From mboxrd@z Thu Jan 1 00:00:00 1970 Return-Path: Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S1752344AbcBJXW1 (ORCPT ); Wed, 10 Feb 2016 18:22:27 -0500 Received: from mga02.intel.com ([134.134.136.20]:32481 "EHLO mga02.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S1751879AbcBJXW0 (ORCPT ); Wed, 10 Feb 2016 18:22:26 -0500 X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.22,427,1449561600"; d="gz'50?scan'50,208,50";a="909615246" Date: Thu, 11 Feb 2016 07:21:36 +0800 From: kbuild test robot To: Andi Kleen Cc: kbuild-all@01.org, tytso@mit.edu, linux-kernel@vger.kernel.org, Andi Kleen Subject: Re: [PATCH 2/3] random: Make input to output pool balancing per cpu Message-ID: <201602110749.BVCqOL5S%fengguang.wu@intel.com> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="3MwIy2ne0vdjdPXF" Content-Disposition: inline In-Reply-To: <1455145297-30897-3-git-send-email-andi@firstfloor.org> 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 --3MwIy2ne0vdjdPXF Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Hi Andi, [auto build test ERROR on char-misc/char-misc-testing] [also build test ERROR on v4.5-rc3 next-20160210] [if your patch is applied to the wrong git tree, please drop us a note to help improving the system] url: https://github.com/0day-ci/linux/commits/Andi-Kleen/Make-dev-urandom-scalable/20160211-070625 config: x86_64-randconfig-x014-201606 (attached as .config) reproduce: # save the attached .config to linux build tree make ARCH=x86_64 All error/warnings (new ones prefixed by >>): In file included from include/asm-generic/percpu.h:6:0, from arch/x86/include/asm/percpu.h:551, from arch/x86/include/asm/preempt.h:5, from include/linux/preempt.h:59, from include/linux/spinlock.h:50, from include/linux/seqlock.h:35, from include/linux/time.h:5, from include/uapi/linux/timex.h:56, from include/linux/timex.h:56, from include/linux/sched.h:19, from include/linux/utsname.h:5, from drivers/char/random.c:249: drivers/char/random.c: In function 'credit_entropy_bits': include/linux/percpu-defs.h:91:33: error: section attribute cannot be specified for local variables extern __PCPU_DUMMY_ATTRS char __pcpu_unique_##name; \ ^ include/linux/percpu-defs.h:116:2: note: in expansion of macro 'DEFINE_PER_CPU_SECTION' DEFINE_PER_CPU_SECTION(type, name, "") ^ >> drivers/char/random.c:777:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ include/linux/percpu-defs.h:92:26: error: section attribute cannot be specified for local variables __PCPU_DUMMY_ATTRS char __pcpu_unique_##name; \ ^ include/linux/percpu-defs.h:116:2: note: in expansion of macro 'DEFINE_PER_CPU_SECTION' DEFINE_PER_CPU_SECTION(type, name, "") ^ >> drivers/char/random.c:777:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ >> include/linux/percpu-defs.h:92:26: error: declaration of '__pcpu_unique_lastp' with no linkage follows extern declaration __PCPU_DUMMY_ATTRS char __pcpu_unique_##name; \ ^ include/linux/percpu-defs.h:116:2: note: in expansion of macro 'DEFINE_PER_CPU_SECTION' DEFINE_PER_CPU_SECTION(type, name, "") ^ >> drivers/char/random.c:777:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ include/linux/percpu-defs.h:91:33: note: previous declaration of '__pcpu_unique_lastp' was here extern __PCPU_DUMMY_ATTRS char __pcpu_unique_##name; \ ^ include/linux/percpu-defs.h:116:2: note: in expansion of macro 'DEFINE_PER_CPU_SECTION' DEFINE_PER_CPU_SECTION(type, name, "") ^ >> drivers/char/random.c:777:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ >> drivers/char/random.c:777:50: error: section attribute cannot be specified for local variables static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ include/linux/percpu-defs.h:93:44: note: in definition of macro 'DEFINE_PER_CPU_SECTION' extern __PCPU_ATTRS(sec) __typeof__(type) name; \ ^ >> drivers/char/random.c:777:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ >> drivers/char/random.c:777:50: error: section attribute cannot be specified for local variables static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ include/linux/percpu-defs.h:95:19: note: in definition of macro 'DEFINE_PER_CPU_SECTION' __typeof__(type) name ^ >> drivers/char/random.c:777:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ >> drivers/char/random.c:777:50: error: weak declaration of 'lastp' must be public static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ include/linux/percpu-defs.h:95:19: note: in definition of macro 'DEFINE_PER_CPU_SECTION' __typeof__(type) name ^ >> drivers/char/random.c:777:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ >> drivers/char/random.c:777:50: error: declaration of 'lastp' with no linkage follows extern declaration static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ include/linux/percpu-defs.h:95:19: note: in definition of macro 'DEFINE_PER_CPU_SECTION' __typeof__(type) name ^ >> drivers/char/random.c:777:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ drivers/char/random.c:777:50: note: previous declaration of 'lastp' was here static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ include/linux/percpu-defs.h:93:44: note: in definition of macro 'DEFINE_PER_CPU_SECTION' extern __PCPU_ATTRS(sec) __typeof__(type) name; \ ^ >> drivers/char/random.c:777:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(struct entropy_store *, lastp) = ^ include/linux/percpu-defs.h:91:33: error: section attribute cannot be specified for local variables extern __PCPU_DUMMY_ATTRS char __pcpu_unique_##name; \ ^ include/linux/percpu-defs.h:116:2: note: in expansion of macro 'DEFINE_PER_CPU_SECTION' DEFINE_PER_CPU_SECTION(type, name, "") ^ drivers/char/random.c:779:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(int, next_pool); ^ include/linux/percpu-defs.h:92:26: error: section attribute cannot be specified for local variables __PCPU_DUMMY_ATTRS char __pcpu_unique_##name; \ ^ include/linux/percpu-defs.h:116:2: note: in expansion of macro 'DEFINE_PER_CPU_SECTION' DEFINE_PER_CPU_SECTION(type, name, "") ^ drivers/char/random.c:779:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(int, next_pool); ^ >> include/linux/percpu-defs.h:92:26: error: declaration of '__pcpu_unique_next_pool' with no linkage follows extern declaration __PCPU_DUMMY_ATTRS char __pcpu_unique_##name; \ ^ include/linux/percpu-defs.h:116:2: note: in expansion of macro 'DEFINE_PER_CPU_SECTION' DEFINE_PER_CPU_SECTION(type, name, "") ^ drivers/char/random.c:779:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(int, next_pool); ^ include/linux/percpu-defs.h:91:33: note: previous declaration of '__pcpu_unique_next_pool' was here extern __PCPU_DUMMY_ATTRS char __pcpu_unique_##name; \ ^ include/linux/percpu-defs.h:116:2: note: in expansion of macro 'DEFINE_PER_CPU_SECTION' DEFINE_PER_CPU_SECTION(type, name, "") ^ drivers/char/random.c:779:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(int, next_pool); ^ drivers/char/random.c:779:31: error: section attribute cannot be specified for local variables static DEFINE_PER_CPU(int, next_pool); ^ include/linux/percpu-defs.h:93:44: note: in definition of macro 'DEFINE_PER_CPU_SECTION' extern __PCPU_ATTRS(sec) __typeof__(type) name; \ ^ drivers/char/random.c:779:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(int, next_pool); ^ drivers/char/random.c:779:31: error: section attribute cannot be specified for local variables static DEFINE_PER_CPU(int, next_pool); ^ include/linux/percpu-defs.h:95:19: note: in definition of macro 'DEFINE_PER_CPU_SECTION' __typeof__(type) name ^ drivers/char/random.c:779:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(int, next_pool); ^ >> drivers/char/random.c:779:31: error: weak declaration of 'next_pool' must be public static DEFINE_PER_CPU(int, next_pool); ^ include/linux/percpu-defs.h:95:19: note: in definition of macro 'DEFINE_PER_CPU_SECTION' __typeof__(type) name ^ drivers/char/random.c:779:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(int, next_pool); ^ >> drivers/char/random.c:779:31: error: declaration of 'next_pool' with no linkage follows extern declaration static DEFINE_PER_CPU(int, next_pool); ^ include/linux/percpu-defs.h:95:19: note: in definition of macro 'DEFINE_PER_CPU_SECTION' __typeof__(type) name ^ drivers/char/random.c:779:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(int, next_pool); ^ drivers/char/random.c:779:31: note: previous declaration of 'next_pool' was here static DEFINE_PER_CPU(int, next_pool); ^ include/linux/percpu-defs.h:93:44: note: in definition of macro 'DEFINE_PER_CPU_SECTION' extern __PCPU_ATTRS(sec) __typeof__(type) name; \ ^ drivers/char/random.c:779:11: note: in expansion of macro 'DEFINE_PER_CPU' static DEFINE_PER_CPU(int, next_pool); ^ vim +777 drivers/char/random.c 771 * full. 772 * Feed into all pools round robin. 773 */ 774 if (entropy_bits > random_write_wakeup_bits && 775 r->initialized && 776 r->entropy_total >= 2*random_read_wakeup_bits) { > 777 static DEFINE_PER_CPU(struct entropy_store *, lastp) = 778 &blocking_pool; > 779 static DEFINE_PER_CPU(int, next_pool); 780 struct entropy_store *other = &blocking_pool, *last; 781 int np; 782 --- 0-DAY kernel test infrastructure Open Source Technology Center https://lists.01.org/pipermail/kbuild-all Intel Corporation --3MwIy2ne0vdjdPXF Content-Type: application/octet-stream Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICAnFu1YAAy5jb25maWcAjDzLcuO2svvzFarJXZyzmIztTJxJ3fICAkEJEUnQBChL3rAU WzNxxWPPseQk8/e3G+ADAJvyzSKJuhvvfnfTP/zrhxl7PT5/3R0f7naPj99nX/ZP+5fdcX8/ +/zwuP/fWaJmhTIzkUjzIxBnD0+v/3z459Nlc/lx9vHHn388e/9ydz5b7V+e9o8z/vz0+eHL K4x/eH761w//4qpI5QJI59Jcfe9+buzo4PfwQxbaVDU3UhVNIrhKRDUgVW3K2jSpqnJmrt7t Hz9ffnwPm3l/+fFdR8MqvoSRqft59W73cvcHbvjDnd3cod18c7//7CD9yEzxVSLKRtdlqSpv w9owvjIV42KMy/N6+GHXznNWNlWRNHBo3eSyuLr4dIqAba5+uqAJuMpLZoaJJuYJyGC688uO rhAiaZKcNUgKxzBi2KzF6YVFZ6JYmOWAW4hCVJI3UjPEjxHzekECm0pkzMi1aEolCyMqPSZb 3gi5WJr42ti2WTIcyJs04QO2utEibzZ8uWBJ0rBsoSpplvl4Xs4yOa/gjPD8GdtG8y+ZbnhZ 2w1uKBzjS9FksoBHlrfePdlNaWHqsilFZedglWDRRXYokc/hVyorbRq+rIvVBF3JFoImczuS c1EVzIpBqbSW80xEJLrWpYDXn0DfsMI0yxpWKXN45yXsmaKwl8cyS2my+UByq+Am4O1/uvCG 1aAG7ODRXqxY6EaVRuZwfQkIMtylLBZTlIlAdsFrYBlIXnx+xyMNTzO20Ffv3n9G9fT+sPtr f//+5f5hFgIOMeD+nwhwFwM+Rb9/jX6fn8WA83f0SeqyUnPhMXoqN41gVbaF300uPFYtF4bB U4G8rUWmrz528F5fAQNq0GwfHh9+//D1+f71cX/48D91wXKBjCuYFh9+jNSWrK6bG1V5HDSv ZZbAO4hGbNx62uksUMk/zBZWwz/ODvvj67dBSc8rtRJFAzvWeenrY3hxUazhzLi5HBT5oK14 Bbxn1Y8E/nv3DmbvMA7WGKHN7OEwe3o+4oKeqmXZGrQD8DeOI8DAbEZFUrgCmRBZs7iVJY2Z A+aCRmW3vh7zMZvbqRET62e3aL36s3q7Io4a7SwehdvyR8X4ze0pLGzxNPojsSNgNlZnoByU NshZV+/+/fT8tP+P93z6hlFn0Vu9lqUnqy0A/8tN5vG50iAD+XUtakFDhyEDz1huAnlR1bZh BozukthDumRF4mu7WgvQ+5GSih7OCqxF4LKgcCJyGgoa0gSqzgJNJUQnSyB7s8Pr74fvh+P+ 