Received: by 2002:a05:6a10:1d13:0:0:0:0 with SMTP id pp19csp290417pxb; Thu, 26 Aug 2021 03:17:39 -0700 (PDT) X-Google-Smtp-Source: ABdhPJwi4cr3e91m90mbOkR7f9YjrNjrIEon/53PCV1Du7xa3V+0+ctYypG0TyEp1D8qNX6w3/u4 X-Received: by 2002:a17:906:8684:: with SMTP id g4mr3361313ejx.262.1629973059388; Thu, 26 Aug 2021 03:17:39 -0700 (PDT) ARC-Seal: i=1; a=rsa-sha256; t=1629973059; cv=none; d=google.com; s=arc-20160816; b=oSKcaD6V9W3nfGJKKxN76vgoz+c39G1JkiHAENFdTxBydV9WfpR36LMvgWf/7o/rqZ SGMZghJuKgiCC7ZFDPeLbmHI/UuvscPEhYj1+5SepBVwzNLrF8rscr5+mZH70vALbE6/ X/PThxXSAAjGkt45UFmwDODHK8gFlErOp57mLmlGG+4y007oEGt1wtOdYSBKLUqyYQlZ m/qtmSSwIWVbOpNBPLErWwR6YALW2b744uWjl8hJL/xOsfryVJ56O88t3PV1trADsxhQ xSwYWXWr48K/ZLN9QGTi4rFDbSuvpPlXX7mPhm9G42r3a+u5D4xjVwIIsv/j89+Wsi5a +Bqw== ARC-Message-Signature: i=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=arc-20160816; h=list-id:precedence:user-agent:in-reply-to:content-disposition :mime-version:references:message-id:subject:cc:to:from:date; bh=0maf6WWVb8yqT9bJs52IklzrpucLNbInSYcmWdTv18g=; b=YEitAIwy+6ukl0nZneWHYs23atD57UAdYXQrpZ3ltSCh+9FkDs1w0SwyFElXPE3xcP avOKvOFtaBfnDwobiGUoMkwfKveTL3PeRhPZLwsTscu/OQzSRErTi5KRmAoqnzRmzCvu xclMwlfDGTOLwGVuzCIIc2BTCBqcA1AUrFlzl0qp725O82DHhjmBDG+j6sgKPxJe8Qch lE6r7eJECoKWiZdIkYa74jpxGhuKkfnY9jVPmXIo5hFp6dHk2OKDDZKhPkoYpLMP0FPj IrZF4PxHJvcaDKbr2vxESInMM4CLdSuCc8cmeuJGvs9FMasRJvDyckymem++8OXhNppU JjEA== ARC-Authentication-Results: i=1; mx.google.com; spf=pass (google.com: domain of linux-kernel-owner@vger.kernel.org designates 23.128.96.18 as permitted sender) smtp.mailfrom=linux-kernel-owner@vger.kernel.org; dmarc=fail (p=NONE sp=NONE dis=NONE) header.from=intel.com Return-Path: Received: from vger.kernel.org (vger.kernel.org. [23.128.96.18]) by mx.google.com with ESMTP id ca20si2531866edb.178.2021.08.26.03.17.01; Thu, 26 Aug 2021 03:17:39 -0700 (PDT) Received-SPF: pass (google.com: domain of linux-kernel-owner@vger.kernel.org designates 23.128.96.18 as permitted sender) client-ip=23.128.96.18; Authentication-Results: mx.google.com; spf=pass (google.com: domain of linux-kernel-owner@vger.kernel.org designates 23.128.96.18 as permitted sender) smtp.mailfrom=linux-kernel-owner@vger.kernel.org; dmarc=fail (p=NONE sp=NONE dis=NONE) header.from=intel.com Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S241346AbhHZKMF (ORCPT + 99 others); Thu, 26 Aug 2021 06:12:05 -0400 Received: from mga12.intel.com ([192.55.52.136]:8798 "EHLO mga12.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S233880AbhHZKME (ORCPT ); Thu, 26 Aug 2021 06:12:04 -0400 X-IronPort-AV: E=McAfee;i="6200,9189,10087"; a="197279382" X-IronPort-AV: E=Sophos;i="5.84,353,1620716400"; d="gz'50?scan'50,208,50";a="197279382" Received: from orsmga005.jf.intel.com ([10.7.209.41]) by fmsmga106.fm.intel.com with ESMTP/TLS/ECDHE-RSA-AES256-GCM-SHA384; 26 Aug 2021 03:11:16 -0700 X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.84,353,1620716400"; d="gz'50?scan'50,208,50";a="643819069" Received: from lkp-server01.sh.intel.com (HELO 4fbc2b3ce5aa) ([10.239.97.150]) by orsmga005.jf.intel.com with ESMTP; 26 Aug 2021 03:11:12 -0700 Received: from kbuild by 4fbc2b3ce5aa with local (Exim 4.92) (envelope-from ) id 1mJCLn-0001AW-Cv; Thu, 26 Aug 2021 10:11:11 +0000 Date: Thu, 26 Aug 2021 18:10:47 +0800 From: kernel test robot To: Isabella Basso , linux@sciencehorizons.net, geert@linux-m68k.org Cc: kbuild-all@lists.01.org, ferreiraenzoa@gmail.com, augusto.duraes33@gmail.com, brendanhiggins@google.com, dlatypov@google.com, davidgow@google.com, linux-kselftest@vger.kernel.org, linux-kernel@vger.kernel.org, kunit-dev@googlegroups.com Subject: Re: [PATCH 6/6] test_hash.c: refactor into kunit Message-ID: <202108261826.fL5iv4HD-lkp@intel.com> References: <20210826012626.1163705-7-isabellabdoamaral@usp.br> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="7AUc2qLy4jB3hD7Z" Content-Disposition: inline In-Reply-To: <20210826012626.1163705-7-isabellabdoamaral@usp.br> User-Agent: Mutt/1.10.1 (2018-07-13) Precedence: bulk List-ID: X-Mailing-List: linux-kernel@vger.kernel.org --7AUc2qLy4jB3hD7Z Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Hi Isabella, Thank you for the patch! Yet something to improve: [auto build test ERROR on linus/master] [also build test ERROR on v5.14-rc7 next-20210825] [If your patch is applied to the wrong git tree, kindly drop us a note. And when submitting patch, we suggest to use '--base' as documented in https://git-scm.com/docs/git-format-patch] url: https://github.com/0day-ci/linux/commits/Isabella-Basso/test_hash-c-refactor-into-KUnit/20210826-092911 base: https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git 73f3af7b4611d77bdaea303fb639333eb28e37d7 config: parisc-randconfig-r014-20210825 (attached as .config) compiler: hppa64-linux-gcc (GCC) 11.2.0 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 # https://github.com/0day-ci/linux/commit/89fe4c8eec63dcabd6d3e8f3f71f3c2248d18dab git remote add linux-review https://github.com/0day-ci/linux git fetch --no-tags linux-review Isabella-Basso/test_hash-c-refactor-into-KUnit/20210826-092911 git checkout 89fe4c8eec63dcabd6d3e8f3f71f3c2248d18dab # save the attached .config to linux build tree COMPILER_INSTALL_PATH=$HOME/0day COMPILER=gcc-11.2.0 make.cross ARCH=parisc If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot All error/warnings (new ones prefixed by >>): lib/test_hash.c: In function 'test_int_hash32': lib/test_hash.c:62:50: warning: passing argument 1 of '__hash_32_generic' makes integer from pointer without a cast [-Wint-conversion] 62 | hash_or[1][0] |= *h2 = __hash_32_generic(h0); | ^~ | | | u32 * {aka unsigned int *} In file included from lib/test_hash.c:18: include/linux/hash.h:60:41: note: expected 'u32' {aka 'unsigned int'} but argument is of type 'u32 *' {aka 'unsigned int *'} 60 | static inline u32 __hash_32_generic(u32 val) | ~~~~^~~ lib/test_hash.c:68:1: error: no return statement in function returning non-void [-Werror=return-type] 68 | } | ^ lib/test_hash.c: In function 'test_int_hash64': >> lib/test_hash.c:75:31: error: invalid type argument of unary '*' (have 'long long unsigned int') 75 | *h2 = hash_64_generic(*h64, *k); | ^~~~ >> lib/test_hash.c:75:37: error: invalid type argument of unary '*' (have 'int') 75 | *h2 = hash_64_generic(*h64, *k); | ^~ In file included from lib/test_hash.c:20: lib/test_hash.c:79:29: error: invalid type argument of unary '*' (have 'long long unsigned int') 79 | *h64, *k, *h1, *h2); | ^~~~ include/kunit/test.h:775:30: note: in definition of macro 'KUNIT_ASSERTION' 775 | ##__VA_ARGS__); \ | ^~~~~~~~~~~ include/kunit/test.h:891:9: note: in expansion of macro 'KUNIT_BASE_BINARY_ASSERTION' 891 | KUNIT_BASE_BINARY_ASSERTION(test, \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ include/kunit/test.h:980:9: note: in expansion of macro 'KUNIT_BASE_EQ_MSG_ASSERTION' 980 | KUNIT_BASE_EQ_MSG_ASSERTION(test, \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ include/kunit/test.h:1644:9: note: in expansion of macro 'KUNIT_BINARY_EQ_MSG_ASSERTION' 1644 | KUNIT_BINARY_EQ_MSG_ASSERTION(test, \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ lib/test_hash.c:77:9: note: in expansion of macro 'KUNIT_ASSERT_EQ_MSG' 77 | KUNIT_ASSERT_EQ_MSG(test, *h1, *h2, | ^~~~~~~~~~~~~~~~~~~ lib/test_hash.c:79:35: error: invalid type argument of unary '*' (have 'int') 79 | *h64, *k, *h1, *h2); | ^~ include/kunit/test.h:775:30: note: in definition of macro 'KUNIT_ASSERTION' 775 | ##__VA_ARGS__); \ | ^~~~~~~~~~~ include/kunit/test.h:891:9: note: in expansion of macro 'KUNIT_BASE_BINARY_ASSERTION' 891 | KUNIT_BASE_BINARY_ASSERTION(test, \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ include/kunit/test.h:980:9: note: in expansion of macro 'KUNIT_BASE_EQ_MSG_ASSERTION' 980 | KUNIT_BASE_EQ_MSG_ASSERTION(test, \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ include/kunit/test.h:1644:9: note: in expansion of macro 'KUNIT_BINARY_EQ_MSG_ASSERTION' 1644 | KUNIT_BINARY_EQ_MSG_ASSERTION(test, \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ lib/test_hash.c:77:9: note: in expansion of macro 'KUNIT_ASSERT_EQ_MSG' 77 | KUNIT_ASSERT_EQ_MSG(test, *h1, *h2, | ^~~~~~~~~~~~~~~~~~~ lib/test_hash.c:85:1: error: no return statement in function returning non-void [-Werror=return-type] 85 | } | ^ lib/test_hash.c: In function 'test_int_hash': lib/test_hash.c:110:24: error: 'return' with a value, in function returning void [-Werror=return-type] 110 | return false; | ^~~~~ lib/test_hash.c:97:13: note: declared here 97 | static void test_int_hash(struct kunit *test, unsigned long long h64) | ^~~~~~~~~~~~~ >> lib/test_hash.c:129:39: warning: passing argument 2 of 'test_int_hash64' makes integer from pointer without a cast [-Wint-conversion] 129 | test_int_hash64(test, &h64, &h0, &h1, &h2, &m, &k); | ^~~~ | | | long long unsigned int * lib/test_hash.c:72:68: note: expected 'long long unsigned int' but argument is of type 'long long unsigned int *' 72 | static bool test_int_hash64(struct kunit *test, unsigned long long h64, u32 *h0, u32 *h1, | ~~~~~~~~~~~~~~~~~~~^~~ lib/test_hash.c:129:64: warning: passing argument 7 of 'test_int_hash64' makes integer from pointer without a cast [-Wint-conversion] 129 | test_int_hash64(test, &h64, &h0, &h1, &h2, &m, &k); | ^~ | | | int * lib/test_hash.c:73:44: note: expected 'int' but argument is of type 'int *' 73 | u32 *h2, u32 const *m, int k) | ~~~~^ cc1: some warnings being treated as errors vim +75 lib/test_hash.c 7d8047a5cceb31 Isabella Basso 2021-08-25 70 7d8047a5cceb31 Isabella Basso 2021-08-25 71 #ifdef HAVE_ARCH_HASH_64 89fe4c8eec63dc Isabella Basso 2021-08-25 72 static bool test_int_hash64(struct kunit *test, unsigned long long h64, u32 *h0, u32 *h1, 89fe4c8eec63dc Isabella Basso 2021-08-25 73 u32 *h2, u32 const *m, int k) 7d8047a5cceb31 Isabella Basso 2021-08-25 74 { 7d8047a5cceb31 Isabella Basso 2021-08-25 @75 *h2 = hash_64_generic(*h64, *k); 7d8047a5cceb31 Isabella Basso 2021-08-25 76 #if HAVE_ARCH_HASH_64 == 1 89fe4c8eec63dc Isabella Basso 2021-08-25 77 KUNIT_ASSERT_EQ_MSG(test, *h1, *h2, 89fe4c8eec63dc Isabella Basso 2021-08-25 78 "hash_64(%#llx, %d) = %#x != hash_64_generic() = %#x", 7d8047a5cceb31 Isabella Basso 2021-08-25 79 *h64, *k, *h1, *h2); 7d8047a5cceb31 Isabella Basso 2021-08-25 80 #else 89fe4c8eec63dc Isabella Basso 2021-08-25 81 KUNIT_ASSERT_LE_MSG(test, *h1, *h2, 89fe4c8eec63dc Isabella Basso 2021-08-25 82 "hash_64_generic(%#llx, %d) = %#x > %#x", 7d8047a5cceb31 Isabella Basso 2021-08-25 83 *h64, *k, *h1, *m); 7d8047a5cceb31 Isabella Basso 2021-08-25 84 #endif 7d8047a5cceb31 Isabella Basso 2021-08-25 85 } 7d8047a5cceb31 Isabella Basso 2021-08-25 86 #endif 7d8047a5cceb31 Isabella Basso 2021-08-25 87 468a9428521e7d George Spelvin 2016-05-26 88 /* 468a9428521e7d George Spelvin 2016-05-26 89 * Test the various integer hash functions. h64 (or its low-order bits) 468a9428521e7d George Spelvin 2016-05-26 90 * is the integer to hash. hash_or accumulates the OR of the hash values, 468a9428521e7d George Spelvin 2016-05-26 91 * which are later checked to see that they cover all the requested bits. 468a9428521e7d George Spelvin 2016-05-26 92 * 468a9428521e7d George Spelvin 2016-05-26 93 * Because these functions (as opposed to the string hashes) are all 468a9428521e7d George Spelvin 2016-05-26 94 * inline, the code being tested is actually in the module, and you can 468a9428521e7d George Spelvin 2016-05-26 95 * recompile and re-test the module without rebooting. 468a9428521e7d George Spelvin 2016-05-26 96 */ 89fe4c8eec63dc Isabella Basso 2021-08-25 97 static void test_int_hash(struct kunit *test, unsigned long long h64) 468a9428521e7d George Spelvin 2016-05-26 98 { 468a9428521e7d George Spelvin 2016-05-26 99 int k; 7d8047a5cceb31 Isabella Basso 2021-08-25 100 u32 h0 = (u32)h64, h1; 7d8047a5cceb31 Isabella Basso 2021-08-25 101 7d8047a5cceb31 Isabella Basso 2021-08-25 102 #if defined HAVE_ARCH__HASH_32 || defined HAVE_ARCH_HASH_64 7d8047a5cceb31 Isabella Basso 2021-08-25 103 u32 h2; 7d8047a5cceb31 Isabella Basso 2021-08-25 104 #endif 468a9428521e7d George Spelvin 2016-05-26 105 468a9428521e7d George Spelvin 2016-05-26 106 /* Test __hash32 */ 468a9428521e7d George Spelvin 2016-05-26 107 hash_or[0][0] |= h1 = __hash_32(h0); 468a9428521e7d George Spelvin 2016-05-26 108 #ifdef HAVE_ARCH__HASH_32 89fe4c8eec63dc Isabella Basso 2021-08-25 109 if (!test_int_hash32(test, &h0, &h1, &h2)) 468a9428521e7d George Spelvin 2016-05-26 110 return false; 468a9428521e7d George Spelvin 2016-05-26 111 #endif 468a9428521e7d George Spelvin 2016-05-26 112 468a9428521e7d George Spelvin 2016-05-26 113 /* Test k = 1..32 bits */ 468a9428521e7d George Spelvin 2016-05-26 114 for (k = 1; k <= 32; k++) { 468a9428521e7d George Spelvin 2016-05-26 115 u32 const m = ((u32)2 << (k-1)) - 1; /* Low k bits set */ 468a9428521e7d George Spelvin 2016-05-26 116 468a9428521e7d George Spelvin 2016-05-26 117 /* Test hash_32 */ 468a9428521e7d George Spelvin 2016-05-26 118 hash_or[0][k] |= h1 = hash_32(h0, k); 89fe4c8eec63dc Isabella Basso 2021-08-25 119 KUNIT_ASSERT_LE_MSG(test, h1, m, 89fe4c8eec63dc Isabella Basso 2021-08-25 120 "hash_32(%#x, %d) = %#x > %#x", 89fe4c8eec63dc Isabella Basso 2021-08-25 121 h0, k, h1, m); d41da448b96d6d Isabella Basso 2021-08-25 122 468a9428521e7d George Spelvin 2016-05-26 123 /* Test hash_64 */ 468a9428521e7d George Spelvin 2016-05-26 124 hash_or[1][k] |= h1 = hash_64(h64, k); 89fe4c8eec63dc Isabella Basso 2021-08-25 125 KUNIT_ASSERT_LE_MSG(test, h1, m, 89fe4c8eec63dc Isabella Basso 2021-08-25 126 "hash_64(%#llx, %d) = %#x > %#x", 89fe4c8eec63dc Isabella Basso 2021-08-25 127 h64, k, h1, m); 468a9428521e7d George Spelvin 2016-05-26 128 #ifdef HAVE_ARCH_HASH_64 89fe4c8eec63dc Isabella Basso 2021-08-25 @129 test_int_hash64(test, &h64, &h0, &h1, &h2, &m, &k); 468a9428521e7d George Spelvin 2016-05-26 130 #endif 468a9428521e7d George Spelvin 2016-05-26 131 } 468a9428521e7d George Spelvin 2016-05-26 132 } 468a9428521e7d George Spelvin 2016-05-26 133 --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all@lists.01.org --7AUc2qLy4jB3hD7Z Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICMVeJ2EAAy5jb25maWcAlDtbb+M2s+/9FcIWOGiBprUd54aDPFAUJXEtiVqRcuy8CG7i bI0vmwR20q/7788MdSMl2tvz0G08MxwOh8O5kfr5p5898vH++m3zvnvYPD9/975uX7b7zfv2 0XvaPW//1wuElwnlsYCr34E42b18/PPH22a/Ozx4F79P579PzvYPV95iu3/ZPnv09eVp9/UD GOxeX376+ScqspBHFaXVkhWSi6xSbKVuP/319ra5nJ89I7ezrw8P3i8Rpb960+nvs98nn4xh XFaAuf3egqKe1e10OplNJh1xQrKow3VgIjWPrOx5AKglm51f9RySAEn9MOhJAeQmNRATQ9wY eBOZVpFQoudiIHiW8IyNUJmo8kKEPGFVmFVEqcIgEZlURUmVKGQP5cWX6k4Uix7ilzwJFE9Z pYgPjKQoFGBhF372Ir2rz95h+/7x1u8Lz7iqWLasSAFr4ilXt+ezft40R4EUk8rQiKAkaZf+ 6ZM1eSVJogxgTJasWrAiY0kV3fO852JifMDM3KjkPiVuzOr+2AhxDDEHxM9egzKk8nYH7+X1 HXUzwmvZThGghCbexmopx0PEaY5zB8OAhaRMlN4xQ8MtOBZSZSRlt59+eXl92f76qWcr13LJ c+rgeUcUjasvJStNgyyElFXKUlGs0RAJjc01lJIl3Hcw07omBTAkJfgKmBXsJGntD6zVO3z8 efh+eN9+6+0vYhkrONXGDPbvG3KYKJ59ZlShwTnRNDZNCyGBSAnPbJjkqYuoijkrUO61jQ2J VEzwHg0rzIKEmWfQFCJgfhmFUutq+/LovT4NFt0dIBYRuq7woBbwLzVOsD68ixIPZXPotPL8 PLSU120GIKpG0bZFNQLYA9tZ8oKxNFfgc7Qj6ri18KVIykyRYu200obKYQHteCpgeCs7zcs/ 1ObwH+99923rbUCuw/vm/eBtHh5eP17edy9fe2tAZVQwoCJU8+BZZHg3GaCJUAbWCXh1HFMt z3tkLrn1ozsxAZfoJQNzw/6FsL0iUFAuRULQME116HUXtPTk2OAV6KgCnKl3+FmxVc4Kl1Jl TWwOH4CIXEjNo7FGB2oEKgPmgquC0AECGUsFBobhIDVPIGIyxsDps4j6Cdf22qnSXn93sBb1 H8ZRW3TWI6ipFb6IGQnguDmUkggMOGD7MQ/V7fTKhOO2pGRl4me9hfJMLSBKhWzI49zyYyVE 3DqG0hhWSCHoLcbH3kbqbZcPf20fP563e+9pu3n/2G8PGtwoxYHt3G5UiDKXpgbAB9PIeQZr 4np+h3oadM4Di18DLgI7Yg3xIdjYPStcfHPw/srwf7hnOE2DcUwWsCWn7NR0MBQP7fFlpFxS J2fwt07GGAdlDpYs3fPGjC5yAZZQFeBkReEWr95cUiqh53MdzbUMJcgBfo8SxYyscYiplkZ+ U7CEGLHGTxaoJR3YC4OH/k1S4CNFWVCGQb93GcHxzAVwx7MWQA4zFhO3unesU48xsir9e279 vpfKEN0XAqOAfdAh0RU5BDh+DymuKCrwd/C/lGTUCkJDMgl/uHVPVQJuk7Jc6bICXZe1A4jX +UiZkYRHkFUnibjrSWqX2/9OISpwMOPCFEdGTKXgG11h1trsPt/pxoZ1wuCKlELyVZ0BWKcJ vZOZz0cmO59IUEnplCEsoazqR+qfcDDN4SwXbvFBNSQxax4tVxhYg5csU6HL18gY3JRRWnHD ULioyqIO4h0nEiw5rKNRl8u5Az+fFAVnRgm0QNp1KseQqlb6EKqVhSdN8aVlX7jBOgFwrmZB 09xad+qzIHA6WR0n0Ihr5VieNqfTyXyUEjQlcr7dP73uv21eHrYe+3v7AvkFgfBAMcPY7g9m fmewd+Z3/5JjK/IyrZnVGVpte72lJ6V/wqliMUhU5RcLt7dMiKsoQKb2JMJNRnzY9yJibXpm DwIsRiXMMaoCDpVIjzHpyGJSBBCmLSuWcRmGENRzAhOhNwDnLFyBTusCE4mcFIoT61TXZTpY tWOcdkI6tFh1gF18d8edFHVkM/JJH20uCzgx8qw0NdIxSEsgR4aIdCdLo+bRfg5U1zjdT5v9 w19Nk+aPB92SOfyhGzu7h7PL+Z+79+px+1QjulKyzWpqtzMAxneMR7EaI+AUc7+AIAfTW3FN 1zLgcDHIDuSv00xYQC5MB5xHdc6VgJEm8va8PjX5/vVhezi87r337291Um6lVp02ryaTibti IVfTySShx5Cz4+POh+M61PVqMjFEJzPzV8FCpnTdbO11FZdR248w9jcRWaSdYQ+7nPtcjYZr u8WAWM0X1rFq8FCag7tYoXqdpYTt25pBaHZKQHAQ0doxCGpYvWeGcCrxq1zZKXEsVJ6U2ogH VglCQe3eNhRSEZhrrylAEsmAAEwfDWCADsGJH0X2Yx2OI76vpkf2FlCzi6Ooc3uUxc7Y5/j+ FgFmv4wYu6b7IFrMHpYVOle+nfeNohUznID+WWEf0HQgp86APgThbv/tv5v91gv2u78HQYQU KSSzKYes444VTdfDufKaMj9O2aYXvEjvSMFwU1NiGVV4V9GwyYmcc/g0nV+tVlW2hOTW5UKh wPWzlQJOhrMRIsLOaDPvCEEhiddJp7JNpEFjISUyKNVPoTom5nIaqmUejKK52n7db7ynVvGP WvFmsXeEoEWPtqxu9XwcvNc3bJ4fvF9yyn/zcppSTn7zGJfwbyTpbx789avRQ7PLozjPXSGW Q/VeQnat87N+feAAEiK5YwCi7sjKKsklcaYh/17o2qOTM/Q83uFt+7B72j00qrGMlsZESi6r hEKx4cy/8oC2VJZX68EgfuEyXySRraX0Z+yYVFb/HAPr7n37gGfv7HH7BoMh32pXb1x4FETG 2qSGZ9sFA79thEgGxm+4289lmsMm+abfBPEVBN8FW0vt9e0WvU5NdQipdOWDdSzF9tiwM65b riNowZQbUUMrqLbCQbnVN381IhbC1S6BdfAALxTigpFgMLpgESTzWdCkOLXAFcm5axaXTlxY swQww4amzcAn6lYQJP0rGkcuVpJRdOsnUOislVmrjIYkSrS9VpPJkhdq0O1EVQ2oIGC2kY5R HprtPUCVCewHlDRoQXqtg9FShAqb07Bl4i6rVTtShaxH67wakgvXWoHICGIUMhbw0sALTtig x1SXCeczND5MAd1tJLzvYiGshmM5Eprm3gklFRiNam9FiruVaf5jVCcCJiZmnSNHrjuiYnn2 5+awffT+U1dQb/vXp92z1YxGoj5X63P5U2OHCf8PvEXXQIH0CCt288TpAlamWN1OjZZgveWu qrkxBt0hTuD8meWBvubDHm4uwDG2jq+dCRXm4EhkNjVZ4L0lWCHPqjLTOgbDGuHxYDf4Uzjn 2LuCK3ZssIlsRuu9ZP9sHz7eN38+b/V9tacL4XfDE/s8C1Nlu9i2mHWg4IftoRsiSQueW7lB g8D25JGKuWABeCJnyDwmtl5Tuv32uv/upZuXzdftN2d8OZlVtxlzSrLSLl77dLnGuZK7erDh Zuo5uqsO4xjmCdhVXQq0aa3tCejwbqSrPSK0B6z/rEuelEfFYBL4n0JrxHLdqIhiiHwkCIpK DYsl7VfB5fql2S6SxoraKyBMXmHKTDO6nU9uLu3aoi5Qu8vQkPCkNE3jGDy+ywWoK2vuLU3H yUhGCY3N+1Z9w92rLSWnujAt9kh2jfhR7m3gIHkm8vaqH3CfC5E4Wd1r5yNc1W8dofGSpdWk LkpTH8shI10M2l4LJgULd8skZwXGA0xorEASlbm+A3WenuMHxLgFYGrk+IPt37sHs0gyAx3m qoYfGP2q7xUG0RGyXbvx50qlc0qJ2dqvs2N7HELAb4OHpHwcsXJ69rDZP3p/7nePX3Xjo89K IVWtF+SJoZcg5YonnICN1oeh74LW8TFmSe686QnYUqV5aI1pYeBtIKq6zSILSGJlOnlRz9SV jPqdSOu8uxro+XXzqKunvoxEXZhpVQfSJhXg3Z2xP9j06OvD/n1EPwobv82CXUwNNBzoJPGt TKmnQ7dW1Kn0uJRrlmFU1HjloK933NGgUy0c6SooIFF174ZGs2XdShsMw1PSjAWXmoql88Yh rb4Iab8taLnUQ3PmxHZ9Pjik9WWe2c0T1HazkMTXDQHrd8VndASTecpHwDQ17w/a0Wau0MLO DY4Ber0YNl5bRWhuMKJCllHWXRDZSdr48HRl+KN2FuZpKvD5lmIYokRRJamVDagpFCuuyltj Vpab+AJWVDGfu+/o0pijVo+W2q1g3RZlZmWHvyA9KOq2tQlM8erbhZC8CHtM74IRV/qrBuVK OlV3lPPN/n2HGvTeNvuD5V2BCnR3pZvp9gU3IHyaXp6vVjXSPQVErkDngC0DAyXCU1DdbbqZ XB/BAtMFRMsqGwzXSVJR8RQcjSKRE6mK1XApaIK5TE4uBWxUN6ocQreogBcM3/qt68z89mxq T2Ox0Jeb+iLD2SQZ02MSLrJkPRQeTVJiYjiSvu+QjLZY73wJf3rpK75rqO+d1H7zcnjWL0C9 ZPN9ZAtC5GOFK45pH5zgFN9dFa1ZFST9oxDpH+Hz5vCXB9XUm9EtMk0k5DbLzyxgdPCkDOHg z4YvzZrxeDWp755FNrJSRGdC3hHXO4CWwIfotoYiBclcDBID7z74DWHERMpU4WrHIwn6P59k i+qOByqupvZKBtjZSex8rAU+dcAGXIRyLhCdYwKh+ISOSBpYTwVaOOQOZAwtFU+GE7nbxhoj UpsF8SXL7FdJx82prrw2b29QybdALMtqqs0DNuAHNgepACwXdQpVcTS0aahQ0rEhNOCmBD1q Bi2ZCI8stiWIci7q+sWaXdKL2YQGuQ2FnFgjbKiSFxf6WsOWQKekxwWEYnCwFX16/gMt1i+l ts9PZw+vL++b3cv20QOeTWBzH3CZM1JUMuUjr5sct4g8BtzgAKhgCIPfUC8qkugyxqoDGywr dDcGsdPZdVNL7A7/ORMvZxQXdqywwBkDQSPjQaJP4/pFd5XeTudjqNJFdPtg7IdK0rJkkHjb kyJk0GrWBzdjiHEC8T07D9d1p8VNMXphaCIlSWVpP/Yw0eAzjuxSSzFboWeORltWkLuqkbqO CZv/4t325vl5+6yX7j3Vxxn0tH8F6HAHNHeQDq+o1cDN1LLBSZodgePWnEB1Bc2QoMkGhuqo ZVEpO5JP1QQpKZbMfNjSs01oleT0fLZaObDpSaxf0HS8/fVyVhkZRb16zyFP13+dkjeEtIeH 1MF4GV5OJ1XmxKUrF1TilS9Vbs0FZMkzZ5HdkajV6iYLwtTFO5QpdfIFy12d5BpzyS8mcwdP zJxcizOfchlLHh6fWmYsKly6UOn5rIK1uKwzZdJslBk7ZhZRHRg9Nr64c6AolLYZZQ4MAc+n H6OMVaajfZVE6ahbke4OD44TiP9Yj/D7XeVyIbLmGb9j0zt0nbphpobvBk+apGNQoAv3ySlS 31et/6vby5SCL/4K3tc7fLy9ve7fHQtj1LWnAIVUr4oJFLVZ9EOC6phpNmTga9ydZIeELU7H Bb2OJIfVe/9T/3+G97Pet7qJ5oy2mswW+QvPQtGlzt0UP2ZsMin9QZoOgOou0TeCMhbgSAfR VxP4zG8+TppNhjj8TMORZiEqSkqosY/YSLzOWWH1LmI/pRAlLi/Mp6055aGDNlDGjovQ/LvC JordQwEgXr4EypcWEFvteF9jASHNSdZu1EL4ny1AsM5Iyqk9U2PmJszqoAi8KYQSdonFltno rxEiWdqzCsgLrJddujme4nOwtgeKBdzgLdcRABCbW9VDq5CH7s+iDJpxTjqgicwHdS2QrK6v r24uxwjI5eZjaCYaKevUapkyT3ZHvz9aJrzzeuOmEVQgUhTYa5DnyXIysx4kkuBidrGqgly4 K4GgTNM17p4Ty6m8OZ/J+WTqur3DFKOS9tsQcPKJkGXBsKWje3lOxro9RQUEWuZ8MkzyQN5c T2bEfLLGZTK7mUzOhxCz2miVoQADNYcpWovy4+nVlev1VUugJ7+ZWN2XOKWX5xfublogp5fX MxfDOtHsCLFVnq0qGYTMdemBCQD8s2DrqpR+vyY6y43vLBkDD5mOY0UNh12ZWV8hNuD6kzDH pA0+JavL66uLftIGfnNOV5cjKFT21fVNnDO5GuEYm04mc9OBDyRu3jb9szl4/OXwvv/4pt8T H/7a7KEAecfWDtJ5zxhwHsHkd2/4p/3w6f892nVa7K4xwUcWBPsEuZEWMxpb75nwMrYqlFzh Hjn0iZ+amLcTy5xkpv9sAG0fuq9ozbNdl69U8rYWG+02IvFS1mThGlB/GskY86bnN3Pvl3C3 397Bf7+OWYa8YHe8sGLvyZE175e3j/ejYvIsLw0XrX/iays5hIUhRorECis1pr5QXgwicI1L iSr4CnGjDBF7hs/4jHGHL9SfNpbLbEaLUrKALYcztvAql6RcHcVKCtEzq1a308lsfppmfXt1 eW2TfBZrx9Rs6QTWD6YNfY+6AQPFgA/xBSlc6ashoZEo4U9Y78wBgoMx+Gqsw/hrZ4Lc4RMR cfh/nruHS0gucgVB5iSTjgryVytF6knour8xGyH11bB+Mn9yGpYQKDesSnyEOy4BtgFZwukR EURJ4wU/0ozryEL88B3nOa0Plwzju5UaTvI8YXr6ozx9ml7cXM2HHOma5GTMEFWBfvMou6Vc rVZWq1WDByVjLXS3s5YjHiKtYNidHml/2NxCKpIRMDsX4jxwQQNrzwy4K6/v0FT4ZjndwaNw 5hIqKszvxy1wZb+Z73ElTxKWCpfVdkRYIeNbfAdvyQNw55l1w90hVRpQBxgS5ML+WG6AOhL0 hlSz85mD+x1+cyUKJ3u8CEvAtJwnpF8TfnMpCv9fUPmjL9ZHZPgwyHkb3qvpjgfww7GW+5hl cUmcawn8m9MzRyRlVPxgraosfGxVhqtTEhJ5MZlOHQJifClTl9GtchI45UYEBOLTYmkijOCn pMpXhcu8vtxx7j5toeTk0vmoXB93/ZTaMPL6NxpjBVtN7fWYSJ4r5np5aNDEJLsjdlPZwC58 5fzszCDJIbWWpkducLVLBquHWmc+dGDaJdfZgTGwB1bX13l6fWkXISaeBFdQcroks4iomzsp IGmZNm7XzV9Xd+nKHbMsylJUOV9R7jpKJqFfzqaT6blbIo2c3RwTB1tn+CSY0+z6fHr9g5no +pqqlEznE/dkNT6aTo/ilZL54HbDQXBCfzXFXPP4gbQBuZmcz90TYf8Fqqdjs8QkzWXMj3xg blIypviPiSKSEJe/GRM5Mg6LaEXPj30tZ9KF5WeuZPmDKSMhAv5/lH1Zc9y4suZf0dO9fWKm b3NfJqIfWCSrihY3E6wqyi8MHVt9WnFkySHJ93bPrx8kwAVLgqV5sCzll8SaSCSARGLAW+hI 57m8NWB3lEh/esFg+JquyKncmUGqPgzYFE0CgUhA7sLAxsHDqf5iEKr8tt87thMa21SZH1EW o6gwPTReIgvdzNE5N2S7Sgbbjq6mU6V0cpKPfSW4IrbtXZUQqob2CaHr7vYDvOTgBG50nU+z iFG2ohqCUzn2BLN2JcY6H0TzVsrrNrQdHGrzupoi2WB9mdFlce8PVoDjXULaXd51d23Br7Lh VS0O6AVkkYf93k23b9FU2O8X9KqexAbuF67rD9BmeKlP6Y6qZaNQ6BMJLsxZH8EdP2UhgvNW dMa4ptQuVRwOxskWUMv/QE4x7esP5GSaBMGcALeNhvADIjQXYPqQombGSVJ/KgwCBrhbmbGi 3wBzZp9ulZFpuqttBpxZlYLA2NimrFaojlE2Sp3lsIg2qG1WMPAxoJbZlYQgwF67VcFP4Ed2 Xf5Ya5X4yYPG52CrTpXry13fNXVh1M+8f6iRmXq+smAz8jMN9rEyJuTuY/qT/V70ju1eZyVe