X-Virus-Scanned: clean according to Sophos on Logan.com Return-Path: Sender: To: lml@lancaironline.net Date: Wed, 05 Aug 2009 09:13:53 -0400 Message-ID: X-Original-Return-Path: Received: from nschwmtas06p.mx.bigpond.com ([61.9.189.152] verified) by logan.com (CommuniGate Pro SMTP 5.2.15) with ESMTP id 3795500 for lml@lancaironline.net; Wed, 05 Aug 2009 08:59:01 -0400 Received-SPF: pass receiver=logan.com; client-ip=61.9.189.152; envelope-from=frederickmoreno@bigpond.com Received: from nschwotgx01p.mx.bigpond.com ([58.170.138.242]) by nschwmtas06p.mx.bigpond.com with ESMTP id <20090805125821.MQSJ1920.nschwmtas06p.mx.bigpond.com@nschwotgx01p.mx.bigpond.com> for ; Wed, 5 Aug 2009 12:58:21 +0000 Received: from Razzle ([58.170.138.242]) by nschwotgx01p.mx.bigpond.com with ESMTP id <20090805125813.OPVM7248.nschwotgx01p.mx.bigpond.com@Razzle> for ; Wed, 5 Aug 2009 12:58:13 +0000 From: "Frederick Moreno" X-Original-To: "Lancair Mail" Subject: FW: [LML] Ice with OAT 36*F (LIVP): Ram Recovery on OAT X-Original-Date: Wed, 5 Aug 2009 20:57:58 +0800 X-Original-Message-ID: MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="----=_NextPart_000_0049_01CA160F.6CE57CE0" X-Priority: 3 (Normal) X-MSMail-Priority: Normal X-Mailer: Microsoft Outlook, Build 10.0.6838 Importance: Normal Thread-Index: AcoVs9IEnB5mk/vxQAWDTWIzAidLGgAFj8TQ X-MimeOLE: Produced By Microsoft MimeOLE V6.00.2900.5579 X-RPD-ScanID: Class unknown; VirusThreatLevel unknown, RefID str=0001.0A150201.4A7981ED.0001,ss=1,fgs=0 X-SIH-MSG-ID: ohw2EdXuCkKhkDE4gja+bFg2l1K70SNytt9NBYd6+kVFXEPLp8DZQ9SicKtfw4rkxFkZYgr0ezYwc6n0XI3bt9G6I71BWLDZ7sI= This is a multi-part message in MIME format. ------=_NextPart_000_0049_01CA160F.6CE57CE0 Content-Type: multipart/alternative; boundary="----=_NextPart_001_004A_01CA160F.6CE57CE0" ------=_NextPart_001_004A_01CA160F.6CE57CE0 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: quoted-printable do you think that we could construct something like this=20 to reduce OAT error? =20 I am not familiar with this probe, but I believe that it attempts to correc= t for further non-linear effects associated with compressibility as the Mach numbers rise to levels substantially above where we operate. Think jet speeds, Mach 0.7 and above. I do not think such a probe will help at our more modest probes because the problem they attempt to address is negligibl= y small at our speeds.=20 =20 However, I could be wrong. I leave it to others to research Rosemont probes.=20 =20 As I noted elsewhere, at our lower speeds, compression heating at stagnatio= n points and frictional heating elsewhere (and mixtures of both near stagnation points) makes the OAT error occur everywhere on the airframe. The Piper curves published earlier give you a good estimate of the OAT error. Going in the wheel wells only adds confusion if there is a fuel tan= k near by with a big thermal sink in the form of avgas that will be very slowly heating and cooling. Additionally, the OAT response for a probe in the wheel well will be really slooooooooowwwwwwww. =20 =20 The thing to do is accept the error, and remove it. Use the Piper charts t= o estimate the error in OAT. To get an accurate TAS, you have to also correc= t for compressibility. The total airspeed error is about 2/3's from the termperature error, and about 1/3 from compressibility (varying depending o= n speed, true OAT, phase of the moon, and other secondary effects.) =20 =20 You can compute the air speed correction with a fancy Jeppesen whiz wheel developed to compensate for all these effects in jets, or you can use the simplified chart attached. It shows the total airspeed error (compressibility error in the pitot tube and frictional heating error from boundary layer friction) assuming you have a conventional steam gage air speed indicator and are reading an "uncorrected" OAT as indicated by your OAT gage. This assumes you are not using any fancy black boxes that make these corrections for your. =20 =20 The procedure is simple. Calculate an "E6B TAS" using an E6B or that ring correction on the outside of your steam gage airspeed indicator. Then go t= o the chart on the horizontal axis with this number. Go vertical to one of the curves that best approximates your OAT. Then go horizontally to the left to the vertical axis to get the correction factor. Subtract this from your "E6B airspeed" to get a very good estimate of your "True TAS." Caution: any static port errors will remain, and they can be considerable. But at least you can now accurately compare your computed "True TAS" agains= t a four way GPS calculation of "True TAS" and make an estimate of your stati= c port error. Then you can modify your static port, and do it again. And again. And again. When your static port error is less than 1-2 knots at cruise, you will at last have a fairly accurate number. (Whew.) =20 Fred =20 -----Original Message----- From: marv@lancair.net [mailto:marv@lancair.net]=20 Sent: Wednesday, 5 August 2009 4:27 AM To: lml@lancaironline.net Subject: Re: [LML] Ice with OAT 36*F (LIVP): Ram Recovery on OAT =20 Posted for "Bill" : Ice with OAT 36*F (LIVP): Ram Recovery on OATHey Fred, =20 Airliners have an OAT probe called a "Rosemont probe". The idea is to give a=20 more accurate OAT reading. It's an enclosure around the probe with a bunch of=20 little holes in it. Since only a percentage of the air gets through the holes,=20 the local velocity inside the "cage" is much less. I guess that the theory is=20 that the cage absorbs most of the ram and friction rise leaving the air inside=20 the cage at a low relative velocity and at a temp somewhere near true OAT.= =20 There might be much more to this device that I don't know about (I never=20 really gave them much thought other than to make sure that it was "there") but=20 if this is all it is, do you think that we could construct something like this=20 to reduce OAT error? I'd be interested in your thoughts on this. =20 Bill Harrelson N5ZQ 320 1,650 hrs N6ZQ IV under construction =20 =20 [Discussion about this very thing long ago led many folks to install their OAT probes in the gear wells.... the gear doors aren't air-tight and the environment inside the gear well is the same as outside (except for rain & stuff) for all intents and purposes. Just another data point. ] ------=_NextPart_001_004A_01CA160F.6CE57CE0 Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

do you think that we could construct something like this=
to reduce
OAT error?

 

I am not familiar with this probe, but I believe that it attempts to correct for further non-linear effects associated with compress= ibility as the Mach numbers rise to levels substantially above where we operate.&nb= sp; Think jet speeds, Mach 0.7 and above.  I do not think such a probe will help= at our more modest probes because the problem they attempt to address is negligibly small at our speeds.

 

However, I could be wrong.  I leave it to others to research Rosemont probes.

 

As I noted elsewhere, at our lower speeds, compression heating at stagnation points and frictional heating elsewhere (and mixtures= of both near stagnation points) makes the OAT error occur everywhere on the airframe.  = The Piper curves published earlier give you a good estimate of the OAT error.  Going in the wheel wells only add= s confusion if there is a fuel tank near by with a big thermal sink in the fo= rm of avgas that will be very slowly heating and cooling.   Addition= ally, the OAT<= /span> response for a probe in the= wheel well will be really slooooooooowwwwwwww. 

 

The thing to do is accept the error, and remove it. = ; Use the Piper charts to estimate the error in = OAT.  To get an accurate TAS, you have to als= o correct for compressibility.  The total airspeed error is about 2/3= 217;s from the termperature error, and about 1/3 from compressibility (varying depending on speed, true OAT, phase of the moon, and other secondary effects.) 

 

You can compute the air speed correction with a fancy Jeppesen whiz wheel developed to compensate for all these effects in jets, = or you can use the simplified chart attached.  It shows the total airspee= d error (compressibility error in the pitot tube and frictional heating error from boundary layer friction) assuming you have a conventional steam gage air sp= eed indicator and are reading an “uncorrected” OAT as indicated by your OAT gage.  This assumes you are not using any= fancy black boxes that make these corrections for your.   

 

The procedure is simple.  Calculate an “E6B&n= bsp; TAS” using an E6B or that ring correction on the outside of your stea= m gage airspeed indicator.  Then go to the chart on the horizontal axis = with this number.  Go vertical to one of the curves that best approximates = your OAT.  Then go horizontally= to the left to the vertical axis to get the correction factor.  Subtract this from your “E6B airspeed” to get a very good estimate of your &#= 8220;True TAS.”  Caution: any static port errors will remain, and they can= be considerable.  But at least you can now accurately compare your comput= ed “True TAS” against a four way GPS calculation of “True TAS” and make= an estimate of your static port error.  Then you can modify your static p= ort, and do it again.   And again.  And again.  When your st= atic port error is less than 1-2 knots at cruise, you will at last have a fairly accurate number.  (Whew.)

 

Fred

 

-----Original Message-----
From: marv@lancair.net [mailto:marv@lancair.net]
Sent:
Wednesday, 5 August 2009 4:27 AM
To: lml@lancaironline.net Subject: Re: [LML] Ice with = OAT 36*F (LIVP): Ram Recovery on OAT

 

Posted for "Bill" <n5zq@verizon.net>:

 Ice with OAT 36*F (LIVP): Ram Recovery on OATHey Fred,
 
 Airliners have an OAT probe called a "Rosemont probe". The = idea is to give a
more accurate OAT reading. It's an enclosure around the probe with a bunch = of
little holes in it. Since only a percentage of the air gets through the hol= es,
the local velocity inside the "cage" is much less. I guess that t= he theory is
that the cage absorbs most of the ram and friction rise leaving the air ins= ide
the cage at a low relative velocity and at a temp somewhere near true OAT. =
There might be much more to this device that I don't know about (I never really gave them much thought other than to make sure that it was "there") but
if this is all it is, do you think that we could construct something like t= his
to reduce OAT error? I'd be interested in your thoughts on this.
 
 Bill Harrelson
 N5ZQ 320 1,650 hrs
 N6ZQ  IV under construction
 
 
[Discussion about this very thing long ago led many folks to install their = OAT probes in the gear wells.... the gear doors aren't air-tight and the environment inside the gear well is the same as outside (except for rain &a= mp; stuff) for all intents and purposes.  Just another data point.  <M>  ]

