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 B1F6BC433DB for ; Tue, 2 Feb 2021 14:29:11 +0000 (UTC) Received: from vger.kernel.org (vger.kernel.org [23.128.96.18]) by mail.kernel.org (Postfix) with ESMTP id 6A6AB61481 for ; Tue, 2 Feb 2021 14:29:11 +0000 (UTC) Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S234518AbhBBO2q (ORCPT ); Tue, 2 Feb 2021 09:28:46 -0500 Received: from mga02.intel.com ([134.134.136.20]:65105 "EHLO mga02.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S234339AbhBBO1j (ORCPT ); Tue, 2 Feb 2021 09:27:39 -0500 IronPort-SDR: mxZrJKCu7RF45yE8RrAt2kjX645nWUfj5WRk1/8rW8k3LdM7i3CnRp6Q6prpqmgzavyMxCBXEy ebuE2vn9uTVA== X-IronPort-AV: E=McAfee;i="6000,8403,9882"; a="167966309" X-IronPort-AV: E=Sophos;i="5.79,395,1602572400"; d="gz'50?scan'50,208,50";a="167966309" Received: from fmsmga006.fm.intel.com ([10.253.24.20]) by orsmga101.jf.intel.com with ESMTP/TLS/ECDHE-RSA-AES256-GCM-SHA384; 02 Feb 2021 06:26:56 -0800 IronPort-SDR: OMbjC0RVnVez2o3fk2UyRAI7fcod2T+/5NrcOY9o8wjXXuQy96S4G0l+magVKRqhZtrH3YIZtX q7PG2Ny0SHhw== X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.79,395,1602572400"; d="gz'50?scan'50,208,50";a="578801188" Received: from lkp-server02.sh.intel.com (HELO 625d3a354f04) ([10.239.97.151]) by fmsmga006.fm.intel.com with ESMTP; 02 Feb 2021 06:26:54 -0800 Received: from kbuild by 625d3a354f04 with local (Exim 4.92) (envelope-from ) id 1l6wdp-0009QX-Pt; Tue, 02 Feb 2021 14:26:53 +0000 Date: Tue, 2 Feb 2021 22:25:58 +0800 From: kernel test robot To: Luc Van Oostenryck Cc: kbuild-all@lists.01.org, linux-kernel@vger.kernel.org, Miguel Ojeda Subject: arch/sh/kernel/cpu/sh3/serial-sh770x.c:15:16: sparse: sparse: incorrect type in argument 1 (different base types) Message-ID: <202102022250.K4vRmUJS-lkp@intel.com> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="NzB8fVQJ5HfG6fxh" Content-Disposition: inline User-Agent: Mutt/1.10.1 (2018-07-13) Precedence: bulk List-ID: X-Mailing-List: linux-kernel@vger.kernel.org --NzB8fVQJ5HfG6fxh Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Hi Luc, First bad commit (maybe != root cause): tree: https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git master head: 88bb507a74ea7d75fa49edd421eaa710a7d80598 commit: e5fc436f06eef54ef512ea55a9db8eb9f2e76959 sparse: use static inline for __chk_{user,io}_ptr() date: 5 months ago config: sh-randconfig-s031-20210202 (attached as .config) compiler: sh4-linux-gcc (GCC) 9.3.0 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: v0.6.3-215-g0fb77bb6-dirty # https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=e5fc436f06eef54ef512ea55a9db8eb9f2e76959 git remote add linus https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git git fetch --no-tags linus master git checkout e5fc436f06eef54ef512ea55a9db8eb9f2e76959 # save the attached .config to linux build tree COMPILER_INSTALL_PATH=$HOME/0day COMPILER=gcc-9.3.0 make.cross C=1 CF='-fdiagnostic-prefix -D__CHECK_ENDIAN__' ARCH=sh If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot "sparse warnings: (new ones prefixed by >>)" >> arch/sh/kernel/cpu/sh3/serial-sh770x.c:15:16: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected void const volatile [noderef] __iomem *ptr @@ got unsigned int @@ arch/sh/kernel/cpu/sh3/serial-sh770x.c:15:16: sparse: expected void const volatile [noderef] __iomem *ptr arch/sh/kernel/cpu/sh3/serial-sh770x.c:15:16: sparse: got unsigned int arch/sh/kernel/cpu/sh3/serial-sh770x.c:17:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected void const volatile [noderef] __iomem *ptr @@ got unsigned int @@ arch/sh/kernel/cpu/sh3/serial-sh770x.c:17:9: sparse: expected void const volatile [noderef] __iomem *ptr arch/sh/kernel/cpu/sh3/serial-sh770x.c:17:9: sparse: got unsigned int arch/sh/kernel/cpu/sh3/serial-sh770x.c:21:24: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected void const volatile [noderef] __iomem *ptr @@ got unsigned int @@ arch/sh/kernel/cpu/sh3/serial-sh770x.c:21:24: sparse: expected void const volatile [noderef] __iomem *ptr arch/sh/kernel/cpu/sh3/serial-sh770x.c:21:24: sparse: got unsigned int arch/sh/kernel/cpu/sh3/serial-sh770x.c:24:17: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected void const volatile [noderef] __iomem *ptr @@ got unsigned int @@ arch/sh/kernel/cpu/sh3/serial-sh770x.c:24:17: sparse: expected void const volatile [noderef] __iomem *ptr arch/sh/kernel/cpu/sh3/serial-sh770x.c:24:17: sparse: got unsigned int arch/sh/kernel/cpu/sh3/serial-sh770x.c:26:24: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected void const volatile [noderef] __iomem *ptr @@ got unsigned int @@ arch/sh/kernel/cpu/sh3/serial-sh770x.c:26:24: sparse: expected void const volatile [noderef] __iomem *ptr arch/sh/kernel/cpu/sh3/serial-sh770x.c:26:24: sparse: got unsigned int arch/sh/kernel/cpu/sh3/serial-sh770x.c:28:17: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected void const volatile [noderef] __iomem *ptr @@ got unsigned int @@ arch/sh/kernel/cpu/sh3/serial-sh770x.c:28:17: sparse: expected void const volatile [noderef] __iomem *ptr arch/sh/kernel/cpu/sh3/serial-sh770x.c:28:17: sparse: got unsigned int -- drivers/watchdog/sc520_wdt.c:233:37: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected char const *__gu_addr @@ got char const [noderef] __user * @@ drivers/watchdog/sc520_wdt.c:233:37: sparse: expected char const *__gu_addr drivers/watchdog/sc520_wdt.c:233:37: sparse: got char const [noderef] __user * >> drivers/watchdog/sc520_wdt.c:233:37: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected void const volatile [noderef] __user *ptr @@ got char const *__gu_addr @@ drivers/watchdog/sc520_wdt.c:233:37: sparse: expected void const volatile [noderef] __user *ptr drivers/watchdog/sc520_wdt.c:233:37: sparse: got char