hF6JlplSZnYYNC2FHcsaNsw2zmEwtTgYboJjYcq8q0bZ9VSyCIoyT7CtMpmJbE26pLfpsvpq Q5K+2qO+oQpTa9QvZIgC//pc27ck8K1wuMr4Je8Dx3GvFOnLvPWA2dINRIAoxvPeNxjsXXOs piWEa6pX8Zn4wweKC1fZCky3TjunUkgNTpsXa2NT3+Z3KCqAyl4tXcnZnjm/pCu+NHVCTX22 G6YmnvSpY8yZL+JS+qWs6ji6oysksUGn3WZ3sGhT9r3o+cEhWo3Ys8f20iF5UXCgM/KZxeqQ d3lmhiJlLPx7cwMnQxgGsTvVWNt/r5LIk0/2OMD8FHd0LZDj9oPAleVpk6FbPwITq4neogW7 AtHnjgrBVWk63U6whg79pxhpFIiDUCU9tkbkHHd0OivqWzW9tLItJL0uP5xKdnmAt54x2Y5O 4NATeE+zwe3YkZkjGVqHil3LJlqlECf2H3bC2Y4kg+MzrVfbpKyolW/Mrk3p2A9cl0rRCWnF dB/5IRbUdMIv1SQZyLcUY129ITTdbWT51+SWCU3XQFhLOAZvMiy3LAmdyJoH80aWsCkQuHxY G7Pkpu2I9E42lK6nnV1NZHm7nUNFRVtfDMs4kT8TJ4gTvSIUCJwA85SY5TNxlcWfBBjOEKbK d2em1Aw6j8GBvw2HJpgds7Nxh2ixjt1pb82CSO2AcFZzeuVID1rONnZbVxWeYp8wknx9CSik 2imUvej5MFNUe4jRnWw65lb5xZ3iieKoFFfqs4mGmwMTiAkBhyRHJ04BFwN2Xnm8f/3GrrQV vzU3cGosubRIlWJ/ws/JD0Jw6QCgTbrbHRo5jsEHkkoHm1wJCX8XJXi1qtlRk0P6jFO75KIX YPIcoOxoM02lJA7E/zMWM+nSEckwabFiNGWbUoi0emHIqfaKK2VhqkphmRhOStvDWYXsZzVT xpr4fiQWYEFKRV4mbwKsyxdPA8yPgB9s/3n/ev/1/eFVd33qe8meOuOb1ae6GGI6lfV3aKRX HiwZ0LWOK3GKNez4i89gmYELCITthAubsziTh9fH+yfd13E6BWA+d6l0tZ0DkaN6KS1kMbzn dGvIID3zB3bg+1YynqnNmNTi7S+RaQ+HhremPFMeq+hKRkpEIKnQaLRyKQtDwepuPLFLax6G dhDApMoXFjTzfOjzWommiDImpIXAwmdI7SpzdrnK0vVOFGFGvMjUSDdXRYQOZzuS959EuOoD PwyvFoIKegvBxK8ywsFnjRqHIpfiMi5Cu7QKndDWQLj4uDqBc/fGl+df4RuaCxshzDtL92fi 3yfVjurR0rKxMbGC16WUrXywNPiK6EOfQxgnrYYcoYpHjMM2YbO7vJopo1/PNC1bEto2JgUz dD2R9Y4MSufDR7yVh+HI8JrxqwXApaaoBow2J4diRp0JZSylK0QKYEx2YVh0ja324Qlrf0r9 QNMfqXVY6C3LyGuOjt62nAPJwMA5t8y1soAy1spzJPoFHg0ytqBsvApE4xeVGBhlpRn5mW8w 6CczInyrttC5j3x0I3HWUJgObvh9SVOapNgX581+Af+w4rM51896NUma1oNeFE42Ng5J7aAg ITpVLJhhbTUP0KLa5V2WIKlPhuynPjmArGL6U+b4gCblH0zJGTHY9WGhcLTJX2TaJacMIsH+ btu+IwaCQXivlqwaCLXisHItiLEbJk/uloyGdpIZPjK0K/Dtu2aO0EWCuUJwRa5s0RqtkLFK jKWo92U+GOqkcHykUvSvfKBjY8yKQ5FSg3nTNiE9tcs2KsjuqulDgt1gM2qfc7474eLHIfOw by64B9kE0yG0IVxFucsT2Asj6kpWRUdc7mUeU/VgMkMrNwMsiBLPwdbV1syEduVyQ1ha2ajF TPuuVLw7J6iG28YQsEeMTFQ1Q8Iv9pXiJ/V4zEppTVGfSmZnYduI53SKKaPlCU7XknusQGcl pSnKy1lK0OLirzQeKvr3ZfHHqPLGXtlu6Jq2lRy6IXIY1psFXIGdXv9RqGBPj1nSy7tNDGEX CVj0I3wjEZh4RB3uKLpPUnSfGfjER2w4gc56WpbsPaeswcJs8SLBtlqz3ytp3aZk3InXZafl F9AZw06+mVi3dH1B5zERN2U5pT2m7ImLVr6+L3GwnQ0kmakwux4tC6XtPtKKx8sU4FL8eCHy Jw+KpsortK9Wxl3iuZhnzcpRDK0nGwArxgVs83NFi66AtnwRoB7zolzxfLirG4IlCl2J0eG0 pFeeh1rRlI5VNJjbyjLQtW7OVhpT/DJ2ce+rebOI3NUpnKRI+w8QNq1K6tGTwm6vVNGDkKSd 4/F2n+PVmDJd60QlR+nzWcek9F+Lto1EZnwFUU+1OVVsvZmRGn9j2hlCj4tMWowAlItO+EWd G7yVRcb6dG76Db7t7M600nD3d8AU/pwN6V33S+t4euvMiLyTTq2w8o5OB/Byo3izaKYjnOJV W0bktw/WB7w2+nruvu5ELRmIiMQjuokV4nd4qHmuX5WSzmRoe7ILPHAlWiarMeAZjb1FcZaJ fCXLL47+fHp//PH08BctNmTOIopgJaAG5o7vDtMkyzKvD9IAnZJlHJg+XuBKujc1kcs+9Vzm zaYl2KZJ7Hs2Po1JPH9t5NsWNczxWAZdjoe7BDzLhY83i1CVQ9qWGWombbaxnNQUBBC2kA21 me/4LOKSPP3r5fXx/c/vb0p/lYeGxyaVcgBym2KRfVY0EcVayWPJd9myh7Bwb8IlZbE6xeAf MwcXc/Y6280/IajcFKvnl+8vb+9Pf988fP/nw7dvD99ufpu4fn15/hWC+PxDzYAv60yVYbO3 1gB9jE2iDBqGIlGGWlqpDr0z+bapEzVxiHJCetyvig1HUCQbY2QKMSJnluXwThKLYCmregUk ZXI2o8Luqyzj2PpLwPkE7svpylb9TBnnZ0I/sSByMsOxOBzLRL51xOlEqW9RHVQCVRGtpgaL pnUHRZt8+uKFkaXW8TavlMEpgGWbijez2IjuA19NuerDwLEV2jmg9tagqZXBcH4PcyE3YA1l aaCDiZpeU6Gx3xh00ZQaHb9LZxuL0VZUUE2JtrVS93ZINAImbvzyviq/4radVIiuwN1QQM25 qeOJlzAY8UgXibui1GYeUlQ9enGegcqUyKzcvYcRQy3hUx3QtYtzwZwvGcNd/flEzf5O/ZJt do+71hB1FViwQxkEHvdq2vACctIX6LIS8EulVJnvOSm0slMJbazLckctXk1/539RM+eZLv0p x290RqI6/P7b/Q9m+6jHnFzHNHA59KSO4LR1AltRLWv0Drkcza7p96cvX8aGLj+NbdonDaEL X7Pg90V9p95VZHVq3v/k8/NUIWFikiszTfVyqfekUCdNdIKUZEcfQIw0xUvAEIjtAjFeVC0P sXixuQHoMKdj9Dkss1BkrZSufG25aAugjccUvzFEWmycyNF2CdvQoErfDUJLIcPmP7jJgLEp LH/ECYL+Idm/3GOEFEoEtpX89AhhIIR42zQBsIrXJFsxJCj9g7ePsAPVtxMPX0+2ZE5Vt5Th c7qWhLDTt2xhL6c8QcxRAEX02DUrNk26SyHYo2r37y+vYjk42re0iC9f/60C+TML+98e7+Ah bQiCUOc9vOQOMR3ZTgTpkwoiSt68v9A+fLiho4KO7W8s9iod8CzVt/8SQ27omS1lX6zuiTAH dJ6AcXl3dv1AWh8I/GBk7091OodIFbKgv+FZcEBYcIPYb1nzc7kS4oYO7iazsICXI36bd2Gh libtMsz5cGGpMrkuQNxVdhRZOj1LIt8a21OLfMOcAh2dvroPKEBFda9LrEheXaqojlBT+FZ+ 83xGCJUacedyoQ+2byElAH90hMz9PXX65JmAlAhcMMV+noEmzUtDcKOlnkVKKwTB14jBKl8S u5RIFZTYpQs9RA8aFzi2kO5dlisofTx4Zsg3QwFWPrp8cSIbtUIlFhdJeAqabUg2wK/gShxO ZPzYv/oxJuQcQISVZ4chbE03a1StLOndoaYLNapzNoojR2peqa1pgbeyOKOk5sRvUWCXd9SA w7IDTbUlavzLcXfwxFAQS4Z8MYIMwiHBcqNkx99qE2AIUdmgU/vmSGSLBGYEgAHwAVay01k1 5ZcQ8Fso5lmzozPm2/3bzY/H56/vr0/Y42+LVqHzCEkwt7plFB/Hdo/oI05XlsgCCLOYAYXv 8ipnL3brjU/BLkrCMI79rS5Y2BCFIaSBKq4FD7entjWdLeFbuXxE3wmovYGGyOhdP3W3Wwrf N9T5go+1aLDdaHHw0fww/1qdCzMCVjTcRJMt1Nush5tsmSzdl8TGvqb0D9XK2yy3h87kK7xt lK182KUyncvbziw1vM2rMeYf7Hcv+Sjjbpux+1Jjm5hiOuQYOuK9ABULjJVnKBZARGEKHaMY MfR6XwGbuyVsM5MfbuUUXRu9jCkwtoWbbFfkmjAxJoO2JcfBFZfZpilIz55vvG62IdslM9xc FHgCb9PUI22HmJ1AHUkaRwEyXueTYj03vrnmbInPxBPEhnT3oYdarRMYbE9NjOuoaACcq2pt H/edntn6Yiwa9rj4Rn3mjTqszMsmXpnhN2U0RmqYfpCTlBke0AJLc2uIrHwDQXtVqEWAH24g nPaWhhL4HES+xBK5s/VWPXx7vO8f/o2Yb9PneVH3cvDzxfw0EMczsp4AetVI22kixB4vR23c 3gmtbcXNThG29AljiPHUI9vFQ02ILM62REMZ0UgUK0MQBsi6D+ihoWABtUau1QkVLChwsP1p ZIfILAb0CDX+AIm3px7GsjUgKIOLt0Hk26huom3gxkrLLw8GGsRWSx1cAhI915R4YRkhxWEA bsj3VXsOt3ch8s+ngt2ePwlbzbAuoUSNwGKdt0l/nIKh+7YzczR7ZTUzf1J0n+WdIr4BpzPz ZyMVWiq5LSyk8WwrVO1hEH7dVnkNjhHhArlrrc4PPFj89/sfPx6+3bBVu6ZS2HchnUDXuLwi YjyA5qh2Ai2QjVtOnKc/yqON10qI7JMP2Pkdv+u+Hk+r5OFA1ANtjvGTa7XF1ccZOHW9jiKS s0vSqgnk8PY2ty/kmhi83fgxcg//WWjUF7HL0TNtztBtta185MxJ5SVTSEWjig8ErU3Passh N7RmOtyXMBWi2kUBCdU2rFoWCUFLjJ8+m5usGvA9kwnEzUh+2RPOW+Zu2mAbjFIOR4S6pGb4 tXk+3pMq8TOHqqJmh0V440zsboWqKYpGbxxSwyGJ4sgjMWASSPXZOFxQy25WSql4xYgR5ztM clKMakeBucZ6FBsZ37ygNwWdgOL02AEbwwcYFCNRB+By9CunNpRG5ZFU2bgXY4Lw0ZD1ruO5 kpPjhv5c3HwY9eGvH/fP35Sdtun1sNb3I9yMnRhq/ASdj/PLiDt2COrewiYBBxlinG588oAP A3A1c/EV18qAbslOMMSj0DPv2yJ1IrPGo/ITT2cNwnmt0rh8UttneqNrTS4v3Tmdh5MxzilZ aEfiYf1KdSKFyv1tND3pxp6rEaPQ1ZSgYgjxlpvPhRQ9k/q9H+GLPT6MSydSXfNkNcAjHkmt nbp+FKvF4nGNogDpPB4TZWP4f64GWT1Ig3+JfCdSeQgPLTNKjmP8Fj3S9TziPdlh43D6CkEZ fH58ff95/6TaRYrQHA5U70JYmY3pp0lvT/hT9Ggecytc7NlQs3/9n8fJkaK6f3uXZPpiT892 jhlxvFhoRRmJpAXIiplmTvFr+4JbKyuPam4gLORQoG2AVE6sNHm6/+8Hub6TL8gxFx/UWuhE elhnIUMbWL4JiIwAe7VVfpFa4hAjFsqfBgbAMXyhHONK37iYZpQ5bEN2rmtO1aVmg7H7BT58 aIs8voVZeiJHGFl4CcPIUPQotzxT2aPcxpebstgsiz64fsPeXpI8qwQy4vSAMfGgYsJaVABh DaF6xaq44h2LcB3yqqixC0MSk3x+piDwa69cVRR5uGcA/+NKaUpa4dh38Lxg1S+HlRPRJeLW lSzWwiIgdhtGxLmVeiUHznSlSbvFt3ICu5y93Vw1mXi7kCclY3jJWDwkpGTwfFWFp86/J6e2 lV+JFul8GwGrcZZwRmEinRaKSZaOu6SnalhKdoqSBdrthNnDE64kyh69n2lLWlPyS8Q/VGOA 49kBHPypDWYF2AbpnEyS9lHs+YIVNCPpxbFsH8sadEmAKUqRQdRCEt020B2dXuYHuoI/uzqy eulopeOBdNFmmVnIDjtwnxuNiE/YVUmdrEQtpd1nED5M+pa6QWx1rC2SWIp9uHQZC2uH5cUR tGJzLDwQFqQsAEfRuD/l5XhITvKVmjl5iKkdWh6+eFSY8H1Picmxt0Vzjqe30REFaSEzvY1o BlEsHjrOAJj5TqjTVQecNSHWuxtlKHs3EP0GVnrq2YFT6kiW9+xaAmsGL/ADtPwswCSCtA7f llfo3Bel2u2wWlAh9GzUX0bikHdwRcgxHE+JPKHhTEDg8a8Wgq52EJEHQHJCEAEpcP4yRKud 6yH9zJdOWB7T2inUByIbEHz+9RDddGjKbF+Qo450vW/JRt+cWddTlbrdXDBrufhG2zpMzXPb nMwpJbZlOWjHZnEcG8LodrXfBxBcU1UYutJJQSf5hj2l46VCjQK2ZlDeZuAkeN2uL4jhza2Z Ka9yWocaAqBNtsTITkfHCt621dJscEf9GYbXbuFFlLHvinYr2yznN4sOzZmWM2/HS0FyrBIi 4z4pOvYStiHUOPIJhLjjjwRtfmJOHWEUy4vAu6Q+sB9YdT5Qpiw/77v88/zJZrnzCuzRYksy 5lOOWY4gIiYiNHAjaytHikdVtcly627CpM2TDuOY8VMdiUWbB9DknowVGvapN1JkMBVuV0/1 tuhuL02TYalmzbwWR1NNKJ3apVqS3GEbSxCOmJH0pjf+3h+ewCf/9bsUUpCBSdoWN0Xdux61 RnSeZYW4zbeGXcSyYunsXl/uv319+Y5kMmspvtLTqw1HUDXBqg0IQftnKZIxX8PDoVgbzOJe jKRJN3O7nh4P73j//e3n87+2GtzEIuyTCesUU99//nn/RCu/0erMGOkhwKvYsKtnLUu9wg6+ V54+r9oxKZPpUG2qgTHvZTiCt5A+bo5U9slYpSeqL2us1zfChhB4pKIhpNgpMXjQh+ao+CQo OwBaW7Ir2X/8fP4K11rm2KL6a+T7TLlVBRR9ZQZUHlz10CqvBrIPiBuizjAz6IjbC+z607JF