------=_NextPart_001_004A_01CA160F.6CE57CE0-- ------=_NextPart_000_0049_01CA160F.6CE57CE0 Content-Type: image/jpeg; name="Airspeed correction 10,000 ft.jpg" Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="Airspeed correction 10,000 ft.jpg" /9j/4AAQSkZJRgABAgAAZABkAAD/7AARRHVja3kAAQAEAAAAHgAA/+4AIUFkb2JlAGTAAAAAAQMA EAMCAwYAABrMAABPAgAA07D/2wCEABALCwsMCxAMDBAXDw0PFxsUEBAUGx8XFxcXFx8eFxoaGhoX Hh4jJSclIx4vLzMzLy9AQEBAQEBAQEBAQEBAQEABEQ8PERMRFRISFRQRFBEUGhQWFhQaJhoaHBoa JjAjHh4eHiMwKy4nJycuKzU1MDA1NUBAP0BAQEBAQEBAQEBAQP/CABEIAxEE9gMBIgACEQEDEQH/ xADBAAEBAAIDAQAAAAAAAAAAAAAAAQUGAgMEBwEBAAAAAAAAAAAAAAAAAAAAABAAAAUDAwMEAwAC AQMEAwAAAQIDBAUAEQYQICEwMRJAQRMHFBUWUDJggCIzcLA0JaAkFxEAAgECBAMFBQUFBQcBBgQH AQIDEQQAITESQRMFECBRYSIwQHEyFIGRwUIjUKGxUhXw0TMkBmDhYnKCkjTxstJDU2M1cIDik6Ci wnNkJRYSAQAAAAAAAAAAAAAAAAAAALD/2gAMAwEAAhEDEQAAAPoAAAAAAPJ5da8Jt+Z03rN2aL1G /tH6Df2hdxu7537DcfPo2eNk1fy7Ger169gD6A0ngby0HgfQWmeQ3ny6LzPoHdp3lN7aT5jf3HkY 7h8/zpufZqHlN5aj0m48/l2eNzafuAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAlHzHn9Kp8092+Q1bRPsvA+V9+37AfLfR9K6j5JlPpPI+W7Xsnaani/oPQaRj/pvS fNdn2iml6d9k6z5v0/Ueo0XHfUOJ876/pfmPnWQ3umv7JhsyfOPP9LhoHLfKfP8Ay/Seo0D0b51n yr6/5fUAJfMaps3ybbz3bLoPSfRmka6fWuOna4fV+Gg+Q+mPnPE+kvn/AFmwbD8h+snfpeZ109O6 a/jDc78xz5tz5qPpbSsAfVJpuuH03w6zjTa9j0DyH0t8+5m+35b9JPSQxfboGxHDKal5T6lqW1/M zbfJrPYbfx1HrNw2T5h9OMT1a7Df3zDYjber5nkTbcn8y+mgAAAAAAAAEoAAAAAAAAAAAAAAAAAC Gn5PX/GbZz070m16by6TasP4eRsHq1TmbE0rIm24jliz6Joe+fOzY+/VMiejLa3qhvzV6fTcVksO azmtRz54cxqHuPbldYypv2Myfzk3DH69jDf/ABapwPo3LUsEbr2aXsxsXr1LbQBp+4eQ0DxfVfMa Lx3sY/539fwpp/q2XEmDxX1rgfM/H9XHzS/SuZ82+l+TIng0j6RjzUMdv/uND69oyxrmF3vqNf0n 7Dhj59m99xBjsXvniNB4/RfOfPMlu41f3Z3EGU9uPyBqPbsUPnXHd/eYLV9gzZol+g9Jok+h9ZoX 0vx+00zxbt2nyj17vlj5FmNuyhpO+4/IAAAAAAAAACUAAAAAAAAAAAAAAAAAAal7s+MB59nGD8O1 DCdOwjD+TYxq3bsgxHj2MMHnBgst3w0zLZ4a/c/B4/aNLyGyDS87lqaTseTDD5gYzW93GrevPDSs xnKaP6tuhjcmAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHixnlx htvVro3J1YczrFcDMMTDMTFjKsTDLsQMuxHIyrF8TLMXxMrcRDL3FcTLsRyMqxNMqxEMwxYylxVM oxYyjFDKsWMoxUMsxQyrGUyTGwybGQyjGQyjGUyTGwyjFcTLsVyMmxgybDwzLFcjJzH8DJ3F0yTG QyjF8DL3E0yrGjJMXTJsZDJsUMqxQyrF8jJXFcjJzGQysxYyrGcTK3FDKXEdhkrjOozDEjLTEjLM TTK3E8TMMUMqxUMqxfEyzGQyjFUylxNMrMXxMsxHIyrD8jLMUMqxYyjFDK3CZg7AAAAAAAAAAAYT Dbd1GucNo4nLB5zCmZtBYFEoJQAlEURQAKSgKRRFEcoFCUAJRKAApFEAAKQpAAJQAABFAApAAJRC koCkWBYACksCglEWCURQsoSkWCUIpFCAKSUFEqFlGHy2Jyx3AAAAAAAAAAA6uPKElE1rZddNg58O QqFAsFgAFgABUpKCygABQAAoJYFgAURQAlEsolgoRRAFgAoARRFAEAABKpKAEUAAShLKCFIWWBYA EhVgsF4WgAACwWURQQWBiMvisqdoAAAAAAAAAAOrjyxx755POZPXs7rpsfLh2gApKEWFlAgWBRFB YFEoCghQCiBZQAAAAAAlCUAAAJQAAKRYLAIAFEsoAlACKAAJRFgURRKEURRFhFHDlQlCUQBKASqQ AFQYXMYrMHYAAAAAAAAAADF63mdVM7w78Wblr+fwh7clw5lIUApAWWFlgAKQCgABUolAAAhbKEoA AAAAAAAKQAAACoUEUQAEoRRALKQoAAAAASgAAAhYAolgKQAgIWWiUJQikBiMxhcydoAAAAAAAAAA Onr7eJ1dfphNc2PAmW9PDtIolAAAAAABZQAUiwoBCgSiWC3iOSCyglCCgAAAAAIKACoFlCUgAAAC wiwFAAAAAJQAAAAQAAACwTlAQAJQACwAMRmMPmDsAAAAAAAAAAB1ceXESwa3smCM12SigABSFgLK CChKAAFIUAAgAIUCwUCwWAsoAAgAAAVBQAWAAAAAUIEUSgBZRFgAAAAAAlgBKBKAACkqEWAAACyk sGGzOJyp3AAAAAAAAAAA6uPVpxu01/ym1YHO6ybNzxuRKAAAAgoKlABSLBYKgAsAQqUQFgqDlAqC oKAlLIK4cioFACpQQqUWCoBSFAEsAAAAFgsAAAABYCwLCLBLCoHDG6YfSUoBUCWAAAAFIYnLYfMH aAAAAAAAAAADWMNvfgMDyznA92HzOAM/y4cwAABKIQtgrpxZm3l9JbxpYoQHlHqnl7DueCGQebqP cnjPa6+wPH4zMPL6Sp5j1PN6C3jDk4cip5z0yicp1Hc8vWe64zvPYABYKAAsAKAgqAABKAABSAAA AWACgiwk5QnUwRwzvfyAJZQACFIsFlIolQxGXw+ZOwAAAAAAAAAAHVx5cRLCazs+AM7zlKAABKMP 15wYdmIa/wCXaxrvsy1MTMuPB7wSw0v0ZPieDj7fOcJ6eo1vZOXeZvT9xw5i9u1fMnt1naMOePG5 nqPH0d/Yefn6+gvkyVMVx9npOju6sie7FZTFme1jacGYDI9nWeXZvFnCgAssLAUALLBYBQlEogCw AAAAAAlAQWCgEL0zXznnO3HHjyOCyhlyCwVKAAQCygCWGGzWFzJ2gAAAAAAAAAA6uN4liFwua1Y2 m8OwALBZRHE5TGjJMYMn5/FpR9KuG7zJXFczJPD7hLDqmp95s3LV+ZsDWuBtfH53nTbernpBvN1H bjq6e3Vzaueu+M27hrPkNx7NUptU13oNpukes2zhrNNpnkxZsHG60bLw1vzG2ctK2EzBSKEsFlAA AAFgAFEsACUAAJQAABEAFkOXRMIcs+xZ3eRlTtcOZUCwUAAACWFSiWGIzGFzJ2gAAAAAAAAAAwWH 2TVz3+fK4o2nWNmxR6ffOQAKQAAADhfCZB19gAABhOGbhgOjZKYDo2Yar7c9DniMxxNazHt5jB5q GC69jGo9m1Q1jhtVNY4bVTTezbhqvuzo8uG2QccZleJhPDtIwee48hQASgAAAAAlABSUIUgEolQo AFCAk5cQQvVh+s69kY4vi7cyPnu2cDy7H5PWFEqChCgBYFgSiBhsziMwdgAAAAAAAAAAMX4M9DG+ XNiazs2tGyc+HMAAAceQxTLQxnHLDXsBvvjMd35XsMXwy48frUko0v0evief0dfQdV9XUYPNebKm f0je9ePFt2pbGder7trx1dfLiejEd3M7nn5mT8fTwGQwncZLj5cgZjHe3BG06zs2vGK7MzijybD4 9jOdAACOUJQAAAAFAAJQiwAAAAqACSwnkmKMFuPtxA5dOZLg5mx20RYAJQAAABZRJQlhhc3g86cw AAAAAAAAAAdUsIsGJy2tmyXjyAAFlBCgLAUhSAAiwjlDjx7KRQURR1uwJRFEWEURQUTlKCiURRFE UQBRFgAAAAsoAAAAASiAAAAIPF5+J0ZP06we70eDMnPEzOk5AKRRARYWAAAsFIJRCmGzWEzR2AAA AAAAAAAA6uPg8JnWO85mNc2PEmV58aUBQAigCwFEqAAACUAKCykUQBRAJRFEoCkoKAAAAAAAAEoI pFAhQAWAQLKJYWBUAgsDF8OR15hr5ezv8J6+PblgAlKgpAUgACAUgAAIowmbw+XO0AAAAAAAAAAH i0nYvAdFyHSbJrOza0Zv18eYAUAAAKCWFlEWApACgpCkoAAJYWUQAAogXjaAVBQALKJYAAAAAAAS ggLAUEpKgWACPOd+DwW1D19WDOeeYU44ra/YdXaAACyksFlgWACAsAAAAGGzGDzZ3AAAAAAAAAAA 6uPKElEwmc1o2Tlw5goAKRQAIACgEUAFCykAAABKCUSoUEWACwUCwVKLKEpCgCUQpAAAAAQACgAA iFjynfgeOWMRk/NyOrMdPgJl+2koICUCFAKCACURRAAAWWBYYjL4bMnYAAAAAAAAAADq48uIA1jZ 8CZvnx5FsFAoEFIWWACygCygApFCABCkBYFAAAlBKQoAsFSgFikqFAQLAKRYAAAJYKAACWCMUd+J 9eWGlZj0Hjyfi9Z1ZmiKAEoiwgKg5ILFIAAAQAsCpSKMHm8NmTsAAAAAAAAAABiMVmNXM75L5DbM FnNYNouNyRbBUoABUFgLBQAKhQAAWAlBAAsoAAAAAAABQACksFgUEsoAlgAAAAAgLBeM1w9Xp58D vwXZmjG4X29RsnqUlAAABLBKIoWCoAABAUSwKAAMHm8LmjsAAAAAAAAAABruM3HgYfwbPCa5smEM z2SlgCgAAABKVKAKAAAAAEUQACwUhUoBYAACwKApCkWCwUEspFCUShAEoAlEAxHfjjAbx4fAeju9 mNPX1+v1kqkKSwUEoACFlhKAEnKiWAgsoSgAAAhiMxhM0dgAAAAAAAAAAOHDnwJKJrGz4IznLjzA CgBKBCwKgqUWUXjSkLLBYKAAAACFIsFAAAAACpQABYFlAIUlQssAABBYBwOWD6cseHz+nHFz2GyB 5c5zolEAIUAFSgApJRFEWApAJRKAAACURYYbNYXNHMAAAAAAAAAAHDh5MUZ54PMZjXth182C8eYs FAAlCWAACoVKVKAAAKAAFQAAEoAAUSwAAKAAFgVBSFSkUJYACAETCnuxff2HvwXHKmI8/Z3mc9co ABFhACiwUAAFgARYALKSwAAAFhx5AQYXN4LOHYAAAAAAAAAADw6378ad3KdJteFzWsGx93DmUCwU CWFgFgAspCiygAAFlAAApFgAAKRYLKEoABLKAAAALAAASiAIMd1Y0w+4YjtO318/Gei+/tACwKIs FlJLTiollAAAAAAIBYBCgJSgSwSwAw2awmaOwAAAAAAAAAAHX19nAhSYXNa8bFePIAFJQgFgLAAB ZRYKlACgAAUlABAAFIAUAAAAAAAAAJRAELGNPfr3o9BwwvuxR78j482eXKqQpKACAAAABKhQAAAE FBAAAQDlxpUpAJYAYTOYTNnMAAAAAAAAAAHDr7OsAa3smumwcpyEoAASwoAAFgqCgWUWCgAAFAEo AhSKJZQlAFlEogAACCpRAAS9R2dOqe07fbcWcvby8xMVt/ceH3USgAABFgAKQEsFlhQCFgVKRRAA CFBFgBUoSiWAGFzeBzxzAAAAAAAAAAB19PVqZuPXrfmNzweb1g2fn4PeAFEoShKEUQACoKCygoSg ACygAAAAAAApLAAABCgCWFiBwwZk8P6vAdOQxuTL38sseH3UQpCkBUFSiWCwWKSwAAAAJRFAABKQ AgoAJRFhZYJRYGFzeDzhzAAAAAAAAAAB16fuHmMRhNy4Hfrux4cy3ZKAUAAolEWAApALKJQsFABK CwUAAAAACUEFAAAAQCFeLzmUxXXzPF7/AD8Dza1u3nMVuXn9gsoAihAAAKEpLAKJRAAAAAAAAQpF EAAKRYQhQFEWGCzuGzRzAAAAAAAAAABw4c+AlE1jZ9aNj58OwlCUAFABAAWUAAAAsUAAFCUJQAAA BKJUFAACVAeY9HgxfAwGw+XpMnw7/aebI+oACkAAAAAAAAoQBRFEAAAWBYFgAlgABYFQWWEWChAF hhc3gs6cwAAAAAAAAAAdfDn5TvdfA7sXlNdNjvXzKCgWCoLAAKJUKAAollBCgAKIBUKAACUJQSiV AQrqxRmujB8js48fMevwZXgYDZunOCglgUJYFhKAAAAABYKABKCAAAFgAVKQAEURQgAAAAAJYYPO 4TNnMAAAAAAAAAAGO1zcdWOvz+0bHrWy4o9XtlFgoAAAAALAoKAACKAAAAKAAQoAABBeGJMx4fJ4 THY7L9JlvHmfYYz3+8AAAAAAJRAAAAALBZQASkqAAACKCFSgCykABKEoRYAAAAJRgs7hsycwAAAA AAAAAAcfN6x4+j38BrOzaubPy4dggUFgAAAACktAFgEFQWwVAAAsAAFQVIcvJ5NQN4xmtZ45Tx+4 8/oyeSNV9OwgAAAAAAAAACKIUlBKIUJQAlAIAAQsAUJQBULASiUABAUgABCxTCZvBZ05gAAAAAAA AAAA6+HZ1jEZfXTYuXGgFihBQACnGhSkoAAQAFIVBUFQUBAuK4mX4a3jjOdHm7Dh4Ni8B15T05A6 u2UAAAAAAAAAAAAAAAAAAEKABFIoiwASwqCgWCxSECwLACxSFJLBYKlMJmsLmzmAAAAAAAAAAADr 6/HiTYta2LDma59XeRRFgAlAAAooEoQAIhbBUFSHJxhzcfMeuaz4Ta8Fhfca97+7YzE5bO0x2RBQ AAAAAAlAAQoAAAAAAAAAABCwFCUAJQiwSiAAtgLBKIoiiAqUSwEBSLDCZ3BZw5gAAAAAAAAAAAxO v7DhTOY/M62bNz4cykKBLAAQsUUBCoK4ioLAs8noObG4g2jho3QbTpma6zxevb/aa9ksgOHNTjyA UAAEKAAAABFAAAAAAAAEoAAAAIFgUCUAASiAgCUqUAAlBAWBYAEogFDB53AZ85AAAAAAAAAAAA4c OfAa9sGDM5ygqUAAlQsCoKgrr8JkWv6gfTnz7xH03y6LkjL47395rkzOYML7cyOnuoFBC2CpQACo LAsUlQpCoKgsACpQAAAAAAAAAAQpAsFBLCoKgWCpSTlCAAoCUAShLCwLAEKBFAMHncHnDkAAAAAA AAAAADr48uJNX2fVjaOfj7ztvl4nreDCm03U8uZSYjrMr4fN2mFmS9BheO6w0Ts3kaXjPowwGc7A oAAAVBbxoAsFvGiwVBSFQVKAAAAAAAEHKABYCygAEsAhQLBSFgWBKAAhUosCwJRKBBUAAAAhUFgU AAGCz2DzhyAAAAAAAAAAABh8L2jYdC3mGt5LI8TEZbnwOWGzFMRmOA7PB64drqHlyHRTuw+Qh63m hw9fRxPZPJTj7vHwPfj+fEyM8PEvu8EMlMeOjMYumUxoZG42Hd78TzMn5PLxMr2YbmZPyeTmZO4g Mxh+RlvF5uJmOWGpl/D54Zhhqev24LmZrx+DiZ3hi+BmcM4mdmH4nt9uFpmvB5IZnlhh7+/D8jMT DQ9/sw3AzuFvEzVwsPf68F2GaYbrMj7MKMz4fH1md54Gnt92E5mZxfRwMx24PsMz4vCM2wnI9ntw lM14/DDL8sIM54fL0memHhyy2C5mc8PhhnGG4mR78J2mZ44jie73YPsMx4PJDNTEcSZ7B54AAAAA AAAAAAA8WIz+nG63FaIfUGo64fUXn9AAAAANYNna7rR9Ha5rx9Ea/sAAAAAMKZp86zRtb5zmza2h 74AAAAAGk9xuD5zshsT55tplgAAAAGI1Q+hNewJv7WcebslAAAADr0E+hNawB9Ea1gz6C6O8AAAA HnPQ0HJG2NP6TdmrbSAAAAAGoZEzz57nzY2g70dgAAAADUeZtbT/AEmztE2IzIAAAAAAAAAAHzf6 RhjHYneNdNRyW7YUy+T48gAAABhc15TA4vbcUafltlx5i998PuAAAAHR34o0nsyeZNc8Ow5A1n6B ruxFBKAAAGs4/lkjXvNsHuMD6e7NmSAAAAB5/m284gwGSzuPMB6tl8htHKUJQAADjp216qY3z7N5 DXMzm8WZnN9PcAAAAND3zwHzfJZrtMByzvnMR9F1/YAAAAB5fVwPju45Piapw2L3GE2nA7ccwAAA AabiNk4GE8+yd5huHpzhlwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJYUAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAE0PfdZMbnuOqG3ePXM odO8aDvJ3zTe42x895m/tB8R9Mmhec+i3QPebZ49K859MvyjIm9efTthNkYHXTYs7oHpN2vzX6Sa fcPsJ2dmnZE5ZbVe8+lAwHVp+UN77NJxZ9Lml403bIfLMyb1fmP04AAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYDPjC6p9FHzr27wPm2++wad4PoA0CfQBpHLdR88xn1H wms476UND8n0cfLsvvQ+Z7VsQ6fm308aVj/oo+c/RaPnOS3QaDy3wfL/AHfQhq+0eP2Gk4/6MPn3 p3gaJj/pY0H37ePkH1zmAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAP/aAAgBAgAB BQD/AN+g/9oACAEDAAEFAP8A36D/2gAIAQEAAQUA6knJNopjCZJGToS2UR0Q+6Lx2iyaREyymWrp 22ZoG+yYEF42TZSjXeu6bNiyU1GxTVq5SdttqE/EuJGTySHil0FiLo6isiCn/OPsV64VWiFVIDMs zfvG8vlE/kLSenprKIKHTmcjUcTM3lQ5G6ncpx+Vkctk1Z+EyuQLLsJ7JJpKOzR7/Ou3GbvoH66U 84D7JcOAI3x6GJH/AIyeJQrOXz+RjyZjJK4pGT2ZvmsDkeZy6kZk+TTDmGzN6pHs8jzh/G5RLTju KeSEsTD5rKnEPj8lkOcQ7SezSTa1JZRmcMoUwGLUrNvInK8OaNptbLspl4eRdZTlcS/yHLJFtKuc ryWKfTL+a/pJ/LpeJXhclyJ1Jf8ANkWZsmyrIsXRhRnF15RzKpKD9h52u5bt5AYJ2rISa8dk7l25 zaek2DSEyLH2kbOSDY0NGA2gjvcSRzMU8a+ui+OPZ9CKyLRt9llQjwQmJbEInNkouE/BIxwVidFH 6/8ArxJNaAbJRMcvBQyUjAQeZJQcRlKr1fEZmVi3+K5KxMOPZBlzafjsnZpx6v2Ycni/y1GMk6ZN Y+Tz4yn8RkWTumbrLvsQ6Z5nJgJBZVkM2yyuSypVCMyvM5CLcyMb8bXJdhjAUJ3P0GMhDSScpFus rcFyMXDcAFRMCgskYRMUogsiNAICHzpDVwtrlWVBAqpH+RIxilK++w0DOYv7CQO6AQEOhIvk49jC ZIxm22M5WWdd75+eaQrKClCy8ZK/YTBq6x7KmE8apvP2DJXG8wZzhpT7Bjmq+N5cwnKnsyjoheCz aMlnFZFkLeAa41kiU8XV04TatoOfYzqHoxAB/wALYL6CQomMUDACCAUvify5EVMhKFMgh+G08lGz ZUySKSKf4bS4AAafhtBWsFhYshUEhDFsFilKUFmjVeiJppkNHsDKimmJTNWxg8CeKUVGIrKN0FTG QQOaTglJKVordAqp2zZQRZtBFRq2VOs1bOCtYqNZgu0auKcxse7BrGxzMdkg6QZMo2HdTYfWsmVV jLSD9DOs4l3SWQolyPHY5kSWkwO5nWuIRMJkWRtsRyJ2zfOZaYymZxmZkISdeS0vlU1BzMjBzWRT clNTeQx8s0XYl8GWZuTNsa+tIpAyOQYawnVsnyP9G1MjmkEipkq7/EI42W5K1fTeQIZSLydxSEMT KF4xtnAfzCJsvcNHslKzuJYKwlPzMImFzyC0zkOTykJPy0JM5dMzbWbkz5lCrRzoHjCh5DLsPZwz PGRFrg315HILvocybLOVBsngTFBzOu0m8dneCtkHeQyREIzOoAhJbN8qaNmmXV9jtpBQ8RJyGN4u kGWrsIrMwWxxqOWzCATsjO4t9cpyZpH/ADDWRfyGby2VtmD2EypvJuIXJkJh6xyNu8mGeUvI2dh8 0YyCeO5g7dz73O2DJ++yxoyYxWZIvXc1mTaMeNMrjXLHDstfy7ysrn5MJlXKGcYhG5M1esyfYUad eTyRhHR5s7jSOUM6jlpCsocOmsDBkyeSapOpSFhWTnLZBCdksib4uxDKXzDBZ2Ul0KZT7J6+LkbA 0u8zuKaunkyLvHIPIV0cbVmmSUQ2l2TmPRziJWcZi9fsIiLfBIR+z7Fkwbx0Ph2QHaQqrrGcnekM b7EzAQDLstelZQf4kO9iY14+Uw7EMsj42MgijO5WzjUkZeNYsFJtGNO3nmscyPPAJ8byzL51vLST A5zsZ+P/AGUPhmSMoiprOX7h9m7Bw2ksjzKMeY81ZC3+u/ry3895Il+xfsVoovDM0IlWHFiiGNQ+ cxUbjxJpxNYl9dSUeVPC0AemwqdYwbty5LkeX5Wdsnmn2aH/ANalkLSCxiJk0ZaPr7KKJoLF0CPc LwSVZRT/ABUoSOWR2ZMZpziDxpCZAgLebzfGnTGDygijfIc0ZvGsHmUodpNZtX2YZMsZkLQq+DtU I1aEbMGjjGYwzVZnjhWYwX1tIRwF9IAgIf4PAVkv3k6g1WyqFk1GuWYA5ZlmcXcN3Ob4m8iW+Uor MHP2FiThknmEQmycZ/k7w7nL3QOUsvxpw0SzaIVxR1kP1mZuL2sw/E/tPsRJAJXPm5WmPCaCR+vl yKlxHKk2ieN5yizQboiAo5mJQxnGcTj5hnMY8wiMQJBRg4c4WMr9dscUhV4X6xerHCsi8MdzPEyp qkjDSisfjYkDEvME/r9yqmT6zemBLA3UdLqY35EN9efWwGCA2PYuOf0mmRIjuKjXp1YqNWcu4mNe qiACA4fjouMoZIlxjE8dbPcdZR7NglIRUfJEYREbGlkYmPlCR8RHxpH8aykUv5uDBEhSkLT6Din4 RkDGRVKpJrJt8QgW6zhsi5QZsmzJFWJj1nogAgfEYE7oqKRU18RgnDtJFJFJGDi0HTWLYM1ZbH4y YBhER0cL2Hjn6khHNJJDJWKv6aDjjxcVTpo3eJM2TZihL4tFS6jGPaR6MBBvi5BJ49FyqsfFsY1O TgIuVPHxbKNRk4SNlSx8QwjQp/HM5JFFsgggpicKoukikik8xKGeOmrNs0bowUWg8/zCseaKzGXw uDll4rCoKKWc/X2PuHMViEPEvl/ruDXWgcTi4I38TCftGmMRbOWm8IjJh4h9fQqCk1g8XMPYPGYu CIywiKYytPcSi3sxNYqzmZF20bvW3/8AMYr8iUxCKkI2Sw6NkmMph0ZKkKUCll4xKWjjfWESIwmE x0Ukp9aMBVkMZjXsQH1fF+MJj8dBo1kWNMsgSjIFjHRJPrREi8dgrViyQxCNSgkPrZAEkMRjUoFL 62C+Ypt47Gsdjf1UN/0JyMq1jEhzWDAHUyzZtGWRxb5T5q+avmr5q+avmr5a+Wvlr5a+Wvlr5a+W vlr5a+Wvlr5a+Wvlr5a+Wvlr5a+Wvlr5a+Svkr5K+Svkr5K+Svkr5K+SvOvOvOvOvOvOvOvOvOvO vOvOvOvOvOvOvKvOvOvKvOvKvOvOvKvOvKvOvOvKvOvOvkrzrzrzrzryrzryryrzrzrzrzrzrzrz rzrzrzrzryrzrzCvIteRa8gryLVwryCrhXkFeQV5BXkFeRa8i15FryCrhVwryCrhXkFeRa8i15Fr yLXkWvIK8gryCvIK8i15lrzLXkWvIteRa8gryLXkWvMteZaAQEPS50qUrIkjFIK5EozcTeTJMo9/ ev2Ei4krzgicch8i/vQoByCxhnLmGduIzvkB5+wmnxTWPPFrzngEDTnmJ5vy+SdCvkmrlUnApRWe ADLT4B8s0AfPOX+ee8vmmqBxN3+eb8QcTniVxPfGVxMeZXE0IflS9gcTNiuZrzM5maF1NBR3UyAA 6l7mdzHko7lygV7NAH5kuAi9mAoXcr5flywh+XKXK7lhH8yWEoPZcTfmSvkV9K+IvZMBB7JDX5sk Ii+lQA7+ULQSEvYr+VGhfyIV+e/EBfyNzSMwIfnTA0Lx+AFfvhoXz0KTkJA4EkX4kCQf0Ei+E37F /QSD8R/ZyQmLJvhIWSeCH7B5QyDwKNJPQOaReeYyLsBGSdgJ5N8BP2jwAJKOzAWVeiX9m8v+zdCI ybwKGSdeQSbwVP2jyx5V2UoSbwAGRd3GTdlH9k6r9o7805Z2YppJyWgknI0aXdkosq7ECyjsaUln JKNKvCmGWd3LKOhAJR1csu6MAyjiwyboBCWc3NKvAD9o5v8AtnfgWTcmAsm4MUZR0A/s3Pj+zd0S TdCQZN4AFlXYilKvBTGTeXCVeiQso6MAyboK/ZPLjJO7BJO7hJvRAZJ3TmbUaIomA6XpchevmJJ2 RCUUmkH7JV+4PMStJP8A8abTOVQlq4q3G61W2862r21tVttgq1tLaWq2ttbaWq1Wq2vFcVbi3RtX OlqtttusFWAKGraCGtg0tpYK40trzQVaraCGnarBoHGlg14q2vGnaraWq1W0sGnFcVbS1ZRYIRqN 23pVLeZEUUxMUpippppAN6YCUcirnaGvHTDQNnO0K49D2oba+1uiGth2hrbW2nbZ7217ae3Ozmua 7hoNdtONl9b0O3jS9d9b172DYFcWrKzmTgmn/wAX0p/9tB0IzUVyJIpip7A07a22W056Y7Q2cad9 nFW53GKBg9tOerbb31vpfX3tVhodLbuetbXmrje59TGEtdwts53Xq+l9MpSBSEblAqHpTf7UOoKy ZMgTE4kvpevbcHU99gahsHUdg6e1tt6vu9racbbVx6C3W50vQhs70OgiNWU8qEQAAG4ANwALBwIc 7b7ffUQ0yb4f0jcQFD0p/wDbYiZwfJykNYC2qw1zXIVzsvtHaF9Od3vttV65221HTndxQjV+L6c6 304rjWwdPvrzu77A28686WDZbTvrYK9hAbAAWtQgFe+g130sNWoRtstoFdqyxc6MIyUFVp6VT/Y8 1FkXdSjBoT+jhLFWIqQ0axfTqSRU0qCuavtChvXOgDt53X1514071bTnX2Djpe9DfW2wdOavxoG7 nTmrBt71e1X0Gw7PerVzoPRsO62trV7joOlq96/7quNcb+dPbKCCeEbhZH0s0+Fm3ZtVm+Q5Mt4O W6kId2UAADllAnY0Jv5NbVxu50407+h77eK7V31vs415052BVtvvaud/Gy1W0tVtO3R51ANeNLVY Ar243jpxparDu4oKCr81cL6W51ykEv0yP/i9LOQ7l+9BOTDIpaZTjXGRyTCTXIYBKxcIJZEQxDlq 9AI2oeNnvp3q2lqDS1Wrv0eNR43DqO7trzV9eNvHS97BparV7VzuDfxpzQVzv7a2odL3q9BV9t6G 1e9WrjfYNmWn8IFvf4PSqBc3xJ+SzZBcqMcwb14hX4UM5nmrFq0rvXN+asOvvrfdx0r9C9AO3vQV a1cV207a20HYA6cbQ3cj1uKtrxqPQ4230uGt6vqFc0Owa70F6407121vQ6ZSmVWFQL4o+lP/ALUI hXA0PlRfzjzaPyAmHNc9Hjr26POzjTnbfUNO1Xrmr7L7racdH31G1cdb3t0B43DQa9wrnQBA2nbW 41YA23oayn4v0aH/AIfSn/25odBvSMi1Z5EkqVZIBGg51voGy+ziuOqOgW046XNX2X0HcA689Htt 52XDW99BHS1e1cVbULVxu404q/NCIVxVwryLV916veuQGw6WCuNnNc17ac1xWWKfFBNxAyHpT/7V eu9CNMUWi2QFAAC3Q563fS2t6uO4dL7ed/Nd9BoR15rnX3505riuNO+7nbb0Ntlg0tpxpauK9gHW +vFX2caCNd6ALVzV7V3q1AFWrJ0gWhWhPBt6U/8AsI1xXvzSSJ3U2kXxJXFc6hvAd1tedeNPfZzt 56l9L7+N1t1tOel7bPbQdbBr3r214GvfoFXRMpfW+t9ltt9cpMn+mbh4oelkHaTJvGSsi4yHI5N4 kud5JQUrfg0q3i8gjptlIn050G+l9eKuNduqOnFXq+t7bb1zXN71euK5q4VfS+t6EShXyE8u9WDS 27nTmrUHWvoIDrxXOlxq+y/Q52W25G8ds4uKfSij4t7bLbu2ltnFZYcqcC3ERQ9LlKxjOjyTQ2Rz JWwZNkXwLztMTNgyAoAHRtrzXFXq4X6F6vrer7edlwrjS+nFcaWCuKENLBQlopSlALhp7caX6XPW 5230Dr20EBto4cJN0jxznIXLeOZNVavQaXvpxXau+vNXHT3tpespSFWFbhZD0pw/7jRbcZCSjG8g m0iEm6tIsk3k4mQqafGtg3XryC96A1OlxbtwnHpkY96V80uFXq9X1vTmQQbqvH6DMjKRQfFcukmq LKYZPjvJlkzUUfN02zGWZPjUeVaEcpLJKhT+TasBLk8YZRF+3Xc3Cr0tINkHLaQbuVr1ejKFIUih FC3q9NH7Z4Fc1enLlFqi3kmTls0mY54o4n4pssylGT42tquG7nQOnx1g6ghThdJsiih/SCmmRImv N6DTnQbVzYatpxpzevbKgS/TI2+L0p/9tB0SfKt8kSMJ0wHTir7RC4fzpRMbGUwr+eDyNj5TKScG qSMbPBSYREGoeMJAmTMWEcFpODcFpjGLNFqGhCplm0j5984E+aNHJf7PNnKJSZIsDeTxYxHR2Tsy jaaOCGSmARJDt3LqWwv8pY/NjdsPMCgNpVweURdzDuDeTz5Zo7K9ZT6eTroKtUsiM3nZZcq0bKOn TNu+eRsGzn3LVRm5l5l3hrlVynIuHjZuE1kA0UTCSVeJv3ov0QxTIQBixK+eBkkS4dOU71fW+nO/ m3SCudLdMNeKvQVxV9Rp06QaItQd5Auuqm0aoZG8ct4iTTlWWlt3vagvtvQ20yxQ6UGgN0fSn/2E dLaNHEe3nyCUxbX2jfod650DaNDapWHWfykzBGfO2kIuzUCEXloFtj8ipJHxqRbOFcRTGKZwkgeT qLhVmUo2gpGJCFK4LH9xgIZeMBGCcEfMIF4hjrnF5NwzDGpZeSa4woVYkBkYtXEBIJzLLH35Dp4l IAxbw88KwQU2wdY7DuIpOVjySLQuGMQApQKWQxSMcAliNodSFyB8tHxDlCet0bbuNL7hDfbZcdff W+lgq9BauB09nTtu0Rbs3U+4IQpCTrxogxjzCzQxdBZvCUAVcA22q2+wCHtWXFA8C3/8HpT/AO1C NANd6bt0XE4UAKHUuFXtQv25XIDrxpfTmlXKKRlV0kCJLpLlOciZUnbVUyrtqiYyyRU0HTZcb0Dp v8vfRZy3REJOP+QjhFQ2hlkiHIskc3FWoOKAQMGiK6KwanUImXzLYjhBShcNwMRZJQdnPS50HW4V zuttDo8BQjXO148QZN0GgZAoQoFLKy7eMSYQ5V3GznUOaEKDcAa86ZSCP6VHhL0p/wDYdOdPzHyG RJCoKentztU8xKLOc8TNZy3406IFaTwUo2yAU1GjwH7dnPoNSoTtitsgKT8edEGSUqRSudJ9ik1l JJY7jK2XiyyzM11ASnEkI6Xx9JGVcNnxlmj8qUblBvLxhySLicwg709XCnDRs5rEWrdyVrI3mAn5 t3FusqcGZvnMglPM59NF0lK5H+JMzj1uo2nXj9lGzbuMgG889Zuk52XfOcIcHXSk5FONbBlze5DA cuXt1Umk69VQxiZaoxTV08YIZFBKxq5tveg096v6AatXO4K43e/bS9Xp69QZN2bVWeVKBSFnZxKL QjopwZ1+S3AxFCKAFcbAoel730y1TwgW3/x/S5EMkoKi7mAkcqcqEPHR71wrScpHRuSMZuMfqhYd lt9tQRSBXfapiGdP5SZiXqsiyipI8i4YP56J/WyklIt4uah1y4m8LGox8m/lwqLhl2UpERk/Eowb ld1GDasah3UURtBu0pRlAvUsZVx2T/BMwm5KXTxt4Y6KWVJsXkM8/dRsBJoH/mZhWLRhna7townI Zxi0S9jUZJq7dNjQGQiJSiUmRR7iSjJiEWfwa7OZmKZxL1LI6Doc6Wq2vOlutbSw0Abx0tXNDS66 DZMjB3kDspQISVlk2KcLBrpuRGwGYN1XeHAcG+znXiudvNc13obaWrLSCpBNw8UPSvpFm2cTLd9D u5RpGu1ZxIYlYl/FnY86UpQHXjZfjW+iipEiKzkakqisRZO+72MchaMYpA8klif9iZE1kVKOsinQ nIBSKpHG9Cqn5HTSWIAWA6hCV8yVAYojoJihXkURvXFXCrhQWoRCgEo1egq1eZa8goDFGvMAoBAd LbLVzVtOfT2tpzvG2splLZg6bs059UpSlLLTKUaETCgkuIgALPwkFhxSIGo+LZxpOasGltAq1Drz t7aCFBWUfCMMgFkfSy8O0lAa4q2TUloRnKEZ403RXpIJQ+SJAoCeltnGh/PwD+kEpxyOxzZENENk lTKk0lFmOwO0jlZw7AxslERPP2BTJLNDSgq1yFDU0m8bT0uoL3KY4SR+VZe6UTZSaaMFNRzQk86b SizmKcNyQmSHExSRhpBxM4S6eLD7SEOyklMbimEqmxeppy4ZPKKMlsqKRk5kHricjJRk2djlEgRN /NuiOiZG4eM4OfXZwqOQP0nS2RvnDvB11HDR/INI5AMwx4RKYDlm4VizbGO7hcYkWwQJnziMPkOO pw+ztsEBGrW3c6Dravf23joHQ9qGuKk5NrGNVISSdniY0ka0mp5CPJFQpmxlFCJEVcuZtdu2SbI7 LUOoUOttLadq42ZccCQaPKXpT/7Wq1CFchSb4jSfSMJ0+dttnGnOiqKSyZoOJPSKCaCVq7bRqdjX TmYl45dOZjWb5xLyBX07HGScT0i1RdQKv8w9ZxyZHUtM2qCjnbWUgkpSHSjHgv2Pvice4YJtotwS YYxrsmKLRcg3Yuk3crOlg3LldKRkis5FBU85DxzolBDSTiCbMEHb6MF7AusQZu2iMu3eOWgRWUAc l/HJG7t9I5VFrSMS9UUnxZxQmylBu3bloAsFg043cei7dDvqNc6Scm3jkWMS8kXlgCpiYVbjBY6m xFZdFBM6bjIhbtUGqVc6cbO9Wrt0baDpl4eUGl/4/Sn/ANhvQ6DxUccwzYCHphvrYKEoCVJFJBMA tVqtVqDRZEi6SSJEU7aW1tVtLVarVavEB14rihqwVYKsHTvQc1bcHSvs4r3286yUo3jkmMQD1wpI x6Sj/IEwPEQyUcDt2gzQSbBPgkkmknqOltnGvOoDtG1caZSVuaKREBS9Kf8A27hQ6INfy55MokJp 20tXNc771fbzparbQrjS2z31t0Aq1Br33d9nFtbac0GvtVujxpxsDf20mZpGPJGxa3yCIADd2gvK RZkT5G8fNmSUag9lFQAADo8VarX140uFd9Oa70OuWnAkEgN0vSn/ANvcdOaauHBJ1IxzJ687R222 3Hb22B0eNLac7+aHd26dtO2y3V52c6c0PNXCuNZWVO3qGghanEQAJGTdvlW+IwyaaiUTBBHRJ3Lj tpzv4GrDXNW152304q1WrisuTFWERt4elnJX9aknPPUXUvK/r0mE06O9pioITYDstrbcGznb3053 +/FXodPbiuLbedlupxQht46QVxu5286c6DpzV6k5sjdaIg0Y05hAoKvDZCUU2OOxpsyaAmziU1F/ a9cUa9uhxV+tlXxfpkLeHpXrNqueWfOV5eYP8mWZYfxmqRj2chkLSMYslNL6c7uN3OnGzv0udnG6 24/mJPQWAdferbr6Xq+znZ31407UI1JTS5nURGfr27lyi1QKD7IlWrZJohOSYO01GEy4atQOVvbQ K9tffd2rvV9Par1zXFBxXN9MrOKcMgP/AGelyGLfrvHEXLTziehXThyWLfy8n7NkJAJ8nmBN/sF9 ea9gv1rW28bb6W2caXrmu+33q1e/U76d67buN9q7VbUdXz5Bi3LlMs5NERTeMbP5BtHt0o99kJ0k kWqDqRdyq0dGNo9GrVbqX3cBpzXOwdMwsMI3SSIX0p/9qG2nNIPEm84mchy0GvOobfbS/R5q19tt BvvvpzoPoQ6nG3iudedeNeB1vShyJlVclyIWGINWz2Vl0ItJtDFfuXDhJoiYRyJJs2RbI7L6cVbT 22X2Wq+/iu2uUgj+oR/19KfuOo0xaNnWQEKUha42BpbZffxs52c9K+z3rnaG/jo33223rjTmuNL7 R1Gn79tHtwK9yIybiMahJ5Ag3CLhlUlpCSbx6SDJ7JrFAoBstQ7L68dXkK4rigq+mVmAsMiNyelO AeQhqNA0WdzqRTETDodtnGl6tpzQ1zu71xt71zXfp++tqtpb0Y9GwV787RHWTlW8ek1iXUu4AAKD RszduMbYs0n8jKEaBHwy/wCSFcDv5q2nYNO+0NPbW+zvpahrLkzKQqIeJPSn/wBr0Pa9DSck2aTa ahFCUA0HFD21t0eatsvpxrxs5oNwV21t0udePSX6g0NqlZorM8fApkcHORMqkirNmTxiDIUqrCMX i4NBkOnN+hzoA9DnW+ludbUGuVlRNDogAF9LOzTeIIllLpF3PTZ4oiWRSxlr0wKRTIygFte2wOgG vag56FtR6g6Bsv6S+nG7ts523oxvGn84CisTFFj0n8izj0W5H+SHnXRomPWlJ0ybBgiyQtXHQ9tg W6dg1toHGneu2mXHEkMiNy+llY+MXUlnBsme5FHPHjr9jLwb0BAQ/Vke5HHQ/wCC4Dtb0fN9OaHb eg0tQ7LaX296t0Arj1d6vV6vRjlKV9Iv5c8XEtYxGVlkWCTOAdP3Tt42YoLtJbIUU8TkiKgHHTHT jS/F6DjYAAAaX5v0RrLUzKxCRfEPS5ShLOqbDlzQJgkyUyiExMvS3sK0olMpCoKeg9TtttQdK9X/ AMINcb+B6M9LljEWboXZ2jNsyQe5CQ7qNx5mzVkphNioSHTdOrFKFg3c7xGhDaNwAgGENltArnZf S1caZQDf9Sn29KppzrHKFHJAHTjQegOwB1vsGudvGy16tXb1/PQvoHG/ipOZZxpUo19MHj4iPhEl JF9PCzaNoxo4kncmdlHJNC2rnQegFc1zr769wvuvfQNb8++lhrnTLVRSh0huHpT0NcahEx0lkSZC pJ7LdHjUKCu+/nZ79qDW1W3X6oX63G7jTnZxQ1KTCqpoqAIzFCdmnCLJKRyUyizCJbfhPZxVBBJu loGgjuvpxqIbLdAwgAFN5F0vsAK7UNd9MpTFWMTCwelUCr1er6JHejNp/IBPQX3c69tb0Go6d6H0 3PW7a99vFKqpopqP3U+EdFtY1CTnWiakUl+OhHSSEWkhCpqugAAoL6jrzttvt0QvstuEQCuatVqy n4P1aQWL6VSh52Iv2TLICGA5en20Hber1feFXq469to6c7r7uNt9nbdbW/RvUlLMY1NJs/nDqKNW LcX73IFZAf0CQS82s9Yx6TNPttENOdO3oO9d9bDpboH5DXLFBSiE+3pZmXZxSJMuZ/kSsyzikmeT MXLrvTZozc5EQpSl6fvxrfS+nG3nULW6A7Lbb9O+/wBr7r1er7BoRqYl1wPGQRyqyc63aJtoF/KK vX7OKbqw09LnZY0/RkQ3js41tst0L9MA2X09stKY0Sn29LJMGToZZ6pLO5dRUMiyEPhkaboArPt2 wIDoA36PtXNd653hQc1xqGnNAG62g9Hiu3X52c1eua7acadqvU3KhFtEpJx5sYyMiEjThpJxGwjK MKSXK8dMYFo0cAAAHR4q2tuqNc1cNl9Aq+ltnGnOmUlTNHp3t6XMEJN0ixVnY1LJ456c6gP5yV5o 8s0jsiRUKqlaudL68V7VbcA77a309q5q+vHWsA7PfcOy26+4RqQyNgzMByPTkVx+IojKSnTunrCI Q/GkJgyDdFuTqj6AbVaudONA1AAoNLVbTjS1ZSYSxqX+vpVNbaR5CBkgCOlqG4bL6X6PGvar7O1c a22DbYPpw6l6VVTSIeWkpZzEQTSJJHtmatQcXHqy0lKriLGETSWt6K3R53cb/aud3vlhDGjU+3pV K4q1WDQI5vITqaYJktr2rjW9XrirX6Fq7bQtrxVt3GnO21e+zjdbbfS9c1euOjJTbdgoaIVlqeyU VBoO0nMo0N/LnqHjUHLWPjGcelpbbzs56XvuuNBV6voG3muaCrjV9l9OA0ygiBo9PkPSqUIXoA1I 