From mboxrd@z Thu Jan 1 00:00:00 1970 Return-Path: X-Spam-Checker-Version: SpamAssassin 3.4.0 (2014-02-07) on aws-us-west-2-korg-lkml-1.web.codeaurora.org Received: from mail.kernel.org (mail.kernel.org [198.145.29.99]) by smtp.lore.kernel.org (Postfix) with ESMTP id 2C306C433EF for ; Thu, 4 Nov 2021 13:24:57 +0000 (UTC) Received: from kanga.kvack.org (kanga.kvack.org [205.233.56.17]) by mail.kernel.org (Postfix) with ESMTP id 74A816120E for ; Thu, 4 Nov 2021 13:24:56 +0000 (UTC) DMARC-Filter: OpenDMARC Filter v1.4.1 mail.kernel.org 74A816120E Authentication-Results: mail.kernel.org; dmarc=fail (p=none dis=none) header.from=intel.com Authentication-Results: mail.kernel.org; spf=pass smtp.mailfrom=kvack.org Received: by kanga.kvack.org (Postfix) id B64796B006C; Thu, 4 Nov 2021 09:24:55 -0400 (EDT) Received: by kanga.kvack.org (Postfix, from userid 40) id B13496B0072; Thu, 4 Nov 2021 09:24:55 -0400 (EDT) X-Delivered-To: int-list-linux-mm@kvack.org Received: by kanga.kvack.org (Postfix, from userid 63042) id 9B3CC940007; Thu, 4 Nov 2021 09:24:55 -0400 (EDT) X-Delivered-To: linux-mm@kvack.org Received: from forelay.hostedemail.com (smtprelay0089.hostedemail.com [216.40.44.89]) by kanga.kvack.org (Postfix) with ESMTP id 8482C6B006C for ; Thu, 4 Nov 2021 09:24:55 -0400 (EDT) Received: from smtpin12.hostedemail.com (10.5.19.251.rfc1918.com [10.5.19.251]) by forelay02.hostedemail.com (Postfix) with ESMTP id EC04556F3D for ; Thu, 4 Nov 2021 13:24:54 +0000 (UTC) X-FDA: 78771318108.12.630E68D Received: from mga14.intel.com (mga14.intel.com [192.55.52.115]) by imf01.hostedemail.com (Postfix) with ESMTP id 987BC508E5D2 for ; Thu, 4 Nov 2021 13:24:42 +0000 (UTC) X-IronPort-AV: E=McAfee;i="6200,9189,10157"; a="231949245" X-IronPort-AV: E=Sophos;i="5.87,208,1631602800"; d="gz'50?scan'50,208,50";a="231949245" Received: from orsmga006.jf.intel.com ([10.7.209.51]) by fmsmga103.fm.intel.com with ESMTP/TLS/ECDHE-RSA-AES256-GCM-SHA384; 04 Nov 2021 06:24:51 -0700 X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.87,208,1631602800"; d="gz'50?scan'50,208,50";a="450199683" Received: from lkp-server02.sh.intel.com (HELO c20d8bc80006) ([10.239.97.151]) by orsmga006.jf.intel.com with ESMTP; 04 Nov 2021 06:24:49 -0700 Received: from kbuild by c20d8bc80006 with local (Exim 4.92) (envelope-from ) id 1micjY-0006Qx-81; Thu, 04 Nov 2021 13:24:48 +0000 Date: Thu, 4 Nov 2021 21:24:32 +0800 From: kernel test robot To: Nick Terrell Cc: llvm@lists.linux.dev, kbuild-all@lists.01.org, Linux Memory Management List Subject: [linux-next:master 6210/13128] lib/zstd/decompress/huf_decompress.c:890:25: error: use of bitwise '&' with boolean operands Message-ID: <202111042124.mRUZspCS-lkp@intel.com> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="WIyZ46R2i8wDzkSu" Content-Disposition: inline User-Agent: Mutt/1.10.1 (2018-07-13) X-Rspamd-Server: rspam03 X-Rspamd-Queue-Id: 987BC508E5D2 X-Stat-Signature: 9qzfxo6hjf69newzekdofssxcwpuhi3o Authentication-Results: imf01.hostedemail.com; dkim=none; dmarc=fail reason="No valid SPF, No valid DKIM" header.from=intel.com (policy=none); spf=none (imf01.hostedemail.com: domain of lkp@intel.com has no SPF policy when checking 192.55.52.115) smtp.mailfrom=lkp@intel.com X-HE-Tag: 1636032282-311677 X-Bogosity: Ham, tests=bogofilter, spamicity=0.000000, version=1.2.4 Sender: owner-linux-mm@kvack.org Precedence: bulk X-Loop: owner-majordomo@kvack.org List-ID: --WIyZ46R2i8wDzkSu Content-Type: text/plain; charset=us-ascii Content-Disposition: inline INFO skip CC on NO_CC_LKML=Too large changeset: 39854 lines tree: https://git.kernel.org/pub/scm/linux/kernel/git/next/linux-next.git master head: 8a796a1dfca2780321755033a74bca2bbe651680 commit: ecea7adad80d9d230df766345e5f8061792da00d [6210/13128] lib: zstd: Upgrade to latest upstream zstd version 1.4.10 config: riscv-buildonly-randconfig-r002-20211104 (attached as .config) compiler: clang version 14.0.0 (https://github.com/llvm/llvm-project 847a6807332b13f43704327c2d30103ec0347c77) reproduce (this is a W=1 build): wget https://raw.githubusercontent.com/intel/lkp-tests/master/sbin/make.cross -O ~/bin/make.cross chmod +x ~/bin/make.cross # install riscv cross compiling tool for clang build # apt-get install binutils-riscv64-linux-gnu # https://git.kernel.org/pub/scm/linux/kernel/git/next/linux-next.git/commit/?id=ecea7adad80d9d230df766345e5f8061792da00d git remote add linux-next https://git.kernel.org/pub/scm/linux/kernel/git/next/linux-next.git git fetch --no-tags linux-next master git checkout ecea7adad80d9d230df766345e5f8061792da00d # save the attached .config to linux build tree COMPILER_INSTALL_PATH=$HOME/0day COMPILER=clang make.cross W=1 ARCH=riscv If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot All errors (new ones prefixed by >>): >> lib/zstd/decompress/huf_decompress.c:890:25: error: use of bitwise '&' with boolean operands [-Werror,-Wbitwise-instead-of-logical] (BIT_reloadDStreamFast(&bitD1) == BIT_DStream_unfinished) ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ lib/zstd/decompress/../common/compiler.h:127:38: note: expanded from macro 'LIKELY' #define LIKELY(x) (__builtin_expect((x), 1)) ~^~ lib/zstd/decompress/huf_decompress.c:890:25: note: cast one or both operands to int to silence this warning >> lib/zstd/decompress/huf_decompress.c:890:25: error: use of bitwise '&' with boolean operands [-Werror,-Wbitwise-instead-of-logical] (BIT_reloadDStreamFast(&bitD1) == BIT_DStream_unfinished) ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ lib/zstd/decompress/../common/compiler.h:127:38: note: expanded from macro 'LIKELY' #define LIKELY(x) (__builtin_expect((x), 1)) ^ lib/zstd/decompress/huf_decompress.c:890:25: note: cast one or both operands to int to silence this warning >> lib/zstd/decompress/huf_decompress.c:890:25: error: use of bitwise '&' with boolean operands [-Werror,-Wbitwise-instead-of-logical] (BIT_reloadDStreamFast(&bitD1) == BIT_DStream_unfinished) ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ lib/zstd/decompress/../common/compiler.h:127:38: note: expanded from macro 'LIKELY' #define LIKELY(x) (__builtin_expect((x), 1)) ^ lib/zstd/decompress/huf_decompress.c:890:25: note: cast one or both operands to int to silence this warning 3 errors generated. vim +890 lib/zstd/decompress/huf_decompress.c 802 803 FORCE_INLINE_TEMPLATE size_t 804 HUF_decompress4X2_usingDTable_internal_body( 805 void* dst, size_t dstSize, 806 const void* cSrc, size_t cSrcSize, 807 const HUF_DTable* DTable) 808 { 809 if (cSrcSize < 10) return ERROR(corruption_detected); /* strict minimum : jump table + 1 byte per stream */ 810 811 { const BYTE* const istart = (const BYTE*) cSrc; 812 BYTE* const ostart = (BYTE*) dst; 813 BYTE* const oend = ostart + dstSize; 814 BYTE* const olimit = oend - (sizeof(size_t)-1); 815 const void* const dtPtr = DTable+1; 816 const HUF_DEltX2* const dt = (const HUF_DEltX2*)dtPtr; 817 818 /* Init */ 819 BIT_DStream_t bitD1; 820 BIT_DStream_t bitD2; 821 BIT_DStream_t bitD3; 822 BIT_DStream_t bitD4; 823 size_t const length1 = MEM_readLE16(istart); 824 size_t const length2 = MEM_readLE16(istart+2); 825 size_t const length3 = MEM_readLE16(istart+4); 826 size_t const length4 = cSrcSize - (length1 + length2 + length3 + 6); 827 const BYTE* const istart1 = istart + 6; /* jumpTable */ 828 const BYTE* const istart2 = istart1 + length1; 829 const BYTE* const istart3 = istart2 + length2; 830 const BYTE* const istart4 = istart3 + length3; 831 size_t const segmentSize = (dstSize+3) / 4; 832 BYTE* const opStart2 = ostart + segmentSize; 833 BYTE* const opStart3 = opStart2 + segmentSize; 834 BYTE* const opStart4 = opStart3 + segmentSize; 835 BYTE* op1 = ostart; 836 BYTE* op2 = opStart2; 837 BYTE* op3 = opStart3; 838 BYTE* op4 = opStart4; 839 U32 endSignal = 1; 840 DTableDesc const dtd = HUF_getDTableDesc(DTable); 841 U32 const dtLog = dtd.tableLog; 842 843 if (length4 > cSrcSize) return ERROR(corruption_detected); /* overflow */ 844 CHECK_F( BIT_initDStream(&bitD1, istart1, length1) ); 845 CHECK_F( BIT_initDStream(&bitD2, istart2, length2) ); 846 CHECK_F( BIT_initDStream(&bitD3, istart3, length3) ); 847 CHECK_F( BIT_initDStream(&bitD4, istart4, length4) ); 848 849 /* 16-32 symbols per loop (4-8 symbols per stream) */ 850 for ( ; (endSignal) & (op4 < olimit); ) { 851 #if defined(__clang__) && (defined(__x86_64__) || defined(__i386__)) 852 HUF_DECODE_SYMBOLX2_2(op1, &bitD1); 853 HUF_DECODE_SYMBOLX2_1(op1, &bitD1); 854 HUF_DECODE_SYMBOLX2_2(op1, &bitD1); 855 HUF_DECODE_SYMBOLX2_0(op1, &bitD1); 856 HUF_DECODE_SYMBOLX2_2(op2, &bitD2); 857 HUF_DECODE_SYMBOLX2_1(op2, &bitD2); 858 HUF_DECODE_SYMBOLX2_2(op2, &bitD2); 859 HUF_DECODE_SYMBOLX2_0(op2, &bitD2); 860 endSignal &= BIT_reloadDStreamFast(&bitD1) == BIT_DStream_unfinished; 861 endSignal &= BIT_reloadDStreamFast(&bitD2) == BIT_DStream_unfinished; 862 HUF_DECODE_SYMBOLX2_2(op3, &bitD3); 863 HUF_DECODE_SYMBOLX2_1(op3, &bitD3); 864 HUF_DECODE_SYMBOLX2_2(op3, &bitD3); 865 HUF_DECODE_SYMBOLX2_0(op3, &bitD3); 866 HUF_DECODE_SYMBOLX2_2(op4, &bitD4); 867 HUF_DECODE_SYMBOLX2_1(op4, &bitD4); 868 HUF_DECODE_SYMBOLX2_2(op4, &bitD4); 869 HUF_DECODE_SYMBOLX2_0(op4, &bitD4); 870 endSignal &= BIT_reloadDStreamFast(&bitD3) == BIT_DStream_unfinished; 871 endSignal &= BIT_reloadDStreamFast(&bitD4) == BIT_DStream_unfinished; 872 #else 873 HUF_DECODE_SYMBOLX2_2(op1, &bitD1); 874 HUF_DECODE_SYMBOLX2_2(op2, &bitD2); 875 HUF_DECODE_SYMBOLX2_2(op3, &bitD3); 876 HUF_DECODE_SYMBOLX2_2(op4, &bitD4); 877 HUF_DECODE_SYMBOLX2_1(op1, &bitD1); 878 HUF_DECODE_SYMBOLX2_1(op2, &bitD2); 879 HUF_DECODE_SYMBOLX2_1(op3, &bitD3); 880 HUF_DECODE_SYMBOLX2_1(op4, &bitD4); 881 HUF_DECODE_SYMBOLX2_2(op1, &bitD1); 882 HUF_DECODE_SYMBOLX2_2(op2, &bitD2); 883 HUF_DECODE_SYMBOLX2_2(op3, &bitD3); 884 HUF_DECODE_SYMBOLX2_2(op4, &bitD4); 885 HUF_DECODE_SYMBOLX2_0(op1, &bitD1); 886 HUF_DECODE_SYMBOLX2_0(op2, &bitD2); 887 HUF_DECODE_SYMBOLX2_0(op3, &bitD3); 888 HUF_DECODE_SYMBOLX2_0(op4, &bitD4); 889 endSignal = (U32)LIKELY( > 890 (BIT_reloadDStreamFast(&bitD1) == BIT_DStream_unfinished) 891 & (BIT_reloadDStreamFast(&bitD2) == BIT_DStream_unfinished) 892 & (BIT_reloadDStreamFast(&bitD3) == BIT_DStream_unfinished) 893 & (BIT_reloadDStreamFast(&bitD4) == BIT_DStream_unfinished)); 894 #endif 895 } 896 897 /* check corruption */ 898 if (op1 > opStart2) return ERROR(corruption_detected); 899 if (op2 > opStart3) return ERROR(corruption_detected); 900 if (op3 > opStart4) return ERROR(corruption_detected); 901 /* note : op4 already verified within main loop */ 902 903 /* finish bitStreams one by one */ 904 HUF_decodeStreamX2(op1, &bitD1, opStart2, dt, dtLog); 905 HUF_decodeStreamX2(op2, &bitD2, opStart3, dt, dtLog); 906 HUF_decodeStreamX2(op3, &bitD3, opStart4, dt, dtLog); 907 HUF_decodeStreamX2(op4, &bitD4, oend, dt, dtLog); 908 909 /* check */ 910 { U32 const endCheck = BIT_endOfDStream(&bitD1) & BIT_endOfDStream(&bitD2) & BIT_endOfDStream(&bitD3) & BIT_endOfDStream(&bitD4); 911 if (!endCheck) return ERROR(corruption_detected); } 912 913 /* decoded size */ 914 return dstSize; 915 } 916 } 917 --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all@lists.01.org --WIyZ46R2i8wDzkSu Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICNXbg2EAAy5jb25maWcAnFxLc9u4st7Pr2BNqm7NWSTRy3ZyT3kBgaCEiCAYApTkbFiK LCe6I1suSc5M/v1tAHwAJOjMObOYsbobr0aj++sGOG9+exOgl8vxcXPZbzeHw8/g2+5pd9pc dvfBw/6w+3cQ8iDhMiAhle9AON4/vfz9/rQ/b38EV++GV+8Gb0/bSbDYnZ52hwAfnx72316g /f749Nub3zBPIjorMC6WJBOUJ4Uka3n7+/awefoW/NidziAXDCfvBu8GwR/f9pf/ff8e/v24 P52Op/eHw4/H4vl0/L/d9hJ8mNxsrj8Mbsbj0dfh+GEyvhlMxqOb7eh+PBgOxrvtYDy52d7c /Ov3atRZM+ztwJoKFQWOUTK7/VkT1c9adjgZwD8VDwnVII6XrJEHml84DrsjAk13EDbtY0vO 7QCmN4fekWDFjEtuTdFlFDyXaS69fJrENCEdVsKLNOMRjUkRJQWSMrNEeCJklmPJM9FQafa5 WPFs0VCmOY1DSRkpJJpCR4Jn1hzkPCMIVptEHP4FIkI1BTN4E8y0VR2C8+7y8twYBk2oLEiy LFAGWqGMytvxqJkUS9VsJRHWICuSZdyaeswxiitl/v67M9NCoFhaxJBEKI+lHtZDnnMhE8TI 7e9/PB2fdmBJb4JSRKxQGuzPwdPxotZgMe7EkqbYy1shiefF55zkxMvHGReiYITx7E5tCMJz W66UygWJ6bRZ8BwtCegLekY5HEqYACggrhQNexacX76ef54vu8dG0TOSkIxivaVizldNd21O