From mboxrd@z Thu Jan 1 00:00:00 1970 Return-Path: Received: from mail-pg0-f72.google.com (mail-pg0-f72.google.com [74.125.83.72]) by kanga.kvack.org (Postfix) with ESMTP id 017936B0007 for ; Fri, 2 Mar 2018 11:47:36 -0500 (EST) Received: by mail-pg0-f72.google.com with SMTP id v2so4311417pgv.23 for ; Fri, 02 Mar 2018 08:47:35 -0800 (PST) Received: from mga17.intel.com (mga17.intel.com. [192.55.52.151]) by mx.google.com with ESMTPS id x4si5129036pfx.114.2018.03.02.08.47.34 for (version=TLS1_2 cipher=ECDHE-RSA-AES128-GCM-SHA256 bits=128/128); Fri, 02 Mar 2018 08:47:34 -0800 (PST) Date: Sat, 3 Mar 2018 00:47:07 +0800 From: kbuild test robot Subject: Re: [PATCH 1/7] genalloc: track beginning of allocations Message-ID: <201803030033.qwnGJuxP%fengguang.wu@intel.com> References: <20180228200620.30026-2-igor.stoppa@huawei.com> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="FCuugMFkClbJLl1L" Content-Disposition: inline In-Reply-To: <20180228200620.30026-2-igor.stoppa@huawei.com> Sender: owner-linux-mm@kvack.org List-ID: To: Igor Stoppa Cc: kbuild-all@01.org, david@fromorbit.com, willy@infradead.org, keescook@chromium.org, mhocko@kernel.org, labbott@redhat.com, linux-security-module@vger.kernel.org, linux-mm@kvack.org, linux-kernel@vger.kernel.org, kernel-hardening@lists.openwall.com --FCuugMFkClbJLl1L Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Hi Igor, Thank you for the patch! Perhaps something to improve: [auto build test WARNING on next-20180223] [also build test WARNING on v4.16-rc3] [cannot apply to linus/master mmotm/master char-misc/char-misc-testing v4.16-rc3 v4.16-rc2 v4.16-rc1] [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/Igor-Stoppa/mm-security-ro-protection-for-dynamic-data/20180302-232215 config: i386-randconfig-x007-201808 (attached as .config) compiler: gcc-7 (Debian 7.3.0-1) 7.3.0 reproduce: # save the attached .config to linux build tree make ARCH=i386 All warnings (new ones prefixed by >>): In file included from arch/x86/include/asm/bug.h:83:0, from include/linux/bug.h:5, from include/linux/mmdebug.h:5, from include/linux/gfp.h:5, from include/linux/slab.h:15, from lib/genalloc.c:99: lib/genalloc.c: In function 'gen_pool_free': lib/genalloc.c:616:10: warning: format '%s' expects argument of type 'char *', but argument 2 has type 'struct gen_pool *' [-Wformat=] "Trying to free unallocated memory" ^ include/asm-generic/bug.h:98:50: note: in definition of macro '__WARN_printf' #define __WARN_printf(arg...) do { __warn_printk(arg); __WARN(); } while (0) ^~~ lib/genalloc.c:615:5: note: in expansion of macro 'WARN' WARN(true, ^~~~ lib/genalloc.c:617:23: note: format string is defined here " from pool %s", pool); ~^ In file included from include/asm-generic/bug.h:5:0, from arch/x86/include/asm/bug.h:83, from include/linux/bug.h:5, from include/linux/mmdebug.h:5, from include/linux/gfp.h:5, from include/linux/slab.h:15, from lib/genalloc.c:99: lib/genalloc.c:624:17: error: implicit declaration of function 'exit_test'; did you mean 'exit_sem'? [-Werror=implicit-function-declaration] if (unlikely(exit_test(boundary < 0))) { ^ include/linux/compiler.h:58:30: note: in definition of macro '__trace_if' if (__builtin_constant_p(!!(cond)) ? !!(cond) : \ ^~~~ >> lib/genalloc.c:624:4: note: in expansion of macro 'if' if (unlikely(exit_test(boundary < 0))) { ^~ include/linux/compiler.h:48:24: note: in expansion of macro '__branch_check__' # define unlikely(x) (__branch_check__(x, 0, __builtin_constant_p(x))) ^~~~~~~~~~~~~~~~ >> lib/genalloc.c:624:8: note: in expansion of macro 'unlikely' if (unlikely(exit_test(boundary < 0))) { ^~~~~~~~ In file included from arch/x86/include/asm/bug.h:83:0, from include/linux/bug.h:5, from include/linux/mmdebug.h:5, from include/linux/gfp.h:5, from include/linux/slab.h:15, from lib/genalloc.c:99: lib/genalloc.c:626:16: warning: format '%s' expects argument of type 'char *', but argument 2 has type 'struct gen_pool *' [-Wformat=] WARN(true, "Corrupted pool %s", pool); ^ include/asm-generic/bug.h:98:50: note: in definition of macro '__WARN_printf' #define __WARN_printf(arg...) do { __warn_printk(arg); __WARN(); } while (0) ^~~ lib/genalloc.c:626:5: note: in expansion of macro 'WARN' WARN(true, "Corrupted pool %s", pool); ^~~~ lib/genalloc.c:634:10: warning: format '%s' expects argument of type 'char *', but argument 2 has type 'struct gen_pool *' [-Wformat=] "Size provided differs from size " ^ include/asm-generic/bug.h:98:50: note: in definition of macro '__WARN_printf' #define __WARN_printf(arg...) do { __warn_printk(arg); __WARN(); } while (0) ^~~ lib/genalloc.c:633:5: note: in expansion of macro 'WARN' WARN(true, ^~~~ lib/genalloc.c:635:31: note: format string is defined here "measured from pool %s", pool); ~^ In file included from arch/x86/include/asm/bug.h:83:0, from include/linux/bug.h:5, from include/linux/mmdebug.h:5, from include/linux/gfp.h:5, from include/linux/slab.h:15, from lib/genalloc.c:99: lib/genalloc.c:643:10: warning: format '%s' expects argument of type 'char *', but argument 2 has type 'struct gen_pool *' [-Wformat=] "Unexpected bitmap collision while" ^ include/asm-generic/bug.h:98:50: note: in definition of macro '__WARN_printf' #define __WARN_printf(arg...) do { __warn_printk(arg); __WARN(); } while (0) ^~~ lib/genalloc.c:642:5: note: in expansion of macro 'WARN' WARN(true, ^~~~ lib/genalloc.c:644:36: note: format string is defined here " freeing memory in pool %s", pool); ~^ cc1: some warnings being treated as errors vim +/if +624 lib/genalloc.c 609 610 rcu_read_lock(); 611 list_for_each_entry_rcu(chunk, &pool->chunks, next_chunk) { 612 if (addr >= chunk->start_addr && addr <= chunk->end_addr) { 613 if (unlikely(addr + size - 1 > chunk->end_addr)) { 614 rcu_read_unlock(); 615 WARN(true, 616 "Trying to free unallocated memory" 617 " from pool %s", pool); 618 return; 619 } 620 start_entry = (addr - chunk->start_addr) >> order; 621 remaining_entries = (chunk->end_addr - addr) >> order; 622 boundary = get_boundary(chunk->entries, start_entry, 623 remaining_entries); > 624 if (unlikely(exit_test(boundary < 0))) { 625 rcu_read_unlock(); 626 WARN(true, "Corrupted pool %s", pool); 627 return; 628 } 629 nentries = boundary - start_entry; 630 if (unlikely(size && (nentries != 631 mem_to_units(size, order)))) { 632 rcu_read_unlock(); 633 WARN(true, 634 "Size provided differs from size " 635 "measured from pool %s", pool); 636 return; 637 } 638 remain = alter_bitmap_ll(CLEAR_BITS, chunk->entries, 639 start_entry, nentries); 640 if (unlikely(remain)) { 641 rcu_read_unlock(); 642 WARN(true, 643 "Unexpected bitmap collision while" 644 " freeing memory in pool %s", pool); 645 return; 646 } 647 atomic_long_add(nentries << order, &chunk->avail); 648 rcu_read_unlock(); 649 return; 650 } 651 } 652 rcu_read_unlock(); 653 WARN(true, "address not found in pool %s", pool->name); 654 } 655 EXPORT_SYMBOL(gen_pool_free); 656 --- 0-DAY kernel test infrastructure Open Source Technology Center https://lists.01.org/pipermail/kbuild-all Intel Corporation --FCuugMFkClbJLl1L Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICPB3mVoAAy5jb25maWcAlDzbcuM2su/5CtXkPOw+JONbvHPqlB9AEJQQkQQCgJLlF5bj 0SSu+DJryZvk7083wAsAgko2NZUZohu3Rt8b0LfffLsg78fX5/vj48P909Ofi1/2L/u3++P+ 8+LL49P+/xa5WNTCLFjOzfeAXD6+vP/x8fHy0/Xi6vvz6+/Pvnt7uFis928v+6cFfX358vjL O3R/fH355ltAp6Iu+LK9vsq4WTweFi+vx8Vhf/yma7/9dN1eXtz86X2PH7zWRjXUcFG3OaMi Z2oEisbIxrSFUBUxNx/2T18uL77DZX3oMYiiK+hXuM+bD/dvD79+/OPT9ccHu8qD3UT7ef/F fQ/9SkHXOZOtbqQUyoxTakPo2ihC2RRWVc34YWeuKiJbVect7Fy3Fa9vPp2Ck9ub8+s0AhWV JOYvxwnQguFqxvJWL9u8Im3J6qVZjWtdspopTluuCcKngKxZThtXW8aXKxNvmezaFdmwVtK2 yOkIVVvNqvaWrpYkz1tSLoXiZlVNx6Wk5JkihsHBlWQXjb8iuqWyaRXAblMwQlesLXkNB8Tv 2IhhF6WZaWQrmbJjEMW8zVoK9SBWZfBVcKVNS1dNvZ7Bk2TJ0mhuRTxjqiaWfaXQmmcli1B0 oyWDo5sBb0lt2lUDs8gKDnAFa05hWOKR0mKaMpvMYVlVt0IaXgFZchAsoBGvl3OYOYNDt9sj JUhDIJ4grq2u5FzXRiqRMT2CC37bMqLKHXy3FfPOXC4NgT0DR25YqW8u+vZBZOEkNYj2x6fH nz8+v35+f9ofPv5PU5OKIQcwotnH7yPZ5eqndiuUdxRZw8scNs5aduvm04HgmhUwApKkEPC/ 1hCNna3uWlpN+IT66v0rtAxqiZuW1RvYOS6x4ubmclg8VXCUVhQ5HOeHD6MK7Npaw3RKEwKd SblhSgO7YL9Ec0saIyKmXgOLsbJd3nGZhmQAuUiDyjtf3n3I7d1cj5n5y7srAAx79VblbzWG 27WdQsAVJmjlr3LaRZwe8SoxILAcaUqQNaEN8tfNh3+8vL7s/zkcg97pDZeeJHQN+Dc1pcfU QgPDVz81rGHp1kkXxzIgGkLtWmLAyKz8fTWagU5M7ok0edKq2pOxcmkxcEIQ5J6tQUYWh/ef D38ejvvnka0HQwAiZIU4YSMApFdim4awomBgrHHqogBboNdTPNR2oHgQPz1IxZfKqsw0mK58 PseWXFSE12Gb5lUKCTQy6Ekgy25mbmIUHJPVecQIlcZSTDO1cWq9Ap8knAn8EQoa1mmVQMVq SZRm3c6HI/RHtmq30IkDpeiTaNHA2KDyDV3lIlbePkpOjCfYPmQD9jVH81oStFo7WiaO2WrL zcg1sY3G8UBn10afBLaZEiSnMNFpNHBpWpL/2CTxKoE2BZfcs695fN6/HVIcvLpD08xFzqlP 4loghOclSwqRBSchK3Bx8LgtQVRwLs63lc1Hc3/4bXGEJS3uXz4vDsf742Fx//Dw+v5yfHz5 ZVyb4XTt/A5KRVMbxxrDVHj8luwjOLmkTOconJSBxgBUk0RCGwa+qklyEiyBa1H2MmY3omiz 0FN6GsXA0tLGXyh8giEFMqf0jnbIfveoCVfWBk04ICy2LNFAVr7cI8R5rmxJM+sLhFYdXN36 wtPJfN25+pMWS7OxuRQ4QgG6jBfm5uLMb0cCgffswc8H4y4Vr8261aRg0Rjnl4HubSBycb4G OKS54/aU55ahLANCU6MTD75bW5SN9rxzulSikdo/ATAUNM0cDtnNeQpB8lyfgqs8tLoxvICD vWPqFErniqZRJJg0c3IFOdtwmhbXDgMGmeX/fptMFafgmTwJtto4iaAFynKHBao2rVbAjQCV D5KaHsOeOzp0dpw0zk4X6IxLxcAezZwpxkK7hCxm5RrJaL1VlftBNXyTCgZ2JsHzNVUe+ZHQ ELmP0BJ6jdDgO4sWLqLvK4+f6RCGoKm0Z4QRfE2Zz+MxGkZzKX0TeVKkBpvMazDKnmVyAsnz cy+z4DqCIqNMWkNuo/qoj6RarmGJoCtxjZ7ykcX44ZTh+B3NVIFbyYHflb89DcKB/lHb2dj0 1vCIBhvsMwUufb5nsSJ1Xk6cT2fDvFary+Lvtq64r2UDIxURJG2gICpriya9ssYwL2y3n6CM PFpK4Tscmi9rUhYe89pN2IZhQutEFHmKhKsg3CRc+P1IvuGa9XRMCyn0z4hSfE7XrRhdSwF0 Qy8BHMYUj65x9F3lUb5vaaOTHdszMNBAHJQO0HMnBnXkRhWAfnfAoSneQT60gU6SXkMaZdw2 DFKDEyZUIJ02P5Kz1BhOcGCWNnYQbSMsoN1UfVLBY6zzsyAss15Jl1OU+7cvr2/P9y8P+wX7 z/4FHCwCrhZFFwscwdFdSU7bpTKmk3fwTeW6tNbtCiREl03m+nv6q8ux2QzDKJMlyVIMCAOE aCJtEbE/UF0tWR+JzqOh8UVfqFUg5qJKTuujrYjKwZnOo325/JUynMTaxbDKWrV2A750wan1 FJPrAaeq4GXkqg7OHyhUKxseRakietWzU8/K7JbRqM1ykXDDe819Cyoppwq8YeK8049NJSHK yVi4P3CLIaxYsx0oV1YWM8kYMD7xeN0ELRiLorcWo2A5YDqKwM3Y/DcIPGg0NPsUHfg58YE4 mlOOPNnUYY/IhUSGRkcYogUIDLbEs9xrxSY7sINzIDT6mgA0EWhCQtc6N1KCRv4wAaF8eNHU LqXPlALTzusfGQ0DfosWGKIxoWFHXAmxjoCY2oZvw5eNaBJxqQZuwBCwi8wjSqLWA5NmeLHr 3aIpAjitXZYmuTCXR3QVi3a74oaFIcvg9YNLtwPvEANt6wPYHtGQii3BDtS5qzl0x98SGdOE lilCAF6suCxstQXNxYizWRGs4rfAZyNY2zXEbhQYEGg3jaohbgZycV8GY+WfOEPURhgMWf/a wMF3PmBqkMT8vR5XHV3yporTnpbMgfAHdIWY0kVmqCAnh+z4zgV4tJJYsIiH7wSyO2fMkcdH 4vq5zO0MLBfNTLYfc4ouUdTnghPb04yiIWpBGRr/AObabc8lONWybJa8DsJJr3lOIQGGJTfq DHtkkaseAoEx6pQjNEWEA25K8hejAaHFTDJkiozx1Ml86JabFWhLxz2FwhgtVpDTTMyMHqox o8e6Ck2CESqRd8clGUVL6kUFIm9K0JGowcEKoQeXUDgWYq38tJg1LSFGCOwWDE5S2YW9PoVH LeSuV2WmDBhlnBbWtkpQGSuIWRNpKVoCN4CbStdbEH1vkaLM0cHvKmCXEwDpjYKfN8Bk3Wge i+KExbUr3eBW7WGn8+eII2wESMq+QqC2t/8Vcsplm5gOAzbIeJ08mZ0Hxd0d1yS7p0BDd7kC b8eIsLw7QBWW2xrfHvQtNo7rc4RLKjbf/Xx/2H9e/OYc869vr18en1yW01MnYtNt5hRBLFrv