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 X-Spam-Level: X-Spam-Status: No, score=-10.2 required=3.0 tests=BAYES_00, HEADER_FROM_DIFFERENT_DOMAINS,MAILING_LIST_MULTI,MENTIONS_GIT_HOSTING, SPF_HELO_NONE,SPF_PASS,URIBL_BLOCKED,USER_AGENT_SANE_1 autolearn=ham autolearn_force=no version=3.4.0 Received: from mail.kernel.org (mail.kernel.org [198.145.29.99]) by smtp.lore.kernel.org (Postfix) with ESMTP id 5A713C433B4 for ; Tue, 13 Apr 2021 11:45:02 +0000 (UTC) Received: from vger.kernel.org (vger.kernel.org [23.128.96.18]) by mail.kernel.org (Postfix) with ESMTP id 293376135C for ; Tue, 13 Apr 2021 11:45:02 +0000 (UTC) Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S245387AbhDMLpU (ORCPT ); Tue, 13 Apr 2021 07:45:20 -0400 Received: from mga03.intel.com ([134.134.136.65]:20846 "EHLO mga03.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S238852AbhDMLpO (ORCPT ); Tue, 13 Apr 2021 07:45:14 -0400 IronPort-SDR: DyCWgIFscEg1THTpbZLANsEI6NB77Ka8Mh5ZSaQIx7ePRB1Y3B05o/cdNzMRrwCbtbFTyVfmHF MfR/0tNm3QXw== X-IronPort-AV: E=McAfee;i="6200,9189,9952"; a="194423183" X-IronPort-AV: E=Sophos;i="5.82,219,1613462400"; d="gz'50?scan'50,208,50";a="194423183" Received: from orsmga003.jf.intel.com ([10.7.209.27]) by orsmga103.jf.intel.com with ESMTP/TLS/ECDHE-RSA-AES256-GCM-SHA384; 13 Apr 2021 04:44:52 -0700 IronPort-SDR: YwaqdSNg1giXCwxnItIrGtCItU/v1KPGOXxXFvqxmGozg2W2cjdJJIx6Nk/F5fzbJDCRPjzDhn glMGIRMPaaLQ== X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.82,219,1613462400"; d="gz'50?scan'50,208,50";a="381943424" Received: from lkp-server01.sh.intel.com (HELO 69d8fcc516b7) ([10.239.97.150]) by orsmga003.jf.intel.com with ESMTP; 13 Apr 2021 04:44:50 -0700 Received: from kbuild by 69d8fcc516b7 with local (Exim 4.92) (envelope-from ) id 1lWHTO-00011g-0u; Tue, 13 Apr 2021 11:44:50 +0000 Date: Tue, 13 Apr 2021 19:44:01 +0800 From: kernel test robot To: Lauri Kasanen Cc: kbuild-all@lists.01.org, linux-kernel@vger.kernel.org, Thomas Bogendoerfer Subject: arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:393:28: sparse: sparse: incorrect type in argument 1 (different base types) Message-ID: <202104131951.fnE3mimp-lkp@intel.com> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="k1lZvvs/B4yU6o8G" Content-Disposition: inline User-Agent: Mutt/1.10.1 (2018-07-13) Precedence: bulk List-ID: X-Mailing-List: linux-kernel@vger.kernel.org --k1lZvvs/B4yU6o8G Content-Type: text/plain; charset=us-ascii Content-Disposition: inline tree: https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git master head: 89698becf06d341a700913c3d89ce2a914af69a2 commit: baec970aa5ba11099ad7a91773350c91fb2113f0 mips: Add N64 machine type date: 3 months ago config: mips-randconfig-s032-20210413 (attached as .config) compiler: mips64-linux-gcc (GCC) 9.3.0 reproduce: wget https://raw.githubusercontent.com/intel/lkp-tests/master/sbin/make.cross -O ~/bin/make.cross chmod +x ~/bin/make.cross # apt-get install sparse # sparse version: v0.6.3-280-g2cd6d34e-dirty # https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=baec970aa5ba11099ad7a91773350c91fb2113f0 git remote add linus https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git git fetch --no-tags linus master git checkout baec970aa5ba11099ad7a91773350c91fb2113f0 # save the attached .config to linux build tree COMPILER_INSTALL_PATH=$HOME/0day COMPILER=gcc-9.3.0 make.cross C=1 CF='-fdiagnostic-prefix -D__CHECK_ENDIAN__' ARCH=mips If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot sparse warnings: (new ones prefixed by >>) command-line: note: in included file: builtin:1:9: sparse: sparse: preprocessor token __ATOMIC_ACQUIRE redefined builtin:0:0: sparse: this was the original definition builtin:1:9: sparse: sparse: preprocessor token __ATOMIC_SEQ_CST redefined builtin:0:0: sparse: this was the original definition builtin:1:9: sparse: sparse: preprocessor token __ATOMIC_ACQ_REL redefined builtin:0:0: sparse: this was the original definition builtin:1:9: sparse: sparse: preprocessor token __ATOMIC_RELEASE redefined builtin:0:0: sparse: this was the original definition arch/mips/boot/compressed/decompress.c:38:6: sparse: sparse: symbol 'error' was not declared. Should it be static? arch/mips/boot/compressed/decompress.c: note: in included file (through arch/mips/boot/compressed/../../../../lib/decompress_unxz.c): >> arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:393:28: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected restricted __le32 const [usertype] *p @@ got unsigned int const [usertype] * @@ arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:393:28: sparse: expected restricted __le32 const [usertype] *p arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:393:28: sparse: got unsigned int const [usertype] * arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:427:48: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected restricted __le32 const [usertype] *p @@ got unsigned int const [usertype] * @@ arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:427:48: sparse: expected restricted __le32 const [usertype] *p arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:427:48: sparse: got unsigned int const [usertype] * arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:435:37: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected restricted __le32 const [usertype] *p @@ got unsigned int const [usertype] * @@ arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:435:37: sparse: expected restricted __le32 const [usertype] *p arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:435:37: sparse: got unsigned int const [usertype] * arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:459:28: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected restricted __le32 const [usertype] *p @@ got unsigned int const [usertype] * @@ arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:459:28: sparse: expected restricted __le32 const [usertype] *p arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:459:28: sparse: got unsigned int const [usertype] * arch/mips/boot/compressed/decompress.c:110:57: sparse: sparse: Using plain integer as NULL pointer arch/mips/boot/compressed/decompress.c:110:60: sparse: sparse: Using plain integer as NULL pointer arch/mips/boot/compressed/decompress.c:111:57: sparse: sparse: Using plain integer as NULL pointer vim +393 arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c 24fa0402a9b6a5 Lasse Collin 2011-01-12 385 24fa0402a9b6a5 Lasse Collin 2011-01-12 386 /* Decode the Stream Header field (the first 12 bytes of the .xz Stream). */ 24fa0402a9b6a5 Lasse Collin 2011-01-12 387 static enum xz_ret dec_stream_header(struct xz_dec *s) 24fa0402a9b6a5 Lasse Collin 2011-01-12 388 { 24fa0402a9b6a5 Lasse Collin 2011-01-12 389 if (!memeq(s->temp.buf, HEADER_MAGIC, HEADER_MAGIC_SIZE)) 24fa0402a9b6a5 Lasse Collin 2011-01-12 390 return XZ_FORMAT_ERROR; 24fa0402a9b6a5 Lasse Collin 2011-01-12 391 24fa0402a9b6a5 Lasse Collin 2011-01-12 392 if (xz_crc32(s->temp.buf + HEADER_MAGIC_SIZE, 2, 0) 24fa0402a9b6a5 Lasse Collin 2011-01-12 @393 != get_le32(s->temp.buf + HEADER_MAGIC_SIZE + 2)) 24fa0402a9b6a5 Lasse Collin 2011-01-12 394 return XZ_DATA_ERROR; 24fa0402a9b6a5 Lasse Collin 2011-01-12 395 24fa0402a9b6a5 Lasse Collin 2011-01-12 396 if (s->temp.buf[HEADER_MAGIC_SIZE] != 0) 24fa0402a9b6a5 Lasse Collin 2011-01-12 397 return XZ_OPTIONS_ERROR; 24fa0402a9b6a5 Lasse Collin 2011-01-12 398 24fa0402a9b6a5 Lasse Collin 2011-01-12 399 /* 24fa0402a9b6a5 Lasse Collin 2011-01-12 400 * Of integrity checks, we support only none (Check ID = 0) and 24fa0402a9b6a5 Lasse Collin 2011-01-12 401 * CRC32 (Check ID = 1). However, if XZ_DEC_ANY_CHECK is defined, 24fa0402a9b6a5 Lasse Collin 2011-01-12 402 * we will accept other check types too, but then the check won't 24fa0402a9b6a5 Lasse Collin 2011-01-12 403 * be verified and a warning (XZ_UNSUPPORTED_CHECK) will be given. 24fa0402a9b6a5 Lasse Collin 2011-01-12 404 */ 24fa0402a9b6a5 Lasse Collin 2011-01-12 405 s->check_type = s->temp.buf[HEADER_MAGIC_SIZE + 1]; 24fa0402a9b6a5 Lasse Collin 2011-01-12 406 :::::: The code at line 393 was first introduced by commit :::::: 24fa0402a9b6a537e87e38341e78b7da86486846 decompressors: add XZ decompressor module :::::: TO: Lasse Collin :::::: CC: Linus Torvalds --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all@lists.01.org --k1lZvvs/B4yU6o8G Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICFhsdWAAAy5jb25maWcAlDxbb+O20u/9FUb70gLd1nYum+BDHiiKsllLokJSjpMXwU28 26DZZGE7vfz7M0PdSIpy9zvA6cYzw/vcZ+wfvvthQt6Pb1+2x+fH7cvLv5PPu9fdfnvcPU0+ Pb/s/m8Si0ku9ITFXP8CxOnz6/s/v355/nqYXPwym/0y/bB/nE1Wu/3r7mVC314/PX9+h+HP b6/f/fAdFXnCFxWl1ZpJxUVeabbRN9/j8MvzDy8414fPj4+THxeU/jS5/uXsl+n31iiuKkDc /NuCFv1MN9fTs+m0RaRxB5+fnU/N/7p5UpIvOnQ/xBoztdZcElURlVULoUW/soXgecpzZqFE rrQsqRZS9VAub6s7IVc9JCp5GmuesUqTKGWVElIDFq7ph8nCXPrL5LA7vn/tLy6SYsXyCu5N ZYU1d851xfJ1RSScg2dc35zNYZZuQ1nBYQHNlJ48Hyavb0ecuDu4oCRtT/799/04G1GRUovA YHOISpFU49AGuCRrVq2YzFlaLR64tVMbEwFmHkalDxkJYzYPYyPEGOI8jHhQOgZMd1prv/Y5 fbzZ9SkC3Hvgouz9D4eI0zOen0LjQQILxiwhZaoNc1hv04KXQumcZOzm+x9f3153P3UE6l6t eUHtbRZC8U2V3ZasZMGd3BFNl9U4nkqhVJWxTMj7imhN6DKw41KxlEf2wqQELWNTGuEAUZoc 3n8//Hs47r70wrFgOZOcGkkrpIgskbRRainuwhiWJIxqDixCkqTKiFqF6ejSZmmExCIjPLf5 LI9B4GowUrjkiZCUxZVeSkZini/sI9sLxSwqF4lyr3T3+jR5++Rdgr9No1bW8JQgwenwFBRE e8XWLNcqgMyEqsoiJpq16kg/f9ntD6FL15yuQB8xuFXdT5WLavmAeicTuX04ABawhog5Dbx/ PYrDzXkzOVPwxbKSTJkjyvDdDLbbzlZIxrJCw6xGYfcM3sDXIi1zTeR9kIsbqgE/0qL8VW8P f06OsO5kC3s4HLfHw2T7+Pj2/np8fv3s3RcMqAilAtbyXn/NpfbQ+C6By0L+MK8cnihSMQoB ZSB3QBHS+xoYXGliswCCgOtScm8GeYhNA+sWMVAurC2E703x4DN9w72Z+5W0nKgQ6+X3FeDs HcHHim2Ax0IHVjWxPdwD4Y2YORpZCKAGoDJmIbiWhLJue82J3ZN0T7mq/7CUxGoJmoHJgHQq ugTVYQS4lU71+Mfu6f1lt5982m2P7/vdwYCbNQNYz4nhuZ7NrywHZiFFWVhrF2TBKvPETPZQ UOd04X2sVvCPP1O95x6aEC4rF9NbikRVEWjPOx7rkI0A8RgbWcMLHqvAuAYrY9uxaIAJyPWD fbIGHrM1p2wABrZ1haOBR0US2I/R4SFmFKgIGhqirV2hVVYFcI+ypyu1qvLQycBWA8IhVUx6 tL0s8jg8Tc50PU27/SWjq0IAb6C2BV/WuoiaB9EjNPu3EPcK3i9moCkpmI94HFOtLddPosax HOMUldDaeC7SmsN8JhnMo0QJFtTyamTsOZoA8PxLgLhuJQBsb9Lghff53PncuIztNoXQlS+5 IFKiAL3MHxiaeTR38E9GcuoYHJ9MwR+BRzH+KvjXMWgDWAo0DbJKxdDHz4nmrnU9SRhy/ONK yAJ8FfDfZO68FdUp6FHKCm2CNNRl1sENozcfam1rqQFwLjlyoL0ztWAa/amq8UiCrFmzyCmK pParwoxtfNSQU9BZb+DlVRDlSWgPJwqep3R30+6lhNDV0mn4EaTLuphC2K6X4oucpImjssxu k5Dzbnwzl1gtQbUGt0l4KDIDu1xKzysg8ZrDkZo7DqkBWCMiUnJbHa6Q9j5TQ0jleJcd1Nwb CjU60w7fVL1L2t8ygEEtpIKEbgJZyUQs7m1IxW5D95ZFLI5txWNECKWw8v1dA4Tpq3UGOxJu xENn0/OBo9dkNYrd/tPb/sv29XE3YX/tXsFlIWBrKTot4HfWPqG1Rr1w0AX6xhktBzGrp2vN