EZMlif18mnwiWCpFe9l4TlPXekLOEE18tGJOSaZWcedyIyQk4bRhw3qTMCa2XRpK1RG0anXB M0zC0hqpfc5FijJB3Bb2AkIyzWeRGulNsHu6D44PLX36GjEwHVrN0vIRaocwWOdC8BwmZIyu M6yWAI0nUrTaqjMrKV4U04yjECPxemtHTJuC3D+Cg/VZg+6WJwT22+p0/qVIoVceUqw1UJLB bwCHwuq8RqzZHrOd09m8yIhaAzO7V+u0M7H60KZRy84JkIpPtF4T/PQtSEk1B6GemyLnSZrR ZX3GeRS5yyjn5HZc9ZtmhLBUwiK1Q607ruhLHueJRNmdVzWllM3Ti8Bp/l5uzn8GF1BEsIEJ nC+byznYbLfHl6fL/ulba6ugQYEw5jCWsed6CGWA2h83bM9epII6sxe01kdIhfLkoVcp/2Ci ljeDSVLBY6QcRGfNGc4D4bFEUFEBPHt68LMgazBF6VmKMMJ28xYJoo7QfZSHpM2SGcLVmNaI QoLxqJjDbPemOAkBbyLIDE9jqk9XrR93UbUPWpg/nH1a1DbBsWdZdDEHZ+V4ueqMCzyH8fVJ r06B2H7f3b8cdqfgYbe5vJx2Z00uZ+XhWrs0y3ieCs8UYBi8SDlNpDq2gAQcizezQLnkuoO+ WBgJsCywe4yka1OVPkmM7pwjGi+gxVJ7xyz0djvlXBbmb38YxQVP4RDQL0T5fuXE4D8MJZj4 ltmSFvCHFSHAicgYzA+TVGq8qqyl4Ru7tBeg3T/E6MyvkhmRDMyu8k4+i9Zaa7xXSY5MRGkI KRd0bXvT2qJgyxZ+zeV+jU0RRMEo904nygGiW9NQP4uUtvyyIWOWrvHcCrAk5a4HFnSWoDjy b6xeS+QzEx3SIgsxiznAJLtjRLm3T8qLPPN7QRQuKay71LR10qDrKcoyaofvhRK5Y46mK1rh 38iardWrLF3SpbWByki007UXtgAdWvpjUxKGJGxpW1l00QYJKR4OJpVHKPOvdHd6OJ4eN0/b XUB+7J7AVyNwClh5awi5jd91e6xXqAGQYcJsiyWDJXHsjQ3/cMSm7yUzAxY6UIER+85CnE/N JOzchKVIArxZOIYVo2lPB64Y94uhKWx7NiNVIGz3XUQQWpS/LzI4h5z5T7cjOEdZCD7bZ89i nkcRQNYUwYhap0jaSYxetwqgAFAlRZYbMClbFfVL3bvZVCU6Hk1thJlRgZctTMkYSossCQuQ hMwDoPmH1/hofTu8cforxNRyBYxZQXSJdCsrgUsryqShwPoBggkibwd/44H5x5lCBMcGDiRk hQqXtOZvAHw/m8SQn1QZFeOhnchoiRUCA9SRFcXFPAfvHE/bneRpCmmtKHLQ/ZRYJw4gAl4Y +FAKeRA5gmQtg+gHhmVCXVtA5KxLna8I4GWrvwh8PUFZfAe/C+P7Kh3OTO6t8zRxW2tbAQSI vdbUDFY4YrCTw25blmQa4+UYLAByUJW2QXSJURbRzA/ylaygEbizXvaSunitgSPOBCoAHOxO p81l40zNMTRI85FEcFjAVSSVJ61HLLm+OTXYtTuGHj09bC7KZwWXn8+7Zli9+dlyPHKwckm9 nlA/9tBGBhsUxnzlQxs1HyWWMcDJSud3QhnycGYZoLCDQZIplyDgiNbDQb6WxrnG2p7BZJ4Q C/U2KVrOkA+LaT0D/i9wZSznl+fn40kV/1KWt/RjxHVsS1luuyNPq2bwyJ1q3cjdBTuIOZi2 yU2Hg4F3C4A1uhp41geM8WBgK8L04pe9HTeOyIDdeaaSr5ZDVQ6wWA6GDi4ga+KvAOEMiXkR 5ix9LYZaMF2luEcQOz4re7UCNmahruo1VSsSUfBIuWU9QHGAIVgYRC9Wwj267snynAHNCTn+ BdkDBPXNt90jxPTudFLbIbE6ZDdjMwW3FAQPDdOXlTLIahZOP5U7NKUdB5qsPoOPWpEMVhlR TBWQKEO3v+tWVxB1bJPtXaFef7Q/Pf61Oe2C8LT/YXCTpqOMBUIne6rSfTkdDzopZk03VKGe hw2AofR0vBy3x4NtxdAebItRFdUlx9yHIhsZvdq6glZP/b+aRHsO6T+YQ+qZQx2dMrZCGVGR ibmVUSurcZGYIoDDZmlMoqk/H8gBhAPs4OsiW0k/5JpiNrlZr4tkCZbt74WQYpqsZRGtvPwZ 5zNVAy+X0KlUwCkK/iB/X3ZP5/3Xw64xhlqt/4KkX3u85jyow0iEDQgUBdAKgnwgyjgrorDF zFS5hpFilaE0dTJ/xa2zf+kCWsVTCXHMVblApcUyc/fQEcUoFbkCC1q8V0yV2L3MjABUM7Xp BaAFSWed8o7TUYbpyNwN9IqUFSfIX+BvNzDVNv6f7IGpde6+nTbBQyV2r8+tXRTpEajYnRPv 3FpsTtvv+wtgCPDSb+93z9DI6xWNu8et0skncP8FZArEd9R0frdoI01DzYj0Mwy1AGQYteoT ZXKe6Cp9oa9KfFV7A2Jp9hnQ9kx00Wxzx6Al55wvWkzYOW18dJbz3Fe1gjWrmnFZhvfU2xVT lQsAtcvcgj118TuCKdHorjD1c4+AMk2D9XuYIeBZlQ+g1Ls0c11lLr6K1ZxKUhb4HFHBVCZR 3jC1tyIjoD5IEE1uoKqwRADBUy8pt0RddPVK6cRbdemjq/JBOYwCFL4VNZb2OtdTnGjEBMEq 5X6FBb5ToXILtnqb6LmqKEOwm+z+I7raF25f3sSSV3V4exRlhAS8vTLUhXPbo9meAnlLgnGl 4bxdczFkFnpMi8RRWRVwaoeNnpw0+rUUvJV+6+y0qsxLnoZ8lZgGkEpy57o3Bk0AsMMLiGGh NUZZLdG1AL3w1vBclzUh+V1AWqUsYbX+tYRVJOkcMwmHWXp7e4XVbg4HTEUpI1M7TpXR2jUj X8XITdnL+hWaEV1kqdKaGebLt183Z8hQ/jSQ+/l0fNgfnJsWJVRO1jNRza3uz6trpqoc80r3 jnGoFwkqf6ugbauc84swU+choC9VfrXjgob4QpXrbodWbVqr1ae2kmMuUGJw77YHnpZ3DZ0i /VTMYuqrpzVVfElmGZV3dmctViGHgy77C9hz6JJXU9meBJAK9tkPDHVHavsj34IVW0AywlMU t3s1DyYKkuDsLvXeXqWb02WvdiGQkK3aeZCq1xnHXqY7TvEAoEDSyHjnjejaL1HyuYgavtM5 AzD2q84lyugvZBjCv5IQIRevTjIOmX+SitGX/4kZ9TcCT5P9QisiT5y2VSYOmQvyMUo03h1L vd+4/vDqWGXq3WpfJZIty7DtjX3WVTHKXbvWubN5rMGbyzrLqKAd5aYGEQJCcV/zWMzF3VRH YevywzCm0WcvrHbHa2w4BDuxfJ5Ihs2v8nCIlCZFnmiX7L64MHwNpQz/NZ637QrcAulrbDPd 1q7rRxLCMS4gqbN0pW+p9NThhEIwtUFLthKE9TH1aD28OiYwRvnKqr/Uv00e+fdu+3LZqPRF vaQL9DXJxdrmKU0iJhWasOw0jsr0wRUSOKOpL/6WfFU1d9xaQ/Z7S8NnVPQUrmASvWWrvpXp ZbPd4/H00y5HdNKkV8v0Vf2foSR3XXVT/Dc83+WlaWxtiRmjfpdgoZM0BoSUSr3Tus5a31Jo DIXbnkLfXWREWZv/fhH8cdYaxGRIRQVGKi8lrBlWcE/DPEZVIAmz28ng47W1GzGB2ILgbHvd k3V24Ufn/qwiRU49TZH11bO/S7AwgsTtTdPgS8p7Cg1fRPeesJXt6asM8E8ZMclY47LC6lqs AvC+ch7J1OUYJAjudeUsTzuli/YBSaVyXgSbWzVtoqG6FEDb7e58DtjxaX85ngwSbO5BEWvH wtL2+9pW/H7zt+rxpPsmKNz92G/tgqOT/2G3sIupT0kYQyrgyjFYdhfM4Lfbzek++Hra33/b 1cVNjUL323IKAa9PbROXDRafkzjtqSUBkpMs9doUbF4SothJ4NLM9FiXE/WrzWqb6prM4bi5 19Wc6pSvynqW5TUqkrYliIC57VTXYFv1IFYJvWmlk2uzMKfO6RMoIrB2lXr5HFDdQDmRDNJ8 Gyy0V1S1KvO+Ze12LUcPB2vVw2tRW7f4YQYJft82aQGyzNzkoCWgjlbZDTg+lRD79pVj0LaV imRk5hRczO+CjnCHJuwKSE1jXeJq2CGpYNsdxMYHqkQl5rDj2hwi21wUKwK8T9rveyp/ZQpE POUxn911crXuKTE3Ny/n4F6f43O76m+yH3XpX8Q9hW05LFDqL4xr3tp36BlfS+JE/jkVNKbw o4h7niWrucQFXaeT9bog/hE/g/kCj4789726iq9uWWDn/SnDnHZ51X2TpSbLlyfCm6jK2h80 UPt5czq7iFmGoOYbDdHthz1AnmJ2PV6va1YzRWDa0L5n9IJH/rYVXV9JfBx88OvBFoShFhBy i6RvKA1wsoIy8GESzdyFlEyZrV26MvFUxP5JgvHr53OdBXoSmEqrWtk5/AkBTqUK5kWPPG2e zgf9YUcQb3521A+ZDTiUtvLtV4vJ8bILLt83l2D/FJyPj7tguzlD7/mUBl8Px+2fan7Pp93D 7nTa3b8LxG4XqE6Abzp6Z4UA6UDDBH732HqLU/mLKGz3IUQU+iCMYKWkvaU8FZ3dMckheBum 3rBn1bIzxN5nnL2PDpvz92D7ff9c3j60FIgj6nb5iYQE61K/SwcfVXjI0F4VIcr6XdfUgZ3w 3u8YKpEpBOE7BZlW3mu9Siy2xHwjzQhnRLrvoi0R5aunKFkUKxrKeTF0V9Lijl7lTrpaoEMP bdQ5v/K1BWonqb5V6uqYhUKGXToAHNSl5pK2bAfsoUXgrD03NBWAi7zn9RVzMvnX5vkZEGlF VMmZkdpo0NqyOa4c+VrpFHLdWcdo9COVVyxG4KvRAId9igSgqyXc9UpxdTVo0VJIz4xiGiT9 i4WY1027w8Pb7fHpstk/7e6VuyhDi3XGnBmrUgdkicL3pY22LjxPR+PF6Oq6rQvFmXyIrye+ 9yNaGSlkOeAuWsdYCDm6atmAiDtWkM6r9dtjyrDvmrt2ryO16E46sT//+ZY/vcVKYX25hdYH x7OxVW5QH62oj8EKdjucdKkSsuTmZdcvlW/8PgB/d1BFKdw6hz6RCVEcL1F9L6cuA3U5yC/h eflkswViIk/8D6JtuZZf8MqM1soDz1p74xzyVVGuxQSBzV/vIb5uDofdQSskeDDn17zgOHT2 RQ8Twmhxy5wsRhHK9mI1V705CEksUe86zELhZPvxXS1SYovXhVTJxRdjawGGsiVx34U3I8RY AdXxaL1+fRTmF2yLTTPMukZkWObpSKKPv3cyfJ2gPmymBSLAWTTCns6X0fVwADjEx2PrjlGW 2i2iGHvxSbPTaEkT7LMBuV5/TMKI+Ub89GVy82HgYYCTJ4mqx+C+ZpPBK8zR1VQ5g94Re5iR 8M4SjuPatzKVwlwNJh6OSkt8CpYLr9qpb1SdiPlmI9l4VIA+O0jB9EaE93agFpilOiHttlSx TX2Q8rp9YxSS1hcrnqOWIYF6LmmaLVbpXTxjnaDA9uetx8uof0FG53MzVCx4Un7W2R2pYRs8 Wt+BvWrQ3UahrpMMXh9hOpXa9/djkZTqRt0HXRhDxPoGMap6qepRgt/mgQoQt5gjxlof3vWI QPj3J91t+an7rW9TW/dMtuLpQKqXFKegtOB/zH9HQYpZ8GgKjz2wxzTwDfjrrn5rK5lnbU2U ZP3RyERdtOovyXtxkhEWq7R6DNbXnyWiLmKWuorf87as3W5BiPdhIogggGrqmz7bKym6cjyF iBxvrbtc61pV5H8DXuaoPaud36Ukcwpk8ynDEKOvrywPF0prKjyy/y7yhEr3G3ggqo8VQzkV DlFdf6gbfYdoSu9e1oJPPzmE8C5BjGJ3pPJ82jSnzsYj/UwQYnzofqlgGDxeuqNygHKtrwAh e1b3Kv0vC2zh6slAkoMO4McrzwGW6m1D2kXH2RSg6v6srrDug6+77eblvAvUp5nq8QDkGVSV 