From mboxrd@z Thu Jan 1 00:00:00 1970 Return-Path: X-Spam-Checker-Version: SpamAssassin 3.4.0 (2014-02-07) on aws-us-west-2-korg-lkml-1.web.codeaurora.org Received: from mail.kernel.org (mail.kernel.org [198.145.29.99]) by smtp.lore.kernel.org (Postfix) with ESMTP id 7CCF2C433EF for ; Wed, 29 Sep 2021 15:21:23 +0000 (UTC) Received: from vger.kernel.org (vger.kernel.org [23.128.96.18]) by mail.kernel.org (Postfix) with ESMTP id 61F7E61406 for ; Wed, 29 Sep 2021 15:21:23 +0000 (UTC) Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S1345163AbhI2PXD (ORCPT ); Wed, 29 Sep 2021 11:23:03 -0400 Received: from mga14.intel.com ([192.55.52.115]:16287 "EHLO mga14.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S1345102AbhI2PXC (ORCPT ); Wed, 29 Sep 2021 11:23:02 -0400 X-IronPort-AV: E=McAfee;i="6200,9189,10122"; a="224619603" X-IronPort-AV: E=Sophos;i="5.85,332,1624345200"; d="gz'50?scan'50,208,50";a="224619603" Received: from fmsmga005.fm.intel.com ([10.253.24.32]) by fmsmga103.fm.intel.com with ESMTP/TLS/ECDHE-RSA-AES256-GCM-SHA384; 29 Sep 2021 08:21:09 -0700 X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.85,332,1624345200"; d="gz'50?scan'50,208,50";a="708406887" Received: from lkp-server02.sh.intel.com (HELO f7acefbbae94) ([10.239.97.151]) by fmsmga005.fm.intel.com with ESMTP; 29 Sep 2021 08:21:06 -0700 Received: from kbuild by f7acefbbae94 with local (Exim 4.92) (envelope-from ) id 1mVbOM-0002pn-4W; Wed, 29 Sep 2021 15:21:06 +0000 Date: Wed, 29 Sep 2021 23:20:23 +0800 From: kernel test robot To: Cyrill Gorcunov , LKML Cc: kbuild-all@lists.01.org, Alexey Dobriyan , Oleg Nesterov , Andrey Vagin , Dmitry Safonov <0x7f454c46@gmail.com>, Andrew Morton , Linux Memory Management List Subject: Re: [PATCH v2] prctl: PR_SET_MM - unify copying of user's auvx Message-ID: <202109292307.smDkJddi-lkp@intel.com> References: MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="jI8keyz6grp/JLjh" Content-Disposition: inline In-Reply-To: User-Agent: Mutt/1.10.1 (2018-07-13) Precedence: bulk List-ID: X-Mailing-List: linux-kernel@vger.kernel.org --jI8keyz6grp/JLjh Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Hi Cyrill, Thank you for the patch! Perhaps something to improve: [auto build test WARNING on linux/master] [also build test WARNING on hnaz-mm/master linus/master v5.15-rc3 next-20210922] [If your patch is applied to the wrong git tree, kindly drop us a note. And when submitting patch, we suggest to use '--base' as documented in https://git-scm.com/docs/git-format-patch] url: https://github.com/0day-ci/linux/commits/Cyrill-Gorcunov/prctl-PR_SET_MM-unify-copying-of-user-s-auvx/20210929-123259 base: https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git 5816b3e6577eaa676ceb00a848f0fd65fe2adc29 config: parisc-randconfig-s032-20210929 (attached as .config) compiler: hppa-linux-gcc (GCC) 11.2.0 reproduce: wget https://raw.githubusercontent.com/intel/lkp-tests/master/sbin/make.cross -O ~/bin/make.cross chmod +x ~/bin/make.cross # apt-get install sparse # sparse version: v0.6.4-dirty # https://github.com/0day-ci/linux/commit/37297835c68662e1781118a01b7a271277e965d0 git remote add linux-review https://github.com/0day-ci/linux git fetch --no-tags linux-review Cyrill-Gorcunov/prctl-PR_SET_MM-unify-copying-of-user-s-auvx/20210929-123259 git checkout 37297835c68662e1781118a01b7a271277e965d0 # save the attached .config to linux build tree COMPILER_INSTALL_PATH=$HOME/0day COMPILER=gcc-11.2.0 make.cross C=1 CF='-fdiagnostic-prefix -D__CHECK_ENDIAN__' ARCH=parisc If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot sparse warnings: (new ones prefixed by >>) >> kernel/sys.c:1997:58: sparse: sparse: incorrect type in argument 3 (different address spaces) @@ expected void const [noderef] __user *addr @@ got unsigned long long [usertype] *[addressable] auxv @@ kernel/sys.c:1997:58: sparse: expected void const [noderef] __user *addr kernel/sys.c:1997:58: sparse: got unsigned long long [usertype] *[addressable] auxv kernel/sys.c:1068:32: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected struct task_struct *p1 @@ got struct task_struct [noderef] __rcu *real_parent @@ kernel/sys.c:1068:32: sparse: expected struct task_struct *p1 kernel/sys.c:1068:32: sparse: got struct task_struct [noderef] __rcu *real_parent kernel/sys.c: note: in included file (through include/linux/rcuwait.h, include/linux/percpu-rwsem.h, include/linux/fs.h, ...): include/linux/sched/signal.h:710:37: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected struct spinlock [usertype] *lock @@ got struct spinlock [noderef] __rcu * @@ include/linux/sched/signal.h:710:37: sparse: expected struct spinlock [usertype] *lock include/linux/sched/signal.h:710:37: sparse: got struct spinlock [noderef] __rcu * vim +1997 kernel/sys.c 1968 1969 #ifdef CONFIG_CHECKPOINT_RESTORE 1970 static int prctl_set_mm_map(int opt, const void __user *addr, unsigned long data_size) 1971 { 1972 struct prctl_mm_map prctl_map = { .exe_fd = (u32)-1, }; 1973 unsigned long user_auxv[AT_VECTOR_SIZE]; 1974 struct mm_struct *mm = current->mm; 1975 int error; 1976 1977 BUILD_BUG_ON(sizeof(user_auxv) != sizeof(mm->saved_auxv)); 1978 BUILD_BUG_ON(sizeof(struct prctl_mm_map) > 256); 1979 1980 if (opt == PR_SET_MM_MAP_SIZE) 1981 return put_user((unsigned int)sizeof(prctl_map), 1982 (unsigned int __user *)addr); 1983 1984 if (data_size != sizeof(prctl_map)) 1985 return -EINVAL; 1986 1987 if (copy_from_user(&prctl_map, addr, sizeof(prctl_map))) 1988 return -EFAULT; 1989 1990 error = validate_prctl_map_addr(&prctl_map); 1991 if (error) 1992 return error; 1993 1994 if (prctl_map.auxv_size) { 1995 int error = copy_auxv_from_user(user_auxv, 1996 sizeof(user_auxv), > 1997 prctl_map.auxv, 1998 prctl_map.auxv_size); 1999 if (error) 2000 return error; 2001 } 2002 2003 if (prctl_map.exe_fd != (u32)-1) { 2004 /* 2005 * Check if the current user is checkpoint/restore capable. 2006 * At the time of this writing, it checks for CAP_SYS_ADMIN 2007 * or CAP_CHECKPOINT_RESTORE. 2008 * Note that a user with access to ptrace can masquerade an 2009 * arbitrary program as any executable, even setuid ones. 2010 * This may have implications in the tomoyo subsystem. 2011 */ 2012 if (!checkpoint_restore_ns_capable(current_user_ns())) 2013 return -EPERM; 2014 2015 error = prctl_set_mm_exe_file(mm, prctl_map.exe_fd); 2016 if (error) 2017 return error; 2018 } 2019 2020 /* 2021 * arg_lock protects concurrent updates but we still need mmap_lock for 2022 * read to exclude races with sys_brk. 2023 */ 2024 mmap_read_lock(mm); 2025 2026 /* 2027 * We don't validate if these members are pointing to 2028 * real present VMAs because application may have correspond 2029 * VMAs already unmapped and kernel uses these members for statistics 2030 * output in procfs mostly, except 2031 * 2032 * - @start_brk/@brk which are used in do_brk_flags but kernel lookups 2033 * for VMAs when updating these members so anything wrong written 2034 * here cause kernel to swear at userspace program but won't lead 2035 * to any problem in kernel itself 2036 */ 2037 2038 spin_lock(&mm->arg_lock); 2039 mm->start_code = prctl_map.start_code; 2040 mm->end_code = prctl_map.end_code; 2041 mm->start_data = prctl_map.start_data; 2042 mm->end_data = prctl_map.end_data; 2043 mm->start_brk = prctl_map.start_brk; 2044 mm->brk = prctl_map.brk; 2045 mm->start_stack = prctl_map.start_stack; 2046 mm->arg_start = prctl_map.arg_start; 2047 mm->arg_end = prctl_map.arg_end; 2048 mm->env_start = prctl_map.env_start; 2049 mm->env_end = prctl_map.env_end; 2050 spin_unlock(&mm->arg_lock); 2051 2052 /* 2053 * Note this update of @saved_auxv is lockless thus 2054 * if someone reads this member in procfs while we're 2055 * updating -- it may get partly updated results. It's 2056 * known and acceptable trade off: we leave it as is to 2057 * not introduce additional locks here making the kernel 2058 * more complex. 2059 */ 2060 if (prctl_map.auxv_size) 2061 memcpy(mm->saved_auxv, user_auxv, sizeof(user_auxv)); 2062 2063 mmap_read_unlock(mm); 2064 return 0; 2065 } 2066 #endif /* CONFIG_CHECKPOINT_RESTORE */ 2067 --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all@lists.01.org --jI8keyz6grp/JLjh Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICAFyVGEAAy5jb25maWcAnDxbb9s4s+/7K4QucLALbNvYSXrBQR5oirK5lkRVpGynL4Lr qK3RJA5sZ7+v//7MkLqQEpUtzgLbRDNDakjOfaj8/tvvAXk+Hx625/1ue3//M/hWPVbH7bm6 C77u76v/DUIRpEIFLOTqDRDH+8fn/7592h73p11w/WZy/ebi9XF3GSyr42N1H9DD49f9t2eY YH94/O3336hIIz4vKS1XLJdcpKViG3Xz6vvT0/b1Pc71+ttuF/wxp/TPYDJ5M31z8coaxGUJ mJufDWjeTXQzmVxMLy5a4pik8xbXgonUc6RFNweAGrLp5ftuhjhE0lkUdqQA8pNaiAuL3QXM TWRSzoUS3SwWgqcxT9kAlYoyy0XEY1ZGaUmUyi0SkUqVF1SJXHZQnn8q1yJfdpBZweNQ8YSV isxgIilyBVg4g9+DuT7T++BUnZ+fulOZ5WLJ0hIORSaZNXfKVcnSVUlyWCpPuLq5nHbsJBny qZjE6X8Pavia5bnIg/0peDyc8UXtXglK4mazXr1y2C0liZUFXJAVK5csT1lczj9ziycbMwPM 1I+KPyfEj9l8HhshxhBX9vosruxF9vGat5cIkMOX8JvPL48Wni12OK5hIYtIESt9mNYON+CF kColCbt59cfj4bH681X3Krkm/iXKW7niGfXiMiH5pkw+FaxgHg7XRNFFqbH2ptJcSFkmLBH5 LYo9oQvv7IVkMZ955iUFmKXe+ZEcXqURwDDIXmypvgvVugGaFJyev5x+ns7VQ6cbc5aynFOt aKCbM0tpbRRd2FKKkFAkhKcuTPLER1QuOMuR3Vt7U+zpQzYr5pF0N6V6vAsOX3uMt+rG5oTe lmgIcviXWhZCG4dlgdqttfeh1cUsanYDfvXtBoDLwW4isEiznK9asRJRpJdSs+jOZklLzliS KbB7qU9aGvRKxEWqSO5sT418YRgVMKpZEM2Kt2p7+hGc9w9VsAW+Tuft+RRsd7vD8+N5//it WyVuVwkDSkL1HDydW6uVIQoCZSCxgHeMXx9Xri49/Ckil1IRJe2hCITti8mtHukVf02z6aOb VUveMQkP7VmEXKIjCO0D+YXdaA097AOXIiYKDXe9mzktAjkUD9ip2xJw9sLgsWSbjOU+pqUh tof3QLhXeo5aHTyoAagImQ+uckJZy169E+5KWt1cml8sbV220iWoDV4wEoJX67QoFujVQE8W PFI3k/edWPJULcHVRaxPc9mj4WnINkNDI+mChRDhCK3N+iDk7nt193xfHYOv1fb8fKxOGlwv zoNtj3WeiyKzIomMzJlRGWZFHWCT6bz3WC7hhyP28bKez3PEBmF47yaKCM9LF9N5gwjCL5KG ax6qhWfGXJXeOes3ZTyUA2Ae2gFBDYzAUHy2V1vDQ7bilA3AoAm1wrtwYzZdWMIl9cwLVryD SkGXLYooiz/0yDIDaXVMRKEgQpRjjjEfw8F+jKFSpnqohuEFo8tMgDCWObgIkVu7YaSQFEpo 1i3ErYSTCxnYX0qUe6Z9XLma+k4W7Z9lamM0iSsdu+TWQetnksCEUhQ5nFQX1+RhL2AEQBMn diYpHIRfHcYOEDWhGAy98m4moD5LFXpmnQmB3sg1KBDyiwxcMf8Mwb7IS7CQ8CMhKXVDox6Z hF98hhScsorB0FKWKZ1eobFzzgbxOiYqUhLzOeQXcSzWHYkx0paug/PgKFjOOc6ZStAN1VHA WICIZ/MCRbQA/Y69Pl8HkDpssY2Ttot2kjN3DBCRsDuF+7LmVYWybal+BJ2w1p0JHc107MPm kDjynaTmy84M2YqlygbIRc84Ei68W8BFWcCq5r5oNlxxWFC9gY4NgMlnJM8hXvTF/0h9mzgD GlhJvLvTovUWov4pvnIEECVABxLeDVlSnTG21MAeC0PmI9VBOUq52TSHy4xOLhyt0l6sriVk 1fHr4fiwfdxVAfuneoQ4hYB/oxipVEfj8Jp5uum9sfIvztiwvErMZI1fdHiWcTEzJt1nQCE9 Jgoy66U7hPiyF5zJJRN+MjIDAcjBT9exXX9u7dFiLsFqg36JZGySlmxB8hCCC9dUL4oogsxe BwRoI8BgezN6kE/FEu26sArCI06bILGLlSIem/C5PQO3CNGFH7nrMiHsnKFApSEn1pRJYsV1 EEWDCwU3tJa2I9JWDraoNrmvtsfd97pU9XanC1Ont7q8td+9vpx+2Z/Lu+qrQbSOpIm5HI/d ABdrxucLNUSAvvJZDg7OhPI9Tk0ACqxmwja02dxUamKQNdD2qRH+7HjYVafT4Ricfz6ZGN0K 8dpde39xceFoEnk/ubiIR7Jz8n56cTGGunxh3IeNO65FTCZ2CIlnWC6KeVM9GeC0UKEPK6+W swEW0ntQ3w3ukyvbiS+yhMRXb6vsnXwERgzsJIgObqs9z+JzORlZP6Cm174lAuLS3WIzi5/2 5rKrDuoqg2bJLSBtmH+XNabE6p/Xdr0kEFpiov3x4T/bYxWEx/0/xjBqOMmTQOr8Bsuy5+Ph Xg9Oto/bb9UDWL+Ao9n7ugVrCC85H3aHe9uowngI+hKO6qwEFT4/0tGINYSibfGj5f7/xUSf h+wXeMgGPDSen+fJmuQMfWhCHK8VrSHpqOMWf+ZdgM+VZSI2Zb5WiZdmRpOr95tNma4gNvVS zIWYY2m3ZmTg71T17bgNvjbHeKeP0c7nRgga9EAATCnn+RQcnrAOfwr+yCj/K8hoQjn5K2Bc wr9zSf8K4Lc/7TMHoFcIf30yY8TIa1Ts4PRU7fZf97uaZcuC0QWRErY2phBZ29lcFtIG6QWW sIWpi5GqVfhGZ8be75TD0T/sz9UOden1XfUEg1Eg63VavOZELsC129nQUhcFLRb/LpKsBCfL 3JhSgWukoOK3Uls5LLz5wqmcqf6Ephjth/4LOZb0o14mYJwQ2E4wk3M59EZd7VRTLoRYDv0c GOSSh1j+X+SMhD0DfDmdcV0DLPvz5gxeCaFJ7bkhndalMjsc797v7OQLWDtstdnQtCnYJF1y gUB1Qxdz31SSUYzXXkChVXbqIoMhA8Lu6GsMJZA4jwaMsRK6DNpjIhFhzUjGKEZYViQkwiKG M4YAvUS/ibvQGy1FpLB8DGIg1qnZ9MEmSTNaB4zgmH27AEQLKzSLgU9IGOgSVDB0YuI67DUC gMmSLzSGyC4VJYtgNRyD6yjqe3BkSioQNNX0NPK1lcP5UC0LWB2zo3Y5MLNzKlavv2xP1V3w w+QDT8fD1/29UwNGoi6I6YLXl8b2I9x/sStWPSvBrNTWYp2OyQTr7BP3wDE9LXWlQA1kwckU