8Wb5EkcTp1bQKt1udgbh5r309+dOfU3rnZxXGl6vTp0g0RGQdzZmTBpEtlMhVklo2FTY09ll5ACR ORoN4dss2j/Tdtg620t1OdRq+zKbDHJhYPSqV2oRr3pF2zZ5EQ5Dl0tfUdbaX0tXNW53hstXfYA6 Bp2289C9t9tnG3ir0Ojhwi2SNl74q7OFcSppGUZRSSUPKzaikhHRpUYuTkwbM27QlvQ86gN+pzQ3 2++lteejlpDnjk+3pVaKsiY6ihEwB41GvZJszezqZCpktXOghrbZaraW2W2BfXn0fGnHoe22SlGs cku6PMooYxBpu0pg0qckXDQRRO8mEY6HYxoW1t0bdGw1Ydt9eNbdAKtXOth3CUBrgdMp+D9en29L Kkkjp4iBhns1WIBmKeGLuS2ABdyKeSMHUkqps4Dbz0LaBe2vOnGnbXtXFcbA2c1z0x6XOqyyaBFJ 9Z8rGwiiR5WSjF5uScMl6JLmXpjDrANvV8dHnW/Pvp23cbB0tQ1lRzEZJ9vSq1jJUwn55zCIucrJ GSTkoWKWRYx+RILJrpbPbUA6Vtb6BXOoX2Xq/qLbx7PJ9BM6cC+lDOZWKiirJzs0k1jlXrWDxkj0 iKCSCXoPb0Ntvegq9c1bW2y+tqvsy4pjx6V/H0qlIsmiCjho2dJoRzBqemZSHyAAANffUN/bUA0t v52WHdxsH0fvpIyzOMTfZAxaJAk7mUhLD4+1TdPZ1uVvBQypkHkw2Uw5gaoqMSjGvqrej99PbS+n ar7OKyf4Pwk7W9KpsG1JlkT5Ej8oJbQt6DjZbW+tg2X333c6X0vrzoN65rmpKaYRZJlyZw6h0m8W j+8kJUxG0ZDiQsvKlYRzZglu50vpfW9caX6/PouR051sNBu5rKFAIyT7elU04oaGhfoMMgQVIuja rVardDjYA9AaDYPQCvfX29A6kWLQDSE1LKLwDKPjGmPRp2MHFRQNRUmX1RsCxjw43X6far+i46A6 33Bt99uVJqHZphb0ylANc1er0yA/70BtV6ARq9BV6AdOd3fQNL686gFhrnbzs9qtstsvoG7jY8fN WabaXeSwhDRsYCU44eBkMOkVD/8AQQTjsdjWIgAW38befSdtgcbL9ANg7gq1d9O9Wq1ZSVIWiYWD 0qlJPWiy6iqaREHbVzom3Vc5GkQxE9ea9g389HjZ2qw3q/Rv0A53Xrml10m6TTLIlykMtITJDNoa KoJaTkirIxMav80rJl/lyKJlxVoQA7bw5DYIVz1rdIN99/bW2vbTvuGsoUOmzJ29LMpSayOLppkl 8oEjyRkWjGEneLJOTI5I0eOllg6PHoRq1W330v0vbXsD6XYMQm5N/KGi2KP5Z3s1IUhGQzBcredl DNIWOZja3X42c7ONONnHVvoOvfqBv5voNZUQTtSdvSqVAFtMT5QQmZgE3cxTQxSz1r1bTjrhpx0e dt9nPUMcpQd5I0QOq3kJRAiuOQx3MlaSReM3r4jB28TZxceyDdbTv6i3oPa9c7Lac9INO9BVtMlB EUCemMF6QjGTdZ4ybOkmcVHsTWtSDNF9kiRATT9EHpQtsvq/kmccivLx7dsWfdSJ1o1NOizp1hdp HArJ2qUjyKnCrwLCQbvfSW9NaudgdIK7b+NPeg25OsKbcnqFKvQjRCSH9KkKnhqHo/a462230428 1cdb6XAKeZFGNiTf7CReQiKDR0u/yFVFCPjlDNoqcWTaY/FtRsAVarV763C/+MDpX2Bt7a8UADXt lJDKN0/UKV20YmKE6Gl7dHjcFcDv40DTnTmr7A1tQDQ6LLoopqZMidWUFIUot0yKRVcHJo06z6R/ nk3BkUW7YoBb1NvRc7uOp21uNc1fo3sNc13rJgRFBP1ClX0SZNXuSEIQha4oLdUN/Gy+g9Dmr1ep bIY6IFxk8Ogm6yR2okg6I5VXF+IR6bYg/rZR1RoGeFGGYuGTOrXHTirf4zjp86jVqDYAdD35q+mT nEiBAt6hXT2KzkFZ9MDFTCuK46NqtuDZfQdb1cNede2gjanMkwaVMZOkdus1fqKRsK7bEYxDcgli JdyRpARbSgAA6A/4G/W538dHjcGg6hrlBRM3L6jIHazKORHJXCaQKfExXZt5tBy1XNttrfQONL6B rer1fW+y4VwNDXFcBV6EwBQGpxJM2wuM0bFVGVlZIysXCgdGCj/x0TxAtYOHiRaFKUpa4/wfPrLB QdPjW1W55076WvVhrKAbfAn6jI2v5jGciSRLKIdGeRjAiKuRJookGuOlcNLa3q+3gdL80NtL1elF kUiy8+wRbryUguX9zMrGQxyRXOhjKxE20IzQOVFMhLceIUAAFB/mh2cbeNOavqF9ffbzp3q43vze spUFNuQAt6fIIZGZZq4vLvSoIJN0f135s8kUSJ3q9CPFW04odoBpxV9L1yNXtV769qEbU4lGDZT5 C2WyGGRVeZu2TM4yOefGJjU+9pthTpBuaByEzSKaA2Zc/wCcvv8Aerh1r1xtuNdqGgG+uVE+REv+ vpz6DzRJBoxnCH8y3q9X0v1RryCr1cKMcpCuZVi2BfLGCSa+XqrpfgsvBtFGkUSYXGKFb4pDN6bs mjUlqsFWDZz6C+4a59bbo32DoOttO3UHb3oLgNBesnIgZMvb059LVFKpmmg0C+t671ah40vpegHi 9CNGXSKDifhmxl81gUivcikzuC51LKJnyDI3ooMp5+4RxKUWTTxFoWl8caA1Wxp4rUZHoxzWg221 v1udOehf/FDt52c7uavXNAPFc33ZQqZNsXt6dQbVzVxEE4plJTiKZUkr1fW9X04oTAAqu2yNGyaD AZGQcyrpDJJNukvkE8c/4GVPWxcSmDiTAnhkwwMpACNdqscdg2iLRJBJEtqtqGnFc7r7r7L636t9 odS+t948bBvbX2vx0LdPtpcN3Fe/A65WBhal/wBfTqDXFGGxWc03bycfIJSDZR23RAJFgIKSbFM4 zDK0tMnE6Mi8bvjvJujITqpVMaI4UUw+LUEuJwRQVxoqTuJhAZuPEKMchNOKtqHbbzsvRTAYL1er 1er1evfb3q+gmtuv0L1zQ0AheuNb1fo3oRANt93G6/SEbUA8bLgA1fX3rtpfS+nA1xXtk/x/jkEB L6fJZgYhktKzkSIKFVbqPjskIc2PumCJcVBSVloVoQJWGChl4kKylxFLR8Y2g29BMRQgMtFhTDIm i637WMsEpGmBnkLZeWCTjhr9nH+OQyDUTA/ZGEH7EQlZxsxYJyLIwfnMri/ZAEROJSCIPmdgeNRB 5Ptmz78puFA8aiEtNpMEvy2lhcoAH5TcRxhyiWIB02ERXRqNnCPVzumyZSuUDDJy6bEAWTGgVTEZ WTCPYA6QEnyECvyG4ljZUr5QjlBQfmSCphYoSXzJgUVUwCZmCRTMVkwKKhArzKIRMsWTR+QtCoQB ayZHL7yAa8gvISRGQCYK+ZK4nC2LOwVibhQmAKYShHioHKavIoVJSpY84qkJVwqTkCx7JFYFUfkJ f5kgqPlSPlflTGvIBpBYf6nzKAXCpSTSjWwGKIeQVcKjZMkgF6FQgC0mEnT75E73CpaVCMJ5Be4V ki5kIRsoAt7gAeQUyk03rm9XAKTlElJS4WuA1KSKcewRWBZHyCvKo+WQkF715ANNVznyIpyGq4CM rKFjE72q4AEjIox7NBUFkb0CpBFjKJPXN6uAgjKpKynkFXrJ3HxNif6+nzwhDJZkkVSLi2/xRysN HrL/AKOLsbHoc1DBRQiOOw/j/PQwm/n4e447DiIY7DBX87DWLjcIUf5qEsGNwpa/moShxqEEAxeC AymLwp6NjUMcE8YhUy/zULQ4vCCY2LQRjHxeDOU2MQhgJicGQv8ALQnyBicH4jisCIGxKBNQYlAA P8hAWNiWPmAMTgwMXD4SxsPgTkHEoCxcRgSj/JQNfyEBYcOgBr+TgwouIQRKJhsEUo4Zj4iOIwIm /jYOgxCCAf42D8xwyBEAw2BAxsQgjV/HwYlHDYAQPh0Gev5CDr+Sh/MmIQyZf4+G8i4jDFMGFw5V xw+Io+HxgibC4k9BicQAFw2GKYcPifA2GQ4m/koryPiEUYv8dD0TEYwhhxKMo+HxKgqYhEKkNicY Yp8PiT0GIxQUOHxdgw6J8AxCLKAYbE2DFI8KHD4gTFxKOKBMRjypK4ZGKEHE48TGxKNMI4exEwYh FlMpiEYcP4+Kv/ExFFw6NAwYfHgY+HxpiFxOOKYuJMinUw5iokbDo8aPijE4BiLKiYhGFEMRZeX8 lHUGHxYCbEo8w/yTAA/jor4/5BgAlw9gVQMVY0XC4siv8oz8v5GPuTC44lJ4fHpqjiLUTrYbHrCf EmBiDiLMxj4XHKAOIR/h/IR4j/GRw0GGxYD/ACUdRcQjyFDDYsA/kY8BHDo4T/yEYJ/USkY2k2pM ccuqKUCh/wCjjlUyDcPsJyR7kcx+miDmyZKFfZgoniSjzJIJuwdkfMull2TuIlLB37qQgnD+YmJj H2cvGIoSmT5EbDsgGcjOllc4eDilpTMY6Nncv/FxtSbybHV8uyhxHt283kcBM9ORyOdk53Gsnfnk yTeVysnBjkbFH+ky2TTxmcLOxfSyWdTgo5fJMyhy5FlSUXDJ5TkkQ5y7KFYdNpk83Fy/SXXTbof1 GXvWsZlQSONxUzn0k3LLSMDjwZVlbFuydpPWnSfvUI9njGYTEtP5LlD5rJQOUSYTUjlUvJSuJ5U5 l1+nmeXrRB2Es4HEY6cz6QRdz0hCY4nl2Sx5EVk10elluRysfKRq+eC/l8ok3E1i+UryK6uVZDML 4tPlnoz02dNSHyv7ET8scOuQfrR+3UDBcs+I2HY2kKMD0swIY+NfXpQJjjfDIWXfwZX6KmA2Jjv1 cAfD0njpqzbyC8xnD77AjSx8b9jpJHi8lQMjO/YnkeYLe3SyjJ2kATDscfFeo/XirxeBfSJovCkQ /kPrJE6cV0nThkgGbIz5l8zFFaK+yCFCMyAiiWR/YSn/AN2QwGJ0VDJkJl/7pyxxpH9lhzjC5eMh 5aQkZbDslSUD6/w45jY10s1km7uYh5KOa5op5l+zZ1Mw/YeCpnLk2LjfPelJPiRzB45RXYwxiy+F PMMmouKnpN3LYhmZvHDcaTMnj/SyfD5Cam2Z5rF8oxQFTZ2mgqrm31qUSxf1eioVL00rjDCVkXrF s/aj9exApyEMyfxRfr6JEhSlIXpSTFORYQsQ3hmB8KZEdwmLxsKmTBGaJImIZRDPpZFBlnY9P66+ FN9i7R/DEwVJRbJMXaz6bfDkAkunJ/XoyMjD4s5jnqGEuI5xAYkwhUEMGVaNIKFbwkf0slx5GfYv MMk5BtNYm0k4hbB3b0+S4o3nQbYcspL9J8zRftGuGTDFu3wlohAFw6aLFKYfH/zxsGk3LNq1RZtu k5g4d2s1wVmhPZBiSknJxWJLITTzC3ZZnGcVSgzdJRNNVOcxCOkmDfDWZMfDEZr9W7w9itjymDvH jZNMiSfSnMUWfyaGIKrTTrEFiTmP4qnEOUsHkmKmNwCECw/5BcP+h0wiBVfsWSQBl9gv3a2T5ETH 2eM5ElkDPJcxThFx+xHrU6ZyqJ6CIBtEQANHC6TZCJm46ZTEQDSWkAjI7HpoJyO0nMpJDO9ZL7CS Yvo37AI+e5BmkfCKweXsJtNL7P8AMcezljMuNCZY2PkUzmrCMfNlVFm+rqeiWb3/AJnnxip49hoD /N5XKJP8mw+UIyyXJ4efCXVzBVNZk4auWuXTUmEu1xvIot67kZbIcnGRlscyVq+nJfJYMs5KucUn nox0RGTuWR2Kz0n4YPLST6Lh5HIZuJxWVftI5vKkfty5pJkxhxG5ATHsCcKOMfzJ3IsYWTy9+XG8 nlJ+OTyt6/JIwUu7Jk1GfzCOYxUhlysgC0y/yvC3SaUrij+eRUj3UgfMtMjfyDXLPrxVm5XzScmG ElKuZ7GJfJJ6VUmpQMixcZcHy2Q5jIzsSi3k1kX/APzHNGDuQgcYbu2mOY7hLh69ncIeR7yci8pR kZccsylSIjiRkbmkDJrvGaeZz8rKxE/DZHHRc9kGQwkPLs8zxOGlmWQQUDJMm+MymTsY3E8WkSNo MuVQaOEQ0y1Y4/CzyaDD+kh2ZsWmHWJCvmDuGwdk9YQbtsm7awGJzP7vO4eVkHs6wlWWWso2fPlV O2WTR+WN57OhWk2ctjuS4tFSj2Yx7+qx5RnE5PO5E4m5ltmFN4qSL9gzGNzkNOZQxmJWQ+wYqSfO cug5YZF+GTZatlcTKozeUjkazNzHO5h8mUxU/wDnrhAjlvAQSEEy9J+rZDI//hO//9oACAECAgY/ AHoP/9oACAEDAgY/AHoP/9oACAEBAQY/APaS391Xkw03bQCx3EKAASOJxL9Czboab0kG1qNowFTl iCxullMtwAUZFBX1NszJYeymu56iGBDI5AqdqipoMG7sixiVzGd67TuAB/HD3N1IsMMYqzsaAY5a pO0YIHO2ALQ6mm7dl8MLd2UnMhYkVoQQRqCD7APcypCjHaGkYKC1K0q3wwl5ezbLeVgiOoLhiwLC mwHgMRXUJJinRZEJFDtYbhl3pOlxXAa9iLB4SrA1T5qErQ0+OEtr24EczqWCgFz5V2A0rwxHPHXZ KoddwKmjCoqrZjuCIuokIqEJG4j4f7c2XRraRRzyXlUlRUkhIw1dNThenloxa3KpDuFACNtEIIzr vyx0y2gkhSKUhmEqI/qVwNXB8cR9N6VJHSZE5cRVCxd6jVsWK3M0Z6hPI2+VVBCqoFFNQErnni3+ h6zZ35cBpIG5cOf8ulTWvDC9G6dJFE0iRsqlVYA7Qz1ZgTStfsxbQ9XniuLS4YMxVQBt+VqUWoK6 0H44lsbW8g6fZwAgySqH3EAa1414Yu7HqtzBcxRxM8M0W1VYoN+W3+ZdfCmJ7yPqdtYmFqxWrBQX pU0O7OnDF9d3RSbqNrIFRQKKRJTaSF8M/uxL1KaWJrCWOrxKAHMZOZpt4Vzz0wRRQFmcUUU1CnPF hZooMMrMzliabhtVa0+Jwtn9HFymQb/QKk0Hq3a188Xs9u3OUeuKJgFHMPoUa/CuG6haiAQoSwAU B3C6gKa4fqMSxf1C2lWK4BBK7T+faCKVxJ1QxQLYRwystABudFNCPUWyYYWWKKBrSJl57lQtVqNw WrfNTFytpcWtukJLRJcKFLipolQeA1OOoydThT6qwG5Vj9PM/Ltp6tGGuJep2kFtJDE5QxqjGU0p XagbOlfjiynvbCNbZspElV9wuVLpXbVTtK5j44tJb6yt5kNwgtkZN6iAJVDRW+z4Y6ZJZwoLi7iX aNp5USqi7gFr50AxDd31vamB9oZ0ViwJ4PR6KT8MdPn6ZBG9rewiUNKCxL19SelxTaMQt1C3tjFc UKhFJAANCu4NkfjXAYaMAR9vZd3EVpCtykjhW2sS6uKAn1cRi56z1KOCa8EopGBuKGlQzb93/TTE FlYQRus0auruGYlizKVFGUcBi1h6ta23JuGFTFu+UkKQGL5EeeIuk9FgSe5bbvMmYq+aqKMvDPFv F1iwhS2mIDSxFjkxoaNuIqvhTEEz2cIviy/RyVqHjJYRVq1OOuWLOwEMK3EsSNcTTV5ayN6TTadB SpxHbXFpDc2j7d9zancqBlFGruI11Bz/ANt7xry1f6b1bnG9HSMDZEwByrlpi1velW9zPR/XuqWV xR0YbFrwOOgT8l5JSsXOlVXAVzJRlzGtRriyZo5Cv6W2SlF9KndopqM88W0hsY7/AKeCxuEdWJRh TawZT6cq50xEOh21ytzI9WjdlCiuYVaV08cJdxxNLd2sUaygsTudYxzCfSDSnl54s1htnjtoVAc1 +Va7nbdQgeWJ5er2L3lhM7OkgY0O8lq+mgqDkRXF6bCwW0gjhkVXMrFqyqY1BViwzqcXdp1jpsj3 iN+gd5pVctpI2ekniOGLy7isWhd5I5reNGZi6oKO1GqaUY0w3QmtnebltDzCwoIzWuQXKg/9cfKV rO5IPwXPQYhvLdDLLZ76xIaOyvt+XI127dMLDPZyPfxKE3bgEZlFNzcR8KYu5+ptJK7FZLaJ2UMQ pDVG2OtTwBxJ0qW0kaVA6RncoAD1yb0gilfA4muJ4nUX1xG0abxuotdrE7MtDwwWcHl/Ry+kkbju D0G4KPHwxfRoWRZZXQgkNSsaioooxeW3WrSWSeNWWDbIQnMXSu0KaNwOeOqXFvayRqyBUHNDGVoi Jdq1jyzGJ7GC3lNw0haMu6lV3AKfyChFPA4spupI73E9wJgoIrHHsalSsYGh8OOOmxpDMr2kogIJ AySMb/VtIzqKZY6J1NUkk+ngRGAIBRSqsjMNh8KYt+l2tvMbiSSMsKqAzCq7RStak+WOidPcOs8U KUlDqApaTiChGR446ZGavLSQq4IA/wDhipFOOLPo7QGWSdYgZQ4VVMjcuhqOFOy9iniM0e6bcGIK eldmlAdf7ccPy1leymAK7WUiSLIkZrqpy/8AXHSJIWZ9y2zRyIwKEPKSuWOnQlZA4Sqspyq7gCgp wpiDrbxyOsm16oV2llURuuYy9OOn2lmk60YRgnaKGUjcdufy08cWM9wJWS2SFiVpRlQn5VPmPHFn H1C0fkSIjRXqyEDky5k7AuZQ50xbRf6fuJp1Z1HMC7dymm4FTSoHGvdLMQANSchiSztRzRD6XkUB lL8RmRppi3v0yEyVYHgw9LD7xhOj20JdObGhkABUqwDOdx8M/uxUyLTxqMBi4CnIGooTigdSTwqM AMQCdKnGUi/eMVBqPHHpbd8M8bq5a17ltDsLGdWYsAGptIAyLL44R9Nyg0+IwWY0VRUk6ADDW3So pJipIWQRc0PTUqvMQ5Z4Fp1ONondwivy+WqV/wDmbpHOv3YqMwdD7Ge+lUsluhkZV1IHAVxNc2yS RrAaOJAK6bstpPDE8CoVES78025FqDPmP/D2DTyyLzahY4smYknP07lOQ88Q36igl3ClNuasV03N 4eOHtbRHmaIkSPsqtRUMB60OXjiSKAMk8IBZXAG4HVloTlXsa0sFN1cIaM6jdGMs6EMK0wbdhyLx BUxtkGHEpmeOHtbJHuZ0JFVWqEj8vzA/dgW+cV8q7niIoDQ5lMzg2I3S3opVFXeq7swG9S5nC2RJ iumrt3DYrEflWrHPsjuJ42lMz8tFSmtC1TUjLLE7IADAVFNpU+quebN3JbqXKKBGkemu1BuP8MST WQcLE2xxINprqOJ90zFeP3fsXdTM5E8cu1WIBZa7TxFdcFWzByIwKRqCNKAZY/ry3ZV8qQmMMvyc siteIx6FC/AUwQVBB1BFRgsIUDEglgoBqvy5jwwHliSRgCoZlDEA6jPCxRII40FFRRQADgAME8iO pqCdi5114ccUAp2NOYIzM1A0m0bjtrSpp54pww0pt4jK2bOUXcSPE0xtZQV8CKjFKZeGKKAo8AKY HPhjlppvUN/EYCRoqIMgqgAU+Axz2tojNl+oUUtlp6qVwEZQVGikVApgqYkIJqRtGZApXAUgFRkA c8GeK0hSZtZFRQxzrrTAaWNXYCgLKCafbgO8aMy6MVBI45HFneSSRi2svWkRQszS1ruYhlyApTz7 GmWNFlbJpAoDH4triskSOf8AiUHX44UmGMlKbfSPTt0plwwsksSPInyuygsOORONtxEky+Eihh+8 YAtbWKEA1GxAufjlgfUQxy0yG9Q2v/MMRi6toplhryxIisFqKZAjFbS1igJrnGiqc/gO7NdXDBYo ULsxFdNMuOeOpXaFXkt4zO2ZqZHO+g+wNibpcjKWhJkjShrsf5q1y1wsMV4RGZYVW3q6p61UbTTI 61xBHa3RX6VY25Cl9olzJB2jPcp+7HUesdTnjna4VOUhZ32OxKj07QF+YaYa6h64ovSxP07SyRu1 ANMgPwxeP1SUxXsDBYLoqWbYWWmYFc9K0wZ4L4cuKsZMjSKakVKVCerhg9G6rdCUbmiVW3s6SL6d u5lptG08cPYdPvBaWsbNy9jOgMamgdioFTn/AG1w3QupTc6JmEYYuzBGpuTYT47sN0/p14LO2iL7 NjyKGRDt5jFQK18Mf0bqt8t2jOkQBMjsrPmpRilM9wrU4Xo3RrsQxqxiBjaRS7jMl3RMgCOGILLr V/HJJGheJmaWSiOaZtyydVxbrWu2JBUcaKMXzodrMgjrmP8AEZUOnkcXHU2o0u7kIc/StFdvwxHc SSvBNGuwugU7l1G6o4Yj6N025VbyGJVeWQMzqoA202oy7mHjgdRnvuXbblqZHaVDvNaFAjEV+A1x N1C2uUt7yErHPNtYKr1UnYNrHOo4YVIL4NDbuOfIWdC5Yg7TSNQdo4Ynt7a7DSNIYUthvZB6QFNA