From mboxrd@z Thu Jan 1 00:00:00 1970 Return-Path: X-Spam-Checker-Version: SpamAssassin 3.4.0 (2014-02-07) on aws-us-west-2-korg-lkml-1.web.codeaurora.org X-Spam-Level: X-Spam-Status: No, score=-10.2 required=3.0 tests=BAYES_00, HEADER_FROM_DIFFERENT_DOMAINS,MAILING_LIST_MULTI,MENTIONS_GIT_HOSTING, SPF_HELO_NONE,SPF_PASS,URIBL_BLOCKED,USER_AGENT_SANE_1 autolearn=ham autolearn_force=no version=3.4.0 Received: from mail.kernel.org (mail.kernel.org [198.145.29.99]) by smtp.lore.kernel.org (Postfix) with ESMTP id 7A495C4332D for ; Thu, 18 Feb 2021 06:10:41 +0000 (UTC) Received: from vger.kernel.org (vger.kernel.org [23.128.96.18]) by mail.kernel.org (Postfix) with ESMTP id 3A91C64EAF for ; Thu, 18 Feb 2021 06:10:41 +0000 (UTC) Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S231538AbhBRGIu (ORCPT ); Thu, 18 Feb 2021 01:08:50 -0500 Received: from mga03.intel.com ([134.134.136.65]:46966 "EHLO mga03.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S231725AbhBRFtB (ORCPT ); Thu, 18 Feb 2021 00:49:01 -0500 IronPort-SDR: v9cWkglBXM6N+A1DV3bBNMKoke6kDmcMr0KddzFuPMhTis6+y10fM56z8zIt0OVZJFWPtILl75 tBwGc9LY0Tow== X-IronPort-AV: E=McAfee;i="6000,8403,9898"; a="183477018" X-IronPort-AV: E=Sophos;i="5.81,186,1610438400"; d="gz'50?scan'50,208,50";a="183477018" Received: from fmsmga004.fm.intel.com ([10.253.24.48]) by orsmga103.jf.intel.com with ESMTP/TLS/ECDHE-RSA-AES256-GCM-SHA384; 17 Feb 2021 21:48:11 -0800 IronPort-SDR: 30VKgicqmgiJeseyJeMCh72N+U67X4rR2s3wMD02CYhDP6v7MPfIi3q5JdfUjcyv4RbkvLQJSL qbvMvLwvwEsg== X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.81,186,1610438400"; d="gz'50?scan'50,208,50";a="419357989" Received: from lkp-server02.sh.intel.com (HELO cd560a204411) ([10.239.97.151]) by fmsmga004.fm.intel.com with ESMTP; 17 Feb 2021 21:48:09 -0800 Received: from kbuild by cd560a204411 with local (Exim 4.92) (envelope-from ) id 1lCcAa-0009UE-Ml; Thu, 18 Feb 2021 05:48:08 +0000 Date: Thu, 18 Feb 2021 13:48:01 +0800 From: kernel test robot To: Stafford Horne Cc: kbuild-all@lists.01.org, linux-kernel@vger.kernel.org Subject: drivers/atm/horizon.c:365:9: sparse: sparse: incorrect type in argument 1 (different base types) Message-ID: <202102181354.gtjmc5By-lkp@intel.com> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="M9NhX3UHpAaciwkO" Content-Disposition: inline User-Agent: Mutt/1.10.1 (2018-07-13) Precedence: bulk List-ID: X-Mailing-List: linux-kernel@vger.kernel.org --M9NhX3UHpAaciwkO Content-Type: text/plain; charset=us-ascii Content-Disposition: inline tree: https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git master head: f40ddce88593482919761f74910f42f4b84c004b commit: c1d55d50139bea6bfe964458272a93dd899efb83 asm-generic/io.h: Fix sparse warnings on big-endian architectures date: 7 months ago config: microblaze-randconfig-s032-20210218 (attached as .config) compiler: microblaze-linux-gcc (GCC) 9.3.0 reproduce: wget https://raw.githubusercontent.com/intel/lkp-tests/master/sbin/make.cross -O ~/bin/make.cross chmod +x ~/bin/make.cross # apt-get install sparse # sparse version: v0.6.3-215-g0fb77bb6-dirty # https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=c1d55d50139bea6bfe964458272a93dd899efb83 git remote add linus https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git git fetch --no-tags linus master git checkout c1d55d50139bea6bfe964458272a93dd899efb83 # 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=microblaze If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot "sparse warnings: (new ones prefixed by >>)" drivers/atm/horizon.c:1135:22: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected void *[usertype] tx_addr @@ got void [noderef] __user *iov_base @@ drivers/atm/horizon.c:1135:22: sparse: expected void *[usertype] tx_addr drivers/atm/horizon.c:1135:22: sparse: got void [noderef] __user *iov_base drivers/atm/horizon.c:1173:49: sparse: sparse: incorrect type in argument 3 (different base types) @@ expected unsigned int [usertype] data @@ got restricted __be32 [usertype] @@ drivers/atm/horizon.c:1173:49: sparse: expected unsigned int [usertype] data drivers/atm/horizon.c:1173:49: sparse: got restricted __be32 [usertype] drivers/atm/horizon.c:1177:48: sparse: sparse: incorrect type in argument 3 (different base types) @@ expected unsigned int [usertype] data @@ got restricted __be32 [usertype] @@ drivers/atm/horizon.c:1177:48: sparse: expected unsigned int [usertype] data drivers/atm/horizon.c:1177:48: sparse: got restricted __be32 [usertype] drivers/atm/horizon.c:369:10: sparse: sparse: cast to restricted __le16 drivers/atm/horizon.c:369:10: sparse: sparse: cast to restricted __le16 drivers/atm/horizon.c:369:10: sparse: sparse: cast to restricted __le16 drivers/atm/horizon.c:369:10: sparse: sparse: cast to restricted __le16 drivers/atm/horizon.c:369:10: sparse: sparse: cast to restricted __le16 drivers/atm/horizon.c:369:10: sparse: sparse: cast to restricted __le16 drivers/atm/horizon.c:369:10: sparse: sparse: cast to restricted __le16 drivers/atm/horizon.c:369:10: sparse: sparse: cast to restricted __le16 drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 >> drivers/atm/horizon.c:365:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned short [usertype] value @@ got restricted __le16 [usertype] @@ drivers/atm/horizon.c:365:9: sparse: expected unsigned short [usertype] value drivers/atm/horizon.c:365:9: sparse: got restricted __le16 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 >> drivers/atm/horizon.c:365:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned short [usertype] value @@ got restricted __le16 [usertype] @@ drivers/atm/horizon.c:365:9: sparse: expected unsigned short [usertype] value drivers/atm/horizon.c:365:9: sparse: got restricted __le16 [usertype] >> drivers/atm/horizon.c:365:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned short [usertype] value @@ got restricted __le16 [usertype] @@ drivers/atm/horizon.c:365:9: sparse: expected unsigned short [usertype] value drivers/atm/horizon.c:365:9: sparse: got restricted __le16 [usertype] >> drivers/atm/horizon.c:365:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned short [usertype] value @@ got restricted __le16 [usertype] @@ drivers/atm/horizon.c:365:9: sparse: expected unsigned short [usertype] value drivers/atm/horizon.c:365:9: sparse: got restricted __le16 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 >> drivers/atm/horizon.c:365:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned short [usertype] value @@ got restricted __le16 [usertype] @@ drivers/atm/horizon.c:365:9: sparse: expected unsigned short [usertype] value drivers/atm/horizon.c:365:9: sparse: got restricted __le16 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 >> drivers/atm/horizon.c:365:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned short [usertype] value @@ got restricted __le16 [usertype] @@ drivers/atm/horizon.c:365:9: sparse: expected unsigned short [usertype] value drivers/atm/horizon.c:365:9: sparse: got restricted __le16 [usertype] drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:361:10: sparse: sparse: cast to restricted __le32 drivers/atm/horizon.c:357:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned int [usertype] value @@ got restricted __le32 [usertype] @@ drivers/atm/horizon.c:357:9: sparse: expected unsigned int [usertype] value drivers/atm/horizon.c:357:9: sparse: got restricted __le32 [usertype] >> drivers/atm/horizon.c:365:9: sparse: sparse: incorrect type in argument 1 (different base types) @@ expected unsigned short [usertype] value @@ got restricted __le16 [usertype] @@ drivers/atm/horizon.c:365:9: sparse: expected unsigned short [usertype] value drivers/atm/horizon.c:365:9: sparse: got restricted __le16 [usertype] drivers/atm/horizon.c:361:10: sparse: sparse: too many warnings vim +365 drivers/atm/horizon.c ^1da177e4c3f41 Linus Torvalds 2005-04-16 354 ^1da177e4c3f41 Linus Torvalds 2005-04-16 355 /* Read / Write Horizon registers */ ^1da177e4c3f41 Linus Torvalds 2005-04-16 356 static inline void wr_regl (const hrz_dev * dev, unsigned char reg, u32 data) { ^1da177e4c3f41 Linus Torvalds 2005-04-16 @357 outl (cpu_to_le32 (data), dev->iobase + reg); ^1da177e4c3f41 Linus Torvalds 2005-04-16 358 } ^1da177e4c3f41 Linus Torvalds 2005-04-16 359 ^1da177e4c3f41 Linus Torvalds 2005-04-16 360 static inline u32 rd_regl (const hrz_dev * dev, unsigned char reg) { ^1da177e4c3f41 Linus Torvalds 2005-04-16 361 return le32_to_cpu (inl (dev->iobase + reg)); ^1da177e4c3f41 Linus Torvalds 2005-04-16 362 } ^1da177e4c3f41 Linus Torvalds 2005-04-16 363 ^1da177e4c3f41 Linus Torvalds 2005-04-16 364 static inline void wr_regw (const hrz_dev * dev, unsigned char reg, u16 data) { ^1da177e4c3f41 Linus Torvalds 2005-04-16 @365 outw (cpu_to_le16 (data), dev->iobase + reg); ^1da177e4c3f41 Linus Torvalds 2005-04-16 366 } ^1da177e4c3f41 Linus Torvalds 2005-04-16 367 :::::: The code at line 365 was first introduced by commit :::::: 1da177e4c3f41524e886b7f1b8a0c1fc7321cac2 Linux-2.6.12-rc2 :::::: TO: Linus Torvalds :::::: CC: Linus Torvalds --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all@lists.01.org --M9NhX3UHpAaciwkO Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICMXqLWAAAy5jb25maWcAjDzbcts2sO/9Ck760s6cJLIcJ/Gc8QMIghIq3gyAkuwXjior qaay5JHktDlff3bBG0CCcjudNNpd3HYXe8Oyv/7yq0dez4fn1Xm7Xu12P73vm/3muDpvnrxv 293mf70g9ZJUeSzg6gMQR9v9678fn7fr4+HP3er/Nt7Nh68fRt5sc9xvdh497L9tv7/C+O1h /8uvv9A0CfmkoLSYMyF5mhSKLdXdu3b8+x1O+P77eu39NqH0d+/2w/WH0TtjJJcFIO5+1qBJ O9vd7eh6NKoRUdDAx9efRvqfZp6IJJMGPTKmnxJZEBkXk1Sl7SIGgicRT1iL4uK+WKRi1kL8 nEeB4jErFPEjVshUKMDC+X/1JpqdO++0Ob++tBzxRTpjSQEMkXFmzJ1wVbBkXhAB5+ExV3fX 42ZPaZxxmF4xqdohUUpJVB/s3TtrT4UkkTKAAQtJHim9jAM8TaVKSMzu3v22P+w3vzcERNBp kaSFXBDc7K9eBZcPcs4z6m1P3v5wxjO2uCyVfFnE9znLmZNgQRTMOozPJYu4b6Lq3eSgizV/ QRre6fXP08/TefPc8nfCEiY41cLKROob8jNRcpou3Bie/MGoQp460XTKM1slgjQmPLFhkscu omLKmUCePtjYkEjFUt6iQQeTIALZ9jcRS45jBhG9/ciMCMncYzQ98/NJKLV4N/sn7/Ctw9vu IAqaN2NzlihZC0NtnzfHk0seitMZaDsDhhu6Cyo1fUS9jjWfG9EDMIM10oBTh/zLURwY05nJ moJPpoVgssB7KaStYdX5etutZ8sEY3GmYFZ98VudruDzNMoTRcSDW/NLKhOnuUOz/KNanf72 zrCut4I9nM6r88lbrdeH1/15u//e4RcMKAilKazFk4m1EcmdJ/oPSzTWBCbnMo1IpeR6i4Lm nnRJL3koAGduAX4WbAliUg4RyZLYHN4BETmTeo5KnRyoHigPmAuuBKGs2V7FCfskzS2blX8x D8JnU0aCjo40xhUtaQh2gofq7upLqyA8UTMwryHr0lx374mkUxaUt6Vms1z/tXl63W2O3rfN 6vx63Jw0uNq6A9sIbSLSPJPm9mMW04lj6yVpuXrLsZBwUdiYZiYaysIHg7PggZo6NVsoc6yT pFo244G8hBdBTC7hQ7hDj0wMnytgc04NA1CBQavhxijrWCXGz8JLs4HxM2xlirevQhFFjGWm jM6yFKSPxkWlwthCKWiSq1SPNBAPElgbMDAMlChTHF1MMR9bd4xF5MGxaz+aIQO0HxfGdPo3 