cdDWQbxPdBXZyQaVEieyUmkZhaUwFWMIEgF7SHAFmhhynAwtasoVmA4QWJGFzJ9DtiQyBv/G thfLMkkghDKuh3keAjbI0VGaZbWWW4NjlHDa6sNO3kXC01YAmvt28yod03Pj7ZiHy7aPfzy/ 7oDiZffYpK26wyFh54nV4XfwEgwdScFMZuFQgsiPYbhezi/GMB+vw1rK3lWYgmbnHzebMdzl 2QjOTExFREbeOoM4HpiBYhThmRiX5jfy8DCOhTdiObq2Irz9lEBscTs+PhUiXyiRn4XzMg7N nCX/TXQZzrcYmgL4Ff7l4YyNuTFQJ5qcmoGe2ulans/c97CxORgxBjJ1ee5oQwKMHrZtasHB RZyHF2yQYV5skFcnkGfTU8iRNXl0ryGckEueh015S0FkNiJf/Rzi9Bz/SaDA9Qlb1YYg5Vqn TJXy5CygkYUKv3lDEvHF6CQ5r0Y2Yd5cb86uxyS0xp+P4vlKCs1XlYwuRt6DkjUvs0pQzTCv PCKDeZpVm1SC0wuq+gRFEaJolO9QtfrB7fKO8cXS8ia7nBQweCQhcKizE34oIjKuwZpA4FSZ kMUJ5tga7NC5ZQspRP0upFZ0GFMHkmZEwh2rsiiE1JgYw9Si5UZARIn5JCqWTAIbWMsUJb56 BeLKiete99OFCMxu0hkcGg4HlpAn+uaiSzU5lslaSp6fTacjqzxgrOLiMPC3h9lZmcALaQKG X1dcEXDs1n2BxFnmbB7BO9R2cWQnl+chEtzIf8zikHiz2M7Z8d+vO9tkm9kC2tRM4d35msB7 wPTnVjLEOCAYnlXnK8eD6hGzy1XYZepJLs9dkjZqwEQwCPGmegA9JcAJkjezmX3kVgDiMisq nUbejpOivRT3poC7AVcOgTVPORMhKmcsVphsVRmR2kwNUWnGqRSNc2QRI+uo+5x6eyGKxw23 TocIvNibK0emEggQIN4A/sf6l5cnnodtMGDOwxYJMLNp2B4hyrVj1joXU3/li8sTC4yvMHW3 HOJ+IpFvl3YN6+EGdtBFUGzDnDiESqKW5vHH3Q1xNoe3vjxvlwm5Dka/ZTEWKkFPiswkLzDi auJ0NxwxMtRlCUArxizAZ+gHreo05wBXLOqaZgrBSqpuzmsRjd4Pk7evqFcOkx8Lyn+eFDSj nPw8YaBYfp6Y/2j6U6/YgKiKJcciJMy1INRS/VlWeko6y0hRybxmNjh0fjObnyIgm5vZVZig jaHaib6FDKe76C/zm09rvxK8ZT2nJXLe56ZAN4A3w4EdbA5qoJ5z3Dr/PE8yXbE0MYPMIxVv f+/2E4hFt593XyAUbc/QP4q5giWPQP0avx9zL+Dl2GWbxmaqAmybje59nhoX2FNh5Y+LrM6f Ono3wzQGJtTi0eTq3S0sescklvQ45RgvNzGrze2jJ+1MbU2RdRSA6HD86cUxNKgZ+SA7ZRnV eoANGUxv5kue91/+3u53k3j//JeXT0i4zMBjZZinAR4MKoWFEAsQvZZ0kMXQu8/77eRTu8qT WcWuGIwQtOjB/tpbx+JVCY7agxeJ1/4MCAvJK4xTqnWsxI3X6bDdg3N4BK/jfb/78LT7CosF ma/WiNTJRxu16cEUeCuJkxYXdUZgNM/a4vs5fkOjm5KIOfkqE+1i+I+aHURnpK3CzFk7KnAn ixwz5hTrcZ6UYAYKuyg0z6sIwhG/W4LDsVDdwO60h1r5vmgNlUwHEXnGPYjZgFHhSyFWHhId W/is+aIUZagSBZeDDN/Usb1joZMA7o3myX2brh8S4BL4UGVu/BI/bYfdNZmImxYU/ziSLcCi gn4xhqi53IoU/iExVRg6t/O69s7uCOgL1LAFkZgebFpjAkSN+v8mWpHGFn1oQ4pRJDiBAqFO tZdarzFjDGjuBlmHUTd/9k1w+ChFvvB2hEzBNtowzooP0PDk4Eku/UadkdK2z+3BsrZNAQzR 3EnBKOb9AjOwDUidyOt+DzxRgPdAcpv0JDjooTt3nAWPwCwQ5Ht3VO9/BOa1nIexSWySqyFP tc08WhSxuMvrcRAfi9L2H1KILaoIbgHMQeyoxGb6OuLCaw9lkzE8EJYlTRL/NsyGmi4zWS2d mhTG1FbGOpSvrhm1FqAm+q5yGZKhQcWqNiFUrD/8vj3sniZ/1g7s1/3bp+cXp/ECiQZBZccM Btvo/8qrT/i4oIE/tQfnnNiyWKTlgrs1Wwscnv/bzGS7FIhahhUp2waYqozCWsfNzPIPRVym LFwyi/D1Ag9GVD7r5y3zugMSnhBMWJk3rQm+jTPdYbEhQoqQGWxI5J1H0BfozXuzf3aP78ft 7y8705I6MaWTo+Uj9G6tt0iPMFbcEnsAuf5DQ6qo5IXT9NIgMq7CmTKcZhiwNc84tvW69LD7 8rb/1/IHh95PEzJbVwMAEM/YeIQQgvjWIyFKVwu7Rm8uYsUgosNan/tYqkhBERTaSC0IPkZu LZ/UzXsR1mLcsnMDqpUJHak190gvtSIZRo6Oms/4QvrFnCU4WySOZaX9zI2xK1qAD2UXKJV1 R62WNNoRgjkz0c359PqypcD0B9bqjLJbZY6KTBmpvZPwa2fhrO9DIUSobPwQlZbFeFDD0mML MxwanNs4XebyWgscCqOYNCmzpsGrVzRlMdYI3GnDAlPaaF1JasdL4/zZ3+MgbkWYcfoz8M5g z9YjYcsJbF46PjECWQAGQsUlo12HdL47/v22/xP061BKgNNW9k7qz1XMiRNJguIK1Vk2cWG6 c5h7cRbYzBR+GthqODvONHZ/o7uWERku1bQ0wOzGGMPbgUkNvi6Qdq6gD+rCY0vmdeZ8wJKa E45HkseLMIevgba6ms5n4QpczKh35tbyp5ZnBh/m9g5IurKXx24fUhQpQ0Rwmc1IWTQlRSix WmDdx+IAzhjDM1w4ZbMeWuVp84fpZ4HLz2Er4SfuB9XsEC7VdatZPNz2rBkGvn3fve+AfX9t GvRqb8VmBqSvaBS+9xa/1KHzd9hEOcqlhQMPnBhVSC4GO687e26HcGlzWgtUSRRaVyWnT6PZ bfjWO4IoObFxGqnQqiAZJwZp0px3MA7U0EitqyGI1SlhNiTwLzt117GUgau+DT+BWkVhBF2K FRuCb5Pb0LmwQez0NSe330BEySqsMvpZTrHmMhluuOCBU8BmgvDedgxWRlf65NaY35DjP8uw xaWWzpft4fD86fnR+0oTjqPpYC8AQr+bB9vdG7ymPI/tXrIWkdyFpiuDmdwWK9W6CI1CeLis 0a2WirsTE1Ov1bM7XZEEdp5i9nUIz/B7Ik5x1Zh7Aw7BmuD9bB5A0Wxw0AaTY8F95CgNSXk2 D66XMacTt0eY76kNzkPcfngEA6gqRMrp2A6QYEHs/uGFGSNF5C6A0IzLgXpFuALPwE2ot5ic hAxStzP82l5omOLBHFKHXkXNSH+DxZDpEY5ewyi7IQHwzen1IDAdLscTNgTqMsfvQa3YfWgn C6LHtRTMZ9bytPiQYqh2G0Qvvc7EmiISvImx1zCKjSeO3YlpyJbHucIWbIFfxbOjeZ0RDGXW IVj759oN1Dp0PtIo1lMMSiu9Q9h4wWOXarx930NuHaOaXax7QEi1UAP7m6tlcIGlkoF5b6W2 7gY/VSpzGkYNDDglFJvWXfi4qvvMFoKmRCnucaTcYNR5X7mdvtFt15PQBCmT4+5wbP27Jpga oDyEHdj0EX0mScy72kmxffxzd5zI7dPzG+abjm+Pby9OvYiM+c2UhG4isiQ8wg5SFksHIhP8 UpdLlDNHETegKqNNtjrMaQ0VpppFgLAnW/LYn385kq7SVbC6Y+CxcnadqaRR6fbw4BfuevSJ ag9gE0Z0KVlXsaxL3i/vu+Pb2/GPydPur+fHtprmPBKeiPJIlyok/g2WZvPp2cY5A4ILMpsO oQlM5QPX8H/vuJlch3IUiNGrkkinWjp6knbYHcTnqRO3t5DKMZ53WDtwk20GpIp7DwLSaGk3 miwwqJo5msKEbTOT0QCDMZKjaQZimMlSgXkeTB+D+xjsnm6pKcPqVdNXXInczi91RJLdlnBK 096PqUu2iKMAGWY3m6/rGhJTPQzQwakl6UliLq0vuViLYltbmpYpkSAfTle7Q4Q9+BvM3nOn ZmRdSJ0ZK05eRCMVgTWojInV/DFc4C5sAFMetU/pQWDK+0LDuGIUR2k2jtQrHkIOugiaCH02 HrzP0PnEdNjSNGhhG1ff1ySTFbd1fv3ZUzMNkOeFXY5poIvCdyiuB/7sdWGym8GvdzT49mCd Wuful9Dg82iXhEHCPCAW7gxVrT76vSSh+KXonFDXK7JHpne1cxbqfSM8FY5Lw/RSC5G2PkSr QuNa3fTdEO36lBLp2Pi6v2YQsxX0w+N2/zT5ff/89Nl8ObLvPHh+bCaeiC6L2CcI68LVkqXF iBmDq9NZMWIxgH/ymKReB3K7V1lP3nV0mF9SaM/c9Vi8vG2fTHdGe2t3Vde25YNMTjiGiZyv Z6FCaRexlEk/ynxdsD6jfZlBAni1NMVSYuhBuwGY+e0ic79rpDmR5aOkEC2aFGCodNJdNPBw 0wrmZg4NnK0lC+mwGo3WoRkLKjET9peSiqy6FapalfgbGkjYo2pYM65gHrZrTcaSdqmF95MD oH6dakz9ueJzOoDdzQagLLO1QzvW/h0B0zqxhDc1D57YDIGohOWUdV/cc8uIQ57vuvNq0+56 J5JmSkfVgqsIGxhHmtxRFeBlgkMcblVc8iHO6pRrV+70kAC90fQm9AIuBQ18nap9kdx2PvAT eGyyLWLYYHBvGtTINHAgmfSjbUwZbQLTZuHf4NDWa4vE/hurD9rlKABiOU9LxhwgIzK9D6NW IvrNAcT3Ocm4s6opdzl+GcAcXhKJW7mBzzCAyTUwl1NtrBEYiTowVONOV35BpNcPWgMgHrm6 +nh9OUTM5lfnQ2guwDehXTS1zthEvX/9+rY/OqGUDa8rqc+HR4uXW0UTX8wvNlVc2I1UFtAV TlBE2b332x1UXZ/N1fnUEliQs1Qo9Pvxwji1C1ykiNU1+BLEDnq5SufX0+mZD5k7fciK5UpI VWnAXVyMfM2moYmWs48fT5OYnVxPQ+WuZUYvzy6sdFisZpdXTg+pkiSUwt7g1+tAGOLEbVou 1gXJgynPJVcc/gOebeVEKHReWD9+xBjIeTY5dC/dXrWBV0TPLVZpgF1zcLeLBgG+2+XVx3AQ 3JBcn9HNZWC3DZrHurq6XhZMbQLzMzabTs+Das07R9N8+c/2MOGvh+P+/Yv5oufhD7CKT5Pj fvt6QLrJC35H5gk4+Pkr/ul2Zv6/Rw95IeXqDFk9VAHGMJyg41JYao/RpZOewdaHSmq1qbyI ta8U2/LXZy+wOyvuflRGUcXbWHLw1ois6hRg/0sWgQGW71n/XIMlaRm3WgFNEscJOo2AOy96 a7pXg4kInnjZWc1INoTglhn+TBeJKVF6jECKMo/BX+BOI4VHM/jq7AghMb9ZhE5ZOZbC7YnR Q4tI6v8eAcQ8oxlbwCk2UsCAv8Ac+InoBtoao/BQN2lmkm8AMc2FEv5w3TyIIqq1eULzS1LB NM8a4gd7TB06/Y+xa2tu3FbSf8VV+3JO1WbDi3jRQx4gkpIYEyJNUBLtF5UzdhLXOuMpx7Ob 7K9fNECQuDTkPMy41F/jQly7G43GxXsi31DPlVU4IJ8uHXhsZ6BUXWHgFQFdH9N8u/29jHGl xvmZUwyNCQJD9fVuBzLn/h6Ts+sRvFVEMrnb1fUNsPotTISWdmYLVtYHP8inxGGoiZ9Bbugb T13lTODLpKyuohY0WYWr4GJ9O6dn4zj68ipovsrzEEmVZ9dSycGlGn7pxrogpfNls/gJTknE LqskfI2Rn4MtEkXXHJn5rc04mAS4nthcxjO5tzNv+JJXDWEQhoWnAEq4TMYniZVQkcNg50tY F33VmBURt7sglpmPPIQIwipam2R5CYRYuZMhD+LRpN25ifsK9pxbm3ioGLEaklfq1q0to6yw m4MNfE8esbUQdjc+GLgcZ+ZSdnmcR5HT25w8FHkYelpVJFvlSF5phhHXdgGnmmsArPJkP8lX Oz6/o35n7Ga05CubHZ9IEA03OC6b01LXJFW63gwuJFPWw4ag3kYS5hOJ6yx8N7CyE0LdtnIB ejKEPEljRQEbM3WKlxeQ8R0I8Lq744I3HgJBMeRB6kbtAPCGfn/94BLR81+GCUm12IUeR7cd garsdFZTTaBwieGK7+gxD5nMFK5y7Jz6dQVzl261XfCROvL/dDEI4Z/Zm9owInYdNgt4r4gl cdrClg8HoCC6zgqUW3KWO6tG67i4zY5W0n5o8jAJMKKhTgCZCxtZjoY5AJT/MxRSVWPYbcJs 9AHrS5jlxEWLshBbMopwCZ7iwKFAgP2RN0et4cZnqaR0U2Ma09zydJ3qSqSis36dBQFKz4MA KwzWvyzxNqRiWXMWN9tdk0YB0l4H2IVytDzY4LBTKoXTgmV5jHxCfyhrJqKO4o3Njhu4CTTf Bfay2LXiIvuFJinqFSPwQ5RFzrdsqua2xo5ARZKe8pX3ONqJqg4iiOQ5dpVYzJQiCtfItz+Q Y29PFvFRYx7FYXBxpheAt6ShNdI5d3wLPZ/1eAEK4ZJFEo7WsIKGs70hgV53e6dYVlc9V/8O biOL2u7XkXn92Z6Ed0UYhtj0j7kOqc2lc6NXH35x4Z1rO+C6Srk0oJduoGhIQJODmpf1dFAJ o5/kUXD1tsWrJ2Q3P9SzWkNhrBNjOZYU9GYmkuMk1WmiJFy5HQhzKfaBzUz3e3HMLLTyeFrQ c72tK2xlMWpZlTW50mezOPlJPjKEDd62k5DoK6I344siHPqio9OH2pfnw31JcOVO5xLaUXU4 YAGfzYXPHPLizgI0r1E86pKhuRs7+7WGbcltpQd10CAyWKNDw/ZnVvttDOqIDmWoWXlwZJn6 67fvH16jjnUSKn5aZ6aSBuGXK2o6E0hEXhO7NY5WJEIJV5vHCRGVOf75/P4KYWVfIIrar4+G MXhK1B5ZZZx/mnQ45NRFQwtlXKuqDpfxJwj+cJ3n/qcszbXWE0w/t/ecBet1AVcnpGrVSXMv ke3tOyGVCW6rexGTZ8lIUfhyW6DULkny3Ius9cG0YMPtBjsDmRnuuFChS4cGkAVopndDFKa4 aXvmKSeHsz7Nk2vlN7e8gmgpIONfSwm4sE5VWCMOBUlXYYoj+SrEGlIOVrQyDc3jKL76IZwj jtFcxyxO1hhSMIza9WEUorU4VOcBvcg1c7RddQCDKpbxrm3Kbc32S8xFtwQ2tGdyJpjiu/Ac D7LPnML5NF+hLR7z8TliCI0uQ3ss9tJN1IHPzSqI8UE42iPbZSlIF4aeGFxLcw+3lw63h2pr hqaHwk++AkUIiYu9nanCz8jmHpuGC960u5r/7To8Obs/kA5MJFczmbm4emGYHBaW4r4zjx0X SNxbE5G68DpUEPKvKjxyyVKJCuQxtEG1skSnG7GeZmwLL1xAQRioPswq2HtuLGF5jQnKdJOC 3XOdYVGCJF7ck47YVYG2mE4mrewUYh/m+NjEB3kLP7FxHIlTvOmnNDXB3PlovRYY1xXnvY9B NPwlc0XhKhvhg1TPeIFifCYuDCXeFhoDJi3OcNFueoLUabeNbtEa7XpUtjXwi+6xtiDHmm8p VD+NnjGhThi3BGaI1WV1BqfzHgEHWhZoNWsRa+x605wh8m+Li3szEyU7rpV4zoqWSkIA87bH ut/k2Vi37RcULgWjZ3HLx57rkv9Akz/sq8P+iF/OnZnKzfpq1xFaFfo15KXkY79pdz3Zjtjw ZUmg68EzAOLeER0KY0dK9DMA4OLwtVoKFlOKnrFu7AuEvGU1SXVtQcxIEbLLeuABKNImUlQF weeezlV3XFHDLO8Lz54cuKqjOS1q2O1mIBsUcSyOEyaXYz50uWJvXu6U3wQrsRTB/dtuzQq7 LUiZhStH8JdU009kQsDwAGKAs/RLfENJ6HHjmMT6eAwum+OAS11KxRmzLE2CS3uwLrvo+Drm TQzr75XSOGe+XmcIo8lWhHGWx5fu3MuqOZoQ5RKuLtRLshCYN1XV6WuUBpUV3C7EsVMtF2Cr xmSohe/eUGGGvlnT4WvKYeJz87gdh5+xCS9RETGMEizhfeUPsCs5ChoG/qz7andsIID11OD2 h/fVcPQ38iSbfs6gms4G02DlAY+oSt4V2zzJVg75TD2dCoin3/rbPEig6rxzvO0jOr5v4eUd cKhqS/P0XzKVJIvyYGpB3DajGNdBEslJ4i0SmNJ4nkkGduYKVjhezDAXagUYm3iFGcUkXlPG m+/oJqzvWJSuMUORGkAkDkwbvwF4PHamj+lPURqMqm3s7xFwmlyHMx/cy/A82PDrab2yvGoE yfRyBQqXPfVPE7RtgKm5AorKyV3Jymar76sTJXIzjjEz9QSt7AxiYlOSRNlX9o/vT8Jruf6x vQFjlmZdgZ1HE43FT/BcNDRWSW3qjVTjNGcsoPcEu3IrsckXy1D/pjJYRGUoQzNBX1zQUkgH pXsLktYNZh3RAYQ5x3KRyL7toWiXA0sS7GxkZmjkDj0dZGKNOz9vhhkSpUvL74/vj18+nt8x Z+VhwGb8JCOANc7QVcWTIOZS03Ti/cYW9TDqOmmPW2YoV+enx95Qp7GObqZTeinQb4npdrU/ +19I4OkM31v+23xcaSj4v844ghSkGtPxJkTogeqQBIFqTjlU+hTX0cPx1A7mqgiwyA+XDDl6 4nUEx+0R6xmVOxvi+KHT/TptxFxTRq453Rt9qSjSzXoJs+mMFm2tEE1/GfojG7SAuK5Rm6+8 ri3bkAF54wgbD2+/1iTbUVoFTbx3cTKJ0gVBeiwszgqi8OL3l29oDcAfX85fca2+4gqTk6ml wS9Uah5wKqAZilUc4LECFE9XkHWywi5PmRx/ueVyUcgl0mYsusZw9rzaBnr66WIKXMEwM7YM U6K5ml1rBI9SRF5d1fhQ2Lwywc2EpeGX0SAecLv5Be4tSKP7zb/+ePvz4/Xvm+c/fnl+enp+ uvlx4vrh7esPX3jl/62vU2IUwGj1mJ4BLyu4VCjuBplbrAWyhpz8aMflTniBymRwx4QYRerF 0J+tqJBiaaBWx/38sMrywKTdVlT2o0ZrLSsx0Hh7e2rGajpU1tSSjlA/zeHf+HT++vgKPfEj 72TeCY9Pj9/EHHdOQKAx6hYsYEfTVCWQ5oAqE1Hh3mAAYt9u2mF7fHi4tKzemph4TlAetIla th+/y5E7VVEbK/ZA2HreR/SORKO9pt43chTEyUPd84GSBS6gwEUUp2XEvSnoOO/gBAaYOnhS 31UffS2d84u1/i4g3AGnwPurRnyr8mySF6Nj3dUC2hc1umqxzkenmClwz/QIsqw2VnYpFfIO +/L29eP97fVV9udCfn0Bv3y9iyELWPFRgcIwMPOf7om99BHrmMra3Qg68XiFiM15K54U0ySc BXLv5CzYtBzMRU1vfr+9O6tfN3S8Im9f/tsGqq8iqqF0sxWPeR584cw+3viHPd/wCcIn7tML XEHjs1nk+ud/6dcd3MK0tqoPxdCj97f4xxg+1hNBxELke/F+eiI7WYKztltrRVRJ6v7OfO1X jm6XWb5eZ9EKY5OfSZdTaFGd50YFVRznBYtUIMPv/fH47RvfXsTGgSwoImW2GqW/oad5JuXC rhuXfg66Q6m01Zy5/mDRtgP8CUJDXdW/ZF7cfRXY9Ugb7ptzaZHgsKo4OS2zyVOm+wFKanV4 CKPMqRMjlCRlxIdMuzmiK4Fkq1v8AE/1b4Ga5gQ671BmIvC739rHWGY0Raw7ZzlDUJ//+san E9bN00G9t5PLQ2cPtPPF2J+1cRZg1MhpY0k178VJDRIkvthtg4kOKXwVFSyZO5ikHepKpwxd XUR5GHi3GqsB5Tzalm7DGu3W1w/tgTjV2ZRZkKDviCg4zPV3dCcq/7SQnk9OdtJM5csNZBMr q1m4MvNpujyLrzQS4EmKuUbMPZqlEdb9YGu2yM4B+9QPjLPmqVM3AeTp1S7kHOsQM9joeORm LY2e3nTS7GlVVFr2EKLzoZy4XhvmCmTcSDcjtsEm6pQKQQV8enn/+M63vavrONntuL4EhmN/ A9LWvvg1l42Wob5Sv3V+DsHqoTaa8If/fZkkTvr454cxQTinlMAuJYtWurOriZgXSHUsPKMO mDOH7XC/IGyHy8lIffXvYK+P/2NaiXiWk/i7rzwPr80sjKLhG2ccPjZIjGbQgNwLgFNjuTFC 0xscYexLmlqts0Co25DOkYua4onRqWRyhP7E8fVWFDzYyqlzJMHoK4Armp8kzvIQb7C8ClY+ JMz0CW6Ol1lMFg/JwH14Q0vSyBfC4szzwqLONkVSwPQAjcuUi2xEPMZNem9VmqGI1snndaFD anmZoWzzwdU/4BT1+pTPlaOusElSu8Xf7Jx4+kq8xO0N/wThAaiPyygaIhk1927TSro3jk4H twingJfL2jwJwqQsIKweX78w++d00iQv7xqDXwIiW0+6JHBLFZFOnEQzDGroTkSI7pIgDVGe qbJwrThfrxLsxEqxFOcoCI0VRSEwIT1+mzpL/g9YMCujwRBhFWAbNKTV9P1so7ulkQNxiCqf zV0EV1K9gGkHtsF9eecHy+Fy5EOHdxkMUZcP5EPTI1FHUMlRfR9nCBNfUssPwWLgcl+YGYKT hUQeJNLlKlWRmnWQxgWEA4IeBEMBiCOmgkCQ9bxVq7Pk+PuAisW2uDoM03i40rzNEKdJiFUR WmKVZNm1vqmmt3UEb5qkaONYsrfRbOvMBfigWoUJ0gMCWCNZARAlnqyyOEGBxFcGVwrwMpJ1 jgCMbuJVhrWgVCXW14bojhx3ldzpViE2yJX78ZU8+iEJYmT49QNf8xKsYseChUFwbdZN+iGW mGuB63WCeX72h2RIw9xdyvdnitobhMyqRyWaCFrYtGU7mCDxZBnzOPUqpko87n4o7uddVz62 e6Hsp8DNs8U3ZQWf+1o+ATn0NRpeUDGqGIS79gQ3t7vLuWYV9hE645bUvQx/dbUSehIRxUy4 HF5N4s8dYbxaX2CAC9UXz61qnW+pnJ5TWZ22fXWnOK/Wu6IgqOGPrygeM6qYUvzdESV8YyKX rss0DniGONllu3MpdrBPRT60Z/VU1SL3KFCeqotj2elSKObVPrPDbQRhZYb8AgdW1lmhBZ4f P778/vT22033/vzx8sfz2/ePm90bV46/vpk6+Jy866spb+gtxzo/Z+i7iMPa7aA30LJiySVj xjA/AOnN5Dbv5MHkASK0PGna8BdGq8M2Cje0QLIF82qQrrGOlsIqDnAx1QWm0AYu8FDXwt/I RZQbkotMdmusJc5YRtOKi7WP8qTDmmg5cCJjGo/jp0xydl3lEo5/V/pDmvwu59I8oaO7jk9B TsW78EKicEqjLFTT22TzSC0e35/MWJds0xVXasLAB9d555XpAR6AxQ6ZB7QpgqL5kLRg3jaE Gc6yGns1DrVH71uYPMfnm4ISpLZANn+JK7nwjosxKQHQKu0rYK4+km5HSXEp6MGDGjq+RPSo 0cL54dfvX8Ub7N7gEHRbWksrUJTepn+RoLM4w+PdTmBkKFJwUUkeMES4kiaSkSHKs8B3UCxY hGP0tqnGoqVOnQS4b4oSvcPDOcSVmUBXwAQVM6qLDMcuCkb/hZgtXJIrqx7TasUXC6VLK20m 6hHyIJtpWbYvwCgEM7crMEWySmOHZoTSEDTjSAAo8LYBnLFCBP3ChMB1e7TbbSJitaZdlEae 6Coc3tfpii8qnutr+wE8JlhdaF8BNF6OdWIBedV3LI0wF1oA3UMOoOZ5R3M0+MCCJmiiFA16 KAeC1NWsJnKOQxaq3SGSah57LPQ1Zo2d4XwVO5lxHSpD8srXkW84OfrgQswt4pDGqV1/TnMS KwnArsip7qpeuEJ46gJ7mZ2oK7YJH9u+lpi1MCNRXyRDknvT3OaB9W3Tjm4S2fIktJE7q1dZ Ol5bshhNgtBJBkS/8UCw3N7nfERhKiLZjEkQWKs12cShj9gOnVODgXbeKgtTqJ1iqC+ExnEy XgZW+C7GAWPTxeuVr8GlTQXJu6H4abroeNJQgqp9XL8PA92KIDV+05dA0jLf1NXOGx3qOnCq CvQoxIwy6kvEEaqVW61OTj35YccZM5yndnbTOSdKjXCqaVycEL4MxtpRh5JYXUFAIeRohABT 90HcBOcmjLIYARoaJ7G1XC0HwWbb3NExx51HRU5tsT+QHeoMJfbv+ejdJWK7VsFWWROhN2rh g2gSBlbbAi10hog47cVNizOMmxUneOXdnOwj54Xmdq99Er3QUF55QK0vhO2eSj8Ee+dXyGSg QtNEziRnA2z4PqGRL0hbZwCci3KNX5BRCty8KOuevj5hd06sDqI0PW6+VGU9grAAMlTmqW0G sjM2goUFQrEciYg7yo7Uc26ysIOhRthp0AQOOxdBdsZSsEAgp+fm4mKCnsMXjalMYn2b1xCx iXiydg4rHRZN6EYyQNxgcC4YUf+EC41epvMswr7b9UpeRzL3HpOYLLo4biGxB5FRMzAk0ld4 C0HTbMkhiZPEMw4EmqOH3wuT7TGxIDVr1nGAB782uNIoC/G70gsbCAkZthZYLGhzirMbdB7Y e6+JJIkX8c0d9wzIZZG7lyc9B9MMCwi+8Gi6A5IDoEn+aQ6WnmFjiWcCg3ifrnBVzeJKrw+c ReXAoQTtykXn8BRrbZWez9OlNxtbx97cueYU4O4NNlv0SQdMurB1fdHAs9xXEQ5yteyzehRd yLvx+hJEu0RGD8Iy6PI8wa4VmyypZwGk3V22jj4ZA1wHNN/UMjGPk4jJlHy2zkvt89OKrNGx CO6hxiVzDdrmY+BBjg+VdxPsTnxR/aRCgie/lgF6SqnxnCmeuCes21R9f9/VeoCCCxngFsnV PC3tVwNsHViDhlUeoJuPfQqqI/QUeb6dRbQjwfWdAHgYvuOxhOZZivY0a3ZcYvd1GuPqdZB+ tk1xrjzCBVCTJztgVeAaVhKmcYRXQWmvV3MHpsgwtpgYXxHQNldKrx/D10xN78WxMEYXcldR tbA1Lsy4SquBKQUVaz7XZxcTyT0XOxaOWadCUkt96bPkyrdXYYXPIFQsZiSNcmjhaUD9po2I gymw5T08PYt9FkeRzY48nWcA/ocxFdum7E/i7iOrmqqYT3zo89PLo9KlPv7+pkc+nGpKqHjq w66sRGUEpstw8jGU9a4euNrk5xAvlfpAVvY+SN0c8eHCxU1vuPk+hfPJWlN8eXvXA1LOzX2q y0pERMeVe9lUrXqSAjuePW1cjdYtUr5k9/Lby8fj681wmp92/Q89H3hnkJSkg0iyP4Wp5gjA wekxjQutD63n3QnBVsGFWsbHArxa2YjXMvBzZc58bJbnSufaI7XUx5RzCiXaSIQPnjtFnoo/ //Ll8Q/tlr6gkq+Pr2+/QebgGY+CPz4tNUCYSh+qfxivzkl/02iike1aeiwi9BijH+6Z/uTW TD+mqWlFmpGHNAhwS5JiKSq+PWArlGKoijDN3UJ3TZ6GWJl0bMIwZFiUKMXSD03EFe2jmyv/ y27vXfpDGcamGZxRJlP0WMhSSLeJimg66+vsmMQYfiU+MbATFprCszau/hP6/1+PxoD5NzZc 2NuvH+IG7dPzry9fn59u3sVzyd6ho9dRr/9p1SxrE/L6i5aFzWY0Il/5rmVjNID2cCF+ndac k9o0ffz65eX19fH9b9+EHY4HsX3JxfD7nx9vf7z83zM06sf3rz7+6Z0/Z0kW2FCSMI8M86WJ 5tH6GqgLPm6+WehF13meecCKJFnqSylAT0o6ROaps4Wlni8RWOzFojT1YmHsqSjEx/1/yp5s uY1c119RnYdTmbo1Nd0tqSXdW/PQmyTGvaUXLXnp8jhK4hrH8vFS9+TvL0D2wgV0zn1IbAPg BoIgyCYA19LeKfIc5UZXwS0dx1puYcWBOoGCy/o97MrclwU2WizAArRxIDh5rr98b55dy2C2 kaME1TNwhnEl4Szd6VtUbH2lu+t1VYM6d+h3NlJFbbBxHEvvaua5S4uYsWbjzi1iVq09x8bl Uwq6udpa5CVzYxeGvbAOjFOEji1xHaUOZD3xcpmBdpptn6+Pr1BkVLX8Jv/l9fbxC6bb/fBy +3p5eLh/vfw2+yqRKhqubkIHjHGrBgQ8bLT0iUHgD3Dy+bdFEXOsvHR6oO+6zr8pqKsCUdZl LcBh63Vcz10u4tSo77gf/H/NXi/Pz5eX1+d73Jes44+rExUukSv/Xu9FXhxrfWXqKuLdytfr xcqjgGNPAfR7bZ0X2aA9eQtX5xsHyidX3kIzV9cPAj+nMGVz6vptwm60IS337sIzZwqU21oH hr6iukbKjV6nmGiTcqMXx/3HWc8NIHRUPnIPpJ6vyckhqd3TRi/fr/DYNborUILLZqtQ/0mn D3xXr0QU9yngipo5nREgRLpsN7Xn6HQg7NqNDJ/3cO0HLv2hd2Ke+rlglMFm9sG6OuQelrCx Gy1zKHUB04/UW5m9FWD6unaUPjKDTL9GtQWY+gvF33Aa8ULjaH5qTGmFRbPUViouivlSk4WY hcj7LKTBkQFeIZiElgZ0Q8xqPwbq+p7b43h60voIZxVqMc59QwZjDza0ioAu3EQD89PK3KGA ninF+llJnFzwJFyMCdVR7KJeOVsFDpfxWpd/wROPnG1dGwo1tBoaDZoa2szh/P99FvzAxNu3 j3/cXJ8vt4+zZloAf0R8y4ibg7VnIEaeo7rHIriolq5HPuocsK7OsDDK5ktdKaa7uJmLUCMm dElC/UDvTLrTczXoK8zRFHTQrpeeR8E6YAaxQfD9WUTHqOP/XI9s9NkD8V+bqxJVmufUShPq dvnP/1e7TYTfn6kteTEfo7oMtxlShbPr48PP3u76o0xTtdZSTgk0bSYwJEdk0aBR/OglDsRJ NEQvGk7As6/XZ2EdEPbJfHM6f7SqzjQP9x79hXlE2807QJce7Yc6om1qGT9bL3Tp5EB9ugVw rgssHkipR29CmOv1LjVEH4AnYxUGTQhGofVGB1SF7y81c5Od4KS81GScnzc8QzD55ZSmafZF 1dZy5FJxXxIVjZfo/dsnaZInxk4cXX/8uD7O2JAcZ/YhyZeO57m/ScGtzOuDQW07hrlVCkNQ PUQYZwWRBvt6fXjBQFAggJeH69Ps8fK/7xjJPBX7NnnnCsS87+CV7J5vn77f3xFBs2I58Bz8 IcKIxXLsL4TGJWikkxmxkeN4LKgso6B1km7x9kbF3WR1H6/QhG9DEiWqg25kNUYzL4u02J27 KpGDTSHdNsTIUqMXGIXEVE5BmhbRn7B1meg0CXiwrprHvFCECGgwNmYHR8j4vfRlPcciOYAf wnZJ1nFvC8vYbTgsV+/RfX/EjrGRLo931y8goKC5vl8enuA3jLL4osxwH20TDCBfH4+INZi6 PvV4cCDITyW/YNqsT2rHFGT/UEMKO2Trm7AKqkwJXduXk8FqVw+7hA5SwpHAP8sI2jhVe11F QYU+Ufs4YwQmPcSaUPUptHdlq8LLIOcRZPsd7OXp4fbnrLx9vDxo/OeEmE+xwytMkEz58lAi qNu6++w4IOHZslx2ORjIy41PkYZF0u0ZPjPxVptYn9WJpjm4jntssy5PyYPoSNyPmqhGXHa+ WzhJWRx0N/F82bjqQ/aJZpuwE8u7G+hPxzIvDMgHIQr9Gd1Gt2fYz71FzDw/mDsxxQyWMkye DD8267Ub0e2zPC9SDMnqrDafI+pJ4UT7MWZd2kC7WeKol4cTzQ3LdzGrS3QNvomdzSp2FnTL oFFi7F/a3EBt+7m78Kl412QBaH0fgzW+oavOiwNmHRSSQkaPIml9f+UF1KAyTHOOgWiDrbNc HRPVvX+iK1KWJacujWL8NW9hZmmHAKlIxWr0+d93RYNOLBv6BYNUoI7xH8hL4y3Xq245b2xL XBSA/4O6yFnUHQ4n19k680VOz53l5QlNeo4ZrJ8q81fuxv0FCRybHJpjVZGHRVeFIFSx5dO/ tOSCrG5B9ms/dv34/WmdaJP5PvCoDkok/vyjc3IsS1Shy/7jZtfrwOngz8XSS7YOySKZOggs LBqJii3U80seJeym6Bbz42Hrkh92J0qwWsou/QSSVLn1ybHIdE9WO/PVYRUfHYs9btIv5o2b JuRLIFmLNiACsLbqZrWyMEkhmZMkRY4haU4LbxHclPQ4mrjomhTk7FjvaWt8Iq3a9NxvM6vu +Om0C+g6D6wGa6o4oYxvvA31Fm8iBmVQJjCPp7J0lsvIWykGsbZPysXDisU7cmccMcpWO9ns 4fP9l28XbdflMXQNUzbaA5MbzFIDBpG5WQ0qHUA5D1BiGWoKleCiT5uN72rTqeLak2YG4lbb YXYPDZ4luwDDrGK097g84avMXdKF66VzmHfbo95TNLzKJp8v6NsGzrsqiDGL29r3DMUwohbG cgSDEP4xKGVfhIDfOKT74oD15sZ+KEyJfjatVTd7lmNQusifA6swp6illaao9ywMhBPOyteG qGEX72JXelc1PHkXaJCtlkY1sMFsy4V1awZ8nftLkNK1ZudhyTJ2vVqLLYU48S4JNEWQn/z5 gnKL1MlWii+Mgo0NRaIU9Em3y8H8D+LDaukaKlVC4TnIUgFfodk+LtfLhTZ80j7vgf3JylAp pj5QO5U0eXBg5KsNHHQVlbtWH8guc712/s5CSHHVUq9VFdMnyRt+IO0+tay60c4XGGJZZGEY NNz2+fbHZfbX29evcGiK9fcZcEaOMsz3KulKgPHXeGcZJA9mOK/y0yvRXawU/m1ZmlaJnHGv R0RFeYbigYFgmAovTJlapIYDNFkXIsi6EEHXtS2qhO3yLsljFijunYAMi2bfY+hRhfCDLAnN NKCN3ivLR1HIARu2+FpnC7ZjEneyPyE2FEQ3Kdvt1c5jqL3+3K5Wg6dAHCom+CPn/fsQ9J6I iwrl20NS0zY0IMe0tJZxubHmF49A3eGXw+qo3VJqHnsgn6xREkJYL6dmsVSNYMC8E4oKsL3z mVYmS9AcKjLq6Ik9097gIKjGTx5KMEtyIXFGhrd3fz/cf/v+OvvnDM4xZrbusS94yonSoK77 JDZEf8apVwjlAU0UN03sLWl3golI+Jr+gqg80hciE4XwC3u3w3pUhwnzKSqy7qhke56Quj/n hAli9MVw6MFz5IoOayaN3Z87AVU3R21IDOwhS7I/o+O2yT/UuRXZkBaaZKrssPScVVpSuDD2 XdmNSBp1FZ2iPKdQvTso2VaipIL5hcAO5flTXlrp9BvqJNjFTju1900Z98XSw72izZXtQ+R8 gC3FuFsGoNQ2i6eolE0F54Nmr2CrQLFw2z25S2E1U5oA8SHn6XKHn4uwgHFNj/TBos9tPFbO oVHU8rO/pZUgquSU9yOo226Nqkr6gmzEsUqrSEnhySEtbIepxq4kvWG53liYNEVJ50LlaLYL k1x0UgJHe7zu0GEM/tKBRVUHen+jot0FGiwLoiBN9dL8eZUGKz1XfRzDoTDehqHsh85yQZtX nE6kz7biQW52RY53S1aSBD8r2PiFaaHV/qIHQZHpsEIDfFYSJgqxzEJWaSK/21aZPvRdCgZh QeagRvS+SJtEioct/ibEDkzZII3ppC68ncZfz6nzKyKh+0aOVg4/2yS5jXgWCr3AMUhBIC1l Diw58is5gwfnyhamD9EMg5mpnGSNBvgYaJk2EdgcWb63ZGUWw85rsLfo9LJIkEZDCEoZmMQ6 IC8Omkggd9Qk6jK0iz9aEPBHKen/Ea5OOIKrNgvTpAxir7PEgkaq3WbhvIc/7pMkfWdFgAnO Ip7CXF/wKRpkOsez4MwDgFlqAzuZr1CjGIuqAgMC2nqBlzSVvsYw4SMb5FaC5w3TARXb6W0W FZ2VGXFgC2AsR1iaytcUCWznGNjawK+80dsrkyZIzzmd9oETgALGrdyKB+XE7wTJiKWcosKP QOrYKzSc9eVTFVEUGD0EVa+xREPzG1lL27XYPCTTID/bmVSXSRL3kVllcJMEmQECAYUtPtE2 SehLmba1PoiKzl+FWgZv9YNa3pFGkLFF1llQNR+Lc9/EMCgJahSBDUxTAqAK60TXFnihtct0 GOZbNNN4yXA7M1s0l7qynquV8vTfhoJmDPNAWyf5xEB6Le18TqpC5ccAMXjx+RyDfVRom6lI X9vt25CERzBWOGToSW65RZSW2vRnYEl4nivbxJTtN2YjIY1SnnpdN0xLGdBTDDlOpQQmcoVT kkSllZGzPCcj05a2nNFOLjamgpUbkLpT7COmXleo3TV8BLl/VZFlqt5FKGxlGIuYWtOIbtOS 9dlhlWLwa24LM8n9vSrcyYK620cqK/WKgjwHVRklXZ4c+2OyotvEW/L7l7vLw8Pt4+X69sJZ bzgKCrcpEdcYTzms1oa/hfpZznhW8V6VKB2xOxLKjG92aq0AwCyucRs1qdEkImNW83jPyQkW cB6kqugPVNs6U4EwLTWfFx5juw7N6eTerS1o0TwWAan/9GR0NiWu4aJ6fXmdRdP7pdi8QuLT 6q9OjoOTZmHACSVPn1MBLSNMRZ8ndVBTWCOtJXfpI6vj0ApDHAOzuqYhsE2DAlPDMSbWJ5Lj tzXlKi03aelRcWo919mXZq8waL/rn0zEFmYQypiIghzdAFWjxCoYqWvK0Op07brvzE61xjd1 m5XZKNaqxnkdoLW5JhHMfez0tCCjOPURnaOH25cX85CNdUxJpCXgMda43WTjsT2HPem/Z3yU TQEmYjL7cnnCZ2+z6+Osjmo2++vtdRamNzxhdR3Pftz+HDxsbh9errO/LrPHy+XL5cv/zDCP olzT/vLwxB9z/kDn4/vHr9ehJA6G/bj9dv/4jUqczVdSHNExNgHJSiOYooAe+qkkd1lBgjF2 rbUe2jgya7X7hfLFG+c19XCTD4LPa1zplfYIa1cEfhfEOzXPz4iKMUpYpSUGFzkxH25fgec/ ZruHt8ssvf15eTZYi/9hwlz1wC90PpezLIA5+3KR3C65cLGiK3L5soF35SgHWh0gfAszlD0i 9FGbFGLcFs5winH4gxiroxZqdlZTVgeU94h+eUa/xJPN2y/fLq9/xG+3D7+DDr9wtsyeL/96 u3++iD1RkAwGAz4jhSVx4QlIv+ic5w3BPsnKPb5+tA/RU4Zo1vG+SHKSpgqiG9hX6zrBQ8KW vrzhErxnYHol1GOsQQOvZBfTCeh25oIZ6EU0a11GCTox3eRYBxK7uOMMcL6T6rCt65U3vjVH WtWmIQslGZM/Yvcgz1dBQdw28s0kV3zJoU40UyVNdkWjp9PgCLuaGq7b4Ocq8m3KJTrztAfa vMTDnYFS4baJGb9ksxmOeD/aP7qQy3J4l20Zz1crEohYqgDbD34c1LcrfKD2cYKMghF6YGGl p/WSh1Qcg6pihcFB3CytVSd7zNzF99MtOzWtJTmHkDK86N8erQRnKE1fH/CWPnMOn6iHlFzN tzyGgbd0T+aeX4PtC7/Ml45tmgeShS+nLuKMhWN8BxPG3cd1KzhoTDsGz/62y3YuUSe8W1fr aZNglyaiNtm6hP8EcFxa5fefL/d3cAzkm47FPtlLu0fex104RQk7qNXz1BCHUD7yNsH+UPRn GR0kdE14Hs4ilB6Zk0/DcBtcOX2/lGOmZThKL8kNutdntgRtOkm31Qz3Homj7/j3GI/A9jZW l7cZHBS3W/zC5ElzcXm+f/p+eYbuT8cPfTcaLOiWDHjPG6soBT/Yu5ZC5SlQwidwk+PQV6TB 5sY5os5LJOXGuHXJZdi+bb2FUFo0ppoGtXk9gOR50njeinbHlBgukoTYdmzuEyLMf1WIyHlQ F3EYFVlZ1MrNOp+eDsPlaIeVtktQ6+uUeZQZhdtQZIlUoLqwbdVrGAEiTxHiV738AO17oN9W CFwSUVlLdZKpx3QtVQ4blH3LHGuy+CcoROW+yK0m5ki1BfbDJFhGbDJTQhlclXATe6eUvcKI fHq+3F1/PF0xO8rd9fHr/be351viygWv/9TqEdLt87LfCNQNqrEp/J0pOELcDTFpcx7DaWtc 4EwYvR0bmTGPNJmRhl50mJTN4Su3qqaCI3GUUHMh/5Lt0pXwuSRf0PGmwDTt6iNr1C95WWaJ cp9kmP+M+giC93F4CzWNj99J8fcsFKzT0r5IGP6VJipS1XDiBGGFFk+OJub+iP5k+S4xnxNg litjF+flg3zueMtNoLUb1HNfJHtRoJiYc272Icr8OZnAfEIv11pd/EGOY9TFwbQKn/CUgTVg fTmT5AjceCeqKd9xqY2Ao0WUUq0ukXVeb6GHao9cOIoA8awICwK4NHpeLpVoQQNwyePL9rfR Ok72Up2A+kAQ6HsmT8r1krSuBqyWsmEAr8k30xNzlvooeijFH0T5c71AH9seUw6qt+kjlozO yLF69p0RaHBcxFaVIXKEeE3sY29N+lwJpjTz5Ubn+hT8V4Y2UYABOnVoGi03rjH9VBDnAaEn G9AXjuwtLMpIWVlkOD6pgzWjQVk9d7fp3N3ofeoR3ml0P58UDr82/Ovh/vHvD64IpFbtwlmf du8NM9dTH51mH6bvfL9pKivE01JmjP+dDNBirOkJ5tKOxxD8NuaJrCTEF6BJwVgZb2YmEd3d