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=-7.2 required=3.0 tests=HEADER_FROM_DIFFERENT_DOMAINS, MAILING_LIST_MULTI,MENTIONS_GIT_HOSTING,SPF_HELO_NONE,SPF_PASS,URIBL_BLOCKED, USER_AGENT_SANE_1 autolearn=ham autolearn_force=no version=3.4.0 Received: from mail.kernel.org (mail.kernel.org [198.145.29.99]) by smtp.lore.kernel.org (Postfix) with ESMTP id 03222C433DF for ; Mon, 15 Jun 2020 06:41:32 +0000 (UTC) Received: from vger.kernel.org (vger.kernel.org [23.128.96.18]) by mail.kernel.org (Postfix) with ESMTP id C3AD42067B for ; Mon, 15 Jun 2020 06:41:31 +0000 (UTC) Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S1728372AbgFOGla (ORCPT ); Mon, 15 Jun 2020 02:41:30 -0400 Received: from mga17.intel.com ([192.55.52.151]:42534 "EHLO mga17.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S1728162AbgFOGla (ORCPT ); Mon, 15 Jun 2020 02:41:30 -0400 IronPort-SDR: tpn+5Ef1DT+jswaPvdoNVfXitxdW6F4YOS3nFr7ceXN2Bv9MJshaV/zjxG8arMNX8Qxz6i5bcn lRVCF46CPqTw== 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 fmsmga107.fm.intel.com with ESMTP/TLS/ECDHE-RSA-AES256-GCM-SHA384; 14 Jun 2020 23:21:27 -0700 IronPort-SDR: JrTCexH3ge7o272DcF0rC+TWXshy7HD1thYqIkMpvGjIxjVqfKesB+lUnaP2GomG+bIsEpfj0J 8cwIveQhcmBA== X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.73,514,1583222400"; d="gz'50?scan'50,208,50";a="449179493" Received: from shao2-debian.sh.intel.com (HELO localhost) ([10.239.13.3]) by orsmga005.jf.intel.com with ESMTP; 14 Jun 2020 23:21:25 -0700 Date: Mon, 15 Jun 2020 14:20:55 +0800 From: kernel test robot To: Mike Rapoport Cc: kbuild-all@lists.01.org, linux-kernel@vger.kernel.org, Paul Burton , Thomas Bogendoerfer Subject: arch/mips/include/asm/mach-ip27/topology.h:19:7: error: implicit declaration of function 'hub_data' Message-ID: <20200615062055.GE12456@shao2-debian> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="Ll8TiHvqIhrSSeww" Content-Disposition: inline User-Agent: Mutt/1.10.1 (2018-07-13) Sender: linux-kernel-owner@vger.kernel.org Precedence: bulk List-ID: X-Mailing-List: linux-kernel@vger.kernel.org --Ll8TiHvqIhrSSeww Content-Type: text/plain; charset=utf-8 Content-Disposition: inline Hi Mike, FYI, the error/warning still remains. tree: https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git master head: df2fbf5bfa0e7fff8b4784507e4d68f200454318 commit: 397dc00e249ec64e106374565575dd0eb7e25998 mips: sgi-ip27: switch from DISCONTIGMEM to SPARSEMEM date: 8 months ago :::::: branch date: 16 hours ago :::::: commit date: 8 months ago config: mips-randconfig-c021-20200612 (attached as .config) compiler: mips64-linux-gcc (GCC) 9.3.0 If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot All error/warnings (new ones prefixed by >>, old ones prefixed by <<): In file included from arch/mips/include/asm/topology.h:11, from include/linux/topology.h:36, from include/linux/gfp.h:9, from include/linux/slab.h:15, from include/linux/crypto.h:19, from include/crypto/hash.h:11, from include/linux/uio.h:10, from include/linux/socket.h:8, from include/linux/compat.h:15, from arch/mips/kernel/asm-offsets.c:12: arch/mips/include/asm/mach-ip27/topology.h:25:39: error: 'MAX_COMPACT_NODES' undeclared here (not in a function) 25 | extern unsigned char __node_distances[MAX_COMPACT_NODES][MAX_COMPACT_NODES]; | ^~~~~~~~~~~~~~~~~ include/linux/topology.h: In function 'numa_node_id': >> arch/mips/include/asm/mach-ip27/topology.h:16:27: error: implicit declaration of function 'cputonasid' [-Werror=implicit-function-declaration] 16 | #define cpu_to_node(cpu) (cputonasid(cpu)) | ^~~~~~~~~~ >> include/linux/topology.h:119:9: note: in expansion of macro 'cpu_to_node' 119 | return cpu_to_node(raw_smp_processor_id()); | ^~~~~~~~~~~ include/linux/topology.h: In function 'cpu_cpu_mask': >> arch/mips/include/asm/mach-ip27/topology.h:19:7: error: implicit declaration of function 'hub_data' [-Werror=implicit-function-declaration] 19 | &hub_data(node)->h_cpus) | ^~~~~~~~ include/linux/topology.h:227:9: note: in expansion of macro 'cpumask_of_node' 227 | return cpumask_of_node(cpu_to_node(cpu)); | ^~~~~~~~~~~~~~~ >> arch/mips/include/asm/mach-ip27/topology.h:19:21: error: invalid type argument of '->' (have 'int') 19 | &hub_data(node)->h_cpus) | ^~ include/linux/topology.h:227:9: note: in expansion of macro 'cpumask_of_node' 227 | return cpumask_of_node(cpu_to_node(cpu)); | ^~~~~~~~~~~~~~~ arch/mips/kernel/asm-offsets.c: At top level: arch/mips/kernel/asm-offsets.c:26:6: warning: no previous prototype for 'output_ptreg_defines' [-Wmissing-prototypes] 26 | void output_ptreg_defines(void) | ^~~~~~~~~~~~~~~~~~~~ arch/mips/kernel/asm-offsets.c:78:6: warning: no previous prototype for 'output_task_defines' [-Wmissing-prototypes] 78 | void output_task_defines(void) | ^~~~~~~~~~~~~~~~~~~ arch/mips/kernel/asm-offsets.c:93:6: warning: no previous prototype for 'output_thread_info_defines' [-Wmissing-prototypes] 93 | void output_thread_info_defines(void) | ^~~~~~~~~~~~~~~~~~~~~~~~~~ arch/mips/kernel/asm-offsets.c:110:6: warning: no previous prototype for 'output_thread_defines' [-Wmissing-prototypes] 110 | void output_thread_defines(void) | ^~~~~~~~~~~~~~~~~~~~~ arch/mips/kernel/asm-offsets.c:181:6: warning: no previous prototype for 'output_mm_defines' [-Wmissing-prototypes] 181 | void output_mm_defines(void) | ^~~~~~~~~~~~~~~~~ arch/mips/kernel/asm-offsets.c:242:6: warning: no previous prototype for 'output_sc_defines' [-Wmissing-prototypes] 242 | void output_sc_defines(void) | ^~~~~~~~~~~~~~~~~ arch/mips/kernel/asm-offsets.c:255:6: warning: no previous prototype for 'output_signal_defined' [-Wmissing-prototypes] 255 | void output_signal_defined(void) | ^~~~~~~~~~~~~~~~~~~~~ arch/mips/kernel/asm-offsets.c:334:6: warning: no previous prototype for 'output_pm_defines' [-Wmissing-prototypes] 334 | void output_pm_defines(void) | ^~~~~~~~~~~~~~~~~ cc1: some warnings being treated as errors make[2]: *** [scripts/Makefile.build:99: arch/mips/kernel/asm-offsets.s] Error 1 make[2]: Target 'missing-syscalls' not remade because of errors. make[1]: *** [arch/mips/Makefile:414: archprepare] Error 2 make[1]: Target 'prepare' not remade because of errors. make: *** [Makefile:179: sub-make] Error 2 make: Target 'prepare' not remade because of errors. # https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=397dc00e249ec64e106374565575dd0eb7e25998 git remote add linus https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git git remote update linus git checkout 397dc00e249ec64e106374565575dd0eb7e25998 vim +/hub_data +19 arch/mips/include/asm/mach-ip27/topology.h cc6e8e0812cf95 include/asm-mips/mach-ip27/topology.h Ralf Baechle 2007-10-11 15 4bf841ebf17aaa arch/mips/include/asm/mach-ip27/topology.h Thomas Bogendoerfer 2019-10-03 @16 #define cpu_to_node(cpu) (cputonasid(cpu)) d797396f3387c5 arch/mips/include/asm/mach-ip27/topology.h Anton Blanchard 2010-01-06 17 #define cpumask_of_node(node) ((node) == -1 ? \ d797396f3387c5 arch/mips/include/asm/mach-ip27/topology.h Anton Blanchard 2010-01-06 18 cpu_all_mask : \ d797396f3387c5 arch/mips/include/asm/mach-ip27/topology.h Anton Blanchard 2010-01-06 @19 &hub_data(node)->h_cpus) 9dbdfce85c165f include/asm-mips/mach-ip27/topology.h Ralf Baechle 2005-09-15 20 struct pci_bus; 9dbdfce85c165f include/asm-mips/mach-ip27/topology.h Ralf Baechle 2005-09-15 21 extern int pcibus_to_node(struct pci_bus *); 9dbdfce85c165f include/asm-mips/mach-ip27/topology.h Ralf Baechle 2005-09-15 22 :::::: The code at line 19 was first introduced by commit :::::: d797396f3387c5be8f63fcc8e9be98bb884ea86a MIPS: cpumask_of_node() should handle -1 as a node :::::: TO: Anton Blanchard :::::: CC: Ralf Baechle --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all@lists.01.org --Ll8TiHvqIhrSSeww Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICCjN5F4AAy5jb25maWcAjDxbc9u20u/9FZr0pZ3T9vgWJ/m+8QMIghIqkmAAUJL9gnFt JfXUt5Hltvn3Zxe8ASQgJ9NpQuxiASwWe8NCP/7w44y87p8ervd3N9f3999mX7eP2931fns7 +3J3v/3/WSpmpdAzlnL9GyDnd4+v//734e75Zfb+t7Pfjn7d3ZzMltvd4/Z+Rp8ev9x9fYXe d0+PP/z4A/z3IzQ+PAOh3f/NsNP52a/3SOHXrzc3s5/mlP48+/Tb6W9HgEpFmfG5odRwZQBy 8a1rgg+zYlJxUV58Ojo9Oupxc1LOe9CRQ2JBlCGqMHOhxUDIAfAy5yWbgNZElqYglwkzdclL rjnJ+RVLHURRKi1rqoVUQyuXn81ayOXQktQ8TzUvmGEbTZKcGSWkBrjlytxy+X72st2/Pg+L xxENK1eGyLnJecH1xekJMrEbu6g4UNJM6dndy+zxaY8UBoQFIymTE3gLzQUlecetd+9CzYbU LsPsIowiuXbwU5aROtdmIZQuScEu3v30+PS4/blHUGtSAY1+VupSrXhFgzOuhOIbU3yuWc0C U6ZSKGUKVgh5aYjWhC6G2dWK5TxxRyI1iKlLxjIbNmf28vrHy7eX/fZhYPaclUxyaveukiJx pMEFqYVYhyEsyxjVfMUMyTKQGrUM49EFr3xRSUVBeOm3KV6EkMyCM0kkXVxOiReKI+YAWJAy Bfloe3ogpJgJSVlq9EKCnPByHp5uypJ6ninL1+3j7ezpy4iDXSecFZxBQZdK1EDZpESTKU17 CFYgBCBm+RRsCbAVK7UKAAuhTF0BYdYdHX33sN29hDZ0cWUq6CVSTl2hKAVCODAmKIENOKvz PCR/otRwfo2WhC4bjjmn0Yc17A0QsSO4PRd8vjCSKcsaqfxptSyfLLOjVknGikoDVau/hpPU tq9EXpeayMvweWuwArPs+lMB3Ttm06r+r75++Wu2h+nMrmFqL/vr/cvs+ubm6fVxf/f4dWD/ ikvoXdWGUEtjxC7N6XIEDswiQASFwZdjK1HeKL38w2FUdAFCTlZz/wAkKsVjThkoFOir3bmN YWZ1GuSehjOuNNEqzFvFg1v5HUzs5Q1WzpXIiUYd3W6CpPVMTcVdw4YZgA1LhA+wNnAG9NCm PAzbZ9SEa5rSgWXmOVqcQpQ+pGTAXsXmNMm50j4sI6Wo9cX52bTR5IxkF8fnHilBE1yzq2v8 1fbbvmz+4QjCshdcQd3mxgg6yiQXaMky0OQ80xcnR247MrwgGwd+fDKcCF7qJZi/jI1oHJ+O FVUjdFaXddumbv7c3r6C6zP7sr3ev+62L7a5XWYA2gvBXIq6Uq6AggWk86DQJfmy7RAEN6Bm eocQKp6GhbqFy7Qgh+AZCNYVk4dQFvWc6TwJo1RgzCPHqu2eshWnYRXeYgARPLwHl8lkdngQ sH0hFQ5+jqoIKAh3V2qtTBmeNCxHjmCdVPEUAIN0lkx737BTdFkJED00EeBmelq+VW7gpcX3 HExtpmApoNEpGM7wvkuWk8vA9FCegNXWFZWO32u/SQGEG2PvOIQyNfMr7rl80JRA00lgAADl V4XjJ0DD5sr7zK/EiFh+dRayztSICowBeOhofO3uClmQkno8G6Mp+EeAmjUe4O6moD9A8aWN P2MY+uFlp5A71fF9aOj06Hz8DTqasgoxre/g+J1JlQ0fY01egNPNUa48eYAzhZ6naf2rwLoa cRj8L1dOcDbxnlnjTw5TaLz1xmtxWq2eHH+bsuBuJOE5AwlRLOZzZTW4VUNP+wmnxmFMJVxH UvF5SfLMkVU7QdvQD2gdzCwNsWcBynXoS7gne1yYWo5clSHcSFcc1tEyMHTYgXRCpOR209q2 JeJeFmraYjwHuW+1zMLzirGGx8UqO7B7KCo2UvM5IRX7HFwNTJWlKQvxyB4NPF1m7KjbRhjJ rAqYhfAc74oeH3nH1tq/NllQbXdfnnYP14832xn7e/sI/hABy0jRIwLHd3Bz/GF74lZTT4YP +l/fOWLvghbNcI0n7Em6yuukGdkPBIqKaJPIZVgd5yQJyR3Q8k5jLsK2EfuDIMk560LvIDVA QiOMPpmRcG5F4VN34QsiU3BcwsehzjKIISsC41meErBBPqnaOm2AIjE/ElY5mhWNYlyBf5Rx OtKM4LRlPPecd6sLreHzYk8/VdIfLG4dJCtRxfXNn3ePW8C43960uafBcwLEzksLstcikBzs ahEOmYj8EG7Xi5P3MciHT2Fv7c3pJLQ4+7DZxGDnpxGYJUxFQvKwA1QQCNZTRjF8gZ2I4/xO rq7iUNgxVkamnhMIx8K6JSeKHJhXLkQ5V6I8PXkb5/wsjlOBcMPfXMRZBHpChz3ZlgKNTKJk FFDkkvGIy2f7r+TZcWSHyg344To5OTk6DA7LVFVgvifs8EkCJymifObcgB8WcsRa0AffnbBt Hw/QirBH8eRSM0PlgpdhL73DILJg+Rs0xGEabyKoNYxyCCHnWudM1eGIpaMCVkCosLS0KAmf R4mU3EQmYUVFb04/xQ5zAz+LwvlSCs2XRibvI/tByYrXhRFUM/Az1dg0dkKXF2aTS5MIsAgH MKoDGPZYgS0gmLuJyJkqTWEKcJbHwgaA0gJCzhOpKgh2lkyWzPGLJKtytCfMLDH/5vk2PYht Gt81kl2bmoxxQL9YMz5fOO53n5KEw5ZIHCPFEMpxDmxoJgquwdBCvGisLXM9v2yNOVPH18QE qqqrSkiNaU5MQrvexqWylxKMyPxy4mWjBU7QbStTTvyYY6D5JkIblGfOsHY/sd0AoMN0LDfl ZqMJhImJ5OnciQ66iwHcV+sb+Cbf0s2PgYHAqCaRYj4cBF988Dl3fuYEFEJoCLoy29blKj0X wOGTPD6CP1POejA3XxcQDE3AA9OGKwJithpumzx2np8lsP1jicVhepTTkzdRvoMK7g+6aL0T 1Dq5+2/P22HtlpCXR0ImrwjIBdA4C6t56/lhjGzOlmGPdMA4Pl+GfNsB4RxoOAcAM+Q233YF ClyAEyovjs/cBeKuVJJlTLs3PQjpzl9aFxVK5mRZWdWxJ5QqwJ0+W7bS1XR3QJjTVJioV2Di tSUnJJClUrSe5miOuYDo32ZnTC6nYHVZ0pFoE8XTVqyPpgDckIuP4a0GPeSHqKg2MggHoRVO N14ujnUKHD/FPPCg0Gs/kxcSY8RxTktRRbSHBymlTeP1asA9rS3MSQzbpTfN+BfoegQOVyRX 5iTs6AEkIrgAgbMcCl8BcPLRu4EB8u/DfpgFnR8YINrt+OgklKXyOEYkHu2Fk++Cf8Pk+qCf bZgjOVQStbAi7yjgxaUCI5djih4U89G/X9o/H8+O7J9+YEYxNB3JIS1SvPoGGyUKq0VRlNuk kh8wW10yJMvpMmXV1B6gx720sVvAVsybq+8cAupcXZw0qip5fZk9PaNyfZn9BObkl1lFC8rJ LzMG2vWXmf2fpj87OQCwOankeEnd6QFnVUU9Ev8CpMnIsjlVsOrSSeqHEMjm4vhjGKGL7TtC 34OG5N4P3Pzu5brbdHrS0nRkofv21B4gitOQe98CIaZyjCYvs8KaTdtqd6N6+me7mz1cP15/ 