From jpehodgson@verizon.net Thu Jul 30 16:55:20 2015 Return-path: Envelope-to: ulrich@a4.complang.tuwien.ac.at Delivery-date: Thu, 30 Jul 2015 16:55:20 +0200 Received: from mips.complang.tuwien.ac.at ([128.130.173.64]) by a4.complang.tuwien.ac.at with esmtp (Exim 4.69) (envelope-from ) id 1ZKpEu-0000YO-3g for ulrich@a4.complang.tuwien.ac.at; Thu, 30 Jul 2015 16:55:20 +0200 Received: from tuvok.kom.tuwien.ac.at ([192.35.241.66]) by mips.complang.tuwien.ac.at with esmtp (Exim 4.80) (envelope-from ) id 1ZKpEt-00013k-7H for ulrich@COMPLANG.TUWIEN.AC.AT; Thu, 30 Jul 2015 16:55:20 +0200 Received: from vms173021pub.verizon.net (vms173021pub.verizon.net [206.46.173.21]) by tuvok.kom.tuwien.ac.at (8.14.5/8.14.5) with ESMTP id t6UEt63j029989 (version=TLSv1/SSLv3 cipher=DHE-RSA-AES128-SHA bits=128 verify=NO) for ; Thu, 30 Jul 2015 16:55:13 +0200 X-Connecting-Host: vms173021pub.verizon.net [206.46.173.21] X-Connecting-Addr: 206.46.173.21 X-Sent-To: X-Sent-From: jpehodgson@verizon.net Received: from new-host-2.home ([173.49.33.217]) by vms173021.mailsrvcs.net (Oracle Communications Messaging Server 7.0.5.32.0 64bit (built Jul 16 2014)) with ESMTPA id <0NSB00HN02R6JSC0@vms173021.mailsrvcs.net> for ulrich@COMPLANG.TUWIEN.AC.AT; Thu, 30 Jul 2015 09:54:48 -0500 (CDT) X-CMAE-Score: 0 X-CMAE-Analysis: v=2.1 cv=MtGvkDue c=1 sm=1 tr=0 a=LAGaCyix1vBTfoWuXDC92g==:117 a=o1OHuDzbAAAA:8 a=oR5dmqMzAAAA:8 a=D8CbCx8wFrEA:10 a=-9mUelKeXuEA:10 a=zOBTXjUuO1YA:10 a=r77TgQKjGQsHNAKrUKIA:9 a=RuMV0j4tCZvyYIiKfTYA:9 a=QEXdDO2ut3YA:10 a=mGyM-rFS4Q4A:10 a=G8RmlMZbMS3FzVNJP3kA:9 a=n3BslyFRqc0A:10 a=Sf_gFPzhefAA:10 a=zEEYXLHKvh37BADE0kEA:9 To: Ulrich Neumerkel , "klaus.daessler" From: Jonathan Hodgson Subject: DCG Draft Message-id: <55BA3AB2.3080201@verizon.net> Date: Thu, 30 Jul 2015 10:54:42 -0400 User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.7; rv:38.0) Gecko/20100101 Thunderbird/38.1.0 MIME-version: 1.0 Content-type: multipart/mixed; boundary=------------070001080000080004060304 X-Greylist: Sender passed SPF test, not delayed by milter-greylist-4.2.7 (tuvok.kom.tuwien.ac.at [192.35.241.66]); Thu, 30 Jul 2015 16:55:15 +0200 (CEST) X-Spam-Status: LOW ; -15 X-Spam-Level: - X-Spam-TU-Processing-Host: tuvok.kom.tuwien.ac.at X-Virus-Scanned: by amavisd-new on vc9.kom.tuwien.ac.at Status: R This is a multi-part message in MIME format. --------------070001080000080004060304 Content-Type: text/plain; charset=utf-8; format=flowed Content-Transfer-Encoding: 7bit I attach the latest version of my draft. I would like feedback on 7.14.9.1 It follows what was agreed on at Radebeul but it reads strangely. Jonathan --------------070001080000080004060304 Content-Type: application/pdf; name="dcgdraft-2015-07-30.pdf" Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="dcgdraft-2015-07-30.pdf" JVBERi0xLjUKJdDUxdgKMiAwIG9iaiA8PAovVHlwZSAvT2JqU3RtCi9OIDEwMAovRmlyc3Qg ODA0Ci9MZW5ndGggMTIzMiAgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+PgpzdHJlYW0K eNqVVk2P2zYQvftXTHvJbhuvRVIkJTQI0HSToEARBEjQS7cHWqY3QiXRleTtBuiP7xt9uPYm tpSDQVrkPL55bziSoIg0KUGGYkMpWUsiIiEMCUUixr+YhJEkMEsxJCSjiKQgqaKFlCS1wo9k gsGQTC1+pKQlFZHSQFakEgwxqTQhZSnunlCsJcWC4sQuYkk6wlSTVh0LrSOKU9KIw8xgDYcY rOmYDC9YMgmvkxWSjCAbywU4Wo00NNnEkDFkwcWklOBMG1Gi8URRkmKIKRVdpqnGkCBhpJwI jLFeJEgyMgkCoEKEEUoIJIoDhcDJaaeOphTyiBQj9JHIGacJaQANPNmDQkKRLEQERKUYHpDK 8oTVTVhpgMYAF6w5KyN61XkCXM3/WHkd8+kA1ThZQH1hIrNgWoJ1EXBAGNsxgFMRosBI2BgY 8EFYSCUY3aZ4DC9EInkJAYmJmAsmnCAcESmMBSlMDLuv2XCswxcZMSCoyIjV0VwHHTt4L/gI +CMFCwadpJS8hHqRnLLhihFywbUkFdZZQ8k1IeCVjBVnAOTYdhlgwjiWi4tx4BkqjXMCsmav ILE0LBv+SKOBDOekYTtATlqWBRCyyx25SctLcE8mXXJATixPgJzAR9GVLtsETjJlUnBQRZFd vHhBqw+0ehs+Blrd0lXjszYP1Q834ppevlxc/Vq1ddjsu4fX53fLfvf72j/kYd+Q3+RtqBty 1YY2tdu2tAnZvvRV21xAUT3KLwGH5us9I5zdPRL8kIWdP79rIPYu1KVr8wdPtd/62leZvwA9 8Lj127zK+cmFvfFA43O5DkWfsFuvWQc3EanHbMtdkTsw+srW/fqwe0z4fR2KcE+7OiCHJtQT UfIkqvWP7USAOgm4D66YCBgUuB0MdmdK5ThkSP31Y+ur5oxK2H8SclRjGzbGbwjO1+5ylZjR HhB7vMjKjAK/C5dyOAkYQ1657C9U/Tu3r+kNSm1O6JDOz+umrV3Wwpq6pOYCz9PwwabfXZ27 deGpcqVvKAvVAzzAJtqGusPMK1csG//3/lzRH+N+WS39FXatmyYln5ToZLGZMYuP4HnBRNvv +s1V93t37znLzO/a/rY1vnTIOLucmh3LdJLbScwoyG1e88MH38wJGo56W7uydDXV+8JPsRtu xC2EXrvGT59y1A/8DkVQ3ZOjY9/Yf//os/3kfbQ3Qs1mfBo2kvg4FFpvSRWq5Vh682AGmd90 bZrClu6/mcmQwgdf5qiPef4iLB4v/f+UKa82ecaNZUq2J0bzuXCAR1xqvDTnMI9HDf/4c7WK 6E7iU8qXu/bzl7d3Ftog5d3Vs5tnd9erlewhD8l9E5g6gD0/BuML6NC7Z/XJDigegX46gnEF WFXde3kWiH4C8k/efqK7q+XLI8x8u2w/+Wrpi2YeqDmk+O9xitgTUMq4RSXX47dSHVrWHT7z 8NOrlehhh7persPm8/L8y/UJWtKjZa4ogDQrJO1Ddp9qtJO5QSLqo747VOIJX/SSeTBi1PT7 SJrXKnpDP7K0X9OgCjMxD3U92r0cvZ66pYevja4ZolFmhds3eFv6xx3aFT4ktnUoJ1vOADh4 Qa/2edEu8wpfYr5rFxM9PrkRyZddltZzYU6RxqYx+Kue0zCT14v/AMXvE+gKZW5kc3RyZWFt CmVuZG9iagoyMTQgMCBvYmogPDwKL0xlbmd0aCAxMjQ4ICAgICAgCi9GaWx0ZXIgL0ZsYXRl RGVjb2RlCj4+CnN0cmVhbQp42q1WyW7kNhC9+yv6KAFuWty0zCkZ2+N4giQDu29xDhyJ7Wag Fg0tdmYB8uupYlG9xD1BAuTSJEus7fFVVb9dnV2843rBCya4VovVeiEyzUopFznXTFZisWoW vya3979c3F5fpkuZieRqdUcbLgXnX+QbkWV5+tvq/WIpWFVoWDireEmqV/Yh46pzoyWlujXT EPePvdluTU+HfmrtgGYgonzBwYTWAiOSiokKjJasrDgZvW7c6Ps36VJJnbz3nRk3pgMzIk9+ 8OlSFEnzOPiOguKCcbC45JJVKkZ1vTWujfq/PwUNuznQ/O45RVHvPvuOdXYMllTOtBQQiWRK aTL0fmo/kWOZneOmSETGNeUhIA/FpMpDHhBAwYoKIlGAU1ZFaLtU8mTswTmszVSPjgK/eFcu KlblYASUs4BqKSIAq40bINqqSBBXntSpKJNN52rTkri3mFWZ+H4kwUOms9Ud/HI8l8msj7jh 2T+h41n9ycx6fk3fx40lAQQMdkfbA+o7jTK5H03XmL6hS2vfB8ggbHpJCvtD71v/CDipTB+Q quLEJZYuc17ArZQneJE+bU3wOK1NPU697QcSv7hh47p4Z/S0uu1Ta7eWQiTRAQFPRHQ501Hn yc2OjlpHOoat6+i7oeMOWPOxtSR6QbYYdPqJBMPGT21Dao2PMk9nMqeT2kOwznT1bMSNG7ox 4uueCHa0R+8spYrvXGA4LKgA4Sqlol5OegeJVZgYwBtYE/IrkycgH5h9do2lK7UPAD7jj+3c Hk74tp66mt7djbuEy/Dg4TswZ6BnASlQIkp7Kq7aDgN6dhACXKL6PIx4l+kf4E9xGdDC1dDy nOJD9M7OzlGIHMW1Nd3jZB7tgEQqJVSJjTc2Zp8QST6GV7Q2mj8ijm2OfUcGRltE4lPvQ1mW IUvfYxRQ+rFWpayS0Dhhnc+hZ8EKydpuwLoPx0BmXLHkcLOvFDhQ14Uqlio7KhU4DnMR8uT8 VICmwTIPryNF4DMsg9u6NrADD2M/hTLD4JXCag9ybAiunuDeOQnGmJWIWYG5pomSzr5Ea/jW E0RDaFPvj5dGHyzB651sFVuCsnFYvaQjASg3zPHLf7CuAiXwzgF0coaO7bvzfsqAeylZmedz p7LPzk9ordCJDfMmHojUsGl6sx7jltp3PSGFsJ/Pk0wd9PAd0UuYrOQGkiteN3vcSYgoXPkR 04qT989UZ1liHjLJh6G1MAEpk0PlgjOY5NmJwR3Sp+0XWiSOQFHRyAqSm9cjOWxD04J1T/7j kAVMp6IoZr/4tFmJ7s/jP4NKMsmL4zcGt9lyPy6PwFoSCEsOq9D/Gq0PWKhmaj3O9jL5yU+9 OYVSnrNKvoYJdcL/GyWLSBcSxn85QR4wQu4hTiiIOOG90DJk8W2cVMV4Jvc4BXQkz1km/4ZO AC/wFl0vefb/oXTnHy2+cVkk93Vo/i/U609CVTFR8ln1Z15w0vyKS35AMThcrRCXOzoc/D9U pLJnF3ye2QVyF/+qRVdHw+ubSGIVqUPCUbmfUwNAp8vsJLMkaOriP4O2SmGk+HkSoLer2KOa U7DpPBA+Kl9d3sQeFioJAoRQSRATDPuv9O373Zf4Z2OAef8qOq41yyGBYwje3t9GCHhViYhr wVSJnUdUTEPq4T7Hb2fXq7O/AM8RCf0KZW5kc3RyZWFtCmVuZG9iagoyMjYgMCBvYmogPDwK L0xlbmd0aCA4MzkgICAgICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42rVX S2/bMAy+91f4NhtoXD/ixMFObbKujyUpGncFtu6gxkoiTLYCWV7RXfbXR4lyY2w9tIB9CklT /PgSqZxlRyfnUepM/MkoGjnZxgnj2B+PUmc0ifwwSJwsd767l4vs1otSdzm7m2aXy4X3I7s6 OW8fi+PUH8dOgPoRKsCnMPQnSRJplYHVGcRDPx2j4lSUXhy6SrLHWglZ2XNty4EzCFM/Tid4 ItuxyhsMw4nLWaWAigK3pDS3QiXw99EbgL8Uv69FsedU0fwj8KPIrazShkhUePKsMgh3RDO/ vGjcSETJn5Fi5ZrXOc2R2yOGANtoZi9pRUt9XOlAjOsmfnSdgLtxBD7uKBKXqyUSBaWKldsK ubXgXBjba6I0mBY+MbVrjnuh21iYeoPQ/XKjudR9CJIgCoLkGNg4cIEcWZKU1gzIxqAWWvkt W2t3d0Tmr3m8/HBN6YYa5dgaiYc2AC2p1U5XzTBi03y1/gGdS7JR9vuaYTD6HJZHHDLtY+XD YbsVh/5kOASPQKQl2qOHIBz/332aemm+MyIVwsxogXmEohh3dILOKN+yutBJeAVzgKYQM3kz 5gybhtn47r0UgpQScWODe7c67Rbziljr94xyWpCfJpHy+AC5oFApyaFuVcfQgmDfsAITu2rY /aYV8fVbUEfvQC2J2jVRX2Bp820les2yqGyzz4UknFaHTlrtCSu7Rbsmqqp37KdnboeBXUBh k8QlhZbVkhxivSJ7Unab4mtOantdZ3+8JIDJ8RDEIafyEPZnKgtiptxzt8HP0WpNOXowhRsk ek33v4gXVI9TCfOr0AQt6ZbxHNi+3WhmJITMK9vQFg53U047rvQcm8zO6SmOYthBqtfbdKNh SM1Fc6VsQ2Os5quQqt4S3gNu08RzKCiUtWw3dV9pRmDVQK1+m9U3bjfURV1uiXzuI+AWLpU0 Z4fK9gPKKOy8ZvdKUlZ2FWOg5146dEG6pt3Cth8xBts8W/QF3hxeImYffuu2uLdiiwmOYQEK vX6xi8r37sC3x5rpl4XA6WsTbfdg3h/oHZc2xXYlmeTWL2NS4ijhBw9O6wre9KTbdH9la/iP YPONk1uJqhlglWqtxtcmydGn7OgvzEEo3AplbmRzdHJlYW0KZW5kb2JqCjIzMCAwIG9iaiA8 PAovTGVuZ3RoIDE1MjEgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnja rVdNb9s4EL33V/hWGYgYkRRFKQsssJtNge6hCRrdtntgJNoWYEuGJDcN2h+/MxxKlm01LYq9 WNRoOO9xvjj+M39z/U6ki4xliUgW+WrBpWQ6SRdJJhiP1CIvF/8EfBnyKIqCx9v7h7vlv/nf 1++me6RMmZaLiJQlKcAnHjMZJwJVQq8Typil+miVCxU8Fs1+GUoe2EvT0SIUnKWC05Z8U3XL UMQqyD/iMwmG99J21bq2JUn7JQ8aWu7bZtf0lrT6jSWp2e+3VWGeKlDcVv1S6OCFVExd0gI4 iTRo2h60nEo6qDQrMvLQNttmTbJ1a3Yh8kfKnLNMed/tTAsaOg3aw9Z2tKxqepamN7QClg6u sF1X1WsSdi9db3d+T78xvRcf9iM3L+mBtWlLenuAMw3M4NV4A6X9FPGYXEQcZti+f7y/fn93 C+GQScCl4Pwrv+FZpkgCMFe40kG1oieQAbiRD1pHxSfvUVw7p+NiesimHQzV9HEGeY6guBGQ ibA3BgAXqzjSBBFH4CUM0zOCNyS4bdq2WltwD2li7FDuEEJ+swxVFh/BJ5/oJV+mcWALtLip IWO2o9nZaBPWYUdgHMlqUHB81ZHvBE9P8fQ8nnbHAD+DdSiaoIblCIIe4SKMBJsjRBUjpXQV I2UcdBQsW1SYD7a7cdtgT6RhK5QeVh5uNZ8iBawUFH5OIZRBa/et7WyN/HrTV019RR+6lxpd 35svXuDOinhFU3d9ayr67sk0K3oOJYSKWEKuWhyQqxZkFkZMqdhT86d6OlL7g/TBCnkLLdkv e1N3QO4UbAIQD+WIck+tuaRUbM2h8zw49EN9SqO4oNG5+PSnuE+HatuHlWcDDiyBak/ocbBq /JH3pqXax5fnqt8cWaPROddMOfmolRecWruyra0LS3jVbr+1O+vDhSFk3hg4mienJ/xwn99h mongGz1yqjQRdK5rYyK55I7Q6ZAanS3pOx4Xn+RCWrs64Jnv+JO9VJViWhfitP3MpLbr4UMM KXoxdIJjvrO5mwiMSMGy2LtL+EvoQ9PuwBmfl+4eCqVWR791P3Ev4QnTBIK53TauB7lIogjr Dp9QB+Tyqu5Igv0QJJ8rTFUve95UBQo34Bkl8Dxtc1hv6OMkkvjqXJwm/sxuZb/0V3O+ckVY 9YfeDknYYAl/xvuvw+zCYnFLdOKQuP1F8zD+/QE5mrY/1Z/0cEnh8yHg8XTEiMH9sXNgxlPi B61IX3oZV+NccWk8PObGGURIO09S+dcg6L75/yDG+wjbt4M5deFwMEBNfoSa/Dqq+B4qF7Pj m4CYYaeZlo70pfMXDRZV77KYds/VCu16t0yhM7Z0gdO9Dam0P7R+hsB260SuJzidykvyj1e0 GLedlxusTtnQmNB6dVOWrj35bj8xBYNB7ZvqUDn+lGfXZTleGecZH48Ny/sgO/OBYmk2uI65 4VdFgdn2tq2p84jA3swEElyu+RBJ6OkxtKii2Xl/HdxMASKws6MV3R242rdVXVR7N0XA6+pQ Fz343mHIaFqTqWYaijIaUkpFv+FFci1mxv2IxZADXtWFcgB194gE9/GEnzagEyb6FSY6ZUKK KZG3395+j0ocgW8G3eHYOrCGBih6M+36MNx3KElhOoUROLCUM/BuSPGJPOp+S+iGL/QVObhk RFsk8pNE6C9OqEYRibNJEG5ppM1+JhuEzwZgAFnQuN8Sx2eolQFewmBoSDTADxgzWcMT8GOq Bt88WjsXdQg6H1NrajV8agD/knnIU8UyIH52AOkPQLd9iLk4l8qaQYOZpLJUMIhZU7oNMwSV ZqN6zmZOKVmWjgngihIsjhMcrPFGpNXzBu7OGYwM/vCKMZ3zSxD446pGjI27AcFcbSHdbEsv mN0+GYSOWJKeJYPPfJlGr2S+yphUfJr5N6FLfD5TgwpKLB10azdCgvFJlb2OlSkmMjXFCsPf qcpm3BxrliR6qu3/VgBGOem3JIH/CFtTDCOqkJrF6Vk36A5Ua8NwiK0Ukkj+aJz4yseSenOX v/kPcLo7JwplbmRzdHJlYW0KZW5kb2JqCjI0NCAwIG9iaiA8PAovTGVuZ3RoIDE1ODMgICAg ICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjajVhLj9s2EL7nV7inaNGVVnyI jx4KpM0G2B6SAvGt6UGx5bUAW95IcreL/vnOaEiZopSNLxZJDefxzVP+bf3m7gM3K5tZxdVq vVsxITKtzEpZnrG8WK23q78ScZOyPM+T9/cfHj4+rB8+ffx88/f6j7sP4U0hTKbFKqcrkgi4 DShSR5IKmRntWGcSmLMiTzan41Nb7aumq/+5ETypblJZFElftce6KQ9pB3RwyJJvuDhXDSw3 /uyXuT4815m4KNRVwFBYFTCsvgGXTXULghhz8lNktEr9ZVAts4WDwenGTVJlC+blcK3IjFXe smK0DO0ho1qQVvAiKUGo1XNl8FglX5H2hUhKOmpOTeqp6cWXvMjbqnvKblIDUhzHr2AlT07D 7/YFaNgCNvnUsHeIgAFlEM4W4DziooYFCWM2CfSDXd3RDbAM0ABINFhWbenwK569EGFJR5Hy 8CJQXue5pwPl4e5p+CXl6bze0a1+X10YDp6KLLkIEXyCkJScbguuFsXg+WPVVG3ZVx1dd/R6 wlWNUAxcRfLuAK+bsneRcXghKlTZM1lQdIqIEGKqbDHoqGMdhUyewCtl2w2u6ugm6YmLgKEM 9LwiVpWL1W31JWeyqTEWeKGSzaE8d2792JbHY9kuxBMrFJjGfa5BPHHOp7y4uPCCd44XvcBw wsOSHpTpPW1OuxmzIUO9yAmqXgKCESMsLyzqU9NdhYr+ISpFJAffhnKWChPIsLl4FSwegBWZ QvXJ8ZhYH8olDOqOLC9pe0li3CGy+NK5Im3Ph+o6WIyDpfr3qYSSiNKkYEMEI1MpKKHhEfD2 pZpCebFkMysyK8cwWg9xrSHm2+qphMQku+Bgd2pxUYAG1eZ8OUcNNrvMRYjjNsHo4fOnu4f7 3wkBJjhj/7Fbly9nyrlLEMlEZ0XGfPJ5yAThKS9BjGcI31XoWYeeqzZ18wgMFB+Uf2572pT0 iIJYgehmO6EI4wb3o/ZqTLIfNAGn2J+tKzbnjVPJkIzFLoVvBzTg2e/LnlZTZUygjPHKINha JSeqwdXLKKurjvViTd+Adzl2p3/7zrmq9n5oqNcYkVwFPcs99i4up90yrQ7VEQYL2PRL4alg JhJFkLhSypBV0FRSCEt6j26lvgWbsj8dibHIQ85SZZpJz/mnuewi42PFQH/i0KJB89bxpZAX TGa5tlP8vIKPp/Jw6+K4ndSFMMqWKWYRcB3c7HW4m9MizMJmypqoPuJ4RgifMQPwCJWi1XPd 72n11NbNpn4aSjFUzt0Zh5hND+YsoK4B1cIGsOZEBZ5YRr5Z4CIza5gn+Bl9c8fmRoHFUElg sJ645nl/8u2qbB/PGHs4MoTFeyw204HgMjP4Mu48NatJqNF13uKve8u7fjEzdMZt6DGbzzwG R85jsHIeg1XoMWPBY99zV+qkTBBEBN7evh1g5wsfJbAUY15R7QRcqnKDQO8j6I2H3hUnqk2v uUAGLhCRC9LX0E+dZrEPROQDTNolwCHRhdUTxO0ccTsibpJnP9MT8HYCvI2An2QA0zYzckRx 97jgHFyNabKUAAy+9MSY1BT4rmbpTMVtOnaJnGYDYAy4XBfVMkIUvbKIKIx7eVjcUUyEqC+F pBLFMJ4FUOL2+zHMDBiZ87DkpOmv341elSk2Ei+HkeAZZ3ZmdbFgdZTQSyBInimlwg4HU1UE Ah4RCLh63tcbdNOetjCZHbFLF7ml5qTJdcOzcZf3foZ34iauRw74pY6jP3a53H+IWRxgYRjY 0tsoRKybzixNRpZPTIePKgXd4d30TdSyL38ILEwhgzFC48hBz+lnH2qqxIWKHnNB2vW9a+lB MUhZmEwwe2k6QYNn1xc0DkvIdamiloJmX5XbxVBhMGoU0axuEhwA266nTdTUtJsZNU2W2sQ+ KrRN7iGrqtYHCAmZ1ga4ymw8Grv/FAb+9McDPoIJGAcbThNTQOBiW/sEZ75k4sq3ZzYplrj1 GT5sIL7nmR5N1z/qU5jpY/28pX+qngEHFG+kywAjA3hhE6WAcVXSUJWEbYSRCdqVoYnBiBgj /MtpgGIQe4MfbVSnScWJK8Z8vGaAwQE/mOUvE8zGTTDvZ9+vIuN87KBv7tdv/gdlR1xtCmVu ZHN0cmVhbQplbmRvYmoKMjY0IDAgb2JqIDw8Ci9MZW5ndGggMjAxMCAgICAgIAovRmlsdGVy IC9GbGF0ZURlY29kZQo+PgpzdHJlYW0KeNqdWEtv4zgSvvevyFEGYkZ8ieQCe9jdfiBz6B6g jbnMzEGxGVuALWUkudPB/vmtYlGUZCuZYC8WzUexWI+PX/Hfmw93n4W9ccwVorjZPN5wKZkp 7E3hBOO5vtnsbn7P5GrN8zzPPn76fP/1fnP/7ev31Z+bX+4+T1dKaZmRNzkt0TRBuMmMdZyy lopZE0UzbkA613lW++fVWgmZ/VgVKivbqnw4eup5rvoDtkTW+u5ptZYi89uexvqGviVN6H17 oo7NP66VFNIxnZT8F0gqLOyni3E/WZisP5Q9jVUdfeump6EShd6soyDQnDkdzXTyp5Ww2cNq Db++hflSZs0jfhWI9NQBu2nYbcWzYUMY7XyfpgelZT5zCmfGqkHtzfW5NBPpVGzJ9FwalnMF imtmXZGMbwfjN/UaTVfV5RHMl+vsj1znqLzKVbAtfPZteTqV7bo9Hz0M8yUDc8VyZacW1iLb lscjHBbO7KmDvIQt3Gb7yGAD57L779/u7j/9J5o4iprZmEvB+X/5LcznRfYR1OCqrvqqqdFR IEIyoVG3OKNinsVmWdOMsm8wQiCemzb20GfbnJ6C75pzvaMu1DMujzEBnTsP0eA7kkHxkM+1 BGuSO0eTBi+/TAKkOU4DJMQvzok2pj409JI78ys/ukU/grGyqt5VWzhzu+Atrg2TZuotYa7s gF3BX9eBaTlTUqTld3dfl1KOmTwF5/PBt35BkrBMmFGPKykWojdthEmJWqFHwxc9SjHjAGGc nnujhFMsJJVlBS8GkQuKmyBpuqXG9IePDWau/b7sqx/oUU+9VY1/er/37S1qJihUqnpP403t ScpT2fbV9nxEP0dxkBtr8OEkYnAiZQe1DeOSKYztxQwXBVOcXwaGyGNgwJZdUESBwVDsc9tD 1hkXzqSMBV1jMnmatD2W5y62Y1S+lvS6YFwnW30/b7e+66Jpji+YP7ALdD716+inuGLmp6Ce zmXIS/xuIavPp9Q9mGbd+b/OvoY9wMpaQWbDZvt6nHcAIKZWMwhq6eIQJmvQymjuXVqA3lxK 42HDLmZoQAXI0eYhSPIvQQLh96kCbcn9P3tUDFdUEfzLMPKysip7VzoLHr3W+lNZ0ckkLL6y wFJOW8uc5MkZ3s+hKK1FO0Q90zbLd0eUeKmkiEoOh5ciHH5Jp1wxrcwMZ/iSRpgzTcCe7fbc tpQ5MLV5QoiHW+SF/pePPV6wOD1crNiXvLgetlt0Jk5WAXWF0SGfTURdNEi4mEMiYgPgN7QP dHPB8G4VjCasCdHZt4N7UErKMZSMOdYO62LsAWnBrDCUFWFjX/u2xMNhbs2CMBr6gUInkgik Dd3/cVPo5DU5eK335e6x7PoachWEcDIKfkv67Jtwh0CLsEJZS5coTmn355Mnny8AghJM5Qlc v6CgBcwHbYp0+XxZQuALADZyVJv+BmZIkGIkK4SaGy9mvY10MTdEF3ObDoAZu6Cbkyx3Sbf6 WjfHhHXDOPEkk1V9R9LHiMZ/w/B0T4QIJYoAETjnEUEvTIpYEXpfuXdFLgObe50QztQj6hIU 7MhY4EJWuIsEOSxdzNxAKuk3DDGlnsjSJeTkzLihp6rpSzQYHIfBhehjecTVy8FFXXJWjMp8 qZ8XoMYxOToukjYTCofzEd2Df1JOGcS+p2O5rfBG2C/tCSZSb1kasTEhWxRMNpbIyy65SCwn sNbBciJWA1QKXO9ewKXv0u6/vXZgrcYDe9rB//TbM+IK7ZNotlY20ewwMjJqaYqsOxM7HS5/ FAVEiPEAT2HBYokigJU4Kd9I5lD9Kcvfxc3gTCbRPdQdfI2XvdBohH9uBrCcb1EULLczxAgX 32EossrTIkaurWZKm6v7TUWknPBpJVJdJBUP3oSut9kRB7W0Hkn2kN8CqNevbXNs9tSmmii0 QtRiK5UagnjaMC+oQ3ddlD6z6huFxqQSjWq/j5HoC2O8SUEkgEIuJte9gkrvWCFoK83HYLRQ QKVgxJFJeWdFDEYTg7EjMZI5dxvPHveZnb1gkmlEO0fAgg3s40xSDCueQxnSBGqbIxfmqg2a 4YoJcAWAdhGg3cjhZBZG6G0gjNBnUj7DDmP5nCZMwuR2iW5GfjmNWA8kI3ZeqIbDFWDWJcOU A6cbwj/WlVd+e5/bi9fcfkusHmvF1h98jXQfn2UW3wQ0c7mavQmYaVbBv/HClLrIApWGKUCu hoIhyrguGIQNZ8QPaILe/IkEzUW+LmykTZ7awxxasW3QbFSotH5HnSE8kbU9wjJGvp6+NNAs iDKKJ/zzgOq+zJSZPpasYyaGaN5FLy1wPXytgP2UwmoJNYCKye8Gjt49xcFIGn0sR8ZL5xJG kYaN18fToS07fyevPaQ044Wc4u02vkpYBnXyAP5SvfK4ZA0rFgDUvBE8Ai7+VHYsYYjjwMAS mG8Cy6cHQMRGQXiGPSV9ZpEYa/LwHjiQ+cDvMWVQkwggcZM5eI6hCHclEszmjCRCuRRI2D4C D6XCTNmlUga7MbzMNLywc3zxsu4irnA4xRX+iXG1BBYzDL+MMhuj7H1JPjwCTh9eMb9dER9l gTLFJ1gjL59gTXyCNfQEa+TwBGteeYJVBVNST+tT0nFexAJVSKyKlOB8zpZCz4T/F4o5cXEZ zPl/wNYmAuZYFcfM4dPKA/YX9m8eXPnsxfXDp82H/wEuKfIOCmVuZHN0cmVhbQplbmRvYmoK MjgwIDAgb2JqIDw8Ci9MZW5ndGggMTAyOCAgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+ PgpzdHJlYW0KeNrdVktv4zYQvudX+CgDMSOSkkXtLclmgRRtXMRGgWK3B1miYy1sKaXk3Rjd H78zHFK2/GiRosgCvVhDk5zHN98M52Z2cfVBqEHK0rEYD2aLAZeSJWM1GKeC8TAezIrBxyAa jngYhsH0919uJj9PhyMpZXD98B6FKLi+uXm8++3+eqiiYHY/eZgO/5j9dPVhX6uUiiVyEJK6 MR2ALR4xGY0FHhm5MyMZMZXs7HIRB9Pteih5MAd7PKhXDXyTOMiqwgnzudFfyqwt66o5Nh4O RoIzJTgpfZjM7iiCb+T/Q03LfChUsMyqJ93QxsLUa9pql5qE++nk6v7ulva5FJz/xWnnV1Ov 6ieSmxZ8y0zBTgUK7kjB0shhG7sYb+v186rMqlzvLnGWxrG/JCRTPHKXGHfXOrOAw7OpLUK5 bpranASCKyZVSkquXdh1tajNuqyeKKr9QKxGQMVppOCW2Wr1DrWjg2ECSsEEWkCl2acwBt9i YMttbYzO29XW69LPmdEOWq9Nv+h8g4k7RrGFszx4aWn1dVlSgnpeu0y1NTkEGIUidh45gDkj d7ocGv3npjR6rSvU1zoV9cKnumxImj2i/UtaINnQAmIYQ/ZIt3id7j32SM+eSzpyWr/s6Vfj oASSdNozhxv8X+hPIY8qXdCSSqN3Pumdb54hr0lgEc5LvJvTxkJn7cbYCoAVOG7zLGxlEh/J sy7iXcYiSPEQ6nOPMZf2+kiOmQzTPlHmJ4kSycRRQuNCdepx46nOsPZRJDYkyAZcLjME5Av+ uHvzXXwQvT3kCFjQyjLQm8NjG/DdAmQjhnpNeT9kAvWQipGnoqOPY2LKuFKvICKkB+yf5yJ6 +PjvuXhS/SvoyP9ffIyZCEU/O/mOj4/6M9DRA4GhbU91pxd3xLcyo7Ni1GrPhK/LunHdrtk6 gF5oa5GVq65z9fpZn0RCsCgRb8Qi/gY0+m9ZhNEc3bFMgjbwRl3toMaLHYumnSOLLUo8gHeT BEd2eHTbFoMTSkDziiFC46cYe44GEJQohyjhq4TfsvI7moR1VlXaOAMQa27KOXlQ0J9zYnLX 3g5D33/3fPLsH/O9EnAIReezvmPWiEsmVNTv+3qH0AQyJNFlGEmCjD5Na0o3M8CqN5vAel1b 5ApNy71XQCpFkwntGF/CIDuapcGmcYJlLtqs6Gv5NCJkvMt70BwyEyvapXDHMhxqiGUEQlkd M8n3DNn1DIhg5QB1k1Dl+ktGH3zzGKEpIpZ241Z8ZpiddWkEW7oqmoO05fjWuhqBYHhQdINf s6FH076GK9jK/LPY2GfUef43Vc/Oja4JU37qhNZ7YnS1yPzTwPpjJvfjSJSPRJ6IBBN2NpIf FMjF3eziO8p6nRAKZW5kc3RyZWFtCmVuZG9iagozMDEgMCBvYmogPDwKL0xlbmd0aCAxNDgx ICAgICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42uVXS3PbNhC+51foSM5E MEHwAfaWtM5MenA6tQ7tND0gJBSzoUiVAGN72h/fXSxAURZdp+ceNMRjsVh8++1Db3evrt6l clOxqkiLzW6/4UKwspCbokoZT/LNrtn8FhXxlidJEt3+erOLpYje/BL/vvvx6t3yoBCSlWKT 0ImSBGCLc1bleYoiWy+zFRmTJQnmLAPlPM2jH4Z4K3hUTwfdxzCwyrZD7/Usb0o2Wy6ZkBVp 2N1pOJhmUT2MozbHeJvKaOibtv9M62b6BGtlVHdqMl627elrw+H3tx+u3l9/TxMuUs7/4jT5 aRy6wakSkQFbwbA+5lGjxsbrMvQ9DO7qZos2Oyvd08nK9mPCM40nhIgUnhBZtB+6bojhzL35 7hJR0JAKVnFOGt7E2yxL4JX9fhgP7nWZqGbzcO84kgm1NmYYac3cqa6jIcGgaaLqejgcVd+i UbQLJx9p3Hg9zhcw8L5we/ZO2bUXorpOWw1vy5KKkMVBA2BpxA0RgHHfel2wN+zpq7/iLXp8 pGmLmp5enQC0GnX0zmIQU33zrPyKgZ4auna+qMkVe63sNGryh5MogwR5y3MFRO2d8zSMdj/T jjMAF4LIiUUwObFIBBaxtbBAP5dMShkiIvcRcf1gdW/gNeb5KPi/BMEcAwI4/5TnAmh5UJ6/ KGCmo4dgtK9xn/vrkDQkv8Yxd/SCJSDsWRJU9YurIB6NHad6NSZcrAAu0uMj3bUtIFcjiK3t YPhIO+4hePMDSNSw5denfkF7AS4kt8nARxg5Ps4qlhKaBgvHytmxS3sLsnd2M/jHgIvRvywI nvshK/gp9xTpZe6BffRJ6XIKTJY+oRXVNC4XqI5UfB7V4aD8WcAVD1u4Yl4goA24Iasyl84A rlWmPcbEf5DkHgccjPrPqR1d/uCQffqQmgxtzymQB3RxFICg2cckT+o9i7dFVUUl4xkscD+F KDT+prO3wdw9R9JzVpNneByAX+bRAYUnY2nmX4oTiNYRyOi4ADvKy/dDv7Uay4LqTDjkSYpi dHR2LyxdxBCs3TvUxi+UNUqXIVaMVYEgY1sTTUV2VpdwNyQCTVOEzWifZ3PGNcEWtJesEoK0 33zYXQNmZRn9jR8JaVBhrBpa3DtylU8Qho0Te8pzuN3uEmAUaPu6m8C4y8QKWYzlBQ+djBn2 lii2DTvnnpusuUxbacpkPndDVKiK6qlZyblZReUTBo50rz51OqxqEp9iTunXb7j6Cd9F5FTR OHmwoPjbgdheOLa7V3jTzh6h+1odzdTNeVBA2mmtz9AD3D+GGqj6c//iZa89IaYaQ/Zumd9F NAB78yL6Q8MjQ/2rnmT4nMmqmMsfS7EA5gnwVS9zH3SewxFzGHQKCl72clm8RcZlaXFR/nCt YAIHuacUrNg7Sgg47vU97R7PjMCtwZcIZwR5hE4738ERnztgDTMzrgBZg9QQZPRabL3UQazk ZuonMiYgh3oIRMqqrDg179hN3D76tvrhuSZEMMl9EBaM+2M3w1kjXj2LNRyhQ+C4t6qOwU1f JuSAzKIbNY3kwHdxBQCOh5f7+puB3kqcUv1n7Qm1H4dDYKNPKM+hJhaoZYQa+GsB3L8QEd8T iPjmE0Spqi29BhMtvcYgpukC0xf/p0DqsfrB0qjXymVeH+G4pF1LCQMMbSdNVR5GxGF5auFc Gnty/oREKRdIwOSU/KmkrdZN39BhS+uD38V5GTVnLXGI7f/0B2ZJYI8BqMLCULAUy8HyYgG1 GiLPaOoC5qbRO4KqjjgVOdeNn8vQrGuNJdNEskzQRcXgFzL0w6X1kuX5XAXuIQPqNTWSyeSb tbSEEsRnkjGAZZsC9Nz3/cpBcHkFh7AUZVDRMHt5CdCsTL/B1Jyf9KyZmubVydQYrfTEgsEC VZgh8V3j/EBzl0KdGH0a6LJq235F57m22f9dW3me5GC8DPfab7RrJhPaCGTCO3iCHTCcf3W9 e/UPpldl6AplbmRzdHJlYW0KZW5kb2JqCjMxMCAwIG9iaiA8PAovTGVuZ3RoIDE1OTYgICAg ICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjatVhLj9s2EL7nV/gooyuGD1Ek U/SQFgmQHtqiaxQtmh60ltYrwJZdSc4myJ/vDIeSLJvrJEhzWfMxHM7j4zej/XH17PlraReO uVzmi9X9QijFTG4XuZNMcL1YlYu/k3yZCs55cvvXL6ulVcnLP5f/rH5+/vr0oFKWGbXgdMKi wCJV0jIpMhhkzBraunvLtaDzip/enDHlxKBgw/rLO4RjeS4HkceHqq0iiqRjWT7qudTimOTj PXW3TJVzSf9Q4cAmxV3Xt8W6p+XuQ7OUNumL9zS/37dBjOabttjtipYm7XFb3SzTTOikaMqY ZUJCOOxwd/+Ztv3W7rf7DUVUGsdMJhepEMzpkJ++et/DxUqpBOzzckIxaSHwEDIng9j6qciT bLh1/UTkufh05C2z3I2KLtVYpvXcPTCZQq+y09DD8iz0sHu/FImPPkqSyHpbHLvqJqw1IBCL ujASxupK1KNmhah73ZEASw25NPk8wuU1bA8XNPU2EmDN8gn9N2eRqXaHHoPxgda3ddcz0jF7 vGnGmXYWjANwAM68rhUpsYDd7Xa/lCZ5rDFU3jVA+PFumYJqiiVJgrdVU3Y3JPFY9w806gdV 3cGfqdb1Wy6yqqRVn6/jDq9AnSapWlSR8enget+2VTi9b8q6IVjzOZ7f3P76/M2rn8hZoaQQ HwUFgqw1o7UiGeLgTuLAMT3MujzQFxNMgazQPPlj6fKkaOvibosm2Sxpil2FKQdeW++bpZLJ O/xT+WFfw5IXo5cPQn3V7uqm2KZd9e+xatZw+CKb6I/FlIcMeEwJl6x+p99ge1h9t9SjTWEJ jYpiGYg00yO73fIIkjjQ3wmSLpVo5sykQjyh4hSLUiaMsZguyZnUI3fcxt5WNhrT78m7tjoA Cip636h+QAjsxcOLz4wDBZk5UCCOJRIuvP4u/Lab4w41m6QPS8BWDY0O7Z6wXnUdQs8vjhSO E6TwcGzfzo9reBYH4PUa3g6d1f5sGkMwKTQ2aUE66IRZTS7vaUYg7tgytcYkb/AW+O09WnDU 7PsCAQgZ0GCIDxGuA170hJdITjSH568+CZJrGDHMTiXhczCihXoSIxnjubuCERhZPZaNoqHw BA4JnQQUKWPEPMpttSna0tNP5jwEFDzxgqYDfmi2vw+rEFJ6e4hrrYjdIg8tdwyY52oMFXMT tmeY9uDC6wjWYFTd1H1dbGdGeKObcpIkoFvFOHRSM09PKSJirTJQg/KrEebWXTHVmmCqtQlS euNNhVVvKiA05wZ4zBM8Ri7jIqnvZwdnuATURxsEKEw8N6OhdSSqUCpF3NSO7BsjJa1kYMh5 L3TGH0QrNdK4oL4Nppv6HaqsGpp6LwPRBSays2cWZT54I0pPvnwXeSUIfTcm5rHebuMMKNx0 b1vtirpJg48KfFODj6GgUc6UijqLrdA9bJDEoWi7UGXPEa5zoObsai7gzdmp6wt9gKL264Q5 cQ2Zc6jF+YIyIn1TIgxnAoIAvSyzmRpqssSKLPXUZxnt+ywa0buAQVn0RaTVOa+w4LnMco/d tutpAr4XYOPhgaZIAfhLBIuj897HSzX0O/YgOBl7EJzQaZPs9p6gyrEHws0ibPpudei3uhfR FkECgQhyYAiC1DYEAUf+Ju0w3jidkowz745GuBRlSpyGxWYXGgvcenyo14iwB5qWFVSUcBoa VS58t+pvKOu2WvfhUeADl0Z5GTnI2DHdkXLny2ZoWilzAA88ruj41KyH5trTMcjASpuWlacc aiPVSZUujy2Wx89o8OBjNTR4I5wste1PY8e6WYOsYs0pfYlctMgZ8cnUoqsrPevwQbEjt8qT nllR0cKvGwKLvQ6WM7RkPPjoR75t4BrRgtMJLTjDgOPvlGgorSnyh6dz4L2Q3hRzOaiedn1W cZGCEG16vDyLNROK5VApU8dUHmQPwQUth1ePox8giZLz5HCycREM2GIGSsTs7pfh2/FFJN9B PtAYfEmlhluOg0tTz1w6RCxUFn6HOFaDQLujkX87wFvf0oUSPtHT3HIF37up4DlWj6/wZeRx XKT0X/j0pWnJv9SnDfmEPON9wmrwFT4Nb/XCkQy7sW+ZnLV3xEHDvkZHjOJf5cj3/7uB4f8P z16tnv0HqVoPBAplbmRzdHJlYW0KZW5kb2JqCjIwMyAwIG9iaiA8PAovVHlwZSAvT2JqU3Rt Ci9OIDEwMAovRmlyc3QgODU2Ci9MZW5ndGggMTUxMSAgICAgIAovRmlsdGVyIC9GbGF0ZURl Y29kZQo+PgpzdHJlYW0KeNqtWdtOHEcQfZ+v6Ef7pafr1hcJWfKNJJIjWcYPSRAPa7xxUNAu WpbI+fuc2sUJLEPcCwjQzNScrq46VV1dPXDikAKnHMQvJRgFphQq40KBkl85kBiu+HMU5cBF gwShFkqQrAOTBE0tMFswrriWkFkCVORc8KihQA1zCzW5GgotpQCNTRWPHFrFaMGIJFAnipvi EoMOjMZMRNkFgZh8SMaNuQBvJEGi0CfqNlTcNJcAbLCMFZ5krgMr1JUCQxTDqzuiBTcZTitG teQSKGxOg0Fha5D4Q1KXYGSqLoFSEpdgGio2sMErZrBjeM0ZT1bcT5dU9wMSZTcXFmZx7ZBk vM7Ol1tQQOpmZHM9GXqaUwv+JDm3ueLGJwQPklxPSYiBEwgihJzBQkGcPYaTws5gQZyEdRsy cQqLBVGC5oKoq3OYAbYEozBAss9Voac4q5i8gBrx5wZVGFsFBiNBpFYMwZ80d6FCfysycDXk Arkk48Z9rSUoJZdU3Dh5sFWpQdJS0A0xjXADILwPCotxg5yS4hINqswDN2hWEIOYqyG3EGA1 J7xAb07kROEGxoO6oNVTrmHu5lNiNkvuAnLaPNUQegPpA8JrwhAidwVsgxFTz1zBFdpdZFAO bs3UVwpeWPNJgMwwFdEIVsRpAqaKDAcHYTwK4w/Lj8swvgnPLuen67PlIrbn4cWL4dnbv2bn V7NP5/Pw+9XidL1cXT6/dwil7Zh3yy9np7Pz8PbrxWxxiTd3hhz7Uk3hQxgPz9YnPujgYBg/ /n0xD+P72Zf5ML5eLtbzxfoy+BoCchg/zC+XV6vTuYtkK/p5/vls9mr5NRwnCDJ0lsYnA1Ss MBbZvcVdq7857S+//oalx7EgVUuyiOW0uDo/P7kfKxssakT0bOgCW+Lo5neBRXNsiN0t8CFY CM7doZc0KteceTlA2m4f2B/a9YMXtPQNhUXB9A3lb7bTQvf4frU8PZqvwzH4fnMYxo/zr+vw 77TTgcBEu4FgfWggUH67A3Ebex2IQpGwou+h64a7t0m5xdYNhh5KiqS7pNQHk9L2IKXtkZ1T YMstFurUbNoiS69mblHgbh84AYxq2gVWhYOpE4w6GnOjTjDo1trpIFWOuXY6SJZjqfnJMhVv vJn4Vgu8z5H6qBzWuxVWea8cHl8uFkuoOt50MG7LzpSb98N4dPVpvXl+d7b4cxhfLVef56uN ajoZfxx/Gl8f+/B04sacwgtRkIjdnchiVd/zJSr2Z+IS0Z8B9zLsbkcXs9Xsy2p28UeUmPDD vNmWboRJpX+d3cZ+Z51NgoWioA/oAhs0p6nVMAmG5sKdYG0UW68ZahJNtBOcNHob1gWWnKNK J5ZrTNwZE/RnEf1tJ9g41tLJHDa+2Hr9o2xIuP0X+z1L+kn2qHx3fecHr++8NdnPAU+4zlUV u8CmbY2EE5Nie69IQEO6pEaT6/zy6pP/XjefWJEoDTdX+iMrj6AeoCVH1xWx7SBxOdrm0NZQ gaTDoooGJdJu7cl71J68T+3J+9SeKbCVFq11moFzB8ygPvC9tWcS7CGfKhGTYMrRF04X2DeT VLQTjKqWc6fNOF3Hmjttxgk9+hm2C0yGemJPWE9kc35/VD2pd3ve8uCet+zR85Z9et5JMBZz I+oDW22xknSCkQGi2gnGsqyFO8FIca2dbGhrsbVOzVpSzFY6wVLRbPRq5oR2rZMN7x/E+rBS kBnUSYaYl+xezYI8ss48EviXc6d/3LwId2Ktxto6/aPmm16nf2QIyW6w9zuGPLBeSKI79aK1 rnrhn0t3+o+Wt/1HK9fX+qTnDWQBdnf/rrcJsNj2wKlqMVO7d9f/rwl5whaEC0IHphRH5OKf U2uNhiApo+9P3zXGbjcfj7OFmjfBIITRoPnXWnIb0BZ5m8Tle7bkKDuNkH8A7S38O9j/L/yT YEP3lic6kEmwYM817sMiD1FDpROc0WFZp39saJomasw0GMRR7SSD5JHfzZ74A4T/72GnQEiq exWImx53NBT/AGMp/4oKZW5kc3RyZWFtCmVuZG9iagozMTkgMCBvYmogPDwKL0xlbmd0aCAx Mjc2ICAgICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42tVXX2/bNhB/z6fw Iw1UjEhaEmVgA7osGbqHtmgMrMW6B0aibWGy5Ily46D98LvjUY4dK1setoe+WMe74/H+8cfz T4uLyxupJznPU5lOFsuJUIpnqZ6kueQiTiaLcvI7S6eRiOOY3X56u5hqxV5/nP6x+PXy5nij UppnahLTjpwUZH6kEQWVSM24zoJlDsdwAfZFErOfq84WffVlqiSzLpg4PiSeRFLxXNDm24dm KjXrDewpTF0/oG+vptFMKtavbWeBjBNmBqJp8ZuyAnetTbOCM7zgnne859MoTWP25vbd5Zvr KxIIJYX4KmjxvmvrdkW0601Tmq58hU6iW0LwPAnpuq/6Napp9IIIuy/stq/ahpbt8om83U4j mTHbmb7tiOWG6Pa0/hwncRH2pVzBUniXc3Yz1TM2bDuYdHZjyEJVEAfizth6KhiGDilnbsx7 Z0GmwGLGZ1wiqby/+O3XlSPh4gMn1m9r29gvU+88ccqhinC2Deq+Big0220NxbqrwyF9S/ym baLedpuqMbWDGqo89aEcO5iSg8eqEJiKWdWUEBWGCbFhAjE0LzkkDeiMC8VnmDfskQR8CUqm W+02lnIVWG3Y02O6KFeYVpmfRSdYsObW0IK06w6KCdKx7O6cLUGaa1ZXf3obuMrYtrMl5KW3 JISIcNV2jtZLLC/q+fIi57DBZwtasrNuV/dVsyLFZdduSNPut9CsBwFYcKOunZSAn99wVM94 rhSpv323uAaLqWbf8JOzhXcN1k9S5A2p+BhkYs3jRA5gUT40ZlMVl1iXRCZsg3Esq9peCmKA +0SUlSvapq9Wu3bnQHrmo5SSq5keLGPbYaQAPTGfnYZ70olKUSeq2ZP2QsljMfgIrCEmJVzn 6TGiyYBoV7WBiv87lPnc4VlF20Eht76B2lA15LsdNVXhDZKnVRM8HzYfsAsXB+zyqo6Ym9Zb KavPsZhhJyLTOFJatnXdYtHu3XykapnmWqTgtuBKktuDN1gbzBlRP0DwMkUsAlaoqYUSnlUr SjJI3JO6vL5zfQeQPh9JWtAP1cX7rnOdA/Ey0++7qu2qHkN8mEMiBDgmZCzGUOYKs4+IPcdo 4PE7lGjbVU1RbYfuWO6awoM2phBwY6Td05SniXp0+8xbzZNEDPKhVk3bjxiT2dEzi/A2jxDS xi5DJGMJ9/VJEr6bwKLoRx+ZHIsM7o6GUiEizbL8BJEApBGRAIdvTy6NI1nGE5J6VCFOSpxy AHu8HUA3lvhruhW0ODEWkL5oN0F1a7qeRPiESP+EWGKUpjd3xln+QjSIs6MbSUAAw8sZEICa v9XZcKv9gyBkGENQTgCBm7fB38f7D2L/8u02+Bvi6YKJw8YRWBp5QZ7HH/I6C17PXwqjKsDo L53ZbExHI0O3q0dflRF8Wg37EIJw3whUaQnx/c9ItYKeEJnMJVLfE1aNuQtTVKbl0aUee+B5 LPSzlxm8VxKQIT/p+meKha9JrJX4x2L+5wXDeqUaDh0xfWg0iEGkJ9gD89U3+tyedDzxRExf Dw1+FKscUYsP9C0tXszGwwtMwAg8mQcekBniHdKAPEoDUjgM4Hf4l+Lt230fpKOjPk2GHgYg kRVNwC2tTENf+9cOJrkkZabGERmMEv+AP0Dfw38AoobTlS/MPuh64IcvzKyAj8N5fqZVckaQ ux+wt9j5/0mCeZy8uF5c/A07RsQTCmVuZHN0cmVhbQplbmRvYmoKMzI3IDAgb2JqIDw8Ci9M ZW5ndGggMTUwMCAgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+PgpzdHJlYW0KeNqtV0tz 2zYQvutX8BZqakLEgy/PtDOO42TSSWS3Uk9JDjQJS5yRSJWkYnuaH99dLChRNtT20Ivw4AJY fPvth9Xb5WT2XqRexrJYxN7yweNSsiROvTgTjIeRtyy9L34yDXgYhv6nq/mHP66mIvU/3EwD KZV/fTu/vrlbLnAk/av5O+osbj5fzZcfrxfTb8tfZ+/HB0g8QGVeSFvzkExENrIJBqNAKpYm ZBkz8IgpcIVHob/Q26po6qkUfq+f+o52keFolyRlKY+9QHAmBe3R0SpcMQ0iEcHadku9n6eB SIeZV14HUcLSTHlwOMsiC8vVfde3edFf2iuMF1h7e8uuQLeVjLH33za/a6umrXoE+/kSfOPg Gxchx+Ww7YntdVOXVV81NRiCTTjcExfTXTFWdFcMT9VRm9OHTdX1DvwGr4RkGednAATYIhWF Z5D933FEGNOU+51j6yHePGEqyWjB/HYJTFVp5P+gZrG/BzATv9jk+07THHDQtM0Dtf0aAcLe 8vcLBzA8TpjkB6fKYoVGk5vl5M8Jh9nQ455EL7xIxSyDLCq2ky/fQq+ETxA8JrPUezSGW08y LlPobbzF5LfJW0zIk8OkCFkEFrhVMiRku9/omXIkF1A9FYNjFxgJ6X8NuWohwuZGdG/zRfil xm+1trddN1NA5hEHCriBRAPepYxH4jRgr+ileORXNbU5Nas2327zlgboL/aUoR7O6KddXpe6 pNHjWtvVd22zaVZkO9rbrtq1epe3w6qHpnVlg37SxR6zgVk+xR59FggRGAvgVJoOqiKRU0DY 5TRTPpDWQS08IIWo0ZKbp17XJWVQv9aUQ83O0Eq3eQ9eUb7l9xtNZsgsbDvDvvTAPpwDD5hC XTPbWMOPi9vZx5trGnApOP+Lk0Vuc/eh2WwajMBjd+ngKLAmE+JE/KyiPFuNWOx0UT1UurXj 2x05/zWMwg5+uBuHEdAcHgiXboB2Z+lAwqcHOFBJkIg3P964slaxRBh8w8FRSlogPiYtNkuD suAvUHZkZhixo1rgTYLgF7zLTDiSJWYxHyeLhGTpdiZAAA2mBjINHUBuY/sqfjB3jB8MTPyg 7QePh0CaZOJKsOiQTLFF8RhdeaA/RrrrIUPytrw4FW04uDylgiWhhPSo6qLa5RtLkX1dHNg4 MOuQlzjAvOxGaaKYVPGQJlIAlqMKAJPkU16v9vkKz0tATJq60Lu+o1FukgI6IA85vMzc76ui c2h6aGiZCvumUHRlOlAaJAjw5r6BIXPkDITHpGB3QRaPVb+mXj9s5QgjzBrF2m/xiHtLJNxC hceFRdO22q7GV7VeuSTmfHp2L94X7l/+kwpZSUmorhFH/UMcjf69ro6sGo3WMmGrondVq4u+ +o5lkf5XIbuCY6LMr5s6wNe6qg1xYqR7WRVWyMBgm5sqhL7lOwttbr/mBtVnkPBWk0m/znv7 jRqQbbOhdm5fwA4OjE8OEvBaYRJia2KFndd8EZDB5YABrnVqI1cJC+PD8/1c5/CczfgFFS7b /aYHXYQH1qGAgDIsTUeiIZQyzHdIMOhCnByOqTqsj6rVvtl3rq2hfFFw98PORjFkrBg8+qfA 2LR3cVyRVJ15aixVji+SOmrHeUrftQBug1TeYOeFOjE3Q0UEdVt8ZOhQt384yA/UGEZ+zrI0 PdJUxXxUUMDAFhTQo6oWe6YAgfZQQpiv6LcpI2CEDwL9jZDmgTOTusZ3uqNBt6/ss40jws5+ 6htqCVbtpGxZ6qEwaF7gW+awcd5pNiwcl9VGAhVPX+QizoySBYfz5Ww2x25C5SpM9ecXvzKx IAaIX+C6wlrnproCKNb5ZkPduumpM9zdDOym/OTc4MRfbj3gVBWOgwgD/FPk2zISYmYnmxr+ DeyL/sKJsHljhsMlFyfawvmJtsBXgOszfRj0CSbtjHlQ0YaGP9FI0MjeHmfM7eX49mcccPg7 dmeUdTkN7/fVpg+GjB3fBG3bE9tiDBTOH4Biw7+PvwE2tw5BCmVuZHN0cmVhbQplbmRvYmoK MzMyIDAgb2JqIDw8Ci9MZW5ndGggMTM3MSAgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+ PgpzdHJlYW0KeNqlVktv4zYQvu+v8FFGI0UUqVcPBdIkG2zReBeNetoNCtpibHVtySXlbALs j+8Mh5IlR2la9CRqHpwZzjcf+XPx7vx9lM3yIE+iZFY8zBjnQZpksySPAhbGs6KcffbSuc/C MPR+vVjc/H4xjzLv5nrucy68y4+Ly+tPxR3+ce9icUWLu+vbi0Xx4fJufl/8cv5+GIBjAJHP QtqaMTSZ+Z3Y5yLIUtJdHXRVr2HHPPH2Wu2llm3V1CR4aDQt1JNaHY7ydqNo8Uk326bznjNP N3MfMl8pYzrXFThFqfeIFSndGpKutdztpDPRh62yGYYzn7Egj92RtErvwF5E3Gsb/Io+IMr2 fbTyoJUzbB6cA6aIHqVs5VIaFcz9lAnvTq2oDtSx8NSpMqQpfiNJqb6ETNTd7nIqzVWjIfze 5tLUpapXEDpKIm8Jn9RTLdb/zdavatQwKh8a7uERoMAegXVyReNS1nCkJa3NoYI6OqPVVh6M cmaYPe4h6Xd8LFMJVzUhiNrIh2dkoQQgIvMIwQTOURpkWe5wGsSQOIti78p5Oad8AEAMmAV8 4BMw9IpD6CCCjDCXCUyaZ/wIJFi36qklJeEPREf8vcD6SagP2Moww31FmB7xAqIec6igA0fx t6rdkKxuah+Pv6rllnRVXVYr2TbOaVGcny+cxpCIZkaVJMWEJw68T/8MzUJobIl1pVR9Oqg+ da2lNaWGKwhjM1H+ICVUQEq3Z856o7R1TLxbkmCS1miUVEJJ/QC6hHsReqeMbOFfbrWS5TP+ CA9Ka0mMIMMvYQZU0CQFYC9J3CHIbWazA/FjtVJuZfGPkNdGWqsQ96ppM7crNBrGjcOI9kGn aMFOKQJ4TFgA5Ie5i83FiLPA1mzkdkvLpZ0Ph/1qt9+qHSQColYe7UtFE41FkvK16eB5kAne IZ1xNx43PcWlsYWbeX1Q8qN3PyjFHImX0GjcsBBu+Aip5u2ZGLIOMU7YMw5zNEWkUVbKnOF/ DFTm9I3jqF2jFfkeQxPxdHJoBzChsoTfqpKESzy8Z7LsyQ14rdLQ5+3zNKO6dlS1BVgcEWfB d1sZe4fErBc1ulSalnhNoKoEK6CYQ2U2TrFRO1o96GZHRqNDhOshhsksLBDBTO32LSX+ysXk SILHnlF/HYj0BeDpSxiH5Jxi1SjCnEHMyNwyB0jdhWFMBbSOt5PIvMWor9bcHi4u8HAB3naG jIOk5R3Ya0nRJqZ8Baine8MyPp5/0NlFANwsI7vFxwKfG2HifcdPakGDvzSaIOiaQuwMGksJ IZFYOLzSHb2eObyPnj45D+KIdS+Tf8Cw4FBEb3hEFmRAIdrmq+WU2ozTMc2Obj0/4mkg0mjc u60EXMg1MpWAScKReplmkgRcdLHfGLZEBGmWvJKoiEWPD2xo7B4bMaf8U8of/xE4RnV59S8K fK8QecKsgOKMamOcBQwSGNV2Ra+VClnMUSQPIk5ER+RhRSxFOAbTfBTFQZYnQ0LqKen6SSJb ThJOBHkwB6YL7ARQruVWWq8Ru9K+eRxIIkSUoUElG+ogx/eq1Q8QxYlB8eIIc7yWzNHL7bZW tcK7oJPblvlT42sn194Jx87gCdn4x3cRx+t8R8XycAhiEeRCjEv+DE6QXQzEXzZrt9KH2txP ZTBpvZT6638xr1r1pnkNF7BbwqPhRaBxF/2pwrq7do0oRLh2dyiS44//8nRgIFqiSIzv+z+5 7JpD/cd+o+nhgJJHpZdOEkyVNtCf7IWaSZdBkBMXeNxUq21/VGD3vzaQ5Z92WF/f0E2VczvZ DLt2P5lAv/GpB3b3/tWcT60BOmT87rp49zeo7+NNCmVuZHN0cmVhbQplbmRvYmoKMzQxIDAg b2JqIDw8Ci9MZW5ndGggMTU1MyAgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+PgpzdHJl YW0KeNqdV0uTm0YQvutXcERVZsy8gMkhVdr1eu1Usk68ymntA0Yji7IAGVDWW5Ufn+55IJDw xslFmkdPT/fX3d80V+vFy9csCxRRCUuC9TagnJM0yYJEMUJjGaw3wUOYLiMax3H46+ru9s/V kmXh7c0y4lyE1+/urm9+X9/jjIeru1d2cH/z2+pu/fb6fvlx/cvL1+MLOF4gVBBb1ZRZER6P ZCJOM5LB7REXJEutZN0c62UkmQyj6Gc7eCjy/iNBBaAuopQo6Sz+S7efzoXbY939uPSnvP3y X8TLXjvxqb8RFUQJEUQMNNDManijW72MBBNhvzMDGXZPFQILiuG32XczsGSUCEk9cp2ue10X +oW1wBgFZxY368XXBUrFAQ1YpkicskAqRRI4W1SLh49xsIFNcItwlQWPRrQKOKE8g9E+uF/8 sbjCzJjcziAjGDWahGTWhsOuzbtzC6b+JwlRajBa9wVZRilNw42um975Xjd11Ou2Kut8370w kEeMSSI4nyL/uAPg8jlseErATXcLRtoZVZcDQpAsl+YBpmmaTM0TQoabJQ3BOhrWMDCGYroP RrpAMzWJNAVoVAK2S5LBv60dgJUw0ERlHL5eqiRs2gosiXgmwmaL/zz83OZVlbd20h73eLHu Lq3FRMwIz5TVvbLVdjoNJsJpbZd3AJQZmBzDva25+qcZ+HySggeKOctv37/R+eYs0W/fXzWb p+fy3KgYx2vmOgZOsIED3EWXVEHB1SGoEEWmpHWGZdJ7HaHD0c5YissfYhkXW4wi1NEr/SGm oi77sqntNmS5BBHqtBW5W7d151S3+rEte6guvwdbT3M8JRVJKZ3mqEXoB7wRsQzLHmOkGHgD eZZXGHjnlE/ACE1Lw8YYCIpBnJ68TOjYS8zV2kqAowIddTJrkwOwbpHCUV67Qe/3HPn4m0wd OrMnLpq0TeJR4sEE49DZYY7shoOiqbu+PRa9xqsSGm7RzaZy1TN5eFIOvDJU4lBpl0AKQUQ2 CKIXM9qA7gybuadjxC+XCiGKmVSjyPAkDcu62B83Zf3Z0ZFKgY7UFIfuYLOmKPM9jug5k8Ex C++MhVAvcSr8rQOUqAVgw5Tr22Y/LFgcZ6xH1pEn4EzmpzbeePSyTKw/8Awnnl1dwZcYvhTC hwioiS8ISqqAuuxWbgUvJDKgmP2+QeMfl2CFDbvyFTRohz9/Lur01yO+Y1YSEzufgYuzGMb8 9PhVZeQS1O1MIuMR1N9mOJ9jazOuRCTJTjuSNITNsXTmiDKisC+zKc3dNfXaufN9ukTyZhx6 gIsz7n26B5/AbmPz/yJdF8a32zmCB5DU4PPY4MsXmwI8QzmYpJA25PB3KnmYTPLULdg8xWnm 2A3WkaC4tssq7Hb53h0YaBcnZXXY60pbnbkLb4rBOqNYS+cYtY12JVhv3LnZjs2xXzw2BGaG xxSm5CVgSUaSZEBhHJs5wARNvejjrizQkp3VbfBTWCu9vwxeeTXOf2T5r8dxw1GYBsAKerTg 6AktVIxoOZAoj0kMnDhxekDSwyUcXOkcXCY16RiuhJ0F2C54IjLzfmdaGRhVua9xmJwMhcmx szTAgFPtfz6WaoxFG3fSPR0MTO2KtnSKzs53R7te7HNQPhdwKFJhOjkRrpzvujr03kTInLO3 zqyVrmFq9aHVnYuGoZGNP+QViDB3KXimtx+IAIU8uf1rzyWf6bkenv+ukETF3NX1u/WNNeNv e//aNGAT5+pmxhaVEZEMjxGSMNyOHPiSzvAnDPkgjE2l1bxtXA86aki57Qvm+2WemS+Qy36Z u37Zld2Ss4HKz3tgK0+oO/HKpM3BpPxc+zz+ClvNPssklpNn5tmnREpoZNM5rky+88TFBl37 2oAofBv4fpQnyYQ8QPT0mnZOoNOHvM1tQhr+hNp58rcaLoAPLp6dv4YQDvPOMf8xwCaPt10x dMjpScT1iqOt3E5HAWbDFwczngF7dYa9tD0BoUlcH4rVuPa6zdXRXO2aJs2kjr1VeIP4RTzM bpV/WTq2AZHjwZWnnUIhY3P8baxw9EXU6iova+zyJsU7RIz4T+p/ANOYXhQKZW5kc3RyZWFt CmVuZG9iagozNDggMCBvYmogPDwKL0xlbmd0aCAxODU0ICAgICAgCi9GaWx0ZXIgL0ZsYXRl RGVjb2RlCj4+CnN0cmVhbQp42p1YbW/bNhD+3l/hjzIQsXzRa4ENyLq06LClA+xhLdpgUGQm FmpLnigtKdAfvzseKUu2ugT7YpNH8nh87l0/rV+8fCOzRc7yRCaL9d1CKMXSJFskuWSCx4v1 ZvEpSJeh4JwHv15ev/3jcimz4O3VMlQqCl6/v3599ft6hTMVXF7/TIPV1W+X1+t3r1fLm/Uv L9+ML1B4QZQvOLEWirbIfLQn9JtCFbEsdUIwoZhiEmQRMQ+uHov9YafN+Q18EUrBcuHOXRrT 7/UyjJI8eEDZ3bjWekOjtkc+dtg1TpwJJiJlSZR6kXfNMgQ2zZew2Opicy5ADNAJv7up3X1N 665AGawgjb/zy1Kmga69DNuiG4nb9Dsn567otGNyCyLAEbx7EYokZ2mcwgCeHSd0b9nU+O4N KaTWjx2Do1EcrLeVIWJJrHF4a5+kSalFWTaAbWW2eliG1a807rZu212zAyjwMVV9T2v3bbHf Fy2tW1hfETyKj/GMWB5FIC6QZOxBbb78ZfH8zGP+AX7ExTKMZRx8+nAD/FDlYfjjQGL26dy9 eZ6JY/Bxwuzi4w0NR9yAxs7VGM7J+edW14AjT4J+KQIAUgTWjHgMeLS0cihaU9WwfA+3RjIK Di2ZTKk3fVvsdl+XWRS4NYDTaDo3oIfcvFECvSxqog1aQircABOwiEOrO72Z4OFsoDAXpJdW mwOdLbvqH+sEKIQKLrwloLGAGi+cBdSbQdn1wKJr2uMWa9e40LRuq7PrFO3aEnQLLIudmdXV Zd0Ac3dWkzMT530xsraRYaqgoA1mDxieGZyykNGOh6rbEs3ofQWvI6geu+ea42HbFkYPVvPQ tJtTs6Et8mI8U881o8u7zr8d1AcGU3RVUzu/AstpnA/pR132fgnV4X0XQUo9SM66yt6xrOoT V90UXXFbGA+j4+EcOA0eDHsKl2SCC7rXirunr9C/XoVWyZLDXjnVtANqekaQU84YhkPSbvcK WMnvbl/Rjh9GmqLhN3901rdVzLIkgUwRs5wrYnX9fn218ndIBSnE5Sjw8hzS3zvrhgL8kTyW B80dUcjj74lojW8GTglROhsSn0NyJkEmLBHKb8MoIVKrMrzINDbwN06SwsxcFCcMjkzvkef3 RJwlXPpt6PHnrECdPJpyUk9x2lr3pSBD+UnJiPFETfVm+rLUxtz1GA7BfDMLIsZSHFvLlVka YCZqNUQhg3ELU54l+9gSGv13r+tS0zE0mqo+9B1NIYV1LvjLPD0ytafDuYgJLOdUl7A0H3Cw JnYGArwxUgMI1k1jic79mYvo0SbSWGF9YenkmUBowdk1ZpF9UdUVTGwqjdX5C+dcVArOVBr/ H8lcZI99lAASStqajpQm04RxdaI0LxQaYWofg/9DjMbJse7AGUYimWY2pvUtBXycH2DufQbn hY2H8w9M82c6zfBGrHRkApUOGmFvSJS74/3p4LD01CgFjxHTpx6LpNp0LSiHaqFovhY6STNs Jopg4ZopCVLZMxI5l/rQmZmKM4uYiIYYMPUBlw3ljA+cwSKijIkjfFgGsJnrwELyLD7usrZI Nd3oGgdWnDIlT4rN70sQCXD9gXXRopXEMQTODs0PhyUkc72ZkSqBqjsfjnq3hhPo1rM3Zelz npoCwRfnffcU15jJqWGJzJXQeMj/7yuzg7KTyiOZcu8TZdEbFwUlBNMYBJxamb0civzaRsE4 t/ZWbXRraIFiFgwo6eAOTDpIGZIOTno/zLFKQoorjazIOVpdqyfrI1+OKVTSstlidTWTaY+l WCqGYK1SGTy02FvEcLZu6nAo+7BQzISrJeFIRyLYE5Ut4IA4YiptfQc0MsCNLZCQ6molYkG0 sf+eiGk6fbABICVXk5l0tTI5T2txBMFKDLuAqs0OUKzrWmMZZmGEM0Y7dwa7NkTyro+n9eMB XuZ2C4+2sczggQ7ujEL9jJhzTs3zucSGZBuNcHnrCN5ycYy6Q7BFNOyr7uumtfrh+TFiwRjS Ls62NKMGs8VnTEOWi1kKIEpzNVgPvIxcGGhokFbHWPJsbQ5zyQxXyW5zNUQTbIfc0kzuBrJ1 pVweTw4IhbNqPsKWzfIU6K0x8FlpVLHKk0Cze0cjHLNxDUwBLxv3FBn1FO6MAwGprvr2XTjQ oGeakxIzx25oj8+kdL3Uthm+CWhnpL4RM5NEcy7vtHmCfsfxMgTA87qduruYbXE+PbstfthW g139ZwtHbjP6rjA0MSd9kKJ+ms5YdWIjhK2Ra5O65tUzm5a6O+9XaAhdC5HOm4hvK36DG5+L gPusAlXnOAjOSJgpxrMht9fdXNaGDKuOmQyQ8cHIXYEfBPBf7w+dRzobh3ScjSII1LwIQXkH ppzwDL+lQYXhSmNsJG57V/blUArx5DRUuRLI942+kkI1gM78hxDv5KQdZ7jFl+Xxy9JhV5TO EL7XJYEA4GxPVrQyOrYu5viNy19Ol9ZWeS+u1i/+BQ2be04KZW5kc3RyZWFtCmVuZG9iagoz NTUgMCBvYmogPDwKL0xlbmd0aCAxODQ3ICAgICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+ CnN0cmVhbQp42pVYS4/bNhC+51e4NxmIaJGiXi1QwN1ugi0aJ8i6pyQotBbXFmBLhiRnN+if 7wxnKEu2skguFjkkh/P4OA//sX61eKPSWSayWMWz9eNMhqFI4nQWZ0rIIJqti9knL5n7MggC 7+/l6u0/y7lKvbe3cz8MtXfzfnVz+2F9j7PQW67+pMH97bvlan13cz//sv5r8WZ4QYgX6GwW EGupccvMd2Q/1CJNaE3DtWmaencdcE0Tr93Vp31B44e5D2IYnKReVXeG6d0u7+jSMBipJUUS SHfrcdfkrVmoa/F0BPtCt+9zEAWbR7okFTIVc+lJEQJZEnGTV3A5i3fabEBizzhZnnamom35 0Sc1ZZIIHWgYSJFFbN7jvrRHksDravrm9Nk2+eGQNziRXnPam9c4zIBz3RrasjM5n93U1VyB BfISpKxaOsSMqrqigTkcO3TgN5q25lC6c+a5Y/Z5S6tlZaUOxuJ2O0Ne3uRWCIBBTu6okfNX /DHCnVShyCQdjGCTjBPvvj4wh2NT24Mb07Z10xIx3+9rFOiJp3zZqaO7yooIvRi9DinogA54 7sAAv9FuI7ZiCg9aZFqzdCxeDtpHKvJ+4e+np7opvtDY93+nwYO4xow/4kbM3pEtymoLcmQR SFu2NLIYOYGEqE8Wk8vtDkMDUxU0qB8vVrZ4tIGj+QFHhAygo/UTj0xZfJunoQcqaBnQXQja xykjKK1FGEYO7PmLejvjTOnvGI1gsgdgMggdqsvCkJvKTb6nJfNswLNlXQngH8XeeocbTgxA thrsW38kSkFaGibT4wP6kcjNoewGL0gybAjLJMvOnKHvT+G7x9Jzx8qqbKAtYjoSaRZzbBQy FBipZBR4q7ryOxSisvqliNYClO3q5tpseG0qwoz4LPmqUTAOhApS559qxFwlkWcf+nf5Q8gW KcRSPo6WxEM5fjRoeSCb1SfEG64g8wmYpKlQYS/FYoFBcclwWNlQeB1FtYiS/gjEwcZM4Q8Y qz7WLq/ZJDCKr+SvSAFQ+uAoxQR30C0Qcuza1fUdqYgiNbyjjznaWrwy27wrKajRYsnw2JqG opxPPIbPf21RJlMbeKXn4zscAEMml8AYRycFSUb/pMkjEQRnYxF3+0xACgyIA4n8sSg2zuAu 2pK4nAIkWKK8FccijC7yFlpJZYMkBWbBJEXk73k9y8BaLzgdjBlEI4cAM3Q6skenY5IKA68x x8a0LqDYOAsbSQc1VpNPTONEBbGIg74gWf2gRGXXcuUCbpdxdmGapuQ0S8F4kMhGoEomQNVn zgyeb8pSvV/f3o9SKgMN6hAIPIF3V2HEj7wPTb2vtzTmjK5DiBTVZn8qrJVw5e7+/eLu9oYm MlRS/idxoq2N6LANvThaf3xNg5w+IwBNxM+XkK1DESn1c8CORZSNXqhOEhCiOUCh8I1mTw2G wo7SP1oiibGImXhZgRZx/7CWi8WEuyG6x33UBC3sDZPcVCJUFg2LxSXqMMk1jCFR9AVoYThh VewUELimagvIIaSXsU3hMQGyG8JK3bjw1HHdzRhquRrjCql2SdE6w5KooIVcq7XG1CUA+3TI BgHYwWhAPaZqOMV4swFOS4XZcmOgprQTZILfcYxByhkUNLXYgtqtPJT7nIlYJtjv93hfZ0iI UZBDdF/XN6bgpO67JbIjZ2uMiaBn9GJijrVQUXh21edA6spW6BGXn/BtT1Tzbvb5qbVxFogh +piG9iHh4GzliK0MXwpTMOhfIk7cS7TysxQjGNDrxlIpCC+LjWhgZCtOCAWiK/Vhcu6YYAIi FzSyNQQNzTNau6x5iryZUbdrbD37xEu2s5l4+sN63uJaaYIrfk9nUp8ycIIpoxUUfjCMIS0v ihIlgdCgYnlZ+uhwpCrOe1Xt6eNkYcfPwd6bQjro8Cu91rYjSDnuc5Ac78wk5y/aSRstughB SB1A2m5qadcAL7SLvr2jcc/Q0ZfVZ86Fan7s5bW1cerdG1u6KoAUYIOJbzDDnJpuB3604a85 1I1x1fEIIUAZISSR1mwJNYNygBCYMELsGddKTnr8bJPYNnRH24wY16p0fIGKlYdOVpKcjJvz BjqBE7x/NDkEWYcQWMOqyUrv+NiOp0SyhUB8AQE7dzIMRFJecVHlcyRozMaVddZxGfedAHI7 53IIFwoDPfWeqfiCkcircPz5mFetfTXD9TPEU6qK+BZO9DUtuHSNKy6STLXcNQXns4ewnnho uybfkImKOTZ6P9itCMn9yu1zfjjuTTvZnEARmkmuPyzKXBIxdIrLmi3XMZdt+WPt7EnFGeSY c6UY0rP/9YXWXAJJsf5Q5nUGcsFFU1pB7/Iv/ZfDNcRX0zww5aVGfcibSnXIv5u6gYKSmyLO y0i/fEXR8OXjhkc36Byrwf82sSuJYbQ3j52/o8wA0xb64SlvX1xImf3aUHEm1LmWcSZaLIJr xaNERGGfJa1lXt2uX/0Pci0hiAplbmRzdHJlYW0KZW5kb2JqCjM2NiAwIG9iaiA8PAovTGVu Z3RoIDE4ODAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjapRjJjts2 9D5fYfRSGRhzuGkr0MMkmQQp2qStp6ckB41Fj4VqcbV0JujP9z0+UpZsJS3ai0U+Pr59o1/c X928lskqZWkko9X9fiWUYnGUrKJUMsHD1X2++hDE643gnAc/3r5789vtWibBm7v1RikdvHz/ 7uXdz/db3Kng9t0rWmzvfrp9d//25Xb96f6Hm9dTBgoZ6HTFibQICUXxCc5GiYQlwH2jNEti wvxus96EMgyqoeyLfVGajzzknal7U+/MzQ2HrWCX/DZCs1Rr+AJMOoXuD6jE0JESj21WVVlL ordDaTpa7pt2QTjBY8aBoFNgIsEl84izJBxRqwy5fiamD+uNjANDm7zo+rZ4GHqTE+sGMf/E H9MSSmfcNisJ5SMXGkR1KgM/IVgahpKUjmKWpAkYMGUJCEtuZEKDJwUY8c2ochwGu6ZeKxH0 bVOOAJBn2PXdpUociCdMJam3ZIHWEirIDUpUF30B5AAig2ZPJybboegH2p2sDSjIGo4cazgd WTvkgrR2PIq+o3tl81jsMnenMlld1I90ktU5Cm3ltAYhOfsDmlry4Ng2YPkk2Jl8IFuKNEDR FZgmMKDzNSLKoNjThawmryUqcCeNOzHPZjf0xBm2RU/fp7Zn643W3ImLNNrHoTKkqgfte+ta K5I5Zm2xFgGQWpDdEnbxaGPBMW5q5tGlYqkQhH73fMzqznpBxqmVVsbJye4InNndAbzL7b5w 37rpadEV1bH8TKQyAoHYZbYzXjECPrgYx/XPQL5ZVGnudx5N+KPtVBS8Xic6sArDKXkPFuak G26tJxDscuMzbU8hRpS/wGqk3ZpFs7sykJHRwfqVz72zWAdI4b4dRtEArnygKCuzoXNJLvjc XT6B4Fgq9EDbmu5orzV1jjWFDoiS6VGLpzUWDVPTSe/v7puytCXjyUYjgrphKkFHQEyOyU0I 0RPXGLmO10HbzZJRrAmknJsAqUtNMSNPSVsTeIwIOCK+sKCMQGONwQNQG6snND2RfjzVwRHM 29q7OaygDvRmoU7LRDItpC+++c4G4tXd/dUfVwKgfCVWWgEOlEkdCwZNb1ddffjEVzmcgeJM wcmTxaxWigmVwKpcba9+uXqBfXPGTauQRSq2lHQixiiHSLsRC11JccGSKHXGjQi/abHChDwY AwHqkTNmOVYgOPcmVTp2uQGLY1vUu+JoYxS2+6He9TaBYGMTZYqMzms7TAEdLTjjdCc63Rmd 4U4XwgNKWf4lh2jFvu4NkQJGEq20jlkc/x9viDRiWmpLKXTzw+6hyT/f6IWJBJZqbNJjIg/n Gawgg63OMAxJFqazNL515VyErpxnvg+Grm4LHVgT+9pNIOqR04YMm19xBrmm1lRnlR0KAPxR KH2BRyvzvJitrlh+g3kjbTXFL9IZC+k3lFt7yCQ6B9UPTdtfY33QPhMlNIJ6AypWRZ2VnT0M odr0Bzo1zztzJK2k65D4PR7arIPRSFwvSQdRDrMchlNIZtfn1VpPZxE0iE6DsVy53Ihtbljc h6Eo+w2RCk+x2BFpiucweLt9f/P27iVthJJCzG3nklEAQhq6HgZNKcKx11ofvYgeSLX3QBrO OhNsbfMABFcmrQsBPCYurIeORgdYUorhObaOUYk0/GpCnTubjK0uI1yHTERjhNPcbL4U5jpI GEx4Audp1wDr/Gs5QV1t45hc9DaccM76E4Iu+hNNVMeStLXbcWgri/r3dRgG2aPHPGuKCTXF 2SUfrY6f+WPAntotReLg2y7pNPWlor6DdiHKSp0FqVKz6WWBPNlB8cmkCvM2VdAzn8aSqch7 ynlULnt0UrM6It81lemLit4vYhZ7cOrjDZZ2tgUM59mzm3xyk+qdiKFN6nl+OHI6iYKCxmdc 5sY1LjdLIAztiN+ng8FhywHd1w6YuOhMVVjDQpcyzw5YZb/7+R+3mWNiGcLYBv6EzEy5wnFR BYvvtX+fJdCRtfI2vXa+r0v3YHNK2mHPTYYQuLmPfrp8Gf2AdvnkwBizKmApsTO3zbPW+PGy 28FzkAyZe17Oe5M4PL2CzoNW2yzfYon0USymL2SZzi0kQ3guRqdnIhNLDZyz+BScHz6NT94Z NQnLWHisv4A5eMZUx36tpC19MNf71Nz4rCQjxsCAx/MHJkkD8oAXYfJ5ZU1DrWbR1xJ8LZKp r9ESHz5db/n11ta0C8cnAsaNaJ5MMIO2g5l6fnGgicMxYLb8+4W/OyRnqRytsWT9jdAwrIQL PpD/6ANU7Vv2Lap148vEjDjUiSiSZ86YFMZEB3MXJJEdtC5dIP+bCyYSLkxeUOz4+FcQZhM2 PShLnfviZz56LP4ho1lix8Ev2uSsdMZanP6+sbOacRzpxQ6L03wMAkyf71AXNB87tkRjblyV hAdHkiRn7yVnaJ5Sd4Gv+xMDuprZ9wQ6UCHm+MzODa32bVMRHgxZwv5TJLCNQY10uGdi4ThJ YolZ80Oq3sdekIV5p/BlqC0eD7YK0/Zwav8gG/Nj+9+CQUhyCmVuZHN0cmVhbQplbmRvYmoK