L3ImvROFFlaiPrbpPKFseHAEYhJCXCbawaYSMJ5jmYoxDQFgzz9a8mEko2exH9rV5WxKcF4p aTTlNUdKV7f6V5r64gHrDHB4sHEDbsFdTMAXVPSjWIiyBb6S8eUU77YiRd14oPvY0lJrNqD6 jvFhmoXFVHz1is9CczWa7WsVysoa29sDCM4Nb3du7GofcRdE7kdvLPQh6XO4QkYg9quRq0pt dzAGoGMc8xJL/m6g+Xd0VJlTHhyfaj2FRWA4FoHn2Kxr5JaigO8PCnDs4Q4qdK9YFKDSouPn SJAWi3quCL16DAY0/uSDhRF9hKi888eHB12+moK+Tgx0FevgK4OVwRAHZmVAD6xWWPa9X+gR 6ns9wXSZGSJfRbFjHtQMV32rNBy7OMTQPnADpbm5s5ZWjrzeO7YST0riOBdt3pleTwaGuh9y RcbgNQWZMm+wCDp/fsJAmTwWusGZZTo3RGYE/uSGMkPNl2uUAvZeJJ6dcNq0ghZp/KBVId5G 4tERI/ElrJJ3ns6llFqUFF4YDKanEDkHHUM5H2Lq5DEf7WqpVj76BB3Dbu8iOnwEPZrsBh9t xPlkmJt5ffX49fXl4enh6/vry/Pj17cbhjM7mb0iLry5PVsqwLDMY7Mx+PGElFrxWATUsjZV TXFYAZr07lqizvDLkbyUEWzWRabxRBMsK1WilSubsKdjW/4gU3wldjP2TJCY0XrarlFjC6FK m0hzUWf3AqmCE+Cjt36E9CLtQ6BHAb6BujDEtlmzTgzbZgBlolOEYReqv5Se5VramBEZAsvb YIAsLqXthO7WwCsr11d1gOYXwYjMt0EToiY91skhwfZwmQHFvU0UK3F60chk+jn4rhmrUOXb lsnCAdBWZIb5UWiTAKPip70T7KFOtRPo2oOWC5wgIRUCxDc9drIUxVNV0sWL1Dz4E1fgiKPb 6jNGLU/TiF4/d1RVzhFq7Q/Vaa8pR9ehw0gJcrBCDCAqwh5B0dj36mpBPWUWiPo0sK4y1YXa tEU65lrrswUvs8SwZpnfelmmLDGSl2nZuHw8H/sKu1LL20tKaIkV2BcDvDrQlH0iHwOtLBDB 8cRD55JThZ6OrMywbch2DRd2LFdqYx6oPjNAsqGqQIFsya0orI8jVLXKPPIaWsAy340jQ9o1 /Q87qRVY+DIZTXlSL2XW2Fs4lVE4akZZlOW6gCwyi5XbfES4Ms3r7c3qaW54CiSOYQUa0H5G xrcgrtpKVsYCfIWsMOHeeRKT7WAGm8TiyOaDguGTpTC+ktp3fXRxrTBJsTdWTPY4EV5TY6tL M3L2XTQ9vvjEkIKUdC2OdjGFAie00XFDJ+zA1Fdg6IXXmogxYVOoyBKFjjEPsLWu5kHtLnyt JzBxO2O7JJQnCAO8KLBE9tHlq8TDVslYU84LZAMWBV5shAKDlAIYxdeGwrRGvlbySHJJUgsu Gs0qJh5uK1hkmdOMHFNTp61NW+qaHqha37OvdEgbRT7erhQJDFJXtZ/D2MFMMoGHrvdt2/A9 YNcEkvt5fYAJjV+isMTmggT4wkFmiq5XNjZMzXyhtvl5uyvEpZwApEmsvK4pgkanEYFpHw24 QdHuT19y2zIlfqYqGfVrUnhwxc2gGIcuFZ4lMw+7tjpuZrqcmmBpMxBeRT5L4YRXBvEul/jM bNJDjDq8XIi3u84j78kIgLozI0DU0kfpvRdZ6OSmbhuJiLx5JCKBbVKPFHO87dm566szrq+J U7WJZRjhAJKr9gHxqyhEr6IKPMw3xJDLtK+0nUB5oKtUfAzwVdOuaYjyioDKcu7y/e6ERfBV OduLMSG2DrvWJHyxOZ4rNMa+wEirbgWoUUKhaA6NjoMh5o2w8vQt8e3ARWcmfZ9Jxhxp51fG fOU9aBVF96VUJnyi1feoFMw2V0fexdIwdPAK8Qf0NSNc9cUA/XaJhClXTHDtVia7Yic+Rqpv 8lISHry2LLpU+nJ6eVl8lLUb63wBxFQLpgmxx5pllmDrPedu/HQWU1/ppKnvDNmSpL7bfCWa OwW1hs+rFI7asu0EhqpFi1VUTW1sjaraSJQ177lIcyI1+fpktZJcXqOhZbs5oLfCXuDOZnOR +cuoUiOcxHuKwAcvsxVydZfXKIUvp3coBEovc0xPDUi0LoenoVy1J/suT6oviSE+Lx0FRb1r 6gzKZajcoena8nTQKnM4JUpocDqAe8pmSqkbRFdW1m4H9W+tGYF21Em1vNk1Uamom3rowOQd +YYJsql1GAMMhi0GOkjNudLhqWiKsmla8MXHv+FXzwtV9Pn9OnzdWTATz4R2EPbZMIZP9VDI OoG9FqTK0PRuWpfUpCrAMdNUDIJ2PS3BsGuGMTtnUmZ9Izw/na5nZwKlbvpirwSdqfKsSBhq uNS0MsD+VtNhtec8Ey5sqIpkOjbLHsubnHZZd2bvF5C8zFMpgzWIy7x1+v73jwfJLWsqYFKB A8i1MtJBVjaHsT+bSguh7XvoHyNHl2TsYWS8sllngubAAwKu1IFdEkFqIIcFkRtizuNcZDlM Mmc1W/pH3zWl9BRUdt7N4jFd2/z28OKVj88//7p5+QEb1cKJJE/57JWCAbLS5K11gQ7dmtNu bQsVTrKzuqfNAb6fXRU1W+nUB3HqYWnuL7V09YcRE3iKR0mK2rrgH4dQs4o3ScGdZ5c7pXoD CKK3xokWmkcVwKWdoXk3ug9JjKWWPf7r8f3+6aY/Y5lAl1W4WcSgZKDtmrQ9WEN2IH+X3dUJ +BixlsWdchgbe7mE5CxeMlWsEAcT9bID5lOZL524VBCpgjiAZdfT6cT65o/Hp/eH14dvN/dv NBM44obf32/+c8+Am+/ix/+pNzysl9FBMytMNl7nxkGqM8uGo6jMlY4IP6NX1BASY1GviCRm enpVUpYNIrT8Q3KQRHzVHPyZOslTk4+cKeaKqXLzGyHjuS3oECgITfFOT0XiSml7nQynwRN7 FXheMKYp6kU187i+z1jUwU6RwB8L5V04tSC7fC6uMQt46YI2aXPq6TJ3v1PzWWE9Hx5Ux5gy OcJ3mnYrTnpKSthfBWUhbrG3hjjMn8BIKqKK0rQmz1L5HTqOTdFm6dR82sh6cW6HC1gbfEnl uSFdt7d7sxTpcUFE+piSwukGYhxiM1/fapp/Qs69JibMwx5SRoFzoer4yTVVitbDAbpwSWVr TKSPBh8uGH90mDtw/XQafgaNuDVK2YQbgWrF2xfMBuR7vcIU28+zdlWlvxGq225gvpne0pDm DFKRERjoV2fNqNo/vj5c4Nb3L0We5ze2G3v/uEmQVKDs+4IuiPrzllEi+rdz0v3z18enp/vX v3UvaV4jMOqZ9cCvIvz89vhCjZuvLxBP4n/f/Hh9+frw9gZPFcCjA98f/1IKNnXfOTllqKvb hGdJ6Lma+FByHInv8S1kO45DRMj7PAk82zdIycpi8KGc1ARpXdwZZNLjxHXFjdiZ6ruej1FL 10mQopZn17GSInVczO2dM51oTV1Pa5dLFYWhr6cJdBc7XpuUYuuEpGqRdmMbI7t+P1IUlZ+P 9TuPxZ2RhVEVJpIkgR9Fojkisa+GrjEJapiGdqTJBCe7GNmLBowcyDEYJACWUsZmBJ7Ic/CP KbD58Q5CFKrFoUQ/0NOj5AA7WuPoLbFs8ertJLxlFNAqBBpAmz605ZN2EdiaGdmpLR56eR7e rW97Wiszsq8P33MbWpY+2C9OhHVJf4ljCz+jExjM7QQwVu9zO7gOesA4tWQyxA7bCBakEoT9 XhoLiIiHdqi1RTo4fuRJgZ4UORdyeXjeSNsJDX2IRksWRkeID5pQU1pAdmX3UQGIzXIAuG/b WHqUDOMCSzN2o9isApPbSHKMmzr1SCLHQppzaTqhOR+/U3X13w9w1+sGXhvU2vXUZoFnuTai pjmkxqGSstSTX6fK3zjL1xfKQ/UleJehJQDFGPrOUXq5aTsF7r2cdTfvP5/pCmxOdjUsMnbE 79AORguvfsqNgse3rw/UHnh+ePn5dvPnw9MPIWm1B0LXQoSk8h389YDJnnAQISA9e4MqU90N ZuvFXCreCm2hlnWtporJOy/9qWabLrzlfr69v3x//L8PsDhmbYPsIbAvJvf1jc04zgamSuSY bmTIjJETf5AP963Wsg2lI00Fj6MIOxSVuPLEDwNzIgy+lkjVO5Z0Y0HBpDscKuaa8qaog86N CpMt3YAQsM+9bdmGrIfUsSSXWQnzpXNeGfOMWDWU9EOfbKEhtt3I8dTzSGShF3BENhjuYnxj XSYU33cB36eWZThN19hQf2yVydh5U0kMl/AExhza82pWdGK1jA0XRR0JaCrm3eapTKcktiyj rNO1rRJSHmEq+thWLiUIaEcnrGuloHLgWna3N8hsZWc2bVnZ9tQ4drS6eBxBTL+Jiu/tgS1T 968vz+/0k2UXkLlHv71T4+f+9dvNL2/371QbP74//OPmD4FVWIqSfmdFsWDnTsRA8QXi5LMV W9jGy4KKA3UiBtSW/Quj2jIRRpaofhgtijLi2tYagF6u31f2lt7/uqGLbDrlvr8+3j8Za5p1 w61ao1n7pk6G7VuxshbyQGXFqqPICx01NU6Whj7fmj3vfiXGzpB3NQbHs9EYpAsqxu5jufau 7cikLyXtPTdQy8fJ+NsNrKr+0fZQO3vuXyeKdEmRNOnCqcsUkwSdM1Y/h4nTilyNSAsfaXVi s6zh0R/AzzmxB9QQZl9P2iCztUpwiPeHi+eKze3802QaPlrPBhgxRIiO2lJUDNXR0RM6+yl8 dLhoVYE414mNNR0tpeyTvMhrf/PLRwYVaalxMmjld0Kk+pSoyCkTOFch0nGayZQy8HhsNKT4 nqkT6qHXJZOOFV8btjAsXN8kIlmxgxatdupnM4DtIEx4CDjyHdBNR08UjnVh5HVVBl+yjy1b GSd5qkkeDDI30IQsc+g0p55iAtWz5XNlALq+dCIXN3pXHLcTBByWOlt6NtL6JrPpNAtnaU2G ymk6TQJGCQUFEKmjhLenY6NUV28+h7nz8sViT2ie9cvr+583yfeH18ev98+/3b68Ptw/3/Tr iPktZVNT1p83tD2VUbo0xjd0AG863zbdq5hx28VMPEB3aeX6tjaLl4esd92NXCcGbI9CgINE T5j2oHH2gKFuKXNCcop8x8FoI204lH72SjVfljQa3WMyK4LYmXuvINnHdVusCggdm5Gl20VM vzoW0QSU5SbP/P/x/1WEPoWAFUoLMTODx4GXTrqFBG9enp/+nuzG39qylFOlBGyuo7Wj0wE6 DTKIuVPyVXyezufuk/vE280fL6/c0NGsLjce7j4pGr3eHR1fEyCgYpviE9iq/cFoSuvA/Rwp yvJCVL/mRGW0w9peIZUHEh1KvbRANkTTZCn1O2q+olGTJ2UTBL5iGBeD41u+IvlsZeQgcgf6 H3X4B/DYdCfiaoM0IWnTO4ZAZvBZXiquh1xpvXz//vIsXJD/Ja99y3Hsf4gOGEiUp3lWsWJT x5LWEbfSjAsc+YBMPw1juR5e73/8CRf611e3Vx+wahiL9nQ23rnOxGDe9A/+2npGpNNioGct VUcDCyeY5We8LYGNPbZTYcECVpjk5R48leScbysCXdFKbkbLNzT/ivRj37RN2Rzuxi4X3+4B vrJJspEuNzM4a6wuieiIMdUgFeNkAO2QVyOEcMLyhfKYMPiOHOFEF0NJemTv7yzPUUz7vjdU X+C7lvAVZaTNS+2kQG17QEhR2gHmHT0z1EPLds5i8UBJA33tNQdT2fjM31WztpNiuQlkuai3 1Q5zt5B4zofcJB9n2uhq7Wf/A2N6pwwLgcc+ZQfel/GYibdlFqQ8Z4oMtUmdl+sk8/bj6f7v m/b++eFJ6SzGCGH2RjhoT3ophLXAQE5k/GJZPURAa/2xpsa4H2sdzJl3TT4eC7hn54QxujaX WPuzbdmXUzXWpSFBOozHFH9DYGWCRtjMKy+LLBlvM9fvbfGGzcqxz4uhqMdbWh6qcZxdIi16 RLY7iDu5v6NTruNlhRMkrpVhrEVZ9Pkt/BdHkZ3i1SvquimpTmqtMP6S4g//rNyfsmIse5pz lVu+ZYhgurJP1/t7Yhn2xwXWoj5MMk+byYrDzDIN1KnJ8ySD6pX9LU396NpecMFaQeCjJT5m 1KiPMb66OSfAx6RLsX4xpiAIHezFlZW5Suq+GMaqTPaWH15y0VF85WrKosqHsUwz+LU+USFo UL6uIBAG+Tg2PdzujxO8iA3J4B8Vo97xo3D03X5bNOnPhDR1kY7n82Bbe8v1amkpuHAarr3h 5eiSu6ygA6urgtA2vOaMcsOp32aBu6beNWO3o2KYuYaOIklFTnSYkCCzg2w7vZU3d48JOuoE lsD9ZA0WOoQlrgptQoVlMhK22KIosUb6p+c7+V7evsb5k+SD1W32NEFT++XFbTN67uW8tw9X +o7fmik/U5HrbDIYntHU+Inlhucwu3yc33N7u8zR+FACd9FTAaHjjvRhaKFDTmbBuxLcZZJ0 8BwvuW3xNuoz8PGhUnghR9MWx8rcncq7aeoKx8vn4XBN154LUjR1M8CYiB3cDF6YqdZoc9qp Q9tavp86oWQbK5Ow+PmuK7IDOu0uiDSPr5b87vXx278elCk9zWqiCzVYHk2dj0VaB46tyXB6 pN3R0yzBcsMXJsDVNWTM0zGphzCQ9pPBLp2mDkqqWah41aylqpiql7KPYtvZqQVY4TjANwQ0 ptOgWMFwD6rog8B2FJkD22CE613aDFzlhwSahlBBzNoBYiwe8nEX+RZda+wvRvkAQ7Tta9cz XDrnfdglWT62JArQl2EUHk/TA9RWpv+KKMA39hlHEVuOYigD0XE9PTUWC47LlCG9/ljUEI85 DVzaZrYlvsvN8IYci10yOSsFzia6/W24iUZq6WU8RHe4gI1Oi/vWsxXNDwGL68CnoyJyjUig IX2b2Q5R3gsBjF+eoeqLjoTARW9eq2yhFEFGQrPWALBx5viKlDup7gOkACPzBDXD2gKSKY3q mLWR7wUb0PgpdGx1QbosTOQlNCePyXE3mhxTRb7CIVixZ3j2a1L0qa4M5VLkfZ2cC/NCP+nS 9oC9osmWx5XtnFwHGZgwlOhvJik85w5iv+2p+lQ2C6bHbA/7QRW+jChrusMp05QmaC/sPoBk s+Z1z+LWj59PRXer7jYUO7hhlDXVPM3sX++/P9z88+cff9A1dLYsmqdv9ju6FMuolSzdet3j 75pXcBeXTgvoOTmaD4+Qfv/130+P//rz/eY/bqhRPl/zWveFpuTBYE/LhJDpfu5aM0CE520n