Return-Path: Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S1757354AbcDLWka (ORCPT ); Tue, 12 Apr 2016 18:40:30 -0400 Received: from mga04.intel.com ([192.55.52.120]:39305 "EHLO mga04.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S1750756AbcDLWk2 (ORCPT ); Tue, 12 Apr 2016 18:40:28 -0400 X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.24,476,1455004800"; d="gz'50?scan'50,208,50";a="957328003" Date: Wed, 13 Apr 2016 06:39:02 +0800 From: kbuild test robot To: Jason Low Cc: kbuild-all@01.org, Peter Zijlstra , Will Deacon , Linus Torvalds , linux-kernel@vger.kernel.org, mingo@redhat.com, paulmck@linux.vnet.ibm.com, terry.rudd@hpe.com, waiman.long@hpe.com, boqun.feng@gmail.com, dave@stgolabs.net, jason.low2@hp.com Subject: Re: [PATCH] MCS spinlock: Use smp_cond_load_acquire() Message-ID: <201604130658.n9ttDvqp%fengguang.wu@intel.com> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="17pEHd4RhPHOinZp" Content-Disposition: inline In-Reply-To: <1460496564.2465.128.camel@j-VirtualBox> User-Agent: Mutt/1.5.23 (2014-03-12) X-SA-Exim-Connect-IP: X-SA-Exim-Mail-From: fengguang.wu@intel.com X-SA-Exim-Scanned: No (on bee); SAEximRunCond expanded to false Sender: linux-kernel-owner@vger.kernel.org List-ID: X-Mailing-List: linux-kernel@vger.kernel.org Content-Length: 50329 Lines: 756 --17pEHd4RhPHOinZp Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Hi Jason, [auto build test ERROR on v4.6-rc3] [also build test ERROR on next-20160412] [cannot apply to tip/core/locking] [if your patch is applied to the wrong git tree, please drop us a note to help improving the system] url: https://github.com/0day-ci/linux/commits/Jason-Low/MCS-spinlock-Use-smp_cond_load_acquire/20160413-053726 config: i386-randconfig-s0-201615 (attached as .config) reproduce: # save the attached .config to linux build tree make ARCH=i386 All error/warnings (new ones prefixed by >>): In file included from kernel/locking/qspinlock.c:70:0: kernel/locking/mcs_spinlock.h: In function 'mcs_spin_lock': >> kernel/locking/mcs_spinlock.h:31:2: error: implicit declaration of function 'smp_cond_load_acquire' [-Werror=implicit-function-declaration] smp_cond_load_acquire(&l, VAL); \ ^ >> kernel/locking/mcs_spinlock.h:91:2: note: in expansion of macro 'arch_mcs_spin_lock_contended' arch_mcs_spin_lock_contended(&node->locked); ^ >> kernel/locking/mcs_spinlock.h:31:24: error: lvalue required as unary '&' operand smp_cond_load_acquire(&l, VAL); \ ^ >> kernel/locking/mcs_spinlock.h:91:2: note: in expansion of macro 'arch_mcs_spin_lock_contended' arch_mcs_spin_lock_contended(&node->locked); ^ >> kernel/locking/mcs_spinlock.h:31:28: error: 'VAL' undeclared (first use in this function) smp_cond_load_acquire(&l, VAL); \ ^ >> kernel/locking/mcs_spinlock.h:91:2: note: in expansion of macro 'arch_mcs_spin_lock_contended' arch_mcs_spin_lock_contended(&node->locked); ^ kernel/locking/mcs_spinlock.h:31:28: note: each undeclared identifier is reported only once for each function it appears in smp_cond_load_acquire(&l, VAL); \ ^ >> kernel/locking/mcs_spinlock.h:91:2: note: in expansion of macro 'arch_mcs_spin_lock_contended' arch_mcs_spin_lock_contended(&node->locked); ^ kernel/locking/qspinlock.c: In function 'native_queued_spin_lock_slowpath': >> kernel/locking/mcs_spinlock.h:31:24: error: lvalue required as unary '&' operand smp_cond_load_acquire(&l, VAL); \ ^ >> kernel/locking/qspinlock.c:411:3: note: in expansion of macro 'arch_mcs_spin_lock_contended' arch_mcs_spin_lock_contended(&node->locked); ^ >> kernel/locking/mcs_spinlock.h:31:28: error: 'VAL' undeclared (first use in this function) smp_cond_load_acquire(&l, VAL); \ ^ >> kernel/locking/qspinlock.c:411:3: note: in expansion of macro 'arch_mcs_spin_lock_contended' arch_mcs_spin_lock_contended(&node->locked); ^ kernel/locking/qspinlock.c: In function '__pv_queued_spin_lock_slowpath': >> kernel/locking/mcs_spinlock.h:31:24: error: lvalue required as unary '&' operand smp_cond_load_acquire(&l, VAL); \ ^ >> kernel/locking/qspinlock.c:411:3: note: in expansion of macro 'arch_mcs_spin_lock_contended' arch_mcs_spin_lock_contended(&node->locked); ^ >> kernel/locking/mcs_spinlock.h:31:28: error: 'VAL' undeclared (first use in this function) smp_cond_load_acquire(&l, VAL); \ ^ >> kernel/locking/qspinlock.c:411:3: note: in expansion of macro 'arch_mcs_spin_lock_contended' arch_mcs_spin_lock_contended(&node->locked); ^ cc1: some warnings being treated as errors vim +/smp_cond_load_acquire +31 kernel/locking/mcs_spinlock.h 25 * Using smp_cond_load_acquire() provides the acquire semantics 26 * required so that subsequent operations happen after the 27 * lock is acquired. 28 */ 29 #define arch_mcs_spin_lock_contended(l) \ 30 do { \ > 31 smp_cond_load_acquire(&l, VAL); \ 32 } while (0) 33 #endif 34 35 #ifndef arch_mcs_spin_unlock_contended 36 /* 37 * smp_store_release() provides a memory barrier to ensure all 38 * operations in the critical section has been completed before 39 * unlocking. 40 */ 41 #define arch_mcs_spin_unlock_contended(l) \ 42 smp_store_release((l), 1) 43 #endif 44 45 /* 46 * Note: the smp_load_acquire/smp_store_release pair is not 47 * sufficient to form a full memory barrier across 48 * cpus for many architectures (except x86) for mcs_unlock and mcs_lock. 49 * For applications that need a full barrier across multiple cpus 50 * with mcs_unlock and mcs_lock pair, smp_mb__after_unlock_lock() should be 51 * used after mcs_lock. 52 */ 53 54 /* 55 * In order to acquire the lock, the caller should declare a local node and 56 * pass a reference of the node to this function in addition to the lock. 57 * If the lock has already been acquired, then this will proceed to spin 58 * on this node->locked until the previous lock holder sets the node->locked 59 * in mcs_spin_unlock(). 60 */ 61 static inline 62 void mcs_spin_lock(struct mcs_spinlock **lock, struct mcs_spinlock *node) 63 { 64 struct mcs_spinlock *prev; 65 66 /* Init node */ 67 node->locked = 0; 68 node->next = NULL; 69 70 /* 71 * We rely on the full barrier with global transitivity implied by the 72 * below xchg() to order the initialization stores above against any 73 * observation of @node. And to provide the ACQUIRE ordering associated 74 * with a LOCK primitive. 75 */ 76 prev = xchg(lock, node); 77 if (likely(prev == NULL)) { 78 /* 79 * Lock acquired, don't need to set node->locked to 1. Threads 80 * only spin on its own node->locked value for lock acquisition. 