3T5sH/fdXN0guioiKrUqXLmJkurtc4NR9Bh9lQjA+O391jfbPPVVV9dm5mIFIWWaxi4cXLyC lXVk9j0O+Mh9MgHY1k9nlu7u/m6yUYPrGEZwnYdmJW7LZN2WYna3e/jneucP05lKLgsIYhim EEHKguucCzGHFXSogVWyjDfuIx2uE/X26+569qUb+9aO7a4wgtCBJ7MeJoQRQI0VM5Mcg1f1 cr0D73sP/tXrbvvr7fYZCPuC52k/2lyBuApy1CaabJLTYhOWTnM/w2XjZAdY9Tv6FTlJmJ8j x3QJhVFRicO5iZTWWG2AeUismNG8NElbBOPOh8OkUWHAFPQItBz7/k2rZDoI8FLrtsVOwGrh hRDLETAtiK1W4PNa1IEqCzDjzVloKkPGpJUN3doKofFUJJuDVSvTxg7g7bm9RK/GE8S0c2jO Httdbq5JCd52RY31ZfoqrwBSq3wP4A7DtTYRzkzuhWax9qaiAJeGu8Zokwvt5LMpGvPBXWGG ax7dvq5oud2UliJYEmGnQKeFKC74zbKJRgDfrJ3oxKhEDxJz4F2cMcIDeeg8TUYxveuYY5HW OVP2NMCBsRcXB6GBSbINOEmibOqikE2jbbdRMfa2eW6IM0LL8Iz8CMEOMJb2QK/BbwjQdYx+ jIiL8nEquZ2rrEWVinXZ9MvJJdZQfBvtf3XZThiiFzcgyUHcTAI8AhOQOoAmiMTtHrsQbQg6 AqEfLrCmjVOOO59l41XZ2AycT5guqhQ/8ZJZiYrd6Q3ca2sYpVmMqKNEgK3zVOSQPwbv072V UVPbQsXq1z+uX7a3s78a9/V59/Tl7t4rUUKkSVxtG+29sTZn5oN393CAaO+b5vUcy/SE0pRe vPv6n/+8m15evGHx+tSWNgVed7oK397+Kbzeujj2TxHefLYTnxwwz01ssJvgG739cBqvwarL QxidEThEQUnaV5MGhWGYfWCWiscL6RwU76bUaVcLchyhCqCTSEw5woqEfz7W6cfvofX+OOib DzhwqBYX717+vD5+N6GBZ0WCOT00Dl7RrcHZVwp1fl+nYnhhA85wcUoJhw0s9mWRiDyMoiUv Orwl3kJHV6GaorIc3I7a8XiSthSq/1waRRUHTfG5Zm7ZWFdwkqh5sLEp8R21Y2J1Lrm+dPe6 A2JuKXS1aUul2ujXOgpy3HudhC+pGsp44ZyFGGEXh7nfiuR9WHW929/h6Z5pCKPd++wuM4rl A1iq4t3OE/BsywEn5GryTSi7KlTmNQ8UCz4nYYrOhSWR/OCoBaFh8oVKhXqDfJ4WB4mPE8aD oOYgh5s3qKs6wrDB6SegIw/OAOOkAFOxcv38YwjiyJEz7S4OHu29dyYmcT1KT/EZcxyTNnTr eB+acjFUDToCBXhcNJcPWJPUvmsYNmgALy8TP2JuUTp4kn12l+GP18ufKo+HieIrCcsIVYER ROMxcdbQsNv6/tQi2XrxASUOGXeW63DXod1yif27vXndX/8BwTm+YJnZmo+9w68hCTKQgg8/ pGyRFJW88kuFGwAo3PCNGpLBfF3w2ik2tybzsH142n1zkgTTgLjP647d8eaBBBoLVrq5uSEP vAEtXUzceFY0MlliHVsxiVgzorSZu2q9HcmtUe7HysGprHQj45jsPXO5AjJPY7qFz+WIWBOt mq6kqFOd6HySNJVG91cbLcgGQOCXJrXn+ixVKHPVud3W3S54aWlenB19OncN4DQICqWRcgY6 HC8V3GEzCOU0ZgBCPXzPGT6jVac9zHXFsRGmRdRwO3ZVCeG4Q1dJ7UQ1V6eZyN1vFajUavO0 eOMaK3br+tmUSJipTEo8yvZ5VHMHhFWjw9A2x2Dbp2Fsc2W6mkTJFZP2NiRadQ/iaRJW0gUW Z8RSMzZ0wRt9DFdJ7mq5+LHrKJSsfw9Rbvf/PO3+Av8/mCaFRbEQb0BLbjyduQHN4tVn2baU kzDvdcRL22SysHV+kYoVvEQMFfnyZklDlWPVVJdSEnlYBgidt2IkRKdhMwJxW+m+dLLfJl3Q ajQYNuPVQzit2SJIIsNwXBev+CHgXOL1fFFvAtNsMIyuy3KU67ssQfGIJWdhbjcdV5pHoZmo D8GGYcMD4LYYsojDWKQAiDdTQy0b2e1huW4jCtyoSdOqa/bJ12kVF1CLIcn6DQyEwr5gqitc a4ejwz/nvbQFltPj0DpxE099MqWFX7y7ef3j7uadT71I30PYFZTe1bkvpqvzVtbtjXREVAGp KS5XmCdOI6Ezrv780NaeH9zb88Dm+nMoeBUOWi10JLMuSHE9WTW0mXMZ4r0Flyk4P9Zl0JcV m/RuJO3AVFHTVJhtRpsTOQkW0XI/Dldsfm7y9VvjWTSwDpEKKKZt9jkGxFe9mB0eW5cJDjgn NqUGlqqIGlFAbjLM4TCzOgAE3ZFSGtWYika0qYw87NGxJ7lEh4vW8pPICE0dUCzrZ8+98nye tilIbJWT0nw8OjkOF5KmjJYsbKPynIZL4QhWK4XtZ6TYMidVpPIFCw/Dw5/nYl2RcADKGWO4 pvfhlBHyI/5CK6WhEpu0VPg+SODL7YsHZzNg+4jNLQSJiYqVK7XmmoZ10Urha9yIq4VnhZfL uJIvqohlax45hYdcqLj70sw0ZeHFIEZ+ii+vUUkfwiqpCmlA6Zb2yMw+/nSN5MZ/hdc+EkOC lYwUGTs4NCdK8ZAatdYSHx0qCNq8xyzJZ88lwRcev/OQS2ldCkz9NT8T4Puns/32pX2c67Gh Wuo5C4uoPZNSgIEU4LOL0Za0vvKE/Ajg+sXOBpNCkjTGr8iRiWTiSAaMkzHNlZklDQV8ay4Z mBp/M7M5HsnjyU1CD3jcbm9fZvun2R9bWCdG7bcYsc/AlFgEJwXTtmCYYjO6tsYNC+AujoYR 1xxawzo6W/Jgqhx35ZNbY2W/h7yQt32fAu8XHT7zyMtHVi1AiML6rswiP9ugwMjFHtSjL5qF YSFr3Sk0pU0XSHehnRQwvTz39i0jPBerYADSXO21Z6Y7Eun277sbt8TCRfaSbuOP9ncUVLBx WocEQIY598S9Yl9AkJPXTU9E8EJb+CYRa29hKlh3gyAIZosxKZOsw9j4OxH+Gj7XXC7ViMAB 4UGoZE3431QU2ieoUVyl62BZKDIhs1B/PkSPmMzFym8AfTtqwLLJIJ/dZbnsp/C/kNA4KGpR 0T6BD9g3T4/73dM9vtK+7eWnURLXt1t8SAZYWwcNf7Dh+flpt3frad7EbeX05e7r4xoLa3Bo +gT/UFNiB9H6BHR47v262OPt89OdLb9yWMrK1Jasj+WiazdNW/AKxOLB3urmbsebST9aP/7L P3f7mz/D7HXFaN06AJrRMdE4CXfylATDGEkqnnLnh27aBqMV/3ByPG23EQ9693gzf3o0Brdn Aky63hh77+ZdjndECgKY89H7mDFS+7pwMkJd4FWw/9MmHRSTX6HMage3d4GGgofUSbe8fr67 xQR/w8YJ+x2GvP+wmc6HVspsNqG5YI/zcIGu2xnUZ/B1eIsiNxbl1N32yJyH0rK7m1bNz8Q4 c143xQMLlldueY/XDDpFL7wfOlrpospGz06bNnCT6jL42kWTMiX59MdZ7EB9VZ/9ZaWJ69GX 1t0/gc7YDdPP1qYv0x032Yxqir9O4dxnbLQk/WjOmoZe9hcKxvwIgsHk5nniVeEMeN0dtbtR 42U4Hpq9rcZL2vA9Sc9lvGttKn4PIbCVjCQQGgTURi0ZsF8FuA3hUBjRCNbsd8i26i6wu/0j ICy1Ags4+t0oyebeJUrzbfgJnbQpt0KubyumjUXhKaqWovvLNl1vSpMp4qmbIQMFpBZENtKS +fffCMxYSZvk/IhRbjnL9JT1Vd231tdy79okLZROzJyrBGvfXSlxOzjuqAD/kI4CkI77pe/C 47cp8CdaYFOCD5EthuIya1EmvetkE+g9BLQ6HJOLsC9dERl5f9LWJoTKFco6z/EjHAa1SOjg KZXChPAFZuRZ4JUk4dRNR6Uu2GGEXIhIjqdFSGUS5ki/mjfgavkGfBO2HR08tkSa4nsGCHBp ugqPgI/RMXAwTEdyHzaqenMr/sfZsy03buT6K3o6lVRtNrzoQj3kgSIpiWPezKYk2i8sZ+zd ca0zdtnO2cnfH6CbpBpNtJQ6D05GAPrKbjSABtDXZqAW9PMoxfyYJ5o4N6hKAB18macziUUY lRDLKBsqHld/Efg23AB7EiY0MgAqlo0FyiXAYyzVALwvc1YBNWxj2iwHk4E+I+oC/Pnj65SF iKQQZS1ARRV+dnQ83WEzXniLtgPplMisGhhZL78YNBpgxfwZcsjzO2S1nLy7D4um1O7hm3Sb G27pErRqW02ehG+z9j0xdzQY8NysFIca443rYxoRb2/g4JnG/sMqFuvA8ULdBTQVmbd2HN+E eHrEYz+LDWAWCwax2burFQOXLa4dTQTc59HSX2hRJbFwl4H2u8I4+j3NbpGFTQND65Ko8ns9 gp1zYdvfRBGxeOG3mFEC+Hm8TUj0HcjuIJJrQ4i8SkvGmSRwjOea5jZ8GAkHvuHN9aGcwQum Dz02S3ZhpAUH9+A8bJfBajGBr/2oXTKNrP22nfMXOz1FGjddsN5XieDPhJ4sSVzHmbMb0Rj+ OEebletMmJOCWh0WzliQpwSId00fMtBHnvx4+Jil3z8+3//8QyZg+fgGYuLj7PP94fsHtj57 wajsR2AEz2/4T92A2aBdgR3B/6NebcVp/MVkBRyJEuY0ibZJQNQGsb/KJlw//f759DLL02j2 P7P3pxeZVve8zAwSlIfiIRhHZZCL0i0DPsIZTaDD+VVWvf+LUfP+9ePTqOOMjB7eH7l2rfSv b++vwKE/Xt9n4hOGpLtO/BSVIv9ZM7aNHWY6q3nvoPd0Vw8ZIwf/swuzp4lxSXG6ZWOfon1p cIEwizBNGLURjfyh4w1EZ/xBaAL2PtyERdiFKXEm0Y8wYmlMY+1kUD+UOeTl6eEDExE8zeLX r3L5yvzJvz4/PuHfP9/h26HV+dvTy9uvz9//9Tp7/T6DCpT+qx2UAOtaEOqHPAsaGO+ni52g QJCHKjIRo3MtIEXYcFHCiNrFtJ5d3JG8r2eYtfrI5p7b46GoOQLMcZaWJJsawjH5Y7c9r3mY l6/fnt+g2mGp/Pr7n//+1/MPc6Ym5ttR0oajCp3qpxgoJjWo7Va3EWpNfkzPEK2ssewUBNcc 7NlOxsJfmJRyu5UZOLgJZdIJmaWBDy91u5YxpInvKeLCJFp61MYzorLUXbR8jtSRJo9Xc1si o54myuPlnPPRGQiaOt1meja4AbGvGn+5nMK/yJj9gvmsacpUkzaBu/JYuOf6Fjg7JYUIVnOX kwjGHsSR58CEdsQdb4ItktMUK44n3fN1BKdproKzpnpUFq2dZMnLDufpzUFOvNDnYxoGXtTy q6CJgmXkOO7lvawihfpzRaQ9d5zuFBkdAKyL2hRTZCRNzZmcsYAmr2LxmKQtQIjBH2QP+qZl fPvsJxAK/vOP2efD29M/ZlH8C4hCP0+3ryDdiva1gl6KFgA0t6HHsju2Rnotr49kVBP0chIT YUr60AiK0gmycrczsjFLuIjQUwDtXhPJRU5UM4hPxMtRFa3S6YehJNvoGkUq/3vp+8I5JBTB