zgVZZqerOqvtrPqKoZh564P9Yuzoy64NhDR69zfnkZQFyTNHJ5ulBw1NUjFMh9PUCI9ltus6 AP2RO409E0u67lrRoZoXBskTTJ7Weh0YFb1Ke5HAEhWsEJRL3q7D2LNXPDY3W4Ib1Uh/Exna 5sSIkoQlBaLrcy/lUduCMixZgm5F0kyynUN9mBiBno+qvCKSPUzXGcgitrVvu9zVgRkgzjQH G1xkW3XLLZqthIwo85C4s9qmu07aR5ntI+c2YwX+hW5LVy8a6J3IpFphkm+vD/vD4fVtcfzz qystfNnfH9/f9gdf2O5Qt+bJEmlQoseyfcEIuG3M5SUjENaCejhGRIHIIEYlrU+SmGcJ6rrg OqhYYsQgkCFSRgKCbFBzuQmXkIElqGQ8Lbs1YBvwxsWplBNiumFLqdPChyikGsc5lWDmQhdt lfGZ20oDJ3cF24LwsvGD1+6OBFc8IKNL+ALzG+d3tNbLDs++V4E78HM3XINDs2yYH0PAKZAN t+nGMQrv2k4krAeUgdNTOaVNNUw35qQ2VZdCmbG1w9AnqlcxalQOAZueCWFcsm5Uc1efrtP6 74cTAKPpLKyqblPa/tpeORsxwR0xvKk4Tw80gE/D06zaQ6/S0PXMxtb/mmn/lG6nqtEizd2V dZ/YTEan2vIaS+x0ZiEd+DJdiqhYSWbGXTLQfMvb8xPQtkz7XRXdKX47S+8NJ/SyTd8iscAZ 2qFqnumFNmpG+jvHJJR2K8dYdeguoLmS4LWPUp5HsEA1SfCEQAHXNKUxR/WGFgQd9HB2tFJ2 AJuO1k0VgkEiwoYuBr2+ipvFJmypeM2rprJ+d0EqXu7CPVm9QE1Zac/qdsVpDNxYyfy8Bg4D ytPtZdpsTzm4C9pDQHHHYYDtAKJEmpnMfIdjo7SKGQIDzxTDEa2paDDzSjITJxhtG6sgYDXg ZxuPqLmf5ajt1UCNcdsSTT/E1ePNthAIpu3m+iqGddGEd6Wsg2BLZE10NZMottAqrQrBa2SV NHNheg/eiBI0ObHJrrjviW5RKGF5HxMhGBXGYiP6xkAYFFMCix9Y98uUWLPamgcMzFNmy3Jq mI3tmrBCXzIIJFPl0Q4n5sa+2fGc7z3ULuasKJtiY8CsV+AJTUEuvXnzHIgkBDQQqbSbPpni fD6vzvH8+vJ4fH0LbpD4ibVOH9Rh2nyKoYgsT8Ep5sMD2vk41mMS25nqlz1aS14Is2dMcgzo AxQBajDz4gn+aR2STjE884LfxpcfOAUFA6p27khBFwW0BsnhgfqoBV7rAWcj5Xg5yFVQ9ewa r6/SvtWm0rIEp+7yr8CYOziJcnF6hIvJCBHCuZeosleTRVFoZm7O/rg6c/9F+0xELdAKeomq nYwz1wUoPgcliXvMNjyYB1tT0HvMGAR5XMlL5KKy94fxilrDboa1nuzbL6oidRMVsoYVOViq HO06h6O11o67fl4ENQ7nKkhxqo9VWejUBs3doCTOVfdpjmUT36fOuaZE5YmBO0L4d7jCxFfn S7sbzXVaVBzDSGMXZ43LVTR+hnXScPSuydVAaVwV7E3qAPSW7N3pHBUNJqVInqvWzL4OcYGF wKziONpae0fWX9y1OU13kTBXN1dn/xs+pfjLoG3SPtJ0C4yp7b0S1OTpUmcqFTxex0vAW1Ju yS6dvElgV+62gj+qV04yK9li+e9vjGYVg/VE/RQtA+vWtY0uVDKtcCeFKEcNe5c1OXyNCYnL Aqxgqp/uCu8ecn//H45OpiPGvpcVunHBvdjYZwV9RdNTKFjms2TDYuE6SOC7GxV2PL9IiLfB QO2tKhIW9lFRSpOOpKx1QZe7zbjAK/9KNXJGKpxJw3vDmHXbem5fZZTnZOJXq0nNDb9js+2d kh1cxbMZNHvwWGVBF7JHPo9CD5I2Spa9Zq8Y2ERIQHQvSql4kMhhRSqV0pWqPIV4156fnQXE v2svfjhLZ/jv2suzWRCMc5ay7nc3AIm95JXCq7mpfAheTAgkwt5ewJJjyv8FdcbRzwXWUmhz zzuT61/Uw2vleHKn+tsCI/S/iLqvhMEyXZu+ENTdS9nkWoRCnNvELNiE2Vwz1rzL3Jy4UWZ5 oeO5TlF2qxl819ff928L8F3vf9k/71+ONmNJqOSL16/4FDDIWnYln3RwkuI2HMizj/DVO56W mnpMZPsLrvCBWlcLwi7Sf5BmW7rLLtbFtSoBhhof9o2iQPty+jKZrnNjSarcciZdMSQu9NST 9nEU27Riw5TiOfNfg4UjMXrijYDFIPEeM2LAqdrFrY0xoTm2zRuYPVU/tcCCTDvk6XKBhdm0 gWI/tTK4uNJTxCUJhgAkDebBRcYQmKSz60aWS9B6+IRjbnFdCDYZgzbaiKrNdX6ynufGsALR SHBu8niVMSzBTGm1azdCOd4Vm1HMdpkCQnMQ7Nn99dqCizjEdtyapbO5ru/MTWOfQBUzK3EC TbG8wXcweN9ji1ZI1GUqDB/Fk0g2ufDTt3cXScIpEJBcQC5NcSJudZJ0C77vTLIc61NCAgPN 3XvrjwD+nZREa1erOIGkC96rS9Thxdv+3+/7l4c/F4eH+6cg0u8lJ0yFWVlaig0+EcPsmpkB D88ogmyYBaOwzebLLEbvT+NA3t3s/6IT0l3D6f39LpjWtDfl/34XUefg883YkGQPgHXPtjbJ yympPtZBaAwvZyg9d3k9wPl79Pgv6DC3/zQvjLue2YS/yYE5v8TMufj89vgfd9vWX5Ej2dzD fucPykmOycoHpf0A8xW7zozESP4wSN5abNv1dZj3GQH/Cp1UD9A7FsGky1vroFQiRVzr90rG cnAcXAZa8VqEE0zhg1+QxOJ0NQfSfmbZLv7KFc9gdVH2vjuL2l5PuAhpUYp6qZraj7365hUw +yz92ci90xL14df7t/1nz79L7qDk2dzm7CN+fBwFkbuNo3wG5J+f9qFCDF2BvsWycAlBv69p A2DF6uABm7Xh+KxMj3hUNLKcsXqOiePXg3ah2fuh3//iH2C0F/vjw/f/9DK2NOAuNOtLgcFi 2u5YcFW5zxMoOVds5uWTQxClpAnmdUBSe84gNuGCwhY3QdjWrytsxZmivvalrY73Tevs4qzE 6xRcpe9iARZDzztr5slT6VQoiRA77mTWExVxdLFMk7q1jyCUsZLZh/zdpoOeXGxmR5Uq7ZVY GNE8pVbslPFV9d6FQ8aKOY/ef95jnQBg+8XD68vx7fXpyb2K/fr19e3oq2kkLAhZjuVF+8B9 lvwDFpOTGfP94fGXly3IPE66oK/wDz1M5oJAaP/19XD0FuSZjQGFvXz++vr4cgzkBIth/a3k gGR9+yl/y+LJwl5dASU3zHT4/fH48Gt6OSEnbOEPN3RlWEpwuouNXobJ/VZKd9NxVBU6eROH Yizv+YH2e6Vi/7CTpWE0/G5vxfkP0CPNUqTkqRsNNTM//HDm3c9aMl/CsapTZyGdMdecnELB FnOeigmtMt/pIuvVNvtj//B+vP/5aW9/OGhhi1nHw+Ljgj2/P91HZiLjdVEZvOI6rgw+woJW h6Sp4jK+r05EYyaYycaK6yDviHPMZHG6NMpl/IMZ3a01LoKcV219cLv5en/8/fXtN/SUJhYR XLo180qA7hu0LFmOjU3Nvaub+OUQhia8jTta9cJ/j4hfWOwJ7yvaVvypnajJPkYMRgKHJ2vx xhYNir0W5HL3MxlQ2xfrIdpwmoyEEINLm+nzTgAIh09wUqLmaDqKlHQvKPFXBNLmWeJLPnTB 89bWjVMhMSC5mjItidbcfw0rW1nL+LvNV1RGy8BmLK2k2KYDK6JC7gAAlyOtXctSYea2am5j QGuauvarWwP+iKl3WH8Ra+7f4XN4G8PDpiZPD1mIwCHqmsYFpA4Sz6UlnqNqG5iW05aBE70D 526JyAczThbALbO4JcytIN7O2A8Lg121A9N3z3MYpwfIGIv7hmLqVkFlqhnpnWhWZNs3h/vF RuAEfOCwS1IF54F/LgcOTxV4ehzaZH5Zso9je/jNh4f3nx8fPvj9qvwHHfxagtx4URR+dSKF tzuKUB56mC0zzkgm4LhX3Kge2jx52RopcY2c9Ry2IGtNmzzeCkCDivHnrri8jhE9HotB6da/ ZK7rKXfNwjv2CtjAh1uKdg/fJ88u/a2hrD9HpNbJEqoFTdaFjYFesS2oGOJRUTPMy6QlM+pn iS/rbDI+ZCc0LXjXXE+4p7KbnRtUsyUEqNtBXKOtInRVkfQFJyAq/gQYlpiwnpf2kFppZGcO il2gH21fudpZ/wysWyWj32oBHPfAKm0JckplrEPoqDGcNw0NC0p5fpj8ZGI4UItIF8NjPt8g DeDLqbOOw3fPp1f3D79FbzT6zpPwaIRragKLjd9tnoFXmv0/ZdfS3Liuo/9K6i6mzlmcObb8 iL2YBU1JNtt6RZRtpTeqTNpdnZr0o5L0zL3/fgCSskgKtGcW/TAAPkRRJAACHz/xIhR1hjJm 3dGblHpJuM78/wrIHZuSmnRAHkPZbAUbX63b/hUuNuZtCLohb82uA6ApMPkpo4E1dnxNk8Nk E86Q9jSMfxacVEdRJGOF9Z0iJa9K5lI2dbRczf3KNRXe5ni2XuSyiFRoZGNN4S2qNVbdm1rE W+rL1fmTON8lc1UOJHj6H5DC0Xm9QMOwOZ6PartwcGvC00RaguqIYiRBzl5+phnwItazyYxm 5s2eZjxwq50j1NGtJtH0YRjdgdZtj7WjdVqsHFjEOMUJL+yDAP3b7NoDOcu48yNyHGINy6hF so0WtljGKtJbsis9lX2ZlaeKkVtXkiT4OAsHK3CgdkVm/qNAVWD5LRpGuyetQojGk1BbH3zc l9asN6Mc3r3d9vD7/PsMy+Pf8vnb+ctvP5vNyHd8Qzmge+6u2Xj7gyangWSEXgA+0iu1VrUo XRMBqWq3fRg9ER64jYXROieID2Nikzxk/heq6Jv0Shf5Ro57sq2TeEyNpYmt8ejwb5IT4nVN PPuDGpORMN+V+4R6Aw/ptdfG3VjCnpw+GM6o/fSBfM27a0NUiYQaV/TsXSnVB+tYzfX7Xkqf lwzbYpzQn8xQwf9BSJIj13NhR0lLlTY2NjjMI/zHP359ffn6s/v69P7xD+O0fH16f3/5+vLs qTpYgmfeTAIC5nQK7r4GJDdcFLENJNQz1LI3HxdIT/57Q+phRqd/XGqTR2rJtdlLoq2sJFvj YZivy+MG8MjsqgPbeC+SI55cKK9U2edK4modLHC20PMFeex4+UZgZliTglvHP3GBycayRDhb