ZXN34cgMa57vv30zVXT/FUPfNIaPG5hBsLLgwDSq90Vjwe6ToGrCRP2KrVCMb+fsbBtIo5LO 2qIQBWASHFhDve5W6PTQ8wpy+EqlTjbn4v3TK97WvcxeBSsnGcsvr1/vH17RZZabBbMPyPHX 22ewGnQBGzlbBXmNL80t/BOxTq39LIOc0VaDQgbWqxYnlK4Mn/rp+n7kq5qLJYiiBJPUoR/n +c/pWd/t329POP4XvP98ebpc7r7LrsIWiqHWqonwjCOPF0HcRCG6H2NGNP45Ui4xQc1jtfBF ygLzgT4AuyTfKQ/0ETZm2QC7J0/SWsUWyoOfAEPeBl1W77AJsr/8DkENzR0fu+DEEElZjNs6 7ZJY/irEsh1+8OhUIPePYgCTvWb6ZJWfz/mnrOziUhQZW+avhfdYqMt2GXXCmSi0Huu9nV6U wJFFG/3I9Ojh/vL4qny9CepzHnXNqbNyTItFME4TmOxsCpKTBWG7NT8589q3TL0sro8cTnZf VNRlxSHpnTPoXiHREClBlQnEgNordZkc4biNNPq5c3CLUccxrrb2NN239jC8X03lb4j7eIGi ZZhtPVzuDopQUEeMWS+W943r31hes0MZjz5bl0HFgz+X6ENDMI7D+yMEWAZ1Hci+g2XvAl80 I+4f/5gq7wcMmzMsO/qtnExC3V5LeCOBp63PrbpPwJ8g4NUBj5ys+kSfYYEmxtgPJo1cS9XK xzQg7MJzyQ9jIo/7hEMlJIVklaCyTu5jHoDFpbhE9eBDXFIrrMeGGF5DlpoezvKybcwmMqpd AA5OTt2kl1UiXL88P3Xc30RKFNBB9S90GFFG0sM6+jrmwC92WdHI92ACWAmHHRmmk/RsU2B5 YpD1vZz6xKH4MLLu3/kQ7mX9C5m75+vL9evrbP/z6fL8+2H27e3y8qq8RBoiw/yCdGp+VyXn sKVXIxxkQFGSyZLRY3WK5avP1eD6Y0K6kpVyEt222mJGqaEqRecJPQSbt+Wx4rEuWZ4W6s2G 2Bsernd/z+rr2/Md6UnFH6Lih0joTuMvQlKVkpWMDAhYGhZyttSBGdlekoJhQ1dI+7LaZxQG o231QOK7yyPGTptx5Ky8BUuQB0yrzSn/FanaDjdsprzg1eXH9fXy9Hy9o9hVJfiYsASWkYwi CotKn368fDPvdKoS7Jtp3PxPrlh1WF7rEG5N7NQHpToGATp2VHRTn5W+SSKPri5H9n+UXUlz 28iSvvevYPj0JsI9jwT3Qx+KAEjCxCYApChdELLEthktkRqRmm6/Xz+ZVViyqhKy5+CwmJmo fcmsyvoys+9+c6j9v/Ifl+vhpZeceu734+t/ofr5ePwTWr31tVJANy/P529Azs+u1qA14A3D Vg/U3s4PT4/nl64PWb5yrdmn/16+HQ6Xxwfo9JvzW3DTlcjPRJWZ8t/RvisBiyeZvvRC6IXH 60FxF+/HZ7Rrmkayj/eCwqdGJ/7EkNQk7gDttF/PQRbo5v3hGdqqszFZPh0KoFcG1jjYH5+P p3+sNHWFeedu2anCfdyYNr80wJr1Ri67y8y/aVRY9bO3OoPg6awBlykWrMK7+j1+Ens+qAk6 jBARS/0MlzO8Mef1XCqLHge52P1csokhyCnFNEXQYkBZMavGeDS27VD6O7CDmYT9feG2npL+ P1cwHmvvNs8ckkq4FGAffREuWWcqxjIX85GuDFecDk/ZisuFTWtZw+GYBxJsRWTc5A/TN0OT VZy0iMcD9uCxEsiK2Xw6FMyneTTmY3hV/Pry3GolYMDkQVcDPZIS6LRJxllEAU0kQH3SUO5a WukuWLJuzmp00y4nXLyRqMJZ6vzNMlhKKZ1cHWcw6idy1Z/0Pot8Y4nKXHOcao2IQ2wsjCFz y7w/NiWqb/lWJQWW86OeBuLx8fB8eDu/HK7GjBLePhyOxmYkecqlYNsVQY/SuojEYNbXfo/6 1m/zGxeGqTwYCnmqLu8Jh2bhCSOYG/R75vU7cJolj4W0QY4e34S8XVDFGHK+ubIzilpC7ANj EDQ8fCVQ85s8Nvvc44qz2btfED6Nwvi7Q4cCBEeRmI5osMiKYMTNBeJkon82G411nPwILzx4 DCTFYwNly4AKNP+9O3FogfJiMxvSKAVIWAgdPNAYkL+RiDkIlllhxcLSDeu1PWSn/fkg45dQ YDpzvlLAmvQnZaBsEIEQkboJTyXnc+4eTniBPH0TnjY05zhoV6lODWNHl/PjnR8mKVq7hQQe Iocu+ymFGApi4ez31dftAhDjAQGirnBTVV2F6TmGheuMaEARSZiNDYK+keDeNWQ9A4GjQyFF bjocOXb0BXzNqiIhmoUlcnF5P1AFZgVise2OgKliAHa0RO7JDT1KPPuerJB9158NuA8lMx8Y cDx1ePGIz02GGR+23d+a+svJoLv+leq4t/j1BPloMtDpIgFnQVmmoMy4AmV+7opQC9dlf1GZ L6/PoHXqr+ojd+SMtY9bKTUZvx9epA9bfjhdNP1TFKFAN5j20Vc7sSTLv08qHts0i8ifsJGA XTef6at+IG7McHZEV8ynfdb1MXe9NpB8awFIKr8PKh6+WKRP+LEOQYaYP/kqpYt0nub05+6+ DiBfHzaYbacgFo5PFaEHHVjBFutAB9XGpDQK49xWZ7daSPv2jE2fjpkor5LIq+1E2cJ5Wn/X lKm1YyymsQ3qCfK8qit0nPBzTwW90neBZiEe9+nVBYYI1/V0oIxGHCIqMMZzB68S6ftnSR1m RgqT+aRjRHhpgsgqdMHPRyNHA0SLJs6ww3UEltLxgLuhRcbM0dfY0dQhSzasUpDveDwd2KuN Z16zGKHu2EZVDx1hRDy9v7zUuNK0jy1ehWR0+J/3w+nxRy//cbp+P1yO/8F7cs/LKyx3cjgn j6serue3f3tHxH7/+o43FjSPD+WUs+X3h8vh9xDEDk+98Hx+7f0L8kFQ+rocF1IOmvb/98sW WujDGmrD9duPt/Pl8fx6gIY31sNFtBpMNHUYf+sTYrkXuYOBFliaLktm+uouS0rd0TVKt8P+ uGshqyae+o5VWyWLaq01u1gNa+xTY1TZdVfr2eHh+fqd7A819e3ayx6uh150Ph2v+tax9Ecj 6ouO1nJfC7xRUTTESTZNwqTFUIV4fzk+Ha8/7M4SkTPUAieuC33LWXsYCIRTDoHj9DuNifU2 Cjze02Bd5A6d8up31enkjm3bEUEgD2Cj4yD8kOFoXWZVXE1+mHVXdHh5OTxc3t8OLwdQEN6h IbVRHBijOGBGcZLPprS3aopZmU20n3BeXUG8KwM3GjkTmgqlGhsJcGDET+SI104VKEPPuxro YR5NvHzPrpcfNIhyjpEoTe3gIXvGF+jxIRuqRHjb/aCvH5EIjG/G6TrAgOlGzjhE6uXzIW0V SZnTPhH5dOjow3WxHkzZ4yBk6DumG8HHM36IIY+NGwQMzSnRRR/Gsf57MiaDe5U6Iu33HZMC le33yfFLozfkoTPv02h5OocGBZSUAd0sqTUfWrgSFSfNEv4JzpdcDJwBG9Y+zfqaY2NdKOUO Sg2sbEzBgMMd9PfI1YoCS9oIoxTy6gCyNHDwOBGDITvfk7QY9nWEvxRq4PSR2rF0DAas9yoy RrpVPxzScDowg7a7IHfGDEmfo4WbD0eDkUGYamZj3XwF9OCYNT4lh3oqImFKz6aAMBrrEbm3 +Xgwc3ifhZ0bhx2trlhDzQzc+ZE09Pi0JHPawQzBVuWyuYf+gs7R8C70lUXdBD98Ox2u6qiE XXM2s/mUQ9CVDNI/YtOfz6n9Xh23RWIVs0Rz5QQaLG1cVchswg/9Iol8xDcZEo+TKHKHY2dE 13W1EsuseG2kLoXJrscL2Knj2WjYydBHYs3MoqGmU+j0ptb19TrX/r81ERFfnw//GCdU0pba 8luL9k21+z4+H09W/zJ2XeyGQcy0LJFRB8hllhR1eBSyqTH5yBLUfp6933sqvuPz+XQwKyTf RmTbtPjJEXR+ly9zzv7kc6n20xOocGCbPMG/b+/P8Pfr+XJE5V8b8c0k+bm4pp2/nq+wgx/Z 8+9x1wstL4dpy/s0oZU26jLtwGCD/YpbzIEzpsFvizQ0VdmOErO1gVakGloYpfNBn1fR9U+U PfV2uKBuw+jAi7Q/6UcautYiSh12EfPCNSx9+s1iinFDeTcOuuv6rJvmOqXI+IGbDioDgJg4 4WBgXVlQNqxS3P4Y5WP9/FL+No7OgTbUDkSrpagbpbAYj9hzpnXq9Cck6ftUgBI1sQjmgmP1 TKtznhDWgp0RJrPq4/M/xxfU93GuPMnorY9Mj0vFSddTAg8j5QSFr+LLt627GDgdIz813Ifa 89qlN52OOg5z82zZ53avfD/XFY793IAdxi+5eYbb91CL77kLx8Owv7cb+sPmqZxlLudnfDbQ fS/ReMZ8KKlW2sPLK55w6POOmx6FH3GYi1G4n/cnVJtSFPoEqIhSIxCUpEz5wQvrdYdyKFmm 9lQv5kxF6vy1NyvwQ20JmlZ6G32AM4FcUUQYvsJdMG2AfHR0XhZGPvKhDr3eQGJxG1qECu9R bb/ZjYxaZSOJAQfdxogCBXnSZ4PohCmd49xU86Gsb2oKd1vyHp3EQ04bkVZhmqxShNwwcLtg RfIL4j5jua+k67te/v71Iv1M2opV7x/1J/OEWMWIq1+uN8o0RgaMUICzJ92o3CSxkHgEpfEp pomAnwgLViRZxrtuUClPKxvl5CKkmHzIwsEQRPtZdFM94tcyjoI9Bj6qq9SRcd1nGgoAMtK9 KJ1ZHEm0BDPthom17qoSDMvUTjcSqXwqXEZeNNGOO5CbuH6Y4Al55lFfS2RJ7zcF39DJoKMU WXXkHSymWQf03AAzt8/Oc30EkQ/RCwjqxao5pKbwowxTrd0yYePBidPT2/n4RHSQ2MsS+tC5 IpSLIPYw3HTqdvGoQ4bxVe27+unrER/hfP7+d/XH/56e1F/Eg9zOsfHh77iyU3UgipDgzgnj nQo7SH/aS2QFG1766IoZWQ22vu1d3x4e5Y5vgw/kBfcqXr36oKjcNaVcsVQYMww1LQJ9savo zIJenzrahW0OCNMVPeRSHrQptrZ1QWcxLSAHkqYVaqj6epn5/r1vcavr2BSHiJts05A68Mj0 Mn+lhZtMljxdEr2lHuugopViueXKSyMYwY8aObGMNZBX5FSwobobFmFoWISELiRAi87KNRBs SVn46AelExOXasf48BtaZ99iDBCDlvW+3qIjw2o6d/hQFsg3nek0Jj4U+JklbXlsp1GZUMzl PKA+2fgL91KjHfMwiDRcGCSoVdUtstAc9JmrIkhxp6IIFqwNoQIS2gpPCwnVOqaDngP7W4pQ QoStPTvAX2pxp5B7kuoaSKaGt6O6rTvi+zm5imvdsxOo6YOWj8gVIuOfnCIvyTFakEt0KX+P zuv6qlXTygW66kMfsOFJgtAvka+eWRCrOvbQYeNOk2AHBkJCxG52l5oQ41RiB/oMe+GyzJtI Ou1a3fl+K1Ac6c6qzWrR+cnNNinIsiZ/4vMQ6bIuxw46IWkbMWJPVIK3Iou7Kq4kugCAFLeA NY6mfbOMinLHXUkojmOU1C20sY64pMt8VC65vlRMDa5kCQ1V6sPC3eacE3D1yod+jLF7MTob T0Ow8QADDpVeoPUFJyLCWyGj+4RhwgNwka9wj+c2ayKCITBlfdmSRT40XJI2r1vdh8fvWkin 3BXuWuuXivTBxlklonT5y+H96dz7EyYyM4/xvQbfQ5IDq0zoZTQA5sbPYtrItQLSrGD4X92z rTpoF4LM3yBXzyfVk0WuMDAHbpNsQ6WIJhTqPxrIrU/Hy3k2G89/H3yibIywlyJS1Ug/sNF4 0yFv9+pCU+64SBOZjft64QjH6cx91uHpbQj9QhENQIsuIW6WGyJOVz0mw+56sOGjDZFxZ8KT DxLmHGE1kflw0pHwXEedML7ij5t0odH8FxqVvVxBkSBPcFiWs47yDZzOQQOsgVl2+cb2J1lZ H9UMzvqkfKtva8bPKjfu+pBzrqL8qV71mjznydTpWaOPOujGaNskwazMGNpWp0XCLcGgogDr NRlM7oIazi0dduwthcVqOFkiCiPuXMO7y4IwDDq8WyuhlfANEVMA9vKNnTFYsaHxnqdhxduA 00m1ygdc/UH93GjvOJGxLZZkeG/jwNWMkooApkoWgSp5r2Ig1nYysR6T8vaG7iSaQqr8DA+P 7294GGu9y9/4d2RnwF+wy99sEYCz3lTrzU4BxUOHoRi+46Uwjxh4wfeM5Co90qLDr9JbY5w9 FchGu310t6ha4rPtXB7DFVngaqgltQh3sF2x6Ha7Rmt/LTLPj6EgqGmiLlHiM2vX9GG2xHj9 F/Rw1FrzZJt1vChB6CJ54uVniAuuoolxVzwVvklbber3GObRH5/Qe+/p/Pfp84+Hl4fPz+eH p9fj6fPl4c8DpHN8+nw8XQ/fsHM/f33985Pq783h7XR4lkEQD/Lqou13ZVgeXs5vP3rH0xFd cY7/eah8Bhu1PECsSjwWjZNYU6wkC991YfN1wLNYwngy0Clbm5x8kWp2d40ad1lzjDf6Fo7B pFEe3368Xs+9RwQ3P7/1vh+eX3WMTSUOahRrYFVcEa5ESo4WNLJj033hsURbNN+4Eme6k2F/ staw5AjRFs3o6/uWxgoSWFaj4J0lEV2F36SpLb2hxwh1CgiraYtaQAw63f7AtCh1+SbShEQN 4d2y9A/8fZEJW1wXXi0HzizahlZp4m3IEx2mjPI/7mVU3UTbYg0rq5WevitUxObFnjJ03r8+ Hx9//+vwo/co58E3DFb4o535de/nwkrJs8eY79ql8F1vzVTKdzMv52Av6tEdsU2xzXa+Mx4P NF1SHWu/X7/jvfvjw/Xw1PNPsj7opfD38fq9Jy6X8+NRsryH64NVQVfHPa37j0U8rT9Zw34o nH6ahHfoJMZ8L/xVkA9YdMS6mv4NBU1uGmctYK3c1d20kB7bCFp/sUu+sNvcXS5sWmHPFpci 5DR5L5iahNltdyUSJruUK9e+yJm0Yfe/zdjrjXpirEkbGy2MuB7FNrKrge+c6/ZbP1y+dzVf JOxyrjninqvRTknWPiOHy9XOIXOHum8XZXTXer9n1/FFKDa+Yze4otv9CbkUg74XLC3Oik2/ s6kjb8TQGLkARq+8BeQqnUWeMSE4iQ4DvJVwxvz701bCCDNuTLu1GFgFByIky5HHA2ZfXouh TYwYGp4RLpIV0xjFKhuwANgV/zZVOSt1REJQ2yNY+HanA63Ur45qRrxdsLC9NT9z7V5ehMmt jjpjMKwXUvXYE5EPdpm9d7gC7Ymuj/KCW0yRztnB9Xbkc2vLUv7f/dVmLe6Fx3yYizAXHw2h evnnvvX9D7ZrUERSDVewGTsjboiwAT1q5m3C9ktFb1tYDaDzyyu6O9XPgcz2W4ai4I6O6y3g PrEymo3siRHec/UA6pozviv2fV40XiLZw+np/NKL31++Ht7qd0qaPdIM5jwo3ZTTYb1ssTKA oyinWuCtNpA8I/4mKwS76QdDESSsfL8ECOLoo/9IemdxUT0tRcpN2Zr104I1grVl0F3CRpRr O8qEWbezlfJGgrVjGq4fS506WeRJ6Bc+N1PALP5gNcIag9G4NI215+PXtwcwDt/O79fjidnV w2DBrouSzi1xyKh2UAJZbg3iVuqDeRIsqsXBBj+3RDoy4fVcW87rqGO9iYPiHtz7begJTuSj QnYqA20NNAXYFurYVNe39sT0d5UrmuYkanGVkWEvXzUfc+yPPlg1UTSIVoXv8pYy8gmwlc3M xdLfuywmIZFyXXU3yJQzksGfy9U+7KpJK9F5ASnyuyjCcIyuPD9DYPs2N8JMt4uwksm3i0qs vXFsBYs0olJMlvtxf166Pp52BS7eZKtrbHImuHHzGV6w7pCLiXES0xpFsoMrw/2okODtAVqw wnO41FcX1njfLMsQMEjALr4o+1NaghcJQX05fjsp/8nH74fHv46nb78RIFK8GqMHljokoc3P EfxS56rTANIy1veWRCln5qg/nzSSPvzhieyOKUzbDio5WIUQnTlvzl75O81faIjK4blrQUXM SJGVGQKD6n6lwnIZqDiLADReBMQkrVB7PMZ+UW6LINSuPzNP86HLgkhGxFlomJpx0rpNukEZ JBLPNBKpnYnisyyDLCOt4h26G6V7d72SjhCZr9lKLszkoND0NXcw0SVsCwuyKral/tXQMX7S w3uyDEgOzFl/cddlKRER7lKpEhDZrTD3XWQs2FsL4E20nVHfJ10KUh8sGrO2FSCXF43xSpzs Yi+JSJ2ZEoA6iTqrdP9v00IquoqZ9HvcX0A7CLX5BmoqkwZSuTRALWWlR3yOoKUy4pLMye/v S80LSf0u9zPtkraiSjfPtAPCRIkEQr8bNvki486rWmaxhlnFZJ3DOswp5xV74X6x6mCAPzeV L1f31I2bMBbAcFhOeE8Rxghjf98hn3TQRyy9Mi6MpYBe+FSsAlbp3MdFgaOVmyhl6YuIJWtx iUWeJ24A+9XOh57IKF40RnqGdYk6qiqSvcIhXYNjk1DnNLZ3DLanpMJ3Ur2mSgGWCnnC87Ky KCcjWAgMdpVDeZvhexRowoUFvA4tG4oMmWtp0DApSHRvlF027+Q68oEeSpmUkBUncc1AlKyU DlxZC/Qy71CO6hZY+LELxl5G7nXzVaj6nuR2Q07jY1hPtLPS8L4sBIXGy25QMSafRGmgwPHb 5XHpkdqgazM6r+ZFpvU7jIV6NO68PLHH6MovMMRDsvTogJE3cZ6f0uAOeC0ar/QNpXmwZGzu Zi7SKsrXoRcM7SJUzKyTGX7EhH3Vo/dflLdtmPodZa2gSerr2/F0/Us9Gno5XL7ZN9bwH9qX sHWvQlA7wuaaatopcbMN/OKPUdN9lTZqpTCiele0SFCP9rMsFpHP6ludhW3OX47Ph9+vx5dK /7pI0UdFfyNVa8e5jC2IJjAzyCv7OtriYdrap6CaywzKKL0b/wBjaEYvorMghQ5FN3jWbSwD k14mK3LtSmQNdARVDGIYfiFn+6iyghYr/RKiII9EQVdSkyOLV4ciNmoM64brN3HEYL4G+G7Z 4Z4o0Q9ufbGRsI/1K6FaEf7Vpv+NgkNXI9I7fH3/JoNcB6fL9e39xQyVEAm01UAzZ98fkfCQ ZiVzuRDdlkZ72mJ4PSklI/R2/iCTKsHqlp4uNGoHW3lkmbJ/lUbUhJaG1/YYAIDlycgAagX6 49NusBz0+580MSyTmlpgBaVGGhutFN6i8QxQ4/uP/j8DyoU/iyDewv4jCpHjcdoazIe+tbts F7mIQQeOgwIsLWyYNhfJox2ihIuOayiXJLhAIOvcSKqDimO7ZRmZ5etg2REbU/K9YCfjATIF UgLbGOaqu5ZtZGRcWcvoM7uEtrczhx5jQypIph9vI/sTOQcj4zmZWSfS2uwK+UtTSx/U6D3r h/bsQRdYy/SvvEaadNttQroCgnKGQHJ6HCeVHPKlWsD59eK3yW2suxBIapoEedLpQq6SThZf YOlj4+SoJTOk6oWcrVXVQSkMYUmjWu2v0BEOGEqWhP9X2bX0tg3D4L/S4w5DkQ5D764fiZc4 Tv1o0l2MoA2KYmhXoCmwnz9+pGLrQaXbrRUZmZYpik9RnAxX17PZzCdqxB3zcNzWHToycrKH Nk2UBZT8oB4nqZaJRQdUZnDydTaeV94kd5oBY743X3HMOUTqYvHcGscr4PgmXybg49AnKlAk VEPNWtcTp5MuLUafn7o0MWFAy8IrVZX4MfAv6t9v718vcIPax5scUov965ObgI7mUhDItV70 4cBRdtLnk3wUIGuVfTcNw/HRb5T7Utu66ELgSAtEPy54rWzEjd/96lNkn0p51LBAISVJeYfT hV1H0PguV99m4YMmNH7ONE8UxZAynjnbW1JUSF3JTAh3rPw597Uky5I0jccPqBeKPJINYYIb U9Ka8hOfe/C+yzz3rwAQRx4SRSap+uX97fkVySNE5MvH8fDnQH8cjg+Xl5d24zPUD/Hcc7Yh xlYZdsnD3fkqIZ4D9mZ0/8KW7ck8tkMWZjuYdiP+eAR9uxUIyc16u0m6RbjZm22rF0UImIn1 bECMkU0VzmUAZ+R70tUVFMBVnmvqwzQNVpcDdGF/KiaJ9hbq0gbfJTi9cdx31qZF9Pdpm8kD tkmptDSfLMX/4B7HGCXFybbwWbGn9SUVBbFw4nPx/gXnlZyMJwtQttQvUQ0e98f9BXSCB/ir FaMI3u/oam8ADfhsHn5drisrybBRvy+f3qSKkaYJPzWu5AmK4Bx5ECHepSNtaE1IiZVr0iTm