iWFKmeYC2NP6+BYVpoJaVk0ExeSRZ451AOMDZtyuAJDoMSYWYPnYwaed2aPHT65DpKkq+tcR Iq80A6PNHxluFR0B/CcmCWUu+XWoJfzFCMyysP1RGivr6kDQwyHMEE5NlBOmYjAwKCQIsSI3 kRbgJYqw9OEXYqS+h7KsjLlj0FLnRD4B1x7m9hbqDeQQcxsWAH/C/TQYk6VRZIV1fJKQKHRf cL1bG1fPg7FAaJkUwlPnJDwtcjicy26RYM7hMBVLu6bOJ0Jwp12YIfVDbIRKNaQg+nhdqOYZ 3jDF57bO1Iuba8PSLAgGjF5Gr0afev6+yomyzfHb4fi82q83Hvux2YM7JmDoKTpkCD9My/8f R9RbncclzwsdIlhhIuYKREGaYaQpMiK+JeYo991KHaWuuBvHgwzEhNUZgz0bYNFsR1yCcQSl T2P37NM8DCGNyQhMBFyG/AXsqGO9OCaZJlgUeYL2i5MIrrelYBDbhzxya5KOC7SttqJaOyNr FuMU0oSImOYDQyQfZZ8EnFgBKmIirhQco0Q6ln+E4LEITFtZRwTTBYPoVPURoHTcF+AIgMFg +R0EMjcyCqkInZXRj8yzrMw627RwBn7FQGhFy3arM+qWd3jBFP3UxnhgRuFIIMI8oWZIGGy+ bfdbTezBSK9l1KgdPGMiYVF5pUgQiLvRv7cjOwNfopiWBp9HEIzEPHq4e/djezxv/r15d4EU rDRkNgLcmFTi7tKkSJnROPuPpGhQWPQmWcDnb9JMF+hR3iQLs/wiDUwD6fzduy8frkYfnt61 ituTXSnR42G9OZ1AMuefL2XMbwWVbUp1NRo5LySgxjcjhwYD4no06iRmMIub9g5LMa2tjvOe QfQP8KuneDQOsMCC8YBhpivo3bs1EB92m7vz+Wcejf7n6upmPDLqQ9XgNqipmXWBLaZ1NnhV p5ICr7e8uzLcWDDH+CPQsUaayN7J4JKsXncagElWeVNWTz/QhD95a7MqVjPAWx033utp89Su DJYOXFwZw4z+ve5cIAiBchJh2MkgA2UUjCZQjTpXEGwC3Pb+9VM6kiln/lrjuo7H5pD/evLS rrQyyiulNbltklplr9Vx/df2vFnjtO+fNi9AD/6srwRTMmfAXW3NDQuswWBDMU5UfJKnuaMU gpWAAmOYAjhjxt26bIVlPJwBuQamjdj5kCa5HvtcFWkYFqqDWRDwrjyjRVk8qcts3TKhNsSw eaWlUpcNarmlQR4xqe8+i0IdcrTYbFLWDCPw5BDtjK2T1weYGitG6FZ8WG9BRCCvey6/PAxG abYjS9KChSGnHAOGMLQCK3QWZijRV/AJTefv/1yBunp/l7rycjx82+7KokUzEZJVmugK7Wp5 aLJK2EUdaNXu+dJKXR/+hno1WYkCywxhLzO0R/sqGePqVx1RWTGnBpX2BfhE3AFgRZUnlygq 7XFF+tV4KWhdJ++EnzUBdwU6FRIVAKyDa/s1aijR65ItHx2TlKFYzKWEeKvAQrHMMPbgMUYY 7nQ/T0DtAwioYz+NXCdXgsc11cyO301osZhypUNLI6etb5aCqBNkk85yqzrto1q71FAmV3fP 7Splgb+QGU+0BNs6Dft3s349r/7cbfRjiKej8rNhtnyehLGCzF/wTLVzNope4UNIMqydtWBX YlxigdEUpmxjzlSwII8zm8/VhRjaqT5GvHk+HH968Wq/+r55dtpf3Ar4HiNNBADYjIBh1gW+ xyxnZBD6FpnSVkO7ylv9TyMWFqfiAS4Y6ItpLHXALxgqS1nObA6Gtr1MBVronMOtVSmkvIZK JCnEFUWVC5S6w5YUdb65wwkDnYFMXxu9WWxF7REjpQdwVRLMSB1+NDWhdngNDF2KjFgiGJF3 TZXwMbNCmkc/NzzP43WYRkGrM6GAC1X7dTPDYQJPAi5GuZadYGmLJXQaEzEz7eiw0FtOmaV4 hs9Ck8p+GEDWgcmZDzxXLNG2rL4pyeb8z+H4Nxjpvm6BkZgx43aUvyGkJhNTv+EiLp02ZBlk uiLHBmwMXF7XNQIoPtOB46cVb4xTZSrDN0EwZeGDhdFDsumD9qDA9DizdBUowGlBrm2KqAE2 gaLL6ijjdsGPIiIQJTRMkcq4Yb7gwYR1fxexsOzbHGYovo7GV/dOtgSMuhkTRcY1gx9jw3Ap Es3an1hjJFkWsQrcsjwLApcfWY5vrLiCZO4KQzZN3XvjjDE80s0na7kGWiRR9RddzgMZJbC3 ixNVutOeKia0WcJQiboervX5/nXzugFt/lgV4ztxTkVfUP/erXkaO1W+rXUaGNpmvYaDSlyY KhM87aichusSplv+NYkYKFrVeBm6ZdTiL51Rsfuof0jlhz3mArOk6+BweS7NT/TRe5OBVQr6 0EDqq96Dw39N59aQC9Gnje/dK4Lhq6TQPdc0nbE++D68d/AAPGrk4kJ4X+IusIIS1zJ6ld50 02l4UagZd/nAGut0BHpYlE/6UKakSzerImH/HXS3Op2237brTpcIjqNRZ1UAYKjOqc1LBCvK k4At+4hw0WUJQvPr8SBLEC/k3GXSTPTn/t7CyOwgqKHl25FrF51nqB4e53PWt2uCGNsmOtmB 9tMacWEgsZ/FEAwgTJw5dT9P1CQT+OMiQcyFcDq9mkCCH42YLSmEJ0T1gRn2GvXBkpudMg10 5rvJYUHZh6LP7EPxnei5fyyYG1KMC8fiIXONU3mCpZgZc73dtUxVrCsPmE8vCjZsYGRF0bdQ FcJ5JxStozaH+eChYdICar0QBInEelOK/UUD704qhiAEwh4nen4pbIMdQN4103GgO2XOnBkj 7jyR0/aIUynaE9wLJUyZ4G9I811S1CiQVY88nnIHefUerKNHyw8YiDKkDGw2iyUmMQ9F9cxW s077TTN49s6b07kONKoovofqIMyAuy0dxYIEeodlhXi1/ntz9sTqaXvAYsr5sD7sjPicYNRm 8AB/FwHBmllE5oOmQQy874hUsp7NJ8sP4xtvX53mafNju954T8ftj/oFrJb5jEuX0D9j0tCK 3M/umZoyw3v75IGmMQT7ogiDpXkcAzMNlo65K4KM9KdjmWXEH0jnyJUwLp6uURPT8sCPQpCF DfBpbAMmHYI/rm6vbwFUcowkXlAuFTSMNIjn5YJt+oqwJXW+VSFORo4BkAG42zQ0DnLhqhHD 3WDl2KIhF7dPWXDBIuZUggWPiWHa9M9qF7p8eve1KfiFMx5FLWn5G6gCK1KpwDzJclcyUqEn WdfY3nYc0W2myxX9EP22ai1xspyHpnR52O1C0TCYBTjcIcylb2wopNYPMKgTDkmRDUwot1xV CcKil8vEVtgc3xI6o6aU9253slkdvXC72eEj9fPz676K7bzfYMTv1YWw7jnOpET45fbLiAxs AJsnrSNg4ehqNOpuKHRmonpAcnN93ZkDQT3+VWA+7nAyFvOoD+kPL6Els7rg3qRSVcLowYZo UUodaS6z/iQVsJrF4pG8DhciuUHUELfV7c20jIIaD/OfhNpUdVwxXidAihZlaOTqUiE8Sue6 rlK9qLktm34XyajRvtL9UXW+Siew326IyLbfowXqOqVVfJymCvMfPQIJbHLCRA9QdREbpS+A F4wKalX4kFhmrvRf0wdZj7zIlNv5aqS/cE+FvcH2wXvNwuZExX3OxczZmIQMtY2VZqPKfeus cFQSd2flqdulaLYKPoyDLNAVxhlisZ6qDWnRjLrMnEkip5rLZcAE1OvD/nw87LAL0xGm4AhC RDB3R+paCtXTfrKw9aoIFfx5pd/VDahiE0F6YhaUuHLBBqdb9u2JENK2VHcRtfo/dxYqNzsg 6iWO6opRA1GBBgbNryHkijv6hq9bRFlPvHp5gtVT0rknJVArrb3d8ihqmkOqgw2CAzfHJqtU 0eIgZCd2I78F7jMXH0MgXVFs1mOgL2gsld9zjcHmtP2+X+BjP6oVPcBf5OvLy+F4th7V4Zov OmsFi3oH1uEDQb4slxo1bAJgbIYvOJeoICF8SFJ3cqYvarz8PLyCzBgRV9fLIaWJyAMIm5Ks pzlTPqQ0rLgHze3qhohJQIqvs97tAIebMfr5DVbwREEyPhmwiayYccGTzpq4RTBnfsdaQirc pdT39ur20wDYpUN5wjP8xKN3B8znm0t6Uz7qHf4Es7TdIXrT1SubA3Hq8znjkVYJZ6B+YbJy ttXTBrsRNbo1jfjthHtJSgKWUDakhHV+8Oa0TTuP2yQ35prtn14O2313I9idpzsAnctbA5up Tv9sz+u/3A7AdHYL+JcrOlWMmmHT5SnM3YH9dvkzQTIe6IyjzVNKUKEk/zK+Gh4Dob+k+uUq zdXd9aiLZonuNRHLQi11OG1nQ/UkkPmzZMITV4m4Ieq+jrZr5HFZsb0wGp8rjWy4ButGgoKW CU/5QcrqZfvEU0+WHO1JwuDMzZdlf0aayWLpgCP9569uenBs4z5GLDXm2pT1wO7aDqjtuopg jUaq9sGz7LiZsihzVnyBDSrOQiMCrSFwo/PEMCtSkSQgkdV2lIly+pCLeEEEK78IrEOccHt8 /geNy+4Ad/BoNAIsdJeLaZ0akH7BD/BjlxbJlgp8dL2I0ZzRjsp16UWf0jWpgYYsIIqwt8lU rJaybk9xXubuiZoqAbZw4UNm3T9hvMLqhhY3rgM1XlV10UPw+YDMqpqIsNuISjh+uVmNLQSL 07nrhmVxcZ/KYpbjt6D2t556PJEPCa1nKb9tNExFOazGlh+LutoG6obiLK8rOIY6pdRuuxBs YnWAlL91otmFyYjHOPa5Cze/OKhgcWyWUetJzQ8UdePeFBRLa11oP7sjMtReRvdAO7Vi4BY2 /Y1taaLWCRHriAHcN7byRVb64qurYuhJW+OWrsAmTpeKWWEchhcRhx9FlLnM5L2uPfrc+PAm nvKi5KvVdNlk4UabEGTYtNNR3zboJc7KWqyMx1T4odVG1kY4Wx3PugPce1kdT92KLVAT8QXL p84GFcT7NP4MkWJJY2orIusW3ksTpGEz1oDqpkxIsmMwS8puJjHQSrjbSpAEdSuTUX9tiwrU T3+s5KCqnX6PQ5pFOfwVYiv8mK/8hEMdV/vTriyjRKuflivT50yzHn9wVY5tx3AJYvxCWPSS DEHijyKNP4a71QnCjr+2L31PqVkd8u7sf7CAUW1FBlgPlqJvZarJ8OHH1RNtUOGV9kkyK/RX