6E0T9enA7t66tSs7dgC8RTRPVW6H1z6e/tiwdbcTqteh6ULicOlznOYGWfVS11GWjHRfoCpq 5+mhJuovFFMk515FaZH5inmDm2ZGaAqwWnT6jXzVEs2RKJu5VUmLDJsNKdE8833BYIupnevr IvJ/k+Zopg55Vk227AqFV6OrdRGm9ufvFrEsVjcVXIsFfsAz8TBn7K51uY3Fx/FITAZWNUJD ZcgInd4h7Mdc5Bkp1CGiuKcmPyNzcBt47o8vc3o9GQ2X14OBmkV/TRdzgJPE+/2i5qv//0KW Wh4ApaH4+GEwQvYXk1TEo4+DwdhehqGNfNmxIImAeACZfzyC3N9yuiVjOh/e3HjoevCPA6vi OWf4enxllYRCMbz+4EA25elAixBp07Hnu+FqiFa6vVZf2a0LEUbEZ9d4ZH9UBaEFTq0FJ5rN 1BzY6NHE/wK65l95Rim5MZkhbL2hKskMra8/3Fx16B/HeH3toa7Xky6ZhrL48HGeErHu8AgZ DjTubuCIu9DyrfXfm3NAn86X08uj/uLz/H1zAkd6USViJRccFH4BB7vdP6s/3YfY/3Fr6yCq d6dIldpSnwUTPHcgeK5e2nq3IV2mCPIgrxdxfIapMmFBq9JGB0IqpnrEYF1GIRrq/8GO/e2g kqr/7wINulA9+ybhG9LSQ19u74sgpc906y0SgylM3Rc3iqbeN9oXa2KaNu7cPFoihATD8f8z 9iVdctvIun+lzl284170a87DohdMkplJF6cimZksbXjKVtnW6bKkU5Lfdf/7FwFwwBBgamGX Mr4PIGYEgEAg9h5+On56f73Bf//QSwWvEt6KeTZazI/2QvK4P3/967te0sJ2fnvRz87PL+8f +e2AfzUPGESyNemk7ODPqSwObS+NGVzeJfSVEY7OjQ9C7pAArZQ7SWo0XarGIeMtnbimbGH8 b3tSqWUMWE97xcQDSwAuTWX5RSmXU1LlyoXWWTLVve9HhLyUBgqqDtZ6p2qVVyt0/RfQr96p c9NhoI4PMOFJyc1RRa26aCvCCw+T4gJ8km3cuDxhWyFogkAiaJysuFtBED5dMH8+A97nJ51M MF5fKLH2fXFURMxFVNboH2E3rxRnNSL+mMKsKa5f5jUNyhmBg5v2BAs7vDcl4vSJmRA7KKdo uQuS+1TWoChDHJ6uwyAma4vgoBWnMNffZjN7QsSdRxSN4hZiww+J59pEejYGPwGnQ3Otez94 NU5dfUqpxLG9JApgu0gkIG5hbeJ8fK6bnkKwQin5Y/7cD4q7og1N06Ez7IFvpLFozzDSmSx8 oMipWSaF/1q6qkQx46ELPmWpMstNMUMIyVpEEE5p51tEVKjFM2wnTqQwpVyPGaECJHUu3ZwS 0PpybQYVJGK7QgHgZtf4TKR/cN0PreOZEXUxouHKikTUaMtnk4HGUjXdpR+EC4WkLqKP0nyy dlJ93pfMfLCQDk3SZegSUBbzeyqKjHnQuMrC6jIumkf119t3UAlf/4aU4MfZ4RalJWCldgc+ 7UGkZZnXJ3KY5vEvW7ealH9bEZdD6rlWoANtmsS+Z5uAv6UxfoFgNTZ0BtuFmdPl1PoF0SwX 4tC/W5Vj2paZOE3vFqEYfjZ1Q4dPcsR9JU+7WNblqZFcjyxCyPiqNcLHVh0BLYColgOr2NE/ Z44YiDvXevgFjYbmk+Cf/vzy7fvbfx9e//zl9eNHWDr8a2b988vnf+IR8T+01sBUN0Mp8hlK rZ1kiKnpg0HjWCQq/5BWTuT6xpo8oMKtev/SGI9NTY+7jNClVT9Q929Y74F60Q4hWCvhR0jG NoQ+mpj1pTokK3BfJqQFoEJbjju0mIpTkTZl0xmiyKv86qiB+PxHLZUR1fst6/KLk8+flwuG UpTomLCE0c9gG8kpvam4iuokfxHVgLJVxmgGNK1LnlUiuB7QSUEe8wr6qyEIqP/Oo9LJZW2C iYbAl5UaLg0DxzaPMtcANCH6AJbhIz2JsEmQK5aGRDfYpno1OQ3tM4BBN2UggzHE2KTa2pzm djR3JL4TZuwSDMZzUvV7XVGQzvsQenS1Uu/d1PFsSv1g6HmqYNgUnRgxcVENudaY+tbgHI+B 9HKTQ6CIHumtqA0PTUm81AEsRZxboaTxuX66gKqu9S12tmr8GEOnQ1uZKv9Sg+YpuWETpdNR luOVbHYcpKbiVlEnCYjwTT6VP5amMWks21jvTV2aSAHm6z6gIH1+ecNJ618wScJ89fLx5SvT mmQvIs33P/jsO9OEqU2dt+YZ3JC6Y6+1UH3dsq3CTTOwVLM4xiuVXTJHrGwjUGuWDMPDKTyk Ms4NaExOTy6IoKZgbDOcYjIlFlXQ9ZOuoIGmWd2jZLPJXNYxN1m8bbZcUwGhd9kKWHQg50wO IdI6BdcnyoUcFKnJYbJ8vRiIKn318g0bT7paCAkGXNLppK7cEDArfzOni12PGsMZOJzDWCoi FqJKsmRyQ4NXJh5QMQzS0QnGkYw+UmGcsWB/QX+XLkGibFa4SGEiKu6zHK3ASeF07rUqQ13s SZcWwyGplaqcDTdI4ZI9tfTSsu1D2zaV+KZNqQGh2WakM68ZnG9FqGEOA6XLspJtY1ce4VB6 JPUfjpSgiRBZQoCoTInDztcfL3WbG/YgxEP46UqrT8uB/LHMR62GVP0XZaCywd+jKUegwMlx /KwOVSgs2yjy7KkbaP19KQFzU0Y009LLNDj8V6oZHayQetgpcpi2Z/giV/qU7w2Ps/2GWJot 2/i/EFKqpkF5HoonPMU0fLiBqb4Q3d0xIVobemoXHAqimyEVHbU9KuJOvbuNHqqK1CX30hds 6p+0HIBuSJsRIghLtEfV5EmUY9s0BSVK6+liskIh1UwEQG9EfdxY631qR0UfWIZzCGSAbtkX zXGHYEgUhDxrFcLdLGrJZJN/NTi0+s8obZcpUYFkSjL1A/J+6SpaGof83QHbnmf6JB6CKFGh GquIBA1W7B5jofVDprU6tsVGN2OBMpZt05r2Fo0FrcdgfS6R8KqQnDRdN0bpiEeKimjRcUVZ 2SqCIa/7BP4c21Oi5vgDFA4reWNmkFG102mXlFS6LR5TbIQ9KGL3jtXDZSSDLv7sZuVIPOdj bauQtg9ZiZZ54IyWUvuylrs15tlhDtHM+2dQ2CrK35o406rmU/NlRiG+ik9wbhCShhKIVz2M uxW7hCg++yEeJ8EPaWOVH4PCpC3bk2/it0941C551MTz6HNCrXzaVnYw3vZGHx710M50fkWv 7Zdv6Rt8GE9aMs+Nj+z0ZsuPAM0z+Brd/B7Rl3cxRo4OLXwM743pn4Jk2X4Ucbf5q0ujJd78 M3Ne0J6f0Z0Nek+s8wFfusELL6wR9ENS4Y2Yh+9fILt4be0VlnMf2UU5WOOxz377v6Jdg56a NTHq/uxyyXQGJu6SXyiNopZ2ngU+busuvsTkEPgv+hMSMHtIWpO01fKcGNz3hCqgB7KVRBoa LOihsiPR+nyRZ0nkW1N7aTMdK1uY1ETtYAGqtHXc3orkkwUNleYsFaXyuUznu/nsoQmU1J7n Shht3xqp+NsC/ZmdyUPENfRQHcnAVTKGoLzRS6v1C0lZJfTG3EKZzf13ktCkedkMZBpW39A9 9sm9OG5kS+p9w9pwJYSkL94VjmXvvWvj4yfKpztNdGbRO/IqK9hrzrimtKm2uS1BtYjZ2tKm LwVLHOcHOP4PcAJaG5Q5P5KeOyR2hjHdaRHp86m+9JM0ii2YfDV1k7b3Iq17xxRjOwNE/brh fiM85B3oS9Ph5KWkJ+HlG3ybW/84rCVIoePTwwIgIaUur92ur8iMtE+RFVBKr8SIPD0xRfvk WXZMxVrcjZUxQs8QOLDuNHHITeQ4e70LGUFAdnSE4mC/+qqsAgq1gS0xbJ+YHSD6MSQKjH3X DoxJ8t27eY7De3mOY9OX48AERDrwlPaeRVYPW14yhRKVyd0Ucyp6Nr9L7dPQju4M62no3KVE EMteN+izircKXR555IjbZ6O/P9j3VWDb9ymkZe5GiGyfbK3Y0v072a5gttinlGgdjweK2vqn A0X428u3h6+fPv/6/f2NOjJYdRvQ/nryJuOakvPUHgl9isuVg1UBRN1T22Rbx7bjfIq7r7YA q4uSMIzjvYLeaEQ/EeIg2siKhuSgtwW+o1+tvDt1JhDpM1Y9YdEP5dzdy7m9BwZkFxHwH81R QG0c6zRnLzER2V82/M4MvRGTHyR6P8Zzk72Zr/uQ2FS6Qb7fwLsPJ4c+9tATSu4C6LT92vSo DVCdtdeaPHIK2eD0R0s+/6H24tFFu+GHvWi6D7UxeH8OHcu9kwYkBYZhhWHGcQPQkLziopEM PQIx1/zp0A/NWEQoMStGqisz6v5Ax2GJ/oGCCx1j6kd+H2hxVGKYr/TPcyOf/ZkTTSkMW+IC x7htvnJw+7lP4yjYXXnO29F6cG5O4cT3Ah89ug3N9hZesJ9KzgrufubMezUdQdXaBns0leaH u7ShmIqGPWe1S1t2qDXNpXr9+OlleP0PobrMUeT46qRkAr0qvgbhdCU6GMrbpCt6CnJCixw1 2DHZHY0eKXuVUQ2R7VJLDJA7RI/G1NhkBoKQnroRCfeTEMBMaszg/pSF6Qx2F1FACIkJBOUR 2QQRie9/Nd5voUBxg7sU397vT1A2bqy08dVfp6FtajlF82hiqQ/rr7Ck94CGqr2GJgOJdfB7 uhT4ZFxxoazqUdWWXv+eBeyeJt7pnV9N9+31HbjmqKjvS5Cie1LPNflusLrvssLMmtLkJJZb V0sHLqtoutqKVHuMl0lxn9O1NgNv7njgz5evX18/PrBkaUMFCxei60LZAySTc1sXMYdczHb5 zFlc/AEYNqA4Z7aCEWUdBDzkXfeMhhRjq6CLPa+WHATGU79jDsxpurmvTNhzGcIJhJmJzMhu Jp+TDM6LHdNDzjC12uk44B9LdPYvtgTRqFOCO3V5ycQGk1yOlbdMC1A09NY+A8vmVKRX0mEx g9fDCCWY0f8Qb82HKOjDUW3jef2BTwJyZFWbRiajW04wG+1yfNxpPIrJrgixs8WlZrVkKXaz UnNPk07jdxltesbBvUMWProkVeJnDgyHzeGyQ9MeepTRRq+svsZDReXyhELZbdowwE7jLaEu IS4DYyqaXzOh4l1ok9myhs6B3osM0wPDKY1KZlwLTMNAH8Izxoj9beqpWwMcV8wFuLBs9UG0 yqaj6rVG6nHZ4Dqeq7Ro2S82NbSvVz2Y9PXvry+fP+pDfpK1vh9FerK43Oj1YCbVO23wdJto I1thjlJHMSZ1tL7OpbIjCN6t8A6Qq/Jn6cxXOiJi5P7ADB8jXxtshrZInUgbc6GhLYdpguWs Ut58Cj5mP1APjqXXQ1d8MF1e4dNZFlq+Q218zTDk1q5uqjqRJbEl+nvYhL6WBuP9iXn0jkKt BlS1bq1GPH4lxb4q5uew+vhTOpHBeHseXqo2V+spdf0o1iu1D/xYr1QuVstmeKpGaqy5lYFl 2BhjhFsVuaRF6opqOb8txxhbN9ebz2q8s9usQKOzxS2ZpcBdO7bJXmapGmaVuq5kdsArp+ib vlOHNxiOPdl7CY+CedMmxy8iAyxj10/v3/96eVOVVaVvnE4wD6H3750JG6bKy84gtWPZT6Zh yTBznc5SZP/zfz/Npv+b+dT6kZs9G6VPWe94Eb1y20gm5UOMxr5RyuHGUBW9DelPtFcMIgti 1vq3l/8n+vmBCGe7rnMuKpqrvJf8Va1iLAHLNwGRkmYRYm/dGN4GkKi2a46FXsxKHHKnTmRE lm/8gEuPAjKHVjxlDr1rInOoAV9k+KJ3HxGQHFjKgE0DUS6fhMqYTW8AyE1HWJ+zp2/Z+6fU vghD8fGhUnZkJsh1ozmaZnK+1WYJJ265hZEvih1/FW9ZZYM3exDQMIjMDBaSqhI2vqvfYy9A