From mboxrd@z Thu Jan 1 00:00:00 1970 Return-Path: Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S1755265AbdEYCZm (ORCPT ); Wed, 24 May 2017 22:25:42 -0400 Received: from mga09.intel.com ([134.134.136.24]:14063 "EHLO mga09.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S1755245AbdEYCZj (ORCPT ); Wed, 24 May 2017 22:25:39 -0400 X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.38,389,1491289200"; d="gz'50?scan'50,208,50";a="106666876" Date: Thu, 25 May 2017 10:25:28 +0800 From: kbuild test robot To: Ian Abbott Cc: kbuild-all@01.org, linux-kernel@vger.kernel.org, linux-arch@vger.kernel.org, Arnd Bergmann , Andrew Morton , Michal Nazarewicz , Hidehiro Kawai , Borislav Petkov , Rasmus Villemoes , Johannes Berg , Peter Zijlstra , Alexander Potapenko , Ian Abbott Subject: Re: [PATCH 1/1] bug: fix problem including from linux/kernel.h Message-ID: <201705251011.3EACWRIq%fengguang.wu@intel.com> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="KsGdsel6WgEHnImy" Content-Disposition: inline In-Reply-To: <20170524132107.6919-2-abbotti@mev.co.uk> User-Agent: Mutt/1.5.23 (2014-03-12) X-SA-Exim-Connect-IP: X-SA-Exim-Mail-From: fengguang.wu@intel.com X-SA-Exim-Scanned: No (on bee); SAEximRunCond expanded to false Sender: linux-kernel-owner@vger.kernel.org List-ID: X-Mailing-List: linux-kernel@vger.kernel.org --KsGdsel6WgEHnImy Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Hi Ian, [auto build test ERROR on linus/master] [also build test ERROR on v4.12-rc2 next-20170524] [if your patch is applied to the wrong git tree, please drop us a note to help improve the system] url: https://github.com/0day-ci/linux/commits/Ian-Abbott/bug-fix-problem-including-linux-bug-h-from-linux-kernel-h/20170525-081427 config: i386-randconfig-c0-05250844 (attached as .config) compiler: gcc-4.9 (Debian 4.9.4-2) 4.9.4 reproduce: # save the attached .config to linux build tree make ARCH=i386 All errors (new ones prefixed by >>): In file included from arch/x86/include/asm/bug.h:81:0, from include/linux/bug.h:4, from include/linux/jump_label.h:184, from arch/x86//kernel/jump_label.c:7: include/asm-generic/bug.h:101:35: warning: 'struct pt_regs' declared inside parameter list struct pt_regs *regs, struct warn_args *args); ^ include/asm-generic/bug.h:101:35: warning: its scope is only this definition or declaration, which is probably not what you want In file included from include/uapi/linux/stddef.h:1:0, from include/linux/stddef.h:4, from include/uapi/linux/posix_types.h:4, from include/uapi/linux/types.h:13, from include/linux/types.h:5, from include/linux/jump_label.h:79, from arch/x86//kernel/jump_label.c:7: include/linux/jump_label.h: In function 'static_key_slow_inc': >> include/linux/compiler.h:127:18: error: implicit declaration of function 'printk' [-Werror=implicit-function-declaration] static struct ftrace_likely_data \ ^ include/linux/compiler.h:150:24: note: in expansion of macro '__branch_check__' # define unlikely(x) (__branch_check__(x, 0, __builtin_constant_p(x))) ^ include/asm-generic/bug.h:115:6: note: in expansion of macro 'unlikely' if (unlikely(__ret_warn_on)) \ ^ include/linux/jump_label.h:84:32: note: in expansion of macro 'WARN' #define STATIC_KEY_CHECK_USE() WARN(!static_key_initialized, \ ^ include/linux/jump_label.h:212:2: note: in expansion of macro 'STATIC_KEY_CHECK_USE' STATIC_KEY_CHECK_USE(); ^ In file included from include/linux/bug.h:4:0, from include/linux/jump_label.h:184, from arch/x86//kernel/jump_label.c:7: include/asm-generic/bug.h:91:32: error: 'TAINT_WARN' undeclared (first use in this function) #define __WARN() __WARN_TAINT(TAINT_WARN) ^ arch/x86/include/asm/bug.h:46:10: note: in definition of macro '_BUG_FLAGS' "i" (flags), \ ^ include/asm-generic/bug.h:60:30: note: in expansion of macro '__WARN_FLAGS' #define __WARN_TAINT(taint) __WARN_FLAGS(BUGFLAG_TAINT(taint)) ^ include/asm-generic/bug.h:60:43: note: in expansion of macro 'BUGFLAG_TAINT' #define __WARN_TAINT(taint) __WARN_FLAGS(BUGFLAG_TAINT(taint)) ^ include/asm-generic/bug.h:91:19: note: in expansion of macro '__WARN_TAINT' #define __WARN() __WARN_TAINT(TAINT_WARN) ^ include/asm-generic/bug.h:92:49: note: in expansion of macro '__WARN' #define __WARN_printf(arg...) do { printk(arg); __WARN(); } while (0) ^ include/asm-generic/bug.h:116:3: note: in expansion of macro '__WARN_printf' __WARN_printf(format); \ ^ include/linux/jump_label.h:84:32: note: in expansion of macro 'WARN' #define STATIC_KEY_CHECK_USE() WARN(!static_key_initialized, \ ^ include/linux/jump_label.h:212:2: note: in expansion of macro 'STATIC_KEY_CHECK_USE' STATIC_KEY_CHECK_USE(); ^ include/asm-generic/bug.h:91:32: note: each undeclared identifier is reported only once for each function it appears in #define __WARN() __WARN_TAINT(TAINT_WARN) ^ arch/x86/include/asm/bug.h:46:10: note: in definition of macro '_BUG_FLAGS' "i" (flags), \ ^ include/asm-generic/bug.h:60:30: note: in expansion of macro '__WARN_FLAGS' #define __WARN_TAINT(taint) __WARN_FLAGS(BUGFLAG_TAINT(taint)) ^ include/asm-generic/bug.h:60:43: note: in expansion of macro 'BUGFLAG_TAINT' #define __WARN_TAINT(taint) __WARN_FLAGS(BUGFLAG_TAINT(taint)) ^ include/asm-generic/bug.h:91:19: note: in expansion of macro '__WARN_TAINT' #define __WARN() __WARN_TAINT(TAINT_WARN) ^ include/asm-generic/bug.h:92:49: note: in expansion of macro '__WARN' #define __WARN_printf(arg...) do { printk(arg); __WARN(); } while (0) ^ include/asm-generic/bug.h:116:3: note: in