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 X-Spam-Level: X-Spam-Status: No, score=-10.2 required=3.0 tests=BAYES_00, HEADER_FROM_DIFFERENT_DOMAINS,MAILING_LIST_MULTI,MENTIONS_GIT_HOSTING, SPF_HELO_NONE,SPF_PASS,URIBL_BLOCKED,USER_AGENT_SANE_1 autolearn=ham autolearn_force=no version=3.4.0 Received: from mail.kernel.org (mail.kernel.org [198.145.29.99]) by smtp.lore.kernel.org (Postfix) with ESMTP id DDF1CC63697 for ; Sat, 14 Nov 2020 16:12:30 +0000 (UTC) Received: from vger.kernel.org (vger.kernel.org [23.128.96.18]) by mail.kernel.org (Postfix) with ESMTP id A16AC22265 for ; Sat, 14 Nov 2020 16:12:30 +0000 (UTC) Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S1726281AbgKNQMJ (ORCPT ); Sat, 14 Nov 2020 11:12:09 -0500 Received: from mga14.intel.com ([192.55.52.115]:47089 "EHLO mga14.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S1726265AbgKNQMJ (ORCPT ); Sat, 14 Nov 2020 11:12:09 -0500 IronPort-SDR: eQqBsQWu3C7WkVXsUOVRwwv+cgdpp75lFHrfaqVL8Np7ljah4WtWDhZHlbpUD2sh+/rJXyCBVP yUa3s+DqyMKw== X-IronPort-AV: E=McAfee;i="6000,8403,9805"; a="169803562" X-IronPort-AV: E=Sophos;i="5.77,478,1596524400"; d="gz'50?scan'50,208,50";a="169803562" X-Amp-Result: UNKNOWN X-Amp-Original-Verdict: FILE UNKNOWN X-Amp-File-Uploaded: False Received: from orsmga001.jf.intel.com ([10.7.209.18]) by fmsmga103.fm.intel.com with ESMTP/TLS/ECDHE-RSA-AES256-GCM-SHA384; 14 Nov 2020 08:12:07 -0800 IronPort-SDR: GqTgWz54JVbg915iTePLtJIlT7eYaEn/+u2LuRB+50frSixywCae15UY5h74l35UO1foF1uz7J FelqVlHtsMsA== X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.77,478,1596524400"; d="gz'50?scan'50,208,50";a="400029550" Received: from lkp-server02.sh.intel.com (HELO 697932c29306) ([10.239.97.151]) by orsmga001.jf.intel.com with ESMTP; 14 Nov 2020 08:12:03 -0800 Received: from kbuild by 697932c29306 with local (Exim 4.92) (envelope-from ) id 1kdy9j-0000uQ-7m; Sat, 14 Nov 2020 16:12:03 +0000 Date: Sun, 15 Nov 2020 00:11:46 +0800 From: kernel test robot To: Shuah Khan , zohar@linux.ibm.com, dmitry.kasatkin@gmail.com, jmorris@namei.org, serge@hallyn.com, gregkh@linuxfoundation.org, keescook@chromium.org, peterz@infradead.org Cc: kbuild-all@lists.01.org, Shuah Khan , linux-security-module@vger.kernel.org, linux-integrity@vger.kernel.org Subject: Re: [PATCH v2 13/13] security/integrity/ima: converts stats to seqnum_ops Message-ID: <202011150009.G3K9oqp0-lkp@intel.com> References: <581db581b900a01887ecfc3ec6b92e19d54cd2d9.1605287778.git.skhan@linuxfoundation.org> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="7JfCtLOvnd9MIVvH" Content-Disposition: inline In-Reply-To: <581db581b900a01887ecfc3ec6b92e19d54cd2d9.1605287778.git.skhan@linuxfoundation.org> User-Agent: Mutt/1.10.1 (2018-07-13) Precedence: bulk List-ID: --7JfCtLOvnd9MIVvH Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Hi Shuah, I love your patch! Yet something to improve: [auto build test ERROR on staging/staging-testing] [also build test ERROR on integrity/next-integrity char-misc/char-misc-testing usb/usb-testing linus/master v5.10-rc3 next-20201113] [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/Shuah-Khan/Introduce-seqnum_ops/20201114-014959 base: https://git.kernel.org/pub/scm/linux/kernel/git/gregkh/staging.git f4acd33c446b2ba97f1552a4da90050109d01ca7 config: nios2-randconfig-r023-20201114 (attached as .config) compiler: nios2-linux-gcc (GCC) 9.3.0 reproduce (this is a W=1 build): wget https://raw.githubusercontent.com/intel/lkp-tests/master/sbin/make.cross -O ~/bin/make.cross chmod +x ~/bin/make.cross # https://github.com/0day-ci/linux/commit/b86077d3629fe6d16070d95b8331344258dcaed2 git remote add linux-review https://github.com/0day-ci/linux git fetch --no-tags linux-review Shuah-Khan/Introduce-seqnum_ops/20201114-014959 git checkout b86077d3629fe6d16070d95b8331344258dcaed2 # save the attached .config to linux build tree COMPILER_INSTALL_PATH=$HOME/0day COMPILER=gcc-9.3.0 make.cross ARCH=nios2 If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot All error/warnings (new ones prefixed by >>): In file included from security/integrity/ima/ima_fs.c:26: security/integrity/ima/ima.h:178:18: error: field 'len' has incomplete type 178 | struct seqnum64 len; /* number of stored measurements in the list */ | ^~~ security/integrity/ima/ima.h:179:18: error: field 'violations' has incomplete type 179 | struct seqnum64 violations; | ^~~~~~~~~~ security/integrity/ima/ima_fs.c: In function 'ima_show_htable_value': >> security/integrity/ima/ima_fs.c:48:52: error: implicit declaration of function 'seqnum64_fetch'; did you mean 'seqnum32_fetch'? [-Werror=implicit-function-declaration] 48 | len = scnprintf(tmpbuf, sizeof(tmpbuf), "%llu\n", seqnum64_fetch(val)); | ^~~~~~~~~~~~~~ | seqnum32_fetch >> security/integrity/ima/ima_fs.c:48:46: warning: format '%llu' expects argument of type 'long long unsigned int', but argument 4 has type 'int' [-Wformat=] 48 | len = scnprintf(tmpbuf, sizeof(tmpbuf), "%llu\n", seqnum64_fetch(val)); | ~~~^ ~~~~~~~~~~~~~~~~~~~ | | | | | int | long long unsigned int | %u security/integrity/ima/ima_fs.c: In function 'ima_show_htable_violations': security/integrity/ima/ima_fs.c:57:1: error: control reaches end of non-void function [-Werror=return-type] 57 | } | ^ security/integrity/ima/ima_fs.c: In function 'ima_show_measurements_count': security/integrity/ima/ima_fs.c:70:1: error: control reaches end of non-void function [-Werror=return-type] 70 | } | ^ cc1: some warnings being treated as errors -- In file included from security/integrity/ima/ima_queue.c:21: security/integrity/ima/ima.h:178:18: error: field 'len' has incomplete type 178 | struct seqnum64 len; /* number of stored measurements in the list */ | ^~~ security/integrity/ima/ima.h:179:18: error: field 'violations' has incomplete type 179 | struct seqnum64 violations; | ^~~~~~~~~~ In file included from security/integrity/ima/ima_queue.c:20: include/linux/seqnum_ops.h:40:27: error: field name not in record or union initializer 40 | #define SEQNUM_INIT(i) { .seqnum = ATOMIC_INIT(i) } | ^ security/integrity/ima/ima_queue.c:37:9: note: in expansion of macro 'SEQNUM_INIT' 37 | .len = SEQNUM_INIT(0), | ^~~~~~~~~~~ include/linux/seqnum_ops.h:40:27: note: (near initialization for 'ima_htable.len') 40 | #define SEQNUM_INIT(i) { .seqnum = ATOMIC_INIT(i) } | ^ security/integrity/ima/ima_queue.c:37:9: note: in expansion of macro 'SEQNUM_INIT' 37 | .len = SEQNUM_INIT(0), | ^~~~~~~~~~~ include/linux/seqnum_ops.h:40:27: error: field name not in record or union initializer 40 | #define SEQNUM_INIT(i) { .seqnum = ATOMIC_INIT(i) } | ^ security/integrity/ima/ima_queue.c:38:16: note: in expansion of macro 'SEQNUM_INIT' 38 | .violations = SEQNUM_INIT(0), | ^~~~~~~~~~~ include/linux/seqnum_ops.h:40:27: note: (near initialization for 'ima_htable.violations') 40 | #define SEQNUM_INIT(i) { .seqnum = ATOMIC_INIT(i) } | ^ security/integrity/ima/ima_queue.c:38:16: note: in expansion of macro 'SEQNUM_INIT' 38 | .violations = SEQNUM_INIT(0), | ^~~~~~~~~~~ security/integrity/ima/ima_queue.c: In function 'ima_add_digest_entry': >> security/integrity/ima/ima_queue.c:110:2: error: implicit declaration of function 'seqnum64_inc_return'; did you mean 'seqnum32_inc_return'? [-Werror=implicit-function-declaration] 110 | seqnum64_inc_return(&ima_htable.len); | ^~~~~~~~~~~~~~~~~~~ | seqnum32_inc_return cc1: some warnings being treated as errors -- In file included from security/integrity/ima/ima_api.c:19: security/integrity/ima/ima.h:178:18: error: field 'len' has incomplete type 178 | struct seqnum64 len; /* number of stored measurements in the list */ | ^~~ security/integrity/ima/ima.h:179:18: error: field 'violations' has incomplete type 179 | struct seqnum64 violations; | ^~~~~~~~~~ security/integrity/ima/ima_api.c: In function 'ima_add_violation': >> security/integrity/ima/ima_api.c:148:2: error: implicit declaration of function 'seqnum64_inc_return'; did you mean 'seqnum32_inc_return'? [-Werror=implicit-function-declaration] 148 | seqnum64_inc_return(&ima_htable.violations); | ^~~~~~~~~~~~~~~~~~~ | seqnum32_inc_return cc1: some warnings being treated as errors vim +48 security/integrity/ima/ima_fs.c 41 42 static ssize_t ima_show_htable_value(char __user *buf, size_t count, 43 loff_t *ppos, struct seqnum64 *val) 44 { 45 char tmpbuf[32]; /* greater than largest 'long' string value */ 46 ssize_t len; 47 > 48 len = scnprintf(tmpbuf, sizeof(tmpbuf), "%llu\n", seqnum64_fetch(val)); 49 return simple_read_from_buffer(buf, count, ppos, tmpbuf, len); 50 } 51 --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all@lists.01.org --7JfCtLOvnd9MIVvH Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICMP5r18AAy5jb25maWcAnFxdb+M2s77vrxBa4KC92K3tJJvkfZELmqIsNpKoJSnHzo3g Otpdo0mcYzvt7r8/Q1IfpEQlxSlQNJoZfg2HM88M6f7y0y8Bej3tnzan3Xbz+Pgj+Fo9V4fN qXoIvuweq/8GIQsyJgMSUvkRhJPd8+v33593++MsuPg4nXycfDhsZ8FtdXiuHgO8f/6y+/oK 7Xf7559++QmzLKKLEuNySbigLCslWcmbn3X7D4+qrw9ft9vg1wXGvwXXH88+Tn62GlFRAuPm R0NadB3dXE/OJpOGkYQtfXZ2PtH/tP0kKFu07InVfYxEiURaLphk3SAWg2YJzYjFYpmQvMCS cdFRKf9c3jF+CxRY8i/BQmvwMThWp9eXTglzzm5JVoIORJpbrTMqS5ItS8RhHTSl8uZsBr20 Q6Y5TQjoTchgdwye9yfVcbtwhlHSrO3nn7t2NqNEhWSexvOCguIESqRqWhNDEqEikXpeHnLM hMxQSm5+/vV5/1z91gogjuMyY6W4Q9bqxFosaa62sJ1ZzgRdlennghTEnlQrcIckdDXgNwrh TIgyJSnj6xJJiXDcDVcIktB5940KMNtmX2CfguPrn8cfx1P11O3LgmSEU6y3Medsbu23zRIx u3P3PGQpoplLEzS1Fp8jLoii2+u3Ow3JvFhEwlVD9fwQ7L/0ptufEoYNviVLkknRrE/unqrD 0bdESfEtGB6BNchuerBZ8b0ysJRl9gSBmMMYLKTYo3/TioYJ6fXUfcZ0EZecCBg3JfqktIsa zLFpk3NC0lxCV/rAddZS05csKTKJ+NprMrWUzdMqwXnxu9wc/wpOMG6wgTkcT5vTMdhst/vX 59Pu+WtPSdCgRBgzGItmi25JcxEq48AEbA/4cpxTLs86pkTiVkgkhb0kRYSdT9BaN/DoWEus 6nHcdpRZ8/M0zQXthoeP9uCGVKB5QkJ7N/6FerQaOS4C4TOrbF0Cz54kfJZkBfbjW5cwwnbz HknpS/dR27mHNSAVIfHRJUeYtNOrV+yuxHWEc5rNrAHprfnDpsQEhcT2/QlTrSPwDjSSN9PL zpxpJm/Bt0akL3NmdCq236qH18fqEHypNqfXQ3XU5HqeHm7rABecFbljUeAN8cJ7MIxwKXBM Qp8zNeychk5/NZmHKXqr1whO3T3h4/2GZEkx8fQMhtc3/b6Ido0+G2LqmNYySCLLC0FYApcL J9EesZCizISnIwhLwHBEBeF+WVBQTzYj0i8Kmsa3OYPtVy4QkIKzfr0ROh7rFfjWtxaRgNWD S8NI6vM6wimXs47JlT+xvFKiXMxSR3Fu9aG/UQr9CFZw2BsbM/CwXNzT3LsrwJsDbzbGTO5H bAV4q3vPOnUb5rgORTn3i94Laa1izpgs29PZWQ4uWQ4xh96TMmJcRTH4T4oy7AUSPWkBf1hD 5FH3YRxa952CQ6XKWpytXRCZKhcN+wTYKxnd25rfdRfFKDPxtAeSTPz02aN2L3aD3mHp6AgQ SFS402m5UQF43NM/yZmeYLc4ushQEvl8iJ5kZO2ORiVR6DSPwUV52iLqWAAEt4L34lrLROGS wlpq7fm0AmPMEefU3ZdbJb1OhV89eeTbL4cP5y1hKPTylRHo+OpVDcyHhCFxVJHj6cQxcu32 6/wprw5f9oenzfO2Csjf1TPEYgQBAatoDLjJjhD/skU38DI1O1Nq9NCzKyffQBKSlVsvWyRo PsIo5j6LT9jcMQRoD/vEF6QBJv7e4iKKIOvJEQjC3kAyA57Uf6IkSXUgUCkejShIUhfPAjqL aDIwq1qPbrbWxhLKhOVdW9QtinRIje8IIF7pEUeQjXDw1QbuOYCZspxxWaY6W7JtwIEDHSSf TiZeVQFrdjHxqAYYkCH3gD304pe9sbJpE6RirhCx5aUYxAuY76q8B4zOOAChm+l0YJAdXlHz zx83J2Wfwf5FlQTUojQ9rZ72hx9qCgplHjtMqRWvTrL2XDeT75P6H9MurP7egaWfDlVl68e0 CuUcMsIyj9cAxcOQe/XViZoIqIJJMjiP2W5/DCgNds/H0+F128zd6UNnvBwgjk6+py4zvlNR ohRFrrbZ2nmLu7LYvfmBQEiXDd+XhmmxCNKVkSEwVan4/D12xm5q1eINYE57RzqfUACOScGa wS5KQaRKPXz+t1ZtLafC6eT7VWdWDlsVVhqZWU+EOj0ok+2sbGBQxswO+211PO4PwenHi8lk rGPUhIfUyhEyrkCo6G8bHNhFliovCTCpPZnzPSy0s+BOMWmo19E3od5m5ghyw1p2VG0a04AE JOpRBErWpn9hTL9b/Rvr1BNDD3+rUPDQFp/s8KmAUKhBD3Oha320vmxeH0+tBQSg5mDT9Le1 K3uNLoLNoQpej9VD/2jcEp6RRGkcDshClaDq03w1cYtzjrgruvWKAkRwxapGrFVSTwdOTW5z 2H7bnaqtUtmHh+oFmkDMtPa2cYEA7yMrz4vRkpgDr9PKmDHLM2q6qhlCvqRbFpm24LAncjab U6m2t7SxJOhogWSsUg9YG8oWFgpNWVgkRCiYUZIk0ijfSu8XUqX0ZQJxPRE3s65MqWO4GU7B M6uCCQ4DhiERBEqqzDyKnGwWcisLJLSlpQVmyw9/bmCng7+Mm3857L/sHp0CihKqt9JOud9s 24/C7+xPmxFA4FTQlViT10hXpApZT63U2GjQD+7Uen2oVGRTO2UyviqnGWysVpGp6Ll8TlBY 89/iedvecQoYYaSxzaxb6z0h36vt62nz52OlK/WBhoEny4bnNItSqezGwuZJhHspaS0mMKe5 H43VEikVeAQzchIWae7FV2PTtGFAunnefK2evCcxSpAEOGDhECCADYdEo4TUqTbnCVh8LrWq tHs/d84ErqFhc34UuuREhUen2JfSBUeu6K2wZtCU1FIYHIQzDTZuzifXn1pfRcDRQs6oz9ut 1RQnBBnn4CSubu5cU+9zCCu22P288GUZ92cRSyxfc68PAXOK7g2t9Rkw9Xws02qFVenSK6HK v0Z9yh3e+kuREUcpAVSurkscPE64Uouui3p7XxR5OScZjlPUT0Nqoxq3m24H2rp/Vp3+2R/+ An8ztC6wiVsibZNQ34C9kGUPRUZX7heclrRHqZt0KoIZ+II9kequCMIEVqvrlZQ0C/Cr9tqg oLS/R50opDRSJ7p9Uhvpm/WHBD9Xp/8oPcAJhKxwcE3XTgFEdWErKuEEzIukn3W1G/Benxbu kL7EX0jr2C4Qt75S/dE5H07DhQ82LROUlVeT2dTypx2tXCztTi1G6jDMivvfJWeFo90kwc7H zJ4iJJ+JL46sZhdWI5Q7mXAeM7+FUEKImunFuRUKWlqZJfUfuihFFVZFjpewZFWtlPhPcIqw EfLjViKHNePOSrC/BhBmQtU8mbp39F03gikg5SyXdtBuaM2fS2fzO3bmjz2WhPcybUTszemZ Op1lPEaPHsrg1LeMhLF8jrzwYkkh3jBfry6ju5rrdkUnCP1B0zzxr9oUqWNfwi8s4/7MpeOg 1TcgKV+s0SxZZG7jMo2pp8qvhs859V09WxI4gfSIhs4yS74q54VYl3Udstmiz0nPqQen6lhf 47W+acDqMexA0OH7lKNQVyNNQrnZ/lWdAr552O0VXj3tt/tHK24gc7Y7FwDfZYgU/k8gVfC7 bM6soMGZIM1oaPVxdhE81/N+MDWOh8Pub1Pza1affyYqT7BPzxpspFTXFlG4cg9Oy4lDX4V3 jVIbpL85g3bTkLXv8AHZyp2z7UCaY5+7V5zFndv4j+n12bVLooLJNukGQlPuCfuqUMJLMx1n 9OVKtfKPH5JlXxyjBAO6leoWwBtnlVCUkJVnqAXvDeX2XL7JxZeX/mqe1kJE1X8jv/NVEmm/ d4sn/kCqYuIqlqSizHGKKXLptTAoHvXX17ByAAHqFmVsOBa54NkilljYmwkZVLBTVekvm23V 28yYnk2nq/4cUpzPLqarcT0Yfl9Tze32cEzXHiAO1FeUzhsFj+G1B86++FdVchI6nhNoPFJu 2xdfQD4judsBEGAVZQvm7J40M+dMsprv7zQWvXaJ/1mN5oS+uh1wUhHpl1luT56I2jEF5JLq VVKvTUSQLDgZhllTSXt8rU77/enbuJeDFWE6l8J4Y4caymTap83lGR7QkoJgxMPe1ICzhH9H NMCXSU9ekUo1j5EW8raeZGs6o8trcyI6L7kqSHRTvqOcAMFDKc2ONFT4Kuvk3SaJfN2jQMy1 IBaOFgrpTZ1UQ4PIqX5VlkIq7T9hdUN1RkjCVDp7h3jWL/4O5TEBHNPcxJQsK7z35I00J58L WLC+YoSsmZNFOB/OXpfAujphOIePtftooZuuSc/zN4etbdszEuYhGpbNW/adsys1jna029BK jlV5QEjYTt91pSVWz1ldx5vXIfunKvhnd6geq+OxsaLgUP3vK9CCTaBeaKqa7Omwfww2j1/3 h93p25OdyrW9QyIZe/erlRhxCy1/oCq7b9FUAUwUGPZu/CzkKcVbY0Cyq0qosb5gMpX/ri8e 3VLvhbqCiteWSzXfNZDu5daKMXBKVjihkW+AyHIu8AHYe0FNwmURM+zA35pU6uDj61J5on4D EYcJHvjLrNocgmhXPaor3aen1+fd1lTgf4U2v9Vexr6Zgp4kjy6vLyfInaN5megMGYX+tx6K l2cXZ2clnXmfAKruZL3qAU018tJBHQMtrXLFGhvjLLrj2UWvM0OsR3FVKK8v4siLBf6lHtsy kECQVBHXsGhkEZI7yIJMpbtx7YgmbGnDc0DrkrGkydvaeswIqM1xHbPa7xqwWW8HFKVUrxFK TIdXODn+sN0cHoI/D7uHr1V72aqL67ttPWLA+kWwwpT8Y5Lk9vQdcpkjGTvvgZcyzSPHAze0 MlWXB96qD8pClAyfeOqBIspTCDDEPMcbLC7aHZ7+URdOj/vNQ3WwKsR3WiP21FuSLlKG6vmd tS0rcFftaNaaulb6JVhfH142bHuSqETfJ6eKztyE9tYS+8toM8okYXf6zVZTTreLUhqqQlh3 QWILYfnIDYcRUFG+bg2xM2VLf7zP0/IzE+VtoV6k99+bd89pNLvuLR99mN4+gcgLC2M3dsCw Su+tZJgsnEK++XY9SU0zXqRPS4fEu+mAlKY2pmwGsS9kmg4xtjCIvtaLwVa0IUW9PQBmRDJs giDxep+RA2gQ8etx6MZTtpJ2VTKNaa2wLr4aki+kNWDU6rlFMQycVl2Qb48f7Eb7krwrwmfC CwpkW1fON4fTTjvRl83h2DxP6uRKxC/h/HE50k97fa5lnLUBk0VvtoXN0DfmTVsPKwRUqZa6 Nhd9Nx+m7ghOF2WR1e+MRoqewxbqVo9lydqr/KFytHYK+DNI9+ppr3moJQ+b5+OjiUXJ5ocT ELQaWD5QjRqeKmwNBpki0csMzYttlP7OWfp79Lg5fgu233Yvw0xLb0FEXeX9QUKCez+DUHQ4 z+2vI5zJQA+6Zup5VmBJqUM1R9kt5DahjMup23mPO3uTe+5y1fh06qHNfDOlmYTUauXzWO1i 0tA8Nh00hvDlu6dr2IWkSc8SUdojsB4BzQUcPDs+vLFz5sp08/KiKphNTqBeaWipzVY9Delt L1MwZtXc9vUOinooZdyua16GXD8jGFlwI8Qib5/691aQ/yXEz14QSIzoCC9XP3IIQ95j9+pX Ha1EGcvWADr660uQ5G6d8z3tmeSrevzyQSVXm91z9RBAV6PVCjWMenwYJZC7uKO35PoGXz9P XPeV3Ukx6Ufj+gjgOJ+d3c4uPo1shxBydtGzPpE0i3eUDMTxcWTYYxvEujv+9YE9f8BKU2Pw Va+G4YX185c5js1v5sr0Zno+pMqb825r3te6yYgAQvZcZEYUcRBADLnWu9mEEe01ot2PTrw9 9XbIIzFbKSe58Oido7tSiYyqHnDNQMC888AYVPQVlBIcX19e9oeTfdnh47ZJj1KVFk5y9Rzy f8x/Z5AnpMGTuUL3WrQWc43pM80iZkWAeoj3O/6pv0b3MYBF1iWec301rn5gOaqpYu5LGBUn XgMid4BlKC0EafsqgBcKyNYFzI6oXpdITohDJIgnaz/rls3/cAjhOkMpdUbVzsyp8AHNgZ3w 7dxCM/XUC5KMpYrw9uMXw1A3rA5N5Z3mgXGH5hHvPx0152eZkkAMDcmhm0izO24taGq9JLyY XazKMGe+4ACZS7ruvXLC4vpsJs4nTpUMMHPChCoVq4WqBMH3FCsPxfXVZIYS+we3IpldTyZn dm+GNvM9boYIK8CeSgkiFxfWzUjDmMfTy0sPXQ9+PXGuJeIUfzq78P8MJhTTT1d+ljIdWGIJ 2Oqs/uWK/+H7mHdeqRfsq1KEEfGVZPJljjLXc+GZd/8JgUOcWq6k2Q5NL5GcWQCrI14MiAlZ ILwekFO0+nR16VyO1pzrM7zyxa+WvVqdf/K0A9RXXl3HORHen6oYIUKmk8m57Zp6CzU/ka2+ b44B1Y+6n/SPJY7fIBd/CE4Khiu54FG50gcw/d2L+tM+Iv+P1l12DygdKQSZW1Ga4Ni5PnBO nIEiWNAmDA62TDHVA0e7C18Dq4g1SMVT6hbliLlj8B1FXr+U6RyBppTT2WQ6Kl9OJxcWOq+J 5uLYpWG7ANDQWHo9+f7dM2jN8d7NNINQsB1fl7MJOIpRhrm1bHZIXbj3lq2EIV0OIWKdQaOR snQtgRKEFfLQv1LvFmHMQQp/JcZun6J75rvrdWQGVcMyS9X/98AtYDbinwuUSRtK20yO/fSC M241Md9lNr+6si+brRZzzlCI7YRnfm65ljlOFdyygp75Lc/g9xBdjxiFJOuXWHxiS1r4vagt pV99+vK5ECzL/eGModS/gBFU5VT6lZ56neLrYNxgyD2OR35haUlFxR9UiuI9sQVji2TkrUkj ExfojgyOeM3U2fB7o6QkAUti/lt4W45i/i96Ayn2b3SgBQWkiW+vL0NSCY0sUD+6yVj6rs1k 7wxzdXbtWESTeK78b/hqdu6+LQRnwvynKwfEAWB9cGVVs+HAJv1XBT45DgdKIO9Pcywh9bqM j4wkUCqKsSenrRAhn73LAGCKOMBkTvzsVDgIRaT4euR1R61ALYGvZ575qM6uzZsR30SwKo/Z F7U2V2rjcqYi0xRhtUPv6VisM5aDq3pbRUv34gY+S3WHjqlcv93wjt73vIehlHcXU+9P91p2 78d+NV2XiHUh1LswS4pmQ7mhFMrWI6ZjEOp76ltR7o+Z4E+d/3WLuAOKPVQCuZDkdLFQ9w6x T40RXRFdRmoq1ABuAiU6qN50gTgNRzpDIc3K3hSayDnWZHV1dXn9aV43awJdHQf7nUEAvDif nk9GOgP25Wq16vWF06vzq6vpkHrpETUPMHt6xRTCKOpPpo6GI3MJIaJ2K2izujwBg+jv0kr2 O/k/xq6luXEcSf8VR+xhdiO2t/kQX4c9UCQlcUyKNElJrLooPFXabce67Iqyq6Nnfv0iAZBE Agm6DvVQfgkgAeKRCSQSi40Gy811vKSfLOVUTJ8tBtdx3UzPt06ZMVxV1rwn3HX2lszF+oTr MK9GNvLgEggsOJh85K4uqZZ7OsSOP+o1eZiSEzJ2BWiG93oSOa/bErEJXamDMr32mbW9mKrl OiO1nwWaKes4zGjHtcnb2I89Ty8FyEMWu66t70CyTUzkFUYUMcHEM9Od+77QS5Xm8J6NcK+D v+0f/L6PkySo1Z3jvGyW2CQqEe0dNTtONNN1yIDi6cphm6IrRJzKhuDpWLKFRQNgh1sjHUrW 93eF4F16NUDsM4IfUUnNmpyhbB82jptoOTJq7ISbeS4EP7b65/M7s0xvf+EtP1n1a30azQYB KiXxBPFgGHDKoJ6VY466ZCblfpKkzXrrfjrDrmOboRNzgn9mbxWbkf2AaExwbIFUtRb8fmDz jlKVAdWv0gCtbttCo0A9pR+HmnlDZdtXh2yq7+H17f23t6evt7tTv52Mcp7mdvsKcfZef3Bk 8ltPvz5+hxs1hr1/qbAb8uwneMnp3VJIMBtwec1mlo/ZBuq6AOaoVbcX7eekGGOqml6xC5e1 cONTS+DG1zeZZtL1cOmww9kCWW94LBx1aklaw2kS0wlg3GmOkSQzMNFZrWXRZbU8LVwSMlrP hr+FfYdmkYki3YO3WU6Bs3eqAkyuerSLMGPIt1TTqR8wK/sM5ZuWXXPNPu6CdnNT5+r68mNG ueR/IG1d5CUb+mjU1kMUhj6lwqOUkxZA9+Mu1SeDbvBGS5QOlFAs8h/z9dSqpnKoZxfZxfWQ 2z//Ldj1joAw7KRISjJ8zPL5U55+3AO4/lwcyW0XOXN06acMeTxI+qXyA7zPaLqaHi59SRvJ 4BHK5ssd2aJ4VtX9MCftpFLdHeEXbHX/d6zu8bdbvl9IK7/LtTzhPGWzIBU/QuV0I0d7gCKe 5cv3n+/m5rCibrcnc///8PjjK/c/K39v7iAJinrQqcs8/3ll1kOrxsIRVLSDK0hyU1MwL4om xxix1oL94LRddiVKYS1KULmDAKKfNMn3aV3oG4kT7XrsgyAmv9HMUmnXIqUmQrXdHK6T+hri c/zx+OPxC6zoxGHaMFj0c1YhZk+AP+CW9J8vW2ZFiMBhiurCqeD3oMXGE3Q4IhKuXqhzLVg/ 6OG3VB6hMosJepeqyjOH1ciTgtCXO6MgHt01b+gFSIjSXIqu2VHu2AzfrohxuEAAjRzrFjNR RCorGzoU2cK2TTe+S+cgHMtJ0RemLBs6shEXlrFs2TyRLhoxTHF3X4iOMs3YKQRjPF432s70 Qt+QR59Z521GrExbippntuKMTpzZ73tEGDL2p62JVsdkzlf22pUVSVXrMDHaVqIJL71M6JUf cpWMciwa+gKeyng8nZn+RB2vANeZ1Qc0rPGTWat+8P3PrXpWqiPYe9VANW94ZtBWn7SRvtxI M7/WonTIpu9O/cCDCAnfY3O18DLTokAiQoNsG9ahwNUDjVsGmM5gGD6wdMWZGrIMFXalMEMX C5SLxF2KKLnYkrAVMz3Lu6oKFBdHZqqZpQtVFIgkBKAaso3vUGfQE0ebpUmwcanEAvrL2gSc pzyywU930ImHWcIWAfJCycOsVl2NWVuh097V1sRFS3d1Syhw4Ohrsf0xd5d0ulf0pn2Zat9s ywFLCMQ221HEVBVZy3gubF5bwW156RBL3+Uhe+/+8XO5DvXv35hl/fzPu9u3f9y+giX9u+T6 7fXlN/Dq+w9d7kFMurjrwjYFdCTrV8sLuJvGryas3IYFzqIu1KCsQDK7KO/UU5D1v2ve2MBw X9StGtAFaA1Moz2msZadBcJId+8bA4CpxkNBB1EA2Ny+l1GG2LTz8vgM3+B31kNY8z/K/Yll 84ZzNu9/iF4o2ZQvhT/Dri/1DkF+fNQ34Va9USMgSgcQW5/mLODlBd5euJHE5Qg9HNKCQOdd 6RPAYpuw1clWSedThgW60ACucDxrTBJe3hqNL8rCS4StnPXjmwzDAncCIXK04aEJqcwxwKkj v551ZbMsHaMOwGWTE6VdO5UX1ZlGjyXfqT8oJLgXBvfu6Rt0wIGHlcimuuITJEnUVlogNxmP Pm7Je9pQx1n1mRuXfeh4emZMyy3JkA/8K43YKwtoo+WGOMf4MMQlf/50fKjb6/6BqElamx6j vDsoKwNhG3LRTuZwh6StDHchu9Sbno79oZd6AIeqCL3R0ZpOjl6dpAWnW+gyrCujD11TacND d7DEt38OPf6BVBphAffldHX2WZm/OPn5Cfy6liEDGYBuo24F492JlriCI5T6tp/yMxUcSJZV PALfPTdLUAETJDv5nJ18m+X1h7FCtkPLCnv98n86ULzw0GviFJAHjLSGmXp/ZcLf7tg0zqb4 r/zyCpv3ea5v/6X6wZmFzbLrust0DUwC1zl2/ZIAHToo/KDy7E5HHrMNp4D/0UUgQEzRhkiT KGnvR55n0vM0cUKCDsEm/N6JsdJsoGg611ET6VnLa6G/J2R0A8fiHTGxDPWO8omci03HKAo9 h8q+TauadBWZGLr72AmolE1WVI25sdSxzvn2+Hb3/enly/uPZ3TaPt1tsbCYZVRNdjim+5SK ebHULi9Ul7SJnvWbqPIDC5AocxOML7RkSALTzvoBLrzKB3kCd46t2ey0pWdKUnYPeM0Q3U8y L1tMoPzx+FJEzYS5owWqmYnXM+VmyeHl4oIaVvHb4/fvTCvmuq2hifF00WYctVuR4vaNoSUI KcylXoXzixbjTGi6A/zjuPTGuCo+qV1rnJ2uqavoobrkWk2qZl9m58yQqt7GYR/Rw0swFMfP rhfZiurTOg1yD055tietTAgoj0OQc7KpYaMmr/PrTnqJ4iiH1GeczSJOvf31nc3s2lItr1G1 QRDH1kLzY6sJv79cJyMTNQebSnzSAWmBvZFO5o0wOmxJuV3tm0kl/cOkkTagGXUXB9GoUYe2 zLzYdXTTQ2tAMX52+YcN25WfmyP95AVn2OaRE3jWlmewG3uxJiSsPYFnNIUwCG1ZVa2fbHwj UdXGURAGKz2cz59rX1SuHSY5MNqcrybmRFd5caaJjjmGtme5xdSezIJ7rt5QnByH5kdm5MT1 dPJDPcahTrxUG8d3DJkZPaR3Uzl8yrbuxtHrf6lj30UbrUQfmjXsD/oWm5XdkA7MOH0D37V5 TiqjlT4tEwyZ78extZJt2Td9Z85gXcrqTh3Vi0ynW+vLbQSzsnj+2e+7Yp+iHRCZVXZ/Ug9e 0ZbcxQXTwNBA3N8gYg7fQ1hMlyWJMKKvee9tYk/NekHcS62VIyHLqrMw9Hu0qUGIoorYPz/+ ecPSSYPoUKh7OTO9R1vwMxnq4gQ2INbqokL89rolQCVidX1b9qEF8HxbuUyh/Kg437Hk6us9 QIGoHok5rE2hqdgERxRbRIpilwbiQt5EIjE3wsMS9xjZM2bVFc7C+F1AdGSnkKUdQ9sJCpt1 h1Nn4s9WpeSjEyprNWReEqh2kgLWQ+jjbqCiv1aAqUWZ6NpZYVfwWA3SQUcSZTKMzQXAHcha Ba0iQniw6pNeeUHVN/BacLcFHM2nUuVN8wwiz7IphPRZTcc48QIzuVhvrjCAT/RVCsnBU9Ln YBAVxoAlKEW6xnFbx6GjrLOwG7LnUabbwAnVcHwySZoNcbIJUhPJLp7jIpNyQmA0hdRqpDKo 4xDRCSE43TPp/bY3q4KIdcrszploSLp98MAtm3afmgpP4XHatdpMap5GZ5/bjZjuQRUsMeoq BGLxtDCaso7ThySSTyxMb2Zf1PfNBuLdEN+3nSCpRa1kC3qoF5mZYjN6KYo3vwlUgx+qNwkV 2dxNEBEF5MXAD1cESxiEZGJNm8VIQjQG6wEbNyBGBAcSIi8AvICQEIDID6h2ZVDASllpV+CI LcUFSUwAfb31N4QYUseOzA65T0/7Qkz1G2KU7Zsq35X9geqv3RA45MI8ldoNbJYITGlOWe86 eJd9rpnVplo4kiQJ0OrbHYMhdOOVmfBwqWkfAFDGcHB1SZpCutETq+SBBw7KHhzp7XnDiSET /Aj+onIpk0/D1r0aAXFib3arRUKQC/68w9CVZPjLiXGKkblvznAVoL1eyr6gKqoy7tKyE4Gw VoVQk/BIafxRztUk9twJxlV5gQFOqfhfH2S0CEflVNTw/kFp8yKRXLB5Ri/c3HpW+pBExPYy 2bdKHhhNIrTtpmgNBN+09EsXK0U7lRQ9fuxEPjaX9FNzwvfOJlA4mYkHqoojf0R4pdBr0xZH frAA+TlEfsbuJ7eMLo/vX/74+vq/d+2PGzxH/Prz/W7/+uftx8srNpHnfNqukMXA17RnaAtY A1GqibaSkwyBiGVbBWah+Ff1153b5JeneFTT1ywXkcVTUvCOK35EtC6OO8/d1hmRAexlOmFC dQyhJZqAvGBjAp/LsgNbhmqFabtnrY5yD5luxct6C05T+Ur2Uh+hGiEdQ38cyYLn4bpefDGc 1sruh7YuM5csQWzhXS+55TkONmZSz9XxKeN+Cy/C9uVWjafFqOiH9JQ+NFyvn7mXr4NYLMWA q7ieAwFjqowGiTW6bVanpBxb7bmjxS/sf36+8KcW7eG2drk2hQHFtDg4ldnFrmvSPKRawBcT u+Rk7BieKB28OHIMTxGOgT+ieCKgsYTVmrkOVZZTDiDAAZdBE2cc9fyZPhNEbn052/MeW88Z LZF6gUE/Jlto+CRToWt+BrzV4ezMpbZvZhQrsjM5Xk2Er9UvZMrO4d+KG1eK9j0TVYMK8pGz NVEXiWhNZrLYBNdPiGeaT5Tkko+zArhPhwJO4vvrvte/Q+ayqWokifiEWQXMz9l6oZfoQh3K cMOmGmg4Wh0eMniysswo7R1AVg7yT4NMy4c+9DSBdT82oHE71DE+uiDbGtzchRCdVbf8JFU7 t1ioAUlVTwYWamJ8TE6P8U01nYEZZNSR4Yx6xhjh5CRazzSh7ytwfAh9cutkAhO9gSZFQZWk +MwdXC0RCGFU6qiCwbqIyzC3EiYKqK4EFS8d8oyFmOqFVam3YZcFQxBT3ZWj97HqecFJQpHQ 8+mLzIh+hBnKTRSOtghJgoNHh+FDQh+Ok3pkFFsHZAQljt1/ilkvx++NbcdAto5d0qFurTJO O6sKbQBXMt8PxuvQZ+gbAWoeMQpqHJFnyzLDqta7xXRKOClrbR+6jrqXIo4DXUenRNrYn44N dZEEPbGNB2WnAycreWV8ar9FwYMwIMRAp5MzVRxOmsIl7qpw6PBSpeoB7xFG+0lKFjbd+ooe NGnIlDozYemJfvVEno0SA/NSuV7kE0BV+4E5YofMD+LE2tzaeS3PZ/II0jQ6cQ5PEs0ROAE2 BcejT115BevAdSitZAJdbXFhplWSGD2NU21jhoHoaFnSfHekaFSPkIjtKs3EEjir2g8X0t4U XXOohQPDaPuCEwtY0trUOyfWEWk+6cR6ZwwkEUikdp0rW8bI07RVc2LKvyv24onLpciZpB/i LICIMnNuqiFVr6QsDHBJ7JRWPMbtqcbnNgsXbD7xvaeZjzzDmtiZCrRH/g4IqlEQNg0KnYgW AeymOKSULswjbSsqhzzwyd6ssAjryZJejscqb2hnBZOVdRE4ZvuImxt/v8BkOTldmCbLbLWS Rk9HEO7qShebTBmiWGGjrBY6myGW5CGtqSImj1yNNBaXLmOXHgM/CGgPI41N8zUh2CweFgtD 2VeJrzo7ICj0IjelMLb+hD45btQVhRAIdJ6IUss0Fo/MGw69LJ+WaxLro25RNqj0YvFcz4Dx hFFIiaaYTUTmgAakOxbiMdyKdTT46HuDXRNu1mvBeUJyZlusKRoKyM9iGnw6pp74aVjs2POM PTpPaZnruhbmiEjTBfOwytIFtC5raxprg40bWopt4zhIPvpEjClcn/jq9iFKPPoLMdvTNnUI /5D1nBlLQE6bs1FLZGx6tVNMWcqWtI866GSbrkrZ7k6fIfIwJWd7ZrMe3Xs5FNuhhIYuNUV+ 4C+96k/gqOCp317P+oM7kqFL+3ZbdN0nuLzTnLJDn3UF7EYPcEOKbmVuUa+2y2JgmxBTAC3Z DpuYNIRVFmn/E0h9pjsiZUIraLWHyIrry+CimlI5sOydkHKkRTyxuIlPQ9GRgpjxFrhspFiw yXYmZALUo/eFMBObO3x7FmB4/0IW9ITKMdcuPXY5MDCy8wiMbkjTJ1jDkG2NsMlEpprBdHAh uM76tW+DQ/EQprDNBz2Qj+Mq3ZZbNZaj3K/ClGMDr29iu4NHQeKofNiSsts4j/HwJSIbsdIm dJt3Z365vC+qIoPk8ibK16fHyf56/+d39MiVkCmt+ZHDXKwmc3pMq2Z/Hc6U5BqvfJzx15j5 e98fN0fe2WWb7qv8Qmnc245kmy97GC01SXIu86KR71fjtmv4/UgRAYa39/np6+11Uz29/Pxr fuP833A+502lDIOFhndLFDp83IJ9XLxnIhjg5Sf7o5qCRxjMdXnkq81xTz70wEsSD+FAoFf+ KLwiDUcvx8lfU7YZVVul2y2XPJW20Bqc4FE7Lr7ink+vBj09v98g8P/jG6vD8+3LO/z//e5v Ow7cfVMT/037ANvTztNG7UInPg6n10XdqPcmlRQ1f7dMbRYsu1Kdx5cvT8/Pj+jZFw6nP+Gd +6+3L6/go/+f8OI9PIcEF03hyui3JxwwUnzX4cy3CfU+M+RptPE9s68wIInJixUz7iZJNBIp izTcuAF1wqkwqKu/INd966MNNUHOet/HzvETPfA3lGG2wJXvpUaFq7PvOWmZef5Wx06sTv7G GG9swo+igKL6iTEGWy/q63bU6X1z/HTdDrurwOav/2vfUlzZzPuZUf+6fZqy1TRWc0bsy3Rj zYJNDpEbO+SswQBKs17wTWzUGMghdq1HAKxvK/MQcMWkA63At0PsJmbmjEw+uzWjYagLet87 ruryKntjFYdMztAAWFNHaPtYJVPDAez/iAyZOY3MNnA3RvtxcmCUw8iR5nApgYsXOxt7KZdE cwpW6PYWA9is7LkdfY8YwemYeFy9VPobdONH1MuJzhu5kdEA2egF8QZdAdR6sFLK7WUlb/Pr cnJsjGne1SOjXoJMcvsbnyQnRFOneeLHydY+kO7j2DX7waGPPYdohrnKSjM8fWMTyJ83eO+G v5SHfPHkJNfmIdORXcoEUjli3yzSzH5ZkH4XLF9eGQ+bwWAn3yIBTFZR4B3oaCzrmYlbeXl3 9/7z5fbDLAE0QNYNmbESkLnrSee3s25sqX25vf58u/vj9vydynr+HJHv0Ju1chQEXkSeaQqY UNzgyb2yLXM5rJX3hSxSCbEev91+PLICXthyYQahk32qFZHiVedDWWhdpm0rEa0KhzJYmUXL mrUvMbFzOr1NtTAE1FbEAkcbXU6gJsSyxOi+S+1ILnBgDNnm7IUbIjOgB/bMAKaWRk636yDN ORClmVRCMkY15qnmHIbmGgC8ESkOo6+LkxAFR17gUplFkUftJ8wwWbfIIlkUrSiTzTmOg5BK loSryRLROkYy148tUUPlAtaHoWdfLOshqR3H1WvHyb6hHwLZdSnuVtuomIHBsdz3XThc1678 MPzskCWeHUqZB8B1qc06ORd0ju+0mU+05bFpjo7LQbs4Qd1UvZm2y9OsJj01Jf73YHMkGqgP 7kPy8V4FJtZXRt8U2d7eZxlDsE139EyoU4shLu4Ju6MPssivfXJ1oadk8agno5kuspNiEMSm NpXeR76pdOSXJHKNSRKoISEso8dOdD1nNSkvEoqLKR4yJkLfTpLCCYZdlwX/kdCoCZzqyccC ZcG4mPmqvbb0okz2vRuGaIE0UijGM2AyND+xj4BQvEsznI7LBk328+399dvTv253w1moDcaO GOeXjmTmnpNAwVaOPdq1FLPFnnqYYIDIscooIHKtaBLHkQUs0iAKbSk5aElZ9yWaIxE2eM5o ERaw0FJLjvm2dmSoF4bkvKmxub4l+LjC9gBv13z0TcbMc5DrC8ICx7FUZMz04L9IwrFiSQPy /XWDLTK2dyWabTZ97NhbC9RgS0gRs/O4FqdVhXGXse9Nuj7qTB4tMcf8tS5sS1msteYuY1ol veeP2iOOuz5k+dj3j6UopzSx9uy+9NwgsolSDonr0/eNVbaOTfcfScE+vu+43c5W1EPt5i5r UHKPxGDcOtqDq+TUhmdJcwOST4r7H4/f/3j6QsTJy9VoGOwHt2qu+bakqL1Gzdtrehqn2MRq rTnK43P1RbWDvXmixsB0X/cyci7OGui77QKhnHd8v3z9/iDwQaTmK2vW/Loru9oSIfP/Gbuy 5sZtZf1XVOfhVvKQG+7LrToPEElJjLiZoCR6XliOo/G44mXK9lRl/v1FgxtANOg8TGL192El djS6h4JESSTnYA/2EXOizZ0OO09WQ0EDcNjxb9jaAp8pIUhv4Nk3DG9Z0t6ubKazVjNSwJwn TBlhgK2kFJarGGnSZbM/K6hzda/Kq6FkjVYyPixSpUrZJ4t2dmZ1uCxtHZEa3qgdYtQr5UTJ zjGVY6tIwd3h9LcIj+/fn+5+biq2D3+SVkQTtSOQhaSmrAGhHj4FJj3R7gsbgromdyu3Kxq2 SQ09JP1uWyZsHw7qMZYfxjpGc2aT2OWUd0WGxjKUDsl0v2RZzW2SpTHpjrHtNqZ4jz8zdkna pkV3ZJlgO25rS+STSYl4Cw99d7eGb1hOnFpsCW9gT1PnMGmWgnu1NAtt0fQjQkjZ+saM8JTT oigzsNRt+OGXCHUhO3H/iNMua1gO88SQ5/aZc0yLfZzSCp59H2Mj9GPDQWs+ITHkLmuOLK6D bTre5RMeS/IQs1kwxHiDs88ui8OF0QkhLgZvDdu9QXWfZd7ecX0bj6aAe+ksMJzgkGn0MgVy eQaPPX1TRtdTKDc0TLTB5uCzEcynk53h+pdEPpqYeWWW5knbZVEMfxYn1gxxizlCkDqlYGXi 0JUN6OCGuEE4IQCN4R9r3A1bYfidaze4ttIchP2X0BK8c5zPrWnsDNspUGWBOYhGpwernJrc xinr7HXu+WZofkIJLLwF12WxZZvvLWvnsY0yxrZGvdj04k8oiX0gaPcUKJ79h9EamuYm8fL1 yhK4QUCMjv10XCvZGWhliGxCNJ2GJumx7Bz7ct6Z2ENhgcnWJlWX3bAGUZu01aTZk6hh+2c/ vnxCcuzGzBJD08hpCh6RWXegje+jylY6rq6qRVIQYnahBTLcWZKodSyHHCu0GAPD9VxyzPEk mwoui9kmqmFd77PBZCA7ds62nuvl5dRqL13FCWh9ym6H6dXvLjftnmC0c0rZmq9sobuEVhji RWBjS5WwZtRWleG6keUv1NCH9cpiqSCmtq3TWHx/IEziIyKtNtKXj+vb17v762b79vjXw3Kt FMUFHVbQUnajA/u68NoCFoA2fknBl6jD/MVEBbe6o6npjMUGg0nWhJ6ptFFYW7Ao4gT1wAUL ffCtd0grcKQSVy3o1u6Tbhu4xtnudpdlfMUlm/YG2qzDurNqCttB1eX6eq1JnHQVDTx12TBB 6hTKlsbsX8pC6WJmaGiI72ZHoWU7amz8aWH/eTXxNYe0ACuCkWezujQNa7GQaEp6SLdkuEL2 lKXVAsfOsxGav5pIsIaKx5EcZTPWrnKWXRBsoxSeyz5joGxCIEgVmxY10PfpQOmVyNggRYrW s51FmiLqB22rQePFgMVdisRn3zVNLdCNKjLKnmgk6HQWpk6ZH+IqcB1vdYBQe7ccU9IU5Jzq BmdSR9X+JBcib6ki2An6LaAdDOJDG9iuH6sArKEt+b2zCNkOPnKLHAd9iDAy8pRNAfZNoyZd JxWRNr4jwOYoV1RWFeS+7S52ykvfo9KyLykavrnvbk5pfZzc5uze7p6vmz9/fP0KDjiWm9Ld lm3LY7a2FMZtJuMKm7eiSPh7OBng5wRSqIj926VZVvfqljIQldUtC0UUgG3/9sk2S+Ug9Jbi cQGAxgUAHteurJN0X3RJEaeyZ0UGbsvmMCDIlwUC+x8akiXTsNFvLSwvhaQmtwNvcTu2Ek7i TtRUg4RIdMzS/UHOPBh9HI5N5GhgHw5FZS1mj37sb6MLG8TLPAt/OicU2ykyCAwmjd59xCDU jPnrETxUus27fds4rrgiZ3LBJtssHJ4kykVNYOFW5skyWd0uHjC2dbGH54TjvQvW4nnht3f3 fz89Pnz72PzPhm2qVE+VQ7yw4eL6nopPbkAyZ2ewacxq5AUoh3LKBoD9DrUbwQnN2XaNm7Mc Yz8wtarQFm/MQNjEpeXksuy831uObRFHFqt+mEDKNgu2F+72oq3cIeeuYR53hi3L+8FUlrGd pc3GUcme5tB0NdU248cmtlwbQ6Zn2QoivTKZxUu7KzIiv66YseGZFjrSzyyu3H7B7YrNrOVL 6BkhMbxUMvAscNDHD/Nn1op9TKFqZrMWWEL9S9fVGPhrRIPgEXAQ13YRSGwxgNqFFLIJLgFr tMEIb2EUDDMDOZVtYUxpRhZGn+Z8nl3L8LMKL+o29kzUUoqQZB21UVGgcSeSF7xPBpoxPL/0 xQd4ONEVel25L+VfHT8PYrNDgQPnPZFf2glYlJ0aa2lYYMi5cvExxk3LUyFM93Txo1v4DAJR FeWKoEuyWBWmSRSKT+tAHuekd/6lxlOTS57GqSz8g30MscAgKymFSw+0AY9p84wj3x3wQz0W Swo2OHzqXxBgF5xAGt+nsNlv+VIB4HNSb0vKClenRYPZPOcJLRyvjaIx9DLSqGHbfQIn2str HjHlyXebFJYmNyewg6eri7w6OYbZnYj4FAcAEoV+v0Ve5LR3Kq1U3inPUT9nEFVWltUyQN5U BLc21mebuyU+mZ6LKh/MWUdyPRjJln2BqeBoQPS/xuCYK/6Na3CKSheTTGo/YGgbvKtnJVxL fUn+6zlSG6lSpTNEKVHaSluV0TFBLeRBoJjv6URXlzzyMlIEfcmkh5cjMlryXOl33BhoWZVs LLlVmg9EnkPVYUaZeKVym3NorvL0WJfQF8qmlNFtlHMbialFu8shpU2GdMfZGyajian3Sjev 0fAE4evrG1sdXq/v93dP101UnabnJtHr8/Pri0Adnt4gQf5PUsUdCgBe/QitUW+KAoUSZRwY ofxGO5CM8Z/YnNCqlccjpqkGqOJUbRccSvrcYHlJI7b3wnKa5i3Px6lFZ4/VqhZTgs95SD3L BLMvSGNM8z0q5AHTQo8tTMaKMByMZRlslk+6njRSea316aBR9fgiHjxR1mThfLDsvYMXYI2Y rDWTvDl22yY601gtJC130P+y5JxkOFrusCwDMvieq8st+tpNprL4yypB3xmKxKLkw/7qY0OR D87cI7aO2oILwyQ64hdNSq7XszvufWmTP96/vfLHb2+vL7CGobBR2TDe8DhDdDs5tth/H2qZ 9mCQtm+/Su4HlI/McAKRcyvkqwUegvDGtVLmttlVe7JM90vLNoeoD8+xNcIR3zTnDIMYnGsr CpvSXIFM7Bxjc053atIMLTygJn6ZI1NaE4/alNT1lsjSzpSCa7y0CrThfRGGmGagR7rDZQWU 3j1M6NExxetzUY4mdXQcN0DLd3RcF1dsESieiV+KiBRUoWomuLZ8qC0gLvq4YSJkketZtlqo bWwFOMC2gFGpyiNqu5ms5y1DmIKuzHD0gbHzGZmBlj+ijpU5uIEmieOaGvu3EstH6gMAG2kt IBeN/Yly8TWXJEf6UC/X9aAB1VlrE2ltG2hNtgk829SYKhA5mpN3iYIfQ8wUeAqr2wBwRst2 /xayfoqJb5nIl4hln76DFDbm06CoZCOhvmmv91BGsT4pb0ID28QuGkSChQ4RPfJJ4xtIS+fN 40agyT3Ny41pLimKEly6GzauqTzyJoNWrI+vrXlIGwZGgIyFHLFdX9kSTaBrrFc3J3nYwY7E CC1fm4Tt259UaE8LkW7YJ48BNA9C0+sucCjLL/TWOYMlCSyTbJ9mesHaZAsMPwjVFAYAn7g4 GCI9ZgBWQ6l72xGUDKIsAN24NMLrEztj2YZ86rqAPvmOI0uXd9YrA6JHtBXSo7pYXdP6Rwto 4+SgpguzrmlbuLL7RGlcz1zvvUCx15oV3TeZrEI4Iek+JzGt9AhYksmJctjTU7haAWH/5WZj 1ncJab0bVtk6NY2JOuyF1ThobtnonY3I8LAV4wDoPsQIrzc7xnJcDx2A2O7RRl8oigQXbfIU VBRQh9ojoyHUcl2kVBzwNIDvIcsTDvhoPhik8acqMnwTGRU4YCHtiwFsDYvlA2x9yEYTJmhH wsDHHsBOjNluBhLzDOJ9UiRomsNEsU30FlXlWS26ipUIn7Qumftpzv5FvuKoNR3sq1CbWJaf YEi/ZESTBszFFHtGBrdZgi2KL3ngmkhGQI59Qy7XxBPg8UiXTKLcQpYr3F6Khm+j/RsQZ22M BYKryZqLF9HH9gNc7uHyAOnpTB5gu9ZerpunB3R9mgZjzgae9VCTZIgtoUDuo92DI+vzH1DQ Z+0j4Utmy8YSJ4Cf6oReZaG7U1jx+eg7+4kBhiSRVjIZmFTjbDzPW99GFeQUuM7nnEDj9l7i aGwQy5y1HttUxGMbPyK9ZZWPmxbR9nN+RGrcNTdw+ll+X5PqoBAHmnq9AZYmy0OUyuo6Mo4c c4IYzH41dYpbEgPCKatSSE1LYH8WOjvCgHPPWQdCu0MUL1JXrjFABueQS0tZIK++/Xx/vL97 2mR3P69vmMJPUVY8xTZKUvwyDVDu1+usK1FDDudymbfp667kY5EIifcJfljc3FYa5UMIWJfs +9FL2kQHpD7zXHTjcalpctMluexUZBCrCkUTgwXolq/v+ifXefQ7jX8Hd1Obw+v7xyaa7bTF an1DPLrDa8BozNrknN9J1IEP8ihKKC1FdYAZr7Jml2NAyZbBNaFi25ZBWiVJrAObUFJ9lsD4 EuX0oDHOPxEHN2pr5e128H/ZAsMM5mm2TYjmTgVooyKZLolqUaEnFm/qsVZjyPLopq97KfID vdHEmzdHPMNtUqCX7ELl9TscRU5yzxUmujzJwSunnMwgU1vRYAHg+fXtJ/14vP8b6+5T6FNB yS4BF9WnPFmNRd+oxyEkucCQKLRK+LU0jDjLeuOJKJKfMpa7Miulu1xO2NagUFOwDtAdLvBS ttjLWli9pQkmQ4rNY8AUp2QGIY1poeaLeriwDcsNySLrhNqe5NOtl4ILaVstBtxba7bgM0Fj v6WvqdowTMc0sWmWE5LMdC3DlvbfHOCadKjQwoS2KvQcSykRiEN0KzrBhriH41LV7ToXa12/ 91GBbx9tsQF1lYJUrmSLYRS63NR5novOhSbMMtVCghi7WZhQD6mZKnA1B6YjHmhWbxwH69+4 Bt0ESw4DuHT0q9KQ5rTsfkvNyEnoqpmPSWRaDjUCXCWyz8EFu1jkEOKxpG/esRUYSFU1thtq 63cwPb+IqokImH1eSrPIDU3lmwtu1eSUR2P6K5+JdQb3H23eBCdlohwUWr1w2R5Tapu7zDbD VsnIAFnyAcBiVOP6E38+Pb78/Yv5K19a1fvtZtBH/fECL8/p9+v9I1tqHdJpKNz8wn7wFzf7 /FdBnZl/EPAOnSu56T1vaQudtewDL8oGfmLUeGAlfNvgi6r+g3H3W0NvXKENVsT1DLrPbVPe 6Uy117w9PjxIs1YfKZtU9gtdNBFQlQBxWsnmpUOJaY9ItLyJtSkdElI3bJ2DL3Mk6qRe+jk1 qk6fZYpETXpOm1ttzjT7FIkzetLm4ymv9cfvH3d/Pl3fNx991c8NtLh+9GaJwaTx18eHzS/w hT7u3h6uH8vWOX2HmhQUnrIse/tYTm6bW1uEihQpvk6VaEXSxAn29GgRGWhsLCeOqTplS8P9 mj3dwnP927FuWBe9+/vHdyj/++vTdfP+/Xq9/yapn+CMMda6idi+VXh8A4JxwTWVDYSHqClZ X0bLDjjDmvKAHRMCOuqZSkGKM1tFKr2MIZvH8W2X0M8gRFo0u96ZtpxjLpeshYvS7pQm3DbJ MgNgwB3di8F5J+RD0VwZQ6nuOSUEA8h2635JqI1lgmyT8gvqGGYitH2kalDFo9OCENPp/QqK