tPOYhSPdwP+sZetKKzvk3TUGZtSalSeZrMBWZ7w3l9y+q+MwmkJBdROnKTjJGdowO4STThob ZVQB9bO2T7C3KTGcsq6NAFPEVtTE2r/JcL6D+u/z5zfAfv8FjrXZdxA9/vdp9owJEf/18FUL x5d1hXv9nJCgvNzgiwRZlaMjQwoqj2N0AAuNhyq/FpAsLdLIhfOGm3hZDV7lcD0QaUb1Mwnc bjlJjuG7OdnZucqtCxJIEnEaJuAx2iHUTOYAQjblTCDuFDIlmi+WBKYbdvReSddGNl/vxPlc Qaw6Wo/umYkwL5xGQ18+xLJzOGo4trYlK9lST4WBvI+GyUGI3oHQij/4lPBYSVriDbDQD3aM KcIwQ9HgxQp9eiDG2DUBwkNFo6sAHtV3bPp7QIkirMRej80HYLNPCzxFjilGNBKXdayNOiwM kE7kt0a7pzqFNYVIvnFQIs2eZiV7UwioPDX3OgAxRTne2sj4P74crjjS2/ukLgmAMSzq0I66 JxGU5TSU35vPNY2og2iMGjFmgCdWt3WkZ9ssvEnujBow5Si7WfAjywtlUgdOnPw8goD1GMMe 2ps0DTNfBLRGuCPCMPWEfnWDsKoXWs5GjUg58POei2hXxYu3vmGWRh2iFwi2B8El40CfxJnr r+ezn7bP708n+PuZeC8MxdM6Qf8pZjoHVFeU4o5o7pfqHk3ISaNyuhvJ0Cf28LKIbf600kTL 271uZSKSC6ERFtcm6QSfWKyQeRihgyr/ISor6tjaMKi7WW4ldxZ3W+iDSKx9R2GwtHhm1anV e7U58P0DeHeUX0W+xGOp+HjlSsXWapHltojU2vTzVWsSvdjOVj3DKSd+/vh8f/79TzQU9U4C oRZ4r5Gf3Wn+ZpHRqNTsMX1AQ5cssKW4rDs/okmXj2XdJLwG3NxV+5KNhtPqC+OwGlxfhnlR IJn7a8vvSr0COFnJXkoa13dtQTFDoSyM5GFFZBABwl0pOFmbFMVso6S/kTVdcG85bcS1QeTh vX7wExQNns7jwHVd6wVfhWuKTZal1wmMo2jSkG9QT9+pw3FZlERJCZvM5o6euVYEv78QY5vE a1/zAJICES0UpCs2QcBmy9MKb+oyjI1FvZnzTuybKEdmZlGJi9aSpta2Opp0VxYWCxNUxu8q lXfcvILXC9pcqc8DjkKapXZTcIZQrQwWKPRXHAgOs/CSA39/KNBvBsbdVbwXgU5yvE6y2VlY jEZTW2j6LMGV5ajJ0ttDavPcHpBGH5lJ2CeZoEpAD+oafieMaH4BjGh+JZ7RV3sGwhPpl8ms mCKwuNLCkNXXtqyQccHGg2r1xZS/q1C9LOXi+PRSGIdB+pB5lgTgsAgwku5yfQmI8Qk18iXe 1b4n9/RpOw2lUtPpFe6OV/qwJy4E+4rP5akXOISnJGWbTwNv0bY8CsR6osQkfEMIdkw6xxKO tuPd5wFu2cBpaysCCEsjiLFVN7f1DBC2MpbXlLa56/BrKd3xvPoL76hynvM8rI8JfXwmP+Y2 xiJudnzPxM3dlcM7h1bCoiQrOc/aeWeJegHcQiocNqw4XURvOZd7vT9pVNPVdiOCYM6fhYha 8AxRoaBF3k3tRtxDrbYLTKM/Zb9pNaYXecGXJc/BANl6c8DyaJjt1dy/IoPIVkWS83s1v6vp fSz8dh3LEtgmYVZcaa4Im76xM1tVIF4JEYEfeFd4DfwTn5Yksq3wLAv42LLhkLS6uizKnGZm 3l7h+gUdU9pBO70BLUcjmCl+TWsI/DXhaWEbBKs1f0lUJN7N9RVVHEEGIMehemXUkMGnBcsb MhqgL68cvSq9Qu9CT2TtfYgvJvCf9y5Bn+NtekXXqpJCYDZBckVbXhUHbrNyR33yb7PQby33 nreZVd6FOtuk6GzoWzYUXu/IAZ0bciJr3kbo+WOLfK7zq8uljmm4wdKZX9knGCXUJEQ0CVx/ bYlbRlRT8puoDtzl+lpjsA5CwXKVGuNYaxYlwhykInodhmerqTcyJRM9iamOKDPQx+GP3s5Z TEwAR5/66Jr+L3Zki8j3V8rI/xv9TLOQsqpo7Tk+d1NLStFbtlSsLVwfUC57b6zXlguyeEQe rV2Lj1qVRq6tKahm7VoKSuT8Gu8WZYSGr5Y32ohGHk+kq02O+c6uT/OhoFyoqu7yxOJKjkvO 4n0dYZxwYTmdUi57td6Ju6KsQPEl2sAp6tpsZ+z8adkm2R8aao+WkCulaAmMrAMxCfMfCEse hSZjw5P0OkuxTzfkHGkifxGwHhVauSM9e+BnZ3+BCLEgh8JyYG8HtGpP6b2RIkdButPCtlBH Av+a3qLcVPXKe8dVZNVZakl5sY1jfoWANGdxYM5VQNnRJunDJ7MF/irBFeXO9Xphefq1qizv j/Lq60Fs+ihzmchfHz+iorDhuSUib0DTsxj1EF0lu1AcbC+xbrq6yWAl8d/tjOelcsSjlBtY znTEw5/N8oXotNrzvORksOkhTr07xZylFcnPtuFcnbMcjl4f4+WcPbYXsAubnEcrzfXUCDpK MxMy2MHIwqAGXdyCquEcIwy2RDdbfi3Wqchpeg2m0rMeyiETEGStc6reWLPgRqGHQ+peSjpC T4KqwxsL/f1drMs6OkqarJOiGD2tEpmuYHZ6xowDP02zM/yMaQ3Q5/Tz20D1OH2D4GS5tFI3 dyLlTzN5t8YE6Z/FahGzp8GRCK/ws6uMWJzeFfntz0+rG1laVAea0QgBXZawO0oht1vMa9gn iCAYTM5hhG0phMqseGN7mUER5SGmLzWJ5CAOH0/vL/gU/Ohr82GMASNMRaIaZ+GYhOHQWrEC GDgoFO1v+CzNZZq731bLgJJ8Ke/YcSdHW5qVAW/wGe2T2TIxqJI3yd3Ew3WAAbfjzwaNoFos LC8rUqKAjy8ziDjN40zS3Gz4ft42rmM5ZwjN6iqN51oMMiNN3OfiqZcBn8VopMxubiwxayPJ rrLYMgiF3A+WNEUjYROFy7nL2xR0omDuXvkUav9cGVse+B5/TUBo/Cs0wAJX/oJ/tfVMFPEy xpmgql3PYsIbaIrk1NgSFQ80mKYJ7Y5XmtuVWbxNxb5/H/kysWjKU3gKeXeJM9WhuLpYmtwD gf0Q7Y3sklPKtrlaGcbvVrnF7KHxqwt4YFaYfc9itJYkMtecxYFGEeB4FD+81BMj7W+PrPN0 PvFbkUAj/lBH0QhwCck3kwq2Dr9wFdLl11qP5AVahfQ5JaVHzae9YEWrHrUYpI79w/ujjPtP fy1ng9/woBSg+fQ8XvkT/2s8JibBIIxWwjOhoKow0Do8EdVdAnvXAiDnFRTVivDyg+W15L6a OjLrIHjFEvU+HYxh7sI8oSMcIF0h4Jhh4NmcASb5wXVuXAazzQPH1X2vuI9wjqhiRCcl8X17 eH/4+olpVMwA3IZm2T/aEtyug65q7jQRSsVAWoHqJY/fvMWSznuY4RM6Ko+G7VHa8r60WfO7 neDl0v6NOttLyTIMv2l4hjYy2oa1HGQyPwx6DmNWDGKJSY62mHtA3Rg45Xr/9P788DJNydLP jfacF0UEHo3rHYHQUlUn+CxuLCOBVESmOeeScotqF5dFWSeKlIuZpS0SgqEhSIyRjkjasLb1 JwfpNGfzH+pURd0dQky6M+ewNb50lCcjCdtQ0oL+FFtEGzK+01WSuvGCgEkB8Pr9F8QDRH5g 6cHGOFz2VYFA4luNojqJxTSqSHDQpkmJUlBnVg2ofWez1i+WLdajRRQVrcU2NFC4y1TY3rnv iS49d9+T9Iz+SxPucKR/g/QaWbptl61F9O5JML79amu1xfSv0HVlP5kAvRVZl1XX2pBUaYEB ctdIcR/du76hJwzRJpThGEshj5o6k0fdZJXIF1r0bHcaXJYCbtmffmcu3AxPWVtMtNJhNJp6 sQ5yGMiKXf+2t6b7IhSDTIxAAAUP0QXK8B3XMBgoQK+DJFIZTpUhasu71Es63b6jACLdGqBT iGlMy53ZfnlK6nKrUe9P/aNmxO41AGUKMhAwjGNjQjbmh+wxYYXvotNKZbbuSYal4StF8FfZ OlFZDlgslAprPo0BDzKxsibaGu5pYGmnheFPquOLw7Fs2Ds0pDLslQg6NhimVJftHYXLTje+ f195czuGpnGaYIk4D2uHin1tmmV3xuMUA0wm92F35lQqG0Xv/lPUB9HQV3yVwQXUjqlpTO8/ TqBUwGCW6aW3F/VP1PB6EKL3UI6agTRsLo1SKqPLny+fz28vTz9gBNil6NvzG9svLGTwmAGa NdHcd5ZmFxFVReF6MedVIErz4yJNnbAJ4XtsnrVRlcW6jH1xXHr5PoEaSoZ0ZKDq6YxTbols V27OeUux3lGWx3QPRuKIKppBJQD/htkdLqVSVJWn7sJfmC0CcOkzwNYE5vFKj1TrYehtTYFp 4JgQQR3JEYbB2JxCKXe19B/xaCXKywRWyMGYxhS0qPViAlz6zgS2XrZmP44pf7PV44BVTE2Z uLP++vh8+mP2OyYwU5M9++kP+Aovf82e/vj96fHx6XH2a0/1C0h9mB7gZ/o9Itz30wUfJyLd FTJDoGlOMNBcRKWFUhe8EZfsPKehoL4npDGp3aonFdLiyyQnG6FNc9sO+nI/XwXGxyilaWuy KKLw2qhEmhvxEAhVt6eTL5X8AMb5HQQboPlVbZWHx4e3T7JF6PSmJV6qHCw5o2QnVYY3kLt2 ezuDrMtN2WwP9/ddKSxpl5GsCUsBcolttE1a3PU5R2RPy89vit/0o9HWnx7SYmUctHEzRy9F ZqElKkktLozftPpFnkmQpV0h2ZjXttooJhxVT2YYYQZ8gPTp36n7g4bgNB+amARj2W0RrIgb G9Bh8g0upa+DuJM/fOC6OgdWc096y5h5qYVYGgpbFVivPNxog3AybELDaQnAffCBpcIzF6CV wQRRdVzB8jQ2H3YdMDm9HtCwoOl1qIIQ+QcRJk9BGPAJ+P+WTbIE6FItelpP1Yae7suNMPTu or7nCAWtMgDe73hms7AJU8t6lh+ztZifEdmUVZSl2y2qfZZut73jnQ4afDw02P1dcZtX3e5W TdW4eKr318/Xr68v/Soi773JBWHcxCH0HBnKp0KTPc+Spdc6k8kw9/aII6+KC/qDCIvK2iv0 JNNjEJ4EvzxjGi598WMVKDcyDVf0lQX4ecFdoWgqpJhwe4T1zXJGFawUPiN6yd5IJYqtXKOS Jj2+swNJv8DH5v8tH/v9fH2fympNBZ17/foftmswIncRBBjwHU2vu/ur/N5XB6+MrS/OaHf6 D4+P8gVKOP5kwx//1I+IaX+07qQF6u7M0HG85DXWHiCfCZQh4OotisX51eyBIq1v6XZVzN9k EVLkEHeCTTEukZO0TRIqL++cs9qhnnT74+HtDSQxebU5EYplufgUVptJB9AgeaV9JkuU6sgm WAo9X7aCJsW9660MqMkiJDDEXA+9wEwfqONGM0qkEvr04w2Wx3SU/bX3ZJw93JLhUptYh5tu r51U2MMvVSjVMd8cdQ+laY17zDZYTCa0qdLIC1xHnyZmGtRi2MZ/Y3o8c4xhnd6XNM5Lwjfx erFy8xOn/ao1Fa4dPTumBGaVv577E2Cw8qezWEeLZhH4tvqb27wNluaEnDL0zTagpzzwXXPu