81 * However, since this thread can immediately acquire the lock 82 * and does not proceed to spin on its own node->locked, this 83 * value won't be used. If a debug mode is needed to 84 * audit lock status, then set node->locked value here. 85 */ 86 return; 87 } 88 WRITE_ONCE(prev->next, node); 89 90 /* Wait until the lock holder passes the lock down. */ > 91 arch_mcs_spin_lock_contended(&node->locked); 92 } 93 94 /* --- 0-DAY kernel test infrastructure Open Source Technology Center https://lists.01.org/pipermail/kbuild-all Intel Corporation --17pEHd4RhPHOinZp Content-Type: application/octet-stream Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICO90DVcAAy5jb25maWcAhDzbdtu2su/9Cq30POz9kMS3uDnrLD+AICihIggGAGXJL1yu o7Re9aXblruTvz8zACkC1FDtQ2rODG6Dwdww0M8//Txjb7vnx9vd/d3tw8OP2e/bp+3L7W77 dfbt/mH7f7NczyrtZiKX7gMQl/dPb98/3p9/vpxdfLj8cPL+5e58tty+PG0fZvz56dv972/Q +v756aefgZrrqpDz9vIik252/zp7et7NXre7nzr4+vNle3529SP6Hj5kZZ1puJO6anPBdS7M gKyFKVqxEpWzQOhE2TYV10YMFLpxdePaQhvF3NW77cO387P3OO93PQUzfAE9F+Hz6t3ty90f H79/vvx459fx6lfZft1+C9/7dqXmy1zUrW3qWhs3DGkd40tnGBeHOKWa4cOPrBSrW1PlLfDG tkpWV5+P4dn66vSSJuBa1cz9Yz8JWdJdJUTe5oq1SAqrcBEfPc7OPboU1dwtBtxcVMJI3krL EH+IyJr5IXBxLeR84cbsYJt2wVairXlb5HzAmmsrVLvmiznL85aVc22kW6jDfjkrZWZg8rCp JduM+l8w2/K6aQ3g1hSO8YVoS1nB5smbiAF+Ula4pkap830wI9iIQz1KqAy+Cmmsa/miqZYT dDWbC5oszEhmwlTMC3+trZVZKUYktrG1gG2dQF+zyrWLBkapFWzgghmSwjOPlZ7SldnBGF6M batrJxWwJYfTBjyS1XyKMhew6X55rISTkhxuOOytVfUBrGQ3m3ZuxzwIctLyomSAfPf+G2qo 96+3f2+/vt/efZ+lgK/f39EzamqjMxH1Xsh1K5gpN/DdKhGJUpi80Tlz0QbXc8eAwSD+K1Ha q/OBuuhVgrSgYz4+3P/28fH569vD9vXj/zQVUwLFTTArPn4YKRFpvrTX2kT7njWyzIHLohXr MJ4NGsRr0rlXyw+oPd/+AsheSUrXimoFS8ZZKOmuzs96JDcgGv7YSxCPd+8GhdzBWicspZdh 31i5EsaC+GE7AtyyxunRIVmCyIImnt/ImsZkgDmjUeVNrD9izPpmqsXE+OXNBSD2a41mFS91 jPdzO0aAMzyGX98cb60JRiczHqSKNSWcXW0ditDVu389PT9t/73fBnvNIv7ajV3JmscrBo0A Eq6+NKIR5JyCYIDka7NpmQOztSAmVyxYlcd6pbECNGx0ShtwCkZ74I+eR8DEQFzKETkNBV3k +GIMdEaIXv7hvMxe3357/fG62z4O8r+3QHCc/DEnjBOg7EJfH2JQfYImQwq6GV/EkoyQXCsG FpaAgcoGRQqr3xz2paykB+kQQ7f7LYo69kqJ2B8kAfeGg1J2C7BIeaKVbc2MFemwHF0Xqxto Ezie67Eej0lSLRhjVmBqc7S0JUMDtuElwXivy1YHG74319hfcOGOItvMaJZzGOg4GXg+Lct/ bUg6pdEO5MGz8QLl7h+3L6+UTC1u0EpLncvkVFUaMRJOBHmmPJrELMCKgR2wniHGxjTBSa6b j+729c/ZDqY0u336Onvd3e5eZ7d3d89vT7v7p9+HuTnJl8EF4Vw3lQtbnkiNZ/uAJqeU2RyP CxegBoDUkUSO2SU6g4czNryZ2UPG1XBeVe1aQEfuGwenaA0MjR3lQJGOhJSElGN7mEVZotFS ukp7LlgFjn5k8wYgmGtWoJM7DAPz8wTeRyfXjNhMa9IqIm4ZThosVeqrk7RdpXmGezPZMbIB 9JrAEagBvAcA/nl1FrlNctnFJ/E2L/cc15y039hZAWpPFu7q9JcYjsID3n+M3zPPa/AG4q7g foBDnIcjRnmOGSoQIGgqjBrAd2yLsrGREudzo5s6Otze5/VyGYdyYIZ4sjoP8FaOlt1y2XVN rDwgwtQjh49J05IYXoB+ATN3LXMf2Az75eIG0yPVMrfjJbcFCNpNvMYOPjjZgymuwaqmR2zA hVa5WMkJce0ooJPxKR7NEsLlg9l4uxJBF4Ivaw3RNCorF4LpQb2BJwImBTQGMUqQFPQIfc9x O1D/BQYFoBs4aF+KkyaN1nB/YcnetTXRVvlvpqC3YIQix9TkI6cTACNfEyCpiwmA2LP0eD36 jrwyzvcxEBrdUYwICqeCCeo8DjPCaZL5aZTUQGvoStAEXNQ+uPOqaNSm5rZemrYumcP0RcSa OtrFsVIdjaTAh5QgWybZDZA/Bcq27awyKVRhywiK3mkFsN2oaKU9pA2GfvB99/DM6rIBzQdT HmnIMWkG0ZIXCSdXEWNA4VYuiZYSnTFiGa04sOeiIddUwOSirICodeyyWDmvWFlEwuhNeQzw TogHDOPVxREu2kUSeTIZCR/LVxLm2jW2cae4oz4+KKijVHPZfmmkWUabA8NkzBgZ6yOfpchj RRgEb8iq9W5Sl9qrty/fnl8eb5/utjPx9/YJ3BMGjgpHBwXcqMgHSLrYT7vLCiASVtCulE8O kNu0UqF9bykmdGOXzDJLWoZLlk0gmozajVInahlY74TyHnALEa8sJPfJGIrnRheyTHxvf6i9 Ko0PiVgL8ERHelWH5oLo2G9Jj48Smx2krZQMcpgcuZDsINf+a6Nq8NgzQcnjkCUZHFecgM/d wsGGI4A6nqPPODVZUQCfJO5dU6UtRg4EygB6O+Cggi+axLO+IwlcQq8C5jQOMJfjbE6AGuFI BChtukGAtqCCC0oH+2l6xELr5QiJuVD4dnLe6IaIXizwGQOFLi4jvCcwiRswqRgleXXsM92j UYyYg+as8pBX7hjZslqO6HhJzQ/oxhbe4xbXcGgEC5Z+hFNyDTs2oK2fw9iigQYCuGtMBS6v g6MRa5axHkEppbBEx712MN2C80aN5cLzbxDjccIQSfBUWFYAW1SNSeMxswI05LImcLluJvKp suZtiKv77BgxPys4aqcWDmni6E7Bw9g8rBolXnDwvhIncYykPL0xDWxOJY72gpvQlMzQCvaA GoRUV1QiIhzZw9Bz4khVmJoQXXYaYwKKzmeuwUxEEqB03pRwZFF5iBJF6FAAbMDAqdHqMIt/ eK8y6iDFfU53SNeb7kBDtBM7/SUwGrwLvrxmJo4GNERz4Dp0ifrzAwTzl1u9pZ1zvXr/2+3r 9uvsz2B0/3p5/nb/EOL//b4gWZc3JLZizwZP1luKJP/iF9NrqqDJFgL3I3J+HbiP4BDFWtN7 Txbt9tXpaEeS4M2DQl4KDhmjvJSOpqkQP97frukeGffcHTrK/nSNreH7BHXqi/YEkpLgDonH 0yTWaoTow4xxr3t8mgQeCa7PP5RgTppIqrM0vi6znBUxNgRDmZ2TwCQfO0ROTsyNdKOgiqvc X295BWZ6satvX3b3eGE7cz/+2r7GogaETvooBRxSVnEyelM213YgjXzMQibgkMbVM3v3xxav SGKvUeoQQlZaJ+zt4TkcOpw7lQXtSHgRJTr7HHoARl5oAOMwRFc9uuvy6t3dt//sY8yapelQ ZqvTKPiq/L0YyFcNLg0K70HSZH8fxZxGw29UlJL2xy00Bnbr6yo2EOEGdAKJI03h9r6WvwrI PZnP4g4k05hxY3NNNz2AD9mPIGAvz3fb19fnl9kOBMznN79tb3dvL6mw3aASzdMrlt5wjq8M C8HA/RAhKRFvsEdiSrqnwAsuSl0goar9SRi3z0BjKzr1NAfFXUi7IJHYVqwdaHq85j0WiCJl KFooa0u76kjC1NAPkQQa5L9oVSavHpNj42GTVwfdvas00sbtwkkC6QQGGry99F6goNyNxQbc NYhSwS+YNyLOuQNT2UoaAjL2R/fwabkM0u2YS3ZJUHHYEgLHfipDOLRSXexZ0IwufZPQkCTY T/JIXn1MOsqZVtpnfEO8P5iOi8+X5Ijq0xGEs3TUjDil1jTucqpD8EucbJSU/4A+jqelvMde 0NjlxJSWv1BGZvk5YR03jdV0SlT5IFSkofqAvZYV3urxidE79Hk+0XfJJvqdC52L+fr0CLYt J7aHb4xcTzJ5JRk/b+mraY/8ZaJXiKEnWqEFmtAKnWOY6luvBDC72VXJhHuDy5ikPJ3GdQVa 4HSgD512jQamBj81pJ9to1I0iHsK6GK0y4sxWK9SiJKVVI3y9x0FRNrl5upTjPdagbtS2STU 6m7FMNwRpaBz6tAjGPOwrCgM6MB+N5Oyth4DCp0gh1PCGnOI8JGSEo6RfTWKJ/BFLdw+GxTD hIIQzwnw6SNO5nFQbq+lTkp/pFaqaReirOPeKl+4FEVFwVpYlSjcAFS0kuovCDEyPUqw0iVo WWY2ZL7N08Sp4dDIa+ZUCHyUj6mQsUBrAmiE0ZijxvR+ZvRSVF5tY2R74GQo0hb7IQXEdRsI XeNaxvTLaTgkGQPL2zP883L4CFPBkQu5Dvdnw8mVHOQTDiLNvSjt4p0HfU3abr8Aa0YnqG5k Em9VGi+uwWhNXmoD7oLMBwTc5cU85oCtS/ArzpO0fQ89o6+pe/QpbW3notVFYYW7OvnOT8J/ ozmka6zZOKtTLzbAqzw3rQuZzhHeZ9Km0QUcLRilFRUjCvS8ezmN9vqlr8KBGDFWJrJEOSp7 BwwLLhpxtV/d0bb9pBSrGpbEwMOMAo66CAmN095ar/tDu7j0aN8demjxcQrZRKFGwW0C7jqN Owwsl5Yzk8fN04x050uB/i2074QKGbzc1M4P5NXWRTJI2JGeDM+KS6fasTbDewqdVOZ0oHAD wScuBQZk1KWcG5aCjohfHw/hBszjUoMM1BypfYKXCr5mk+iMpaVsfR/r+oxXKJ3JzdXFyf/u LfdEpi6qpjjEt6y8Zhsq4CKpVbjoilNpglXej4jDSQ0KLdwRDNnJiVq8m8mygZtaa0rgb7Im sso3VvVlq4Na7co/gVM17fj3rfpIpQP3STZfa9rfaUxlBWBDhDFoUP1dQFBveOed5EPwUsFj 8GpiSc8mhG6rPosc6z88Np2BCgHlJD46tKBJa3cQJnt/DYJljRWmxjT1xEkI5gx8vxXmvq6v Li8ic+YMnXz2rAlZ3MnwGHhOJXEGhxM8xXjSopCUoghJ+Wi5N+3pyUmidG7as08ntBW8ac9P JlHQzwllHm+uADN2mRYGa7vIGtG1SOSRG2YX/naEsoqgUSQ6PSCKBg3jaWoXjUCfyKX2aJ8v 91neKbgvG9ob3LORwUW++wp3P4JNdZyfkb8R3Lfcc0O7umy8YxulK0HFYzStYvRJnN/DkH6E G98Nr3Krya3pE6HZSCPEWV1ZbNoyd0cu8GM70lmLbkL7zNfzf7cvs8fbp9vft4/bp53PfTFe y9nzX5hxTfJf3S3BhLO1fw1AbXmSVqjVZNYHUOGucE98/SU4idHNbWcYqAXz+OoRv3pd4sXJ HqS2w5WKr+EP1y/YpI7fdnhId9ceJuJfn9jo/cygE3h/ozkXE1rD9w8OcmEnfV9PY8Sq1StQ tzIX8fuJtCfBw3AFZc88BRsvJWMOvLXNGNo4F1t9D1zB2Hrw+j2sYNXhijWpFTzOx7ZGwCYm N+w9G0IcK5Ma7hR5MJqsFaUlPS49qYdcD8Ox+dyAVNCXlJ7WLYRR8eVrWEtjnQbZtXDoivF7 