Return-Path: Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id ; Fri, 5 Apr 2002 15:38:06 -0500 Received: (majordomo@vger.kernel.org) by vger.kernel.org id ; Fri, 5 Apr 2002 15:38:02 -0500 Received: from paloma12.e0k.nbg-hannover.de ([62.181.130.12]:53930 "HELO paloma12.e0k.nbg-hannover.de") by vger.kernel.org with SMTP id ; Fri, 5 Apr 2002 15:37:43 -0500 From: Dieter =?iso-8859-1?q?N=FCtzel?= Organization: DN To: Ed Sweetman Subject: Re: some more nifty benchmarks Date: Fri, 5 Apr 2002 22:37:29 +0200 X-Mailer: KMail [version 1.4] Cc: Robert Love , Ingo Molnar , Andrew Morton , George Anzinger , Alan Cox , Linux Kernel List , Andrea Arcange In-Reply-To: <200204050549.08558.Dieter.Nuetzel@hamburg.de> <1018002175.23296.71.camel@psuedomode> MIME-Version: 1.0 Content-Type: Multipart/Mixed; boundary="------------Boundary-00=_HY34P25E94MCPC6549FY" Message-Id: <200204052237.29299.Dieter.Nuetzel@hamburg.de> Sender: linux-kernel-owner@vger.kernel.org X-Mailing-List: linux-kernel@vger.kernel.org --------------Boundary-00=_HY34P25E94MCPC6549FY Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: 8bit On Freitag, 5. April 2002 :22, Ed Sweetman wrote: > On Thu, 2002-04-04 at 22:49, Dieter N?tzel wrote: > > On Tuesday, March 2002-04-02 17:15:40, Ed Sweetman wrote: [-] > > Yep, FOUND it. > > Ingo`s latest sched-O1-2.4.18-pre8-K3 is the culprit!!! > > Even with -ac (2.4.19-pre2-ac2) and together with -aa (latest here is > > 2.4.18-pre8-K3-VM-24-preempt-lock). > > > > Below are the number for 2.4.18+sched-O1-2.4.18-pre8-K3. > > Have a look into the attachment, too. > > > > Hopefully you or Ingo will find something out. > > I seem to have lost your earlier emails. Did you get a max latency of > around <2 before this 0(1) scheduler patch? In short: YES with 2.4 and with preemption+lock-break I repeated it for 2.4.19-pre5+vm33. See results below. It is NOT in any case an -aa VM or preemption+lock-break bug. Ingo's latest sched-O1-2.4.18-pre8-K3.patch for 2.4 is the culprit. So all latest -ac kernels are broken in this sense, too. > 2.2 with low latency patch gets that. 2.4 with low latency patch is many > many times worse. The high latency areas of the kernel are already known. I know :-) Bad we badly need a newer lock-break for 2.4 from Robert (sorry Andrew :-). I will do some "stats data collection" with my next boot. > It's just a matter of deciding how to deal with them that's the problem. > It seems that it might be a general consensus that it can't be dealt with > in 2.4 mainstream. No I think it is not. If we can eliminate the remaining bugs from O(1) and use preemption everything should be smooth. > As you've implied before though, the scheduler is much more important > than latency is to the average user. The O(1)-scheduler is great but broken (latency wise) in the current 2.4 version. Have anyone of you some older versions from Ingo around? > As most people would know from > 2.2, audio would skip unless it was running -20 nice and the highest > priority etc. With 2.4's scheduler and preempt, well you dont have to > worry about skips and you can leave the player at a normal nice and > priority value. That's not true with the O(1)-scheduler. In most of my tests (Ingo got my results) you have to renice the audio daemon to something like -16 (first "real time" class) and X to -10 (for good interactivity) during "heavy" background stuff (40 gcc and 40 g++ processes reniced +19 for example). This load resulting in ~350 processes, 80~85 running in parallel and sound playing on my "old" 1 GHz Athlon II with 640 MB...;-) But that's not so good for the "normal" user. We need some "auto renicing". BTW My former 2.4.17/2.4.18-pre numbers were much better for throughput and somewhat for latency. I used Andrea's -aa VM and Robert's preemption and lock-break on ReiserFS all the time. But together with bootmem-2.4.17-pre6 and waitq-2.4.17-mainline-1. Anyone know where I can get newer versions of them? Best dbench 32 numbers were: Throughput: ~55 MB/sec real ~1:15 Last one: Were is Ingo? --- I hope he is fine! Regards, Dieter 2.4.19-pre5-vm33 32 clients started ..........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................+..............+......................+........+...................................................................................................................+..+...........++.+....+++..+++++.+++++++..++++++++******************************** Throughput 40.4878 MB/sec (NB=50.6098 MB/sec 404.878 MBit/sec) 14.440u 50.650s 1:45.35 61.7% 0+0k 0+0io 939pf+0w SunWave1 dbench/latencytest0.42-png# time ./do_tests none 3 256 0 350000000 x11perf - X11 performance program, version 1.5 The XFree86 Project, Inc server version 40200000 on :0.0 from SunWave1 Fri Apr 5 20:06:34 2002 Sync time adjustment is 0.2107 msecs. 3000 reps @ 2.2644 msec ( 442.0/sec): Scroll 500x500 pixels 3000 reps @ 2.2663 msec ( 441.0/sec): Scroll 500x500 pixels 3000 reps @ 2.2635 msec ( 442.0/sec): Scroll 500x500 pixels 3000 reps @ 2.2654 msec ( 441.0/sec): Scroll 500x500 pixels 3000 reps @ 2.2714 msec ( 440.0/sec): Scroll 500x500 pixels 15000 trep @ 2.2662 msec ( 441.0/sec): Scroll 500x500 pixels 800 reps @ 11.6017 msec ( 86.2/sec): ShmPutImage 500x500 square 800 reps @ 11.6358 msec ( 85.9/sec): ShmPutImage 500x500 square 800 reps @ 11.6463 msec ( 85.9/sec): ShmPutImage 500x500 square 800 reps @ 11.6122 msec ( 86.1/sec): ShmPutImage 500x500 square 800 reps @ 11.6322 msec ( 86.0/sec): ShmPutImage 500x500 square 4000 trep @ 11.6257 msec ( 86.0/sec): ShmPutImage 500x500 square fragment latency = 1.451247 ms cpu latency = 1.160998 ms 4.2ms ( 0)| 1MS num_time_samples=63551 num_times_within_1ms=61215 factor=96.324212 2MS num_time_samples=63551 num_times_within_2ms=63546 factor=99.992132 PIXEL_PER_MS=103 fragment latency = 1.451247 ms cpu latency = 1.160998 ms 3.8ms ( 0)| 1MS num_time_samples=20758 num_times_within_1ms=19668 factor=94.749012 2MS num_time_samples=20758 num_times_within_2ms=20693 factor=99.686868 PIXEL_PER_MS=103 fragment latency = 1.451247 ms cpu latency = 1.160998 ms 30.0ms ( 3)| 1MS num_time_samples=17604 num_times_within_1ms=16825 factor=95.574869 2MS num_time_samples=17604 num_times_within_2ms=17591 factor=99.926153 PIXEL_PER_MS=103 -rw-r--r-- 1 root root 350000000 Apr 5 20:09 tmpfile fragment latency = 1.451247 ms cpu latency = 1.160998 ms 14.8ms ( 12)| 1MS num_time_samples=24448 num_times_within_1ms=23863 factor=97.607166 2MS num_time_samples=24448 num_times_within_2ms=24425 factor=99.905923 PIXEL_PER_MS=103 -rw-r--r-- 1 root root 350000000 Apr 5 20:09 tmpfile -rw-r--r-- 1 root root 350000000 Apr 5 20:10 tmpfile2 fragment latency = 1.451247 ms cpu latency = 1.160998 ms 4.5ms ( 1)| 1MS num_time_samples=16142 num_times_within_1ms=15463 factor=95.793582 2MS num_time_samples=16142 num_times_within_2ms=16134 factor=99.950440 PIXEL_PER_MS=103 -rw-r--r-- 1 root root 350000000 Apr 5 20:09 tmpfile -rw-r--r-- 1 root root 350000000 Apr 5 20:10 tmpfile2 122.970u 18.150s 4:09.80 56.4% 0+0k 0+0io 10418pf+0w ******************************************************************************* 2.4.19-pre5-vm33-rml 32 clients started ...........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................++.....+.........+.........+....+.++.....+.+.+...+.+.....++.+...+++++...++.+.++++++++******************************** Throughput 39.637 MB/sec (NB=49.5463 MB/sec 396.37 MBit/sec) 14.370u 53.580s 1:47.59 63.1% 0+0k 0+0io 939pf+0w SunWave1 dbench/latencytest0.42-png# time ./do_tests none 3 256 0 350000000 x11perf - X11 performance program, version 1.5 The XFree86 Project, Inc server version 40200000 on :0.0 from SunWave1 Fri Apr 5 21:29:15 2002 Sync time adjustment is 0.2172 msecs. 3000 reps @ 2.2866 msec ( 437.0/sec): Scroll 500x500 pixels 3000 reps @ 2.2899 msec ( 437.0/sec): Scroll 500x500 pixels 3000 reps @ 2.2885 msec ( 437.0/sec): Scroll 500x500 pixels 3000 reps @ 2.2847 msec ( 438.0/sec): Scroll 500x500 pixels 3000 reps @ 2.2958 msec ( 436.0/sec): Scroll 500x500 pixels 15000 trep @ 2.2891 msec ( 437.0/sec): Scroll 500x500 pixels 400 reps @ 11.7923 msec ( 84.8/sec): ShmPutImage 500x500 square 400 reps @ 11.8264 msec ( 84.6/sec): ShmPutImage 500x500 square 400 reps @ 11.8240 msec ( 84.6/sec): ShmPutImage 500x500 square 400 reps @ 11.8370 msec ( 84.5/sec): ShmPutImage 500x500 square 400 reps @ 11.8484 msec ( 84.4/sec): ShmPutImage 500x500 square 2000 trep @ 11.8256 msec ( 84.6/sec): ShmPutImage 500x500 square fragment latency = 1.451247 ms cpu latency = 1.160998 ms 4.2ms ( 0)| 1MS num_time_samples=48986 num_times_within_1ms=47284 factor=96.525538 2MS num_time_samples=48986 num_times_within_2ms=48979 factor=99.985710 PIXEL_PER_MS=103 fragment latency = 1.451247 ms cpu latency = 1.160998 ms 3.8ms ( 0)| 1MS num_time_samples=20764 num_times_within_1ms=20537 factor=98.906762 2MS num_time_samples=20764 num_times_within_2ms=20762 factor=99.990368 PIXEL_PER_MS=103 fragment latency = 1.451247 ms cpu latency = 1.160998 ms 3.8ms ( 0)| 1MS num_time_samples=20603 num_times_within_1ms=20109 factor=97.602291 2MS num_time_samples=20603 num_times_within_2ms=20602 factor=99.995146 PIXEL_PER_MS=103 -rw-r--r-- 1 root root 350000000 Apr 5 21:31 tmpfile fragment latency = 1.451247 ms cpu latency = 1.160998 ms 6.8ms ( 2)| 1MS num_time_samples=25283 num_times_within_1ms=24655 factor=97.516118 2MS num_time_samples=25283 num_times_within_2ms=25280 factor=99.988134 PIXEL_PER_MS=103 -rw-r--r-- 1 root root 350000000 Apr 5 21:31 tmpfile -rw-r--r-- 1 root root 350000000 Apr 5 21:32 tmpfile2 fragment latency = 1.451247 ms cpu latency = 1.160998 ms 5.3ms ( 1)| 1MS num_time_samples=16210 num_times_within_1ms=15669 factor=96.662554 2MS num_time_samples=16210 num_times_within_2ms=16203 factor=99.956817 PIXEL_PER_MS=103 -rw-r--r-- 1 root root 350000000 Apr 5 21:31 tmpfile -rw-r--r-- 1 root root 350000000 Apr 5 21:32 tmpfile2 116.600u 19.040s 3:54.15 57.9% 0+0k 0+0io 10418pf+0w --------------Boundary-00=_HY34P25E94MCPC6549FY Content-Type: application/x-tgz; name="2.4.19-pre5-vm33.tar.gz" Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="2.4.19-pre5-vm33.tar.gz" H4sIANXprTwCA+29B1iTy7YwrKKgIGDDCEixRAXkpYN0FUEhIlKj8AYEDAihhBSQrqCgICIgBKkK AgISRFoSpPfeifReQ5Eu/Q/ufe49+95z73fu95/7/ed+/57nNTOZWW3WWrPeycwwigOSgJisMBqD lBJ2tJWQENnzj0+iopKiMlJS9FxUVEZa8lcuJvlb/nvaIyojKSUhIS0pLimxR1RMXFpGZg+/1J7/ AwmPxZli+Pn32OGROBekzX8Ch8Rg9/xfl8T/rf0lHotLSQs/tMKiMEjThwDazvL/vf3FREWlf7f3 v7c/vSQj9lf2p5fFpGSkxffwi/5p///29PLunZuszFzM9CKr+q0bOnv2MIB79uz7tJ+BXhNUOHyb np26e1tPlZ5fvXrVzs6uqqpqbGzPDv37zp6dnR3OLch+OkiP+o1reo+jZnpqcyIpYYwPKj7tp7g6 BdsFuHhFpUDuBShclZsMeT0hyDNGg1DOHjrEcthncnnn4vzXa6vsois1nZre/Ae9/uYDxvLB2fd0 HkNnMJPuHQA/7wMM9kJSn/jrF5ULDphx/HNV20W/vuTCSjRKghl70zomb6XcFODe2g+u3klqTLfz k20uwi/eI1Z8831KG3MAAwpObc/t8MtUe1pmoMVGTmBTxbbYc7kOM/xz9DDBS2gr0Pwc9d81h/LV w5eHaXNjq3Mma2cHKFoekoXtgSb16ftOkmbf8pkURlws9EDl9pu0vzt5AFytDjTxoeXKFSfGFiZK zr9kJG6UOQicrV2WIl/2oimtDc6KWhDHUCBdSy8LJDZt7aTQYt/cL1Op/Sts5l9L0ircvQOrPy9w k2F+fG7eA9P/ZxSyEOvJN7YxfLZq71qSF4vl/1lz+I7oo/YTL7mOMxNhf4Do4jTO9/LXTx8waxci AcmsxOi9cGCAktXX8QRlqeh8y9OIgRi9XIR/kD7g4mBXnN1S5wU7yczLhU5rZ4DbFoWykDqmnqZK D9QcAFHLRfqR3Gh1tD4TSH6SCrKDy87KxHMdR8FRl4EUdhJmL5zMS5piIIJF+kQm4voTIQg6lPY0 dbv0/O9td0anvmqtSu8lMoJajOCocTFeCZ6bu/KVl1S0DPaFofrTY4s4xg2JtjBmAK0IMQDZ1fYR 4ynze6m6dHwm9FManW8Pwy50kf6s6VhNGwO11Lj4ABHDPrCPiv0FMzM+xRu4H7yJH2YgJu0jYtJ/ b4H/ji30OzYHqIVNYx07jt4a7/dd2ybdct/uOHnbdctum8g6tgHOuRbE++bfrN9ZFpFYHtLsz82J rlbmAK/kUYb8uWMQdKIaRct60hj9dEeB1ZGpEsg1K3T7SYVIoWP74GcGXAR/BzCuhWoySKUpDAj2 DT8VeuwBwHPdYohTwuSRfNLtm1+zDgLil8LtBQY1jFjgAWGRbTkNxDoDQEa8n3YUFL98adh9dFAR W7VT9Tn6MLcIRjVfQ3nqQozFF5J4IxQidFGR0DleedyhPnMu+AyslOMEjv2aby+YmimPY9/7vWdh c2DjTXHBxweYseeZLMyOYs4Ij2epnErPRM4SB14Y1V38BNF8XByKeyDjVHxyQegz9avuBi+WDFEF TNqxQaMLIhrMDnxfUS1Kbte0mqD6kMxZLs5QWb9aqb63Y5mf4QM1+Ad8fmALVvt4WpMd0PmcJwEs oGH4UsFi/QvnogdT8tW2qxqiz8B7hgBALkhI2RTdjmlmI9pVc2SFY6q50arnjNKdeCE8ddDi0b6r I0EgD2m2UnWuSCq9veZZ+kDwc5fYwNRaB3xCyoAgRhjixEQYaYTex+DpqmUh4ZyylFbhDs1e/tbk iVZMdTTo76JpGbYhTnwgkIvVFoaU53dgqxFgrbkgl4C+QzMz5LktJKzkxOfhYGfio9pgmI9/XqB/ CunjZJoPbHn+BCQNrX0AfqVUg9g5uhdiOxS3Bdaqino/qBsNi6tS5SaN3Acl05vOgNWhYjyvRuNS yZsSk5fsyttnxsURTnrFqnmkT0bfNL+9Sg1ZjCKAVvkq5E9lqhb9ghDFalUtTPMyiLMEKDyEbxEw L1oa6ZFYrBRA4YSvsoH7ATRPGXQV0yzvUM0MOJ8nuB2FuNMVRoBJD3SVqzZi1NF0b0kamjKugtI9 /UkqA7WW/OIoRHjqKQsYGwPzUAPivkxBwf3Et6nyT/1/OuAvoqtd6VjuGgDlBZ2bNXCIeJH0sEh1 wKwGWqw/EFyJOUq6gql2Ggke+Jo9onAKre9QPQMuFYDHwAHKGcj82JRxI9QSSBmLC/cvOkCcYN5D ZCFNtKKbaeRHAbC+MJgXC+jrUO1NOk8qwgsB+yCkHDpFtpG404Qtrvg6KJz08Mq4L+ghaL20dBjS 6wUjYpodwGKVMigD0FWtSgMT359x2JIHDMenDEiPilW7yY+UCQIqiUGZpAl+IjAW9+N0WIy/AakK 2+leUOQ2qU4q8f7I4pbQD3GoDoe5HKjn0Kt3OCBMxDZ7wRpaXYUhtqMLmZ6HIFLNEbE10PjyW+SD IBOm2hCYJAfnjl0m7Ic3LdepnoEolkIbx+Ly0PW+j8s4ehT2ZypHwmKq6BYMdgbkYmCMYFYDlJPO wj8Hq/0aRkQ3T4ILxwDq0CJ4AtMcBM7y2IvAmQBjEHeAsJ+K2O39cge4NAYuzdI9twh/BFK+uBdC ksZWp9IFAEkTIfRQyVMOzcVWywxPhWOr5bH49ME4V4x2mP/r4anLhM8DwY0O2qtv/GMGp+6MBDdi miXAYBaCW5h/3wv/O+PBPeQRQUjyznB2lHzigwEXH0msep6sG6wKU32YgAqyJj/kINRhm+s4JM2Y FLDVx+Buzh+Pkx+dI0T0fP7SoJoKFuCq6MpuSb+/xHkWYSVxKoIgzxO/Xakl2fipWurY4SvhdQqV 72lv/BUI3JV1HKc1J5vBUilI4EkBudPLtWch9bqTQ2IX6VGIFCUxytIA3iiOQn5l3jbMH9EwOhwm 2Qg1BzRIZ5+/L197Wvdk+JAlaSjemZuK6ez15wHFS/Vn+Qf9ZGijcbf9mwVxh6prgoJ5NVmIdQ8x 4Gj1CGls/e3bgr0QnlpVVeKD5wYkccQ4WaOyzxVNV45dIxRFDkN5HISz/bgHLLS6cULy3wpNzOyF CMtRzhG4a5SITBL7qf50b6QNHu6NaMckYD3OQKKLocV4ZUCmciQCJ00fwRiZoc/kMe8T4Dhm9MQK utkrVfRsjeYpUApceuN/ymELuk5VaHJablV0Y8+ZIDw06SK5jMC07zWGNm9sR/himIgFfQv2PXG0 ZfvvZnKG+XMbcexGPzbiaJ/EviJ0cwb6nUUdO7TbcTcWrxK8343fqrZYXoxdz0Q5fxua7nJyrGdQ nDd7LA2hD9LcwbNs4CyyhEPTTgSyO9axR0l9T4SSmYlyxI+qzJWkBo60JSXAj5sMgfBUqK6xtcjy 1YReiiqDQhgU/WF9Pqkw4xPksHEhknFjqGROAIrMrIVuDgGbf1yaPAimguRy2UAhxAc8kUx1GvDr SKgaZU6kv+KjUM4y9Nf9boDJFyNwy5BW0KMXGAA0omFUWrmRQ9GNEZB76e/F2/e8NqFKVQsNzWSE kNhGNU4S5OFdZy8C9JAkRirJOEn2iirLPn0YWvpNGC6ao1XFcXjLnRzmrtAIDZlcq5gix5Hz2g/f XH9HDvaK9RW6jGYgPqpnGzQE2EhFqoGklg83VJjghhciFEmzRaHT3SWhOE1XcpVyngAEKtzn5X8S GdcLR49mPhcS/uKo8BnbPLTnhTWSHIa4qQ+5GdLtKEPMMjL8PFaqUBvKrShMimtDa9+7YOXIDc8Z wNyggamddaG4zOf+0phmA+J13/v0AMORzUp8vwdRw2HbV6x/kIRxLWGLHTBkIQ0FHSW19HjVznRX hrpnTIvmpn+5QkW3jxiA1VUHwdqgp6ij6Of6Nooue6nexQq12Y8N9ENZqV1Fq2gO7lT1d6mU7YIn KHctpQEXi4FpkqMlLdJGb1mDuBzUTAY3UqLeQrA8fGgOZi/a+u7Uaznm383SRolgDh5dblrMYStA 2DqRPLj+sgfKF2oJwfi3GR8OMvr4mpb5TapHKRtM31p+2Na8ye6AbrMZiiDQOEDxb8v7Ie39VeOk kZcgJX7a8+mmru8hwn4C2+7sz6lqsHCTiareudB4vRjv/Gve11bZvpeaqERkI0kvO+Bz0O073M76 OkpDXZ9ycsAkbPQaqr39fD5mxDAmFoJpX87Y8NpHVHSWJaR+IcAKIoQ+xW5yB9aDLxEfhrPnT1dC UwnyVFo+qaQ4nxs+HsvREDX6oO8FDJh6KjTzw5aEEcJjAU7lNtxjgIqWIU7wJGG9QZziQy5Yyzip y6b5acWkaTSqc/hU/tSdganqRtyXQHqfKhMuxoxzVReesoFfqx28zAK6rI05xBZL/Yw1D0P98D5E UmN2dTzOeVPiUz24pQJIXWaSur11CSj0iMcJKbDphlrFigqz7qU+Gv+egpElOoxZ61dfwyc4Bdoh b61+NriVf7r+hVrmdevA8Ygp1vhBLptx73GuW6SVpWc936YfniU2z4arCavp38SbJTBWQntATYlS veZXpWxmp6qVJhbihWVSOAOjuVzkj55ukGIEQ2onLC/VMx9/iQcyaqR8QG9jVjHN8un7GFYUmB/u 6O/Adb0OulTyUmzgmM+XMqSLGOg9c4PVXI/h9FliseRxh4AI1AmX6weADN/aACcJ+Dj54yDXAlgq SCXVSLVh8PLkEWniIJr4wQ81kTi/LDnF0aJbhWbN581RO7KXIHuBg3rKIfv6PaL0KJehVM9lwhcw fjxCWhNUeYdCg96DXDKYSRWzMa5jgJgehnUlIq7Y5xp2WYAgSnXVt7xNrjCeHuSikSrCUy8GYVjv Ex0uEk7dKJEy2JVKck6im5QoGElWw9+4AA6dgZs0QhOXzJVfGIQfjj+dVO3XcWrJwlxkKfilVUxO 1CNfK2+uCj39UHgj7n6eZ1t214dc7vYTSZUvMXqsgccXRHOup1jGz5msitsaaG4YxndLkUxvM3Tw Wu/00AZcObYUmPM6pa6Em35K8dg5VXf307rF5/zID50JMhGJakFLclPQgxdFbj/XrmvmWTf9fj0t mf5DgB5CB+iTjKID/1HRnY2oPBx7zW0R9KwcDDzSX6F8vqCZL3O+MZgWOb5+Qc9ZpuNBmW6afWns M1qk9TB3QH+ScaX9ULqL9Pp2PcXNtWz5psNLBcKU/uZLcpkKoKzyYSoyY1udVMYMJ+2PJBW8S/Es U7aMRZyVywsDfX/lz4yw8z+mXer0lfKeKd/qIBk/FtNjjSqHxowca8S+fAaLKoI6Orx8A+vAvjQE MmJhV4AgNGv8lTDYQ/K0T3itekwp1A80q273/tt9ox0l7KHmk8s4wLMjxzbIZeeA4kjYW/KNMqlA Wz6CletBVDvmpSARPagBmkXDzuf7uTqsSbG3dO2tMxreKlboObwk2q1PfD8DhavWyT0HO4tVbVnH ptHdkgR3iw3eyuvtsmJwK3SJyDuRZDKOZRyr/3G1kRFuf5yaQ8rEFocKjVVK+ZTWKQrpR4cIG32K fW830mLV+z0TZEpMG5ADjMgidUpAc+DKglaxtgv6BIHsccv9S3RF+aVIkpf1ypKCukZSduVNVzO+ Hvpv0c7q52AIc9rYTc0zI8A/7zrM/141Nb+1XISM3qK2M3yqL2YRHH2XFhumVdM+2Zoa2XRrzNDk cu0wq/9eu/4v8dTIw8OvjL3vEQXGvj5uPZrJWZFK4kpJdaXiKdWixhXtE/6DO2ec1FcQWv3WA2aP 20TvKOUdDt5dzkBcLAyOfB1eLwqMUVBKk+NEao4HWPT812IXxmNk+GzurdyfiF7F1uZ3qK6Me94C WbvfznE7D0VoXEgibAeHVH6AaoG6AMjKTZytkzpAbQ4asP6JxicRBSKNAl7Xp1Uko2pMD3HhPW9f vkP0eVF/gEVAlcdK3Dnfza/nfPLLywo37Y7iBQis+HUY+yIHa6fylfxZCFbsbYvHM+ncwDF20iyk UfUhua1araXg6mzowDRGpD2Xj5Vkx7lY/3b8a/qdbeb9nTzu8A8FaTI73/Mj7aXQGDIuiYc8ng0q 77di/KpzXTFcptY9+bOsyQBMnoVVkymVs2/p0+uxcqoBu1HOTU8i0pWdmHcvZ3NdYeSsibUJxZL8 ccvI+lZDv1DN9NwhvhzQRSholnov0d+/wFqKr+ej/MPlD/G5JJTt8dO20Yp5Y37+P1myJD0Tye9K W25RMUE8L61qJS3VHoUZ1jzeM1utF9MTqbJyrr40TD/oem2MP7Bhk6pl7XRiqjlcCz2iXHbgQsvl UIGLmYWSy3zbVdnXTCVCwcQ7EBlqOO0Lt7Xkk/I4ilHGjLATu2GOFpF88s452ia8ampaR7eZr7/H 1uLedx7PHDOLKsdDVW05IuNe7RCV9mfboS9dzCrMabCNaCfHPdbAYuh1QOuppeFs3UWwt1w1F7ty CwPOVmFjmYdM8yIP14Z6stxNSsnE+JrJzBG5Q509v5SixhgqZaC1DOFzql/nEOyGswaJY4TJNk/F zJPJ7FBPMb3GXucEE1WIitShVTV4wSk1EOGm2YsRyyIkPNKOfIFyrv5KvYox4b7cd5kv53KkWa3F Ol2Ds4cDXm71BdV5HuPfvEoYnKrSr+u3Dpc/mXky0dYzVXuDs6g/Bjc7/NFEebEULAuT2X8eobrl 5lzvkoiUevwVAeKlwMYtRnzfNfctpmTLxTIms/3Xjuy/9sZJq3tp2pDI58V7LU8nzikwLhB1kiX3 +tZ9kXtTSXdJ7NwmahMZmoGtfQVzIfmhwpZiHUYe7ksHDQzaXFb8xd0z0Mqal3uihe6fumV3Pn+r OydnXqfXeM4WoqmX0zNWQe5bgMWxnRgc600lXP8ekNbJe7p47MUCTcTQ1S13ltxp/vq6089li5gc dO9lzbnrMt8p898rzn7qk+Y+rHNw41PNZfKUYQxjYfYo4SPVMAa13s3IfRzwdHv3dDU/7bv02NAR PmwiGmVpw0Ktb1nqo4S0vkoSY7pe1U6xKDWvibnk4lqYO+qBrRVR5zNOb+tMSBQPQNiDr1JyA2eP TG91R7sAQ0P5noeZ4TGIVsGpoNvZiRctFDxIgzBlH2SlBSCCWoNOmgNOI1JhQpzo/p9mAbLxdaF9 sQqUJ+RTlOFCq5KSdnCr5zNPYGfz+pmfmXI7d7qSLDfCwlipiWEmx7BSE1vu17pzZ7+1pJ+EqBx1 UCW8dnQQO7Ho8iyG/dx03MpknNxcDj7AUuT+7AzSecegEzNvds9uDZrhxEFZ7FBwkOFcl44L7Ee1 w7AXUT729glG53p9T3eWZMsslBTU56ZtXRowivE86DqjYXfQRvWDks3l9Pvj2ZspS0IbALeemGJp GLumSR/UYOXM78vwGIRHIneB20SlzSC7btza2uJw1t4zQmtmhyIqlNdEu7HPNYNisTwj2e/uKXlI myzFxlZMqChTjeqIgZOe6+c3fzbp05UYc3u08PKdOyN1bhkXa8/Pz5teaSv1NdMzdMkbFrdsr4Sw fg9n5oMcXl8cS6pYX5AYijAWVMvMsFIaon3sGicVuH1kPWupFqvKfAOxdJrqq5jHVTuqvaTlHvsh JnlhzejYyMd7YSIRoyomSyfCKAPu94D8VpPDnhHdIYGMkFIWM9KFI56wD3byStPHsR1Ss/mwaHhE bY8pKb+KlukYM+DnlPc56uLP26/+uP+AMd3mU1Z5hvv83qp0d8NEXfXODeL1B17/d+//PRYT+4ds /f09+3+iYrt7w7/v/9Eh6PCS0qKif+7//Q/a/zty5Pf9v6g8x245LjWygc2H+uQ78qiYIsvEcIPn fPwBrgYa/pLFNHaHM+Ust56KC8xjV3LMF/dt/3yqefX9SGjKvn8j2ZPxxZXp/Q9YJ4L3IXTew5hx 6k8BgSboAcrHq4QT/99X+lZckfl+k/pBLN4dx8M1/HnHypZDuglvc/uUSeIZNkkcT9THVL900wm5 K2lEwds+O2syp595IpFinIJHCVz1EBjrtX+evtAr/XKn2ndctj4pKXkoyHOSyo2WBz23Pnnww57k Uqmk+eFzjzceL59jZavpDvxEK2X/MrYa6OP31FHPEGGs3bLsl1a60EEUJVJSqOOJ+xefhQ7eBK1F OXljPtKWz6WJcsEvS71mCazWcSvSvuR8yOy/ImpGNJB3/3z4gf9idzy3u/xMIlXXVdaM3/s3/3+l aXVEpB4y5+DCo4IngKtJ+4TLiYl1hQmXPf9nBZmgiU9QmHCKe/4zTRnC2/sLZ1PX54TFO4PnDlBO /d4BYqE3Me8qleHfcugz6ygozvnYvhhw2jj/pmWW1CmntNrPTUiMa04sufcnMdPbhPuHxe2NJJMO Qydb7ZS4ycO6CY4/WY83krNCayLHnmRnZFzwuLmmuYS6ZZ5qHPjxywXWsAtM2LQUnqtiEsc9czlO jUcsNqyLDBeWpI9lYT2SkrvGW6dJ6O8/zRrCv6DcIwqunuv9uWcw5Ufo2XWEiS/+A+x6WeI9bMeN kjVBDlxBgnTUov73I3F++pGosquXvi9l2L/SqqFOpKeAJOIN6s51+ZLQa4SX1QlZuiEV8rDxljt+ 9w3QtrbEXPM8iZyP0nmJOe9eGMNzjYTbc1Jsn1MYqREbcj9e35ahZrvbZlI+d37IccX1dj5tbM3G GyIpK59YERPrITjFHNuJ6xBK03MA94E2qUkvsrVI49y1EWyIRvvuXsoQEYulcwNXwO2UBP5FJ22F PD1R+PIMG05GgjNJQQNVkGNT5nCAqQVvX7xGWzgwvihzwKmZkaJ2YLUFn0kuofSMWwvd6dRkmf2c +tjlL5xYEBN/s4jCpVWd+A/a/qMiIRjIVaNiVDhw2WnoiZYWKepHbWzvj54JSt/so4sQB3Qv/9As ZcyybXwCk4tE4rJfGU6sH5jJ+nmWwSn+SC4ugHGLf6j+WoitkTH8AlJmtsfYLKQmySrA6/b1V6ju OwTu2elEFLpeGAHztgheCEjJFBhviXinv1Cn/6aQETFRc/HLYQqmsvI9C2Jtf9g1+OzPU7gPQrFF 4hM1PHzeAG70+D1GBHnYvOk50W1f7XshJ7fDlKZQrQecuNHXgdcglIVDl72JPfNiE9fhSk+RTaHy Sn9F1O0oIr/XfMKwq/4JgKvXWwjFI53sPy77TnGV34CTiQka0q3ZbnZpxNuvu6emokOalu919O3Z ePYYuE7ZgzD7j4LN3ISOV/M/VTQ/hphDn2h4BUDDDyd8mdChV4pyavxvUhyiTa2TV7z6XR9mCBfC cAhiOXy12NCHA7TQ6B1bLaBoeNv3mAjhEbNzhWc94lBB4gihn4qKP7DEBytl54usx6ynSQ7rr5ll LJSKuRDceiSxxUPiFCV2ihIDpeYalfF9KjtFril778SUN5ENZ7uHsv4+lQHB/YSoNDF19W81H6St vyayCvacUoPz4fCnr1NZm9qfElmv7n57j2JoamdC8Ex07cEtX4MzUaT3INz/V814k1FZafsNwtBe ygP5X/2+1LxsoHPw9b5/Hov+71S+DuCcDaOtGxhXKqnCe+7nnXDXYLon/13xcY779g3EhcMirbew xd1G66tp+eKuA+GW/WzuKzEX7tyicA1lvSDmN9ilpmLaAak42nHNKHS7/v3CHZMrzPdNTJOLH14S p8Sdn/NL8PEiHp3ook3bUWp+GoCYpLjR5FndpUmeu+pIf2B3EhedUQ6tH2n9ej/C8gePX8SQDeJ4 dpZpuWoAVmt2z46HnoO2zFqWjfSjxWz35gtPW2xsnUvr/JS+x+uj5IpkPmc9ehyZQTKVP2HLHGbR /cq7Jc5Rle/7kB48y1rTJK1JP61Zv+dLzQlI9ijlc6GpjExenL4de2a7McWR84UQTn+UYhAubN/O xdSgiCD0qsAzPX76UQwCiBww1kyz5IzKlPOO148GPEH4zX71+CIUxiXECF+Tc0yC2q9d7yMp+nUp xjx02xpVYeS9Hm6vttGqeeWg+UVHC262p574L6EmDD6FVyVMj73qP5w+fPSiCqpVsC1LSMcozZmF mfdGUi35Yy27tGUr22n/vglrJ023HRYE0/mCM62TGq6Tq1hd78Om+oN81cN8eZE0He/idjPHPOyq PxjjFfDy8tuDyj1b+m8L3UVjXyIOjmD900fn7WK+5WElFkBaS5yr0sIwObm2XMfJkjJUT3a7IL0l ISHwszOxt6qA8/EuDMXJa/ys8rOfAxbdRjmdjvOzVuNdKU652bJdsyWHevfbDju15jw2IorzpDvY fj4FtJ/GfHEMv5rX7JrbZkC+GREZ5B7UWQVHaLmUH/Km5MOvS88fasCzOyhenGzQ5Anb6vng+hNr e5jKorsZZPrN23cw5efFU9TmVth7anJD9k3M3MH+1zYW59hxipaAjbhEb3/Yz+bRyGPK9yI8BO3S DUqfv3urCyE9xstjwbmfQ43vwarzSnBj5QnmM8P99Q+Pi1IDyxZUBiSCNF30szIIMdcoIUThV07G G3qit/NczwZCxkz2fbaK3ZFDIIr1+TgrGqnEvuFDWOEgrfeo2yv2FnZq0iyaNMqkVTpCukej9+FE brcDxwpjyAf7ZyhsTPRhJkrdgzvCth9h0daV0YasOM2kz0tXprq6bb965HF2GmQGmS8OV4QY+DSr u/Q3l+8ce79zldDMUfl9+aX91c0vIvsPpvedccxtuxQ9nzf60orvYt62f+HQeWnEkSvdxqcWohru x76c7p5pqci0KEW+JrR5yCwv8n1U8m+13/2JU2QclWIIYJyZz3i3Xn9J2XJO9oUDHEoIuxNRebhE dO/WxM0CAwd15cg5CvGmJcs5S+Tlmx4KZ7yf82oq0dTfuSSje5WjhWRDbgEhclvy0UPGF8BoZqmt +7EXzjCfi8U4Azc9Dm6rkbNm2M4NYtSZtOYfz7G9dtLrXWkZbetDzzgqYA+Zp8NJBScBFPLz1rF9 MV1uZj7tV/WiS9h87veeDO+DJwRFZlHVPA7iv7RPWm9HuzDdpFBeDh1j68BTfuiVV5s+bsx+3s12 8HmtISdKOTsXU5fkJ3PdhJrM6soJgvq2WtRVNSKcLgU+8nGPLMJNN6KntLjaRjcpNvrp7GiDvYlP eXdJEiwdPThh7SL2sAVstylzo+A28hBs8X7Dp8I7ckxGfO+y47OdjENxAceIqcR7HDf1oibzio8z l1V/EQKXWSC0lHRTXaX5smTYB+52MrylLfkdlRhXpU1NqWI/08Co7k/Qj+2i2/xCyCDyPUoUH3Uh xDRKcuh866JzCGyqzaUnOc3eRDu8PFHXoCdgTYtq/zwoM2QQM+L7xoDjw4JuzyMIpymnWBWVnXtH jkcLjxzSfeHUTW3msKs0fGwlUisIHHS7kOQ42KNWsE35SEZl8d+CVKRahHG53vA4sVxCToJKwYRP OetOrekSnv+2aPBDoa+Sybhh0DLnh2zYp77+xjzofpZv5w/ot9tGDc+Dg/dGtlxYFcLUatfyXQ71 zzU3y9r4nptvI68xe/9wYyPQx49MxIJISPEh14VgRpj5kNtruc3ATOqE7fPhNOKVlAaRaw84RK4o n5lUJqzy00bd36d2LnMNF6fIsY+rexLblzG8TM8UD8VXscyHGKfSotTgoTi8Tsncl4YfRgVuHur7 5IOyvu0XHheddL7vUSJ/ETH4UIazoHK0mmwm7rZPG37uo5HOT2SlrG2ZNjw7HeEBHkA4PG+OeV6Z KXknfJ6tsuTK4LtT//LTfeDlJt/DtsOCNpSip/8Xrpn9/+D8Pxpjb/4PWwD8X6z/ScjISP/r+p/U 7t9/SIlJyvy5/vc/aP0P8uEv5//lg4flIg48ULsdOtCX1TIzwdEW3fnkFXhVdrI2DvwY77mh8u3W E3sdt4Fb43r6FwSe8D8JfHZpOQBg9jE99Tefsc1N2TyGuuA3LIIjXszk99eBT/+ExRo5jfOdF+Ed 2mnuGCQPtGuzjfKFe6RGvqbPJMUvr7kq1FkBPthXSs/3wU0hpTtbIiHq263+5eVHBGa149dLb7IW /TN2sCZ2KHdteSPv5/a2q6NlePKmQEF9emG5idnekca5frvhuVz8xrbtrOSF1s01GqmgntVga9so YSAgDLWPcGYBLEwOtd1+dvGVT+pPdztC+OD3i6X2q5+Ky0U3HhP7+7cPxX8dilcrGKx8+MlNgvyw wejI3H9/1xbmmOiqf1dcnvdfR254aeh0itygXgAKueZcWX+/aBO8OtLC0N05fps4jw1JvTjScuBI p5BD9XTERWxa4THs4NSKeYplLwbDiuSAb4AjclNVMkNdT4PBCyNcNUZYRVb6NO4VaWX91XUiQP1u vCMUbVMuJY1kCT5D4BrVQIWgyslVUvdXFQD8HuqPG8Eo8fRGqcdKGM1QbuKH0S/us/ABwwWHoVGS z85FDszy20I5Ai8AhecCJwhcl/0ZrxNjdDDLYSGpqxzniUgT1jeoK09AFf4RrgmOY4SptG4PpCfQ CzwdmJo0ysuHgg75uQMRuu9A90qcRuUFH/BCtwNrXel5wuvVqvY0GPHlm9S58H1PYUFCAlAIFyFl tYLESPiUO6QRO1ulf7o4NOcNA4Ht4mmFxKqXqBcDeNLSLBgBGqEFCpUDhWyDQPt6qZ/EzkjlmWtL M6MlCTEjzEgWcvCsE3kJA2QfJ0y9vTzWYomZvAZETzcOt/iTp7oEYxhnfE8vk1xDVy38UlsNCKmK nb2w21DXmdON0HJOUI4PCJ3OXv8mBgel66HVMal4JUJfAMy2LKHUWL4VFExeO0yIqU6oJEewIcsS coZ1UslDlQeQ/ftyRloKelnJwQkfBeSDU/OmL0itDjBvTQ1b14yhJx/ZQwl+RpfM3p8kGJcnNA7q lJPBmdWwcfJbv4vuysQYq8l6ScLpGmRFqi4QKkbo8kndOuMiOiJoHAkrPEb46Vjdfnr+MuECvEqD uNQ8cBpQJZ7tc7UC3o18jbdyUCfAirFQ4fqB4LjtC1/GmPnsc0eDQ8GCRfuK9o295ijiUigv0NvI 0bhfDq44Nk5aX89+BZMDZ8rt5IFoKfhX3rqxFgaQol/AQJguQ9a+HW4RKdVXvvAcPobJnjNXAExy yxMsHSalCV0E2FzZqEshJ8GVEDmmY4SBspMZwKlTRNHBYdDFL3VDTB5CFPUJIJ0gjzlM3lUiwKo4 xh6xEPdI1kMZQIdJUUJea9WyOEi0USR0BcAaxnX8SdYxz0HMPoKHPVG0nkYeeQwsp4AuvASbMmgp aH2S4DWgM7JvrOUmpno/Ybq4HeqMBJa9wPVQcttTEHOEcIEaQvcHd9AlGJZLkiS/Hm7RBQUZADw/ 4QKEvDLSYoQ9RGYbaUmvSugLg82VQkfOwomgHyhSmWAGbA2B1m9hQf6gESb5OTg1Q6bjDxzDKFYn BA4Ea5LaLMCdbbdnbtKRFnOLKtOolSThzJ26lfHK8Zvft7+4rnBkjtaqzHzabryJWO+MKi+40D4X iy7z7ZTxBNcCe3fWDmVrVgfKb/h2b89Lle/MC6/ZLjZGbV0U5DBaN4eVBll0B5S2b65lGcXaHRy6 eKtEyO5wbOwyWnmquJvXvUMX6a+0mSM7mxRzflXj+4avE3x8tuW7E2QP4fOQzojLcSBbiFATBBtE q/vDjL1grJjJvUC+BEHpLcyJ/HZchwdoH2phwlg1IitPapIUihPkwMEXRQmXq08DUtUJTOQlA5BV JRLGU5rgQmo7RbiNnnwOrhxsHEVYYCdfwKDguhWgzGOQGghjx1jxvFaOgo2WQ1FkXD3d7fX8ax+o S4MLNaA1DyGFLKlAMKxLcBwJzt5VZnTdqJLzfuLEO82eJXaHZG0gey/BuCgBjp0Mp8uYfJJu1oST WDIT0yi5xOEpTBUUHNSJBzVyn8iBKaVInXu8lQnngDyIA10IkaEWc1Bw6KuCN/1T5xDByZ7YEwHL 8iPplUixTGs95rUmTVWvggX4BBfy1BYbfKkyP3PZYdKnVhMp5X6UcB485vAyndqYkDt+jHNYR6Si PUXYmgOumfUGFlutTwhCHSC0Ie+jVWFs5A5stSThDYoB0CQeJn0cpOtNACM8EOxNHrkP3C8JvX30 BOFWkWExdCRiINiN9JCRcBhdrQBMYqrNgGxhQlcQzAKtXgIddxDABGCtKqG64HUidaxlrighczjY GAgVIrxONJMHhAdJce0afISGN7C5cihzAGy8hO6N1POEN7Q9QKgi4Y0/SMaoN9CRkeDXYNgT0tTc GZOnsETyCXIHJrkclBsKtgImx3Uq0e26P8NAl7cwVdsr/BieugTjEFiLQFcgrII0Mkp+KER8qGMc Chsg7Y+BKZdCEfReQUGuKFj+ZQKOPBQxMjUenEkfKRXkoeJgf9AXk+wMYq4Q3tS2v8nCcdPjihIg +7R2phYAU2qhIkUcT/rCYX0vhFLmu0CXZ6nEmwDmqYO6BbjwFWR+CbOs43A5yft6DC210b60F11t AQazwnth1MJnMB9yGwbo9IE9xVTHgC2jwVi6wSMx6sqEywMaNOiu3VlIdP2+G9IZEqndC1g5JHeC 4jUJ06vDW6C1Fx39vOmLQu/GEJgUKN4wWgFxqM6kt0N5ANmAVHdITAm0EV1NBsVDYDONUFbCwwYo jPRQgi4+dTj4LawKz0tYwiYLANUBsJjBYDY4wvUNTHp4ilcmEJYzFFwOxn0dCg4XeuXISvDwgi2j 1QeCzUkfCbCVMeuu2LHgGfLIA+B+FQer8TEfXdJDZaAzGsZImjKAo1Vb3UUJNtXQApFzYAqg+AxW QT4/GMxKPk+ULYdmkj6OHWukR8rq46Am6jmfLUFoWh7gHA4OIQdvWL2FSQ9YN3Dx3o9jIiSRH76F yUAsG8CWIT9YV63JM7d9BBxpKug2pl1RLoou6jErrTJ+umsgSM/AbmxC6f1yaJ7D8/lX6OfDcuBZ LPkZSPdG5rSP4Fl6RPMA5WaHJeHiPiDpukwiaf8ToXfbPCTrN+Okpadgc5kmWl2CNb0Oyo2WmkkE 6/npGngO1p/4Jgv/xD03OWLcHQyLONetgABkY1Lpjl0dDSuEEOpGgpPIEU48mHYQz05wWPZ6k6q7 yE8kjbPuOQwHXV+kxjzG8NS358r4CuEAHrUsVeIpuvfJxbb3vRbyQNrYMxFdjLpKa4NgVe1tYO3o yp0x60D7k4SoklCzoFSjrlqOREc2uGtX4HjwCi7LR4YexV7UzlRC08s4NPM/D9HfXlZ83aPmczZb 4MyBrwIvC2GxjVBfLH2cJaHx6761oTEZ0R7E7b0VrjxE0pgF+IHPNLUc6opuF9pPNsBUz4LRss4R qe49SqB7d+9WJ1j9rB02s4/oaB/p2ekwGRM8RvpMaolwxuBrK0nrF+xfpG486Fe0ewE76VBd9MbE G2Uj6U/e/wL2UIlwGLM2U08aCtYlt2wlgKaXRqb4WMkuNXfJlMALSlgy5aZtZaijxOSPq5y88MYN lLgPA9040dvBNHWg812qP4Fjd2RjySNHiI13dpTiPWcWGh9uYD9mATuTIqEGVtGxI9l2zp492rHV 25Y6vBrdwneiByW61k9fRsmEhrl1ICc/SnXH7nwb6ZV660TOq5JqFifHFQTX2tPfWyNcl1Ayy2pg qWvpGQjZTSYyzZY0RK3WnwtheQGrUiV++OqoW4lljZKRpZ6Cc9Olkq7i4CFwwO25R/xeu7ITHTdU ts5ByFXZPqj1byPHMIfIVfSQRHhDxwXoBJ+B1wFMtQSoeYHMSI9HFbDq0VxREuUMRJTaUzc4Ze9Z vbYyHBxAqlgveJWa/jzm83AERSh3MCKWDOItMNHvlgkaWgtDEZDLQOKhf8QcW9yX5l8Nhfchbg2a HeTAXHsO3j0D0as68PcXGwZcbHoHEsmxvU8z3qRGS4G+AROyRHzveeqUQnW29ejjw7Mjb+ADlFWn S4MRig3ZIHdB6itJpB8vPsBxlTefyddQsf6OI6WwfMWfPVfen+ZRqPzq9oZFirFbVteiopM7OqE9 Y6UnYWcmpWemOXBK32lgizfHJk9/eeozcmK5N8tk+Trv7ETKdXyWbOmWnSueQHJlb31rdS7r+6ke vtHS6CoenY7xEJ2SZA2HysijPbZaPTSLIzrsbbOEsR++tLeoQeCDSGBLQOY7iOvb9IGLjfU1+d/y ZLPqKUGdiXUWk+vaW+GleJHaBW2p1UulP0qzwhJzEzi12jPzkvXbJYwSrTs/ClIia1bwRiLq7dS8 fjeSgWDVWJPvzJPvtpD5hFm3xPmmT7SbnScIgRMP8UG0AMWRmKWK25GyTzt/IMdOrPpyv6aVla6s zh9kJfGSMnt7H7mn10Mt5R+w9F6aW07mQyroDqGeZZCfKtZ8Cgx8DiIJNF6SYWZLneGpontd5YEN K+afrpzemsgaufBl7vJq4jtp+KRvd3ds0aiQFLjC/ANEftLrWB7C9sQzDmcqtFxTHLomPGgd2I44 mtbx7tx/0Ws2VYCPP2a9/Izr27cbjcIZMOcgOn+fryCFIWl3qgWBsc+XB8wa2Mnvv0Kowr35OGOr UMDaNmtT+t6xFZHqQ90XC29IVbYoAR75+jl2E4o3ERaPODzH9Mwwh/5Z1xP+i8WF1xpOEgNmEDXK ++Uow5s+iFOzXl9zCSlNN5ys0zrXYjnkfaMnojKVlJPxCnCO3MvBqI3M2WL9KmlhS0UHkTL97+U/ dsLBFhYLPinSKQuZb0+TeEY9LilZTzt2CJMNz1BXLBX9aFFfWBbz9rRqOz79tTBjsToxKciEGxwx vrR30ksnRH/ldUvS6nUIVzzL+nRqjUeAs4eIpBqkYS6BVtoJa15DvJFFXMknqJ4EOXFPnajTn05f MGOjds59uSCrYP2w6fl9LXlLE932OOEkk05O3BnvxmO3X5DtcajCvOqHwTkveb9bfH3xYk366lvE 4mfj7MHthZUaETuxti7lLfJF7VUCuJYwdmweHLM4PuMU/u1YL8IU/jw9pzoU0UMApQj9tYPc+xJF VpJL3E447mTkWfNKPcY+/9RL7NkyjOk/MCMnDl6LiKWJY1/V71PWu9J0dwsE8/0jZTC9RJnOhaaJ TZVcq66eM71hgY0nCEYWsfdsxj1EZK4kd+3oMiBE3RcX01wLmaJsnB/hKLdiirXWfZrd0a2DwWk5 5WlfTdOEg1PTOO9uvRTRzL+KWs3l+ph3OeHSGCzP/HzWaMTieO7iR3zX0y/Ntz+K+zohLhhJ6zMa ssFRDn2+UFdd3zNdfaTUm1PsDhnqWac6Yn8azjwfPp91RlsCS+4RE7QlovvLfIgXeF5clEIvK+E0 cz/7GK1IablFpbokTtnH1/cifcyUC55X1mW5aIu8bH+qiFjR5Z99VGgEj3J36rygN6gMp2z/XETt LDvbM6Vs05Zaur8goR4/7cIaXhQG74OTFkqSvBxzjxO3c/dgUxlT0ZopiTjj9B75wDnjZvAKXtfl