ALhez8kCm87QmN1sMnPGbDSGWxz9dvvJ1wQRAJ0S3eVk2PIJC4n0ONVQTU0c+UP+Le0tAK7z eLBe/OzSeL6eTI9a8a4JjXw/CMz5rVJRitrc1nXozh2SuJ7pi3ICEhtugvtSDJb2CU4L/WnW kzvwP/eX/z73sv9EpDi5w3tJ6F1Rtnr58SUl4c1pnAjFBbzxWidyT+w7PCMFVX3P8MHlvZ8D ZiT6CMXLA0mBCPVI6abDcOyc1K/ggrydO4JxUM7CGLCG4v1UCI3LbVhay9LSsufbWg4czv2Z FPZda7f9q13yA1vhhcNta52CaPUU4fKIIHHm1pEm7orVA+mXHqUwNJx34ZEKjhKIbyBzErHC ikNVZZqCoUPNVEgEtz/l+p1rFYcKT/hYLxyEcYTvsMF65i6LFVfuUHon21eBJ5XKxwkklKmr b6ULgioPlnqWZpS1Ma8Snm7OUk/92BfBL7V0eHhgg1vqCYjGNWDEhvdIGrpmww8poQy8Ufvm 1lu1ul5oIKi520Tu41s7Mm66A3xgmHnTKXUcNBzyrAeNTqBLAcOYAe4uuNk14GFbec55NWhQ ENi2hyTrduFhl0wrgvPLXSlRYNLrHsdzb0LksUlChkHYV1sqKmxhioBag7WeonxAoBAkRePJ 8kAMddY0CEzt4dyWXD8XSmaNv1y4fNnWnS9WqwuFUUJYLdfMWOQg16spAhbW3F20XIMSxcZS 6RTewlLrSrfpa4hFsHamCJFv/PlqumjkWsKbFm89d7mVM/i/XFjxdbNwfGZS6mY9X2idNBip /NkdyVteEtQbGZXWqBwoVHZCxjGmT1Ufr3yXnDAaZu7yySIICbfazgS56+g5dCliYUMsbYg1 31NAsYF6GsXam3OZ+uNm1boWhO86fHMNDNvm7aDT8LdshGZp82nQaFbcSqcU3EwKn32bQESr JftJRJXQzH8jpmmrS7MbiyX3bAI+ccA1pNg8HvhTXLq4AXV+M0VsVy4Idluue4gKvK3lbYSR aOGvFmza054ij1x/Ffh9v6YVNCBrHxo84C42tMsWbiA4QV6j8ByRT8e4A9kiZMHeFLpP90vX Z6Y93eRhknNDAExlSa01koCOJFnJhf6nTbCaNvslmjO9hLO4dj1udciUoLuE66fiqbx/PqFh jwCNAs4PZv0hwnOZHSMRHjOK/+Psypocx5HzX9GTwxuxG0OR4iE75oEiKYpTvJakrn5R1FSp uytcXWrXsfb8e2cCPHAkWB1+6OhSfgkQNzKBRCYDVqYUHrlKcGhu2uC2ye+CtcQIeZY33wSM aUk9upA4vEAvNwJrohOZfu9TTYBBOMjZzABnbQCoMcEAKpwKA8zFWpPtXES1Y9lz7dxFnkvu cEVSbu3lpog+HfKwJki3KUMfF6IhwESl1l2gOuQ4KfxPRnrh+58x0Lr2xBDMThRQoqjyBi5d 3uCz4qzn90ZgoM3DR5gsztq1nZUBWFHTnAHEpK2jwHc8oosQWMly9QCVXcTPR7LWdKU/skYd zDnqGEHk8KktGwBQI4kpg8DaImpf1lHhU0OTnQGvpcWlLrR7YyVRu+uW84MROAxPdQQOh7Yc Ejiiufmq2aeMgkORLH2HWB8S2LtXFjFqALCXBsA72ha5+KKDhJVfzBaxZ1kTfcWxjbMmB1Ib 7VzPnp9BjMfx5r7fda1P7W1tUcDaSomz0dIO4mBJbAZh3PqBbQJ8SlSE1guozSArQ9siZXRE yFNvgcGxqTy7yCdX725XRIZngyNLUYPOMLc1IAO5LDNkflkFlhUZyEFksMkhdshCL/BoO6qR p1sqkdY1hsB2yOyPgeP7zrxAjDzBknKQI3Ksl7HeIwywSVWBQXNrH2MgBiinX7Yhu0g1ZJ37 gWt4sSdzeQbXxwIXTMIdbWUkMyU7yh/iyKPcFrE9Isw1Avqe7TJ8cNfqWFIkoPWX+MKnt23m 3r8vRfu7pTIPRwHTWWcPoDduFlEZXbjTjTSwxgk3UUsrjMeR1JdjZngrSKXYhlnDQ6JSVsRE AhYWl3lYp8otcvZH1BgzPTTts0O6Xy6KVEu99RFGK6FLbypEwPMV+KTgPXecHLZN8k/zCEF3 kmGXiec84tm4lk43jx8oyvOUkVxWx/BcyS/9R5A/D2Bm0X1obmptGNnxse0Y3Nsi8tMsEthx 1PH+/eH74+3bon69vj/9uN4+3hfp7V/X15eb6kahz6dukv4z2NDmDE0P5dtq24ltNRm88WOI AaK6DDg8m2joSXEgsS+Wt6a6h19W6EDvyYYq5Jcsa/C2hyrlyMQ42nquKr3JG/Hx+EhVAjQx 50SVFXpjT5DDPCv8pbW8HGPRStZzLCtpNwq1SGsY0Jw2XWDAeAptloFupxRl//jz/u36OHU3 RuCTBgy+f41mWgDy5eZ7wy3ypzkCz2yOLTrRqdo220jv+sR4d8jSxlnFQvUJvNNeIzAYPjEG YRZofcTtIqtb5WPbPGx3JHNy6rKt+u0eUz0Z9BybCOOcEcVGQOslZuD/9ePlAW2ohgez2sFz sY2V9QkpeFgpmsXj43bByGQaJcgbdnbgW5otrcAC5XPXlqgXMepghqJ8m10bUTQ1biUiBT4Z oYxRWZHZHddJqYd6r4XZ9KuPZAAq0IkPM4S62h5Az6aSeJQ01oP89kxOkpeUwMxqHi2dk9qm PVGvyABIN4qg+V3qsM0iSeZGKrDVObXj5DWAolEMEpTnEfi9P8LyyyUqKpODXOS5Swr6Iwiy CzpLaxBONrW7fqvHxwi/ENOoyh3YSA1WOjVYW74++IBMhtAd0TWdaE1d0zC085y1WtJhfxOz Sr6wh0GG+BqQ6pDVGFVLeX8uMODeoRaujrYujFHTIJ2Ml0SicmvGaNwATM2+TaIZX8TIkK18 7/QJT+Fa9KEHQ+/OAfS2adaoLh3Dzcm1ZhcvkJwiWcRHapeB2u047unStZHi2kdgU43mOA0v hWUaZJcXem+EeUHGhuvq1lta8m0s0qBhaBWcgz5928AKwBgC2uXNxEAe8Q8V0GwBx3SB98mX 14ZyCwy2MRC6xESHP+5ZYEGRVfTumK8sx9j/vU0isUMe86XtOwSQF46rzgbV3pFNz1MgXimz XW6019SJ1BY0QKbHqmxvb1d+TlojsloU7tLS9imkzvQHs76kj8xGmD6q6eEV6V2yB52lNoR6 SZ32QyMwKG9iBsS15pNyU1JFeB+fronPJU3S1CSNp6g0ymHNRqLxgc7Esc1OCQyNKu9C0TBm YsBX0Xvm3KBs90Vi+NAYQm3koxWVMQHsm6kyRymefkOmIc/yKSyMuiAQz0AFKHaddUBXISzh P8oFp8AyCKlUciYwziYXhFIigzkbaaFHB/mS6m0mOn7S8FxQ/Owbtmz5oGAG/0nToApL13FJ WXViko1ZJ3rW5mvHIrsPIM/2lyGFwSroiYK3gMCOKB5iK4hNI4FvG3ILfJcsnbrLCgjzyrum WxRBz6e3wYmLMrEysLmGPVXiCrwV7bZN4fJIj1cSz5qehgxyydYl5FQJZFLy/Hd75ULeDWXc F281ZShY0+UCUdg0vxGzPymUIklPSL3df8FIKHTW9SEILIP3FIWLvMdVeNbkisnc2suv1SaQ EJ4FkEnbs99t89TtI79oGAhB7hLajs58kCtns0cmW7qxlTHXsg1ln5VCFbYlGeRMYbJX5Kog SHoaposYEgbCAHVe1+stQoaR7iwPn+uaglA1pA89fEEcVTF3Jd0TMwytMQISHQaGge6R9D8O Yj5jafCQvirPA0QUDDnC8lyRueIBf23ItwCZ424Tz2d9KkzJM241OZO2iYpCLxVryEMfh1Ps kBD0kiYpKtJ7VP9BqgxNSEXF4RXci0eKWKQkbsLOkduoa5Kw+BLWEjVLq6bO9ynPQfpoug/J IG2AdR3wZ3IfZEWqFTs1lxrB3VHNAccZkQuMGnMuOHC0fNiIIHJiY4icEEOBI0oqGUFP6uHh vbA6lNmBrGEQZ/IgOW2q0yU+CJeozGM2eyDBfd1MR6c/ro9P94uH2yvhoZmnisIC3XFNiYXT c8ShRzEub3cYWGiliPHGWZp1INj/EnMT4huzz/nauKG45EpgJE5TDRAkV64ersquQXe6Qisf sjhhHvvF3DjxsMpBP99v0LdWSKrpE5+aIUsrHV5yehgfxjcvyue4MlVkJXN9XqYJdZLC8i2S woZ/F8lTNUO2x7JisRT7R7k4JAjPG7w50E/+552CDwjnuOC749PcIdCAkXEsuc4ncLH3N1PM ArlhM8lwXSBi79MACIXYVu3v3kqFoTh6GlytpZUGx9VcHfnzRz7rro+Looh+w2uZwfmJcH8R nesGow1ss6aQnUSwj2/2W1vZuSc6Mc4YHRq0qtWGYkhc8EGfpWR+BbtxJoduV6fyKLp/eXh6 fr5//Wvyv/P+8QL//x1a4OXthn882Q/w6+fT3xdfX28v79eXx7e/qYsQzqfmwNwztUmeRJ0+ EXA9lQ9AxkfXycvD7ZF99PE6/NV/nr3TvzF/Ld+vzz/hP/QBNPpICD8en25Cqp+vt4fr25jw x9P/KnOEl6U7hPuYvN3q8Tj0V7J4OgLrgAzd1OMJuux2tdZndNHimZOLtnZWsgrAgah1HIOl 0cDgOitq25rg3LFDrRz5wbGtMItsZ6N/dR+HS2dFSbwcB8lUMlGcqKKtbz/eattvi/qk0pnM t+m2F46xvmniduxDvbPaMPQUZ/OM6fD0eL2J6dQl2V/K6gsHNl1A2kePqOuRiTxag+b4XWst beqtU9/PeeAdfM/z9Zyhdr5yzkngWjN2h9pdrmiySwwoAHzLog+Ceo6jHVj0056BYb22KJ1P gD2tQEBdEuU51CfHlsMMCJ2Kc/demtrksPCXBi2unwQn21Umq/CN68tszjO9yfBAmwdsxPna HOdkV28CBJyVuUEZLt4M9uS7ICDGw64NbLaS8Prc/7i+3veLqOCJWilCdbC9FX3IMDG45tmC cKDVmFG15qkOvYG/9gnXW5tXsurgS6duI9VbER/2Pb0DMAeKd+2tqIHZeh55U9HP5G5dKO8z RqBbLs1rJ+AHS7RmmMhLndw2lmPVkaMVu/nDXZWjf4Ic+le3phiGjxvY44DYPt+/fTcPhDCu l55rHot4n+RphcHz1ZU3fIJPq6cfsAf/6/rj+vI+btXyJlPH0PDOUtubOMCW7Glv/43n+nCD bGFjx2sPMlfcJHzX3rVDatA6FkyUkQWG4unt4QoSz8v1hh4fZZFCXfB2re8Yogb0vefaPnkZ 2Ys8/W2Z4Fjl/yHqjF44tNIKXjH0FFzAQyyc5FXBF46G8gb4eHu//Xh6uy7iw2axHQS+ofm6 2+35Dd0jwUi6Pt9+Ll6u/zOJheIHTBkxnvT1/uf3pwfSwdQhBZ21oT3qxY3BAzwK8DUK9Npi H0IScdj3xRPJnC+qF//OxcnoVg9i5N/QE93Xp28fr/d45Sbl8EsJ+OR7heV48efH16/oz04N C7DdXKICY9AI6gHQyqrLtmeRJC46g6ZxAfGbMq2ADGLxLSX8Zlach6QVzwqEIsC/bZbnDRfe ZSCq6jN8LNSArAjTZJNncpL23NJ5IUDmhQCdFyhnSZaWl6QEPaNUKtTtJvrUNIBkaQ+QwwU4 