MzcyIDAgb2JqIDw8Ci9MZW5ndGggMTM3MSAgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+ PgpzdHJlYW0KeNrNV21v2zYQ/u5foW+VAYvmm0SqBjY4aVq0WJMO9j61xaDIdOLNljzZThp0 P35HkZQlm07dbcD2wYlejse75557eLqY9oavqQxSlCY0CabzgDCGRCKDJKWI4DiYzoKPoehH BGMc/jS+fvPLuE9l+OaqHzHGw8ub68urD9OJvmPh+PqVuZhcvR9fT99eTvqfp++Gr9sbML0B TwNsXJPEmNC0ZRM5o4hxJIUNAhGOmLFmuGXNMRIscQ4/4Ri/GLyAf2Q4pB7nPEZJQp35VwhY sjAvizzbqiLbLspCLwoimSCWyiAiEjGZtmNABPAgMQ5fqU1eLdZuTTdRHESUoJRIs3R6rww2 d1W2WmWVwe+2H1ERlvBXhrMn80wt1UoVGuWtJ1tCYwiCttMdDy50usch0BRxwZzprI72tt5L bUwwWxMVPwCgflfOfduzGHHclG98vKlEcUzc+6yY+ZykiIkmhYtjHzGiTdjI4yBiFKoghGYK EIQZy/V9lW2URqSFyqAfxTQOJ36EpEAYC7fVwqFS7Swsi7mfcKmM3aLJNyBY/G2oMUUpl80+ nvAJtIn8LrAn9NgLUJCihHPgOhA2tk3/eK8q5fFHJZJ7AuwxHzukiR9qQRAj8ffEuvd94XzT s3xXal9HZLqZpBhJQiBXBj1p7N6XznBdqXyxUUvbgdvs90VxZ15t1GoBFavbUX3ZWlqY+9KY ZHle7syTgScpbHFNzmApHpwgaqqRaYg6MBsbavGGr/DkEyY+jYzs+k6FPbWD/UkrHk8FyKkI iYhRSqmvl5BP4519BIIm06QlsPwskR+dlnjQKIrJgcRny62qdNOBeIcPfUZDZaih42DCI/T8 fyf0o38u9AaGPgkBiYc+xKSekyBILPnPtR6DCxhJ2q170ESjf0PqT7QOB42NO2U47I1xZ+P6 cnSyf/Y2J9oogQM2Od1GAEOaIEp9UkZlWkuZZvgCSrzRF1rVJNeSQVPZSBtN8bG06Yd7adPe nLQJv7RRkBOWsGPB9lTlfGnTG+u8dTh1feq0GQEJ4F0tPVUzAueZiM+qmQvrG2XrmJ2oHNRF cvZc5YDJMdFMFiB5VoWvb6Z6mI5F+Kf+l1gBgXuls1P51txBg9av83K10nXNzK3uuvq9qeay LLyFwgIJKp8bktupcNLOxOcQhmORnpbjzsQPHJG0fXQlNFxlmlRPJgcrVSaPXRFZtKBjGaPd M2umqo0hpxNTWCUaFxsNlhBwC3dP5jpbr5eL3E1bQpyQOk5BH7gL87FabGvi9a6mvT96WuRw QAIGM5mWPAgUJqY0yFe9j59xMIOX7wJcfzA81qarAAZUpgFfBpPez70L/aXV2ZBh+BBJa0/c JpdnRVlAqMuhh14JQVR2KrhRyiS02Zn082W229hnUp9gEKyBx6SsJYMhLR1tSN9OboZvry4N WwmDnv5qRrhaFt2ImnkOtWq3VHYUcTqSLYpmdIIzZ/XSCzXMtbx7av4Ymdaqcf+1AcJpyUYV MDHnyhhF0Q/mAhL/DRrENumDqm7tZVk/H9VJkwR4JA6SLk8stB51/vrnpkfnopZcq7lNFO0A rZvRvsNwN0j78ChWt2PdbIFkKJFJN+SWy/J5jwdJuJ/9rvW4foIx4fizwFen6b3TtX0Hw81S ZTNb9NLOpG4MmpfLZam58dgQ40MFOnVnv4YcZzXH5jCbNBP5OquaTyQezuE8Ky3v1BeV7/Sr c9nlqqNxAik/OopfGskhuiPJMeqHqLZ8tGoG5xNPDlbrotQLSOcLxizAPkrW1vRwlAFLj/fR AYFacbEz42JuAT+Oyx6y7bz5eYE1raPV8y/W8H4+CmVuZHN0cmVhbQplbmRvYmoKMzgwIDAg b2JqIDw8Ci9MZW5ndGggMTM5NSAgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+PgpzdHJl YW0KeNrNV99v2zYQfvdfIfilMhAx/C0KBQrYaVqsWNMN9oACbR9Um26E2VImyU2D5Y/fkZRk yWbctGuxvUgUdTzefd/x7jhbjM5fUBUkKJFUBot1QBhDsVSBTCgiWASLVfAujCcRwRiHv06v Xv4xnVAVvrycRIzx8OLN1cXlb4u5+WLh9Oq5G8wvX0+vFr9czCcfFq/OX/Q3YGYDngTYqSax E6FJTyZqhSLGkYobIxDhSDhphnvSHKOYyVbheyzwU3iQ83PqUc0Eopi0wrdZfe3RSCXCSdzX GD17WCXsz1mn8m9AQLEwW0f1tc4jvam0WRNEhFPEpYCBQkwlfacQAYCJwOFzXS3L7KbOivwY ORxElKCEKLf06s0CSKAcw5bHLjCFEiEeBmVICYpj0pddrtEk4oQ5+7hZ6baqdPnZ8K8r912b j9sJjcMCJlgSrrL3mDBd6txM1m5yvcuXxqdm0UrfwACU5Kss/+TmwGErenutAbfSQRZTFIOJ gI11xppXlABwzMO8qM0AkK4rNwMb87JqZtPy027bGWHlGrHUfS6LrbOi2OUr96fW5db9tHFh 5z6V6XabNnsuwUpYUZfFplWSV3W5W9YeBvDQbk8UDTiQSBLWcmDQV3E419oMVEODm1wbBMwA cHKDXdWIFWuPHYQKhEXyyFCQiLIu8s1WHoUSxYq2MukGYMvTOvusj9WJGAnGW9GzSSSoNBTn Bx601FnWKdBOqRjC1/GpbFAp6XdWCBQL9UhfOfjaiq4KF5KVU26jiyoRZtst2EjC1YSEWVrr zZ0TsKEAHqQZ/MjdXOpeXch0cm3INBMPhkykYKxU47n8rsDxZVMnEkEgqEQMEg/9jsSzMKyZ LL8/G1AJPoJ7LguocHXn5vRGd5z5AxOSYp8sEyAinLpX9My9Z+711L0u3MumpCNLY4kE70rB yjr1sSPW2Fzk2tnmDR+IPCWlx6KzgSn+zTm4Izsm/EcHIht3WfnCxTtjAC6lADIDkIn7d3Nd ppU2Fnw7Lo2xc7+ZBOIed0cka3CBkGyAydZNvXJyg1OY+UCD0V7f3u4Ws/mZWTO6XIz+Gpki gwMSUBwjLOOAK4Ek9B/L7ejdBxys4OerACOWqODWim4Dhggz2jfBfPT7aGYalmGtJhgwlVYV p6pjzuO5QkIQr+PWYcXh8CVDh00N91VXBnseiA4Z6yLm64RAp9XLucd2QVAyCIvBZrYIWLHr hjabQiEXVSZb1e5nVWx25kifp3l1a8t2s8pfKFiMuIi/jUmmYsi4JOA8gb6R/hsmWYKRAgKM KgEH6QSTkMoggdEDUNpe6xRZ8tC5i9PkSGgFlfCRgxw7SYJowpvD66ReF2WTIW9KvcwqWzQM R3X6p214LDd6m7XFQX+pm7Pnvgsnki6X0JzYmbOvNxg/ImPgs4eShqE3Jieyhmn7fCWtXXnU DLktPVGG2wFxfWffg734rJMaENh30EMyPhb2O3wA7hHxBzUWN9VVDqora6rr5Zd0e7OBEuQl EdK/UkdpvzOuNxqT8f2Yjo9hGbPxwPMxHx+ROyast7LaLZdar6xJD0fSjzeC/h+M4P+9DW8r jwn2q8hNunCjpXajXZ6t72zqcGt9xro7S8s0GojIn+7Pu7cf9gvXabap/KcEaowSpHdK5KNu 9E/un5y4gEMTIenBBbzSkF3NxU5xUy23bhYKn33vby0TRsK2AZC2Xh1f0OV3XdB/Yp88vZ/5 0xZNEI/ZqQa4axgcBNAxWBTAJn2qNwDHOkKmX2mtUsDdoyJBLO68mHkui73rGPKVEoZBhVSD WnvQdd0/ot+CjgXj+NtLGWfQ6XiuK54SdqIUzR5bgYiEhnYf1kcVyPRh/wBKCrQDCmVuZHN0 cmVhbQplbmRvYmoKMzkxIDAgb2JqIDw8Ci9MZW5ndGggMTc1NSAgICAgIAovRmlsdGVyIC9G bGF0ZURlY29kZQo+PgpzdHJlYW0KeNq1WEtz2zYQvvtXsKfQMyaMB0GAzfRgO47HncZJR+4p yYEhIYsTiVREKrYn6X/vLgBSlEQ5SdMebBIP7ePD7rcLnt8enb7kOkhJmvAkuJ0GTAiiEh0k KSeMyuC2CN6G6jhilNLwj7Obq7/OjrkOry6PIyHi8OL1zcXlm9sJjkR4dvPCvUwuX53d3F5f TI7f3/5++nKoQKCCOA2oE800bgmibjoSMdHKrb2qVwbksSRcro5ZCO8szMvGzB9xVoZt9rGs 7tyOxizKvK7QttY8tG5DCWMVtrUbZXler92OE2eXoAPDOKNEx3Fn2HK2yhrzjkqKf2dfz+HB To4jyWU4oScTHO57l6ZEKNXJOPFmNM7GdrU23lvQxTkLIsZIKj3K5TvKxIhhjJNEyU4mWuOs 2Fh4tmuXHT3f3XY+um3cEZYmQzSsC3Cw6AIZsTHiNCWS4fkJOD/hfvXs67MRyZpoLTrB68YU IJrTMEMVnIWZG1Z1FbVmtSirbD4GCuWEMjVEBbShL6enfF9pLAkVvTczp4uG7cw4pU22MG7q w3EEEWJmGQbK57Jer7xZzZgVTBHF9NCK5wdtEIwIzYexwUV4PzNVFxPOxq2Y8PAkaTit0RAF OFVuIpsDPFXWlp/RUjiVSErIPGPctmaNnqgwn2cgxM0pwmIS+5231ncQ1C/X07G0kJLEgv8A 0JL3p1tWTWsy78Go+EhQat3dcvsbQMZE0YEOF5oWF6CkchrBsVaRmTfmxC3lU/e0/ssTt6+Z ZfO5m/dn7gblYjk3C+OIAuCFOCzM0u2oCj/vc4CnW644uyIuiU4TT52oUrndLB4CRYkSSefE 9G4EG3zr3Tw9ZSM6GWZdt+ULOKBFeLfKFotsFX3ACAtr+794jO5ql0hBpIB8KKQqZKLQ6dBO ApzAmKThC9Pkq3KJ3u/jT8FFOCyIe/tTF0iiV+zgddFXW9yKRzdnNsCOIMIANxb3kTYWLTFJ Nxl0NSJDkk3w3e1bDg7T/veF9dGffcdvzhcwdbFs0dBHN9+YT2tT5Y77ALlYkEQmgIMAHNhW uYLdy5Xp6xTI6uuUFbRbpzBk3bj2gfx0naLbqbKh9xE4REISJr6FKPtBRA8fyabA+Jfx4gIk wTaRPawtHo8DlRBQV1LsV8KrXq97/uaHTxU4BWzM5MH6hiEOFUYof8aDUOeCjVSnLdCUIonW P407eyKUtwSA/1yy8L5sZ2MUnpB0U8qvRrAAzu47ssx5+GZVz+s7947U4VVgcK4KG864gjGL z+vJ69Pryws3YFAvWcR+ZWkqT3zCcEWE3CluuaVsrcJs6fnVkgdOtP5ZdTmodbicZ7lx8/XU r7vH1mnYGSg8ZWEGm3RPi6v13EQ77ASsCVUxoUl4NgVB1uadPDMPywyE1mhy3BFFDDy3Aqsa N5lZAoCXelG2rSmw0sTJZq+lYLvhyj1s2MHCusrR0VlW3ZkCLIlVHL6u3Jp5MPm67RVvfjk0 MumMxL22ZYBgnpcfsf81fX3c8Fl3uphtaBUZc/kaUZaJVQmPcrEwRZm1jtdgouOxDNB2M5lf WLfuxXYLWFJY+Msz30CLBMJmVvpfdE9wvZhbw2FgDXcFeSN0UNZgrbYHCGUNdY3YjprzKUIJ ENrixmhnADIMMX6t7aqXvV4g8Zi8dTP1dKcoOL9w70MLvYDnjHrd+mATA3HfYAgB7DKoRf8/ RYx3LJCWcSrHWhbCfStw+ZBhR3SgEsGI71WiL0ijf3tSBiDmZdM+XRF2RDXrPDemaPxpreH2 V5XTR6SdfTM0gyLX+zkZq/py0yQd4ki4ZKV9afE2j7SeWFD5k5iyOCVxokYw1R7RHBpP385Z x6ErGXZh+t93YbGgmy4s5mm4SRbXheFc14WprgvbuW1qkqq+MR3YuhNccFtOD/ZSqKftLLIX DHzBhMKVzA07EsIpaJmKMgdy8fUiSYlO9HZOt7Oszz9fMPK28XmHhHF/7Jy1dFcUJQKX+R4/ W92tFzbHHWk1ZDyih/fXTUQjDPi0aXh0eXv06QgjigYs4HAThfPjHCgmiYN8cfT2PQ0KWIPT hRUd3Nudi0AQJrApmAeToz+PzvHby3YMUmkLMceOA0RZG/jwu8N48uzch36sneLDkz7gIl5N 0zT+L3wUkObQH+z42Pnnn2/fjzsqUVf8VM8mJLikt3o235YrudWWq0FbDkv7bbmSw7Zcfcfn I7hax3r/89ETuMYsIRrg4nAH5tDY/gSuMdKnUlYUlWOxc/CbFaCq6bAT9h/kFKFsp2PrYkoc jCn8jCfkd8QUNIdwdRUB05pwcPSn8gbIGxgeRdE03Ympg37bW8jhaEJz/wH5GioUCmVuZHN0 cmVhbQplbmRvYmoKMzk5IDAgb2JqIDw8Ci9MZW5ndGggMTA3NiAgICAgIAovRmlsdGVyIC9G bGF0ZURlY29kZQo+PgpzdHJlYW0KeNq1VluPm0YUft9f4X3D0jKeGzBEaiTH2Y1SJU5VU6lS sloRGMcoGFzAalbtj++ZC9ish22jKi/2cObcL9+ZV8nV4o6KWYzikIazZDsjjKEoFLMwpojg YJbks49eNPcJxth7t1y/+W05p8J7czv3GePe6sN6dftLslFfzFuuX5vD5vb9cp28XW3m98nP i7tzA0wZ4PEMG9UkViwzvyf7jCMRmbv1h0SZ4cL7W/3F3qqu2iKXjSF2O2kO27osa+XVn0X1 xXDKb+n+UA73Y4nYy+qmke1h7oNQXc2Jl8sqs3cD95cm3e/TRvuHZz4hKA5sQppjKVsT6met RHba/pxGnpSViZrhs7BDiljQB52lZblYEEdy4MhYz5ZWuUMTiRGL6EgVc2giiImB64VDj0+Y QDhmkHKChLAmu3r/kO3Sps2L7fYTDvASKDdzP6CB93uLhxNckRe+zg3FKKZ0nKCTnic6VpZG bkZ5Da3Y4SCrXIlovsHayQElikzL9HYpQzE5mR1ZVexG1vdfmoPKmLp2h6oETjbwE+0Psm4f Do3ULn40+u6tc/3npfRIfNKbc91GAYxmPCoYRzHnUK8IicAqjZCiOsrLMYpY2DfAYdekrRx6 bqzXsvpEQM/E53oRJI+QAHuvZZs1xaEr6uqy11ScUERieyjRUwaj0Q+QRgo1J5FX62nJHw1N lnIP0wKUztXoNAAn6DgElat1XSWy2RdVWur6XjhEMEVhLHrJXDtvB7V15YoiHg2QdKb+UnUQ oYDxnhW55opRVR82ap2T85Nh2DbaTIQUQDHoAA0F9BGl1OuaozSn4hMmzN0HnD2fxH+xTCJE hcuwnUNGQiQA3EbN/r5ubBdAS2dFK0tb8y79alAarlq5L7LaNID81hmGwnzXhiXNsvpoKDeO 6J7g8nekGd9MxRsFGlfOAlaOmExrBycy7feSEy6dZ/wZ81QgcdqP5+ZtvnsOsKe3hea7mwvm 6c2lkmb+cjBLeFXoqdWUemuL0I/o52NRdn5RDaXKiyztpGsaI+h8ETwBFMfm4TC14dCorbSW IA7iHWHVmjnMyvTY2oQKBMjjhjxoNXgWCAfmEexq9hDxcPDxerHADqWUg8qe5y9wQQxQ5YNz jCqUgt/80c+Oncl5RBCF19AlRBL84zDyMj4hAKgG368vzcQoDKZwz/TRziZd7g/6zfJo6T3i 2cFU1fpDlUuf1BMpUwfpRLwYysfoBOBdPw8vYYjwqa3++7RxeC8GQ5ttjI2f7Cq+dzyIoOqY TY7VxSxzjgJOxqDmCGpyjgVBURT+77jwKLDN98Rl0SLEiKriaLSghu2tehz3qzdVHavkCIWH cQXv371BaPjWMKz+d1ozIV7yq6G0O3i5mGNVd+ZgAUeaL41GIGHmHAip+XsOZRjsfHoK/3pB XasQljsZreCr2+TqH75COqoKZW5kc3RyZWFtCmVuZG9iagozMTUgMCBvYmogPDwKL1R5cGUg L09ialN0bQovTiAxMDAKL0ZpcnN0IDg3NwovTGVuZ3RoIDE4MDUgICAgICAKL0ZpbHRlciAv RmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjaxVrLjhw1FN33V3gJG7fv07YUIfFQAAmkKMkCGGUx JK0QgaajeUjw95xbXZCZdCfj7hSMMlK7XMf28fV9uiLEqSQhSWr40dRLqpZILNWeqJXUJDHj XWmJa0Bbkup4tmQU/Z7cbCWlplbivaeueM8lUWmMBiUijh5GoxIakoiBE6poePR4LKloaCL1 jkZL5EVXwqDh2lID1rukjumqtNTBsoJcD5qBLpi1VcFQvOlBUyhxwYwi2AMRgCCJhWVFhFeM LRG2gO1hKF4z9xiliUUxjxQ0sKwoGtqjB2AX7EkcwqgBxoS7tVqIglaiseXgwkFFY4eYgju6 p0kxQqTHgOiJ2SFvUbA0yF4UryqmF8NDbdGDh8aQcMhnWgtHpUUhNuOk1DDcPGnwJWxZpcZk NaliT4K9qTp6HKMM3VgnaS3RU5I26SvBEWgP0TnjUGOUSzI2zOw1mYTMsXdTCdXoaAQxb8ks hI19YeLowSunmFnRMMyM47aKlbGnZA0LEraMjQIDltaxXTJgeo8eS15CNpjLS4uenpxqnTTO JdQLD479rKQR9A5SJbB0l0lIaKBboBVeQ+MwhVdQIGwZb6IH4BYah8PzDt0VCN07lEiap0pS VnHklUPFW0tVobWCZap5aKSk6hQ90QhhgnetBTQgqFrjPKGYtcZxt56goNGDebrK6tGj1fqb dCalw+aepvVPP/8CcUqumNq9ZgLw4uaPP16svvji42DpWWwUTC03CHIIbGaZcKZDYOWecRhj YGhtLjC7O+DH24vr9OhRWj+GBTPzbtjjaJe5vbPC+QHOgCHR+QFGSLuVMN36yeX25bPNdTpL 6yffPE7r55s/r9O/Kz3/6+0GL85fb1brr7Hq5uL6Cg5oGr5aP91cbW8uX26uJp80df24efXm /Kvtn+ksmMSh41BfYJnzS4yFsesO9+XFxRZTnU0eMbiER9z97oiGR4zf96hM41brZze/Xk/P P7y5+H21/mp7+WpzOS1JL9bfrb9ff31GeCgvguRL7A6OYzp72EVu0HQYeC5hDDiMJg24LyeJ Pkvrb7fPtwkH8tnVza9XGPxme5E9y+chrkW4kEIPw5KKZ23hmCk3nWw2w+V9kMs7OjVr5uUI wWVlg91ZlxwOjRuEA4/sxXLnNkSIJOuCjBjqbxFDHYwitFiuEUsFx8d8mNHMhcptHmFY1G4b Fk+GVbE3qNyeEd7F3uNlDoGNa44IOwRGdMpd+tHmfceib9n6qRbNdc+i2U61aNYlLRfpBayF I4xmRZRgpRx8DaLzYzWBfVwT7mLv0YRDYCsIIaZjYOnwMWUULAWbo0FwgYtrNgYO6RrrYgq5 SLwR3tNOKUdp561dC42rwF3srAIF3pf7GNhahSetY2DtcAZKg+Cq2WyQRkQ/iOboQ313dMu7 HKX9Q+2nuhyZkwiZk4iZqMwcF3JFFKeJbF215AIvwIQzQKGmxrmYjMbJJVOJUGA4R2RRGQkT gYhGDk6eS7k3qwGbBWM20sLsKIWoc7aoziLddqhQgZQOC+ft+eX568vzt79lJBz4x7YcHS0l o4RCMY4wgaS75CgFZ3JDbMjfDx9axn3HXezsDipnqjwGZkVEaHUQjCjZxRarE0626rZn1epj Vm30vlXroomEsmWFi0Epnh1GElbbokY3yi40Zr2aaU8p6hFKUQdzigfIAc32jg4Z+KlHNztk 40WrOBzhdE+B6q1C1cQLCheFCKM80HusGjEQf0u6X45cIAom75m77qwQW2c4HVI5pZILLTEd 16i72H9KkBCPjIGhXDmuax7ac7jvqZ/rqepnu6wl7up2vzT/8vwri5YojXPHkoaCPi47I48j jYvezE5HlCifSKNTRDxVzXGxVyR7CTcHt9fs/2OhiLBxS4tYF+bPFbEUUpEGWmXkMmFnpwsm JnD4HAnJzAj6klno44z+A8lo3DlR3IF7roS00aEnleAtGhInP7KUdRt3Enex/1xwUlbSMTB7 /NZBsBpyERoDU6+5DbKg2nPl9omu6gNFzal+q+4Xp7Uc5bdu7boeUZxWOuJ+4iBYOzSgjoEN oe7gFfchsLaezf3BU5pW9s+mnRpT6lxb1rrs9RZExnH5K1lREzOcE00X00h1uo9mpQvWcdQd hRjH96Ycn5MmhiU+MhWYtZzEaFKUfoRuH/Ot5yD4g7p98PMNAoEMgiN6dBnkvEuu+iAYEZvL w18G9/2bmdZPtZo2W02bb2TaojcykeQYDNMQRTy+XQrlEtYEbyVeH8B62EJLkfwhuTCPbyma ffp6izSMeJTRghchUd/G/1GQ3nJ8nKa2K56USubxsncvAelHXIb0g5chSFepD4JRrEfRPgSW Bt9JNAhm1GrUBsEF3rnagp9jKRwsfZq97n+O7WOfY7XI+/bab312/RtkMj5sCmVuZHN0cmVh bQplbmRvYmoKNDA4IDAgb2JqIDw8Ci9MZW5ndGggMTM4OSAgICAgIAovRmlsdGVyIC9GbGF0 ZURlY29kZQo+PgpzdHJlYW0KeNq9V9tu20YQfddX8JFCxfVeuUsXDSA7jpGgddpIfbKNgpEo W4BEKqRcO2g/vrOcpURKK0d2ijxI3Mtwd+bM7fBs3Dt5x02QkCTmcTCeBUwIomMTxAknjKpg PA2uQ92PGKU0/HV4dfnnsM9NeHnRj4SQ4fnHq/OL38cjOxPh8OotDkYXvw2vxu/PR/3b8YeT d+0LhL1AJgHFozlFEZ60ZKJGKBKSGO2UIEwSxlBc0Ja4jImMVXPiDVXuTCZbQopw0YjkvkNI Ylgj8BMcwk5OmEc3DkO9EfwH7DUivCvT5TItI8Ap/AxLLCzgn4fTr1FerPdBiExMYqmDiBki TIJnje8z+yoLV2VWZfmkntGwmHm01YwYJf4Hk7nfZNO1mMsNvPMclXQmo47lwyKrcL26TxcL XAUkIFScUfPlqs/CRWYhWma5DaJ1up4XOcpOsxVK51O3SXyBwRgjggURV8QkcScwCIOjmaLh 26yalPNVffaeMRTeZSRhBt99P8OARcj7XIdrXKjNhGfqwS2WRMXyh4EvNe+AL0QLfMjBBnxY b8CH4RZ8mEyzG8pknk3xjdSJz4rForBgP1an9mrAl0pwtrEZCIkn2oFJTetamOAFRf0//Ypr 2SJrfOuBhHHwk5DHZ2E/UlyFl5/OCrhgDxoJwmwDzbT2urO6QnXWjeLZcrW2Wjk111m5nOfp AmdV9uXBphvx6BMxLQnlugvI6r5Mq+yA4wWkNhOvM3KAk5ENh32D45hQs01E58R1+ZChW+fg ZOHRCLyqSawTmz4kUerYoERltsY6R9Srg9HAvt+7GPe+9KwxNGABF4ZoJQMF90B1mix717c0 mMLeh4ASkZjgsZZcBgICwcBoEYx6f/TObBvqKMIlFLiE1ycJSPgm01iDED5+wcf17T5Yyl4o fWD5/awMUVAVIi4gqn6Qm+nggKcNI1rHR3l6xwxQX+iuow8YwCh0TfZSAw5FA/WFg5JEQueQ WpEYGvT3xIPSRBlRHyXjeD8eaCcgRt+Khxp2LPQVQrqJDMx5Ti37SKDLumB4v1xti1vduOBF RZNwUuSzwtaTOzuHzQLX1/dzJzH+hDuuOtslywrqtaYy43JR4upD5RZSfKxK6J1165zCYD6x o3SdeXxGj/K9bU7shWxIeJoTJQnfiDn0BHRiITqJdPVxfIFo/4tgY0eBubVeZJM1Lnupjm1J ccKOaLfslfzucL+dpPleN5XQMLK8yxKw0cDWDNyDTVWHj3VI1FY+pTZ6mvCCxiW0cgixdo/1 tXYfJGCMlF0mk2LkR9EbHNxAp3U5+5l4GGjnDEexl2nTJOFua7JuTM6eVikws6kztzg9Vivr LlscWn2tHp5G+2p2ZP96Jrv91LC5fo8a8qO+GaI3GBTcc7iEWrkNrwhJ/3wWgd9zP7u3Kuyz e2lUK+TtzBvysSCSP6dchwaxusi2GKI9dxNGduIYYn370yRbubsb2XWjmi1FZeV20/LuYUPm Gl1xJ9+SRdM0G4d4ugBylUN9/LuPCSO5rC2YzEg/0kyiTxRGgt10VVHyVpbZyXyv4KK870uh PthyeSvQcHnUm2OW2g1rp1V8p0auSiSxk6yqinLgMtuVpDkktOsQHRItHIneSfnKF5rUG5Sv +l7xlwlM1RYVtxm7S8W7uQoKMbmpc0NXPFztOPN8tkuiqThItkGjIs+eqeKaExPHnSJeXzUc NFdiOfDSIUsGpej0mV3iw6FnKyUP8Df727WxXV/81zLKofOYl9MwKYAGb8B9Xg18/IyPWTpf HKEX8JJtNfomteVGESCTr0PmIEVlTBPNk7YWPNYOHDs6CE6H234HOIdVA94pJPOpRhqW+h+V doaDCmVuZHN0cmVhbQplbmRvYmoKNDE1IDAgb2JqIDw8Ci9MZW5ndGggMTU0OSAgICAgIAov RmlsdGVyIC9GbGF0ZURlY29kZQo+PgpzdHJlYW0KeNqVV19v4zYMf++nyKOD1a4l2Y59b12X KzqsuQOaYQ+74aDGSmPMsVLLvt5hX36kKNlO6w4Y8mCRlMif+E/Mz9uLq488XxRRkfFssd0v mBDRKssXWcEjFqeLbbn4M1gtQxbHcfDb9eb29+slz4Pb9TIUIgluPm1u1p+3D0iJ4HrzCy0e 1vfXm+3dzcPyr+2vVx+nBgQaSIpFTKo5oy0gZCwq0pTjptDvCkUS5SuHImIpAGE8Ddbf1a7v quYJzK3SYFfL3ihDhPp+kk2pSqL2rT7S6qmVx6NsiWj7Gva/ARcvQpZHIi/I4t1+GSaCBRI/ 8agBeaiB2J0mzuMy5KtAEXFq1Um2iAKp/ZIF2h1UhF03RB6kITWS6EY3YafaY9XImgRVU1Y7 2cF5wGshWkcRxM326mpzCRvBNFwbFzkwiVEZ+nYHRYJGHhWx9J44TrRCwNaMI0ejTuPVvbPy UnUHWt2TzFvZzOH7CWSxCLg9HJNZoCV9Hvuq7sKqIerUgpvAPgtKWFQ7XAEgd5SQwrZWmb7u aE36OAXdkFNRvfUELIZDGJw8UAeJ2fut0n17rgA3TuFnBH8MIyTFJIXy3CUAstEqcjCyiLkH 9BRglKJ77Pd4qtVRNQigk6O8VCdKHEhaEkbLMGMs2B7oaB6UmtCbOQ83ukNpERx0XdJqj2HD hb0+Llr13Ff2HryIgwbTEdMM0aLTj7iokC1rQ3uojGyJWU2avmPEkBqSxhBdqi8xSxqwMwMU D2FzgDpOIr+Bi6hgJP/joHBH4pISF6Xs5KM0nhrcYEl7cVxYp2vn2MrpkPQ5tXRop8q+xVQS KQ9OcNExsIlzGG6fFCeStnvMXEU3CClb2aIWWRYcdes4Y44AQW3G7qCyQeZ5hSNnUmy41dY0 SQA0dTlgW2zhXJa6bgI5Y9OZUceCz5OW9SV1kUlDYjFdGHdMuxGQ1C4nGl61I+C4+gclZ7LZ gI/Xgrj7VoXvBkVYzNcl8vEi+HUbExfIFQVbGeO1moOs6zNdRGBbxXN7Xdcalb+YDxYkJF+R JOdIbaNPfI8RRaDa1noIeAcog9oGAQX6bGcSj7gcJuTZjghf08FZ2ZZ0dKcbcPuRVIFU+l2u /ncVFo+rnXAOpm2URRqYnq5K7x7xVhH8aGkxwvfu4dPV3fqGCCY4Y/8w8H8qUoTvdNFFYOGv jDwIKq0sRrR4It8OGC0X8MyE/Q06XhC6R1rT01NM4AHh4FGuvhz8Q9CQ1L1SRQDWU/lED7eI Jy83F1kUZ36q6Ju/G/3SvH3gkzjK89xvo5erCIzqnB09oxrOZIz7M+SmN4pDwVYR1OO5J97k 5oc56HHEVim0QjjJcmfle2U61ezUV2vvS5zGkGhDE0thBsInGfhsBsugcRXlRTamuMhc4oqM +Xgjb0xxpPTrnWMPdWUHQtOfKCV02xliueZfdYpoH39UMemKMVk2l3O5Q3l5VvgeJ/JsXp5V feLHrv/yLAMWT9/1rAP3Fbv1/3BuGhWxcM51oDWgbgnWTtJEOl7lvWaXvNvDZkcG3O87hn22 oVbQ8bvhTYVMLIRDtvm0XT/MPLZQaSyFkf5zq2ttA5+8irONajpgA3mrhpCTjALphTiVuSRK /NyNmyZPKggou8ZxfCYJ/KuJXbx79V4YO8Fa0aPpWmld0OG46J1Tq2/oL1WfvwNjBgJzYuEF Mg5PgDud0F3SmOqxVueDinMe985DQ7I1dGuYF8AJJ5jeEpwVQW0ru0Fk742zzfjyJ9h5nntM RjfS9KOqEW+SD3gTmrbtMKTCOd/5+SvkWWzfC26LlYrEVyTy8gj+6bCIZutbbwwlzhguZet2 wzSIwyH9r+LUHLysovzURPmE4kMHmJ1ah8FG5G40GfI7d+OYmIxjdmwoIFjwrwCMHUh8lCdD K5cfoGsIh8gDr+YsFkC7WUzglDiDzbk+REeEVJBUGOUPOMX55MZIqcmfUSBx8OTCjl7EeKoo IZuJnAfGvm/P4FWbAHTIJgkIJ3/GkHR+jObAPihfGa+eXUx6OxJMx6nhzUVieHNpTnLpXyoY omsydrHeXvwLBXBTPwplbmRzdHJlYW0KZW5kb2JqCjQyMSAwIG9iaiA8PAovTGVuZ3RoIDE3 MTcgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjarVhtb9s2EP6eX6GP MhAxIimKYgcMaNY0yDB0We19aouBlhlHqC25kty0QH/87khKlhzFydB9sfim0708d/fQl4uz i7csCxRRKUuDxV1AOScyzYJUMUJjESxWwYcwm0WwzsPLv2/+mGU8XEQ372YR50l4O6Ph+6s3 N7+9tutX89mnxe8Xb4cSOUpMVBA7WYy5I7BJE8KTlOGhqDsV8YRk8vBZEcfh5b7YtFFRwiel CHe1WRW5bk1zEESJEsIKioOIcZJR7kUQilIoE+F1rbdbXTsh9X5j3Gh5WrgaWAKyaUZ4pg6y CUXpIg5397VuzAU/BzngCZzCTtgYcNCFNbl7ffR2//4b0+R1sWuLqnzsQjQKTKSZe/UGlWU0 bO+NG+hlY8rcTlhY3bnFxmyLHKSxLGzNt9YbxONRsAWRNO1C42z4GIv4+v1ltfoOtghw3BxW 6GOlECBUdO8Wjdep3nulCq/H3KnVHdDu4b7lxnmFSn6NrJcixiTJOAVn2ag68Qbigojj4XLG ZPjdjZ0DYFBWZdSaeluUeuNWqtoBdFvV/szalKbWm8343SRcO1xECIloOYtAlQp+Zbj6PuEy plKSSNaZ7Rw1AXoKOOlPEWcZR8tEYhGq6CGWTHp1mEwOscRVjCUuviiWnHAun4tlPAzqdGAp lUSCfoPIWg1tZFEbiOzj73NFqOLdS7ePxUqIZnIsVDuJHg0u/iojTIpx/D1EMPYjKGThcThH UJhwExNESf5s/BIi4/6ULldTohThsneT3u1MuUKH357Pe29PezijRMp0lDrcOdgjhaWUZIxj WYRqyAdpPzQVilWX99xhBZ+AFaw8z+NFkfSg/gEv76py4f13AM0TNYCCn+JsyhBvh4SqLo5y 2cEH3adAittK3RaY1qWrE5bYeoHZ21dvmNjqPWFSDLnJe4yBIe2RIS6N0CVuIYp+dYPr98tJ HESKE3pswAk4sKn8W47yb/5k2uGnTjiTckYE/++qHJA5sL/Th54u8ogSTk8glSpAqjqu1huf zFDoWJKONydiXFY9dIew9QAoVz3ufwIcOOJjtA0A8kI4UNv/sxfUhZcA4QmXx1ApWXaqOsgM fC7H1eG2rmzvys1q79rcY82EInE8kfLX9ZMt4sU4Nd9MjnVnD4SnNTjyYdNT1SeiEuiDUGNo rPI1nj27Wpx9OUM944AGwI6gxsiAp1BLqAzy7dmHT3Gwgk3gVMCnsuDBHt0GoBhHxTbB/Oyv s0skt+PICMAjE1aUoJ5lYlBO9En/vK70Bv3hpzl42L7klyfcpIBbHfrxgwXvBJ+AXnsIyaQD ODAtBWTif3AAB/ZC2WP7L5JpIzgAjclR0wYqt7Jc1VEls/LcJgYuK4/iWfiOlW/0vvFNi8ak Y8ND+F4BfPaW/UZcpK6ZCeF7HSz0xHwq4SDjRHxEYy/4Y3MSAdnbm9OY+iuWGtO4T7Q4eUCK UbmPryG4zatZlKg4fFvUTWu5oz1Jw06xjzFNHOuEifm206XnsTSFm4w6qtcNWIi4QfuSVGAB w0dfwHCCBcyGw87wdH5HZlGW4C3Bfq5wjsJtgISHZaIyRJlfb+8xWji6135QVq3f058tkfJH dxudm/6GMizjut4UpkbZaRoWBOpPJFPLO3a61m0BbrB6gGZ3SLhxYA6BTLiygcTlom3cYGm5 tatVUGLtmi3xeFrX6/3WuAbQYA35Be1irvTruxaVmVC0MdA1VhAduHmdH10NBvog/DqW1O8D h9pv2qJc+wttXW2qtW8rGP8erZa0e9b+7s/FFZyJs5DiQ4U/3Ox1OQHPVAEr6dH5eoIOEh73 /cIqCKL0dGdBMuJPXk5L6lnr1uiyQXdQyMCqbKCD5O2EVJmSlCXP6MdH9R70WxW1yV1GgP1d 19ZFadk5HLDJ77ae/DSFjBRKnLBIEMaPr1FJTFSSjCGwuO8aUccN/H3PM4sWMKZr35JcksMM aHIX+LvK84ddXdl09Ds83Ohyvddrc4ACXJAU5yMosDhk7vHDPRbuch5Dym939s8GqgZEBTbc RR0zRvsTMJGEJu5vAZxtdXfFYS5zoFq5ictB62uQ65kRc3k4lcpdFozh3PnO+EL9ULT3k2Fy Dh/+CeHa5SvXDoeXLliiULNgbV/+M7jYHWk0j/27ebUFY0CFpvhq3FInKmrMlz3ecPzRD5C1 vgGvqrUfLXX9ufk0+YlOldpsAZg2oCfFD0RFUzYfGBMaN0FVgAxDxacsISnlP8VUgD3EaWZF JTQZfv78WV+cj8x5gp5kKfRC/iTLRMP+BRHcHBkKZW5kc3RyZWFtCmVuZG9iago0MjYgMCBv YmogPDwKL0xlbmd0aCAyMDY3ICAgICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVh bQp42q1YWXPbOBJ+96/QI1UbIsRBkMzL1HrjTHlra2Y21j4leaApyEYNRWpAynGq5sdvNw4e Eu04R5XLAnH28fXXDVxuLl6/Y/mqIIVkcrXZrSjnJJP5ShaM0CRdbbarD1G+jqGfR5f/u/7P OufRJr7+bR1zLqI/1jR6f/X2+l//tP1XN+tPm3+/fjfdkeOOolglbi/GccoqDt0xFyTP3Nj1 bh2zVEb9vXKNpm3iXpm9bsra9bQ7dwJPJkcUKRGUhRN+fX/Zbr8sCEIJz3mY9Qr2y2ik/ZFl s2ZZ9GWdCzfCIt25kV1b1+2a5dFn/Ke2rvcWP774tfiTRZ3a66ptcKBXj70b+5ikSbUj61jQ InqrPiZUNLrXMM1agTJJsiKFBiVF6s3NCaOwjqIgeYLWaKAlM28XKeEo8Eh0ehwOYP89OKWs a7fmFjeJlPs4GCvBo9UCpvftbOMsMmpf6kY3d358tL1EBf86qqZSVvRkLnO5g7mICR7dl2jK Bw1S4D4IEy8E6oEzDqXpUARsG9Ud0Dwije5Uo0zZh5HPprcDwomH+8zxgJMW8cAKkCyRLwLE ABviccnA/Hk+1+4P01oNKrU9GjCtx8n5yZKCO8OOh3tTdgoR4CQAf6YsjW6S0EAnn4tFKSfF GDCIQ0F5pB5VdbTGwa+AP2xXIJF1GQSBsxX2gsx1e+fady3YywEuS0nGi7l6VWvQDVbFttm6 vcAhCA/7a/eEhno8lE2H6LWfYPz5+J0p9/vSxOZYq9g5HQ2XRcH8czdJTvL8G90EthMZaKQf bDg2owRWPwZcwGRwn3RrAmTigOBuQZpcElYMwtwkC44RpMjDhLLZLqmUkDQb9jjfAoSbMpBI RVRWYH5v85Q7m6ce89gBTtQVwh17pw6AT+sAmOPtHjglI0km5y5Gj3QuZLaqq4z2IeljTTcu wLrjrfVXhTxSl0eIYUspyk2jiY/IG+UjUo8h3evqWJeeBIaQrWCXLhy9a82S0XJGhBwAv63u cNLF1ebirwsKvcmKrgRnJAV/pjngNxGran/x4VOy2sIgcBHh4JjPdup+xQnl6KZ6dXPx34tL THGz4wRPiSyE3SqFrQb7vBYv4oiT7Wwm4wlADpijoD8c+jQdMNbdWxpHyw00jh9db/m/3IJ7 dmXXO0uPqQYcBCTG7BkzL+m+C+7Rxru+NHfHvbLpr3c9N15NVkzVDLJBWgMD+4ydEwp/hIE4 NE2izbqQkdof6hIl5ECSGCbQ4NEecM0Zgm/BhpBMGICV5qfW+8ecUUZL/lK1e8hmkBo7/aDi swh/tZSkfhnS2/mCZYck6F6oT7jb4B1WOYDhmDFUZczmnetazEaZmLLcV+R22lmrYeMZgc+F jf1JM5075UHz1mIGRcbEHKRGdABW0rNkzAlMQ79G8tVzwUtTCsEbtDtz17mUUFgyPnDkc+IF 6YB3lwDJBIc4zhYByT0gLx3q2r7rTXk42A/lEXl71HUfazy2cT3gmC1wbR8wmj8N0Y2l51yG XZCQ83TcYclSCcg7ZgcH8tfs/CghiRw552Bs9fmgMXTskZ3ea0u0+LE7NhUaq6x1H2qC3FZ2 CxKIHIp7diIBX5CAklzw08pIJFCXiDm8rB0Q+qHEODmSF5BVs69WRMvRV0jC5bQOwoN6c/RH fg7FrvI+xE5X+OI8HzB+mfbjfRDYcaiB5XtswDhWzbFLd5NCF64+qfXbTG+oDzx7hjwH4QQ8 Gki1CY2qUgdf0opoqLIU+MwVMFBL2olD8UsWHectL4l4iSVt+01s5YeSpGBsLv3X0tOHT7jN YtSBMXIpF4NO+KC7MqY13VJ2g7pkqkQ5un2uLlDuSBFP1oUCKgE+hYc1uLP0wxovZkaXt7UK 8LXTZ3b4e/lwNl4TddP1ZdPrMtzZ5mUJg5hIc7riiQCa4j9SliCdZbSArbh1tj1eoSkXmL4o CJQxoAzYXfrkdPuUNQXIQb/Pmo3SEDDG2bR0fTPT+muZmRjfXUjGUQzE73CBCLL0Xw7q3PK0 4FC9ZSsGSS+BZT9geQo8IyGHsQxwx+TE8rak8sr40HD2W+armGekyCgomJIkLU4YcnxIcPdr BmXY8K7QujnKhY5jMqPcLA0FlbIlGlz1HRCnBYi9zCPD7fy6w6HWrpMv5wGWSbgfZy/MA5Or l/MigM6+3EzdqImCwgFCAcAAbs8KD13brLC4vFcVKvCnVR57Lcbg1wDbamMpEr5s2odfS7Dw 65gUO9xPuPhiG6pYv8fmvft94oIBGKGF+N68B4SV8BP+v97h9Y2CWuFtKIuUY3TjRyAYRELH e3iS2Fzu3hG6Do2D4y04kSt0Os6AaNv79dDUfg6otXfj1hzYhfnmmfeYPYpyDFcDd6kL8Xiv QkE3AeSbkOxs6M2IpXqapidhunhjBkobK5mBVNp+RiiLpa0VBRf/VLagUH0WufgZbIFbZbk4 YYvhdeo8VWQJEXDOTxABiUryExHGm8+zNRWYE4oJeUJS4WKzYN0Mrj8vKVqhHpCDF0LwYzKw DwALO6eObcO96HzLHG789BQ8gS1IAElB8qTwgGX+BeFFmfDmhSe+EK5u7TeWF19BqwDjw+/P QCtsJZP829H64yIMaJ2KcIrWp8CK7rXPeUPR+NvvmyugQCnAvDGoJyDD2jdSifV1XT76DClk Gmn3foXN8vQVH+f7V5XKItT23APB+sdUaanSDaRDZsbuqj3W2yXWdTe1tXupcZeL26PZqmYG oJAR7LvZLCOQ4Ij/A+4PcfAKZW5kc3RyZWFtCmVuZG9iago0MzYgMCBvYmogPDwKL0xlbmd0 aCA2MjAgICAgICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42rVU247TMBB9 71fkMZFqN7GdNEECxEJXKkIIbcPTskJu6l5ELlWSwlbi47E7zjZJncIDlSp1Mj5z5sx4xnfx aHJPQivCUUACK15bHqV4GoRWEBHsub4Vr6xHO3SQ9FP77uv8kxNSO0bzzw6ilNlfHM9+mH2Y v3938s8WzlP8cXLfZqSKkUWWC1yEAYRELQxqQIgyHE51VuzJH/Zlcs937dkzz/apqC4zuBYi Ho48HRdvRSUcxBi1RRMjv4jNq+qQ6ZN6y2vw1lvtWhdpWjgktH/t8g2cbUqeZbyE8/LwwrTl FfiWDpIBQuTgT4qyFEmdHpVIpcuTuvwAdO1LseelWKnOqWwltFA8i+RQ74oc/DzXAAkFQwbV AC3W4DlJVkZSqPJqAccrXvMlr8QraBF12/fKcMSYFCRdRF/rSkaW2S4XUolPfBuhN2A8ygRP uFPDX0P4OYBQeRmAz4tD3kcui2OPPBgGb3ZlamT+KcplH5zufojKLNwErxLZ42pQ9/f9tuRq kjpR5w6MwaGgg+WYOTohvZrMEepksK7hkJZEDeqm1XkrkdciT0wyddj4zNkm6u4hMg3Zosj0 sOplhFlNeJpW4JdTfTmvkTRd1jwakHJCLnMyH3sBbXBqeQyzH2E6JT0uauDycMheuExbJCvz MKWhfnBCQP6G5rxF8A8Jvrm+e9qjcWunpNMzXuMR3rXePAwSNxfW4tam2hdtnrZB22eA2r5/ lnFbHY2vWPErmvLiNp25WRcW+rPD39K+6Gzb6wuh586Azv8h8XKVzZ2BJ9E4NNp8EFU9VJk6 61Z1he9KWaNZPPoDrRtA3gplbmRzdHJlYW0KZW5kb2JqCjQ0MSAwIG9iaiA8PAovTGVuZ3Ro IDc4NyAgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjaxVZtT+JAEP7u r+iXiyVHS7ellV6iiXroeSF4keoXNWRtF2hSdsm2oOb88ddltvQFCui9fSDMsrPPPPPMzrBn 3kHrwuworu46pqN4IwVZln7kdBTHNXVk2IoXKPeq29CQYRhq966BEFJPe7enZ71uQ7MsS724 7Z971zeDxqP3vXVRhLIEVNtVDAAxbXBJN1Fbt9qOKZy0zEuz2nrnKI+HTFvtLhqOqeJojp8i koY7stXRnPoJ4/F6OEPRTKR3TAQY/WtPMnwTX221z2DpN8yOOsF0TGLYGHE2ha1kQsC4Gly3 rrrnsI8sE6GfCHZ+cBaxMdhxgmmAeaBvSiylY5m625YSIkPm1GPj0McRZNN9mWEah4wCgmXU 5/NFa2h2ep7NHgzbQGltmi+j1+bh22G6RksKyyOW7iJ55BOc8CZhDNaMszHHU1jMYyJ/xrMZ oUHLkiv5a0BGISUBLEIK30uFhJHpIGFTe07KJEoclokGWTz4+np+CQafRyQLk7CSTzGMcGuC +TwhkhCV/oRzxsH0GQ3CRIiaZReFJN5ELvDHQ4EqFBUfONBn1CN8GlIcyXDZUvLXtBMwLm/O WPAKtqhCc2VKqG8ESwGz8pUPiM9qX/BDtu6k7NKroru2k7OkjA4TyULAr3McGJnRzGMDKZn4 EtPOMZ9SKgILsliDybK5ZDhCW4EyYrFAW2lVoVPCM2vxcn2Oq2IuiRRBch2huFpJPXvPGv/b mkpWa/EfkNVey3gogw+LdIqi/d8b0szT31CESp99gJ8o8sfUPNb1tTrf0nCxMVMYfxVO4L3E uM+JPRaYCY/aigiHCpXszHaZtvdSVaGBUeqVXhgnewmWp1zXrhnUdrbZBbnDfNft2DnmFphL qP2Hw2zCcUzqGOwxGd53w3fqml5ymQYAbu2u9H8qTrY6F9rb/61erEv7TzZhnnsBtVYAMe8+ y4dGSYt9Du85PeVkP9kxRN8FWuD9l6ZyJnh9563edfLVNGJRxJ5DOl69f1It534Sl99u8kkl XoBTzKtPL3ElRMSDrnfwC/+jHcYKZW5kc3RyZWFtCmVuZG9iago0NDYgMCBvYmogPDwKL0xl bmd0aCA4ODcgICAgICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42sVWW2+b MBR+769IH6YmWqEYAgmbVqmt0ihT1UwJD5O6ClEwLRI1GZCpU9P/Pju2g0249SLtITEXn++c 851zPnPuHJxc6uOerdqWbvWcsAcMQx1Z455l6yrQzJ4T9G76QBsoQNO0/tV8Ors4uxoohmH0 Jz9/DMZG/+x6OZtfD26d7yeXIpJBkIZ2T6MYukW3GJqwR+GbFGOojkd056eBYupm30shvQhg GCEY0JsI0TV/YG/9JE1htkpQEKF7+ihb3/mxt85gphKfOAJFN1QbUPjAv3f9BGV5+ksztZtb /A/UgTLUcX7M9UgFQxVwWwBU2zQrjd2Ny+11CxuK9jq9Vli8MH2MkBezCOHvNUQ+bHdBftTG PWYrXYhb5hrXSQ7dkFxjMN/LIfLyKEGSR6vFI12+1vk1SxkPJbdejHMmTv/QNIGuqbo9lpMV zU3JPAoVXGOkwDij9kolQG3sR5uj9oitxogbC/PsvjBQwxrJqKN2a9+LY7K6YhnNEs64HWf1 kHoZLCOV07Tbq37Ix2BUssWzXxEF21FiHxjDz4x+PhWgPFVAohwl+a5IGnyKsnw7FrQDHlcx fIQop43LtGClEujuMRFqlFO3aVyAXtV574pL0BvmyeGCtUoj5EcrLgXhGvl5ktKbJCypWxil Wc718H5NvHIdDCIy1VkDE4JGEjrWPrPNE7resdfwaeWhAAayWopyeZcEf6laMhFaavxi94Cu 39htMXpqbRfvUJ2Nk9UiTxMv3lK7vfuiUDExVQsTvIfJZTbrjqsydalB3EVZaMt0cUnKwnEW S4gJDoqM6zwWCKJ92bpzrjwwOZzCK49j+5bGVSMDBRINpoywlEJ9K2mTCDdkKp0p08U8fQ1v FRAiQCfqBJXCHwoZnqls2zaVZ59yunf4HfNM9imtLA7dXJfbq6DmtTDztK4qVktVLnbNt6vJ hBy5r6jKHoQM0KkqTaWYLmZhqRzThSNKNDgW02lk0y/ovBBavZxdK45QYJxtbXnj7en87nnB XzP/b2I+op+tj+rnKtaeiZa/tJNBtrWeV93OLP4Bh/skb6qEuG9vT3d3xXfeOX1S61De+Q6X h+18Hn4QmYIkTxeVYe+5FkyKjJkxNnMlirpH16aWZSGq0aGGwMsIsv0b5nEW1p78s7CjhJEg 6g598m5H1MHEOfgHybYI8QplbmRzdHJlYW0KZW5kb2JqCjQ1NyAwIG9iaiA8PAovTGVuZ3Ro MSAyMjQ0Ci9MZW5ndGgyIDE3MjM3Ci9MZW5ndGgzIDAKL0xlbmd0aCAxODU2OSAgICAgCi9G aWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42oz1BVCd29IFiuLu7iw0uLu7u7sv3N0l OAR3ggeCuwUJ7i7B3d0hOFz2PpJ9/veq7i2qFt9om92ju+ekIFFSpRc2czABSjjYu9IzMzDx AETlRbSYmQBMTKwMTEwscBQUalautsD/yOEoNIDOLlYO9jz/sBB1Bhq7fsjEjF0/DOUd7AEy brYAZlYAMwcPMycPExOAhYmJ+z+GDs48ADFjdyszgDwDQMbBHugCRyHq4OjlbGVh6fpxzn8+ AVSm1ABmbm5Our/dAcJ2QGcrU2N7gLyxqyXQ7uNEU2NbgKqDqRXQ1et/QlDxWbq6OvIwMnp4 eDAY27kwODhbCFDTATysXC0BKkAXoLM70AzwV8kABWM74L9LY4CjAKhZWrn8S6HqYO7qYewM BHwIbK1MgfYuHy5u9mZAZ8DH6QBVaTmAoiPQ/l/Gcv8yoAP8mxwAMwPzf8P92/uvQFb2fzsb m5o62Dka23tZ2VsAzK1sgQBFCTkGV09XOoCxvdlfhsa2Lg4f/sbuxla2xiYfBn+nbgyQEFYG GH9U+O/6XEydrRxdXRhcrGz/qpHxrzAfNIvbm4k62NkB7V1d4P7KT8zKGWj6wbsX47+ba2Pv 4GHv8x9kbmVvZv5XGWZujozq9lZObkBpsX/bfIjg/sgsgK4AdiYmJk4OLgDQCQD0NLVk/OsA NS9H4N9K5r/EHzX4+Tg6OALMP8oA+lmZAz/+wfm4GLsDAa7ObkA/n38q/hfBMTMDzKxMXQEm QAsre7g/0T/EQPN/4Y/+O1t5AnSZPsaPGcD0199/v/Q/JszMwd7W64/53y1m1FCW1ZCQpv13 yf9Viog4eAJ86Nk5APQs7EwAZmYONgDnx4ff/8b5LwP/qf5vqZKx1b+z+0dEaXtzBwD3v4r4 YO8/hbj/ezKo/r021ID/PUHB4WOegQCqP+Ovx8TOZPrxw/z/eQn+dvn/N/t/Rfl/Hf//m5GE m63t33qqfxn8/+iN7axsvf5t8THPbq4fuyHv8LEh9v/XVBP4r4UWcbA1+786aVfjjw0Rtrew /S+NVi4SVp5AMyUrV1PLfw3Rf7rwEdzWyh6o5OBi9deFA6BnZmL6P7qPnTO1+bhUXD569bcK +LFS/3ukuL2pg9lfu8fy0XdjZ2djL7iP1n8gdoAP88eSmgE9/55tACODvYPrhwvgozg/gLmD M9xfHeVgBzAK/yX6F+IAMIr8QZwARtE/iAvAKPYHcQMYxf+LOJkAjBJ/EDOAUfIP+vBT+C/i +rBU+oNYAYyqfxAbgFHtD/rIReO/iPsjF+M/6COmyR/0kYvpfxH7h87UwfaD0P9I2Nj+ktjZ /fH/i2lGs3/Aj4yBfyJ8nPyvJv/XgOUj0Q/ujV0s/+HEAmA0/4fJB7L6E4P1L+j+j6B/6R3c nP/h/2Fi8Q/4keWf6GwffbH0crQE2v/D4kNm9Q/4QYnNP+BH3bb/gB+k2P2BH/cE459Q7B+u 9h/z9Q/9BwMOf07/cHb4H/VH9o5/1B/BHD/eE3tboPkfktiY/y11/h/u2D7YdPxYdId/8P3x nDI6/QN+lP4PYpg/6nT5k+tfCOj+DyLYP8xdPi7N/57wUY2L7f/0hvnj0D8pfFw7jK6WzsB/ dOOjAlcPh384fMRw+wf8INP9H/CDD49/tPrD2/Mf8CO8159sPly9gc7/iv0/u2rq5vzBjuvf t+nHMP0H//1oAoGeQFO4pXkHU94Q67qQ9ocaYXwP+r0J/lmKPc10anqfJeefbk9I0CnU1Vmf N5x/C6cM96Cs7ohT3QktE7/6nLQ0QIe3Jim3Pfu+GCaoTO+1wS1OYQ1MFp4I1/cTwhLQqwnt +746+WoE2YC3gHbKUOQ5uXEhKRWgP3j0SXrW95etjIXN7ynvV3PIwr+UzdDHqH/RCyr+RZFv kj2HQwrlSk8IQ4N26Yn86+73LFru5DuxTAItnN9pDGuRj84mS+zjnPdahRqLSxcuOa4ODiH4 HdrYNKWPyGGqDPaCT8n3Lxv8CzmckXFDyyF9iXOyGrik/ko4ziGl9PxfA+U60cm7cj1Mvzrb aphOKgAoPxHXw/iEUpRImidVkQ2XGGYTWAU8vpIRqiZqgZrR/uwm6jo9V++k8U2Mw+FhjjmY sCP6zY++3ZHtz/HyCMVYbjwtKQeZYg6yTrasoIg1M66a7yeuMuwS01Doo9v/ns/w/Z7eGtw6 3Pe7q53eOk8fvCcXttLEs4lSw2HSxdlrUWe85bBuYw3GHWbwFIphB3fEzpQryxtrUhPnVQid NAu2CNJZeTbXkEz6BtMchp0LgTqY5pTyk5nWKQnBdL8g0uxrdsdZmeCK8jnaKdsZUCVaKgZe fzaKIcMxwHBqnEAwK2iX6zyHx+GIp1kdz61QLElH1y7DgHHIuHF2dT9gni0NptH2lm0ocQ5r z1WOz5+SWDMztMJDzpjbAk0JptvJcks5MHMiD6vL2r1qmjr0Qt+l1kmF9HWqejCU7CUeeN5F 2Jzy+AqpIxugJHWZ4Czxle9eXKag7jmTF39zmkHB/6Q0UGO2xglGTobWcBrGerZhG871Tdtd dqmA+CdQzw0mQ+5S2SmWTyNRWng+FO/4kdu4Hdpw/RPlsYRYM7ckmUZb0aOQu03UsOsPBnEC X+/yTp0Cq6+8OQq1CIqyxIxcT7iklzDTKKVSwsucHfOCAqTlOd+ysV1PU4c9eGmm9yJs2eE7 4SUkEEU0d5+YQ1WJSN76wQpZaBpP8aF+jRvhf+Hi0YpvDbq2VS/Hg/4RIl1wK6jrUQ6Gtz1m Ckupc2BUjDtdmtuxXoPgYiYFlPie9gnrB43L/iHizFSQmhn3LxHjzcJolM+hy7qxY8YJ5KkW dcxtL+bI0HqHKdBMR7CcZ0TGKpMGqFSZL3LY1qhkoyR2HussbWRt9qPOW+S+0e/TamhnctDJ SfpTPuVaxUbvT2z9DJIpHuhNFbsrvkoPLCLHFqsNHjcmNl0SNTnw8EEKFcXm1ryxZoJk8bak tByn5YQ9FmD7cT6Pd6g0j+vnZ2m40/DodKrKu0gs39sKnisoP5XYV+LqGdXpK0eHBPMcIm2v tfRw2OLaM5lwh9npt19e0Z0wLpcU6WmTc+Dp0gapi0eRDfz4Ip+veEqFOFnHIPayJVe9XYaj d0ezJfTgzfqp+DvlVArH95BLlrRVqKhOCkhaqpTbTJtAozocsY03xrohsBQbKrThxNg4m3QU x2okV6PfBkcivU/hONtztXpSQf7H2uiGv0tHExveMGGe0U0pupD9qTBIluFk3BdckJD90ge5 neY99qc2fXbyOMLQqiZcJpJQ5UMyYB8olel7HT8ffIqkjMqQp6zjbEBtQU111dl4htBzJgzw ZU+RL/7BTlr/maajGrmT8HT5mK/my0SKWOyXero2uRtza9rkhNORjp+do6C/T3KHs0k9mXru LcnAyzfcdIWW/bYOl0jng+GGzaQTxGlg6QDWnfv6+/3uDN2uni0wmKWwF4k24t3atgXV3/3M whnogTLwB/WDd6LxKdAB3/mJS2V3sBrFEK3tq6VJvTC0wvERVsWafB8o2/Mjeu9sBA6tstt7 lk5RQDDQPWu+nJi0uPUI4n8Pm65NHALQZVxotLhke3elvOwJmyIGtCFKEs0iFAzwmdqWDlxM NhF5q4pKNZuB18rFlHBAZKeOufZ3EeuBrepPaeUN2Vr8Ah/5aZOor009D+G8dAfJ9emiVWBj k1MqN6/NCLQvFro94FNfEzWqM1zrdtNMbH2u5PB8NVhRAbiO/1fRgzS4aHUGCETxaNG2LdZc SL/5j6c/ta94Wxw9oYLkMUj0RddzbNyzyr5H1ImskUzNqpUB5dbqQXOB8cpqjyZYUNZoeTgn vw9l6RX/3e/IgneiM6EOuSJJqPDnF4F5qerAiu6T58eL0hU7e+4x5own+vD7vbxnzFJdlEQw 0IqzfsRehANXa054GNZ++TWvbe/vIft0W4I6l81C+08qGEoiVgI3u1MnRRenK+4RGhJzesKW NrUO6U1VkJsoWVwQxFBgGRAXFzRQnQOEkQrSeMruxdxsYN5t75FsC/d2QcgAey5qQrHs4w0T /cGlHOh3votxdSqLvbvFx3WqQiNFlrToltdCnBVvE1ZIph340Tt6HDWNGp/2atgHQ6mL+GiD cN0OILqtyOD2NmJaLOEL2xeFq1DAbtdTBFaLgEAnPzC3mFU5aYo+8xOT1/TGWSlObizZnQyM JoAJZmMtAp9T7zkUzfWSvWoVlzUmmZ84tneiHXexFQK7BLln3ldXJXOrVoA9SDoGPaQs27n5 DsETxbLK0otkx0ZjVHWoijNcGv5BzXLIWC3pDmPN4WQ46D4klqoKQdPMRV36gf9C/2k2A0Xe dxYyM8FM5kFPu0wFqVzSKxC5mc2MCmVDIW6H4IcPKZbto14UQN9mqIpLAy7jAfTiUviCn3/y wfkOoLFrEPCbZs/O844KeF9BcM2vNzBSQ/L4ltcr0pRjwhU41TKthTifIV9a87PhSyXaYvE2 mhWcY+xmejT1oPNFKUKe/+4a800mfM9CXCY0H2+AGV21wSxH0Z55Np1Sl+NEie9llU27Clcr Z+MtkYAVfARURFMtEGDQGVKfla0wU0Ag1FZjiXaYbVStKyIR3rFOJ0fxy06dIKv9EL1BBBjY TkNeQ2zv4LnFKgtAueu50SDv0C3Q7f7yGppurs6Ly/YWHVOXg6sMZd1yk/gUUp8QBWXRFk5s kbbhsL6KSEJBqI6H0dVuGVlU2rZK9SsbwHJ32LKQW99ZG1xQTAfYatjM+KmIozsVkThhqCcY q+k6yjcUysjbEoPQSLqvQlBpt9ZTlfuVuup3KcZX8Vg95yFNZoTu2elEh+SiKXQQr535yCVq kbGoS70OoWWLoKMvkzKCdgBxJ6el5JBbLjaD+emRbeTOabHcJgLjF25OhJ3CH11TPpXDxV/R ynVIGgyN6J2XbZfiaC7anEA/f8XJ2SVYal2MyndFgJATBbWYgeOxN5GBjXiSa+1zisNLHnQ+ sGY36OMGL1NQ0aiXQT6o5ARibl7H29dRnG5N1qBrD6S4DbnOB6QSrUBEYLMN/Ije4XMi1XQV 0ePNFy55gNR/+fYNkqjuDt8cZ9jDy8tXCiPf5zhM3R+Lz7ZzzPhN/ooQMh0BpCMQ9dxlZaFl cRPZcLq973liTkBiIrovLco9UTl82Bo59w0VDyzxqSqbA5MixzQQnKxw0L8xHj4talRxHxIR HAg2E5kQ/sl4SZU583oSGA7Y75GAd0N0MbAixTk6DvVq8IinS24M9ocVvSxK9N9WGUg0aqfD f7UmDaZdGqqQtYlBVGbHjswakQ4usx59EQ+7MlGjPkeuRs4jjQmrF2j0OFpzf67f8iXHZmA7 TqIRmnURXIGzeoiYdARpMOnf1nOGjeFGEi7v3dThe3SnLRuBqpYT3W1LmaAtIVzhAovDSCV4 9Ipm8BSdWRrIpfzcqV6S4rekJ72HF+FMnD3yNIItY4GPkN21xbO/IiaIg1c6AkiEpvp6jYfa zZB6Ssgeo6WCYMS48vSzxAea26iKaxMTOS56u29ZAk2MUu7zmK/h3BvDcEVeorvx8abqXhov pzrFmA0v+I4cgoiI0bmrTaEfrHjPHnJjoF6ElAriwDipRMbxmRZKTbjvqtfkhZv/njKqZblN pzubBvRsYR4o5hGarGbrRDbXVUlyQA8reizoM+qc9ovBYgL9mcISlV86oR/8XBLDTYKmVTmm ceFMCD4/qEdwsSBBOZ7/WJYOOFsF4Py88UIBZVzAk3cdaRiu2D8iy5QxT+pwspyWKHaMQsTu qImecwoBK0c1k+XiNYzmql88edDBiYi3M2KubZJxHzW2leNYtwRBDmX+HMXhRzd+sxrC9SpM ab5EZHKdAH87ytUi12VTFHl8Tq7ZXjQlGRPxtMNDsqubbsOs8vjYs7j6IAkBTv+oHvF6vAu6 h/j7zUNF9dIpR2u55kIMfBi6Mhcs4lk9HwKFpy1lEH4x3PxtJcq5v4jlNv+mREPBBimLXos+ 3W7AbK2QM5CqBMlW4oCmP0qb82UpZnnRqBC+1lFVkOKHle9o9KOrL4guzD2WCd8jPqc8/2PW DCe2y/CUfSPe5ymUpukyDxa2dZSF0C4zRpNzMX9d6upHaAu24nzWw9c1SUoQRkeF4B4K5BTC Jd7KdtekfUTQNB7QLziOh8cIxxiPPX4e8pmYqIwgPrBFkxWB35gYTErTdqxJdHZihfiiC/cR P/9+8/aat/1F/f5KWgdYubyTzUef3AnuWlO3c5jJOIdZYikEMQVL86MOzN458E7a5MHlQ629 v7hbCZF4JIbNc+i57A9GKc3ZPZSUQ/YaUVvmvOYTX7nYfutyitT0F20oeLTTxr3hPwDuMJhR PCHsMwm8f+fdQO+Ma24m370ymADLE6DTzmIglHheTS4EzcylAE2W7MVuxbDuoKMEOcdSp5xQ rShjQj7OwP9Snq5aOW7Robfzo+c5KuNkbRqC1pKLIRyDZLi4QTDhnc0PkrZ/bPg2P/3CTHRs Pp/39wmRZF9HzbfAwoF+HTLhhkSc/NL6ixkUoJN4iwAyWKeKXBns57dA2UUhct8lMc3KjOjZ W0YlhXoog6kUVhom2bvdoKO+19WBZmq/WfAqmSN5C9IZcvYnrivDDotyURcW0UZOOtnsXOS5 HEGYibaJSeq8/ZQItnWEJ6RVZjLQHofW8tSWZmxMaWIt02yl+0X/yGZmwLcjGOPrz7sGRf1s r5jDHISzydTWhIrfl40xAX3GiAYOXq8xBnnlM5Tc6BtpkXcwB4PlFAWdfHwe2yX8NoLJE+Ar b9ZCFUq+BDa/sQLYvkm8nYa5+NFovfYuyn63Ls64MXXUD/DP4OLrEtqJ705nbfpm3bLHkh3+ mSIFlJtTYeKS3Ns/3qCnOwpMwE6uV05hh/veK/Kkvhs37BQGBGC8QA01Saz+Qi3GIDg+DzLP 3Z5dbc6m8pul7CJ2WqulZQwRxoOMCNlQxRsfRmfMjdppa9MH8IT+G+kOhtVyR/V04+uBEuYm qthIf6InFDUXzOxpH0wSxXxaz168sj7fL4e+MfOpaP9586/8Tlk/mzFk+sorxEh0VjrmZMXw h2dMu++Pqfb4CrRwBuNxGLIPiaekjloQWaWwIgZBQktl4u56wJU4HxJTyEaJ4lRof5iqb5UT qqltgVLlUBM3vYjLGpitUDR0kV6/qUYzyPaX5VL6cjqFe8xJvuIufn3KId/UiJxWyO9YfLO1 m+FwYtGTDgvYTPvSugoy3nlaSBohZMxK3QeXBw+qwHkow1lPDPFri5mzdG9etsGbRpwXZ+Nx ZBwH1ciBwoUIfVhFkJICC9urGzuiTEszTV5jqcZPtHT8kXh8NNui87DUnJJuSG9x/uJmk0+P se80cKVBqwCzUpAj0WHyvHdL0vBtPTDvZd7uMonwd23bqYItCdXsUnbqhcrzL7G59hx9+nDQ +12lG3PqT6fuL2xRk+Xd4jIaARO63J12RbxgEafO8UjOYCQxwNPxU94GT4OZ8+BVheD0sYyj igRrTs3vx2Rf62cSoWahkxdG6ocHW0U0JKkCNq12sXV3pYs1hfmEfhzufOWv4fgtWI1+ZAGC +oUcUW1EsvQELT+IScFFjv1uCWTiKEGO+MYtij4WlGPewtD9CQxObt+hSLz6x0CBvzR1gywJ q9bVhMdPNHgQOeX7PTSf++501wlgMgP+b9MBPXqYYuFc4fTuTyCs8sjD6L5rdTtrwMJSx9ta F0x0Ay5Z5vRnLxoLxuSLvpJlzopjVQACnxWGrvVQsmnfq6a7bBEs7tBKpaeW1gAZmLRDKGc0 fGzX71XUuS34EhnTbZ5hWlWizuA2KCpA2qGjcfEGBOnpkIs+ZVr1yrZ+ls3NWY9qg9yF1+m6 4Zv1w2i6ykIT38UO4HqsZQ7GmbG5vBv7qwV096oX4c667Dc6zPgeBwx2VSlEMtlcZGxdSoSF Cpz9W9N+hDxcyGtevq9mLcQoEL11G9sDwkufjmgJuIS8vJRVT9xGUC+SJ7W833LsjpZYPRdu I61kSWIqXdyipxLNouuX+J1xRGu1BG9s24NTxjQCNM281lbYZZDj66cPbVZPmE6mH+BVW9ss VddkW3ZjqH9gQgYSBS48leFFpjTa/jDZcrnEr3nzAT3hkfZpMKIEqDq+zf1CqAMtSE+o0l63 KAYX4C69nxoHoKw6j5uTBPN8W8D02LRHIl7mRW5JARwJCT/JwmYKWsT2QCgkOIUdp0GwgdRx oVD3xakVjcP2m4J0oa2VpKuotkzKjozznNiwfbvBWFWFSfVb4mXlS105HmnkO04DqKobgE1E xzk43qI0vJuTsgsJR8MW7F+ZOGEcg+oT/O7QnKfRUIwjkq90XZ6nU720MIQx1G/MYwqNqjqm lxzRmnvwrj+klfRNhMk3N0x01heXTFjZMHZayYq1iC+2g53Tb5S3//aeBuNOVSNWx9hwuyxn Uo4acBS9YLZ9saRSybsi+VVQ0FimV0MNeevNy+BwpfK92eKbnf9mplGdDsuXw62pCN9oyCmf XWEZ0zRllYdCBCd7M6p15JUsr4zr5t8OYuNGamUyonEQqzdS4d4qxqu3g7OESi91r98WklEW jiNHPAeyRIXa3r4kyTtO8OnGxTBNCpa8Agd5wXTUjm/jaENLVXQLbB4s+ieLY94xMIOnsZON IUM7ScuckAxqTeYvazo2loZgaXZeAnDfTp3vT5eufKt4eJpRNCAV4kUUu9W9kYZXpUwujSWr xaSQqs/IOcjZXOXaG1GqZUxAG+Hapc8VpHFE57OcGo0ZZDNQ6QYqEQQCRRO94GxTYDg/5diZ J8FTNjiMMPdvlfKE7lu9zYSWou65EdYh2nWvARUmA0FzM8CEmHkBIiLPp5jnfjpU+b+w8ZXQ WbtABcwjd2GMym7tPJ69wBcr6jY79ZP85JhgnBy2ZBbOBgEZt0sXm7hsu2saoiIiQaVyB8+e 48wuhqUVuFR6LCM7OrsdOgyzq3CSgvdr2/hBx0C87C8Nbk1NXEeIyKybjqkvXKhiTnRJAx2U D2vIuqzyCLdbLlB9rvOM6JNl3T/UEHgPzhOfm5BFeTGT9cXEat2Y1sCgvyHMFSq/6PJ7B76N FCnl08iKqjsl2uSBJAfvkE1iCB7YtNTAI1LLw16dPUsSqBDVDGpKIxKTqmhzXhZrvrWtzoDM Hs8P1JxEXmTsMNEKTdTPqa0pqA0K3mJ/KVw5DzJukyn39PJv4cIdcnNsLPBFbBVkv6jBfSfX pXZ5VTDjyyaLrZ7aPFIvl/9FxTWFSJRhIt6pfCKFtgeF4srQY85xgHc6n9+rjjG2iDCYS7OX 77kTMJmraLUQb9TszKhn6jAZqcozRgYhFnTPLyT7W3iPJRet+ftuzhFCJZKFHKGUneJSenlZ ngkSN4xSfF4HHvSPZ2KHnsGUabiU4eWQKUUMq5UB6ZI+rhwVddUSLyyW4x1a+xiSpCSKqtv1 62jDwbivlFuoWnxOs8R+ca+vrsNKIg2H0Rmd8YNGc5xFv0GL+ukzwSLNFb4zuNDJzhaSHF7x OLlx7TvQN6QOj60tRM5+MePF3kFBXFr/2oxzpXiF4iSOJ30xzUTqofaE34OJ1Ek/BFGGYO6Y GmDLR+OCMjYg0/AZ96y9IKvDHG+OxtQJSdEPfzHUv7cJTZ+22VhWyZKLzt1MjLQKJyP3jTMd NbK/yy55H0wKS22P80sMuj9P+CfVsRWefOWCQsbVnf4sdXsVdnW/PPV8W5YyUjn48mgTCXc7 ffDg0XtiZu3G2mVDrJiXlGm8lOsC5otStzBIJgxvYRjHW9THYhi25K6M9GfsWv5wl2kQQSZ3 d5wIgbUIGm9rqE7hA1aUZMHiz+opNH4mWYGHiwyjXuv89AbwlbJHpsFfJlgQiRQbUb85f/ox m43lO6J89uamKGMSoC5uSjmu0pDMtfpMDj5SqPdLjwwULeXMolIMM2iB8ZkbQUOmoxV45364 G+VGQeeEhXydVyROavqQr5R7fMVJngEfr2HiHYk8q6NzyZuXtfHd6Feqj69lPyelcHcJpZCL Z/6SetlDxyI/k3ypFGoIECa+suO6jtN0jN+kwRu8k4AbYsNdV3sxZdqrpdRg8S13NdHpFdRH cO3QNGZTvA+13cvMIqhPaXlCVQd+DF3aVngtS8c3c2aFz8vDQ5s11i84Bck92Js3jFq6PW78 qMEmU5e64D5dgc/u52KHF1eYdXwvRtchrtpmgMEPhTet/tAFaAnu55iO3mGXdz/relqXCt5R ri+yJfmzWdsuUi0SsJTnjVR9uppMX1DYYlhqF+YUTeiOB0ejxTlJVouN6SHQSolrBB+OClTY rI5HsXyZ7vUwlcknjt66qlsjOJ6+et1+E65ooroZeG9VZhXeuPrW9/0o9JRRh9DVRRrSyftW 1ffRhGPgSwOWvjF4+Twl79YJYp6vaDJtqsw+R217W2U4a5v5a9gtQ+xFXmkSF/QBaGGtsLBN gioH59yCps40w27gOJQdCq5tbL+wyjvXYvRwHgcKHdHFYTkh2vdd60XCk3xt4sAtKgLOjvRF U5bHl/vN9MRu3NoT38lTLTLHeRPsy2/mBLCELPSCV+w+YjboQxFI14MmAk3+onvB04H9nedr b1H+jLTPsEhcswfCuVMM5EaYhUlQy6b7yEQuiBo5cYPFZ/wZ7e4U7rMRYSevIcWICb6g7bgG QlnuyMafU6s7z3Ej83JzM5FPiu9t5/H6mVKfvokoxUv7uLtjWNn5Twxn7XpDua1cH4b8ktto qIP/RZ0lkbEdhvMb0MqdWm3dXyRY/7MGcmk0szp7igi6lVutLmIcTZk6pFCS3CA4lsJFzgNx ZP3UnsFberRr+rl4IZXvgs4AAoYtMl8utkps67pVTxAbcwqET7j1ZRKGggT7uOdlH/HGThUn sY2nrOjpFMK0Bpidhn3ZNlhhWz0FK29qJhZ9Ak7jarJ1vSJU19oCC1mShNsg1apcJtiSAdNg gzKqk+0EwS6kcBNpHkIaNVrooL8hOjsi+lUcauwt/lp6Lrkp2XcdYZVxjXR8U0jjJI/OGFST V1qsOWR4QgV7aJpradNPYZm2SmQddOjmmp3rM/ZLoeAlw+QZIl56hy5TqrRAVU5H9bRpxA1C lOqLQzSUHpg9gSRauv5zFU8u7HNN0MLBF7H1qkvoexGiYXwyPsgB+cJa60rRNJ3Ox7m38oIt GivCqj18mTEoTWL9cebedwX0bDv2rkyE7ZA9hz1efRwrijRU03o1+7iATKghkPkX7rrxKydR 7i1Eb0XzMO29071rficLREU16QPsT21W018bqOviyfgWm8tSmAgjyqdZhWOjRsa/toXTiClV yIRwvfIjpuvNOqYm7y3PR23r9KFrJ0B4E0vgFR7AQT0c+/Jo5X8i3+J0LAnyJyxofD50rbpI L3CjZnOFvCt3Ft6GdaKz3SJKg8uiVb56h5K0lMBr8ECNFF2LpH9fimXGv1lBzK+VSaT2zPSl 9E5wwTk8wgyz4P2qRYHspd0asA3Ja4t4J3Ppdg8X3aJ7N+FaOkvq1q3RKUucMkYumEj9FOuK 73l3+yDV1mqMSoOjOFeqO9wjeKxlPWonQgYiflA26esQNtkJPMDEwLk38pMBgxGPTGWfRjhA y4aLrxTI3xtTRxRORYe1rG6kkvlUlpI/9nlbML9IEWIGRXIZrkkbLoagT3L8k8ooEnQZ7IAT 2MMmwshMy/1PBlS5fDgjz135OQdtKU74CXzAjteMXDj9LYl47NlG+saqcgU2kpxbjJI6pel5 yncbH61oYR/AbFWI/SRlUjKSU8VagtINmRtErzJJgZAeug+OpMy9EJBXCt8FI9KIMVRJUh5p M2THdKimcmXR34ReAhrUHckV04M60hVaENIb2spmXgDET3LSdio0r5PFjux19M5QHRV8F9nN WFGByFfjyJRUPdKIM5VipPMu3bZjD5F/FuwCL5RUW4uh784e1cgsTZPtTADKQuyF9zxnTHmw NF4En9cIPUgTZK3TFQOBX2LtiwE4SSx1iKxGzrpA74qtHIT2BiakvYE1YuabsgpwaDfWeNWu /jUBmy4WOC8LvBa/GWoJ1y3XNNkZB5bpq+jd1yRqL8Yy8BYxHrIhD3YChlSrG3+B0z3iEN/M /ObMm0HnlKgEt0rH88F/OKVNYfbKhhSSG7VJDBD0YOV5+/4opNHAFb3Zua78ZbJLUD2awuk0 PPgIfxkh1YXH3/DnVqJXPppoJ4TRVz+XNplVgthgjrAtcgH/xdWtzEbDR9rX+9tAglkpF2Yc yYTRZ0PdMvx1Mc0fOwdN7sJyznrN5ObTq0N2yzFXyUSy50Ek9jm/J0HHH1sSiumw7Tv4qkaa b55l0T9JrMcBvH9wwJ5in9KSD6zt++WMj5x8kfxpBcQ3GZj4DDsgInHABQKSbfJToQIC1w27 Kf1r5EK8RurcbwPQVT20MiXnDi+ga31RRyK3QiCozajNW7lrDd43S4ESLrEs55xVdSJwsM+R dMEYE8M/YwcMSY/nzVHMRno0Sk9/uyc7D3pZlEE+2WPbl91nwHy+klanGb1CIUDoFReq3hJb mrv6gbfZ8tP7wMqOuf7MsMzBR8TkBTOio72sWDj9/HCqZTyKuqnvKwcUOT4Bpcq74pNjwY9P 713V3E7KkqJJ8jdHdpcANFCTQT0ApdJUf2LJ8pclvVELf6zlS+EKS/8KmSccdPFAgijaF85M qXLEyqxVVrApQieu5QiWl7Uga5oGHK2fUddYbmmFR6+hWx8vsNbEmq7dvoBJIYo1FvzzMlnP TFLFM7qXw2tpo3xxXioP0yu2+W92slp/SbG51VKNq6mraGWAqOImdk48AIqSdB1KoVtEhkN7 MOMLWryzdw610QBM11H+eapPykXDjNqjLvKTAmlj3qgiIzCmYAL3M4UeOYa9wYX7txOFXdHw Vb0FMySHHCWJFSLVX/pTgStaD8A+6aZnkKJLlihbWkcNxwnh4HdxRSfxQXJMhS1IqPXjeZDD EuAR7ed53rid5Mda/Vy9Epr3mk9kL3y3dhWHjQNUhta8eO+ChTIr+LkwQtP8Izw149hABK9B KkzpmSEVx0c1Uz3BRfHTNAQP1DVRnDidm90zJENZiSw/oSKuyxWDAmZUcMvu5tOeoMRbGrjT gcJRSuUH0dftAMx89ThZ8fqtUJSSbqer5kU9giunrLGqdhkw8NGcGvtM/Fzy0m3tazvzZSiV oNVOGdpdCVdl8vs3VUbNMezEwcl4hsI0yZJX9jMKZsoTshnMaUke9UTCa9/GUe8+JCKcGeTd vrALpZ8/vLA/rWjQITE2Ej2HglrT160211jf26rQzAVKJTjMqGGUMA/iaXWxyoJJMDudLERj 9ijbMgp9h+z0aVWuSBsPL75dI6ycmZbCA+ziXeNRokDq6ntYJr51Na4jHPeHukuGWUUJVyUe LDR0m5LmJk/nER4yEH9vjXMjJQnO7bWKnqvmmGXarcClmHMsblY19ifiN2LlugvBKFE25uh9 BrKTpx2nGHnI0HwbvM5bz3jCi3gfHloTu/C6i5wgh7Rw0gjkuaY5IAgdByOOq1UBzDpPjZuE 4V5+t1qtiOpzLxDt/2Kxet0C419OJkVWdWGx9aWwIZG3KeV17LqvbtHxwkGLv1p0M7YEHo1k RMNHZg7yzc5vd8HC6SrXfvZ3P2RixzgXQX/ECf7SsFAYzqmdwlIuumIv3ZMUec/kdab++0bO Qjh1sHEX3F3XOkP8XbLEEjLdsG86IXHPlgtCrjz6m9NpPIyAKy/7OUK7hgXjpotomk2u3ayo lyUxOGaeqyvdAfKzf9wa2InHSARfJ9E8IiIJx3gYGGMsktRjJUDI1ZOiCh3N23glzX/wZ68Z Ik9C61dJkTYzSl3v5/wxQ7NsI3kNE4rP5q2Z/StrN7+IMRIw0GWfUabxVMB+N/SAeD0rVDW0 rtwfzzllUO8t5Vvu268Xx91JE4pcaFyxlVOs2hEO6KApTMXxhhUciiLfR9gn02OhJ49sJ4WA weq+3aCWkYd6y7wpGOM24Uj7hWeqE53qFufMuAtknW4wU7HMZCZIoKhGhWPRbn+6t+rFj8PZ xOM36ryJRJR76z8M4bPPlNuxQOwSjcGzjNpjcHiH/En4c+GeEhADo9qRfB7IRYqBhTXhnQbC Kld9pUj8DLnZTwL5uHt+DQ0kQWos1Iljppxqxh63th31eqW13Lyvw3032HwRsR0atAVts4+L 8y65qIpv9EASWGpjC2lVfk/X7ezi4p/8whLWo5ksQ1rnsl7dvJpa7OrVS559Qx/0CUbTdH+C EUwxIPkM11WtL39ndX0yA9dKqVDZ0YSYuUnDKzzitJNjac/QTEVh43wza1pKfQn7dN07Io7X FDmCFp4vsnhGwEfTM1GPzwvJJXWZW3JvMooosmAsl7Jrk+ni6caroURQuJZNjE56TNrCAuEA oT4T2/6FbuSEfnMMqswkKvOt3zMOnQ+r0Qur8vuQwt3Vp5pS2K+/G5XJb6KEax0fFWYDcWg+ X+cOIrG51n2mPlYWL8J5xZjhP1jyTF3GZ+UPeszmsQV7bBuQR7j1j+iXr54WU9VpWoAgB5d0 vwIxy2qeOifjbSMSt2ALl8ZwIyrfges3L8CCojZHufL2g1+i0BBF2CBey6qh52uH6KZJxlbo Xi7IkSwOfsfy6q/IITkMY4tMzC+hXyXwQcLTuDVPtZLRUOdkPOgfTKb5drZg6rbQaqxwam2y YkRt7otCeM3So3Ucd0anCuwdVoDqFfz5U+kHkqMR6pQRlo1+XYHnaOSvo47RR9iMezVYjPM4 2s92n6jXAgEWGqfJnkuw/hFbIFxKhFIQkCubri+HG7dSEV1p9Xh1T3lFnHHR607eX444KOgS akWWgkUCRAjJ4xB2FrwvWAVrtZ9FEc67s8OVbNkEHWQmJ9k2Rs1aQKtJXdpaTFFXAtAOcMHn L7S5uekAfBgEOYEb+GwWs85bUj27NSGxn3bWFgE/WcseyMO0i0UTkni3o1xeIv2X9dQ/FRj8 /tRoAGMfANfovIB/Ry/C4ykYCAMmrTirG7rLOHvw2efW3v9dAaFvq+/rscT0tMY97dxs+/kl mTawaoVfIrRk7HX+SYM97eInDhDhaXIOzI2QwdkAdxQrM4aeT4Lx27DB2fLnOqkuH5n8TL07 voTcaAxnW9iZfi0IXu+ktSmbrRoXe3P1rolEYhtHHkCVXCyOEiy12LJZJ0E0MJpBX7w8xfS7 