dBHrDaca05gVifI5mIxofTwLNM9fy+ThNg9cz1ZrDVxYh5KzkRlYeMOZgdHhjZIPrRePEadu ZEvujQYgpZlpyQa0ZWj1EwwUNEstQzT+pAZGFe0CfM0oMQys+jhie2ij45j3abwB9lUcs5FN ecqIxqn3SFJ9h43AjW0dVfHgkAIp3sK75hQAcUcpYNz3xVoziMCVS4iFpmw/Exqo55OBsctB I0XNU816sInL3cDE+Vj7TnK2efQR/tk2sDoFuY006Rq87iDflsZsUAimGaZK10dC+OChpomE 2jHD0PigEymovzCB4CCpcjlSOSAP8QYLAwyqCzNVVOgb6Pdx+u+mjjKtZ2oOwaWBxlkbivqB D/lurFNapoXVeFT54aLBIDqZ8EXBnLg6xyGfge2t179Unxvcl7PUMsPIUqbZ6unug+1Dnj/P h2nhDtpmgmui3wIQ1NSmODUFbrcjeZrdamLwNHtXibI2fTOCbwWuJnrf+Tx+P/gXHFTpciZY jnj5NckXjuRFOT5x0OZo+g3Bj5bm/h80q98MCDZaJYCg91sTgeae5SB53t44i0OBqQ1WbqQ5 Qhkp0EpRj0QDvnyMKXSBhefvEflyW9zk1djxXl9+g13U6mg6nHFjJdg17C/c1uY8AvDX08jQ sHCKPtWKb/OhrX90xPb5tDe6u5pH4bn1lMk4J/2TXPV1DIO2p53qmofeFhG8wJffmF24HClj H02Xl+dEsR4wYKNhQ6ogbE9c0UV+JznfuiS4bd9F5qfN2KkdrL/MSR1ix/HFO354nUFolKbw pnkWV9yeQn/u3OVsTyf51K0Go3RlM2H/+c+cbzDsCC+kt1lX7nZocxYp2LmLgC/OzwdErKeT 5hgVXteP7++QNACWbYD0Ejjkws4RznEl+pg5lLTp0rLJtgvhkgPRLWVs770UnWkp330MYpYq XjoOR3VJ6XCdO1jGUO834G3H++vXj83h5/fr22/nzcOP6/sH9hDkM+qY5X2d3PYXzHOvaMg+ LbCbPqwvjrKuSivstuwADw6jTFhnsx+wTc7K8ngSrpNGIrwwrIjkc42fsQ2RzC1vkg5jJdb6 Zo7qmVQGQ0eeMQVU2cdhJJq6Nqr5suDIxvFkEL0ckSmOgxaAIaKWjIBEcZT4Bl5swEJLV+yI WoZhdPIDyJnIGIO3+vVMo16ABVz1KIpwRJMJgvwcuah88J2OYoO3tFweMQ4XtlItWF6PSq+L nl7v/97Q1x9v91d1nuJHrf1DNUnCn6aJKeQp6+JgWov1lMZzcK0DNC0hDpJm2xJr6Skr4EnQ /OjN/l5frm+P9xsObqq7hys/3NxQdbz4jCqnww/YdpNRnvr6/PpxBT9Y6Lo6ycsmYfWBe5JH AveRfn9+f0DWBVVORbfx8JPPJUuZMCuMKUkxCgMe2AK4pLV6ocxG8s0v9Of7x/V5U75som+P 33+FQ837x6+sruKFj7fnp9cHJoZXo2I1jKZxEbgPB6ekf2mDqWhv/OXt9e6v+9dnXTgU54Si rX6f37LevL6lN7pIPqP2R+b/m7e6CBSMgzc/7p5Y1rR5R3Hxe0Wskykfq318enz5ZxHnEGR4 i3iOTmKDwEJMR9n/6tPPmarA4PV5VyeY3kXSNtF8x5D883H/+jLY8lEVE3pyR+JoNAIhA4NB kCnlQTy6HdcmDwxbcrAzyJfnWqO4KWRvZoO8boLQtwmSBZq7LmrGdsBHnSxpWGSjA3ocnIr3 EexHx5bGO/mqbpZ2EeajS8DZ0hqLbTYPgKKgslEWoGtSy/hxl+44SxYPtylsfpkyK6D9n+Jt ghBGofJUaVfxa6SeYokUtnmZ7BJJNcKAIYCmSuZcJuf+bqofh+7vr0/Xt9fn68diBCds+2F6 lmZHO6LYHprEbSaZAxwEssr5KJRUnrhQPB0fBChLjm+bE1PcG7Hfveu7Kc9MgjsE3rJdrWvw +69MjGCWLpMSEClnMbHEPMTElswY5qSOxWVZLwgXAtNQvm4zJGaTNsWWTceWxtJhMhdodJh7 TCrRsY3+AOPgotOHyLZsSeuM+I4rrRsHkUZ3f0QX2vog9lCjoAwJJCtKTBC6rrnw6zpIF3GG +Blczh18CG2RCTxLHA9pRGT9I9oc2c7CkgVbItvPX/Sbvi+93LHZfvPxuvnr8eHx4+4JrkTZ MP8hjfQk7t8PsY6cNURs1L4RmrXUbXxT1PSH36HUN/6fsmdZbhzXdX++wtWrc6umayz5veiF LMm2JnpFlBMnG5U78XRck9i5sVNz+nz9BUhJJkjIPXfTaQMQRfEBgAAITFy9TCb+piGQEsLx ZomYkkeHE9rUuG/9rqKF54dtEooOtDHfgJuMOSudREwrhzRDzBv42/qgSUf8C6CmU04QAmKm G7Px93BmtDqbcQq2F8yGeh5W4HoV7EAU09oxw8dK9w4FhqnKPwGzXMrMvdqZN5oOqVVytZl0 pG+PUs/dbLBpztNf+u5wQgPAEMReCZAYvYKBAug1g0CXIG4fBDgOqZwjIcRHiSCXPQMjxvAL 4pF7zJem8fOBq/u0ETCktxMQNOsobJNWj850Ws/B5YncHbszc/hadOqtYb1x+0NpR6C3kEmV GfXuUEcz4/EkRuRJVEX2ExJ+Z3TtggEE64dK0UM4pctKBFJFTLLAjFgrZUN9o7xCAx1wH9kg h6LvOmZLjusMpnZTTn8qnA7XWvPgVPRH3e9zxo4Yu2PjfdCoMzJhk5muiSrYdKBbQ2rYeGp3 VaiQwI5+JKAUb+jYYsbj2B+OhmRH1Y5hWLrsHpTWEEAbK+VuMXb6tPn6NLJp1kEjSK4JDV2s LD6Oh3MvPDxrsgR1gyIECRaHTJvaE/VZ9f0VDjKWnjcddBTrWiX+0Ewz2R5s27ZUYy+7N3lr Qpn3dXlXxrCT8lUlwlToK1YhwsfMwsyTcExVOfxt6mASRrQv3xdTXd+KvFuqOgg/gLniYOZd MOhRVGAmYrHMu5I/5KIDc/c4nfHJpaxhUm6R/XPjFoEZrRN5kcRsLIG+ChJRj6KoP0WZMkTe PNc2qquVIm+fUhzNOKZcCFbrub7C7IbJY6XRGR5H5s7A1XNUJ9tXG+OMRarlyub1qlF/TLSl 0YDeo0fIlFM8ATF0DT1jNBzySgsgZuQto5mLcY4itKBGi6PZgDudIaZPOz52h4WtR43G03Fn WhNEz8YdqjggJyOiWcLvKf09Ngdg0lF/ClGTPh9pirhZ14nRrMd8YUBTUn0jzzD9rV6ZSwzJ RWlQXZyxfq0RdZmxHoGSjN0B+e1tRg5VbUZTXeiBbjGcUKs4gmYdtwhBVkAP+1PXDDon+NFo QuUqwCbkRFjDxvpxQ8kONQBaSvore0AFFAJjeP58e2uqwBlbXd1NlIkrrdOlhlPWAT4G06JV 9g6W0Vm9qXN77/73c3d4+tkTPw/nl91p/18M+Q4C8Xsex20iQ2kPl8bp7fn48XuwP50/9t8/ 0UGq7/fZyCW1z68+p6JBXran3dcYyHbPvfh4fO/9G977P70/236dtH5RKbkApZ1nHoCptfC6 I//f11yyfl8dHsIMf/z8OJ6eju+73smSuNI206cnKQSRoLEGNDZBrsk1N4XgbxpJ1HBEJPXS GVu/TcktYYT7LzaecOGoodNdYPR5DU6vy+XrQV/vTA1gZdDyociUNYVHYVTTFTReFTDR5XLg 9vvcprXnSon93fb1/KJpTA3049wrtuddLzke9mc6tYtwONRD6hSABMGhxbfvsIauGkVuNLPv 05B6F1UHP9/2z/vzT23hXRZL4g74eiGrUud7KzxJ6Mc9ALh9avhalcJ1udPeqlxTaS2iSZ9P fQIIl0yJ1XnFO4FlnPEiyttue/r82L3tQHH+hMGwdtWwb22h4dgGTUYWiCq0kbFNImabRMw2 ycR0QmoT1BBTgW3hHSbAZKMnJ4zSuyrykyFs/T4PNTaRjqFqHGBg343lvqNGf4Ji1RSdglMO Y5GMA7HpgrMbvcE12lQjn7pnXG8A547eXtChF4O/urwjs6Uz7PiPoBJE7HvBGm0tlM9iGVn+ PAEoTFnCceA8ELMBWZMIIakmPDEZuDR0cb5yJqwwQwSNuvYTeJhNzIUYmtwQIAOXt875eLWS 26KIGOuZJJa56+Uks6WCwAD0+yT1UXQrxq4Do9ORg7U5gogYxJfDpnwkJDQbnYQ5HVUW/hCe 4zodcat50R+xjKt5nXVltSxGtLRcfAdrYeizhae9zXDYN6xyCNFOJWnmYXTzBZDl5aBPX5HD F8irtx1p8iLH4fNTAkJ37ojyZjAgCWzKan0XCXfEgIysQy3YOOuUvhgM2cAYidEdRM2YljBd 5HqHBEwNwER/FADD0YAMylqMnKnLZeW489OYDruCUEvuXZhIexDXgETR9FJ38dhhT6SPMGEw O0SrpOxFxYZtfxx2Z+WEYBjPTZ1bRv+tC6ab/mxG6k8ov1biLVMWyHrBJIIqYt5y4FBZniT+ YOR2pHapObVsqMvB1UzzKvFHUz0s30AYC8xA0ux1NbJIBsTITeF8gzXOECrsdKiJ+nw9799f d/8hJgtpuFlvSBM6Ya2bPL3uD9Yca5KMwUuC5iJp72vvdN4enuHYeNjp2lrUpPQu1nn5C/+x vBKn+a3b9/NvqQXiAZRLeRVge/jx+Qr/fz+e9nges1er5ObDKs8EXfS/boKci96PZxDle9ah PbIqQjbaqYBtyAsutBQMWfO5xNDrGQrEOaHQmNDXMyUjwBkYFoiRCXDIfZ4yj03tveOz2SGB 6TnTVBNJPkPfFR+XzD6tjtEfuxMqTQzLmef9cV9PfD9Pcpeqvvjb5CQSZgiBIF4Bw2RLT+eC SJxVTstYRX7umCcgzScUO47lszbRvNoMSOBs1EokRuMO5x2iBtxiqBleXoTCPl9KKKvKKgzh YeWInAZXudsfaw8+5h6oaGMLQJtvgAY3s2b5ouQe9ocf7PFPDGYD3mFgP1cvpeN/9m94IMMt /rxHFvLELCypjZlKUhRgXfioDKs7doPOHVc3Auaqylyjpi2CyWRIr3KIYtFnU4JtZlTF2cxG /b75JB8ujGpCx7WPu3g0iPuXhLHtwF8dkzr68nR8xSQLv4w2cMXMsOe4wnE7Nv0vmlViZff2 jhY2lgFILt73QJqECUmMiiba2ZQN0QCRjzVWwyLJ/Gyd0+saSbyZ9cesLqhQ+gyXCZwcxsZv zexbghSja0hCXD5fG1pLnOmIrxHKjUK70PTIZfjR3ie/KN/3SWdqLcRhBZNFabRSjy0FykQz AwqT2VamI6MPsTv18zgwu1He87WlalwVM6mLouK29/Syf7fLDgIGw53pwbZaRGyAkBeEhYeP aDur7iXqJdSVj/c1ilt2LqzutL3JPf+mMq46ABcNSwy2K4ssjqnCo3jS6qEnPr+fZBzo5dOa 4kKA1s6mF2BdE1mhtRPFvIqXCRJw520/qW6y1EMyl7aMLdZ3taoyKwqSUEJHBp2PCS++yygK F1aUbKbJLb6S4pJoE8b8VyA633iVO02TaiXY6SQ0+D1mAz6sy9zOvaf3wMvzVZaGVRIk43GH AEfCzA/jDL2FRRAKdk3QSdSexopY0A9WR9MGBH7A3iJLsPDsq2fe4fnjuH8mQjANiiwK2F41 5K0m42nWLJmswvhppqKogRg3IgIvaUxPq/ve+WP7JMWruSWFzkfghypRhR5LUhugRWDBV1ou B1BWxTOCFdm6gPUGEJGxVU41ojZ5jG40xFroJbli1MCqZckly2vRolzZDQG3WLON5SXvPW0J LKZ8sRzbQ9waYfOlRzleiYwtL4ABSU828wGy/k2yLFpiQ7Nr8W1FHQ4Z+eHQUpxbbOL5q03m diizkswseF/3ZlGE4WNoYeu+5JhER4nqwuhUES6jjNScyhY6hh19iQ8WMddJvSgY/JAZ/PAm WZoFtMYu4FRRwK4kQBqFimaw4WZ+SUQJP0vMF4l5iLHgHA/BrIAwLpuLWVg70tt3FOD4DxrZ cjJzNbleA4UzpPlAEN7xcYhqrzfZtgTuQkWU8QmqRBwlXelTpbUA/p+GPpd9A9ZEWpI1Afv+ du0FpP7S5VJUCUwWeHG5JvG96hbm5avlTUkj2dHlmEovVCg38x7TEEnOrw11XVQyhBnEEFZB +inQ8IDF6n0trDXc4MWqhbAh1RxvjVW0LHYUh3jx7YYcMxIQBxip99CBX+D9T794yEtj3wDi DlSLklMbFsK6n9wCtLmSIJnrjGvDsx9pYHUqKLyHkEQCVkrKL4fbdVby91u9dZktxBB6egVt YJtOQIcrqi77AOLOT+rGL6XNYNRi78FoWwno7dMLqRwvfOCQBhuRoCtyoG5EaYqn3efzsfcn rLfLcruoGrDK+U+UGNgBcQBq3WUSb8Ii1VebIfvVHzls5Lhod0LbPJFQV+DVDXSuM2lY3mfF jU6l6Rsx/dGWEf2yPx2n09Hsq/NFR2N+7NxbhtVwMKEPthgjizzFTTgfESGZ0sSIBo6zAxgk oyuP81lGKBF7d8EgcTq+faoXpDAwg07MsBNz5VvYmHuDZNb5+Gzwy8dJcK7xsNvd8JC7MkT7 RROBIS4SGS62ijexkKcdd8SfG0wq3miHVDKlQkcvm54YM9yAXR484MFDHmzNaoPompMGP+Hb m/Fgp6NXTke39ABthN9k0bQqzL5KKJeBAZGgkVZFlugJvhswnOhK/UBygYNKsS4yBlNkXhmx bT0UURxHvtk3xC29MGbPry0B6L433JOgbMcgzTuXjaRJ1xGnGZGPZ/sMStBNpOfKQMS6XBAN cJ1GuIRZwUS0HhX+u3v6/EA7opUZ5SZ8IEITf4OGfrsOUddCCchJrbAQEciHtET6AtQYTTaU xRpQQdNyoy8p1caCw68qWFVYoFWW+daFXuivUe2pgiQU0lojK67aBDZkwTVTizcGk3v62RGz EEe+1JawnL2qZv8LtGriy++n7/vD75+n3cfb8Xn39WX3+r77+GK9r8yS7CFjOqIQaG+Uilde wriVxcM3tz+cXiVeB1FZYdk1p+8OuyizBIiw3yLH61lxhma37l5EqYTA4W8dwY5MgaAslcqq hVbUz3g5aNJJxtZbb2gevMRjH8as7tC4aSoxyVBlDrL7FEN5OiwBS7oeWhDetEu9+nhBDjEK 7YmHJAlxfcn1ea11NdjaO8jd4gQO3KEncNhyH47lwQamRHsj4NEgHnsd2YWRIF2yNBqFiC4k 9OVNTtsW+2X/tv162v/4Qt/R0K08sarEyuu4dcZQuqYd/ArtyOHUMIvyPh85RFGw20o4h4FJ 9u3L3+/QkvGp9wU6hvIMmD1vuEKiIvQChkajgBVeeJEIzX42cJlICW9EsmtTWxfGWqPzB4x3 HVahV8QPKjOTwUbvEvKj8sqygGPAeh0FBiIIqg1iaS6qerSMvc65Vk1KEogPO/DbF4yyfj7+ ffjt5/Zt+9vrcfv8vj/8dtr+uYN29s+/YWbdHyh2fvv+/ucXJYludh+H3WvvZfvxvJNOwItE +teliENvf9hjUN7+v1sa6x2lwMKwCPlNlWbk2j4iMG9CHGO1Uz2zs7bdFQ3atDQSVoZ29KNB d39GezHGFLnt4Q3lYNbYhPyPn+/nY+/p+LHrHT96SmJcvlcRw1ctPXK/SQe7NhwWMwu0ScWN H+UrXQwYCPuRFU3kdQHapIVu4LjAWML2QGl1vLMnXlfnb/Lcpgag3YKfJQwpqGbekmm3htsP rEU3dRVEwpvHYWXki6uplgvHnaqE0RSRrmMeaL9e/mGmfF2uQPFq1lr++f11//T1r93P3pNc dj8+tu8vP63VVgjPaiqwpzz0fQYWEON9Cy4CwduHmuWWcJKi+bx1cRe6o5FMk6u8LZ/nFwxG edqed8+98CC/B0OB/t6fX3re6XR82ktUsD1vrQ/0/cSeBgbmr0AB9tw+yIUHGkbZ7qllhPlC 7d0T3kZ3zOisPGBCd81XzOU9FVQVT3Yf5/bo+ou5DSsLZsD9ks2p1XTDbiYu7plmsgWXWKVG 5lwXN8wKBxF2X3j25ktX3QOLifDKtT0lmJe+Hb/V9vTSNXyJZ3dulXg+85Ub+JDuz7xTDzWB VLvT2X5Z4Q9crmWJuLbsNxtknN0vn8feTeja06Xggn9l6fSDaNHd6JLl4J1zkQRDBsbQRbC8 pd+YG4oiCRyXC73W8Hqw+gUMCicHHrg2NSqyHJBrQqmnHHhgAxMGVoIaMc9sAVcuC5KdowY3 Sq4S+/v3F+L+aRmKvX0AVpURM6TzOLvvKCHWLAYvCeM4stm57+Hx3shdoOFG3MoCOGd3aiQE 0/WF/GsPnRcLj5m+ht8yLwf5msNZuPv1IrFXKZz3FxGz1Gv4ZQDUnBzf3jHSbV9fuTY/b9Fx IGs46GPG9HvK5kluHxkyjwCUrW1Rox+FlPQq+Gt7eD6+9dLPt++7j+bCI99/LEVS+XnBpvZs vrGYL408pzpmxfFUhfEEJ/YlDgTU9TdaTf4RYa0StHxk+YOFRVWr4rThBtHVmxbfqLbd3WpJ OQVWR8KmuLMFW0tRK+KdPQlTqRhmc4yW6LAItOzGuybT5Sk5ShfmweJ1//1jCweZj+PneX9g BCXeXuK4joQXvr2p5HUnJX6aoKdrNCxObfSrjysSHtWqg9db0LVGG83xK4Q3chDU4Ogx/OZc I7n2ek2eWju8/b6LbnmFSwB1K8PMplb3zIPUwiALkV66qCHz9TyuacR63klW5glPsxn1Z5Uf FmW0iHx0qLfe9Ivr88YX0yovojvEYyuKhl3qzYtsEq21SZOsuuNtE3nOwnbYO0vLNAyqPFRO ePSry65HmhjA+4B/ypPFSVYuO+1/HFR459PL7ukvOO1rIVXSTarbvAvi1LfxAnNsU2y4KQtP H0freYuikmtz2J+NiZ00SwOveDC7w1tVVcuwS7Eulyh54sbV/Q/GpA4K72I3cZSGXlEVmIqc RsB6MhCCi4mMQMXCrN/agDRhlqB9pX7+UC2KLDFO3zpJHKYd2DQsq3UZxcStXgT6ZoZVm4Rw 4k7moV6+VjkqPHI29+FMCVKLgBxjv8JG6lbM/Soq1xVtYOAaP9us80bDiIGNHM4feAVbIxgy j3rFfZc5WlHMWU8W4MZEPFBh4etFDqN5e0a6EGjHZnUO0riPdGhc2KsWepkGWaINBdMx0MRQ tTNuVSAUg9Vs+JClHrLUqH0x5BLM0W8eKxLypH5XGz0VeQ2TAak00LTGRN6YC3uvsV6RMM8A tFzB0u1+TgD/tHs29/9gWusY6csX1+qvDa/V1WZL+yvyQ0aKljKRoB5s4gmR+RHss7sQPqQg pQ88gWmo9fhYBJEMr2kIzC9Ak7uXS8VJYyCB9Bn4sVdgmOoqpOHUbQ1zWTECaRdZccm0epXK z9cMCWIxp73+sos5XvoPos4bAGIZK4u21v9bjfEs42yut4e/r+2MNEaPgM0MvTKDUzvZzfFj VXr6dffiFlUa7eVJHpEL8bqLrelslBAS+LEItOHOokCGgwp0cl4aKlEQ6cyu0Q9CmRjqFlhy HXGn3SoyBA/1NjRiW0LfP/aH81/qTs3b7vTD9ooD50/LG5nLnYgqBfY987ZAK0Bk2DM6YmMQ XHFr0p50Utyuo7D81rpsG9XGaqGlkE6huiNBqKqCXNbTQ+rBRHauJ4I30589JHP0f1VhUQAV ySPXOWLtwXn/uvt63r/V+sBJkj4p+Ic2vpojCnuABxZW7tQHo2SNZopVSPPy1zQL4Blhde8V KfV6w+rJgYNgxHxi3PfwAtmsJxL2rasQPeICPd8lzDHL8LDboGmhCoAxdYlX6izNxMjuVVlK yz2pVoBn+KCHrlP1iBdHeO3Z5S9F6I/ch96NzAxtFEq9qGv/dEL+pdcJqDdLsPv++eMH+rSi w+n88YkJMWg5dm8ZyRqcBZfsvO6oXhenhkhOdo//MmMhpJdEEiQYO3xtEJqW0API9ECWEpH8 92YZEPaIv9mG13Ph8X7AfzQ49EsxeFPPiaugGH/ZHDFq52LbGIkVxe0P+j7mHWRr6qjmkMyU