y0kHqyDDuM2jPWwDtf8v7XG35TLK+2oJxHYMoUUveKDlPOh1smsNBuSUoJcctV/Z8esOZFwr rxdUsY722e1Rb3dyTPF8Dxg7K0pK3mWMYBfhTWai2Hvux7zyv1CkdFtZujLqI3RCLhVVVL4N ilUUNtThzk4jUtNJjUCcHP3vKZshuiz6JYAZmIsFl5Y7rK6sztepws500j7cLAOD7afMxFrQ 7g1LxngVAz2pEUtSPnYuttnmwf6BcF1gJrNcY394A4EfvgGadt3Ndx/n9w9CZan2DcybkF5d l1UHb1xg7snldexYXrNY7a76/ATMxvPHXf305eUnZvp//Hz++Wo5tZmnHuJv+MJyhvBTZIgF tF2XuWNRlXJ8qMraf48Wdz/MA345//fL85k6t8n3IpDsu6wYGZW2qR4SjPtyv/ZHmP8dIsqk MXWYYgns4pYoCi8sXCypHMvpkdFpoZxUlzeWp2mDmGNJbK+bMLNS/HadPvXErmlIUEiopkgq rwiSYLHrgl6NXgaBVsoRugxwdyKunM7upMO3j+7Vz1h6fbgCxrVp+kW2n5yb19/nj58/P75d mR/YCS4OjASq1cwj/HF6nddHRwtmKXy9NW3ep93etksDn28qNl3tg1CcBMLXB2bvSeSMmoh1 uheZtX7q36OhNGRRVAfqwQ17W/m2xbryV9l1ZbaKwDqyrsZuKc5EAFM1qXadB2Pe15XaOl7K YePZCrD7XGLBHY+nIWFCO62sGL7//h2BHXGyXpyf3u7Sl/MrIgx+//77h1FX7/6AEn+a+Wat g1hPU6f36/sJc3uMIORej9OY1CiBUxWL2cwtr0idiLzRkQ01FpqK0oEGjACMlzeubWXqGxOJ xmfpqS4WJJHq6nqxS52UD8lAHQjsDp1IrWXCcv56FBd/NUYcczehZYvJ0EnmwheprS85ompD +goeVSK1kegXmlgvL7EbxaDuhXh5NuS7chziftCYkrskq8gFFZpp8ip1cCo1BXZmJ4FWNqyI WaYdnMM41rqBVNS5Cq9VeNhEQ+lJodzYS1LSNjW7lLTgfy+yGmFNd95ayig2GIFZhuhOji6Q ocKC4MPUUbtlayKuRFyLY2CMFDs51u7qqem4V5iyYFTkJalyKCGmkFiMqL7YwHZsP0oLb4Ps 5wWLvjoY3BBK27elEIYscIUCso+HDC9s2YhMNM5Bbp1snQAD/Vt9WD5N2ikRhpbntnekL+ze N4BhK+oimRjRy1MisA+j2kbLHPxTjKDfMODe5ApTn1Tj4iM1scaWoUXRgaXSvBGU1AYsslg6 Lk1lJ6qcyL+mbvVOFQo8U2XckOemY3nEPMModbftPoNGd+u7zSpTisrq+8szGE367eNFbSG/ nt7erWXkAD/ucn2vjYK0bd6efrzrSJm77OlfDritarCsvMYUgiseFGK6vzKJ+lZrlv8N6vbf 6evT+7e7528vvywlyX6+VLgP/CmJE+5NXqTDBL5cC+KMOtSgDGENjRZ6vTgVNwzMypOIm103 dSv3uNFV7tzvgccPgKIQnQignIwlSfSI/uGF9zCKFlHDJAK4Lz17da0VjEOFtXvcFsthD4zH dNg62JjqxrOrz4Dl7qxCM82RYBupAdjU1Mqffv2yQsIx0EtPsKdnBK3y5leJG37bJ3lKf1gw 7y0nU1ctLnxq3ry/0BVMJmtENpqXlsw2QSyTQBtyw7tt27oN6CA9zG9KwbjfecORx/fLVhuz FlnwXetZuEhO5CaqywAeEI7QfjWZt9ckJN9EnepHUAS0m4/za5CdzeeTbQBeB4cqEGCovvsK cTrimN4b1XOrCOkjAn9S+7hqIGONnmZut9AZOapcTTJ5fv36F0ZuPr38OH+5A+lrvgBsIueL BXVqjExEr9Mv0uvBhdGdatEkGvOaspxd4bKpRosQ31XRbB8twouKlE20oOIoFDMbfYfVbkSC P0izpyP87pqywdRThAm1c98NF3QNaW7Em0Yro9m+vP/XX+WPvzh+uCM11x2jkm9ngV4XiFGc cO72sqd2Mufup4Mc/x1cpDcBz7Qantw4KsOfAFYTJwiZfXVC23Jk6spFyFjJ49Kl2h5g6o7U 7rEsKH0lhZY6dEXIfalgtci2Brbefq8Fg10rFCNYpJ0qPhbdbBr1FYxfmZoDc7J/nKUBpLGL hFwsZiT0Wi+Bf3nm8oVHQf/ZOlGRmDk1Jpqvuesfyqm8lzGKefARejkv8pOUiVoc7m3tuvnU 95RVuMr9m/43uqt4fvf9/P3n279otUyJue/hQQF6kCoYGAP+4uvwDySaYemE9ME2eShEEwLE T7HlvHFAs4G4LzefHIKBNndo/eSzac4FcPDbCWOA33ls2zJl2p8cOTTMmB7fEmolfmswbfem 1p5guyU0qasCiFmGvQ2c5/d81q5W92t6/e9lYAGmLiB0gpBVBLKycnMYNrZNBlti7IgHYZPG pv1XxzzxEzPyl/fnsUkHKh1YvBIv2Zxlx0lkfUMsXkSLtour0hkmixzwNNkSjqspPuT5o2+L ik0O1jmt91Q7VjQBnUhuMQWH08p0I9Jc+R3ouBEu17NIzic0EmFS8KyUCIOKaZO+pX8R24FZ nZGJ8lUs16tJxOxgfSGzaD2xI4c0JXLQLvrX0QBvsaDwK3qJzW56fz+xYsINXTW+nrT2K9vl fDlbUNZLLKfLlWOlVBiXsCNzog5yY47julSy9Xw1sRuBFboRmDbEq5nJ06HfWx04/3ASffwV aFjJhOQdGNa0Hssj/L5G626S4LpF5UVpTseaiPogB65zzGXIwcA1w89Zu1zdUyXXM97SK8RF oG3nFGia4YM92q3WuyqRzovmm/vpZDTv9YWJ538+vd+JH+8fb7+/q/tzTO7mB/obcFjuXkHJ vvsCy8TLL/yvPUwNGpJXZiMuH8b1azkAG9A50QCtAuFbymTIAwn8Fy78uSHQtLTEUbtFjznh 4hc/0FSCTQq247fzq7rq/N1dMQcR9IZpvbjnSS5SgnwsK4I6VLTDzLgQkz+9faGaCcr//HVB iJYf8ARglF+wV/7gpcz/9J3W2L9LdcOk47vA8XabKUz1IJOlh96pWlaBy/xALHR1bXm1gcun 7mvy/bKmbmqIL3eCSi5Fbx8Or7KfqcDsdMb0sBQhLXTNoWKaMAhSID1ILzhfv58kSe6ms/X8 7o/05e18gj9/jruTijrBE0C7Oz2tK3fk8174hZtAMNBLSeeQ5IzD11IicJF6WZR/Dio1fm1L 4xReNpGXmVeqe3ztvqgtnl7ZHg5gbIVujFQZNQkjFXzGMQbW6hUQYFGxmz22GXl6fgmcGfz4 IQ2ecUnmfULP4H+gdloB2ANtrOoWCvfcCylEisJrqeE/9nlKozLy+x/uQwGvO6pRV3dDkydm x6Sx/FImqsdRo4sMA3vsdbnG8GByEDBgnJgheq3AU91hs/ByeuMX2Fhe/vM3LqNSZ9yyt+dv Lx/nZwSsH9s3m8XMCSdfzJQBMz4IckTQIAgfFikJtMq1hHWqj7XXbDNi9EHaG553Mo3GjKws qzE1b+4XM0v50oCkaD1j4DhNth6PqPC4WiXLtm2vsLptVm5YFrkzyxWpmmrMfuBstR9XLHNY Xvt4diIu3+aHzpQpUWW0XVpTwTbOhHT5WMUR1L6y7ma8dOJYjqDKJbSe1zxWu5LMjLLqYzGr Ghe9zZAUPhsumzcq2CbenYfNdDYNZFtfCmWMo6vBjfeTmYANObDuDkWbxAfkSoqAW8KoV01g 87Srzdnnm2PlwmvDz9V0OsW3F9DVoWwgdBZTy9vthu5WzzTXE/FwbHzfMdg2ikZQUZ22VO2u wBc6zr7SOW9gTRbod5PR9iAyAk8DnNDboSeu3bdDXdah5zIgDI6Ph3EycmaoUV+1bp/bbOZz 54cysvBg2sdlNzx1VckVvkXgOW6ujiKyKVp6aHloEjdiWxYzermHyqhPTeP1+c4bkKbsE3dw uAfDtiluTCvOjuKQkzOL75JMupfJGlLX0NPowqaf98KmPRoD+xjKNOh7Bmqz06/gEmIXwnsP i8CF322HV09T7oPCzpS2qovdZVdpd4dMhELp+1Im6mbQJrOI1r3loYh9SLJxfQjUn7jhmklU kGlCdqnPyg0/hMqo311RYWR9AXsCZiR1iatkWcVb9zI7GQVih48tmT9nVbVzzpd21ZRENLUL HNgpEWS3eoj7YVbQtSHZwilRPy3NV//udic7PENsrQwj+AFsD3wOiEc6JlDAbkB0A8l2ZrLe M0bVKnLMaetSzCc3BlisokXrTJBP+Y0iOauPia3e50fjpR4WalTaQacM+C33W3ozkfvHcC5K 3zo0zYry5t6CmmcguceTUvrpjUd+rB2EG/w9nQSeIk1YVtzsX8FAb8kpI9cWwljxoswTckIX RxEL5tjPiHoWeyrLuGC59wC5dl1IW0F8y5DeawBckmIr3LC8HehbMKhkhY8JRsWl4oY29pCV Wxew8yFjM1DwyUofsuD++pAFXhM01iZFFywXwEGz+wjmPB7GXn+SOkE91b4Izk0pX01na05b 5MhqSnrtrFfT5fpWD2tYoyW7oXPXsTPO9XIypyGl7TKYNBP2YxgpyXLYpkIJfr1QkjyQ01uK zIXalXwdTWZUbINTyr1uTMh1ACEbWNP1zSfF+wXqFP7cWBXRAHQ2l0rwaahlkF1Pp/RcVsx5 dGOfkyXHcLeW3oFloxY2ZyCaHLP8b64N8MLcT7mqHvMkkH6MbzcJ5XJI6QUbDcMrKOxuqxNN sjs0zhqlKTdKuSUQM1OewA6hv/+G9pdZ9R3dxRV+dvWOvs4PeUcENhfNI/lGTuJz4eaHa0p3 WtBayIU9c9HgDR0vmB0DII5lRHFBMaSqYEUIdqCfDo9FWYHBMTxUfOJdm21hMjlezws1GHSS xjHNgO03lL6A6W+bAI699oQph63rWnFB6jSF402gQnfaYYhmw4qtT4WhcZCpbKqXNeKwMPS4 TvzqiAI7IQVoCrkNVF7tHh2cUHkCiv3isiTGS00Rfx2FRw5KvKwP6aMIsX7nyVU4oHXAbVwL HrVZTWZtpxvvzQae3yv3mi0IxNU9QdTagX6agW5Mc1caDG4WM7ctY4l13tPHYIqa8uRkiavV bBVFPt/mzlejSpG8vA8UStVl8E7nBK+ygzQPMSja6iSuPbHHQE1guaLvbDKdcncAsrZxGzDq