Return-Path: X-Spam-Checker-Version: SpamAssassin 3.4.0 (2014-02-07) on lipkowski.org X-Spam-Level: X-Spam-Status: No, score=-2.3 required=5.0 tests=DC_PNG_UNO_LARGO, HEADER_FROM_DIFFERENT_DOMAINS,HTML_MESSAGE,RCVD_IN_DNSWL_MED,SPF_PASS autolearn=ham autolearn_force=no version=3.4.0 X-Spam-DCC: EATSERVER: mailn 1166; Body=2 Fuz1=2 Fuz2=2 Received: from post.thorcom.com (post.thorcom.com [195.171.43.25]) by mailn.lipkowski.org (8.14.4/8.14.4/Debian-8+deb8u1) with ESMTP id uBCDt19x009746 for ; Mon, 12 Dec 2016 14:55:02 +0100 Received: from majordom by post.thorcom.com with local (Exim 4.14) id 1cGQzl-00073j-EW for rs_out_1@blacksheep.org; Mon, 12 Dec 2016 13:50:21 +0000 Received: from [195.171.43.34] (helo=relay2.thorcom.net) by post.thorcom.com with esmtp (Exim 4.14) id 1cGQzj-00073a-4f for rsgb_lf_group@blacksheep.org; Mon, 12 Dec 2016 13:50:19 +0000 Received: from mout02.posteo.de ([185.67.36.66]) by relay2.thorcom.net with esmtps (TLSv1.2:ECDHE-RSA-AES256-GCM-SHA384:256) (Exim 4.87) (envelope-from ) id 1cGQza-0002R2-TX for rsgb_lf_group@blacksheep.org; Mon, 12 Dec 2016 13:50:18 +0000 Received: from submission (posteo.de [89.146.220.130]) by mout02.posteo.de (Postfix) with ESMTPS id 836D420B1C for ; Mon, 12 Dec 2016 14:50:09 +0100 (CET) Received: from customer (localhost [127.0.0.1]) by submission (posteo.de) with ESMTPSA id 3tckjr6KB1z106P; Mon, 12 Dec 2016 14:50:08 +0100 (CET) Message-ID: <584EAB0D.4060004@posteo.de> Date: Mon, 12 Dec 2016 14:50:05 +0100 From: DK7FC User-Agent: Mozilla/5.0 (Windows; U; Windows NT 6.1; de; rv:1.9.1.8) Gecko/20100227 Thunderbird/3.0.3 MIME-Version: 1.0 To: rsgb_lf_group@blacksheep.org, Renato Romero References: <158ddfd1f0b-5980-42e@webprd-a47.mail.aol.com> <584AC31C.20803@posteo.de> In-Reply-To: <584AC31C.20803@posteo.de> X-Scan-Signature: d557763986d50bf6fda7413e64a7cae6 Subject: Re: ULF: Finally 100 mA on 2.97 kHz / 65 km ULF experiment Content-Type: multipart/mixed; boundary="------------070502080500060501030504" X-SA-Exim-Scanned: Yes Sender: owner-rsgb_lf_group@blacksheep.org Precedence: bulk Reply-To: rsgb_lf_group@blacksheep.org X-Listname: rsgb_lf_group X-SA-Exim-Rcpt-To: rs_out_1@blacksheep.org X-SA-Exim-Scanned: No; SAEximRunCond expanded to false X-Scanned-By: MIMEDefang 2.75 Status: O X-Status: X-Keywords: X-UID: 9782 This is a multi-part message in MIME format. --------------070502080500060501030504 Content-Type: multipart/alternative; boundary="------------000903050906040300040306" --------------000903050906040300040306 Content-Type: text/plain; charset=UTF-8; format=flowed Content-Transfer-Encoding: 7bit Hi ULF, More news from the latest experiment on the 101 km band with QRB ~ 65 km. Yesterday i have been in *JN39VH41HL* again and took all the equipment of this ULF experiment home again. Everything has still been there and in its right place, which was the first good message. Here's an image showing the coupling of the loop antenna, 2 turns primary and about 200 turns secondary on a big ferrite core: https://dl.dropboxusercontent.com/u/19882028/ULF/20161211_123535.jpg Even the audio recording process was still running but the USB stick was almost full. Now i have saved a 29.7 GB raw file containing the audio data for post processing. This recording is almost 4 days long. 2 SpecLab instances are now running to produce spectrograms in 424 uHz FFT bin width and 10 minute per pixel scroll rate, using a noise blanker and a 4 kHz wide filter centered on 2970 Hz. The accus (5x 7 Ah lead gel) were discharged to 12.17V, https://dl.dropboxusercontent.com/u/19882028/ULF/20161211_123758.jpg, so it was the right choice to use these 5 accus. The single turn vertical loop circumference is about 45m out of 1.5mm^2 cu wire and the captured area is about 70 m^2. Now, while writing this mail, the first pixels are coming in. So far the result is looking very very good, the SNR seems to be arround 20 dB, much more than expected! See attachment. I will write a summary when all the spectrograms and eventual EbNaut decodes are available. But in the moment it looks most promising that i successfully crossed 65 km distance on the 101 km band, which was the goal. This is the path:* http://no.nonsense.ee/qth/map.html?qth=JN39VH41HL&from=jn49ik00wd *73, Stefan/DK7FC* * Am 09.12.2016 15:43, schrieb DK7FC: > After doing a lot of modifications here on the TX side, the effect > still exists. I can't get rid of the unstable phase shown on the VLF > tree grabber. > > One thing to mention is that the phase seems to change slowly, no > sudden phase jumps. Thus the peak is 40 dB S/N in 47 uHz. So obviously > there were much less uncorrected phase glitches than expected in the > first moment when i saw the effect. > > Just to be sure i downgraded to the last SpecLab version, the one i > used since the last month. But the effect still exists. > > Next to note is the i never saw the effect in my last tests. I still > have captures showing a very clear trace on 2970 Hz during the 31 km > experiment. OK that was in September. The QRN levels may have been a > bit higher and the signal was 7 dB weaker. So maybe the effect was > just hidden in the noise? > > Next i found that some SpecLab configurations seem to be corrupted by > forth and back installing old (V2.90b2) and new (V2.92b2) version. So > i am now using the old version and a config file that was never opened > in the new version. It all seems to work fine on the TX side but i can > still see the effect. BTW i even disabled the NB and checked if this > makes a change. But thill the same result. > > The _TX schedule for the experiment_ is: > *07.DEC*: TX 2970.000 Hz (antenna current between 105...110 mA all the > time) since 13:30 UTC. The recording has started about 15 UTC. > > *08.DEC*: EbNaut 5ch, 80s, 8K19A @ 2970.000 Hz starting 7 UTC, ending > 18:22:40 UTC. Then, carrier at 2970.000 Hz. Some interruptions > happened in the late carrier. > > *09.DEC*: 0 UTC starting DFCW-10800 (3h per element), 'dit' at > 2969.9975 Hz, 'dah' at 2970.000 Hz. The message is 'FC'. Between F > and C there is a break of 7 hours. In this time, starting 15 UTC: > EbNaut 2ch, 68s, 8K19A @2970.000 Hz. > > *10.DEC*: End of DFCW message 'FC' at 13 UTC. Then, EbNaut 5ch, 80s, > 8K19A @ 2970.000 Hz starting 13 UTC (repetition of the message of 08.DEC.) > > *11.DEC: *End of EbNaut message at 0:22:40 UTC. Then, carrier on > 2970.000 Hz until 20 UTC. The recording will stopp in the late > morning, due to space limitations of the 32 GB USB-stick. > > From the local recording i tried to decode the 5ch EbNaut message. But > it didn't decode. I just got a '*****' message and a false decode. > This is strange. The dots are quite concentrated in the two horizontal > lines which indicates a stable phase. See attachment. Also the signal > peak is strong and narrow. But in the red field there is nothing to > see... This EbNaut message was transmitted with the new PSK config in > SL. It is the reason why i will repeat the message in the end of the > experiment again, using the old settings and version. > > I should have done more pre-tests before starting the experiment. But > now it is running. Well, the main goal is to detect a clear trace of > my signal in a spectrogram running at 300 uHz or so. The signals do > not look bad on the local grabber, not at all, despite the strange > (propagation?) effect. I'm still optimistic... > > 73, Stefan >> --------------000903050906040300040306 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: 8bit Hi ULF,

More news from the latest experiment on the 101 km band with QRB ~ 65 km.
Yesterday i have been in JN39VH41HL again and took all the equipment of this ULF experiment home again.
Everything has still been there and in its right place, which was the first good message. Here's an image showing the coupling of the loop antenna, 2 turns primary and about 200 turns secondary on a big ferrite core: https://dl.dropboxusercontent.com/u/19882028/ULF/20161211_123535.jpg

Even the audio recording process was still running but the USB stick was almost full. Now i have saved a 29.7 GB raw file containing the audio data for post processing. This recording is almost 4 days long. 2 SpecLab instances are now running to produce spectrograms in 424 uHz FFT bin width and 10 minute per pixel scroll rate, using a noise blanker and a 4 kHz wide filter centered on 2970 Hz.

The accus (5x 7 Ah lead gel) were discharged to 12.17V, https://dl.dropboxusercontent.com/u/19882028/ULF/20161211_123758.jpg, so it was the right choice to use these 5 accus.

The single turn vertical loop circumference is about 45m out of 1.5mm^2 cu wire and the captured area is about 70 m^2.

Now, while writing this mail, the first pixels are coming in. So far the result is looking very very good, the SNR seems to be arround 20 dB, much more than expected! See attachment. I will write a summary when all the spectrograms and eventual EbNaut decodes are available. But in the moment it looks most promising that i successfully crossed 65 km distance on the 101 km band, which was the goal. This is the path: http://no.nonsense.ee/qth/map.html?qth=JN39VH41HL&from=jn49ik00wd

73, Stefan/DK7FC


Am 09.12.2016 15:43, schrieb DK7FC:
After doing a lot of modifications here on the TX side, the effect still exists. I can't get rid of the unstable phase shown on the VLF tree grabber.

One thing to mention is that the phase seems to change slowly, no sudden phase jumps. Thus the peak is 40 dB S/N in 47 uHz. So obviously there were much less uncorrected phase glitches than expected in the first moment when i saw the effect.

Just to be sure i downgraded to the last SpecLab version, the one i used since the last month. But the effect still exists.

Next to note is the i never saw the effect in my last tests. I still have captures showing a very clear trace on 2970 Hz during the 31 km experiment. OK that was in September. The QRN levels may have been a bit higher and the signal was 7 dB weaker. So maybe the effect was just hidden in the noise?

Next i found that some SpecLab configurations seem to be corrupted by forth and back installing old (V2.90b2) and new (V2.92b2) version. So i am now using the old version and a config file that was never opened in the new version. It all seems to work fine on the TX side but i can still see the effect. BTW i even disabled the NB and checked if this makes a change. But thill the same result.

The TX schedule for the experiment is:
07.DEC: TX 2970.000 Hz (antenna current between 105...110 mA all the time) since 13:30 UTC. The recording has started about 15 UTC.

08.DEC: EbNaut 5ch, 80s, 8K19A @ 2970.000 Hz starting 7 UTC, ending 18:22:40 UTC. Then, carrier at 2970.000 Hz. Some interruptions happened in the late carrier.

09.DEC: 0 UTC starting DFCW-10800 (3h per element), 'dit' at 2969.9975 Hz, 'dah' at  2970.000 Hz. The message is 'FC'. Between F and C there is a break of 7 hours. In this time, starting 15 UTC: EbNaut 2ch, 68s, 8K19A @2970.000 Hz.

10.DEC: End of DFCW message 'FC' at 13 UTC. Then, EbNaut 5ch, 80s, 8K19A @ 2970.000 Hz starting 13 UTC (repetition of the message of 08.DEC.)

11.DEC: End of EbNaut message at 0:22:40 UTC. Then, carrier on 2970.000 Hz until 20 UTC. The recording will stopp in the late morning, due to space limitations of the 32 GB USB-stick.

>From the local recording i tried to decode the 5ch EbNaut message. But it didn't decode. I just got a '*****' message and a false decode. This is strange. The dots are quite concentrated in the two horizontal lines which indicates a stable phase. See attachment. Also the signal peak is strong and narrow. But in the red field there is nothing to see... This EbNaut message was transmitted with the new PSK config in SL. It is the reason why i will repeat the message in the end of the experiment again, using the old settings and version.

I should have done more pre-tests before starting the experiment. But now it is running. Well, the main goal is to detect a clear trace of my signal in a spectrogram running at 300 uHz or so. The signals do not look bad on the local grabber, not at all, despite the strange (propagation?) effect. I'm still optimistic...

