IGNv dWxkIGRlZmluZSB5b3VyIGZsb3figJlzIGJ1cnN0aW5nIHZpYSBhIHRva2VuIGJ1Y2tldCByZXBy ZXNlbnRhdGlvbiAoaS5lLiwgY2hhcmFjdGVyaXphdGlvbikgb2YgdGhlDQogZW52ZWxvcGUgb2Yg eW91ciBleHBlY3RlZCByYXRlIHZhcmlhYmlsaXR5LiBUaGF0IGlzLCBpZiB5b3UgY2hhcmFjdGVy aXplZCBZT1VSIEFQUExJQ0FUSU9OIGFuZCBwcm92aWRlZCDigJx0aGUgTmV0d29ya+KAnSB3aXRo IGEgVkJSIFRTUEVDICh2aWEgUlNWUCkg4oCmIGFuZCB0aGF0IFRTUEVDIHdhcyBhY2NlcHRlZCBi eSBhbiBlbmQtdG8tZW5kIEludFNlcnYtY2FwYWJsZSBuZXR3b3JrIOKApiB5b3Ugd291bGQgaGF2 ZSBleGFjdGx5IHdoYXQgeW91IHdhbnQhDQogSG93ZXZlciwgbm9uZSBvZiB0aGlzIGlzIGJlaW5n IHByb3Bvc2VkIGhlcmUgKEludFNlcnYvUlNWUCBhbmQgZXZlbiBBUU1zIGFyZSBzb21ld2hhdCBv dXQtb2Ytc2NvcGUgZm9yIFJNQ0FUIOKAkyBhbHRob3VnaCBJIGFncmVlIGRpc2N1c3NpbmcgdGhl bSBpbiB0aGUgY29udGV4dCBvZiBSTUNBVCBtYWtlcyBzZW5zZSkuPG86cD48L286cD48L3NwYW4+ PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5bGU9ImZvbnQtc2l6ZToxMS4wcHQ7 Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90OywmcXVvdDtzYW5zLXNlcmlmJnF1b3Q7O2Nv bG9yOiMxRjQ5N0QiPjxvOnA+Jm5ic3A7PC9vOnA+PC9zcGFuPjwvcD4NCjxwIGNsYXNzPSJNc29O b3JtYWwiPjxzcGFuIHN0eWxlPSJmb250LXNpemU6MTEuMHB0O2ZvbnQtZmFtaWx5OiZxdW90O0Nh bGlicmkmcXVvdDssJnF1b3Q7c2Fucy1zZXJpZiZxdW90Oztjb2xvcjojMUY0OTdEIj5HaXZlbiB0 aGVzZSBjb25zdHJhaW50cywgaXQgYXBwZWFycyB1bnJlYXNvbmFibGUgZm9yIHRoZSBSTUNBVCBw cm90b2NvbCB0byBleHBsaWNpdGx5IGFjY29tbW9kYXRlIHlvdXIgaWRlYSBvZiBmYWlybmVzcyBw cmVjaXNlbHkgYmVjYXVzZSB3ZSBhcmUgbm90IGFzc3VtaW5nDQogdGhlIGFiaWxpdHkgdG8gc2ln bmFsIHRoZSBuZXR3b3JrIGFzIHRvIHlvdXIgYXBwbGljYXRpb25zIGJ1cnN0aW5nIHByb2ZpbGUu PG86cD48L286cD48L3NwYW4+PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5bGU9 ImZvbnQtc2l6ZToxMS4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90OywmcXVvdDtz YW5zLXNlcmlmJnF1b3Q7O2NvbG9yOiMxRjQ5N0QiPjxvOnA+Jm5ic3A7PC9vOnA+PC9zcGFuPjwv cD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0eWxlPSJmb250LXNpemU6MTEuMHB0O2Zv bnQtZmFtaWx5OiZxdW90O0NhbGlicmkmcXVvdDssJnF1b3Q7c2Fucy1zZXJpZiZxdW90Oztjb2xv cjojMUY0OTdEIj5JIHRoaW5rIHdlIG5lZWQgdG8gZ2V0IG91dCBvZiB0aGUgc2l0dWF0aW9uIHdo ZXJlIHdlIGNvbnNpZGVyIGZhaXJuZXNzIGluIHRoZSBjb250ZXh0IG9mIGFueW9uZeKAmXMgcGV0 LWFwcGxpY2F0aW9uICh5b3VycyBpcyBhcHBhcmVudGx5IHNvbWUgdmlkZW8gYXBwbGljYXRpb24N CiBydW5uaW5nIGF0IDMwIGZwcykuIFRoZSBSTUNBVCB0cmFuc3BvcnQgcHJvdG9jb2wgc2hvdWxk IGJlIGFnbm9zdGljIHRvIHRvZGF54oCZcyBhcHBsaWNhdGlvbnMgYXMgcG9zc2libGUgKHJlYWwt dGltZSAzRCBob2xvZ3JhcGh5IHdpbGwgYmUgaGVyZSBiZWZvcmUgeW91IGtub3cgaXQhKS48bzpw PjwvbzpwPjwvc3Bhbj48L3A+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48c3BhbiBzdHlsZT0iZm9u dC1zaXplOjExLjBwdDtmb250LWZhbWlseTomcXVvdDtDYWxpYnJpJnF1b3Q7LCZxdW90O3NhbnMt c2VyaWYmcXVvdDs7Y29sb3I6IzFGNDk3RCI+PG86cD4mbmJzcDs8L286cD48L3NwYW4+PC9wPg0K PHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5bGU9ImZvbnQtc2l6ZToxMS4wcHQ7Zm9udC1m YW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90OywmcXVvdDtzYW5zLXNlcmlmJnF1b3Q7O2NvbG9yOiMx RjQ5N0QiPkFzIGEgcGFydGluZyBhc2lkZSwgdmlkZW8gZW5jb2RlciB2ZW5kb3JzIGFyZSBxdWlj a2x5IHJlYWxpemluZyB0aGUgYmVuZWZpdHMgb2YgZ2VuZXJhdGluZyBhcyBzbW9vdGggYSB2aWRl byBzb3VyY2UgYXMgcG9zc2libGUgYW5kIHRvIHBhY2UgdGhlaXIgb3V0cHV0IHRvDQogdGhlIHdp cmUuPG86cD48L286cD48L3NwYW4+PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5 bGU9ImZvbnQtc2l6ZToxMS4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90OywmcXVv dDtzYW5zLXNlcmlmJnF1b3Q7O2NvbG9yOiMxRjQ5N0QiPjxvOnA+Jm5ic3A7PC9vOnA+PC9zcGFu PjwvcD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0eWxlPSJmb250LXNpemU6MTEuMHB0 O2ZvbnQtZmFtaWx5OiZxdW90O0NhbGlicmkmcXVvdDssJnF1b3Q7c2Fucy1zZXJpZiZxdW90Oztj b2xvcjojMUY0OTdEIj5PZmYgU29hcGJveCw8bzpwPjwvbzpwPjwvc3Bhbj48L3A+DQo8cCBjbGFz cz0iTXNvTm9ybWFsIj48c3BhbiBzdHlsZT0iZm9udC1zaXplOjExLjBwdDtmb250LWZhbWlseTom cXVvdDtDYWxpYnJpJnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVvdDs7Y29sb3I6IzFGNDk3RCI+ PG86cD4mbmJzcDs8L286cD48L3NwYW4+PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4g c3R5bGU9ImZvbnQtc2l6ZToxMS4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90Oywm cXVvdDtzYW5zLXNlcmlmJnF1b3Q7O2NvbG9yOiMxRjQ5N0QiPk1pY2hhZWwgUmFtYWxobzxvOnA+ PC9vOnA+PC9zcGFuPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0eWxlPSJmb250 LXNpemU6MTEuMHB0O2ZvbnQtZmFtaWx5OiZxdW90O0NhbGlicmkmcXVvdDssJnF1b3Q7c2Fucy1z ZXJpZiZxdW90Oztjb2xvcjojMUY0OTdEIj48bzpwPiZuYnNwOzwvbzpwPjwvc3Bhbj48L3A+DQo8 cCBjbGFzcz0iTXNvTm9ybWFsIj48c3BhbiBzdHlsZT0iZm9udC1zaXplOjExLjBwdDtmb250LWZh bWlseTomcXVvdDtDYWxpYnJpJnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVvdDs7Y29sb3I6IzFG NDk3RCI+PG86cD4mbmJzcDs8L286cD48L3NwYW4+PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+ PGI+PHNwYW4gc3R5bGU9ImZvbnQtc2l6ZToxMC4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7VGFob21h JnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVvdDsiPkZyb206PC9zcGFuPjwvYj48c3BhbiBzdHls ZT0iZm9udC1zaXplOjEwLjBwdDtmb250LWZhbWlseTomcXVvdDtUYWhvbWEmcXVvdDssJnF1b3Q7 c2Fucy1zZXJpZiZxdW90OyI+IHJtY2F0LWJvdW5jZXNAaWV0Zi5vcmcgW21haWx0bzpybWNhdC1i b3VuY2VzQGlldGYub3JnXQ0KPGI+T24gQmVoYWxmIE9mIDwvYj5EYW4gV2ViZXI8YnI+DQo8Yj5T ZW50OjwvYj4gVHVlc2RheSwgTWF5IDI4LCAyMDEzIDU6NTkgUE08YnI+DQo8Yj5Ubzo8L2I+IEtl dmluIEdyb3NzPGJyPg0KPGI+Q2M6PC9iPiBybWNhdCBXRzxicj4NCjxiPlN1YmplY3Q6PC9iPiBS ZTogW3JtY2F0XSAmcXVvdDtTb3VwIE5hemkmcXVvdDsgUlRQIENvbmdlc3Rpb24gQ29udHJvbDxv OnA+PC9vOnA+PC9zcGFuPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxvOnA+Jm5ic3A7PC9v OnA+PC9wPg0KPGRpdj4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPllvdSdyZSByaWdodC4gSSBtYWRl IGEgbWlzdGFrZSBpbiBteSBpbnRlcnByZXRhdGlvbiBvZiB0aGlzLiAmbmJzcDtJIG1pc3NlZCB0 aGUgcGFydCB0aGF0IHRoZSBuZXh0IGRyb3AgaXMgYSBzb2xpZCBzdGVwIGludG8gdGhlIGZ1dHVy ZS4gJm5ic3A7IGRyb3AxID0gdCAmIzQzOyAxMDAsIGRyb3AyID0gZHJvcDEgJiM0MzsgMTAwL3Nx cnQoMiksIGRyb3AzID0gZHJvcDIgJiM0MzsgMTAwL3NxcnQoMykgLi4uPG86cD48L286cD48L3A+ DQo8L2Rpdj4NCjxkaXY+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48bzpwPiZuYnNwOzwvbzpwPjwv cD4NCjwvZGl2Pg0KPGRpdj4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPkknbSBzY3JhdGNoaW5nIG15 IGhlYWQgYXQgdGhlIHdvcmRzIEknbSBsb29raW5nIGZvciB3aXRoIHJlZ2FyZCB0byBmYWlybmVz cy4gJm5ic3A7VGhvdWdoIEkgd291bGQgc2F5IHRoZSBmb2xsb3dpbmcgc2l0dWF0aW9uIHdvdWxk IGJlIHVuZmFpciB1dGlsaXphdGlvbi48bzpwPjwvbzpwPjwvcD4NCjwvZGl2Pg0KPGRpdj4NCjxw IGNsYXNzPSJNc29Ob3JtYWwiPjxvOnA+Jm5ic3A7PC9vOnA+PC9wPg0KPC9kaXY+DQo8ZGl2Pg0K PHAgY2xhc3M9Ik1zb05vcm1hbCI+VGhlIGZyYW1lIHJhdGUgaXMgMzBmcHMuICZuYnNwO1doaWNo IG1lYW5zIG5ldCBlZmZlY3QgdGhhdCBtZWRpYSBuZWVkcyB0byBiZSBkZWxpdmVyZWQgZXZlcnkg MzNtcy4gJm5ic3A7Tm93IGxldCdzIHNheSBpdCBzZW5kcyB0aGUgZmlyc3QgKGFuIEktRnJhbWUp IG91dCBvbiB0byB0aGUgd2lyZSB3aGljaCBjb21wb3NlcyBvZiAxNSBwYWNrZXRzLCB0aGUgZXhw ZWN0ZWQgcHJlc2VudGF0aW9uIHRpbWUgaXMgMzAwMCAoOTBLaHoNCiBjbG9jaykgb3IgMC4wMzMz MyBpbiByZWxhdGl2ZSBbZGVsYXkgYWRqdXN0ZWRdIGFic29sdXRlIHRpbWUuICZuYnNwO0J5IHRo ZSB0aW1lIHRoZSBmcmFtZSBhcnJpdmVzIGNvbXBsZXRlbHksIGl0J3MgMTgwMDAgKDkwa2h6KSBv ciAwLjIgW2RlbGF5IGFkanVzdGVkXSBhYnNvbHV0ZSB0aW1lLiAmbmJzcDtUaGUgbmV4dCBmcmFt ZSBhcnJpdmVzIGhhcyBhIHRpbWUgc3RhbXAgb2YgNjAwMCwgaXQgY29tcG9zZXMgb2YgNiBwYWNr ZXRzLCBhbmQgYXJyaXZlcyBpbiB0b3RhbA0KIGF0IDIzMDAwICg5MGtoeikgb3IgMC4yNTU1IGFi c29sdXRlIHRpbWUuICZuYnNwO0J5IHRoZSB0aW1lIHRoaXJkIGZyYW1lIGNvbWVzIGluICh0cz05 MDAwKSwgaXQncyBhcnJpdmFsIHRpbWUgaXMgMjgwMDAgKDkwa2h6KSBvciAwLjMxMTExIGFic29s dXRlIHRpbWUuPG86cD48L286cD48L3A+DQo8L2Rpdj4NCjxkaXY+DQo8cCBjbGFzcz0iTXNvTm9y bWFsIj48bzpwPiZuYnNwOzwvbzpwPjwvcD4NCjwvZGl2Pg0KPGRpdj4NCjxwIGNsYXNzPSJNc29O b3JtYWwiPklzbid0IHRoZXJlIHNvbWUgbWV0cmljIHdlIGNhbiB1c2UgdG8gcXVhbGlmeSB0aGlz IGJlaGF2aW9yPyAmbmJzcDtJIHdhcyB0aGlua2luZyB0aGUgQ29EZWwgY29udHJvbCBsYXcgdXNp bmcgc29tZSBjb21wYXJpc29uIGJldHdlZW4gZXhwZWN0ZWQgYXJyaXZhbCB0aW1lIGFuZCBhY3R1 YWwgYXJyaXZhbCB0aW1lLCBidXQgSSBzZWVtIHRvIGhhdmUgbG9zdCBteSB0aG91Z2h0LjxvOnA+ PC9vOnA+PC9wPg0KPC9kaXY+DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PG86cD4mbmJz cDs8L286cD48L3A+DQo8L2Rpdj4NCjxkaXY+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj5Tb3JyeSBv biB0aGUgQ29EZWwgbWlzdGFrZSwgc2VlbWVkIHNvIGNsZWFyIGF0IHRoZSB0aW1lLi4uPG86cD48 L286cD48L3A+DQo8L2Rpdj4NCjxkaXY+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48bzpwPiZuYnNw OzwvbzpwPjwvcD4NCjwvZGl2Pg0KPGRpdj4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPlRoYW5rcyw8 bzpwPjwvbzpwPjwvcD4NCjwvZGl2Pg0KPGRpdj4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPkRhbjxv OnA+PC9vOnA+PC9wPg0KPC9kaXY+DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PG86cD4m bmJzcDs8L286cD48L3A+DQo8L2Rpdj4NCjxkaXY+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48bzpw PiZuYnNwOzwvbzpwPjwvcD4NCjwvZGl2Pg0KPGRpdj4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxv OnA+Jm5ic3A7PC9vOnA+PC9wPg0KPC9kaXY+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48bzpwPiZu YnNwOzwvbzpwPjwvcD4NCjxkaXY+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj5PbiBUdWUsIE1heSAy OCwgMjAxMyBhdCAxMjo0MCBQTSwgS2V2aW4gR3Jvc3MgJmx0OzxhIGhyZWY9Im1haWx0bzprZXZp bi5ncm9zc0BhdmFudy5jb20iIHRhcmdldD0iX2JsYW5rIj5rZXZpbi5ncm9zc0BhdmFudy5jb208 L2E+Jmd0OyB3cm90ZTo8bzpwPjwvbzpwPjwvcD4NCjxkaXY+DQo8cCBjbGFzcz0iTXNvTm9ybWFs Ij5JIGRvbid0IGtub3cgd2hlcmUgeW91IGdldCB0aGUgaWRlYSB0aGF0IGNvZGVsIGRyb3BzIHBh Y2tldHMgaW4gYnVyc3RzLiBJdCBkcm9wcyBvbmUgcGFja2V0IHBlciAmcXVvdDtpbnRlcnZhbCZx dW90Oy4gJnF1b3Q7SW50ZXJ2YWwmcXVvdDsgc3RhcnRzIGF0IDEwMCBtcyBhbmQgaXMgcmVkdWNl ZCBzbG93bHkgKDcxLCA1OCwgNTAsIDQ1IG1zLi4uKSB1bnRpbCBjb25nZXN0aW9uIGFiYXRlcy4g Q29kZWwgaXMgZWZmZWN0aXZlIG9uIFRDUCBmbG93cw0KIGJlY2F1c2UgdGhlIGxvc3MgaGFwcGVu cyBwcm9tcHRseSwgbm90IGJlY2F1c2UgdGhlIGxvc3MgaXMgc3Vic3RhbnRpYWwuPG86cD48L286 cD48L3A+DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PG86cD4mbmJzcDs8L286cD48L3A+ DQo8L2Rpdj4NCjwvZGl2Pg0KPGJsb2NrcXVvdGUgc3R5bGU9ImJvcmRlcjpub25lO2JvcmRlci1s ZWZ0OnNvbGlkICNDQ0NDQ0MgMS4wcHQ7cGFkZGluZzowaW4gMGluIDBpbiA2LjBwdDttYXJnaW4t bGVmdDo0LjhwdDttYXJnaW4tcmlnaHQ6MGluIj4NCjxkaXY+DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1z b05vcm1hbCI+Q29kZWwgaXMgZGVzaWduZWQgdG8gYmUgYXBwbGllZCBvbiBhIHBlci1ob3AgYmFz aXMuIEkgZG9uJ3Qgc2VlIGhvdyBpdCBjYW4gYmUgYXBwbGllZCBhdCBhIHJlY2VpdmVyIGZvciBh biBlbmQtdG8tZW5kIGNvbm5lY3Rpb24gYXMgeW91IGFyZSBhcHBhcmVudGx5IHByb3Bvc2luZyBh bmQgc3RpbGwgYmVoYXZlIGFzIGdlbmVyYWxseSBpbnRlbmRlZCBieSBpdHMgaW52ZW50b3JzLjxv OnA+PC9vOnA+PC9wPg0KPC9kaXY+DQo8L2Rpdj4NCjwvYmxvY2txdW90ZT4NCjxibG9ja3F1b3Rl IHN0eWxlPSJib3JkZXI6bm9uZTtib3JkZXItbGVmdDpzb2xpZCAjQ0NDQ0NDIDEuMHB0O3BhZGRp bmc6MGluIDBpbiAwaW4gNi4wcHQ7bWFyZ2luLWxlZnQ6NC44cHQ7bWFyZ2luLXJpZ2h0OjBpbiI+ DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5bGU9ImNvbG9yOiM4ODg4ODgi PjxiciBjbGVhcj0iYWxsIj4NCjxzcGFuIGNsYXNzPSJob2VuemIiPjxvOnA+PC9vOnA+PC9zcGFu Pjwvc3Bhbj48L3A+DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5bGU9ImNv bG9yOiM4ODg4ODgiPktldmluIEdyb3NzPC9zcGFuPjxvOnA+PC9vOnA+PC9wPg0KPGRpdj4NCjxw IGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0eWxlPSJjb2xvcjojODg4ODg4Ij48YSBocmVmPSJ0 ZWw6JTJCMS0zMDMtNDQ3LTA1MTciIHRhcmdldD0iX2JsYW5rIj4mIzQzOzEtMzAzLTQ0Ny0wNTE3 PC9hPjxvOnA+PC9vOnA+PC9zcGFuPjwvcD4NCjwvZGl2Pg0KPGRpdj4NCjxwIGNsYXNzPSJNc29O b3JtYWwiPjxzcGFuIHN0eWxlPSJjb2xvcjojODg4ODg4Ij5NZWRpYSBOZXR3b3JrIENvbnN1bHRh bnQ8bzpwPjwvbzpwPjwvc3Bhbj48L3A+DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNw YW4gc3R5bGU9ImNvbG9yOiM4ODg4ODgiPkFWQSBOZXR3b3JrcyAtJm5ic3A7PGEgaHJlZj0iaHR0 cDovL3d3dy5hdmFudy5jb20vIiB0YXJnZXQ9Il9ibGFuayI+d3d3LkFWQW53LmNvbTwvYT4sJm5i c3A7PGEgaHJlZj0iaHR0cDovL3d3dy5YMTkyLm9yZyIgdGFyZ2V0PSJfYmxhbmsiPnd3dy5YMTky Lm9yZzwvYT48bzpwPjwvbzpwPjwvc3Bhbj48L3A+DQo8L2Rpdj4NCjwvZGl2Pg0KPC9kaXY+DQo8 ZGl2Pg0KPGRpdj4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiIHN0eWxlPSJtYXJnaW4tYm90dG9tOjEy LjBwdCI+PG86cD4mbmJzcDs8L286cD48L3A+DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+ T24gU2F0LCBNYXkgMjUsIDIwMTMgYXQgNTowNCBQTSwgRGFuIFdlYmVyICZsdDs8YSBocmVmPSJt YWlsdG86ZGFuQG1hcmtldHNvdXAuY29tIiB0YXJnZXQ9Il9ibGFuayI+ZGFuQG1hcmtldHNvdXAu Y29tPC9hPiZndDsgd3JvdGU6PG86cD48L286cD48L3A+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj5I aSBndXlzLDxicj4NCjxicj4NCkkndmUgYmVlbiByZXZpZXdpbmcgQ29EZWwsIGFuZCBpdCdzIGNs ZWFyIGhvdyBpdCB3b3JrcyByZWFzb25hYmx5IHdlbGwgZm9yIFRDUC4mbmJzcDsgSXQncyBvbmx5 IHNsaWdodGx5IG1vcmUgY29tcGxpY2F0ZWQgdGhhbiBhbiBpbXBsZW1lbnRhdGlvbiB1c2luZyBh IGZpeGVkIHRpbWVzdGFtcCBwZXIgcGFja2V0IGV4cGlyYXRpb24uJm5ic3A7IFRoZSBtaW5vciBk aWZmZXJlbmNlIG9jY3VycyB3aGVuIGl0IGdvZXMgaW50byBpdHMgZHJvcHBpbmcgc3RhdGUgd2hp Y2gNCiB1c2VzIGEgc3F1YXJlIHJvb3Qgc2NhbGluZyBmYWN0b3IgZm9yIHRoZSB0aW1lIGJhc2Vk IG9uIHRoZSBudW1iZXIgb2YgcHJldmlvdXNseSBkcm9wcGVkIHBhY2tldHMgaW4gYSBzZXF1ZW5j ZS4mbmJzcDsgVGhpcyB0YWtlcyBhZHZhbnRhZ2Ugb2YgYSBrbm93biBiZWhhdmlvciBvZiBUQ1Ag Y29uZ2VzdGlvbiBjb250cm9sIGFsZ29yaXRobXMgd2hpY2ggZXhwZWN0IGNvbmdlc3Rpb24gdG8g aGFwcGVuIGluIGxhcmdlIGJ1cnN0cy48YnI+DQo8YnI+DQpXaGVuIGFwcGxpZWQgdG8gUlRQIHVu a25vd2luZ2x5LCB0aGUgYmVoYXZpb3IgY291bGQgYmUgcHJldHR5IGRpc2FzdHJvdXMgb24gdmlk ZW8gY29udGVudC4mbmJzcDsgQWx0aG91Z2ggSSBkb3VidCBpdCdzIGFueSB3b3JzZSB0aGFuIGFj dHVhbCBjb21wZXRpbmcgY29udGVudCB3aXRoIG5vIEFRTSwgYSBwYXJ0aWN1bGFyIGNhc2UgZG9l cyBzdGFuZCBvdXQuJm5ic3A7IFdoZW4gQ29EZWwgaXMgaW4gcGxhY2Ugd2hlcmUgdGhlcmUgaXMg bm8gY29tcGV0aW5nIHRyYWZmaWMNCiBhbmQgdGhlIFJUUCBzZW5kZXIgYnVyc3RzIHRoZSB3aXJl IHdpdGhvdXQgcGFjaW5nIGluIHJlc3BlY3QgdG8gbWF4aW11bSBzdHJlYW0gYml0cmF0ZSwgQ29E ZWwgaXMgbGlrZWx5IHRvIGJ1cnN0IGRyb3AgcGFja2V0cyBiZWNhdXNlIG9mIG92ZXJmbG93IG9u IHRoZSBxdWV1ZSB0aW1lLiZuYnNwOyBJIHRoaW5rDQo8Yj50aGlzIGJlaGF2aW9yIGlzIGV4dHJl bWVseSBkZXNpcmFibGU8L2I+LiZuYnNwOyBUaGlzIHdpbGwgYnJpbmcgYXdhcmVuZXNzIHRvIGFs bCB2ZW5kb3JzIGFuZCBpbXBsZW1lbnRvcnMgdGhhdCB0aGVpciBpbXBsZW1lbnRhdGlvbnMgd2Vy ZSB3b3JraW5nIGRlc3BpdGUgdGhlIGZhY3QgdGhhdCB0aGV5IHdlcmUgaW1wcm9wZXIuJm5ic3A7 DQo8YnI+DQo8YnI+DQpUaGlzIGtpbmQgb2YgYmVoYXZpb3IgY2FuIGJlIGVuaGFuY2VkIGFuZCBh dWdtZW50ZWQgaW4gYSB3YXkgdGhhdCBjYW4gYmUgdXNlZCB0byBleHBlZGl0ZSB0aGUgaW1wbGVt ZW50YXRpb24gb2YgZWZmZWN0aXZlIFJUUCBDb25nZXN0aW9uIENvbnRyb2wuJm5ic3A7Jm5ic3A7 IElmIHdlIHdlcmUgdG8gaW1wbGVtZW50DQo8Yj5yZWNlaXZlciBzaWRlIENvRGVsPC9iPiA8Yj5m b3IgZHJvcHBpbmcgJnF1b3Q7ZnJhbWVzJnF1b3Q7IG9yICZxdW90O21lc3NhZ2VzJnF1b3Q7IG9m IFJUUCBwYWNrZXRzIG9uIG5ldyBpbXBsZW1lbnRhdGlvbnM8L2I+LCB3ZSBjb3VsZCBiZWNvbWUg dGhlICZxdW90O1NvdXAgTmF6aSZxdW90OyBhbmQgc3RhcnQgZWZmZWN0aXZlbHkgaWRlbnRpZnlp bmcgaW1wcm9wZXIgaW1wbGVtZW50YXRpb25zIGFzIHdlbGwgYXMgcmVuZGVyaW5nIHRoZW0gaW5v cGVyYWJsZS4mbmJzcDsNCjxiPklmIGltcGxlbWVudGVkIGJ5IG9uZSBvZiB0aGUgbWFqb3IgV2Vi UlRDIGJyb3dzZXIgaW1wbGVtZW50YXRpb25zLCA8L2I+YSA8Yj5jaGFpbiByZWFjdGlvbiBtYXkg ZGV2ZWxvcCB0aGF0IGZvcmNlcyBpbXBsZW1lbnRhdGlvbiBvZiBSVFAgY29uZ2VzdGlvbiBjb250 cm9sIHVwIHRoZSBwaXBlbGluZTwvYj4uJm5ic3A7IElmIHVzZWZ1bCBmZWVkYmFjayBpcyBkZWxp dmVyZWQgYmFjayB0byB0aGUgc2VuZGVyLCB3aGljaCByZWFsbHkgbmVlZHMgdG8gYmUNCiBuZXQg dHJhbnNsYXRlZCB0byA8Yj5mcmFtZXMgcHJvY2Vzc2VkIGFuZCBmcmFtZXMgZHJvcHBlZDwvYj4s IGFuIGFwcGxpY2F0aW9uIHdpdGggaXRzIGVuY29kZXIgY291bGQgcmVhc29uYWJseSBhZGp1c3Qu Jm5ic3A7DQo8Yj5UaGlzIG1heSBzb2x2ZSBmYWlybmVzcyByZWxhdGVkIHByb2JsZW1zIGJlY2F1 c2UgdGhlIHJlY2VpdmVyIGNvdWxkIGlkZW50aWZ5IGlmIHRoZSBzZW5kZXIgb3ZlcmZsb3dlZCB0 aGUgcXVldWVzIGJ5IGV2YWx1YXRpbmcgYWN0dWFsIGFycml2YWwgdGltZSBjb21wYXJlZCB3aXRo IGZyYW1lIHByZXNlbnRhdGlvbiB0aW1lIChjb252ZXJ0ZWQgUlRQIHRpbWVzdGFtcHMpLjwvYj4m bmJzcDsgSWYgdGhlIHJlY2VpdmVyIGVuZm9yY2VzIHRoaXMgY29uc3RyYWludCwNCiBmYWlybmVz cyBvbiBSVFAgc3RyZWFtcyBpcyBlZmZlY3RpdmVseSBpbiBmb3JjZSBiZWNhdXNlIGltcGxlbWVu dGF0aW9ucyBhcmUgcmVuZGVyZWQgaW5vcGVyYWJsZSwgYW5kIGl0IHdvcmtzIHNhZmVseSB3aXRo aW4gdGhlIHNjb3BlIG9mIENvRGVsLiZuYnNwOyBUaGlzIGltcGxpZXMgdGhhdCBUQ1Agd291bGQg YmUgb25seSBhdCBtb3N0IGFmZmVjdGVkIGluIHRoZSBzYW1lIHdheSB0aGF0IGFub3RoZXIgVENQ IHN0cmVhbSB3b3VsZC4mbmJzcDsNCjxicj4NCjxicj4NCkFuZCBmaW5hbGx5IHRoaXMgbGVhZHMg dG8gbXkgc3VnZ2VzdGVkIHNvbHV0aW9uIGZvciBzZW5kZXIgc2lkZSBjb25nZXN0aW9uIGNvbnRy b2wuJm5ic3A7IEJhc2VkIG9uIG15IGFzc3VtcHRpb24gdGhhdCBDb0RlbCBpbXBsZW1lbnRhdGlv biBmb3IgQVFNIGlzIG9uIHRoZSBob3Jpem9uIGFjcm9zcyByb3V0ZXJzIGluIHRoZSBuZXh0IDUg dG8gMTAgeWVhcnMsIGEgcmVhc29uYWJsZSBzdWdnZXN0aW9uIGZvciBSVFAgQ29uZ2VzdGlvbiBj b250cm9sIG1heQ0KIGxlYWQgdG8gQ29EZWwgb3ZlciBDb0RlbC4mbmJzcDsgQW4gZW5oYW5jZWQg dmVyc2lvbiBvZiBDb0RlbCBmb3IgaW1wbGVtZW50YXRpb24gaW4gdGhlIFJUUCBzdGFjayAob3Ig YXQgdGhlIGNvZGVjIGVuY2Fwc3VsYXRpb24gbGF5ZXIpIHByb3ZpZGVzIGNsZWFyIGZyYW1lIGRl bWFyY2F0aW9uIGFuZCBwYWNrZXQgbWFwcGluZyAoZnJhbWUgbm8gPT0gcGFja2V0cyBuLi5tKSwg YW5kIGRyb3BzIGVudGlyZSBmcmFtZXMgYmFzZWQgb246IGFuIGFzc3VtcHRpb24NCiAob3IgZGV0 ZXJtaW5hdGlvbikgb2YgdGFyZ2V0ZWQgbWF4aW11bSBiYW5kd2lkdGggYW5kIChvcHRpb25hbCwg YnV0IGhpZ2hseSByZWNvbW1lbmRlZCkgc29tZSBmb3JtIG9mIEVDTi4mbmJzcDsgTm90aWZpY2F0 aW9ucyBhcmUgdGhlbiBwcm92aWRlZCBiYWNrIHRvIHRoZSBhcHBsaWNhdGlvbiBhcyB0byB3aGlj aCBmcmFtZXMgd2VyZSBkcm9wcGVkLCBhbmQgdGhlIGFwcGxpY2F0aW9uIGNhbiBtYWtlIHRoZSBk ZWNpc2lvbiBvbiBob3cgaXQgc2Vla3MgdG8NCiBjaGFuZ2UgaXRzIGJlaGF2aW9yIGlmIGF0IGFs bCBbVGhpcyBjb21iaW5lcyB3ZWxsIHdpdGggdGhlIHJlY2VpdmVyIGJhc2VkIG5vdGlmaWNhdGlv bi4mbmJzcDsgSWYgaXQgY2hvb3NlcyBub3QgdG8sIHRoZSBSVFAgc3RhY2sgZW5mb3JjZXMgJnF1 b3Q7ZmFpcm5lc3MmcXVvdDsgYnkgZGVncmFkaW5nIHRoZSBhcHBsaWNhdGlvbiBwZXJmb3JtYW5j ZSBpbiBmdWxsIHVuaXRzLiZuYnNwOyBBIGdvb2QgaW1wbGVtZW50YXRpb24gb2YgdGhpcyBzaG91 bGQNCjxiPnVzZSBGRUMgdG8gbWFpbnRhaW4gYSBjb25zdGFudCBiaXRyYXRlIGRlc3BpdGUgdGhl IHZhcmlhdGlvbnMgb2YgdGhlIGJpdHJhdGUgaW4gdGhlIHVuZGVybHlpbmcgc3RyZWFtLiZuYnNw Ow0KPC9iPldoaWxlIGl0IGRvZXMgdXNlIG1vcmUgYmFuZHdpZHRoIHRoYW4gPGk+aW1tZWRpYXRl bHkgbmVjZXNzYXJ5PC9pPiBpdCBwcm92aWRlcyBncmVhdCBzdGFiaWxpdHkgZm9yIHRoZSBzdHJl YW0gaW4NCjxiPmNvb3BlcmF0aW9uIHdpdGggYm90aCBsb25nIGxpdmVkIFRDUCBzdHJlYW1zIGFu ZCBzaG9ydCBsaXZlZCBidXJzdHkgc3RyZWFtczwvYj4uJm5ic3A7IEl0IGFsc28NCjxiPnByZXZl bnRzIHVuZmFpciBjb21wZXRpdGlvbiBmcm9tIFRDUDwvYj4uJm5ic3A7IEluIGFkZGl0aW9uLCBp dCA8Yj5wcm92aWRlcyBhZGRpdGlvbmFsIHJlc2lsaWVuY3kgZm9yIGhhbmRsaW5nIGludGVybWl0 dGVudCBwYWNrZXRzIGxvc3M8L2I+IGZyb20gV2lGaSBhbmQgb3RoZXIgd2lyZWxlc3MvY2VsbHVs YXIgdHJhbnNtaXNzaW9ucy48YnI+DQo8YnI+DQpJIHRoaW5rIHRoZSBiZW5lZml0cyBvZiB0aGlz IHNvbHV0aW9uIG91dHdlaWdoIGFueSBvdGhlciB0aGF0IGhhcyBiZWVuIHByb3Bvc2VkLCBhbmQg c29sdmVzIG1hbnkgb2YgdGhlIGRpZmZpY3VsdCBjaGFsbGVuZ2VzIHByZXNlbnRlZC4mbmJzcDsg V2hpbGUgSSBoYXZlIG5vdCB5ZXQgYnVpbGQgYSBmdWxsIHdvcmtpbmcgbW9kZWwsIEl0IHNob3Vs ZCB3b3JrIGluIGF0IGxlYXN0IGFzIG1hbnkgcGxhY2VzIGFzIENvRGVsIHdvcmtzLCBhbmQgbXVj aCByZXNlYXJjaA0KIGhhcyBiZWVuIGRvbmUgYW5kIGNvbnRpbnVlcyB0byBiZSBkb25lIG9uIGhv dyB3ZWxsIENvRGVsIGhhbmRsZXMgZmFpcm5lc3MuPGJyPg0KPGJyPg0KSSB3b3VsZCBsb3ZlIHRv IGhlYXIgZXZlcnlvbmUncyB0aG91Z2h0cyBvbiB0aGlzLiZuYnNwOyBQbGVhc2Ugc2VuZCBtZSB5 b3VyIGZlZWRiYWNrLjxicj4NCjxicj4NClRoYW5rcyw8YnI+DQpEYW48bzpwPjwvbzpwPjwvcD4N CjwvZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PG86cD4mbmJzcDs8L286cD48L3A+DQo8L2Rp dj4NCjwvZGl2Pg0KPC9kaXY+DQo8L2Jsb2NrcXVvdGU+DQo8L2Rpdj4NCjxwIGNsYXNzPSJNc29O b3JtYWwiPjxvOnA+Jm5ic3A7PC9vOnA+PC9wPg0KPC9kaXY+DQo8L2JvZHk+DQo8L2h0bWw+DQo= --_000_D21571530BF9644D9A443D6BD95B91031556C061xmbrcdx12ciscoc_-- From prvs=28610ae442=zaheduzzaman.sarker@ericsson.com Wed May 29 07:44:48 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 4EFFA21F9023 for ; Wed, 29 May 2013 07:44:48 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -6.248 X-Spam-Level: X-Spam-Status: No, score=-6.248 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, HELO_EQ_SE=0.35, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_MED=-4] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id i1pnlyHr6opi for ; Wed, 29 May 2013 07:44:42 -0700 (PDT) Received: from mailgw7.ericsson.se (mailgw7.ericsson.se [193.180.251.48]) by ietfa.amsl.com (Postfix) with ESMTP id 906A421F8FE8 for ; Wed, 29 May 2013 07:44:41 -0700 (PDT) X-AuditID: c1b4fb30-b7f9e6d000002643-ac-51a6145884c0 Received: from esessmw0256.eemea.ericsson.se (Unknown_Domain [153.88.253.125]) by mailgw7.ericsson.se (Symantec Mail Security) with SMTP id 24.7B.09795.85416A15; Wed, 29 May 2013 16:44:40 +0200 (CEST) Received: from [150.132.141.88] (153.88.115.8) by esessmw0256.eemea.ericsson.se (153.88.115.97) with Microsoft SMTP Server id 8.3.279.1; Wed, 29 May 2013 16:44:40 +0200 Message-ID: <51A61457.5070806@ericsson.com> Date: Wed, 29 May 2013 16:44:39 +0200 From: Zaheduzzaman Sarker Organization: Ericsson AB User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64; rv:17.0) Gecko/20130509 Thunderbird/17.0.6 MIME-Version: 1.0 To: "Michael Ramalho (mramalho)" References: In-Reply-To: Content-Type: multipart/alternative; boundary="------------050507000808000309070905" X-Brightmail-Tracker: H4sIAAAAAAAAA+NgFjrELMWRmVeSWpSXmKPExsUyM+JvrW6EyLJAg1MvxC1mLzC3eHGonc3i /Wd+i9U3P7A5sHj8u7qd2WPK742sHkuW/GTymH9jPWsASxS3TVJiSVlwZnqevl0Cd8aD798Y Cy5/YKxY8HAjSwPjyxWMXYycHBICJhKHFt6GssUkLtxbz9bFyMUhJHCKUWLRxw3sEM4aRolT szuYQKp4BbQl9s9rYAexWQRUJW7emwTUwcHBJmAj8XixH0iYX0BSYkPDbmYQW1QgSmLOugds EK2CEidnPmEBsUUETCWWXd3ACmIzC6RKdPT0go0UFjCXuLTvDtQRs5kk7h5cAFbEKeArsXR2 L1RDmMS8XTvB9goJ6Ep0vYybwCg4C8mKWUiqIGwLicVvDrJD2PISzVtnM0PYGhIL7uxjRBZf wMi2ipE9NzEzJ73cfBMjMAoObvltsINx032xQ4zSHCxK4rz6vIsDhQTSE0tSs1NTC1KL4otK c1KLDzEycXCCCC6pBsYFc2yDlVedsbj56Oa5NEmH89O2lPzL2hT+JZbDZ9k0B5s8q5iPpy/f Mbgp5tO65mEw/yfhAwt+Lgk35FQo8rqSlJzq9+7M606rq0s3nthl3cjWPmPDVaUt+79wVTb8 s1wk/Px8QsXWe3V7pTe7h5h5+ff5rZ56mq1cQfDmCYeEoOs8p0788WFSYinOSDTUYi4qTgQA +NetBFUCAAA= Cc: Dan Weber , Kevin Gross , rmcat WG Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 29 May 2013 14:44:48 -0000 --------------050507000808000309070905 Content-Type: text/plain; charset="UTF-8"; format=flowed Content-Transfer-Encoding: 8bit > Back in the day of IntSev, we had VBR TSPECS in which you could define > your flow’s bursting via a token bucket representation (i.e., > characterization) of the envelope of your expected rate variability. > That is, if you characterized YOUR APPLICATION and provided “the > Network” with a VBR TSPEC (via RSVP) … and that TSPEC was accepted by > an end-to-end IntServ-capable network … you would have exactly what > you want! However, none of this is being proposed here (IntServ/RSVP > and even AQMs are somewhat out-of-scope for RMCAT – although I agree > discussing them in the context of RMCAT makes sense). > I would not say that discussing the effect of AQMs are out of scope for RMCAT. I think in the requirements it says a RMCAT solution need to work when AQM = true. > > Given these constraints, it appears unreasonable for the RMCAT > protocol to explicitly accommodate your idea of fairness precisely > because we are not assuming the ability to signal the network as to > your applications bursting profile. > +1 > > I think we need to get out of the situation where we consider fairness > in the context of anyone’s pet-application (yours is apparently some > video application running at 30 fps). The RMCAT transport protocol > should be agnostic to today’s applications as possible (real-time 3D > holography will be here before you know it!). > > As a parting aside, video encoder vendors are quickly realizing the > benefits of generating as smooth a video source as possible and to > pace their output to the wire. > from adaptation point of view, when the congestion control algorithm is recommending an available bandwidth value to the encoder it should actually allow some headroom for "applications bursting profile" and VBR nature of video source. > > Off Soapbox, > > Michael Ramalho > > *From:*rmcat-bounces@ietf.org [mailto:rmcat-bounces@ietf.org] *On > Behalf Of *Dan Weber > *Sent:* Tuesday, May 28, 2013 5:59 PM > *To:* Kevin Gross > *Cc:* rmcat WG > *Subject:* Re: [rmcat] "Soup Nazi" RTP Congestion Control > > You're right. I made a mistake in my interpretation of this. I missed > the part that the next drop is a solid step into the future. drop1 = > t + 100, drop2 = drop1 + 100/sqrt(2), drop3 = drop2 + 100/sqrt(3) ... > > I'm scratching my head at the words I'm looking for with regard to > fairness. Though I would say the following situation would be unfair > utilization. > > The frame rate is 30fps. Which means net effect that media needs to > be delivered every 33ms. Now let's say it sends the first (an > I-Frame) out on to the wire which composes of 15 packets, the expected > presentation time is 3000 (90Khz clock) or 0.03333 in relative [delay > adjusted] absolute time. By the time the frame arrives completely, > it's 18000 (90khz) or 0.2 [delay adjusted] absolute time. The next > frame arrives has a time stamp of 6000, it composes of 6 packets, and > arrives in total at 23000 (90khz) or 0.2555 absolute time. By the > time third frame comes in (ts=9000), it's arrival time is 28000 > (90khz) or 0.31111 absolute time. > > Isn't there some metric we can use to qualify this behavior? I was > thinking the CoDel control law using some comparison between expected > arrival time and actual arrival time, but I seem to have lost my thought. > > Sorry on the CoDel mistake, seemed so clear at the time... > > Thanks, > > Dan > > On Tue, May 28, 2013 at 12:40 PM, Kevin Gross > wrote: > > I don't know where you get the idea that codel drops packets in > bursts. It drops one packet per "interval". "Interval" starts at 100 > ms and is reduced slowly (71, 58, 50, 45 ms...) until congestion > abates. Codel is effective on TCP flows because the loss happens > promptly, not because the loss is substantial. > > Codel is designed to be applied on a per-hop basis. I don't see > how it can be applied at a receiver for an end-to-end connection > as you are apparently proposing and still behave as generally > intended by its inventors. > > > Kevin Gross > > +1-303-447-0517 > > Media Network Consultant > > AVA Networks - www.AVAnw.com , www.X192.org > > > On Sat, May 25, 2013 at 5:04 PM, Dan Weber > wrote: > > Hi guys, > > I've been reviewing CoDel, and it's clear how it works reasonably > well for TCP. It's only slightly more complicated than an > implementation using a fixed timestamp per packet expiration. The > minor difference occurs when it goes into its dropping state which > uses a square root scaling factor for the time based on the number > of previously dropped packets in a sequence. This takes advantage > of a known behavior of TCP congestion control algorithms which > expect congestion to happen in large bursts. > > When applied to RTP unknowingly, the behavior could be pretty > disastrous on video content. Although I doubt it's any worse than > actual competing content with no AQM, a particular case does stand > out. When CoDel is in place where there is no competing traffic > and the RTP sender bursts the wire without pacing in respect to > maximum stream bitrate, CoDel is likely to burst drop packets > because of overflow on the queue time. I think *this behavior is > extremely desirable*. This will bring awareness to all vendors > and implementors that their implementations were working despite > the fact that they were improper. > > This kind of behavior can be enhanced and augmented in a way that > can be used to expedite the implementation of effective RTP > Congestion Control. If we were to implement *receiver side > CoDel* *for dropping "frames" or "messages" of RTP packets on new > implementations*, we could become the "Soup Nazi" and start > effectively identifying improper implementations as well as > rendering them inoperable. *If implemented by one of the major > WebRTC browser implementations, *a *chain reaction may develop > that forces implementation of RTP congestion control up the > pipeline*. If useful feedback is delivered back to the sender, > which really needs to be net translated to *frames processed and > frames dropped*, an application with its encoder could reasonably > adjust. *This may solve fairness related problems because the > receiver could identify if the sender overflowed the queues by > evaluating actual arrival time compared with frame presentation > time (converted RTP timestamps).* If the receiver enforces this > constraint, fairness on RTP streams is effectively in force > because implementations are rendered inoperable, and it works > safely within the scope of CoDel. This implies that TCP would be > only at most affected in the same way that another TCP stream would. > > And finally this leads to my suggested solution for sender side > congestion control. Based on my assumption that CoDel > implementation for AQM is on the horizon across routers in the > next 5 to 10 years, a reasonable suggestion for RTP Congestion > control may lead to CoDel over CoDel. An enhanced version of > CoDel for implementation in the RTP stack (or at the codec > encapsulation layer) provides clear frame demarcation and packet > mapping (frame no == packets n..m), and drops entire frames based > on: an assumption (or determination) of targeted maximum bandwidth > and (optional, but highly recommended) some form of ECN. > Notifications are then provided back to the application as to > which frames were dropped, and the application can make the > decision on how it seeks to change its behavior if at all [This > combines well with the receiver based notification. If it chooses > not to, the RTP stack enforces "fairness" by degrading the > application performance in full units. A good implementation of > this should *use FEC to maintain a constant bitrate despite the > variations of the bitrate in the underlying stream. *While it does > use more bandwidth than /immediately necessary/ it provides great > stability for the stream in *cooperation with both long lived TCP > streams and short lived bursty streams*. It also *prevents unfair > competition from TCP*. In addition, it *provides additional > resiliency for handling intermittent packets loss* from WiFi and > other wireless/cellular transmissions. > > I think the benefits of this solution outweigh any other that has > been proposed, and solves many of the difficult challenges > presented. While I have not yet build a full working model, It > should work in at least as many places as CoDel works, and much > research has been done and continues to be done on how well CoDel > handles fairness. > > I would love to hear everyone's thoughts on this. Please send me > your feedback. > > Thanks, > Dan > -- Zahed ================================================== ANM ZAHEDUZZAMAN SARKER Ericsson AB Multimedia Technologies Laboratoriegränd 11 97128 Luleå, Sweden Phone +46 10 717 37 43 Fax +46 920 996 21 SMS/MMS +46 76 115 37 43 zaheduzzaman.sarker@ericsson.com www.ericsson.com ================================================== --------------050507000808000309070905 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: 8bit