h+OWJpuqzx3V1c3FINzu4XeKt+WtMq0GG/1EvVd0UcjOqrJIpyNDtRlApXKmHvpWjbqER5O31BWk Oamm3iBXw88Sf6ii6g3KFd5DuKEenaItm00rwGHMciwyW5I6hIQ6q8Ko1abkr6sjkMPdWF1EbOM0 u19VX9LFQA6A64v2vbxJIo4jKdqUXahzbdsXIVw1r0m9WCL1NHFGzx0Rcqu+wEkjhj+i9cuVmjLh Szl3dCw9BV9mYao1wLa36glpGFRoYQHYvWo9WyJ9TwriPqF/flOc/o9bPGTkactVoBTyxb3QYNzo 1csoIUkjPbuoaV7KYivIrtneWYRsJhWu4M1aoCcqYeQSodsdwySAsqjN9SVDCh8sXszzJMyIE9IY n1mpNZEGtMUspFET3MkXKXdnG1ar8tMj58MOfBSf3YlmeZJWSN22LvrVmA3epFFM/HBeGVEC3APL PMrulA3DJKZlvGmJLmaaN5CksgiXeG3MQCfUgFPUeODcQSxpsnjPIAkLfqIu75EIz3HjiSa5O08y WXZnmVqAuY/jiE20yWmUUhpvBDVAr6EbMj/f2QPLcRRdMFOUrbt3Ood3yIx0wbq6MEkU+z+nKpIY 79xYv6K0GuJf9SRdUAiBJZdzgbEJ3ERlNtF+GJ+pXhjFxbERkeoKzmm2tFJz8q4uerW/UuXbwSM9 C8ij0er0IEzAGLq3huYlu7QUvZDuAltSjBm9SanjTwwzWs6ixTO8iJzNVYR5EePh+2ZIElAsLTfW MSK2aLyz6VzFWOhwOmWsLXvUTT/LoduRG75iDnThhrG4j+k6ihYG3Lh/lrUAjiAMxi6s44TE1qK1 LK24bihyWtMxi56SIykttu9RdDv2kVooO7F6bstcJWRYoImB3MrnYDVjTLyriYXKfSXNupdoSweq LmdtKZimY4Ykg6hcKbWQstqqgAVZqJ8vl44uLCS3kaWCoUgpR2yoM2yriC4kiZ7m4jEi2qMpYA+L VprhbO7tJLCSWnKMrL6t3y5GhG6uWD0+3ga8uwKsqMAFJ/KfPEt2xMLQirwsQz5/yhTmMTW/Udgq AINi09QqWBzPDsjtenzNFaRBVmcb1KvuYPUKyFgBT8MdOiuTJdG6jH+YjUAVXIlg77sXd9JG1vbW ZNXcg7kAqGAXPMYCC1n5DOUE9F2+kVJpWtMRdRIe4t5mCqYQGIqpapqR4YSFrecRPt3T7RsUsK5+ quXGmI7MwSpFM1IrpqCNl4P40rl2XlxZsUnjVWRhWo9S108sfWv1cW0ZZlEUrNUFTtz9QOvni+v7 y7TqTKFa32Et6mAABq2lTw4Z4bqkV9EhkbfHZNIUBWpHFqAZeOEupEWDqAlCy8klgU9XqXYfhhb5 OsokrqzLasxDVQ0KmpyxOl8gZLcII5xkWJ3VDZ5nLsl6fGksdxDu3iRNo9DbTQ4bpAWX6hDTfs/T JC7z6q+GGtlinuNuQkhQFWPEDcV0xc9R6XvEqxkxqykOrjhtwvUetCQskhjZgu5zU0UlRSmP6yd7 WmwSelavtY0Hp+3B6kjMtsAxJdWVhtND6SK4EPJuURiFEzwkJnxPED7MLf2D0MEqNKAfmjPppl/x EYt73bsM6K7JrtJGY7sVgsZke5fc+VQET78y1P34W6hkjtY7hd6wF3R9PTv2p/HxxHBeQAuCLeVk FAVlpR1JA8sANb88GaEhiMlAjXy4a4twLbmsRbkMMiSXprT7MSSSWf1sMhEc0BJUBCCSxZQ1KEYu buEm2vYmqllt5hIJqoVgAxFDrjqcN5bf5aHYbdpa0J3AMi7v5aYNlewyQFHZkdI2dX3GvAZHhhr0 WDCAu8ruagIGB2FsqVOXHEnTupxPbRB2jMwXdsP5STT5T4/bgWtnb3F6FlH621VUbT82ei8a1wLH qUTWsKyNHJIFNADXa1RqD4+GIYbO3ubtY5FYShdqttK+o1r6MtcNcS2LciGR9gUGnLcEB0Iy4/hi M2tsbi3gUBZCjKzFqFlNRWmLd5I+U7RoWj/lO0enjpi6swu93TdGpNKuhDoK+ZGLiwvbeS2EkleY AzgOPQUZaVBywlr/AKeRyoO0yMgPMYngrrkBTX44hvp7cy/VpGZHBOUsYAdBTIVAwLOKNzcXKoHi IIWPaVY+s0rSlMsXkktvy2uWEgTOretEVqHTTCjlcoiVwTn6zl6s/uxsNoWczEiWpGfL+amlBiOd IucLaUPIBWqoVILZcNMSXE0xjngNDaDeWkJ+WnqpQ8csXF5DZSFI7lC7SgoNtGQbaOSdpbM+eEt/ pyLyCqpajdtfc1d3MINBmcdSvbiy+nj5MqxJuJ5ihPmHpXxpi5sQnKupiGVaswkCrnrUDHWLVLfl vPatGCCfSX9O3PxOeJ7bqELW7ygK0xDMQ0Zb0svDXhhWtbbmqZlG6rUMMZA3sMqCmeLJpLd5qCAU BIX58sgtSR8cWUhTcqzmp8KocvtpjpdzcW8gSWOONY4xUr6akncRwFcRdQgR44pt21ZAA3pYrwJ8 OyEKm8/Ur8R6JM8sC2WDlCaOaPYSSGYlhu9WlTi6tr2MW0jpQyuxXND8hDZVzxJepZfoq8s5k3P+ mXLFSTXadaUw3Tba2m5rxuSXChBQaEqxyOlcS2V/ALafa0BmZmyYHd6qnbQ0FDTEjxWvPg5xZpQX yEYosh4UqoxNZ3UCwMvMg+oZz6aeqp3NtowXBltbYyw7wxuVLqVEQCrJrtABUZEZ4kjvbZUcTOnP RmFBNQq5DMVpQ/vwkVtb/UpzIlkljYiqxgbzUZUHj5dlqJIy9ZjtYGgU7cdMuVt9othGzIKkorrR qEmu2v4Ye6lumiSBirWm5yzVNRtXmAZ1xf3NpZzGNJoX2lW9YTcrbf1GPpDZkYmaWYWccTAi3V5j zA3BEEgqa5Y6zdWto+76ZkaoYIw9WQJkauWtNMXFmFEV5KysACxDqqnStdMz7qCMwcwf2J1SIoIp zuJBJqaSZja3gcPN0e8A6kr1kjYtFtkjorqsjLt+UH9+EgvbaOS6kco8+5JGUutQ4kVRXLL4Y6kB SMspKln+YCQkmh8KjF7PD6EcXBUqQyyVcZ5j82uLprhBAXMqwM7AoGLjICmRp54Q2CIbdiyuy0Mb nlku1MxmcsX6OoRpGnWGpFCeYDtAI1yrri6juYQ55s5QMQy71r+UjFvYWccMU9vsjjncKKsw3jcS rZCuWWuLOO+uPrLiKaANIhBAG4NsoqrWlcdQa/AilZpxE0pGT7xl4V21xeJYWrfVokhkm1hb1bZN q7iMyfDHURlzCEMe6ldtX0yr2dNR461EHMIYKM5W+b0nHS05YEZUhgtFqpcZaZYgisoFitOcnPWM BaKFO3h44GUchaGgGRf6lv31DYt3JbkyXrlFJBUbY6eFc88dBZYQHeIHelFPyISDka46LyY1CmAg MlAdo5ZHDzOEKmoKgg+OWL/cKjYuXnvWmBeXd99ON7RmIbQarQ6t5Hwx1G3sZGn3tHK5LAt6WQfl Gg1xJ1kysb1ZNu0EUX1hApX4Z4gM5kfbclI/VoAWpU0zAwnU7nqP07uhYxEpkRwzxd2NP0YgJK0H zMaagV4cT2W/VVRhb3P6shrUEsdk20Z8DX7cdb/1NdQiUIspWMnM1UyyKPD00FcXlz0q3gtrNVkN 2SQzMir6kG/c1KHH+oKjMKlSDQ0NaDBGw/rXlAykZU9QL/cRiPMLujjWi5VJlH/qcdPEIKie5kMx BObLvArn4DTFs07WMVgNjQzVKyeoDLdTU/mw29xMq2jIWjrQlSVUjcK5EYkJBCm4faTxG1Px7o+t to5yooC6gkDwrhY41CIooqqKAAcBjmXdrFNJTaHdQWA8A2uEu5bdHuIwAjkaBdMtMsCa6t0lkUBQ zDOgO4D78EEVByIODcfSAOa1Cu4U18g2L23gj2Ike5EiFKbSDotPDES9XtiztI7puDxSBailSrAk ZZYEVpEIkAAyqSaCgqxqTgR3sIlAqAalWFfBlIOCLG3SGuRIqWPxZqnCpexc0JUqQWVhXI+pCDjZ aRbdfWxLvQmtNzVPHHJvYubGDUCrKR9qEHAhFnGEXTXdU8d1dx+/CoooqgBR4Adg+pgBINQyFo2q TuOcZXjnhjZxUZiSXcl2oeAZqmmGjlUMjAgg+YphphAZWY1Cyu0irXOiqxph7eUVicbWAJXLyK0I xyLZNkdSaVLGp82JOI+oSQhruE1jlqag026VppihzB1GGuzAwkc7mAkkCk6/KGpgRKgEYyC0ywLy SBjMDuykfafLbupQ4WGJAkSDaqAZADhj6uGAJPuL7gWpuatfTWnHDzW0QSWQUdqsSRWv5icL9ZG2 9PkkjYow/wC3Ba0hCOw2tISWcgcCzEnCyXcPNdKbSWYUoajIEDH092peKobarMmY/wCUjEfTenWj XDMeXF62AiqCN7tuBpnxOLeykkM0kanmSMa1ZiWOvAVoOzk3Kb46httSuY/5SMC3tlKRA1Cli2Z8 2JOOdcK6Tin6kbFSdpqKjQ45NomxK1OZYk+ZapxP1me2+it2VkigMhZzX8zD1fxxHNdxnnRV2yRu 0bUPCqEY5dpHsqAGYkszbdKsxJwsl5GxkQUDo7Rmh4HYRXTHJtEKKfmZmLs3xZiThVvItxU7g6M0 bVH/ABIQeGD9KhDMKM7u0jkDxZyewQXsfNiDBwtSvqXT5SMLbRLSFBtVSS2XxapODNy5FLMWZElk VGJbeaqGprgRRqFjGQXhnj6mVJAxNTGkrJHX/lBy+zC21vGEhUUC68KZ1wb6GDZcEk7gzUqf+Hdt 4+H7ZTqNvazyw9QG2aSIAxRF9qHeoUn5gGrXjj6mZHhnapkeEhS5PFgQwrgXEUTTTr8kkzbtvwAA H7sG42yxbiWaOJgqGvCm00Hww97aK4kdSqqzblQNrt/34mlLzKZiWoGHpYncStVOGktt0s7jaZpa FtvgKAUx/VAsiy7xKEVtqBwd1cs8z54l6vCH+rlLFqtVQZD6qDDXzySQXDgBjGRQlcg1CDi3mjeZ JrchhIrAFmU1DGoPHBvZZJIZWCh+VtAbblU7lOemG+kVmlkFJJpDudh4ZUAHwwvVLeSZZUkeRY6r yxvBG2m2tBXx7IusSl1niKNsQgIzRncrNVST4Ytr64lkU21By1ptYK2/PdXXElrcoJIZRtdD4Y3/ AFU309QeT6a/DfT8MQdOQG1itjuhaICoJFDXcDWvHFlYyySolgnLidCoYjaq+rcp/lxaJcvKv0UY iRkKguop8/pPhgKuQGQxN0+ZiiTAAsuo2kMNfhj03dwB4HYf/wCnFxHK7XgulCSLIAE2gnQD4+OK R3s62u4sYDQ5nwPw8sR9IoYLWIqY+VQMCvxB1rnjO8n3eNEp923DRWSHdJQyyuau9PPw8uyFLhmi eBqpIlK7WpvXPxpj+lIvMgZWWVmpuk5ldxanxphwvUJVs5FIaJRtcn8oJrtIHwx1CyN1JLD1BUQn aFKbCTUa554k6GWd4JWMhlNBJvqCGGVMqDDwXPUZpYdYY1GxUavzbSzAmmG6G5aWJiz81/nWRtHW mm3Cw3PU5ZbFDuWBV20JGZFWZRn5Yt+kWxdEldIIlVeYxVfUa5jFrZH50XdJltO9zuNQCfGn/wCR TnXZKxbgm4Atm2mSg43CRiudWCNlQ04jxwLy4cRwsKoTkWqNwAFNSMGK2lDSAV2sCppUDLcBxONM afvxp+/Gn78afvxp+/GmNP340xpjTGn78aY0xp+/GmNMaY0xpjTGmNMafvxpjTGmNMaY0xpjTGmN MaY0xpjTGmNMadmmNMaY0xpjTGmNMaY07NO3TGmNMadmnbpjTGmNOzTGmNMadmmNMaY0xpjTs0xp jTs0xpjTs0xpjTt17Ne/rjXGuNe/rjXs17mvZrjXGuNca9uuNca41xUe7QxsHbmTLklNAuZYnhni OHqPR1tklNRI6LQAgLuzAqPhjpvTZt/LbYyLGRyyHYrUj/ppixvIV5MwYEKgVVO1hmcvP7uy6sbX lo1qUJLrUMkgBGjfHwxQcgCpFaHIePzYAT6fad1TtOtPTX1eOCTyTrlQ8Tl+bgMEEW5poSDnl5Nj 0C3p5hvwbAI+n8xRv478AAQUFKkg5jy9eAeXB5g1/wDfwdqQCSuVQaUr/wA5wDFHA+mVCK1NP5/t wCEgauoNRty4UfPFOXBsA1zqT/34yjgIp51r/wB2P8OA1PmKCn/PnngfpQkHzOX/APPg7ooT8CRn /wB+By4ISa51JpSn/PgEW8JJ1G45H/ux/gRE0NaHjw/Pj/xoxpXPLXPPf4Yb/LQ7RTbVsznQ19WW GrbRkClAGzOWf5sf+LFSlfnzr4fNgH6aLdtqRv4+GuADaRByKn1+kGh8888AtaRb65jfw/7ssENa JsoCGDiteI1xnaRg5ZcwfbxwaWamg/nAOXhnjOzjrT/5o1wd1kgXx5orlii2iGo15gyJ8sH/ACSE Z0/UFfLLFEskqQc+YKBuFRkcAGyUihqwkGorwPjgBbFdvE80a1A8Ptx6LEHz5g1yGmFD2CkliDtk GQrkdPDDVsQwqdpEgHp+3A22CmpFaygU8eGAFsRtNasZRlT7Mf8Agjj/APFH92F/yNFr6jzBkPuw wNiAB8h5gzHnljKxAbaDtMo1qcq08sUNgAOJ5gP4YANiKZZ8wU/9nALdPzJ05gyFcuGD/kCRwPMH 92M7CgqRnIOHH5cAfQEAnMmQZCvwxX6CuZy5g08dMA/08kUq5Dg010AFTg16cR6Qf8QZt4aHAr08 gZ5cwV8vy4ysCcv5+PhpgFbFsxUbnp+GP/BalMzv/wD04Jj6bxy3SUNK6024J+iNc/SCBoK0qQ3w wP8AIyOcwx3gaH4DFfoGHh6uHn6cZWLn/q/3Y9XT3RvAuCP3A4UtYOHrRgGGR46gZYo1g4IoCQ2X 2ZYp9BIB4lqfhhibCSgrT1Zmn2Yb/ISUXxYVPwyx/wDbpAhNASw/hTyxv/p8hy0rnX/tx/4EoPAf v4jXFRYyEfHP94wKWMhr5jwr/uxT6CQrQH7TWvDhii2EpTi1RX7jgKthKxJoSKUAHHPFDYS1IqKZ 5+GmCV6fIWqQoqPCueWFP0Eu0mjnitRuGVM/DG4dPmCEVDHL92v34qemzBiKhajwrmfjlgD6CWnE /wBhgqtjMaak0ArSuKf0+atRXTShJp54obCamXqHwrjb/TpgpXcGy1zyOP8A7fNXUjLIf30wp/p8 5qCSBTKgJp+7LClunzVNQaUyoK8aa4UfQTUNc8siDpjb9BMcia/ADy88GthNwAApXjXyxt/p81OB yprhC/Tpl3+FGA88f+FKfHLywKWM1DmTTTBr064JBA9IBrU0y0wK9OnBJpTLIeJw9bCb0mgFMyPt GBWwmoSM6V1O04UDp82ZPhoBr+/Ap0+fWhqBoBrlip6fNX4aDUfxxT6CbLjTFR0+fQ1BAGYNCP7s MRYTkrlSmuFA6fOQeOWX34Zf6fPUCumpPAHTC/8A+vmq1K+TEgYFLCY1Phw464D/ANPnoaUFBu1o aj9+K/QzDyIwGFjNQiulMf8A2+enlT+/AJsJs9RTxOP/ALfN8fOoGFZunzAsK7cqg+GK/wBPmPkK YoenzAUGZpSp4YUy9PlWTQgaV8q8PjggdPmJoaacNM8Bj06WpzKjz01A+3Ct9BMK5kHUYzsJjllT WtdNMBR0+WpPEjIeJxlYSnKoz/dmMH/ITZCtcs8Z9PlqNRUf3Y/8CWp4f2GGuLqzkjiShZtaVNBW gOEcaMKj7fdkltreO4hJpMXJ9AyoaDKmLaz6UFuJgweQ8AD6QNR41PwxY3kIV4YQkdyTkF2GoIHh ri2h6cUeGMfrSMCaAtU5VHBceOL6O4UhGEZQqjMSNvGlchgOvysKjKhx5ewy73n7D8O/5dnnjT2n l7fw9x8+34+4Zdv8e3Pvad6nc/H2Pl23BKGRRsJQVzo65ZZ4iNCvpHpOoy092ODy0VN3zbQBX40w VYBlYUYHMEHgcbYkVB/KoAH7uzqYGRCRVOWdVHlw9y07/l7DP2fljLty7an9h5e+Z+43TqxQjZRh qKyKMsQ5U9C5fZ7sf393qAtbp7WUCNztVWV6jjuBywqu29wAGcgDceJoMs/b+fZn7Lx920wVYVB1 B7mfbn38/dNO9n7n/bPGmXx7flLVNKD/AH4zxQY/jjz7p7K9vn23CmRYhWM73yUUdeNGxGo0CgD7 Pdj2eHbffRwxTKEj3Bn2NTb6TWh41wpkUI5A3KDUA0z7fLH4Yz9nTu5+/Z/djw7cuzy7mWB4dzP2 GePL21ezLt/Dv+fHHl3QajbX1D7P7+yp7PP78ZnjlilPaeWPPsrjyxcmdGljGwlFO0n1rTP44jKi gKig92PdvkgdYwscfMBAqw2rt/fXA3OSaZ5AZ9mWPPsr7GuNO959n4d34dyvs/Lsyx593x9lT21e /X23h7XPXAp9tfA9hy9hwx/DGfsJ2VWodgZ1bYVBdRWuIZCpQuisVbIio0Nfdjh7eS6jWVDtZSaU bwwr3NwkasdqkmtTrQUwD9ZHnSmvE08MCSJgyNmrDQjF7HPJKJKxv6HEdfQtANuZwkQLMEAALNVv T4njjMdumNOzTGnZp2/h2V/bGfs8+5l3aH2H93d17fLt8e/l92K5f7vZU7LhS6R7tg3yEhR61OdA cIK1ooz92flEG6cbYEJFdxyBodaYhjuRC0mxTKfSCzsrszqCczlTFmjCJoCG5iOVDUqldm5lzwYL rp625l2kNI4YcNuVeOKLSnlpi9awEG4ogLS1qBtWny5+OGPUuQI89oiruBFPHgc/dfPtz+/s8/dt PYePey7Mvdf7/e/LFcaYz7njilMU4+PZ4Y/h3P7+ybmq7x7k3LHTcRuHjXCcMhl7tHcQTpCYkKIW jEhq2pz04Y+lN0Hvqqq3JQUQiNslHgMWqXVsJo3UFrlgNysDRqLt4a0xZwWjpMQzb5QD6WO3aKnw 18sAgg5cMdTjkcIzrGwL0WoCitCcbkYMp0YEEfu7c/u9hp7HL2nx7csV9hninss/2TQ+55nLu59v nivZlkPDuXJAY12D0GhFXHHwxHu12ivHh7scb9g3fzUz8NcbJo1kXP0sNwzFOODyLaKMniqAfhig y4ZYvluozNPtSkZBIoFFSuzPhnXBFtDygQBQHLLyrimOAxXKuK9/x9n4+yz7PwxSvb+Hf09hl2/j jP2eXtPPt8/YZ9ync8e75Y19l5d7z9jPGzpDuMY3yEhR614qDhFrWigV+Hx92OK/u7PPGQH24vor WSGAhIy8vKLljTIH1AZVwolYNJSjsoIBPiBnTveHtPH2fh7l4e4V9zy9w/h2+XZ5dvw7/h54yxn9 3YSNO75d3Psri45ys0fp3KnzfMMxkdNdMJ8B5+7Hu9Sa7ZbfcIkjLELu9IrmTnwphZYiGRxVSDkQ fCmM/dfx7PPs8uzP7vZUPsMu9Q+7V7fj3ssV9r548sUrn2a92lR3cu38Ma4zOXZ49nn7DPsuHqwo Yz6NfnU6jTEZGQKgge7Hu9UDpvcCLcsqqy1K/MuZ1FMALQAZADSn7K8sDvZ+4effrjLs8fc8vfPP sy7nh2TxMyxq2wFnbao9anXESbg+1Au4ZA0FK+7Hu9RQsYVjEdHiLK0gKjJyGGnDCqcyAAa6/br2 ZduXsfLuadufb5d7X2fl2eXe19l5Y8vd8veMtO4YlkUyL8ygior4jFe5l3s+3PuzCVHdGKAiOla7 gQcRrQCigUGgp7tNdS/JEu5hlU+QrxOLcXErRx3JMogr6VVo2KrQ4tum2Z2S3eRkBG4AnaNvgeOL SzuLo3dpdMBucDcNEqSSTkxHZ1BpUcrIsVdg3GoXOvhSuOXBvDhSxDoVoAduunfz9jr7TPv/AB7n l3aHv1P342jMjWn9+P4YrTPSvd8vdvLvfHh3suzPGeK97+/vyzWg/VGRcU3KCabgG1zOIxBJNJKz E0VlNSQPmqD6Rx8sDcM+NO7n2ZYpl7K5dq09Hy65uvjiMnIlRX3a2tpLa4uLVWWaRYU3LIRUbHPl rTC3zWtys6KAlrsUMaLsBpuDaGun7sWEs7SRuwj5ZG3ZVXORLGo1ocdOtmaRZUIICLUEO41YsOK9 nUlQuZnWIybgAi7QFABrU1+GMqD2dO5Tj4e0y7f4dmXstO/TsGQP8xOKAAU4DLHnxx5d7Pt0938M Ze55dplncRxrq7GgzyGBPdsE6UgBgSJw/MIbMsRl+XDS28KRSOKMyCmXhincp219jl2TKrrGdyep ztTNwPUcRitfSM/djgdR/wDjjQ0FaFdpFT5DAEirzY68lyCdrEeAIJwLiQ86dRQSENUcPzM3Zfi7 