const *__gu_addr drivers/watchdog/sc520_wdt.c:294:21: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected int const *__gu_addr @@ got int [noderef] __user *p @@ drivers/watchdog/sc520_wdt.c:294:21: sparse: expected int const *__gu_addr drivers/watchdog/sc520_wdt.c:294:21: sparse: got int [noderef] __user *p >> drivers/watchdog/sc520_wdt.c:294:21: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected void const volatile [noderef] __user *ptr @@ got int const *__gu_addr @@ drivers/watchdog/sc520_wdt.c:294:21: sparse: expected void const volatile [noderef] __user *ptr drivers/watchdog/sc520_wdt.c:294:21: sparse: got int const *__gu_addr drivers/watchdog/sc520_wdt.c:316:21: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected int const *__gu_addr @@ got int [noderef] __user *p @@ drivers/watchdog/sc520_wdt.c:316:21: sparse: expected int const *__gu_addr drivers/watchdog/sc520_wdt.c:316:21: sparse: got int [noderef] __user *p drivers/watchdog/sc520_wdt.c:316:21: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected void const volatile [noderef] __user *ptr @@ got int const *__gu_addr @@ drivers/watchdog/sc520_wdt.c:316:21: sparse: expected void const volatile [noderef] __user *ptr drivers/watchdog/sc520_wdt.c:316:21: sparse: got int const *__gu_addr vim +15 arch/sh/kernel/cpu/sh3/serial-sh770x.c 61a6976bf19a6c Paul Mundt 2011-06-14 9 61a6976bf19a6c Paul Mundt 2011-06-14 10 static void sh770x_sci_init_pins(struct uart_port *port, unsigned int cflag) 61a6976bf19a6c Paul Mundt 2011-06-14 11 { 61a6976bf19a6c Paul Mundt 2011-06-14 12 unsigned short data; 61a6976bf19a6c Paul Mundt 2011-06-14 13 61a6976bf19a6c Paul Mundt 2011-06-14 14 /* We need to set SCPCR to enable RTS/CTS */ 61a6976bf19a6c Paul Mundt 2011-06-14 @15 data = __raw_readw(SCPCR); 61a6976bf19a6c Paul Mundt 2011-06-14 16 /* Clear out SCP7MD1,0, SCP6MD1,0, SCP4MD1,0*/ 61a6976bf19a6c Paul Mundt 2011-06-14 17 __raw_writew(data & 0x0fcf, SCPCR); 61a6976bf19a6c Paul Mundt 2011-06-14 18 61a6976bf19a6c Paul Mundt 2011-06-14 19 if (!(cflag & CRTSCTS)) { 61a6976bf19a6c Paul Mundt 2011-06-14 20 /* We need to set SCPCR to enable RTS/CTS */ 61a6976bf19a6c Paul Mundt 2011-06-14 21 data = __raw_readw(SCPCR); 61a6976bf19a6c Paul Mundt 2011-06-14 22 /* Clear out SCP7MD1,0, SCP4MD1,0, 61a6976bf19a6c Paul Mundt 2011-06-14 23 Set SCP6MD1,0 = {01} (output) */ 61a6976bf19a6c Paul Mundt 2011-06-14 24 __raw_writew((data & 0x0fcf) | 0x1000, SCPCR); 61a6976bf19a6c Paul Mundt 2011-06-14 25 61a6976bf19a6c Paul Mundt 2011-06-14 26 data = __raw_readb(SCPDR); 61a6976bf19a6c Paul Mundt 2011-06-14 27 /* Set /RTS2 (bit6) = 0 */ 61a6976bf19a6c Paul Mundt 2011-06-14 28 __raw_writeb(data & 0xbf, SCPDR); 61a6976bf19a6c Paul Mundt 2011-06-14 29 } 61a6976bf19a6c Paul Mundt 2011-06-14 30 } 61a6976bf19a6c Paul Mundt 2011-06-14 31 :::::: The code at line 15 was first introduced by commit :::::: 61a6976bf19a6cf5dfcf37c3536665b316f22d49 serial: sh-sci: Abstract register maps. :::::: TO: Paul Mundt :::::: CC: Paul Mundt --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all@lists.01.org --NzB8fVQJ5HfG6fxh Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICGJUGWAAAy5jb25maWcAjDzbcuM2rO/9Cs125kz7sLu2c9vMmTxQEmWx1i0iZTt50biO 0/U0G+fYTtv9+wNQN5KiHHem7RoASRAEQdy0v/7yq0Pej7sfq+N2vXp5+en8tXnd7FfHzZPz vH3Z/K/jp06SCof6THwB4mj7+v7f18N35+rL7ZfR5/164sw2+9fNi+PtXp+3f73D2O3u9Zdf f/HSJGDT0vPKOc05S5NS0KW4+3T4fvn5BWf5/Nd67fw29bzfndsvF19Gn5QhjJeAuPvZgKbd NHe3o4vRqEFEfgufXFyO5D/tPBFJpi16pEwfEl4SHpfTVKTdIgqCJRFLaIdi+X25SPMZQGBr vzpTKaUX57A5vr91m3XzdEaTEvbK40wZnTBR0mRekhw4ZjETdxeTdtU0zlhEQTpcdEOi1CNR w/qnVjRuwWDHnERCAYZkTssZzRMaldNHpiysYlzATOyo6DEmdszycWgEyu1Xp0Ypizvbg/O6 O6JkenjJgkqgo2s2zFHLx1NzAieWGX0akCISUvKKpBpwmHKRkJjeffrtdfe6+f1TNy1/4HOW eZY5s5SzZRnfF7SgKpsLIrywlGArowWnEXMtE5ICLpUhX5LDXBIBjIAKRB3egEo9BL10Du9/ Hn4ejpsfnR7G5KGajmck5xTVV7lLNKE586RO8zBd2DFeqCoSQvw0JizRYZzFNqIyZDTHrTzo 2CDNPeqXIswp8Vky7bAao63oVIZ86hbTgOsi3rw+ObtnQwzmdjy4TDM6p4ngjdzE9sdmf7CJ TjBvBheYgmSUs0nSMnzEqxqnicogADNYI/WZTWOqUcyPqDGTNgWbhmVOOawcw3237q/HbquT OaVxJmDWRNPJBj5PoyIRJH+wamZNZdP1eryXwvBGaF5WfBWrw9/OEdhxVsDa4bg6HpzVer17 fz1uX/8yxAgDSuLJOarDbld2uQ9rpB7lHCmElT1B+IwLIridec6ssjqDy9b0An+MpxERTB6r 3GXuFQ636UXyUAJO3QX8LOkSFMAmQl4Rq8N5M75mVV+qm5fNqj9YZmWzEK4O6In6VOC7EMBd ZoG4G990Z8gSMYPHIqAmzYV5RbgXwr2UF6WRA19/3zy9v2z2zvNmdXzfbw4SXLNuwbZSneZp kSkMZmRKK02ieQeNaewpBqAaVTHSQQPC8tKK8QJeuiTxF8wXYQfOxQB5Bc2Yz3vA3NffnRoc wB14pLnlEGoCn86ZRy0jQa9MpTbYoHlgGedmgVXV2/XAAto0LcW7VtMQoTzl+MaBZYVrpq5W CF4m3KZcmQcIjZTT3KDtLiDz7dMkVBjTwFl4sywFfURLJ9Kc2rYhdZAUIpVbUd6GBw6H7VMw Sh4R6qmamHKueDg5jciDZnSiGZ6ZdApy37onN03R6A1cPnAQ0wzMNHuk+JTJY0zzmCSGFhhk HP5gmU0+0AXzx9cdz6AB3Y/KtGjHgdSWqWJwahielUrMp1TEYELL2mewiVzKr+dpBCFcLPXR qlyf6oFSoNLAmL/LJGaa1K06S6MA5JxrcnMJeABBoXPaYoMC4gfbTFkqee/2zaYJiQL7Acs9 6LhmHnQQAkW5CFNiA5aWRW48YsSfM+C4Fp/tJoCNc0meM9XuzZD2IeZ9SKkdQguVYkFlFmxO NVXpnxysR31fvSJSy1BRy9YDao4LgaA05TyGOVIl2sq88eiyeQfq8C7b7J93+x+r1/XGof9s XuFFJfAUePimgm/SPZT6Wq2wpPHqrWl9wc9csZt7HlcLNo+M3V5hoEUExGgzK5pHxB1AFDbv nUepq6kdjIcDz+Gtq8MM+2xhEQQQ7slHUcqAgD206U5MMkmwKIsETRYjERgS3foJGkuTj1Eu C5jXeDKKi5cGDGJZ2x0UObwM0ipz1SvRY9t2sQLOTnloG88hXFBwYBVXGTw2byanxjFZmutR 7QysdR8BXjFLEQShi2L5s6kgLggrguON+N2k9kykv+Qcf75tlDwD+HI8vNDsMIIKVzxkwEp4 cz2+teuFQvbH5EMSmGkyGp9HdnEe2fVZZNfnzXZ9eR7Zx8KIl9NzproZXZ1HdtY2b0Y3tpfX JPp24qBvRh/vDcnGo/PIztIJOMbzyM5SnZurs2Yb3Z47W34m3YDpNOnOXHZ83rLX52z2spyM zjyJsy7KzeSsi3JzcR7Z1c15Wz2Pt5vzlOnbmWTnXdBv51zQ5VkbuLg88wzOOtGLa40z+QjE mx+7/U8H3IPVX5sf4B04uzfMPFdRavuGFrbkBj69aRBwKu5G/41GetZY5qjgGVqWj2lC0xyC 7bvxpeLRpfkDPnK5HPxNH9yg4aFGrJGQvpi4asJP5voC8OtgVEkTfOkMZJUVOwNdexwmnkbU Ew1TcepTxVWUUkBGy8uZ5sh0iG8zu0fUUYyvPyS5vjRJaj9j+ASrI1ytv2+c9UBVgUCwWC5y JqhLZM6i050OJUIIJKehXcUkGWiBPYlkWVxyle13683hsNOyIorWRkwIcFho4jOSmG+Uix66 xNj8SdAFoKGxlmICKPFtuUWcD6sV4L3RuXLwDZznZe6qbp2Fc7kjd7faPzmH97e33f7YbQYW 