hTHF9PaHqrEgkfs9niY/OCqjZXGJpSFTb9fgQI1C7jBRcFiYrA7gPQOl7oLPdDCb0SnK0FbQ qiHmjBJuoY+QgXfRYLX4Atzra3DFWl2Vm2ly+Ita+HCUWS3Gd/t7eHfvn/aICDpyxQsRDYH8 XE4k7mxqvfvC6Vnxsv3P2/bp7sfs9e52fFfanw+ypfz6sB1uoJA0PSk9pJ3rVVuCe5wW2iRo JSq67NerQDSLdmjAdVOXE9sZPJdxkbmfc/b22tuN2b9AMGfb3d2Hf0eVVzzaDBTcuUbvLLEN HqpU+KR3wpPk0oiJqvBAwCoyNQO4bswIEp4xHEyEV9nZSSlCvRrdmUAbkMUVNv0Rwg6QYNSp YBOmweNsTUVCiELPN500jDoRmCFWWXkAmHjI4TkwqWUQa8JLud6XwDLaCd5a12Txfc3CJ6cm iJk7YLnUq8lZ1IZS/B7DrMzT5Y6qb6JdobfKe2TJVewhtq1W4PBRCicilZlKGBChvGNFek/x UHhwjg9hF/41VfDggPqP59fd7O75affy/PAA/tzXl/u/w+V1Il1tfu1v66gruvA8Ni3dAuDw IQ6+2lWZ4Z6o0QsPj8Np4h/kckNraVwDPrcZvTRIqfz9KRUUcXTSo0SP/16YztpFGwA+/Zro oBLu06eT03jic6FJP0rlbZWlgorpH3LSBjiYS9qp9yHhxhbZgeIU37d3b7vb3x62/kn7zBey 7l5nH2fi8e3htvfE+9BDVoVyWEYUhSMBZrmR9cGDN3x/Mqb0wMcRUEmbxnEaDTIZxYWeQ52A 1EnWoFbcY9I0KlWZAZvQy3G13f33+eVPMI9U6FEzvhSU4DaVjIqi8avNJUvkEQaBCJX2IsAF ooUP4Pj2FYNvxUjlj93WroZ4hYF3XmxGQ/rWEFh6gYSQQU0kZoB0X20Xtw/AI3p5oKFKXwbx d5TCsi6u7wEHNE2cBQgccFZ1tYD05EM5IzAij5WDb/b55Ow0UacDtJ2vDJ0Bi2jUFE0ueEWK QllGsQ58nCVpqZq+2WSOlXR99vrsEzUIq7Ph2NQLHUS4H0UIgdP/dEHB2qrs/vAPI0AuwAkv SUqLjwbj32ZgvOv3MRXsg7c/A584XV6eV1gzazU+kyYWCPGhYr6cKh5qgPZ/0mY6oqvoC7aI QuGLyX8imj4Aq8AkSmUDZ0pZLYMqiJah6pKsDI9vmkz8HswU/vVh7EmsY7z1yfvusVL6FjUA vZYw8cuJCBFUR+S4INDgwze7adP3HdmXMiUrSn3dPadPNehst31NX2QumDIs93Po6unu/tzu Zub26/0zVnDunu+eHyL7wkD0EwsK37A6cA9sCQd+ShsZ8sbeaCugMz8wW3+AQ/XUzfPr9u/7 uy3lrKilnCg6ukRDQElt/UVg0D4cTct58rH/xY0oqclbZ9aCLyhnNmMbcPparPUu8nVkKQf4 goDXzBzARF0PsA1TwwdnVcxo+AQH4prOCAIu43SuGXHzpFngJqtmeWByfshkbLTiE8UiiLTl CBvhcrEaT5yzkmNRsvMO4WSvEFZSR9AvwQR+RKBfWXXTSvjrPFK6+AZ8TMgpXnrg8UK3iIzT vrmn4L/8QuXJEScLif8v8vHoqp3mn/2VYdY7XUMH9H43idg/txuNJJQ9Ov1asOWYIEIvVwzF GUOjZNi6XHfApDdn4d/TqYXpwtfVPw4i2FgwRPgG69vt3fZABHHunoLsTtgcsWfjOcwPGiXo bkXT/XqOADpd8GcsTQ7QpLuQyw/XUbRekianykKzJD2c4WMwkdPhf4avwcku/JGJLIHDu/XC JRWNmesTwb2Szx7etrvn590fh3p2aBPqgx4jCKiY5Nu4FL/gMnMJ4yKgb/2DQmA3BwgbbFLM AoA3zJAvz0Mjrs5OzteJaxIQBb3ZAbtacDkaSZkVdWUCGOYW51Gxy7XEH8iJs9c9BGtpIyh8 tekPfHkQ5p1HIBuXmHVEMioO48Ucvb3TYRLBczz1xcJYS5EEaR01CqgoNf580zUz+ANIpKLt qbkwbv9osNVVnMPaExkBH6Is8Q1Ou0hfCyZE/jersIxUmom5hcv8+uicBhk+7OH/GXuy5cZx JH9FMQ8b3RFT2xJ1WNqIfqB4SGjzKoKS6HphuG31lmN8he2arvn7RQI8MsGEvA8+mJm4r0Re MBZ+IDCIdiG7rvuWqcU4Dm/Wo09k2BKxNX09gqh8bopKkRdOXBCkbmR1LTikZWHccvZorDuI dpIpgzGpAoI9hKyIexGHbfZkA2JJjntuuWHS3hDjYpkt1e//eHp4fv94Oz823z/+MSJUd+E9 k55ucT2YmQ84J9mZGbgYDprRSAZuU6lrOnT6XquRtfs80oGfhILyMp/4WrD6V4NofdjA1MG6 vG3Y+BC+iPGxJOJRGASAqfSGCcNAsjFnMZo76kPdhnYCLpyYQl3TyAHfghp7FyYE+2Cs6cjO t2+T+OH8CC7XT08/nh/utNxq8otK8Wt7CJHTH3IqsuV8zl3gFE6KlFYV1vNMM00kjzjkuhEw sMfTLAAy6iUDFV5AobJqO2cEa2lpp9UFoFxtmcenMltamRkgLTk5VYcsi4hRXAgRjMDkyCGG UhMBrrt4C7nRZssDQnf86DIwxG17uGvBk3wsfTsYb3djbsvUQRVTpQVdpx2sScHmlVeYVX4W +skFS1tdbCzKVOsCdfAZpvj4pN34sDKzTyOy1hMRya5rtWX0FChGR5+PcfG1rYtZdBP7SQKO lehA97WNwrGXnhIlYwL3dox1CLk0x6m4AkeHtwxpSZ2L5I1Ebi9szn28qeLAcbQMFWh7rMBl akcjEl/zrSeyDZNFitZQC0xTLBHpUuM4YKCM0BEhQwgDFJNxiLIg6qOS9IrHYYfpdsRcraPA bLvduqiwM2cVGucrggcVtLapBsdAB8roHrXxpTbJ/DJzZqDDDGh7poi6io4IwWvX1nYjYuQa aVcrj1uolb9fXhnEaLM+vKuFnpowkDpKRvV2+/xuFA2T5PY/5J4AWW2TazVZRiXo5vMnb4dt Sk66EldkY8a3A/hqSuR4KCi+jMM2+TDtZRzy0kaZAq2zhnnO8qOA0uacT5S89xUF/wFfWm5n Ju6Yn/5W5ulv8ePt+/fJ3feH1/HFSw9nLOgg/hGFUWAtM4CrldiHDSSVUTloAWmuzRpdzYCF tfWz60aHj2pmNHML613ELuwaWPi1s5vtSjg8m8aUc8+1GlTjhdUYDfO4bhIOB68Ovb5UClyR 4cbwZGP8VJ3L4RiujjV/XLNDJRIKLbEkUAPy1J5x/lZG9PTUsyy9fX0FTVk7tUBfaOba7R04 slpTLU8L1YLOOFjSWoDtY+oXtCYtsDVTZBP01ptramSJSZIo+51FwBCbeGaetcJagjx2Lctt 0OzqmlbXKH/BDi1OFPtOkWqYrlZ1mae0GSLYj4GR3HpmFHD/Xa+nizGtDLZeY8qzppxiyT7O j84plywW0x2nktYdEFj7wq4ATyCwfKfV11Y4RwihUVpjp64ao6mVQCS8Lhs9heT58a8vYDNw +/B8vp8oIqegSOeaBsvlzCpJwyDOVSxquxNapFt9o/swsewprMlwCat+LqH14eNBs+zFEz68 /+tL/vwlgAXjlo9DJmpG7bjriR5liHsTBQEdlw6qTh4Gw9BucVBZksMIow6zNsCktUvoJGEE AY2ccmCbLmRv/R0RzDq2lFwvXzWXXMx4T0miDvZQxVTm1gI1tRLyOteOrXzjerQ5DC+Ge7iQ KNSxM6aXSLfb6lSKKmIqD9NhwdYv8GPucjbg5XI5r5l2wy9y0e0xnLC/R+6FFMvpwlGkYlDa 2Ua5HQM20cJuGt3Kyzn0vrZPHDKvClcRXg1dvrMWqF5eSaFGYfJf5q83KYJ08nR+enn7D6sJ hL1LJ3AcB2AESgUrZm9Yz37+BIx76zEp9TV5oe08FEPv4qIOW0GngwI0p0TH2pH7PAmJW1JH sI22rYbWm9LCAQtBIHj/kI5ilxyirbC7WOds890tPo8xtboXHDJROSKoK2wb4GtomoJ1a4SB UeM5BSc3tjxuiC2E+k5DfM2Da4qVgbaXszIhd7Q87mwVCAyspsfvJyA7fhMEiwqAOwCaKy1I kfMSiBa9k1wI2w7r1+v11WaFFJQtYuatF6PiISBZU6A+L7KCfPSySi3e7PU5BdLTD2on6asU fN2zAuxcuXpnBfWTaIPyjABNdkgS+EDKnhYTh2MYmBhKCYtPFHOvJhzBN9dRraP+FF+bQKj5 xevQ2uxDP9ispuNKHqygFR08yE/tceksGMgSK9COYRHKrWKHHt7BIu9+8uf57vbH+3kCmhwI 0qGYbW03ZpI8nu8+zvdIrdZ13pZohDuwrLnbRocFxm3UQnAyMp7jw3soGKcl1XoDGpUG6NDn mM0gLMFc4boKwiP2+cfgVvQCDvWDPoYQnFxiSYhKCau0ifBrLGDzqdhZM6VGld1zp3nfEkln VN/Nx3RsiJ4+vN+NBULqKiXVHg9PYcyT49RDc9gPl96ybsIir1ggldGGhzS90RsXjmizTRuf dWQt9n5W4euD3IGhc7AYcqxEnFrKQw26qmt0yxWB3Mw9uaBmq1EWJLmEUELgwugQ6GkGZNmk 8a5ALcTQIbaUateVRaHDxbRBT2WJumJfNCLBTkJFKDfrqefj8HNCJt5mOkU2HAbiYQPednAq hVkukWVEh9juZ1dr4kSHMax5RkegK7WZErXxPg1W8yUnXwjlbLVGopBjK31u/ayHfS8tpuul /U1nSqEd+A9I3wDacHkScB2Lpb9ZrIk+Q7r2ycK3oukNC9KDY2W0BKKoAIOs9x+vry9vH/jQ MBi1Qj2Of2yxvYutnSz169X6ijONbAk286BGh2GwvZpNraltYLZWawCqdSQPqZFrdedfdf55 +z4RoFr88aSj+75/v31Tu/MHiC6hjZNHdZOFXfvu4RX+xW2uQCxzYYbAltCOnLFUe/w4v91O 4mLnT/56eHv6WxU1uX/5+/nx5fZ+Yh7QQQZzYCHrg0SkwOacxsUXOyD1oCYl8rwBXtWs37yZ gsdUSwdMmLpnkDEo7k0Lv839tdPoyEDEDPioTroxdMhoD24ELmRw+3bPFeOkf3nto6rJj9uP 8yQdvEx/CXKZ/moroqB+fXbdpAr2xEYkqBPt6csvBYVs36vxHZ4WQBJF3FsyJkRoiKap+TDc 1+P5VnEA7+fzJHy50xNQC8t/e7g/w89/f/z80FK47+fH198env96mbw8T8CvT19qcBzBMGpq dag2rRkHAhvLOUmB6iAlPhkQpMlyf++DKiqcJEaoANmF9ndjaIbZ10MLTn+Jsg8Ytk+D4U65 zSHqaVmq9cQd1IpOFcAPHKJx+sjoHoJIxOrkdIj0ta9sy6TZ+yGMBYhIFaDbFH/788f//vXw 0x6dUXypnsEdbuQ2r5mGqwXDmxq4OqH3Wljh6BaLhR8TaGVYHP+OXH5Qc97RJs9kHtDZ07ql gfNYXhKdaZcoj+Nt7uN3DTrMSBrQJ1F79cqbjRHlN23myE1VaFRhmWW1WD8KVuoCcaFT/ETM lvV8XCBIexd1PS7Rr4SoC8fQMfRVKeIkqjk+FXgijw+pgEnm/w8S7hwlBKtxzfZFNV+tuIr9 oYMvcTan/e0jmHnceBRCMH0gqvXsyuNKUhhvxklGCQHPsMv11WJ2qeFFGHhTNf4QhJgrvMdn 0elSW48nHK6xBwuRWnFiBpTq8ovNkkmwmUYrZlSqMlUc7Rh+FP7aC2qssuiTBOtVMNXMvF7X +cf385trZRsjm5eP8/8o9kOd0y9/TRS5OpNuH99fJuBi/KBYlPfX893D7WMXnvnPF9WM19u3 26fzhyVZ6yqx0EYGvFUrXm2Li+sxrALPu1qzt7pqtVxNeVvdjuZruFpezP+Qqr668lwbSa/U CKTo1BijTRGQcOoiVbIv4NirSuzREWDHWZ3GFDDw6ABrPUx4pbMu6CsXp4LSuM4q3Yy2/iYk 7S+Krf3XPycft6/nf06C8ItitH8db/cSHc/BvjQwbALZwnIpK26oJBu1vctoN85IBvtRz6j/ wbDH8WCQJkny3Y53KNNosC9XV4CbLCDjWnWM/rs1piDK7UaRFhQHBuEqSejfJu0TzdOX3MzQ 8ERs1R9ybRuSsNGBOzQ8mEhjBRtUWfSVsHvqpJ/0dGUa7u25um/K0A9GPaHg6qouuf2yw0dp