73, Stefan

--------------000903050906040300040306-- --------------070502080500060501030504 Content-Type: image/png; name="first pixels from 65km.png" Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="first pixels from 65km.png" iVBORw0KGgoAAAANSUhEUgAAA+IAAAFACAIAAAHANGFGAAAAB3RJTUUH4AwMDSkYCkR3dQAA IABJREFUeJzsvX1gVNWd//8+kRpWEpAKykOCPEwghEiCgAQGZECBTBCNNTXfloDfbktm26IT umuhLd2Z6bJV6m9rpuq3O3HdfoW43XTTb6c+ZCJREiQDiQVJNDxmDJgQI/WBlQG6Dej5/XHu 3Ln3zp3nxyTnVRrPPfc83ZuTzz3ncz7nc0hXRxs4CWcUgPzCIsDc5Zhc3z5ACAFACBECUwvw 4bvjCFm1funLDW2YfMfiKX8+euxjZMxYmHPlnY6P169b2bDv6JzMq91XhIy+P1UjY34rMbVE 0ICJ4//G972Tro62eQVLDhw40NLSMg64FFGtczIJf+/+0h84cEDx0stKi0nqyxn7q2+U3ndv slsRY9IAwN3jdvcIEe4etyfQZO+EJ77d3ugG2gcgxgAX6pt74O6Bu6d9AADckN4VihWysNIk nHSjqdnZ1NzTbncCcJ/uPOn23q1vFsq5dPXLGD5t6iDImbDyHO9sj1NrRg6jABzvbK/YvLt2 z3YA+YVFTPJsrdrR0tLCEilk0feN2xPdzJRh89WMv337Vd94JsopBQFAghTS1dGWxkLspUP+ irs62ti/WDR4mPDeO7fDYTCwzygxKO4SAhBQGrycsL+rW6t20FAKHqYcb53/8fVf+cZ7+zsB aJAu39XRNkq82Fq1o7m52W99XKYDAB5GoO88Ya87mJyBMJ7B4d5Q6uyrO7irKJSEwxgb/mIg BoMDAOBQyhkgJCEDz3tfOi2UtNnlK3ZyWX/KRm02PQBAbxNjKRXeeAh9HWDjGZFVq1b5S/ds 9ZPhN1HgOevupeW1N9xwww2jbhg16oYbbrhh1CifsM/dEJKliTGyW2qlsRhCSM0PS6P5PhHy tp94MRRSOWkALIWC9Hi+ubm5ufn50sHBUhZsnv3D5h82Nwtyv68uJHGkxqVTz1x8buEnv7rz o6O/6H/7CQBYV35m/8MnLfMiLTIS5t94KsoSKP1GYDkDJmqC/WZHATB5hjQa9tPodHpuC39Q jOzykMSRP3SbxOAHh3Yd72w/3gmMmfyfT06OplQPXwBfxKKcoJyw0SNCUCJnRIQhfDASIWfg GQ6JkzKG4jJcWHb2k83yEjDVqLlzUuAEhIT06kcBsBQWdT9efzPwfHMz6/JWF07kGGzUZnCg VA99jMaRivcS5Wti2cVCWCDK32VQfv+Opp0Y0GCz6QGHQbXLhzJl9cqZrX8S5AwAowagNijk TAoj/jnGu8vvI89do9eEC7WXjuDTJkAqZ56tfjJ+k6NwVW8xJ3aPNi7w7bDG70GoeOl8SIUF wmV1QWt1KOJkV1HXkRA+ByCMZyB7HGH8TiRjSv+E9N5rN2aF2ThfNEYNnEa9Ik52FXUdCcMj fmWPw163OIEKzCgA9fbGmLdMwbBR7xTRrYETkND0kYJ8LystRl+dZcM50yvT81+ctv2RpX9z VP2X8Wz1kxHo34eNfD94/ZcADA7W5R2KLg+PtBEUk/4ZBaCstNjSCtPtMHVsr/CMw3qzi6Oa JanjsGpLfncITkrBBLpVqzE6AWitrkMnuqnnD5gQA6U2AFqidVI2jWPCVM8SO43JEUtf+cqN 165dU5UzkIj4oIStf59XsESn04WV5Tnr7tTp71GuH9zdMetn//2CbzwhxPvSQ9S/VxQW1aq9 /XkFS2L15zls5PsTV/b8DC8YCKkBAFBKrS4YNTCbzRYLAJjNMMFsMZsDl5Og/i6Gw5pPShPn FxYh2LQolMKj7O9Op/PatWu+8ZGsr+YXbom4HeES1q/Zd7E3hoVHSqB5EyFBFZECowB0dTwf iwaNCCgtAaAqZzxJzOZgQgZMzhQuWu4pdMPXkP3DLS8v2noe8wb9ZYlGziSduMqZEPHacXBi QigrHoxRwZNwJPxWtxSB5IyZAqCwWMyBy1G30xP/alT/JEe2nHnn2rVLvvGSNxZ83iSzn5Ey ki2TgvGXQDdDeOmMURDmWlSrtb748O9gdGoAYnDQx89As16iJXRZXZrIJufDyZ5y4Il0RYxM R+NRSQYdxZOujraw9JEmkylcOTOcuLm10H692jdenDchBP2MIGfKSotDr3jYzPgjYx9UBpEi ohL4MbP5V+xLu7ACR2vFBGazMLrn48jwuEZeV8TIl9CEzu4Up05HawEs9NwVp1Sq7/2wpXD3 QRbsq4uyocOODxTXCl2w+bFiSjF3ofcSUF4iAr0Yhtd3MlymtRbsuW71jZeOIwEsIjgqubsQ ssuujrYhsK9s+CGo6JnQYb+xbELO++wNvGf9PR8e3E8WrM7JuHqg8e0pK3Q5Y6427DsCSUr4 5BoGWyCjvCXdufrJf//PhJtHb63aoTJjUrXW2N+wHwA52HwKIIScPthyhpD161Y27HsLk+bi o5Oh/pZHGNLRuU6nY5epLl7sr76xevXqsTcNq+GW8DBs0ynbWSrsX2XbTQc6AdQ39wj7UT1b Ut2nnU32zpPNjU2nr8CT3o0L4t32ATQ192CgE+K2VQ/t9sam01fcQFOzkxUOd0/76StCpfbG pmbJxldg//79cXv85EDC1b3Y7ciZMaLnStEzSphttu7Or5mu++qxlpZPZYtNfXXILpdnWTKS R43iDl4FMuuBYHhk5fLtXXvK4bu8p3zjHBlWLREH6aIRZFDZIftARbmJYARidFJRPnu3kIVi 5M4IbD80wnVeoSC+66DrG2JPP+y/LE8BXBsDANBaXdIw0coVAyEsbogvfam/FN7hDZfvAACp 5aXTqKFOI0TZEspODql4CbBhDNGJ+yMf5ke/rZTFRLO79YYb0gDYHn8g4gcJQOiyBeyl7928 e9Oe7cLuU4cBehtb/HZZta+td1blEErpv3a2n9tctGlPJNPXy2eeBbAPqPjGmwX6OxybbwWw H1gN/Hjdz1W8hcSH+TeeencwN/pypGbGvibH4Vn5hvgh7T67pLpaF1Yrfce2SfwsRznJCDBO h7h6hyBCJhHihRDC9o6KMWazWbpeWG9vVF0+jKGNcWJgS3dBBbv3pYviRXvm8Z1GjR4y8RL9 w0s1awnYqRM/AosXhCBhEiFeUscIKXoPRIHFC0L/kDLi+oecOjs34kost6HGBDaJIFor4LC6 vF3DBVi1YdjEJh2HxBTAAVi1gnMNZnUUyuglcbalwiTCaQRg1MDo6RUawOgcSqZ9enlY7xR2 vAsGMCGoX0aF+00riEhQDK1BSMQI7zoU7zHmrnENO5dOa919cPn2FUBvX93bR4PsoQ+X4STT vbsx1bafCn/AAT+no8pKi8tKzwPA8u0rgL19eP0nyMHnpj3qmpbus5E01GXV5lTls92kQVIC 8Biyaq0uVOU4KRV3oqYCej9hhDZ0ATBqXsGS4xKHu5uyscnP644GjdFJjcGTQe5dwGnUwEgB pM4bD0DoY1Fh0+mxYNOfeQVL2MQysgYNG5lOCGmg9IwLbEok7taQbjoNyigAtR1tQV/K8c72 BBtrBHBjFW83SAFgcyu95+/R5vkbZGukIW4TEMbp/j504thmXsESqfIkAQTwYZWatjrSIWNg hHG6v54u6qES39NTkwDiRfivxQxzkEJGAfBsNB03iVb8w8wPjT/5I77+77jpm76pj3equ5cc OQQQLwDMZlBqDn25jhMDQh0yxr8lwwpf8WKjDYSUeLeYhrC/dBQA343ZhBCgAnzDow++4oVF MvFiMkGQMgHhm0tjSRg7SwEQQqq76eyniL2U2vQwEIONisozYd+p0xnanNKH4Wf7qOLxS0JQ yU5C8aUhpaDAFO7K0XAi6MJ0SB/SsDaUIlKF1wiCLUtnF6OvsWIhao8CQPFj5sZfmcWNpuEN GYf0gnIMcfiJX8QcIFGgrxHASc+uusZfmSHZZaq+m7RC2E3q18BxhONPoAu7Ron6JlLxUnX0 srS2g5k2+jVw5KjCujalIETW082/kl0yM6Alnr2NMJstYhFSH0oS0/dQIyPLFcOieANGQgP8 eQs5cODAypUrWXjVqlXPVj8pCJiWlpaWFotOp2NjorJ7Zje9eYbMXf75ydaHHlj3+z++ngXc tToHGTMA4PJZ98CFS5fcfyLz8eG798zJHBi43O/GJQCZsxZl9kxZsPrlhv0Apty56sOBj6cM dA0AmQBy7gJw+fLVKR8d/5BVPCkPH51gwdkZOHNZtdkcjl8CLAYpbqX6Bl4OJ1bc8L2/+w4A uHuQPt7t7nnL0T4rV1yXvwBk1NsbT5xy5U1N60+/sf30tdETLo5FRr29sf+Ua9bUtHpHe54n /Uk3Jg72tB9qz5oxuenIyZ63O1iCE6dcYpp2uzMrd1pTc0/PuYuzZgy2n/5zW+uJvNx0IKPJ 3jgrd3LT6Ys9594f/LBj4hSNULVYfrNz4oxpTfbGWVPT2j+7MQvn6x3tYjPEwIlTLmku92nn W5/eMiv9/MnB8RMHe04e6u3pvJCVOwlAU3PPsc72vKlp9Ycunuhs7x9IGz1jPDntHJwwTfDg 5e5B+ni4e04Oju841PnJ6ElZmbLXd+nql47X3zx1pufUmZ7c2TPj93viRA+X69Fy6eqX+/fv H34nng8/AvX1rVU7YrKbOoIdBZzhQWvrx9evHw89vXTSyRAX1kJcKvKH0v90xea6isItllYo dI0Vm+t6gfzCooqXzm+t2gGPt3+Ab6nmBOLHGTEwVgtx20XwcuI9htlatcNobOZyfWRytfXO t6//Urx0AHrhwExh0Vmx9uxPrgfdqBsUdX/fTHJHBvcgw5HyJ1yVXuohHlLq54QvCVKzIAoQ dhlFjxf6OjtNs+Opl4A/6HQ6YT91+Agazb46AJYNT7Ojgjkjlv3lzuCJ/CAV8TTqjg7RQqB2 Y1btxqyuju2xGdJklyO73NTRFouDUTlDmDV1d0G+Ydth0ALeI4Wt/k8T9voyYv0+6iG7yhgm rodYx4nU8QSRakTvmSIaxmMM5Pvk9TYn4D3GWfU0lljpXhSoj9ejHcMkgyVf33/5zI8A4FwT pq95/zf/39J9C/7823umLN5BCElLS0tLI2lp5I7vGU/UPJuWlpYmxJK0tDSSxoKSsBhP5GmE bJ6wJ6W0NE9BPqVJmqGaMYbNKEg/DSAmbrWi4aK67/IgKLp46C5fA+PROcpVh4QQl2dSzBwU EoND6q6dBYjBQYhWvMXILyxCX13+rsP5mxOsjuwfm/vouDzj+PWv3XLHD5ZUD+BU46SFP1Qk 6vrXZxLbquSwtWpHNDqGWLEO0xDpGEZEdLMb+pGC6uUMD53jc9bdoWyx9ue9LZS7vsTc51s8 nMgldwyz9StfljW9FXp6X50jI8SDkQPgV+c4FMcwvgTt/QHOv2Z5QzkgW5o4RMEhLVxaPjM9 FcsJsfZU5hsth8sizSs96z4mA3dPX++rq9hwrrZD2CZHCOmmNIftu/O4JmTb8NhPdonKBtTs QuVO1JQkfZekb59Q7SVS1xSKNvveCvpQLEuIiYMWzkSMxGF7tK80sAPUBDCNPgrAqiXi9NRh 0OptTrisbHpqdalPTyEZugAheU4LyvAZw4DvVAMgP6GTDdmTKIY6Wu/47+thTJAUYxhFw6Pp 637PSR6imEwmAFYXqnIIpd3MaZjHQ1sDXGegMRJiAGpodzU0RgMhzAGAS+5fTHE5hEipMWTE qOgcQzsxIDAy26+9fbJ7ltZAOfN3BdqLGjhvXDFqmCQTuqvTqHFSCujZR5NSG6WUhW0SX6lS hmhHT0FuwVcAaAnRWl1MZhuYj2CiZQm0cuUegx1xJFs3jUVjZHJ9U7bsnml5oJxdOwNtAQ6c N04MD6k2nNiY8TkAJ5MpRgrAJpzvItgOOP1MXbyinf2M5dw0bjxb/WTCXGzw8Trk4/Wk0395 TGQZ47GcNApA99kku4eOFWy8bnCgpoTQhkrobUwD4LJqNUaZEZI4Ijc4YJPY2rFLh4HobVSR 2PeoDJZYS4jTI4UIEeqFj7WqoqI4kWpftj3k1y/gV1pCUN19qCqHUmrQWm1OIyFaJtrZ2xOV e6pEr1xnkK6ONqY4I1+vFoYl7MTSvjpkl1cUFq17pW33hqLC+ds63n26cP62n+8pLyksCmtq b7cjMXqYpPt0TzqKvp50PUzLtw7jkb+Gnt7fWhJCduzlD68eZgEhmL8NWDqvYAlYjylYcryz vbajDcAmQS9ZLmaTlqJ4v9IOd7yzPZH9L9WkGucr38m89kh4WRQjdVGcRz9kF/p6raT7hthj QvfLwRmxbEsLe9nUd6Su6PQRI+ocz+cXbmGheQVL2L/AOVka1elgiCUkgNg65xdLyy8s8lcy uyW9K80Vei3h5kpNnv7yBTAzwRBQLYEQMIsv8djviBH1MFnikfehSOXAaVJHrsd2VVgsLUCx AUwVQmwMSxZurtSE0rWIesIQKyt2oa97TnYQGUfp3ZMxbSmoduaA9p4/LSr6EIu+xIz/qzju YV7BXT5lUjGSHwMxwnnn+53BE4VMlJpHfpoGJ47c/dyDiG4MI/0kKBZTw4X3dU4ceWPLqwBo aPgrhI3Uo1ec8r7OiSPlzz8YZQmiLI+ZztH3qCT/dQda4uJwpHyAjugLiXIVSUQq1x0AtIQY iJYd1WHVEpd8RyAhBlQ2GBze/YKK7HBZxeycpJN011T/MnMCADgMAAyEwLP3lBADSyCNVCWG ctVrIxAP2LppAmwEOKlJa+vk69d/G3p6cYYaK1kuItgIxFUdfryzHUj+ohInKRBSD4TR12VQ mC1meM9GFgKRXSLec1NuZDvC+fmUrwPBxzC+Ckfm6Mv8QpvJZBZdZbiAzyRpXpGfmWk2m6U9 W5pSKDO0ZbnDwFJL4e5uwNCxHcAKFtnXi+zyANmYFwruf33E8lbr3C+v/zr09L77TWNizYtw 9psuBWDq2K6MzOanE3ICcQP5NyCMvs6QmTrGbtQu9HU+2ODEgxz6aAS5VGel0c9W+XlJnBHB qHp7o9ls8lxapGP9YX8GLG/AMGiA9LRe0VmdNAzgwIEDaRAGRkQYHmUtgA9L7l/rGwmgdNEk Fli9/h5J9G25d68GsOHOW3MzAYwBoCvWAbhvxYw5GULMynUrgYkl2ukla+/Wr1mUqVmkWgWH E5jjne3sHwBCyPHOdvZnwAIsBkzVSAhaWlosFgsAnD+GcbPXlRaXlRavnSs5w3NsjiegGZu7 LGvxGuFqztKpi+4F8MD6ewAsmj0TuDA742MAr7zzZwAb9IJZ733Fussf/XnS5DHr14l9+mMA DfvCcGnJ4UQGMZvNJpOJEEtLi06na2FDl3Wlxa/bG+P62Vq5buVbni5OCNGvWeFoOhh9XSPt w80b0NLSwsItLS06nc43DECn0/HJKGdEwC14o8X+6hv2V99Idis4Qbjhe3/3HQBuIN3d404f /4rdmZc7jd3rB8biStPpa8da/0QunzjwtisvN7MfGZ7Ik+6BjqwZoiegC0CG293ziqP9xClX dq7mFXsnudwxcYqmvrknb8Z4scqm5p5ZM8Y3Nfcc62zPztWkCxWh3u48cerEiVOu7Klprzja +0+5bs3VvCLPC6De3uke6GjrdLkHXFkzNPViLXYnuXxi4pTJTaevHXvvvKLGY53t/QNpo2eM Hwv0H3G6ycX2DzN73jv/yejxbW825k1N608fP9bdc/JQ74HOjrxc4aHcwFuevMc628V4EbGL nzrTkzt7Zux+L5wYI3T0QSB98OJg+uCC3LnivbGAGzfOTT+fPfry2PmrPzl1pWeAFM4Y78aN cydczCYfTVy0ehBIF5JnAEgfvJh36439/ZlZuURDPho7f/Wgu2f0hwMTZwh/PG7g0ujxWZno OXdxg34xyz4WcOPCgty5/aeujEZm1sz0BTNvGZy5eOygLG8/4MaFeeSjiYtWL5iaNm7O4kFc EGrBhQW5c0dP0Qzixrnp54kkV729cfToWzboF8+acJGc601Pvzp2RsHYzEmzJtzYc+7iXz+5 