NU0EpdNjKDXXf6rB7RoaLCWBCmigvwUzFzx7NT9cKWM0Hb+IUUJChUCT6HtqneWjO9WlNGB4 tZZRir4/mGeCS3dEjqJJJN4FaBNbAYY1fLnwhUQ1/u26qGEE93K1Xi/sm6GrzAatqyr3R7eR sQu2hcQ4wcuTnMwKJF9BnkF2XlX0HqWYiHQRPIIDidLDz3B4oXoDZ0DYoEoUCXJVFomXVWn7 eEkYnWzHe8gnPP/96/3ly/nuIDf9qaAqcz5/OX9RUdTI6VN72ZenXx/nNypy4eTt4DrQ4YeC 3jy9YPrgH2M8yj/vPn6C9Pnu41svRUTSnm4At/RnRI4pPnBTtk8y0qgfZGCVXdZpNLNcDRTX yvkcS+UgMv80p6vgPFpEToCKXX+c3kdz2tq262CraEorsce8RQ84vdUfPolGHjoyQ0gfs+o4 x75FGbteDfjdiXkgaAKZnAVUBsWN62O3FVsmA6d8u0eQolQK1RE7/FJXJwMnpoqbTUsxBgr+ jry7b09vX/7n6Y2O1laldykPRun2AmoJuCLCjnlai+bzFRGFN56yQOy7Hm/4fxG8EVeJnJbL deCyWMWHV/spGQcfiR+/fn8E4xJUjq41g/Gnzuf97tLSFK/dwYxhn4OHyxogwSHr2+r27q1Y ipMz0KNaw7lkIb3idT0vP2C5+fr07F4xboqVeJk8CbagBT6Vjx5Qg6Ynx2ulkuNmuENID9Yo FN0psE8eNyWrrWSXngIfdrVYRJMQZ7Uaxs7jrClOs99QrTyAKmPH3lmMaLqkGLEB06iXqwVR YbbHhsbFlOpsDafDUO+djAC/iDWcLefTJdEicFbz6YqsXE8PcqIPPc5Xs4he/hyZGZUzYLXU 3s8W1NDnXBK9zqt6Gk3tJerCKpJTQx5yXiQQUAXPtyRZPuytGQbd3HJvsh3papryxEARvj4y 0BK88BsyTR7Qi4Yngi+YPi0a3nMedU154DsaaXmQO2XzyWxCPlPb3OwsbEjTacA9eREC24je tIbV5QofFhfpX9LmiSjs0QBCtBbAkZCg8Sb0Om96IiTl9K1zMdcBUN8dkpPxrihO0LOm5BuP ktqhwD0FA45tY1nRo9iEWTpmhSoxpdyBhhWNxWe0LmOYVACsZi0W/fK863d08Xd5hxuZE0ru 4LIRUfiehPrZidVkHvlE+NuN19dk3qwifj91wp6RDjudXkAHXVzTuagkFfes2WChA9uNv0Z6 zU60gq+4JvDCq9hvWUaotwSbhtFBGf9BWLUhqOoSAFbZYMiaobcBu8DBm0Fblif+VXY9rSsk bHxEFy8C2Zwsl+SH6WRPn3JfhNJ85cbXa4UCdMKnZzRpRqkITeMYzkdq8BASf73qqsb2yZlr AENEcxt5tFi6LwnM+6IsNLRC4OKDovxc5gHnXLcNJC3gfaOYaBewWS+7SMiMBF2JvpgaGHt9 VbFJjnx7eXod+7nMs6l7UbmN6WUYq2gxIYnQQFUnKle+z+Om5XSeij+YipWiL4jC1rCFuImn pCu3o0xsxuhg3eLlSQEqA2Vz2lJFraBgrHuObW4Ns0TkyUWEbChpm6SIA6djtiBTNkd3DGLP OKMmAycM9ssJr0mXJ2ii1YqMmbGEMucmRmcQ3TvSHVbZBqKktRBmhhEpejoZ6eePv7ASoKgJ q1wehEPDVAU64Sx4dGSLBA6QtAgOeyZIaHEj4YYyW0Rrevq1fgp88oYtOS9a2li+SEyXQt4H NCUjBLNwk9Rx6OjGSJlt6FPDtrfmmBG9JSbSdtkur448HpbfqsZ4Gyt5UxI2wWvsugrvsMCG jwYm8602OJ4TsqJRgFK8zAIJkv3MgnXk83QWQCrXMghpE7qfCtZ0BAssmoC/sla32xOTsqrQ crYj2nUot5mLtLZa5QJ0qyLOAt7V3Ym4vHnYwY6hTKx6tl7SdgWrKgxkDXwFZfEY8EvlJxoO 0CAsGDu3Hwu+up8t/+lRC8lH9vCuIoO5YEy2+lJufbvSEGDP4U9lBfQpgpDeYmCoYzEHb6cn gv6PgfNudJXNpFxLhFhxOJbefbzILkhjBDm60e+u+FU/Fgrwmo6WQt4RBgdTfNvQVSRmGJrZ 7HMVzf2o8LCgh9DWiyWZusjQOl5Njr62CstJ9uh9b9pVBI2P3WmRf/cxDm1/kavlCAOqskox n9ol6+ufPBpeYas+UIuoz0j12ePv14+XX6/nf4Jii/1SgApU52DN22i1XUH0JsU2GVXqnZgO VOdQtidnDZ/PJkvH021YFWfrxfx/GbuOLrmNXf1XZmkvfC5zWNwFm6GbHrJJsdhJmz5jWbbn 2ApnJN1n/ftXQDFUQHG0UGh8YOUAVKEASkdUOf41UxXXuEaKbXPNe9LHGHBM3sDAflhtPq7+ KpHToB0aiII4msQefeUvPbxonPCs7osea+6Bp8zp9oBzSg2ypnZDy+K+4BF9qrXg1w28LWKL 548JBqN6K14nlgfJCDKLXwwBtpZjDw72dX2lV3NcdUSsUCvOaq4kpvY243hkOVeY4DSipR2A zzUtVk4YX4qMaY8B5S0dzPKWeOkJ68T3L1/ff3j4DbyaTQ6LfvrAB80/3x/ef/jt/e9w9/af iesXLq+CJ6Of1Ymbg5WDuiUBuShZvT/iO1P1bEgDZ/FYn1USi+Ez18ZouzIBtnLvOfaxULbl 2d7XUDvL1O7mk1N5YOXZWq3v2qCz6AsTtlmF4ZF0FCKGU6u96AGqkDiNji///fr+5SPXODjP f8RC8TTdpxpKM5Zr8QlhEu8NnGTpGY9Zx+5cXTey7r7+JXaCKV9p4CkqjxB/6IcdWN/xtFPL g4NEW10bfEuDL8PN4QUeJOyeEBYWWHpfYdE24bkOavhLRkW2lzDVQR3IBe3TF+iSfF2+CRdE 8KlQYyzpZlf0a7ra40rYbOakEk8jT65qZCsLiDRtPrwRVZpnnyV/3U0Q0Jo25vp2QxoFcBgV GMXkaSIqYiYQOz7U6uNNLxSfSJ5NlVxgy+NpYJitT/R0uZaa8GXdsahfnGPk23RTVxUohJbE r+iWWmlbMU9V2tvb8U3b3/dvxKH5MipmJyfT8JDPt3rsae2mEdu763pwQ2r3HoFlb8rIu5K+ NSBldX4tJFQljIZCRLxImp/3kunKIbwPTP2hyKHilJ3VcjzfWdxB8j/P4LxhbQ1IAKRTSX3q lasp/nMjBPJx7IHDWMCANuVlyrGQJO9+eAbzOGtYSn4T2BS1zVnOyjQtsKROvDBNs2sp2p/g fPfp66cXUyYce17wT+/+JqMg89q6YZKI+OlUlgoDjG6lavUxHweqh6F8ylQGf4OKrCA86OXy zJ4+Aoc4+iwUC65lP8akIOou05KfvFhpVLxkda7z4GqFw6kPT58/c6EHsyB2JvwyDq7CqNNW CLEiK3cESG6LnupQBItL1u/kVkUqHO7Sx+WAViP847jUpJVrLktZCjzoJwdIri0iNYLN7XhF XzS2PNtdErH4qmXVlse3rhfrfcBH06nXWHkX5qq+j+TzNQlpeRthi7DT86H+y9SpcDm32bFV 7NIHxaJZxiQ2OoiRC/0M+a57NSpyqY/gIcL22YW5UR4k87QGMR0L/f7fz08ff1eW/Mn9pLDg +E5Rda9SE3ak9l5pVjjUXPGuNJXMAzVon96EJ4YqCWNrY499nXuJ6yzTsyp+oBlUyzZBH+q3 neUFJzLsijSM3fZCx9ARczNLHdJP1IqGWts0vZ8Gvjaymz6JfX1mADGMQo3aZw0XCY1mHfJw DBPKeEQMOTCO0Eoy9iwKPVcfIEhOXU/LdzZ4UJkvbeJTI7lN0jQw5xyXrIy+MpZCq84vemVM LCKcGHrNve42Vql+awmDx94QuN3m43hmKgWXR58SiP4oct+zvNkRPdKBhXrTmJ6nQJrbHNF8 m3GjQF9H4Y4ndcmpqIS1R2ru+0ni6EOrZp0cTkgsn0PmBo40YC+KPdHFBTnOqIP7y/89T2dQ qzwqfzSFIgLTKcvrzJWpYF6QULNMZnEvrVzGGZAFoalQ7J+n/8n36Jx5klgPpXresCCMvmBe cCihEyr5S0BCpikgdKC+o0PvKKyub0s+sgCe5YsES0oXiHwvp3L49o/9e265oVL5aF/jMk8c ka+cZA55+KqAa6l36QQ2xFU28B5Cxt2zM6W+C2womfycXSLeM+bHnuoiUEItIqrOAv8dM/Vg X+ZpxtxLyZ1H5loTIcBFmrJigtRVisfTCRpKDAIAAbithWCnvm9uZhUEfUPJ6uGNjzVsH1/S ktQLNzjErnSHaWWJHjhx2JPAIBgGPIG7DI5CbhD0L0mDUBHoZ0wM0Y2P9aGq0CUDr5kORk0m N9tJh4yg18JrL4UofDBoxPnz3RsvFl6UjApMkPXOSuc7FFTwy6VWKClRDcW70421R8Q0i0cV EzGPdDI0NweXKEMnUheuGcPB5FBy08wBYhjqJ8a3lrm8Jo0NT33Jp68fhTa3J4KnKEeM24E1 DKKQ8m4p1SKOo1SykFTqlyYmwLstcMOrOXgQSB2q2AB5YbxZbOCJ1TsjkyPkbU71Bmt3fhBv fDvJrLE5kvfZaV+KdTFwzdkzW5GZ9R1GPoWlvXt2miH/vJ/rQidNJ8XiIEIY7jx95eojZWA2 uZrd1eNpfxpOqqWMBtLXZQtbEfsuLXdKLIFLGacqDJJl/0pvXUc1F1chqldVjsiWaiqbDkmA 75JAyuUaKqkxvroOXcCRN8yWA2DgCFxLqoFLloMDkWfLLohfzS4OiVRZHkeeS42BxwQ8NW12 7qPrvMpTZa0bHqy71+r5uG9KEWvArB++o976GM31iNqN155oyoJFtONmcKjsUULnwgAPWVnb EmnilsIbmqyBUL4326kOH7m+SRtBTi0Zu1xarqj08UjIq8hrm4Ul9OOQmSVvc9ePE99W9Irl h9ZmMSlY9k3oJozSSSQOz2FEs+25bJ2Zs4CTPYIZT780xxoTdqgPkWu5yl6bOLSaJgoOuGrT R7SeCJyvGUX7NQ+IAvNBP7ieR0xzCEjF92OqJmLX2FrdkCOlUh1zvo26NOC5xPxHwPMsXwQh tdwgZLU0lHm2phIIEq5LrjwARU60PV+QyaXdyCg8EWUkL3OksVl9PMAQmpOJRJFHtDECfmoB qOGBgGrOLQFpbGkbXrB0azVs8953PGLdG/MoDKidJVeF7qUT24iSRVc4JsrOqT4xnFrVlbpE pyU4iWGr/5o2IXdgeL22/Rk1GdqEGApNm5LVTIke5VSfLg7Xj8k3OgpHQE1dBMjGE6aWW0MB