nfaakIh9UEIf+M7hIcINQDj34yYv/mGCxqucw2B+q3Tvmy7mcN7D27e3xkprTvaZfYiPth4/ tYlB56SiL3Sc7J4Mc9qHhceNMgEPDhWXi9LrI+rgoaCJKJiWMUmvW9v7kzFS80OZxXL68dyp K8MwGBGnQoy2iRP0EHGMBRk6bZVA4L8807mjcQ6TRGpGsUrmrUbEqSGYbwp4G+QnDkqNVCO0 PU+wXWfn1rN5lNo+n+7wfoTAwfmZosvK/ulglST0jsrH/1oPcIZdYmQs38kSajD+3q4kPkkE eHr4JrAf4rdwzsNKR9OqGgtmmvjU9rzSD/TzuSdOYl1opFELE5/s4WVa25mmotCSGkvDhlvc uyOArwkG4nwE6LBqYG83yWa1zDrHduRYLgcqW+I/ZT5GqMo1t2C0/ejmJ46yeTpq+CCMiq4b ZNyFYg+e8bZe1eh9Ft4sYbC4Ypg0wGGcQ1tTPvCvvyvFN0z3It9lfRW8jbhopfajDYFtaicG SRCchrt6FywolzDrnRYZflN2VaKrLAzv+1K/qZGhOw5QxL6VZWLZww0Cfp3rjJDFcHIseKjM rBBGUa5x8Uen+eoZuyibijQKa17Cpu2xynzRQIYYl+CowgDivVupIAmkqwAr+u0n1Bv5qf2O CPTRZd2z3GkVKsyfV2lC3zTgCI6wl/4chK6MckkNPBLudad5Fb1D5azsDcpsxCn/F7d+7PXL fQEA --k1lZvvs/B4yU6o8G-- From mboxrd@z Thu Jan 1 00:00:00 1970 Content-Type: multipart/mixed; boundary="===============3058331277435751524==" MIME-Version: 1.0 From: kernel test robot To: kbuild-all@lists.01.org Subject: arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:393:28: sparse: sparse: incorrect type in argument 1 (different base types) Date: Tue, 13 Apr 2021 19:44:01 +0800 Message-ID: <202104131951.fnE3mimp-lkp@intel.com> List-Id: --===============3058331277435751524== Content-Type: text/plain; charset="utf-8" MIME-Version: 1.0 Content-Transfer-Encoding: quoted-printable tree: https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git = master head: 89698becf06d341a700913c3d89ce2a914af69a2 commit: baec970aa5ba11099ad7a91773350c91fb2113f0 mips: Add N64 machine type date: 3 months ago config: mips-randconfig-s032-20210413 (attached as .config) compiler: mips64-linux-gcc (GCC) 9.3.0 reproduce: wget https://raw.githubusercontent.com/intel/lkp-tests/master/sbin/= make.cross -O ~/bin/make.cross chmod +x ~/bin/make.cross # apt-get install sparse # sparse version: v0.6.3-280-g2cd6d34e-dirty # https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.gi= t/commit/?id=3Dbaec970aa5ba11099ad7a91773350c91fb2113f0 git remote add linus https://git.kernel.org/pub/scm/linux/kernel/gi= t/torvalds/linux.git git fetch --no-tags linus master git checkout baec970aa5ba11099ad7a91773350c91fb2113f0 # save the attached .config to linux build tree COMPILER_INSTALL_PATH=3D$HOME/0day COMPILER=3Dgcc-9.3.0 make.cross = C=3D1 CF=3D'-fdiagnostic-prefix -D__CHECK_ENDIAN__' ARCH=3Dmips = If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot sparse warnings: (new ones prefixed by >>) command-line: note: in included file: builtin:1:9: sparse: sparse: preprocessor token __ATOMIC_ACQUIRE redefin= ed builtin:0:0: sparse: this was the original definition builtin:1:9: sparse: sparse: preprocessor token __ATOMIC_SEQ_CST redefin= ed builtin:0:0: sparse: this was the original definition builtin:1:9: sparse: sparse: preprocessor token __ATOMIC_ACQ_REL redefin= ed builtin:0:0: sparse: this was the original definition builtin:1:9: sparse: sparse: preprocessor token __ATOMIC_RELEASE redefin= ed builtin:0:0: sparse: this was the original definition arch/mips/boot/compressed/decompress.c:38:6: sparse: sparse: symbol 'err= or' was not declared. Should it be static? arch/mips/boot/compressed/decompress.c: note: in included file (through = arch/mips/boot/compressed/../../../../lib/decompress_unxz.c): >> arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:393:28: spa= rse: sparse: incorrect type in argument 1 (different base types) @@ exp= ected restricted __le32 const [usertype] *p @@ got unsigned int const [= usertype] * @@ arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:393:28: spa= rse: expected restricted __le32 const [usertype] *p arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:393:28: spa= rse: got unsigned int const [usertype] * arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:427:48: spa= rse: sparse: incorrect type in argument 1 (different base types) @@ exp= ected restricted __le32 const [usertype] *p @@ got unsigned int const [= usertype] * @@ arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:427:48: spa= rse: expected restricted __le32 const [usertype] *p arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:427:48: spa= rse: got unsigned int const [usertype] * arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:435:37: spa= rse: sparse: incorrect type in argument 1 (different base types) @@ exp= ected restricted __le32 const [usertype] *p @@ got unsigned int const [= usertype] * @@ arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:435:37: spa= rse: expected restricted __le32 const [usertype] *p arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:435:37: spa= rse: got unsigned int const [usertype] * arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:459:28: spa= rse: sparse: incorrect type in argument 1 (different base types) @@ exp= ected restricted __le32 const [usertype] *p @@ got unsigned int const [= usertype] * @@ arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:459:28: spa= rse: expected restricted __le32 const [usertype] *p arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c:459:28: spa= rse: got unsigned int const [usertype] * arch/mips/boot/compressed/decompress.c:110:57: sparse: sparse: Using pla= in integer as NULL pointer arch/mips/boot/compressed/decompress.c:110:60: sparse: sparse: Using pla= in integer as NULL pointer arch/mips/boot/compressed/decompress.c:111:57: sparse: sparse: Using pla= in integer as NULL pointer vim +393 arch/mips/boot/compressed/../../../../lib/xz/xz_dec_stream.c 24fa0402a9b6a5 Lasse Collin 2011-01-12 385 = 24fa0402a9b6a5 Lasse Collin 2011-01-12 386 /* Decode the Stream Header fi= eld (the first 12 bytes of the .xz Stream). */ 24fa0402a9b6a5 Lasse Collin 2011-01-12 387 static enum xz_ret dec_stream_= header(struct xz_dec *s) 24fa0402a9b6a5 Lasse Collin 2011-01-12 388 { 24fa0402a9b6a5 Lasse Collin 2011-01-12 389 if (!memeq(s->temp.buf, HEADE= R_MAGIC, HEADER_MAGIC_SIZE)) 24fa0402a9b6a5 Lasse Collin 2011-01-12 390 return XZ_FORMAT_ERROR; 24fa0402a9b6a5 Lasse Collin 2011-01-12 391 = 24fa0402a9b6a5 Lasse Collin 2011-01-12 392 if (xz_crc32(s->temp.buf + HE= ADER_MAGIC_SIZE, 2, 0) 24fa0402a9b6a5 Lasse Collin 2011-01-12 @393 !=3D get_le32(s->temp.buf += HEADER_MAGIC_SIZE + 2)) 24fa0402a9b6a5 Lasse Collin 2011-01-12 394 return XZ_DATA_ERROR; 24fa0402a9b6a5 Lasse Collin 2011-01-12 395 = 24fa0402a9b6a5 Lasse Collin 2011-01-12 396 if (s->temp.buf[HEADER_MAGIC_= SIZE] !=3D 0) 24fa0402a9b6a5 Lasse Collin 2011-01-12 397 return XZ_OPTIONS_ERROR; 24fa0402a9b6a5 Lasse Collin 2011-01-12 398 = 24fa0402a9b6a5 Lasse Collin 2011-01-12 399 /* 24fa0402a9b6a5 Lasse Collin 2011-01-12 400 * Of integrity checks, we su= pport only none (Check ID =3D 0) and 24fa0402a9b6a5 Lasse Collin 2011-01-12 401 * CRC32 (Check ID =3D 1). Ho= wever, if XZ_DEC_ANY_CHECK is defined, 24fa0402a9b6a5 Lasse Collin 2011-01-12 402 * we will accept other check= types too, but then the check won't 24fa0402a9b6a5 Lasse Collin 2011-01-12 403 * be verified and a warning = (XZ_UNSUPPORTED_CHECK) will be given. 24fa0402a9b6a5 Lasse Collin 2011-01-12 404 */ 24fa0402a9b6a5 Lasse Collin 2011-01-12 405 s->check_type =3D s->temp.buf= [HEADER_MAGIC_SIZE + 1]; 24fa0402a9b6a5 Lasse Collin 2011-01-12 406 = :::::: The code at line 393 was first introduced by commit :::::: 24fa0402a9b6a537e87e38341e78b7da86486846 decompressors: add XZ decom= pressor module :::::: TO: Lasse Collin :::::: CC: Linus Torvalds --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all(a)lists.01.org --===============3058331277435751524== Content-Type: application/gzip MIME-Version: 1.0 Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="config.gz" H4sICFhsdWAAAy5jb25maWcAlDxbb+O20u/9FUb70gLd1nYum+BDHiiKsllLokJSjpMXwU2826DZ ZGE7vfz7M0PdSIpy9zvA6cYzw/vcZ+wfvvthQt6Pb1+2x+fH7cvLv5PPu9fdfnvcPU0+Pb/s/m8S i0ku9ITFXP8CxOnz6/s/v355/nqYXPwym/0y/bB/nE1Wu/3r7mVC314/PX9+h+HPb6/f/fAdFXnC FxWl1ZpJxUVeabbRN9/j8MvzDy8414fPj4+THxeU/jS5/uXsl+n31iiuKkDc/NuCFv1MN9fTs+m0 RaRxB5+fnU/N/7p5UpIvOnQ/xBoztdZcElURlVULoUW/soXgecpzZqFErrQsqRZS9VAub6s7IVc9 JCp5GmuesUqTKGWVElIDFq7ph8nCXPrL5LA7vn/tLy6SYsXyCu5NZYU1d851xfJ1RSScg2dc35zN YZZuQ1nBYQHNlJ48Hyavb0ecuDu4oCRtT/799/04G1GRUovAYHOISpFU49AGuCRrVq2YzFlaLR64 tVMbEwFmHkalDxkJYzYPYyPEGOI8jHhQOgZMd1prv/Y5fbzZ9SkC3Hvgouz9D4eI0zOen0LjQQIL xiwhZaoNc1hv04KXQumcZOzm+x9f3153P3UE6l6teUHtbRZC8U2V3ZasZMGd3BFNl9U4nkqhVJWx TMj7imhN6DKw41KxlEf2wqQELWNTGuEAUZoc3n8//Hs47r70wrFgOZOcGkkrpIgskbRRainuwhiW JIxqDixCkqTKiFqF6ejSZmmExCIjPLf5LI9B4GowUrjkiZCUxZVeSkZini/sI9sLxSwqF4lyr3T3 +jR5++Rdgr9No1bW8JQgwenwFBREe8XWLNcqgMyEqsoiJpq16kg/f9ntD6FL15yuQB8xuFXdT5WL avmAeicTuX04ABawhog5Dbx/PYrDzXkzOVPwxbKSTJkjyvDdDLbbzlZIxrJCw6xGYfcM3sDXIi1z TeR9kIsbqgE/0qL8VW8Pf06OsO5kC3s4HLfHw2T7+Pj2/np8fv3s3RcMqAilAtbyXn/NpfbQ+C6B y0L+MK8cnihSMQoBZSB3QBHS+xoYXGliswCCgOtScm8GeYhNA+sWMVAurC2E703x4DN9w72Z+5W0 nKgQ6+X3FeDsHcHHim2Ax0IHVjWxPdwD4Y2YORpZCKAGoDJmIbiWhLJue82J3ZN0T7mq/7CUxGoJ moHJgHQqugTVYQS4lU71+Mfu6f1lt5982m2P7/vdwYCbNQNYz4nhuZ7NrywHZiFFWVhrF2TBKvPE TPZQUOd04X2sVvCPP1O95x6aEC4rF9NbikRVEWjPOx7rkI0A8RgbWcMLHqvAuAYrY9uxaIAJyPWD fbIGHrM1p2wABrZ1haOBR0US2I/R4SFmFKgIGhqirV2hVVYFcI+ypyu1qvLQycBWA8IhVUx6tL0s 8jg8Tc50PU27/SWjq0IAb6C2BV/WuoiaB9EjNPu3EPcK3i9moCkpmI94HFOtLddPosaxHOMUldDa eC7SmsN8JhnMo0QJFtTyamTsOZoA8PxLgLhuJQBsb9Lghff53PncuIztNoXQlS+5IFKiAL3MHxia eTR38E9GcuoYHJ9MwR+BRzH+KvjXMWgDWAo0DbJKxdDHz4nmrnU9SRhy/ONKyAJ8FfDfZO68FdUp 6FHKCm2CNNRl1sENozcfam1rqQFwLjlyoL0ztWAa/amq8UiCrFmzyCmKpParwoxtfNSQU9BZb+Dl VRDlSWgPJwqep3R30+6lhNDV0mn4EaTLuphC2K6X4oucpImjssxuk5Dzbnwzl1gtQbUGt0l4KDID u1xKzysg8ZrDkZo7DqkBWCMiUnJbHa6Q9j5TQ0jleJcd1NwbCjU60w7fVL1L2t8ygEEtpIKEbgJZ yUQs7m1IxW5D95ZFLI5txWNECKWw8v1dA4Tpq3UGOxJuxENn0/OBo9dkNYrd/tPb/sv29XE3YX/t XsFlIWBrKTot4HfWPqG1Rr1w0AX6xhktBzGrp2vNcdDWQbxPdBXZyQaVEieyUmkZhaUwFWMIEgF7 SHAFmhhynAwtasoVmA4QWJGFzJ9DtiQyBv/GthfLMkkghDKuh3keAjbI0VGaZbWWW4NjlHDa6sNO 3kXC01YAmvt28yod03Pj7ZiHy7aPfzy/7oDiZffYpK26wyFh54nV4XfwEgwdScFMZuFQgsiPYbhe zi/GMB+vw1rK3lWYgmbnHzebMdzl2QjOTExFREbeOoM4HpiBYhThmRiX5jfy8DCOhTdiObq2Irz9 lEBscTs+PhUiXyiRn4XzMg7NnCX/TXQZzrcYmgL4Ff7l4YyNuTFQJ5qcmoGe2ulans/c97CxORgx BjJ1ee5oQwKMHrZtasHBRZyHF2yQYV5skFcnkGfTU8iRNXl0ryGckEueh015S0FkNiJf/Rzi9Bz/ SaDA9Qlb1YYg5VqnTJXy5CygkYUKv3lDEvHF6CQ5r0Y2Yd5cb86uxyS0xp+P4vlKCs1XlYwuRt6D kjUvs0pQzTCvPCKDeZpVm1SC0wuq+gRFEaJolO9QtfrB7fKO8cXS8ia7nBQweCQhcKizE34oIjKu wZpA4FSZkMUJ5tga7NC5ZQspRP0upFZ0GFMHkmZEwh2rsiiE1JgYw9Si5UZARIn5JCqWTAIbWMsU Jb56BeLKiete99OFCMxu0hkcGg4HlpAn+uaiSzU5lslaSp6fTacjqzxgrOLiMPC3h9lZmcALaQKG