uEG/uN3RfvxyZv/gV8fOyV5ZMBm4keUdBM6fu7hBv5i11vf1nTrTI4Z5R09l+Bg9WphQL73v 3mQ3hBOIuG8jstuRMyNVnGRwRixhm6eHfzzVku8btwdPxRmOiLq/UJAqEEVi4oC3q6NN0LpU bK4DkF+4O7+w6OCuIuEUgL66/MKiCvmxjMc721l8fmHR3j7B41QqHB3IGTaITgGYvW6UvZwh Uy92dWzv6qj/7pltwnV2eeHj9QDQV1exuU7pRa3s6ZVvbWngQ3xOrCGSAzMoYnNchscj6R5x I0VWlzeM2o1Z2FgOoHYPRO+7yC7v6mBhbpXOCQ4RzkU0VKKmprKhuqtEPOyOEEN3dddr652q Z9yJsjx6M93YHJWR9C3onNSmEgClNsBmAxwSEU1pKWCD1gCnTTWnMEaPugXD6lw7TmpCqawT y48L0QMw+vRycQ4akwE6VDt6xDNLLtc5sYIQpZM6gqgEu0pHHx5HrXOGOlJZTmm0Z5V6tS6W wqLel7ZEUISBaA0eTwaMXqB3iPu656QOMVEyCh3dsnm36ZVtP35KoziSNxRsDfloUJlJcOMC jgyHwaC1ag0OrdT1ocMAwcWhOoK+JeqRujB0Me3ZDqA2Mk+Repuim0+Lrk2cYYnrTJfNaYPc xSdy8lQTq5yzHh1c68JJEOIBsTKVucYIjx5GcShAbI5V96DS0YfcnJKdS8pRZQgZGglLodT7 UxDnUc5DAcRVvcgc00VWVFjMK1gyJuf7aWmEpAk/PP/xhIkQJp4Y4X9p8ngiS6NWGhGLU2SU VZcCzWBvZv6NpxLw/mOL71glFv18GKkX3aefff3Hj637ufWr+ds+efeXEwv/4cI7T/164/Zd 3bJkbxhuXfv8x0lqY4Jg/Xtr1Y5hsLIRKyty4U8/v3C3pVAyAPA4/9daXVYXhMmDw+AwEEK0 7IoQArjgslq1RHSUir46S+GWvX1An8zmMQGM/do+38ifnUb/20+ef6oAwDnnP509+LMZt9/6 NXLbvC3fPfXGzoZ9P05wI0c0frQuVi0hBr96F9niaBSdXpDoDR3bfyN2dIeBlNRQagRwqCrH aaTMKEd75vGdqKFUmFJUAg5Dzq4a5ANAl5A3uxzPlvf8pAh7nsbRzyNvV/jQ4y9//WRamt2Y lpY2Yf4PSFrabXc+npaWNvWuHezzP137U+844flf574ghBPZyMSQmlbT/rQuvztUueyQHTa9 v4zK9dGIIJRSxZAj4iMxFOUkzHl0S0sLO2wjaMohN8+OnuRORqPZeCHTMLJwpN1c3Xl0rHpD YmaiIkGbnV9YFHgNK6zNUxFMtcPfnBXL7EMOmQlA1Ar1YWXUxbqy2KEVlwGyxLU94uWqVaui eUVRZh+6CKI9OuXL8NG6iIi9XHqpgN0N+gcgTRbuH4zU1Ef1buDSAjdv2CPVo0dpt8jwal1k 0XKtC+ACHAqTBHWtS1KR9oyujrYAHUW86y+NeFdMELjb+d4NnDdoacOwl/vRuhiIQRYDQKJs oTHRoku1LtK6FVoXLXnKSW2EkEqgBpXMjl5d65LChHL0ZOgT8Qim7BF/KiPOniLfWIY/rUve siqbMdD2opg4Aoij1oWRMK1LXKsYugxdrQsjVu4uhoOtC4OfxISEa7riilR9niqbo1OBlpaW KMcGw4AhKqRUYbvpxHCUKN1GK+RiDC8Tg8uqBeACiNbKrlm81uoiBgc81gxs9qMlBD6n0wc4 rJ6TAGTei0QHL1FbvMTGP/rBXZHswYs5osmExtO/oZnN/nvod6915+0i5BExsdZjtCOinPlz 4oDBodhP5N/Kxe9FJHg7eoV8i6fiEq0y/aNiP+iKnc/L7u46HG27IoLa9IJ1v8ZInUYAom8F 6jRqjE7RUMdp1Dip00kpANGZDtsPIF5yYgWbZbJvrE2PXexS+LlLoZ72SnFp5476d+Ido9fK FbeKSyyXTd6DqIF3cg9eHC/MY7NH9IDJFyGSOgEY/Wb0hqOU6SrqxdjC1YvJZYiqF2N7Vrqg XozrrLEgUq08ZySjcOqCmBh1xVX52n02fmXL4Hp0DC89uohUzxgxXoleVlqMvrq9P3kD//z8 pmygr86y4Y2ZrwhhZGsP7iq7kG8Ot4KESXSuR8dQ0KMbHCjVS90vOqxa+wnk2ZwqA3XFmhGi kOujABQUmCCI3iVFFuC6EP7mH7xhnMWkjXRShLUkCEIMtDuPeVAwOGDTwwVoAK3VJXVLbNUS o5NKE4O5Nm6ohN4GwCFxhMkSu6xa0VuDNLGBEJtc2rB6HQait1HfkkcmgttorZU6jTY9tITo KfX4kt5Fux+2+pmOMlkek2H6KEA4Y0g0HO2VeCDysSY9HK5P9O6ziRujU2rTWl1MNHSdcUEv dO4XjRpCDAqfrtLEAIBK6EsBAA49lNu6Hqk6JJc4QmKbzzeV1VuCBuqTeMQSmdbF+2pjZb3I rLi6OtrQuvtgyx9u1z14sOUPt+9sE7p7X91elO/eUFT4eH3t3b35G7YVPl5/7BcPhVhBwsbo DFFyswC70Mg9F4uacqmYlySQ9XKW2Cnv0Iq/Gd8GUMkOyACJOQFQzEdj4E3XO7Bbvn3F8u0A pnm05kycbwI2CXJdOOsinLEg17pwwsPXxCV6WxdhwYgNUertjSaTicUE3rglmvL6JgtwK648 W/1k6k/FOIFR2RAdI4SOLg7Ej3e2h7KNMkCXCrEEzkiAzTjhMEBvI4R0V1c+gsfzq3Lyuikb NhJCKG0gZBdwyGw2WyxCRrMZsABmADCZzBaLOcqWqJjpRt9HeS/nMITjmvU2MewEYKSKBJTq 4WfjBQCzCTCZoxmgl5UWpymuxXCIo44AyRK/ZZ2dfhp9Iao/Q8wYcfNi0vjhgWim63XnErvN 0UUA6u2N8wqWsH+BnV6IyQLcSq6/KN9+E1avVS0wcALRa4C/qqVpQqluePR7EhryLF4DRql5 ejTro8NqjK7wAqB6N2jDpMl8f4aeN3CZgRsfYnVDAhpF94zVahFUN17wMToNIPZhAAAgAElE QVRn+CGbjEYwRg/AyHQrxZESktalodKaY6vKIWazWZrXZBIuFfGRIXT0wkXLpbGUFnyJxVqM XoRB7ar3lq7snLrsKubdhtvCO8vreOfb0TeRM3QJUetiBIyUKkbqYvc2w4zojLqUWhcOJwWJ ySnSw8fdBSc18acdV6A6Z43JlgsG7+ic+BKx1kXo5TFqBu/onBTF62RU7PF86MJJTUKzdaEs INWuiCoXoRzAbGGT0gjhHZ0TR0LUurCAdDTvq1GMppuXlRYLHf369evyW0cpPRJucb7TDr5y xIkYGosRi8goT6HePzLxaxIBinKiaRlnhCMdo8feySiimibTAJccTuhId2DERGB6O7rX/53o odNllfuAZGGXgWh9PUMSYhDixewcDgCvm0UDCxskPVeM9MkiBLzGutEhDF2IwVEJEEKWVXc7 jeslCfRiW5mEtro0XcsezvNusfdm98RLsycCnU6X4Bo5YVIJgFKbw0Cqly0zOp2iQxEx0l9O 7wAmupUjwfdixMe5BOZ4Z3sCfC9yUpZoj3aRn9RVsRC1RyO59PpejJ8/N+57kRMZ4vGiYv+X 9uNwL4eP70XOsEE464ItEsEF1AIAFprNGwCX2RzB5bBwG81JWaIcuviq0ouz0SiYii8Ejkou lZjN5rYXzOxuV0cbN9PlxJ3AWheX1fc8XYFpbCbquTSbH5PfXxi43gm3esO8o3MSgEzrYqNU VE9TatMYnXhE9eTxhUxYe5wZLTSbfzXh2xWSBEcllwsBVJi9l2azGRu8iUMauhwEVgjBw+jr tWw41w0YOrbDG+8XPnQZyUQzdInhzuhQhy63A3vD20PH4UQLIdmiuwsAQLb8fliXoVkvTgM2 CRmXInupqSPEpnI4YSM5vagPsvV/hawN65KP0TkphsR70UKl96KFFdJReDiXIJRSi+jaMdaU lRbzMfpIJtqV0RjR1dFGmLfocHOqtilhkbwBvAG8AbwBw7UB0TDh5tHCdNRsNlEKNophYQCE WGLhJSkMVq+/58hrb16KogRdse5oY4s7YJqV61ZmAA373lK5N2mu/o4J7x8+eOZyFI3gcDic 0Jhw82jfyK1VO56tflLhaLiro21r1Q6z2ewvC9t3Ld18QZhxNxPuhHhmqVkLykqLmfHXutLi ccwQbFzO2rmZyCpcOzfzoQfWjQPm3ZWz5P61WQDG5nxttfZr9xd87f61AB7csAZjNQ9uKBib u+zBxZOyFq+5awoAYMr80kXeIx3n6u6dmymEH1h/DwssXn9PJnB/yR3scnXJ6txMAMicXbTh zlszZy9ZNXsMAGTO2KCX2UneV6zLzLlLlzMmM+eulTljACBj+vp1i8UEgkCflFeinQ6gZO3d APRrVuCjk61n/+L7vjgcDifxdHW0sX+qd1W9y3uXjZjXgZaWlgMHDuh0OrO5hQ3Ss6feJs2w prQYA534/CPo1j0EuM+8//ujFx56YB3cPW+euXLP/WvRchb48/97uTtv9Vom1gHg8hVgjNt9 BZmSsibll96Xv//VrtX35bsvYwAAsGr9PfjoOLv/p9fefGD9PS837EfmzPtXTAcwe8HM2RnT X244jpJ5Ohx/5Z0rq/SrMgAAmQAbW68s1uHCCXf3nzOKdSuB116/wgbmLI1kCD+xZP4EAHdO OvcRULL2bkfTweDvmMPhcGKN9MQQ1XhVVGW9oE83+VGy+FO+DEs1Fm8AbwBvAG9A0hsQDRNu Hk24Wy1O0rl09UsWGHsTN8PicKJC/ifk7mHeAfrdPW53T+CVxiaPH4Gm5h6Vu57IptNXAqdU xX3aWW9vbDp9RVlmsFb54uvvwNsMeWlNflLGqt6ICfze2N2Tzc4AydynhbtNdieAdnunb+LQ fzueQoV3Is0YbiH2V9+wv/rGfg/2V98Q5TuHw4kA5bBoXWlxWWnxVHYhini1nGvkLjOYQFR8 CfqPNK6ZM0aWkiVw9/QLKS+c9BWW7h7M0ZaVFq+Zc1klmaIEd48bF+rtnaqP19TcwxZ4RSkm /QngdUlGoZ3+nlqsLpx6Fa0VPg/iQw34PIv0swrpV8dvXWtWjenHlbGrtPD8Furtnf1HnP1H OpuOXGg6cgHAibHaNYsAd8+a0sJ+XMkqLZC+Cu8HWJD7suztfjqA7Hk99YqFtNudwTJBVXzv 378/aEYOh+OP+Ope2gewZLKfe+4ed+bMTD83w04WkKbmnjWrZkZXhg8DnZhcEGHeWDxU6PQf aZy6KI4+qxSE9bYvXf1SIcRL77s3Do3icEYKXJ/O4XA4w4dRAJgf6bh6ZYwr3WeXAODbsjmc EcWPJrrX/dfR4OkiIhSLFMU5P0QllFDYAF3Qp4sCvaKwKL+wqOKl84Ezb63aEWI1oacMNzGH wxnJ3Gd/N1lVi27lCEC8/ok8/5KKj+nY/G1dHW21G7MqNtcByPeIeEsrALCfUpj0r9hcV7F5 d35h0d7NRRUvnUfrbhVT+b66XgiF5O86DODgriIxksPhcMLibro1WVXL5DgAQOltLnkoZXrt nnJpgG1Lrd2YZVoetKjpXa9sW7mnDa87K7a6ujrqfT8AANBXt9pTlK3+wcgbzuFwRjZlc88l uwkAVIR4rDcShUd4Wzx8JXvtxiwAtXvKa/eUI7t8Ggt3PA/4fAayy6cByC5fAXTtXAqgtmO7 EMnhcDhhMnHSp4oYdsqKweENyy+Vh4SLkS6rNuJmiGN24vGAnlrj9BB5tvrJmKcMNzGDq+A5 nJHJN1oOi2EtIYSQXVYXgJoSQrRWdnC5QWu16QFgFyGE7GKJxfVPMVKz/mFCiEEp88NGlOZJ 1MCEdPQLh8PhpDJOiQSlkrDNaQyQwBupMVJqjKYBHv/k0ZQRG0KS6VurdjQ3N8e7KQqGrm0l h8MZlqgOvQkgP3cuyfjTvZwP7OMx9jgMQeY+zEKG28lwOBwAwLa0bye4RoXqXDR9SbqtixSZ TD+4awv66gCgz9nQ0cYsDtXNV2KNoaSLUooS1ZPjVbAU7o5rezgcTorz0RfpCa5RYbBIKUAB 6l0dTQVIV0fbvIIlgRUdqax72Vq1w2hsBt9HyuGMMJxO5/Xr1yHqxx0Gh96mBwyE1ADV3dSo AeAA9J7/OBzQ6yUliJEwEL2NsqRsBdXs/9xOk0n9lsXiN0tiYKfR8TVSDoczVJEuh0LPLFxg o9QmiZX8RybQZZE2KiZlZQbwDWAyAeJyqFTlwmR98gbsYcj0Z6uf5CuWHA4npdhKK5NSr0za kxSyeGHwcXqq0NLSwj+cnHDZWrWDps7yXGIZ9AyJY3sCXLjvk0jWSFNBsg9VW8Z6e2NZaeJ8 gieMu8r2EEIIgfB/QgiE//pcyOPhG6+WGH4LgbRA+IkXG6W8I49XRIKQAIXIK4U8jbfRvs80 wt7GN++6Wewnq1atqvyFff6Np5LWU1MAG/7yHIDwpXAMScHvqcKWUTBhVLUqIYQQotxBa5BE WrWsK0ojHYQQq0tZDgs4DIQQrZaEuX9ruJszXj7zrBj+/IR1IcWR49UVP9jx9rYp3kS5xRf+ UAwsGDiyGUD/20/2v/3EfAD6jb2H//mD/1yD4m+cbf2nsy/di3Xl7/98tavFDODM/n+cB5x6 86en3tg5D2jY9+O8ex56IMGPx4mU453t4r9ktyUlqLnzQnIbIBXohIBArl5PEvJxep+zwf8R GZQ2WF2KNQbYKLU5DFYXZj9FZjtpJdFKI40aPaWUEK2Rek8y665eRoiBUpve1l39uMYIq0Oj B0CIllKfA89ad2P59oO7ilY8sq03uxwvbZl29zA/B+d1oP5BvLLumQ1Nj7GYRfOqCCEvEUIe +NYna96daDwmJL3vDmAi1m8Cjk+9q5YQct6Ut37pTx74xdpzP817fPlP6wkhxf8L+HPOlre6 m03/tuVnx9c8DJzKvbde+LK++fs/it9YDmdIYTj2+rcJQSzsXpi5SwOlodi9iFgsgMcMhjXB YjHDDABmkxmAORmWMEPHlrGvrlfi8EvUvQwbW0amT+e6F657ISrpxLwy5t94aiTr039z93sz fqZ04xUrfN+2KirHYiRviMTOxEhpu5d6e6PkahyONr6d+EYklrfrN8eqqHp7o4lZXYUP+3Wz A7BiTlwLj1UtMcnOiSuzn7h07WeJrtT3A5pq89yUtnsZlqugQckvLGLfWzEQOJm/u2azOWLJ wr4HcRJMcS1cZGvVjmjGIjHJHlleTojUr1vEAiGOqUMk8LxHWhVLSKl8aJ5sET9U7V5GLEyU R+ONR1oCC4ifEHimbwHyiuEAHx5ppKK6wK2SNkOaRbXNqln8VeEvceBPo7/HQWivixNXHmpM uw4geXYvxOMtXVY9TbIGRiHTz+cXlm2fj93vqnRWQgiwTLGMaSCkBssodWoJOQQAlZTaiGTh gi2HKsphtxwGUlKzbBkOHapsoDbl6itHVV6wyMhEia+49JXRoTcsgCSVRobYYDGBb8C3EH8t D0VG+yskFHw/LWFl58SWyVic+Eplti5ILY+MDBW7l2lAT+EW36SB7V6clLqsWo3RBjiqu6lR 42Drzb47vcKzexmRxElYBJabYZUQtJB4D2D9lR9WfIiNVDxpxG+PE1s+Is8RYkWM7F7E7CSg 3YvM1gUy40WSJEMXBUPH7sUPw8zuJdmt4AwZmMp+JNu9bMv46wOvHg6eLiJC19GrHEbKYhI+ fh8Cdi8cDofjj2803nk12W2ARKsOUYwnVRuT0nYvI5akTIw4qQYfSAXmGtkLPJf4egPNi1JA tx7hGdOcpONirhi83hpchBBCQj1UhLltEC8IIVIPDtJbrBq5fwcOJ/lU0pht5ggLIp5w5INw SkZSCS7T5Rt/hsbd4YTLqmUOc4jWSogWcBGtFYDGyNaTD7FkVm1OA6XVy2qYWGdC2WXVMk86 gowWy3JZDQ79Mkkt1dILoHoZRCHupFRxl8NJBWz4i/fCYRAHIgbP4MbAdt8aHBC8USlHPJJI h+p4yPdgI18fL0R+pl3Sh+rqMr2isGhvn988FYVFgQ60a438VLmKl84f3OXH5KOvrhfYu1nF IGeY4mB98amqQ0aNEEWp06rNAQC4iMFBKaUNlcwBmtFJ9UDVITDLUUopIeSp2U51E1GNkduO coY6t2Oc90JvE43sbJRSanOwQEMls5Oe7aSUlipKkETqVQcuUmGtPjwnSR+XK1HXp9cGNNIK