6yBLvfkE0bTKgbCsgNJLdUNj+NLncIQkKmfgARAwsBWgweGA2/FcuZZIOYkYpu1fwZvYqmji CZAEfDAOWt4swRQmgZrXJau0CJfl6FtpVcMYd6mJig2DT5Iww+jBa7DxCZr4jKHl3PKMuFur +tajN+39BJwPFHBhCOfEQ6JKZAmHhU6TgWfWsOS3mqTLFRqIxHlelmfMw9f9y4FiGyP5ChSw AL7wpipUs7xFhZqr4KEACM6EVInkxBu5UdJJSj/GQkmNsQRzCyZG28urtE9jdw0+ywezO/w5 O8L2Z7un+9nhuDseZru7u+fXp+PD05fhHGtZGecnca7qwjj26JeyxwzRxAGISfBWY1a1b01P 1NPNdYJiyAWoFyA1JJFheoUe8vjoFa9nmnqtYtsAzvNUOfh/G3gUP3ZwFOEySEkcGcfDFrJs eO3enIIvvUHdA5FIdJ0xzokmfUZQXXYVG8xM7GDlZBpuTKqrs2FwdzrQgaKZK0XZdet5QCBS XHhGQq7aWMx/ulVnE+BdSAcBJ0tBRcrUXJ3/EmjzGmJE59aAy544WZxyM4sawps5y1jBTzij EKqcX3zy7ntRqbrU/o7BLvEJ9spW7QDiIA7hdup5iExWTYgZ3jMFzQM27kYmZkkuCILhjZ1e tJSJjs/UpMADt35QDTIG0Y1HiE+CY1vMaIZErCUP1EqLAPpJ8eq2JKr0FH7K5MBB+cqGlKik jKpCtQZeDJgdEHDKabFMgt6kXcIfByYixUikrAQHDU1dZRWGkvjWcH7rFlfeg9rfLIfZnKHy nNoq6RzW4QET5w9S6yWRpwoA30G1eBVNFvl5w6XyPiBDrWADW9qtC7w3VoD7LQuV+EGNIwIN wEVpw1KrQyI/q+S6XFVNmTGDSRrv3sp0+BHryBy8UQmsVgVvA/FoDsqyae04vW+88NjOtzsd wVfwS29zPYY0AR0ovsIE4VSguqIz0ioBArUmrcldpzWoa+8yShVsXi4KlqUea1mD7AOs2+ED 4HK90w43uASdRWyASS+uYclaatEN9+4G38PGCf5KJZfNdS2rlUcIi8xZVcnw+WweJCFFynEK zN7ETpgFwsLNOu+SAtYCt+nFcv/y+fnl6+7pbj8Tf+2fwP1g4IhwdEDApRpMMzl5m3AYL9E5 HLkb0lhfwmWugngWU2zVinxvnbH5BKKeU5ybqXmkiIzIrd/bQPwrU8lt7ocYCto5lVlgy1Zi I8DVVH6GRzk6AtKe0gpdmfmsaB/mxMAil44bB9xvdV6CLz4XPguDFwWu70psQThFlmIOwD9s my+h3VDcgs0Xg0yCKKDm5ui4TfGRSOGuJB6oLsIRka3HN0f3BNw2cAghvo3OLeH6MEsKm4uj x1Wc4HHQShgSASqXHuCgmGJJKeVpt2kRS6VWERKztOjpyUWtaiJu0fAO6O23ERmR6gNDtwVD ifGRVas2zR6tUokFKMMicSnv9iIbVsqIjmfU/oDOSVmEW96A4Ajm7HeEy+UGXmxAa7uHiAh1 EcBNXRUQwhgQD58HY32CfEphiYk7bVC1B07qPOYLe38Um7eZ47WTC81SuJa8xDx1fFkO6rJb E7hE1UEKd1haC47KpwEJNKNTg4G3G0emFRzcIs9ZI1C+YxAi4VoLyjUYE8It1hl7YzZgLkVG dW7X42jGR09HfoG8joO/CXkqMCMh2mw4JpwpOpspB5tAPr9WqWkS2JbnCeYqqTOQZtQroOSs o0hsUWxAlaE7hfkevKQRA2k3HKRO5ePCw7hiFE0Q4oZSEzHaqxNNTeKTfIoerdy2yqUx1lFw 2WSu1u9/3x3297M/nZX+9vL8+eHRJQR6FkGyNitJeSTdTViyztxE7ozdRafunDpcCnxXyotG +wY85utg65NptPpX515Y556RmKN7YBs0Z6CRa4835mHM2YUFc70ggUGCcoghjFhU0kThBc8T W4WyabSqu+dy93J8wLLqzHz/tvd9HVYZaR1ycOUgyvXDTAY+QTFQTCIaDlFywfzbjimE0GpD muyYUnLatMd0LEmpa4/JSnUDwYLgpzZXSc3lxO7kZiAkKZRO36AAo7lgb9EYVsk3aHLG36LQ idJv0GRJ/gaFXry1E/D9qjcvRtfFGxQrVuUTF9OFAamk+A/rBpefKIzH/THKylyroTqxkGqm 7/7YY6HMDwCkclF/oZSfR2+hCegwXCRISLU4nl6fKJlQIzscrnViaLvA1bv7/e4e1ON+qCbq 4tyLuwpbOQVVVYKnWhenklvMKPTnqvwmokCjZMssiZ3GJtCnSaqbiGDIETnd8/J8tz8cnl9m R9A9Nvn7eb87vr5YPdRfRFcxppkppy4HW0FSwcCxEy6JM+zBojDJ3+ExjAhiMqTYXIDTSSUQ EZmXVof6YxYqS1KpqcISjgCvRBQJlumHDEawHjU+IEClnjVZqWkliCQsH+Zvk2lUkQX1Uj6X AftaSOxj45w9S7Tls5TJrA6TZI6/gWHgSissKLcdGpSXtgXHeC01eHKLWvh1DbhQhv7ZGNLv ajiroDTCCuLsbtJBkazzNj4nbUK/xqTD11NEyeBC2VS1K8IPanb1iVa/peY0AoPriwmlDkJI 7LmvAJV1+FT20jG51racuBT3pU+SnU/jjObhfG0IEXVUYeVpHUJyWci8zq1rnYJNy7ZXlx99 AvsC3GS59uKItnCCTr3IBA+eDWcCznNMT0UPLR44nhrGwXljNcmApTBxqiHxo7oFmAcQCNd9 NUzMMkBsHYJKu9xIFTS5WMJmKbLSX6mwLToa3MT+DoTIS2ODpCAV2MLXKgOGhJVJDmmpyFyO G2/52TMBGGsaYZPK4RPaEBLj7IgHpCKAlagUOME289t2d6AsYCgS6dk8TOe3oPGzjijgYU/i ZfGbmCgIrPNPlxNauCvdNiKvMxY6AfKTJ91g/IA7QZQIkNt9IPU9Ktr2CA9K3olpyoib0RTH WpEraxlnXsrlFux0klSNifsgXaci5k1ItJVIWcH9NYs5hq2xBXeFdlBtjSgY0R/Wo1sXJMZb ce4MBkQ7fnJDZplYAKu1NgLr7rW4OvsHnZcz759esk5NNuwEooyaUZg4K+TmAfnQwpcM78gb iMtyQaHW8C+MZ+NbGShs5rdxGyoboxbCLH0FMJprvL0oAAzAjdXuwTD31hCmsCohhrfnBYvb 83sY97ZGDLgyVXZ62ha5aZbKlBlZRtNlBua/NM6TRh33Mdihu7KODP0U0240zITzqeT0NLd3 3mGDHX1XPeM4sw5W2k9qrrTHEJ0Dbd/U9Vok1dXHs18vQ3ae9IDCyyE8o+UNsLm2Na9JdUXl kai2C7/HcxU4HTwTEJ6jWadrdaHjPGyazD7dlkp5cnQ7rwMLe6tddeOEX2IbFLus91SAAXcv qgqjCJstdl2roVmySWcLp5oTUImVeAhUJ5y2j1Z1Yn23mYOLi3WMqi4nGMzZNQ3eKeZkbtCB GbjfVJRmtidy6bXIZ3YHH0pWqaRDF5eBpesVt8352Rnlwdw2Fz+fBVx22/wUkkaz0NNcwTSx E7+ssIdmovNvI6hndzWisLDjYLbetMXCoxeFV0wvo2w4yrZE90ODp2PAFpy3JmCoRAv0T2xr xoRusONtmQbGX0TDHYsM1r+wjeRUc0hE6NyEQKRHc0XpbU/sXL4BFCzt6oAtw+vJEnOiEm11 dAa7LaOOQU+phsq5j62f/96/zL7unnZf9l/3T0cbXTNeytnzN0z3BRF22/JNe5lkqZf7pRv8 1d2MfSU9ymu6bLBtvXYJZBxS+u34FtLWK21uzn1XoL1PI7w8XVcRWoRxZkiBIUaq3WwThwDe WjcKWLWSifBb3sOZgJ3tchOZRaBg8VHmzICDs42htTGhGbbgNayupqZO2XhAokI59XE2DqvE dVMGxcruRlzQJYNe1xA5Wk2WOa3CoknZYlEBGxg1ed3oD+UsG63Aaw3hbpPohDaTbhu2Ocax WP9o0+Sjnp9o21xivZyKn5x16QPFaKsKQjIQ7ckztpIINrCNncLxej6Vx8axgpZC/5Jy8CrV CTKwqzX20C7BJ7wBz6JRRUZbSEsO/0fdwSCmrBRx3bOHtzXRcEZETK8HHnam6HcpMeuowDtf TOaOQ1vatZDO0pf9f1/3T3ffZ4e7XVwk6gSCHCnvH/dDghdJ4+bWDtYs1BoC6CQhnz6gykUR JBCs+kMfTg90EJyXWfjcdlP5/uvzy/fZN6vAD7u/4DCBspa/gLm3U4yGzl8PnXqf/Rv4e7Y/ 3v34H6+mw72HRP53cWCQegBonrsflLHFQbaLW4cz8WJ+cZYJ18UToARq78ANRyALJQtBoGUr Ok3WDiD8aJ9Al3m0BkDipKYH74LXcBnEWYuh2ZpWLgMZBPL4yWBBJlrxVuDYE2GLvWctR4CJ 7nl775P6DLGV+96p8wqwL3FiU9rUQZPQ0qZuJoiZiR5a+uk/BJRVdIqSaRn1dnUtDs41Acb8 4/lwnN09Px1fnh8fgc/vXx7+Cist7gvBsEcEM9zF3J8a417/d84li3+DM8KShku/ZxWGOZZs d/T+bvdyP/v95eH+i18E3WImcRhmfzbqIoZA3KOW/pU6sJHEpbYopZdy7m81ufzl4lc/H3Vx 9utFfFT0N10bVPCArcHBiyVq1nCFid+a1wIao+UvF+djOKYTrO1Ttbn6yffDW4KWxapNYzaN DejoduJuPnhGUSwk2QjSE4ViOixV51hhl33PXrX79nCP5bm/H453f4wZxzvdz79sxjPyUjcb Ao70l59oeohtvaewMd5Wp/NuS+Kf/d3rcff7495+3DyzzYTHw+zDTHx9fdx17nY7fC6LNDfY nDFM2cI0r2QZqCRnbeEhiKtrB+VSB9yAJQWMsMg3keyniyH9OeH6bPxvM/u6aPDbJn/ry48u 6MrDZFr78VY80jbuxUBXH1hbJlGlr2tybuuQA2Sde6JeiPGeAAYx1wqsr9ZhXhMwYDzAOdUR UHQw+5DF/vj388ufYHGpKKlkfCWoh6gL6TEU/gIZYn4lLfV7lvGX/d44Aul6DtKUSb6NEBA3 VdEn1gZvcwTwKIcXLwTtUgMcP+/ENETOKiqawFlLUzY8YxAXpVt/2m40RN9WV4BWysupD2WA 2LWZUS6z8a4GfoCtKPzkqvG7Y8DhH7VZ4S4THTSZrGGO5tPZxfk1uZ1E8IJ8yCzzojj44YmB