DTVQUqw3ktDrkmqqIu1TdPi6Zyf7b8NKbdPMdfoBHZ8efmruKXuJHSQaKx1YJHJBJr9AM536 CzY9qut3v0B1+eHKv0sWzfVk6tsMo0WvTt+3QPBq8AJUnRytYb8ZMko42oPsE7q9xBEirF0N 2NYlIixmSkjiurJkyRN0Gq5IaJcDkbyCRb49fdk/vn043IF2fKnapEp3lGFOrPJIbnx1I/B1 Vbt9NKW/mdRGJbGzSgsH2ZavXKjYPOfKW0msUaWaXFiNrxr9WfRyYUSsZ/5ujBkE1ryMfCVU REsWliIjcX9K0/6HBIXmt7pcN7BR2fZ43qOZCBQE+26Ng+SK6xofCVdYLvTpLUn4nHSk1kHJ UEgfgkXcAXcxVI8Ve4HJp3LFYYxo+hFcdE0HK3ICOi5M4TiEeKG+/NAJbIde3s68ta0GP4s+ wbl1zU/nfe3qZWqlpfVuy4yn2tCBfwCnOMBjIFPjX8J5x65BptjYYBvpju4aEHrz2H+r3fN5 ++W+0nduAl2jOjuHP+NplCj02H6ZNGhJc56NSK2hwP6EF4/RbVgkmTf6H2NQc5hUD4fjTzuj GwTQdWZuSaNp+dv9xcbHZzHYikzpTYOQQd581P/1Rs7QQtXy2rpODTKxCO1rlx2o0F61CmsT OUPL5nR8QZXyHnfwQxkfZTcDURVKiONmhWUZl9Jab9OTxQQU5kUVDvObq4uP75z4pw7K2ysR EeFxkbsq42A8K0wZaEsGeTDGW0uLBxozsBoYjFowpzuWkH6rqgXZoRoCdcrsgiCzJfLmfcfq 50wIvy//rCMcQT3smwQhIZt2z3TVKJndTC4urCp62FQqMVtZ+uvpsAu4CYOe+7zIyn4ipkU5 3J63AdlhuSVIDo/78+HoBIchSVyZ04ByhafpVZyxCRv8uO50x9leZUir838Oxx8wgaVhlnug S+bX/SLlGy9iE2a6G8n6ZfPWkI3MCHC8fYY5TkLypVcMUYszvJcHLj+yfHIzNluYaypwPEnW 1Io7GpNQed9OlLfCray0LMmth1nOwznrP5ermKR13tZ7fU0Ak/htqUHTyMeGnvXDxXTyyZ6x g5bzVe6raloUycrmPmQUheDBkjoNKXNRKK/PjGPLOMHDtIt4iCLxsnvE4IdkWcxqcHfyWRj6 F7+ZXvteSbKZPT5biJ7sNBMzxnCV11cdFx2sTOP6F92VBOlIFbFSDIvSyG03SUJoO6/T6Nbx g3cpIfW1W8JUYvNb4KVFe64ZiB3RwZfv9Go1sgc0sDLkxGeeWjy4rQzTamewDq9aGt9wl6IJ lx8sPYMwZKnfbm1TFktHFzWknEvR078ylb5LGAvpFDk+5congfXtBm0Ecu5MbaGMbfCFsVq8 N+hQb8u6Tducwqe4Zw+Dc3Wq73G1dnWA6iFsG9qVPZKchF1Im213P6pzkG/v9gfM9nVp2gpq CGiCpVjwhO6AYKfNLknBUnKRdIS5kOzmoa7Qb96ANj3WzN5V/+x3lVUq7Zz+EjIxrwi/Q7Pv y0KyT0wt+gJ8CzJS4pWRKPQ7BItk4ZLUBLckscPwFxfQCgNJbTbgsczJ2ic1gJnRpE88H6P9 e/Lx8mO3swiCiBLcQL29AAhCw1M4qD8D8cpwZkM2HmZljBP5WQAD6s5ASUwh2FZ4dcN1Kogl 6uNkZKYoZpsBP/Pcx0+RXnF/EA/YDTZeNz2OHQpsV46th9L37y96K0IQbCzxgTOI37Eo1TsF yCnhZxT2WU/6r3alghK/w2+QZtJREvk3GWnQaSwWRdO5y2kNLKm0hQZSxmDftKUcTcQxC345 mfj1R6+RZtPriU95LKzeGh+4lCQ1JYzu0uaQI/eNphphbq/57z94NKG1FPZFYLy5wEKr3g2Q PELP4gGVyim1wNiUZQMALM1THG+Quq1XvhDrAeHCW2ZRpVNGwkf7/h8AEhnpj03c1xIhM4D6 p+xyHXuIr3FjWmz3z9X5cDh/H9rubjTWnmJnjxeUFyRXPli5uOq9vEHMqPSFjRYFUYvLpbMD Dcaw4MOQ+bvNpo8JVTzpMzdTl3QAiwsGWuloucGs4H8/s0m+inv0n0CYZOK9QKeaMpPlc0Y3 vQ1xqJ0JrHnOYibddkU0x1hxMjjQFvFYVXen4HwIvlTwXqx83GHVI6ijzIlV4qohmGbqUq9O XjFpvbHy1Txacu9FLIx0Pmb92OtjVi989Prmx2zYUrKMAvfXidLIl3NnEjKwmDmhI9hwS73i tSpS516HjqyxRpNIx8thYUKsRpQZQhIlRNyEpsP8e8RZmytklNsvyrwSllEtkF1tR3epncxE Q3RnpKR82CXK6Ovd9ngXfDnu775V7WWKubk3VPMWiH6JixToeAmWpuwqUGE6UgsWZ3Yb0QHX tXOrNQCmXCXZyJ0EkLM0JPFYtyDLzdzttQf9pdVgme2dgfvD9k7fNmgOcK33xuZW38xpJ3Q4 banNVWSzIP/Vz5ayaT14PVWfr1aNSap0utoUKm1ZMO0KG+vP94yfzPmYfLaONO/7UYcAfUE9 DWSKCYi7//IIkhF5m9KGWLdKPFLbXiPLisaNd7ufs7m5tuI8l3xKBzAZ8wTF76EPtxvtLSzh A8Ik4WL4Jrt03YymdOZ7TUlWdqwQYj60AKEJ8bOHyI0BEBmxlJoanv/y04jatRdcjAtwQjS8 DmT6PXh/sYxHbu2oSUmy2Thu4zMvidgotxajXWvJN9nVZlMy/3zo4ADHfVffkwWvLUaX7RmQ z75bt3GalVul6ZThV6KOkcwF9dyLbcQulZasJCp0HrT8tmFx1w162h5P/fxU4W2F97qP5Fcc pIDU7t0l7NKAyqKhiW4SGRqXHRG1UGfaBq4vYn28+DD6/pYQfY+8Hf2oAmmBEO0ZT8icKeL3 shadyv35AJKg/GcyfnHZoCD6YwHPshtUCHEMHu9t3TJ9PRmdQN/01/d37YtVQzLsbok0dpKN 4Tnrgy7g1yA5YL/N3JlWx+3j6V5/5h3E259u1w8PO16CJeutxXDeOz8NLHMxcFHp4VwF5+/b M2Q+wenwUAW77QleX8x48OX+sPuBI56O1dfqeKzu3gSyqgKcEPBm0jeWV1NWCJ4Onsp8basN R5jnqHLIz5yxUkYhtRckk9I/VAugyAbS27ZewUQmRPbSIPPRHUne5iJ5G91vT9+D3ff90zDP 0LoTcXe7/2Yho+bjVQcO7qZswA4zMAPWN/WXJ8L7gRBSoamfkXRZ6g+1yokrYj3s9EXslYvF 9/OJBzb1wNDwYnr30MeQJJQq9K0NQiff1z8NulA87ikfSfrz5MLvULQNnEkwtV6T/cIhmi7q 9ukJq5I1UCcbmmqru0d9a4sxFKwe9xN7Jy8YssWtTEY+6NbWiV5PL+hIrR8JIFbXNKMESl5f e4su+vUxUblbM/y3lZrvG6v7r693h8fzdv8IqRdMNZpi42vwW4Qoxns2D15w3YvXXyvcurLU 0QjlBJVaXOkim14ue3eEegRXH+J3Vxfum2XGSA7WgPfFR0o1vR654YToeOwSsTnMHtbmRIVm ozsYPJdKKBKbdNRuN9dYluv7ZoidTD8MTPXUxAQmN9uffrwWj68pHtUgUXPYDAWdX3q14N+P 1Vh+yHDcA0aIuYHrxgQpQ4wXWJ+2OXr3zBuK5tvifkRRoyEtloW3s2xTecSmQU03aGfnLx1p TtZ6cSMvwZC6XqG5KkIp7OU32L3g9Pz0dDiePfvE9J9McbW4hpdyjY2OpNcwH6Wd9f8iQ3Mj xMNH22PB09Pcxhk2xv/H/JzilfHgwXS8fU0OeLUZ4Hvhv0/VUyTcOO/nS3WI4MoMxgzrWF9r lgsRh31lMUEFm9V/D2V60cdF4Lt7Xxc0qHlcQPA/zkl7B84ZubiFTBrSAF+HUlmpn4jskQL/ JANX/Wqljcd7eKGa+SYGLF7VUTlj9gvKpZj97QDC25Qk3OFCX2kxdbYO5qSOImr6qg4Mq0XO N1P6KkyCH1o1hR+Mkurb6tZ9Bw0auYGHfZnBLcC0gKXDg3VvJTS9uS71q0mxJTssT+UzsFf7 kykHfql22+dTFegcK5IBuDF9X8IMua925+rOucLVcDHzljprLNrwAeNoqs1ftZi88+EG5l2v q8yWioYru9Ngg+uMXN588KPXzV0h694F0aeFdbzxhrTZYGPHVwkLZN9OIbRnyzVIf3isa2E/ HXhEZmCkZY/6/zj7lu7IbWTNv6LVPfaZ9jXfZC56wSSZmbT4KpKZSdWGR10l2zqtkmok1W17 fv1EACQTjwBTMwtVSREf8UYgEAgEdolC6ON2LzoECEQYLLDuHtqjkvLExc6WvAYE3o6+DyPV jCtwGBCLMkekvuMPY9rU1FhNj2V5N02Ty/Yj6Tau03kW7eWMvnSwpHeUKTerkqLujm2GZ7jc kCRUbJ8dkhF6lXYBPOSB59inwLKwQGZLRlLnVZIZ3LQZAoVh21Dli5u020SWE8vXm/OucDaW RUVN4SxH0K9Ax+7qtgPFs3BA9RR8ByfG9mBLp5gznWW+sYYL51AmgetLQQLSzg4iylKDghEa FFbGxp1v9V+ykOYtP4Mdu3SXScpF4qgiiy/qWYO7Cm1B53Tob0fYJ12IvkbkwX80chkPQRT6 YkkmzsZNBkq1XdjD4AVaerB1G6PNocm6QeNlmW1ZnqjvK7Wbbrz9df92kz+/vb/++MbuYb/9 eQ+b+Jt3NCsg7uYJdQsQtl8ev+Ov4pTqcSdHTsv/j3SXkYlHkDFuERvhmCNLDpL3SnNq4iqn ZYIkAfguJunyWcHVeheZ6D8vmFHjPGXR3wRZx1Cqaw8SFYgU54RRpkMWsfSMPq9X6ihkhZ1K ya+a/gTN9O9/3Lzff3/4x02S/gLd+DO1onWGI/lDy9lrfvTANpz5z1/TiqpwGWD984RaqlhD LLJSa+0Kz1hkn1HGKer9nnY1ZeyOuXigwX9eAFmb9vPYe1M6n9nLie7eJSQ5Z/9SnA7DCxro Rb6F/yQb1czCIHDqHWsF1TY8YXo3p9ROa60zu9puTj6lNxfUtJG0EHrrQgbu4Ku4rG30Ccgw zRaJVLyEbTh0RXbDSkYsDZMD30UH4Zcisiy7sd2Nd/PT7vH14Qw/Pwty4HI0lrcZHlOTjbGa iKCzZD3hAMKL8fz9x7suhgRrZ3PUF6XD/etXdhCX/1rfzKP30n2wb6bbaR+XmbrKLZWhEl0q ShWT5wky/B7U6VdBv5p7pZeCw50oHQvdnzfR2PR3wuZkipNnIk7qtuMHl8SLFGMVYAAk9dLc ZLJ6fbx/0u1T2FRxMUaOb0mz8EIW4yOZTa/iB3YAik88nmIgqYJKgO3QSEq5B0qZs5WD/D65 Vo6qHY/syMKjuC3G0ANVeoaQeWRDn1WpwUNXBMZdg1cbTpjatSqdpQtiMsvUCRltpBEheZ1Q KqpU596JosHUoLXJFCuCiiaxo4E+UBJxZR/4YXgVBsO/OeSGE2+pdtU+03QbAtcMlBFdRLDD V1M7b5MydELKDXJC4Tndxa1wOgp6/gU/BjSbZExHIUTZlEJcbmNIw7Jpq/WMwn3UGqDMupr2 VpwASdF0ockXcMIQRkQVwprrKgBWoKO50UDHd0HzFjc9An0gOiMvV8sN7DGL2+IuIS9STSic jAXaV9V8Z8ZFRNh60xxADaA9WSfEocPZ4DoD5U45d0It35CaK96tzudTH/mGkDDzMFTmqlL2 fIeRB/RmLUAg5/Tuef40SaphVQx0iR3kXbguA0C0brM2jdWwMTJqOnQ3V2Ta9/zWx3vZKVHm M54qUQUeDjR+N1hdCkTQNj6mGCbpn7btO+J9LgKLani9XrlyAL1XXQ9U0LQZb7rxGrJsOucq KG7Ja2ucuetgADRTW6lfXphU3QhsXqFTONkr8Fc2MJeofJ8noJC0xFBk7ker8rxr2tWFt+tL lw5nPTfZKdser7YZbATW2DCIV/PIi20Gatd47HIq/PU88UDakKN0ZjDHTD5GdVm0gMhhtxxf SSqeKmqTvi3GfcPcVWVWxbeUqeSbWI2HtJBOaqpx31Hne8xwjaruxXB1mp3KiIHG9sXkyQGk McdU/KbTeCSyfy5W5MmgO7WIcF+rKfORR3IUvAQZlVlHuMeRZN+78DCIh2E5ZCi+i2HH++1O cwsTkeRWjHNAOmvZsxjkaU3t3nnxMHrUHMB63mtynfM26ThmW9LTqWpAqRmG68ApQXQLJ2CX 4my1drg09OE8RW0hSDxSZV7jbWtBIFz429hzKd3rguC+bGIrXHi6U7L+OegNbbVPqMIxcUIx mKZFMsTonxdyNtxVdUdxsCcoOkZg6uU4OwsvgYkrXgy5cAZQnWFBWq6EMd/hmy/EfvQyB++q hN27IzdP6J2Mtwg9y5Ku2cxU0Y+gS1rHG0RTqjF/wXydncqMkiF9Aj9NSfcrMEyf5J0S+Wqi agTmZSrZUxbymLQ+rWvNoNxJPgbSlHYCA+tmXmV1RZUG+dXxVPekVosoloPYTEg8QQuh5XS4 W8m76133c+N4ZCtMPCzAB5KYGnPiggpT3KFLKLsxqdMJZL0T7cq8k9sjaATo/7c4eF8uCBFD Ck1HUFjNcC15HmN7bmsYv9DotUzmQaEUGos8epKJ5XGYZ1j54+n98fvTw19QEsyceZtQJQA9 bMvWWkyyKDLYu0puuTxZhqAk7MLmeWvfFX3iuRZ1NDIjmiTe+J6t1WRi/EWl2uQV6gj0kjZh 2oxcoYCbZkIaVPJlMSRNkZKqy2rDyklNtxLQ0GUoSTd5mS9jJH764+X18f3Pb29KJxX7epsr YwCJTbKjiLEo7ZSEl8wWIyK6QVP2TKxDPviHVFJdLwOah6P8FzpRTz5oP317eXt/+vvm4du/ Hr5+ffh68+uE+uXl+Rd0TvtZzYDvVIw9ydd5M1u5ByozhyE3pwwbOidy/TU+KBBtTesfM+K2 rigjDmO3Sdn1W2XeokyZVFspsTQ+wYAkNTE2ZDGoNruGIpvgFaZyZ1rhCtYgOe9572PIPSuz k6NOFK46mNtPlRjKsNofYIOfGqxpHNLRJg22MpUGzZfxQOw0yvIgI+rGNdgEkP3bZy+M6BUU 2bdZqQkHgV00iXNrlkxGUxjj9oG/UrCyDwPHPN7LUwAK58rngyE6CS7lXPE28mscdubPjfZY xjxTigZyQFAZB2VTmUujWE4lHnetMJjDENDmBtssY9665mw7N3E8gy2U8Q9jCWKatEcwfl72 WaJOJKPtgDFpewBnwSZgR4fmu/BpuzbjH6sAdmvO2dxUoIN/OsKeyTxLuUV12xgOPxGyajcX ASN91xIhGCcx7rXIzgLiXJJRUoDD7Vbq8BoKc4GGotmszAX1ev0UewyUvuf7J1wZf4V1HRbF +6/335kmqPtosqaL6w52+KWWVP3+J1cupnSEBVZNg9RUBP5uRYZSF2MFjYHUDtQRdqQCvzDW tBDJeCRODi5r37EbU+h+qSbArw2iKDKukwhAHYj+VLHmSBVe6jh/5YrBYnPYfQEFL2ULhrFG ukqLOzRTfFrk8Xsp0ucjD+fGDz6b/Ka8f8MhM4X4xpeHCN9w5u9g1psubK2pZEy7cT2DaZx5 VBzCzcrHZZzGI77muJKC8WBo5o4gX1IWlIFssXjg3h2wLcGQh9/kFNZUOIEfH82VJMz6FH88 dEohVdT4yVwL0Ny3sRzEhG3mYfNYGQxzAp9qIhlHnJ5JI3JWANX2S894aG367MxvserfbHta B2Ed1WwMpyTA3HW5mhy35a/VDhHXWgB1RXyRr8lMB4QzqNuB4DOXsBoaFkBGuuiLDFVlRxoo ofD/zlws48kg8H5bnZpFE0WePba94dRhapdr7bbaaEwVxd8ScyYLRnXfFTFmpZWzjUorZ9+q 9wskPiqm4y4/rgNWRxA/STQ4+iKgTtjTeer8RKXW8Vaq1ufarNcSwKcu6O0AQ7S56WQc32HI E9Op0cwdu0/m/EFNNpz4AhN2trfTq5vSRzMdp4ox5Xat2p+OhkNZ4IEKHaw1aZfYUd4Flrna qGR3eU3rihyw9u1hreT8MNrMNp7yTcwxTlcSN58Bztz14YROhl1CK/yMb4xnNXGDFS6l6YvT dJCvd7Hhj7q/Y1tMPJsnCaJs21xsnowF4w1vD16HqRFPJBS12RDYgxyCiZG07QGjFuYxjI5W XQz/7Zq9WQP7DC263p+IKJtxv6I5xOVyY41ph4LxkfLawY6SlZ3l0/lNmEnD1PRJ+EkzKiIj k6CLXyZ/71bumCILnMGsBTKV3qRkqPefpmgaQgIlX7ndIDRlAYiygzUAEkJrNpHVQXzbFf6Q LO3cSxM2Sl8WpXuJVsPIT4/oAS9E0UHf5kPcXqxwjXwfHf5cCSpU9Q0itF5C2pSXbqnHJJOC Pfdwy44mpcxnFvOsVEsy8VR73JLn9FD9y6uYLef2DZQIAwTo5YFK2H4UTa+pfqPpkxdmXBgB qejypPA+wer4abmwyYJH3TSHO3zBGp8+MsW/xWhTbw8Y8eABtuBfWRAG2Jezirz9t6kKeBkj chrXNRYHAIl0AVtvnuXL5WxhIsyBaSbGqD0em1f8AEXH44HE7lixWNvyF/gbnYXE4Dtf4rhj Lgwa0WFw0BJ6AZW0iJ/529KODEbTGZLGEXo9Hpv1lNbcNmcMhvlzO0OMkhk0azKrIHyYwWBW WiCD7Vvr5WlyjLd9MFi8l4T6creeDuE6qiDqJCvqnupGEH9QY6a5GW3vSyoGR6Klt7l7xf7K mJhQ9A5cRdHPgyzjB/fq9pVuX9vwC5jAtddHBsM4H8D4H8AEtFInYz5SnisgdhhlPlaZYcnd vjp2qh6gwYyPHc/s5npWVed8IJ/mKibuXMPivjRQ1oKWNm73nuFp9yW7lXOMZbLCtsi/Dgmv iCCDX+zMZ+cQTDlBxeQD0G77AWiBN3DxeEtbyltYxt/u326+Pz5/eX99oizGi2CEpaKL1wdA s5vO/a6i2igOw81mfVZegOsiRUhwfUQsQIONUk/wg+ltDM4zBJC2auglXJ/XlwTdD+I+mO8m +GifBB+tcvDRrD86bK6oDBfgFQFxAcYfBHofw7nx+oBtPxve0BIA643Rft4766vxpcwfbQXv gz3vfbCfvA8OTe+Ds9tLPlqR7IMjzrvSDRfg9lp/VddT6g6hY11vE4QF15uEwa6LMYCFhvhR Gux6vyLM/VDZQp8+RFZh0fVBx2DriuAEcz8wj1lNP9QLoeEJOxk20MGWTCurngz3iVnfA6AP wRUFZc1IumDQ3Nglm+iK7J68BJz14TWhrgzCyaPAW+/ACfWRtA7XBAtDlY19ReefYVcGap+P ec0eFl/ZYM0WRGqLtXgqFOn6eFqAoLN/ENkV6bqeIKa53hwX5NCtCwKhQgEdc5VA2uvyUUBe kVZiOaVxML2H9vXxvn/4N6HRTulkedXLnu2Lct7fklvk3gkNwWAukDC4IlMYZH10l310bcwi xFkfr1hce70Dyz4Ir6h5CLmiJCNkc60sUOlrZYns4FoqkR1ea93Ijq5DrmiYDHK1A9yrTRf5 NuW8LDScuwlFB3DjqCX2cnVyqOJ9TB1WLBmgg3msD/Ck88LC9alB3pfNKTS5ZSwr1adjXuTb Nj9Snji485dufk8EFpAII0tN4dt825kR9Y6fkWuf5O0n9ZiRWySN5gXmja69JS8yE8n1fSGN J1uhzoEJZWoZD6FrXXzlefy7b/ffvz98vWHF0kQN+y7E2NSTU4RI5842UoAoRjb7Lgv8FWsd RxndcBi7hVS2WdveofOF4TYsA1Leyjpi2HcrXs8cxv2ajX3DvVa01ljxUmH89IxPn/2tfJXl Kw6SHEGbYRhv1+N/puvr4ghZ3FBXkO16Rxkdljm3OK9UIq9Xeq6o93lyWumRNYv5DDDc/ebz YRsFXThoXVY2SWRyKOYAs28H5w8rpTa5IzMmO8y73vkmR2A+NUzPIHGu4bIsZxJHB5J0isvY Tx0Qp/X2qEiX6Ua7OpK7Cs/ilFspCmS1riB5x+FM6q6zxEzkVzUZ2RwU4cK2DXsyjui8yLCa MP6qfy9DnHIsWb8yO85JavRFZIAB5+nY0ToqR7Bz/BV+YezNuEzHXXLQmi5Pe9fxVIdw+clR atVYbsgw6sNf3++fvyqmWJ5v2vh+FBmLlVaNup6dQVClyvLDlzNLKz6jO8ZZz+5XuYP22URX YxdqEDEy4ETdRX44KNS+yRMnsvXiwbjaqONKcMdV2o6v1LtUb1OtRR1Lk2TbNLQjm1b2LgDH 2BVpvLF8R6kZvwiiEIvG3XiuRoxCP/B1Acu0O6NYhv4D5V6vTZv4vW/QkbkoKJzI6BfOGz9x /WizMl36pgt8xza2CONHwaAMUEbe2GpT9Z/KIQpU7LnwLNdSqOcycm3pti7R64tby+poAH3N Djx9trj2xlaHKZ9Etj6JEtc1HWzzUZ93tSH0Hpc7IF49MiInT//yEsocHEGvFqvu6fH1/cf9 k6qgKiJlv4clBh9sMWeY3B5VuaK/DkbmNn9ztsUxebYxtIG2f7d/+c/jdH2A8DmCj7g7/Jh2 jhfRu7kLSNEkiETsc6kUamIZrq5eAN0+F2tOlFusT/d0/z9i5DRIZ7q0cMjE9xsXesdjCKhk rLblmxiRUheRxd4b2SrvldJgmxp3cnKBMSfn2seRsfyuZUzVpfVFGUPLNhlDiSYR4YsBakVG GBlLF0ZUTAepzpnl0clGmR0S42gaL8IWHONjYARvw5vgnI9P2Bd3JOBwLulL9zgAxVeeJ4IQ wVRh4IvueddjUGiNl5VZC0oXhvGbAnqMzHQ6lp34IN8Mlx1yFSY+HRBvC3ygKm+kKHszYn6k fl9jnNOsGc95Z3gNjPhiF+ctfx9rpRDiB+yRta6RwoHMODlBqrAfLyQi8eoH+2elbFqZtJSy 8gg7VJO3+IxC4wSRDbv6cBkey2d4VXYik8kCP8L3SVcgt+4qm7/fsYo4VlG+ilg80ldByZV8 GAAG9Hp5b/P29lzX6SoorWdxbwBMl6NW0wCNMnAoyATAixGXLpsCkL4/PKFf4+s3KUAmfwM7 Ab0hr3rXswYCc3lqehV3CSJKZcWfi3t9uf/65eUbmclU+MlGtNoCaG6ququQztCt8xNuptIY 4mOvFBrDYeNVkJXcrqfHNdP7b28/nv9Y6wYTZIr3n6d5DLn98Xq/WmJ2+xYKzcpMS4blgu5q SzOYa8GmjMV4Jyu/WipWrE+gMUJf0ENjSsWIEYVGS07AedGdAlBdRPdM0WIYLoyqPsd39ZFe cRcUj8XFQruMWYUrFhULeYHXTVYx12NI+J+WxmYmbKKQh5Z5cOMLo/PH0wQ/379/+fPryx83 zevD++O3h5cf7zf7F2id5xdFe57TuqSBa4imgy8Jml6ExXe7xQa9TL0UdvhDedyR8b4kMeY7 H8D41zGB+wEMnZe0gZxrc3mYJqt2jr0tE7KmfMO5nvUU+3AV8znPW1QFV0HzznwdtVyuHa7k GXflxgmsK6B+Y7eAsz6A6+JycyVPbvv01vphvrlKNfeuP6e9ZV8pyxRqYS2T9Cx29fIlv4G6 