aB9Ds8ETXg4GVcAiD4gOyQDd+HlK0iGKPV9aAi9YenMsw2nsQsHKNpxUiZSIUpIkgtBgJLmj y3vRp96SU0lYJXWiCZfghyc0hx6NgGzGpoLn7IkqqgXOhukCrQJqBb2h7WUa9CPXoqLi6tR+ UOWAe0Gg8dmhRbq/VihEsTLEEafypWxZm5Yn4wVCjc2htiUXgjqDbHGyKiJbzhr54AaG89qN knp2YDjME9Jve364l8wsn980ZdzAD8hSUHRLGRHPgheEm21Uh4MOQYvxbJ8obQbEFlVoCDmG owCRExpOFQSOD9/eKQ9kRMZE+LHBekTkBOQ2zNpfq4PrhXrumcpsxUQpM8SxQ73lnpLLKcem 4MSeTfWLU1Nmx6KnV8YLqRt8yzBfLknoBhgqKZOINVepE7q2nvZL2tuW5ZDFmcVx7FPH3GzW 2eJiP0HJzFTRfHuTbxxz/5Mv30HF1HdmV6d9GaRSUOUFuWeUR5S8si1HKnIZopuhzKHMsGRG bPiya/yyTXZ2gRGDEkfFOoSjbQBcE+CZAUMCATIYg0oc+gKCxPDJD5wH8k77iqPJJZHkPp2v o+kxjsV0TOq9yxVrJLOrDlU+jC0ZNb6c1F5N7tg4J+uDXa+V6GFSuke3yNlUCkWVUl/mWxS7 H8YHDUeqwy+EI9ra+Uf90whEzvFEIb4b+r0OVKnthpFrSu6p9O2op3QKgeFYsnHqCoGWRl5K 3XBHTxE/JUhqHTkX58CW9ZcFKg5VktOu1AVKmxtuzy2UIaLnuYXwc0oa1SwwqMSd7ThEM8fn pED1IAA2gZA9ikMhqoa7iVp4hkumIismC49D+2MD03kMepHIcey9lssYDlHpDDAWg+cY1H2Z Q15mXto5qFg2PTQiRKqTIiGwAp/oPYjYxFTBgICYvRCQz+MFxAVdeL8aOMmwUhdIgXJERDFc Ot1B4BEVxADKRy8D4pAEIKl0i6vS1rUMh1irV+A08A33JhdG2ztuFOxHU3WhT5t+bZNaqlx1 X1pVFeyFKytqQgOpS0qJ5gNSouBAGtHJIVe0Akx+OCI/HJFtsKwMxq8CYW8ABNg1xOs7Lnk3 V2R4xHTKAXJkaNModEmLLZHhOWRW6yHl+39FP5DOp1ZiOkBPJrOFUBjuz+bACSNrr9C0OyQr 0CeuQ/afJk2nNlJnBi3zx8iPZeOmSnGZoga5VfTUK5o0LEsEXXEhjjZ00mFQfRtrjK7am8l6 0DSJNg1iWo8EwP17/4vnwft7/4sppelVOYzFRA/OQaviBwk64NgW2ZYACnDray8ZVZ96YUWk ZEFihywAhh4UWyeVNAx96JNxVwE198GwaTtRFtFrtD6MHBMQEl9JIPsRpU4XdeJYMZUtREzu EDaK6+zOhEMq32Ja5ecqJV2EroSqtS1iomRysoYZQu17CwTPIpswIvemy6r1bXonYaFcB9ux 92O5RW4YuqRjfIER2cRiC4HYCDgmgOglTE6O+BzBIQqN5PZTWYaRPxArHg4FNbFKAihwwjOx suJITkJsB51MrXavZyaweScR3cFyAXvKHOYj/qyGguVV3p3yOn1enUBPzPh2qqRHkha66fhg wcXXZBYZvqTEHtUZuqIlkrA8Sn9qrpDUvJ1uRS976yWIx6To+IPLZMujgrBXtWEZTDrRXgLI ceuJVRNJwOi1aZJdN4nwlgxpD629LCwyQ1l+PXb5E8XRavSCDxfJk+kCohkjtT+HbpC09oPe JjfhGheIo6raTe2ju5PQxeCBivup6Qoyk1s3YA9f7jIudVTsMlbvOruk9M53GAH6DpnXrSiK 7vHWNNlOgWTNcmosF8bs9mwnYBJbgaNXHJqmb8L5sYPvr2/oWeL9z5c31UlgksIiv6gH17NG grMeX+7zNg/81Kf4o+XvX14+/vrlT/Ijc+Lxnnto2zvZnm/CU0U2m7HuBwYVWC8zlPedFOfy hLgp0YYHSnbyNhTsCXuyvRifLCE/27/8+e2vz7/vfYzfdNn9mCmW+emnIisSSNDv7y+7mWKe NiFf7Ev0cLw649ztK4zmwsDA5zoyybupYsl6+uvlDaprt5Gx0yz2GfIjxiiW1rK6CSXaILv2 s5fN5R0GStPoDzAR931xEF21glT6MfVZ0ZwbdlxOcFdYlmZdcd2OMbdmnxCxoFjqV0hjX+wb anXI8PkDlTTL8w8sz6CKQv1tVDGWU5WkU1rR709KRNqOnlNmZ5ibR/ff/vr8K3tWXnu5eRk7 j9prwSARbAsEKX8D5dTybW6R3ruhvC24SB3y+iRzwLTaOopBksGJQktzaMqwIbZBm0jIp+w4 AZ1eoutC+SXTFTqXqbxBjxAUnB9b9MO3CAumk3JyxtaxRsPuARJU68dNpr46ICAmn1+smvA2 DLkzvKLyXZlVHNG7Kytu2K/acMNTxqySi5S82Yh1zEwlRL8ei1A0OsVY5uMexSGdgJiLWTdX XaSGg7oVppI9g4qVBkrR0vsRlv8utRZhBD7/MCcDauBTMuToA6ufTqRnR9YCUtuVrFsEIVUy C2Q62WCc1lEu18nwCOntoDubkjQ6oHb0Wn/nD+Kx6lRTNUN9S+4+zQzfH7XA5yHF1wuV1iTB kFPTxhhGXDz1gWPqx9x8Wc5GFLVVZFmUUGtQTByQbjV49+WGKmp3V22dN6lPSqOAkorr+1Ua ebo0ii09CWjVpg83IFav7Wk47X+G4UNAbxovoHw8w6R5fXRs09NI+Qf2lgflz5MNQ4ipMdbD SL4niFiXDxeV36ZHH7q9qd9DBWv9b/XxosbVDV5EvoHEQTRI0YKk/uBHdPNm+GNE7mwxrPaH QNwkZInLU2Lu7gsvDEZyCqX2lkW48kXL71WkP7+NyONzBE2emt8ZnKJZ3VJ0ywrvMPqWRaV5 ttfnuv5Qffr1/Qt7Hfb9y+dPv357YDhbab3/9gJqTKbZxyBBtv/jomXgXFYAPx63ovmgs/4u VfQK9ZoSygb0zum6MMQNfZroCkfZurFnaoNolRdFWoRldZFl+r0INLKyLZ/eyuW2WaRpCYfC UU0ml0eUjc8Gx8ogplt6LRlY7ofI3+CAb7iFLMRoHokYIQpMA7N+v0OQOrRUbkcSQszDgMEk YrDpHm6lZ7mW5iF+g/HiCNlZb6XthK4pJGssleu7yiSw3XKRE8kurhgLsWzSc52cSI+lTMvj F5A0HZiLd7SzhUGUG9MsDS+5svxXvm1ww7zAZIPmIM5ucsncFC9fs8xTFYB1K1qT6e1ilksO Mhe5OsHPVuBUHJK/Mj4e3rxITUTXnCu86SX78hQRvAOmzTprKIM3RIEES52xulDvIs6DtOtA h1X8y24QAzTdtx9wEjBNlZqbTlYkaaa+maAsBVMn0BdfEufxnGQJGknQN1/5KhcN7XFGys3x sK0TpidSc3PHbrq0ZAfGVxfLqbIt43uQrOj76rKbEUbQ1oXim2OmRf6ayPyEe+Tyc02r0Oh/ eGMcizHPpmtTDtz8iogEr1BdkhLtDPtLRV6D2Mh4JsCOBFb61pw2FqjcJxjYDZCsuW8Qbl1E sp8PGcR9jd3UJZnvxpEhghr+UEqqQOF7GIbwbKdkN/zWw4nw63bEbhSLtqxXtbL2VhBDqeGC mDz/lSiObcgzw/aDH5Pad33T9xkaGQzXN5rR1cZG4avTHyJdfXKlL9F8n2ydRV/GrmXIDICB E9r0Zd6NBnN74FJKjUABRTK06a8wjJ48RVIUkgtmmeKSmWSKmyGPXIu993Wuqux/HjhBGFDf F1bcROSI+qTyKnGU1bmK+SYsCrzYCAWGfoBgFNPrP5kVk05XFY5jKHwG+vfqnrFCahmiFkJk Kn5lY0LBIvnShIqSlwcE0ry5JS8VZTyU7clkMDLsWYqs1oYavktrfc/gAkkkRZFP77PJpIBW akTSUxiTJvMCZwhc2yaLBRHfhDim8hpUN9g0hW7ygESmFq/5htIo60JWRw6FvMIVoDSBWfze fNAeo9HgAUQkXT7k9n3aFeYfcsNL4UTkkMGgmISYftm11ZnO6nwPLUPKnTSuTol/hHfpD9PV +IDxyhVNFofmkp77tMvzGjRwfIVotzi0LSsBguUGnV3cViPN90SKurkmYoFtsHKXSI5H7ziI pCfHdunVqciqroaXBKSogvDugNw7VZvcyTpyerrn934VhUFIQsvVNuqr5QlW2eRTAQKJre4O TSO/q6cSrl1+PFyOZkJ7M4Rmi93pWlWpIZXPkW0F+1o7cCLHM6jNDAwpS66NM7S9bweuYdbC HSCH3vKWSTCjkJMitc+movEPRG+7pP6u77ypmEeqccL+mClZoPzvr+a015OEZSGaGFKAussi I74hPXy/5k5P4hsqPzIIlsmhOFDem1JtZx0ldTMUx0K+r1/lWZEwFD0ONB19HY6zCAbb8D69 v3z9A7ei9Xe7q3Eq2svVVVKTiR434Ad/NjM7FJS0V6RZOyWXceJPja9JFJD5rXiiXBiJXVqt lARwaZ+XR/RrIGOPVT+/eU6FgY9W/QCzS9uUzekZ6uioJex4QMeHq6kfWcbIK5skm6Css+lY dBU+8mikwmdT8vQIwRM+R4UmIESqMTcmDMP15wr+T6F9emYXLFenXK+ff/3y8fX94cv7wx+v b1/hX/jCunCsgaHY++Pn0LICOTb+oHEpefZZ5PiG4wDr7jgad0Bf81plShA3m+uqeYdJsi3C aM9ZmdIHs6wZJiU0w6JvS9LhGyvUBrpIIiZH/Joc3WN1oGKTONeT4SIjA6EKDengh/hLHaXd kCq1MT+a7rkuNN9UPPvZUOh3ozxKCBjac2kjQM7L/Rt7L+vw/unj76/kd/XOPMvPmfwYmpSY VPte/9cv/9RMgYQwJ9HSXJAXbWv4yrGoTJ1pZnTNMO9B6lifJqWxxGiTCSQwk9TstuReRcpr po0k3NXTdGovhjjbpM5XM9Ls07evby//fWhfPr++aa2eUafkMEzPlmuNoxWE9LaOQMYkLG9r 3+P2l376YFkwNlZ+60/14Pp+TK2btzCHJp/OBS7unTDO1MxvnOFqW/btUk11Sa9tN3qGj9mZ OxMnYVHvJqwvqlZ+TXzD8rLIkukxc/3BNvhx2MjHvBiLenqE9MP06BwSwwpeCvGMNurHZyu0 HC8rnCBxLeoQfAtTlMWQP8Kf2HUcOtUrpYhdj9LbSWoU2akhvrpuSph985+hMdWUsqtzWyuM P6SJ3PY55eesmMoBclzllm/Jr31trPmUZOgtw3JaoBb1aR52oa6sOMwsWskSWkWeZJjxcniE +M+u7QW3Hw8CqT5ndkQ6BxcaVlL1F6jdMost0TOEECWAB8v1n8SbRjJ88nzxwukG1qj2lZHl RedStnAUOM01wSSz/mnfK0aBHQShc2/AEOixZdiH2tgVPh88TlWZHC0/vOX+frtsyqLKxwnm bvxnfYGO1VCl0HRFj252zlMz4LlLTLa4ps/wP+iYg+NH4eS74s2hjQf/T/qmLtLpeh1t62i5 Xm2RNWfYfaCroUueswJGtK4KQjvez7jAjRzDt5v60EzdAXpQ5hp6z9L2kqFOXHdMDVsBeoDs EJo8xenkPsjsIPtxdu6eDa+okOzA/dkaybvdBnpFlpdCUU/8zcTMcJOVDBFFiTXBT8938iO5 W0IHS5I7Vdg3R4iQWn8L3Lx4bCbPvV2P9skQHSyd2ql8gk7Q2f14L4Wc3VtueA2zm2h8RZA8 d7DL3EAqBmiw0PX7IVTeYjCR7k20EjuKr/foTY0+6UbP8ZJH6oRUp/qBnzxWdFqHrJmGEjrf rT+TB3ECtQVqZjnRAEMUWTozw3OrIU8MhcM47cm+O4AP3aV8npWxcLo9jaf9ufpa9LBkbUYc bGInjunP3wpYTpyLtp9u6KaSPqPc6DBStzk027FtLd9PHfWsb15EKfqrmLhDV2SnnCqtFZFU 4M1AjlyfpFm9rE6k5GKemjqfirQOTPdmOQ8aG9pL4FJ3RwlMO1gRwKSc1GMYGM4Y2fJ+1lRA