KtyOLIvDsVe/Wgq8ctz2mYMeLK0saoy/FeGRMTSyHg9qxdjNh0uJ3sFYudS4ESuihs9bES0c tgRFkRxTQgFDfHpbubAHm/T2WIO2YhnxmGPX2jpwrQSrBINiPOmSKi0f3+ddmbDgEwjbHGBg s5xynCuhIGfaBWHZYtguC2w5HJzQNl06pDV2P1wQCh5vz9ACeYaOvitjbM6FeQ7CK2PTBqGg PRadP6Wo7d/OjKQ51cLuCFH+GJUgiEBq00ojjHmZ6cQiT2M/kulZlVBDHCwZLZ3jJctbmUTy z5r+AHqXXKoiK2QiHaVtl1Pd0ez3sFEro5+khx5nykgXBqd+upG6eo7WsElA4FURVPDmCrLW QfqfVVS6zijnDPcg06TLyO+uI6c6X0NuygwupZpz75p03GM7F4CeIZgzoU3cFXV/q9bM9Moc +5I/6an1wgku7unkMTtV1Z1Ohs4Z8zOd3XBMp56LTgeq9uRZ9niS3hAEIEnpKnFeNIhVUy8l MeJURqkREriSb2oEtCx9m5xVEgk8NeHp5vzJDnwf05trvZQBQ7u9Smpn8JCqTq8EJud8E5yf /Pnd4pP1MfuVuVCL++oLTRp68MBgl7P7ntSC+pL/HnhytU7o2xSAwK2rS9EpJZupYMQo3aHM 62ywDYb1HIB0oU+15VbujWQ6AXmX75qdmstSJrg+b6HzosTWJyRNKkO9qqY/YRnsTe8ZTUoj LfCdDYCVZwZEqWoUSYc3XljvSzG4ZmR+dWVD2wLbrDGRpLUxyoljMrDVgBkkbVbsEbgCaW21 0TJB6ReIrhV4PtWN6dHYQPzaJP3IyLFLKydyfZYwLae5Ocf07lCrbUe/Dlz2lgMZL8eC9KWq 9PI2BgbeH/zU/iWdbofBWf3+9eHh7ev908NN2p4W/9HpnHdlnS6eI5/8H+kKw1TWPYFznm5D OhgLSZBeA6D6jPQYS/RELYUBxwgxpGboYoByXgS0AnQ23Bfoi1cC05Ce1WlmLapz7JGywgE0 zMZU2HEQKnlSPgQ62omThaT0zON/VcPNP1/uX7+xDkIyyUnkOhFWd5bVoS/VEyGMzdyyCZNZ ajSY61gMpuzBHjQOmZkpVZ5/WG+QbEm41Kh02ByLwLGtSUdI+Xz64oWehY1MiW15kkwZ5lqJ D3htD6wYBWaXq0zKdXsRhs2/soRF+gkP2CAys267niVn45liWVJ9AxuezQjxoboanvBLUrSA bDuYcF+FktpZZjMV2OHdtV2fnklmnpiGxOFqbaMOsA7Wi87e0BmpLJggfbEv40n7ObJkP9qZ gfQNupGzTB3805HskOmRByxoqqqp0bRTuEa72XCYW8CGuugenh/e/h9lT7LkNo7sryjm1H3o GJEUJeq96ANEUhKnuJkAtfjCqLHVdsWUXfWqytHtv39IgAuWBKvnYpcyE3sykQByuX8FrO6B 9T410r1q//dWFxKUzUwRZdnvs5k+An8By36vdtAWcTLGg+Dg5qIeLf+LSqW5x+Pjnw/fwevO mhZr5xOZx4Sa754BkS1R0PR3s3Ok4dJNazVsqzkCPMjoyVJlZkRKzAB17e0MfD3PGLPO+CkK Yq2g2htcj09IR6bAhGRqy8jmNYQxIdQ8fCvIU4ztSxC1BOIkJ2MH7KHKTXPx58Pb1789bFGv eYfxt2fRrM2OImliOqLeDFnYPPG8GXR9of4Mmn/AxH7gGsj6mCJzG6JCJu7gOxCmxIzJhheY mNXEs319IO+oyOJZAv6uRxkiv0bEInEUyXkuRztX8bnoju0OO0U4DvbyhEHarmVZjp4+SOsF G2QdBoweAkzDbnS7AR239hyZTFQy3Z1fw3he5MZoYQ4tJN7juxVe5d1qFaL6J8eEIWYtpBCs dWccFbPC3kcngjCI0K2bY0I0aPjEKHG4Vu2EB8Qu8SMcwfimjXyoMQ3CPEAWQCKQmiRi5UKE LsQaQ6z8XHdI1FChxT8OOvyOW6fBHH41ig062JWPj3Xlr9GhrnzVXl2DI4JQwk2/dhV7uUTv fEScKvACvNFghTcarLZ4gxBxZl6xiy/+cuO7LoCAoj+sOOU24P1w95520lOul3+TcIMQWlvy xveQZU60BHgDVL7P4gI1pRsPYwwO91eoSIRDLprsQCXwEekk4bhEO7BijUtgsL7smrtgGcy1 CXFKomWEtCowQbhB7gUEKlza17cDDvXr1yi2avAZvUnsMxww+CRI7Bb5AmRvMAQtoi0//Jzj pFdn52n6oKHYiLkK6a0jzLRHpdhEW7uFHuH6/AV6a2VHRemi9d+iC5ZrV3YxlYoPCFn3ATPT X0i3hpmuaiT+X2jdgMAXmLMx+mU0d5GH8FGT8y0QkXtwS+oh2xDAA/QjEveqcxdPQBAiKzvc WSGY7FCQBDsvDBh8DnozJ8L/HUL84hTWdZ086Dp0WUoLH3esUylCTGsCxBrT3XqEYxy0WIXr DdoXRgIff9VWSRwG38qhvaNoPpPx8EeoH4ZIxwVi7UBskPeqAeUwJ1BoIC3AuzQbb25bFRQ+ wlIcwTVNvHcQG8/DDDxHij3ZRhuEhQVii16LKuHn3hU6I23goUnMbDqEfRWkS/j0JEl88Wa/ WEYD4vubFGmESn0LrR1wswcBEW0P0wjORWQY/asYRwIhjWSuWSCIXLXjCeZVAvzWXYQCxG2n NRI8/bJKsnqvAyHCzwKOnqlE7MI5fQYIIuQD5nAZHw6F45IKEl4sEWVEwPG6tpiuIeB4n7Yb Rz0b17ps0UBtKsEWqRL0oE2Iqvwi+9TcKskMVkidQ9oqFN6ROE5S5Laeo41saAOmJG3kyrql 0oSz3zdQRB6yDALhI+sgEcissZrws/2S6M6g2iWOVkTuv/AUhF61TGhz9PJq6tCQ+mi9JClk kOpTvWxT3rClyUKW2JfQHDiV4D+6nbj+uopUF+WBHTWslk6itcr2b+NDg/T59glcu6FhKwIs 0JMVuBWpwxXQuGmxrUDg6jpPrQIt2FegjCFGlOZ36AMSIOMjuBWZNcbHjP/CfSAFvmooyfDE DRLf4lmMAVmQmOT5VZ+6uqmS7C69Uh0ciwhMBuxqWBYAkC/NoSrBU2uCT7BuvzeHmBaUQx1d hDQM6oOUgH3k3TNrOaTFLkM5UmD3jVHJIa+arGqpWc8pO5E8yRz18IaF15de19011QFnkrOq 1mGnLD0LHzOr59dGmAc71zCDmOqODmXMaPpfZNcYy8TOWXkkpdHntKQZ/6z0dzPA5LEwNnJ2 x7Jo1HBldcIMzQWy4mfT1Jy8AQo/as12ZMTo3KHhm7bY5WlNEh/nIaA5bFdLyXcK8HxM05wi 7FiQQxYXnDNwCx9JkoP3lPOruu5zQo1hijQ+h8pYhSIDl55qzwxwBY/DqfFlFm3OsoH9tA6V zMWwVaNlIRIfOCkZlzWc/zX5roDdn2OdMpJfy4tRI5dReZyYverBkzGsc0IHSjCEfZcmTfBn FJUonhGJdU5K4fwWz9STkytl1mepiUnwsNbngUtia7Z7V0MDmBYIJXgi5FlpgllKCnNqOZBz L9/iUuz8KCjass5bQzY3upeIkD7gvkpohl2GiHoK0rB/Vde+skkdUOBufmHZqTKEUVXTNLV4 BRyfDpgVACBb2O67mgaGlM2yPvuXArxkZWE0+TFtKn0uBogmFQTpNeGbvvmVUi4rIedxu7PW QWLiljJIpil+uRSGvNbi3mI6iVBWwApT15DGJiHBCKDc7G9Hehqq2z1xaP3y9Pb0CULPmFoQ VH23U9QoAAgxqHb6ncpMMu2FHA7gjnHBG6SQVhgfTcjuUHHdRLNMMCs1C40Z/QbLWIQWRlod 46zLM8a45puWXNMp9ZmwMikBcLQ7UWBcPHWsUZOtALTN66zXgLXF5H+WwmcBGTfgSQMbI6Hd MdaXxqyIlGXVlnHalel5yJZnsYIeYRgWCUnvA7X1JsYdOBxkaJYxoNrzprIyY3xvYyCJzD65 k/2oE88OQuVsY5Zn1JhgQCYZJTtYlUtvL2V8hv2kUzHrh7QBgCPxlpgoSO7VcllbgpE8JJ/x dY4vh0ODYOKn17dFPEXpSbDPJl5vLstlv0Ravy7AVUfHpgYEuyYuKMOsrgGb9sX1SRHQpqoY zETHmNmowDMGnCACyMxVvqc5UjlvsivruNioHpMaFnTn0oHjc0saF45laHcBR5gjRMJIRXGj 4RGfXq5lhW/qI02BuyKKdSxpAA7IQPfOiiD2boJfL63vLY81xguQ9cZbX2bZAWiCtT9Ls+cf BRhfGjSmLLPYpppZn0pfHxQTxP5Kvx7U8HkdBz56caqRwSI7WgCDoMCB602UEKyqZ49AyQiG sO5XFwgcreCL2nqBb08nzSPPmwHztazMyZJIh9oJBE0Egc22m5nFhapFdr5C5p/Ty/eJmPjf R1v8g0CTfp6L+PH+9RWz8BEi0hHrB3DC2wg1SgLsOSnMLjE9yKdoq+Ra2/8sxIywip+K0sXn 2zNEKluA/XxMs8W/f7wtdvkd7GQdTRbf7n8OVvb3j69Pi3/fFt9vt8+3z//LK71pNR1vj8/C cOzb08tt8fD9j6ehJAw/+3b/5eH7FyUWlSr7kzhSX8IE14DzNb75A+ZYmVsWgANzEgSwO5Dk kLr2JUniqK8zP0sJzQpDPhestdoGmKjXuaaCYrZzgiJpCQSeUQNUTbgx/56KEfyaOLJ5Cg3h HGMuvj3KNysEmDUUGbvu/vOX29s/kx/3j7/xrfrGV//zbfFy+78fDy83qepIktG28E1w0e07 hBr9bOk/0BBXfrKan4gJ5s4wUjlmReKwWRGY3nlvrmLWgOtikVGawi3v3lavxiZEV7lmjL2W C245QtqJlFhs2cP5Aeu9ohhnDqiCFg6MxaAjZrqgxbAsPTRWb2Fz3OjhPsbvWiwpeqZpKd34 1rYlHfjQqnQlGa2Tn97Vd5Ie5K91EEla1hrjp+mJphZL5OmhYuadm4q3tYn+6pX/v4nXrm8o vsKNjiWSs8S63lL1CwZunTkpzWLixnsuJp8g6Io9VysJZRDh8YDfoYmZyLgWvjsdsHsHMWZj Y4UsxTE/1+waooW2EQOqzqThX0BjbT7pjNhLjzRlci/dZxczw6TGeHB5tT/rjV55AVM9/igm 8GLwBqjp/H8/9C7WyeVI+QGJ/xGEjuxPKtFqbaY8UCcsK+86vjQiZ8nMsPm6VPQuxaJWwGlE 7vJZyZUx9SBUf/35+vDp/nGR3//UopWqusFRu5Uvq1oeguJUj/+hFBHpr0+aeyMjx1NlHnFH oJBD3e46HFGdS1ZD8GubH7hcgX46ZwcO6kidvdneMELlmsMxMdogxdaq84SE4TtEj0P2CIxM 7gD7LEevAm1CinYE1qATr2o+gu2Vq65si27X7vfgfj3RDe7Q/DeVG+HENreXh+evtxc+P9Mp 2txt548Ow3mnTWJropqZnWvQpfXhKhqycdYQmVEvZhPFaaYJQAaWaKZlDWXEacJVEHpmSIld EvdjVIBlynx/YylCPRi8Id9jD+kj4LoMkdFvTvJKRdUtwJ1+PMWq7I4uqCa4sx24HFdUe5oS KwknCxMEqZ2NxtspXb0GNYIT9eUR0n1X7UzZvO9aEvsW7BSboP6Eg9zU8T/3+Kmq1y2fX26Q wezp9fYZQjv/8fDlx8u9kcMc6oLrZ0NX6Ic2NtmvHu8zZvIwra+tFu7bUqTNRgNHiILTnOms DvEcZo8BB9fkHJy30hKb7A5YHAaJPKe7mFhKCtz4253RePH9WR/3lGut2kaLnx2L6wKBxdoN lQQ3zNt4Hn77JCnAmAQN4K/UC9YtWWHXvgdhZCaF04tD6JtthH3GkuCYBJRCokdzQJTxyr31 8mIihONkXUw2EjCj7Ofz7bdYZgp6frz9dXv5Z3JTfi3onw9vn77axhv9JEAQ3SwQwwkD35Qd /23tZrcIJGH/fv92WxRwukNuL2Q3IMR4zuB+xMk68zVqGwbf0Tp6zpj6bl0U2l5UnxsIb5IW jszNPX4mm57IjQwhUJAV5rV2fZRzJdmyzLfsvp8eq4biVjQYDUsT/MITcEV10QKzAEx67mmC RzQi7+jczQTYPipGV/DR6xnvB7AO4T3NbEhHrxS2whhBTV7Whe5mDRSD+56jW8lZrzA58z2d 7QsLusvbdJ9p4ZF6jHkR2YOPWbDZRvFJC1LX4+4CYxhH+E/1zAToqYUMOtaA6BHnQInkE7Lm /Iwmm4OW2vJiTG/8QbstBdCRfjCb7eNxOKqtzsr2XKQFZZkapWmAjLpwn7f729PLT/r28Ok/ 9mFjLNKWlOxTrtTRtkixou++38BzGbweTf0Rb0kiPp06zAnaCeMOzNRkIhGWGnGV6ydSQbBr 4DBZwtn9eIbDWHlI7UdbsLFB5JuoYSbim8CTkm8m4ZYYQyJNluYm7OwbGQxlHyFCio/59U1o 3Q1RPsC1/BBOuXgoUWsCQSNi9i2togKM74ATHj8gD3jch3HEbv2L1Sps2j52eSKw4sXjYpeK qx3fXroP7Q6X5SpRQz64qq9jsh02SQTuehUWNH2UO2MO6mC7wu8HRnzonqM61DKYDsDwcrHe uUecGud3AgYIUL0v64FRqB/QB3DkCOk7zU7o5H1ArwN7zWR0RvDK4PqQq7AdHlLWecbsUgSq SQ9trt9HyS8k8aOlvbQ5C8LtDBf3kSJdrZXUnER+DrzsVFsD+R3GZB0uNyY0j8OtZy8x/7JE Kh29KxXDQ9ALZEYDb58H3tasrEdI3wRDkMlAAY8P3//zi/erUMKaw27RGxP++A6pQxCTmMUv k3XQr0rkUTHLcOVVWF3n2kCMmm3J1SyiJSK7ivzCF9NVqKWpLclZxiev7T8OV0nQ3L1laE1U jQhBEkOUgtA97/lhChL7eP/6VSRqZ08vXGfWN4xx6tnLw5cv2oanmkrYO9xgQ+EKeqgRVXwX O1bMWUnBsEdMjeSYcu1ylxJmMmuPH00HnY3ENRY8WCMh/Dx8ytjV0YYeMlRDDXYwk1HIw/Mb vBi9Lt7kzE7MW97e/niA80R/CF38Agvwdv/Cz6i/Wpv4ONENKSlECHZLhXGkhK+Jc2MdqGpi mBgbWLCpd3PrMGPmdYTeZ4ZdHpM45kpNtoOUK9ffJ8P7+//8eIYpeYVnudfn2+3TVy1uDk4x 1NqwWI8uCIBBO1NAx5hV9IoDh+ii/3h5+7T8xzQoIOFoVjmUZsC7T06ALU+FnoJIjIxjFg9D WGxNf4My/ESyh2b3uBnASALRP5FpHvFGOFMV3rVZ2pmBTdVBNSftRAlGdNBpS9EeiAeV02xw