C8MsiqGxfbFPqvkrF6ehxGZmX15W/tup8iYb342aWaj/B6M2a+LTctFBneoIOac3Qxf1cy9m3yJR YGFbjpUeVeoFN+41fQUuGDoS+tW1fBrKlBdfbBTuf6HcBAVng649z/3w9CZrXqILQHXc+iTmVJ7O p6X388r9xtiN0ZMZswxPJ3xqT0v9+JRBRLaSXHWa3Wk2jNXpuhuItnHPNy7SXsr7fy0khudjBOzQ wo1zXjPFyI8VwpuX7SeDvENFEtbkjR0mFBhC7R2G09qSJJRTBfJ7DTkscnrKw23Wfn7nfVX3afUb fqqHUag/5Wl5ubsUk1wLNSRyx4n8s0J+dBs3ZjmZmvZorWVy/GGt70eKgR3y1Gr9dFiC57zOOlEK UbAWu+KkbVxyAJKDULeay0ev9fZI/qxZVJtsMO5iFPmgXJCxf2os0lbOmUXCU0KiazSCimlfSxDm C45sTyGneBImyk/C8+++XSnvrud7LNAzhIYRZeFrQzenhRq5E+Q3oGArUfl53hEzIuxRjs3rz0Kk YXiOm1HPwhlyOS2UnHcbnlLQDZFPra/fOUwYSPPIk+hGGm4Z7LwSbPyWl3I/SzH5dYo06Dk1W5GH 54tTsSVoSCT3Zs5Q6fgJ4GCNkAIcxVrIgc8u6dW2S0i35zUqFvYZXBfxIy3YEI1aP88FCpHaEJ/m pj7WG33PvKw4h8g0dAT9DZXOe/SmxrIAuTBS+rSxpdjl48SHkyTcydKv7wK/Y8UTYtuMXHW8V0eP cWkRLicNQogF47nvhJ0gpdVh7C89U75cLCQF/HhjynfuGIDtDl+1gutRHWKvv7KtazZynvV2m+wf E4Hs7Efk9mwKbnVxKB/5XnnQtS9ypr0ovoJXmC+0+1anVTRXHeuXUU0sNyB4s+YvC8qyIiYzEA/E TGNfDRwe/3OdMttxxuJ8ocI17TZu+KqLCRI+mirrIyvNUbuc+hO54yEbn9qbk06KQy1X9j2jpiqW 9SAs4lN2UrFYcdcxQuF9wZe0dodwPnjpo6xp2tPaXn2qyckvaCZQa2JpY6zWbGtdg5SCKJ0wvuyH otyJ+Fq0TOuye9MpsQKI81s0s4BwTyeOmFS1jMIZrE+n+PIGn3p49NB9j/thqYilw2H3fxBjak92 +A8SXBXIJ8HDWi+GU65O3WRe/O6wzD1LFCpxJZDTLxNcSw4m1M1z5mmRhpCEoI1nsS85/7iIfqdu h0FBdLDNsclt8I8bcn97/wd4hLO1+cfd//Wf7v+ISopK/Mv+j4S01O79T5ISUtJ/7v/8n0gKt/Q0 bysxK1zXunGfnqmo3tFT1aEXbokpMV/DP7SyF7YxxSHtzJ35cUgsjh+DxOJtcFj+S6a7bfxmeAsL JIZfgv8xP91r+M2c6UACzAoiu9gKIn8hRqe+S3L3g1mYH/cISSfzkP6PjkqnjOS3sbJD8lthf7VY 2tibmdrw/4E81soFyX+Z38qCDkEHe4g0fbiLwkwv21phsXRazvZ4ficrGxv+R0i6MU35sfZ4u4f8 DzH2aGF7PA74jfdvrJ0eWeH+yNLUHIens8SaP0I+xNMbLPl/7/LlX81WdH42/E72eJuH/GZIfubd OpyVLb0Bx48zRSHpROz50Tamzvxiv4ttgTG1tEXa4QD+S38p/oWkwF+LYolBIu3+IMovursFlbv6 /0oc+RhpjqcLbWrHj7RF45yZbezt0fyX6D0xf7SLaW5qY2WGoTN4yG+K478iCuW3t/hF5V+479L9 nTXzBTszLFr+t8/fFEp/8LtapLPCWtnid0XdVaSj8y8xzO1t0XicKc7K3o6uezxmV0F04sy/9XW3 45fpGsc5o63octBlNbVF2yDpWL/ri24MZzs6/K4RMfy/yfwbSeSvPjM7mToiLewxtv+iRis7um+Y 2uzK/Lvl/lpkrNWuy/xS1qPdG+r4MXi6XE5WuEf8uiq3VG+YqKmrafGjMVb2GCuc8794DfMv1Vra 05ni0b8Ma/eLiLkpvev/Ku1u1Q3Na/wi/HdV1Omf6rrX6I12dNvt9p/Z/jckrDMWh7Sluyf2Mr89 Zjd35kchMXZIG351ES1+DN3n6EbF/rWtnZE2NvZO/4HT29CFoZvMnl7zRw/iZ770y/1snP+t72If /RKZHryc+c1t7Ol9oKvvdya7AAL/3ucVdPV0tO7cVDJD4px2HU9IRFjMFqsg8nv1X4T5zXv+4og4 exzdqr97L/MuO+yugX4NYlM7SyT/H6n9xfPs0XQK/4oI/F3SiP9DpRH/+6T5bRD+DWlEgf+1PLvj 49dg/EuQ/F/I9IvmX6Sys7e1sqNL9W+J/L3iif03iCf294i3m/4qpP/rS0NN644ev666oaqikIQS 8z0xMbp/0t8Y9IEgstuk9FdYCuqaN/l1dVQU//D3Zkp/oPtHciK7Z1L4LaxskL8Pv7+X9l/Osvxn xHfvu+R3wuw65t9LdhflF8bfRdvcHu38XyK9i/B3Uf4VBP8rlP9yr+cfwH4jL/L7NEDkt1kB85/n o/5/ev7rD87933z+S0r8r+7/FRPbPf8lLSb95/z/f9L5L65zfzn/VZgTSclhRFdcOWS9av21S94O 2x2FNSlS5eXXdDE4l1sjHJ7u2az85mrVqXMSSE+TYOSwwLMmdtGVhjut/9ENsD2v3ydqj72Tcz7v dFOSVV90KZZpJUEv/llT47SW3X2+t48e/TT33VYCDeoUdM/XVVcIcAJnFAg6Zt8Pmfk5XoZInSOw ZbLAZqcXwOsm/M+qshSlyhuABPZWBnllfmeiz6d5kDWTVhIeDPawNXODK+xBY2aOiFO6QwbeS2lq eIiK5sd0pjmsGE5mYSzpq39UcF77qTuC1qcJBdoj+PcBsj/NquTImanBT4RMTMNWh1piD9RzuDhG M0JKv88Bt9u+6aj3+cH6599FHvwwJ+g1BxSVixY7QU70E739Tb3YSwNeFOTtgZReJnGBhzkrTQ4/ /wqSTn19vT17vd/4oHvIUXenvYBPceXIpQFBXvSoUN0+otvz+0Wh6aIspAUOi73wgpLLAzXw8APg GnPmrggn//mAZGVnTWpPMxDdRkfqmBh3M5KnMHYzSbw4ND3q9Kr9esCO3GnSQmjrMKlHOfQQHWDp MSCft7M2N7zgybSif3YnM36hbBN+jAVS6ipoWblV2rMvlytS8H+iLv5BQJs2BTTfOc8IZU8P5e8Q kt+45eJN5U07D2W/A8SLI+OrcyvVc8oVM41O7okzLPTmcfva5ZuxD0qH587UNxxnBcuHyZJBw+sF q18PEofWJudELxDHNhoKivQVxhp+BOa3F5W/cT9NXVWeZTP/UpLG2D9gjqGz9zwCdC6cfJb5D+7r TFrUsX/kB7lG4yiYdADUpndnZ/sK4Mk+nXpDCRv6cF4is2FwzZIB0gDA1U8eyM1kAYn7ALu98BNo DnYSeADs2Uf8Nc7IzCTSb/gDGA60Awsp7knq46JRwYGhk2jVvfD5J7X6ReXCA377iEN7CalP/I2K OA6A5QwAfC8k94kQM8mP6W8SjvEm3/N/+h+3/2eMww4T7uZc4VYmsdXEWO3/DfH2ARDJQPRlIA4J lOm7iRQvo9WAA8TrewnJT1JtipbRu2TEOdChrCReNroT3AL2wSe/cVCnnACvIn3JAZcruyzfMZNq GEF2pl35dffCO5/QBnd5IgUH/LBLJkN7qKW/OqxXxMEE+u4HE/cRrwzInd+lW76XemaXlxAbie3Q rjAORfhbvxAZiCr7domdRvMc22Uw9IT25r9OQue1UF+zC/k175rK2mqlw4fAwMKx6v7ARvYt+ap+ htz4Ree8akx0+zW3FpPuwc/l4z9Q+IT4xUZGIAqRqFPbib9C6LNFhzKTbo8GkPeT/BJOUDeNeX8J IO6gyiMxUsM+HmPlrAikvKN1FAUOdnUsSFO/lvOAxITBoRGp8YhAzf0iyfMJOB3QY3QcI9B/tiDL doC5r3S/PSDRVEkuKwYn6xVLQq/MtYBxvIDYbNYC4UUkaDYUt0HWo4yaghrYgI0TttUOLzmA7Ln8 r1c9KDQCVHv7w8swNeJj5pKwddVjNehJXf9ntmMib4oF5GbIzK6RDgcqAw4a4+rL3daHzK3lCb2F b2C3NzgwLx+oaErqzttcHrvQIx+qdKF9ISH0MxrKW3FhGCvmWoUVpt6zuah0K4z7IO8Nx89CoOT4 Au0UEDR2dpTImZubK/598kWB1BiFNOTLQL5RFNq1WaQa6GDLKUGyW22+zT5Xk73wQweMwxC7VVpA waFj49gD1gMpPrAnLOBpkl39jWh6ZZylg+pGfSTsKY0MZlndGkh5VTudigFx0gRKefb3jC5SiRTf 0FlHcIoN4HAQQCuWcKw4+PsHg8OLjys/nQX8SFUN+wNg1i73+FosgH5Jd/67S1+uNmA1FRlV+ipH I1VBWne36NjmoYEKN1H41AvE+NnaUDsXPviQqfOhW2yyXQvBtco9A3EvUBn5aebG0vDm8DUslL05 Mu9OeglH4Bov0UrTxRJw0QQiGk2gYHV94WWqWwf7EAVLDRzRKSc9Elvi9hZu5FA8XZwt3u4fShtk bksZMzS2MHmHKp0/BKBHSZeGzv66ui0Ce5RUdIA4BE65k06QipYbwJezvONx8IFjAykv/H+71a0a 3A9cAPf9R9fZuXBB8pWo6w+Kd7/7v91HdQBXCjUSyBNHALlomLJISUJRuT9MMdDf0SGZOqQjUpVg AWbVhIYvM5NPckc5NGeS2+bBrAB/O4eASBimeWkoH9T42VvtkDxM7rCzDQatp8wj+uNJbV5Co7gQ 2AGhC+S2aY3bw6dFGqpfCinozHTYOZDze8uRbFcyoqypoGa30bDOXkLE+vtScpsYOHUUkBpmHndj h5PW5EknuXWOQ4TJJa7eDoLDsGtigD4TxHZA5xCwrAamKMDpM5yEvlf+vMMLraQSVW7yxF2gPBw1 u2QHWldwaPVL02NONDilB+CZ4BjXAZe9xDU9L5otqcRdOXj3zuFWspfwx1y4FCT/EiTNjp2uGhai VZo56UYvXXvZ2OSXvytUla7qTeOCS5DQMS6m6tdCMXHB4NmedQ+gq0KV3UH15r1gfzv0S04IT1F2 eNwL2OmKhJOgrvI5QuS5RRHDQM/4FwIQVfDtkLhnfcNs+LA4gwz+Q+wRFMBF7sHlRUtvNO1nXOlq /u4bDaZcol7ZwzHN1bwUnGfBkhvJAgw1JJTIRPd42xMrsntsANLEeSD7FI2L0J/BSRAHy94I4SiB QmDt5XqSXlnC5qu5QR0UaFatKkvMzmclXxqKUyHVkYLBkYNsYzrDKn61Co+ToJADlTNZ29+xw+k5 rYdvw788qgj1HAZfZb9kendaqJ5RYTgOStj+UOL9NcMHhT2+lHHlXpi9dOb9x69QGXPN2z3FUpEv ArrVowpk2NPc+OTJFmkCMmOhir04OZsRCpaLWqnDCTmQGlMlRVz2Ao2ctoRJl3rZScdAWSl08hr/ rtPNjJ01BlstPdG9mdF+5EvyFrPghl063R6PMsvCaSLN4z9qFd64//zC7tnKrru45m0S65V4Qric XYiblMHjF6a0oPIanqh306L9UebDbo91PgfU2f7Ovg/pr9b4ohAiTo7ClHPofG7IgTy23xw+5Z3/ vx0G/heppNgBl0NEh0N/VbkXjgn7bVRcJBD2wkfBE+n3vFAZGAGi1eYGuS0ePBGwSMwoE5UhP7JZ XQEXmdBPUVF4Me7NV6jpYyCSNCTbX6ZaPFCcEKd4gDqk8WaYrv4XrwfjPgVaoustFGM2bcHqZ5Hx bUq6WZkvuWnotIkfpkWqtYr3JocvEdHMbaQtefKle35YCESVPZJ0qTHhNDWr88YQi/prVI8axpdK eiREDVirdSgXqouBkgx03viPgSeuCJOHxHyTn/tb6N7dC3dL2gOg85mpZo/mZ4nZRnb81Rz2d6BU v8pFA5AG05OBKPoKkdNFilVr6x2G/HKjR/w27s0hn/9S0FHSGPvAPrjCWwy4nyhISqRHWDdyhcye GPDGgEsUavtq45Bh3R5uolVgbAMeQdwDyAULGZtDB74eoOuhxxz9VKhYaoXOvp5kdzhUAm72ZJBX 8Z0/72AEn/3bwZokNcCPy6aT2krGRPZrcDjV+6Na/SN1X6B6rVxnjXzPwJ+KjlFELmK3rpNGSsan 5c5SuzVT2OL9B4/upS7255XkNWQbcYmhxjEBEWU7B2Q2TXxqz89nnN+8/MBEx1z1M1Fhzns+zUfD 4bkMZD5Xi5bLleTwfJh9x5XKSPyZ8MOg1GAFA5Uz4dwcQw92zXH2NwSZUGKFtnuMvVDqSWEiFpZx Rwjfq6AWkd/MR7TjzUknZRZWMcntDd5Weg4ha7lc2nzY2kzS2A7tgULLT5XWGhObwHSvl423h18J SYPF8nH9ehFCHhC2DjTr3DhXbma00GmrTY505rFq4YCd1Yd48GVQxuAxX2xyEjZtufg57DaK5DOw G3qn6slDeXD009rpKbeq4VvFB4jWpEQuUlH5s1SqMDE1ZB+Ajq7Cu7MSje2Pg6/ILse25LHLxbWB 6OwoElGWWCBNVBqhqF2VJ7ugOQamNoLBPtgkNuAotb3+MWFswT2rh0TMl0yvCaLJYRCLoHtYKh+J +DpVOTBVC43IxSCMesOPE7JAeCWeh7z+MpXP8WIxlIFI++JS6ZOaWUpbh1KXGQk8P0RnX9IML8K1 7HRmB6fGQWFXotIYl4XKUnoxfqbXcBWNtzAg4h2WLZDOB6lSLXNzA1OtoHsZNF2VVFF7u5CQCsMg 2Metx0GqnTycD4PHEpVK2ymckyHgVim4dQ3c4gV6e4vaIYNTuqB7ow/qCcmCtG7pgAgcmPKni+mg Lou7mGca5+sUc4dyGNvDBitFjzbRfiSF9n5xa08YdEo1yjKszAqt0bslwgbN5/fxvRPBkU4p/9Kz miO5aVePygc601ZchFTU2ZHfoZM+cd2sKpxsEcb2rVncxhMuyTepk2KH6/EbaoTpN/Un11M9v5i3 I1i5p+WDh6xXHb5LSZSoseN+tgYMtzBAM7tdkiXyOrvzJ+s/lX8ZQ9+dGquZXhA9nKnY+6Ku58UH 7pY88c3Tn2f0JtzzchwFDeX3pnXmSO/5W2/i9ErobrQJHZqi+/K+pzRO8BjoRjpPMn6b2lsOLV5+ CFR702ox7gdAZZ+ElzTfTa4wRSp771Bl2TIVM5nA1zGCffwz2EI1szX2KDXwBU1oaP0raHFJeR+R LwZmXEjv12pC5Q8kWQlXzeZcgaxMyWvBbqkuYIfEz202MYQOr5wETcJoQgPrYp/Vc2iFFgRf0/AZ d1ki39Z4mRRuBUkuILYQ27ttO6FrSPK280InNBbjWL3YCEw2AOTJ6eDbIj4eM+GwvmJoKyheDPV3 qO4GMcVQCIiJhrkAnJjkANDxtAx5pAo6NyJemw+OB8Nzc8a5krTkAE7sZJ9PaSW6Gg/IjnN51JMp pwnffqE24KMdqvcTCj4v8fzS0/xo8EDKE9qUEyMoAdCnQk9R7AQ3QULv93N0bWkNBzOhNTd+eIAL ewDy81TFCJTGfaDaS6hrThEUr4ayYKFZjujqKVJcTzVUAvx6CS4uBIqXQqnkCs7BUqlGD0DW4UB0 9T6Q9s4hIKP30s6KBKbzAgvxQXQKucfjlblWvudScnkSRpg7gZRY3Cl2hdi23VY++mR9VGOTVOK7 dmVjrfY4wf2e9Js68ogXSnDEIEKr2CZjkcDnfJbadS+9U81dkqkSs8yE7u2q5FbHPLeq5LwSTdtW c3JQr8Szkj+uqVXO5g0Hw4DuFevAxWByNUe5nCaogw0Q8kuO7uyPA51GAOJ8RUVSwLof4fbiKGwU U3qRIO3yIsTJj9vWeuOuNEZYzaJFLfSx1Qz0tVW875VQ7BlLC2+DRSzs3DNYkb7+/51PufxZ45Ha cqeHOy5DOW/9Tq7dYe4PUgyChbfCDj962GMRIm4UxT7dtCCRu5w+fTap9/Uwyed77VlSjOJbd5B1 ZoIFDCQ4YaTGzH4WHiSc7/9cn8YI+IyzjhIza89aCfVYR0m83SDxTu2CBY6YnSg45zpWOXL/5y6X 6KrfrsTVkZxyDAmJ+872um2zkFtJaOjjTN/ruyBTUuEJnfHT6n60o58vPpsZ2IQTtdi7OTNUzOWu HCCq/sS8ZAT9f4zqJDmIuctQTd1SM34KaWixNA47HTxKDYEdicafC1SAjj2LEhaJPXtbXEZbqPHo yWaCVnsT2tdsmzGiCa63yp0EKfzu/0GnpoCPJe9hIfMeSN4r8MZrWKzNx559JULFnaOQ5zts3OD0 2Wlfj8bRsCueHD/6xJw4GALy2x+V4VKfhtTePCGPqV3+5n6whu1h/t419kPylVNsaZHvgB+o8tC9 h7m/zI2Wam2pFfxMmbBoRKngZHq3q7+Oj4+fJCgRZky6+pz32effSb+TgvEs01Cu8SRYahKGv3Uu dh3p1cz1xLTkvlvxjlzw/SwrVy+0bdh942a35IhD75XhA4ad/aVcK19wrDKYIO6XM7WO4wYQu9PN HVshHxTfjT9U9gDIdsufIz8vnZ7euM8XVqc+E8ghwbVx6HUFu8OZF7545S3fgi/KhbxrSpemLYbL m4jnhma5NtLS+ayzlkc++pU1O+RZZnyw7HLp4Yk2fWi2OWYUi3CB11XKeEbKonixwoCGHXMVcSb9 tOAne67QyeuSs9gEnkAjBDl9SteIOhzbZ6ybVHROkWXjENVm6GO3rNN5TddHgQo7yQ+UpmXhQ6kw 9xQXIc/bfu8LrPQsaCWs6e/YojKEQntcjm8uC2T2lrlSA2JUXQqHYrRc53TG7nKJ+KyTldPrdHBi OPuMkUTTUbNTDi8nIijLBt49H1PWPkofpS4Ejyq9DlaePblqL+NqUG/dGNDplPcyZPZw2suNvqBp 5UNHPN77k3oCvhVitPjWxzRvM431di8p9lnbFASt5l4s8Yw6Pd6o9N3/+4LPk7cmzW6boHEm7+S7 uoJuzSi8VJ1v//sanl8nDiX1doDfFq7fanTj2netb7HfNlF13LMGMMZmZ7yNPsw1LmdiY5ngILP9 CJnSR5lhs6UQIzlkVqIqHvWq+fbXxsTySXjVvZJrtGtONLLtqfdLDhNiUA/4iPXs6gASKCHEwaZE