VDP/cDt7BjBnwlxQDlFsO7TDfpkXBzsZkWkXgytXthYfoFiGIKDP1llcoFVDDqBlKPs6+Snh jaUfsnbEg7JTPh0i37q60/Gm1kF9K9etIMOXcE+gHWrXC7TBvUuyfGr7KHA09WmFPG107Qsc QYqIdv/EGUVsOaMesIgdw8Y7x3EhMTdSQ9TDuajximEauFCEtuV46leGpj8Xh4Sby4UBtcFJ 0O5FQ9tTE0Rzu5WJIXXbg9FAITq2nq2VO165qwMfatpgaayQzBolfqLNbKe3yDsnSAFFDl97 GLE3Bq7ny+1DREPJZk1CM21LQQoYkE9GLntZSXYNfV0xFyB1l08eTXDUqs5ZG/meaWFN7i/M Qoxc3LQyD5ZSwiut1eNGL/anssQV9+5WGbumfNWW0iguM/PwhTgm2RQrf81ai5WLcRPaEPDq qltFoAxfi6sa0yzeu96LI9uoLBlAcDwoLadL29NFHzdwXMg6ys0anlUi5zxGrh8K6V0AXJk7 skGFCCnre5LjkdYmC6MqQD9xnwbqC13eJq3BoerCAR3MN/RVgRK6PmV4xwbr0rYV3Qgakbb2 gQWhsrZbXvE+am22SjPzFtZQZL1pR6jE6evZsNDM64Ht8U9Pl6J77NXkHWDtVmfsfh9TT47v L3++Pvzy12+/vb4/ZOvu9BzmeJjSKkO/cVs8IGMHOc+iSPj3fHDAjhGkUCn8dyzKsgN9QgPS pn2GUIkGQIGe8kNZyEH6556OCwEyLgTouI5NlxenesrrrEikxTGAh2Y4zwhZV0iBPzpjw+F7 A8y4a/RKLhrx+isIs/wIS3ZoMuK9W/xMkj6WxeksJ74C7WY+LOmVpOMWKWYWGrhknqrX+x8v 7x//9+WduN6KlTA/1KTEDuOhqUBggDFB8C/VjaYI50d6LQvQ6UB3FoDaa0ev1wFrQM3Hsz+q L2EN2JlyaxDTj7ddlezeKtAOaaMHTMGY2AalBMOa7GMwAWeowgPUFO4iGYttoP1wYHg3lZuU m87ngl1+Qlcqcs9VrihhPR6q6TQOni8OZVjes+dgpRyyJDK4OwJwNmKmU1rluB5uKjlBh65J sv6c50o31ra7UdhDZZGmfVjRVdI6UhxMshys8qNjAq8veDza/9vVQ/bou6mgAmW92tm2IGbP +jrtSNsPyUTDlWaJdIVWvlMujMMVrqZSHKfNHG/lmOPxVw5dJuhJwIBIB28SUhX1dEwfJxjB pjZ9/LdFx1zmeTslR3yBAzPLXz9YZjHkHQ98mc7OAOcDQf2i2xopDgsZRNa0iRtQDWchrOsE I2HR8glOuiyfp+xakE1mY6hlv8flKj6oIHuVznWCrKVKvhXOpsh0tfPmfnsG7QxWyssRALlP crf8tw9UVcsUdDIeUhvhrmBefv3P26ff//j+8H8e8Kx8vqqhWXzgXnxaJqyDXQvZaRJipXe0 YD3rDOSOLWNUPaiap6P4yAqTD1fXt56uspRrvqMuVJwmonjIGsej9GsEr6eT47lO4slR6S8R ojSpejeIjycr0PJX9TDCPx4N25NI4Vq8IRkNWpo5oueKVe9Qy1XDuZcI1UnEhj8OmeNTxb5R 1it5RHDuDWE3uHo/Y0MIk+8NZMZMtzKnzjQ3lmpyJWRc9cUhQVEUmKGQhtY7MFQJcae5RD4W I7bdbKzORjREcfWyffIKmQvlZ/c29JAFNjkpC5/s0jGtazr8fAWMbK5CGtQ3UhdvS/vjwpKW a5HljaIrz5A8ncGo2si/JnayB1paLd3hFqDrKbGpxatAScvL4DjSc2Sa1doSrG8utWR60NdU w0QL5OacFtr6Yg2HDMJmbh2IBc2xvXV9/jTllHDVxbaA06Fs0kdChLN5A6UbiQN+yt7q0ZYg APyrz/6F3ocezl++fX9Iv3z+/v7l7U2at6V4TFftEOszKAwx+6sQBtHhSFtgbBxQnO8x0JWc kVPlPSy6T4ZLlyuhGllshjwIHMVjAILNaHDeAyDOwNO5V8NkybWoU9KVCOar1QvMNaUN1yD6 Pc0ZMNcJVSUFW/lmVbJb5AW7AdrV6JdRoQpE3XqW5fum/uaNQJMeygssOnPJtQlHVlM2WXwu 3DCO0qsjm4TM6KPBPQXm6Ix/CvJ2MOYDcxzA2liLtr/Uo6kG0yei0Z/7JwN9doWntazh0Zjs 5kav1qu8Qh+h1GNydX7D8VooO/zF1QdKNmmevQSsupTwmaYk3WMz3qHDGaLOcWlyQ+Pb+rSZ ieK8oe1qsGBJ7VqOHyfad5MO2gOtPTEYHSQbtCuWnLQKXMNd8Y1A3hfi2ZYvn3JZZ1m2Z9ue lti8tNGzPH0FgTGYSmVpAZmYOrfZUFdJBaoeolv+VRhLCjBK9etSTAyji+MZ9g94RptDUoJC djHs9oikLqGaOWPImgxPJ7oN8Qih7+hl0/q0R7MF9dnVOnUlvaLkgeSGauUKwkAr1zbyZUOE RaxcDVVQSdlkQvZYr6/W0CyligqhwFUDLL4ahmS4qN1Yv3PAxLrGruOGiz0zntqO11sG/2uM s15JMA4PmaPcpeRFNbh+TK4BWSfXXxLm7ZrfmzQFq3u1Gut8GA/FSZEOaYKXWbTohzL1Y9vc 9PRrtWtv9f9WhM0gnU4wWdG79rF0bdnBiQjRT8jzzstdEh3KIdVH14ffvrw//PL26fN/frL/ 8QCa50N3OjzMWvtf+CjtQ//19ddPL28P52Idkh9+gh/suPlU/UNU9njNge78SK6XWXIW30Fy IOZ9zNhBqnKEBqOUCrpTUESgGU2H5yHXa4g5E5o7v7lVFq3BPI3X10nKFd+Qf3v59gfbOxm+ vP/6x97ElQy2E6tVC8u6QPI4yaS45A5iovXDqG2RLyoL7SzWB/AON4r3euMQ+YaHM3m5nirX lp9pXBvS8P7p99/17A4wvZ+kFZsonhRvKhLWgFJwbgYDWg2ZATmDoj8c8sQUUjyKUZrHzEhb 2m2KRErSobgWA3VQLfFU92ESuLgsl1sjK9RPX7+//PL2+u3hOy/ZrSvWr99/+/T2He+nfPn8 26ffH37CCvj+8v7763e9H65F3SV1jweM97OWJlArlF2XxGoT5chcQfF5wp1OtpbjJTN4rkjS NEdftWhAThVzDjOMcDawhuuGlKuf1AksuhrFLTD5bsQq1Rep3A6sSvTz1aR/rmEBNcLinbm8 R+WVWfjdiiEVHOBCYKCcpHNYlK1eY3i4XkZF7/qgMKF/1Ko/ZeIJNT5vh4sraWsGXVsfEtCv CtLIH2L++YMnPYGMsj6x7VGVod83QXQTP7jUQRu7+H6s7EH42JdQOxXVhIoKVh9ZOkkZ4c6C CpCJ97lmadPiy4cC+9GVQ1fpkX1NWhgVJQwBlwE3iEwL1YUy7qxl26ml84HQoH70Oo0GWzt0 NkpHVB/a41yuW5b4lWEl+lVYXaixn8OVGggdVNNfnvV5rQkxz9yONSXtQQ2pcGyLVY3BMqPS gs/Q6lC7Uj+9IlqdzITxhK5olTyOMELU4/ThuX7C8wm1xrZKGB5heW2oT8DSJyVitrUMOSRj Y+AZG+1UnSpqa2djSIPNzbx50h9N7a2DfPdJr7WJM0pymNR6yh6Q3xGTeuwSEe4vqsXffTBt 1oDmpHYxNkhVpNPSgTVnZq4KY5F0tY136lLJ5DrIpm+f0A8+MchK/QN+KDdt1zGWjXyLigvi w+X48OUreggTPWZipMdC8qV+Y1KpNc7BqZri0FThcw7comaPZtr6nOHl5rA6KSEG6kxLHzQv gZ/7Y89WdrR/e6UM1oK9jLOp3VYGePe5TMWXejMP54ptuSzLhbG6wqpKi2Li4cUzK4eaiPkJ Jd/vwZ3TXnrbsp3v6jXDiv3P/2yRzumENQZMk3T9iBTKtEfAFX/1F3FJDT+gR3ZXfPuj6J5k IMO7zhTQdhdxs+x6FKPEX9BkCihSyY6PyZcTQyLFDK9AT5ECgQ4xcef4VCnzC5/Ct/kF0Cqv L2osID4kZdkYFkZLSHq7+MqeC9Ci5Y8IpIY7Lhxmg8R8/jEbx+mHDei29tuX374/nP/79fX9 n9eH3/96/fZdOEDefALeoS4pPnX580HcCknxEra0G8slxr67wlyFZ12x+IB+0v/tWF60Q4MF msi0tE9WRZ/u1OrMKvrlXQQtG1ObltI5oSCW7cFFgDaxFBjkXZQNj2yHjjoy3N0TGdSqf8Ur l052UrUllFTROJaF5bH3Fc5tU8cNVKqBGLhI1AoROkIknx+IALUru7SBJLWoEsqS3g4qattx I1jRnBYy8G5QyVekEMogDzzxqugiH5zI0tsTimUDdBGgXusUcd8UkDqQFnBxw3oRV6D8ikv+ WX4sfVvPTQIjGfxnO1NEYkXRNZMdEMkrsDUWjvVI628zKw1gbj2RI+XSw9s0oFt09mS6hzMz aiANEyjfhkvLMm0nDYxRidODAthBRmFlcmhTsmdAR00ycgiosoR0pLMRqISA+CLvnizFh+dK T9RO7kzofSfQoosc36OEVDtE8bQ/oDzyv2VBOtEReq6xEClgoCukay5oCkyklCmO5HowOSkh ZhH3yKPNssnnj+9fPn2UHgGbRUqcoJklndA2Tv10bE8J6muCIlQXoJriU/RSfkCPnNLycRrL Gi0rHm8fOqnJoMHskd6kmudsphd2Db0qWziUCxyFothjr+LmRAmbFjcOdYQ9paiLu+SmC6/F oZPdgKxZYje6sqk9P+ugfMqzSCVf2otwNj1QpbKpwCJOuvRMFRDuITGbG9nv0vIU2zU9F4LC y35OqaKYSmRQG0nD4rbwxHNKWMfjFhNW3lHq9eyMH1OsOGbacjTbO5OKPjSVfFWspSXWfJ/S cERelgneXN1RyZsSBsKxscWXuc9oEQXtWpfAsiCH3pBT3UHp10sn4cd2Wk9N3778+h/x7Ab9 BXWvv72+v35GF9iv3z79/lmyvynSnu5T+JW+jdSLv3P//8EPydGd+4y2SCirR1B3yXNrIc+6 41UZjD3xPXIBU30SC1CfimZiEtCqOv8KFT7t2kTh+DYdc+Hbngnx1KlfwELjtL6QDpUdkQ+5 C5w0S/PQogsRMcWcUkR7UKZhyU8b9QlE3OXFB8dMz3Yp1D6h7GAE0imvipquJn4Py1Rm3DEk FTmg8ysTdLRjgX9PslcNRNjbpMYOU/a25UQJDA0l6Hn3Ms/2LO+RuCvYe6xmrO+Tril9hid2 o6p1dk5exLbGHbLv1xx3kT+rcFJJ4SlZoz68KOCHpHhMymmgrxgyxvxEaHaldhoXBreLkoVT 4Mqe5EU5e5XMHOH0yF/80PNatF2T6t9Kn0+1tJ0wy8+dQyWhNtjMbjg5Ss5o36lxCs5i7tXo uYAhK0ivruFek0qlPTsrLP//V/aszW3juv6VzH66d2b3bPxI4tyZfqAp2VajV0TJdvpFk029 rWebpJPHPbv311+ApCQ+QDlnptPWAESCJAiCJAhcB01lg+wyEJ7Wobo6odsCXnz2UjANxJEW cS1TIJuXLc3S+IpEzJzA5uYMKUQdODTL9ngTSS+GUpZkduVxNF1yjw6LkURbOkwnB/52eDo+ nIln/kplS+0ePfN1I28K5/SQuWTTC3rT6tIFJMAlCyyCLlkgLYJJtncj/AaoFgGfj46q5o0/ ln0WZKJPCcG9ie9QVuyE54l2hnFLpy297PD1eF8f/sK6hvsMU7Xj3q6Ob2jzqZ46AXI8JKhx 4OfkAqJok2z9ceJtFHOHOki7SVZAOs5oXG8+XvkyKj9ODCvjx4nXM5eYJnXOoWyU5m+kwZiZ 68O9DcSfy7Xf3yP02WrNV4Fzbpc0U6wGCfRIj5LE+QjJ5dUlbeMrlDJdxj9HL5YTFGsen6AY a6kkUEMyRrGVIWzGxlbVtHLHNkyalMk5O8U5Ei1PVwtkE/af1DxZfqDm6UfYm55g7+qk5YFU