4DNdnhBMSi0kFQwbNdkmTQMavXhRhcwwbCWXXliKMLpj7i0lagFqaO/OVs66y3JW/Y770NZH zvfBF6W24mNvZE2zlzOsC1v9Dd2yrS7oka0qS62nz5uksaUje5GqDaiwzXJoPTmTrGi7TukO MgiP0HbLWDEiw+E/hENWSaoNwgSYbrYnDrFHxAxA96eOPbE6viwkYAcydz80exPGip/tkWg0 HJk4xuJ9wjdT0bA7L+1AKQAn0tlLXHL3YmQRtaWQOFig5xEd5WFgM7QRYvTUaB3la62Dg84w asKDZJ4wkuQDuokcRpHoxxyBrFV/XxxL7W9GJcOn4sBKKli2MvmDd2c5DC6QnHhLqyqAHaoq rirqVQ+CoHnajrxQNCBdKNMubO6Uua62ZQRbnhLPVahj0Ub77UlJso+pE22cFZsCurdbuVpj zfi3wMpwwxF5PRQiuAvUDVRbWRJ6Gju7TJW1aMD0xaHNipoMgMCqDYqeKKKROzVbiTf3D//1 /PTt+/vi3xY48E1hEwG7RHnYtv1d0FRKRPLVFrTwld3JD8wYVLR24KRbi35syVi6g+Na/6TD BiIDrMdr26bm3YA64iEUEru4sleFTDukqb1y7HCllnHGqzTCYdE63nqbiscAfdVca3m31Su9 OwWOS2naCFZd4di2K2wC47JhaOIJ19xbTpBqGzchuiGNjBkMaSamugjWq+XlSL+TmfjUF2IT Qpi3S2AQkNYXCo9vyGCwTJ7NgVnNrA0lYNZOs8llGx4h2wPUy89rCtvE3tLyyfZoolNUlhTU G8mJ0/eTSTpqZ2mIT+/EuVml0oqNv9EbBUYtgMWJGqATB2Qnu2EUsCjfdzZ5nsCYMBJ9zyLW Q9OPhkRttS/lN5alNNK442DQCLR1aZdJ6eDn5F6sa5IyNUSFBkb6Qne/k1wNQX7TnOMq68/r A4bDweJoEivyh6suEY34GS2K9iyCoEpu9ie1/Ix42VJPMRlc1+IbnJEk3sYyYivKzYyyx0DE WnMl+V1G6Qoc7Kr6IgWgQWqWbpJSI0c70CHOKi2LpFttRqyaNlTLG1X7NFRoRRiFea6mZncz Cg1q1mU4cTaWK56KMZBfY8lE6P60Khv+TFLQuAeq0gFSkyVFa+6fJBf1OU5JpODXnFYphC93 yVkdeMUma7TxnW7JnQqhXSXHmea/eUfJeXRe4FBWIAhCQYixendWRt0+grku7kVIPIY5jBiZ dsiSY1uVKmt6boY3oFLZMnzAZyha1iUq+x/hpqFflyPaHbNyR6rCvKZlC2ppVyk9lkeKYz1G TGKVUFYHpRuxSfrpL5VjoOOPmjK9HRnEWYXEZl9s8qQOY1vpRwTT9cqihyKix12S5K02T5lk z2KmqqUsoPcaQ+xZjp/ZoztDczJjnVRtzCKLmgqfpmpfqzB0VkL5wGTwPu8yYiCWYgB0Tmiy VM28auhAhYjVoN3DWpVXjdCjApGYMKDqFxiO0pRj0oX5WfTWzaiw9sF+reXFySCpGxt6YJnT bUW+ma8YIpuLLJG6FoNAjMYnpfSEnwFNVoRKLRvUdGJtLDVVFIWmcsPyLy9UjFa0e/FZOiNK mwe7ZdU7h3lzy5XAnSLeJaGy/gIJpgbs64lSQyhCnctxuFhtCsqkhi1jGBI4bMUdaSRpU68t wqb7ozr3nxiqJVC1JLCtKWsMLLCt4r6OkXewlNEHyRzGWGDGmCdsRUeZ6FK3jvy9vb39ksiq P1/qYVczfu6YZQbLQERPGUwnNUP8CDaBIc2Xcwyikbq6cO8Ul91+Q9IjqDNaA7NfijiU93El hvsGQrAb3XCTwifaJBECaE0eXffMg/GW4MRbzHsK7UV9kIUMy6RQYxrvGOdXzFUoQ7WLMvmc eGoWwchKJmIAk0phhIXl0q+8AnWfYzAaeQLxHMrS9PYacdCIYHMM28suiqUc5ez5u3Yp57As YWWOEgycPliqasqDfEGGrX77iTcZb3JvDg468BQ7a5VGiM9liG+cmdWbVsGqSy/HHSxreUa+ bx94Njlb09tOHrN9i7asSdEvKj7J1/qBWSLtYb0rY+435XdbhHkfTYMWI7+RMYfEjvH8k2X1 zS7V6IQjZWc4DUWG5DOG6rS3l9auVpkEFvQIvPROWrdfttBYkJgqGPrIW9nLmVyrvmRylgOV GkUj1rZUOGE5uRbcg4386ZtSzvulY88Utc2D5VIv60iGFqpkqAlCz3PXPvWx+RogyuwVC8Hw EkdK71Eker5/e6NsMNnYiyi1g03KhgVBlUt5jJX26YpRhy5hZ/iPBatmV4HImCwerz/xHnVx e1m0UZst/vx4X2zyOxYqto0XP+7/Gu5q75/fbos/r4uX6/Xx+vifC4xoI+a0uz7/XHy9vS5+ oHXx08vXmzzeez6ltTlR9fAuQqg7c5lFapUxZdiF29DU8APXFiQDJc6qCGdtbJPvN0Um+Dvs 6DK2cdxYazMmvuYSsT/2Rd3uKkOuYR7u45DGqjJRRHQRvQsbOVyYCA7WpdBwZARvkTcpod4b T4pgzuZW2IrDOPtx/+3p5Zseo56tGnEkPbFkNNRN9F7NatOjZbZixqV8pTMSL2kYp2R0gYkF 3Z8ohWBTM24ibZ1jgOIuReeY/SjjiPFZa8NjdXMvM8/37zBHfizS54/rIr//6/o6mpKw9aAI Yf48XiU7bDbVswr6PKd0NvahY+TIlUMKEwrUyjHA4AtmxHnVyKRjnbS9Xq4c3/QGg2d1UeOl CGtK6OxxW6uQPXQit/q4f/x2ff8t/rh//gdstFfWcIvX639/PL1euazBWQZxDA1NYAG7ssBd j0SJbJQ/shq0Ufnthc5HNoKWmRjKb0qqGvaPyAFdW7SzWXYNxpYrsrZNUEfbatLQ9AlWlyrO qPtONit2GUawU9aXgaoXfkT2sTZhWHgBTzeNxD5gLW/Y2vRnLmMyWXDUDnyZGFRknjJIgCQ6 dmfbZ7zv9idlnUwObaJ1AjSXa9Hmi1xKTKvOEO+D4aooMSy00dmPPEfFlFA4rBnj4XRIlMe6 OFMON1m18Ow5hoZHYVSuXAaS6uaQahsA6ZaGSQhNCHL8Ids06jt/VqrqGDbQNqZ6o2Cjpkl2 bdJxkWebnbq9cU3PWjxl2R7VDM6QhLpXYpl/Ye1ystVEINjj/7a7PBklsRYUCfjDcS1tKxmw lWcwXGaNmJV3F2hz0BTUEI/yvrQLq/ZOPmQbB3f9/a+3pwfQedkOQI/ueif0a1nVXDWIkuwg dzeLOXWQolZ34e5QyTrcSGJL6GVzHlQuaio7qisaQWk2FF0qEbl5cOpMBEmVCW2+DI7wdVbT PtJzYfvgJcNR1tt6dJB2yn0BKvR2i6ZUttBb19enn9+vr1DpSamTO2tQmoi1MW2QaqzGoFQY GTDMqm+aCsWh/6RCc1Stpqy1p72MF79NX0MjvIkjtfDiElTErut4RJ1BOLVtn7JeHtFAkQjT 6m6vrOVyOGwuTxXFeVS/xFFJdpG0OmcbUADqqs06dYHFGGctrZ9sL9tWpUgXlWyqsz/1vXig E9sczadoejRTtTHEV5C4yl/JKvlFJnyPpQTvonmbEnakX8gyMWm0I4vSJXQ+20sOQ9s09QW2 mb5h/fl5kbeX/cE8iQW2Xif/FdZupvnxTNZ8/mO4XGfzaLbr+YK3NffRdl9GeDk4wyJ2zWer c4exhswDJ/1saqSft2eMTgv6iT2TD8ytSzGzm/BrL9Muoh43c2K8SWnXCBw+JpsopPuiO9eJ aVlFteLSHrNO1O4L2VEe/Pw/1p5kt3Fkyft8hdGnbmBqirvIwztQJCWxzM0kJct1Edy2qkpo 2/JYMl7V+/rJyOSSkYyUu4EBDNuMiNy3yMhYdnM1LPGoxQGW1OtQZ7HL0qqsi7iBcotUYZT6 oQgTclGkNgBq4pV8cRhAOwjdGkWMHS5lPeURX6nJ6jQqV127p9RZu8gxIswizLvydqaLHORY 054GbK9dqKbSuFtjmGg+w+ZnANxwq3T2n7a7Y0rjBRBfvjqKRjDPcD23aXdiOTCoK6VL1qxP Uo9Nm0lGnewMppWuQTcrLJPlvVY2q3TO74DaJuUt9eo3jtA2KRQHg0kOvsmpVPCAADL4sVlc Is+V8uQsRuhO9xzOSeY1XCoKuHutboETL5b82U4YOSWE/hBPNnW0ycFcwc+ggBYFtCc15nZN NJPF8Vq/PxwrYjBbk1w7uO5th9OokfhEdcB9I33BGfCkq8kO67rcKxJ+mBpwOBjBCNa2D7De tHlZ5btk5IMeixxhjT2C/UfK8Is9BTTIuReH9j742rBdT2ei0O/Ud+QFHc8OH5mW0xg+pQzO KUjfe2KKx4yD1g7SJHS2mGeqxyrx7hWF4L9IhWaRG5hbtUMmkRSHee/+nNRxcPE6OWnGNchf DP58Orz89bv5B2fl6+X8qlN4fYfoytT78NXv48P7H7JQSfQN3NHpc1fUK9uyjtXjwdOgHiu8 mnYLgGxZ+3b4/n26vXQPjOou1787ggf6WoMr2V4mngmUunR4xnXTnACiWiWMJZgnIc0WINLL piOINKrWHxOFjKncpC0lvkZ0WNsXt7F7Ih6fWg+vZ5Dknq7OosPHKVPsz98OT2ewYOTmc1e/ w7ic79++789/0MPChWBNigwhcDu5YxztEFRhkdIMACJjd984ofwvKpmBKm2hLUznbkJwWOk8 zVJufTOkTtnvgh3pBcUK1W20Q8ZmAJgcvgBcRYw1uKO5aMAzXFuu6G4AvF74A9hik+OLofDm 0LL8XthYfrtHT0uQgl0NFiIKBK48h1d1GakN4Ah6AHj96k0vzhwUQqB8Qnzdk1/QgUckxlat C/dwMp+7X5OGdH03kCTl1wC3T8C3vsyr9PC4MW3kLhHBdxGb4ev6jqoMUMwo3XKJwJtZVFJt TOCeAKI9BMh734hQ3DvKCMWDY4eqGzeyZxo3pB1N2mSmZVyqkqCQAxH2mC2Du1Mwj3cmG08h hOHZVF05zvZos29ERHrRRxQ+UXbumK1P9SuH46gYPW5+Y1vXUzDlS3rocuG+8WIrGsb9Bgat E9zTLHLbtDV+KPui2LzWeGqWSFxf4yJWyoX0Yt8TJLltWMS8qzcM7lNw3zeIAWhitqz8fseA qyPeMYhxCTTjiHw2y8uWmKMcTkxSgDvkTOQYjXdXiYR0QICWsekRvRPMDJMAbx3XpyfU1qP9 1KBF7vhUWrGZXF7/bMFYJu1Ntc8lqlCYsFqEiNixQ7Lzuj2MKLhSmJ4Fk85jtzhydxQYbQRQ XGV6x4NJGUTW5HQc3tw/OKaivKTkpNLAWz4xrAzumsS4AtzVzTLPhyBreYq1FSjKGekdaiSw HINaEn2sk2mWumAkw2Jtr81ZG9KzyvFbn4qIKBPYxJIDuEuc0HmTe5ZDrN35jeMbZAPqyo3I W29PAPPAoFKKq+pkfhxfPgGD/sHsWLTsP+PicpxEZukRgwhLTdC7Kh6MyBrhPujiIpJUiOFC NGYbQ1Cc3hvqBKaKIiXMpkfxeoCCzcRlBnjAS4olcpkBsMEx/SosiiSTSgaxWh2yEV7GWNEK kkGPkF6UwQFoHkc7kWZgzdskg6f/0EMGstyb8grgu3yZU9o6I4VU7VvIferHt4MTufQpkACW