fBfLt0fcmtqNWYCfwrPLP9hVtGnPyLEe0zOzfptnYECdRgBGJzWyS5sGAPQ2qfG/1ARCJawx Oo3exE5JAqNT1jMDX3I4qYAO16WXin0wnvONbJJL5UBGGml02hARopRPERfqMpmemooU7918 88hRuXA4nMA8/GBCt7P4WxoVbV2SLs0ZMpke2L9Kat4dlnDjUQ4nKB8P3JLI6vyJbEHWi7aM yZbsQ97uhXtK4nBGJv+77StJqVexZOpVtSP5Ah2q+vS9m4s27WmzFG4xdTwfekH5uw53PdKb /+K0rp3Ze/uypr9YtGLnyNF9xxhun84Bt08PjuScI4eBlNSwdSMDITWopNTGnASgsoHa9FYt qTpUqdC5SyOJ50yMoChcM3rV6Ckg0CHK9O6zXj/RRRbafRbf/MO73WfDKOgPG5d0X8cfNqL7 LIoAbKRhZeeo4SCkBMuqqbCy6SIkR3IJQkg3pRoxuctKcqqYGzXfsuSJFSUrkFUkmogtq+52 GjW+qcNphvIRWEv87G4Pqxm+JXOGPeneoN7b2WyU2gCHxxsV8+Yy20kplGdkipFWrYFSatBa 9WH2H1/Xu6GkjCuCTM+ZMYRHBNIP0vBCTyl1GIjBYbTpQchTlFJm48jMs6TWV1pC8gH4rP6L yE21ZCUrUFTk8a9JVAV60GYYCMkTvCn5PILLaug2StsVIHHgZvi+HM6whxDZGTnR2L0woxeb mkD3uzQqymjqE5NUVPTpFZvrAPT2HQaQX1hU8dJ5Zhsuhi2biw5KUlZsrut9aQtzJVixuQ6t u/MLi9hx1ZbNRfneGE54EEIcgN4myKiGyhoXYNWWdKvJLGdDZV43pbQhlAO7FSUr8K3IYSAN oTmKCtwMZckBzeSDNsMgOb488MvhDEso/UYCalE1USdEolIXpXpqWPwKfhkhUd559OlFple2 Hcwu31+4xfTKvb3AB2LYcy5oxea62j3lYMp03Vt7b9/++k/q8O4btR0mS2tWd01d7T+jN7v8 x4VbWIxpeewfYF7BErsdGF5+Gbk+nYNg+nTul9HpdF67di1OhUdwdlLS3Xgxv4wqMl0kxY3B mY0jl+mc4QqX6YFpbZ11/foLcSo8FJlOU8Z+kaHia7eisKi2oy2/cEuXx+JF9dzIiM9aVHXU HrQ0MZf0CJutVTuGsd06t0/ncELAa4ZhIAYbtWmtLqdRY3DABgP0NsChteawBRhJpBcx0mEg ehsNuhijdPbio1IHki/fVfTphXgv8e3gcDicsCDkoBjOW1YDgIlvmx6uM10A4DrjNGpcVoMs UoIYqbeFNNdR9friPY80NcwZZeN05shF6s5l1apVMawsstLEXDqdbmvVjhi2J/VRnG6MJJ2X FqAZvodzhnKQdCg1iqX5O8Y6cF0RVOovl+9p1+GWxok3CpdEgtdSjRGAxmiTRcqRRkZjMcXO sUsFPUyQMzF0Op1qfGSq9shK85drhBNYqClOQ45tdVJhp1q4ar1ik0I/BTS/sCiUXOLdWAlc RaWK46QVd6WXXOInkq9Q39OO44vqyoX3sDokX6BDIdOlmnRGbPXpvtTbG4OqxUegPj0oipEj 5AJUVehEWaNv+ZAIu1AOX45AoKu2P2ghATL6a5u/2qWfRsVd1Rq5QE8kgziXgFqoxPzc77op i0+NtWqZTN8+/71eAC9tOXD385uyk9QijgSpjAglLI2J4fH2AaoLq5awWuKvZF/pqUgZ+DKs 2v3VFfj9cxIDIacTUkuQBMzlS4oIdChkuuCdfOPzmzwxMdSn+1OFBx1uj2R9OofD8cc36Hox HLXdi1Zvc4a1CVmmh2HhFFC8ILA+vay0OIb6jYjVNdzzIofD8WXSDX8Vw3nLagCb1+7F2qXR M7sXvctq0Bht3kgJYuQZPKwXz0kKDbaVFFJ9Ok0JsS6T6YWLAm/0HEfpdGDal7htKtKng0zG l1NxffrMj6fe/tF0Td/kqZ9Nzf4fZH+J24AJtyFzN276Zvyafrzz7eCJOBzOMGXfFzf9whOO 0u7FaDMCsIVj90IVNukpI9aD2L1wOBxOajIbXySxdoWenapFJgUu0zkczpDkv/DX4IliisKW USrBidT0JamSfcifc8ThcEYmo0i8nL34Q2rOqD4kT4GtpFymczicIY+BGABorS4ABgfgMAAA HFqPO2ZJpCSXJ9KgtQLQBvNTLZ5qJIYV/1IBLtM5HM4Q5W/EUJT+XmxOo8OgdQZbI1W4UJfd YgP0FBDrXJ/O4XCGJAvod8Rw9P5e9DaVu4FRLpPS1FsjvXbtGiGEUurn5yeEEEqPBC2UEELp eUIIpRv9FRhaIf5aQgkhfP8ehzOSeQcdyW6CgFeepYAto1L3wqSt70/p3aD4y+gbH1ZRERfC 4XCGH1Jfu8lCVKML2phkC3SErnuJWIYmPuOQJsXPluJwOCJS916pg/oaKVtEdlm1LqsWADsv WFgTdlkdgJYQuKyEkAAnPLFCAAAOh6KQgLCMYvrQMw5pLBYLF+ic0NHpdCO8w/ieMc2EBJMV DoCJL8gjpaimDB1xpTR1jF4QeJyuMTrZo9JSOyElwsBZYywhZNmyUCtgQn9ZdbeskBAQ09sQ XsYhCj+AlMMJC0J+C+xhYS0hh4Bl1d16o6amhNQsq6ZOI4xOQgiWVVOn0RvpWasDoJoycKX+ 5JBg9JICA/ZAZ0wPCYbNGdMcDicsyj8d/933/hCnwlU1EL4CXbZ9FEmW6cxsRNC9DFGBjqHc cg6HEw2PnvxqgmtUP4yUgvoxTC9+zBygtDjdFcbpQ1oydp9dAj5O53BGGE6n89q1a3EqPMBK oXS0nlKro7Jx+lBkhC8QcTgjntsTXJ/vWmh28WPF2RAG6t7h+sKFALAwG6gwV/gUs3AhFrJz 5FTvmr2o5hVQywvwfaQcDmeIQunNihgHoGenF+nhAHKsWnGbqBgp3f6vmjIA0lH5Y2bzV4Fv F6HtOEAkdo0AcFRrNm8AgA1tL5h9ijmqNZu/ig0AVO9+hg1MqdT2Qq1q3g3CXd+8QGzH6Xs3 F+UXbgEAHM4vLOoFAFgKi/I31/mP5HA4nEhYihViWEsIIWSX1QWgpoQQrVUPaIxOQgjRWqWR kOhVvCnXP0wIicxgesKtqXU3dvr0vjrLB+Wm2+t6s8tLNtd17Sm3FG4xPavpXb59Gg7v7Vu6 +ycqkdGcZF1vb2RH63F9OoczAkm8Pl1dk54aJoyIvT49uxxbi/I3nJsGdO2Zll9Y9K2O57F8 +28Ki/I3927KVo/kcDicyPhC4sMrMUjtXphu3VyxUFWgVywEAHPFQpV78byL2OpeTB1tXR3b AQBLuzrapomRe8r9R3I4HE4kpGEwWVUTsnARAQDT3qMyB16eNdKTR4GFFebao6qroHG7C/A1 Ug6HM0Rp27I/wTVKdC9HFfFyB15HtWbzhs/asMHsb400PncBpk8P7XE4HA6Hk+pwmc7hcDjD hHp74yiEv3lHdUU49MjoS+AN4A3gDeANGOoNCLBVNTIm3Dwaoj7dbDYBROG0gIJYzObY1srh cDgcxsqVK8NKf+DAAX9ZDhw4wALeNdKWlpaWFovZbGbHURBiibSdkZI564E78ccD70deQsaM +xbg1YNnA6aZvl57+0fvvvXORyo39WtWAH9xNAU/n4/D4XCix3dvUL290WQyHe9szy8sEiO7 Otrq7Y06nc5fFnYLCltGszAql80I2L6eEJj8tfsLQksJAKX33Rs4wdSF98zNBDJn3r/wtkUL bwPG3F8iPOEG/SpgzAb9EuBWALkrVuVmKrPrinWZGLN+3WJgIoA5y1fOyRBuXe458s5HuHPt 3SVr784EMCmvpGDibO3dszPgaEr+aVgcDocDoKujTfzne5dJfKncZ8hkektLC6XUbDZbLLJB ellp8bq5mRg3u+ye2ePmrlg7N3PtA+sAPPTAOmQVPrQ6B8gc50m85v61a+5fmzW14GuLJ2ct XnPXFNy7YU0W8OCGNfD89CGz9L6lLDR2ztLVczIA9B89PvvOWVNnTz969MKRoxeQeZs8yxXg JuDPACZnyMvKuUuXMyYDcAtpPgYwaYyyynf2vSWkz7gJwMCFq7dNukmtbRwOh5NydHW05RcW +Yp7r0xnQ3dRKSNSb2+stzdijpZJ7c/dlzMzM9iw+Pd/fD1rym39Z7oB9+eSLG+/vO+8vJBL /ltWet+9gNub0n05M4MJ6Y/cGdPn3IZ+AJPvuH/F9KMNQutfcbAjga4C2KBflYGPT3kLgPvy lYwMmQhfv25lBj45fVm9AW7XkYbOjzPG3HTho6v+m8nhcDgpBBPovuN0rz6dUkoIaWlp0el0 Op2upaUFOsCje3Gfdn6OycicWbYIv/9jB8ZlPPTAOgC//+PrSx5Y99BCvPnyPuCOr91fIEjX /h4sXLoY6O/326bS++7F5XMfAuIgHRnTH1iAP772Hrs64rq6GO8BWL1gIoCFJavhujoH77k1 SyYzyZ45AwAwccOKGa+2ngOAMbffV4BXG49j8sT7inUDnQeQMR0AMGH98umvsTQAgDvX3g1g xdq7G/adLFk7FxdOOvwIfQ6Hw4kfolxWDLoV+nRFLhbjG0+Y6t1sNrEtUoRYADOT7BSQ2b2M m122CPVvnhnaJkT+10gJIb5rpMPSiIo3gDeANyDpDSCErFy5UqHoZphMJtV4nU7nL4tOp5tw 8+h6e6Mg001+bBZVbRmH+qvkDeAN4A3gDUh6A+Jhny7I9NiWy+FwOJykIOwj5XCSyKWrX7LA 2JuG8EmKHE6KwGU6J5lcuvrl/v1e73pBdy1wOJzAyEZGTfbGentjvb2zqbmnqbknUD53T729 sen0Fbh73Gp3WaT7tDNISj8IBpQ+ZQZplW9DTjuF2n3aBkVpYjsVKSOqFwOd9fbG+iMXwsul SuD3Jty9cnIgULKmI53sWU66AVzo9y0znN+OUCZ7J9KMYRaiEOgA7K++EWYrOByOjBu+93fe s0J6BtI26Bfn5U7qOXcRwKwJF+sd7WSqZmK6Mlu7o3dt6fJZE248eaj9cKcrm1x4pfUEmarp ONRzrLOXfPbB4U5XXq6mo/Vi/9lBacq8qWn1jvZxuZr25s5jnR3ucZosny2g7Xbn2tLVebma puaennO9LJn73fbDna7Ro29hrRqXq2lv7jnW2e4epxn3ofOV1hPZuRqfZl7oSZ+7skAzK/28 e/DiYPr4dCZ00sd32BvbTrlGj75l1ujek5g0Md37RHD3sKf+5Ej74U4X+exTVm/PuYusuiz0 1DvaTwykZQ+e8FPvlZPIXlmgyZuSwUoTn5cMuHpGa04e8Tw7ehTPwmI8b7JdfHD2hlXqSh// 1ukrs665JmakD6aPf8veeOzUhbyp193p49+yd87KzezHjWNxYfSUWR+7MXi69/3BzFnXesfe mD44eLHnvfYDb7vycjVN9sZjZz/V5GresjceO3Ulb+pVafZ99sYTA2l5M8Yrau45d3HWjPEY vOitd2bm4ODFjkPtbZ2uvFxN0M7neP1N38gpWdPTvxLjtSMOZ4Rw4pRLLtPZXynAZHrPyTN/ BT4+eyUvd5IiZ1buJAx01p8mK+ePzS5YnJl+/cTZTz/+LG00sEE/d+KEtOyCxelA/7hJSxbL Ur516OIG/eJ2eydGZ27QL+5/05mVO01R+MmB66wZn3T2/tWTrHD59OyCxefPXez5EJ4S0jfo F5880nPp/MC80uIJvs/n/vPozPHpANIHPxm8lp4+Pn3w4iCAwYsTCxAa3sQAACAASURBVBYv yNX0dLaPXrx8Zrrsifo7j7OnXrl8SnbB4qkT0li9AFh1rAH95y76r/e8UC/QJH3e5beMnrP4 /SM9QDp7qJOfZSqeRXznoz0xSxbdkl2w+ETrCfW6gE9aT7ovY+KU9MHBi8fPfgoMjitY/LEb WTOvjh28MjZ9fP+R1qlTNB3vXfgYGVmf9n7yCSZOSR8Exs5YvGBqmnvwYlbB4gVT0waFwNX+ zJmS7IMnTpEy/Vzfer0yXax35i3pwMQ5ixfkZp50Z/gOBRScOqMy+5kxYwaX6RxOZJw45Qq0 KjUWKCstLitV8eLSdOQCJheMc18BcAloOqJ0C3MJgLsnb7Iy5djPzwD4PEv4SPSNm+xbeNGU ATcAXLg0VyNNxjajKkoAgLkrpuLKSd9pf+bM15t7ALTbj00FLgHuDwcAIPO2EwMAgHGzcaRR 8UTSp74kPov0tXw+ELxeeyeA/iOdKq310Ddusu9d1Xd+KUBdwJIluJRbAACZY7KXFJeVFk8F Lh1xTs2c2X7aDeCEezaAPLiy5tw2Nxfnp8hH0Jljzrvh/nAAmWNODMD94YAsu/tKWWnByWan SsWSEsR6BQY+8p1+cTicBBBHW8b+I41TF/n1/9XU3LNm1cyghYSYLBDuHnfmzJhLmPojF8oW 3RY8nRoxeKhwaB/AEpVPZ3wI820rFOirV6/m1i8cTsRw+3RO8hHFOhfoHE6UcPt0TvLh9osc TgwZBWBewZJkNyNyLBZLQYEpZ4bSSTyHw+GMQEZB7dSMwGyt2vFs9ZPxaU/kfN+4PdlN4HA4 CaL80/GLl3cs+nXAQ82iIIAzFrPZzI4PorKzPoWzhMwWs9n/kZ9i3pjfhcdHYxrCH6eLhyQF ZWvVjtCLDSsxh8MZyTx26tWl/3Y+eLoEQgGkgBWufEmqry6/sMjXyXrE6HS60D8YoX8qOBzO COc6/XYSa6cUHufksn+pgNLMoIGdfddXZ9lcdBDILyzK33UYQH5h0d5dMllfUVjEPgB7W+t6 Q6hJSL/rMFp35xcW5RduESMrXkqt7y2Hw0lxWje1/Fa3NHi62MHkOKUwmcySWDY+TyH8mo59 a0/bitbdAFC/7eCuoq6OtunyBLUdbQ2P39HV0bbpdrBvQMVLh8VjT9mXQMb8bV0dbb/GNghn pz5vaRUiazdmxfShOBzOMEdX+/43Wt5PZI3iYNxiMXsH5gQgXnGvlPjJIKA58O3Tt7/Stn0+ Vuge7AX21wdK+609bXi9t+uVbb2eL4EyxbtP5xcW2WZ4S+n+gA/PORxOJJi++k12xHwSETQw FEQu8ZPbKrlMzy6fJg1kl2/KxqY9bVi+fRqwuiy0Ij1fAiXzt3V1tOGpl4TLvjoDH55zOJyI MH862FIxK7ltYEKcaV/EcXrSCWPP0Yqdyh2n0zY+D3i/BLV7ygFMAzYB2KNMzO7WdngsDrPL VwAr9pRH0GgOhzPCycfkHXsnHfyNcEkIwbJq6jQCDkJKGijVw0FICQBKKUvQQKleXogYSQgB llEa0K+RH8Sl0VQQ6Aiie+FwOJyUZCq+/Obcc+IlpZTunA3AYSihlJ7RGgA9pbS7ehkAq9ZA KbVrrdISpJGVDTQygS6FCXeTyZxc4R6JTFe4YAycMvQNTaEXK6I8N4PD4YwMZuPaoyf7xEuX VevQ6wHobTKB+gheDKU0mx4AHGG2Qbo0ylQw4gpqEuH+XjgcztDjKzd8gS/yhAuXNafqEKoI pdRhICU1gr4FcDiNegDGF/MIIdXdFIDLqn0ELzqNGmmklpBDEHOFikJ2C5IdZpNJPUFi4LoX Docz9Dj+xeiVuEW40BgppUwi621UIpr10gRGDQs6nZ6QGOmkNBSBLlorqi6Hqlg6JgMu0zkc ztCjH2kDCd+Jr5DaUlJkgRSh6F7q7Y0tLS3xb4mS5ubmcJ2LcTicEcJx8gwA4JeJr9pk8mpX pFAKAphhhimZjl9C0qc3NzfHux0cDocTOmvp99/Gl4ms0d9IXDFgD+o9Md5w3QuHwxl67CPP /XDqJ4msUdU3gK8GJkVtGfduLrK0JrQdhJAADosBVGyuE39yOBzOP/ffEjxR/JGul6aCLaNX pve+tMXz8/Dud7F6ORLoMdFR3U0pbQjNPvRwbB0CczicIcfR7932rcTqXvwheAigqeKj0SvT p218fm8ffnz2b4GlhfO3rWjd3dXRZjgbopOXRLK0q+PpX/OjsTmcEcw/Plf2Lm5McKVKW0aJ EBd9NCYdme6l5ye7DTs9Lolvn34Q2F9/R0Kaoa/KIYSU6IOnBABL69IV8W0Ph8NJac4h7QDO eK4cDsBhIPD8JAaHsC3UZQXgsmo9kV5kkQ6DVWsIWqnSlpEI3rtSCtLV0TavYEkAq8F6e6NJ 1XIn/gS1ZWS+AdgZ0/w8Ug5n5OB0OgFcv34dXi9dBkptEFx3CQ65DFqrzWm0ag1Gp81ADDZq E0uQRhocyNtlMDpt4qpeANsVVQ/pBDAn28tuWWlxvb2R+wbgcDhDjy/od9Lwruh4i2itVJDX