gTyeFtXV5ZR2VHWpPlDjYjI7bV4DVSAejkN1RfuiO1Skz6pDc+3eLNhIQqcFSUdnjqQYFXtN UbYJLJu7yvSHJ+jKeEwKJE32Qd2tiD+kxxRpdrpqQeYH9gkFRzclMdrWcbWoSHq1GGDqwr1K C53UWIaCYUvoi1B1mvP44/kb2C0/f9y/we/HV/Ps9yPkhqkralbB33w2mbUZbIxPbngT+IJv yEsS6TizjoSxz+oyhXBOdh+izU5TnjsXsxAjCn/loE2k3L2WXECbssW1fRlkE4hof0GFaeqp dAYTpzFy26ZSn2gwK29hTeLt4nwxt6FZNoAHyxQQrBSiDTWyJ7g8J69XE13f/Hxy7RaM8BOf Lc7N/HQITUmoor2yeIdOVfBLOpFyh3Y6foDPAom9e4LARgMJ0lGCSJUAeOoackCbIQMQmg5Q qzY1dmP8KIbJx9UD2u8/XfBVIIvoQHFNXcQOJVv5NwfopQ3tygqMRyhdNhKUzSmSrnBK3G5h iikpNfgUHFcpgF5N7PxL6DiRiFJjyAoNkil5jAoEa7roNfGRi4fl+px+NgMEaYnP4vBe5QSH qtM+QDHCTQZVuSUMWHXDQzazRwULB3lX/b+YU6pP6FninJogWA516CBIfifbResFlIW6qfAK UomDoZJFe3spYHtdImqEp4UZqm+o0AN3naAQFotafMJtl8NMfbuXLFzQFqToO3UauNvX0+1y Enim0eOn4/jZePmLkG9Bhz/B32KsfNXbYzUoipE6+qEZKaWnCZbTZbfHlThKqGAsyoF3Bevr IBo3uKDuueUoKm8vVnrYofJgnf1GI3Rbob1z7XPkOIu3UxtUfbFD+UrYlcA8pMGKqwW7mjF6 tejwoeO+AR86l1bYmceUBAd2TD0+dOfVE7DwBYEiWJ4i4KeqiE+UcEV6qPXYa7LlZFKrATtx RlUCvQsDBSa9qXrsBf1R6MB9IAhKokJfUByawU0GqL2MDPDrUzxcnxCPazZSAiAv1+ezwP5e U1ytz+eh/hMbmBVug9BvnpdrjLlIYNZxPkU0jZpplM0FIhuxhO9kqA0ReKWuJvd6Su1LDAUh mYP1vXJYsLB1SWNB2dEXwzoevLVkzfjlvH8wHbzNEBflFp+DnCDTSW1moB8/SDr/IN3Fx4u8 mF5+mHT+4TZdzKcfJWVVdvnRduGxjZCDwwOXTJoQSIqG9vGQD31ON0SRTQNkJtF8ZruumLMp WSV2fN4B2pYVD1xP4n2VfBkiCo6uZFTN+JKJ9piRKMGvFziwodb1NDMWaJvkFON1OE1CkJq2 gsJAq7L+sZzdbAu/IP0fPLJrqxhdOaciEBszt0bPUWWnWBx0D6qCvZ6uM7wAI0rXr6q23PLp N+pU763Ikjc7USY59ljgRks8v788ECFL5YNg6+2jgpRVsYytzhcVb22n0c7lrHtU3HPT3ecr DNFUHWjH/xK9eGX4Ev/TgWYnX8qFCVZ1nVXnMP9C1Sf7ElWs8xhahhO69HkqdulIZVVENNOU pnkyjr9I2o0IcSqf/fksbevFxTnRvp4gL3l21TWRkmQWxTmP27rmbjcwkV2jwnbAWgKi5R5r xrlji6mOexusER9keu3IQWqreKQdqKPW0oUTxjzcGsVbf8LpcQ2zdTa9ceYqItQbzjR4qS+F vhS0scMq3XnUKT+TYalxKolyYZ6kAGJ7leEdNAYEMuAyHmBpRlBVIPPZXce2ziNT7oxDTuke VmfuwEkXprYqhSfv9Y0LkjqbHvjPeIai2RvEd6PbyLPAStgRZHUTykmsbKQChoJahLoCalve 4r5364CWR6b75HfE0Jd7atHbLGY4sbJqYX7SQwPvajQ+EMZAMYoh8WW87XpEhEUNwshNCeDQ 5ZNzbzpWieBbf0JxWELqsN7rXCvczzoE8FcE/FY7khAe9vVVgWlCUEYu545zinXF4axFvTyy JF0WlgMZ9lkGMLLGzk+4zTbUcgrzjIFunqEarHYwLzJVeNeBsFZKdm1w9/LfYUQ5JIV5UZ5M Ht5uWauf0A4tKFJWrVADghXWUY1cn+DlR1JS92O44pYR9/hW+g2+IQPC4RPsLLr1v0LbCqMf hNiReiLYGZLZQJ3yFSa0xLK5FDCUsLg6PD6/HX6+PD9Q7lNVnBV1jD6CpMQRH6tCfz6+fvPN oaqEVhtCgj9hlXIh6r4MA+6EMfYNlML2z0MH/iw+eq2HQS13SdXnRYIp8/R1d3w5GFExFALa /V/in9e3w+NZ8XTGvx9//vfZK8YO+vP44Ad0RlumzNqoAGHL/TzJNrqrvLuGFM/c7zEVhJGz fGueommodI9iojF98LvQjyjzSW6/O+hxAxOU3EqqOLZZtZCZXXz3uoZoiGqhdHemG6hTUuDL Azu9uIEQeVFYAV81rpwy+RFtPigazScpvQRfxvf19UQqjoROhtzjxaryJtXy5fn+68Pzo9Nm 04SXtr18bUPrgIKr4Hyks7LEgpEo6qW7MygzenEgWZI85fvy99XL4fD6cP/jcHb7/JLchvi+ bRLOdWQCauNRMiYjg4tCGwW68lNVqBBB/8r2tJDgQrUu+XZqy6TVWdI/lGy5V65yHIVdyt9/ B+pTO5jbbG2v4wqclzFZD1GiTgiNkY/O0uPbQfGxfD/+wMhHvSIhehqzzMpZht2JaSpSV1B0 rR8vXb09N/woCHWj1yxLawAsireMXBkRCfOrYnxlKHaEyqsI210GwYKXls/IAKP1TX1j+LV0 j+KpNsjW3b7f/wAZd+edtczj+3zY6PsOELBMsjxqI+r9o1p4wERrRex9uRZLykqWuDTlhNvH xisDgCUV4UgiaY+LHc+F6LRm3zlkF9hTRW8KiNp6s21drUwWe3hSqCGiNxsdFb2+WDzoPVYQ 30Xt2RZpzdYxjE5TelPApZ/9B/TUiDVy962Ufrc8748/jk+unuh7m8J2uI8ZD13d2GfxdlXF t13N+ufZ+hkIn56t9O4K1a6LbZdEr8ijGOXXOu8xyMASQXOe5TyQ6MmkxWVJsO1pSgxXKEr2 kTKZEIldotVKIso2bvL1cbB+LSkp6cMClRXtI3Tq1GeMahiLNt46Mea6HfK+5jKEjFLxf789 PD9p69G3CxWx8/BVAzO2n8wvrq4oxGx2cUHBr64W9tWkRvmvrhx8nV9MzIidGq6UDF4gY6gO D13Vi+urGSMqFNnFBRkiQuMxKpMbMXBAwSyEv2fky5YMNh7VnWX0qeOaqGIZ/cRVEcRL+kxe m0tgo6xoYV3WkzYF66Wm7Uk8ko6zhA7Pg/GkQjgZDX1dBpjOtvGyQWkDyaWPW0UqHWzyuG45 FbAbCZKVMWrqJUmbxxl313ERyOoiMym1UVSFWt+dI1UlDzRT7YVXGZ+6Q9AR6FO1zBIwObtF VRiLm5qfJlm3GMQecEYBJ9N56zS+D/AWB8YhCbwdLHd+eNSkuj17AG3uZ3wBDC6Altim7Soh TScW4VmIFW1JHQMyOxBl1/dJXnMkL0PLb0cHTFBrezeEX9hE0lgWdDpd8DKNZCXUSbmYLzAm TWWZhuZjIuyUcKWbheLf+rq6HSLksSSKKT2LSh0IRR07Z2oIz2s6dqA6vtP1dS3Ud3ap3bla ApEXUIJL2NfQNgNGklrj3rfkm7ZMApNZ1G4/DLsDV2j6FsLyedNawZvUs77B8LelAXGs3gTe E2j8XkwCbnuKQO4tA44smiKu0oSKNabR/vbTQuAvToZJ0I8WRXTjfwzDSj800Gh5qbrejZDc OD5DFjJleZ3c+tWmJXefBTsUGd+ULUb/2I/1mTweCdauDk/kYx8wRIiuw3ulkdLHfMwVRb/D cWVJIsqI+3WeemqrqdCHA9fscnPnnblYlHZsAg3zMuhpePB2XOPt22sF7F8Yugg/+4YNb9dp E7tIvPX1nEe6Z7X6mSyN1I9r5YoAvXIm3v94lcb+sBzgS/kK9KMdBmUA6kzeCj0sOYDQAqkS 69T0NgnpepFAyiBV+Mm+HE6Wq3DKPMboa8RoIJU+tQ4xjFet5wlyQfl9y7aq08fJlEnHIbcA Gz3DuFRhlvVM2q8/Sib5Rlqdre6jn2BTg7T6fA75pUK1yL6V7+hlzYME6G/B7MFPrRt/dbEv Hassoek+yUXXeQYiF1MV/9QMYiS/kD4YrGZuZ0vEmMRo9kZ7t7/lLqqK3iSZVJHXng4jYG5W Hos9lqXbgGkGVNL4lS/D3eaYY5rsYdUwRddA6rslNRBW2fpWaqyb1PP+kao3CS6FaFkQFQvM KpQXxIiqdardVnuMBOhLj8ZXYHe5c0ldzM2uLuQOK20EZqkclWK5zksxOUUz0sVyGwPVArtN ba4AJnYhHe+8nij3rJ0u8gxsgoQHUJTKQOTY6GRZOTtNgJWGKfAWf6z3kKAJpE7t8HvhlODg 7axvHVTJq0g8TSuNkFbEVURmEkaagsdpUWsau2hpOVLiru8Vb/H51GivKVsCZJLa+PcEzhHr AMeRHC9b5orLS9Gu4qwu2u0HyDdCiskHyg0PVdcB+ORrXGykyzt2QaADKiavKC3lLuG9Sy0u cW739Menkfy1p8xYi04qDy08dEmSgotkdBmzqaOPUrtrA0VT35WxM6P1hisq1ZMGEilFv0Nb tWuC0XWpO2gYm5Y9jSOMBklvNvrq2UR5w9gjR5kcNr6bgBOpZLNWmf4ms8k59kpQjQyEc03o qY062czPr0Z0uDrBUTa+M2jqWOV63pbTxi1YnR2Fi2XZ5cV8UEXWt5+vppO43SVfiG/luZne A9vGEOwAyqSMvZ5Xu8ObOM6W7E7mjwx2rE06Ntl1hPe1vCBahi2RgW60Yiu4P3lQYO8ljK/x UJ6TAeozbiga+KG9nNTW5PCCj5vvMcDd4/PT8e35xQo0PZgNbZTxSzCFyqyhGRspydjZ2QfQ XijOrr48qgr3aj0QpjNihgtRvs3izPmpgsa7QHlElFjvqAdEwYua9kvUx6fxqhH09FWFdDu0 GL1jKN86m6yoS58R9Nr0GOmGEUwAyYP/WY6ylkdFS3+pltlVWRVE2+Upv4hY4JyhU9zh1vck dOWqFtw+yIYRDEgtg0EsqU7r1WLXdOvb7eoS9GBXcNdRnUtKoLdEvsVkdOuS2tnqhL96FI3T QpVfzCtSumadEo3KaZuDlpuvfFsx/2R5szt7e7l/OD5988+WoeMsTuoM3chrjHPvWLAeBd6u 1+7HUZNl9DKPWFE0FY87X45A6ZrITFFlnA2jPqw35Awn2mnceNBHQivbFIafMrlnFG/bvIgo FpEkY3IDZF+9GYhNs3RL1RjtHUQXK3iR2eWJZezFeQVwQfrp1XHvewb/pS6WTXAv6Rgmukzj vTzjUu4c7z/ejj9/HP4+vFBeJFmzb1m0vrqeBlLIKLyYzM8Dr9kblZWRUlCYiDqz/e0odowL 7qI05q1ITM9Q/NX60YFFmmTW0TgCtL+G5S4m0/PC//OYe2LYwVHx05c/JpEsvMC4CnQwG4uY cGPQZLxokNDjpWrKuuXkcYlSjdrlO3cnrPSk75HBa8jbmF7W0Hf9tmFRFAoQ3HsY12BAgJ1R NxWt5DLPSblLzWJff6tUgscfhzNly1iSuYUtUsTqGCZJCxtaQZ47Ai5BM9C5Pp62q8Al96xd CYd4JmsoRAKSzunLzY5KxLypAsnZ9vW8NU0MCYBloF0VleTJqXYerNah6Sr1vg8l6vi8jIzt CP5SpKY6arMlZ3zjHLkn0MuAIzvvs0QY5Zrs22CDYwPa8TDYUTqNT4IvMagq906V+Ft7Kbfb uQ2/bYqa2SCCOwRXtf27yFNMoyR4ZWt6A4dxrBP62g+pdiyQ+G+/IhLs9dj1SgQEdVlXTtM7 CNWoHgfjyW/0mx1HYHqaqsGTvBzQwUD6itYbLgVmAmSE0k1DDfEKH34kK2P88yRVjTVkcOo0 