hcWVodF97Pgi9pONxfX5lQNmfULXQDELAGc1sE19mDiQ3XuAcPCupA/NIY21oSCFDiDtAIgv wSVbEcSw5Moof/Xygm88FVD3lWuq1Rrb27sXET0knBI5h31LwyqdTR8kEA1fDHozHlFnZRXR CVOaoqsTSt7cOD8PQGSZiM2xP1p0LjJkCSX32ozkjYOX39Fudt/eY5S92u43Tx5M1X9aMpeJ 6c3NVe9+aSh+WhcONKAZVEPVfCTBL0XDiOinSWtsgygWgivdRs5D19uwTZyqrKvJMZ1m4+vZ +MadmGvJSTW+cVVYNTKq2Wzpgui+a5lLqqCDLusa29Pf79P9e4oyGSrW6vOkdGIU4X3dBJNA HBPfXX3qQ9Xdp1YJ3pavpZQQBOuYzVYuMJyI6Z66AlfCKCUz5H0q0rZ45kBKEss8mbiRqdnd ZyLGSzSuE2HWppqzMEoxzZwSCJSSnntzkBQydoUTpXFaFC42mLP4dv9IlYD98xF82gqy2J2H xN630lS12botbz0hJP8k4jYvDISu1Q4iA+XAAXfxozhFHLgULNnYebBUuxBnW0xDA7nTJHWO rqKDS4MpCZlrtyq227waTEzEnDm/022XjSjGhddjM3FtJ7iIxTLkoJjTZUKG/LQmCCEU4iF1 Dp6Hn69G+FQ0aCnK7S3fIADDFkZUuT+WblWBzHlC3Y8BreSWy9skCAd1XhP98fjpy9eRg1Vw X1gCKRCjtGtmm4GfRoh+a/rxjY9K5mRbufxbOhjCxXVsEQzK0nVRMH+4GX1yYHT91KE0auaC LrvGrGSrfopwXggVX48LYPj40mHKMml/3uodvT8tun/8xv+ytKuS4qWViSBS15XK2Gl7Wtu2 Scb1y0h/d/iH9eTcYMDkp1OXueJylib6AeESsoyem9Zwh5130Aa6/3LkuhldYvw/3VxiijHA 95X2c/YeIDWvXcP/U3YtTW7byvqvzOrWOYtU+JBIapEFxYcEDylyCHLE8YY1iedWXMePlO1U 5fz7iwZACg02KN+Fk1F/jSfxaDS6G7LfqlYU//A/6v/BQ5vVD5+VMwEpVUk23ANP7FI2xqlB b+f3M7ZEGagY7Rou0OFoTQ1BmK7V1J87CDNU5b/tvENkMxyLow6sFXg2BvGXkJ5jBk7VUBxX R6fzS1t04kxOqYF6QzPSlOb6Io6yoKJx6GUEmlaVSH/kZgbSHQfcnBCxSLvqhYYem+M7RMhf LmnNUK2WYWbSkPqlKbGTiPhd56YxTFNKf1SxpcG0rxGnNhxENLjhR47t0lOqBm/4+WYfzrvY ld1FmNqMos0mjTdN+w3ig4wrRWndNFM6Jkl8iIyrSA34QbJbF3dpdDWUHcxzXaBbmNmUwqQv a9Na+SROh7zpuBigPKyevcA4jKb5PtiPU96a8bMMIlbGmYAyHrlpzYa6foHPTHXCOb305gWc OrLVTKzRvTHbelbWlqQtSfE4Gp51LOOHMOA7z6BJwUicUYx9RyzqVcOHrgATPaWJNKp7bidW 0UFEpJYsa4ScQAtUEoc53bVGcWmb80PiBWmFymG8Cg6eFxL5KChAjvDzl+oFtt/TfvUzz/Hs x/E2i6zUwaOPn+c6i8I9teXm3I8SQ2nSgon+2TTCgLVBdKmQYtrwFmxnLr2zrsSX6zJL76xN GXheFsYgAwfFqes5srZsn9v0Qt79ZIEZiKIoWjAg/W5fhSu6GCfBzuzvG3lP9pHGq+KUZnRU Ns1Rp2OUxHuifprhEGZjZLZooY/jLnKnY3k/JYdzW3BDLtdYUfietzOvd63mL310jIWQjWeW otm2gTfilHI+1EoJN/du//bP6/cH9uX7j29/f5YBZL7/+fpNHKF/gAISinz4JI7UDx/EMvTx L/jTDPY2aaODOUze/z8zakGzFyKE0YZp2gKE92lbzdIJ+/JDnETFViYEiW9vn2SkUuIW+rlp J2tvvsU13Mhi+XLZubGGelplEI/KNDdbpoB1ol3IyFTwnB7TSzqlzOxdtBMorVbG2aznWM0P AMHx2cyCSjDzlwOOWKB+wzSAAFe/iV3NuGlTWNWcTlZEHdXzRVE8+OFh9/Cv8uO3t6v492+q 60vWFWDFS07DGRQ7J3+hv85WMXMzlFmsvrZCJrcweaih1IE3pLENyN9iV0e7kyZ6+zURWWtr Wpa2a1pTH7x//nHRTelpzpmJ1cOcGbcUgSf2Hao1fa3v+AzpTRJhd0fbLfiZpgyTxLnX7DZN cio3Z7wfIPTE0GGbpBmVABgW+NGV/PQrxoSyyVlx7a6bpQX3M+lknXBHITTZKKKDGvxEezq7 KogPhr0QRAqHohVY3tMeoACJDRXiuuCPqIkyrggfLgy3z0TF1hSL7WKPOSQ12CPFmUnfHA4L U5c94/hqCDXqhspI66PYtdKcPNwBw7np2HvznG4Q7b1QlpiumpGuG4A/iVgoxPwiFwsorMAl nAtna8Q5pyFDAkijfnuaSmrfv5gVljQ47ro9biTLmbSck5B2QDAFF/CQod2syzzHh4KiJA35 +GNpKjeU4Q8OvCmJ8820SUt5W5BOgSpFJj6RkIEyK3ugiy6u0xXAerF7nmzqwKd6GFeFa/qt GFq3ZLKCespZW80jVVvTyQ9SZ4lg1NAV5B0RYgPHbbirM52YJEeWPrOhtojYB0WSpI1iWax7 irVP4sx1WFMTL9pZ1LoZkduCIvIsEzIMsytRPyNxRtKarC+ay6o3xDTZkbYQACp7YjvJ2Gak rfn5pWJGqfzamnGzqyKHOCCnE5i7SECdrxl7ED+d14Fpzi6S/7bA1LlFeBrEaVgsI5iq9ANH TF0MHM5oWguyOBJLMm0zktVJvMZv6JS9nC5ixNiFKS/EuWdu+XVNmktfNleG+52/81bZJbsk 8TE1YxlY3WKajNxiEUFTr4tEK0qbhEkQOGoCaJ8lvk8m2yXOHpN4FG9km0QHXMGSjUVul8Oy tlL9Shaj9B7jNX1xlFSJuVf0vuf7GS6tGntM0Bc+dgVmsu+dHEXotWZcJ2VZV1SuVBBJUGmH US0Wcr/qc4mBrb4jy4sMEZ5WOEfwNurfpb6/DPtlR0y8cDUVnjYKEGKROOg94mw6sUbwlNv5 LMb5rk/HxerlKIf34hw+GhsanC7FTBKiEi77mfUFhziSJlErQU5iaQk6+C/uXXD45snhsK/R 3tBWZMCttjWqIX5MRw4TF3mbAllszFXaO6IHC1zFnaELmOq2LXApctcBr2tD7dO2DcSmMfka K5k0OcQkaYSopJi5dyvzIoRX5wxji/kmjuAqIQjbQZvwS7iGOFTwF9K/yIX+/PX7j1++f/zw 9iD2pvmYKLne3j7AIyZfv0lkdqROP7z+9ePtG3VuFWxyXdUSG1mda4X9Z2X660dxnH6Ag+qn t+/fH47fvr5++B0iTq4UvMpllQU7zzN63KRijQFCsKfrcl6+W7pRe9L51wiVMwurnwmsTB+L Cm03BigmfdSVQUgdVg22WvDs3u08Ry5ZJg4Nd7JIe9RDJpKXcbALSCxLk8D3NiDj/Qui2lkX eCmZ+nzFfqpi/CyujEi9nK/HDfvy198/nJoe6ZVslAk/lQezRStLuHsBn2kbgYgDypje2NkA UI+BPFoWYIilToVYNQLLrHkDa8ZPMLA+Qhjq/321XHp1sgaC9jm8xhXLu+bFYkBw8Ywcnmci HPk+m/3mMjpSCR6Ll2OTdmipmWlipFDaRgNu9/vE8A6wkAOF9I9HZHWxIE9CTHDcECCemBr4 BkfgRx5RcFa1PBa7MAHlOr5GFyV7smrVo6j0VqlFC2pvImv7Lh8Bctw5ok4tjH2WRjufUqib LMnOp76DGpwEUNVJGIQOIKQAsXjG4Z76pHXGySaKXcwnvXAWDn55FhLFtRMEModLce2by3b/ NG1xAV0mvQ/dilJmZ9tMp6bKS8bPKsbrvRz75ppeyXcnDB74m6OQFjdwuKi5sALOKhUF9bUp q9x6Qaw/O4LeZ6GYhyPZu30dTH0zZGc6AM/CNzqnbJa2INduJVaxOqjFb3vl4/CyzwaLjAZM RsZTMLSLC2mzMHT6BhGMLuCZC1YYm4GJpzmPk13kAuMkjjewwxZmBx4gOKxwEw5WWlmDeDpf bL+OWyPEKO+b67F3VmwQyxUbM0b7S5isx0HICT51Q7ziCg6u8uDsAhGcWXZJQj+5k1n2kmR9 nfo7j+54hZ9833OW99L3vHXdiqw5d/a9PsGx8Z1nFjquiMmZpwcPK58R+nJJxVC++03Oad3y s+uyyeQsxDnvPtMprVJq3q+ZwFqBmVFWEMuYQfh2GiyHd6zng6vpp6bJ2b06nFleFC2dvzjg iSE4uvJ3q0NNLh7xlziidjlU1+Hy3jFYise+DPzAsZoUFY41hLH73/2ags7pmnie/5O899cK IQn4fmLeByI043vnJ61r7vs7B1ZUZcqnmrUuBvnD8S3rMRqqqefOGccuxeh4ZQcV8hj7dPxD tHsUF+laem8G5OLU0e9Hz7GP1OzUdK4Ky787MPm6Wx3595VRh1bEBr47YbgfdT9RDZNLvKtK 17yXelhrjNC8QpD0aUMdkw2UCaDwaDjtV4C6a+RT1Yl9z1W/egwoixU8PP0wTkK69fJvJk4Q ofOj8F3ieB4Es2Vy3bs/3gRn4OFHkTb47rVOccXu2kt4YuQNDhoH6MreRLp66h0yE2dVkeau wjnjP7G48N4PQud2J8TfknR+tJhax2Irr1ucmQ9dmWZF+FPSFx+TaE8914b6u+XR3jP97U30 fdFHQeAYiu/VSy20fNHA80dsei73Tnmma861lrHuSWLsie9HtA1qKZ1xMjZBzWzhR5IsaUfS aPFGQfXRyqD0jFc6ZoqaRhZnkGurKJvf91eUwKaE3oqCTOgUbY+mmlKhvn77ID3n2a/NA+ig kEVqhw/6kgD/BWM+Sscu8Tbt0BFQUzPW8sCmim+uqFYZXUpZdihM6+LHVhyz1zlqszECESRQ ga8SdNlE1iFtoW4O001gaKo2E1yc0qPproKpSeeudCWcsuwcrOFxSmsZkGxNmS58v0/MzBek oubxghb14HuPPpFjWSspaFExUyPkZkxHKDGVXvDP12+vf4CyfaUHh4sDM5I9NZLgPYBDMrX9 Czeve8HA00lUz9f8FuyjW+aVDIoCz3Laj7NoH9JvH18/rW+IlXivbOwz/DyxhhLr1SxlAv71 yy8S+K7yldcRxGWDzkOeTx1jR8CGcs9OuaX40SxCoA1dj34hFlqc0SxCBN2CIexhRcs4c03P