R+H6FIw1X3okKwJoMYpqe5RAdorZ9N22II4gx34PW8+4/BtGABtuxhz3sEWrpdavmCl2VQYY 4p/vi07zpkST0ttmtVMaFd00wRZ62lPJ3IWbN5lRhP3Vqsi93Bl1QZuqLk+xtY1DnduZc6DH lMIoOtoYXibEaEvf9IUfHxS2dlxBzPGHoZ9cRcUEQSuo9KSnSfUfXo8Pqk3jFw7keFtvduLT 5uL5X4gHNdVnDvTpi4eAYPg2L6G2QyUuUo0PCt9SkqTI+U2QDHd3f0HTbYnZcFoK7ZsEPbxm l2AjwLatVdc1CRQ8uvIoHVqXnRwran1aX7BmOdQcDM9bt4TkXKsmUCsY789h1QwK0uDz2xGE feNYSwrB1w5U2Ze+rejoNaRhoz+0FdP+npc1BeKQE6JRty/PNWFPDam9hqZX8itZXcd5PKYd MHHiEv/mSO9DSyZUmteMeI7Kngv+QOc1bKM8dk8jjSCsw9+n/lKauNcRFVeKu4k5rRCNs/at AT6N5Luk3apdF3GvCL2hutgdBipDYie5YFMOYMvLTHiRlvQW63n0POG10pCgkmF4+nHi9xiM mpBinZK9FDvpFOh2reEPvaE3ZeHYzSYOHTik2CFYZBOiw6guKW9n5d7ZAyux0uzl2GAL1/dV G95ZFAgHnf0spvdWkQPl0Bq21tRx4dfg+8ulEsswLU+oxtjQUtQdSHafQCvoyndsPaLp40q9 7uCbhU3C4/pYYSwaisoWOGqVthqmFuZDPVNT3MhEa4JWp+7UXeJs/35fLx8CJ58iZ+W2Xnsv EelxmdVpCKrieeMwfXxO2Syt2b280OvBnikhWfFQ2WDcci/vNhb3dvQQkx+QZA3OPaEqA6Eq 528ZyfsikrjsJyXX4lJ40BeiE7x8R+ygXm7rivzMhbhHUqS2vD3jK1hLI6B1/E7jayVdNZTn ydwAO0xvUXG7x3vBV18vg1MJ4jJQ/WIikDLukhFmhoFxW0hCpL2z+Qghr9tQgadAzioUGtVj 3hOT62BpVlKUC9911I0aiIsMI8NtqU0bX5VxvEeepAGzqLUcvrAcDl/seAUcagWV8OxPWRmn d+BuNMlA+7BmVyTNem7cokcltVh6YnoTggkRK04ueUdHEske5zKYTbs4RlS1z48kK1WDc5Av u07HlDRD7om6jE3cCggPK98v3cSO+3hipy0cmUN8RF+JeLHS5VijUVWfA50ehmGQaTfcXb4I y9d4sbbMbY6XjE6TbjWko83RNljaYNS71moZpW6Adl8mr4+tUaI6bMGMggFyNif6X3XTByIa Wm2L+6E0p/ZGqVF7oGuURZCVUiMIv6FDlwaQj1Vlquuz2A2j3wrpw00Cudz5sCBvboWYK8rK rGuCMiSTGKd6R+orXAJ/UV5pTQul11+fZuHW0VSUB9H38RagLsBpOyf1v3jq901IQo6QDAgl rt6OPOf4M0xK/pJmpsY3HwrJQumbXdZzJmjcJnnAyn6v3YPJDMrWrBYq1mUV/MaT8Ib9rIlj WtioVyCz+pn0SVlVEqTip550eOZACfoaKmTe9N7Evk0eDIGFDZtlLNgXJ0g8ZSyXNqVsnC+l 5w95+owSnV32OOA3g2YkFA9e9lg7acqaHbbA+f4tvUEyyHF/9jcojaCH20vADQQGt22VDMS7 Xi4+3m10ri5PrJ/jjdJEiEXt+Geos1/4zpzgJhMSaT8eGXdiH0DLbVi+ayIHKeaUPXGLIqN/ dZMpmZ8mGQnflzUhLiwhDyyzRGqqVk0kdJMgg17RwRm1pLFRGHPxffe4Wg3ZUePOGBj3db16 LKKA69zMS42K9S6aEQnQ9Pt0Jv0FxebGMN4IQ4HrYqHqiw2nnGw/8LeI/rfFeq/hTLTcymZ7 xfhMjOf5lHGs7fkpaNgxyk8eKhbPU3JEaxbUVCUR1CG+1x5XQexATyWGO3z8urmkhRUq7jD8 deQEtFBcmDufDGx99Wz7SGvFd1HE6/k4fuiaHmWbZGk28kVLl00C+JKFDYycWIGJn33ni7Hj qv3H4JNjoy02MXkCPSjKTVuYI5LFtu7kjZgb8wORne/ZMtM5dc6UQWY0znfI2KbY1oJGJeIr M4yBtK4sKU/uUY7EGiZmbqIn/m/hLx0xPNhZwOrZQ9uUehSGrxeZ8FOCPXo5P0ndYNlHzkSJ YBlpsO0yy7gNfnFSWr3BlWVKUjL/uipjFt6ndhAkkw2A1E3tfwpxCSZSXFzg0kPNuQIp2nLe +xzRrbO8IyjgK5JgETCP9XlZXCVfXIbL5uf4cnZOscjR1rINqPk8Uz1I/zw4OtntBoXIDiqS jFTA+C+MgFPOliBFq/U8M+2ngmG1U2kzckyWFvzlCpKEtZblBtcvX/O9xrla19l1zN4Nv0Xe HiY2F3aQZGc+JNy01xftp3v9bMGHFEVQyfVFl01rCFL07ZJ8O21DXz04z0IgNPipjYYkYtOw Jt5uaSc0IwsBcQDNZbVS42CXgE+PWZ45efSrZkWo/v7zbkwO3funWUkKZuTg8PQoxrEl/Jdj Az8/OE/X4NZBryPluLuJJEErqs6fJetTkbLIdPSL647JlgjXXyklRVbPSY4VNx4V+ZIKCkvX QuD9DNbhrAO/5OZgjLzi5xPVdl7kixJWTjd00w5/e+dCjnqN0HacL4fGiDhUxpXuQhh4JsnS pOIn2vteOpcWtduEOqKhqwJM7PfT5kFxXytcMZIjsGDRLRELbi6gr5do5Y7krrFhUN1R5Kk1 AWapNpCamDasJ7VZ21znrUrjFDCXCQS1EDlfL0NoYnXT3cDBZmbMPigdtmfED7jBwNLLc3XP XAdD1zD/VG8/F15UMWBCpB4GyQxvczWewKM1BklYLL1MMCbM2traNA6HGODetKOs+z4WCFLk 0tTLd8n3nVtXXWJVucwSyHYKkuxyc6fDHXjXYUMnIQ3NdKUPZae8v8vxy5y7h0xsJdpOvhMR OSJcUhqp1DZop5lsqtfKhWQC/XtZGK/Hrr/9m31Fk6ylnZ7zbfhXuViCX9+ygrO0vuzSQOvY JurxrMg1/laHyB0uNl82AzaWtff1cXpvVIVmjTdXKRwgSrBW1PGANZdxYaWK2+Iesx35nnan GaTx7sSvLzasF/NSaN5agvANGcMFDYvFlNl8Y77bj5LOKJSHiCsUtd4J0yzWe19sxYDUb4b1 loz2SrVsyVdIVIKhyWGtwi5xYSozT3nxAFGSqYt/ZWzbIWXq/ZV6tNG+l3RXZRgr+FsKe+Gg tZx/0K1PHveqEPxY5UAPzHL85z3vw6m39aGblEVlxmo7dqxBnUFj/+IriyVDy8NrTLJ0n6IS Nnbwfv6ifi/rQO5nZVRyle64GBFbNNbv/pN47Gc3SXSrwpn4/IccV1SyI16dkSQgzRv+jG/2 3Y9KWXnJbd8ZmDLGFd78lS63nkZJXzD0uPmM8SMsU/rSjSwp7EFltHAdlMiIpW1hTtPR9cII Aq02BKwLWrVOhEFCqdfmjWMKXJtLgmXo4Lp0pd3SKwq2fM+hkV3D8aUmVJcgKw/55n+jC16V DS0Vheh+74PfvMX0J6DwiYCkhxQPJLKy1TyQLEPkXn9PK/lG0AH2tITbZPaoWnj/OdEsG+rr qGbSeMjjuqOV0KXijL0Oboe4cep20Gu3iQAJZ6y5yPrLEnxt6tVtpQetWVzPbvR3HL/SvddC mKavhmH0rayp3eUmxzPkWmOI4zrpv88Vk2wwMrZ+9F+68mz1lYozBwLUNPhVMAr0mkQ4/f2z qAwT44vc2ucVL7YKBi16gad4xD5PwTBJhJ9fiPbD4nYc5ReZpRSRzGIemCNwkWRJUMmmGeNz 9QtPICjJ/VBOxrOeZ/T4lTPaYHczBgl49qy+86MIbZ4dISXk3DMp5HhyihxUDBzj+Ok56xy4 twUS+RhY3qodls4UO5KXUaBprpXq4OYCKrw5brXA3vEatzxEc6pRFnMfCRhmyNYcJGALRmir VeCMPLD1sZoKxiZ+hhDCD/+WYbsTkgvwyvUC6RjrCpOcQmMZ80TEiRIVWrC6kmS2g22GgLw6 hNYE+n6bXyphpimfCBdGw17sxw6A9TnhWCqXDLDKEB27a5l6MzIG0p9VwtlYAqjLxIDLyGan /lmSbhVay/3CNUCstfWegLIZjaSjG5jPkkGtnSIzcZZOaqkB+VflgQOxps88HUd+drx9UYxM DgSqm4126mRF7kgTdPNuIZ3J6RgtIxhwPb4DKWiu+AdpkJkSZwZBUEurxXtBdrAndlbSneYA KfHuYIgDCCOPe851oNuA3I9J7XVVay3hGAywOtUXrdDckCdoWx/uNLBZs9gVpJ3Ycwt3jW/S +K2v6ZNHQWsK0wlUA5pDsGwC0PMr0H1V4IL15a6OL4i+U+DDzW72fQXimgf5XyutzyhpeXq9 +7S4QxkS8n6RZxoXguYIKbri5cnmmIGHu+f/eL9LU3LuEbh6STax4DJegVWK9OQNgrTlHUXW hvtM8xPDUKHQAJTqoFKQN7wnTXtaV4UaI4s7yqC3O5ypL5NPAPvOCiJHBjWVxcxDndbHBQi1 HrshHNHqHkw5+yuzcSTg8c0J+zRqHJZmtMt2uXEQf9/hs/vcPJbMi36IxmKBqEA/hWksTyy5 JuXZKHQrX/IFl2HrXbLkLyaTXnBHC550J71ZBUnzhmaOKr3IfOrENYQq9FRBi5XGV/glFYQc 14GfmuoKv8S+MStuCrcZya9gqKNOjNymm2oNIelmK0AdtZZnBsAlP0BuhQUBChyLRmWzDNDq jKZEROU1XvhyYoCRyOc03SYbWA5c9OY274zvrBqxSbJpNJmiNyfGxBKX7patuLQLUNDjxrkc zJpFt+9nGTw15jA/aX2WTmXsK5/l050DUD0hwaeUHZTrw0wgk15vo2+L89WPoi9HqlC9WiIM Jkq4kZHKVyFvfgGimQ7OutbNehHZa8EXmOdH43trS9JGKHMCeA9+BoitWeuYXPU7AFYf4pVK 6mwe9GHzxzgtJeaVCmBiUGx9Np6zZRhr+jY7VqhjmX+iE/J9d+4ZJ+LrCkngg8A6LicsTKEa LEJpmEhrxxA7g8x+k7YUCIKKNTgL0fXNy4i/0Gs08v+BzgRHtFS1B9xmMlyMmD6Eh+AgMr3W vK2St0v/4hGBlKnulnMBIxoX5EzPyPRJD04sjiifinPwvHHao/RuG1OC3Ci/tJJRhuSmf8jA 5oRFeZwvRcYKAVSgYF2x8XNA3/BLMK1IBNIzjwXDU63UVGry79t36l/8OyKg/OKCz6i2UQ4N MdFvBkNq0SP0mMI/6E/DOVChOWHSTsDBWwJwJWrSB74Yv2esXeKb6z88qcFsOm017WEq22p7 6Cmh7WXhkE+YngZyyrOGFCmvD3x/zchUvUaPSc2cv8BtypEdBiP6huS/92QNOiQf5m2fplbx lSXLxbDl0Z3V0RQJ14QcUqXop1w81kmiks5yT107RXAk+jda408lJdQlC+lMWR2sj6+Mbuia KsXKmEaJ0ZuFG0e1EnxsP9mJiqJJam3X3n6CxhAp5sm4Nl6wqLZ3+ouN9ttyknni63IrDzWF 9FeTZmofnEZ3fPN1IByWZekVbhW0Zm/01vmmRycOr03tGebMW55uvNy3EDma3sDymUyDpJ+R 4VBAewFjZ19oV2khy94WLNn083OZUIx/WMlDQmauC9bIZTxgcfJ3S4r+Ob0lXtlnk8xyC74J Ix/MbJ1NCRhcZkYshpikrK7t3f2uEFv5k5UEhM2XPvX9df5vxsqar7H5060+79vn01EK0Bpl XwGT3K9nLXq7ey71y+XG7DeuY9RepKhOCXpMdlLSXfvfxwk3yQfvzGZFiFAFT7SzpGjnexqi cOwr2OgNN08P61WprYMTPSiwdXtHKRayUrEH4KSaKa7p/KRZ2ZBxz+KpG+DdQvPBCZ+nHefT b2uFR/Xp16qZ5MLn2a4o/PLIPl/aYX1V1ZhYAN4LLo5zHTVnNM4nzp5OstBi7apt5vAIs5+z 2Wzjo3Q/FjvZd/pylSFHBfhfxiPz73X8SkDvt/cI/yoEqsgP1KsUos6soPQYMR5xU6MzCoEs wlyo6D3tRfaVeDWPwjKKeu3da/j6jfr398VMR3Nd8AEIZ4zaXQLBN/Lpw3AcjITl6M+Nppf9 /DdtTzPphtdr3wdCUGam0j15ZRyHm2pV9d08WTY6iUyUvgqTZO+TyPdpU8JVe7JAq7Tfogx1 2+3GNUZVYffmRqL8xPk9vkBEAINlCK3kpsGrcJPbk8NyDcE15nsO796vY6sEampIUBRco5AT VlcpBQp5/2nbTnTe73Qd3b3ZKCj226tiI6N47LQmXPDO/VizAWszwgvzEI3Mj8UvFW24+37X Ff5Q310xoiNQZnXJj2VUhH8QnSkrYt+mw/rEE2EdhfT8oOgAZ71gOPKujPTRcovlkdhp8EUa CKXvn9AblGZyDBgXXVP0qdoVkps22nffAWmHHEr+ii+kQL9xPWjfMHzI4S7IzNOO6vvuPz9p cV8IErB7EChs40T3zlqueAADayALXxcDrsVp9XAkhgchezTsIjDDVIxzO4nhUhUfA7rUTBIM 7JSypgEfemQRwfum69Zuln2C7oQXpMxLDxc3ZSe6ND41BG+Inu2C45woDBvgafo53GuXtG1D LyMVqe9SO00bov2xRfX+vNds9jG/63RYUMZb6vuT/TQ58PdYAFiIIVPWfYoKXBCpulKJ+1P6 zSwQ+0mwgXI3xGyoyiXSFKGzHjrxbhub0uFHmX5hruGL4NA+FboLXCbcUsBkVPinfb+sal50 yumGiN/QqmJCelAbX1F8zcxhtIZBOQFFz28dT0vZ0P3zlzZHGnFVMYtQEgjII+AE4sY22Eb4 8/QrWcrYpP1RhUwDQ+nrmdNnHWhF52cneAGbrcGnM6a8lSRepIGzb0IEIon1FlqgjimifkYe 7r1q91dMWiFOaE8MJvzlAWD0IzjrT5PZ53oQNIKiunuD7D+iRrQbzg4ltDl6OxB7toa6K2H5 famjMlRuKiKSsTZ0I5K4BN+/rgzb1KjIhNLnrVcMm3U7JX6PbIh0f58/bKBIlJFKrnAomWLy M401hbVvhpi8/o2h9A7FoX9pVBjpOCSBOni/Yig+nwp5HpO5PdVsgLWz9HzUunU3bU04VyhV 4J+VJ8HKNQ6wuf5/AvcGCPlunPyVFaetTkho4wjvsWGhX2wtmacvlRfqO6RJxk3r+j4g2kJu m1VmKYPDRB9uqlbYZdTjRIEdquNzelfsbZDBOeeL0Jv2DoPelOqjCie3MgR7pgIRtpnGSNRE whys0nVF5coF+XomTQs6JF+gutgMPt2z4vKK9oPfzePtTNVa7+JGHzQ3mmHO/a/PkF0KTqtK Rv+xbS6W60ATdSJHPnwPRQUbFAzkkb95jVG/zp1aRGlFLlIpXgvdiCZf6VddPgj0+/0z6XSO iZtmILr1p0kRKxHH5IfbvoQd++4eVKN22UzcyOJcex5vVr/P6qxnRKKppwx+/u+zWWa0wHKF 1ny2Ly/HcKcGTMEgReSntAzeGN4PHkHibekfdpxWxR2DkZGC4EQftizVVtOQyrlfEqaxfNSB sa9LenTimUqIdwbTWrp/s7kiR91AuPmWy0JGmY3LkUnTwEDYmWXQAAIFjEmaWTx6AgEe1JRq oNC6J1xaIAbdP23SKTp3OwXKEgYHS/WyJstTdXiG11jNPwJcRIwyTov+vIsrMkj7bdmTjJgp fj0dGg5JKOJTFWnOCwCnl5HIQ+12nRXc/osIjGZVFL7QCOcAfU1BkQ84ZMe46+c54VcMLaab 373Tbgl80p4JAQz9IE5K67vlpYTXYJgfbV/qhfRqlQunnD0VxPmyezeBWlAFI/zfLlAc4sQS a7Qez9uxpuu40M1dZjTuNevbo4Gg1a8tFeM+b9k7Lst0ydFNR/m1v4POkNDpqHmHman4xVjZ J2A/weNwe++Rf/9Jv3ggBG/uAIjIb75WUyAsYWzP0IN8Zzm1BhOqruHWy832bstBNfAoElKv knGRnCVyCwCwBmdr/MUzCOpere4c3Io15yw6q/mv3AcrPY0tG6Gpn7PjyB/2X2USFmnG7gKw IofX1ptOR4oCsR8t5Ch6qpaIrilvrBXGOm7Z1NUDQaMezDazHTIgSxh97mtcmVXMDg6onwO6 BkPCyLc/fGD1iPpbfS/Gw+l8y6l/yd3QDH+VMkTtZT/2IqPyevkTvVbW0dZWbHVRmcEMuVlR 62QfWgcAjjGW6231et/MLf8WICCPmsbUSCfaee54t7YLhzX2lYrgIwydJBO3AtjvYtHKo5kp LmFv4Vrl1RBHwSGNjMaT0vRuQ1dpdr6seFDVJPwGfK/7HoziFF7q3tujEnnG+mKFONF8rTQG 8au8yvOt9VChm6p9iyOqE29pD6jn6J3SaE6F9/7O8IAHLOL1hLE19JgZ1vwwn4pYBobgG2Fe ciYn9UaAgRb1sVcm3l1uGsIEmjW5Kx63EVFgFc51yzc0ahGoqvLgfDfuAr9Y9Ijdt1ixxMys cxrHEEmGoaxORGfli35S235GOWtoHUIhXwhP11xyaf+4FrB1qk5Lz1E6D2AU48m7dx2aactL OLVIUUja/eiwWyzCF/QtYHI5fQt4pCrlGaljr0/uzP4bkulcd3yGCWkieb+UGZwW3vFtimvP Aw9mDl5sWW6PyhFEn59ixqVb579nr7SD4AcoDpOYy/EO5K36jj1YgsnaJrxItFV858T/93Ic A/llB8uy7oHSFoGzJylbmyMkpZyQHu0UcSVGcA9ESP78Mcelv0mtfa/2Y0ZG/gMsqOdKUtGc FaDfZcFoAkvDdeHYIrdiD7QbTNgn2oIg59XK0V9ozE0OTcyhIfi9gi7yMDVZjHawE2oyxhDj amtm1Rnmdom7LGOyYzo+W3scQBw6E5gdoag+rbljn946Y11eDkI3Kk9LJF+hHarAo/NmA9Uq Uf0RY9eprDjwX0npiDlXF69Eh28svYhxiS/rKayHgYbc3jU0o16h5BuvnXXPcXaJJfIVJAeO blwpKJBNRXNQBgskoCFjpKk6I65QUe7A3QDzW0UEpDqRPxJ7iXCR5TfZXWd9ZLQ+r0rLrOJP Z6vf/IWoTKTVX4zBKXnkl7dsGCqgiFJNfIDBFRDUqxExxrVaskIN3yoe4KFt6cc6FX8HnSp+ va4A+SufDAjnYcKQloQEjqO5k+lhhiKgpAM3zeOvGWd0X44/FbZZIfZ8oUY057mO9Hy7U4JG mvSe3lbN4m+fXeH2R1+HidnIKjzZA5gmw0FgvufrUh+PBAPE/D19tntLcm8j3uiUJk7P+T+J PKWcLKwn0sddRJS06sQRPPRNLLTPtobVF5h69biy25j7rDfiQiQljTtqE53Eg1DWHhxWsNc8 idZGiJ1Xv4SjQAma5RYiO+6odohmCXP5pe3Y6HXENHPFRkwHWK+Bhupmybxawvm6WOi99HzO GYIygv5nU7/5rfuoRlVb2FC5M872TTMaRoAunwNeKbcMqlet1oeVNQH7garFby01Oeidk6WW Jvf+jFFlp36tXg2OyxsN3IkTryw7GwplbmRzdHJlYW0KZW5kb2JqCjQ1OSAwIG9iaiA8PAov TGVuZ3RoMSAyMDUxCi9MZW5ndGgyIDEzMjMwCi9MZW5ndGgzIDAKL0xlbmd0aCAxNDQ3MCAg ICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42o21BVAc2hItikPw4M7g7k6Q 4O7uDDDA4O7uhODB3R2Cu7u7EzRI8OAJEB5H7sm59/+q94qqYVb36t69enfvoSJTVmMSMbM3 AUna27kwsTGz8gPEFES12dgBrKwczKys7IhUVOpgFxvQf+yIVJogJ2ewvR3/vxhiTiCgy6tN HOjySlSwtwPIutoA2DgAbNz8bDz8rKwAdlZWvv8Q7Z34AeJAN7AZQIEZIGtvB3JGpBKzd/B0 AltYurye85+vAFpTOgAbHx8P45/hABFbkBPYFGgHUAC6WIJsX080BdoA1OxNwSAXz/9KQStg 6eLiwM/C4u7uzgy0dWa2d7IQomMEuINdLAGqIGeQkxvIDPCHZIAi0Bb0tzRmRCqAuiXY+S+H mr25izvQCQR4NdiATUF2zq8hrnZmICfA6+kANRl5gJIDyO4vsvxfBEbA380BsDGz/ZPu7+g/ EoHt/gwGmpra2zoA7TzBdhYAc7ANCKAkKc/s4uHCCADamf1BBNo427/GA92AYBugySvhz9KB AEkRFQDwVeHf+pxNncAOLs7MzmCbPzSy/JHmtc0SdmZi9ra2IDsXZ8Q/6hMHO4FMX/vuyfL3 5Vrb2bvbef8HmYPtzMz/kGHm6sCiYQd2dAXJiP/NeTUh/rZZgFwAXKysrDzcfACQIwDkYWrJ 8scB6p4OoD+dbH+YXzX4ejvYOwDMX2WAfMHmoNd/iN7OQDcQwMXJFeTr/W/HfyNENjaAGdjU BWACsgDbIf7O/moGmf+FX+/fCewB0GN9HT82AOsff/98M3idMDN7OxvP3/Q/r5hFUk5dR1eZ 4W/J/zhFRe09AN5MXBwAJnYuNgAbGwcfgIeLFeD733n+6cB/1P9pVQaC/66O9XdGGTtzewDf XyJeu/cfIW5/Twbt32tDB/jvExTtX+cZBKD9Pf76rFyspq8fbP/PS/BnyP/f7P+R5f86/v9b kaSrjc2fftq/CP8fP9AWbOP5N+N1nl1dXndDwf51Q+z+l6oF+muhRe1tzP7XJ+MCfN0QETsL m3/aCHaWBHuAzJTBLqaWfw3Rf27hNbkN2A6kbO8M/uPBATCxsbL+j+9150ytXx8V59e7+tMF el2p/z5Sws7U3uyP3WPn4gYAnZyAnoisrwPGzsUF8GZ7XVIzkMefsw1gYbazd3kNAbyK8wWY 2zsh/nGj3NwAFtE/TH8hHgCL2G/EC2AR/434ACwS/yAeNgCL1G/EAWCR+Y1ec8r/Rq9ZFP9B vKwAFuXf6DVO7TfiBLCo/4P4XmsB/kavWUx+o9daTP9Bf/SNxexf8LU20D/wtS0sf13ZbwI7 gMX8N/wDgX/zOf6Abv9K8Iff3tXpX/GvFIt/ICcXgMXS08Hy9QH9zXi1gf8FX6u3+Rd8Ld/2 N2R7Lf93LNerbrvXu/+X/1WP/e/jXoPt/8v9Wp/Db/erXIfXvbL/V0PYXhv7r/LZXotz/n3e Hwjk9q/quV7pzq+P0u+A15y/2/e6xCwulk6gf3XoVYCLu/2/Al41uP4Lvsp3+1e/X+n/ys7+ ms/zd/2vXC+Q01/J/mvUTV2dnF5/Bv58jF734D/4z98cEMgDZIq4umRv+i7Eqi6k4+GzCKE7 0/6U4DzVvlYqHZP3qlOn609U+CS6msygLac7kaTRPvSNPQna2/drpM/eJ60N8OFtiSrtjz5P RvGqs/vtiCszOEPThSci9YPEb4iY1N8f+Dw7+mgGWkO3QnbLUuU6uvKiKudjPrgPSHnUD5av T4Qt7asc1HDLIT2VzzFFa3zUDyxZoMozyVrEI4dzYSJGoMe49EBbuL2bx8iZfiGVjWdA9D2N 5ijy1t1mj/mx6PWlUp3duQefEl8Xjxj6FmNiltpb9ChZFnfZu7Q4VjYsqtic2HCpWagTDejI WUvWvSpQPj69M473zShQrBxtbzYs1lRll0p09JuNWk4XHkZuPU/J3DObUQGis0rX4TOOV1TV QqZTsPCQtcuZMnt4Wn+CDUnILa0wXNdR+FHyMvcKfv7QIJ/fHE1Dwov/+/gVdpM8F71eb6AH ylkXFM/Dd9/paSk7hGy9G3WdMyH1GQiiUQrgGJslWc47OOOzbK2RoWqMF2shSMKy6FkoOauJ 2i3Zbi/Ul37F7BPTYOE1Q4GDH++RobaXHdX3XUNWzMr1QLMx6Vb8sr12MONyjx8o2NXyP+t9 OhnMEjXBEJ6oVIAMsg+p46kpBQILkyPzaQhawi1uSu6VifmnGmbL5iKQvpnViJol+MzKlM+c h0obukcooFVXTIMoxMUv2LIqOLQSC3oimSdmrrtlmXG4l6sXiAVS1fEVRk/JG4VCnPBo8SsV g4axs5ORd4MpMoSada167yzzRxsZUjV+ude8fN9DfGqgjPvaP7Orv6OlyCxWRKs5p3+heHBA lNvZ18LxFhV2QUT4ysYI3bm3TCFMufm+HKkrxtNczbN0Z6nbZPvtZL8xnyuxQ8zQnfLuSNxn RVenJTp5QVfLspjFoLkR8anVvLZe5YUowxJfvOYWUtiengXEr0ylU14a9JPrJByVh353e9JF 7rjBXvsq/FCLo/DtpKhLO5PMn2axTT3aynEK3PBSyglo04MwBHQFPnCvpHPJrS+k10POM3g9 vZXqzGOFpOvxd9KpTPzAv1yDNWqaD4kjilKWxyOjuRj4DLu0n6v10pqhaoDSmMk3AKurm0Fs 62OKax8SXhsXOBoko28bpggR5meX9ul4/wz5LhefVR//2VweOcMJZmUJJqkjUGngxQ9h7cvk WUxGVQ8aJPQ7yBDaMZq1A9LAlF7z2mCUJ5YiU62UYPHU4Wf8Ul7I4LGfqkO0+milIW1TmPkw A6tz3elPlA6XmIlkM+TEG9d89R9VAYI8ule+ZZkbcQYMJ16gUDxNeL20sTcEcLaNTF30W3s9 25zFWJSrnzTFdZlqknur0xa01uSSHRprkM/zW5ry/NRd74sul5RO6tmw4yvJfgQS+QEzqHk4 C4MPYT9+25jrHoRnFGxjGC/XlMQ1PeAY5Pg8jj/Maz2IZHlqBHsGZ9OOfShihxC3BUzfbwxq vlPsGUZZ6Oa/zCvRS6OczDHjnwGbYi+lWT2LPSqwfzWe4HKqlo+95i/A+1pfOPJzu6pr0m/7 l2kuxrKC8ZvS7UhMMnM+IyHl4xpfBMnCsrsqIdiVg1TMpKZU+H0EzsQOYl4vEJQGAoMs3hns D3zrt/jIAkKM0n7VhhUjkBpCNX5vMTb96GD4cJOlcpiwjEIYphfC4VLYHzribNPBBz+mstgg nGqTyk5vBoV0K84nNoWnYyZ5d5V1IW2P4uAobEHiyjez6aUR3G2E8Z9+8BW7CVpK9Bhp0w55 xoUpPqTC0/IRlBzimnEtCeRvanOWw7ZzYZLFXiJri2XAfZYgkb2LqehqRtdfWTDQzsPCa0sm aajOeFq1oW9ZmCDk1yFqZBIichjluUtqkW97bBhe0c0eFvOrH7a5/XFb+QGj3SyNrXCSnyXw J8CCjBFrGLFzwzc6D1VliuESno9D0xvQlaQSbbN0IlXd2LSLwgNB9o4UCtLTkWHnoOI7ypxs Q5K/yAks3JsDt3srFqeZxbXMYF1iZXQ6zs/mSwxKDtpGES5+AK5kvVhVXUoBy1yxTffUTtLv j5zKIpif3C1Nuv2lf3CAJXxDghr10IpsT73uk1SxHyiJ55+g9SRyOb0xQwccvFRZtH58Q2V6 0x5YCjSSgT1oTLS1TCwHmV/RdLQEHOo5ZjSXIDBnLYmxuhJp5N8Tn3ZSl++vM4rMvnFnImfg rKfcLBKaay1MFaSoBr2Xo9eC6pCIrHGBMRplku38NIxkQjxVEF5wrWsWe1lmGZ4cVxcVOyDk oXhWlr/psBfrDF2c1SolH7CqVGQpdJ0zbx99M3+SW5pF0AOxJvvuUpZB3xZxipRIFv+RG2+s zxofM2bJNpCPHE4RGWAsPter13kJOLLkdvcWQTMVENysdvPNmEBThhAr2kKYo//g4yyynHJq LjfEcFPFRhZYFV2SqGb3o3Bwz48i2t/oLX2YAXF2oz74kgz7h+wkOHPMcTzVVhYgVw8w78yN 8KRX+wGJ6nsXCZbS5HYHNkPi7lDa1oW5CaB76aoQGsovHrIqHqs6pt+RrdPzjLrKK3VMCZr4 T/qdPxl9kX3zLBYkIyzA9b0IFkkd2cu5pOHM11XeOFlhJaC8i5wnW65rHgn6/P6w/epr2Bde TyVAlPfVVVyhT66bMR1JH7N4GBERR97qQZIcZRI+VsHRm7QOACOHf1168twX5/4scdz27XnV l8jEoj51lKaACdNa+Ar20/hgqsAnT3F9hYa3anzSK5cq0R2LWU7mN1Ilhk/6XFzhSRR7q27Y eqE60w102Ic4cl/VigyJGvzsWtOqFAi0Hxl5qQt4gChDZpS/Ur4kIRm6sGhhBK54Tnf7dw/g lSBcV3K2qMh5060KTkKEaol3mAm12xOAjtd0MxxWkwjAIUwgtPfKCfIvJrE+lXcUDrDk3N1y 0ajypMra41teJqjFObphpnP3vi+BZ3RUuPIrcuZK7GhfqgN3twG0igsNGnE1TA2gl04n/5yP V67IqhWtnh/VrW1whNpotuukz+aRN/lmg5g+0f3ofnStRexxZcCyaTC7/crZ+K3Fq8xU3jk8 EedBXRZOjx+20m2K4Cn04KOwVqTiQ5QCNn0bymdFWPDFubz5tbnkAkuJMFIBxMQne/SpCSPg JFnuBsqu6LGLwa1XkH4nbgZs5eYnVZY0J87Ck6MTHIWfpck4ixAZy5Lu/iMXIC6aGIMr/wbd HuVJEocRyJjl5aZipxrhEeU4YMgo2pR8Ig0TNOEg4rQp9tvyqI17DinfInVI/EOa9LW8WLse ihFDIajYudwlmlymjBaYgM2ADcmHLncFJfW4GnFn2dRxFcK2hp+9wd7wbx4DO9U3u5pv2Ks1 8eOrFZ235mIer9D8u6hEg9csP16tUxItM+5cC+UchBNc23+TS1kjl86arkFdQMsFtFSwT4mi l2pM8tDI1tI2XbQTD2fMXlWZsinLfInbuWe2yVVZgLQalaSyyilVbkBkO2/3MmEfra7VCthU YLCVaw5pHRo2ZyTfYOHwKxioefd4l8yTz8LTWyU4bs90qEoV8OFg2y6ZSFa0iei93QHkC7cI 67c+yx4sVUm+zznqS8jecbT51KmXlFuhcf784zeW3QT3L7exCi9WPYfwpTnIK4SnVHGSULia IS9rEVK7I27NQXDCxmr82yf8siAH1aGJplG0B/9dvowKiI+5418EdO717EZSmqpuhjehYk4Q sOa3u3aWgnmPKX92U5CDEGYEMRatiZGIv5tvmofkJcd+zBlHqsYoC2pAVnYnlGjkK7mdplRs D1kTyH8ufYkgt9KGbdd2hn5WcCJYOZaoaTjNWpR/Ij8iO6U3x2PIIIPUEImMnx6DQmYU5sDo 2fPgSf7OTUHY/QIku/4gGLFHMYL5+Iw0mjTqWoQbZZLfwpK4JdVdv0EBkFa+1y/TNzbZ2Vuk vHMS7KKbFI5jKSa454sRyLDHFNVAPz5Z5almzuUq28MTbdpTlQGk1RfxAcnxNMkw96iJPd6y WRyUnFQ6plonCSaHnX5kAuiydYRF13R8kda7qE7/KgmEblNzez9XAP7W5H4450nxbJb+AtU3 fhGGTuU8tuWXoQ8N+hH5MG9AG3Oxhsi/fwVkbysUnsXc2PAOzd3fk8pZykZ4X8c/lGdT+XPQ GXjAe7TaJdU2p/nBvP1G9m1H3kbXSdGEDKSAcet5DJPw+a3BO6brExw4KV81ShKgD/L9jj3y cpO1K82Fewb6c02KZyCE5HFqyKZDfwM7CVZr4oCvDP1mA66o2LSQp3C6ktEoJGwHZwrGE/9u Uq2JxGGupkEIW9Oc5uUPE8Zg8nA5e0lWM5M4IEHbKf7LRM6mOaeU4USldQKt92H/JP8GIkJa 469NAyaQbPOKCUHSuGngojB2bc7ThOXovTMDxlS+/4efQ0aNzhnZQ2p1uFlHxIxAl1JPMGTt 99kJp1+tVA1Xkhz4TxboRTlFm1HU+Qq+K+ulIxw54tYjlsbR+jlOrmZCW9/f3YNbRQiNus4j sRHtJY1m00ytbxUzFqIeSO2M83+6LWMv0rGnJ62nJXylpDhD4f4x6/3rAuGp4nC3uklf0u1W 41SLGKk7wOYckcoDVs+iYQH9LNSK268IQwxpAXuDPCHB0NpGrO7CE61tg4roFyndDJVdk9ai ZKYSCwSWAnqaZ5X/KNbCod+1rmPnWdkaKVgmPzSQsjhHbFw9g94juHzQ4LH8MJnuhhScAwnp wqmbkawJsWBgux8ZqDkPEb+m9JgYGFB920FnAQH+1Yp4RcUEJasxlKtn/lldm2eBhZkg1DQc JyoQQQMmgvHekueCVyGfc/qY6I3XER//3kT9jtUvWye32wzlmxgKFKGEXASTAI+r9j2j+/bi cfn+loEcJM+KsPLE4M8301xos6rvWbzNT1TEvvtWmI31IIws3/mt7DnVfyOrgeZsf86Zjbtt /2iuXGDffBbQrTDPYEjDmIp6zm3Esq7lbbkyOXoxyhI5m348YXVYr+Y79+tMNtwLadY57MNi 09cPO0tWuG9KN+v9vDLkvR1F9CFU5ywp6aL4vRTVZOW/eBJZGWYPfBpOIG6EjBsiIqGbU5/x m5HThRbB/qnMChsbBCerjONHK+THt0vdX7Tp1rtr+EKOEAzbRdcZrs11SChoCa04FwRURF+p K6OKZoPdXXKDY9uwcBM+DODkrucJlL6Lxzkh+3XdqHjz3GuVv6vESVzaibXaZfLlZb+wNRrS JU/yyvPqoH7/9jv1hfe1u4oeg+4H2YR8xxZEhtad90gXe7Z2jFtWCnYS5jLItkilqlLENRow VQ06qDW8fekPiqG4pQUvWXLoH/gJDQYKRcnKB3EVhQNksT9cHNIsizDfWfd4CyiP9KUI71Oy mOTvUZmqNgSG7dh1kMHQB+9dpefxYWHxfiDdUERzNVLPOk5na0ImpT6nhwUVKhpSl7jK+Nz+ CGF4WWItayRH4keCjDPDVYO/rKro467WcL9VIpdYfvQnnrm8OhGUjO0XGCLNRZvVIw/1YMWC eLv3jJR2q+vtHRTdf7NJyhyCh3zGOz5M06T7pqF30ghIZWGG4tfuH2eydySntVBxopHrFXYF eZcfNaaYFZZ/xygDmAGdg98cQtkINT0dVu2Y7hWE9cAysNiI5s76YUF7hd4zHeQidSnCZmph Y2qZtjvFzmB+C43E/Sjs36fJaBYAqU/5rrjShUhdtYcKS4G3V/zUv2VGPsdZxztSvIGCE+kh WNwbWKZv9a6Z0q4I3Wwsh2ZyUk4COZnGIXEfGThPcrdhJPYWF5JtyQwV9WnsCSghgbrBSd5d LKB3PFrpC8sTwEO10pZ2GGDNwi7TZB1JU1XiDm0iMCGahHHnM/xOZzceqbrbpkfSe6WcEfsu 86CIDxGThlEo2OaEqEDX0fH9Z2OcSDwssajP54yo3PhrPlca+Ed1euzDZd4PLRP7B943RvVE H16H2yarQ6+H9jZ1Q6JyLzQuk7pBjoyZ1eUbXWVRHLr55e3iwjVPElyMzaxduoL7vrZAJpLP KEr3Q17L5aY7HjtF+xi/z/hMB/dm3jKn9I/PRQvWTt/9ZEIgJGKKbG8Wvqe7VUXWmDD26aV7 lAcF7oyg64S+b07ddiKSx23uoflJyjHOb1wkwiMW66fNYHSQ2qVKIfVVRHPAxeCD+KYZSlcD 2Zsl1oBd+kDXLdh1rxuTr7ifg1I/E55UOOnMnhXXKX74nNNEdT2Lb4EAcTVCoKFNbTkZwR23 otR1eP1ze0Frir3WcA3vIQ4S1Uuq5uwJAFbMnZuqeH72NO80UnshXxV6ZLYwviMQ5ZY6RHwe ORFNInkaMdM+j2vEuo1p1ZbwhajNPAsNPQBpYbQbHeXY2KiUYXI/w4HtS0MCEyQF6uMIOBbS nnShf33ZVaTC2VSBM3SfwvsSHNXvnUEtUfWRP99aEIAW+Y3wezqRaGlts4xPURJijt/iWkaN uVwZ2NqjCBB77tVr29gCQJrn+Lla72d7Zo2oWsBU5N+859QuXXvinLwWufakW7JfWc4MY/Cr 1wA3X4CsCduSbgLQ75NhrieNXW6zEcaxHjimtxXuNYQ6yAKAK7kI1nkuaU9mPDKbDde/7ua2 j049q1lY6TlqJZDo44WQWtRDn8NENW8o8XwfwKOtl4uMHgUJ/80MQ4uGu11WpPRR6laW5QKJ 0k+MOIasYdc3F2UvAEZBrh5JpFmX/y4Xv6sXJT7e3hdrolpSJW+TP0rtI05is7KlGjzO1MGa W+tzukYBuB6StwJv7aKB28Dw/tOlzER/R2VisCtaKH26qkDv1tVuE/kFPzP0id9U2gMCddVj 2Gqj+ptPEPKEinz1Un6CDMCpTmAey8/lsHbaBsQXxG7osfkXJ75yy5bpkQPi3QK7zjkqJDk/ gY1xj9RdV0+gIsV3FVNc3hm7H5TJekbFQX1Vbb/cwyI19HoVzA7PTlS60n5tmjdEws80uvN/ +UIxjkptcKTQ9i6Dvpk7/vZp11Chb87zUcqs9VaeqISbrI6KRG7TYTueMX3PzqEXh0TeT0uc wcd5zExLiru6zpMN3qQCC16bE1ZOqqiOYuCcZ/aQY5HJCQcdPZ6T3A5lSiRZ9noVgxAuaYcU +x2zH2SsuNwi5PiGfZBu8cy7AncTj+uOE5xgsqeQPi0W26S+se4hwhSJ7Q42lwscLDFcNwNE jiiFxUsGQ+77lel7y+zBLrIGNX+ZbXn1lmLcoJ/snkFMlgiY8OULNcz1MBEGJtVuTu86d7gi b2p327xi4wjbvil9zWxstUXvmDnhyHGkZVAiZkcqvfkYkrZ8Q3eSYYD1GOmMkhzFlQoDiUYn b2ITmK5gqGeD3RIwmRDaD/yK0wVDClcw4MtysK6NCz/q/sNmj4VcNLLaFxaJ9lOTmpvLQdLV oKGmiG35EXCfqvrCoKaViclAMXQEa+miKQ5Fi8/Bot/AVj6X+rmy4QyiaDbg2LjAMIdHgyZL LNIhXCrQ7/6HpT8H2/H4zvwltaoPKjn0u96XA59Z0u8lrqQDjlgh8LpVlCKKgSVzXvhO4thx J1Q3qy+6mlAGG1FFQXmklNq5VMkKUeZh+izpeAlV9PWqMf6hRK7mbYE4MniWH/xDDPgkO3rE Z64bo+mybe2v3PvLWFxypyYqNfVxGgV8DAkALGqmkYwOv5pZhJ4Eb3/066FYz3P9ms5zpQ5T WlJPNSA+o9tprqy1a0/OLUYCL/7ixa9NC3I+Nnw4h2aG473b+Iof4/1zMH1jq4mnrjqFikEV ndCe407gzgyv/biz1L0JW6WSCvMGDz8rzJNTNObZv1mcGayxVw+EhPxmbezSkk8TZBpDdEEJ 565FBDKD9oDmZ/45MmDhDLppEuFLSlS4TEpcKWLAbnC8cn2Jm7hi1MgXc5shx32MYHYTGYgz h6CCrRiy0vqFza+4Qq9J82S3KFzSjyjiShM0NtAPdFvvJg3xcUQxzTtggwFHUF5/+KkKaey1 No9rckwSfm7j9LCmvTJ6ZxuNHMwfCJ6+Rs1rYaPC53NkD6FyLtXz+1DtDkdxRkd6ej9bmHFY ZXuCIECx/8koIs/VPMuZLLfCDSNU8ij7nTa8ti+W9PSH1jb9FMz1eCNYfROoXEOJ+3WKRUbT SmBdfnN4JgeI4QpQ2BEqd/lQdreF6wWEI4dXn8KrTTMM0VNmpFdC/EhiFTuNtmvv8TB/oiY5 k6hjkRgmeuBNjf/x63NirQ19IOul8Xi4XcYJGmuFvumA7szSMjXdieF3P2Qo/SQ93TVzTvsP LMj2+jl05RIjpFhEZNdb2U+K2auXn8MPSPDcc72IfDnV6cWtdCQarmjkwihrY9Crd/TG/FbT uvSim3GWGGU8zmNThTsHGW6UpN7MbVGO4ueMPIXnUyKRhuoa4dAHV3IvVwlyhr8UWo9Evb1N VOljQmWxsB0FTrUwUBDHmZOXLJW3lsz2PRMf4IN1lxJugUiuPzi+1NFGvdh9AqbMCCoQErzr 6PC+9KyN8rvlFZoLo6+UlsXvCLjjxY42Dhn04oSCLsM46N3vxzYK0+zVj2N9eNgjctHKcvlG nQInm8ornz2SusQKMzZZOYiz/H5TlIT/I0kM/AVpxbVZ4zc/7PJu8MTUziR5ZhFIyfM6DI+b 5EG3ZT9mdJsGXkykTS16ycQOv1gdKI+MIk3Fa+hdigTq0o3XRY5UQCsXxfGOI9TuUrMIdaHi 6kaskBb4+SkcxpS/WjjPaoLVpwdFiGZoFoAXh3y0rSAZ8DXzW+b6WUkLwmlA60sEKJmLWHIB R8mmH6m0JfRFpTN3tgqQonnwBg0nV9jmcVEvdUjS7etKMnfOEDnBcy81kJWNCHiTE7WQxHe1 +1gdJh9uNOL9map7jjo7GW5ZiHJ/W95uKHln9KbW7yfDAuw7CMYN1Jzv1/rX70c1IcaW3Dx6 NrXgWWFyVE6DEaOzxaiLMTx637cTL0eq3SLqwAs0TQH0RrqMy4taECH4cPkRqpI0ERqeZapI uLlGrNJn0kVe2pcZCv1beFjpCWR/HmLEoT92kbLsy8lpb6NlYMCo2EqkROfySHKU+6/W3sod Mz6YPh66c8pbaquO8Ha8W1dYjsy0U7PStbSrwpZHgApiUkaqDXm7IhyvzrEXPTrMAXt9tKQm r7n7lkipWzatrEqapyKe9zK86gGnlEy/F8TC+SLn84lMwm36u2gp16SvyXSZVgymScm9CWfx eLfFi0um8+mBUMzTuGk85UH62XLO/QADjzn91jkhrxsllr/UrUafj6UpSnbJHtT9lvP34axP 0roxsEOxiYcFjUchSnmsKasdTUCTmgZ7XMFwKJLwnY9pht8+QewINqKi57sMUEeyxDMGwfA/ VBNyVhYHsxt2bjB2qhooqCKnoL79OE07PhyMT6U5/oZocW9dd4Po/mMhO41s0Q5Rdt8soCU5 NikLYAoK8Dyi6Jmskd8cLgbdIvkSU0zMx/8iC68B2QjxBs2nJ/A128Y21dj6B1R26nk8ZzAs uD5QW535h30P8vY0qSUwF4zLX4W5R9YaPz9qyUuYUJApQwUawJXCXhwILG9C7iJXvWTwtdzO XZeU6kryJQexL0C6zWsN+rXdvBtjG0DWmu6spSgpBk6HbyronNuY0MwzdrikBw7M0CWmmR1n 75smpb1EgHXCpBd4mBiqF5qc+roQuZ3LmQ0F7RkmnH4QcUn2FG3XdU+IwYyv19NTE3V9Rzvs EnOoVBh931XC6KA7dKLKVcyvJrjlsHcrTYTHTVhgMnxXKE+G/3NmYxhXIUE+QC7hctqmoROa wi02xPkq3hnTB7KH8WRQI83as+/A05DixjEftqMFpC2Sl/BwXzgrN3Jeyvy27PzT2QRDHbUK 9Dhf3gW0NeYX2RH4u9ADa77P4+vM6MoicQknP0rXaOR/wnou9BM5y4duY0186z5ancgAGz+9 h70isth+Lx9NbsX8HakfGvKaX0dIhtuHueaiTiOtlXDsBPfXlbcQRqhygw+zH0P5V2JUYyyb KY7hT0yeVnXQxZSXOBlWJAZ44Aw68r1v6Tw+hb/G9/N0EO1Krz0IaTsHpLAVn7ticGxT5KH8 so6h1pROGVFymxGIWZjhwbyzPOmfjxmW9Z/SPySsn5wsEOYZ124febnVLcb0ykYENCk4tW0N nS7Maa0GIzEq+cqjGSVO+rF2XKIIlhrgjOb+Wl/JX77WYN+MaF0XTIvV3c+WBgeOknBS+Hmo O313hkKl4yJWJtsuy0xP9N0hLLM62C7LM2LmAI6MtCIZZ3SUPn6ZYDfkubnafV/FWNNHPLXu r87MFWb7fXkV0p4zwyGxWTJAY8dNsCmW50S9gZCfU3qoTwfM857sZW3l6Wvr8YV0W+rs7p3s cyK9mHsKF2QNvEmDNAeR5kibMcyHQ2tVkF6iEF0Aa6y01tIR4/WHiOhxIcxM1wcJIEdWewxC 4hPEYEBbZkmDgny0dtVTHBfqk+iauFjudRe77zrJ8wb0Up4tKyE7vQGrEq/HwniBVJa2uFsj c6+dRErRwDSVz4rBUQzCfLzo7MAUNfrgqPNdCwzgKGQ8xZymuuvDmnErSC5dR9n4HVnZzqVh yE2lfyOn/dhPukmkURu3cxXzKdRj/no2XPJ+qPkp3P6t0xdpRK/rjvbbSBdcGBjXqxbyuZPS L/s+D+WSsoaKJYvHkMJge7j24gOqzPLarLN3F0XLv6jClzzeJJY+9/YB60onCSINiL5zwOO7 9754c5Hsv28UPWNG6rHsUA1C2I2Ya3SPYyCQWWL9wUoG2QovGewUKOYIv6AuMcRtPHzES1ac x/qddWy7qahWav6kid6XLTXh8Gw8nbNsEP7sGAouLKITd/oCQ17yUiPlI2SI+yw8iAFX9Ii+ K87QiJHrE/1nZOQXN74DZtJNHM2FMFIHj6V3W77hOoOV7WiXph7e7/SWbXFjvZGa/ANzHOM+ oGOaxDrvbzcKRQqG7SqjPgb1juPWvKtgo0z4OW9jbXYd3TR1moXKpJSpSk3DFdIsGgJdfkET 0Xx/ZW7uEV9qop1y8DWRVsGUdoF+5eMecfakmiKn413symi9gx9d71HOw3eA/dt5bYeR0Df1 tFjN2oonB8SeIKibhjk5j280a0zFEu02dhRBhwYyzMY3iJNCk14f2AyubM9/NPKWto07VmUE eZ3nKCG5kWjofAtD6p+Nb2JvnxOjPMoOaPhSBOORe458lRnqxTWWqJU3vdlTboFH5a2KqNC+ w9i1t9Xk0DgwTdyKu8OayGuQc99PR/NySCbleZhXqdFikgxPjm+AK+mBp0xbdxQg8sTdyxWo rpwexy2xc/11zxIc3ZoPeVBjbHE89PXtgOPiDKY8axe9iXcP3fkNHDrBw1jt+ojsJitH3OdS LXZLXdrn7siYzcWLAbrYxaJjU8XkLKCkNKeO5VsDDb0Pib2yxnvPZni2wdnyAnfs9vbNL0ty JgL3SoubIgFDxeA8z8GLgy+2zjseOjFLGaSh67zHFCMhTeF8VDHZN2PJO24/3zPhceNtT9bq 9LJ5hthZkrEMCs3q/hpOvi+VIZCrr+6Qir9PSG/zFlIu8wpv+8gg54RUT9rlXmGdt9Dqt07d qvFgDKB/Sxqm9OmzBak7Z1m2aZu5+8WoJWLadPp7Ftfps8QDjOE6Zh5t9BGXXcOz96OMvN/H fI1XeP2z50gQA+ch0KqAxLw2Ir0xsGEqVcPeHH6WF4zCGrrv+Ixw4tJBjMWMdhLbfQGpsmgY x9V5bWZH7HzAo0DdPFjjJAlUafqXgKHUfHwL+SCENtRQrDLXcdeoZ1Nd3HfmCt9+EqJyWXub 54b0DG4O6alVWZGiqohzikvEaMUFyz/Ff/o4Y5HrF1mhknO/4q1B1seZM0F48KGKfxCSogH6 uOQ2r5E40ao3vvvy/eqwOYxQfTf8kAYYHSfxci7TmBXbZ1udP8klb4LknJInaVBRF1m190hr o7Hba95G+6MPT8+5cXF1D6I/cCZbq0mxJJ+T3kiascAl79wG8lQ6CzdvtEc7/3pKYKKbMS1x tDu49Ie6EWXkYhNO3PcajUiemKxp+198Wm3ForONvLKeYvG8/X4Qc1aO8YXUkfhQjXmW2hSF pY7Eo/gJMxjVDb11mtXgq5YHzQy7CTTw23Zzep2y7nmmwbS52S043dWSl+ShnFmYOJaSj+TY t586ERl5g2lZednVa4lPHvKqxNToICCiviR7wyJwZyJ8TLTdoUVFgaKOIoldOOxgQXsU0fku +sPNO5C11x35h1O8jB7ubRTFUzDLOXWBOStEQgxuKKyiRclzD85Ww3wCHoDOmNTcGBLdZIuA oEAacWg//NE7JLyGJAJTDl/YFcPJLnIHc+WBZTw1wCi7fA8piiob3zN6x4JOipLjXMkjpkLp i17/dOxA4R5iObdYXtObuzKqnITnj+NRGVqf1zoPgqojqOKp2uXnvpyyyWUOy4l6dtuKFKCx 4gRJI52N0aVZHzDzCS6Xr2NT1Xefdcv+6iowaoQ0mN7F7jP8WDOG+DyPk4ieDGXRSWh5t73p r45K3rGBX4J72bFMcaYvN0nuAf6e1dPrhJHGC57sjiVEM7awH8cpO7M+uWiUUj1eAO5gaNfy EVIUHjhoRznwx/VFBksP6boYhQ2S8f9cn6Iox3ZV/9oYGPCNaP5geWd8W/zFtNK95n7p7UOZ mJPOEJnhByzkfeLN3nk4ennPKRMjujCnpqi6e4rDznPEOvLK+TwxCinhnIvgY2OdMTklY5iW NTqqs9GT92Ora4dpV5uwnUN2u534w81Q7IUj6GadpcNj99fsG997QNND91v8ohFkHJt55QL1 yG3D5VPno1dJ7HKpfZv6nA2h1i945DEs0zY342a1u8m2pqGEeZ91sq2TJTOobkvsK136ZJhV 2a8Ky7hh1KWi90v0RgytwZ88vwYDJS00qUeDdsfHs/QdxVL30dmMjN/i5FwRVy+H06YwHssK ZTFrNF8RSVyp+5ZhiLtESZQJWJK9AfRKL59rQGvBMAtS/qCAWdrlaiTcfB67xJlkiWavUVfN QJt7L8jBTOBEd+LbRrTwfrrz+KncNhemDE3tkMnMh0CKhy4CguwBCgSbNrBHsQjw1/lU2PvG erh85m2SlT/WBNZs88SGFCYoSYfU95N9+kvvd/L2GIHjrw6R3SOeguPs4ufvcLWR9ly8NEoh Hr+98GfpHIhYh8rnxSlvys6rD6b9ylbqKML0qpKAfdHgToU3vRiPpq8eEIf0g+P1gyMkzjR3 1PVWvRBHCxSC3t+hK1VNoJXovTHM5Yr/ZECq6EDKDCsgRo7eDfGhlp1shfvKKjUirbhCqf00 +7NG6Wmzt014yNhhY8lJer7fJFAINW67/p6tBiId5vaIrX5RXJAvfDRHgLAdzVbO0knYpsZN 5IItymfKM9PV2zmVZBSO0D830HqvzsH0+otFUX4zkWjqbZXlBBkGUVKdr3R5SF64C80iT0Tq PN94N2wqR+FJcjPjfmqhzTsMDfxmOZ6vuT+qhY5xfgyRrSn0iHeqQWDWMuQtHmgZBRmCaz/g JkQqh2gyPhd5o9hW5VVjOIaEmW0bOf/Q4lISXZgb+XjNlXbv0IrtP4nH3M/VrRwfsy7AF73B Y6DIbgPB2Lbpo4kh1bSRom2GovQAs6XfpbL78UIr4ZC14g0simZl4VE2NEstj8FJ41WEjt6x iNu3Scf1A+axt+4t3JcqHUc4jJ23mDpBXkVVLDYR4cZedvkhls4ze8We+mkfCuv9iuycT9vY RnwZ5jyapcmpnVQJCwfXUrK8woyt3KUkN9e7vkgVnHZjBdOT8tYhdo7I4bqiblcXeVWWooRZ tuta2SjIzxofuO1BdOAmPlPYdHv4HHzjmdS9U9fTT/10NqTQShBOIR0qGpcSEwo3Uj2ERR41 Bq1/XsPTV5S5tNMT38iyizd6WAFrqDDaGlrFsXtAOC5PPfcpdU+A4wUbuNsTFIkbkxU2vMbQ w1JCapOrhRSRYJYQ0Z9eTPSJ6ErStyYIdrLIPZs1mIrRrubuJKk8PDSktMIcaHlCAhbKrtrg y5yj1pgIbLtVHuAwK5ZTtkmHL1XukVWRLhrH1V9LBiDIf8HV2P0if+ya1oNO4zGdqfV1MVyj 6lGRhPGkgs+z+nLYgK/fZps5Y/zpC20Yba4uJZYXPm3FFYF8Gy0rloeZ1Wn6ThWUlt4KnoP7 CzG1E1YffrCPOsEJ4MF/b0Pgi/P3gpSf1E8vnti95989br9B1r6r6IqG3xCuEph3PZevmkm/ xfQUyMT3xOy4FrCexpz/+HnbVZozYOBwZTiS16MyE6fckUb519SBFZL8ujA9BJqwO0LrGO9b v73wgeADsXKHip96nZurOsH81kSr/YYF6x9pT7SGsR2I1WbZIzyxCaT8rdJHzlU5drSXMgsG AqVmkTlwmj8muxQtE6vPsHDdnVjIP1bJfunpljqCIVetZ4sukTpeayGEy8dIiKZIuXhZaOn7 ZP+2wTGu91jFGoljNsdleAjLyd2tJbiw1FNePdSsO+biwt0q7awNqW6ewUxsIUsHTXGe64hS 4mEJBOVxDCTFEw+DiiciiJ8FQcWv4MxDMgggt19H4KPe7VKIIm6X0RWa6nTVvvXC2cCmOsUL 482I49ygizxOM0YQ1rTVCh9rP6HGFepwWO5wH/Z2UjLi87VZb6vlCLEliUU4FWAOaB7qtTz6 lW9vYt1A8Z6XGG2cgbTiXvCNJLK7kzpunuw6iY58alnBw8iBPDnsj7Vhn3b5j91qJc8e3HHj XMDevgUITspBP6V9fw8Y0lZ8uutw8+RqSsFVzgDX06PbGI5WQmS3flyVROqRquF+6B5FdXpM 4mTxsvcR3xBtzjaE+h1cp5GNc0qHiThWqAEqj0D/gZWBuTi7VErGAq/aRI4YS0zl+Gzkmrry WFg/vpegUOoh5KwrlgyAeR7PJR0FfctP1LjLzII1btluAeAVxzDpLk+esV/2GbGfHiPikuzN 0Yp8efG9ROiUxg5EQxxKdI1Ka18dbtscoXCEW/XXvYpwI7Hw7FN4RzneN4LdIEoB74QyibRJ oEfvm0zSE9izT3dQujdvnrw1MZ8R34nVc44eDzfI8tfObLTZnB4cKZlnp2kE02+f+BIPEqGx 2n8SZS8W49ASYHqDJg6BseBPztoj1G5IfzgqKWpbUX24KXsUpZWRF/7ymamL0jOUMrTNvbP0 bkX9FituIMchAuIpNoE5XlOcGBpEwYac23VGl0+Dy6oqHZAxK3/Xx9kBwS92bioaxQqpfd1w 8iT+QT9iLVAqQO7cWcFainf3rZKTTqhftWf6PD+vQOAettnolGdKRRGdPFW/MlXKMsLaPiBi auTZM+v0x1xp8uF+GSrmAguS/aTO+zFDJFe1+JL9svj9Azeck3i+MoWq1Uku/6ZGw9hFmTMy bG5kJW6jijaa9U9Yqnnh9Aj8/NjnT45+jIW5TGAyZtzjBn99K7csNE3kuVSVwKtxUblkf0F8 gjsBiQg+ZZ1DDbHzrQYZ4NpGmre0/9a+NQNB960foGqgm0Y1aO3HJr6tU5kP3LbulLjFgOXA 8Pzy/ACtPK45Hl3VdvIZJXVeo/tqCV/pFHLJrBcLnoScXKvYxfuNxiqDMD1WGxim6Dg58NjR rTDp7cVW1G35MsGkwEJ+PonJzg0bLqROZaxz5xz29Jkqyvtty9xf5E9sB+8bN4zlCOwyyhZv 66S3cchUxTvjfm2FUcB/3bze5/I3cbpIq8gTJFGA2lI9S6SuQEdtmzR70Cz+ZPnQSP4GoUBA cXJTsTcoerYHy+FHeUq3wbUqZMM+46yZ2U7yYXlEE2q7q9Rnw7u3RCc/P/o0xL5M2SPEZYjx 2+a4RKjf1MTuc5+A3H+Q2H/C+qqRcEBh6Ki8hk/UiDUQZ5BY+0a48RGlHsY/vfYzdFkWk2hQ 1nOBBRTF4VQ9dsiE8e2q7ZokjCdqSn120A2FLAvUlWti7Sqx9hhDwe1PWU3gzmKXu6O53IcR stWXPYXKo+eYTwEWMssT1USSm19acIGE+biW7tGf5VinZbWo9dQzast8VtHfdAsZfF0yvaBl G8pPeBt/mPPYLwNfmeuHxMpdrCbg1+aGrcimkwcvJwBuLsIXWnfBpm/8LDTe2MBi//Ug7vQ6 BbXRkXmD1AGPx95yzstzyM1W0Ea84+v9u89xef1p04VxcW8zpIzfcltgIVwHFNSla/pfBQ/U 3Ifun/HMHDZEmQ/q1sg9Hl6xc/xc0NJLygHMFoUY9BGYV94pqpgSXse0JTzeuPJaZcCQh40I 3MLgERHHX00iJ6B7x78/PnLZt6U1DlsssOAZy62iRQ/B5OW2cUqDhKq+Ggx8vqDmmKmrkvFb ISTVnPJoZLeVxIaLU0DXyFs1pXscR2D5VVh8LdWiRKBw/Ql8SDJjh23ELpgptf8BVRnrG7iX gNeC1f3YP+T0xiXEuoEyyjznp1FQswbvokuvwTkMDa6NM4MDLEIAQmBkF/1icWVj9Wrdtifh PHS77t384Bn1/BgvAu5gM8tTqnwqdkkfu/6aU4cbHWWWTkkNjWro2q2xC8HUd+CvqdJri0lY 7tGcS7NjiBC5G339ppdBv6MIThG5LYlSTXw6pL6b7g2vjUdS1WtclyuCD2aWR/gy6CRkF/PL 7JJX3u2ytNa81C9PCo+D+UnFy0BGenF0vmCZRjv6Mzkw76TROGRjs9x7cWip+Obl0vRmVHv3 7B9NUUn0vHanxMnVHztSLMWHaDmz7c825nSI5hc0T8FVW0zlc2oMdX6qJMJqXgLc6C2FgvJ0 uo/9GF4tQvVCdp9tVN81aHqCZINaEdngfzqyWzFouzAkUYR3EEYjVt4nsWmJmhy7tCbL1qv3 fjXJynwZ+fgtNBgp25sanIhb0nEhNR7c4qJRVSJGRDkzSzFpxZnFrHtqoJBQy3aOskNz3pdw zseOUYU1yf8FZ7OkjugFcJ23zXaIB8NF5YUYL6+BFrwFYUlNPxkk/j6gCQN5zvXohV6ZC4/H y4d++6F3JORN9Uye3QefIWrzgfppM2MRPvbe3boJhNTE+q92VNfrlA1DzfVIubEV0yjUkv7w khhTBVLxyyTv+q5fbIvDBVcQIF0iu1BWg90qLaNGZx0/5u59J+D3njIPF7bvxZYsIaWrM12T rgn2wfopPQwU9mJXsgWR6KFQo3OK2F+Nvjl129ARlU4+Nj04FvqMn9KYQqYcAjZfflQ7YKlN yqwF5ozBc1c2R+CbeLheByPTmx07Y6cqugzSoryTTIqLhDSWaJgYS47CqnrIOBNZ3Jyc2hoL I7VBAZcyRRbuPSPf5txY7Sh3dLBtRxg0LuP7WmeaNMLU6xCOu1/Xaqm06D4OOz4THQx6MmTc AZBPsSu5eFZA7QPE62GRT9dtZ2zgBeA4IQw8exxZUAUQTC+EW18ZZhqkWfgyfq/AUOk3VNOa ku3bH7ATJ5vounLakz0XKXyAz27gCw9H3CtisudEFL+Vo/tZ9ZfAmkxIQOe7aOqBQBjDUFX4 A5mlCVde8mbWPXat0Hg3Bp6BdqSFlAAJu+WCMQN3WUQMHqgCZjJMtbEgXaRLY7ar09KurFNw YovjnhUIjxVSKrd7kVTJTG2T6+n+smEtJQ6BE2ZpeGXTIIbvmvJWf6sLFSleitivCKoU2uRb yJo+28sy5ZSTPBmtZgGXZrtGSw+CEcU23AieX5yhlDd/3BNYBBFXSj+JN8KuluHlo0tN+Yl4 CPikVcg6SKV6IWcOm+HA//Y8NVcK+w7L2v/+/wC+lDu1CmVuZHN0cmVhbQplbmRvYmoKNDYx IDAgb2JqIDw8Ci9MZW5ndGgxIDI2MzUKL0xlbmd0aDIgMjIxOTcKL0xlbmd0aDMgMAovTGVu Z3RoIDIzNjk1ICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjajPcFVBT6 +gYK09LdOXQ3SHdLd8cAQwlDN0i3CtJId0gIUtIt3d0d0t1yZ+99ztH9/7617l2sJfO89bz5 G6SlVNNklbB0NAfJOoLdWDnZOAQBUsoanBwADg5uNg4OLmRaWi1bN3vQf8TItDogF1dbR7Dg HwZSLiCgG0QmDXSD2Ck7ggFv3O0BnNwAzteCnHyCHBwALg4Ogf8aOroIAqSBHraWAGU2wBtH MMgVmVbK0cnbxdbaxg1C89+PAAYLRgCngAAfy9/uAAkHkIutBRAMUAa62YAcIIwWQHuApqOF LcjN+18hGIRt3NycBNnZPT092YAOrmyOLtaijCwAT1s3G4AGyBXk4gGyBPxVMEAF6AD6pzI2 ZFqAlo2t6z9yTUcrN0+gCwgAEdjbWoDArhAPd7AlyAUAIQdoKigBVJ1A4H+Mlf4xYAH8pzcA TjbO/4X7j/dfgWzBfzsDLSwcHZyAYG9bsDXAytYeBFCVVWJz83JjAQDBln8ZAu1dHSH+QA+g rT3QHGLwd+ZAgKyEOgAIKfA/5blauNg6ubmyudra/1Ui+19hIF2WAVtKOTo4gMBursh/5Sdt 6wKygLTdm/2fyb4FO3qCff8DrGzBllZ/FWHp7sSuDbZ1dgcpSP/HBCJC/i2zBrkBeDk4OPgE uAEgZwDIy8KG/a/wWt5OoL+VnH+JIRX4+zo5OgGsIEWA/G2tQJBfyL6uQA8QwM3FHeTv+6fi 3wiZkxNgaWvhBjAHWduCkX9Hh4hBVv9gyPBdbL0AhhyQ3eMEcPz1879PxpD1snQE23v/Nv97 vuy6WlqyCgbM/1T8P52kpKMXwJeVhwPAysXLAeD8a8n4IB/8/x3mfw34b/F/S9WAtv9J7o+I CmArR4DAPzVAmvffOjz+sxYM/zkZRsC/GVQcIbsMAjD8Xn0jDl4OC8g/nP+fD+Bvl/9/e/9X lP+31f+/Ccm629v/rWb4W///owY62Np7/8cAssrubpCzUHaEHAf4/5rqgv45ZWWQpa27w//V KrgBIechAba2/18bbV1lbb1Almq2bhY2/+zQf6cACW9vCwapObra/vXYAFghA/s/OsjBWbyF PCiukFn9rQJB7unflDJgC0fLvw6Pi/c1AOjiAvRGhowegngBvpyQC7UEef292gB2NrCjG8QF ACnPH2Dl6IL810Rf8wLYJf4S/YNeA9glfyM+ALvUb8QPYJf+jQQA7DL/Q3wcAHbZ34gTwC73 G3EB2OV/I24Au8JvxANgf/MbQXJR/I0g7Mq/EYRd5TeCsKv+D/FD2NV+Iwifxm8E4dP8jSB8 Wr8RhE/7N4LUrvMbQdh1/4cEIAwGvxFEB/yNIJmZ/0aQzCz+h3ghOgtHe8hw/yvh4flL4uDw 2/+vqbNb/oZckOiWtiAXkCvk4fxtBOkp6HdcSK7/LOJvN0hgkIMl0NXmDxmkeMjG/Cnj/kvk ZWEPdPgjNqRjVr8hhMnqD/iX0vY3M/df0ON3Kpx/Cex/6/8yd3R3+SM6xMD6f5AL0nNrkIsD 5Fk1t/+zPkj6v7PkgVjZeDvZgMB/WEBktn9ASAvs/oCQrr39A0Iab/8HhEzlj4Ihjyb778i8 EFcw5Nj+0ENa4Pg7GYiz47/UkBqdfqshwZwg36xge5DV73nwcP5H6vKvMfFAsnaCvHqOvwfO A+mPk737H734q6XOvzcKwubs7ugGgjTsXxTcPL8V/2bhFviP5t9iTk6Ixx+T4YR09DctL8TJ FeRg++995f3LBuTxxyB4IUFcId9Y/8sf0j5X+3/tHSekyt+0kEef3c3GBfTH+kJa5ubp+IcD JIb7HxAyPY8/ICQzzz8WEuLt9QeEhPf+A0La5fM7OUgkH5DLP1T/ejgt3F0g03H7+6sNciP/ xX//+QICeYEskBdmHS2EQu1qQlvuvkqQeLLujIpM0e7opjKy+i64tLo/oL9KYqzKCF5zuZFI GujCXN6SYbgWX6R49j38XvsqoilBvfnR78n0k8bETjPy/Dh+31jBocS3XjIkUlYt8V2/Z2c/ naC3sN+h29/Q5ji786Or5eHcefbIeX3rLVsaDp/dUd+teq2I8lQ2yfpB+71RUPE0ba555gwh FYIbKxkiE/aZF8b09c0UdvbYC8WbT8zI/kcfuAt9Dda5Pt7P+KyUa3G5dhDREBkQksFeYw9P 0PlK7ie/IZjzLSlc7pv3+i5cSJGNxpKyzIrJts+VXmWrEQNu6K72GF5o49zOSQKE0pP04Wwn VJc24Jq6UKniVTWbxuC4VXO/BZHtt1lJrrTc6HRa2aWQLgpMfnsBTKPp2xwGNnb6PtY6rwwM 9rHehqc03Q00DG51+usWi/WKkVp7cjLJ2BhGLy8JppOlwJe5jcB06IIUcDFZFj2S+J/ggWHC vsHnkg/EnJsFHBwG/PDd0MOkJ7w5fucf/SvqzlTa1qex5uw9sY1DXkJeq7yYt6ecnRUQ2XDL mGWEM+Smy3RG5a7G0qsL1YDqpkPK2M/WK/DZpEu9KZTiN3nnz3/QFPIoyHXvzFUORBsFe9vd C+SznehUaDfH8earU24fxbCO7NcF9UuGhPUI3Fjub958+SJpgnfgqHN/VuEZKTnwcUOLLzQ3 qk0jMLvDVTVNTiIGpuh2a6YbyZz6WEvSg9KhIRZDV0vkYWuko+jJk6VMQZqWvnBBuVfxQDjC b8F4Xrqwm+hroDh+1HVDIFdNq+odAxRqBubKR9qM3SVYatPWgQad81/EkiSaWnd51D7rUN1z kyNblEMTWzS+9hVGxTw9jQAh3vdpsPaf6CjntgI/X66JMLyP/mUV3biq7SlRu0hanT7dB1o7 6h+Gk6R+1crNgSs6eiQPKCilz1hVKmTGfZlNyLLb9MkUf6CIbRSpdDWqWcW9Fg77ImLUoQ9N syYtFqn9E2l89+l1Uvakl1yuOvjHF5LP0UTbtlW0s4lZlHMTyEpcUATVhlmfsa62CgMYKd9b hekFI1rsY8UgQm0Jz9Dj9tfEJp9r4Khxy+RShrIKVmPRY63/GpdAf4NRxQa/0FMj9WYU6o1b GRRdty8fQtzramTqIJ3x7vGOw5lZ+RmShMsY9tJBdNk5a08qWd7EWM9zzUgav6qXIEd14dG9 0RQUlAmzd/XCmeScHKV+iGkvws0HDqe1DffzGasDNmerOaFrFQeBiHV1X7+miw0QmYld8iUf 4qOYDufAGya1XfJ7qQnzcM6QXYq4jd3JQy1ioAm9Tvve6O+i6M55wP34WVsKCt72M36tvFtF zcSU/403Ifnsr3cW5LRGa86ngUZNTbs8qjwelIbpprcKTXlfT79VPeH17VrEEHOskX25UH5z r5ytz1E+HOvh+3qNMHHW6K4bAOOS7TzwmYqbSOQWNjFTa1JfkW1ZkfDnAGMnC4HcoKIvMFLK QFIuqxWZnMx7iQE9WpE+vJtLlWNKJ6XytYIaDY3948FDeSNrAsG6YQfh4TRoZCDm7gcxIpHi 8BwdF611onmVT8Ttm2GiNBZ3x3fK5Vw9hD6r7vFpORHTr5k+NzMVofV2oX2ZeBFoHy1ZE+vJ V0zEt2AkHBq73TA6s852q6ATK936ONZz9QhG0Dr0bE3YbaHJsVQxkmpMLxhdVL2ZHRMv1OXy otjnd6ZUspys3CJxPHy3zanD/r5fUkS8+urhmJIjvlM/19Hnnub4fvz2RyBtT0X7xACe58bq BpexY1n3GqDS9FlMwWYIw30/V9LhRBaBQLCOEx1xPtkSsbTf+/VtcMfiKoBMFq0klFAJzKt5 4UlXyno49bUqS87nrkTgJ6FIP338NsPwc4vCk43KQ+2s77YqNgA9lRNWycNixgEP3rauqIOu n0r56KdDj3iD7kx4BWFBhcOyOS3HQio804PZ58NXPbkJawnsVtfdmfattGoyXLmC5DoSjJqS Suy7wmX4J7w4ZVJZEvlrt5n2QpW+Qx0oDNRN83rwYFmEeCrEGKhUqFB+X415x3iszh4tAoZt U90zGHOJXwGKfo7KKKY4s1Mpulhrv0g/taJ5byvvv7wO/JJTbdJ6C3TLokAUV+U8zGXPhJI9 p0is5/Ymp07bssBQVp4bl+s1eF4xhHUof2nyGXsvG4CAhG1fdv+FquuNaCUIbl5HMlZXktR/ T4cxDm5Zs3/Jlogl9zRotfhUAxu/Eb+wtVn2ww/Ysla1TLb9ViW4iUCvO7giQlPDUT2dSCyC H5dX6jlVaFpqL9ceITn3yKBBlninX4vEIS4BNgkPjQnu+Odxoe/NmO19iRFvQeq3s3Gm4lYE r7mJ5dfUgB4TPkTaI3imX7NHcPsMvnCSM5Vt//iAXRWrzPzD3CkwXMh3pWwYKahCnRt/X0dH aD63ZSRyCh0Nu1KVTTVr3ZalhZ//yyx5yFF3eJh1toiRyLo4lez6g6LsnVau+WPqpzadoI/2 DPbWlZ2Zi+aTFR9WKBv3y2aSZ4aMNp7vgTzqnARfh98BvghsOusUNhYPFwLiXU3eHue5Wn5M B6P7fOpEfFWRv1cgOEuqlOVDZPwR66zMBSW6MK8sxENFui1GWY5PgEZByfYXXYLEvDXJBtj+ tTd0xBukWFnVugthRaSdQ7WRAtWPEhKEgx7hCQGrk/Z5dHt1d/o7c7X0C6NQuovjOyF0HXkc QYqAX0R4n9ltkWwXJt2RzLOIu6SQ+X/0+EjIF85kc0Mje7NdGOZ4fd9cceOUcK8oy0R1khhj M+TJ15znMvdMZLYAuJUWnKiAiAltSKWHa1ZQeqnSKMnfbX8RYuZzMirw9CLC1t+UQzZZ4ZWp HFneT8DDJs02Xf6eLFd3u3F2EMhALoFq34AzccJptszvznbpznyytUD1cCkqdMYS4DNQO0GL 7NhctZbjBdvPkeoajDXbT4StyynrNXYyvZ+yBrD+5fDpQ52Xjvd13SLWRCaVMbXPO8KUYieP i060TLLwT2k3870lbC6SAlE0eOBGfakKKc6HHrcyS3Hq2xJ+qPG3KhHTMYpfoXOmhPI7fk4n 2AfJPjAgoMy/V7mMLoIWWt8otPxV3vV4DB1fgfm0xtQSLdxXlJu01YsTilMG69pRJCBcJxeL JiVjFqZzkGez3jrQQ4unnjAqW+io1tqzOYEVEkBTFtdKNcHN3XKrJjAncGTwwVUgAprebKuC HO3IZVH3XlAlsfCo33Xq+kdiA4U4glUIaoYJme5KGB0Xjyd2qb0Pyi7NNJfuKU6N50pY35Gq gPlL/g6ValE2zuCIbjeTLLbxCnuRmXfZe/VqpMiBRCP1pC4SWaayZVst/PMP+yYqgBtL03xl s5CCcE1arW8qTYp8sVWIzBpps0eGLoXpT/361704x/rOIP+W6nlS1MKY23n9CLWHK+RRWWht mbyjy1/vz6YUQzpmMOTf09fUiUIbqIuPYigsrLvR5m+/JGd0GJYw8vXQtT3l2IyCM1GriQ70 6aeXgF31Wt3n9HouAdNraexgU3AS7BulXHwURIZkceSavZyh8c/IFXUqZL6KsnVrS2cmb9PN V7vAP9/hH5spVeUbIy4BC7Rzob/3+j5FYntsniqtLTft5vEkXHGm0gTguDhIvJy4JuF29V1e gA3WYJnSmkVKbwddr88c03HNxX0/ec+iIFJKSVHE+BJYILLpBhjUH52S73IQgFHWzZ3CrF3V Ui1pWCeMbqpGp9PplISd2uGwGzHscVD9vr9Lr+Xff2Ab6EmuZ7Ya/eHjXeIRQrFhWiPpUzkY kR1+xSXmMd2CiADz87Llei6iWw8amE/JTzRT4ICcvBRBaO25QPkKGfGOb0cWSV/cW9P43XlY Nkxaxb29o+TsQXkCEkVypgclx/1+Q7RsYjDqytrDSanMGtAwMtjqTs2LJ1A+LAfP7+cr3ada oSU58llcTH0cKm7JK96Fy6fduw15I6qpL4YId5zJo2nHFrwqdwJlTqJcfG+aJZ8v61zZYU+i 660Zrkq98NRZ0N1EDSs3+UcS5Fx7G4MEKTRoBIxf49JFPjh4VzLa1hFFewwc2HXd6JbEKPVo SJqQaUgC7dsPvb6Z5szpZwrW8CoXV8Gt7Z4s4Z5Gv8L52FyBUUcSUPLIblcQtt67kEvpv2qW eHIoTadLGthftj2rrvedBkF+rXgPY9hNoaCiBSmgf4ZtQZ/0XHwejPfFJRnT9OoIvBzUhYjW pvq05SahAs+qhAZOjkkRgzddxTcxDVuyxo2ve5eF3xcr9MGM/Ov4cYmiZMTq2WtQT33nMkXV p0Zk0cR9+3Z1p0/hxF/yAqYYO8LrM+/rCi/YPwi90iSiRzX5fi247Qb3ptpO/Ceu15dvITIM HHKDQqNNeEvqzjAfS38kvtWi/36WhSmUJRznTAKe33YPcrNXkuJM0OsB8I4QpyA7f5rrcZ4s DBLbjhn34ZTSZO4gzVfj7H5HDhqA0eQaQeH+8iZZeXEwNMme4XyqjgaRvAk0oL7D7uCkwqvI B637DIr2Y+xeml8FRssnV6wbfJ+q4nH/oO3f3tuz131VgoCrDZigHErWTzr6CXVPOQ2tgDit v1MylU2kSLtvUShT1XhE/pguIrkwrGBMEqiJwHkLoL6casKyQR82VA9XsinTZ90Jfqfp8ssb yAtQVtOXK50ZFyIXgPtAagxXOkGgD4UfEybOGxi/sjbBQIx8l/FJFCWzO6RhQFreLiIPc8sV zwUv2Gs5GXmXrUt0cXy2qip37G1K5aJ9jxBdchW18N7i568XoDhGq4ltWZ90s4YfDWJ5WwoW UOKa8nTJwi/wLfEncCAPMBQ/TlCmbDCp0ZZOdRl37yWwQoLS27tlS/B8ihk3y4Iy3+sMPjnY fEz512zUBruVP/dacvrhUNGPLSq50mSsij16K2XXiVfTFHq62s/+Tzd1DY36PXUfTFACp+do 7UZ+UMq3ncaoyr8gDox8pDC9r48R2o+oGb0I+LT5ptEjF70myHiZGplm4VUZxhK9lI1YEG+a cKgm4TNZ8/HQ185z8YQKwkykz8Dy2kBW3DSJAIvo8AN7R13oWmWGi1gEF6iGYuols7lxsL6v 3ZIZt589jAdZpVkTvYJ9znPAejXlTu1T7vWUWtfgkW9iHoJMVeqpyKgTcN8EJWje5lD1LaxZ ZsNJ+pbT3QNqBb+79zKNy0XyymWSO7KVv4VzNzNvp/c7yucV45nMB5K7jiN0bZYK6Da3HMZd W0H5i5w21bCeJYZKU5Bq0AGZrE7bL+dxBHzRcvf99R5WOcHIjfMen5CssHR5AyPaWO1jj/kO KHK0cZ8tE8L1IckP3rSBKlqbjfXcIoSVeofrYi0OuG/i7/BZp7hDb8lst+bkxZfjgqzGQp7f NmqwHaZfP3vQB/5wYMOmH9Hc6pJuHl6w936iIORLwM9D1b+elfpW0etwUGdSXyXnzmsql/7q rm6Bs+gRw439/TTKr/UPw5tnyOs8UdWcFeBI00dpUX8nBOZdqzJrARsasoeSXmhj8VPle7N5 k8nvcoo3QrxfEAo8fxw2w20ruDifSpRwW0kEr+lj2bqXB3atbHdftE6cHk1i67tgHpBJX98I xn5YtCR/pVEIuwJIkHDDQj1kLYtjwWXcbAKWFQw02WyOCRhOF7u/IGruEQooxhOFYvVoKZYC 9Wi2Pa0HEupVQww3YbxiSJx/hOR7wykwJL+02GHyKhWXKXRY1Pn72ZB30Hzykd7E0R7rivNs 1v/A3PpcbiA4errXM1bQm8HZflFnH7AA6iD5AW3mficOQ+wHV35EgTe7HLlf+7nPZPE1yQl7 lvfEoxnwLBe7qB8t2rBqNBrTbLJtWCYrv8uTuBP+CEhOgprrs2t7oQQMJcD2txv8ujcg/pgf vePfG+CFsXuqWw//Km0HHOH6MZUDzITui15lL2ZQ6nMZkzSIHSPauMd/TOHEqjRB15//CHuq aCYKMKstoe0yS847WWkfcC0Ta/IYau4zMXqKYorHm31WH9woUTG3CmNeamlbDc1ypEL6sFCs jdTiM3Fp/dN6BLj9Mc69VjZnIk24G0fvwXulsax8HOaBqQWm3/rmhUdMj8u4K46nRP7zSF76 3MVnk85xZyWQY01Gqvbx5TvU28L4+HE+0SPGvoLLNHlwXBZMU0mFBB/Vga90uIYwO5fbs3Lv j6t7152iwMe3Agp6V/FW+aUZE7CbL2PPj8w4C0V6MkfFyZj9bD83KDvGu6mY3ixp8qF3LOqT VyGS7sOf2i2hkdFNLkjsv0Fl/rIb2f69GRF7EVvkOlkld4fmtUeNJrGWPlYU9RJhpVLKC89o 8cmeWDrUGP3N0W33fYAsgaWOnNIsC/MeviteudyvgnUT9sZS59puuIEbaJv3vRjl9/cG5OU+ odKlbuKo3Lcg7M/p2fvK8+KidozCujZm28otkaIvc3kDL+82QOvHOtJvZvxSmpr0MPwniqVc ovsJ+rT6Jfr3UawIn2FS8+MT1fyF4KOpploUb6aoRz9p5TSgy94+GO0RP9+aTCfAkhHDogil IXX4/dQASBv1BKPJu0+/flHvfR5Ppc9U5+43F/KibvxIwX1JoTksWGZnjnW8RNvo9ubTK3bR wVzVl5MMMhed1aAuIi/jr98RWkQZN0+zO+uMA+0z72F5HdswDfdyx2WFMFlU6ErocWxLo42q VdQ7FS7kp0euxik6xLQEj8XnZU8J9lReUF5p6nWucFQLlzM226zrziIEtfJYfZeVbrCJXWKb /6YFw2iiCT/BSh4G9vR/ZkGJNFBplMEbl4K+qrpF0Uf5oAEPqvPpmr45426ZNEKun3c7/vVL f4PXLJZA9p1pulfnhxBY7Sy/GHq9+LofEaFy4hjas5ivFVCMKNJC95ZvRJ8EB3RMH2EGRGeK BJgUOPzxp+qMqHzn8RBPubUXffrOB9y3ZTOsYIcXCsKu1dZKBhll4iL5MYKftAszHjwZK8+s caKH8JynBdct7agLv1ct40XavHL+gVKY0eLqiMb6XTweWRFWji92i6rCT308Ama37GEHYHDh 4+oXFuyf36M0U6uJE10oGGhVNuPQUtwlwX0aO3umicLVI0L0adbwm2XDfMLTmwyj5W/45BWk F/gWR4uEgU/3GH4IQ25tdpwTfekSey6/ovEqOyYqfxENv/HoYlGk8INGuqgNG0vSWY2Ly0BO fUpXD601XF4V1u7UEySFC15cErNgvqFdr0Y6VmleltTkFQi/C+n8Bv2hLIuqe7Yn45v1vtZB y8q2iXmpbi8iwhJDDRMN4L0nQvndPiNe9PuErTATXBVKl4pufZ9C4cJwOgKXFCEJSwUpEjP2 yCB/ZFY7APRrH6Mh+wuM4efoDEUeYqaRIEVWorkV3ULNHbWYkUqJMjn6kB78nuUHgm/jk8My p1zz4/JqfJ0EVeTH+tu6A6w1sgPYMsqf5ow/90tGbWbTYEMZn3PRCqt/3918twtrY7JBvnUw fPQ1IP8H9eIPX8siJ8+JUDIo2wfbnxSOiAIuCSPavmCfIf/XmsaXImqmW8f4QVF1WoAWdS0n 