 

Back in the day of IntSev, we had VBR TSPECS in which you could define your flow’s bursting via a token bucket representation (i.e., characterization) of the envelope of your expected rate variability. That is, if you characterized YOUR APPLICATION and provided “the Network” with a VBR TSPEC (via RSVP) … and that TSPEC was accepted by an end-to-end IntServ-capable network … you would have exactly what you want! However, none of this is being proposed here (IntServ/RSVP and even AQMs are somewhat out-of-scope for RMCAT – although I agree discussing them in the context of RMCAT makes sense).

I would not say that discussing the effect of AQMs are out of scope for RMCAT. I think in the requirements it says a RMCAT solution need to work when AQM = true.

 

Given these constraints, it appears unreasonable for the RMCAT protocol to explicitly accommodate your idea of fairness precisely because we are not assuming the ability to signal the network as to your applications bursting profile.

+1

 

I think we need to get out of the situation where we consider fairness in the context of anyone’s pet-application (yours is apparently some video application running at 30 fps). The RMCAT transport protocol should be agnostic to today’s applications as possible (real-time 3D holography will be here before you know it!).

 

As a parting aside, video encoder vendors are quickly realizing the benefits of generating as smooth a video source as possible and to pace their output to the wire.

from adaptation point of view, when the congestion control algorithm is recommending an available bandwidth value to the encoder it should actually allow some headroom for "applications bursting profile" and VBR nature of video source.

 

Off Soapbox,

 

Michael Ramalho

 

 

From: rmcat-bounces@ietf.org [mailto:rmcat-bounces@ietf.org] On Behalf Of Dan Weber
Sent: Tuesday, May 28, 2013 5:59 PM
To: Kevin Gross
Cc: rmcat WG
Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control

 

You're right. I made a mistake in my interpretation of this.  I missed the part that the next drop is a solid step into the future.   drop1 = t + 100, drop2 = drop1 + 100/sqrt(2), drop3 = drop2 + 100/sqrt(3) ...

 

I'm scratching my head at the words I'm looking for with regard to fairness.  Though I would say the following situation would be unfair utilization.

 

The frame rate is 30fps.  Which means net effect that media needs to be delivered every 33ms.  Now let's say it sends the first (an I-Frame) out on to the wire which composes of 15 packets, the expected presentation time is 3000 (90Khz clock) or 0.03333 in relative [delay adjusted] absolute time.  By the time the frame arrives completely, it's 18000 (90khz) or 0.2 [delay adjusted] absolute time.  The next frame arrives has a time stamp of 6000, it composes of 6 packets, and arrives in total at 23000 (90khz) or 0.2555 absolute time.  By the time third frame comes in (ts=9000), it's arrival time is 28000 (90khz) or 0.31111 absolute time.

 

Isn't there some metric we can use to qualify this behavior?  I was thinking the CoDel control law using some comparison between expected arrival time and actual arrival time, but I seem to have lost my thought.

 

Sorry on the CoDel mistake, seemed so clear at the time...

 

Thanks,

Dan

 

 

 

 

On Tue, May 28, 2013 at 12:40 PM, Kevin Gross <kevin.gross@avanw.com> wrote:

I don't know where you get the idea that codel drops packets in bursts. It drops one packet per "interval". "Interval" starts at 100 ms and is reduced slowly (71, 58, 50, 45 ms...) until congestion abates. Codel is effective on TCP flows because the loss happens promptly, not because the loss is substantial.

 

Codel is designed to be applied on a per-hop basis. I don't see how it can be applied at a receiver for an end-to-end connection as you are apparently proposing and still behave as generally intended by its inventors.


Kevin Gross

Media Network Consultant

AVA Networks - www.AVAnw.com, www.X192.org

 

On Sat, May 25, 2013 at 5:04 PM, Dan Weber <dan@marketsoup.com> wrote:

Hi guys,

I've been reviewing CoDel, and it's clear how it works reasonably well for TCP.  It's only slightly more complicated than an implementation using a fixed timestamp per packet expiration.  The minor difference occurs when it goes into its dropping state which uses a square root scaling factor for the time based on the number of previously dropped packets in a sequence.  This takes advantage of a known behavior of TCP congestion control algorithms which expect congestion to happen in large bursts.

When applied to RTP unknowingly, the behavior could be pretty disastrous on video content.  Although I doubt it's any worse than actual competing content with no AQM, a particular case does stand out.  When CoDel is in place where there is no competing traffic and the RTP sender bursts the wire without pacing in respect to maximum stream bitrate, CoDel is likely to burst drop packets because of overflow on the queue time.  I think this behavior is extremely desirable.  This will bring awareness to all vendors and implementors that their implementations were working despite the fact that they were improper. 

This kind of behavior can be enhanced and augmented in a way that can be used to expedite the implementation of effective RTP Congestion Control.   If we were to implement receiver side CoDel for dropping "frames" or "messages" of RTP packets on new implementations, we could become the "Soup Nazi" and start effectively identifying improper implementations as well as rendering them inoperable.  If implemented by one of the major WebRTC browser implementations, a chain reaction may develop that forces implementation of RTP congestion control up the pipeline.  If useful feedback is delivered back to the sender, which really needs to be net translated to frames processed and frames dropped, an application with its encoder could reasonably adjust.  This may solve fairness related problems because the receiver could identify if the sender overflowed the queues by evaluating actual arrival time compared with frame presentation time (converted RTP timestamps).  If the receiver enforces this constraint, fairness on RTP streams is effectively in force because implementations are rendered inoperable, and it works safely within the scope of CoDel.  This implies that TCP would be only at most affected in the same way that another TCP stream would. 

And finally this leads to my suggested solution for sender side congestion control.  Based on my assumption that CoDel implementation for AQM is on the horizon across routers in the next 5 to 10 years, a reasonable suggestion for RTP Congestion control may lead to CoDel over CoDel.  An enhanced version of CoDel for implementation in the RTP stack (or at the codec encapsulation layer) provides clear frame demarcation and packet mapping (frame no == packets n..m), and drops entire frames based on: an assumption (or determination) of targeted maximum bandwidth and (optional, but highly recommended) some form of ECN.  Notifications are then provided back to the application as to which frames were dropped, and the application can make the decision on how it seeks to change its behavior if at all [This combines well with the receiver based notification.  If it chooses not to, the RTP stack enforces "fairness" by degrading the application performance in full units.  A good implementation of this should use FEC to maintain a constant bitrate despite the variations of the bitrate in the underlying stream.  While it does use more bandwidth than immediately necessary it provides great stability for the stream in cooperation with both long lived TCP streams and short lived bursty streams.  It also prevents unfair competition from TCP.  In addition, it provides additional resiliency for handling intermittent packets loss from WiFi and other wireless/cellular transmissions.

I think the benefits of this solution outweigh any other that has been proposed, and solves many of the difficult challenges presented.  While I have not yet build a full working model, It should work in at least as many places as CoDel works, and much research has been done and continues to be done on how well CoDel handles fairness.

I would love to hear everyone's thoughts on this.  Please send me your feedback.