expansion of macro '__WARN_printf' __WARN_printf(format); \ ^ include/linux/jump_label.h:84:32: note: in expansion of macro 'WARN' #define STATIC_KEY_CHECK_USE() WARN(!static_key_initialized, \ ^ include/linux/jump_label.h:212:2: note: in expansion of macro 'STATIC_KEY_CHECK_USE' STATIC_KEY_CHECK_USE(); ^ include/linux/jump_label.h: In function 'static_key_slow_dec': include/asm-generic/bug.h:91:32: error: 'TAINT_WARN' undeclared (first use in this function) #define __WARN() __WARN_TAINT(TAINT_WARN) ^ arch/x86/include/asm/bug.h:46:10: note: in definition of macro '_BUG_FLAGS' "i" (flags), \ ^ include/asm-generic/bug.h:60:30: note: in expansion of macro '__WARN_FLAGS' #define __WARN_TAINT(taint) __WARN_FLAGS(BUGFLAG_TAINT(taint)) ^ include/asm-generic/bug.h:60:43: note: in expansion of macro 'BUGFLAG_TAINT' #define __WARN_TAINT(taint) __WARN_FLAGS(BUGFLAG_TAINT(taint)) ^ include/asm-generic/bug.h:91:19: note: in expansion of macro '__WARN_TAINT' #define __WARN() __WARN_TAINT(TAINT_WARN) ^ include/asm-generic/bug.h:92:49: note: in expansion of macro '__WARN' #define __WARN_printf(arg...) do { printk(arg); __WARN(); } while (0) ^ include/asm-generic/bug.h:116:3: note: in expansion of macro '__WARN_printf' __WARN_printf(format); \ ^ include/linux/jump_label.h:84:32: note: in expansion of macro 'WARN' #define STATIC_KEY_CHECK_USE() WARN(!static_key_initialized, \ ^ include/linux/jump_label.h:218:2: note: in expansion of macro 'STATIC_KEY_CHECK_USE' STATIC_KEY_CHECK_USE(); ^ include/linux/jump_label.h: In function 'static_key_enable': vim +/printk +127 include/linux/compiler.h 1f0d69a9 Steven Rostedt 2008-11-12 121 1f0d69a9 Steven Rostedt 2008-11-12 122 #define likely_notrace(x) __builtin_expect(!!(x), 1) 1f0d69a9 Steven Rostedt 2008-11-12 123 #define unlikely_notrace(x) __builtin_expect(!!(x), 0) 1f0d69a9 Steven Rostedt 2008-11-12 124 d45ae1f7 Steven Rostedt (VMware 2017-01-17 125) #define __branch_check__(x, expect, is_constant) ({ \ 1f0d69a9 Steven Rostedt 2008-11-12 126 int ______r; \ 134e6a03 Steven Rostedt (VMware 2017-01-19 @127) static struct ftrace_likely_data \ 1f0d69a9 Steven Rostedt 2008-11-12 128 __attribute__((__aligned__(4))) \ 45b79749 Steven Rostedt 2008-11-21 129 __attribute__((section("_ftrace_annotated_branch"))) \ 1f0d69a9 Steven Rostedt 2008-11-12 130 ______f = { \ :::::: The code at line 127 was first introduced by commit :::::: 134e6a034cb004ed5acd3048792de70ced1c6cf5 tracing: Show number of constants profiled in likely profiler :::::: TO: Steven Rostedt (VMware) :::::: CC: Steven Rostedt (VMware) --- 0-DAY kernel test infrastructure Open Source Technology Center https://lists.01.org/pipermail/kbuild-all Intel Corporation --KsGdsel6WgEHnImy Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICBU9JlkAAy5jb25maWcAlDzbcuM2su/5CtXkPOw+ZMa38cypU36ASFBCRBI0AOriF5Zj ayau9VizlpzLfv3pBkgRAJtKNpVKzO5G49Z3APrxhx8n7O2w+3Z/eHq4f37+c/J1+7J9vT9s Hydfnp63/zdJ5aSUZsJTYd4Dcf708vbHh6fLz9eTq/fnF+/Pfnp9uJgstq8v2+dJsnv58vT1 DZo/7V5++BHIE1lmYtZcX02FmTztJy+7w2S/PfzQwtefr5vLi5s/ve/+Q5TaqDoxQpZNyhOZ ctUjZW2q2jSZVAUzN++2z18uL37CYb3rKJhK5tAuc5837+5fH3798Mfn6w8PdpR7O4nmcfvF fR/b5TJZpLxqdF1VUpm+S21YsjCKJXyIK4q6/7A9FwWrGlWmDcxcN4Uobz6fwrP1zfk1TZDI omLmL/kEZAG7kvO00bMmLViT83Jm5v1YZ7zkSiSN0AzxQ8S0ng2B8xUXs7mJp8w2zZwteVMl TZYmPVatNC+adTKfsTRtWD6TSph5MeSbsFxMFTMcNi5nm4j/nOkmqepGAW5N4Vgy500uStgg ccd7CjsozU1dNRVXlgdT3JusXaEOxYspfGVCadMk87pcjNBVbMZpMjciMeWqZFZ8K6m1mOY8 ItG1rjhs3Qh6xUrTzGvopSpgA+cwZorCLh7LLaXJp4M+rKjqRlZGFLAsKSgWrJEoZ2OUKYdN t9NjOWhDoJ6gro0uqrGmdaXklOsenYl1w5nKN/DdFNzb82pmGMwZJHLJc31z0cGPKgs7qUG1 Pzw//fLh2+7x7Xm7//A/dckKjhLAmeYf3ke6C/9zNkMqbwxC3TYrqbwNmtYiT2E5eMPXbhQ6 UGczB/HAhcok/KcxTGNja9Fm1j4+oxV7+w6Qo7ESpuHlEtYDB14Ic3N5nFKiYIOtggrY5Hfv esPYwhrDNWUfYfVZvuRKgxBhOwLcsNrISNQXIHg8b2Z3oqIxU8Bc0Kj8zrcCPmZ9N9ZipP/8 7goQx7l6o/KnGuPt2E4R4AhP4dd3xEoGYx1yvCKagCCyOgcNlNqg1N28+8fL7mX7T2/79EYv RZUQjUGlQfKL25rXntI6QQA1kGrTMAMOxTPF2ZyVqW8Eas3BHPrjZXVK+lG76lYTLQUMCwQk 70QW5H+yf/tl/+f+sP3Wi+zR9IN6WLUlvAKg9Fyuhhi0W2BCkIJulsx94UNIKgsG7ouAga0E CwbD3wx5FVrQnbSIU2ytIQsxEDAkYAKdggc2UFdMaR72lWAwoGUNbcDWmmSeythq+iQpM4xu vATHlqJfyxm6i02SE6ttDdKy37zYOSI/MJal0SeRzVRJlibQ0WkyiCUalv5ck3SFRGOOQ+6k yDx9277uKUGa36FPFDIViS+spUSMAJEmJNYifeo5BBRg17VdBaX9Ji6SrOoP5n7/r8kBxjG5 f3mc7A/3h/3k/uFh9/ZyeHr52g/IiGThvHySyLo0wT6jFNiVDpDHcUx1itqQcFBUoDCkpUGH AOGgGQ5TJfVED5fIKA5eK/GCRPgA5wPr5keYAUUCsqJhL0Ko7XrICkaT5+hOClmGGBf98Vky tf40wGWshEDa81Q9EPwyy7wgsptBYyPgkM2i9ZcVCMHNWdC5TKa4E/4K+3D4o6TEI6C540qO MoBpE+2tg4dYuLzwwhexaHOBAcTueA/OJXLIwPSJzNycf/Lh2CeE1z7+uHow/9IsGs0yHvO4 DEx1DWGKCzsgYk2dVlKh3RRtDhDUJUb5ENw1WV5rz2ckMyXryrMHNii1cm2zpeOagc9JZsRC OQZuHJ4rYkI1JCbJwL6An1qJ1E8jlBkhd9BKpNofTQtW6Ygnb/EZyBxs/viw+5C3b1qB2wwV M2ab8qVI+CkKYBLrfjQhrrLBLKdVRkzSOiGCk5ZopFoa5zj6pnOeLCoJ0oQmEaJZerQYlYDb AltF8beSg9Gh7cNnDy4mwzC/UjwBC59SChjmX9N8gctmw1zl7a/9ZgVwc47OC1JVGgWgAIji ToCE4SYA/CjT4mX0fUX1jnE0rJSLk99//U+fESTHxAd9v904rBmU1ob1Cx6RYf5IrApYxhJ6 lamf4jiNFum5V7tAJ25yMPAJr2wGGFnNNk3W1QKGlDODY/JWu/KEK3YSUU8FhKgCRN6rjWhQ igLcRDMIJdzG9+Dj/F24OnS9XZwM5HpTeJPuIE3EqIdPtcxriHhg9KBOJ5iCPdE2pYNceemt kbOm8XdTFsJP5ALnzfMMRGFEW6LlJmnsULKa9CkZzMYrO/BKBksrZiXLM0837Gr6ABt3+QDY Z2KP5kGazETg+1i6FDDEthVt5lAabOqSUZpdJaK5rYVaeLsJPU6ZUiL0GbYQkpLmwckvdNMc A1Jvnc/PrgaBUVsirLavX3av3+5fHrYT/tv2BSI4BrFcgjEchJd9xDTCvK1NIBKm2SwLW6Ig l2FZuPadOxzxCW3ZTC0oG5qzwLnovJ6SXHQuxxBsav0YBl+NAs8pacmDHTW8sJ6ggdReZCKx tSNqB5XMRB4Etda8WIfh7WqimJ5bffD0lq95EsGkYxgYxA7WLqG1MlXO12Oy4PGIOYDCOl3w +f9cFxUkQ1NOaVpfRerTA+zElpHB4oCqoWtLMEgfGxDPYAUFjr0uwxZRoIVihOEiJAIQ/K9Y