LDfBrZabtuA21bWRUTe6ufjZW4CVvi1bqoCnpRACj/DzRwrWFFn7P7bpXaIEhmGVR6tVzLh+ 64gjmnj+7isSKwfXr/vXPQjHh7Y1Ivg4q6Vu+Pw65EsELs08Yh4HTifqoh0B8MP0xtyXRMS0 tgWZfvqOpCI7yDus0+2jQZrs4eiwRlxn45ObeUpNtTi9gUSjSI5ng//6NY2evKrIe7jGGzqx DF+qlaBGXp88KQ/LMB04vZ7GECyxTMfAUooxkFTcltrLd/HH3eHw8PnhLvobIUjLs2gwAHqn IgIbLotEbOJLQVR6M3EniKwDm+kANkAYQ8dPi5hKr0tqVYRTBc1+V5n/sW8H5d03SfGpy3QM xCmCOjUaxjzMOA6wtt10+FrfQ/F8dIYWU8y3hi5s9CTuCqnBuTBUEcOjwL5fcrOcFTIZH5nx iJxhFQKN70geELNgZNjZoXOJxYzxhAWjVhHuO/LRIlpOOG09wWqOY0/SoOk7sVPy/YHjCZmV aaBcE05/iZIU2FqvFf59BcpJBRXObA+pZ8Z7WFMErquHyPH7aHJBj2jqq761s3ie1K9zmwlb QzxIYHvHMShZddDQl8vLWJsgpFloFdI02CQRVa0sHDz8uqD7lZd+g4y2tdT280X34frg4zuw ddBoFe9ROPctemII3iAA3jbhV2Lz6z5Kb33h2XF/CL/CXrK8Yi6gbDuI7/7cHyEuu394xibt 4/Pd82PgODNwe6gthnlt+AlBF6VjETPneUy8CGjdgsD8yf6vh7v9LOkDw2DQmjPaZUOkzk5h IUw5gcMmM9d0R0fDskroDsY5pVluJP5ZFt/odZAm0HQ3+L1D+IWWBWFOPgLpcjsikp5U8nSB ruB5oJqsl3lueyTzqe6AbiAeX2QKq9QgbPg3euib6OkrsTiR1OrJuKhM/+Vao4qaKsJ4m3Bl /fAraw89KuOMiZxnzzLcYUJ9ZzfsDV51/Me7evRN8FgBGB33YFAm5939RxBYZVsaGFVO4jjP p5FmJSlklHJpQ4Hg/TtYU3FskdCmIvWWT9blVd+9cyKpn7/uZ38/vOwf94dDl66ZYboeYLPd DP8oXJcJnO0evzy/PBz/8P4cQj83xJjL8W6bTPgfo/fg9p0JTJsdsG0FQa9nOHaUw+/RhXKd 1KcCqnMsf8+VFicYfNhRlv+/6MDxmjR5PdGS6JjtkYrP355BzrWeYg4Qq0kUWLcTS2OGZvn2 4vnyJi9PTQNc0Ohtwf+PsStrbhtX1n9FT7dmqk5qSEqyqFs1DxAXCRE3E5RE+YXlSTwnrpOT pGynZu6/v2iACxpsWPOQWOxuLASxNBrdH/5Rw4JwJP5BqylJ493meTVxJm7no7uOEelLfcMD OEHkrNWAcIaB9cIllbalpkee0Y4EsJpvacUxYpxGRShSEhzjojUTy8ACYeAf+RgaMVtfJ/Sv 5089eVH+sKyeJx0dbLvEInIHXcRAOJDrSZNXKZrIB1qXQxtTrmgNK2KWlaYRqap1MSmvtR6o 8EQmfnpRZwRmxUZRXvTxZRMPfATZKGFUeMxHx36OLzvWnhToUpZlO0Ye6CssPbCPDlZdw1aW yW2bg2dRjdZTaopc90llfdRi6gQ1urgKw3ef7FGGWzqlBhFScEJlgVjJ5RZp4Pq54ybqS08T lem23RPzHJ1z9KkVYNTUBDnTqIUxAMGkuB3GU9TPqpMb/Vf+KaxIWIVnYqMB5A1ymJOPYGtS /tEQekQGBEoZMzxJ2BmU6btpWb0Z06kXOL3KEZhrlD+FZNC8PH571QcRi+zx/9B5CeSwy47y m+G3GEMRp87bUGt/kZoQH/DU1YZBgmN+ncZdiuHZhEhjajYSeYeSqpYoq1nrjBFd8ovmctNI fNGa5b/VZf5b+vXx9cvi05fnH/NzI/UVUm7n/jGJk0h1U0fryy5tY7H1Waktaqk8DmeVBnZR 2nB4M5GdnKquTeLCzRvEMkNsXo19UuZJU1/tOsDg2DG5wVWIQJ3vKMASC25kQ1mSCbHwVm0o mxchZ5rdhhfmPtXc3BFnM7BpqJuR7YjsgU7ZvPdtVLgA2gaM3SOPxXy2AI5cw0in3Z59arg1 LmQHn806ZPSQmi92vfO7djd5/PEDDrwGzfzP7y96hDx+guA8a4CUOUB7wEeAwx5rxgBPTMv3 1SD3p3TOZhzEytRRb7GLun3bzrInT701p3cHsOSVUwCAEV2lEuGaVfcVBL+ASzh6Rx2HdwZg A4sDoXf6OxjETBkh+2z0fujp658fYL/z+Pzt6fNCCvWLDT0lVXm0Xs/6s6YCglDqiE82pJxK K7RpRnSd6iCJruHXxPZLyueuKRvw4AV91vSg77lJrWLkgetPSAI9U3ZHcLycXPfHxSfQi6nW Op9f//Oh/PYhgq45U0GNlHEZ7ZeGRUudV8ida5f/7q/m1GaKVIDUBYCUJFFkN8lAl6sStVYN Is5kOxJzVH2BfIbKN6aME8CecTJ6f655iT07pvRjW0hEteqjYIxR/dT7O019L/T8cJYExgRZ YKlmZZmLUqzfKxVBx43UmQPNVEsujmUBuKXObq7l5Gd3LT1KIGJpQpQM/wmeE5w52NjIOnDB 194Kc6QC0neBOXFwhr/UHJ/OmzK9cuxeZ3o5a70hZYIWlJK9NY7VSMoq+ZUX/6P/Bgs5HS7+ q10OyQlIieGXulfRQoPSg8oX4FBKuv8C97SzOrMkdJdMwX+IQym3ZNbkoQR2ya5HiA48mweR 3Lmt9ABjn52S3Wx0qOwy2ne6RAe1Uuc+Fbxx4ExLLowVZKCdaNjPUtIRZq18Rgf98jlH/lmg 7lsZKMc7KxNrpyEp4BKdsStRX9v9vlKAEbZbfU+iPAELM2CjqEYT2ehoMwT0j9b/SRgHC/Qo JWa5A3BJccoyeKDN5L1QSns+D2xwzhQC1ileLYOWXhwVHEp1Dz6BonOZ5fsMYxZt7+jwmkHk ZOHhzQQiuVHXk/y7YpmF9KAXvnonNYTnV3Av+7z44+nT48/Xp4Xae6ZiIZU15eCjk3x9+vT2 9Nk88hibdvd+s4njDX5L678D35poJgtULPXQrjo2UXx2uKyDR6XsuF3iQCUdiji8X8Na4I9t N8A5T8g+J+lyDRRzt/L8+fWTYQeY9qtJIcpaAKL+Mjt7AbXcsXgdrNsurkzMN4PYmzQmo8Qp z6+2F+50dLSTWpKgNLLqwArkIwcQLbyMjKWp4Wk+nBCNOSripm2pPR+PxHYZiJVnnEQkRZSV AtAyIEQOjDtmboeq4xkNGM+qWGxDL2AZpWdzkQVbzzPUNU0JPOON+uZuJGe9Jhi7g78JHfQN QVdV2npoH3HIo7vlmsJNjYV/F6I9b3+UvAP7G+lCucsrLzT8vPSz/clPYge4AaB6pYJtVyE9 xwhaFY8C68RJPct+JMVZ3QW+aintnZpUsBd8/fnjx/eXt2lm1nQ5/gKjt/REHcw1I+esvQs3 6xl9u4xa466daLfxPetUUtOsowODKDu4OOWjsUQjmj/9/fi64N9e315+/lfBcr5+eXyRs+Ab 2LPgbRYAeAOz46fnH/DTHKcN7KPpNjVGMHyW2dBnX9+eXh4XabVniz+fX/77lyx18fn7X9++ fn/8vND3Z0wNycCzkcGmvTIj3dVGMTdDZ0ZSZwaYT9SmNciGx8LQHvzb29PXRS5VRDBR6t2P 4TGv81H35YxNKCKektLAMAXPculBclN/LysQnDXSVJsDOPOPCS1mBI71mKkq5ZT//mOEBRJv cDiYT0GMv0SlyH+1zx6g7vb7SWX6co8x/OXzhI+T1LUCHYxg7blOm88kOqAtTtRmCuGNXt0k s78Sg1V0yBOIJAm1+dNQfjF21o3nQT1qcepNBLNBDEwIJTUsrIzHcMuFefoEUvipv31pGhJA 6x1eKFusKuaeCppRrEEdIeveV1qDPP0iB+t//rV4e/zx9K9FFH+Q04cRoDSqG8YLRYda05o5 rRQY72dMT0ZoDRlhmPuBGtHqh3q/cf1ztU2k4jLQSYCiZ+V+j2+xAKoAlxEGp5jTOJUN1QzT 2qv1gWFXNXxSXLE00gxXvbj6n+gOnWDCSc/4Tv6ZFQYsuNzFBt2ypOpqXicskpUXdVORq9YD fxbQo7vuYVaz+NDVUlF35SfZUkcRl1lGXZJHcyLLTnaZpYhV+ClnFuLpyD2Rdo+RHSv0b7X0 JCZO5CTgjlYlnR/NYIih25u0XGPTx0mTmL6OkgwHTaxGJJg0vBnFn1PmQqv1HaJp/Gdm3vom qWraMAEpFWCF/WzrBz21H3szz4Nxi5YPCMwUb6JJOTSHTWQrY5Vhau7JB5keLFCj+s48SCAd B8sIoH4gcgWXT4kGDqFtXz7JVW46lPKZd6JgFb63RRKbA1eHTmcON1rZVRiaFpWgGjJ3xEMM fJGTIIUDWyGN4APtWBl36UTgFVva0nABB5x9q2sV6HTQq9ALPSR1aWUz9jLXC6mr+uj8tc8B KiHNGIqnkSSw2DVXq1hN7FISCgO+llLoUT7wwsrsZ0y0Dav3ie2310S53Olh/B6gAbYGNrsC tbL3rIgLLUwfd4GNYac6r6oDvd9Uk9JcYJiydlXPNCuVnoQVUaYVuyRJFv5yu1r8kj6/PF3k v1/nakzK6wQcHKc3HyhdecBG7pEhq0Ft2EZ+UQp85AmDFeIue/8Has2UGlDvvGDMXtzQnYrZ Z1Nbd2NHdH9iGX9IZgEZKW3Y5SntVg1JmsRhVZGvYvt5mwlBGSkzWmWVbHD5dZYJTAVxUMsf DnCNGg7bqZ7RnIrurJpIXbmGw+jPloFnKDRDZx+sjpB1VD93fmCaIwaih0/GerLlRGyzI/Io fWCW+db7++9ZUT0d3XDRl8blsCVqIVMEnhdQ4DsQ5db3QZQQyNCbHFqACo1jDmSFBtDaqINQ 4MCYAN9NZoXaPcyC7x5UJfBqCKSCRwDPY1e3JyvQV3Fylm+K8bjZyF3/GuevqME6sAsY6M5D TCRUR2d85QriDpXEbJbL7Z1gsXmci+lUexzKmj+gfjsRKXlTidXPlFQKaKCel9BU9QJwx0KG Bogp0bRwnYHcz05X9SK+LtPDbXyg1mFgyEmkHA0EypdwMrzMzorOameAxq4m1Ug/UTRbRE8X SRFzuS8abU/Due/by/MfP+Hm6D7km718+vL89vQJgIKNeqBpLBasy89hmNy1jjOAmVSPsVZR AJ8Kxw+9Gz6ygcykUgGdZRmVCIZCORsso/VmRVFDI+T/XNboBp/mWh1Ks48ZpbCYVRq8fPhe