9UIVDcPi6FtVx4JnXdXXZWyWfRsVxOKUe3Mp+xImxJUEe4oolctSDUK0bsvDs2HN7PC7msyN up1oho04uQC0Q9S3o/KS1OZTHMgU7+TuUWSEPpaR96fBqaRMyrbgdVxtWzre3dv0Ss97Q0s1 yHOrgzd3kIcDt1mG0W0M8aXo0JDqe7OhbLP9fv26BB3Uuq2FRFHzsMZQV0ZukFdFbpbNSn4w Pcl405wQJLVPlvyehlTe7jTv7KRuZnjiBmNqsRshmSRGa0vcrrGA1cxe/b0av247GYLED4/3 DakwBnWpQah8fI4OZeboUITbN28YcpXqg752M4/m8FyIb1CtGSXVx2yRe0O9kA9atinhCQ7g qp9Ttc78oBkKpOYzOA3lVE8RLW3dfwwIkePYyJLtI0a+vplo/X7FUots0Xw0ncpQRKUsl8la GYbWqG59skAF2624jIOvoyCQnFfEiNE3gEy3v0yL8ZOuLPfV6rF7KYzk9JEA8aZ6BFwO40dd BHmLPaHZqVyhTJiNszpaohl3ZPAreQeBFf5fnX0PdMGPUQ0pW3zFaXy45PRBpG+5bRXFUqO/ DhwjbNdW122o7X6uetuQBPN5uN+vfa9tdifzE8X9TcK0fqexTG0OHZKAUBJy2VUzEMtmNfj7 Q0tpafh+wmdPdS7xJG8Q6qytXEg3vMQg9TLqofgy06DK4E/mT6/E2KuuQE84CWHMtn7KAt6c usZuyc+va5hrKu2b8/OQCaP46BOJ2VPZ+0tNvdKxZisxp1927MILs58GkKF2P520iL5l1U7J 25roTlb+GHEol4SY1s/mT+ewFYrxdctScWBDe1hKKssoXWlabob5fL+eeKuuV5WAaVry7VhT 6Y7NVS0rPD/q7rHb05avJFfYJrWXROnPjj2r6mbSckVlFP51kzUS+inlW7S2++f6oOHO70Db ZPgzVYWoDlmEYcVEvQaZqUvOEODT+xakMUMGXV96M8kc9NBhjlv3fnj7SBo0BZEU0ug5gZZ9 TjSOuI8x70NAa3tRu2LPH/UCPL8rGyeM4BVS2vsnZYAu8aNeqXxsqFL2TMfUPms1ffK94hDg QV1ipTduzaBfG+EloFUnk9wUxbve+BQnMfL1VhZUYJpTRSlkeAJ2rX9HvioOxbTUst/irBPq 7Rmxt/iTq3pIeC+81/1TBXz37iOMWU68uaTRZ3GG0imJ6mH9qcfdElWKwwgKxYYqxfT0Moah UuQWEGWP1UT5k0nq2o1xEUvc1mej15J4zMuRl2q6d9g1evgLbF82Tx89NE6xj5Qdn39qU1+z UtF6Dck+wEUsEzF6x3gGUnDxMQ68MKYCx6NcOhn7BYQ7tAeG2g6ytnrPP2NLb69Q2DcMTnZm qy+7xQgzT1J8ZxSa2vElb3MOacQy8WeantMyuGSIHp1fNWNb3cPSD/FszO33uMvvb/3AwZXj 1/y6747z7QyiodQhe5SDosLVrbPFYEnkIUmyVscIBmeS3cx5nG7LcsTxncX46HI7fWscBR9U mMGwYMVGElWHWFExRbdsrgIMg8+p/dYnQQNxOxkqX+GKl933uLBw16MSKe7fTRYubO8LDXsj eBvYOcacZUgQj4lbtna4PogFOY6/O/FNo9Fpf7UYTZ5kaOjfkdVLO57aRP4V+EXPhl/35/dQ TNszlCKomBVxPTeVyW/rQ/yuVqgEIUNLHHuc8AdGjcyb4Vh+tu+8C69uTJc777kYCiKD4XS3 S5KHSVfj+WiUPvngKOdSYRkJDSLIPdtovv94RLUvHqx08maI4L2qaGfR3bt4yshm48BWtQtq 2qGiD3T+IJEZDJLmxfgQwVSfpCcKesNktdOgxycMmvDuBor1VKWjdbNcZFSdn/KTbM5n1+/i 7LbOTRFYCoIUT/MfBrSww3ThfzXE0XYOXiZ+C/5k5SBvXssiKSSmzXJE9nQNqoT9LLFERtLr g0UHl4q3Qng05l0p3kVkd1B99LANV2mW8gohXXtw99oZo4lHBH9g7mvjhWMRMYmYtI2T2C4S SQ8ZOVLRG3HsoU59aX2ieIUtA5m3GUKv4QxYwy7PocvJA9/JB2ZxqTuH/KQ1vnr/1JSm+rWr sSJNOyA9tNlx3pYeXC6EPg4AwJ7LXdGY9J/BUF5hBgrAQ7HIMK/REM3e5j9cuiS4AOtKygDS lqRlLwrlwA6S/bcsyM5gMxF3bb4cwc2a9kjX3mPnXJxGfqE4ZRK6xJ8Pd7I+rPoE6O5Q3FrD yKN8QRJ9wo/MPTn9ye+ID+MvWzE1OpwJ5man5IbNxeX5tEe2I6ZfJHv8pDIO29/QCWk1va5o 39JZmf2mz2VMaVfJdht0PUMOHQ3LMDX06h3545QnwywtmkCiUKC52HV2w4Lusj0HOxxW3Zdb 85MN6TPNa0P31i3/xzAVZi38eeZSY1/NXbU87vJAIsGPSz56MK0L/BFspqpkX5tZUbaxKQnY Yo0DexLDEY2hyeSOuK333UR7e4Wxd/qDKs7LaArgAdqiZX2iegdtGvfizF+euV+Fl631Zxnk C8QhGK+WSUKpXeCpYTBQLKXjLuqUiA1U6SeiftEJzAMjkLGbJcEjmW345VIlQrdbKA9+VTEQ uQzigdni4FclZaixRf7S2QDP2RSAammXjowlOFpp4HC/OGVrMJ0y40XsumDl8PaJWprHjGKR 2D77C32VKMyBQ+2HXueabdGbgofgAQfw3f4AeK1igJJs7Unb71m8/c0vgmNNtY2sAxuKIVfv Yiy9pG399CevgVedfcl3q/PGTXGJG/CDEWoalsqc1c6Rwj2mdEK5JHv14QKR9indMpkfe5ip /IdHxfTFhYh4lKdf7TzVcjLMhNS8/+bBlB7AUJ7Bf1DJ/6X5dcy5piotT3DSWDz7DfQssdiB KdGtl915sOre2jHK/rJxNc66f+g+aUgHuKF4Hc7xEzYgiSPfVDmzzf2cjfwrxRSeT2OYsXQJ t9ru+LHQzkw4xUNnTndVCzRgBFgHxGMPzl203c+ZnCUWzkEhqXNiM0z8fo5gmpZSHgkc6Vel 9k8vkOhnZnPixWtiYF/rJae8x6XatkMJzeZXMe+WfVW8zOAcDoO9KEIiTyVL3+BBlTkRuX/e RSzRSlR+FDOEo+6MWlb1XpQzK0pRqzmary9GGfk6ubWzJW6JkjxxqhDp1dcxyyyY++ujj3uq FjlEwRIYx6IKKzF5d0zR5rG4FJPd02o3vhjPOm64jvwD61XfSJ6Fi2NFWkIzBducN6yDlMmH xbZE3idMyklTSf6wf334hkzWRnSC2Xq+T0wkf8WiZUX55MNcEddXN1Lrrzke7Uo1+AKiq8my NQv38AFT6u5HyQL63GA+v2HVR15x6Qi8YbHoGGeHEek5imYX/ZeRs48zZOFMBujn4z5CGuyl jzGxGKJoW9RBIrP9snM+Jxs9tQlqqdmKArHzvl0fBeN/Tmf2EQIJuxq+bxp+OHpPZaa+XNHg FeJqxp0RWxlfUkdA8D7zl/4oiudjYWlBMWLicxnO3qIcRmfWvkxC4BwKssKrhlL+dpHxhhJf H4N9yUhXUfBAxo+9tyr8lKnxvh4LYKUW6VcYPzID19pWZflq3ztUfWfvdElrlbsZZxGLnoKL sNVQaEa2ZSfdQaBT9D4djfRHVqKmWEeCx5gPd/wlk1+L7H5Ag5HhVbST/I3528IQkJILdeZg UMzgOZaDBrao5Ql/UxZlxktTVjOPyZPYjcl369caaP8NHiyudPFKshAWHD01pnXAknoGoR8V UKYLzvnkfcVVN+lzDOksgkSm1AQNKdyGEu4SlLAxJVGAK1V4ALuLMj0+NwOppQN+HLhGWRj+ U51wqwjzZxYNc6D81mAxYBUJDm7wM7KlyrIgWDKbKD7O2Fdvg6Ds8kV21OA5F/7y5D3v4bjN BOePSxgqfsd4FTgD6MB+R9e2w9iy8+dhuo0PY6eIbkXxOTHncA119rh7NZWlxmoJIwXBY9vk Z4ESDnnUgfzDuH7AyWUe376GruHBY57zt7ybmkYU/jc9EhGJwWH1o/VifHYL4ilDM49Pkm0K jS4v9RjZorTbdSs14R3+6PTmXCkazjKzrPO1ALuZdjuGlYG9ZPGTJ0UcZG2/tdIHKcI6ZkTv TqLuC/3EfHUb87BFnXdOmKZ8JofuYTb1ceaIWDZzybu8ti/rS4DMMT5vFedwcfF0Jehn0/2g +zTp1O+DtFjxpWQmGzAEyaSverIwkSgqnVWzqWd1qhmmsKQOtua8XLYYMONsoslW1aJV2WN7 PQ7VuYIxIlrQtK3efarR0HvOV/rqkBKI9v3k4eYxZTbjjIHKoYC8uEQyWq8DvFjS8SkgegNK QROJJK9uQxsXkQ1UuCWxu+VRJBqEi5B1hns2wI7oBC+/Hzfqsw/kEFdhMnzPhLOcuG+99Zpa QjB6eBF5iaI4Gpp5HbBU5/Az+oDzm5sGgRsK+pODZDehWKvWSyP3lfF4tya08sHP3MpS9z2a NpVyLVeDbmFTn9JyKtrEBQvA2y2oZpyRluK0ihkxLJ47fxSjhVR7CQRmJn7GmD5X3UY8lgsK /feyxmqwyqJ8BIbs4bddZb7NUcwlucjA82PqCPMQWuooXtVsR/H3leQSgXwKJTm3U5VVb+U6 roucInp9tYlKmS0Hc7UT3uoFgBODLFTYP06fTpvxXc+7TLt5us+MbP+qmPVQvOZFmPTXmnNe pFzA1kU1t3xEMGdZ2BTVPjM8dOkGQn1AHF4xu7x5S3tthbq+3SdSch+4cft8b74n+oXNyHiR IUH8S806+Rjme87lUltrQJh46QtWRV66gbcRYxWBXr5X87Eby2a5XgN/VAk++cHxPtMMQt/w ejKsnPTMcqnO+fjZuEEs/PuYj4+lN2/bzFy2x7QFiVk57ivPqUICFRwM9LmJJhdFx6OKsxT6 CIhpY0TcRZojfaswZ8u2xTLlllUQ/LweIjjel2hmTKGyqJ1OKamcGcrZzl0GLIyieoalBYqS LEjZURUzecUDjQc91IuHOUfo8gSOJuGmo1q2qsClsWMrdgYg4+3Ql6m3eZ1r5A9tFPSsrlDX bJHKG6U5Boxr3t5K5ijUHM+G/DrFqyGyerbhYNYpdVpRowIG1BATTlAkyvDl0XOLIz2b/CPi NeJsGrwjLLfKjbncdOiUwcCNQz5SlBFzFB3Wj9tDjF87X17Fa2Xv1jnsOWMsOwkIOilpvkU/ ++aexnxQjJx8WE6zyEIzxCRTkXHZ/MvkFdI78Hng6EopmUNlvcKni9SU5dmYnu4I5KN6FJf9 fKPgtQXv1lpBz8wPG9iE0g4I4NJ1TqZ1mEBS1Qcs1h8DFcBFse/O+vVg3Vnvpk/RKTv7L4H5 XzCoKOqgSmkfvuE4q1+gXzGeJ5uGOvws+0RIsalL+LyGgzUmFMCNVL0Pu9z3vvEnY/c5VnNT i4ZWZ6oauXGdm7dPhrdysEQp0o94MbnLHXChr7uKEKh2ooIEKYjYDQiA82/yI8/CsX/0XyKh tSAd/ymdsHGEJHz4aj7bssfCwoWw2Op8V3T0Gw9cbybYN56Iy/2djTnbNx6UXCkUgYKdZu7t onh+QIC/kZTy1cgeaWaPqKvDoqzLvWW96FIQ2jzdOPB+ImYZ2ivZ20rPiMuCG/Gtj7B8+Hxl cfJTUXzVbRryUPiMtzzMff0Klnb36Gs5Jh/30cmbpLqSHX0E1841ZqrtXyntE1Q/hJcFdZtB MZvsK022CtxlQQGWmVjhC7MmaYfaDaRSCUQjTGUnJY6Yt/wkDV4I+no8lU9EtJetNShHBWxf j2rW021UnINQSq2dYI7iGmp6LRlWiSaltNR6Wm3NpGxXru0EQIFnES+xDoTdJZISBGGdjp1Y Ta+S0S+K1aKq39y9FrO+EZKsD4VdYskSf5qcDz/uI9V/jxiEU5y4TUZIet/1XV/9WUDKxuJt lMHl8U8rQr72AxF6MAzqEfFIYDJq78EsODGHVIj4BLxTiTXoNioqBa/nIq/cA4sp1V/H7mIy t93RJmcJIz9qxVzq/iqyrCr1s81IIm8SfSzf2ABTQ8aA0y3RiI/7jKFB4MPDnaR8AOPNnok3 geYbnqQYrHUl1GA3D4HYYH/PvjBJn3V4HofxvoqOg5/7vdgA8lEmY1XSxNiZ6wLFLxr8BuxW C6zrZuTgXmgamWq/GYKis/uXR7Ld6LSB6UK0q3ObXRKpxy8yuLMHW73ccibCewMUrTX4YaUU y4uUQAWBt5YC3z5Zfhbt50+Z+TXvMoEXW2ARl3XO8fABtU+u87w9z4rVOPwWB0cf/sKC8VKO 3rGFUPk+PLPmVXAYhnDzbpUJNnY9tPlyYlxMsmd0VrR56mLZo8QYfJv0piTjRu/AorcDTWIX eCfEoLtmEMqzupsfagCWU72uEH2wh4g2kQ8ovFZVJzNPqLirZopJn6dwUqEdqJ53XkVuf2Vs zKY7DOXoH7gtkJq7mVgWZkX8w37wABYrOZHIbYfQ0avf1e8nClCJI3Rfl10IF3gcMlyvZdM9 vI1FeUpYy+EsgS97ZVIkVKxCSmVGpHZiofWwNPSQejXSY2jG/SHVd9djk4FeNHnLS4pLMGJz NliYQRimAGSk63yxg8KCr4lchEza1IvD/0UGqxG1/eIkXmNJlvbC8gy86lfpOTScuSHEoLar 9hTkxhuHfzXAYtM46m4OLt+i3/duWBj7lAX1IbiE61iFsW22iPsESYVFTGD9yBiTJS2/7NFk 4N7OvgBW62FAnKfrZsq0WMH6rvCrs/HnBE3iRLckFzw/FHX4IaIz0hUWhNlpbfnVuxlFXGXb pxaO/JYLPbVNA91WIUJts4g5R/TeBeijAj/SqB+vleYIAouNTeJgT2ArUHZNJ3T037hHt+G8 KXv10ypKNSCKJo2ncHT0I6EQk/62UAvzx4eya1rvqnpBLerY2JrFbQ1SvwdWYV82Ppns00UG LUHCnpgRWzpTBSaXcuS0MeNBDJJynljC+moUn0u3Yy9zxy+X6FEgnJq9kf3lLJ3BJF/5MtyH tvYNI+lVFWqVMkwZMlJT5WPNohMstCVfikx/LjrHJ2S9vZPnbcz7ql30YUrTxglFkGiGCmxY Fs9Fczowup9AuM581Kq1xyForTSAF3Gw3KNYm5pQNSjn8i6Yks4hCIZldfCXOn0nizdhb25b OHdWV/+YIzEu8nVP308OROmBDbeCLDWaIKIF2a5zPNOU1whzTG8l5h+X9ZvcqbtKFJK1L254 WytYRPRRXmVnF+smUMi5FE/gSj/wG9DgIqCgUsGS0MPspBoavJMZXr4m8uj+phay5YJJeLxG zcUoMlZkHKb9RZqnoVBt4AMXLnEF1iesaqm3b6AcrFPaJvK4RL7ImE0M2jzO0iw8yOy2fLy4 tRy9HbrUiJ8+GPDS937n3Lui1W6JUe3HxT0gdPRJtSKE14E2nHH1IfACJ2fjIZGD3s6fTNmA qH/2GI+sIcU88q51vRoArSae7Vw4sHq1gNf3iZsiN7WWMDAUu3c87NTwkwnBjW1BxmhtUW5I v2jpRdY64T3u3ElIgXmDVflaGQA/xizwQ9ieqRA5kPwlAut8g7XYnT4NtVUykZ7vzTdV+w9z rt+U8AexnXt9Kywvhn7eFhH2bXfowbn24rRH9RUkqLyGsgUSqbzthT4fcMb0aGFZhuXGMJDw APM9ugiKynO+zP16pzuN/OJBB12OZpvHQwTkdqitWPAO84Sxlsv1kflkTDC7Mi9sRDbmL7p/ Oek538/WTiElSSaJ7xrXKuE72QjXgmc+dCvH+dg0VNsMFByN3aIM+rHMPCsFUMfwoSM00hVX Uz07sao2xvQX8n2DOEBR2Zvk0R3emlh2U/lTO+qaFUbxesNOyVLEqpi6dI9CTbnQfGKYgsX2 u3U8LFUk6vzczy03p/v4b+6nuE2m71bQsGm/l60ohut79m4kPRy5HcpsP4op3Dpse0qGGw7C Nn95SItiUMfaAqzGGcQupyoqlAT33RVSKONJIuVs+3nN55V3sn8ep+0pbh7sjFJtymGYzzz6 dps/9jp4Gb/b6TM60GiAiEu76XQuVTQm2Jvbfyz161tYBeqw7LmtiAE2393PBZOMtzeSNxuY 8qfyMqS51K3gHf9tkJyG9alvbZ7sBC50hqdju9Slaw0jTO+U1kFslhKMaDOap5qsJgravJdY frSLaquj1Wl4MDk2/w3yh/ksqe8fPuYNlhwdKTdWDW+Kfc67Z60k3mJiIiWPEWY80ZoUc2/o TaT/ue8gMv2zvrXAWbY8CiogGeoUzU3Zl89exZvRMl/nGxOcFwyImV2Ln34fTki/NlX4tOEl qIygYZiONJ3LwNJXgLBQnUh4h+bTWC2RO+03FnY45fqNeFLL4a9MxkALhliNmu6DDMyqA8YP PGKKUC+H+bS4Zd090KjPQCRYJFQk4VPjBx/7+AbP+55CjuMPfpRZzaArTwNrf4uNBB6UbfrN KKd0vBT82kMvQi11Rj/024GcYlQWzeK0AQ1UnLXFu8dR13pyerbF3E6sazPiDF+n4AIepZUp +4QOcEfN+T7ObLgzVoAE6WbZvAp6VftRHf32F/jcytd2e2YVY/5ugkRpa87t5WlOCBPDrMwI i9AaR5cJ8MH2Jkj4PxsxNpChQrnPCogP9ruO+EhKgIbNfZGlC9qW+nklbYCyJX6P1fZHtfoa /ZyyqfKoVEVf4OI3qkWTrV8TNZQ7PjoUTVO3+UtOS6FP8xgyaeK6HD4/2vtxaqSEQkU6zD5L YuYvi/+ywA0N3FovoDNjlOmr8N4h3UVb+kko2JrSyZnUJLre1szaYHuwGNukxNMSOg6tqTU1 QQVXAEuFDOs+OV7tTq8/qVwWE8Xk9Sg9aBaoBKLf45OFHwBrYNTIbYbVIveVKDOJKC5WzXwx WfYvUFrXCz4f6snXaEmg5JI/wMcs/o7Dmc2koIEhuMKxo/tJRKg7vfdYhaDIEZvxXO4NYRFx oirBUEsQPbHOBuU3eYDR+47oi5skKO4pRt1+sCvC7vgSdht1j8JErmXXUeJpmDCiMXhPT614 eGyUeRiVLFIOLfWjEyfVvVvjDAxVEvd6WnURepgv3jeW7p6oK7WYUmsGu/fHaDr+e5fO6m1c C5YvSizKnz7LuYZ+2xEqbsfVtQu8XffNm8SWrvzcY/BaKjAu7hj6oNyIbdLUnM2uw6PvZv8z DxEIWeBrjtTXsMzbjKmM15alku7wCKVNjlFH3gLAERgmoQ989tMCKNZrqqvR1qx+aYidZ9rt 5TcyLcv118nI5dSBrAPTsYQ2LvssgU4ued8993u6rOQ33ELwG0BKSJULGOa+Nh9zekfo+Oea c9ZlTCYsVQkQ5lnTH5O48N7BXPPLCJhZpCgwmqvUcvXv5Ch4tTTHClscJft8C3Vu5yCz0nXZ stzQ6+lcCE9flYZniWf6HvpByh1rvG0DzeL9fLkwsTUoUb92PdJowqJBEvWIyp+qgvA6H6i9 cSbt226laxsJgBrfrkFRUuELftCvFPbFIzgdXKx63KybfYgXk6Yg7mv6aRueM0RG7+6JC1U+ xLj09bv3x0PKLPu6hr6e8u/43WGdebyH66gA8LQGIpH6hIMMfFbWzdu6BRzhabm00gMJDqdo NxOKtdP2lU21OW08pDdzR/Z3ilYFnlhaT9E0aCXJ1cQ2fQC60iqB9gauGbhNRhzd7Z77IpfG HNK08Nb2FI6vkbIGNuWF1XrbUkwuJVwxAGtO7aQ5zooy56JKB8bUzc2Gc24yNNlYN1Opbhki fcq0/CAYadjAEv7pYvqoSY6yMw+eckR77lGiufMRM2IhEUz0H1d6RP20W9DDFOaPHhe/NGeM UerNQm2ycah3UMuFM0JzWxwvRqRn4lFEHOrUoibdHz8Rf/7yTQETp3kN/Z7V4+epVR5bsURq vSFdgp6WcL45HqE9bi46V5opI1VeVq6ojA4n33KEzFP/qxx62LeMlcEaCg/BjCwlUjwI5ZlW ZLzJ/MrZq4XKH1nsaxVezpD4sN+91PonN3twkxvWexHJqPFTlsbF8LtuGQQEcxeOyIdHHlNN 7y1ZZvUbP3VaoStIw6m1z/1ixhGPuhOIPLNTrhzdwy71ERFK8GRqNpWtn0P/SvC4mpmSJU3q 9IsJv4uguorJ8CS/r97Q55Y7O+trF0XVIPM84zSq382JqLSWV/INzKAbtWLfT9cRMbkMdqEc 81W2S72vKL0XQTwBnC2kZnXQyFAMloUw2npxltXOrTx+eQsIhNU1xUxnHY/fFO6jvuMpxZYu Rbjuxd/6I+cj8Yxk1Atd5y35A1uIqC69b65PnD+8UdD2EYXPtKMl2vqSsM4ds4yo3bVftZXb a71QauupLL7iC2Z8Bcss0C9Z5rmXEgXPXdENk01Jj0QtgaQ5gQMff2CRlWqnPttRZrJi8klA XbvOsv7p6DPKa6S03Fg3975hs1wEUftaqlpSoyvfG3Ekjyi+XPh6W0cEqqWIkDHlxwGWCayN i7oxaXQSduUCgprh1PTnZ3Y1NLaNrNJtmKhquVwnbkdY9pPU3WTmzGE+GSfaY4NgAv3ir+Wm jukcc5UKF3xBmQcGnsPAWfqyDnvS2nc+hrd7BSxf9u/GgTr+S3Kbgulffe2x8neAI18q/Zgq fJ14mcVtKxvQCFzpNJ5lJDwXLtJTVn2GblgmjtZ23vPo1SdbthZwrd40F7X770fF1yIsAZ60 /DKjFSwTayYbHLuLjNcjCqUmmzJ7L92q7KJ/JFfsQjkwTRKarHNizmQHYPbUanD/uMrdbNKF vYK2Z61pFErmyv52f4JGkVpfLld+jRG8H60/TWJhWNfFl9+1fCOdYIfsBhWkZP75acX0MRiM 505D/bGBwUReHEeT0IZyHuUY5br74/qpikFUbFiPHbvI1HGAqkMFV39GzFyiwkdST+CVbd9+ mghJaHzF4iCC8D4YZlZDpEvflosWqEpOKK9fsBBtMvaZJ8Tq7BxYPB3FDxvdcd+wh0q9k6xU 7OPu/0Mo0Gu43oCpi4SzCLxotEls9FZitNSzATNcB4eE/rE+1/Pye1nIQYCM8lOIVcDLyRb6 4JvdHHiV7LXzLeTpUYT6HbrANC4cEsnyxQ/NnFLOYoV7RKxlaI5Z5FRfdchG39mul7Kx1KUj 47RrzHI8xaKd4HyUN/0ef7nhvCCJHGdfhfZCbk8yjBWA5g5tfW99cAgLpINmgUpzVlRMY57u dFfyLlWwGrd/Stu4T0dJAavyVT5Pi/dM0LkIPGCUq6qZ82AZlirRErl7vwXt8bJlNJnO7BoO Yt19fJkUzSBJl5iI3KRhVBDr5gUqjBnuTZ7hLvTtFeZKOFEsiLQYuOWYnl2oiHgSofOWXe5e 4/P34fO4kffQ6FNnBUh4gbVOZ8zOPv6EDhy2jfabMXilP+NmbWu44XsjdQGINtF8iuYr/NGH iWp9FXTbnB6x3845H75dM7DdFHaPFn2y1qTNHm/9jvlImxIDhrC8NQlJHG/d/UhH64p7CRSy bKO6VhLY0RL8/bKqLf81gSr/7UlRDXIYarxPAOaqf5WgS/X+bpNt1aiexrCu7qxF2CvXHiMq TMGMs1rJIW6lvOyTJT3lYPMFhQt5xqfwgdLSZlo8EZK8W4aHB6CiGuukNdKJx4lAeq6PqajA RoDqt7EupZqkuoWe14zEK4mjWiPjq5PxT2OODTHqVITRLolej6XN1+/tWTxPSvrR+rPngCL9 7Ekpq5eY7pooBOIZQqiZd905GMcuUdBFiRwRCjLtjeuR8VvdxFyJ/Q0z+SJKHWlJb8sQq0A9 J9uOL8I3yF4sx3SG2SV0H8Akik0oMNGtjmvfYqS/gienqb9hRDtgO+KyKYi0bEL/oBKtp/X7 zrrMKpueXYD30098ede9Gu4DttFbXu8ePsbwXegsGpfmbNmQi7Vhj7uo7jr2pYa8zhJCwiTb q3pRXYmlTK4D+RvzdKcDUhmrobaHMmWDl3iL4lCpboHUInJGmZM45hV0MXMueMFDprqpEWAQ H54LecnNpiAW3H7QVTPneqCVJjk/zCft6+ZE9II3fX0rk50ML1R+fLuREiRESibv2uEWaY5V qp/elbIo+OHHxL8zLeWsfy18Gic+M/1apT+mVc1jgZZkneSXslc6ynmdsXCZ+dcY4UHY3TlG CQ4+dRVYfvN6wbEV8s5gbYHTLdE+MSeXXtdz2Psx9TmWp1ga0WMqu4+GUvaRXyyZs32eYVje es1yHISRiK9oH+7jLpJXAOl/VYoQKnJkEjPumbNONjzTrV6QZuNj0qiMhzSgO6o1dLtPIJg0 E6Y6rb0r9T404Xbdp5mgGMxA4xO7wjfBLwhFwCnyttneZUuJeYzYQ3lrBjf8bmHYCDYEPs/B QtRbcWrli0x1wDFH76EN5YTIxXOLojZzJiL9TFOgWoBRVptoUZi+YK0XSBz02c+ZXEybgCVX j5wS5lviiD5UOBc5Q0T7KO/A1lAyMa1gciXdj8ENlyK6RQVqD9h6a7dZCycOULe1S6FrtH1A F41QjuGijMnP3HabPa0qNIs+EPCUm0ZK0tRsyh7MlZeiKfF8BQ+FUsGT1Ybt5s2mExv7TgW7 GOjTlM5h7cyx+Eww0Xdi8Qw7XbuJzjN2hcw+scVC/FXDvYWafMPWqJDE9o1H5Qy0MT553Q9c AFBQZvhEqFSCIrSmf4qWUO5G+8vrVOtmK4t780aT9UOv7a+tw0yxz4NJ1dZtkP9816HZDNYS /lDkTSlG4X2VmWbLIG9Y7klcblo2XU5xMT+Yq4Qnechsiwn6AL9anralKoCK87D4cj8k9xLr PD/URZcm0XfmBbv39ikdE93Mjy3wUl89iQZIyddBofyC0efegPHWYQXfuPy99ez9UAbt97oz LiY3IvcEpJpabWOZRUxuUeuFG7+FDI2XC9xUB/93xl0ttbW0igqa3QFnw9MNXytyu10vwuLE teIxlPi57oMM5myFmd8xoAkVEfzsO+v2tBGmPgWIhvF3UcMYWsckjMJyNKWQ8KIaLkVNG6NG jMGeYsc1fPRvsJ/aMcZacE+K0E5ru5NDifdrQcC2EvD9PJ/6/wS/GkDlz3DRyA6XGLf4Kb3E ncnfl1UNKQl/gwHarUcdDdFv7K6LVmscZUHJKEk8aeV8hiZAKb7GZBySbTb0LAgeQWoqFIr/ nnip4lUxVA3/wXIjz1jFehkKR5OAh4tbl0TxbUxgg/kCfVGKXby86tSTAtqUB8vxs/536VgH 1sr6co/nFXqjUfzNEnKZty+qK3rEYfTQRgr3aBlCRibgmPx0eQtmH1r53rcc924qf+NPkGdR YDfSveOsJJ4Og8cLCWs33RW8QnpXyxSHC+Wd2cJvpybx4ayqXYRkzLHg7Cy6eYhhFJuW0oNr wdGvTzpsQKKhmsU2f1VInfcdoyn6uz2YAHnNJaNLJKkf1V3aHHFLHXF40Q0/mMMpxJaZvlN4 NIL/40PAcOYeFDcug9XqDe+CQPmeF43jxZ4BeWHcrLR13GIX+PZQGBGoPble8FcK9r5k/PbJ SmSWPL+dWirsHWAlyZ3+xcbPXqCv1t6rmm0Xlp9rsOX6eg238bTOf3k6jreqL/t/JepnzmX1 TAKJGthrx3ei02pIpnMOZZuja03tYxZOL4waxZ9mLrhuuCVLk/+BmR8LjUbXtF69RuzoeoCY 8RPb103kq4SN+XRYCM1fOX+cQtQmfuQnhJViD5EDj1s9R5TQAZLBf+qQ3OnLE2X2io2hoYX4 GxhNrfUYH14RClENitJ4sR8xP2EPQCy+mFG092YU2VedIH9ObcuMQya8ZTbkn3XD60DQ9N5K R4IdPzPqNiGHF1ze+XNlPtlaFtVJylKYuL6ExYLEtFSrGWnSK1/d1j7zcUjqH+lStMgl6hMy XHVtx+G1SokM5QC8y12imuGi8wPpws29yfv5/JK33PtQwGT8dInGdLMlNNmXhwtZJzhIJ4ln kgOa7aF9WvEgY6yhck4+w+a/y1ztlIuAVAOnhN5ZUpO7GUdrp5gyLY0HJZlTIFLBFvN+xcUL SQERNUv3XKz5GTJT8ADbAvHjciicD7x+fXfw79HqJdIsT08Nbs/exuCeAoRmMGs8LT3mOEsB 9o/90OUd31PYulKOhbaA81BC3gnick+rLxU3aPh3CVy1tbw9giWqPgnGV6L3bd/KVhSTCnqI 242R4AzJGSZLkuhWRIY8OheQqOhP6ZjrYt+Dbq96qH62hl8PYmb9aXo5YsmE+K42Fkc4UwrP PRZH17YVV74d3MBsGgYJ6yq404/SconIAF6uXuPQGddhTuv1YlIpvkj3Bus4T1JCZGJ0NKKy 3+5HoU51Vk++QzBjB+TbwbQG7XxPJJkB+Hv6SaGojA0WXN1cFa2ciszTdK+NoiebiMxg4twz nvtw9vTXZRiJvgbqeemE02TZspWacMhq5B7qPuMl5+iy3lCS6JuBRELquf6UOgscolEzrmRo xM48NsVqB2EbEbbeE6Y2uYb/S8Iom8388igjW7TYILHbTiKlZLZ0omH6bYz+WWhJlBEv9RvA qj9toFnr0SdVaEFysWeASBo/HifcHu6UTb4VoZoEn20f1pGn5oRFj3J+iBpWp01obFqWunX3 kpbMxIPPASYN/g1yqTd9uZSBgU9ZHwvXXb8icmSfhoqVlGthES0Ld8jzG9YDxlpjCxcFPQvB fU1SUm1+Z8VJ3SjHWLeTPHZXgAuFoN42ywqMExn9NwyrUgycKL6tg0veeWtPfjrUBiAKHZuq zdfpZkuyLeLcsTGrIHfW6NKTRiOM9Kd4Kxa/yjl2CeFLeDisBdNlEMb2l7BNj7I9tunee/IJ RaIOssOMcy94zxV6dTfduRTNL2ODqcmrl40G24Sj6DDopvZ/DsX8FIZ2f/dbF/rgeHbuLp8O EI+H2ObDaOZO6PCMwQEoLqB41HV3jwloe7lMJWxxXrkJqTqj8yVvkwB3ueZIT9tnmIpmiHYK eGc3GULSp6NzsTBb8j7P7zRH9tfqO/Mt8amCZxt36ssCgDa1RUjQVvG/ia6/YRcZjET2vsk7 KoFd+UmA49MRqkaXtIrhFmL/09i6pxitNCWcrvSYEvLSnq95WYhPzN9TlsSraDe0RpAwhr0L 0/9586mJGgco0/9euEVax5F2CP8RADL6nIDzY5YUohhdVW9pWs1KFCoaetL0vf+LGba9aPvt OCB3PkHGU/hy+aGJO2JOitN/LIornzpkhtFS35P8dC/alYCF4f4ZgpK++BTQbm0KtU1z9TQz cIgSirap74YWn2h9bpLWzCYnwJi8y93gm8vG2mTV6A5VmjkRQRysaFXvqYlddi6DnWYZEQ7t adyxDQANmd/tXX63aFwdhIJedM5m3G3GFH8EMPGIZZMyOGfQWBQWd71JI0vshj4HIE3L3vDs YzdpbqwYn+qzvqv7dOfivvTx6XyixTeAuYv7/dzbWuzlZ0LrXRmqWzXXtI5k5szRdG6Fp73t iSCiHiPbtpTe9aQT4Xc+YSZB/JkHjw76YFl6LiIG1o52yVwCn73SrUp0FpWjPUEdKs9CqzBi 5f3kd1+n92vvCvopEJRFYLFTGXUCILpJhdq2Og/1H+0Rfe/0BUAbPI6jPu231CgfJtwWUJil 6EgvYIlJrSNlHGURW3gOatgzPyid3Iadrd1qrZtLWo5aD1LqtLj1ctOymiIaA2uoihfGP8oV Lx7ngHJTPzcmlIS+ky4gbg3HsSQAVOQlNaVutUs+eUZifHRUAaxPXkh+hkWgBMvuHm3iKEuA em1Rv9G2dHQhKkZI15M4lCLboGIWJcWxUnlyV5USZjECi2HuUSiJvbco4LqKxA0RzONayU3l cbD8StOtXJ03vr1rRbSLI2cGedUm6aX6vWtcqAq/+zqvjQ8b3duZrS+zb4ChqYDf/Jy4kfWB 7cqoYqSUcrA4qC9Z/dABfqc1m20l81GKUX9Lpf3uRukc6IuL8WhnNVp2/Lo+IuZyo6dAE6xw nH5v826YBIbroYBvUs2oltWhaen7XYGlK0tHM68hJPUEo036GAICoET+aP/fHc5d191JOhEd KjBVNHE6yRCrGwwJOG08WDn1YyNabzwg4j3bscJsxmJB7wdu2+r+5HIbjRzQmadUiQcdJL59 620L7lCHaUwPl8DK40f79l69HXHQG21fp8AfjGk98iEpPHdS/yKzfh3QY2DmvcY9fDCcwLzL fgHW99HlTHAWUyZYxSiYrVnNlo/BY7XDXfmNB8PXjKSPy6xHgWH+S5pTCcq1Z4lG7eYNfL5E NzLmdeQU2iy4nIa3gQAWE4RXp/hrIjYGslovcPGtfbdyAfZDFpRpC6kFLfZx3YXgkCzSi7po J/HX8ItuueZlaByZE72oDPAjaiOTI3fB3ehLYLv65/5MEkS0rfIE9ban7SvnijLua8czeV5s i7g6AbNEY+m/XbyuIujqIQEJn8YqdKH6D1etd+DSxtHqC3RBU8dFMvIu1071r1dp93NNAfXR hVikBRCu8BusjCmF4j5vE+smqWzd2JEdE5FSFAtoh913k8/rFRVFZIbTiEDiwnnLvXvOl8ol /e5/SPSpJq7NBt0jFBxbkrZ45POAJ0aA9WAhjTGApz+6M9fJcXBaTrPZ5P/PFdE1yhE5fmAE ayocCaHUyg1ddRH2k0dYbgRcddXEN70wESFvPy1EvENG6FL2dHtvW+Awy3rWa6UvI37CTETQ hmEUMNfBWvpKmbDMZJXcm/T1lgfr2QX/If0mcqSVJEJYYQ+3pujnXrgR1EBbpUiiryBJGzxB 1vxfg4XgCIU6GEtJ836twTUtAC1nQfIPT16SDFyBMLsRDn7lzsEGRSmm0Xzg4bR/IPRjs4bA l9ckDo+IRkRRnalPkzd7qzo5LpSHK53mUFEQePErk3RKNYQL7DtIK8+VRi89wpcmeEDkETJz zuQHmk7vtr+Zr/Hs8YjlnD3Lu4AlXll/Jleos1bmFDlDAv0lVS/gRs6g9ARSfOK45eSJo0XX I6kGiVNfmUhJ9cU943xLYOkeSXg9lfPwE77vBbMLDOMeHg8+oNaYD/HSBVPto2LDwy79lQEn bVs5KNh+b40MCsxqWusuoNm/zaAcvt9cCUfDi4qnefMPrlwJgW8GVB9jEGGWVFGA4d4LkIyW QWKMfHadshDSDalaowLrLktrENiq6/fsezrVfNgX9VvjByGECT6LkfTiJ+nnDqpJf3jPetwo YfKzXD+SD5hqih/ha9fUEAl733IYlxgZxYYkqFlAx3kgGjL6++SbaS7QVD+D/YVAFgMigaF0 TlPOuf35PwJsDrgLj1JCRXwZaU3GXv0grvxPDuvpRyY3/KD6XjrWeKSGRgAWK44p0ZsX9iEf /x97mF0pvJU+1Cakq4cqM9P/v4tUAcOcEUStYQ3w+M6P3ipLvlOEyehLlkc+Ibyta6LcbH9p +FhpmAM0MmyEgGftbxogKWH3k/zSvx3QvGYXaldEWLA3q0lNe++wwZrQ5WdMqe57ORVi9MMw kaGTVmfaMmZWUre98k1UyEck4q9CLJGsOaGNrE7+JQXyxxclG53KssWUUhYtPGDmR3rhMxgb JEo+LsA5ukN8YX7nXRfWUtQNiLFmhPteQcYisWCUX5O6ByurigbsR/+nYqm68Twg1ncstM58 ghUTIbXymNnBNYYVC9ZKts3GFe8pZhSIiLY6qpllhAURLokngZUO1r0NsfUci2WLOezxPrNr Stf7+jgNod9s8n+Ebs0l+iRylQTl9xpaYEbYUWZBLk2qRaVvvUACi6IdHyUOtUKwY+fYlLD2 io136MxS/V8y6wDCgW9Dxs0xQjC+tb2O4eZgd4BQPtJHP7EoVcoIE2obulqU7wffKzYAoVCG HuYByKQYsuU094AVNCbIiIeuWMe7a2g79NFYv4xsOplrE4lJ0Gp+T5cybme44Kb3DOB5+CfY DKqwnycHm+MsaRopVThndZUZFxvCvpj6Y36uo7yI2xDBDiA2SGhsHiZH10zGQ7Mcr/wfy7t6 ioOFIVi1wGSXFMIoa9OfhdkUfjIckdou91WNgFPdN//dPuM0L1xx3qabBIlxhRj1Ccatw3+u WC0x8uepR570zis3WF1pKeEIMYMZ3UTyw6EInum/M8muiTZw0CQ0yP39/Kb8kS8qGiFTLIRx cJtU929TOJkZb5i9ntxzaVmNfVinIvMEgL0w9ZsuGozFCg/l4HjJ0WQ/mOrQmmiB3yIfBFLh a5cgO0ApHvTgeZ46h9Z9oACqyKNDvW8t0zo8G+9j6I6vMCjyXEcoNSyR/9s3En0FmsuxmOVX i4a/yZYmVtBX9MpNZqt+sK/KThZFF/Jxy/ymnT175CKCQZEggwdJo1k1XlvH8D67O4cO7yPa z+h+6+/TTEFn6AvEO8MphsLRrBExxQt1VxVYXMYSD6S4Heqqd47SZEv3jDXIlxIGREVKPJ2g JxJPoeqhPFCdQG64iTP+wnDIE9dzttVJyBjCCwBPpl7dgD16G40n/MPrJ54dvMlxo5zo2kDM VEd2k0b3laKnGXwf/FNNnttsAGF4Wh28mZlj4eh2N+QAPBq2OSthVmXpz7r651/nFP/z1U2p d2Ba/HioQAu0r1wO7UNAGbcayl6/U8dJeTzBsRL4jorLrEOnaEGj6Xe2/amSQMV2VqlBSIKs SQpMkoeqayzjRUhwLKgKZ41sRip0E2eyMtqPebjA6hb6+nsq80zTseudoO0WAkZwhHynuGXY kPJg0IsaGSrl9BgeolRpZymacAQk68zN3aVm0dVdBLP9UNbdCCroTITsyJxVIu5G1DRR0N+D bxTEbPM5RhiZXBE4oid/KGO05tXtKbdU3XzhoPYwrMSq8R/sBLXBK0DdtzOIkWTkdwuHfZrM yYZXAVh+/PaElY77h5p3i1EPUaPGFJBLbbBwKrH+t3E9A7aNh5yfsLlRAgb/jWUeHFaZPwNt BSDgkK11QKJWCVAILLz5WlMnZnIwBtyfJnEze5kzvxtnHFZTY0CxSqZ5lvW986a8zu5bX9Cp 5wU6YH7XRMmr/NCVoYDN4LNMg+dh2Q1BvR+NoWulCJCqRj3QnGUEITqFo7o4gVYrS/anY4Rz 5MN0h1O6pLHE12paf3RB0i5SdYe0uZeFLcqroH24n3SOXvt/TXqAkQkuyJ6d+3BFLD8w4rHK OnkQumbNfoh2sHlFeAKBL5+yCsgZ0TygoBwOpBVZFdGXUQSuvlGY739jk1ChN5nOp5VpH02k 0vYNvnM7IA4o7RIh3EwFDEW2GYC0epYZ1lTAhNhUmz9KrVrE3mc6tdcD6I7oup/+IyhuRFa2 MXu0ZXoWut5juvmr3Y2tc6MEY+leRdyqpbPoMpQNhaTvBCDo4MKMWctseaj+tS6peLRUzLUr yWWwon4boaL81Sf9Ts+Q8h3F7zWLJjNO1c30mhWR+zeNegr0P0mBU3GUDXnADxjMLBt6Dvwt dCbYJnnMdZW1ruNgfyMQKY9hd8iFDPt73ob4bvI1uTrLhmJtpRZv5iqiRX9WcDsnH3bC+Fav NfRE2s7DyvFsMECUdacVbSaIRO7JsQBArWzP3b83ciCsyq63yYgrpMWKGSEruqSLjr67ujb5 UdbileYnwn1GPuI3lWzfR/4q6ieo7mULGOpWQ1aKWHDO2n2mNA1rAtQaWXJYCKb0PPyU2K28 e8fRC1ivRVnYqh/ZwnlVHj7TVYZW4lpLD/Xrd9ofGVjnYWHDzT5qOB7DeSldtn7c1n05cC9v ll1ZWRE60CcGkRRQJZvXdIHGR4GrUlJgdfV5TFW5hry7Epd8qOj2o+Lui6A6kvkBH93+av5W 7QzHMBoFcXUo2vHiY/202Dc2LdJPFdF9S+4plOOccHHzSrClg7cM6eOmXT7mHCIARNh3LZLd OWzSY8LtpCoNjVnNBa1/oG+VoAySuzUX7s8sUHRCvvNEo6yusadwedCxchevYTBurhMX5vF3 EzpT7N3Hq46mQohNcSGla71intaUZPemasB4co1iuMOlKdHUWK/LP/o+ktVI0escA8rOAusA b2vTO8pPOS1qfpIftbfbE6ZSflvqSU3NqrPF/f5B6P9o0q4bqqPwzWZJvSI1WuzZcrZ9+3bc pYJdN+yhm6RtsAbdxzlDDHGnPGyf6uEqYKCQ58mfdVx0qoqiXZiWGbhHCT2JEJsUIy6ZYLyC vDkeOcsYgkE1KaP8f2ZT8YsOEuDyi/+BrlVkEJI2yCKgHWq79jjqdkJSnYJrvpLLoNFVfpv6 +39icZUZJnpXGDR8jLZuBa2eDhly6/KeXnYI54WEvWA6e0ipedUx0+R+AK7wj82vuVEiKvgP 4eEoQAoGY8N4vEtQdvD8w1HghdIQRyohYJ39ygkBhJCUKrqSjSiLDMNRdbo1P4QJqQDDzqIl kSog9IrEoijY1NpU1IaNFdW6Z1zwLLqrfpuCfXBJWr6/yqdrPQgwU743koe3MVJW1VdJCH0N AEnpD/OpezUl6gKWJVG7ZydNMEcVWPKh7nWbj12dCwyy0+bjpkYprQzwrefGCghupwUYheNL XMxg4IHsbRk7bWC4QOyRhHbU4r6ia8hS6vlMImLfA2g6OiHndVU6UcTkE5K3XvhgzID0mkN2 ZUB94gAxlr7PHABDHD6DALslFpujx5DeJfuPZ2nHyJrfBsdk75Kb3XFE5T3xqX4liZQU3p58 AandHgPeEGutpBbi4kI25Ajn77WWy8jkXgwmtMlDwbCMIeVZFnNsKLhertt22+2KCpvcvxhp okjoB+ado/wHIrmKT0Igx5K1w+WK/sBQSeBNWL28r/Sz/1Hhg7ApjsZB4+Clm1VkPF377dp8 juijmy6uL+bf3CxTFqOPCAJ4qHPzxCMWPaHFrJDy0xGj+z4YzP9IeM5kJbZyB1MLloaHuBKM BBag+YLMMs2P6QToxw/Rf6PyficsKHzilFFMgJ8gqk4a7Qigw8LdQ4c4n0fe3aShHJJS3JK/ k064aQpxJAH55kQxpeXyeMl2ac3o8hd/FCZH/QNZqE4Qnh62VgxNbGhVoGA8cTA963CDlaX/ /mb7YhtsJzHPxk1Q/KcjMRNiGcOcd4HZJzZKXYRSMyi2XeDmyRdTNyh1cWPnjXi/3Un2beL5 V2+lxyB5vAGrFwC7BMKqvTE99koF3nXHd8ih97JZ+XZc+ZYfHg2/QTd835Zgvw8Gk2NdiXwg Ln9pGWjtFo0c4+RC+ncAkiGTkjwu9ZXkykmQTfNmoltSJeYhb6xagX6arTbONxhiqdroqmjo MKCPuNc5bgc4BRyCfGnunumqY/xdaWWR4qFiyJxBsqxXbzX35yBFdu4la0jD1z1XezWjJSbC YKBTwEldHx5I9BiIL72OFyDs7l6p1P2dM03ksajYBy+zmxclohlroqohcpo9HmvNlZN9BF3F ywgsm5pseveItwh52eLKfzPEwaEsFCLC7UjJMuwDmSIE8ZWryeFE5cP78PUyLtGRapFEfrSy rY9vDCtD14Ffuh/WceC5PFrE/iqWL3tJQaUmyNJX6nlKCvF8kfzwSiOWVbCmgAzHuL/ti5eg J57KAXP+0oXV/lAHcuPMQwNaLdWdctfQwwvtaQ4NsH3Ri6V1HzawkGgDpbCRxYWbViAfdFD/ UKPURFzeOMDJnW5U8VDAUQUtNe6Uu54yOhmrfxU3Bta4OhY0MvDnbcYyKzUrbHJaLr7ZzwKU F2Vq6Z13DnpVIvGj9u3FV9o0bNoKGeLMoQ6CvLjcRvC9OllYmz9vPnDSCe+frdxr1DISMkMp Ry9ywXi+1bgwN1Cl2JgacsDc2Ar4TNESI2z5ZjGkM8PE+yKnHtzspk5ANae9uGjm1HyszWbP CYOgQNYm6bsjF9QFWQQhiy86fxaZizH7yyI+cXjY17/xvDp4TbUSOI0c92WsXIaHAOISj4Nh 0RXMPGjvvg9nLjfUb8DMnYniwpeu4+7A4ync8Dg6UJlrecLmeV4jxfS6ZXyNw/hHL7qBPHV5 f5bY3zroD3u3KSHqWSxVymEptvlfuhFNT4IAZrN5TAQ6tuvhrQxfzV1BU/VdapvlSFR0Y7yl MJo96pZ291wZFI47fY+Dp7oKVrERcxpZ7R3SPdKZu/qsmj5SCTMvFbJWWcsGGtPCoDER6QWU BCjwzEieKM0MxkfDg7vExFEz+n2YHpQ82KDL5tVxR3alE77bzFxJ6KpvTGJUoj2r/fjxm5Vk RO9k8AQHG6sA9Pf9XLAss//v8TeBoFmMeQ7fP/Ek8EKJbjUKZW5kc3RyZWFtCmVuZG9iago0 NjMgMCBvYmogPDwKL0xlbmd0aDEgMTg1MAovTGVuZ3RoMiAxMTI4NAovTGVuZ3RoMyAwCi9M ZW5ndGggMTI0NDAgICAgIAovRmlsdGVyIC9GbGF0ZURlY29kZQo+PgpzdHJlYW0KeNqNtAVQ HNoSLYoT3N0Gd3d3DS4JBAk2wCAzuLtDcBLc3d0J7gSCu7sEggcJhMeRe07u/b/qvZqqmVlt u1fv1ZuWUl2LVdIcYgqUg4CdWTnZOIQA0iqanFwADg5uNg4OLmRaWm2Qsy3wbzMy7RugoxMI Ahb6LUDaEWji/GKTMXF+iVOBgAFKLrYATm4AJ58QJ78QBweAi4ND8D+BEEchgIyJK8gcoMIG UIKAgU7ItNIQew9HkKWV88sx//kLYDBjBHAKCvKz/JkOkLQDOoLMTMAAFRNnK6Ddy4lmJrYA LYgZCOjs8V8lGESsnJ3thdjZ3dzc2EzsnNggjpZijCwAN5CzFUAT6AR0dAWaA/4gDFA1sQP+ xYwNmRagbQVy+suuBbFwdjNxBAJeDLYgMyDY6SXDBWwOdAS8HA7QUlQGqNkDwX8FK/8VwAL4 ezYATjbOf8r9nf1HIRD4z2QTMzOInb0J2AMEtgRYgGyBADU5ZTZnd2cWgAnY/I9AE1snyEu+ iasJyNbE9CXgz85NAHKSGgCTF4J/03MycwTZOzuxOYFs/6DI/keZlynLgs2lIXZ2QLCzE/If /cmAHIFmL2P3YP/rZm3AEDew19/AAgQ2t/iDhLmLPbsOGOTgAlSU+TvkxYT8r80S6Azg5eDg 4BfkAQAdAEB3Myv2P8pre9gD/3Ry/mF+YeDjZQ+xB1i8kAD6gCyALz/IXk4mrkCAs6ML0Mfr d8d/I2ROToA5yMwZYAq0BIGR/63+YgZa/IVfLt8R5A7Q53jRHieA44/PP/8MX+RlDgHbevwb /uf9ssu91Xr9To35L8b/+KSkIO4AL1ZuHgArFy8nQFBAAMDPywHw+e8q//D/D/c/reomoL97 4/i3oCLYAgIQ/IvCy+z+Q8P1b1Uw/L0xjID/PkEV8iJlIIDhX+UbcPBymL18cf4/6//PlP8/ 2f9R5f+m/P9tSM7F1vZPN8Of/v+P28QOZOvxd8CLkl2cX7ZCBfKyG+D/DX0L/GuTVYDmIBe7 //UqOpu8bIck2NL2nzGCnORA7kBzdZCzmdVfEvrPLbyUtwWBgeoQJ9Afbw2AlZOD4398L/tm ZvPynji93NWfLuDLOv33kbJgM4j5H3vHxcsHMHF0NPFA5niRFxcvL8CL82VBzYHufyobwM4G hji/pABe6PkALCCOyH/cKJ8ggF32D9OfiJ8LwK7wL+IBsCv9gwT5Aewm/yC+F5+J8z+QVwDA bgaxfWHxHwsPzx8WO7t/U/6gx27+G+QEsAP/rcANYLcAuQJ/879YLH+DLwWtfoO8AHbQb5AP wG79G3zpx/Y3+MLS7l/I+dII+Df40gjk38ZfYl/e8N/cL0Ox/9f9cpD9i24hvzHhfGnN8Tf4 0prTb/Al47dJvRzmbOUI/I35SzfObpDfEl4m7fIbfOHi+i/keing8Rt86c7z3+5eYj2Bjn8V +y+hmLk4Or48oH+u8ouK/oP/fK2BQHegGfLSPMRMONi6LvjzXY0kiRvr3lfRGdq9tymMrF5L jh0uD+iInxirMwI3HH9IfhrpxVzdkWW4kVimePL61tqAGNaWqNH+0/vxfbzm1F478uIk/uBE wTfJ+gEyJFJWbYl97ycH7zcBNrCt0F1KtDkOLgLo6nk4d2798u71A2UrY6Hzexr71XyvUR7L plmjdaIMAopnaXNNM+cIqRCcWcleMWGfu2PM3vyYwc6eeKZQimdG9jmJ5i70erfJFXM/57lW oc3l1E1EQ/SOkAz2Bntsis5L6jBJiWDBq6Rww3EseQ6/Y3zL7iOn7SGD556q5p3j0aURHe2E EAMRITssruKHqI02hQS7YsoEBJ7M81WlDXfFS/5WUycWtQTQs5otfz2vJorgXs9Ddr3nISID Xp0uU5imFd6negpwH28YGXR2PR16eP6e5dBjNMG6wZDZ2ugabmOLILqxLFlrh/+2ZUadW8DR mjblyKr7sOLshZLndLjr0Q6TLe75tVk6ZLBrf9zJ3I7ICPoTbWNjoOhhTdunbBkUZpIP+PWZ ZC4/BFtJ4ImjqT9lpOW0cjeqowy9N6zb+4bCmF592D7ghnwXPnC8g1umU/YsWV2ZI5CBVYCk gBgbc98ME7Y17oIvP7klJLOOHbalFB7ziyE07+ptZe/VeOfVmWE+K4cIW5mllhQGqqrtR5x3 WWpxymczuTG8JEaCDX24v4SKX7cxwXt/l0MODH726osALIf5l83LsmwQZf10+AxDINZhzWGU 7P4tqU5j4Be9bt/Rqd9RSMRnEBHqiDCRx7sR9RvnFridPBh8sefaxVX7A3LOAK03NdA+sUNC Rd3rZSZX5hxW/Qtefn4idghzXG6nY9lJD6F4IZa8g76wgUnDZ1DI90GkJILygVb+Ub4Tp1ez jCLcWlOEaCHmXeUwSn1Q8wTK5A5MH266aElCdkTc6DlznAKujFRlXPOborIwM9jk+xu0wJ/d 3519L0jA95xJ/8mWqfUhUeWagjF0RWSkOeq765P6jJU/tQinIrXa+z2ntYL2/mG5W0uXmr6d U3zTTesVZmeE0LvnxITc859o2Xbq5Yzu9A87sXRcfF7G9hbzVhgRBLcTj5iI0SC4J8sLMpXy CYN2VcSKK/QL8lrxN2kl0wTu0+m6wO9mJPagotHXqD2pGEfJ/Ku94hopdPjpPDD97/pnGZN/ FTATR9hp9NPjCPJtLSryI+SZCOzRy2TATFFR6HLkX4y2pN0zH0+YrxlKHSXhTqOJDyVYFpt4 NJ1JFtVNGe02lxkjxN4I4qfxsh2BPjEHRXUqwbtXowr15O+vTpzp+WgeTFgO7Qn6Vk8eOR/Z 6jzgeVKWGdKHOYr/FGeyoNi4846b+zHFkCd7Ld8z2CUB346KBbZJ9/U8BJ4uRw7kq/0Q61vf UcqKqpfMZsz6mlIept+PhNBegZtGphPRJ/oE73EWTch7g2f/8bxFM1vntuUSh26I43NbCU5c IH0S62Z6aZ0AzqcpZ8VnSXemsXyaLcpVSwpNWEIFfy0o0nJhzZ43UKc6m/4n4pS2RdEqSxVT XJY4aocrbLgh2v38iYQPTW4TiX6M4q2whdKvNnKS3pji8htt26Rnld4oCVeYoSGrdn9kukJb ipYn7S4q2FzyTk+Y7SMP1yl4Nhuv2sg7RB8psZ3120rkm7ZK44PXR+Ja2miczI4jp3i36apz nbZt+1ndm5bxzVALut1520J5Jhk2tijdZxPkgwr8a6WYPqeU4Pdk+WN1CanwHjF+S8TeXpqB edF8/Q1Zo8lSybH81oq3xIgBBGH+wylcycRP9Sa4EY/FtKjPKRL8PCgSz1B4xzwMCaSf2USh vwPGKYyzpq3o7Sumd5jdP7mO6/qE1ol/GMOSn+fGkiETSg40aoptzJ3JjmOia+W5sF903HaP ftziBcKS58QaWWGk20hcaL0fi9mjkLY1MkIY81luYnUQlGib2gA+ryNJ1Lb/KkLMafaOdFOJ dEw0wxXcUMdj2M0SsRFoR6wW/lTGP6TAnpjfzJOsuaxA2M7bWTnjjzC/p9OIt8AiR+o9zrQa FBUMi1MRaUKxZx+BThikqoU6qU9JVwmPE0e6N0Dj5z13a0cLI6bdMWFTs/XqyNElpEZPQgUc 2ezy9a0xrTgxhoYA2bWbPLclmf8v4c8o5oUILau2oxCkceJWrifURJ2tqxuXbr7tFOn5D7TE A3raN/Sa11FDxNbTUNmQeU4ylTKwj/KvWGao80QhtV+N7GPGtxJBBzPZMzF7eFB4IzwtMQ3l SsjowVKoH8aGacr1TOZqFPCQJOP9LDnwFTU+El2JrAsjJP909RY55UOclV/alXCOdtANjRLb Gom1VySopK1hINe9dv00us/vw9kgCG1bLln9ernKH5qCrxDrVVKSYWIPJnPaw2atbfz1ez68 K/okom+T3KvGNkzaqE0MVaWGWX0YfLyai6z6PQyylSeSSpTcTkLwQCbJvOPV/DFU+He/yoZl nRpUp6LsGswmyy7Y2FbuxVDDesNnLjPENLrC6FpJkobcq/a+jbV6glPQu8JDbaRLaiwc3rIu fXoK4nOIgCAypdgzs/2wtLZ9l+NIbuVMEvtVnFuIq9B56WLJg45ELpXSTeSHA8UZ+mlNuxyb ygy6F2HplnCaJAf4wTShSty1H0dP9SuzUvLgTjXOAB9dDs1J+s84ERQP7GNqe4zbiRpYMHHQ tXUNm/buJxSomzDCQ7pyrDCBvdlsz9qBTHlIuGD32CyVEUHlvb8mZgGOe5j3O0qjAYxON1mT BYva6e8jzSC754xoHh4SdtMq1ecTeuLUH7CvV3q59zqwLi6PagPK1awmlCSHUtPqP4sZFWML umbPxHkwkSDSK9o5t8xUCZmrUp8lB+Z/VJ4h2TfRdM/powx5NKfs0ESB/pjuF57WyHSRgxDQ tSu4n0OgVTUgY45js9hHnGBKU/Pw5mIotMzIOYnHx4oXGL+uoBru2K9QqVjIotaMyEe/WUi0 NYFlm1dPEZqOHPwcqqp2TLhM7W4ChTSqpp316s0eaztDM6VSY/O7Tg/dDaSOEkrDas+FVYkF tib/0ns8VN7TCKgJ1thEGeUG3veOSwp7R5UOloHF1ezkjgfFgZiHluPV6rSJH9wBFebHXUnd 7jmzkk9m3wZSRtsmcvMe9czXGIKZhLLuINHmxuF5eZIqD+qmwVGhrOCC+LCjame4BEPqxsKI QVtLupEZYElyJcZhkimvOc4Uk5osEm8cWq2OttUD0Zqta5dgO8l7Ruj7WaIxGnvp9LTBb2SY zGMMLSoxSHOfl9V/vvmQoGafOzrkbCZt3DaXs82RHtNf518lwFuhJ8kwQH+UEM6plIbCiEpc jfNxRnQULC5rHxOzZeKAlRdpUH1/TM/45T3PElmnz2u93GrmRvN5MSOz9Tcf+AaxOWTfDTqz DD/h4hAxVoB+wAL9AGoU9ZUz2bxgrCISkIAU7y+m/cHgZPdNcIcERY/sTxgZ9WexthwgDa7i zcqJUQt4qdsERa9MDO8uN8+GerPKTbzHvm+r4Xk8se9py7kxE59spZvyPSfg80y/uWOdV+Gj OWrCDkvitMSlIfNiU3xHpPQKhmfrDRjLC+6IQ/NEp6rr9UUUKQvdXMDyEQlFjQHxYGXc6u5k HqeyVE35BDa10m4ddON599WvvosWMnsCAg68cQAu1FfdECVsrPjX/O+UZahM8j9dW+wrcpaQ is9aO/fRjwgIsTNEKWbJ52YvIyJAjTbyRQ7BEYWloIkEMefWlTr+ANxluGctWgd8EQ1v8Ktu F+za8+xT7KSEKxpscsQCyqt26araS0Yk8SDoOBmaClvGQ5NHsyoLHUTdsuNVLFeN2eOYLCa9 whDameR0vx/6eDm8axyP8Kb70wWdrCxMdoB4kxkmIfr8HS6q9EryUCo/fx2r8dASDVx1pYrr BuIx2TG+d30InVN/1FfUKj5dyn5LarD5RJh+ohvWbnAAmCHYfCkmGTILobgtfh9y8hHChb4j stZehgQTXks6hNaDAUMe5q4Sp9hlhNxxXalPYy6jffxuHvMedbrPur95MzAR5K3GdiAr6Gaq BdPmNCCF6Bm3NZ823EDZmMZleQ5TMP+Iy1eCubkybopo5phC0Xq5Ev+WmBPdT5JqA6ybN3bB 2QjdzhMCjg94TdajJs2KrypZuiUqSGDJK3r61sh9fIwB3j2gof95OUvWj7ymZ9lZgADTRzX7 el4xRmY0+GNCSkRXeVohRRdlQBzhCMw6vD+VoQ90kxxu10B3/JKsNg7XsJ0mSASpqNeR2wSf Y+jbACW5xXbC0CF8e6RWBt1bPK83JPNQVQgr75/RytA3+4sb2ZNT35ohB6DtcSYu8mZ7xAvU k7Cjts0jvGnbqS6+Xipu7bsMCMzEZDKS8yGmoBZHVSfZj2nxZ0V4PPNNIrbr87U+/5iR8ErO lfTNIIAi4vX5IhsmogG9Xt6PwZjrd4GR2TjRZBHh89772IJ0iBkdA+jrFo78GFtN/hqffcHN rABl3ggN7L1Tdv1ImA5SQv3EQH81TRdgMcGj2J58/wRKoSfUQ7W1+pdqFuu3BwEf8TWXq1z4 GxzQTtrvrO1skUMj07izKVfPiQQdE4K/EUeDkI4wjV36BSjreGmI683gSu51dFIf1UaFfX1W SjBasO7MxYIjh4lfjaKPJd2jUVi2dSLCQ9vqPEJcC58is5mx6qk0aD1F+2lKdKCgXUSa8ZT4 NOWTf4w2rI6Fudqt79YT0N7c97Vn10/jGlaIqkv7BD+uvudaHZq1ebrBxaH7NgiDciQMrJXn X0iAL1RMuovq4NCw6GFvi/+BFPmTgmjjLD0LSKm17c0Vkyg3KRw9HwfG8+cWupG3jgu7ZfS1 +ZQ2tqRCL/mheEVTTJq0bUPFyOfBMNRcWcqlhcEtZXiADjAnr8SEcTbbqRXN4Y17KO0+COkq BKlG+b+WUJVIifqGm3JrUd2/u3YfxLVeU9ALmnfM5Z+CD6UlzcNxj5wa5ynk/3Aq8KX5NNi/ Nmw4j9fGd07oV0emjJs9Vbmw9UWNJNxDJdJXYy1NgyY9OPRatmk31U2CJ+naeJs9D5xy33UX BeojBgH0CVX+eoArxga7IgE5iqXwYSKHigWx12LCTzluMqTE6CAtNwWwvY9MLccp4sO3a4+b XROLgiD/kgxJbnHZHzFsmpjZUujQG/B7AcnwZhM63mqXJcytOmQ0DY5TokthEXFVJOC4p4YD XuOxT/ksm1vss+dGjsK84sSCo4vnGGIaGaoL8u9AiEEVG7cZ8ZbJofaiXqEz7zGGUzlmFcbF GL40uLztmCn09E7XHmvYeaOoslNtwbSRH8zXi4c4ZnZQtWwkkpyhyTvuyupWxbSngrEYG35/ lcQZ+CavCBUUJr6bF6gkZRGSQ5T5jUyzCAYR5LWrQN3AY4XCEAKdQ2I54PsZWaCTdT5m4Tik YxxX4o7B5ySd8DFiH187A0EbRSU5I1i9sjbQ+Mx+NjzX2DPK6xd9eka4O2rEGR5zWgLyFwKR 7yLOCwmCqmlLPWMbtooKZDlrTpl9omdOQIyase0xOIIffgWcSl/LSpmiF2q6SpX1U5v7o52Y zCxvJBZ97WwsXEukBdZGh3CCQ9HQBLXt30nEGmEFjQ3CFgfngPjtm8u5mj4FaiiX1/PXFdh3 ozXjm0scMGoa9jxbiS/r24XYi1OfuOcnc7DAue2LQzzrL9ObV18pbruoSilg0J9A15/HEAy8 eVuGF0WpyzcLTNNtv2L383G68xjPTDtlWPER5Iw47eDo3nVaSgnvR7h1gY/YvyY4qHEaypdH 8wg3KCCQvlSCymEMoNvotlOJoCWB28kZ60JMM4CT7OqZHLvkt5euyMlXLsYuVJJq5bj5gXWT rul7n2/3zCccFFOJ5Kq+zYgjX/24s6dOSItRZ2FIG6vmHOAX27q3Q2hr8VnSBnE7F1tsZD47 ZKuRwqdJIvz9RHPdzjN86dVbXLqDEkZ46vuvC/41aVHzP5lzCWhG4rj2Qe9TS6UyPV3hzoxJ DaWPhgzNmA/9A6ai2oIb4JmCRu8bq/ZUSDhaP4fe5i4YjA//QoAMUqxcxVzZtb1BLmUp1Nb/ fIWQvzRvEnxGP+AYs9y51PxVlDmH7cj5feM0C71/Ua864/LVZHGWI9MM1hbP2xD7BZocFFId LzLWqKaSqUCpCJIrQHZUKLHDck5qHrKJsdqYt8NOhHkKfO761lfuI2LYmb42mq1j9ivvaRXN h2ZW4yiSzWrUUmG+fZUH74HsPkvfS/9bPYBLmX6t7SUD5PPSM8JsgCVxqq0sxolbYnNLz3ww s3+Un/21+XK9ri1urIyuCwVuXpY8Siu5KZcKDLASbS+CCbiwcLcB0lzRdRdolTxMlgVrYX8y 0MTLRcjxSJad2cIISO+FTe0NIrGeeNQW5CQ8U08sdqxuWro21Pbun3LhSPXcfKsSqXUgWhOX CHsFJoFeIw6atkm/T//VH/0KOBvNchjdP3dHIZk/L5e5aNPAbmpws3NY56q4drs/AtOMApur gb2OfZUJLVM7e3z10+bOKSnPSqwpzTgkPtskulS9hsHXmla9KrRleEQMA7lR/q3tJ+WAKXGY 1Myw3cbz+6IfcGvxpXQ9kVYuN1B0HeSS0KE0mFGB0bO0DzGCZgbqqFTyDFTrqAPbZfdPN42h WyfwI909uJ+mMaE8Q+BIo7KTmakSd/1JWnCXW4LK3mwrRKYm3CwTNUZzyi9n3yq4R27rYXw+ 0q4bny4fgXaKY+2z14pCKO+Rrq/LcRBCDoQVFHQHmiEYas54eUrXwoa1iXuotWnNs+0zb2pT Gz8aUy0CApAGbeIzbLgk08X26EiDjOrWDok0PadELbAijpIY7yytJdcS6d3DTKXUzUWqdwqN pmNYZigx+nJd5/bsFlGUKONrmUSqatm16mCGe2FEVcYEfXTJ9Fc0ubceJLmYVYPMv1Ftu0LJ 8SHJ3iTon7Fh5H6deaeqGihDQrbTe0BhRYgXle9NgX3++kCMd/oDGy/D660HvBkxZsTQIGae do85iRK8dfjMmEmpue/6ehQtnz/eIFWQsRo/YkV9ivgYfzEeT1lYzOpdeqP5RsWRD8mcBss6 +rbcrQpInN1WGX3KQMtmzPbjEs25OxHZmPBi2C886/BHQyyYc88KgAH2nFoBamZu+lOD7+12 cdfVamB+LYUSuvW6qbkwqQ7dodtAuZtFZqY+v8mf7RGsUOh1EKjhGimYwOK+yPt6ebngN5d+ nRfEFqCVhsA8TCBBh9ERGW/QP2XYnWn6diOXMk91vdB+Cc+k7ztHgkXsZ9vYNXD7DLKsTDRq gz3iobSj0EXNFRnW3uyJBiacaP4uVPwh7vZY5ttGElh8AS/yeDtpncVm4WYN518kO5n6VZHv NsqwsawH0xq89WA1eCiG96VF8N4BJxa/E0B29x5kQpyu5gWgJxTKHzJX4EZVrhWSD1vPcw64 oU5Trc/aK71D+uwFzkPmRSmeHbDEpz+H4DSLysqiAydhxbb5sl4H+FhwXbiZxBuaiIlZy400 14b8Qk7OSi57cvoc0jQJ1XKJFJkwjNj5+CbuA28iTMfPLwX9wkzgcVOaS60q11Orxy+s/gIe 41/iajebfn0nFz0HOa10R1E4MmSyo50BMaAE6N+Etz68i1Dm4BdIVcZDG2IsbZF9UGkdHx2b 8n/9UaY3eJeOWusZWpfs+BEWlWXEZ29rmc+mbQLK1NT90/pJPZt+JXbuFPkO9lFoMNRM0k8E jqqPigI1zyZIXlEplRuEluG3vd0nuAgBKGTZzw0FCm9oclP34iMvcidprJX8gI4XoqhmJ89q +yZP+lrtt4U2jM0PmKOOOIHZXyukkbXLaod8iy9OzO9CjPx/TEV2yD5TWPLYr/XZINauaNpl 0yA250wdceJTQeACGwwzfacZfNTVkvJBz1+aBEhEdU2xl8PWmRq609MsS+nalB6Ik7mx5/TV PtFiPl4BXH5x12mt1HtkgNwRp5KWTtoF3HRDl24zEzNK12QWY0qLr6x17K+aqMljHnoRueA6 mvEQKg9gvrBFKYHQy3vSyAaskD52b5/GQml+JXu1xPvp4yTZhbRAtj9stGU+m+1henUHWTTV 5+x1T+fVb7UWy1r1tDWUI1Pu5ySHVDMOGtVUOzA8tcrTKz06SKUtPuAr4tWFUaAja6F3vfs9 1J1oxaDfqnLqXlseYdrAt0lV/gSrvPIygDMPPuPjlgDzLNbP9IJBSpUdvRI0rO+FCXLHnTvS +0+qNIOK15tFYjJGlfBxfUb3Ed7ChNWMwtC+0EYKvXrlE50J64xFYfxbOng9H4YxJIjrPBOw OKt+DjMzSmXb5wy3wUUmM1KdebjBIJkann2ljYxIe0dkYEVNm25PS6aDVNEBMQ2M2/DeXOwV BhQwv2rpt7Y8v9t+Xmrg07ViVBYPDWl9/1jMTShLKhOfIdQkh0DHDpcFkgbrdmTbsZUMymsJ ThciySwVQfrn8MMencOjLIv4jLRrWbp9c+G/09GeBLaproSfParaRzsxTy/KnokCLHYdpMgO hiIuwI1fznXwZ3jM4D8kE0GL1qXllVTE5zlM6gjSI0Dm84jQfvykvtD9Lmvz7AdwTOTnlxxB A2BG6lP6ePZ7ZrIrYT7KJKcqNMYgtCqBO8uLZS7dN5GQ8ljeTQk8DK4v78xKSx7kFpvI7j3g 3psqC8TaEJEPdq7Lx+QECCDu0AzeBjEiXC0YcEfBKDWT4DjIcZXjBmbRjMEpp500sZw0XRSR LYs2M/7si/ETXqU+PHm9u39aZbsfF+vsC4LyremByEp7HZHV3I5TIeZ688CEtLdsZDKb4BsE KhOjo+nxsmXgQmr03RNhOqFb1CVEWSdPppv6Dmk6lUlZGFp1YpOEJlpdqPINt1Imv2tdch06 pF7G0R886JIpaIhYLCK2wuzil8Q3oQxXQHuW7Tfv8VmOJknxta1KfQPljznFVfD489PGDxKd yOUGRc1YOzL32ujbt/H/WJEdaCN5RDBFO/xa9+XbJ5c0QtK50kyZYe6nJBfu95dXh/uWDgpv xPtmpEBBCxrQF89f2zOK4n2OQx3qbbo++ZkWaUHHpBBsjKJTlhvJIFigqIdFv+4o8SFsTLVZ tduz400bGitGifrWOVy8aGmQc+9cXNeBt8Rw4HPfxlTSF3KACRccjM5g3Qt/Hqnmy/phnVh2 s1SoyKlXB/6RN5VLL/mH0sfiDhZdHSr/LE9T1aQYEQJ+Xtv7KWX3Ewp5yfQVjFloX9rdQu3S Dc8h4KDZddk8Q7SGVXV5ogQH2B+5WiaS/BPrvjq4npsHTmp/0bWpw/+AqWc0NBolKVc320qE 3L3JVtySr9BjIN5U/RFuc1OWdzlxB5T3ocEfNTLT3ZvvoP2QUs+lA11hEIVaKoyn7UCHB4qF yCj9vaVhEq61D1O3VZVZLRleQXpBU+L3iUkkyev6BRUVcQrgaQ+VTFLRwYY0Q6RScKjo7KBJ Voe69bfSjr4bVdxgRDqyL3R5wIaevqfM/IPyOHg/SKATARLC7fT18cB8lFB9CmL2kVXSqV94 uGT2ye6DUyVZKaACtikWedDYkO/7uDuNt9bbdSe2GL3vXDta266VuvgneI41evdJAsQVOnj1 IYM0fXyN9B047Wdf40du2B0ukHGmg7bFM2rVO+PF9TS3ulgfIkWire1yYtWTgU2iAroMxo8o v8Zd9ZUexYN03JprFmcRsT3Zh5kvrqGe6BPco2adSJRVRJsodT51OQksIV9lJkGolIpZqLKZ jF3QVzAJOAgm827QRJQdnfOLa+1tFxgKp30TCph3dK/Qwu1bnI/e9HfyZCYtmnV/O1zKFi9q /PGMsooZOfK6idTHRvNVCun0CclW/+Pb7dlC6Nwdcb/jBecsE3EW9sH00Nx+eCOnFhG8EZ1d T1bcEtnMQ38Kb8NyQnJPY2BbklZgjDm51OUT9nTuA4/uTPez79R3PglITi+2T2tR4aNyqkNh qckgX+RnjK4y2OVfbUgeJoMMwyhVRIpCd4rK00ILIZp76fBS1RMzKhE78TmnmL4qYf7nm+9h PJ5wsHulvrJSt47nr92d17uExjPFwYuugoN5vTB26h1K8xnY+VrP840lXNeavv6M25l4Zzol lPIRkhC9UVExf9BRuXnQOiWGCS0dt0rRQtqqTYikLkbA9xH+VnOlFFlQImizHVeoKS+V2NvF 1wK29FL6koGfQTvYocL30cq2hbNi7HNClSV+jgw9St4DKX/M4uG7gr2n8ovNMOFSjCsOh9dd eRlp550qSW6WFP6h0x7SzprlrQwgl7xM535AfK8PCTdpfv/UvfneDexKlXX/yhwjSDoFAiW1 hXtZWUoSQoO6bNVg7yq8oPZFQMd6xuL7T3lSTfKaobceXxmVO6fGSSsRJKVNnteNu8BxOAff 657y4S6wd/nlTsfUi8cJfHG/IOapVMuvDoCjm8aeqt93nDSGKnliuEDFCDi9+hmi6KatG1LX QqEryiTanr3jDiDHHmcvG6xffBziX4YiGuruCILx0xeEmpPPNO4U6c61kOjrU9Q3atGG4xjE VS9U9HygxFCv27W8G1AoLylvZu8u04Aw2WgIsx5OR7TI9qVOanFRRrK6fFpP6yNYL0S0novk vV4sKItditkOYTofOUGd8VyTZeXeQ2rSYamXegtnoCxxIfepzFKYd9YlcvLre05p1I3dWH0N midGfBvMV1dpmidRc03FxdhOzwsoiqFoXKdxviOQvNCASfFdOw/aTLj9EVOazQZbzeFqqr3Z EGTp0L0v9qXLkcdAFZwh3gZMTojJxw2xRtX9VDOUHivt45n5i+4OOOQecvXsyQDOXm0sFdOd +4FqqptNRra+qDvUtaqeU31kjxvTCaXjBpc46BNqcqzsPJVX9WMJ3OpI2InmPQ7MzRm7wacZ p8WRPSKsjbFplO5WqgU+e2q1RgmHVF20a13pH5Hi6L8rRBPrwGf+CoIR/bbrXzRgljXZGXsw CV+1DMt9uVQefUEbbCqn3dgGNDgzWplxJZwuvA5rnSMu4H5vlHSLUjIr/2OPaQRsA6nFMkea QOZwPcnbtbFt/EYKF7wNJWejViTCmNMfEw8u1X3tJXQpz05FWlv6TqO2Lfj+x7vjTPwarqZR KD869wZz7M/C9YGdEMNwqUy+yg8RtzQ29FRUjZlmNF3r43BiXNrZTQWnUs4UPAec5aSeHUWD +D1sSgW9J3rl+GrWsJgHXX7mY95+kXl5zX6VIjqsLXGgrx6lDzEkbx3tM3QCuSQQsuhxZNIP qn/VycuwYUp7FktiioM2H94nyuq9VVWpM8t0m6rSkx0Shrrr+nDYpq8AM/ja6YzNhyOfHyLX 9d4FE0iRU5Pu5Eqb+bCGqAr9VYqSeeGni2LB19d539t8xVdsYAx2QhlD9XX1PE4rvVI5Jqzw iCHovLDkfTJhAfbLhYspkg64SmhhoHcxBxmduVedgn6tNPw6S7hhOzOvnyU6r2DdfNIjjdLx mMsaMZ3oSjLBQiGTUF8GJgdYjtauGmlsDBIR0vr1oa1Oe8jydyxTEXrDfuXZRdWwlVMvfdVv TURFLsD2jTfE/FyxmTdHBT2JU/WldFs8mPMIHC5xPI9uutt0ddsJohPmfoubd1XMZbYTydpN cGtDbv2KezotcRuFhbc+bKSHZSfpQfDmx0at02jasG+V45fBdPP5pGbFdNqwFiFpsbP5KFX5 GKRCh+YcinFGfkJV1UscMauoqC9mO2VjRetCKYQfIKpOflk32nCBJnkR1EfOEe6vRotD3kgH mkvNFlaQh/Sq63A/n8sRc3sPhotsrHX8yNccm0w/33GCar2cUsHkEsKQv061e6JSUYDBOgOk Od0pH1K1mwyaIA/uHElG4i7Xf/vcFm0Naithqay94Fj7JJ5XZBcMFxe5/A3mfh85bc8ZZWri eBHSORkgqJCCsj/2hBGp17WjuQFWAdCtrxpKHn6QWelH5n5v9jOx7GutYt1FzJPv1koLwK7F ZkOUe3Wy5CcHppUii5WpCHGRgLYurAKrqcrcUsss9tr1WPhEIyuiyMS4ReidItaqlRlW4SVa yIeJTDSyro8uK5sieNJC2Gkm+ZrM9Q6dXBhfGLY/im+RkJBcgeeFSm2GTqdgs054UKqhWoVe 1eCgDS72S3v4slQu/bQ4Ol9H3XU3nWEPnWZsHqAdvgCfzcl82V4YfDzbvzQgFc7SaGBM9BAz T4Pi6T2gL0GDpyFR1OlVqFMaERiBY380+8X5IVsmY+FtdKYzPaLENY+Q/6BXuo0aOuTwp/zk MFvKm69lphGq9ZJL4NfHT5dHul3pZq59VO/chFBCHEu9yAmouO/ZDmWKVqHvriUdvUmBctUj pSAALoVnNp0BrzstOjp+LCH89T7uM3z8xu7F0cFTxiVXNFNVKSoiuV/Y6z5tUzaDCGVKSHxG ICArJbPUWHo/RKK7JpTPkeHQ+gk+DV/t3mbqvi03aplvyPFp7gYiPJNsSDZWfqIjiqbkb8Mv maQLwNpGOFIzpmyR+FnxJRgsvvMuvkBt5cL4I5z76Cv8Yl5qai1Z6N1OG5rBXuJekSd+C12R 5Opzj5gl1C8P/ts4uesDlvHqsCi3b7T1yrlg/RoGPtLUQA8PgnailfGWCCEqmPcL24/MFaEj CkLmSC05ssXRdgejlXhECI26kaOC+A6CewNVk/nJ0OuNXWhsEINnZE9sy9cfrU5z5eEc5pxf O8P7JzPWzzBfB7+O4QO8ra+8FAITT9y1Y0U/iBAcjvYnVqd946cGhTIiHpCGOOJR+6yJaTSn 23CQQp6HHFAzGFK+a6M69Wv5S/cmtkOT0n5ZipGxlcJYpHC3ZjqWgHaT8QafeMQ8yrXyRiMq fEv8LlIw98uvvgqU2jA2A7c3vj9GSdQT+nZCP8X+y3HBIgvVDPeWBjIRpkrRW0Guw9HmuPyy c4yYL4I8pZkwGpKkpWxbXa0FH8C7/kZLa+WEmyEDHWfDIv1UnEGx/VNDEELhE1Xqm68W39uI TH4tkmUaCmtBYdDx++iVVvoE0cLBE/ITYecZtXLYtbdVrKwOzc8YtWqOPdUS9N/HYvsxlxCQ v58/cQhxsS+0+Xg/k0gtOq66LaFTWNBQpW1UMJxBlHTD1f++I1DI2ig7VkGXYTJYXFBEb6yH 1JC3mpFv5HlkWnkzHEPHfee9Yh3YfJaJORW2HT9AKN0i/tYbQD19SBluhvMizlNHr4M9vSZF +4D53HV9NH0mKS3FfFHFdShmKsIDD4coHn2UL4XVvD8IVniW3N9Vgyqb5GFb3h9kxyF2iBZa 9k0dtPFZObFjpz/4OUjIEGNFEWQJbejVsZsprLtqNLMeM/ofZfgMsOMIX94iniVQDVGgzXlR a/6g80H0In3FellZEg6t7uZ9IIrsVlS15epCt5AD3Q3CrRy8lwhirV8lXeiwBhU0mh2i/9om nXwUFh9jUZOPmQ+6PNIJHwjmZNv92KtKtIOd1Gzcq309B7Trfq1NVf+ZC+rDco9yy6uAd9Gx ymOtja35vfoX3xZndNP8YrSanWdtdKsJWuULDf3TkvweIc/+FV7L6twfZoYNVCWLxfbO6vwu e+ZMdEbXv15Z3FWi5wTXEtVVJdKgaakvrDHEB9Go8KnepxsINGLT3dXuk2WuB5H264sahP1A U+NW9JPz8TDgiPNdVpwmichWuz0mRLgJn/I6btwq4c+v+NlW3Gy/5bcIb1iMFxKWmuJ0SS7f 8erRTF1PcnAwX/8q+aI1wwqCMjNm1H2Cv8hlHhXRZmMBuqZSlEU816X6TrUnmEl6nVDuIHfn sbvsfSR+g6HjYmB3TlXBkFg5ABX+7YO/92q0PYSN2wB9kmxH1Mt6uUC4x7eL4qKc4+hrPwF7 0PxV2lw7hRWcbK5tisrPp6nP3gOdH/fHk6xHbwkfLnVR2xh1WRZDtb+bq4VmFa+mcQ4biECR Er2WDOhADjWzeHtXm+fhhORzabA4ClPFJ4R4Q02mjSNilHo7uiRVRsSws2t01VO2TiDnZ9bM CzfQx8CdZNOfQhEc0fgF2cJTNQHwGuvM2zWQqPhubh6RxdV2IjyTX0JgK+BOiavY09nQLfFC o5DuIuFYs+UQ31AqR7HaeNi4LJMmgtq77cOJl517oddaSkuUE5PZuU87xizUOXXSSSFtda6h gLOfnwGiSO5xOFG5kC4/LGVdilBIu6xC8U1parfX59aB2Gu2puLHqhrEwzLMEVuFoovSnYwv hpOAH3qYw4VMP0/SZg0MaQglwmQpIA0F6OIerjwWmdDlOj2XiUNs5HtUxnd0VDiUwRqjkeCH xNJdNyy23UYUrzeU64Us8VQRKCC9NG7y8m+1YKyfursGGS3v1zCDzMtqJpOInbG/BNAblbcv emELlULg/DPrIHpq45aExYHkW7eqFWVM6oGZxJYZNU2WQJlHNXUYNtJi+f4WfMGRaWjvNKQe piqWSaWEbTU6agc0/aForntv2BzaqtyAGwQpfKOx++Ss6ESs0eZwQ03nwoPJAPfOnhIu7LdR BGo4nNLNbJ+gh9gsOVITmEq1gliRVEH2RMELJccHSibxUhNFE+iJZbnHMBMCRhkWj6qrT9ew 2M7nuJ/dTFt6P9iSAg1uMUzh5WYoRXntrSzGxcz6+M8oYAytajXEMYj5qImXi2+D/VFhgwsJ Od3EB28E8CvemMjSvoUv1ItRI7h2easSe/p9W5DI6qrjEIiV+RY+S+9JYuVWea8Q1CFKU+JU y6djGeOCp3wvSwCK2g1uk82YvxtOqQSMcHNlJStaCA6YdYw1pnymLNG5B8FJtfocNVIDTR2i 5NXXAkb8qUaYnUM5wiPzNZweS6XqwwQfMoHfxOtsHWxgTpRrwNlZezWoq8RuOuZLrqInr3+8 