XDIRsFYYfcGYTIRaxNUuB1XckAjwMHQDB23ATWSUnwgsXp/qW9K5lIsIiWVe+DZiVsuaSBU1 rDxmZW0SHC0HFlIhgGqLFERQCoHDBgIPzFetj7H1tmgIis/AA5Spq5m3696wKp5HklODB7o4 dbe4+QrUlDMXGEW4Qqxhg3u0tmOInTQYRoCbWpWQQBjQMd9txjaNWHeLJRh39ki1E07rIhYj u3691A9W3e2zyx2SosJiebxYDuqqfyO4VNYjdWRRJY2rcHT1RGJ8midoDxvQWzNYmhkESVVe z0QZaKYHHtNFoLDrgirEsTjr2SgC5UdlIXIsXRwSwibVOfsLbiC7sqRi835FVsLMwTC4bc0U BtyxfSDrCZS2llhi4m1NHxM1zwHLtM7BBKAxwiBGERKiHca6kOHxxvBQKSLga7CdpMqHrT6H WyerTVcON/nQJHdjm5NODU+VprXVfGrXcthNCLmSxYqp1BuvhNwd4qn2eORygGD2UDDK+rCk 1Bv9LKPdfT/oJc7a7itJaGmkDd5Z3hWK1Wr9XxF3NWQqlTgaWwNG2XiNvFBwHBU3dwLU0riD ikQuf/rlfr99nPzLxV7fX3dfnp6DShkStfwJ3hbbufEo0I9xxBQtiTuhtXloylHvBkxaisvm ilxbn+aq+TSmrZ13c95vzlHRvJUEo4unOUHFosCA3tdnG/1rDClvzr3SidNNouNOa21tLAdP HKbZUyzrUPEbCwvFTJfnXn5X2vM5GEgFhqcuidrQ8biNGYmOWBVehd7OyjWGgEKuSt+Qu5PY EST2NIY7hkr2RCO1ZLa+3ZOMY+LGakU37eHHNSRKQFa6q9fdw3a/371ODn9+d/XgL9v7w9vr du9fPLhDCxNVmTqR8F00nmxmnEFkwF1VJUJh1b7D41ldhC8q61r9gSN4CjasoA+7ZmDKMjFi NrEtXxuwfXjcfCpfRUqIdvAMq9K0xUMSVvR8iPJXZ62lzppiKvxpdLDRMlZ7JiyUCPbNVZ9A Oo3zmo2Nysha3nwD4RNkteCQZzX3S9SwqGwpVGAyOthwQEOSoyhS1QdID7vu+urFsmgzzBH3 kdsmruHpvqOQgDQDLWlU/gU/NpXSuCpAb4WuPl+TPRYfTyCMpnNjxBUF7cyK6zGG4I2NqAsh /gJ9Gk9LcoelnUCxGBnS4tMI/DMNT1StJV0fKmz0wMOUu8euRIlnmsnIQFr0ZTrCO2dUKl/M OLjF2fo82GoLbPKR7Uk2SqxHF3kpWHLZ0AfoFjmyYFgSGGmFXmZE81uvG1pDq+hYJG1v5Lgj kGufJD+PcIG5qiCuAHNbklbK2jNM6AuM8/xSaG8MMRXDyDXEgTJEZluUoqgLGz1mkNLmm5sr H29NQWLyQnuesD0cxPSB51E8g4zAObtR0OWmlsJuIhjOk0Rgtk8zgRVgNXk+0lLYrKPghrlr dgMOdZFEg+iMcsXNsWrTwlI/Hy7tJSgvXXAWXxd+1GVBReIvHudFZWweF1j1Fr6UOdhLpja0 cXVUZEnMtbfmNtxkmy5jBhJLqSSAiiuJRWs8A5gqueCltcWY5OnYuxeheLqwxCtvftu9PB12 r0G8bQfEIYHZQP7hX3YMv4wEvZh6IaL4vIi7VxxHlol1XVH+zY7Ql1sEwI6J1Pc0eOoeOZoW dEX71hZ7PYJeFrrKwedf/hUas6WTJBenOVwMOEQE5zM/jpjxRkJKyM3N2R9XZ+6fyOYw8sAH I9cMIieYc8NLRtzhs5HfONraiO7KDyQMfqIlcpSFvIuN8JZIzfsD9JNtu0EVrKxZkJn1I3I4 6ijDNQ65NdZku3ZeaNyzwxsPvsK4whsvpmH8EoBbpiy+MZgKnUDSTzRvpwvxYM7iNN+yboMj dzsP2VPBvZWBytghWDt1FfGf4sFBVETAo4BkpOheiJkajKeabyAJS1PVmNE7zi4alFgH8SZZ 1H4Fsg9ANeVpu5totlDjru2k6ubq7H89v0nVl8iaC2eldb1eDa4ID58hgx6L9o+4TAft7X1a ffPJy7wqKSnRu5vWngW600V3x7Rf1PZiKEy2oiPnrpWVyGGB29437er2Y6kzrClXCj2WLWA7 G4EHykH2g2Vyi8Fi+4IejTWseGAP+Z7Eo2il6iqWFJsOguBi0F90MtiTOgYjzBWHcGaJFYbV zfWVF5gZpUgjaWd64qwJmcIS0pkpz+jIsq0N017hrjk/O6PCiLvm4uNZoMJ3zWVIGnGh2dwA mzi7nCu86EVe9lxzP+gALRUYBIC4KPQA560DaPGKY4xgWuvdXzPqKq22LjSyN/Z2lWWgiQ5t nAodXgT9zUEM8noW34vqxcMjoFfK5ahjZL45g5Aq1TJU79SWl6aRfvr1LpFtmjw13THzMMzZ /b59nUCYc/91+237crD1F5ZUYrL7jm8/ghpMW8alojb/OnhxPPPpLUGB5914VyM9ke6nQNZd ziQ7gUihCjpyx05HBqtb8MAr8L99+fhE3TbxT7HwqwvorADpvg7oK2OBzyXa4jM2qfznERbS nv+6gaBdA1b9M5NetZPucGzGR5Tf8ockJdOO28gkQGqXjVyCERQp958ghJx40hn8MT4snsqU GYhmNjG0NsY/dbLAJfQtI1jGyuGM6UqqxdnsTXHYxOBst1sGl6sldklH0SK4eB0iI/iI9kYM 2WymQCyMHF1+M+eqCCM3N51aQ77dpDo9eWzgeFhHWVcQmqTx+GMcIUIn5CcReKdh7M0W6FCU G7qhS8jdRDmAd0smZJtxhZ3pKV1sc205nQP7awUJ7lyeIAM3X6MNmUPEuYJIpZFlvqHczFE/ WcUHZ+4dvD0XDrtAxIh1MtlQDz0TJ/DqGciKGCk8dSsLf5M6qDPRHfngPavsdfvvt+3Lw5+T /cN9eNjTKYoXuXWqM5NLfI+ANQ0zgj7eLQ6KCBaNujVaqLAUXQSLjLwreP9FI1xBDfvw95tg Ecjejvz7TWSZQsxYjlddBi0Ah8GZvbo2UocZtLHRS21EPrLSY3cUA5q/tx6j60ARdrMfFYB+ qiMk/syOEvkllsjJ4+vTb8FlLyBzqxQKXwuzRxcpX1KVvqqz62EynyRd+/EzkdZ3xEQ+G1zk Uq6aRVRl7BGfRhFdpBB0OlvbcKiQVDhkw/IKAkqIBFxxT4lShh0M8Y0Jyw4hlfBfGIUoXQyG V125w4jx8XW7UtqHNBcxg1yWM1XThqzDz0ERxo+9eskeHvrtf71/3T56MSY5r+jNVIi0b0fx yj1k0oOc6yiy4vF5G9rNNkAINMxmhyj2OeTj9DV1n6rgZRgxoCvH/EH3dImsqzz0eHZQ07d9 N+3JP8A5T7aHh/f/9G5LJsFeovueSUxHaadj0UXhPqmY2RKkQkX1bQeXeUWfKjk0Kynfirgj Qx9mn2rpuJeknF6c5dzdVKXZcYyNg6oKAllYUEEQxLCKfKPnyMGS/BwPizNdFTEfhJ06duxJ xpKHI8lRyMk+2iSgrk6Y+J6Ydqf+/Kti0A/EJWNL0lSmCPeo0GIACN/eBXt3colAA13txpVL 7cWQEXHRpg40eW7r8CPEzISCAMHmMgRUaqAjFdNi7I50d02v776NYlH9Yv1Mt/unry8rME8T RCc7+EO/ff++ez34qbBb+ZV1aMOkGhr+utsfJg+7l8Pr7vkZUuzeUx5J+Mvj993TyyFQfljN tLsWGcywg5+KIC1dldmLDZ3jxp72vz8dHn6lh+Nv0wr+FZB/Gx7E9u3lL6LD9scG2guhfgMq vk2wfBIUuC1krlwOQjRBA+U3wO9mLc8/QlPqIhrLxdqnL7n5+PHsnBThGR81qljQJrgrmGYq /KtHDtAYLT5dnA/hWBu3c7Nv885idKs4at2YdWOLmWHVqmUC68vLmShp83EkGyn09p3VBda/ /Lp/h0vmBSuH4ALH1CQuYHOPIu+/Pz0KOdFOoAZS5C3Ix09rajZJpZs1dfncb3r9mRgjNJzx 8oJiqtYWdzleI93obDrQU/7H9uHtcP/L89b+RMrEHvgd9pMPE/7t7fk+ik3w2llh8OpmPzj4 CG/gt0Q6UaKKbzYzlIKYkgQWwj/gxh7Ce8htQfAyfvnf3iITMiiXl/xoDMrt4ffd678wdB/E XpBYLHh0QwchIMWMEqy6FN41RvyylJH6NQtOHwGDPNOpJsDxNx6wTF0wRd/pRMaVqdqXtRnd Q8eomm+sEkKCUYycQwDp8aa0394BT/jBnqarb1JWyXfD8AEeqfRkRhtvs2ZMeV+F/zFVIvWv GrvvZgnc2nvewY1lC/98dnF+S8Ga2dLn7SGKAJHypPQrCe67sYfr/o3DPAk+PMkU1Tr4aG+V +CvC/NcD+DqRVRA8h2BRpWlwKdMCwKwl4fFHp/UXH70Bscr7NZVqLoMpCc45Tv3jFQVryrz9 w77fE3hZJSz2ebT4FHRErAuWOCJa/I7vba2e3r5t37agpR/0w6/bx7e2+hOIv8afLJhSQVSH nZtpYAQcMNNJrKIIB7E8wcq+Byda2ddEdGbekaiRsl+HjwzzAHs7nIPhtzkBnWZD4Ez5j5g7 aKrRsgzh8P/wCsWxgaKik+Mq3LbrE2/PXC44xe42O71m+BNZ1JFrh89uHQnFOzspEnNijSpB DhJD5BOs2tzIb9mVxrrhnTgAd/s6aFllIpP2ku6Jtu0Ibt7tv/z7XZvqP9/v909fnh66Hyzz BpuEjx1akAuFRuaHeJOIMvWfiXaIbEWxq8nLVx1W6WVFtUI4fQ3x2FsuVycJ3MPzE30Hb5B9 tr797uAFHr9FDwQQxy3i5EDYyE9sdHhBnhwexVZkgYVJE8ospCU+B9MSfzPJc4RgvBjepVj6 HHpo9+eSHJ9HV9LVEI9i/ARt6Wy/l7vifREITv8SQRTkYVVyUS4GoVfvTaqRJ8NzTVkq5f+y hMrsD6L4d5DWPr79KQMbYwV2zUO4wCsyrQp/TENvmvA99TQ21ih77S9rhWHp5LDdHyJXN2eF YhDj09Vx8iquUCnrOIvXlOFzmcPuYffsBbtC5eHhpFC4CyPcGjA7KuQ5CJ8tXfvDdfjIINcs DFcQb58fkL7Eortzc9fNy5dXrJL+hLWHyeP2t6eHbVxG0EINMV6XxmwapBlUOXYvXyHh2R8L G20LvBij67JJZTn7f8aeZblxW9lf0epWspiKREm2tDgLiIQkjAmSQ1AS7Q3LiZ0b1/U8asap M/n72w2AJAA2rCzmoe5mAwTx6DdcU/SdytjDA+iqU8R2vR2hmvn+3U6d1E6/LGUgEAfYZniO tficKQM6tAe4iGJXFpkFDoxtqCWC6bAXifWs0jQk6KXQXPjNnHMVQgQLG5WpivDbuWodpqXz rPYg9R5nnLdj9cAOvhu9EwGjglO7PWCOIqu8Fo4q4J7TJgSNyahNDTAKdNzGS+bYNU7kmDFq