mqBAtFJez6KYhnT7pHYuDKNQ1iSkZbO3dDUioStl7j/kQ+j7PjSd+eJSHId59W1R5NE7K9pY Qk3eSWgIwIcqTdijJgvQE14x5DPd+zPfbNyspV/4JBVcc2Sr567YhaHn4RQRi5MCB5fJVZyK LTDy1xdFmv1pt1qhB43RIfd5I4gu5oGu8h7f3GvlcABtihStGdNYYNCJhu/LYkmZv2UyZFxX hE5IreFMaZMK8ss+ipRp3HFuU+tAq77fhBE78xPycGkOpwI8cOX7dBXtHm2KnCl3JFNgt0dv m/H7EwBH3KjWIcmEOYP0hK7xKVrn7wnyiqKdU7KrRlKpN4pLrK8ZtR1cVUfvpmhlz8g8xtco KN31lDlcNsx0DnOjIQJYFeakuEuCAm88NKU7XFzHq2ZuD05PElOqZZT90JBITx95I06/2zN6 mp8/+iE9WRxMtNfKtyeIXmqGLpzQOJBANnJQj+ahwn6HHnTzmPlK4pnu/bzdU/MSkM0S4JHI FsiujFcevfYAw5EmzX3vRhfhYbA2EV0+5q7VL2f1OXln8zOISRlWlNRxsinFo9qMCjiKMFwF +HkNwT1I5kEKtbbjVpqwrLhRXMHksmv6vM8JIlyGAd2t5M+6LErz3KlIVXjoGeMTaKJT3Tay DJdbbzYAWGuNziIJjg4XzT5JFc2STNU+y6nUFfrdy5RHow0AGm82F2ngFjcGkZHZfVbuTViA +4wtW+xzep/BUkhkc5/t7Y7XJkVnCU/5OBEghrqcWAZeI462AcCvJrkxNmq5pGtTPsEz4Tfr O29Fd50aoqVrkiVYLjdU5umGmhS0ykfVWSSJG5djkOH/QBEU3HG8QAY2mQlzjJbUd0KRR1s/ 2lIGpaTiEZqtIYut76NOMdD6K6fK8kgeyYDUKvBcrdMoqPib73663TzXoqykZvV+WzTJ4dQY g8d+NkVNMYAYFRepFWOfkn/w2c6cdrYyRC784aa+0fKa2mUBOTAxpNI4NuodJykeyYqggoao b3VMZ1gWYueAU64OV30Vl/Yc4nwhKU6/biZHdtHA1HdAFkrWhN6yBSq1JcljW75fzuwE0/tJ 3TcC9ysH/x7WD0dxGcSHHwzDptxLyD0mpp3BrC0STIQtomwsHglMh86PKXLLoefnofUGer/t mUlvYJtuE8ONTeRRlZ2s0vvZEhMLFVLOMquijdSmWjNiGk6AG9/z/Wj2CZQS4P4ClVySV6Gj jRX3bkPlWYKe6kiWqqstUZXBGgGX6+2YBTgBdPDaJg8QJa+MYKtvZyQbLz+1s4x6+rsZDjIw qupkb+cMZxMFz0205Kqq0EO3E/DxLaIcqzYWN5CdsGLAzKsqwbmoYyPYdCByqc2gZsalA/pT 5qHO7Z1cFZrcNHR3ENaeaCQfRkcA8KX58Pr8+WlxErvRdQLSPD19fvqswnOAM8BzsM+PP94A KNY+UrlkzPiu8DTZjnI5EtDEE+dh4FPOgBCzbYcnoLxM684Y4I0ntcOahKoGOjZBSNL2KLcU NsWugKbumqhM2jn4guLawpbCrYnsQO1zNG/CD7ASKfjNstB/RWPdSojzuBb4Yk79NgcGQdbD baXzmpZJPm+TukC24sPdMbOfO4Fskj3RMjNfeHYXmMf4PaHjooaTLZRebr3s59kXAxr10Uc6 iZl+iYrlnblp6wlUu+P+lpNuI6YMZTVbogeYh9AZvKKdRCIUR99ULKjOgQXpLNwp3ca65Q1j na5yV5kfWKU6XLtiTjpYiTFIBlCGHoXq7/ZBkdz5TRvjch3lOCQRKAJN8kBJSYq6GLvscrHf ndBWdBQQtDVtyiAyUeOAPPfMAGq827u6lbKO3ehWM8sMry4BbZwBTmBuGXpCJ6cxjmLIB4ZC VGrMQJaBAw62snb97dyocGDflw64oZ7v2shLhUuKmDlqijMBv9hOwZKy2t6tEWG5Xa2Hpez5 r6/wuPgNfoHkIn764+e//w3RpjN8iCF7e77CdBPQRXIuPOUzwtDZp6a4ZPl5HgfVYxT9L9Tu r+c/n0Hg56uGqfnr+e3L959vC5k0lkkhykJlMnicvv8iqhazORExHAhESAZBe3anyIW/ZHfS Wu6gb/TlfudgqLh8l9SNaSgYKF1EEfulxuw8muGeQkYRwFqhe6Tmg3cTgGuQ+Q9Md1QrNCAG cOxJs4lkJgAziUMgC0l4DrNNk5gzS7Ey+TWzrd20mNOsg6QE0mfkY7f1KQuimQh50F58PUNN RwCKohM4W8rMjoQ3NwUerjH2Iu336TW7klpTz5azyNr09pigjS46UlOHNXxTgNuXZ4DM+WWO 3Pzr4u27zPxp8fZlkCLOii8kWqKBnUv4afTG/45EOOEixvZw+dzxFW1zVszI5TquuHF97vZ8 z4QLwBekKGvJGdsNz8SIQdx9UhRnEm1XMuu6Gnco/NsPOTO6HNJ5UZ2QNVcR1JxMtZZipilc YoTh7jQHvJF0sCAi63v0jijwU3NyBhdQ95wRDOUrXH70/E3uk/58RKgufSK5tiZEMQO9qwQ7 tU6uiOokKbr2d98LVu/LXH/f3IVY5GN5tcIhNT05W3iDFnc3Yd/qL+IKitcJjsl1V+rLEsaC Bprc/1XrdUAHIGGhkA4DtIS2RL0nkea4o6tx3/je5kYt7pvAd4RjjjLZ8egIdxxFbBMGLaH6 n+NGnlGwidjdCsOVkELhyr/ReLrz3ni3PFwGy9syyxsycj7cLNfbG0IRraZMAlXtB/77MkVy aVz3vA8yZZUUsPu5UVx/3nBDqCkv7MJoC8wkdSpudhJANaBRYYzvupTd/cY3a6Si7C1vdNq2 uVkfuVL4vsOdaRSS+0TnrKGmI2NhhUc5uWFIn4HYsayiv8ckAqdl8m/lACQY5cS1YJXDVjJJ RdcKh9QbBfE02ZXlkeKp+yHVhbL0eyRSJWkSGoBjqmEC2zvz6M8ooDxFh6N5e8/ES+HmZMid Lvucq9/vNI+QKj5zXREIAqyqskRV4R0h+dXX2w0JgKH40ZVVzK4/NAwGV8P0d3kiR3c6ae5Z tG3LZgXNcEP0mw+dwo7BdMqdBO0sPa6kwr6/Egmoi+NQJ9EUFYvLoiRi9AA0pXhlKeeU1IEV UrGk5ylD7LiTD0RtexHdM6SKGpX5ytY+VIfQWoVx9DIRwW5QAXAuijsw+GFY5eGd19JcFm/C zfY9Hu4ciF9LRch/hw82vC43TZ+IfZLrLm8jjryNTYndKfA9n17gTDk4Q4HbgXlUhEu8+FLS 1zBq8r3ve65yo2vTiEr5/9/MCyRX87h7Qsbq/IRkzLYedo1GXBgejlNjU+7A8kocuMP905RM EnJrh0T2LGOOvqN5ffd11Tpt7oIlhfGGhEY3KzKPfVnGnNr0mkI847K3OKq6PxUPieMt0PkJ 5pSuGqmx2l1Cz6MOU+aSzjEi1TPfD81dMOJGYo3cvxAzF76/ctUwn60kVJvl7d0p6xrhqB0v kpY7GyE/bnzKkQLNTkmhAFwdLRzLTWGzbr07mq9+1wBn46qD+n3htNqJKqJmmlsfK27UKbMF 4YBEpM7t06qZKQbTPhxuloKT12Hgr+wvN+HynSbgcjPk4otV6DlnMvll1fi8PWtIycDzKMVi LrWhqyIaPzBhGhGvDe/MG45QppW4W3ub1vUSD2lZR7dns6jM+K7m3TldU7Z6U7QuD7leXYLl fEcOZviZFfnw+PJZwUPw38qFHbud1FbAkA3CZEmox46HnulHqInyf3zMqclREwbRxvdsehVx rdcjqmwIglqzi03qHf0JYUnKbQQAnaSOgEkdb2t+hcs+We++Z3mC33CgdIVYrxFe6MjJ6O3Z yE/yk+8d6Q3qKJTmIZ6utYHwy+PL4yc4Wp9hATc4LvTsuhNuG3ZVc7Xhq6tG9OGrGaBLA2wA DZbcH3z0WcyIGmX892B9hz8Fy/pbIotY7gdpe1/5UDpudJZroqCDDmGbBSCODhu2fDMLBmti HPNktNuKp5fnx69zp6i+6gmrs2tknvb3jDBYeyRRFiC3jRFrkthA2yXkEIiZyYh0vKQj95w5 ssMuBShD0vnPECjq7qQQm1cUt5bflefJKEKWkbRNUsQO45QpmAp6d4leko6YRJVqgjCkFzhU GpxA0T3EFMv5uxUHyLseqWU2MIvv3z5AHpKiepJykJns0HZW0IgZvdj2Ejie1yAaHcPO9aNj kPRsEUVF68DIGCT8Oy42DmtOL9RPwx8btofX+Aeit8Ra8H5q4aaDmxk67mLu2XVFx5f3bNnp uqy6VYZ8SlqFcM/3XK7TDmx5Od92Cj6D3NpXOYcNd5zhmGtFrxhE6Kh4//+v7Mma3MZ5/Ctd 39NM1eYbS7J8PMyDLMm2Yl0RJdvdL6pOt9NxTfrYPvab7K9fgNTBA3RmqyaTGIB4EwRAELB9 Kt57i4vTdRDKLxwQLQfO6QAi8mUfR4LpeJasNdABA6xGxUYD8yzTxVqi3h7gMM4j2XVlAIls 9EmRxSS2904wEMqjvBG8VwMjS9WU9CWQFie48pYzSipEa1UinG+61Mp4p3d1R5ym42q4zkOe actibsbMx5jya6o53xIEU5ogKfv0SZbrXVuub5CNiHQJ47CVlms5WJCbcBtjnAWcNkruDDc4 1pLoiwA5SXUH4NY2bjOhUXgfnitOnDI2b/ZFrSNzRbELN0Px45YLN0PB9J4EgrAirVdd7az2 vJvSnerFyjib8SNOQzUQBspN2hNBYGXpNRmYDMo07yVlTRsjkvLRKUBy2CTy8CCUG9Ixxq0K 1lMXc9gWSJWbQwAK31nhCv7x4/388uP0N6x8bBcPX00cVnyOq5W4dYJC0zTON5bHUqIG+xVW T1CGwdKfkiEeFYq/jda3wnNXKbHLVWLJKy9bhIdJCPpsTm/KPPDcxys1B2IPLkPqueWIDeTy B90LA9eNg9rxnStoD8B/nWmeF544vuerA8GBM48AHnVgFs3lMEgjrAU1fOEaGHwZrQITxdjD IUyOJCMgmbb8yiQ5TlVQzrVilwRCa5YLrZcsAe1q6euTAeCZR/q2CeRydlTL2cshDjpAWQ1Z AnHLUQ4YvLgwM8Ov8l388+399Hj19WNMHPbbI8znj59Xp8evp3t0iP6jo/oEYiHmLfhdndkQ HdI3it8kgqOYJZucR1hUxT8NaQYB1wlULUDDroJrUJtIdyykjLN4r82U2dRdnJVysiLOt/hl qV4xbA9SbFaJjoH+Hk/BVzuPMqmKac9q9aUvQoVIacxf/Dec9k8gnwPNH2Ir3na+6uQW7IJP