From mboxrd@z Thu Jan 1 00:00:00 1970 Return-Path: X-Spam-Checker-Version: SpamAssassin 3.4.0 (2014-02-07) on aws-us-west-2-korg-lkml-1.web.codeaurora.org X-Spam-Level: X-Spam-Status: No, score=-10.5 required=3.0 tests=BAYES_00, HEADER_FROM_DIFFERENT_DOMAINS,MAILING_LIST_MULTI,MENTIONS_GIT_HOSTING, SPF_HELO_NONE,SPF_PASS,USER_AGENT_SANE_1 autolearn=unavailable autolearn_force=no version=3.4.0 Received: from mail.kernel.org (mail.kernel.org [198.145.29.99]) by smtp.lore.kernel.org (Postfix) with ESMTP id AFF55C433E0 for ; Thu, 16 Jul 2020 20:12:21 +0000 (UTC) Received: from vger.kernel.org (vger.kernel.org [23.128.96.18]) by mail.kernel.org (Postfix) with ESMTP id 7FB07206F4 for ; Thu, 16 Jul 2020 20:12:21 +0000 (UTC) Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S1729735AbgGPUMV (ORCPT ); Thu, 16 Jul 2020 16:12:21 -0400 Received: from mga12.intel.com ([192.55.52.136]:24144 "EHLO mga12.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S1728788AbgGPUMU (ORCPT ); Thu, 16 Jul 2020 16:12:20 -0400 IronPort-SDR: oYlJZnjKQCGln4OmIgzJO7+Vfh7HFS9MEOZl4VvL9HYY54GMeRCgOH1gFRoCCmsobzfDGR9NXg wjWXUG56LawQ== X-IronPort-AV: E=McAfee;i="6000,8403,9684"; a="129046853" X-IronPort-AV: E=Sophos;i="5.75,360,1589266800"; d="gz'50?scan'50,208,50";a="129046853" X-Amp-Result: UNKNOWN X-Amp-Original-Verdict: FILE UNKNOWN X-Amp-File-Uploaded: False Received: from orsmga005.jf.intel.com ([10.7.209.41]) by fmsmga106.fm.intel.com with ESMTP/TLS/ECDHE-RSA-AES256-GCM-SHA384; 16 Jul 2020 12:48:56 -0700 IronPort-SDR: 3RVThvvuETtQqqDay50jq7Q9QqKSJPaCHMC2sUs00iUs+PkFW2S7TKGHxVNeLSbDzAKNMi5fYf n7WxLExoh1GA== X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.75,360,1589266800"; d="gz'50?scan'50,208,50";a="460592942" Received: from lkp-server01.sh.intel.com (HELO 70d1600e1569) ([10.239.97.150]) by orsmga005.jf.intel.com with ESMTP; 16 Jul 2020 12:48:54 -0700 Received: from kbuild by 70d1600e1569 with local (Exim 4.92) (envelope-from ) id 1jw9sD-0000B0-RX; Thu, 16 Jul 2020 19:48:53 +0000 Date: Fri, 17 Jul 2020 03:48:44 +0800 From: kernel test robot To: Syed Nayyar Waris Cc: kbuild-all@lists.01.org, linux-gpio@vger.kernel.org, Linus Walleij Subject: [gpio:ib-for-each-clump 4/4] include/linux/bitmap.h:639:45: sparse: sparse: shift too big (64) for type unsigned long Message-ID: <202007170339.nHjeGJBw%lkp@intel.com> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="k+w/mQv8wyuph6w0" Content-Disposition: inline User-Agent: Mutt/1.10.1 (2018-07-13) Sender: linux-gpio-owner@vger.kernel.org Precedence: bulk List-ID: X-Mailing-List: linux-gpio@vger.kernel.org --k+w/mQv8wyuph6w0 Content-Type: text/plain; charset=us-ascii Content-Disposition: inline tree: https://git.kernel.org/pub/scm/linux/kernel/git/linusw/linux-gpio.git ib-for-each-clump head: 3358c938236d6a1be51124fbbb2698e50689d382 commit: 3358c938236d6a1be51124fbbb2698e50689d382 [4/4] gpio: xilinx: Utilize generic bitmap_get_value and _set_value. config: alpha-randconfig-s031-20200716 (attached as .config) compiler: alpha-linux-gcc (GCC) 9.3.0 reproduce: wget https://raw.githubusercontent.com/intel/lkp-tests/master/sbin/make.cross -O ~/bin/make.cross chmod +x ~/bin/make.cross # apt-get install sparse # sparse version: v0.6.2-49-g707c5017-dirty git checkout 3358c938236d6a1be51124fbbb2698e50689d382 # save the attached .config to linux build tree COMPILER_INSTALL_PATH=$HOME/0day COMPILER=gcc-9.3.0 make.cross C=1 CF='-fdiagnostic-prefix -D__CHECK_ENDIAN__' ARCH=alpha If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot sparse warnings: (new ones prefixed by >>) >> include/linux/bitmap.h:639:45: sparse: sparse: shift too big (64) for type unsigned long >> include/linux/bitmap.h:639:45: sparse: sparse: shift too big (64) for type unsigned long include/linux/bitmap.h:594:63: sparse: sparse: shift too big (64) for type unsigned long >> include/linux/bitmap.h:639:45: sparse: sparse: shift too big (64) for type unsigned long >> include/linux/bitmap.h:638:17: sparse: sparse: invalid access past the end of 'old' (8 8) vim +639 include/linux/bitmap.h 169c474fb22d8a5 William Breathitt Gray 2019-12-04 613 e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 614 /** e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 615 * bitmap_set_value - set n-bit value within a memory region e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 616 * @map: address to the bitmap memory region e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 617 * @value: value of nbits e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 618 * @start: bit offset of the n-bit value e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 619 * @nbits: size of value in bits e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 620 */ e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 621 static inline void bitmap_set_value(unsigned long *map, e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 622 unsigned long value, e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 623 unsigned long start, unsigned long nbits) e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 624 { e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 625 const size_t index = BIT_WORD(start); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 626 const unsigned long offset = start % BITS_PER_LONG; e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 627 const unsigned long ceiling = roundup(start + 1, BITS_PER_LONG); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 628 const unsigned long space = ceiling - start; e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 629 e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 630 value &= GENMASK(nbits - 1, 0); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 631 e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 632 if (space >= nbits) { e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 633 map[index] &= ~(GENMASK(nbits + offset - 1, offset)); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 634 map[index] |= value << offset; e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 635 } else { e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 636 map[index] &= ~BITMAP_FIRST_WORD_MASK(start); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 637 map[index] |= value << offset; e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 @638 map[index + 1] &= ~BITMAP_LAST_WORD_MASK(start + nbits); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 @639 map[index + 1] |= (value >> space); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 640 } e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 641 } e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 642 :::::: The code at line 639 was first introduced by commit :::::: e77c9b6f35c4bdfa60c52f137a4b48c04ab87627 bitops: Introduce the for_each_set_clump macro :::::: TO: Syed Nayyar Waris :::::: CC: Linus Walleij --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all@lists.01.org --k+w/mQv8wyuph6w0 Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICFOiEF8AAy5jb25maWcAjDxNd9u2svv+Cp100y6Sa8uJm7x3vIBAUEJFEgwASnI2PIqs JDp1pBxZbm///Z0BvwAQpNNFas4MBsBgMF8A9Osvv07I8+X0fXs57LaPj/9Ovu6P+/P2sn+Y fDk87v9/EolJJvSERVy/AeLkcHz+73+2jz++bSfv3rx/c/X6vLueLPfn4/5xQk/HL4evz9D8 cDr+8usvVGQxn5eUlismFRdZqdlG370yzV8/IqvXX3e7yW9zSn+ffHhz8+bqldWIqxIQd/82 oHnH6O7D1c3VVYNIohY+vXl7Zf5r+SQkm7foK4v9gqiSqLScCy26TiwEzxKesQ7F5cdyLeQS IDC5XydzI6rHydP+8vyjm+5MiiXLSpitSnOrdcZ1ybJVSSSMmKdc391MgUvTr0hznjCQkNKT w9PkeLog43aKgpKkmcWrVyFwSQp7IrOCg1wUSbRFH7GYFIk2gwmAF0LpjKTs7tVvx9Nx//ur bnzqXq14TgNDy4XimzL9WLDCEpYNxcZUJ4Bs2a2JpovSYAMsqRRKlSlLhbwvidaELjrOhWIJ n9nMSAHaGWCzICsG4oaODAWOgiRJs3ywnJOn589P/z5d9t+75ZuzjElOzWrnUsysOdkotRDr MIYueO4qTSRSwjMXpnhqT8FmELFZMY+VPaFfJ/vjw+T0xRu03z0FfViyFcu0amapD9/356fQ RDWnS9BSBjPR3dgWn8oceImIU3t8mUAMjxLmDstGh1aAzxelZAo6S0FLDcd6Jr2BtZojGUtz DTzN5jOzoHnxH719+mtygVaTLXB4umwvT5Ptbnd6Pl4Ox6/evKBBSSgVRaZ5Nrd2hYpwVSkD /QK8tufo48rVTWBKmqil0kQruykCYd0Scm9aBmVkaDaD6Fzx4Ir/xNSNiCQtJiq0ytl9CbhO BPBRsg0ssrXqyqEwbTwQzto0rXUtgOqBioiF4FoSOo4AlSFRmc5sfXHn126lZfWHtbmWrR4J aoMXwLPSwdZ4opWMYSvzWN9NrzoF5JlegumMmUdzfVPJWu2+7R+eH/fnyZf99vJ83j8ZcD3S ANbzLsD/evrecjpzKYrc0SgwfnQeMo2GtFR0waKOQUy4LIMYGqtyRrJozSO9sDuQ2m4w3FPO I+WPtJRRSmxmNTiGrfuJyWFmEVtxynrsQMfrzeiTgyW0tFTgzq5RRDsjQLelctAfFep9wegy FyB2NEZaSGsIZvrGdxrGNk9wGCC9iIFFokS7QurkiLs+0OcsQYuwMq5WWgtivkkKjJUoJAij c8MyKuefbOcBgBkApg4k+WRk3wE2nzy88L7fOlZOCF1Wf4ckRUuRg7Hmn1gZC4m+AP6Xksys WrfeHpmCPwLcWr9vO+ScqnwJnBOikbVlm/O4+/AtVArxCQfXL62VmzOdolHtHLu3dDUiMLJ4 AXsiceZURSyVowqFOcYq2PGVpZn9OXXyJgpkVIRHUUBAbO1i/IQNZ0khF4klP8XnGUliS5vM cG2A8f42QC3AlHSfhFvawUVZyMo/dsFUtOKKNaILSQL4zYiU3F6LJdLep44Ja2BleAlatJEQ biPNV86KgEKMLCEqgwlbnemnMxZFtgGsdA5IyzYwahft+uptE2HUKUy+P385nb9vj7v9hP29 P4KjJWDVKbpaCFeqYKRu3vEMOu6f5NiMZpVWzEoTtDTBkpUdEA2pxTK0yxLihMMqKWZBU6US MRtoD4sq56xJBFxugEXDnnAF5hO2jUjD3BdFHEMGkxNgBEsGqQlY2uBOEjFPGrWrpeUmU622 JvnCMna3b2fctgmpFUK0MTCB7ECCua7isY7gE8STZWTbzjboVsRF5HNNZjCVBFYkUXc37XAw jTAZRaM2yoQjbQrY7SIceNNBUFwVBUmoKyMPv0lGkGDKl9djzFcEwl/wfiM0lMwg2k9YOCit aKJ8evt2BM9m1y/gb9/m48MAktsX0PkYns/ZmBiTzfgIk/tsM4JOiQRFGCPgEI6M4pdEjRFk EIDwpAiZ25pAYIRTUieGa1CSa7IMZ2YVCZi60fnn0+UIVpL1gkdj/CVsfU6yMYoXVkC9hMcN OYZfEDk2BxAQkWMroEGGYxNY8ySKuQyFOWA/LJ9aGZOS2H7cXkMfylZvfVBCA1ZqsQYtX2if 9iOzrWAtDDusMgWQFDLTOvoq48hJ7Q0+4go+NZ+Dcy9Z9oKw15Ahhg3GismZAHeempA7SLL4 VN5MhzADOgAYSJiGUNN3YduBra6mbwMrZvhdXdlljzsEWN5MohxWQc/uGH2nFLg9774dLvsd Zn2vH/Y/oAF4/MnpB1ZEn7qsXFQ+kHlhSh/cLL5Kc1N9KfUCc2OvHVYrUxHVhUDleMhyTvSC SSzRgPOeM08xTPss5VW6S9N8Qxdzj2YNbqTkoDk5kbC2TRnSr5kqTSDLkkIzCo6/qd/Y41xx yDrd0gzO0KOCmVT9qpxRHtu1BkAVCVMY+5UsiU3U6G69WaHcrSeiCHNdCJ0J1c6wBdZH+VwV 0E9mp8xVsHUzhWDDBNieOECSdY3KagOTAjgDM0g5RnFx7ARwWJiz4zvH0FcqRMXq9eft0/5h 8lcVOf44n74cHqvaVlcoBLJyyWTm+6Mmjhpj4wdbL6hrm0RqSL8gNWGWZpmgXaWYdl17q+OU MQwIc0SKxRQSzqFrqiIbo2i0e4yDkrSthidhh91Quumvj0YdkEyNdoYx7hpcu1Kox20BouRp LqSfFDRJSwaqC2p3n85EEibRkqcN3RITpCDVDDUqlBVl1bEFbB6eGYnS9sCC/Xe/e75sPz/u zeHOxOQlF8sszXgWpxp3lpVRJTF1CiY1kaKS2zugMkSicEuqFS2Cw7OoO0zf3wbmUmNBwo7D wuFERZoH9X9ojkYA6f776fzvJN0et1/334OWOYY01EmYEQBbO2KY94IftcozKk/AQuTabG6w AOrurZeyGYsTLvdiliQZagpoTyhLWtyDJYsiWWo/7zFmVAu0da6pz4QGe+nk5cqaSnPMk8Is QKqZYX/39urDbUORMVA6SGyNPVtaTWnCSEYJeHVnJdJwRPUpFyKUsn+aFZHd/pMxICKcIBl3 Z8SEdeFlWEqLFNaESymsOccSI+WV8UJWTsckTqpXup8XeTljGV2kvQCyVqlhrenEZtfSl7OS bTTLGl9sVC/bX/45nf8CM2zpnKUNdMlCR1iwna0CEX7BxnPqSwYWcRKSjk7cU4pE1RXYsOEB tBahAHcT2wElfpUCcn1hByIGSpK5sHs0QCzUBDs0WFXMylwknIaKqIYi5XPM53t8cSm50pyG siZYEnCT906JuAI1/EKBvLOQPK+qjpQox6gBnEQrLIlCZAGWLVjwBqI8yx1m8F1GC5p7vBCM RdlwflsTSCLzgVny3C4ZV5C5xPJHWmx8RKmLDEKHAH2IxUzCEtfTt4RiJo0GLrXDqRbjTpqn EJyurv1JV+BwHqDuM+AuljxYzK+Gt9LcX9tYFOHDyQrXzT7EFZe+JNYxswGAR+9DLN3vplTj IC+iAwtZjRvdwlD3/toYIG5tDwRdhMBF1ILdXiF/71kIlwKxoDBKS3Eftg3QJfw5bzU/ZG0a GlrM7KC9cTsN/u7V7vnzYffK5Z5G74ZiMljtcIIHITgd2BZ4UaNUjKJV9xTFoMC9mtgejEia