UQJQHpwpqgnbPavJpxsSr5pOfSiz0CT551hG5qU1n64Bjx4rTMFIXtFJqqRADs1avhR5HJoz 2I3m1oQev3iPEu3qJQVrl/L1dBFIiYUpvVqkSAKecitMNcSru9Jt/IDHsbKFpQeOCO9As2wS sDpAqpJ1znBNoHtCJQ0zq4lG8oglCifdx6jimF+c1ADUbgfhvLaeirKmLlZiTo+aQrrCJFU5 PQoF9ETK7hy0WszuH76bOTTzuB6UmDE/FBhzmpnS0qloG9DTGYOhEOHhkniUFjpnmmZTsRz9 Bjud36NtJNfmYWnuhkYU13jtYffP5yJNYtro+AJfkB3dRKuulI4Pum7lB1iI31es/j3e499g 4JDcrTr90dkiAr5zeN0qIlKu6j5zFcaxLDET23x2NUxVt3wF6b5JCsyzJuL60y/vb38ujBRu ee0pCQs385CdzTTWbHWA83p4//p89ifVHfgwx+JXAm50oovh6AiheGlek2krEItdAZYdrBxm Pg+JAqMwjarYuG+/iavcrNU5fqmz0h4RCThhhCma0CqAuT26eSVg07aO63RpV9IDqb1KnK2i llewRzUmnCx0w2DPkazxQk31woBX/zjrGEyzLascwSbGqK8ak5/JqXkH20o7YUdRYb7AsOSw KLT0sJXD1sb/XaaNOzWWwbVs6TXTtQfdFb6DaFPCSPvWY3awggBytSK1vCITTZax6o4oV8oC ATfXWL9Oyoh3qAxDAJZeL6K/RfvFCpmiYBXuwszKecWywBAK2HOJTQC53YeGA1NH7K3uLjJ3 hEtvFbvN9/NQiYC7dErQIGf3UA01GYd+CMOMQXHULu+U2UIdpzl0Kq15uJiiphwnFBke6tmf lwKUE70nhcm1Dc2iJjzB4qoI9VduZrCGH90i8OmX4+vzYnFx/dvE1P+p6FeUFlYUusCB5Gp2 ZZc+YMzsOxZmYXpuO5hpEBMuLcTB4jJYz+UkiLE2wA6OPkhxiOhIXg4RFaHOIbkcYeT61OfX s/Dn14EoaE4B1H2iTTK/DrN4RcV1QhKwslDq2kXw20koTJtLRcXIQhqZ8dYe4K7WCQ2e0uAZ DZ67rHeI0Kh2+Eu6vCsa7PVu3wjKNc0iCHIYCFCIJDdFsmgDcUI6NB25ANEZ46jvGLV76/A8 hh0Yd1lTmLyOm4q+leyJqoLVCaM3xz3RXZWkaUKfDXZEaxafJKnimI5Y1FEk0ByWUwfrPUXe mHE6rG6CdlAdARvTGzphGlI09cqaNk2ecOfKoDflrANL9Qj88PD+cnz7x8i73ZeEKTDoBUmb IZhVWUhn07pKOHnqqymttR2vpWCrEcU5rJS4S+ZFeddiQmNuZ9zziEZQsP9JU532bzCbPSpU E6IMyMsKDHDcuaurH/IQm6EljaVl0MfuG3gSDVXWm0+//P76x/Hp9/fXw8vj89fDb98PP34e Xn7pvuw2YUPPmnngU5F9+gXjX3x9/vfTr//cP97/+uP5/uvP49Ovr/d/HoDB49dfj09vh284 lL+okb05vDwdfpx9v3/5enjCy6hhhPVj2cfnl3/Ojk/Ht+P9j+P/3SPWSFPC5e4BDxRa3BOA zVZjU2rYHhm7CIrqC1ge5uUFgNCR96bNnXwqBgoGrys9cKhikWIVxPhIKnRxRVnqO9X0pu4o VjCVbQLjBS7ZMR063K/920h3TvVHtkWlrEszNhkecBXdlRd/+efn2/PZw/PL4ez55UxJiTkn FTnsuUrKrtNYlq5VmAwKPPXhMYtIoE8qbnhSbqwYPzbC/2RjZWw3gD5pla8pGEnYm6we40FO WIj5m7L0qW/M+7yuBNxd+aSgukGt+OVquB0k1EJheGK2TOPggbZDHu9rDOqFxF5t69Vkusia 1EPkTUoD/ZaU8l8PLP8hZKSpN3HOieYhh96BYvn+x4/jw29/Hf45e5By/u3l/uf3fwjxruic 3woZ+eIUW6kGOli0ITgD8FjhMa8iJ3e3FvAsELZU91BTbePphZOCTTkIvb99Pzy9HR/u3w5f z+In2XbQC2f/Pr59P2Ovr88PR4mK7t/uDQWsC+YZwc2aUw4m3ScbBn+m52WR3k1m5xfE9yxe JwLEJVyIiG+TLdl/GwZKdOs1cykDNOHi9uo3YumPD18tfVhdEVXysZkR8yXxSVrRz6g0uliR eaC7OUBwuycmHNhHTsoUPbU2Rs87/R6BjVc3mS+t+IC8WwU296/fQz2ZMZ+5DQXcU83YKkp1 KH38dnh982uo+GxKDBeC/Ur2pHpfpuwmnlIDozAj4wn11JPzKFn5+o2sakTIs4iMI9whyU8S EG/5niKQNF7rpyyakEHvu8mzYROPUwBOLy4psJ33vgfPfGBGwGowZZbFmmjNrrywM7krVXv8 +d16wd/rBF/EAdbWviUBRswOczgHEfo9mS9FDHM1J5SC5UzUgeDSA8HlyLJge+B2hpL897Su pDR+XJX0059+NOZeA+tdQXaMhg/9oobi+fHny+H1VVneLgNg4aSBzKday30pvIoWc1+W0i9z on0A3YxK+RdRR570VPdPX58fz/L3xz8OL2frw9Phxd05aNHJRdLykrLpomqJ1xZ5Q2O0OvO6 Q+IYnTncIOG1b4khwgN+TnC/EaMTtrm1NEzUVocBM23zH8c/Xu5hf/Dy/P52fCJUdJos9Vzy ehwwJxUgEimp7F5TBkpSRGMDKKlIw8Sni4jZj/BOv4JNlnyJP03GSMb57chOcuyYL+N8B7Sq RBHzc7OjJCve4pZxl+ShF/IGoUhnTmIvn0a/5CBlH4u4KENcyDAf2q4er0OTEsM2YGtqVAc0 9N0INpmSs7DHx6T3J1XJ9HxOV3TL4xA8vNXsCQLcI47c0nbIOJdbLuaE4CaJOi5OSYX5yfik dLkATse7UbZ1h6Fx2jTOP8GSThJhnK2AvCXZuo55txOnGFJPNlCaTrGu4lCenCRsFe95TGZG GKg4r2JaAOT7UREHBTBLi3XC2/U+kJnB5GTanCTq3soUXEiTBzTHf/LJxg75rlaLw8sbxsKC nd2rzMj3evz2dP/2/nI4e/h+ePjr+PTNyuD3AfKun5ZJzqq7tqySvF51q1MaXJYqlkSXbWlH htCwdgl6BtbbirrwRP9BVrXyHt9+3cQ8r62eNbBGMXSyMaxdTAAwVHOOB7WVfK5ozmyTBGTc wfKiiqy3s1WSxW3eZEuoaABXDG+7WeoXW/Kk97XVKFGDuMM4JrYG4iCTYBVYoMmlTeFvT3ib 1E1rf2VvluAnphFZ6TC+NjwFJpZ3C1vWDUxIFiUJq3aOjehQwJCQs5BfWqsjt38Z10+wlPp7 Qr4YfvWbQEO88qjIjDYTHICh2jsrDGUhNIp9OLoqoDWWWk4uX5Tl4kDBLCZKRihVMpjBJPWc 5gNsYoJcgin6/RcEu7/b/eLSg8k3cKVPm7BLy3zXYFbR73AGdL1pMuqcQ1PgW2u/tiX/7MFs qe1mFXFhU6motGmR2RFMBiiWZ06oJd9YP+SjHLxoqFhmdKN8XbBlYNFYKwbePSSF9WZOgaSf tTXhER5lhsUAP5CZlFX4EmgjNwI2lmfWPhVBZVyB3pEoT+NHhz/v33+8nT08P70dv70/v7+e PaqrhPuXwz0o9P87/I+xWYBS0KJus+Ud9O+nyaWHgcrwDhTdtiaGB1KPF3hQIb+mp79JN5RF KQOrxMS6hLRxjIpIhSQsTdZ5hl24sHuM4UP/oG8nUuBT2LFlSKxTJWuGCKaFdbiEv8d0TS+y dZEltuJLv7Q1M04iMVgW7DyMVSQrE8tPCn6sIkNUiiQCEV8nsHgZu8iGo/9XjfkPjVUHH9ml 5v2vwLevhRkaWjoD4kXXjpkJeyQoisuidmBqowpLJCyZ0/MeBWrfeVxSYvQM6iq+WH5ma3V+ pK0Rz5hwOzIpqtiaXh1Cbn7FJo2SWRBZBZHpGLLhWRmZ11cmEpZy+fpVSFHZxX2I0/66rjO5 JPTny/Hp7a+ze2ju18fDq3k52hsd8nFgC4ZmChZN2t83XQUpbpskrj/Ne7mBhQCdUrwS5qZr V7YsYJVv46rKWUbf2geZ7c+Qjj8Ov70dH7Wt+CpJHxT8xW/aCnRrLF9+gF6ZzgdpqpISc7gg V+Z9fYzB/DDEHcibOTGEepeAXqAZq0FssUh8d2K7yuPkx6t12Masmlx9ItVF6+R6MGfAjuW1 ZrQspPa3vcZNDO1+mIH5iq/4GP1kzGRrF7Mb1JAtd9NwdNb5R/tYjog8FDs+dKIXHf54//YN b4qTp9e3l/fHw9Ob/ZCRrVUCDTLKoGbUGJAOokTd3cf2WLxalAQZvtYb64SuJLyfJziQDhty VG7W0dJcUk14e7tfobfDjfXEBDGhMcYluVkKpl/14CJjyZfEGaqaG18sMc2BCCBZVbE7j4T+ 8PQXYpOsrDYpcJRsPTcEh6TJqxjPspbkI2NFA8pXvrXEwzWP1cLtjTbOzcsjsvd6qf2QHNpC hc7vMSFO6OjtGTzaUaIv13DdR70X7+s4Rz9kvzjEyyWd8tjHb4tdbu4AJQxmuyjyxM55qMqr iojVzLt1doVNEe/2fgE7yq7pt4911DgBfyREfRvwvlXlqtENeFGlzbIjo51eJIV8MROalXrU YOlLQYf57eowIywqI6IRtGko+AaNd0kT55F6rOZYK0PXbrO2XNco76622mY+c0CN95H4vGeE P6CqKBVi1Aj7v7WnHyleXHaTqm4YIe4aEaxVBXCWzkSEcKuFBFce8phfaaobhlN3ODG3sbui whMW0MjD5I4ivbV0PZWGCeiN7caJ2Ko3KkB/Vjz/fP31LH1++Ov9p1rNNvdP36yFqWQybRMo qYJsioXHV89N/OncRuJrgqKpBzC6PzU4dWqYGObeURSr2kf2vIAyrOWu0CSUdVDHUEFil0tV VbvBeEk1EzemFCnnsB7Vt2UyPaf4GghPs+XQulztbsEAAosqKiyzfHzglD8nWCdf39EkIdSy msze61gJ9tTM4M5GFGlPB+yYmzgulW5Wx5HoDDKsOP/1+vP4hA4iwPnj+9vh7wP85/D28K9/ /eu/B/7ke1FZ5BqFf3hqOEhkVWzHX42qjL3QmODkxZOBpo739pmmnjBEKkx3KVTfjlDsdooI 9HexQ+/PMCs74byaUnDZCG+BdIjUZhYqiWMqWM1QEvYlbsO7DbJ5zIUVwUzDt6/OMc/QiuHc 0hCZlfUZKTj/iQy4jQO9JbU67YTLb+qKmSe3cueBjqFNLuI4AilXR5DuonCjFuROStWE+kvZ R1/v3+7P0DB6wGN3SxHqvkxI80JrfcQSAkWdkiuUfAacOBsbZQ200pzhhQyo4T39trRBgHm7 Kl5Bn+R1wtI+M1fFG0pFOLIwnOjypsWQ19RwGyRhmTCI8JU9XZZBhCuo3G/2anc6ceqqQqk5 EBvfkvELutxpVuu9CXyrN4aVtyU0jS98dCoZREbkXtR8JwrAgBJbhTkXDINJB+xF6WSvTzq8 Rf3l+Prwv9aImscf9eH1DecgrhYcU67cfztYrv5NTl4TdDKK5xNFNcQisHRyRpORjShWMPxj hdOO+eFICK5ld8OLrWdOgREFYDVQbWndKiI9JYKwZcZbJpRQHEbbWyW9ieyAVUiGJ6d4WEKf N0gKzOZO+aQtO40mla2jiKslHnr7M9I8VQ9MJOvY3CuhOw0lT05txjfxHnc8pDaupJh7l1vy O41VLyGE12OAFrykYtJI9A3gazOQkoT2955OWZzlgQQmiFbnoaGamiaJvBL38lQgXCTGTljB Eh8qtMKT2W4H4vQn7cYkcUlkXTusEth2Aff0Gbld7CqpMlgKqY2camYUp+zO6U/QJpxBtzpg 41TYHjJ5+Utqi644d1+keEMRlM9vQtMXw1TA17YYDQD3BQap04ZKpUmQJUKgAEYFb/B2gtas ynpYJkoR0Vawc478/7dUXj00vQEA --WIyZ46R2i8wDzkSu--