MvsOnJ5AJT1c6uQwDrIvuJ1K4nZ4gi/VPbC6+3kBqDPEN353jeFmF7wnc6sRqxIWaaBT6McQ lyr0zg7t17ALN9Q8+TYDwpvdCiEjtT4xoEF6fMNxio5kREj20mljEINLaxCSS03YY569Vdoq 8Ihj9GD4TvxrMzrIExG2qSJFJOk9qWZtOj/MjJH2RScqS9XYwtcvU882nDJoHibWyXgyDom7 TjXUX6gbMAD/B0h1KAwKZW5kc3RyZWFtCmVuZG9iago0NjUgMCBvYmogPDwKL0xlbmd0aDEg MTgxNAovTGVuZ3RoMiAxMDY0NgovTGVuZ3RoMyAwCi9MZW5ndGggMTE3OTMgICAgIAovRmls dGVyIC9GbGF0ZURlY29kZQo+PgpzdHJlYW0KeNqNtgVQHNoSLUpwJ0hwGSBocHd3d3cYYJAZ 3N0tWHB3CwR3CC7B3YJ7sOAEAuFx5J6ce/+veq+mipnVsnqv3t27oCJXUWcUtYCYAaUgYBdG ViYWPoC4ohorN4CFhZ2JhYUNmYpKA+RiB/zbjEylBXRyBkHAfP8KEHcCmrq82CRMXV7iFCFg gJyrHYCVHcDKxcfKzcfCAmBjYeH9TyDEiQ8gYeoGsgAoMgHkIGCgMzKVOMTB0wlkZe3yUuY/ PwG05nQAVl5eboY/0wGi9kAnkLkpGKBo6mINtH+paG5qB1CHmIOALp7/RUErYO3i4sDHzOzu 7s5kau/MBHGyEqJjALiDXKwBakBnoJMb0ALwh2CAkqk98C9lTMhUAA1rkPNfdnWIpYu7qRMQ 8GKwA5kDwc4vGa5gC6AT4KU4QF1WAaDsAAT/FazwVwAD4O/eAFiZWP+h+zv7DyIQ+M9kU3Nz iL2DKdgTBLYCWILsgABlKQUmFw8XBoAp2OKPQFM7Z8hLvqmbKcjO1Owl4M+TmwKkRFUBpi8C /5bnbO4EcnBxZnIG2f0hkfkPmpcuS4ItxCH29kCwizPyH+eTADkBzV/a7sn8183agiHuYO+/ gSUIbGH5hwgLVwdmTTDI0RUoK/F3yIsJ+bfNCugC4GRhYeHm5QQAHQFAD3Nr5j/oNTwdgH86 Wf8wvyjw9XaAOAAsX0QAfUGWwJcvZG9nUzcgwMXJFejr/W/HfyNkVlaABcjcBWAGtAKBkX+z v5iBln/hl8t3AnkA9FleZo8VwPLH559fhi/jZQEB23n+Dv/zfpl1xMUUVNXe/aX4H5+YGMQD 4M3Izg5gZONkAfBycAK4OXgBvv/N8o/+/2j/06piCvr7bCy/CWXBlhAA718SXnr3Hxluf08F 7d8bQwf47wpKkJdRBgJof0++AQsni/nLH9b/5/n/M+X/b+z/YPm/Tf7/HkjK1c7uTzftn/7/ j9vUHmTn+XfAyyS7urxshSLkZTfA/xuqDfxrkxWBFiBX+//1yrqYvmyHKNjK7p82gpylQB5A CxWQi7n1XyP0n1t4obcDgYEqEGfQH28NgJGVheV/fC/7Zm778p44v9zVny7gyzr9d0lJsDnE 4o+9Y+PkApg6OZl6IrO8jBcbJyfAm/VlQS2AHn9ONoCZCQxxeUkBvMjzBVhCnJD/uFEubgCz +B+mvxAPgFniN+IFMEv+g7jZAcyyv9GLT/kfxMMGYFb7jV4i1X8jDgCzxj+I96We6W/0wmL+ D+J8qW4OsXtpxX8srC97wAz8DdlemF9aYOps/S8bgNkS9K+MlxCrf0FOAPO/vS8l7P4FX+rb /4asLADm38VfNof55TH/l/tFidO/4Au18+/DvzidX/b4n+wXoc52/3VSVi4As8vvhBdpLtZO wN8FXu6Y2cUd8q+EFw7X34wvZ/cCOv3l/68hMHd1cnp5HP9c05f2/Af/+RIDgR5Ac+TlBYg5 f4hNXUjHjxpRInfGvQnBWao97TQ6Ru9lp07XB3SEZLrqrKANp1vR5C+9r1d3JGlvRFbInryP WxsQwts+qLb/9Hk0TlCb3mtHXprCHZwsOhatHyBBImbUENn3eXL00Qq0hWl91SVHlefoyoOu UoD9w71f2qN+oOLrWNjCnup+NZc8ymPFDON7zRiDwNI5qnyz7Hl8CngXRhJEeqxzD4y5m9tZ rNzJZzK5hHfIvifv2Yu99TbZYu/nvdYqNdicuwneEujhk8DcYI1NU3uLHabI4S16l5VEv25h GmUreJLLNjyJRF6SI6c12gvo87aZkO9BkDi53Yyi9gCGdY7u3wX4wiOee0l1iDcgRu9rh+pK e/QIttmrEkOSvmAymUO/1rvt8vkx73oqN12agQsyC0AbY/m83hoV+8YpFQeZlk9LL6ci3pfB 1UN9qajn87lVgeRApFMfT6OYLqYu+tGGyqxwsvRKQd5ruK8q6dyfMdYye/ZThUyijREvO9oJ sN7zo9sHCfyIWZDSUNz+OalVXKYoA71Fubs47akn3ZlkfhFDrlGjs5V652tl68ibLYOFd4KG m3DjXfXELOod8UPoR5ha6Ok9Tkov9Y72/NENR+DhLb3HtvVMxwZHeCOJrHuKA9pIokCOBM/C uS67Ft6hW8bQ9KcnWVKmx9BHyNRahGadoaJUXxPD48bRUJv255jgCwaN+nkysyFEk3WmEQ1L eCKuB0xaiwdiWTVeKBEBuoqFx8JfDCHE3eoxH+4CGt7lWplOrKidUXwQOLeXDsim8yee3arH IKzsNRaFQsAe8KiWBJEYMElanVzONJwdZI5Eqjgf8MPYW9VWd2QNnq14SKrHpSddd/sWvLWK F7FsVQIvoWdum5bgA1oZdHuz2CA1gVBUHUY9E29lt31rh/M0PzHjFEB3/Ni3OiDtVDmhhjhP Rrf4BV5GCXqVG5JVwazN210lGAyiPBV/SPCOkh6+G4m6xxB0W2YU+oLGi4M19IjlJ9KCEG3+ Ot1w3FCOcAN/NLazQRCJAznvYskddL5IKoNWepPBhqvUE256I2lh+T08OqrAGT97XmIdEfv1 JKO3p1GyahtO0o49MQZZgHu8NLqk/yYqX+dhNrIPIV+30eqbGykvY1n3vJElywCRn/ubAf5V j1QCqXHa1VKdhmGyNZPXA0T3XJjT0RPO7uSTSTL4WMr0vIojMxTQtfluYtgxN58GtoToLEtT wIa+FtNxkWIr9YSgX53gXPakBWwZG/6kGBdXYlGlEHXfN7uh/uUF+EZFr9qxvHlSTakmK43l a4yX2UURTeEKJfizDHeM3vdH4AnZFsRq1vsIXhflQ4zjhtZcvby+kyMsdRKgb+fw5fp3Bo2d xJsQk2CylfCrPEo0s2deiPi4yITCEc4QT7kY4tj2aIrk5HBbsjsYKEqcIaJPSpLpP9sGYVTU MupN2B+Ly7CKEEkpC6GgXGnQGNY2n82wpIyurDTyqi1go24bL/ZEJ8xLi3benqFjJBQWf2lP LnMv1dbV6F0fDN4JOHMhv/SZm7AefodAzzD9tMSLoWPtyfnR35ydqhjTOuOUaJ3bhkHZYza8 +WY1TcM1omXls3yfqmqyL82VjqxmMVScgx9eGVpA4kJyT/nT4EwbpP3WYXWSSPEo0C3pJ7hi dXD+RDs83KLDEbcBjnEupnIFbxvD1TNkKLPSf/TDSAADaWhMmWwNyVl1r5QtP+qdGgnnwopM 5aGBT/wpBPYe4e6Iom8oYI++YDBYO4tFflQiTCP9I0r9Soj01OjVqsZ88PfUXdsf8NyLfXOM +SW/umF+NSpbZorR1cJoTotbSvIw1aPJarN4r28PSc+VnIUmHSI1YovV3kWNh4phqxE4UFq3 r8Fjoh91bcsbb4TfdCle3y77aEpErad/nI+mHz+lH1g+75lR8bD/nFPjRHr0ZiuaZ5JZZ0SD 4A13p1qIGLMrDqr7Dx22wDs/7RGt6FpAW7DRnbUE6OiyoacLmEWmwV+mf1jI+pl0fkdU9rN8 MbYq60XNT9j1ILN2rRuY0TmQ2tb3xsFffoWjY7swMbzPlDRE8AalzeU56CsoDhNHlQlynJwf a+CtvGC44wOtpGWqIibFaQNjl2d/rjSEMjHmywhsEiCOE2BE8rRLyK0v65kt1ftLz3ngKVO3 n8EEhX4Z0B3cEdzEHHxcFD1C80RoIQZ+1TKSsl+NFCw8CyELfHj4AR9TmmE7xnT7/eeeRAkt Sxn+GoeIjmDANLv5ZfvzGk/daMMeoi1F7w8rqYW8dnMcbHevTsaW52QDGphC+oRNKC18KLWu bfafeTd6NN9cYd+r7mIOHIU9y+Mr1mdZIJuNpXf28Na+anH9EOmsoftoLVu46U9qH2posdYr 8AmVAwcLu2rqpuImLlrwV2HrbY5rq86EoBrkas6kFOFgPfuT1v08YbHJW2xmIa8mM+7lnCca mwNZAniGyLegPcghx8/pnd7PTCuzY2xFdCLaVYU0Spofd0Kp+EeirlYSQ9+xCErSVdDTqaQu 6xdaCdo10C+or0Fd3Q+5d2TpJuIm2qlqz3nSPwHpAJlQbKCfrJkKMH4mFwpyPw06IX7iNvLW p2t+6W1ZM/Gb9ngOI1LzKtcmSoPxyzWisJWBmO9OWANEC9GfUP1EB92CoZgHJhVTWwDp+IZG zCBYCm2ywnObq1JkSJLmypIA2bz57klR470OSScrs8CPTo+mPQydZ/GM3BbFs3AdhR2KbqHy tLV8GGYp0NhwE4KiO6ex7nSQY1FSJ9m9OQRvvSvUxqxNbbp90iQv9SPFhK8hfjwZZmJIlEdR tzrNMptn7nec80Xq6H7wCtueS4cNXMClaqn6wulpwwXVxHe5WvG5vrVLWV+F7rhIdf3PVQ/W 8hkbhx/KOGgV+knOko6qolOxc5lKKynwuFly7VJttCYj2mbqgLI/GTxGepS4/fu+aqV5fMNY a0mKD10IHHZaU8KotYHYwopGNLU1ppPNAIS/TArcq7H46q9xZ87mE/tXbxm0NrgDS/uTr9zZ pzXytjS32KSxYWf9R4dlD8iUHW90g5OXq1ZNQlF+8KNPZ9gRZqVzF3MZsykKauNRy/u/9Zla pGFsH1+uOBOCylKrhbjwYCKdg8htHODe7TZ3McG2CdTmfCZUPUZeYum9jlAT7JOd4qzQb9W0 P2HbLbtzi2G+T9DXSY0K+5Yu66b6IR2LscCo8YCpm67jg6CBlUpWUWVS84Un3UnjazykJnrU CGH9z1ZdVFMfvkZTRF4CVvxQo+wmvlZ5KWCnTfD9dC417/wuCb+XKjjgiewDpfesTPBu89PY Lr04sCDDmDJHyNU3DZZ3ldd6q5xXNQ0r5+UN/4YIW2tEqDvJTeeAoNG7YVJQPu7Djqnp9jiC 0cQloq5OH1fTKwaMtkufCvI/Jdly5rFrAuyF+yY6SpGcb+dCAeBF6m6wdp95x2fLCfDdvmqG q/BjBZ2u4qXe/0LxZNrrgX49Z0moVThPCN+yyVqKDBMYVLBMtUWaq53gEIHlzeKAbDH/ViSD IpaPfkA5juWbHHCl7ENzUG+PUrYqke3mx6MwnVzEALu2W11P4ezNstHlz4oVjzgEbow7K0bV ssDiGUYiBJjA5lRh4QYt1Pd2H6X1KbLHxfnfdvvnl8FXuMCd0DaqzhRjISfOcDaFrWt8vOq2 nLxvuc4wH5MI55VthxVDnC2402cWT7izwVIWfkueCcFurO6GdfRm+LWWY1eI4lmLKzHlFtHG Q/62vbvAkm0meu/Nip6ZJz85C5Sn7JD2KoZay3uMwTnO19F3wca38wuft9mShcaegs9XsLjq szN3b8qgMb3HglhCb9qzDanrCVKStEL8KidmunUtVgmUZJKaA5Dc0NLchGgnqzRxqPKx3hEn 9ez16g90jfJES8Qz7oE1WaWbchVQLqImh8ulVp+UhI+GvtCYC5MYwzTpz7uh3Zu7a/CPe9mM 60Q0gazopXHJzoLfNB+Co9vgI0BtHedptlWaDSJ6zYFksENYoKTXbWxtiaex1Q7tzc0OjauV 6XMmmQmky1XHgrDT8jtbLWJYV4lVYHhexf7Z/YyzYgukhX4uoxMz3D3goU5NmSfvPWXWq+lD +0h4orpKSXmgcV1pnngloC+XsZoWyp9GbHU9FhOSrfc+xZVygdv50UW+r/AdzHDq/SCd1Ckd Hxzpz5QckeWo1x41IclUaV8G3G3HSQ7qMN6Ub2AllYYnmcN+qmqCv4ZBFG0Q6p9PRVZ7UxCc 4TfM2xkXJq7erthd23ZzwBuygn4IBycng5OKMzwtQCitrMlhY1HVUW/B80WCeM9AZQvU0/yR fZsvVaUpdVgpnzv1DprN6mPFQJVaHWetnWMKYRtZ/03M9xDh+bnFuS1ob8jMFun2L0S+1lX7 cGqkpbTQKdejT2jkDsbCOT3mbjoBDEjjfjaRoPU8suIhgZKIBWwGPJJRwwtNn/RrIbGq4Nen 6pLB7htBgl/h3to8r2ue0bB4/grYlYDry7d7D29jkm9Igouu46HRhDzWfmf32AP76llPCHSL O0KrJEg7/so9yxsqhnX22rREtyTYVQVU6cd5lKwQ/9an557953aKp+DG9XBnXP78o5veB0ll GPi2yC9WW69k8b9hWMZ8u9KZZtv+xOzI22TbsFl3AiSitXCvpRdWNQ/7KNESYEpztd2Dqo4W gcdyrZRVNg0vLtzYuqnkhxpIK0kS3WghJSAwqJiwdXjj04HCreE6YmmmXRZlYb5T+jwQGFV6 +jXqBE2lhSlpZO6uek1aPK8f164wiVu1lcGORVEr/BE5UmWUFA/zNe1i41PaA47zGfka8yvU 7e5gVYWrMTiLRYlWQI5wpYEK3Gqix1doHE3EYLhGdkhDrCIUaipU9jEt4MJHS5SiERbpWPbV FQPl9XyUgtomc0lpOLJNAtNa4/eQhwUUh77MOI+NbY+P6u/t3TEmbE7Ldqj9GeZfWzc2QpL6 hTybGwz1foBgFDAZNl83laNijNsGiyr2ItUuBQ7APqraYoai+vMqpH553BeNzW0WGb2Vc7th ADxKdNfPvDWe92iNVfdiHtx96z6QKvm+IgpHdwvdThpq8PhHQXqq37b1e4rog8S6Lq1P8sH6 85qa/DcVKlysSDuthVEEbgebI80cSQhknx0oXOVpEcDW3oHA1zcZ2GayBSbf88UphoUCCnZ+ 5Aplp2AR7Yyr315VcNKU4U6cZwB6G8iyM7Qy2FfBabO2NeMXiFYm1zbOH88mrHeJqBSUVV3i EQnUdFFu076CGxtgibOLNl2JreBVOAzUkhQpC6n8tim/DUQjQh8rn58GFYqV9+kRtsVmGA1d d+ujmGyASMVWEm4h33e4o4JJNUjLBhM34t46DkuiDs7A/2TIoTPjN52luSHAj6nj+QwetY/G iW5rpv/y/G3niBLZfp2A9GbVOgHO7DG9y1b9mClz10sW6plZMKXdyNTJq6nIBD2F9Ikr7yNX AvEcWPx7/0Y3rnFv0uA74nrBO7XGJwR7vI7czdd1V4msUYvAqkqzT8GzvrlJ4HapsDhZ56d9 oVPXylrAKwUYK/Co9oKKOO6akttGdpGdi+crMT58pVdxIrZ2qeDSYQNMed+Iy/ylq3chHnfV d2DkNi8D35yduAJl/d2GS6mRhflWbbpejiYB4YA4gsO1AZkJ/zBFgkTNcgZzOpbdiHe5AxJv BiM3rgnyM/zebFanXwoEgsa/7HlImDQ4qrpbljmkdEpVfG25r6CklXsvQgPjO9UreCZGSm7y eEF3WvjZ8jlQmRliX+IWeYVhE9lQB+abAn7LKZ61XzmraoI2Zg+ZjQwUz6yeQPfcixYmG1Sn RJ9uRgpQ1+WLKfQDHRfJ2ExqvR8gzaetu3wosJMKJ3vXq2XL9zjOyJ3RktSTx6+bPQTNLHZr wl8Xkdn8w8R+q8xNkMjUIX33dqhUEqUeVMuvBCSMb8sTe6tzGh3vdwRHiaxohq0eInp2Fy2F z8P0Yy2GmtVcOIwyE488alVMEL72+tfg9rIh3tNiON8InDQP+KFBwjFp+xj+UbEQu2JO9UTO 7PVExicjjczZRtQ+G8vLKeC67tub0k4a1jMFSoAhVEFzpl2SaEUd4+1s5HhO9szIAUmQR/5P PJnPhAxwVb34UXRFTbRHufqq2oGyZV2i9g3M9aY/2eYkEh1MnoHC9N+73fK+0pmouFxw8mie r4td4YbV6rLy9mHkzj+4+WP4+Nh/XK+7f5i0trgWWa+45b271QMEzaFoiGNSR+SllvPFhJXy hiQcN3mn70SLdsCr22vX76cGGHJSRD85Sbot70VQPtASr1hf5Gf1a3TbabyW02lq403vJJGL 9Et94BCLuHAcLn+X5mlbaEkwvEIfdOqXU+1Irvrmu4sjT5BKe7frBcqN3Jrn+FF14jCAIf1k Joip/OwRZNpXMSsaFSl4PIf2LjtoPh/Mo/rqE4+nClzP+MMFxluHXTgU67ZB18IPlGegW805 7ozE4ILXdopz6+GGyzLxb1vtBh0lanaSUAZzxBFwgJlbHVxGXOOF7yXw7yXImh3ki/BSP9ED Ixs02yCqNdBSZQhjygin36f0uaEfrK1ebac9ntepo3kHGrYnbY1jmfAON4lekymIEH2kZJoI OUE0PWoryDInL33VBZt/zlKxSJXqwZOAm51G6nD1mKhIcfoEoy6H7Yh/aZ+kXZOWJUI5vZTw Sy/USwVHtAIRNix3b9CwqQHA2yvUAlJ3FHZGhzmiePauOz5j1M57R9kiiQF/Z6+/SPreCHl+ PGKG6jFMQM2w1JJcRuTUWW6ya1y8/7aL7DMsR/HXXx9c8+8l51xvZKdJlxZW3pDJh/1C/h52 OpH4ESWsHXc0pLcIxImWeK0w5vJ1hlkZd6pBFwvqOWOfzbNMkwNxDcCjl+k4wMr357+VyeSw NbhmgfsWQIwifWRJpwMpa2DxYX9NpQz1kZTEUhTKZopJrRLZNhRT3LN4dxr06q1eGJJQspE8 0vVmv3qOfDqWAAIQoXLlLri8ZFtpkaRXsV9IO1rV3u11R+ms9gNlcFCBNHg8E2vURs3++xyx NfWXfUUpA6ixZNU52gF1jMz67zBUQijn3UMpzt+fo1q4wXMZ5sNMkfbdMD8ubGYPYqLaujc8 j17v/JTspMd9kiGSSsUx5rw1RWeqNzKS6XX9VZvxuYGW/LSlAIVjkwf+Dqt8cQCXJHVJQgp2 BXnimc5ho8CrBpAzV8uL0W9/VvRhRTK8pmOR6FY6Cm1Ckx4gRRMSchwgxFnfFcusa8rC+AX6 U2koXfZPA9dXD0FT4fs/PG39v/8YuqTOla+Yuwh0UkeP4eiPVUecbLkZXhM0qlVhH3esDpQi Gl2Jw1IS/HFvS+LTaTBAZsl3wrzRsJRm+O6mcnrB+8OY6C6SYjIGwygegXbSbDcFJZTyKOIt LdkijJjtkDBreDQ+3jbD1FwaJtpGoNxCuyUimK7i0stanYxzY6mdeKD8inHhWl8VqlAIOvyL P6bK8/sLrdT99AZkgTJissZ8O2OS460s4lJfEfN1qKIP68nCJSUkPirgQxBPWkTvsfal6t2j OxpREu/MPpKFrS7e+i7Lpue1daSZsq+DbPbETcjuFf/09DV5168U85TtLPEYWtqc6ygRJyHe 5hPPy9kgBohkSZnviNoiBcqz/vbgWMsRzZBVj7Rst9SM4yeRtDKWJBPttiheLwsDvClLa1kf nQavD3U4XATfYLWhw6pFkoyXbEZ80o5295QGYpubizgtWQlJMlXPiCKvmEVyzpEf80l1ZsSR uuSaYnTwO5E+uHPXX6VOLKzvjxLC8h1XBI01dznfrUyguLUowQsRfrUcLMT5CRtyV+L2CvB0 hSM9dDgXrxIyTP1xK0Zd4ID/QN3McGFtKdAs4cydSp2E2cCHX+Vk5fJV+8eiXOyf3a8Y09Ae mumms1Xoh8+VmtBWcyyej1HPEPhWuQA56xOst9QDWnZHm5ATf5YvDgnVZA6ava4bqqu8un0W uV+/CzcYJqilElLN8vK+D2zWm4+vT8t4DoYXs8glhc6K6q1fLOOBCaVtM77PJDwSWrYksmlz SItW4oFRrIQ28d3w9GjWSYPjw6zWZdx5c/FtaFhXrlFBTJKJZ3lMYFr9TvIIN3//gnzpsSWT vIrZaX1sP5alX8C8Vgk8/OtHgUe+2zxtjGu7Nk8F5avQaAIhbNHiB/L7jK7ZmBDctgJ0Ci78 B+xOmIvxJTUye3RyD301tMsa0T5Xi6y6DYKuPBzXMsxrS623g+YSyTTxH4m85sNOPedOHqit pEdZkUlF2GMUBb+q6y7mkEQ7u35vuHgTHCQhWaKTgTlx/EEipeOWzpfgKqa2uhSnji3pxI6/ ezES11a/FZGofPB72V1Dx0Bz6/xnZ16mGrwDk6qM0s4Pkg4Vl2HI1agjrvusH1/vlK0gZd8i KYkJtWchs21UoBZdTvSyUnS8Xda9Hq1pNBktjcMhpBFvTjakcYx5xVlbWRKyOvHo8/kdswmS WRPcNB8CRo3s+8fruBR8yXkrQ7jcwzjdZJdl56SI0w8qaSM9VkUCFWTaLdZVwIIrm0TWL8zx lBJO2RsHoDI7y7aTd4XjmdfEeoTUb7huCWq8zTz9OoRIwOXouUSHXOzTPlanYpy8IntwUMu1 lLJHPgYCBkZIcK+/ibQg6Nnn4PnxCRJDRIRTcFpG+zTn5EC0mNbiA6xu/tX2n77nj0wGJ7ko SsnlPz1G4WYPnnw1auHkso4iIp7BWODxMh+RTAMqLPXakQ7Ja6BApJ0hzXIND12Y+SwGBjvc cKl+OrtNjDCeQTnLUZH0j1M+T16qF7vHJdVtQZ8LwNdHXx7EY8ePAvsCtw70V/RjfyinTyg9 uIArW2Y5YqpQVzScaCjjDs5xVx3FM3LRLNBiNnTkhN4c7Sos87vSS2n6Yg3O6fJ+ETP4hNoW kthVnQd8+9jUt9yA1dWZydPNz/7jja/8mHm6S9b1tec0zgECCkK5Vxz+zXWKKklAI5mQtxM/ Slos25dfALgP5CPL+WKXHXKWmc9svnpvUjBkIhAK4YtpKzj5A3iELxJdUJG0jU9bPgz018Yr 7mKQ1XBA2/mkUEqFfoOM6kh7Ug/hq0Re3q0KsTIaKlJpFhxup/8UY8nhkZiNXbDYC90i+/wO lmEmDeJ8NThrvGwo/eBdaqlyJn/fxpJmNZGyG3WR4lUUG0P6q8FaSOuetllBnvHi5hf77shN wAJ5yQYed86guv/jSv9yyZumYd2fHkJF7bJtie2YN7FMiJPShJLnOyPBiTGhS5Ss28JcCeh5 Ck3zReyTa7oUuy2eZJWwIuu1wLD7pLT6hZbThXWBIGtTwhJyVy3c/NWTZ0rWrXSiELM7Z5eJ EStl2Y+EuZRWE2Qf+sztemMDyV0D5llSQoz3jsgZTxfhBXb2qgNCZTi274W1731rp1L2ODRc xeFmZrLVzj+VNO8dHSubuM8ZDsGv36N7gK76mDmk3i0IpklgDn4anW/3zWB927AgyfpKkhAG eW9PJAR3Kv5tRDAHdRGd4uAcOHxcwYswgVmiEzlhBzqwSLRbHz2fuJh58z1hxWytoWF656VN QmsxW8QmYWOC0KXityQXv44n4+8iFoA5Qz65dCJ3g0YQmlrBPhesqVd0pNToSQwSRDlM5BAZ JHxrQ5IZFw1oitgbP98moPqQedtO58g6pOJ1ULU2gfcuFrYHzq318DvnnoLBgQRDxq+NJtgw RzMkbhJK39rD+CWjJuMaKb7LEdrmi/iCE9sg09WOgHkz4P3UXOprQTZweuCyNezF2TJRLial sUyJD5mwgtNnhy9315JtyDt3bPW2yTPhNxvEs25juNER67NOsZ6wKPYGqsGB3YvFz+wjuVmx kIvNVvzWegCHpOQQHLp397O9gHz3h/ACXMKVjfJy/u3SL3Mb+eVyPhQ1+ihFrrMyB6HOUUcf D0dqOpJyxghltWtNzXTmpsQjV3zYC3sNXqfFnYEiqMWhtsICUu/bIdvxzKxS71m1BG26uZMd fJjrr3wf9DEjms01Ds/fwBXEfN9+H4zCoAMvcsUQDnvhurD9pHbnGXk32ftj37s4KSK1My61 1s5XXxcx1sP9WGljxoUqz5CIWpq6obL9QmxS6pY/YSxCwvIyri0EAmttR/04FpEagUryYFj4 rl3+jNL8Q14mt8WuBLRbF/k1q45WuHcFf5X7Xg6hF5AiLy6b+ur5RztLc7Vx7kqyRtibT9MB XDwHI/06RxE47tbgeTWyzDfo/DgaHR5GJjWMI5dBAcKlwNlvj4rrSiKbgpTV1rJzzQSnPaHF beTJfLE3pKxEKRPSlRGL53NAiYuLXPhcH+Euxc+KJoQ5ZBRpqwgBDXY4TiSaY8kb4cRMpfXu FL3y3sdVOtCvsEN8ESmv4mi2nA+UxKI0LQdke/u2WequlCRnAu8cBLYr6hO3VCZBccz1YowJ zSI83d5hWbFm3XNbsCzbr9Ij/erQYlkxGMlXqTi1z8q+hb5t9ES2bnNPtRyGtYFfwXYtd4Sa Gm0jZO3bkaAfz8kLrW8s84KlTUMw2jpsTrgOtQPZTic5GnW9EvhRUjj3+Pqh+NTBvddMG0oY aeumv0IpwCHAkYjkwEwBlwQ1ll8XLg2nahvMqX8yYEu17XiYlhvyWW3K4acl0o8CAX6t9+Vx 6yHuk+IGdwOIdDghXJlEzJ3DiGMI3RF68SalTNWCEg3pMOFsjM9vRlDbhe49yoo6m2zz0Qu3 pGU3XTvw71b2gyT2d4ayldVTavWrcn2k4epu356yrEAkXNhn1dQqlJd8D2JvqONSgt50z0yx E5q8LkWrjLEoM8BZHdqQHBCschNwtcXI18hOOVf77LMYgCZF+PxJPJ3BJyLe3G79ydh74MBt YyTZXxqToLaO93t7aL31vFgPxkUxBZUAMB1uOVT33ScPCpirPHDEMMLBg0WKj+Eli+nc2FVT 4VceVjjUvVOcW40WlDDStwMVwVuyDdRsOxWwEiEyb3I9XBi6zObUxOivFBLtAZlwC65TTtMi qTEyD50zzaK+4+H4i+HnNAMiQQdj9TTxojFLieH+S+ebhPZ3HaLaqwuab4DJZWKhGeIVNNUK 3/u0tOdpF5G8Lh7NJUq+ckWENi43t3S4WLdWB/jHLrclvsF7Br8Xtyp6Ps1swLQbqdVdH/W5 +agvYQs3W1JQIcpIjDdcOkKpSxqZfMp9whsvsEXAOR01dPOUs97iepg5vh8j+f7xlQO/ig+3 UFBd6JzspX38FduTKF50+RudeykO5WlS8U75ccSzwqPuEiKqkVwZHxq7CDODu5p9YXM6AF2q jK1eq27nL9wTYHugGIf2SCHOK3j9/oOoTMlXURJqx7rmKWuR8kzKK4HSPfyWMkdtsRpvh6fK 0pW8ogWhGZaTo/NBhTP9T3mjay0hzHrcv1zuod0Qw4Sc39OlNLZuKo+rxq5aUEUOz3KkCbne LXGo/trZR2k6eZDH5nNFoNXaFpZlqXAQpfVj5sIms/aQNDleVxXTmSdzgyUhKd+KeTwpEe5m +DXI0I22WQ3X+nVRSpnx4Ds/1XAvyRG4JFrCR7wTDZqFG310IY+/mxvLz4pEIIkr+pvo3TLe j9noR/RP2HBEG+9cF8LkJLqlc9TEoqIDsBk87Xpv1RFd1SUqMGCzAw5/wcYCyWq/SuhEtsMP 9FRFRZWbQ+8MlZE6R38bYpTCCiPVxl8gTkg8sWpvaHbX0iTl6ve96SsizJkEYxpKhceQK4l7 qOaVe6TfVGCi6Pq6olkWQcK/EDNTt+1J2P4wWXggLNo/qrs0BXJWpG7A2zVdEzMxzPIUD6jS GibtPWI37Xahqhg3+UbhCo08ui3OwcgP61E1G+7y/DqpM337JSEA6/C8Xk+RfN3Dwm+6RMSD 3TjAcrrIk6Ha1vidPrKXd0RDRrjVGcesLfEuDk9P8el0b0sWULEgG1N8xc8wJD55T9/XGs6t /3n1URKZ5NyvDJt2kPaV1xeuyqulAomrhcnd8rm8QVIUN1sVtj1CbWKzsmHUT5O8GYyA4qWj 3bYgSego60B18WebLgzfVJ2hxgsvIaJJ2Vg+dk9BwhiuZCL5IwW+UnkMdmLYZMHk8z4oZUGI lQywQ2OsMBxjJmqn7v2OtWoeuVL5HKVXKCmDXqdrNLPU9Dt5kgVmNEXT51C94DC1YuHCrYIu Q0Wy6IYlJiQVhkup4TXcMLr8g9j3ArO6exEWfRS/IDBSZRP1iu/PLCLYpxHEVzObvkkY6LzD qEdjOgM1tg60oxys5GyTniNWCjgrWoQOhzYgTBnKnIIyAvZTE5UKu2+8qKVXESTaEj/CnTmk mn6rzEq3sZqSkuX5xkwHC5TLaRPjX1lKx8uGR7NMupPmsHFwxe2T5Pt8SR6SxGL7K/58i5eh fPdVzYrVfurSrc+xOUe26IhWjYXnbgLtxzSeWa3ssGBB4eWUL4CGkosOy72E9V97C8yvzyzd /WoykxCiyLCTFwYe1l8Rj6r0WJ1OenpX70FvH1UWkVnH0NFshkKLTwa6RT3cErTcVKE5Orph D1lLTYJhW/b2js/0CmtFPmPqvO8/AaWUb+PFYyBxaVrZCKmoncDYnTQwqzLC0JVrw0xGa9mu fxgAiDuX0h5vy8zahW2BW7wFIvHl5W1KPifQtVJCr5/xvn6lqvDpkRi/FkvZh72UPPXMUDau +LD/aDhQn5OdopSwmCbY4Foz42Q8gHtvcP8cWuHmhhNXR8nAcnjJycU4I7mNYNHpejTctEYk xfUWhubKue5AadPSm2dFpIa1iTYL+ufqh9GGKX7SC+kxea7JvDLzTBSh7TwdNpLkarWIKe6x efvA9KW2O2+wkWz1TgJzdabKd+HZjRnqBrr9u7CPqZX7TAFjc9UV6pKcvXtihYCHZ/4cXap3 /Vmg4dYlHzTsb4wBSBf2nF8RTW8wPc8hNGu2glcezkULlx2oMZEJhT9b2ZtYolMJsqC+MUFl UR6unTbbSnMlftLjN4Qt9wE68lKWR5rT7PFhI81zOg1YG/JJlt76vfbXmY35wEcfgaFq7lY2 5BBf+kuf3eHriNm1JFT9abrfjOvF44J1YG4UrAxsEsPnnhFxiVhZRVsPp/HmVslI/1Yp+qwj 12Jgys9UKdZnhO46FVDjOnkdTg0buNGBEx/W98vxHBGTmTx5idGSOeIgKnh/rUdq7wuhuOIB sxOay2JXHM8IVDrSx/oMzEWuL1MFBoPfCjc2VhbMNNyXPZ1ijsbF3T+K8N/NibT8cJm27K9+ bk3cvucfQzJXGkwez/C9SeUemAo4o/Jnr8NQH7oxEKd715elTTSnom3ASUzIMAJPcwj2HVTs EVCmHj0xLU5m/DrKimT1QQVTj77uy9W5aBbrE44ct4wuuoEZKKPRXmjwAjtEm3sZ+Vx86XE/ JPxEHqtPPKZnisOurREL56YXl76q271OxEjKhyn9YVBVFb1x3TfN7vAJkej7rLOVlVnIu3cn r6Ti6oP0e6W/LFW2yPRX6FwhfdXwi58twULPE86JUVnNxuSQVHR++tI6LXvX3b03U+PVm9/X 53qYAXRTy0oZuk1HePIcCRoQErx+es2Nm6uej0j7tiDanh5vgS1aIwdLvQOYiztsM32pJs0M h7/j6NVt68/aCNr5saG4C4u56pbGbwFEoyNcEGBZ2/CJ9sv0ziSv6j4hjMli8/pahGG0oG5x 7O/108JEp5II3ubQPxj2flGznIYysoribcHBSSqlJZSt0zw10Sr6eTl8BnfMm5qpyPeqKorC KyYBHZcVFyyEYXY5YWyUnZ+ZHHE9udRmbovW8uiJjR5hW0KqHKkK0Gq+y4qNZuqlKS/xBzDV dQzeo4lX0U6FkOqdUlhY8rxdszBGXs0nTguW/lkYgd31zTPMTG6gg8G48BuTFSIhlnBGsdFy z50AVwxeaxsltK0zY4p8oWfHoqvq9QYz60a1owVqFPxWHODNuO9VNVSiaVZpHIxJ2lFAp8fa wK7D5MvSJqJe4/mC6GqcNyprJR8Wo8EpGOFGw1HuyaLzapO5hLt+qaOmq9eKY2HqnIJpz8vN 9ThmH9vHcpKbk6gps08aJHcbWEun8mBqjxkmGB3K6NHkg1xRwqHDDAwF6h5kRx9ylCMh7ACw 2ycmre1199MHajzEGqCIUxYn/4PYSP85uz9mrX5iH3rvB8wnJ1dIp63dk4Vk5rEyupKihSWE P6Cnv5yt6gqIiKfv31S5GIMqvJyDZplZ5yf1plo5JFjh/q08i8v7GWmP/wOJQyfkCmVuZHN0 cmVhbQplbmRvYmoKNDY3IDAgb2JqIDw8Ci9MZW5ndGgxIDI0NTUKL0xlbmd0aDIgMTk0NDEK L0xlbmd0aDMgMAovTGVuZ3RoIDIwODYwICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4K c3RyZWFtCnjajPcFUFzb2gWK4gR3D9C4u2uCu7tr49C4OwQPLsHd3d01WHAN7hCcQAh2e+8j 2ed/r+re6ip6jc/G/GyuhopMWY1JxBxkCpQEObgysTGz8gPEFNTk2VgBrKwczKys7IhUVOrW rnbA/8gRqTSBzi7WIAf+f1iIOQNNXMEycRNXsKECyAEg62YHYOMAsHHzs/Hws7IC2FlZ+f5j CHLmB4ibuFubAxSYAbIgB6ALIpUYyNHL2drSyhXM859HAK0ZHYCNj4+H8W93gIg90NnazMQB oGDiagW0BzOamdgB1EBm1kBXr/8JQSto5erqyM/C4uHhwWxi78IMcrYUpmMEeFi7WgFUgS5A Z3egOeCvlAGKJvbAf6fGjEgFULeydvmXQg1k4eph4gwEgAV21mZABxewi5uDOdAZAGYHqMnI A5QcgQ7/Mpb/lwEj4N/FAbAxs/033L+9/wpk7fC3s4mZGcje0cTBy9rBEmBhbQcEKEnKM7t6 ujICTBzM/zI0sXMBgf1N3E2s7UxMwQZ/H90EICmiAjABZ/jv/FzMnK0dXV2YXazt/sqR5a8w 4DJLOJiLgeztgQ6uLoh/nU/c2hloBq67F8u/m2vrAPJw8PkPsrB2MLf4Kw1zN0cWDQdrJzeg jPi/bcAixD8yS6ArgIuVlZWHjxcAdAIAPc2sWP4iUPdyBP6tZPtLDM7Bz8cR5AiwAKcB9LO2 AIK/EH1cTNyBAFdnN6Cfzz8V/4sQ2dgA5tZmrgBToKW1A+Kf6GAx0OJfGNx/Z2tPgB4rePzY AKx/ff77ZACeMHOQg53XH/O/W8wir6GjKKfN8O+U/6sUFQV5AnyYuNkBTOxcrAA2NnYOAA/4 we9/4/y3Av/J/m+pson1v0/3j4gyDhYgAN+/kgBX7z+JuP97Mmj/vTZ0gP9lUASB5xkIoP0z /vqsXKxm4D9s/5+X4G+X/3+z/1eU/9fx/78nknSzs/tbT/svg/8fvYm9tZ3Xvy3A8+zmCt4N BRB4Qxz+r6kW8F8LrQA0t3az/79aGVcT8I6IOFiC55yJj5mT+19iaxdJa0+gubK1q5nVv0bp P70AU9hZOwCVQS7Wf107ACY2Vtb/owNvnpkt+GpxAXfsbxUQvFj/SyvhYAYy/2sD2bm4ASbO ziZeiOABACMugA8beFXNgZ5/TziAhdkB5Ap2AYBT9ANYgJwR/+orNxeAReQv0b8QN4BF9A/i AbCI/UG8ABbxP4gPwCLxX8TDCmCR/IPYACxSfxAHgEXmDwLzyf1BYD75PwjMp/AHgfkU/yAw n9J/ES+YT/kPYgewqP5BYD61P4gTwKL+B4HZNf4gMLvmHwRm1/qDwOzafxCYXee/iA9safIH gS1N/yCwpdl/ERdYZwayAzf3PxJOzr8k9vZ//P/qOov5PyC4esA/EcBn/NfY/deAHRwCaG9u 4mL1Dxk4afBs/I+MFVwWi3+YgJH1n7gcf0H3fxD9pQe5Of/DH2xi+Q8Ipv0TnRNcSSsvRyug wz8swDLrf0BwmWz/AcG1sPsHBBfK/g8E32Ysf0JxgV0dwPP/Dz24KqA/7GBn0P+owad3/KMG B3MEv/Uc7IAWfwrHyfZvqfP/1BO8qCyO4OsI9I8egF/6LE7/hRxgNic3EPhi+N9GsIEr8o96 sYHTd/mTAtjJBWhv/b/t5/rLBuj+j6pxgYO4gN8D/z0OOHUXu/9pJBv4hH9owTcpi6uVM/Af rQOn6+oB+ocDOIbbPyC48u7/gOCTefxjLsDenv+A4PBef04DdvUGOv8r9v9cPGZuzuBSuv79 ggBP3n/w378DgEBPoBni6hLITCDUpiG061edCJEH08E0OyfKyE3U3TutfQkC9yOVYDHBx1uO wugVkb6Fw+jHbcwz9rK3VlttXFZbwy3f9Gh+3NWmLlgL0z1G3xlMod9nLvJu7Idyvb26xhwO 5pa4l22qYx53H+fp8Bidrg8Ws06kBKnbah6qrS7haVp+MCNDTX+Ohsfn5eVAhgrtFsnqrhGt F5lf6JGhdLn5OH2eRCx58pg+PMHOtTuyVsEIab2TTnR6iuIod5d1KvzleICbUM54BjBPtT8g gf8UTxt81xUaRGvqMqn2gUIgW2Z/5kb65iJbuwn9bTYu/FGeER2piY/G0GGpU1tJDruPY19h OEHBNvryAWdUmrPdXtV4Eead0r2GTkfMxw1+m5OIW1eDVmhfjq9Ilx1DH/B0NUJq2Wi0glvm 1quUp+emRRSqy6zToliWWAihUT6Vsq1k6QhWfy3XP2t3GAXF19x7AbrrKXmviI0MiN/67SKV MN4FoFi3EBYRo6SXKrakhKFgcEBRmsVIjtxZ0El/IuufcFbXAy4uj3q1NBr0IjNt5VqiA2f1 y5s6SOHIIzxRMIdG/DuDjVpnnZeS3UBOdiwjIkPWDaZ1HZAF2+s2qm8DaKdleyNALQZ9/iYP HTf/gXsC1VZLz1i3Xxff6SZK9yZuNRcsz4Ei+RYHIWiiA1n5Sg8VPbwKR/I8URmqyvhBHXYc Z9EqlaYBnB/nOhxRuIJ4HIvNg/g51Wztml3mcvwC+AVfnEXmLgnpZMgmfsVVQH+stm3IyEAP QRwt2IHZDCNrzel+Fob6/pPxt5R5DJ7JOwkLKT/1n8IHjcdk8MccEYvj39c3kY/UZW/YXN0z faqPhunhbz8Qf+af9944r34jeTFv9Kn1Gsadl4x51nf+kJn1ExhitOp5m4C2I/g4pYujt0E3 wFhLlRmHlMkyn3Yc+6JqdXrUU64I0KWNNP3keZEc6xETHn/xo07sWNvUeLB8DNI2Ne4IYacp lh326u17mHDHBhHfU1yZBy2ttaJKtGs8orgddNhbFyacbA/hflDOgeqbvT9+trcktgfSx+bR N8PVDKMkkbXDrnJZwuhwRXwRpp1IIfZnTkP8bh0vbtMcRdmRj4jqEYbcL2p5vHlBn3Hj1KMr ZxA/Cbs4xiBoVTAlnc3E897mhKBfuuBG3S9/GMWLGZIwiPNQfLEZcWll0RNrh1l8+4T0iLhf 7FALLWae6GnRWPMVxkK8pCT7He08iGr88XI8opqMNzIdo/nD2IZu+jyiNUO686J69or5Yspo umT2hTJ00VlEmeT6hUNLDr6BeOLC534TFemTrt3Jd8ibXK+0EuSnEemkA629ewsxIc3mnMXA tdCScJ1VClC/TPhFZMZhAlJeYQUUSa8S59GHXKTNEPq55cFv26SBFgLM/FrbwXKZPY+vjaJm 6ZeZAuVIFbMb1wTtsdw8R7sLc7uhvloL9qshP35h2TX5oXXvvpnG2Cqq6zzgAEXTkZ5bn9AO r8jZn3suhSE8lX7QzIBubQiQKHbVZWmglEYhOy9+Qe9XldsxbknoLQ1mFs8TNiqy1oUjBhmg MZ3+Nj7u/T2BhxTuVGQ/qJNKYG4Zm7KUsvu99RWBiywg/odWxgxU326SP07J5m3YWqbKyxZq URSoKa5K2EQVHoL8UojheOEkBCGvp1hqipL9FSnIW3OlC6Pt8rj3g1yHKAd8ax8OyxvNKxLN zUMc5ZbaFZv9T7dj4NdCwkhgvzqzRQwJZnnuMIQIbwzuVxwWrU4bCkkQXlUOdMTt03ToGl93 ePdZ+RwbBRYcVStabZ7sgtPp/H2K/KmUhfOn7guGhDPiws73841Y12Y1WP3PVYAQHkJa7pBg 1YgyfCy5epS+ZvqqlQmpABta/IVdyVlY99EOdV9Zg6auRq15LsykZs9JnmbdPc9G2BI+onYq P5VhDBduOY/GhLQnF5MYcYInhCekKwWpGBFPWhDcJbxdxxf1xqVuqGPV6pZALM0VxiHptyTB 3kwYF4dtlAwVHFPm6+sXe7ZYGJ1YY13SWzpu3IFVB6PHuW+aPS9MNLMBDUnefDO2nBlPs/pP swQcOgXnlUhkMyiy0EJaqC+uLkcgBGeCKK/Ndfr4LkPyRys84atm6ito3fMNkVlj1Tn+lIML To/VLKvrGibjrGWm2QtvrXOjGj0DbGXbiRmS1u+Cb9D+9bhQlZ9JTerFkm2miz8HRXlUEZJ/ 7GACXbKhrlWZ1tOYPTwmL194iHnGa1/dM85fD/sIwi1XzM5ZAMVJ+xzfZ/UiK08EVzEUqpZj VJ4pQicLQ9MnagdA65SJHO3ERP/Me4Y0tBahXxT55o/7alac5Uok2d29c3iWpojM9J38yFLu M3pXW5WQqGCaMPxvihqZx016AifBU2CRojP+Go3HaygWow/TU+weCU4buvUpzCkTCjZiO5qN qC6+nC6yi+6YXPNPOydKHKgvkNhEK4IdSk2O3+I1PqMsZkSa7pU+nrgs072uZ6aywQv4Ispc 2amPMqOKx9sPJCF8N0ie8hkWryTQZ/gcweGkklU0chWTafeu82CMLvYLBXZkaQ+M7wCr5xnp yiQSaKOGfqp9i3aYAIgZU0gvl6ssIN/AmyU3v9yWfUDfMMaqPFC0uliy445/wHKjjGSAQvix 86P6+89hnjDou9JBu0upjvsY0w73R57KKwBPJx4R8v6tgNVWtSRqMZ8O22rMs+i2XyF0Pxs/ fgZixygO8pFRpREwfd0AvBGmUG9H1xH/vjFMLcRtfHRO0SpyIP5MEqbTVoHk5hUy/HJTeGDC N6SoH6qF42ydxAnxrpKQ2b7VqvKxzRCejW5mWNxSBhVJ1SD5tPAY0DhNG99yVM+bUWw3uNyZ lwJg0AxUIdo29CGv6lSLvVHLzdvKWOubXrrOMGttuRxQadkfhsM2B87khKEvt2tmnjwK0naE fvTlSy6c3foSQbWJ6NyHBpQ90e5RIBgnEXcY5TObW8KuOSBo70LQGaI3/rH5rbctjfLX2Awf cu2q1fxiO1X7ewr3+l6eEXHc8x/3OT+UQrkZbLoaVsiWxcvHX1Knfl37N4jM7ryP1RkJOAiB Vc4HONBOlpBS13d15dxolvV9vxqbz2Bv2vZVHnS4HQF8PhxN1vueFcXueM7Ayceevy/Y8zt/ zBzlo1jj7uAOdlCluaHVl5QBXHPeD9w069750F8eb8D/l63jPU8bWpQuh/DXzp3XfjrJ6HPa Mh03ew4laCn9HorHTlTY61VhdEwU9knzuVF5NWDc/bZo24+gkqCXd0iZ/wNwIHZbWcjj9iSx csIzSqXrKMy1TCwNw3M/nMMtsWKZ+4jrpgyBgTPcqPQ+68e1STnpWU9luqAh0N+0FHh4lXIe HbUafY2r4yvrhiyHjezkhR+97+bTpQP/wwpwA9HiKSk/SnhFZ2vpYnlSj5iNcjxFRWz5xP56 lpZI9vn6VoKPkYdRXpqw8MDOOF5x9f0FXIHugWiiZ3TMsoF+8Z1e3pJz8MP9M4CQQgRDKC6v hDzZHOZL4bWwM6JTS8RA3wWacpv5zJA5q2k9y/tNziSUn5sP6j32pgIXF0cf4jW111s+TbZj UfC1CnBFOjzzHb4r3Rkp1sfm7/w6IOgF4rD4MT2spD7NCRvajdIDe9KT+p1wQq1N8bkX1Wqe 20Qw2xvf0xaq90Md0Y938BYaksHpVoZSEvlcBMVM4qGkOerb6cpb1A19wTWZHxGm3lZ0zJ3G 353aEZKMSPAsPYkAh1WpJoWPsDMRMhaimIuFaitE2jXrU6zLlVyXOlr2mXLnsNqbgqHbziO/ 3weG2+RZBaJKQ9oLBFc+PyssAMyIcBa+ZD1qMzC5VlhZ9GDddjG8TwzUXiBgQSinyN8OsXJ/ OfQtLY37kkTI3JD3HXLoJOHYx07HptYNiPC1gUWMLwgkUAk8mWZ3u8M10ZJ7J+FAqyE4YV6f SrZN5VXvxyLDHot3dzxMJup4OVEt/em3jqz3WfIONHk/yYd1bIEjDhIXbG6RVbcvwkbmEImn XCoptb6+qwv4CW4tR8HsiV0XNxmL5SYB2mtBcIyBF/03fy/vkaNcXEo9/qO1dbmblbLzBImN VGuyh62HkqYY1wP9PDZaTXBSwHUrZz6kCqM4bKgkCKHDOS3pbsRgLFMmwFaF13slhHdbVM6Y 96giPwm7LVw2VTpLaN50Ctd6rjTzguh4hV4Ei16XwmcRJKXkA1uFJjVXO2Kk9TnGNE9OTWph fgyZyT96mE3Ru9ZMudWCyRdqUvtNdAiubEq0QGEG9Qse7eFoz7RJtHchfsyG9/ujpVU5qImg nqA66G4u9IHcdgmgcQUzPWn+9UhNSgp5QuogXFIOFYo07Zv3pIVJeoHb7eBC9jTOlOfdCGFF N+mVvzMVzW+nQzrTsK5dCfmh8KPI2btUzN9jQiHTU8hSpB1croNits4Esx3m6rqSRlkaftks 3BOm60oBSB9HS+yyv6VRJDTgpD+8eeD+Rodi8PGqYFYysceo7fW8nOmAI1h2MJxZwSqHQlvR ZkSKUHrgfl7Cfzv7ckSzT/1RfivkaryBoZ9Pyc2zuDDMhvkI1++2xgdku5azc/tDwH302r0f HV6QIL3SIbgaL/4lczzLtamY/XiuJLBu851jQ+H0VPESxP2NtATX/f4WFgWZzi3VCIeei9Jq MDZFPDzltLQ3iwAt/562ZyYii0QaDV7Fnn8zC7ID+2zEY97gB62auOLVOBvTBidSW9FZCAt2 j2XEdteW0Of40ALkxKiXq+CJZLzTqQkBoQCD2Uuiwe/2H2V0nqey2FTzfPtzyM6aodpFQs1D s+UvXpiyfhvcLMEUytM3xe+dn8tQ4J3ACc3dxXwXuvlcuwrslDv5ba4movsOXolebM2hJLGB kJ9vseLGexDhzflsmW1m/Espp68LznVCswz8zre0bDtrZNiACWIG3VmBAtgKO6ZI0KFfqv1b 2l0yRzCovjAAPs25EofbdtMz9K12vXvby9tU4WrZC2cP+dvEYNadAxdqtowhZMQLeqhmWhmu J7Z+Sq3IGt2ceaIVvSXjun3fuCM2aTbOrgGDp7VBJ+MjbTL5IVxxi4FwLol9l1N4DXs+sr8M Wc0qk8vACB3mdP0UfsbAZNdR0qJcrG+xAZsMjBpcv4kVfRELw7wft8+z62Y4yscl2/DXe4tL 5VH9ucezxJpbUV8QnjXm0gUtlC2S3ncgbHhPLY+gHhDlY5qTgqHs19rvrimIyJXyTWKPGfd7 p3aXjPpALTveD5rCmfnNtkMPc7xGXUXtvNtVzHHRbSrBukoGOQnVYt/w1vEy+ndRLh72NYsE aDCzxyPL+QPhSSG9ePi4fCFaILVlkLbg5ptzL1Z7I5iGtkd+iURGx7tP8SB4ewhrMHi3yJ1/ IuEBNqNkPxg5xbo2di8XWBNfdrqVLJeanJucVoEIk+znfdQftT7v26GdnDZJuOabpz5SvdP0 G2PFjMVzYuFusVTy1/apOEYixqoz/Tk1J2hAFjgSMvfL8uFVISmvyT8psOA3B87LGAZFQpxF r1jNmEJKglD305oia+GqM9X4tvr1y+vZHVoZJ004m/ikCbzu/DWiI9C+YiafLjCB6kpaW2lf +arb06FF4TRUawNydX+9fpJtXPUNT9IXbuhlKTnTv15yzAmT3CUJY0MWL0nmU8CQAH81iWta O36Oy0yC76zwwEgXS3qHoGt+8VRrY+U6X4FNQ7IMz7dfKBgHPiseAj0KtliTb+H8B4w1uwqV xT7j42sWM/iYp+StdFQ3LwOKBDs8xfHDjV0axENvX67CUOokWtId+7yQ3wqR2WaMOam4661W QrU4iMkch3eJA3J2s+sTp7JhLk+wZdfpjTdn8dZSMZVmDzTqVzQ1DbwP0jkSrvCVbu3Tq42x vW/5e/HVb3XCoogt8wz3HVQ5eD52jMZNPR54kWFgJBYsW9jdhhKXQOTAoju7KBDSEqJVfXrq wY2b5rnY3g2d5YnWRicxvlV7zz9q7qLv6ikYwbOmgid1if7DSJTUYDQ+LyQ3i4JJIL0TB6NP 1eqAYnV22oWiieb43iYfRoLL9Iw9MNtg3BPmGd+tYDp18+Dn8JB91jUTWlmddfvvKcmprZq5 o9IDzQXVdjKDssIrAbIZkRlC1hL7omnhQpostV9DP6LxA2pIe+78vO+EDL+0Dk7ysc8I8//O 6RbrP1DH1ogWwiL8VcXhmtOK8pHAbNbBtr03sgJnCk7ZaBxoJoS6fj6p32JLe7zICMH6/mKC Fvc9gmx6sq3r97yYmoVZsqvz/mvqq+lrwaxwNsxtQQLqQeOmHIyZSO13eQuD7oZ1m1Ow3pT8 ES/UR7QcvYNMyliI2jNruB1OWMIrwnCbXQx4CBdUE4bRZCrzIObCePeWzqSv2FizfiMJ59/L CbFqZeSeXKJfYuYPbyaQLPlI7kKmuPHsXRqDsD77fGC8FfEEvh2Uds36VgxriWhJBizb37Ji aFIWom502NLvxFuWBjlij0P3HlPlZL9NikgYq24A951lXpZQSp4wGPsxD+Dcvv5odaNCd96c thr9yrNWjp+WwX8sEWZfQlWTrEqmuegj99SYXnzbx7UqbTQCeCY5P7WoXsLP/Yji9InDgZOY FI0F08YCOWW8Ey6httpQUaa2giG7ehdls/hrqHdecMJsZbBZsgYhL4AFJBC/uUJ9nsj6tYAT tmPOK9El5X44++lgrSYpVSF3/vm4O+rkWs3zI0ZY2eEwwnf1PQS5Cci+hp/h7SUKApchzJe0 jR5P6G3RXDa/ToWCO46Zdrk2ZjKEIODJW2IB/UsKEE5GAsUnN5/SOnTlBLrtJga83yS/QFde f9rUhOIe4De3nHI2CnPPcv3EvRj5zoBvE/sznum5Absh5F2CD9xAyTJsky/cMQuGAS352cL6 G5OMYSlcfg+ep5Ayiofd/UrMpi/CW6lCPvCk+Z1Hkvynp3BkcQ7HoTHcVHwkMmfrlCxBX+9T dY2oDelbXgwLPa0rob1vbgo21nN4KQZQOXAr5sBfeLqaNVZKy6woEWVrT48hF2wcgi8q673M UPvN0l1KwXa81EMRfbiKdWIy+pS4bS1c1IizohELOl2Pekxxzz8k47VF0nZmlGNzEQqMOzX5 t4MnR1PbHd8p5T1k4nxomOkgS3ytRmeQ/FXAgXOfaegPmOFJQs4gKViqqOuZWcpW6sBUqpv7 gG8d7MquSnPQTWJ6OLafSQRDwOgUxLfzJeYJqgQGzkU9xdZbNrTIkwtvzszpgIn4zJitx2uu BXniK6d01ZfTBgW6HAcOJZ+XYqTF0aU2R+U4VY1Sgqo+9kHJIRwfn4dCC5OekAqmlg3AGB5q 86PID+G16Xv7b7eB9lNEitagwvEvBl1FPfddWz514pLz+IFm1ox6+50l8Z7sYeVzHb8PWNSD REzEOg1x7rb883ciKdmzpFAKM2OtF37tkeuFD5Cj13k1ATpzoAlH34tyQOy+d/5up3F77taD UxEVUJ3qzVz6XbKsMkwjtArerLuQVoSzdS8Mz4oE0UKBPHyXYJlj3jl1egcjxDReyZRlgFrz TbU3/esgZOtBwtSlBKEc09pIqcojgdgOfOI+gv2kXmWsfg0S4reJkW7MDLqtMvGRhncGNuIG pOHuXNU45OYD7xk1igSFAlbYIsyWKsUJTrrr6Z7TlPC6MUnd5shZhpuormvZHQ5kemV09qHl J3lxBiB07mqS3U0uVgPXGhJ2ktfbgp7FeF5KKfHj7SGeIwjIfAgMR/Z/z97mBAoAqo1l55No V0FkCTVNC+eOfDom8UhO6IpszmOzMKQrel2Wkc/ilCQr8w0iQCd7D8S2WoId4yL3zLJC9fnY 0xNHZUPu+C3bcrv7DQnhhrNoazMXtZEoJHa9pCrzxzFGCUNos5lkmxO0OPKfXAKy3VaTUsi/ ne6Iu+DORQvfYwb53WG0wLgE6F+dNsnEfloomrT85kqi7kq2IdXdnfYJf1lQsoln2akjDnYw UT6+4Fu0FCUh9wd0k+dvr2asj3N6PL1ajjb4pVt9zSG4v+GX/HZz7R24SC/IPx47Aryk79SO qLLmVL5JU0cV+6lcDo+QiTnuEKDgCl4VzQfa9ShfCzL+uC1LNSO0Sl1B696fon9bsAe29KZE unjO851By5hjD1Hf/1Jok1UXLtoLcjktnzM4c/ODCELbQop3inQfI9dAcgNlrbfmEzdn0SCn T1puHduZIaYl+LO5MERVpfQU47fRGRHPhLUSkwC3fDARgzBJ0EENIrAVAdPkkF7aj4jJcEz1 HFpEp9W1B69YH0/8OF56nr7AvMcmMkL+tkdxj0dcZyFHc5vaXhF0lr+ecS3DpkaJAbXxI0K7 TLGrZC5nr5MKehU74xGz55DndFwjclGQEUoPwYWDnsWQmIjno+Mg4T6r+iAFOeLNTwbSkkW1 p1+X64KcqFhlX93dP2NIzVC/r95frNgckm8+WGp/nhzuvKNh7yNOcTLSQhPwEEjip/LKQd7D qbnvD8IjI/tU+FGgLQy5H1O03sc031fuxnj/4DBI86ND28WzZLg68mu58u4992+GQgLxflT0 MCDN7flMFCplkNP6xkIHDFvNBMCG3fcyxqf48bJ9Sl9KjWwxGB/Og8GcO/uueLPFKT1J7PNc e/aU2qOJhL2ZE/nV5GRdT6DJULatKlS5ofHDGFa9FTFeBOki1t0bQkZ2O927SRMn+CKmekNp J14VXFZQIg8SZvB6Y5oiYxiDueN54wbGJyTT1TXuAlwlk7Oxph1zCqEfgMUo1O1JVMb9rcUK 0hvoBJNoZA7veNBttIRiUUmnB8siFqxIKDqSt++hZKXuUKlWrAmJ/gRpySxzRmMN1ztrO0bX 2OrA3HddXaiwdt4CpK4zNQKtOhDmvyeH38hD4Czh1VkQv94PaXgVoBHrQaXethXSjJvjQODg OeTvhuW3jTXmaeHSH3Erbr+TJvkkOIqOPXiO9+qtZoRF7PoplGDR91Mpddi8d66WprkbX38Q rSea7IUyrZRZ9evuiZ+eqalo/fyRwRGWqlf0y0ZOXVP/XKBwFe4pyT51GB+k7W8LbBqqBdmZ 1qET01eOZSOxu09Cntc2kB/fce6hbtfG5ArF5mQ3LfYEgIDWLUNx80j5+V1hmd/Wv/92cEXD cMGkCF90d8v/qCLkgMoaUrntFZC+TqGJ9zmobzUEqh636GezoxtEYJZR5y+dPtH2iq2tYvx1 dRKFGiYPjes7hW4fDA26RokjC9CmSxYkD1TisuP1tkXaL3J/6padlM32hPxHZpk0YuwcoGuR xGDkhTSTTcFaxFngZrzt9Nx5q2LHatgx7U+9OMxVp9vOjP5ckqhdLt5VErQy/DECTdOyp3MB EiLUawCrNzmI8IPg7Pyb4+5rwcbdx/jSpBzpk5/03SGxRjaBO2mI3CrswUEEQSntKTc/hemj 5pP1YP1Oj+KC8Ki/mf+UJ4zoGpfDIM+Qb9nn6RdMuvTBizyJ8a5JjHtYgBQLqJCQdFDEQJDd QW2QbmoZnXa34D2s4CE/JsaTpoyf/Oq3xHI3JV3ezYzVJa6pxgdrnr41YtlMnZxx8+WQWSYZ NbSo0/IGKLsrLrPrEGgsbStgjyJGFyC6CnnpG1gl0D+ZqZEIw5/aWDZY2OvDda59tFVZ8jzM Se0oN1ud3Cs/x4xEIKuYTwm7LrXygGnSF90EUusfQzZUB36xWqL3DgP5JW5OJ0ssvfjPWej6 b0hYmGzDDr6ih2wNeqId3xotD7/cveKNR6isLwLCn2Tsawb9NhPQXK++8FqQrpGUF862Yp2Y 6MmWf9l4sogewd8wfuVoZGuqKwNm8J81K2tSU0F7JnoqZQATkQ1IqbrveGbXOe54LfZvWLHT gFEP0xOY1wGKqRsdw4xpnUwvP8LY7yBYrHw0mbXj5UZ1PBydI+XRgkUHPAT3YkkG5zg8q9hz Nwmstwbe9Oi6u50X52zmIfPiJGsXyeOiYU/MTfGk8S17AuR8kLbw6NX4jZHSp4u1PJBndmrh WrM4Lq1/Hn4QPxq6U/ot0rg+jhaWcTiuCRHjTum+gSRgxpeXPT/All8bfEQzLlK3M3MK3HRA 12ScSVBVYTJ4LN5iJj64gJBs+zKmvMppKNol4Vm4bpgqOSUhW5BiZ08fTcqsFqK1XxE+Rpo8 HCfcs1WPPF/dEZ5YAaEdyC8gXtiDkmFVDCqBO/Nluv5q7SPx1tnIsqg0OBqwh1Jdi8fOE/Mq Enn2vU/R9jasNvsaH4l4xzAIzsRohvnZAfNYlTJ8DwWN6DDhFwe+MFv7CWnIkB2IFfhSLq7L 2Zh8nff+q8kgHuqMvTExQYdw90eBfT01PVxSZ9cFaqn4+M+ybT2eWJ0ymm9jn7BADSdGOtyC wNGTi/r6lJ870LVQGgH6kRkj4+R6em0eVPC/WW0bmy8cX83eirCi9cvvVA+jG+m3tPgjFDdr +fi+jD31B19/iPXSSHgONrc2opJd9GdPP7mkTNJg3BcdOXsuc5OGNRfnsqRwZ27UXyzvdYhv d2eSswZFjyLNG3tv9UV468ZZCO/gG7TyYVLNDtjU+2Nzf2gJunQaaBp7eYWBnq9tYewEwfnU aofH44iXHXDbGyInpKacFvcpWMQF8AQSBW56DMTqfG89roYR5pr9Lq7jL8rivHNCQ7COliIy EjjuWyLgQaoN7zQYFKUf/GwlSDASF/iTY2dHRqHPthdveYR6ZSYKxKOtCuGylsWnqTztou72 Bno4zE1H9HddnCMOIu73t2Kq86LMwKAyQNN/yw2a6BW2peZSVrT/bVT5Y77uxUrjiWfN/uFl ZX0QLj15UX/XuIBkmXi44XPHEH+r/sH46oD/C3Bzz8/5V+/x0wqnpXhUuKmHjzbB2Xk5LaVd Zv+7+vqv7x8WoDBHz9bPg4+C7ytrudmhoe9r3eD1w7t+YN1zPPv2ncPUQZgdCsb7oPU6VeW+ wXbf1S9Y2G4ls8hE6H4smjVOVKWS+oycVOVfkf0AGqS6pOur++SzpvJZJqoaOedrDX+ApOj8 k9CAGbz+iJz3i4owl6ZXZirp1/NDhdHPcI0q+fTOxz/Xdz3ejBurxRxRcpqJ6vSb1LYDSPxo i4T8vrR9QnBHM3zVtzgHpEAm2NbhU+EJE3fWGOGCHvce7br2fVU9g5kCNCNChKEsWc5uHZFo D3+HjWI0Ryyz8dFHmEPQjy9nMBBT0Rsk19OAfh7Zl4OG9VUUgK1sKN49ZpJQVSUL+jFCdu2w oTzOpHaTIO+QyKTXivaccpNnCAGabP3SmQocbzIxMMlbmKuEw6HXz5Wt55n6ElXj3Ihm9L4k NsPLmLmuTDpz1ee++bDhycwI5wsDsZOrvHZCloPX+rmoKBX3HTdv68PF2QTgd4YrxTihjk+h cJRnjUGVnbrPxAu09ejv83F7l9hR390UUO4zL+i4pn4f6L1Wxu0Qy4dNX5Y0bXnEYMgmCe59 AczBfPa5T0sYgDdjO4aRVBM+CGte2+V4Ma1zHUj0YOCF+kkFpKNz0WIK3WcdL1TKRg/iZ8uz ohJAGwFUKL8zcljVQkVMqWLY3SHljSW+wnDqWn1aHKSGCg0j+v0WmCH97ueCT0p/vOPdhp7n k5q+plASGeOkiE/+Z8zg0cSYIsZw7a1GeUWtaxgz3kt7BOvxWvWp7sObHKPf+vv2vArl5Kdi iOa55HEIDE8WiR5z5W99icN+yvv4LzyNJfo+dMmLg6Qz4WzbhXkf4+7Rsc5IS7HODXQuAsw7 HTDSa4E1RKs4wQnvO/pxLSapSyYORDDYRlSzDEPDV0OuW2Ph+2A7WqpfIi0f5kwnnK7eoPmw jsoeohPUrfQbS+CosrizJ438bXAGjHHm5x7vjA4IXiDNKWoPzqbQ5x0ADlq/YorGEuYmPGaj J6AddspePX8k8i1TSKmUJ/JtY/qpbPQEt02RPkBMQ5FFM/pvvkcnYjRauk/ag4Mh6x5ofbe/ y26l8R6RdG2tetf26uVQd7+Cy4l6gdTIDmCW2y77NRRGaw1xILztekKTjX2Dkkefro3kN3B7 7mKoVVeXNPcHc2vGYsmPgexbAQ97xEm6eE4FiEDTTdDE13NVotQirmPxKZ/cpznxZ4eaG8qi kJyK61ND2EoGg4cS8s15XdpKNPglnMro1Er9B/iZN6Ph4cHoJJmDrfOK1qf5BqNi7I72B2wO A/7SQEe+ZmxJ9zODXD93KhWGNhDoxxTE7e2dDxOMogiugiEM0oCXSSrhRf9WF9Mh9ZDfcV7Y zzij7Vw6nr4GiMgW9H0mPyT2U+M7ZtKtUW+I2CYfwXINF0Md1KEmra6dy2Pul1k94Zsm2rAc JomQXqc13qDufGvIHLEdhb7uzYzBzoyTyGyc1sjT24R7BgaHkUEroww02WwvadlUtTTCDbNF dX15uZy6GLq7r+evZr0qiVEE/ANhAiI0nzzb9L8jtQrfyBtPQYpGkQB7jUINms/XNkq+scLD vql7GfLk8QdqIf4w7Z+/3LzaGXghPydVrYCWLFAyB9G2PXNhlQ1xxYbMhxIvGJF6y88gz+v6 Ti8umMNpwxb7xdgNvLOV6B5LvGAet7vtT195p3hDvB2AQV0qrX8nQjb1qZf5R635iTS8x/js etah/XApJ32ewJ5ywfUXA66r07473cQW+ztWuikGQUr7S2PNyMIOGP3S3zNNcGad8hAO2FhQ nSCVw8HiwXXhiMDnZYoe/iN1AiVv0j0NQpk3imjl6X3i0em8V/6lqMtI5iciASwboei0aC/+ StfviIr7ZULR2KqBzE1qVWNBCxeY6Da/SBw+qQwxL+PrExPQBcvv5DZPZZ2OWXesS2LfSL9n cC2CTL3uZBGbNfDVan0fITW8obc3SdH8+QIynPp2rQH1p4ku+0Y/Wn8Mm/4cH6qgqEjtLkrD kuX2i8nVpoRmKkZUj/5Jf98LvHO12fH9W515lRp0zHeiwo9jv0DWZMks1cQHJ3URVYSpiXlD Ut01ntQBCgswBd8wlDDLeWqu8+TwTvr9lTVVLlAvRVEoPlba6XemyqbeiE0l64W1UsqrGj7P vXufFau+wLIv4wAxKFBIZWxxx1GcVdFrrsO4N5tWl/nGH5hY8xO/Wxq+AhR8XNvv6m0SvUv6 OvMTQbE23MRknrT9oZ647RRxzM+gxOHrOJEyiQKbS0lSdfgcZn+j7dNgf6zTvCOnRul2GlmN vCT+AQbUTft4OfYH1wdRe2EriV+cYrJFPxKo7LBazHdICHb3IrpV30NQr3tgA8QSX3CPxdVb oCXee5w3B6H2eHUlNJtpMKiK5BVLSS0JSRHkmgQtd/vboGksakwwjue0S455OqqfVl5ZccrG oNJkbFKZhB3o+pkqEiHieCm+p4z79XLBQ/M9Hb5lxXOLEC1NnIjMJ5nYbUjhLEyMOsQEMY10 SAntemAxJQ8h432NuUAYRt7HltvXPTiBSkaPn6rGlp7JXepDZIfDJJwQhxRu2+csjYRQLBIH 74aKmiCddXem8vRM5q6YCvELyy99CpS00bbT8VfNl48kGEt4HlEvKQuWELjJAgfQ9+Lhwq/M FX1vrPFCymqg6bLjyzHeIXsqKkLTrSBtYmMvOnyxJt53eSW5rIgYxOuuakmxfXd9Ho7ceNEW hqjQ9z5Xv8mk7LM7F25wOVZlyPKsPbXXL2F2i0CPOewK7wA903TlLelIx+nr5xap41d2IbSU imUJ7oU3yzxRjwv/Ag6qTnXTEan4d/hxNGwHF9vPp5vYx52KDywuVhod/TkKJAmvp1cVKKmb 260f9sbPMxikLQp/QKxxHxs+2Cc2K7HujE17iJui1PeYIyfiz+/HKR2KIMiUyzdEFTDk2G8R b4z7sI/m3wIgR9Njo1coILhG1yd8Ymw9n00xSANySGF+NIWxEerTB2678wdHhRvq76y+eRZI 6WRYSF4WsynUsJFc6dMQSYaslB/eoR+CXjX82HkGSe+MgqtZv47bb96cu/VIVXu1Rc+2TIQK mC4wk1Y2fvu62h5ve6LZTS0e9Zm97T6AlrXBtPFgZcOnqGzb00NFFP+yirIEygaq71gcOyuV cFYF60dU4g98Afvs7YoNjP3hV4u3F52fzrxcRBJoPmM4eJuHzok/Y4mf777kOdyrSkq9/yrE m1tanObsqtbk8BvFI6d7Y/1Zfwq+UMETGV9MQrhgho0iwWzR1pn29Nw6ZmqNQ2qjJJbIi/aX H/ovkee3dhp6TDnCMCgY7kbhC7VxeAFOFYFpmB8oyUW0pWcsRfrc4pIQ7LB9rul4NfkxzLIZ 1B4egd7Oyp8qAyQVmUkGN6XNv3A7sKtJar0sXUTQoEKunvnx0mFnkss8jIkEcC8EWRsmWleu mp0If8nNtPyk+8vwXTxo5S7PpAUPZa4hX+2df7Bo6ejOG1naW5tqFu/x9DvYQZbm9PjCL5At V80Lh7v11aN2bMShCzNO/TtnyBzoixlbAKr4DMcavAcEMRwKfTwY/qqEgmqoUaqViVMRJMvP Esr4y6/sp/hROSnHw8lwP7sAMdCZbscwwS44jF76K1x0uQB6rpWUoE2utjvnZqAwAef72N7M V1bYJTROisy2Ruhg0eRsc7mVKa9XBYMi3UaGEpANnmM4dTNL9K+qY+g457cboreV9AMfdezI 7YcACKrTR51HX+/UYutUIm6JTMpNZdU7wlj/mxRBngucCaTPNB3n19vAot/dSrvss7BhKgzf ZgmSr8aYyJyqx+S3opN+JR6wMWWbD0hF0XRJA1Fr6vCNmSrTx+iMPLlO63flgrcI1DPapikF veG/cagbTTLWHx81FhVCGyTrSZQZQj/2PGOR+qTVJgkJTNtQ1sVmmf4UEzkzgjG0mlSAJiTM rJtWyFurqaK8YW4z9zVncz5xuFAkhp1MGt7/vuqZuZn55PVUOA3tSHtiPuBJzL4Z+TZxhhyC Agn4vmXaOdPp5dCMFfyFyoe4eV0nZy6C37dgo/NtzvijfdspAlKxDzPbGlHVdbLgbbk24AZV MS/nQjtjnipCCVqXQtBsG9OOi+zLqgvVd0oLjMpxL6k9hjnhj/nEZdjREp+vb6kXbrjzncYN I3i066RElStlwo0oOGadDfYNgsjjcuxpf6cIi9btkohwY+qF37niYaGSQAH8Hhw0RCyZsbB2 RcoKh8fttA9eaaNSZM/IFQdU1I+tAmLLk0XJqPjD4HkjrpecONE3UNuBHpEhvbldAaKi6RbF 3F8VWMMlczioAXl3TIlLQ0c8TTb8iBeQsvIKTdcOn6/ROsN+tsn7ELVxEZs2b6+jdd6yqgsa a4itk/qzXwFRZLW5ZyS2mj2dsNuH8AksgbohD2e3RP6UzaJuN91jNBqGcQIqyOamItzv0PYk hrtNVZermwVQr1S/eebf1fScZkgjK0GY5R05A6ZnMLUx8U+OsCSgOdL1e3QE4ymIbGqQpzcs MAlhqhOdXlGvxFQXA1I4Hat3+uTdhr8LSCBivOdA6P50k2/QldKzs4mWgskQ9OBIiIsXkHE2 oZirUYx9U8V15lMtS84NbNlktFKr5keMClYlVS4n5ZpnDH/NWKtr7q8RsSWm4DcM11/3dPqV f8aOUjwrGUaVaXu7xUb4XppCKnJ1NBbP5tswHEdiYzON9Uzn1SYlyrF3Uu7tB9sL989dP+fV 3D6ptKYl3nfkEWLStf0OoWDZkCEGnIQ8z1wmO3LzVnh3kuWZ+CFGPZLZO+hOVU9OR+oNqm3s 9s3n7ypcNsRzHaglpLjpPfvX91uDdAT9/I2a5DAZDsOtV4e3P0yM0qsiHK+le3/+xrrRVcPa QmebesLnbsDcLbqQGYGC0EXdPhMx9+hDsyUxD2ubzsu5Elj9yTwEIrZIC4Kil0/a6fayW83o izpk+84D80W/nk+H8DiLvMeGgdkueqI5pDI5g8z0t97PZHkv8qKEjW+eFElZwsBzdIQL6AVT yPB6N2pQjCa0XvCa8jKM86yw1PVnC4nw0bEoFSWsggKV6x44k2/7HLV1AntrnoSpMkesNYZP w1FVeJoO3JimlcrqllJOL1oCil6Q0BY+of6i78xjyZyx+k1vVUvGSN/o1jhEV0Nq21FK5umg jyeVfh94tSIIDTJItXHDbH76PWAyjrvokiwxmE4cuUrGFAnlA+lZWW8bK9HayLrsYibPmEvh IcWUkcy9rBNAAA3VHK8ZjK1SpH9kWMgz7k7AZz6iT0h+ycOi53qsnJtQx87kneKQaLpD3Dy+ bgTH174NY7cubF5ezm3bD11J8KP3s/v+DsrRlawksqSzgqDcS5sxcv7b6slXyxoMyMsBNudM r/Zr9hgVBWulSX/Gay4cQa5p0d+DTLWsathc/RfWcWKF+9B6Sdsc3ngGVjrFkXW1S4VsxMmA z+d0WTiaUYSfryqwMWC3oEWcI1w0HPp2OFJLuoaXEd3rlONfgEjNS6MDDC7CEGIhm0KiWp2N wsxJCL+MMTcvCDvStqXKRKkK4ivvuShlCS96XUEqz9mX2zOdROn2PgUDsFY89OYulioK0E/A fUssVzOSWAsUghCiLnkK86o3KhpvvhlvvM9emxplgU+dd2lpuJJU3wL8PeBMlG1+JUWqErFE hAZqynufvY+KmOANgu458lzbhhD51sanl/csb10VXb9ttTHhc00alv3D1Nl9GX4Qf/Q8INxm +5SzQ7u2Rw1KBnf6dYauPh1zUNY4UT7jV3bnXlMqLt9WpYQexRuUYWngSUrZ9cDthr7s782g OiZ3LX2+z8qLiM29mmXY3Wi8tF5fewdauqBL27vh3fYNNYsYWRLziReJkwJVt3RH+9AjFNIR BZWRluMQnV6qpCJ7HlZfULROMUXw0oKtk/zptTex+bc+8uAyzIxCtTCqBIpfK81R+PIalG/v ub1XKIUM4YaMFCk8idx+PNhJg1U2rArVN1OTJiFz1S3sxJCCw2lOvSrPKN9WJn6O3IYKXsB9 yjQ+eT7vLYDdcA7MgNORYX7JPs6dlbVM8pVW8PJDD2s9JH1hDy0xiUenmKeoDxpKqyV8pxJf +fVL7ad1w65DN8jb2Enb+5Hg9xlJTGq1zyrpPxO+CWDvW1E7Wfs/09cQ6cf1CPrEW7NstuNT h1Mj9AG0tFueR6KRQJ9wMs3VRQ+kpmFdAMchZrsNFa/EFPJJ8FCaSGyEBWZq+KoA6nGi629q dthLWgqS2s0H5YsasjHbWVVuRhgIPdaCCi5v+840lcvuay1Debw4Wp8asPln1Ia6ykM+/BKJ 7mq+P+f+zfjLd3/CrSEWMCZhoqHdJsSo6ssZdLDrxH4pZSS2/zTN4SLt7rSEDaFPUKyn/2qg 9aFxQCzlSK5pTr20Ic+R/ozZTXUoDfZBkIxvcbeDx0G6i3iFvOZMzRTWJPVVbBbriNYlofji U7ndou8Uo99kAL6KZJdHXUbzr2RXK47l06oRiackdvVqL5tDOVd5LuLNvl2S706XItH5w91M hPqHx7LYalg0wZz2Cod5moeUMMYUz0I1IbS4T8/RB1CsRQIvFnmxEH2SS+47LRnTnm5T1vKg 6XwZEi+iMs5pQLrJq94OJtq8uQL7ZbrQOchwwK9xr1AIQdAKyc6Z7FLRk9D/nEzUoV1pdFga 0/otV2IxkZJuz3i5DpGMnXpVGwcGZWTrTpZGzM0EMXVDLMFHSmPnWtvkFRFeU7pNf6ag6sWQ OZ3NGZ55X2hshYaaJZvOuc95OpuKflaFj9h64eCl1pXD5IFSpXYOb6uvHmKpwqdP5Ny6W9dy /KEgflM5/bTyHq1DkzEjR+6x7bfZD6l3PABikwPjEz72vF2JcOxZpVCIn1JuPumb7tEwcwWj VGgjbw/3pOmSkId6VYrmD8B89Zv4qIhvBsRpezSeSSqSsop4pov3glGC7mId3VScF8XTVvyf hIyMiswhQExPik12rut+Q9/WdXW/7eHgjuFZdstH5KCm+xdAH+URsHbJvEOrTs/gVTHTXrf4 VIDxffyyCbS8l/cFDbrmx0I0JkLQB0r9wzLZAYObF76oH0biIWrtKvuPizsG0hoY00blPlGB n6rSZpKUFB0422WKGlMaavVRiae+1xL4AR914w3hsfx4EL/y12H2LNjxlMzxxEMuvb9CqIwl eQc/MsYbE3csxKDi74f6yGa/sQnKH5RnU67zyCjpKK27nFlsHBCqpPsaV4086YPaPnRmuCqD isegoESTf5oqDbXQVL1hh0gx94RR/vIL05SpZXKD1FGZaEOgy/LsUmd7DAqi50sPZfQLdGYd hQcHMyd8Kb5MXS+pOP0QT0q0KZTqJvYEjXIH0SeW30C8b48wHdTuEfaSSmnRNYUh2J27xDNr tW3h9GQYDAaPlJIt9vdvWwMtKrfViyY+GD/grmO4pUNY9glnTZ5VkVlbmhAs8TS/NbWznJ54 /aAtdmPwqVwLxbgG3oRsZW9eMUlgyDck4IqLtiRx0Bp6z0tLYalTdd+id7Ia9kqIZCOKCahv Rw8ijYcWEOMKIyJjJqqXqAdKfRuKHGBFIA2SkqKJ9xKtL+k1vFEMsUcs10LA8Jj3DBt7K1WW 2QK0kgSpm4SFFMaZLqwUfIRv2Q66P57ar6M+78GEjkaR4j52uFHHp+IokOcd6Q1mQYjpzPqm 5AfCvVWdcBN08bVR/T0gPlCKMQ/J2KF4gpwg8B5qkEAriUqRpi6+b8A5bkAYUf0whHfwBlWV m1LrVPtgS6PNRHMpF8Zc7pgCp4L71KuVW1QCpijgS26j9MPINy3aPHq58kzqWIrHqvACAFcS 3DFXnkK6i3H7KPsQUGPQowiezudDWsTrlJkFmg9WnwfgKIso7TvVFq7CXUuaEA6U6UaZ29bu 7BIu9mvZ4oEiz/M2PuaGnded+xOLib1ml/fHcNgsRE0+lBeo1U4jz2C5YKcB1UjX0zXtMMrt EC44XDxTtYUZs2/nuRauH4hiOBfdrFWApUYTjxqaLVcIlH1e1Uxz8vnuxrm5j7MNWXkrI0Rm H8Ru5sp3ksNce0ScjLRs2Xs80XLyYHntTtHPc11Hx+jc6i/ibF9swrHa7abQPjy2/KKPvGGW Qa9ekmaPhec0FYcQX4eElA3pYLxPs2TAu/Tyy1JCpSAxSKK47TfcXlveYTQKu0QchnGj79Rx zfzY0xr1AnJYdD0N/EUa7z7R3Cv6/VXbv5S0ZQdWiDqifppxKwXZB8EoW71WVko7J/OYolce jtiRru8XBMc9KgI0EfbAM/4VbujDjTO8/73AYz7LvaCUV9JXkL2gDwdhFkpoJgqzWB1tzMKk dI85NDcdwema18nqhf9xWOipu/JLJKpwE3Vf+wo6pPEGvx2bXvLI52uLlx0NMgoa42ijLahs x316wFXkqZrX99PHRF7xybgURFkjUVKuM4mnhm58+YX8Kz+GY3bN92uyfOQEDXHtt+cExeIs Bx2KXe+d7az4CT2MpxHM0hKzl/2Wniia1PFABOeIuX5rjjcMuMstudnRSSW1r2quMHHRplkR qSlZrS1Y3lmxdLXvPHxVI7BYdyX9fVl7dZHlWPFx1C156esV5Lb2WCe/cb3GxAlx89i/W2oV QMOsk6uHQNoKuvEUb6bZHvf32JpswFNA2y9cRNqTMKFYiPYU0ClhstqL/fmezW1sdxxKZWgV GQnqsrXFyiqR7ftK4iNn7J2D2yOzHfu8XO7xycrUq7da6gwEaYrNKtFKb1p1wyk1x3Tfzdn9 VUfQ5Hhzwg9Ue3SU8BUTAgwpHPGZ44N2eJ9+8w0EMas4f2z3+sBp2T6+74UH6h4ctR5QhYh6 UN92BIxuknyDDvRORftZf+fSYSQhWcDoBgqQlmPBXOYYdFvDm/WKxjFHU6DwaOWYkVaxf+od TtY9ndu1xPwgXYm80ZsMx3zVNhy8we7IvFOGYLI0Lo+STI4NQ/716l4iH4YEpdZ3ZruMoIFO fF0mcBYiunbkOLu1bzEwv8mSTBLDw3cI3j6GJQfCvsvxuCWksN+iRA6gFJFMoiqF88M80oyk mLLqi5lsWz48AzIJ957rXHARhdGskNgSrQ0q3hBUmjUJVVWdhe/qheH7vufq1VJJ5eC0Z2LN m6ZfS2ITRVMc7LTjLVNZeNwCabZhycIEUxLiv6OxCNt8rQ3tHETDHCl+IPnaaj/dH66QiJm/ vpc+TQhYepFZ8pA0MDY5J099auckbOJYRIjwltkPLshXvbwgJPwCc+ComP0RG6C//QTjWrmZ cLC0FP5lZEiPnE9QXSaWGwNznlizzMveMYqfr7LwiTSV13KDlyzLSibBLjBC55JzvffYAg0h RkDG7jAPdaGA1Ggjcl8SsNCX+QR1Qvq9yAcu1JbDlCkiEL09/EKmrPc62l6A1g8NR181Yu9K YUdOrackmlT3HeTd5M50Nb/fz15Yrkgzn0Zzm/afLmmQstNX2pTi55PffqRR7WQqyFnUH++A UmvI9AizrfRNUt+3LAcgOk+G3n/eNOzmnyOlOWGA/5j7IHsSw2E6O/UjveEKo3uiurTpSOM8 DBY58ulCCfEGi4caiOCTK8J50NXBJvSQHyAdQP8pvzmD5mVsgVspMg6ZdzoiV32OMU6EHfZb YZE5nq4RH/aqXaGNCzDy8KqrG/5iCf69KekZsecmfq061UDxnJh7UZaNF36eVRkh/+cykeD8 