EzeNJhEZntsapGt/sG6i4hBE3lR3CzA/FcbPfO0xN3cwfsH1RpxLJb77O07ZaWlQGp2DY9mq qAUxsrbawUr1FOWqIyRwvyMqMFh4WpdM5plll5F2AF84/IjxeNz8/D2rj0WXp44XTjWXto9w 11wv2e/69CTjaK7ra3Hc7wydQGfnxGAKqFBIuw2mYzrk8DDjb+r9OVftfq5mrByjMfKIRoIB /5A6N1aYsOKskNpxWTWmd0WxKdp5rKa92HXuFJTiIJU36k/0vGAS01r1qr/Ko2upHU+D4IJa teRHu0Ebk1MysUtZFeN2+8SvYpSxgdiJCckTH1jnKQDhdugz4czRdvRFx5JDHW40t34ujgM9 RhXkWiuaa0W0XlDvfx4xW4mkgno/ac2qYyG20gksxVfrDEKneVIZ3vxop7UTZ32nYy2vK3eB 2AAQ44qMmHaZThzF6bk075uaDGw8VJVte6mfj28G2pBCv68KNhM3Q/7nOQATUVeIHEV7BYqC b286r2j6Zn/xWJRUM2RW1a5HQ9vCZenyUxmBLmy3S9S2ZpN6iLqzqDJCH37kXNFT6RwNF0Zm Iw2M944nnCWPshOVllTy+GkVy5lN4GY8bEm6wosWeYMiH6jy4Y2MpqTejZH4Y8anY43WL2WN KhHJciS9xi+ttNhDbEQux34rEwEd1803wz9difeRNabX8POVKU3Frei2hZBRtP24KK0unNBj TYZIFQj2q+wz8a81rBkkgXH7SkBR12woTLVBnLJuj3a7GRNHa6cEbPKI9ZxdCtMc3EQvw3PT 2+AcgcEgPYu2wf3Y+ELUsg/D922AXp2yMZeWx2ZD3SC+Z/WCAqLNFBVDek1uUBTu9SFqOePL ISTWp0HsUhCfaonbp4wkRGXXNiWmkyj0nbzMBG9tNMeDTL8mSl9UAnwW6WgjDoGCRfZsiPv3 px8f//r09o9oAVRJxouh6iWkhqM6EcvnbYqL+QCaztQyg75RVYEWueqzXWiqqGegzdLDfuev UyjgHyIFu8D2tE7RFSfMnReb/HU1Zm2Vm194s4fM9DpGIpxkccYcR9yTnVmdmiPrzcGwHOIh btztC+i4pw8iE0H/8+v3H5uhT1XmzN+HyKRkIUekB+2MjqFVzTqP99GKlvi+9XXObNyf8wAT GbqskRRuXqQApWVs3GHSRaogA4v4zHKWiqE02DOBM77fH2i3U41HIX3I1vAhoo9QAD8z6v0D jYjF6rfPxnT+7/cfb58ffoe4fzos1r8+iw/26b8Pb59/f/sA9o6/aq5fvn75BeJl/dv+dDjQ tqTJTQ13bdofrK4FinJPQU/vrQbBODpbJE6BQRLu7Q4mfTQs/LG5pNbKpQJu40pmsIBqGdKc lCqajEUsODtdZGhUrAWwQNlmJzrHLrEbZbKQweclk3H0MMhFKc4MuMTiFHi9XUZRF8/U2UJi Mrb3ao7aTi4IhEgiVQrR0p0srCYFPomIFbdFL1hIctOCBZlVcxUVx5HTY1HPS6RBrdosoGLt y5UVB+aWpD7am/oeRYujwLfrUj9Hu5HUTUh05DhjLSLa1WvctloSdphaAoRPcnLRylIyKI7J Uovh364SkjH8JTJas14QlqGN8lBhFZxjllBwAbljLLNz6h5DV3V4mAU737P2sbMMVV5Zs42z eo6xjagd/ZKeBFvyoCihHldcHtDL3WrVl+TYmckQmrYAkjZcInE0Ca7WOsNfLk+DOAF0mCyj LE3Htm5xNkt0eJI6lTgX4kEFIF/r1WLhfOFBglW34q/ag3NWwNsTSySHf4R0+kUc7AXwq5Ii XrWRPSk95KyBh2uHYPVJdVAVV5nNsenL4f37qVFHRZS2TxsuTquu6dKzy4s2rZeVbn78qcQt XWNjT0U2zbACKJENj7X58sMlV9mDaTi6RtJ6d9GbrIwQYTdT+QA4rLluDCD+rXckQJwxEYzj gpEupDZlFMsZzneWQy6QVKRaiyYjBKlbl5Y91K/fYZBkN2lzZcsNqRaR5aZoAWp3CHekQhnA /myaKip++YpEGJsPryheOChaJCHqDBw5Rkr6KJ9i0sHxcZqbbLMmpubpRNOjEO8hBnk6c/p+ WfNMT6sPMDvHYuLQg/KherHLcUdSk+h852R94lmeQSovQK4QiduRGbxDYkbG0DQd+Rvlo2zN Hfko3a9qN0oFgFhec5dtA/Co1zxKsVq6CwB3NlAao8M7APjICRQhA4n/41DKiu7K/J1WoCD2 qo69qaocVzDA0CbJzp+63jEHta77iGsHxFUjgJivqMrDUPyVZXblFqh0Fa4FLDzBVwKWoj46 wrjJjhfy1FSyAeckqe2qxuqCS8aPsgpp1Brv7EwZI3Tn/Pw9I2aVjB7qe94jrkTTMVPbBCTR habEvpAm/mS1QIhdgd1tioYjywB9eZ8I5dCtesUUyVCjhZQVudvMMz8RZ1cvsPsS5DDOGkq9 qmAiwdm9ZC3XmiZNCGi4EUABt2yLr1dHIVycDEP5tDXleQ+DhDY/k7jDP11j0WqdWaQ413QY 2WpMqkeAfMoKY4EDT6xMOmg0hVXo4kFCTZtVrCzhstBCxtHa9YynhlDNRgiD6aiWEhRXKSrS xAWQvrjwVPyvbE8pLv696DQ1r6yBCUDdTif7G5qbbZ0jYcHQklHmFPAJBjTSl6StfvJWCxyW eCH+oSsUucw0TQvPkKgwaLiPqyIKRm81PJxxO3hb08PUiuWx0NuWr5rR9u3DH5++/vEf8sGl XqxS+yQRO7dYMGBYkBLeOo+5XStt5fw6iAYm+cCx+aAiuyCNq8EPSs5yEMl0ODKjCPEXXQQC lJi6qtJclZSHcYBWhAUZ28A70F06swjBTmzn1IRcWOqcyvxY+wmpsJgZ8jTZe1M7tGRycHaI KFXNzFC1YjHGepIZqrM2CLlHuYrMLN371KeSCjptvHZjuFAm/jPM2eVUIcFlQUZ/75FPv80M fV2SzdFhl7da85h4e6rQJiuqhjoeLgxXYsRwJPIv1ANFXVSh66Gjbv5O9JZic1H2zDZPtC5e nhd8UzxACFadLh0KqlNX9JqZSccRUbN2lQX5escNbC2V6g0JJrQOmElI4Fh0lfXOqDGvt+aX SjkdT7usJwrUSrkVAGovojSQuPZbwxcYTPvmZTJiQ4Ol9iq4ztZXB45kR39AGa9nI/Etdg+V OPHi7VEpeCKP9DUzmpVEkUcVANAh2vo0dV4fIn+/7nxIOsY7Gjj4xASQQByR/Z4cDmT3Kcjx UiXi2eqBp4zvzIjqNzq8Hc+PQkqvrXdT55Uki/2Evv9ZWPI6iu6yJLutZUO0wN9TC1kN5qbr is/vURA9tn73004L2ll6N3IfKRaO89SWGVFRSXcsJfAqgJAaVvY/y3wsiesOkqtL0jhMt6bi zBXvPFdRCt7asG9cIbHqLCAx+G8gMWVuYHyncunWxn1jO5KCwQ3Ptmb2whYnG1WND5tFHLYH /o2P9uRb8/3cGIgP1E30mmvrCx2oCWeg2317uDPlDcafbXq0tULc2OLNaifbI+tw+KkhcTg4 hi8/x4HnmBSARY4el9jBiYWpo1ECiwNnkyR6f8RItnsDRjKRe9CMhvfWHWDax1tZJPc+sWQi 9k6FjUTPY2WLSRWb1yGJqN2jR1fQiFzuAnLGazDakmT0tdqOqL+GInfeZ7HYbm+iwFW3/j7e ZOvhEfq8qMgYFzMT8UqzhUxVTgzlBRVi+RbMq5xYVM3UxPy6wSMnPo9Rs+hIdaPB4G+vOQYn GZGJqlE4K2zqtw8fX/u3/zz89fHLHz++Ed41BQSZr01D2EVUcxCnZ6LBQK8bZL1hQm3aMU71 Q90HscNz/MYSR5srgmQg1qu6T/yQkoYFPYgpehD7ZNuiOCLPwYAcqKtpVDUyy8SPiQUC6ElI d1Sy9+/I1n0UHqwJN5u2ucbBqgJguZiulyEhlMcVdbT4P8aurTlSHFn/FT+dmI0TGwOiAPGw DxRQZcZQ0EBV0f1C+PR4dh3htjts927P/vqjlAToksLz0u7KL9E1lbqlMjlAXUCC1L34dC75 89KzEvMAlptwg2ISeNiINh1uZayY0CczR3MwlrDzJ2X3iR/WW1F/nTY33Nqx/9wfsLU4B+eI c1pmwmWRt5pYihg63+6/f3/4/YbnZo03/l3MFu7W1RtHxB2ru5BOX74KOvV2u5g3sZzWMX62 ne8+w6XfqBk5c3y293JlB/h47E33wQKTVmF6KeSFp8Fre87i5PyatmYCRZnNs6heVtSwmiOH Af54vmc19nL06bbwEXwd0qC31TU3Clw2rcFUNccyu2RWzvKU0ZWh9UhOSNueRn1sUduMpTRa WYgrQFcO9WjJ8thbacBOe2lyV1LiZEeTK2GUopFyk4lti9MwJ0wtNPuziRkXVZLYjFa396e2 nzLczbNg0JZcgjS03KOsmf7nPlON1zhRhGBDaD6NjGSF5waD1168cPJlpGFo0Lgz5qk3JV7e Aul5jZUpaV9Gc8DX+XTIxA3hMgs49dNi2sqpDz+/3z//bpjgiFSFR74NBZWf8It0MZKuk2XB YytUbJmzwsRsDG4sHjioMo6WIdfZgYaxc/gNbZkRqnqpnDs48TzVYhxpMDERHHK7IbVW4v7z U1vj5rEXEux4bIZ9SijyWRLGfn3FngEIVWr5eOLk39LTl2kYsFcfHLcNQKV6CpIdtiKTKI0D e6SKlYXroy4Lh5AG5pDkjjaM0ScdzhnU5fWr1dnCRwbFHByueOITs7c/1SPf3emp2V5nTDQ0 dcBVnJiqLw1s+ZDW/+WHA1AY5TslZKD2vFGxmenWKFSrh8mUNLYfAw/wqDfImaUQPPoTHank 2bRluuSZLz3tqi33wh9Uma2WfPRIf9YJgZ9YiwehSXxzksuCgFKzg9qyb/rOqs7Ygb83p5zX zTgUWnwmpC7CX2u/x+oov0JQs8+PRzbDpQNquiPLkt2dlSnh6s/2lf7f//MoTSKtW/erL60D uRvPRmnCFcl7wrSe2jY6RrGzWSXhMXN961+xBdfKodt7rfT+WKpjCamgWvH+6f7funvc6/x6 AqJy4E/1FpYef7C34NAC/IoUBagTAE/rORg2qPpF40HdG+qpREbLrhC6XVY5jHtd7WPHExqd B1NAOkfgqHwQsPVa5qx3gE1+KkfojXjKWnBhHfBdlaWFwzOWzuTju2pdxJQNObyKndILerPD