OAKPqNRxzMUJU82UGNILno984vhmDQGIKUmCA1zFJFYSAFKHGHd4tp5KVe5VQ7OFD8mkKOfR owqiUuRV1ZMWDzPP4IceNUua1uMKWmRZ+bx0ezxyXSpxQ3IRgDUtoJLlmOfEZOQrddondMJ+ EAT0KpJECSFac70l4AosKUtyLPSjON0oyykvUnAzaKQLgOeQktXbJtoW4fpLO23tGsAOo0t2 Mgc2ZTWO+/+S6eWkVrFlK7fIcW3pxj6lE84cJRenlBNqCfBcCxBdPIeY+uBJJIhbYozOSErM N4HtfHr/YOPIYouyv6bQRtG2epW7XlIk8nXNijHXoWYAB+LEIzU9DsRE/TPeMgmtAtbHzHO2 Bikw0LsaR3xvc+SMeUwsV+OhzUM63kvbuw79UFFiILoe6UQbcnrgUBs4p1OiB7jwyvsTSK5U jTkcJZHtCdDEM7qe5aZrZUk88kh+Zrgkfhz7e6oIACXuthoBPOmP8Hg/wLO1+yMDsYUJOixD YChC4g1fg0diMxJQJHvjkqDIiw+VDSnV+NoLiIfCxl2WzYB2mTNgNW8/SV7YxkfHJU8oUCrI pNpPBLA+HfblEZ5lTifxoA5nt3srxaSbmQ1nrzPQ0Y5kZxjivME7cPAVZglJMrMWZZWdmvG+ 787gYam/X2rLE3TqiyqrBxFF+Yc/wZjZrM9Ix8XUB9PNjQhhrL4An9ntRSEYl1raUgI7Sfzr lYTWmpjd/ErBhWnVxEw2XVGeq6F8s8mzjqlTg966iALDmUnkLePR8FiGhcybzHL+xGWfe/8I dydtv1kWkRrr8nsxMopznXec1Q+cK/hfevmgvN6VUwOWH8gRXuNtcV0gsmrRkWc6bMerz1i9 U97hsp3yg/ewEgYYv8rrQ4eXScTXM6rscZy8C3y0RtgNdWFzfwzZ1U15tFhucthqV8x2S2j3 yYc9XTqVSS/khFquQXZ5mxHJAln9dRfNk9cW7gWnyHwQaeS1zMptE0DMHg5Y/hT9UuYt/SRM YdyoObb9YqQEz53++PbxHUYptzlcbKvirrcz0iAUKCUcAkjdQSKd+THp7mIG5ZOWvq1zyReQ mlA2eklsRkmTWeBh3b1qyqsSTGGFDk2uHnUCxJspTJ0rdXOH8Gx+JV1lQoLX3nOuWiZIm96y qU03wIMDi00tVBqWPPL1xIKGnprZdOys2JxLdOVB3UIPTVpEpBv5egU41SXjGgII58hX1R+7 RLY8IpQ5jMIe6oiLu1h5OVWuwN37jNU5fTkFME+qt0X1reZw129O2fBIPp1ZmMF1h83OFDDr s65lT4HC/wDLPT+Mlx9lLOBBwSuVA0cBKAz+CJ/Vixtn+zU7vuXrT1dYmgh4HvkeS74rBDBJ +jaRjwtWYqgPFiRHFucAOFbg+jm0nBlODHEckS6oVziJ1IFm3lgv1CQwZoG4pacOARbUM2om rr43P5IvxpE4Rn6qmAIhtTxWnrtrqXfF5Vt8FNqr6eRIUpp/KMeTSpHMEuY1Z6LgxZBsjzTT rbMGc9gwOUR8DB3SvRiCwn5UrcbwmKjGa0g8hmPk0iZcgLMy39orWB3E0VV7+4dAGzqunhkS bfssMjzeEj48Pb3z4UiG+CTbXUPH0Z6vZztwoEETu1Hrx9mSVphqju3zu5dP7/95/+7ry6eP z+++PAg3ZPXsFtD0yYcM6sorSMaOoltoAW2s71nr+yEXd1ku7g8ldDIu1toCLFgS6gh1SrBp T2oyi43xrDv0LHKdUNlo0BLDsXj7FGBsH4uCIaHNbFcG8tJlgT3XmKpAT+iL+bmymqm1RFaM raVcEr1BkZ5YnukuDCmp7EuwR5Ue6JbocQqL4jNtQviaL9tTTCbb2sBG3gnJTlooFg5AQAf7 A0j4+tK4XuxvTfKm9UPV3ko086afFmTJ/TBJNxq23VgAjYcgsogorP01uVEQVY90MiAaWRPG g7ixWH5j47QhfTI5g64hYaO1vG2fQtAYgZwa0G7uBei7mog8GTwaAt9E1x6lzkjobAxFYeS/ NtxQ7uFooZMsyBfSog4ZgHCafu6aUbucX1nAtctJuKZhp5a0aVmZ4aAFz1kWdjrRSUYi+3Hl Au0qIQ/mVR7UwMyWgNDufpqQyJH/01MtInYe8huhtlHIrBURdSDfsRhcmsgi9ZymA2lISGcq NJzNHCeFh87Sc8kWQMSlkCo7ciXZVhyr4LSyCNXnh5jOoU/NvZWtZk3qq2b2Chh5sUtfDqxs fA2NSM1UYuHbfexSXYOIR7cFGrS+lrC6SaqIrZGnPXQ7ZbHCk2UGo9g4onIFHSSUVQgFSqKA TBChyLFBoDLQeSVpSM4yQ2dQoFnLIVpm1nY2m0YoPw451WaFfRKbqSyETdl2DpwnSemqcc2H nliAeOQ0XbQlAzEfqUkYX2c2S0mZa0todXqrh+Kj2M5J4pCGGhpP4liKCSApf0o88pujlfwG 4o7gG3ayBvanehLPpHkZAKXvrCiYEriRv73uUtK8inq0iYvKFDqeb09Cl/5pJte3VwTl+9eT UB4w6lhArmGU+K2gKEdvZ728hqTkFf3RO8Fj3jXSTNozypXJVLJX6a0s6gxf2Wh+AlBn3b88 ff4LNFXivX+2p6bmeZ+BG661mScCrFh8Zz2x/7qSq1gA2aUec4gkTG+6BeH1Msv7h5+yb78/ f3rIP/Uvn969//Ll08vP4Obkj+c/v708wdH57LQga4uH5vm3l6eX7w8vn759ff6o+t/PD7Zz fp41+BAh/Pzh99XL04f3D799++MPcKuie9ytlHf4VT206F6INzd1Elft7nkLjuwl5YvTjt1Y V8qrKE4sCvokkkP4zupcMrJHpaz4n6puGgzf9UED8q6/8ZJmBlC3XOreNbUSG3jChvJ877l0 3oABx313I52Dcj52Y3TOAJA5A2DLuR+6c12U9305ws/Tsc36vgSVrKRc2UCt+Tyo98d7eeTD /qi09a4bDytdadV6PwG2dudFG5uSYNJq3vVMqVxRVuUw8BLL3iw4/VDmp12m1Zbx2cKHo60M bQbHwGRcFKhDlj/Obpakb/gHk2c5plV6rBts8rFW76vNob8ViQSGRz0MFo+e0IUt7QgHPrzt ysGjI7RxGMKSqw3E28elXj7B0IBJoTT9MXBd7fvD3jJqyOgG0CNu4Vojh0IeGEbVhg712YrV sSVSJgy2MnHCmD5UxXFgfSYNmWaFzYEltOl4cz1rypnFqTa0hCVaD0eyc2YLZwuX0taRYXNf B+1adnxFsNzccPzxNtCbCcf8orI2zrnriq6j9TqAxySyxOWACTPwpchywY7DlXZbi3PAmmie Da0WF1KG96X2plZpWzgPpwc0WODur2MQOo42pOe3b/R30+mKMpHaJZKwmhK4cPHIG1tYjiBk HzuUpboLZKfu/uimzpWkOiTVVbcLxqekE+sTtY1dStBdVsV7kxfznrmukEDMm4yxORjkBxlp gspxvMAbHUX9QKhlXuLvK4e2V0WW8eyHzhvqoAXguqlTz7uqOQLRV92TAHksOi+g3vcAeN7v vcD3skBNynTmgy0QlZHfGhk0RWqL3Atw1jI/Squ9Qy2+U3PwofhYyUaWQD9cEz9U3mfO3UG3 +orP3pgIaDlPNhBFBVvJ06GV8l54xibdn6z6yoWv417h6bl8Hrj3Cx1VaOVj2SEbMro0piJg FmXxYENBSRLZodihc5117O35AydQjqXcCFLmwBJLn4TyC2Mpe5C+h4yCFgWXzHVDL5QGkuZa UCrRmbdjTDoYXJl2BVePYzoBLqBc8yO913JRhY0ZKSU33V4SBuEXPEcD/8B8lSUBlHtIJG9O o+cpgUZYd1LdRgn3d1wrMVzRceLa6vzH6khgHMrjfjwoZh91oYV2mYCTSEZmnKevUQz2+f07 CGMAxSGkSfg0C8aSdJeFYD7IbpwX0h39UshUmLF6qTJmkVMRPA22WNXYNGXzSEaeBxDU2+Gm lis/1PzXTS9Djgq5LZ1bPygx6oDIm33fHQewO13oK+2ueuSAD8qWayK0nS/CTWlzQo/wWy3a ldax7a4eqBUO0UrecIDC08K4URr1VqqES9bABYhC298GtE1VqRD0V/u4Ho2e/jXbDbR0Ceh4 qY8HUo8TRT4yrhON3VFPtcltz6gRLY1p0JTH7kxLqgh3+3pjsKMIjJG91Pq22Q1tF/XcRGDe riK9+gPeQfyEUhunGCGS6KPjWOsZcNmJDE8DGF/FwZq26QZpTZGIxgztyzEDN4Fqrj2EmcgL kghHLtpQn5FlUba29czJ/7zOUxb2dYILVuCq9FjnlCaOHEPNxQq1CizjPf2o0zBqnkaEp/QQ 8FBvfDaWZQNRNEp72XhyEGLaig+WeEw43SCwW8asaxNrs2H8tbtBBtJbColqdPFYnzu9Gnya s5IUkRA98JmnLSHjYTixcXJ9vCAy1cj4BFvVvWe+nvulrtuO3JUBvdbHtlMzf1sO3VTjJaGZ trXIvr0VfGMiDeuxMfEdyP0gO6iW6DmvGlwb4C9jF2sIl7Po7Z/a4zG0gLzPn9ju3h3yWj3T WtsPcENRAiLGpDtk7H7IlVBHEHKZkAqEPftsHAVMGLto3fUXev/X9y/P77hU0Dx9p+MPYGKW cOTHrkf8mpc17Z0RUOEc1Bp5JjucO70i6vdZsbdERxxvvcWoGD7kawmcHNC+rYDh1KA/bbpg pwtdpJa0P2z5zg9RHiX7lYmiWaCjF1v29fnd32R04fmj05FlVQluwE6t6ZpQTgVCc7/ihHxJ dayr9t7S9V2YfsXN7Hj3E4v9z8w4hCml+B/LiwgEvErN/JdQO+XBu1Lv9vcAyLQbYH85cvEM QgPlECanNOVs0P4MW378Puslk0+RYt5GvpcYxUE6GVtQlHYyzlA/Qq3YosIvOKXizWgUeFr5 gJgqRxRA1a+AkXgsxyC56qyXQbYiQZLw+OoZxZ/oG6bgwLWNosEj9ch/QUOjilyZxpv0VvHz tGDya8+VqNceiLIF/0RMQsf8HDV0cwCWZ3DPWdP6x9pCIXU4sMCRfzUadrbp4sqoZY1BNtN5 rY7nrhcwJ7EceGERLuQZFUCrOZg2BQpPOC1QU5ps7lngWe72RWOOfpjSJ6tixomjEjuD3UwC YQgAHTqx1q9jk4epe73q3c3nV/iv0bPduFmFmvlu1fiuxcpR5tGOWrXV5uGPTy8Pv/3z/PHv