gXagQo6lgzZChajfhhY1XaqgBV8AMh26dzPuUr9nbJOFL8pS2wZEhc+OFn/pU/KI3Ft8eS0qTTdX Ed0qGMSV9Daihpn93f1xBC4ZnnJVNorSlKlvLPAebd6sgqqWJphjDuUoaMrrtYZV0OGmmbaiCpJ8 s8sNHCW3rXJ1K1oaGhORpjlzFi1Qp2IX2ltA23Aunf8ASOhAJLV4ADOuGSBm3rTcrqVOefHsFrVj IWCVCkruPDdpgmJw4GRKkHsQXG/9Su0qhYZU126a4VFMhD/I3LajZVy+IxJbJu5sQq9VIX/uOXbF ayE86f8AwwFYjWmbAUH24lhiJLwmklVZQDWmROR+ztLMaKoJYnIUHE43IwZTxBqP3dsnIYvym2OS rL6v+oCvZUYzw087bI0zY0J/hXDXcMoa3Wu6Q1UDbrXdTTHLgm3SZ0UgrWhplUYe3mm2yx/Muxz5 6hThktZC5j+b0stP+4DvV79fYefssvc8sPPOwSKMbmY+GBcXSOlghpHCSQJNa12t/bTCxoNqKNqg aADuad3Tufh2Zdz44m5wcx7o6rH8x9aimeFpkKZD3Y9z8MdT5Vq91u5StyRmKKM23EedMK5UoWAJ Q6rXge5/HukVpUUrxwWN9dkHIDmnIcRliR0vLreykKObwOe0Hh6s8BvrrsUJIHNPH/eMLI17dllU qAJmpmQa/uxc8q6u53ET7YTISJDT5KeeIYZLO+SSC15LxLG3JYldvjni3L3FzalkO6BWKgBzWm06 Yql9cigoKuxA8828sA/1K6J41fXG5+pXLOSC3qoMuAw0jXk1wjAgRyGoBJBr3Olx20BXmyKxfe7V JkXLbu4YtYSpdI4qqCSR8shLBRlrTM1xcRxD0uhDsK6qiE5Vyz8sWUEjD1S7nSubACgqBnQ1x0ho F/WeQDaCVBXcijcMsszrjqplXfWcoxYs1RVjSrE+PDFlDM7vF9aVCsXHzCOgY1G6m6n9suklAQ8x 2MwJAYbqAEDI0BOCAaEg+rw88dTiW5kjEblXk3F+Z6iujN6dDpi4kaZ+VE2wxMxfcx0JqcqAdhpm fA4u6qQyuKbjupXdkK/DHVIGdzHaxyMiijAFT+X064m6s906G0djGgI9QAFSxUUNK8RjpdtCTFdd R+eRD8q7uXWtDTxx0q2nnkuQxqJd1MiRvVl4iueeOrSuHlW2fZAKCgLO4XcFAIHppniHqsd288s7 bvpXIWMRMd2ZIpwGlMQ2ks/0CvGHl5ZLyh6j00Qfdnni+s2lkKQwtKszjcxRS29G3AkbvPMYF3DK 8r3EghjVzXZt3Esu/dmfDFuWvvrVmKLNEwasVSFY+pRXM5U1xcS29wbeC3ekIFNr60Uig1oKk1xe mQOHWUBgzb1Bp+TywJLS3N1KHUGIEKSp+Y1PhjLor+NOavn5YBORIFfInFzHzWjtenRPuKShDLMQ fSPGhWmAqs6HnlJArkPTM/MBx88dNnhDRPGypVDtIGzRjx0xeNawPeUGw2+4hQAUq+1hTyGHe5sz ZOCAFNCW860Hfy97p7DzxTvtPO4SNMyT/ADUnH1cu+36YmUcJIBlP5q5acKg+QxJMVokKFyq0GSi tB92BPD0qeRDoQyAGla03EGmEvI1MYcsAhILDaSvqp409zndSVIaLMGhH6i5g54Q+Kj3Y48+3PHU 3nlEUx5Y/VKou2g+Q1zrxwGBqrZgjMEHj3Muzzx+PuHniwu1dUjszuauZb1K1AP+nFt1C1lEN5bE AMwqrKG3aeWfxxf9Su7oPeXEbKJVXasaqMjTyphYLm4drjfzre4kUhgeBKnOmeIOodVvFna1WkKR JsFfE4u5ek3i2qXhJkDKXIJzqOANSc8W9nDMVurZ+alweLmm77MhT4YTqPVrlLhoV2wRxJsVSa5m vxx54vr15VdLtiyIoIK1YuQfvxdypfLHaujMTtNQ4GUhyOnliM3UjyTtuZ2kBB9RrShANKeOK4ue eyMZ5C4CVoBn446ldmRR9YjpEB+XdoTli46VKyc+UsVOZQb9pppixCXCwX1gWCuM0YbtysDt3Vxa 31/dpPynVnAqNqpoqAD835sdYM5QRdTJKFakr6mYEggZ58MR9Me8iWxiICyJuEu0H5a+WP6lYPCw 5QjC3G4kMF2Vyr4A1x1AXcsbrfoy82MFWDOST6fD1ZZ4msnuUEYZZbVVGkq6lyRWjYtxdzwcmJgX aJBvYDh6kxcjpc6LBc5h5NYqknJfFcTrcOsjyuGBWtKAedKYa2eR4gSG3xmjVGD/AJu6JP8A9Xyp 4eWAOA0xcSxQ0upQxRi7BRI1WDZeeJLV2Vb2UgtKPUlUZimRpT0tQnFnbdReM2VqQzMhzk2kD1ed MXfUZABDMrLGN1WzZdfsX2fj+waHvGa5kWKMfmY0FfD44N3fuP6ajVgt0NQ2Xzbh8aHCogCqoAVR kABiaCeVEe5jeOJHYDcWG3jTSuIWltLmS4t4jDVacs7iWYha5/NrThi2hm9Mqbw4I/42x+PZ8e5T Tw7muOPcoeOPLsuE3KpcxgFyFX51PHEf/KPdj3b8XEEbiHltEzKGPqQVOdf4YoBQDQe0/j2i2qeZ xoCVGVaM3DGXZ4+fbr2eWFSVwjPkgOrHyxzJnCLpVvvwXhcOoJFVNRUYLuwVFzJOgxsilR2/lUgn G2WVEalaMaGmmmOczAR03b65U8a4IglSQrTdsYGldNOwwc1ecDQx1G7SumPHyx54VZZUjZ67Q7BS aa0rjlC4j35im4flpXP/AKhhkR1ZkydQQSvxHasbOqu3yqSATnwGGRHVmT5lBBI+I+zuVBqD4dn8 MExOsgB1Ug/w7m92CLxZjQfvxvqNtKg1yp41wOXIrkioCsDl9mChlQMvzKWAI+OCI3ViNaEH+Htv Dvefunh2+Hcrh7idtsaa8ST4AcScDqF6ji1XK2t3NFJGrsFP9hgIoCgaAZAYV5QZJZDSKFM2c8af CuF6r1BGe7PqRZaHlA5hdoJGVfs+OKdle/n26dmXenFwrPFWPcq/N86+OEAFAAMvdjih7nVFsLRb kqsJmJcK1dopTLPwphTIu2QgF1BqAaZiuNe749rBDRiDtOtDwwB9fGDlU8keNT+bBKX0VaCg5OVR r+bjgf56IEa0h/8A1YP+fiIJyrBnT/vGPTeQ76HLlECtGA9W74Yls/pa3zEnl7mb5st2bZ5Z1xFH HdwkoqqEaJjSn8z7qnwxndW9fHlNmfP14oLuBjnm0Rr83kw4YH+agrx/RP2/nwfrJ4ZY6ZBIyrV+ O7TudPWJpHM8gqZJJHAbmJT8wyqc8WdlcU+nVKiMk7WYgtUjLiKYmtIE2QzKWILekErzDtUekZ4s bUfJcTgPRipyIUfLSo9WOky2qLG0soRqVpSoUelePqpjqdxeATMJGjVqsdqlmOVTkRiysXL8qS5d FXc5ah2AEsDX8+mOlx2acpZwUcLkhqSNBxzwdvzU9NdK46isBhS4gdnd5A7oJGZlPLWoy3VxdO7K YOYQ4cs0m+mW0k0259i8+JZNny7hWlfDF+88W4CeibyWIWmgJPljqkUcEataRswkAO5yKbQ2fl4Y PVoEjht7eSsi0q0irk4oxOQJ8a46etnGPrepA7QdI89gOufq+Ix02HqLVdGWjRVCOJHGoFNCKY63 JJCqiwb1FKh5PUyLUkkVNPDEfVREs9vNSlsi1cBjkQFz/ecQW8IS158Yk+omIAQ8QVPhxyx1KH9N ntYjWZSfUvrDkFaZ5VXEU4VGjkk5cPMJLltx5m7MCgAyzxEl9LHcR3silQjAtCHFNuXn4+eLl7CI G2tNxAp/igMQNeJC5YvJGrRpFNGNaMQSwx9TLHJIoYKREu5s+PwxQ2V2DQGnL8c/HAYaEVH24a8F 1NsLoDbggR7TTdoK/lrni0eNmXmiFWYHa1Chb99MdMu4d4lDostGyfJW9eXl4YvjfwvPAyjJKttY BTWgpw44lmsreS3KgI/MBXdXPKpNdO/n7by73n2aV7PAexp3vDD3Nw+2KMVJ4nyHiTwweoXu5LGo +lgBADqtDubKuZ+8eWAqgKoyAGQ/diiDm3kmUMA1qagMR/LUY/qfU2ElyQDFHwhqM6fD+2uNnMTd WlNwrX78ehgwHEEH+HsNfYeGM+24bMfIMtc2GI/+UefD3aC06e0kTXDFZLiJQ2wU/MW0xbQXF/cX guAAYmVSCa7T6mbcMWNrFcTWslxIQskNKGm0HdVhpWuC0XXjcrG6khG3blGoYbsq9nVGvJtjSCIV Kmg2op2jbu4NxAwYbSbmSBd5Xay+mtPzAYr4+2MwQc0jbvp6qeFfY2F3E6LFZsHdWObetWoMvBcW 3U7AoZbf50cZNnTL/pY4n6zdmOG5MZjgiXNVy2gyEjTEUnNjN5bTMyTBSscgXL01HylgDxBpizu7 9Ehis/Vy1ruZtcqjiVGL82SR3MV4zPHuyZDX01y8G/dizCSRr1C1madmIJQ1/KP+0Ygv+oxxww2i /pRKSzczPOpHn+7svr2R1dbtiUAr6RvZsx8CMXik25SQNKkjEmklPTXIekAZ4hnuDukfdnSgIDEK ftHZdJcFSJZN6FTXLPXTHVLpivKvo2SIhjuBIy3ZZYuOlNtW4mDBPUSo3BciwAPDHSZrfat701Du jZiVJqHGgz0ppxxZdQurdLeC2IPLD1elamtRma460JigHUW327qa0ZXZ035fDEXS4o44nt6KLtSf Ui0oBuXb9uEvbiJb+25aooYncrKoFWAUim6p+3HUuYEjF9E6wrG1URm3ZNlWgrllhenyCFTA3Ngl 3k1Zj6kYbeA0OLcf022tkhKmeQhm3UNdyV20+Xz1xdrawrcR3bloSWIWM7jRmyP5T+7Fyt6EEk0n MGw1GmeOVa3BtZdwPNC7shqKZa4r/XJBlQfpjL9+AGO4gAEnKpHHLDWtvTml0YEmgG1q4hsUos0I jKqTRaqu0ior44sba6tlgitJFkuHLE7yvp9NVGRp44uuoOFFrMhVaGrH5KAj7D3648+54ew8vY+P d/H2OR7hluJFjjBALMaCpNBrhbm+IXpcR320ClWEh8X2+WAqgBQKADQAYaOIpJesP0YCaEk5Anyw /VuqtzupTaDIrCP5VpljPIDF1JNcpDTfJCNyHfIGaispNQDXF0GK05wKhWDLTaBwJ8PY+fc8R2+P cuEDIhJjG6QhVHrXUnEYpSijLwy8vdltZ5OXJMBy6jI19OuLa+jaO5NStZFbmVJAU/MeBoDwxCt3 KqS+nlox1BP2a4tD0qONHkJXPeSCCtD82hrTPLA3EE0zI0rjqSSIlFWEqaVZgV41y8cVAA+AAwfY Zjtz7DI5oq5lvDHJM683Xb6tBrmAcLLGwZHFVYZ1GPHt8+2uBuYAnIAmlTjcxCr4k0GGA2yIaqwq GB4FTjgiIPgoA/gMeh1f/lIP8Met1Wum4gY3EgLSu7hTxxRHDEZkKQcfjjbuG6tNtRX7sGORQ6Nk ysKg+RGKDLywNzBanIMaVP24qXXyNRigIJGoHaKmhOgOCAQSNRXMdmXcz0xl+7s/Ds1GWMjjIg4z yxke2n8PZ+fsM/Y+Hcy9l9KkbTuv+LtIG0amhbWg1xH1K7Vvpk3CG2elPDd6Dp8dfhTACgAAUAGg HhiNAjT3MxokEeb04t9mP6ne7nv5VBYOSeWxqWAzI408hkMEnIDicP061jkeMrSa4X0oqsODGlfs wpaJt6jVXZakZgnPhiRLRCiyOXYEk5+Xfz+zvV7vgPPHliYTqzxlkDKnzfOKYQaZae7ATCksYPKl FNyk+FcRzXsz3kkVNm/ICh3DxJofPA5o2zx15U6/Oh1yr554S4upXvZoT+k0ue0D5RnXTXs6oOnP DGVEPMMylq/p+mm2mFEp3SBQHIyBamZHbXvMUpvodtdK8K+WDlaKa1Hz6eBwCgtSa/LV9DlUnywA i2oNDUkuQDw4YzW08xV8XElwtuYljq5QvWopoDir25N6GX1ncE5YzJajeo5V0xDJbJbNAY1MQLPV lIBzJBwpWK2IJqQSarmPwrhjybfjtUu3j47fDAPJtiTkVLsKeJrQ4cXqRLHT0ctmY189wHb+GOlr PcNdJJICm4bWUiRSVAQhT93DFn0qaptBGZHRXI3MQxG4KwOW3LE/TLfcLeaIOEZmajAB6rUmmpxB aoAUvZRFIakek04KRXXHSRYKw+pPKkTc7Jt3Imlf+PHU7i9LDawjiCOyiMjdxqNKD+xxZdKkYost yIt6Od2z9M0zOlZMuGWLA2m5YboCOZSzNuJOypz+3DMi7nAO1dKngK4vZY7dZLmCVnaNpmVUfdtK g1ocXCkb4A5MkruzOHpkihuHn2RvdBy0VQm12SlTn8pGuL76gOyxy8tP1HBAAoa+ryx1YRw7Ht0d y7yM3MKngp+UfAY+uisl5MLbZ6tur5LShy8cWcqW5a5vQ3LhroVOzhXVtMdLi6jAbW6DqQitVGVj UVFTn446s7IyC2LNI7SGQuN7gbVbTC30ljtsJG2I24b61p458eGLe06dbGeSdObveqRhMvzGgrnj qEP04+qto23CN6AgFkdg5/k8vsxz7mJ5IQ5S2keTdJK5JqprXaFpqcWtv1K0W3W8P6Tq1RTz1zzG Joek2f1MNpXnyOdoan8v3edcXUkhJbmitTX8tfsx9Rdvy4iwSoVm9R0FFBPDBH1Ryzzjk/8AcwGG YIqD5HFxfzXVyq7i4jR1FXdqhV3DzwZ25q3F/IqgF/XElCwIPmAfvx0/qNtJNLPIyxyqX9LggHQ5 YvYuqyyRW4oRIHYDcNhVQqA+eJpumTPPokrSFjoKgDeBwOKcfDua93x7fL2+fd8PZfhhrm5air8q im5j4CuB1CKCTbcyMViJAZFJDBm3cKnCwA7mObseLU4UpkOGBDD+vfzemCBPUanIFgOH8cC9u5Gu OoOp3uxqF3ahch/bTBeRgqKKszZAAeOGtLItF09arc3AyZj/ACpWuRHlhYYVCIugH8e3L3HTsnNW oWjB203ULitK4Svh7se5ljqrw2891I/JEixIpCbUAGe7jXCuVKbgCUYUYVzofMd6uM+55dmWGilU PG4oytmCPPHqtIjx+Ua02/wwkMKBIowFRRoAOA9h0u6gQukDfqmmQXepzP34tetwIZRCNksYVnel GX07AeD+GLrrs8RirFy7aBgwOQAzDBT+XPLEM8USLc2NyTLGN9Bt1UblBY+NMWNwYGt7ezPMcyB1 LE7WoNyrxUY6gn07XEN05kg2q8gzrQMQrfzUxZ3MUYku7e4M8kRLH0HbQUFT+UaYtbtoGhtrMEuJ NytvIqtNyr44FMdUmkQqJ5GaF2GWbu344voHtjJLuMquK7CaCg+XT+1MRXZUKZATRSSBQlciwB/d j+/F4s8ZQyzF1qrLUEcNwGOsXboaTxSLAxVqGvntz+yuJ7OWNkn3MVWjBjmp0C1zGOk3kMVXsKiW GjVb17hQBa0OeuOm3yW7Ja275MQ9SK+ok7KCh/hjrcYBjNw36e5SoNJTJqQAcqaYt+mW1rW7hIQy SRuU2qaAiq8V1xDHfl5OnrEFaOLeFrt1IQUoWFKV4jHVAITCbi3ZLeIKwC7gxVd7LTRhxwvTuS8c llKZwzKwEisXDKopWo1yxaiK2uS8NHdp5pNqEFa03KfDF7ZSw84XMha0+ajNQlRkpyIpWmmeLpbp DGzyBgKMvDP5lXQ45VnyuaWFeeu9NudcqHPHy2BXaKfpqcx/0DXChtaCvhjp1okZktFcPcZGmZpm 1KZKDx44MVuKyxMJEXSu0FT8cjpjp9lFCUWCRWumNaJtFDTyy4/di+ubiDmQSoQjuu5QfR/MKVyO NkESxL4IoUfu7PAcPdsu9+HZn26+w5szAuco49yqznwG4gY/qfXFWq/+LZijLGPFjx/tXhTywLPp ypcdSlySMsoCaZsCR44+tvKTdTkq0kuoQtWoT79cGWZxGg1ZjQZ4ZWbldJViKKVLzMhp6iCRSv8A bwENvGsUY0VRQV9p4dzLvyouRd41rUKB6xxagGF+Hux7PDt6pGUVVQwkOK1bclatnT4e6V75U6Go P24WOJAkSCiqooAO+8MgqkgKsASMj5jCRRgKkYCqBkAAKDv559zy7BUCozHl2fHuefsqdmfdp75v lq7t/hxJ8zHywOrdRWT6gtWGGWlI1HyjbVgPEYMUtzGki/MjMARlXTEdr01Td3E9ArREMiAkAkmv hniSQsZrmZi7yvm3qpVQST4Yae4bZGup11yyAwt5PzY7Ov6Vu/p3AZFjsY6+f2eOFjiUIi5Ko0AH DvV/d7LPuV7jNOrMiyRmiKGau4DKpHjhSNKe7Hu9VRZpLZ4zCS0RpuBXj92FUtuIABc6kjifZ5+y zPdp7fL2GXuPj7z59muMsefbyUJe9mFIIVzapyDEeFcG+6ixmunzRWoREOAGWv8ADBJNBxx1ZopY TKGiWAz05eQowX44ulQIDFbRj9P5KsQX204VxzbhwgOQHFj4AY/qF+dtqSfp7WnpKflZt2Mvu9xz +/v5YnYkqN0ea0qPWvjha60z92Pd6r9JAZXLR8wUUAbVyO4yCtfhhWkXY5A3JlkfDKvd8+7n7bL3 n4d+vvmfZn3cuyncFtYhLjqEnyQlgKV4tng3t8/1HUZCWaT8qV1C4zNMN0/om2RqAzXSuKRqTQgU 0Pn92KTRfUOw/UkYmrMc60Bw8lpAkd1MtFiD7TJQgfmJyFcDq3VUrdEEQwmlIkruUGmpHb5ey8vD 2fjjPGWJUWgJeKhYgfnX+agwKeA92Vo4jPNIdscYIWv254it+p2a2wmICOsm/M+RUVpx8MLy4jPc SECOIHaDnSpah8cGx6jai0lKq0ZV+YpDaA5LTs6mjIqRqISsgrV6rU1OmX7Bp3tfcPP2Wfss/dvo bdJJrt6ACNQQhfSpJpX/ANTliScs0txKWLyPrRiDTjgkmgGpOHs7NZY7Ou2W6AFHFNBn8pw7wwlk UjeB87scgScbzbTAaZgZH7/HH9Qutzzud6BzURj+UDSncqNeFfafj2a9nl3cu2TnKzRh03KnzH1C g1GBTwHn7sJpoEmlhFYi6hipGeXhnixPWbb6OKI7gBRiFrmwbw3AVxYLsrGBEeZQeqrMcidRjppA 2SZBZaZmkiHI/wDD5+PZ1WO7i3rEYiCGKbiyDXaRXBktoyjMNp9TsKDyYnsp7vn3NOymM/cWCHa3 AkVAPwyxn2+P7KbpfSYzNeAfqSCmyH41BFcbZXM1w/qllbUsczTyqcPcTuEiiBZ2PADHMBlsumAU QekNKa/NTPw+GEt4RtjjFAPxPxxJ03pytPdnM7RkhjYVHqpniG2W3lWKM71qsdQX2k8BxriISDa4 RQy60IHbp7Lz9vKyk13xUI1+cYFcjQVA092g6hYyMXt6b7cNRWCneppuUHjiBuoR/S29uSdnpO/c fVo7EVUUxa31hQPZ7aRACrbDuXVlHli26j1GP6aG3CkW5zJZTu13H82vZ1RbKZI93LZmmRpKb10W jDC8yheg3ECgJ40HsRXXjT3XLvfh7TXu6+817aeyr2NcTmiLkBkCzHRRXicPCJIoEmb0zEgcmME5 6/ZU45aHmyP6pZm+aRvE+Xhgz3DhRmEUkAs1K7V3ECpx9T1UGCxVqwWympan5sj+/jwoMLHGBHDG KKNAAMGw6OdsQymvQQVAP8lD/v8A445cQqxNXc/Mx/3e559mvsXFQKyRjMgfm8Tj0KB8Pdj21xrj qAupIoEpHyyW2M9FDMW3HPb5YDxtuRhVWGYIPta+4U9vT9oF3IVVFWJyAA44ksYonFijfqTkALJt ORTPxH/pjnyNzoY68uNs91Rlvrrt4YQsjSyynbDCnzMfwGIurdURzOADHbuarH5bakef8cPPMdsU almOpy8BxxsVZbeyDAlmABl26qRWtMLBCuxFFAo/j9vdpjT2dOz8cZ9vj364k54cxl0BEfzVLAKe HHA+A92Pbn2dVS7ijnMRiKl1B+ZPA14ZYCIoVVACgZAAe5/39zXu/wB3tvPu/jjXvZ6d2vufljL2 jXNwwVFGQrmxpko8zwxHM2+06WufLr6rgGmo8OGvwwsEc0MQT9NUDKKbfy68MLb2RF1eTHZEkdGC k8Wz89MC/wCozG4viOJBSOo0XL+378CSY5udsaD5nbwHDC3XUDyrZaGK0GYrnUv9mAFAAGQA7/Hv fHv59und/HFez+OJCSyjfGCUpWm4eOBxyHuxxTudRFnfS2csZiMgEalSCgpRiTXTCKzb2CgM3iQM z39PY+f7Cy/Ynlinb6irTt/hQF1RnzC5buGeDfdcTaI2pBaA1QLQEHcDnr9pwABQDQDKmL1uVDcX