BC4jY1xa9g51kb9d2NVDY+np2S0PJxdtjVUzlAn76weuN/AeYQ9pr+c6lHM5XOU6K1pwV6T6cgiO tBbc9/X570elj+qNU1gZOymZtVn3MbY051Obho12+xoGp151VEltWnlDLMHh5yXMuGijDNvp8jNK YyAhOvaJ/EqLXf5yave85MrVg2TDftvHt9cYEVPT3V3Y3C6sOfsz1UYtdUjdJ9m8pXCfjEgIJH6q p1H7gVteayOy5xtLjqh032NHqXWeRkdU/1YiQwqqpNzhcCulWPZLT9cZxe77cucQdaOB3yoc6pl6 XtVzuap1Cm09XghnnO2L+4Vc167ZS5n/fl2ezVQhdVhpKzpgUOObk+1UJyZtWaHwtYLIinXT2obX oDqtUSgzi3Sq5oUQBZfl7/8BBA/nacYH2+nkrX10sc8/g+UwMv7KBW/xvt9XaDst6yx22tVOR1EZ OksssfmWrbWp6UMOeFGRyi6ypWQLM+feELjR7XM6J8Ndno/bPj+IMGtbYLsVgEV/pTBNEhGZ3Pvk k9OiF0KNAphcw6pp0yEtSOskVmspxHNFvgi7/PMSUr9uTaY/DbXpayz9wJjl1/nynEceW5QT3EeC q2VuNkkOh/i7K7Z/l16TSvNWkGGoHYUv1m9uIwOAMbJzeRhQKoI9ZgxYcLg7Tl5U2bD3Dzku8M5+ 9iHneQBS+8ETlIzvEE93BVwNEAWcRRVEtKxp01ykCSOtO/0F6l7bq5XyRHIZVZ0+O+0HFtmCgsUs gxibIYqNeAdL+DBJ7cTio1mJJYleJXeY1wk/8zWLe8BYXFLG0oG5IdJth2+ntr/mXiQwQkqPm5EZ 38yHXe93BHuOu3ZIbefDYuE+tX2mPwUXNkcajoPz36HYmAEJsT/u4lS9XPM8rxInPFTy5vKfV4L8 j9j//csJhP/u+z+kRGUk/nX/V+bX/q+ouOSf+7//g/Z/Ofv+cv9vftgwBaNGDrN8thRVFu0i6yCX Y/Le2/lJyG1i5BuBrr20Zc3NY/zFZwWu6VzbmmmNT7wxpHI08smlXnIr/m8JmBufqCxnc+vMSdX1 8tCoAepw3t2IOu/ONqfXh9s/VYpDEmYLX7S1PlNWgQiIWHNxStn2eMjC2/TTPzm1JtQfOK1mMbRS Sx6bZlbVjJsVmqrH94pNBDbhnbTnPvnXoX8GTZ6/7LPs56KCsJBMDGlxIsrj8eS4WeMP/ZqQd6nf p3RWlDlzuTIutaxyLNtRpqJv13fqCzNTcp4QK5209QkrJgGf5Ov1O5Y/z9lytSK/fr7k3hgNwhHw 7Dlbx0e3qZJcNcZFIYCOU10GhWLtoVrSEg7EC1z2cRkakzVwF/u8lF/PljbV0tEx08zerj8f9uia K6WKKHmHOgN3cEdkF5w1tdIiaN8wJrwv/9KyKi0vmVh7WzgVRsZr16Sp/cYDnn3e7XbfPsrUXkRL yb33MMNTLDh1FvOngJXp5Sao8KsDlI/PM64SskRPTgSfrNj3zwcUdlHXo4Zee1nLWMGXDuH8dYua MObZfIwONFrt6FG/84Kbjm1k4WRAUMbTEXLqZqOAVRGZ7UZPpaid9UJrbT3hZDPt7JLt+Ess/h8+ hHaO2kkNFT469D9UIf8YoDCTXq1F2njsbGOsJ2/rAVz7MHy1cnM9aWP82tf3qRcKPbZx3DubGX3b m5ISaYJN+oEmO1cQnnX7Iz12JJrbox/Ra97XXlqgeBgYn/yQyltYwlPxOXXjfi7LRIpvvsTmsJ3U l1MaB83nKR7b806nQug/5r5JvjrAF5LwPGNzr86VhZPPOv+dzBgNqq3+NbjiH8XWwYd2X6W+8/5A O/SP1sZoLz45jfoBxTCRwoTT30N5n3rw32YDzpTtjbnjbtGyVxYcYJkYbrn+tQ7aKJtd/J3vJkw4 U0f9Pf5ncBxPicxXIX9XlpwA48gpYWnSD5BpTzDgrmV4jyJzGD8hWkvG1xbsQViyeYQC7dcIDBTB PYgm/f3/uEyu3otYlNuuP8dX7wNMdO35T+BvvCV+FPiD4NQNWlcKXamCTSmAviADpSbAbvIQ/VsB ceTuhKAMJSGpG5eWd+wTLFRomSkrHSVD15vkHyjAhRFGwu9TjxOFhBgoFGbKdVFc6N+vtX+fEW4h jC7uQ9hOUqCHKQuY96iNWxNy/nsQbe58iOpTu1BByTAVOOeEXHHkpI4QouvSE+IxL5zVhNm7ufda LS+ArTHKa7bmc7i15vZemeaE96lEIFSfD6bIghO+jkGsGyNSPsIqdRr3Ifzf+E7oZBIft7Z8Iu5s u44Nz/EU5ARmpbu96V3/GVn3wSSnfGkJhV9i5Dvzk1abs7Z+MN2TXDB5t44gND5sb6T+amsB6VGu 07gQCuHOvePrvpl/SiVkk7oXEfgOsdTSmdDv5HiNeqjvDsGLeO4q3PgCDt+0rIiLJm35ADHBxPqc jBQGShuC8ukjTIWqA1eIxeuP47SlENvYXLkkmKc8QtDz0lTLdjEtzhbBJIgxk0uH9RJh6bjkm5M6 13HJDzTsaQsoPX1EjlcePlkYYRjdmjDMAPXHOuUCCcEXK/HQ4NDXtvqJMAhuckQY2jz6UBZRs8n6 7jhlKYboXXoMR9YAbVJgi+c+fzX5Bozin4fIS04XaFNeWJVLha+Fnp7GrU1+HE+7YjN4Qj+uVvl0 R8JiZnSGWFZbgsoZbYKGxaBCxKDnEVammwjB5tEFXcT8iXGaZF6hdoY3OQdXXo2b3HQ/H4Wmwwgg 8ZNXpnEgvO0DTtAquZYtkU8gdJY5TS8OhqSMlTIrPsyrKtRQ0hHBJ38XXRtTFimRlBi/Tgbym7Ll yhXMPsBE8Fb9klNmEiXesbQT+MlPtDdfTNSpKU33CWFob8A9D9DACyT5870qpSzVU5hZPxOjD6sR CjQJwFSNxsED8ojnx9hpXXLRlRM6AFaFame7bevfojM1oWNPJ407ilNUhag3J3xIvY/Yj2g6gJhL gl2D4GxpcQa4tbPvUxUR50GCFzCxTqScwOUHAVsA3f/pAPQnPwMwCqMPOa9fj8srgBUR2JrQ3SRF 7SABwioQOkgaftKQDv+L9PIFykQvTnv7CP4oThaRkgPs4hHHdiW4RkhcpEzQXfcRwuoU7hpBFMFF KQgFtg4iUtwR6x8oBykYhKEf4CJCp/MZwFwkvmehzDardkeH4pvjXs8l+d+ZbEkGIkzyTSChOKt0 fzflwDbVO4SwVH+7poTNAZ/mHKtQ3GQo8HV88wbivBqkvSXhOGI9C+ApPBJ/5fL2vqZ5IelVr2ak MZpyCZH+tgHfzIDTTvEvm/h60VWDQEzxL1FpUi3wvwG/dEWu2e5NB0UyCeVhHzF+fpTy6T0MS7lO CwXc7xLuONJ5VwU2sFJKzqpeq+ul4OJgrZtHUrraVD1usFAuTUX06wnw6C8eAYzzWuwmIoTuTUSk Z92GcODJLbWUloP9+m0J8YDMhXdABB4qFARMxsUB8mG5E2c9/WQmF1g76BQ0LKwJq28mMYNGlKEn widpCqSPtYVc8h+++OE6q0eyQ3Ha96kY6AL7oivjJDOlxVBosuUapJ7yKDR76gxVFYowHYClreKa C4D8BNjclJyLh32aUIFhm/6lobfEhceOtV3S+OZa/GR9w+uJuPuQfLofmVBTciiUMYknxE/+1rSv 7sfpmsykuDW+nYhbbeGQimpPeO9PVcXgmonEmRc3aRoin+QoHdAsuurbVaPoLkEGrDWpK+v7EbmT ZydS4v1TaGd/9xj645f2PvVTbWDNFuVWIrDrDEF7EEuKuy5xB3KNgPvNI+nPPnzQPQROY9elrlFL cc2rLapN5RNnkykTyXSlxPnRPcSuVbUpu0N1XmGUpjMJ1OCSE4glt58D/8LLgDo9fQFxZg+lIAQQ pMXBJ+Ls44RIT4EPlLE9dD90alIVQiw+uUa4gRgE6e5lnOb/PpUDsbRCJy2OYKa8pwEIU8mUyQgJ rYm4TMrEJ8Ddmxgost6tcMT9iLumEd/gmdmv7CZ2yuWIrC6kR1B3hKd7OFy5xXyct+Ck4k9pPpPq Jh94odJmwcz6EMB8oDwCY1PsduOT7dF5qdjHOgNml6UbRV6VgxXw4B/Ud52qeZm1CCYHuIcqMlNo KzscMW1WXA8YNgCGHYRZjQ2TeHeRJEsIlMfStFNUEeMoUHMxZ0eZey3J8Qvl/bnmUa1zJr0wysQr YslBEWP3DOIVtlActNgXP6kHN/6QBjVJ0ve46/LTH6+tDn8ZQumwDTGbawnV0YQ3aBybocWJcjnc unS7xdmDryW0fnaE8UVLXVoLYXzQ/qW0ryF9ULcM6ygWXnyWy8IjOP31KOUmlXKfnLLgYUE9K1Ug kxAfETNifPux1LveTMCpqC/UYLpchP/tZx7TnfsIKx+r5Fb4O11sHm+8/1N7Srjdtumc1z2aRuwJ xuELCAfaRCfEkQdTMu2SRuTIDZgSdNOipuTx2MlvrFNuZRFbFa8SqKHn9OEdXJSGk+Aeyor4jcmh 5GQhFCuCibkg2qmpfC/CBjVByXzAOyG4D3HzCZFnd7bDs5fi+IR4tgm/f6JrUJbyeh9C/ir86ITc PtzMHoTqe9rBpmyG3bfvuatUtt3Jwus9fwAQnHA5mI0PdeIZTaZcsWtdfvxvae6l+F2lHn2PYvqP mP47gD4E5HjjGV3qQQSy7y51D6LRHMe+Olkz1GGuaMeDSIGeEJWhpOU4uBLcEP5D49e4mTa+yJ/v LlV46OBE42I8LjZNE9w4dTIPdpOnTeqbGoHDLLdiCepLDZV6kRQShbIoY7N4JHk4ntPMqcwaJ41P q3T4IrLszS4c++q12OLe5HdnohpPabnhn3+k+MzMwGlTlY91xnK5+72IVVe6hm+6/hgoVcOSWpEM gZNcW3vKzm3gcKD2TbwmktU7tSZ91NxG6XC+gK3oqDCO43jSUD35dqB5f/fXxLB84bn3xP6rzLG+ lpDcqoufgXcjzx0O605WTXPVq3b5hs3D54h9fY3ponnTgXm88EwUTtj3TUg90SEGUdA+kFTr4rhM NMiT5wzc7uiU+olXiNlc+hbLdVsXNZHUKRV+oNSm9bGbY4AUjpUhHnVpagpCUVOJQ4XjA3xxARZB Dow2LEmoV5T1+9TH96jhU1OpExF6zgj3uNRCfbidXZ105ei22LfRLu2Deau45FDANnI1GZApVTs3 EUUs8ANWCXPHERboUlcakTjJpaurpg5XpnGJI4aPIrbaIt+F6244WPfm9eff/wxmKbovYuZeiw5L h28ztqJx+d0xrkZewlZZTOwf3nErO1lEUqY/qExUOUFKzqpRi2hc0w7bTj6eDllSwdjICS4q5boP T9/aW0Yj9e8os2qR08QcVkSq1/opZWRUc7sIPsCI8lZYtHn0ZnGgkz7C/T4VHQusvqFx0San+FKE ZDOzAeUuMfxpRPJsPmbWmjfIVKpkkbMbYZ5e8eBZT+w85VHwZM3NHpOLFue46xyWMpWk79OmWhVV FnBy5cXCrB8WaQM1hhwn8PUceXs/yjY/TDat+eJ96jW3RvyxIftm/JojBbBjoTBDr1FP7gbfdhV6 zIWbPIp4Vubr3+1FvK7elH1g9/W//KsVEnHhzPzgUM771LvHcLZ7d4O14q/W54nqt9xIJOEJwbf7 EUb0eau7OcLqviLOHUsHeNnUztLCYXx6wc4JX4+ndrQrq8O3bW7Cddalk3DOQLyQd/uo1o8soFCm FSl9yZmlsbOlvbYptMJ2Ysrkc6pyor9AShjRQxfe0unI2RT6tuHEAYQRZ1M2ghEHTZBQvUY1YMTZ EvYi1Cdvazdlh+5FdCOvwnXkdE/gbJFXqb+jQPXg7IjyuPco+rw9p/YJ8SMu8dJEV80T4oz4eyGB aAFmSo74e1Teq5sTGsaPuRH3e8fxy+rdLpT1bQ/E/Uat5uW5VdrUfUQtZRU/f23x6QHExkyixGst CGUb+XUbf/5ymTDO/bD08DNiobFoHlt03zXExjX/uniKBaBu0IQUaCAO46NjEFuok6WLPR+EEkiY WYx6TmaxlEpvPxGlwRtWb5IkxNPris9/y5K3aoBArvhMvie+ey9U2FEZ094uSYBD3qBvwWtGpfAF b2pTWW41WeLdlYF0gH+QGeEKGiOulgSV/6AGeT858T5V4M9n94FJC3quP0RMzJ43VKYwseGc2JBJ hIiPQcZLaIvF/js2frTh2z8yN+4N4DVJSO2uu9fham3tzZPH3tPm3S+H4/GOYpsm/M+H5GPz24vM LmUHQmsUL/VYv5g2Z7JSOYS4XO8pvmbcm997yD1+9tcinnX8KntyT+9xV70li16BbM/b9bNLuq5t 0R7ps0vYJEKH1qx2IdxJq6Nd8T7Bxc5paWK2D6TmaY6tdiTEuHsFdiyPGAXMduZyzTlaLvZUqy71 rAaPO66ONLIOaIfLJkEaqZFXD8Iuuphzv3hS5aZytYZI6OjLGvQQzR8ZPKmSthUdn2eOV26CBn7y r6KJhwRkee57GFRH/KH3PD3vA+z0bO2XT7XKrtu5wMCpFWKJ2ytHz05EfS5XOLh3+YvQqkN1JayJ +MYW99OoCGcOWb/X6vy0v4ssdk+X4ioyVyWiZBmSO7Uo0zsY6Y9fWOxsRboFy//IMWsvTnDB3s3e iZe+jltYQWyaXHeiw7UOdhtlvldc9W/cv1qs6QvrMI5eCf3S4Vjdnqjybvbnzw8iZ4Cmrq3btj1I daWBJt/HVJ/rYf5YnrwPHXJzijZlgWJd+JyObIINW+et1xS/aq1iR54CtZx2khb6hHJZwvWsXh6D V3QqyiVbd6veS47Rf6ZLCwbSemRyPrR9Xg0F4hZMWDq1DCKrteFiawK3Q5N/pmW/Q4zpTVfmoiPf 8czg10qyjYU1PA5WZa9ojcezxST5343eASenXs4IfBNJI5Q9Blyk4cL3yVqkpRL7s5uhJ3DPhUTc BO/CELMBCvR5Ct4q0RrNQVSXmlPCxch9fjjrXeM2WLZC+e5KOP1oQ/ib08z51AVnfHWCwR0P5i5j DQcxyW5T407L2vKmKKZ6ioa/aSJsFDVV7HpiwTuF4N2FpHTAwnY8fYOp2QWe3ZodvRZf5Vd/uPfD DFTGyzznbs3G7r+l3ISkbO7js7MaZ3eXmJWmMt4jS8v3WZNGx6/qD67ceB4Y4rCJ+3Sepmjz04nf U/nDckVahW31Q/tX6oQQKH/6p0pEW/oOP17kpsWv/4SuSGa0BREJUzL2ShsoOe3AGrglZU92Rivz OPfKolNjA7zT5wdbCI4+iNbGZRfEnHIwGHbUkSMkNjDtCaf23CJFbozi/EPKRvSm3QmdlJGpHRCY 7RRvaDvpqKlM0C8rHvk8dspjPrB8JOkB8FYpKjffbr2v8LFD+kX4l7w4ounbdf/CAhHT7pnJmR4s 06r7dzQTnzyM6mrPIPKBF25KeElZ/373Y9oMFxvCBH4zJClKdeEb6tyaAJiW9gm1jlU3Bif8GJq7 Ienw/h8t5PIzhWNuD6scf9HYgN4+BtcaB57pUaFlFWfNPe0+pudeMIFXJxNrm5Fx0tS7JFfMZH3y 7exuCDy1vl3ZB/aDq3+2znFbmiPHEjE24J2J4lI1qm6z7kIvl2FakzJ8yEjxvI783pioKZf2EcMp ZrjxOD6N+bUv3k6NPKpwh9f1idFhKqXOwRePGL9nEtjtoH5dRJ0VW6sHH8yn3f3amv1JeorybDUj adjAG0USCZcGdp0htfxLIw4Jq0Rmn1pZ/JGg5DS59d6Y4M3lFvl6WjDH+HApkdYuRIZ2xmoTogu6 kfZSxnjLiTlBm3FI7lE78WnbGwbp76TH3Ltm/CpJWmcqbFNKeWz6qenzA/EyC/mekYVgifCawv3S 9L50xCTr052eJl8D7lwumfOVCI96t2br79Bz38aQqrYYW1GyIHUGoZjJ/ttmxA85DxGTn/NWfP5M npRzlP5CZT6DIw9+DnLgED0/cekENkffzZjuJ+PiVmubvVtflAuj47XybE0c8pSSdqbPb25madZN i3O3zisbhBxXCObz+Hr7gpJyNNviDytJLqOV5fe19SmNfAYPxrncCt5PzNXaC9Eq525Tl9oe4UQc ey0L7kS4X6MGNiL5H593PMl5xqKZhaK0NT31jXipfDtnldOi9rRJAXQvewlqzTTbrUu1sUqcpS+J inSqKP+Rm6e4Nv3lVMGeJNSxY/YCdbaVSf3oTCLLHMLC+D5ilu3c9IFG38iL9+bLiuuOu11g/Ov/ iBGysPOhqRhWM+L3+M+t2z/Tn+nP9Gf6M/2Z/kx/pj/Tn+nP9Gf6H5r+H5F6CugAoAAA --------------Boundary-00=_HY34P25E94MCPC6549FY Content-Type: application/x-tgz; name="2.4.19-pre5-vm33-rml.tar.gz" Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="2.4.19-pre5-vm33-rml.tar.gz" H4sIAEv9rTwCA+29B1wUS7Y/bg5EFQmCCIqApCEHiSICAgISR2AaRBgQhswMUeAqAioCVxBHcgZh pBGQ1KQLCEjOjIQhSBoYMpLTf/Deu+nte2/3t7vvt+//83y0u7qqzrfOqXOqq/r0VCMCE4MJXxdw ckGKC7jZi4oKuNjbCR7655KQkJiQpLg4+SwkJCkh9v0sLPbr+Tc6JCQpJi4qKin+vVxYVFxI+BC7 +KH/AcK4os1d2NkPOWCQaC+k3X9RD+nieuj/dyTy1+wv6iEiLiFgaeOKckGaW8KcHKz/MfsLCwlJ /Gbv/2h/YRFJEeE/sb8oub6EuATZ/kI/7P8vp+d3tVSpKZgpyElqtdu3dA8dOoo4dOjIu2NHyTmv KsfukE9Md+/oK5PPN27ccHBw+Pz58+TkoX3y9f6h/f39C7uMxw4doker3VLU94idi215kyIVceO6 dVZzoffKqlurrKKPqOCIsvwNe5eFvpFsW4ZQPNu3mrCfD41+khgtK8q/ffTKldRgy1ijHoPjfylc zhQeR/mTQKIGPVH3OKT/GGbwT0rWRsNWXvMmnkFnHgGybmB529Mo/qEkPilTOdkHzRrtlRcGKukF 099l0SthJEpLFMSYYYITHhKlpRThE8M17RgnaWDok98+XmS/yOWS25hCft49KvFRNvH+fY/uu6f+ mTr+s5I7Wb79jgoKuLa24agVovT5yizt7Tn3VRluSuDkGL4tYa92QXtqbiUjzuboQamvN5Dg9qRg 2K9IP+V5IKjUMZ334gmYMIY8CwR9ha8/FSZm+Ya2ppDuFnPXaO+/q3rg4UEuThg9nYKpTalzHrXI 45UfvTausFEnVPov17C2ct90sq3R80tIJQVa+P+4vSV56Jv+1vF/0Is8vIFVmiSNB7OvrFnR9E5F IEGVFjieiPJrX332lFYJB2oeT8YdQs/RQhR0l46i6blkTxB573hQtRu8XWRKxAmNCt+Am1db/ARW P60/BAScDjv831fUNi+Ak8s2zrcjFfGXSqb6E1EMZIZHFMS8RFTYoKt9uzglGUX+ONqovUB1vkSC GH2cDJ1wBOIn9nOsI1jQLU8OYA4DDOjsB+0FrAf1KKD5QwfXT0AqlAEjsbH3BRj0E3juoEAkEXfs ewGR9zCAS+Q7CqnfwPMSG/+keBVqXjwCEG/CGdCRP4EG0kCT0mMweWVYA/+rsTYJG1OtK36BjH4u U/iv4Ar3p8+BZq35jxrGq78b0fB65+zNA8wPupgQGCVkqAg/8R2pFxNVIrupMRNQTv8HUTTHLFsT +Q4DnIOZTS9D/XxKom4JR9VsT6sbZ38WogOiAtenX1RGLjWpZtcEjMGBagfrneBjotK67tTJ7OmC Vi67HzHR7sTU6TY1gJuaoBJYmM6W5DCGYwMkZwIvhMDltKQbrlxWldO6q5zzUkBoGl2cCia3CEkX UNrlhMiUf8qxKVa738A671ByGy5/G7CXlaXj6RQf+sx+naJTOQseEeaWf7oOWk4LRde+eoHWXOio nxGZwQjgv7EDqyvoHuJNPP7gyAjFp+DCnsLQSShFrCIjdAU4ATwBpzknWaYbi1SwvoDILbJhuaq8 p8PlMBfQhBQc2+wVoE9xbfdRGbiUxgelDs8mayQfGePvit7h43AeAtBqptiXKq4Alp/USNvy8/o0 dBUeMY1Js3BchppjYX0A1gjPaYYXFxUrJYWfnAkvRUddB5bPA8vHACsdrF1PZK+lrSI8hy/HMgWW r4btU4JXjsjpYz3zYPkpsD49rFE7PfcXHbyYbhTMH1zI0shL2RQCJuXQUYwzjRf3DCEqSIJ4Dl0e BFuRgGzRSZTAgZLtaffgg/7SWplq8IpbB5mOKbgFfqg9AHZwkdPNGYNGSj8FSzFR7l2cw7ewib+y VQSAzhkdAeDJaZH6TmTnbaJ0PEwRX9SDNE1tSiQ9hGx3IZEjr2fCrz4mtnMuZJDz5Mm9t5Cp8R7W MC2ykN5UFgPLD4NFhSo/hon2cDZionwwUaWYhl2oeQzTEIFJU9J7p0GBaShqR26F3EH3zTON0bpX dtDuqzsWL5SafXMvD88FG5IF96Akc/dPDl5AipMFoFMu0ss5Zi7qY7okk6ImSRRRxE7nvUSr3b6f WhrQ7CE6SOtg3T6xEtVxT9/HlMVO6uIJI8RCIyZEM6rCT/GXe9hpTIkad8rj12pmJ4Ca4b4zomvn SlmmX5y0fI0UeUB4qJ6j0fxp7zbWDs8pCjW31xbrj+FiZ0RKhgpyfZ7HwUo04DMTpsBkE2Spg6WC mu/hU7sV8U6tt/xju8QpruimN93BaJpMYRpkpkVS+DUgkVcM6NNQ/HsNmncaocko6RN0wN6HjndN X8xL4XAvSxzMMw12PRTWl46TKYsAx3vlQNDj03e7kHzQF8jHQ2SL/man75b8NUnbYbCQjvM9CWxq 8fVylk43KkPaWLvug0yVg0qgIClc7Wp+DGwMQ81TRBQJ60RKzIQ/h3GIECmy0/CcJY0L7cgXaDUt 7DQLk581BrI0xDYQs8rNRZl/zoVFEEUiLn2CZnLB5EpG6W9daBa6Y8cElS4QzC1oNRAqeJuoLnqC 127XXebUdZFcppCsbyk2lOejvDRpYjo400Np8WPV4S4v79DWm4bzpjiLqC2cKDmXNdtKP934Un0W Ofkh1Z8/6vFFeHxh6yTrJ24GURdOBTFPoOu2g6qIOJIudZdVtTG0q3lUDo1UXTkNWdXd931YOGOs 9iECtFuIz0HtLb4HdRQMZkQ2jxG9noBiC5I9kW/erq2chaxURJmZ0axm+C1ztJwy9mE35/c+W3WD LNWwlt7rpwC/vVeVuyp7rxTGQmT404IIXP2vNsI/rt4Z8hMJSlOQDbm6eUw0yPX01UweRjUG9bi1 nYS9cAW14spth88ez/pbzJrBciu4z+u+AHC910DB+PeRQu5x7unoW400HUcxmnw3sCqAK0OHAagx dBvOxQkNwb/X86IECMPKt/ClMy+yZN/AFLEiwLS1N9nGQtAxMgp+gBheRh5f2zPhcxCEI0N6/JwP deqGgTgWSzQ9MbyGqL4dPhPNdBOvh24onWkMvaeF/SZXrIRHf9AnRkPeWaDY53IoPXt1OryhBD+d hUersY2nQQdOFg4SB2swDZegcS3g+pJgeyRLtD5e6ExX9Ql1NLWmJrHnas/4JBPhvD/sQsF8oD16 9+f75zJLr8KRXjUCpBcv3l7FUkNblIXEaKrOh1RF4QVS3lIa84Y/O0ey8EaFibk22C1/LYvg78Cs nH6BbsE654B2qZzXeTQgiVv9RnhYIim0TAMqNM0LCZruL/iEn45W+0AeFe3iV2/gbw5FHdM46B6l I2iB8bi/q+CJ4Ey0agmYdkyUfBVxTPRVe8HP90+Q7+XhhwATRbzLcyLzuUQUH9EYdvYAxf440MTp wGqJzuwsYJ5HPexZPaw6ihArHWF/LRDodEZ973SjA2rZZLEz91pPpM86blvTS4pzEy7rfHl3kvJt M642en7DBx4nWHApjq+Kn8psjfHaXsIbnt7IwktZt/DO6BaaFldMjxoKPcHRcBjTsk/jwSUIuXWJ 76vRA0mP0ALKN/E31dFJfNhDQMlt8jTtwgRs3n4CQyM50hrId9me20Tj289h6IlziXyMpwGiOk0K H5sa2Q3sUsWuQ+0FzKcBSp7KdJIEVkAzEYHHgH42Qxqwz9szEOstvMBrs2SSdKO3Wt3EXehNnH3H xJW5JBKDRERNxJ29UkqXfDPMI/kOTNwCTsZez1T7FbhWu9oP9xToxkTipnFlDUSrBrc7j5ZegfMv 9LTw4lcbUiXgmTk65mA5WwbqPc5ZrjiKlH0LK7jEcPxNeglAIrXEo/o/4pNQRf0LX64W1eEHfR1V u0IXssu3xv0HBx04WuYm64qWYupOlBYk5cydZttwQ+0sDr1vMIQPTKLtJUNYqQYa6nwrN4XLtpzm eODVPZcWOazyzQBv9/4KN/9uhM91/N2X25MOL9a6WwKKTLwnstckI1nm6yaLFB0rNnDDg7GeMU00 SjHlubsQNFPKUgv4rdQDGZ/mxIrSVzvF1qw+4kvyogdqMMAKFH0PLppCYkAXqDmA+y2Y9h7yXJP7 EiP+CsaS1oUR6OkZTCN5HQLmajVdV1lQmZ6H5IkTZ5OwelZuA/CiKL7BQ5bMg+EceLtwzcHoqzPH gQYYZKiThmsQv4G3UMTvXlSDi2bg+hL5EizpiOp6k+4dBVSQbntkevNCMioKT3pxAy9CbGR8DEpN rKHI9rx4spc+yxNBPI/2oUdrciTjjgJmx4GuZ8SZL0Z4XzXp+d5VwZh1szD8amUYZTmtNDpuyNmN cBTS7yD1u1TBi83g/rB6Pgz9l5twqj9ZkXMBMtxKeKv/uD4WOvlbLdEBtFH8lhalMBIaYT9g6vyU dgufE67idP4ffY77N0li7GY84M/BfQ/M4YBZ0wzhDhjkhlyQRkmWzxhGSznqAWoV4zeueHifegCr vUiHLtg4eLgKvp6ON2iI2+ym8X/z1uIEEGlCtX8y9GZvjHf3fWFZp+Zn/Y62l8RDmV1Po1lhk+ce zfdHquKfg0CHLvfBsz1D/tD4qe6GnJnQ52+Deo1wTE8b9271XyvOn20LvmSU0SFcPtgmZTBotKpE 0k/G6aY0JeI6U0hVmGSUWbMFqXv5nQ7Ks9vDKY6iLjGNQUe45GP36eBiI8k+bbNqxbfSwqI5o2e+ iHfqd8oHFlc+tvJT4RgNnsbI7jx4aDxombUbv30Tv0TEPD8GuOU9Py3jxK+SjxvInpNVwl/OJLRx eAHmgo/87G1+rpIz+Gi7k6JiQBvGfAcM3TJ3nx+7gsXef3Q5/2mRWomCsjlb0HHf+fE77CYx+6SG B/tqr9V8L31k9gTdR5NKNV6p+MqjoDtfhgCbXQOAayeK0hIeM98vvX60o+ezazklLQF4wbj7rsfP SZQgMFDBUNnohrIXhwaulknsBpzePWK/Ax9Q8zOBCtOKUitVoHvyiM+IoBs6hwmUXWlvvYnGIXYx zSoSSi/wRJeI/qfetQZjClVq+5cdxq/eo+ZwdJF8sD+qDTGJ0Oi9azLTqx/lrWR2T1M5/vJEz7De 19jUzV4OfP4rb6Dvs3ZS9vs3oJRMqR18sL5oXljUYchxLiAqvObMs0rpWRrqYEYllurd1k8Vi6tP SYQMjRw+gcQ3SxeFps9vqI9Ll2GmOBQCnLipF9T3Wkny9HeaQtETw0dm9ecQmHVLVrNK08gm06Dl rNG6aaWoviNXgKh1MPLz6k08NG/NoXB8zCHNV/hjTqnnxFp47QfvlBgzKg4AU5buYERVk3ee2pZ+ Wh37ftFZHyqAeeYjQuyy+j6vadx8wSh3wYt7dCr06z720Bgt+hVs//PIcGCQ9qOzBU+5GRQY5N32 340qnD6v3yMX302ob/Dd2ZGsfJZGe+xB4JU5A9Ew5nXlwlqN20tZPU5RY/SrxTFbq2ypFeqjlgeR oI3Q2Kxg6PMEZzGFFqUAjFBY8gneKiEvvoYqGUXER9VhnRe/WY7Zoorm+pomwmMFX8S+cj5d7sBR ZGYzPjXGe4+pY2Ql/GNJs0TFRyUJ+TjUdb3bYLjGhqt0wEhJ6qi299rrp9dePlKfubjaH61O7gNv SgmgUtCtyKa6KkJBHvLfZe0J83OlWF/P9J5r29guLd2F+TLdHMsz3ZoNofSYmTlddUUHe6aQb7lT /CHzcIIMR5Fz5+ckJW7GHXEI1mqYg9t1ZWaNJc4wUkgyRZqcnU3Sm8DGbTishWgThDbqkOXf+rQJ 499W9fdUmEjSGPPtK4IpOo4iESViy5x0fev95fZpK1vXEXWkyDigkM/N3k1y5mOWxhe3opE0v9L8 nJhiT7zUp7UQSms4cpjt0ZdF047hu1jbsgG80Lz2Pm/LWuTniJgtesQDgBAHPw5EiO/orrbwKqTs qA9rX8L/IhhI2GWjCqirhWBKX+6GKTjPaBCtVy3VzQLhJetg8mdT/FWXVFJasPk+wgmKhX71i+do ZY16HiOqGPONOnm4TXWiabp//2bh80eLlg3Sm6RdY/eoSb6XF73Oq66VZuyNU57SpodtNlQSL4lo 7RG8Upu0YrhkObZpYlWaNjOLGCVptC/tZZe/592/cZ/vekDYEZ/xURO6XnDp6GMz4iPG2QP/cFdZ YzTc/Nz2Nc9pHqnc4qLD5AmHrWREB/wall2Ulk8/6RtLkBjYmDXRZ2ObCqI/RrlziiIry895rd41 xCcibJTZA5b9ZkV1tcbHx0PVer2fdSmjdc7P4Vx82/w5mdLZ4MLdMEuXao7Ns1waqK+P1qRnJ+3E jU3mPTKa2rJWaLk/LDPGmt39tj5R07C1dHba1j1bxe9DVuuStE0bBvKNzTg8+qrYyDLgi3JOF4Ym H0cBefHMl3q3fsix297hOC37LHEiqMvFLTg+EslY5to+obUWPBrkJ3sdzh8o+AvJNuBb2Pm13LGL phtGcMwC4GZ6Hdg7nSJD2WZtE//hK2togGe19YM/xEZ/Ylzen9OMibq53/3+4FpNWesWePP+k39e /N9DWPgfDv3/LfF/IVHRP77/ERc5iP+Li0oK/Yj//y+K/5/x/j3+X+42JnVOxbP1ywNpVk3IOuGX fBa7rF9o25+7qrg0ajHnVH5i2+fpQGqMTJUUlSLVjzO8KD52rME1PesvJUuUFUyj/CnsJxhPO+dx KPUG9jwx/Aigm6hBgVZ7/H89E/PQdoqrrQPzcKbPFc0a3V+wl2uPc/oJtNAL2jRw//Q8EPSPQBss yVEBJ7lJWdUPNhL8ahQ38Fn8DEqcXw1TtmsMlc78O+jxh8yvaV5rCvHDWUVFCWnBj03K9B336ttm uPOOeXj6hp5UGH5SVGSt0DWSWLbzEhraOUby3Zt99/ahKidp+UU4aG3H+gZbVsOENmhDajyxr25d FHAQv0dFq925uvPGjSmOr5C5PiCsQbesSufLCsOn2b9LWEmbSjGT3cz8Dgzd36Od81XAb/8nlp2t Tjs/e5W9waTgPkwERwsMTTj2f8VhpEDqr4cxcnmpbfSPaI3RRimcN7DXjY+go/5fSbCS7XFqZ2sp cmf1+cPTvkD2NB67VkDoSpBBC5fypvUFgBRAwrM3h4DJh6fbkaH/WaIiAFz95A1FdEc2Ghu6K+PF uhNmwG/ibfu5MZeJWSQ3Tr25hFIvHb3yHlU56cUL8LKPPHNXFIGw6Dsibsc/7jlSfdzFpaTvUi71 3L0vUxZtdmd6ACodWhwxyx74UuidRKrdTGlH2vUEnpxiA1iZ0+qzvE038xAUmPo9/akc2cBqC9au dISvrN7yW771ETbDenTd/gNOWEZzpCYNICf3/k12ljMfVqnHFrRNifEMK2EpygHjsgfzIheqX/PF stDiCgx7WpIuBsynkwz5imTwoOE5yK33P4RGfwvH6eyq9kzIR+HczN410XdNPOhI2VJVLtFxj6gJ MXQQxVs9yUbstc/hUNZ8khQhGM1AtO6yyioHsDLg7VLsCW92SWp6hwrHlQ+lbN8DHEoNeACa78hu RKiD468EZH+NM7agr/9Vaf6bZMVtfMH+8DKM3EZ9N/1zAu0kIi7H0RYm8VZGTfDOTViaVlp6RxvN 1rFMIz/FaV2EFmnLVQ8ABT3FqBzQX2SclcLy71ZQ1snBVP2KYEWe3hmv7pF1T+ILvef7kFuQZsVq 1PL1/STUZyGqJlPA4dOLiNSmkHjt2GKvd/dBPuu4HnEDNse3njixT8Ik9bDNOvsMTJrIslEKS1Hb aghmldVXHW8MaADBUPqY+LzzKUJnwUXBv1m3SxlNPgisCU3TC5gkyxsMsJmXQ2rkNMMX6OJfgJ4A CQqkbIob7hW/pI5OQvWehNoNTLHbNNBgXtjdbiviYYjLcSkMP5EuN99bwCRYBMenrivi3787zVeE 71EZ050SbG2zx2arnGYIimjtV8Z5TTzlY5QQs4eTioVFSAHDM8L5GowXj//nd5e9W9hzzf9WE+Vs xyqF6mjzrO6T2rsvGAD1fwAOqvOePjL5SBe/4N2zOvq437166GPlbuTunk9f19565HvUq0j8kKP4 Z2Cus4BrQi7SKztmXSBuIdh1imdom9gqcyXBM7te+flCBFyFBzY6CoFJnsO2HZvIlbLhsfMpDr45 CPVhKmBYG3889KY/jPPvl1DGLokk9fcruEb06us6FXrk325t83dlhmrK+dh2rwblukPbI5722/Ry jxaWZEJB6Ts5UMRkf8UEW89eTU3c0qtPYVJjrlgZjumZZ01fO06wAXReQOT2o3ml2CXaDoOA2sVK p/OGw1XVhv61dy3dlNWG6E1CtmOXCiCri/aLHZjInuMrEqUuXQRsQoaz4nCpzIrnwSrR7A5KJtt0 Z8Zu2Ka112I9aagTMIiBcHH5GHykDQQRpnrS83j3qZ1R797zNXWm7DPXdQLw9GyZgZ6eyaVBGd7C gSSK4evRvCh7ud70eSifn9ADimPwxvWu7lEqQKQB1n4nq1/KVwWoK00xUaqMAnu9FMO6kfOtkNvs pciTpKyWpoAlNz9iv7cf0JutYk+wZRreDjEJ2UoiXJDUZetLZuLGOuNK/ZqkZRaSWDxR7r1hPObc tlK0858Qt8u9Tp00n08lSAUqjQzL9Df2mJe/dDSE7SK9WMOKmQrt+6/3ejJOJySTnL5BsRrQjqWr vdeR+gdipctd0r7WAeDRc5XANCbNek3Qc6TiKRCwz8S6b7Hu9cVWqERklTA/uI0cMrvJQlnSeUVW yptRJsf53kjRE5bnj+xHy8u8GdfdV77GpMZEFYEwe2ilSmRlrCSzqdZwUl1hrfaL+pjELk5SfRGn 6VC8dXyopdkEjvfzZqF9b1bgG75Rld1SZOc++5UQge+3RRdNMA/sfTq+e4RQV0koqB1YVkofuw6b ejGt25YUWBjH8DNt/07Le9clL/nYPsm+Zlki77dQOi5MBfym+BJdLEnhU0hsqowk9ZeZBYotWj/Y lFOKmDem1nXGBuL1VYzViDsvxKyPX/+45kOaa161mnwOiqDM4UYEP7WhumGvjOFzAn4RcvxiS58i w7vOFHuQn5v7L0M5WT9f2QmtY6OqLKDgGSvawh3vrlko6q8YymlE1GsXjya2u8EIapsUK3FYBfo7 TfMKr+rp8MNH+qX99kiYVWqFRJxmpS5LWf0NuY/3BO8noybKSSqTW41pQMvOmX4nvtXgJIXWFV7Z GP7AvSsI0NNVOJaYxY2aGQpG29wd2Ew0pAOaOPl8LmI8s01mhx2sHHAtzUvLY4pJcebo8Ap39JLf aaG9G0XJfK25o3TDTzcooZ/Zy7yDBncNLRZeDDtqz+w457FVlkU85D4+fhQ/STdmxGJCbWLlR4Cx vjamznEtS55318Pus68axe5xHoyDwWC9ns8H5n43gk5TjmATbPnW3FKXoSFe8QHVwLhrJ+bA1YBF uPin20ZbMQxGeQIqrYOrpc07HjePw1XENu0Y7KNb6gg/x2lJGjuczzNUi9irjW0xhvTmy1Guxqlf ojY/Glo3PjJGdI8tSpInPvdiRxj221eeCnnIf4y1Z1wHiu3c9WmsF3Y57W5esau70u0xbFA3JHh5 lAdPx/eeKzn6tRtivJ20XNEfUyLjI+raDKjA6exWIcgvoyNYFPCpwi4+6Eql0zZAXOzl6sxk+4kW gZzdfV3P1atXy2L+nvS6K/RF2fioY6/V8FBzi9Uk1zAF58OtPZxU6U4auiCIkdFAfDpXsr2SsDnW 9HHTdiwuH8dSe1fN3dD9DGm6iVVhDsWUMLBeOju3ElXzEdGwcyY6E3w0ZaCGTx6pMKK31kdMbzfQ MSO2JLeZmCWHsnEXOtO9Hox0Y9vbZrp2BkeNDYdK3ZChkKFoUL3uAuAs/jDQR9G1kewBJvyB2Odg Q6ezMX+geZLawJNXbTGIzkSJFUXW8uH6cbIXyFGbhEzs2VtPopVRUdoZ6D2Qb/NBJ3gF7fvipGfE 2cKz+bUDCqvBaqa1XYbSDm+8vLvqynUS/MwMnJXO1E+iL0gIG4hvOauh8HZKZxLqfLGo3inR7ctG gDXbLVdOw/fvNJmrms3U81khxPPDB65w47rplKBsXM2Y7ZirnU55RfyC4RnEKA/Pu6y9kYtmZqiL MWU0U79YTH+MNcNlLK6LS0sHjS2qU8WVKpifi28bPa9QuqOI37MRvj4aL5vW0BkllZBCs++0xlye vejVS2/ds8lz6v3X01NHlPddPanz4k25ISjD1OJRblZrF6azPg/MWJG9PBghFFx2ppKIBKbESrNS cdhzvoE+gQrLc/iiq07c4W8yEicuMsgJNgl6TKXyHduuXRR30G6lDzY/nAxq3a5MWxwIdZV+lg82 LgC+pscB56BXKYseYAudYVmNMzJ+MYrpj1EC9v2T2uw/T/NUV7X/A2Gw/2fpv4j/Obk4WvxTAoD/ bfxPWOKP8T8JyYP4n6SoxI/43/+m+J/z7/G/kjcp8syq162z2OdCpeNEte/uRzE63aVtV5u4JWXA 3UuifXg094tHgBm+XL+P/+tYBCw8wJuH4i/F+hIflk33E+rfdA3cLx5Z0CcBuWmK96vgwcz306Yh PIMU0JrmxBa856sMM+Sm1W6w0SaEnot9h3PyH/XbPyozOpyfx0QVuagX4maedfnUv9VSfkmnzN1x wawWj1/Ijnis8ei8GWFg4atk3rEND791vsrK2KKcdTCjSmtzYw7jg2F977NP0G3vWFPv7uGhgIZy C0zkv1Kl4A3KHGPO8Y9ZBZr5ZlXdL/Z+Aq7nCNU8BIR7vgjKcmksHfc2b1E9U/4v1axWQcGce+de UvDQ34/kxdWTcjSZFHVQMEcvWkQHeB//3/BMdqicFn36bwqTlxnjFRRGaXzTChSmaHNG6imAb2Dp faHXfz0gPAHNB98rSTMTrHascJ9njsSNfAjn2o3+oCBo3rlVbDO5rq2hmbymFp9hfG9B4uYqA8ag r7fkGHxRJ80KzPvc825z22fqzYOPpvyXskUEXJs691Y0XmUnhLzKEANHxFbNOQJ2DXjN33zlV41L rzDEY65cyh/kmLjcdJRXOIXUf8IjFKwXjLH5TyIyeBWoeQ6ujJeAdhz3Xxz8ztAZCqT8r+I4qCko 0K/1T8NcTsCJ34sV/5j863G4UowRmpBJyp3R/Wg9bcxqzgZtoeH322Zm8C0B7+u2tz3G9lXZdzeN m3sFd41LHfoFLKr37mXcq2MT7dus8RrgnylTd29O00Ge1saJZP+yeFv84buV9ak7sT+7wS+4BsBM jBh5KrbTKAaW8M1lw/kfPcF7UGAIytm72G1VpFggq4RT4taw0JgVk+EeGPjBkw6RQUK0dhVsY7Jf iWc4XluuQBril0UcXmxjQrLc8kFfFsD625wRXgwvgJ6oufq3RfHmTOGr7MDaZBaOCOl1paAJ5YOZ KOPLB1UGZvKI4V3iLRMuINGrHAxlcV0Nzu5tswb63qjykPYdHCsxRpHOkEPW2nhoYfrMfjjxI0RJ HWFQ5ZoG26+AaHwk1hCm2njxSHe1KM8KWMzQ3ENaqJco8idSDN/AKuMlu5Ed5Es5ZXyOU6Pgeqnt Zhdsj5Be0BTMN7A8pdbU9i1G0C9v1YH0Igsmqcg40XZn1d6rKEJuXk6jf6V+L9F9N7L8d+teA1BP /7qickb4WijxPxRJtGOWzHz3DKDZS+jVHKxjNjCdRzQueoQCfDjK7pClyyf7QHYHEuwVJ/iBwms5 TaEkoXZky7WVV7x+k1EnJClVBflMM5pmlfAfstxnmHFN6zTrL49bTbzcpzVcDlfDL/Z8uSh6j6QR /b6sobFPp0S2Qjv5tnX9mGejxsAuIcbAMb1xzAYjhf8UbhrDKlH14RycJI2VkY0pRVfhFP+xm8S9 FBLdWvXjobRj/kl/F9CDArCr7vnNk1DqBguG1VHKerhHQ/wmdgrZY1LRHnW+XfwIECPcg7nuic7+ +ibeyad5GyPH3+aRFHUVm+McCVp4P7foar4lf6n0bn1deXxg0FZnBrrKoqgjXuQOTtDno+jJwQZ5 F7/F8/7xus+rOlKaeBmdZjpn3CTtP1h8tvzZ2PvRW5/hVIf1Dvi38TXJ0a3c01qeWRy0mmWGxbZ0 rU10a7kx7SqavHNd6nApsLsnljmHxNSqDUWv/ZLrQx0LJYxlDgxUiBWa2OyMOuTwjVAGhDjxg6lM o1PEN+CnXFpXZgZ163VhLX8hTf6O8YDQDD23JKt7X8WwmlKPLj69PtkQj9B4ysbCG3ucyeBLKBhO FHyle3pzKIm0ASfaLruEdWL6teCiX7tVA/BP/h6b+CZqnPaHcdqief6O11lhMI/rRcQnLeRcdxLv yZwuYv52nUY/3K1S87p7L2LcuUR6tmEsvi1du7J57U5Yve5EIvq6MUNEyHNqPTYurHhN6hXMi7Jq w6Xc9DOzx//XxRn/LHMuhnd48DFMVyriiTBKvfyc7j2tJBcCzjbNSJQH01RX6fBlJItR4pwiPJiN AZO1GAdG34YovF0/LHQ7lXYYFFct+n1gtAooyTzhP1qR06+3iX2RWReaAz3Toq/oMmDsm6M7yTNo OpP5c7WW7vcHGBPuEd0vUsGNL1LvGjAGy8Y02sUH8LxUobAilTb6hJT4MKhwBMzlf7tuJ3fePuEJ EFE9acRQ2l7gf54I4DLX2s+g0Pa7pwdygzLraHTviQ/0bcXbnrQv3Ywr9z/vtsh/+BU4/LZjDU3v Vv3ludG9IOC+/br9T9mDb6dmC/j2guYLFHbuP7zzdncz6t0++cn8NvSeGoJarTS//OQjTASc81+Y 2aeg3DcES8LBDwVBjqfu00jiiJcCds3ccrYyT8Tx6crNtfqYjq/yMCV8djk8UDlU1yi9dnSnsyrg hrntxUoOISvE/IPxtH5qDvddy3Obq4jOiaA+mRMDBcNNAhJZpyt7blJw+Wr3U8u4mimbvizTLzUf n9sT6lIojvJoKiT1Dss5vxfIK83Ouev1tUnt6MclBXvCjr1N8INyG7/QkNxHxU4+eK268dOfIt/r tLzEBr8qvcLI4bj2YZyXfoEeG+L3JH/6sgPRUogpnbtCp8wjPkR4lr3ZGNiL5aWFbzg+sMgyOuKv kt0ZOblH8Xnic8+D8Tt4CQvzGKPIipB5Lzicfn2DISPKc+kK9fO65pDbSaffK8iEXkxXgGB8jMm8 1a5pbdyI4ac5bdZ07x6omWXaMBZzuyA1jfseSjPOp77jG/Jcyrwf65aO2uNIJGV19HiMF9/EssXu +Kv7jaXetRJ+bI6clC+F3QJb9QWUh2bzm4pNeKgDCV6zcAc+FqrdxDdoAarAKJCXRQ9v2BmoIj6m IiACdF3mkw3t/5Y9KFUT/Eozl6lkO9ccmRKV5H7u5Jl9syNUbEQRwLfxZ/mLDOnMDneooUezYj33 ZL5mTKvRs3HrbW9KKjzT5D7W+5Que1/FwTzL2WTcgf+jORLXsSi7rTHjKbm6Rqu7/mAV9/13T/yN yW+Cy+SPYxU902+xmsVIK7jmOvVZBrQdT0BYJznFHWfTCYybQ3V1CxQpx78SfoZoVvaVg/mLCjA/ 6o0QWX0wCr1r0uBkPBfVlEpTibzwJIxSzNx627j+geQtWIYnzRWs6yuzm9453cKv1moJr82tp9dp 5+/7qfbkRkaja2oxfqnOBJ4hX4yhByCw28PC+OHl5gZV8B191uq6qwBfnZIr1uRCiebWnXHonpyW 7Nv+PnWIwp2UGscB2CQ+HNSSvIIuVS8aijPRosB6jmIKvsEFlbgzfeQDKs8GQo1MElx9cV2fzlCW OxqMe13Py+m4uqzxzuKrb4odwjgkpzG1AuMRUnQ/Tn4eWuUSlDfxQC7MbKnM1RTyySe8nncSnTij dfHb4wdiNAq8LnIXRs1U40gv3E2ZtkkdTKaMmfdGvV+zTetNOR/fuc+0sF+2aAtg2CTGx2hf8wR0 404KE9Is3qQM+Wpa5qAkyE2rJAC+Yu+2PRWBOt+JQi5/84jpxsBQFxEmCR9vKh/T1NMhxmEs4luw JiZZtrzBY6VrHOZAc/OwoUo8TaD/51q7cewZK/r5r2lmzyOoJEM+ozHub2PYty+o8NNl6XJ5NwXg tcZjFoXNoLZtsec8L6pM6OrA0aeJz1b8nXqr9cfiP1eomIQE1iYGZNi96b5ScH88SFeQzbb14tHv Pweb27i44CFTjO+rPmmWvLEjKytwWarG5O7d8zYTI+tt9GvK8tuuIwUfjWkSamO2N7+F0jgQ5paC aOa+So+OjmhNe8GLOt/4xaC1PLgck/I/ctGczEnxvo5mljFx8Oue8O4ZbTnNv3M6iDp8r+KRtJFj QhTolt9FdGeovczGXWqhgx8wv3gm/jlJOe5nh/ZgiCbJnV4RHv51iCCbYkJqbNNWG1E7JuCo1VRF 7RX33uEXmWPA/H1mKoXdb+N3hZgcfsL3UKjpvXDodz7FV4GnX8rHkeBa2ATzTymLXq2rdCplBOf0 hMU7VH8ID3y4vH9y7fTiS0Im89CPqN+/Jv4He4i2t/vnfP/hv4z/CYkJif4x/icm/P33f8Ji4j/i f/8TJHtbX/OOPIXsTe1bRuSTkrKWvrIuOXFbWJ5CEWNp4yhgZ45GOlh4sqORrmh2F6Qrxg7tyn7N /KCM/QHGygrpwi7K7sFO9hj2B57kSjwUsoIH3LKCv4OR0Q8gDw4UAuzoh0gyjCX5P5mVjIxkt7Nx QLLbuH4vsbZzfGBux/5n8K42Xkh2fnYbK3INcjVLpLnlAQsFOW1v4+pKxvJ0xLC729jZsT9Eko1p zu7qiHGwZLd0cXQScMSgYb+2/WvT7g9t0H/epLkFGkNu0tXiIdISQy6wZv9NZf7vxTbk9uzY3R0x dpbsD5DsFAd5aBt7cgGaHW2OQpJBHNmd7Mw92YV/E9vKxdzaHumAhrFf+z35OyTPn4pi7YJEOvyZ KN9xDxJKdw3+CI70QFpgyEKbO7Aj7Z3QnhR2jo5O7NfImlg8POC0MLezeeBCbsCS3RzNLiXEye5o 9R3lD60f4P7WNAWXwwNXJ5lfj792KPkf5qAXyU252thjDkQ96Eg3z+9iWDjaO2HQ5mgbRwdy32Nc DjqIDE7xq64HivOTexzt6WRDloMsq7m9kx2SzPVbf5GN4elArn9gRBf2X2X+FRL5XWcKd3M3pJWj i/0futHGgewb5nYHMv9muT8V2dXmwGW+d9bDg6+TsLtgyHK526Afsusp3Va+ZaaipqLN7uRi4+hi g/b8g9dQfO9aa0dyoxin74Z1+A5iYU5W/Y/SHmTd0lRkF2S/q6RGPqrpKZILHci2O9CfwvFXJldP VzTSnuyervzsji4HZ092FNLFAWnHriaoze5C9jmyUV3/1NaeSDs7R/f/xOntyMKQTeZIzvlzD2Kn uPbd/ew8/9J3XR9+F5l88/Jkt7BzJOtA7r7fGjmowPMffV5WT19XW0tV/gES7X7geHyCAsL2rrKC v2X/Lsyv3vO7I6Id0WSr/ua9FAfNuR4Y6PsgNnewRrL/OdrvnufoREb4IyPsb5JG5J8qjcjfJs2v g/CvSCME++/lORgf3wfj7zfJ/0am75i/S+XgaG/jQJbqL0H+VvGE/wXiCf8t4h3Qn9zS/zhpqGhr 6bPrqRkry/GJylPcExYm+yd5xiAPBMGDIvk/4ZJV01Rl19NVkvuzvQbyf4b753CCB+8j2a1s7JC/ Db+/Ffv395j/FfjBt47Y3V0OHPNvhT1g+c7xN2FbODp5/l3QBwx/E/L3m+Dfg/z7N53+rNqv8IK/ LQMEf10VUPxYH/8//P7/zxz8X/j+X1jiT77/JiH6/ftfkhKSP9b//4ve/9Nx/Pb+n1DulnL7SKB5 q5FkqqiaNmSdk+i+fuL8xhFp51aua8hzPXOC+jrK9ArnwgPetfmaFdhfvay/eOqprJyosuKtv6D6 dRLxcLtcFSc9Qvff6GAEvxCBCOIjZTVgivNAEfv9cntKmcPwIQO3/SxoMPQEfJIaEeBN68+3Igs3 pw3c32REdiow5kox8U5oiUOUGcxP/k2U2eX1/abg++g8G1tl2CUqwgx8qWN/A9g5oZFopuBb/HyY rXduTLUyQyd9d2uuWH6L9f32ZinuvmqTeFsPHTVCob2x0GyPymKc1/eizFXjtvgLvsV61DSBfZJO uxtMrULSfFriyyFhDbo+d2H2npQPFsIpYJkj/4rD3i43spONpfhLaeoTDd7iv/3Ah+0XEK2K1HBS O47V/7c94LtwbggJhDbtr+oOpCdZnUFIFI/0Xy62c6oqUHLqG3mCChrJqzqOp6lC+lOCrE+aTjAi ZI5hqcGQgZFhv8n2YVXa+xZ+c8WzlftffqkdwmgHLQBOBLo/oCCrC6iPwIrdToEyk9LyxfNvSRsi Y157VihJgXwCRkk2J06lL9CxaCvy5ehanT23wpR2F1fXXHXsnN2eTwkoWLqsxHTyPK2Y0WNApW+o yaDWIiY091RRUUf3Iy9PcBrpaWP1JXVvG52fWvRpBUrosaywdUFtlatP4kBqWcJVe3GfOc3KDD37 s5Vn6iIFk0sG01jqJMCGZ/hToGsaPsdZQKGaimW+AHsBX3DZC5zDDsSMRiHW7TbaTENHKexiTnox 4uUYiysu4+lgc28wQZSw4pEnf3Ywre259BlpmO46LqLqUjCaUXqxHlntTpcb9YwWPA7S5wHFzT2U CLrk6/iZS2tXYaIlhRNH4J8mKmsiOfEen/2/w5BuwOiAg2R8E7JavHjEiwcue7N4ZGsGIYAwJv93 ChCuOc6IOOm8iXnKxwF6sJJbBstLqBBOVeTs74fhN038LheKXcajQz9MMdfv2lwrXhsTcapaPQJz nTD9VdQKJrh0teAnZHhmTj1y5NyIrfvki8cVkviCo2v2MFc2fCNXy2u+oXFa1wInHxvQhGW3195K BBlYafbl8nVQwqmAAy4276w33zSBNaU2u+BUsO5i0CNdVaxwp/5smJM01qfNVpPlbT/x61RO8jTe uWQgK8vbSwYpXTCOefNIU6Kxq2RHpa+1J8x7LK9I3q9RtHLeIfOrSTWf32C7xsnPHvE8+qW/iJd/ 45N5vyxV4DPBK3r4ollJwrhtkXPUlHPIdkes9bTIVPT8UWHdGKe027VPLU/zWEUjLo2oO4atfS5U oNeSUGNJD5dcdFoQRgh3oYo7PfElhj+7jYiYFPc3lKs62Y9uMiPiVd+Szr7vZTrodSGQAUYPo80N QDXmS+K/HWFEmPmj5o4KIZzkPkXaMf2JkWkOuvJ7V68yg/QfsE4GpDO0Lp7h5cXyJ9fOg8of3pL6 hx22ruJ7qT+wwP1KIkjOIr9yxrfSOzq0GRDGRXrmEfZvcSESW+sTLySHNyQdVJ98W+Pz61h51WQI DvAZvr8TVkSvwXKfDm5Gg6gRCi2VDSNt8cYsElJjDoGI78ZeFYMdxR7BqvlWc35CjuiOMFeONL7h k9+p5Z7fdG2RP1NzHF80uoUr3bGpvFS64zP2wNBRvENc5uUYzMRwJYeaLwb8eNoMrORGdHDsfcYs qJt5zAJGbFT1OjWc9eK+Qo9/VReMLfmaWxPJg0d/XNq8TG6WswUzd33kRT0luQPm6sXZBBBPEOa2 fultrva1nZPqlZSuUTg+7xhUv+Sol53DQc+KIjTWf8EcwhpFBVKCjk30XbedNR2/+3p/EOpIkSR+ dWrjEqJIdVcI/+3NWAkXy71QVNM72qnlpj0quDc3NmHlGtj4aT/ksfd6NopD/iUfMGQP9p2Qf9aU HSQ85gf/JazNzHVfsHSpUvhugEndWc2wwzLOUbXbha4hw2NTYkffmjVceW+5U7H6CEY3WRyG2tvo aYHgXZo+bPhHtMxtJ+u3wR6ulQ2DOIfkjR6puEtJnQsxEgM1iJP0HG+P/TIs4/dJaqp/sCjq0YBp 8Ip//TfqrSpOPwFwQrUsnhS6O1HBWROpRaAASw8svEZxoBYfWW1Uzvdx+WsmKNiKHJEGU0oKT2Cp /2oN8oBkwMtMdKrZLWxNZrJSVXqa7NG/TqmXctsvDfHLWV4AEkz61+a9FyARd2kxcdBbW7zzuqtc z098XscQJ8neeAKMIyO50uLl/QpOgMSzTqznEU4Xit3IyFSIMPcKt6kxxET1oJOPfHHnCPNCjDZZ ZLHiTpFJiKk4Xc2Fuqg6Uhy/Gav1y+oZPHLlRqEcUbbVOfQT7DQ8P4rvit8JuKxTcfPLpghOBONZ UOPtAs4lzhox9Za0QwWKItYxIU1QLB2o4S436HsKj1zOpwWDp2xPgHUu4jz4zU7Crh3o+haSGME6 xSXU93xzlego3oZ7oVXO0K66hDqWPuUYrCWgtVo5Wx0CJ+3c3026TDvaSoPp+OmK1jezNKDrxiR+ TQ1hvd6TjpJ531KboyE5HTqiPS4dRC/jOGHbqtmFSFaYImrTzVPGCXZkr2kHhcs6vM0srSF4TVdC craIRLMhTw9El0dqsJIULfeZSD+DjRZGrbsPQI1mjNFEniB2MzogcmU9LqLl7DzJtGGqTqr3+i9S n+nBTarIJY2FBBtBsCHLYUKarbWn7AlqZlUfnOSJgztUvh/0tVebegiV6GseCklIV3gjgZTUcSvq SzA/Iak3TXtEc9r0IrZAWL47rVDwhqSc7JwnYmCUZw5uX1ndVOzX01/kL/TQjBp+FC+HwqxztPLI kW83l4sRTYjRViHyNOsjCBIdipnJk4BQMWKghLk4noCfsB2ZIU++s+TsHaogZ073muNYGHw/227E y3b4Ca4kCLdZgfDhgT9iRLive4IJksW+bnoKLOuRQxMlvpeaVxW2Cz6vivo2Y0d4HecAam98l9dT PuDGpifIJQhymYHbA5/peWOOlnzNQEzMDHwqUKQE67f4ySJachWbniHfAQrg5Nsf3lSzJFrbdZPz YGFQNYH9VubgJO7UsjDLx3IddA4UKTkOEp40YRZk7vSNN9C3FTdGrrEWP5p4pObtsgoQSF1RM6iw