9goI1ePSi2bqPDp9l02Vqbb1y27999ChwZQZTIaJlfu7K+Pa4XoRpgzVpHALAw9wSrwHlY/T izYJSyfYb/7vffO6/ukc1quXKkd5EqnIUTL604SU03ReEiEgsKdiAN1mik0k5jNNtZCIpjSB o5W8wqB57A9KFxD5QLQ3oCy9AZgvkMmhD/lJE58CN/aI2joCcDD7XIasp/gxdjsgzXZrA3h1 JzZ8w791o6fYbRXl2VQU52m//UeLe4GsEoOuEzWszMDO+3SuK3enY2r62qaWp9GSTz8m1mts ZDcrSEkyZjmYJAdhYelH0nghSRIMvK47BtRVKvHsfrytXuHOOd737ZuWJDZREkeenrZ4RSHC 5O9vm33o+Jt/thDj+61Eu9oIhWfWpcQeSmcF7IUvmPBCqxH/eKU2m61ElGrSo2/jw8dyPBoZ JaDJgLcOqIvRIArmGVmOIHy8Gys17JzggRVqOTkLHziE+tGgFzItuJIExl/VW1BFz5Uovjo8 /Bzv/ty+NPJw0taB6lQFnhevLTZi3mX//nZEW3vc714w/b8zB+EIeSMZJh9VSUkMxPcZS6b9 ZHZ3GB8zaGSKzAdtd+yz9Ujz1OL5jRWxyeRvxJKZSvJNkyxNBHhS/RmU13Fn+DHu+0FzTRtC BVx5Frt/YYt9b8j5TeaBWQxrk+h3JdEWa15bPFgfyJo3vPvdZG+qcq2SFFzcV9a2pEHAPIZJ tZ5v2R8PElGKhA57etmo11jW2fyI2l2tdkDrqZwpCa0TY7Vff98eN2tUhM9PmzeYSw8KmuuF +dC0Sosp70XV3ABgl3ITmlNhRVSJbhUivW6Z+wrTVJF4W2aLMymIugJuqbwjEhPa6FuoNRA5 s4wfUPtKs20gp1NewgtXZd+wpCorq5nJYLgoXVi5qsUYuJgtqa+guZzVYKHZeFVW9OJs6YVT g2ZBQGuwllTV9JsuFouoOPUwK1vCWWi1wap3AbcCghcQw6R6ZUPDDJVWIN5pwiTqYXJUqT2m fhFRLjPRWInA7HqHTbHFhk15AQMTvwcnntC2U+eVq8PB+oLuhSSpcpfAcOjZUDVx3XYnTL10 /vnP1WHz5PxdWbi3/e55WzuoXXcEkNVtMLbukuq4eEVWK3xdYuhyvadWMhPCH1wxpQQbY61G vS+yhsEx5383VsLz6hhsye/6gEROsXidzuRdUCp5IDrbnnky7hbFtDm2cYECsAR+qdVt+t9m /X5c/QmPC/a5ObLScFTshMuSIBZSOwI/U5UHQL3KVUXMvZxZ2ynas6gJMehXhPMBEBXPstoj 4iyLNcyEJIf7bJ01ZtxTFRgIKw+jPfMh+ai5l9iWe2mu6KnUQ5PzAJ+8IHrtrs1oVDjL9urB +mxwy3xaVuPUynE7HcZd6iHyDCL1MhPyDsI15Xe38h8jg5FTLErYyycJxHhFWVdmQFNZXNIl 2l1Q8YaEwgnAkyUNwUzh2YsoxDuYguhgj1maasJ4dAtbofLxIqgUotl/TmK0srWVbNinucyi Yf+MOukU+wwo+Pgxya1XqFHVTNDKchLNYgyffbfptmMo2Rz/3e3/xnippyEQr83U+Ln6XfqM aEVWuMS2qu/Sz2TfA1UrmgqwNw/YAdtlASj2deJLhAJRKlIU1SPDJlLOWaA1EjSDwBGXBh+E HGcDSkKF+bi1ICwgY9Sr1pxFrP0oI6K2oXKhKPeU5MqvONctZM78qS30nsOM5bfRZKxkNjpY OZ2rkyqIeK4v4FPPLtEo8lQ6+GnP8RLw4WwKuJxcKU8kyVw18EkTVWUYpRS5u7q0wcokqv+g uo2aTnS0ldrYXiLimUugajTtRVLN79837xtQ8q91V5TxTtf0pefeWyXR4ENhqzO32EC12Q1U U5gGmOUsNfRVwmWbyP2JNXLq28bxwJ7k7fCnJhX0PurzKNygD/Rc3gfCdbExJQhu88S601y9 WQ3U5/17jnD4P7WI0s9zqyTvP1icz9z6FMwthumM9sH3wb2FVn82G3BwP4TxiG3u4N62hTAM TvCfMWobBEsD5tS4qJjaBlIx1CkmpdyGmIp9qbKJVtVqkI0YLKMqnFVtG6IsYEFaBoTb7n1D VLN49+ntefu8K59Xh+OnOtJ9WR0O2+ft2khz4wgv4qYUAIRuMLM2Ctd44bHEp0v9CBERLGzT FRd209rgcz7PTqyG6GvbvEGULk6M85r+vP7+siGdaqY1HkIJj7GBnuhNXIijEnFyh8TaZdlq K5yvph2e3Y75Cca6PMUPLuxtgWBm4SWE99r2ovb8kLnhhJhgCGiyumzVoBh4maltKh3RKyzA VmXGSl8pziLDkCKknHLDICU81FKZ3BZM3+dCs4H4G2I5ezVAIkVhK3DVHarSsdJMo4KovC3D bOfL0i34Q1k3+jVnct9+BVG7mc5xczg2b2/trvZQBkJ1TRVBkDgnvtXAe0ZZD9QiJ7bbghjX U31+AEwX5uA/xrcXWrtKZVtIciItjuPmnrWKKFFLC5M8Gh5Q1SU0co9EHkSLAttYk4E2ILwR YqgDBZBBRJfDi/IiuWS6dLxauiZIFk+wRtTj0hvslAAsCxj+f6ATFCni0uBPF9kfZCBHL7Fp UH/V0J4Yx5oKJsmfV2u9Xd6C1Q8AmyOrfnKtF8+iB63+a8+li42N1B8wX6I0k68qxrc9zYCJ eSA/2fupwOqvcDQYxPpB/fValfF+ed8cd7vjd+epYr1XK3OFrFtH2jT3HjF2FHrMFdx+Dyt0 QXKdvxpWhpdWsOvxzIogIryYWTF9Rtsx0+vl0sTM4V9jG3E+tyUyECNmuD1DDGkM1lXVgkGB NsMWLKcRZh5+mpBSO8AF/GrarlUQ2GPdAgRTDHrGfbvUIF43m6eDc9w5f26AS8wTPWGOyKnD pbH6LVoFwVQEJhZC2VtTdch0Ky4YQC1CyoMZU61+9VsqbQ/IkqzQLkUNn2aDrvqtog3V7/rF NX2R2+HPLzzCAtVosaAi1Y0VQGEeuOID5oZhX7Q1/gvUsC/w4KmfsiqQVYCJx3oAzHtq+6jB qLz2hUpDeRHEQz/yeoqQbFZ7J9huXrAh+8eP99faDXZ+gzG/13qqPVo4l8iDm9ubEbH7dLgY iwc4C/xM3yAASjYxZJMlVxcXFlCfkotaZvr6EorUA2zUBDwzxb3MLGdQAS2LXwSLPLmyAm2s 3l6FgWoQzpS+kszkBDzAocCNBVqwFy3AgbMXFQLConSuOvFUhCJNo8YRbd6AYecl8zyif33T 1fG2634tussEVqWSkEaZ9assuFsiztS3qYGUcf0ZYw0HS5T4JOp/MykXCFgeL0hOq4+te4wG 2/2Pf1f7jfOyWz1t9p2hCxbg2OO3ed1CLUhmk338BE+R3FLkpF1N+Uq5GyU/v6o2bJtUQcPJ RJHZCtdRYo0KIhz716XmjpQcnfz8AL+ZamoEAwG1dF/gERmIn1r/Jqf2BuOKAJ2IehqIx+LU 2jsEkRCGA4r1p1Mt6V/91q9RDdOubQuL+8A4Vl/lZkb1K2rsj6lLLHCqgf7pFSIDmni0KgZb pT6g8G3PgMWEkjyW7sg0x29Gyige8OnGJcnska7ELW2dP3G6FFR7PUPGWcTgRxllnnU2dFVK 6jLbN/1gyTOsZcf1YXVFv5AhyCoTdd/tg5qCLTIrwPjtcP2RkWXtaaK6QrFoE7XZan+ULUHO 22p/0FxSoAL53mDNWi+YIALiuOuL5bJC2oQHNF7sy2KjdYI0ODlWlqnyEnygKRVaIN8hRb7U 4ah9GY/sC4JeynaW3qpdl0VPFlJEBfzRiXf4bW/1vZXYr14PL9XzEq1+9oSWphnvMSwY1sjh bsSEV8WP6ttqEn/N0/hr8LI6fHfW37dv/dhAyjJg+pR/UJ96sglDh09pUlrAMB6TNfIzzDTh fWSS8gXJTKEhxgW7/4ClL8Bblb4hjM4lnNI0pkL/BF8hQcvikmRWyi+Zy7HOrIGdnMRe9jfK xhbYpKeewpYnbOkxAtLiiFbGsc+FbxMjPLHkxJSFYJE+HaiGAUgNAHE5TYTqBp1Qp6pOvXp7 U3o1ZYAiqVZrbIXWvhRAxlI0WcumRW3wsoYPPO4rTw2u20EGNaIhS+2fesuL7V1NRp4/dCTg aUkKXTqCX13pjYkILTywSYUtsJK8RERUcu/Kux+IrGoh3Lw8f8YewNX2FeI+mKof6Wts4CeK QQSx39Ad8MJscjGbXF0bJo6LyVVkbopHwPTg4fQUCf41YfC7FKnAFkqMQy9Ht9cGluayYwWx 48m32qfdHv7+nL5+xmbWvoOrbjf1pkoU4spSTgK+Tax8SdJBxd1ldwAfy7aKv8CD1RdFiBHb y6ud0MRofVbA1XejD9XnEgMibUjrHrWhmSDC4MVAqlClG7Y1DcVkiTZ92jtIiaQeBEQLzNDG 2l8gM0BQ8tgzDc2itElEHezqZYfq7Vr9+xVeytXLy+ZFit95rsxO2wt7sBwICAWc20j9Sxla XAp2oGeKW4zJhEkDMcw0tcxauwUWDPbN9C6TxMQkn1Pr3xDQTRt56AdeTJZLy9Sxhu0v4OZe nBhfEPQ2vUxIz4+RmAC8HBbYQvKWZB5cj0d6rqRjbtlT2lpSZRB54uS2fTJnWlzfyX+5vE38 wFSvmmErGO7H0jYVetpXo0sLBj1s+4kJW++EsmVmY0CGDnZZiPhiUsJubL58Ny3lavGphWOG zQK2pe07UwWBqfGBS/Vobw9r8/2QA/A/9vxQd1qMz6rvFyzcdMjKZbS035yi9TF+7v4WuWFS /AudTk/pukIaXOOxy1hnmJpED5p5KY0oAw6c/6n+P3EyL3Z+VK1YVg9akunz37MkSFtvuV3i 44l7TOqxmAKWDbWXspsKAjabA4WEhGfYF1fdEaX1j8mLUHLrTZcrLGUIbwYHhdsHlItINlnz EHvljAdeErjUrf8uvsnIcJoAi10BMRl6qZBiGhXUZaYgwoeM5kZ42yQFhHIlU62nBcLDImHi /zn7su7GbSbRv+IzD3eScyc3XMRFD3mgSEpiTIpskpLpftFxupVun89t97HdM8n8+qkCQBJL gcrch15UVQCKWAuFWlD/QRQEbFKWUF62jgEgGj6igawCvK03vyuA7P6QVIXS9DSbZZii3ai3 Z8XSCn5XykNFvR1fzBUY6gZ51B0BY+aEFUaIEJFImFW4GvzBBgBiCjY+65sIFqOiIHDJEMfR OjQRINutTOihFm1zUetU5eiUIhyr5rUpw6eti9TbZIEXDOesqel7QXasqnscABJbpN3a97qV JegEO9VBUqZVNLDFlnV3bEGWzVv2vEi98KMeJ63hoMuVgINN1q1jx0tUY5aiK721Y4ltwZEe 9WgKt7cONgW4qZQe3FUkdaxAbPZuFBFwxsfakeSOfZWGfiBdhrPODWPpN64M+FiQ5xpfxHOS 6h3vPOL3gAFShnOXbXMy7uOpSQ6q3Jt6OE+MoyvPYXetTCc8DoeR8qTJNgMDAyh5u6qIKhnC OKLd+QXJ2k8HKkbUhB6GVWi0WGT9OV7vm7wbiGbz3HUcLQ7CaCiufjP3B7789fB2Uzy/vb/+ +MYC97x9fXiF28w76pKQ7uYJbjc3n2G9PH7H/8px9s6dcsn//6hMOlTEFCqLzj93TUF2nEKk Pf1IqvAe7oSo12hKY+DRM+7pBnZZOEdfL08sfO6btGOIOk51Y1V9LlUxjVW6r5XLurzf8Jt5 2hXjfdH0BQUkmuLLVVAFplXGNmyMLiQJcvx78zy/cf316uan7ePr5Q7+/Ex98LZoc3yJpr94 qZKRB/5mKswiZph20WUbqDJvPxxZtCTqnQiL93miGXsihPkpYBDfJEsTORqvStDWx0MGYlRx sFKA2FZbG0AHohOLW3BsbDT4brNJSj20XJWkaJNNX7KTtCM3MKgZ/geHtWobKmCmgAA41dSK mWyhUxr87lv4j/wc1R8P5xMbkrbuYBEp/J7ynrrECqs2RcQ4lFpsVTR/549BlqA07KV9gQDa Ruco0qobhJk5fqMMVJ6WRrI214FchlWGhpVOYSvFxwl6hEYSEPZgtGx8bYp+kyi6DcHYuToO NHRu2GRJUOhWEDQVPny1uUWLoxCiLTmqS8k1xkhTuDsfK41h7aqIICb1b3PoEYP5ovkAcg8d zmkkiB015JWMrupBsRDiwC5NQSYtdNbqtM/VKcjAzFDN1sCAWjGjyNCklJzV7O/LQvJn6O4a OUJyiaGR22K3w/dihuBSZVHcwE+rMRVGUj4rFSVVpgFgOzz0RaJBuVS8EdD5kXB87dpTbxaA jQaO1QrF0VIhvouMPTCXY7styBhaQbniYOWunCWCeBXHrqXptEiTLNHZTZlbV2KtFPU+BFcj ton92PPU7kRgn8aua4KBPwIYRjpXHLy2tLplDrpKPUXalLAgtWrYg815uEvuLTWVsODy3nVc N1XrK4der0zoBi01jVjX2ak1MVXReTeURn1F2ubW6gBZc12KWYojettAM5IurwqVkQOLiZgY fCR97PjGfJ3ftseaKKO0HKXBW7WdFjaCLuk0YJ3eSp8zrnvYgTRIDxL2oLwpobgJSwZufxYu TkUPd/hcrUjcZXawaXgt/k10/W0Xr9dBRb3PNaWsOmsa9QeG7cbnLRWY5aiIyFWg7vSGsKpp NCp2iAizoRlcK05NCNCKJd39IVVBCDn3vdylyqd05V7VNgF2sorJaQthRoPuQmR4b0QyUQ3/ F46b9f7l7f2Xt8fPlxu05hPSLCt+uXwWNpKIGe3Sk88P398vr6awfleqNtyTQeddRks7WADk LRA80bGwgvl5nYwUzlQK7clARo5b99V20qJLKQtMmWY0syUrKFhU14J255EJiYcMmi7PikTr Iops3HVsjLUJzt4rtYjtwlpHR0kXMoV8FZHhfWGr8+N9llyfJkwqyA8HZSfgmgxm0ntz94hW uT+ZvhI/o+nv2+Vy8/51pCKefu8sNxXJ75KQ36VLh2luWHTZQf0FYmaj7XIAJa7o33+8W6/G o+mw/FMzMuaw7Ra9zIWttXTgIg6vSDYDX07B/dFvacUyJ6kSEAGHW25gMFnkPGGcM8W1QC1U H2ETU704VAxagJJ2ABpZBydEfjgPv7mOt1qmuf8tCmOV5Pf6nuQiP2n9omG5tbQ0TnbzUV7k Nr/f1IkliLvE7gIeeO0wS8UCCQs+TKtsBUF9TPe8O+xdy2MtaCWTLHJX9vHgSl2Y2awFfRJu qsSVFaiiG/3BgetZ36t3GDE3q3i9AsnproWuW/gioEPh/lRsWj0utd6/yRBFYeCc64NWpU4W r72AU+ksV6nrR7GPbE2MqwRVEq8Cx/wevEaeN3lOmwJLNFmOjqCtpQb2nQsfmTYwBjN7C5S3 Q/87fU/leLhUH0tmtrmHUS2oy/9I2B+VDtHnXNOFgefGNFcq6V25cnxnsTZBcq0jgC50VgSd QnUk99EmKSsUjG2D3KTbwAl9mAbVkcDFQbTSwe1t7ARiNus4NrBtjVlv8PmDHv0sWTuBd2Xu MiLL1MWJocOSbCj91WABqxbJKkrz1ODI4kPnhWt7b6dV4juOsQ8IsGhO/+725IXOICYhmQRk pguDkc5SEdxgr1XElDsspBjvRP1ETL1o3G+WDs6+AVnMtY5XWxUrTSfMQKoROEJUE3AGqRSF BINt1ectGeVl4sHALKQ6TKkozyT3addFgaR0Whwlx6IQkGC6fzy8fma2/MWv9Q3KOEpMHuVx lP3Ev9XHVw4GQeV2k+nQstg0nadD2+ROB4nXEoIYQJUSTU4UaFNBLT3LMESDTVrebZCgLpsU qDpKpBKfiAo8ihe2Uyjw49hHUyO7pMr1x77pCYPq7flBhxA4uSTz9eH14RPe+ua3YtGacoM9 qZFihbq+b5NDx1NW0RL+qR9piR7Z341IRU3fSwgMEpXZnH4xHM8azp7+nm6cv1wa+BGbgTDE Uvzg+8Y4Z7vL6+PDk6nYxLFIynOetOV9Kh8bAhF7qmQggeWcQMII3DI9xgJuGAROcj4lANJS l8hkW7yKUhc+mSjVX1tkZAWic5VuaOShZd553W8rCttiIrUqn0hIDvMBrnSZTaUhEQoznJPF HVDpzTtVb62gaHjbe3E82LoR1qwLguaVZmGyNXsleY6MhSmaH5SYXhJytHRTUeiGoT1lHl6e f8ESwAObhUxfQzxlihqYYG5nOy2bLnLdwWh5RFCrT5AQBrQqAYjSvus4Rt0cTvV1UQ1L0wDQ 0+paosMZUtIGwiPvezjJC4MzDp5ntevQBLYFI9DWHWDfmTapBspauyovSEBrCWYog7OO6OsJ t7D7jp9VbJVUTgp4YYaU+IhDxcMZK0jTw9CY9TLw0sxL3bDooqX1CPvOJm+zhCwvHozspYU4 8Huf7FSPfRpv7X8L3Xlz3yQdtWeLAvoWp5NVQwen0hUioVpvuuvVgUxh87IeGWvNjQtlIOuX Aw6WEUoinRxCU6DRQhq4w4gby+3Cr3zA+KzoRZ7CMWxuriaJfX3CDaYzP4SDFyYcnoEfXT9Y mMpoj0xUjFbKC/We8s3xSs/XdyVREqDUutXJYAUs7M9FuckTvAZ3upytY8VAmke4SkVyNDmK KFKT3lrat+X42K43ckC3E3SBbimD/MN518m2K8eyFHLp/DbF03vRqu/9KRVqXaJp1B8aJlCz 8CtyCJJohrI4GDcNrWAUhibG/C3gOnnmWQ5bDYoCwphGc76FMgyaAXKvU+q6iyTcpIS/V2yV hAQM3RU6oCu2RjssoXRW0wI45wTv01ruEhl/m3bnjeyCIGQ9hDMCBXlo2JO+BSuKYsiWGSez szG+mr536EZRE4gnZSxqHtV1qnrGb5KVT12tZ4opaIeBQRmnPexSCjduMkST7Pl6sclKTn05 g/Ph/lB3FAa7mYLf5vddr8UimLEpLGTLXQy6HbqMMk/IT7dKiNw+hT8N3feNTld0mmQkoCaZ prWSwOe0DSgb4JGk8NLpbZFAwUlWHHJZ4JOxh+Op7nXkCT4EnRuGe4LP3vc/Nsz41mRW4Cwx PwwyRX8EIkF5P/q3jyGbjNv9pKsRPd4e4YBE7+wpXAR/+QAGzIcpRWcIH8+ePdCTQwVzr1MN tgdSOeUIArkJGTcs+vH0/vj96fIX8IqNM79GigOQPjZcWcLi9OVw8TIqNc6aGV7RD08CX/bp yndCs8ImTdbByqXq5Ki/6A1S0GhWbBq2Koe0KRVT2MXuUOsXMTdQkWFpo6v4tJhGNnn68vL6 +P7125vWteWuVrKCjcAm3eqfzsEJKQ5obUztTioqjK1ADu6+GIJ95inTkOdD+QPDMQhH4J++ vby9P/19c/n2x+UzWjL8Kqh+gQs0egj/rLzSMW5R9rb0j2k/ybeENbXPM9QwFIlOv2xuOVLc 1gcbG+iX2PUbvd4UrRytBpNIIfwC7fgc0xCzMDKjxsFOO8rZVop8W/mUYx7DVfnJ0z+An0KU fI1Y1QZzhJx5wNPi8LsRboNPk90eLqAZ/eCGm3a1UyvFo7ds9GcIRNQNfV1E5O8fV1HsqDXB Td671XaIPgzkaz+HRaFnbhincDUMtCKE4QdaHGVHDReNrPgaT0p78dry0o8o9RqCIFja1ydL U8GMpQNOMPTBzmwzWJ5YAMddgFLKEmVC64oPRLRFYV98nZ96K0uWVYbfnyvY/EhVCcMXVZ8b s6crWjp2AkM2NqMARFre8hkKVtiWenOZsZHBSX/0yfiQDHk8hCCpe3eFOkm7+8OHIwjJxgJj Kksrgwx73jSVbUJJylKl4Ag/k7cFIED7m6Qv1As1Iu4qe39xZYgdXdo3s6Fs1gtLqk0TpaxI 1wECFSbyAopf4WyFg+lBWM4RdkdssnNfPss390ndwU1u0gLX71/5qS8ql04+vWIhOVgPYfLA VSZAqWSym0DC2UrF8MBYqjw+w1Eg0EeNY6xuRpKQOdXnq85tGA4ZYCJ2D3W/uJPwkqJDvQ7g NcAWMxFxRPEzv7XwV6GmuKke3nCI0zndmBFvgzkUM0lDbztp1z5pYsOQ/T5aq20nbYWG4n6k hlHh1JUllviERWO6rCOT6jGagQUNPIPsXKhXPYSClOLFtDpsxiay84eAo9qVqIyZ7+87Ozso Fn1QrjIMOjmeqBUee7zYl9TDO7vrcU9+vZgAX+kY4sWEzZtRfDJm1B1GV7NUBkgRuU0pkzdr i3oakEx12hh9gWDBuV7d6KV+PtlrRYU7amONelXZCyEgN8G/20KHal3yu/ZcAaCyipxzWTYa tInjlXtuZXfz6UOVZzwBJL+d+nBu048e+PSZz2iYXGZb8oaAxqG3GDzA1pMggp23xVFlkUEb gkf+RqL7Q0sENez+xeFeL8eCsaysnPcFsV5YmBbXcW41cKvkB0NQU6SKOnsEnbsPxheAmOZZ +RgdCtS6WoM1WWCTwCCRoTCsAVM3LrrQ0RhE6awr1EAFHG4dfP5eZ2EdkHuDz+kpTK2HnYdV 71nepJAEBD2jGMDQHcrOX19ZUiZMWDbMCyQ4sygxkWHVkOYCFOogSgBk62AobJOWSX+uu9KL MLjnwG5kia6lEKmeFgw1DGu9zlFgtHbCgEkILG1xuVCvEkQ+G32fH7oE/tk2O+ME/wg9ZYyH hq+a8+4DsQ8klRm6lYkUkpaHeubHcVD1VVPR5vXl/eXTy5MQS970cvCHfoVgPV3moTc42lRQ RcF56qtpBGd4dw8yUzX64Wpnpu7Hq0Y2xV+woGHXBCLU6EnaYPldAn4oSkZuVtYVWqCrGfz0 iF75StpeqAKVj0RXNHKwSPgxhcrm8TmbbqzP1FUhdVqyNIq37MVAHnIJyYyMLK9EE5H9eiAR ibN6Yu0LS4T4/vIqc8exfSPSkJts93BGBHEMldZqeF4Vc856+ulRI/sAx8sHY34Khw3uX8my oluTlEmeGw9zhmTG/dv/s/F9btL9Au9F1sde49MxQUzaVNNvjCFJjV6UKikO+KRJDNicl1Qk rGfKLMloHn8rgo8AsCA/DdwERBygwPVGinqrCWpjkaL9oPsD8QuXJcg84wVWrRyWmsHmaHoy FI3qfWfW0PNATN8evn+/fL5hTRhWcqxcBIe6FrSYwc2bEQcz7Ss5WBL+3C19lHaD4lbXUHCT t+09Ct2qOyM32Ce0sSbFsOtMra5CZGpt+euEGVJMQRtXDe4hcKckmWOwvEgNCYMjaM0c15/2 +I/jUhohecxlGzQF3Zpz7rwv70wuiprWADJkWe+K9GTtPGF6Z9QprKVsxapNHHaRWazKDx9d L7KzUzVpPCzUO14JFOBgLIxBX0DsGLOOk6brVCZpmrQGvWbYoSK7pEqCzIM9qN4cF8iYLGvd BIra7L3ugKeNLeACJ2lIKw2Og50V3by1roH9JlWdPRjYUDAaSDcOtar6bhWr+hAGXpQRGQUL jHAmM1pw/CgoKsDS3DM+WqcOhjnYimNJzU5KbZjT4xaDXv76DoekuZEmWRPAUWXumByuB+lS