aixHWHjvrvKO1Y7HwLTWTsrHV43/J8sPNPBTA8B6TgHAKRxaIX5Tkq2edfYDRXvnNV+W0WgF TfprpEvhnpsNxmXVGeAXsqpiXDIDnkNR7Pvyhs0u1TzM9wWc0EvhTennd/iL/YY5Wm+OphUT iBt+V7DKlJOPVNaoIlzLPVeNsLCp+QzeNVfR70IuY7yHvKf+/yMmtA4n4DR7g2rEzVdlXrsg gWS+ODwPLyw+TU3SBv5Dn+U9dReXv7SSJV485BgK5PS3hvC9mZasVH0arYSTOHX/JmCQNTNk HCHByWhlDfJecpzl2O0FjGgLHUMQLycV0/hZAWbqt3gKdgyHjajPU7aTXFX0zjHqPR69Ljf4 1wmtFSbZM2g/HlYSh2EugO9Bj4L56bvNF8Q79n26pTe1cUCHz3soCCnxUdyROEqnG+wBh9Zm /m4rjYM2ngOMbRuh0d8xeqdZ6qNLuWZha5Ut1tNe4kTdG+pdURznFHOsyRSRqVvAeoOceFqE 4zfLWNiECf76kiqf7qwgL51Qjn4+w9r1Kfs6q75KMBX4y+mlBx6H7ryhreiTINFa+wr76Uup 2MkYjR+Om5gzBuOvnB6nxtMO6fImU2XHracvAEFXRukYMVuO9R7gjt68Q5Gpc+N63ecsQkFC zSJ5DHl5NGVGiAXgfDrdoZO4xvdKmMS4Vh/EYoaYSoo+qfBYxbJ9ZTmGpxKrE32K0NGSh6Ic Sawlai9d3fXvoche0FlSouj3ibNuVzfs1H3eRy7JT0BaXoOj3Sgq0x+t2eDZCpaLcVQgPoaE Rcqa0qCp3YK0PqSSZNM++JhbHZaihsFwyOWW+FqpkRoVAA1FoB8+83zTUYweoNZPO/AsYvwY SYTgTcueg7AS4cjvXcDuhYLyIeOMXr+1rKFit7w7b+VNo+UB8WCfjtQallaQndJSiB9ACihC JMyLOnBbcNinqrNPuaWAkDNp82saZ6yEKHUDjAuR13Ex1dbY2c42KY6C07ReTRZQ3DVkzotE B+GQ3k7oW8CQ4GF3RV0gKkhqMa3R8NtDnwK0N7Y5glFM5ASy9muk5g+qwHGSL4kWy9dhUcW7 JwdsYTneqH0vsBjPuinx/yunqolhqLbm1xpJsXicqRHm6+lA50qJWp/1GcuxKoHifFStCW9X 0WmpZDIViDnBwg+lBSIYmAAtuVR4wgfps4S6oAwbDcEXdKLZIDliPh0LR+OdCWl0edG8D4aM VE8LUitvgEX1YFnkXGQYXIBfuIjVLkaGNPsWKxve/GXJb2atMux38z4igY6xOocUmnhko4js z5VvoohTX305mPGUMcGx3qnJao2dDCboYLGuHwrdJqcIhBXoJdov1G37pe+bJwv71z0rLxXQ 6we5XoPCg08izJJrzVP6oI5dPqwqhrCbgmDcWjRKltz/Sq0l3R+RoN9gEnHtLBWyGD81YSFl OU8cfegsYhFqAzJZ4vzVnKHZXtTYvg8C19YG8K8L9uuzRhT5C9nJvzTXscKZ2Pj4ARdKBhjT 02X/Io76q5HZ6ULRk5QzuycP7BDWUGAwhNSZZe/36+poGJ25oRSLKsNO8QkLy99IKHETPsi0 RLfnfGU3uWZ2UsSCEJ32IUVyolxIkIwGAvFXTErra9nG5dtWY0obnnotouMmW2EUs3tBgFTV MTZpL8GsN0q3sO2MOPg9rDDbdCVtGL5ER/PIN937giL2dzTmnQpdNwR0fgRPZctEW4429NFb ZyT5MS0uVwrLpAM5F0c6roXDinNl3l1DifZ03jaAUlSkGRvANItnA5KpgLrz9N6/t7nPo1ZC VwDt7fGA6KxNhbaElD/RtjVldIwrZgMJm8LkoiuZxmrRyEV10ZwVmAKhNNQif8Wnuvxzo+p8 Gtc9xNOpq6JnksAyjpHynDB3x7a4QzZ7+hK8ZrAVVHYuqN4F9jBAMwJdJZmNTS3Zb9U7aa6L IoPqJHqaKh1vR9qsc8drOHLzUkBm207N1kEnJOt2kzuDygMQdegRIJjkNejd0DHvYuzA1rEQ mb8vPg+VaL/W2yqW4sCoo03r5XvrJRkOLU50VzPIoB7mhmMCFmb0fJAT+A5Iw9tH+zOaNEeZ yC864aYKO2TB6oK9REXZ4tA+Xh3c2gGMfkcfx2PkJ2e73FOJuudbEW74pDum9FCEDL/al+/Q zc5n2vkURXsvY36YtZKdDShIxecwRJw4cbX3RWTq0wvMUYt+zBlwC6r/PhJZqyt7Ikw/r+pR Rmb6R64Et0UN8OxD09ToRPCzxk/eEKpdFFZL35B/nu2ACIe3M+Fp3ZUkFdkQp6GSjl5bDuex hcyiiKYvmAb7Np3KUrG++lazcs1uib4IU/JsvCa/kGTDO3iJmXfL+/vORjRFI3FM6cDvBwtt NE51V8rA7di9g8J1JZm8y+I59+zMuLPzzo6whtC5/0MDsVb2tpfox0utLaLtlPzuVMCexzqZ HP9xGS0BhgO0fz1NmLElJPTbbzOQk6UG1W8E9XWuMN0FeTb4ugvptrAapppUUnQ+MfyZrDta KFzEJhEvaTvbn4xI9Pdtmnjunm748PvDibFTo4rqAVHJ2WlK+lbrsBGzZK6KkBwSG7qeVwKA GhHN2vcTyW9E2xxzKaH0aDci5L6qdvNrwi8EhiefbdElgPCdoW4inyf7hnHcnxtuZ72uNI/V X2bMHCrcD5SStYWZOpYWAB/2WKoDWaJl/P8XbefpnK6pkW5nmdWQ2Pi7KEQ8YyZOPr0XRvXE 4p+VYHXCNKr+qFspCgv1CD0wivQCyjA5noeE3f/B4NEcRHQsWVS6ZSiKsO1FQQmaZQdRimRl RB9es6ukVZ9zllwyef7T3DzJc14K+m14/Ivc0yiBc5idQ90PT4dsFXbjg9T/Rp1oFFPy7O/S it5FkwBLNzcW3rPCJBM71hRwgW7UAO/Tc3XXmOyzSshteNeqMIgiHs+2vWTozdYzDsGj4qD1 G5PT/OXpgPcBvcuOH/xFnWUF9eXelACp9x28S5loINDhaDRO794JRPEeeMuFV5rNAB/P5tTq H9sASWDbw/cHl6yEg+vRx2EBvntWHkz6gf6jTROcUZPTDPqC2PNndkwHDKn7++fpaj/TIA88 Jz/kAmh9P/cyTyeutOfnLp6e6IReRhm2/wc3m0fAG4Va7LMMQnKcKm/KIgfr1vlbpMoL8u5p A16vu73taEPe10sYftCYQKypT97ReOSluWYab6vbyrN1U2r0LurNZ/Y34nfgscBY04OXzpkc qBh968UeqPLzMSSCC/gFWcueZIrT6uAyqfHI6F4XNfPwDN2f/ThDPrm4JY6aKIgqqkZtxhoI 6cDwKKsQyc9eYSqNB7Z5jhqROE5HIm23GZw2IeEyYgwOrBFPVdDPCxS02Lx6YZZDk15Zj3Tc bld4xtfpz8LhNvCkEJEcE5W8JR+YLCHiG9uJ+pvF3LcMYyiRYg6g+iUa5xnJXMkqwzmm2JZC 6N+77BVb2+C7PxZ4E31MSaUaVxz1V3BH4FDcELSP+tHzvTe3yUNuUuMTLiNNtT3nb2Rdmcf6 +yZvBhKxJwCCfcHo/VyczH1sWYhpPzYCI3zBl8Q7ab5519OC6kLIb0F1OT6lptRmcmVLwRui r77AYjEcPY7jDZhSa5+AzUdmLGFdKkgGvUkaGPxwIMit6qjs5ItpJ0szLk+6SnDbDEcnFqm+ y3Jgo7vgPokr+mzE6uMWX6K1lxh/YQ3BMzLlWsVI8Q8fJVreGkpIFnb1OmFLI4Ur5NcP5vh9 eazFhsLNUQQHtsr0b+8G+VBZ25hdNbkeabmzeZ14Kt40dbWYIiKAvdYQvzk2HfbYhoOyoZFD lDh96yeJ50IyFypl1mg14Hsr5WPcCqRh6vlXeDaCCxGfNRO7TzJhhy/8H3dPYXZ3aV6gJSLD qI4u3k3Bo/iBQhDVqerF2XoolTiov7f40bDHTnMj9ED7ZHPFMoUceQbv0mr2kLyGzKOWEWfi bNSoT42J93YKFtgsI/KkCH4FjHwJGP+A6AtN0axgYgzpsMfEGCDIJaGXB8XAP1ijsMM6k7Al SfRvqTuBpTaslrJM2OYBCCy7kT1gzPAlvjQl9vcWJAk+QIA1Vo9exOururUne/xPyYhltC3I Y5GBi8DZPVe7U4xmSj3GJfVktG0JXZJRbml+7IhLJR0u3OY35cEByxGE5yiLDLO3DCHys/I1 AvupE1vMGkqzhAtodWuC8HL/nSsQ77GX6li0X2tWgp2d1y4tGnL1o7Y2+T2b8esFnZXVnBAt lQt2bRA5zxAMDUevn99jKWhYvR1gducim1raVdbqboe20OyiaMUC9KCMCsgg2RCMNub85FiE 2Dq8DXruo68Bv9kkSD2MjvEMLENx3b6i/NRVfQ0i9QD9QzoSJJlFNCcYOq1zqd4yCQG+FJhx 2s9/R/w46THSWj0lQ5Q/JKt1lqayZ/FRiT5g2PZgk9PAYr9SU0CAMMcjOXxqqGDVzYQkoWQ0 LwVpD0P7GCWJeDGwXbTafEuaxGc2H6Xh/WQlhxrDlpTzTzy/uRaEYIrQURbcHLr0oSVclZ1H +ULFidO42MtKakBMb8HtekZ4goM9sArayJm18Yoh1EyJEc+bjfzRhVXwEiThCb4Sadi/rRAg /ox0VNoHWZcC1EkvY5uf54KXBdtBHTWjN9c64wVmkX8Cse+D2ZUdJNnqOFj15vn3fJYTU36u Co+0G/8cXpq8CS5jaUATR4Fnm2HWlBkZl5alLGCqyvl2geELjjfNoj81JkKp5VbsTbxSJXG2 AqMM8fJ0xZqSf0n2YCFmGGVWX4XHlN2p6QCoUmKKO8ryPIG+Tv2N63nAOHt5bCVS/x8LRw/p UQfbCLtn/9Xc5iHdnWypwM+IJ+wEF3cSJB7SAAGd/hHVekeK0rMRecBp1dEXZxrAobWX9EXR hdP8EUqwmbP9rS3pSM/Ok0kM2NcABDcEdR/Mok7nNuDsa/zX9dC02LeU3/vStmncdPB2GdJ/ fmpb/sc1bcuHTWgR0YNxfSt0H1JNCh8pziEyvqdQtKd5YxcjITKd55NSrG5+CMDHkIFzHOwq UDsunJAbg1b+MMuS2q2LUYKmRIg9du0ODU+oHEGNS7EA9XsHoMrAAzkzgbhpYvxclYn6sQr9 p02Su6poK5nBaTcFukzC4iDohkAA4VfhBuD80YHDF2w2QaSp4YXI//CmqVRtS96QEpTY9MAn lCukMLgfaz+gvZ8MvNliZFMO0NwbLFFCvLx5wTDtmAW6j5La5SN9S+tMS4po9ij/sZcek7SK 4RZi/9PYkeS/11oHJhuIu8GfmJ7EmqqefagCkIjrrLLhSSmoNeujLHrIVGL0yvbaEwQvcLQv TUjqC7b3ZwyXAJ7U6DGv2SkFTFXLzewciLQuMdAEX9GGalIarPiSOBbTFmlXmlnneEGYPky5 N4Q2Lp1bZkrp0avMIYVQzp04K8vQ9ZYKZW5kc3RyZWFtCmVuZG9iago0NjkgMCBvYmogPDwK L0xlbmd0aDEgMTQxMQovTGVuZ3RoMiA1OTEyCi9MZW5ndGgzIDAKL0xlbmd0aCA2ODYwICAg ICAgCi9GaWx0ZXIgL0ZsYXRlRGVjb2RlCj4+CnN0cmVhbQp42o1WdzRc7bfWIowSJXobRPQx o5cgahC91zBmBiPMKKP33olOgkSPFr0lSASJEtEFIXonooZEuZN87ff97v3jrrPWOefd+9l7 v8+793PW4WLXNRBUgKNtEapoFEYQAgJLA5W0DDQNDSFgIBgsAgKDhQFcXIZIjBPiHw+Ayxjh 5o5Eo6T/A6PkhoBisDZlKAYL1UKjgBoeTkCICBAiLg2RkAaDgcJgsNRfQLSbNFAZ6omEA7VA QA00CuEO4FJCu/i4Ie0dMNhKf70CeWC8QIiUlITA73CggjPCDQmDooBaUIwDwhlbEQZ1Ahqg YUgExudfKXjuOGAwLtJCQl5eXiCoszsI7WYvxysA9EJiHID6CHeEmycCDvxFG6gNdUb8TQ4E 4AIaOiDd/3AZoO0wXlA3BBBrcELCECh3bJAHCo5wA2LrAw3UNYE6LgjUH2DNPwACwD+PBwgB Qf5O92f0r0RI1O9gKAyGdnaBonyQKHugHdIJAdRR1QRhvDECQCgK/gsIdXJHY+OhnlCkE9QW C/i9eShQVUEPCMVy/JOhO8wN6YJxB7kjnX6xFPqVBnvQKii4EtrZGYHCuAN+7U8Z6YaAYU/e R+jvFj9Eob1Qfv+s7ZAouN0vKnAPFyEjFNLVA6Gu/CcKawL8Y7NHYIBiYDBYEttYhCsQ4Q1z EPpVxNDHBfHbCfllxvII8HNBuwDtsFQQAUg7BPYB8HOHeiKAGDcPRIDffzr+vQJAIEA4EoYB 2iLskSjAP9mxZoTdH2vsFLghvYEWYOwQQoDgX9ffb1bYOYOjUU4+/8B/N1pIzcRcV0Wd/2/S f7sVFdHeQD9BYTBQUFhEBCgOkQCKS4kDA/6d6O8j+Iv+b6suFPnn9v4joTrKDg2U+oMF9vj+ YuL553jw/KkeXuC/K2ijsWONAPL8owJLsBgYhr1B/t9a+B3yf0ngV5b/hwr+e0+qHk5OvxE8 f0H+FwLqjHTy+RODHWwPDFYkWmisVFD/DTVB/KFtLQQc6eH83151DBQrFgWUPXbgBaVAouJ/ mJHuqkhvBFwXiYE5/B6ev9qBreCERCF00e7IXx8goCDkr6b87cMqEPYQ+5FxxzbttwuBFdi/ q6qgYGj4LyUKi4kDoW5uUB8AGDtqwmJiQD8IVrJwhPfvKQcKgVBoDDYEiGUYALRDuwF+tVZS FChk+MsE+FdamIebG1aAvycAW/Ov9W+1IxDeCBhgehINkwl3rAtvO61RYPISXP0o0iVudHLl wSYKSHDCXQbhvdWmf1jGJJp/LJmeq6w74CD3wgJfCx838hGTSoKE10MpxXbQdSrqCCo8tRjG HVD9HW1p0m9EPMP74C7G5Hj6zKebSj7v1PbYK07MuOSUBqkMItE0QSyn5usbrjqETKwVhVXE OhuTvFK0P0K/6qg5BepJE473dSiDHUOjMkk0XjeNnHFrmJM07XynrmqnspmY7FYkEwsaj7wH wNR9s2UyK5OQ7hh8LfzDof3+3Q7cNwLFsc+41w8Fivu+T2vipwRy3pJ1k9CjfRUL9HibVqKs Ork7KPzyWD1Bx8rFS25onC9cepI0y5HYzitku9hB7Wuib55E2XZfsPiYGs/eU6rR18jRDzac qwRPtePu0Ebmq9+KUpoyiR2y31SLUGht3mE4uXJKXlUVT35g3cBAbHY+kfYes0AO6A021DCu WKfcRQiQXHPD11HuHLO5D7UoZN715x/meTywcX9x8magiqqhhWQbpBXqnbbMPV04IQ3rHvW0 Mv/WWbn2wieyfkhrBMKfXGbquzPSEMTqOSRiFapQxXD56pZsCoWC1fAU7jrDeAHrj/0xDV5E 1Wt2cgoa5EZ041KXIWR7d4+0Z0wNN6DVvBPnqlzhA49PG4HcCxJYZiWAX37tbJQA/pn7NmzK 4qYlI3zuImaTwjQsU9Lm4xDYlKlsBjxBeZKQPe3lOr8N4qT1507e/YxbrFqNv5c/RFtJREbe CKK/dn1tlJrMZ8vQn72m0tsy810DW3uYIF8xeyM38+do/4ZVCimKTnLyPl1pAONwd4zXIJBw IF78JvWRooYSixdgAGYyWq7kk4wanmSwlddhDhabN5ym2lteU8+vmxlT9AqQirPsBywNxN7U ca5/39wxO3zN+ChHl/zshbrVFlo2nQL2xuhYyGpsvBfEwEVvAIKPO7m/17yV1dHxWJQcfLkn wc5aMcAbfVwSKUi1uuBrT+0hIrbXxmEvyugik2KUwuTWFQw7qTsMWs18QVjqhy9GT/yieecc R+heT7q0uTm34Q89KyUtYfJnfoQ5mcUEOk9yJFyQ+Y/K3QeIeF6SEz5sUWBk5dUCkVuddtbr mz0Yu+047/2C6rtVxs9xbaXvNJ7LbV0KForupd2hn7qagZTLDzyIkwvmrvgBmEyaLMPt4HTx rlAk0DN9fUTcF6QQNpGs9hxei5sQY0Lf7lnHwhCJULLegekgjCtO8guLnzQgTyM3NAIqugTk bNCXqvBu011qVkLf82oE5HPJNSXFjvDo0fh6vfcdaSBkUilJtkHI3lqT425p2dWhdntrG3OO fNNleacYUUl0vDtnlpusUD6upV278weHOHI3i8Ex+Nwn1PmND9HUh3X1DYbghHApAb7dCDYm DV2oy16wbOZMARE9njuXqQCh3WZq8PaJXvjByAluCSO6OfQ1aH/94aI+Y95136RO4ewtSOCu 4qDZ0UpdbIO23o00IXbKyvPEww24OuRG4ka8vZc5vvW0roJeqxWJQracsYhd+2Z21ftUzlNV iYTSeaj6LXkjJR/ZqBudTQQH5mnkUrB7mhCTI44HBaUMhNdPIJxbljfkKejiEaw8HS5fOnYO Zkx7GKQu50/fNSxm6cy+yi71ZsjOuSVYOCPKSzQwYvZ9G+SrwMc4cRMvHy/o0bsfU54w042k M10qY6PEIRCrp6HFm7W98oQFdd2C/XmewgRdezb5mYvnS3MOGqqiO3UNxgSuAaTbmXrHlLna is3STz799GYdYb382bjqK0p48V1KS7HA9QGV3J0+woXBAV+ljItFfqsTUbFcb0kL7t3qtxVf ToJ+EtSC3UkP3371d3LpYI5OoffRDv2cEdj52Jcyvd1TmfxyAOaoysYnNFB3NptNpHpuYRHK bRmy4fqg6REPhIrLtuRi0Fo5o3ZLicPzrh7V8WOfXuuSk9ks7n51djDaRnrt+v7txuv6lHo+ SpVqq17p8xxCdPnlhhabMJw2CniyISzeLjQxOIr1qS+oIq9A/a46wYORug7rV88xjYyitffa hd3Z2s6XwjQvlW5USqVubYuCdkurvm7AihQ6b0mNPNVP9oxNnlNp74QT9epShYS10T4tbG4j dxgTv8PSHwhdArsOOlpHMDTKnZ3j9fjTuigIx3IxWqKy9SJVuddNRB+JvdKFcdPQH+E8Zf3B mKMZM7hGswn6XB3oJ41TNW1WehBN2xvBCni9/7mbSSL0/V7oLTDL1GXIi/NdbaUYnjHnorGz Dzg4bx/Xgn0PQvaKRpwzYkc6LRSRtecAwyJQXcsraRrrYvmNBK8nZ2odbJsqWjkS8S2HeVwN exPvFJ3WQJmdE/zNoh0Eg7epv121e74UfjNxB9DI/JnTduDcBPpt8qFOdMvQZjOZZp82XYCV SqZ/2lbRB/+sxyrnrYa6Aw+EJ/myh3es18YoCpTaXLhoamyLhqCX9O9ucdd7el/on4mQVQvc vCZpbUTRvIK6WwsOip4490CpkLJHHtT5jLgseHeqi3EIlthazfh0ym7yFblYzdomTt3Hn6H0 1dKxtXSmFiW3ia4Nm9UUAmOgSq0G4/0Ct0arnzhEPX4hmI7/1fVpoqGZ3FBQz/f5LbRIhAWO 32MG6r3LRcZnPxbhxzy7Nd3ZRBfcLwqG6e/XSRvFHHTaFYfIGW61RBzmZZaRThoX30LPxugc lAg3Etnjsp81Ud7254/zPgtRORwY6qyKBbyhqdcoLTiWCqmMARdNzDR2u+3rWa2ZNvqO+Obk 407pDNNnsfXw5Q125OQmHspxpM2rKcu+EH69YStlJDClEsK++EanglB//wGz1OxGCnVz2wRv b0nQAbv7y3vP/C3A8+f8GUKR7rK1MdNbKotNN/IpTCmfBw+wFqTazcXU4+XEbnJO5cnHm4g/ ERl78Dwhf1erGyEQVkaA+hiRQE8uYEVvwMGwkVJO8ZpwSA4k0sCNd8j0hXDxxt5d/9Y9Spv5 fpkmG8ZmRbmxbPiBkMXR0J5hVAlJwIVl0s5FB/afRvXl4rkbiY0GPofeVaWGp0lmc4zP1LuF 6A8S8vXZlUsyE7NCmNb6QLKauR204PsNhs8rVgYYAXjH1KNZz2WlR084ej017O37j+YdFgLy TJY18jZZimQMhkTOuposea43B8NTogLGKi0VV2jCx78lrftR2KAkV4a44N4HIcL+Avis93Y6 eZde0qrNyHmXrRuRvBEFNfqbi92ysEFKXbDJO4FoSOavjfrRUeeqTbxO1yc/I9kb4E3YCRwW zD0GOAc5h71c2SLnT1GzFh2saMd/XyfgMEXPNOCtAqW9irNweGBt6cptW1H0OqNVNe1ojunR St+Q6CNKjev32Mlm3MpWKnSzbcv0hY9DZbZzKzpbcvmJRdnypvNjJ+YsKCGRQvSO3yt0UTf4 C5d+jE7pmcK0MCSZz/Dlk+2ZhCVEJAAmIsl4WWD71f710h2y04MY+JisinVFtqJoTNrYR/EQ 8x6gEI4bk5kDTvo0/6HW8GrZs557JMpNDCan7rafQGJf7rGFvjIb2xTnNRKcx/8+3CGU0Wz+ mlKbr1BnR8PJkPpY9tqbS+poq9ugEFjfpe1JKYalNZaEtLsuDBpx/wv/I+lyWtWtnVnmFNwV KceQu7rxdyzjbB/zEog3zpdEjqTlpBt3Mlrn+eDhurHeF0k3p3iLOL7yUJcjbPkYz9GiAv8S icPsxEcEsxmtsepPPP2AV0uyKcs+W52dWRAwrvZe+VWFGmtU6jZj3M30ZYFwmecBmPdC87O+ lF8T3NU8OYg1SV3yeVzMvMTCYNN+0C98a/A2if0FkXp+YiAZsckVpOQtxYpyVCAup/f6zcLF cILhUNvnRL1zKtnfXRH+mNMEBYaeVPmRg9SCtNcLzoT9nlzjb6dxWuu+uHHrfL2k1WNrh7Jc ag/l/Nzc8FsYe/3ynCnr+igvM1Whnq2KgDopAShSxN8lR0B0Wd6w8kdk/UCf6PYVU1/8FL7f nBHL8Qu3+2+BRr0O+emB3hepg7uUe3KpFuSfGH3uX0tzJtPPDsl5MszlQx8a6pUo0agbR9Wa zfSYQfOl72gDaT+p9CUm+TPm3Dq707tdfZUkTTK1N7gkOJnEgO4wzCubQKLNY6V2S74/IuTZ bfXl2RX1+Wd+O1xj/J9h3wCbufiSKZeqqhixhJjkiz53vFgSdE7+NUtF5GA5xI9Htf959ylk SQzsWaCW+io89BvZlk0SJZ360qbS5LJMRNip9I4lomjqsvPB64NUTYdTU9Pma3m+fh8QKz+3 C0urDAiefPg4uBtvbH+1L0f8sprMkkDW/F0biQcFybFIb3GUSZ7RxI758U8UoeE2Z552IB9l gEUJc8u+y5fh7lMFBzozxFRzagkiV14zaf3H4otbjrW4cmYtZZSb9LQOQ/v810llcX8WXT1k vCYfGyRePzOVqj70qXt9LsSg79ZYOgfXGluG7n5aJVPW4IX5AW7Y1F3fQidyeEer3UBB5n6Z cK9x+0LAVx2fqQQD6SC3VVjZQqm82tXhzShB6nECpuhEXJGfVNKOy5nQCwIzx+Td1cIioKIN 6zNjjxDVKbvJFxlCMRTwwaD+2kWBk077SGERpRCRd0o9b9ros2gmA9iMP6tN1ER8b5pbAUZv MyYgiV+57VMNzh02F6Yc3m5Gvzz1QM4MbVQ335QQeTLfXjEhHmv2tQl3NUVEBMF8rbs9krUi hXnBwaJ4kIa4S1h8ruVL2kfNyX08M9hZPOioQtBSGL64P7ZU6pW1wCsKIPRIngkTPGew0Le+ bJKg8Z7MO6xbt3iZfPgzbwlBCJmYnO2jVw/ylhkTTJnXTgSZbFsHF7Z9S0M8u7VzGZ0kByNj J/cc7b9jePmMbrzB6fKjUtmGUsQbMF8HkNOzamAXiFJ/Y9xdLDvFkyQyMlevb2KDMlllmPG4 uKEU63GMw7G9zDYzDbjDs1Cu8tyO9NO8TLXDfLoZYrM4sc9jYTVQPzGj5S5uq97O/i5a4pPz YdtnvIRJdzQdT8r8a/yQ2du+hZ+YcNYolp/5WfKZ7ku5Hkbp8vfQeG1xuip8YrHMmfIZpHGu vuKb5LDK3+40FlK8xo94KcckBvXlu69cL3lLjohB4iZOA4PbVX19vp3rhM46FY3KI8trPuI6 N907UnYWpvv9LF2/jX9McVMSNK/1zJPcIN9P5WfSOsHzvJ9w6ix/qODkkV0+n1LBWtuY4ObK o6XXgdO7CVyRzZMmWMKMfiKO4hNUT9Q2ew5IyX5IUBlsQ7DKOWd98L6r9aqaj5554lNYlqDy 1Mj8mM69D7LZRpwEUx8Jonep4FIt9Ul3umzuYswX88him1+bxW8y1K1dSmScFeD0PmkWad+N GBFiU4zNIaino9Jd6cTIBIcPdwXquriL5Q2zs3RhYFxxZ/3hPY36pbURsQXTO5sAe/8ay4x6 n8lSzxdzi7zXDaPmaZAz25x+AqdRBgSv2aWmp4iuEVbmbsp5+SnRNE8z7D2+9nzD0nUQ7vFL DfL1c9l8ewt0TYdZ6Y8YGQyLFfvJTmPbj3e+Yzhp+iAQ5rHK210fLY+Ysukg86Y/BhAAdRc5 SLeDwLflb+Pa8he9kPPHRnwKXRq3tLVLg9uPSPwvGNf1Z10+zTQQQsvrJ5yPJcCM2gwceISA peI2qJLKfefH9x7HdKh2mwMHvSN/0oVPekpuy9R6P6TI9kvYTFlwGOatLXqpiCdYYyujxlfO YN5Qsi7enDMU95FEchb0fEn0IvBSMmtijKWz+y3/F43mRnTUbIT0lVXuw2lBuDbtU8H2j34O Cuqy1QMFMlpq37gspATlnPY1WDzH1Bqf1hTLK8wLMeCsEei+N5mwAF/3z4NSXTTVkEsKe+Bz x+43F0vlJptE5gdOm+nBteXEOiGPv0hd2caQTDsSRWMC01giwCyTX+JCnrqXDN6+QtGJnC8J vGjtEGva1W7N1yAYnWJvKd9Ond9iRNWMjH5TWZ08xaXZrFNo32ZSvY1QTtpvyUj9MuueQjRL VK0GbT/QNhsLX0SEO5O/b0CL5KtGRJ4D8thoD69qmRaPPYZkqq6Yfopy3A+el6rA4618XPl2 c2bDN1oJWLP8EMeVAzOci/KTnyqrZriPS9qcjNM/KRA7iJYkIJB/CmDL4hBUSeV3VGRXP2EU K/9w9w3Lu82PRYitBqmtRcXvdAICMs+8pBHe0HBHg7t6Ti2HbRwcRFtsWcM+wvrARefTz3sm fZR+GZb2XhIV2d2+q0P30OohqrUfH/ANpYBIRKcBk73GX9Zibhg5GaYrsXuNJ6Fp6dXqVms2 O32/9EjmQTJiMvAyWaM0qy67CCzZkyTcPKDPbUwvTjCJI+6SaLXdpYSQ8Uzw4JZoCPHHb2s+ KZrlwJ0gNGfiHUtBiq/J3QRCu/tWi4fV7kE8QlWIFuaknpWv1/0eWTwmWSjUT5yYnx2YEaT2 J1nOfgZvF4o+wpBHfIHfpc1t/r6gbb830slGOtNXQ/zt+sKmfOXQYC3aJJvZC4Dn+i5rRTUu 0LrQQ8S3+87l95ypm6F0pnheA48MikiqSigMioEKvGs3Sw3fDbHIJOMbe5FUJFYTsouYdlmm mAqFdHTGpK/NVEVJ+UmqPgv40TObNCfBRQoJFXvQF+P5LmRJ08bV6EMe9u+yIkxvbVA2l9nr mx5u8PwLwfXX1PQx1zswNhKNgd6SvBe3dzjFxMmj6OC0rPKtHNYVLBxeNAsKAvjtNtXqtUcz xivMYNaHI/gs11XtM0/vRehpKZKgOy7sVuVvE5ekn56pymha3Quqguhasf04mPxA5ujMdfCQ uAWYwj0tAIdqMt+spmTWStsMeDldVavC/6qapH2UbKI02puSskeUO/8dkEtcmCvDlM781aCI WIbI58TUkayoow6fGgsXRcyGTgtlovvGPFhM6+Fyx/qkS7QSbkR7+/Hk5SC904R+pRvLlQUM vFuG0tO4mOo157ac8BnkIlpc4omXHXUQ5+by16uTan91VRyIuuh/RClMAHzfmad/FcpNuy0R XVUU51okG/ZRKLxzGz9vxMHxw73RhVhlRt/oDkWJDrZnpKoKVVWEBQMeR3jfi9lXZ2RQXgum 4Is5r3RVTTweQbjeibBAbtL4cgEcLE3/UPkuQbnTKsMq6ZZhylGYXK4JU1Om4wClr92s79DF eerS5Q9BWjvORHdB5JncQXyQbpDVI0fQjmUhmUGnfPz6ftRjVT7Z1bb3Yzw7nk/va0qlVBNt Iz5rqjFTxEFqcpb9alxxrNrukYaGWh/wJ4IWpQfLg9kvANcP7IiKboqJEQPeK/j2Fb8hPr8h NzFHdmiwApBMicHb4xep10sRHWSwt631w0uqMJjcF1AAuL8b/mFMTPqzTOl75czBMD5h9ws9 M+L7P5/G4c6msMeMezgnd0RArBGYPqE70PiUVJkUKbq8QdQZPyAF//Nxsei5TshAX9tmr4B1 e38b5LscPfFo6sm9GulH78KvyvwOHWyPnrOz1ywRL68/u1DP3bp5PQcyaTmdVIps76GSb1j/ dtj+5jR8Aagp3UTzNInWnd6L3tRhuaZG5PLbKlGnpQHNMZAoVgiE2MfTCm3+0vPSyT5tuZJw ImzQniKOx3HjGU0Iz3qzn+x9mb4g5q6vhDU4AbTDzE3URda8heUoX7I0+5l80xA2Z19N8qCG FcYyvxumsT2NN655xYYJHB3lQOSlReTXVj8YZr63OxL8KpNHiz4rprW1h+nVB5H3B9xmZ2bT 3jgFtKvlDz5nxbMqBvGnfzb+8fOk9+HtQeCkdlvGK6UGs1PcYDzRfJwncfmGJ0Q1ve9Ra7F4 xOC5ipyuGk3tO3kS745+cEIz3rQOdEc2acOpRGJIfmbAN2HUtstGsQrp04EuhPf9n1S13jIg FSx6MBLXWAFnjpOZD7TTeMD5Dt3mf1XjRlVuRfEw6X8A2bQuaQplbmRzdHJlYW0KZW5kb2Jq CjQ3MSAwIG9iaiA8PAovTGVuZ3RoMSAxNDczCi9MZW5ndGgyIDY1MDUKL0xlbmd0aDMgMAov TGVuZ3RoIDc0OTkgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFtCnjajXgH ONtt277a1FZaO9SeCbU3tbeiVNGIhBAJEpvas/beSu1R1KhNzRo1q1bxGK3WXkWV9kvH877v 8/7/x/F9R44j+d3nte7zvs7rTo5wsRveE1K2Q9lC1VFIjBBIGCgDUNW7ZwECAoBAMWEgUJSU i8sEjkFA/8ZJucygbmg4CinzHx6qblAwBovdBWOwjnooJEDbHQEAiQFAEjIgSRkgECAKBEr/ 7YhykwHcBXvA7QB6wgBtFBKKJuVSRbl4u8HtHTDYOn8/AnghfACQtLSk4K9wgLIz1A0OASMB emCMA9QZWxECRgDuoSBwKMb7Hyl45RwwGBcZERFPT09hsDNaGOVmr8AnCPCEYxwAxlA01M0D agf4SRmgD3aG/qEmTMoFMHGAo38b7qFgGE+wGxSABRBwCBSJxoa4I+2gbgBsdcA9LV2AgQsU +dtZ97eDIODP4QBAwqB/pfsT/TMRHPkrGAyBoJxdwEhvONIeAIMjoAADdV1hjBdGEABG2v10 BCPQKGw82AMMR4BtsQ6/tg4GqCsbAcBYhn/4oSFucBcMWhgNR/zkKPIzDfaY1ZB2qihnZygS gyb9ub+7cDcoBHvu3iJ/muuERHkiff9eweBIO9hPGnbuLiKmSLirO1Tr7h8fLET6b8weigGI A6UlJMRBAKgrAOoFcRD5WcDE2wX6y/gLxnLw93VBuQBgWBpQfzgMiv0g9UWDPaAAjJs71N/3 Pw3/XJGCQAA7OAQDsIXaw5Gk/86OhaGw32ts/93gXgBLIFZ+IADw5+tfT1ZYhdmhkAjvf7v/ arGIqrKOspqewB/K/zKqqKC8AL5CotIAIWkJIAAEAkkAJCXFAf7/zPOvE/ib/S/UEAz/s7v/ yKiFhKEA0r9JYE/vbyIef5TB+2ds+AD/rKCPwuoZCuD9t/wfAsWBEOwb6P88BL9C/n/a/5nl f5X/f+9I3R2B+GXn/e3w/9jBznCE9x8PrJ7dMdjZ0ENhJwT53673ob8HWg9qB3d3/m+rFgaM nRFlpD1W50KgO8LAO79xOFod7gW1M4RjIA6/tfR3M7A1EHAk1BCFhv+8d7BRQOB/2bCjB3HC 3i1obMt+maDYyfpnXTUkBGX3cwRFxSUAYDc3sDcpVgHYlTjAF4SdVTuo1y+JA0SEkSgMNgSA 5egPgKHcSH82FoTVkYgtGOKERoDRDj9tv2GgKBZ2A0OgCCgM8x+w2B/4d3f/hYtjYexJQ39D /9ghxN3NDTvEv6SE3f7f6183BhTqBYWQzr9DQWRDHV+Etp/XKjN5Cn14Q7iy2hmVYNEfKY7h nn3q66BLlKUx5aryyK761ki64Vx5+OQ7Pyb+vfMxr4evcoKW0zTzMThq/esqB0IFQ1+PX9lD We1QjPbjkulR69T7iUYslI8s8S15ku+/uwyT7BHbfP6x6KoTvflAehvgDCg5pWJPY8LEKud1 buM+sWDnXMUMWzykiqNxs8xwN9EyHb/CfQKPO1Npj2H46r1uGZc5vLT0OmegP13sqFCnt0ai OpyW4YaPNnveSNIgA11ijvZLNA63ivipanlqAgdDsXM49zLeI8nlb9OFA22Jg2Lujfb6qkHX DR6PNrnXo8Tfyef1LB8x22xkm3wVIb/VnBTlIFibzqnCVWOHczqcsV8jhsjvxadnBRDWdy7+ 0JtGlZadWejiLjTFED0OEbP+OHHr/FFsViJI1CpVHiE1+NczFQlDBKvLCOz+wqVcKoCWkYvW UAtPn91x1X3ktqDwl2f98EpztmTkyafm1+3DPREHKM49FrqpoATzjqztvq3El1rip2+pzfjV JDB1OrOoLhu++Lz46QDj/Dx8w7ZODdkHStJzExzxZmKUBSbUsya6mzgZ+iQWMmHKgdNUFLRO e+UszxeqJEafygc3y6dKBQIfL04cXLtrtBNPVbd+3ajnK4F1gq3bgYgosbVOfucDh0el+jza mDsJ8KbthMtPKhZTQQeS75bzVb6bBtjQlj1+mA+L/Rb3ZfOkcT/fXLk+8gEiKqVrKmDd5tko S8eDgTjmjO6Jnd4OntRNL83Gi1P8A1rbYQ2ZQY7QYkRlU7x4q+rSAF2UqeUAWLf9pJnYrWcU 1nTylQxkeSZ7ZyPIxfpTo/6+y7cKV5W7ABpKnrkwabH1ar1AbmlffLJIs4C75F+kaMjBE43B ou+QwjgOsCbSDYSizgJ94bYl55PmaOr6Cw2Xg9Ne5iXa1jpmEe1BH8gZXnGwutQ3D0Ox93+J mBtIvPZWRnXV7T3e3rS678p0N1ivhTDS4s5K6XF4M3WhRfzMaKG5odqB7pXouo1oy/XqlnKU ZqovKeim1xTDjaEtnq52dwa/NhT5+enFfX02FuMstZSjkt3Mlvhp3JNv3CnrGQg29R/0DwN0 qXGNHUDPWdXzbA9Lqsf9BSIQ5KrnVoCS4sUeXuJQZg/YDCpEADZ+K0dve5et3v8MocgM4V+O 5Nirtg4wrvpoVeEcvkH1Fl4aqlNhMDQVx651PebF9Itvm7e+GFN/t8FM35fN7Bo9zBh0V+K9 XYHhHy2lnb5u+jTH12/9yxcjf7DYB/UyBF5q57GUF34VE1HRFCZJ875yWU/1mmw9+4LZ8sR3 ctXW4RshZqj69EWP1rydJMWe+hQ22ZScOvmR9wqCoQPrpZWdDzkqvzalZt2cNN4l8DBWTZ0r xs8xuutAykAxrWQjmDdIP5JD2eFEQx9rC0NsKmudG1rjVtRnes5n0ZbYaQ1p+jjxQs7EQry+ JbBGDwXt3Bs2NdSqh/nqjJW/QTOGke29sahpL9gV2fF4FT9uWdDybY61WZfLoEBpO1MzJDyZ Rm7ZkCdO+9nIYoBH4ozgAGcDh4NpqZ7iSf224mqyC/+7UEkPitmb8ouGILT/ugZlslKRfpK4 9YFYapTJh3opWGs4gNHbqCQipMWAL7SBvAooOf1xiosijCRUg6zoIsnY5xnt8THss2/EhDX1 XYf3J3Ibhb6ZmWsqqSNb7/wvugfm89CiMB7VY+/ltVqbwefTz5WsIKxSyXVIRklXnhCGj9d0 Ii/vOBnI39z9Xqn0zhSQVPYeIbhkiFJ7snzzoxPu20x+CkliVzzLBXbCnbOLl2Nzn6YfotqC rWc5X3LHfDg+sqKWQqTGb7xEt3CHhr4SSVhbs+bLYjf50BcIJj/GXa3am5+oX6UP6rjHUSAb /yn10t0a514UqbL4UaaEijz1YqEHcjHTZJ24OjO+brydI2zyrJzWSoTwjVCAv2/k5MCQUv50 msAT5iw4xbWrcgh4zAU5tLjeMP3XjG8FuX55MM6+Axf6a8XngzwATsvsqn4RffDGhyqzhY2x wZAucHmW1cknxRlBMtzdI1tMASI5w4FKIvGHQaRHj00pofHn0XrphHsAazzDXXYjlzOSVwlM Zy1uEmftr2SL6x+kfeoa2PCYY5V2IvOmjqNv1EzydpFlvDs0uw5IdmTYBeVMyBwYh1pVLWXb +mioKnJwBftBl4o92T/Vpb2RiB0pNjb8xPnxZYvMj463fEMdcWq35z4V2/FU9X7oYhJqaSJ7 LYojwtQP4DqM84+Y72KKmXt/k8x5JKzmwSVjX6EuhdR498l8LGTkuHEcdWMetyo6W1ez+G2r zvuT46Y8vowvRK55ArOLEAvv1P43bcX52ddIaW30RmOuHgkp1RMBacwIr5h4TnLG6yZOyzH3 yoaKKO0Ul+rM6fBpeUMsQsL6zpz07zdadO+qz8l9UvGvT/vsVL/YS7RivMu7MDNuLTrHRQXE Vb682nEObcOJGaP8jPBzDkFNv94pv8Ng9KGVrjq0wDuX1i85fsGDjWZf4HFCUT5rX4paIyTu 7Yt5vCS9ge1ZkepTFvptzFwY3qUmNCt83lC14bOH/t4mh4aEP1nJDvkeUX6eVSOoQPlmQndM ioDfZi3vRovZzOFKtEZZFUIyWAfGdP+Gz7Jbvs2u/DcNDl+eijsj4eZ6gBLerlu9qXXh+ww+ Iu/rm+Z9pnR7H4T6tUTdvcY6cEeI8usqUG3XpSma8cG9i+Zj5cHViCriyPrXqwxzzcobKS2v OjCIzroxzasCSxyTIC/0mF4hS5hhFH/DUyi0PL4EVtKJ4+m0EHGL9VwTxCdJXBYP54id6N0P 5gSyzH0PaqjsNVOEd9HQRPkcb0oN9Pt1FSvY/XD0NsmKDeptNHMe/Ji+yuBaOmqvOsyQeJy4 P9fdmnVN2oeg7YNJpOpygEgf5nFrYn9GOEEpioV/N106ZsBtfEbrSQHKscZ0V+eU1suxoFWY RJDwzbmALaj23YtDsl6tbMRd3X2jB3hiQWdNhkJI1En7UQeP3IRFxwohVGgHJHJOEZMvGRTD ryZ+O90u4rAIFZfma6VaocD5HU+dxMeefSKS/xmqFWeawDH6rZD+t6DdN8VvqlFHUvH9Op5G 9kuxLjn8IGtaimDhd9GRuWM923VkumZRj09e/7g8dya/gQCPkVtx3dgR5ih5lNBWbvPc6CWc OYBxw6X7tD+OdZiICJ2EK+4tbB4Sj8c89eY53+FH5kKTgl2cklM7kE5+oVNl5Wi041JAZSEx ExLoc7NC4znLKptr1Mv4bXD5faPPXD6h07e0X7TMmRcxFvaIYbS8gX2dz4Txp29H9Vsm3y5i Cbl7W+1tcJKLS406f2XZl7rlDI99N4NpuzGkJPJ6EfUUHkw6hL+Gacdc5kvnpsJge5YM/5tl XRYY7ptYul7pJG5wkqOsAIsvXRswgoRvYkE5yb63Vod/K8hcpwd30ayJx2f+wfGoMssCHwly 73T8ev2MSXsKdW9mwqLu2AqF9vb+0Wfru/CyK8uSAxm0XO77ZtEe9sMby6YRF37ZOGm3Cb+K m4VuwyZNo7dcDYP8zy6n/OR/xGRhf8/0iBv4GfYSfkJnSR+Wssb5b3xI5idlEbB3UQ4UrBV8 Je/nWCkqTq06FCyZ/WWGLGk/raYxfY6ZKkD4s4h6GRPTUMsIsDANY5yz2hqNK8zB7Aklc2Bk 6KIwDHwK3Xjn7HK0px2BalCqrVtLC/phc7ClPBUgVrpmRPe5S4XV7OQx54G0WmErfYKjPOkT K0VA5adcX0+CGhtKcbGzYvU9++mu+ju5KpmfNrJ3lMsqaVY7XF+MH4xQsq10L0/eaSSKZo0o SpjYAz03hN16S1J1LPjuXn++xMl6OwHzU7eiUsvEpVcej/4ia2+s+xZ786QrwOtMg/NHPlNo 8da4sH9By9j10ZSXZTffj3eqv8lMgdTWZSUGy9+qfgVjv3mNjX+ko0KYUGTTk7AvyliqlVdp fv5Jlg85pLlDqVefW8s5PW/pmYI5+2vnVOjhsNIYgp7i/g+OKTNVzU/nuVJvnW7OJBLIeZ/n 6LuTg1OItorLOvqFSwb2cTH6DcV9kQjRF1TNTspaVhF8N/XOKQOa7hV+/GGRNo9sZAyOJSTM jJ/hLuO3jmMZTOS5hCjhUK7duuR+OeQntzLWX5R+1sk6ybhbS/Nja75CIAVCUR3YJFfw2JvH eQctl2n6OUjahd2mE7fUqH3hywZPiX62RsP+KkGGAgVuf9mbbkerBhrksZi5gnaBj+L83d1A ef3zsGsdtkhyllhf15u2FrwKHPNS/J+edA69cSrzFjtHrUWf47wHBB5Haa73kMff9VxrObcq CiTrYEqg27Z76quWRDdc3PvEM2ieYTWTWpiTzmx104ERk3Pq48Tp5MRpdWe7hg7/AAJrLrio oWpTxb+fpnQ0cvxNLPc03YUNYVTzNNnoY2YUvu1qGZ2Iy/G1xuOnzCbJrp3qk1L4Nt9nlKmT upDbtEZviX4UOuvE+XL7yMrNdOURBjkfrVvCJUfH6Ru2c54d8vDTX7maB5pcQx5h5JhmYpyO RIgVy0WdGfjyRsZhJy01u6mra4Xn3rd512secS34VjBRlbK3G7HmiAC50SteLSewTZVKgaoZ tyf7aiv7lpjJBXsDHeZYo2ecF5wv5G8w/hU8m6O4ZackBuGjshKrYEyj2JphnsHh4tfz12Tu Zcz8XJwnq2r3bDWDYMjNpYOhFnTD8SpfnZqRqisSEoZmwaTuavCcrak+TGt14cOv5jsl/J5j w5ZFXchXN8PbcpFd3HhdT6+VtLE+lNx1wIO7qWb4THXlg5g+TpPuA3S9p4mhu28iPbq9dbz2 3DDviYBQbnV5gemT9Dr1L6bnhhxtOmPh4QKV7VMWnVBJWkVgJW/qKTHcjokpS7dB1t6JSPoV Da+FllBCDOLR8y97so9m6DY/Kk8Qa8o0PH+6aqHJYgtKblxr0xz0bfYMGTS2tpjMYqAQJH3K qV72Nk3z7vyRGaOiyxGR92R6yw3DZS51+bbgnsEBlQjC0/nTAg2dOUOH+sf6DZbN+FrDNluR garEByb0PstTMJJNErnptJSYy6Brj+5gv5XVQO+0edqvVpc4H/kbkxBSBhMtBDwsC6Re0xd1 ghWCj1Hu2pJiuQFUWw1HHqtbXScBOov3fXP0ppfFFGfjY8v1jqy+ytxnkL1B7cGWEEaVQWC+ JksQqsKWRBJVak4bL2y4qiWrmM9uUhQJEL7+Ek2/g3dqarXxPCRJftI8+vv1qyTxhu7oQLdA PYyCt3xNOP96kK0qXudja/IOTD+TsltdAYKn6by/JPXy+NrDk7O5/CFm3SDc7ZACw2RuSQyG EvfUXcNHVsf+zsLxZCyr7Et3Po7P9bIX7++lpvV4dIwcXH5RfVyv2KUd0iaSpM4hYSpcC1TY JMQ9EXivYzQdCmTgGJ6unJTfDjpEf17eDfFCaVutzlawj3peShgsCfs/yQvEbI8EiFMfFJqt jZTXC1RRF7+squ6+ZJGMrjdFB2c9f1c+4L35YbgvmcgkP0ZV/FLDzX7NlLCPSnyUMz4iPYbb rza+sSua+HHqkkbFxpxUXvoWeUENoZ7HhxVex5uY0pD1FQD54Xgh8nA322rMqt8Id/T+rTCD uUTGSGcK4ZhncdUHJMaWnTcnMlD6co63PxJ/5wne7GsHVdPOUXTL+rNRHoQ91AvIhbzjlZmD xtcpnoaFr9M+yLzDqhNpH4Ff3v+pqKd8k5JWKSbHpCoFMMMDPuXgGtDxe2Sk4/9X4ev1I/e7 4TnJURT+x9yBV31S0sJX70rbNm0ZPVQgAgFqXQKKZEPiJZHcCOkT8xZDhQmk/QmJlvqmjGIP JmUugfCeqcEYZIDCUVTV2bL4r0oDSYUgp/sXTsWF5R24I+Y1PCEv9lhK6HMo6XrkTEtfzOov Sumi7BwX0bMUYlQRCmSZt5kYD9MmMTzmqXZ00gJqknUH+huExJl2MVK+/VZHMc4tuSIRDNcH Dqny2mbj6IrtGD0YnljghhNapJ1+Z/NEudCefM5kz1TrM8yVVFdE3RrvczSklF47qubIfmWf rBKdGzPWP2+4F3ciq2JtFG9Qniz2tYtf5bpYfYg7sg2P8+WK1gDF1o98GwNC6PdHb0nZMji7 Vx4F+wtJ0xmJ9BV/0KuHBuYpzr0aHNqaqm28xkq147CBZxVdYnvQRXL1uW2r0mZLVG7y/E3a gAA+1Q6Guaei1nI8py6SQbvge7mBUhGXXqJW8PJnckxJ45wHYUj4zEPGFhHb9cneIz0zdbph oPiPMQEnrQ+i96UVYGn+5S8BVBPnfU0nYpiIpsofrQWOFeElvX4cpQ0fT/YS3pHmDw5Z0k3r Rjvk48ZZ0NDV882hxCWd6Fa+J9/mCiDSTHqII1jlNeZ3gq5Be+0Wa+bJqetQr29EzBG82XUo vd7yQGLiVhiOs+DypMM9ofsPaOIp8Ma0b/G8rD0bli/beO+p/yG3HoyokIniPDcQXzHcCPXs tZmIUgNGs+ssi0VNjHBYf5j8au/6XRpYB1Mb4JV14ZD/PgyDzApnO2mgd2dUR7aD1qNJDL4e bj+iGSYudUnK8G1eKdOSuKmapnOliifiWZvrfIOo8v3wvbecz42+sU6q6p4UHic203tleJL8 1VnCEqbevJxNwE3+mCN0Qy1Z4U24X5PsI3zKfjKPb1znbAs1Jpa7kHeEVvvBUNxoDo10U0bH 2JVKwlDv6AOMh9eMjLudUSK9+wNvmxsvTOw4kiue2QpsvjIIt5pD1Hj9xSPhebQuYf5Clarr rg6rARHDqwhYNq+9kqcVrMQsc6THcivg8XYMSP3rZ1ZrSmUxjyqSwTWDbI+pGuYm0WseZKQ+ Fx9MmpcvRoDzSzdsb59mX7PM9vEeT5rhxIeCqhadZsTT7YyVdx7x9ocp+SbIE3jfV+g6iNxQ uEis2fRW+tj/o8V09YL4118KvZqygxDftAM5bxVbyXIEO7dXfOsBgVJ5xNv9VGIhuwL8xQ73 ja2HOD1vcD9yZASc8bjvDfvRsSssin0DNsTe7G1/Zj3zPOUW30ymkO9Lg/iWWoN3F6JUxmU9 DZRerz9tE7NFGvUTn3iq2E8krrVf3btqy8vmmK1AZNsenPrIttRlaHnPPFSbJXg1shXl4lbm pEf2UolQqQfK3f1ULDUD0Tschbl39rGPiyVol++TiIvx4PnyfHcFxy3RRnfSDDVokvi5QN98 Lbr0wREPI/GNupbSLxl/bdpGGr1gPDmovYegyXfsPwUkMDD6EHkw4FAtB6495hKm1fF5qH+j IDp083L9jF5ti0hwHWomOkUtr3cTRct3QyhIGzJo9leRzBSj6bzoZLPCEChy9nUyB2WX0f3W pyEGV18mE+/wG/h8axWGNB87QlIqLbgvV97PzY3Txu9syW9L0qRY3MpsOD1/fbAlqCyOHNZa UY9OFclRvByNzlwltwKjhRv0RX5Q56T6Sc4lIvQvquy3/dbVDaVY0+Y1HpsAidtJuK8ds3QW cXkapcdZXs+ZdD6sncb/uvOxnLonWcAYtdBkJHvBdjv/yojHZzaAXm1/3JfrThTRdRuNy7Ec BfT7j7kPdD0UegrcuCVvTXe/eJ/+hQJPh+IZWHiOqkeEgQ4nesGbJhhPpEO8hmocOf/DNXDN c9C17bU2kCilZG/EqmBufMa6WZgs7GkUd96Sg9jJmuINYsjMqu7DJ9RRD7o3c66zM2vtbMY3 vHiurrPzJfzhEij45RQDijtIflbIxzNAbCJ2acmqA2+oRpiyEvmN/NDlFQHpNJ5HFAIWwfew KbpUxuzFqJF54StUStZZAODODNuzG/PU0WbHgfyvqMRN3RwcvC93SXe1iG+a7u1bEZ9nG8fd GVNr/hq8+tQBbv/cQfC6xjOKDEXAi6+r46BcuY9fN4yY7d9+b1h6wSA5n3DbNTayYY++aLL5 diPGXh1onEPr9o6H1xsmv/xU12LZmou4li26i3bz68oVf1lpzo6t1CZ815vhdQ0BM7uADQ8N oYNgWwWBekuSnkLl7LgG9ObjOyOcTJrdlE/waDgy+hrZnqfXnn39QdITSmvvi7eGepzFFpU3 Q6eFKTILXJKK2uOtTlPH9ACuO+a2Lr8PQ11SXzJHf4j6thh2V19Jbf2ZJaGrSdtcWT+lrOmj tixVr4TqrTyHYTCLzVoV7sxorOrRF9weBnBWAa6XLDKbnWVBF6/L53OWghZ3+3HknObKk6BR 4RC7cNjD3fbjCOEF18P6uROQ+crAB9i5vEtzXGcuEqctgoF3o72ZNBraBXo0PoXwJ6BzipmV N2zuZLAynDmQ3JlO1eoW17E1k9e78PB/Xg2IKaCpvwSK1zmEvT7pvu24OccuRSykLxQmZhIi mCsskRFtP/oCVa7ofFtz6XUKydMki9Y5a123B3nok+tljud9bygyV12F5xHOEj2fLGyY6PRy PV0Z5PgVmoVb99JTO/rw8a76mwZIhtRPmxQ55w39dICRVv2Hpd1UXKghPtghS/FlpbqstS5F c+iP4LgEIsmlOzcsxzjx4taFtLPANBr85uPdjhKDvFeS2Vy2FKBZRhv/Cly2YUN4kTcT6qmI Wg9HoqDQZLHhgXYKHRuY2MjC9xhQpc9lT4Yz9p3CvEzmcdf9ESuEmpzqZJnnmUSMlVAjbiK+ tEwrK7R0eLFWg0kgh7JT4ik5uU1trKQxKZCNtS04V3tVt2nlfwBprXvOCmVuZHN0cmVhbQpl bmRvYmoKNDczIDAgb2JqIDw8Ci9MZW5ndGgxIDI2ODgKL0xlbmd0aDIgMTg2MjkKL0xlbmd0 aDMgMAovTGVuZ3RoIDIwMTYwICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUKPj4Kc3RyZWFt CnjajPcFUBza0gUKI8HdIdhAcHd3DU6Q4M7g7u7uGiBAkODu7g7B3d0hSHB/c8499yT3+/+q 94oqmNXdu1fr3gM5iaIyvbCxrSFQwtbGiZ6ZgYkHICqnosLMBGBiYmVgYmKBJydXMXeyAv5X Dk/+GejgaG5rw/OHhagD0MAJJBMzcAIZytnaAKSdrQDMrABmDh5mTh4mJgALExP3fw1tHXgA YgYu5sYAOQaAtK0N0BGeXNTWzt3B3NTMCcTz348AKiNqADM3Nyfd38cBwtZAB3MjAxuAnIGT GdAaxGhkYAVQtjUyBzq5/48LKj4zJyc7HkZGV1dXBgNrRwZbB1MBajqAq7mTGUAJ6Ah0cAEa A/5KGSBvYA38JzUGeHKAipm5438UyrYmTq4GDkAASGBlbgS0cQQdcbYxBjoAQOwAZSlZgIId 0OY/xrL/MaAD/FMcADMD87/u/jn9lyNzm78PGxgZ2VrbGdi4m9uYAkzMrYAABQlZBic3JzqA gY3xX4YGVo62oPMGLgbmVgaGIIO/QzcASAh/AhiAMvwnP0cjB3M7J0cGR3Orv3Jk/MsNqMzi NsaittbWQBsnR/i/4hMzdwAageruzvhPcy1tbF1tPP+LTMxtjE3+SsPY2Y5R1cbc3hkoJfaP DUgE/1tmCnQCsDMxMXGxsgCA9gCgm5EZ418EKu52wL+VzH+JQTl4e9rZ2gFMQGkAvc1NgKA/ 8J6OBi5AgJODM9Db80/F/yJ4ZmaAsbmRE8AQaGpuA//bO0gMNPkPBvXfwdwNoMUEGj9mANNf P/9+0gFNmLGtjZX7b/O/W8yorCr9SVOY9p+U/1WKiNi6ATzp2QD0LKysAHZWTgAHNwfA+3+9 /Jv/f3P/W6poYP5PbH/4k7IxsQVw/ycFUO3+m4bLP3NB9c/SUAP+l0HeFjTNQADV7+HXZmJn MgL9Yv7/vAJ/H/n/N/l/efl/Hf7/G5GEs5XV33qq/xj8/+gNrM2t3P+xAE2zsxNoM+RsQfth 839N1YD/WWc5oLG5s/X/1Uo5GYA2RNjG1OrfQpo7Spi7AY0VzZ2MzP6emP+2AeTdytwGqGjr aP7XfQOgZ2Zi+j860MoZWYLuFEdQs/5WAUEb9b+M4jZGtsZ/rR4LOwfAwMHBwB2eCTRfLOzs AE9m0I4aA93+Hm0AI4ONrRPoCACUnTfAxNYB/q+WcrADGIX/Ev0HcQAYRX4jTgCj6G/EBWAU +424AYzi/yJOJgCjxG/EDGCU/I1YAIwffyNWAKPUbwTik/2NQHxyvxGIT/43AvEp/Iu4QHyK vxGIQek3AjEo/0ZsAEaV3wiUrepvBGL//BuB+NR/IxCfxr+IGxSZwW8EsjT8jUDshgZGlo5W Bo5m/0qZWdj+Ejv8IQDFZehgYAS0Apo4/SFm/0f8n0351yvzf8SWQKf/sedm/Vf+fw6AAjb6 F7GDQjSytQJN1X8lbGx/Saytf6fx17gxGv8BQZTA3x5AxQH+DwPHX3p7Z9CO/lcCumQYQbNl ZWD9hxdQOUx+ewFZmJi7/OH2L7Wt8x91YQKZmP4mAelN/3pYgX+agGL/XVo2UMXM3O3MgDZ/ WIBk5n9AUPAWf0BQ+yz/gKDiWP0BQZX7IwHQhcr42zM76KgNaBP/0IPKYPs7GNBh2/9RgxKw +60GObMDPbw2/9NENuZ/pP/bQtB9zWgHdAA9sH+YcvwtM7f93Sg2UMHsrJwd/+AESex/l/Av 5Ax0/PtS+dc3219CWyegseEf/eP+R/i/cTAzg4z/KD8zqLi/2dhBhxyB1ub/O17sf9kAXf7o CTvIiSPoZfs3bFB2/2dHmEHJ/aYFvQ6MTmYOwD+GBVQ9J1fbPw6AfDj/HnkQ599fYhyNbB3+ bAGovy5/QFDArn8sHMip2x8QxOr+O0jQUQ+gw38o/+eiNXJ2ADXM6e+3EHQL/xf//YUHCHQD GsEvzdsa8QZZ1AS13VcJ47vS743zz5DvqaVS03suObQ7PyLDJFNXZgRsONwKJw/3oK7uiFPd CC0Tv3ieNNfBhLYkfmp98nrWi1ea2muFX5zEHpjIOxGu7SeEI6BXEdr3erH3+uxvCdkM3ilN nm3vzIWsmItx79on6VbbX7IyGjK/92m/kkMG4blkmj5aNUrbv3CWPMcwcw6XFNqJnhCWBv3C DWX25nYGPWvijVg6nhbe+zSaNd9Tc5Ml5mHOY61MhcWxC48MTxOXEPIGfXSKwlPk8Is0zoJn UUHUBv/CNyZqBrCN0X5irx+dJD95tGSl0HGYrByWuCVHybxbaxn91XsR4TL2lPXtaGrsTpAX cGlNXF0lJHMVmgr6dPeHQuHuwhxojeVcYmHk3T33t5be3Wic3Mic/KyZ0PIY0TLZhoPfxlpt FFkTewm198aUgya43ufq8sqzSC8mq/bstZg4tZtx23dTbh8oFT9zRoaHyUtOQ0HFyPvawEk+ HH9TjcGmDVfJ3WoIBqfdTa01jLcsobrCYH+5/8r2M2dUM5VL5snD1ZWg3t0qaaJAit0QvZHY wij+pyZWGQRyWgRdImdW3vxwiUw1z/0HIekV4wqhqVaJU/AxudCDu269kpwnY7QPprQ1jyf8 jYcCJxHvZjUzQw18mxpT1Agi5G8wIz6yazAu7/Bp1gzkHeblhPYngmPji4/la/0Yp8iOlkLo YTucu7tFitqF/oKCa2ZnadIYJq9VnkGOLfI8PPKrUqJH0FQpTaa4Vid8LI5PeUYxoKnrDSW2 LJ//pmRba5SgN3FJp+qDT+qo5ky35qL7iNtQZVRNaPWgvxqFmFb8zBFYOgV6/V7LHC8pN0Fr sKL3g3dH/EZn75TBzbwFg97LeHT28o+PxPVrNvvRusf3A66xwzNyjTM0btZNc9j7GhUpmKMC p6tIDA57GGVxdiaeTGJdXhxCpQdZR5m8OseMlR1mXhOTDPeFSsLv1oerZGYhrTOsbnVXKdRW /XAi1wY9iRpzL16sJfrer52XEmbWpXTiL8+lDbPGScj4SGGH5HMKYatwCq/KPSkoIkcw8Mas xUV9HKE1D1Gv/sbrXZNw/w1z36JfQ/1GfMG5lLjtO/tgq91KnIhUW8FWToQyAPu5OJvT7lN7 NBuTEfjHtNk5tgtnrVMkV4323i9fv+1lsrRpOU1OD498Wf4eVZchaHadFtFkmLH1SrNECEHm B288kK8fQQZQDEYMTg/n8UclDci+LKaOKfZSnTofKD6JMsGBfijFEKvPc7pHnTVO6SnM5i9L z2Afu2rzpcVvyDuz4OwmPzEXekvB3sYYQqPGA58K+6HCCDZpH/ZedXVS4qj6Lq6ZOclJfCJg unEtVwhpKtcPhxmv93uNhK6S4Bf6zOTMXz0F9thBMLoZJE9REDTMpq53ByxdOWyMBdlZTayd QqXb2lWcHisGHsdTzARH1OGNDJtpF1f+keJuARqULUMld8fsYRJGvvw2Fh0s2+1z0PNGmIdx rsyI0c/3o4esfoZZUjqhGRHd7k01PDGju0gm8znFq8eRiXvHlwVPRSamp+SddjlPfOaXxApE VJSexbFzNT+QXUtflfeVgemUXGJvlz+m8LdrWSbGu/a9ie4kyv1E5opsZ6Jb4n9i6L4L7E45 0yzIgkY4WXqjTI4rD0EGV/CckkgN7zXYSlcb8n+6n+BlX8vIU7QWnh2izf68MOKxNvI9Id0I mzgUV59VVwUZPkvRBZ7ifVXVTvdxWbzOnZJSeolovug73Ur2F+4P18I/t2gFB0VOyA5WB6mP hRJqeAqp1Cj36SBDwV5F+iVLEPHoHRJGVXJCkuewNcz93qEEidBZZkIWHVCg+o6XipOmO1+2 LmlsPhbrnwugTenqE4HVUSWXz1BCW6c9EiLIUKLIbM8gUQpkoWWIbyrK0/HIHXpGKLNKsigh C3FoZ20K0l/M6WKrR1P6rRze+EpgM9ibpfZC3WngZ/16sgowKClyHV2Sr1C1GyvULy+/3v4q x10NvauHKW06behKsp2CONrm2Oc/ojKdBFYu1gVpGDDMo2ZPouNrPpDj2pqo/3aYV/wOJopy r0d/00wXugdRRSVWqtTmYzjQarchF619LOFXzF1vtj762u38jn+q3+3CGoCyiMgubAOZiv9d qQZz8/5taXi2audUWRHjqcIjlAo8uT7FKYFnEBWuTD8Pg+ip+ZgMd26n28d+egyXbfHnWTY3 PXaisL3Y7KWW54ivfXTX3wqNt63YKQ1/GK7Z0335eMsAUEisOuTq34KTl7e50+yT/AUFY+88 RtQ4WD0vlwTRcd1t+nQ0a8wICcEAY/vTh6av/Qv6VksHykgnENPu/kc9PPNZjbctip8M2CnV l3NP4feTjnI7hPqCADTEb/U/vPFQvdB/ZaCDoRfpTi8XUj0tM3e6ZMmBqz8vClvEkXx+dxVo yc5/PECRrpFzak605HoV8sMLpwg3M8RFtDJSEeixI/Guej36SF8icFsaRoGkq/TVYyBnsPe7 OAM113fhDCd92pRx2+Ol4yTYinIkv0APTP19Eq9X33IDmoox4wNVhLh3MNQMTlIEZvbxC69h RDRMkNn2Z34t1X6VAgdB8liDqnD9rAPEQ7GbnCh9ftwKTg1arF7RF+wOTJBXzXYDi69Pi1ww G8lqqQT2YrL97W0xnqs/9WswE4eMXZPwvRaCkCSl3zwYGzMOP1J2aJIFhS+BpS3KjedxRedt xsQOaKKOhsWA58HycW54VsraraP13n2mJsdA3zq0HFllDQw6TVOxzXsWtfFmE2jUfHMYqvJs dcDpVtV84xYvyZqflazYco5n414W2NS3xbPvGGMMyNvyOUJ22/4SqxzslWHCTbxQJtilfsng PCTiZiJpKP7M4KrG+xScZkvXBYeTLyJraSlT7wnDbQJravpMB2515FVK0YbvN42LLDdkQPN9 luw2nLDT5cNqg8App+qp0ZHvWG8DTCkYZSMEZqhNkzzKZNo4c9TXgwK19YHSV5iipbfPq4jF qfLO0LTcb8sobJxoke6SKFRTPa8bG0hF/kg9XRGk5R4j28i2Cj16SV5lRpqvBB4iefuBQo2a fsLEax0Pm0IG34FuX/bwDQXjDgRIx7GSwd+GYTS6gs/PMuZxwo9UCkxF6qzeYSxFc6u+SBxL VwqSomvZ6fQgLEON2I2bRS12Z493JRRdhqhCcPlNzCV65Bysd8iGCNb6PUIk4jzzEMlE8lbc POaovZGPqicF3bwjWwzlwTEc5rbbqZPQNf4qMk40L61EBc6hRa9C85ONJCN6yl0DTJ9Srv6F ChKhHLby54gcRqmi8IcBk3g/FVITgijSd4LAu5RX9UKKBKWOPvHBEwSdIhZZv+OQPjCOd4iX gmbUXBSjWIwiBqgmgbdfEklwWpjC6i+cUBvl+PojIdWZwD3amTfIOMiwGr2f/NX4Npgt9sy3 OTkOXsg62KqB4FV1tYCDYtk9OpfxHBXnT4e2zTxrv/gvvQnrxet+FFHtKI/8GGNiSOysjGFe p0YwfsKODPxwNSIFPcbb6qeog4PePlx/2YytBN75mvx8mNwiBUmXRDokmJ6Z6H+7YyiSNTE+ 9LzA5bW6IjnxbX3tXJu35SMivM3AFrQRS9hGpRux+jg0ZjYziSDPJtYWWvOXPVRspw9EvZvY guTNU3fJpkERyp1ALY+vWcAxsGBvwMiGGXXKo9gpIqQF/WMwbFDfqUIQh8uNh3NenJBhIFxk P5y5W53RwJq+wwo6hUPXAQESstTpMTR6LF7scrOeABqsPxKz8rGyMdQ1GO6eBtlZsD51Xk/5 zVQf7gIPVAT2WWcymg7CvRK6zqSEVIWKpdtFuoWp4bePicawDFQ88N3b56UZBAxRkxAp5Hl2 9p0l1wLYvmUCukcebnTLnroJY0Y6DunbHLYVjSH1zTc5Q+tlTh8TVVZFXyYWAMkKvJP22/46 XA9kmO5NjSJhtrIOSH6e/CZdDWVklACJ+35vmptA8geaSGT0x5JHJ2PHXOx0UXB5D6OG1q+F TwHskj5jvos9Td+AgGOWSMJZ41ICdPCIHR1DRw/KziGevQkDNeG6kjQBNlxa+BeIAnbnDX5p IpVfj+WJH8OwwLmKNLYasW2aMCYnPJ+r6f1R2u4fYb85vU17Kz6fJjn1YeUWSrvVJnMtDM0o EaxsMeBoe47oO6+9aWGF4RPXF16THzWzdofFPgdz9mjPOdgEhMhLE9cfv0ZO/Ep7yZYotyyr QaiF+tWhYNGZ0v6+YmN5n7YORg34fm7SsVhu7nNKJHXJfeqXq+5NmBLpS43Plz/SuepOu5i7 X6CNP0jLMmMLYsjVDQlikPanGxaOfupGJjjvaDYxapycyXKoa69E4DO18ok+T4ln16iUmeD3 V9671DkxhhcKy/PTg2Gf++i4GfB0s4o1cMz4a7slctTyM8Ga877prm/SS07k/BmqNyWbVfJk 0p7QQ2WnnoLURjMnXvoEo2ec7jsPd3pjhzFcNyQT/Jz2UeJHdE7pjan5y/ughZmuuzrlzOId yqz3+B6eeM0nhvX5M0aWioawPgP+YIvwTDnVPb33BWMe+DtSM+UkQUgqgU2RSiVkM3T5RAFF p4zZhyJgeafb/hTiqdBc3bVpg89ycK6qdxmnbCmLy310GZvmBaEa+hvNNMBFHQ3aaPtrufg8 msZMnxb8Lo/VFr51d3/VfdFJoZAUje8h+FliOi0/NqydM0PGOZ68FY7wxBlUDOs10eaafb6i 6bFGfM6tO8PLhq7DZ1M6Io0lxM6rmaw/vthCRkYqtg2RTolR66boxGr2UtOkegg6nvwoCzcs tB86zmms0Pt9fyTIXi0yxCD+F17lajnONx5HHHIYFyIaUjm+UWiiVPejhW0LbnkpbajUAfZo s7k1FHrtxIiHXVkiw1msbrpKUwUbSi6s4eehkvIKEpz34rMhlLyEr8HM2IDQnZCMEV9KvCsD zQGA1QFB0UzZLecDac64oZ/KtNAX0k/4Sa524xbpWIlzZurMd7W8lDdFk1B1ugX2KHwTVOdX vo/d7JJdCEFALlS9OINxXQR8Yj044xRaq1IVUk8ic44qPReHzwor2LkhsOBxJtBfDrICSswC N0wZ09xac6rkp34OzKiyCP4yFT3D/ORfivnBDt5bQwpGRivgoT+MrmPmTjj1XElxlBhG0dKc 705NBXwvMS8OafNEP8xpXCEsQXHgq9Vo7K2KJ402kwrCGBH5kMjyXrZ8NmKNIBRTUood3tvP V9mLuiT1umqk5fUHsSQDeeg9AQN/dIc2toXEOSG8B+OOkpTupAOXSnbMWojjlgx2IFafmIkS baMRv6I5xJtj6Yp6PBfh69fZSWvrSL+vK7zi5ZWyx306GR+9ypUTe6qqQxsBH26GOmE6Cy/u fxDWFe4dVHW1DqCUWB0g39TgP6TtAIbuin4FKXMgYz9E7F8A8866O0lYwf1gRTRUTFFT30Ev Q1d7Y6vkqBikjocFhGWVTkCYYKXPmmYVtM6+XqgX6NE6JTHnsFALzyN7bhTdn+8YBS5UZceX Fnko0nz6UZyivKC0Z0xDfGAl/xNnMdYQw2I4tBgTwrXdWa+/EBKXgGkDlzVfr9O6lx+S8XDD 99Plda2zyfV2LvwlpRSc/Lvc1m3BYQx7i5LLNGr4kZiTrzM1tN8acoTRB6cIJx1yt1uLOSg+ TiaJcs9bO0B59XI61KBfST6Q84T+knZ4beBbpyo1ldTt6aur9al0UzyC1vWT2V6fxcPp3tR4 1AgW+5FIet+URIYpaNLISZSy/HXDG605Qf3Hru1h2AHrcwblNq1KMNCL88Yny+2eW6IjYR56 JBGQjOkMP3qemmS+A2sGBs8t74SGR5gQzB3Q6mxutO84tivt5wpvpOnV0I0JRSY6pDVFZB6x ALwIRJgmvQN7qtnsGOB9z+olHO8hsaXBdqsGs6hM8HEkVXqr8NsRtc8bJnlGoaFWJ5qCYO9l Py9WlpJr6EbzoHg5+3dB0m9qe15+vHMVUhxn0RBJ6hCU2sYRhzIP147eLFF4np+EqV3fSx87 wahvxmCZszpHKaGzQqik27PHG3oR+Zw8JvAdsTx1ceIZCnsH+2elvc+XVZ9V4Dh4YkSlhNDn IZ6YvWyHqOusiy8iagHHuuQyjZICJ7uRpEt+G5XTd/eWPC7IwBkRpDZKWIVav/ry9Y1zSwaB hEtkpD3GCnyYYRURwvaGaAK7fs45zAVepjFIWXCMSZOvhLDtl5zuN1txiK358yQkPvUwYwOg DJKuz+Bmox8tHAlyxyaftWSzS7S7KRO3QGEdKRHzUcFP7XLgeJlUA6KyI9qwiJRKY9TcrMsv 9CXgYX0OMZxSq6WLFZlXufndKZO93UU7/Cc3sCkH252Pj5/CatNcPC4P0vsDL4BhS5dssfpF g6PAYsO71BbB0s+UlQZuF1hEiD00W2PYcIM54K0+kXJ7oqLXueEVSTdM06QOX/Ed08eVRSv2 Ifh7pt1HEJ+0Zp9mdflI6AuYyarYZZPW5dDQpOgFXrHnkqTOwJhDjT9koEtzn1GkScVCBn+o Bkz0m8ZsNBjRtIqggdMWlWOtSqjZGIfIeU8oaTinGSpCNgaUu3w9MBLUM5WzZNe07bNdw9wl KMqqDZw2yQ6B9MHZ+CnZIzD7vFh/MhZGl4WaXZa6Y2o5rAMhzoXRKAiZmrWobxAmz6hvB12I cjC+fcTCYg5Z9Oj0A46KUatPaMeLV7RgA0zHwIFjZ079BilIrYkOok00MgIMTAH7NvzTabiG ftGBvrSeSOUmkVnhrP3lEQYXIgnvMMOviUH8Tpq+Tlm5u7LB84N0w86kAjkZvBQDT0NbmXSp fZsp1SDbJnzXOVPCX6wJ3XPRXvFKHfaEgmgXpZSPxSj74MqP87ZS85+1+2BWdMznVUyHIqO1 9DY06/VOLUIIKr6/JrHnVRZRynO5osiFkcPQivO4RMFHjJAGQTbNlJwX+24lGhS4YfNOaCDG 6NdaI95Vjw8Ao3+dnxeTGjpumtsL0PW917QZIewtSmfd74kCTo5S5VebDizaPhVgtQH4yU6V HhrfsupfV8seoSqzKCG3pXmMLEpYCwJMWODlE+p5WEVF43gVUEdcSPl8sYdqhQW5+TtnQw0S ZnCHPDEfH+V+tEY03FJ4y+7bOGcW+OLms61kfdYa3aRlyNULNjwuInO6LY1jPmZo8B6eH5zp Npp6rvTcLeXjS3c5vVtt2sAe9Zi/DuV7RBgDu/wyNPl9DYx71AF6HbfenzTDMMCpIW0klcz9 aLJkPufzKUBH7Qtuz/z0rMD3tR0myG9oN77EinkiCY1qNISaosMD6REK346V/f3gTphqj/zm DGJxWgLG57taoPeUg6rZx5Pv6L05wwNgZwewl+i702lwmqREK2I9mYeaQ4QjUjc0+2t3YSrw HBTiqSRhEd7bpKJz7BBjtsXmcpvvsG8Yoom9yN/VEBNRusr2ICGB79Gh11iQJh+BqbnUusuN G5q4pDfnPRBQ0M2FfISpCAlEnWpok9QKMAn+2YdFkVis2OXWVEchhY77Ne3tJC/WnJ8K5UdK 9qEHT4CWN+Ar2fGjwPy7KZ26nAMpK5cKd8XrpWfjqBktIsgAJ7QWjynXXd4pMzCjfO4vlUfq iMpcp+iemfHIc5kaZdJslliOzReUZA606U5fX0L3OamDqDesKSJl1UY/zSLtyHImUpfXmt76 NfqHLFzFj8U3kDKEdbW9mQDCUMXTX2i24VGqcORGbgN4OAkqbyzeW6enQiKWkNRTFrzrxGRt dsPsw+fTcgCc7Za+OwvPxjuxiVvTTXNsGebJ0k2R8+zlFk/sb8ScIoAY5ZpaE9lx4ltW+3BS q+a4Asea4N2D6r/vozMhL/wy5UZSgPjTJOmC/HU6rW/wvsq1Z4kAye807KT3Ry3dYuen+Z2o OrXessgS8NHW/NJq1rptzUamuhlzkrEtegwXKGZEAHOWIIsHxIH98u79JAdRbQYWAAee5zJ0 kBYtfe/yG32Kq32mNSZLH2P6Tyy8AbfbXDajVAelOMuGYzE7MjUlE34DmCtsyjkcRRa7e4iW yIxaKrMO7pn1dFtiwxgUDc0nmQbr0MAzljjhyVv822CRzzQ2Sui5uZdVokvvgpDNym7juQW2 5NLj+eMKBIMwXr0PTTMaoT6k4C4ITeynEjQ14geWjPmXS1hbr7NadyUxaCwqeLL7qjV0CKly BYoBkqpdwZ7lnd7zL32Al7kqmeYP0d9QGPKvrsG3I03b5ZykHxjm5RdqlgrXacsa3Sh7vfPC fDRuNlE0c5znzdMkK9stHN2J7yqRiveXl6VGIFa1JkJ/T3ZOw/JJDCzW+tlrN98qH9IjWn6r f8Xumod8zllaOsw/gG7CqM+QaSnM+iGF1nzyvFyY5Yf9eP1Sx6/3O924giNMzbpK9BeKO7bk r5RwFQQx2DC5/FBxxSgE8j2D8tI+wfd6zQ0J2bkJI+8M0IcAFQFirHd8oyhP+2wy/iy/uBJU q6RQPz/PY42X+ec+1kb4az3O1qN8s44Mf7HMp0u1imvGl07OEdgfpoVJgeFSNRWY2UiwElN9 9f1hIcu83bo+s107rZ3c8DkM4fYKT/47qu5ZgloZVDCmp3Ho/oapV4pH3byUB1oKbO4CfztV 5g+dU43pZgjIk1O8qxz+9ZhlaA1hpKz0O2wlXLCMPewZa4RMAx6OKDN0BqVtQFaxB2BTF8Jb E2dTHSbqK8NM5sMUAlfH6RFWg2ntisMw0Bq3twGdLtDBNvw2awCJ1cG74nM1PcxPKCc8VFge aKXaocX8x7zWATf8anM/h1pn1dzAMscomOk4ZvCXbJ1BVbLBE8ZGrKZirzWfCjoE96098P5R 1jNEAIfPJoFfyLtJ3SflL1505whhzFukEzYqV6G/YMUMip8/UH38YjFM10XdY0f5wepdYz+V +iwRFy4tQllErT8QyTBtWLRsWGlAXgttReam6AmJvjgzuXXcgMiBasKFx6xYG6eT8vuBZvRP pdkIxN1DqNyMsKGibNqE71DPWDRp4nold+bT7wN7huXKHAUOwdlD25jkpXrcnPS/cYcd163O GjKGiwbCd5gw2xZazPtqR4qqJ+SvLsS04CVEGY8bJEdqwxxC/nIny458kYFAk2C0xJPvYxK1 uUepyGPVnaOIsOhOmsaeMEHfsoVcwrkYakXkknw1aspYOzMU0Gtc+VCpNrieLq7zI6E4SQRm Hp+pEPWlaCuDEIkoJN+/XQR2/6FI9F2akBzLj6OtJlKk5k+cCSeatTe+b1WQt+1OtsdvNBdi Jl5P+bRndtDYgpTdMxWpYBP8qZ1SMQ/LB7aHvMocQ6QJXLBir96cOvhO63KZpRL21JHk6Nx5 TkDq9ydCfu8tJ3Rs5bGBr2JRESR16LW04ZXT/H2ql63elwNAjKcl2RKEquvGp8HkT555EO3u qf6EUalI1XifYsMxfNHt8bB8xeBCrxOTXZ2vFmGpX1BC0R3sVH6e24IV7PaZo9S+f+KCzb3a FQgL4bKmLhw9b6EyHmJR8si6NkXByClaGQlhSf2IO5tb5PKzI9j2QkZhltT2c2TR930ffuMW vyxxZ2tqyJnbDMbb6cVtMGx1mZqMY0MNdgVhHkKrlOgkEoNsBbO76s1aHv5++C7kxJJ9NfCv sLhSC84nz7AkadNDE/23L98dLcd0/Amc1WHlMmZhz2M9mq8OCLgdK3NkNQIyDXnh4JniLfC9 rb8s1kncVCpb8MzoWtn2u7dYtUB2IdE2IbIEGmZjIV2jdsw69ANOfEqL0VF69C3iyBdwQk1h 3lDncYWScx6p3kdv+OrMM0u2jGHQulBmlNCRbOq4eFdtoB+LolHwSAjA0bbYH0cvC9yYRY+N ZIh79iNEn9XQD3/NSD3E2KwWgfDx1Bpo84DsJOB+t+ECkKqQFNcbuzObSEANGKpOjbyOWnKw +pWXKf4aNgHOHG4HP4UPXVwno0sLKWKOZe7A9lLvLHMlgZWT+EjyfZV8fX/7akMCcUtdiFf2 ydhyvG+NI3JtjaFsM7mKUeID9nlCmhvqZ0f1KCIrjDApJ/ifxPmiNkz7CCGIg9xDuGiUyfNa zgNhP1sqNQUIMqqVC+ViNFZh5083z8H5eKwmax3gyzloVGvV05wvKvhXc5YUN2+97rBGLuVF UzIBitd3w+FV6C3jeDW2k+rkY/OBFaNz8d8fo2oWmKi5oD37V4MKTPSiNLpzwUlyZfLxtYEv kbxD/SceOh2HuYlGfVI2YUAiXbLJcQgTg8lOVeGzDqemRSlTD2ZN69rG7cXEdFxxC4Xl+CTo s8QUrYhjr7Ekb2Kr18MP9Or8C1WJyw9lgG/ZpoFxJ5P8BmVTC+uT+uJXgKjME1yJ70HLMYS4 CByv36n32y5/FpQd9XyGdKC/v8zCpWgptOehnQmj1eVAjuV/UJqn8tsjXeT0TD7grTpyd+MY QSDUkdpNesW8+Eb9pjohJYL9Bd1tq2n1WY4/tUhK8C3nxPedNLe2mmjJQwjYSH1Y536tnRUq Y+r3wDDiuYQ0m+1+/5OlosxEBtVLmceEHtOoSVgFwkfknorIYEf1ge5ier5X8hozRhIZ2ZkU ShZGQpEvEzePu1brmQlxEWm+JrKO7QyrEbZ8a9MzRQI+SOTrVhHQPldcVNNM91imol/vcH1D d6X5Cipohmci2+oGJo45InwUc2zs8+xtr4VWxnvo7Af2TPiY4+Hcsd5HKRwEzso6BROiyr43 X9JC/bUpYijBOerNyZD6vmslBG1HtvnQc/iTTt4BzS8M4sQ1QUhjbccgrE58bL70WofyhhkS ZD0YBgf2o+qWpg0kddm7yRnUNZOgMh7lvPh0kcpl/yNBbYlY5E+SL5PwLTIeJRriPbA2zsYV p9KMVgOspGq1ObXKIc15TCoVc7GtaJ+e4XwM9mEiSrbgx0VTCcazSnZ8c5oQCgMSTqVDe2gS bNfa+BnAw2xR+HRi8dlynwrm4NyvkfEUKvG6RfbdcxB4VhKhsnp910qjet8BCx34YkwZg4rj pteRj777SDh+SEz65GvcMht5YMOWoWywnwgRcAmxbyt97ifbhm18UaaygBLzvCjjxF5IAx2R C6EYy9eyyVSApOJnd/by0mhR72uOpeP1bdwqnUEb1YHOhtg+kkLsGFGnZok0cuXINdB/Pxyr jHYXl4lWqOmXUKqASzk6aZyNE9moYcm3LQe80KmM/I88YPuMAOXaDr0Osk0ZohD1K7PGJfKE 7wmTo6Jns965ka+r1RtU7aW9plA++TK8IgeedGrffXGeob5SK2OdEPTWXfR9BJf1ueE4zk3V MpxvWgmmG80e5rfZ5125kOJO+96TnBwIJaY17+ZpaCAHszXNSTuiL0e7kmTBHpbGqSDtyFy5 4V15d2Rygz0NgaxoVJWSmB0YGC2uP/LoGQRh5UTf1qfEUV6FrPfTPflu6aC2joe/fTbd76U2 IHWTQfKy7opDuPPWHltjShEf71NmSFKNJwKskCV6Evyu+KGgf08xrFzMi/E39H5Th63XxWfR Dx7kYowWVTfRS4VH8icfnEzb7yte3G/Xv1Sr5nxTHxP+ppuILSD8SvnaCtTTQBXv5g+kjnmn 