v/79/Pb169tf73x37E8qdg18/1gnNF7FFrshOLGakg3s06lM5svWHwQA76HRYCgAfD6mtKcX 0LI+064N1dScSZOAS332vdh1NeaSufMVqxwqAoK5QQ4UfgUJ/RrklzTSIOVGxFsi4Z1+6f6A 6saC6GIudhrl6EcW0qX1fdUAwyqKS1MZRzZ3gkJ629rQsS/Pz08/Zm9fZ78/z56/oBXmCS0w M6soLcZdqYege1qnqOq6Tboy6HwcUumWEtU/bXSVrks5hrfX+zvhnk/mt14BE6AoKtc8Y6GH KpT2t1X42x7yoRy1jZcRSplwKxHBr2kclYYCH9CRIxy6YKoX+4iHRzGQIciCbtBNsfdUgvzS nIoikgiRYR08PPcIXiAwdCBo5MofHug+ijeOnYPd67TCEWGN8Xo3yfxDTxfufPnDgmdleBKf TKWLI88rV0r0wLCAm6NT4wgabmS1DyqUGFgnMReBOq8aVmQsn2ZA6IbgWJA6RkWXMKO2CpCC SuYVQx6eEcUkmRdWec0GCqfvAx9TuCB8bxINkkieY8K223N051y0/aU3OdIfXK+qDDacSCiM JeDnmtNCqiHAU8WyAaFelhH/mLpXTmZhxJRvix1WJ5sUSR1mLhU6q4JSmTU/eGZT87sTbuE5 C5PS8wJYQrfeJBrtdZ3fDGvH7f3kG2ZSooZSUuO4YMqzn+M6OI3NyeodqfBPoesfEC8rG0c4 hx9oh9EJMHByubqIizJeXR1TryP5PyyiDHQtFh1sy99rB32EGcZo+TR95CrRl3I/QEchC+Cs vjWIyeCcfsAmIE1ZYV2CqPn++OWHMd/P8sd/PAeFbqKsJuyRtcD4bUxzAiGdiFmomfytLuVv +9fHH3/N/vjr5dvU/6Ffbi9C7h95xlM93egvhVMzrNxqWWmt0xQkUFNkUdo6N15ziNnBvnPf 8A7xtAZpCfN/S3jgpeRNTYUEIAkugR0DnVUXFOwWfmcDbPIudhW+UICPZIQSnYikeE4pSetN /+ZiMR15kVCjLiJJrz16E2mldF0AAzXGRXkS4jAnJBy62RQOBxKbQv0ANb1GmQwAZQBgO2XK LuipLx+/fXPCvbSYphfA4x+Yux/M/xIFi7bP+ghmLUbUy+mUtWDr2YoOYk9W7iMDqXZpd2jb kL1xNGPw8T4PSpy43FPhdxYFPZOi44FNwNoZi9gEGAwHmAxujqazno1R259f//yA3vjHly8g 9QLRVHFyucp0vQ7moIFh2by9mLyuRcYkTT0iuelnMLwAjK3vJgvfDDMcmrLBfAyUxXUak4/l tS7EgdhFsrFC3cuP//tQfvmQ4gSaSHhef+B7HZaR/hRYlYqnqT8sPRS1/SmGoN25YXUeB4Px p5G0trr3+pRxLFNGMDWI6SxzkVkTtqmxOBGji0JTlHpDg3k2kTantCAElbE1YDoj1F1Z+IW/ CaQ5sgbP57+jzbC656i3xUkxQZUcDIdyt2sutWgiZQCGB2AaxTdmTZKyfexsNni1XruGhQGB fykhCYxTDXTa3lEosZ5TvsCBRDZ34aMgnhRBULNeMnkFwzr7H/NvMqtSOfv8/Pnr938oQ4ze kvQDsRFRFUoWEamyO+2C+QuA7pLr2lLqWOZZuBFogh3fWZtvMvdbQyzaRSXpx+0pDvmJuw2X XoVekBpPhWgily+gTAknHBb3cRn05e88WD9BCZi/cgHuSfzlvvO8yvBbesFC2IuAgY5uC5hY 94YHw+Se6S0qTiqSKQkXphhZEBUoVrh5VIU1SnQS3pId+GDXq6aGcyC24dBGMnj58YejmvQq Gy9AVVN478cyP88Tt05Ztk7WbZdVbg1GB2j1rVElOkl5H4kWFDvZMeWGOB5Z0biijDpg+GDq OPYbsZe9kW00HSPwtm0pa5lI1XaZqNXcOYBBe8tLhSWEMI4e1U3PSIN7xbqT+0MkM/4IymJO xUqyKlPbzTxhrsFEqDzZzufLEJLMnfe0A94AZu2nafao3XFxe0tlF/YEuvHt3NnkjjK9Wa49 QTdTi5sNJStX6DE++mGeaOo3AYXdXrHtakPnQKpA6KDDHiNrO038+5vMb5g2wJTVXbLQo2HC vTjuAo7TY2jIYDrWJNSObLEmOdCZBAYsWXuzuV1P4Ntl2t5MoKBsdJvtseLKGed0d7uYTyal gUathSMW1oA6yUFFNHc8PP98/DETX368ff/7sy7Oa0Pu31A51h6lV5A9Z0+wfl++4X/d8WhQ lXhnquC6tgtVP8Ze356/P8721YHN/nz5/vm/GD779PW/X16/Pj7NzJU/Ln+GwUoM1ZWKChIw 8rV0E7cGUCc5BW1ab+zOxop2lkSEr/jy9vw6g31fm1WM5Dn401KxJ8DnsiKgI6MjBvvGkOnj 9yeqmSj9129DSTT19vj2DOrXkJ77S1oq+WtoEcX+Dez6IcDbbro6uBSDp8eIK7XNJ9nRHpLt T72xriTrlJgamtngBlSpEr1aM3E0IhLzk72dCmGxiwQ00rrFSYL9SQWJd2ZcOeezxXK7mv2y f/n+fIE/v067sxc1R6eMZ4nVkK48+hkZA6IoFe2kkyyFiVmqox0varCMDd+eHP1zwq3Kw0Nf kD4JnQ3l0wkUhocwiKPhbBLBhDBddWS8UCYaqTHS1uWpyEASF5S2E5DqBPt4s1iL48zR3ByN VBmJ0Vi9Y7lNmhvH9Jy7McoAUG5pAOAB/wPRiVOwqagHOD9MQYc7lPrqlaKp4T9etUXhhwya 3xi2Pei2PqZ2MOO2eiq6s/6w+vaoiDf2zBtKObNBI143ijyIG9EhJbR+CiJj4Yf3Gki3SCIB 8j1+vn4XX7NLtDnMzvKkVjOt5Xb+8yfRFYsRpGxkWxNwiFIsk7mRiAieGhVme/RUjeyXqcMV gf5ys2G7TPggXkwBYcnrHgyfH51BtV+psMdqBM6oxQ05niHZ5jJtYUCu3kMml3j79aT9OOHm X9Ktrr9PTfUKd1rjbo+280CHrSKqEFgpoA6ZWrD2NirQGaOsXUKQ2m5B3FpHiTVBsqYEY0Qz CUerYplXgsCDU3PmWNbiwV/fDvi9xH/sEX2M6nHFAoHzOVklC/nzSYv8+nDBLlsSd30xEHRG kZOwRmifdRDu4qLQFqHyIL9uxNwXVAynxh/dXDcNGVzy/RGKlRu8DdXX2HH7OIMCAp9nmfrn 2xmUDE6XdWzuq2NJbsEOP5axKsiysiBd2wan/hUGB+6rC7xZLBdUYo37UM5SNJf5lk2VC5Aq I1LK+GjDg7mYwvqlgwusfN+QxXZcppIFE5wXbPgs1571hEf4uVksFl1weDq6JDwbqdKIRXXb w44+jnukrb2exmKG+26BWFY0gpGzCI4kGo5vXCp/3eWRzjZ55DgGROQVABP7UPQcdvt2qsua itYzx3vGg+IGIJjFAvotRyOE+utpt6INtLtUotuelld3RRspuxmbmI04lJE0MWRGD4Yp6BNa 0twHr0xVeOE0KN2yK2JDap9J2VmcJDlb0iPPlR9aZEFdQ0+NAU0P8og+U341t2mh0tJfr5GR TtsOrySjwz+uLu6MT5JUmlMuYspD/5SNHRobyhNaWYSjLIvkWTv8uDzl3HOu7Xhyte/8wTpO xkHSkK6oML6+gJ1bF7wNpzXBqfXlF5VEvEDnliwR6LA6eh06VnSRN+cBbVrxXoJ+BMGOIVL/ 5OHv7nhx4zzEYef9AHSgxwDQn4ojBvZiymSEW7TD1OzYE7YIjjFezendExGRZ/ZyMadqGrjj uEnWvj/6o7zyrSSrz9xPwZBnGQuLlahRsm4XuYzq7hCJqrq7jyWs9N2APrCi9J3LebuCiUt3 BHHRO9sAu34Xqy4TNNEnkdb+tLxTm80qcss0oNYL4E3HLd6pB3i0DfXC8eNylhdXBKqCgYzj V1+xIPpYVZvlJrmy8uC/dVmUfqWHYn9l79sst3N/y0zuIiqv29ZZZMKrGWquVaZNEM6D5V1Q guHYxQQoLOkVE5pshrFJb/d2KBANYdMkGd5zjFPcR+1Stouf8vLg1yj7lLNl29KH/Kc8KjR8 yiNrCBpredFFnyOTgd0enlge5gB8AgBmW10RM7H2RsO9w26zWG5TOoQLUU1J7x/1ZnGzvdZY wRVTpDBSZ94Q1zfz1ZX5XWPWU00yU0zCyewZrJXeya/OR8X5J5qlCBJ9VLpN5kvK0+c95d+B IdQ2UuoUUIvtlTfGAsj1Hv54U1xFIrMBjtG56TUVUkk/k5dXIl3Eegm028UiIt8icnVtW1IN br6e8AcgmKj/4uOcgtrPVXUvOYskWMAE4PRhlmLOWcQGUQjqZlKnEw0/nhpv0zKQK0/5T2Cd MTioWMR029B3Qzj8zv5uixlF9TFW2gOxZ6xIK0j7iMP2Ih4C466BdJd1bEoMBMtroqC6L8oK lCBPsr6kXZsfgn1qPEWyLPKZMN1zFykOLE0dE3SL+CYZVAMxwEMyb8YblGh2jCzqYNAnELpP bcjPQINMDg+FMd41PwRYjNsByUAyvyqxqVTWz+ALQNx+5jzrmlpgoVcknljJ8B4WhMdiAPWl P0fXGG2NDAG02cyXrQ+DgbuFI28C3NwSQHMk928zKj1WXw/7Pq5LAeotC9H9TAFF1j7s+LIq EIRWGwJ4c+sD9/o6SA8k0iqHj+TDtCe4vbD7Lhx8+GC8WcwXizTSw7xtwoesCB55wEihfgf0 5mii1wJWiECJMMKsYPayOY/dp/4J73A1h36EEW7jPhPVgPrVVv6eVzP4yiJVES5n0XCluM+o xUtqYbXARE3qg/FTjrJfRQsditbXMShE5wCFThdEpKzxVjjC7tiFPmEQWfEDUycVPlM3+Wax pvaYEZv4TcPWfbvxNTUEw5+Y+QnRR0X5qnSOa3WEbo9tXDz35ZABeMm8ziPVaCOW8LUJ9h5R 49ly4Wc0ZARw6zs/Bs3nJH3VykX2e8CV3vT2IQLVGxQiqFq5QeoYu+Dd36t/j8lPrjTho0Cl oWOYLV2VtxO23pBUtVByvYoNhN0Z6CPVpeOgWAWfjySsWTSkwSMza/86naIPXpcm4v53SUi5 yCV4uM/YEG10eZGsnWFsxevzjx+z3fevj0+/YyV5ImnJZGaKZDWfyy6WDHxhtI3BKbVDxFaM 4sfpo2jUqYuknwmVEYEiX779/RaNVwkSQfXPIGXUwPZ7vBPCT/c1GAwu8GrfGrC5leXOSz0z GMlAaGgtZkh1esVxfcE71v989IIu7UPlSXHTzPi+HgZTP0+UXSMgU3DIgXbb/mcxT1bv09z/ 5/Zm45N8LO/JXvBzkLs6wQebl/NxJskC3pN3/H5XstqJNe0hsJNW6/VmE8VsKUxzt6N4fQJZ 4nZOIpLFDYXI72hOvvDpgfVk4dRDTcpuVvqutNGQ5eA2qwWVYzSQmDlFdVJulsmSZIuoJZWG 