ekqpOCTPe9EIYP3DANBVWSotQRpp08O6C5C4B1A12VDdOypihhnxPEU6qJUkc5nFZTqHwxl6 3ED+TXpJnUbZpU3Q43q8ANgAOG0y5a4i0ui0IRhMgosnkQI+i6Kppk/ncDicIcE0+ujN9Lvx K1/qc1Fx3oXFYibwLJAS+b8UIKRxelL26M8rWJL4SjkczpCglzzzozGb41d+EBtzn3MwkmuT LiW4TI/ArXlMGFHOXp6z7k52EzhDkpFsGvDp5b9JQC1qZi1mk0kQ4l4NDE2VcTrXvXA4Q5WR fCbMV2ilDYIfKhJTFBVJ3QBIbRlFKPUeSZoKDFW/jFurdjxb/WQi25MA7irbA28H9fZUEGmv Fa4gTyOGfW5Ckk6ZHor7rEurJoZ6IZCmkVSqjFc8CPzEy4pQiVRJPDLeBvGRNfNvPJWEPpoy XCM1GfTvWDjcsyziRIqoX7hfRg5nCPCNxeOkl7/90+fJaknqcIX8K/BMctuQGl8TGVz3knI8 se9Z9+lnLp16Bg9+579PWC8er74TwAN/++m7v/yk819YmsPHnrrwzi8+OvoPQUt7/y1LfJvL SRSEkOOd7YQQi4X/TvEg/R6lfDu5CjKZ7nHHePigb0KHgRBidSljJZEuQpilvzfSQAghWmkG l1Wr9WQghFgdVt9JZWCGt2vGRdt/qn/jicw5j47NfRQAzu0b//WmN19d/9muO26Z/4MJBX8v plx75w+bcOv/ArB+U//bT5z/r7UAeg//c++hXXcA51r/6Wzrz/IBADv2mmvWAmsfPvPiKtz7 9VNv7Dz57zo6S3f831Yeb/xaMp6SEwldHW35hUVd3NMRAGAQ5Ac3zE5uG6RGL4SkhAMvyGU6 c8d4XkWgQzjm73ePWKVxDkMJpbQqRwuAaF+jlNr0ssiu6m7akC/9EmiMTvzuESbHq5ctM+qN y1DJvgeEEF+/jBWFu4HDe/tQUbgFOJ9gD8CJZ97MSe+7+jvYOB3A9LUX/2vN+Pte++ode6Xj dAD73vnFmrd++5/Ah+Z5ADBt1cO/+Pkblp9MW7YT3xX2X7z8xB0Adm+qX/3jh7dX5O54pPn0 j3IBIFsLANkT5hX/v8Q+HydymEDnHkkZ9n3PnflitOcqWn8vWqsLjuD+XhQoXahLR6fJ89Eo 1acvLZy/bQWygD5VsW4gWqdnJy5Db5O0+tAJwGF16Y2SSKdRAzX/uQ1KLZSGNlRac2y+Prw6 yu4GlvZ8AMy/F8jq/iAxvn+TxouG3/yf7mcz5zzqPv0MAJzbN359AwiAd26Zf+zTd70nda29 84f73vnFP87pAPCDu370OwJSsulfvrUGr7+Hsx8DH89Y/p+EkJ6DZRRdZ1H2nexPZgNPAj+6 d5edEGh06EvokQKcKGEj9K6OtpFs7iJi/bsHXyPPEWIFQCnVA6SmktqgtzUQQoBlsDkBGB6B zYnXfpdvNKKyxg6JjJFGvohHSEk+pV6XAIF34Yt3Fb5fLMzlC1UmU80buOQI7jJC9Q3AHrVG a6VOIxwGA2w2PRwGUlIjLDo3VNYQUkMplUYSQpZVdzslotpl1eLhh0sIoZRWHToEh/UQaoBS UlID1KBbOMZbpGHGv+cXbuvqaKuoOcfGKZannu5FeYjNHoIcyZh9lBAyNvdRQsjNdpnBw4SC v2dXSxc8DkImLfwhIeSfFu8QEjlqpzUSEPJe439Mf50QEACz7jYRQtboLMx0Ys49/yQYYrzf Mu87yTvbnBMmq1atkl7OLqlKVktShEXad6f1PPo+FUY5Ufl7cVm7jU663uoI5u+FIfW7IspY lo+JeObykABmk1lhtJ5ofy+1e5isVPFkK7MW0tuEl2ejopszMSyN9LUx0hidTgBGo3jXSI2q KRnTNj7ftZEFp7NxionrEzkjj8pf2JPdhNTij/+ha/j7WvGM6ej8vej1ADTGEH19yyqSyC0C gCT/PNIh48PL870ZzrxdvzmGHhFG1EbcGJEaB9VwQuDpL194+pe4loz91yaT2df7uDAcpzDD 7B2oJ4OU9vcy0vSGgR3Zh0s0ju9ZM+Lkcieuhcekiphk58SV6/TbP824lvh6FQoFXw3NEBin J9HfS4Cqk9WqIURLS0vEb6ne3lhWWhwn2RTXwsUqTCZTxFVEn533z3izCen1l2/6WcLrJf61 K0zcJ33zAN9zlOokxXYtrt4gkuJqgjPMeML8f8syhM20JKaE2ACZD14KUJDUcA8wVP29jDTE zSbSACT7UMTLAHmjrz1omnDriiwXhzPdcvXai3uBF5Akfy8KN16eECwWz6JMKuvTub+XJCKV 2l0dbaLsYzEKgR5UOEpFv29e+PkqKEoI8CERw+L0QvEp8veM8JHv0gmK7/dM9alD//b4VhcK 4b4rTlwZtTnn+jeT3Abfr4mv/WKC4bqXoUT0ehjFVwGhyVxFCaqJfQUx5B+e0BupyKL69VJt eSgCHfIPW1gNE9+e9DVyksXtWJf4SimFyWQWjz1i20CIZE9p0k+a9vX3cj6/sCh/12FlwsD+ XlxW7+Z+h8Hj+AUOg3K7f/T+XkYg/uSIr4hJsKCRNkkqzVWFeIAPkngrxIG2amSIHzzVbw9n yHEz/e4HOJ3gSpXW6GIolWSYr7+XrK6OtoYZ/65MGNjfi8ZIKa1eBj1gKOmilKLEAEBva1AU E66/F070BJWSQUedvt8Sf2l89TCBvzfSW6qj4AC3AsQHfhA+yh4GXMSb9yHHcxWlvxdv9sDI zsSQHF8nLpOmAr7+XgAcPnD385t8kgbx9wJU5TcYERKh+3vhJJJYSbpUK4cz/HhiasGPP4yV vxebmD1Efy/+FmVZrvh5dInI30tf3cHs8k3Zyuig/l7gsjbYjABsDfmEkMoGCjgIKQHQQKn4 IsP198KJhoh3zcR1VTwBS+7swSN+/Jhkjzcj3Crsxx/+l+mr39x54UV2GZW/F0n2EP29EKIU 68KVyWyxxMujS+T+XlT9zAf19+L1luCN1Ufv74UTMc9WPznC/+yHMXxb0zT6qOWzZ3ZCkOnR +XtRZg8FItG9SCPN5iSfN83tXjgcztDjsZnnx3jOI00RmJRPui1jSvt7SXylHA5nSPAPZ/+w FZXJbgXgEeVspZTZMpphTmJ7UtrfS1LqTTojzXMZxx/R+JwZCTxLap7Gc4mvV9UvI4PS5Pt7 GTK+dkcUEftT5HBGCJQW/OCGRcmo1+8tQfdiTlRT/MD16RwOZ+hBSOfTX76QjHo9B9SlKlym D1XYLi1xZ69VG96mLQMh4oZeh4EQrWQ3mcPg3Z3BdghrrT4FcDhJppKGfSp0rFA1dKSpse3I K9P9rUlurdqRsndHAoRoIRG7Vi1hkphSSin9XQ4BAJf1dw93U0rthADQenqcVSt4a2AiWuvt iQ5UV4tV6G3dsir1NtEUDBojpfK7HE4KsIA++nJCVMdSn7rsHzt0VHTw4v2XgNaEAB+nDxm6 d56Q+dtxGAghqO4GAM36Q1VPAa4awAE4GyqZEK86VKm6NVdLSmzrA1Tl4gNzTopzjDwzgF7x UjKbdHgmrA6pP3TVWawYafAzx/XVnit1L9IEqeH4JbVk+t6XknG8YEpi1fr0Dr1NGJV7Liml +VU5LgDQUGoDNJVADgC9raZEC4ehutumLASAy/pwdwpMETmcaMkQQ5RSunM2PE6ozmgNbM9j d/UyAFatgVJql49UpJE2P0ufbAAuhVKYTWavKE8BIa5ATab31eUXbvGbo68usE+7ipfOR9aU g7uKNm3cbmn1U+zmOuD83r7Iyh56nDjE/utA5U4x0km7qw4BEolfA4jOFBwG0lXdzS67q0FK atQdLWiM3AEDZ6gziX5/NiaIly6r1qHXw8cJ1SOejabRoNCxmC1mqG0iTRESOk4/uCuQQ9QV O9sAmJar362tPHdwV5mvI5rhimfgoGeqbb2Nsk3OlFINYHQKXUnqU0Fvo06PtNYYnd5behtT jzulHVBjdHpFu0a+NzrwJYeTfP4HX67DX4ULlzWn6lAJEfwyEkKMTjZDdbBObnwxjxDCfL+I 7r6lkYSQkoj8whJf74zJRk2mZ5d3dTzvN0d2eWBvebUbs/zdWrEzCh+ny7d/F09HmJfD4Qwv /pv8R9mmN4ULjZGZDEBQSYqSVbrUTz2+X5xOT0iMZNmj9wubAiI9xfTpgenauTTZTeBwOClB Dt2sq30/WbX7GsOImE3mZLWKITMGCrwrPTXvcjicEcgifPFo7n0Jq06uNzeLISL7D8A84qaI v5fjne2qrl1YZGreHa5wLx8ccDd2AfkteUn3N4k7gNDXYXrKMpR0LyOE4f254vz/7Z1/YFTV mfe/R2t3Vwm0/kKEhB+dRAkRYqESGBBi/cGE0o27KWxLgLc/zNRKndBdX7pt3p073bTbLPtK RrHdibV9gVAXzNa01kxQa4IwIVjQgOGHmSkgARGrthqwW6We9497586d+2vuTCZzZzLPp9N4 7znPec5zb4abZ555znOsQ3/aTfh19eS6l/6QyRnlvBdx7zopzZGBZ9MXpJD9dIpvEASRQ3yu /dAYZEX9dNmF5wCypC6jUXwjJ6C/RgSRh1zBv/5lfGTL1Mpau2IuI2OxvY1sr8tItXazDvor RYhQ/XQTLrD/bOP32ZLdrL/jaCzgbmUj6BFE+0w/XbsNrSsHtw7OS2KBz54mLFhfW17R2te7 dfU9q7Y86ttjuHqISAjVTycIc67j953Fs/IpYwzzm3nII25t38G5K7rHvZiuzhjr0GSgy41+ J6vvqVNsr2wV8TnOAESrCAiCANvzXpSOYc3VB1tXrgcmrSpE7ertrVucWwcn7Vx2T2vfo2WN e/sbsBvzAuVNrX23bh2cJ7bHlM1cV9u4967oGfmbBEGMEIMX43x0zjmCYhHSKs653+l2hQKc 84jfiWhpF7fT71KsiFY2loQ4R9LLSOVMGA7lF6SKyAxsKAjzMQCzZsW8wjCAE9Kx1zc3fAIV QMWTh8In8OTKueETuA7wPvkLZTsATPwFTsDrE1Ov6sMn8KWJwMRMZGIdPGj3VxIjhpuxFiDM xaoAoisROw26WVV/s3LVvpOxHkDrjGiFVZpVKCcKullVi9TO9ZK5kjJDdQmiJf3N4ZBeAZqk zNBqJkY3Gyav/NmZ645cfFA8jfidYU/IpVfvJTRiNmjLe6mQn/WZfLhTLmOWEnSzas4552vE N07QfaSBc86Lo+8jVdFzxljIeH2zUlitWTOxciJxpTXnHAb7+SZhhuYSVGXcUzdDRzMxyvnO 608M4FXpZNj1XhoZY6wxBTNiWYxcJ9NRmfKYMT4GoHhqDn8Pc/Cg3RaMDLK7IdZnDLa3VAcC MHqyRvzzm5sZY/MNfF4TzSr0Jwq66zoshBp1zAgy1sh5SFezk1WFws3Op2PTmAibmJHg5hCj lG9dGv3Gz+HhXPqk6Aooo+IurYDDEwppGkMGC4oMmmPfgsae1VnjTuj46VtXq6sn1q7erjN0 cHtZeUVcVd7B7bEa9dh7CvDpDiQswxgTQw3FpfPNJXt2gHPecKTYYlBQ1qxCdyJ3VUvAWn0j jRku8Rmto1mnjLuxsKkZCW8OMSrJwH6kOpsZMUBZ7wXZshWGjOaZPrh90Zbe/r7eU4M4te0e +eEuH9eubiorl3au6Ojr7X/q9lNAWXlFWeNesVE83rp6XdXqpicObVT1ElYJuhlzy49dhydU 5fQDkZb5esEKhwc9OwC0tyDxszdes0aTzkQtFj1gHTOC4t57Opp1yrgbC+uYkUCYGN1wXnMr X2vL1GJ0RWGJFHvJEqS8Fzl57vCepqJCACgqRNmJr/T3zRM3qaiKHU/p71shCleVVwA39fet KAf62n6KNbdjTxMAtK1b9dS6RYUrvrN6SlG0ZcYT6b9on+1rtkYOl3rrFfF7SMW3kXFlzUUP 12i7ljhhjWYVmolgmuNlboZLGVrXaobDozhLIBxvRiLNxKimDBO+XNFvowHa726ieY0CvHZ6 7lJ+emxpw4KVtdtOt64crN1WWN72AhowbfK8MKA8luno6y0CsKepta9XCsJMnrL+qV58VxG6 ibbQ6gmCINJFzVVvH/rtNLutUKMt05h5tGuOJrWujP5cuR7AqkKs2iI55spjFK4oEg8WrAcg bqNRBKwCsKVXPG7dsgKKFoIgiLSw8+0rx2Yq3qH5XCt4vRo/ncfWHGVLrV0t2bxoKHcL1BAE MXx62aaL/KuZmUv1+BYEQRAE+UEv5Z5nzdekimf64PayZRshR1SAmuol2grOPp8vtZXrhw/u S0Gb0agZs+aO4mDOKL40wjpUP92cS7F/RPVrv3aSPHGvAK2fnjXE+elf2NTrRdPWQciVXuSH S1l5RepbiUZJ7VGVbw84+ghCiOTbOz9JJgOl0eNgEC64mSvAg27mCnDmDvKAy82Y+HW9slEe HycZRABuuOJyAYy+BdXpkp/+WfCg18ReJk9p2rx3VfzOn6p0dbtIy98VgiBGBa99hDsYYwDE dcuspY4H4Ap0MMaA+Qi4UDdfXIcR1xglrrGKMaA5HKgvlp7KusUV5Tw7VacXAgCfTwqkmxdm HLleEZ14evlUdT3G/r7ebHis0wOdIAiZS3DqYtRzZk5/NNXVxTln7iCA/v7lnIf8EXgcsUYF scYA5w/4nQ4HPLJC49iKGE+XTzmH/HdA22s+No29iH7EV6w5KlzhXQAUrmhdOUkrTc9TgiCy h2eW36g8VS1NEGMsoZAHgLy0jeutQpYbHZ5Uin3FHujIlmVHZnkva+u/rdue2nekqWlLrw25 hfjZSP5rah56kj9IjdxfX9EApVVGx6ohSgstmicLq6awfjdUViUVuEvqzusOIUaaO3ccY+yY 3VYAqlg6B+xeB2n2TN/U/EPd9tS+uklNW3ptyC2UDwiLj6RkH14pWyXOYnRsMjCpWYxGyX9d Es6V2q1QjcrAXSWS5TJe9yFrSSyXJuJzYASvV3LPdSI0QkYMMoby07MXpetn9FhR+s4w+DZ7 +M8jK9+mqDxrpNtpVdqgvRtaF177qWI4mPxpUZoE+iY/Uzy+5KW/7yzJ2HRy6S4ZHv2PtBmp JJcxiwyJe6ZvXV3RdAjrn+oVcxnTm5+uS2VlZVdXl4lAfuani1j3Fs2/xE7XE838yZ7JB1lC Pz0DkSitPRmYiJD5fuc8xh4Wj02+z0wBo/J2gGKlaPx3pIrBiNvnyI5HvOKZvqcJ3+/tj895 ofx0GzGK6qpixKpfzXDiyMlapesFm3+YSDmervoEYDHIk9Bai9doPpAe6Jnn81e9/fI70rHJ U3iYGCakK5C6REmWODtlpIk900+9FsFkfaFsSGRE/nlDRs9K1YHyp4lwuuzR/v2wOGT48XST qdMbWLd4jbo25NVb1EZ87/z8Cv71kZ7F6FGu/COSDXW7lMRyGYtWepu+ux1A3DYXALLmbZol ZhAEYTucl7yHi3bNrrMvXXYkMiJ+T4xJ/VtWIFphUQU9TwmCyB4+jsWXsp/YaIC0E6lIltbw 0pDe3PDKysoURuVzfjpBEEZMwV/dxeV9r4Zb78UfgSesrvdihdiao6x5prP+vt629s4cTQ0U sy1nzfIWT913n2e93eakziP+JgD5kMxDpAXx32xbe6d52tgoJhQKAddevPg6ot+RMubmPAAE GasC5nMecrudLS09nHNlo0JHrFEs/BI9AEwrq3i9sS4GCD5DyQwjviXM/HSCIIjsxHvll/xv j/s9f0g8HWa9F/G5D0UKjWl+pJTZIu4xzQRBTnpBFtR7iT3Ty+csMJEGAEzmvAiYOgaXX4/L puKj6/DR1KvevX7y2xMnn50ybXDCxAtjp3yA8cA1wCcXY+wvcenfJNKZIocPvjhCmgmCyH6u n/x27dtj5NPh13uBhe3ZVcQe+4rnv9crKAPDmU9RvySxCEEQRJbhfnnnIXzcrtnFL0hjX5Py 6Avw+YS4rJiMQ7EXgiByD85Lnsef7Jpd9bDmeo12Qc90giByj8m4a+WYd+22Ihuh2AtBELnH Kbb9V+fHiccsrVg0QBl+sSvMogs90wmCyEXenIiPxCOeVkymFJ/gXq8gSqmD5jwrVpPSM50g iJzkGfZIhmfU2Vpa+RzPjtWkFE8nCIKwCmOQnfTshPx0giByj8cXz+v/1idtmVrMVkR8SF1+ eb2CvREYeqYTBJF7fLF7b9mDf4ieBYNA0M0Q/SmuDnVHfWllo4yiMQgAEX/CSZXxdG3gXYyt +3yCvREYir0QBJF7dNd+6tXDDjFNhXPuAlhLHQ/AFegQi7cg4ELdfMYY5zyuMYqiMQTAvQaB UKwkgO4qfJ8vrtiLGvEp7zOrFWOkOS29IvRMJwgi91jc+rulfEmsPMvw6r0AKN3sgYV6L4Ig 1V2J2xZD3pKUAYLZkzej9V4IgiByBc6Xva2IcQy/3ossZhHtc4rEzgAAIABJREFUUtIs+daU 4ukEQeQen8SkyjHv2W1FHCO2K2pyxPz0ixcvWtmqlTH2R84ZY0c4Z4zxc5wxxl/kYtxK/GlF iSxs9HNYl0UQxKimYdob/3j84vdsml27H2mWOOkgP50giFzkP45fD5yya3Zl5UVp4ZFeJowt JB1PFz1o5U9tu0UlRgrJSScIwpwJuGQKFtptRYzs8dNjz/SUn6SZH0gQRJ7zMnsYALDRRhvk B1j2PNBBsReCIHKTcbbMqkphzKqKjCKUy5hdiLtmEwSRiHc5tyH2whjEHPHsdNKh+0x3M1bN uQtAxO98emnIE/ZHXDuK3SEppR9AxB109Df6QyGPmzkDcVtxxykp9jsdnpDfyTyhDo0SfaKz B6Py1RYHjgIOH9wnrhogCMKcYv7NL131tnzKGMP8Zh7yAEHGqjrEJxjAGKvr4AFXXGMUXUmr BihLviCbnuw6z/QA7xBXVjmfXgoAwXaPy1VS1wIEADiZOxQuBTzoqWesHnUdus9aUYnDEwJw pKdOpcQEaXZZPgiLA3Md8tAJIimEtz/WED3mnCMYBBB0V3HO/U63KxRwB6Uv7ZSN8nBdyVFA 7JkedLOqltiFRfzOnvoeAAg3R4CB/vnSH7DmB+BwIAzxr2LQLa+K1VECwMmcIR5CxB+nRIN6 YHGpJP9AqfnA0cF9nvV2m0AQucSzwmNv/75APo34nWFPyAW4ArGHT0ujP+Dy+CPwBHSe1/qS w1hNGn16CV6vnW577DtSVyBujw+HJ8Q5n98chsNTzNiRBinAshlrGHMCQE89Y6y9Ou5mqZQE 3awHPYwxlRItqoEx+UQDCYLIQyYLxbN/dE46ifiL63uqmFSXkTHmCQUAhJfvYIx5HHGNEb/T 6Y8YSSZEWZdRfok56nJdRnvjMLp5Ly7ZKQ55HAA4j4WZHJ4Q56GACyHOle26SsQntZx1bi1W Jc0uy1seSBBEvsDYwdiJwyM/Z5TeoeiYahvFx5qupAly3Fx8as9ZJcTyXjQ7HM2uFUxUjVwv lLGXwwf3mYsSBEFkCUv5fSWX/k8mZ5R3OBKjK4CArdEYi3L7OgDAgVbBRNXI9UJ+ptMXdARB 5BAhfPTlOw4mlksrise6BOdRPz2K4BUgZNaseD6GaNXdHIX+GhFEHvIHHKjZuf/DjM/LGARB UO6MIcVkpP9D8AnRh3ph7ezB1gNGmkaql9YcEQSRezD2Yiani60wEje9AASfILY8JQiqp2ut IMjfts4+kLleEXqmEwSRkxTxb2ZsLp2cRa8g++YqWk13Ixq5XhGq90IQRO5xJ7/vu58esGVq X9RDj5XY5cpVOkDhktrZAHC/cL92eG30uSzo9coqRA2a5iWChOFYyU+fMWtuzuW9rK3/9qbm H9ptBUEQNvAMe+SZl/GVzE4q573ILT7f/YL3oWi35LbXfvXqVgG19y95SAjNBjQRkkjt/Uta H+oU9HoTxF6+enV0S9LZepoB8tMJgshFVvN7K/ha+ZQxxpx+AECQMRZUtLuD6sYosUbGmLSU 0hTlqiKPZwkAr/chrZveKhwVBOGtEATBqfvYbX2os1YQdHtbhRg6vY+9Fe1cZvQFKj3TCYLI Pd7AJXsRy2XknPOGEkSruAw43QDEKi4BV1yjjLKxroNzvVqEhhQuufLKCp9P8Pnul0PtXHbk C68BULGsQneo+Fw2XLJqIboCAHjHqIO+IyUIIvd4hj3yOX6ffDrMei/iSvUgYHHFuhwD4Rxx 1V044BVqUWsSITGPnwynVySNz/TTZeU165/qXVUIX3nFEzPX9W9ZAewtK1/X0ddbBP1GgiCI 1Pg14uq9oJ5xzpXVAMPLdzBWr2qM+J1rsDnkcSgbnYz1JLPzmuhrA/D5IAiCcpzPJwiP9Qqx L0LVD155bNp7RdL2TPeVb+vv6wUA7L2tr9c7uH038Hz5C/19vbXlTa19t+o1UjFCgiBSgfNl jLUBjwNivReP2O4KcHmrBYcnJDarGkMayVCShXb5qU6gU/LOhbhMR0EABjsFwXgt5Mj1Akhj PD2MJwHUrt6OPS9MBlBYdHIQT8ycAqAYEf1GgiCIlPgkJv2Ffy3Dk4qZi16vYFS6KxtI2zO9 eOY6AMWHnsOCW18DMHhqSiG+cOgkgDAc+o0EQRAp8Uf240vZtgxPKue9LLlfAIDZtYVQVNyN ouzVMnK9ImmLvXi3FJWVV/y4rxfA8+UV985c178FC/tuLSuv6DBuJAiCSIGL/KvTcbldswf9 AvwAWnX3mP59NCdlUG/syPWKpPE70nnReDq8fb1ea40EQRApMB2Xh9nDwIMZmEsVbJd2mTaO ukjlcA+0ZrhXhPLTCYLIPb5XuX+pIpdxRJH3vhBfgk+o9dXKIRdpDb9i6VGtUAtAqJ0tZhyq GLleEcpPJwgi97i3q/yP7BGg2S4D5Frq+1UpM14BQKuQaXtkyE8nCCL32Fhx7MA3xmdyRtkx 93qFrd5WZUBG6cX7fAIrWiIIwmNHp+uv/n/srRHqlYwRQ9szZs31+XwpXqtNdHd3b2r+YVt7 56xZ3uKp++7zULY7QeQLl+65+fPTzngGdoyQfpbSRtHynqW20N/X29beyejrSoIgiNEBPdMJ giAIgiAIIutoa+/8mHwEQBC8pvJxcDCfhX2UZKyHp0ZCkgwgA8gAMoAMIAPIADKADCADUvvC NJNc/Ym/Fg90s9MZALGeoyAI8ft3iORYfgxBEARBEARByCxatMjips1t7Z3d3d1dXV1JyYuO dLKzCPERcB03nXO+a9eu7u5uSG66D4AgeDkXP38I2iGYdHPNnFjy/9CroZ1Hh6zYZMCEuZ+/ aSLOvfirg6eHoUWf62dWf/pavNHfvv8NM7GCT91265SC8ye7dv3uPXXfdZ9ZOuN6vLn/6Vde B4Arbrx1bsmY9wd2nxizcMb1UaHzkX3PD1yIU1kyd/GnpJJDZ/u69p8FcO0c14wJ8pDfvdil HDJm6uIFk8dceG3X7hNxd3PCjM/NukbSc3DXS28AuObTd5XG9Bzfvyus1DNlkXMyju9/IfK+ svHW+UVjLpzaHTopKi9wzFk4TTLvjVd2vxy9PQWOOQum4nd79w+cN7thBEEQBEEQo56ycv19 SQGYZ5KLA5Uy2hYVOm46Y6y7u3vx4sWLFy8WnXqv1+v1YteuXbo++rjpC++44Qq1az6u5K7K aQXy6dDx554PvwtgUvnfzx5v3njs/LSJADD+ls/feQvOvdj9/vTFUwvOn/jNq5d/djZePIBb Zo/H2Vd+8duzkz5zx2euw5kDz7543nH7oqkF5y8MjbmiAADe/O0BfGb2tQBw/sRvuiIaV1tB geOzi6bIpg6F9z0vO6RjplQunQIAcf76G799+Zq/vfnaG24Y8/rABUyYVjIGr7/ce2wI6JA2 0po4+7bZjrlzhp7ffxaxlvGSd15QMndxeeUcdO0/++b+4JuiwPWfrpz9qVvmDHXJQySumLxo yWQAuPDart0nUHzLok9dfv53v+0OXygovmXRrEWLCvbvCv/+pZ27JD3li26eNufTQ6L7bsyY y8cozibMuvXm8Xjj0AsvvYECx5yFNy28GTFPnSAIgiAIghDRdaxN3HflKKVYwgWiukkvHNgF QAyoL1q0SK4CIwhifF1QSr97dHfb0Qnzqp01N0Sbzh5sOwYAGDr+7G8G3p10c82cabffcv65 oU/dXnJFbGTBtNtvOb8PM+dOwJkDO3ujkXPGLhQoo+lji6cDGHN5wZmDvzgDTJx1i+HlvPni UxHcOP+zxdfeOLb3yacOTvrMHZ+5buqN10defN34HgxFfhu+5rZiybCC4rLpZ3uPiieid379 TX9785TK2Rd+eSDqt77+SlfBvErH1IkDv59w8zU4dzjmWxdMu23hlDEAzp98VeFwnzmwb+yt c4vLK5eVRwULrsDZCwBQMLVygc4QCTGaPmHG52ZNXnTzhV0mIe0xUxY5J48BcOG1cJIe9tmD Bwqcsx0zb62aGVU25nLgfdNBBEEQBEEQxEihXzl90aJFYkwdwK5du5SRdUEQtJ46cHZv+1lA nf0iUjhxPIAzr599F+OBK4Bz+37ZF8tmmTR+7oTxE0uKx50Ov4uCGbdcd+a3F6Dl/PtxiR8F Y8YlcZlmTJxz+2euw1B4329exfTFc28YoxGYcC2A18/Geb7vvfrKwHVzZ1ddC/z+wIFzQJyD 3vXCcSmTpKSi0nG5mABzbHfXMQATypaVX4Nzh7sGLigd9G5VZks81193DYCzb7w5NHTF+U9N HnPdtQXhN6+/7nLg/TfOXlA66C/sOZlSvtGFgdALAwCuK62aeTXOHdsdIR+dIAiCIIjRjzYQ PhKFEFNIepEKMiorvURz0ME5l511FYsXd3MIZpVexKQXMZouzmT3Wt38NUA3N92yWvPc9Ny4 A2QAGUAGkAFkABlABpABCslsXkIqVnqJFWRU4APEsoyC+HPx4m4r2tW8O7CzfSCVgUTaOX9y 186TSLUC0VBkfzCSZosIgiAIgiBspLKyckTlhzNKJi6aPqLk+Uc3MoAMIAPIADKADCADyAAy wHYDUotaZhJ1NL2meomt9hAEQRAEQRAEEUN/CSlBEESe8N77Hz3//POqxttuu23s5ZfYYg9B EARBiCT/d2jo+LNdx4ezd1E6ySpjcgu6daOPtPxOs+eNMfKWvPf+R+2/fk7rowN4/vnn23/9 3HvvfzSS8xMEQRCEGcZu+oj8jTy3rz0U3QTp3L7955KbSCN55tWzk+ZccWQ4Oi0z9GqoLabz 3L72zmdf1SscOTKzD9ekJND7HenMrbjGTF5v+8Ez0dMz+2PHNjOsO3DhaFf0hg/vTkb/OUi3 ZejV0LNdoX1n06A5zaiMscM2EwddCTnrBEEQhI2YRtPfHdjZ3tkmvQ6eiftrem6f7DAl8Vd2 /KRJQ4d/09m2/xwwfq6mwnqMswfb9p/D0PFn2zv3aXf8icrshWN6gbnOc/uiGoZeDUV1Rr2i sweVbp8ZQ8d7X5+g2Fd1/Nzqm8cejZwx1ybdGV0botd19mBb1/GhoePPRsda9T5NTFI50FLL haNdmpupmDeK9n5a/l3L06muTnEHFDLJX+/RMfOqZ02MNkycM2uiye/37ME2+UCaUfWbsvB7 0V67joz+/bT8KeKK6TeOOfzqOQBnXh0Ye+O0gtjbRnXbpZahV0P79h/cdxbAuX2yAdF/DqXT zx959QJw4fTQhIpKB44dH1JpNv8FSWhujtHsqVxy/LNFqtlq8DZL7R8sQRAEQeQ+prnpYu1z +XTo+JHY8YX3xhWMFY8Lpt1hudrMxDlLauaIh+f2tb8xSeF1Yej4s785O+mzzukFwJiCcUMX hgCMKymdoKvpwtFj52fMGZ9I54X3xpVUTACAgusnjPvNG2duKMC4CZPEq5pwXSEi7w1hYoFG vYqCK8a+Gzk9NG26LCnfAa021Vh9G6LXNaZgHICCaXdUi/a/PIgJ8+YkssfcJF2Gzp2GZIbM e6+ffXeSQ2Ww+n5+tiDp37Xq6s6+MTiu5C7l1KldL86qf1lmv9+CceMKpAPJqvjf1FkLvxft +3zouFomzsjkrwvAhFnzzoSOnr1wGjffMQEYki9NfdtLp0eOnD2H1yeUVo4/3XXwDIAbZxUA yn8OBTc4xrZHzozFexNnFQCl1x88PXTuvaGSUlkzNL8gxW00vLFzZunPXoBULln5bBk6/ux+ g1stCSf/D5YgCIIgcp9Ul5AWTLtjzvFn2zvFrYvUDr0hF4527T4sjSmY8VnnRAAF00oLOne2 D4ybvrB00sDe33QeBsZNmgBo9CkkK9B3+vryOwoS67xjzrmonRPmVc+aOHT8SKym+4R51U61 V63P+LnV44deDbVF00EK5y6RPAkdbdHZxauIu1dRG9T6RS8HAMZNV/vNyZkEVFwfEk2Ku43x v7LC6SUAxt7grMG5fe2d701feMcNVwB697MAE7W/a+UdviH+erVMmFWDg7Gin+NK0nK9mHRz zRwr9zaK5jc1fUyisdr3ua4bGrsbJWOPDiR5XQAwcY7jdPsbpdXTzKaunFZwgwPtkbGfdRYA 029E27GCuyoBYOhV+Z8DgPGl0yM7j00QuwquLzj9m5fHzl1i9s+zYNodN0q/IMM3LQD92VP4 VRrYYHSrU/kHm4Cxl19y2223JUx6Aa0lJQiCIOyDmexQqi2mPvy6jWnSqYmaW2fo+LP7UWHp Q0UcRqXlx40rSUFbWjAyKQvLa57Z37n3tHg4YV5qvziD67V6san+3jPAsP9RDOOfg00k8asc 4V+cbpkXEXLQCYIgCBtpa+80c9MJgiDyAe0iUXLQCYIgCHuJbW9EEASRt5BTThAEQWQhkps+ Y9bcwwf3iQcjNJOon9DS1t45a5ZXPC6euu8+z3p77SEIgiAIYiSYsafst/j4S+i7eDHx2phs gzGW2kBBEARB0O3iXKkf4ED8JCZjhzNv1o4FoMxziUXTRU995JzptvZOr9ebXp1Ka9P7AYM+ VBAEQRAEkV4C6GXsYBn/pt2GZAtqz5/FOe4AAEF2HlP9mJDDZDTppbKyclPzD9OoUFyI5vV6 0/4BQ9SchWsxCYIgCILIURg7CKAfRjvCjE68XkEVp2Vx/4nvSl80fRRgmpE5uL129fZTmTIl Nbq7u3NOM0EQBEEQeQtjbfGn2UsKV8e5+gWAMTAGBukVFR3efcwDEi2cOrSxqryirLyiTPTX B7fXlt+zVSySrHDidzdW+PYAe5oUYhW+PQl0n9p2T+2208O9Ai1xny72+kSD9zSVNe6NCZQ3 7VZLEgRBEARBjCCc16zldW3xe3DwLCaFa5Q8csXL5xOifbEXB7ieT696eb2CJJqXJHLTZ67r 6Ovt7+vt37KiSGq5fVEhAOC1k30lRWLjwoZe7wLs7n7yC3UrigAUrnDXJGmI6DHLHwOUB2K7 6iPBcChc8YMHIgHxE4LqcwhBEARBEMTIwNjTm1jL1zo/Y7chNqANsSthqpfSxWf66TH5wDDK kC1Y37/4hTLRx23cC2BhQ+9t3RVl5RVl5U2pL2CWPwbIB9D5SGCNvb7yn0576tFVheqO1068 Ujx5EqD3OYQgCIIgCGIE4LwawJcv/cBuQzKK1ysYxeVld1zti+dxBF2J6RLSwhWtW0xbFqzv 74urHriwobe/AQB2Nz6ZzlJDC9b3o6msfB0A1Gzsb5hnbdg8b9+83Y0VZQPrOuqAtnVlUjLY Teuf6vUWAoNpNJEgCIIgCMIM4Sr2wZ9XAx/abUhG8fksLwPVRM3l5ad5WOYFw4qmm2Il5l20 8tHWlZOkk8IVrVtWFIk/5VPlwYL1/WLYO6GPLg+JWtK/ZUWRPLyvt78vGl+PlyQIgiAIghg5 fO/8fNv5cXfdHdL0BN3MHYweOf0RnVb5yOmXBkX8TqkREb9TGhWT1EdXUqHJHnQWnnKAw+cT pHB7XsLEIupi0fERLRbe1t7Z3d3d1dU1clPkIpWVlYsXL6btjQiCIAhi1LNnz4S/w7Vt+ID/ 5T/lxriVmkE3q0IHD7gU5y3S8fzmcMjjUIg6BwIhj3jid7pLQuKooJu1V8c0qNGVjPidxfU9 qmlUlV4yUBjR69WZggGCT6d9tCJXA29r78xc3fSa6iU11Uto2yAlYnV2giAIgiDyg3NTLh33 xw1bx96vzrz2O1k9mnkoEJ/G7QpwHhDd6CMNCh8dQXdj6eZYVH7pcjwdgcsBRAb666oDxhbo SQY31KM5zD0OAEE32xD0BFyqzw9p2oXUSvEY7TSpfULI0V1IlZv2ZHR7I4IgCIIgiLzlS7hp 40c/2viP+PB+dZcnxD3GAx2ekMq/dQVCrjiBgEcWNXHS9SVdAS4rUx6njaRKO/L8reyiZqRy 0wmCIAiCIAglj7O2y3jdan6v3YZkGmUZdSuScmlGQSzImK+kJ5qeb8kbXq+XsncIgiAIgkiK 6/gXnrznl796/Da7DbETraceF2uXj/PYO5dJW9JL/iwPJQedIAiCIIgUeIM9Mu8n4PyN79lt