IvJFImk2UirRilCK5nHU2hVCIp9kJUhtqU3UBBNP92OVCVlu5DsjhLKKMQaE6ZVyweodTk51yc0i FNkXEUPGnZ8cUHuH49ufc8fYSIpUEvGfUQgoHB1YgVwFrWgAr4+7HuVxfx3W2EPyzG4DbpPT+bXT CyIdyuAVYcQcx2U7Kae5596nZ4978e/p2Ze45e0y7nhinsRbwo09xICKRgNy2I9G4eeP6hes1xeM BQyZ8v4AEiuCzkKoFSSaCgw1rYJPDbK+2S8AVUYDUDcytQ+QwFa1V2GZdiSxPnQjD9P6Pas1zNm2 zONWGQ3M7AePHBmlP1F0zF2nfWrGuQzp39eyntvx7mnb44rp3HE27lmSMegAtUsAMiV44AGgAHuy PKpeSVtsUY/MaZ1NDQYgg6tYtZrcLWOQHeBmoBbIUHq+IxAY4RcSTvsEe7a2mRFAa55YhWTpbxpK 20sd2RJ1+Xwz7OrK8SkAQHcc61XiD8MUGgyp7v5d7LveWM+5n2U/ZtSaAZknLB6f0qs962roAyxC tGJOlR54LSNzrpyTLO2bEsakA+GeDPdyrElDQH5mIFaKOJwLicyWfTAAY4RSspz9VaZjz+7xxCtl +mVYKigAjaoqRQjPL7cWqyzMkV8u4MoRWCEDQivjgRR5k03udWIGvZn3c+7p2Vxp217mnZp3vPGf Znjy7HYE5SRVpSpG8eNMV8h7st9fqP8AKDcsjMVVAKNU0IGoxHadP3CO1YkyFPSxYZsSSNq5eGLF raMkWpqX2qwqxWmTOpy21OWIk6vdC4tp81fljKhoaMCtDxORwDwOYx1D/N3EJVY2Kwty6EqBqDnk PDD3Bup7hnXYBK24AZfvy/YOff8A4ey1/YdcFmIVRqToPjg2HR6CE1W4uyRtAOqrSv8Af/HGyIbp WA5spyLkfwHlgqjJJdkDl27OqE1yr6iMsDqX+oNskoAENmM44hrn545krKigURSQpYgZKu4gYV3E VtbxuGhQ+osaZkstcqGmWIS08bxRspKVf0qGBIWoOXgMU92oMh7DLvGJaVaWIZsF/NXViBinCgGf u0dvZW6XNswJuEditTltGTpXCQ23TreOIH1U+ZqClSeZniCbpqLMRTmxMzLoQcgHC04Z4t1v+npa 20B3lmYuT4gFWXU0x8MdRHTbaGV2MZkaRiDQINtM8IZQFkKjeBmN1MwO349/TvU9h5+28PcM/dvj 7FVKvWYMFlQBthWldSM6GowLCae5eO6mCysaCtQFUk7jTwp8MLDbII414ca+JPHH9N6cklxcPVWl iUFYjUAmrFRpXOuWDdy7ri8fN55juap8OA0wlsqtLdSj9OJBu8gTmvHzwL2+3SsM44ZDVYz/AMoJ WvwwBoNBTu5e3JAqeAwGf0vShUGoxr204nu/x7392NMN9SGKCSOgQbju3enKq8fPHh7sO71dSFXY IAW4sSn4e95duXsvLx7mnsMveaewpK2+c/JAnztXLTgM8PcdUd4IDuEVqu0EA+n1bgf9+uJZd5Iz d5ZSMhlX+GHt+kEw2g9Mt0woTWlQob7f92BEpoiCryNQFjxY4Np0gFUDbZbw02qM67c64PqMkjZt I9KknM0oBT3XPvfD2Xhjw7HYGjcyMDIGtW0zxU+Xuw7vUhcq0kkfJNBuQJ6Fy3KwruGFjTJUAVRr kMh7v+Pe0+z3HPt8vY09zy7z9P6OBNeMKGQMtI68fiPuGGvbw/VdRertK+ikjReH24M8PToyhOxG 56gM2lB9uBP1AiHp8ZA+mQgiR0PqrQ1+/CJVIIwCIo6hdxArtG46/HAlv1MFgh3QwVUl/NttRmP7 VwsMShI0FAo72mMvcP7u6Tnl4Z4DCoBzoRQ96mKdmvZ5YEYANZoq1IFBuzNWI93GMsU7Na46lHZR xKyiIl5d1H9AoPThebQvQbtvy7uNK9mfcz72XsvPFMU7c8Z9mR9p5e+Z93z7zSSsERBVmY0AHxxL adN321sPS92V+YEaCrKcCOFatQcyU/M5HE/fg9OiV7i5m/T2xLuCsw/MSyj9+LInptzNJaGQrKSo 2mUndkXz8MfRtFIbyadi0NE3IZiCN1JKUz8fux9dfM882scb0Cx08FUkYoO9n3Mva+WM/YZd7M0r 49nhjPG2fcI3ljWqCpqT4EjAHkPdh3eqNdTJAG5Kgu1CxCDx+OAyGqsAQRoQe9T3L8e5/d7TP2X4 +6+WPLu17d91IAxFUjGbt8BhLi+DWlktCtmdrF/Mn+/hpgu7LBBGONFUDDRdLZrawiYcy7I2mQg/ KleH9j4YtYLR2CSBy8mxXZmqu0kmn81PtwLB5vpXlkVfkQsisTT8x1xtB5krf4kzfM58+/59nn7z TvD07sxrw8+5uWobmxbcgc92WumM/dkkuWNXNEjXNmoRWnwriOC4t57YSn0SSrtUitAfHwwj3JJa Q7Y4kzdvgMtMLaOkttM9NizLt3FtAPj2dVW4jWeghKq6AhPQK0JrrgIoCqBQAaAfsDXP9nx2PSGW W/Z/UoKkKoFSDU654+v6sy3XUD8pI9MWWijT7aYeO2K3N4GMaW6Ou7fTLdU+OFvP9QylgPVHYJlG n/NTAiiRd4X9G2Sg+GXAVxHdXrxQbflhIJyroVH8a4hu55o35TlnarF5Bntru8NNe7Tvfh7Dy92p j8e0KoqefFxpo1dT7vFLdKCbfc0bk02VpU+HDjiC16dbJdIgLGR9wC5ipyIoBTjjp0UkUckVEVZG rVXZjuNK/wDCKYsJYbeN5Cy7ppK+kRupH5lrr2dQqph2rEwkjdlaTctPUAaZU8ME8ySQn/5jlv44 r7tXHiO7l73l7DLTj2Zd/wA+zXsWcozb3EYZF3bNwPqYEjIUxLEs14ZLmiM23iWWp+fKmmWGkiQR ZHfK5zpXdmcNY9LSQjR7vaNiqw1BZlof7Uw0gUPOatJcOBuJOZ+Aw9rYo8pjPrnXbyx4irEccNdN umuGNRJISxGXmfM+1y7PPuefdp7Cvc071MeeM8V7IxK7JHz4wxQAnXLGevH3aC1skdopOYZ+Xr6d mwHMZGpwYrXoqgE+twTVwuQJ9Rxa9WsouZcW1DIi/NRTvFM/HyxaSPYvbwWnr3TVWrAhmH3gUyxn r5Y6k8yyFjHEAI1ZyxCBs6ZLwwkoBAkUMA2RowrmOzxxl38vfPHsr+wfDFOzlITc3GW2GL1EmtKV +Ixz+sXywwqQfoAyLtKt+Yglvj+GH6ilybpyDHFGGVjur6gu0D7zwwk9+TbWIO9LYCjNmSu/zA4/ uwiHatfTFCtAznQU+3U4508j2liaGOAUDsPzb/iRUfwxshUIuppqT4k8T71l3NMeOM+749le2h7P LtrxwlDt3TxA0AJoSdAcDKmQy92Hd6s4erFbcMvhSP7seGPHGWMhX4dvl3vLu17349/x7a+xpjy9 rp7ancaSRgqKCWY6ADAg6SnLtFYCW8bPSh9Ir9mGkrzbh6tLO+RzNctaDFxdNaQ3Ze/dOZI6/pwZ tzNTUDwxfz8sUtpgLaNactRmN1Bxy44+j6QBNeMwBeqlIwD6q1OuWDeXjfU3b0JZh6VI/lH9vL9h Zd2uKdyncr2R7c/8xEKVp8x2+I8fdwe7fC4iMfI5ZWRHoZGZRmw8gMLGvyoAq11oBT2Wnc07349u Xezxn3M/Z09rX2nj2rAEee5kFVhiFT5V8KnCT9Ud0jIWloh2KMs921mrnhIiNmR5VvEpJIBA4aa8 cPd3TXFtaIpb6NAqSOtDrRmzoRr92DTp9wWf0K6kmtBmfnpuHHDNZrNY2k9GX1EOw20zO4+NRT+7 HLtkpX5nObNTxPvufe+HZTt1p2cca5duWfb5dkbXBfYk8ZGzia5AgsozxmKGgy92GPDudREFm1wW WLeYyN3yihbewFOGWEdlKFgCUb5lrwNPD3inez7Mv2Fnxxl3GnuJBHEmrt55Y5fTDJbWwza7oFLA 0yTcDn/bLiZZXBkVBzrl6Amnx0BJwbLokbM5HquXG1Fy/wCL+6vlgXN5N9TeAUa4k4VoCBX4anPE 1j0mJpWB2SXAIVVqNUJyJGJIY1YRSSl2Wse4hsia18vuxDBOAsiDNVAFM609JI9vn7Svb4ex8u9T j340Y0DzxKcq5VzGfu47Px7eoNcXEcRkEQKvUH5F20YmnxwHQhlYVDDMEHz7Pw7mXe8Pe/HuV9x8 e55d1pp3CRp8zMaAV8ziaQRQm2AIii5iB92W0lt+eetBhb7rc3Ojb1w2iE8pailT46/jhY/SZjQQ 2ysqs1ch8xFBg3HXHa3tdwMNhGwpQcXI1/j8MLaWSJJIKhbeEoCD82dSMb+sy7ITmtpF6QPJmFcc u3jWNTSu0akALU+JoO3L9j5dnn25d+FU1+pi1IHE8T7uMGJXUuvzICNw01H24q7BATQFiBU/binO Sv8AzD+/s6hHc2qOY1iAdhu3BlHBssqcMLGg2qgCqBwAyGKex0xnincr+1OZcEkn5UXNm+AwyTse n2LHLnBVaULmSp36fZ9+BO96skIYslvUfKPyk7jWnww9p0uOWOFfSbzaAgA/k3Op/dg9QuazXP8A 86U75Gen5A2lf7HFIRJZW7ihd1G5hoabXqPu+/B+nT1t80hzY/hr4e+U9wp25d7PgQfDTtj5+4rz 49oUBvVU0rUjL3dB06SON6neZQSKUypTzx1ATeqeIMrSeo1bfRzUnyy8sWEE6r9OZOZI7McqUU+l c/lY4ihiaZZWoI2kaRQ7VoBWuuAP44vvobZZ8o1kWu00QKa1agz3YZbyzFsoWocSBwTWlMvL2eXt fLvZ/sQySuERQSzMaCgzx9N0aJpa1U3LCkSkA5g+WWBddUl+quhUKGzRATuyrqRU4sIHnRokLC4D EcrQ7dzHLXHT1eS3RXumEv0zJ/g6AlhmPPC2XQ7fcqrtEzDbEgFRp9mFm6nN9XMtNoIG1aGvhn+z /L2duQxUfUxBqAHKp/m88H3YY6myy72LSB1CEbaS6EnL7sWydUgMkkn+DJt3IoDAtnXhlXyx0+Lp 8sbXW6m6Eb/QdP8AD8/u1wB4AY6ibqQRiRItp2k5hRUZVwk0RrHIoZDpkRXHn7PT2Hj259/Lsz9v p2ePe/D2OemPprBRfXdSvKjdRtIH5j8cCfr0oCkhhZxH0LlShP8Ab44S1BVZPljto9obPTLKg88O 0xbp9gDu5ais7qBWmWv7sTunKVIdu4vKqswr8206facJdTSqsUbsuyKjF/GsgPGv3YWKJQiIKKBw A96z71Pdfj217YUWm5rmKlTSlKmvDGdN2VSPH3YYeWCFI5Jf8R1UAtU19R+OBHcxJMgO4K6hgG8c 8cy3to4nAoGRQpp8R2dRDwggrF62z3ekDjl+7ApkAO7+PtKe7j9/ey7mXs/hhXumYBjQKql2+5cI 4rPI+0iGIbnowqCRw+3Aa4Etlb7v8E0V3GVQ206HOn8MF40AJrkvrlkbj54YW6S9Pt23KZWA3MRU ZUYN/D44Dxxme9BCFqGV1YjcCddgxWbfZwvWkejnMj1Ubw/scKQ5DChkalS586k0B44+niYv6tzO dWJAH4fsHL23hjw7umWPLvQ87cVNzFQKK+qppWpGWKjT3Yd3qYsJEjcCLeZVJBGxKBaYQSkNLtG9 lFBupnTy92/DFe5p3svc8+9ljz7N13IFJFRGM3I/5dcSX7LLFDONsbuwDAUDKFU6aHDdQ6lIIXud pUTMNy7QfIGvlgQ9GtnjjO7fd3C7UFMvRrU1x9RfzG9v5ASN1GJ3a7V8MtThGavTrVqkqpBlZSMs 6en+2uBHCCTxds2P2+659tfcvDueeNO959uWPwx5922BqFe6hUkcMyfL3cfb3eozSRSyyMsS7YkL lUCKdx8jhJo67JFDrUUNGFRl774+/D6mdIgTt9Rpnh4+loltbKxR7pyGJApmu0/HFzc3T/VXphdB POR8zrQU3nFvJJZvO80BkkuBJ6UcKSBQMNeFMsW991q4WaSQMIIpn9CKjEGmfq8fDAt7CFLGyoNs 5IY7fAKhy+z7xgMoMswr+q+ZzzyB0/aVO9n3PPs8uzXFqqU/8uHcxYLQVOYrg+7Dtp2dRJjVVKwg SCtWovGvhindy9tXu/Hj7DP7+7l209x5lzKsa0JAJzangOOGSxglt4QxDXThaU/4QxrWnkcS33UX N04YEPJVjmAvy1O45YeHpthLt0WZgqotQMyGZfH8cC5vppbuUsAADTaudaJuC/dTFonPmmjlAPJU mkatVNr0loDhZRGJZlFN75geO1TWmeBTIDgPec/aU7+ff0y79PYWqyFqfUxhSor6vUBXMZHFPD3Y Ykt4pkeaLKSNTVlpTUfbhpJWCIoqzMaADzJwfp5kmpry2DU+7s6ktvO1qyJBudRu31UZEMaCnlhV dzI6gBnOVT49mfcz17c+55e28vcdKdmXsGmmYJGgqzHQYmkLmEw1JR6BmUcUFc64MfSoWit2JVru WqemldyY+o6pdtcyuRnMS9Spr6YxXQ4aPo1sYotBdTAIKU1VSD+Pwx9R1a7kv76m5ImO5RlUKF+U eVThBaR/RWhNHkc0ldTpyhQgZYjS5u5pCu4vQgB3alTofDA5c0q0FDkmemfya+fsRXI+H7Zr2WzR mj/UxU0z18dMZ+7Rp02dLeXd62dd1U8tcXqvcc65QMJaKy1IdQxq2ua4sulPOYonKNJGFJEm99oB K+AVtfjjp89nILVZBseEB35g3KpGppUHj2dTkt1+qdhEjxqH/T2oNSAQanBSa2aJAtRIa0Jr8uaj FfYa/sPPGfsDzpV5lKrEGG5vhU4WzeBLeFaSAGQF2DblFQCP92EfqkiJBGC7LvTc23MIVJGv9tcL H0iFbO1BKtcSFSaDiqCoGmWuBJdTjqfUHNOUGUjdSmYZv4nH+adbCyIpyojukcHxYHT+1MBooQX/ AJ39Tfv0xQZeH7Yp7CnesyBWl5DWngdwPx193GL4i3SEev1q1S55udRwx0+8NsJVJVWmrQx7W1px oGriwhjtlumU7jKSKRiob9wG7svkEBUukZaYaNtUUr9+KY8/2iWYgBRUknTCxwxS3LuQqiNDQniA WpXDC4d7C3eh5YoH260Zlb+7zGGW1R7y5qQQlZmXht3H0jPKmuJb82txbzywLDGpC7l3EHevq/di G7ubWe7mSFYRCVU7nWpLsN2eXlhFu5DBAAB9NGAmnmjt91aYpawIh4vSrHOubHP9o5e2rivcrjTu WYmZlQ3cQBQfm9VMH3bww88MSpNLXmSAepqndmfjjk3Mayxn8rCtD4jBa0gWJmyJGpHhU59nVOY0 sZiEQHLkeMtVeO1tPDCxqTRFCgsdxoBTMnXv696o91p3fP2HOvJBHHoMiSfgoqTgXUk6CFl3RncP WAK+nxOOV0m0YigJuJvQi+NBnXH1HW+ou5koGgDbY2oSVUAAE64eLoVjzguXOYbV3UWjH7PGhwJe udUZd2RtbdstrZU2rr4aHHJ6J04rCQCtxL6d3ma6/fgSo73LhkkVw6qFcVBFGGajww812r0dG9bc seosG0i8f2Pp38vcfHv0x59y0IYqzXkKigDak/zYPvA7eqN0xoN5WHmrMGqPQKU2/DCiXbzdo37d N3GleHvWXfp38+7nhikqzzrksEZBdmrSn34luJwI0gAAjd0/SST1UbPIkYaTqiCWNYg1tCzLVmkz BVXYcMMyww9KtEBP1ErKx2UO2ijIHyxQhusXj5tMW2IBJpqa5BsBJJk6fAopyoFALH+Y7W1+37MK 6QiSQENzJCWbcPzZ5a4/Dv097r+xq9vljLFkiiv+chJbL0gE554PvA7epARBCwiLSVBL0Wgy1y7P j7LXP22mPPueftK4MszhI1zZmNAOGFhsrea4LigkRCFDHSofb+GFfrF+1skulrFUMR/L+mzbj48M MvRulzNStLh1XPzrI4J+GuOoyTQ3HLuhEbj9Mfp8tqLmXWny54e+t4WL8tYhLJGBEgWhqv6pqeGW BL1GeS6caqSVjp4banAihVY1JJCjKvE/tnLv5Y07umfc8u3Pts+cWCi7iKhBUsw3FV+3B94HZ546 gLqEycpI+W25qDco3DIimAijaqgBR4AZe+ePtFW5cmRhuEaCrbf5s6ADLCuZw5Zd6IgLMwOg8Afj hmhjWxhZapc3LCp9JPpjFTX78LDH9T1uYZuzERQLnWoNAafHLAF/1OOwiBIFtaULZZ7armDn40wn 0PTJrkZf5m4oP+Kq7qrhmu7swqxygh27afymq1+OuOWLpCGAEgc1UqGrSgXzxybl1eTcWJXJaUAy FBTTsqc/DvU/bOfd8faWR3FAb2EEgVyqa4PvAxXs6mbK+W2ZuUXUJvNNgUV3inDhhQ7bpAAGbSpG p7K+6V7a9uXfyxr2D6m4jiroHYA/diW26YyyySKU54mjjVailVq4aorlljfdSiaVwQWeWNiMwiE7 n0phZWurawWUAiRmRpCimh2a7daZEYM1rYydQc0IuLiRCtfEKjUIrXXCxXl2lvDmGgtE2DZkAu4+ WFMUILqd29iWJahGdfjin7Br77U+xr2+fe/Htz7LIeF5CxNK0puzwfeGuIQTIpUAAgHNhX5gRpiK YURZNrbGkTdQ58IcssIJQBJtAkoa50zoaLjqMZVYacrdK8g9Z2k6Nnx8ThlhlSVl+YKwYj40OMve K8cU7+ZpitKY2zTKshBZYyfUwGtFGeGit7aeWm31hduv/C2emlcUU3cMBJDssccSKPlpvL1rXzwC 0s11LLUOIEL11Aq5YDEzwdNuUYBiJLjbULT8ke9anwyxJa/S3E5MiuJAqiQqAAqg13UriK7FuGkf dUy5mu7+UlhWq42qAoGgGX+yf8O7Z/VScqMXcZBABzFda+WCK1p7wLb6hbYs6kFjQPtPyag5+WB1 O3mla4R0DsZDmWIAK6/m4ccWty4o8sas1fHQ/fjqokjDNHyCC3qGcfCumKxxqhPFQB/DGXs8h2Z+ 4U4YLSuqKNSxCj7zi5gguh9YqHYsdWIbhmARxxFLLPKPWpVpGrQnhoBxyI0x9P8AVS0jNKqaM2pB 9K1PDjgyGOYtnteSQRggkFt1RUlqfjnhv8wIJCao0aqzL6afPRW4njjmsGmmruMshJauX92OWiKq /wAqig+4dleP7dy94zGnaB2WZXjeRAigO4Hdlnlio1OvvAtpGMbq26OQCtDSmY8MJbdR6kJLKMg8 tFoWAyochTI64SCFdsUShUXwUCgx1VY7qa2ciIloSV/JT1VH3fbhULFioA3NqacT7Gvscu9rjXEc VxOkbzf4e46501+OK7hTStccmS7jD03ZGo+9a4ZLSAzsDQMzqik5Z5bjTBS3ZbZaV2Q0Z6NlSp3H j5YWZ4yWLE/ruDT4h6n92JXDqs/KpEgzqwByLVyzp5YNmIF5DOJSrMjtv+VqVIoCKYgRoRFKqAOB QkEeLDXv+f8AsJ497PGfs60+/tsFpl9ZEd1aUpuwPeB29RMkbgvyg0iAvuZV4jhkwwGAIDCorrn2 ae08u3y7PHH49m5jRRxJpgmeYCg3ekFzQmgyWuOZHDcTVFRtjIGtNXoMMIrGdI2IDSChZVJ9WVKa eBxFNP02c82oiLyZmpBqADlrgx2ltcxwhiTzJAq7gcxQnXbkP34UmIwFTWm8y1oOO7AKwbmpRiXa h86VywI7aFIUGgRQP4f7Mefd+HfsjPup9XFtC6bqmlcD3gdvWH9Q2NGG3V/KpFf3ex8u749oq6gH QkilNcbJr2FX0K7wT+7HpnLkglSiMc8wBpxphL83JTaTsi3UFVy+TSlcFUijBShMgoxav/B5VwyL PMcqbYlCEkMtMkFftGuHj/zRUj1KzMgoa0Y83LUYKXEzR1OR5pbaBx2hcz9uELTylht3UK508yta YkitAY5ZNoMjOxyBG48RUjywN1w/orsrKx21HnHgW8NaEl23Hd6mzbPLj/snTuZdzyxl2eGMsZd+ zKkAm7iFSA3833YHvA7MxjqQu67l2bERmQ0Zc92QqcsJEtdqAKKmpoMsz7HWhy188hgmWZEoQDuY D+PxwV+sQnjtqR+4YeHp93uhJUxRxkqxCoX/AJa51/hgxyvDM6egLKWRwUyO4itScIicqJHGTICe B0LA+GP8eRzSjoz8sVrT+QVA8jhVlUNtyUu4IArkB8x2jCCW4jRirJLQE5GvGmee3DvNdjagGwIh rQD1VLNqcPbyxqea8VJGUhwEb8p8c6HCvcWirchjVmXhqKA8M8BIo1jUCgCgAUHDL2nn7v4efdoN ffxTX2lferOgrS8g/icD3gY88E+Ari8uTay7rsrWhDUMSkGu7aAPtOBcIpRSxUqSK1U0OmAZJFXd