DBTR7CHLrSbfkGeRyFIjmoNiYHxBN0z5wGOD9DEsMntWs/kfIe+JqPeRdOSuaVUiAfs9qFFh Gqjtb37lXWK/7S6RtvqOmKWWppjbjVX5chF7S2E3qhLUS9cxx/B9KeNvPBgnxhigsBh0pIZT jiYc3NA5X6uJpsP5sibMnoiVcetNeSSQvpcd30+/9TDP2Oe72uqr7eGHLtCwljD6vjMSqU7A GBe/1gweCokyMFuX37QgFpEtSozFWedtUuOO7YrIarXGgBZPcDz8/hY4JPDJIFvqg3H9q1RI G/C1509kZnQbNe53Bm2OKH7aTRjmxulTHWTRM3fZ7f8+ve8P6K2DDv1fZde20zAMQ3+FL+gD f1CFVipsRaQp3Vs1jQghNCbRgvh8fGlG4lwk3qbEaS52nGMvjs9fq/2x8MOup6qqvOzP/Flt 4NwyzaFJiFMqzYyUOG5boNDTIC5wCwKGc2DyweSyW2ELQGCPaJzNjMIagLMI6GZpc04TD7OE NQfVxu0dWvvH6l5FBU9S0Gzz2A+A70FHsC0od/MDax2na1mU3ll9vxzX4w3q7RP6LhbJOfSD RPp0K5SMTHtVuJJiJzqRruxKQ5qxn+9qUyMEwyc3onioYB9kBh+OU2lYk9509e4vMY8ag83h UHTIFAeO1DjT+8GJ8pwYYJ1uWq9dQg7oA7oWiQahsHkaCtEV4eDlCoPeYCykc+niqUswY0Q2 tqHGZyvjiJCPt8tymz6R+TIWQ+7kUGVb3/QwdllRxFF7qcu3/Ty+Wu/27dh3wYpSgUuwlJgV 10s+cGlzoLlFfBBkuIVor6fsw01w0QYAi7br7xnPehZbCxwvUftWuOH4vCIV38Lye/KCkLod Aw0CNMnQpaAxufpU8KeRpPDgadjPfq/cvef8QQ8HuHp83mRLxAQDaEV3IS4tqtVM9kHAE1IZ FiUlunDGluwv55fS0Vl4AQA= --7JfCtLOvnd9MIVvH-- From mboxrd@z Thu Jan 1 00:00:00 1970 Content-Type: multipart/mixed; boundary="===============2094385740749792558==" MIME-Version: 1.0 From: kernel test robot To: kbuild-all@lists.01.org Subject: Re: [PATCH v2 13/13] security/integrity/ima: converts stats to seqnum_ops Date: Sun, 15 Nov 2020 00:11:46 +0800 Message-ID: <202011150009.G3K9oqp0-lkp@intel.com> In-Reply-To: <581db581b900a01887ecfc3ec6b92e19d54cd2d9.1605287778.git.skhan@linuxfoundation.org> List-Id: --===============2094385740749792558== Content-Type: text/plain; charset="utf-8" MIME-Version: 1.0 Content-Transfer-Encoding: quoted-printable Hi Shuah, I love your patch! Yet something to improve: [auto build test ERROR on staging/staging-testing] [also build test ERROR on integrity/next-integrity char-misc/char-misc-test= ing usb/usb-testing linus/master v5.10-rc3 next-20201113] [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/Shuah-Khan/Introduce-seqnu= m_ops/20201114-014959 base: https://git.kernel.org/pub/scm/linux/kernel/git/gregkh/staging.git = f4acd33c446b2ba97f1552a4da90050109d01ca7 config: nios2-randconfig-r023-20201114 (attached as .config) compiler: nios2-linux-gcc (GCC) 9.3.0 reproduce (this is a W=3D1 build): wget https://raw.githubusercontent.com/intel/lkp-tests/master/sbin/= make.cross -O ~/bin/make.cross chmod +x ~/bin/make.cross # https://github.com/0day-ci/linux/commit/b86077d3629fe6d16070d95b8= 331344258dcaed2 git remote add linux-review https://github.com/0day-ci/linux git fetch --no-tags linux-review Shuah-Khan/Introduce-seqnum_ops/20= 201114-014959 git checkout b86077d3629fe6d16070d95b8331344258dcaed2 # save the attached .config to linux build tree COMPILER_INSTALL_PATH=3D$HOME/0day COMPILER=3Dgcc-9.3.0 make.cross = ARCH=3Dnios2 = If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot All error/warnings (new ones prefixed by >>): In file included from security/integrity/ima/ima_fs.c:26: security/integrity/ima/ima.h:178:18: error: field 'len' has incomplete t= ype 178 | struct seqnum64 len; /* number of stored measurements in the li= st */ | ^~~ security/integrity/ima/ima.h:179:18: error: field 'violations' has incom= plete type 179 | struct seqnum64 violations; | ^~~~~~~~~~ security/integrity/ima/ima_fs.c: In function 'ima_show_htable_value': >> security/integrity/ima/ima_fs.c:48:52: error: implicit declaration of fu= nction 'seqnum64_fetch'; did you mean 'seqnum32_fetch'? [-Werror=3Dimplicit= -function-declaration] 48 | len =3D scnprintf(tmpbuf, sizeof(tmpbuf), "%llu\n", seqnum64_fe= tch(val)); | ^~~~~~~~~~~~~~ | seqnum32_fetch >> security/integrity/ima/ima_fs.c:48:46: warning: format '%llu' expects ar= gument of type 'long long unsigned int', but argument 4 has type 'int' [-Wf= ormat=3D] 48 | len =3D scnprintf(tmpbuf, sizeof(tmpbuf), "%llu\n", seqnum64_fe= tch(val)); | ~~~^ ~~~~~~~~~~~~~= ~~~~~~ | | | | | int | long long unsigned = int | %u security/integrity/ima/ima_fs.c: In function 'ima_show_htable_violations= ': security/integrity/ima/ima_fs.c:57:1: error: control reaches end of non-= void function [-Werror=3Dreturn-type] 57 | } | ^ security/integrity/ima/ima_fs.c: In function 'ima_show_measurements_coun= t': security/integrity/ima/ima_fs.c:70:1: error: control reaches end of non-= void function [-Werror=3Dreturn-type] 70 | } | ^ cc1: some warnings being treated as errors -- In file included from security/integrity/ima/ima_queue.c:21: security/integrity/ima/ima.h:178:18: error: field 'len' has incomplete t= ype 178 | struct seqnum64 len; /* number of stored measurements in the li= st */ | ^~~ security/integrity/ima/ima.h:179:18: error: field 'violations' has incom= plete type 179 | struct seqnum64 violations; | ^~~~~~~~~~ In file included from security/integrity/ima/ima_queue.c:20: include/linux/seqnum_ops.h:40:27: error: field name not in record or uni= on initializer 40 | #define SEQNUM_INIT(i) { .seqnum =3D ATOMIC_INIT(i) } | ^ security/integrity/ima/ima_queue.c:37:9: note: in expansion of macro 'SE= QNUM_INIT' 37 | .len =3D SEQNUM_INIT(0), | ^~~~~~~~~~~ include/linux/seqnum_ops.h:40:27: note: (near initialization for 'ima_ht= able.len') 40 | #define SEQNUM_INIT(i) { .seqnum =3D ATOMIC_INIT(i) } | ^ security/integrity/ima/ima_queue.c:37:9: note: in expansion of macro 'SE= QNUM_INIT' 37 | .len =3D SEQNUM_INIT(0), | ^~~~~~~~~~~ include/linux/seqnum_ops.h:40:27: error: field name not in record or uni= on initializer 40 | #define SEQNUM_INIT(i) { .seqnum =3D ATOMIC_INIT(i) } | ^ security/integrity/ima/ima_queue.c:38:16: note: in expansion of macro 'S= EQNUM_INIT' 38 | .violations =3D SEQNUM_INIT(0), | ^~~~~~~~~~~ include/linux/seqnum_ops.h:40:27: note: (near initialization for 'ima_ht= able.violations') 40 | #define SEQNUM_INIT(i) { .seqnum =3D ATOMIC_INIT(i) } | ^ security/integrity/ima/ima_queue.c:38:16: note: in expansion of macro 'S= EQNUM_INIT' 38 | .violations =3D SEQNUM_INIT(0), | ^~~~~~~~~~~ security/integrity/ima/ima_queue.c: In function 'ima_add_digest_entry': >> security/integrity/ima/ima_queue.c:110:2: error: implicit declaration of= function 'seqnum64_inc_return'; did you mean 'seqnum32_inc_return'? [-Werr= or=3Dimplicit-function-declaration] 110 | seqnum64_inc_return(&ima_htable.len); | ^~~~~~~~~~~~~~~~~~~ | seqnum32_inc_return cc1: some warnings being treated as errors -- In file included from security/integrity/ima/ima_api.c:19: security/integrity/ima/ima.h:178:18: error: field 'len' has incomplete t= ype 178 | struct seqnum64 len; /* number of stored measurements in the li= st */ | ^~~ security/integrity/ima/ima.h:179:18: error: field 'violations' has incom= plete type 179 | struct seqnum64 violations; | ^~~~~~~~~~ security/integrity/ima/ima_api.c: In function 'ima_add_violation': >> security/integrity/ima/ima_api.c:148:2: error: implicit declaration of f= unction 'seqnum64_inc_return'; did you mean 'seqnum32_inc_return'? [-Werror= =3Dimplicit-function-declaration] 148 | seqnum64_inc_return(&ima_htable.violations); | ^~~~~~~~~~~~~~~~~~~ | seqnum32_inc_return cc1: some warnings being treated as errors vim +48 security/integrity/ima/ima_fs.c 41 = 42 static ssize_t ima_show_htable_value(char __user *buf, size_t count, 43 loff_t *ppos, struct seqnum64 *val) 44 { 45 char tmpbuf[32]; /* greater than largest 'long' string value */ 46 ssize_t len; 47 = > 48 len =3D scnprintf(tmpbuf, sizeof(tmpbuf), "%llu\n", seqnum64_fetch(= val)); 49 return simple_read_from_buffer(buf, count, ppos, tmpbuf, len); 50 } 51 = --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all(a)lists.01.org --===============2094385740749792558== Content-Type: application/gzip MIME-Version: 1.0 Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="config.gz" H4sICMP5r18AAy5jb25maWcAnFxdb+M2s77vrxBa4KC92K3tJJvkfZELmqIsNpKoJSnHzo3gOtpd o0mcYzvt7r8/Q1IfpEQlxSlQNJoZfg2HM88M6f7y0y8Bej3tnzan3Xbz+Pgj+Fo9V4fNqXoIvuwe q/8GIQsyJgMSUvkRhJPd8+v33593++MsuPg4nXycfDhsZ8FtdXiuHgO8f/6y+/oK7Xf7559++Qmz LKKLEuNySbigLCslWcmbn3X7D4+qrw9ft9vg1wXGvwXXH88+Tn62GlFRAuPmR0NadB3dXE/OJpOG kYQtfXZ2PtH/tP0kKFu07InVfYxEiURaLphk3SAWg2YJzYjFYpmQvMCScdFRKf9c3jF+CxRY8i/B QmvwMThWp9eXTglzzm5JVoIORJpbrTMqS5ItS8RhHTSl8uZsBr20Q6Y5TQjoTchgdwye9yfVcbtw hlHSrO3nn7t2NqNEhWSexvOCguIESqRqWhNDEqEikXpeHnLMhMxQSm5+/vV5/1z91gogjuMyY6W4 Q9bqxFosaa62sJ1ZzgRdlennghTEnlQrcIckdDXgNwrhTIgyJSnj6xJJiXDcDVcIktB5940KMNtm X2CfguPrn8cfx1P11O3LgmSEU6y3Medsbu23zRIxu3P3PGQpoplLEzS1Fp8jLoii2+u3Ow3JvFhE wlVD9fwQ7L/0ptufEoYNviVLkknRrE/unqrD0bdESfEtGB6BNchuerBZ8b0ysJRl9gSBmMMYLKTY o3/TioYJ6fXUfcZ0EZecCBg3JfqktIsazLFpk3NC0lxCV/rAddZS05csKTKJ+NprMrWUzdMqwXnx u9wc/wpOMG6wgTkcT5vTMdhst/vX59Pu+WtPSdCgRBgzGItmi25JcxEq48AEbA/4cpxTLs86pkTi Vkgkhb0kRYSdT9BaN/DoWEus6nHcdpRZ8/M0zQXthoeP9uCGVKB5QkJ7N/6FerQaOS4C4TOrbF0C z54kfJZkBfbjW5cwwnbzHknpS/dR27mHNSAVIfHRJUeYtNOrV+yuxHWEc5rNrAHprfnDpsQEhcT2 /QlTrSPwDjSSN9PLzpxpJm/Bt0akL3NmdCq236qH18fqEHypNqfXQ3XU5HqeHm7rABecFbljUeAN 8cJ7MIxwKXBMQp8zNeychk5/NZmHKXqr1whO3T3h4/2GZEkx8fQMhtc3/b6Ido0+G2LqmNYySCLL C0FYApcLJ9EesZCizISnIwhLwHBEBeF+WVBQTzYj0i8Kmsa3OYPtVy4QkIKzfr0ROh7rFfjWtxaR gNWDS8NI6vM6wimXs47JlT+xvFKiXMxSR3Fu9aG/UQr9CFZw2BsbM/CwXNzT3LsrwJsDbzbGTO5H bAV4q3vPOnUb5rgORTn3i94Laa1izpgs29PZWQ4uWQ4xh96TMmJcRTH4T4oy7AUSPWkBf1hD5FH3 YRxa952CQ6XKWpytXRCZKhcN+wTYKxnd25rfdRfFKDPxtAeSTPz02aN2L3aD3mHp6AgQSFS402m5 UQF43NM/yZmeYLc4ushQEvl8iJ5kZO2ORiVR6DSPwUV52iLqWAAEt4L34lrLROGSwlpq7fm0AmPM EefU3ZdbJb1OhV89eeTbL4cP5y1hKPTylRHo+OpVDcyHhCFxVJHj6cQxcu326/wprw5f9oenzfO2 Csjf1TPEYgQBAatoDLjJjhD/skU38DI1O1Nq9NCzKyffQBKSlVsvWyRoPsIo5j6LT9jcMQRoD/vE F6QBJv7e4iKKIOvJEQjC3kAyA57Uf6IkSXUgUCkejShIUhfPAjqLaDIwq1qPbrbWxhLKhOVdW9Qt inRIje8IIF7pEUeQjXDw1QbuOYCZspxxWaY6W7JtwIEDHSSfTiZeVQFrdjHxqAYYkCH3gD304pe9 sbJpE6RirhCx5aUYxAuY76q8B4zOOAChm+l0YJAdXlHzzx83J2Wfwf5FlQTUojQ9rZ72hx9qCgpl HjtMqRWvTrL2XDeT75P6H9MurP7egaWfDlVl68e0CuUcMsIyj9cAxcOQe/XViZoIqIJJMjiP2W5/ DCgNds/H0+F128zd6UNnvBwgjk6+py4zvlNRohRFrrbZ2nmLu7LYvfmBQEiXDd+XhmmxCNKVkSEw Van4/D12xm5q1eINYE57RzqfUACOScGawS5KQaRKPXz+t1ZtLafC6eT7VWdWDlsVVhqZWU+EOj0o k+2sbGBQxswO+211PO4PwenHi8lkrGPUhIfUyhEyrkCo6G8bHNhFliovCTCpPZnzPSy0s+BOMWmo 19E3od5m5ghyw1p2VG0a04AEJOpRBErWpn9hTL9b/Rvr1BNDD3+rUPDQFp/s8KmAUKhBD3Oha320 vmxeH0+tBQSg5mDT9Le1K3uNLoLNoQpej9VD/2jcEp6RRGkcDshClaDq03w1cYtzjrgruvWKAkRw xapGrFVSTwdOTW5z2H7bnaqtUtmHh+oFmkDMtPa2cYEA7yMrz4vRkpgDr9PKmDHLM2q6qhlCvqRb