ARM1XwAAVSL3ZfR02L+cpb4Mm7si2rVb3Ej20fHVky7f1WEaS1nO1wtJR3iUaUO28CJMSc1F MmUcGIRNpWwBBStXlu7lUCltTB2ut51qBVWafEVlH7soXWBABTN5mRRpfYMRMbi1pBCh7JUS AE1SR6VsEMDzBUt11RIZEOxWia4XnLheN5r3DobNFzq3VDXpVbNusSRRQEDEs57sOfnh4e14 On47X61+ve7fPm2uvr/vT2fknaf3G/QB6Vjgsk7u5qSNQtOGS+HjZCBmCyOJadl13Wa+GVi0 zIIh2UWYRvkzU5uqcZWrhrg9sjv66dxpRg4bnnAP9PCwf9q/HZ/32PNnyKad6VlYN6UDqp7V esdBOCuR/cv90/E7d6x0+H443z+BHISVf1b2/zCe+SZ15DGECDwsk1q+pgaXSpPr06P/PHx6 PLztRdgRVLOhsHZmy2xmB1CjofTgiS8UXLOPyu183L3ePzCyl4f93+o406W2eIaYOcJ6u/dc 9WG+YufjFWN/BLr59XL+sT8dUKcEvq2MCYM49Namy07oge/P/z6+/cX759d/9m//fZU+v+4f eR0jTYPdwLbJov5mZt28P7N1wFLu377/uuJTFlZHGsnNTGa+68hjzwHYD0sP7CfEsBh0+QtZ 0v50fAKps26Ah9wtxhB3L31d1h+lHQyDiFU/9qPwEuJOVSWb1/39X++vkOUJlFlPr/v9ww/k l42mkI5IsREKH7qTAsKXx7fj4RH5HOtAkpSxTXaMpZlZDiXQ6t9LhfxxHIxls1tUyxA8gqFT qEibu6apQlqaDq5nFqQPb6SpDV+7SPG9zYEFqXzNUdxh3iSBNtYWIJU30gF53cxozrhKHXvw Lri8P/21P1Ou4RRMn3qRJlnMtdJk/9zXVdR5zBrLFyB9+LiegH617rFo9fTAeGolcMuVKuYh bYW/vqUekpPtImyRppSAxGUBJi9r9nuzkG0nOnTaRCG2s+8QYGEFCs6M5yOrIciuk5px5ReE yn1uoCHIWHVtzfunBXDpXYHCkWPPaIq0ZHeBuknaf/32fv7m/yax69mSDLaXVo3kFVy9wUga COoaq9IK2/besgEuVJ0PsUc/HR/+umqO728oGup4BFF4afqHaTYv6YfMtMzzNeXavdtPn4/n PXjJJm+XPEYFiOHJc4NILDJ9fT59J26IFRtCdPMFANzNKMVkgZT41r5QlLm0d4InlNu0nlo1 NKz6vze/Tuf981X5chX9OLz+AXvvw+Hb4UHSixGb7DPjNxi4OUbUQFBokQ4280dtsilWOJF6 O94/PhyfdelIvGAAttXnxdt+f3q4ZyfJzfEtvdFl8hGpeIr7n3yry2CC48ib9/snVjVt3Un8 wPKXoNrT773bw9Ph5aeSUUfZxb3eRGt5FlAphmP2b433cAjkfdT14QorPlHI8f5S2sVn59Hi uR+xXVnESR4WkkapTFQlNewboJ2vIQB7hCbc4Lu+RDBEzaNu/nJGYdOkm0RtRDxd1WOLd8km KagjONm20fhMm/w8M5ZlGjxd2qaBnEeg/xKSCkIdxaIJA8c38IHBMRrVjg47jZU7ImzbdYkM L4QIkyl8LGofUWo0SUxQtUXnVx3D69YPZnZIZNnkrkvqe3T43hJA4pvY7it7BUplJPvoNN0p GDv/STAoU40xGiX8NfcDKkQwErh7rmYnOVWW+FfmGqQ0E1JeagMrYiCxZJLmdnTfNp5eAtEl oCRyqJZ8PvfT9qMrOnrV6IF0wLsw3ma242r5zx5Pc3AcK8cQ7AA4HnYPRHzePA9N+XGQfVuK N7g8YhNROLMk6xaHFinLjENbfhhgnGQdyyawHIB1JSXZLi9vZ1PaCNfbJkbu4jhAx91yHOZt t9GXa9Mw5XC1kW3JGnx5Hs4cFKhWACbxaDuwTh80nHkeztZ3UBD2HBTPTDWgroCqALm+28gx DLQtMZBnubQvR8ZF24bGcK1pr33bpJ/KADcP3f83sdIwE9nhtszBgW7WhniVzExS6gjCJQ+J e2ZWoCwwBqFe8xnCmeGknjH53qULiBzLrqJhliWZkvNIoFuB7CzwlEQzz9/RT9CAJNcMIAIT 1W0mvwWDOM6foe/AwvjACZR6BAHNuYtosTs6jDcgfR+Q0ooNA9gKlhWCrlJ2xklLZbWdyes+ LULwkxpiG6C0ACF3pClcKIvgwrM2shw5hCoHyGEfOECJPM/OdYOMrAEY05T1TQTExwAb62ww UOBpQs/mUWUr0XcRzrHI6OwME+D4DnlS7L6aov1EiiJcz3z5wZ+/8mxCYeagRPYbIm7uUjq3 kWCjDNGIYQhKT6LlGMM3pVHqYbLmcw9zGsMyVbBpmbY/ARp+o0To7qn9xiBVjzu8ZzaebN/L wSwv01VhswAHB2HQNosc16EeV7tLwrbvon8q1+bhCK4SJWTBFNldEV+f2FViIl/1bTUk0HBp HBKIFD/2z9wCU7ynyjtvm4WMRVpN3C7N88TDfAB8q7wChykS9ihqfNJDaxre4GONXbhnhqwg A5VI6xSY12Vlo9FoqsYm41x89YMtEp6rbRWPyYfH/jEZpK0RuybyYApTPkMwj1hVXUGPDOfo wonMX+YZ86bLouk6UYgKmqpPp9aJc6JNNaQSlVJ435FAuCga76STjFGyVqkMjUPsooLrhrJ7 iRCT/QyBk/gU1r2BuIZHn+auiKQrk9qaE9F1LHQiuo7jKd8B+nYDC/STZTP5DqoAbAVgoDcF 17OcWp3t7Iwx6XjUcPp4toVz8BWeACBaFsL1Ak99w3BRnG/+7eNvz1S+HaVIxlDQnIatPiL6 vmrW3R/8jeOQbFnuWTZ+cWInpGvSOmTsqHNmpMYdYAILHxlxyI4MC2wfVLDrztB5KaAzm9yF OqSH3a5fnMHD0+zj+/NzH6hQntd8aQjpDLc3JjflSQb/JeJr7P/3ff/y8Gt4cPsPWCvEcfO5 yrJeSCjEsUt4pLo/H98+x4fT+e3w5/sQEmYYskCxm1EkuposhGLYj/vT/lPGyPaPV9nx+Hr1 O6vCH1ffhiqepCrK3PuC8XuGPOsYoBuSrvR/mvfoDv9i96Dd5/uvt+Pp4fi6vzoNx5xy3TbU 92iENckTpscpK5ff3smFz+7VdeO46PBcmt7kWz1MOUzZXhbbsLEYV2pRrJp0LC3v6nInm/Dn 1do25Dp0AHK/F6nDbaqeLh0KdBwvoFmdJ+h2aVuGQS2x6TCJE3p//3T+IXEoPfTtfFXfn/dX +fHlcMbMyyJxHJl/EABH2X5sw6RNIwUK7QNkeRJSrqKo4Pvz4fFw/iXNub4yuWWb6EYer1py S1oBg2tMvIsP/jLzNFYMYUa6trEseo9etWsNpkkZ26URDDCURV/vJy0V2yLbT85ga/W8vz+9 v4mwa++s5ybyLyXMaAf0Li1Ih+QA5nlqeopIKu3Wk5Yc8zLX+dZDV9INrA+Prw8k9JQRaOFI CIpLyprci5utDk6uwh53Ib9dauOAbvrelzOA3sT2OjJ0FLUKezQevmA6neMvbEoiCV6Y2RDL VQJUcRPY8h2aQwK0963Mmat8yxeNKLct0zcxQGaj2LctizjYt+fJwrFlZYUVm8WhYUjS5YHf bTIrMORrPcbg2EUcZpI8iiyblBU9JXhVl9IU+NKE7HIrK/dWtaFYv/Z1EXbBJFdZu1iQnG3Y JuZEtOIe2+PYjqjb/gAlscpFGWILgbJq2WhKXVuxFlhGB5M2DdNUNX0klKPZatpr29ZYbYBy xSZtyH5vo8Z2TLTJcxDpPKbvz5aNo4tFNxyksU8B3IzMkGEc15a6ZN24pm8hlYRNVGSaThco WTq2SfLMM1DQ0Mwz8ZPVVzYQrN9pF0t4vQp1yvvvL/uzEMSSzNC1H8zoUQmvjSCgA6wIuX8e LuVgKCNQZWdGhMLTMJhNG3JISwcSJm2ZJ21SY8Ymj2zXwh4Quk2SF8YZkQszYZVHrvIGp6A0 54hKhbbpHlnnNpIhYjjuIgWn6KWRYyhG9/3pfHh92v9U3r8RvDucH54OL/p5IMs1iihLi6G/ aY5iJBcPZ7u6bHlgCPrCQ5XOi+/Nna8+gd7byyO7cL3sseSDu3Cp11VLP+9xC05KEENnje4J r8czOyYPxDOda8mPZnFj+oYq7XUdm5TaAkY+tQRAkszDlRYdOwAwsekcgNjmorkQmwZ+HGur DNhXjTIn2VayH1g/ydxalleBadC8O04ibo0QFZexHgTHMK8Mz8iX8qZQWVioCN/qxsFhaHXF FWM8lFAxwxGbYKPjVUWGCGeXc1OW+YpvXHQHU7erKmPbFb1b5o2rlf4zlE09NHSblRLoRoaS 3KHAoG5pXXT7WVWW4UkJv1YhY5y8CQBn3wOV7WcyrCNv+AJ6qtPRbuzAduUspsTdhDn+PDzD RQJs5B4PJ6HoTGxPnPnSuPRI47AG3/jJboPFTXPTIldovQA9a/yG0NQLjd/GZhu45AEOSRCH uMlcOzO2WoXyD5r7j5WMA+UWBWrH6kvu39M/Flvx/vkVJELkCmabWJrvuNvRMirXk2hWvdlV kktxhPJsGxie6agQ9AKUV4b85Mq/0UNdy3Z4cuQ5wpIZAnaNN30XadBTrRq43Fa6B7EPtlJT DEhlC2gACNdarWxxA+AqLZZVKcdBAWhblui1mFMmNa0d25WvdwzKcwQ/E6o25TgB82SnmLmM mle3U+8IaX3Do3QTMSvqG6F9GlVrxF51b7NttAaaS2reVYrvp2pZUqYV+CWm7XPYVpeAbi1E tsmyBPmyEbg2BRYgItypVKu7q+b9zxNXxxvb1oeMRT5S51G+uy6LkLuAxSj2AX40d5Zf5NzN qwYFKTEqqqKwwq5UAcxfT4XPWLk5CiqlOE+g6ULuEOW1DKRaHuBOGKhB9Y9VTjpb4ixhw/sF BWLOZV0u9qE4WmOArBoesKr9GxgT8z3tWUjMKKutS2TDqI8e4mXLg36nK+K6VP0u6q0S0nmx idNcE609pGwVuDMRaS3D5+AqZJx/IujjLgE15enqWt1end/uH/ipN/Vj3rSUG0thz9mu8JoT MNWjmopetpIm+ABlc4WAVm1KFkGow/cyv2lrJNl0taRiVlf5rqwqLB8go1U3WZor4WcAJJZD 1NZU6F9+LYiG0OHjozOYDKg+mHrmFauRimeXA5jD8OWBWI5NCJwF4yrY7aICtX1KBZDh0jIP URuTbWvRPoUZxlYsHThgBw4ot7swyqaoJonWdSqHw2YYR83FAV1diE/PS5/QagpwlALkJjja yN5f5jFineBbHwa8YXxYFEYrpFpZJynrT/BjSh9WXyaoDrHlCDkrgNys2eVTQy23HCXSnKGA KosMbIubqF7TZj1AdBvWdMw9QOq6Y7loLKUBZSRgZF7z9kIvFWk2Tdr3u9X3lAwAX3RTKPvZ hm1bT8Fk5/XIfuLoSmdjzo513FiRVljD8LMmJZ1a6GYscD545guIcGfKNhu5aSk70ACcymwZ qMuDT7w7DR4cDBdRfVd1QS5H8CZRV8kAvDT7O4r5Os3atADlxiIEl/ZyTZuibNOFtMRjFZAK ANfIR1UIBYKcH5NlgTFgAscd0vOddEGr+XPKqJVGAaJZLRq8AwkYnll8Q5IAkRK6sjMCJ2dv