xKHa6EBBdrvwY6pab06YtPq4xeCXSL2yGOC9uRRSgAYb38e6l1AvWGJu3iqB6t2kwNdqrJEB frwWUajnbB9QBbmst46MQApNtJ3tEKfYbNZ6wI0B19xFS0wvH/E0jAOs1xnNPX8ZuRC+s4j6 qjlgLhweYt2r473pKYhRyJT3GCbAJ1bg0GdOjSLCV2XlsQjbU0euSjbL0EfmZvch8O/Q/pC8 QD13x3WIQxZGyCgBsfa2WKWUH3G2S/xCf6DZFxBBY65h/uGoTmUKPNTzAKslfOzsPhCkBT9P btCiJ46ZZUdOEKCfZXOKIseL5zgfIaZ3j9iEf9bRuM/UmVuCIRGOgB6UJ1vyIQKEnxGxY5PC er6nhonQpmcb4+O/rI1c5aLt+vH+jevJ3+bFMRdNfoR8lxyuJaVQ4SHCjCDiorDbkyLLrw7h uY5wR0eNBPPbVgg2foSKC0Ct3q9/E6G+pFotDtnvr9AUaiMBP/FhsoiyO2/DSISLk4hFmGuv SqBGF1LhIfrlF7RY++j1xSSJVsaBcmSkOowd6aMGEmDDOZkxpi6wP8HY3zjStI4kYE06/3UM qQcMzMdr+aGosWZLdkltq8Gn77+Bsv/O50posfXRl5hp0Q1b0hGRHexLu1Hy0rzbs6IjOUGj VY5rmVL1qkQDdyf+08ZV0tYC2RBcCqAQyyJIsV3bqVl5F3Q1wfa24bODHjBVIkoKRCmzTLbG Fhnf0pfoCOBGeW6yTnZtfHpJQoIIGRr4QZZqmoBxcRj/C933KCtqGyoDP2E9zmtx6TfL8m57 hZHpi+iCr4GwQJmbkUuMSohL3J3mBAQtTxQtKN5v5jVS5m+8ubrhmnSL7G8F26xxpftyMBIh m0JrEyyRfUrEFEX2UZZ42l3T9K3X6ZQgF26N6I2fIl/ekxGHKk/2GXqJn3Dmk94z6rgmqH0g lKnhCmKn6iH0WsYdu3RpKTxY4LJfJNYzXhMhvqeM4K7DwI0erEv7clTHVprnKsn5uR5MMQ+G TciAv2TWExjUAl+CI0AuoCnxvAua/AyQbblWs9yd1VZ6YB9KXQvbLWKIaxCIjFwkcU829kCG QM44dI3fa/cEVd0RfNh3gd50Ee+Nprnqs0tJyyCImvaCOMAv5sti3dV6DQXkRNYg/AtQ74SL C9W7Ue7qfT9X6nhl/F18JCNOhk0yyhQuSyAIHOyqUb5vWGwhRJS/7Ei9cxoYSRpv6Zp3lhU7 fchjqNTCbG/EiJlGKhPSxJyrPvapVCK6pHb1FOJiHyneS8DFH7RuCrOII7BcVxwKhiE0jocu G0/XPVRbpH1ndnAQSb09mh7X/iiSOnQ7ogZR6KGKGBRZqTXuVMzbDEwfZdiQIVLzmEgACB7p dKe6CMnPLJfFR3kXPz5APF5VwI4SDx8shxrp2kfJ1zUkS5Tad+1ecU4cZgBq32spsulZQBU+ k4W1NvhvvhGe0q6sWLa/WjjLCrOHD/nl8Zu6nuiYktogGFLk6cMYRXF76a2op46AsXSu+hId kxUIZuvprYdPgDvK9Z7I/C0yzfy+/CvYRAbC8HkEyUtonGWd1jz/oQbGrkkjMhbVfVrzESyT JzeyNQPcVGKpwmnGJEK+eYNGTInDQLyfjm6XQ54nhJNUAs1QXUG43umHQUwCCH1oPe31K3D4 zRko4wuCvTgIdGFcysIOPuQrwsoMcXK0AlBPWrboxJyE+bOJ7p17P708vT798bY4/ny+vfx2 Wnz5cXt909yte8Z8j3Rq79Ck112L8z9nzTRxZJxghH/U+L05pnwpy9fwWkdHPLzhIs1zAlmB BzJkaiuupPNN2NtoFw/ya+ri/A4pcjzTOivzKtau/CaokJaz5YbkCVhhRwR/laLXftHSoGqh k3GkadG1Uei4di4I12Mq7KwiGBnyjylyXoAmbzfpWnX7fnt5+LSQjF/ff7mJF7AFNW0AZWnO vfWBgb5r1jthICfEe+hR+M7Q8aPiaaMp6g6SsTJUTr83QrN6sV04nm8Git5/nlDKOEu3B0wQ VXtJPo1QWNY5YeM+NWz2feaKscT0/cksCC5ZldVQ26mgmkZFILEqXoAGW74VxWekJcAMHXSo WFYhoUtZJXSd1ULLp7Xbt6e32/PL0yf0fJdCPBDz4WxcZ6SwrPT52+sXtL6an6d6mYzXqJVU RgAZFyGDmDUAyvv2C/35+nb7tqi+L+KvD8+/wpvnp4c/OAcm+gs++fb49IWDIeUEYgQHN0ox KU9EN8WU8PyO/0Uo7tUkaQ4iF0xW7lUrS4EpVMyUnAHpjuynOIcb3VSUQuFkAAI5Zg0eHU2h oaWRtM8kqn1iVaRTYH23u6hUzLaejEWNG7GPeLpvrBXdvTzdf/709M01/CFZmRVUa+SVeEhJ pqi1ABwfO9W6ROoyd4AuTtHVxQ7lVrSn/0/ZkzU3buT8V1x5+r6qpCKSOh/2oUVSEiMebZLS aPKiUmxlrIotuXzUZvbXL9BNUo0mWpN9GY8A9ME+ATQO7ZC9k79eUz7dX96Se37R3W+SMOwp KzYAq9LiC4EYXLYUwje8g7oO/ahZbXGBWbnYzqgZy3bTzKyzR65fuHdy+PffrilCLIzqfbbk JqjB5pL0nalRVRkrj+K79PRx1P2Yf56e0T6k2+S970iT2vRWUT91BPsCA1WlaWN81LT8z1to zGEfT4f6+Jfr45UQnEWcnSKigKMV0tR/4IGeL0oRLpYUis4E+y+lKVEiuAqlNswgLWYZANlV yvZXdfj+8/AMy9feaealggwePvVFho2AQizjPNmb0rSGVvPEAqWpuXQVCK6BVe/6QqDkODqF rbI4s2pBkDJAtDtREf9pDeofYOzHmzdO2Ar/nJah5RSWJdEaGhxEBHwGn9wMz70uiFlXVFu2 w4mrNPZMuYZA+3QzJWW2123yjFRD1VlYYiRLmTpP0FZptS3SGj0VG2p6oiqigCMi41jznPZm B0w2c02otbk7PZ/O/QOmmTwO2xlA/SOOoBNeM9yRizK+75Ql+ufd8gKE54u5JRoUiFzbNqpr kUcx7hDjdDaIZFyqvEPkkYUQ4MVDU9SaaLSTrKSguV9JeWCIQRru68+bj2D8V5AtbRaD8lFt KJnLHwgxxaFBZagqunGzUxYTcNtSXoTyByRSUqaWEnU7C2RddnPU4dWoMP774+FybmOzMGOg yfciClVCa2eF+0UlZkMaZrvBOMzJG2wmdkEwMh6tr/DJZDwLeghtAcO0I+t85Dki3zck+oiD 6wKjW/Cmdw1lWU9nk4BX7DYkVTYaOXznGorWz9z99UABux7d1kwHOjivi9JUFkbkpGjS1Eal cHh9aYJ4zs1/w9sBa7QwttK89vYpcEq1oWOrk72IM9P9BzW5BKAkxKWkPmkd0JkKPNsCApet FZcOn2dQo53H9T7klG9IkCxIa/oZaZ/HGevjhWwADT0ZiSk+PUQlfOwNtXgpaU469dixyEIf x9WA6/tpT4dAb9TR0Md3E65fzU6uSjPCcGJaA8OPxuGdg+3DOQumb1sEbrPOBhbdgYBH3mR2 Y+tFslBUFNyY44K8w/VQ/9f09jfK9EhVqxWe/x2Jb5JUbVBBWhLAbI3XrrWHrZYTHx6Oz8e3 y8vxwz7ko13a5G/jxZpMDFmzhXkWwmmjjI+NTWNCacz8SPj0eIxE4PHmMzBbZTTgLH00hpjy KJDH9XCxSyuMqy+M6bvCaO+MkKK674FxUa93VTSzftLi613429qzPLqyMPBZk0HglCdD88xv ALROBI7HxE1RTIcjoqgE0Gw04kdR43hLv2wXwqzy9l+AG/sjNodAvZ4GnhkfHwBzMRoQeZ8u Nb38zofnyzeM/PR4+nb6ODyj0TlctR9EjhDRZDDzSqI3BpjvCE4IqPFgDOchcD1dQmEX5WzG aWLbrOqCRrhQWgfBBp/QCgmRiVHkN8VazE76g10fNp1SGOoJEtSU2a1GYoZbZymtlq+nar6N 00LGcCDUcViz8W5b4cBscbWbmLaJSa6SEROSJEcxLbSA2W4S2b1MZehNdXGm+cZAh9aT1qE/ NFPbKcB0ZAFmxNIV+B8vYA2PMVPF2PPoTpMBXDasvi1KQPBbN2ECaMdM5GgywfdBipf+2J/Z I5CLDdy4POODsTsdQ6P5Nj29ltC5RfbSfm9swgSgOdN+V/QLKTYuccC3DjiATftIfMZefi0L +xPLHG2lp44v6TjsCjYdLajNFh3llMGi3VSlVhjGVNTSptMAQ49RSQScDuM221hUUeYop3Gu 3Yb2a7GrbpWquJ3Kq22GGuDB1ONrVOgKbgn+3EV0BrKAa/i2i7FnLeDGFGPX9qM9gm8dt+aB vHi7nD/u4vOjcQojF1HGVSioxrBfolGUvz6DuEzTemTh0B9R/XVHpXmPw+vhATp2BqHLdSmY p3dPrGkzrfywHl3R0/FFRYrSRmq09jqFXSlX7hDimiL+vWhITGYnHpsWAfq3nX4qDKspm2Up Eff2wpRZNRkMuFOvCqNgYNm7aBjNTKRAdmge7HiCgYP31VKSPKCy6v3spc9SwH7cvnZZ/t6m AGsnxR5tbSN4emxtBGGF3YWXl5fLmaaCafgvzRhbxhcUfWV9r+HF2frNRZ1VTRVV84VaPw3E VZglZG20mmYbpx+SKtm21H3FVafUQxKuvba6wOOaWdb6mWZNw/I+6C3Is06jwdhwpYLfAeW2 ATIc8vnlADWaBezSj0Zj090Bf8/GFl8vixp4FxNSDYdmsqSWZSBE2dgPTJNTuNVHns0BjKa+ g7cNJSaIdR/7ZlMdyNo+aHUlwtFoQngJfcxGgn/JvDkd3YJ6/Hx5+d4oHOnJqsN7xVtgt6zp 11pChXdjtFRHH95tEi2Tsr3v9U17NGO01uP54ftd9f388XR8P/0H/b+jqPpVpmn7JBo+Xx7+ 0i/2h4/L26/R6f3j7fTHJ5pYmTvgJp12tXk6vB9/SYHs+HiXXi6vd/8H7fz/3Z9dP96Nfph1 /68l23I/+EKy0b59f7u8P1xejzB07YnQne9Lb0zOe/xNt8NiJyrfGwx4mH22Guea4sMC/hk0 k5tgMOqlZaVroG6qAIGGe4lI6mXgD4io5v5kfWQfD88fT8bB2ELfPu5KHbrpfPqw79NFPORd f1DTOfBI3B0NIeGq2OoNpNkj3Z/Pl9Pj6eO7MV3XzmS+lS6uPaJWNZUgVlEIXWNTjkWhTxwc SF4SDN1W05RYdeX73HW/qjdm1I4qgZt+RH/7ZHp6X6bPF9hYHxir4eV4eP98O74cgSH7hJEi CzWxFmrCLNSimk7M6Wgh9iJdZ7sxy7/k230SZkN/bNZiQq1bDjCwksdqJRNdn4lg7sW0ysZR tXPBb5XZJwFhjW+Mng7dcPr29MEupeg3DMXPMnIi2uy8ganBFmlA1gz8xtSjBkBG1cyKI6Vg M9aDSlSTwDeF+PnKm4xIaYQ4/AlCuP88Nv80YsxbGH4HPlFiAWTMJv9FxHhENtFS+kIOBpwc rlEwBIOBqUy9r8a+B6NjJkJsGaQq9WcDklWYYGheUgXzWI7AVO2ZDRlwWRbEtP+3Sni+x4v4 pSwHIwdb0vawHzSpZYXq0o69s4WFMgy5ExuORzhKrQMTIUT/mRfCCxyqvELWsMa4iZfwgf4A keYJ5HmmuyD+HhJtXFWvg8BzZDKu95ttUvkO4TasgqHHXQsKYzrOt4NYw5SOTB9RBaCe5grk 0A8ibjLhFiNghqPAilE88qY+f/tuwzzFebiBDPiv3sZZOh4EjpIK6cgLvU3HHus6/zvMKcyc Zx5q9NDStieHb+fjh1bC9hkZsaZ5ZdVvqnddD2Yzh3q+0fFnYpk7ORJABp5jpRgbD+uI6yKL 67i0mJ+2oiwMRv5w0DvgVfOK2eFR6HtuoduVtcrC0XQYOBGWSN0gyywg3AuF0zJfRSZWAv5U bcy11saGmxc9Y9dwnJY2pvU7aqswCRuW4OH5dHZNtik752Ga5N1wOzhR/d60L4t+Gj7jHmWa NDuto7ujSUP3CNWGRLr75e7943B+BPHpfCTWYFBuVaoISK2I72R3VXjJciNrjpIsBxT+Uklq tVcMktwgqDEOUloUkigezBowqAzf5Wa8+G9vWI4z8LwqKMLh/O3zGf7/enk/obzUn0x1Yw73 suAvsiYdnnYbwtBdMT0nftwSkYVeLx/AH53YZ8ORz56tUQXnVkCurNGQCPogupNrHQHWaVzL FOWCmxK41Te23zDUJlucZnLmDXgZiBbRcurb8R15ROb8nMvBeJAZZnjzTPpUFYi/LU1JuoID 3zQAksBQ8pKFnd5XmmOahNKzJCmZet7I/m29J8o0oETVaGzylPq3zf0jNOCi5jSHrdVTE0rb r0dD8yNW0h+MSUu/SwHM6Jid9d5cXLn1M6YVeu9r7/rIZlYvf59eUKzCffB4etfqY4blVzzl iGWf0iQSpbIX3W/NtT33fOpJIl3OOOUimkyGjmekqlywInS1m5EFA78t/38sOXUyKnY4CoPd GAXpYNe/zrvhvzlojYfA++UZww26NfqdO8BNSn1ZHF9eUYNE9991bvAcHAjMIpKxrkHXrYQU xhSlu9lg7A3JElcwNtRMnYFAQwJCKQi3HwDheYazfg23AuX1FcRmMtsLgvnejln/YljJwA99 31CQ5aGCIGUGRRZjCwSmm8t8iPjGaJ7WNI9L4BssmB0RDIFhKquJ5+0o1A6YgbAmqofdvVUy 33KhuBGXZDvPpgeYP2GXtMJq99kln1VNUeh15MSr0K6cJKeRWrFdhTX9uOYZ3O4sDE51y3UO aZTld1JJWmH7Um3XmO14G17E9WK5GDhloxZliuex61SRXNm4Pwq7E3aBUlQSVkj5VSbAmHBe L4oqFL2mWmOzmg0lqSiat2a7ZGN35vx4OLqnoUw5iUKhaSZGDSojC2LmftMAEiWjA8HE9vqH r8eOxns5thQwiUPWybFBrsreKQDSNvyyO9nFhNGiQXl/9/B0eu0nDgCMPbACtmTCmhGKCGNc QBGiJcHnlL1IHDEcm7mFPRhiScnauHdU0Jvrd3RGiL8Lz0K1E6vqNQ/b4RSFMNrD1qylDjeI utnP1VT3lZc4yvtrtASRRHZujJYs2yEp5gh3SC5IkNcg0bltd7CtsMjmSW7KISB+5Ev0EJPh CpOtUxat7n9eK6jZC6Cbf4lZ7kgCqCabUCKLsDafj4GXQ4vUwvCJIRhRryY0vJYG7yqPD0+p 0MqlajiyK7Pvmgbaiz9pghuDBRu7qqJ1v1to1uRYCQqt7ozllxska5+1N9RIzHGf3PebbS6L