n9yfcVcd9ruH6SzqGziOpXTvh59Woetnbb3agRDaGhUSdsgbbWoNcjTDIjqSTAQzPSMjLmDH yY6u8/jy/Oef5hIL++xeu+mSARHRzF72ma3jq/yho9Qoha0dC31sTMih5FLxrpQDYSm4fFlH FyHvT69ln+Vcvq7HmzF7ZgaLpbzCM7+XxdUP2/f589en/6fs2ZrbtpX+K5o8nTPzpWPdbPkh DxRJSah4M0FKcl84rqMmntiWR1amzb8/uwBB4rKg+800TbS7AHHHLvb25/PxfXSRg9wvoOx4 +evpGdONPAo9/Og/OBeXh/O348VePd2IlwFI03E20NMgjT2yukEHsiSjmB6DCO4hI9NYEIYx uhGyhJkJckWmN7YMyAjrMZx2DZxW6O/Dw7LWrB0EymGPEdp/VNC0KXStTAMCZZm/trAQVbVp aDxlyIakkSehoELfeKzPBT6+8SkwW/R8MoBmi8niZk67+CqC25v5UA3TK88J2KJ9B6REx9Px IMHBE0BYlp7PBiu/8ZrNdJ33BNoS+HIxuR6sfz7c9bnPdK1t3ZRUjZdVaGa+QQCGPblejBcu RrG8GmgTVjm/p4FKJ/PpfHm8+tQ3CUkwVwuIjmSTEe9zMUZcttOyLwNg9KS8YrRTHAnh7l/Z 26aDF6Xu4tuBrXQ2OrypWSz83P2tLndOzptOpsaWOvy8KiXNxnWzshYRLJfzP2Lz+aHHHRYe D7uORJh2ewYSCSLe6kBJuB211MKGcBrX5b09YIrixmNj1pNc3wy1bXOfLubXU/fzGFXN0PFq iNZlj0IYJrY9wnIjVBjbVlKB+TyEMXURjCdwvhCfkAgzdrfCHQBD88GKQsTWmpBmnTrFFTVO AjP1Yq7JVSVQtB2pGrPZuFpcEWMp4M0+qlzc8m462VKfa00eh/rnWv2qsgM2lWq6bAdEheAg xN5eBVS1q3Q6HmxRCftuTCw/gM8XY6pKLEHGuVUEcTq9MsNBd0XRYnjqHCnohT14pOBs3FKb B+Ez354lfYwMAmJ3Idz0DzQwpLmtRnBLrSXc4uNrckBubzwJOvvRnsE8DE7gteUwZWzvGfVi Yh4+xAEAG2cyNkzaVYmwMKIUldKvvQGWsfWQ6mb04fUrcVkQwzqd0ObYRls86wkm+TacOCuq eH64gOz3MryswjTn5HUBDA4Jnxv2/xp8TgwV3gkLDNyUsuSeOi4kwfCCuhaOIFTRm4nn1UGn mf0LmsUQjewDMhj4WkE/lWiEgkNxKKmGTegRmcyuPrhp/U8yBsnguNpuVeocrbbjmypYUE1L Z4vK44yrk5BBSHSCOTmfKU+vJ7OhXbC8m0nHF3cTFPPwg0MEt8nQJdC6Q1LHgOV/3/NrwgPP Oetk7sUvbTqZ0+tnFNk/OAFWFfyLzsTWN8TwvOsOIxXcw57IbMfJSRTuOMPnLeYCGmiJemfu 7Ef48fX9dPb1MUoDKTq4yilALevV6PSGZvtm2LT7LER7cUojF9SHiPEiCe77bmOcflM9HM1m RvYXlq4xqjpjjUlXja+3RniFIIsT62eXxPbKApc5tvHL3ARLHUCTxpxLd1UDK1OitLhPnzq9 mGmOVGMyc0brERFX4Eys44yVd16aCCSrj2gCn4oKs0/FZZh7DHzrNhMWYdBj0GRxRT1Ni+Jl zbnd53R1PaGe6tEAtY2oZDCPu2V+WNeWlKaV0e3r5W+M1GEkV2jBdEbXFrnEoGu67NTCWVbU lfuFlPpsilMqfT1aYZp3ijcMEPF++usy2vx6O54/70bffh7fL5T3zea+iEtanylRGPOhsCyv 1a6qgjXTU/ayMurzwp+jYPTWJog1Y6eVCWkUw8osNjwzWIkKE7Jt+KWmTirzRa//MHEGiCJh EG7iJgl41SQ8oN+bBOEKSUrKBkegDT0ne/3r/HA+fv0sNc92pC3Jv7HSxWifrKr7BmmcM+30 +u35aCdQXQ3WlnE87DxpimS+Ry++yvmGLQMvnqchzovzAXWYJgwx+izuEs681WFIU7omVhjO gvBTqGtKauVkYdHo7zjwG5imIgi3mFeKrTO5SvsBEniWh1XSYKBDRoZSlFQcjXDWdt0Z/uFu nTmfANxfWQobP8qdpmaJA4oPsLiNL8BmiCPasAZ9SzBQVRT6fTJ4ejP3+oIc1sxZevzt+PDj 5xu+wr+fcA2+HY+P341rVR4AjWNrKB3mXr+eT09fqQIimzLdFlbGe/iDtwXz2Ekq3wIZSoQY 7LSKeqIMJCl9PSISpCkEw78ntyuigiTTHQrwl/A7LIL7JA+iL+MrEANurg08j5MVPu8ZapIa LVxhaZLdiNYZfdGtebMq1gHe7NRdlzEQCngRlNbiwARBYbJtDkmGFrvb/R++MV42FWm9l+Zc 6zb+akJDzyFA1iktYBFLyfgjiDMinazL+N6I894CBB+DcSwdhHJ51L+pcBtG91DhHVs9G5+v 3Q+qDOUuRphlUu2gLZYVdseWpamU7jotQm1GaHTkIluTcgtKjabpkaCAViAZBa4DwkFX2Eed /hYOqM94ofwSrw0VsA+fCXm/YDOdyRVBWFtHEI0X6T4dhHHZ4K5OgE8lJwwpNhHNn6I5NVzZ RZXT97XI1vMRnqf5whd6RRCUy8pzdNa/s4rXQ19QJCKmMbXe8MUib8rVliVGiNt1AXOfi2tq 5fEK3RRCu+ixGC+GhzWFq3eg3SBBBBxNTIeI4GQpgsEBhiruh/AsioMiiIZI0DZgizTeWIZd BqAo8ESMltYcwI4n+d6/kD5YhgUD2Z1uAZqUVkE52I2We1pW7WQPUm18PRHNCNNiKFJkuKlE FOLpitYsSir4/9XV1aTZeU2aJJ2wyN/53A4lzc63Q9pPDU5LkQ4ED0A3wrJKiI1zyMfEtgHo vMFkoJSVeGvu3E6TIU+IluTBFjgrjwmUKnznCTIn/D2adVrTmjX5hZIPDaMwZQZIFoc0WbEr bBsEYjCZZ3XwulxhJKqizKfNsq4qD0eo6AaJ2s8By1F5P5gmh+7wJ6YD24o2Dvp90PFmlj2q jS5YYVz74QY4hLj7ms+2MwH5Mh9sFHBHqLOFm35ba/GwNpibF1moooyLQA9g17NXSugLTy8v p9dR+Hx6/CH92P8+nX8YASF6lmwg8gaiNzyinXq1KpQu8iM6oZn8iIiz+dSXCtSg8qR9NIlu 6L2iEYVRGN9cfdh2JPN5SepkHL35m9B7XynC7PAhidQffki1p58hdJIDbVykk7BwSj+0a0S7 kO7/Zo9CC0qrDvMm1yA//TxTEb6hUl4KI5O5nqs12ca7ioAuk6iD9seeiKhdME/Y9420eIMr 6wOCtKrpAegoqrQmCeK0JeC+mMhwpC898QoYDG/tDU5THl9Ol+Pb+fRIvqnH6MmB+hq34NvL +zdCGVak3HhuEADxpkw9gwtk97aoMVV1FiGz4srl0JT/8F/vl+PLKIcT6PvT239ROH98+uvp UTOJl0L4y/PpG4D5KbSfpJbn08PXx9MLhXv6LT1Q8LufD89QxC6j3SrZgTW8DOj9guGtK/el 4fD0/PT6j6/OA0sYSLS7kDJVLFKViUIdzO3P0foEFb2e9JlROStElg2W4lWeZ1GcWi8EOlkR l3iHBBmZDsSgROGQww2iz6JO0EWJ/KiigHO2i+3+OEF9+65L1k0z9Tsgg6EqiP+5PMJNJSML udVIYiltai1vwR0bOZ3dUm75LRmmJ5vOjeCDPcYXhk6nwADcLxbCDgncgstqcXszDRxyns7n uuq9BSu3HL1zKWzqkvbzYR4+OatoF5kdMCQ0G4NC+S/tR2dt1nN6ANSSFXivGZE1jSfNqiI5 LMC2QZhfzDKDUd97ggHmDWiExb+eR1F0pY1IbdRW7SkWvsUIv1X1YF7ejR7h2CLcyMq7Nru1 unnKtFmDgIrPb1n5ZazdSS1mN21A+CZfkINw2yxNpzrx8thUMCg+c0/58Ail87AKqA6VMQd5 HX5UZZ4kdqxXxAXV5oZOWdriD3zss80TBMu4TBjNkksClh48WleBRt9RRmvpWoIiHC889rqS Io25RyiQ+IKBMAxz5QtxysXTe+oLaNES4HXhHeKK9eHIrYKoFR+ot4rXJUjhhSdp0Cp1L3P0 ++M//3wX92q/IFuFpHih03O+NFuM1Qxny8R8vIMfyAo2k0WWAl/PzJj6OhLL0htTZDwiA1am oeGaDD89ekbEwByrDVccz2i88/AKFwBILU+X09nde5a6AX42oUedW22AOYnLZZ647BTx7A/3 a5mT8eqi4GBdlwgiCJVdr9qkVaoPLPxsojpN6SMdscBOlW185pw0A9CIereKFwK7qspADyYj b0gziIWCeQ/fjmBdDaUWAQJeUX77HTrltduUpqgY2RzHcrrfEgUdtIwbFcHPpvWF9nh9aBSb emmX5VZECLVaMTYAnBQH8breZy96ez7+Q3vqpvWhCaL1ze2ElroQ78vggCFQUv1pHRipvNDu HM5yM6Uk/G7Uizy9whKWWkyA1NM+nV9ESDuX64o0px740eRmgI0u0CMs+9SjqG7frWmBKQqj ZUBdi1HKmOFYDQDJmtDEMGkBMmlw1mdxkwFHFa9YswqSRChJ9GXGQ5hjtlxV0PzMo3vaN+Fq 7X5PexvK18CXq/7TwiA0AI+KIsC1HpQ8dhXn1fHb+WH0l5oAuYY6/fkT6jPFUa+LB9I6YI9h JKRHTz9FqE/OOYNVFyY6R4oSpcnUKVizFDn0cjI9Mdr5KNWzcaLDUYmqonuDgtxnTZyF5X1h hi5ZcTfUZyRB5CkiMMoxTtURuHXc1XlF7zSBCcnH26Cu8hWfNeb4rGruVYnmO2B8gnsLLTf+ w+N3M+Dqiov5cm/y9+PPryeY+uejM8XC7tJiwhG09SSWEEhkQipt1gUQbWIw1AmzMicKJOyV JCpjylZhG5eZbqtguaAAX202TwD6tUdfx4LmEFQVGTSmXsdVstS/0oJEJ3ooHDUifRncfMbT J/4F9a80rW3KuDSoQ1+dODVanJdoryYK0LtXLNuGPG9+X634xLDlUJDW5ObKgWMuUUCtVvoa 7rGAaWBVWetZ4jmwDIFHDuxqcIbVIkH9GEZTgn0Imx23o79jf0i3KauG5A/qnpK4El+93CJl vfTIB2EZpJ6BL/PUmRW1ajE/vMbUyN+ivV0HjVUu8dDyDk3zsopu9q/oCPbMJsHnsiG8ZM+8 XQS2VlOVZ3EFp/3WWskKKde88Xs3sX4bz6QSYm9THWkkhkcI33sud0neeMyQ0egz80wzlsQz