SQqktCepcfhcoU0tQg56FMpNJwiCIAiCyBBF/Js/unuXsiXlpZkZQLmKNM1mMlG/7qxgIGcd oNx0giAIgiCIjPEBPqp90qls4VnMSN8NZc668mMAj1ZSz3OScdMHt9eu3n5qxEzJAoJupthH wHx7ACOUd2n03zGCIAiCIJLgLMKft9uG7CFuP6PYwlEwWFpvOuoxcNNj/uXpravv2Tqo6S1v 2g0Ae33lmt7cZn5pMQDAVV2Xso5DG6vKK8rKK8qWbexT9+31keNOEARBEPkKY89sYT+22wqb UbrmcY3S3qPiOcAheIX41vzCwE0vXNFad7Kqce/uxprjdY+uKozvfe1kX82tCwFg3m01rxx/ baSNzCQ9R8IAgGB7SwJJY2au6+jr7e/r7X9qXXmsVfzAM8+7ZUXRcI0kCIIgCCIn4bzmCv51 nY6gm4k4/Xqt8jf8ckt8M+B3apoMMJKM+J0pphIkg0kqixxHVxdkZHmaqm6c9LJg/Y+x7l5s 9C7Q6eqY+tOy8oqy8ornF/fqCOQqrgCP7q6rOEwDe5rKymuaDr3StKyirLyidtvpdCkmCIIg CCJXuI7f9zmMv0m3gIcrIOWDN5TIjnLQXYUOsTUw4BQdaFmOh5vn11VLrorf6S4Jic3V7XGO vhoDyaCbucOeUPP89FypdRjTeOdEFLNKLwsbevuV54UrWrdIh0UrH+1fOXJW5TKKuxQ7XrC+ v2+9bSYRBEEQBJEFvMEeeRrg/E7d3ojfWVxf1qGIEprtCBp0r8HmUJoCin5nVQvQwloAwF2d MFBpfXEnAwQI8MbOdTLOyTU3gCq9EARBEARBZIJ/vmL1F/k3GHtG3RHxOxkrru8BWqoYc/oj YnMswcXp94SUvnPQ3Vga8jjkc8/m0kZJtLF0sydecUyhkaQnxDnvkFbl9Q8kvBBVhRaTlzJx hWt3MlK+CA1UN50gCIIgCCIT/NuFTrAhnQ6HJ8Q92mZXgPOAriZXQBVIN9Cg02wgaTabKeaR dWU0XQqa82gHBdETQdF0giAIgiCITPAX/nngTxf5V+02JJ3oB9GjcKOXshQjhdINSI+b7vV6 u7q60qIq+5kxa67dJhAEQRAEkXvMwd8A+Bh7zG5DRhyly+7zCeZF0FVeO21sJJOepJfDB/el RQ9B2Msj/ib6GEYQRAbw+Xzd3d0Z2OWRyCpeZlu+yL9xFS7abUi2QxsbiaTHTW9r70yLnlzB 6/UmFjKgsrJyU/MP02gMkXboYydBEAQxEizltSfA/idfVwYyphMmV3vk9NFVQdreKN3d3XmS 9yL6cKl5cvn2eSanuaVGqqzJGIP0HGHS04TpnIGp/iePiR+tGKlUo+gzmECpWTNRvGaVRSql OqbH/8fgQnQsiVqjuVLVRPEXHK9V70IMRHTuZvT5rnNLdTQb3tL4C9G9pLjxOr87em/Qe0M5 qwkzP34soQwxWnkGH36Avi9hjt2G2Ibqn4gyvyX6bzDDFmU1efp5jiAIgiDSzhc/M043iNPW 3tnd3V337+2ZN4nIKibgr06xF8HzyE3nHICgm4XAlD45eed6UKWXDLDXt3r7KbuNIFJlzn8P bDo/sKnt7vjmu7/27hH/HzuWzubA337lD4eb/7BpNv72K++8svHthz+tr+nGJXtf3nDuySWz ANy4pOfAv5/dv/ofRtx+giBsoKy8Qv5JEDKLcfEv/Gs/xyt2G5I5lEtIVQtJpRIvLN5Hp6QX BcZu+uD22phzuddXXlFW3rQ7scKgO1pEP+J3xtXTNxeNSQbdjDF3MKGkwXAd9PoVbRG/UzVf Mpzadk9ZeUVZeUXtttOAeN+afKsrysoryhr3Aqe3rl73xKGNVeSp5yZrAl++C9j57bU1TxrK fNoxHsDvjp+VzhfXvn3owbcOPbivfkIC7S8c+i8AN9y157c/3L12AgC+tPb0vn97Ye11cNUO 9n7/1PY7bgKA8d9tuuOm4ju6Qv/ade94ALjrH07s/t5vvn4t7lrxuxd8v/tBGbtzRaRbiHz/ JgB/1/gvA8//y3/eAXyqcudv/k/nPeMB4Paao89+N/i1a/mnFnc8853DP3E/vfM7hzv/7m+H eYMIgiAIy3xP2HwJLqxBmU6fvJWR06/XKjsqsS2PWLy/5HdqmgzQlbQ+fJgoXXbZa4/VeIGi SiOH4BXyefMji9H0ed6+jV+wJOkKcHFXrMjTO9C8WbFBlo5oePmOYsYY24DlqN8QBICgu6q/ rm5+S5Vy0yxdSd1GI3rqizXvPalN3PULQMxhj/idFt+ne5qqTnylv6+3v6/XfaLGt0dsnfLl Lb39fb0dU39auw2rvr+ufOa6ji0riizoI7KNw8ffAPApx0TxdPWPH37v2MNPxEfWX/q///bJ GfVzHnwdv/zplTetu+qmb10181tXr3gOX/6nt37luln7Rd6NS3q23TYNePb5PgCz7pwxLdrD nm6dNPefb930xvLKUgDP/ezZVwDg3PfXP4vbS6fKGnb+19SF//LZ/3xTbuDPbL/78bfg/LtA 3W1fd+Lk44GvP4sZt904RZZ4rm36Hd93/UQecuyBu34wY8kvfjms20MQhD79fb3yT4JQ8l+V J8fiLzodrgAXaSiRHZCguwodYmtgwOkOxsnxcPP8umppkyO/010SEpur2+McfTVGkh6xsQNV I+6o66B02aVjBih2MI0jbzYuTX9uesTvLK4v6+ABTyiUSNbhCXFPxO8srq+v6+AuAHBV11W1 V3MeEDW5S3jApS9p0GhAXUe4tLG4vtH/gCv60WF+czjkcYjzHJEUNtSxKmdpOBQKw1ns9IdD Zp8zAEyeUt72wu6GeQux9/m2m6atAQAcem7X4IpVhad37XyluG5SoptAZDX7m/51zL9P+rdn /nnoa3LbuYEBoERHuHbTxocWx05/97P/uLr5rM6KsmNILY0kAAAgAElEQVSd82d3/sPGf28W ms4Kb/5n7YPXP3PXnlbPmdVS//GtDy3639/Z4aod9H7/lJjPd2rX577on/LcHV3/b+2JlZLY iW2PfPZkTOsrgU3ri4SmLy5E6Bclj54DcPjRH9/QVbmzpe5YNLfm5PZHXd0p3QiCIKxBpQII EwaOFtX8497Fd70EPKLtlT0o2aNxBYy9m6B7DTaHzJ2f1OgfANKp1+vVz01XoUqJAQAe28EU UDjreZPInn433XAPWosDYm9JhyfEzSQtzxdV5FIIOmKfIpTzuALRFcfWLqNwRWufeDTP2zcP AAaBmbcvKgQwadUWMY6yonVLYk1EFnPmn+9c+x1VEYzDPxnXLleEkGhdu65VU3oixrHOeTd3 yh3/te5/b4+Vhti58Jad6moewW1FndHpxInCz1UueC6+UMX2T+2M2fXf3/X9QlVt4nddSz7b FV//4s2qO3dZKEdBEETSPP7bd0uq6nW7jNqJvOLOHX/6xPZ7/4A/Xvyn+I6I3yl9t99TxVqi cUQE3ayqBQAwv5mHAooBQXdjaSgUCyV6Npc6GasSRcMhlWJZoaGkcqawcqI04PMJgiDodinr M6pqNer8meJ55KCLGLvphSrnMuqGEuao7xuRq7zYtjqxEEGMWrjiJ0EQ6aH/W++VPfhjhnHq DoOYoyvAub7P7AqoAukGGnSadSWNZxpR4laUxj9vdJ8+eealU6UXgjAmO3ckXVv/bbtNIAiC IFKh7ME/AADetdmOTBEri84Tv5hmdalJlZg8IT1uutfrzZO9jRB13dbWfzuFV3d3t93mE1aZ MWuuXP9YWVvN3p8AFi9ebIunLk+anZ9eTMhdy1XYeyFZMjtB5DTF/JsAfnC9taocuU/Mt2Y6 Lx1fncdeBNKVm56Hm6tvav6h3SYQmUNZtKG/r1flPat6jX6qJHU1J/xpI+LHg66urpz79567 lquw90KyYXZ68BK5zhA+uozX/fOZ7gfstiRriUXMOQAIECDYZYv9pMdNz7eF7V6vN9f/3hPD ROk0y/63lSG6znpaUG6kkpRy0SSLV5FwamiudDgKR/rDidFNG47xSc2erll0fwUZIzO3iyBG AfPAVy556Vudd9ltSFagLJouIx8ybRPyLjk9bZVeuru78yTvhRx0AnrundJTUTm+un6wtlFu 0dWZ0J7U/KS0fGzQtXY4PnomfT5d73xEDRiJWVL7aETuNUFkmCmX/rlm5/5bQdvTxmGSdK7O fome5kmeOi0hJYhUEPe0El8mMkjJExqJCKucoiM3quKv2r3Nh7nPuUqh6sBkIvGzitJU3eHW FaZsvMnlJGVJsvfcSH44V5FezcOZOgOzE0TW8t9/ufxOft8LbJPdhmQUr1dQJp3Hss8t7FKk WkKab2tJ0183nSDyEzkQDoWfrXVHVBF03VEjbWcGZkkKrUmqbxgsjrLSlRRJpTMlFLCiTRll T2+oe+Q0EwRhnVPs4VN225B5lHXTdfNbwPPI804K42j64Pba1dtPAae23VPWuBcAcHrr6grf HnOFQTdz+iMAEPE7o4cWRMWjiN/JpD1qFcODbhZtjR1G/E7GGJN7TJDV67cpJiUIK5g4jqr4 uvJUdaA81RUzmUh3ajkCrfT75RaLqnQj2SOB+URas1XpQMkqNEE5SqVcq9PKLLq3XZUlpT01 +vZgOCTUrLJkOKjeftqbkLG3FkFkM2t5Hed3FvFv6vQF3aJbw5x+vVbZUZFb1E6Qdb9IR1J/ 9nSiW79FrvuSMKyenySOphetfLRfOhw8fuju2xaYi8ubiEae3oHmzR6HmWh4wFnM6oG65mbU bwh6Aq7ohqAR/5p6NIfl4fNLi8Ux1XVoBxCtzh90s/aElwCgp16cSLkFr9QGAKiTZnUWH2ng gWLNdr0EkfXo+q9av1N1rPp4oPLhhmOArn7dg4SqtD607nEKEeKEoXpdS5RdFi2xeHMSGmaO FT0mb4mUsfLeG85biyBGDT/DJZ9D8du6Dqm8wVAwGAREByTorkIHFx0rv9ONUMCl2Igo4ndu KJE8Fb/TXRIS3eCg2+l3hQx3UteX1Js9vSSMl4tpMBRWV2It6WVwe+2y5+566lErG5FGoi6u JxRKJOvwhLgn4ncW19fXdfDYmyLiX1Nf1sEVPn7PkTDgAILtLUC1JaPjqesIlzYW1zf6H3BF 1Ua3zo34ncVHJHsa6liVszQcCoXhLHb6Y3vrEkRekJ3+U/ZYlT2W5Bx06wgCwPW47Gn2q/+Y +mnd3ogmSCjHPnUIutdgcyh9DrV2ditYK3AueL3SkYkXHtclqs17lz2xm767seLeNgDoW1bR BJQ/0Na6cpKJvMFutUkNcESD6iKugPwuUBxGzxO/naLqXIp5HLFPEcrZYvqTvQyCyBA11Utq qpfYNW8uVjrKXctV2Hsh2TC7LVOnkbb2zu7ubqr+ns/81307Pvjgsl89XqDuiPidxfU9ANBT xVqicUQE3ayqBQAwv5mHAooBQXdjaSgUCyV6Npc6GasSRcMhlWJZob6kwexWsBL8FoRYbrpV GDgH41Q33YjCFa1bAKCoobe/IWP2EARBEARBjE5m/4j/bG7xyfNj1B0GMc5Ygou2RxVIN9Bg EAv1JBJKM0ZB94TBdUEQBC7kbVidCjISBEEQBEFkhjfX9d5YgL/YbUam0S2qyFh8fUYVnFJf 0uSme73ePNnbCMCMWXPtNoEgCIIgiJzke9MHy6afsduKbEG3FLrktbO8dtBF0lM3fRQkfRKE CWJGqd1WEASRFWxq/uGMWXPpDx+RGg8fnToVH92raGFZXNyEK6Lc1laL6uDzmUwQf8qAvNlh 1Aq0vRFBWCV/vjIiCMIEctCJ4VCmyXjhKfu/mSVl79ls+aieTvF+kLMOctMJgiAIgiAyA+er K6efOjt4pd2GpBMLnzIUBRl1++NbyUGX0XfTk02/rqyslCtM0VjrY4ncJVa9SodYMSuFWF2H tHFWj7zLVsTvLK6HovJVRNkvl7AtVs4l6Y4V6QLmNzeX1de3xPpLNsidqrpasj3zNbNqbI9H nLDOqKKu5lIIgiAIDcJVF+8/9iLw5vfwmN22pI2EXrVYkFH05vVder3dSSkxHSbRdOtf6rW1 d9LYlMcSOYpcvUrlnwbdrKofO4rZjuZwyONweDY371D069S8im7dBSDy9I4ezG9+wCVN0VBX XyVutyXuuFvVUtchzeMKhJv7lYpLwKpaol50gIdLtW5zxO8s3rE8HF6+prheaUH0WsRL0aD0 4vsHInCRI04QBJEawtsfAJ9g7E27DckQ0UB7LJquCzM8yXeoIKMxg9try5t2220FkYMs38x5 w5Fi5vRHzMQiT++Ij8c7PCFxoIgb1XWSGw/RMZ/fUuUOAgCC7uL6Htlpj9JSJQ1lmlB/0M2K dyxPJdrt8IQ45zzcPD/ZkQRBEEQcjLUxNqDXE3Qz+fke++sR1yofOf3SoIjfKTUi4ndKo2KS +uhKiocxdcNGv8aiAqYo8wLli1CQbG766a2ra47X9XoXWB6xp6msZUrHlhVFSc6k1FD72krz rU/Tz+D22u/iB323/mz19snJGH9q2z3fgVe0VnlMjBakoHZ87kdZicb5dQV42O8sZvUAoO/g OjyhMJzF9Y3+B1wx71nezCKaZiLP5PCEOo6wKmdpuOFIVcv85rAm/yRmV3xkPOJ3VrUAqJfs AVBf7ASlqBAEQWQazm/5C25SVnfhnMd2VQ+6q1rqOrj0cHYFOtpjov3+B1weh7yxUdC9BqHo JkdP7yhrEDcldVXXVbUHAy6jTdp1JcXp/Y1xkqoSNEntJCpXd/F69UdxwGdNYdI7mOb4WCWW 3PRT2+6p2nl7x5YVRZi0aktvcjMsWN8f9el3N1YEprYl4bbuaSpb+yQA4MmyDUDNxv6GecnN njLRTVi9W5KbsWjlo+7Ge7YOProK279z4iutDeSjjzJcgY66lqoqFksMD3PpeSpnh9Sv8S8N eRwOT4gvjc9hV6aUq0ZDlSRe18G1m8+5AuFmZ3FxFeo6uMLFjqptqWL9ytz0qC8el9aiyaiP b5Vc+WiOumpI1NGXus17CYIgiDju5Pctnvjm62cu3agJNfudrB7NPBSI75FCNxG/s/hIg/LB GnQ3lm4OyadLl+NpMSsxMtBfV62/dWmSkqoSNKkVjhQEKTddtxPxK1C1KenGY61MnXtjAdRU L5GPLbnpRSsf7V8pHg4rmr6woXdhUpYuWN/ft96eaPowWNjwledXN/kA95YVdttCjACGezfr 7basajPe99lIgSUZtdpkLEwwrblNI7/BNEEQxCjiGfbIzjPLPofLtF3mj1OHJ6Ty6+WgelQg 4JFFTVxvU8kEI0cGlfNP1RiVJJv0MqxoeoosWN86TA2ZZl6yMXiCIAiCIEY93iu/dP3kt08O DNltSPai2o5UXn6an447LSElCIIgCILIBL53nna/3PtvF7bYbUgaEBeJWnl5vYLOclJu8FLA GHw+QVpmmpfoR9MrKytT1khjCYIgCIIg9HgXmAy8a7cZacC666ybq21YBkblqUOAN38rwOi7 6cPZf4fGEqMPr9frNS/6ShBE3pDsrnYEIVPB1+7Fi4uwTNmY2tLMzMAtbDE6ogi+YS3HzHWS zU0niHzE+g5WBEEQBGFEL9vB8GbllXGlsGx3hTOM7uXqfFQRxbwUTQdAyRsEQRAEQRAjzGp+ r++dHzdgs92G2IPRRxKpwAsUHjkDhl3cMNeJuemUvGEXbe2ddptAEARBEMSIczNfsYX95Gdz 8zcwqinkEgdHXG56FmcDZQiLSS+nt66uaToEAF/YlEzR9GQR9zOaua7j+/jOsufueurRVYXi 7D5834vv1jQdGmEDCEKPtvbO7u5uu60gCCIr2NT8wxmz5lIuHJECZ/ER8Kcf9JbV2m1JNiB6 4Vy9ZlR7lL9YcNMHt9d+Fz/Y0rsKAHBqcO+pwXlFEBtXFEk+9KOrsL32uyeL8eQTh+7+cd/K k1G3vvwBadvRU9vuqdrwSqxlUCm/PrbtkbjV6OB2zLwdm+/Zukb01CGWbJ/SWPF8um8BQVik q6vLbhMIgrAfctCJlHmDPQJgAK9qeoJu1l7NAy4g6GaNpdJWznGt8pFzIBDyAEDE79xQEgq4 xMM12BzyOBSS+uhKWh8+HLgqUq5NdCHiiXPTdVevH97T1Fdya1H0tKhwHgAM6mqb8uUtvV4A g9sDhwAANRul3UP3NFWd+Ep/3zwAuxsrfHt6vZMV8gYsanj0tcZ7tq5Ri4yyVfaU9EIQBEEQ +cCtfO1JsPunnVZWd+GcA64AdwFA0F3VUtfBpTWmrkBHe0y03/+Ay+OQtx8NutcgFN2K9Okd