njq7mLeKaKrBs2CrdWVAspgt6yBQkGC+r2Payu8D+0puoCgNV9KZw+ettNpkdCG7putLDIwy 4L3T9Yy4TfgaJnTWy4LvaYh9JZaFG7+cK3mAggoCITUEySiH8Fg0Kn9u86w/kgOorAeMX2lK tevxOOVK1dmiuwphPr+mPPi12/2w3a4nwnFXILBm99ntlZE8RwBah00HTVcGM/cuNlZu5ref YxNkOhldzWZxHlkvTJ/a9lWJhvrGKmI+wbjS1l3i2u61FQAfgTQ2DrcpG9n4NC+b4GY+XpBY 47ND4DVAaLnRypzaN2liHrgN1k6r3mUdHmPHRq441Y9lsSYlum47NnXX5aCOSdKqo86goQKx CBfIknqDMP5uh+GsmyGm98bLvKHPKkXQvoyTMSnpDboEpA2SHIKuEVIQv99/PH9hrwMb3+3c pUpkSaTESR9tPF/ySkA6uyQMRYhTyqDKvuzc0JYM4TNV9v+ZV0p27XI6d5GLEPdOFFqaUs54 oGuMx45+goADMDoIxmJI6lL/GpmHIjFWAhrT31hy+FVGR7XWLs8nevhi2kPjWIMhvCQCVJec C41FdPxG0JWInqzH0IFHPpFSubJ7z0I2uNkufMNFhwuftrXzTs4Tg+sV9jIq4C51nrhwfUdu l2l7oMTJETimMG0LxFxZvh1YZ9OVmdi24aYHsvG0+XbrbtwVCHP25TdyjKA9rL14S7Ub94YI 4myYJDbTu0y3xUXMWouVjWPyTGTsAYrbKjNfQTg+KG5rEP66nXZTSUeoV7knlu8P5mtOhx7f qDSOQmRD/U0nm5hD/qkLyDNvZE4nttIQjaKmjMQgwheiTyADa1Cn/mB7fhiqA3xWYI1SZDnc 1ahRQFE3rpZxGEaeTo02Vqg2PCM7JnHDuMyPUSNGWr36wA2MteL+kHLp5933JfnsMwvv2sgZ JhNJyq7qh8w00FCFl/Nqkp0Ps15ok5kCS5QUeW+hG526WHql0QGKLabU9T6xgL0XubZcy7b3 LfGWOaPxA3217u1tZFGnXIzHt4xyOl2WqI87IzX3wmCYGXIFCEcBkV36lq0khiTF1ZPRb+8i mAeOWocucVBhNc74eDv4lmUOVMbSgH0pdbIz6TMYxbAVo5Uz+uwNJdB6DKjhuiCA+i7B8SDV bPHckPJG1w3SRWdKsCiP6idNXJSG25XoHmFbPiWfmOeEJfvJcJrhIiorAAMYvLcugBWVYPLz oN225zpCG5DrvsDn7i16whFB5W4jejE2tkmuCG4l1GeaHkFBCCUMeCD6yTj+s51E16xnTnxM cynMIDACy7syls+F7YSuKYYhG3Gl66sCYnLXUQqiONWwj2efck1lbvPPuPFbUx9mDB2PhpW+ jDxLUfMnhx0lv8mqau6XCUCohsjBZ7RWSgqQjeEmMRcYZy8yPCfFhGd9KLnL14pwn0GgphqF 8JKOo4zziTPZ0DWxy4I9FQ07B1gTe4BiGLOC2fUoWmmfiimRnWnqTl6XcslhI+4EFk2cNjhS BreHOI07UE/pEG18L4ph0FHMG5dyZg5jilgkjy58t6MYS9sauQYhd1FXHleGGGPPA0yM327a U4tGqj2et5NuVIm2yiKlqvt8p9wbY8Y3xkV3DvqVdY6Z+PrHEwNf1OzJsFYzbJu2JxZrvsuK LFmOlNh9lLme+BqtaDngxYtLtkddSiBx4youapBtJxMATYc9PqNlRMCOA30SaWaXtibW7JJv 4mMwKqnhxCs4cpWFpvjy8ko8InzK06xmr91/U1qnrvq2LqQXetLT9mLUkDKVEp+89r4+vHjF 4/OPv25evuOge1NzPXmF4C95ockPRAh07OwMOlsMUsnZcXpaTEiC8RJZu3zIQBnPq7rFhyz2 GXW7hiVfZqUDP3JrMM7uXNVpphD5Q72S66BeZakDlti2WoOobY5NrXa7wG2zT0ccBLwleMyq p4f7twesF+v9P+/fWSCoBxY+6qtehPbhf/94eHu/ifmalw1N1oLErWBIi6fWxqIzUPr4x+P7 /dNNf9KrhIMFH8wCKdnADO7+aQcia4qAxjumk8cYf6gClHr0+4GlHSN/iMfeiDkWmdDjU2mJ 8ojCQLUg8gm6FPBvmY7bB3E94JHMJ9pFYC5Y0ueQs/ss9kPRI3f6Ko7D0AoOenp9toPdMG3k 4QiuT9FGe6+YQHk3G1/JQY/zY3vcOYpUv9CJGcroMEvqpqM4ackHqvi2vZBeGRegqZGTvm+k 0yisxCIIV+rgFZd5y1G6CMD3XfYtiLkTbb3nqKQ23IzhbPQZawwXzRZENP7WGG66cMxyLPVR 3Kmh9QsFVqbULY8ZNMs19hhYEcu31GYQO3rLHNrExEHTW6Rj5zfj/sPIK1UVoaUh9upUxsEZ s7KMm3atG+b0Jjulyf44gWEbt03zbjVBwBxOa2MDEWlWGB4W55j5+G+XNrTWKsN+W+33JbFk reAz6tStZzn7GbaGsJ4cBnU8NfQGDwXyByYr6jwqTJ+tzGERuJRjLU53pv4Yvz7l5JN4MxP+ 18c+I6O6uv4hW85AOej+GXgqG2aYJtVykCiZIOywlZTCCxz4qD9J1z+kRUtYx+6fvzw+Pd2/ /k2ciXHdtcegfLNmEP/4+vgCauGXF7xT8Y+b768vXx7e3jDuJYaT/Pb4l5TE1Nknvs1X6tSn cei5mtYG5E0kPj03kbM48Gw/0VuccQxREqa53jWuZ7h+N8nrznUNkRBngO96lOn3wi5cJ9ZK XZxcx4rzxHG3Ku+YxrbrOXqFYGMehua8kO1uiJHXOGFXNtRGdZIsdXU3bvvdCCBxcHysU3mA tLRbgKIv3Swt40C5i3cJACN+edHqV1IDPTy0I8qaJfJdtVmR7EUDRQ7EawcSGScssQ8II08b nxN5+kIp8xZDJqwMI+D7VCyEhRsEan63nQXamUotiyiAkgcaA/VA29amDycPxOxBq5gphMw8 fxvf9szjivHlK3YLI7QMYcgnxNmJLM+c8nmzsVwiYaTTBtsLgDSEzlNlcB1HaySQyRuHHRwJ AxSnwL00Q1T5xto2JNo2GRw/UmOkiRs8ckY8PK9k44R6NoxhONEWpkp4ZSqFvp40MtzVwcEQ hqh7F4RvU/bhmb9xo40mHuPbKLK1adwfusixLG2rfGk1oSUfv4Eo+58HdDK/wYfztCY9Nmng Wa4d6zXnLPWCqJSlnvxljfyVQ768AAZkKdrJyBKgyAx959BpAtmYAveOT9ub9x/PsIlWkkW9 CMaxM3fn7Cqv4LkK8Pj25QFW/+eHlx9vN38+PH3X01uaPXQtTdaWvhNutGmkGDhntZa9/5Oq 4mBWUMxF4SvD/beH13v45hnWJeGpW3nINH1eoc2rUIuUJB1FPuS+rwlc9Ie0Iopqa8sHo24o qk+mEJIpEE1Y4gVbvRWR7prlJWMT0xjpvlmjALZnE4pIfbKc2BD4Y0Y4gWeWK8j2iWogfWVl Z2yiGkAPV3PzA11xZFSfpGqLZ30KJHeCCzYkljdGN7cqsjdExqHj2wQ1dIgVBOjr7RsaSqbG 5lTYUeQH1Gew/K0t1wBYL84moPQAoIcro7Y+2W7kR/p3py4IHPN3Zb8pLcvWv2MMl3K0u/Bt W+sEIDewGJDp9ZZlXsGQb9uapgjkk0Vmc7L0fQ+SiUJ1reVaTeJqo7Kq68qyZ5ZaYr+sC6Od jis6oT1ifCol2TaNk9IhkuQMcyO0v/lepRffvw1ibVvEqIReB3QvS/YrWxj/1t/GOzU9EO8q Keuj7FaTwZ2fhG7piisjvbKwRacAmr4vnrUWP9I1yPg2dCk9Kj1vQsPzLRdAQB2RLuzICseT /HiCVD5W4t3T/dufxuUxbezA1xZxPCsPtJoANfACMTc57SV6xJrasO9smMGSHqJ+IdgikBfz 9x6FlJIhdaLI4k+dtIRVQ/pMOd06VuzMiasQP97eX749/p8HNOkzXUgzdjA8PjHaiH7PIq+H TXvkSC5nMjfC1dz0aeSEw1q6oW3kbqIoNDDZgYDpS8Y0fFl2uSX5Jom83lFdfxWuIWiqBjP4 j8owJ6C2xQrIdg2F/dTblm3okyFxLCeiG2BIfMsydNeQeEZeORTwoS89WKPzQ/NR9QRLPK+L LNeQCWrxgW/qAj5iDI80iMBdAp1scG5QYQZXYBV2vUun0l1PL8NW/kCuoFCTjk1ig0VR2wWQ nH7Kzct0jDeWZZgoXe7YfkgPobzf2O5A81pYBQiXg2UcuJbdUtZnafiWdmpDu3qOKSGG2ELV lDVkXsMI0SbKvLeHm/S0vdm9vjy/wyfLfXfmyPH2fv/89f71681Pb/fvsAd7fH/4+eZ3ATqV Bw3LXb+1oo2w4ZmIgS16/3LiydpYf4kVWsikZWbiBrYNX33TvgI6pXuwk2GYbcMgW8BhLKSd a7MtK1XVL+wlpP91A4sG7K7fXx/vn4yVTtvhVk59ltaJk6ZKtXN1zrLSVFHkhfRkuPD18L3A +6X7SL8kg+PZtiWXkhEdV2mY3rUdmfS5gN5zA4q4kYmdf7A9WTmcO9UhHTzn4WHJodWWjzab 9ZFAjSlL64vIily9gywrCnSoE9hq8U9ZZw8GExb7bBICqa2IKg3Du0EvC+Q6qLmCNMJZY0iP pxTI9efEkOpltaVgGMqrN8uyg6XQlCNMF0udxBjUMrYDreisdUObHK/9zU8fmVRdAwrNoFXF CdX+5URHqR8ORFcZxzBPU5lSwB4/sqmh4Wn9UQ19YFqKponjm2cwThfXp7w2WMnyLTZuuVUK PJGVcz0gh0hWSzjR6VPaCbBZGaK84pFchni3sdQRmyWkOHeDUC0SU84di/a/XACeTXrdIb/t CydyNYnCydQOfhGySj0+pzYstejuU6fqrGEbiHkbgGM0mRYA4+hEkRDpgo43oSFaqwAwyxIu 9UJt5sR9B4WqXl7f/7yJYUP6+OX++dfbl9eH++eb/jKdfk3YupX2J2PRYRw7lqUN77r1bce4 hCLXdpVJtk1gZ6jK4GKf9q4r+jIJVJ+kBrFKhu5TxxdOaEtZbuJj5DtKoThtnM+3dc7Jo+Kd LHnItzIn9SGQ7/PxQEFd+nFhtnFsbQ5HxKLHBKpj6Q9Xstzkpf6//p+K0Cd4F1CRiEyv8Jjq KvnYCQnevDw//T3pjL82RSGnym3mxGoI9YMVYH01ZJjNMvG6LJmd/2Yrws3vL69cydE0Lncz 3P2mSPNqe3DUIYa0jYZrHG2VZ1SzAM87WCwsypq7cB1lJeFEVxmfkbNxtbz3XbQvTIkzrqrA xv0WdFhXG0EgYYLA/8tUzsHxLf+krOK4L3IsSxNnKPtd05p1qNtj5ypTN+6SuncyNaFDVmRV pg3q5OXbt5dnFgfr9ff7Lw83P2WVbzmO/bPoBaoZ2GahbW1U9bNxRA9N0+aGR616eXl6w2dM Yag9PL18v3l++I9RwT+W5d24y3Tbku4ewxLfv95///Pxyxv1gDD69uXN8WS8n5KKES7hD3Yu NqbbnKKKj+4iNW1Azg3j9ijZHgQOPqqrPEIsw9i7AV1W7NB9iC7eeFt22KcNeyKX+BzyKrt+ 7OumLur93dhm5DsD+MGOuVkvkffk2nBmfcpa7ssJa6ecHQcUWcyeqO1YHFBDRkUdpyNsmdNx l7flORavHE3tIzl5IG2flSMLYsDr+rfaBiYeftcd0A+S4nbJIVuenMabFdPZ9A0IO8VaKlUW nYKTA6h4lClsBnR5IcXjnenV0DAz4UZ0fdGYvnRyvlY2rpW0pWBMlgp7SIuEdtpkgzcuYPDm XUO/E8Taty6zNJaOvYXc5ORuyy2VmoQ57Q2vGDAm9KaRqb84JTC5B+EZ6lsqE5RxilPayWQe BnjcN0eZ3sRVtkQhTB/fvj/d/33T3D8/PInSaAaO8bYf7yxQtAYrCGMiKQxwNaLrH8yrIiMB 3bEbP1sWTNTSb/yxgh2MvwnUKc3B2zobDzneV3bCjbljL+D+ZFv2+ViOVWEarxyc4lPfJVVA vfE4PSvyNB5vU9fvbfEW3wWxy/Ihr8ZbKAIIXGcbSxtEEXaHkUN3d6CrOF6aO0HsWikFzYsc fZ/zYuM6ZFoLIN+4nk03ooCJIptyARWwVVUXILCz36CXK7KHZ0hjhZvPCQn5Lc3HoofalZnl q0v8gprul/Wd5ZMq2wWYV/tpokH7W5swtTyy57I4xZoW/S0keXBtLzhfwUHpDilsqjZ0EWdP 6yLdWOQRs5AooLaw2/5kOXRaCNh7fkiqNguqwgtnRQQ74kNhGzq0qk/MJZ5NHdpsSWGDIHTI 7hIwsO0OKEgZV30+jGUR7yw/PGeis8AFVRd5mQ0jyGD8tTrCbKjpKtRt3mV9lhzGuse7gRsq Vr4A71L8gYnVO34Ujr7bk3MU/o27usqT8XQabGtnuV4lGQ0WpPi6Tl8fk0OXtFlW0dC7NAeR 0pZBaG/IiguQyRFMh9TVth7bLcyK1DXMiHm4pdvQc9f7dblTEKR2kF5Jrwsy92B4rJREB+5v 1kCGtjfAy+slQJDhArIZj6om0ZgCLIpia4Q/Pd/JdhbZOyI6jq+VtN5BOlcaP8tv69Fzz6ed vSdzBH23GYtPMGBbuxsMxeKgzvLc3i4yAyjvYeTA1Ov6MPwIhFyZJEi0OZEYdMSOk8FzvPi2 MTTShPEDP7416bwc2qfoaA6j/dwdXHJG9A361VtO1IMgIGvGEM2em9yJ4vTtsbibNIhwPH8a 9uti5JR3oO3XA87TjSOdGC2Yc55meFekG88YRJ8sF8i1JoOxMjSN5fuJE0reBIoaJX6+bfN0 r2wBJuVl5kia2GWTun19/PrHg6KUJWnV6VMES19X2ZgnVeDYtsqEgYAXr1Gnd121XZO27kZY guJqCAP68AR3LdNiDCRYr/q6lfMoIAeUhkUfbWxna2JuArVwMu84JGrxQJGBnyCwSZcflgRo b6N6LQV1/2wf827t+rQZMN7SPhu3kW/BnninqAnVubjsdJUi4K6l6SvXI0Pl8A5t4zQbmy4K dKVtYXnKnIAtFPzk8I3GyDeWM+hEx/XUwnEnkWkwGYrXH/IKg5wngQuNZYMGKifd190h38aT D36gaTMKn/KEI2DhaibRGjf0FS6s2LvGsy2N3FWBD10WuUaOts/AxJrUdjqLDNmGEH5RHoQn TIrA9Xw1CZEfRuRjbBIs1YSrlEJABnOaN82T37q+m54YujmBCYnykDaR7ym6ncQafwsdWzVP LFtM2d7CyeqFMk0C6uJLmc7VPgNlzbxBdqn4RWx33FfxKVfWsYlIvYfARMDQ7ehnxlgftEmz Pxqy4/MqbaXTrz6v7pjRYYhcP6R3pzMGN18O2bEiQtnCiSwvovazM6LMYRl1P/WX9pg5bdbE 3GKmMEAT8MVwZAI9dH3NxNYUtsFdh82iU+aYTilRKMMW3tzwPCTsfkcHbGHVS1LDtUw2g9PO ZCcpUOrfUestbEAwFAC7f//pmLe33Wwb273ef3u4+deP339/eJ2iqwvL7m47JmUKmxthpgCN xQi5E0nC75Plj9kBpa8S+NnlRdHysB4yI6mbO/gq1hjQmPtsC5t6idPddXRayCDTQoaY1tKq WKq6zfJ9NWZVmsfUkzRzjnXTSYmm2Q52VdCfYhgxoOOrRkW+P6gZlbBUT/ZKqhMBgYYkLCEM 0CV+qtRHf96/fv3P/esD9Y4CNhnxPKnIz0sjC2SCiQW/YawKE7szvIkIrOMp6+jZAMz9lh7o wGpOLXX0DBx8rQDN+p3Stp2dssiSxuphsFUT81yCbkRf38LCDLEd0F5++K1tEAZYqAP0+Rb6 dFSDvIqovjTE7sMUXONnLIYd3Uj5thz3Q+/58vkntnldpLu8O5gSTWN6Ud9tmVn1KK80OKYz 3G3VpbErt20dp90hM7wThRVhC45h3nXoVRAqmWLke4NjY9mMegCA2X+aknb8NZj7L/9+evzj z/eb/7pBq/oUdoc4XEJ7T1LEXYd3x/OEKvYy/SXgRUJc+Ld96oju4BfOEj5tyfjCa860mf2C 4GFpV4vGI7fDOi827YXNYz6uprBETNM4l/crKVYUBWZWaFEJLjFLic+WYJlUkjx2M92M6F/v WtQmWsFsqCIVoEf6dIHiKq3bmGJR4SWF0rKQ1avlYRErqeFygvYOi4ZOeJsGthWuJgzSf0iq ikx7GiPzU0XrU2X+nl0/EBe8SyMyLVsoKGwHanK+aoe8cwpdfaykgdtVlPJ87EBUHJJ8xBUV hDBf4MXvEEEENRPECRmVLSvxublbcVzNNH4+qx3E83d2u/fHL/+m4jxM3x6rLt5l+KresRSv P3RNW4/bomZZLsSFouVweHl7v0kuB/zagzlVdsZ+FToF/+LySuqahTru4N8D0RgCpDwWPX+A QUkX9ugwkqoMMIczHpDDXiid9Rt8nkhrEvaZMO3lEsWVazn+htYsOAJUXsoLiTPPDnrcfZPL mJSBKwZAvFB9lcpj/Cq01rLQucnT2i8rbJidrsm1kWH6Y9vmHSxsVU5JJIZha4KlNQYjU8L+ wlXryq4WOQRx4+iNjdGQDf50jM8euTEoXrxl6m1cwIpzNOh7IqiNP5kxxiDHvPwY+Za+4bXw Df6jE9+31qoBfH/AAMRlaXi/cILhAmfqDvbmtK838kS/UkVEBWQMW8aeg5HCVu+oT2NdKVD5 ie14nRVRO3ee/blUJ3bqRJY2kHrX37ha/pNWYEq86hwl8Srrh22+V6h9EmM0Ya0F+yLxNzap vPJhTLxDPTMwbPjaBPL/0mpT9w55cMKT1IOFM3reufaucO3NoDTZxHCYD5oiFZmL3r+eHp// /ZP98w2sWDftfnszPer2A59Wvum+P3xBT8JDvojSm5/gD2b/3Jc/K3J1i++ollpD8GDT5gFS FkObUW+bMC4+/KnUCi8Mbu/6TO8rFnH66lTKG8PDBbxj9qW2zPIbkhgwpH95/fKnsrYsDdu/ Pv7xh77e9LBM7ZU4VCJj1CLdUqAa1rlD3RsTKXtKV5Eghyxu+20W93rLTYhFPbuWVNIc1Qk0 ceKkz095f6d02syWg6NLrPkNWuZMxhr18fs7ukW//d/KrmS5cZxJv4qjTv9E9KJd8qEPEEhJ LHEzScmyLwy3S1WlaG/hZaZrnn4yAZDEkqA8h662kB+xI5EAcrl4lz3bTc30+P799PCOWk3P T99PPy7+gwPwfvf64/huz8u2mwuWlnhl5W2+9PZ6ru0giUfcOw7AXiw1PTqPqgqL1FsT4Vjr XCaV3suM8xAD+6Cqyk2rmvtyvPvn4wU76e35AcTpl+Px/qcRapNGNLlisDM0Jv+lJzjyHCZu eJXBUicXFtKBVoHU7KU7Aq5Zg3q7S6NKuEbTOw2p6d5SHpQerSooq7k8Ny608JsorVYyBqW3 QgICEjIlqrd0dAP7i0qtd1EotCNNMvohVm1otQixpq7bUQV2z6gGhSKw5XJ6G5Zjt2S2DLPb S7v/JOUAefkHByAqbG0vJijxWuUsZE7LUxpkNqdEzwawuUkW09nYbToGzbs0laU0Esb+6C1Y RfX4BIba1zWEFaekoRTllI/nI5cQlfFwpHv3Ngkj7yejGdXWA1Aocauh53y1mI6I/hOEAdWz gjL2UmZjmx+0pAXp8rbpq8mwWtDjJSi++ITNnJQe6N1KLa/Goy2x9GR4AoLQhF5wx0yFHyGq iKTZkLJ0bBAlnJIuB8zNdZWMh1Q9CliG+quslj7VDd50/GjqpocJHGXnBH4/HlD9heljYpYV +8ViQDa+nFLKKy01AD6waLehPOrncjjYl9R6xvSJ2wzBZ4jqivQpVV2kTPpmogDMqVmMFE+Q EIPvDKnnxbYjLw3Vo278JvS4IqeYEAxBcriRS4C1NjKMgtsveD6/tKaIeO1OA+X/vx0jlHDP 7khBCed2bwV8c+6Sj6i+LQ5oDexs3vnD3TucTx7P1WQ4WpAMECi0ZzodMCV5Fm4+i2m9YkkU 00rpGnI+6dumAtR+mhCzVAaDc9LLajucV2xBs8NFRb5f64AxwQkwfXpJpJfJbDQhxnF5NVlQ a6vIp3wwpLoMx7d/fcgrhF6IjIXUx1LykBXktLMu6hvK7U16leTN/H5++h0OLdaEcuUgGTO6 f9xlZON+TBMzthe1KuN6VSU1i5knQn07Wuh5+zyi3guxtweGb1z94+B5Gmx3FhFCuheyLybD M5Au7PZZGEbd7pkW6zANC/M81tajAmGmvwARIesc4tCPSGijrLYNIl75eNE3t1VMcHd2ryr4 azAkJSSM/NUr5LGc+uzr7WRu+y61IHHuv3vVMHix1IvpiRDXHYbWBX3h3nbvoX9CAr3ee6Ig ND2V7v3nPJGHCGvdD6lG82Eft2/D+xGfzmceC9VWYl9bdpY2852Pad4r4iD1Zi1eFXoRKg50 /ywWKkbORo1Xg6X0sNa7VTcKApoeEYZ/xRfskkprw3a4lL0RBhgIroYRBpgI07WhYYRpStdA PBWlYWyWXGer7jfDgEIMNsl1YMZGZocIwd6wyHW5xKA+kcfSCorB9bfwKHoBuWTD4aGHbDOs hnbdVk2fgpJbYzKtJgEbUOgjRsm6TgJuf9xQhQp0BMSZoUOr0rO8Zr6Mt2NvhRK+8lcIJLJl yHYVPvV6RqCFHPyQJK9zbxEJGlT6iLBOPTs6Ro/1fZYu85UaG5IuQ5mdpSY7eoVKQOL9HuO3 e4nykc0/owV7Hg1qli+9mUjMcOAf8CpK/J+3seoTby1aiH9UBQP1lnGI4ig9KImwDvzDX23r TdlH5Vc+qlB9gS4g1oogbXCt1Mk60XQLO4KhaXvtDEgzXisxdTVZV0XvkDk0qA3+DuslK82g 8DKd5vPCHNbXu00xqNjgB936ql1FYlFb7DbRY9xWkQwLVGQlcFAjUJzkKLHV7y335w+n49O7 Ic2LqFt15fC9rnR1B+vsF4J1a3vLcrdyo1aJ3FeR7kqyvBaphhKI+tzDyYEEYsc+VHqvfTDf 1bgiNzb/pdEgpGxClhsX9c0XePEtHnQ9xtPa5+Li3rbAbpTUzQ7SBmB36DPr3nleo/cr8tED t+3aiYci7bHt3/hIutObrJL3QU5NBUVdopsC3YlBk1lihjdpExsN5tqRYRRI7NUbhmq80EUr /RETq6Lh4Zf1yrnfZGUFW2gVL/WdVSZj+5x1kJzuX5/fnr+/X2x+vRxff99f/BCB23RNw9Yh ez+0qcS6CG+kNwqVwNGuX/NaIX/bglqbKt/yxGyLbjFe/F+jwWTRA0vYQUdqDiMUOIlKXvsD BymUFs7MqVXO4/lwSCaPDAUbnUBdumh03TCvS17ovvj05BmdvCAyScayVmY6S/IYuiHK4OyM jXU+lAA4wY1n/fTZmKTD9F3ovtr05JGDDhgfjIiuC1g5nCXUFVwHGCxUBciPez9dmI882ncL Un+iA8wmVCuq0WLgTgxM1g2F9GR3ZETylE6ek5mMDi46AWmOVQ58FU+Hbr0ZhiaMsuGoXhDd gdQoKrJ6SIdUaVYMTrZoNNjS27pC8dkBL7Uo/tysz5zPdEu4phbBlWHBqJJToFQ1yI1TdwEp Wka0SZB8mu0WZjijT2EdLGbLnOMk7MPBSmS9GQEgYOTdQAcwNpIueUckC33Hq7GTXk5HFPdI eNRxPPsbvpSLqeYuTa5AXtK9HLCreo7B52kRwQQiO5pYUE9nExVJkbdnFOVqx4SHAygjp+iL 0dRdh5DorkJMhLM1wam28v9xtPTXXme6fQyX7mOqwaIzKEJFzAhILrKdst4xSVLwI1Pr8MBM h+cGVWWqyy4gEa5lIdrpUiRJp8WO3MGevr0+n77p8kWTZOVZLzNWaKZb67Je5Wu2zDKN18E5 D6TNMtfv+aU2V83jbX2I4QwHf1zfFqYRWLWybaIgpWbrZDiaTbbAO4mRVaBlMJuNJ3r4FkVA k8TJYJnShHlApk/HnvS5U2Fhkjicjcn0sW7mYKRP6fTJgM5nMiTxk8WQ6DDCSNKG5DxYTCeU wbICFGyxmE+JzMtZgEFn+jJHRxxDjxPOBhLmwAYp3YYGsBkOBzOnM9DgZ7S4dDpDGgJNSfx4 YLwt6pRxfyURMvUYUQmAMhB1SrVdS6h0NCyNeUD0ahVj2CxanUZBdnw489iddoi5z+ZL0PMA spgPJk6Fr4UaW1YZy0+dHGpc20VGv2s1mMawkyi8gUiTx0cnOTNCAXfJWY5ajD0ZFuzazW4f LQsm3TC4DRG+AAL0VNfbGFbwDWm5xRNpuNLGRe8II2AO9Z5vIlpBXcUPlDgSkUcT0tXjIYrx Rhi7eKXbkUZhHGBlDc21TYLWD9iIsjYOfUjIi2wFR11D767X4A8dZCRhG8WVFiCSMI4ZOhJp YCQqi0FkOGRDMhzThu1D3A+0dqgUqHMIu0hIbSOWCNBsLu4TtbxRenhubWuEyjS+1BbH78fX 49P98eLb8e3048m4fIo46X4RyyjzxVCaTjaeLj+Xu1bhWFxQbsnOipMtHJw9z0FaUxsFNVre 0VCwG0w93bWJZtMpfSGtoUqe0G+nBiY/j4mmsJX11xcx06ElzGrEIbVrmZCJeXrRKHP7uNnQ lslw4XnN0VA84OGcdP9ogS5HU1L04cLPa81zTzWEJkEcHsrzfYnQkp2FrcMkSs+i3GdBovtG SV4OfSODLyPw/3VIqzcg5CorPOwRqXE5HIwWIjogHFDPVdh5aKVAccY3KVszSilfg6HhCt2o 7JAyz2Gogey5b2klST5yFcDJyRfMh7RhtT7e0QH2LnEA/WX2HKrqZ6nnfIfZs2jL4rqihQeB gI1pPhzWwZ5+YW4wvs1L0euZT6VEB9RrOAz2orZZ6jnJKwC/Wae7ngYDZFN4+Keip54w8B29 //uSfkBEsuZQ79zIbyLgdTO+H3v0W2woHbvYQvlMH03YzKMeZaHmn0HNLxd871MCMnebkU/F LCxDOGRFJd1nZbVbnstCw3ymdcusrDzKWKiLAhDvCEfJYZHQkk5L9vNBQfbPPkE2+KQ0MXj6 cXw63V+Uz/yNUn1THoRqvt716QbZsNGUNgWwcZ7+tGGe6WLDPFutDjvY0Vw8qIXHCqxBVXzn jmXjYJnqU3KybEO0e/FsOehVS1jH2QXRoqdwXV4d/8Fi9RHU945qZB3lfChPCC8DNZvPPHzb RM3PshdEXdLGFwbKqyhloz5R4mLo23VM1OwT9VoM57StsoWy40rTqMtPtHExtW/tfWcGY1po M0e96MlzxePD8w+YsC9KsfpNv7L7DFzjcWXFMMQgHw/HdQJS17m25BF8ASfcs+IMakN4uZsY db8kojQUzh4kpItSehtAZZjhQIP3wEafgk3G52DyfLGK9n7JRuo/lBnHC1O6LNTxoQvSi0FN Vu100STBXxnflhQlL1BiQZWzPuqil3ppeOVQJfLduZGq8OXIO7vibasU5D8YrBNk9SRdKQTt z9dD6gyRqM01HLdS7DyixxMWxcvMCNWFESQSSKPvcdQ1SJ1s6DpJPeJ6PAdJuLiuEn9WBdQI HXU6iCYnpdyI1dPOL1L68WcrJSg/XbW4tuNPdE3MYlasoiLEydzASaTUpco5Gmv7VS3zgPtr I9Xi4HOPFiDqciXBVU8GOO1RA9QLwFXn/Vw0wS6+mQgwvXbw7157fZdpymtMo4G0Pj5hyKgL QbzI734chUH0RUmEJ1F51vm6Yss4xPmyn1sMsfGAcyZbO1eh4+ExlUU1Lgnrn4t+CHT0dBD1 AcaXwJX59TlIb0VwwHu+x7F0yNKQ+Pj4/H58eX2+Jw1HwiSrQttMuO1p4mOZ6cvj2w9CXTqH +WaoeWOCiP1CTCNJTEv3AzH51uiPARO8n7YqVF19jXq1b3joGOkaFm5jtlw+fzx9uz69HjXd a0mAfvhP+evt/fh4kT1d8J+nl/9Cm/L703eYb4HpM6GRMkBuobpWWrRwlu49+7oCoHAQsnJX 0FuoRK0PyHSidEVLIRKUeEDN0yZRX9kQeQvmaYfyzok32bwq6A1Nw5RpltH7jQLlI3Y2o95m uLXVvq8uh4I9ezTYW3q5Kpylsnx9vvt2//zo64nmvSPPrj37NuYsnCN57oMEvccQXWwLyZJs N1k7Ub30kP+5ej0e3+7vgAtePb9GV74mXO0izpWyKLGugpwxFA3TMotDfWGdK0L6u/gjOfgK FmOCJ3yybc6X8uh/yCf//uvLEakgS1wla3osFD3NQ7JIInORe/gk9pL49H6UVVp+nB7QZ0fL Bly3XFEVaqpQ4qdoMCSgi9BYxatSJX++hC4IvTofkXxGiQLebSMI98wjhohdJV0VjK/oQwUC 8iTi9XXhscJBRMlzn+8MJCeJQ9WjmdltE427+rh7gMnuXYtyiwjTqC5pvikB5ZK+VxPUOPZI V4IKewz9PiioZRLYe5MJuOZpWfoZnRIRC7JbyMaba6nvwNgKLeuC1t/WpJoABKCIvrMTbLLv wAl0j5Pb3WE6GBB8WIzg4fRwenKXtWo7RW29vXxqe9YkdgwMt18V4RXB68JDxTtfPeG/7/fP T0oe0Hb6Ni8Jd1yRmdSEHYaT6dyww+9I4/GUvtHpIPP5gjTz7xDovaPjNSo9r9IpaiK6xcrJ CktY6B/7cy6qxeVcD6uo0stkOjU1ZBUBbSn6OwMQMEHg37EZsTYBmbOgVREiMj/Dwxr8kAYA ZlKjx92NPST63Ru31Lri9FaMCNyOI1c4thDeZxsF8Os+ID0sYs/6E+QeYQHpva6tEeDaO2tE ZcBtd9smWu49R2CgRgnNDiTtQN9xKeKIvqtU1LryMFRBl2Y06x7EVTkbDfxD0fM6gORtGCZL j8UH0oUnRfp+VJI5PmbCXujvuj6jY0mHLaNXoQRRfmN6QcUd3/H1bHweRBjsyw840NsK0sRx OUh8Lt8QItwxmooXIvngHxk9FFee0fu5wHFGy3qCqIy8qpw+IwuM2vi8gL79TtD9d52CHI8W PI/ps4cAoBeIHmrR86lnr5U0nxl1S4XJ5Qfs0ok/c7+Nu6BGoc9AW5E3hc83twBc+zk00Oo4 9HfJPsLXp55+cV0oyINFcSXCiWoGRs0GVFzh/NAtqetVpHmsREPugiFOn+BfUTWuZlG/+SGw MI5f5h6G3+KgEr2A4pYN/ahmEorySERVThZoflPQhwb9CdGHaaqyWZT+cuDjzviVRYHH270I TVxclVXoOVYLQFr5TIhloFRRGkg7Szja0tmgjdwaL0pyvqlzz2BhAGGn0c2Z0Z437bTJGd/a 0Y/LsIhg+kR5xitG6XDLt3/tkKhfhAkaqzaex0lFP5RDn987ARCXERNa/FAIvwCiAH2O83QE /uKMXs1KzcGn+ifJMMweB3eSLCSA9XUPZDsa9qlZxBjD0jefBUBu4j2IhG/yGlX8D32d2uPv pqNLJamaFX19m+bc41pHkPsfJyVGHjWz0nNY7DC5JxqHhJxT71Go2/UoRtE/39z4T78S61Wv VGQnAoYN6HlTVAjb+41BbfUXDK8ngtT7OmdC6nW866slvsCRZPVK12gAndPdaXC2HpD0OLa5 uSg//n4TZ+NuO1PehVD1W7Nd6RJVjDtJ7nZOIDTirIgWUHkEIsC1ExCRXpRfbVFME5ZK77Y8 RDMwL049aTVV7sPhiwyePL0Yda0+HKH18tIjOzm4MZoa+huilvVh/VmYaAtiVQC4z37S23x1 AY31pS+wRJ8LVcL+ekp9P+/ANmdf0YFe64Imo7Ts7+i0HEn/DD4RGPMRb/Ks8kijDaJvJqo2 9bZbubOqq6wAMYfShtdRYvU8UpQSuIMe8sSgsXifmSQ8jUslOGyBvSCT6BDGnxh99czd1wfq pfwcZH4Ogns+Clz91SkjETC8f/TlzlzviwPahfeOjoIWIJx6s1ROy+ZTcQkV70C0LPpnqJCC zswtibH6RB+ifbjc1VAsNGFXmeFcdPpCxEvoqw4cluvRIk1AYoqoSzsDg72g72ANsW/wkiQf nwfYpZuIagtn7Z5GIGDneXZv6IfyXA4YF6cX0IRp9W8HQlpDcTwI/bXJeBhn1TmUEMh7O04p TlxNBsNPAHGm+1eFgPjUdzpA78oSEBHRJ83LehUmVebzN2fAN6WYXZ/I199bTV8sBrND/2wT 2nHYG15IwYQ+QF8uwgkQSBrj/q2/ff0IxC+PtzIDKRhY70w0obyMepm0iQ4+i+7liy2qusnt qKwaTB2Wg1wa553DidX1KWRv5ZrY6n38oMX0TedW6v40yj8RWlRv1bsLjE3P9Cwrebc3HA8H 2Gl94mkLnZyHRpvJYN476+Xtnjxx+YddXOINLyd1PvJcjwJIxDnsLYwls+nkHJMUYYTr6+iW RIgrZHXp4d2T4WiWR3noHzt5GaDu7OvQCknWA+1rXfvGIMQa/4zvcL0FG27byAsl89jW7u6o X8J192JBlRuvNInn0aowX4QdJweNeJQGRWZryHgcIARMU20QsSqsn+1rXJu9TBaXdhG9gXSI jGcVvb9Je4k6XO08L/wyk+agGqIWW19pDdBXnkShJ0R/nVDeOFehFGdHGmTeguSmvbKra/Yp vtiWATMs9FoO769CC+lvJZ6C/K1UVRB8BU2h6V5t+eK5DtmvZsATezq1UV47lxH6wYVhXNta EwokXXD35CK0JB2yUUQh57fdXXiqTPcFc+O0bK4v3l/v7k9PP6i4qNCHZE0kA6k25AoksmzN 3/O14QMGf9fJuui9CrNBNTMvSRumINWq8wIktlqY+j96SeKRUvPz0JTQAEvlmt+tAzLD2q6q DVKME/N4JPKIeAg7p2UrbIMSxjeHbKQy0anSH4LjLHdVhOFt2FC1clVtcgzxxLNdHpNPnyLr IlxHuh++bGWlm40JVp7gy3pvJbnTXy4QvSfhU5WnY0uzI+FIjrEuMc5PmnkCqyMoYeLg7FHz 0BCbneYhS0uXupomqQT2Z6UsQ+HlwUjMuOEJuAqpRSt8TcGAHMTjiVSX+3h4P708HP89vhIx RXeHmgXr+eVIu5ZRieVwovs6wlQV7avjVJCWON67Gl02omCNE0SkLUMZR4n9bARJco+wr881 5lHA36mM824wlSbdG9PcAIlSshL2RlrQMsDE07iCwaJAoGYMgD+LXV7V3AxXJvcUoT2AJJpL q9fqfhT6ZL0KKQfyGJHgascCWKyG1lHEYXMU5yO+rEG6qrwa15ltANL4CzWVw2RsvRNGHRPy mzbP9nBYDVgVwkyuc1aUoe4sp0RNfV26Cw/VCJIN3StMqA+sqgoHB/JhGcGU5bFLKkO+K2QE tY4ytjMf+3MZe3OZ1LrOlUrw5DKxcmn7VtAch7AmuQuVRvkg+LoMNN+U+Mv24QlFJ0sO7D80 H1QjGAagrchcBaHrpK9W0zqpVGuYJx9HFe2r8lYbYTxjqvSDLF37BFOUMU29p/0jIeRql1UU wz/4qo8ET6QAJGWp8Apb8mJHHzAQdM0K+m3z0DSeqNF6VY6MCbSsCqfVTVpXdyKnFgQDzKV5 4dqcrC2i2OGVLsymm9bRnFWWr7qSykqYMhVZwyJc4abrc32cRrFsMMWgRk7DRRJOkdpzP6K+ kRzBl6fsEL2T5WfCR22Ufg2FwwybWorL6AKjL1LE+DYjEwvdM1+XPnGaJZM9oRMbxG1Z0c8+ AhBl2DdEs2+zNLRWLg6qfmT18ShcWuYgNGkygnid5Z6hiOIQXaxsI4+eGOQQpry4ybG3SblJ zByTMbaJ3inZIZa7CMQemNrROmW4jekjXkqH3NrdQZug7esiSfhtpkpi7ic+TiPSMWqouJ0V G/+K6aFgBIBXBhdiuypblRPfZJdk71KAWvtoGfRQzG4ssjyR3d3/NANprkqxSZBbvUJLePA7 nIL/DPaB2O2dzT4qs0t8TzP2jyyOQoNz3ALMU+tdsHIa1NSDLlv6d8/KP1es+jM84L8gJ5G1 WwmmoimwlfCdxX72K4fzaF83Xq45HBVyBmejyXiu9SIguh3bs6t7808ra/mKBGtDF2nFtZkw dj4bA5851AfBylystR82Il1fH0rNirfjx7fni+9U36JquNG5ImFr+8kTqahpUlH7maBiv4Lg Cd2YFVZ2ILPGQRFqrHkbFqleqqUOXyW5ObwioXdPlQhL3EzCZBXUvAhBkNW9euH/uh2sucl0 u6nNBx2fI9eUrviNqmUFS9ehTypjQVOOmWBMBrayQKHgvabM2yThZVPpeInd+LkNkPJ456nf st18OgEhpKSKjuwvye0FTYB0hYmOeywj/5e8YAlZ9RKOSOXGrHuTJrc4hzmSqCAqrGNoS8fb kiSHXSpde9S4bKg4zvcVqePqHM6mehzvFmXN4zb9VoaCdosH+aSvVCkCuZ8d6AeOrjyfUNMi JsI6bymcaNye6aMwWYZwqKW81XVDUrB1EqaVHDyR6V/j9lB6cGYr+sg70HM7SyzOvMmdz6/S w8S3doE2sxamSrK4e9GVpF1jYxo6QsUAFDdSIvNceJtIOo68k19WbewaZKkshkiHTDWmXFbG 5aj83e6SW7RMX96gY+rhYDQZuLAYLwYamdvJByZbH3GiE7sdpiVveAug36UkcjEZkTgThRO4 K8/qAT/BbmPTN8ae6La2gfXVW++Az+CNFlAf0E1qa/zl2/H7w9378YuTM5dG0v68bF8IKtl6 ROi28L2x2nbOmpAp9TUcAWhOses5z4ZF5hw6m7S++5gG4jt3toBb3WgCjgPXWbG1Nv2GGJs/ ur4+vT0vFtPL34dabyOgETxrEDwpGVKHzMdzM/eOMp96KAvTctKiUYERLIg/Yy1whkmZDbyU ob8ys/OV0V2yW5SJt0hvA2YzL+VSn5wG7XJMuYo1IdOBJ+NLPY63SZlc+ntmTu3gCIFjF06q euH9djiaUu9hNmZoVouVPIrsLmgKo3z96nSriU2yNXRN8oROntotagi+3m/oc7r0Szp5OPaV M6QvJg0I5fgaAdssWtSFnbNI3Xk+SRjHLZmlZj0xmYcgEHI7N0lJq3BXUO9XLaTIWBWx1B5M QbspojiO6MurBrRmoQWxAUUYbs1BxOQIqs3SgCCku6hyk0XjI6r91a7YYnhSg7CrVkZYHTik c+e1Tx3fjGcM6QrneP/xenr/5caPQ5+Q+mH0Bm9Dr3Zw+q+dW3eQ0csINgAQSQFYwFGAEjeq AjV0A5mzHv5TXqMpCvEhJNfBps6gGCacAetlI1FcZEWcOZ6Cm31XXeXXARwMhcVGVUTWecZ/ 29+QdCFX+HDfsCIIU6g33rDxLL+pMUIbZ/J03x0ubRhVBj4ccIFIYPQ2YZzrr0kkuc4ZyLdf /nz7+/T058fb8fXx+dvx95/Hh5fj65f2XlAJrF0XMM3OMS6Tv7483D19Q+eKv+E/357/5+m3 X3ePd/Dr7tvL6em3t7vvR6jp6dtvp6f34w+cLb/9/fL9i5xA2+Pr0/Hh4ufd67fjEyozdBNJ +TV5fH79dXF6Or2f7h5O/3uHVO1WDa+U0LZkC4OYGpNKkNAcAvu0bQd519pA8XFfQ2rXGRxG AcQXEGRg9sZougTjUYRrYyoRZPoNmG5TQ/Z3Sevhwl51TT0PWSGPJ7qjQ1wcWfPwzV9/vbw/ X9w/vx4vnl8v5Gh3/SnB0Gdrlkd2Hip55KaHLCATXWi55VG+0eemRXA/gZ7fkIkutDCCB7Vp JFA7b1gV99aE+Sq/zXMXDYluDnh2cKHAsUF+cPNV6WbsOUny3MqbH6KNv/CTZ0dQkqj1ajha JLvYIaS7mE50qy7+R4z+rtoAY9ZCDch0EZPUBrdhrOVd6sffD6f73/85/rq4F7P1x+vdy89f ziQtSubkFLgzJeScSCOBgRU7q0kvgpJ61WhmbjJymgnMch+OptPhZdMq9vH+8/j0frqHc+K3 i/BJNA0W78X/nN5/XrC3t+f7kyAFd+93Tls5T5wy1jxxR2MDeysbDfIsvlExf+zmsHAdlTDu nptA2aTwKtr7WxxCGcAz942nvKXwrYvbx5tb8yUnKsFXZCAyRazclcCJ6RvyJZF1XNC2v4qc reg3a0XOob7+mh30+LPNMg9v0O0V1dMBiGHVzuPuV7WhLM2elvqCd28/ff0pg59b3DBh7iQ/ YNfbyL1Eyqeh04/j27tbQsHHIzc7kewWciDZ8zJm23C09KS7QwmZV8NBEK3cWU7mr81vi/EF EyJt6mSbRDCHhamc20dFEgxnAyebcsOGDhYSR9MZhZ0Oid1vw8ZuFsnYiLChUisQRpYZqUkl Ede5LELu66eXn4YSW7va3c6GtLoidvd0t4xKah4XnAwr0wxpdr0yjhUWQZkmuzySYXikyGXi nOEhofnIYR1Apc6LGnlGfGaZIpjElfi/u4Nv2C0L3IorJusOr6HG2CYWeZhWxLBPiN2R2oCq 68wOQyXH/Pnx5fX49mZIxG1zxe2qU4KhqKHSFhN3A0MdDSJt464WvDxtNoICjgLPjxfpx+Pf x1fpgdcS2Nu5VkY1z1Fes/MLiuW6CXBNUEhWJymSUTgDjzRO3ktqCCfLrxFGfQvRACW/cago fdWUiNwQaKm1pbZisN36FiG7hpL6GjJM9T2l2mhDhXTuLSdMhYCYLfGe2njC7QRt9P5onyAe Tn+/3sEp5vX54/30RGxUcbQkuQ+mq22gcTLQh3FnIdDkCuz9XEJoUiuc9efQyXBUHYChkOnN 1gTyKT6sDfsgfcW3W5y/AzQ5jwJ59iZBIpjP5ppaPeEeT9DXUerzl6MBlY1f4VF50pDl1BPi RStVON5jHgsyB1j5bM0cJHRLDy9oYREhA3VU6lRhFDEaTChejpgr7omDoEPQt+j5foySdRWK ywlPlMIOqqwEPtGh0mN2fx+VbBUeeBi77BuInIPsQu7Be2nqX4Y9QrboxiTO1hGv1wf3HGrR XU1ao5qjnSe6QgdqjP4yXgrZCBbH/+eTDafuoll5kyQh3hOKK0Y0t+1aohHz3TJWmHK3VLBO ya0DVnmioyh93ungsuZhoS4zQ0epPN/yclHnRbRHKmamEI86Yq7UX+jv5+IIjx9r14vRGu8n 81BqewiNV3Wd2u4ax9d39L8KR9w3EX0Fgz7evX+8Hi/ufx7v/zk9/dAMMLJgF6Nigrie/evL PXz89id+AbD6n+OvP16Oj19otOhpdTfQaTAQEHHcpx9ZqzDRb5sLIya1Sy//+qK9RSp6eKgK po8GrbcRwh8BK27s8vwVg32Rb+OorLxV6xBi88a/sIYmqAj3mRwiCbAz0ehdExt9w08MZpPd MkqxeTDp0mrVzIbYKzwULApmdX7V1adJqZdhykH6K4zgpuhSje6uZQQnKLR40tZd49QIDlcp z2/qVSHcE+hzXIfEYeqhpujaqYpi87iUFQH5wgONT8I63SVLDF+vtQy7l8Vu9jmPbPMPOCED XwWhVOe4fDgzEe4hmtdRtauNs411joefMA/jlX01J9KBN4XLm4XJXjWKj1MKCCuuvdEMBQLG yEed0UdOPjH3FU699YOE415i8EX3y761KFgaZAnZD7oOTNevmCrVzMx0VB5DaTk2tCFvpbxo pRo6PEaqlrOWPiHRui5PVw9EU7l4dHVEMoU/3GKy/bs+LGZOmrBHz43LPkWJ2MxjnCLpzOPG tiNXm11CXRgqBPpucSu55F+dNDG2bS91La7XhmqKRlgCYURSDrdksnHCbha0/rDXbu0YvwJY wB7D2BRM20/xrSnKDCN6mSQsfQy2gOlBop1z4AcaJXQJqQiVIQnA0Na6TpugIQG9LeAjoS6j FHwjsi9vUi5AqwyNW/cRP4syNC4xEU+alkafkVyXFgUrpDP8ZnNax7IvNfSVxkDT2NTqbPu/ ypIIeIrGEOLbumLGBTK6BoUDFaX6nOSRVAvtOMwq0LhEFon3PthIC20cV1latdGOHo3Uxb86 6xZJaNAA/EcqyrbthRplsdXfaVbLgDmR9kYpXkGDMM8qK01KAbA3wUY2ajUNS+C9iXltnaND LNpoK1t+ZWvrNKKEAWcvt/teMj/py6EUo3cdBvo6SIf4hp8FQhA1X4UbwVCkvryent7/ubiD cr89Ht9+uEoHQsrYCtNRTWqVifgwa72J8y3IaDwUpjJBHemvWFJvr4ZTRgxCRNw+Fs69iKsd 2nJM2hmjZGgnh4mm551lVVO9IIwZ9bIf3KQMQ2vYq0dPrm1bAjg1LDM8VoRFATh6C5afwn8g JC0z2xuCGl1vn7c3kKeH4+/vp0cl+r0J6L1Mf3VHaFVAdYRx4F/D6XjWDUYRwdm0RD8hpu5/ EbJAhvoq6V1iE6KzZfQvDCNKLl7FYaRhGxoaJKziGhe0KaJ6aOWo20eJPIC3wXRZ7VL5AYvh 4FPPJktrfV4zWM6ypXkmrJ1MOz6dQtR3n8RRikbk5vLUq3Adsi2qzSCnpU2CPjsyRgg2te6C 498fP36g6kH09Pb++vF4fHo3o8kwPHzDSaGgYmaoipZO76nVj/8SDSvFa7UAJGgr3jNp25zS jIxQJNRrxFBs14HB4/E3dVpvtrHdsmTKHDS6De2aCqqvPDgcw6coB0SNm2YrFF1v95p9hdY7 YWz3IBrJNGcopUXSZqZxQeQ7cP4M09LyJyFzQbrYRKmjCn6bXaemn2mRChO2zFL6sCUzLrKA Vax547dKhS0E1hl9+VTGu6WQP6g3GrV8xVa2Q56qrVy+QeFGkMI0kLatdqftE7cy+0S8hHqM V1pMsXQzq/M1CPJrZ3bLgCVCl0gXz/ah3gA0PVzBxHVrZJCpo49UQUKNaRgCmPjdHA0CJbTb Gkbd3HBK21jey+WDMOIvsueXt98u4uf7fz5eJNPY3D390HdZhn7fgf9lhqBpJKNzg512+y2J uDFnu+qvgTb02apCjaVdDlWrYIZkFEuUpHqDnt8qVhpjLNW1WlJbyHA0MLdakG9YogFFnaib Ax9WNaqVoa6vgNXDhhFkxv2juCCTbSJ5c383S71KYNnfPpBP6+u76zQx731q/JKq3mz0NLHC 