ULUjPjljcLiKhzqHX+/Co0oLMAw21b01OfpB8MMyl3VRUlUY6eGWEmjguooUBViWESMXK7MqPurX XAt4reW6aEhd63BdH3KW0K+fHAROnrufLmc5dq1Gp9NcvhghpAgIGSyAMCNassJ18sc25upy2XoD 1UUYOKVA44BIKtu3FhSpoAKGvwwFFsBQgkqSMwNcjhJrCJIBH8jrIVf5dmfob9xxLNJEg5gAWj8w Ch3VUMikVrnihHwwNzBamgqaVPljz7+fsaqajx/9O3Xtp2V9h/avuNP2Z4Y8O4K8dOw9uvs7PmFl UXcJBUVzFaA4BGnvCyxoJJpGKRg6A0+Y/DEF5fMJra4ba0dKMhIqBoM+PHHMSuyRNwp81GFcvPE1 rJGsU0iU9fM5gORLVJ9JP9ssbryRIpTXcjTMpoaZmr+IwJI5IDIujNJXUU/M2IGszazSCdVKijbU f53AU8PHG76q3FKCu9OJ0+/FTeQDQf4i8ftwZxdK08I/QjjlHqZiK1CZnLPEF39cVmKIzRvOpFSK 0ZftxuF5BTx5i/Dxx/5cIp/9Rf78XaXE8EawTtFEd4G9APmzOenDH/lQ60/xF18NfLAIuoaEVH6i 6ffi9snliWG2EfKk3U3lhV/VWhpiv1UP/wC4vD7cbvqoqeO9fh446aEnQqLyMybXWgUVPq1yrggX ERI1G9f78bvqYqeO9f78NdQyRzMCoVA4z3EA6eGP/IjrQMRvXKvxwV+ojqMyN68ftwSZ46LXd61y p9uJZJCkPLlZFUsKlBSjGvjivPjpSpO9dPvxUTRn/rHH7cWlspSSO5JVpAw9BrtHlrivNSnjuH9+ NwmjIGp3jh9uIHiMcvNnSF/WAEV61Y08KYrzo6UrXetKffipkT/uGKCVCRwDA/jgF5Nu2SQNzGFR 6vswaSoaU/MOOBV1z0qwxeRSKsS2spiWQOCr+oqPtwXkmRVGrFgBiiyoT4Bhi1KBZFuZ0gJ3fIHr 6sq+GMnU6jUcMZMp+0Ylu41WZ49oEe4LuLMBrn44Qs6gvSg3DVtBjNhlrngvzUKj824UFMsXibVQ Wk7QBg1d+382YFMEJIrFdaHzK/xU4zdRw1GOk0kK7pmFARRgF3Z43FxTxqKYqWAFaZka4+qKiX1q hXdtpvOtaHSmNzOoHE1FP349TAfEjHzD7xiaUR8oQzPDQmpO2mZ8K1x8wwAWFToK4u7NVp9IUBeo O4uCdPKmMjjXFvQCQ3EywqAwBG6tW41pTFajBXetVoWFRlXSuDnp9uEZ5NxEjqC1AaFsv49t1GE5 YtZTDuLA7yOIxUGuNRTFohTmfVyiEEGgUkjM49TBeJqaZDsluyhl5e39NdTuYIP3nCS6b1DU8Kiu KbhXwr44NXXIhTmMidAcXcQQxm0lMLV/NTiMEbgSMiKjXGWeLlDJ6BbIAmgrVT+OKkgDx7BcSAuC yoEGTEseFcA110xrTsuGRCgt5ngJJruKUqRjPFKipzHwxdWSo0b2gQuz0oeZXSh8sAFhUiozzIGX ZA5jMonmWH08N3HFK5jUY8PDF1KrFGRQQwAJB3L44iJfcdikknPMa4z07Lu3VCps5OUxJ+Y0rUdl cS9MCnfFEsxky2lWIFP348fDFf4YlvipkWKlVXjVguv24SVfldQwB8xXAodcfwxdwRqyPZymJ91P URxH3Yz7L2Pmbo1hjIjoKAkA1rxxQMD8MZYhkeMyiaVYQFIBBfQ5/DGfZLdSeoRLuKAipBIUfvOE m27RIoYBtRuFaGnZtDCulK8Ri7t0Qo1lJynr+b/iHll2ZZ4uOmhSHtkR2k4HeK0H39tmQ5Rnu4lD bQ2tf5sCnvFkXcIlZVO4MRUhTqgP8uLZNyqolBBJPBH0oDwxaxJmqRIAa/8ACMNcTWsckrfM7AGu g4/DFPo4SPAotMssNWxh9QofQo/hgE2MBpp+muNosYQK1yRda7v44DfQQVH/ANNcV+ggr/8A21/u xX6KHWuSgZ6cMZWEA1HyLxwR9BBQ5kbFppTTBZenwAkUPoXTG02EBHmgPGvHHp6fAPggGuP/AAIf +wYI+ghAOWSga64DCwiG2ooFA18cACyjUbgxAAz28PhgA2UYC5igp/A4CiyjNBSrDcSPOuKCyiGY OQpQjQihwG+ijyFABUL91fPAZrCIkeX+/BU2UYB8KjT4HFDZR04a5HyzwVFqDXWrNnWv/F545n0i 6U27m25mulcIv0i0QgjM50rrn54INjHQ+Fa/xwK2SALXIEitfHPDFbJFLChoW/dnin0KeNasT/7W P/BSvA1NR9tcBvo13CgrVswOB9X24dXtuYrsWozMQtaZD1eWNhs120AyZuGn5sZWSA1rUFta1/mw 1LMUbVdzbfu3YP8AlBQ8Nz0/9rFPpAMqZO4OlP5sf+LUZZb3yC6D5tMUFtQGuW9uJz/NhttsRvFD +o/w/mwQbckkkhi7bhnlnu4YQ/TZpT87500r6sBvpaEeDvn8fVgAQsAG3EcxvVrkc9Ac8Ei3NWNS eY/jX+bAYQsEAIKB2oSTWutcsU5DZ515j/34VvpjVdCZH8KfzYFbdsiCP1H4f9WCpgY18ZH8a1+b DA27HcakmR//AHuGKGF6GlRzXzpw+bH+C/j/AIr+FP5sFjG5XgnMbaOB44IjjkSp3EiRtcvPywG2 SU4jmNn9xwG5cjMOJkfz8/PHNCyAeo7RI4O4nI1B4CuAFEwANT+q+Y+O6uAUaZDuVqc1iKA1K5nj hS5lJViQS50NKr+7FAstPAzSEU/7sMwSWrCn+K2Q+/BUGdSRQsJmr8dcBlWVKEGiysB6SD+GC1Jh UGo50mp4/NXBUGcVpX9d86HzOPSsqDP0rKwFSKfjjcjTKP5RK1Nd2Go043Aj/FY0JNSRU/ZhS5nY rQrWVsjxI+ONjCamtea1cxTxwF3zihBJEz508c+OMzPtIoV5rEV8cycAbp9ijaF5rUA/scehplbV W5hJU+OdcBX5rmoZmMjeorxIwwVpxv1Ilbwp/auDuMzM2ZbmEHSn5aYb9SfawACiVhQAUpgN+sDq TzWqeOuuuKCS4IzoDKSADlQYCNLcuw/OZmBr40GWCpknJpQFpSwB1BofPCtzLj009PNamWlPD7ME mSf1CjfqtnQ1BPmMbmuLk5gn9Q50GKxtcRgmpCTMASeORwRzLkE8ee/8K4Vi1wzLUBjO9aHhhqNO NxBylYfLphGaWdmRaA8wjP8AmHh9mATPcnL1DnMAdB+GFUy3B2kHOZmqV0ybLG/mXBegq3OapP8A YYdufcFWpReacvHPzw0bXFwdxFC0hbIUyIORwNs9woFFylJ9P8ueCOdcrXPKZqbv5s8GtxdE6Kec w2geH3YqJLipO4nnMDWlK5YZmubo1IK0nYUp9ueuKma5bKhrO2eN6vcCQgKZOc27bllX7MIOdc7V 1XnNQ5bRxywQs1yK1pSZhSprkMGMvcGM1qhmYrnnoa49M92qfyidqVruqMBudc0AoFEzDOp9Xxoa YqZrotmCee2hODMj3Cs3zbZmBNfE43Ge6OVKGdvvrivOuidM7h9PDXBIluFc5F1lZSVrVQaeAywZ FmueAVRM1ABX+8/fhT9TdBRWoEzCtaUz4Uwu+a5KqdxBmY1I0P2Vwy866z0JnY0r5HA3z3LIBQqZ mzPjjY81wYyu1lMpJY1BBJ8qaY2ie5GVP8ZtPCmATcXZp/8A5D/wrhS090XUklxMwJr8Dhistypc 1crMwJPjlgfr3X/77/34KpPdAMa057n48cEiW4DkAM4lYM1AFzP2YBWe5BGX+M1KUppgvz7oVrUC ZtTTP92I3eSdzE4kQPKWG9TUGjVHvJgnQMV9UZOVGp+OmIYupNvt7enKXfv4aEctfhrgKooBkB/+ DssyxtM0aM4iTNnKiu1fM4hsrvpb20srqjCRypUO23dtKYmvlUPItFiU6F3NB92uF/1SOpSgu9Gg YtTZv2KaH00r5aYh6tGq/V3X6QCnJJPUGYA+G3HTutS3slxHd1YwSMxWlNwVq+I8MQXkYok8ayAe G4Vp7Oa1trSZpXhqt2BSKMuStd3iuv3YWe7laabmOpdzU0Byx1S2suqGxt4JNirNJy1NCUop2kip XTE1x1PqIvrRYy6ENupQliakeH/Fi96j026a1t7OrR24Iq1AWC02008cbpsru3IjmzBL5AiSmVN3 szdRJzJ5HEUIOgZgW3H4BcW3X7m7EsE7gtbEKAEepFfQNacNMW3UbVdtz1BQIRqI2pVya67dMdPu +qXRvLW8Qu8A21A1IrtGY3A/uxa23TR/nOoKDG5odimgFBmCxrli06b12Zbq3vNtJBmV3nZk21fl bWvtJei/6fKQfTFhLO4BJMZo/wAwNADlpniboPW6G9iLCOZQF37M9pC5VIz+GOoR9KvUjtoJSFEo RQFJKqAWU/y+OLy6/wBRTrNDGnMjEe0kBQzPTYq8MXnWOlmOLptk2cBCsxVPUdRU+nM5jywl5tCT KTHMg0Dr4eRrX2ZuSA87sI4Ij+Zj+AGLe96rHG1ncup2bV3BT69g2kUO3xxDf2wEst4F+mU6UYbi zU8Bi0n6+FexvU9IRVBXP5qrxAOnhi3t7BBJe3n+ESKhV0BpxJJyxD07/UYV1ugvJkiVRQu20EkE aHXL2clxKdscSs7nwVRuOJ+r2EcadOgZ6hkBO1M6aknI50xddSA5d1aRvzRt9IkC1Uiuowk1oY5Y nJHMZYgRQkEkEjw8MS3vXhvvTKwSNCCCXPoA25AccWvV+oxxSdLumoFRQHoQWFKHKoGVcQ3cNRFO gkTcKHa2Yy9nNeXDbYoVLMfhoPtxHa3DoLaRXYxhApFBVaGtTiLofSYwb+Up+q4BUB9AKkYk6F15 FF2T+i8YAWoBcg56FdDh+lf6aQboN3NmcD1FDQ03nIVyxL0+/hEd7bKxkdfSCVbZt21OftEsunFT d5PMxXeEQ6A8KnC9WnlDXAtnlaUrlvUNSqr54juLVIpYZixRysa/4ZoRmwwt91iND1JmMawrQKzF m2V2lvyipxZ9S6xDG/S73NeUo3qCNwp69aZ54SeFg8Uqh0YaFWFQfZ2nTOkmMzzrVlkUHNm2p6mZ QNDiH+oQw/RF6TbeXXaa5ja5OB0P/T6KbmIsJ5JVG2qjMDcRkP8A0xcdM6nGIepWm4vtFFYIdrcT mDi7k/09GosrEbnMigvIAG0qeNMhgXBXZcRER3C0ou+gNV1yNfd7Fd6xGdIgxAIavMZd1QNcH1U5 c0ZNftX8cKrOtWCxj487T7hjp0hHpW5c1z0ffTUeWOirHMrKpQUzO6kZUkfDHT4yQSII6kZjMV9n fhCFPLBJPgGXd+7CZg/qyEkHzxeXJ6oLzmkyUgZNyM5LVam7LHW+iw3PNt4ba52x6q7IQu5VrlUe eOrMHVXBerVFVpFkTrljqGWe6LOvCjcPZvc3cixQR5s76Dhhbexj5XSoJKbyRtHDmP57TkuOkWtu a29uJIwW1LEJQk+dDjpk6sNykqoqM1ZVJ/8AZGOguyhEEVsu4sM9j1NfhXHSVjG986KpG4kutKZ8 cCooaZj2ey0jil6jKabMhsBz3SUzzxL1/rFVupdxjQkfnzLttP2AYnkn6jG0bMz0g9VJGqfUNMdd 6JcSGbkW0pi3PuKlKoyrU6Y6nQ0aTng5in+EAPhi7kalHnotCCPSi1zB8/ZobySOMM1IzKVWra5b sfUdSYP09biRbRVIUbDRlPnVePxx0Ga0QRWrRPtiJHp/w8q8cdOVKVEhAGQyKY6ELhidkVoGalMx Id1Fx0tdhKxgHLPdVx6QB8MKw0I+HsmaUhYwCWLUCgca1xJ/Q2ik6Pyj9QINrMzVO8CnClNMX3TL JUgu2cLJJI1EfcRnUaZLTEvUT1HZNbIWEMTMF5akmgeo8SdMWc9yea0N20ckppU0Q7NPI0x09QPk W2L56ej9+LDcCpEdMwRkGND93s7botzMbfp8IE1461JYn5Uov9s8G8V9tizusT0PysuxMjnhWkNF ZwFJ028ig1xZ8tak8lqLmTQGunkMdU5how5gYeJ5ueOoucgWuQKZivMHH2c966l1gQuVXU04Yvbi 4l3dUvJVldACQsYb5N1Mv7qYfo9lMn1qQ8uQOCFTc1aEgeGP6kL8me0BbkxlgEjB/I9f3Ux06a5q 86XLRyPl6iqNRqDyx0yMr6mMJOVKUiauWOnIylWFvHVTkc1r7OG8guEhg2LGzZ8xNu5twApWtaa4 g6U9093bXRTcGqVZZDt3bWJ2lT4HHVWbKn1G4a//ABVpjq4hFCI7g0HyncgpUjStcdQDDPmjI/8A JjqMjbghaJV/lqA5P26e723UZ2kWa127QpG1gjbwGBB44ktLpA8Uw2uOPiPuwkJuLpoI2LrEzqU3 HU02DXDdKdAlvsCRbR/hlfkK/DEUc9xczww1KRM42CuZoAuVcBFFFUAKBwA9nPYysUjuF2My0qAf CuFsbdmeNWZtz0qSxrwxPd2F1PYPcV3rCw2+rXI8MSCEGWaYFZppM2cHh5fZi6itry4gt7w/qwoR t2VJ2fChphLSzQKqgb3/ADO38zHj7P6F5mgG8SblG6pUEAEVGWeAlv1a4hpnRRRd1KbqBxiHpVzI 0jW9OXctnIGGp14/HFq3Ub+a+hs8ooJAAu0fl1PlXEAeQ28tuSUlRQTtOq0qPAYh6lf3ct/PbheV zAFA2fLkPDX4+0ub5r8oZ33oDHuK5aV3DT+GDdXHU5r0OhjeGSu0ginF2xM3R+pvZwXH+JGUDkCh oAS3CuJ03G5mugVmlcUqhr6QM6DPPPF3ZWnU3S1uyd0JjGmm0turpQE4SygYuAS7u1Ks7anL2a27 uYpYm3xSagGlCCOIIxbWV91Xm2lsQVURAPkNvzVzouWeLfpkT/Tiz2/TuBuptG2jDKtcWg6l1Mzw WY2xoIwp2/fxoMQyLKba6gyjlAqNvgw8uGeI+p9XvPrWt1TkoF2Dcmm4Z/H4+zms5wTDOhR6Ghof A4uLOy6tybSeoMfL3GhyJBrkSPDFx0hZTzboq8lzTPehBWg8BTB6R/VQbNqApy6ELXcRu1+zDdCi ZgpPMSdqFubqHNKfD4YtenX3VOZY2rVWNI6HbpQMTw4VxFa267YYVCRrUmiqKDM+zM9zZwyytkzs gJPxw/UmMbWhJMdnyxtUkUGuWWLfqtjcC1u4doYkVB2GqsPMYbrfU7v6u7/+HtXaoquzTyGmJerd IvBaSSncVYbvU3z8NDia4llNxe3GTynQLWuXmePs2ilUPG4oysKgg+IODbWkMNnNvVhMsYrQHMem hzwejyud70aS4jARiysWSuWYFeOD0d+qg2JIqojo+ytdm6umF6HE7KIjvhmbNhJUnc3kdxyxZWXU Oocy0sqhFRNrFTwqfhTCxRqFRAFVRoABQD2adW6feNZ3ahd1ashKZKafDI4XrPWLsXU0e0xxouxA U01rkNaeOD1rpN39LNJnKjLvUlj66fEcPHFzfTzG6vbotvkICgKx3NQeZ1xeL0rqYtrW8qrRmPcw U7sq14BtRj6WNjJI7b5pD+Z6UyHAZf8A5fiQKkcMFpukMiA03MzKNaDMx4gRekNypnCGQMzAbm21 B5dMsJcGHnySuESPdt4VJJofDD3CxGCSJ9kkZO4aVBBoMR2dvbm7upAGKg0VQa00BNTjZ1LpL2+4 egkstfOjoMvhhZENVcBlPkRUdtTl3ak0Hie2S4mO2KJS7mlaBRU6Ykl6fIZEiYK7FWTMiv5gMZnX TsuL4oZRAhfYDQmnngX6xckF3QITX5T2xWz2c04lFeamSDOnh59y4sVsJJZbd2Su8ANtOuQOILNu nSxtO6x79wIXcQKnIZYa12NcXgUMY1yUV03NiYQI0VzChdoH4gcQwywwPTWNKU2SV+NfRhbKWJrW 7YelWO5HI1Cn+/tboH0781SV5wIK1CczTXCdPhhe+umNHjhI9LHReNWPhiOWWIwSOoZomILIT+Uk ZdyOwuLhUupiojjoSSWbYug8f9tJKek8yIA7QVzbwbXTFkzMHLKx3ABcizUFB4Yt7BbmNLO3KpO0 gQxqwO583BGlBifpyzRvZXBdYiiqFLA7oyCgzyqMR9X6MEnIA/SKoWUqPFsyD8cJbf6o6QhCmgYr mOG5VlBB+xsRTWbK9syjlFPl2jKg+GLPofTZxavPt5srAHdzW2KuYOlDiF+m9QjezqrXMUqBN9Mm H6aHhpibosV19NYoxQoEDAiLVmDDMlhi06ZPem56dOVohRI6LKduigUIbHUelJ1JoLWMylRsRjtR toUKR554v+jr1LlwWqudojTa7BqD0bchXM46rb3N0CLKAvbuqqOVQNuNABXOnDE9xe9TJjB5cS7V ILqN1WyFKbuGOq9OvbjfLZwuYCablMW5W2+IFBi9mvrkzmJ6RsaFlyqcgK0x1Ut1H9S3EbJ6F+Vd 7MKBRk1MX/U+egt7YUa1WJVDSOKI5Majjli56h1Pq5i6moK2sQiDLQUYfkNM9KaYMpnB6gJuSs+w EFWXfXSgIFRpg9ba/SSS5TmTxGKPaYpM8325+OFeTZuEsgARVUUy4IAK4e86fKYnideYVAJKN6T8 wOhIx02a0uQOoXBKzOFVmPL9LZUpUmnDHSLY3hFxOhN01FXc+5eO3ICtMsJaS9UgsumyoFeOnMmI p6mK7Cc9AajFv02w6hz+nSSVIKKgf0Et+Xsv16ZFDdTBmpCyqp2nb+b0n0/HEaX/AE2KG0kzaRdV FPHdi+gsGhkn3SKrOg2oisKnMZnhnXF9ZX8CR9TZWZpVFK7MnQr8vnkMXsfSbaK9qQ0hYBdnzUyG 35sQf1xI7GY7dqhFAY5hArMT8xOoPbcyWTILhWAjKopkFUz1XF5d3Thuoqd2YC+hvmYBdc9cWtp0 25EX1C5oVFdxbYM2ByxBXqIuXugry71Ay3UINeHmKYtuj9IuEgaUASFgDuL/APMp0XFtL/UFmt2d WZCnK3soBKnXI18cWVzFdo03UuVLbO6LWBGb9MVzGXliwiW5orRFbmbaP1pBtDVFCPhixfo3VEf6 gos8E6rGSwahU7VIAI8/9spLezjM05eMqg1+YVpXyxbQXERjuYkcGNiK1DNTTF1ddfgeKIk8uMt6 ndiamqmtFxa3X+nYnkCHcw31ZXU7gfVTL7cRda6OZWWVUeayMldj7fUpjqAR8MRWD9NNnHGwMjOp C1IPqLuPDgMW9ijbxAgUvSm5tSfvxa9b6QnMurUAMg+Y7G3IyjjSumLea8WXp1nblecBuhDAeo+k mrFtPAYk630i3a7tpDvZFO4+v50Kj1aiopiDrXVLY2lpAQyI1VPoqVCq3q+bOtMXd7PbsLSfnbZ/ SVIYhlzGfDHVLi7t2ihmEnLkNNrlpNw2kHwx15epW7xRT277GJWjU3nUE4mXplm93aysUQqpblS0 FSAmehx1K56mpiuuoRNHHvpvHM3F2amlTTF30iDpbyS3DjbOa8tCVpXePSRTzx1WG4tzbm5jUW5k G2r0cfGmYxedEu7J4Le7Rt1yaEKwUhAKZa8cT9KPR2ndy3Km5W/YWoCdyqQw+3D294Q3UQ4nghGw bQooEJWgLEV1OP8A/nR0xlEKbXmZSpaJNFXdRa5UywLe+hMEyyuQjAA7TShyxLayiscyMjDyYUxb x3sDLYWUztvcehth/LXXeVGOnS2Fu06Q7t5WnpJZTnX4YPVJOnN1W0kClI1QyLQJtp8rbSpFdMWn WrjprW9szA8uMAiJCpjAYZGo1OXZd9V6d09rhWZhGzL6GVlAqKEYj53SByTsElFIOvqYVfw4Ym67 ZWhu7S6DcxYxmDJtqPSCQd+emL7rfUrd7YzIwiRl2EmXLKtD6VGLhYOkPMZwpYOhyCFtCv8AzYtu qdXg+kgtWU0IC+mM7wqK1SanjiDpcqIOm3VeUxX1MBHuNGrwbslvpLZvo3DUn2/p0MO0Z/EUweq9 BjaWGRjIFjzKV9To6/ynyx0nqFvYymsSNIm3/DYPuKseGLCaytmuBCkhkKLXbmpoa5Ytet9FiaV0 Rd4UAurJ8p2tnpiztn6fJaQQkc2RwQu4+lpDvVdBwx0y86bZG4t7RI1jSID5om3kNQemvjizuILR Z7Z0BvrEqJGViKsMxupTKoxDFY9Ibp0sjsDUMkWWa/OoAooz8cKrncwADHSpAzP+30tu9QkyMjEa 0YUOGs7eR5UaQy7npWrBVp6QP5fdf6oyF7sJy0diSEXiEXQVrn//AAT3/9k= ------=_NextPart_000_0049_01CA160F.6CE57CE0--