MYjVqd6ersTVrgLBYFMlH+AYma0423ThpwQK37Goy9Pm612N27wKMjD474A/8VdZhdHAVtX5 E7GlVMohhMJTDRlJQkf7yILgIHi8HRrVXFhFl9U/Wk2B/tUG68zHEyqoLtS7Ap6Lcq/6K1Hm pWLfHKXKSIxuIiHMaY2nLr7vz21bfcapixG5kadEb691g/kBbCFICTAqk6vcX6d5Nu1TsIE2 Im+MNCGh+Aob9XypNYGaPGunORLY+g5MgHhh1gfGTDYW2pIUPJ+FiDWwr/Ectz+y6FOaDTTZ hdgadmbJdLd2C/lKPPXwbKaDclIP/VU61SZdDdkuJmfBZuWZoSqOzVRcAjtfaRJkA70aBXlu M41Yp6d0JiLl3n8CUcVkdSn2vEWx6b7uhY7bl7m7H2BKp8O5qKZjej4WWHnAxWjs7bCdpsFC nJ8TdB8wt84sCpaolX0L6aJ9OPPwoYEuPWcO2GWph9gzXV81renx3rGBagii0LeTgQruQtUF 9YzkxVBkbCkqWCL10bDycRxHSWAnK4w46v3e/ohJyM4PRweQeHZiAJAQKSIAsW6jpUBs94h1 +yLV9T7YIQ0rtpGJdoo4iwMXMzE17bCV0cIn3b9jItUNoRfgt2pzEbqBqR/8/fNSejYlBLh+ WAeEe+KYkzlnve95BGlzcUCBAUmShMo9G58njJ/TpdRs+gRRPqW61ePzCCdu9++P/0aihi3h mnNWWyVThb7ztQtiDcHWmCtDDS7N8W8BwjtA58EvanQe3EJW40GX2SqHr45QBUiI6qh8BYZ4 VN96qkDgAna+I6md7zuAiDiAWFPkOoRdty8cYJSIdkmfOY65F46xnA4p+DQ9sT1uhRRMmJra 9GFsfbtJ9hC36zJg9ZDQlFZpV+NPkGfWvI/Q29wV9+EBj1UoMUtOwkWxgZXhHcTzxEp2AMu4 EH1HonBQcjjiX4dBHGK7mZnjqLvFnsnSF7IjzMvycRX6tK/tCjGAeH1t98GRrZpSlEwwIRHX QCke52Nmui1vIx8Nm7S0775OC6SYjN4WI0KHWyKuBW1ooLFd/t+yHcGaka10Op8Ql//IOXr3 qWBz/Eb5xfwU2qURAFIgCUyaMwETNN8CqjA60yocbMZHhhgAxMcLuiPq5lgDHFXbkQjRbALw UakF9/MOqwyVJ/JQKzCNxU+wtuFQtDULAUeC9Ag/7YyxJhBIgOhqhkSoMuFAkDiAHTqWOOSI oqTxoHYRemETdDaoszbwNlV6XY1dcYQRjZVwyHC/2etsk43IaK3qKMCoMdKijBpgRWf0LYlg cOz4bEsWqppiAlxTtLx6hCmFvtUfVZ2g1UywsVYnATrg6yQkqN2dxrHDBjwHQizVNqNxgFq9 qxw7gqyDTkMmznjLflA9uyx4NrBBiHYkQPFmXzIOtkVHmmd1S2ICfRoQdBHTZNnUUodXs7Wa BxommsJqa8uJgPnRtTYnPoNDtQExluwzS387YMqYkQnSl4wc/MTalAHZ1qiW7p3sFPO6YIoN UYYFW1/sPLQDGUR8dAOtcERwLINUrO6zXVxvINiwENg+SNAh3g9DH4eb1a/rKEKamakrn9Cc quHXVqyPxX0wBsTY8pzVmuK7m/KUup7tqSwO58ELQ0AwqRiyGNmmDbd1FqKTwFC3bIu0kRNn QPUQR3ALBYVl57A6VFk2JyHGEPqIBr6UaUSjFAEGn2A7pstASYD2yJUGcRy4PIuvPNTHjHNU jsRHNjgcILndLRwIHHRkgAo6KBow8EPxKqahGtVDhyLNY8YKRSS+PaAfMaS4PWCS47ygVxnU O3o+RaSa6ydJYqM2HUoIFIc6kZVMRV10x+IEfu/l9cDETZqnuv+HZ6dpnZ9bHOh7/xm8diWP TAex1tWXwDOeF4f0XA3TsblAmOV2upZ9gdVNZTykZcf0c+qK3oV8AnERIHpptv2JO3WEcbO8 wACuVfg/HyS0Fs5uoKI+VzyOtg1Ji0xJ5c5KZuFQvf/U40xGisFQWtfYd3cB9tkqv22Rdtsc 5xMtN7JeInIjEg0meVufAsyEOFC+nYtddnfXpsmVKkkkb+ZLdL2i0sOPOzfxCNtOECzF1/xl hNn3h6cb8BH1TYsNwcE0a8ub8jQEO29EeJZ72m2+NX4GlhVPh4dy/vryDclEFl3evNp1AhvZ U283K9D7TusqWQ5nZrwow8PP+zdW1rf31x/fHp7f39CKz4JdTn2T4UIlc/s4PWGmc//t7cfz P7da2cWyjDI2bhu7gdRLwhXkCX/6cf/EGmKj2fl9wgCaXW1B53fzZ19GkkSx3Sn8JQ4i0bP/ a2xW6fdM7/d9udd8w6tmnMDScx9iGqnNytuG30kiX8+oThSuzgHjkTGUL1clYbE5Ci2ZdMtm JpUpUiAgayKdTqLoWengXnCMzGTSIK8l1q5XFKguW2wS5izSb4vjy2OdZlNW43Ouxoi/3Bcs 8k58daX8x4/nr++PL89zxB1LNutDbvgzBcp8iaxTRWyiY6ud63L2PohVF7wzzfC8UfMB1IZ4 0Hb+UToQGntYiRAna4IOEVvBFVfW1Bh0W2VWcTnQ15meBWvCMPFUtwCcOlutGmnw612jjOLK V/OaDXTzucpKM6OFKQju6oZ31/LKRfuOkwPsNGBBKf4Rev65onYnwtSI+upc0JCYOck7AXe1 JINoPftTV8XENI19gvqWlqCve5jn1OqEP/wEULyBn6o27bEBDizHdCiuTXc33zOoXZr5wWgK liTq3tdUwJajlkQkMZiVYJAamYRsygG6lsRtGbENo3BOYAJhOBrA7QBeNvsy07awQGVlM0zk JQgBzkrV0xQQet2MF/IrP/URwUQIQG7xndVNrmp9ABZTb4VGaVtrTxpWoiXunByhnmjE0JP2 BH+aQxJMBRxXGytD6BpHAlZf4a5U/ZhyoVPUdF3CNPFiU51wKyUkKZqYr+0sHDvW5egQBbqX j5m6lWRxOhAfD3VRfBlFSE2tHSwbFCBeyrboeLgBZ05dMZydYJsdQqYBcFMFzlBT3NSHJy1s xPVyCtsHg2a+CODEO6pa1XLSKRwin5q17IvM5Z2Vw+UujkZkNuzr0PPNzuZE1/qAM9x9pky+ iVWKGo1wySFug2GohXQ/hp45Sad7CB43E9dtliA3A+YPjucgX0+IBfxQP359fXl4evj6/vry /Pj17YbjfNvz+sc9W8Hk9gaCszij8QrU8v437wf+eo5Gown/zWxH5aqY8VILaFroYUtpixcr Jo3GlJpdPYA/0A3hT6s6RU+D2j7yvVAP9s1NhnxHNF8ZutVRx/nVilFLxAhpoRMfu+KZK2W9 ylGAMMKNWpSk8QPVhYE6IissDInvUuHK+xvsM+K4F9FYrJmeIWzm0o9Vh2u18wLPUgsqQ+Tt bAYl3Wvlkzgw4vBwaaqD0FRh2qMklW4+YeLE+b2RqqrlM0GtXaomuz2lxxSzfeRrZfm27E+E aK98ZsDwDbmsUQl2ocdbog599f5rpvmeSYN5EqFRi7Yz1xriLBejYYtZibjXwebJ70qz22V5 tKUp1OuO+tYgEpGQ4Wmee9aTLLrtnP4xoWZu4Fy1apkU6X5DV5BDrlVzP8DcYuwdLW+AvK5Z bvrw1oPiuPa6y/FhcYRDVS1c8kwyfZKvwKEcCybjTTWkaoihlQGCqJ1FhMD+XKvmqysPHPXy k16Vaz32XPjY+vToUlIaV03R96crD+zgaRRiBbY39wqWh0GiTTcKdmJ/8GezCpPYwX/EtXdG mlWY5KCv8ga74rIZmSCB+T/WAfKEAm10cVLxUWH43n6zGMv5AZK/Nao0yHwuq4LuN7Mrl7WC VuSa76o/qJzT36jGQlSlaSA+VulDegqDMAwxTLcAX+lig4rlI5BLGHh4TcUOdrMSZV8lgYeW h0ERiX10UMC6LEZryBGCIzQmI56aXOOgCN5achWI1rsSE/VmxYEnUh0lrpBtQ69joTrdaxCN dokTihy9JHevm6WdN7N4iWgSoi1ub7JNLAmc34GRjKu8DHWYSitswob0L3DRZHug1Vnrs9Wz qzhtuHM42FGZKA23BQJYIlQI6/ZTnBBX77G9v8PmUGdCnR+vLO2+THuso9yKrD2cvxQfTxrt hVLP4UnP4PqojMCjb2JWkF/pdG19+0FG4ilJi0aXXbmsUwQF0s8SFGA5UbAhtlpD6eIAA0HE gwwUWc8MbKw6stW152gisfjbN02PR8o1OS9dcdifD3jvC5b2+lFCYjHpSIKvi6dLjZ5NKYys xl6EzgQMomSHqnW2lwv9SPWCp2HWtltHCW49qDMxrRDgbY1t051sqJMJkylxaACO+sFHKwqx HzdX6zgb2xp/VCCxS8YW1lb4K2Vhrtv5rIDcsCGfyL0XjmgbPw3R9mBdZmy8GaFW31tWZads 4zoItZQ1OdsgrMSym07FAmh2HVxbzAhm2gEMkfLpSv/t4kqyb06fsTQ1nvT0udnOGMxnWkcW Ndv83O3z7QTGukVLXooXWDbQZXVtA7xNIaByr7VzOpSs3+pmKLQ0ipP+ew4eahbALlGXXjUi q6MIGqZWvBzYrq90VPgAEZ/vzKaCaDo4P7g7VHO0ghlDmxR5lw6B2cXogQMAQ1ek9RdVQhn1 Wp72zSmHkpv1OTZdW52P4BEETbA8nlPdaxAjDgPjd7VCN4a+mQsaOZJ14hxsQyutcNBmFVW4 yEH3BDKyn9ZC59PoaiMeq13LUoZvH7r01NfloEUvA7jUBZXblWgqNZvGfTNO+QW/4WDffEEf P8orgzU3oJyaoTxoHryA2pYnizAVXQf7ndNvyplLAcFsgQH2z1qQbyCK6E5pg1GPPkkB+qZC cnO31IWnLByMT32I3QRwjqHUkxFeZTWS8HSmJH0GK5Rz1RcUcLQlgaVLyxPTTnlzNdm0Jlir vx49qQAbrxW+mpnZ9nl34TGX+6IqsiWiMndtOR9Mvf/5/UE1wRCtn9b82t/sAIGyAVU1x2m4 uBggNuwA8ujk6FJwiOQA+7xzQbPfQRfOXRaoDad689SrrDTF15fXByw6zaXMC5hlsAMP2VAN fyJZqcKeX/brzZOWv5aPlv8SRvDlO5waajdKZk6QAX7w6EqMp5Y//vPx/f7pZrgomShFZpvL Kc3TdoDJ34/W/AHMP59SMKeoy1ODHp9yJh4/vC94AB2mG/sevDmq8gtc56oQB5xoHZBSqjJr 