h30LkEIypo07tdtXwKAkKpt+Ou/R3kP8cdmfe7diAqygfz/Y7NHAXxDXLZ1tWqNikvLkHnYr j+YsRFC3xdNMCx3jamTGuTpQPPP0N3cNBkbgQBx5WFwaeYfmYZPhyaybHjnohMzCe9ShinUe nkvJJR3kDROYcaHK7EX+inv89dgSNBKeJwVYRu20zEjvuzd6hFXjdmH+KBAG0S+XrN8JBKfq Y8EkiZg3f1PNHlevTUXThCsbE0I/TXan758PR0gmv5/wSNsKlO2mZb3LnKaX7fnr/vIU1nho o4mcg+kBtXphYJ4AAzwyPAjMw9vUoop/oq+aNiDjAJUj8BG6sB3qkYExS1W/MtAIFPKY3bf9 sEBTc6cKY3p9n4fCmwB1yAL0qar4bJQEgzFmH+iMWkErQFBeyKWMXDd303e3HhRyIExceN6j bzEpoUNIzLR6uAVRixDDGl4vWhA3xs9kdYNcEesHmk6n/TkYVIWwo6gWBexqruFQ1CYMMwdE hRvj/zJzHhPKej2Yo0N/oVfK622lqgsf4V4ACyYKV1PdXU/rK3z5Sk0u5+3x6cfpfMFK1+W0 Oz1OHk/bh8nn7eP2uMOE6+n5B+LtjVMxxGKlKMMxhE0BkVV/rBUKYr6huL2lIeGTL5tEUTf+ 76b31Nwm6kxv1VDK/pjWMpxpVdhkINGumiahy50VLhbeypViFfd7T2YjPBApfTbRos9FjUkr XQx2oOxT/wqUfWyckhElcB6UJqhvq17vrTbpSJu0asOziG1cndz++PF42BlbN/m2f/xh2npT yWI6sKFQK1jt+mue/zcSUHZ+HiJtSUy8bB0pARwvTlVZkwvXoHyb+wZuRwxRkRtwOKGqgsGB lLRC9vqS7E/wpx4cJgsonrfBhwNvo28H2nroPx3/XCGdUMGhD/nqiiAl2TzpQSFpst3Z2BIM xJpVPB6qaxoEErNZO/OuJlphAYX5d6HDxRqLSteCGu6poqpkE+Lw/mpa3rzUDYGEIGSbbRJp OT0LzvOBjs09+Jc6HkgpLIp8qTHkGehEDZRWLJJV4p79BqcmWZ7cD/QRgXDHGeAsyqEFaMLN cRZqeAXDka1FYIJfa3HyfmoLeh/RIV+IDsomxu8yms1LMfuTDhwGVzR19l8VdMoFRDGY64fu IQ2RqwW57vcdIMQjxyHGXv9WvdbH1t01c8f6SNWjV1uR0cABTvidBNFO3RY+S5rwgVstgASV HDiDB+RMTm/fh61zMtWhNVS6tzcDusTnKax1JoRfE/EJ06Dxr06TsaCk3Nu5FSh8ZQAmihbo +mOAYcSoF5ZWkOHCa5JY4TN8WJdniSaJFc/j7VyS5wlzwYnOveOmPFgwzCM/KgRAyTJKQpLZ TC2VS0ju3NjLF2IgdGeMoWje2T6zhZVZUv9hbsvylGUwlSBlFQF0KNDzlq+zSr3b4J3gaejy YJQpvFMt8BWSo0+gpQRPmFaBRiJn2UqtuXavM1ngch68abOq5mFFCg3EK4i24ARUeebkt3h6 xkWIlYvoamC2gEyVZ+C4Jc0Tix1KEyHlXFnhs4Gg8nrXbg0cAiFTAh6oemfKEddChfTfLKKR YVWps8DJDUZBmLZ7RbyPUg+xyqhyC+3wXQoGtiuNyiquCmcV9T195JFLLgLsLQqaEKV45A5X bvCE875070DPPrYvuOoztcll/3TxrkmYbpd6zrzT1zqa67X0EPYxXWfbUogezfVp01O+3f21 v0zk9uFwalNPq0BGqi3fmW34LiOSErxSuxqoz0hhHbRJodoXUGTzZvpucqzH/bD/+7DbTx7O h7+9W8npkg/cWrjFQ8awSc8/MrwjFN72oDI05M+U/TYTPtr7tpafpqWWG0YXoeWfkXvYYZC2 yTKOrIMqC74wcMumGExOQsp6T1I7Xh+VV6uBxL7FBOaqCvotwIymLmC+dnwDQP68/nDzoX8I AAFlVPUatatktVpVfTucVhs6cAURsSqhwSAVcc5WRwAlCcVkFt9ouIYGsXHC/K7sKcrA2JYr giuSU87isH8w3ZZjM6D0jz+uBjrlMcf/x5HfcTrKMmdkGRiULbY/yfWVuernNGSpwnaDjCt8 Snk4aDFSfH99e3U90G0nL3dhmgH742knEtpqFgGOyOOYbPrd1LOur6a6elSjmscqg/PTCv4N 3y83fETsX11x8KaWV983CL+QCOwRa7OH4iECeflGuvFZA4NI3VQYEjFgAFvCoSqj3CzdU11o saRpyPZpyUha3Ye0ChRrSOIgm7ffy8VzjLOsfKKK2a7NQ+9UuEc1DTVKjSUCL+KsicxAysFX bQ01ZRLv/VCCt41KkRUqyFSyjwUM0LwiwqsLbB6FIjqLHj5YkhQJAVPMnbczDhHewtzg9Ucu B2ZTpWp5eF0sut7D595UZQT+s2iq730ea7YJKU4d71rr0EDM1VX75K1FSIqXpHCpkzC2vU/1 M1R3r74fjk+X8/6x/Haxzr5b0pSpUHGzxScscq9WNojge/EAd9XcpQofd7v8oEFWBLvLRHXD cLy/5iJ4b68FhpakATqfSmnSvgft81jon+lJ0NnLHfGZUiM95YFTij6VjpLh0wxnTvXRzsa8 oex+oGLN8RDsX+ezXhnzKunufWu14iW3A+Tqu1EXF8izvNA96Dy3HwVi6Pwh97/r7MhPFz/k g7OkhMeu7+HxKHHgdoEBFypopli+KKsfgvAgeDtb6/veErZ4vD1u563BKrZ3hwD2MZ9zSK/D xJAXcb8BgMqCyHBtDAkWbvxR5zTb8yQ+7B/xieD378/H5hjhN2jxex3I2sfwMT7ocC4JGEDJ p9QF5tm7m5sAqKZ0RoaIaW/wFoHS9Yx7sH7H2SbvE9fAPrW6idcyexcEtkNts7WfElbDKVcE 0mzm6zCPQ8lYsm6vY3WltRqG5dNQLQQk0NyRrUGQ4hof6tUFzEv2VDnqGROeiLA2QnamhUis CyhGV4byi/qhjyXx6v69A/I/6l8pUS4w8LQag1R0v7PgazXEEpWnDhsDCT0ubXG5WDOpvLR4 gAz9/08Rd2/XBwnLXIcDYJx86v4kh4XBQGqpvJkMGjfEQbyIN53rt1Xeb/UYSeti5kLw9XMP SLS3QowSV9glFyuPkfSWOidVsaUrJQmdJ8Xcz4iqOgfAdqfj5Xx6xN+0ePC1DRnGGv69th9U IRR/Tqh3k6xF9H5IxKzHBl8GbzoNfzp8Pa63570ZhrlToqzT/NoOjJFVF/9Pn2HUh0dE7wfZ jFBVOf32YY/PuA26E8lT6IKBmQwlEctw4+EbApx0OA16kW1DObAU7TKx48OP0+HoDwSULjK/ fhHs3mnYsnr653DZfXtx4dW6LjZq5ljmcRYdB0rs38bw09vq27wbKil3sxpo6Fmgeuyvd9vz w+Tz+fDw1XaU91gc71ibz1JMbZ4VDHRShALxCuteO65hQi34LFwoyKPbP6Yfgij+fnr1YRro CRA3t5YH1NTdJkYo3m9TVaLEEzBzLd7x6JLkPHJLsN2rxcOudiAT4b+FKaoHawuW5HaW64DB luiF81NiK53m7u3OBlam+PQtfFSoSRaRRAykFRDRmT5jLlPIiFn162a9CcWH8/d/0ArgBSD7 vka8Nkpkz6IFmTcmEf7KT4eEJFKStjdrel2rwhQoG9F0XjxEAL49SWZD5deuSfjVWb2l/Mm1 qQG+zsSzrOZdlFPBMG/UbGy4yFvVaiQPxx9tKUcyb2ERjpWMui24uVQM+GVDRtR9Rhtio8KB 7tqfcsiLclUk8EFm4BY0t6+ISDZ3HmNV3248WcMgGOA94Pq6B0pTOw9qGMqPHQwfduNL80pf YlufEBUba29+xso2hgP7zKjs7PnJCuq7RHLBS8+8tezsJm3uIyAu9R48SQw3vN88mWfK+8JC OydOhGfAKf4ElkEFV7Nq+j/KnmTLcRzHX4nTvO5DTWmxtkMdZEm2laEtRNlW5EUvqjJmKt7k 9jKzZrL+fgCSkkkKtLoPuRgAF3EBARAAy/5AEKkk5/1ItFAPlLk2H5S5azXlsT1goNNgyY4I WAzTG/qiUCuYHtv9Ow2QPzdpXWqtcIdZzWYHMG3S24PuNtkeZs1Rg6HsriUcEYH3GLO/hN53 aa/7jdoAU5dRMGBJB00HV1BcKta5PEW2NmobNOkYx1ESUq24XkxF08/oppX9vhVs1l6NzaUu KOlLgwup7e37H2uNN80DLxgnkGg0VUIBIxOg2dy5rp9xculBOgEnbSlz71Ae6kmPguWgaBxV T5GMJb7Hdo4CA4ZQteyMVtei55bwG+4EzKXSZjPtcpbEjpdaQoNLVnmJ41BpCQXKUyRwVjSs 7dk0ACYICMT+5EYRAee9SBzF+nSqs9APFE+KnLlhrMlOrE/titQsf66ymy5UQuyfWH4o6Knr Ll3alOTliCd3kIhxLoDv1YpEPk8Eh4P65CmuFBJYFcdUdW+X4DodwzgKVvDEz0Zte0h4mQ9T nJy6gtG5ZCRZUYCitCM5u9F5RdrdR67DV+BqOw2vP1++P5RoWv7rE08v9f1PkBI+KH7RH98+ vz58gM309hX/qyaHnGRo45yU89+vTFkCcv1UJfOtWzBFr7MU5b2uWn1L+fnH68cHYNAP//Hw 7fUjT0NM6FaXtrMejveqUOSL65OeZAN+LxdiU4HxxMDjM2Tpz78pWUHMq+zbgVayTCRzst4q cpJ+YKOV4pTu0yadUjoRqMYNNVNPmS9uAixj5XzbvdoDiMTkBeqMUwUWYfes5/kQv4Wx+lj8 BqeBIsQKXNUej8b1gpjZoigeXD/ZPfwD5NjXK/z557qDmF8H79CUJiVkak+aPWsGawfzDdqy Z/Uj77au2OXkZaVuq5N8/3Yx2Ta57d6THzAkBvt1PIOKRrOGp3Nale8tLhg85rOw8Nc6zUzv 1dt50VlRl9GGQenbIsLvQfI957QKcbR42UL/mIWnw3fB/0CSsigMZ7qDAJ8ufGZ4mmhL6Usx 0IEE0s2rsaQ8a6rakrIB5DnaSw8dMoVKo2lHHGxdEIi1xQpL90+TESjYorHjcBuIC2oryfvU YvZEJByzwJ4t6dQGfs5FkRfQsdtIkNb7lLE0t2W2A5JT25fvbeOMbVhSdeHnwX70HMfuG3uy o2CttZZLaH47JSZxxb3yNzgQ337/Cw8TJqxaqZI6R/PDmk2S/2IRxcSPSX30gENYxA2M4uRn reY7XFS0t76fBW5AYqTRCAgi2mv4RhDT1qoLCFkFLdgMz92pbSl3IuUb0jztZiPhIrJzEAoD vSW1mlrBsdAZcTG4vjtuFKrSrC+hEc1zklVl1trirW9Fh0J3/wS13hBBTbFmYFsfUafvtbhq FaX7ntR57LruZGNj1Z17DajVkmJNTnNTZzb235Qh5ZyvdhQOq2ZQ7bQqUgtiVuC4vluDP1Y2 HlJZ0loCwra5K9c2M1tL5AzSnuYlJSBTs49jh/JXUwqLDBn67tzv6C22z2o8Wy3xLs1ID0Zm W3JDeWwbS9QOVEZvVfbMhqI2YznVguSNr/bBmRFgvm8oc4JSRl6DkOsiSy/lWRu+4XRu0BgK 3z3p16wkyWWbZH+08C2FprfQVOXT2TSeE19xKiqme0dI0DRYPOhmND2DC5peSjf0hbqIVntW 9r3hD8bi5OfGss4wHaTGa2ndWy3CM1lp++hY1GVTLkcbLTHTIpVSca4fGiJRihE4Q5SSF+W3 hipLjlMGi8Dkpev6ivpcFbo3cuFt9r14L18DuQ0kh0xNxzDuEM40DNqYTLawrulwflcOTPPI krz8UF/eufEGkzu2rRbjqKBO5/RalCSqjL1gHGlUM+i+EWjVIPpQmM63HEAz8fJI560GuGWX l6OtCCAsjeysrdN89l29sTREdmDdvn2pc4splj0e6fbZ4zN1Gag2BK2kTautwroad5MZ5XDD BSujkYpl17vow3WjP2XW64vgkcXxjj7HEBWgsx99n/DI3kPRlW2EbrQ1dxUMS7TzN/YAL8mK WrvBrTFIoc2Kqp3DZjYqee718vDbdSxTeijSqtnoVZMOZp8kiBbPWOzH3gb7hv/iVYAmvDLP siAvIxmkrFfXt01b0/yj0fteTiOGB/47vC32E4dgbOlo1dFRAXRsqEergW2+Ojf1+IXgXA2W JNHXPHZ+UoZ3dSQuICloJyD3u8oNEX5dsH3UxhDo243TViQMhLE9lo1+J3sCFQO2B/kRzwVe Bx/KDVWtKxqGef7VamE1bUkAT1V71B0PnqrUH0dasHqqrJIt1DkWzWRDP5HZx9SOnNESW2tS 5VOWRhj1YHXIfMLQosIWzdbXm6u419Nq96Gz29im6BM2FJqUErt+YjEKIWpo6T3cx26YbDUG CyVl5BbuMeJRc2MQkPs1srQG2UnzYWR47JoqK1GyKJ7IjrC2SvsD/NEUDHagJ4WhqytO9cZ6 ZmWlBzSxLPEcnwrd0Upp+wp+JhaeAyg32ZhrVutJbFmdJW5y1xbDSbKEPk6LrsxcW3+grcR1 LRogIndbJwhrM9jx+FojOU0DP0u17xlqjJ3fnvpzo3OrrnuuC4uTAS6vwhaghGmXLWdked7o xHPTdqAKa/rBNZvG6mgwgHXZoTiddScwAdkopZcop6wD4QuTEDLLwxIDnZJCqfOinzXwc+pP tsAMxGJMUVYOVKJVpdpr+d4IuReQ6RrYFtxC4G/ZSxb3zqWsvPlNx9LOfSVNVcFYb07QWPaG QUbuJ0R4lhikQ55b7uTKrrPc54GEfy+dLkxuVdLaSWfL+9B1NJwZBbil+fTl+49fvr99eH3A CAl5ncWpXl8/4AOuX75xzBzsnH54+YrJa1bXbleDPc5hbCD0UDZSJL9ZdWvjBANI7LkUb9XK 6Y/Rwc87UTWIxTgz6b0jPOsQwIPSbEUCy3MgiLFKiIBNrOXCR3qrXssq9Fx6a0Ax16FrvGaN H46UeqCPVK3rWBywUYg2S1qMhTtfOEDQ2D6rmW1fIvJAb0i1NytrUlr2tByDiInM56zWt7I9 lN3Vs/EmxHk23LXaJSF9YwI4P9lZcdfyQLF8s5s9yB7aedei5wPNaYq+NgNlZ7YQ7KQfPY3u S1YHlGeW2h3CTAH8qeiHlG50Rk4DbDN0haW5IA6E5V6ovlYxlblJ61UBKpPBQuohCn9arDQc 59lxjm/HuYEVlxg4oqd9apoU+8EbyQNPK7YW8vuhit2YKggY7tnOVuSJZzlmJJbdxVoeb0Js 5PnpXazFjiY+Ii7utnsHC4eEtd1rHG+Nqp6VBH5OCXkXqBbS07hnV9fbnD1dbrtWrhfQ9nxE WTRdQMVWlGl/I/rw/jlX9TYVxW/iikY3uz8NDTJlHoJyT7/o0+fMwm8EAXDAwKE/9xZ4e2Ul zRn4KxUmm+SCy/WtTscH9ML5+Pr9+8P+25eXD7/jy8Y3X0/hy/eZv+OhSjc/vkA1r7IGRBBX 75vVK+NPythK3iTCrUPBHtLHorIYoG9Ud4aoRhMXfSwLdyRbSZR3qYDBW/ssb1YDX37++tcP q3uYERzMfxphxAJ2OOBbKDLRwa1FjsNkPdBvalQ5nvGcCY+a677A1OnQl6PE8O6ev79++4gT 94ZPZf7Xi+YGLAu1+E6Omv1Eh2PMp/oKgoFlWV8UzTT+hu+E3ad5/i0KY53kXftsxCsLeHEx RmCFNyRdZXJsMZ2i5GPxvG9FyNRS5wwDyZuW0hSCLgg8WhTSiWL6rTWDiLI43UiGxz3dz6fB dYKNXiBNtEnjueEGTS7zdfVhTItyC2X1CP29T4Jx8tsUfAtYcqgthEOWhjuXftVAJYp37sZU iG2z8W117Hs0m9Fo/A0a4KuRH9D+QTciy6FyI+h616OPlYWmKa6DRdpdaDBdHB6fG82xob2m 15RWb25U52Zz/lvgTbTFTpkyH/bFxnQMtTcN7Tk7AWSDEhQUx99Y4+Ow2fMs7VyXVDUVZnfj kvwnsE6PAOETkMYTbzNm/0wZ5m94vB+Af7uOLs5Ave/M53zu0U2spoPQb7TZc6cH99xQPEkv D0ugsEWFkpXuNrbGrntA9bdAfbWktGSlN3w9lGRfDm2GOkR2MpFEYBWHi6yWWOOdru2zOkgi SmsU+Ow57dJ13fjppne/RgArykjOIzs1lJbXjAUeV8feomSKochc1+lS+xq7sHEcU6LPVsYt h3FZULaoBZPOSElinO8gF+CzVLTVR5DwtM/0RZQkwNkToscdKowpoNTIutwZ8UocpAdHIgTW rwE5OP4awldaa8C9XIZ8mPRqmiUJ8UyIr934ShjNXAUyuIvUDndhHX359oGHy5a/tg8o6CrC lPE1RKCeQcF/TmXs7DwTCH/rEXwCDGKukH90aFZqXFVAq3JPQLVchAIkvUwJYgDVIreGXqDP KOq0oxoUwgvTwrrOzIwplIhjWhfmPp9hU8NAOrxTaKp2ZLmiPruO5UnzhehQx6ZSKhU/aspv cUGE6iOCiv58+fbyBxrGV6GGw6Dls7zYXuhL4qkb9OskYVLlYKJQlfN4ofPQyofERPDO67e3 l4/rRAuCzU9F2lfPmeo9LBGxp4f3LcApL+D4y9KhQGlp0N8GVuncMAicdLqkANLihVWiAxo0 H2lcJuI4tBtBtR+WhyJVGtrzR2vE0rGm59f6+Pwmge3xoeG6WEjIxvmDjTnpWKB9x1XLOKWj aHg/eHE8EgPTHsgUjCJG9svnX7A0QPiS4LaPdTyXqAg/rCoHavBn1Dw/9s9bKJfBdA0K/TxR gMrk68h3rCb6xMpDaYkvmimyrBktF2EzhRuWLCIlWkkieeW7IcWwq2HVOQN/ZwVbKEHc7VIy iEAvd691Xh9oVfzB4NXyVYn26Tnnr2C6boAPldsp7R8ir1E7ZveCmevrLR4XAt13lKeiRB5Y NVWd/Gqz5A1JLUmSumwwXe1WjzP0VuCZMMpjmQFb7ckjwmCxRtfrbOiXdHhmCyK1SpMbMXyS qJmO6lO7Tfu+NZz6znh9TV6+84QRMqP9rQoBZdqDc6fLnDxjtaLQVLXXPb0VDP8wfCSDfsUJ MHiL1AxKWzeYzDi4vMfFoWoXqm7NA7pOM8vJqDticZZdXYLc1eQV6XB0uuK79bl+l7kA+RuO IKHUFjeRG6HowAZRBuNEJsfMB/WJANSvSnG9KpMO8ZwKf9glCUx7wk1R2SqLEabJ39ncGW8E pDMZKAjebtRHc769J9e/tafLhxYX8fz1UiNAHo3hvWF00XfI4E9nm6mOniJeqLQ8pSFwqLis 771JKryqbArSI0wla86XdtAdZBFtu1tH3GXAnHL4YJJZCitlg++/77ydRTUG1ls9a+91z5A5 0cmcDMw6M/Mw9mc28AeDl4xGwnwM7a5N+qrCh9/NzUEwRq0O5o+V66+/IfQExLQtH7DidWGR qOOvjz/evn58/Qndxn5kf759JTsDB8te6BlQd1UVjf4IiazWrq/fCOBve7+mash2vhNSdXdZ mgQ7yj9Fp/ipjxBHlA3yUarWvrA8Xetl4iHmufCddutqzLpKi86/O7BqeZlnSk8riAhuoNJB +Ei39p78DOyyAwVM1SW26FiYheg2xZINPkBzAP/zy/cfd1PHicpLN/ADs0UAhj4BHH1z3NM6 j4LQMqAyfFKvCBR4E8JUqxpCurIcdzqo4W7cntm+cPeGtUh5G/KxL0EPTowvBGDoOytYEo5m /RdLELTEdf06oxtnAn9///H66eF3zBIlxv3hH59gQj7+/fD66ffXD+ga9quk+gX0jD9gTf1T n5oM+ZIpBomljMnDeQa2u+njTVpStUMiPfXwDJlEXm2R0F21LyHBY1GLXaLAWn4PYExkli6d NIe7NiKRESqk49WQFj+BGX8GmRFofhXL+0U60pHLepXRCYFD2rIJTtZ5J7U//hQ7WtaoTJZe G5zkj6sRwC8zEvsj+MDoxCHWbasXx1yj1slcPVliTDXmgbOGEt1IkKFskFgTuyjnm1LOtygq HWlM0BLBnZj+QzschQ2Rqfk2F78EDv74hvlxlKS7UAEemKoErGeIvZs5vBk6pFgtP4TJttYn KlYJYiVG2TxyQVhrfEZxY5PZE4mTq5UYK4VIbtKlP/+N+exefnz5tj4Bhg56++WP/zER0pVD +sTinX5je4hdunjADoGN9uENc+XB7uO1fv9P1c9j3djS9+WgloA5o6BETPzlITWRbtnUqpuA Qo8n8+EMxXTrGdYE/6ObEAhFgsaFbRcA5l6lY+c5iTZTEpOniRNaIvolSZ11ns8cyuw6k4Au qQWBLvDRDZyRapcN9YGSs2Z8/xg7AVVQRNTdKVmj7Jqu+5KxXVSpUoGGiG2IRDlRcblqZjoJ gFOFDZiuVDw7+VvgejNFezBOorlI2T+ZsYZiNk0RVSmHQfYHptelZDsWEvPrpy/f/n749PL1 KxzHvDLiMSdeMtqNI09NaWtOGH80gzqXsEXUva1UfjUeoRMH74D/OC6lbKrfoZ6seg3H3iq9 c/ypulL2E46r93HIotEYunXMgPjsOp8O5g3nLDfbh3eRkzj09edXYEbasSsqF14wRk8kVE8P KTFNtx6KKwwTfTMvPhfdKUgXxBvaW3+4hJt5DFUSrsL45kBKKNF9kPzjYDXwQ1dmXuw6qkZC jJxY0If8XxhRz1lPI08ERGWQ4Oh9ngSRW18vRt+QIwbeqjYOpvKXcOwiOuqFqs5PdlRsp8TG