Thanks,
Dan

 

 


-- 

Zahed

==================================================
ANM ZAHEDUZZAMAN SARKER 


Ericsson AB
Multimedia Technologies
Laboratoriegränd 11
97128 Luleå, Sweden
Phone +46 10 717 37 43
Fax +46 920 996 21
SMS/MMS +46 76 115 37 43
zaheduzzaman.sarker@ericsson.com
www.ericsson.com

==================================================
--------------050507000808000309070905-- From dan@marketsoup.com Wed May 29 08:33:26 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id B0ABD21F9399 for ; Wed, 29 May 2013 08:33:24 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -1.68 X-Spam-Level: X-Spam-Status: No, score=-1.68 tagged_above=-999 required=5 tests=[AWL=1.296, BAYES_00=-2.599, FM_FORGED_GMAIL=0.622, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_LOW=-1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id G4txxvj-lcrt for ; Wed, 29 May 2013 08:33:17 -0700 (PDT) Received: from mail-qe0-f53.google.com (mail-qe0-f53.google.com [209.85.128.53]) by ietfa.amsl.com (Postfix) with ESMTP id 06A3A21F9206 for ; Wed, 29 May 2013 08:32:05 -0700 (PDT) Received: by mail-qe0-f53.google.com with SMTP id s14so5218605qeb.12 for ; Wed, 29 May 2013 08:32:05 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=marketsoup.com; s=google; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type; bh=BtYR0sS+NCINfoldbcQpWsMfrYcpnlrbtjZbh0Tb5iI=; b=Jpb77jzc3vu2gSRs5y3IaCNPuCdOkSoShzUS5dj1ZaVYG6o24h+0F0FtlkDkj8ghws Zlg9gCyntsmZy4QtioCm1fOcPXKxCubpSd5Q/J/5qQ62qeBiWSGV0QdFChTPxLpRp2Uz qicaZKV2essMxPisIMDqrpA8W8E4FnDnuRY5A= X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type:x-gm-message-state; bh=BtYR0sS+NCINfoldbcQpWsMfrYcpnlrbtjZbh0Tb5iI=; b=ClatYZgrMCJBSgGXM0WaDt2k4Ejmt1EZmzzg9JAo/8pY0fLJo51m9xcNJe0OGrUhjx 4DedufKoaoZbMTpLbapC3FVDwo9HJqBVAC+2trULP/vafOAWRMP+OUErPHxdEmhCza9+ eolXiVfOMl37Wt1CalUwGt4sxACw2kWcICsAdH4gF7Zus7UalE1/P55j2J2DUXwwkQZ3 2rz6L1swEmoDBkijgdW4c83uABLYm2Xx/ps2UzDW5Ykhteb9tAeIVGalYDGkS0uC2HDD CrjW9yk2vKAwTEFOD5ZKcKi1IO9oHK9Sbst0lP34vVocP3aGQLZ4wq7lUjWkNOHGofMM DQ/Q== MIME-Version: 1.0 X-Received: by 10.229.69.34 with SMTP id x34mr1160229qci.75.1369841525034; Wed, 29 May 2013 08:32:05 -0700 (PDT) Received: by 10.224.70.146 with HTTP; Wed, 29 May 2013 08:32:04 -0700 (PDT) X-Originating-IP: [174.51.153.161] In-Reply-To: References: <8C48B86A895913448548E6D15DA7553B8FADD8@xmb-rcd-x09.cisco.com> <8C48B86A895913448548E6D15DA7553B8FB058@xmb-rcd-x09.cisco.com> Date: Wed, 29 May 2013 09:32:04 -0600 Message-ID: From: Dan Weber To: "Ali C. Begen (abegen)" Content-Type: multipart/alternative; boundary=00032557fa1e7fc78d04dddd15bf X-Gm-Message-State: ALoCoQnjKfBji/NT2cpt3p5KGm7FDflUBns5EkJq0hOpxYlNme/TSt2RR2wM4xfXUAq4qQMr95H3 Cc: rmcat WG , "Fred Baker \(fred\)" , Kevin Gross Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 29 May 2013 15:33:26 -0000 --00032557fa1e7fc78d04dddd15bf Content-Type: text/plain; charset=UTF-8 On Wed, May 29, 2013 at 4:41 AM, Ali C. Begen (abegen) wrote: > > On May 29, 2013, at 1:15 AM, Dan Weber wrote: > > > I think the behavior is right if the RTP congestion control mechanism > drops the entire frame and notifies the application it wouldn't be > delivered within the appropriate time frame. The mechanism by which it > determines this is still open for discussion. I particularly liked the > thought that if any one packet of the frame would have to wait in the user > space RTP packet queue (i.e. while pacing) for sending and exceeded a > certain threshold (e.g. 100ms scaled down), then the entire frame should be > dropped. > > I dont think that is the right move. There are so many skilled > receiver-side concealment algorithms that can deal with the loss of a few > packets. but if you drop the entire frame, until the encoder deals with > that, you will likely be in serious trouble. And you will likely have > wasted all the bits you already transmitted successfully for that > particular frame. > > OTOH, it is true that if you miss certain header info, the remaining bits > are useless for that slice/frame/GOP/etc. but do you really think that the > middle boxes should investigate the bitstream in that detail? This looks to > me as a non-starter. > > My concern with this is that the application layer is often stupid. Even if you decide to transmit the frame, and then drop the packets towards the end of the frame, the application should be notified of the affected frame. I think it' is unreasonable to expect the application designers to be experts on both the network layer and the application layer as well as RTP. Many of us speaking here have had the fortunate benefit of working on all of these, but we're more the exception to the rule. The mechanism that is developed needs to have intuitive behavior for the the implementers of the other layers so that they can adequately adjust. We know for certain that no mechanism that does not include feedback to the other layers is not worthwhile in meeting RMCAT objectives. Although, I think we can all agree that an effective congestion control should have a clearly defined unit of work that is more application specific. I've used "frame" and "message" somewhat interchangeably, and I think this puts things in the proper perspective. Thanks, Dan --00032557fa1e7fc78d04dddd15bf Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable



On Wed, May 29, 2013 at 4:41 AM, Ali C. Begen (abegen) <abegen@cisc= o.com> wrote:

On May 29, 2013, at 1:15 AM, Dan Weber <dan@marketsoup.com> wrote:

> I think the behavior is right if the RTP congestion control mechanism = drops the entire frame and notifies the application it wouldn't be deli= vered within the appropriate time frame. =C2=A0The mechanism by which it de= termines this is still open for discussion. =C2=A0I particularly liked the = thought that if any one packet of the frame would have to wait in the user = space RTP packet queue (i.e. while pacing) for sending and exceeded a certa= in threshold (e.g. 100ms scaled down), then the entire frame should be drop= ped.

I dont think that is the right move. There are so many skilled receiv= er-side concealment algorithms that can deal with the loss of a few packets= . but if you drop the entire frame, until the encoder deals with that, you = will likely be in serious trouble. And you will likely have wasted all the = bits you already transmitted successfully for that particular frame.

OTOH, it is true that if you miss certain header info, the remaining bits a= re useless for that slice/frame/GOP/etc. but do you really think that the m= iddle boxes should investigate the bitstream in that detail? This looks to = me as a non-starter.

My concern with this is that the application layer is often stupid. = =C2=A0Even if you decide to transmit the frame, and then drop the packets t= owards the end of the frame, the application should be notified of the affe= cted frame. =C2=A0I think it' is unreasonable =C2=A0to expect the appli= cation designers to be experts on both the network layer and the applicatio= n layer as well as RTP. =C2=A0Many of us speaking here have had the fortuna= te benefit of working on all of these, but we're more the exception to = the rule. =C2=A0 The mechanism that is developed needs to have intuitive be= havior for the the implementers of the other layers so that they can adequa= tely adjust. =C2=A0We know for certain that no mechanism that does not incl= ude feedback to the other layers is not worthwhile in meeting RMCAT objecti= ves.

Although, I think we can all agree that an = effective congestion control should have a clearly defined unit of work tha= t is more application specific. =C2=A0I've used "frame" and &= quot;message" somewhat interchangeably, and I think this puts things i= n the proper perspective.

Thanks,
Dan

=
--00032557fa1e7fc78d04dddd15bf-- From dan@marketsoup.com Wed May 29 08:44:25 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 97D0221F946F for ; Wed, 29 May 2013 08:44:25 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -1.639 X-Spam-Level: X-Spam-Status: No, score=-1.639 tagged_above=-999 required=5 tests=[AWL=0.737, BAYES_00=-2.599, FM_FORGED_GMAIL=0.622, HTML_MESSAGE=0.001, J_CHICKENPOX_44=0.6, RCVD_IN_DNSWL_LOW=-1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id oyUk7+GsMXqk for ; Wed, 29 May 2013 08:44:21 -0700 (PDT) Received: from mail-qe0-f51.google.com (mail-qe0-f51.google.com [209.85.128.51]) by ietfa.amsl.com (Postfix) with ESMTP id C27CB21F8F6D for ; Wed, 29 May 2013 08:44:20 -0700 (PDT) Received: by mail-qe0-f51.google.com with SMTP id nd7so5258333qeb.10 for ; Wed, 29 May 2013 08:44:20 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=marketsoup.com; s=google; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type; bh=oPZn6jenjxQEaHlkZWDM1oaiqfcCOxVyt2JFshlmwFI=; b=UESFOfzPt/vKzEr4oD6qVsVUn/iRzuKZixLNinnzOca428VQWCQWwBTwij0y+1I8mV xxP8BiNIcqQDasjgs4VWR8uyfu0cPbrrGUL1HjTuX7k5OgSwWDS9cNLoSnexW2R7pbF1 ctatj//s+14RgqTNr0FAxor7SPBVCh1x4W+Kk= X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type:x-gm-message-state; bh=oPZn6jenjxQEaHlkZWDM1oaiqfcCOxVyt2JFshlmwFI=; b=Ph/tKotPmtmaKZOvkue6E0Rvfv8/mLjAbo5/Cpm84TuzoX3ZAUP0u0UqJVJ49trAW+ ui4nLgf3A9hJkzVK6NLF6F9JrjGW2zX/2r2kkEjNOkHyzhJDHjQzkMbUfG55mZH6mPVW 4UqKmLfdHcmJGcec90TBEvx33Rq4REunS22g1A7qswSmnFzngtDmDNFXyWGFilcIvsSq FvGYuUM2MQQxKbHf8kxpjQ9jkmewqMQQSvEtt5A16QNYcOvJBFJI9jMoODvKa/pXB2p6 G7lzDPf6l3X/MoFZGMhjF5CnLj7AwySlE4EtBGHpy8fBfOyCvz2LbkzJOO/Av3yUlHiJ O0lw== MIME-Version: 1.0 X-Received: by 10.229.136.68 with SMTP id q4mr1177551qct.54.1369842259910; Wed, 29 May 2013 08:44:19 -0700 (PDT) Received: by 10.224.70.146 with HTTP; Wed, 29 May 2013 08:44:19 -0700 (PDT) X-Originating-IP: [174.51.153.161] In-Reply-To: References: Date: Wed, 29 May 2013 09:44:19 -0600 Message-ID: From: Dan Weber To: "Michael Ramalho (mramalho)" Content-Type: multipart/alternative; boundary=00248c6a65664d00b704dddd41aa X-Gm-Message-State: ALoCoQn0Qfo+disvloMp5UJzOdtT1t0iKdboxlWWRshOVG2SUYTtikwU+uGHxK8hFfj7KFCpWSOT Cc: rmcat WG , Kevin Gross Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 29 May 2013 15:44:25 -0000 --00248c6a65664d00b704dddd41aa Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: quoted-printable On Wed, May 29, 2013 at 8:12 AM, Michael Ramalho (mramalho) < mramalho@cisco.com> wrote: > Dan,**** > > ** ** > > Thanks for all the chatter your post resulted in ;-).**** > > ** ** > > One of the reasons why I proposed that the initial RMCAT candidates are > tested in an environment where sources are smooth (i.e., producing data a= t > the envelope of the estimated available bit rate) is that fairness is ver= y > difficult to quantify with a variable bit rate source with arbitrary > peak/instantaneous rate to average rate ratios.**** > > ** > I'm sold on this point. This is a paradoxical situation. Each sender sends data who has no real control over the underlying media stream. When the behavior changes, everyone thinks its their fault and beings to adjust accordingly. It's kind of like being in a situation where someone snapped at you because they were having a bad day, and you take it personally because you thought it was your doing. In reality, you didn't know that it was truly outside of your control, but responded anyway. This behavior isn't helpful, and we should do what we can to minimize it. > ** > > > Given these constraints, it appears unreasonable for the RMCAT protocol t= o > explicitly accommodate your idea of fairness precisely because we are not > assuming the ability to signal the network as to your applications bursti= ng > profile.**** > > ** ** > > I think we need to get out of the situation where we consider fairness in > the context of anyone=E2=80=99s pet-application (yours is apparently some= video > application running at 30 fps). The RMCAT transport protocol should be > agnostic to today=E2=80=99s applications as possible (real-time 3D hologr= aphy will > be here before you know it!).**** > > ** > Point taken. > ** > > As a parting aside, video encoder vendors are quickly realizing the > benefits of generating as smooth a video source as possible and to pace > their output to the wire. > Maybe we should consider an additional RFC to present recommendations for audio/video codec implementations on best practice behavior for support in a real time media environment. > **** > > ** ** > > Off Soapbox,**** > > ** ** > > Michael Ramalho**** > > ** ** > > ** ** > > *From:* rmcat-bounces@ietf.org [mailto:rmcat-bounces@ietf.org] *On Behalf > Of *Dan Weber > *Sent:* Tuesday, May 28, 2013 5:59 PM > *To:* Kevin Gross > *Cc:* rmcat WG > *Subject:* Re: [rmcat] "Soup Nazi" RTP Congestion Control**** > > ** ** > > You're right. I made a mistake in my interpretation of this. I missed th= e > part that the next drop is a solid step into the future. drop1 =3D t + = 100, > drop2 =3D drop1 + 100/sqrt(2), drop3 =3D drop2 + 100/sqrt(3) ...**** > > ** ** > > I'm scratching my head at the words I'm looking for with regard to > fairness. Though I would say the following situation would be unfair > utilization.**** > > ** ** > > The frame rate is 30fps. Which means net effect that media needs to be > delivered every 33ms. Now let's say it sends the first (an I-Frame) out = on > to the wire which composes of 15 packets, the expected presentation time = is > 3000 (90Khz clock) or 0.03333 in relative [delay adjusted] absolute time. > By the time the frame arrives completely, it's 18000 (90khz) or 0.2 [del= ay > adjusted] absolute time. The next frame arrives has a time stamp of 6000= , > it composes of 6 packets, and arrives in total at 23000 (90khz) or 0.2555 > absolute time. By the time third frame comes in (ts=3D9000), it's arriva= l > time is 28000 (90khz) or 0.31111 absolute time.**** > > ** ** > > Isn't there some metric we can use to qualify this behavior? I was > thinking the CoDel control law using some comparison between expected > arrival time and actual arrival time, but I seem to have lost my thought.= * > *** > > ** ** > > Sorry on the CoDel mistake, seemed so clear at the time...**** > > ** ** > > Thanks,**** > > Dan**** > > ** ** > > ** ** > > ** ** > > ** ** > > On Tue, May 28, 2013 at 12:40 PM, Kevin Gross > wrote:**** > > I don't know where you get the idea that codel drops packets in bursts. I= t > drops one packet per "interval". "Interval" starts at 100 ms and is reduc= ed > slowly (71, 58, 50, 45 ms...) until congestion abates. Codel is effective > on TCP flows because the loss happens promptly, not because the loss is > substantial.**** > > ** ** > > Codel is designed to be applied on a per-hop basis. I don't see how it > can be applied at a receiver for an end-to-end connection as you are > apparently proposing and still behave as generally intended by its > inventors.**** > > > **** > > Kevin Gross**** > > +1-303-447-0517**** > > Media Network Consultant**** > > AVA Networks - www.AVAnw.com , www.X192.org**** > > ** ** > > On Sat, May 25, 2013 at 5:04 PM, Dan Weber wrote:***= * > > Hi guys, > > I've been reviewing CoDel, and it's clear how it works reasonably well fo= r > TCP. It's only slightly more complicated than an implementation using a > fixed timestamp per packet expiration. The minor difference occurs when = it > goes into its dropping state which uses a square root scaling factor for > the time based on the number of previously dropped packets in a sequence. > This takes advantage of a known behavior of TCP congestion control > algorithms which expect congestion to happen in large bursts. > > When applied to RTP unknowingly, the behavior could be pretty disastrous > on video content. Although I doubt it's any worse than actual competing > content with no AQM, a particular case does stand out. When CoDel is in > place where there is no competing traffic and the RTP sender bursts the > wire without pacing in respect to maximum stream bitrate, CoDel is likely > to burst drop packets because of overflow on the queue time. I think *th= is > behavior is extremely desirable*. This will bring awareness to all > vendors and implementors that their implementations were working despite > the fact that they were improper. > > This kind of behavior can be enhanced and augmented in a way that can be > used to expedite the implementation of effective RTP Congestion Control. > If we were to implement *receiver side CoDel* *for dropping "frames" or > "messages" of RTP packets on new implementations*, we could become the > "Soup Nazi" and start effectively identifying improper implementations as > well as rendering them inoperable. *If implemented by one of the major > WebRTC browser implementations, *a *chain reaction may develop that > forces implementation of RTP congestion control up the pipeline*. If > useful feedback is delivered back to the sender, which really needs to be > net translated to *frames processed and frames dropped*, an application > with its encoder could reasonably adjust. *This may solve fairness > related problems because the receiver could identify if the sender > overflowed the queues by evaluating actual arrival time compared with fra= me > presentation time (converted RTP timestamps).* If the receiver enforces > this constraint, fairness on RTP streams is effectively in force because > implementations are rendered inoperable, and it works safely within the > scope of CoDel. This implies that TCP would be only at most affected in > the same way that another TCP stream would. > > And finally this leads to my suggested solution for sender side congestio= n > control. Based on my assumption that CoDel implementation for AQM is on > the horizon across routers in the next 5 to 10 years, a reasonable > suggestion for RTP Congestion control may lead to CoDel over CoDel. An > enhanced version of CoDel for implementation in the RTP stack (or at the > codec encapsulation layer) provides clear frame demarcation and packet > mapping (frame no =3D=3D packets n..m), and drops entire frames based on:= an > assumption (or determination) of targeted maximum bandwidth and (optional= , > but highly recommended) some form of ECN. Notifications are then provide= d > back to the application as to which frames were dropped, and the > application can make the decision on how it seeks to change its behavior = if > at all [This combines well with the receiver based notification. If it > chooses not to, the RTP stack enforces "fairness" by degrading the > application performance in full units. A good implementation of this > should *use FEC to maintain a constant bitrate despite the variations of > the bitrate in the underlying stream. *While it does use more bandwidth > than *immediately necessary* it provides great stability for the stream > in *cooperation with both long lived TCP streams and short lived bursty > streams*. It also *prevents unfair competition from TCP*. In addition, > it *provides additional resiliency for handling intermittent packets loss= *from WiFi and other wireless/cellular transmissions. > > I think the benefits of this solution outweigh any other that has been > proposed, and solves many of the difficult challenges presented. While I > have not yet build a full working model, It should work in at least as ma= ny > places as CoDel works, and much research has been done and continues to b= e > done on how well CoDel handles fairness. > > I would love to hear everyone's thoughts on this. Please send me your > feedback. > > Thanks, > Dan**** > > ** ** > > ** ** > --00248c6a65664d00b704dddd41aa Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable



On Wed, May 29, 2013 at 8:12 AM, Michael Ramalho (mramalho) <mram= alho@cisco.com> wrote:

Dan,

=C2=A0

Thanks for all the chatter your post resulted in ;-).=

=C2=A0

One of the reasons why I proposed that the initial RM= CAT candidates are tested in an environment where sources are smooth (i.e.,= producing data at the envelope of the estimated available bit rate) is that fairness is very difficult to= quantify with a variable bit rate source with arbitrary peak/instantaneous= rate to average rate ratios.

I'm sold on this point. =C2=A0This is a paradoxical situation. =C2=A0E= ach sender sends data who has no real control over the underlying media str= eam. =C2=A0When the behavior changes, everyone thinks its their fault and b= eings to adjust accordingly. =C2=A0It's kind of like being in a situati= on where someone snapped at you because they were having a bad day, and you= take it personally because you thought it was your doing. =C2=A0In reality= , you didn't know that it was truly outside of your control, but respon= ded anyway. =C2=A0This behavior isn't helpful, and we should do what we= can to minimize it. =C2=A0

=C2=A0


Given these constraints, it appears unreasonable for = the RMCAT protocol to explicitly accommodate your idea of fairness precisel= y because we are not assuming the ability to signal the network as to your applications bursting profile= .

=C2=A0

I think we need to get out of the situation where we = consider fairness in the context of anyone=E2=80=99s pet-application (yours= is apparently some video application running at 30 fps). The RMCAT transport protocol should be agnostic to tod= ay=E2=80=99s applications as possible (real-time 3D holography will be here= before you know it!).

Point taken.=C2=A0

=C2=A0

As a parting aside, video encoder vendors are quickly= realizing the benefits of generating as smooth a video source as possible = and to pace their output to the wire.

Maybe we should consider= an additional RFC to present recommendations for audio/video codec impleme= ntations on best practice behavior for support in a real time media environ= ment.=C2=A0

=C2=A0

Off Soapbox,

=C2=A0

Michael Ramalho

=C2=A0

=C2=A0

From: rmcat-bou= nces@ietf.org [mailto:rmcat-bounces@ietf.org] On Behalf Of Dan Weber
Sent: Tuesday, May 28, 2013 5:59 PM
To: Kevin Gross
Cc: rmcat WG
Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control=

=C2=A0

You're right. I made a mistake in my interpretation of th= is. =C2=A0I missed the part that the next drop is a solid step into the fut= ure. =C2=A0 drop1 =3D t + 100, drop2 =3D drop1 + 100/sqrt(2), drop3 =3D dro= p2 + 100/sqrt(3) ...

=C2=A0

I'm scratching my head at the words I'm looking for w= ith regard to fairness. =C2=A0Though I would say the following situation wo= uld be unfair utilization.

=C2=A0

The frame rate is 30fps. =C2=A0Which means net effect that me= dia needs to be delivered every 33ms. =C2=A0Now let's say it sends the = first (an I-Frame) out on to the wire which composes of 15 packets, the exp= ected presentation time is 3000 (90Khz clock) or 0.03333 in relative [delay adjusted] absolute time. =C2=A0By the= time the frame arrives completely, it's 18000 (90khz) or 0.2 [delay ad= justed] absolute time. =C2=A0The next frame arrives has a time stamp of 600= 0, it composes of 6 packets, and arrives in total at 23000 (90khz) or 0.2555 absolute time. =C2=A0By the time third frame co= mes in (ts=3D9000), it's arrival time is 28000 (90khz) or 0.31111 absol= ute time.

=C2=A0

Isn't there some metric we can use to qualify this behavi= or? =C2=A0I was thinking the CoDel control law using some comparison betwee= n expected arrival time and actual arrival time, but I seem to have lost my= thought.

=C2=A0

Sorry on the CoDel mistake, seemed so clear at the time...=

=C2=A0

Thanks,

Dan

=C2=A0

=C2=A0

=C2=A0

=C2=A0

On Tue, May 28, 2013 at 12:40 PM, Kevin Gross <kevin.gross@avanw.com&g= t; wrote:

I don't know where you get the idea that codel drops pack= ets in bursts. It drops one packet per "interval". "Interval= " starts at 100 ms and is reduced slowly (71, 58, 50, 45 ms...) until = congestion abates. Codel is effective on TCP flows because the loss happens promptly, not because the loss is substantial.=

=C2=A0

Codel is designed to be applied on a per-hop basis. I don'= ;t see how it can be applied at a receiver for an end-to-end connection as = you are apparently proposing and still behave as generally intended by its = inventors.


Kevin Gross<= /u>

Media Network Consulta= nt

AVA Networks -=C2=A0www.AVAnw.com,=C2=A0<= a href=3D"http://www.X192.org" target=3D"_blank">www.X192.org=

=C2=A0

On Sat, May 25, 2013 at 5:04 PM, Dan Weber <dan@marketsoup.com> wrote:=

Hi guys,

I've been reviewing CoDel, and it's clear how it works reasonably w= ell for TCP.=C2=A0 It's only slightly more complicated than an implemen= tation using a fixed timestamp per packet expiration.=C2=A0 The minor diffe= rence occurs when it goes into its dropping state which uses a square root scaling factor for the time based on the number of prev= iously dropped packets in a sequence.=C2=A0 This takes advantage of a known= behavior of TCP congestion control algorithms which expect congestion to h= appen in large bursts.

When applied to RTP unknowingly, the behavior could be pretty disastrous on= video content.=C2=A0 Although I doubt it's any worse than actual compe= ting content with no AQM, a particular case does stand out.=C2=A0 When CoDe= l is in place where there is no competing traffic and the RTP sender bursts the wire without pacing in respect to maximum st= ream bitrate, CoDel is likely to burst drop packets because of overflow on = the queue time.=C2=A0 I think this behavior is extremely desirable.=C2=A0 This will bring awarenes= s to all vendors and implementors that their implementations were working d= espite the fact that they were improper.=C2=A0

This kind of behavior can be enhanced and augmented in a way that can be us= ed to expedite the implementation of effective RTP Congestion Control.=C2= =A0=C2=A0 If we were to implement receiver side CoDel for dropping "frames" or "mess= ages" of RTP packets on new implementations, we could become the &= quot;Soup Nazi" and start effectively identifying improper implementat= ions as well as rendering them inoperable.=C2=A0 If implemented by one of the major WebRTC browser implementations, a= chain reaction may develop that forces implementation of RTP congestion= control up the pipeline.=C2=A0 If useful feedback is delivered back to= the sender, which really needs to be net translated to frames processed and frames dropped, an applicati= on with its encoder could reasonably adjust.=C2=A0 This may solve fairness related problems because the receiver could iden= tify if the sender overflowed the queues by evaluating actual arrival time = compared with frame presentation time (converted RTP timestamps).=C2=A0= If the receiver enforces this constraint, fairness on RTP streams is effectively in force because implementations ar= e rendered inoperable, and it works safely within the scope of CoDel.=C2=A0= This implies that TCP would be only at most affected in the same way that = another TCP stream would.=C2=A0

And finally this leads to my suggested solution for sender side congestion = control.=C2=A0 Based on my assumption that CoDel implementation for AQM is = on the horizon across routers in the next 5 to 10 years, a reasonable sugge= stion for RTP Congestion control may lead to CoDel over CoDel.=C2=A0 An enhanced version of CoDel for implement= ation in the RTP stack (or at the codec encapsulation layer) provides clear= frame demarcation and packet mapping (frame no =3D=3D packets n..m), and d= rops entire frames based on: an assumption (or determination) of targeted maximum bandwidth and (optional, but highly= recommended) some form of ECN.=C2=A0 Notifications are then provided back = to the application as to which frames were dropped, and the application can= make the decision on how it seeks to change its behavior if at all [This combines well with the receiver based = notification.=C2=A0 If it chooses not to, the RTP stack enforces "fair= ness" by degrading the application performance in full units.=C2=A0 A = good implementation of this should use FEC to maintain a constant bitrate despite the variations of the bit= rate in the underlying stream.=C2=A0 While it does use more bandwidth than immediately necessary it p= rovides great stability for the stream in cooperation with both long lived TCP streams and short lived bursty stre= ams.=C2=A0 It also prevents unfair competition from TCP.=C2=A0 In addition, it provi= des additional resiliency for handling intermittent packets loss from W= iFi and other wireless/cellular transmissions.

I think the benefits of this solution outweigh any other that has been prop= osed, and solves many of the difficult challenges presented.=C2=A0 While I = have not yet build a full working model, It should work in at least as many= places as CoDel works, and much research has been done and continues to be done on how well CoDel handles fairness.=

I would love to hear everyone's thoughts on this.=C2=A0 Please send me = your feedback.