YHWCAvrJwR/VKpehjmIhXDE0KpIGZEGZmRWh5TeLKAgHiSS7CtWKK4dKAPBbkYdcXhpZ6D42 +13vF/0++fvh47uif/6iuKnJs+Lg/30eXBPQrNKF7rEqtgcxXKAGB9HRt0Bf81J8tbJQ3RbM FHNj56zjybVF0nZKkXi8/YLGxjGLY91tK7/cRa2R+iB6CtJGGDsmAoMIJ1QJCNBCL0Uma4UD szgPWTLmeQGWcW2xWPgDk8iGym0xgsUH+oKF+YYFP4b5cgTTZrzqqJ95SIDZ4lx3iBbNbFHm GhFF0WQ23ywmv8TqwD2pn1/HR00sygi8BFBLWkiTW2PcI1T7+Vi4PUWWS9Y6DOyfIWBnay+I +sEYCYNIEKmvhCAEo/d+tHSTk+98PShG4Fs0MmOOOe0IIKrIT21igOm77/BoJm9nTGjL/JCF Zb4VHHNrkeqIYMi6jGAh4uExgml5KFw0YOW59RO4shGrfPBORv3oBzIKSB5w9OU4QMsAG+va FI66eGpX0Vy/IplVpfqHhLattiOT7+qQNUc9gvqxXBof6hhVnJSjlcBnEWEAsiRlrw1+GViU BtKoWwTnAdZhp9hUpAWW/mkEC6iNXQfN0830509+zyMkjkALXYlC7Wyf5KJuQ/Qq17qtiRgJ FhnFtDa3rypunWgU8CTaWxa3b8DcZNya0fi9JG54CmLGbAAeNRthDYwBOnZngyyNYx6GjXMw cwmeHdbOmiBp4ixoPt4e/vzxcb6fSHWm3n2f+G/qzvJxvoNHE7j+aoMENOlxvY5Wdc17Uoyo 2hfp2ff4tMMvUTlTfTNkdlQNyctmHmD1S5Sgh27mwXK2RML+vDTP7A2n3k2xz9nVgQrwQ7+o IhxrzQC0lVxMTgKcahdhsXhUzeazmqdMqii3Iq9FipXg1qARRlf02QiclysUR0+AnY7Uh+IM /cAS4XdgoiEAMnWluQY7mk+KgLHDUZj8KiGCBvXNB6oHBK9wTGa42kntav5B8Zd8XBqzJYUR H7wW5WGOLjyntgukzVMfJt7PQR3LOg4yIQQc9OYlPAIEKcjdcLCWrEZsVpBhiVwldnmGpjfQ YmZTBzKkdhGKpGInnWol9AaRlGTunmtTBf5RHDg1KKbZR4mkzp8tqKlYz+IOSayvBmhzAAbp YsJjzLYxEGVJPB/levNzan8zD52SPGSA9h1Yl1Rl0cDDspymkQwryjGk4VQ1e3JIBG/pgdPZ MokxCQTbx++IbiPPOkkMpNmfXKYTOLdvn6/1qPbxE3MevVQc650zokSXw/6TEqxnDqIZ9qyP qARaf0YWGt4cxK6tYoc0turDdAbRmey2R/7mJeod550KYMIMaMC4lzH2iAI8iQWuNXxhbJzO pteODU+sPV649kfKH0upXx4j62myY+qKapUCC+o3WzbM0DV+Og++eq3vcMkFKOxwUrBymusb j5LfeM7wsbgRqgV+lqOZnib1Qi1OxNIDgF6GNcj20E3q5eiS1AMb9qUfhZancd4tbDydDI4P 0YAbJQLif3st1+vlTKUmsG/r9aKmluRx5CcZz1pkvmIV8GMbHWAgluv52pvyqSHuS5ZTdXYW 6/g2R86IH6VdzzdTOmc9Phy1QlzT9hySqiQyplO4nv6cf7aRZEeh+NrLtcqvSeDEfWPW7cB0 5qO92UQnUzNhJxy+jCj/r0m+E7y9IaZSd22wXrtcV4jLWEX4GbcK3WrXs/kmICa6AKlyziGr XM9WG3aES1iavmRPvhJHSi5X0wV1zkWEEKqJExUiGumn8oCf5JR6h4zoq/c4QUTjprI0wvUe EiFyCKvjT8dJpqxtKKaotFYONatKgVGGdj1ZMM7mOzwBplW9ckyExovi63q6QivcgJMimK3r ETiNJLZkMsCOc7fhMg/ADmYErsQIdMhqMW6U5WGOuubwybVK3ZPzQvGsqPNaiCpRd2HzlcaP RYmraH+oPtlQK7TWK4i9qXZhP8HSUSLzQSmPAke8E35T7tXiR9frDtQ5uw4cjwBhd5IHghUf oDJO4hu535rv5rQkDE4PnVPf+BYOmv5xsNwxjcgMFa4qQlvhdAfpZBjyMhYdnW7reGCg2N+Y d0GNuaYQEwW5EBHMV/thVqmOAzL+Wriezmsb3SFT7VmGZXeaw2mBw1JTVxcdxMtRyFc4F53Y BOK4sOWr654f6roTzldUkYS3xRz5wTVedaIIpCNb2HvaTDvWPUjNgWS6FzP17Y3VkZVKeAXi Fju39VUPHBjXoEgOrjq1JxLNyLwL4Cd0ENRNdDatiQBQ3dVACjKdzQJH/oYDohmFheJPFmta pgaurqxx149TaYcgTBvrR8UpZQh2yqLa+lhmpqGtbxQhVP2RHmo7uYFeSKD3hjLa2QlBmZIJ S7xSJOxNq8DR5dRHs5Whfi8E+zkU4FYA7yQ5Qi0U3ZvfTnRaFNwFW6MUNyZ0nIn/kDSO5w8h iW9LQAkWkLZwdTiU+W6Qyb633gRDxi/vD/dnHXusU6RDmvP5/nyvDfUA00VM9O9vXz/Ob2M9 Dhjraplkq1ghVrzqTh9QyLV/Iqc6wIpo58sD0ey2AbHWsyW3NQ5Yj+akTqIrcpYDUP0QIUJX Y3BKmV3VdrEDatPMrtYcK9yRBWHQhVQcZaFwTRRxzCmmyIKUS7w/qG4SHcUneaRb7BzXj0e6 WU1nY7gsN1f4aETwNT0ce4zaQ6+WDnE0Jtp8RrRLVt70UodmsLOtmdrBdrodg9NAXq3nDH2p TmpjSzDGQZ/Jw1bq64h+QucCid0h4BeaLles173GZ94VttnXId+i5FpkFOaXqdoODkQCC/Co UGynt17zkQL0Cgq82ca1KqDy3/xDOV5Nuln12pvPpg2v9+qorv0kFT6X/qs62k8nx2WhIxJZ tZzVnIhS7whh0IUEJr0uiv1oX5AiKkvf1uIA5pisWJ6pb+h+4xH+j7Co8DVoJVJ6OwzTNQk1 5isGuncp5jLAzjtAbIlGAKQDsehHAAkjDigIDNfqPU3MHADoKHKsAH+/JG5BGnDp+RON18Xz RiiAtixM2zTwnnKw9yHOkqMqm+tmfyIdpSBj72sD31ZBDm+jm5BzrgzH6Vy+2gbr7zk5osEN gdEIWD9yCMYQ8FcC62g1HpLGsov95wwZrunUwPHv+mh0VW82dvGn/DQur+1nrdWOamfvqM7I 8aOO7RjgI7YHcXHhujErnbFny2QzY92EVNLVdULKUd+NDk9pA63ooC304iQFgktB6loSCGuo n+Zg9erLpYesnU9CHTYz67anQY2QJcgY2bueoWjrQroapMdP9JsK3FqYmpN2urFEF8P5l6kM wVCRUdJP5+gpyOYrVqpN968Ui0vNJ3LOEj0I1eBqFSyntSN4LM6d0wJik/TFHDh5n6AbKbcU oK4CkdSEDXjOG/xwbyMUbFcMJJIPgarwbm3k/BNt5LyRRKvetaopbOgYsL9pdmNQNgYlxRi2 t6phRcFVEL3Y7c5yqQYUrvWbeRqBLnXPQHGpk1qqUR1beFfTEcI6TxHCmjddNaw+Hqj15IFY MXZ4WEqVul5mJmWMyDqiMkh1IKMnDJFwUSWQ2ECQ9MHA9Fzii+8oXGGdewJwM3dUbby1ATTc kkmCV7DW3PL7C6LS6sVP9gIdnVYK8uIQ+APa30PcQRfCPDI0QhcJuvl1MCpZhUfrHJb8xXJx yRm+KIVMl7yVKW5lKzf7nC4Kha9Yz08JS99pRU/IjFTpkzEoseW++mg22JoGAAzfAGDnrASk a0Likh02jJik4lk9TPLtJvT54RtCAp+kuHRlNldDfSNoZSHRs35W6PQA0Wt/Gb+y8+vk42UC fo0f3zsqRv7quhehJ0taGQkvJD78ISp5aFjXdCFDqlpX341YOFz8ABm4vDs1NiyPzU7sfMm+ ErO/geIGaVxbOv5sQkkD22hgMsvFOFLEE+Am32/f7o2L8Ch2lk67jwMa2KuDatGZXbyCE4GA gfrHNC5F9Q2veIORRRSFMRvlwRAI9X8WWXGjNOa0Wm14q2ODV3PqD7Yb24wLvPNnRxKIQ326 FfUKt4sykwLBynJ42Uw8v/74cHrziKzAr1rpT3P+PlFYHMPbtzqCu4UBY1tiUGvA5s34axIU z2BSvypF3WL6QJqP8GYueeCAJsoVb2a9l0ExTSH9Azd6FpkMyijKmvr32dRbXKa5+f1qtbbL +yO/USTOcqIj0xnRERiUJzwio5Bp/0fZlXS5jSPpv+LjzKGmuS+HOoAgJbGSFFkkJTHzopeV zq7ya2/Pdr8u//tBACCJJcCcOXhRfIGVWAJALFqCh+pxsR5di19od1L2cZxhDlAMFuUpekOm hwLP9vfJ91Lc2lLhCfwEO/2tHM3DQ1Ei5Zq+0DSADyLUDdnKNlGSRH6C5MyQLPIzBBEjDQGa NgvVk6AGhCFaT7amp2Gc79WxpSOetB/8ALvuWjnO1W1Sr49WoOurM4jMI4ItT/0IMnU3ciOP GHQ54x8IfNJFWPfemsgLPbRhMwym/RHDdhnfR4+YK4sWLUOZicqKDj/ZBNeUW1finTS9Y8df WYpHvJ4bByiUsH97XD1w4xsfz6SHSyFsPV+56GMvHYBhRdWHqug6h8/flQ3k8Ad+J/gGY8Uk lami2I2tUu8KBHDVdkIpqbvQ04Ma/HTDDh0FsVFzo7iC1xb9UmM11KSxPxbp+6bihTmrygZD nKeRnZY+kh57GBAodIHpUF5H4M+bye9jq4WhFSgbk4bLM9mcqZ5dgeUBhyGFavTJDqS+7/VE dX7L6ddxnmdC7PJgqdwpbh2ZZlOdfPjtzLrPwd2ncvG9UNghmbCmbdXegLDEqGWNUGlXDASh Hw/BA0YedKeWGnBHg2tuLJeabS+t6pVqxfiRk9AJzXusy+pWn0v0anzlmtqSYjkfuoFWaL4C cnS/yRWEAfIN2CF3qFWvtSsCdvlNo4b22trDJM2qGwq8sQCCfyZ06GxsEJnK8cS9dcmtLtmP vdY9narz6YKNgLLI8S9N2oqier5buZehAIeZhxnNgYyx52Mb8coB0t2lxUfazOaqc7rwQPTK Aip+i4c8WlF1lqtQ3cPbEgYdJ6rbjW7QiZzZURI7EShMDwX7gWQg1mY2fmjX4ncVskGwTAtB 2C1UG5FuBZWUqR+5JfGiJb7qmkyKyOHs3YvLNOkHrOXIMKdpkoes5bBwuetD5iwP4nt3ZsIF kk3LJEVUXUDi/SX0Ys9OyHYel+MwwXDsA2xvWkDQRqmqXo2sqEBT3UxSAjbxWz2CZvC9mM4j Uq2pISPHdqrGNqn7AItfhT1Ir8cNNvvPks8u6GGefst3yui7WzW0BHWEKzgeK6IHVxFk2vpe bhLXSD/yc9v1Garpcu9vgxgv7jnZj0kc+NnGivTh3AfefO/RezGZjZCAtVxQhmutbWkrCCq9 OHgRB3DzSE2aln3YnVr39BB7SRje+xYz6luZsjiNrNxv7d5oHLqJDI/gD7ErbZaS5F4crBPM xmI3loQ4dmOHLn++o1+nnJtwZy2peczGiz2sSKgFhtTIppwosyorNs3Bmzr7X0HwDU7ebXRU LlV3tgsTV1Bs3u7hGiRsfJ3sMwPGmcQYJ8KXLnzK1Wxbr4YY290rEHHJl0NBKb33abe5gBzQ jVJCgc0e2gbAp+VCr/5H9870OVJp8XwR18MGB/95rzMvCkwi+1s3xhNkOmUBTX3NCybQezJo R2BJpbU4YGrUpi6AauQsrLA3ZTpOlCajjB3XuBOljEHr9GYjshmomYeO94VWz4vop/U3SEl6 byyU+3mM4wyhN1pQkpVctRffe8ANSFemQ5vpRuziwvuv52/PL6ANaPmPnSZNW/jqikefs2V7 ejSjYfXTKDQl2UHyXnNvKLir1uUZblL13jeidAUcxIne/0wycjhZ2W5ku6eudWhr348j7nmU K9iw8wRqWMja1apaG+z3gyDIIBPfwBuVdSsu61uRoXmkqoMPCWRB7KFEVkA/VDya0hL4BufT vGqrADV9NGipVMNbFTgPPCLe+GuEoQP7IHVbrSzmd+FM1TxV7DyGfxmV8TDi8prWDXiQaC0b OB86HFQpbG39do3absZVDyQTeHJHgixLl2Wff4FMGIWPBa6Ki3illVlBFzZ4XALJoduhK0Tl 05q5/uYY2xIeKT3P+O3ZyuEn9Zg6VEAlExsDRTWUpMFf2CWXXGx/m8jRGWRRZ32LDYzU3uKZ QUGbCYvjm5xsFd+DB4eXGgmzwXtv+rfKYL+qmYfJq4817RpHnAbJ3V6r4uKuN1uW4QH7PGEL