t6lu1kNkHRQMxDhTGSjevwvO2lUhLRW1eJbCEa+tfAR1IUzNORR5vCzW8pEE2dIvSLQzahR7 SsrKriY22jL1h3I2CQMUSyT2NsTE5OAfZ4yaKqXuxEiF22DIRVGWzDwpSzXFTlna057lddmR D8V1dZLFtiDlYQS0HZeJ9Eo6ZBollqTgEpF+9g3VP2Aastv351fzQKhLaNzz3V9E06Abjr9Y tL3QITuYicdJV+hBlNty3kueZrf392f0P4OFz2t7+7f07gsNgDyjl7BTgAaEHVHePpGAMSVX BwT9WGUUIluJEmi9KwmjSuNFmCxL4aokvmfXTHaw5bAuKcEgz4hMAY+3Ly/Ae/k0EEydfzmf Eo/rVBKhtF7AZ1FJy9diVA5BSUmgcsMJDi7QFTEAiXqNz2HpNWjy6FxgqwhGLVTfwHPw/rjw qay3HCl4plb7zSA1lrA8P3VjjHZlbZzlj5wJCNH4tMqZGU3ocO2UuvrkFOu5s1jo7Ujqxdwo yxYetUd6jmOeAXiG87af/n6BDWS2vvMpM2rr4NaI6B1RTptYOJY7OJHe+SNajVMiwy/XzOVm 8pjs0OuFPzfLZkfHn5ijlK0jc5SI8bA46ImtwK+IbQ36HOQ3ba2mXeMIIVvYPuucm7Tlwa9l luotuYywtqJzgzK+M6/OdKxs+e2By+V0tDEkv1hmusTNoat6cTTWfhdEO9LgWdomxVYDVlHo uY5eBCvw3W3KzYbC4g3n/PPrrzdDFpauxyaLsbyDEqzo4KDBzFg+zifMrst1oOwWJGHNwdnp kuJx78KCNjeORBFzpwtqBmUS55Bp7epQ5LHctY/9uP0f+RIFvhICGEZs0ssTGEZfKAx4bKw6 XAoCXemjlfICT6GQr07VT2cWhHorqKA8Ss9WKWzVeV4bVqGt5PmM4mEKhZz9QEU4NGIRy8mL BszqiztX3Aq4hZK/sEyVGy8ZfsGtvMT34khK7e3ueA6iELSkuo4r+TlzcFwsXV98rAwMZxUt TmpD8/6Owlat4CZDwR0Us/zosK5Rsp/UUEmPE4NPVKMQONZPqY3WE7AVo77DOTrSmU76kntv IRMuskIYZaKzyVwzndIkRLEdVwcKOZwIahkbWCOml1mPgUPSn8zkTdGXWB3VsJ79F3xVTGi3 r56GcLXVKNJyMXfnZnt0H0WpVmfqz+cXioQ5mTo+0UeOkKPkyAjXJ1qBiLlsiJIQcBZPqBaC 5utNL7WPH8yuMzeHehM0m7hN69BdTsllWtX+xOJK3pde1cspKekKLgF6ixxUTgIaQ67j8J+1 7QpJJuYd8OkLKZnun5YnRPrLXeqIiFscQRTI+XT7MFnyz3afRDqoMzsIdU3cdt6+g9hPXZd3 2WxWSd1smkqKRWagPAIXzafO1AJfUPAMnTrl2VJR1AJQKWa2UpcWhOeQiKU7nVCIen50LIip Kq2qKOrgVihmrqXUub3U+cXxYOF85hK92y0wFCJV6M6ZIOpCoesgc/yteWSOaY/KNNayV5pE PMLNZZL6WNIONT1FxGZk2OMR75C9jzCWDcsyAsOPtFacMEZ9ib/DaL2XxgbU3Im/pj7mGrC7 pqxbI4nvzX1Gfd256GHLLhUA+nEWUd9vUt9ZkJm9JAp3wjLyYxANaeOJREE7ZHVobgIIcnPA t8l25njk8k5WWUCK5RJBKUdsHOBQmcYHxxn0J2RlaID9xbrvrBUa9HM4dakCYXtUjntxefL0 GJvYLFMckz5VLKBAArjESZDCdXyy1KnrEiyGI+zVuZZXcCrNpSahZDObzIg2cYxD8GWOmBHn AyKWxDxgxrCZR5c0m02JbnMEleeNI5ZzchsGR8+ZLy8PCKjX3sTyWG2gifO166yy0Awnqg9v NvPIqcnmVFBcCU3PaEZKmBKaGPQ0o/Le4es/uorFpUMJ0OTYptny4m6B85hqw5IQOgDqu97U UovvTi9PjqDxL9KU4WLukRqzTDF1iaWa16GwRSRMCdEx4MMalj7RLUTM6WkFFCiIl3gwUiwn hCTGjYhL6Zgs1QdXAx0NRgnKnVP8JnNB7yKEMc7eyGVWh96CYl0dAyEaDxh3MvdJeRE363RK apsSyWK2IJoCmswUtFCStTdhtKSj88kULn3Q3KQzOpTLMMyHrDsqjW/ZtnYu7SzA05IzIMJL DJq4mh8koix25t4llhGDbDKdkJwAUK5jUaQlmtnBJZ+xDM3LWDidZ4Qk12Mo1iBwK486LUBO 8jEIlB7wS8FTe5cjPGJRgzg5m5EjCCKb4y6iheVR9kjGnIlzmekAzXzh/qIcGM+Fe2k4kzxw J8RJifAjIU/V4ZzYefU2C6nTs85KULUscIKpAVxkgDV6gphfHKOyTegi4T4J2rBsdBGPopst ZlQg4IGidlyHWIr7euF6ZD8OCxDdHTJpm0SxdCKzUI5wbQhyz3HMJS4BBOl84dcELxeomRJo d0TBhtiSqo3AxVvKo2qg4eZSotz+1uWi886wuNGfzjC5EqrjbuI45CMcPHcD2cFRAHSFoQer udp7KKbZwqezbV0lJeWC3xN2rrvtpsC0knHZHhIWUyXKhOsgqYBlB7YHlMQn+MalNTKdXfyk Mx6laRFiqsGL39lbRRBe7CcSYOxQ/r9f1vkPu/X/7Q6G+uexFWl/Gn4zx4qwjWrWf2Oj9KaT 469oeHrJ7UWqL/hGEx1yWuRQ0I2gIi+kDP/uHmI8AB4QeXEIrouG8ioYaHp/DBGu7Pb97vv9 84M1zgsr1jXRlM52QiNmng1BfSGuXi+DhZMLpsoMRSamoeujbtXTXrrAoWgkCn8iN2T4uHve cOHjmySp8K6L+rrL0XK5fdHhUvFV7tczZ0GMUn8mEhj+VJNsEeq83vFih6q4bohCg/BLg1nw DpGSgX4vQmF04KGeIE0ydIBFOFEHoucgBqmlcavaItbLYqUPojSIJ2RU7VXYrpO6DF2yv3FT FX37iK+T1RwHSq0PDVJkvt9DsAbeo1PPvMkkZiu9hpEAk0HZ6odOqWPAIUNc9lL3UUfjlOOu rcUt5mpx25KYSuGkoXdkWwKgzfkLlrCIEgvfZqGI6mbpLdeGHc+Kz/f6RA6o2cQ6TiDS+WrH ePDvzk3IxHjz1VwfChQNFUAv6hjQxXy+1kcHwMsOTDY+C8LtjRWLqzQuQQ/xLvOCMXW7rSQM Wj7xFvZ2YMAL19HxvVvLp6+3b6f7kfdjMnWJ5eMr35A4faJaidLLYLmXBWPJSnJKeX46371d sfOP893z09Xq9u6vlx+3T1Jae/hKLYJ1jrJyqWHCE7hJpZtYFdjHwV1VSbQxPsDHQhdL7Am0 pkVJceGzHq1Bk1TJA4sw8dZnCMZLF6cSkTjVuVDE7tVmYPX6fHt/9/x49fZyujt/O99dYcpB KRd6KL885UXw7LBGwaLjYUK0VsFTYFaEGnjsnLyfZNQGg+6GGS2mKYR0nHhBEksB7PgrmW8f T3foOWtNm5CtI81ZHyEB8+aOouD1UJeyu4EwF/budFpBQe0u5hOqCh6wZp3Gx1D1FB+R2zQk r4CQgsdmmqipJ/iXx9Kd0A5ZvKsV+rxbXKGxFyinkU6IA1Z2A8EiO1lQC2MxYCj1tEfOiKLk tzEdzPG1UcUbsqNsvpCAWnwpQGyT2RS4IXZAOetqfB/AkpC2WSEaiqI9GbFYwae/NEG1Ix5Z pGXYef5KAKa6Ao/aB7btYjVpyZg+vCOG68q//F7drojjLpxhVigh3hGhPw9BGPe6mUwooE8A Ff8cPj+dz4sBnc9ni5neOQFf0nMzECymFwkWywllzRywrk9Uu1guL360XGg9qGeK3ZHDerVE BaNYrUIkhyVJfBIwywXwgFYXHC9/8B1VOlXV7GhJlyXQ6I5jfBT6tb+wD2+1AzndVqJQWPQi WRza4lxxdDKdz44Eq2SZPzGYMQdas4Ygwe56AQvO1ctSUzUFq6M/mdgf5fBv6qy0Ntpw1Edo nbRB5nn+EYPY2OyVSJiW3vLCGka/Mkt0VL56ghTUFNr+UbKZM/EtwYN4EBzaaEbEx+E94nDy 1m5AC28w8zPXYg4fCBYz6sQZ0EtH4zq9UzgNNU8AwADnkl1/esVZN6Vw6g4XNLaA1UCBmc0u r5pD6rhz7zJNmnm+R13t8nYMnvJq8+jUUojiz0MMiYDnjw7s8RCxrdliSt5UdUjFnDvCzJHW HetHGEkr/O2HplTxBq11FpMej4XeK8SGYrN5vX35jtoH8RA62FDOHvtNgM+jJe1QAJDNA2Np GCa8HspAJDuAao65gOllERGBRdavt4+nq68f376dXjsrmyR9rldy9zEEPX/hCR2lpI71Cg5r TG8q8UeA5UWdrK8VUCS7zcLvVVFgnjMWmJltsFD4s07StFLyg3SIsCivoU2BgUiyYBOvUvXJ dYerML51coxTvGlqV9dkpBSgA+5J14wIsmZE2GrGjOTJJu9yfl+osVDyua3QVh5XVQzCUqHA t3HYrLT6YR2Ip3RyzaC8gBRFBlzC0Q/CXf8CVfoGPugewKutqUGFxN7VItmIuYy+90/UidsT nICkqiyvQwFbZrRLK354vYor1xYPAwhs4VsQBYovDDpluOFrhdX6bMFAOlSsRkA1uFR1cgDR 1PlUVdVw4ja0DxugyKjQ0vw6kaZbYA08Y6hWhwBa2epIYX/LMNIMS4RuFai+evUIulQ5x9ve 2PZ4eWXKHydz0pUCMGkM4v58oe95OGTSFKO+5WQcSL5F8KWQugM4qM3wXVMuEmqbSAy/+6WJ jQ3HsZa+dVhNJcVOBxGdhB5XcH3tuAulDQJkHaWgJjPpwSLyNErmIUu2EAd7xTNwABHt7xBB GJIJq5AiUZkJ/G49WWvrYY6vbzBLGk1cpHEBLDexrrXddUWJJIDxovVRqwdBZg8MCjqIC7az KKKi0Hf8vl7MXEqSQoZaJZFilOOsbKf8LjNP+Q0rOtMP2g4G53yQtfFejUOrIMOG1QV1q4ej nymJSHC3rbJ2c6ynvjZP+6SqG7UWXNx91mXL2l/BQGj8q4Nxe94m0hdVj73ATHj2M7aNyRyq OJpN0e6c5USttodO9H3TwSnHFb48szLVNgQDriyHAuXjOHeUp0PdJm3TMDLFHASGacBYF5tL xZjvucfi6K9G/PiY3fxUZouK5XMgKQ/UMhnx5sOrHkNYMEYkd8ynbalj1SB/Tx3QUyzx/kZK FmyDijp9R5JBSaAaYz40pmgWi9nEWsBiMb9cgGl0knpKWFmk0oWN9hdjAKrazJtcHgROs6Rr