SQ6NvqLvzo2cqlXa480+ZXDP+rXszdPXe0xARfQ2bQ0gLrLuRty1Rq+wh3upF7uOOQ/WgmdJ k6h1JT+zttmVLm6Lj3AGaA1sssgJPLPjuaOO7Ru4h45WVdn465VvAOMoCHXS0YlN71XmsaQf bmnQB7FeL1waZa923lmpH8Rrs2e7MFi7ng7+UA3msuNuWeYS5m5Ytu64q2I/MEsBeL2mw3cR ozXddxZHESQON1yZ3em7a5c4JdicpwPYcYLU9+OYfiriQ1J0dbe038DutbIEpeMtsAQHZCcQ H6sv/90ONmmrR6RoAAM6EUNzJx1vd+6Zb82sl91f/utRvBTMd8qZkmvIz1nnreTgdjNGOSfl Au5dRSFU+WKGd7tCXtoEWzK73dPDf15UTsWtdZ+3arvi1qoYI01g/C4nkOeKiorJvpQoXN9W a2hBeJYS8QIfPrXcVArX0hzLRWSp1Ydzn76mqnTXeiFQLf9lVBRfYz2KLazHuRyPWMW4ETFZ xKSQLmxoo3hOTmQgJIZr807NOCKB4QriRx6178tEeBG4Vc4SHatdE2T0Lq+Kw6ItpUKtLB0d g//tuWU72RZq3lgKeoujhUxbp3lZ9/zHVeKyT711QOs0ZTrB31W60RjxKiGXMa90Gieaupju v5bbANDIj9Ip2uYspQkGXZHUWrwJFUdznOrq5IkMQ7lWch0Ln98dm6akXej3dxXZJWxfVFOP C9CYNousbqRhE6ezeNmORHmVtyByo++d6G2MO5/cn6tOzrM3klvST4xoDE+NwQ8wHlmz1OyY JnlXnzCIUXO+K7qc+lCZcJsULU+etMiEXISluuoa2rh4LKDWPc8RGb/IJBLgCyj760pDM0dm Q3l15B6aVCOopqGnD74rCirKbqEaqJkE4LiqqHITya2/UG3X5ElLVdwdDzHJz0QxRbey146X balyGQqz1TdRt0V7e1fXGcVRVo9ChoUh8YRvZwfvC6FntopPkDNQiumKdiHfFOdUhkxSEBmL Q++vnIGgmQ7HZTo19quO5pnAXl8ePn96+UY0IlgXp5z5TSzmXkf1I2K6lu7JMROXrV1LgF8r exjPF59cde76guIMX1TJyapQrBZGGPGB2VzWJlHgKU1a4wuTn9w9fHv78fxlabBtJNMnY8YO k7VRK5hkqT4HP/x4eIJBoEZ/6hD20ssed/q8as5JmejWg4I9a2UjIx8Hbx1G5FaAD6v2Ph8d ViSBUUBGy6VZPB0Rh/ouua+P1AvMRMMddJip/Dk/4HmUEU3UTX5gLxxQ25yfYUKPynfWZ3cP 75++fn75ctO8Xt4fv11efrzf7F6gF55f9NBVonjT5qJu3PWNd5epQls+IEwTTXSQUHcQGBGZ xIIIZMS8MeK25i87Domtj6JRdAVGuwqYv7aA3NynSakmk8kPW8/dVOlSE6gtdsI10QpbHAP5 dVyrsVStcM00a/1YFC3eW0xMVQJ9JtndT+ZfA1VR0lVrL3QoTL92W0A6NmSXVGv6w7heebX0 ZaMRlVn1tgf2HZdqVdjd0lPlbnmacFupZRpm97LAdHMYVo4TW6YqM5xfbgAElranaUYJ4hD0 oUutH5Zkh4CPXm7E1BMxkMgh6iu0VR/QnGqZZ64pX+K57yJvoGcCxvW3dftMEkWhR7MJQqCH 05nkDJDRsWx0/HSr6o/U+mCRk8USmbujaLd4nC/2RNfjY9JiTzBjZrNRdpYpq3IMI7vZUDwy JNmfIr7jlS1xcnBe4FW8l5GLu0y6iECMoWC1zhvB7ceEHgrx7ErMaRH+yMRM1t1UL7R95rrr K4uZne1Li7mK125IMYVJCNXRAsFyxdaY+uHCgNUyAcdHYaOqCWrmU8cg1I4fL0z5XQPiFN1g 1SDnjs4l8xMJHVshEDISz1WZ7Pbq72NVyh01e9n9+eP5E8ugagviXW0zQ1ZCWJL28XoVkLk0 t5kIbbRrQHY0SnZ+RAakGpGe4jXErYLwlYtM3sIKJb0XRw7NJxx0cCW2qZg4CZpJo1GsFjPW oNmXaSanL5sQalq1LUvMG6wdLekcwrN1ELnVHR2Mk1U4NJ4zWNN9IEmF3pn0szDrLZSofOq9 bsLKKWqwRiHbaeZqEoZ2Qp0IAqpYSGv/JjQVyUwglSiSCON+Y7DnaeE0ELeDDRUtirrzjjSu ZV2WunhaqpUKoGpnLCM0FzGGarzQW9taGYDFlpjzcArC3a8DjKXkvghXsIgbxU5OIIJgGBGz SqZHT5KuSKlORCSwPrqRSrUVH7rQo1WNiL6Fi5ruQSKh4xj2XNKvaMYaM4GBQ4dM9crm8uCu gigyekxIFfZi2vvoDGWPlkRla9uEY+hYfpkV0HjtRARQTow0AdcU5To2WOlDP6SfE0f0mjZa YejxLkN8Sf5x0II/sr3bBKFgpULGQJeSqnsMfZnIG94E1X2qWSWVxZyGnQcsOoQxu9s+cHyt 343nbAa8jR2jL4WsbWsyT/W0swgtVlE4kEdFd3sfw1wkE00imkeE1FdishkCh589toLiJZ6r a/rq8dPry+Xp8un99eX58dPbDcMzXRsLokxc1ZFA9bjnoHG/HvU8/7xu7cu5S2Cb2o6/yXBH gvVoy+z7sDn1XZro5+Jk66A0hMYOsW3AenQc0WfmaPAwX2eaLnSdgJpozJDBkU1EOCQyjmEO j6l0ZDN6re0uIsCtsVX1zLUlIk9cCc+NPEw2PHUGmwRxaN+xhe2GbZs0TTtkKHW+TTibt4Eg gnOADH0y3lmpBTbikmNGmm+OsXypsnel60W+sczU2VX5gW/b5GfbF5UnZuVir7JO94dkR5qM M2lNtxmSgOqKlRGGwJF2q6iUk/CxT64C1/FMmOsYnYN2NPZTg6HtkwzQK8d+JKGWy10WSAUJ 7RAxEuiHtdCeGZ3EjYKMzbm/W8WubYm19b5C1aUwICUwug2XWsqzHiLM9aZsDLv+GclQ1FMk J2EXZKLk1r6o79JM9xBVxbR9ksF1vUo1m085XojtYjerAkTYb1k7MEYCH6+1BoJn+jnVZZ/I oVZmAox3dOSx2rqj1mUzFT5RshfKiY7U/4zkIELuYBOk60qywF9TwyeRHOCfhmJX3BwtNRuW HgTReNG7RsZn4CKbxvydUZoUJ43UeJkj2uQ3s8UmgcSTz0sN45JzIDkEfqBe+TSszWBuJrMY 8EvB6NmFiGqfY06BT/LN70s0b0VXrn2HTlKqUIVe5FKajZkIjprQJ4cKBZ+IZJxhLGOFAoLl YqYSXRlQw5pUQvET0IYKo5BCSfczEhfEtmLj/Yz4ELwbhSs6K4FGZbkrqVRwTVvsFePWpqFs K0hc7P4JB1e2IOpmqmPJ+6lGFDt2VgHrURKtRCT0GrqApVJE8RVGgAa6k+zNtHFh1G08NsHK pWUtmSiOg6tTA4gsUrFM9CFakxoEiQbu2/Q2h5iY3GJ0I2wJsynUy4qESpP1Krg2mXGbv0rC 7+CLn9Vsjx9z17Esv+YEG/TVhcWoSENNjWZtaYY9mrRNRbn/alTCI9RWybHbnE908vqZctYb ENUw/cFycRAGqTHVVRQzpvOqJnHIyYOoznVpXrqgiqNwecdCZYNvK1/u4GJA6uEkIiabbupa jWWiE5zafLs5bi0NMZLmjrYtl+mYkHuViknw51NFqq8kwvvYdcLEwtN9HHsW2VijiiiTx5kG LrGBG/rkPoa3YM8PLRObqwc82qZfJ4uoO4tOtCY3GoZzfctuOqojrlfvrUhJxVQOSLjJz8MU 3o3g95L4j66wFMJ0AFFwhhcIvQ+UyabYUJ5bra7qazEKkOKzVRYWq/Y2HXMx0fHSGP6Emb4p MwhTyYgvvAzeqsqVCY6GurSLN6cReLOwQIgclgvlN1l7YkEgu7zM0/63yWv38+PDeCF8//u7 7Csh2Esqlkx+4kDBwj2qrHfn/mQjwHfrHoOyWynahGcuJpFd1tpQo2eqDd/nGAFD6rjJ7874 ZKkrPr28Ejn3TkWWs+zaxqDWZpbx7LSZxSmlUaVy1ujp8fPlZVU+Pv/4a8xXqLd6WpXSepxh qppEguNg5zDYskaJo5PsZL5PcxS/xlfFgWWKPOzIqc2qZ+E7WALotORPbwr27jDatYtPpz5R 6fApYNbcAfoSmXoZO5fWcNgqY7Vlj18e3x+ebvoT1QgOWEWHP2SoZICeSxrM6/mbG8ooEceC 95si5jFsjuFbO1huRX04lyzlvM28A8iPmOBeD0I2fSDxCfIK1h8I+Kqa2JZ3Wb7eilXkWM7M icC1nGeMoM+TIAotmzSvIkmiyAnpGDxjJVu4Alk0KoyCa3mvEMT0l8CMFERFlyzk72RLAGQe T9u4ZzixCBm8yqtaDhMyY7KKz9tiR9ZXJWVZK6cBMjvtaQSvCiG066EfyBIdzql/VCFusv+4 ZbatkkTq/iobJHPQw/Onx6enh9e/dQv1omUeuhx68/Dj/eWXN/Zidfl888ffN/+eAIQDzDr+ Xd8ui1ZsjNz4/cfnxxfY7D+9oKvkf9x8f335dHl7w7AoGHjk2+NfyqrhVfQn9hyh7559lkQr VfSaEOuY9HQV+DwJV25g7NYM7jk6uOoaf6Ve1Dgi7XyfvLKM6MBfBXptCC19LzEaL0++5yRF 6vkbHXfMEtdfEV8KclkUUeqmGe2vjUOp8aKuagazuq4+3J83/Rbu5QM5l/7Z8LGRbrNuIpQ3 d9FSkoRBHJONKCXnU1muTT9FIzcmxocjqGv4jF/FRD8gInSoUF0zPqbGQyBQhrQW3vSxuzaL AjigVEMTNgz1gbztHNiLzaqqMg7hA0JaKzYNQOSSj5IyfjBmKSooI9kOQ4Xjlxu4UxO4K6Kb GYKM9T/hI8cxhK3+zoudFVHd3XpN5l6U0EYfItQl5s6pGXzPoxUwopeTYe2p75LSZMXl8KCs Fn3ash6OiG5JBy/Qti9VeCNXx+V5oRkv0r+bgWNjd2JLJjK2QA4O6Anvr5aXmL82pguCA1mp p4CpSZRkaz9ebwgObmP60VGM776LPTX6hNZfUh8+foMN7T8v6Mpzg3Hpjc48NlkIl27X2L05 Qqi2lHbMOueD8FdO8ukFaGAbxbfAsVliv4wCb08f8cuVcaOWrL15//EM57n2YShswFT2xuEd DVU0ei43PL59usBx/3x5+fF28/Xy9F2qT1+N+y7yF5ZjFXjRmlh4tkds0Q+YFLspMsejZR07 g5zDh2+X1wco8wxnlpRCU2tlXwQBrQQXPFbQX7SkLRHQGvKZIKDf+2eC6FoT66X9CQj8azz4 Af3Uxgnqkxfq+5BBYHkImAksD40SwRUeois8BNeYBILlJoBg6aysT2FoeReYa4iuElzjYb1M EHkBrb+dCGzPkxPBtY6Krn1FdG0s4nhx4dSn9TUe1te62vXjxZVz6sLQW1o5Vb+uHEtAGYnC Eu11pnDdK3U0mv2VSdFf5aN33St8nJxrfJyufstp+Vu61vGdJrUkneY0h7o+OO41qiqo6tJy mWUEbZak1aLc1f4erA6L3Aa3YULb3ksE9pMJ0Ks83RmyL8CDTbIlrk1VkTSUtoqj8z7Ob2Oz tjTyK0VgoE8ndjyVAKM8eEfhKIjJV9RRRIr8yBD1srt15K4oaGgwC9DYic6ntJL5VZhiXG2f Ht6+2s/VJMO3Z1p5xCnQPtDy7DkRhCttixHsqI1PoaiWxZRd54a6vksK7WSKEFx3griEZ5FQ Kk2HzItjhwfVbU9kvUQNmqb8eJhTe6U/3t5fvj3+9wU1jUwiM54EGD1mPGlK45WD4/oscUXK axobe+slpBzqzaxXtqXRsOs4jixIpq60lWRI1YxXQlddoW2cFFHvOYOFb8SFlg9mON+K8+R7 uIZz1fdgGfuhd+nonjLRkHqOF9PVD2ngOBaWh3RlxVVDCQWDztqXDB/Z37oEWbpadbHjW6vB K0RIqaLM+eJaPnGbwqhaZgTDebbWGZbeV4jmSfcBiSwXvWlpCgR3iymu3B9x3HYh1HOtY/tj snYcy1d3hecGlgVU9GvXH2xstnAgWPzp1MH3HbelAlgpk7dyMxe6eOXRrDD8Bj52pRxnxM4l b2lvlxt8Pdq+vjy/Q5FJ/cyMY9/eH54/P7x+vvnp7eEdrnSP75efb/6USBW1etdvnHhN30QE PnQtBtQcf3LWDp0UcMJbslEJfOi6yxWENhmLvWnBKrRYqDJ0HGed76rXaaqzPrFQ3v/3Bk6V 18vbO6b5Xei2rB3o8FGIHPf21MtofzP2XYW+6lW+D3G8imjhc8abXwW4X7p/NvTp4K3chaFh eIshCGOh9y0SNmI/ljBtfPpKM+MXJl6wd1cWcXacWJ6uB9cmrnNl4nqLE59NzCsT347H09+J 7b2Hk8RxLN4ZYwVeaJ/4p7xzh/VCA2Kvy3RzKoKKT4VFZoEX+yqDrXhxl+D127+V42lNwjwV FwYDFtPCJtB3IB3YS8MGsdRFGIQ7WWCej2Tkkmuxv/npn+0oXQMC38IXItr+hdBBXrQ8AIC3 r1a22ix3XbHf2beyMlxFsX2i8v6xmLUhwWHoF5cqbDSWYIvjRuJbrkaM9WKDw1ttrlLQ6lNB ESHFNQLavlUQrBfXIe8k+36WbNc2QQ3ReXrtlPYtr1p8esDly3NoW8iJYOVaYo8jRduXXmzR YMz4hRmI56H98z9mLshbaIhS2yeiuEOSCzEVR/zCEsQdNV7YJ/gYeddm+sKRyQ+dyGAw6Tvg 7/Dy+v71Jvl2eX389PD86+3L6+Xh+aaft49fUyakZP1p4StgNXmOxSAG8XUbuN6CQIV4d2Gg NmnlBwsHY7nLet9fYEAQ2GUfQRDSmihOAZNlYbrjbubYz/bkGAeed4Z+vEZyWtEB8aZWXHPb L7rsf7PvrxcmFOwa8dWjyXM6mgdVDvw//0vG+hS9r65IoCvVMVgxUZOauXl5fvpb3GR+bcpS bwtAVyQU6Ak4Y6/JMYxqbW4AXZ6OFnWjmuvmz5dXLi0Tsr2/Hu5/t8++w2bvLUxfRNsnH6Cb hSFnaHuvowPXamHtMPxC9Rxv36FQn2XHlrsu3pVLKxfwC4JY0m/gQrZwSsAOGoaB/TZYDF7g BPZly5QH3tKSwXPUkjIJ0fu6PXa+fedJurTuPdpNm5XPy1wN5Myn18u3by/PUqyCn/JD4Hie +7Ns6UmoqcdjzVm6qjS0GtamLeDRRF9ent4wLRWsh8vTy/eb58t/Ldx3j1V1f97mZDs2ozhW ye714ftXjNZgmCJjaN2iOZ780VaRH4VtpajBx4d6CcwV5q8P3y43f/z4809MUGvqzbe0vFdV DewSei7vUQ9O1ckjwj58+tfT45ev77CNlmk2Gl0b3wQ4bkwszOoVI33AlastCAgrryff9xlF 1YGctNuqwWYYpj/5gfOBynWH6KIs1p4nqW1HoO85elV9VnsrKh4GIk+7nQd3gWSlVmXmT0Jo UnV+uN7uZPsg8RmB495uVb0nYvZD7AeUYwcia/TK8QLJSmSTpLdlsdv3er8aeD3204yZXSQn TmYkD39XWjJzzXRJhn55lCJao1FdrmfkgnObVMPktG2gmFvu2lJ3cshqMs/QTEOF+JixFqdl qflT4DmRmitoxm6y0HXoC4b0cW06pAc6GL/UkD4UY3Tk5TU4crzPmLud2Haf315AYv78+Pb9 6WHcmcxly7c3+NHV8kOQAoZ/y2N16H6LHRrf1nfdb14g7b9XWh/pjC1y7pWuPh7MlJr7IqPS aCLYEAQxOTpNjnnLtSJqTnW52IiQgWM3oAdjvU+Lc1n0PXREfsiKRInCjhQLnkFygLnmru3y D+ecAk4PdXP/oEn8MbFVy2y8Jw+hKv21y37FIjf7l7f3xQznWFiLFIEgFoR136nAXV1m26Lb q9C+wux3qvsUgLtsX5gQDEKEhvYpgSoOfd4eMDQ/x0tnWbqcE4x9xJ2lazDTcJUWW73GfUcl 20KMiCgpv2RUmCFBya85wkwHECm5Yvf++OlflLgzlT4eumSbYxKJY2WKU3ItV4fykN/hniIN Gv7SfX5mGPcLUo6tGVcdy56HL6VOMKTbtLiLHXIg3t9hRtbDjkXQ5tYIsLcRn80KJgff8YI1 LXtyirbI6YsSR8NRrEWt1AjuPJsOibOOSew9WgkzEwSU4T7vIhHJQ+u41nHwokxbFjGSvHTh cNG1sDIFC3/kaMPFgJ4JDFcUcK0IRyPUcXUoz+6m1yCgRnQ4hrQcnrwRDBa20lsGYGAw2QQB C2BQVXI8sgmnJnGfwaQoOWJDjygUB6QRwIiNVefg+fvJyGQTOlQfVRmc+8baSukimwCmrrfq HNnGmiHksD7avMy82KEep/kX9X4gW1IzoAgGoUH7NEG3Zh1apsHaHcyvGyOB2Gc2EWVDn8HB X1pzde855gDc9pkHc9hWU9H57rb03bU+nQXCI9gXUf82ZZ8aW+y8UzFNyR9Pj8//+gmuq3CU 37S7zY2Q0n5g5rab7vvlE6p5UDoQ29vNT/Dj3O+Lw676WbogseHC7DuVyY4tuxHvyXKACaB9 HAZb0kBoQLS573N9DFkAPsviwt1BH3QEetHK5HJX+e7K1DFhh/Svj1++KIcPbxuOhB13XiTA 5zH+FoWr4SDZ170FW/WZBbPPQSja5Imt5CRuG983UqTN0TYUI0mS9sWp6O8tbajZuxTUmGVo zsr3+P0dldtvN++8D+fJdbi8//n49I7GZC/Pfz5+ufkJu/r94fXL5V2fWVOXtsmhw3Ti9s9j 3uD2hTvSwc2qoB+GFLJD3tNp6LXKepTlLJ0y+upNLSRpCmJEsYFbfH9P1I3h8XmO7akIgpik Yqplq2Rz3Jq+2d39IUWvezm91x2DKhK8KE7qoBjqXGGioEPdF1uKV0HU5eUWhXLVxZjjYM42 tJuGxvtYZ3IcUJdTyrl499lqFak+bejtRXobFhWGf0+LAnUP0m2Dp6nHoc9LGQw/R+Sc80SA 25r1YaCCufiHMfM7Jagcx/LMZwL3b/82cwzFWlSHbDBnGN3pMgm1Z0r4UZ6V255/CkK5wzDQ 3aKTcdurTqX4G+P3HvVaMMcs+geTLAqC4tAclXV6yhpKk3Ha1+jEorfCoAdL1j6OPXV1Spvr cHzaokc7v7bCktwl6b2xfFj02beXP99v9n9/v7z+crr58uMCNw/5Yj350iyTjh+0a/P7zVE6 Fbo+2cF5KY1NjcZi8udyiHm50tF8e2UrrviYn283v3nOKl4gA0FFpnSMJquiSxcmhaCS3NP1 zwAZsYxkK0UJLIcHlcEhCZYvAjM4lqO9yGCyktiNiX5t0sqPLD4QgiSpmhI6oqgxmwF87nXa JvX8UCe1EIY+EhKcwVKhw5PLeI+aKklKisYTunPDyiULggy+zDYrbPQuQGPHHCIk1tKaz5hw ZbFOGUl6kPDpZy2Jgky9IOPNacbAAQ2OKF4BYfEWGimqyvcSej8SJNsyIG1px9mAAS+K2vXO scEY4oqirc9Exxc4gQvPuU0JxtNwwBA21D11XOFNGnoromiSfXA9KjSRwB+ApMdEHYE56gJX E9UyVLXE0UjhhhlVcZlsmlSsF2MdJ2YRgGaJSy0SwCwyAvhjQX0D0wd9oHUqgqQLyMiFAht7 gTkpAWhOSQSeiW+95f9yQZDuoxlRp31eH8455pU75JNutICPf3t/+PL4/MXIuvjp0+Xp8vry 7aK7bCQgfLmhRz5lCdxK8R/WquLVPz88vXxhD5HCbgCkfGjfbCyKXaofAeHFajNLVcqNjug/ Hn/5/Ph64TGFleanNvrId5UAlwJkDSU+4g2vXJXJaywI59vvD5+A7BnjPFk6au4NV41FBpDI 4vdzvV5h0IGMTXYd3d/P718vb49Kq+tYjSfCICuyVWt1rDG47f3Xy+u/WP/8/d+X1/+4Kb59 v3xmPKbkBwdrX3EG+4c1iMn9DpMdSl5ev/x9w+YlLoEilRvIozhYqR/HQJbEMSNWS2Bgb4pH /bi8vTyhtuXqAHud67nKhL9WdnrVIVa5Jnty7wRVjGcOaCXIxXDqZCeLoM3dvxMMb0WK+swF FdOImnVPGW1PWb7owo5J5ojKeWKzk5aEen8/V5yxX8Oic+RICxdK06Yref78+vL4WbFIECDp MUp04aZO2ozgc9edt80uwVufcrU+FN191zVkHP7bLlKSPog7A7s6trWiQxtR26Kt7hIyY8dI Mmp+dLCSgXIC1g1qi0xMm9xR7Z+KTYtaWrKzJ/7bItvlGQ7TIh1mvqStbTBXGRu6/+HsSbob x3m8z6/I69M3h2/aWrwdFUm2VdEWUXaUXPTSKXdXXmepyfJe9/frByApmaBAV/VcqmIA4k4Q ILE40ybUWRhMPSS29+9/Hj84GxMLcyqoy/I+6jIc2g23ujdZmifYWhVX7/QgW+CrDvYDOrzn nXdlhgTQP3vH0o93MM3paH3BxuJP8zwqq8400Ri/rzArYFd5bLCjHabpjHNjbuEHhtyDSb/a G0HZJaHSjCn97gbYXJlX9BHwBJV7nu2YQXNt5SbjaDAJ4g9p6oa34jBp0MKEJxJp0e9X89n0 bjd+en3480K8fr5xaeTk/W1fbU6joiB1U12mZGgFhu4szLuTIUvfJAfDmIpPYvh7N53V8wzF mGvxDM1NH9WXZwg2bVs0mPN0QqIJsq4Ou86+xpZ5Ihc2tLrJbVCTRNPuqxx7rhoVx598dGhx 9s50ZUhH6qYYUs66ataTmKjESJhVaG/OcC0w9pPdQ52z0h6gTky7UDdZEfnO6ktYx01ql4QW AttG5XWobaRucZ3B8QQHHFViFK7N+sDnL8g0RWlfzFL0kEnEPWBFLah8KKu1k4sY6EJvIlGv Zvx9DNAclgW+GqHFACeIyfSFdUZOW53TkDMYGToTFbD60OiEMNKNyGErFGfWTtWVmGi0Fs7p kxnv6fSoLN8W7FYM5jIC7TTaYs/M2hc8+LB7bGPwMzmAccH1dUQX7Z4ESVbZUiuYUaM9A7HV kHScpJaTy3Q78S4waskDw7AmO0Ob3a0C3LtFs2JgVPfSYPaBSjUIbUtxFON2uhNUplxzd8Yw iN7AOMyKigyOZikVAsUi5AO2sofDOONRll9WxpsstqwgkDFgZbHb0y1yyo3d3MDKw8/YuR5l VydFhEGVIzd+lwUL4Ho2fsQufH9mNVv3bDCx0lBpTRnVseizmtxC4XmG2WEdVeDOiIvkeqjE PAgWWV+IravpcgM5OybbA03hFLWsKoo9/HuIhmuQ5vj8+nHE2IzESmdUsyZY9dX35/c/OLOe poZ2qyZs8ckbAewSoiWM2w6N/26yk200rLGXrzegPhsGzwpRxRf/En+/fxyfL6qXi/jb4/f/ vnjHR/nfHx8Mi6gTq4JjuC76BKSzrJy+FUbPT69/wJfiNWay5soE0HFUHsxEERqaX8FfkdjT