Fpm24LAncjabU6m2t7SxJOhogWSsUg9YG8oWFgpNWVgkRCiYUZIk0ijfSu8XUqX0ZQJxPRE3s65M qWO4GU7BM6uCCQ4DhiERBEqqzDyKnGwWcisLJLSlpQVmyw9/bmCng7+Mm3857L/sHp0CihKqt9JO ud9s24/C7+xPmxFA4FTQlViT10hXpApZT63U2GjQD+7Uen2oVGRTO2UyviqnGWysVpGp6Ll8TlBY 89/iedvecQoYYaSxzaxb6z0h36vt62nz52OlK/WBhoEny4bnNItSqezGwuZJhHspaS0mMKe5H43V EikVeAQzchIWae7FV2PTtGFAunnefK2evCcxSpAEOGDhECCADYdEo4TUqTbnCVh8LrWqtHs/d84E rqFhc34UuuREhUen2JfSBUeu6K2wZtCU1FIYHIQzDTZuzifXn1pfRcDRQs6oz9ut1RQnBBnn4CSu bu5cU+9zCCu22P288GUZ92cRSyxfc68PAXOK7g2t9Rkw9Xws02qFVenSK6HKv0Z9yh3e+kuREUcp AVSurkscPE64Uouui3p7XxR5OScZjlPUT0Nqoxq3m24H2rp/Vp3+2R/+An8ztC6wiVsibZNQ34C9 kGUPRUZX7heclrRHqZt0KoIZ+II9kequCMIEVqvrlZQ0C/Cr9tqgoLS/R50opDRSJ7p9Uhvpm/WH BD9Xp/8oPcAJhKxwcE3XTgFEdWErKuEEzIukn3W1G/BenxbukL7EX0jr2C4Qt75S/dE5H07DhQ82 LROUlVeT2dTypx2tXCztTi1G6jDMivvfJWeFo90kwc7HzJ4iJJ+JL46sZhdWI5Q7mXAeM7+FUEKI munFuRUKWlqZJfUfuihFFVZFjpewZFWtlPhPcIqwEfLjViKHNePOSrC/BhBmQtU8mbp39F03gikg 5SyXdtBuaM2fS2fzO3bmjz2WhPcybUTszemZOp1lPEaPHsrg1LeMhLF8jrzwYkkh3jBfry6ju5rr dkUnCP1B0zzxr9oUqWNfwi8s4/7MpeOg1TcgKV+s0SxZZG7jMo2pp8qvhs859V09WxI4gfSIhs4y S74q54VYl3Udstmiz0nPqQen6lhf47W+acDqMexA0OH7lKNQVyNNQrnZ/lWdAr552O0VXj3tt/tH K24gc7Y7FwDfZYgU/k8gVfC7bM6soMGZIM1oaPVxdhE81/N+MDWOh8Pub1Pza1affyYqT7BPzxps pFTXFlG4cg9Oy4lDX4V3jVIbpL85g3bTkLXv8AHZyp2z7UCaY5+7V5zFndv4j+n12bVLooLJNukG QlPuCfuqUMJLMx1n9OVKtfKPH5JlXxyjBAO6leoWwBtnlVCUkJVnqAXvDeX2XL7JxZeX/mqe1kJE 1X8jv/NVEmm/d4sn/kCqYuIqlqSizHGKKXLptTAoHvXX17ByAAHqFmVsOBa54NkilljYmwkZVLBT Vekvm23V28yYnk2nq/4cUpzPLqarcT0Yfl9Tze32cEzXHiAO1FeUzhsFj+G1B86++FdVchI6nhNo PFJu2xdfQD4judsBEGAVZQvm7J40M+dMsprv7zQWvXaJ/1mN5oS+uh1wUhHpl1luT56I2jEF5JLq VVKvTUSQLDgZhllTSXt8rU77/enbuJeDFWE6l8J4Y4caymTap83lGR7QkoJgxMPe1ICzhH9HNMCX SU9ekUo1j5EW8raeZGs6o8trcyI6L7kqSHRTvqOcAMFDKc2ONFT4Kuvk3SaJfN2jQMy1IBaOFgrp TZ1UQ4PIqX5VlkIq7T9hdUN1RkjCVDp7h3jWL/4O5TEBHNPcxJQsK7z35I00J58LWLC+YoSsmZNF OB/OXpfAujphOIePtftooZuuSc/zN4etbdszEuYhGpbNW/adsys1jna029BKjlV5QEjYTt91pSVW z1ldx5vXIfunKvhnd6geq+OxsaLgUP3vK9CCTaBeaKqa7Omwfww2j1/3h93p25OdyrW9QyIZe/er lRhxCy1/oCq7b9FUAUwUGPZu/CzkKcVbY0Cyq0qosb5gMpX/ri8e3VLvhbqCiteWSzXfNZDu5daK MXBKVjihkW+AyHIu8AHYe0FNwmURM+zA35pU6uDj61J5on4DEYcJHvjLrNocgmhXPaor3aen1+fd 1lTgf4U2v9Vexr6Zgp4kjy6vLyfInaN5megMGYX+tx6Kl2cXZ2clnXmfAKruZL3qAU018tJBHQMt rXLFGhvjLLrj2UWvM0OsR3FVKK8v4siLBf6lHtsykECQVBHXsGhkEZI7yIJMpbtx7YgmbGnDc0Dr krGkydvaeswIqM1xHbPa7xqwWW8HFKVUrxFKTIdXODn+sN0cHoI/D7uHr1V72aqL67ttPWLA+kWw wpT8Y5Lk9vQdcpkjGTvvgZcyzSPHAze0MlWXB96qD8pClAyfeOqBIspTCDDEPMcbLC7aHZ7+URdO j/vNQ3WwKsR3WiP21FuSLlKG6vmdtS0rcFftaNaaulb6JVhfH142bHuSqETfJ6eKztyE9tYS+8to M8okYXf6zVZTTreLUhqqQlh3QWILYfnIDYcRUFG+bg2xM2VLf7zP0/IzE+VtoV6k99+bd89pNLvu LR99mN4+gcgLC2M3dsCwSu+tZJgsnEK++XY9SU0zXqRPS4fEu+mAlKY2pmwGsS9kmg4xtjCIvtaL wVa0IUW9PQBmRDJsgiDxep+RA2gQ8etx6MZTtpJ2VTKNaa2wLr4aki+kNWDU6rlFMQycVl2Qb48f 7Eb7krwrwmfCCwpkW1fON4fTTjvRl83h2DxP6uRKxC/h/HE50k97fa5lnLUBk0VvtoXN0DfmTVsP KwRUqZa6Nhd9Nx+m7ghOF2WR1e+MRoqewxbqVo9lydqr/KFytHYK+DNI9+ppr3moJQ+b5+OjiUXJ 5ocTELQaWD5QjRqeKmwNBpki0csMzYttlP7OWfp79Lg5fgu233Yvw0xLb0FEXeX9QUKCez+DUHQ4 z+2vI5zJQA+6Zup5VmBJqUM1R9kt5DahjMup23mPO3uTe+5y1fh06qHNfDOlmYTUauXzWO1i0tA8 Nh00hvDlu6dr2IWkSc8SUdojsB4BzQUcPDs+vLFz5sp08/KiKphNTqBeaWipzVY9DeltL1MwZtXc 9vUOinooZdyua16GXD8jGFlwI8Qib5/691aQ/yXEz14QSIzoCC9XP3IIQ95j9+pXHa1EGcvWADr6 60uQ5G6d8z3tmeSrevzyQSVXm91z9RBAV6PVCjWMenwYJZC7uKO35PoGXz9PXPeV3Ukx6Ufj+gjg OJ+d3c4uPo1shxBydtGzPpE0i3eUDMTxcWTYYxvEujv+9YE9f8BKU2PwVa+G4YX185c5js1v5sr0 Zno+pMqb825r3te6yYgAQvZcZEYUcRBADLnWu9mEEe01ot2PTrw99XbIIzFbKSe58Oido7tSiYyq HnDNQMC888AYVPQVlBIcX19e9oeTfdnh47ZJj1KVFk5y9Rzyf8x/Z5AnpMGTuUL3WrQWc43pM80i ZkWAeoj3O/6pv0b3MYBF1iWec301rn5gOaqpYu5LGBUnXgMid4BlKC0EafsqgBcKyNYFzI6oXpdI TohDJIgnaz/rls3/cAjhOkMpdUbVzsyp8AHNgZ3w7dxCM/XUC5KMpYrw9uMXw1A3rA5N5Z3mgXGH 5hHvPx0152eZkkAMDcmhm0izO24taGq9JLyYXazKMGe+4ACZS7ruvXLC4vpsJs4nTpUMMHPChCoV q4WqBMH3FCsPxfXVZIYS+we3IpldTyZndm+GNvM9boYIK8CeSgkiFxfWzUjDmMfTy0sPXQ9+PXGu JeIUfzq78P8MJhTTT1d+ljIdWGIJ2Oqs/uWK/+H7mHdeqRfsq1KEEfGVZPJljjLXc+GZd/8JgUOc Wq6k2Q5NL5GcWQCrI14MiAlZILwekFO0+nR16VyO1pzrM7zyxa+WvVqdf/K0A9RXXl3HORHen6oY IUKmk8m57Zp6CzU/ka2+b44B1Y+6n/SPJY7fIBd/CE4Khiu54FG50gcw/d2L+tM+Iv+P1l12Dygd KQSZW1Ga4Ni5PnBOnIEiWNAmDA62TDHVA0e7C18Dq4g1SMVT6hbliLlj8B1FXr+U6RyBppTT2WQ6 Kl9OJxcWOq+J5uLYpWG7ANDQWHo9+f7dM2jN8d7NNINQsB1fl7MJOIpRhrm1bHZIXbj3lq2EIV0O IWKdQaORsnQtgRKEFfLQv1LvFmHMQQp/JcZun6J75rvrdWQGVcMyS9X/98AtYDbinwuUSRtK20yO /fSCM241Md9lNr+6si+brRZzzlCI7YRnfm65ljlOFdyygp75Lc/g9xBdjxiFJOuXWHxiS1r4vagt pV99+vK5ECzL/eGModS/gBFU5VT6lZ56neLrYNxgyD2OR35haUlFxR9UiuI9sQVji2TkrUkjExfo jgyOeM3U2fB7o6QkAUti/lt4W45i/i96Ayn2b3SgBQWkiW+vL0NSCY0sUD+6yVj6rs1k7wxzdXbt WESTeK78b/hqdu6+LQRnwvynKwfEAWB9cGVVs+HAJv1XBT45DgdKIO9Pcywh9bqMj4wkUCqKsSen rRAhn73LAGCKOMBkTvzsVDgIRaT4euR1R61ALYGvZ575qM6uzZsR30SwKo/ZF7U2V2rjcqYi0xRh tUPv6VisM5aDq3pbRUv34gY+S3WHjqlcv93wjt73vIehlHcXU+9P91p278d+NV2XiHUh1LswS4pm Q7mhFMrWI6ZjEOp76ltR7o+Z4E+d/3WLuAOKPVQCuZDkdLFQ9w6xT40RXRFdRmoq1ABuAiU6qN50 gTgNRzpDIc3K3hSayDnWZHV1dXn9aV43awJdHQf7nUEAvDifnk9GOgP25Wq16vWF06vzq6vpkHrp ETUPMHt6xRTCKOpPpo6GI3MJIaJ2K2izujwBg+jv0kr2O/k/xq6luXEcSf8VR+xhdiO2t/kQX4c9 UCQlcUyKNElJrLooPFXabce67Iqyq6Nnfv0iAZBEAgm6DvVQfgkgAeKRCSQSi40Gy811vKSfLOVU TJ8tBtdx3UzPt06ZMVxV1rwn3HX2lszF+oTrMK9GNvLgEggsOJh85K4uqZZ7OsSOP+o1eZiSEzJ2 BWiG93oSOa/bErEJXamDMr32mbW9mKrlOiO1nwWaKes4zGjHtcnb2I89Ty8FyEMWu66t70CyTUzk FUYUMcHEM9Od+77QS5Xm8J6NcK+Dv+0f/L6PkySo1Z3jvGyW2CQqEe0dNTtONNN1yIDi6cphm6Ir RJzKhuDpWLKFRQNgh1sjHUrW93eF4F16NUDsM4IfUUnNmpyhbB82jptoOTJq7ISbeS4EP7b65/M7 s0xvf+EtP1n1a30azQYBKiXxBPFgGHDKoJ6VY466ZCblfpKkzXrrfjrDrmOboRNzgn9mbxWbkf2A aExwbIFUtRb8fmDzjlKVAdWv0gCtbttCo0A9pR+HmnlDZdtXh2yq7+H17f23t6evt7tTv52Mcp7m dvsKcfZef3Bk8ltPvz5+hxs1hr1/qbAb8uwneMnp3VJIMBtwec1mlo/ZBuq6AOaoVbcX7eekGGOq ml6xC5e1cONTS+DG1zeZZtL1cOmww9kCWW94LBx1aklaw2kS0wlg3GmOkSQzMNFZrWXRZbU8LVwS MlrPhr+FfYdmkYki3YO3WU6Bs3eqAkyuerSLMGPIt1TTqR8wK/sM5ZuWXXPNPu6CdnNT5+r68mNG ueR/IG1d5CUb+mjU1kMUhj6lwqOUkxZA9+Mu1SeDbvBGS5QOlFAs8h/z9dSqpnKoZxfZxfWQ2z// Ldj1joAw7KRISjJ8zPL5U55+3AO4/lwcyW0XOXN06acMeTxI+qXyA7zPaLqaHi59SRvJ4BHK5ssd 2aJ4VtX9MCftpFLdHeEXbHX/d6zu8bdbvl9IK7/LtTzhPGWzIBU/QuV0I0d7gCKe5cv3n+/m5rCi brcnc///8PjjK/c/K39v7iAJinrQqcs8/3ll1kOrxsIRVLSDK0hyU1MwL4omxxix1oL94LRddiVK YS1KULmDAKKfNMn3aV3oG4kT7XrsgyAmv9HMUmnXIqUmQrXdHK6T+hric/zx+OPxC6zoxGHaMFj0 c1YhZk+AP+CW9J8vW2ZFiMBhiurCqeD3oMXGE3Q4IhKuXqhzLVg/6OG3VB6hMosJepeqyjOH1ciT gtCXO6MgHt01b+gFSIjSXIqu2VHu2AzfrohxuEAAjRzrFjNRRCorGzoU2cK2TTe+S+cgHMtJ0Rem LBs6shEXlrFs2TyRLhoxTHF3X4iOMs3YKQRjPF432s70Qt+QR59Z521GrExbippntuKMTpzZ73tE GDL2p62JVsdkzlf22pUVSVXrMDHaVqIJL71M6JUfcpWMciwa+gKeyng8nZn+RB2vANeZ1Qc0rPGT Wat+8P3PrXpWqiPYe9VANW94ZtBWn7SRvtxIM7/WonTIpu9O/cCDCAnfY3O18DLTokAiQoNsG9ah wNUDjVsGmM5gGD6wdMWZGrIMFXalMEMXC5SLxF2KKLnYkrAVMz3Lu6oKFBdHZqqZpQtVFIgkBKAa so3vUGfQE0ebpUmwcanEAvrL2gScpzyywU930ImHWcIWAfJCycOsVl2NWVuh097V1sRFS3d1Syhw 4Ohrsf0xd5d0ulf0pn2Zat9sywFLCMQ221HEVBVZy3gubF5bwW156RBL3+Uhe+/+8XO5DvXv35hl /fzPu9u3f9y+giX9u+T67fXlN/Dq+w9d7kFMurjrwjYFdCTrV8sLuJvGryas3IYFzqIu1KCsQDK7 KO/UU5D1v2ve2MBwX9StGtAFaA1Moz2msZadBcJId+8bA4CpxkNBB1EA2Ny+l1GG2LTz8vgM3+B3 1kNY8z/K/Yll84ZzNu9/iF4o2ZQvhT/Dri/1DkF+fNQ34Va9USMgSgcQW5/mLODlBd5euJHE5Qg9 HNKCQOdd6RPAYpuw1clWSedThgW60ACucDxrTBJe3hqNL8rCS4StnPXjmwzDAncCIXK04aEJqcwx wKkjv551ZbMsHaMOwGWTE6VdO5UX1ZlGjyXfqT8oJLgXBvfu6Rt0wIGHlcimuuITJEnUVlogNxmP Pm7Je9pQx1n1mRuXfeh4emZMyy3JkA/8K43YKwtoo+WGOMf4MMQlf/50fKjb6/6BqElamx6jvDso KwNhG3LRTuZwh6StDHchu9Sbno79oZd6AIeqCL3R0ZpOjl6dpAWnW+gyrCujD11TacNDd7DEt38O Pf6BVBphAffldHX2WZm/OPn5Cfy6liEDGYBuo24F492JlriCI5T6tp/yMxUcSJZVPALfPTdLUAET JDv5nJ18m+X1h7FCtkPLCnv98n86ULzw0GviFJAHjLSGmXp/ZcLf7tg0zqb4r/zyCpv3ea5v/6X6 wZmFzbLrust0DUwC1zl2/ZIAHToo/KDy7E5HHrMNp4D/0UUgQEzRhkiTKGnvR55n0vM0cUKCDsEm /N6JsdJsoGg611ET6VnLa6G/J2R0A8fiHTGxDPWO8omci03HKAo9h8q+TauadBWZGLr72AmolE1W VI25sdSxzvn2+Hb3/enly/uPZ3TaPt1tsbCYZVRNdjim+5SKebHULi9Ul7SJnvWbqPIDC5AocxOM L7RkSALTzvoBLrzKB3kCd46t2ey0pWdKUnYPeM0Q3U8yL1tMoPzx+FJEzYS5owWqmYnXM+VmyeHl 4oIaVvHb4/fvTCvmuq2hifF00WYctVuR4vaNoSUIKcylXoXzixbjTGi6A/zjuPTGuCo+qV1rnJ2u qavoobrkWk2qZl9m58yQqt7GYR/Rw0swFMfPrhfZiurTOg1yD055tietTAgoj0OQc7KpYaMmr/Pr TnqJ4iiH1GeczSJOvf31nc3s2lItr1G1QRDH1kLzY6sJv79cJyMTNQebSnzSAWmBvZFO5o0wOmxJ uV3tm0kl/cOkkTagGXUXB9GoUYe2zLzYdXTTQ2tAMX52+YcN25WfmyP95AVn2OaRE3jWlmewG3ux JiSsPYFnNIUwCG1ZVa2fbHwjUdXGURAGKz2cz59rX1SuHSY5MNqcrybmRFd5caaJjjmGtme5xdSe zIJ7rt5QnByH5kdm5MT1dPJDPcahTrxUG8d3DJkZPaR3Uzl8yrbuxtHrf6lj30UbrUQfmjXsD/oW m5XdkA7MOH0D37V5TiqjlT4tEwyZ78extZJt2Td9Z85gXcrqTh3Vi0ynW+vLbQSzsnj+2e+7Yp+i HRCZVXZ/Ug9e0ZbcxQXTwNBA3N8gYg7fQ1hMlyWJMKKvee9tYk/NekHcS62VIyHLqrMw9Hu0qUGI oorYPz/+ecPSSYPoUKh7OTO9R1vwMxnq4gQ2INbqokL89rolQCVidX1b9qEF8HxbuUyh/Kg437Hk 6us9QIGoHok5rE2hqdgERxRbRIpilwbiQt5EIjE3wsMS9xjZM2bVFc7C+F1AdGSnkKUdQ9sJCpt1 h1Nn4s9WpeSjEyprNWReEqh2kgLWQ+jjbqCiv1aAqUWZ6NpZYVfwWA3SQUcSZTKMzQXAHchaBa0i Qniw6pNeeUHVN/BacLcFHM2nUuVN8wwiz7IphPRZTcc48QIzuVhvrjCAT/RVCsnBU9LnYBAVxoAl KEW6xnFbx6GjrLOwG7LnUabbwAnVcHwySZoNcbIJUhPJLp7jIpNyQmA0hdRqpDKo4xDRCSE43TPp /bY3q4KIdcrszploSLp98MAtm3afmgpP4XHatdpMap5GZ5/bjZjuQRUsMeoqBGLxtDCaso7ThySS TyxMb2Zf1PfNBuLdEN+3nSCpRa1kC3qoF5mZYjN6KYo3vwlUgx+qNwkV2dxNEBEF5MXAD1cESxiE ZGJNm8VIQjQG6wEbNyBGBAcSIi8AvICQEIDID6h2ZVDASllpV+CILcUFSUwAfb31N4QYUseOzA65 T0/7Qkz1G2KU7Zsq35X9geqv3RA45MI8ldoNbJYITGlOWe86eJd9rpnVplo4kiQJ0OrbHYMhdOOV mfBwqWkfAFDGcHB1SZpCutETq+SBBw7KHhzp7XnDiSET/Aj+onIpk0/D1r0aAXFib3arRUKQC/68 w9CVZPjLiXGKkblvznAVoL1eyr6gKqoy7tKyE4GwVoVQk/BIafxRztUk9twJxlV5gQFOqfhfH2S0 CEflVNTw/kFp8yKRXLB5Ri/c3HpW+pBExPYy2bdKHhhNIrTtpmgNBN+09EsXK0U7lRQ9fuxEPjaX 9FNzwvfOJlA4mYkHqoojf0R4pdBr0xZHfrAA+TlEfsbuJ7eMLo/vX/74+vq/d+2PGzxH/Prz/W7/ +uftx8srNpHnfNqukMXA17RnaAtYA1GqibaSkwyBiGVbBWah+Ff1153b5JeneFTT1ywXkcVTUvCO K35EtC6OO8/d1hmRAexlOmFCdQyhJZqAvGBjAp/LsgNbhmqFabtnrY5yD5luxct6C05T+Ur2Uh+h GiEdQ38cyYLn4bpefDGc1sruh7YuM5csQWzhXS+55TkONmZSz9XxKeN+Cy/C9uVWjafFqOiH9JQ+ NFyvn7mXr4NYLMWAq7ieAwFjqowGiTW6bVanpBxb7bmjxS/sf36+8KcW7eG2drk2hQHFtDg4ldnF rmvSPKRawBcTu+Rk7BieKB28OHIMTxGOgT+ieCKgsYTVmrkOVZZTDiDAAZdBE2cc9fyZPhNEbn05 2/MeW88ZLZF6gUE/Jlto+CRToWt+BrzV4ezMpbZvZhQrsjM5Xk2Er9UvZMrO4d+KG1eK9j0TVYMK 8pGzNVEXiWhNZrLYBNdPiGeaT5Tkko+zArhPhwJO4vvrvte/Q+ayqWokifiEWQXMz9l6oZfoQh3K cMOmGmg4Wh0eMniysswo7R1AVg7yT4NMy4c+9DSBdT82oHE71DE+uiDbGtzchRCdVbf8JFU7t1io AUlVTwYWamJ8TE6P8U01nYEZZNSR4Yx6xhjh5CRazzSh7ytwfAh9cutkAhO9gSZFQZWk+MwdXC0R