tapIZyc5azXBGZSTnPH1Uk5X0HM4RgNc+LR6/IlGVggCo/dU44KmY+W3JiZB5bfqjgkIwVLUhJNn T9X7+fgMBKLBpaZRci1XO/t9fRMDaGZilYz4+xZm/yYHvoWsb7Y0iJfm5YWa4KTQnboPxkj3nCwl 0V6BC5NbkX7vTT2Jiglm1fCLGzePwrEy/L5VBW9YN24+xglJXuIv7c07avZwnHe2arHytUYwek3f 33/Un9ZrdWjiZy/y4viSR3tTCZfPd5ZAl42yKiYJbI3QhaNnz57VuVRQZN1XvrZhrj+5IWz3Lsuh LX+bqX8sqINhbtTiy92YKlSWvSuTSkwVk8ObWibXkSwRppq5PCYLGsT1l6NuRi+F/TUNkHk8Dq9r t1EMGcz1YeYaF8qSX17fC4irYbqG3WItikMkaOtyaWr2R9o0XrHYMjvxtnFv7dMMhm6ethTuW+Jv PkCTUEvwfLd9FO57HGZxAvS1Fp1zCljm7S/d6Wnct2IBZ10qv1Igagr4fRVvUPblv9jD780LlsLH Mk/IYHP65yJLh8OLaJMwR40Sql4Os6HGpENPbhTIwBm6Q1rKsYxWUhuDpeMTBagUv6f9DMEavj5F xYPma3QnB7IrI00I7+YWDbKpkkKGKrb9qO8XPovRMEXIrLdpEzoHPylWmqHZBo33wwtytLyDFXoZ GnD2iKTF54ICFxNN1jO8L0BtT9KvFWqU1jNV8hcVj27OudkOoA/5Xnn00iZluvTNYJuIiYtM7AUq nN9gEGep3rbfrL3qmHxV1OJlmMRzmsBRumFLzz3nOsGaW8F9jROX9NKC+QYXzHfvRhxuLr74eWfa QbDE2Hg5lvTWwlwyj3cHBg2Xbhnksg3v2FhJe5+leU44yhgoa3ekayulnCA957FQqNOnrF+7WNIZ Yu2x57Yxsfn1UDX0MX7iuka8MytaWrIsXBbrN7GpfXzFXBXR5Hh4F2QeiuJWDZUpHqxq8Ll7wUzK XGcu8vBTTv4dZBR5IDLA7VsxX6o+iJ4+WePbvwBfM3YRQp8s+KXARehOcdb4WwjD2fJBZ2BaReAc uFnltFGkFMJWP7szNxk+8MCmYVS/horuZNwFaTpJaC8bv3WLjXgO5t54d7MoKVKP2vsOa/FgXk1m XS+Hr5Rc5k59w4fdQVr3MzEJtlQLN6yY6nfern4JD/Jz6+vHzS2Hu16rVJxbT5bf8++2Ft3C3SA/ tn+EI3WaBDy3z8yeauRz7d7z1ssIQ8SV2L3wqAUFHq3J8oniG6q7qrvENQmaeIxclPlY+BSTecPu Lb027M7W7CnQrqMqP75FL6cVwYgxGn7rimTX4MgMysm7yCBfWgkLCurp+EbQ0KqLhZUkLOaXl+1x ftlYBbdxmqKD96CBFPgHb+UeXz7xicUt2O7H0ozc7Xi/TeqcGvNJe9R0fHkuJf+ux+Cp4GNZlxhk aDrDwI8rzSWFAiUmjTPhhGjWGgOT7F8MvmC1ip2r6WnOh5R3XDq7FdN4mNNHvDRqV9jyreeAMWTt zuHsF71481mJeuUXLq/USpTLxQrHhtUCTkkNDV+1ArbiUl2J3Sy0RZFka6jE6iKh8hhp0Q2vLTk9 izk7ecl6qNgdY9IRmuqtLzlaRxfIYkZtcYqWdSGPX9BkWSNLD7bfyHcCbBAug1XbBQykDL6Sn5V1 O+EuFOu6umI/mVVfSzPm7P6642bTQ6rRpAaIv8zd3jhvzBiRNyBK67XgouovLS14bdcXmdNCE6hZ HXlRurGv6sPpFa54SVRgiLG2ZNb6fMLnS7VcQe/NlSRqVOISKu0ReX6L1eGkSM7K1NH31fKe01w7 aoFyIbeLtwjpF1pfBV9pFi3LwSoKRvdV5ODNJ7O5l1sWJcz6ixKdzund2n7P0iB0QuHz6G6jvM7+ u0i9kDZ+z41nTu0dH54VLpbVnCgwFigezzDMGe5BlIQ9O6BQko9XzUCDr1ns5vjktaFh7VLqZ+A3 iTPnld9KlQxgrdzyy8LCkvC9ubFDwZLbU4QLcbMfy2sJmBmYG7ds3KzSVjkugTjpFzMX+9Hasaa1 Uy1WKzRl323mgreAd+mUi3fPdMsRhvnDGUdP7Pp4F91zXDgNdy+wRksy1PLIaa2Rp9+iLvTjj9Zu gjOKW/7xU9LU3nBhp+Pnt7virb/p7e40ZVz9qHe0KQZ5vc/fNKyHbVHrKLZc9CLVMGG6IXPkvseN UNzR0xnnd23qbd46eQOj5PG/2+hSIkrlJ1hegdo+rVo2C+UlLEa9ffY7EX/Zo5Xut3uvf7rf79/p Fyv/Tfz397cQ/8r9X6KiBzHf3//+g7D4QfxXQvjH7z/+N8V/GXx/i//GlRamQG9uXEjBsctxX5eZ 61DLwDju/+S/9ZM6rzu3lAHm/q5vCuOpe19ERJj6XHthjmc6O8O5jswCYVlH/kK0zxkda6s9Nueb w3YhW15kJV+BWcLpi3wxMrOZTQK49AHiy+mUO106y7cfwAHDVx09zm9RVyDLsisZuM5tzCMWdMNL DKtVdGi46jlvkq3++ruqWieBUvkLbuugFragLqWO160Hc7ud0x981D4xfEQiyFO//Dj0ukmDPre5 fUKBjoSenlxEUQHqpbTxGG4tVp+QpCY+3V5DVzsTIjNJ2jb8MNoI6Cd9ffDFVR+YXLo54I0dkBch Sq+5RP8EQzck8rGhkzROAJuJlIAIsfEkQAxXhMsTb2KpoGVFRsiyPZIW+rXxANgF9IT/P5VF+iOo ErZ/gRXNaoK3ZAPqeyf2Rvv2FC4r4nMxJfs8Sfvu6x2Yh4BB+8Q+3Tk0fXLTxObCfn/I/lAOTnWj Es59ZkNbh4GxRrjeFBjdb/+qU+NqB9D9KwT9V7HsvKuIcRz2g1f67fcX8qEnVlK27Ct2s3zt+SmB tpH69QWHMbwjaW7dPb9T4jC5+sYEeleC8v32Hi6l3yopiS8hsenaMlThiDa6BZdXqKarS8RtVWjC iY318hf23MKYEVS0YfjV3SK/aiJi6Z0zwiMG8Rocdjqv66D4Hkw2ZPwfVd/gNei3W85ito1ZPeVn GndjJOcY8D8vxf8RS5TK4KPr/wRI+nwHiu/VaxNRrAeFVFDv4z9cXn8H24126CigOUA6AZBukPke hKZqPOq/CW+OIap7gb7p8ycxAlPr93RbsnTsMlHhWg3Q6w/iE9To2gvlObCl2bKjZECQGh0S3LGq 345hRGcfBYgQ7UEraMJJMiQjNO8PYmR18Bx+oYcAkkcyuHKUkIxiVZ7ewg+bLNZX+PblxAs66zl4 ZWyobAd18ETunTLpSjHz2184SvBtUVmCP4EZwnVwB19YD4VxMg7b7AsRb+J93PAY99YOjL8IWtxG s96kixWdPXIKurR50fwwOokkz5aK23QCcCpxIN/WJy9VQKM+emm0Hp3pP22rYjL60zlbAdnVkujG O1nLqw4z0eJzRVann0Jcyx/Xzg/gZtyTdcR2zU3yDLEvwrK4NOB5xWwh0+qrgkATV7RRz4YRy8yX W5rOoh91NcU/5VqIcLZ81JpIz8yXklMIDF1t1xzjKojCWGCoXdl4DcuTdHCNRVlczjtiJKkwNV0f 3izHtKAG3YjEma8zTz/yDXvTJ7DW3ELnt39KuZeiIfBS811+qkafsBq0Ja2psJRf42WY947kFhcF BqBX7yQKpSoDzvWKeBezsb4QDOfeBzs1+E21aNCKBVgnvW8vkJ3lJtmeAJYuPAO3lQ72cWHuAjq8 f7nZC0MFTN5LkewuEFMtwmQGDAFxRR2c8bFh051dNWqQStfFes83sMgklPyLDvamrgKx8KPEc+qd mJYxfi54IfgwMaczrbA97U349j1g5YIOsV8fK58OCwA1MTZoVjhWBX4BOg+54cUTrMjOSWA+d7BR sKj3gKVjlQH6JgFZHfhrAk6Dlr6jIACM4SD74cFGu3ca5SEwg/ewENB/WpeT1EmWhzyjiEQFVn5a Toe6j0Lf9OGizf16GHEilKKhoIm9ic8gdiJJurVE5sAQ0A6wVcSq4CPQIdg6E1Knkh7aPkPDMZ0P /RI8h55OxkynkHSJxp1pRfi0xl76wKcgNWZasjuNNktDQY8sdCZZ6MKutEtdaUXtE+FeFgB0CFiR IvLexsq/g3HOdOZ0I2nXu3YtgRkMpBLBHHa1kx7LT8rblCyHYTSwDDffbX7pneksQk+LYFZx1dkL S7eTz2V/lfaHiUehcjS00Zn1GB4zbopXSRpt6GlVjA2wqkc33SnxKBQW903QATVwk1awJSTcFMvn FpRybjgxT/VOwPwBmyI2VOXcBXyHJdUrn/TdiwKkzt2LAYeLDWGvdXXUPKIIj6yhLSmvcPP2NEvA NpmvVbVeqf82/u45dItxCKbWgpKjo/yFrZQd45N4zEXVS3WT0pcq3S+gQ3yenvFy/tkn1tdeG/ZW CWeKndd7jg7ocio7grtMKAHlWw9jpgcgdCGswBC7Bk1Oh5r4PIX5mOD5ieGgeWhy09hlzLSaPPFF 4FBzOje53+FmznCAGTAhUkQsUZATZOMtpPK9LksBdS6iyzNgcsEvf3NAeBQk9hfbSCV7xFkOQeGY EK49V7TmyU1hcg3TdI2U71ta6TCZVzAlFilf310F8HNSXWrlKRphEfnueJ12S8BY+VUBs8jLIP2n 4DVHAezDchXsG7SNXLPdC/BdD78WBBOgspEnD4rO/PCx6ei2z5rAV5Mb6PI0WAjM+aoNuZkhDbLP JINqrGifWLBDTxAq7OzBXryLVWGETJM0Ph8CbjawAl60gJnfx72u3a1lQTNCji/36424edJC0q22 mW+c/fW5by8lM3o3zz5MGm9a2JlmeXnFb/OBwKdNZizRHJGin4pWzbz1ipvTjDIijfDeA1g/YcPs q1m/niGzhm+Cw6XSRA2xoRwKKMx0w6Gv+t+S4IyQvAHWF4LJ2a6+he2iga0QjM0uFZAiHdSbpkd2 WnxaWI5GkkYn/dfZVI029fg0Pq1tAnpa3qUQlGolr89yYbsUQE1qRRHYt9JtAX27jR3u8J7uHLvQ p48/M/scciBkzs8wT+zAoLrWdk5iZ0ImiuiUyvfhOWz3HSiki+acfsHyvjstIYUvOqGG2JnTS4/M fUUeli2YaexM51gcfLpzk9x1Er30IXOamGkjvgNTjkUp4jvQyvbzM53ErVvAm7CutARQIwWVrMFm AE9AiIk+MHPmpdwkFtNAVnobzED+Z+I5lXPUX3WAyzsdaGol5shbHCHulzrSujA8avhHdttE5gDt Xs5v4qkiMxozKn4/g32WssmoS9bnTbvFE9LdO9LIjn+OrKhXMxeksvk6CXW+iuQiyW52sTrgWFCr tc03mRJocrAjLQKtuc08ofcU5OnK32KgFC19tvHs57NThmq6z6QSOAHaM9MvSktS+D6o49+IRSy0 he68W+Oc5BMKCUbEMp0E+BSxx4GiG3j1g78EJdBecA5t1I4Jrpnp5xWB4ikgh8dgZGLTE9AkEcVJ zEskMRCNT0P8bFl8Z9HZxwAGNOHIX0Mo7Jq4AddJxF1rNzi/kEPivhjQlZENwmtqP1xbRmfStnPu YdK4c1faSttXhUbn3ERnZQ9B84/BZDLT+XSSYWBQV0GVdSCPX/bm4Xb63Cozmxt4N/ItVecWWo4e ncT34hmY8QSGVj57MCcHgNeuHEjaTq98C6+niD+LBvT4klE8SqIBC+9Q0hylJEj8iy5G4CWPCb7g EOBqrTz9ohA/DVGZX+rl1J6v5m0nGiehZsbZIZjOJ5tDel/kU3E4zHPb+QyS7TbzCVfnYdB3/2uR IAEFgSiFd7fxyDSw6dusUSdGswNZYWas4MC46VIun4ULwQCXOsXRpG0IkTwfZE77aswQj1PrFbOZ u28c85IwF+hcjlbGB/todvYcL0b046IicRc6al/OuNgPBJ92zy3VoZHERDWD2XEI3MDLNktMyTcc Rqx0LhnsfZnUdKeocClNvGa6c7qx1EKCsBad3HRHBZ7LEmpjx92kOSSuBh9YHYzOwXlOl/Tjg/1K oOQP4l/PsZU+zdOoZI1Gl/qDTm53NKev9YrPmD/rCZDIuJFK+mo1fg4NDD4GZwrmTEwFfVIXO62j EzWYXBJsxOy1sNr3pWwCpRiRLGZBz0NM49P51OcDQQlN/OoXCHQF8M/BjhH33gJRiY5+O6qa2ISj PE8NscWbylmeRcFNdvlaNlyrrqenHG/F9a69BD/C2gs+BRGZdTIKlOEPGLW7OdPuZhTs3iAvoPDn iMbHgOeJqOcppOXuMflwRXJO/2OlmWi9sO3bJwCNRNRJifbIqFe35eY5LuQqxvUyALjMep+r/iBn e8HRA+bvlyuFkDFaU+o96Lcl0HQYsyt6ULtKwcaeFoebL+I/2W1AhpsUgOMtScXQJTKuXRZK4Dp0 zi6JVEJuXECet3nSB0N94OwExe/OO6SJPQbxpxG9OMhuTOSlQNMfhxoztHCBoMXdDAMlvPC7rqwk ElO3TQ95xTHz0fa3Ki+uqMF95itmNVBmtiudW3FJn3ptarT0B6Ezk/e8aTjBByjjAp/Y83axXt3b spEfOwbQJgnaLMs2bbujqk8KKtYN374HP6jTIpenua9G17mGg2w8kSPXfh1MvzdxBFD+dbj8r80m fREbI7Bidut9gfK2D6+Z5ypaiuvKmj4wl5ZFa0UXDgU6KxNUYhRSW7BwOV2YSw8m28oDYJ3P89hw TmmayfqWL3oL/wbi9RbeYZOi+LrbK2/rJDwIzUQYYiMsyY9mucge6+loJ3JlvklgKPGOR5d5Oal4 CH3vIMIwkDwP92Roma23H8CkrbNEGZZS42zdSJkiCby4uMm7BrY5r6LCnq0xv7mA15IzWHNtJLTS FAx/jt4NLEgBbbWBFl8O1HnIRUcm9GVP5HCP90z/ik5K34qORdGrua13uVNfO72K8u+Sdhnw8bTL HyjrMqJn2yRH2e/EvQuwlzo2KZ/IS/gSZjI4JdPvl1sWGlTKxDsxXFZ6Er4eAI51kDr7SSLBmnyV R+uvGAPm+Efzukmkn4vbPnkBvo7DtGbsrNv65r5aI3sfvEVlbT8UH2mxsp53e9Wldxf2Cjlor5uz cDl32umxmXSxkBFwct50qDw633NttJ3wWYNnK2j+g3BYmcI6Wryid+aOXgxMK2u5MiZAinewoqda +9qCiqm6TgBbYkmInIJtiJPjoL4Ucq7PRqO6oPBFq8SEmcGwk4rfY8N5HEuMjADm4tdLYAhNLkJq eLA1QnfsWLXKvoQKSjI+iCOGl/KVBSAIjX1RZm2ljwnxPpmxLen8io4VPAEmoa+sOe6hnyWNCT33 R9tHOxc3+jgNCC5JPY6CVQprLPqOWwkv38ajwADASnN/tMAIsLq2Nmfi0fySTxVL2XX3dp/2Y7fs mkgl6qCuvLzLs20mzYFN9UXwvS434cfm/P4lGcoOO9kmJUZex/fuMMNc55spFyiiTaBxk5+Msqp6 vjW+kr6N9x7rwgXSZdCmOVwdkWSeVjV155CUDOzV7mqaBxrj1Xdr2+2CMMh1rnVY/gDJuJgpFC2e grKdob+1rWbQpZatAk1i+ffHbFm1ivpWBgifs4xf2lV8HPboiEhy/arg3j2fcOzZcHsIukT1hN/C zPBSiJNfRduJD+6OLKV+3U60faeNAuojuMriXoLO8u3XHn8YXbix53mzJcfo+ivN5X7Hshlbj5gx zgKC2u6WpG7JVdiJg52e2qlga62ylnaV1d3hd840OXOeg7overcafS1yvz5QoIxs29W46En8SBPS 1rP5KF7/9ktZbIeyG6EkxHN8N/fC4FudhRVZnCuDf1QntMYiaQu7egXpslZJ8iI+6M90/RItvcp/ 68G415sM5wW+KDIPIMStzlJnD785sFUNhags6Mpvw7fLbUlO1QH27qmrqAXE5gU52sgulWkvR/tf pMfHlEJvxfl8uaym8GpPLIqkHjwY4nzpurHnzXFAysSkHCY6+M4pGaddVBAwle94Dz7/VUh+ypht WNsfFyuhjvdm1UJitSe0nt6Ds1YX6mjAq6alc0IeMVxZJ/U+armyUH3deNINE5WELhmo7vNo2xOP fTK152ZdOKC26qovqa+FAAj8/XcgQ0JgU4a25NCcKzGmDposn7gVCsejGPD6cKkV3hyUC7UC3Keg Mfua+8Q0Y1i2UAkT9GqzsQFqVbqXECZzd53nG87r/MqslzudIKE0/IoMEPGZAxAsZ5IWsPpp8qPs yaBVTzdhO1VIBRvqJXbKnTOzhs5xdgWWndC9gtbdnqroN5ypCbza5tA/p5kHBkwVffq8Ejx6fZB5 sC44nmpXL2CuzI1l9HKNvMpLdBQdfjCDkFQR6s34YLBOesYpxD2jFBe7xT68NYlhvRSrND5qwvLm 7rcbIwlW/YvslYvvcmF5jkTjcqLtPWVR2SmkmoALTGhZ77ogm63jb3uB8Uuuxotzlma1jdzwlK3N lY9GN538HU0VDVZZuOEwAzcDXxr7+2bSAhkJPZLbq13XpfvsTb7SxEFmbmfjtQqfk0daCm7fvlDK XKNis7YzSioulmbFRYQ5RMDkErrEALNlddwQrJo+ruYHU8h+76igCkFASge9YY/Nozix+iegY4bN jS/nSl+8POPaQQlp+WIMTOGCtb5FbResmrqxbGr3OcreOBo2NZh+e8nvWiXjCazd9xPemb6krUXP WMM4gsbc3FKlWPnivMzi0GMwOoTsjeyZiBeq1vmSYEJ6yjc0Wpyr5aH9x83Aizf3yJjI9ypoOZsf m4F/0A/6QT/oB/2gH/SDftAP+kE/6Af9oB/0g37QD/pBP+gH/aAf9IN+0A/6QT/oB/2gH/SDftD/ U/T/AdSdiWYAoAAA --------------Boundary-00=_HY34P25E94MCPC6549FY-- - To unsubscribe from this list: send the line "unsubscribe linux-kernel" in the body of a message to majordomo@vger.kernel.org More majordomo info at http://vger.kernel.org/majordomo-info.html Please read the FAQ at http://www.tux.org/lkml/