4XBtb5frLfm0TMlLGwd0VS+SBflkwS8NqQQPFGXFCzQaKuKFRlvCBNOUF3Zxw6lH1KmgvxWo uhUne4mJF1TU6PhVZNI15Sk9AoTk0OJMo02UPQmKkB2nbEIjCatAwW/JFkC2f2fJ6dUc3Q9g ISu8nWUclB7SMRBbywOFWGYUNPPkxgGeljvSwTgQHPbJHfnkoSZFTA/fufUKRswJr+ySbhD6 gNPiCPPrJQ9IJTJ+wcpQVHrEQNVI91qQkbO2rkYRNnc/gkzcco8DEmSeWviXrQ84yQ7ahk9+ +/GNsKJ8WVNeFZ9mx9x4uRGHt6K6Br1xFC4igx8E5uHIi+OJkb1maj0n61YMFHi2mHqY06fb ilFWVzOXdYF177saiBbY4Q1TRq9Dl0pUMTHMoTo0KW1tdWiOrLgEhguK7G4HP64RWTWIeHFL pHgtQMe8MJDhPdnWDgzuT+YwjwsGwrc3GijLbhcr2q5oCXS0EtbtqFDtjLLX6gfuYrovoSy0 k8xE8vvCwrKdT66j6YWndrNN1l1ZBNuuRaeL5e1m2VWX2jwff20Jh+q0aVYxrzqDgR6qhE1h aFXivPKrizrIRuSNPfHfGUhNmnGsrEenbhmyi1DoP+p2TRGRfu1w50xNiAISoesyNP7tAIO0 BZtCYQneaeiubT5S/oVeKL7g5Tn+xQ8Gdc8nmpGHT+Vivp0+VvPDKcfreuyMiz5f8+Y0fn9i TVTqZp0sNvQcCYhP+p/4a7JcwnC7rfn4dL9Z364m4It8f+bUJV6xivlIV2ZFxrbztV0N0V4i 0c1yWDL+tAIhcNF2066zrM2Xq5baGTQC80SiLQqJWXWnkGcq2XLulwr3ECHPgAqOaFiemOMM /9sxstya0b3K1G4fsE3VbPLSWX1ObuZtv3eR6Jv1++jbKbqWYhUE92uQX2oEIUruAsjeTQTr IXp7LwN4ktl8nZDerfxkIUkIWc4nEO/YMLC1FxGrNbXj4/cnnf4jfitnqEN7aYFeL4kkxoBC /+zEZr5KQiD87Sd+GXDabJL0djEP4VUqKjVhkosdAa3ZJQTZgEaCGEDSlEH1H6hTippVVIO6 qj2rlCOonoKRODDJ/fftIV2hQIMl4PmKAHJ5WszvFgRmLzc6xdHYav56/P74xxteFBDmdjaN d5yeqU0Pi4FvYeNs7p1Zby/XiwHtjc/J2rkK1UotRVmYUkt1pJRw+VDGIi66g6J1H118B8R5 8oTJ+Nm7VRd+3xmArd/w/eXxdeqosf3V15am7lZpEZtkPSeB0EBVc11NZ1rsxaUzibvhAGnU HvUW6mVcojTMkfE6IVmkVddA6iJshBqBKerupOv4rChsDZ9aSD6QkC/E24aDokV/c+/NVcSV 7L4bnazgdapJNhvKMOYS5d7dhC5Giiz2aWTZRrLaDBGmgttqAZMNtfj65QMyAYiedDqQnshh taxwRPOgIoJP4R88DtCZHCHXj5FFZNEqTYs24gXqKRY3Qt1Ggm8sEUyJHa+zmHfdUtm9+GPD DmExyAjpNTKMXrpGY11glbpKyepIXIdB1xUdrWbRMJdhjl1rA37B0sPrTcVBpGUeqYtmqSUv uofFch2fE2jL3fluNAeTNnWO+340BBrLzFY17D+0YmxT1+z0ogW3SgrUiLOcNKwcL0SO4QA0 18eIUkbiRkZC7YS6QsMkZUAY8Qdeuld0joizG/Xvgv2sE6fb/s1UE8/VKG0ttzeUjRGvSRBB JL0qi/uKPgzlhZF3G9rqSL49uko3t8ubn2GxS5X2kHHoKjKQGb7mwdymHdww2qQH++ouQKhg Z7LQKRmIyYOzkkAJgBTcPX1dbHE6l4G6h2h4L8p4kh6mblEE9m3QqwEI0jpis0lRZMLLvuqy pTSxvq+qWS4fqmQ1fYseE1bKgJmtr/yjxZmwNgjsZ/l9cKmTcbWAajV1fyXh1cA4lv1tp47i A1BtcoYBKn2wqewVwPAeV88lBkATrWMCY/5+fXv59vr8EwRR7JcuGUWcfXpG1DujE+v69bwg I+It/2BS99C8SVfL+c0UUaVsu14tYoifU4SJHPI6qIOK8jatIuWZkMYW54xcpYYUoBGeBr8r jgl7/d+v31/e/vr8w/tccPbhvYHBgCOwSvcUkLlMBy0Oqx6MA24vFJtBJwAev+LM/zC5WKzJ w2fA3izDHgGwXYYjCDvz7fomxsgkgIXPgPJIVnVBlPLz4AxMklYcQFVCtKuQ3t6eGf2gSoB2 to29PGBvXE3bwrY3rQ/zThYLqHQspim/gfe1R0ZfpZIogYFr/J8fb8+fZ79jaVFb1u+Xz/BF X/+ZPX/+/fnp6flp9pul+gAyKNb7+zXknmK0XFiczMFnXIlDoeMy/M09QFK1skKSSJh+QLZj 96DZCfqQR1p+SOaxT8wlPyd+J8PDDmF3XL63iEvtkozNopS5b+tiWjYB+JoXAuu7ZRv2RwnZ 8IhBDNBGdJ1MAv4T9PsvoFEAzW9mRT8+PX57o24H1IMsSoz/OLlHge6mqTLV5WjJCbtWl7uy 2Z8eHrpSiUjiDZA1DP2b54iXEgnE/1N2HU1240j6r9Rx9jCz9GYj+sBH8x676ETgmdKFUVNd UleMpFKUWhG9/36RAA1MgqU9yLz8kvAmAaTpHnRtEWU+sGVzef3ntev/+lNsGnPVpHFuDGLx uDqZPq5V+SjLD9pU1e2SV+Ls7mdnwILfHqs5zMYCa/M7LNomvgmCA6bDQwbVXOVEzOVhGAi2 yw6DKS0A7TP443786/XN3CrocPf05fXpPzpQcn/vd0LX9A40WjpbsLa/Xlluz3esO9nw/OMF vPqyMctT/fEvpXh0mNwwSUTgYzjUIdWH6awo67KjtyoMCJ+fwsWZ+hF4IVN9IooO0JcIngJE HESdUAM4e6LWMuVaFM4m/AgPfl8fv39nSzFfZI15yb+Lg9ttcUmtFkKcf9HRIfC2GLC1UDw1 XUXUNPUTuPGxfVFR+MdxHeOrxfU2dsuh8I1IZ9TqNs1pzUN3437BbCmxM+9H14uND9ve4oRm 6bVclmc58XJLwtBIyLKqDmyU/3PuM7gC3+m3KnaT5GYkXNMktpYPaQpG8zXTjnWT57k///2d zTBt4Ztd23K9KFtuWSG7CZTGqINRvRtOVT0cCu0mEJt9s+ozXXf3pzPBWxl2TyceU4c69xJ3 9frWVsW7zSCeqG0pCn9+RmHFk5q9nKaUoAzgwU8D3xyerM3iyMNNNkT1+VOiLdkxD2mY+Fp7 L9pLSjutl206AO+eThJhZM9NMHLq6iNiJnsaWbwiGrVm5DQNzLnERD6j67T1a5b5ZeqBCj1u pV2bqe5PxjA0ZxN3yQmWHhbf4aKVi9z3LNZUosF7MHto1Msu8XTAduXXN3xyKgXOB88nTrIM Y5B9dj9QRKC1NFfcIYCIS55dLAGQOcpkWPReZ41pPshu/WWq7sxmAOOQOd7cdhk1K2hwAMlm fnAWTsO2tGaykRwPJmGktcKHjLKtkJWMeLHFDaXCgjebwoIf+hYWeNNDarXA5CAHXDtlI9gG CaKR1OGDF9vMVtcSscXIx+wdJAZFgWahs25wYyewI4rux1LSmgyAIfktHLx75bfqBWiGJFb3 5QWxOrne0gTnCXgHS/m6QRhjO+jCUpSUh7kQvFEYmYVkTR644c0CpA4OeGGMA7EfokCYYEmx A4sfICnNK3CMjZFjdj6WcIHlpQF237HwjTR0fKRXRpoGoVTIxXWC/JMtMcraIojzUeakamKK p6vHv5jcgx27Vp+zh5qej+cRs900eKRir1gRB65yKaMgmGSzMbSuo2oeqxD+XCJzRFiBAEit qaKGxxJH6gUOliqNb64FCOyAawEizwLEtqRkB7crQHImqiB53CfgLwehuw4O8HDPwmO/2Wzc XHSv1chQyqryK53eBqRwBYkwz8ng2BirSwFmgES10V8xuwS4sNThPXh52+WBc4AT4pcjMk/i VZhZ18YS+nFIzCosuo5ZgTZwxQ4Qre2RXbAcm9BNCHZqkzg8R3bFvQJx5GRYtgzAHJCsMD8h aab7M3aqT5GL7nZbs4cO0slw4YKPQDh0mdTf8wCZKUzKGF0PG0QQ1Cg7lgjAF2ZkDnEgxZKi OduBkAEJgOeGWLtwyLM9L0s8wf6g5TzRXvsKDnTxhE01cqK91ZOzuOgiyaEID/Aj86TxeyxR 5GNqpwqHKtwoEGo8qnCkyIBhgO/GWH8yed63bDc0j9Co8OunZVd57qHNTYdGa3+0EWags8Ex snkyKjYi2xipGKMmeMbJ7jhpE9/y2TtDsEUvQTYYnTNs+0SpljKkoefjHtEUngA/DKg8e+Nd PKUjBQYg8JDm7mg+gU/AtiZUNe5YOXLK5slepwNHjPUwA9gZCB36AKXOfpvw+5cUk2OG+W1S /wAngzzkxfhC1nqhE+EHcGXljPdXCsbjJ+67S5ETBehU9pwYW4FhkgcBJqfBoSdK0InChPeA Hab2F+dzXqS4awyZw8O2to9N5GJ0UCGvss4EyIniuwgDvD0pleH+32h6Obq8IU+gpiTVlm7s 7834kkkxgYNOZAZ5TLLezYDxRFebo+u1pC3Jg7jdrfzMgi00Ajv4aYw2Q34Ko9vNHkBqZaSU iHGHFLCNov2WZEKe6yVF8s7Zh7iOi4n0BYkTL0EA1n4JJh/XXeY5KU5XrRElxPd2RxjNY2RC 0lObh8gIp+3g4qsZR/aWSM6A1JbRlXgvMh1rBHDUkw9nXLRkYJREqAx8oS4eonljSDwfyfCa MIneLbA0AUpd7N5Z4fCQExMH0CnGkb11lDE0cRJSZJ0XUKS59drAyItPmNtRlaU8VUjSy3Xy rhrEOoZBb8l+RbidG+8d18UWYb4jZ7LamSCA3sB4LDtQZIfk+wpCNzfZw9RKkc4WZu1qZSGr Aa0WKkQ3Aws+8B+ERt1YGIuyys4NnY79Bfy+DGAHVmIpyoxVVo8iTC2urIZ8wmMIc3PQX/5k vmwW4WItmqrLd/ZSIYy79QQGcAw16d6hUM5frNavVgdCDM/f4Dh/ot7j2IYWWLPVFlXD5blo N6kP/Vh/2OXghl/eLotwsAQGUwUlGOc2BRmrHzg3eLJ/+6qYScipAcsv5Ai62XtcVwiuWfTo xQgYxvaE1IdmC0rz+u3l6ccdefny8vT67e7w+PSf718e1ehHBFUzOeRtZiTHPZ08vX69+/H9 +enl08vTHbj0315m4CPpZh2S4GF54JVJSmu7zpU58Av/lYP0uMoP55gj9eymMvOAE7cpbzGR RGHTtBwEprsa2tQ2P/389sRDMFsjm1aFphTGKcZjK1CznCZpEGJPtBwmfixfdi40TxELhrbO xZM36uuQf5RRL4nNWFwc4wbKVVPecD9IG8+pyWXzfwBYa4WpowWmhQ9ug+fYbCR5ewjlJK2R