7eP3HoIwdrfvDPf1/oKmo5jrE37Ph8o8s2qOzCk0qwp96m7mXx+u4Y5hxfRbRV3PsaQyedos bPxWuD5jqQMQyW0SGk5597Hvyl+iltT6LAe/ZR7CrP4sMn1o1WY7QSR6Qd6qEHxu7mTrBz5x N11oWK5fFmQaBQZCTzthaM2XT54Lx8MPvc0iqb8fDRYrknR6oAyDCcU3IY2okBxQd2UP0D0T z6B65AWHJ+jvLVVQdgeYJ5/qrTg57uJCYUt8HN6rD7cvaESbsBbStToaZPnM8N5eHc6XZd+v dqLpQ+puTwFHJFGhuXqjFH1xjRwd9kcjZG6diHL6APutAnCiFj/rC+LtxGtH4udkyysCnb7E z4bSH9HTWT8pmWAO5+2gOXq09QRYx6F0HnVnEWcpjVgyztfGsZhYgOE/Js7Nw7olvMKZ0R8l Q5/COHbjT1hLVu3dlXyCHrhE2vx+tALzYQ1JBeJyQbULi4kjKDINJ/4ibNzbaZutw+S5/ZXh BMuUUNouiThII/ZTPHQdE7QnN2WtuOYZBpOb9dRYSdjLhfX+qHt6Bbd22Vi+5DLeDMJ+3KWq hh+QOhOh/u46cjjRPP1Jwv0jixegQOflhIanVWhEGHGWtkzESQ/xCa7GFDC8aF+ARhGcn1oh 2M9+mB3E13+/73wuMn5q8JC88jJuaE6Xf2y8jPOiKu80WKV4y46WaRK3+47uJ5+xykbziSIX XME+OVZnRhyctniIgVNa23n4fgaHpMjK2ZTjNRstlwdzz4t0H7iuvD3ajgacdWrlEvh7PBbh 0AJlEz8OebSej2tyC+oirvLvofLmFSZL2yJl1wMPP92bGJrwT8Rnpudd0CUcCtVVtbnMUNTD GiebQd00qPIUt2KpdiN9sHji+mSs6TpX3KWOXRtEqr3zfK94uhYlDGC+Udi6udRk5UA65lgj cxCqXiEQ3f+WPriAVuj5JfnMqfNSl4Br/uydKLkEUPAXDMx0bIfW8mB3uxx/DHzQwNh3Ot1r 4AH2Rdksndf9aXmMmYNdTo8la7U8GrJ+BwHDq1PzmIgAWKwgtop94JILitndsf0tg3L2fHQM 4rcFMleMLxylIfufREVrLTz7iQ6SFanvT6nrzqDDH2hlI4PMBHUuo5lvK4UOMAi4qJy6fKR1 aXaAoZ8tLz/O4moTr7P2iLVDJmQxbogIn2Aofo0+NxiLciY4WNVtG7lN+6VxOjey0Nv0ccdA XkW4WXWqb4jnLMfIINgCoU8G2wrAcPT8XJXuE+8FW3cNZJxEjK1yDf5wt6J1j+ogstI1eNXY 0Dz9y+dRyzAj1qziWdQ/MT9sf9HcFlO2U6vHPYUPI0fy29PqS3N8ihX1cvusv5mqmMfMhwZ5 iJQs4mhWySFx45VdCXJJWuFnVppO5QiE0fMmxVKq47Mhag7crkJ5E15FzLI9yS0GL7JFIyoF ZfN63w0nVMtvnbuJ5GouDzdSsyvs82DNcn5N9HWQi0yj7gTCiMeKeDEf/PAoEc0k0ijCo3Pn 3fMepiuC9Ay4MOgawS9tH/sUyvePZvQudWZe557M4CLtRQTuVm35E3Hk1Z2ZYx4vLp0A786G dcRn3H/JK+z3w65ZcgtFbnSHZqLz06IkJYttUcl4+gVdREO0/zDETmzz/tW3Sb8tAHDo6yBg pyXuCMYVLqd7cRNhZnKcP29yhGAproHLeMuqC/dkihZ9L8bF77g2jsF6/9N/U51HAAUH7T7T w9EBYp6Lyrjn0I7y11d0i6bLL8ryL+sonq2CFfg/bb8+FU3aVvDI5bIq4TEN4zvLU7oOSMJW mrSJGIxh+V2XGbEMI2wtEX4sBEtcQCmGohfX9TlXRew6Qui7JTJLkBC9OJ2Cbyv9yZAYqvKI urwuV3HoI6DcIyEsg+OB5PL+gfXIUwXqoBrbR6fAeYX9x61wVmBQXuGAhcRgmS9Gdiizun6A d/u1drqETGZO5narlVBmrEd0xsfj7eKjXap5U9LXnw7FzGx3MsDJvkJc99ICaLNfttqN5Dw7 0nhHveoibhhUfTnRSq18uRNrC0XM91SOcqFSiKcoQu8ETr0RLtPO2Se4esMbQt3HRqR9+a9e T8P42yCyVuhVIDa6/Ur4D31RfuhMr3e1Fuk4uISq4qVn3J0MYEuhO3rkjxe046KiZjfRcyaG iOZBNwS0E6equLHBFLgy0RXQ2oEZymJTXdDR4Ny+mr//rKd1zxuwoxn71YI5kpDRUGUI+wy5 GUpIlpCkt8cDQ7SBECnzWyhikaef5TFX0KRiGekAPoTKzTP9qQZcelD/Hp0aIzmzKnwAB36T u5l0bKh3Bb9bXUD0a8WFk5PBJy+X4gVGtQbPTd+7zp3I4aqNcznwEpiQJTXqYava7qCsqKWl JEvru6sbHuM4SZcmKXqaTL6iOxOGF+UUbwR2H5xdx/Lv5+d6Kk4xZ1qvvoFtpDVUWNMGaONH Egtz/mI1OIp1IRiybG+W2wh3Ql9jzjFdLzvkUOuYwEPYKB8qXGCAcnoeV7GBFIoA/kfg8+F4 Q0+ATpQv6xokr6D4pW3Rmi+hAGMqjxlMCb/YGck212jjMpkIk8KVMnQ1fu2NZJsAJV+d6wIt 3f0MBAAGPcOEivn4itcW9yHAOjGtorqmlUVMKwXgfl6Bh5r45Si7O4pjF8pS3+f8Mll1PX2/ AAq/kJwrUZv4xrTHiqcULWLoIsy0lUHondUhKtuaJEwz9Qn/Z4WAZiFUICPjXnsVTbXqcPfK PBtYSgglVy6YWKQzvBcCd/B60IcyQU+3rp3N+FUKtOoFqbZEHhe4lDRTjGasWOl3Q1JnFOEu TVBzCYOn/TuVprrvZG9OrD3FuZCxxV0P5Q5NZ/hu+20amlu/gPW3HQKjqdra1bJN6hXyjg1O biG86FE/DvyaqskhHDAnjFdFzzBlr/hozNkYo3THEHqVKtCyZreCZq1r9slaZ3e6jsyGnbRA XLyugdYkrsyOVH7gPU2mcT3Cx3BxdMR40x15iStUVXkh+all2TDSwC1YVRcnYePPUpfJSqqi SE80nI/eY7uL33WLkUPaqbQ9hjHGh/ignjtGYhaW9iuFwbLBXOcClTbaLTPt520y5AdDwn/Q aG5yEWx+GdqFE2a5lu/scobrCt8XSCesJHgnlnX1yqbFjP4KUUPqEI3ycCPa+0sA4Zek60m8 z3Dp1AtKAW9QTo7IB4wZXeYeqgqFWX5aeKfDT88lsw4X3B8kcjRmtfkQKzdVFjYioe2lCVc3 sr+M2KZDkKt8hjPH6T15K+ybNYhHtOhFT0krJMQS5BrqSqxhg2Z811/gsUXwxmHDqrf1Fkki Hj0bXOx3Y3UdgN5eUYDN80uFAjHUVtZpiJL6wAw1/TrOFSsVtaF5Ims1/Yrmwq/zE2eTUeMF o2BFUZOkup9aynUTiY3HQ4rTrCsFjLKN8gcR/+L7ha4R5e4vN9Dp6spigTpejrxmG+68fXnP ic8OSosN6lEd/J5YY2tlH30xOevmwurE/SbyA/lvYL+2Zbzf5MDc74mMXhe4m59sXDaTmAn6 2trJHOEZXPU5YtZEqoImETPP1WEk+ESAuCXqdmeV6QRbiOOlnpFp7zukb7F3fKPPKCyKgOsP X/zj5tYYGVW1LCBses6DrpQrVoSJs4mDrWbLXCmHq77192llzDW7NfOVNDrsikA4bMcEzbMT 5/6oy/Uk+2ki55P3b/jxd/5SX2aV61+QhdAxZSW4w8k/oCAsImgdO+T8vOkVZ2cf+RDxdZ7w +3oZYku3i5HYmSCbmYUMUqFxlHIpi3g75CEFPkxdbO4hXCBcjfpI+X4AxmHFhbOlOnZs1pNa UMHAw5dvPOvCmK/OM6YX0CHpM+ENZMwJgWlw/AHu00pXE0OczUyexRAzur+yOTAVxForXlQ4 CI5v/EKH1PDDdA7m9RiS6kI0oVI/kX7I4vNtdeqgzZtdKcxrjZ73Ix8+FsGATtOrVcjoHNbg WmXEgEA4kC53argwUqflbY4hFUB0QX9hMWxES5M/4M6iFLAPj5tUYiQWjcy7p8YaHxbuJH5i QaeUgMB5ZCCxZTRN2XTPeFt1ohqUBAs/nIUJGI5iYw8V9MSHmhLMZrEez7V+H6kBHqc9wtvG 23lpw+uwdOLLnXerXbMLbEWknDemQRf+0GFyfmI1KGHy8/bpwuEL6Vv2cT8xdxIJZH1YSZZN uQEix3Qwk/hcbuAC58xcdD6GkqOyYJ/WR9W+2F24BsOH4YIYiphdMUqvED89m+dpfrPKJuoB AOvyGVvvj+DkJ4jpqQX4PIc5FI3v7uTKJx9TNr1xP12mnbFMY+VSwWbwz7mIuyJrPfXMna8u O2M8w/jdWOOt4DCxVNumykbkgSVJsM65qpPDuYhV48J8eNnwclhx1CByoE7tsSl6EmGd3A/L Wy2mLRa+YxSky6Jj8kVjkXI/qkaKlGShd3FcoRwnEr0NaKKovCZvgM6KqxsQCjMLh+T9nlVc w+9ukAXeETTA59wmRJOP+y14Xyxmc1DMDlrqTIZT1xCc01kbtfXwMrtNZ32TsMaoFL7XGp2f Gcc6FEr9Ck/fcgowUx/sPlbJA70GEZqlmfANkutREim5Pn+LiY6WrrVGsW7BHlXM+ueODPvH 5+S4m4G5jt6Y14nGBZ0sMoZKUz4wqtkY7hXzZpJH0rATm3AMRkJqWbfHcRR/mWZOh2FWuwV3 bcPEQGjVYwN0BruZPZaGhs1pskWWKlaROpcMP+KQmK+SpQ93G/H4FGIMtpaFb9pScYzYL+79 M0MpfvxSCsdFB3vp5unjh44lorpFBtY4KLhIqeKLd1LYB5SQfO+pObXicgkaDE03nww/jUCk HwEfXzhzN4Jt0RdXu1zJ8I0TVecdVv3tLSne7NLG9JzCD718jtqaT3Rh79a+CA1aTONgu98Y BYvTPV3BcTSkvHxjGzUOdOYl8O3IIjlsP9KpvScLo3lGwZrluLW6xmp0xOL/0jnA/25uaQYN +NE8ActdDkqq+gudkX5/7T6Rny8FbWGZ/AEx5TdMi9HBxYTiQbKEwRDTplitWvPg9uokCZLv pJOKEHpogRtqZ47+CSSDC14CUBoWxSzlRVyjC7rs46qk9RzC5iOiNyFyfEqiNfb3uZn9rUGR HrFe6KVYsZcZmTZJJoHbYVvYhx3xD+gmMPckbKYV225l63CrcmXGHzsTgwZSHp6ePjhqFZe3 Tyq/bQGwYlrtoszSXJx5iclTvtQk92orYn+I4Z+y12b0R0ldpLZHAt+QCUD14tqif6BONJVb NG5d+6pAon4b5kkNxTxPKHimeTr6nLZN11b1FbqhFH6bwmH2NLd3BdZnRMSfBpPXj577E7Zt dbYoLAr6UDfJ8is0r5MiJD/tp5S8ealhcMmtSVtSWh/drizNaH6eA9SWnvVQZMbuT76kXl4B CKnI/AvgpahzUSvsCP19Fln9HAQEMBMIcda7aeOE5CkCPJatoneS8PRmwv2xN/X3TGRH3/ss 4D6wIbfOdHg6v3nqQ5u4zVZ5slBMkfmlmGxSVd+2fpVL2Q9mjkWPsFZ3px6aY8hwVGKCJxeW pbG7hJlcFXyWlRciO6Jvb0VyiZejueZjGFMUPX/4bsjr0OwBF8R/4NyHaEvjhUtps9baKfR6 1/LWy26c+jLTHO6EGN5nUHyrWIm30lODhVFDLJMoBGGdUULrSUC4i+h2gNMeo36VR2VK1zs3 E9mvYSy/d09Sko9wo7rKE9wGftF1fhi7io48mU9Bnt3bF/gVgtWHnKN/zdqXs7qzcpIpDtb3 Y3mTT28YbInXKYtmu/lsIIcdBf63MBXlEO9G35+hjHz3/J0lQZq+8/25efPpXQu7x9awcDZE iQY0NpJinZvPYmfnHUVmKN9KPUOKJlgnOcDkS9G/gkmZlZH6SBWxsM8Pa+yCs47ZuaBs/YAm 4vl1CG8HWyGTa4hK0DVM4lrH6dLJ1trznPo+VflcBKLjIws2KiddKl7qBftn+pgkZxh/i5LJ vqbAfPSbLqfGWXIwZqINIF8XJf4NNAbQnyXjqhuRflY8xZSPxEiO8PUV9bb+DYM9/00Rk2Og 8dbPNsLPxx48MbCeXekYnUwRST78eiwLQgcz+FPALxEsv61ttdLUNfsS9ze9jvEoLGr/r452 MEE7gerhVHcubov+2zpbQoHc4Xo/5wd3h5oyOXcQ9xVWYD60pmzpCgc8ayN5wi9YMSRPya3S eHnhJkHef4E4D6F2W6t0K/15uur1tgyvzjbNSPal+65nLM9bGytFxsc5u2saDmpwTNxg0txo elBxbiVPFFaDsoiBloywrhxBW4dzhteoTGseCqHYh0fL2iD8fcUa5KWIkNKcGoVHvOLb8qlj TIpUvoczw06CDjnz+/FOR/ODi8d3ejPx4opCXYjJnxEpljfMWBsD3ll7edyQ8mhcy9q48rZs tTrJVa/mmCpC3uF5cOvQvEsc22YpaqJujHHP5DOALWxMp3clkXM2L5bRT5myPnT8urRsrLbk i7/liXLZrtuVibmI5E9LfrzMandpiCjTu16nR8AgGwuNdcrxthwm+jIqoo6Qnbu/R6L9yBb1 9h2phGFZU9jco0ePKu18bAjrY7xrD8KN0Zjal7D5sdtBMCqlEua0nKU51/DGhqjUVav+8y+X z1N8ixRnZQKI2CkYYHwDVT8ya649NsreDf7wj+7Gmshp1ZfFSiSoML6Pixxry0QBfCFBKHg+ d/lZmzoUdmYXWHsf3VllaOpN6L27LD7NrpgsYJnlNyYp5m/Orz1C75nrhzIeIeUUuZALCzDa OUbBa5Lvfwn2/0Yrt93VjcIU+4xu6er88Y5zU2823exYrKakT722AoXpmgB6Ho6Eyd5+ejwz 7NGizMIh4/zcArOQjvoNz1KUmIZYedWUCdHSMMvDY+a6xt37ybDBSa7owXZiHRvFD/1hVDpa XaZQIvp11L6Nf/1VL2ynJu3px8enn+sllzploTQeLTI/vi4CorII8sIjFB8754MYNvMXwVtP biCD7hymtFoSqoZrRbZXO2+QZd/4u6kLvZf8xATdJy0Ge9tpaYOvJm/ORF7V0MpyyCF6MZSx OL7txS+ujQl9vyDTdLJpxvnyIObzaQn8TFJhqAkZUXNILo1/2zuA2cElcNVAaYT1Wke3vgcu 0oBdhq32DCu0LgNaKV/3m9Y8ZOoXIYzyIDbNxG9q3Tj87m9JJU/kmybrkCrm0dV0rHAIvww/ pMQ0zIYc2W/9ZKm/gnWQeB4jdxcm4d2B8vtcwOhh5fV2wwm+cOWOOsI2riIOUTr8ZvMLU1Ev gIHqJP4NQgSqbzDUPI0wIUvTBSd/Bw0xVJtJJ9nj7IjsSF05Y5m3KilVKU4c9F/9fl5QTcCN OZGly+6K/4aD2qR6Zz1ML6vXiswqHYGoZynxxCxGg4h1ulDhHZ/8HjgAXUlEycwXR02hgpP3 ew/BbhXv49X8mElURXDy+iFuviMbTzg+y1pgZbRFgHP+HBbHGVa8TXkIXsxu4+KkyI8ooUeS C/m3vW/lX/k7PqyOzDet9NopUi/tmLznc4EOTrIw2NeFJx/mYYd1WeB0LgFjN/P3Z8HTP2Lw wn/XZMybhfE8rTqxC0+EQJh01vMdm+uEO4/n64j/G2WTA7HaDEEAQjLeT6gQzke3cA5PaDD0 63D7DgTIWvN3WKrTkkZcpWkbAV0ijpheZe9Pl+IitGQ9yiWIBX+dI/ubBqnWpIg+LAL3rIhN zU4pUGfsytmyXH/MwD5IWFQwwrL7xqSRT3e0uKUcWDrc6Bl7Y+nsNPaEvV/cphK5574OAEzI WLZB/tzFVFkN/eSaY9Ce2eiBLJQup4tTgfE5M0VHO4T3vUhvtn5nVH8kBC/C9cl9+dzk90HH craDrxCOTXsWlY/LvHjtV9yKxzm4UEhn4kTcv7hCFSJ/YNHcW7UPFZZp2662VPuDp/K32HRA /8rJ2517xT646sBkwO9owFWASihgfZ1tOndLxX+2cMC6jRRjgz1evvpUNUckWJ+l5Fyme6B7 vzXTUQUoc+3umeGQWZcNb0iX5E6Pv2XXR8ctX5iNsA1mPNSWQxPC/Aaui0TIHt8RvyX6s3G8 mTRisBnhqdZJkVGFhSyR35pFWUbop08wNESDv24bj4DynD052ki7S5WzUrd4PQ+lKVw+V66Z T8aXixUKH0Fk96d8pzVc8C7KIsG5pOJLee3MW5hZAtWZgI+49mkCCwUPjcwPfbsWe3qX1n3X Q27Wn1AWwwmkWCTP5uMkjTMA3FWTUAKfcaHiv+Xjm84jBNH7mbt5iBhp0ktaoNBHqodRWEKr y6j2V2tK2yb0IWkEzqUxH0nPEdo7QSMxnhKTREAjXgOv5HNhM/LbqRZ/oAl4tk6cQhOLHDHP Wj658HKpUwlMUiD11Celg2NHPhlU6u0TyeR08jO20LMsmiQbPc1K6gNhIbiMgyQl89Rkk2U6 VHllAj6vhwQjUbPw38ClNXzQBX2FO9MSLJC88o2KGpOLyIHSC2sqKIhXOvy2hkdKBA704se0 ZZtO/excgTzO1tRVUGWvtjL6w5o27abI5MztJb/ATpYbsUnYJa9NXw/f2TlI1yySiqQbbS9C NDOyOaySUnxOfDhd+oOAeI5qEOsXRoSKNFXcpIMevKNV4ufCDuw2LYUtvMze/rZ+ThaXyTxn bw/4+GNUVnkmc6eHVAnlDAg5jEsBXlliPrgzZchSrGOs2W/ctGYWiQf4M6gfZqGgyN9fGpx+ wYy+ZM5Wr7b7NRccZUxQXfE9WTG57HbeNEvCqu6+e6IhpL9S6vHXsbi8SCQSI1vwScbbx357 qNAY9DUB/RsCqLzD0+6EAT515o3gcw+McUAXeB8bi3lrKOlIYw22Vs3wMd+ADtYYUY1pxKjq xKYk3VL1ixZH1Q0f4k1hCyS2LENGnI5EbesQMEy+BWsQL8RZTmdyRAgfkY2iXOFM92kSnf47 EK3k/wnkDBvzrIoHfcvbh80J0OXo8Jz9sElMO/F6MjP9Ad9/hlEjEAQrTS9dU6ymjFSQRD35 gyocok87oZzmBLUZYHos/Mw1HoqXGeZJv/bs/4uRYxYUdvli056JlO7rHVbCk8Nmt/KfeJFC UX40csfHRvdNb7KZlRO+B26tsWwVwFGOOgIA0IFV2sNGp3rSIxuIQsGZLtAOdCz24QTGmJ3w oMLW/2RQz4w5PqNnBDJk2kMyMdgISyaPdMlSvUtWdnHVCVyOE1tFbL7F0+6Zf43z2F/v3Hhr ZssMBV5Au1T83LXz+5JRvbHm3olM5iPHUWDN8gec6Kh+aUBkB6Xrh71L1M0Ln2F422sCLIap piyUuw83zFuRa1Ms6mowzeBKMRc3HuWdlIgn6OGVEl7Li99sdQ4aDdB5F7jWkPpTZ3Qoxg8U kERnZ3DJAw0XhKMJSaDjZTJ+SvMh8RvdrDCFsHV2r5/VTO7ucIlkR6pGzkakGNOJzwawrV01 nRoCCF3a+4F6aE4ZGLjCFYT3Ef/V88XexTM3Vor7cOwh/djlXXSo/gZcb4NpAozLlfDIa4BA r677A4JKmucvuVm2JlXqNr4JCyAf0zSYPjyDKcCimgDNJDCVtbc5kAWKL9FafK4g5to/PxJv ubo5gz0D5UN5/V8nnSWqM7Kbe11bGDb5e1zknn9CYpNkUDA98iYe3YD213wgNFYAbXYLqDOk 5wsK5i+j+dYe0v8vu68Zw9Qvw151Wn46v9UNdR3LeheJeKvDWAVFP1Zn7BMsuSXLVLXco51/ DwdyjkjIDOh9JWrr9w0D2+t/oYaZZqsjyZO659mwgPIIGG0D/YfeH0d2NGENZwKDG6A2DK5n DalgPsE/i9eiRabdgshslWB4dkwrLlmbjN+x/LH85LrqXdP9AQlkYeriCWnNhhj+oT7Slpoe 1ddRv6fGt7if2eAFbBDUIPtTus/gHhZEdg+KIcZSAhUhbwx2wUI/1z8InYgIUKBuoWO5WkEu AsAw+Dabne+WuFkrwXKkwqVZ6fND9s/nnsjDmHn4dfJgjWEB3JdHXvtkNgQltmt5JNzCzKmb pfXyMU6r/BSci2ozCLibjncE2zp16h/QMzkV+MGLo7IC26KywqJ5dxTH7Kcm++uZlYqagkh6 7uPBxsu74Y3LlMfTP80eg/MlONgz9XOMVFscHIp1tq2aFIZWlbl+xZVnd/jAAu3F2hZOwvZN 0+K0HF/glRCK4L6dowBYcRBqggeR0uMV0u/taMlVSqk3jTAMkMfX91QWNaM+V9byfprWscDO VWp1uk5ft7icFB8kZfxRE+iyD36RorTTXCLK7AeciczNp2Fi0GPCoizRmoboOo4bcScbHB1n I6eqqUj4/ZddsP71KICqkWsbZH9WtH7FPb+CGFOrePYwCgTg+psaTZTyPIu7jYTDvxWq3wsY AwL6P1QKt7GcDAoW4nMFu1ErIorSXq1/i6txTQcl2wRocIy6FzpNRdcHd3nANPWBSkvQdumE 9+KNeEerVQDVqc9/zvXFrBm1wtckBcHbi34XnAkNca2YadECyuAFeDS3b4Znb0uX5pdafkg8 HJeiclaGgZ2/QsTqi9d9fnkGxS2066k/NhqXP2fkRYLDPFl/azK3H+5RhTdnBhpcxCk1K+CF 1WLoHjWUrDr1d9RoU/9GAK39MibHc2PiE/bkJircGZCseg1jfhmVDJdHmU5P+mJxD8nZLV6z Y+3NP4A3PwC09wNXcPFqHwyeTi1jK2W8P5xMcr1r3N91lBWymBIGO8xV/5UYzedb3z6cJ09d 2QJtIBgbCOOZjdaeAsVemUuU6at6msjMbg/HPRRPYP25C4qR7CAvk9wOl1Z+ZwXoK/ba4oyY 1zda6C0TfbKzDSnXHDupcHdAv9vdHuHfG7ryrzUOUlr3rk8b5NPg8GoKDwMeQ3Sz/RCarukC RuyqcSy3kB7Y67lyqttJcLOfKqtdvGtNIk94fpPXxYAHa5LmduXyXe3NzLjgL7xtFtUuYh/Y WvFa2QVpHPuFbrjXyydpawTqO9vROGr+9/bXX+G9uzWna4dib9EgpClSk3uWlHgftoXMSiiV yeAG0zf87VTfcTQ/LeroH8TKIEtDuRO46+V1yshFDOtsCnHDE7s9Y78CPk2QKmVNqSG22fXm +hhVUZsjYgXlKMbF3Fx3JmV16Rqw3Lf5nbCxgmom6PZ9yFSZW/ab8iIp/UEUCgrpkdR5nQMo AD97M7On4/yZlgmGPNiIJhAGPWqqpwUUG8Qd6fWmGxFAUQXBLcW/2991OeVEh4QUCtD1KJf4 Q8nFj/sILruxlyJI8ORjd21mlpWYRjniEpohU8PZrfmKpQhXdQyKUXxkIq3g2ocvhuA6fw8o f9tfsW4mV1Te8TDMmfJOb7vX8TLcFENrghiVzIYj2OLElcR0msvZavx0s3CQOrNSkaV0U23k d03dvxLXOMTQUSEF6zngytvge+6yZteuaiGaycBUJ2Azk9h2LZ4wkP3c477yNWi9IMYQhYwc 0MReoBTzovdkTjQn4tnM99S1VV5q/oj4BxnIK+7JfCx+8DEaFYQHXRevtwuf+EXySKsefFSs Ve/ID77HDKNjSmP8Ekt0FyJv4oCn/8aLS7BZIllHgw2CDAAy3j91G9y5ao3jybya40BvVkeB HMnebnUXArDId7JdCo02EFOobmK0QROMp0E/HAKp5hou7aLkVJSVZCu+F0IRduA4CdG3LMlV znbYhTDLTGuSRxeoaysMp1L7p6gGUUi9jkXss11Psn/2G4QHaWB8wyI7D7QWZORKjgVi3cLB rY6S5AZLGSTU8IAkeK88kdHG8FE/84YexpANptrS27bcVC2g+HHEf57GNB9D8NbUlOZO+7QM wzk4R3uDMUTdGSAk9zRo2rJV1jiNHKOWdKl2zEtZiuIzH1NCRg/b1EUUOJOaFq0v3xPeidCx sIwT+u0wzLUBQjfMsPKkDyssBnQTAeFccSleNzxEoY4p6z3tQ4vv340ZAP4CmKQvpw04U2ih MdvBgDjTiJsm36yVoZ2Lml3b2Gd7wnkH/DRBYaULsqLKN1H4uSg3nLRn83iknOFrtAE5G4n6 56WJRZIhzhCX6HM3VcaTZsMybowgSg09zz97u2eZCmKmLwKoPjoTLJeIyyTVxRixo3TPtTSg wPCoVl8x9LbNI2A/OnHyZX2CQnz24TG7LXpgmo4NPbG2X1FVYKnPIvgFbt+TCzb6nRcg8h1k bWiP4Ida5rrZZV48t09aFv7OS8F8a7shyoe6Q64RwyzGL8u47Re4CBV5XpxotsrE480tOPha r5DCoSCdOT1pQclK+yPwmzX4pZrXNYEv2LFi30oh1X37JVxkYMX7HKnXBN1gtME7qx0DLv6w r1+WqjOcqw7kD5hHbt4edu8Ahxd6CSHMMmymhR5VO9xvm5S+9V5lCK1bct/Bkd/AfQ/2S3u4 SSfYT/7WDeEiJvYEC+PDvxdVhqCA+hvhC++ZARa/34/sbFP/PK3f5iAthQZ8S3mGtmfPdykU OUhV/1OfMVqOsrzI2WItVLqz6gaJyh1Hj90fHFI+Gz+dbDoHQzvABRNsY8qpA0gBhG+EvS/B kFNYjwR0Ntyp0bbArrQbMYJR9gv5fDGcb8O0/hIdSUJhy2KSJHfkDiOsp61RiS6aN6FG58Il IWw3rCjhx5XvGYQaemEb+z8e32dXi8XKDxioeeofQLQeg5TmPg3n5MhJk/Rj8CakYhEB3G3D z4/EpNHUw6MOzM4ne2kvXDsxJ2o5RtlURAA7rmmp82kU981h3NUS6+RydjLUU5Qap4jg7K7p pxjhav6hiav2pBlW93pdS6H2cKjfNMgnLF4zWYnQwhLai0yMXc0iTrqccVaOFFhXuwaL0Z0U UWEozCxa2m88pZYUf42z+oMwAjTC/5RNROG5OqaX/YYuttu7hcZjZJjhlei6EtCcoIKEWLS5 GmbGhapa+eaO62GWhF7UH5D9kLxFRNoCzV0W8GV/YemZuTy27hnJqGF5HWluCT5H49Rybi2e UKBXIx4a2JjhzTCRDKwzrjnVffhZPDkcQUpALkNLTnpYJlxVrZXEz1Vs1ocncU682n5xPZrp fizSmz2vEvIKLZA5jfMX78CQzO+uI2P+tb4AjhSKYJZtmLV1OS4xht+M23XaTRNMKyDGWcxK At7fzs8OkuULJlSEJH6rpzuoEJqLiSqjzLtMMlluXqA3COQYU/R4rynPwIAo3wOXSnt4d1EH eTG3mcfaMzyhUiXnWmzuy0CJ3BZIPHb6DA9YBVyl4I3ejYFRoEG0ZEa2EIvpQrBacYWV2tlu glw1kVKPW13H+f28r1M3J/mc8k/zeHu4586ZxQwCr6k6JZrObgnuYIWofLWKSe1yUMJIwVMt QydhcFj1qqHR3kmMmhmetjxrVwplbmRzdHJlYW0KZW5kb2JqCjQwNCAwIG9iaiA8PAovVHlw ZSAvT2JqU3RtCi9OIDEwMAovRmlyc3QgOTE3Ci9MZW5ndGggMzY1OSAgICAgIAovRmlsdGVy IC9GbGF0ZURlY29kZQo+PgpzdHJlYW0KeNrtW1lvG0cSftevmMcEC7PvCwgC+IgSx0ccW4kv +IGWxjbXkuiQVOLsr9+vqmbI5mlSMnZfAojNPqqrur46umfYciU2uvFaN8bHxiTTmEJt01gX 0A6NzdS2jbO+cSU1Lha0U+OjxXdpQkigK03U5sgb3UTik10Ti2m8MU1yEXSxSZnavskZczV4 axB7YxtjAlUwyxZ0Y9g4BxnGoZL9kbe0uIRZBkOhQKzFrGTRggyTeNE0k3iUgkoEQ+tIlYBZ hYapB8rogNWY3FioCs4JapIuNpO+pnGBKsDE29JY7zHLaVSyRwWYBHR7Z1FJDhXX2AhmHtDY GKkHIlKIR96BcwZD78AwY3XegaYQQ3ycxlTvAaohyRrIQh9UMmCGlh76O0sA+9A4FzDdA3kf 9JH3IPYF6/EgDokqhdYNzlDSlYAeEsxDwTbBZEwPrgnJUrdvosNUD6axRKrANi6nIw/dsw5k Wd1kkkMmzgk+4KNviiUTxNiUgMJjZsmEaoJ1tCUZ0MBoT+4D0UYnAgw4GGNjObJkBkPQWrKn CbCPBXbGRKyflDaGRFmyLQyHuZBnrCaAsHBjDRZqAaexFu5lyb6WHM4BPmOD0UdkQQgjv9I0 mqjmqZapBu6oJaicxNnIH7Aqp+GWllwSvgAZFAwOC4TbgM5xG16HGlAyGStwFCAGToEaMDKZ ZgR4gSHOLtIMQsNFakeakYhfpBkZGplIMwqtPNCMQhyIApERj7777kid/P2pbdTty8vx7Eg9 u3o74/bD0eXHI3VnPDlrJ681Ite8UT+p++rua4OGfnOknrans+Y1wmlgsWYsb5BsJBQGiXwp pAHcEnS3m+++a9SzRv04Phk36l7zzfTqLf1h/mh8OcgDg79vm++/P8Ifrehe8xrrhJinjXrx 8hXhMUjQLekwQHxfXp2fv9lO65jWFzPICJT9iJMZ2FD2I0Z6GgDO/Wg1vs0K8fH4csaYHLPH WZl2nNlfpU6pwHX8jilBwLupAQ7qyWR8+qwF9I16cu+4USft51kzZy7WfDJ83x6puxDUXs6m cFLmRTabjq8mp+2UEyV3PWrPRsM7488NWzkiTaZiYbYnwwnmsn8T3UJRSsn7mmaFVkCJMQ0M 0NqP2NqBN2E/YqQ9fJs9iW0caKh7qG0qc6wYioLbmhsZCpquGsq4gwwlkTyFVNr7aC209dH3 iujrRrzxfoDkjyyfB5ryb0Q8YDMMmTLA1oDvoh2m93Ws32wt1iBwkdEtBTBtqHkQcWqw2Q6Q gK+bfOjwsLeHL9Pu8PB9XAt7AnavNde6rjeJMy57U7muN5n0Vb0oAapM+4Qe0DaPswP2DTTL ACewzZbrbGb0qr16APex1zLtFzLSRmL4f9iXFntF3LALbSbWEbrd0Gu2Zadru1BccyHrr+1C +Wu6EI7GA20p8VgcQehgnAcFR6VQHLaMcqgPhQN8KKxbL/gwKNbuR+y9Gbg9GTtvN503NtM6 PSgbnXMTsdaDvCdjJFkcp8x+xDiRDvw1HPlrn3rcuu86f91TjzvAP1z4invCVw5ov74nuD33 BL8Gij8g8fpDEu9GYvhgMeb/vqv6dbfy/toI7ulWh4XPbtVeBxvecNn88/mffoB6xBm1NFIi VQ9cVzqDkw/OPwZlSGHtkyONBxx4DXa4NLBNRrKPTcYzj8wwGrsKvd1gSunvucIZtR3kThZR S62m8p64SskSaw7Zzde4aXXbPt3s+Sq61XpHWnApPaJdpsN4r1c2QCiFgHqyDmXRHisrml6V RUaBZhZNiMXCqmv+IhI8+9P0TIRSz9EOQgd8JoqMh8VOsDGZu2UVXCbGS1Yeq/qqViH01hTb dHWLxFZZU3prG9Npr+8RW3Qz59RC4RPp7gOXbJt6VLCSupSdhySOcEZPyuzIglLalEgfzaOA YvWTdWZpbCu0Ex7Ckcp4FrUL42G0YYy521Yls2BBi1pN5RhsKZl9PVYtcNPStn3s2iqEq0+0 dCmlJ8ENkybAO7XYO2JmIAMpltgziM5FBrPSMyKQi4ndeNfHczvu4pqd2zJ/ogv87nIunuKR 7bRQdLVWQcDMOmtU9cp+3LtkVbvg0ZkiLFMLheOAcRLpYpBqVBSQupQLnzBaa3Kxuf1uXhJL KTb39rZe9FTEi7YgK+VGUsvJkigjGVLKLBmAS9pR69gRiioSqnjoXIClpZIpxYTIeEXUU+IM IGgiuyXOWoXeemM0cBmFT0Rk5zLgV9GaSKwmBoX8KRYOYfa7jCSASWJmMIjkk7wETvBZRJHJ YxQv93Mlt5YVZGLi9bJHv47e5TiV+UH8IldOd3ACogD5J/38k352p5/aAnSyAjaMj6MAkdIZ 2vQd/SjRBD4AbCuzL1QnbsnToYFn5tSPw90ouI0BL+nveVtacDadRKGW+oLKc9tXFBWHeW33 CvcpO47VylgDZwhILqktuqZSyDyiJ2Y7+nWOTz58uoQXIlxTIYObwhpmeBr8LQUYymh6dusI KJ3BRWNmIDnBuUIZBeZI2fKhyjNdYQzp5z6uShnzwlYkp0aj1ih4PudYsRN/c6Kr7Uu9S1Yv VEqPWIXnzWll3AdaB/14lTsrLcYEIalzCV+ziX6njlCMaj4zSjcoiUv/SYh6+t2TYJNSepKj c66bWyh5jn4kcDoTCvyOqRxOi7C3djzTcrDD0vzUQOPCT2Z2vK2W7aTnTVSOflzVcd4IJS8p vFxbtIiNd4GWMK9ZOFs9zjO4L5jIucLS/iYz5lQy5tjtXKblSn0xJsuVupQsDyby4O4aKZOn 3CKl9bJi2jN94IPulpLAdvRLGRlCeuDzwMOU+dzsSH7hJy/p7/hzKTQJ6d8s1WtKFzw/KvgF TT2qzXzNu1e7T1mvTcpOFydJikrpEd1j8HyOYK2BA501MjmUZi0QAK6jdJZo6IdU4UCPPUCH dhoe77jy7K6e6XwTDJ11REInk8sS+GhU9YRIj4s1Euv1ukc4i/Xqem156V/yCN58O2zYVt3c mifT9HaTRzq/oMxy3mI8uN6VCz96U71dohc799rp6WT0aTaeyIuex8MLjPz+64Pfj+//6+6j Oy+MxsD58P208UJxh18y3QqxuWVpc6cf/LGt0zvv6Sm9aooFlHeHn35qR+8/oJnjkSIxNHbL 0OD92fB8dHr78v1524D9s1l78Tttb0fqRTcJuy14fBhO6DXSN+q2uqPuqnvqB3WsflSP1RP1 TJ2o39VQvVWn6nR8Pr5EeXExVGeqVcxCtZdnw+kH9U69G+Hvz1a9G19N1Hv1QX34+9OH9lKN 1Ed1ri7UpbocXbZqrMYoP6lP9MLsvH03k9qEmX1qJ6PxmfpDTdRUTds/MX06+qym5yRipmYf Jm2rZn+N1ZX6U/2lPqu/1X/ayfhbgex4BEV9SPUbuC+Z4PjByctXT8QEdosJHJnA8JWTr2MC XbaaoDfAj+q+ejg3gRhgAfo62j3Wm5AWUJchXQVzM5TlECifn5wc338FKJ9uc2avO2fW+ktI ur2QjDWQzmz3Zfp16Wf1QD0CpL8A1KcM62/w7efq1Ub/Phu1k3Y6mi4c/YIdvfP39vPp+fCC DFHZ4rw3x/t2cjG8PHt7Pq3j4N+HR8Kn86spwuGPq/GsBTum6htCyC2pioUvRqLInuGzbvVo Dgqg588evPqFrb4lfnCu4PgpOX8do4etRv8Bhv4Z5hzO1rIVW4jSEtlBrLAhQFZB2gyQOwSg F3fvPPz1KQOUtgDkJCyKx87qy94AhS0ABVcDpGuAJCLuIwaedoml9/t2nslHgKlPJAQQu9UW N1rHJhyCzcPfXj5+8ALYPHu4LWfgQaLbAK27ifvcKj08ad+kcR8J4+HGlPFCvdy9KS7liq+8 N9404tdMdtCG+dPzV09+uM8mOznZZjRLiR5uHU2im6GVzYxZshk15zaz1m6z2Y5Ef7KszEFb 1t3bD27/8IiUeblVlYJl0BVLnMBwXgwLXeCMh/gfnbtEGa+3KvN2ePpRjPd2Mjxt2Qe4JvZ+ e4UtYLakcDooWz/77edfX92Gwttt58V0wd3IdNfbojdFWx9rFTTDyRZ4UP3YzubdqMvA1jj9 42p4Xu3lVYy+n7RDhNkN9m9CZm0fb6d0O2W+h183mK8uz9rJ9HQ8abfHddqyTVUXcagTJrkz nLb88/PaE8mSI9GjjfwKfjyaTGdkyIY2/YfDeQMh8Hx0Nvsw5RvkB4tfPY2viI/6C+JNJd4f Ln7lBLsq3a5JN0vSUyX9GtivnKRWpftV6fTgUEm3lfRwuPSVY8qq9HiA4ePh0lcPAqviv+R3 vhJvDhe/vqmtLCCteV6u0c+VfJ8Pl7+6D61KX/e8UKtPc+bq28PFr+4Kq+LXXM+5JfRDpf2G /Zeu10zpfs0VbSOLuzKpuwr9YHQ2pZu+cuXFdhfOrJUbPVau1DQ2dt+J+99cR4bTcpXGaeHt uvuKTi5BQi+53O3kdtL1ZHi5y+UkAzVOjsSNSx3v1MkuN5DR/StCf+29v6Pc3zrtL+1199R2 ybDbZPQ3tLoLTDt5xLkRresA7pSXaOyv2/X3o1aY/XI1O8eOOu1crOn8jTyM/62GWyIKKbef OsJG31jTReZtUMpBdqFPl7SeTNo/+Z9yas+U2f3/SNBsu2M2/dMOtx7THat+TSu8TM/LlLzE y5S4Tm9KWtD7Ffo64Pm/iGpAdA3ILbPK1i3Y6h0qrWgUaon9gkXivLVFYi5ziTkuSexlCIZu Ewo5LCYvW6Cn72ZnvWn2AvOUd83uVWdt6d+t1nmlhT2S38nLLvHatK60MELSu3j1O5vwSpsQ igt4Y9zJyy/xspt4LdCOO9Huj1rCK+ZNvBbYh53YhyXs4ybswwL7sBP7sIR93IR9WGAfdmLv l7BfHFv+C9wKDDcKZW5kc3RyZWFtCmVuZG9iago1MTMgMCBvYmogPDwKL0F1dGhvcigpL1Rp dGxlKCkvU3ViamVjdCgpL0NyZWF0b3IoTGFUZVggd2l0aCBoeXBlcnJlZiBwYWNrYWdlKS9Q cm9kdWNlcihwZGZUZVgtMS40MC4xMikvS2V5d29yZHMoKQovQ3JlYXRpb25EYXRlIChEOjIw MTUwNzMwMTA1MDA1LTA0JzAwJykKL01vZERhdGUgKEQ6MjAxNTA3MzAxMDUwMDUtMDQnMDAn KQovVHJhcHBlZCAvRmFsc2UKL1BURVguRnVsbGJhbm5lciAoVGhpcyBpcyBwZGZUZVgsIFZl cnNpb24gMy4xNDE1OTI2LTIuMy0xLjQwLjEyIChUZVggTGl2ZSAyMDExKSBrcGF0aHNlYSB2 ZXJzaW9uIDYuMC4xKQo+PiBlbmRvYmoKNDc3IDAgb2JqIDw8Ci9UeXBlIC9PYmpTdG0KL04g NzIKL0ZpcnN0IDYwNgovTGVuZ3RoIDIzMTMgICAgICAKL0ZpbHRlciAvRmxhdGVEZWNvZGUK Pj4Kc3RyZWFtCnjanVrbjhw3Dn2fr6hHzwKZESnqBhgGggQBgs06wV6eAj90ksbsALbHmGkv kr9fUlJVSVVUtRMESKlJkefwIrGm20BxMhMQTcHzg5cOJ7B+QiB+4mQxTYBxsgn4SRP5wE8z ObITgJ+8cfzEKUC6ARPZDesNTTGyL2OmRDAlL0t+smuTEuvYBZgpMgT6OMlWC7ZQQJgC76OQ blgFzpnJ8z7Pvj3vC8ZOjvdFxhSq0YWJY4DEHzgKNGgnDgNNoimH4R3HMCGiveEw0MoH3kdG NvNTQHmfEyes8sD8+BHcxBuCNRMF/hzFbUgTJv4fMWHmizcUgZ1HVkXOFFnghZ2sy3sYPzAY RSYQ+RNFz8ysLJgyGtkcmTPJHjbw7IMS4yWmSpxuBy7Jp8nZJCoJXCA4MheZNiU3eQB2xgn2 1rGzFCbvOA2UOFvBiCpNPrLYcS0CGHfjGDhIVZ3hqglVxykN0cqC62bYmeOiRguRF56rJKlm X5EJ8YLr5bM5JyoQS6SSbH7jAKaYLFuxQUwu3bx+fXP/78fL+zPXM3Gf/fPm/mte+rL86fR8 /njJ3VY+P5//l1sxf3p7/v2Su1E+vXnT+XKrLzz0ZVpfudV3vmDxZaPuq1qTYm3Dak2ddcKW CHSuYgX67vH55bKy/OEkn2L1883TZ3bzFeAW0q6QpicMXfCohYtrGdAfWndlsFoZcC0D4qGv rgw6r7UMEHVf1VorA6xlgKMymNgF5bsyYFeGGvFcBtoirlWATRWMFp9Z8278mGHqYoWeIGBL EHqCsAVci2P64qSuNsZobJdqpKjaFn5GqUVaSpH0SlTT/giYLvemPwKbE5CW1Kc+83KVr5H5 rulm9II3h1FPXOzgXA8Xl8rFvnAzQEaLShrjUoLYV0DdvKQ8xDGMb09lf43M90aOaXuJ9Fhh qVHoazS7z1hBOfNhyX0wY0vfHrNalM6NX3LqveqmWCoE/JJTj2qaSmZMm5mZTs7M3CM1M3bj fqmCiwe9Zdte7lvLd2WIR2BuKYPry6ANPbdk3vWZt+39QV1LuLbNnT9qiXU8b6Zz774tj8Zy ncybwdy7aWulTeV1KG9mcuemm8/aeF6n82Y4d/Uj5TSuQ9Ye3THYNrrvms52ucejG2adyZuR vAFrk68N5HUeb8bxxk+bfW0YN7P46BB0c1kdy+tUpgM/bVioTaN11G5q0d6/yiRabgrNqr5N KAdtQdM5F8NuMrf3y2YsL7Pr7enD+WX6+dW3T79+9a/L6flyK3+byN7p1feX84c7YEGp6iww LImhlciecqfMEhRJaiWWJWUwvmNKjx8eLxvYZd+7LbeiIHEArUsnko6aF4ltJUEk1EqiSFwr Sbd8nOyW2oK67NKJSai2xUROkIWWF4JIuj0okpYXcoKonOpZQiIBlRferpsGtJxYdyy8SFoW UhPbkpAc2zY3kuLYOpEMRz1Xgjhv0jlJMWKLJ7WILV4SQW2/T6eHc24/cK1AsouxlUh2rc6J EZdNO05FIZUgbP1ZkaRWwnmxrqPFsVofWglnxgbbShjcxl39FtRl14AYJ8emjhhnh4xpJNJ7 2LKQ3iPTcpfeI2i5S+9RuYr3vOLtukvnlRu1B82N2kmk+bqk5uajdk9uPmgE0nxlUO9oCea8 SWcljerbPsmN2rqXapiWkuQX2h1yD+CS3ufTw/Pp03/v7J3h//I16FVy7lbbrtDcbJF71OEA TvCcHSil7I4GSsmrcwOl5Hht5I1Sclhe/voY97w12+sBS0lcHIDL3eBHzOSeWE/bRil3hh+4 zZdzGuikAOWV/zBef6vaXo1XTh6GQT9hruGImdQwwEApNQyDvpGDh2HQN3IGsfxpdRSw8NZs rwcsNQyD1kOpYRgUWOKlQabytTCwk2hp0BcSbHmJPww23GqmV2OVUGlQPonUDaKRZnW7yvo7 vAO5YywOdDKlEHWdzCu01yLtA50tDwItW2T04S7QwPdMZWxJVdqsJDtQSjz7HGUlZUsXFCVV TH9Q14W2ZnoQbtmTb3oyqINndAKja7FoQdViIZ5UZUlWIFVZ8hHcOOSGumZ8LWiXAaIes8ul inaglN6LOm9f3DpVGbIy2YFSMBNdidhpAYvttYBjAdeZpdIBuyqyUSztR2gHyvxmFQdKSZUb KeUVCtOVgOMm4MX2IOC6J/81UMFfzr9eHp8+/i1nYSPiCMJGxLznnq4yMZxfyheRTFNzcC5X Iq3NjvmsYyKQeoj8xtiL8izsRfJmvqHLo8BtfPFtmHav5g12s3FIMQrFDZTc76aeh5fPvyyk yp2myHOnK/L856Ail0YJI+Ly9r7ZvWff6jlZ8zRq5PnkeqvIpT2SIme281cCjTzkt1EAp2k4 ELC7S23Lbmd0FE/I77CgMmG4pPEQA7M3iPmlE1qTjplkwqlKXy4JHw5CK0RVQzW+fpMUAUbQ nPAw4JVHULSassxzqVUaquVE4thaKo1q0Dv2uvmVyMu7gTQNDDjkQQk2jdV8R4GenTrfRX9g LykYJpByhsgep2AOQ7e/ngPKiaYwJCEpcuMUSb+7cQq8qMcZ4GsT/DgBcmR8uJqAHINu/yUJ SFKlQYS5CCmNlJIcM+DvygFQHZfhJRdC+oLo0u3Afonu74+/sS2V39Tyv+DIz/ID0UT1iwuq 72S0/8at/eJ09z1S9V7fy6i+glH9Yo3q/Uj1K1uK6ei7oPHfgRUmVdJ1FFL9zorqyx3Vr18p uT/5x9j+9WZGrIGkGkiqgdS6u/odmTPwZa8jh7dRwXT1TwJXu8cZ+kvnXG8EV34Wz/+upTxD fcb6TEcNcAzx7fmFLRz0v2H88ek83X9zupzePz3IrwkPfNoo1F8Zfvx8ef/4MUvmnxfycXSw /PrwcP7H02/n+/+8nOfNWfjD6Zfz+5fXr+/ffv7w8rPhxU+v4PbNG8gr5BXmleWVzSviFeWV 45XLK88rn1eBVyGvIq9iXiVepeLZiOuKkmEKDggQFCQQKChYIGBQ0EDgoOCBAEJBBIGEggkC CgUVBBYKLgouFlwUXKzx5QALLgouFlwUXCy4KLhYcFFw33FJ7n/8dP74da7fhDXJLP4/3hPF qwplbmRzdHJlYW0KZW5kb2JqCjUxNCAwIG9iaiA8PAovVHlwZSAvWFJlZgovSW5kZXggWzAg NTE1XQovU2l6ZSA1MTUKL1cgWzEgMyAxXQovUm9vdCA1MTIgMCBSCi9JbmZvIDUxMyAwIFIK L0lEIFs8QTVDNjVCNTA5QUYyODdGRTZENDA3MTdDMTVFQzEyQjI+IDxBNUM2NUI1MDlBRjI4 N0ZFNkQ0MDcxN0MxNUVDMTJCMj5dCi9MZW5ndGggMTIyMSAgICAgIAovRmlsdGVyIC9GbGF0 ZURlY29kZQo+PgpzdHJlYW0KeNolljtwlkUUhvcs4RYgFwiES7hGCBASbuGSbC5ASAIkBAIB EsIlJI2VFjo2zsiMDQV2nsrKcYYZC0ftbGwsmGHmdI4WFutY2Vg7Fo6j//PaPNnzfvt9/+6e 95xNSin9m1PKyVJqbfxJsaExrm+hGchoG9G6CdeAJrQtaIcI14J1aO1oBwnXgw1oO9AOEG4E zWidaPsJN4HNaJfQ9hFuAS1ol9H2EraCNrQraF2E7WAr2hzaHsJtoAPtDtpuwu1gB9oi2i7C TrAT7SEao6wHvBFLaJqij/Jr8QiNr2QtiJXGYzR9Xpthl/EEjRVkHQQnFE/RtDQdYuN0raxB Y/X5MDiC1oSmbfWAo2hr0dh5PgaOo21H05H0ghNoOmdOLfeBfjSds47zJDiFthONE8+nwRm0 XWhKxVkwgLYXjWzlc+A82j40pfECuIi2H41M50EwhHYATRYoYBjtGBouySNgFI3NVNlnDGCB wg9VHJYvA9Jd5A1ZbxxcRZM3cGeeAJNo42iy7RS4hgYqzs7XwQ004KuE02AGDQ/5CuFNMIt2 D+0Z4S1wG42c+zLhHMBmZRntKeFdME+YwRPCe+A+Ifn1x4QPwAIhteWPCBcBdvRNYIlQwHq+ FTwk1AewmZNf12v6cS2D/PoCoRa+Qkh+XT/JpqNR7AOqee8D99E4tdCacY6z5uDEQ8VOjqLZ 0tpZ9QgV+3rmXQccsZMAnwIcp+uIZ5mnSt5kqfm53lWxU1bRaqmlU5oKW5VMkYTql7IKbWYC kJSgQkMVSg3GCdBlqWNRX1FJUoihQqT8QuVH0QUtLSi1OAIosDgKKKs4DiimOA/6ATUTmDX6 LO3+Rb9xClA4cQZQLjEAKJKgKuIioBZiCFABQQU4XgsMEqOWupv0PXwfmDquAqwckwADxzWA beMG0AdmgE5Dp4sx4zZQypRLMh1kP+Yt9fx/ODgiZJBbOJYuX7BeaQZK6Iqlvvc0eRUNgxQD 2dLzHxRizNIG1lsaWpC2GXAblBbQCjBr2Q3aLY290rxtoAMcAnssTfyoB13gIFBjPAzUDnuA mlu3pemPNFk9sReow50Fp0EjR3O/acpJQK9zFay6mVrVGUuL72rKOXCBKbSqoqZVgFrVCFCD wnpl0NLyX3ptDKgjqQWpb0xaevtzPcX8hYIo00AdRIf9ANy09M6M5mlV6ht3Ad2i0B4K11Oh ARQuoELplgVL77fpNbpAoewL10l5xupVxOsIVy19OKyQlDm3i3N1+Jzl1y/0gMw4ifJG8l6M ScMHjgWcNDqpdRLlLZY++UdTuNSdG8e5EnwP6LD06ZKecu04mXZS5o1q/OyZHnBXOJeDk1on 594NSLKTZKf9e4+lL17rDVLrXBNOBr3X0quP9QALOAfm3FZ+ytKXv+sBiXcs4CTZyapzf7hS S859EJBfL5a++lqvDVv681uNRsz6v9Fo1OzldxqNmX3/RqNLZn/c0eiy5ZEpja5YXnip0bjl D2Y1wgxOLn3e8s9ac2WDlSOpuLiyt6orUHceBq5sq9KBK1aubLpi28q2Klut7K2yt8requ5G 9lbZW2Vvlb1VvFvxbsW7Fe9WzFp1c+qq1P9NuiBZbsXZlZ5dpyz/NJ4s//p3+g8gVGM2CmVu ZHN0cmVhbQplbmRvYmoKc3RhcnR4cmVmCjE4ODE1NQolJUVPRgo= --------------070001080000080004060304 Content-Type: application/x-tex; name="dcgdraft-2015-07-30.tex" Content-Transfer-Encoding: 7bit Content-Disposition: attachment; filename="dcgdraft-2015-07-30.tex" \documentclass{article} \usepackage[utf8]{inputenc} \usepackage{fontenc} \usepackage{hyperref} \usepackage{verbatim} \hyphenation{Pro-log} \newcommand{\tab}{\hspace*{2em}} \newcommand{\code}[1]{\texttt{#1}} \newcommand{\codenl}[1]{\texttt{#1}\\} %\newcommand{\code}[1]{\small \texttt{#1}\normalsize} %\newcommand{\codenl}[1]{\small \texttt{#1}\normalsize\\} \newcommand{\bypassop}{\{\}} \newcommand{\superop}{{\large \textasciicircum \textasciicircum}} \newcommand{\notop}{$\backslash$+} \newenvironment{squote}{\begin{quote}\small}{\normalsize\end{quote}} \renewenvironment{quote}{\begin{list}{} {\setlength{\leftmargin}{\parindent}}{\setlength{\rightmargin}{\leftmargin}} \item[]}{\end{list}} \begin{document} \pagestyle{headings} \title{ ISO/IEC DTR 13211--3:2006\\ Definite clause grammar rules} \author{ Editor: Jonathan Hodgson\\ Email: jpehodgson@verizon.net\\} \date{\today} \maketitle \setcounter{secnumdepth}{-1} \section{Introduction} This technical report (TR) is an optional part of the International Standard for Prolog, ISO/IEC 13211. Prolog manufacturers wishing to implement Definite Clause Grammar rules in a portable way should do so in compliance with this technical report. Grammar rules provide convenient functionality for parsing and processing text in a variety of languages. They have been implemented in many Prolog processors. %Klaus: find "variety of languages" OK This TR is an extension to the ISO/IEC 13211--1 Prolog standard, adopting a similar structure. In particular, this TR adds new subclauses to, or modifies existing subclauses of ISO/IEC 13211--1. \medskip \subsection{Previous editors and draft documents} \begin{itemize} \item Klaus D\"{a}{\ss}ssler: \textsl{ISO/IEC 13211 -- 3: 2015 Grammar rules in Prolog}, ISO, 2010-2015 \item Paulo Moura: \textsl{ISO/IEC DTR 13211-- 3:2006 Grammar rules in Prolog}, ISO, 2006-10 \item Roger Scowen: \textsl{N171 --- ISO/IEC DTR 13211--3:2004 Grammar rules in Prolog}, ISO, 2004-05 \item Tony Dodd: \textsl{DCGs in ISO Prolog --- A Proposal}, BSI, 1992 \end{itemize} %\subsection{Draft document comments} %\begin{itemize} % \item Paulo Moura: \textsl{Portuguese comments on ISO/IEC DTR 13211--3: 2004: Grammar Rules in Prolog}, IPQ CT 167 WG17, 2005 % \item Klaus Daessler: \textsl{German comments on ISO/IEC DTR 13211--3: 2004: Grammar Rules in Prolog}, DIN NI22 WG17, 2005 %\end{itemize} \newpage \subsection{Contributors} \textsl{This list needs to be completed; so far we have only included people present at the ISO meetings collocated with the ICLP (2005, 2006, and 2007), Richard O'Keefe, and the authors of the drafts cited above.} \begin{itemize} \item Bart Demoen (Belgium) \item David Warren (USA) \item Jan Wielemaker, (Netherlands) \item Joachim Schimpf (UK) \item Jonathan Hodgson (USA) \item Jose Morales (Spain) \item Katsuhiko Nakamura (Japan) \item Klaus D\"{a}{\ss}ler (Germany) \item Manuel Carro (Spain) \item Manuel Hermenegildo (Spain) \item Mats Carlsson (Sweden) \item Mike Covington (USA) \item Paulo Moura (Portugal) \item Per Mildner (Sweden) \item Peter Szabo (Hungary) \item Peter Szeredi (Hungary) \item Pierre Deransart (France) \item Richard O'Keefe (NZ) \item Roger Scowen (UK) \item Tony Dodd (UK) \item Ulrich Neumerkel (Austria) \item Victor Santos Costa (Portugal) \end{itemize} \setcounter{secnumdepth}{+4} \section{Scope} This TR is designed to promote the applicability and portability of Prolog grammar rules in data processing systems that support standard Prolog as defined in ISO/IEC 13211--1:1995 and, if supported by the processor, in ISO/IEC 13211--2:2000, and the two Corrigenda of 13211-1: ISO/IEC 13211-1 Technical Corrigendum 1:2007-11, and ISO/IEC 13211-1 Technical Corrigendum 2:2012-02. This TR specifies: \newcounter{Lcount} \begin{list}{\alph{Lcount})}{\usecounter{Lcount}} \item The representation, syntax, and constraints of Prolog grammar rules \item A logical expansion of grammar rules into Prolog clauses \item A set of built-in predicates for parsing with grammar rules \item A reference implementation. % \item Reference implementations and tests for the specified built-in predicates and for a grammar rule translator \end{list} %Klaus: In my opinion NOTE 2 should remain, because the requirements of pt 1 are fundamental to DTR DCGs, % but what pt 1 excludes to define has to be explicit in DCGs \noindent NOTE --- The scope, expressed in clause 1, Scope, of ISO/IEC 13211--1:1995 applies to this TR. \section{Normative references} The following TR contains provisions which, through reference in this text, constitute provisions of this TR as Part of ISO/IEC 13211. \begin{itemize} \item ISO/IEC 13211-1:1995 \item ISO/IEC 13211-2:2000 \item Corrigendum 1 of 13211-1:2006 \item Corrigendum 2 of 13211-1:2012 \end{itemize} \section{Definitions} \textsl{For the purposes of this TR, the following Definitions are added to the ones specified in ISO/IEC 13211--1:} \def\theparagraph{\arabic{section}.\arabic{paragraph}} \paragraph{alternative:} A compound term with principal functor \code{(;)/2} or with principal functor \code{('|')/2} with each argument being a body (of a grammar-rule). \paragraph{body (of a grammar-rule):} See \code{grammar-rule-body} \paragraph{clause-term:} A read-term \code{T.} in Prolog text where \code{T} has neither principal functor \code{(:-)/1} nor principal functor \code{(-->)/2.} (This definition replaces subclause 3.33 of ISO/IEC 13211--1). \paragraph{comprehensive terminal-sequence:} see terminal-sequence, comprehensive. \paragraph{cover, a terminal-sequence by a non-terminal (resp. a body):} A terminal sequence is covered by a non-terminal (resp. a body) if the non-terminal (resp. the body) generates the terminal sequence. Alternatively if the non-terminal (resp. body) parses the terminal sequence. \paragraph{definite clause grammar:} A definite clause grammar is a set of definite clause non-terminal definitions. \paragraph{definite clause non-terminal definition:} A definite clause non-terminal definition is a sequence of grammar-rules. \paragraph{expansion (of a grammar-rule):} The preparation for execution (cf. ISO/IEC 13211--1, subclause 7.5.1) of a grammar rule. % JPEH Is this right? % KD I think so! \paragraph{generating (wrt a non-terminal and a definite clause grammar):} Producing a terminal-sequence of that definite clause grammar, obeying semicontexts, if any. % \paragraph{grammar-body-choice:} A compound term with principal functor \code{(->)/2}. The first argument is a body (of a grammar-rule), and the second argument is a body. \paragraph{grammar-body-element:} A grammar-body-cut (the atom \code{!}), or a grammar-goal, or a non-terminal, or a terminal-sequence. \paragraph{grammar-body-not:} A compound term with principal functor \code{($\backslash$+)/1} whose argument is a body (of a grammar rule). \paragraph{grammar-body-sequence:} A compound term with principal functor \code{(',')/2} and each argument being a body (of a grammar-rule). \paragraph{grammar-goal:} A compound term with principal functor \code{\{\}/1} whose argument is a goal. \paragraph{grammar-rule:} A compound term with principal functor \code{(-->)/2}. \paragraph{grammar-rule-body:} A compound term which forms, or is in the form of, the second argument of a grammar-rule. A grammar-body-sequence, or an alternative, or a grammar-body-not, or a grammar-body-element, or a grammar-goal. % the next definition is changed JPEH. \paragraph{grammar-rule-head:}\label{defGrammarRuleHead} The first argument of a grammar-rule. Either a non-terminal (of a grammar), or a compound term whose principal functor is \code{(',')/2}, where the first argument is a non-terminal (of a grammar), and the second argument is a semicontext (cf Definition \ref{defSemiContext}). \paragraph{new variable with respect to a term T:} A variable that is not a member of the variable set of \code{T}. \paragraph{non-terminal (of a grammar-rule):} A callable term (cf. ISO/IEC 13211--1, Definitions 3.25), i.e., an atom or a compound term, that denotes a non terminal symbol of a grammar rule. \paragraph{non-terminal indicator:}\label{defNonTerminalInd} A compound term \code{A//N} where \code{A} is an atom and \code{N} is a non-negative integer, denoting one particular non-terminal (cf \ref{ssection:nonterminalIndicator}). \paragraph{parsing (wrt. a definite clause grammar):} Successively accepting or consuming terminal-sequences, assigning them to corresponding non-terminals and obeying semicontexts, if any. \paragraph{remaining terminal-sequence:} See terminal-sequence, remaining. \paragraph{semicontext:}\label{defSemiContext} A terminal-sequence occurring optionally after the non-terminal of a grammar-rule-head, constraining parsing (respectively generation) by this grammar rule. \paragraph{steadfastness of a goal wrt. an argument} Goal \code{G} is steadfast with respect to argument \code{n} of its sequence of arguments, if for any term \code{T} that is the \code{n}th argument in the goal, and the goal \code{Gnw} that results by replacing \code{T} by a new variable \code{Vnw} the execution (cf. ISO/IEC 13211--1, subclause 7.7.1) of \code{G} and \code{(Gnw, Vnw=T)} is the same. \paragraph{terminal (of a grammar):} Any Prolog term that denotes a terminal symbol of the grammar. \paragraph{terminal-sequence:}\label{defTerminalSequence} A list (cf. ISO/IEC 13211--1, subclauses 3.99, 6.3.5 and 6.3.1.3) whose first argument, if any, is a terminal (of a grammar), and the second argument, if any, is a terminal-sequence. \paragraph{terminal-sequence, comprehensive:} A terminal sequence containing a prefix, and the prefix covered (cf. Definition 3.5) by a grammar-rule-body, i.e. accepted resp. generated by \code{phrase/3} (cf \ref{sssection:phraseSpecification}) . \paragraph{terminal-sequence, remaining:} The rest of a comprehensive terminal-sequence without the leading terminal-sequence covered (cf. Definition 3.5) by a grammar-rule-body. \paragraph{variable, new with respect to a term T:} See \textsl{new variable with respect to a term \code{T}}. \newpage \section{Symbols and abbreviations} NOTE --- No changes from the ISO/IEC 13211--1 Prolog standard. \section{Compliance} \subsection{Prolog processor} \label{strictMode} \noindent A conforming Prolog processor shall: \begin{list}{\alph{Lcount})}{\usecounter{Lcount}} \item Correctly prepare for execution Prolog text which conforms to: \renewcommand{\labelenumi}{\theenumi.} \begin{enumerate} \item the requirements of this TR, and \item the requirements of ISO/IEC 13211--1, and \item the implementation defined and implementation specific features of the Prolog processor, \end{enumerate} \item Correctly execute Prolog goals which have been prepared for execution and which conform to: \begin{enumerate} \item the requirements of this TR, and \item the requirements of ISO/IEC 13211--1, and \item the implementation defined and implementation specific features of the Prolog processor, \end{enumerate} \item Reject any Prolog text or read-term whose syntax fails to conform to: \begin{enumerate} \item the requirements of this TR, and \item the requirements of ISO/IEC 13211--1, and \item the implementation defined and implementation specific features of the Prolog processor, \end{enumerate} \item Specify all permitted variations from this TR in the manner prescribed by this TR and by the ISO/IEC 13211--1, and \item Offer a strictly conforming mode which shall reject the use of an implementation specific feature in Prolog text or while executing a goal. \end{list} \noindent NOTE --- This extends the corresponding subclause of ISO/IEC 13211--1. \subsection{Prolog text} \noindent NOTE --- No changes from the ISO/IEC 13211--1 Prolog standard. \subsection{Prolog goal} NOTE --- No changes from the ISO/IEC 13211--1 Prolog standard. \subsection{Documentation} \noindent \textsl{The corresponding subclause in the ISO/IEC 13211--1 Prolog standard is modified as follows:}\\ \noindent A conforming Prolog processor shall be accompanied by documentation that completes the definition of every implementation defined and implementation specific feature specified in this TR and in ISO/IEC 13211--1 Prolog. \subsection{Extensions} \noindent \textsl{The corresponding subclause in the ISO/IEC 13211--1 Prolog standard is modified as follows:}\\ \noindent A processor may support, as an implementation specific feature, any construct that is implicitly or explicitly undefined in this TR or in the ISO/IEC 13211--1 Prolog standard.\\ \noindent A Prolog processor may support additional grammar control constructs, beyond the required ones by this standard (cf. \ref{ssection:controlConstructs}). These additional control constructs must be treated as non-terminals by a Prolog processor working in a strictly conforming mode (see \ref{strictMode}e). \medskip \noindent NOTE --- Examples for additional grammar control constructs include \textsl{soft-cuts} and control constructs that enable the use of grammar rules stored on encapsulation units other than modules, such as objects. \setcounter{subsubsection}{1} \subsubsection{Predefined operators} \textsl{See subclause \ref{ssection:grammarRuleOperator} for the new predefined operators that this TR adds to the ISO/IEC 13211--1 Prolog standard.} \section{Syntax} \subsection{Notation} \subsubsection{Backus Naur Form} \noindent \textsl{No changes from the ISO/IEC 13211--1 Prolog standard.} \subsubsection{Abstract term syntax} \textsl{The text near the end of this subclause in the ISO/IEC 13211--1 Prolog standard is modified as follows:}\\ \noindent Prolog text (6.2) is represented abstractly by an abstract list \code{x} where \code{x} is: \begin{list}{\alph{Lcount})}{\usecounter{Lcount}} \item \code{d.t} where \code{d} is the abstract syntax for a directive, and \code{t} is Prolog text, or \item \code{g.t} where \code{g} is the abstract syntax for a grammar rule, and \code{t} is Prolog text, or \item \code{c.t} where \code{c} is the abstract syntax for a clause, and \code{t} is Prolog text, or \item \code{nil}, the empty list. \end{list} \noindent \textsl{The following subclause extends, with the specified number, the corresponding ISO/IEC 13211--1 subclause.} \setcounter{subsubsection}{2} \subsubsection{Variable names convention for terminal-sequences} \label{sssection:variableNameConvention} This TR uses variables named \code{S0}, \code{S1}, ..., \code{S} to represent the terminal-sequences used as arguments when processing grammar rules or when expanding grammar rules into clauses. In this notation, the variables \code{S0}, \code{S1}, ..., \code{S} can be regarded as a sequence of states, with \code{S0} representing the initial state and the variable \code{S} representing the final state. Thus, if the variable \code{Si} represents the terminal-sequence in a given state, the variable \code{Si+1} will represent the remaining terminal-sequence after parsing \code{Si} with a grammar rule.