oGYERvsL/9KrIvw/9BFlYeDE4WqgAey55nLj4MR1aPD64wlvEQONMYlGbdc69t1RUzrXU7mk Bb87xfshHtdrrpwwf8bkmh/NM6RzlJqSkaP6PPM9vVNE4+ZCOh5BC0+HlrIiijlrs8ez4neo pgC+umibnNmz+8v/vUlhuX4BRUlny0Ar31FE56vW4tq7EOXM28X04a0SuVdal7rRWBnrjYQd aR2A+CD1Q9nHl/99Nb+Ry/wTJu+gjH8LARP2QhOMX+0ENkSsLl4DhS7zuTVbtkbsUrtWry60 dMHzaYQh0GhlLJ5YOo3FP1yj2ey2bx0gkNQ2CkexQ39aFLuWby6cnQ3jRuo21NfLIorxZznS i6bv8IDqrKPdk0UJ0NnJqOrlmQ/x4DYBXR5oonCnq/7iRJ4KvMYwpRyT5hm+VQt7h3bFg8M2 TrxAVEANPGefEy7XsyYBSMSq3M1yjPnQbdXKLk1x3NVxqAvnqGUecbzhRHVCypI5l06zIU52 gXZMzbjs6jkudVLOBLhgQmUlqfDYBnctcI/qQlUc26m4UJthJmF79dE5+eEaUGSamIGrNvZP XmRLQbD0kMsSRC+4QjauFw/CQQw8nAtQJdMzmT9jrhwWkBtpx66B8SyY+QA0cPKQRwGEzIYs x+jewgFpDxYOyYTmVvoxcKmifDs4tpxVgsYuhswUKFJ5EVW/Ra26Nc8nmypZDX4YkK9x3rru 7oKIbDYvBm5pFEQhaVVW6omiMPGpemC17dyAYtAahZ7uREV5QbRROPIDS2EQPO8NOqv3/o78 eiGV3i0sJdRovVb5+scLFy/Zueu92g/AgMgenzPmOo4l6d38VXmSJGRko8Hj+c/poj4hLUDS NCl0eOFb8/IDNEHKy0qmP8+jnaschxo8puC163iuDRHYEKENkVgQvrYjVZQbUatGoUi8HZXo PR+i0bUgdnYE+a2ACD0LInLoniOKDstYaJhPPhl8w2dR6NEDM5bTAV8dbhsQ0im7262Srihy so5h7CieMuNzFlIp9zE9Pt0pcdRYQ3U0MupwngnK4BHT7K6bPkQuSLAHGhF7hyOFCfwoYGtE nbl+FPvYW6LUAArHeUiHglEfeqwCN2bk27k3Cs9RfWYWBIgdKVlnZLGBLgTi7oi6/J9JTuUp dH1izkq0TUmmsqq4HOLobsvvsh3tEiXQIEH0rkctFXxJNT0WVKOCp97fH4Imsjqua3SJJV3M jQYOr3vLHSk8N7B0dud598aAU+wIdsgRITU2HEHuIzynQ8cSuq8RuXS4kkYT0jFWKk1yf/6B xHcjUuhRSMKQOic4wk8snxmGd1cWp6Be9+CIJCIR0NWEKpJ1vkPzrSELyWN4KVo0B8/d15l5 MC9zWau3+jdo5JOrqd44F4Dg3pEHaOKkruqYWmWgqJFQep3XG5ygqklBSkETpyRAyT4kgefv 6G4AivRi0SmI7dZlceSH5ImMqJ13b2CbIRMWoZJp19ILPhtgNxHfgogoIroDCFAniTFBROKQ X990WW1z/p2/5BAHibLZuvr/Kbuy5rhxJP1X9LTRHbsT5k3wYR5QJKuKFi8TLIryC6NGrnYr wlY5JHmme3/9AuCFI8HyPsiWMj/cCSBBJDI148gJaXhDJupXTgjKwo4e/2oweOyyb+yKId7v a7DkrCT1qRmymtRbFcga13fgWUlZyArghzErpia+Z3jGv4BIHiC62W/Kk0MPjYDSyrcWcLqN DGYbdcoxKC4U4iIbkIppfQdHf1yyb7SIghzr5oJMIb5pf6GLJNpSwRjE8zxwIrFjcmB4RL0I Xp/S3WmrgvTQ5Vl0V9W7h3J8NwiBk8IpTiLLApY5xnAssLZ9Uqf25t79OQ9sKNP6oWD6ls4g xxbWEyjD2Vq2KN/9C8wvBrZOzcJqUaCLlG7HwO6XUqXWs4AFijIc2wJ3I8oK2NeyrWoXJPbC ApSlmQfG+pRBOxfasUl89IO+10LpSnz5e4rEcqHPGQuibYlhEpCiCMBgAOvaGNsOShB8LCYh chCUL6b9iTalICvxaAkB0MUrJoHuOpBu1cYhcJRvj0UM6UxtUdvQVsTpgMxwOthEyrm15jKI 4Rm8APFt+GPbDOkyHKAAuj5dEK3t2OD4di1yDNcVM+QBuWHoQhbxIgLZid45jBEZGY6JAXQz pwOTfKSzBUg1yxUQOV3F2639dcQEJXAypiw6r47AaXrkpCBrvlCd6Fxdkl9pT6SBh+ol6pN3 BZQWaXNIS/aYkH2Hrvb7IUlz/DgURAxNNsO5/g1fOEyIyhQxYWQ/NBl/nTy0TWbwljhDp4ju w6HqaFvSenjIwAAoEH6Ps2aMpQr1jIjk7v5IjUFbljnB7Sx/tZIMt8Plgf+jDaNSI53PAgXg VnG+PTNVM57VqIgbeM042GREuLECcBPqAbfxMamEis8U5QHfQi6rB/xYnWSPnzNzfJfDnxtM oesh450FzlxycGs+lp+lsWfDqNEL1Pn96c8v16939evl/fn75frz/e5w/ffl9eWqXLfPyesm nfJmo6CZSi4ZmnzokGrfAh00fZMzMHyRIY+Xu7CAPplGVM91tLrYJo9P0rMya2OcC3aM6zEb qtR05bhRqekFIJT4c5Y17NJ3IzXnkxpMPoe6h5Kvvfawlf18s6X3DfuW4fY9wKEScQLrg/Os CG3LHh4Sg5uFwLWslOxUwMQeTYUYU8yV9v+AHS3T0aaM4H/86/x2+bIKYnx+/SLIXx1DNS2y nip2D7CdGFRQHWemgtb79ThbS4NmbNLWYkBFQjuirgjJdsrLUdnRxUTdxQUW4QJZ/ov7u+Q2 QFDmEsJUDOeTKlYynkOIx5mWI9nnmMCeT8SkzNXzEBfwXikB4TvJETKZIazPoP74+fLEbJZn XwPaPVOxT5SlmFGEq3qRStxQ1t1mKnhcqwu+P2iGdjwRbh0U6kFkZRB7/zaw97ZxZXDFsqCO eWy4xWAY7l3GAr/RcLZu1sdz5hfuEE1+ysbougXeSjU7cmGdzwyGQdOHhSsaIC9EBBEjraNH ssFYmw0Q2xnAWCULVwy1zLKcdiitC8YNSqcFQPrAVStKqbbBDxtjH3CbMgt9MhxAJzO8t2Ob BXhQBmYkTtWVR6d2Agf+IM/YxyygRyLeD9CVb8te15AsllrCqLQkxdB2YuY1ZYovvBiBKF6d aMHZJxIYIqYx9kdcfqZLRQXHAWMI3bKUUbkRBmjgu3KV4RPsNiSp1m0XJnoYBgaXfivAN1Vh ZIv2qCtVPIktVOTpVBRZIUB0fKC2KDJcpKx8+KsZ57eBa3D4N7Mj6BMmZ86ak1xTpj/IlNk4 Rqz8TFPvbVW2/IaA5y9Ysork1rcMzvY4O/ZbH0H2OZx7j+SPDpxY+m1gQ68/GJeksRbHmNMz Lwx6bU8QEYUvvplcSNrzQM65f0RUTuG1b0xKDFEad71v3dicSFvUG9xHEoPPvhmzzQZcuK7f Dy2Jpetsxh3tv9XGMCMl0A/xlGFenNQkNc4LDJ7laxLYli/JwWh1Y3AbPzJD0/ap25GvVPFm b6E6trZ2sCbQJoI7kcCXTN+F/DQJ5HQUbFZZMmYXqA5M1Xc8yqELqitI5Hxq0FWqmYNPiTgt JzN4cD4wL86huy2GeeH6oO0cL3O0/9f65lPRI+grLGN2PfK1tTKv4mOJDxgyDuVa0fhsQlGV RiK083KtxIGvinjLC9+2IJ1yZqojRw+bUaQJFaeaV3DK9oz7ofrhbKVBDWIc39pU9HhlQAeH bMGsjgVVQ0N7fLMgL6YTjypd5rasGWyASMuUGYMP7XFN25v1joc4iVwPmlHzUXwRYtFhgOkI sh6a1wu5pbyFqD9S1RD7rE+p3FZ5O5quaADmbOU0euUhJ+ld6ophH9H4NzQRBVSHakQHZVmB UUxvgrb/FcQOWSjw4XLmE9h2DonvRsiQAT+sbSdXzjcrB5BEkTmdljYzV08OCsfQ7I2npQoI WvMkiGNbxjKUkDAAaI9L3/VBq7cVpGodKycjeeRa26nZNbcT2hjqI7qsB66h/5mCEN6qPwdB K6gIQaEDDj/faX0jJ4BZ425jqDNlBiHsYXpFzQeLX4D54AYmYVDgRVBFOUu08JJZ4/kBLpad I25XDkWg/b6EUQ46Kk826Fa4yGCnrMKcG100nYwV16wSP0SmilAmMnxXEFG1TZXAm7DaN7kf F0EIGbx9y6Cbq3NRfwojwzFVQNED3I0FVDid6bz96XMqmSkIvA4hC5ZAzkKGlYszQYMuAfNQ QPny90+yx4mVOZ/hdAbVKiA6cYoaWzZcS8YkN3qO+AUKA8NEI/mBBXfbbiehhzsrwIYcHhFy vFtywOxW7MDdnqvCYQnkOS48kOPxxwFlYz5PmXnw2iAcqeDmBL7t3pps8wns12DQkVMBRaaN dj443S6Jn6K2SxqPT6B6J3vXWBmqCt/onx0oqTBEwMozg9vJhjmHiauEKoxmfpfFKXT2jtdv HwKlrFoWuErQTHkkKs5r5MPGQmfPC2FnKSNm4uuJJwbVm5mrBljdn4C7pOm4Gy+S5mmsX/4U ly/P51mxf//7h+hkcKopLtgX8LUyEheXOK/oIbgzAZj/zJaq7mZEg9mjbQOTJI2JNbuMMPH5 g0ixDxdnDlqTha54ur4CsWy6LEl5dEZtfCv+GiQXRz7pdvpBSs+cF9o9f7lcvfz55edfd9cf 7JT1ppbaebmgha809RQrcNi4p3TcDaEmRyROOuPZbESM57IiK3m4svIgusQaEe2pFFvOC98/ lHRqiY2HGil1+eLZbe0Cdb4s/cy6V26V0sVaZjy35Pnr8/v5213bQYWwISuUdURgjQFMRSzu af/hmkXk+6cdiKw5qiTvNjkkLONy530k5f5/hrwihAUqgG+3KfyUp5CTp6nFQJvESa3dFI7T Js6EWSEOw/nH+09J+BWBaR+ozg5/8pkB8ssHPfMP55fzt+tXVmPDHMu6ttOlmlFF7+NZFbc5 vHhPorvjaTYQx7TPTsVwSAtT3F8JVzWZwQ5qhBU9dLM9rRuta/PTmLFDPvz5979en7/I/aKU EPfgXj4zHR+JFoszWXQ6s9KGXY7j+10mh34S+Mok0wFFnR70tLsWeeZKEoxD2/XUCk1kZZ+U edqk11GyaIoTYZ0mzDBgilurzX/chbbh8zlj707JIW3N33I5xomd6bq7NsaEZcA6p1syrFbx VaKgNYHPqTx1C388GHmGeyBcMr+ym9UvmU2YuVLJrsmSgxlAikyNETgrVHyLXxZMUX0bN//M Cy2Dsr8ADJarI4AuyBn/bQPTptgPDQvYVAyVo9AKYGOPOZM9PfcbNGKOGD/63wAguLV0A51A GZkNRiAldJn0rifqx9My3KV0pawKhb477R1Fc13pgJLB6UVaVLW67XNOUoy7cnYA8ytwnotW NnJCIq8dtNWLNgc0WgLSGjn0ZxM3TrFfyJCpl1vAcRUp4g+EiRZbhM7A6kEKMhAevrsx7Dhe PqqjpiL2z68XFmHy7jcW6PHOdiPvd+NCtc+aNFH3Nlm5FZ2TjaTzy9Pzt2/n179NegFuWyxb Mkxbb6NeivBc8c8vz1eqRT9dmfOk/7n78Xp9ury9MSeOzB3j9+e/pDJmyVQuzyZygkPPdfSy KSNCHrwmT4iUBb7zoWt0ASC+lJ22a1K7nqWRY+K6lr5jEt8Vn76t1Nx1MFDtvHMdC2ex45p3 0VOC6camafb0yCu9a1upbqRSu9oJSVFrCwCpyke6Fe+HkbcIx6+NGR/eJiELUB1FukoGozO7 JWcJvh5sxCz000eoBC0GEfBCuiI800q6IAJrS2dlCAQ+iV00GlvreEr0A1D7CeCPoCP/nlg2 +BxykskcBbS6QQgqSLYmrCO5B+SPfccPQRd08zysfduDUjKGwYhrQYQWeLM7nwEcJL+ynOmR ydGLAIC+d69s+TPVPAd615E/BQvyx8T6LEk9IMyhHWpTiOvTnuSqUJFooZTLy0be8kMqgQG+ BhREPwRaOzK2E7qiTZVAlm8kZkbkosi8SOF7hEAJOxLkqDEmpH5a+kTop+fvdMX59+X75eX9 jrkJ1zrsVCeBZ7nijZrImK4ypHL0PNft6cMIebpSDF3n2BX2XKw+IEHoO0fYV/R2ZmOsraS5 e//5cnnVS2A6Bnsbaqtv0OcYMkrScdN+fnu60P365XJlDvAv334IWatDEbqWNuSF70iP8qfN HPpkRFjgvzpL1FueWaUwV2Vs5vn75fVM07zQnUQIVaKeozPf31ocs4J20dZKzQHw9dEK8GHb iRUQ3irC4NViAbi36uD68MltBFSdE2xqNAxguCVbAZsbJwfcqEN4ow7+rUpSwHYRFADfUMyA INjcaFgOhpDNAuBWHaJtQOj48FF6AYQGO94FcKujwlutCG+NBUKbE6fqolt1iG51te2izZnT kSAwWHtNy00bFZbhhaqAMNxtrQjbYNexIGrL8MR0QbQ369HahiutBdFZt+rR3WxLt90W0liu VccGH6Ajpqyq0rJvoQq/qDY/hjYffa/crIt/H2A4OogA2NLeKMBL48PWXKEQf4fhx6IjIm1R eq+I4RzHCNxk+C6TU5p+qJ31Gx85kB51H7qba0fyEIWbuxEFICscurgA6ytVajzifzu//Wne HnHCDC22upgZihrM1RdA4AVgdeTCR42lzlS9YlVJVJ5yszbd+oyt+Pn2fv3+/L8X9n2V6zHa pwWOZ2FSavF5l8ijB31bDjuqcJETbTFFBV7PN7SN3Aih0MDkXwvlx1IaG3weIKCK1rF6Q90Y LzA0ivNcI88RHacoPNs1tPZTa1u2obw+diwHmXi+5AFE5nlGXtHnNKHoCE7nhsDt9sSPPY8g w4lRAjLV2uC5SxcF22BbKwD3sWWBxi8ayIGbxnmGwZtqYUiZmntzH1Pd1tTTCDUkoEn1O/Cx 0BOOLMsoyiRzbNBPqAjK2sh2DZLc0DXWUDQdZteym71BJAs7sWlveYb+4PwdbZgnHvygFUdc it4u/Evt/vX68k6TLHF2uDHz2/v55cv59cvdb2/nd3qseX6//H73hwCdqsEvNNqdhaLon98V IndeoxA7K7L+Aoi2jgxsG4AGLLyYRGRThC4eMg2hhLjMe8h3sFFPPC7Of9+9X17pKfWdRSc1 Ni9p+ns593m5jJ0kUSqYsUmm1KVEyAsdiLhUj5L+QX6lr+Pe8Wy1szjRcZUSWtdWCv2c0xFx A4iojp5/tNnnYG2gHIT0cbagcXZ0ieBDCkmEpfUvYl8xtE63mL2YBmXOCiVilxK7j9T00/xM bK26I2vsWr1Umn+v4rEu22PyACKG0HCpHUElR5XiltDtRsFRsdbqzwK4YLXosb9CWxSx9u63 X5F4UtPtXq0fo/VaQ5wQ6AdKdAB5chUinVjK9MnpYRjZUDs8peiyb3WxoyLvAyLv+sqgJtmO dWKxg8mxRg4ZGaTWGjXSxWtsgTJx8D6yVGlLY3DJdANNghKHbiYNQPXsVCE3be4g14KI6iix 1Uup5ufEpjsTM8ipElGU4mkRNQoRm4RIld6xKxxwiNUFbFxEwrlQ3BJaZnl9ff/zDtNTzvPT +eXD/fX1cn65a1eh/hDzpT1pO2PNqOw4lqUIVNX43GGTRrTVXtrF9IShrmP5IWldV810ovog NcAqmfa+Ovps3ljKQopPyHcciDbQZoP0zsuBjO1lcchI8uurQ6SOH5V6BC9KjkWkIuQ97r/+ X+W2MXtoA+2jntsvojkZsQgZ3l1fvv09KUAf6jyXc6UEaDOgTaKLJ7hPcFZkzSWSNJ6t6eaT 490f9PDNt3RNk3Cj/vGjMu7l7uioIsJokUar1Z7nNKVL2HMbT5U5TlRTj0Rl2rEzpKtKJkGH XJNiSlR3LNzuqOqlLjZ0fgeBr+hyWU8Psr4irlxFdzRZYmulq1TqWDUn4ipzCJO4ap1UQaZ5 WqbzeMXX79+vL3cZFbHXP85Pl7vf0tK3HMf+fTN27rzAWppaU7P+V7VuTbnmZbfX67c3FmqR Csrl2/XH3cvlP5K4y5ZEp6J4HPYp+KnCZK7AMzm8nn/8+fwExK7EBylcSnfALDg0ZM8phm+l f/C7D6p9SI5fGD2p6SLTb0St5iAeD4Ck+Z7Zd8gZ3xdkCqSs0/c7kLXndruizy+NWXVpM9rW 0K1FZ+cp5kEwiRJIiSFYhO+BHq8SZkJSsFC6QJvjFDKmYMy2VfLrGlyAzaBIkH5Ii4EcmfUO xO2U7El85G70lxB7053iHV2E4BsxlmqMNE5VmEBt3BirN1cMBRVA2df8u1CEeij9wlY/qAvx 7EzVHHf7ppA+As5XjAJZLrXBCRx/njFxkRzqk1rRkTqo8Xt1RJzdb2bMH9XWrTJOE++Am3aU /9UJG47ru99GM5P4Ws/mJb/TP17+eP768/XMrJTl8WJxF2kyyU7ll3KZtsW3H9/Of9+lL1+f Xy63yklioKsodTgmMWj7zWf3fdqUaT4nXmyvNwqWyyirU5diKKo3l/pDWqi16ugSYRoY0qro 4oAPDvjYistPjBvmKe2YFNoSx3l5lxis6CjiUw97D2S8XRUfTdVkL7ZZyMr6JMtOjWlXztIy 92F9frl8k3eJGUrbeyLDZ8tqh7bwa38o6VHIj+D7sDXVrkqHY8ZecjphBHnykaFtZ1v2w4kO Va6tGiNK7SQNsHzdBhKneZbg4T5x/dY2uGlZwfs067NyuGfO5rLC2WHD40spxSNzMLl/pIqd 4yWZE2DX2m51lmdtes/+ixCyY2CQhqwsq5xugLUVRp9jDDftY5INeUvLLVLLt1SLEA1+n5WH JCM18zd6n1hRmBiMs4SeT3HCqpq397SEo2t7wcOvJ6F1Oib0uAZfqK9JyqrDLAkXL5MV+IKu 8qxI+yGPE/ZreaIDZvDDuSZpMsKiQh2HqmVOnCL4uk1IQBL2Q8WgdXwUDr4Lup1dE9B/ManK LB66rretveV6pfg1eUU2mNS7tGkeqeLTVic6i+MmTUt4hBv8mLAHEE0RhHYEfRcHsUhxDi6A qvied8THo+WHJTty3Orvpip31dDsqJwlhqtQYSbigpzodCBBYgeJaVlUsal7xA5cYQEUuB+t 3nApASZACFt0kyGe76R7w700nBDjmw1Ns/tq8NyHbm+DLkNXJNVh6yH/RIWpsUkvXwVoMGK5 YRcmD6CHcgDtua2dp8ZMs5YOX9YPpA3D2z3ATFdx3HuOh+/hZ50ruG1O+eO0I4TDw6f+cGtS dRmhanXVMwmNnOjWqkDndZ3S8ejr2vL92AlhCyllHxO7anwyAU3ChSNthevpbff6/OXrRdsV 46RkAaHMql18pN3d0gKYEryx28zLMCWVPFidEcn2voE9lzUdDIr0gFlINOb9Pal75pLgkA47 5FudO+wf5NYzDbpuS9cLtLWJqbpDTVAgxihQWJ6Siir09CdDUuCskZFFlugdYyYqIVBG8v9R 9jTNjeM63vdXuN5ha6ZqZ59t2Y59pCXZUltfEWXH7osqk7i7XZPE2cTZN72/fgFSsggKTO+e EgMgxU8QAEEAD++6/77F1GmiOMP0tf7MgwEZDc0swwqfyyheisb5dvY59sZugYXnbykVIbDs VTFhEz00eJnNprBC5j1RBssWwWgsrUydVCJWL3phv4psP/MmnK+pTXZD8jQTbFBQBOpQ6I06 HfXYhYH6RAntJNk+EItxMnp/U9Evh1UmdjH/dEP1pvSLtUt+9+OyBBH1NkwtUTfBXXGwlkGw skaqHJn37o04by9aSQG72KYQO2FzmXCv34jj0/tQVpLjQSCUhFmlTA317TYuNxZVEi/x4W+g 3hJpL5a3++fj4M+Pb99ArQ2uemxTZrWs/TTAHGRdPQBTj+MPJsj4v7FEKLsEKRWYcfXgtwoa vgsl8xYdv7vChzFJUgIv6yH8vDjAN0QPASrCOlyCLEww8iD5uhDB1oUIvi4Y/zBeZ3WYBbEg IpbqUhU1GGZ1IQH8YUvCZyrgWJ+VVb0gj7dwUMMVCH7qBS3twG4tYLbpgAt/k8TriHYohYOg Md/Qqqs4Ud2v4mzNLpcf92+P/7p/Y2IY42yobWT1ski5hwZIfQD5dTykIqYJx9XDFxVwYsCY VVbJOJUVF4oBO7amk73FRWgVx0j1+LaO16RxgEeBCtbjwme7GKaSb0AZ72gLEGD7crdg15P+ Fs/PanxjHqw4zSoVvfUBDaxT2BthBoI+/5mW6iCr+HYbMtXWa75i66GZ0XJlBKNjoEA0pGMH NntJhkijPxkkUR0IS76CnHUC2rEDPYtSeu51afPwK4iZ6AYhfD/kkjYgRUw3J/yuvd52UVCH LIBrMsyBp8WOBm8OZW7V5wWO6IOA2+V5kOe8/I/oCkQ47sUSbkCQy8LejhXlxlVZkTpq8kWZ 6tOJcA0NhSNPwLm5YxNhEBp/K6s8tQcT49i6WoSZ29b7ajJl7XTYfx3ikG6WEFWnPLW20BJG yhS4OpgK7rC2zs0WxywjJfY6OZbEG3Leh19198b2om6dTTkZQR0Hy/uHv55O339cBv8+SPyg DcLChDxA04qfCCmbSDzMoF23IyE0u9hRNMlO2L50VMUdx9E6vB0RscMwEao7pIrcdcenOumo