Thanks,
Dan

=C2=A0

=C2=A0


--00248c6a65664d00b704dddd41aa-- From mzanaty@cisco.com Wed May 29 08:56:43 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 5528021F8EBB for ; Wed, 29 May 2013 08:56:43 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -10.599 X-Spam-Level: X-Spam-Status: No, score=-10.599 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, RCVD_IN_DNSWL_HI=-8] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id Ls0YyqJnznhU for ; Wed, 29 May 2013 08:56:38 -0700 (PDT) Received: from rcdn-iport-7.cisco.com (rcdn-iport-7.cisco.com [173.37.86.78]) by ietfa.amsl.com (Postfix) with ESMTP id 2BE0021F93F0 for ; Wed, 29 May 2013 08:56:38 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=441; q=dns/txt; s=iport; t=1369842998; x=1371052598; h=from:to:subject:date:message-id:references:in-reply-to: content-transfer-encoding:mime-version; bh=8LxOt/6xHp3Oz/VeD4vGAk7i3sPw4nks6yXwNd3JEso=; b=DDYr16WKNjLANDj8mGwu+MK8113ewGLOhRMjtEqUZ3DIA4z7i79zzQu7 2CR2QXt4IARPaVrHUUsr1bDunu+9YjemB646PuvZmRUfgKlqgP2hcXUpT 9On43aEcOezkT66tEk6MkwLo/uSVka5h6zwcBKbYf65yec545Tqxdz/PQ 8=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: AoMIAI8kplGtJXG8/2dsb2JhbABAGoMJMIJ0vwqBChZtB4IkAQEEOk8CAQgiFBAyJQIEG4gFDDK6FgSNX4EDOIJ2YQOoe4FYgTeCJw X-IronPort-AV: E=Sophos;i="4.87,765,1363132800"; d="scan'208";a="216293108" Received: from rcdn-core2-1.cisco.com ([173.37.113.188]) by rcdn-iport-7.cisco.com with ESMTP; 29 May 2013 15:56:34 +0000 Received: from xhc-aln-x06.cisco.com (xhc-aln-x06.cisco.com [173.36.12.80]) by rcdn-core2-1.cisco.com (8.14.5/8.14.5) with ESMTP id r4TFuYJU023911 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL) for ; Wed, 29 May 2013 15:56:34 GMT Received: from xmb-rcd-x14.cisco.com ([169.254.4.194]) by xhc-aln-x06.cisco.com ([173.36.12.80]) with mapi id 14.02.0318.004; Wed, 29 May 2013 10:56:33 -0500 From: "Mo Zanaty (mzanaty)" To: "rmcat@ietf.org" Thread-Topic: [rmcat] RMCAT Eval Design Team 13 May UTC 15:00-16:00 (4pm London, 11am New York) Thread-Index: AQHOT9dQnc+eVI98Qk+teOhDHvoC1ZkcaQKA Date: Wed, 29 May 2013 15:56:33 +0000 Message-ID: <3879D71E758A7E4AA99A35DD8D41D3D91D47D95C@xmb-rcd-x14.cisco.com> References: In-Reply-To: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [64.102.88.107] Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: quoted-printable MIME-Version: 1.0 Subject: Re: [rmcat] RMCAT Eval Design Team 13 May UTC 15:00-16:00 (4pm London, 11am New York) X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 29 May 2013 15:56:43 -0000 The recording of this meeting is available below. Topic: RMCAT Eval Design Team-20130513 1505-1 Monday, May 13, 2013 11:00 AM EDT (UTC-4) New York Time 58 minutes, 120.31 MB Streaming recording link: https://cisco.webex.com/ciscosales/ldr.php?AT=3Dpb&SP=3DMC&rID=3D68177092&r= Key=3D47e2081d5fe85152 Download recording link: https://cisco.webex.com/ciscosales/lsr.php?AT=3Ddw&SP=3DMC&rID=3D68177092&r= Key=3D208ef3be6f4a346a From dan@marketsoup.com Wed May 29 11:17:14 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id B733B21F9695 for ; Wed, 29 May 2013 11:17:09 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -2.062 X-Spam-Level: X-Spam-Status: No, score=-2.062 tagged_above=-999 required=5 tests=[AWL=0.914, BAYES_00=-2.599, FM_FORGED_GMAIL=0.622, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_LOW=-1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id sjCRHDfyUZdp for ; Wed, 29 May 2013 11:17:04 -0700 (PDT) Received: from mail-qe0-f50.google.com (mail-qe0-f50.google.com [209.85.128.50]) by ietfa.amsl.com (Postfix) with ESMTP id EEC3D21F968E for ; Wed, 29 May 2013 11:17:03 -0700 (PDT) Received: by mail-qe0-f50.google.com with SMTP id x7so5240018qeu.23 for ; Wed, 29 May 2013 11:17:03 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=marketsoup.com; s=google; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type; bh=DMwym+b4h9i66TSo4RbCMSC2K/TdueHn/ty6yEIA/xM=; b=INANURDATkH51Tu0z0eY/qtOWLIeyxcszffw2Fcd6CrOd/2zbbMoODsJrBimRmwIx5 uGxKmUdkm95JNNJuqU3PC+/TeDztXDaMiBYkvWsEnCQ8JhWSMYVFD5n9W2RRYrN3UYMg ufpX0iPI6PqlLn6PouHVnLrKeSi7+Mho5bGXs= X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:x-originating-ip:in-reply-to:references:date :message-id:subject:from:to:cc:content-type:x-gm-message-state; bh=DMwym+b4h9i66TSo4RbCMSC2K/TdueHn/ty6yEIA/xM=; b=U8WBXWUI4PhDQ65j1Fv6fBTsEXeeaIV8m6Qrvdl9bknGoalLkUuQURoBYv3v5Q2Iu5 4Dq/bBgrFx5QrjzpKlj/hexO+vKgSpSSdht1im/MoF915Nc6VXs5P9Tr7bVnq0YxWj+W S6Mhsy/10gzVkj1m23vNzhdVvj7h8XLxOj2usVYdwemYNTiPhgiMDjFbcsUS3OlhOyHI O6FEHYC+uQ6Qlo1GTuJ86/iPsmkjBQ2JAIj45On/82IetPvh4DS8kW+N2s8bGm8kn+pD Q2+J/qkyeYTCOWXkzTn4LfOjOEYmSRd97PhYRXmlw+b17FUI7ddE4VQvuDpYTzZlu0Dj seEg== MIME-Version: 1.0 X-Received: by 10.224.41.3 with SMTP id m3mr4127192qae.53.1369851423232; Wed, 29 May 2013 11:17:03 -0700 (PDT) Received: by 10.224.70.146 with HTTP; Wed, 29 May 2013 11:17:03 -0700 (PDT) X-Originating-IP: [174.51.153.161] In-Reply-To: References: Date: Wed, 29 May 2013 12:17:03 -0600 Message-ID: From: Dan Weber To: "Michael Ramalho (mramalho)" Content-Type: multipart/alternative; boundary=001a11c2b1327a288e04dddf6341 X-Gm-Message-State: ALoCoQlMf4orCRZ/QfqBv1oV78HbAaBIa8DyT1AHFT9oARvKHfbEghXCFRE1k9lUYF9TRcDzOyfE Cc: "rmcat@ietf.org" Subject: Re: [rmcat] RMCAT Eval Design Team 13 May UTC 15:00-16:00 (4pm London, 11am New York) X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 29 May 2013 18:17:14 -0000 --001a11c2b1327a288e04dddf6341 Content-Type: text/plain; charset=UTF-8 Is it X rated? On Mon, May 13, 2013 at 6:41 AM, Michael Ramalho (mramalho) < mramalho@cisco.com> wrote: > WARNING: contains banned part > --001a11c2b1327a288e04dddf6341 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
Is it X rated?

On Mon, May 13, 2013 at 6:41 AM, Michael Ramalh= o (mramalho) <mramalho@cisco.com> wrote:
WARNING: contains banned part