G9Vm4UrCMSTKHRt0TdNYQa6uQB06di/Keb9tNEtyVimTqhZwFBT9cspwSBQV69lypZCW9ZDC GLeCszQ+rtsfo98ye9AiXMil6IFp4gQNrJMmEnW/U1zeCQfJfplu2EhKigqjnxA1ufZvb9Zd EowdodQturHvM6EIV1/vqs8/3pVnyvXAbqKANanQ+sB9lsAFHBE0glsuBa3xi3pJkSrCC1WE zpFhslO1GUVCkevgyZhdzjwMEKkto3QOOQqeteDrtacR6C+NHgD8XY7fhct7qjP53SbaL3fp PyLzfPG/0AVw6ibsdd6Rit1SEdHvvuLU5CDBXuQiLZb2QFiUkStVHtK2zqjQMzbMBk7S12W+ qdoe2aVBTMTCTFlErotcj86+t5YQnasgNz5F5JWvQ98QJgpLYGbDStSi140m5aHjA5pe9oe0 CUXXLnRSZ4urRLotnMOnvCjQe/Xebp/OSLKDi+DHs6F38Y1P0cdBf1MgfMLC8UpDFoD5REBi bp286K1fg6jle5gNp6+n/bbc+cAv2cuaIy2BeXLulSZm4GSkXHnSTYWaZffZoS/3dj30Eb2x 0K4y0AB0dlObt4WJnapMGcxoaYIQBHNd3NEtEGr2/jTPVL5Pu44OefPAQCr3EsgyGXCzoeDY qKscSIN1bxcidEMUAA1wV/VoNT+BrF0UWyVCkPQkM+RCylWRxxgvbEye9hFbhHFa1Gx9ig3s 16djTsj74cBzYe+bA4WMjcLoJKyO0ekoqlxW+0Wc1QVRx1m19KfWQKop/mE7FVsDfNx0MN7d Pk0wZKOHG85JUgqVSfZWLdpiO86D3o1pEnUekOrXzprBq+sxniJhlfRZBkoS3STpn9Adykr+ h7hGxokkSK9RXLBIdeS60dyd1rqhbdjci4Sid3VVI7lVaU6ZNdgxgzcOW5MmoFV3KK7PV3mS TwKn+lZrVYUXQAdhXHq7u8MPHfhkNRxMuKNHaSG82XAvfVb5AiTaVbC3ZaNs6o0tuFIoNRIi ZRuAG5eJjK2RUckRfc9amlr2WsdxNhdfVVY/u9eUwn3gdpo/dY8WfDWIdqcORO7YDHXIK8YJ r26URndtS6FzlddZ7WupvHob8/zHt8vpkTy45VFZ2FFSOtt8Td7WFAlD2aoyZVg/bQWyBirl RNKjRXARFrWhkmycTuPFxgzsoMlbcSPGcEBEv0vxUCEzCJoGw3ZaTeL1ZrWnr44F34xyd6ki wcq97QFlVdjBScu6PuRH2y7ZTSkdIIZP4/XM3UZXzbEkuiJteqxa4ZRwbYAgdtgxDDGM7VKa 2hmxBV5YXqeigTdeOlY9KvgTW3fJrCDFvufbUnSJkVZf7j7eDg/qwc1WNlZU0w8/0eYKruu5 4JmfKwWmkantwsrS2VGsKjZlGBtRb/o4JvmRgV2AdEv8bdVhUa/6kP2yJvFJOnhV81H2OgK4 jLgn1RYtTa1uB71Gy2wtRPtDfm0L9SVMG4vKqBp+qESMmLomLyJyRyEuE4qhdzjxGxQ6jzVX Fv51ObMbNE04aVJBBfvbUa6ax+iabZcoQm4t1XHnTQH/5aKEmOBuu2EmSZnGO6XisE102Hg+ G3TdWk5mPhvyFrA04RVCsiwhwWa4Jrp7DU4gaRxMVVLs6C8VgcNOUVilSTZnc+8pGxr4fx6b D1gmFA9/N2aaZbeQ+S3kvQOpDvWignsicFBcQ+Jw2C7vq6Fy2yABNyWFGeQQf2lhICKHlYKH sEMcNcDRS5K1W8FEtIvFCRNsKSaBLJmtQEuCGs6cCl2YK7abiCuqBBZXaKi44x3GijRv8Ray n+ugmZIGl0gwviMgXBYJUDDOw/Kr7Bt9XSm2cZmwScgWVS/Ebwcwjj8FUtFquDqEXcf9piCa AkyCroH7L6LMExoZSSNcUTc0ti5jk4VYZPV+69kA3+qBjgty5cU2dbGohntW2NDIPU0Pj7cq T17AiKbiq0V/he7LOEpKXNnwh50VjlakXwTcm4siTQv+JcMoleRRzD3TGCQ7mDn1ZY5OZjEM UiHJwmg8PR+ezMj8eYwL9Bro9MoBaUQtam6UFlUowpV1PSlQv0iPAvVpBQg7/GWiaXqBqFtE Mf8NBzRNHCFMmw/Uivv34+fj5e5P2OzXvd4t3SK0JlmB1viIygsgiMaHDDZOi8JKjKWVFXlS 09QpCgmcbBqVMffquo7L3Dw5LHGgzmTvJ3cEacRO1HVpAxPkJohHYhmu2nmvgF1YxnU6p+PR AVnmN1tE+7CMSRQ3/ee621qhrD8PxnGeVDqUOSYgjDOusdx0E4AfbVTZf/10er9Mp6PZL95P JjqEb1VTMQyIByPBTVgjOkpCbbAJbjrinhwtEv9Gcd5C3SL6YRenpluRhfGcGN+JCZyYoftb xtz7qEUyvlGcS5pFSGaBu/jsxxMxC1wfPBvOXB9s2uMjJqkKXGr7qaOA549cUwEoay5UoHn7 k9oWeCt/k4JTfZn4gO96bwpbhHstthRc8B8TP+FbnDm/kVOWEgJnZ1kHQiRYF8l0X9KOKNiG wjBRBcjfIu+DwxjT1dstawwwrZuSE7s6krIQdcJW+7VM0pSveCnilBW5OwLgkNb9OhPoq8gj rsok3ySc0R75eN3RXtl6U65dMemRZlMvuDyHmzwJLXm1AYEcW2bAVv+unBfY+OMtN1rsv9yb 9wbh0rWv//Hh8w3NXq8ZMbr21rEdR7W9TeNwg1zyPsriShkM1GUS8hZDLS2ny2hQ5lW8Qo3O SpRRnMeRYqOR6wJ2Dxh7YTEBPTK+A+jkESqaDEZvFaeS5c3bwOrXjzNd7NMq+9dPz4fzIzp/ /4z/PF7+ff75++HlAL8Oj6+n88/vhz+PUOHp8WdM0fsNh/XnP17//EmP9Pr4dj4+3z0d3h6P ymj7OuJNMN2Xy9v3u9P5hO6bp/8cGr/zTrJIavwWkHvygoR5QwS+rOMQ0bTShliiaRaw8g0S lt9z9KNFuz+jixBhL6mOmUHRq2h1DeHb99ePy93D5e14d3m7ezo+v5qxBDQx8DHSWB0NUKRL klyAgP0+PBYRC+yTVuswkSvT5sNC9IusRLVigX3S0hTqrzCWsGPJeh139kS4Or+Wsk+9NjUt bQ34yNwnhcNNLJl6GzhhyigKLX1VsoRerhuePN7VpdDEvdaWC8+fZpu0h8g3KQ/kOibVX950 SVOoP5xdbTtIm3oVm3mBGriZ9lp+/vF8evjlr+P3uwe1zr+9HV6fvveWd0nzJDTQiDN6aXBx 2G85DqP+EgRgJRhoyYGrjBsrOAi3sT8aeYSf1A84nx9P6E70cPg4Pt7FZ/WV6Gb179PH0514 f788nBQqOnwcep8dhhnT3DLknxfaQiuQV4U/kEX61XYItvf2MsE8tv3PjO+TLdNyDBXDGbnt feZcxfp4uTyaIn7bn3nIjdmCe/pqkXXJFbm1M2IzEGgDS8svPVix6NNJ3UUK3DFbC256Gl29 3USrdrD7R8V/KzuW5bhx3H2/wjWn3ardVJxxvLnkQEnsFtN6dCTK3e2LyvH0OF0ZOy63XTWf vwAoSnxAquwh5TQAii8QAEGQyMDe0V0Zcxg+w2zXQX53/j43fF4OMSs3OeCeH+mbIKWbvSB3 PL/GlTXp7x/Y6ULE/Ojv94N4D8slhdjIDwtTbQjioYYK9eX7zH161rI/q0lmJ6DMrph2ldnC uigV8DmFfHFD0ZTZJfs2g108ubiMVxSsyI/XHPjjJaNec/E7I3sYGHoxEz+IcEDtth/9hwuM NXF6/u7dKx5FAWM+yLbXsfmQFPUOs0fNIqJHu+yUCkwbpWKpmtLRkC0UsR5gFyYL0fHAZkx/ VvQ3rn2Ql4wUbLbeO+XjRFxFML2r2TEZ4FPvzCz8fHzGe4ye5Tq2fFUY31Y4EMUtH8o4oD+x 6avHstwqAGjOBz0MBLetjh/ab8C8//l4Ub09fju+2AeeuK6IqlV9uuXMuaxJ1pREjcew8s1g eDlDOFAb8yOAFNEnvyitZSMxWmV7iLBYVz9kgXBt8b9O317uwPZ/+fn2enpiZHahEnZFIXwQ eHEu55iGxRl2XSxuSLj5RiRrrMR03ApCuBW0YJOpW/n5colkqZGzAnvqwWTDsESjTA27me9i uYev/fxJZtj54k/YR51PD0/mkuX99+P9D9iheW+X/QK5bVGiKtEczJHUynJKMcsiharw9dMG MzD6pwAiOpIbawAxjwkMne2sjfcHDVClsPNfNRSa6O0+6iZzBx9aWEow+MsEPjWBG/KPuJdm xrsEKSUwcw0evM4WvUMOuhpMVVhKHujy2qeI1XnaK931finvESL8yWShG+AFNCI5fPIZwMHw CYsHEtHsQMouUCSsJwtw1570T/1fjjsSWHQ0pyYCx9gejaZxIqqsLtke3yK/gyQqvFOPW7NO AyioCQDiDtW/kA/CvuehHDVKfhaxv0WwO+gG0u8/cb7aAUlhcG4SowGuhO/fH8BBPhsGrfMu zLHl02C8M5vK2KCT9EvUmCAz7th5HNIZ+BULx8GLl5PrnLNTbnKlFXXpX+aaoPhZdyUlbtpy +EHhTZqePS/d1xcw0uFGFMExd443LGsvisuAKLest9LzMCUyZSt2vUwVNdMgClmt3cAowlEK Z7ENUy7RCSDiRJY1ve6vr2Ct+fVApwvRYOxWTurZZREqiXcxZo73ba2JrFKwIxrHhd2uCzML zuQUdeL/4gROcdtr4WaaaL6iAnNkZrlVsBq91b/KnE/UKsNMSgrk9SEYiqrGUaSttStoQR1k clvrAGasEhDtmCDCSfjblL5fvU6+iHUQ4DE+iBEop5BTjVwxQZ8tjdhOjqmhR8+m1ZoEfX45 Pb3+MK9CPB7PD5yjnFTkhh7YYQ+yCZsK/2YpdZoC8fqkU3jf13VSmti+vqjXBWjIYvQG/neW 4munpP58Nc6byYEcf+FqandS19o2j5I3c1x3qARmXwueX/DA8fPjhzKpQVn1smmAjhsVUxD+ gf5P6tZ7xmd2zMdNxumv439eT4+D1XIm0nsDf4mTe69AhkiKpwHOuvrkng00atuLFuOFZzIC N1JkJt1ry4vuXOLdcQwIgBktuEgG09VWpnReU6q2FNqVdiGGWtrXVeHGGtE3VjWFb3aVKSAK ta5QzAQLbycqPXR6W5PEdKSbB5/ANyUYcBiv58pKt9adFBvK4pJuO3eyfnk6/uGm/B0WW3b8 9vbwgMcI6un8+vL2OKR9t0ws1opCRBonms4BjmcZsqK0wO//vuSowtfCYxx6Bju8Wff5t9+C znu2rIUZ2dEvzTcQofOb6EqM0Fv4Dp7oMB+iwzCa0c0688JP8TcXmoW0qOC6pBV4C61SGjYz WItbmrBz9W1SLIoqXwXZIX9p7vxBwDgc/4kWAw+zc7knYON3PRGLskzuNb7zXnNtN99FMqsI gypH1MAslnf40CSsrt5V7EkhIWEBtXUYnzfVBHKDCwk2BE2dCS0iswxRJhqrnQG7Kjyo1FLg Ed9sxZaInkWZrWRXN5v5CvC2JMo8dtx8UpAWICwW4lN9cn9eph14W3SJiYILW2wMhw4Vnad+ 0hwtOELKKgMTRPqZ7YL23nCBcwOjUqY2OkBlJtpIQ5SZnAeflpPTUAwnXJlctsGHPDS3O0tp VePEAMeBuJhWNpiasvWCw6JlFNWWB29pGM850l/UP5/P/77AB8jfno0cz++eHtwwP4H3bkH5 1J7N7IEx6rdzXCgGiUxXd/rzaNthrG63HZP9OAqxXukY6ZkttC9wCakOzscwSzy08r07PFhZ n+M1Oi1anmV2X0G/gpbOat4IXR5HE3QBavKPN9SNrqzzmDcwtwzQz6dNMLssptN35tshA+BM bKQMn24zDh488JpE+z/Pz6cnPASD3jy+vR7/PsJ/jq/37969+9fU5kGswU6r03IvGZXZQmU4 +PMLbSzpf3PXyjKCwmYTjc+2gE7EdQ0x4LSZsgKTW58URA68pbtG9qFU3e1Mk5bia9p0NVs+ bTNTwU4oHe/ppj3L/zHe/iDAIl4VYu1GuY5bCq8naE2C5uu7qoXdK/CRccjMTsXGCOR4YAcE 6LZCipZJtUqs/8OYB3/cvd5doF1wj+7Fc8gsGG8cTuuWA7aMhqUoegUqjF2hpFOqnnQs7Ezw DdW5V14XW+y3I21g7CqtzBPb5sAg7bgVHLCE3UiA3qSkQwx8vgSYEbOlUPXQnmMUrR8uva+G nIBA+bVd4Ea/R/4AgOAzO4HG7gEsq0M7cpCyhdFkWtp7so7XAKBVetC1e+2QnpuFJjqSn1Tm uL9Zxq4bsc15Grs7DS+6Mch+p3SOHowwCG1Al2S9AAF6nQMSjF2n4UdK2lG5QeVUPEUZ4Ewb yqUwp6ZJ64v0yjtRgkEEi7dvoYVp3NGI3jo5ZgidOwl2JxiMDqpK5KT407MzMjcZ03r1Bpu/ xWC/sW1qDFvnL4EYa85UwBLgs2T1arVEYrToAkG+K4RmCAZ03VZg9ct4hNGcnkq6/R+4aOAU Xl6ZUn1bgRkJ64i74GfcRCC38W00GqZg5+HhZLShdC9OEIGoKnz9GjO8UknJPitgiYHHLRlT 6dKIHypYXSanDz/iIPHtu9ILozOsEVWh/pkbIFqBnnt0knzTupsIZgdaooMZXa3Ye2Y2jTDA P10TbkdH2nWKScmHEYzZP+CPyDVrEVqAatgG0n+SGL9CQS+VWw6cGxX3M7wjzCEeb/WRuMhk AdYyP/8C3zprI0vh+e7ldL5nlSc12do23kUq6x0My7reW308v6IdhRZ3imnr7x6O08c3XeV6 5Omn0W5uDLIB++NpYHJP/WFxpAiGwMUpwHswVNARSs/TfzG+Pl4QkiuLpfH3gbD7Q+YyQ+Ue PjWgqkiAQztwuvxAhGKTaeeAhNgCLS7YGblqgeClqnCXvw3ADGWmbtyTw2T0aiNPR2Zxk+DB zQKXuUdEc2Ht7hlQMBdmZ3B9xawoam0u91lXege/xNicY8X02OBN2DgnJC1Vm24PUekNIHTN 3T0k9Hi2HtSZiorzHhEyUdr4aP0yXae4mFXC7UXTiLhxCw4Hwjd4IqPJsRq1UG0ROVcShENU xJzkcCJQVRn2ipfcJs2CakrYxvAqDYrCEisysw5ZP0ybs4u6kcODCBzSXExkUbRoeIQTAxHg 0jJDNFsOuhCS2+gFnz6Y8+jQxseXskzBKuHe2hi4lkIzVLT4ZRk6vMw04HpD72Yg7P2rAawI DrajpWpbXFZZnXZlaBx4+9ZEGdnpOTmCo7r/AU0ygbAwDwIA --7AUc2qLy4jB3hD7Z--