X1dcEXDs1n2BxFnmbB7BO9R2cWQnl+chEtzIf8zikHiz2M7Z8d+vO9tkm9kC2tRM4d35msB7wPTn VjLEOCAYnlXnK8eD6hGzy1XYZepJLs9dkjZqwEQwCPGmegA9JcAJkjezmX3kVgDiMisqnUbejpOi vRT3poC7AVcOgTVPORMhKmcsVphsVRmR2kwNUWnGqRSNc2QRI+uo+5x6eyGKxw23TocIvNibK0em EggQIN4A/sf6l5cnnodtMGDOwxYJMLNp2B4hyrVj1joXU3/li8sTC4yvMHW3HOJ+IpFvl3YN6+EG dtBFUGzDnDiESqKW5vHH3Q1xNoe3vjxvlwm5Dka/ZTEWKkFPiswkLzDiauJ0NxwxMtRlCUArxizA Z+gHreo05wBXLOqaZgrBSqpuzmsRjd4Pk7evqFcOkx8Lyn+eFDSjnPw8YaBYfp6Y/2j6U6/YgKiK JcciJMy1INRS/VlWeko6y0hRybxmNjh0fjObnyIgm5vZVZigjaHaib6FDKe76C/zm09rvxK8ZT2n JXLe56ZAN4A3w4EdbA5qoJ5z3Dr/PE8yXbE0MYPMIxVvf+/2E4hFt593XyAUbc/QP4q5giWPQP0a vx9zL+Dl2GWbxmaqAmybje59nhoX2FNh5Y+LrM6fOno3wzQGJtTi0eTq3S0sescklvQ45RgvNzGr ze2jJ+1MbU2RdRSA6HD86cUxNKgZ+SA7ZRnVeoANGUxv5kue91/+3u53k3j//JeXT0i4zMBjZZin AR4MKoWFEAsQvZZ0kMXQu8/77eRTu8qTWcWuGIwQtOjB/tpbx+JVCY7agxeJ1/4MCAvJK4xTqnWs xI3X6bDdg3N4BK/jfb/78LT7CosFma/WiNTJRxu16cEUeCuJkxYXdUZgNM/a4vs5fkOjm5KIOfkq E+1i+I+aHURnpK3CzFk7KnAnixwz5hTrcZ6UYAYKuyg0z6sIwhG/W4LDsVDdwO60h1r5vmgNlUwH EXnGPYjZgFHhSyFWHhIdW/is+aIUZagSBZeDDN/Usb1joZMA7o3myX2brh8S4BL4UGVu/BI/bYfd NZmImxYU/ziSLcCign4xhqi53IoU/iExVRg6t/O69s7uCOgL1LAFkZgebFpjAkSN+v8mWpHGFn1o Q4pRJDiBAqFOtZdarzFjDGjuBlmHUTd/9k1w+ChFvvB2hEzBNtowzooP0PDk4Eku/UadkdK2z+3B srZNAQzR3EnBKOb9AjOwDUidyOt+DzxRgPdAcpv0JDjooTt3nAWPwCwQ5Ht3VO9/BOa1nIexSWyS qyFPtc08WhSxuMvrcRAfi9L2H1KILaoIbgHMQeyoxGb6OuLCaw9lkzE8EJYlTRL/NsyGmi4zWS2d mhTG1FbGOpSvrhm1FqAm+q5yGZKhQcWqNiFUrD/8vj3sniZ/1g7s1/3bp+cXp/ECiQZBZccMBtvo /8qrT/i4oIE/tQfnnNiyWKTlgrs1Wwscnv/bzGS7FIhahhUp2waYqozCWsfNzPIPRVymLFwyi/D1 Ag9GVD7r5y3zugMSnhBMWJk3rQm+jTPdYbEhQoqQGWxI5J1H0BfozXuzf3aP78ft7y8705I6MaWT o+Uj9G6tt0iPMFbcEnsAuf5DQ6qo5IXT9NIgMq7CmTKcZhiwNc84tvW69LD78rb/1/IHh95PEzJb VwMAEM/YeIQQgvjWIyFKVwu7Rm8uYsUgosNan/tYqkhBERTaSC0IPkZuLZ/UzXsR1mLcsnMDqpUJ Hak190gvtSIZRo6Oms/4QvrFnCU4WySOZaX9zI2xK1qAD2UXKJV1R62WNNoRgjkz0c359PqypcD0 B9bqjLJbZY6KTBmpvZPwa2fhrO9DIUSobPwQlZbFeFDD0mMLMxwanNs4XebyWgscCqOYNCmzpsGr VzRlMdYI3GnDAlPaaF1JasdL4/zZ3+MgbkWYcfoz8M5gz9YjYcsJbF46PjECWQAGQsUlo12HdL47 /v22/xP061BKgNNW9k7qz1XMiRNJguIK1Vk2cWG6c5h7cRbYzBR+GthqODvONHZ/o7uWERku1bQ0 wOzGGMPbgUkNvi6Qdq6gD+rCY0vmdeZ8wJKaE45HkseLMIevgba6ms5n4QpczKh35tbyp5ZnBh/m 9g5IurKXx24fUhQpQ0Rwmc1IWTQlRSixWmDdx+IAzhjDM1w4ZbMeWuVp84fpZ4HLz2Er4SfuB9Xs EC7VdatZPNz2rBkGvn3fve+AfX9tGvRqb8VmBqSvaBS+9xa/1KHzd9hEOcqlhQMPnBhVSC4GO687 e26HcGlzWgtUSRRaVyWnT6PZbfjWO4IoObFxGqnQqiAZJwZp0px3MA7U0EitqyGI1SlhNiTwLzt1 17GUgau+DT+BWkVhBF2KFRuCb5Pb0LmwQez0NSe330BEySqsMvpZTrHmMhluuOCBU8BmgvDedgxW Rlf65NaY35DjP8uwxaWWzpft4fD86fnR+0oTjqPpYC8AQr+bB9vdG7ymPI/tXrIWkdyFpiuDmdwW K9W6CI1CeLis0a2WirsTE1Ov1bM7XZEEdp5i9nUIz/B7Ik5x1Zh7Aw7BmuD9bB5A0Wxw0AaTY8F9 5CgNSXk2D66XMacTt0eY76kNzkPcfngEA6gqRMrp2A6QYEHs/uGFGSNF5C6A0IzLgXpFuALPwE2o t5ichAxStzP82l5omOLBHFKHXkXNSH+DxZDpEY5ewyi7IQHwzen1IDAdLscTNgTqMsfvQa3YfWgn C6LHtRTMZ9bytPiQYqh2G0Qvvc7EmiISvImx1zCKjSeO3YlpyJbHucIWbIFfxbOjeZ0RDGXWIVj7 59oN1Dp0PtIo1lMMSiu9Q9h4wWOXarx930NuHaOaXax7QEi1UAP7m6tlcIGlkoF5b6W27gY/VSpz GkYNDDglFJvWXfi4qvvMFoKmRCnucaTcYNR5X7mdvtFt15PQBCmT4+5wbP27JpgaoDyEHdj0EX0m Scy72kmxffxzd5zI7dPzG+abjm+Pby9OvYiM+c2UhG4isiQ8wg5SFksHIhP8UpdLlDNHETegKqNN tjrMaQ0VpppFgLAnW/LYn385kq7SVbC6Y+CxcnadqaRR6fbw4BfuevSJag9gE0Z0KVlXsaxL3i/v u+Pb2/GPydPur+fHtprmPBKeiPJIlyok/g2WZvPp2cY5A4ILMpsOoQlM5QPX8H/vuJlch3IUiNGr kkinWjp6knbYHcTnqRO3t5DKMZ53WDtwk20GpIp7DwLSaGk3miwwqJo5msKEbTOT0QCDMZKjaQZi mMlSgXkeTB+D+xjsnm6pKcPqVdNXXInczi91RJLdlnBK096PqUu2iKMAGWY3m6/rGhJTPQzQwakl 6UliLq0vuViLYltbmpYpkSAfTle7Q4Q9+BvM3nOnZmRdSJ0ZK05eRCMVgTWojInV/DFc4C5sAFMe tU/pQWDK+0LDuGIUR2k2jtQrHkIOugiaCH02HrzP0PnEdNjSNGhhG1ff1ySTFbd1fv3ZUzMNkOeF XY5poIvCdyiuB/7sdWGym8GvdzT49mCdWuful9Dg82iXhEHCPCAW7gxVrT76vSSh+KXonFDXK7JH pne1cxbqfSM8FY5Lw/RSC5G2PkSrQuNa3fTdEO36lBLp2Pi6v2YQsxX0w+N2/zT5ff/89Nl8ObLv PHh+bCaeiC6L2CcI68LVkqXFiBmDq9NZMWIxgH/ymKReB3K7V1lP3nV0mF9SaM/c9Vi8vG2fTHdG e2t3Vde25YNMTjiGiZyvZ6FCaRexlEk/ynxdsD6jfZlBAni1NMVSYuhBuwGY+e0ic79rpDmR5aOk EC2aFGCodNJdNPBw0wrmZg4NnK0lC+mwGo3WoRkLKjET9peSiqy6FapalfgbGkjYo2pYM65gHrZr TcaSdqmF95MDoH6dakz9ueJzOoDdzQagLLO1QzvW/h0B0zqxhDc1D57YDIGohOWUdV/cc8uIQ57v uvNq0+56J5JmSkfVgqsIGxhHmtxRFeBlgkMcblVc8iHO6pRrV+70kAC90fQm9AIuBQ18nap9kdx2 PvATeGyyLWLYYHBvGtTINHAgmfSjbUwZbQLTZuHf4NDWa4vE/hurD9rlKABiOU9LxhwgIzK9D6NW IvrNAcT3Ocm4s6opdzl+GcAcXhKJW7mBzzCAyTUwl1NtrBEYiTowVONOV35BpNcPWgMgHrm6+nh9 OUTM5lfnQ2guwDehXTS1zthEvX/9+rY/OqGUDa8rqc+HR4uXW0UTX8wvNlVc2I1UFtAVTlBE2b33 2x1UXZ/N1fnUEliQs1Qo9Pvxwji1C1ykiNU1+BLEDnq5SufX0+mZD5k7fciK5UpIVWnAXVyMfM2m oYmWs48fT5OYnVxPQ+WuZUYvzy6sdFisZpdXTg+pkiSUwt7g1+tAGOLEbVou1gXJgynPJVcc/gOe beVEKHReWD9+xBjIeTY5dC/dXrWBV0TPLVZpgF1zcLeLBgG+2+XVx3AQ3JBcn9HNZWC3DZrHurq6 XhZMbQLzMzabTs+Das07R9N8+c/2MOGvh+P+/Yv5oufhD7CKT5Pjfvt6QLrJC35H5gk4+Pkr/ul2 Zv6/Rw95IeXqDFk9VAHGMJyg41JYao/RpZOewdaHSmq1qbyIta8U2/LXZy+wOyvuflRGUcXbWHLw 1ois6hRg/0sWgQGW71n/XIMlaRm3WgFNEscJOo2AOy96a7pXg4kInnjZWc1INoTglhn+TBeJKVF6 jECKMo/BX+BOI4VHM/jq7AghMb9ZhE5ZOZbC7YnRQ4tI6v8eAcQ8oxlbwCk2UsCAv8Ac+InoBtoa o/BQN2lmkm8AMc2FEv5w3TyIIqq1eULzS1LBNM8a4gd7TB06/Y+xa2tu3FbSf8VV+3JO1WbDi3jR Qx4gkpIYEyJNUBLtF5UzdhLXOuMpx7Ob7K9fNECQuDTkPMy41F/jQly7G43GxXsi31DPlVU4IJ8u HXhsZ6BUXWHgFQFdH9N8u/29jHGlxvmZUwyNCQJD9fVuBzLn/h6Ts+sRvFVEMrnb1fUNsPotTISW dmYLVtYHP8inxGGoiZ9BbugbT13lTODLpKyuohY0WYWr4GJ9O6dn4zj68ipovsrzEEmVZ9dSycGl Gn7pxrogpfNls/gJTknELqskfI2Rn4MtEkXXHJn5rc04mAS4nthcxjO5tzNv+JJXDWEQhoWnAEq4 TMYniZVQkcNg50tYF33VmBURt7sglpmPPIQIwipam2R5CYRYuZMhD+LRpN25ifsK9pxbm3ioGLEa klfq1q0to6ywm4MNfE8esbUQdjc+GLgcZ+ZSdnmcR5HT25w8FHkYelpVJFvlSF5phhHXdgGnmmsA rPJkP8lXOz6/o35n7Ga05CubHZ9IEA03OC6b01LXJFW63gwuJFPWw4ag3kYS5hOJ6yx8N7CyE0Ld tnIBejKEPEljRQEbM3WKlxeQ8R0I8Lq744I3HgJBMeRB6kbtAPCGfn/94BLR81+GCUm12IUeR7cd garsdFZTTaBwieGK7+gxD5nMFK5y7Jz6dQVzl261XfCROvL/dDEI4Z/Zm9owInYdNgt4r4glcdrC lg8HoCC6zgqUW3KWO6tG67i4zY5W0n5o8jAJMKKhTgCZCxtZjoY5AJT/MxRSVWPYbcJs9AHrS5jl xEWLshBbMopwCZ7iwKFAgP2RN0et4cZnqaR0U2Ma09zydJ3qSqSis36dBQFKz4MAKwzWvyzxNqRi WXMWN9tdk0YB0l4H2IVytDzY4LBTKoXTgmV5jHxCfyhrJqKO4o3Njhu4CTTfBfay2LXiIvuFJinq FSPwQ5RFzrdsqua2xo5ARZKe8pX3ONqJqg4iiOQ5dpVYzJQiCtfItz+QY29PFvFRYx7FYXBxpheA t6ShNdI5d3wLPZ/1eAEK4ZJFEo7WsIKGs70hgV53e6dYVlc9V/8ObiOL2u7XkXn92Z6Ed0UYhtj0 j7kOqc2lc6NXH35x4Z1rO+C6Srk0oJduoGhIQJODmpf1dFAJo5/kUXD1tsWrJ2Q3P9SzWkNhrBNj OZYU9GYmkuMk1WmiJFy5HQhzKfaBzUz3e3HMLLTyeFrQc72tK2xlMWpZlTW50mezOPlJPjKEDd62 k5DoK6I344siHPqio9OH2pfnw31JcOVO5xLaUXU4YAGfzYXPHPLizgI0r1E86pKhuRs7+7WGbclt pQd10CAyWKNDw/ZnVvttDOqIDmWoWXlwZJn667fvH16jjnUSKn5aZ6aSBuGXK2o6E0hEXhO7NY5W JEIJV5vHCRGVOf75/P4KYWVfIIrar4+GMXhK1B5ZZZx/mnQ45NRFQwtlXKuqDpfxJwj+cJ3n/qcs zbXWE0w/t/ecBet1AVcnpGrVSXMvke3tOyGVCW6rexGTZ8lIUfhyW6DULkny3Ius9cG0YMPtBjsD mRnuuFChS4cGkAVopndDFKa4aXvmKSeHsz7Nk2vlN7e8gmgpIONfSwm4sE5VWCMOBUlXYYoj+SrE GlIOVrQyDc3jKL76IZwjjtFcxyxO1hhSMIza9WEUorU4VOcBvcg1c7RddQCDKpbxrm3Kbc32S8xF twQ2tGdyJpjiu/AcD7LPnML5NF+hLR7z8TliCI0uQ3ss9tJN1IHPzSqI8UE42iPbZSlIF4aeGFxL cw+3lw63h2prhqaHwk++AkUIiYu9nanCz8jmHpuGC960u5r/7To8Obs/kA5MJFczmbm4emGYHBaW 4r4zjx0XSNxbE5G68DpUEPKvKjxyyVKJCuQxtEG1skSnG7GeZmwLL1xAQRioPswq2HtuLGF5jQnK dJOC3XOdYVGCJF7ck47YVYG2mE4mrewUYh/m+NjEB3kLP7FxHIlTvOmnNDXB3PlovRYY1xXnvY9B NPwlc0XhKhvhg1TPeIFifCYuDCXeFhoDJi3OcNFueoLUabeNbtEa7XpUtjXwi+6xtiDHmm8pVD+N njGhThi3BGaI1WV1BqfzHgEHWhZoNWsRa+x605wh8m+Li3szEyU7rpV4zoqWSkIA87bHut/k2Vi3 7RcULgWjZ3HLx57rkv9Akz/sq8P+iF/OnZnKzfpq1xFaFfo15KXkY79pdz3ZjtjwZUmg68EzAOLe ER0KY0dK9DMA4OLwtVoKFlOKnrFu7AuEvGU1SXVtQcxIEbLLeuABKNImUlQFweeezlV3XFHDLO8L z54cuKqjOS1q2O1mIBsUcSyOEyaXYz50uWJvXu6U3wQrsRTB/dtuzQq7LUiZhStH8JdU009kQsDw AGKAs/RLfENJ6HHjmMT6eAwum+OAS11KxRmzLE2CS3uwLrvo+DrmTQzr75XSOGe+XmcIo8lWhHGW x5fu3MuqOZoQ5RKuLtRLshCYN1XV6WuUBpUV3C7EsVMtF2CrxmSohe/eUGGGvlnT4WvKYeJz87gd h5+xCS9RETGMEizhfeUPsCs5ChoG/qz7andsIID11OD2h/fVcPQ38iSbfs6gms4G02DlAY+oSt4V 2zzJVg75TD2dCoin3/rbPEig6rxzvO0jOr5v4eUdcKhqS/P0XzKVJIvyYGpB3DajGNdBEslJ4i0S mNJ4nkkGduYKVjhezDAXagUYm3iFGcUkXlPGm+/oJqzvWJSuMUORGkAkDkwbvwF4PHamj+lPURqM qm3s7xFwmlyHMx/cy/A82PDrab2yvGoEyfRyBQqXPfVPE7RtgKm5AorKyV3Jymar76sTJXIzjjEz 9QSt7AxiYlOSRNlX9o/vT8Jruf6xvQFjlmZdgZ1HE43FT/BcNDRWSW3qjVTjNGcsoPcEu3IrsckX y1D/pjJYRGUoQzNBX1zQUkgHpXsLktYNZh3RAYQ5x3KRyL7toWiXA0sS7GxkZmjkDj0dZGKNOz9v hhkSpUvL74/vj18+nt8xZ+VhwGb8JCOANc7QVcWTIOZS03Ti/cYW9TDqOmmPW2YoV+enx95Qp7GO bqZTeinQb4npdrU/+19I4OkM31v+23xcaSj4v844ghSkGtPxJkTogeqQBIFqTjlU+hTX0cPx1A7m qgiwyA+XDDl64nUEx+0R6xmVOxvi+KHT/TptxFxTRq453Rt9qSjSzXoJs+mMFm2tEE1/GfojG7SA uK5Rm6+8ri3bkAF54wgbD2+/1iTbUVoFTbx3cTKJ0gVBeiwszgqi8OL3l29oDcAfX85fca2+4gqT k6mlwS9Uah5wKqAZilUc4LECFE9XkHWywi5PmRx/ueVyUcgl0mYsusZw9rzaBnr66WIKXMEwM7YM U6K5ml1rBI9SRF5d1fhQ2Lwywc2EpeGX0SAecLv5Be4tSKP7zb/+ePvz4/Xvm+c/fnl+enp+uvlx 4vrh7esPX3jl/62vU2IUwGj1mJ4BLyu4VCjuBplbrAWyhpz8aMflTniBymRwx4QYRerF0J+tqJBi aaBWx/38sMrywKTdVlT2o0ZrLSsx0Hh7e2rGajpU1tSSjlA/zeHf+HT++vgKPfEj72TeCY9Pj9/E HHdOQKAx6hYsYEfTVCWQ5oAqE1Hh3mAAYt9u2mF7fHi4tKzemph4TlAetIlath+/y5E7VVEbK/ZA 2HreR/SORKO9pt43chTEyUPd84GSBS6gwEUUp2XEvSnoOO/gBAaYOnhS31UffS2d84u1/i4g3AGn wPurRnyr8mySF6Nj3dUC2hc1umqxzkenmClwz/QIsqw2VnYpFfIO+/L29eP97fVV9udCfn0Bv3y9 iyELWPFRgcIwMPOf7om99BHrmMra3Qg68XiFiM15K54U0yScBXLv5CzYtBzMRU1vfr+9O6tfN3S8 Im9f/tsGqq8iqqF0sxWPeR584cw+3viHPd/wCcIn7tMLXEHjs1nk+ud/6dcd3MK0tqoPxdCj97f4 xxg+1hNBxELke/F+eiI7WYKztltrRVRJ6v7OfO1Xjm6XWb5eZ9EKY5OfSZdTaFGd50YFVRznBYtU IMPv/fH47RvfXsTGgSwoImW2GqW/oad5JuXCrhuXfg66Q6m01Zy5/mDRtgP8CUJDXdW/ZF7cfRXY 9Ugb7ptzaZHgsKo4OS2zyVOm+wFKanV4CKPMqRMjlCRlxIdMuzmiK4Fkq1v8AE/1b4Ga5gQ671Bm IvC739rHWGY0Raw7ZzlDUJ//+sanE9bN00G9t5PLQ2cPtPPF2J+1cRZg1MhpY0k178VJDRIkvtht g4kOKXwVFSyZO5ikHepKpwxdXUR5GHi3GqsB5Tzalm7DGu3W1w/tgTjV2ZRZkKDviCg4zPV3dCcq /7SQnk9OdtJM5csNZBMrq1m4MvNpujyLrzQS4EmKuUbMPZqlEdb9YGu2yM4B+9QPjLPmqVM3AeTp 1S7kHOsQM9joeORmLY2e3nTS7GlVVFr2EKLzoZy4XhvmCmTcSDcjtsEm6pQKQQV8enn/+M63vavr ONntuL4EhmN/A9LWvvg1l42Wob5Sv3V+DsHqoTaa8If/fZkkTvr454cxQTinlMAuJYtWurOriZgX SHUsPKMOmDOH7XC/IGyHy8lIffXvYK+P/2NaiXiWk/i7rzwPr80sjKLhG2ccPjZIjGbQgNwLgFNj uTFC0xscYexLmlqts0Co25DOkYua4onRqWRyhP7E8fVWFDzYyqlzJMHoK4Armp8kzvIQb7C8ClY+ JMz0CW6Ol1lMFg/JwH14Q0vSyBfC4szzwqLONkVSwPQAjcuUi2xEPMZNem9VmqGI1snndaFDanmZ oWzzwdU/4BT1+pTPlaOusElSu8Xf7Jx4+kq8xO0N/wThAaiPyygaIhk1927TSro3jk4HtwingJfL 2jwJwqQsIKweX78w++d00iQv7xqDXwIiW0+6JHBLFZFOnEQzDGroTkSI7pIgDVGeqbJwrThfrxLs xEqxFOcoCI0VRSEwIT1+mzpL/g9YMCujwRBhFWAbNKTV9P1so7ulkQNxiCqfzV0EV1K9gGkHtsF9 eecHy+Fy5EOHdxkMUZcP5EPTI1FHUMlRfR9nCBNfUssPwWLgcl+YGYKThUQeJNLlKlWRmnWQxgWE A4IeBEMBiCOmgkCQ9bxVq7Pk+PuAisW2uDoM03i40rzNEKdJiFURWmKVZNm1vqmmt3UEb5qkaONY srfRbOvMBfigWoUJ0gMCWCNZARAlnqyyOEGBxFcGVwrwMpJ1jgCMbuJVhrWgVCXW14bojhx3ldzp ViE2yJX78ZU8+iEJYmT49QNf8xKsYseChUFwbdZN+iGWmGuB63WCeX72h2RIw9xdyvdnitobhMyq RyWaCFrYtGU7mCDxZBnzOPUqpko87n4o7uddVz62e6Hsp8DNs8U3ZQWf+1o+ATn0NRpeUDGqGIS7 9gQ3t7vLuWYV9hE645bUvQx/dbUSehIRxUy4HF5N4s8dYbxaX2CAC9UXz61qnW+pnJ5TWZ22fXWn