37eJ1oFhJbsdv1QR0pOVGJfRzjXMpk07RwHimYFtHBzm8vzt9utreIyRnpqpzgfFOGel6/57 LrtqFWVhS+VqVJPNkDMKzd0edIM2Nn62UhcNWme/9mwQ3oA0yaCnZo1gjDIV8o9v1kBSDR0F 6f756+PT0/3rn4hZl9Aaw5By54rKR7AOSK28szEnbLsrAi5i2WufGQrgfCqW8K7Zj7f3l2+P /30AcXr/8YyUivNDmN5Wu3JSsCFPfT1MhYFSorpasMB43Eo39p1oQtUXrxpYpGEcub7koOPL eiC6UZmBGRYWJoqagehMJIqcyfv67aKKfhp8D7/vVJjGjHjabZCGhZ7n6Icx2xknA1rBxop9 ij7WttniAZeDOtvt2M4wcNQ9HYmvO8S2RQH1saCyHTLP850tyFGH0ZjJ9lE/ygIRR20o7fqI taijLYZzmnjqMzF9qBE/dEhnOSS+ceOuoB0l3pZ2X7op8HxHfG1N4mo/91lj7D5uM866ZxXe oXMWpmZU/fP2wJXs4ZXNzOyTxRifXxS+vd8//37/+vvNL2/37w9PT4/vD3+7+UNhVbR9P+w9 tr9X3hMIYuSrki+IFy/xfiJE1TWFJEa+j7AyqrYP4msENgbQG1sOUpr3gXhihtXv6/3/PT3c /O8N09qvD2/vr4/3T86a5t14Zy4cZoWZkRwz9uPFLs1hxgt2onQXY+c6KxrMFvSM9Pfe2Rla utlIdr7DVmXBUceCPN8hUD2oAulLxToyiDBiYvRPeOvvCNLphFKTuIehanW6RxIzTSEJmCAZ RJjXPN3p/txBnnGiZzJQ4nAZBvil6P0xwS8u+PdSS+Rw0OtoVsEjuiYwJUEUAD8IFB+nke9M WiRqdI8gxnoDiZ73zAYC8XQOn6Fnk5v1CRtR7rqCe/PULJDohdhXBXq4+eWvjLq+ZUsOU1SA NlrVI7EpFIJIzCbnkuo4opUj3TWaq2gHjihN0WO12416IU/jYAs5G2ChVRwYTUHoGpN5uYfm rvd6pjM5s8gxkPVsJbU1c2b0ZENsRb2MwZseEjZZmzJRZG4ZhfEaRJY4sgU18cw9KlB3vrl1 7YaK0MDDiMTQDaBtqaGtcp9Nv7AVbHIkO+6ibxHLTE4KGzoWVAJ1GDuv7UbcOkUyuHpcaMJ4 nrLSoWeFOrH9+b9u0m8Pr49f759/vWPb9vvnm2EdQb9mfC5je72NojOhJB5qpgFo04X64+aZ 6OtBo4G8z+og3JhoqmM+BIEzKwmHel6SGqWmoFZH1q3uzPiAdrx65zJ7piEhE2sbV5NDAnwd K94r9vm2gtJzT9An5nKAUVsJgIokXj+LHc9Nn9//5+MiqPKUgQ2L1UV8FbHT36Foxy5K2jcv z09/yoXir21V6RkwgjWx8jmN1Y/p9e15j/Pw7agwYS6y+TxIHn693fzx8ioWOWbTMk0cJOPn 39xidtrfEuzpywIaS1NGa4mhwDnNUCRg77LzrHUbJzu7W6CBniNsxi19WR17eqxwe90FH92r gnTYs7Ut6uhKapgoCn+auZYjCb3w4kyV76KIe0YA3R8Y1bttunMfpMYk0WfNQAqz9W6LqjgV ljxm4iRrtSj/pTiFHiH+39STQ+sMZ9bgnrVqbIl60Ona8oiXuC8vT2837y8giw9PL99vnh/+ 4x7q+bmuP08Hw/BYOwiyD514IsfX++//Auv59UxXpns5plPaKdO7JPDTz2N75iefEoJX62V7 vgTGFUfe1doPeGhZTvm+xKi99jwT6HnLVOTIvUAaJ8s6G3fxiEa6X+G+qA56nHfA7uoeer/V bWDXr1gJ6n6YhqZtqub4eeqKA+4TBz457FkpVxcAjuJUTZpPbMecT4eyq6/p/zN2JUuP4zj6 VfI0t5nQLmsi5kBLss2ytl+kt7wosquyqzIma4ms6uiptx+AlGySAvXnIRfjg7iCJEiCgNNe mGVZlzbtWLeTeuC6FNWpgg/D78QJ3TU/0Wcsls+//fj7T3hC++3DL5+//gH/+/GXL3/YogVJ ACt0AKhpnr3KzCJ444RRWLF090Gd1RU7z/zh8rmOwIy4KL7Ca81kbJcp3BiV2FR9W1fMPCQ1 WU3OK7Sc3ZRXaGebcqkaW5iUn4PqNp2q1hFwhTTXStgfDKyrn84Iqi9//vH1098fhk+/ff7q FFwxouuDCQ+oQboaR2hmBnER08cgAIFt0yGdOlDr0yKjWPd9PZ04muVFeVH5OOQ1DMLbpZ26 JiOKrqvkDByN6GNizxDQLHXDKzadqziVoTV7PzkONb/zbjpDIWCKifYsiOjcgPGB3jsOD1j1 o6TiUcbigL6gfX3FGy7rM/xTxBF55LHm5MVuF5ZUWXnX9Q1MVkOQFx9LRpfzh4pPjYQytnWQ Bh6juBf7mXfHiosB/b2cq6DIK49nZ6NHalZhURt5hhxOcZhkt82qGR9AiU4VbCEKT5fON8FN VdC+rY1EgWsPm8c38w2HDR+TNCc7HQ1oumYHG7xTYyn9L47+yrDISrytQzqKBbaF5AjoG97W 96kpK/xvdwFJ66mk+pEL9Ep9mnqJ5vuFvQt48YkK/4Csyijd5VMaS/Ki6vkB/M1E3/Fyul7v YXAI4qQLAjpx05Ga7C/lSZRjXdNeB8yvHhWH0Tu2WR4WpHZI8cIm0leMvjyrpvjhFKR5h/rz ezI89t2+n8Y9CH1F64UrARNZFWZVsC2FIqvjE9setgZvFv8Q3M07Bw9XG7zDstuxYIKfSRrV BzMEEM3NGJ1gzc/9lMS36yE8eiqqjLKaNxCoMRT3YLv7Zm4RxPk1r272K1OCLYll2NQeN2Xm NC6hA/kdNv+5L5Sqh3tXkLvaFzParrHynkQJOw9kI80caZayc0tXSA49KAtBtJMgl9tNNLMm cStr5mkfxTMcQ/J+zWAbL81jXl7z6fZ2PzJq6rhyAXpgf8dBVUTWbcSTB6adoQZhuQ9DkKZl lEemfuIoBebn+5FXR1INeCKWXvHaxuy/ffnpZ1c3KqtOKB3cKmN5gg6VkCaqgO4ivSxNQOqU 134bRuVgQgs/Z71s6yNDT1Lot7Aa7ugy4VhP+10awP7hcHM7prs1zw2CV/5QZxxkFye+0xjV OCOr6mkQu8zzbMjhSvxpgboLf/iO9rOtOXgRmNEEF2IUJ3anaVWJ7E954h16wSqzGFozDKLE Tk/24sT3TL/5zLNtNHfndAen7lQVGyw5hyEJnYkM3T91WQq9sstWiByqMBJWWBJEtDkUTBCs u2ex7ZPVxXP6waPFVg1uCriBYNU1T8kodkpqKQV9Jk7shKdyFXc0gQXmkXjC9m5xZljZsjnj eD0IzWxgG23ni/tqFMimgSE4Dzc3a+Ux7upTtRFtqv06WdUGblI6QotX6q+lX/1kYzkc6aft atDfxYGyO1W71DaMLnFkKHKSdw9ETvddnObG9mQBUBOPIusYzIRiMlCGyZGYQrsALYeFJH6T 64KM9cAG2zZ6gWCtS0nTfIMhj9NxpVE1Pjfgagxd64g+78K21pGYj4e7m2hbVj5JkLwSzv6z vmvjSDTWr4UUpJo88rqT6kBjervw8exwYUzskXWVckCmFpzDt0+/fv7wj3/985+wLa/cffhh P5Vthf7kX+kATRnCPkzSq6jLOYk6NbG+qkxXDJgy/DnwphnRhNMFyn54QCpsBcA2+FjvYYu3 Qsb6Og38XjfofHbaP6RdaPEQdHYIkNkhQGcHnVDzYzfVXcVt1+MA7nt5mhGid5EB/iG/hGwk LC5b36pa9IOwilPVB9hugJCZrnyQ+XpkGErd5EWz7oYfT3aFMDLYfOwkrCTw9AKrD+PjSMrM L5++/fTvT98Ir2fYLXwcL1YUKCAOLbURQO5X8G+THyZAD/8DdllRYO9/TDqKHP0pTIBuqa4j rWcA1oPSh2el9GkiNnRYKXdSnszQFZrV3N2VQxc7JdBEj4+LF+48on8Br541wZFf3YyQ5PXk suArU1YHp3PjuRltBgXLCSf6JMH8DQtlB7tYK4EFfAjJ3y61M0Bm1FOuGbVCVGBxQUU0X288 Sa7niBfwrJynATTXuieYfIT2K/MnkU7T4fOM+dielmI1lVoDnV2ZHd3sSdzq6JmDlWVNOWdF Dm7PNPB7im2Tw4Ua0hdRAF85FSgPBbfuYXrldnedH2Pv1CSuDp6hde37qu9DK4GrBE3fbjIJ 6josjBaNjWfr99Da35RsbLn5aulFg7WUwYJ8tR3rWmB5EbKnLjkwpzuz7AuAdAtXs5g4TTp4 JJ56ebtQtqQnKiUmpSM25XxPMtZH9B3tDi7l2sqTVivKy8GdmC+VR2r4HvTEu0zSwJ4MngHs zVSWSGh0UhXTUaxteVLOQDyTQI3HGn3rjga8MI88l6G4LI49q8Sprr3DUwg0AaEe1asGym23 RbhqtGygVroW39/B9sCyB51pxnMI2noT+J6HHydY3j3pH/bmwQSp5Gl3xp9+/N+vX37+5a8P //EBxGx5SbK6X8SD17JhQsxv/l6zDyJNcghguxtJ88xOAa0AHf14MG00FF1e4zR4u5oSiHS9 U6DG+oJaOw8kyqqPktbO9no8RkkcMSsuOQLL6wGybZGBtSLOisPRc4E21wnGyflAhpRABr0P skvZ4yurKDVd5y7LgaddX7j2pKo8rBLo7DSZgmZHVFaEwQVbuyxZsaw8RLwg9eL+1pix0l6g +/LXqEmFHhECukQKJM1ADB7t+MZTWSuA0QtZv643Ely5rDFa1uME+JXlNY2CvBmohPdVFgaW j0sj07G8lx2l4Btpq7Z9eQLfHqfL9zAhYKACY9FST71o7X4+WHkJd3/sbamfM1+ZHSwpiP7S mdEknB/aKZVNGsp2RZjqxgw9MRN5XRbpzqZXLau7Iy6yq3ROt6oebNLIbi1oxjYRJHcATV5M /eGAt/s2+oMOxO5QYD85XCQOUbO9EO2FQBMCoiuXaqx8dql6vPfsDJmW55CwPk7MiawG8BVd dwpoiZF38uxJYxXA+Ulcvvd8WMpmAv2GV06ABJVzy4RcV0rUoLB3JflyE/F2uCRBOF0s99Kq PO4LMEVEKxlzYCKR4cNkcmZWGciB0YYnGhUZGZJKFV29M76EWWo+iHqV2pFZ6JaWddE9cQs4 lNaxt1pjT9V/sn/99OV34xEaymvFHAGu2CzETrsiMNaa4K0dMmkp3de1v4mQbUAX9sqyxdtV