yXotC+9Q+hEGISvTmk2eXZyi3qBIwuw2vGNVY9xjeUt2hpQqLWIycIBEsmVDwdurKThPWH+V 1dR1f3T/8GOPTphFwzdG+o1eUAvy+BPjLz7Hm5gfVsRZlTZl4HmGxpN9PPiw7jOnMxQiobL5 vAjbz0WrFDbMuFZZ03nD0tBFb1TTvo8M5jTmcofT0ffd4JP5mzz1R9J1u6DUe4tWmZQcMImh wqH1Lc0x0N0hGN7T/v3xePWN6iYwXFP6iYOuNSGKOHKTq543JHAvaI3XORWKllPCRUheqxwI fQxB5tJW1urjqGiVZnGdSBsdmEXKPab4x2O388kntVULhHKqrNZLtuPM5Qw6EK+jtEkn+aIL Dy1BxZ+RAejvE9NRkOZm2gjHH+BcMMmpOcp2wduyvpappAmjTiDY0S3lGwmGBQR6gyoLkM6/ njF5cxvSnsAFuUZRvC7LdqdztQ4pYQPOkmUYsfOpIFveEfWmsEWjNISysFjWXBeehwca+wHO UfUTWoo6StWlZLfYuorU792yaeQe6qB6Q90oqVb09hOlC5QVfHMeqKHEghwbwjHBzgHO3PT9 h64XQHWbhNe76hZCX9LO9DnVuoJA6Ho8Xx66ikx2qRFKG2SMeL5FQEBwem4Iwg/qV8ahju0M 9RxpUNEDUciv4uxjiB8j7+wSuj8aduxoQHNSxs1ImTommbm43AHjy4oHCsbSYvS56avpa/Ra FCJ6kStE1LRVSGxdFbHyp4KjXtcVEk+bcaDNOLAp/zCYRDsQAdYexTgn+LDGs0mDGZsEk23n f9zXpkV6aFFpTFz3sInSFIP6Mk0abNFgmwY7NNjVNVTX+z1+RucXaJqgqZWp7WhTN6+uy9Tf 1Tg7DltjGPgWY6yqHL+sB0cJu1BFFJxdZ9Z1SWDqMmxTMq+7Os0yKrdlmPxfZce21Eiu+5XU PJ1TxcwAw7CzDzy4u52kN32jL4TkJRUgA6kdApVA7bBffyS5L77IzJwniCS7fZFlSZYtHl5K PRV6BwYFLTEuZPeIrIlre5j63kGjPAOFJGAuzqxEE4iyld7Bp5mwGXKyOFQJZE3AKsNL4km8 pOP7/tEzXcUyXGTqssLm9nWPJ1lOQmbcdnR1ckH7fqE/4EHAUl42mOGt8w11aqnK4QxziGQl 2OZabYFTf43p0WVkQVsLfoD3QwO/V9F0lcNnqLt8eIjya+CDaxWdMtRlrHvFXZdcBzE0566a VsFkMDAqmst2iu5ksHgimUHLG3rErViQRhLaz/g7ZFw/MCAjJArMHDyVSaHHTrBo1aQPnw83 293n18Nmj2kxPz5sfjxv9prt1fegSoUvjUxHUudpvuDTEfU0oigEtIJ/6qenSnIRFTHvdOuJ FiLlXIFDi8UYj430NFzaB0BtzecZxlgavmiOYCVF6XmklJxRRNeq1uO8xFTnecY/wuOhR7/M xONh8xQhLHAGiDn3FXd/bZ0dPbC+0K9Xwmh8wDsDd0//7I7e1o/rox9P67vn7e7osP6+gXq2 d0f4yvo9ioSjm+fvH5SUmG32u82P0cN6f7eh0/9BWqjwpc3j0/5ttN1tMXJ1+++6vcTQtzjG 9Hp4OIhDZ3Ymxsf81eLQXvdnh7cjxjzOXtoucopvUof296i/bWVLxt4ZnZfKTan7zehhSvMq nIKBCRwWCxt6rVvwClRc2hB8EvMcxFaYa29DkUDEPVG5jfZvzy9Po1tMtv20H6n1PQy8IobB nQg9yMQAn7pwKSIW6JIGySykVLl+jFsIjS0W6JKWukt3gLGEWi5Lq+nelghf62dF4VLPisKt AfdElxRUATFh6m3hhj7coux8I2xBfC1LBImk4ILKqX4yPjn9ljaJg8iahAdyLSnor78t9Ifh kKaewobNVMjmGSteb35sbz/+vXkb3RIX3+/Xzw9vDvOWlXA+FU2Zr8gw8tjwHb6MKuZFvNeX BwyAu12/bO5GckeNwach/9m+PIzE4fB0uyVUtH5ZO60Lw9SdhTBlmhdOQUESp8dFniwwJNs/ vkJOYnyJ26m4kpfxFdvzqQDZeOX0LaALYrj1H9yWB6HzgXAcuLDaZeOQ4T0ZumWTcu7AcuYb BdeYa+YjoPbNS/OUthu0CHTvuuGDA7om4utG7vH++vDgG6NUuO2aKqBd+TX0wT+nV6pQF6y5 Oby4HyvDL6fMnCDYHZxrVooCcX1yHOlPEXdMydJ3zOgKqgi9mzbsqwuLgfdAa0ljt+VlGnFc jGD99sgAPv16zgwsIL6ccjZ8tyqm4sTlvDhAhKrRofeAv55w4hAQXPRph02/uFXVoKAEubt1 1ZNSPahrgueF+rLa0imFrcuL2CMh3SXhgamX0Sxw1gSxS001l6Hhzu5KANjfd9CC5ua7hRbC 8RR3bCpSCWa6YEY7FFXNB+ZqBJw7ROtMxAyJgtmVjX+x1c2mYskoQ5VIKnHq8nAn4zkukpKP wO/xZcG/o9Yz2pnLT9LdG8FGZeekhQ9Torjt6fEZw4INfb0fsnGiDm7sxiZL3g5s0d/YhA59 2TO2xjNPxqiWYFnVkSO6y/Xu7ulxlL0+3mz23UVoriuY1GsVFpw6GZUBPcfS8BiPtFc4Pvuk TsLtnohwgH/FmOxLYnhksWA+iOohmNfxO0cVFmHVKre/RQwj81t0aAb4u4xtwyxjOdOBKZf9 FAydNJXoliGPDibENaygDlk0QdLSVE3gJauLlKe5/nr85yqUZR2P4xBjwVQgmN7MYhZW3zDR 8BXisRZvsFj3mb4SrYo/gJeqCr3KPBZ1YSyseS3iCTqACqkiWTDOhBoZa6sUr4R+JxX1QLkS D9v7nQqFvn3Y3P4NBqwW4Z1HDeYOjslLdvHhFgofPmMJIFuBvv3pefPYn9Kok1Ld/1YacTQu vrr4YJeW13Up9PF1yjsU0L6lvDg7/vPccM/kWSTKhd0czg+k6g0SylFY1d6WDxTEnfgfdmCI ofiNsR38lhm2jrJRjy/6y7U3+/X+bbR/en3Z7ozkdGTAk2GvxZoq2CoAWwmES8m9dIlx1EZf ghhUCszGoI1sF/6cSYybiBNzf8vLKOb0UeUuFYlbT0H5mVM9lrhDWWDQCqZ04BymxXU4VU6s UhpKZwimEYg0A3RyblK4qip8qm5WZilT+4WfpmvbxICUkMGCd6cbJLxaQwSinDvbHiJgEvhC 58bOHJq/9DSpceAq+aGmIfdavcYuWZSnWp+ZFixR5wGpmxgLb6k0IQsKOzcA0Wlh3lWC/XfF Qznq6yWC9XYqyOqaTZ3UIilWXY8TaOGx0AewBYoyZeoHaD1tUk8wp6LBp+Y5zm/RQfgXU7Fn aIfOrybLWFsCGiJZGjluBsT10kOfuytMPxzo97UqD2NYrlcS+l0KbcsALsE1qYe2KxBGUa6M tYpwIwkPLV5MvCOiqFzVq/OzwDzQQlyY8vGGVA7UAF+cZDVJVFeM1VM0qahmYPmPyQnMLaKi ATtPb3d0qYuoJA/0GvH3eysiS8yApTBZrmphVIEXY8D65YJ70iI2HlaI4tT4nccR5mSGjaQ0 5gTmqZvOq6hiJnkia0xnlY8jfTLHeVZ3b6tb0G8/dZFJIIxYhJ4btzsqvAeSa+NFwxzJIteJ YJqtAHc8D8sm7EBqN/6s3c3uFFmP1TSJ4i9uj1tk6UUm7yFhe4l0/7SOa3qkeULRKUMEfd5v dy9/q1t6j5vDvXvKSVv5rMsypoXrERjDanivbJ5VOYUdTxLYl5Pe9/yHl+KyiWV9cdYzWasl OjWcDa3AVBpdUygbAr8mF5lIYzawqp1D7zD0JuD2x+bjy/axVXkORHqr4Ht30FRwUqvnOzAM 2W1CaTyfoGGrIon5iH2NKJqLcsxf49Sogpq/gTeJAoz5jws741eLlxn50NMGj60xuJ2L+C5F KuluwMXp8dk3c9EUwNR4j4iNQyzBRKL6RZXa42OETAIdPmYdZ7Bcdfd8h6CmaWKnAC4FpRkK JHFmqIeq8kqF4WOsZCrqUHMB2BjqF96OWDgNpNNHFRan0npf6PHGv8sqPZeLSUzRrHqqMw3Y n+KpKbk4/nnCUYEdFesqq2qrOjB12QxjRR1XQXseGG1uXu/vDXuJQoDAPsGHKs2HVVV1iKc9 jVXUoWw+zyxTksy/PK7yLPbY1UPVwC9jVvNAgjzAuxWV26gW4ZHdLCmemv7qQyr/fGWPdIdt wx88HyjDhnj3lx8BzsINv73g5ftYu0o7udgzRpU0QUeqB6EimGJCrT25ZRbQlhJga4eJfgHH A1zaXZXBenJ+fHxsD0BP+4uZ6On6s+uxf+p7Ytzx8XVvhjXVmXqDG8k7n73ioojapULpAehg 3R6AdvmjNsmPKH0cL0yMk3zuyCIeGYakkM5EJTI3iaECU1GYbvsof1i6Vm1QKMyv8Eo1BjSH TlOmKtGiOnvBSkb4aOHrs5Jd0/XuXn8qA0zZpoCiNTChro5X+bh2kcZejQ+LpzphITLWCPcT 423FBuSgPof4sdUUbwrXoEYz1c0vQaCDWI/yiS6tfX0dhBd+ELaF3LhvZYDb9pyYSNJimxqa 2Q0O7FWRG+pMYFqTfKwPlVJMLLPI3YstRsbPzqQsLKGqvDB40tmzyOg/h+ftDk8/D0ejx9eX zc8N/LN5uf306dN/zclWdVPKNEcJL0pgYfduGRXDbtmshsZXU8tr6UjQLmuTDfeQz+cKA1It n5vRZe2X5pVxv0FBqWGd/aU1FkwBV3i0CK9sAGsU1coqkb7SOGbkaebzq+qjBasFL8v5JeTQ 43etkf9jlrveKLkAMmCcCD0IkfiOkAOM9CIYwFWT4YENcKdywLj9n6lt6j1pryhgfwcxXr0n oNEn6Z2GgjyWNjtN3BbRBcIYdm9vVSFo5iqkrL+VD3s2qxMR45eh8WZED/Q1WJ9kw4kFRfC5 DJ+XBfFWWQ2DmxBpyL3YOT0xSrZTaHxOXjJ3d4dXVIxe2wMJ4lSpwSXtgO9MnLqtCroj3uli HRHtnKxkWdKLXO1VWb25mayhNE/Kfvuda7fDohOgz4aLOufWd5YXatT0O124sY+bTBkK72Mn pSimPE1njI6thaUqUEsxJcWPAtvKyCLBi2801UgJKnTmqHNhW1DVMiBV3aEpZMm/YacdogQ/ RG9IdfhT41Sql2Gc7mlVtZeL8LqXvldImYKJBuYK23jney1A23WGGaYa2IktodOwDGidqDSf Zu7l3r2Q2qtQKcyrSNQCjwfwITYf91QCH77mBAlNAbkQZ2Bl69Xjb+6ED2lRS2sCUu5Af6jR iDUsXsJZP23S/kMKi5d3k3iSpfyhuSLqKfTydAJHeE6EGZsFNzcULdx6ZfhjhjSiVwdAyeO8 i50mYEk6dYVYyRXzXqTl2vofwAOTkxWwAQA= --Ll8TiHvqIhrSSeww Content-Type: text/plain; charset=us-ascii Content-Disposition: inline _______________________________________________ kbuild mailing list -- kbuild@lists.01.org To unsubscribe send an email to kbuild-leave@lists.01.org --Ll8TiHvqIhrSSeww--