rrGOmBqaGPyflgea+dzUqSzUDYvqxwc3hqMXHK3DqfCGQ+FELVhMMZ9OHV0sUMwsuQOwo+Gy hl/72KY26M89iaJttGYHQ3qTFHx7lsFsxIb/ND5Z+ns/y/jyTUTVX6w4a1Fct9AvNkrbFhDa MOeT/aKfF9Go2gTqWU5/1cqSCfJdRti6gYLPjbgXmgaJn2yrsakaK1yAMbOumGsve7e53Vdl vs3I0CjmEMVB/+Y3ikkQE/h5TSYvqzLM1lXEtBnISnFnFtxi7dx0YY0MA9FOEq/HB3TFwLKd WEuKiglaO/kmwBFebvd28xWwXq1cZQriR69AW9BIEgpbhskmzijMj9Dsa3/Pj2L4xQkxCptv 16K0y6QCUwk5yygvXuvbhwLkY0mBMAnrPEPbuKl5tjAYA/u7IV6eu0YGY5zRc1lBv25CV0PX YdpEwTGBq7JXyTrBCEBsaldEwxeUJd0utjlwRxdi7kRS5YVNv4vDO2XEd6/EQ6kUdidBjLmT 3NjKjfsiliwHRlx1F2eRsJbTJswkaHtVbsETX+WWs4BhYAOyfJdbsHwd43bhofijKAhz0XC6 ThBcbtNlEhYiGFvLhVCtF5PhZ/i7KAyTTxacEo9TWBZhf38kKLw5yx1UViG7FGjmavE7pyiN /TLHxGOuitH2W4YHOn7pNqnidn0a8KyKKSAvq3BjNwqOZkwQBxuAk2AURViJ5JDtaWUFcBU4 vFigtgHRzzSY6+no+lhDB+tJuurwYy7QvaJIRKYuJHyLExUl3hfbFUqB96SOuprrGlqPLMIQ TWAbC1yFIu2BYHHBsRJaTYFKi2RrAcvUmqs13tkJabLZK0hvCLPKVJTVl/zQ1Nudswbcvcyr eJfbIwPMS4asTKuwEfCFHhOtohI0pxSEFkfYSiTa4sFcF5K/ulCsM47TvHIx1n2cpRZX+RqW ud3zFuba/qrcIYCz2LmLdYrOOtr21nKD0Xpi88t1midNOu/27R0jUVw9oFgBCA3nrRBkuCER 2hZhAtvyW7ms8wg0R2JU7EYQ8UwsUgTDHkTtnA9giATbpIhrKyM6IYB/M1dKNMSrzIWRkHXk B9bXHSV0Djc1ZEiEXTVEsyu8+PHz/fQAA53c/yR+kddPZHmhKtz7oeNyALEq0eLO1cVKRLvc bux1Nj5ph/URgcHn+C8cipCXFrBgmcOEyru4YiXQNCUmgeKulOEtiFgpX2GD75sNWmaCMbC2 goRiTf268Yw0YmnpcFrR+f2CjlOta2rQnwIszsS/NLAyiNhkf4i7W8rAakq8gu1oAWUAkn0e 1T7hD4jxlzfsRRvidio6bUoyQAF4Cw2KZzDsQwr3byOaWxCBkbx1dqy9EeRzGSJFWhlnTAqC cRX7DMRKKnh8Pr/9lJfTw1/cmr8W2mZSrEIQSDCVRk/tMWtxT6Ndpxr9lI5yi/uiJJus9uZs xp+WrJwuDANMFt61YkArtIV4V432IA5W94QuhVuWKG5koJzU0R06/GbrsK98oq7OjJiqoTWj 8IIkUghRjVyxRTRB5g3H0wUnf2u89GY6oaNVDlPJc+ZO3TU/nXmmObuDTm2oykQ07H1AgXkf tBY/m/wCvxhzs3pFD80ghgpa+GIxpSHhTHjvxKBUjvNEfw+zc03srgPQtOw1wOlUZVdIU5p+ +Yplk853WI+pcNbvE5rFWF+bFqvNesxATD9ZcEgw8z4haHIhoQGJVWsVkW3y1FWbGQoUxEwB RBZaMJ4PmR5X3nThXLNdxlET2iWzMKGVLzAQf+8LVeJPFyM2X6iujUnScV3t07+dxYy0f7Tc pgrGswV3XanQsfRGq8QbLeyF3iC0Qd/iM+q5zZ9Pp5e/fhv9roSFcr0cNDbDjxf0MWekxcFv nQD+e49TLVE14XOx6h4me5hMNx49wt1Ynceu2TKuseCy1ymEXKfeiIayuY5I9Xb6/p0cK7ou YN1rK6asiVDZwznRmxDlwPujvHJWEoUg1CxDwamkhJC5XCV43/SHJhjhg5IVVwcHmhqxCarN ba94lBqv0+sF3wq+Dy560Lrlkh0v305PF3ySoBzWB7/h2F7u374fL/21ch3DUmQSPUV+1X2d K8DRzkKA0u3AZWGlg+vzDSiUPZe3itBR3LpCAONdKaaMRsfnA0tRVr6WEjhHH8wDjNdLNKD7 FdoXUrVXXyr6TjIY/zbM1sRJBmHXJGcgf2RhIik2NxR6gWkfBEhS68DMkB3c1WIfIzW96JNJ HWJL+t2KlaNgDMgZ8Ykrkn3Nl1B3WRGWqNN1aizzDkEaFKis2CTocAPtk1nJt+WqLqxGXAfV fzodXy7GoAp5yEBmVs22pgjVD66S5XbVT7mgqlnFpn1d3ikoUT6b4twy0qg6zXdh4/j0GVn7 cszxAkMTAfsp+MiEVjeM5b7dNw6evCaH7l+c/mxyGfhR+zGxrCKowJQi6zCLS155QZoA33j1 aQwKEfp2xXCy+LnkxAL1Wbza1rcwtInAO/a9NpZb6bA5YLDwlTuYWckGaTbQNGFc884F5IIt X2FQcNtop9LQYylSmYJmDkVfY3cy93m/B41H87BsTDiNC2Jfezs9vJ3fz98ug+jn6/Htj93g +8cRlDjzHv4a/PFz0u7z6zI8uKwgIGMCv+OlinWeBKtY8jHXtSABbJk1wd7JIs6SXCm9+vB6 OoNCKs8fbw+Ml1k8H0+9uqFvP5BslkmgUUQvRW0UfZrrIq5mE958w37uqrKKOFnmhrh3jTOe RmTWW24OxJzmq6up6fPSGMZla6fxWB9fMHrAQCEHxT2c6SpkgOxP669I6XesR34lKP+XIwaP 7o9xGaJltihz4ojLlNA1vT6/f2cqKVJpWNXVT/UO14apQ2dNje02BgE21tjHbQtJS4yVi/fQ d3HZN4HAPhz8Jn++X47Pg/xl4P84vf4+eEdx/BsMbEANjuL56fwdwPLsExtC++CRQetyUOHx 0Vmsj9VuNm/n+8eH87OrHItXBNm++Ofq7Xh8f7iH1XB7fotvXZX8ilRLov+Z7l0V9HAKeftx /wRNc7adxZvzhUa+3mTtT6BF/d2rsym0B6Ew29c7f8tuc67w1Vr/f1oFxsGLT8Z3qzLkzsVw X/mdFB/+fQEhvZEf+1Y1TYwp5OsvwieXdg1qJcViMufslw2Bnf20AXNJPHsUnmfmF+3grVbN IOY0KXqDKqrMDjlOCcpqvrjxRK9OmU6nw3EP3NrkLStjXnIuALEp78CPGqSplXlx3cFqn9zy GAi0GTYph/lP1JtVvFLktOJGawkD9rP635Vky/RI1edlXSh1TZOMaWtBjnX60jX4rnLNfR4e jk/Ht/Pz0U5DIYJ94k2mznTZCn8zduKXqXAF/wfUxPEgcJn6sFKcbq+BGJsR8gLhWY9MUlEG bIh5jVn0iFnjv3G/p1pSewGdDZDCGgSoY9KBw0s7C7/Zy2Bh/bS9Njd7/ws+DXbERfS9scdf WIibiblhGwB1n0YgyasLgPnENP8BYDGdjiyNroHS2w0EsWntVcxIsyl7fzY22yarzdwbEash gpbCEXPBWqZ66eo8YxiRpAmcA7wUGGh/Id8MF6OSe+UEqPGCdAogs+GsjleYZRzfpCVJyD+P B8rFgre9iiBWaroIHFtH5fS20QZyPkekwfeyXZjkBSaKq9RDPrPJ0Z7PIZ5U/nhyQ3qnQGxS AoVZECMrnhHezLEKxX4xc8Q+Tv3Cm4z524JMbO3MyL5hXMDct3UsaAyHDrNzDWhHAhRc92Sg TtE0D2wbdqXKDPUD+e7GFaFyZD2iM5ApHI57OklN9lMYG9p+gM8Qvi74Cd+tZqNhbRVq5JV9 r8fthvhs8ZvbQ0XxGYQkIhVyqTKUvkhIDsd+iUawfX0CUcd2e0z9iZ1n+yrqXgvoEj+Oz+r6 W6rQznRzVomAIy1iHCgsmvBr7vayWKbhzDwY9G+bs/q+nDsWbSxunXnTQJ+4GTpehGOLYswb WMt14Xi3LgvJcuzd1/mCJO/pDZT2iD09NoABTFwTA4r4xrZnlZYTmqssHt0d/52/CFu/uVYw 95WqQjYjqrUjWbTlrm3qhOYe0joiaYU8rjmCaHA0zPii1qmL20+HbPQfQHg0ZzdAJhNOVgDE dDFGU7/ps6qgXkkAJD88/l7MaI+CIsdHBTQojZxMxlwT09nY88yjWOynI5snYw5IrqxfTG7o 8wTgU/Dl6fTGERde8R2g4M2On423dlaCxfL48fzcxu8yp7+Ha54KHv/r4/jy8HMgf75cfhzf T/+Dl1lBIJvYdoaFR5kv7i/nt38GJ4yF9+dHE+/HMs046BRh8eP+/fhHAmSgQifn8+vgN/gO Bulr2/FutMOs+/9bsnsX82kPyUr+/vPt/P5wfj0O3vt8cZmuR45I8Ku9kGOMOel2IG42/PpQ 5iC6cqul2HpDEotdA9jtqKthBV2FYuTcuFp7bXQQa0H1u6253PH+6fLDOCJa6NtlUN5fjoP0 /HK62KfHKpxMhuxWAvV1OCKRtjVkTFgfV72BNFuk2/PxfHo8XX4aU9Y2JR17I7L9gqhi5bIo wEipe5ZFR9s0DsgVYVTJsZn0Vf+m8xRV2zGR82QMBxYrBwFiTKal1yO9t2FTXfDS+fl4//7x pnMvfcAIWYs0hkXq1ABX+1zOoSGON5+bdE9j78fZDtfhrFmHLh22qhOZzgK5763GBn499ltm 5O6MvntWr3CYTSiCLzAznkNkEMF2D+uJ36QCY6Jzhz4gMHEgOYeKQC48h0KskIsZ+zAsGt1M yYmGEIfO7afeeDTn1iNizFMHfnumX4uP3jtT+ntGVcF1MRYFnzJOo6DHw6FhGrme/jIZL4aj uQtjujUpyGg8ZTeOSGwHaw0vStM+/0WKEYnMXxblcDq2dKTS4aqzgxmdWB6EYj+ZuGJiNUg+ Ak2Wi5HnSACcF5XnynBTQA/GQxt93d6jkedRTjAaObI4gcLteY44WLCZtrtYjln1x5feZGS4 VynADVXmm1msYM6mDh1S4RzJHxF3c8OtJ8BMpmb+i62cjuZjwz6z87NkYsUN0DDPkQ4mTJWG 9gnyhpXfk9nIVDq+wrzB3IxM3kN5i76au//+crxoUwbLdTbzxQ0rwSLCWP5iM1wsqP2rMZ+l Yp05WCigPJJo0tgsWCys8jSswlKbvAxjj+9NxxNuGBrmq77JSwltc2x0u0pAl5zOzZSGFsLW 41p0mcL6Zc6f9mKTG+h/u2ZUeH060gS2StXZEo2MEDYn48PT6cU9e6a+lfmgxF+H83M7o7bb 1mVetWFhjfOL+aSOydt4TA3+GOj8EE/nlyPtUFQq9yii+BlodA8py21RtQSOCa7Q4ynJ88JV kTzIleQquXaDb2xzAr+AJKZTeb58/3iC/1/P7yeU5MkYXzfVr8mJqP16vsCZf+qs3J3GNqaM K5AjZ0Ya0L0mDi9Z1L6GNPGMgSH8qioSWwx1NJPtAgyd6RSTpMViNOQlbVpEa0SY1xJEIEZ+ XRbD2TBdU25SjB3iRJBEwBb5x7RBIb1fmdXtd6LFkBxbsV9gJiPWzl0ko5FpW1a/LSt3kXiU SE5n5tNx/dvmKwj1+GgIDSdTzeZOpenEzM8ZFePhzGjP10KAiDXrAWxJtTc9nXz6cnr5zu8F G9lM9Pnv0zPK9bhLHlX6mAdm2pVQNaWB/TCUaYkvhcJ651juy9HYsRMKlxNIuQowDSJ3psty RfMJy/2CX0GAmNKTHcs60hrCme+55PNdMvWSYS8cjTETn45f4yTxfn5CH173FcTVOeJTSs3L j8+vaMlgd6exc6owJU+K02S/GM4ciew00mMFqbTQAbTN30bchQo4+nBk/R6TJ2hckw0Jt2KT DqchPhZrzXrws4nY1r/+RlJfLEYYKtIQ7wBagVg7mVPYSmxCUusZsyUxD452aYz0oCgRcfBa 0HUbT1zi4Yc+8sypQKAr7BDi0E1zVVm1qMcKHoUpx/75lAKru6QHaF5ca8mkvFVRyJnXg+Ut +jkRnRNaEvPyYYCuSlCEiCB23QZnLIS/sd//tXs+lGGFV9dVmScJFRo0bln6qayWzXUEzzgU ofZjXfNxgTUJxkU8SJ96pWtuGB0G8uPPd+XE0Y1L42uIsfSNqwM/rTd5JtDLYNyguhmODjW+ vc9AVKvysrQcplm6AL/+KyIZgxjGhzYlZCLZ8c7PSIXrK0738/S2/xzRIEvjPQylzonwWduK vajH8yytI8kuFUKDo9UbKVjHxedNEUUR5VlYp0E6mzmyjdPZMyrAAATwBYdExnGfUpANC02b 9BaLeHl8O58eDdEoC8rcjFzYAOplnAWYl6sgUgTFrrh9YVXQ+p3/488TuvD/x49/Nf/898uj /u8f7k+bmSmMqzzdB0MoE5zrYbYjGSTUzz5fa8B4vyoDwb8saYLh1CF6Bqa9QY3uBpe3+wcl p/RDQcmKr1Rv+ipilwVTpWF7LNZspD1pvLCHH+p5IebUyPKAhgwDnH7E7nppZlBYr8MNjFCh AnjrKFABs2ID7CFqGaJHkV1v7rNMG4M/FEm47xx7DM21730JWi7oPuubxdjwuUJgz6sKowWl 9nuLvnLMuenFrLOrTOJ0aQUoAJC+wverkvP6UUqqr4MYk/vcfJu5wgykuazYVlvHu76YOj2B BKP4CxUVBMrCIAeDaluIUrLqMeJyiWFyfeOA1rFZ6T5qYfUSPZTrvOB4A75MUB7MsRl2IoWN j44LBwd+hQ7hfnkorsaDDrGDQ46PXyivYVs7PtF/0HCdBYVRz8PIF4SzyO02r4wVpn6i87ty 2lWzin42hlRTArAhuxNlprvYuXkohPux+O0qreodbzfVONbzBGv1q4Tw8G2Vr+SkXvHO7hrt wq62GNaIx2FqHwzJTdF6zd0//CCRdkEi8iOLKymQetDp+HZDEcWyytel4NmLpmkfjfcK58sv sNNAA3RsoaalWrR6P348ngffYAd1G+g6nblfWyIygja2q4WJRBGuMiVdBBYYCzPNs5j47igU SLZJUIaGywMmczF9KtvzrFN0aJsUoNvDvEFa0ezF/1Z2NF2N48j7/Aoep933umcmIdBw4KDY SqKJYxvZJiQXvzS46byGwCNhZ3p//aoky9ZHKc2eIFVlqfRVKkn1UZaYCBDb4ySuI06tQG3q j5wn1iHf77GuHFYo1yTBsjjnGUxnHDzWdVlansgFj4MET0UhXTIMhsR8MIlzMUdMIz/1G7wN ExB6QiLra5p+/BRJss46NDaQmmpkFuIhZ9GxOi5Hww/UsS7KOFxJEOG2UbtYom0deWS4Qos1 7CNfWG3APsAb1fF8+tB8e9ocmlOPMC0yO2NNiwEXiWMc4YJDSO5lxuf4DE2dyQm/b4fOb+uS T0HcJWciRzI7nQWpcfHOIXJ4GhC6ijUp24J4kNnKl0psgdh800Q6VVTqtDVmBRmLrbmKcyyU jiDBXgCEiAZDU7FDZ8YBA7Z39yf0hlWha+lVVCnPI/d3PTVnvwAUVMLqOR9b5gotuW4GSwVh BUHb0wjizwS8vtqPApceEc1nzgbQgsKD0RLg8ljTMHOmwS+1JVonUAmGNHrLvjG+t5xNXuUQ 8jCM9zYAGx1WTRT6AzUc7RoggJmOdUkWE2v9kX7jMSChkSJ91egntei+kH3mVV6jp9zUfJMX P3p5td2/XF6eX30enBoLJFEZSORWPwpcw1tEXz5E9AV7w7ZILk1DKAdjzSgH94GCv4Q/D1h3 OUTYK79DMgwxf3EWxIyO8PXrZl1cBAu+ChZ8dYaZWtokwYG4Ogu18moUrvLyC34rDkSsyGAK 1tibnVXIYBjkSqAGNooUEWM2SFc0cNnUiIClvEGB+ViYeG80NQK3dzAp8Cx7JgXmI2birwLN PQvARwH4uduIecYua0zb7pCV+wmEGODZAk2XofERTUrTv7yHi/NoZce773A8I6WThcMnWnGW JOhNqSaZEpqwCKsBwjpiDtAazwTbJI19tllasTLYD3jmEE1SVnzO7GBZgKrKCbYq4sRM3pos /PNjlTJYG9jdQVYvrQcF68ZFmZM39+9v8ODmBWyY05W1j8HvmtObioIzvLtbakWW8kKcX8Wg Aj0X5yD7zAdRKqkM6otrNu1tCkLSc1HHM8gKooL1WnYtYrdk5QpiJBTydaLkzL660iTYDVmL MjfzGdyuyizFqeCokmEU8pXUbiLi+gO5ZFgdYGUSSQqIJO6m6kXREKJldn36x/7rdvfH+755 e355aD6r9LfdyUNHqum7wAwDkhSL61Mw2354+Xv36efmefPp6WXz8LrdfdpvvjWCwe3Dp+3u 0DzCTPj09fXbqZoc8+Zt1zzJ9DKNfOzuJ8lvfbC6k+1uC4ae2/86yWFZykpoVDSv08zODSFR 4GQLXWkE2gncRyviiVitQdouyTXKkkaHW9S5ULgLoj/Gi4mZ6Yve6O3n6+Hl5P7lrenTEfdN V8SieVOSGzuTBR76cEpiFOiTFvOI5TNz9jgI/5OZitDnA31Sbt9faBhKaJzhHcaDnMzzHAX6 RcCh2ycVIpZMkba3cP+D9vIUpe7OXk4yr5ZqOhkMLxdV4iHSKsGBfvXyDzKyVTmjdvybFoNG 1snfvz5t7z//aH6e3MvZ9whR/n+aN+d6VArsFaZFxv4koFGEwOIZwhmNeFzgL6a6sRW/pcPz 88GV1wLyfvgOtlH3m0PzcEJ3shlgPvb39vD9hOz3L/dbiYo3h423mKJo4Y8OAotmYnMiwz/z LFmBsS+yoqassFIR6bVDb9gt0hMzIkTQrV76Y+kBA2J47/M49nsyMrOyaVjpz8cImX3U9o1v oQnHH+RbdDbBHmFbZI6xeFcWSDVir13ywEOv7kqIhlNW+DuibkNR2FF+1dPkZv891IlWECst qJzgW5pz0ZxwY2/VR9qkr9kf/Mp4dDbESpaIY+26uwPheYxinJA5HeLv8BYJpun0bJSDP2M2 8ec+KtCDs34RjxDYOdLyBRMzXtoqHOlavoixJQRg09G9Bw/PLzDw2dCnLmZkgAGxIgT43HZp 7xHYCU5jF2fYN6VQMcYZeqnWSuYpH1z5En6ZKyaUMN6+frcefju54y9wAatLRENIqzFDqHnk D+I4yZYThkwFjfDuLPXUIgsqjk4EQYCKH/qoKLFJA3DsqkHvOkjbJ/IvJnhmZE3w93s9UCQp CJq3ydkEsEHGg+t3WJ6rlGjuhPF7vqR+35XLDB2MFt53q5oqL8+vYH1q6c1dl8nHEkz+rzHT iBZ5OfKnZ7L2mZcPJh4UHkU0c3yze3h5Pknfn782b9rlU7uDuvO1YHWU8/TI0on5eKojsyGY gIBXuF8IWkkUoY+EBoVX718Mol9SsJPLVx4WlMYaU981AteoO6yhorv8djRHO6yjas8FvrQi aOZ6Q7UXZ6eJe2Z52n5924gz0tvL+2G7Q/ZfSE6LySoJVxLIm5EC9cutDIjUujTiDWIlKaJj Ay6pUEXTp8NED8D1TinUZbam14NjJMf51WS/5NjRTI/z3W14blEzXPsjxWoBiQ1ZJG9J4PnI t3YAn8xvUgHfyyDI++3jTpkS339v7n+II7FlISafG2FkIfpu0V3q4PYJHyi7tawPTUBIcEx4 LV/d7cdpIi1vkA4bM7FnQ1RJ40VdW5iK7TyN8lU94dnCOQOaJAlNA9iUlnVVssTWjjMeo5oR JLqh4gi4GFvp4dRFlZlErLOAjRgEAiTGwVdm5YAHz2iR30Uz9QrJqaX9ReIoJCSXBRpc2BS+ zhjVrKxq+yvLARV+2maNNiZhER2vcKt/iwS//m9JCF8SNMOMwo+ZzeGFtXG5sifCrsnF2umU +p7SUFWV4m6WpFJxG81HijUNI/qyABpTH76GFSyEb2LZpqyVPHKgYNaBlYEbcngWHAY1yglu qiHBGP3dGsDu7/rOjLnRwqQpcO7TMmIOWwskfIHByplYLx6iyMVC8KDj6C9z1FpoYLz6ttXT NTOWmIEYC8QQxSRrK95yj7hbB+izANzoCWl7d0uSGo4ZxpoviixiQkrcUtEjnJhxCEgBEsK0 FlYgmYLekhwAt4JEp0LPrQsV5DqR2RodnIw1TfLayXQpRRDgSBzzuqwvRmP7rUPiwIw98Kpd TBN1sWv0yI0h/tIE3vON1Zms65LYQQD5DeyqmBXCImdWPnXxYxIbQiOT2d6mYrfiK6dRaVar eKfMMtaEd4J0iq59w+HL2bPsC3K9c0ro69t2d/ihXJiem/2j/7YiLS7nMoS+tcspMJgqoDav kbIsggR6idjzku7q9UuQ4qZitLwedZ0nzdOQEkY9F2Mw6mlZiWko0HW8SsmCHUsiZFHUAeND obOMM7Ft1JRzQW5Fxgr2Y3d02j41nw/b51bB2EvSewV/83tdMdJqxB4MUgRWEbUUbQOrV3TA rtygLPKE4YZnBlG8JHyCb5TTWOh+EWc5qtzTVF5WLyo4os+oGXJ5wkUHSgve68vB1dCe4LkQ M+BksMA9hkgsixU0ZvtnFPySCrDkKQm6GlWTChqBjgOWlAtSmskQXYxkr87SZOWOwSTjkeCe krmMtakSOvTK5UdH+zczYHO7PuPm6/vjIzz3sN3+8Pb+bIe4l7kmQdeV3lc+sHtzUn1//ec/ A4wKEg6aWp6PgwvmCjyKrk9PncbbDjLjwn31dsJLH22YXbSynHN7G2xer63MVX1hhpwCWUHv Sgi3Zhu4q1IALyU9btUIX+cZg7SrAfdUVYyyfA5E6lcTLCH4NWqLlo+MFYg2TMaIdRK3NDSN 3WWjirhd+BB5f9waZ7koPkaA+VSodtPC62wZJVe+Y/aoORGDrLgSZ0/3AbMfDK+tMyf2v7rd BvqT7OV1/+kEAmi9v6r1MdvsHi3nihyShcBraoY7Qlh4cMWoxIS3kbBtZVXZg+GMUuVmmEzd 89mk9JHWTgPRPhcmoawDO+gFiTsujZ6CyupZlUKiwAIz8VjeCFEkBFKcWcYUoAC07UEX4PF+ ViYVQjw9vMuEbf6KUnPRs+GQYMS/QD9KI0W68wJGZU6p6wmuTtzwYtULi3/tX7c7eMUSjXh+ PzT/NOKf5nD/+++//9vdLkHNrEp6R71ZbeQIcFhpPziyYPmyoItjBK2rjbpIO5rKQzr1iIlV gqWpr7/p4V4qrn6h5f0f/WSUDVuaEIOQ2k/o1WJ81XnySPPmSuQFlvEPJd0fNofNCYj1e7hE 8RQZuJBBRLLrP2KP2dT/QvoRMScvR79GQT6ndUxKAjocBC3xcmRbayPAvM1HJJQtmpZMBZBS t81RhS0Yc2StI3tUgZ4wCR3/AO98a2K45QEFIHpTGOtShxCwmHJ7TsgQpbVwqa8gXMh6xAHH So0hTxtuYHID2JpPF0tiOY8XBLKD+h5Mm6fX7xus6yjhyarV5I2TUJLPiDa6FyJHLHA46Fl3 AEJVm9GFpYC5tZjnn7LZH2C9gCCMXv7TvG0eG3PPmVdpQCPWcw/Ufxm75y+lLyJdqVSwjsLs mQlhiashGCiliOgTqfVVPQGhgLLm1Ncpati5LJKnb7GfR9ltO+a2dzKvUpDPcibCQAfT2ghV ISidjva2Z+GkjqT/A76SYzM5sgEA --k+w/mQv8wyuph6w0-- From mboxrd@z Thu Jan 1 00:00:00 1970 Content-Type: multipart/mixed; boundary="===============1125898102267184515==" MIME-Version: 1.0 From: kernel test robot To: kbuild-all@lists.01.org Subject: [gpio:ib-for-each-clump 4/4] include/linux/bitmap.h:639:45: sparse: sparse: shift too big (64) for type unsigned long Date: Fri, 17 Jul 2020 03:48:44 +0800 Message-ID: <202007170339.nHjeGJBw%lkp@intel.com> List-Id: --===============1125898102267184515== Content-Type: text/plain; charset="utf-8" MIME-Version: 1.0 Content-Transfer-Encoding: quoted-printable tree: https://git.kernel.org/pub/scm/linux/kernel/git/linusw/linux-gpio.g= it ib-for-each-clump head: 3358c938236d6a1be51124fbbb2698e50689d382 commit: 3358c938236d6a1be51124fbbb2698e50689d382 [4/4] gpio: xilinx: Utiliz= e generic bitmap_get_value and _set_value. config: alpha-randconfig-s031-20200716 (attached as .config) compiler: alpha-linux-gcc (GCC) 9.3.0 reproduce: wget https://raw.githubusercontent.com/intel/lkp-tests/master/sbin/= make.cross -O ~/bin/make.cross chmod +x ~/bin/make.cross # apt-get install sparse # sparse version: v0.6.2-49-g707c5017-dirty git checkout 3358c938236d6a1be51124fbbb2698e50689d382 # save the attached .config to linux build tree COMPILER_INSTALL_PATH=3D$HOME/0day COMPILER=3Dgcc-9.3.0 make.cross = C=3D1 CF=3D'-fdiagnostic-prefix -D__CHECK_ENDIAN__' ARCH=3Dalpha = If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot sparse warnings: (new ones prefixed by >>) >> include/linux/bitmap.h:639:45: sparse: sparse: shift too big (64) for ty= pe unsigned long >> include/linux/bitmap.h:639:45: sparse: sparse: shift too big (64) for ty= pe unsigned long include/linux/bitmap.h:594:63: sparse: sparse: shift too big (64) for ty= pe unsigned long >> include/linux/bitmap.h:639:45: sparse: sparse: shift too big (64) for ty= pe unsigned long >> include/linux/bitmap.h:638:17: sparse: sparse: invalid access past the e= nd of 'old' (8 8) vim +639 include/linux/bitmap.h 169c474fb22d8a5 William Breathitt Gray 2019-12-04 613 = e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 614 /** e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 615 * bitmap_set_value= - set n-bit value within a memory region e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 616 * @map: address to= the bitmap memory region e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 617 * @value: value of= nbits e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 618 * @start: bit offs= et of the n-bit value e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 619 * @nbits: size of = value in bits e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 620 */ e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 621 static inline void = bitmap_set_value(unsigned long *map, e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 622 unsigned lo= ng value, e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 623 unsigned lo= ng start, unsigned long nbits) e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 624 { e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 625 const size_t index= =3D BIT_WORD(start); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 626 const unsigned lon= g offset =3D start % BITS_PER_LONG; e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 627 const unsigned lon= g ceiling =3D roundup(start + 1, BITS_PER_LONG); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 628 const unsigned lon= g space =3D ceiling - start; e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 629 = e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 630 value &=3D GENMASK= (nbits - 1, 0); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 631 = e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 632 if (space >=3D nbi= ts) { e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 633 map[index] &=3D ~= (GENMASK(nbits + offset - 1, offset)); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 634 map[index] |=3D v= alue << offset; e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 635 } else { e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 636 map[index] &=3D ~= BITMAP_FIRST_WORD_MASK(start); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 637 map[index] |=3D v= alue << offset; e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 @638 map[index + 1] &= =3D ~BITMAP_LAST_WORD_MASK(start + nbits); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 @639 map[index + 1] |= =3D (value >> space); e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 640 } e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 641 } e77c9b6f35c4bdf Syed Nayyar Waris 2020-06-27 642 = :::::: The code at line 639 was first introduced by commit :::::: e77c9b6f35c4bdfa60c52f137a4b48c04ab87627 bitops: Introduce the for_e= ach_set_clump macro :::::: TO: Syed Nayyar Waris :::::: CC: Linus Walleij --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all(a)lists.01.org --===============1125898102267184515== Content-Type: application/gzip MIME-Version: 1.0 Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="config.gz" H4sICFOiEF8AAy5jb25maWcAjDxNd9u2svv+Cp100y6Sa8uJm7x3vIBAUEJFEgwASnI2PIqsJDp1 pBxZbm///Z0BvwAQpNNFas4MBsBgMF8A9Osvv07I8+X0fXs57LaPj/9Ovu6P+/P2sn+YfDk87v9/ EolJJvSERVy/AeLkcHz+73+2jz++bSfv3rx/c/X6vLueLPfn4/5xQk/HL4evz9D8cDr+8usvVGQx n5eUlismFRdZqdlG370yzV8/IqvXX3e7yW9zSn+ffHhz8+bqldWIqxIQd/82oHnH6O7D1c3VVYNI ohY+vXl7Zf5r+SQkm7foK4v9gqiSqLScCy26TiwEzxKesQ7F5cdyLeQSIDC5XydzI6rHydP+8vyj m+5MiiXLSpitSnOrdcZ1ybJVSSSMmKdc391MgUvTr0hznjCQkNKTw9PkeLog43aKgpKkmcWrVyFw SQp7IrOCg1wUSbRFH7GYFIk2gwmAF0LpjKTs7tVvx9Nx//urbnzqXq14TgNDy4XimzL9WLDCEpYN xcZUJ4Bs2a2JpovSYAMsqRRKlSlLhbwvidaELjrOhWIJn9nMSAHaGWCzICsG4oaODAWOgiRJs3yw nJOn589P/z5d9t+75ZuzjElOzWrnUsysOdkotRDrMIYueO4qTSRSwjMXpnhqT8FmELFZMY+VPaFf J/vjw+T0xRu03z0FfViyFcu0amapD9/356fQRDWnS9BSBjPR3dgWn8oceImIU3t8mUAMjxLmDstG h1aAzxelZAo6S0FLDcd6Jr2BtZojGUtzDTzN5jOzoHnxH719+mtygVaTLXB4umwvT5Ptbnd6Pl4O x6/evKBBSSgVRaZ5Nrd2hYpwVSkD/QK8tufo48rVTWBKmqil0kQruykCYd0Scm9aBmVkaDaD6Fzx 4Ir/xNSNiCQtJiq0ytl9CbhOBPBRsg0ssrXqyqEwbTwQzto0rXUtgOqBioiF4FoSOo4AlSFRmc5s fXHn126lZfWHtbmWrR4JaoMXwLPSwdZ4opWMYSvzWN9NrzoF5JlegumMmUdzfVPJWu2+7R+eH/fn yZf99vJ83j8ZcD3SANbzLsD/evrecjpzKYrc0SgwfnQeMo2GtFR0waKOQUy4LIMYGqtyRrJozSO9 sDuQ2m4w3FPOI+WPtJRRSmxmNTiGrfuJyWFmEVtxynrsQMfrzeiTgyW0tFTgzq5RRDsjQLelctAf Fep9wegyFyB2NEZaSGsIZvrGdxrGNk9wGCC9iIFFokS7QurkiLs+0OcsQYuwMq5WWgtivkkKjJUo JAijc8MyKuefbOcBgBkApg4k+WRk3wE2nzy88L7fOlZOCF1Wf4ckRUuRg7Hmn1gZC4m+AP6Xksys WrfeHpmCPwLcWr9vO+ScqnwJnBOikbVlm/O4+/AtVArxCQfXL62VmzOdolHtHLu3dDUiMLJ4AXsi ceZURSyVowqFOcYq2PGVpZn9OXXyJgpkVIRHUUBAbO1i/IQNZ0khF4klP8XnGUliS5vMcG2A8f42 QC3AlHSfhFvawUVZyMo/dsFUtOKKNaILSQL4zYiU3F6LJdLep44Ja2BleAlatJEQbiPNV86KgEKM LCEqgwlbnemnMxZFtgGsdA5IyzYwahft+uptE2HUKUy+P385nb9vj7v9hP29P4KjJWDVKbpaCFeq YKRu3vEMOu6f5NiMZpVWzEoTtDTBkpUdEA2pxTK0yxLihMMqKWZBU6USMRtoD4sq56xJBFxugEXD nnAF5hO2jUjD3BdFHEMGkxNgBEsGqQlY2uBOEjFPGrWrpeUmU622JvnCMna3b2fctgmpFUK0MTCB 7ECCua7isY7gE8STZWTbzjboVsRF5HNNZjCVBFYkUXc37XAwjTAZRaM2yoQjbQrY7SIceNNBUFwV BUmoKyMPv0lGkGDKl9djzFcEwl/wfiM0lMwg2k9YOCitaKJ8evt2BM9m1y/gb9/m48MAktsX0PkY ns/ZmBiTzfgIk/tsM4JOiQRFGCPgEI6M4pdEjRFkEIDwpAiZ25pAYIRTUieGa1CSa7IMZ2YVCZi6 0fnn0+UIVpL1gkdj/CVsfU6yMYoXVkC9hMcNOYZfEDk2BxAQkWMroEGGYxNY8ySKuQyFOWA/LJ9a GZOS2H7cXkMfylZvfVBCA1ZqsQYtX2if9iOzrWAtDDusMgWQFDLTOvoq48hJ7Q0+4go+NZ+Dcy9Z 9oKw15Ahhg3GismZAHeempA7SLL4VN5MhzADOgAYSJiGUNN3YduBra6mbwMrZvhdXdlljzsEWN5M ohxWQc/uGH2nFLg9774dLvsdZn2vH/Y/oAF4/MnpB1ZEn7qsXFQ+kHlhSh/cLL5Kc1N9KfUCc2Ov HVYrUxHVhUDleMhyTvSCSSzRgPOeM08xTPss5VW6S9N8Qxdzj2YNbqTkoDk5kbC2TRnSr5kqTSDL kkIzCo6/qd/Y41xxyDrd0gzO0KOCmVT9qpxRHtu1BkAVCVMY+5UsiU3U6G69WaHcrSeiCHNdCJ0J 1c6wBdZH+VwV0E9mp8xVsHUzhWDDBNieOECSdY3KagOTAjgDM0g5RnFx7ARwWJiz4zvH0FcqRMXq 9eft0/5h8lcVOf44n74cHqvaVlcoBLJyyWTm+6Mmjhpj4wdbL6hrm0RqSL8gNWGWZpmgXaWYdl17 q+OUMQwIc0SKxRQSzqFrqiIbo2i0e4yDkrSthidhh91Quumvj0YdkEyNdoYx7hpcu1Kox20BouRp LqSfFDRJSwaqC2p3n85EEibRkqcN3RITpCDVDDUqlBVl1bEFbB6eGYnS9sCC/Xe/e75sPz/uzeHO xOQlF8sszXgWpxp3lpVRJTF1CiY1kaKS2zugMkSicEuqFS2Cw7OoO0zf3wbmUmNBwo7DwuFERZoH 9X9ojkYA6f776fzvJN0et1/334OWOYY01EmYEQBbO2KY94IftcozKk/AQuTabG6wAOrurZeyGYsT LvdiliQZagpoTyhLWtyDJYsiWWo/7zFmVAu0da6pz4QGe+nk5cqaSnPMk8IsQKqZYX/39urDbUOR MVA6SGyNPVtaTWnCSEYJeHVnJdJwRPUpFyKUsn+aFZHd/pMxICKcIBl3Z8SEdeFlWEqLFNaESyms OccSI+WV8UJWTsckTqpXup8XeTljGV2kvQCyVqlhrenEZtfSl7OSbTTLGl9sVC/bX/45nf8CM2zp nKUNdMlCR1iwna0CEX7BxnPqSwYWcRKSjk7cU4pE1RXYsOEBtBahAHcT2wElfpUCcn1hByIGSpK5 sHs0QCzUBDs0WFXMylwknIaKqIYi5XPM53t8cSm50pyGsiZYEnCT906JuAI1/EKBvLOQPK+qjpQo x6gBnEQrLIlCZAGWLVjwBqI8yx1m8F1GC5p7vBCMRdlwflsTSCLzgVny3C4ZV5C5xPJHWmx8RKmL DEKHAH2IxUzCEtfTt4RiJo0GLrXDqRbjTpqnEJyurv1JV+BwHqDuM+AuljxYzK+Gt9LcX9tYFOHD yQrXzT7EFZe+JNYxswGAR+9DLN3vplTjIC+iAwtZjRvdwlD3/toYIG5tDwRdhMBF1ILdXiF/71kI lwKxoDBKS3Eftg3QJfw5bzU/ZG0aGlrM7KC9cTsN/u7V7vnzYffK5Z5G74ZiMljtcIIHITgd2BZ4 UaNUjKJV9xTFoMC9mtgejEiah30LkEIypo07tdtXwKAkKpt+Ou/R3kP8cdmfe7diAqygfz/Y7NHA XxDXLZ1tWqNikvLkHnYrj+YsRFC3xdNMCx3jamTGuTpQPPP0N3cNBkbgQBx5WFwaeYfmYZPhyayb HjnohMzCe9ShinUenkvJJR3kDROYcaHK7EX+inv89dgSNBKeJwVYRu20zEjvuzd6hFXjdmH+KBAG 0S+XrN8JBKfqY8EkiZg3f1PNHlevTUXThCsbE0I/TXan758PR0gmv5/wSNsKlO2mZb3LnKaX7fnr /vIU1nhoo4mcg+kBtXphYJ4AAzwyPAjMw9vUoop/oq+aNiDjAJUj8BG6sB3qkYExS1W/MtAIFPKY 3bf9sEBTc6cKY3p9n4fCmwB1yAL0qar4bJQEgzFmH+iMWkErQFBeyKWMXDd303e3HhRyIExceN6j bzEpoUNIzLR6uAVRixDDGl4vWhA3xs9kdYNcEesHmk6n/TkYVIWwo6gWBexqruFQ1CYMMwdEhRvj /zJzHhPKej2Yo0N/oVfK622lqgsf4V4ACyYKV1PdXU/rK3z5Sk0u5+3x6cfpfMFK1+W0Oz1OHk/b h8nn7eP2uMOE6+n5B+LtjVMxxGKlKMMxhE0BkVV/rBUKYr6huL2lIeGTL5tEUTf+76b31Nwm6kxv 1VDK/pjWMpxpVdhkINGumiahy50VLhbeypViFfd7T2YjPBApfTbRos9FjUkrXQx2oOxT/wqUfWyc khElcB6UJqhvq17vrTbpSJu0asOziG1cndz++PF42BlbN/m2f/xh2npTyWI6sKFQK1jt+mue/zcS UHZ+HiJtSUy8bB0pARwvTlVZkwvXoHyb+wZuRwxRkRtwOKGqgsGBlLRC9vqS7E/wpx4cJgsonrfB hwNvo28H2nroPx3/XCGdUMGhD/nqiiAl2TzpQSFpst3Z2BIMxJpVPB6qaxoEErNZO/OuJlphAYX5 