\\ \subsection{Prolog text and data} \noindent \textsl{The first paragraph of this subclause on ISO/IEC 13211--1 is modified as follows:}\\ \noindent Prolog text is a sequence of read-terms which denote (1) directives, (2) grammar rules, and (3) clauses of user-defined procedures. \subsubsection{Prolog text} \noindent \textsl{The corresponding subclause in the ISO/IEC 13211--1 is modified as follows:}\\ \noindent Prolog text is a sequence of directive-terms, grammar-rule terms, and clause-terms. \begin{tabular}{l l l l} ~ & \code{prolog text =} & \code{p text} & ~\\ Abstract: & \textsl{pt} & \textsl{pt} & ~\\ ~ & \code{p text =} & \code{directive term ,} & \code{p text}\\ Abstract: & \textsl{d.t} & \textsl{d} & \textsl{t}\\ ~ & \code{p text =} & \code{grammar rule term ,} & \code{p text}\\ Abstract: & \textsl{g.t} & \textsl{g} & \textsl{t}\\ ~ & \code{p text =} & \code{clause term ,} & \code{p text}\\ Abstract: & \textsl{c.t} & \textsl{c} & \textsl{t}\\ ~ & \code{p text =} & \code{;}\\ Abstract: & \textsl{nil} \end{tabular} \def\theparagraph{\arabic{section}.\arabic{subsection}.\arabic{subsubsection}.\arabic{paragraph}} \paragraph{Directives} ~\\ \noindent \textsl{Syntactically, there are no changes w.r.t. ISO/IEC 13211--1 Prolog standard, with the exception of the operator syntax (cf \ref{ssection:grammarRuleOperator}). For the semantic changes see \ref{sssection:prologDirectives} of this TR. Whenever directives are applicable to non-terminals, the non-terminal indicators (cf \ref{ssection:nonterminalIndicator}), as arguments of these directives, shall be used like predicate indicators for the predicates, resulting from expanding these non-terminals.} \medskip \noindent NOTE --- The directives \code{dynamic/1, multifile/1 and discontiguous/1} are applicable to non-terminal indicators. \def\theparagraph{\arabic{section}.\arabic{subsection}.\arabic{subsubsection}.\arabic{paragraph}} \paragraph{Clauses} ~\\ \noindent \textsl{The corresponding subclause in the ISO/IEC 13211--1 is modified as follows:}\\ \begin{tabular}{l l l} ~ & \code{clause term =} & \code{term, end}\\ Abstract: & \textsl{c} & \textsl{c}\\ Priority: & 1201\\ Condition: & The principal functor of \code{c} is not \code{(:-)/1}\\ Condition: & The principal functor of \code{c} is not \code{(-->)/2}\\ \end{tabular} \medskip \noindent NOTE --- Subclauses 7.5 and 7.6 define how clauses become part of the database.\\ \noindent \textsl{The following subclause modifies, with the specified number, the corresponding ISO/IEC 13211--1 subclause:} \def\theparagraph{\arabic{section}.\arabic{subsection}.\arabic{subsubsection}.\arabic{paragraph}} \paragraph{Grammar rules} ~\\ \begin{tabular}{l l l} ~ & \code{grammar rule term =} & \code{term, end}\\ Abstract: & \textsl{gt} & \textsl{gt}\\ Priority: & 1201\\ Condition: & The principal functor of \code{gt} is \code{(-->)/2}\\ \\ ~ & \code{grammar rule =} & \code{grammar rule term}\\ Abstract: & \textsl{g} & \textsl{g}\\ \end{tabular} \\ \medskip \noindent NOTE --- Subclause \ref{section:logicalExpansion} of this TR defines how a grammar rule in Prolog text is expanded into an equivalent clause when Prolog text is prepared for execution. \pagebreak % inserted to avoid a widow \def\theparagraph{\arabic{section}.\arabic{subsection}.\arabic{subsubsection}.\arabic{paragraph}} \paragraph{Semicontexts} ~\\ \begin{tabular}{l l l} ~ & \code{semicontext term =} & \code{term}\\ Abstract: & \textsl{sc} & \textsl{sc}\\ Priority: & 1201\\ Condition: & semicontext term is a list\\ \\ ~ & \code{semicontext =} & \code{semicontext term}\\ Abstract: & \textsl{s} & \textsl{s}\\ \end{tabular} \medskip \noindent NOTE --- Subclause \ref{section:logicalExpansion} of this TR, \code{dcg\_rule/4}, first clause, defines how a semicontext in a grammar rule is expanded when Prolog text is prepared for execution. % Modified JPEH. % Accepted and corrected KD \subsection{Terms} \label{ssection:grammarRuleOperator} \noindent Extend the operator table of subclause 6.3.4.4 of ISO/IEC 13211--1 as follows: \\ \begin{tabular}{l l l} \code{Priority} & \code{Specifier} & \code{Operator(s)} \\ 1105 & \code{xfy} & \code{'|'} \\ \end{tabular} \medskip \noindent NOTE --- The operator \code{(-->)/2}, specified in subclause 6.3.4.4 of the ISO/IEC 13211--1 Prolog standard, is used as the principal functor of grammar rules. \section{Language concepts and semantics} \noindent \textsl{The following subclause extends, with the specified number, the corresponding ISO/IEC 13211--1 subclause:} \setcounter{subsection}{3} \subsection{Prolog text} \label{ssection:prologText} \setcounter{subsubsection}{1} \subsubsection{Directives} \label{sssection:prologDirectives} A non-terminal indicator may appear anywhere that a predicate indicator can appear in the following directives: \code{dynamic/1, multifile/1}, and \code{discontiguous/1}, as specified in subclause 7.4.2 of the ISO/IEC 13211--1 Prolog standard. \setcounter{subsubsection}{3} \subsubsection{Grammar rules} A grammar rule term in Prolog text (6.2.1.3) enables suitable clauses to be added to the database.\\ \noindent The non-terminal indicator NT//N of the non-terminal of the grammar-rule-head shall not be the non-terminal-indicator of a grammar control construct, and the predicate indicator NT/M where M is N + 2 shall not be the predicate indicator of a built-in predicate or a control construct.\\ % no mixing remark! multifile, discontiguous geeignet verweisen oder wiederverwenden. \noindent During preparation for execution the Prolog processor converts grammar rule terms to Prolog procedures of the database. Section 10 of this TR defines a correspondence between grammar rule terms and suitable clauses of a procedure in the database. \subsection{Database} \subsubsection{Preparing a Prolog text for execution} If a Prolog grammar rule with non-terminal indicator NT//N is prepared for execution, and a Prolog clause with predicate-indicator NT/M, where M is N + 2, is already part of the extended database, or vice versa, then the effect of this preparation for execution shall be implementation dependent.\\ \setcounter{subsection}{12} \subsection{Grammar rules} \subsubsection{Terminals and non-terminals} \def\theparagraph{\arabic{section}.\arabic{subsection}.\arabic{subsubsection}.\arabic{paragraph}} In grammar rule bodies, one or more terminals are represented by terms directly contained in lists in order to distinguish them from non-terminals. The empty terminal sequence (empty list) is possible. Non-terminals are represented by callable terms.\\ \medskip \noindent NOTE --- In the context of a grammar rule, \textsl{terminals} represent tokens of some language, and \textsl{non-terminals} represent sequences of tokens (see, respectively, Definitions 3.23 and 3.17). \begin{comment} String notation may be used as an alternative to lists when the terminals are characters and the flag "double\_quotes" has value "chars"; see subclauses 6.3.7 and 6.4.6 of ISO/IEC 13211--1. \noindent Using the values \code{"codes"} and \code{"atoms"} for String notation of terminals shall be implementation specific. \end{comment} \paragraph{Example} \ \vspace{1em} \noindent A simple grammar consisting of 11 grammar rules, parsing or generating terminal sequences of the form \begin{quote} \begin{verbatim} [the, dog, runs] [the, dog, barks] [the, dog, bites] [the, nice, cat, barks] \end{verbatim} \end{quote} \noindent is given by: \begin{quote} \begin{verbatim} sentence --> noun_phrase, verb_phrase. verb_phrase --> verb. noun_phrase --> article, noun. noun_phrase --> article, adjective, noun. article --> [the]. adjective --> [nice]. noun --> [dog]. noun --> [cat]. verb --> [runs]. verb --> [barks]. verb --> [bites]. \end{verbatim} \end{quote} \noindent Here the symbols \code{sentence, verb\_phrase, verb} etc. denote non-terminals, whereas \code{runs, nice, cat} etc. denote terminals. \subsubsection{Format of grammar rules} A grammar rule has the format: \begin{quote} \begin{verbatim} GRHead --> GRBody. \end{verbatim} \end{quote} where \code{GRHead}, the grammar-rule-head (cf. Definition 3.15), can be rewritten by \code{GRBody}, its grammar-rule-body (cf. Definition 3.14). The head and the body of grammar rules are constructed from \textsl{terminals} and \textsl{non-terminals}, including special non-terminals, the \textsl{grammar control constructs}. The grammar-rule-head is a non-terminal, or a non-terminal, followed by a terminal-sequence (a \textsl{semicontext}, see \ref{sssection:rightHandcontext}): \begin{quote} \begin{verbatim} NonTerminal --> GRBody. NonTerminal, Semicontext --> GRBody. \end{verbatim} \end{quote} \noindent If \code{NonTerminal} is a grammar control construct its effect shall be implementation dependent.\\ % do we need this? JPEH April 2015 \noindent The effect of a \code{Semicontext} which is not a terminal-sequence shall be implementation dependent.\\ \noindent The control constructs that may be used in a body are described in subclause \ref{ssection:controlConstructs}. An empty body is represented by an empty terminal sequence: \begin{quote} \begin{verbatim} GRHead --> []. \end{verbatim} \end{quote} \medskip \noindent NOTE --- There is no \code{(-->)/1} form for grammar rules. \subsubsection{Semicontext} \label{sssection:rightHandcontext} \def\theparagraph{\arabic{section}.\arabic{subsection}.\arabic{subsubsection}.\arabic{paragraph}} \paragraph{Description} \ \vspace{1em} \noindent A \textsl{semicontext} is a terminal-sequence (see \ref{defTerminalSequence}), which follows, separated by a comma, the non-terminal of the head of a grammar rule (see \ref{defGrammarRuleHead}). The terminals of the semicontext make up a prefix of the remaining terminal-sequence. % \paragraph{Syntax} % \begin{quote} % \begin{verbatim} % RightHandContext = TerminalSequence % \end{verbatim} % \end{quote} \paragraph{Examples} \ \vspace{1em} \noindent Assume we need rules to \textsl{look-ahead} one or two tokens that would later be consumed next. This could be accomplished by the following grammar rules: \begin{quote} \begin{verbatim} look_ahead(X), [X] --> [X]. look_ahead(X, Y), [X,Y] --> [X,Y]. \end{verbatim} \end{quote} When used for parsing, procedurally, these grammar rules can be interpreted as, respectively, consuming, and then restoring, one or two terminals. \\ \noindent Another example may be a small grammar rule with semicontext: \begin{quote} \begin{verbatim} phrase1, [word] --> phrase2, phrase3. \end{verbatim} \end{quote} \noindent After preparation for execution this may occur in the database as follows. \noindent \begin{quote} \begin{verbatim} phrase1(S0, S):- phrase2(S0, S1), phrase3(S1, S2), S = [word | S2]. \end{verbatim} \end{quote} \medskip \noindent NOTES\\ \noindent 1\hspace{1.5em} In case of parsing with \code{phrase1}, as soon as \code{phrase2} and \code{phrase3} have successfully parsed the comprehensive terminal-sequence (input list), the terminal \code{word} is prefixed to the remaining terminal-sequence. \code{word} is then the first terminal to be consumed in further parsing after \code{phrase1}. Thus further parsing is constrained by the semicontext.\\ % process from path JPEH March 28th Simplified second sentence. JPEH % KD fixed \noindent 2\hspace{1.5em} The concepts \textsl{comprehensive terminal-sequence} resp. \textsl{remaining terminal-sequence} are often called \textsl{input list} resp. \textsl{output list}. This is misleading, because it only considers the case of parsing using a grammar. There a terminal list shall be parsed wrt. non-terminals, and there will be a remainder after the parsing step. The inverse case, generating sentences by expanding grammars, where the comprehensive terminal-sequence is the output list, is ignored by such wording.\\ % Above par modified JPEH also March 2014 % KD In former versions of the Draft (by Paulo) only the concepts of input list and output list were used. % The meaning was that during parsing a non-terminal consumes some terminals from the (larger) input list, % and there remains a (smaller) output list, subject to following parsing. But for generating it is the opposite, % there the output is larger (i.e. contains more terminals) than the input list. The wording input list and % output list is very colloquial, therefore shall be a clarification here. \noindent 3\hspace{1.5em} There are cases, where the remaining terminal-sequence is the comprehensive terminal-sequence. See, e.g. the following grammar rule. There maybe a trailing terminal-sequence, however, as the following example shows. % Above par modified JPEH % KD OK \noindent \begin{quote} \begin{verbatim} nt,[word] --> []. \end{verbatim} \end{quote} \noindent which may be expanded by preparation for execution to: \noindent \begin{quote} \begin{verbatim} nt(S0, S) :- S = [word|S0]). \end{verbatim} \end{quote} \noindent This non-terminal \code{nt} represents an empty terminal sequence (cf. \ref{sssection:emptySequence}), but constrains further parsing to take place with \code{word} as next token.\\ \noindent 4\hspace{1.5em} It should be noted that \code{phrase/2} (cf \ref{sssection:bootstrappedPredicates}) cannot succeed when applied to a grammar rule, whose head contains a non empty semicontext, as in the case above.\\ % Modified JPEH % KD OK \noindent 5 \hspace{1.5em} Some processors allow a cut in the semicontext; e.g.\\ \code{a, !, [word] --> b.}\\ \noindent Moving this cut to the end of the grammar body, c.f. \code{a, [word] --> b, !.} leads to identical execution. Thus this TR does not permit a cut in the semicontext. \subsubsection{Non-terminal indicator} \label{ssection:nonterminalIndicator} A \textsl{non-terminal indicator} is a compound term \code{//(A, N)} where \code{A} is an atom and \code {N} is a non-negative integer.\\ \noindent The non-terminal indicator \code{//(A, N)} indicates the non-terminal of the head of a grammar rule where \code{A} is an atom, representing the non-terminal, and \code{N} is its arity, a non-negative integer\\ \medskip \noindent NOTES\\ \noindent 1\hspace{1.5em}In Prolog text, including ISO/IEC 13211--1 and this TR, a non-terminal indicator \code{//(A, N)} is normally written as \code{A//N} or as \code{(A)//N} depending on whether or not A is an operator (cf. 7.1.6.6 of 13211--1).\\ \noindent 2\hspace{1.5em}The concept of non-terminal indicator is similar to the concept of \textsl{predicate indicator} defined in subclauses 3.131 and 7.1.6.6 of the ISO/IEC 13211--1 Prolog. Non-terminal indicators may be used in exception terms thrown when processing or using grammar rules. In addition, non-terminal indicators may appear at some places, where a predicate indicator as defined in ISO/IEC 13211--1 can appear. See \ref{sssection:prologDirectives}. Furthermore non-terminal indicators may be used in a predicate property %(cf. subsection \ref{ssection:predicateProperties}) . In particular, using non-terminal indicators in predicate directives allows the details of the expansion of grammar rules into Prolog clauses to be abstracted. \def\theparagraph{\arabic{section}.\arabic{subsection}.\arabic{subsubsection}.\arabic{paragraph}} \paragraph{Examples} \ \vspace{1em} \noindent For example, given the following grammar rule: \begin{quote} \begin{verbatim} sentence --> noun_phrase, verb_phrase. \end{verbatim} \end{quote} \noindent The corresponding non-terminal indicator for the grammar rule left-hand side non-terminal is \code{sentence//0}. \\ \noindent \begin{quote} \begin{verbatim} :- multifile(sentence//0). \end{verbatim} \end{quote} \noindent Thus grammar rules for \code{sentence//0} may be distributed over several files.\\ \subsection{Grammar control constructs} \label{ssection:controlConstructs} \def\theparagraph{\arabic{section}.\arabic{subsection}.\arabic{subsubsection}.\arabic{paragraph}} This definition of each grammar control construct gives its logical meaning and the procedural effects, if any, of executing it wrt. its arguments after preparing it for execution.\\ \noindent Expansion of grammar control constructs is not simply a replacement by Prolog control constructs. For the expansion of every grammar control construct there is a formal definition in subclause \ref{section:logicalExpansion}.\\ \noindent The correspondence between the following subclauses and the corresponding formal definitions is given by the argument of the clauses of predicate \code{dcg\_constr/1} or, respectively, by the principal functor of the first argument of the clauses of predicate \code{dcg\_cbody/4} in subclause \ref{section:logicalExpansion}\\ \noindent After preparation for execution of Grammar Rules, named ``Grammar Rule expansion'' or ``expansion'' for short, the non-terminals, with exception of phrase//1, result in control constructs, respectively built-in predicates of ISO/IEC 13211-1 Prolog. Grammar Rule expansion is defined by using the built-in predicate \code{phrase/3} (see subclause \ref{sssection:phraseSpecification}) and subclause \ref{section:logicalExpansion}.\\ \noindent The following subclauses explicate the linkages between the terminal sequences upon expansion of the control constructs. \noindent The meaning of \code{phrase/2} is sometimes defined using if and sometimes defined using iff depending on whether or not semicontext makes a difference. For \code{phrase/3}, only iff is used.\\ \noindent The procedural effects are described using the logical expansion (Section \ref{section:logicalExpansion}). \subsubsection{\code{[]//0} -- empty terminal-sequence} \label{sssection:emptySequence} \paragraph{Description} \ \vspace{1em} \noindent \code{phrase([],S0,S)} is true iff \code{S0=S}. \subsubsection{\code{('.')//2} -- terminal sequence} \paragraph{Description} \ \vspace{1em} \noindent \code{('.')} used as a non-terminal \code{('.')//2} separates its first argument, the terminal on its left hand side from the second argument, the terminal sequence on its right hand side. \noindent \subsubsection{\code{(',')//2} -- concatenation} \paragraph{Description} \ \vspace{1em} \noindent The grammar body element \code{(A,B)} describes the concatenation of \code{A} and \code{B}. \ \vspace{1em} \noindent \code{phrase((A,B), S)} is true if \code{S} is the concatenation of \code{S1} and \code{S2}\\ where \code{phrase(A, S1)} and \code{phrase(B, S2)} are true.\\ \noindent More precisely taking semicontext into account,\\ \code{phrase((A,B), S0,S)}, is true iff\\ \code{phrase(A, S0,S1), phrase(B, S1,S)} is true. \subsubsection{\code{(;)//2} -- alternative} \label{sssection:alternative} \paragraph{Description} \ \vspace{1em} \noindent The grammar body element \code{(A;B)} describes the alternative of \code{A} and \code{B}.\\ \noindent \code{phrase((A;B), S)} is true iff \code{( phrase(A, S) ; phrase(B, S) )} is true.\\ \noindent More precisely, taking semicontext into account, \code{phrase((A;B), S0,S)}, is true iff \code{( phrase(A, S0,S) ; phrase(B, S0,S) )} is true. \vspace{1em} \noindent \medskip \noindent NOTE --- The effect of comma and semicolon, \code{(',')//2}, \code{(;)//2}, may be understood best by application of \code{write\_canonical/1} (see subclause 8.14.2.5 of ISO/IEC 13211--1) on a grammar rule, containing them: \begin{quote} \begin{verbatim} ?- write_canonical((sentence --> subject, verb, object; object, verb, subject)). --> (sentence, ;(','(subject, ','(verb, object)), (','(object, ','(verb, subject)))) yes \end{verbatim} \end{quote} \noindent This may lead to the following Prolog clause after preparation for execution: \begin{quote} \begin{verbatim} sentence(S0, S) :- ( subject(S0, S1), verb(S1, S2), object(S2, S) ; object(S0, S3), verb(S3, S4), subject(S4, S) ). \end{verbatim} \end{quote} \subsubsection{\code{(;)//2} with \code{(->)//2} -- if-then-else} \label{sssection:ifThenElse} \paragraph{Description} \ \vspace{1em} \noindent NOTE -- \code{(;)//2} (cf. \ref{sssection:alternative}) serves two different functions depending on whether or not its first argument is a compound term with grammar control construct \code{(->)//2}.\ See \ref{sssection:alternative} for the use of \code{(;)//2} for \code{alternative}, when the first argument of \code{(;)//2} does not immediately contain a grammar control construct \code{(->)//2}.\ \paragraph{Description} \ \vspace{1em} \noindent The grammar body element \code{( A -> B ; C )} describes one of \code{( A, B )} or \code{C}\\ \noindent \code{phrase(( A -> B ; C ), S)} is true if\\ if \code{phrase(A, S,\_)} is true\\ then\\ \hspace*{3em} \code{phrase((A, B), S)} is true\\ \hspace*{5em} for the first solution/answer of \code{phrase(A, S,\_)}\\ else\\ \hspace*{3em} \code{phrase(C, S)} is true.\\ \noindent More precisely taking semicontext into account,\\ \code{phrase(( A -> B ; C ), S0,S)} is true iff\\ \code{( phrase(A, S0, S1) -> phrase(B, S1, S) ; phrase(C, S0, S) )} \\ is true. \paragraph{Examples} \begin{verbatim} phrase( ( ("1"|"2") -> "3" ; "4" ), "13") succeeds phrase( ( ("1"|"2") -> "3" ; "4" ), "23") succeeds phrase( ( ("1"|"2") -> "3" ; "4" ), "4") succeeds phrase( ( ("1"|"2") -> "3" ; "4" ), Xs) succeeds only once unifying Xs with "13". phrase( ( ("1"|"2") -> "3" ; "4" ), [X]) fails \end{verbatim} \subsubsection{\code{('|')//2} -- second form of alternative} \paragraph{Description} \ \vspace{1em} \noindent The grammar body element \code{(A|B)} describes the alternative of \code{A} and \code{B}.\\ \noindent \code{phrase((A|B), S)} is true iff \code{( phrase(A, S) ; phrase(B, S) )} is true.\\ \noindent More precisely taking semicontext into account, \code{phrase((A|B), S0,S)}, is true iff \code{( phrase(A, S0,S) ; phrase(B, S0,S) )} is true. \ \vspace{1em} \noindent \code{'|'} used as a non-terminal \code{('|')//2} has the same behaviour as \code{(;)//2}, when used for an alternative. See subclause \ref{sssection:alternative}. The use of \code{('|')//2} instead of \code{(;)//2} in an if-then-else, cf \ref{sssection:ifThenElse}, shall be implementation-dependent. %NOTE --- \code{('|')//2} is not equivalent to \code{(;)//2}, when \code{(;)//2} is %used for "if-then-else", as \code{('|')//2} shall not be used for "if-then-else". See subclause \ref{sssection:ifThenElse}. \subsubsection{\code{\{\}//1} -- grammar-body-goal} \paragraph{Description} \ \vspace{1em} \noindent The grammar body element \code{\{G\}} describes the empty sequence.\\ \noindent More precisely taking semicontext into account,\\ \code{phrase(\{G\}, S0, S)} is true iff \code{( G, S0 = S )} is true.\\ \noindent The non-terminal \code{\{G\}}, with \code{G} a Prolog goal, according to ISO/IEC 13211-1:1995, can appear at any place of a non-terminal inside a grammar-rule-body. After expansion the braces are omitted, the goal G is unchanged. On execution G is executed like any Prolog goal. \\ \noindent If {G} immediately contains a cut ('!'), this is handled like a grammar-body-cut (cf. \ref{ssection:grammarCut}), i.e. the effect of the cut extends outside the non-terminal \code{\{G\}}. \paragraph{Example} \begin{verbatim} phrase({true}, nonlist, S) \end{verbatim}\\ succeeds, unifying \code{S} with \code{nonlist}. \subsubsection{call//1} \paragraph{Description} \ \vspace{1em} \noindent The grammar body element \code{call//1} describes the use of a Prolog predicate that expects two additional arguments. \ \vspace{1em} \noindent \code{phrase(call(G\_2), S)} is true iff \code{call(G\_2, S, [])} is true.\\ \noindent More precisely taking semicontext into account, \code{phrase(call(G\_2), S0,S)} is true iff \code{call(G\_2, S0,S)} is true. \pagebreak % inserted to keep note on one page \noindent NOTE --- Consider the following example for the correspondence for grammar rules between \code{call//1} and \code{call/3}: \noindent \begin{quote} \begin{verbatim} atom_charsdiff(Atom, Xs0, Xs):- atom_chars(Atom, Chars), append(Chars, Xs, Xs0). atomchars(Atom) --> call(atom_charsdiff(Atom)). at_eos_pred([ ], [ ]). at_eos --> call(at_eos_pred). \end{verbatim} \end{quote} \subsubsection{\code{phrase//1}} \paragraph{Description} \ \vspace{1em} \noindent The grammar body element \code{phrase(NonTerminal)} describes \code{NonTerminal}.\\ \noindent \code{phrase(phrase(NonTerminal), S)} is true iff \code{phrase(NonTerminal, S)} is true.\\ \noindent More precisely taking semicontext into account,\\ \code{phrase(phrase(NonTerminal), S0,S)} is true iff \\ \code{phrase(NonTerminal,S0,S)} is true. \medskip \noindent For a definition of the built-in predicate \code{phrase/3} see subclause \ref{sssection:phraseSpecification}.\\ \subsubsection{\code{!//0} -- grammar-body-cut} \label{ssection:grammarCut} \paragraph{Description} \ \vspace{1em} \noindent The grammar body \code{!} describes the empty terminal sequence.\\ \noindent \code{phrase(!, S)} is true iff \code{S = []} is true.\\ \noindent \code{phrase(!, S0,S)} is true iff \code{S0 = S} is true \medskip \noindent Implementations conforming to this TR shall not define or use a predicate \code{!/2}. \pagebreak % inserted to avoid widow \subsubsection{\code{($\backslash$+)//1} -- grammar-body-not} \noindent The presence of \code{($\backslash$+)//1} in grammar rules shall be implementation dependent. \paragraph{Description} \ \vspace{1em} \noindent If present in a \code{($\backslash$+)//1} in grammar rules shall be defined as follows: \ \vspace{1em} \noindent The grammar body element \code{$\backslash$+ GRBody} describes the empty terminal sequence. \ \vspace{1em} \noindent \code{phrase($\backslash$+ GRBody, S)} is true iff\\ \code{$\backslash$+ phrase(GRBody ,S,\_), S = []} is true.\\ \noindent \code{phrase($\backslash$+ GRBody, S0,S)} is true iff\\ \code{( $\backslash$+ phrase(GRBody ,S0,\_), S0 = S} ) is true. \ \vspace{1em} \medskip \noindent Implementations conforming to this TR shall not define or use a predicate \code{($\backslash$+)/3}. \\ \noindent NOTE --- The effect of \code{($\backslash$+)//1} can be seen in the following example.\\ \noindent The grammar rule \begin{quote} \begin{verbatim} a --> \+ b. \end{verbatim} \end{quote} \noindent may be expanded to: \begin{quote} \begin{verbatim} a(S0, S) :- \+ b(S0, _), S0 = S. \end{verbatim} \end{quote} \subsubsection{\code{(->)//2} - if-then} \noindent The effect of \code{(->)//2} in grammar rules except in the first argument of an alternative (cf. 7.14.5) shall be implementation dependent. If present in the processor, it is defined as follows. \paragraph{Description} \ \vspace{1em} \noindent The grammar body element \code{A -> B} describes one of \code{( A, B )}.\\ \noindent \code{phrase((A -> B), S)} is true iff \code{phrase((A -> B ; {fail}), S)} is true.\\ \noindent \code{phrase((A -> B), S0,S)} is true iff \code{phrase((A -> B ; {fail}), S0,S)} is true. \def\theparagraph{\arabic{section}.\arabic{subsection}.\arabic{subsubsection}.\arabic{paragraph}} \subsection{Executing clauses expanded from grammar rules} If a grammar rule to be prepared for execution has a non-terminal indicator NT//N, and NT is the name of the predicate indicator NT/M, with M is N + 2, of a built-in predicate, the result of expansion and the behaviour of the prepared grammar rule on execution is implementation dependent. This does not hold for the required non-terminals expanding to built-in predicates defined in \ref{ssection:controlConstructs}.\\ \noindent When the database does not contain a procedure, prepared for execution from one or more grammar rules with non-terminal indicator NT//N during execution of a goal, prepared for execution from a non-terminal with non-terminal indicator NT//N, the behaviour of the processor shall be as follows: If the error handling of the processor is standard conforming as specified in subclause 7.7.7 of ISO/IEC 13211--1, then the error term as specified in subclause 7.7.7b of ISO/IEC 13211--1 when the flag \code{unknown} is set to \code{error} shall be: \begin{quote} \begin{verbatim} existence_error(procedure, NT/M) \end{verbatim} \end{quote} \medskip \noindent If the error handling of the processor supports definite clause grammar errors, then the error term shall be: \begin{quote} \begin{verbatim} existence_error(grammar_rule, NT/M) \end{verbatim} \end{quote} \medskip \noindent In other cases the behaviour shall be implementation specific. \medskip \noindent NOTES\\ \noindent 1\hspace{1.5em}Prolog processors shall report errors resulting from execution of grammar rules at the same abstraction level as grammar rules whenever possible.\\ \noindent 2\hspace{1.5em}Parsing resp. generating of terminal sequences using grammar rules is defined in subclause \ref{sssection:phraseSpecification}. Grammar rules are expanded there into Prolog clauses during preparation for execution, which maps the parsing or generating with a grammar-rule-body into executing a goal given a sequence of predicate clauses. See subclause 7.7 of ISO/IEC 13211--1 for details. \pagebreak % inserted to avoid widow \section{ Built-in predicates} \setcounter{subsection}{17} \subsection{Grammar rule built-in predicates} \subsubsection{phrase/3, phrase/2} \label{sssection:phraseSpecification} % \def\theparagraph{\arabic{section}.\arabic{subsection}.\arabic{subsubsection}.\arabic{paragraph}} \paragraph{Description} \ \vspace{1em} \noindent In the absence of semicontexts \code{phrase(GRBody, S)} is true if S is a phrase covered by the non-terminal or more generally the grammar-rule-body \code{GRBody}.\\ \noindent In the absence of semicontexts \code{phrase(GRBody, S0, S))} is true if \code{P} is a phrase covered by the non-terminal \code{GRBody} and \code{append(P,S, S0)} is true. \ \vspace{1em} \noindent In the presence of semicontexts \code{phrase(NonTerminal, S0,S)} is true\\ if \\ \hspace*{2em}there is a grammar rule \code{Nonterminal, Semicontext --> GRbody}\\ \hspace*{3em} and \code{phrase(GRbody, S0,S1)} is true\\ \hspace*{3em} and \code{append(Semicontext, S1, S)} is true.\\ else\\ \hspace*{2em} there is no semicontext and there is a grammar rule\\ \hspace*{3em} \code{Nonterminal --> GRbody} and \code{phrase(GRbody, S0,S)} is true. \ \vspace{1em} \noindent Procedurally \code{phrase(GrBody, S0, S)} is executed as\\ \code{ dcg\_body(GRBody, S0, S, Goal), call(Goal)} where \code{dcg\_body/4)} is described in clause \ref{section:logicalExpansion}. \ \vspace{1em} \noindent Execution of the predicate \code{phrase/3} serves two goals: Firstly the final expansion(of a grammar rule) (cf. Definition 3.7), when this has not taken place earlier, i.e. preparation for execution of its body and arguments; thereafter, secondly, the execution of the resulting Prolog goals. \\ \noindent NOTE 1 --- An \code{A} of a \code{B} means, construct \code{A} is directly contained in construct \code{B}. This is general standard wording for programming languages. \medskip \noindent NOTE 2 --- The simple grammar of example 7.14.1.1 may be prepared here for execution.\\ \noindent Then with \begin{quote} \begin{verbatim} GRBody: non-terminal: noun_phrase S0: comprehensive terminal-sequence: [the, dog, barks] S: remaining terminal-sequence: [barks] \end{verbatim} \end{quote} \noindent \code{phrase(noun\_phrase, [the, dog, barks], [barks])} is true.\ \medskip \noindent If the non-terminal of \code{GRBody}, if any, is followed by a semicontext (cf. Definition 3.21), then the semicontext shall be prefixed to the remaining terminal sequence after having been parsed resp. generated wrt. the non-terminal of \code{GRBody}.\\ \noindent Procedurally, \code{phrase(GRBody, S0, S)} is executed by calling the Prolog goal corresponding to the expansion of the grammar-rule-body \code{GRBody}, given the terminal-sequences \code{S0} and \code{S}, according to the logical expansion of grammar rules described in subclause \ref{section:logicalExpansion}. See in particular the clauses for \code{dcg\_rule/4}.\\ \noindent \code{phrase(GRBody, S0, S)} shall be steadfast (cf. 3.22) in its third argument S. \paragraph{Template and modes} \ \vspace{1em} \noindent \code{phrase(+grammar-rule-body, ?comprehensive-terminal-sequence,}\\ \code{?remaining-terminal-sequence)}\\ \ \vspace{1em} \noindent For definitions of \code{comprehensive-terminal-sequence and remaining-terminal-sequence} see Definitions 3.25 resp. 3.26, for \code{grammar-rule-body} see Definition 3.14. \paragraph{Bootstrapped built-in predicates} \label{sssection:bootstrappedPredicates} \ \vspace{1em} \noindent The built-in predicate \code{phrase/2} provides similar functionality to \code{phrase/3}. The goal \code{phrase(GRBody, S0)} is true when all terminals in the terminal-sequence S0 are consumed and accepted respectively generated. \begin{quote} \begin{verbatim} phrase(GRBody, S0) :- phrase(GRBody, S0, []). \end{verbatim} \end{quote} \paragraph{Errors} \label{sssection:phraseErrors} \begin{list}{\alph{Lcount})}{\usecounter{Lcount}} \item \code{GRBody} is a variable\\ --- \code{instantiation\_error} \item \code{GRBody} is neither a variable nor a callable term\\ --- \code{type\_error(callable, GRBody)} \noindent The following two errors are implementation defined if applied to \code{phrase/3}, i.e. no error checking is required on S0 and S by this TR for \code{phrase/3}. If, however, a Prolog processor offers them, their form and consequence must be the following: \item \code{S0} is not a terminal-sequence\\ --- \code{type\_error(terminal\_sequence, S0)} For \code{phrase/2} error clause \code{c} is required. \item \code{S} is not a terminal-sequence\\ --- \code{type\_error(terminal\_sequence, S)} \end{list} \noindent NOTE --- \hspace{1.5em}This relaxation is allowed because handling these errors could overburden a Prolog processor. \paragraph{Examples} \ \vspace{1em} \noindent These examples assume that the following grammar rules has been correctly prepared for execution and are part of the complete database: \begin{quote} \begin{verbatim} determiner --> [the]. determiner --> [a]. noun --> [boy]. noun --> [girl]. verb --> [likes]. verb --> [scares]. noun_phrase --> determiner, noun. noun_phrase --> noun. verb_phrase --> verb. verb_phrase --> verb, noun_phrase. sentence --> noun_phrase, verb_phrase. \end{verbatim} \end{quote} \noindent Some example calls of \code{phrase/2} and \code{phrase/3}: \begin{quote} \begin{verbatim} | ?- phrase([the], [the]). yes | ?- phrase(sentence, [the, girl, likes, the, boy]). yes | ?- phrase(sentence, [the, girl, likes, the, boy, today]). no | ?- phrase(sentence, [the, girl, likes]). yes | ?- phrase(sentence, Sentence). Sentence = [the, boy, likes] yes | ?- phrase(noun_phrase, [the, girl, scares, the, boy], Rest). Rest = [scares, the, boy] yes \end{verbatim} \end{quote} \begin{comment} % I left it inside the source for the moment, to wait which results the discussion brings. \subsubsection{expand\_term/2} \label{sssection:expandterm} \paragraph{Description} \ \vspace{1em} \noindent \code{expand\_term(Term, Expansion)} is true iff:\\ \noindent --- \code{Expansion} unifies with the expansion of \code{Term}.\\ \noindent Procedurally, \code{expand\_term(Term, Expansion)} is executed as follows: \begin{list}{\alph{Lcount})}{\usecounter{Lcount}} \item If \code{Term} is a variable, unifies \code{Expansion} with \code{Term} \item Else if the goal \code{term\_expansion(Term, Expand)} is true then \code{Expansion} is unified with \code{Expand} \item Else if the principal functor of \code{Term} is \code{(-->)/2} then it is assumed that it represents a grammar rule and \code{Expansion} is unified with its expansion into a Prolog clause \item Else if the principal functor of \code{Term} is not \code{(-->)/2} then \code{Expansion} is unified with \code{Term} \item Else the goal fails \end{list} \noindent NOTE --- The predicate \code{term\_expansion/2} is described in subclause \ref{sssection:termExpansion}. \paragraph{Template and modes} \ \vspace{1em} \noindent \code{expand\_term(?term, ?term)} \paragraph{Errors} \ \vspace{1em} \noindent None. \paragraph{Examples} \ \vspace{1em} \noindent These examples assume that the following clauses for the \code{term\_expansion/2} predicate have been prepared for execution: \begin{quote} \begin{verbatim} term_expansion(succ(A, B), pred(B, A)). term_expansion(0, zero). term_expansion(1, one). \end{verbatim} \end{quote} Some example calls of \code{expand\_term/2}: \begin{quote} \begin{verbatim} ?- expand_term(Term, Expansion). Term = Expansion yes ?- expand_term(succ(1, 2), Expansion). Expansion = pred(2, 1) yes ?- expand_term(1, one). yes ?- expand_term(odd(1), Expansion). Expansion = odd(1) yes \end{verbatim} \end{quote} The next query returns an implementation-dependent Prolog clause; therefore the example below illustrates one possible answer: \begin{quote} \begin{verbatim} ?- expand_term((noun_phrase --> noun), Expansion) Expansion = noun_phrase(A, B) :- noun(A, B) yes \end{verbatim} \end{quote} \medskip \noindent NOTES\\ \noindent 1\hspace{1.5em}Despite the fact that \code{expand\_term/2} may be used to retrieve the translation of a grammar rule to a Prolog clause, users should not rely on a specific translation of a grammar rule, which is implementation-dependent.\\ \noindent 2\hspace{1.5em}Users may use alternate grammar rule translators by defining suitable clauses for \code{term\_expansion/2}. Prolog implementers may use this mechanism to ensure backward compatibility with code written for older translators that are not compliant with this TR. \medskip \noindent 3. \hspace{1.5em} Some Prolog systems provide support for term expansion mechanisms, based on \code{term\_expansion/2} and \code{expand\_term/2} predicates, that may be used when compiling Prolog source files. The specification of such mechanisms --- in particular how term expansion is performed during the compilation of Prolog source code --- is outside the scope of this technical report. \end{comment} \section{Evaluable functors} NOTE --- No changes from the ISO/IEC 13211--1 Prolog standard. \begin{comment} %KD: term_expansion and expand_term are flipflops. Lets wait for results of discussion \section{User-defined predicates} \subsection{Grammar rule user-defined predicates} \subsubsection{term\_expansion/2} \label{sssection:termExpansion} \paragraph{Description} \ \vspace{1em} \noindent \code{term\_expansion(Term, Expansion)} is a user-defined, dynamic, and multifile predicate, which may be used for the rewriting of terms. The predicate is automatically called by the built-in predicate \code{expand\_term/2}, see \ref{sssection:expandterm}. This predicate exists even if it has no clauses. \paragraph{Template and modes} \ \vspace{1em} \noindent \code{term\_expansion(?term, ?term)} \paragraph{Errors} \ \vspace{1em} \noindent None. \paragraph{Examples} \noindent \begin{quote} \begin{verbatim} term_expansion(next(Previous, Next), previous(Next, Previous)). \end{verbatim} \end{quote} \end{comment} \section{Logical Expansion} \label{section:logicalExpansion} \verbatiminput{dcgs_exp.pl} \end{document} --------------070001080000080004060304--