FAdUYbDp7SWg7433GeklRTJiAk3f1nCYLTUnLZzKTiM1Fa6ytQPmhrGDkUsXjHMJlz3ifudA UF8EnG/UXv8lSYY6kb7nHGIbZx1rzD6TYzcIF1SqF2Wi+nBY6g6KJf3ptvjbUZq6EmFGwBbf oqriG5thv70BpC2Rsu7HCnRcPmElXlHzThXXfakode11X0VXlyvucmrwZXUI8wRzqQ13xzXV +2jszo+OR+z2xsRIbP0TUa50a5KeZmmY/G1QzyO1nq2Y5IcElNy6sK/w6cVG+ZGeKriigq+J Xd3Qo+w9lVCPFoHfU1sadyq4vFS7SpFs58u1M06XAJ9RW0xA0EKxwjQGOuCqH0tVxikMn3rU jTob0NxnviYaSeF2zYctys1jcUGcFbNjj/3irUbXBJd4vCs6Jg8dNSdpQOXPU6x9muEhACKi GzbvATyxVGogECAKuyZhp/fvjz8+fP34+je4KWVV5BG0sHqyTaQQZ3KWZdNU56N+NSOydb8K LAw9JXkc4XK8zvO3o0nAAQZWRukyeCto8zkSLs8p6/cgH//88u3Dj78+fTea2hy7op7MjgZy T9EVdkWJmv965AQX7Ybf156+Y/Vh9L/A9evL6tEQU9UR2dc+7lx4RRM1GsNCnEOzo8Cfcpy4 MmrLzOf2BFqaOkOdg3FoVF/jBKW1+g68ETsueGHy88cF9EoQvhv48M1jM0tGTkL0/lSAeTKb zcC3Eon03KJbxAoAj+WODzHS1g6VzWf3z+8/Xj+9+wMC18ogjv8Ffn0//nz3+umP1/dgpvYP yfULE6HBI/B/6wOPghHhUdMIBXJZjfXxzDUJdf8TBojZmpssqD8KYKqOgTfp5VZtdQ3MzHZn +EPV9mgMOb6uGboDfFxQgnji4chMDNaZ6Kc5IA4Pagw28eVbzW0X0ISovOrP/f3j9dtndnBh 0D/EJHyW5oLWsZZ3X93Bi+zFuKgL1oBUjvYu4aEauEkykzKRrpsOl6ene2dIbRrbRLqRSZ6Y sMXh+vwoDRhUf9Nru5TBaI5j6Pl6xH3bcqmE0MLo2eliUrg7vJ8WSQYOscchRAKBUeBsrwwW wtbSN1iMPXaTwtCAB3rIas0fH/uh7a3isnCslTV5DWfByR8/QKySbYhABrDNLt+g70d7B2VE 3ZR2dCvSTb1kX7OTZWKHbMiJNjVE8XmwpDmMqylrPPbZxrKFVbMxKYOuVfsTQs0///jyzd7h pp5V/MvLv5DeYE304yy7LwKVqtcqLN3fgQreuZpu3cBNz7moOk6khYC3qoLr8/v3H0Dtlc1n Xtr3/3GVA6fqrU38kpcHdhe3TuxUCm0TPgwkD0rYgrRLYncw1mwR4FULyCZzgkhM3CGHdpEI 49m5rPLMxscRNbvhoBXdglO5ipi3CXoiIOOn569f2T7ES7MWO54OYi0Y0dxFe/jNhXY3y8lt 2WMLoOipG+kLK8kSiR67YDI4B7NbVLRWPyenNI/nmesoWWWyDqToGYSj1zmLY3W14lSxa7hr 9zRbckDPhvkvso/hnWGnn30vgp3lHmWVVVvAagB9TE5TWVhyow8OqZ9ls9WYespSV14j70ij w+gp9P2d1t9GP6FRhopCvNmvf39lc9huuNQYtUeSoMMUcZdKSjSyijLiPStjTg+wdzuh7gmn jXC2kkn6fn3Es6Yz73H2Y8/OeuprGmS+/UjVHsr9zqPDI1sE4brtWhkfXkQfsT6keCR1zlD+ TGol+o2cn+6Tw58253BKeqJb+KMx0m7xBu7OlnNkyc644xy5j19ZCg7xAr7LAK/grspfaOFH 6oOtGO/8Ydgm5nn0qxLFZ3/oy9OVvrIWk+YDQkxXET6sLs1VvbnX3ckg9sj8HUoaBnvzd+zA N07T2KEWQYT68u3tidzSPghHL1vEAdAgcyW4aUfKm383VmOegf/Lfz7I03L7/N0Mb8ISsTE1 QZwtMg0daii6spRjEOWeUaaCZdiMUFn8W4unNncktebjx2cRGUxNJyRi8LuBSfErwwiPbJ8s MlTWy5wA2FGV4Pt8GxIahx8arVASY3uLxqHZJ6tAaH5NBcJi7agcaeLhuaaZE/BxIKu8CK1I 8XuQOrxUwX03N+tvtJdflb5j+92DzydgxdYOKdaQkt4LMrGxoml9LepgruRS8cT0Yy/JPJVy +wruDgRNtQsVpYJH/CyPYjT0rmQxP4RK1+NXagh2CaQxBHaWY6Ea0EoifCE9gpIO6DE31yLY bhViteZ7nHKVOvcBSP0nCD4xWPTDha2tR3I5VnZW7DP5qfB6iCNICxeVq5aourey9FU9CuvU YY5x58giaT32UKT6jReIDycPd4+58CAbocHR9FkapFsHLXTzpWEr9UyO6PBV6uVHcZriqYXm 5H5ytqNmWGo2MiI/RgMfqxy5Z38CAII4xYE0jO0OYECcYVmNbRFGqT0G+HC6NxMN8si34WGK vTC0sxsmNlE1+WvRATSXCWOpYidQ1IpPoOSqzLnFNa36836tNcMrQZQXNCfEKvIsQusgeh8y IG9RT5fjZVDU3ywoRLAyjfzIQVfUgzZ663tqWEIdiF0pEleK3AGEWkBmBcoDVHLcOKZ09pEo yABEbsBRHIMSXP1K4UiR2MoC0EbWCo00TVATsIXjIQOX8liNHnwPoJ20B9L68WndsOzSwexm bLErqK2CheYOc6VPc4/2Uzkmwd5HgfjP2KApwWPk2LZonkK5lC3pexmL45P1Tev4gQn7hV0i nM69+GCn4Mf24HDEkDhM4xEB2Bm9LW36sYn9bGztwhkQeCPa2iOTBtC74A0PsK8prhwIdrOy sJzqU+LrNntrNxUtQRUJFIZej9i5Iqxcl6f17SvEHjLh4AKaj28sW/yaZIF/o7rCp6CysT74 ARb6vKnPFdFfSleIbxXYg57GkSPzgAFsJ/QduUYBGopT4wjQj8mht6oUBQn6LQW0t6qAaJB4 CbomcczH1fo1ngQzNVY58tTuMIhwnoTIUs+BKMBmBIdi/BZB48n3BgzjCP0U+4js9ByiO1lb nQ+BX7TU3LjXnm6TEKOmIdYORo93G8EY9lrA4AwZgm3m4aVlmHinwDGaWYpnhjoOVOAAyyxH eyePgzByABHyGQSA1Fbo56BzAKAo2OvN80TFVUA9TqrB3IrTiQ1xpAEApClSHQawExvSEQDk +uFhq+chi3NsrvZcR8JuM04GSSnAhYymDdipB7ti0JY3PcCsAW3GN/vZhJmPdIxcbiLHchN4 KXr2UmduFEXYzGVnlCRDJsXUjxE7ICLf4kLL3MNEGgACDHhqElQGAoOZg2pPuQDjacJ6gZED 3x5OjEzRDUQqW+yuGGVb+WmY7vJULfUjb28tYBwBk7PtKjMguQUeVut2pFHa7iA5urEJtAh3 l2omTcXJPC8uIZFpwzl2pzfn4BG+kTq0bD/ZFeWpH2Rl5iMjizAJ1vPR082YZgE6iQjrxmxX zK/PJPCQXRHo84w1YqIprsWzMpxaiho1rgxtz05ddkM4PcTawZAI1T5SGbCNVLuWsQoEn/20 v8iDjg0mWULsPK+Tr7lb3ejgqhbrslsWppmPhrVVOHK/xNrOocClzq/w7E00zoAsDYIOqwmd hsbuBIY3aRZPyMIvoET196FAbI6ckCOOQCoUWh5XdtWv1pENmpLuC5LtuPjg+T42GPkOTJQm S4IdxWcBOkztbwFvQ83tme/TUOt6HguH1N2+HzsI3131YEuLKQRj/AdSD2y9Jnq0IoyTO+Tl lvO4jiuSRF4XNU1HHfvsksqqCoKvTcNqCgzge5//tVvB/0db3miDxQ+x0rhDXVy9iL+68fxo Q1rcfkQwgdllOY1Lxi7OMPJmjEcvkJ7WIaksAr9DcAfQXLrDIsUaSPAXpEWz/6dJMQxrVvK5 u5HHTvW1tUJc0WR5z7w9/3j56/2XP53+ocbuMCGWBfLqxK6YNMrFgSRUgU09BqAtsx2FBIRD 4tuRCuks8cBiA9K+xgae6nqAVya74TLSJNYlN5W4Vnw4x1PiZ3t1X3YxLDmcP8N53kvOrdPt NhD6+wUCUN9KTVeGlFfhvQcAJDfS1C2oIct0CjVl8gmnKtWrCnpnwnnkyIzfhWWVntfYQyic u+FvgpuHOLIZWSmHeuppgI6f6jJ0WIu2WVqkrEA32pIRX1Nu5MDWHbxSdRJ6XjUWeuNqiIBr 9lLN2urKZcpSPzjYKbLUkeLUowNFaGs4G3nqGXI/c0Ml2pU16s5jZOKp6Chl0xeqohqNH4L9 0Bxa5yt8VLT4xBO9gn9cJjV4xhgpaBpEnlkCk+ZiZxN5ZB2p1LTLFKZF6uxeEBq1qizSjt4F jJql6cFizTeiMofp6WlnaFc9O5KEyBSWKiJVbQ6Pc51D4CRXI9lieCeBb+JCeWskv/zx/P31 /bb20+dv75Ulv6fYJGvrmW1WN4djb6SgntZvFlQrZWlxASdDi33RPnHluCZlPFueWH9DdJdu HOuC2xIKbZgvnz+8fH83fvj44eXL53fF88u/vn58/vyq7IKqZ0/IYuTKzz9VUgEKqJoHASiK 1jxAt1KkjRr5SM/fxVCXRyMB+LzdyW+BDWrdCLNGhSZsylYH2Xh2OhOK6VqxwsW40bvFty/P 71++fHr3/evry4d/fnh5R9qCbH3Lva1/0rKwupJTRcNpjdRWwzV9iRVg0hym2QD41k4jx6WR PJJ2e7YyVjrBmbf0Fb6ZYv3z359fQJvZDpy2zLRDaYh1nLLo/im0RQtEExiAPoapjxtgLXCA a9f1LVdv6eM4wO/FeXoyBVnqudX8ORMY790PTQXLBiawrTynhpaaWyeAuF8+D3XkyFPyJ3S9 h+SzurC40zKjA5hYoCrx0F6uc6JkthJVhRPIR0q9mk3fSo9tWhLo30vIwGbtGNV3vEJwuDk7 nP0ewAWoH0pdGkdPneokYlsBtElREJjAdmWsqVYZoLKMcKVPyEvsR79fyPCwGgptLWx6qits A0E3HVvPVXp1trybfhzN0bwh/Fpgt26cS/fazDCu60rbTosNAoAQmswCs6xvM1S3bENjNBET cxypVqWZnwY1TZMswai5NVA4PYtwjSDJkOUednu5okGM5Jrl6LXphmZGBaeECToGbTmAmflf 674auPmNowg4v+h5KfpUq6ggHVBp+lcrVR+IUrvXjOQMRQmVWYM4jbM9ZlZ1Hq0xnNflXJ4z 0HiK0Qcyjj5kqqYnJ4nzoU4cK4psAWMdpcmMAW3s+WZVOdG1N3GGh8eMjcnA/GBmdNzt6FjM sffGsj9OLRpykGPcQkOv+lTfSRuG8XyfRio+rpZf04f5zogH7TbUNTUfRouKuqSBXrnvxdq1 N9c19/ArRA6ls9k/gp4lzkoJhty9pEsledecW3TojZ6SevNodXK0BQps7EQL1fJhKzC2+oXY ffxyU2EPwQUhFy3wzOKNzorEzpLcGj9IQ2s4qV+3DWN7Dr7hsYWz0DDOclw1nuOtc1ZYhkJc tBjqp+5M3I5uoTltFjk3DXn7/dOmYfIKILG3s6mvRgmStr6iqjltfg1ddogbhwimeu2aiahn jo0BXHBchBOY8dKqGrcbD1zo8vvcjeuTzQVCa6ariOigqdeMsZVxmGPTXmE5s396vD+EpLib 3JQJdURfNA0MewHUWVS50EBCBxKoeoUG4mPIgZzZeSF29LPTFlFxhskFx9221GOTh56jCAYm QepjKmcbEyzvqY+1mSNoP3GN5tmFxDGKiBUBg2zJTMfiLME/NlcSiDAP/QZP4rkzYALZmxnk 6jnEgFJ0wGxSG14sFzrfKneRQXFMU0hRMCYa+ugHlUIjgpj7tIIgivUKerg8VT665ipM1yzz XF+Ag6gGksJza7FKr083GGjIeQpgSnsKZOiPb8gYtD3x0FkO0Ij39xi3WZqgHb5KfgjGdv/Y T8IA7/JFhNrtMWAKwgRdsIRsFKDjahW4nEWbloU4kyEkGajLsFBh27Eu3LjE9r1bG3Ob5hG2 loij2qXQp9f3H57fvXz59op5ABDpKGnBsZw7YKlgE97y79NVKUhjAPdtYGCqcRhlDQRsk5Gi DL6xHP4PXAN9s9bsxzSAT+rBrsyG3csr5sL+WpcVN9pX0wriNWoCCJwMYXYIenmw8dmpSXnd MRUTPEJ0auszj4x2PqLuQQXrdDmrMhEnFpdDYJxUN3pbtV0/Ysi15a/hyvPjtbCk7Amu0aWn DqRSkISt5ayVpIdAeL9mKvK/jD3bcuM4rr/ip1MzdXarJfm+p/qB1sXWRLcRJVvuF5cncXen