--001a11c2b1327a288e04dddf6341-- From mzanaty@cisco.com Wed May 29 15:28:33 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 0657121F966E for ; Wed, 29 May 2013 15:28:33 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -10.598 X-Spam-Level: X-Spam-Status: No, score=-10.598 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_HI=-8] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id hixJzseuHb61 for ; Wed, 29 May 2013 15:28:18 -0700 (PDT) Received: from rcdn-iport-8.cisco.com (rcdn-iport-8.cisco.com [173.37.86.79]) by ietfa.amsl.com (Postfix) with ESMTP id B1B5E21F9545 for ; Wed, 29 May 2013 15:28:04 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=17046; q=dns/txt; s=iport; t=1369866487; x=1371076087; h=from:to:subject:date:message-id:references:in-reply-to: mime-version; bh=dEXdmGBeNaqTclTnMvjjCP8inX+mioxjZB+jEYczrs8=; b=hdK14LEyw5BluayAJLwgwtQFcoUCrjAbI6Ytd1HuQOw1N4hORbZnTqtX VJ+PtgBWHrX5zTYJdakYn3UxQu2EelVJGE4TbzaDi3gtApvpO/cxz/4H8 fjr7iGYRZcJNeORy4ySx5UhaBM+zzqE6UzZJdn7a6VhQaFpTqF+WqNFVF o=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: Ao8GAOd/plGtJV2Y/2dsb2JhbABagkVEMIM7vk0NehZ0giMBAQEEIwo7CBkCAQgRBAEBCx0DAgICMBQJCAIEAQkJCBOHcqdvkheOYjcBgkMzYQOTL5VMgw+CJw X-IronPort-AV: E=Sophos;i="4.87,766,1363132800"; d="scan'208,217";a="216465660" Received: from rcdn-core-1.cisco.com ([173.37.93.152]) by rcdn-iport-8.cisco.com with ESMTP; 29 May 2013 22:27:53 +0000 Received: from xhc-rcd-x02.cisco.com (xhc-rcd-x02.cisco.com [173.37.183.76]) by rcdn-core-1.cisco.com (8.14.5/8.14.5) with ESMTP id r4TMRrLa007832 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL); Wed, 29 May 2013 22:27:53 GMT Received: from xmb-rcd-x14.cisco.com ([169.254.4.194]) by xhc-rcd-x02.cisco.com ([173.37.183.76]) with mapi id 14.02.0318.004; Wed, 29 May 2013 17:27:53 -0500 From: "Mo Zanaty (mzanaty)" To: Dan Weber , "rmcat@ietf.org" Thread-Topic: [rmcat] Variable Bitrate Impact on Congestion Control Thread-Index: AQHOXAU6qY5z23+0D0yWlqGUOGppaJkcuqnQ Date: Wed, 29 May 2013 22:27:52 +0000 Message-ID: <3879D71E758A7E4AA99A35DD8D41D3D91D47DD52@xmb-rcd-x14.cisco.com> References: In-Reply-To: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [10.82.245.93] Content-Type: multipart/alternative; boundary="_000_3879D71E758A7E4AA99A35DD8D41D3D91D47DD52xmbrcdx14ciscoc_" MIME-Version: 1.0 Subject: Re: [rmcat] Variable Bitrate Impact on Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 29 May 2013 22:28:33 -0000 --_000_3879D71E758A7E4AA99A35DD8D41D3D91D47DD52xmbrcdx14ciscoc_ Content-Type: text/plain; charset="utf-8" Content-Transfer-Encoding: base64 SGkgRGFuLA0KDQpJIHdvdWxkIGNhdXRpb24gYWdhaW5zdCBhbnkgYXBwcm9hY2ggdGhhdCBzYXlz IFZCUiBsZWF2ZXMgYXZhaWxhYmxlIGJhbmR3aWR0aCBvbiB0aGUgdGFibGUgZm9yIG90aGVycyB0 byBlYXQsIHNvIGVhdCBpdCB5b3Vyc2VsZiB3aXRoIEZFQy4gV2hlbiB0aGVyZSBhcmUgbWFueSBm bG93cywgdGhlIHN0YXQtbXV4IGFkdmFudGFnZXMgb2YgVkJSIG1heGltaXplIGJhbmR3aWR0aCBl ZmZpY2llbmN5LiBGRUMgc2hvdWxkIGJlIGFwcGxpZWQgaW4gcHJvcG9ydGlvbiB0byBleHBlY3Rl ZCBsb3NzIChvciBtb3JlIHByZWNpc2VseSwgZXhwZWN0ZWQgZWZmZWN0aXZlIHBvc3QtRkVDIHJl Y292ZXJ5KSwgbm90IGdyZWVkIG9yIGdsdXR0b255Lg0KDQpNbw0KDQoNCkZyb206IHJtY2F0LWJv dW5jZXNAaWV0Zi5vcmcgW21haWx0bzpybWNhdC1ib3VuY2VzQGlldGYub3JnXSBPbiBCZWhhbGYg T2YgRGFuIFdlYmVyDQpTZW50OiBUdWVzZGF5LCBNYXkgMjgsIDIwMTMgODo0MSBQTQ0KVG86IHJt Y2F0QGlldGYub3JnDQpTdWJqZWN0OiBbcm1jYXRdIFZhcmlhYmxlIEJpdHJhdGUgSW1wYWN0IG9u IENvbmdlc3Rpb24gQ29udHJvbA0KDQpJdCdzIGltcG9ydGFudCB0byBub3RlIHRoZSByb2xlIHRo YXQgdmFyaWFibGUgYml0cmF0ZSBwbGF5cyBpbiBjb25nZXN0aW9uIGNvbnRyb2wuICBJIGtub3cg d2UndmUgZGlzY3Vzc2VkIHRoaXMgb24gc29tZSBsZXZlbCwgYnV0IGluIHJlYWxpdHksIGFueSBk ZWNpc2lvbiB0aGF0J3MgbWFkZSB3aGVuIHRoZSB1bmRlcmx5aW5nIG1lZGl1bSBjb250aW51b3Vz bHkgY2hhbmdlcyBjaGFyYWN0ZXJpc3RpY3MgaXMgYW4gdW5yZWxpYWJsZSBvbmUuICBJZiB1c2Vk IHdpdGggYW55IHNvcnQgb2YgaW5zdGFudGFuZW91cyBtZWFzdXJlLCBpdCBjYW4gZ2l2ZSB5b3Ug dW5yZWFsaXN0aWMgZXhwZWN0YXRpb25zIG9mIGNhcGFjaXR5Lg0KDQpKdXN0IGNvbnNpZGVyIGEg bGFyZ2UgZmlsZSB0cmFuc2ZlciBvZiBUQ1Agb3ZlciB0aGUgbmV0d29yay4gIEl0IG1heSBzYXd0 b290aCB1cCBhbmQgZG93biBhIGJpdCwgYnV0IGl0IHVzdWFsbHkgc3RhYmlsaXplcyB0byBhIGNl cnRhaW4gbGV2ZWwuICBOb3cgaWYgeW91J3ZlIGdvdCBhIDMvMyBtYml0IGxpbmssIHlvdSBoYXZl IGEgdmlkZW8gY2FsbCBnb2luZyB3aXRoIGEgbWF4IHJhdGUgb2YgMS41bWJpdC9zIGJpZGlyZWN0 aW9uYWxseSwgYW5kIHlvdSdyZSB1cGxvYWRpbmcgb3IgZG93bmxvYWRpbmcgdGhlIGxhdGVzdCBE VkQgaXNvIG9mIFVidW50dSwgeW91ciB2aWRlbyBjYWxsIG1heSBkZXRlcmlvcmF0ZSBzb21ld2hh dCByYW5kb21seSwgYW5kIHlvdSBtYXkgc2VlIGEgZ29vZCBiaXQgb2YgYm91bmNlIGluIHRoZSBU Q1AgZG93bmxvYWQgcGVyZm9ybWFuY2UuICBZb3VyIGZpbGUgdHJhbnNmZXIgb3ZlciBUQ1AgaXMg bGlrZSwgIk1tbS4uICBHaXZlIG1lIGFsbCBJIGNhbiBnZXQuIiAgYW5kIHlvdXIgdmlkZW8gY2Fs bCBpcyB2b2x1bnRhcmlseSBsZWF2aW5nIGZvb2Qgb24gdGhlIHRhYmxlIG9ubHkgY29uc3VtaW5n IHdoYXQgaGUgbmVlZHMgcmlnaHQgbm93LiAgVGhlIFRDUCBndXkgaXMgYmFmZmxlZCBieSB0aGlz IGJlaGF2aW9yLCBidXQgdGFrZXMgYWR2YW50YWdlIG9mIHRoZSBmb29kIGFzIGl0IGJlY29tZXMg YXZhaWxhYmxlLiAgVGhlbiB3aGVuIHNvbWVvbmUgd2Fsa3MgYWNyb3NzIHRoZSBiYWNrIG9mIHRo ZSByb29tLCB0aGUgdmlkZW8gYml0cmF0ZSBzcGlrZXMsIHRoZSB2aWRlbyBndXkgaXMgbGlrZSwg IldobyBqdXN0IGF0ZSBteSBsdW5jaD8iDQoNClRoaXMgY3JlYXRlcyBhbiB1bm5lY2Vzc2FyeSBy YWNlIGZvciBhdmFpbGFibGUgcmVzb3VyY2VzLCBhbmQgbWFrZXMgaXQgZGlmZmljdWx0IGZvciBh bGwgcGFydGllcyBpbnZvbHZlZCBpbmNsdWRpbmcgb3RoZXIgY29uZ2VzdGlvbiBjb250cm9sbGVk IHN0cmVhbXMgdG8gbWFrZSBiZXN0IHVzZSBvZiB0aGVpciBhdmFpbGFibGUgcmVzb3VyY2VzLg0K DQpWYXJpYWJsZSBiaXRyYXRlIGluIHJlYWwgdGltZSBzZWVtcyBsaWtlIGEgZ29vZCBpZGVhIGlu IHRoZW9yeSwgYnV0IGl0IGRvZXNuJ3Qgd29yayBpbiBwcmFjdGljZSBmb3IgdGhlIHByb2JsZW0g ZGVzY3JpYmVkIGFib3ZlLiAgVGhpcyBpcyB0cnVlIGZvciBhbGwgY2FzZXMgd2hlcmUgaXQgaGFz IHRvIHNoYXJlIGl0c2VsZiB3aXRoIG90aGVyIGNvbmdlc3Rpb24gY29udHJvbGxlZCBhbGdvcml0 aG1zLiAgSWYgaXQncyBvbiBhIGRlZGljYXRlZCBsaW5rIG9yIGNvbnRhaW5zIHNwZWNpYWwgUW9T LCB0aGVyZSdzIGEgZml4ZWQgbnVtYmVyIG9mIHN0cmVhbXMgYWxsb3dlZCwgZWFjaCB3aXRoIG1h eGltdW0gYWxsb3dhYmxlIGJpdHJhdGVzLCB0aGVuIGl0IGNhbiB3b3JrIGZpbmUgYWxsIG9uIGl0 cyBvd24uICBCdXQgaW4gdGhhdCBjYXNlIGl0IGRvZXNuJ3QgbmVlZCBjb25nZXN0aW9uIGNvbnRy b2wuICBJdCdzIGNvbmdlc3Rpb24gY29udHJvbGxlZCBieSBkZXNpZ24uDQoNCkJ1dCB0byBiZSBj bGVhciwgSSBhbSBpbiBubyB3YXkgc3VnZ2VzdGluZyB0aGF0IHdlIHVzZSBhdmVyYWdlIGJpdHJh dGUgb3IgY29uc3RhbnQgYml0cmF0ZSBzZXR0aW5ncyBmcm9tIHRoZSB2aWRlbyBlbmNvZGVycy4g IEkgdXNlZCB0byBoYXZlIHRoaXMgd29uZGVyZnVsIGRlbW8gdGhhdCBkZW1vbnN0cmF0ZWQgdGhp cy4gIEluIHRoZSB2ZXJ5IGZpcnN0IGRlbW8gb2YgbXkgdmlkZW8gY29uZmVyZW5jZSBicmlkZ2Ug KH4yMDA2KSwgSSBoYWQgYWxsIG9mIHRoZSBwYXJ0aWNpcGFudHMgZGlzcGxheWVkIG9uIHRvIHRo ZSBzY3JlZW4sIGFuZCBJIGhhZCB0aGUgZW5jb2RlciB0dW5lZCB0byA3NjhrL3MgZm9yIFFWR0Eu ICBBbmQgd2hlbiB0aGUgZmlyc3QgcGVyc29uIGp1bXAgb24sIGhlIHdvdWxkIHRha2UgdXAgYSBx dWFydGVyIG9mIHRoZSBzY3JlZW4gbGVhdmluZyB0aHJlZSBxdWFydGVycyBibGFjay4gIEhlIGxv b2tlZCBwZXJmZWN0bHkgc2hhcnAsIGFuZCB0aGVuIGFub3RoZXIgcGVyc29uIGpvaW5lZC4gIEV2 ZXJ5dGhpbmcgc2VlbWVkIG9rYXkuICBUaGUgdGhpcmQgcGVyc29uIGpvaW5zIGFuZCB5b3Ugc3Rh cnQgd29uZGVyaW5nIHdoeSBldmVyeW9uZSBzdGFydGVkIGxvb2tpbmcgZnV6enkuICBUaGVuIHdo ZW4gdGhlIGZvdXJ0aCBwZXJzb24ganVtcHMgb24sIGl0IGxvb2tzIGxpa2UgZXZlcnlvbmUncyBm YWNlIGlzIGNvdmVyZWQgaW4gdmFzZWxpbmUuICBXaGVuIHlvdSdyZSB0YXJnZXRpbmcgYml0cmF0 ZSwgeW91J3JlIGlnbm9yaW5nIHF1YWxpdHkuDQoNCkEgZmV3IHNvbHV0aW9ucyBjb21lIHRvIG1p bmQuICBJdCBtYXkgbm90IGJlIGZlYXNpYmxlIG9uIGFueW9uZSdzIHJlYWwgbmV0d29yaywgYnV0 IHlvdSBjb3VsZCB0cnkgdXNpbmcgc29tZXRoaW5nIGxpa2UgUlNWUCB0byBwZXJmb3JtIGJhbmR3 aWR0aCByZXNlcnZhdGlvbnMuICBZb3UgY291bGQgYWxzbyBmaWxsIHBhY2tldHMgd2l0aCB6ZXJv cyB0byB0YXJnZXQgdGhlIGJpdHJhdGUuICBBbmQgd2hpbGUgdGhpcyBzb2x1dGlvbiBtYXliZSB2 ZXJ5IENQVSBlZmZpY2llbnQsIGl0J3Mgbm90IHJlYWxseSBkb2luZyBhbnl0aGluZyBmb3IgeW91 LiAgVG8gbWUgaXQgbWFrZXMgdGhlIG1vc3Qgc2Vuc2UgdG8gdXNlIHNvbWUgZm9ybSBvZiBGRUMg dG8gZmlsbCB1cCB0aGUgZGlmZmVyZW5jZS4gIFZhcmlhYmxlIHZpZGVvIGJpdHJhdGUgKyB2YXJp YWJsZSBGRUMgYml0cmF0ZSA9IFZpZGVvIFN0cmVhbSBNYXggQml0cmF0ZS4gIE1heWJlIHlvdSBj b3VsZCBldmVuIGRvIHNvbWV0aGluZyBmYW5jeSBsaWtlIHNwYW4gaXQgYWNyb3NzIGEgYnVuY2gg b2YgZnJhbWVzIG9yIGZvY3VzIG9uIHlvdXIgaS1mcmFtZXMuICBXaGF0ZXZlciByb2NrcyB5b3Vy IHJpZGUuDQoNCk9uIHRoZSBwbHVzIHNpZGUsIGluIHRoZSBldmVudCB5b3UgZG8gaGl0IHNvbWUg aW50ZXJtaXR0ZW50IHBhY2tldCBsb3NzIG9yIHlvdSBkbyBoaXQgc29tZSBjb25nZXN0aW9uLCB5 b3UgaGF2ZSBhZGRlZCByZXNpbGllbmNlIHRvIHByb3RlY3QgeW91ciBzdHJlYW0gd2hpbGUgc3Rp bGwgaGF2aW5nIHdpZ2dsZSByb29tIHRvIGFkanVzdCBmb3IgY29uZ2VzdGlvbi4NCg0KRGFuDQoN Cg0K --_000_3879D71E758A7E4AA99A35DD8D41D3D91D47DD52xmbrcdx14ciscoc_ Content-Type: text/html; charset="utf-8" Content-Transfer-Encoding: base64 PGh0bWwgeG1sbnM6dj0idXJuOnNjaGVtYXMtbWljcm9zb2Z0LWNvbTp2bWwiIHhtbG5zOm89InVy bjpzY2hlbWFzLW1pY3Jvc29mdC1jb206b2ZmaWNlOm9mZmljZSIgeG1sbnM6dz0idXJuOnNjaGVt YXMtbWljcm9zb2Z0LWNvbTpvZmZpY2U6d29yZCIgeG1sbnM6bT0iaHR0cDovL3NjaGVtYXMubWlj cm9zb2Z0LmNvbS9vZmZpY2UvMjAwNC8xMi9vbW1sIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcv VFIvUkVDLWh0bWw0MCI+DQo8aGVhZD4NCjxtZXRhIGh0dHAtZXF1aXY9IkNvbnRlbnQtVHlwZSIg Y29udGVudD0idGV4dC9odG1sOyBjaGFyc2V0PXV0Zi04Ij4NCjxtZXRhIG5hbWU9IkdlbmVyYXRv ciIgY29udGVudD0iTWljcm9zb2Z0IFdvcmQgMTQgKGZpbHRlcmVkIG1lZGl1bSkiPg0KPHN0eWxl PjwhLS0NCi8qIEZvbnQgRGVmaW5pdGlvbnMgKi8NCkBmb250LWZhY2UNCgl7Zm9udC1mYW1pbHk6 Q2FsaWJyaTsNCglwYW5vc2UtMToyIDE1IDUgMiAyIDIgNCAzIDIgNDt9DQpAZm9udC1mYWNlDQoJ e2ZvbnQtZmFtaWx5OlRhaG9tYTsNCglwYW5vc2UtMToyIDExIDYgNCAzIDUgNCA0IDIgNDt9DQov KiBTdHlsZSBEZWZpbml0aW9ucyAqLw0KcC5Nc29Ob3JtYWwsIGxpLk1zb05vcm1hbCwgZGl2Lk1z b05vcm1hbA0KCXttYXJnaW46MGluOw0KCW1hcmdpbi1ib3R0b206LjAwMDFwdDsNCglmb250LXNp emU6MTIuMHB0Ow0KCWZvbnQtZmFtaWx5OiJUaW1lcyBOZXcgUm9tYW4iLCJzZXJpZiI7fQ0KYTps aW5rLCBzcGFuLk1zb0h5cGVybGluaw0KCXttc28tc3R5bGUtcHJpb3JpdHk6OTk7DQoJY29sb3I6 Ymx1ZTsNCgl0ZXh0LWRlY29yYXRpb246dW5kZXJsaW5lO30NCmE6dmlzaXRlZCwgc3Bhbi5Nc29I eXBlcmxpbmtGb2xsb3dlZA0KCXttc28tc3R5bGUtcHJpb3JpdHk6OTk7DQoJY29sb3I6cHVycGxl Ow0KCXRleHQtZGVjb3JhdGlvbjp1bmRlcmxpbmU7fQ0Kc3Bhbi5FbWFpbFN0eWxlMTcNCgl7bXNv LXN0eWxlLXR5cGU6cGVyc29uYWwtcmVwbHk7DQoJZm9udC1mYW1pbHk6IkNhbGlicmkiLCJzYW5z LXNlcmlmIjsNCgljb2xvcjp3aW5kb3d0ZXh0O30NCi5Nc29DaHBEZWZhdWx0DQoJe21zby1zdHls ZS10eXBlOmV4cG9ydC1vbmx5Ow0KCWZvbnQtZmFtaWx5OiJDYWxpYnJpIiwic2Fucy1zZXJpZiI7 fQ0KQHBhZ2UgV29yZFNlY3Rpb24xDQoJe3NpemU6OC41aW4gMTEuMGluOw0KCW1hcmdpbjoxLjBp biAxLjBpbiAxLjBpbiAxLjBpbjt9DQpkaXYuV29yZFNlY3Rpb24xDQoJe3BhZ2U6V29yZFNlY3Rp b24xO30NCi0tPjwvc3R5bGU+PCEtLVtpZiBndGUgbXNvIDldPjx4bWw+DQo8bzpzaGFwZWRlZmF1 bHRzIHY6ZXh0PSJlZGl0IiBzcGlkbWF4PSIxMDI2IiAvPg0KPC94bWw+PCFbZW5kaWZdLS0+PCEt LVtpZiBndGUgbXNvIDldPjx4bWw+DQo8bzpzaGFwZWxheW91dCB2OmV4dD0iZWRpdCI+DQo8bzpp ZG1hcCB2OmV4dD0iZWRpdCIgZGF0YT0iMSIgLz4NCjwvbzpzaGFwZWxheW91dD48L3htbD48IVtl bmRpZl0tLT4NCjwvaGVhZD4NCjxib2R5IGxhbmc9IkVOLVVTIiBsaW5rPSJibHVlIiB2bGluaz0i cHVycGxlIj4NCjxkaXYgY2xhc3M9IldvcmRTZWN0aW9uMSI+DQo8cCBjbGFzcz0iTXNvTm9ybWFs Ij48c3BhbiBzdHlsZT0iZm9udC1zaXplOjExLjBwdDtmb250LWZhbWlseTomcXVvdDtDYWxpYnJp JnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVvdDsiPkhpIERhbiw8bzpwPjwvbzpwPjwvc3Bhbj48 L3A+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48c3BhbiBzdHlsZT0iZm9udC1zaXplOjExLjBwdDtm b250LWZhbWlseTomcXVvdDtDYWxpYnJpJnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVvdDsiPjxv OnA+Jm5ic3A7PC9vOnA+PC9zcGFuPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0 eWxlPSJmb250LXNpemU6MTEuMHB0O2ZvbnQtZmFtaWx5OiZxdW90O0NhbGlicmkmcXVvdDssJnF1 b3Q7c2Fucy1zZXJpZiZxdW90OyI+SSB3b3VsZCBjYXV0aW9uIGFnYWluc3QgYW55IGFwcHJvYWNo IHRoYXQgc2F5cyBWQlIgbGVhdmVzIGF2YWlsYWJsZSBiYW5kd2lkdGggb24gdGhlIHRhYmxlIGZv ciBvdGhlcnMgdG8gZWF0LCBzbyBlYXQgaXQgeW91cnNlbGYgd2l0aCBGRUMuIFdoZW4gdGhlcmUg YXJlIG1hbnkgZmxvd3MsIHRoZQ0KIHN0YXQtbXV4IGFkdmFudGFnZXMgb2YgVkJSIG1heGltaXpl IGJhbmR3aWR0aCBlZmZpY2llbmN5LiBGRUMgc2hvdWxkIGJlIGFwcGxpZWQgaW4gcHJvcG9ydGlv biB0byBleHBlY3RlZCBsb3NzIChvciBtb3JlIHByZWNpc2VseSwgZXhwZWN0ZWQgZWZmZWN0aXZl IHBvc3QtRkVDIHJlY292ZXJ5KSwgbm90IGdyZWVkIG9yIGdsdXR0b255LjxvOnA+PC9vOnA+PC9z cGFuPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0eWxlPSJmb250LXNpemU6MTEu MHB0O2ZvbnQtZmFtaWx5OiZxdW90O0NhbGlicmkmcXVvdDssJnF1b3Q7c2Fucy1zZXJpZiZxdW90 OyI+PG86cD4mbmJzcDs8L286cD48L3NwYW4+PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNw YW4gc3R5bGU9ImZvbnQtc2l6ZToxMS4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90 OywmcXVvdDtzYW5zLXNlcmlmJnF1b3Q7Ij5NbzxvOnA+PC9vOnA+PC9zcGFuPjwvcD4NCjxwIGNs YXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0eWxlPSJmb250LXNpemU6MTEuMHB0O2ZvbnQtZmFtaWx5 OiZxdW90O0NhbGlicmkmcXVvdDssJnF1b3Q7c2Fucy1zZXJpZiZxdW90OyI+PG86cD4mbmJzcDs8 L286cD48L3NwYW4+PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5bGU9ImZvbnQt c2l6ZToxMS4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90OywmcXVvdDtzYW5zLXNl cmlmJnF1b3Q7Ij48bzpwPiZuYnNwOzwvbzpwPjwvc3Bhbj48L3A+DQo8cCBjbGFzcz0iTXNvTm9y bWFsIj48Yj48c3BhbiBzdHlsZT0iZm9udC1zaXplOjEwLjBwdDtmb250LWZhbWlseTomcXVvdDtU YWhvbWEmcXVvdDssJnF1b3Q7c2Fucy1zZXJpZiZxdW90OyI+RnJvbTo8L3NwYW4+PC9iPjxzcGFu IHN0eWxlPSJmb250LXNpemU6MTAuMHB0O2ZvbnQtZmFtaWx5OiZxdW90O1RhaG9tYSZxdW90Oywm cXVvdDtzYW5zLXNlcmlmJnF1b3Q7Ij4gcm1jYXQtYm91bmNlc0BpZXRmLm9yZyBbbWFpbHRvOnJt Y2F0LWJvdW5jZXNAaWV0Zi5vcmddDQo8Yj5PbiBCZWhhbGYgT2YgPC9iPkRhbiBXZWJlcjxicj4N CjxiPlNlbnQ6PC9iPiBUdWVzZGF5LCBNYXkgMjgsIDIwMTMgODo0MSBQTTxicj4NCjxiPlRvOjwv Yj4gcm1jYXRAaWV0Zi5vcmc8YnI+DQo8Yj5TdWJqZWN0OjwvYj4gW3JtY2F0XSBWYXJpYWJsZSBC aXRyYXRlIEltcGFjdCBvbiBDb25nZXN0aW9uIENvbnRyb2w8bzpwPjwvbzpwPjwvc3Bhbj48L3A+ DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48bzpwPiZuYnNwOzwvbzpwPjwvcD4NCjxkaXY+DQo8cCBj bGFzcz0iTXNvTm9ybWFsIj5JdCdzIGltcG9ydGFudCB0byBub3RlIHRoZSByb2xlIHRoYXQgdmFy aWFibGUgYml0cmF0ZSBwbGF5cyBpbiBjb25nZXN0aW9uIGNvbnRyb2wuICZuYnNwO0kga25vdyB3 ZSd2ZSBkaXNjdXNzZWQgdGhpcyBvbiBzb21lIGxldmVsLCBidXQgaW4gcmVhbGl0eSwgYW55IGRl Y2lzaW9uIHRoYXQncyBtYWRlIHdoZW4gdGhlIHVuZGVybHlpbmcgbWVkaXVtIGNvbnRpbnVvdXNs eSBjaGFuZ2VzIGNoYXJhY3RlcmlzdGljcyBpcyBhbg0KIHVucmVsaWFibGUgb25lLiAmbmJzcDtJ ZiB1c2VkIHdpdGggYW55IHNvcnQgb2YgaW5zdGFudGFuZW91cyBtZWFzdXJlLCBpdCBjYW4gZ2l2 ZSB5b3UgdW5yZWFsaXN0aWMgZXhwZWN0YXRpb25zIG9mIGNhcGFjaXR5LiAmbmJzcDsmbmJzcDs8 bzpwPjwvbzpwPjwvcD4NCjwvZGl2Pg0KPGRpdj4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxvOnA+ Jm5ic3A7PC9vOnA+PC9wPg0KPC9kaXY+DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+SnVz dCBjb25zaWRlciBhIGxhcmdlIGZpbGUgdHJhbnNmZXIgb2YgVENQIG92ZXIgdGhlIG5ldHdvcmsu ICZuYnNwO0l0IG1heSBzYXd0b290aCB1cCBhbmQgZG93biBhIGJpdCwgYnV0IGl0IHVzdWFsbHkg c3RhYmlsaXplcyB0byBhIGNlcnRhaW4gbGV2ZWwuICZuYnNwO05vdyBpZiB5b3UndmUgZ290IGEg My8zIG1iaXQgbGluaywgeW91IGhhdmUgYSB2aWRlbyBjYWxsIGdvaW5nIHdpdGggYSZuYnNwOzxi Pm1heCByYXRlPC9iPiZuYnNwO29mIDEuNW1iaXQvcw0KIGJpZGlyZWN0aW9uYWxseSwgYW5kIHlv dSdyZSB1cGxvYWRpbmcgb3IgZG93bmxvYWRpbmcgdGhlIGxhdGVzdCBEVkQgaXNvIG9mIFVidW50 dSwgeW91ciB2aWRlbyBjYWxsIG1heSBkZXRlcmlvcmF0ZSBzb21ld2hhdCByYW5kb21seSwgYW5k IHlvdSBtYXkgc2VlIGEgZ29vZCBiaXQgb2YgYm91bmNlIGluIHRoZSBUQ1AgZG93bmxvYWQgcGVy Zm9ybWFuY2UuICZuYnNwO1lvdXIgZmlsZSB0cmFuc2ZlciBvdmVyIFRDUCBpcyBsaWtlLCAmcXVv dDtNbW0uLiAmbmJzcDtHaXZlIG1lDQogYWxsIEkgY2FuIGdldC4mcXVvdDsgJm5ic3A7YW5kIHlv dXIgdmlkZW8gY2FsbCBpcyB2b2x1bnRhcmlseSBsZWF2aW5nIGZvb2Qgb24gdGhlIHRhYmxlIG9u bHkgY29uc3VtaW5nIHdoYXQgaGUgbmVlZHMgcmlnaHQgbm93LiAmbmJzcDtUaGUgVENQIGd1eSBp cyBiYWZmbGVkIGJ5IHRoaXMgYmVoYXZpb3IsIGJ1dCB0YWtlcyBhZHZhbnRhZ2Ugb2YgdGhlIGZv b2QgYXMgaXQgYmVjb21lcyBhdmFpbGFibGUuICZuYnNwO1RoZW4gd2hlbiBzb21lb25lIHdhbGtz IGFjcm9zcyB0aGUgYmFjaw0KIG9mIHRoZSByb29tLCB0aGUgdmlkZW8gYml0cmF0ZSBzcGlrZXMs IHRoZSB2aWRlbyBndXkgaXMgbGlrZSwgJnF1b3Q7V2hvIGp1c3QgYXRlIG15IGx1bmNoPyZxdW90 OzxvOnA+PC9vOnA+PC9wPg0KPC9kaXY+DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PG86 cD4mbmJzcDs8L286cD48L3A+DQo8L2Rpdj4NCjxkaXY+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj5U aGlzIGNyZWF0ZXMgYW4gdW5uZWNlc3NhcnkgcmFjZSBmb3IgYXZhaWxhYmxlIHJlc291cmNlcywg YW5kIG1ha2VzIGl0IGRpZmZpY3VsdCBmb3IgYWxsIHBhcnRpZXMgaW52b2x2ZWQgaW5jbHVkaW5n IG90aGVyIGNvbmdlc3Rpb24gY29udHJvbGxlZCBzdHJlYW1zIHRvIG1ha2UgYmVzdCB1c2Ugb2Yg dGhlaXIgYXZhaWxhYmxlIHJlc291cmNlcy48bzpwPjwvbzpwPjwvcD4NCjwvZGl2Pg0KPGRpdj4N CjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxvOnA+Jm5ic3A7PC9vOnA+PC9wPg0KPC9kaXY+DQo8ZGl2 Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+VmFyaWFibGUgYml0cmF0ZSBpbiByZWFsIHRpbWUgc2Vl bXMgbGlrZSBhIGdvb2QgaWRlYSBpbiB0aGVvcnksIGJ1dCBpdCBkb2Vzbid0IHdvcmsgaW4gcHJh Y3RpY2UgZm9yIHRoZSBwcm9ibGVtIGRlc2NyaWJlZCBhYm92ZS4gJm5ic3A7VGhpcyBpcyB0cnVl IGZvciBhbGwgY2FzZXMgd2hlcmUgaXQgaGFzIHRvIHNoYXJlIGl0c2VsZiB3aXRoIG90aGVyIGNv bmdlc3Rpb24gY29udHJvbGxlZCBhbGdvcml0aG1zLiAmbmJzcDtJZiBpdCdzDQogb24gYSBkZWRp Y2F0ZWQgbGluayBvciBjb250YWlucyBzcGVjaWFsIFFvUywgdGhlcmUncyBhIGZpeGVkIG51bWJl ciBvZiBzdHJlYW1zIGFsbG93ZWQsIGVhY2ggd2l0aCBtYXhpbXVtIGFsbG93YWJsZSBiaXRyYXRl cywgdGhlbiBpdCBjYW4gd29yayBmaW5lIGFsbCBvbiBpdHMgb3duLiAmbmJzcDtCdXQgaW4gdGhh dCBjYXNlIGl0IGRvZXNuJ3QgbmVlZCBjb25nZXN0aW9uIGNvbnRyb2wuICZuYnNwO0l0J3MgY29u Z2VzdGlvbiBjb250cm9sbGVkIGJ5IGRlc2lnbi48bzpwPjwvbzpwPjwvcD4NCjwvZGl2Pg0KPGRp dj4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxvOnA+Jm5ic3A7PC9vOnA+PC9wPg0KPC9kaXY+DQo8 ZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+QnV0IHRvIGJlIGNsZWFyLCBJIGFtIGluIG5vIHdh eSBzdWdnZXN0aW5nIHRoYXQgd2UgdXNlIGF2ZXJhZ2UgYml0cmF0ZSBvciBjb25zdGFudCBiaXRy YXRlIHNldHRpbmdzIGZyb20gdGhlIHZpZGVvIGVuY29kZXJzLiAmbmJzcDtJIHVzZWQgdG8gaGF2 ZSB0aGlzIHdvbmRlcmZ1bCBkZW1vIHRoYXQgZGVtb25zdHJhdGVkIHRoaXMuICZuYnNwO0luIHRo ZSB2ZXJ5IGZpcnN0IGRlbW8gb2YgbXkgdmlkZW8gY29uZmVyZW5jZSBicmlkZ2UNCiAofjIwMDYp LCBJIGhhZCBhbGwgb2YgdGhlIHBhcnRpY2lwYW50cyBkaXNwbGF5ZWQgb24gdG8gdGhlIHNjcmVl biwgYW5kIEkgaGFkIHRoZSBlbmNvZGVyIHR1bmVkIHRvIDc2OGsvcyBmb3IgUVZHQS4gJm5ic3A7 QW5kIHdoZW4gdGhlIGZpcnN0IHBlcnNvbiBqdW1wIG9uLCBoZSB3b3VsZCB0YWtlIHVwIGEgcXVh cnRlciBvZiB0aGUgc2NyZWVuIGxlYXZpbmcgdGhyZWUgcXVhcnRlcnMgYmxhY2suICZuYnNwO0hl IGxvb2tlZCBwZXJmZWN0bHkgc2hhcnAsIGFuZCB0aGVuDQogYW5vdGhlciBwZXJzb24gam9pbmVk LiAmbmJzcDtFdmVyeXRoaW5nIHNlZW1lZCBva2F5LiAmbmJzcDtUaGUgdGhpcmQgcGVyc29uIGpv aW5zIGFuZCB5b3Ugc3RhcnQgd29uZGVyaW5nIHdoeSBldmVyeW9uZSBzdGFydGVkIGxvb2tpbmcg ZnV6enkuICZuYnNwO1RoZW4gd2hlbiB0aGUgZm91cnRoIHBlcnNvbiBqdW1wcyBvbiwgaXQgbG9v a3MgbGlrZSBldmVyeW9uZSdzIGZhY2UgaXMgY292ZXJlZCBpbiB2YXNlbGluZS4gJm5ic3A7V2hl biB5b3UncmUgdGFyZ2V0aW5nIGJpdHJhdGUsDQogeW91J3JlIGlnbm9yaW5nIHF1YWxpdHkuPG86 cD48L286cD48L3A+DQo8L2Rpdj4NCjxkaXY+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48bzpwPiZu YnNwOzwvbzpwPjwvcD4NCjwvZGl2Pg0KPGRpdj4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPkEgZmV3 IHNvbHV0aW9ucyBjb21lIHRvIG1pbmQuICZuYnNwO0l0IG1heSBub3QgYmUgZmVhc2libGUgb24g YW55b25lJ3MgcmVhbCBuZXR3b3JrLCBidXQgeW91IGNvdWxkIHRyeSB1c2luZyBzb21ldGhpbmcg bGlrZSBSU1ZQIHRvIHBlcmZvcm0gYmFuZHdpZHRoIHJlc2VydmF0aW9ucy4gJm5ic3A7WW91IGNv dWxkIGFsc28gZmlsbCBwYWNrZXRzIHdpdGggemVyb3MgdG8gdGFyZ2V0IHRoZSBiaXRyYXRlLiAm bmJzcDtBbmQgd2hpbGUgdGhpcw0KIHNvbHV0aW9uIG1heWJlIHZlcnkgQ1BVIGVmZmljaWVudCwg aXQncyBub3QgcmVhbGx5IGRvaW5nIGFueXRoaW5nIGZvciB5b3UuICZuYnNwO1RvIG1lIGl0IG1h a2VzIHRoZSBtb3N0IHNlbnNlIHRvIHVzZSBzb21lIGZvcm0gb2YgRkVDIHRvIGZpbGwgdXAgdGhl IGRpZmZlcmVuY2UuICZuYnNwO1ZhcmlhYmxlIHZpZGVvIGJpdHJhdGUgJiM0MzsgdmFyaWFibGUg RkVDIGJpdHJhdGUgPSBWaWRlbyBTdHJlYW0gTWF4IEJpdHJhdGUuICZuYnNwO01heWJlIHlvdSBj b3VsZCBldmVuIGRvDQogc29tZXRoaW5nIGZhbmN5IGxpa2Ugc3BhbiBpdCBhY3Jvc3MgYSBidW5j aCBvZiBmcmFtZXMgb3IgZm9jdXMgb24geW91ciBpLWZyYW1lcy4gJm5ic3A7V2hhdGV2ZXIgcm9j a3MgeW91ciByaWRlLjxvOnA+PC9vOnA+PC9wPg0KPC9kaXY+DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1z b05vcm1hbCI+PG86cD4mbmJzcDs8L286cD48L3A+DQo8L2Rpdj4NCjxkaXY+DQo8cCBjbGFzcz0i TXNvTm9ybWFsIj5PbiB0aGUgcGx1cyBzaWRlLCBpbiB0aGUgZXZlbnQgeW91IGRvIGhpdCBzb21l IGludGVybWl0dGVudCBwYWNrZXQgbG9zcyBvciB5b3UgZG8gaGl0IHNvbWUgY29uZ2VzdGlvbiwg eW91IGhhdmUgYWRkZWQgcmVzaWxpZW5jZSB0byBwcm90ZWN0IHlvdXIgc3RyZWFtIHdoaWxlIHN0 aWxsIGhhdmluZyB3aWdnbGUgcm9vbSB0byBhZGp1c3QgZm9yIGNvbmdlc3Rpb24uPG86cD48L286 cD48L3A+DQo8L2Rpdj4NCjxkaXY+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48bzpwPiZuYnNwOzwv bzpwPjwvcD4NCjwvZGl2Pg0KPGRpdj4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPkRhbjxvOnA+PC9v OnA+PC9wPg0KPC9kaXY+DQo8ZGl2Pg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PG86cD4mbmJzcDs8 L286cD48L3A+DQo8L2Rpdj4NCjxkaXY+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48bzpwPiZuYnNw OzwvbzpwPjwvcD4NCjwvZGl2Pg0KPC9kaXY+DQo8L2JvZHk+DQo8L2h0bWw+DQo= --_000_3879D71E758A7E4AA99A35DD8D41D3D91D47DD52xmbrcdx14ciscoc_-- From mzanaty@cisco.com Wed May 29 21:33:05 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 7501721E804E for ; Wed, 29 May 2013 21:33:04 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -10.598 X-Spam-Level: X-Spam-Status: No, score=-10.598 tagged_above=-999 required=5 tests=[BAYES_00=-2.599, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_HI=-8] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id 1MyKtJcMaoiK for ; Wed, 29 May 2013 21:32:58 -0700 (PDT) Received: from rcdn-iport-6.cisco.com (rcdn-iport-6.cisco.com [173.37.86.77]) by ietfa.amsl.com (Postfix) with ESMTP id 8383621E8053 for ; Wed, 29 May 2013 21:32:58 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=21532; q=dns/txt; s=iport; t=1369888378; x=1371097978; h=from:to:subject:date:message-id:references:in-reply-to: mime-version; bh=39wnQlKSvZhe2OJVuUpBm8tfMJ4GFw+g2azCS0pN3BU=; b=CasiEJhFM3q4HDZ2TrZrio3e3PA720ed9wmO7ijI2+YXjpDYHxPtITWF 5dS2/7TpHsN65W6tXvuaKD4x4hf2XyckIRpH0PYPANrs5IyX8ZEZMkUT/ cVN3bGs2AeXWrUA4CCVfwvtsiWUwAujw2Ek7+UtM1bs6NDIf6YLrI9AF0 s=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: AhEGAAXWplGtJV2d/2dsb2JhbABPCoJFRDCDO75MDXYWdIIjAQEBBCMKXAIBCBEEAQELHQMCAgIwFAkIAgQBEggTh3KoCpIUjVeBCzcBgkMzYQOoe4MPgic X-IronPort-AV: E=Sophos;i="4.87,768,1363132800"; d="scan'208,217";a="216559455" Received: from rcdn-core-6.cisco.com ([173.37.93.157]) by rcdn-iport-6.cisco.com with ESMTP; 30 May 2013 04:32:50 +0000 Received: from xhc-rcd-x08.cisco.com (xhc-rcd-x08.cisco.com [173.37.183.82]) by rcdn-core-6.cisco.com (8.14.5/8.14.5) with ESMTP id r4U4WojD008873 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL); Thu, 30 May 2013 04:32:50 GMT Received: from xmb-rcd-x14.cisco.com ([169.254.4.194]) by xhc-rcd-x08.cisco.com ([173.37.183.82]) with mapi id 14.02.0318.004; Wed, 29 May 2013 23:32:50 -0500 From: "Mo Zanaty (mzanaty)" To: Dan Weber , "rmcat@ietf.org" Thread-Topic: [rmcat] "Soup Nazi" RTP Congestion Control Thread-Index: AQHOWZxLdXtDX6TK0k24Ys5GUemaVpkc5aHw Date: Thu, 30 May 2013 04:32:49 +0000 Message-ID: <3879D71E758A7E4AA99A35DD8D41D3D91D47DF36@xmb-rcd-x14.cisco.com> References: In-Reply-To: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: x-originating-ip: [10.82.246.149] Content-Type: multipart/alternative; boundary="_000_3879D71E758A7E4AA99A35DD8D41D3D91D47DF36xmbrcdx14ciscoc_" MIME-Version: 1.0 Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Thu, 30 May 2013 04:33:05 -0000 --_000_3879D71E758A7E4AA99A35DD8D41D3D91D47DF36xmbrcdx14ciscoc_ Content-Type: text/plain; charset="utf-8" Content-Transfer-Encoding: base64 SGkgRGFuLA0KDQpJIGhhdmUgdG8gYWdyZWUgd2l0aCB0aGUgb3RoZXIgY29tbWVudGVycy4gQVFN IGluIGEgcm91dGVyIGlzIGZ1bmRhbWVudGFsbHkgZGlmZmVyZW50IHRoYW4gQ0MgaW4gYW4gZW5k cG9pbnQuIEFRTSBtYW5hZ2VzIGEgcGVyLWhvcCBxdWV1ZSB0byBhYnNvcmIgYnVyc3RzIHdoaWxl IGF2b2lkaW5nIHBlcnNpc3RlbnQgcXVldWVzLiBJdCBrbm93cyB0aGUgYWJzb2x1dGUgdHJhbnNp dCB0aW1lIG9mIGVhY2ggcGFja2V0IHRocm91Z2ggdGhlIHF1ZXVlIGFuZCBpdHMgZGVwdGgsIGFu ZCBjYW4gdHJ5IHRvIG1pbmltaXplIGVpdGhlciBvciBib3RoLg0KDQpJZiBJIHVuZGVyc3RhbmQg eW91ciBwcm9wb3NhbCwgeW91IHdhbnQgdGhlIHNlbmRlciB0byB0cmVhdCB0aGUgZW50aXJlIG5l dHdvcmsgYXMgYSBiaWcgcXVldWUsIHVzaW5nIHJlY2VpdmVyIGZlZWRiYWNrIGFzIGEgcHJveHkg Zm9yIGRpcmVjdCBtZWFzdXJlbWVudCBvZiBwYWNrZXQgdHJhbnNpdCB0aW1lcyB0aHJvdWdoIHRo ZSDigJxxdWV1ZeKAnS4gVG8gZ2V0IGFic29sdXRlIHRyYW5zaXQgdGltZXMsIHRoZSBzZW5kZXIg YW5kIHJlY2VpdmVyIHdvdWxkIG5lZWQgdGlnaHQgdGltZSBzeW5jLCB3aGljaCBzZWVtcyBleHRy ZW1lIHRvIHJlcXVpcmUuIChSVFAgaGFzIG5ldmVyIHJlcXVpcmVkIHRoaXMsIGV2ZW4gZm9yIHRo aW5ncyB3aGljaCBzZWVtIHJlbGF0ZWQgdG8gdGltZSBzeW5jIGxpa2UgYS92IChsaXApIHN5bmMu KSBXaXRob3V0IHRpbWUgc3luYywgeW91IGNhbiBvbmx5IG1lYXN1cmUgUlRUIChsaWtlIFJUUCks IHdoaWNoIGNhbiBiZSBza2V3ZWQgYnkgdGhlIHJldmVyc2UgcGF0aC4gT3IgeW91IGNhbiBtZWFz dXJlIGludGVyLWFycml2YWwgaml0dGVyIChhZ2FpbiBsaWtlIFJUUCksIHdoaWNoIGNhbiBiZSBz a2V3ZWQgYnkgYW4gdW5rbm93biBiYXNlIGRlbGF5LiBFaXRoZXIgd2F5LCBJIGRvbuKAmXQgdGhp bmsgeW91IGdldCByZWxpYWJsZSBtZWFzdXJlbWVudHMgZm9yIHRoZSBhYnNvbHV0ZSBxdWV1ZSBk ZXB0aC9kZWxheSB0aGF0IENvRGVsIG9yIG90aGVyIEFRTXMgd2FudC4gSWYgdGhlIHNlbmRlciBh Y3RzIG9uIHJlbGF0aXZlIHJhdGhlciB0aGFuIGFic29sdXRlIGRlbGF5cywgdGhhdCByZXNlbWJs ZXMgdGhlIGN1cnJlbnQgUk1DQVQgY2FuZGlkYXRlcyByYXRoZXIgdGhhbiBDb0RlbCBvciBvdGhl ciBBUU1zLg0KDQpSZWdhcmRpbmcgdGhlIOKAnE5hemnigJ0gYXNwZWN0IChubyB2aWRlbyBmb3Ig eW91LCBpZiB5b3UgYnVyc3QpLCBJIGNhbuKAmXQgdGVsbCBpZiB5b3Ugd2VyZSBzZXJpb3VzIG9y IGp1c3Qgd2FudGVkIOKAnE5hemnigJ0gb24gdGhlIEJlcmxpbiBhZ2VuZGEgZm9yIGxhdWdocy4g SSBjZXJ0YWlubHkgbGF1Z2hlZOKApiA6KQ0KDQpNbw0KDQpGcm9tOiBybWNhdC1ib3VuY2VzQGll dGYub3JnIFttYWlsdG86cm1jYXQtYm91bmNlc0BpZXRmLm9yZ10gT24gQmVoYWxmIE9mIERhbiBX ZWJlcg0KU2VudDogU2F0dXJkYXksIE1heSAyNSwgMjAxMyA3OjA1IFBNDQpUbzogcm1jYXRAaWV0 Zi5vcmcNClN1YmplY3Q6IFtybWNhdF0gIlNvdXAgTmF6aSIgUlRQIENvbmdlc3Rpb24gQ29udHJv bA0KDQpIaSBndXlzLA0KDQpJJ3ZlIGJlZW4gcmV2aWV3aW5nIENvRGVsLCBhbmQgaXQncyBjbGVh ciBob3cgaXQgd29ya3MgcmVhc29uYWJseSB3ZWxsIGZvciBUQ1AuICBJdCdzIG9ubHkgc2xpZ2h0 bHkgbW9yZSBjb21wbGljYXRlZCB0aGFuIGFuIGltcGxlbWVudGF0aW9uIHVzaW5nIGEgZml4ZWQg dGltZXN0YW1wIHBlciBwYWNrZXQgZXhwaXJhdGlvbi4gIFRoZSBtaW5vciBkaWZmZXJlbmNlIG9j Y3VycyB3aGVuIGl0IGdvZXMgaW50byBpdHMgZHJvcHBpbmcgc3RhdGUgd2hpY2ggdXNlcyBhIHNx dWFyZSByb290IHNjYWxpbmcgZmFjdG9yIGZvciB0aGUgdGltZSBiYXNlZCBvbiB0aGUgbnVtYmVy IG9mIHByZXZpb3VzbHkgZHJvcHBlZCBwYWNrZXRzIGluIGEgc2VxdWVuY2UuICBUaGlzIHRha2Vz IGFkdmFudGFnZSBvZiBhIGtub3duIGJlaGF2aW9yIG9mIFRDUCBjb25nZXN0aW9uIGNvbnRyb2wg YWxnb3JpdGhtcyB3aGljaCBleHBlY3QgY29uZ2VzdGlvbiB0byBoYXBwZW4gaW4gbGFyZ2UgYnVy c3RzLg0KDQpXaGVuIGFwcGxpZWQgdG8gUlRQIHVua25vd2luZ2x5LCB0aGUgYmVoYXZpb3IgY291 bGQgYmUgcHJldHR5IGRpc2FzdHJvdXMgb24gdmlkZW8gY29udGVudC4gIEFsdGhvdWdoIEkgZG91 YnQgaXQncyBhbnkgd29yc2UgdGhhbiBhY3R1YWwgY29tcGV0aW5nIGNvbnRlbnQgd2l0aCBubyBB UU0sIGEgcGFydGljdWxhciBjYXNlIGRvZXMgc3RhbmQgb3V0LiAgV2hlbiBDb0RlbCBpcyBpbiBw bGFjZSB3aGVyZSB0aGVyZSBpcyBubyBjb21wZXRpbmcgdHJhZmZpYyBhbmQgdGhlIFJUUCBzZW5k ZXIgYnVyc3RzIHRoZSB3aXJlIHdpdGhvdXQgcGFjaW5nIGluIHJlc3BlY3QgdG8gbWF4aW11bSBz dHJlYW0gYml0cmF0ZSwgQ29EZWwgaXMgbGlrZWx5IHRvIGJ1cnN0IGRyb3AgcGFja2V0cyBiZWNh dXNlIG9mIG92ZXJmbG93IG9uIHRoZSBxdWV1ZSB0aW1lLiAgSSB0aGluayB0aGlzIGJlaGF2aW9y IGlzIGV4dHJlbWVseSBkZXNpcmFibGUuICBUaGlzIHdpbGwgYnJpbmcgYXdhcmVuZXNzIHRvIGFs bCB2ZW5kb3JzIGFuZCBpbXBsZW1lbnRvcnMgdGhhdCB0aGVpciBpbXBsZW1lbnRhdGlvbnMgd2Vy ZSB3b3JraW5nIGRlc3BpdGUgdGhlIGZhY3QgdGhhdCB0aGV5IHdlcmUgaW1wcm9wZXIuDQoNClRo aXMga2luZCBvZiBiZWhhdmlvciBjYW4gYmUgZW5oYW5jZWQgYW5kIGF1Z21lbnRlZCBpbiBhIHdh eSB0aGF0IGNhbiBiZSB1c2VkIHRvIGV4cGVkaXRlIHRoZSBpbXBsZW1lbnRhdGlvbiBvZiBlZmZl Y3RpdmUgUlRQIENvbmdlc3Rpb24gQ29udHJvbC4gICBJZiB3ZSB3ZXJlIHRvIGltcGxlbWVudCBy ZWNlaXZlciBzaWRlIENvRGVsIGZvciBkcm9wcGluZyAiZnJhbWVzIiBvciAibWVzc2FnZXMiIG9m IFJUUCBwYWNrZXRzIG9uIG5ldyBpbXBsZW1lbnRhdGlvbnMsIHdlIGNvdWxkIGJlY29tZSB0aGUg IlNvdXAgTmF6aSIgYW5kIHN0YXJ0IGVmZmVjdGl2ZWx5IGlkZW50aWZ5aW5nIGltcHJvcGVyIGlt cGxlbWVudGF0aW9ucyBhcyB3ZWxsIGFzIHJlbmRlcmluZyB0aGVtIGlub3BlcmFibGUuICBJZiBp bXBsZW1lbnRlZCBieSBvbmUgb2YgdGhlIG1ham9yIFdlYlJUQyBicm93c2VyIGltcGxlbWVudGF0 aW9ucywgYSBjaGFpbiByZWFjdGlvbiBtYXkgZGV2ZWxvcCB0aGF0IGZvcmNlcyBpbXBsZW1lbnRh dGlvbiBvZiBSVFAgY29uZ2VzdGlvbiBjb250cm9sIHVwIHRoZSBwaXBlbGluZS4gIElmIHVzZWZ1 bCBmZWVkYmFjayBpcyBkZWxpdmVyZWQgYmFjayB0byB0aGUgc2VuZGVyLCB3aGljaCByZWFsbHkg bmVlZHMgdG8gYmUgbmV0IHRyYW5zbGF0ZWQgdG8gZnJhbWVzIHByb2Nlc3NlZCBhbmQgZnJhbWVz IGRyb3BwZWQsIGFuIGFwcGxpY2F0aW9uIHdpdGggaXRzIGVuY29kZXIgY291bGQgcmVhc29uYWJs eSBhZGp1c3QuICBUaGlzIG1heSBzb2x2ZSBmYWlybmVzcyByZWxhdGVkIHByb2JsZW1zIGJlY2F1 c2UgdGhlIHJlY2VpdmVyIGNvdWxkIGlkZW50aWZ5IGlmIHRoZSBzZW5kZXIgb3ZlcmZsb3dlZCB0 aGUgcXVldWVzIGJ5IGV2YWx1YXRpbmcgYWN0dWFsIGFycml2YWwgdGltZSBjb21wYXJlZCB3aXRo IGZyYW1lIHByZXNlbnRhdGlvbiB0aW1lIChjb252ZXJ0ZWQgUlRQIHRpbWVzdGFtcHMpLiAgSWYg dGhlIHJlY2VpdmVyIGVuZm9yY2VzIHRoaXMgY29uc3RyYWludCwgZmFpcm5lc3Mgb24gUlRQIHN0 cmVhbXMgaXMgZWZmZWN0aXZlbHkgaW4gZm9yY2UgYmVjYXVzZSBpbXBsZW1lbnRhdGlvbnMgYXJl IHJlbmRlcmVkIGlub3BlcmFibGUsIGFuZCBpdCB3b3JrcyBzYWZlbHkgd2l0aGluIHRoZSBzY29w ZSBvZiBDb0RlbC4gIFRoaXMgaW1wbGllcyB0aGF0IFRDUCB3b3VsZCBiZSBvbmx5IGF0IG1vc3Qg YWZmZWN0ZWQgaW4gdGhlIHNhbWUgd2F5IHRoYXQgYW5vdGhlciBUQ1Agc3RyZWFtIHdvdWxkLg0K DQpBbmQgZmluYWxseSB0aGlzIGxlYWRzIHRvIG15IHN1Z2dlc3RlZCBzb2x1dGlvbiBmb3Igc2Vu ZGVyIHNpZGUgY29uZ2VzdGlvbiBjb250cm9sLiAgQmFzZWQgb24gbXkgYXNzdW1wdGlvbiB0aGF0 IENvRGVsIGltcGxlbWVudGF0aW9uIGZvciBBUU0gaXMgb24gdGhlIGhvcml6b24gYWNyb3NzIHJv dXRlcnMgaW4gdGhlIG5leHQgNSB0byAxMCB5ZWFycywgYSByZWFzb25hYmxlIHN1Z2dlc3Rpb24g Zm9yIFJUUCBDb25nZXN0aW9uIGNvbnRyb2wgbWF5IGxlYWQgdG8gQ29EZWwgb3ZlciBDb0RlbC4g IEFuIGVuaGFuY2VkIHZlcnNpb24gb2YgQ29EZWwgZm9yIGltcGxlbWVudGF0aW9uIGluIHRoZSBS VFAgc3RhY2sgKG9yIGF0IHRoZSBjb2RlYyBlbmNhcHN1bGF0aW9uIGxheWVyKSBwcm92aWRlcyBj bGVhciBmcmFtZSBkZW1hcmNhdGlvbiBhbmQgcGFja2V0IG1hcHBpbmcgKGZyYW1lIG5vID09IHBh Y2tldHMgbi4ubSksIGFuZCBkcm9wcyBlbnRpcmUgZnJhbWVzIGJhc2VkIG9uOiBhbiBhc3N1bXB0 aW9uIChvciBkZXRlcm1pbmF0aW9uKSBvZiB0YXJnZXRlZCBtYXhpbXVtIGJhbmR3aWR0aCBhbmQg KG9wdGlvbmFsLCBidXQgaGlnaGx5IHJlY29tbWVuZGVkKSBzb21lIGZvcm0gb2YgRUNOLiAgTm90 aWZpY2F0aW9ucyBhcmUgdGhlbiBwcm92aWRlZCBiYWNrIHRvIHRoZSBhcHBsaWNhdGlvbiBhcyB0 byB3aGljaCBmcmFtZXMgd2VyZSBkcm9wcGVkLCBhbmQgdGhlIGFwcGxpY2F0aW9uIGNhbiBtYWtl IHRoZSBkZWNpc2lvbiBvbiBob3cgaXQgc2Vla3MgdG8gY2hhbmdlIGl0cyBiZWhhdmlvciBpZiBh dCBhbGwgW1RoaXMgY29tYmluZXMgd2VsbCB3aXRoIHRoZSByZWNlaXZlciBiYXNlZCBub3RpZmlj YXRpb24uICBJZiBpdCBjaG9vc2VzIG5vdCB0bywgdGhlIFJUUCBzdGFjayBlbmZvcmNlcyAiZmFp cm5lc3MiIGJ5IGRlZ3JhZGluZyB0aGUgYXBwbGljYXRpb24gcGVyZm9ybWFuY2UgaW4gZnVsbCB1 bml0cy4gIEEgZ29vZCBpbXBsZW1lbnRhdGlvbiBvZiB0aGlzIHNob3VsZCB1c2UgRkVDIHRvIG1h aW50YWluIGEgY29uc3RhbnQgYml0cmF0ZSBkZXNwaXRlIHRoZSB2YXJpYXRpb25zIG9mIHRoZSBi aXRyYXRlIGluIHRoZSB1bmRlcmx5aW5nIHN0cmVhbS4gIFdoaWxlIGl0IGRvZXMgdXNlIG1vcmUg YmFuZHdpZHRoIHRoYW4gaW1tZWRpYXRlbHkgbmVjZXNzYXJ5IGl0IHByb3ZpZGVzIGdyZWF0IHN0 YWJpbGl0eSBmb3IgdGhlIHN0cmVhbSBpbiBjb29wZXJhdGlvbiB3aXRoIGJvdGggbG9uZyBsaXZl ZCBUQ1Agc3RyZWFtcyBhbmQgc2hvcnQgbGl2ZWQgYnVyc3R5IHN0cmVhbXMuICBJdCBhbHNvIHBy ZXZlbnRzIHVuZmFpciBjb21wZXRpdGlvbiBmcm9tIFRDUC4gIEluIGFkZGl0aW9uLCBpdCBwcm92 aWRlcyBhZGRpdGlvbmFsIHJlc2lsaWVuY3kgZm9yIGhhbmRsaW5nIGludGVybWl0dGVudCBwYWNr ZXRzIGxvc3MgZnJvbSBXaUZpIGFuZCBvdGhlciB3aXJlbGVzcy9jZWxsdWxhciB0cmFuc21pc3Np b25zLg0KDQpJIHRoaW5rIHRoZSBiZW5lZml0cyBvZiB0aGlzIHNvbHV0aW9uIG91dHdlaWdoIGFu eSBvdGhlciB0aGF0IGhhcyBiZWVuIHByb3Bvc2VkLCBhbmQgc29sdmVzIG1hbnkgb2YgdGhlIGRp ZmZpY3VsdCBjaGFsbGVuZ2VzIHByZXNlbnRlZC4gIFdoaWxlIEkgaGF2ZSBub3QgeWV0IGJ1aWxk IGEgZnVsbCB3b3JraW5nIG1vZGVsLCBJdCBzaG91bGQgd29yayBpbiBhdCBsZWFzdCBhcyBtYW55 IHBsYWNlcyBhcyBDb0RlbCB3b3JrcywgYW5kIG11Y2ggcmVzZWFyY2ggaGFzIGJlZW4gZG9uZSBh bmQgY29udGludWVzIHRvIGJlIGRvbmUgb24gaG93IHdlbGwgQ29EZWwgaGFuZGxlcyBmYWlybmVz cy4NCg0KSSB3b3VsZCBsb3ZlIHRvIGhlYXIgZXZlcnlvbmUncyB0aG91Z2h0cyBvbiB0aGlzLiAg UGxlYXNlIHNlbmQgbWUgeW91ciBmZWVkYmFjay4NCg0KVGhhbmtzLA0KRGFuDQo= --_000_3879D71E758A7E4AA99A35DD8D41D3D91D47DF36xmbrcdx14ciscoc_ Content-Type: text/html; charset="utf-8" Content-Transfer-Encoding: base64 PGh0bWwgeG1sbnM6dj0idXJuOnNjaGVtYXMtbWljcm9zb2Z0LWNvbTp2bWwiIHhtbG5zOm89InVy bjpzY2hlbWFzLW1pY3Jvc29mdC1jb206b2ZmaWNlOm9mZmljZSIgeG1sbnM6dz0idXJuOnNjaGVt YXMtbWljcm9zb2Z0LWNvbTpvZmZpY2U6d29yZCIgeG1sbnM6bT0iaHR0cDovL3NjaGVtYXMubWlj cm9zb2Z0LmNvbS9vZmZpY2UvMjAwNC8xMi9vbW1sIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcv VFIvUkVDLWh0bWw0MCI+DQo8aGVhZD4NCjxtZXRhIGh0dHAtZXF1aXY9IkNvbnRlbnQtVHlwZSIg Y29udGVudD0idGV4dC9odG1sOyBjaGFyc2V0PXV0Zi04Ij4NCjxtZXRhIG5hbWU9IkdlbmVyYXRv ciIgY29udGVudD0iTWljcm9zb2Z0IFdvcmQgMTQgKGZpbHRlcmVkIG1lZGl1bSkiPg0KPHN0eWxl PjwhLS0NCi8qIEZvbnQgRGVmaW5pdGlvbnMgKi8NCkBmb250LWZhY2UNCgl7Zm9udC1mYW1pbHk6 Q2FsaWJyaTsNCglwYW5vc2UtMToyIDE1IDUgMiAyIDIgNCAzIDIgNDt9DQpAZm9udC1mYWNlDQoJ e2ZvbnQtZmFtaWx5OlRhaG9tYTsNCglwYW5vc2UtMToyIDExIDYgNCAzIDUgNCA0IDIgNDt9DQov KiBTdHlsZSBEZWZpbml0aW9ucyAqLw0KcC5Nc29Ob3JtYWwsIGxpLk1zb05vcm1hbCwgZGl2Lk1z b05vcm1hbA0KCXttYXJnaW46MGluOw0KCW1hcmdpbi1ib3R0b206LjAwMDFwdDsNCglmb250LXNp emU6MTIuMHB0Ow0KCWZvbnQtZmFtaWx5OiJUaW1lcyBOZXcgUm9tYW4iLCJzZXJpZiI7fQ0KYTps aW5rLCBzcGFuLk1zb0h5cGVybGluaw0KCXttc28tc3R5bGUtcHJpb3JpdHk6OTk7DQoJY29sb3I6 Ymx1ZTsNCgl0ZXh0LWRlY29yYXRpb246dW5kZXJsaW5lO30NCmE6dmlzaXRlZCwgc3Bhbi5Nc29I eXBlcmxpbmtGb2xsb3dlZA0KCXttc28tc3R5bGUtcHJpb3JpdHk6OTk7DQoJY29sb3I6cHVycGxl Ow0KCXRleHQtZGVjb3JhdGlvbjp1bmRlcmxpbmU7fQ0Kc3Bhbi5FbWFpbFN0eWxlMTcNCgl7bXNv LXN0eWxlLXR5cGU6cGVyc29uYWwtcmVwbHk7DQoJZm9udC1mYW1pbHk6IkNhbGlicmkiLCJzYW5z LXNlcmlmIjsNCgljb2xvcjp3aW5kb3d0ZXh0O30NCi5Nc29DaHBEZWZhdWx0DQoJe21zby1zdHls ZS10eXBlOmV4cG9ydC1vbmx5Ow0KCWZvbnQtZmFtaWx5OiJDYWxpYnJpIiwic2Fucy1zZXJpZiI7 fQ0KQHBhZ2UgV29yZFNlY3Rpb24xDQoJe3NpemU6OC41aW4gMTEuMGluOw0KCW1hcmdpbjoxLjBp biAxLjBpbiAxLjBpbiAxLjBpbjt9DQpkaXYuV29yZFNlY3Rpb24xDQoJe3BhZ2U6V29yZFNlY3Rp b24xO30NCi0tPjwvc3R5bGU+PCEtLVtpZiBndGUgbXNvIDldPjx4bWw+DQo8bzpzaGFwZWRlZmF1 bHRzIHY6ZXh0PSJlZGl0IiBzcGlkbWF4PSIxMDI2IiAvPg0KPC94bWw+PCFbZW5kaWZdLS0+PCEt LVtpZiBndGUgbXNvIDldPjx4bWw+DQo8bzpzaGFwZWxheW91dCB2OmV4dD0iZWRpdCI+DQo8bzpp ZG1hcCB2OmV4dD0iZWRpdCIgZGF0YT0iMSIgLz4NCjwvbzpzaGFwZWxheW91dD48L3htbD48IVtl bmRpZl0tLT4NCjwvaGVhZD4NCjxib2R5IGxhbmc9IkVOLVVTIiBsaW5rPSJibHVlIiB2bGluaz0i cHVycGxlIj4NCjxkaXYgY2xhc3M9IldvcmRTZWN0aW9uMSI+DQo8cCBjbGFzcz0iTXNvTm9ybWFs Ij48c3BhbiBzdHlsZT0iZm9udC1zaXplOjExLjBwdDtmb250LWZhbWlseTomcXVvdDtDYWxpYnJp JnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVvdDsiPkhpIERhbiw8bzpwPjwvbzpwPjwvc3Bhbj48 L3A+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48c3BhbiBzdHlsZT0iZm9udC1zaXplOjExLjBwdDtm b250LWZhbWlseTomcXVvdDtDYWxpYnJpJnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVvdDsiPjxv OnA+Jm5ic3A7PC9vOnA+PC9zcGFuPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0 eWxlPSJmb250LXNpemU6MTEuMHB0O2ZvbnQtZmFtaWx5OiZxdW90O0NhbGlicmkmcXVvdDssJnF1 b3Q7c2Fucy1zZXJpZiZxdW90OyI+SSBoYXZlIHRvIGFncmVlIHdpdGggdGhlIG90aGVyIGNvbW1l bnRlcnMuIEFRTSBpbiBhIHJvdXRlciBpcyBmdW5kYW1lbnRhbGx5IGRpZmZlcmVudCB0aGFuIEND IGluIGFuIGVuZHBvaW50LiBBUU0gbWFuYWdlcyBhIHBlci1ob3AgcXVldWUgdG8gYWJzb3JiIGJ1 cnN0cyB3aGlsZSBhdm9pZGluZw0KIHBlcnNpc3RlbnQgcXVldWVzLiBJdCBrbm93cyB0aGUgYWJz b2x1dGUgdHJhbnNpdCB0aW1lIG9mIGVhY2ggcGFja2V0IHRocm91Z2ggdGhlIHF1ZXVlIGFuZCBp dHMgZGVwdGgsIGFuZCBjYW4gdHJ5IHRvIG1pbmltaXplIGVpdGhlciBvciBib3RoLjxvOnA+PC9v OnA+PC9zcGFuPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0eWxlPSJmb250LXNp emU6MTEuMHB0O2ZvbnQtZmFtaWx5OiZxdW90O0NhbGlicmkmcXVvdDssJnF1b3Q7c2Fucy1zZXJp ZiZxdW90OyI+PG86cD4mbmJzcDs8L286cD48L3NwYW4+PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1h bCI+PHNwYW4gc3R5bGU9ImZvbnQtc2l6ZToxMS4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJy aSZxdW90OywmcXVvdDtzYW5zLXNlcmlmJnF1b3Q7Ij5JZiBJIHVuZGVyc3RhbmQgeW91ciBwcm9w b3NhbCwgeW91IHdhbnQgdGhlIHNlbmRlciB0byB0cmVhdCB0aGUgZW50aXJlIG5ldHdvcmsgYXMg YSBiaWcgcXVldWUsIHVzaW5nIHJlY2VpdmVyIGZlZWRiYWNrIGFzIGEgcHJveHkgZm9yIGRpcmVj dCBtZWFzdXJlbWVudCBvZiBwYWNrZXQgdHJhbnNpdA0KIHRpbWVzIHRocm91Z2ggdGhlIOKAnHF1 ZXVl4oCdLiBUbyBnZXQgYWJzb2x1dGUgdHJhbnNpdCB0aW1lcywgdGhlIHNlbmRlciBhbmQgcmVj ZWl2ZXIgd291bGQgbmVlZCB0aWdodCB0aW1lIHN5bmMsIHdoaWNoIHNlZW1zIGV4dHJlbWUgdG8g cmVxdWlyZS4gKFJUUCBoYXMgbmV2ZXIgcmVxdWlyZWQgdGhpcywgZXZlbiBmb3IgdGhpbmdzIHdo aWNoIHNlZW0gcmVsYXRlZCB0byB0aW1lIHN5bmMgbGlrZSBhL3YgKGxpcCkgc3luYy4pIFdpdGhv dXQgdGltZSBzeW5jLA0KIHlvdSBjYW4gb25seSBtZWFzdXJlIFJUVCAobGlrZSBSVFApLCB3aGlj aCBjYW4gYmUgc2tld2VkIGJ5IHRoZSByZXZlcnNlIHBhdGguIE9yIHlvdSBjYW4gbWVhc3VyZSBp bnRlci1hcnJpdmFsIGppdHRlciAoYWdhaW4gbGlrZSBSVFApLCB3aGljaCBjYW4gYmUgc2tld2Vk IGJ5IGFuIHVua25vd24gYmFzZSBkZWxheS4gRWl0aGVyIHdheSwgSSBkb27igJl0IHRoaW5rIHlv dSBnZXQgcmVsaWFibGUgbWVhc3VyZW1lbnRzIGZvciB0aGUgYWJzb2x1dGUgcXVldWUNCiBkZXB0 aC9kZWxheSB0aGF0IENvRGVsIG9yIG90aGVyIEFRTXMgd2FudC4gSWYgdGhlIHNlbmRlciBhY3Rz IG9uIHJlbGF0aXZlIHJhdGhlciB0aGFuIGFic29sdXRlIGRlbGF5cywgdGhhdCByZXNlbWJsZXMg dGhlIGN1cnJlbnQgUk1DQVQgY2FuZGlkYXRlcyByYXRoZXIgdGhhbiBDb0RlbCBvciBvdGhlciBB UU1zLjxvOnA+PC9vOnA+PC9zcGFuPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3JtYWwiPjxzcGFuIHN0 eWxlPSJmb250LXNpemU6MTEuMHB0O2ZvbnQtZmFtaWx5OiZxdW90O0NhbGlicmkmcXVvdDssJnF1 b3Q7c2Fucy1zZXJpZiZxdW90OyI+PG86cD4mbmJzcDs8L286cD48L3NwYW4+PC9wPg0KPHAgY2xh c3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5bGU9ImZvbnQtc2l6ZToxMS4wcHQ7Zm9udC1mYW1pbHk6 JnF1b3Q7Q2FsaWJyaSZxdW90OywmcXVvdDtzYW5zLXNlcmlmJnF1b3Q7Ij5SZWdhcmRpbmcgdGhl IOKAnE5hemnigJ0gYXNwZWN0IChubyB2aWRlbyBmb3IgeW91LCBpZiB5b3UgYnVyc3QpLCBJIGNh buKAmXQgdGVsbCBpZiB5b3Ugd2VyZSBzZXJpb3VzIG9yIGp1c3Qgd2FudGVkIOKAnE5hemnigJ0g b24gdGhlIEJlcmxpbiBhZ2VuZGEgZm9yIGxhdWdocy4gSSBjZXJ0YWlubHkgbGF1Z2hlZOKApg0K IDopPG86cD48L286cD48L3NwYW4+PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5 bGU9ImZvbnQtc2l6ZToxMS4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90OywmcXVv dDtzYW5zLXNlcmlmJnF1b3Q7Ij48bzpwPiZuYnNwOzwvbzpwPjwvc3Bhbj48L3A+DQo8cCBjbGFz cz0iTXNvTm9ybWFsIj48c3BhbiBzdHlsZT0iZm9udC1zaXplOjExLjBwdDtmb250LWZhbWlseTom cXVvdDtDYWxpYnJpJnF1b3Q7LCZxdW90O3NhbnMtc2VyaWYmcXVvdDsiPk1vPG86cD48L286cD48 L3NwYW4+PC9wPg0KPHAgY2xhc3M9Ik1zb05vcm1hbCI+PHNwYW4gc3R5bGU9ImZvbnQtc2l6ZTox MS4wcHQ7Zm9udC1mYW1pbHk6JnF1b3Q7Q2FsaWJyaSZxdW90OywmcXVvdDtzYW5zLXNlcmlmJnF1 b3Q7Ij48bzpwPiZuYnNwOzwvbzpwPjwvc3Bhbj48L3A+DQo8cCBjbGFzcz0iTXNvTm9ybWFsIj48 Yj48c3BhbiBzdHlsZT0iZm9udC1zaXplOjEwLjBwdDtmb250LWZhbWlseTomcXVvdDtUYWhvbWEm cXVvdDssJnF1b3Q7c2Fucy1zZXJpZiZxdW90OyI+RnJvbTo8L3NwYW4+PC9iPjxzcGFuIHN0eWxl PSJmb250LXNpemU6MTAuMHB0O2ZvbnQtZmFtaWx5OiZxdW90O1RhaG9tYSZxdW90OywmcXVvdDtz YW5zLXNlcmlmJnF1b3Q7Ij4gcm1jYXQtYm91bmNlc0BpZXRmLm9yZyBbbWFpbHRvOnJtY2F0LWJv dW5jZXNAaWV0Zi5vcmddDQo8Yj5PbiBCZWhhbGYgT2YgPC9iPkRhbiBXZWJlcjxicj4NCjxiPlNl bnQ6PC9iPiBTYXR1cmRheSwgTWF5IDI1LCAyMDEzIDc6MDUgUE08YnI+DQo8Yj5Ubzo8L2I+IHJt Y2F0QGlldGYub3JnPGJyPg0KPGI+U3ViamVjdDo8L2I+IFtybWNhdF0gJnF1b3Q7U291cCBOYXpp JnF1b3Q7IFJUUCBDb25nZXN0aW9uIENvbnRyb2w8bzpwPjwvbzpwPjwvc3Bhbj48L3A+DQo8cCBj bGFzcz0iTXNvTm9ybWFsIj48bzpwPiZuYnNwOzwvbzpwPjwvcD4NCjxwIGNsYXNzPSJNc29Ob3Jt YWwiPkhpIGd1eXMsPGJyPg0KPGJyPg0KSSd2ZSBiZWVuIHJldmlld2luZyBDb0RlbCwgYW5kIGl0 J3MgY2xlYXIgaG93IGl0IHdvcmtzIHJlYXNvbmFibHkgd2VsbCBmb3IgVENQLiZuYnNwOyBJdCdz IG9ubHkgc2xpZ2h0bHkgbW9yZSBjb21wbGljYXRlZCB0aGFuIGFuIGltcGxlbWVudGF0aW9uIHVz aW5nIGEgZml4ZWQgdGltZXN0YW1wIHBlciBwYWNrZXQgZXhwaXJhdGlvbi4mbmJzcDsgVGhlIG1p bm9yIGRpZmZlcmVuY2Ugb2NjdXJzIHdoZW4gaXQgZ29lcyBpbnRvIGl0cyBkcm9wcGluZyBzdGF0 ZSB3aGljaA0KIHVzZXMgYSBzcXVhcmUgcm9vdCBzY2FsaW5nIGZhY3RvciBmb3IgdGhlIHRpbWUg YmFzZWQgb24gdGhlIG51bWJlciBvZiBwcmV2aW91c2x5IGRyb3BwZWQgcGFja2V0cyBpbiBhIHNl cXVlbmNlLiZuYnNwOyBUaGlzIHRha2VzIGFkdmFudGFnZSBvZiBhIGtub3duIGJlaGF2aW9yIG9m IFRDUCBjb25nZXN0aW9uIGNvbnRyb2wgYWxnb3JpdGhtcyB3aGljaCBleHBlY3QgY29uZ2VzdGlv biB0byBoYXBwZW4gaW4gbGFyZ2UgYnVyc3RzLjxicj4NCjxicj4NCldoZW4gYXBwbGllZCB0byBS VFAgdW5rbm93aW5nbHksIHRoZSBiZWhhdmlvciBjb3VsZCBiZSBwcmV0dHkgZGlzYXN0cm91cyBv biB2aWRlbyBjb250ZW50LiZuYnNwOyBBbHRob3VnaCBJIGRvdWJ0IGl0J3MgYW55IHdvcnNlIHRo YW4gYWN0dWFsIGNvbXBldGluZyBjb250ZW50IHdpdGggbm8gQVFNLCBhIHBhcnRpY3VsYXIgY2Fz ZSBkb2VzIHN0YW5kIG91dC4mbmJzcDsgV2hlbiBDb0RlbCBpcyBpbiBwbGFjZSB3aGVyZSB0aGVy ZSBpcyBubyBjb21wZXRpbmcgdHJhZmZpYw0KIGFuZCB0aGUgUlRQIHNlbmRlciBidXJzdHMgdGhl IHdpcmUgd2l0aG91dCBwYWNpbmcgaW4gcmVzcGVjdCB0byBtYXhpbXVtIHN0cmVhbSBiaXRyYXRl LCBDb0RlbCBpcyBsaWtlbHkgdG8gYnVyc3QgZHJvcCBwYWNrZXRzIGJlY2F1c2Ugb2Ygb3ZlcmZs b3cgb24gdGhlIHF1ZXVlIHRpbWUuJm5ic3A7IEkgdGhpbmsNCjxiPnRoaXMgYmVoYXZpb3IgaXMg ZXh0cmVtZWx5IGRlc2lyYWJsZTwvYj4uJm5ic3A7IFRoaXMgd2lsbCBicmluZyBhd2FyZW5lc3Mg dG8gYWxsIHZlbmRvcnMgYW5kIGltcGxlbWVudG9ycyB0aGF0IHRoZWlyIGltcGxlbWVudGF0aW9u cyB3ZXJlIHdvcmtpbmcgZGVzcGl0ZSB0aGUgZmFjdCB0aGF0IHRoZXkgd2VyZSBpbXByb3Blci4m bmJzcDsNCjxicj4NCjxicj4NClRoaXMga2luZCBvZiBiZWhhdmlvciBjYW4gYmUgZW5oYW5jZWQg YW5kIGF1Z21lbnRlZCBpbiBhIHdheSB0aGF0IGNhbiBiZSB1c2VkIHRvIGV4cGVkaXRlIHRoZSBp bXBsZW1lbnRhdGlvbiBvZiBlZmZlY3RpdmUgUlRQIENvbmdlc3Rpb24gQ29udHJvbC4mbmJzcDsm bmJzcDsgSWYgd2Ugd2VyZSB0byBpbXBsZW1lbnQNCjxiPnJlY2VpdmVyIHNpZGUgQ29EZWw8L2I+ IDxiPmZvciBkcm9wcGluZyAmcXVvdDtmcmFtZXMmcXVvdDsgb3IgJnF1b3Q7bWVzc2FnZXMmcXVv dDsgb2YgUlRQIHBhY2tldHMgb24gbmV3IGltcGxlbWVudGF0aW9uczwvYj4sIHdlIGNvdWxkIGJl Y29tZSB0aGUgJnF1b3Q7U291cCBOYXppJnF1b3Q7IGFuZCBzdGFydCBlZmZlY3RpdmVseSBpZGVu dGlmeWluZyBpbXByb3BlciBpbXBsZW1lbnRhdGlvbnMgYXMgd2VsbCBhcyByZW5kZXJpbmcgdGhl bSBpbm9wZXJhYmxlLiZuYnNwOw0KPGI+SWYgaW1wbGVtZW50ZWQgYnkgb25lIG9mIHRoZSBtYWpv ciBXZWJSVEMgYnJvd3NlciBpbXBsZW1lbnRhdGlvbnMsIDwvYj5hIDxiPmNoYWluIHJlYWN0aW9u IG1heSBkZXZlbG9wIHRoYXQgZm9yY2VzIGltcGxlbWVudGF0aW9uIG9mIFJUUCBjb25nZXN0aW9u IGNvbnRyb2wgdXAgdGhlIHBpcGVsaW5lPC9iPi4mbmJzcDsgSWYgdXNlZnVsIGZlZWRiYWNrIGlz IGRlbGl2ZXJlZCBiYWNrIHRvIHRoZSBzZW5kZXIsIHdoaWNoIHJlYWxseSBuZWVkcyB0byBiZQ0K IG5ldCB0cmFuc2xhdGVkIHRvIDxiPmZyYW1lcyBwcm9jZXNzZWQgYW5kIGZyYW1lcyBkcm9wcGVk PC9iPiwgYW4gYXBwbGljYXRpb24gd2l0aCBpdHMgZW5jb2RlciBjb3VsZCByZWFzb25hYmx5IGFk anVzdC4mbmJzcDsNCjxiPlRoaXMgbWF5IHNvbHZlIGZhaXJuZXNzIHJlbGF0ZWQgcHJvYmxlbXMg YmVjYXVzZSB0aGUgcmVjZWl2ZXIgY291bGQgaWRlbnRpZnkgaWYgdGhlIHNlbmRlciBvdmVyZmxv d2VkIHRoZSBxdWV1ZXMgYnkgZXZhbHVhdGluZyBhY3R1YWwgYXJyaXZhbCB0aW1lIGNvbXBhcmVk IHdpdGggZnJhbWUgcHJlc2VudGF0aW9uIHRpbWUgKGNvbnZlcnRlZCBSVFAgdGltZXN0YW1wcyku PC9iPiZuYnNwOyBJZiB0aGUgcmVjZWl2ZXIgZW5mb3JjZXMgdGhpcyBjb25zdHJhaW50LA0KIGZh aXJuZXNzIG9uIFJUUCBzdHJlYW1zIGlzIGVmZmVjdGl2ZWx5IGluIGZvcmNlIGJlY2F1c2UgaW1w bGVtZW50YXRpb25zIGFyZSByZW5kZXJlZCBpbm9wZXJhYmxlLCBhbmQgaXQgd29ya3Mgc2FmZWx5 IHdpdGhpbiB0aGUgc2NvcGUgb2YgQ29EZWwuJm5ic3A7IFRoaXMgaW1wbGllcyB0aGF0IFRDUCB3 b3VsZCBiZSBvbmx5IGF0IG1vc3QgYWZmZWN0ZWQgaW4gdGhlIHNhbWUgd2F5IHRoYXQgYW5vdGhl ciBUQ1Agc3RyZWFtIHdvdWxkLiZuYnNwOw0KPGJyPg0KPGJyPg0KQW5kIGZpbmFsbHkgdGhpcyBs ZWFkcyB0byBteSBzdWdnZXN0ZWQgc29sdXRpb24gZm9yIHNlbmRlciBzaWRlIGNvbmdlc3Rpb24g Y29udHJvbC4mbmJzcDsgQmFzZWQgb24gbXkgYXNzdW1wdGlvbiB0aGF0IENvRGVsIGltcGxlbWVu dGF0aW9uIGZvciBBUU0gaXMgb24gdGhlIGhvcml6b24gYWNyb3NzIHJvdXRlcnMgaW4gdGhlIG5l eHQgNSB0byAxMCB5ZWFycywgYSByZWFzb25hYmxlIHN1Z2dlc3Rpb24gZm9yIFJUUCBDb25nZXN0 aW9uIGNvbnRyb2wgbWF5DQogbGVhZCB0byBDb0RlbCBvdmVyIENvRGVsLiZuYnNwOyBBbiBlbmhh bmNlZCB2ZXJzaW9uIG9mIENvRGVsIGZvciBpbXBsZW1lbnRhdGlvbiBpbiB0aGUgUlRQIHN0YWNr IChvciBhdCB0aGUgY29kZWMgZW5jYXBzdWxhdGlvbiBsYXllcikgcHJvdmlkZXMgY2xlYXIgZnJh bWUgZGVtYXJjYXRpb24gYW5kIHBhY2tldCBtYXBwaW5nIChmcmFtZSBubyA9PSBwYWNrZXRzIG4u Lm0pLCBhbmQgZHJvcHMgZW50aXJlIGZyYW1lcyBiYXNlZCBvbjogYW4gYXNzdW1wdGlvbg0KIChv ciBkZXRlcm1pbmF0aW9uKSBvZiB0YXJnZXRlZCBtYXhpbXVtIGJhbmR3aWR0aCBhbmQgKG9wdGlv bmFsLCBidXQgaGlnaGx5IHJlY29tbWVuZGVkKSBzb21lIGZvcm0gb2YgRUNOLiZuYnNwOyBOb3Rp ZmljYXRpb25zIGFyZSB0aGVuIHByb3ZpZGVkIGJhY2sgdG8gdGhlIGFwcGxpY2F0aW9uIGFzIHRv IHdoaWNoIGZyYW1lcyB3ZXJlIGRyb3BwZWQsIGFuZCB0aGUgYXBwbGljYXRpb24gY2FuIG1ha2Ug dGhlIGRlY2lzaW9uIG9uIGhvdyBpdCBzZWVrcyB0bw0KIGNoYW5nZSBpdHMgYmVoYXZpb3IgaWYg YXQgYWxsIFtUaGlzIGNvbWJpbmVzIHdlbGwgd2l0aCB0aGUgcmVjZWl2ZXIgYmFzZWQgbm90aWZp Y2F0aW9uLiZuYnNwOyBJZiBpdCBjaG9vc2VzIG5vdCB0bywgdGhlIFJUUCBzdGFjayBlbmZvcmNl cyAmcXVvdDtmYWlybmVzcyZxdW90OyBieSBkZWdyYWRpbmcgdGhlIGFwcGxpY2F0aW9uIHBlcmZv cm1hbmNlIGluIGZ1bGwgdW5pdHMuJm5ic3A7IEEgZ29vZCBpbXBsZW1lbnRhdGlvbiBvZiB0aGlz IHNob3VsZA0KPGI+dXNlIEZFQyB0byBtYWludGFpbiBhIGNvbnN0YW50IGJpdHJhdGUgZGVzcGl0 ZSB0aGUgdmFyaWF0aW9ucyBvZiB0aGUgYml0cmF0ZSBpbiB0aGUgdW5kZXJseWluZyBzdHJlYW0u Jm5ic3A7DQo8L2I+V2hpbGUgaXQgZG9lcyB1c2UgbW9yZSBiYW5kd2lkdGggdGhhbiA8aT5pbW1l ZGlhdGVseSBuZWNlc3Nhcnk8L2k+IGl0IHByb3ZpZGVzIGdyZWF0IHN0YWJpbGl0eSBmb3IgdGhl IHN0cmVhbSBpbg0KPGI+Y29vcGVyYXRpb24gd2l0aCBib3RoIGxvbmcgbGl2ZWQgVENQIHN0cmVh bXMgYW5kIHNob3J0IGxpdmVkIGJ1cnN0eSBzdHJlYW1zPC9iPi4mbmJzcDsgSXQgYWxzbw0KPGI+ cHJldmVudHMgdW5mYWlyIGNvbXBldGl0aW9uIGZyb20gVENQPC9iPi4mbmJzcDsgSW4gYWRkaXRp b24sIGl0IDxiPnByb3ZpZGVzIGFkZGl0aW9uYWwgcmVzaWxpZW5jeSBmb3IgaGFuZGxpbmcgaW50 ZXJtaXR0ZW50IHBhY2tldHMgbG9zczwvYj4gZnJvbSBXaUZpIGFuZCBvdGhlciB3aXJlbGVzcy9j ZWxsdWxhciB0cmFuc21pc3Npb25zLjxicj4NCjxicj4NCkkgdGhpbmsgdGhlIGJlbmVmaXRzIG9m IHRoaXMgc29sdXRpb24gb3V0d2VpZ2ggYW55IG90aGVyIHRoYXQgaGFzIGJlZW4gcHJvcG9zZWQs IGFuZCBzb2x2ZXMgbWFueSBvZiB0aGUgZGlmZmljdWx0IGNoYWxsZW5nZXMgcHJlc2VudGVkLiZu YnNwOyBXaGlsZSBJIGhhdmUgbm90IHlldCBidWlsZCBhIGZ1bGwgd29ya2luZyBtb2RlbCwgSXQg c2hvdWxkIHdvcmsgaW4gYXQgbGVhc3QgYXMgbWFueSBwbGFjZXMgYXMgQ29EZWwgd29ya3MsIGFu ZCBtdWNoIHJlc2VhcmNoDQogaGFzIGJlZW4gZG9uZSBhbmQgY29udGludWVzIHRvIGJlIGRvbmUg b24gaG93IHdlbGwgQ29EZWwgaGFuZGxlcyBmYWlybmVzcy48YnI+DQo8YnI+DQpJIHdvdWxkIGxv dmUgdG8gaGVhciBldmVyeW9uZSdzIHRob3VnaHRzIG9uIHRoaXMuJm5ic3A7IFBsZWFzZSBzZW5k IG1lIHlvdXIgZmVlZGJhY2suPGJyPg0KPGJyPg0KVGhhbmtzLDxicj4NCkRhbjxvOnA+PC9vOnA+ PC9wPg0KPC9kaXY+DQo8L2JvZHk+DQo8L2h0bWw+DQo= --_000_3879D71E758A7E4AA99A35DD8D41D3D91D47DF36xmbrcdx14ciscoc_-- From abegen@cisco.com Thu May 30 13:45:53 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id DD50B21F92BB for ; Thu, 30 May 2013 13:45:53 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -10.599 X-Spam-Level: X-Spam-Status: No, score=-10.599 tagged_above=-999 required=5 tests=[AWL=-0.000, BAYES_00=-2.599, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_HI=-8] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id