CGFU6qiCwbqIyzC3EiYKqK4EFS8d8oyFmOqFVam3YZcFQxBT3ZWj97HqecFJQpHQ8+mLzIh+hBnK TRSOtghJgoNHh+FDQh+Ok3pkFFsHZAQljt1/ilkvx++NbcdAto5d0qFurTJOO6sKbQBXMt8PxuvQ Z+gbAWoeMQpqHJFnyzLDqta7xXRKOClrbR+6jrqXIo4DXUenRNrYn44NdZEEPbGNB2WnAycreWV8 ar9FwYMwIMRAp5MzVRxOmsIl7qpw6PBSpeoB7xFG+0lKFjbd+ooeNGnIlDozYemJfvVEno0SA/NS uV7kE0BV+4E5YofMD+LE2tzaeS3PZ/II0jQ6cQ5PEs0ROAE2BcejT115BevAdSitZAJdbXFhplWS GD2NU21jhoHoaFnSfHekaFSPkIjtKs3EEjir2g8X0t4UXXOohQPDaPuCEwtY0trUOyfWEWk+6cR6 ZwwkEUikdp0rW8bI07RVc2LKvyv24onLpciZpB/iLICIMnNuqiFVr6QsDHBJ7JRWPMbtqcbnNgsX bD7xvaeZjzzDmtiZCrRH/g4IqlEQNg0KnYgWAeymOKSULswjbSsqhzzwyd6ssAjryZJejscqb2hn BZOVdRE4ZvuImxt/v8BkOTldmCbLbLWSRk9HEO7qShebTBmiWGGjrBY6myGW5CGtqSImj1yNNBaX LmOXHgM/CGgPI41N8zUh2CweFgtD2VeJrzo7ICj0IjelMLb+hD45btQVhRAIdJ6IUss0Fo/MGw69 LJ+WaxLro25RNqj0YvFcz4DxhFFIiaaYTUTmgAakOxbiMdyKdTT46HuDXRNu1mvBeUJyZlusKRoK yM9iGnw6pp74aVjs2POMPTpPaZnruhbmiEjTBfOwytIFtC5raxprg40bWopt4zhIPvpEjClcn/jq 9iFKPPoLMdvTNnUI/5D1nBlLQE6bs1FLZGx6tVNMWcqWtI866GSbrkrZ7k6fIfIwJWd7ZrMe3Xs5 FNuhhIYuNUV+4C+96k/gqOCp317P+oM7kqFL+3ZbdN0nuLzTnLJDn3UF7EYPcEOKbmVuUa+2y2Jg mxBTAC3ZDpuYNIRVFmn/E0h9pjsiZUIraLWHyIrry+CimlI5sOydkHKkRTyxuIlPQ9GRgpjxFrhs pFiwyXYmZALUo/eFMBObO3x7FmB4/0IW9ITKMdcuPXY5MDCy8wiMbkjTJ1jDkG2NsMlEpprBdHAh uM76tW+DQ/EQprDNBz2Qj+Mq3ZZbNZaj3K/ClGMDr29iu4NHQeKofNiSsts4j/HwJSIbsdImdJt3 Z365vC+qIoPk8ibK16fHyf56/+d39MiVkCmt+ZHDXKwmc3pMq2Z/Hc6U5BqvfJzx15j5e98fN0fe 2WWb7qv8Qmnc245kmy97GC01SXIu86KR71fjtmv4/UgRAYa39/np6+11Uz29/PxrfuP833A+502l DIOFhndLFDp83IJ9XLxnIhjg5Sf7o5qCRxjMdXnkq81xTz70wEsSD+FAoFf+KLwiDUcvx8lfU7YZ VVul2y2XPJW20Bqc4FE7Lr7ink+vBj09v98g8P/jG6vD8+3LO/z//e5vOw7cfVMT/037ANvTztNG 7UInPg6n10XdqPcmlRQ1f7dMbRYsu1Kdx5cvT8/Pj+jZFw6nP+Gd+6+3L6/go/+f8OI9PIcEF03h yui3JxwwUnzX4cy3CfU+M+RptPE9s68wIInJixUz7iZJNBIpizTcuAF1wqkwqKu/INd966MNNUHO et/HzvETPfA3lGG2wJXvpUaFq7PvOWmZef5Wx06sTv7GGG9swo+igKL6iTEGWy/q63bU6X1z/HTd DrurwOav/2vfUlzZzPuZUf+6fZqy1TRWc0bsy3RjzYJNDpEbO+SswQBKs17wTWzUGMghdq1HAKxv K/MQcMWkA63At0PsJmbmjEw+uzWjYagLet87ruryKntjFYdMztAAWFNHaPtYJVPDAez/iAyZOY3M NnA3RvtxcmCUw8iR5nApgYsXOxt7KZdEcwpW6PYWA9is7LkdfY8YwemYeFy9VPobdONH1MuJzhu5 kdEA2egF8QZdAdR6sFLK7WUlb/PrcnJsjGne1SOjXoJMcvsbnyQnRFOneeLHydY+kO7j2DX7waGP PYdohrnKSjM8fWMTyJ83eO+Gv5SHfPHkJNfmIdORXcoEUjli3yzSzH5ZkH4XLF9eGQ+bwWAn3yIB TFZR4B3oaCzrmYlbeXl39/7z5fbDLAE0QNYNmbESkLnrSee3s25sqX25vf58u/vj9vydynr+HJHv 0Ju1chQEXkSeaQqYUNzgyb2yLXM5rJX3hSxSCbEev91+PLICXthyYQahk32qFZHiVedDWWhdpm0r Ea0KhzJYmUXLmrUvMbFzOr1NtTAE1FbEAkcbXU6gJsSyxOi+S+1ILnBgDNnm7IUbIjOgB/bMAKaW Rk636yDNORClmVRCMkY15qnmHIbmGgC8ESkOo6+LkxAFR17gUplFkUftJ8wwWbfIIlkUrSiTzTmO g5BKloSryRLROkYy148tUUPlAtaHoWdfLOshqR3H1WvHyb6hHwLZdSnuVtuomIHBsdz3XThc1678 MPzskCWeHUqZB8B1qc06ORd0ju+0mU+05bFpjo7LQbs4Qd1UvZm2y9OsJj01Jf73YHMkGqgP7kPy 8V4FJtZXRt8U2d7eZxlDsE139EyoU4shLu4Ju6MPssivfXJ1oadk8agno5kuspNiEMSmNpXeR76p dOSXJHKNSRKoISEso8dOdD1nNSkvEoqLKR4yJkLfTpLCCYZdlwX/kdCoCZzqyccCZcG4mPmqvbb0 okz2vRuGaIE0UijGM2AyND+xj4BQvEsznI7LBk328+399dvTv253w1moDcaOGOeXjmTmnpNAwVaO Pdq1FLPFnnqYYIDIscooIHKtaBLHkQUs0iAKbSk5aElZ9yWaIxE2eM5oERaw0FJLjvm2dmSoF4bk vKmxub4l+LjC9gBv13z0TcbMc5DrC8ICx7FUZMz04L9IwrFiSQPy/XWDLTK2dyWabTZ97NhbC9Rg S0gRs/O4FqdVhXGXse9Nuj7qTB4tMcf8tS5sS1msteYuY1olveeP2iOOuz5k+dj3j6UopzSx9uy+ 9NwgsolSDonr0/eNVbaOTfcfScE+vu+43c5W1EPt5i5rUHKPxGDcOtqDq+TUhmdJcwOST4r7H4/f /3j6QsTJy9VoGOwHt2qu+bakqL1Gzdtrehqn2MRqrTnK43P1RbWDvXmixsB0X/cyci7OGui77QKh nHd8v3z9/iDwQaTmK2vW/Loru9oSIfP/Gbuy5sZtZf1XVOfhVvKQG+7LrToPEElJjLiZoCR6XliO o/G44mXK9lRl/v1FgxtANOg8TGL192EldjS6h4JESSTnYA/2EXOizZ0OO09WQ0EDcNjxb9jaAp8p IUhv4Nk3DG9Z0t6ubKazVjNSwJwnTBlhgK2kFJarGGnSZbM/K6hzda/Kq6FkjVYyPixSpUrZJ4t2 dmZ1uCxtHZEa3qgdYtQr5UTJzjGVY6tIwd3h9LcIj+/fn+5+biq2D3+SVkQTtSOQhaSmrAGhHj4F Jj3R7gsbgromdyu3Kxq2SQ09JP1uWyZsHw7qMZYfxjpGc2aT2OWUd0WGxjKUDsl0v2RZzW2SpTHp jrHtNqZ4jz8zdknapkV3ZJlgO25rS+STSYl4Cw99d7eGb1hOnFpsCW9gT1PnMGmWgnu1NAtt0fQj QkjZ+saM8JTToigzsNRt+OGXCHUhO3H/iNMua1gO88SQ5/aZc0yLfZzSCp59H2Mj9GPDQWs+ITHk LmuOLK6DbTre5RMeS/IQs1kwxHiDs88ui8OF0QkhLgZvDdu9QXWfZd7ecX0bj6aAe+ksMJzgkGn0 MgVyeQaPPX1TRtdTKDc0TLTB5uCzEcynk53h+pdEPpqYeWWW5knbZVEMfxYn1gxxizlCkDqlYGXi 0JUN6OCGuEE4IQCN4R9r3A1bYfidaze4ttIchP2X0BK8c5zPrWnsDNspUGWBOYhGpwernJrcxinr 7HXu+WZofkIJLLwF12WxZZvvLWvnsY0yxrZGvdj04k8oiX0gaPcUKJ79h9EamuYm8fL1yhK4QUCM jv10XCvZGWhliGxCNJ2GJumx7Bz7ct6Z2ENhgcnWJlWX3bAGUZu01aTZk6hh+2c/vnxCcuzGzBJD 08hpCh6RWXegje+jylY6rq6qRVIQYnahBTLcWZKodSyHHCu0GAPD9VxyzPEkmwoui9kmqmFd77PB ZCA7ds62nuvl5dRqL13FCWh9ym6H6dXvLjftnmC0c0rZmq9sobuEVhjiRWBjS5WwZtRWleG6keUv 1NCH9cpiqSCmtq3TWHx/IEziIyKtNtKXj+vb17v762b79vjXw3KtFMUFHVbQUnajA/u68NoCFoA2 fknBl6jD/MVEBbe6o6npjMUGg0nWhJ6ptFFYW7Ao4gT1wAULffCtd0grcKQSVy3o1u6Tbhu4xtnu dpdlfMUlm/YG2qzDurNqCttB1eX6eq1JnHQVDTx12TBB6hTKlsbsX8pC6WJmaGiI72ZHoWU7amz8 aWH/eTXxNYe0ACuCkWezujQNa7GQaEp6SLdkuEL2lKXVAsfOsxGav5pIsIaKx5EcZTPWrnKWXRBs oxSeyz5joGxCIEgVmxY10PfpQOmVyNggRYrWs51FmiLqB22rQePFgMVdisRn3zVNLdCNKjLKnmgk 6HQWpk6ZH+IqcB1vdYBQe7ccU9IU5JzqBmdSR9X+JBcib6ki2An6LaAdDOJDG9iuH6sArKEt+b2z CNkOPnKLHAd9iDAy8pRNAfZNoyZdJxWRNr4jwOYoV1RWFeS+7S52ykvfo9KyLykavrnvbk5pfZzc 5uze7p6vmz9/fP0KDjiWm9Ldlm3LY7a2FMZtJuMKm7eiSPh7OBng5wRSqIj926VZVvfqljIQldUt C0UUgG3/9sk2S+Ug9JbicQGAxgUAHteurJN0X3RJEaeyZ0UGbsvmMCDIlwUC+x8akiXTsNFvLSwv haQmtwNvcTu2Ek7iTtRUg4RIdMzS/UHOPBh9HI5N5GhgHw5FZS1mj37sb6MLG8TLPAt/OicU2yky CAwmjd59xCDUjPnrETxUus27fds4rrgiZ3LBJtssHJ4kykVNYOFW5skyWd0uHjC2dbGH54TjvQvW 4nnht3f3fz89Pnz72PzPhm2qVE+VQ7yw4eL6nopPbkAyZ2ewacxq5AUoh3LKBoD9DrUbwQnN2XaN m7McYz8wtarQFm/MQNjEpeXksuy831uObRFHFqt+mEDKNgu2F+72oq3cIeeuYR53hi3L+8FUlrGd pc3GUcme5tB0NdU248cmtlwbQ6Zn2QoivTKZxUu7KzIiv66YseGZFjrSzyyu3H7B7YrNrOVL6Bkh MbxUMvAscNDHD/Nn1op9TKFqZrMWWEL9S9fVGPhrRIPgEXAQ13YRSGwxgNqFFLIJLgFrtMEIb2EU DDMDOZVtYUxpRhZGn+Z8nl3L8LMKL+o29kzUUoqQZB21UVGgcSeSF7xPBpoxPL/0xQd4ONEVel25 L+VfHT8PYrNDgQPnPZFf2glYlJ0aa2lYYMi5cvExxk3LUyFM93Txo1v4DAJRFeWKoEuyWBWmSRSK T+tAHuekd/6lxlOTS57GqSz8g30MscAgKymFSw+0AY9p84wj3x3wQz0WSwo2OHzqXxBgF5xAGt+n sNlv+VIB4HNSb0vKClenRYPZPOcJLRyvjaIx9DLSqGHbfQIn2strHjHlyXebFJYmNyewg6eri7w6 OYbZnYj4FAcAEoV+v0Ve5LR3Kq1U3inPUT9nEFVWltUyQN5UBLc21mebuyU+mZ6LKh/MWUdyPRjJ ln2BqeBoQPS/xuCYK/6Na3CKSheTTGo/YGgbvKtnJVxLfUn+6zlSG6lSpTNEKVHaSluV0TFBLeRB oJjv6URXlzzyMlIEfcmkh5cjMlryXOl33BhoWZVsLLlVmg9EnkPVYUaZeKVym3NorvL0WJfQF8qm lNFtlHMbialFu8shpU2GdMfZGyajian3Sjev0fAE4evrG1sdXq/v93dP101UnabnJtHr8/Pri0Ad nt4gQf5PUsUdCgBe/QitUW+KAoUSZRwYofxGO5CM8Z/YnNCqlccjpqkGqOJUbRccSvrcYHlJI7b3 wnKa5i3Px6lFZ4/VqhZTgs95SD3LBLMvSGNM8z0q5AHTQo8tTMaKMByMZRlslk+6njRSea316aBR 9fgiHjxR1mThfLDsvYMXYI2YrDWTvDl22yY601gtJC130P+y5JxkOFrusCwDMvieq8st+tpNprL4 yypB3xmKxKLkw/7qY0ORD87cI7aO2oILwyQ64hdNSq7XszvufWmTP96/vfLHb2+vL7CGobBR2TDe 8DhDdDs5tth/H2qZ9mCQtm+/Su4HlI/McAKRcyvkqwUegvDGtVLmttlVe7JM90vLNoeoD8+xNcIR 3zTnDIMYnGsrCpvSXIFM7Bxjc053atIMLTygJn6ZI1NaE4/alNT1lsjSzpSCa7y0CrThfRGGmGag R7rDZQWU3j1M6NExxetzUY4mdXQcN0DLd3RcF1dsESieiV+KiBRUoWomuLZ8qC0gLvq4YSJkketZ tlqobWwFOMC2gFGpyiNqu5ms5y1DmIKuzHD0gbHzGZmBlj+ijpU5uIEmieOaGvu3EstH6gMAG2kt IBeN/Yly8TWXJEf6UC/X9aAB1VlrE2ltG2hNtgk829SYKhA5mpN3iYIfQ8wUeAqr2wBwRst2/xay foqJb5nIl4hln76DFDbm06CoZCOhvmmv91BGsT4pb0ID28QuGkSChQ4RPfJJ4xtIS+fN40agyT3N y41pLimKEly6GzauqTzyJoNWrI+vrXlIGwZGgIyFHLFdX9kSTaBrrFc3J3nYwY7ECC1fm4Tt259U aE8LkW7YJ48BNA9C0+sucCjLL/TWOYMlCSyTbJ9mesHaZAsMPwjVFAYAn7g4GCI9ZgBWQ6l72xGU DKIsAN24NMLrEztj2YZ86rqAPvmOI0uXd9YrA6JHtBXSo7pYXdP6Rwto4+SgpguzrmlbuLL7RGlc z1zvvUCx15oV3TeZrEI4Iek+JzGt9AhYksmJctjTU7haAWH/5WZj1ncJab0bVtk6NY2JOuyF1Tho btnonY3I8LAV4wDoPsQIrzc7xnJcDx2A2O7RRl8oigQXbfIUVBRQh9ojoyHUcl2kVBzwNIDvIcsT DvhoPhik8acqMnwTGRU4YCHtiwFsDYvlA2x9yEYTJmhHwsDHHsBOjNluBhLzDOJ9UiRomsNEsU30 FlXlWS26ipUIn7Qumftpzv5FvuKoNR3sq1CbWJafYEi/ZESTBszFFHtGBrdZgi2KL3ngmkhGQI59 Qy7XxBPg8UiXTKLcQpYr3F6Khm+j/RsQZ22MBYKryZqLF9HH9gNc7uHyAOnpTB5gu9ZerpunB3R9 mgZjzgae9VCTZIgtoUDuo92DI+vzH1DQZ+0j4Utmy8YSJ4Cf6oReZaG7U1jx+eg7+4kBhiSRVjIZ mFTjbDzPW99GFeQUuM7nnEDj9l7iaGwQy5y1HttUxGMbPyK9ZZWPmxbR9nN+RGrcNTdw+ll+X5Pq oBAHmnq9AZYmy0OUyuo6Mo4cc4IYzH41dYpbEgPCKatSSE1LYH8WOjvCgHPPWQdCu0MUL1JXrjFA BueQS0tZIK++/Xx/vL972mR3P69vmMJPUVY8xTZKUvwyDVDu1+usK1FDDudymbfp667kY5EIifcJ fljc3FYa5UMIWJfs+9FL2kQHpD7zXHTjcalpctMluexUZBCrCkUTgwXolq/v+ifXefQ7jX8Hd1Ob w+v7xyaa7bTFan1DPLrDa8BozNrknN9J1IEP8ihKKC1FdYAZr7Jml2NAyZbBNaFi25ZBWiVJrAOb UFJ9lsD4EuX0oDHOPxEHN2pr5e128H/ZAsMM5mm2TYjmTgVooyKZLolqUaEnFm/qsVZjyPLopq97 KfIDvdHEmzdHPMNtUqCX7ELl9TscRU5yzxUmujzJwSunnMwgU1vRYAHg+fXtJ/14vP8b6+5T6FNB yS4BF9WnPFmNRd+oxyEkucCQKLRK+LU0jDjLeuOJKJKfMpa7Miulu1xO2NagUFOwDtAdLvBSttjL Wli9pQkmQ4rNY8AUp2QGIY1poeaLeriwDcsNySLrhNqe5NOtl4ILaVstBtxba7bgM0Fjv6Wvqdow TMc0sWmWE5LMdC3DlvbfHOCadKjQwoS2KvQcSykRiEN0KzrBhriH41LV7ToXa12/91GBbx9tsQF1 lYJUrmSLYRS63NR5novOhSbMMtVCghi7WZhQD6mZKnA1B6YjHmhWbxwH69+4Bt0ESw4DuHT0q9KQ 5rTsfkvNyEnoqpmPSWRaDjUCXCWyz8EFu1jkEOKxpG/esRUYSFU1thtq63cwPb+IqokImH1eSrPI DU3lmwtu1eSUR2P6K5+JdQb3H23eBCdlohwUWr1w2R5Tapu7zDbDVsnIAFnyAcBiVOP6E38+Pb78 /Yv5K19a1fvtZtBH/fECL8/p9+v9I1tqHdJpKNz8wn7wFzf7/FdBnZl/EPAOnSu56T1vaQudtewD L8oGfmLUeGAlfNvgi6r+g3H3W0NvXKENVsT1DLrPbVPe6Uy117w9PjxIs1YfKZtU9gtdNBFQlQBx WsnmpUOJaY9ItLyJtSkdElI3bJ2DL3Mk6qRe+jk1qk6fZYpETXpOm1ttzjT7FIkzetLm4ymv9cfv H3d/Pl3fNx991c8NtLh+9GaJwaTx18eHzS/whT7u3h6uH8vWOX2HmhQUnrIse/tYTm6bW1uEihQp vk6VaEXSxAn29GgRGWhsLCeOqTplS8P9mj3dwnP927FuWBe9+/vHdyj/++vTdfP+/Xq9/yapn+CM Mda6idi+VXh8A4JxwTWVDYSHqClZX0bLDjjDmvKAHRMCOuqZSkGKM1tFKr2MIZvH8W2X0M8gRFo0 u96ZtpxjLpeshYvS7pQm3DbJMgNgwB3di8F5J+RD0VwZQ6nuOSUEA8h2635JqI1lgmyT8gvqGGYi tH2kalDFo9OCENPp/QqKdBHrDaca05gVifI5mIxofTwLNM9fy+ThNg9cz1ZrDVxYh5KzkRlYeMOZ gdHhjZIPrRePEaduZEvujQYgpZlpyQa0ZWj1EwwUNEstQzT+pAZGFe0CfM0oMQys+jhie2ij45j3 abwB9lUcs5FNecqIxqn3SFJ9h43AjW0dVfHgkAIp3sK75hQAcUcpYNz3xVoziMCVS4iFpmw/Exqo 55OBsctBI0XNU816sInL3cDE+Vj7TnK2efQR/tk2sDoFuY006Rq87iDflsZsUAimGaZK10dC+OCh pomE2jHD0PigEymovzCB4CCpcjlSOSAP8QYLAwyqCzNVVOgb6Pdx+u+mjjKtZ2oOwaWBxlkbivqB D/lurFNapoXVeFT54aLBIDqZ8EXBnLg6xyGfge2t179Unxvcl7PUMsPIUqbZ6unug+1Dnj/Ph2nh Dtpmgmui3wIQ1NSmODUFbrcjeZrdamLwNHtXibI2fTOCbwWuJnrf+Tx+P/gXHFTpciZYjnj5NckX juRFOT5x0OZo+g3Bj5bm/h80q98MCDZaJYCg91sTgeae5SB53t44i0OBqQ1WbqQ5Qhkp0EpRj0QD vnyMKXSBhefvEflyW9zk1djxXl9+g13U6mg6nHFjJdg17C/c1uY8AvDX08jQsHCKPtWKb/OhrX90 xPb5tDe6u5pH4bn1lMk4J/2TXPV1DIO2p53qmofeFhG8wJffmF24HCljH02Xl+dEsR4wYKNhQ6og bE9c0UV+JznfuiS4bd9F5qfN2KkdrL/MSR1ix/HFO354nUFolKbwpnkWV9yeQn/u3OVsTyf51K0G o3RlM2H/+c+cbzDsCC+kt1lX7nZocxYp2LmLgC/OzwdErKeT5hgVXteP7++QNACWbYD0Ejjkws4R znEl+pg5lLTp0rLJtgvhkgPRLWVs770UnWkp330MYpYqXjoOR3VJ6XCdO1jGUO834G3H++vXj83h 