Kom7kvTu5u8PQEo2L6B7XrpjAOIFBEGQBIEhB7Do2eXCOBeCap9ZioESKZJ16WYvx6fzt1Gz FW9Hreiski/VtgaspnI0hB0cwUF3Szw2EVAZrMQWb1OeqjG2JYI3d74/86xEyzqWheoxiIYz P1mXc8+b09CDljlMw2QliyyZUT6DFQCDfcrsTc8qzz89PH57fD8+2bw3hbz1FoH9yj9yfa7I iMh8HehCKPIMJEtPdVVU4foD9gum2POY2gdeCNrZTE+ee8F8mXke7ao4kIQxLEjUMj8QxKE/ W9jtXWeLmW+D8y7zfZ8nNqZusmDRda2Ngf9h2dXhTSOSsbfRWk8ofsVFsSOuZ85lqTWVGgy/ XwVh0B+/V2YCZArv3CQiMeO+MPekz8jpr/vj8z9QMH47aqL2+61JHueB9ghehUr1S6NYxpkD BU3TdupCCaHKu7UkYX+GuCRU/kN5JSgX4dPDKM/DTyLVZB9ASndXg2FApDkORhnJ4+tph6/H f8PUiyN/vJz8PmLX8pSWJWkdR81Wl5MeaKbPk7wIu2A88S3GNttLhKYe3ueIuiYzfXbJyzDS UtkfX+4fn56Orx/XoGfvP1/g/39AX1/ezvjHY3D/j9HX1/PL++nl4e13c2HABbjeknl4e6Ol aZi4KZAK7OfD4xnk6P78IKr58XoGgcKaRMyg58f/anyTHc55NdZiOvTs4dNxNg4sEWoj5o8n ltCByab54Pc6vSz2h1WTHPLq4sJYR/zSxCEg0vbx4XRWoXopjM19aqSqqZahpAfvgoU3saHL pepRrUBnQ8tkK5BTR42RZntAcqYL4f6ufHZ60bsUHp9Pr8d+pF1zu9zOZxOrB3mz3HpicyJK Sp6Ob9+VEpRKH59hiP99ej69vI8waN4FLSThkyS6PwMViAHenWpE+ePb/ekJb+zPGG3x9PTj 9KpTcCmno5/oPACfv53vD/eyY1KmTYGVltoHAcToc5V696zimogtgqV3AznvnEgfsL4Tu1ws 5jQybwKvcxSLONUWUXGYgNF34Low8IIFXWYXTj3P0ccunDhxsGrCh1NO1yix88aBDScTvvDG t5inXaIo2CT0PHWLbOGCG7gxjetrdHwZT7SXIHqhMOccuKZlS89ztJSnga++b1dxabP01SCJ Kq5eYNDHZ2Wv+fYOquH4+jD67e34DvPm8f30+1V368tRvlhEfCzd9qkS7kU8t/8dwUIGU/Md g8U7y4rq7k5fcwahD4PoYrwC/J/87zQNtNfEV+OXiPY2Y9+wR/l0408CzwA2Wy9YLq3mLLyF UeLA4cjXxvSKEu3wja9k40x6DpPKhAELQOx9tfsNLLB/g59QB8ZA0csDJkdUDZPOYtTUYNSX DMZ5anREWPIGDIxls9qwiwIQtFqHCmt47FFAc5BAuk0DXBidhyRWWRP2IudkyjbmIFIkk01Z kTIwv+yaGg6lF2CxfR8xWBoe748vn+7Or6fjy6i5DsenUIg8mGPONhQdaF3PYPgqzMdT32hY to6a8dgk7aFTExpo28qLbIv3Pb1vX/S3pYcvA2Nnk68WMxZ4XCtNn4r/8+sqtL2jQgXL7tPH SBqOn6os01sDgKFaDluePjDnYCyMvoLpIRSDpVHGy27/h8GoYlWZfcPLiIkJxLXalIkqsOV/ fNF+zfn89IahKaFhp6fzj9HL6T9a77VdRtTm+R4E2NoZrF+PP76jyyFx1sfWVOgF6d2ybpTl cbtmGLFb2Q5IgDjSWVct/+wryWYQyXdpE27iuqTuPqNa2SrAj0OeVukh4po7HcKjCuz4bgg7 Tpd0uIONkQzXrReK8GQ1oD5UVCLO6C6vN8xq8SDkAOtadNm/OKpumvwiwUE42LMY7sywDJVv RFzsaDuf6nGxB1S4AT1L3ZcMBDzNfP0Z6oApukpYb8sFdVQs2hslnc6k2tef+wkYi+gI+4hk eQQDbn4ioYcwpRMfKCR4cVs11NOgnkg+mIFd8/7zNX726De5TwvP1bA/+x1+vHx9/Pbz9Ygu jtqE6EvCD+l6irLdxkw5OukBvQ/llAQPT50+j4miRKgtGZtZE7V06U+twQLYATbIWZqnBWak 2+xuHyMM39xmXr5m+uBuU2ZWzdmWrWlnBvHFmgygIVD5bm1Kj4TBdArtSbTO2ZS8L0NkG2WW CHHqxL7v11p71YzAMK3rlh/+hElslvSnI3Mx4lZluKFPdyXDRFoXkFNHUypMljnIZfT49uPp +DGqYDf4ZMxyQTjs355tDPzLYKefhofttvO9xBtPCrOLfRkyFfqBz+IFYzQJ6MfqkP0Je6za 551nKRaNjHuTceNnMfkKVvBo8AbXepnCwvP69Xh/Gq1eHx++nYwOo/KpmmI80WMZyNpRoxwq vpjprsByq/4Km+PRXz+/fgV9GZl7/kQ5rB6UsVDN11kGOj7MI4yNosGKskkTLSofAKOIPuME 1KosGzTpbt16YVUJnpFlWR2HygLZI8Ky2kMDmYVIMXPxKku1o9ceV8NSVKVdnOFT6cNqT+a2 Ajq+53TNiCBrRoSr5qSs43RdHOIC9m+Ush9q1C6FkIVxEtd1HB1U3yuxzobtihm1cLAFMPy2 g+c5Q09Z8hYLR8TWqPgNvt2SizrXEE2aiY5iEudBeDXh+j4k0LCulHAkhD7RelrlgfkbBiAp DxjzvCwK7WwRi9iv4jqQWzdtkAf4LfFzZdUCFPCQjNwMqBYFVmtkMdHtChyZNe3jBKiywmSo tWsEuB8Jn2+jwGKbRqmzzDrdOnHpfELfdQMuixfedE7duQtJwSCtWk8lCGxHzB+TtrkuJT0S 81v/2cYUbm3ohh7s8rvDnlmGkTaCzd4P6GDEEutCccqFF+FirTZnlADeamVPwcLQkdcZaVJ6 EURpc49sEZegTVLKUxCwd/u61AZorFmbPUC2y2C9QNAuiNiisozK0pTqbQPLCe2ti8oA1rC4 oM0pMduoXHBijo915c3qHFcWY0ZLKKxuLD/EW/IxtkYTtrzR83tBKeIZqmPoey9rFcLDNjFn IthRzqm2Ahusaya0ESYGWrhZ6nMqxpzcZR7rUNitB11HwcQV2Fp/U6NgnWO6qmGPxTdxrC9l rC0Pd/7S60ioR0INPnFQWerlt+DdXD2pu6wrhyyMKL8UBIcZ47zPtEd04VqGSqiOzpWiD+V7 sxTb/fiKq3aUTX7F9/6jRP96/1GyVMIjkKAS8RVv1l7li+XEP+y0FO9XNGdgdTIKY4ZAVyqN qsVCtyMN5JySaaVNZJBchdezMRmf0KBZOr6vFlPSLe1KUjbahkVpGeYSpPlhe8opIqQ9OlGa sp0G3jyr6IauoplPPtEBi4I3rDH9gGjTahPlymPFrFyX+i8MS9jCUgt6Q5tEV5TLgFFIwqxt gkCNqFa2RWT8PJScW45HOga31TAjUzIMpFZgEcl8hTqoCnMdEOUsLtaoyBH1rKI2uyiudOqa 7XKwjXQgptQTt+FlkuDRkl7KH1q49QEyZERXk+0hjsdgzRShEQxVIuQhIN1xZBCed+ml5bDt qBFllgZ9RbCjLMQOvDMbIVtnfqxR6d5ejjp6tXwoswid6cyaqroMD2QSG8Ru8RUYj/usr8aA 9q9kTdDwkY7ayjj9lkwc+HrVJuTgIxf0IS6rbIzp1knMRMHozFyxXYwIJyP7LOYmjTrAVTvx fJEaV2/r0CQLKpqjNxI9z0CIozg0m0i4tCjYHed2FeghNYRE08CLQ8QrE+jPBFRrTsqZTsYi WYvWNBb5C39GBqHtsZOF9U3GDRdvHf2l8WeeI5idxAdjn36rdcHTkYVRS+TpYmzEXhvApD+Z wPKJDBRmwmY6z2Lu6zEGJWyh3uULjoczY/+K0HXLhZVD2jA9Qdw1dazajT0czAyzOJG32Mxh S1MceEN5WUot+eWLP7MnGmeBCWzSZdANY07iej7aOD2Tj9SZNXWn0QuxLcDktHYWAAIfWtOA h6yKzXYgexIw1h2xR7ClQlGmRcFC0oa70PSDay8CdlyMTfRPcRKvxKvAlRATWdSxcBOGveWX +PNsouLRJ/DDAPTP955NcMt8zyfAvAv2ZguFvyVLmUv9yQ/9IMjsAmfo6UYVuEkdObWRYBVG gR56s/8Kzx9nNrgqIxK4IcBNWcR6prwBs2V1yjodjs3fpbWxXg3QXovr2jp1hD8T0t4lO/d8 5GhPOlgiqizrO8uIWMWr0jV7L+3EFwLyAlv79oJvGEi/w5rD5/06U/C9v1iuZG5eAzPkVNFt OotssNdsTH+pZCyPIrKE1RQlTWoaXC66+TnsXQ7xnjl5PZ3e7o9Pp1FYtVc3uPPz8/lFIT3/ wBuuN+KTf+nzkAujKDswXhOMQQxnqQPBXYgqShMaFZOlpXmHcxvTQpuqT2DJUDlCzcGmNAFz T0k8a6DTyuyWBMr0iHZLZAwI3txA/epTPBZUA03oBKt9E4rnVLOJJ2Iv/Zpw6g+ENm9kpXcZ EAaLmaCzNDB7evrP48vL6VURECslprSgi0l6sdsshGNcuyap1qwXWbN9eHWNfwuO9Teu6DZu 5/FQ5yJpOgpsxFp/7tHRYy5Ed5Pp1BEm9koy88mYpQrBJCBUxd10vJgR8CyczoIx1eaQj6fZ mEyicaGYBNnUt0vtEXoyIh0Z0FUiigx+rVLMHe2dBDO3zTqQkAcqGoGjQ/Mb/em6hRPh/Go8 WdrwmFO2sdDpTT6j4/leJlVRYmJnb2ybYhgdJszBNL4tgkgzX7pOMxUqsP4XzG79gDEjICj4 qR/89xfl19nMslEFHJQKYWb2GDK2gkow8egijYwQCmY+d+VF7on4usmmlpUkMGmdSMOPVExI 0aslq2bO82DmBb9gElBNpupL1AuiYeOgo+FTqqUNqEhm2TSIApMkmJJJMBUKjNphl4qIuU80 o0nYcjEnJL/JtrBnZGmouhQSSHo+XQjGfkfVekFTSD5mQTCPbcwuX2juhSqcaibCFzT93Cck GuEBoToQTs0AASfGHOETUowRQwcWVwnorszn5GQDzAKz6N4UT3yl69HFLmek8keMHiWdIiCY 1VQME+WYu2HpkoK3U+oORJyhVnWaE0eruEXEHSKtIi8ksNGkWjmczpqVNTVsstIiVc+lBAKM 88qEbcWhqlVC2pmw3K5IHoFZfWUWYaV+i7G9xOmoyg8EbkRGyLJ0bLtFSZzc9QjUPh8v1Lso CcXzudliqh+8CAyLI16Rh+eXbU5viW3SyLYDAaiWCT+viRSbGjZBzYbsBxDWjN4PtliR4xvq qktuezAe4/FJNNIyFvFDNsGoule+CFhYtx0BOiSJOioCbl5T6dgWzyYIHgp+xNldWujVoOdq vTdhKfwygWUNe6BaB1Z1GaV38Z4btOKphDkc/Us5Z9thHNZlUdMB3pEgRjfXRK8K372VuVlV /AUa5ShlHeerVFUJApiomzCEQAFN2ZoDdbePzbp2LGtKyvtSlLuvpd+tVkqK8a7NcppdWmwY 7XMhG1TwFMTY4ZaBJFnoDu4v8HFRbqkjPYEs16ktmQMUf1Ta5dsFkyRkhYiv23yVxRWLAoNK oVkvYUOZKBcMCNxtYvQSs8VfeGXkZcvdcyBPMTJlmZBhnhFf4plrbMh33mZNSox4WTfxnTlW FSsw7nxWkuH3BEXcsGxfGJO6gomVhREJRAfADwquOofpregJMtCcrmZkDKM8FGnIzZmb5sxo Hcxv2VcNJnwyTQbwKo7REZHyLRH4BscPFGTMrU/bospaV4NrNfSLmEF1HBeM6+rkAqTFSlST w0rzR7nHupRFSIFqQidmYLotrVlZVhy66qik2cCMNBRHs6lb3vSXaUppKtw1Z6Q+oUO7Clya 5qV6mY3ALi3yUgd9ietS7/gAsTr9ZR/BUmNqKJkK5LBpVyRcOvn0vz4racz1pfm6korDZvdi Wuk4rbjVGaDV6/n9fI9vV8wlFYu+WylTSoQSQAXxWXmvQJoMeMgjzQbl03ITpgf0rQTTUXqM XvmlR+JQgGY8C3HoX6PWZGBHhZFGrQqFDNJQgAEUxoci3vXeNfbTef01LvKmPyo12TwkKUHP hpR0NBdUZhgSlQON5i/Ygw67DWiHzCjSolplQlvxBmXnJmXCcye+zaoULT5H6y1e7wi27sTA rFhCS9b57R2fVeCDqCd0x6bkKpzNO88TA6hV16GM0FAt4ukVej3n1doY9wU5+ll2beB7m8qu CxNc+7OORoxngY1IgOdQmI0oyc4M0L5D+ugNOE6a//rn1gm3GN9rnfq4++PA5IdGwLOF79+k