Zo0lRS2XV4+/Axm58ItKbycXcZOpZiIWBSwp9K5hBl01+hynNh0aXbkq+NXkTX6slYhq7QA4 1RETv3hFpacJCipopM59lca+HppCL4tYVD6cs/F+Ve9DygYGebVshQ4EXV10XRGhQJYKCqbZ aAgpCSBcMHn3+1kVUEnj96z7yKZuX6CVAA6hhKB/lyRDm+AuGFfUmIOcHDmY4gXvtfnhTevL eYPCqEmkZyHoKX6UWxmSYJchSR3sILminlEzTrbcKG64Jeo44DTyU2uey+2d2gTKc71EB6t0 vXxDXoVs0tlrjegjyCglNy3qMKeqL4Erp+KEhFN1nRJOvE+cRC/o2IU0cu0NRcp8xwc4MNRB HN1sjsA5Rxs6rp4vJ9rmMme4f0jY6DRWMziyo4XJDrfQcXYLMuvUCLGCti9Pb6/PX56f/nqb RQzAeVg/7qjL9FrFGcxFTldBAxqFkO++HzKBieSZvresqkQKLYkTo39YOk2LvbXyUcYVixRR eiCR64SWMDdcTQg/J3Eo1pZ1Sa9ILRSnoz6UV1h79V7qwirp20a9pK9kZpdEu58p+kwS1cOp uiXOjLEV1scvnOi1CRzfHF4yAzjS3ht/18b1Yh+RoJrWD/WJrSh7qeXM/TBJ8S7meGudVIte pCzOCE06lGgO9ZwEcSObOPF6taG4ztForiFXcK0x27LLQaPzGTWw7nvrbYJBwzoYkNDwRKGX QKrc6phETmnzVmLz2rlxCFe4l76hyhvjxgCWhmdhHUrObWnJCI66/KS78u3mCqJ3EoVYflkR +mmCIh37Z0ARIWGj0DxOmqJ393AmbYGeGcqiHQRURD0ObNginO+2wypZo4iqIKxiEX7przB5 Lq6UpjHhy4k0RLKOnZ5C7KZuY1JVrCV/OVy8xpCaNKnvWKrIwMiLXexstjHBHhW7eAIcw04I MksSe2jjA2JrfLEJ7ics1j80ZQZFcYRBkqyLZAso22F285XkYjyFJAqw52uNJ0In0ibm4lBo mQccjHExUy/6r9QvkddxCZvPd5oHHAWPZXlThZIUT5UJ4fjUXwUbE6nOH0vl2UzCLkniRJYO 4iD68q3xpHja1xZPl0f/ABOdd/pgFsl3818kdBPQJP8NkcRkA2MCTehGvg2LPB8fjEK889D8 TEFRxxJ0/nHMtZdFlxcNFD+iaGwpKtwaTGgpLuAzAQN0IUNBhLywiRngQ5rrVGuOF/iZ4/j2 +P1POGkgplrZETNxEZcJR6pY6V2OGdhOow0CGLnWNIfwhJgYWMhGjOwH25uHeirkyJtALYYp O99Mc2+Ocf3RtsWp7MjYVKDbrcL3LZltpU16dUCh6gCuLNbrdAzsL+XI7/V/Y2uCdDvOGCAo 9cS6o1gdjeOtMVGq1eRYthO/s7UUV8FWw53nb0+vfzy/ganAn89fvrP/gf2tdHqEz4UJfew4 yplqQUjduKjXiIWhuw0TZWJFmtzUYo1ZUeotJGhceByoVo2sLY7DWS+DoE4Wf+QSR17jbkMk ljlbS2VmpmM2UjFwqtVCPsuHu39kP/94eb3LX4e316fnHz9e3/6L/fj26eXzz7dHuKKWZ86c HtzJWQvV9edLmWHnaN60qapXsdCmrBlO6HQ2WcEN5nksp3IcLS9MKyvSNLw+f7x9/e8XxnBX PP/75+fPL98+69Xkn1+NLHQOzZhjpZPrVEHwz3mu9offy1x+/90Y0SnMoaa/Tk15YasSd8fF LfoI2ngik8uhybr7qbyw0Wgp8+VYajPw0l6P1U1PVVDZzM8tb2t88rZZiJ4XATwXjTHmCWYx wxfGY3ZUFHeAmNfjeCbTB7YqabMtz5jEf51ORastpR9uRqaHPj9hT8O8lsL1jpieEn2YvZfy MVG8/Pj+5fF/74bHb89ftDWGM07NpTC6RSCkbofG1heC5feiZsK0Eztt6YSO3gaCh/2dkb6r 8+lyublO5fhBpzqAlLIUnr0nEpX+KcMPVyh3kmX4KUviZlvUMDUfXMcdXXJDfUcY3MQJfOo2 pawywjtmrItjqbfydiV4eHv54/Oz1uDCqXZ9Y/+56QFJ+M54bg98Yy7QGHF8s2K9tfgE1bZn cLd3qgfQMiqGG0jhx3I6JKFz8afqqjLD/jDQzg8ipCNgP5gGkkQWlTbgYjsQ+1MnEfreJjjq 1PG07Yf25FQfMnE1FUexhtYTrQbF6GHZ0LLiEoeqCxANYmKILY6mwom6u+etj83JmThlp4PI wOizmaH2iFkCue/HfDhqM5VHnGLtIT8g8K68EYNQHfS26h4K1asGHx/c6aJt8NSHzdcWH7jV 2+PX57t///z0iYkhhe4PslJsxNcwLCArITkw4SxvIU6vdPJjtK6ndfWgkAr5mpv9PvQ9RCQj 6w6qoDn7U9VNM5a5CeT98MDKlBlADR7SD02tCMQzNkKkjPpWNqCxNh0eUJd6jI88EDxnANCc AbDlPIz9pWYz61hS+Hnu2mwYSrhDLbELFqg1O0XXx47Nd3ZY6LTkDj09zQj+9aE+4l+yotGm 3P2W17wfiNptZcUkClZi+Y4JmNmSpcUVY9Q2g9dL1FkKFC7L7xevItI37INZYlazpnXDmxT8 0aNj98/Fq5GhiwB9zvdiJcGh9fTfrKurfiogzFHXGWPt4VCOnrLDydR5SMv1t/kKBIitnqzp cUGRj11CrSBrbBe7oAGITSGtFF2AKiHCQeqoDl0k4Ab0rVtoz/iQqBladiFa3TdvHLbb8I1D HhxyAmN9scyUOg7UnmnKxAlVuwbor2xk0xncAHeoCxE+bOnYq9UVJHb+Bd9jSuR2CYQYBR/O JYYdMaLyYiKlk11Kfb6K8xle3Iw+uJ5eTUHcmtH6qVKCDBz1UoO0+Pdo8sLMZjpiN+szhs9x 4ms/je2AZBfxCiJnJoh7w2vmyPIc9fQDHLU2uGsy+aooulBRywKYYrU6a0A9uKhhg4D1Pa+I gd5m93j1gU16rcm7smebRa1W//5BDcXKSH5RWdr50vdFL7+pAI0ysUxtZcrE1bLTOne8/01d AtVv2GRp9c18pjFpImvhqKYcWBQwPxNq8ZLE0uGONi2dNGsByBSSn9VTHuyfBa41CKvBgR3v bjTAz3e8X/hrmjoBsdjcQD+w1rSY6MNGBtHzyKlE/SlAK5/76d5NHXVJWagOStWqz49hKomw VdmJtVaK5fvKdfLBxDXlKiDmTUbIFpR1rRVgO958tpRtCWwc8+Kxm8r6qI18b12wEd7hig+3 jUO88+0WBlEj2kBuy7z7+dAmaeBOVxHgC0mCZOxciW1iG4t+jSzlXwxJop7YNDC2+b9YucQb 7XsdEvlOho4lgFIUGZIwREu96quYjWG8SWwY7hFhrQZ/DH6nrhalIalkl9Bz4mbA8zgUkevg mmNSQcb8lnfY5szkNEJF9JOFwtbgHhdx54PnNgX7I1Z00p872bgDfk49IYZSq4pM4IC+yWrU yltJsCt0j75AGvLWIExlU5jEusxTOWIB0Is2K7sjbAxGOmN2beuiVom/Z3JEsoWyBN5QAw8C Skomd3U5qutARCvA04CaZMuOfyNAZh16VaFTIrNV8cwqgh1pFq6l9ZTPi4cuAw1etjv2o+3r eYme+oYdCYfaKAKTLqbK4g6Q4RdQOYTgvnZf3bwoFuF77qiJHA/nSs977iZoaWvC/dD4/ILh HabgXSZyyK7lLscc6WKXZy+GqOgs0zniqfgnf0+QFPkY5wlcHEGM1qaHl5eP5W9RoKZlC3UK WMWEQ4gIbOv1PldHICgdLyK3PnPUZupz7DVD4hAa60YOkkfV2iNWTGQ5W1bkd+Kh5dPrGzt3 Pz//eHr88nyXD+cfi9vH/PXr19dvEuvrd3h/+YF88j9q+xI+sBu2po9IWwBCstoCEBswFLUx jBeQnZJR95kzS93e4CZP+KpWEoA7vlMdeS7ohtmHlkgEN0xacf5ee7iBUBJ7bgqCR5r4YZzB xQku6pjfjtRLk1/+4IHmXEMgCpz//zeh+6vfkPuGx9uIjA809huthmOmDsKPt4kWrdmp/PoW /s9Xxvm5qyhz1ChwmR15Gk+Cy16IrMjObqzqHatY5Fo0AWW22JEVYlbkPgjVeNMSErkWu2aJ JUD9qKwMoa/q3K5Ik4fsCLjz7YFJX3I474WeEz9sfKQqAvCx3ASEurlQOEIs1cBrAjQ7BigW +iqg3p+ooIcXEiDs4kzhUJxpSEBkKXzs2DKL3xs2wHS7JXi6DNA1UyXYRxXINobQb2Tf4wtQ 1L3nekhN+AsGnykmVpLY9QOMnvgeUnpBx/vnSNsIn2p11/XgANvxLa4hZj6+TIY2NxYyU+pZ /MjITLgnnIWDsNOcG01Xdh5e4+Ga6UhcELKFZqif6Zmb7apulCDjGoA4vVkB22hgsM9SNC5e TbbQ9f5GkwcA76+xiVQb9YXONgQ3wuk+2r+AxLHNcfXMRI60UV+RV6Q+tlkhR1HTEbwCpB4r 8Sy3Dm+jaFxW2CsVab0IW91nwJIzaYNQfuBcAZop/nRleohVnTLBOyMmQDPihSFSLgphdhOk ewCIXSRvDnhI5rTK0iROEaC5+J6T1bmHLJgSiDfOyuBrYa1NBjRo18JF/Mzz4tLM4NomoYvU B+geuokBgvs72hgU/XOZjq2DQMfmDqfHliLENodEEgvuvkpmQLoE6DEyJBg9cZDVXdDx3gNt RgfPI43Q/ZAjFv84Eku8J0NwBryd2Y5g0rvsnIQBMgYASLDBwQEPFdfokIFbuswqjvE7Wriu ZKdBWjfGDYLEsJ8Eyc+cS0/gpmpli/NqXZjxfE6aJ8+62DzT0pGdJykuxDNGds5HCncWKUrp bT7uxfEQDOQfv/DiGM+vwJ8FtFQNbDk1z888IDSSp8DH803NmJOmqtKow6AaP63EGlew4zix xFbg4BnO+1b4UDb3NXbnJ0DaD0YZQc12fNBpNfulE/uRHU9HlTiMfVFDWGaNl2sRa7TBc11P b438YRhLgl09Aco6/th3o+ZtY6Oy2ljbogS1XGz75GBTihBmCq3XCB+VmMRigLWHejTG8bFC HyQAOvUNLaVrQ/FbdIOaBo0SH41DV4NJ9YMWopxTH4zRdc5BkQsTuAC9Zo1iIsXzfRg15WSg 1nlWGInTa92dUM0MUcaO1GwW60k1+eI4WyaWhU7o+ovWAVCVeYIiVPgxKFfkK4L2O6DjuT00 5ZAVntYDAB7TwLF/ej2VoJdjdhx/KG37M8Gu0gTDQ9VkxFhn2hp8KvQVrlHBOfqOrY9o9GwO nxtaL+NC+bCjuAa0wMYavwMCtB+1gK4K+n+VPWlzG7eSf4WVT0nVJhElUaJ2yx/mwHAQzaU5 