osS+PNrSqX+1 for ; Thu, 30 May 2013 13:45:48 -0700 (PDT) Received: from rcdn-iport-3.cisco.com (rcdn-iport-3.cisco.com [173.37.86.74]) by ietfa.amsl.com (Postfix) with ESMTP id 0F32421F91B2 for ; Thu, 30 May 2013 13:45:47 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/simple; d=cisco.com; i=@cisco.com; l=13561; q=dns/txt; s=iport; t=1369946748; x=1371156348; h=from:to:cc:subject:date:message-id:in-reply-to: mime-version; bh=5ROVUSP8YHQ88yu7fFtO8Aur5ETIo7Ly4HQvucb7BiM=; b=f5u8RmIdA2KV0FqqRkMvNnBHUZ6waWnI8zfgHQ8GoeDAP3MIhoZI4TL5 B4MnpQTgQG7oZew3mfFfa3HP5XgTjPSf47O5FB86TRwRejGHw9qDTrRfO M2evXvtdpdMPRCqi1IN+4/xyUfPSngrxn9uMKSChS6pUsl+h4GHnwFy4h c=; X-IronPort-Anti-Spam-Filtered: true X-IronPort-Anti-Spam-Result: AgYFAGK5p1GtJV2a/2dsb2JhbABZgkUjIYNrvlwNcRZ0giMBAQEDASNIDgUNAQgRAwECCx0DAgQwFAkIAgQOBQiHfwYBqT2RbY1bgRAgEQcGgj0zYQOofoMPgWk+ X-IronPort-AV: E=Sophos;i="4.87,773,1363132800"; d="scan'208,217";a="216945556" Received: from rcdn-core-3.cisco.com ([173.37.93.154]) by rcdn-iport-3.cisco.com with ESMTP; 30 May 2013 20:45:47 +0000 Received: from xhc-aln-x12.cisco.com (xhc-aln-x12.cisco.com [173.36.12.86]) by rcdn-core-3.cisco.com (8.14.5/8.14.5) with ESMTP id r4UKjll7024857 (version=TLSv1/SSLv3 cipher=AES128-SHA bits=128 verify=FAIL); Thu, 30 May 2013 20:45:47 GMT Received: from xmb-aln-x01.cisco.com ([fe80::747b:83e1:9755:d453]) by xhc-aln-x12.cisco.com ([173.36.12.86]) with mapi id 14.02.0318.004; Thu, 30 May 2013 15:45:46 -0500 From: "Ali C. Begen (abegen)" To: Dan Weber Thread-Topic: [rmcat] "Soup Nazi" RTP Congestion Control Thread-Index: AQHOWZxLNJY3y1cPlE+gbu/SBSn9ZpkbRk0AgAAKEQCAAAlNgIAAEqEAgAAWGYCAANBOAIAAUT0AgAIcRIA= Date: Thu, 30 May 2013 20:45:46 +0000 Message-ID: In-Reply-To: Accept-Language: en-US Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: user-agent: Microsoft-MacOutlook/14.3.4.130416 x-originating-ip: [10.61.111.39] Content-Type: multipart/alternative; boundary="_000_C15918F2FCDA0243A7C919DA7C4BE9940D0ECA42xmbalnx01ciscoc_" MIME-Version: 1.0 Cc: rmcat WG , "Fred Baker \(fred\)" , Kevin Gross Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Thu, 30 May 2013 20:45:54 -0000 --_000_C15918F2FCDA0243A7C919DA7C4BE9940D0ECA42xmbalnx01ciscoc_ Content-Type: text/plain; charset="utf-8" Content-Transfer-Encoding: base64 RnJvbTogRGFuIFdlYmVyIDxkYW5AbWFya2V0c291cC5jb208bWFpbHRvOmRhbkBtYXJrZXRzb3Vw LmNvbT4+DQpEYXRlOiBXZWRuZXNkYXksIE1heSAyOSwgMjAxMyA2OjMyIFBNDQpUbzogIkFsaSBD LiBCZWdlbiIgPGFiZWdlbkBjaXNjby5jb208bWFpbHRvOmFiZWdlbkBjaXNjby5jb20+Pg0KQ2M6 ICJGcmVkIEJha2VyIChmcmVkKSIgPGZyZWRAY2lzY28uY29tPG1haWx0bzpmcmVkQGNpc2NvLmNv bT4+LCBybWNhdCBXRyA8cm1jYXRAaWV0Zi5vcmc8bWFpbHRvOnJtY2F0QGlldGYub3JnPj4sIEtl dmluIEdyb3NzIDxrZXZpbi5ncm9zc0BhdmFudy5jb208bWFpbHRvOmtldmluLmdyb3NzQGF2YW53 LmNvbT4+DQpTdWJqZWN0OiBSZTogW3JtY2F0XSAiU291cCBOYXppIiBSVFAgQ29uZ2VzdGlvbiBD b250cm9sDQoNCg0KDQoNCk9uIFdlZCwgTWF5IDI5LCAyMDEzIGF0IDQ6NDEgQU0sIEFsaSBDLiBC ZWdlbiAoYWJlZ2VuKSA8YWJlZ2VuQGNpc2NvLmNvbTxtYWlsdG86YWJlZ2VuQGNpc2NvLmNvbT4+ IHdyb3RlOg0KDQpPbiBNYXkgMjksIDIwMTMsIGF0IDE6MTUgQU0sIERhbiBXZWJlciA8ZGFuQG1h cmtldHNvdXAuY29tPG1haWx0bzpkYW5AbWFya2V0c291cC5jb20+PiB3cm90ZToNCg0KPiBJIHRo aW5rIHRoZSBiZWhhdmlvciBpcyByaWdodCBpZiB0aGUgUlRQIGNvbmdlc3Rpb24gY29udHJvbCBt ZWNoYW5pc20gZHJvcHMgdGhlIGVudGlyZSBmcmFtZSBhbmQgbm90aWZpZXMgdGhlIGFwcGxpY2F0 aW9uIGl0IHdvdWxkbid0IGJlIGRlbGl2ZXJlZCB3aXRoaW4gdGhlIGFwcHJvcHJpYXRlIHRpbWUg ZnJhbWUuICBUaGUgbWVjaGFuaXNtIGJ5IHdoaWNoIGl0IGRldGVybWluZXMgdGhpcyBpcyBzdGls bCBvcGVuIGZvciBkaXNjdXNzaW9uLiAgSSBwYXJ0aWN1bGFybHkgbGlrZWQgdGhlIHRob3VnaHQg dGhhdCBpZiBhbnkgb25lIHBhY2tldCBvZiB0aGUgZnJhbWUgd291bGQgaGF2ZSB0byB3YWl0IGlu IHRoZSB1c2VyIHNwYWNlIFJUUCBwYWNrZXQgcXVldWUgKGkuZS4gd2hpbGUgcGFjaW5nKSBmb3Ig c2VuZGluZyBhbmQgZXhjZWVkZWQgYSBjZXJ0YWluIHRocmVzaG9sZCAoZS5nLiAxMDBtcyBzY2Fs ZWQgZG93biksIHRoZW4gdGhlIGVudGlyZSBmcmFtZSBzaG91bGQgYmUgZHJvcHBlZC4NCg0KSSBk b250IHRoaW5rIHRoYXQgaXMgdGhlIHJpZ2h0IG1vdmUuIFRoZXJlIGFyZSBzbyBtYW55IHNraWxs ZWQgcmVjZWl2ZXItc2lkZSBjb25jZWFsbWVudCBhbGdvcml0aG1zIHRoYXQgY2FuIGRlYWwgd2l0 aCB0aGUgbG9zcyBvZiBhIGZldyBwYWNrZXRzLiBidXQgaWYgeW91IGRyb3AgdGhlIGVudGlyZSBm cmFtZSwgdW50aWwgdGhlIGVuY29kZXIgZGVhbHMgd2l0aCB0aGF0LCB5b3Ugd2lsbCBsaWtlbHkg YmUgaW4gc2VyaW91cyB0cm91YmxlLiBBbmQgeW91IHdpbGwgbGlrZWx5IGhhdmUgd2FzdGVkIGFs bCB0aGUgYml0cyB5b3UgYWxyZWFkeSB0cmFuc21pdHRlZCBzdWNjZXNzZnVsbHkgZm9yIHRoYXQg cGFydGljdWxhciBmcmFtZS4NCg0KT1RPSCwgaXQgaXMgdHJ1ZSB0aGF0IGlmIHlvdSBtaXNzIGNl cnRhaW4gaGVhZGVyIGluZm8sIHRoZSByZW1haW5pbmcgYml0cyBhcmUgdXNlbGVzcyBmb3IgdGhh dCBzbGljZS9mcmFtZS9HT1AvZXRjLiBidXQgZG8geW91IHJlYWxseSB0aGluayB0aGF0IHRoZSBt aWRkbGUgYm94ZXMgc2hvdWxkIGludmVzdGlnYXRlIHRoZSBiaXRzdHJlYW0gaW4gdGhhdCBkZXRh aWw/IFRoaXMgbG9va3MgdG8gbWUgYXMgYSBub24tc3RhcnRlci4NCg0KTXkgY29uY2VybiB3aXRo IHRoaXMgaXMgdGhhdCB0aGUgYXBwbGljYXRpb24gbGF5ZXIgaXMgb2Z0ZW4gc3R1cGlkLg0KDQpN YW55IHdvdWxkIHNheSB0aGUgc2FtZSB0aGluZyBmb3IgdGhlIHRyYW5zcG9ydC9uZXR3b3JrIGxh eWVycywgd2hpY2ggaXMgYWxzbyBvZnRlbiB0cnVlLg0KDQogRXZlbiBpZiB5b3UgZGVjaWRlIHRv IHRyYW5zbWl0IHRoZSBmcmFtZSwgYW5kIHRoZW4gZHJvcCB0aGUgcGFja2V0cyB0b3dhcmRzIHRo ZSBlbmQgb2YgdGhlIGZyYW1lLCB0aGUgYXBwbGljYXRpb24gc2hvdWxkIGJlIG5vdGlmaWVkIG9m IHRoZSBhZmZlY3RlZCBmcmFtZS4gIEkgdGhpbmsgaXQnIGlzIHVucmVhc29uYWJsZSAgdG8gZXhw ZWN0IHRoZSBhcHBsaWNhdGlvbiBkZXNpZ25lcnMgdG8gYmUgZXhwZXJ0cyBvbiBib3RoIHRoZSBu ZXR3b3JrIGxheWVyIGFuZCB0aGUgYXBwbGljYXRpb24gbGF5ZXIgYXMgd2VsbCBhcyBSVFAuDQoN ClN1cmUgYnV0IHlvdSBjYW5ub3Qgc29sdmUgdGhpcyBwcm9ibGVtIGJ5IG92ZXJ0YWtpbmcgdGhl IGNvbnRyb2wgb2YgZXZlcnl0aGluZyBpbiB5b3VyICJ0cmFuc3BvcnQiIGxheWVyIGFuZCB0aGVu IGJlaGF2aW5nIHRoZSBhcHAgbGlrZSBhIHNtYWxsIGNoaWxkLiBJbiBteSBib29rLCBpdCBpcyB0 aGUgYXBwIHRoYXQgc2l0cyBvbiB0b3Agb2YgZXZlcnl0aGluZyBhbmQgYWxsIG90aGVyIGxheWVy cyBoYXZlIHRvIHNlcnZlIHRoZSBhcHAgbGF5ZXIuIFRoZXkgY2FuIHByb3ZpZGUgaGludHMsIGZl ZWRiYWNrIG9yIHdoYXRldmVyIGJ1dCBpdCBpcyB0aGUgYXBwIGxheWVyIHdobyBzaG91bGQgbWFr ZSB0aGUgZmluYWwgY2FsbC4NCg0KIE1hbnkgb2YgdXMgc3BlYWtpbmcgaGVyZSBoYXZlIGhhZCB0 aGUgZm9ydHVuYXRlIGJlbmVmaXQgb2Ygd29ya2luZyBvbiBhbGwgb2YgdGhlc2UsIGJ1dCB3ZSdy ZSBtb3JlIHRoZSBleGNlcHRpb24gdG8gdGhlIHJ1bGUuICAgVGhlIG1lY2hhbmlzbSB0aGF0IGlz IGRldmVsb3BlZCBuZWVkcyB0byBoYXZlIGludHVpdGl2ZSBiZWhhdmlvciBmb3IgdGhlIHRoZSBp bXBsZW1lbnRlcnMgb2YgdGhlIG90aGVyIGxheWVycyBzbyB0aGF0IHRoZXkgY2FuIGFkZXF1YXRl bHkgYWRqdXN0LiAgV2Uga25vdyBmb3IgY2VydGFpbiB0aGF0IG5vIG1lY2hhbmlzbSB0aGF0IGRv ZXMgbm90IGluY2x1ZGUgZmVlZGJhY2sgdG8gdGhlIG90aGVyIGxheWVycyBpcyBub3Qgd29ydGh3 aGlsZSBpbiBtZWV0aW5nIFJNQ0FUIG9iamVjdGl2ZXMuDQoNCk5vIGRpc2FncmVlbWVudCBoZXJl LiBGZWVkYmFjayB5ZXMsIGRpY3RhdGlvbiBuby4NCg0KDQpBbHRob3VnaCwgSSB0aGluayB3ZSBj YW4gYWxsIGFncmVlIHRoYXQgYW4gZWZmZWN0aXZlIGNvbmdlc3Rpb24gY29udHJvbCBzaG91bGQg aGF2ZSBhIGNsZWFybHkgZGVmaW5lZCB1bml0IG9mIHdvcmsgdGhhdCBpcyBtb3JlIGFwcGxpY2F0 aW9uIHNwZWNpZmljLiAgSSd2ZSB1c2VkICJmcmFtZSIgYW5kICJtZXNzYWdlIiBzb21ld2hhdCBp bnRlcmNoYW5nZWFibHksIGFuZCBJIHRoaW5rIHRoaXMgcHV0cyB0aGluZ3MgaW4gdGhlIHByb3Bl ciBwZXJzcGVjdGl2ZS4NCg0KVGhhbmtzLA0KRGFuDQoNCg0KDQo= --_000_C15918F2FCDA0243A7C919DA7C4BE9940D0ECA42xmbalnx01ciscoc_ Content-Type: text/html; charset="utf-8" Content-ID: <733DEB8A20303F4282FBC8BB89A5A11B@emea.cisco.com> Content-Transfer-Encoding: base64 PGh0bWw+DQo8aGVhZD4NCjxtZXRhIGh0dHAtZXF1aXY9IkNvbnRlbnQtVHlwZSIgY29udGVudD0i dGV4dC9odG1sOyBjaGFyc2V0PXV0Zi04Ij4NCjwvaGVhZD4NCjxib2R5IHN0eWxlPSJ3b3JkLXdy YXA6IGJyZWFrLXdvcmQ7IC13ZWJraXQtbmJzcC1tb2RlOiBzcGFjZTsgLXdlYmtpdC1saW5lLWJy ZWFrOiBhZnRlci13aGl0ZS1zcGFjZTsgY29sb3I6IHJnYigwLCAwLCAwKTsgZm9udC1zaXplOiAx NHB4OyBmb250LWZhbWlseTogQ29uc29sYXMsIHNhbnMtc2VyaWY7ICI+DQo8c3BhbiBpZD0iT0xL X1NSQ19CT0RZX1NFQ1RJT04iPg0KPGRpdiBzdHlsZT0iZm9udC1mYW1pbHk6Q2FsaWJyaTsgZm9u dC1zaXplOjExcHQ7IHRleHQtYWxpZ246bGVmdDsgY29sb3I6YmxhY2s7IEJPUkRFUi1CT1RUT006 IG1lZGl1bSBub25lOyBCT1JERVItTEVGVDogbWVkaXVtIG5vbmU7IFBBRERJTkctQk9UVE9NOiAw aW47IFBBRERJTkctTEVGVDogMGluOyBQQURESU5HLVJJR0hUOiAwaW47IEJPUkRFUi1UT1A6ICNi NWM0ZGYgMXB0IHNvbGlkOyBCT1JERVItUklHSFQ6IG1lZGl1bSBub25lOyBQQURESU5HLVRPUDog M3B0Ij4NCjxzcGFuIHN0eWxlPSJmb250LXdlaWdodDpib2xkIj5Gcm9tOiA8L3NwYW4+RGFuIFdl YmVyICZsdDs8YSBocmVmPSJtYWlsdG86ZGFuQG1hcmtldHNvdXAuY29tIj5kYW5AbWFya2V0c291 cC5jb208L2E+Jmd0Ozxicj4NCjxzcGFuIHN0eWxlPSJmb250LXdlaWdodDpib2xkIj5EYXRlOiA8 L3NwYW4+V2VkbmVzZGF5LCBNYXkgMjksIDIwMTMgNjozMiBQTTxicj4NCjxzcGFuIHN0eWxlPSJm b250LXdlaWdodDpib2xkIj5UbzogPC9zcGFuPiZxdW90O0FsaSBDLiBCZWdlbiZxdW90OyAmbHQ7 PGEgaHJlZj0ibWFpbHRvOmFiZWdlbkBjaXNjby5jb20iPmFiZWdlbkBjaXNjby5jb208L2E+Jmd0 Ozxicj4NCjxzcGFuIHN0eWxlPSJmb250LXdlaWdodDpib2xkIj5DYzogPC9zcGFuPiZxdW90O0Zy ZWQgQmFrZXIgKGZyZWQpJnF1b3Q7ICZsdDs8YSBocmVmPSJtYWlsdG86ZnJlZEBjaXNjby5jb20i PmZyZWRAY2lzY28uY29tPC9hPiZndDssIHJtY2F0IFdHICZsdDs8YSBocmVmPSJtYWlsdG86cm1j YXRAaWV0Zi5vcmciPnJtY2F0QGlldGYub3JnPC9hPiZndDssIEtldmluIEdyb3NzICZsdDs8YSBo cmVmPSJtYWlsdG86a2V2aW4uZ3Jvc3NAYXZhbncuY29tIj5rZXZpbi5ncm9zc0BhdmFudy5jb208 L2E+Jmd0Ozxicj4NCjxzcGFuIHN0eWxlPSJmb250LXdlaWdodDpib2xkIj5TdWJqZWN0OiA8L3Nw YW4+UmU6IFtybWNhdF0gJnF1b3Q7U291cCBOYXppJnF1b3Q7IFJUUCBDb25nZXN0aW9uIENvbnRy b2w8YnI+DQo8L2Rpdj4NCjxkaXY+PGJyPg0KPC9kaXY+DQo8YmxvY2txdW90ZSBpZD0iTUFDX09V VExPT0tfQVRUUklCVVRJT05fQkxPQ0tRVU9URSIgc3R5bGU9IkJPUkRFUi1MRUZUOiAjYjVjNGRm IDUgc29saWQ7IFBBRERJTkc6MCAwIDAgNTsgTUFSR0lOOjAgMCAwIDU7Ij4NCjxkaXY+DQo8ZGl2 Pg0KPGRpdiBkaXI9Imx0ciI+PGJyPg0KPGRpdiBjbGFzcz0iZ21haWxfZXh0cmEiPjxicj4NCjxi cj4NCjxkaXYgY2xhc3M9ImdtYWlsX3F1b3RlIj5PbiBXZWQsIE1heSAyOSwgMjAxMyBhdCA0OjQx IEFNLCBBbGkgQy4gQmVnZW4gKGFiZWdlbikgPHNwYW4gZGlyPSJsdHIiPg0KJmx0OzxhIGhyZWY9 Im1haWx0bzphYmVnZW5AY2lzY28uY29tIiB0YXJnZXQ9Il9ibGFuayI+YWJlZ2VuQGNpc2NvLmNv bTwvYT4mZ3Q7PC9zcGFuPiB3cm90ZTo8YnI+DQo8YmxvY2txdW90ZSBjbGFzcz0iZ21haWxfcXVv dGUiIHN0eWxlPSJtYXJnaW46MCAwIDAgLjhleDtib3JkZXItbGVmdDoxcHggI2NjYyBzb2xpZDtw YWRkaW5nLWxlZnQ6MWV4Ij4NCjxkaXYgY2xhc3M9ImltIj48YnI+DQpPbiBNYXkgMjksIDIwMTMs IGF0IDE6MTUgQU0sIERhbiBXZWJlciAmbHQ7PGEgaHJlZj0ibWFpbHRvOmRhbkBtYXJrZXRzb3Vw LmNvbSI+ZGFuQG1hcmtldHNvdXAuY29tPC9hPiZndDsgd3JvdGU6PGJyPg0KPGJyPg0KJmd0OyBJ IHRoaW5rIHRoZSBiZWhhdmlvciBpcyByaWdodCBpZiB0aGUgUlRQIGNvbmdlc3Rpb24gY29udHJv bCBtZWNoYW5pc20gZHJvcHMgdGhlIGVudGlyZSBmcmFtZSBhbmQgbm90aWZpZXMgdGhlIGFwcGxp Y2F0aW9uIGl0IHdvdWxkbid0IGJlIGRlbGl2ZXJlZCB3aXRoaW4gdGhlIGFwcHJvcHJpYXRlIHRp bWUgZnJhbWUuICZuYnNwO1RoZSBtZWNoYW5pc20gYnkgd2hpY2ggaXQgZGV0ZXJtaW5lcyB0aGlz IGlzIHN0aWxsIG9wZW4gZm9yIGRpc2N1c3Npb24uDQogJm5ic3A7SSBwYXJ0aWN1bGFybHkgbGlr ZWQgdGhlIHRob3VnaHQgdGhhdCBpZiBhbnkgb25lIHBhY2tldCBvZiB0aGUgZnJhbWUgd291bGQg aGF2ZSB0byB3YWl0IGluIHRoZSB1c2VyIHNwYWNlIFJUUCBwYWNrZXQgcXVldWUgKGkuZS4gd2hp bGUgcGFjaW5nKSBmb3Igc2VuZGluZyBhbmQgZXhjZWVkZWQgYSBjZXJ0YWluIHRocmVzaG9sZCAo ZS5nLiAxMDBtcyBzY2FsZWQgZG93biksIHRoZW4gdGhlIGVudGlyZSBmcmFtZSBzaG91bGQgYmUg ZHJvcHBlZC48YnI+DQo8YnI+DQo8L2Rpdj4NCkkgZG9udCB0aGluayB0aGF0IGlzIHRoZSByaWdo dCBtb3ZlLiBUaGVyZSBhcmUgc28gbWFueSBza2lsbGVkIHJlY2VpdmVyLXNpZGUgY29uY2VhbG1l bnQgYWxnb3JpdGhtcyB0aGF0IGNhbiBkZWFsIHdpdGggdGhlIGxvc3Mgb2YgYSBmZXcgcGFja2V0 cy4gYnV0IGlmIHlvdSBkcm9wIHRoZSBlbnRpcmUgZnJhbWUsIHVudGlsIHRoZSBlbmNvZGVyIGRl YWxzIHdpdGggdGhhdCwgeW91IHdpbGwgbGlrZWx5IGJlIGluIHNlcmlvdXMgdHJvdWJsZS4gQW5k DQogeW91IHdpbGwgbGlrZWx5IGhhdmUgd2FzdGVkIGFsbCB0aGUgYml0cyB5b3UgYWxyZWFkeSB0 cmFuc21pdHRlZCBzdWNjZXNzZnVsbHkgZm9yIHRoYXQgcGFydGljdWxhciBmcmFtZS48YnI+DQo8 YnI+DQpPVE9ILCBpdCBpcyB0cnVlIHRoYXQgaWYgeW91IG1pc3MgY2VydGFpbiBoZWFkZXIgaW5m bywgdGhlIHJlbWFpbmluZyBiaXRzIGFyZSB1c2VsZXNzIGZvciB0aGF0IHNsaWNlL2ZyYW1lL0dP UC9ldGMuIGJ1dCBkbyB5b3UgcmVhbGx5IHRoaW5rIHRoYXQgdGhlIG1pZGRsZSBib3hlcyBzaG91 bGQgaW52ZXN0aWdhdGUgdGhlIGJpdHN0cmVhbSBpbiB0aGF0IGRldGFpbD8gVGhpcyBsb29rcyB0 byBtZSBhcyBhIG5vbi1zdGFydGVyLjxicj4NCjxkaXYgY2xhc3M9IkhPRW5aYiI+DQo8ZGl2IGNs YXNzPSJoNSI+PGJyPg0KPC9kaXY+DQo8L2Rpdj4NCjwvYmxvY2txdW90ZT4NCjxkaXYgc3R5bGU9 IiI+TXkgY29uY2VybiB3aXRoIHRoaXMgaXMgdGhhdCB0aGUgYXBwbGljYXRpb24gbGF5ZXIgaXMg b2Z0ZW4gc3R1cGlkLjwvZGl2Pg0KPC9kaXY+DQo8L2Rpdj4NCjwvZGl2Pg0KPC9kaXY+DQo8L2Rp dj4NCjwvYmxvY2txdW90ZT4NCjwvc3Bhbj4NCjxkaXY+PGJyPg0KPC9kaXY+DQo8ZGl2Pk1hbnkg d291bGQgc2F5IHRoZSBzYW1lIHRoaW5nIGZvciB0aGUgdHJhbnNwb3J0L25ldHdvcmsgbGF5ZXJz LCB3aGljaCBpcyBhbHNvIG9mdGVuIHRydWUuPC9kaXY+DQo8ZGl2Pjxicj4NCjwvZGl2Pg0KPHNw YW4gaWQ9Ik9MS19TUkNfQk9EWV9TRUNUSU9OIj4NCjxibG9ja3F1b3RlIGlkPSJNQUNfT1VUTE9P S19BVFRSSUJVVElPTl9CTE9DS1FVT1RFIiBzdHlsZT0iQk9SREVSLUxFRlQ6ICNiNWM0ZGYgNSBz b2xpZDsgUEFERElORzowIDAgMCA1OyBNQVJHSU46MCAwIDAgNTsiPg0KPGRpdj4NCjxkaXY+DQo8 ZGl2IGRpcj0ibHRyIj4NCjxkaXYgY2xhc3M9ImdtYWlsX2V4dHJhIj4NCjxkaXYgY2xhc3M9Imdt YWlsX3F1b3RlIj4NCjxkaXYgc3R5bGU9IiI+Jm5ic3A7RXZlbiBpZiB5b3UgZGVjaWRlIHRvIHRy YW5zbWl0IHRoZSBmcmFtZSwgYW5kIHRoZW4gZHJvcCB0aGUgcGFja2V0cyB0b3dhcmRzIHRoZSBl bmQgb2YgdGhlIGZyYW1lLCB0aGUgYXBwbGljYXRpb24gc2hvdWxkIGJlIG5vdGlmaWVkIG9mIHRo ZSBhZmZlY3RlZCBmcmFtZS4gJm5ic3A7SSB0aGluayBpdCcgaXMgdW5yZWFzb25hYmxlICZuYnNw O3RvIGV4cGVjdCB0aGUgYXBwbGljYXRpb24gZGVzaWduZXJzIHRvIGJlIGV4cGVydHMgb24gYm90 aA0KIHRoZSBuZXR3b3JrIGxheWVyIGFuZCB0aGUgYXBwbGljYXRpb24gbGF5ZXIgYXMgd2VsbCBh cyBSVFAuPC9kaXY+DQo8L2Rpdj4NCjwvZGl2Pg0KPC9kaXY+DQo8L2Rpdj4NCjwvZGl2Pg0KPC9i bG9ja3F1b3RlPg0KPC9zcGFuPg0KPGRpdj48YnI+DQo8L2Rpdj4NCjxkaXY+U3VyZSBidXQgeW91 IGNhbm5vdCBzb2x2ZSB0aGlzIHByb2JsZW0gYnkgb3ZlcnRha2luZyB0aGUgY29udHJvbCBvZiBl dmVyeXRoaW5nIGluIHlvdXIgJnF1b3Q7dHJhbnNwb3J0JnF1b3Q7IGxheWVyIGFuZCB0aGVuIGJl aGF2aW5nIHRoZSBhcHAgbGlrZSBhIHNtYWxsIGNoaWxkLiBJbiBteSBib29rLCBpdCBpcyB0aGUg YXBwIHRoYXQgc2l0cyBvbiB0b3Agb2YgZXZlcnl0aGluZyBhbmQgYWxsIG90aGVyIGxheWVycyBo YXZlIHRvIHNlcnZlIHRoZSBhcHAgbGF5ZXIuDQogVGhleSBjYW4gcHJvdmlkZSBoaW50cywgZmVl ZGJhY2sgb3Igd2hhdGV2ZXIgYnV0IGl0IGlzIHRoZSBhcHAgbGF5ZXIgd2hvIHNob3VsZCBtYWtl IHRoZSBmaW5hbCBjYWxsLjwvZGl2Pg0KPGRpdj48YnI+DQo8L2Rpdj4NCjxzcGFuIGlkPSJPTEtf U1JDX0JPRFlfU0VDVElPTiI+DQo8YmxvY2txdW90ZSBpZD0iTUFDX09VVExPT0tfQVRUUklCVVRJ T05fQkxPQ0tRVU9URSIgc3R5bGU9IkJPUkRFUi1MRUZUOiAjYjVjNGRmIDUgc29saWQ7IFBBRERJ Tkc6MCAwIDAgNTsgTUFSR0lOOjAgMCAwIDU7Ij4NCjxkaXY+DQo8ZGl2Pg0KPGRpdiBkaXI9Imx0 ciI+DQo8ZGl2IGNsYXNzPSJnbWFpbF9leHRyYSI+DQo8ZGl2IGNsYXNzPSJnbWFpbF9xdW90ZSI+ DQo8ZGl2IHN0eWxlPSIiPiZuYnNwO01hbnkgb2YgdXMgc3BlYWtpbmcgaGVyZSBoYXZlIGhhZCB0 aGUgZm9ydHVuYXRlIGJlbmVmaXQgb2Ygd29ya2luZyBvbiBhbGwgb2YgdGhlc2UsIGJ1dCB3ZSdy ZSBtb3JlIHRoZSBleGNlcHRpb24gdG8gdGhlIHJ1bGUuICZuYnNwOyBUaGUgbWVjaGFuaXNtIHRo YXQgaXMgZGV2ZWxvcGVkIG5lZWRzIHRvIGhhdmUgaW50dWl0aXZlIGJlaGF2aW9yIGZvciB0aGUg dGhlIGltcGxlbWVudGVycyBvZiB0aGUgb3RoZXIgbGF5ZXJzIHNvIHRoYXQNCiB0aGV5IGNhbiBh ZGVxdWF0ZWx5IGFkanVzdC4gJm5ic3A7V2Uga25vdyBmb3IgY2VydGFpbiB0aGF0IG5vIG1lY2hh bmlzbSB0aGF0IGRvZXMgbm90IGluY2x1ZGUgZmVlZGJhY2sgdG8gdGhlIG90aGVyIGxheWVycyBp cyBub3Qgd29ydGh3aGlsZSBpbiBtZWV0aW5nIFJNQ0FUIG9iamVjdGl2ZXMuPC9kaXY+DQo8L2Rp dj4NCjwvZGl2Pg0KPC9kaXY+DQo8L2Rpdj4NCjwvZGl2Pg0KPC9ibG9ja3F1b3RlPg0KPC9zcGFu Pg0KPGRpdj48YnI+DQo8L2Rpdj4NCjxkaXY+Tm8gZGlzYWdyZWVtZW50IGhlcmUuIEZlZWRiYWNr IHllcywgZGljdGF0aW9uIG5vLjwvZGl2Pg0KPGRpdj48YnI+DQo8L2Rpdj4NCjxzcGFuIGlkPSJP TEtfU1JDX0JPRFlfU0VDVElPTiI+DQo8YmxvY2txdW90ZSBpZD0iTUFDX09VVExPT0tfQVRUUklC VVRJT05fQkxPQ0tRVU9URSIgc3R5bGU9IkJPUkRFUi1MRUZUOiAjYjVjNGRmIDUgc29saWQ7IFBB RERJTkc6MCAwIDAgNTsgTUFSR0lOOjAgMCAwIDU7Ij4NCjxkaXY+DQo8ZGl2Pg0KPGRpdiBkaXI9 Imx0ciI+DQo8ZGl2IGNsYXNzPSJnbWFpbF9leHRyYSI+DQo8ZGl2IGNsYXNzPSJnbWFpbF9xdW90 ZSI+DQo8ZGl2IHN0eWxlPSIiPjxicj4NCjwvZGl2Pg0KPGRpdiBzdHlsZT0iIj5BbHRob3VnaCwg SSB0aGluayB3ZSBjYW4gYWxsIGFncmVlIHRoYXQgYW4gZWZmZWN0aXZlIGNvbmdlc3Rpb24gY29u dHJvbCBzaG91bGQgaGF2ZSBhIGNsZWFybHkgZGVmaW5lZCB1bml0IG9mIHdvcmsgdGhhdCBpcyBt b3JlIGFwcGxpY2F0aW9uIHNwZWNpZmljLiAmbmJzcDtJJ3ZlIHVzZWQgJnF1b3Q7ZnJhbWUmcXVv dDsgYW5kICZxdW90O21lc3NhZ2UmcXVvdDsgc29tZXdoYXQgaW50ZXJjaGFuZ2VhYmx5LCBhbmQg SSB0aGluayB0aGlzIHB1dHMgdGhpbmdzIGluIHRoZQ0KIHByb3BlciBwZXJzcGVjdGl2ZS48L2Rp dj4NCjxkaXYgc3R5bGU9IiI+PGJyPg0KPC9kaXY+DQo8ZGl2IHN0eWxlPSIiPlRoYW5rcyw8L2Rp dj4NCjxkaXYgc3R5bGU9IiI+RGFuPC9kaXY+DQo8L2Rpdj4NCjxicj4NCjwvZGl2Pg0KPC9kaXY+ DQo8L2Rpdj4NCjwvZGl2Pg0KPC9ibG9ja3F1b3RlPg0KPC9zcGFuPg0KPGRpdj48YnI+DQo8L2Rp dj4NCjxkaXY+PGJyPg0KPC9kaXY+DQo8L2JvZHk+DQo8L2h0bWw+DQo= --_000_C15918F2FCDA0243A7C919DA7C4BE9940D0ECA42xmbalnx01ciscoc_-- From kevin.gross@avanw.com Thu May 30 17:11:52 2013 Return-Path: X-Original-To: rmcat@ietfa.amsl.com Delivered-To: rmcat@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 7495121F871D for ; Thu, 30 May 2013 17:11:52 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: 0.336 X-Spam-Level: X-Spam-Status: No, score=0.336 tagged_above=-999 required=5 tests=[AWL=0.150, BAYES_00=-2.599, FH_RELAY_NODNS=1.451, FM_FORGED_GMAIL=0.622, HELO_MISMATCH_NET=0.611, HTML_MESSAGE=0.001, RDNS_NONE=0.1] Received: from mail.ietf.org ([12.22.58.30]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id 5wpMH8BbvLxE for ; Thu, 30 May 2013 17:11:48 -0700 (PDT) Received: from qmta09.emeryville.ca.mail.comcast.net (qmta09.emeryville.ca.mail.comcast.net [IPv6:2001:558:fe2d:43:76:96:30:96]) by ietfa.amsl.com (Postfix) with ESMTP id 40B6321F8700 for ; Thu, 30 May 2013 17:11:47 -0700 (PDT) Received: from omta10.emeryville.ca.mail.comcast.net ([76.96.30.28]) by qmta09.emeryville.ca.mail.comcast.net with comcast id iPrW1l0010cQ2SLA9QBnRr; Fri, 31 May 2013 00:11:47 +0000 Received: from mail-ie0-x22c.google.com ([IPv6:2607:f8b0:4001:c03::22c]) by omta10.emeryville.ca.mail.comcast.net with comcast id iQBm1l00p195Pdh8WQBnQl; Fri, 31 May 2013 00:11:47 +0000 Received: by mail-ie0-f172.google.com with SMTP id 17so2279059iea.17 for ; Thu, 30 May 2013 17:11:46 -0700 (PDT) X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20120113; h=mime-version:in-reply-to:references:date:message-id:subject:from:to :cc:content-type; bh=JLYiusGT79Y1DK4cHU9v7u/Oe/2IU3l+qIposD0LLq0=; b=ZCDBumJjWJSFFCQ98QVJOSNIiHYGPSO4IjrQ8b3m4fjCtDvKS0nLFOdrnpv16+y4Fk Ys/9G9hEo5ar0GwiiZTlIR/UlB04iFQNIiZoN/G2cSAUV9bEnIXWwC1/rbzlKLTOK/kT MxRxtwW+aQVhGvrv/9vtEe7XM6s/1mz2XGMJAe10dJW8L15jwy576FokH068DUCkB1UJ +/Pkg0CGucQqo71f0yh/DrS6FeV4VrtN4TXJjiePZJ7o2Rl2RVIYpfaEE5P9oIPq0Qu2 GfmVISEofx2b3VUE3C4Inh9Ye8+okPvLWFRoSvWPA17yAier1hL2cZdQRHA41u2yEoWy QLlQ== MIME-Version: 1.0 X-Received: by 10.50.22.106 with SMTP id c10mr560193igf.14.1369959106814; Thu, 30 May 2013 17:11:46 -0700 (PDT) Received: by 10.50.65.69 with HTTP; Thu, 30 May 2013 17:11:46 -0700 (PDT) In-Reply-To: <3879D71E758A7E4AA99A35DD8D41D3D91D47DF36@xmb-rcd-x14.cisco.com> References: <3879D71E758A7E4AA99A35DD8D41D3D91D47DF36@xmb-rcd-x14.cisco.com> Date: Thu, 30 May 2013 18:11:46 -0600 Message-ID: From: Kevin Gross To: "Mo Zanaty (mzanaty)" Content-Type: multipart/alternative; boundary=047d7b10d025eb789304ddf87522 DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=comcast.net; s=q20121106; t=1369959107; bh=JLYiusGT79Y1DK4cHU9v7u/Oe/2IU3l+qIposD0LLq0=; h=Received:Received:Received:MIME-Version:Received:Date:Message-ID: Subject:From:To:Content-Type; b=eot/ftbrt59woZNfurNToqV4nYOH105Qn8ONr9b00Mr6bSwL13AcrtQi28dpLUzqu nwSxBh41BEK/uiEu0CEtJDvZmFo2Fm5wpCBVoSL9VriLSBIcWTsehfCmYVoVC7R/Zc uokUFhwKP89QWmQcoVfTGNlXHKznpF/wSiEbliSgC3mC9wB6qCFhtnCYngrD0RqmsW i8W0ew0qHuSfP92myEMn6TB1Lh9HPPndEc1dCfDYkn115urULlWc40xzaYjIkoPsSl dhFyDqRIA6E9fY38SoXkPE4tW6/EipWmdfEcgx0sseCqN8d02oAU4IdslbSK6zhbkg Dz21imIo9DTwQ== Cc: Dan Weber , "rmcat@ietf.org" Subject: Re: [rmcat] "Soup Nazi" RTP Congestion Control X-BeenThere: rmcat@ietf.org X-Mailman-Version: 2.1.12 Precedence: list List-Id: "RTP Media Congestion Avoidance Techniques \(RMCAT\) Working Group discussion list." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Fri, 31 May 2013 00:11:52 -0000 --047d7b10d025eb789304ddf87522 Content-Type: text/plain; charset=windows-1252 Content-Transfer-Encoding: quoted-printable A delay-based approach is going to need to be part of the solution because I believe congestion control needs to work on networks with AQM and networks without AQM. It probably can't fix the use case Dan has outlined but we need to be sure that it doesn't do anything stupid in this case either. The only way to avoid stupidity on a buffer-bloated network is to pay attention to delay. It is not necessarily the case that sender and receiver must have common clock in order to be delay sensitive. In Dan's example, for instance, the receiver can notice the increasing gap between the media timeline and packet arrival times. It is probably too early to go deeper into solutions at this point but I do think this discussion has surfaced a number of interesting requirements 1. Support AQM networks 2. Support buffer-bloated networks 3. Support tail-drop networks 4. Any solution requiring for synchronized clocks is undesirable 5. Handle bursty flows (I think we've already discussed this and agreed it is eventually important but that it will not be one of our initial te= st cases) 6. Contemplate both delay-sensitive and loss-sensitive approaches Kevin Gross +1-303-447-0517 Media Network Consultant AVA Networks - www.AVAnw.com , www.X192.org On Wed, May 29, 2013 at 10:32 PM, Mo Zanaty (mzanaty) wr= ote: > If I understand your proposal, you want the sender to treat the entire > network as a big queue, using receiver feedback as a proxy for direct > measurement of packet transit times through the =93queue=94. To get absol= ute > transit times, the sender and receiver would need tight time sync, which > seems extreme to require. (RTP has never required this, even for things > which seem related to time sync like a/v (lip) sync.) Without time sync, > you can only measure RTT (like RTP), which can be skewed by the reverse > path. Or you can measure inter-arrival jitter (again like RTP), which can > be skewed by an unknown base delay. Either way, I don=92t think you get > reliable measurements for the absolute queue depth/delay that CoDel or > other AQMs want. If the sender acts on relative rather than absolute > delays, that resembles the current RMCAT candidates rather than CoDel or > other AQMs. > > > --047d7b10d025eb789304ddf87522 Content-Type: text/html; charset=windows-1252 Content-Transfer-Encoding: quoted-printable
A delay-based approach is going to need to be part of the = solution because I believe congestion control needs to work on networks wit= h AQM and networks without AQM. It probably can't fix the use case Dan = has outlined but we need to be sure that it doesn't do anything stupid = in this case either. The only way to avoid stupidity on a buffer-bloated ne= twork is to pay attention to delay. It is not necessarily the case that sen= der and receiver must have common clock in order to be delay sensitive. In = Dan's example, for instance, the receiver can notice the increasing gap= between the media timeline and packet arrival times.