ZQ0hBwC4quuq2oMBl5GjrSup26gqQTOcHHFxrM+nbAHkU1PFuvN6vVaMEcyLtDFA8BnqGf71 Dp+Ymx4+MTd8Qk9k4i+eXAlN11yvD38+gTDmVvj+HhcRjrUAmOt98sGoWrWS61byLwHhi0p5 7VxS73UrD113ERCnOCGNbW9Py7UTREpE/M7i+p66Dh5wSSdoluIecrfUou4Vh0qC85Wj1OoN OhMYZag5gc0WdBtcUdDNqlokvXrnw7BZIZPs3TC3WWtAMvpH6m5YtJkgiJzmAC7OxscCxydp q7v4nawezTwUiO9xBTgPiA+IIw3KJ0LQ3Vi6OSSfLl2OpyNwOYDIQH9ddcDYBl1J3UaVkSkX jky4DFQ3yg4AzHCsFTfYyvJTweAjwnCWrg5z2WtN9RL5OOamF0+lb/Hs4eBBuy0gkiG4ob5n fnNY8rwcns3NO4rr1/iXig5VxL+mvqeug4vPUocn1HGEVcm9Dk+IexB1yHR0u1lVy/zmMA8l 65yZaza32RzzK5L+gMj2V7WgrsPil6XpuBtBN6tq0bjZ5jZHZZzFO5aHw8vX6E6ekubh3A0r NhMEket8gI9eYJsAAA+quqQnogEOT0jl18tB9ahAwCOLmjjpBpLWh1sk3sPXj2rL6S5q/59y YKJcYrcBBJFjuAKcK6LjrLi+p65D9qXCR3q0Q3qOhLWNOkQG+gH01Be7gwAQdDPGnP4I5Lm0 iJLDs9lcs/UrSs4tTYjp3VBeWezaoiS0OehmxTuWm8aqU9SsmCK5uzGsdw5BEDnCh6wFADDO ZjtGHsZiL59P0A3Ec4BzwxcBa2766a2rK2q3nQYA7PWV37NVNzF9cHvt6u2nLE6rFN7TVKY7 0Eih3J7UjASRTiTPdkNJiHOuzGlwVdcBLe2y8xxsbwHqqi2Gl5cunw/ISRKuQEcdeuo3iMoc nhDXkoRPbGizuWarV5RmJz3B3TDH3OaI31nVAvTUFzPGiut7gJ76Ys0HgFQ0x0j+bgzrnUMQ RI6wmt97Bf/6ZXyF3YaMOEqH2+sV5LLocS9m9iKgTHoxWshYc/XBppKN/eJKUMzz9olLSLfX Ljvp7lu/EHt95T+d9tSjYh0YvfbttbHSisYMyqVj9vrKX7hNrv0Sa8fuxornF4trT43GSjIz 3sqZRZnKDCQiFxBzISRaqqTASCw3whXg/AG/k7GqaAfnckA2Lhsb9cWsPm6smAYSdEcHA3Ud nFvPazbSnMhmc0yvKDZ/Y9JOejruhn5qirnNcck2OiHs1DXHrszsbgxHM0EQuc1f4yOAfeeq 83YbMuIo/Wwrudrq9HQCgKrSi9fr1akzNfhu+cCpU5hXpGx87WRfza0LAWDebTXrnn8NmGzc PvP2RSY++oL1/QuAPU19h/AaUAQAkZODWChPFK0zs7ChdyH0isxoZZAbvm9be+eMWXOp0ktO EZ9+rI/DKMXQsCPZGZLTnJJG6+otCaQ6JoHtJt3DtDk7NRMEkducxMfuHzM08PYnlI0pL83M ANqlriOE9h5EZxYEIW7PIyCPktctJL0UrmjdUvSz8oqy8oqy8mj2y4L1HVN/KrY8v1ix35BR e0IW3PoFPHlveUVZ4wvAK8dfiynsX/yCqLCscS8AFBYVH9pYtXr7KflAK0MQBEEQBJFlXAb8 6/nLHmc/UjbqpB1mDWm/AybJ6KqXmBXjEwsmqtJl8gaLu5DO8/apC5wXrXy0f6XivHBF6xYA gFE7zBsVUzSsBwBEZRas7+9brysZG6KWIQiCIAiCyC6eZo98DOD8FrsNsQErPj8zPMlTUqz0 kmyextr6byO6LVFmfmbStqTmGmV7MxEEQRAEkRSMvWi3CSOO7hJSLeplo3kZMjfBwE0f3F5b XuHbAwDY01QmH8dj0eO0Jfc6k7Zl830g0oLX6+3q6rLbCoIgsgKKthAp473yS3fzb+j3Bd1S PVynX69VXX9XLqUb7TCUNJ5JKWl9eGLMA+dxrjjX5J0TCsySXp5YW/GEeFSz0WKWeVl5BYD+ vt5hG5bb0H0YZegsrSYIgiCIJPG983Owa7+o66nLy8uDwSAgVooKuqsQrXHld7oRkraS3lAS CsSvONeV1EVX0vpwK6jWg4qVXmTfXcct51TdRR+zpJcvbOrt7+vt72tbP7COlmYSBEEQBEEM h6X8Ps7n7selur0Rv5Mxd9Dlkl1kV0Bne4zwkZ6WRini7ndKuz7oSuqiK2l9eMpQZfQUMHPT n1grVnepacK6joZ5VtT19/VSCBl0HwiCIAiC0DAExthTR/G+uiPid0r7rbVUKXZcljNRmNPv iUa4XQEeXr5DbK7HcnEHBl3JqOK4LZx1JY2GjxDyPqPyJkeELgZJL4UrWvsSb5Hl8/nSbE76 yKRt2XwfCIIgCILIEvbigxn8m7NxUd1hsGuC0T4LWvFhSg5/f43U4DDOeOEAIECAWNQvL115 iwUZ1dRUL5kxa671ZTRer1Q4MWPFXjJpWwpzETlNWXmF/G2J8ti8y0iDbpdFPdmD0X0wuhAr 8tpTZbt4oO0duVun1WZydVrbhm+YlTfbCL1bUnvPp2CM9v1PEKOJD1lLP192mD33GB6y25aM oruoNEEQnQHWdjAdxaTopoMW1RFEIlT+iqpR6Vdp5bUyRsI5tF45je6X6m5kDJNfllJGvNLU 1Br9Qs39VxvfAFam1n0Da69U6+Vb1E8QuQLnNSWYcIyvTCyafVjf7Ejrf5vEy4E8jZRbYRTW TU/WsAzXaKdKXqMbXddcicrPU8qYOHbmwqPYj8mqSxPXnIgvo19Wyp9DZLW6+mW1yq6Eb7ZM YvLpQtVudKXaW2d+qwkiNzn35D+2/vFB7b6POYB2DajRy4S4rUaj9RhV+48CcgcErxCTyz+M 3PTTW1dXlK3efgoAcGrbPWXl92wdVAtlbb3wDBuWtfeByDxGrrns3ml7TboSCmuDlNlMrmcy WLnJI51wAoWnniW/dPOYt8X3Z66/NwjCIn+Hm6b/37+/6h8/sNuQdKJysrUvcXujmAuuIObc q4qpS90QfEI+b3ikn/Ryapuv6dBN659aUQQAKFr5aL+172foO0oRug+jG5XPlLBL25iwS/vT uh5bMLoPRvfKinyykyacZZiY3H/tXNqpk7p886swmX2E3glJXamJVUYHVv4dEcQo4En2o0sB zr9otyHpRA6fJ9jVKGEmel7Gy83Rj6YXTXYArxx/LcPGEARBEARBjFq+yL+xlN/3cRTYbciI YJQD4/MJRj46jyW+xG9Pmq/hcxUGS0gXrO/vW7l1dUXZWvH8pvVPPbqqMLE6CnuI0H0gCIIg CELFzxEag3kf4B27DbEfuW66BDnlephUepm0akvvKtPBWVsvPMOGZe19IAiCIAgie5iABW/j Q8Ze0OkLullVCwDMb+Yhj6a1riN+n1C/k9X3KDsMJY1nUkhG/M7ieH1pRc6HkcPq0gEnB92M UVs3PSnDMl+jnSAIgiCIfOMN9ggwGXhTp0/eYSgYDALRzUGr0MG5CwD8TjdCARcQ8Ts3lIQC 8dsW6UrqoisZ3HCkQWyL+J3uoCvdjrpu0kusqIs1+TyE6qYTBEEQBEFkgjv5fe+B7cUbur0R v7O4vkwZzHYFuNZfDh/padnhD7g8APxOJzaHPA59SV10JQf6UWJteMrEBdQp48Ua+m56+ZwF w1M7DvgE558AxgKfAD75ET4+Fh8rwKUFuOQq8LHgV4AXgI/FX6666nzBuD8VfOL9sePeK/jE hauufqdg7IUxBX8uGHtx7LiL+ORHGANcAYwB/ga4Yjw+Ph1/9b/wV3fj0r8ZnpH2cPjgi3ab QBAEQRCEDXyx4giA3Q1dwONxHbGck54q1jK/ORzyOKBIT8H8Zh4KiLKuAA/7nYzVS+0OGEnK imWFRpJLl/cXRyPYdR0jUnIlLkCuKg5jPCGDAG/ckLwi9Wg6QRAEQRAEYZ1A74xetunLy8Z9 +GF8h8MTn8MiISfCqNCKD1PSYH77ER14VTH1/CHFXUgJgiAIgiCIpOhlmzhfdje3thnNaMds tyNVMcd8rdJIbjpBEARBEESGYOypD/LN2bSA6JQTKijphSAIgiAIInP8Gs/abUJWoNy+VDey TlA0nSAIgiAIIhP8x9S7Z/BvMjZgtyH2ILrj2hdU249SZD0KuekEQRAEQRCZ4J9OPDmAP9tt hW2Y+N/crNxL/kJuOkEQBEEQRGYY9yFrAcbZbUZG8XoFzqOeONdZJyq/8nCRqDmUm04QBEEQ BJEJfl09+fixov6jE+02ZGTRJppDGSznGlecXHMDKJpOEARBEASRCZY++dffPHplAH/S6Qu6 mYjTr9fqDsaL+52qDkNJ45lkSbnFmoJE6BZV1ImaG4TPlWnrYiRemcWeV5CbThAEQRAEkQm+ hDlA76d1k15cAS7SUCK7yUF3FTrE1sCAU3KfI36nOwhPSBIPuAwlddGTlOfm4eb5ddUu3YFG C0BNFoaKCF4BiqSX2MsAExc/3yA3nSAIgiAIIhO8DVaGu17CC7q9Eb+TMXfQ5ZLdZFdA8sKV hI/0tDRKEXe/0+mPGErqYiYZdK/BZqNek5xy/UTzKIJPUIfPNUF0I18/5uLnJeSmEwRBEARB ZIJn2COH2cNfglPdEfE7GSuu7wFaqhiTXG9lMorT7wlJ/rMrwMPLd4jN9VjucRhKRhXHFJpI AkF3Y2lIVJdBVKF3la8fc/HzElpCShAEQRAEkSG+yL9xmTY47PCEuEcr7ApwHtBRohUfviTg CoSsBeTTihh3l6qn56s7boS+m37x4sXhqX0beFvV9C7wrq7sm8Cb1jWfAc4Az6Vumt309/Xa bQJBEARBEDbA+bKf403G2h7DQ3bbkhWoVoWqwuqEYTSdcw6AMcaj9yzlY1KiPDa64QRBEARB jG4+h6KTuKSS19ltiG0YVWthTJOALp76Rtig7CZB0gtX3E4rx7pjUx5oRUlS1qY80GjscO4P QRAEQRB5xa8RZuyZifw+ZWM2h/Ay4MNIF88NEtCFkZ4/q9F30zPvWebDjOKkhw/uy/y8BEEQ BEHYDmPPADgTX8Ajr8J5Rh9JeHSDUkIJVXohCIIgCILIHIfZw3abkDm0WxTpfirJz7LoCUlz pZd8CIrn1adegiAIgiDSBeergQ/H6G5vNBrRekzkiieFdTc96Gbt1fEV8SN+5xpsDskVO6ta ANR1GJXNj/idxUcaeKDY7yyu74m2GstbsSQS0yUrSmxJssRfu1Z/+mck7KeystJuEwiCIIhR xcfx1x/g/fN4325DMoQYIBcEQRAEuVHKbwH57Imx4qZH/M4NJaFqTeOaI2VAafSssTTMuQMR v9PpL46rji+50vPrYgub5zeHZe/e6Y+4LBbT11oSqwcqTbz0aRNLkkczo/ZKYXbtRO6yqfmH dptAEARBjCo+ZC0f53Uf10k5jgUEg27WWCp5SXGtsYBh0M2q+mVPSjteHVY1nslU5whhlp5u TTJ/sOKmOzyhABBslxukKHpoqd+5RmwJH+kpq3YAgKOkrKc9DDjiZDkX320t7dDQs+PpiMfa u0JjiYT0lg45gKChJSmhmVF7pUjvjISdrK3/toRKcWAAAAd0SURBVN0mEARBEKOWX1fP/J8/ vfTXf/OBsroL5xxwBbiUEVDVUtfBJU/CFehoj4n2+x9weRyI+NtRN7+nvpjVx8KeupK6WNep KkGjjIgni3as16uvTZxS8AkAxEHpnTf7xypJKTfd4QmFACC286yruq6q0f+AywN/Y0tdg2J3 K8fS5SjeEPQEXAi2twDVGm0oK0nZr43m0UhvblNL0oOO/hGekcggtPCAIAiCGDk+136I82WM PaX9c+N3sno081AgvkfaM1T0d0TP27G0tH9HKechABG/2x8JSI66RtIAqzpVRqZcOFKV9BJt jDuVp5L+q+fEs7j/pDhvlo8FUFO9RD627qa7Yq5wlKi7ruz1hLhGiMsyXJIJyd06apOwxKGZ zsSS1FEaqdU/EjMSBEEQBDHa4PwWxp7S7ZKTeHWJ83cU7pfDE/CYSJpiXadFVB899L16jto5 aD2gbjb6CKB0eWfXCtOPCq0p2SaN1cybzWNBBRkJgiAIgiAyA2Mv3s2/YbcVI4VYVNG8tOLs VQIA8PgXYYB+NJ224CEIgiAIgkgvP5tb+Uyv3UZkBCNP/UCrcAAAiw+961ZSF//j04xNiVwc C6WbLqbCzJg1dxjaiOSgu00QBEEQ+cMPest+j4ucL7PbEPuR/XijRWFykrrXm78lX+Ki6RRE JwiCIAiCGCHC7GFo1kCmvDQzA6RQWUFvRDS9XNM1O9Hmo/rLMQuX3P/Vq0OppXzn1Ng070JK EARBEARBWGeUFRkzC5NrPPIUE0IGOx8SUhuZY2NpCSlBEARBEEQmuIzXcT4LGGe3IZlAXk7q 8wmqLs7VL0IXdTSdsqUzQ2VlJW1ySRAEQRB5hRu47NI5Gz86aLchNlG45P678WToap/Podre yMhT9/nEYYt+/1B8usjsWsH51mMPdQ4mmHJ2reC88p13QsrhohmJx+rZbzVxRc8+qzbH0El6 oQz1kaatvdNuEwiCIAiCyDRd+KuZf/nL3Ri1NRll4t1uwesVDzoB+AEGCNG+2cws9SWal37l NYXAIDC7Vlh2Ze9jD3W++dY7Vm15J/RQ6wGlh33t1VfiLaujlSSRuJKEfSZQ0gtBEARBEEQm 6MfZn+MPM6/6o6Yn6GbuYPTI6Y/otEpH4klMxlRSB13JiN9pOihplDXUfT5BecoYoHjJPnpc AkxcPfXBzoeiIegDrYLwUOdgXJspB1pF13yw8yE5Cn6gVUghlJ4cevYlPy8tISUIgiAIgsgE X8K1iz/9u7UvTf4/ivomnPPYjuZBd1VLXQd3iF2uQEd7rBBMv/8Bl8eBiL8ddfN76otZPeY3 h0Meh5GkLkaSLVWsBQBiOlUlaHQqrlhGOVaV7iLi8wlMjrBzCGI6u5DOeXNlrBJy0wmCIAiC IDLBCVxy3cFJvol/eOA1dS6238nq0cxDgfh0EVeA8wAQ8TuLjzSI/rRjaWn/jlLOQwAifrc/ EpAcdY2kAVrJ4IZ6NIe5eOxmG4KegEtTgiblwpGCIAjCY3I+eMyDVeRqcy54lXNFhVRjY1jI 887FsYhuZCSSjW767saK5xf3ehcAe5rKWqZ0bFlRhNNbV9ccr+v1LsCpbfdUnfhKf8M8DLeR IAiCIAgic/SyTb0fgZ+Z9YCmyxPiHuOBDk+IK09C8mHAYyJpikIyGstXH6eRwc6HHhKPFM5/ KwCvH1CValR/HIiNjWF1e89cHBsj+3LTB7cHBtZN664oK68oWxtZ//0VRQAGQzux7ssLAKBo 5Ve+0PbTrYPDbiQIgiAIgsggV/Cvc17D2Oiv9KIstqjKcpEy1MXUdL1sdUImG6PpABY19K5q ALDXV37P1qceXWW3PQRBEARBEMPkPVy8Cte4+Oiv9KJMkBEEARD0Sy5GGxnMHfTCJfd/teJK 8TjyVHJ7eebiWInsc9MLV7hLKn62Z4V3ATB4Kjzz9i8XAnDehZrvbHO2rpx0attPn6j5Sn8a GgmCIAiCIDLHpewnfwQeB7bAb7ctGWa27paj1tLdZ9cK04/GVmXOrhVqYdXrzcWxMbLPTQcW NvQuFI8KV7RuEY8mrdrSK8bUi1Y+2o+0NBIEQRAEQdhMykszMwBPxwahXq9cN12rXzpIdA8c ywRhmfJcEJZZDVHn4liJbHTTCYIgCIIgRh+cL/smJjyMo/GNaXCFsw2jazL0xrl5d55CbjpB EARBEERmGPMw9j274s92mzHiqHLTBeGpWmH6UaEViOaDtB4Qj7Z6W2Oi8c49AwQI8AK+6VIQ On6sNVsiOThWIvsqvRAEQRAEQYxGGHucsYN37jhmtyHpQVnOxeTl9QqcH9jqbd3PwTkKr7kS V14DDvADrd5WVZWXuIovDIJPACt8650rrykEII0tFI/eeevNxDa+mYNjY1A0nSAIgiAIIhPc yteeBXNPO223IenBYlK9IAjxu3I+JHQC8VXFjevAiHntD8EPxjDY+ZDQCUC/LrkeMbncGRuD 9ff1Amhr70xuHJFWZs2S1lYUT91nryUEQRAEQRCE7bS1d0rRdOXGpIQdkHdOEARBEARBxPj/ fe9SZlULoEoAAAAASUVORK5CYII= --------------070502080500060501030504--