SEpfphSZsVW2JS1J1Yv//aIbmBkcDdpb9fJkdvfgRqPR6KMKCgiMkpXkaYEUrMgxqa7JJ5i4 fdwXFtesII1k5OwmBe4TKiSKTkCaY+gE4r8fFCHWocW7qkz0sQazUBtRc3E1M2F1GUWB1VfB Jc0djzA0CLXbCXkTvWONIYbtbPQmRQtLUpx4zH9iiGqrrPMx2Fo3K0RuUDNWBI3OvEeQc3Y0 eVC3f5X3UIEhFmjwUyy65WvqMQlRZdUw5iyNNhUcxsdq27TumjYPxLDomR81qNODDkSLvtJN PySfdE6HDed5qT+aAXDLxWI3QQ+sLu3xGGD+8+jhPhYihBlnFUcY44P1aUfr8VEkyIgUSaD4 J4UwgegdsakyJTNFE7O1Uy7m6TPKHb/CVIKk/SWUV6YRN+37piYA3rEDAKAMW2jCMIF7GjR9 GsUGxiQzQk/gd0Uh2FLE+oJtlGXA6LCRPx+edl8hJNPr+wHHTr0R6P2DQoYIY/BGykmze6Qy XtXMZpTtyh5qAeo3qeAZmb9IoAkzZHdNC8vBKbVP9EjYAATWBvY1K4i1LwDu+DqDu3HGcYPz EAaJBzx6akzLDjI0RlOGRicGBX56db09O3PmsN/CMqGhzoxKKJHED5BMFeQbz213Pj9LK1WX 8SnkmZhfbU98DRQXV+duQxMxEfAIQ5RaEg0yCLrTLW6y5Xzu1jiCRaNKu856GVxdLW6uTxS7 IQc83QQEMIqH2GImqxBwzISSW6ZT45KQ9tuz6OvjgUyIh/szoo1kcDPD07EngiJ2IvZ/2+aR 06ZCMPL/nuHwtaW4TLDZx93b7uXjYQYPhVHDZ3+/H2dhdouZqJt49u3x+/Cc+Pj18Dr7ezd7 2e0+7j7+zwzyxOklpbuvb/i0+O11v5s9v/zzOnwJI8G/PYJXlIpPZm2KPI6Wuo5RwHhleSxL 2JqatQnew1ZvPiwJZCEOEyHYzI1BEkiI7uYbQ4F2XueNMc5xGcQeu2JkiZuIevRRqHNzoQEE GzSwldXjx0+745/x++PX3wVX2Ymx/bib7Xf/+/6830mGLUmGcwkS+Ik52mHGv48OF4fyfVHq RgKfQcJIAN5jt4LJNw0DSS6xOD2mq7k6I4Hu5hoREGWvLqdof9A57JJn38iU6eS2M481RwGC bDLnV9boC5CeZAT3Zty15qOzrHndMN8I1bxcmAas8khala0n9xLiXb6pFATi73VExoCTRBiu 0eHksXMtM/BJG3Nx7Q9oXzzsOShrYjE5WUBdwrDN1ky2YBIo5IuwVnFX9AaVm6AWQ1PbLQX+ 6SmfpQ1rJYNN+BY8NO2VAzcg9KMyirwXlLRxKJb6gAOwpfSGuJu7EP6eL+ZbSyJIGyHaiH9c LHRVq465vNIVtzhG4hbTiyGEhEKGUyZOXhqUjdS0TE2MGuo9BqekteQcvCdZ2hEsdwtaOXtY OhasMiYK8RS/Ff8nqxj3UfX5++H56fHrLHv8TiWqxSMqNdpflJUsLWJ87alJZlAzwtS3Qbou lTA7ljUCJXMI7wcx9JR0Yj5mYnVBvGKuRz928PU/6GX1FTr2HVOjtt/fdr+TRgxKtOxtLYI+ xlnFe6Nj3SY0foCEYQJAEDGaLGB8frk8I0OHGZHt8shJ/rapG3YnWJmZ3keBXffR6eYKD3Jd UFNjC/Wo1StvDXn0ZxP/CZ/8WOiFj5vY6uMI9J5GE4UvXuNURNYmuTkqElEm4tIUNPqNy0S2 N3MKBRrAImIUKoG/F2d2XzZhQ8mZOHA8ycVH9hdReO0JQgRY8FJo4jwno10BvguNvKAA65o0 siFxyq/EmWpRgiYdVLFmlEINYe1D7IZyE7XmS6PI21t6iresIH1lcpY3LdctSweIebeSqXmb 4/PTFyKu7fBJVzRBwiCPYpcz6tMfr9ShKJyy3IwhOuD+Qt1l0V8syZh2A1m90OPmTGBj5N3S tQkgSocLvKm2w5su2vwbKt0R2qP6ldLrAklYwwFagJCRbuA0KlZsTOktKNzRlp9F+ZVhZzJB FzYUPQnOnMZJBwNfu8CkXbdAQmDB2ksj0yhCN3VQWSCZ1vbcqVPB/YkPkeo0FoM/Uk+iI3Zh tzurFosxEYU7EBAfmX5gnvD+gRLYK7fCpRW0cwBb4bkcvGV7Y68ntoaMuZyypZkGeLElB/6K tBqQUyiD/oFlfmcvbTsMnCzPjOeEsDGwj3etx+dGgCwEKuvI5vL8jFij7cXCExwX8Spwlq/C Ngog2pJTbJtFi5u5x3tp3ByLf33llq0R2EI2RYt6a5bFm4t5kl3Mb7zDryhk+hBr5+N1/u+v zy9ffp3/hgJTvQoRLwp7h7y41Evz7NdJYf2bLkDJiQCRmJJBETvGYzU/grAr/gEreHS9DN2c 3NDQdv/86ZPLw5R20GWbg9oQvQa8c6uISsE707K1ZmPA5m3swaRMCFohC3xfks87BkVUdf7x GIhO87KBalDtmmc0DuDz2xH0CIfZUY7iNO3F7vjP89cjRErC2D6zX2Gwj4/7T7vjb/RY4/2w 4YbPo9mnQAx54O1yFRTcEz44ihhE90dvTmLOWBxEQtgrQTXdiJuRJpEjalLBj0UyOt5H3Ua9 9KvXAJAr6Wo5X/aWxz3g8BQmCorzYFLFOzAnCtCEWRuikUC4MSLAaUQ6KRglTAFLxUFfsMys GcVsE1Jqqm800o/19AqSd3IB0/N5QQKJ2NSUQjRcgBGjgAH4Uiijz1e5ti4mhNakDZQSOY5V Ck4NsvrCkHPTplMtHEcw+vq8ezlqIxg094UQebe92YA8sAIrjQPd1wGPtSLDLtFeUoYrFhSa cN1xtNkgdAIE3VYpXSYYBHLLdLVZGl9eXi+NE4vn0OqIc/vld3oxa+dXt56o5h3plQfrZXDa mSqXMY6Gvq6f96KXrqCoIiFZcu4E9UdFUTQhOPforzQKjj5nRJm5FTlZPW897V8Pr/8cZ6m4 1e9/X88+ve8OR+oRL72vWL2mRw5REAy8Aj03YSvWBituvnGL9cti+mYLgR0gwUEceUJh1cvr +Tl1+ZcuxQvbO367cv2mxLH8+OX9DbjzAfTGh7fd7umz4ZIhGy3DHjrfBy8f96/PH6kPMIw+ 3TPlWEWoZqfduipoJr4Sl5VqFUDgGaLrUnwW7PS232bFFv6xeTCi+Zf6zoRfNp8IeN5H1tOu hhL3i02p+98D0PLuTOO8j3lu2nLFucfQGzDGs+Jtc32mWzmuanYfmg/mCtSzhtJPDlgn7NGA gNGryXwpA4XxBD4ArZAQI7hcUcCyCg1/0AFjGTsN4DrYuEBXSzx2AcN4xUqvaCHttDgD3BeD Ymza5tSYNJ7R9KjDRrQ+t1F9X7UlPptFUc00Ho8/xd6AMGCuoCGxgudj3rGoTFktJCR5/nrM G/5fSstWMC9xlEUVNQDb5dX4jqyZBmiCFavTmDZjAWvNPgtEpylnR5XIO+SlLmYAUH5iHOCS tlxaSVJMgjpsaXaZdH/xVhzqblscEkzuRr/2BTmHoAbJLc88VqaVG8dERwLjyyyDzknB0/BT 7avGeHwniDBmSXaKAoyqTuF5zIIqiE+RwK3tFmg8WtcxKXgcVMZSkeKguIhm5ca/Xk4OEmYM 3HiiMYNZVBvUJ9uuVJRhe2oeB6o0qE40I8ormqPIfkZpi1nVLhJamy6p0JR2LbbzCZq1b1kr +ZpMQ6iSteWR9UYOUVbq1ogAsy3np0ZDoBc9E8fGLTXZKpiju2VlA8rgVtzpOF3y8PGdR82N D4z9Ku9oTYisofa8zSvFDVjbRTI0GL2v1v5L4zSG3DPVTVcnkLihqsuLPuza1iOvDXQUkVlZ V/AWqtMElUzIMlUW6+Y8Q+NzeWnVLwLibGcjaWNjymaaKhtRgZmGfiqppGZOlOgBkenNHIBi KFrjqETEbYjmpCejWwmBDc5GIT3cdroddrBmKNVVNasCo4GjxDfcNZQ/e/T19emLDDX3n9f9 l+nOocmIdsAWDaVlw3KRVhR3DdPwxYXu/Gqi5oaLiokjQ7toJFEcseszuj2As2Lf6NgGA915 YidrhMX2hyQybP/pllqKVx2zDX5YAY8uKJlWI1lHi2Gu0yF4YPP2/IITPsk2cjEgsHl931PZ DkVpTS129vJc97wSULZuCWgoNuAAnRgUxmqoOM1amlSqCMVJ8QOCvO08flYDRZvTyjymgpeA wyEtVgjmG5YeBirGtfOGs693316Pu7f965M7eDUDe1+IbjLMRv327fDJngHIiPlr8/1w3H2b lWJbfn5++23KzBmbxGPqTohGYRX0/Ee+teAaby22vG/qgAyUA25gZlgWAXlo6TO5QhE3qc0I JcNQb+EgGfrL/j1CvlJlvec8FEpiN/2SgtuXFAVWBzrkYr2hPaoV4ZDvxNtMoLi40LNBKbid e0OBxzwXYLMVEU2rW8hEQmnoFEGTLxb664kCD8YcepG5WD01bdvPPerooqVeO9fiqJO3Y6lp ypkK4exOCJBGwc082urPhgBtGzClMGFJcMuMUl8Fs9EKnVRLOQf66+XZwtlA8KFvfcBH8GJh VivGSWuc5KXTD3j50A3pAKTlN3XpnVSlAAQ1bdJalHbGOglrGhdi6+smuD/2HNDgC5/u8Ykd Uin7hsmv7yAWtqZfgYjvHL3++6LWDTN5BfaFIem7UTMwChM/2rrMMjvrFuCCNr2+IdeZxIes zrhH84YEPN/ScQokWghG86Xn/U5S5KzxqfYQX3FxlRGDQe8GSSM4GajDTlG0+YUv1xXigXUS IwjO6/jKJuncAXy4L+ggThLdslUtLllVTt37E/MNUvzE7Uar3QDb1nzNjbiPYE5T85b1DM6g 3MRM4iruwiq9nzXvfx/wFJo24BCtydAhiR8gp/TnyyJHiz0PCoz/JlQY5f0t5EEDsFvgcMtR H007R+DY9r4om0swiwc0fShNdNv5+c/QLc4XPygP2b00S/wZGk7pLoGmFfj5uZkJEHV8UUBN fR7pmUyj0DFyEaCscm3Sq93+n9f9t8eXJzBvfnk+vu5d751aP9batCtiCK6WjSZphL46KOK6 5LSmOg6o9/BCsGk90FFrRvhqMR1ATj1aAK4pu1ql+SuNN54Jp7/7GuUqfIJ5Obz3x1az8xwg 9iiPcJ9T+UjQ/IhArOzTBFVL8ZcRbbxUIjMz8sCIjWtNMtAY3ANiUdVsxelQy4Adkz4Mk561 rIbgcL3jQOCg8FQzdCVcHAxboIhZVHZVxtxEL0nD3dWZNGMIrOR5/w0vLq7UGGuad/GjL02P 2jGYv1iEObnDlB5UT1kQxWFgPORyXb8PMYQsuQJBUVBgJDB4uSzEQcASLth0lim9/jTT4BLS 8zABC+yCzDCw6aNkNVYydUaDDzkIaA19Wa4yRuZ5mqRU0TxQHlQBLLqgboh5aXef9o+zf4bR