9HlCFWPOauzMbRjm8p5JXt6gskfHw/7z9nJ6QgUQaM3jx/vx3yP8cXy//+OPP/6rmzOKQcDp ZVeFh7AkFoA/zKxaYO2XZp7XpWE5IFOlwA+MBepu05RZtnyIUwd+/UyNdt0wDdFm2uFl19ey Hu2HZP+v3O8bafn/0Xl2D8GSFZyH1v9UwmzXDiHFCG3EFB+mUSNRXHPY3bGVnLkZXjk7/5Fb 1be797sL3KPu8XbPkAFUX0Yec1611Zyhl/QLhyRKtVwQnkiM2FPSWuw4IP+iI5nIdqdvLDhP k8zO4AX0VFpFTFztyUdtvqN2WWuEG3GV72qMbxA2Vw2dIAsU/RvKAA0g6DJCy8DI2BpgTAqv dFciTYBTo8Z2twLXkkJk4YiP+q7VSrmi1MLa01rqumD5hsY0Z5SVVW+CWF9H1aZRqDXKkeRE eA8CAN6xWhC0mcZpLpBCqtbNnMXn3DTZw0RkAF0g4k42Fx/QQgrDSAOuz4CXu9fT270xRfRD bHV8e8eljhyeP//38fXux1FTk0ejeH2aSCv5vmDEtB29QQwPoq7WdZekia4SHE+3ZFBLDQ+M WdG5ASErYLkK8QsrIKLwbK/GwLwaLGA48VIca4JDgQof5Nrt60WNLSOvA+kYzYjrIOM7tG+l u0+yxWUkm0praFv3D/8HuyEXpNzTAQA= --jI8keyz6grp/JLjh-- From mboxrd@z Thu Jan 1 00:00:00 1970 Content-Type: multipart/mixed; boundary="===============0992859560005402260==" MIME-Version: 1.0 From: kernel test robot To: kbuild-all@lists.01.org Subject: Re: [PATCH v2] prctl: PR_SET_MM - unify copying of user's auvx Date: Wed, 29 Sep 2021 23:20:23 +0800 Message-ID: <202109292307.smDkJddi-lkp@intel.com> In-Reply-To: List-Id: --===============0992859560005402260== Content-Type: text/plain; charset="utf-8" MIME-Version: 1.0 Content-Transfer-Encoding: quoted-printable Hi Cyrill, Thank you for the patch! Perhaps something to improve: [auto build test WARNING on linux/master] [also build test WARNING on hnaz-mm/master linus/master v5.15-rc3 next-2021= 0922] [If your patch is applied to the wrong git tree, kindly drop us a note. And when submitting patch, we suggest to use '--base' as documented in https://git-scm.com/docs/git-format-patch] url: https://github.com/0day-ci/linux/commits/Cyrill-Gorcunov/prctl-PR_S= ET_MM-unify-copying-of-user-s-auvx/20210929-123259 base: https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git = 5816b3e6577eaa676ceb00a848f0fd65fe2adc29 config: parisc-randconfig-s032-20210929 (attached as .config) compiler: hppa-linux-gcc (GCC) 11.2.0 reproduce: wget https://raw.githubusercontent.com/intel/lkp-tests/master/sbin/= make.cross -O ~/bin/make.cross chmod +x ~/bin/make.cross # apt-get install sparse # sparse version: v0.6.4-dirty # https://github.com/0day-ci/linux/commit/37297835c68662e1781118a01= b7a271277e965d0 git remote add linux-review https://github.com/0day-ci/linux git fetch --no-tags linux-review Cyrill-Gorcunov/prctl-PR_SET_MM-un= ify-copying-of-user-s-auvx/20210929-123259 git checkout 37297835c68662e1781118a01b7a271277e965d0 # save the attached .config to linux build tree COMPILER_INSTALL_PATH=3D$HOME/0day COMPILER=3Dgcc-11.2.0 make.cross= C=3D1 CF=3D'-fdiagnostic-prefix -D__CHECK_ENDIAN__' ARCH=3Dparisc = If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot sparse warnings: (new ones prefixed by >>) >> kernel/sys.c:1997:58: sparse: sparse: incorrect type in argument 3 (diff= erent address spaces) @@ expected void const [noderef] __user *addr @@ = got unsigned long long [usertype] *[addressable] auxv @@ kernel/sys.c:1997:58: sparse: expected void const [noderef] __user *= addr kernel/sys.c:1997:58: sparse: got unsigned long long [usertype] *[ad= dressable] auxv kernel/sys.c:1068:32: sparse: sparse: incorrect type in argument 1 (diff= erent address spaces) @@ expected struct task_struct *p1 @@ got str= uct task_struct [noderef] __rcu *real_parent @@ kernel/sys.c:1068:32: sparse: expected struct task_struct *p1 kernel/sys.c:1068:32: sparse: got struct task_struct [noderef] __rcu= *real_parent kernel/sys.c: note: in included file (through include/linux/rcuwait.h, i= nclude/linux/percpu-rwsem.h, include/linux/fs.h, ...): include/linux/sched/signal.h:710:37: sparse: sparse: incorrect type in a= rgument 1 (different address spaces) @@ expected struct spinlock [usert= ype] *lock @@ got struct spinlock [noderef] __rcu * @@ include/linux/sched/signal.h:710:37: sparse: expected struct spinloc= k [usertype] *lock include/linux/sched/signal.h:710:37: sparse: got struct spinlock [no= deref] __rcu * vim +1997 kernel/sys.c 1968 = 1969 #ifdef CONFIG_CHECKPOINT_RESTORE 1970 static int prctl_set_mm_map(int opt, const void __user *addr, unsign= ed long data_size) 1971 { 1972 struct prctl_mm_map prctl_map =3D { .exe_fd =3D (u32)-1, }; 1973 unsigned long user_auxv[AT_VECTOR_SIZE]; 1974 struct mm_struct *mm =3D current->mm; 1975 int error; 1976 = 1977 BUILD_BUG_ON(sizeof(user_auxv) !=3D sizeof(mm->saved_auxv)); 1978 BUILD_BUG_ON(sizeof(struct prctl_mm_map) > 256); 1979 = 1980 if (opt =3D=3D PR_SET_MM_MAP_SIZE) 1981 return put_user((unsigned int)sizeof(prctl_map), 1982 (unsigned int __user *)addr); 1983 = 1984 if (data_size !=3D sizeof(prctl_map)) 1985 return -EINVAL; 1986 = 1987 if (copy_from_user(&prctl_map, addr, sizeof(prctl_map))) 1988 return -EFAULT; 1989 = 1990 error =3D validate_prctl_map_addr(&prctl_map); 1991 if (error) 1992 return error; 1993 = 1994 if (prctl_map.auxv_size) { 1995 int error =3D copy_auxv_from_user(user_auxv, 1996 sizeof(user_auxv), > 1997 prctl_map.auxv, 1998 prctl_map.auxv_size); 1999 if (error) 2000 return error; 2001 } 2002 = 2003 if (prctl_map.exe_fd !=3D (u32)-1) { 2004 /* 2005 * Check if the current user is checkpoint/restore capable. 2006 * At the time of this writing, it checks for CAP_SYS_ADMIN 2007 * or CAP_CHECKPOINT_RESTORE. 2008 * Note that a user with access to ptrace can masquerade an 2009 * arbitrary program as any executable, even setuid ones. 2010 * This may have implications in the tomoyo subsystem. 2011 */ 2012 if (!checkpoint_restore_ns_capable(current_user_ns())) 2013 return -EPERM; 2014 = 2015 error =3D prctl_set_mm_exe_file(mm, prctl_map.exe_fd); 2016 if (error) 2017 return error; 2018 } 2019 = 2020 /* 2021 * arg_lock protects concurrent updates but we still need mmap_lock= for 2022 * read to exclude races with sys_brk. 2023 */ 2024 mmap_read_lock(mm); 2025 = 2026 /* 2027 * We don't validate if these members are pointing to 2028 * real present VMAs because application may have correspond 2029 * VMAs already unmapped and kernel uses these members for statisti= cs 2030 * output in procfs mostly, except 2031 * 2032 * - @start_brk/@brk which are used in do_brk_flags but kernel loo= kups 2033 * for VMAs when updating these members so anything wrong written 2034 * here cause kernel to swear at userspace program but won't lead 2035 * to any problem in kernel itself 2036 */ 2037 = 2038 spin_lock(&mm->arg_lock); 2039 mm->start_code =3D prctl_map.start_code; 2040 mm->end_code =3D prctl_map.end_code; 2041 mm->start_data =3D prctl_map.start_data; 2042 mm->end_data =3D prctl_map.end_data; 2043 mm->start_brk =3D prctl_map.start_brk; 2044 mm->brk =3D prctl_map.brk; 2045 mm->start_stack =3D prctl_map.start_stack; 2046 mm->arg_start =3D prctl_map.arg_start; 2047 mm->arg_end =3D prctl_map.arg_end; 2048 mm->env_start =3D prctl_map.env_start; 2049 mm->env_end =3D prctl_map.env_end; 2050 spin_unlock(&mm->arg_lock); 2051 = 2052 /* 2053 * Note this update of @saved_auxv is lockless thus 2054 * if someone reads this member in procfs while we're 2055 * updating -- it may get partly updated results. It's 2056 * known and acceptable trade off: we leave it as is to 2057 * not introduce additional locks here making the kernel 2058 * more complex. 2059 */ 2060 if (prctl_map.auxv_size) 2061 memcpy(mm->saved_auxv, user_auxv, sizeof(user_auxv)); 2062 = 2063 mmap_read_unlock(mm); 2064 return 0; 2065 } 2066 #endif /* CONFIG_CHECKPOINT_RESTORE */ 2067 = --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all(a)lists.01.org --===============0992859560005402260== Content-Type: application/gzip MIME-Version: 1.0 Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="config.gz" H4sICAFyVGEAAy5jb25maWcAnDxbb9s4s+/7K4QucLALbNvYSXrBQR5oirK5lkRVpGynL4LrqK3R JA5sZ7+v//7MkLqQEpUtzgLbRDNDakjOfaj8/tvvAXk+Hx625/1ue3//M/hWPVbH7bm6C77u76v/ DUIRpEIFLOTqDRDH+8fn/7592h73p11w/WZy/ebi9XF3GSyr42N1H9DD49f9t2eYYH94/O3336hI Iz4vKS1XLJdcpKViG3Xz6vvT0/b1Pc71+ttuF/wxp/TPYDJ5M31z8coaxGUJmJufDWjeTXQzmVxM Ly5a4pik8xbXgonUc6RFNweAGrLp5ftuhjhE0lkUdqQA8pNaiAuL3QXMTWRSzoUS3SwWgqcxT9kA lYoyy0XEY1ZGaUmUyi0SkUqVF1SJXHZQnn8q1yJfdpBZweNQ8YSVisxgIilyBVg4g9+DuT7T++BU nZ+fulOZ5WLJ0hIORSaZNXfKVcnSVUlyWCpPuLq5nHbsJBnyqZjE6X8Pavia5bnIg/0peDyc8UXt XglK4mazXr1y2C0liZUFXJAVK5csT1lczj9ziycbMwPM1I+KPyfEj9l8HhshxhBX9vosruxF9vGa t5cIkMOX8JvPL48Wni12OK5hIYtIESt9mNYON+CFkColCbt59cfj4bH681X3Krkm/iXKW7niGfXi MiH5pkw+FaxgHg7XRNFFqbH2ptJcSFkmLBH5LYo9oQvv7IVkMZ955iUFmKXe+ZEcXqURwDDIXmyp vgvVugGaFJyev5x+ns7VQ6cbc5aynFOtaKCbM0tpbRRd2FKKkFAkhKcuTPLER1QuOMuR3Vt7U+zp QzYr5pF0N6V6vAsOX3uMt+rG5oTelmgIcviXWhZCG4dlgdqttfeh1cUsanYDfvXtBoDLwW4isEiz nK9asRJRpJdSs+jOZklLzliSKbB7qU9aGvRKxEWqSO5sT418YRgVMKpZEM2Kt2p7+hGc9w9VsAW+ Tuft+RRsd7vD8+N5//itWyVuVwkDSkL1HDydW6uVIQoCZSCxgHeMXx9Xri49/Ckil1IRJe2hCITt i8mtHukVf02z6aObVUveMQkP7VmEXKIjCO0D+YXdaA097AOXIiYKDXe9mzktAjkUD9ip2xJw9sLg sWSbjOU+pqUhtof3QLhXeo5aHTyoAagImQ+uckJZy169E+5KWt1cml8sbV220iWoDV4wEoJX67Qo FujVQE8WPFI3k/edWPJULcHVRaxPc9mj4WnINkNDI+mChRDhCK3N+iDk7nt193xfHYOv1fb8fKxO GlwvzoNtj3WeiyKzIomMzJlRGWZFHWCT6bz3WC7hhyP28bKez3PEBmF47yaKCM9LF9N5gwjCL5KG ax6qhWfGXJXeOes3ZTyUA2Ae2gFBDYzAUHy2V1vDQ7bilA3AoAm1wrtwYzZdWMIl9cwLVryDSkGX LYooiz/0yDIDaXVMRKEgQpRjjjEfw8F+jKFSpnqohuEFo8tMgDCWObgIkVu7YaSQFEpo1i3ErYST CxnYX0qUe6Z9XLma+k4W7Z9lamM0iSsdu+TWQetnksCEUhQ5nFQX1+RhL2AEQBMndiYpHIRfHcYO EDWhGAy98m4moD5LFXpmnQmB3sg1KBDyiwxcMf8Mwb7IS7CQ8CMhKXVDox6ZhF98hhScsorB0FKW KZ1eobFzzgbxOiYqUhLzOeQXcSzWHYkx0paug/PgKFjOOc6ZStAN1VHAWICIZ/MCRbQA/Y69Pl8H kDpssY2Ttot2kjN3DBCRsDuF+7LmVYWybal+BJ2w1p0JHc107MPmkDjynaTmy84M2YqlygbIRc84 Ei68W8BFWcCq5r5oNlxxWFC9gY4NgMlnJM8hXvTF/0h9mzgDGlhJvLvTovUWov4pvnIEECVABxLe DVlSnTG21MAeC0PmI9VBOUq52TSHy4xOLhyt0l6sriVk1fHr4fiwfdxVAfuneoQ4hYB/oxipVEfj 8Jp5uum9sfIvztiwvErMZI1fdHiWcTEzJt1nQCE9Jgoy66U7hPiyF5zJJRN+MjIDAcjBT9exXX9u 7dFiLsFqg36JZGySlmxB8hCCC9dUL4oogsxeBwRoI8BgezN6kE/FEu26sArCI06bILGLlSIem/C5 PQO3CNGFH7nrMiHsnKFApSEn1pRJYsV1EEWDCwU3tJa2I9JWDraoNrmvtsfd97pU9XanC1Ont7q8 td+9vpx+2Z/Lu+qrQbSOpIm5HI/dABdrxucLNUSAvvJZDg7OhPI9Tk0ACqxmwja02dxUamKQNdD2 qRH+7HjYVafT4Ricfz6ZGN0K8dpde39xceFoEnk/ubiIR7Jz8n56cTGGunxh3IeNO65FTCZ2CIln WC6KeVM9GeC0UKEPK6+WswEW0ntQ3w3ukyvbiS+yhMRXb6vsnXwERgzsJIgObqs9z+JzORlZP6Cm 174lAuLS3WIzi5/25rKrDuoqg2bJLSBtmH+XNabE6p/Xdr0kEFpiov3x4T/bYxWEx/0/xjBqOMmT QOr8Bsuy5+PhXg9Oto/bb9UDWL+Ao9n7ugVrCC85H3aHe9uowngI+hKO6qwEFT4/0tGINYSibfGj 5f7/xUSfh+wXeMgGPDSen+fJmuQMfWhCHK8VrSHpqOMWf+ZdgM+VZSI2Zb5WiZdmRpOr95tNma4g NvVSzIWYY2m3ZmTg71T17bgNvjbHeKeP0c7nRgga9EAATCnn+RQcnrAOfwr+yCj/K8hoQjn5K2Bc wr9zSf8K4Lc/7TMHoFcIf30yY8TIa1Ts4PRU7fZf97uaZcuC0QWRErY2phBZ29lcFtIG6QWWsIWp i5GqVfhGZ8be75TD0T/sz9UOden1XfUEg1Eg63VavOZELsC129nQUhcFLRb/LpKsBCfL3JhSgWuk oOK3Uls5LLz5wqmcqf6Ephjth/4LOZb0o14mYJwQ2E4wk3M59EZd7VRTLoRYDv0cGOSSh1j+X+SM hD0DfDmdcV0DLPvz5gxeCaFJ7bkhndalMjsc797v7OQLWDtstdnQtCnYJF1ygUB1Qxdz31SSUYzX XkChVXbqIoMhA8Lu6GsMJZA4jwaMsRK6DNpjIhFhzUjGKEZYViQkwiKGM4YAvUS/ibvQGy1FpLB8 DGIg1qnZ9MEmSTNaB4zgmH27AEQLKzSLgU9IGOgSVDB0YuI67DUCgMmSLzSGyC4VJYtgNRyD6yjq e3BkSioQNNX0NPK1lcP5UC0LWB2zo3Y5MLNzKlavv2xP1V3ww+QDT8fD1/29UwNGoi6I6YLXl8b2 I9x/sStWPSvBrNTWYp2OyQTr7BP3wDE9LXWlQA1kwckUDTVQUqw3ktDrkmqqIu1TdPi6Zyf7b8NK bdPMdfoBHZ8efmruKXuJHSQaKx1YJHJBJr9AM536CzY9qut3v0B1+eHKv0sWzfVk6tsMo0WvTt+3 QPBq8AJUnRytYb8ZMko42oPsE7q9xBEirF0N2NYlIixmSkjiurJkyRN0Gq5IaJcDkbyCRb49fdk/ vn043IF2fKnapEp3lGFOrPJIbnx1I/B1Vbt9NKW/mdRGJbGzSgsH2ZavXKjYPOfKW0msUaWaXFiN rxr9WfRyYUSsZ/5ujBkE1ryMfCVUREsWliIjcX9K0/6HBIXmt7pcN7BR2fZ43qOZCBQE+26Ng+SK 6xofCVdYLvTpLUn4nHSk1kHJUEgfgkXcAXcxVI8Ve4HJp3LFYYxo+hFcdE0HK3ICOi5M4TiEeKG+ /NAJbIde3s68ta0GP4s+wbl1zU/nfe3qZWqlpfVuy4yn2tCBfwCnOMBjIFPjX8J5x65BptjYYBvp ju4aEHrz2H+r3fN5++W+0nduAl2jOjuHP+NplCj02H6ZNGhJc56NSK2hwP6EF4/RbVgkmTf6H2NQ c5hUD4fjTzujGwTQdWZuSaNp+dv9xcbHZzHYikzpTYOQQd581P/1Rs7QQtXy2rpODTKxCO1rlx2o 0F61CmsTOUPL5nR8QZXyHnfwQxkfZTcDURVKiONmhWUZl9Jab9OTxQQU5kUVDvObq4uP75z4pw7K 