qOEqnTR0KM7KTcVgTm0h20+i09TRVEJVmMWflDSmI6qHMDrHr3wHMde2ygpNtqPKE43iNAaC 586bE4UoKzMpk8bUftTrIPKnFk4bcmJMa082JqMNGcBi00xm7vLt9f7rw+sz37NB2qyrG3Le QGGXIMqI9tJsGluWuqTp6l83b8fj+8P90/Hi+vUtu7YqPG3AfRbHfVqCZsxppEkdRb5heXu6 xflBFcpo4H+Kju8pstltHR98x9KSw1p0K34/TspVl6Qg5/71l6M+JQNfF1tTLlPAsiY9Y4o5 xcdpj386dp1mkMbmAQis9yaKN1sKlamQbxqSGxXAIq7hTCQbDKBFAUB2FNgGyaZef94/wcJw rDLF8NIy60VqnQxbcZlZoDyPyUHBZlahWFGk/Lyx7aKTriUczppiOEW3jaHKjVCyjowCtbhI 5CKV0DkSvKOSRmOpGXdPpPH8wtVII31ata9zh0SK7ZOqAZzeOrHdz9EH/4CeE/32Uj0aeZdc NN3j0+OLY/t0GZyPXX+I9+ZOYb4wR/7ONPK66/z1YmkP2hCQ6qfOR0MLK/AqZ9OknCl02rXx yW4p/evj4fVFH8hT42NFjJmG+y/kEk0jNiJah2YqJg2ntlMayOWTPqECV0zKE4nMBO3s0jTX s4bbSaEGcFvOyZOfho9Zj6TNANPYpl2tlw4nO00iivnc8SKsKdCnwGF3i7Hsm1sifbZen8M5 0/Lm01/u0GaoL1NHDACl326K2O/TS/69Z9Aa2fw/mTmZGRrF7DcbosGPsD6+ZMFoS37KO2ng r/BSsld5jgywNioDqYOrS/25Eew3E1JZKzAkaVinSHyTRNxM3LI0+FQi/5Y4iDT6JZGYIQxA LiF9lHR5sDQUVw2g2WcHIMkvcllEPvWIA0jImlZcFjGsb2mGl5sFnKB20QaGtCSJfGqTlkQB a6yQFFGTmM50CrC2AOaTgBzqVtca4D21A4cOP+fwaDlr4a86kRCXMwlwJMNVODIiV1385cqb eWZUuDjwTQOeooiWIc24qUGO97UBO7yvGWBXRkXArUJHDBHAreeOALEKx2ZdlpHjTF+YLl6Q V3sRRwGJLSfaq1VArQ8QdBnZ9uP//9fycd33ItsWEexKOMPpnlrO1l7DnxP4duxzsfsRsSab bUmC+eHvtbV3AcKPt0TxPiaACpeON/7FjFYIv/tsg2l266jB18ncgbY4wnJptXy5WPV225ds akBErD368TqwPl2tOGN/QKz9gHy6DtfWp+u14/ImWYeO4C0RWud0aKHDH1xSVzyLhHMrmie+ kwjvbbK6QZXYQRFj6JnZpJoBiz5BiKPcb42Mclu7ykzLQ5pXNaYRatPY9Zg4yNlsxXi9njco eFmV7zIQgtjXsI6YJ2Zl5Hed/nqEoV4zKRI0yWXiHKC8jjH3saOdgA0m9eRt7IdL6u+DIEfE b4lbcztHYcxAiCBDznwL4HkkCKaE0IziAPJDNnAoYAIS9TPq1gsSjDKuA39G4y0CKHREuUDc mj0bpWlCm15h+lKQgtH825qHIi37O2+1ck5FGe2XK4dciY9DjjlSArBar5b6esAVZnuVnCTg bPqFhB8ccADT5NNx1PTb26Zydkk78TjRdRo1jm4JuWb7okqmflVK5FWdY20JFEGyEUlhubma GGuCAAWb2tlW+eg34Qoa28rRma08Y+AGmOmuN8BCMaMecwrh+V7AOQNo7GwlvNmkNM9fCSsX uUYsPLHw+eBwkgJK8zhmo5DLtak/KdgqMN0FNWyxWtkw5SRHoG0eh/PQ2Hs61SVsSjoPAF8g 3M2BD5uFN3OsG62tj7vvn9rdyVAkF6kVZwRl0SYFsSnnw4xMP9Z31d+fQI23BKBVsKBPRkUc 2jF7xjvisQDVnG/H58cHtEyT4cSpFSK+5Pb1rhdpKRynkqJJ7yqGaFQU0oWp9KvftjIhYUR8 iWOxIkdUdG2nuxZxAvPq2rPQoKzBHH5iWwdEIRG1CDih53C3WnfmLE+GR4UkePyqAdLKTMW7 MR9PeAJTDymEHjBh5j0Toh6+Gws1lRdRj18pLmxrNyPBbk9ut6cFW0oRbQyPI7Nj4cyoNmNM LMxvJJcxL7fPZwvL0nAesDFHEGGuIPgd+pYYOw9tu08TxavV8/naR+9AkVplIdz1RdCQhsxn dh8Wftg4lEbErhY2/WpiWGsg1ws6JwBbmpqX/L2ivxf22LgSPiJq6YiEiLg1J5mA8B7MLE1g 5fJXSOoKg9U4ok2KMGR1sEGITGgMCJDvPJfWi7LfIuD8DIqFH5hHJshsc4/KhPOVT2W4cOnP KWDtW8qsPPYdHWuVJ8rKR8du/jwE/HxuhsRXsCVJYq9hC9PZR51Vw8hYaUbZLTcavX/9fH4e IrNQzqKCu6QHEPitLS6jkCi8GwNfpiV1c5yQqJs59lCatE0HvTr+7+fx5eHv0Wr6P+hqnSRC R9UzrNW2aGl8//H69mvyiFH4fvtE23JqUr+e26HgiE2DowhZRv3t/v347xzIjl8v8tfX7xf/ giZgPMGhie9GE00etwmDOeFcANCqjq79n5Z9it91dngIJ/7j77fX94fX78eL9/GYH1uEF48z yl4R5AUMaGGD/IVlf981InTECLgsth7L3zddJHwMJmrwuROM8j8Dbt+J1ftgNp85U4PpE0vq F/Lmj7u7breBlQfOPYZKFjjeP318M8SnAfr2cdHcfxwviteXxw9bstqkYTjjHWkUjuOK+Owx s5VXhPhme9mqDaTZWtXWz+fHr48ffzNro/AD010s2bUmd9qhBkF13V0rfJ87NHbtnp7YIlvO ZhxvRIRPZmDSQMXQYLt+YByG5+P9++ebSp33CR2eLO5wNlnJob1sJdCRe0tj2WuyyyLzFkS4 xd96yRorX0Jd7jObrhKr5cy9dEcCx1100dEjPysPfRYXIezOM/vBJHI1DYlgYy3ObiyDxlmO 2ny5KBaJ4LPGnplQ89zB2eiJ/5cJPT0AqTgVMoQaw/S+JL1QR60xzXu8LeJ5V4QZMFjZNA8w Ia+xwOpErAOy5BCyJqtk5y3n1m+TA8cgXHgr6qcKIIctN6ACR5TTGIP+cLsMEYs5qWFb+1E9 Y91nFQq6OZuREFrZtVj4HowBx0tHlULk/npmZnOhGDOVjYR4puz1RUSeTx8SmrqZzVkuk7fN 3EySkh9g0sKYmoFEXRi6gqZqJB9+tKwizxXKuarbgE82VEP7Zbgno10i87wgoL9DchUm2qsg cASehn20P2TCEZW3jUUQOuJPSdySm+FhSlqYgLl5wykBKwuwXNLbIZGHc0cSu72Yeyufs/w4 xGVOExIpSEATyKaFvL3hCpAoGoHykC88R96dO5gjmAmPZT6UUSgTpfs/Xo4f6kWKYSFXq/XS uLqSv0297Gq2XpunpX4vLaJtyQKnZ8YJxbN9QAELI6+LcTBXbqiU7cpC+NfQoepzaOatdFgv uyKer8xEzxaCCm82ktwoDMimCIiQQ+F8gRpneSGyM/hfYz6c709HmkdeXszsyQUQIdRyx8PT 48tkWRjHGIOXBEPApIt/X6hUPE+vL0f7UnDXaOtzZUzA21eoMInNvm55M4bBRYEUxZGcIWjR bQ794Qw0Pc5vxUZw7RyHgu+wPphfQE5V+a9f/vh8gr+/v74/So/g9+lVpDxowr6ueOO9nymN KETfXz9AunhkbDPmPuVtCcZxYB/Fo24eUj9gCVo5Ho4AY146xHVIzkQE2InhAGSxVZOYuEq2 dW4rAo6+suMA02PKzXlRr70ZrwfRT5R6jJmkQWJjuORlPVvMiq3J8Wqf3gbjb/s2WMIs/S7J d8DuuZMkqTHrFdFDaod2lcU1DhybYq/OPVPbUb9ttqyhDo5c5wEtQ8wXVMpUEJe1h0IStoiw YDlhzHWTiim7llD2EldhrCFt5y4tdFf7swXXxLs6AjnUuAfQAFrpALQY8mShnIT0F/TTnq4f EawDknF8SqyX4Otfj8+oJCIT+CpznT0cWVaCIubccV2ZZ0nUYGjftD84XmwvPZccXmfllkU0 GwxL4HiJFc2G1fZFtw7MHQ6/5+RYhO/IszVKT4FLfznk8yCfdc4IDT8Yv3/stb8mKjd68VNu 8oOy1Hl5fP6OV3KUs9AzYRbBEZgWvNct3gmvHWnJgCNnRY+RQYpKWf3yZHm3ni0c4rRCspfO bQGqFLnplxDOXKaFg9RUDuRv3wjogrc83mq+MMePGxtjJd4Qk3EltzTXMkEtk5uguUbzbKIL 5/0m47b/F+mHF2XGXh/c6EAmibEs2AZEWxvQUAtT4IBu7iJP0pgDEa5Q4Guu6d2Gskpp4z2i +A2nC92tVLN4g5q7shb9lu0mFDxGm4beJilxq5TJHJpr0aa8gIbosh0kyaE6Zb+DJcdVcZmV DjNzjB+3RSefOt4BS+G362Qyx7rrKL7qaaC1tMlgPrO6itsoN+dNpC1avLZNledUvlO4qN0t uZczje2ER2//FPwybfKMC4Gn0aPvDQfWj+I2dieSq2lNaInkmH+JBiE577dcTHBFkEdlm11P y9XPT87vpBPW9DPlmyUDW/ZRw6fkUJRofeMs3XReJgjlbliZx76BqKnRg8KIuODkFI20UkFr KCoGRa0SytrFVTEG9TjTs0nYEgvfZu7It4pi2HbT2scNuc33PLdWdHe3JefKoF7MhwUlfUCN GzeKXCiraSVa7G4vxOdv79Kj4sQ1gQvBxooxqMepGAPYFxlm9yZoBA9vmzKRQEtcaRDdba2U OgQLwzufZfgtp5LIWpWXoedHSOXbxVN0gCHU3LXpBd1tf5ZMdhlp+6iM8oqXhvATGVtdDcLO 0ZH4dlvuhSyNDiAaaYoGPyXXJUMICey1M9LK8H0pJN1P0LjGuRQ+0zaE4sQmTWI1usFWR9RA eURgnOlzTYHunp2BOErSMk77tmrg6ONc4E2q6ZocMAJ2VzNp4oiN8gPngYI0GDBAuhhe64kx 10fWAR92bAftbj35SDtpW7OsMHhO4BlqzTKlwVwSZTVsAnMDSq7fH5oOg1pO51DjG5Av6MfK Rz1YzhEe53s4/xu9/emMyQNQzrZ7VhXNuYkvDunlvof6oJX7luXjJtlKBtOfjG/dRb2/Kgs4 Qk2hjaA4RoHIs60r6uA8AYZ/OLcPkWC/4UNiDPhOuOe4itO8QgukJkkF7ZkUXLi1oz3kr8OZ t7Zbb5Ndc8MiMTLDCwqPm7RoK5emSMh3Qg71jwmFe0CGxq9mi+5M45tIut8zvVf2tWkZTBgb JRujg+EGSkSWuCfh5DE62Ucjqr2tU2vpaWE4qVVUKxYpGYYbrSukx6P2Szu3rEYai/8bJKOg MWUeJiqwqx+RZ5k1Ws2hnbIH6j120jm2J8JQE9K2iDbbhbMlN9PqdhcQ8IO18QYa6fvqrcO+ 9vf290mkRRTmW5kWSKsNVPoB4a7O6nQyLkoQR45dOUdF0WAmJCeJtsRF8c5W+IdbDCKqjZ3F AAAxcRA3/Q7hh46RosS949vvr2/P8vrjWRlQcHGvz5GNAq30I53E1BuOkzJpKkdKqmm8vSTi 9JHyUKRG7Br5U13M20CplGYTWgRXcdUS7V97iKabveAMa9WXgxybprWKzcdiVckEhb4qkyqR 2U/qG7GKH2+wIv5lVvUbfQpEEvE0IztyVzOSQOPO1IMSmezAubbIDYjR7DhFb2QUsi32ACkL v+kQDaE/zs+LKA+Y12ZbmzEvlNvEUNvp7hHDyUyKU1ZBNxcfb/cP8qLVvjBS8ZKM9+gCw7+1 