OK/Wu6IgqOGPrygeM6qYUvzdESV8YyKXrss0DniGONllu3MpdrBPRT60Z/VU1SL3KFCeqotj2elS KObVPrPDbQRhZYb8AgdW1lmhBZ4fP778/vT22033/vzx8sfz2/ePm90bV46/vpk6+Jy866spb+gt xzo/Z+i7iMPa7aA30LJiySVjxjA/AOnN5Dbv5MHkASK0PGna8BdGq8M2Cje0QLIF82qQrrGOlsIq DnAx1QWm0AYu8FDXwt/IRZQbkotMdmusJc5YRtOKi7WP8qTDmmg5cCJjGo/jp0xydl3lEo5/V/pD mvwu59I8oaO7jk9BTsW78EKicEqjLFTT22TzSC0e35/MWJds0xVXasLAB9d555XpAR6AxQ6ZB7Qp gqL5kLRg3jaEGc6yGns1DrVH71uYPMfnm4ISpLZANn+JK7nwjosxKQHQKu0rYK4+km5HSXEp6MGD Gjq+RPSo0cL54dfvX8Ub7N7gEHRbWksrUJTepn+RoLM4w+PdTmBkKFJwUUkeMES4kiaSkSHKs8B3 UCxYhGP0tqnGoqVOnQS4b4oSvcPDOcSVmUBXwAQVM6qLDMcuCkb/hZgtXJIrqx7TasUXC6VLK20m 6hHyIJtpWbYvwCgEM7crMEWySmOHZoTSEDTjSAAo8LYBnLFCBP3ChMB1e7TbbSJitaZdlEae6Coc 3tfpii8qnutr+wE8JlhdaF8BNF6OdWIBedV3LI0wF1oA3UMOoOZ5R3M0+MCCJmiiFA16KAeC1NWs JnKOQxaq3SGSah57LPQ1Zo2d4XwVO5lxHSpD8srXkW84OfrgQswt4pDGqV1/TnMSKwnArsip7qpe uEJ46gJ7mZ2oK7YJH9u+lpi1MCNRXyRDknvT3OaB9W3Tjm4S2fIktJE7q1dZOl5bshhNgtBJBkS/ 8UCw3N7nfERhKiLZjEkQWKs12cShj9gOnVODgXbeKgtTqJ1iqC+ExnEyXgZW+C7GAWPTxeuVr8Gl TQXJu6H4abroeNJQgqp9XL8PA92KIDV+05dA0jLf1NXOGx3qOnCqCvQoxIwy6kvEEaqVW61OTj35 YccZM5yndnbTOSdKjXCqaVycEL4MxtpRh5JYXUFAIeRohABT90HcBOcmjLIYARoaJ7G1XC0HwWbb 3NExx51HRU5tsT+QHeoMJfbv+ejdJWK7VsFWWROhN2rhg2gSBlbbAi10hog47cVNizOMmxUneOXd nOwj54Xmdq99Er3QUF55QK0vhO2eSj8Ee+dXyGSgQtNEziRnA2z4PqGRL0hbZwCci3KNX5BRCty8 KOuevj5hd06sDqI0PW6+VGU9grAAMlTmqW0GsjM2goUFQrEciYg7yo7Uc26ysIOhRthp0AQOOxdB dsZSsEAgp+fm4mKCnsMXjalMYn2b1xCxiXiydg4rHRZN6EYyQNxgcC4YUf+EC41epvMswr7b9Upe RzL3HpOYLLo4biGxB5FRMzAk0ld4C0HTbMkhiZPEMw4EmqOH3wuT7TGxIDVr1nGAB782uNIoC/G7 0gsbCAkZthZYLGhzirMbdB7Ye6+JJIkX8c0d9wzIZZG7lyc9B9MMCwi+8Gi6A5IDoEn+aQ6WnmFj iWcCg3ifrnBVzeJKrw+cReXAoQTtykXn8BRrbZWez9OlNxtbx97cueYU4O4NNlv0SQdMurB1fdHA s9xXEQ5yteyzehRdyLvx+hJEu0RGD8Iy6PI8wa4VmyypZwGk3V22jj4ZA1wHNN/UMjGPk4jJlHy2 zkvt89OKrNGxCO6hxiVzDdrmY+BBjg+VdxPsTnxR/aRCgie/lgF6SqnxnCmeuCes21R9f9/VeoCC CxngFsnVPC3tVwNsHViDhlUeoJuPfQqqI/QUeb6dRbQjwfWdAHgYvuOxhOZZivY0a3ZcYvd1GuPq dZB+tk1xrjzCBVCTJztgVeAaVhKmcYRXQWmvV3MHpsgwtpgYXxHQNldKrx/D10xN78WxMEYXcldR tbA1Lsy4SquBKQUVaz7XZxcTyT0XOxaOWadCUkt96bPkyrdXYYXPIFQsZiSNcmjhaUD9po2Igymw 5T08PYt9FkeRzY48nWcA/ocxFdum7E/i7iOrmqqYT3zo89PLo9KlPv7+pkc+nGpKqHjqw66sRGUE pstw8jGU9a4euNrk5xAvlfpAVvY+SN0c8eHCxU1vuPk+hfPJWlN8eXvXA1LOzX2qy0pERMeVe9lU rXqSAjuePW1cjdYtUr5k9/Lby8fj681wmp92/Q89H3hnkJSkg0iyP4Wp5gjAwekxjQutD63n3QnB VsGFWsbHArxa2YjXMvBzZc58bJbnSufaI7XUx5RzCiXaSIQPnjtFnoo///Ll8Q/tlr6gkq+Pr2+/ QebgGY+CPz4tNUCYSh+qfxivzkl/02iike1aeiwi9BijH+6Z/uTWTD+mqWlFmpGHNAhwS5JiKSq+ PWArlGKoijDN3UJ3TZ6GWJl0bMIwZFiUKMXSD03EFe2jmyv/y27vXfpDGcamGZxRJlP0WMhSSLeJ img66+vsmMQYfiU+MbATFprCszau/hP6/1+PxoD5NzZc2NuvH+IG7dPzry9fn59u3sVzyd6ho9dR r/9p1SxrE/L6i5aFzWY0Il/5rmVjNID2cCF+ndack9o0ffz65eX19fH9b9+EHY4HsX3JxfD7nx9v f7z83zM06sf3rz7+6Z0/Z0kW2FCSMI8M86WJ5tH6GqgLPm6+WehF13meecCKJFnqSylAT0o6ROap s4Wlni8RWOzFojT1YmHsqSjEx/1/yp5suY1c119RnYdTmbo1Nd0tqSXdW/PQmyTGvaUXLXnp8jhK 4hrH8vFS9+TvL0D2wgV0zn1IbAPgBoIgyCYA19LeKfIc5UZXwS0dx1puYcWBOoGCy/o97MrclwU2 WizAArRxIDh5rr98b55dy2C2kaME1TNwhnEl4Szd6VtUbH2lu+t1VYM6d+h3NlJFbbBxHEvvaua5 S4uYsWbjzi1iVq09x8blUwq6udpa5CVzYxeGvbAOjFOEji1xHaUOZD3xcpmBdpptn6+Pr1BkVLX8 Jv/l9fbxC6bb/fBy+3p5eLh/vfw2+yqRKhqubkIHjHGrBgQ8bLT0iUHgD3Dy+bdFEXOsvHR6oO+6 zr8pqKsCUdZlLcBh63Vcz10u4tSo77gf/H/NXi/Pz5eX1+d73Jes44+rExUukSv/Xu9FXhxrfWXq KuLdytfrxcqjgGNPAfR7bZ0X2aA9eQtX5xsHyidX3kIzV9cPAj+nMGVz6vptwm60IS337sIzZwqU 21oHhr6iukbKjV6nmGiTcqMXx/3HWc8NIHRUPnIPpJ6vyckhqd3TRi/fr/DYNborUILLZqtQ/0mn D3xXr0QU9yngipo5nREgRLpsN7Xn6HQg7NqNDJ/3cO0HLv2hd2Ke+rlglMFm9sG6OuQelrCxGy1z KHUB04/UW5m9FWD6unaUPjKDTL9GtQWY+gvF33Aa8ULjaH5qTGmFRbPUViouivlSk4WYhcj7LKTB kQFeIZiElgZ0Q8xqPwbq+p7b43h60voIZxVqMc59QwZjDza0ioAu3EQD89PK3KGAninF+llJnFzw JFyMCdVR7KJeOVsFDpfxWpd/wROPnG1dGwo1tBoaDZoa2szh/P99FvzAxNu3j3/cXJ8vt4+zZloA f0R8y4ibg7VnIEaeo7rHIriolq5HPuocsK7OsDDK5ktdKaa7uJmLUCMmdElC/UDvTLrTczXoK8zR FHTQrpeeR8E6YAaxQfD9WUTHqOP/XI9s9NkD8V+bqxJVmufUShPqdvnP/1e7TYTfn6kteTEfo7oM txlShbPr48PP3u76o0xTtdZSTgk0bSYwJEdk0aBR/OglDsRJNEQvGk7As6/XZ2EdEPbJfHM6f7Sq zjQP9x79hXlE2807QJce7Yc6om1qGT9bL3Tp5EB9ugVwrgssHkipR29CmOv1LjVEH4AnYxUGTQhG ofVGB1SF7y81c5Od4KS81GScnzc8QzD55ZSmafZF1dZy5FJxXxIVjZfo/dsnaZInxk4cXX/8uD7O 2JAcZ/YhyZeO57m/ScGtzOuDQW07hrlVCkNQPUQYZwWRBvt6fXjBQFAggJeH69Ps8fK/7xjJPBX7 NnnnCsS87+CV7J5vn77f3xFBs2I58Bz8IcKIxXLsL4TGJWikkxmxkeN4LKgso6B1km7x9kbF3WR1 H6/QhG9DEiWqg25kNUYzL4u02J27KpGDTSHdNsTIUqMXGIXEVE5BmhbRn7B1meg0CXiwrprHvFCE CGgwNmYHR8j4vfRlPcciOYAfwnZJ1nFvC8vYbTgsV+/RfX/EjrGRLo931y8goKC5vl8enuA3jLL4 osxwH20TDCBfH4+INZi6PvV4cCDITyW/YNqsT2rHFGT/UEMKO2Trm7AKqkwJXduXk8FqVw+7hA5S wpHAP8sI2jhVe11FQYU+Ufs4YwQmPcSaUPUptHdlq8LLIOcRZPsd7OXp4fbnrLx9vDxo/OeEmE+x wytMkEz58lAiqNu6++w4IOHZslx2ORjIy41PkYZF0u0ZPjPxVptYn9WJpjm4jntssy5PyYPoSNyP mqhGXHa+WzhJWRx0N/F82bjqQ/aJZpuwE8u7G+hPxzIvDMgHIQr9Gd1Gt2fYz71FzDw/mDsxxQyW MkyeDD8267Ub0e2zPC9SDMnqrDafI+pJ4UT7MWZd2kC7WeKol4cTzQ3LdzGrS3QNvomdzSp2FnTL oFFi7F/a3EBt+7m78Kl412QBaH0fgzW+oavOiwNmHRSSQkaPIml9f+UF1KAyTHOOgWiDrbNcHRPV vX+iK1KWJacujWL8NW9hZmmHAKlIxWr0+d93RYNOLBv6BYNUoI7xH8hL4y3Xq245b2xLXBSA/4O6 yFnUHQ4n19k680VOz53l5QlNeo4ZrJ8q81fuxv0FCRybHJpjVZGHRVeFIFSx5dO/tOSCrG5B9ms/ dv34/WmdaJP5PvCoDkok/vyjc3IsS1Shy/7jZtfrwOngz8XSS7YOySKZOggsLBqJii3U80seJeym 6Bbz42Hrkh92J0qwWsou/QSSVLn1ybHIdE9WO/PVYRUfHYs9btIv5o2bJuRLIFmLNiACsLbqZrWy MEkhmZMkRY4haU4LbxHclPQ4mrjomhTk7FjvaWt8Iq3a9NxvM6vu+Om0C+g6D6wGa6o4oYxvvA31 Fm8iBmVQJjCPp7J0lsvIWykGsbZPysXDisU7cmccMcpWO9ns4fP9l28XbdflMXQNUzbaA5MbzFID BpG5WQ0qHUA5D1BiGWoKleCiT5uN72rTqeLak2YG4lbbYXYPDZ4luwDDrGK097g84avMXdKF66Vz mHfbo95TNLzKJp8v6NsGzrsqiDGL29r3DMUwohbGcgSDEP4xKGVfhIDfOKT74oD15sZ+KEyJfjat VTd7lmNQusifA6swp6illaao9ywMhBPOyteGqGEX72JXelc1PHkXaJCtlkY1sMFsy4V1awZ8nftL kNK1ZudhyTJ2vVqLLYU48S4JNEWQn/z5gnKL1MlWii+Mgo0NRaIU9Em3y8H8D+LDaukaKlVC4TnI UgFfodk+LtfLhTZ80j7vgf3JylAppj5QO5U0eXBg5KsNHHQVlbtWH8guc712/s5CSHHVUq9VFdMn yRt+IO0+tay60c4XGGJZZGEYNNz2+fbHZfbX29evcGiK9fcZcEaOMsz3KulKgPHXeGcZJA9mOK/y 0yvRXawU/m1ZmlaJnHGvR0RFeYbigYFgmAovTJlapIYDNFkXIsi6EEHXtS2qhO3yLsljFijunYAM i2bfY+hRhfCDLAnNNKCN3ivLR1HIARu2+FpnC7ZjEneyPyE2FEQ3Kdvt1c5jqL3+3K5Wg6dAHCom +CPn/fsQ9J6Iiwrl20NS0zY0IMe0tJZxubHmF49A3eGXw+qo3VJqHnsgn6xREkJYL6dmsVSNYMC8 E4oKsL3zmVYmS9AcKjLq6Ik9097gIKjGTx5KMEtyIXFGhrd3fz/cf/v+OvvnDM4xZrbusS94yonS oK77JDZEf8apVwjlAU0UN03sLWl3golI+Jr+gqg80hciE4XwC3u3w3pUhwnzKSqy7qhke56Quj/n hAli9MVw6MFz5IoOayaN3Z87AVU3R21IDOwhS7I/o+O2yT/UuRXZkBaaZKrssPScVVpSuDD2XdmN SBp1FZ2iPKdQvTso2VaipIL5hcAO5flTXlrp9BvqJNjFTju1900Z98XSw72izZXtQ+R8gC3FuFsG oNQ2i6eolE0F54Nmr2CrQLFw2z25S2E1U5oA8SHn6XKHn4uwgHFNj/TBos9tPFbOoVHU8rO/pZUg quSU9yOo226Nqkr6gmzEsUqrSEnhySEtbIepxq4kvWG53liYNEVJ50LlaLYLk1x0UgJHe7zu0GEM /tKBRVUHen+jot0FGiwLoiBN9dL8eZUGKz1XfRzDoTDehqHsh85yQZtXnE6kz7biQW52RY53S1aS BD8r2PiFaaHV/qIHQZHpsEIDfFYSJgqxzEJWaSK/21aZPvRdCgZhQeagRvS+SJtEioct/ibEDkzZ II3ppC68ncZfz6nzKyKh+0aOVg4/2yS5jXgWCr3AMUhBIC1lDiw58is5gwfnyhamD9EMg5mpnGSN BvgYaJk2EdgcWb63ZGUWw85rsLfo9LJIkEZDCEoZmMQ6IC8Omkggd9Qk6jK0iz9aEPBHKen/Ea5O OIKrNgvTpAxir7PEgkaq3WbhvIc/7pMkfWdFgAnOIp7CXF/wKRpkOsez4MwDgFlqAzuZr1CjGIuq AgMC2nqBlzSVvsYw4SMb5FaC5w3TARXb6W0WFZ2VGXFgC2AsR1iaytcUCWznGNjawK+80dsrkyZI zzmd9oETgALGrdyKB+XE7wTJiKWcosKPQOrYKzSc9eVTFVEUGD0EVa+xREPzG1lL27XYPCTTID/b mVSXSRL3kVllcJMEmQECAYUtPtE2SehLmba1PoiKzl+FWgZv9YNa3pFGkLFF1llQNR+Lc9/EMCgJ ahSBDUxTAqAK60TXFnihtct0GOZbNNN4yXA7M1s0l7qynquV8vTfhoJmDPNAWyf5xEB6Le18TqpC 5ccAMXjx+RyDfVRom6lIX9vt25CERzBWOGToSW65RZSW2vRnYEl4nivbxJTtN2YjIY1SnnpdN0xL GdBTDDlOpQQmcoVTkkSllZGzPCcj05a2nNFOLjamgpUbkLpT7COmXleo3TV8BLl/VZFlqt5FKGxl GIuYWtOIbtOS9dlhlWLwa24LM8n9vSrcyYK620cqK/WKgjwHVRklXZ4c+2OyotvEW/L7l7vLw8Pt 4+X69sJZbzgKCrcpEdcYTzms1oa/hfpZznhW8V6VKB2xOxLKjG92aq0AwCyucRs1qdEkImNW83jP yQkWcB6kqugPVNs6U4EwLTWfFx5juw7N6eTerS1o0TwWAan/9GR0NiWu4aJ6fXmdRdP7pdi8QuLT 6q9OjoOTZmHACSVPn1MBLSNMRZ8ndVBTWCOtJXfpI6vj0ApDHAOzuqYhsE2DAlPDMSbWJ5LjtzXl Ki03aelRcWo919mXZq8waL/rn0zEFmYQypiIghzdAFWjxCoYqWvK0Op07brvzE61xjd1m5XZKNaq xnkdoLW5JhHMfez0tCCjOPURnaOH25cX85CNdUxJpCXgMda43WTjsT2HPem/Z3yUTQEmYjL7cnnC Z2+z6+Osjmo2++vtdRamNzxhdR3Pftz+HDxsbh9errO/LrPHy+XL5cv/zDCPolzT/vLwxB9z/kDn 4/vHr9ehJA6G/bj9dv/4jUqczVdSHNExNgHJSiOYooAe+qkkd1lBgjF2rbUe2jgya7X7hfLFG+c1 9XCTD4LPa1zplfYIa1cEfhfEOzXPz4iKMUpYpSUGFzkxH25fgec/ZruHt8ssvf15eTZYi/9hwlz1 wC90PpezLIA5+3KR3C65cLGiK3L5soF35SgHWh0gfAszlD0i9FGbFGLcFs5winH4gxiroxZqdlZT VgeU94h+eUa/xJPN2y/fLq9/xG+3D7+DDr9wtsyeL/96u3++iD1RkAwGAz4jhSVx4QlIv+ic5w3B PsnKPb5+tA/RU4Zo1vG+SHKSpgqiG9hX6zrBQ8KWvrzhErxnYHol1GOsQQOvZBfTCeh25oIZ6EU0 a11GCTox3eRYBxK7uOMMcL6T6rCt65U3vjVHWtWmIQslGZM/Yvcgz1dBQdw28s0kV3zJoU40UyVN dkWjp9PgCLuaGq7b4Ocq8m3KJTrztAfavMTDnYFS4baJGb9ksxmOeD/aP7qQy3J4l20Zz1crEohY qgDbD34c1LcrfKD2cYKMghF6YGGlp/WSh1Qcg6pihcFB3CytVSd7zNzF99MtOzWtJTmHkDK86N8e rQRnKE1fH/CWPnMOn6iHlFzNtzyGgbd0T+aeX4PtC7/Ml45tmgeShS+nLuKMhWN8BxPG3cd1Kzho TDsGz/62y3YuUSe8W1fraZNglyaiNtm6hP8EcFxa5fefL/d3cAzkm47FPtlLu0fex104RQk7qNXz 1BCHUD7yNsH+UPRnGR0kdE14Hs4ilB6Zk0/DcBtcOX2/lGOmZThKL8kNutdntgRtOkm31Qz3Homj 7/j3GI/A9jZWl7cZHBS3W/zC5ElzcXm+f/p+eYbuT8cPfTcaLOiWDHjPG6soBT/Yu5ZC5SlQwidw k+PQV6TB5sY5os5LJOXGuHXJZdi+bb2FUFo0ppoGtXk9gOR50njeinbHlBgukoTYdmzuEyLMf1WI yHlQF3EYFVlZ1MrNOp+eDsPlaIeVtktQ6+uUeZQZhdtQZIlUoLqwbdVrGAEiTxHiV738AO17oN9W CFwSUVlLdZKpx3QtVQ4blH3LHGuy+CcoROW+yK0m5ki1BfbDJFhGbDJTQhlclXATe6eUvcKIfHq+ 3F1/PF0xO8rd9fHr/be351viygWv/9TqEdLt87LfCNQNqrEp/J0pOELcDTFpcx7DaWtc4EwYvR0b mTGPNJmRhl50mJTN4Su3qqaCI3GUUHMh/5Lt0pXwuSRf0PGmwDTt6iNr1C95WWaJcp9kmP+M+giC 93F4CzWNj99J8fcsFKzT0r5IGP6VJipS1XDiBGGFFk+OJub+iP5k+S4xnxNglitjF+flg3zueMtN oLUb1HNfJHtRoJiYc272Icr8OZnAfEIv11pd/EGOY9TFwbQKn/CUgTVgfTmT5AjceCeqKd9xqY2A o0WUUq0ukXVeb6GHao9cOIoA8awICwK4NHpeLpVoQQNwyePL9rfROk72Up2A+kAQ6HsmT8r1krSu BqyWsmEAr8k30xNzlvooeijFH0T5c71AH9seUw6qt+kjlozOyLF69p0RaHBcxFaVIXKEeE3sY29N +lwJpjTz5Ubn+hT8V4Y2UYABOnVoGi03rjH9VBDnAaEnG9AXjuwtLMpIWVlkOD6pgzWjQVk9d7fp 3N3ofeoR3ml0P58UDr82/Ovh/vHvD64IpFbtwlmfdu8NM9dTH51mH6bvfL9pKivE01JmjP+dDNBi rOkJ5tKOxxD8NuaJrCTEF6BJwVgZb2YmEd3dZXN34cgMa57vv30zVXT/FUPfNIaPG5hBsLLgwDSq 90Vjwe6ToGrCRP2KrVCMb+fsbBtIo5LO2qIQBWASHFhDve5W6PTQ8wpy+EqlTjbn4v3TK97Wvcxe BSsnGcsvr1/vH17RZZabBbMPyPHX22ewGnQBGzlbBXmNL80t/BOxTq39LIOc0VaDQgbWqxYnlK4M n/rp+n7kq5qLJYiiBJPUoR/n+c/pWd/t329POP4XvP98ebpc7r7LrsIWiqHWqonwjCOPF0HcRCG6 H2NGNP45Ui4xQc1jtfBFygLzgT4AuyTfKQ/0ETZm2QC7J0/SWsUWyoOfAEPeBl1W77AJsr/8DkEN zR0fu+DEEElZjNs67ZJY/irEsh1+8OhUIPePYgCTvWb6ZJWfz/mnrOziUhQZW+avhfdYqMt2GXXC mSi0Huu9nV6UwJFFG/3I9Ojh/vL4qny9CepzHnXNqbNyTItFME4TmOxsCpKTBWG7NT8589q3TL0s ro8cTnZfVNRlxSHpnTPoXiHREClBlQnEgNordZkc4biNNPq5c3CLUccxrrb2NN239jC8X03lb4j7 eIGiZZhtPVzuDopQUEeMWS+W943r31hes0MZjz5bl0HFgz+X6ENDMI7D+yMEWAZ1Hci+g2XvAl80 I+4f/5gq7wcMmzMsO/qtnExC3V5LeCOBp63PrbpPwJ8g4NUBj5ys+kSfYYEmxtgPJo1cS9XKxzQg 