qBdsNpvChsHN1h3Z482OEcAwMkKpD1BuSxyCRYL53PB2vEhdnw8mfDq+vVGJmoQ6CCntLy7T anFbbIh+ZPC2ycNB8xWwVvxrJPjWlDW+hnk4/cA3dfhan4c8Hf318320yu5Q7Rx4NHo+fgxX M8ent/Por9Po5XR6OD38H7TlpJW0OT39ENc0zxhe6/Hl61mfOz2dyaMe7IyLotLgVsYwvnqQ iHlRufh0qYM1LGErnT0DMgETIixzGpnyKNCdA1Qs/M1cinWg4VFUqyniTJwaUFHF/dHmFd+U DY1lGWsjRuPKIjbMVxV7x+qcuTo0xDABfoVupT1Qw8b30K5mgSO6urzZtlcwlP/0+fjt8eWb HfBCaPUoXKgnqQKGtrwhAwBPK1eAW/GRmIxRHZr9lYjyxhImKNYMQwfdKjzCoK11eU3HUD0d 32EyPI/WTz9Po+z4IYJfyJVbTPycwUR5UJJfiHIw/VJZZHtzvY12Ie3v3SOpE1mxYG1SMKVi Q0IG6KFMHAhCyV9wLZnIe1hr5jPPXoDmMx8/M3vV08vMEci92+X24zDwmSzqMhCkuKG551Kz LedzRzYGIeywd9EPUi6l6qaYo/g4T2d0RMQeG9DeU2IFiNqmpcMsy6ZteezSnXVaTm3NlcXr snEeDQgK52opvZ112ej1RbifhzO3oIZ7kZzNNcrRYKWrVkoTpYc4Y6YtjYdeEQw6vpXV9VvK 4b/t2hD5zFjHm5qBhb1NVzXT0geLhpQ7VgPfarObuJY7Gh9vOEimWOyTtGvaOjZnAW7Yk50O 3QNdp4PiL6LbXaCDNxyMc/hjPNVze7bS/+buAIzA2CbxDV0WbljJjXOwixBX3z/eHu+PT1JX 0duqarO/7gyKPqBZF8bpVt8wiCxyW+mHct3uss1WRAK8McnH6mn1VfNSMNOZVcFcvVm17qvf 4WvCmD55tEldu46hOugonlXuPgcEdlgkizaHDUySoH95oLD99Pr44/vpFRh/3XzoXB8M9VbN ySBqqG3YYO3q0KpjwdwQtHxrf42wsbl1xvICU+ZWUXhjIWB5NJ2OZ1b5YJEEwdwqrAfj/Ydz SATNwq2f1+Ud9XJZTKm1jM1jD47MTKijZDgJy/DP0hU6R5U8bUwVdUBnX8OqbA8x6jqTsghz ExTboGqDtptFGFuEvF1xm7AuQDOawByf6lxtcA2XWNQtC30CFliwbWhVpN1XSZh1qJLQexf5 Z8JNARngxCpM0xl7JpqoXMXUUxaNplC95DRMfAszjMyHo2oxRL+qGwecrqEXEFfp6lj/mg0J CO+BfPBgkCXc0ZxeXm4gAydSfzNiIDdp5C51Gzpxg3C5GJQcGuemGg9GdalEyGFTVLi46lUa fry9VrGZAbrAWOWbTT9NTbp+1HXdhmJ4cxGyp0zSFiFeNDlXL0MhUOtfw2pj32M06xfTUTwJ ubl5Wit6QB+qSDqjCn17owVFeed4tCvxoAgO+Y2FXl7z3MC7TqklNlqt6dzGEr2LV4YHr2GF i6t80nTfKZc/8ANPoxQR2slDK50k9ScLTwnskudq8q88NLLkiYirMugq5ndUTjwvjcSPRJZA +sYffZnw/p5oP37ZzxerNvdRq1YxjzYhmYYMsw+v+P8z9izdaSPN7u+v4Mwqc86XGUAIw2IW QhKgoJelBuNsdDwO43ASjK+Nz53cX/9V9UPqblWTLPKgqtTvrq6urkdkdLRhyRK4rgUMFzdG 6EUA7Xg49Swz8/EgYrvw6MQyGUre69AsZwvNS6Zw0xyaY6wUUmamK2xgUa+TRdBHZEx7Ysvi rGYJd4vrWidhfR2ZDB97Or/+qC/Hx2/U5bP9epvXwRKVaJgzhpzQDPNt9ie8xQrUX6d+vb8y paodfKYce7Il+sQVPXnjzRzphRRhBcIp1dgWT80HPqzgI6n2xgy/hDNIR9XBmiX8vVYdB3j/ fsSJF2E29XTzrQ7q21Du9jykgF4fKEx4u6d0BIMEMJmRqRs5+q4KSqugMgzmvh4TUIdaSUY5 yso8yBuDmcImPaDv7/e9V68Wp4eE64Ber0sInlLTKbEzKwGbAs+m1MaV8xfDtTMLkpTqtr8n oFNv36tEZpFC12HyFYoT2d7oLdDvjbme7YRDutxS1uKJxkYOGA5UJvoTw9VajAbz/Hl/ZKM4 TXHFLIpiQ289TsbCAHODXCFIQ38+2tObklOolDbOWYQl7v9rtdpyGhcFtakOTfiGRePpvL8f ktobLVNvbDbO2rH8heLv78fnbx9GIo56tVpwPHzz/owh7AiDrcGH7nH/d52piSlCBUxGVspe j09PfT6Bh/5KeJpbwysQwsX4yixIMrgF4NuAa6gVWRKhs1G9cVa3juEUX8TkI4ZB2JmenEh8 WG6dlTiTYRlU6rnatGriA3p8uWBQ0LfBRYxqN2X54fLP8fsFow7ywHiDDzj4l4fXp8Pld3rs uQawToyUzWZXeB6YDonBWzAhcpImTFODxVEQNrBv8fG8DqvtwkIRMTYQTgx0xULTZxgB4kgy QOsQRIl7GqiCcfz2enkc/qYTAJIV69D8SgKtr7rHNRY6ZA7ADI4qKppxzOM3wJ6W/WQiNgH6 sZvN4WArv4wOb7ZJzENXOorF4Pdc6NQMPbClvcNaEQeLhf85rj2zGQKzn+mhWBQ8qs0QKyYc pHTDvVvH3kzsbnUYR9Z6jWhqJGmT8PV9NvOnZtouiQIuPJ3TObs6Cp6nlv4Y85pd/1hl1O19 zbNyXfm2qv3Quxn3Rymp09HYSOhlIMbECAiMT0zIHuFU88pwiab6VxrIKcwcgTrGiZjRMzEZ MYfeUpEsbr0xJXG3a1pkyiJ7w5O6XS1dJeu6UkENUud8GPT7tcy8EV1xBfuDzIaqEfizUX+W 8cOx368qzrzh+IYawWoHmHnoyCfWEs1mQ/rpqe2l3z+k0ZvHySJ0p78fHT2mfPgpa4lqb+wR ixxWyng0bsNht+/EVwsLs6KmRgYYw5jOMNgR+CNiEhDuE2wPOc3Mb5ZBlqT3jhqB4OowcxIy X2NHcDOekZsTUZOfl38zm5H5HJFC9IAHSQGZ2jomJZafTQpNN+L6aovq8WRIuaa0BL3wUwbG 2XpJQPEYzHh1w4IZ1eRsMmNXFwISeH5/whHuzwl4nU3HE4LjLm4nZk5Ktf9KP9Rf7xQc9y7J QPqJ/ShWzWNZXenX5/v8NivV7jw/fwQJ9PpeqvNd3W9mm2u9dSgRyUysstomRllAWGa26GC7 l6/TlG5Pv2dv0R9Q90ZGQIlNWsV5Ut2aiCiLMxIR6A6FCKjjKix0yYaXixHrhJ+KiYCb4d5q QrXVdSEIypZTPUwVBtFTYXBMKO+fzDvzesHUOPZkyGjDhlKmg6F5QhDe24XC7SNNCzNNHIeL hE1GWjsOz6z809Jw9vH1/Hb+5zJY/3g5vH7cDZ7eD28Xykp5fV/GZsapTvfJghXcBonZ3c+m WuIrsUb09R9gjKi7jNY5I3Id0bbgQQq3FR5Uwfl1vYX7dVDS7idcBVBni6Qw2sPB/Y9MvKtG hWwCx91OVlrA4eyIfrr9lLB6e60FioQFi9TxHMHC0Wg4dDZzXV6JCQpIDLeROl2RSme5ZRvK +krzUW2wKQMePoMuRpjN1xhLpqTbIBQ+WZynBe2aFsdxebUVfG1cXTjUILTLskzwY0NnXifO 8tBJggXV1fZgkVIn7ihD6MsXrKmWmySlJ09RrV0jpwjcOw7aEWYlHVNWjDv3INu5YqoKmqSk Bg4jkVbMiPmqgpo792m2z+yxVt/cjuhNxM2hmlXmMBITLawcpkFSmYiOMKEI7Uyv9R2s9uTa MJVZiBFJ6CW+rTC0EMplXrPYMkZmWZDlbPNEBDxpD4BwXRVZ3PLV2sYUiu91Z0OLKPGRU7N5 CNMN6hLgJNlsNXdb7t0KOIzmVAZ6cCGh1kacOtZkmJrw+/nxmwi0/X/n12/d8dZ9oUJ9EoWJ DCJx7sKpC7YDaUhhGlIlxW6HXsPVie/5dMAHk2pEybYmyY0h1Wm4MArjGzKPh0VkaR90bM1j hoc069DbIRJzU3UBFu7N0+HE1c58/9Pir9yudao7+olXJ9kbTE4ImSome/1yfOYrqROTxCrj wPr8/vpIBG6HYusKNtxsrF/kABrvGAFdpFEL7fgGj99UJg6P7rXQQwN7/AlBxrb0famlYNmW JIhlOE0MOkE/9AVJuigo5UUCw7u1EyGvDs+YU2rAkYPy4enAdcYqS6gu3Um+zQl7+s3D6Xw5 YEJM4iIRo8udqb2sWcydPIDbS4Qo5uX09mRPa12Egw/1j7fL4TQogIl8Pb78PnjDR4d/oOHE yymw/n3S1BUdCwzjHRgxQksudi4rMjJmvEcmr9oX/3t5BD4mvVCIqgV5E0QhD83qLLAJ9uV4 ZlxNJcKp9Zd44GWjiX9DhertKDxPd4/o4PyhSechEtXftya+YrP5jacp9yW8znx/OCZ6oaxa XW/RRUVd9BL9opfgBYYbgFKwJlyY4A1Pt2AEWkWwfJ2II7Is8V/dTkv7pkeKdgAgdZb8MUSQ jHWS+k77VATgenw8fD+8nk8HM6XuIgtGM80QYpGFI38o492fKKgdD0jzJRV4jza74e1iiibY k1Z0m334aTMys0pmwc1EX0QSYLcDwLMJGeAGMHPfH6kgzCbUKHduqNYynqzTOOkANB2TOqCa bWaYWlGXFwG0CEzfmv/Rcr5jmjSZBw72Mmxgc2qC6GY819oHv+dz431bbF3c49QxikkIhyPE an2EPetNjZMkC0tvMqYPgTzYorTiuEHhToW9FTjyg9yG6FdcwhUzoVvYEeyMRrIEGz2cjYz5 RWgG7GTv6K9UtUMXTXcVLkoAvNdQid8tp6NhIz4Ss3N6+Q4MXT/Ovx5O3MJepsnV5oilARp1 Kv9prd4kuLUdmzotx+fZvP/WvT5+UbqrBE27uKhqRhyRG02wAdNkw0Kr/X/S+QJm45Y3Vtw9 SjNel6retk4zSyEmS+ZLll6n/nCqaZfgt6cHToLfk4nx3pRNxx4ZjQ6Wpz8yXhIQMhtTYiKs 28mNKYfWbD8idbtijqOg7TKO75f30+lHL70xDpMwJI93KOIb4yfjEHG8GyNunBYrNwjaE0Dm +zn87/vh+fHHoP7xfPl6eDv+P1ouRFEt80BqMiWXkh4u59c/oyPmjfz7XeaRE28SXx/eDh9T IDx8GaTn88vgA5SA+SdVDW9aDfY0P/14Pb89nl8Ogzd7nS+ylZFbU/w2w3dpC3B1XxWNZzgb SfYvMA7un7CVJ6xJxH44PHy/fNU2nYK+XgbVw+UwyM7Px8vZlHuCZTyhFfwojQxHWvHvp+OX 4+VHv7fRmukRvtYRslI9wgYIzWaEruRmOCRPBUBwJbpYdTB3FzRQOR0e3t5fRTrvd+iD0YNN tp9SCz7JdxgXajqEk9iUT3REt63T49PXi9Y5U3ESpKS6KPoEk+jpvQ9SD8OtaYAyquee6ZnG YXPSlmuxHt34moQRZt54NNMqQIBnPLgAxHNkyQHUdOpTw7Mqx0EJgx0Mh5pOPqlTOET1V0td XklrEl4aWZs+1cFIZLLunjnKauiPHfEXJYMVBoGUWQ6rjDw5Rcm8oWkdV0KN4yFCHSrsjeeR T7gsrL3JSDPy4wDdAkE1j8HA+FNN2gHAxPcM83d/NBtrdrm7ME9l9nKhj394ej5chEjZ30TB BiR17d0q2AznczPNlxQrs2BFB0ICBCxFqp/aZOHXMSuyGIOxeKYZseePTSWC5EL4TZ8L9bW6 WejPJp4dHk/u5cfvx2dX5/XDOA/TJNfbR4nO4rmhqQrGg0z1qlPmaIOPA5Fc/Pv5+WDciaFn 60pe2cXZT99rRJz6alsyWkYQL6zW9UEdES9wt36GE6e9RuhiJC4fak2WKbDdsSqqfD28IfOj DhkQZ4eOHRnrb1pwlI5Gvv3bPI4A5o3MNKZZ7U9H9JZClEdbT8o104t4prrnT7rs75znPqNf /Jt5apWv53+PJ/O0aWtIkwhV7gmLm51DG7OfWymxxKo4nF5QHDCHs+tUup8PpyM6DjHLSjpn L4MVMBwZIjRCxpRXcc407zn4gZH7V2XBo0xpUFYURupUThlXVMAnTo4GfjKofCczZ7Ejjgya 5P7QfoglbIKEvmydoneKYcKLyLAybgwIwkjhS0apbRCbmmEXJcT2ve/gUvlN36OAitsuO4wn EA93GEdLAMPdujthoLpFf3+N72JaW4wPFOybvPpr1BKWmLHHCDm/KIIqgv0aJlbIDOEtBJ8U