l1eJ4YaRPMMTGB4S+jt5JIaA9ZuyjpUJgXbWwHNGA3lBIu1sYlu4TCWNC+nDrBQyixmfn4uO Adh6G8wFZ4K3j3uDghpczCsCDwuGl3rSjAkcJoYmQeR2RMwgkE4zFLifjMi7rmxp2QMxUUvr /IKuLZPm0hcUM+kgcAEl1UEusCwQA2IsogkquIAK6R1zd+6jx6fPRpKMBmdWHzE51WBj1rjg VMhjpRBqDHY/IP0OQAOFzMXU206M8nA77N4/vop1+XXnrD8VP9Q4XgF0601UjGgQ3jzjj3h4 pAYHR05bwyGN2PpZXDNtUd2yutAXtsU2hCxvthQB0x6h5Eyk2AatnsAs7VaszUK9aAXCdutK MPgjCtBJ4fqKm0a0rmW6ArSswXh1IJ84B+4e33r8K0macx+yCzkWR91BytxqmIQA+wQ16L1p +iWRcG3XobZCVv7uHyAWKzz11Mw06lX47KEc0fQaGOguf4pOiSvUQpEEVd6siHa4oopNQets 1DM7PYtFVBnDKn7DIoNhbSGsWGFxUonnpdgPFBu16BoIbnCKoID/6NGSBKVYLmSsYVVBLs7Q uGzcJhbZqWLZVgwmWaxupCV+DLZ6H355Prwul4ub3+e/6GgIqIbb//Li2vxwxFz7MdeGntnA LRf0I45FROl3LZJTddC3bpOIDA9okcw9PVxenftrJ13sLJJLb8ELL+bKi7nxYG4ufN/c6NHo rG/8Xbu5pNUhZnPISF9AwpsSllq/9FQ9Pzctkmwkbd0OVGiw5sUO9VLJcnT8udmuAXxBgy9p sLMsBwStqdUp/Kt2oKAigxo9vPDVPqejahokCy/JbcmXPW03PaIpOzNAgt2kOLjMTFUDImJZ S6oNJgJxCezMpCkjri6DlntcT0eie8gywemH2YFoFbAfktSMUU/bA55H4AUbm4sCEUVnpgsz BoXO0jWQtF19y5vULLRrk+VwSbzd7V92X2efH5++yEyhg8gEZypoSpMsWOnmQvjV2/755fgF 7X0+ftsdPrkWpjLSPD4aGZIUnPBgzSWTfw6HyPUoVgkZATarQ3E5dR8TwqnyxT00oO8NQwAQ R2geHnDfhCD8+/H5224mRPanLwfszZOE76ngIzITKS8SykKVFWg1JS6OhSCElApBq4fXUvi8 a1oI96YbrSVCPJFffpifnV9OypqaV4IxgT7e9ACrWRBjaQJJC4xFh/7w93lYZtRpjgyx3BRG mkjsniEOi3pY3djtlYSNuGhwkCS5kDVa3e/XxshBKYtMU1hiBJlNULSq95gA1szrpsON+6Vs Zwlaqg0LbiEQjO2EMKwmiAoG94f6TpPcJ+DocCBn58PZv3OKStqQ2gMA15Qplap07zNy7upj LeQqiMxm+pPIcgCP6QNoCRa+FqMANlnkzXwqRKyLxG5kXYr7fWA5fPvy9upgKnmvgU+kZaHV mQGLj8Wkt4FBpsxcPYXUUYdr8IfFiBUQQT5piHnmLumBSm3BgaPM7WqbLCCDnYFdiJrynOWZ WHJukweMt6nwzALOlMbNUuU2zt3y1pCnOMBLPc3dBipPAvcRX62QgRPtGoM4KVo765UNtsqW j6uCHXqsEtS6lHtTbCfSekwbWxwgULMkWblxqzPQvpKwSzAVNMdKOfIB6RkBG3WWvT59eX+T rD99fPlk8Hu4xnUQdqUVy8eXjRuRfQoPL23Q0GHiNneC1QlGGJfUBq7ALgzu5KWhsjPA/TrI OvZhbiJhk5Vd+0FLWd+Inp/I44JYOME0bg2wQRtllSMXLStieQScmGdoyi1jlcWjpO8bmMeM jHH260HZ0Rz+a/bt/bj7dyf+sTs+/fHHH7+5x23dijOzZVsyVaiaV1ErzJU93+o7dy1tNhIn dny5AU2ut2jUpCJz1iamFstQU6Zqq0Uc/Hpt+DUM7YmBU595WzD4imWMVW5PVCsgJdDIsKmB wpaINYy55RVXn5bnOByqBEqDZoiD+ouSWCGIJHiiZLzeron/VF4iomN0GDbFVDjinf29siGo VuaGWCERUc0g46E41UejDnHYkKc3zrZAWrpRCRRHbsVA0MvIpzh8IEC6SY4ZBtQzGUgsuJwv Gg3grW89GFzdYMwILPonyaQ8/eHiNPHPFGiUZvTOpY3EyVl01B4Aejg+xDLLspHfnc+Nuu3V B0B215xQlys2cKekyNonP0LVadlCYi/cx2yw9jBuY2qR9ayuy1p0/C8p/1KvKChsjhSasBvw DMQPEyKlOov9IEJGyLjrrMWDuAT28o8r1+V9rQCTZtreoCX1hX/LxMgU0T3tfgGPPXo5TpBJ CNODKF03D6d50hWyFaexqzqoUppmuAMmwxrxI/sNb1N44W3seiQ6R+FSEESl7uuFJPAMgusT KHGn24VE6kNZisYFsNVod2Q1UdYamedajU5vXZLoPUWzfqQ3ziNYqeLW0TeiY5E7PlpRuMI2 glCPX+GUNxiy2AUpQiI5u9Ujdzq11zhiLukH//quKZOEIDEEF2c1bMQapSpWa1JOIHVyqhlq CiHAGv71FmKUdN1hZH2IGUrh2EjgXd94ODBw+AZOvoAoNERQBUYUq++Y/WYnqcRiHPDkMKpK /aOIgp89ip0oP2RywWkrPKwSB2ZROlqZE28242JQvaEXwjBzbSBOk8p3WoIrrnM+wBvrGHWB LHzayH0oOFuaBzV1s9P30EhnnEQawQ9aKrvDii6Hu9Lgm220CAqTI+qEU5ASzPsLqrPa3eEo ZZjpczhrMWxtY5lgmyRebDjxbyEkOp2Yehy24EToxUtx9urypKwJLUnZNu5yQ+SVLWxxUFWO VN/Xt4Ks1RO1IxR1holTZMhb2sgFsV1nBmZGYC3uzSm68Hnbb8WaB5GRxwxD0M4vbi7RrdJ/ eYYoCBX3XuRUJEJpqOK0rnO0osN2YLktb6KCRAgDoCUSJ1TdVbbsMt0JAwjZ5r3Gy8v3KjYC T8DvU7qHLmwCIWaI62zLH5Bx6V+PWsKBsCj7osuoJ37E69+6JXve1oEsyPiqyC33OIMCqrXU l1J3AoZ6PW/kIWoGS4e1GrWKhigZfF6HzKyg1O6M5c6COrsnMrZqH1ct7BHLuGxC2LeejREQ KS47sX59QQzVtT4Lk6wzV7Ly5mh9KUNgLYx81xULeCmvBegO3J9tl2cfznw4MZxzGieX+Idz GguHqH7tGLFQHS1XTBSMttMcKby7a6TA6rWxV1K13kS9deo2jK8aQR3k9JkUVYGXHZRi0+aw ynkhxAtDbJOFi5Vdm0Za8n6c81OMGFaSuiVUmqWf9B0ETm7aVTa7p/f98/G7+xhkJqdRgdtB ahUIYOeGiBCqD8hDsmtA9jHLU4ZpDlz86uNUDA6TyVV0tQWLupq3Ap+zBq3Jcasam1eRUNKR QiW2mI8W4QWL8dITldW9vLyZ0QUcohMovAE2lR42Eu6hGOKV1RDrWx6EP0CjueKHX/48/P38 8uf7YbeH2M2/f959fdvtf7HX6TQ2QeSu4gH74ZfxQxlvYFgF0f772/F19gSRt1/3M1mJ5g4n gxME2SrQg/wY4HMXzoKYBLqkYXYb8SrVx8TGuB+p09oFuqS1cckaYSTh+NbgNN3bksDX+tuq cqlvq8otAWytiOY0gQOL3U6ziADmQSHWodsmBXcrM12OTOoxwgQqKx2qVTI/XxoZ2RXCPIE1 oFt9hX8dMLw23XWsYw4G/xhn99BmiaF0Q2q0uzZlReSO4xD1SvoEvB8/74R0/vR43H2csZcn 2CRgeP6f5+PnWXA4vD49Iyp+PD46myWKcneYzJzfA2UaiP+dn1Vldj+/MH3FTMqG3fE1Mftp IA6Q0aklRNdW4BYHt1Wh2+uodac9IiaZRW68kqzeEBNJVLI1r5TDVmD3EIHTuRWlj4fPvh7k gVt6SgG3VDvWklI+Jz1/Ercut4Y6ujgnhgnB0j2BRtJQMR6Z3BrOxNdROz+jU5UOK4ZkcsNK odZ+TNlhjciFu8G5WD4QeoNHRHF1Houd7S8R8GaCyAlxTuZmnvAXenrSYYWnwZwCirIo8GLu DroAXzjAdlXPb1zaTSVLkIfg89tn0wt8OLLcvSBg0nXYBS/MBN4apuBy9ZxgTEUXcqK2Orp0 gKG4uiScWB0DwskCNCy7IGdZxt2TJQrAzsX3UdO6iweg7sTEjNrrCf6lxWTFDdLgIaAF+WFu g6wRnPInSGAa/OM8sFx38TDmyiziXKxk2EmnMonpm4ad2zXatC3zxDhQ6E0Jk/YTJHZFo23U fnc4iPPJWcBCoAFtv8u8H0oHtrx0d0n24K4+AUsn//7Hl4+v32bF+7e/d/vZaveyky5a7lYq Gi4uRZQ4Ftch6DqKjsYoDm8PicTRMap1EuqMA4QD/ItDYlW4ehlCviYi9ZQMPCBooXTENj5B caSghmZEkhI11GiZBwwY92yWblCxeqFwRnPCAsM6MaYaoeC3nqJWzMpr5JKkPCn665vFlmzp iFXDQlUCLutREOTjEkMNXEMbZmnfRRGlPdQI7gJXGFVwIYMvbxb/RuSKVCTRxXZLvejZZFfn dN/1atbJjypa00HWiMrWJ6QNoBvjc04KveY+zxnctfF2DpoQl/3s9keI2yHk4QNGfT48f3p5 PL7vlaGm8Twv/Ta0tGxKo6BdiG0KXORoPzBdYfH2frvWxGxl98QfrLysa8z/UbDWBq0b46lu rXInjV2XVBAqoVHJ94jAo9OT6qqjdTIhL4L6flJlSwub57/3j/vvs/3r+/H5RZd0Q97WDKKm mi8go752wlPvG9h33SZseARs2rqIqvs+qdF324i1qJFkrPBgxQCOqbAtFLh3gm5bauZdPIRs 5WWuv7INKC94go2a2wQkFEzeWmXcZKOR2NGCdxuguSWJRf0JeVtU2Xa9WYAp04Mw71pYKnjG IxbeL60KJwxtia9IgnoTeMLOSIqQk0Gx6kjzxsl46F5dIqNFEPizlcOJ4QDbYbjJhVTEZU52 WQgJuo+ZBgXHZxuOLmnigDJlEIQ6konunmZCqZJ1JzUDmkY0nCxl+wBg+zcoUh0Yhi+oDLav MDy4omdY4QMy+MmEbNMuD536wBjJbVkY/eXAbKvfoZv96oFXJCIUiHMSkz0YYasnxPbBQ196 4JrcOOxrQrlaM8wDl5XGxUOHQqlzbTrCyAplUK8DMOXQ46YGjWDuXHBDZJt1YKhswevPCNYg QfDq0RvsCN+LzIDk8M5XlGVlB1g1CDD4dUnaz6JZJrojBmZSMrBEqI3a4zudj2el8UwHv0+9 BBSZ6TsbZQ8QwdTgUGUdk5s/jg2TC17fgdKBurnmFbfi1jdgRJf54p5BDJCSKmhk8g0MUcC1 pTCi4ImqHx63hhLB7CFmlW7nARmnWV+ILSXtCP8P4XbEaHCVAQA= --KsGdsel6WgEHnImy--