tnUNjWh7pJYIjyPgDSPLmGnFKW59XQrNEuymXHdJhkvK/ok9NQbKDn0Akl9ZhPbvZm34EBYh JvYCWLMtl2Z2eEnu52fDuNjQSz1k5gGLv0XcAo8WANH7OEAlQGOH+NZp6iIEnsip2X98CPRA DwS6q9hPw9PllMy6GeZoyGhaYvgOgFvTgk78pDgeiYBpqUvp6qzm2LBgS7jy+P7y6en9tFjM bz+PP+lodEMWV+hsqjkYGpib6Y1ZZY+5MV4aDdyCzFxpkUw8n1yYaUYsHOWqZJLoUTEtzNjT l8W1tzG6R4WFmXlrm3sx117MrQdzO732jvOtx5jQqoAMmmOQzG79c+lxEkUixnNcVg3ljWVU Mp7MfbMCqLE938Ko31On+qY1lwpsTaQCT2nwzP6yQtD6P52CeojX8Td0+25p8Hjqa8mYMp03 CJx9uM3ZoqG40A5Z20Uw8zGwJqRNuMKHcVKZ6WF7TFbFtSdOd0dU5kHli7vfEd2XLEkYFfxB kayDONGjBXfwMo63VL8YNDzwiMIdTVZ7FKvG6NAZARRJVZdbxjf2CNXVitogUaIxQfDDtGff Hs+vx+fR94fHH0+v33rhSXBW+ES/SoI118JTiFJv56fXyw9hNvj15fj+TbPB70QjllXbpuVo e/ECWT40xUziHbIi7cVx04slwrnFpZjpz/rAELX1RzDkNE8f3WeBSLFsX7rKouMNZMbPl6eX 4wiEzccf76I3jxJ+djsk6sEYH5p7Rg9ryjiqw9h8a+mxvEg8064RRfugXNGH4DpaYtQQVpDK jzhDW8QGimdQHzDeIQh1+pOTxKc12vhuYvGQ06JWwCLLkl/GV5NZ/wQK34LjEfVYpsAHAmMk agMk2dQ6A1YTc4umyzzxCAA4w/k+I8OeygExBFj4ZFxyu+mSELgTFMNQSE2DKtxoXKaFkeOT Z8m93f0iF94G7tytcnwElgyhN4COCKmKon15p4nXPbCLhyOn4cvVP2OKSqqi7O5Jlv2LEWRv FB3//Pntm7FdxZDGhwrjzOqst6wFseiFFHoRao2o7fbLqBgGCE1HzecrE9NksMrh4PKke7CI Mdyld+4FbRmv7MaWwOJWgYirYaPy5e8w29wD7u31PfgVHOnu7CussEXxmPUbhCheenuliMqw Fiva1xZYaLDO4Kis2zVJUlnTpalKeVIvFbHHGhApHCFIbTY0i2vXXhqnCax9d2QUxttZVBdu Qea0Um5K5I5SC3SRQFuaNmmEW1givF+W2n44UJkz2+0Whl1XcLfiDVtvoPDwkIh+4cPlKsn3 bh0GemDB8I3lVymNP3Bbj5LT44+fb/I22jy8fjNNbvJVhTJ3XUBNFayEnBY3N0EZ/Rs6iWw2 aAZbBZya0P0dHJxwfEa5tfvRlByfwehHbwPf7IKkjg0XWBaKfZXXmmcshxM+6tiTvtMCjFck vZwR7ZfpZWm5IOMskreId/lgm7ZxXMizTgaHQ4O77sgd/ef97ekVjfDe/2/08vNy/OcI/zhe Hn/77bf/2txCWcGlW8WH2DmZlH2fDe/JrSWz30sc7N58j7oQbxeEJsI67THpla6DaMHi+SYu TIA4GtwGtLTez6rYZkmsV9iXxWM/KFh3FnPrq7BEga+Nm9avSq2+rtvOEW5yqLq6GKZa6m21 TojLH0YFA9DGcQRLws3QZp9y8rD19hj+7FAvzmOnv4wTI1gwgRg6Fyjtj0QJNQ2THswGIgTO E8Qi4B06l2C4YkgeQSwCQGpjqA+6zuXBJYXWcE4QKw1vldUweMjCLMBgqy0+GRsl28nRQPEd dzd+u/LvWj6sdDiwXvxpR6eJyxIz4Ga/S+aPUqYJXqyj0HjBOpMMo1WHrixjCU+CpQmR/Ira cL3GClErXLu0btRsRsf2ksQJ8PNZeG95oiiGmwtLWbXo3UiCGM1aoDRuQtxpXY+HsesyKDY0 jRKyVtaUEshmz6qNCG5if0eiU8HxAEGI4f5NElTKieWElIJbdyqBLVDeW8CwrU1WbZ0cIh+u vRRlU0LzZC6FF6uldBJWmILeOFHhL5jxqk1Q6QyaQ69MjjyE7mTaI+3OoaZ8JSaQNkAp74Cz WBEkxiXqfmKzh6XpL9ZObTt93JkBngErtsmNo8dCdVybrTwxZmwJhzkMtwyqYckpBk4YNXh0 Ti1BkMFpggJ0W5LMjtgRw6pUZMRH/QMq+BF3QLdQ8TKWq8sTvv1DCh+BOlU9e3Zgu7pLqu3/ wKTb+7mvo10UVQD3R+HcML15RMpyn35PbQ9g5bU9D5crGa+3PzaaJZyjm9SXV0/b6f8PSl9P jBUaAwuMzRXqR3efy9lybJdVslJMrjCe3s4wIo6QbWgmApDIYvn1TCVMCVzJoqnSmT8jnzTi 1OYIpDzZCAkcZrSsC/t+7TnuAC1BvcKlkPS268hQjuPvIamwXvIgkw8M7A+x7QxNVymed3AE JWGWN1mdUFKiwOtl3ZrpbSfIgoSts9RynTQo8LP99GpSLdo0NowLRmGvv86hQ3XLR4qnTd1J LQ7K5L5969QbrcObaLmm1coGlchnES2pF2/h0l1FdVrI/O+/XITNde5NU868XibyKcIvWSXL VVJz7YFOrIZul2tXXVcvfl9GMS47AYAybcrlO7BIm9FcHRZXvUxp42DkxzSuFv/+MqGxeG18 mTo48THdLK5HxLQmoKOo/W/XHY19WXUj2rKPehP7PrfiiXgmD8rAfMANi8AbVBdNWlLcBSCc Mvu9T9Yq+KwBESZL2dBUyRkVrG5hRFKSfqcoRHpbV2d7hpbI/lfbjgLDOrlmZfz4+PP8dPnl Pu5v43vT5AVuELhNkMUDFB729FW7bMuSx37NkYkQVeuuMtKSr8UQBQHcRBvMHyxzlemibauK x/BcXNi/w3UXGltGkVA8R4ta2cwzvhYBHxoJUQITaktpJrCs3RwyWrCBPYx2htKCmr4ggL0C RgOrwWTSMpf0wDLvux0YL9gmVguIJkY4V+JweP71djmNHk/n4+h0Hn0/Pr8J61CDGLq8DkQI Tgo8ceHGE64GdEmXyTZkxUZn722MWwitT0igS1oaAkgHIwndB37VdG9LAl/rt0XhUm9142pV A5qDEc3Rs2u3sMjtdBxGG4cuDTKQut02tXAj1GOLqjm5yMyCTcS4eFm3nqhaqvVqPFmkdeIg zGtfA7rdLsTfDhiVB3d1XMcORvxlOC2qNkuMv1NBXW3gvHFqNN/YWiBnaeQA42zNslgZ6gc/ L9+Pr5enx4fL8esofn3EnQUn6ejvp8v3UfD+fnp8Eqjo4fLg7LAwTN0BJWDhJoD/JldFntyb YYZVS+M7tiPWySaAS2untv1SeEq/nL7q0eDVJ5buoISVu5xCYg3E4dKBJeXeGboCP2IDD0SF cOCLrEZtuzcP7/9r7Oq2EoeB8Kv4CAKCepmmBaItxaQF5IajZznKhboH8Jz17TeTNO2kmbB7 yXzTJA3Tyc/8vceGXbBw3HOKuKHecGU5rbHh8LY/ncMeJB8NibkxZBtbQoPBmxqqnoQcPhcC rAbXqZiGAkEqvqgoFOkNQSP4hJYOyBjjO5Y4TVSksRL2iGNCOZt1+HA8oZsekdljnSzP2SAU cC3+4wlFHg9ChaLJI6Jn5VeI72mAmRzch02tl9BB87Xzw+93P7uAW+VCGda0XUWsnpo8xumg EX0hGnkKwEWdCBWSJQ//60QfpqaCkBgHBM6oTgIZ5A4RjADAS8I+FIitxsaEIgY65aflFjVi wqZuFei39ThnW3ZBpyuWK+bXc/cRmPD44065Eko1Czc0eslcQrQ50ZlFdkplw8s9qqXnttEu QYxotVqX8KddkFvLEPtXHTw2dRxaT5/j/nTSy1QgyXozBFfrxEBoN/0GvLsJ1V2+DYVT0+at wpUvn7++Pq4W3x+v++PVbP+5P76cqUFBcSN9SqN2dalMZi4HLYGQK4FFmO8uhjFOBpIgjqDJ BwElveEkqA8BAWrsEdRW2gF2NP0JbFEV22+2HNIUuKX2dwaGXXj8jaDznhuXQ9bh5JnAs9S3 B4QYqRIxrlU0Nf0Z5GHWJ6BLKw8wzcV0sbu9j5REQoyQOIAzVrSyZG4DFR3Yi57jsfw6HcsT q/Tu/O5+/If/szng5aNYjag+4yRSLCrS+YrOHEh1/5+segArKjMo4mtytgTHFTN34D3UlQdT z0WRwbncnOTNzcwPAS7rJG94VJ34bJvx9f2OZ3CQFuDL18Q9ejcUj1zdtu6SkbhIvj+eIVGM 3pOfTDW/0+Ht8+X8fWx8Hq15uDuXm6gYfHMh6YDEhjHJTc051V6SoJuKPof57IxdvDumm8uH x5WXLqzx7xFbFrHfJmLBZHOrOXXKNT+8Hl+OP1fHr+/z4RPvnBNRyQwyf3veAN1FdIdTZm4z COyV5+x1qpILvnzeTWVZ9EIqMUueLSIopJGtK4GNYg6CeFqIidWzlmAvpjY9AReQ5QibPhzU I7fXzybDdRN5LXzVyrUAa33ukQYTnyPcq+uuqnrnPzUa9n5ipw308RlEy36WPMf23IglkpTM sjC5ZmTpbYt708ft/hE3QQV55CIJD0Hcq6gLqYgrO7kmYWZ1MZW99TNBs0F0qncUXejdB6bC 9XefbiL19BKWe7Gbhup2NC0VovZQG4jeRel51Dmn6WQrmy2Q+7/hlte7xrdUk+sikliwYREs UpawwRmZuaYDq3ldJETXkEGZtHxYOOEPwTv4dyTdy+9mW+GZQ1og0cCQRPJtwUhgs43wlxH6 TfjN47taJ3IZuLyVeekdYjAVrqHv6AegwwsQ1g0JR/s4yVIBDhVZZjVNKVOsaZhSJRdaoRrN K5nnrAEJ2r2cH5YE9qCejRdsaXgy1SwPfW/AEJoKCa6NZSRTKbCYwhAxBr6sC6YeIVeDMdZT SmZZ6/M9Hl76hNeKvPRkEX5fUgKLHMIHkdrJt5Bl2NNZelIFJchpih4U8gluTNBQiqXwijiW IgXbvl6O/aJ9anYhVEFBupqSDP5364xNfSdw7GdlTOVoJfgLQbVLftyUAQA= --FCuugMFkClbJLl1L-- -- To unsubscribe, send a message with 'unsubscribe linux-mm' in the body to majordomo@kvack.org. For more info on Linux MM, see: http://www.linux-mm.org/ . Don't email: email@kvack.org