ISNjEsLeiBlqJlhVpKmusVjqrizwo1kGmxgtBU86ENjNLjHSuqGrSIU7IkaFnZmFDv1D+tm1 xT5b3w/q97/fuJKuYy0qiL7hBw0/UL3bjGd5xt20HahtvTDTkYVZsynygCOQlJobdNEP9aCg 8iknKI2dkJlROkQfDq9oWPTw/HgYnISI2494VQXaxLH1No/Qdzpt1anB85fX8/GLdh7nUVVw r7xOahOgZpHg1/YLUMucFvkuSjJtj6kwM2Vmerxh+oSU9jhaMFoRncO2JpWjTM9xwDL7zoWg uthWcGYCpBZxJfq41jzaEAL4TLB+lHoMIm8m6Na0z2rxlXqAAh52PltV3JpF4URZx9cTfyPo haOKI227wg/MsGUsb5UxGEYmC6487VcLMuNzGC30tRFlie6LCT9t/shBYZDz0P2YYCIv8iZe JrBV03QRmC5NCQYbapLFEsMl5LSqb3nXhMuV0454VRQruAqrfrYPAOfz0/fDlYGT38GwdFMu xxq+E1tev8WF0J24uSuqSJqAG1rjcWO6XkpQsw8Yow34gcKzYgrouAkdb+DTItLEb/zVevN1 94k4ARaL7q1kCRyh0yMEHSwxMSnFjj9xh+twWwmDd+O7nlm4gUU3mQT9r6iG7EVDtEFDyO0W hFaywP1Pmol4Pf4e/oYVYWRl31NNVgtiWY8NF/gibCFtAQrWFGNHRKSWAjtPT68gEVElsqDe pAXVHp1K32ALVvVGTsHoAeqTwVLmCfZYvMJZvU5cbfOmDnKg41b1dJ8EtXs5CHxQw8qkTNzz JLWHfzlWK1UH4Kha61cS9veajhc9Jj7k2k062xF2KNDe7PXx1Xc/CpdGQxNgLOgiKdJwq8MZ Dkh07Lp34NHTPw+r+5LHBdbAbRp3xYpsQCIAIEGYvu7LQCAobTluM52WA9D+j0eR4bc6Rw4o 7qkt6XF/iU5YBbk2mcCyKjbCstwuM9bsqOuewGj207yAkGnjjyHflvXE2hFLGAyaARa7uEqD e0EvLjgPj1/1oGPLmjN7YygF6MqmVhRrYHjFqnK4eysq90ZRFMXiUxyyxg6sKak4DQ9eo+nC Wlj/TNBwZAPFOEQfQTj+M9pF/BDszkDtvC7m0+nQEQsnsmJDwO88rdtbf1H/uQzYnzmzSm9X K7PmMKvhG7quXUutfa18xjCvRonhDCbeDYVPChT4MS7Hb8e382zmzz+OftO3TUe6ZUs6n3nO egesELffDu9fzoN/qB7KjJ3G7RBBG+fTDkeD5AMLntyJmDkFowplBbDnQrsocRTIX2lU6ZZF m7jK9SmyZDe4xfd+UixPIDi/1QyntivgHgu9AAnibdQtmPAfi7lnIAqKaEz3NYt1y64C7u+r uCe1BJFLwgmW6nxUHJpzVaO6FgQCYF1zG16t2b3zFSAiSDJV3yLun8fxFUFj0etL7BbW5Kn4 w4bILT7swfk9t30S0sQxhQcchsayzgWLsIYLUlBdo7hy4AoClUMOTjOeSBKk7H6DPsOF8Eol 6WcqKr3AcfWkPTDVFq6f/WpCntcZbiL0NtOJSoz4ZslEBBlP8eioZxns4MJItx3a15t+BYM1 vcNwdDJf8pWvcWA0Rqugn60ssAIR4EApAymy/yCAkssvhFPCXNj17Tao1zRL3ve2dA6Mw+xq kfWWerfJSjfuNt9PXJsEcFNrx0uQFRuukrUbjy8chvdStKW5vxLmxKbMGKXD7JVXsLXdAtgQ IoJGHw6FGscDt1mlNBr39c48bK0REL8FNzCperIBCH2YvFLnvpSEnmq1wQ91RBpnqIZWh3AD h7D5YYu54ZiuHQbuhlZgGkQzMoGRRTJ21jHzf6kOWpFvEk1pg2yLiH4tsIgoUwaLxHN3aUo9 VlskxjOGhaN0+BbJ3DGdczO9nIn7+UzNzWdbEzeZ/8LQ3dBvE0gEgiuu0YZySDYKGY31VGg2 amQPfFCHCW2wqtdK3Wx0fK/jCkG9+Or4iTkVCuzbzVQI1+wq/I3ZdQWe09WMPAd84urPiDJr QIJNkcyayiyOw7Z2UVkQIrsMKL8BhQ/jlOkK+A4O99qtHtetxVQFHJNBbg8cx91XSZomtF2a IloFsUViE8Cdd0MVn4QY15Z8D1MU+TZh1Kd8HJKrQ8G21Sap1/bX9r2G3102h9fnw/fB14fH b8fnp+7ewvUj+Ba0TINVbZtav7weny/fuDf0l9Ph7UlLQNFeRpKcbRpTXhNyN+pBVmm8i9P2 PJloYnRRMPV1FNNelCpjhRHULDyfXuAG9vFyPB0GcLl//PbGG/go4K9UkgyhaUvypcNOOUe3 M67xAFKQbMOAxbTGWpJm25oJvROlWwLRSpT212g4nnSvDVVSAlfBZ8fM9EqOg4gXG9RkDMB8 W4PEAV8titS8YvIg8Hc5+YTfVy+uoR40B+YN18sRpHXMwwnifY2nBXaYPJhEYtQwoDl1Xas4 Qc7kmJQF1z7p+jQdrunBRNsLfJq5i4MNt2C2Is/wtFAoLVWUFbwoAS/FcdraofBwZoPo8Pf7 05OxDfhAxnuG+baKvD80iOf53+mrPH4NfUA/QdJhtCsE5nrZL14ohMj8SOiyJPuSxVkKY9H/ XGGcNdcMn3C3tbirW1/vaHWWRCYV25IvuVLHzQ3jGzPVoeyumDKYp7K2cetktc702KdaP3lj UZO3TIs7YpXqaNeI8YWHw+Ja6uvEXDVCjYULY4BWke8vgqmsH56f9MhOINlvSyiDwXTpOhl8 ZHYikdWVASx0naxET7tfoWl2QbqNu+f4jhLznf2sNJumLU0bEGxvs0bnQxbU9AXp7ha2Mez2 qKA1m6Js1AYUpJOkgZdtGJpIPEKKLevANcxdZN/zBBA5uQXj2lubTqz7OI9almesAqxyE8el oSFSvkqiOJsPwEmflay3cnDNdHxl8OFN+nu9/Wdwer8c/j3Afw6Xxz/++OP3/rlUMThPWLx3 BBqQKxZa6by/yr3400Lu7gRRU8PeKQNHekxBi5U1V3heBXtQvXQ4NA9QAI6jk3momFopzEF/ rGXZTVAmcOqky94DlV4PbDiMyK9iQ5HSjf7wD+uCIwlmKpixs9Hwh4g+L5tMa/Tl2kk43l6E 9cqG8JedxIodJ1BhFUcg6CaWUa7wRAu3xtFmTRWiyQO9RH05otUxTPTAGt5OcoGvdBylNQES PAZgzNO03eXjkVWI450OcfFtT90jl/OtFBGqnnAg54qvDTjX0QqF1o9h09bALVNxtLBYGSdR grecmCauKm6w+UkIQ8ZrDJRH0lFcMaNJtXfqJQgM12rXrjsxQ1MbF5X2BMLfSVTbqQ0Fo5CH 9+hqrRmHycx26hCuEjg08FUSxqu8F/yVWLAOQkrKrQXblRuzn3QPs1FwVGWJDSoO9k+wqyoo 179EsywbMxC4kE7kbWSpGIcb2dwlGP3biE0kKhLoLCy2IBTj1FaRRYJPQnynICXfkXYhofxQ lKKdXLxr3H7PaqKoNbQUk8hcbRdD7pHC6Y1DEfcEbqMaOhb2B1Erih8Zd0Com7T1ylNmdnZB krA/+fagO+ccmD3IPMsOrrFBfnZLDM0LudTQJzAaoWao7o18nQcikZcL0crE5vAsMFPNGvk0 Nx/AtwzrIZHDMWkkcqhIfuA46ltyWEQUoX4G9oZPWewp0wlNvwzlLmKxQIzHSAU0d7+xH6ix VBMom2taN8iBZgEcLaU75Q1G/+lV0GK7HdQsgKGts6ByqP+15fvrlK7WGXsuxqQwcAPiGvj+ OhcDp+Iyi2P8/ZmrNtjh7WLcUdNNxDR7ZJ6IiGfdrK3go4uOh4LY5B69aoHGGq72c1EAJPWm JTJMluMK17HjWyHYTSet3Kb1HJu9jvfRNjNSS3M4nhY56ilSTGVKDSpSbYDsv30d207kOuxX 0PkCZriIfeAhbTMzWXojbWFmXiqWZRekA6wG0NH+/YmTtHVqZySkEbabprk4tuNLW23J09aa xLmKW2yi2kIEYqYFa3OobWzaoaiYC7l1objl4uzbOWQFs9oud/nbqdwoLFXahG7i8AgIsbFL YzeTN/O5Hc9M8qFJHf3K0Vdy1pY1sWELXeGnZT4BojW7Fsq78wxSQHBi1FDh1O51FtxUwv8x 2xBIFF3SCO+FpvaWbYX3nA1rBEUCCXgG96pxJw92cffCh6PAjdpADYRj2occX17Ot+o0ziMj hc533njJQ23VCPxGmzKshUVPqhgyNEfUMl1Bicv4pvaSMZ8laLDz2XKlXQ5hRCWXd8PrIduZ OpVVndknzpQ7V6XzZJV3oTHaZ+9oI/EwdsWMHJwe+RBfC6u2b3e17E+3V6eTbWCOM7O+4HF+ 5S95rD1qz4KF4bDwOnYIEUXERDxSdDG79kjhT/pxJAcfJtRF3Duv1FjLOVh3ImlrasZHb7ql r40KBvtMlbk6aq40J5Pezee5LBTD1GHlepNtqIa5PE9wHESyTDdPj18HiHYiNwvAg4KmXHFr EE8NCs6JiLeqf5Y9krsGxCfb9ORC5DwzB/jEPbxfNGRkbGzkimUZuE8DCSdeeVTgP+8neGpZ pHHs9T/jpfvWaHJWl0Xdtp0epYb08PfP5/vJIxTmfT+cPD/9+wcHqztiwyHXokYlZQLwksKl yFggJTVyY6rqDRYl5xj6EBy9LJCS6kAbGWEs4XjdRLoe7YmI9V43gsAKUYo1Q+vhtHXrvPvK U0PWfnv3Y81b5NH1arG8KrqcIMou54H09bX9JWBwDLntZCcJxv4EzipDnx2GdSdy49i1G7Of ghhth4lIisNzoHc4sY8OQd5JjwNGM3j2iq/PZwgxfXz4fPp5It8eYQdAJM5/L5/PJ+Lj4/3x xaKyh88HshNSXJJveFFaMB1PN8L8LU/rKt8tztjgfU/ZyFtcJtNDpXnaMNq7od+JTc8AhYE/ aK+SlE5GS4ckZVaKxOmFPCzX98xqSFLy6dtQe/NQww+hxAxh2puHj+fYFxSCfsLGAefNb01P 4qN5V0xZOLKX30Yboi/T6dmSfowDu+gtHsmseAM1Q5NzW80g28VpplZ0aW5czaDZCPuVQrd8 dk6ZRnZBYcqsGUgGquhY6iJb4PJDCHx5ygyyQSwv+LrDE8XZknPhGZb1RizI+wzQNEt6Z8AX iyWhbtd68Y2O+n19sRjDvVNbJJWuKCHpWjew/uKKvh7gpfIzT5BllyimLZ3SWTGH7f1KMXM7 IKasOoRfiELmeVixbk4BzgPuebLWDI4uCIDSr81kw7x/ZX+PTfjNRuzFESbeiLwRy1M6uQ5u R55sK88lmRXYSHnsZVLXYFEiC8zB+6aRS/aNraQnc3tfrRQjU3h4bNAH9MV0uoCXCeQfeMGJ lcZxX4GJnHJb67g7//yrSJ758SE2D+eItEXpnGHo4e3n++tJ+fX64+kw5Pfh+gdFb4wWwIlM mU5A+S87HrPhuLfDiFC3w7iU9RRHFKTJ76ptpQYFA8wbnLjUc3LqgOg92533ZsQ3Xpw7NvAj sWZ1oDkVKwtDP4bL6Hn7G845QTS7opCgR8Dh6hQ8nB1nQtdG1fZUTZcAITmGU0gS9MsKQB+2 6NXHy+83l+PB+kXNrgGd/y9WgjSv/lnF/OYOeWd4LxC1F2EAW6JKob3NY3U9phP6cXg4/D05 vH99vrxhGUELlV32Ncprn6hWS8guHxi8J1vShOfuBm1vBOL0w7WC0dTKtN71K10VQ+gcQ5LL MoItocZrq7CNf0BBMDOY2ZxJkeIhub2qCmzfH1BR8AQbzVorOCRs5dI6V6FUnBrp1WwgzBHT xWVIQQUW85626wM1wElCaOGCEDRo95G9Y0nMypTJjo+eCkh4r11PIvS9aLmJdfhgdA0IObBC pW4i+6VIKoKqvS2qgzDtMIuwowyBGGIk4i3kosyqIjIongYCM4AHhEeChZKDwpwQY+xMCM0k Bzfcf6J/RXCWfrsH8Px/qzPNYTbrRE1plcAJ+jxQ6IKDtZuuSAgC3Alou0n6PbCGOmhkRKdv 69d7nKEEIRKDWLKYfF8IFrHdR+irCPycblXrDyMC7y4twdGoyqsgySKGQqt4fyYpklCCaxbE B5qmSpVhcJYTamy7B+5gOEnoPQcgMJ/2AYex9nE8HC5UulHrUoDPxnXouAAB65Bkwl4Ncvuy 7oy2gF+Q3WLum1eB4R/+P7ZzyjyMMhx533h9ZJfkyoYpwkig78j3UCsCASqdYW0py8I7YVDK UFeLWs3iqRrwhMnZe52xXw0MoFAl02WwY/eDBfx/JY4TfrTnAQA= --17pEHd4RhPHOinZp--