2ysREeFxkbsq42A8K0wZaEsGeTDGW0uLBxozsBoYjFowpzuWkH6rqgXZoRoCdcrsgiCzJfLmfcfq 50wIvy//rCMcQT3smwQhIZt2z3TVKJndTC4urCp62FQqMVtZ+uvpsAu4CYOe+7zIyn4ipkU53J63 AdlhuSVIDo/78+HoBIchSVyZ04ByhafpVZyxCRv8uO50x9leZUir838Oxx8wgaVhlnugS+bX/SLl Gy9iE2a6G8n6ZfPWkI3MCHC8fYY5TkLypVcMUYszvJcHLj+yfHIzNluYaypwPEnW1Io7GpNQed9O lLfCray0LMmth1nOwznrP5ermKR13tZ7fU0Ak/htqUHTyMeGnvXDxXTyyZ6xg5bzVe6raloUycrm PmQUheDBkjoNKXNRKK/PjGPLOMHDtIt4iCLxsnvE4IdkWcxqcHfyWRj6F7+ZXvteSbKZPT5biJ7s NBMzxnCV11cdFx2sTOP6F92VBOlIFbFSDIvSyG03SUJoO6/T6Nbxg3cpIfW1W8JUYvNb4KVFe64Z iB3RwZfv9Go1sgc0sDLkxGeeWjy4rQzTamewDq9aGt9wl6IJlx8sPYMwZKnfbm1TFktHFzWknEvR 078ylb5LGAvpFDk+5congfXtBm0Ecu5MbaGMbfCFsVq8N+hQb8u6Tducwqe4Zw+Dc3Wq73G1dnWA 6iFsG9qVPZKchF1Im213P6pzkG/v9gfM9nVp2gpqCGiCpVjwhO6AYKfNLknBUnKRdIS5kOzmoa7Q b96ANj3WzN5V/+x3lVUq7Zz+EjIxrwi/Q7Pvy0KyT0wt+gJ8CzJS4pWRKPQ7BItk4ZLUBLckscPw FxfQCgNJbTbgsczJ2ic1gJnRpE88H6P9e/Lx8mO3swiCiBLcQL29AAhCw1M4qD8D8cpwZkM2HmZl jBP5WQAD6s5ASUwh2FZ4dcN1Kogl6uNkZKYoZpsBP/Pcx0+RXnF/EA/YDTZeNz2OHQpsV46th9L3 7y96K0IQbCzxgTOI37Eo1TsFyCnhZxT2WU/6r3alghK/w2+QZtJREvk3GWnQaSwWRdO5y2kNLKm0 hQZSxmDftKUcTcQxC345mfj1R6+RZtPriU95LKzeGh+4lCQ1JYzu0uaQI/eNphphbq/57z94NKG1 FPZFYLy5wEKr3g2QPELP4gGVyim1wNiUZQMALM1THG+Quq1XvhDrAeHCW2ZRpVNGwkf7/h8AEhnp j03c1xIhM4D6p+xyHXuIr3FjWmz3z9X5cDh/H9rubjTWnmJnjxeUFyRXPli5uOq9vEHMqPSFjRYF UYvLpbMDDcaw4MOQ+bvNpo8JVTzpMzdTl3QAiwsGWuloucGs4H8/s0m+inv0n0CYZOK9QKeaMpPl c0Y3vQ1xqJ0JrHnOYibddkU0x1hxMjjQFvFYVXen4HwIvlTwXqx83GHVI6ijzIlV4qohmGbqUq9O XjFpvbHy1Txacu9FLIx0Pmb92OtjVi989Prmx2zYUrKMAvfXidLIl3NnEjKwmDmhI9hwS73itSpS 516HjqyxRpNIx8thYUKsRpQZQhIlRNyEpsP8e8RZmytklNsvyrwSllEtkF1tR3epncxEQ3RnpKR8 2CXK6Ovd9ngXfDnu775V7WWKubk3VPMWiH6JixToeAmWpuwqUGE6UgsWZ3Yb0QHXtXOrNQCmXCXZ yJ0EkLM0JPFYtyDLzdzttQf9pdVgme2dgfvD9k7fNmgOcK33xuZW38xpJ3Q4banNVWSzIP/Vz5ay aT14PVWfr1aNSap0utoUKm1ZMO0KG+vP94yfzPmYfLaONO/7UYcAfUE9DWSKCYi7//IIkhF5m9KG WLdKPFLbXiPLisaNd7ufs7m5tuI8l3xKBzAZ8wTF76EPtxvtLSzhA8Ik4WL4Jrt03YymdOZ7TUlW dqwQYj60AKEJ8bOHyI0BEBmxlJoanv/y04jatRdcjAtwQjS8DmT6PXh/sYxHbu2oSUmy2Thu4zMv idgotxajXWvJN9nVZlMy/3zo4ADHfVffkwWvLUaX7RmQz75bt3GalVul6ZThV6KOkcwF9dyLbcQu lZasJCp0HrT8tmFx1w162h5P/fxU4W2F97qP5FccpIDU7t0l7NKAyqKhiW4SGRqXHRG1UGfaBq4v Yn28+DD6/pYQfY+8Hf2oAmmBEO0ZT8icKeL3shadyv35AJKg/GcyfnHZoCD6YwHPshtUCHEMHu9t 3TJ9PRmdQN/01/d37YtVQzLsbok0dpKN4Tnrgy7g1yA5YL/N3JlWx+3j6V5/5h3E259u1w8PO16C JeutxXDeOz8NLHMxcFHp4VwF5+/bM2Q+wenwUAW77QleX8x48OX+sPuBI56O1dfqeKzu3gSyqgKc EPBm0jeWV1NWCJ4Onsp8basNR5jnqHLIz5yxUkYhtRckk9I/VAugyAbS27ZewUQmRPbSIPPRHUne 5iJ5G91vT9+D3ff90zDP0LoTcXe7/2Yho+bjVQcO7qZswA4zMAPWN/WXJ8L7gRBSoamfkXRZ6g+1 yokrYj3s9EXslYvF9/OJBzb1wNDwYnr30MeQJJQq9K0NQiff1z8NulA87ikfSfrz5MLvULQNnEkw tV6T/cIhmi7q9ukJq5I1UCcbmmqru0d9a4sxFKwe9xN7Jy8YssWtTEY+6NbWiV5PL+hIrR8JIFbX NKMESl5fe4su+vUxUblbM/y3lZrvG6v7r693h8fzdv8IqRdMNZpi42vwW4Qoxns2D15w3YvXXyvc urLU0QjlBJVaXOkim14ue3eEegRXH+J3Vxfum2XGSA7WgPfFR0o1vR654YToeOwSsTnMHtbmRIVm ozsYPJdKKBKbdNRuN9dYluv7ZoidTD8MTPXUxAQmN9uffrwWj68pHtUgUXPYDAWdX3q14N+P1Vh+ yHDcA0aIuYHrxgQpQ4wXWJ+2OXr3zBuK5tvifkRRoyEtloW3s2xTecSmQU03aGfnLx1pTtZ6cSMv wZC6XqG5KkIp7OU32L3g9Pz0dDiePfvE9J9McbW4hpdyjY2OpNcwH6Wd9f8iQ3MjxMNH22PB09Pc xhk2xv/H/JzilfHgwXS8fU0OeLUZ4Hvhv0/VUyTcOO/nS3WI4MoMxgzrWF9rlgsRh31lMUEFm9V/ D2V60cdF4Lt7Xxc0qHlcQPA/zkl7B84ZubiFTBrSAF+HUlmpn4jskQL/JANX/Wqljcd7eKGa+SYG LF7VUTlj9gvKpZj97QDC25Qk3OFCX2kxdbYO5qSOImr6qg4Mq0XON1P6KkyCH1o1hR+Mkurb6tZ9 Bw0auYGHfZnBLcC0gKXDg3VvJTS9uS71q0mxJTssT+UzsFf7kykHfql22+dTFegcK5IBuDF9X8IM ua925+rOucLVcDHzljprLNrwAeNoqs1ftZi88+EG5l2vq8yWioYru9Ngg+uMXN588KPXzV0h694F 0aeFdbzxhrTZYGPHVwkLZN9OIbRnyzVIf3isa2E/HXhEZmCkZY/6/zj7lu7IbWTNv6LVPfaZ9jXf ZC56wSSZmbT4KpKZSdWGR10l2zqtkmok1W17fv1EACQTjwBTMwtVSREf8UYgEAgEdolC6ON2LzoE CEQYLLDuHtqjkvLExc6WvAYE3o6+DyPVjCtwGBCLMkekvuMPY9rU1FhNj2V5N02Ty/Yj6Tau03kW 7eWMvnSwpHeUKTerkqLujm2GZ7jckCRUbJ8dkhF6lXYBPOSB59inwLKwQGZLRlLnVZIZ3LQZAoVh 21Dli5u020SWE8vXm/OucDaWRUVN4SxH0K9Ax+7qtgPFs3BA9RR8ByfG9mBLp5gznWW+sYYL51Am getLQQLSzg4iylKDghEaFFbGxp1v9V+ykOYtP4Mdu3SXScpF4qgiiy/qWYO7Cm1B53Tob0fYJ12I vkbkwX80chkPQRT6YkkmzsZNBkq1XdjD4AVaerB1G6PNocm6QeNlmW1ZnqjvK7Wbbrz9df92kz+/ vb/++MbuYb/9eQ+b+Jt3NCsg7uYJdQsQtl8ev+Ov4pTqcSdHTsv/j3SXkYlHkDFuERvhmCNLDpL3 SnNq4iqnZYIkAfguJunyWcHVeheZ6D8vmFHjPGXR3wRZx1Cqaw8SFYgU54RRpkMWsfSMPq9X6ihk hZ1Kya+a/gTN9O9/3Lzff3/4x02S/gLd+DO1onWGI/lDy9lrfvTANpz5z1/TiqpwGWD984RaqlhD LLJSa+0Kz1hkn1HGKer9nnY1ZeyOuXigwX9eAFmb9vPYe1M6n9nLie7eJSQ5Z/9SnA7DCxroRb6F /yQb1czCIHDqHWsF1TY8YXo3p9ROa60zu9puTj6lNxfUtJG0EHrrQgbu4Ku4rG30CcgwzRaJVLyE bTh0RXbDSkYsDZMD30UH4Zcisiy7sd2Nd/PT7vH14Qw/Pwty4HI0lrcZHlOTjbGaiKCzZD3hAMKL 8fz9x7suhgRrZ3PUF6XD/etXdhCX/1rfzKP30n2wb6bbaR+XmbrKLZWhEl0qShWT5wky/B7U6VdB v5p7pZeCw50oHQvdnzfR2PR3wuZkipNnIk7qtuMHl8SLFGMVYAAk9dLcZLJ6fbx/0u1T2FRxMUaO b0mz8EIW4yOZTa/iB3YAik88nmIgqYJKgO3QSEq5B0qZs5WD/D65Vo6qHY/syMKjuC3G0ANVeoaQ eWRDn1WpwUNXBMZdg1cbTpjatSqdpQtiMsvUCRltpBEheZ1QKqpU596JosHUoLXJFCuCiiaxo4E+ UBJxZR/4YXgVBsO/OeSGE2+pdtU+03QbAtcMlBFdRLDDV1M7b5MydELKDXJC4Tndxa1wOgp6/gU/ BjSbZExHIUTZlEJcbmNIw7Jpq/WMwn3UGqDMupr2VpwASdF0ockXcMIQRkQVwprrKgBWoKO50UDH d0HzFjc9An0gOiMvV8sN7DGL2+IuIS9STSicjAXaV9V8Z8ZFRNh60xxADaA9WSfEocPZ4DoD5U45 d0It35CaK96tzudTH/mGkDDzMFTmqlL2fIeRB/RmLUAg5/Tuef40SaphVQx0iR3kXbguA0C0brM2 jdWwMTJqOnQ3V2Ta9/zWx3vZKVHmM54qUQUeDjR+N1hdCkTQNj6mGCbpn7btO+J9LgKLani9Xrly AL1XXQ9U0LQZb7rxGrJsOucqKG7Ja2ucuetgADRTW6lfXphU3QhsXqFTONkr8Fc2MJeofJ8noJC0 xFBk7ker8rxr2tWFt+tLlw5nPTfZKdser7YZbATW2DCIV/PIi20Gatd47HIq/PU88UDakKN0ZjDH TD5GdVm0gMhhtxxfSSqeKmqTvi3GfcPcVWVWxbeUqeSbWI2HtJBOaqpx31Hne8xwjaruxXB1mp3K iIHG9sXkyQGkMcdU/KbTeCSyfy5W5MmgO7WIcF+rKfORR3IUvAQZlVlHuMeRZN+78DCIh2E5ZCi+ i2HH++1OcwsTkeRWjHNAOmvZsxjkaU3t3nnxMHrUHMB63mtynfM26ThmW9LTqWpAqRmG68ApQXQL J2CX4my1drg09OE8RW0hSDxSZV7jbWtBIFz429hzKd3rguC+bGIrXHi6U7L+OegNbbVPqMIxcUIx mKZFMsTonxdyNtxVdUdxsCcoOkZg6uU4OwsvgYkrXgy5cAZQnWFBWq6EMd/hmy/EfvQyB++qhN27 IzdP6J2Mtwg9y5Ku2cxU0Y+gS1rHG0RTqjF/wXydncqMkiF9Aj9NSfcrMEyf5J0S+WqiagTmZSrZ UxbymLQ+rWvNoNxJPgbSlHYCA+tmXmV1RZUG+dXxVPekVosoloPYTEg8QQuh5XS4W8m76133c+N4 ZCtMPCzAB5KYGnPiggpT3KFLKLsxqdMJZL0T7cq8k9sjaATo/7c4eF8uCBFDCk1HUFjNcC15HmN7 bmsYv9DotUzmQaEUGos8epKJ5XGYZ1j54+n98fvTw19QEsyceZtQJQA9bMvWWkyyKDLYu0puuTxZ hqAk7MLmeWvfFX3iuRZ1NDIjmiTe+J6t1WRi/EWl2uQV6gj0kjZh2oxcoYCbZkIaVPJlMSRNkZKq y2rDyklNtxLQ0GUoSTd5mS9jJH764+X18f3Pb29KJxX7epsrYwCJTbKjiLEo7ZSEl8wWIyK6QVP2 TKxDPviHVFJdLwOah6P8FzpRTz5oP317eXt/+vvm4du/Hr5+ffh68+uE+uXl+Rd0TvtZzYDvVIw9 ydd5M1u5ByozhyE3pwwbOidy/TU+KBBtTesfM+K2rigjDmO3Sdn1W2XeokyZVFspsTQ+wYAkNTE2 ZDGoNruGIpvgFaZyZ1rhCtYgOe9572PIPSuzk6NOFK46mNtPlRjKsNofYIOfGqxpHNLRJg22MpUG zZfxQOw0yvIgI+rGNdgEkP3bZy+M6BUU2bdZqQkHgV00iXNrlkxGUxjj9oG/UrCyDwPHPN7LUwAK 58rngyE6CS7lXPE28mscdubPjfZYxjxTigZyQFAZB2VTmUujWE4lHnetMJjDENDmBtssY9665mw7 N3E8gy2U8Q9jCWKatEcwfl72WaJOJKPtgDFpewBnwSZgR4fmu/BpuzbjH6sAdmvO2dxUoIN/OsKe yTxLuUV12xgOPxGyajcXASN91xIhGCcx7rXIzgLiXJJRUoDD7Vbq8BoKc4GGotmszAX1ev0UewyU vuf7J1wZf4V1HRbF+6/335kmqPtosqaL6w52+KWWVP3+J1cupnSEBVZNg9RUBP5uRYZSF2MFjYHU DtQRdqQCvzDWtBDJeCRODi5r37EbU+h+qSbArw2iKDKukwhAHYj+VLHmSBVe6jh/5YrBYnPYfQEF L2ULhrFGukqLOzRTfFrk8Xsp0ucjD+fGDz6b/Ka8f8MhM4X4xpeHCN9w5u9g1psubK2pZEy7cT2D aZx5VBzCzcrHZZzGI77muJKC8WBo5o4gX1IWlIFssXjg3h2wLcGQh9/kFNZUOIEfH82VJMz6FH88 dEohVdT4yVwL0Ny3sRzEhG3mYfNYGQxzAp9qIhlHnJ5JI3JWANX2S894aG367MxvserfbHtaB2Ed 1WwMpyTA3HW5mhy35a/VDhHXWgB1RXyRr8lMB4QzqNuB4DOXsBoaFkBGuuiLDFVlRxooofD/zlws 48kg8H5bnZpFE0WePba94dRhapdr7bbaaEwVxd8ScyYLRnXfFTFmpZWzjUorZ9+q9wskPiqm4y4/ rgNWRxA/STQ4+iKgTtjTeer8RKXW8Vaq1ufarNcSwKcu6O0AQ7S56WQc32HIE9Op0cwdu0/m/EFN Npz4AhN2trfTq5vSRzMdp4ox5Xat2p+OhkNZ4IEKHaw1aZfYUd4FlrnaqGR3eU3rihyw9u1hreT8 MNrMNp7yTcwxTlcSN58Bztz14YROhl1CK/yMb4xnNXGDFS6l6YvTdJCvd7Hhj7q/Y1tMPJsnCaJs 21xsnowF4w1vD16HqRFPJBS12RDYgxyCiZG07QGjFuYxjI5WXQz/7Zq9WQP7DC263p+IKJtxv6I5 xOVyY41ph4LxkfLawY6SlZ3l0/lNmEnD1PRJ+EkzKiIjk6CLXyZ/71bumCILnMGsBTKV3qRkqPef pmgaQgIlX7ndIDRlAYiygzUAEkJrNpHVQXzbFf6QLO3cSxM2Sl8WpXuJVsPIT4/oAS9E0UHf5kPc XqxwjXwfHf5cCSpU9Q0itF5C2pSXbqnHJJOCPfdwy44mpcxnFvOsVEsy8VR73JLn9FD9y6uYLef2 DZQIAwTo5YFK2H4UTa+pfqPpkxdmXBgBqejypPA+wer4abmwyYJH3TSHO3zBGp8+MsW/xWhTbw8Y 8eABtuBfWRAG2Jezirz9t6kKeBkjchrXNRYHAIl0AVtvnuXL5WxhIsyBaSbGqD0em1f8AEXH44HE 7lixWNvyF/gbnYXE4Dtf4rhjLgwa0WFw0BJ6AZW0iJ/529KODEbTGZLGEXo9Hpv1lNbcNmcMhvlz O0OMkhk0azKrIHyYwWBWWiCD7Vvr5WlyjLd9MFi8l4T6creeDuE6qiDqJCvqnupGEH9QY6a5GW3v SyoGR6Klt7l7xf7KmJhQ9A5cRdHPgyzjB/fq9pVuX9vwC5jAtddHBsM4H8D4H8AEtFInYz5Snisg dhhlPlaZYcndvjp2qh6gwYyPHc/s5npWVed8IJ/mKibuXMPivjRQ1oKWNm73nuFp9yW7lXOMZbLC tsi/DgmviCCDX+zMZ+cQTDlBxeQD0G77AWiBN3DxeEtbyltYxt/u326+Pz5/eX99oizGi2CEpaKL 1wdAs5vO/a6i2igOw81mfVZegOsiRUhwfUQsQIONUk/wg+ltDM4zBJC2auglXJ/XlwTdD+I+mO8m +GifBB+tcvDRrD86bK6oDBfgFQFxAcYfBHofw7nx+oBtPxve0BIA643Rft4766vxpcwfbQXvgz3v fbCfvA8OTe+Ds9tLPlqR7IMjzrvSDRfg9lp/VddT6g6hY11vE4QF15uEwa6LMYCFhvhRGux6vyLM /VDZQp8+RFZh0fVBx2DriuAEcz8wj1lNP9QLoeEJOxk20MGWTCurngz3iVnfA6APwRUFZc1IumDQ 3Nglm+iK7J68BJz14TWhrgzCyaPAW+/ACfWRtA7XBAtDlY19ReefYVcGap+Pec0eFl/ZYM0WRGqL tXgqFOn6eFqAoLN/ENkV6bqeIKa53hwX5NCtCwKhQgEdc5VA2uvyUUBekVZiOaVxML2H9vXxvn/4 N6HRTulkedXLnu2Lct7fklvk3gkNwWAukDC4IlMYZH10l310bcwixFkfr1hce70Dyz4Ir6h5CLmi JCNkc60sUOlrZYns4FoqkR1ea93Ijq5DrmiYDHK1A9yrTRf5NuW8LDScuwlFB3DjqCX2cnVyqOJ9 TB1WLBmgg3msD/Ck88LC9alB3pfNKTS5ZSwr1adjXuTbNj9Snji485dufk8EFpAII0tN4dt825kR 9Y6fkWuf5O0n9ZiRWySN5gXmja69JS8yE8n1fSGNJ1uhzoEJZWoZD6FrXXzlefy7b/ffvz98vWHF 0kQN+y7E2NSTU4RI5842UoAoRjb7Lgv8FWsdRxndcBi7hVS2WdveofOF4TYsA1Leyjpi2HcrXs8c xv2ajX3DvVa01ljxUmH89IxPn/2tfJXlKw6SHEGbYRhv1+N/puvr4ghZ3FBXkO16Rxkdljm3OK9U Iq9Xeq6o93lyWumRNYv5DDDc/ebzYRsFXThoXVY2SWRyKOYAs28H5w8rpTa5IzMmO8y73vkmR2A+ NUzPIHGu4bIsZxJHB5J0isvYTx0Qp/X2qEiX6Ua7OpK7Cs/ilFspCmS1riB5x+FM6q6zxEzkVzUZ 2RwU4cK2DXsyjui8yLCaMP6qfy9DnHIsWb8yO85JavRFZIAB5+nY0ToqR7Bz/BV+YezNuEzHXXLQ mi5Pe9fxVIdw+clRatVYbsgw6sNf3++fvyqmWJ5v2vh+FBmLlVaNup6dQVClyvLDlzNLKz6jO8ZZ z+5XuYP22URXYxdqEDEy4ETdRX44KNS+yRMnsvXiwbjaqONKcMdV2o6v1LtUb1OtRR1Lk2TbNLQj m1b2LgDH2BVpvLF8R6kZvwiiEIvG3XiuRoxCP/B1Acu0O6NYhv4D5V6vTZv4vW/QkbkoKJzI6BfO Gz9x/WizMl36pgt8xza2CONHwaAMUEbe2GpT9Z/KIQpU7LnwLNdSqOcycm3pti7R64tby+poAH3N Djx9trj2xlaHKZ9Etj6JEtc1HWzzUZ93tSH0Hpc7IF49MiInT//yEsocHEGvFqvu6fH1/cf9k6qg KiJlv4clBh9sMWeY3B5VuaK/DkbmNn9ztsUxebYxtIG2f7d/+c/jdH2A8DmCj7g7/Jh2jhfRu7kL SNEkiETsc6kUamIZrq5eAN0+F2tOlFusT/d0/z9i5DRIZ7q0cMjE9xsXesdjCKhkrLblmxiRUheR xd4b2SrvldJgmxp3cnKBMSfn2seRsfyuZUzVpfVFGUPLNhlDiSYR4YsBakVGGBlLF0ZUTAepzpnl 0clGmR0S42gaL8IWHONjYARvw5vgnI9P2Bd3JOBwLulL9zgAxVeeJ4IQwVRh4IvueddjUGiNl5VZ C0oXhvGbAnqMzHQ6lp34IN8Mlx1yFSY+HRBvC3ygKm+kKHszYn6kfl9jnNOsGc95Z3gNjPhiF+ct fx9rpRDiB+yRta6RwoHMODlBqrAfLyQi8eoH+2elbFqZtJSy8gg7VJO3+IxC4wSRDbv6cBkey2d4 VXYik8kCP8L3SVcgt+4qm7/fsYo4VlG+ilg80ldByZV8GAAG9Hp5b/P29lzX6SoorWdxbwBMl6NW 0wCNMnAoyATAixGXLpsCkL4/PKFf4+s3KUAmfwM7Ab0hr3rXswYCc3lqehV3CSJKZcWfi3t9uf/6 5eUbmclU+MlGtNoCaG6ququQztCt8xNuptIY4mOvFBrDYeNVkJXcrqfHNdP7b28/nv9Y6wYTZIr3 n6d5DLn98Xq/WmJ2+xYKzcpMS4blgu5qSzOYa8GmjMV4Jyu/WipWrE+gMUJf0ENjSsWIEYVGS07A edGdAlBdRPdM0WIYLoyqPsd39ZFecRcUj8XFQruMWYUrFhULeYHXTVYx12NI+J+WxmYmbKKQh5Z5 cOMLo/PH0wQ/379/+fPryx83zevD++O3h5cf7zf7F2id5xdFe57TuqSBa4imgy8Jml6ExXe7xQa9 TL0UdvhDedyR8b4kMeY7H8D41zGB+wEMnZe0gZxrc3mYJqt2jr0tE7KmfMO5nvUU+3AV8znPW1QF V0HzznwdtVyuHa7kGXflxgmsK6B+Y7eAsz6A6+JycyVPbvv01vphvrlKNfeuP6e9ZV8pyxRqYS2T 9Cx29fIlv4G6njq7mLeKaKrBs2CrdWVAspgt6yBQkGC+r2Payu8D+0puoCgNV9KZw+ettNpkdCG7 putLDIwy4L3T9Yy4TfgaJnTWy4LvaYh9JZaFG7+cK3mAggoCITUEySiH8Fg0Kn9u86w/kgOorAeM X2lKtevxOOVK1dmiuwphPr+mPPi12/2w3a4nwnFXILBm99ntlZE8RwBah00HTVcGM/cuNlZu5ref YxNkOhldzWZxHlkvTJ/a9lWJhvrGKmI+wbjS1l3i2u61FQAfgTQ2DrcpG9n4NC+b4GY+XpBY47ND 4DVAaLnRypzaN2liHrgN1k6r3mUdHmPHRq441Y9lsSYlum47NnXX5aCOSdKqo86goQKxCBfIknqD MP5uh+GsmyGm98bLvKHPKkXQvoyTMSnpDboEpA2SHIKuEVIQv99/PH9hrwMb3+3cpUpkSaTESR9t PF/ySkA6uyQMRYhTyqDKvuzc0JYM4TNV9v+ZV0p27XI6d5GLEPdOFFqaUs54oGuMx45+goADMDoI xmJI6lL/GpmHIjFWAhrT31hy+FVGR7XWLs8nevhi2kPjWIMhvCQCVJecC41FdPxG0JWInqzH0IFH PpFSubJ7z0I2uNkufMNFhwuftrXzTs4Tg+sV9jIq4C51nrhwfUdul2l7oMTJETimMG0LxFxZvh1Y