5/fr22/nzcOP6/sH9hDkM+qY5X2d3PYXzHOvaMg+LbCbPqwvjrKuSivstuwADw6jTFhnsx+wTc7K 8ngSrpNGIrwwrIjkc42fsQ2RzC1vkg5jJdb6Zo7qmVQGQ0eeMQVU2cdhJJq6Nqr5suDIxvFkEL0c kSmOgxaAIaKWjIBEcZT4Bl5swEJLV+yIWoZhdPIDyJnIGIO3+vVMo16ABVz1KIpwRJMJgvwcuah8 8J2OYoO3tFweMQ4XtlItWF6PSq+Lnl7v/97Q1x9v91d1nuJHrf1DNUnCn6aJKeQp6+JgWov1lMZz cK0DNC0hDpJm2xJr6Skr4EnQ/OjN/l5frm+P9xsObqq7hys/3NxQdbz4jCqnww/YdpNRnvr6/Ppx BT9Y6Lo6ycsmYfWBe5JHAveRfn9+f0DWBVVORbfx8JPPJUuZMCuMKUkxCgMe2AK4pLV6ocxG8s0v 9Of7x/V5U75som+P33+FQ837x6+sruKFj7fnp9cHJoZXo2I1jKZxEbgPB6ekf2mDqWhv/OXt9e6v +9dnXTgU54SirX6f37LevL6lN7pIPqP2R+b/m7e6CBSMgzc/7p5Y1rR5R3Hxe0Wskykfq318enz5 ZxHnEGR4i3iOTmKDwEJMR9n/6tPPmarA4PV5VyeY3kXSNtF8x5D883H/+jLY8lEVE3pyR+JoNAIh A4NBkCnlQTy6HdcmDwxbcrAzyJfnWqO4KWRvZoO8boLQtwmSBZq7LmrGdsBHnSxpWGSjA3ocnIr3 EexHx5bGO/mqbpZ2EeajS8DZ0hqLbTYPgKKgslEWoGtSy/hxl+44SxYPtylsfpkyK6D9n+JtghBG ofJUaVfxa6SeYokUtnmZ7BJJNcKAIYCmSuZcJuf+bqofh+7vr0/Xt9fn68diBCds+2F6lmZHO6LY HprEbSaZAxwEssr5KJRUnrhQPB0fBChLjm+bE1PcG7Hfveu7Kc9MgjsE3rJdrWvw+69MjGCWLpMS EClnMbHEPMTElswY5qSOxWVZLwgXAtNQvm4zJGaTNsWWTceWxtJhMhdodJh7TCrRsY3+AOPgotOH yLZsSeuM+I4rrRsHkUZ3f0QX2vog9lCjoAwJJCtKTBC6rrnw6zpIF3GG+Blczh18CG2RCTxLHA9p RGT9I9oc2c7CkgVbItvPX/Sbvi+93LHZfvPxuvnr8eHx4+4JrkTZMP8hjfQk7t8PsY6cNURs1L4R mrXUbXxT1PSH36HUN/6fsmdZbhzXdX++wtWrc6umayz5veiFLMm2JnpFlBMnG5U78XRck9i5sVNz +nz9BUhJJkjIPXfTaQMQRfEBgAAITFy9TCb+piGQEsLxZomYkkeHE9rUuG/9rqKF54dtEooOtDHf gJuMOSudREwrhzRDzBv42/qgSUf8C6CmU04QAmKmG7Px93BmtDqbcQq2F8yGeh5W4HoV7EAU09ox w8dK9w4FhqnKPwGzXMrMvdqZN5oOqVVytZl0pG+PUs/dbLBpztNf+u5wQgPAEMReCZAYvYKBAug1 g0CXIG4fBDgOqZwjIcRHiSCXPQMjxvAL4pF7zJem8fOBq/u0ETCktxMQNOsobJNWj850Ws/B5Ync Hbszc/hadOqtYb1x+0NpR6C3kEmVGfXuUEcz4/EkRuRJVEX2ExJ+Z3TtggEE64dK0UM4pctKBFJF TLLAjFgrZUN9o7xCAx1wH9kgh6LvOmZLjusMpnZTTn8qnA7XWvPgVPRH3e9zxo4Yu2PjfdCoMzJh k5muiSrYdKBbQ2rYeGp3VaiQwI5+JKAUb+jYYsbj2B+OhmRH1Y5hWLrsHpTWEEAbK+VuMXb6tPn6 NLJp1kEjSK4JDV2sLD6Oh3MvPDxrsgR1gyIECRaHTJvaE/VZ9f0VDjKWnjcddBTrWiX+0Ewz2R5s 27ZUYy+7N3lrQpn3dXlXxrCT8lUlwlToK1YhwsfMwsyTcExVOfxt6mASRrQv3xdTXd+KvFuqOgg/ gLniYOZdMOhRVGAmYrHMu5I/5KIDc/c4nfHJpaxhUm6R/XPjFoEZrRN5kcRsLIG+ChJRj6KoP0WZ MkTePNc2qquVIm+fUhzNOKZcCFbrub7C7IbJY6XRGR5H5s7A1XNUJ9tXG+OMRarlyub1qlF/TLSl 0YDeo0fIlFM8ATF0DT1jNBzySgsgZuQto5mLcY4itKBGi6PZgDudIaZPOz52h4WtR43G03FnWhNE z8YdqjggJyOiWcLvKf09Ngdg0lF/ClGTPh9pirhZ14nRrMd8YUBTUn0jzzD9rV6ZSwzJRWlQXZyx fq0RdZmxHoGSjN0B+e1tRg5VbUZTXeiBbjGcUKs4gmYdtwhBVkAP+1PXDDon+NFoQuUqwCbkRFjD xvpxQ8kONQBaSvore0AFFAJjeP58e2uqwBlbXd1NlIkrrdOlhlPWAT4G06JV9g6W0Vm9qXN77/73 c3d4+tkTPw/nl91p/18M+Q4C8Xsex20iQ2kPl8bp7fn48XuwP50/9t8/0UGq7/fZyCW1z68+p6JB Xran3dcYyHbPvfh4fO/9G977P70/236dtH5RKbkApZ1nHoCptfC6I//f11yyfl8dHsIMf/z8OJ6e ju+73smSuNI206cnKQSRoLEGNDZBrsk1N4XgbxpJ1HBEJPXSGVu/TcktYYT7LzaecOGoodNdYPR5 DU6vy+XrQV/vTA1gZdDyociUNYVHYVTTFTReFTDR5XLg9vvcprXnSon93fb1/KJpTA3049wrtudd Lzke9mc6tYtwONRD6hSABMGhxbfvsIauGkVuNLPv05B6F1UHP9/2z/vzT23hXRZL4g74eiGrUud7 KzxJ6Mc9ALh9avhalcJ1udPeqlxTaS2iSZ9PfQIIl0yJ1XnFO4FlnPEiyttue/r82L3tQHH+hMGw dtWwb22h4dgGTUYWiCq0kbFNImabRMw2ycR0QmoT1BBTgW3hHSbAZKMnJ4zSuyrykyFs/T4PNTaR jqFqHGBg343lvqNGf4Ji1RSdglMOY5GMA7HpgrMbvcE12lQjn7pnXG8A547eXtChF4O/urwjs6Uz 7PiPoBJE7HvBGm0tlM9iGVn+PAEoTFnCceA8ELMBWZMIIakmPDEZuDR0cb5yJqwwQwSNuvYTeJhN zIUYmtwQIAOXt875eLWS26KIGOuZJJa56+Uks6WCwAD0+yT1UXQrxq4Do9ORg7U5gogYxJfDpnwk JDQbnYQ5HVUW/hCe4zodcat50R+xjKt5nXVltSxGtLRcfAdrYeizhae9zXDYN6xyCNFOJWnmYXTz BZDl5aBPX5HDF8irtx1p8iLH4fNTAkJ37ojyZjAgCWzKan0XCXfEgIysQy3YOOuUvhgM2cAYidEd RM2YljBd5HqHBEwNwER/FADD0YAMylqMnKnLZeW489OYDruCUEvuXZhIexDXgETR9FJ38dhhT6SP MGEwO0SrpOxFxYZtfxx2Z+WEYBjPTZ1bRv+tC6ab/mxG6k8ov1biLVMWyHrBJIIqYt5y4FBZniT+ YOR2pHapObVsqMvB1UzzKvFHUz0s30AYC8xA0ux1NbJIBsTITeF8gzXOECrsdKiJ+nw9799fd/8h JgtpuFlvSBM6Ya2bPL3uD9Yca5KMwUuC5iJp72vvdN4enuHYeNjp2lrUpPQu1nn5C/+xvBKn+a3b 9/NvqQXiAZRLeRVge/jx+Qr/fz+e9nges1er5ObDKs8EXfS/boKci96PZxDle9ahPbIqQjbaqYBt yAsutBQMWfO5xNDrGQrEOaHQmNDXMyUjwBkYFoiRCXDIfZ4yj03tveOz2SGB6TnTVBNJPkPfFR+X zD6tjtEfuxMqTQzLmef9cV9PfD9Pcpeqvvjb5CQSZgiBIF4Bw2RLT+eCSJxVTstYRX7umCcgzScU O47lszbRvNoMSOBs1EokRuMO5x2iBtxiqBleXoTCPl9KKKvKKgzhYeWInAZXudsfaw8+5h6oaGML QJtvgAY3s2b5ouQe9ocf7PFPDGYD3mFgP1cvpeN/9m94IMMt/rxHFvLELCypjZlKUhRgXfioDKs7 doPOHVc3Auaqylyjpi2CyWRIr3KIYtFnU4JtZlTF2cxG/b75JB8ujGpCx7WPu3g0iPuXhLHtwF8d kzr68nR8xSQLv4w2cMXMsOe4wnE7Nv0vmlViZff2jhY2lgFILt73QJqECUmMiiba2ZQN0QCRjzVW wyLJ/Gyd0+saSbyZ9cesLqhQ+gyXCZwcxsZvzexbghSja0hCXD5fG1pLnOmIrxHKjUK70PTIZfjR 3ie/KN/3SWdqLcRhBZNFabRSjy0FykQzAwqT2VamI6MPsTv18zgwu1He87WlalwVM6mLouK29/Sy f7fLDgIGw53pwbZaRGyAkBeEhYePaDur7iXqJdSVj/c1ilt2LqzutL3JPf+mMq46ABcNSwy2K4ss jqnCo3jS6qEnPr+fZBzo5dOa4kKA1s6mF2BdE1mhtRPFvIqXCRJw520/qW6y1EMyl7aMLdZ3taoy KwqSUEJHBp2PCS++yygKF1aUbKbJLb6S4pJoE8b8VyA633iVO02TaiXY6SQ0+D1mAz6sy9zOvaf3 wMvzVZaGVRIk43GHAEfCzA/jDL2FRRAKdk3QSdSexopY0A9WR9MGBH7A3iJLsPDsq2fe4fnjuH8m QjANiiwK2F415K0m42nWLJmswvhppqKogRg3IgIvaUxPq/ve+WP7JMWruSWFzkfghypRhR5LUhug RWDBV1ouB1BWxTOCFdm6gPUGEJGxVU41ojZ5jG40xFroJbli1MCqZckly2vRolzZDQG3WLON5SXv PW0JLKZ8sRzbQ9waYfOlRzleiYwtL4ABSU828wGy/k2yLFpiQ7Nr8W1FHQ4Z+eHQUpxbbOL5q03m diizkswseF/3ZlGE4WNoYeu+5JhER4nqwuhUES6jjNScyhY6hh19iQ8WMddJvSgY/JAZ/PAmWZoF tMYu4FRRwK4kQBqFimaw4WZ+SUQJP0vMF4l5iLHgHA/BrIAwLpuLWVg70tt3FOD4DxrZcjJzNble A4UzpPlAEN7xcYhqrzfZtgTuQkWU8QmqRBwlXelTpbUA/p+GPpd9A9ZEWpI1Afv+du0FpP7S5VJU CUwWeHG5JvG96hbm5avlTUkj2dHlmEovVCg38x7TEEnOrw11XVQyhBnEEFZB+inQ8IDF6n0trDXc 4MWqhbAh1RxvjVW0LHYUh3jx7YYcMxIQBxip99CBX+D9T794yEtj3wDiDlSLklMbFsK6n9wCtLmS IJnrjGvDsx9pYHUqKLyHkEQCVkrKL4fbdVby91u9dZktxBB6egVtYJtOQIcrqi77AOLOT+rGL6XN YNRi78FoWwno7dMLqRwvfOCQBhuRoCtyoG5EaYqn3efzsfcnrLfLcruoGrDK+U+UGNgBcQBq3WUS b8Ii1VebIfvVHzls5Lhod0LbPJFQV+DVDXSuM2lY3mfFjU6l6Rsx/dGWEf2yPx2n09Hsq/NFR2N+ 7NxbhtVwMKEPthgjizzFTTgfESGZ0sSIBo6zAxgkoyuP81lGKBF7d8EgcTq+faoXpDAwg07MsBNz 5VvYmHuDZNb5+Gzwy8dJcK7xsNvd8JC7MkT7RROBIS4SGS62ijexkKcdd8SfG0wq3miHVDKlQkcv m54YM9yAXR484MFDHmzNaoPompMGP+Hbm/Fgp6NXTke39ABthN9k0bQqzL5KKJeBAZGgkVZFlugJ vhswnOhK/UBygYNKsS4yBlNkXhmxbT0UURxHvtk3xC29MGbPry0B6L433JOgbMcgzTuXjaRJ1xGn GZGPZ/sMStBNpOfKQMS6XBANcJ1GuIRZwUS0HhX+u3v6/EA7opUZ5SZ8IEITf4OGfrsOUddCCchJ rbAQEciHtET6AtQYTTaUxRpQQdNyoy8p1caCw68qWFVYoFWW+daFXuivUe2pgiQU0lojK67aBDZk wTVTizcGk3v62RGzEEe+1JawnL2qZv8LtGriy++n7/vD75+n3cfb8Xn39WX3+r77+GK9r8yS7CFj OqIQaG+UildewriVxcM3tz+cXiVeB1FZYdk1p+8OuyizBIiw3yLH61lxhma37l5EqYTA4W8dwY5M gaAslcqqhVbUz3g5aNJJxtZbb2gevMRjH8as7tC4aSoxyVBlDrL7FEN5OiwBS7oeWhDetEu9+nhB DjEK7YmHJAlxfcn1ea11NdjaO8jd4gQO3KEncNhyH47lwQamRHsj4NEgHnsd2YWRIF2yNBqFiC4k 9OVNTtsW+2X/tv162v/4Qt/R0K08sarEyuu4dcZQuqYd/ArtyOHUMIvyPh85RFGw20o4h4FJ9u3L 3+/QkvGp9wU6hvIMmD1vuEKiIvQChkajgBVeeJEIzX42cJlICW9EsmtTWxfGWqPzB4x3HVahV8QP KjOTwUbvEvKj8sqygGPAeh0FBiIIqg1iaS6qerSMvc65Vk1KEogPO/DbF4yyfj7+ffjt5/Zt+9vr cfv8vj/8dtr+uYN29s+/YWbdHyh2fvv+/ucXJYludh+H3WvvZfvxvJNOwItE+teliENvf9hjUN7+ v1sa6x2lwMKwCPlNlWbk2j4iMG9CHGO1Uz2zs7bdFQ3atDQSVoZ29KNBd39GezHGFLnt4Q3lYNbY hPyPn+/nY+/p+LHrHT96SmJcvlcRw1ctPXK/SQe7NhwWMwu0ScWNH+UrXQwYCPuRFU3kdQHapIVu 4LjAWML2QGl1vLMnXlfnb/Lcpgag3YKfJQwpqGbekmm3htsPrEU3dRVEwpvHYWXki6uplgvHnaqE 0RSRrmMeaL9e/mGmfF2uQPFq1lr++f11//T1r93P3pNcdj8+tu8vP63VVgjPaiqwpzz0fQYWEON9 Cy4CwduHmuWWcJKi+bx1cRe6o5FMk6u8LZ/nFwxGedqed8+98CC/B0OB/t6fX3re6XR82ktUsD1v rQ/0/cSeBgbmr0AB9tw+yIUHGkbZ7qllhPlC7d0T3kZ3zOisPGBCd81XzOU9FVQVT3Yf5/bo+ou5 DSsLZsD9ks2p1XTDbiYu7plmsgWXWKVG5lwXN8wKBxF2X3j25ktX3QOLifDKtT0lmJe+Hb/V9vTS NXyJZ3dulXg+85Ub+JDuz7xTDzWBVLvT2X5Z4Q9crmWJuLbsNxtknN0vn8feTeja06Xggn9l6fSD aNHd6JLl4J1zkQRDBsbQRbC8pd+YG4oiCRyXC73W8Hqw+gUMCicHHrg2NSqyHJBrQqmnHHhgAxMG VoIaMc9sAVcuC5KdowY3Sq4S+/v3F+L+aRmKvX0AVpURM6TzOLvvKCHWLAYvCeM4stm57+Hx3shd oOFG3MoCOGd3aiQE0/WF/GsPnRcLj5m+ht8yLwf5msNZuPv1IrFXKZz3FxGz1Gv4ZQDUnBzf3jHS bV9fuTY/b9FxIGs46GPG9HvK5kluHxkyjwCUrW1Rox+FlPQq+Gt7eD6+9dLPt++7j+bCI99/LEVS +XnBpvZsvrGYL408pzpmxfFUhfEEJ/YlDgTU9TdaTf4RYa0StHxk+YOFRVWr4rThBtHVmxbfqLbd 3WpJOQVWR8KmuLMFW0tRK+KdPQlTqRhmc4yW6LAItOzGuybT5Sk5ShfmweJ1//1jCweZj+PneX9g BCXeXuK4joQXvr2p5HUnJX6aoKdrNCxObfSrjysSHtWqg9db0LVGG83xK4Q3chDU4Ogx/OZcI7n2 ek2eWju8/b6LbnmFSwB1K8PMplb3zIPUwiALkV66qCHz9TyuacR63klW5glPsxn1Z5UfFmW0iHx0 qLfe9Ivr88YX0yovojvEYyuKhl3qzYtsEq21SZOsuuNtE3nOwnbYO0vLNAyqPFROePSry65HmhjA +4B/ypPFSVYuO+1/HFR459PL7ukvOO1rIVXSTarbvAvi1LfxAnNsU2y4KQtPH0freYuikmtz2J+N iZ00SwOveDC7w1tVVcuwS7Eulyh54sbV/Q/GpA4K72I3cZSGXlEVmIqcRsB6MhCCi4mMQMXCrN/a gDRhlqB9pX7+UC2KLDFO3zpJHKYd2DQsq3UZxcStXgT6ZoZVm4Rw4k7moV6+VjkqPHI29+FMCVKL gBxjv8JG6lbM/Soq1xVtYOAaP9us80bDiIGNHM4feAVbIxgyj3rFfZc5WlHMWU8W4MZEPFBh4etF DqN5e0a6EGjHZnUO0riPdGhc2KsWepkGWaINBdMx0MRQtTNuVSAUg9Vs+JClHrLUqH0x5BLM0W8e KxLypH5XGz0VeQ2TAak00LTGRN6YC3uvsV6RMM8AtFzB0u1+TgD/tHs29/9gWusY6csX1+qvDa/V 1WZL+yvyQ0aKljKRoB5s4gmR+RHss7sQPqQgpQ88gWmo9fhYBJEMr2kIzC9Ak7uXS8VJYyCB9Bn4 sVdgmOoqpOHUbQ1zWTECaRdZccm0epXKz9cMCWIxp73+sos5XvoPos4bAGIZK4u21v9bjfEs42yu t4e/r+2MNEaPgM0MvTKDUzvZzfFjVXr6dffiFlUa7eVJHpEL8bqLrelslBAS+LEItOHOokCGgwp0 cl4aKlEQ6cyu0Q9CmRjqFlhyHXGn3SoyBA/1NjRiW0LfP/aH81/qTs3b7vTD9ooD50/LG5nLnYgq BfY987ZAK0Bk2DM6YmMQXHFr0p50Utyuo7D81rpsG9XGaqGlkE6huiNBqKqCXNbTQ+rBRHauJ4I3 0589JHP0f1VhUQAVySPXOWLtwXn/uvt63r/V+sBJkj4p+Ic2vpojCnuABxZW7tQHo2SNZopVSPPy 1zQL4Blhde8VKfV6w+rJgYNgxHxi3PfwAtmsJxL2rasQPeICPd8lzDHL8LDboGmhCoAxdYlX6izN xMjuVVlKyz2pVoBn+KCHrlP1iBdHeO3Z5S9F6I/ch96NzAxtFEq9qGv/dEL+pdcJqDdLsPv++eMH +rSiw+n88YkJMWg5dm8ZyRqcBZfsvO6oXhenhkhOdo//MmMhpJdEEiQYO3xtEJqW0API9ECWEpH8 92YZEPaIv9mG13Ph8X7AfzQ49EsxeFPPiaugGH/ZHDFq52LbGIkVxe0P+j7mHWRr6qjmkMyUDBTR 7CHLrSbfkGeRyFIjmoNiYHxBN0z5wGOD9DEsMntWs/kfIe+JqPeRdOSuaVUiAfs9qFFhGqjtb37l XWK/7S6RtvqOmKWWppjbjVX5chF7S2E3qhLUS9cxx/B9KeNvPBgnxhigsBh0pIZTjiYc3NA5X6uJ psP5sibMnoiVcetNeSSQvpcd30+/9TDP2Oe72uqr7eGHLtCwljD6vjMSqU7AGBe/1gweCokyMFuX 37QgFpEtSozFWedtUuOO7YrIarXGgBZPcDz8/hY4JPDJIFvqg3H9q1RIG/C1509kZnQbNe53Bm2O KH7aTRjmxulTHWTRM3fZ7f8+ve8P6K2DDv1fZde20zAMQ3+FL+gDf1CFVipsRaQp3Vs1jQghNCbR gvh8fGlG4lwk3qbEaS52nGMvjs9fq/2x8MOup6qqvOzP/Flt4NwyzaFJiFMqzYyUOG5boNDTIC5w CwKGc2DyweSyW2ELQGCPaJzNjMIagLMI6GZpc04TD7OENQfVxu0dWvvH6l5FBU9S0Gzz2A+A70FH sC0od/MDax2na1mU3ll9vxzX4w3q7RP6LhbJOfSDRPp0K5SMTHtVuJJiJzqRruxKQ5qxn+9qUyME wyc3onioYB9kBh+OU2lYk9509e4vMY8ag83hUHTIFAeO1DjT+8GJ8pwYYJ1uWq9dQg7oA7oWiQah sHkaCtEV4eDlCoPeYCykc+niqUswY0Q2tqHGZyvjiJCPt8tymz6R+TIWQ+7kUGVb3/QwdllRxFF7 qcu3/Ty+Wu/27dh3wYpSgUuwlJgV10s+cGlzoLlFfBBkuIVor6fsw01w0QYAi7br7xnPehZbCxwv UftWuOH4vCIV38Lye/KCkLodAw0CNMnQpaAxufpU8KeRpPDgadjPfq/cvef8QQ8HuHp83mRLxAQD aEV3IS4tqtVM9kHAE1IZFiUlunDGluwv55fS0Vl4AQA= --===============2094385740749792558==--