It is probably too early to go deeper into solutions at this= point but I do think this discussion has surfaced a number of interesting = requirements
  1. Support AQM networks
  2. Support buffer-bloated networks
  3. Support tail-dr= op networks
  4. Any solution requiring for synchronized clock= s is undesirable
  5. Handle bursty flows (I think we've a= lready discussed this and agreed it is eventually important but that it wil= l not be one of our initial test cases)
  6. Contemplate both delay-sensitive and loss-sensitive approach= es

Kevin Gross
+1-303-447-0517
Media Network Consultant
AVA Networks -=A0w= ww.AVAnw.com,=A0www.X= 192.org


On Wed, May 29, 2013 at 10:32 PM, Mo Zan= aty (mzanaty) <mzanaty@cisco.com> wrote:

If I understand your proposal, you want the sender to treat the e= ntire network as a big queue, using receiver feedback as a proxy for direct= measurement of packet transit times through the =93queue=94. To get absolute transit times, the sender a= nd receiver would need tight time sync, which seems extreme to require. (RT= P has never required this, even for things which seem related to time sync = like a/v (lip) sync.) Without time sync, you can only measure RTT (like RTP), which can be skewed by the reverse pa= th. Or you can measure inter-arrival jitter (again like RTP), which can be = skewed by an unknown base delay. Either way, I don=92t think you get reliab= le measurements for the absolute queue depth/delay that CoDel or other AQMs want. If the sender acts on relative = rather than absolute delays, that resembles the current RMCAT candidates ra= ther than CoDel or other AQMs.


<= /div> --047d7b10d025eb789304ddf87522--