7MJzyQ9jIo/7hEMlJIVklaCyTu5jHoDFpbhE9eBDXFIrrMeGGF5DlpoezvKybcwmMqpdAA5OTt2k l1UiXL88P3Xc30RKFNBB9S90GFFG0sM6+jrmwC92WdHI92ACWAmHHRmmk/RsU2B5YpD1vZz6xKH4 MLLu3/kQ7mX9C5m75+vL9evrbP/z6fL8+2H27e3y8qq8RBoiw/yCdGp+VyXnsKVXIxxkQFGSyZLR Y3WK5avP1eD6Y0K6kpVyEt222mJGqaEqRecJPQSbt+Wx4rEuWZ4W6s2G2Bsernd/z+rr2/Md6UnF H6Lih0joTuMvQlKVkpWMDAhYGhZyttSBGdlekoJhQ1dI+7LaZxQGo231QOK7yyPGTptx5Ky8BUuQ B0yrzSn/FanaDjdsprzg1eXH9fXy9Hy9o9hVJfiYsASWkYwiCotKn368fDPvdKoS7Jtp3PxPrlh1 WF7rEG5N7NQHpToGATp2VHRTn5W+SSKPri5H9n+UXUlz28iSvvevYPj0JsI9jwT3Qx+KAEjCxCYA pChdELLEthktkRqRmm6/Xz+ZVViyqhKy5+CwmJmofcmsyvoys+9+c6j9v/Ifl+vhpZeceu734+t/ ofr5ePwTWr31tVJANy/P529Azs+u1qA14A3DVg/U3s4PT4/nl64PWb5yrdmn/16+HQ6Xxwfo9Jvz W3DTlcjPRJWZ8t/RvisBiyeZvvRC6IXH60FxF+/HZ7Rrmkayj/eCwqdGJ/7EkNQk7gDttF/PQRbo 5v3hGdqqszFZPh0KoFcG1jjYH5+Pp3+sNHWFeedu2anCfdyYNr80wJr1Ri67y8y/aVRY9bO3OoPg 6awBlykWrMK7+j1+Ens+qAk6jBARS/0MlzO8Mef1XCqLHge52P1csokhyCnFNEXQYkBZMavGeDS2 7VD6O7CDmYT9feG2npL+P1cwHmvvNs8ckkq4FGAffREuWWcqxjIX85GuDFecDk/ZisuFTWtZw+GY BxJsRWTc5A/TN0OTVZy0iMcD9uCxEsiK2Xw6FMyneTTmY3hV/Pry3GolYMDkQVcDPZIS6LRJxllE AU0kQH3SUO5aWukuWLJuzmp00y4nXLyRqMJZ6vzNMlhKKZ1cHWcw6idy1Z/0Pot8Y4nKXHOcao2I Q2wsjCFzy7w/NiWqb/lWJQWW86OeBuLx8fB8eDu/HK7GjBLePhyOxmYkecqlYNsVQY/SuojEYNbX fo/61m/zGxeGqTwYCnmqLu8Jh2bhCSOYG/R75vU7cJolj4W0QY4e34S8XVDFGHK+ubIzilpC7ANj EDQ8fCVQ85s8Nvvc44qz2btfED6Nwvi7Q4cCBEeRmI5osMiKYMTNBeJkon82G411nPwILzx4DCTF YwNly4AKNP+9O3FogfJiMxvSKAVIWAgdPNAYkL+RiDkIlllhxcLSDeu1PWSn/fkg45dQYDpzvlLA mvQnZaBsEIEQkboJTyXnc+4eTniBPH0TnjY05zhoV6lODWNHl/PjnR8mKVq7hQQeIocu+ymFGApi 4ez31dftAhDjAQGirnBTVV2F6TmGheuMaEARSZiNDYK+keDeNWQ9A4GjQyFFbjocOXb0BXzNqiIh moUlcnF5P1AFZgVise2OgKliAHa0RO7JDT1KPPuerJB9158NuA8lMx8YcDx1ePGIz02GGR+23d+a +svJoLv+leq4t/j1BPloMtDpIgFnQVmmoMy4AmV+7opQC9dlf1GZL6/PoHXqr+ojd+SMtY9bKTUZ vx9epA9bfjhdNP1TFKFAN5j20Vc7sSTLv08qHts0i8ifsJGAXTef6at+IG7McHZEV8ynfdb1MXe9 NpB8awFIKr8PKh6+WKRP+LEOQYaYP/kqpYt0nub05+6+DiBfHzaYbacgFo5PFaEHHVjBFutAB9XG pDQK49xWZ7daSPv2jE2fjpkor5LIq+1E2cJ5Wn/XlKm1YyymsQ3qCfK8qit0nPBzTwW90neBZiEe 9+nVBYYI1/V0oIxGHCIqMMZzB68S6ftnSR1mRgqT+aRjRHhpgsgqdMHPRyNHA0SLJs6ww3UEltLx gLuhRcbM0dfY0dQhSzasUpDveDwd2KuNZ16zGKHu2EZVDx1hRDy9v7zUuNK0jy1ehWR0+J/3w+nx Ry//cbp+P1yO/8F7cs/LKyx3cjgnj6serue3f3tHxH7/+o43FjSPD+WUs+X3h8vh9xDEDk+98Hx+ 7f0L8kFQ+rocF1IOmvb/98sWWujDGmrD9duPt/Pl8fx6gIY31sNFtBpMNHUYf+sTYrkXuYOBFlia Lktm+uouS0rd0TVKt8P+uGshqyae+o5VWyWLaq01u1gNa+xTY1TZdVfr2eHh+fqd7A819e3ayx6u h150Ph2v+tax9Ecj6ouO1nJfC7xRUTTESTZNwqTFUIV4fzk+Ha8/7M4SkTPUAieuC33LWXsYCIRT DoHj9DuNifU2Cjze02Bd5A6d8up31enkjm3bEUEgD2Cj4yD8kOFoXWZVXE1+mHVXdHh5OTxc3t8O LwdQEN6hIbVRHBijOGBGcZLPprS3aopZmU20n3BeXUG8KwM3GjkTmgqlGhsJcGDET+SI104VKEPP uxroYR5NvHzPrpcfNIhyjpEoTe3gIXvGF+jxIRuqRHjb/aCvH5EIjG/G6TrAgOlGzjhE6uXzIW0V SZnTPhH5dOjow3WxHkzZ4yBk6DumG8HHM36IIY+NGwQMzSnRRR/Gsf57MiaDe5U6Iu33HZMCle33 yfFLozfkoTPv02h5OocGBZSUAd0sqTUfWrgSFSfNEv4JzpdcDJwBG9Y+zfqaY2NdKOUOSg2sbEzB gMMd9PfI1YoCS9oIoxTy6gCyNHDwOBGDITvfk7QY9nWEvxRq4PSR2rF0DAas9yoyRrpVPxzScDow g7a7IHfGDEmfo4WbD0eDkUGYamZj3XwF9OCYNT4lh3oqImFKz6aAMBrrEbm3+Xgwc3ifhZ0bhx2t rlhDzQzc+ZE09Pi0JHPawQzBVuWyuYf+gs7R8C70lUXdBD98Ox2u6qiEXXM2s/mUQ9CVDNI/YtOf z6n9Xh23RWIVs0Rz5QQaLG1cVchswg/9Iol8xDcZEo+TKHKHY2dE13W1EsuseG2kLoXJrscL2Knj 2WjYydBHYs3MoqGmU+j0ptb19TrX/r81ERFfnw//GCdU0pba8luL9k21+z4+H09W/zJ2XeyGQcy0 LJFRB8hllhR1eBSyqTH5yBLUfp6933sqvuPz+XQwKyTfRmTbtPjJEXR+ly9zzv7kc6n20xOocGCb PMG/b+/P8Pfr+XJE5V8b8c0k+bm4pp2/nq+wgx/Z8+9x1wstL4dpy/s0oZU26jLtwGCD/YpbzIEz psFvizQ0VdmOErO1gVakGloYpfNBn1fR9U+UPfV2uKBuw+jAi7Q/6UcautYiSh12EfPCNSx9+s1i inFDeTcOuuv6rJvmOqXI+IGbDioDgJg44WBgXVlQNqxS3P4Y5WP9/FL+No7OgTbUDkSrpagbpbAY j9hzpnXq9Cck6ftUgBI1sQjmgmP1TKtznhDWgp0RJrPq4/M/xxfU93GuPMnorY9Mj0vFSddTAg8j 5QSFr+LLt627GDgdIz813Ifa89qlN52OOg5z82zZ53avfD/XFY793IAdxi+5eYbb91CL77kLx8Ow v7cb+sPmqZxlLudnfDbQfS/ReMZ8KKlW2sPLK55w6POOmx6FH3GYi1G4n/cnVJtSFPoEqIhSIxCU pEz5wQvrdYdyKFmm9lQv5kxF6vy1NyvwQ20JmlZ6G32AM4FcUUQYvsJdMG2AfHR0XhZGPvKhDr3e QGJxG1qECu9Rbb/ZjYxaZSOJAQfdxogCBXnSZ4PohCmd49xU86Gsb2oKd1vyHp3EQ04bkVZhmqxS hNwwcLtgRfIL4j5jua+k67te/v71Iv1M2opV7x/1J/OEWMWIq1+uN8o0RgaMUICzJ92o3CSxkHgE pfEppomAnwgLViRZxrtuUClPKxvl5CKkmHzIwsEQRPtZdFM94tcyjoI9Bj6qq9SRcd1nGgoAMtK9 KJ1ZHEm0BDPthom17qoSDMvUTjcSqXwqXEZeNNGOO5CbuH6Y4Al55lFfS2RJ7zcF39DJoKMUWXXk HSymWQf03AAzt8/Oc30EkQ/RCwjqxao5pKbwowxTrd0yYePBidPT2/n4RHSQ2MsS+tC5IpSLIPYw 3HTqdvGoQ4bxVe27+unrER/hfP7+d/XH/56e1F/Eg9zOsfHh77iyU3UgipDgzgnjnQo7SH/aS2QF G1766IoZWQ22vu1d3x4e5Y5vgw/kBfcqXr36oKjcNaVcsVQYMww1LQJ9savozIJenzrahW0OCNMV PeRSHrQptrZ1QWcxLSAHkqYVaqj6epn5/r1vcavr2BSHiJts05A68Mj0Mn+lhZtMljxdEr2lHuug opViueXKSyMYwY8aObGMNZBX5FSwobobFmFoWISELiRAi87KNRBsSVn46AelExOXasf48BtaZ99i DBCDlvW+3qIjw2o6d/hQFsg3nek0Jj4U+JklbXlsp1GZUMzlPKA+2fgL91KjHfMwiDRcGCSoVdUt stAc9JmrIkhxp6IIFqwNoQIS2gpPCwnVOqaDngP7W4pQQoStPTvAX2pxp5B7kuoaSKaGt6O6rTvi +zm5imvdsxOo6YOWj8gVIuOfnCIvyTFakEt0KX+Pzuv6qlXTygW66kMfsOFJgtAvka+eWRCrOvbQ YeNOk2AHBkJCxG52l5oQ41RiB/oMe+GyzJtIOu1a3fl+K1Ac6c6qzWrR+cnNNinIsiZ/4vMQ6bIu xw46IWkbMWJPVIK3Iou7Kq4kugCAFLeANY6mfbOMinLHXUkojmOU1C20sY64pMt8VC65vlRMDa5k CQ1V6sPC3eacE3D1yod+jLF7MTobT0Ow8QADDpVeoPUFJyLCWyGj+4RhwgNwka9wj+c2ayKCITBl fdmSRT40XJI2r1vdh8fvWkin3BXuWuuXivTBxlklonT5y+H96dz7EyYyM4/xvQbfQ5IDq0zoZTQA 5sbPYtrItQLSrGD4X92zrTpoF4LM3yBXzyfVk0WuMDAHbpNsQ6WIJhTqPxrIrU/Hy3k2G89/H3yi bIywlyJS1Ug/sNF40yFv9+pCU+64SBOZjft64QjH6cx91uHpbQj9QhENQIsuIW6WGyJOVz0mw+56 sOGjDZFxZ8KTDxLmHGE1kflw0pHwXEedML7ij5t0odH8FxqVvVxBkSBPcFiWs47yDZzOQQOsgVl2 +cb2J1lZH9UMzvqkfKtva8bPKjfu+pBzrqL8qV71mjznydTpWaOPOujGaNskwazMGNpWp0XCLcGg ogDrNRlM7oIazi0dduwthcVqOFkiCiPuXMO7y4IwDDq8WyuhlfANEVMA9vKNnTFYsaHxnqdhxduA 00m1ygdc/UH93GjvOJGxLZZkeG/jwNWMkooApkoWgSp5r2Ig1nYysR6T8vaG7iSaQqr8DA+P7294 GGu9y9/4d2RnwF+wy99sEYCz3lTrzU4BxUOHoRi+46Uwjxh4wfeM5Co90qLDr9JbY5w9FchGu310 t6ha4rPtXB7DFVngaqgltQh3sF2x6Ha7Rmt/LTLPj6EgqGmiLlHiM2vX9GG2xHj9F/Rw1FrzZJt1 vChB6CJ54uVniAuuoolxVzwVvklbber3GObRH5/Qe+/p/Pfp84+Hl4fPz+eHp9fj6fPl4c8DpHN8 +nw8XQ/fsHM/f33985Pq783h7XR4lkEQD/Lqou13ZVgeXs5vP3rH0xFdcY7/eah8Bhu1PECsSjwW jZNYU6wkC991YfN1wLNYwngy0Clbm5x8kWp2d40ad1lzjDf6Fo7BpFEe3368Xs+9RwQ3P7/1vh+e X3WMTSUOahRrYFVcEa5ESo4WNLJj033hsURbNN+4Eme6k2F/staw5AjRFs3o6/uWxgoSWFaj4J0l EV2F36SpLb2hxwh1CgiraYtaQAw63f7AtCh1+SbShEQN4d2y9A/8fZEJW1wXXi0HzizahlZp4m3I Ex2mjPI/7mVU3UTbYg0rq5WevitUxObFnjJ03r8+Hx9//+vwo/co58E3DFb4o535de/nwkrJs8eY 79ql8F1vzVTKdzMv52Av6tEdsU2xzXa+Mx4PNF1SHWu/X7/jvfvjw/Xw1PNPsj7opfD38fq9Jy6X 8+NRsryH64NVQVfHPa37j0U8rT9Zw34onH6ahHfoJMZ8L/xVkA9YdMS6mv4NBU1uGmctYK3c1d20 kB7bCFp/sUu+sNvcXS5sWmHPFpci5DR5L5iahNltdyUSJruUK9e+yJm0Yfe/zdjrjXpirEkbGy2M uB7FNrKrge+c6/ZbP1y+dzVfJOxyrjninqvRTknWPiOHy9XOIXOHum8XZXTXer9n1/FFKDa+Yze4 otv9CbkUg74XLC3Oik2/s6kjb8TQGLkARq+8BeQqnUWeMSE4iQ4DvJVwxvz701bCCDNuTLu1GFgF ByIky5HHA2ZfXouhTYwYGp4RLpIV0xjFKhuwANgV/zZVOSt1REJQ2yNY+HanA63Ur45qRrxdsLC9 NT9z7V5ehMmtjjpjMKwXUvXYE5EPdpm9d7gC7Ymuj/KCW0yRztnB9Xbkc2vLUv7f/dVmLe6Fx3yY izAXHw2hevnnvvX9D7ZrUERSDVewGTsjboiwAT1q5m3C9ktFb1tYDaDzyyu6O9XPgcz2W4ai4I6O 6y3gPrEymo3siRHec/UA6pozviv2fV40XiLZw+np/NKL31++Ht7qd0qaPdIM5jwo3ZTTYb1ssTKA oyinWuCtNpA8I/4mKwS76QdDESSsfL8ECOLoo/9IemdxUT0tRcpN2Zr104I1grVl0F3CRpRrO8qE WbezlfJGgrVjGq4fS506WeRJ6Bc+N1PALP5gNcIag9G4NI215+PXtwcwDt/O79fjidnVw2DBrouS zi1xyKh2UAJZbg3iVuqDeRIsqsXBBj+3RDoy4fVcW87rqGO9iYPiHtz7begJTuSjQnYqA20NNAXY FurYVNe39sT0d5UrmuYkanGVkWEvXzUfc+yPPlg1UTSIVoXv8pYy8gmwlc3MxdLfuywmIZFyXXU3 yJQzksGfy9U+7KpJK9F5ASnyuyjCcIyuPD9DYPs2N8JMt4uwksm3i0qsvXFsBYs0olJMlvtxf166 Pp52BS7eZKtrbHImuHHzGV6w7pCLiXES0xpFsoMrw/2okODtAVqwwnO41FcX1njfLMsQMEjALr4o +1NaghcJQX05fjsp/8nH74fHv46nb78RIFK8GqMHljokoc3PEfxS56rTANIy1veWRCln5qg/nzSS PvzhieyOKUzbDio5WIUQnTlvzl75O81faIjK4blrQUXMSJGVGQKD6n6lwnIZqDiLADReBMQkrVB7 PMZ+UW6LINSuPzNP86HLgkhGxFlomJpx0rpNukEZJBLPNBKpnYnisyyDLCOt4h26G6V7d72SjhCZ r9lKLszkoND0NXcw0SVsCwuyKral/tXQMX7Sw3uyDEgOzFl/cddlKRER7lKpEhDZrTD3XWQs2FsL 4E20nVHfJ10KUh8sGrO2FSCXF43xSpzsYi+JSJ2ZEoA6iTqrdP9v00IquoqZ9HvcX0A7CLX5Bmoq kwZSuTRALWWlR3yOoKUy4pLMye/vS80LSf0u9zPtkraiSjfPtAPCRIkEQr8bNvki486rWmaxhlnF ZJ3DOswp5xV74X6x6mCAPzeVL1f31I2bMBbAcFhOeE8Rxghjf98hn3TQRyy9Mi6MpYBe+FSsAlbp 3MdFgaOVmyhl6YuIJWtxiUWeJ24A+9XOh57IKF40RnqGdYk6qiqSvcIhXYNjk1DnNLZ3DLanpMJ3 Ur2mSgGWCnnC87KyKCcjWAgMdpVDeZvhexRowoUFvA4tG4oMmWtp0DApSHRvlF027+Q68oEeSpmU kBUncc1AlKyUDlxZC/Qy71CO6hZY+LELxl5G7nXzVaj6nuR2Q07jY1hPtLPS8L4sBIXGy25QMSaf RGmgwPHb5XHpkdqgazM6r+ZFpvU7jIV6NO68PLHH6MovMMRDsvTogJE3cZ6f0uAOeC0ar/QNpXmw ZGzuZi7SKsrXoRcM7SJUzKyTGX7EhH3Vo/dflLdtmPodZa2gSerr2/F0/Us9Gno5XL7ZN9bwH9qX sHWvQlA7wuaaatopcbMN/OKPUdN9lTZqpTCiele0SFCP9rMsFpHP6ludhW3OX47Ph9+vx5dK/7pI 0UdFfyNVa8e5jC2IJjAzyCv7OtriYdrap6CaywzKKL0b/wBjaEYvorMghQ5FN3jWbSwDk14mK3Lt SmQNdARVDGIYfiFn+6iyghYr/RKiII9EQVdSkyOLV4ciNmoM64brN3HEYL4G+G7Z4Z4o0Q9ufbGR sI/1K6FaEf7Vpv+NgkNXI9I7fH3/JoNcB6fL9e39xQyVEAm01UAzZ98fkfCQZiVzuRDdlkZ72mJ4 PSklI/R2/iCTKsHqlp4uNGoHW3lkmbJ/lUbUhJaG1/YYAIDlycgAagX649NusBz0+580MSyTmlpg BaVGGhutFN6i8QxQ4/uP/j8DyoU/iyDewv4jCpHjcdoazIe+tbtsF7mIQQeOgwIsLWyYNhfJox2i hIuOayiXJLhAIOvcSKqDimO7ZRmZ5etg2REbU/K9YCfjATIFUgLbGOaqu5ZtZGRcWcvoM7uEtrcz hx5jQypIph9vI/sTOQcj4zmZWSfS2uwK+UtTSx/U6D3rh/bsQRdYy/SvvEaadNttQroCgnKGQHJ6 HCeVHPKlWsD59eK3yW2suxBIapoEedLpQq6SThZfYOlj4+SoJTOk6oWcrVXVQSkMYUmjWu2v0BEO GEqWhP9X2bX0tg3D4L/S4w5DkQ5D764fiZc4Tv1o0l2MoA2KYmhXoCmwnz9+pGLrQaXbrRUZmZYp ik9RnAxX17PZzCdqxB3zcNzWHToycrKHNk2UBZT8oB4nqZaJRQdUZnDydTaeV94kd5oBY743X3HM OUTqYvHcGscr4PgmXybg49AnKlAkVEPNWtcTp5MuLUafn7o0MWFAy8IrVZX4MfAv6t9v718vcIPa x5scUov965ObgI7mUhDItV704cBRdtLnk3wUIGuVfTcNw/HRb5T7Utu66ELgSAtEPy54rWzEjd/9 6lNkn0p51LBAISVJeYfThV1H0PguV99m4YMmNH7ONE8UxZAynjnbW1JUSF3JTAh3rPw597Uky5I0 jccPqBeKPJINYYIbU9Ka8hOfe/C+yzz3rwAQRx4SRSap+uX97fkVySNE5MvH8fDnQH8cjg+Xl5d2 4zPUD/Hcc7YhxlYZdsnD3fkqIZ4D9mZ0/8KW7ck8tkMWZjuYdiP+eAR9uxUIyc16u0m6RbjZm22r F0UImIn1bECMkU0VzmUAZ+R70tUVFMBVnmvqwzQNVpcDdGF/KiaJ9hbq0gbfJTi9cdx31qZF9Pdp m8kDtkmptDSfLMX/4B7HGCXFybbwWbGn9SUVBbFw4nPx/gXnlZyMJwtQttQvUQ0e98f9BXSCB/ir FaMI3u/oam8ADfhsHn5drisrybBRvy+f3qSKkaYJPzWu5AmK4Bx5ECHepSNtaE1IiZVr0iTmnfaa kIh9UEIf+M7hIcINQDj34yYv/mGCxqucw2B+q3Tvmy7mcN7D27e3xkprTvaZfYiPth4/tYlB56Si L3Sc7J4Mc9qHhceNMgEPDhWXi9LrI+rgoaCJKJiWMUmvW9v7kzFS80OZxXL68dypK8MwGBGnQoy2 iRP0EHGMBRk6bZVA4L8807mjcQ6TRGpGsUrmrUbEqSGYbwp4G+QnDkqNVCO0PU+wXWfn1rN5lNo+ n+7wfoTAwfmZosvK/ulglST0jsrH/1oPcIZdYmQs38kSajD+3q4kPkkEeHr4JrAf4rdwzsNKR9Oq GgtmmvjU9rzSD/TzuSdOYl1opFELE5/s4WVa25mmotCSGkvDhlvcuyOArwkG4nwE6LBqYG83yWa1 zDrHduRYLgcqW+I/ZT5GqMo1t2C0/ejmJ46yeTpq+CCMiq4bZNyFYg+e8bZe1eh9Ft4sYbC4Ypg0 wGGcQ1tTPvCvvyvFN0z3It9lfRW8jbhopfajDYFtaicGSRCchrt6FywolzDrnRYZflN2VaKrLAzv +1K/qZGhOw5QxL6VZWLZww0Cfp3rjJDFcHIseKjMrBBGUa5x8Uen+eoZuyibijQKa17Cpu2xynzR QIYYl+CowgDivVupIAmkqwAr+u0n1Bv5qf2OCPTRZd2z3GkVKsyfV2lC3zTgCI6wl/4chK6MckkN PBLudad5Fb1D5azsDcpsxCn/F7d+7PXLfQEA --===============3058331277435751524==--