GP5esNcpJwqMU9TaH0sDQcdTd4GRYZo4HcJm/IhszAXC7iumV0MbUbE1G4a/+2LbcEqvg6SP zAtbHYaobuDMtpxGJigZF+mEHwseCC3j6xGPvHBouY3T7JL/MIvTcObAFVG86yqfwapAlvSi UDZw06TpXarxzEjpttSYDEXHWLCKbtJtZnoVVRseLoHJJp9C+mizdwxRUU+nV/DRVUcrdviT i4tkgscTBONiQ5+6k+GR8W7Mpn7boxPTdrn2uXWlscIL6Q0/wl1RAAClgy1yb9eTJtfAwmqD NYvMDHeFv/AS0YrMIPKsUFeLp50HIMWe7ThBxoUtLBH4u0xjNhBdtUcCoxbjZTouWxsxvGrH NN8NyB7pdcqzZIxkd72PElfE3VPksxZkAZAU2r0dZXV4BKWRL5Sd8uPT8UKJHMYjyCHCt6Q2 hYWGTrskdROCKpHBJMfGOk47jIG3sQKgKFh/qeKL1pyhFeZi6RGf0cgsBUgY6Ol2Syi4AjAf SNzcwsiSrWaCYadvBd1AGOyOz9WzESo1jkmfOLPlZAoz5Lc61RA5P7neV/QqRQIwM4rUfeSS Q4doXpZsAK+/uIma0vVspyhc2UcUtm1SM+zPpmj7g2cDDB1CfhW3OeGh+7baiLDfcJOrkL0p 0OF5TQAxESJ0phmToIKZyqNbBwx4bJI1sDt7+M9sGEcS5TcRnOGbKs8r7mbd+CYrk7RjKyxS GISqvh24ZXz/8O1obJ6NiOEMSulyk6DpdBgB3mUhSoh/P35+fb34HbbmaWcaC6CK+dGWGOAE edKYnhBXaVOaY2dJ2Bi3ud+hz2y2xcujGHa8mQBJ/TfM4kmFmDZyZOeYfwZ3LQb8TAtz2hpM smStiFTu0t7iHQNQZ11yLfMvm43w+eHYX2anVlswOKEOURmnibx24t7BRsr8zjhERugdMeI9 gYWZ502BI2T5Q5RQ5psuatuGbaRI472DSZ06sm93KU5bRPlf3EQF7buCYCY67vmiKqxpURCM J46RaW5pBjuFRInehNaiJZKi+o3Ji3I8TORQK8OP02pWJDDII5pb2QNVaBYyQe5iN3oV+m4k Tpsbe6bddteGRE086572gqM/162BnmmK2cGfaQbp84/bMWnBL0//Cb89/DIhszJzazjG15wA YUGaHYED8KZqrkzWwSuprMU2qKVxRTMLaFBfVk0BEs2d3CJjYjvuMK/6m2uTyxHxSHm5Hh8+ 39DUZJKe7yq9NePxwC84eK73KaYtsw+EOm1EBj2EoxwI4Ujfcl1qG7ymT4aST8xRCTYaw3wI 4D7ZgcQF6g32mUq9mqv0CbBW+ezYNhkr3Q6UxtmhIRu+RD2DZ4rCxIpGhjvRRnjioPBUwEzt 0rym0jSDVkX88uv7b48vv36+H9+eX78e//3t+PT9+PYL06i2Kqpb/u5upIlqEHMLh5v4SHUb FZzGM+IxEbb4v8qOZbltHHmfr1DltFuVSdlOMvEecgBJSGLEl/mQbF9Uiq2xVYlllyTPTPbr t7sBkng0mewhFau7CYJ49BtoWceRP2CkwEb5KsNTJOzYmQRrKcqEY/ukSBMVSnWZgCqDfoMs z6zlNUCmbh93BMrPHiJshCJGuMUtLSvJa7hVnXXpun7ZmbXTcTTe4BHG++e/929/bJ42b78/ b+5fdvu3x82fW2hnd/92tz9tH3DTvVF7cLE97LffJ4+bw/2Wsun6vfhbX3R8stvv8EjO7r8b fZ6y622MmQKYa6IHzkSQtQBjYVc+NT5V0aDTwCBhlbqBfrTo4c/oTr67zKaX7rD/804DPfx4 OT1P7p4P28nzYaK2Qv+9ihjYamGq3QoIhpGw7i0wwRc+XFrFunqgT1otwriYW/fb2wj/kblV /dIA+qSlVXyxg7GEhtB0Oj7YEzHU+UVR+NQL0xnRtoAC0ycFs1bMmHY13H/AtSttejB6KhGA fUyVWjkHhU0ur2ssx6DLuto0s+n5xWXaJB4iaxIe6PeW/mNWCCmpfZTi9ev33d3v37Y/Jne0 dB8Om5fHH96KLa0aagoW+StEhiEDI0J32MCsiIYKQeovaMqlvPj48dzKHVNhkNfTI2aP321O 2/uJ3FPfMUv/793pcSKOx+e7HaGizWnjfUwYpkyHZmwuVfvIHPQGcXFW5MkNHt5inhdyFlcw b8ONVPIqXjLjMxfAypbtlAR0jBwl6dHveeCPbzgNfFjtr+uQWWgy9J9NypUHy6cB88UFdGf4 a6+Z94E2pK9Y9kYP68jWzcgUYFXnbpDmm+Pj0Bilwh+kOQe8VsPpdmWZ2tcxtCcdtseT/7Iy fH/BNUKIsdV9fY3sdIwiSMRCXvCZERbJCLeBbtTnZ1E89XkMy+KN9e2wregDA2PoYljOlKbD jUqZRqM7BPFWOl0Hvvj4B9/e+wu2wKvecXNx7rUGQNWaB/7o1LnsEFz2VotN3/tNoTsvyH25 WM9K61JIDV4V6s1Khdi9PFp58B1/qViuUzm3SXsUWROwlxS0+DL8wDQcJPlqGo+vUKwHnyTx OBcXVc2fMDUI+Ct3WjkjR3o/pf99RjMXtyLiJlMklRhbMi2n9ydV1TZwgWUhM//9Vepvl1r6 MhSMNBzkIXh/SZ5aGs9PL3j0xdKhu1Ei/4fPzk2nmYZdfvDXYHLr95g8Hh5Ue9bUWY7N/v75 aZK9Pn3dHtq7T7juiayK12HBKYtRGczaEuUMRrNub1UQzmGhDAknChHhAb/EdS0x7bFUHmVf +Vtz+nmLaFVmt58dvlW2x5Z6R1yyARaXirUB0FL3JS/2bq0rfZiWyvfd18MGLKPD8+tpt2fE KV6GIKTfIMF51kH3J/xMMiGR2mtttvNAS4pobNSIilUWfbpWwIFGG9/Kz+djJOP9asl+2jNH dRzvXyec3KbmXJREVDdpKtFpRI4mzJDrJ8pAFk2QaJqqCQbJ6iLlaa4/nv1nHcqyjqfo3pZe KLJYhNUlRsSWiMU2Ooo+tKpbVxjOvwmNfNJRBv4Vn8hgwlYMv048y7BOjFThSQwmTnsfvFrr eCPIn2QtHCd/YobV7mGvDj3dPW7vvoHFb2SlkL/T9PiVscm1fHz1+Y3p7VJ4Zd8ZYzbk0Mqz SJQ37vs455ZqGHZWuEjiqh7sWk9Bux7/Uj1sI1y/MBxtk0GcYe8o1jn93F2HMsQ0kjjDq1Mp uGR76cVQ1DiIQVvCemfGemvPP4AilYXFzXpaUlqruRxMkkRmA9gMz3vUcWKrTnkZxQP5gSVG iLImDZwqexqvnLjmwSK8ndW7yR/UbrAyQaBYIKv6PNby8zTzcB3Xzdp+6r2jkwJgzHGuCWC7 y+DmknlUYfiTiJpElKuhBasognjg1X9YSoQrHULu3CJwvc6K6imNI+3KUjIYVhPFNcecYdVF eTo+PHzwCaGYUeTCMbaIUtPWrAjq6Vtm4MyGci3zAbShyBlSs/3jo2UE5uivbxFsjpmCrK8v eRVcoyn1tWCvtVUEsTBnXgOFXVW3h9Zz2GBj78PCziNvC8Iv3svsknrt/if/sb6muV0lWFWs ypPcun3ahGJU53IABa8aQZk7PAjn1g8KyNV0874ZiBcVlmADtrKUMDSlMCQbpgLEuZ2Zm2Mt C+M3dYAKXKyBC87MiE5ExQzCRFAwcE66rY3N8qxFYNkGyy+DeNQxh/JWqlmiRtdo8srgi7Mk D+xf3bY0up/oiLs7bXWexjYzSW7XtbC8UHgEFpQqrqpcWsRWVgD8mEbGe/M4ooxAEB6mJoGB iEgWuUGJwShh5hMGX8TMSo/CmF02Y3mOcduAIzDt4EmrgRD05bDbn76p8/NP2+ODH94kYayK oloiVoFDLOzAluFVAWGsWJ6AwE06Z/ynQYqrJpb15w/dsGrVzGuho4huMoGF1GjVGCvDBLs3 n9+kQY7aqSxLoLLKvg2ORWcO775vfz/tnrTmciTSOwU/+CMnM3LRpw1GgufSrC01hW0pKY/r 8/nZxYffjNktsMIx9tPSIkowvqg1QDKjPQc0FgCKYdML02uvxgAUPwqBp3GVitpkFS6G+rTO s8ROg6NWVFxw2mShzq2L8YKmC+64hfq+Io91liTb0kqKBZUsCu06sb3q+KtDThNE/oDdXbvQ o+3X14cHDK/F++Pp8Io385nV+sQM9bmbqjQL9vXALsanZvHz2T/nHJU6p863oM+wV5gMkIHC 9uaNPStm1k0LIS63Wqs5dEetorAPEaSYgMoKNacljHRyC0aQBIAJX8wig3fpX11r+Lv9kNBP Zjep2uiS/SxBMXAa5DmnIhHRwupCFHCD3zeLD8ibIBcll9GEaPizjrMGJJGoRYU+ljkob2ct SRNUwgruEgCMIsHVx1bIAEu9GhOmoLp8mgWjfZFKnemrl/IvLU57MahovL8M8J1exECHnLt2 Df6NPBTsQ7xY3tRBVGOIbQWr854O1TKykVwhfEe+yiwLmszqPK7yzEnxtTGoZcCwDaUYOMS3 suQyyfseA6ec+t8CghQYHWdj0UbQAw7KTwI8yX+8xYxsOJVX0KDE4m1vkACRppJZpATC4Jcs U3eilimFinRCkYsqAwZYzMBomHlMJqOiyuqIgodUhfko28FQh0LSDhcCl3dvCtlYTABS00mz Gd9iFZGoy5+zUyP6deqN49y5H0UFxJB+kj+/HN9O8Nbp1xclCeab/YOpqwi8ZAWYTZ6bOQ8W GJPcG8MXp5Co3uRN3fMIzIppiq66kSEx82k9iEQmRzq3SUZv+BWarmvGmOAb1nM8+wmcjF+A qyuQ2iC7I/fugi7/f2zwVHYbSNf7VxSpJgfp81EYtDtxOIILKd37pJQLB4PMPc/71/Flt8fA M3To6fW0/WcLf2xPd+/evfu34d2hvCRse0Yqr5tIW5T5kj1CoBClWKkmMpBAQ2nERIA+7MGd WIKx0tTyWnpbpYJPxee9LcSTr1YKs65ALNvZcPpNq8pKmlZQ6qFj+lDKmCw4UgaszBt4reQf wcGlkIG2KSr7RXg/Ax4tcWze/nN6O6u3QP6P+W4bBOmLqWrllcO0iGUS0pxjUlNhWNZNhqEy YK3KHzM4jwslAkx7t2P88G8pyyCv+mogtGW+KWF9vzltJiil79BrabAbPYaxOS5aEmmgy9w4 27blyui6BR3efIpEF9j6oMWgHYN3Z8YDOWejPbZfFZZS5/V1J33LsGF1B7WTQiNY5qyG3kAJ G9Tlp2vfLDUozKcHiUCCr6nI0E/aKp2zMgZOXlWdVdhf32Z9pLM7r7RRUpI5YvpACvWm0lk6 nR00jp2BUjnnaVo7ddqubqsBtR9SOmkGQ4JuZIcE7yTCLUCUZGsZ20Y9HtoMinwHbrVZKoNB 9JZ7H3VoUBvX1SpGu9D9gqKUMoXlCHbO4Put9jTA4OPGUTd3Knu1SeB1T5UnUY6P3Hq1eYgv Mqo5shMMgUTrIM5dLuM5EpoUT7pGpsYFjGcKTGeF54RKq2XQYwO8x9JSndT8mavQ6rnpmam3 xxNySxTN4fNf28Pmwbpod9FkrCO85Rzo0shLeP8XZdMbc5XyROYc5FNaZMMtcm+WdSSXg223 s0uWHNOtqYgTpbN7FojzTGfUco4mpX6C0hnmS70CCttTDzOAgZZaKQIU/efceDJ15djozHjp vDqWZcsosNYqfGmUhw0ahdYn/A+GUSwzaLQBAA== --NzB8fVQJ5HfG6fxh--