AVXe9+kndkMzMVhaFVA9kIwZRNm99v2LLgir9i+IbPb1sSN7mMt5WlLNXEUzR96mIONhSkt5 txUbNccX/EbveMzuClyNqFmi4CKj5eswbWrXpaLHsaLJZbcq/NkWjBnKv4ppMQBoGiSWmIw5 6eTFSygxvxpRoVkXD3+Kfg10HZwmygLyqQJH7rNEzkbdl5oczboyRgYQFbiy0R3zRE8s1qUO e6FE5Z6PQ64zbyEzbAHFaI6zheJcyOFBHLHSkZ0vw9lMSZjOf2N+BgMWRninOKWgq4DFf07U qnbBNm2GGGBbUL2NYC7bRHlpAz/HJ7V1FeebmpJ6gUwJg9xslcd5UIgWCIXhpd3tD94GQrfD L4KpnnVERYdVQzEZjitLNewoBzaYG87yxSpOd0muf4IWkIrOhCPQCfy6gBcJWSxVwohtirxK 5JQyI6xVAlsCeZwxE5bGSqJWDrvZxdf62GerpNInZF1pX8J3PJq3Pgq7a0oAQ8whSOui1Mq9 rrgXml4K5j+nz2nE1ock3wb0nahoW84SWHykSoMEaag9QOfAOC/2hQYrNomecEaGt9FnWxU9 BfwolWeGA2a9JnuA+KrJVmlcBpF7iWqznE4u4Q8gmaZMo5DayJUXLU8Rh2NSdHRx07sNRxFs 7phS7zgaI233q0KCg8SppmpEIJzq6A6YFhV1YnCKuA4wIpBaWInBa0OD73RgkICty6InIY0K JCX8sbWtp9Dyn3Ic5kACXSSxhFjlNHAWBjaOxIKEGLBLCbk4vozjyJr2klPUuB6As5JWHk7R 5GUqP3FBYKUEScNdiwH8AyYHIRxABtthGRxlcBx15Y5npQS3L9E60bck8BAGHdVHB3OVbmiZ RKAr0D1F6BQrEc8TYuNeSZIVtbZRjkmeFXpLbuKqwE5ZCsJEnbC9cm2UuNt2u21WxrQLjFCd u1+GOZ1H6KROaB5NVD5eMSlGsQWFFy2padwZhVW8oSXybEzoa7oNWLtVN5+WJ0rkgQQYDxU+ ntYDvPz+8+18B6d5evtTiU8ol4hh38hpyouS448gH+5JCsSKoGC2WICcIog2pNbeHCQJDX60 h63iHqDcXWeh5luThX+w6A+e0RXdx0zHYfxkpYbbHUDAd/OiYn8uTMwKJLJQFcoxDpke81v6 DsOsUM3aYojWcAzRSraQRVvVJWkAWsNZjhS60wVVSFqvqY2GFIcVi/Sq62QNS59Wx0WpIC0W W1tMayQJV3PyYhdx6P7IImNqG2hsMquKdGK0p2DbZGWP7Yk0WU0z4gxkM0vmtDw+aNnj8Zew tFCwdg3/3/azjPYKw4+LE5s2AA5ehdnMcxWb9Qj3KScGjuaXsxOtLFTx5RfGHChCt7lGBR3c plNzGs1tiNeBTgFTA+j78is2tSbEWt5PjXjKPDpgZ3qn0GAhGyp7oGal6WYp3mOYOzIo7TgU /pEcohnpcMbR3T0zGhHUU3XAkvl3OFY3nYn61DBjYh1ErvaeVsV3flps6pJ35GJgas+Xnydz oOESyKFjCia1Gsz56pMOSwKdhv7SOZpDiOvU/9ve/MEZyU6yqyN3tnSN823calffnl+vvv44 P/31m/M7P9+qzeqqMx1+YOQ5Snu9+m0UWX7XNusKRbhMG5vBnWaovn49PzyYW72uks1Gy6Et I6wh8hWiIo/ZtqithWxjOHhWcUAdPgohccWr4MOysVZyiTv0NP1rrnFszi/vGEr27epdDNA4 D/np/dv5B8ZEvnt++nZ+uPoNx/H99vXh9P67LH+o41UFoEzSOS3UrgQwsMptJF7moJNwAqIW pTLFIAi2AUh1CbpAVo0keHCUIYYhVKPpUhT1r5eGujnSds3JkVlGlRfPffeowZKFu5yrPErA PfoJeId0ZbOUgMWeY0KP3sIs2p9arts79KWa8UmMXvNcueyr6rDVvBUQxA9VotgoC8Q9h5pe aoCaA82XExCYri0ABJl7o9yhIay71MJIX3kOWpqKVaMNI6SQ1CxMABOL3ElD6wRzTgCqpg7R CYqgxnaane6jc8IE4RMjJTVTdMDfoeaT2EFNMuFgO4xJOITKHrcKpiVp62NLtwWgnTzb0zfH KGGgaEvGq0YWGBpM7SAnh0FAGVV7tC0m1RcVEYFQRiKCOFQBoD2HhXqP3YgUcL3RklY5gCaP a+o855+DcsrUirL1TE3ngQukc/Y303Dsz6/v52dKmcLPRAPJhnVoPXS0UBvOd6/Pb8/f3q+2 P19Or5/2Vw8fJ9AeCE+y7XUZV3uidyChbIS/zqi5YM4acp9VNQOxYNGvlQTa9PZ++3B+etAV yeDu7gTay/Pj6V2GPt3+eH7ACOH354fzO4YFf36Cz/Q4rUE0n01mRn+7z/tvv54/3Z9fT+Kd hFLQUEw992RbfAfoHBREjbcvt3dQ3NPd6R+1yyHlNo5w5Yrm8+ls2FO8lfCXKJv9fHr/fno7 D8PSIx5+wnTePb+coOint+dx3OBk/M/z6198AH7+7+n1v66Sx5fTPW90SHYcZDpvkEbOD9/f pSL7ae5DKrDUXU5Ur2cV55LZggHlq9Iggv6e/22u09uHp9O7WAv2dmCshsWUiL7QIeRZC+54 IECMb//w84oXjIswCdXZiucLf2o0pzq9Pf9A0dA235yql9+uPuEaf7qHpSc/CBMX+b7q+HDc DHwUhMrbvz5esGCo7YTvmk5338fvlbyfcu5vtOapUYHEDhVupMSeuH99Pt8rgQi6D3h2BJKp HBLuKhplc9eSc22dVDFmiWovZGSPNjnNTKMNefO3AX243ATo0zmOWlhdlzWw7V2sXtg0eQIy EysD2hoo1EkQCHbtMc3xFnV3uLH0NisYbUk+LmaDB0XnKEFxvXBbFdmY/UQ6BwSmAFUG5k++ OhkQJYZPko5gaCdU1KZFsWvkqxZ8hY2dKasYuix/MHR04FjPj4/A8EKevoH7VyJvkBeANDjW cOISDV8LcuZ0Fdc/c7EgFxPFfiChWeJ7ZBg4lUaOvKli5hMSE0ZhLBxICBxDP1BQWyxtsiUi lEg0zxaS5EgJQVoT55PhABhyM7GX8xOfN+24FJPJnj9eqbd+UGK8r1HM9z1lKa3SaICObI+/ wSttd/NboWG2YfYLgqxuLFkNe4o6a2gVoMvPB5yIfLsTJOmqUNSVMqSc5ro0jtlK9r/svu7t p6O4DKPfWL3sq9Pj8/vp5fX5jgzdUsfcrTlrq7IqzLzG1cvjmyHiMCD8jYmkTMUTT2b2+/h8 NSJqafJj0rIqsHhmFGhHJVElZ0/rKqbTMMTHOrQECgG5uago3TZRMithAoBmvdaSRg7QNqQC iiJ+t07WnEotrNO542gsVsKKf8rZVaRvDFLWwFICTsp1fUHiyiTsIH1KC59Dl1ZZ4NAxyrMQ JDvh3jm2QIaq70Ckix+B9SK14azuEcExYRYcHvc9fmjj7hh+3jkTx/K6KgvmU9+3uJkCdqE+ HcvQfOnoj9MEVAfIL1iPISj46pucYzhzfUvwr3oH54yFXQBuFahi8/9XG3CX1DkCiKX6zkg8 um03pfXtWnB0vJllaMPSm5LvpPOg6c65DjDGwkmUSO8jfK/F58WXdVE4WThkikcybDx/reV1 vRnB+/XMmXThf8U4Pr78AJ4jHyffT4/8Co/pwnYSfFGXwv5GPNUS59T5vvuE63ZC0lC8ifpF L/amGphOQ5P7OWOjbjGK8yDn9fXqdXb7Rf2IxnUdU1QqWFy3YpnZ1pY/sdhfAOUtaBsXoKZT 6g1INnM9T95+wdGXQ83j74Uc7hnW3HTOZZlBo77/eHz82R022jhwB+M2arJMyUCh40SOX0qU NSgH9ty91jn998fp6e7noKP+L2pAUcT+KNNUFVY2fXKxP6Lz2/vr+esH6uE9Tfn99u30KQXC 0/1V+vz8cvUblPD71behhjephn+iCA8seePMJjKLxt9W5ry5rgrBm9XRqjsMMl/a+lZvPO3a RGyR0+2P9+9muzCQ50TYNQXdx+P5/vz+U6IcudS2JgOtb6MQSlAY2haEMEt4wWQODJqy6ADC HdqRwCy94+3G4+n27eP19Hh6er/6eDqr5r1ddiSjIyf5Hn0sZxN8B5kMafZ0i4JkUS+Bz6XU 0guizzArnvrkKUhhu5DOyUEZsaViE+aQpTL3W0fRwMPMcx05zQsC5O0Ivz01bQ1AZjNSSdmU blDCQAaTiSzcoEHEUb3XZVkgtXsUdSSlLe/QZxY4LpkwCoTSia9GTU3ryp/QC6Moaxg3qktl gNG+EanaF3aeR7+pDpknEiOMxxiC5pdi+HK7kBwMAwBTX4062TDfWbiU69Y+zNPpZNxGFtPR uIB2i+WclkmC3WS5JPdZJ9ZlwSaXWfMGFueE5CJIGdeg0WNeJ1nSy7LQ85UUDB13wS8soh9H yZJft0/vfpyf7B2VD1eeIHxojc1TTBB3Gd2rou79OP+JdYuHp686LY86x3mG+KopaxrNr7t0 sbzn7i+giT3BYWGK53ga+mryKHGavJ7ekHlRA7PKSpcU6ZU9F8vmezj/HDmEM/z2VADzZ3L8 VPHbCBUDUI9+u9BNtc1huPZFMOKRmT6h+VKz+pavz3+fH9UzpN/+SRRU6CEWt3LOXHZc+uPe qU+PL3hEWwYuS4/LycyhhZ86KycTSsKpYWpV/sEhLm16y2tKcdxncStlx4afV6vX8/0DEccR SUMQ6sOj7LyC0JolznShlPFMenTtswTp5yLcy0BtRI4cr1yAGqN6WlpeJoXUFOGXMf4wb3p5 sGyWtuua1vsR34e5+QUBkc5YouEuKQtfrxvUCMsHgMErcmnr6tlRgyprN0nITYR59acjzzqP 02jLDJmUAXrFkU6WImMQ/KirIk1Vm8M6M60v6GrIPr6KzNbjvA45TbfSHSNmo8Wkzu4izzDD b2hBNWwlP04Ls3aHsSYQbBa4TWZwbiJSgqN/ehhIYyXuY6ugVAN9hqb3ZXl6/fb8+sivb0DZ OYMQbTqGVoHEseptk0dxtSrSwWeQMPwHeVQVCb0T02SV76MkoxZPDstaTapSU2Sig/VW73K9 VSM0DdANSZuxhiqhVlOH93D65h7vEfDm69v54QM4HF4AMn0AkUa6nYFfbbap2pvr/EuPE2Wd Xx+5cdbgHHGkKA7wsy0s3vxDCAwYSfrdE0/oU60Ud5oojFaWl0pRlpCxNACupybmoDDIeRxH fMqbF3kbr5N2HaRpl/JxHFgWsqRNVusa2ky+BdsUxQb0w75H/TBtnp8ffpyo0RrK7r6EIQAA