d6HDxRqLSteCGu6poqpkE+Lw/mpa3rzUDYGEIGSbbRJpOT0LzvOBjs09+Jc6HkgpLIp8qTHkGehE DZRWLJJV4p79BqcmWZ7cD/QRgXDHGeAsyqEFaMLNcRZqeAXDka1FYIJfa3HyfmoLeh/RIV+IDsom xu8yms1LMfuTDhwGVzR19l8VdMoFRDGY64fuIQ2RqwW57vcdIMQjxyHGXv9WvdbH1t01c8f6SNWj V1uR0cABTvidBNFO3RY+S5rwgVstgASVHDiDB+RMTm/fh61zMtWhNVS6tzcDusTnKax1JoRfE/EJ 06Dxr06TsaCk3Nu5FSh8ZQAmihbo+mOAYcSoF5ZWkOHCa5JY4TN8WJdniSaJFc/j7VyS5wlzwYnO veOmPFgwzCM/KgRAyTJKQpLZTC2VS0ju3NjLF2IgdGeMoWje2T6zhZVZUv9hbsvylGUwlSBlFQF0 KNDzlq+zSr3b4J3gaejyYJQpvFMt8BWSo0+gpQRPmFaBRiJn2UqtuXavM1ngch68abOq5mFFCg3E K4i24ARUeebkt3h6xkWIlYvoamC2gEyVZ+C4Jc0Tix1KEyHlXFnhs4Gg8nrXbg0cAiFTAh6oemfK EddChfTfLKKRYVWps8DJDUZBmLZ7RbyPUg+xyqhyC+3wXQoGtiuNyiquCmcV9T195JFLLgLsLQqa EKV45A5XbvCE875070DPPrYvuOoztcll/3TxrkmYbpd6zrzT1zqa67X0EPYxXWfbUogezfVp01O+ 3f21v0zk9uFwalNPq0BGqi3fmW34LiOSErxSuxqoz0hhHbRJodoXUGTzZvpucqzH/bD/+7DbTx7O h7+9W8npkg/cWrjFQ8awSc8/MrwjFN72oDI05M+U/TYTPtr7tpafpqWWG0YXoeWfkXvYYZC2yTKO rIMqC74wcMumGExOQsp6T1I7Xh+VV6uBxL7FBOaqCvotwIymLmC+dnwDQP68/nDzoX8IAAFlVPUa tatktVpVfTucVhs6cAURsSqhwSAVcc5WRwAlCcVkFt9ouIYGsXHC/K7sKcrA2JYrgiuSU87isH8w 3ZZjM6D0jz+uBjrlMcf/x5HfcTrKMmdkGRiULbY/yfWVuernNGSpwnaDjCt8Snk4aDFSfH99e3U9 0G0nL3dhmgH742knEtpqFgGOyOOYbPrd1LOur6a6elSjmscqg/PTCv4N3y83fETsX11x8KaWV983 CL+QCOwRa7OH4iECeflGuvFZA4NI3VQYEjFgAFvCoSqj3CzdU11osaRpyPZpyUha3Ye0ChRrSOIg m7ffy8VzjLOsfKKK2a7NQ+9UuEc1DTVKjSUCL+KsicxAysFXbQ01ZRLv/VCCt41KkRUqyFSyjwUM 0LwiwqsLbB6FIjqLHj5YkhQJAVPMnbczDhHewtzg9UcuB2ZTpWp5eF0sut7D595UZQT+s2iq730e a7YJKU4d71rr0EDM1VX75K1FSIqXpHCpkzC2vU/1M1R3r74fjk+X8/6x/Haxzr5b0pSpUHGzxScs cq9WNojge/EAd9XcpQofd7v8oEFWBLvLRHXDcLy/5iJ4b68FhpakATqfSmnSvgft81jon+lJ0NnL HfGZUiM95YFTij6VjpLh0wxnTvXRzsa8oex+oGLN8RDsX+ezXhnzKunufWu14iW3A+Tqu1EXF8iz vNA96Dy3HwVi6Pwh97/r7MhPFz/kg7OkhMeu7+HxKHHgdoEBFypopli+KKsfgvAgeDtb6/veErZ4 vD1u563BKrZ3hwD2MZ9zSK/DxJAXcb8BgMqCyHBtDAkWbvxR5zTb8yQ+7B/xieD378/H5hjhN2jx ex3I2sfwMT7ocC4JGEDJp9QF5tm7m5sAqKZ0RoaIaW/wFoHS9Yx7sH7H2SbvE9fAPrW6idcyexcE tkNts7WfElbDKVcE0mzm6zCPQ8lYsm6vY3WltRqG5dNQLQQk0NyRrUGQ4hof6tUFzEv2VDnqGROe iLA2QnamhUisCyhGV4byi/qhjyXx6v69A/I/6l8pUS4w8LQag1R0v7PgazXEEpWnDhsDCT0ubXG5 WDOpvLR4gAz9/08Rd2/XBwnLXIcDYJx86v4kh4XBQGqpvJkMGjfEQbyIN53rt1Xeb/UYSeti5kLw 9XMPSLS3QowSV9glFyuPkfSWOidVsaUrJQmdJ8Xcz4iqOgfAdqfj5Xx6xN+0ePC1DRnGGv69th9U IRR/Tqh3k6xF9H5IxKzHBl8GbzoNfzp8Pa63570ZhrlToqzT/NoOjJFVF/9Pn2HUh0dE7wfZjFBV Of32YY/PuA26E8lT6IKBmQwlEctw4+EbApx0OA16kW1DObAU7TKx48OP0+HoDwSULjK/fhHs3mnY snr653DZfXtx4dW6LjZq5ljmcRYdB0rs38bw09vq27wbKil3sxpo6Fmgeuyvd9vzw+Tz+fDw1XaU 91gc71ibz1JMbZ4VDHRShALxCuteO65hQi34LFwoyKPbP6Yfgij+fnr1YRroCRA3t5YH1NTdJkYo 3m9TVaLEEzBzLd7x6JLkPHJLsN2rxcOudiAT4b+FKaoHawuW5HaW64DBluiF81NiK53m7u3OBlam +PQtfFSoSRaRRAykFRDRmT5jLlPIiFn162a9CcWH8/d/0ArgBSD7vka8Nkpkz6IFmTcmEf7KT4eE JFKStjdrel2rwhQoG9F0XjxEAL49SWZD5deuSfjVWb2l/Mm1qQG+zsSzrOZdlFPBMG/UbGy4yFvV aiQPxx9tKUcyb2ERjpWMui24uVQM+GVDRtR9Rhtio8KB7tqfcsiLclUk8EFm4BY0t6+ISDZ3HmNV 3248WcMgGOA94Pq6B0pTOw9qGMqPHQwfduNL80pfYlufEBUba29+xso2hgP7zKjs7PnJCuq7RHLB S8+8tezsJm3uIyAu9R48SQw3vN88mWfK+8JCOydOhGfAKf4ElkEFV7Nq+j/KnmTLcRzHX4nTvO5D TWmxtkMdZEm2laEtRNlW5EUvqjJmKt7k9jKzZrL+fgCSkkkKtLoPuRgAF3EBARAAy/5AEKkk5/1I tFAPlLk2H5S5azXlsT1goNNgyY4IWAzTG/qiUCuYHtv9Ow2QPzdpXWqtcIdZzWYHMG3S24PuNtke Zs1Rg6HsriUcEYH3GLO/hN53aa/7jdoAU5dRMGBJB00HV1BcKta5PEW2NmobNOkYx1ESUq24XkxF 08/oppX9vhVs1l6NzaUuKOlLgwup7e37H2uNN80DLxgnkGg0VUIBIxOg2dy5rp9xculBOgEnbSlz 71Ae6kmPguWgaBxVT5GMJb7Hdo4CA4ZQteyMVtei55bwG+4EzKXSZjPtcpbEjpdaQoNLVnmJ41Bp CQXKUyRwVjSs7dk0ACYICMT+5EYRAee9SBzF+nSqs9APFE+KnLlhrMlOrE/titQsf66ymy5UQuyf WH4o6KnrLl3alOTliCd3kIhxLoDv1YpEPk8Eh4P65CmuFBJYFcdUdW+X4DodwzgKVvDEz0Zte0h4 mQ9TnJy6gtG5ZCRZUYCitCM5u9F5RdrdR67DV+BqOw2vP1++P5RoWv7rE08v9f1PkBI+KH7RH98+ vz58gM309hX/qyaHnGRo45yU89+vTFkCcv1UJfOtWzBFr7MU5b2uWn1L+fnH68cHYNAP//Hw7fUj T0NM6FaXtrMejveqUOSL65OeZAN+LxdiU4HxxMDjM2Tpz78pWUHMq+zbgVayTCRzst4qcpJ+YKOV 4pTu0yadUjoRqMYNNVNPmS9uAixj5XzbvdoDiMTkBeqMUwUWYfes5/kQv4Wx+lj8BqeBIsQKXNUe j8b1gpjZoigeXD/ZPfwD5NjXK/z557qDmF8H79CUJiVkak+aPWsGawfzDdqyZ/Uj77au2OXkZaVu q5N8/3Yx2Ta57d6THzAkBvt1PIOKRrOGp3Nale8tLhg85rOw8Nc6zUzv1dt50VlRl9GGQenbIsLv QfI957QKcbR42UL/mIWnw3fB/0CSsigMZ7qDAJ8ufGZ4mmhL6Usx0IEE0s2rsaQ8a6rakrIB5Dna Sw8dMoVKo2lHHGxdEIi1xQpL90+TESjYorHjcBuIC2oryfvUYvZEJByzwJ4t6dQGfs5FkRfQsdtI kNb7lLE0t2W2A5JT25fvbeOMbVhSdeHnwX70HMfuG3uyo2CttZZLaH47JSZxxb3yNzgQ337/Cw8T JqxaqZI6R/PDmk2S/2IRxcSPSX30gENYxA2M4uRnreY7XFS0t76fBW5AYqTRCAgi2mv4RhDT1qoL CFkFLdgMz92pbSl3IuUb0jztZiPhIrJzEAoDvSW1mlrBsdAZcTG4vjtuFKrSrC+hEc1zklVl1tri rW9Fh0J3/wS13hBBTbFmYFsfUafvtbhqFaX7ntR57LruZGNj1Z17DajVkmJNTnNTZzb235Qh5Zyv dhQOq2ZQ7bQqUgtiVuC4vluDP1Y2HlJZ0loCwra5K9c2M1tL5AzSnuYlJSBTs49jh/JXUwqLDBn6 7tzv6C22z2o8Wy3xLs1ID0ZmW3JDeWwbS9QOVEZvVfbMhqI2YznVguSNr/bBmRFgvm8oc4JSRl6D kOsiSy/lWRu+4XRu0BgK3z3p16wkyWWbZH+08C2FprfQVOXT2TSeE19xKiqme0dI0DRYPOhmND2D C5peSjf0hbqIVntW9r3hD8bi5OfGss4wHaTGa2ndWy3CM1lp++hY1GVTLkcbLTHTIpVSca4fGiJR ihE4Q5SSF+W3hipLjlMGi8Dkpev6ivpcFbo3cuFt9r14L18DuQ0kh0xNxzDuEM40DNqYTLawrulw flcOTPPIkrz8UF/eufEGkzu2rRbjqKBO5/RalCSqjL1gHGlUM+i+EWjVIPpQmM63HEAz8fJI560G uGWXl6OtCCAsjeysrdN89l29sTREdmDdvn2pc4splj0e6fbZ4zN1Gag2BK2kTautwroad5MZ5XDD BSujkYpl17vow3WjP2XW64vgkcXxjj7HEBWgsx99n/DI3kPRlW2EbrQ1dxUMS7TzN/YAL8mKWrvB rTFIoc2Kqp3DZjYqee718vDbdSxTeijSqtnoVZMOZp8kiBbPWOzH3gb7hv/iVYAmvDLPsiAvIxmk rFfXt01b0/yj0fteTiOGB/47vC32E4dgbOlo1dFRAXRsqEergW2+Ojf1+IXgXA2WJNHXPHZ+UoZ3 dSQuICloJyD3u8oNEX5dsH3UxhDo243TViQMhLE9lo1+J3sCFQO2B/kRzwVeBx/KDVWtKxqGef7V amE1bUkAT1V71B0PnqrUH0dasHqqrJIt1DkWzWRDP5HZx9SOnNESW2tS5VOWRhj1YHXIfMLQosIW zdbXm6u419Nq96Gz29im6BM2FJqUErt+YjEKIWpo6T3cx26YbDUGCyVl5BbuMeJRc2MQkPs1srQG 2UnzYWR47JoqK1GyKJ7IjrC2SvsD/NEUDHagJ4WhqytO9cZ6ZmWlBzSxLPEcnwrd0Upp+wp+Jhae Ayg32ZhrVutJbFmdJW5y1xbDSbKEPk6LrsxcW3+grcR1LRogIndbJwhrM9jx+FojOU0DP0u17xlq jJ3fnvpzo3OrrnuuC4uTAS6vwhaghGmXLWdked7oxHPTdqAKa/rBNZvG6mgwgHXZoTiddScwAdko pZcop6wD4QuTEDLLwxIDnZJCqfOinzXwc+pPtsAMxGJMUVYOVKJVpdpr+d4IuReQ6RrYFtxC4G/Z Sxb3zqWsvPlNx9LOfSVNVcFYb07QWPaGQUbuJ0R4lhikQ55b7uTKrrPc54GEfy+dLkxuVdLaSWfL +9B1NJwZBbil+fTl+49fvr99eH3ACAl5ncWpXl8/4AOuX75xzBzsnH54+YrJa1bXbleDPc5hbCD0 UDZSJL9ZdWvjBANI7LkUb9XK6Y/Rwc87UTWIxTgz6b0jPOsQwIPSbEUCy3MgiLFKiIBNrOXCR3qr Xssq9Fx6a0Ax16FrvGaNH46UeqCPVK3rWBywUYg2S1qMhTtfOEDQ2D6rmW1fIvJAb0i1NytrUlr2 tByDiInM56zWt7I9lN3Vs/EmxHk23LXaJSF9YwI4P9lZcdfyQLF8s5s9yB7aedei5wPNaYq+NgNl Z7YQ7KQfPY3uS1YHlGeW2h3CTAH8qeiHlG50Rk4DbDN0haW5IA6E5V6ovlYxlblJ61UBKpPBQuoh Cn9arDQc59lxjm/HuYEVlxg4oqd9apoU+8EbyQNPK7YW8vuhit2YKggY7tnOVuSJZzlmJJbdxVoe b0Js5PnpXazFjiY+Ii7utnsHC4eEtd1rHG+Nqp6VBH5OCXkXqBbS07hnV9fbnD1dbrtWrhfQ9nxE WTRdQMVWlGl/I/rw/jlX9TYVxW/iikY3uz8NDTJlHoJyT7/o0+fMwm8EAXDAwKE/9xZ4e2UlzRn4 KxUmm+SCy/WtTscH9ML5+Pr9+8P+25eXD7/jy8Y3X0/hy/eZv+OhSjc/vkA1r7IGRBBX75vVK+NP ythK3iTCrUPBHtLHorIYoG9Ud4aoRhMXfSwLdyRbSZR3qYDBW/ssb1YDX37++tcPq3uYERzMfxph xAJ2OOBbKDLRwa1FjsNkPdBvalQ5nvGcCY+a677A1OnQl6PE8O6ev79++4gT94ZPZf7Xi+YGLAu1 +E6Omv1Eh2PMp/oKgoFlWV8UzTT+hu+E3ad5/i0KY53kXftsxCsLeHExRmCFNyRdZXJsMZ2i5GPx vG9FyNRS5wwDyZuW0hSCLgg8WhTSiWL6rTWDiLI43UiGxz3dz6fBdYKNXiBNtEnjueEGTS7zdfVh TItyC2X1CP29T4Jx8tsUfAtYcqgthEOWhjuXftVAJYp37sZUiG2z8W117Hs0m9Fo/A0a4KuRH9D+ QTciy6FyI+h616OPlYWmKa6DRdpdaDBdHB6fG82xob2m15RWb25U52Zz/lvgTbTFTpkyH/bFxnQM tTcN7Tk7AWSDEhQUx99Y4+Ow2fMs7VyXVDUVZnfjkvwnsE6PAOETkMYTbzNm/0wZ5m94vB+Af7uO Ls5Ave/M53zu0U2spoPQb7TZc6cH99xQPEkvD0ugsEWFkpXuNrbGrntA9bdAfbWktGSlN3w9lGRf Dm2GOkR2MpFEYBWHi6yWWOOdru2zOkgiSmsU+Ow57dJ13fjppne/RgArykjOIzs1lJbXjAUeV8fe omSKochc1+lS+xq7sHEcU6LPVsYth3FZULaoBZPOSElinO8gF+CzVLTVR5DwtM/0RZQkwNkToscd KowpoNTIutwZ8UocpAdHIgTWrwE5OP4awldaa8C9XIZ8mPRqmiUJ8UyIr934ShjNXAUyuIvUDndh HX359oGHy5a/tg8o6CrClPE1RKCeQcF/TmXs7DwTCH/rEXwCDGKukH90aFZqXFVAq3JPQLVchAIk vUwJYgDVIreGXqDPKOq0oxoUwgvTwrrOzIwplIhjWhfmPp9hU8NAOrxTaKp2ZLmiPruO5UnzhehQ x6ZSKhU/aspvcUGE6iOCiv58+fbyBxrGV6GGw6Dls7zYXuhL4qkb9OskYVLlYKJQlfN4ofPQyofE RPDO67e3l4/rRAuCzU9F2lfPmeo9LBGxp4f3LcApL+D4y9KhQGlp0N8GVuncMAicdLqkANLihVWi Axo0H2lcJuI4tBtBtR+WhyJVGtrzR2vE0rGm59f6+Pwmge3xoeG6WEjIxvmDjTnpWKB9x1XLOKWj aHg/eHE8EgPTHsgUjCJG9svnX7A0QPiS4LaPdTyXqAg/rCoHavBn1Dw/9s9bKJfBdA0K/TxRgMrk 68h3rCb6xMpDaYkvmimyrBktF2EzhRuWLCIlWkkieeW7IcWwq2HVOQN/ZwVbKEHc7VIyiEAvd691 Xh9oVfzB4NXyVYn26Tnnr2C6boAPldsp7R8ir1E7ZveCmevrLR4XAt13lKeiRB5YNVWd/Gqz5A1J LUmSumwwXe1WjzP0VuCZMMpjmQFb7ckjwmCxRtfrbOiXdHhmCyK1SpMbMXySqJmO6lO7Tfu+NZz6 znh9TV6+84QRMqP9rQoBZdqDc6fLnDxjtaLQVLXXPb0VDP8wfCSDfsUJMHiL1AxKWzeYzDi4vMfF oWoXqm7NA7pOM8vJqDticZZdXYLc1eQV6XB0uuK79bl+l7kA+RuOIKHUFjeRG6HowAZRBuNEJsfM B/WJANSvSnG9KpMO8ZwKf9glCUx7wk1R2SqLEabJ39ncGW8EpDMZKAjebtRHc769J9e/tafLhxYX 8fz1UiNAHo3hvWF00XfI4E9nm6mOniJeqLQ8pSFwqLis771JKryqbArSI0wla86XdtAdZBFtu1tH 3GXAnHL4YJJZCitlg++/77ydRTUG1ls9a+91z5A50cmcDMw6M/Mw9mc28AeDl4xGwnwM7a5N+qrC h9/NzUEwRq0O5o+V66+/IfQExLQtH7DidWGRqOOvjz/evn58/Qndxn5kf759JTsDB8te6BlQd1UV jf4IiazWrq/fCOBve7+mash2vhNSdXdZmgQ7yj9Fp/ipjxBHlA3yUarWvrA8Xetl4iHmufCddutq zLpKi86/O7BqeZlnSk8riAhuoNJB+Ei39p78DOyyAwVM1SW26FiYheg2xZINPkBzAP/zy/cfd1PH icpLN/ADs0UAhj4BHH1z3NM6j4LQMqAyfFKvCBR4E8JUqxpCurIcdzqo4W7cntm+cPeGtUh5G/Kx L0EPTowvBGDoOytYEo5m/RdLELTEdf06oxtnAn9///H66eF3zBIlxv3hH59gQj7+/fD66ffXD+ga 9quk+gX0jD9gTf1Tn5oM+ZIpBomljMnDeQa2u+njTVpStUMiPfXwDJlEXm2R0F21LyHBY1GLXaLA Wn4PYExkli6dNIe7NiKRESqk49WQFj+BGX8GmRFofhXL+0U60pHLepXRCYFD2rIJTtZ5J7U//hQ7 WtaoTJZeG5zkj6sRwC8zEvsj+MDoxCHWbasXx1yj1slcPVliTDXmgbOGEt1IkKFskFgTuyjnm1LO tygqHWlM0BLBnZj+QzschQ2Rqfk2F78EDv74hvlxlKS7UAEemKoErGeIvZs5vBk6pFgtP4TJttYn KlYJYiVG2TxyQVhrfEZxY5PZE4mTq5UYK4VIbtKlP/+N+exefnz5tj4Bhg56++WP/zER0pVD+sTi nX5je4hdunjADoGN9uENc+XB7uO1fv9P1c9j3djS9+WgloA5o6BETPzlITWRbtnUqpuAQo8n8+EM xXTrGdYE/6ObEAhFgsaFbRcA5l6lY+c5iTZTEpOniRNaIvolSZ11ns8cyuw6k4AuqQWBLvDRDZyR apcN9YGSs2Z8/xg7AVVQRNTdKVmj7Jqu+5KxXVSpUoGGiG2IRDlRcblqZjoJgFOFDZiuVDw7+Vvg ejNFezBOorlI2T+ZsYZiNk0RVSmHQfYHptelZDsWEvPrpy/f/n749PL1KxzHvDLiMSdeMtqNI09N aWtOGH80gzqXsEXUva1UfjUeoRMH74D/OC6lbKrfoZ6seg3H3iq9c/ypulL2E46r93HIotEYunXM gPjsOp8O5g3nLDfbh3eRkzj09edXYEbasSsqF14wRk8kVE8PKTFNtx6KKwwTfTMvPhfdKUgXxBva W3+4hJt5DFUSrsL45kBKKNF9kPzjYDXwQ1dmXuw6qkZCjJxY0If8XxhRz1lPI08ERGWQ4Oh9ngSR W18vRt+QIwbeqjYOpvKXcOwiOuqFqs5PdlRsp8TGoGYERvsL/9KrIvw/9BFlYeDE4WqgAey55nLj 4MR1aPD64wlvEQONMYlGbdc69t1RUzrXU7mkBb87xfshHtdrrpwwf8bkmh/NM6RzlJqSkaP6PPM9 vVNE4+ZCOh5BC0+HlrIiijlrs8ez4neopgC+umibnNmz+8v/vUlhuX4BRUlny0Ar31FE56vW4tq7 EOXM28X04a0SuVdal7rRWBnrjYQdaR2A+CD1Q9nHl/99Nb+Ry/wTJu+gjH8LARP2QhOMX+0ENkSs Ll4DhS7zuTVbtkbsUrtWry60dMHzaYQh0GhlLJ5YOo3FP1yj2ey2bx0gkNQ2CkexQ39aFLuWby6c nQ3jRuo21NfLIorxZznSi6bv8IDqrKPdk0UJ0NnJqOrlmQ/x4DYBXR5oonCnq/7iRJ4KvMYwpRyT 5hm+VQt7h3bFg8M2TrxAVEANPGefEy7XsyYBSMSq3M1yjPnQbdXKLk1x3NVxqAvnqGUecbzhRHVC ypI5l06zIU52gXZMzbjs6jkudVLOBLhgQmUlqfDYBnctcI/qQlUc26m4UJthJmF79dE5+eEaUGSa mIGrNvZPXmRLQbD0kMsSRC+4QjauFw/CQQw8nAtQJdMzmT9jrhwWkBtpx66B8SyY+QA0cPKQRwGE zIYsx+jewgFpDxYOyYTmVvoxcKmifDs4tpxVgsYuhswUKFJ5EVW/Ra26Nc8nmypZDX4YkK9x3rru 7oKIbDYvBm5pFEQhaVVW6omiMPGpemC17dyAYtAahZ7uREV5QbRROPIDS2EQPO8NOqv3/o78eiGV 3i0sJdRovVb5+scLFy/Zueu92g/AgMgenzPmOo4l6d38VXmSJGRko8Hj+c/poj4hLUDSNCl0eOFb 8/IDNEHKy0qmP8+jnaschxo8puC163iuDRHYEKENkVgQvrYjVZQbUatGoUi8HZXoPR+i0bUgdnYE +a2ACD0LInLoniOKDstYaJhPPhl8w2dR6NEDM5bTAV8dbhsQ0im7262Srihyso5h7CieMuNzFlIp 9zE9Pt0pcdRYQ3U0MupwngnK4BHT7K6bPkQuSLAHGhF7hyOFCfwoYGtEnbl+FPvYW6LUAArHeUiH glEfeqwCN2bk27k3Cs9RfWYWBIgdKVlnZLGBLgTi7oi6/J9JTuUpdH1izkq0TUmmsqq4HOLobsvv sh3tEiXQIEH0rkctFXxJNT0WVKOCp97fH4Imsjqua3SJJV3MjQYOr3vLHSk8N7B0dud598aAU+wI dsgRITU2HEHuIzynQ8cSuq8RuXS4kkYT0jFWKk1yf/6BxHcjUuhRSMKQOic4wk8snxmGd1cWp6Be 9+CIJCIR0NWEKpJ1vkPzrSELyWN4KVo0B8/d15l5MC9zWau3+jdo5JOrqd44F4Dg3pEHaOKkruqY WmWgqJFQep3XG5ygqklBSkETpyRAyT4kgefv6G4AivRi0SmI7dZlceSH5ImMqJ13b2CbIRMWoZJp 19ILPhtgNxHfgogoIroDCFAniTFBROKQX990WW1z/p2/5BAHibLZuvr/Kbuy5rhxJP1X9LTRHbsT 5k3wYR5QJKuKFi8TLIryC6NGrnYrwlY5JHmme3/9AuCFI8HyPsiWMj/cCSBBJDI148gJaXhDJupX TgjKwo4e/2oweOyyb+yKId7va7DkrCT1qRmymtRbFcga13fgWUlZyArghzErpia+Z3jGv4BIHiC6 2W/Kk0MPjYDSyrcWcLqNDGYbdcoxKC4U4iIbkIppfQdHf1yyb7SIghzr5oJMIb5pf6GLJNpSwRjE 8zxwIrFjcmB4RL0IXp/S3WmrgvTQ5Vl0V9W7h3J8NwiBk8IpTiLLApY5xnAssLZ9Uqf25t79OQ9s KNP6oWD6ls4gxxbWEyjD2Vq2KN/9C8wvBrZOzcJqUaCLlG7HwO6XUqXWs4AFijIc2wJ3I8oK2Ney rWoXJPbCApSlmQfG+pRBOxfasUl89IO+10LpSnz5e4rEcqHPGQuibYlhEpCiCMBgAOvaGNsOShB8 LCYhchCUL6b9iTalICvxaAkB0MUrJoHuOpBu1cYhcJRvj0UM6UxtUdvQVsTpgMxwOthEyrm15jKI 4Rm8APFt+GPbDOkyHKAAuj5dEK3t2OD4di1yDNcVM+QBuWHoQhbxIgLZid45jBEZGY6JAXQzpwOT fKSzBUg1yxUQOV3F2639dcQEJXAypiw6r47AaXrkpCBrvlCd6Fxdkl9pT6SBh+ol6pN3BZQWaXNI S/aYkH2Hrvb7IUlz/DgURAxNNsO5/g1fOEyIyhQxYWQ/NBl/nTy0TWbwljhDp4juw6HqaFvSenjI wAAoEH6Ps2aMpQr1jIjk7v5IjUFbljnB7Sx/tZIMt8Plgf+jDaNSI53PAgXgVnG+PTNVM57VqIgb eM042GREuLECcBPqAbfxMamEis8U5QHfQi6rB/xYnWSPnzNzfJfDnxtMoesh450FzlxycGs+lp+l sWfDqNEL1Pn96c8v16939evl/fn75frz/e5w/ffl9eWqXLfPyesmnfJmo6CZSi4ZmnzokGrfAh00 fZMzMHyRIY+Xu7CAPplGVM91tLrYJo9P0rMya2OcC3aM6zEbqtR05bhRqekFIJT4c5Y17NJ3IzXn kxpMPoe6h5Kvvfawlf18s6X3DfuW4fY9wKEScQLrg/OsCG3LHh4Sg5uFwLWslOxUwMQeTYUYU8yV 9v+AHS3T0aaM4H/86/x2+bIKYnx+/SLIXx1DNS2ynip2D7CdGFRQHWemgtb79ThbS4NmbNLWYkBF QjuirgjJdsrLUdnRxUTdxQUW4QJZ/ov7u+Q2QFDmEsJUDOeTKlYynkOIx5mWI9nnmMCeT8SkzNXz EBfwXikB4TvJETKZIazPoP74+fLEbJZnXwPaPVOxT5SlmFGEq3qRStxQ1t1mKnhcqwu+P2iGdjwR bh0U6kFkZRB7/zaw97ZxZXDFsqCOeWy4xWAY7l3GAr/RcLZu1sdz5hfuEE1+ysbougXeSjU7cmGd zwyGQdOHhSsaIC9EBBEjraNHssFYmw0Q2xnAWCULVwy1zLKcdiitC8YNSqcFQPrAVStKqbbBDxtj H3CbMgt9MhxAJzO8t2ObBXhQBmYkTtWVR6d2Agf+IM/YxyygRyLeD9CVb8te15AsllrCqLQkxdB2 YuY1ZYovvBiBKF6daMHZJxIYIqYx9kdcfqZLRQXHAWMI3bKUUbkRBmjgu3KV4RPsNiSp1m0XJnoY BgaXfivAN1VhZIv2qCtVPIktVOTpVBRZIUB0fKC2KDJcpKx8+KsZ57eBa3D4N7Mj6BMmZ86ak1xT pj/IlNk4Rqz8TFPvbVW2/IaA5y9Ysork1rcMzvY4O/ZbH0H2OZx7j+SPDpxY+m1gQ68/GJeksRbH mNMzLwx6bU8QEYUvvplcSNrzQM65f0RUTuG1b0xKDFEad71v3dicSFvUG9xHEoPPvhmzzQZcuK7f Dy2Jpetsxh3tv9XGMCMl0A/xlGFenNQkNc4LDJ7laxLYli/JwWh1Y3AbPzJD0/ap25GvVPFmb6E6 trZ2sCbQJoI7kcCXTN+F/DQJ5HQUbFZZMmYXqA5M1Xc8yqELqitI5Hxq0FWqmYNPiTgtJzN4cD4w L86huy2GeeH6oO0cL3O0/9f65lPRI+grLGN2PfK1tTKv4mOJDxgyDuVa0fhsQlGVRiK083KtxIGv injLC9+2IJ1yZqojRw+bUaQJFaeaV3DK9oz7ofrhbKVBDWIc39pU9HhlQAeHbMGsjgVVQ0N7fLMg L6YTjypd5rasGWyASMuUGYMP7XFN25v1joc4iVwPmlHzUXwRYtFhgOkIsh6a1wu5pbyFqD9S1RD7 rE+p3FZ5O5quaADmbOU0euUhJ+ld6ophH9H4NzQRBVSHakQHZVmBUUxvgrb/FcQOWSjw4XLmE9h2 DonvRsiQAT+sbSdXzjcrB5BEkTmdljYzV08OCsfQ7I2npQoIWvMkiGNbxjKUkDAAaI9L3/VBq7cV pGodKycjeeRa26nZNbcT2hjqI7qsB66h/5mCEN6qPwdBK6gIQaEDDj/faX0jJ4BZ425jqDNlBiHs YXpFzQeLX4D54AYmYVDgRVBFOUu08JJZ4/kBLpadI25XDkWg/b6EUQ46Kk826Fa4yGCnrMKcG100 nYwV16wSP0SmilAmMnxXEFG1TZXAm7DaN7kfF0EIGbx9y6Cbq3NRfwojwzFVQNED3I0FVDid6bz9 6XMqmSkIvA4hC5ZAzkKGlYszQYMuAfNQQPny90+yx4mVOZ/hdAbVKiA6cYoaWzZcS8YkN3qO+AUK A8NEI/mBBXfbbiehhzsrwIYcHhFyvFtywOxW7MDdnqvCYQnkOS48kOPxxwFlYz5PmXnw2iAcqeDm BL7t3pps8wns12DQkVMBRaaNdj443S6Jn6K2SxqPT6B6J3vXWBmqCt/onx0oqTBEwMozg9vJhjmH iauEKoxmfpfFKXT2jtdvHwKlrFoWuErQTHkkKs5r5MPGQmfPC2FnKSNm4uuJJwbVm5mrBljdn4C7 pOm4Gy+S5mmsX/4Uly/P51mxf//7h+hkcKopLtgX8LUyEheXOK/oIbgzAZj/zJaq7mZEg9mjbQOT JI2JNbuMMPH5g0ixDxdnDlqTha54ur4CsWy6LEl5dEZtfCv+GiQXRz7pdvpBSs+cF9o9f7lcvfz5 5edfd9cf7JT1ppbaebmgha809RQrcNi4p3TcDaEmRyROOuPZbESM57IiK3m4svIgusQaEe2pFFvO C98/lHRqiY2HGil1+eLZbe0Cdb4s/cy6V26V0sVaZjy35Pnr8/v5213bQYWwISuUdURgjQFMRSzu af/hmkXk+6cdiKw5qiTvNjkkLONy530k5f5/hrwihAUqgG+3KfyUp5CTp6nFQJvESa3dFI7TJs6E WSEOw/nH+09J+BWBaR+ozg5/8pkB8ssHPfMP55fzt+tXVmPDHMu6ttOlmlFF7+NZFbc5vHhPorvj aTYQx7TPTsVwSAtT3F8JVzWZwQ5qhBU9dLM9rRuta/PTmLFDPvz5979en7/I/aKUEPfgXj4zHR+J FoszWXQ6s9KGXY7j+10mh34S+Mok0wFFnR70tLsWeeZKEoxD2/XUCk1kZZ+Uedqk11GyaIoTYZ0m zDBgilurzX/chbbh8zlj707JIW3N33I5xomd6bq7NsaEZcA6p1syrFbxVaKgNYHPqTx1C388GHmG eyBcMr+ym9UvmU2YuVLJrsmSgxlAikyNETgrVHyLXxZMUX0bN//MCy2Dsr8ADJarI4AuyBn/bQPT ptgPDQvYVAyVo9AKYGOPOZM9PfcbNGKOGD/63wAguLV0A51AGZkNRiAldJn0rifqx9My3KV0pawK hb477R1Fc13pgJLB6UVaVLW67XNOUoy7cnYA8ytwnotWNnJCIq8dtNWLNgc0WgLSGjn0ZxM3TrFf yJCpl1vAcRUp4g+EiRZbhM7A6kEKMhAevrsx7DhePqqjpiL2z68XFmHy7jcW6PHOdiPvd+NCtc+a NFH3Nlm5FZ2TjaTzy9Pzt2/n179NegFuWyxbMkxbb6NeivBc8c8vz1eqRT9dmfOk/7n78Xp9ury9 MSeOzB3j9+e/pDJmyVQuzyZygkPPdfSyKSNCHrwmT4iUBb7zoWt0ASC+lJ22a1K7nqWRY+K6lr5j Et8Vn76t1Nx1MFDtvHMdC2ex45p30VOC6camafb0yCu9a1upbqRSu9oJSVFrCwCpyke6Fe+HkbcI x6+NGR/eJiELUB1FukoGozO7JWcJvh5sxCz000eoBC0GEfBCuiI800q6IAJrS2dlCAQ+iV00Glvr eEr0A1D7CeCPoCP/nlg2+BxykskcBbS6QQgqSLYmrCO5B+SPfccPQRd08zysfduDUjKGwYhrQYQW eLM7nwEcJL+ynOmRydGLAIC+d69s+TPVPAd615E/BQvyx8T6LEk9IMyhHWpTiOvTnuSqUJFooZTL y0be8kMqgQG+BhREPwRaOzK2E7qiTZVAlm8kZkbkosi8SOF7hEAJOxLkqDEmpH5a+kTop+fvdMX5 9+X75eX9jrkJ1zrsVCeBZ7nijZrImK4ypHL0PNft6cMIebpSDF3n2BX2XKw+IEHoO0fYV/R2ZmOs raS5e//5cnnVS2A6Bnsbaqtv0OcYMkrScdN+fnu60P365XJlDvAv334IWatDEbqWNuSF70iP8qfN HPpkRFjgvzpL1FueWaUwV2Vs5vn75fVM07zQnUQIVaKeozPf31ocs4J20dZKzQHw9dEK8GHbiRUQ 3irC4NViAbi36uD68MltBFSdE2xqNAxguCVbAZsbJwfcqEN4ow7+rUpSwHYRFADfUMyAINjcaFgO hpDNAuBWHaJtQOj48FF6AYQGO94FcKujwlutCG+NBUKbE6fqolt1iG51te2izZnTkSAwWHtNy00b FZbhhaqAMNxtrQjbYNexIGrL8MR0QbQ369HahiutBdFZt+rR3WxLt90W0liuVccGH6Ajpqyq0rJv oQq/qDY/hjYffa/crIt/H2A4OogA2NLeKMBL48PWXKEQf4fhx6IjIm1Req+I4RzHCNxk+C6TU5p+ qJ31Gx85kB51H7qba0fyEIWbuxEFICscurgA6ytVajzifzu//WneHnHCDC22upgZihrM1RdA4AVg deTCR42lzlS9YlVJVJ5yszbd+oyt+Pn2fv3+/L8X9n2V6zHapwWOZ2FSavF5l8ijB31bDjuqcJET bTFFBV7PN7SN3Aih0MDkXwvlx1IaG3weIKCK1rF6Q90YLzA0ivNcI88RHacoPNs1tPZTa1u2obw+ diwHmXi+5AFE5nlGXtHnNKHoCE7nhsDt9sSPPY8gw4lRAjLV2uC5SxcF22BbKwD3sWWBxi8ayIGb xnmGwZtqYUiZmntzH1Pd1tTTCDUkoEn1O/Cx0BOOLMsoyiRzbNBPqAjK2sh2DZLc0DXWUDQdZtey m71BJAs7sWlveYb+4PwdbZgnHvygFUdcit4u/Evt/vX68k6TLHF2uDHz2/v55cv59cvdb2/nd3qs eX6//H73hwCdqsEvNNqdhaLon98VIndeoxA7K7L+Aoi2jgxsG4AGLLyYRGRThC4eMg2hhLjMe8h3 sFFPPC7Of9+9X17pKfWdRSc1Ni9p+ns593m5jJ0kUSqYsUmm1KVEyAsdiLhUj5L+QX6lr+Pe8Wy1 szjRcZUSWtdWCv2c0xFxA4iojp5/tNnnYG2gHIT0cbagcXZ0ieBDCkmEpfUvYl8xtE63mL2YBmXO CiVilxK7j9T00/xMbK26I2vsWr1Umn+v4rEu22PyACKG0HCpHUElR5XiltDtRsFRsdbqzwK4YLXo sb9CWxSx9u63X5F4UtPtXq0fo/VaQ5wQ6AdKdAB5chUinVjK9MnpYRjZUDs8peiyb3WxoyLvAyLv +sqgJtmOdWKxg8mxRg4ZGaTWGjXSxWtsgTJx8D6yVGlLY3DJdANNghKHbiYNQPXsVCE3be4g14KI 6iix1Uup5ufEpjsTM8ipElGU4mkRNQoRm4RIld6xKxxwiNUFbFxEwrlQ3BJaZnl9ff/zDtNTzvPT +eXD/fX1cn65a1eh/hDzpT1pO2PNqOw4lqUIVNX43GGTRrTVXtrF9IShrmP5IWldV810ovogNcAq mfa+Ovps3ljKQopPyHcciDbQZoP0zsuBjO1lcchI8uurQ6SOH5V6BC9KjkWkIuQ97r/+X+W2MXto A+2jntsvojkZsQgZ3l1fvv09KUAf6jyXc6UEaDOgTaKLJ7hPcFZkzSWSNJ6t6eaT490f9PDNt3RN k3Cj/vGjMu7l7uioIsJokUar1Z7nNKVL2HMbT5U5TlRTj0Rl2rEzpKtKJkGHXJNiSlR3LNzuqOql LjZ0fgeBr+hyWU8Psr4irlxFdzRZYmulq1TqWDUn4ipzCJO4ap1UQaZ5WqbzeMXX79+vL3cZFbHX P85Pl7vf0tK3HMf+fTN27rzAWppaU7P+V7VuTbnmZbfX67c3FmqRCsrl2/XH3cvlP5K4y5ZEp6J4 HPYp+KnCZK7AMzm8nn/8+fwExK7EBylcSnfALDg0ZM8phm+lf/C7D6p9SI5fGD2p6SLTb0St5iAe D4Ck+Z7Zd8gZ3xdkCqSs0/c7kLXndruizy+NWXVpM9rW0K1FZ+cp5kEwiRJIiSFYhO+BHq8SZkJS sFC6QJvjFDKmYMy2VfLrGlyAzaBIkH5Ii4EcmfUOxO2U7El85G70lxB7053iHV2E4BsxlmqMNE5V mEBt3BirN1cMBRVA2df8u1CEeij9wlY/qAvx7EzVHHf7ppA+As5XjAJZLrXBCRx/njFxkRzqk1rR kTqo8Xt1RJzdb2bMH9XWrTJOE++Am3aU/9UJG47ru99GM5P4Ws/mJb/TP17+eP768/XMrJTl8WJx F2kyyU7ll3KZtsW3H9/Of9+lL1+fXy63yklioKsodTgmMWj7zWf3fdqUaT4nXmyvNwqWyyirU5di KKo3l/pDWqi16ugSYRoY0qro4oAPDvjYistPjBvmKe2YFNoSx3l5lxis6CjiUw97D2S8XRUfTdVk L7ZZyMr6JMtOjWlXztIy92F9frl8k3eJGUrbeyLDZ8tqh7bwa38o6VHIj+D7sDXVrkqHY8Zecjph BHnykaFtZ1v2w4kOVa6tGiNK7SQNsHzdBhKneZbg4T5x/dY2uGlZwfs067NyuGfO5rLC2WHD40sp xSNzMLl/pIqd4yWZE2DX2m51lmdtes/+ixCyY2CQhqwsq5xugLUVRp9jDDftY5INeUvLLVLLt1SL EA1+n5WHJCM18zd6n1hRmBiMs4SeT3HCqpq397SEo2t7wcOvJ6F1Oib0uAZfqK9JyqrDLAkXL5MV +IKu8qxI+yGPE/ZreaIDZvDDuSZpMsKiQh2HqmVOnCL4uk1IQBL2Q8WgdXwUDr4Lup1dE9B/ManK LB66rretveV6pfg1eUU2mNS7tGkeqeLTVic6i+MmTUt4hBv8mLAHEE0RhHYEfRcHsUhxDi6Aqvie d8THo+WHJTty3Orvpip31dDsqJwlhqtQYSbigpzodCBBYgeJaVlUsal7xA5cYQEUuB+t3nApASZA CFt0kyGe76R7w700nBDjmw1Ns/tq8NyHbm+DLkNXJNVh6yH/RIWpsUkvXwVoMGK5YRcmD6CHcgDt ua2dp8ZMs5YOX9YPpA3D2z3ATFdx3HuOh+/hZ50ruG1O+eO0I4TDw6f+cGtSdRmhanXVMwmNnOjW qkDndZ3S8ejr2vL92AlhCyllHxO7anwyAU3ChSNthevpbff6/OXrRdsV46RkAaHMql18pN3d0gKY Eryx28zLMCWVPFidEcn2voE9lzUdDIr0gFlINOb9Pal75pLgkA475FudO+wf5NYzDbpuS9cLtLWJ qbpDTVAgxihQWJ6Siir09CdDUuCskZFFlugdYyYqIVBG8v9R9jTNjeM63vdXuN5ha6ZqZ59t2Y59 pCXZUltfEWXH7osqk7i7XZPE2cTZN72/fgFSsggKTO+eEgMgxU8QAEEAD++6/77F1GmiOMP0tf7M gwEZDc0swwqfyyheisb5dvY59sZugYXnbykVIbDsVTFhEz00eJnNprBC5j1RBssWwWgsrUydVCJW L3phv4psP/MmnK+pTXZD8jQTbFBQBOpQ6I06HfXYhYH6RAntJNk+EItxMnp/U9Evh1UmdjH/dEP1 pvSLtUt+9+OyBBH1NkwtUTfBXXGwlkGwskaqHJn37o04by9aSQG72KYQO2FzmXCv34jj0/tQVpLj QSCUhFmlTA317TYuNxZVEi/x4W+g3hJpL5a3++fj4M+Pb99ArQ2uemxTZrWs/TTAHGRdPQBTj+MP Jsj4v7FEKLsEKRWYcfXgtwoavgsl8xYdv7vChzFJUgIv6yH8vDjAN0QPASrCOlyCLEww8iD5uhDB 1oUIvi4Y/zBeZ3WYBbEgIpbqUhU1GGZ1IQH8YUvCZyrgWJ+VVb0gj7dwUMMVCH7qBS3twG4tYLbp gAt/k8TriHYohYOgMd/Qqqs4Ud2v4mzNLpcf92+P/7p/Y2IY42yobWT1ski5hwZIfQD5dTykIqYJ x9XDFxVwYsCYVVbJOJUVF4oBO7amk73FRWgVx0j1+LaO16RxgEeBCtbjwme7GKaSb0AZ72gLEGD7 crdg15P+Fs/PanxjHqw4zSoVvfUBDaxT2BthBoI+/5mW6iCr+HYbMtXWa75i66GZ0XJlBKNjoEA0 pGMHNntJhkijPxkkUR0IS76CnHUC2rEDPYtSeu51afPwK4iZ6AYhfD/kkjYgRUw3J/yuvd52UVCH LIBrMsyBp8WOBm8OZW7V5wWO6IOA2+V5kOe8/I/oCkQ47sUSbkCQy8LejhXlxlVZkTpq8kWZ6tOJ cA0NhSNPwLm5YxNhEBp/K6s8tQcT49i6WoSZ29b7ajJl7XTYfx3ikG6WEFWnPLW20BJGyhS4OpgK 7rC2zs0WxywjJfY6OZbEG3Leh19198b2om6dTTkZQR0Hy/uHv55O339cBv8+SPygDcLChDxA04qf CCmbSDzMoF23IyE0u9hRNMlO2L50VMUdx9E6vB0RscMwEao7pIrcdcenOumorrGOmBqaGPyflgea +dzUqSzUDYvqxwc3hqMXHK3DqfCGQ+FELVhMMZ9OHV0sUMwsuQOwo+Gyhl/72KY26M89iaJttGYH Q3qTFHx7lsFsxIb/ND5Z+ns/y/jyTUTVX6w4a1Fct9AvNkrbFhDaMOeT/aKfF9Go2gTqWU5/1cqS CfJdRti6gYLPjbgXmgaJn2yrsakaK1yAMbOumGsve7e53Vdlvs3I0CjmEMVB/+Y3ikkQE/h5TSYv qzLM1lXEtBnISnFnFtxi7dx0YY0MA9FOEq/HB3TFwLKdWEuKiglaO/kmwBFebvd28xWwXq1cZQri R69AW9BIEgpbhskmzijMj9Dsa3/Pj2L4xQkxCptv16K0y6QCUwk5yygvXuvbhwLkY0mBMAnrPEPb uKl5tjAYA/u7IV6eu0YGY5zRc1lBv25CV0PXYdpEwTGBq7JXyTrBCEBsaldEwxeUJd0utjlwRxdi 7kRS5YVNv4vDO2XEd6/EQ6kUdidBjLmT3NjKjfsiliwHRlx1F2eRsJbTJswkaHtVbsETX+WWs4Bh YAOyfJdbsHwd43bhofijKAhz0XC6ThBcbtNlEhYiGFvLhVCtF5PhZ/i7KAyTTxacEo9TWBZhf38k KLw5yx1UViG7FGjmavE7pyiN/TLHxGOuitH2W4YHOn7pNqnidn0a8KyKKSAvq3BjNwqOZkwQBxuA k2AURViJ5JDtaWUFcBU4vFigtgHRzzSY6+no+lhDB+tJuurwYy7QvaJIRKYuJHyLExUl3hfbFUqB 96SOuprrGlqPLMIQTWAbC1yFIu2BYHHBsRJaTYFKi2RrAcvUmqs13tkJabLZK0hvCLPKVJTVl/zQ 1NudswbcvcyreJfbIwPMS4asTKuwEfCFHhOtohI0pxSEFkfYSiTa4sFcF5K/ulCsM47TvHIx1n2c pRZX+RqWud3zFuba/qrcIYCz2LmLdYrOOtr21nKD0Xpi88t1midNOu/27R0jUVw9oFgBCA3nrRBk