Z9OVmdi24aYHsvG0+XbrbtwVCHP25TdyjKA9rL14S7Ub94YI4myYJDbTu0y3xUXMWouVjWPyTGTs AYrbKjNfQTg+KG5rEP66nXZTSUeoV7knlu8P5mtOhx7fqDSOQmRD/U0nm5hD/qkLyDNvZE4nttIQ jaKmjMQgwheiTyADa1Cn/mB7fhiqA3xWYI1SZDnc1ahRQFE3rpZxGEaeTo02Vqg2PCM7JnHDuMyP USNGWr36wA2MteL+kHLp5933JfnsMwvv2sgZJhNJyq7qh8w00FCFl/Nqkp0Ps15ok5kCS5QUeW+h G526WHql0QGKLabU9T6xgL0XubZcy7b3LfGWOaPxA3217u1tZFGnXIzHt4xyOl2WqI87IzX3wmCY GXIFCEcBkV36lq0khiTF1ZPRb+8imAeOWocucVBhNc74eDv4lmUOVMbSgH0pdbIz6TMYxbAVo5Uz +uwNJdB6DKjhuiCA+i7B8SDVbPHckPJG1w3SRWdKsCiP6idNXJSG25XoHmFbPiWfmOeEJfvJcJrh IiorAAMYvLcugBWVYPLzoN225zpCG5DrvsDn7i16whFB5W4jejE2tkmuCG4l1GeaHkFBCCUMeCD6 yTj+s51E16xnTnxMcynMIDACy7syls+F7YSuKYYhG3Gl66sCYnLXUQqiONWwj2efck1lbvPPuPFb Ux9mDB2PhpW+jDxLUfMnhx0lv8mqau6XCUCohsjBZ7RWSgqQjeEmMRcYZy8yPCfFhGd9KLnL14pw n0GgphqF8JKOo4zziTPZ0DWxy4I9FQ07B1gTe4BiGLOC2fUoWmmfiimRnWnqTl6XcslhI+4EFk2c NjhSBreHOI07UE/pEG18L4ph0FHMG5dyZg5jilgkjy58t6MYS9sauQYhd1FXHleGGGPPA0yM327a U4tGqj2et5NuVIm2yiKlqvt8p9wbY8Y3xkV3DvqVdY6Z+PrHEwNf1OzJsFYzbJu2JxZrvsuKLFmO lNh9lLme+BqtaDngxYtLtkddSiBx4youapBtJxMATYc9PqNlRMCOA30SaWaXtibW7JJv4mMwKqnh xCs4cpWFpvjy8ko8InzK06xmr91/U1qnrvq2LqQXetLT9mLUkDKVEp+89r4+vHjF4/OPv25evuOg e1NzPXmF4C95ockPRAh07OwMOlsMUsnZcXpaTEiC8RJZu3zIQBnPq7rFhyz2GXW7hiVfZqUDP3Jr MM7uXNVpphD5Q72S66BeZakDlti2WoOobY5NrXa7wG2zT0ccBLwleMyqp4f7twesF+v9P+/fWSCo BxY+6qtehPbhf/94eHu/ifmalw1N1oLErWBIi6fWxqIzUPr4x+P7/dNNf9KrhIMFH8wCKdnADO7+ aQcia4qAxjumk8cYf6gClHr0+4GlHSN/iMfeiDkWmdDjU2mJ8ojCQLUg8gm6FPBvmY7bB3E94JHM J9pFYC5Y0ueQs/ss9kPRI3f6Ko7D0AoOenp9toPdMG3k4QiuT9FGe6+YQHk3G1/JQY/zY3vcOYpU v9CJGcroMEvqpqM4ackHqvi2vZBeGRegqZGTvm+k0yisxCIIV+rgFZd5y1G6CMD3XfYtiLkTbb3n qKQ23IzhbPQZawwXzRZENP7WGG66cMxyLPVR3Kmh9QsFVqbULY8ZNMs19hhYEcu31GYQO3rLHNrE xEHTW6Rj5zfj/sPIK1UVoaUh9upUxsEZs7KMm3atG+b0Jjulyf44gWEbt03zbjVBwBxOa2MDEWlW GB4W55j5+G+XNrTWKsN+W+33JbFkreAz6tStZzn7GbaGsJ4cBnU8NfQGDwXyByYr6jwqTJ+tzGER uJRjLU53pv4Yvz7l5JN4MxP+18c+I6O6uv4hW85AOej+GXgqG2aYJtVykCiZIOywlZTCCxz4qD9J 1z+kRUtYx+6fvzw+Pd2//k2ciXHdtcegfLNmEP/4+vgCauGXF7xT8Y+b768vXx7e3jDuJYaT/Pb4 l5TE1Nknvs1X6tSncei5mtYG5E0kPj03kbM48Gw/0VuccQxREqa53jWuZ7h+N8nrznUNkRBngO96 lOn3wi5cJ9ZKXZxcx4rzxHG3Ku+YxrbrOXqFYGMehua8kO1uiJHXOGFXNtRGdZIsdXU3bvvdCCBx cHysU3mAtLRbgKIv3Swt40C5i3cJACN+edHqV1IDPTy0I8qaJfJdtVmR7EUDRQ7EawcSGScssQ8I I08bnxN5+kIp8xZDJqwMI+D7VCyEhRsEan63nQXamUotiyiAkgcaA/VA29amDycPxOxBq5gphMw8 fxvf9szjivHlK3YLI7QMYcgnxNmJLM+c8nmzsVwiYaTTBtsLgDSEzlNlcB1HaySQyRuHHRwJAxSn wL00Q1T5xto2JNo2GRw/UmOkiRs8ckY8PK9k44R6NoxhONEWpkp4ZSqFvp40MtzVwcEQhqh7F4Rv U/bhmb9xo40mHuPbKLK1adwfusixLG2rfGk1oSUfv4Eo+58HdDK/wYfztCY9NmngWa4d6zXnLPWC qJSlnvxljfyVQ768AAZkKdrJyBKgyAx959BpAtmYAveOT9ub9x/PsIlWkkW9CMaxM3fn7Cqv4LkK 8Pj25QFW/+eHlx9vN38+PH3X01uaPXQtTdaWvhNutGmkGDhntZa9/5Oq4mBWUMxF4SvD/beH13v4 5hnWJeGpW3nINH1eoc2rUIuUJB1FPuS+rwlc9Ie0Iopqa8sHo24oqk+mEJIpEE1Y4gVbvRWR7prl JWMT0xjpvlmjALZnE4pIfbKc2BD4Y0Y4gWeWK8j2iWogfWVlZ2yiGkAPV3PzA11xZFSfpGqLZ30K JHeCCzYkljdGN7cqsjdExqHj2wQ1dIgVBOjr7RsaSqbG5lTYUeQH1Gew/K0t1wBYL84moPQAoIcr o7Y+2W7kR/p3py4IHPN3Zb8pLcvWv2MMl3K0u/BtW+sEIDewGJDp9ZZlXsGQb9uapgjkk0Vmc7L0 fQ+SiUJ1reVaTeJqo7Kq68qyZ5ZaYr+sC6Odjis6oT1ifCol2TaNk9IhkuQMcyO0v/lepRffvw1i bVvEqIReB3QvS/YrWxj/1t/GOzU9EO8qKeuj7FaTwZ2fhG7piisjvbKwRacAmr4vnrUWP9I1yPg2 dCk9Kj1vQsPzLRdAQB2RLuzICseT/HiCVD5W4t3T/dufxuUxbezA1xZxPCsPtJoANfACMTc57SV6 xJrasO9smMGSHqJ+IdgikBfz9x6FlJIhdaLI4k+dtIRVQ/pMOd06VuzMiasQP97eX749/p8HNOkz XUgzdjA8PjHaiH7PIq+HTXvkSC5nMjfC1dz0aeSEw1q6oW3kbqIoNDDZgYDpS8Y0fFl2uSX5Jom8 3lFdfxWuIWiqBjP4j8owJ6C2xQrIdg2F/dTblm3okyFxLCeiG2BIfMsydNeQeEZeORTwoS89WKPz Q/NR9QRLPK+LLNeQCWrxgW/qAj5iDI80iMBdAp1scG5QYQZXYBV2vUun0l1PL8NW/kCuoFCTjk1i g0VR2wWQnH7Kzct0jDeWZZgoXe7YfkgPobzf2O5A81pYBQiXg2UcuJbdUtZnafiWdmpDu3qOKSGG 2ELVlDVkXsMI0SbKvLeHm/S0vdm9vjy/wyfLfXfmyPH2fv/89f71681Pb/fvsAd7fH/4+eZ3ATqV Bw3LXb+1oo2w4ZmIgS16/3LiydpYf4kVWsikZWbiBrYNX33TvgI6pXuwk2GYbcMgW8BhLKSda7Mt K1XVL+wlpP91A4sG7K7fXx/vn4yVTtvhVk59ltaJk6ZKtXN1zrLSVFHkhfRkuPD18L3A+6X7SL8k g+PZtiWXkhEdV2mY3rUdmfS5gN5zA4q4kYmdf7A9WTmcO9UhHTzn4WHJodWWjzab9ZFAjSlL64vI ily9gywrCnSoE9hq8U9ZZw8GExb7bBICqa2IKg3Du0EvC+Q6qLmCNMJZY0iPpxTI9efEkOpltaVg GMqrN8uyg6XQlCNMF0udxBjUMrYDreisdUObHK/9zU8fmVRdAwrNoFXFCdX+5URHqR8ORFcZxzBP U5lSwB4/sqmh4Wn9UQ19YFqKponjm2cwThfXp7w2WMnyLTZuuVUKPJGVcz0gh0hWSzjR6VPaCbBZ GaK84pFchni3sdQRmyWkOHeDUC0SU84di/a/XACeTXrdIb/tCydyNYnCydQOfhGySj0+pzYsteju U6fqrGEbiHkbgGM0mRYA4+hEkRDpgo43oSFaqwAwyxIu9UJt5sR9B4WqXl7f/7yJYUP6+OX++dfb l9eH++eb/jKdfk3YupX2J2PRYRw7lqUN77r1bce4hCLXdpVJtk1gZ6jK4GKf9q4r+jIJVJ+kBrFK hu5TxxdOaEtZbuJj5DtKoThtnM+3dc7Jo+KdLHnItzIn9SGQ7/PxQEFd+nFhtnFsbQ5HxKLHBKpj 6Q9Xstzkpf6//p+K0Cd4F1CRiEyv8JjqKvnYCQnevDw//T3pjL82RSGnym3mxGoI9YMVYH01ZJjN MvG6LJmd/2Yrws3vL69cydE0Lncz3P2mSPNqe3DUIYa0jYZrHG2VZ1SzAM87WCwsypq7cB1lJeFE VxmfkbNxtbz3XbQvTIkzrqrAxv0WdFhXG0EgYYLA/8tUzsHxLf+krOK4L3IsSxNnKPtd05p1qNtj 5ypTN+6SuncyNaFDVmRVpg3q5OXbt5dnFgfr9ff7Lw83P2WVbzmO/bPoBaoZ2GahbW1U9bNxRA9N 0+aGR616eXl6w2dMYag9PL18v3l++I9RwT+W5d24y3Tbku4ewxLfv95///Pxyxv1gDD69uXN8WS8 n5KKES7hD3YuNqbbnKKKj+4iNW1Azg3j9ijZHgQOPqqrPEIsw9i7AV1W7NB9iC7eeFt22KcNeyKX +BzyKrt+7OumLur93dhm5DsD+MGOuVkvkffk2nBmfcpa7ssJa6ecHQcUWcyeqO1YHFBDRkUdpyNs mdNxl7flORavHE3tIzl5IG2flSMLYsDr+rfaBiYeftcd0A+S4nbJIVuenMabFdPZ9A0IO8VaKlUW nYKTA6h4lClsBnR5IcXjnenV0DAz4UZ0fdGYvnRyvlY2rpW0pWBMlgp7SIuEdtpkgzcuYPDmXUO/ E8Taty6zNJaOvYXc5ORuyy2VmoQ57Q2vGDAm9KaRqb84JTC5B+EZ6lsqE5RxilPayWQeBnjcN0eZ 3sRVtkQhTB/fvj/d/33T3D8/PInSaAaO8bYf7yxQtAYrCGMiKQxwNaLrH8yrIiMB3bEbP1sWTNTS b/yxgh2MvwnUKc3B2zobDzneV3bCjbljL+D+ZFv2+ViOVWEarxyc4lPfJVVAvfE4PSvyNB5vU9fv bfEW3wWxy/Ihr8ZbKAIIXGcbSxtEEXaHkUN3d6CrOF6aO0HsWikFzYscfZ/zYuM6ZFoLIN+4nk03 ooCJIptyARWwVVUXILCz36CXK7KHZ0hjhZvPCQn5Lc3HoofalZnlq0v8gprul/Wd5ZMq2wWYV/tp okH7W5swtTyy57I4xZoW/S0keXBtLzhfwUHpDilsqjZ0EWdP6yLdWOQRs5AooLaw2/5kOXRaCNh7 fkiqNguqwgtnRQQ74kNhGzq0qk/MJZ5NHdpsSWGDIHTI7hIwsO0OKEgZV30+jGUR7yw/PGeis8AF VRd5mQ0jyGD8tTrCbKjpKtRt3mV9lhzGuse7gRsqVr4A71L8gYnVO34Ujr7bk3MU/o27usqT8XQa bGtnuV4lGQ0WpPi6Tl8fk0OXtFlW0dC7NAeR0pZBaG/IiguQyRFMh9TVth7bLcyK1DXMiHm4pdvQ c9f7dblTEKR2kF5Jrwsy92B4rJREB+5v1kCGtjfAy+slQJDhArIZj6om0ZgCLIpia4Q/Pd/JdhbZ OyI6jq+VtN5BOlcaP8tv69Fzz6edvSdzBH23GYtPMGBbuxsMxeKgzvLc3i4yAyjvYeTA1Ov6MPwI hFyZJEi0OZEYdMSOk8FzvPi2MTTShPEDP7416bwc2qfoaA6j/dwdXHJG9A361VtO1IMgIGvGEM2e m9yJ4vTtsbibNIhwPH8a9uti5JR3oO3XA87TjSOdGC2Yc55meFekG88YRJ8sF8i1JoOxMjSN5fuJ E0reBIoaJX6+bfN0r2wBJuVl5kia2GWTun19/PrHg6KUJWnV6VMES19X2ZgnVeDYtsqEgYAXr1Gn d121XZO27kZYguJqCAP68AR3LdNiDCRYr/q6lfMoIAeUhkUfbWxna2JuArVwMu84JGrxQJGBnyCw SZcflgRob6N6LQV1/2wf827t+rQZMN7SPhu3kW/BnninqAnVubjsdJUi4K6l6SvXI0Pl8A5t4zQb my4KdKVtYXnKnIAtFPzk8I3GyDeWM+hEx/XUwnEnkWkwGYrXH/IKg5wngQuNZYMGKifd190h38aT D36gaTMKn/KEI2DhaibRGjf0FS6s2LvGsy2N3FWBD10WuUaOts/AxJrUdjqLDNmGEH5RHoQnTIrA 9Xw1CZEfRuRjbBIs1YSrlEJABnOaN82T37q+m54YujmBCYnykDaR7ym6ncQafwsdWzVPLFtM2d7C yeqFMk0C6uJLmc7VPgNlzbxBdqn4RWx33FfxKVfWsYlIvYfARMDQ7ehnxlgftEmzPxqy4/MqbaXT rz6v7pjRYYhcP6R3pzMGN18O2bEiQtnCiSwvovazM6LMYRl1P/WX9pg5bdbE3GKmMEAT8MVwZAI9 dH3NxNYUtsFdh82iU+aYTilRKMMW3tzwPCTsfkcHbGHVS1LDtUw2g9POZCcpUOrfUestbEAwFAC7 f//pmLe33Wwb273ef3u4+deP339/eJ2iqwvL7m47JmUKmxthpgCNxQi5E0nC75Plj9kBpa8S+Nnl RdHysB4yI6mbO/gq1hjQmPtsC5t6idPddXRayCDTQoaY1tKqWKq6zfJ9NWZVmsfUkzRzjnXTSYmm 2Q52VdCfYhgxoOOrRkW+P6gZlbBUT/ZKqhMBgYYkLCEM0CV+qtRHf96/fv3P/esD9Y4CNhnxPKnI z0sjC2SCiQW/YawKE7szvIkIrOMp6+jZAMz9lh7owGpOLXX0DBx8rQDN+p3Stp2dssiSxuphsFUT 81yCbkRf38LCDLEd0F5++K1tEAZYqAP0+Rb6dFSDvIqovjTE7sMUXONnLIYd3Uj5thz3Q+/58vkn tnldpLu8O5gSTWN6Ud9tmVn1KK80OKYz3G3VpbErt20dp90hM7wThRVhC45h3nXoVRAqmWLke4Nj Y9mMegCA2X+aknb8NZj7L/9+evzjz/eb/7pBq/oUdoc4XEJ7T1LEXYd3x/OEKvYy/SXgRUJc+Ld9 6oju4BfOEj5tyfjCa860mf2C4GFpV4vGI7fDOi827YXNYz6uprBETNM4l/crKVYUBWZWaFEJLjFL ic+WYJlUkjx2M92M6F/vWtQmWsFsqCIVoEf6dIHiKq3bmGJR4SWF0rKQ1avlYRErqeFygvYOi4ZO eJsGthWuJgzSf0iqikx7GiPzU0XrU2X+nl0/EBe8SyMyLVsoKGwHanK+aoe8cwpdfaykgdtVlPJ8 7EBUHJJ8xBUVhDBf4MXvEEEENRPECRmVLSvxublbcVzNNH4+qx3E83d2u/fHL/+m4jxM3x6rLt5l +KresRSvP3RNW4/bomZZLsSFouVweHl7v0kuB/zagzlVdsZ+FToF/+LySuqahTru4N8D0RgCpDwW PX+AQUkX9ugwkqoMMIczHpDDXiid9Rt8nkhrEvaZMO3lEsWVazn+htYsOAJUXsoLiTPPDnrcfZPL mJSBKwZAvFB9lcpj/Cq01rLQucnT2i8rbJidrsm1kWH6Y9vmHSxsVU5JJIZha4KlNQYjU8L+wlXr yq4WOQRx4+iNjdGQDf50jM8euTEoXrxl6m1cwIpzNOh7IqiNP5kxxiDHvPwY+Za+4bXwDf6jE9+3 1qoBfH/AAMRlaXi/cILhAmfqDvbmtK838kS/UkVEBWQMW8aeg5HCVu+oT2NdKVD5ie14nRVRO3ee /blUJ3bqRJY2kHrX37ha/pNWYEq86hwl8Srrh22+V6h9EmM0Ya0F+yLxNzapvPJhTLxDPTMwbPja BPL/0mpT9w55cMKT1IOFM3reufaucO3NoDTZxHCYD5oiFZmL3r+eHp///ZP98w2sWDftfnszPer2 A59Wvum+P3xBT8JDvojSm5/gD2b/3Jc/K3J1i++ollpD8GDT5gFSFkObUW+bMC4+/KnUCi8Mbu/6 TO8rFnH66lTKG8PDBbxj9qW2zPIbkhgwpH95/fKnsrYsDdu/Pv7xh77e9LBM7ZU4VCJj1CLdUqAa 1rlD3RsTKXtKV5Eghyxu+20W93rLTYhFPbuWVNIc1Qk0ceKkz095f6d02syWg6NLrPkNWuZMxhr1 8fs7ukW//d/KrmS5cZxJv4qjTv9E9KJd8qEPEEhJLHEzScmyLwy3S1WlaG/hZaZrnn4yAZDEkqA8 h662kB+xI5EAcrl4lz3bTc30+P799PCOWk3PT99PPy7+gwPwfvf64/huz8u2mwuWlnhl5W2+9PZ6 ru0giUfcOw7AXiw1PTqPqgqL1FsT4VjrXCaV3suM8xAD+6Cqyk2rmvtyvPvn4wU76e35AcTpl+Px /qcRapNGNLlisDM0Jv+lJzjyHCZueJXBUicXFtKBVoHU7KU7Aq5Zg3q7S6NKuEbTOw2p6d5SHpQe rSooq7k8Ny608JsorVYyBqW3QgICEjIlqrd0dAP7i0qtd1EotCNNMvohVm1otQixpq7bUQV2z6gG hSKw5XJ6G5Zjt2S2DLPbS7v/JOUAefkHByAqbG0vJijxWuUsZE7LUxpkNqdEzwawuUkW09nYbToG zbs0laU0Esb+6C1YRfX4BIba1zWEFaekoRTllI/nI5cQlfFwpHv3Ngkj7yejGdXWA1Aocauh53y1 mI6I/hOEAdWzgjL2UmZjmx+0pAXp8rbpq8mwWtDjJSi++ITNnJQe6N1KLa/Goy2x9GR4AoLQhF5w x0yFHyGqiKTZkLJ0bBAlnJIuB8zNdZWMh1Q9CliG+quslj7VDd50/GjqpocJHGXnBH4/HlD9helj YpYV+8ViQDa+nFLKKy01AD6waLehPOrncjjYl9R6xvSJ2wzBZ4jqivQpVV2kTPpmogDMqVmMFE+Q EIPvDKnnxbYjLw3Vo278JvS4IqeYEAxBcriRS4C1NjKMgtsveD6/tKaIeO1OA+X/vx0jlHDP7khB Ced2bwV8c+6Sj6i+LQ5oDexs3vnD3TucTx7P1WQ4WpAMECi0ZzodMCV5Fm4+i2m9YkkU00rpGnI+ 6dumAtR+mhCzVAaDc9LLajucV2xBs8NFRb5f64AxwQkwfXpJpJfJbDQhxnF5NVlQa6vIp3wwpLoM x7d/fcgrhF6IjIXUx1LykBXktLMu6hvK7U16leTN/H5++h0OLdaEcuUgGTO6f9xlZON+TBMzthe1 KuN6VSU1i5knQn07Wuh5+zyi3guxtweGb1z94+B5Gmx3FhFCuheyLybDM5Au7PZZGEbd7pkW6zAN C/M81tajAmGmvwARIesc4tCPSGijrLYNIl75eNE3t1VMcHd2ryr4azAkJSSM/NUr5LGc+uzr7WRu +y61IHHuv3vVMHix1IvpiRDXHYbWBX3h3nbvoX9CAr3ee6IgND2V7v3nPJGHCGvdD6lG82Eft2/D +xGfzmceC9VWYl9bdpY2852Pad4r4iD1Zi1eFXoRKg50/ywWKkbORo1Xg6X0sNa7VTcKApoeEYZ/ xRfskkprw3a4lL0RBhgIroYRBpgI07WhYYRpStdAPBWlYWyWXGer7jfDgEIMNsl1YMZGZocIwd6w yHW5xKA+kcfSCorB9bfwKHoBuWTD4aGHbDOshnbdVk2fgpJbYzKtJgEbUOgjRsm6TgJuf9xQhQp0 BMSZoUOr0rO8Zr6Mt2NvhRK+8lcIJLJlyHYVPvV6RqCFHPyQJK9zbxEJGlT6iLBOPTs6Ro/1fZYu 85UaG5IuQ5mdpSY7eoVKQOL9HuO3e4nykc0/owV7Hg1qli+9mUjMcOAf8CpK/J+3seoTby1aiH9U BQP1lnGI4ig9KImwDvzDX23rTdlH5Vc+qlB9gS4g1oogbXCt1Mk60XQLO4KhaXvtDEgzXisxdTVZ V0XvkDk0qA3+DuslK82g8DKd5vPCHNbXu00xqNjgB936ql1FYlFb7DbRY9xWkQwLVGQlcFAjUJzk KLHV7y335w+n49O7Ic2LqFt15fC9rnR1B+vsF4J1a3vLcrdyo1aJ3FeR7kqyvBaphhKI+tzDyYEE Ysc+VHqvfTDf1bgiNzb/pdEgpGxClhsX9c0XePEtHnQ9xtPa5+Li3rbAbpTUzQ7SBmB36DPr3nle o/cr8tEDt+3aiYci7bHt3/hIutObrJL3QU5NBUVdopsC3YlBk1lihjdpExsN5tqRYRRI7NUbhmq8 0EUr/RETq6Lh4Zf1yrnfZGUFW2gVL/WdVSZj+5x1kJzuX5/fnr+/X2x+vRxff99f/BCB23RNw9Yh ez+0qcS6CG+kNwqVwNGuX/NaIX/bglqbKt/yxGyLbjFe/F+jwWTRA0vYQUdqDiMUOIlKXvsDBymU Fs7MqVXO4/lwSCaPDAUbnUBdumh03TCvS17ovvj05BmdvCAyScayVmY6S/IYuiHK4OyMjXU+lAA4 wY1n/fTZmKTD9F3ovtr05JGDDhgfjIiuC1g5nCXUFVwHGCxUBciPez9dmI882ncLUn+iA8wmVCuq 0WLgTgxM1g2F9GR3ZETylE6ek5mMDi46AWmOVQ58FU+Hbr0ZhiaMsuGoXhDdgdQoKrJ6SIdUaVYM TrZoNNjS27pC8dkBL7Uo/tysz5zPdEu4phbBlWHBqJJToFQ1yI1TdwEpWka0SZB8mu0WZjijT2Ed LGbLnOMk7MPBSmS9GQEgYOTdQAcwNpIueUckC33Hq7GTXk5HFPdIeNRxPPsbvpSLqeYuTa5AXtK9 HLCreo7B52kRwQQiO5pYUE9nExVJkbdnFOVqx4SHAygjp+iL0dRdh5DorkJMhLM1wam28v9xtPTX Xme6fQyX7mOqwaIzKEJFzAhILrKdst4xSVLwI1Pr8MBMh+cGVWWqyy4gEa5lIdrpUiRJp8WO3MGe vr0+n77p8kWTZOVZLzNWaKZb67Je5Wu2zDKN18E5D6TNMtfv+aU2V83jbX2I4QwHf1zfFqYRWLWy baIgpWbrZDiaTbbAO4mRVaBlMJuNJ3r4FkVAk8TJYJnShHlApk/HnvS5U2Fhkjicjcn0sW7mYKRP 6fTJgM5nMiTxk8WQ6DDCSNKG5DxYTCeUwbICFGyxmE+JzMtZgEFn+jJHRxxDjxPOBhLmwAYp3YYG sBkOBzOnM9DgZ7S4dDpDGgJNSfx4YLwt6pRxfyURMvUYUQmAMhB1SrVdS6h0NCyNeUD0ahVj2Cxa nUZBdnw489iddoi5z+ZL0PMAspgPJk6Fr4UaW1YZy0+dHGpc20VGv2s1mMawkyi8gUiTx0cnOTNC