K9SHnN1Y41UY38iyy0UIDY/bQ1FFnU/O2Ln4WLut5jojQO0xqGuKSQPea9dqGQjAkIAJPuFO TRSLw6ZK6msFM9VLmdpLmV4oJc75LVciG0v6TxSc3MWp1Tvo8ypSrlzwtz1iAmuzFR/fse4q TuB4WzNtXAcwEJPurwMBGsnbLu+6+fmFqfncVyr9lsdz7JM0mpZyesdu9RsUc9F9lzp4jlrt +PtLA5KxCiIbhAhLsjxEwU6hDfDHtT1j/GbN9LVdhAJGaS21OWU9bGwz2YiBjM8sZ64by8gO pFWTtyzIgYpftRDV2rolsAGD1SBd9OZJOnS3X5uu0SEOwknUxkAloFaYSiE6So4jtjyQH/xb tjTeIymtTYC38Zijcu6BDA5djPx0bcGvmR7mKNIBiQBwmVP6MNDp+qU69JQD0G0JPVKFSrbW 4tD30koF2I4el6rm8SMQtvkU2LqKJRbyZZ3V7d7RAa7W2rBOTQgajstAcRarizWb6kuhwXeT 1AwW+7hKg+t2jAcf3t59V+JTsZ7ljcUJEF9c9LIQ+C1mPNpUgRzVpUMZHKdHFKvPcViDjMXI ANBIg6tD9hwYYEOpJkZuiuhm9Kkqsj+ifcRP0vEglY73YjmbTehxa6K1sv/wd54OgxgV7I91 UP+R11rpw4qslc8zBl8okL1Ogr97F+CwiOISI8ZMvTmFTwpMoor5Uf91fnteLPzlJ+dfsirJ N74pTL+dPu6fr75RLebnlKaNIWhniebIkftMvSHhQPTvltcyB2Jv8MlloqTI4igQxNKokp0q dnGVy0Nj6InbZgM7eWXhex2W10n6HuBfBjvNQNzjjAlqq+OMWhTAPkDw2slUcgl5WNKLKZdd YOFHP4/K7EnofvpbmH71wwEz95Q4jCrOYuVTiBY+fV+jEZFXfCqJb23IwqdNPioRmXVNI3Es w7CQn7RoGM+KmdpbPPsnQzejrD0aydJax9L75edL2VSvfWzr8HK6tHV4bnQYeB+uu5byVlS+ dVw19beOpGzGSBOwMElstdLGeJmCvh6XKeh7aZmCihMi4311uHrwjAbPabAxzUMfqZdYCoF1 UsikcEiwK5JFW6kN4bBGhaGfOhx+8lPYHhzGaS1bekY4iERNVeht4riqAE3BEqNgILrGOEgJ dWXfk2yCOKXqxvfWO6riBFobkIr3QJE3SW3pfKJm3etxdVPtEkbF8kCKpl4PhtLd6fXp9OPq ++3dX+enB8kfFSO6oDlvnQYbJj1t4V+9vJ6f3v+6un26v7p/PL09XD2/oNFFOWpBwtxxvy9J QgBVHvdUinaBfTwkd/pzKukSGOKz+zqCoaGUkug6D3gYd/ktb/j8+AKH/qf38+PpCsS/u7/e eAPvBPxVauNoVeEpxVFzpR2pcp4xCyVkIMU4OkFtCTLVkWYNq6368hpEN1Han+5kupDta1VS AjtBa3FGn/dVHES8hoDMiNzkIB1jFOdsVaSqgIMDXhxy0n4t+i+LIVuoB92reB8kJYUTggaO lgkUIzJMrCFJLxpGjFmRp5K+wh+kHwJQPMRAlAVXUWTxUIbrla+LCtMPxcGO+35pL9F4aAwU olQDtFICilzcnUtcJZ4en19/XkWnrx8PD2Ltq4MWH2uMS2LxpBNFIiFP4HWBRmgDZHgBdPPt 2pbFWQp9U8yBCsbaLdBgQLdtmIi+qH29py8ZOqR4w3SBQvgLtnpoJ7P9vBGoiK3T4mA2Q0Hb SuILBLurLT4JGTCV4XWlb7V7B6G/4Mxeoc/Jx4tgBdvbpwf51gyU86aEMmqYH1lkB70jsiKR QZUBRkeUyEpgxeE/oWn3QdrEfzomJcZv+VVpOs1QmjQg2F5QD3Lg4QGjVs3hC5leShQIe7go yPyACr6reKIikdsXTS0FpoKZjHSNVgA7c6EM46q4TidWd5xHA0vSJh8r3cVxqSV56s+xzvFY lCwuWNFdadj2V7+9dU7Yb/919fjxfvr7BP84vd/9+9//lp76irqqGjh8HR9l1b1bglC/Giai 20A0+eEgMC2D/VAG8sWIIOBRJDhnUTTJPWFSQgCcTvLI8K+x01amMX6kgPvXrWls4rqK26BM gN+n694MKNcJOwVkj7hVX/+pwoQ0wzi3HEmwPcE2rR2AP3u8AVMCbIl2JqoneMepE5s9ppvA jfkNt7gl2vs9jSasYgzKmmiuPsJPPGyU80WZR0BqhggBhKO+jFHOSCnRB1/AMEFnnJPa4I+y AxDLOMqUDyRwouKMpOmwj11HxhsThcD4C2H41YZIhESB4xS9T6ja+3Fu46riDi2fhTihiLZx jS9lSFLa7iusSH1ZRLUpjHIeXisvdYaoOf25VSXATnlST4zjLpgQM5eKhZAS1ZhgSN3KN1+N 8+Nu3eRCouJElQ27qYJy+49o1qW2KcXh3UnS635y7cj2kNRbTG3A9IoEOguLBmQ7EJILJRod kqC5jC8spOTr1igE9lB1rQHDrjRRtM5PQpXfVvyNm/a8QAJybnpo2UG+pMeSkIRITyi6Ze7p jyeuYdSnt3dNakx3EXlRjuPOmQ+c32odq3EVAEO1bs4VGtu16ROcejYdWLGE4o+zqyCJZjoj xpZs42PUZKUGxQWcb8xA/hy5A2wtv7rhUK6lrTVgBZtnyzMN69wtiWIeycrxllP+JN4iVa6a JAWhoQhZpfhX8Xf1ZXKB3fAG9BfVdorGpleC6KnzThagd7RVeBdS6SZSQhPgb+KDgbU0K5Bi xWVachO3WipYjr30ObBBfP6eMLGiZYedjgsJihHMvc9IDD557I5RLmbKjxDjoEqvO1VcbqAM b6MVmZOEP6WscZlpT01GhMlDqyIKajKcQNHAehKmAlP+S1frtCGNHeINmHFN0z0Nq23hO3Fi 8YG9hT9j/AFcQG19Xcbt5LiYjAKvjoPJcWicWITS0yUFmxd5/KcnN7nDYnW0h9VIEVPWpAHf VfyT+BRrJQWk/kZGaiK0XD/mueUG9RRaXgpL+51iUYLMgZsBpOgkV8RbUbh2PHTyWZYQ7A+X 2KB11nB+oWCzld2nRop1KZkVywZ2JGesqmWJne4+XtHv0rBy7eJrqVhknMDloamIQHaqCAo1 RjSMeSRWatl1nh8dgcKDOscHDHvBuL8c38zkIF9wkuhRiq9QN7VjFUo8EA3757+GK5wjCF9c rpMKE+eOut8FDHX68lqHHmW1WoDKLzpEHGMoB+xHlHglPlj+Xn++vD9f3T2/nq6eX6++n368 yE9luiflQboJ5KAsCtg14XEQkUCTdJXuwqTcynKHjjE/2opIcCbQJK3k7TDCSMLBpKrjSrxl p6FE563NDmxdrVhgwLIgDzYEbQc3S1ddHlTqNkoYt4BqemdHtVk77iJrUgORNykNNKvHi88v TdzEBob/Za6HzAIPmnoL+9mEw4LoRCyzA2nT51FCBtUv7uDj/Tu6x9/dvp/ur+KnO1zs6OD4 n/P796vg7e357sxR0e37rbHowzAzKyJg4TaA/9xJWaTXjicnwuwDMsRfEmMDtjF8BOx63zd2 xZ+CPT7fy84XfRUrczzC2hyHkJjcOFwZsLQ6EMuZqOSoOit1UGCyh0r1zOze5r99t/VACZbU b1kKeKTasReU/dsH0B/MGqrQUx8VKAjhBksfrhId5Q8goWGUUmqjALJ2JpEchEnH2D7dkNxM Wkx6O3sUP4pn1C1mv8OiqbnrInN9gi60DUT8K5M1ZZGSEUkCqzEgR4TrU/fXI96ToyH2W2Qb OCSwZYzFHlERIKEigbZXB1S+4w6FEOVn5u4QRVNg3zEZX72pnCXBD0uKmE92yxdCmydiTQ5H 8fnluxqroj84zU0NsG76SZRUtD5uQd6sEkqG6vFVOCU+A3nlsKavRTUK4y2zjre0G2MKpmli noQ94lcfYs+h48H++M8pXTspXkbSPUGcuYs49HLtrJ4RQ8vh0of2IY6IlQAwr42jeKxVL3/N /7aXutsGN0FEbbEgZQGZs0clsHa4OxipPneoX3a5C3+uA6tSSealwmG7x9aJ7WkuTJREYi2m js2FWh8KXOA2uG059WhbTQq69Q5yHECNRunUcLOPL/7Ee3J9GkDgRUOuffhvRORITXq4KQzY Ymoyu/TG7A3AtsNJXt0+3T8/XuUfj19Pr/0r+LMcsmBgWiwBVZQS5qNqhcanvKExpIghMNSx yzGUZIUIA/g5wfwvqF4XpTkp3Fgt1CZ93HsUb4R99AcyNmoO1qIqS7oEnQ71MHuV/HxS7xd7 zIGoHa8VyoDf0l5iW3sQpk0FqoO3kbnDe5T4SaK/BLWlQV/QE3a7WPp/k6GQNMqwS/VpKymc uWTQL7q+vSkBKhVx/KWq9lR2CFDnM8z5l4Qoewsb0k8CWTartKNhzUolk3Cgt2tK59GfLNsw rvCCCB11Wn5Vpqy3chey+eCGJPCGBhBihIRvXOF64+Gi384PT+LZLHcrUu7yhIusbNupFOuV iWeSFYWbGnd7SR/rXDKSGyPNzirJg6qzu66NRqfnr6+3rz+vXp8/3s9PsvIiDCiyYWWV1FWM YUnVLEqDPXvEU5cRvGGBpAP0Dy9ZXeVhed2uqyLTNHmZJI1zCzaP67apE9mRuEfh2zS07INA s5Kd4YZHn2GCZl35aqdHWcHS6sNe4/OCMCuP4VbcZVfxWqNA4/saZSqeN6dME1WLD2G3J7Vy oofOTKUwFSxoSd206ldqCH6htPV2Tgt/5CSwN+LVNZ2kXiGhH3l3JEF1sJ2niFfGH0CS0ygc tIMGOxIokUQxGX0thlM8+7gYhrfCTIKZpfcdDZzavCj1TT9Co9iEozCAZ0OqZPPj0E6QkLpz UxAlI5QqGaQCkhpkBRpOlnK8QbA8YgKCIhH9oEyg+fvjkjoqOoIkUAXrDhxUtIPYiK63TUbn aOpo0CXhQsWr8LPePe1WchyHdnOTlCQivVHiWY+I442FvjD3PPenCRRvripGH6MiLRSpVoZi qfI2Xsl+jyu+jnPWX3yMmDo+1izGhU7B2p16ATvAVxkJXjMJHjBWhAnwYc6wq0C5NmfI8OQr PgHCK6xWYYT8KlEeVPFGjiWbPEBXEWlYv0jcPk/xpR3BGYcLab7a1vwRHTZRqiC9aetAlsWL KkrUO96IclNNqi9oMZJakZWJItUXmPYq3iRM3BKN1yHoMZOS18xDwxl2PUhyok8lXrQqtwYD Ci8IW37xCMj/Az2/S8nTdQEA --3MwIy2ne0vdjdPXF--