uCER2hZhAtvyW7ms8wg0R2JU7EYQ8UwsUgTDHkTtnA9giATbpIhrKyM6IYB/M1dKNMSrzIWRkHXk B9bXHSV0Djc1ZEiEXTVEsyu8+PHz/fQAA53c/yR+kddPZHmhKtz7oeNyALEq0eLO1cVKRLvcbux1 Nj5ph/URgcHn+C8cipCXFrBgmcOEyru4YiXQNCUmgeKulOEtiFgpX2GD75sNWmaCMbC2goRiTf26 8Yw0YmnpcFrR+f2CjlOta2rQnwIszsS/NLAyiNhkf4i7W8rAakq8gu1oAWUAkn0e1T7hD4jxlzfs RRvidio6bUoyQAF4Cw2KZzDsQwr3byOaWxCBkbx1dqy9EeRzGSJFWhlnTAqCcRX7DMRKKnh8Pr/9 lJfTw1/cmr8W2mZSrEIQSDCVRk/tMWtxT6Ndpxr9lI5yi/uiJJus9uZsxp+WrJwuDANMFt61YkAr tIV4V432IA5W94QuhVuWKG5koJzU0R06/GbrsK98oq7OjJiqoTWj8IIkUghRjVyxRTRB5g3H0wUn f2u89GY6oaNVDlPJc+ZO3TU/nXmmObuDTm2oykQ07H1AgXkftBY/m/wCvxhzs3pFD80ghgpa+GIx pSHhTHjvxKBUjvNEfw+zc03srgPQtOw1wOlUZVdIU5p++Yplk853WI+pcNbvE5rFWF+bFqvNesxA TD9ZcEgw8z4haHIhoQGJVWsVkW3y1FWbGQoUxEwBRBZaMJ4PmR5X3nThXLNdxlET2iWzMKGVLzAQ f+8LVeJPFyM2X6iujUnScV3t07+dxYy0f7TcpgrGswV3XanQsfRGq8QbLeyF3iC0Qd/iM+q5zZ9P p5e/fhv9roSFcr0cNDbDjxf0MWekxcFvnQD+e49TLVE14XOx6h4me5hMNx49wt1Ynceu2TKuseCy 1ymEXKfeiIayuY5I9Xb6/p0cK7ouYN1rK6asiVDZwznRmxDlwPujvHJWEoUg1CxDwamkhJC5XCV4 3/SHJhjhg5IVVwcHmhqxCarNba94lBqv0+sF3wq+Dy560Lrlkh0v305PF3ySoBzWB7/h2F7u374f L/21ch3DUmQSPUV+1X2dK8DRzkKA0u3AZWGlg+vzDSiUPZe3itBR3LpCAONdKaaMRsfnA0tRVr6W EjhHH8wDjNdLNKD7FdoXUrVXXyr6TjIY/zbM1sRJBmHXJGcgf2RhIik2NxR6gWkfBEhS68DMkB3c 1WIfIzW96JNJHWJL+t2KlaNgDMgZ8Ykrkn3Nl1B3WRGWqNN1aizzDkEaFKis2CTocAPtk1nJt+Wq LqxGXAfVfzodXy7GoAp5yEBmVs22pgjVD66S5XbVT7mgqlnFpn1d3ikoUT6b4twy0qg6zXdh4/j0 GVn7cszxAkMTAfsp+MiEVjeM5b7dNw6evCaH7l+c/mxyGfhR+zGxrCKowJQi6zCLS155QZoA33j1 aQwKEfp2xXCy+LnkxAL1Wbza1rcwtInAO/a9NpZb6bA5YLDwlTuYWckGaTbQNGFc884F5IItX2FQ cNtop9LQYylSmYJmDkVfY3cy93m/B41H87BsTDiNC2Jfezs9vJ3fz98ug+jn6/Htj93g+8cRlDjz Hv4a/PFz0u7z6zI8uKwgIGMCv+OlinWeBKtY8jHXtSABbJk1wd7JIs6SXCm9+vB6OoNCKs8fbw+M l1k8H0+9uqFvP5BslkmgUUQvRW0UfZrrIq5mE958w37uqrKKOFnmhrh3jTOeRmTWW24OxJzmq6up 6fPSGMZla6fxWB9fMHrAQCEHxT2c6SpkgOxP669I6XesR34lKP+XIwaP7o9xGaJltihz4ojLlNA1 vT6/f2cqKVJpWNXVT/UO14apQ2dNje02BgE21tjHbQtJS4yVi/fQd3HZN4HAPhz8Jn++X47Pg/xl 4P84vf4+eEdx/BsMbEANjuL56fwdwPLsExtC++CRQetyUOHx0Vmsj9VuNm/n+8eH87OrHItXBNm+ +Ofq7Xh8f7iH1XB7fotvXZX8ilRLov+Z7l0V9HAKeftx/wRNc7adxZvzhUa+3mTtT6BF/d2rsym0 B6Ew29c7f8tuc67w1Vr/f1oFxsGLT8Z3qzLkzsVwX/mdFB/+fQEhvZEf+1Y1TYwp5OsvwieXdg1q JcViMufslw2Bnf20AXNJPHsUnmfmF+3grVbNIOY0KXqDKqrMDjlOCcpqvrjxRK9OmU6nw3EP3Nrk LStjXnIuALEp78CPGqSplXlx3cFqn9zyGAi0GTYph/lP1JtVvFLktOJGawkD9rP635Vky/RI1edl XSh1TZOMaWtBjnX60jX4rnLNfR4ejk/Ht/Pz0U5DIYJ94k2mznTZCn8zduKXqXAF/wfUxPEgcJn6 sFKcbq+BGJsR8gLhWY9MUlEGbIh5jVn0iFnjv3G/p1pSewGdDZDCGgSoY9KBw0s7C7/Zy2Bh/bS9 Njd7/ws+DXbERfS9scdfWIibiblhGwB1n0YgyasLgPnENP8BYDGdjiyNroHS2w0EsWntVcxIsyl7 fzY22yarzdwbEashgpbCEXPBWqZ66eo8YxiRpAmcA7wUGGh/Id8MF6OSe+UEqPGCdAogs+GsjleY ZRzfpCVJyD+PB8rFgre9iiBWaroIHFtH5fS20QZyPkekwfeyXZjkBSaKq9RDPrPJ0Z7PIZ5U/nhy Q3qnQGxSAoVZECMrnhHezLEKxX4xc8Q+Tv3Cm4z524JMbO3MyL5hXMDct3UsaAyHDrNzDWhHAhRc 92SgTtE0D2wbdqXKDPUD+e7GFaFyZD2iM5ApHI57OklN9lMYG9p+gM8Qvi74Cd+tZqNhbRVq5JV9 r8fthvhs8ZvbQ0XxGYQkIhVyqTKUvkhIDsd+iUawfX0CUcd2e0z9iZ1n+yrqXgvoEj+Oz+r6W6rQ znRzVomAIy1iHCgsmvBr7vayWKbhzDwY9G+bs/q+nDsWbSxunXnTQJ+4GTpehGOLYswbWMt14Xi3 LgvJcuzd1/mCJO/pDZT2iD09NoABTFwTA4r4xrZnlZYTmqssHt0d/52/CFu/uVYw95WqQjYjqrUj WbTlrm3qhOYe0joiaYU8rjmCaHA0zPii1qmL20+HbPQfQHg0ZzdAJhNOVgDEdDFGU7/ps6qgXkkA JD88/l7MaI+CIsdHBTQojZxMxlwT09nY88yjWOynI5snYw5IrqxfTG7o8wTgU/Dl6fTGERde8R2g 4M2On423dlaCxfL48fzcxu8yp7+Ha54KHv/r4/jy8HMgf75cfhzfT/+Dl1lBIJvYdoaFR5kv7i/n t38GJ4yF9+dHE+/HMs046BRh8eP+/fhHAmSgQifn8+vgN/gOBulr2/FutMOs+/9bsnsX82kPyUr+ /vPt/P5wfj0O3vt8cZmuR45I8Ku9kGOMOel2IG42/PpQ5iC6cqul2HpDEotdA9jtqKthBV2FYuTc uFp7bXQQa0H1u6253PH+6fLDOCJa6NtlUN5fjoP0/HK62KfHKpxMhuxWAvV1OCKRtjVkTFgfV72B NFuk2/PxfHo8XX4aU9Y2JR17I7L9gqhi5bIowEipe5ZFR9s0DsgVYVTJsZn0Vf+m8xRV2zGR82QM BxYrBwFiTKal1yO9t2FTXfDS+fl4//7xpnMvfcAIWYs0hkXq1ABX+1zOoSGON5+bdE9j78fZDtfh rFmHLh22qhOZzgK5763GBn499ltm5O6MvntWr3CYTSiCLzAznkNkEMF2D+uJ36QCY6Jzhz4gMHEg OYeKQC48h0KskIsZ+zAsGt1MyYmGEIfO7afeeDTn1iNizFMHfnumX4uP3jtT+ntGVcF1MRYFnzJO o6DHw6FhGrme/jIZL4ajuQtjujUpyGg8ZTeOSGwHaw0vStM+/0WKEYnMXxblcDq2dKTS4aqzgxmd WB6EYj+ZuGJiNUg+Ak2Wi5HnSACcF5XnynBTQA/GQxt93d6jkedRTjAaObI4gcLteY44WLCZtrtY jln1x5feZGS4VynADVXmm1msYM6mDh1S4RzJHxF3c8OtJ8BMpmb+i62cjuZjwz6z87NkYsUN0DDP kQ4mTJWG9gnyhpXfk9nIVDq+wrzB3IxM3kN5i76au//+crxoUwbLdTbzxQ0rwSLCWP5iM1wsqP2r MZ+lYp05WCigPJJo0tgsWCys8jSswlKbvAxjj+9NxxNuGBrmq77JSwltc2x0u0pAl5zOzZSGFsLW 41p0mcL6Zc6f9mKTG+h/u2ZUeH060gS2StXZEo2MEDYn48PT6cU9e6a+lfmgxF+H83M7o7bb1mVe tWFhjfOL+aSOydt4TA3+GOj8EE/nlyPtUFQq9yii+BlodA8py21RtQSOCa7Q4ynJ88JVkTzIleQq uXaDb2xzAr+AJKZTeb58/3iC/1/P7yeU5MkYXzfVr8mJqP16vsCZf+qs3J3GNqaMK5AjZ0Ya0L0m Di9Z1L6GNPGMgSH8qioSWwx1NJPtAgyd6RSTpMViNOQlbVpEa0SY1xJEIEZ+XRbD2TBdU25SjB3i RJBEwBb5x7RBIb1fmdXtd6LFkBxbsV9gJiPWzl0ko5FpW1a/LSt3kXiUSE5n5tNx/dvmKwj1+GgI DSdTzeZOpenEzM8ZFePhzGjP10KAiDXrAWxJtTc9nXz6cnr5zu8FG9lM9Pnv0zPK9bhLHlX6mAdm 2pVQNaWB/TCUaYkvhcJ651juy9HYsRMKlxNIuQowDSJ3pstyRfMJy/2CX0GAmNKTHcs60hrCme+5 5PNdMvWSYS8cjTETn45f4yTxfn5CH173FcTVOeJTSs3Lj8+vaMlgd6exc6owJU+K02S/GM4ciew0 0mMFqbTQAbTN30bchQo4+nBk/R6TJ2hckw0Jt2KTDqchPhZrzXrws4nY1r/+RlJfLEYYKtIQ7wBa gVg7mVPYSmxCUusZsyUxD452aYz0oCgRcfBa0HUbT1zi4Yc+8sypQKAr7BDi0E1zVVm1qMcKHoUp x/75lAKru6QHaF5ca8mkvFVRyJnXg+Ut+jkRnRNaEvPyYYCuSlCEiCB23QZnLIS/sd//tXs+lGGF V9dVmScJFRo0bln6qayWzXUEzzgUofZjXfNxgTUJxkU8SJ96pWtuGB0G8uPPd+XE0Y1L42uIsfSN qwM/rTd5JtDLYNyguhmODjW+vc9AVKvysrQcplm6AL/+KyIZgxjGhzYlZCLZ8c7PSIXrK0738/S2 /xzRIEvjPQylzonwWduKvajH8yytI8kuFUKDo9UbKVjHxedNEUUR5VlYp0E6mzmyjdPZMyrAAATw BYdExnGfUpANC02b9BaLeHl8O58eDdEoC8rcjFzYAOplnAWYl6sgUgTFrrh9YVXQ+p3/488TuvD/ x49/Nf/898uj/u8f7k+bmSmMqzzdB0MoE5zrYbYjGSTUzz5fa8B4vyoDwb8saYLh1CF6Bqa9QY3u Bpe3+wclp/RDQcmKr1Rv+ipilwVTpWF7LNZspD1pvLCHH+p5IebUyPKAhgwDnH7E7nppZlBYr8MN jFChAnjrKFABs2ID7CFqGaJHkV1v7rNMG4M/FEm47xx7DM21730JWi7oPuubxdjwuUJgz6sKowWl 9nuLvnLMuenFrLOrTOJ0aQUoAJC+wverkvP6UUqqr4MYk/vcfJu5wgykuazYVlvHu76YOj2BBKP4 CxUVBMrCIAeDaluIUrLqMeJyiWFyfeOA1rFZ6T5qYfUSPZTrvOB4A75MUB7MsRl2IoWNj44LBwd+ hQ7hfnkorsaDDrGDQ46PXyivYVs7PtF/0HCdBYVRz8PIF4SzyO02r4wVpn6i87ty2lWzin42hlRT ArAhuxNlprvYuXkohPux+O0qreodbzfVONbzBGv1q4Tw8G2Vr+SkXvHO7hrtwq62GNaIx2FqHwzJ TdF6zd0//CCRdkEi8iOLKymQetDp+HZDEcWyytel4NmLpmkfjfcK58svsNNAA3RsoaalWrR6P348 ngffYAd1G+g6nblfWyIygja2q4WJRBGuMiVdBBYYCzPNs5j47igUSLZJUIaGywMmczF9KtvzrFN0 aJsUoNvDvEFa0ezF/1Z2NF2N48j7/Aoep933umcmIdBw4KDYSqKJYxvZJiQXvzS46byGwCNhZ3p/ /aoky9ZHKc2eIFVlqfRVKkn1UZaYCBDb4ySuI06tQG3qj5wn1iHf77GuHFYo1yTBsjjnGUxnHDzW dVlansgFj4MET0UhXTIMhsR8MIlzMUdMIz/1G7wNExB6QiLra5p+/BRJss46NDaQmmpkFuIhZ9Gx Oi5Hww/UsS7KOFxJEOG2UbtYom0deWS4Qos17CNfWG3APsAb1fF8+tB8e9ocmlOPMC0yO2NNiwEX iWMc4YJDSO5lxuf4DE2dyQm/b4fOb+uST0HcJWciRzI7nQWpcfHOIXJ4GhC6ijUp24J4kNnKl0ps gdh800Q6VVTqtDVmBRmLrbmKcyyUjiDBXgCEiAZDU7FDZ8YBA7Z39yf0hlWha+lVVCnPI/d3PTVn vwAUVMLqOR9b5gotuW4GSwVhBUHb0wjizwS8vtqPApceEc1nzgbQgsKD0RLg8ljTMHOmwS+1JVon UAmGNHrLvjG+t5xNXuUQ8jCM9zYAGx1WTRT6AzUc7RoggJmOdUkWE2v9kX7jMSChkSJ91egntei+ kH3mVV6jp9zUfJMXP3p5td2/XF6eX30enBoLJFEZSORWPwpcw1tEXz5E9AV7w7ZILk1DKAdjzSgH 94GCv4Q/D1h3OUTYK79DMgwxf3EWxIyO8PXrZl1cBAu+ChZ8dYaZWtokwYG4Ogu18moUrvLyC34r DkSsyGAK1tibnVXIYBjkSqAGNooUEWM2SFc0cNnUiIClvEGB+ViYeG80NQK3dzAp8Cx7JgXmI2bi rwLNPQvARwH4uduIecYua0zb7pCV+wmEGODZAk2XofERTUrTv7yHi/NoZce773A8I6WThcMnWnGW JOhNqSaZEpqwCKsBwjpiDtAazwTbJI19tllasTLYD3jmEE1SVnzO7GBZgKrKCbYq4sRM3pos/PNj lTJYG9jdQVYvrQcF68ZFmZM39+9v8ODmBWyY05W1j8HvmtObioIzvLtbakWW8kKcX8WgAj0X5yD7 zAdRKqkM6otrNu1tCkLSc1HHM8gKooL1WnYtYrdk5QpiJBTydaLkzL660iTYDVmLMjfzGdyuyizF qeCokmEU8pXUbiLi+gO5ZFgdYGUSSQqIJO6m6kXREKJldn36x/7rdvfH+755e355aD6r9LfdyUNH qum7wAwDkhSL61Mw2354+Xv36efmefPp6WXz8LrdfdpvvjWCwe3Dp+3u0DzCTPj09fXbqZoc8+Zt 1zzJ9DKNfOzuJ8lvfbC6k+1uC4ae2/86yWFZykpoVDSv08zODSFR4GQLXWkE2gncRyviiVitQdou yTXKkkaHW9S5ULgLoj/Gi4mZ6Yve6O3n6+Hl5P7lrenTEfdNV8SieVOSGzuTBR76cEpiFOiTFvOI 5TNz9jgI/5OZitDnA31Sbt9faBhKaJzhHcaDnMzzHAX6RcCh2ycVIpZMkba3cP+D9vIUpe7OXk4y r5ZqOhkMLxdV4iHSKsGBfvXyDzKyVTmjdvybFoNG1snfvz5t7z//aH6e3MvZ9whR/n+aN+d6VArs FaZFxv4koFGEwOIZwhmNeFzgL6a6sRW/pcPz88GV1wLyfvgOtlH3m0PzcEJ3shlgPvb39vD9hOz3 L/dbiYo3h423mKJo4Y8OAotmYnMiwz/zLFmBsS+yoqassFIR6bVDb9gt0hMzIkTQrV76Y+kBA2J4 7/M49nsyMrOyaVjpz8cImX3U9o1voQnHH+RbdDbBHmFbZI6xeFcWSDVir13ywEOv7kqIhlNW+Dui bkNR2FF+1dPkZv891IlWECstqJzgW5pz0ZxwY2/VR9qkr9kf/Mp4dDbESpaIY+26uwPheYxinJA5 HeLv8BYJpun0bJSDP2M28ec+KtCDs34RjxDYOdLyBRMzXtoqHOlavoixJQRg09G9Bw/PLzDw2dCn LmZkgAGxIgT43HZp7xHYCU5jF2fYN6VQMcYZeqnWSuYpH1z5En6ZKyaUMN6+frcefju54y9wAatL RENIqzFDqHnkD+I4yZYThkwFjfDuLPXUIgsqjk4EQYCKH/qoKLFJA3DsqkHvOkjbJ/IvJnhmZE3w 93s9UCQpCJq3ydkEsEHGg+t3WJ6rlGjuhPF7vqR+35XLDB2MFt53q5oqL8+vYH1q6c1dl8nHEkz+ rzHTiBZ5OfKnZ7L2mZcPJh4UHkU0c3yze3h5Pknfn782b9rlU7uDuvO1YHWU8/TI0on5eKojsyGY gIBXuF8IWkkUoY+EBoVX718Mol9SsJPLVx4WlMYaU981AteoO6yhorv8djRHO6yjas8FvrQiaOZ6 Q7UXZ6eJe2Z52n5924gz0tvL+2G7Q/ZfSE6LySoJVxLIm5EC9cutDIjUujTiDWIlKaJjAy6pUEXT p8NED8D1TinUZbam14NjJMf51WS/5NjRTI/z3W14blEzXPsjxWoBiQ1ZJG9J4PnIt3YAn8xvUgHf yyDI++3jTpkS339v7n+II7FlISafG2FkIfpu0V3q4PYJHyi7tawPTUBIcEx4LV/d7cdpIi1vkA4b M7FnQ1RJ40VdW5iK7TyN8lU94dnCOQOaJAlNA9iUlnVVssTWjjMeo5oRJLqh4gi4GFvp4dRFlZlE rLOAjRgEAiTGwVdm5YAHz2iR30Uz9QrJqaX9ReIoJCSXBRpc2BS+zhjVrKxq+yvLARV+2maNNiZh ER2vcKt/iwS//m9JCF8SNMOMwo+ZzeGFtXG5sifCrsnF2umU+p7SUFWV4m6WpFJxG81HijUNI/qy ABpTH76GFSyEb2LZpqyVPHKgYNaBlYEbcngWHAY1ygluqiHBGP3dGsDu7/rOjLnRwqQpcO7TMmIO WwskfIHByplYLx6iyMVC8KDj6C9z1FpoYLz6ttXTNTOWmIEYC8QQxSRrK95yj7hbB+izANzoCWl7 d0uSGo4ZxpoviixiQkrcUtEjnJhxCEgBEsK0FlYgmYLekhwAt4JEp0LPrQsV5DqR2RodnIw1TfLa yXQpRRDgSBzzuqwvRmP7rUPiwIw98KpdTBN1sWv0yI0h/tIE3vON1Zms65LYQQD5DeyqmBXCImdW PnXxYxIbQiOT2d6mYrfiK6dRaVareKfMMtaEd4J0iq59w+HL2bPsC3K9c0ro69t2d/ihXJiem/2j /7YiLS7nMoS+tcspMJgqoDavkbIsggR6idjzku7q9UuQ4qZitLwedZ0nzdOQEkY9F2Mw6mlZiWko 0HW8SsmCHUsiZFHUAeNDobOMM7Ft1JRzQW5Fxgr2Y3d02j41nw/b51bB2EvSewV/83tdMdJqxB4M UgRWEbUUbQOrV3TArtygLPKE4YZnBlG8JHyCb5TTWOh+EWc5qtzTVF5WLyo4os+oGXJ5wkUHSgve 68vB1dCe4LkQM+BksMA9hkgsixU0ZvtnFPySCrDkKQm6GlWTChqBjgOWlAtSmskQXYxkr87SZOWO wSTjkeCekrmMtakSOvTK5UdH+zczYHO7PuPm6/vjIzz3sN3+8Pb+bIe4l7kmQdeV3lc+sHtzUn1/ /ec/A4wKEg6aWp6PgwvmCjyKrk9PncbbDjLjwn31dsJLH22YXbSynHN7G2xer63MVX1hhpwCWUHv Sgi3Zhu4q1IALyU9btUIX+cZg7SrAfdUVYyyfA5E6lcTLCH4NWqLlo+MFYg2TMaIdRK3NDSN3WWj irhd+BB5f9waZ7koPkaA+VSodtPC62wZJVe+Y/aoORGDrLgSZ0/3AbMfDK+tMyf2v7rdBvqT7OV1 /+kEAmi9v6r1MdvsHi3nihyShcBraoY7Qlh4cMWoxIS3kbBtZVXZg+GMUuVmmEzd89mk9JHWTgPR PhcmoawDO+gFiTsujZ6CyupZlUKiwAIz8VjeCFEkBFKcWcYUoAC07UEX4PF+ViYVQjw9vMuEbf6K UnPRs+GQYMS/QD9KI0W68wJGZU6p6wmuTtzwYtULi3/tX7c7eMUSjXh+PzT/NOKf5nD/+++//9vd LkHNrEp6R71ZbeQIcFhpPziyYPmyoItjBK2rjbpIO5rKQzr1iIlVgqWpr7/p4V4qrn6h5f0f/WSU DVuaEIOQ2k/o1WJ81XnySPPmSuQFlvEPJd0fNofNCYj1e7hE8RQZuJBBRLLrP2KP2dT/QvoRMScv R79GQT6ndUxKAjocBC3xcmRbayPAvM1HJJQtmpZMBZBSt81RhS0Yc2StI3tUgZ4wCR3/AO98a2K4 5QEFIHpTGOtShxCwmHJ7TsgQpbVwqa8gXMh6xAHHSo0hTxtuYHID2JpPF0tiOY8XBLKD+h5Mm6fX 7xus6yjhyarV5I2TUJLPiDa6FyJHLHA46Fl3AEJVm9GFpYC5tZjnn7LZH2C9gCCMXv7TvG0eG3PP mVdpQCPWcw/Ufxm75y+lLyJdqVSwjsLsmQlhiashGCiliOgTqfVVPQGhgLLm1Ncpati5LJKnb7Gf R9ltO+a2dzKvUpDPcibCQAfT2ghVISidjva2Z+GkjqT/A76SYzM5sgEA --===============1125898102267184515==--