AXfJWY5ajD0ZFuzazW4fLQsm3TC4DRG+AAL0VNfbGFbwDWm5xRNpuNLGRe8II2AO9Z5vIlpBXcUP lDgSkUcT0tXjIYrxRhi7eKXbkUZhHGBlDc21TYLWD9iIsjYOfUjIi2wFR11D767X4A8dZCRhG8WV FiCSMI4ZOhJpYCQqi0FkOGRDMhzThu1D3A+0dqgUqHMIu0hIbSOWCNBsLu4TtbxRenhubWuEyjS+ 1BbH78fX49P98eLb8e3048m4fIo46X4RyyjzxVCaTjaeLj+Xu1bhWFxQbsnOipMtHJw9z0FaUxsF NVre0VCwG0w93bWJZtMpfSGtoUqe0G+nBiY/j4mmsJX11xcx06ElzGrEIbVrmZCJeXrRKHP7uNnQ lslw4XnN0VA84OGcdP9ogS5HU1L04cLPa81zTzWEJkEcHsrzfYnQkp2FrcMkSs+i3GdBovtGSV4O fSODLyPw/3VIqzcg5CorPOwRqXE5HIwWIjogHFDPVdh5aKVAccY3KVszSilfg6HhCt2o7JAyz2Go gey5b2klST5yFcDJyRfMh7RhtT7e0QH2LnEA/WX2HKrqZ6nnfIfZs2jL4rqihQeBgI1pPhzWwZ5+ YW4wvs1L0euZT6VEB9RrOAz2orZZ6jnJKwC/Wae7ngYDZFN4+Keip54w8B29//uSfkBEsuZQ79zI byLgdTO+H3v0W2woHbvYQvlMH03YzKMeZaHmn0HNLxd871MCMnebkU/FLCxDOGRFJd1nZbVbnstC w3ymdcusrDzKWKiLAhDvCEfJYZHQkk5L9vNBQfbPPkE2+KQ0MXj6cXw63V+Uz/yNUn1THoRqvt71 6QbZsNGUNgWwcZ7+tGGe6WLDPFutDjvY0Vw8qIXHCqxBVXznjmXjYJnqU3KybEO0e/FsOehVS1jH 2QXRoqdwXV4d/8Fi9RHU945qZB3lfChPCC8DNZvPPHzbRM3PshdEXdLGFwbKqyhloz5R4mLo23VM 1OwT9VoM57StsoWy40rTqMtPtHExtW/tfWcGY1poM0e96MlzxePD8w+YsC9KsfpNv7L7DFzjcWXF MMQgHw/HdQJS17m25BF8ASfcs+IMakN4uZsYdb8kojQUzh4kpItSehtAZZjhQIP3wEafgk3G52Dy fLGK9n7JRuo/lBnHC1O6LNTxoQvSi0FNVu100STBXxnflhQlL1BiQZWzPuqil3ppeOVQJfLduZGq 8OXIO7vibasU5D8YrBNk9SRdKQTtz9dD6gyRqM01HLdS7DyixxMWxcvMCNWFESQSSKPvcdQ1SJ1s 6DpJPeJ6PAdJuLiuEn9WBdQIHXU6iCYnpdyI1dPOL1L68WcrJSg/XbW4tuNPdE3MYlasoiLEydzA SaTUpco5Gmv7VS3zgPtrI9Xi4HOPFiDqciXBVU8GOO1RA9QLwFXn/Vw0wS6+mQgwvXbw7157fZdp ymtMo4G0Pj5hyKgLQbzI734chUH0RUmEJ1F51vm6Yss4xPmyn1sMsfGAcyZbO1eh4+ExlUU1Lgnr n4t+CHT0dBD1AcaXwJX59TlIb0VwwHu+x7F0yNKQ+Pj4/H58eX2+Jw1HwiSrQttMuO1p4mOZ6cvj 2w9CXTqH+WaoeWOCiP1CTCNJTEv3AzH51uiPARO8n7YqVF19jXq1b3joGOkaFm5jtlw+fzx9uz69 HjXda0mAfvhP+evt/fh4kT1d8J+nl/9Cm/L703eYb4HpM6GRMkBuobpWWrRwlu49+7oCoHAQsnJX 0FuoRK0PyHSidEVLIRKUeEDN0yZRX9kQeQvmaYfyzok32bwq6A1Nw5RpltH7jQLlI3Y2o95muLXV vq8uh4I9ezTYW3q5Kpylsnx9vvt2//zo64nmvSPPrj37NuYsnCN57oMEvccQXWwLyZJsN1k7Ub30 kP+5ej0e3+7vgAtePb9GV74mXO0izpWyKLGugpwxFA3TMotDfWGdK0L6u/gjOfgKFmOCJ3yybc6X 8uh/yCf//uvLEakgS1wla3osFD3NQ7JIInORe/gk9pL49H6UVVp+nB7QZ0fLBly3XFEVaqpQ4qdo MCSgi9BYxatSJX++hC4IvTofkXxGiQLebSMI98wjhohdJV0VjK/oQwUC8iTi9XXhscJBRMlzn+8M JCeJQ9WjmdltE427+rh7gMnuXYtyiwjTqC5pvikB5ZK+VxPUOPZIV4IKewz9PiioZRLYe5MJuOZp WfoZnRIRC7JbyMaba6nvwNgKLeuC1t/WpJoABKCIvrMTbLLvwAl0j5Pb3WE6GBB8WIzg4fRwenKX tWo7RW29vXxqe9YkdgwMt18V4RXB68JDxTtfPeG/7/fPT0oe0Hb6Ni8Jd1yRmdSEHYaT6dyww+9I 4/GUvtHpIPP5gjTz7xDovaPjNSo9r9IpaiK6xcrJCktY6B/7cy6qxeVcD6uo0stkOjU1ZBUBbSn6 OwMQMEHg37EZsTYBmbOgVREiMj/Dwxr8kAYAZlKjx92NPST63Ru31Lri9FaMCNyOI1c4thDeZxsF 8Os+ID0sYs/6E+QeYQHpva6tEeDaO2tEZcBtd9smWu49R2CgRgnNDiTtQN9xKeKIvqtU1LryMFRB l2Y06x7EVTkbDfxD0fM6gORtGCZLj8UH0oUnRfp+VJI5PmbCXujvuj6jY0mHLaNXoQRRfmN6QcUd 3/H1bHweRBjsyw840NsK0sRxOUh8Lt8QItwxmooXIvngHxk9FFee0fu5wHFGy3qCqIy8qpw+IwuM 2vi8gL79TtD9d52CHI8WPI/ps4cAoBeIHmrR86lnr5U0nxl1S4XJ5Qfs0ok/c7+Nu6BGoc9AW5E3 hc83twBc+zk00Oo49HfJPsLXp55+cV0oyINFcSXCiWoGRs0GVFzh/NAtqetVpHmsREPugiFOn+Bf UTWuZlG/+SGwMI5f5h6G3+KgEr2A4pYN/ahmEorySERVThZoflPQhwb9CdGHaaqyWZT+cuDjzviV RYHH270ITVxclVXoOVYLQFr5TIhloFRRGkg7Szja0tmgjdwaL0pyvqlzz2BhAGGn0c2Z0Z437bTJ Gd/a0Y/LsIhg+kR5xitG6XDLt3/tkKhfhAkaqzaex0lFP5RDn987ARCXERNa/FAIvwCiAH2O83QE /uKMXs1KzcGn+ifJMMweB3eSLCSA9XUPZDsa9qlZxBjD0jefBUBu4j2IhG/yGlX8D32d2uPvpqNL JamaFX19m+bc41pHkPsfJyVGHjWz0nNY7DC5JxqHhJxT71Go2/UoRtE/39z4T78S61WvVGQnAoYN 6HlTVAjb+41BbfUXDK8ngtT7OmdC6nW866slvsCRZPVK12gAndPdaXC2HpD0OLa5uSg//n4TZ+Nu O1PehVD1W7Nd6RJVjDtJ7nZOIDTirIgWUHkEIsC1ExCRXpRfbVFME5ZK77Y8RDMwL049aTVV7sPh iwyePL0Yda0+HKH18tIjOzm4MZoa+huilvVh/VmYaAtiVQC4z37S23x1AY31pS+wRJ8LVcL+ekp9 P+/ANmdf0YFe64Imo7Ts7+i0HEn/DD4RGPMRb/Ks8kijDaJvJqo29bZbubOqq6wAMYfShtdRYvU8 UpQSuIMe8sSgsXifmSQ8jUslOGyBvSCT6BDGnxh99czd1wfqpfwcZH4Ogns+Clz91SkjETC8f/Tl zlzviwPahfeOjoIWIJx6s1ROy+ZTcQkV70C0LPpnqJCCzswtibH6RB+ifbjc1VAsNGFXmeFcdPpC xEvoqw4cluvRIk1AYoqoSzsDg72g72ANsW/wkiQfnwfYpZuIagtn7Z5GIGDneXZv6IfyXA4YF6cX 0IRp9W8HQlpDcTwI/bXJeBhn1TmUEMh7O04pTlxNBsNPAHGm+1eFgPjUdzpA78oSEBHRJ83LehUm VebzN2fAN6WYXZ/I199bTV8sBrND/2wT2nHYG15IwYQ+QF8uwgkQSBrj/q2/ff0IxC+PtzIDKRhY 70w0obyMepm0iQ4+i+7liy2qusntqKwaTB2Wg1wa553DidX1KWRv5ZrY6n38oMX0TedW6v40yj8R WlRv1bsLjE3P9Cwrebc3HA8H2Gl94mkLnZyHRpvJYN476+Xtnjxx+YddXOINLyd1PvJcjwJIxDns LYwls+nkHJMUYYTr6+iWRIgrZHXp4d2T4WiWR3noHzt5GaDu7OvQCknWA+1rXfvGIMQa/4zvcL0F G27byAsl89jW7u6oX8J192JBlRuvNInn0aowX4QdJweNeJQGRWZryHgcIARMU20QsSqsn+1rXJu9 TBaXdhG9gXSIjGcVvb9Je4k6XO08L/wyk+agGqIWW19pDdBXnkShJ0R/nVDeOFehFGdHGmTeguSm vbKra/YpvtiWATMs9FoO769CC+lvJZ6C/K1UVRB8BU2h6V5t+eK5DtmvZsATezq1UV47lxH6wYVh XNtaEwokXXD35CK0JB2yUUQh57fdXXiqTPcFc+O0bK4v3l/v7k9PP6i4qNCHZE0kA6k25AoksmzN 3/O14QMGf9fJuui9CrNBNTMvSRumINWq8wIktlqY+j96SeKRUvPz0JTQAEvlmt+tAzLD2q6qDVKM E/N4JPKIeAg7p2UrbIMSxjeHbKQy0anSH4LjLHdVhOFt2FC1clVtcgzxxLNdHpNPnyLrIlxHuh++ bGWlm40JVp7gy3pvJbnTXy4QvSfhU5WnY0uzI+FIjrEuMc5PmnkCqyMoYeLg7FHz0BCbneYhS0uX upomqQT2Z6UsQ+HlwUjMuOEJuAqpRSt8TcGAHMTjiVSX+3h4P708HP89vhIxRXeHmgXr+eVIu5ZR ieVwovs6wlQV7avjVJCWON67Gl02omCNE0SkLUMZR4n9bARJco+wr8815lHA36mM824wlSbdG9Pc AIlSshL2RlrQMsDE07iCwaJAoGYMgD+LXV7V3AxXJvcUoT2AJJpLq9fqfhT6ZL0KKQfyGJHgascC WKyG1lHEYXMU5yO+rEG6qrwa15ltANL4CzWVw2RsvRNGHRPymzbP9nBYDVgVwkyuc1aUoe4sp0RN fV26Cw/VCJIN3StMqA+sqgoHB/JhGcGU5bFLKkO+K2QEtY4ytjMf+3MZe3OZ1LrOlUrw5DKxcmn7 VtAch7AmuQuVRvkg+LoMNN+U+Mv24QlFJ0sO7D80H1QjGAagrchcBaHrpK9W0zqpVGuYJx9HFe2r 8lYbYTxjqvSDLF37BFOUMU29p/0jIeRql1UUwz/4qo8ET6QAJGWp8Apb8mJHHzAQdM0K+m3z0DSe qNF6VY6MCbSsCqfVTVpXdyKnFgQDzKV54dqcrC2i2OGVLsymm9bRnFWWr7qSykqYMhVZwyJc4abr c32cRrFsMMWgRk7DRRJOkdpzP6K+kRzBl6fsEL2T5WfCR22Ufg2FwwybWorL6AKjL1LE+DYjEwvd M1+XPnGaJZM9oRMbxG1Z0c8+AhBl2DdEs2+zNLRWLg6qfmT18ShcWuYgNGkygnid5Z6hiOIQXaxs I4+eGOQQpry4ybG3SblJzByTMbaJ3inZIZa7CMQemNrROmW4jekjXkqH3NrdQZug7esiSfhtpkpi 7ic+TiPSMWqouJ0VG/+K6aFgBIBXBhdiuypblRPfZJdk71KAWvtoGfRQzG4ssjyR3d3/NANprkqx SZBbvUJLePA7nIL/DPaB2O2dzT4qs0t8TzP2jyyOQoNz3ALMU+tdsHIa1NSDLlv6d8/KP1es+jM8 4L8gJ5G1WwmmoimwlfCdxX72K4fzaF83Xq45HBVyBmejyXiu9SIguh3bs6t7808ra/mKBGtDF2nF tZkwdj4bA5851AfBylystR82Il1fH0rNirfjx7fni+9U36JquNG5ImFr+8kTqahpUlH7maBiv4Lg Cd2YFVZ2ILPGQRFqrHkbFqleqqUOXyW5ObwioXdPlQhL3EzCZBXUvAhBkNW9euH/uh2sucl0u6nN Bx2fI9eUrviNqmUFS9ehTypjQVOOmWBMBrayQKHgvabM2yThZVPpeInd+LkNkPJ456nfst18OgEh pKSKjuwvye0FTYB0hYmOeywj/5e8YAlZ9RKOSOXGrHuTJrc4hzmSqCAqrGNoS8fbkiSHXSpde9S4 bKg4zvcVqePqHM6mehzvFmXN4zb9VoaCdosH+aSvVCkCuZ8d6AeOrjyfUNMiJsI6bymcaNye6aMw WYZwqKW81XVDUrB1EqaVHDyR6V/j9lB6cGYr+sg70HM7SyzOvMmdz6/Sw8S3doE2sxamSrK4e9GV pF1jYxo6QsUAFDdSIvNceJtIOo68k19WbewaZKkshkiHTDWmXFbG5aj83e6SW7RMX96gY+rhYDQZ uLAYLwYamdvJByZbH3GiE7sdpiVveAug36UkcjEZkTgThRO4K8/qAT/BbmPTN8ae6La2gfXVW++A z+CNFlAf0E1qa/zl2/H7w9378YuTM5dG0v68bF8IKtl6ROi28L2x2nbOmpAp9TUcAWhOses5z4ZF 5hw6m7S++5gG4jt3toBb3WgCjgPXWbG1Nv2GGJs/ur4+vT0vFtPL34dabyOgETxrEDwpGVKHzMdz M/eOMp96KAvTctKiUYERLIg/Yy1whkmZDbyUob8ys/OV0V2yW5SJt0hvA2YzL+VSn5wG7XJMuYo1 IdOBJ+NLPY63SZlc+ntmTu3gCIFjF06qeuH9djiaUu9hNmZoVouVPIrsLmgKo3z96nSriU2yNXRN 8oROntotagi+3m/oc7r0Szp5OPaVM6QvJg0I5fgaAdssWtSFnbNI3Xk+SRjHLZmlZj0xmYcgEHI7 N0lJq3BXUO9XLaTIWBWx1B5MQbspojiO6MurBrRmoQWxAUUYbs1BxOQIqs3SgCCku6hyk0XjI6r9 1a7YYnhSg7CrVkZYHTikc+e1Tx3fjGcM6QrneP/xenr/5caPQ5+Q+mH0Bm9Dr3Zw+q+dW3eQ0csI NgAQSQFYwFGAEjeqAjV0A5mzHv5TXqMpCvEhJNfBps6gGCacAetlI1FcZEWcOZ6Cm31XXeXXARwM hcVGVUTWecZ/29+QdCFX+HDfsCIIU6g33rDxLL+pMUIbZ/J03x0ubRhVBj4ccIFIYPQ2YZzrr0kk uc4ZyLdf/nz7+/T058fb8fXx+dvx95/Hh5fj65f2XlAJrF0XMM3OMS6Tv7483D19Q+eKv+E/357/ 5+m3X3ePd/Dr7tvL6em3t7vvR6jp6dtvp6f34w+cLb/9/fL9i5xA2+Pr0/Hh4ufd67fjEyozdBNJ +TV5fH79dXF6Or2f7h5O/3uHVO1WDa+U0LZkC4OYGpNKkNAcAvu0bQd519pA8XFfQ2rXGRxGAcQX EGRg9sZougTjUYRrYyoRZPoNmG5TQ/Z3Sevhwl51TT0PWSGPJ7qjQ1wcWfPwzV9/vbw/X9w/vx4v nl8v5Gh3/SnB0Gdrlkd2Hip55KaHLCATXWi55VG+0eemRXA/gZ7fkIkutDCCB7VpJFA7b1gV99aE +Sq/zXMXDYluDnh2cKHAsUF+cPNV6WbsOUny3MqbH6KNv/CTZ0dQkqj1ajhaJLvYIaS7mE50qy7+ R4z+rtoAY9ZCDch0EZPUBrdhrOVd6sffD6f73/85/rq4F7P1x+vdy89fziQtSubkFLgzJeScSCOB gRU7q0kvgpJ61WhmbjJymgnMch+OptPhZdMq9vH+8/j0frqHc+K3i/BJNA0W78X/nN5/XrC3t+f7 kyAFd+93Tls5T5wy1jxxR2MDeysbDfIsvlExf+zmsHAdlTDunptA2aTwKtr7WxxCGcAz942nvKXw rYvbx5tb8yUnKsFXZCAyRazclcCJ6RvyJZF1XNC2v4qcreg3a0XOob7+mh30+LPNMg9v0O0V1dMB iGHVzuPuV7WhLM2elvqCd28/ff0pg59b3DBh7iQ/YNfbyL1Eyqeh04/j27tbQsHHIzc7kewWciDZ 8zJm23C09KS7QwmZV8NBEK3cWU7mr81vi/EFEyJt6mSbRDCHhamc20dFEgxnAyebcsOGDhYSR9MZ hZ0Oid1vw8ZuFsnYiLChUisQRpYZqUklEde5LELu66eXn4YSW7va3c6GtLoidvd0t4xKah4XnAwr 0wxpdr0yjhUWQZkmuzySYXikyGXinOEhofnIYR1Apc6LGnlGfGaZIpjElfi/u4Nv2C0L3IorJusO r6HG2CYWeZhWxLBPiN2R2oCq68wOQyXH/Pnx5fX49mZIxG1zxe2qU4KhqKHSFhN3A0MdDSJt464W vDxtNoICjgLPjxfpx+Pfx1fpgdcS2Nu5VkY1z1Fes/MLiuW6CXBNUEhWJymSUTgDjzRO3ktqCCfL rxFGfQvRACW/cagofdWUiNwQaKm1pbZisN36FiG7hpL6GjJM9T2l2mhDhXTuLSdMhYCYLfGe2njC 7QRt9P5onyAeTn+/3sEp5vX54/30RGxUcbQkuQ+mq22gcTLQh3FnIdDkCuz9XEJoUiuc9efQyXBU HYChkOnN1gTyKT6sDfsgfcW3W5y/AzQ5jwJ59iZBIpjP5ppaPeEeT9DXUerzl6MBlY1f4VF50pDl 1BPiRStVON5jHgsyB1j5bM0cJHRLDy9oYREhA3VU6lRhFDEaTChejpgr7omDoEPQt+j5foySdRWK ywlPlMIOqqwEPtGh0mN2fx+VbBUeeBi77BuInIPsQu7Be2nqX4Y9QrboxiTO1hGv1wf3HGrRXU1a o5qjnSe6QgdqjP4yXgrZCBbH/+eTDafuoll5kyQh3hOKK0Y0t+1aohHz3TJWmHK3VLBOya0DVnmi oyh93ungsuZhoS4zQ0epPN/yclHnRbRHKmamEI86Yq7UX+jv5+IIjx9r14vRGu8n81BqewiNV3Wd 2u4ax9d39L8KR9w3EX0Fgz7evX+8Hi/ufx7v/zk9/dAMMLJgF6Nigrie/evLPXz89id+AbD6n+Ov P16Oj19otOhpdTfQaTAQEHHcpx9ZqzDRb5sLIya1Sy//+qK9RSp6eKgKpo8GrbcRwh8BK27s8vwV g32Rb+OorLxV6xBi88a/sIYmqAj3mRwiCbAz0ehdExt9w08MZpPdMkqxeTDp0mrVzIbYKzwULApm dX7V1adJqZdhykH6K4zgpuhSje6uZQQnKLR40tZd49QIDlcpz2/qVSHcE+hzXIfEYeqhpujaqYpi 87iUFQH5wgONT8I63SVLDF+vtQy7l8Vu9jmPbPMPOCEDXwWhVOe4fDgzEe4hmtdRtauNs411joef MA/jlX01J9KBN4XLm4XJXjWKj1MKCCuuvdEMBQLGyEed0UdOPjH3FU699YOE415i8EX3y761KFga ZAnZD7oOTNevmCrVzMx0VB5DaTk2tCFvpbxopRo6PEaqlrOWPiHRui5PVw9EU7l4dHVEMoU/3GKy /bs+LGZOmrBHz43LPkWJ2MxjnCLpzOPGtiNXm11CXRgqBPpucSu55F+dNDG2bS91La7XhmqKRlgC YURSDrdksnHCbha0/rDXbu0YvwJYwB7D2BRM20/xrSnKDCN6mSQsfQy2gOlBop1z4AcaJXQJqQiV IQnA0Na6TpugIQG9LeAjoS6jFHwjsi9vUi5AqwyNW/cRP4syNC4xEU+alkafkVyXFgUrpDP8ZnNa x7IvNfSVxkDT2NTqbPu/ypIIeIrGEOLbumLGBTK6BoUDFaX6nOSRVAvtOMwq0LhEFon3PthIC20c V1latdGOHo3Uxb866xZJaNAA/EcqyrbthRplsdXfaVbLgDmR9kYpXkGDMM8qK01KAbA3wUY2ajUN S+C9iXltnaNDLNpoK1t+ZWvrNKKEAWcvt/teMj/py6EUo3cdBvo6SIf4hp8FQhA1X4UbwVCkvrye nt7/ubiDcr89Ht9+uEoHQsrYCtNRTWqVifgwa72J8y3IaDwUpjJBHemvWFJvr4ZTRgxCRNw+Fs69 iKsd2nJM2hmjZGgnh4mm551lVVO9IIwZ9bIf3KQMQ2vYq0dPrm1bAjg1LDM8VoRFATh6C5afwn8g JC0z2xuCGl1vn7c3kKeH4+/vp0cl+r0J6L1Mf3VHaFVAdYRx4F/D6XjWDUYRwdm0RD8hpu5/EbJA hvoq6V1iE6KzZfQvDCNKLl7FYaRhGxoaJKziGhe0KaJ6aOWo20eJPIC3wXRZ7VL5AYvh4FPPJktr fV4zWM6ypXkmrJ1MOz6dQtR3n8RRikbk5vLUq3Adsi2qzSCnpU2CPjsyRgg2te6C498fP36g6kH0 9Pb++vF4fHo3o8kwPHzDSaGgYmaoipZO76nVj/8SDSvFa7UAJGgr3jNp25zSjIxQJNRrxFBs14HB 4/E3dVpvtrHdsmTKHDS6De2aCqqvPDgcw6coB0SNm2YrFF1v95p9hdY7YWz3IBrJNGcopUXSZqZx QeQ7cP4M09LyJyFzQbrYRKmjCn6bXaemn2mRChO2zFL6sCUzLrKAVax547dKhS0E1hl9+VTGu6WQ P6g3GrV8xVa2Q56qrVy+QeFGkMI0kLatdqftE7cy+0S8hHqMV1pMsXQzq/M1CPJrZ3bLgCVCl0gX z/ah3gA0PVzBxHVrZJCpo49UQUKNaRgCmPjdHA0CJbTbGkbd3HBK21jey+WDMOIvsueXt98u4uf7 fz5eJNPY3D390HdZhn7fgf9lhqBpJKNzg512+y2JuDFnu+qvgTb02apCjaVdDlWrYIZkFEuUpHqD nt8qVhpjLNW1WlJbyHA0MLdakG9YogFFnaibAx9WNaqVoa6vgNXDhhFkxv2juCCTbSJ5c383S71K YNnfPpBP6+u76zQx731q/JKq3mz0NLHC9HlCFWPOauzMbRjm8p5JXt6gskfHw/7z9nJ6QgUQaM3j x/vx3yP8cXy//+OPP/6rmzOKQcDpZVeFh7AkFoA/zKxaYO2XZp7XpWE5IFOlwA+MBepu05RZtnyI Uwd+/UyNdt0wDdFm2uFl19eyHu2HZP+v3O8bafn/0Xl2D8GSFZyH1v9UwmzXDiHFCG3EFB+mUSNR XHPY3bGVnLkZXjk7/5Fb1be797sL3KPu8XbPkAFUX0Yec1611Zyhl/QLhyRKtVwQnkiM2FPSWuw4 IP+iI5nIdqdvLDhPk8zO4AX0VFpFTFztyUdtvqN2WWuEG3GV72qMbxA2Vw2dIAsU/RvKAA0g6DJC y8DI2BpgTAqvdFciTYBTo8Z2twLXkkJk4YiP+q7VSrmi1MLa01rqumD5hsY0Z5SVVW+CWF9H1aZR qDXKkeREeA8CAN6xWhC0mcZpLpBCqtbNnMXn3DTZw0RkAF0g4k42Fx/QQgrDSAOuz4CXu9fT270x RfRDbHV8e8eljhyeP//38fXux1FTk0ejeH2aSCv5vmDEtB29QQwPoq7WdZekia4SHE+3ZFBLDQ+M WdG5ASErYLkK8QsrIKLwbK/GwLwaLGA48VIca4JDgQof5Nrt60WNLSOvA+kYzYjrIOM7tG+lu0+y xWUkm0praFv3D/8HuyEXpNzTAQA= --===============0992859560005402260==--