yKYuAyBj1ujH8ySsD3d9qOBH2JPVjdtKLw5na+DhwpnqO9j0acO7VQJifWed9JW6ZEEYBv4y I+4x/HYY1Vubd8sjeBykybo0y8puLANPUVqnZDrDWKj1XXqQAfu16THzj/X/ZIk1GAZuD0Um 87iMrAhHBnWSGPYX5I7LEZeeBI1VTcaLioBgtRE+a1VH857GQfzCQnfcIblknL15yHoE2IVX SYkwipr1R9mBj7Xb0Qic+MEJZ2Mw7MvKPXRavht62ozFwE/bHBKE0/vad2G6MpiuyMBG2H19 adcU434soTXsBfRvl21ZHNcIc9fRmaiC6vJI+EExVPxAwC1GQBjcVlyg8iOoqHkUFu29QHUa tNGS9gPlfDXKNEvSFbsluCoygdtMT/I0mJq2DUH7+SAhvAkCpBLdgKuWuXARapS1xTEKUK3W 7qPsFfGZCrrICXwLnJXaPX03MbUn8Uuq2VYtJ2MVWlxaQFZd1vLz2KMG00vfTNCWp2FJAn44 bbgvW9hfpkYerkA/jt1FrD7KYuX6X0y3Exeyse+KkKceCmSBJLyKFSxunbroWGVsYHqUaZv1 38sPavJWluqHb58///njp6+fP5TD5flycjZifrHOL/KJT/7bcs49V/cg0K5w9BV6YRGMU92B UPvmVUeX9C/Q5fd1U6uEhTdhNQ28k3S9VTBeHrhP0Vb9j9evoHCvRtICYsEvTsGRrmcCp4/m rY7T8F/+q71/+Mfvn779pNqfyKQWu9g+ATZRcZSN15TQYvyO1mJKwNlY+avL76b2sCmBVqtE GAQ7i8KAGrk/fEzyJFjGnKeQz1hhunWtBExsDhEW58FU7d9pFr/2q3Bl+iK0AXhTX2tP6LRl 7pHnaS/Lqz3LaZNkbChTANivX3//+cuPH/74+ukv+P3rn3bfz657+MXZOWjyHe9ED73bCAY6 VpV3z/Tkkj1w+TKQVYt3kqBsS3fDbTNhI42o2/iLA2ycDBPrcvUX6ctKHQwQsmlwoIDrFDzl UBzcE6nd4oQ1aLO8WI7pInkjqNJoJfzYXGoKPd7tyhBFUN6ZZM9UQu8Ud+bFDY2kz6Kf8qn4 ZRG49yqLMfz7QmrV5i5ozVAB87S02s3eMcjrxiqICbxZMaEWqgriM8HM4oOWo1gfzoe3XZAR 6wxGcG5JtRG/CLNJ7N8r7uwMZ532WyWG7F3U3VC9MHbYgkCjJZToGa6IltDQCMMEb999Xwrv lwBt5EnIgkA3iwSwxJP0I7T69UQHqnpP1LNFeOItg01AUAQbLFrtJxjOsBzvZnsx4rBi5omL YjqOF+JEc9Ga0UjYAWbL4dVR5NOkmKjWDJGt9fyurc6ooae71Yik2IrCe6yF3C0b5ds7mS0l Xef1ygPruTljiaF+CE6aNC0sst/XY9uPj3V59nXTkJuEpr81rPPvRRSPMpxBi4LtEnY99b5i gftq7DnR+2zsVOQObxvKNloCXmwqkuPn3z7/+elPRP9cq4/ilIBeR4xWfJBE63HexFdp85EY YEh1LSjXmDru9DBcBLmDF/2B1MJWEkMpryr0ZltWVJ7Ke+FGFKM4+oCr1SezdYiWVo6OPZsN DTqarYdLjZtx4yRm5qsOomqtLvz+0muV9OvXf3/57bfP39ad71RPhY9cDLntYqugwSstheag J8tLlwYrBjeThG/sCzROzYwqb1apw0k0UWhnJ+WLvrPRAuvuUS4s14r9atCsY97SY1Pyqa4w IOpqrteg2AIvL9ATuBcWabNYxN6yYlfelRytSdd5LGBbbsLXklpl0UxhwlMcD9SWeyrRGdML u6d19U75w7+//PXLd7e0Svdp77x0/vd23FoSFufVG2NUm6XQa/KM6YnQs8Uy+DyazF0ehiNz N9Mf/fv8j05x4LekVChlQd9Vc8ym+UgIB/jKGvO5mDWNHsDkYrsRu/G1GuqgUquy3NrpdNkT bQgAqygZYviOJPDMVoiXRb49Yalz5nAXEzor0IuY2D9ouh0nzMGcgLEmSsYzeDHkcRyGVLrs Qu1AFyyM85jOEbCctMqyWe6rs9wXloX+sH0uI+3A2mbbeSqIiG18uUI9jQ5oYQZHcZHt7/x5 5kEQeZDQjOrgItPptgH6srvuAlLcEKCb7IqOFQlAhNCjBHBOwiCh6SF55ghIklJPhQyGNCa2 TUhPV7fbM5KRfhZNhoSqL9Kp7gB6TvKn8Y4a1+c0TanOa8rUsvu0gDiiKrOvIrQV3ajNXk6i XB3eIaLiQW18Wb4FQRFfyZmkHHsxqavorSMjxSnitNm4bX7xbNVCcxCio4GULKOCqLcyL44k aqguVUBK9OkM0ENIg97kMrqQAOXbVU+ijJBwpOfEiYKie4qeh76lYUa3p09kut8J0Z0Bb7PE YUyXNE7IeV8hVGwig0FFN6e/9YR6tDioSWMJf04D1PHNEvucLEcaN+Qb9CfHPQoSUvwAyCNi Ap1vLrz6BuJRun9X5UC+/JWOgzbEHKTusokGUHQfPyEp+k6cpMdUjXVUd4JO6vv6VSRdq1rk ITWDAD2ipnu8CAuJ6ft5QUbS6SEwY6QWcJRtRi2vp4qVyz6ChqhrQjVy6LUCfYbgUWGwOSdy wfAkizgsatqkgMWWPuKa47hOZIzoha1Fiy1GJaAPSHdbK73/DHVGCClRSJzmREtpiJooFZJS eopCMkLPU4Blauwg1Fm1RnypxTkxqjTibQPX9O9VZgrAs/Iww4ipvqMQh2uOHrHRR0PZhhml XiOQ74hxPwP0sFFgQcwKM7D5FT3aENxRtzIz4E8SQV+ScRAQM4ICqKafAW9eCvTmBS1MyPOC +Bb4J769xAMbxkKmM0jD6P+8wEbGCl7FVnf48BIj2poAxgY0XUK2gB4n1BAfZZQToxjIlFoO 5ILoxBH931O5Ip26r5Gh5dHTopN7HI1Moto62h9lmoZkZZBOCwteKVErGNLJhsQrKOqOync1 BXRKSVZ0YqwjnRoOik7MdoruyTcjuyrNKI1Y0Yl5VtP9bbcjVDNN98n6jDpdSbDBxv57uMLw u7jSd4THuB53EZ7k5B01Gj6TR14LYp5wr1iUixEGf6twU1sle13SeNQ2/82eaCMYaVuJA0dK KaEIZNTJygy4EeRd+L3TKOBLQLQ2b1WYVneJexkWp1u7BmBIlT9X6tOyyDP65deLiU+CbdnI SSailNrGKiAjdUuEcvLtk8GBQSXJVNM8JGRQARF5gwxQlmzu8SRsKJKQbCZ5YMUu39pdyuYa RwHjJXUaY4D0Am4ykHPLi4FqjgWMwzvVKE+YeLyxYvC8xad5t8tKnURrEDYjMbkrmL+tyntI evB78omYRVG+MunSmD5b2PwcWOizPnlrkiDetlYEnoz2MLhwXCoWxtTWUQEJ0TAK2BHzLajR RUwfVyko2arorQkjaldwa4OA2pvf2jBKg6m+Emv0rY3IBQHoEU1PQy+dmCue1gQruh071aAn a/utGfG5WDdZNg9BFQPRgX4bFbQvJ506mQxR7vt0U5F92q5TdEJPQTp1QoF0T1vmKSknu5zS jxSdmIqQviOne0B2wWp28bFt7ziU2b+vD4qADjpisWytA8hA6bRIp86VkE7pqIpO90GRkfK/ K3LybFMhtGcri+UdCSp2dA8X1PmlohOKkDKM8tS28NS28ORb0OOroM5lbh4zPUWnR0BBbc5u bRFQxw1ILzwyVeQB7ejDZPHE67JY3pFMwXa7cGs6/9jEO/J44KO6ri8ydMdPncLtUs+hUU7t uhRAbZfUyRC1L2rLMM4p8WqbKAupebSVWUztBBWdylpm5E6wwxgVCdlxCO1IR5kWB9VkGiCK rQFCPuXAMtiUM8s7pm2XYH2iNzw+M20DtgG98TmObDgtqH5wy6u1cdSJW+bb8HPaK1uOhwrO 3B0l/bwMGEdG7Q4vJ9NWENN7PdjUFmp/fP4Ro2JgcYgAn/gFS9BBL5G4AsvyotwHu+Vm5Xih RobChsE8fH6SzEjJiihsv1yKdsFXoZ6E93Vz5p2dyL6W/TAdDg6VH/d1p8lW+uUJnSJ70i9P HH497KTKfhTMjjityZcjo/bFCLasZE3jJDSMfcXP9UM46asXug4NGkHyaz2JfeAMJgU/1AtJ T+YgK8e+QyfU5ncvKrSKT8qmuhUObIINcxofQx+blvea1juEj1BpV0rbPR9Xg+F48LhFUWDT j7wn31YjfOobJ8C6pvirc5TZLl71K5RVCbzno/Ojdr+4lOhblNqkIXpjDQioXf0rr2/Kkfeq AR7jKhKExcBLRho3K0w6g+4HtrevapAob7w7kZ79dO07wWEe6p2Obsqhv9XO+F38g1ikrr9S 7ygVCM2Ec42TykzFH4N1GPVEPAKL+Hhp9009sCqiOxp5jqA+4lTwt0m8nWr00miS9ciFrmxB zFbd3EJHjmSQDo0+Dg0TTt3GWg87m9pytL3oD3KVRY9Po2rf9NReGsnJ2biT9MG8xkaPzwZE +xHGiCe/gXUSpksYd8YiYxBXjTfUHTSd6dVAUyVrHt3docJU25QrAZrJ04F+iGeybDnIM/kw l79JoK4EjZR8dACY+pSr8nK1Yg0jRsXwlGFET2CVMy7HviyZ00iwxFguLjTNefGhiHqBeilX 6PPcO8cpv68N79yUZc1atyJAhBEB2kPtm2OhNENzcdav0bzeVpPY/3P2LM2N4zze91f4OFO1 U2NJ1sO7NQdZkm1O9GpRtpW+qDKJJpPqdNKbuOv7sr9+CVIPkgLt1F46bQACSRB8gSAAiQZC Kq9pI2imMvxpyJ/FrcpXhopP1DmMHAujerDZlrJGG5oAAbJ3s6bX++pAaxFSxsj4AJuwtqSY lULM9LO18ERIVujTckPYKFFBX5OqUCUwQJDWf72N2e7rwiJB2SReVOAIa9qgpaXWiVnETiq2 Je+Vsa0j3zse6Abf3oqoFciQxh/O9ORaoialiM0rg5Zvr+fXe8iypvsTA4ebjVIggPj0jT5Y vMJXJ1OeP4ClBG02+D8PzZYyDs0ZvJy75wVEGcTZ8LfDDD1jhn83xmORy5GkUOwjokbznUYe 4PvQTiqwf3aowNg0CcErdyr0kJak3Ryo/n2e86BlKjisYH0PabuX52IIyvJdJisjJcIU/zLP 2YoSJW2enPr4dHSmLtnT+333/Hz30r3+fOe918cskM86wC1OtiFbRFsIQkYoHuCE0xljYylk Rb2D6A2s3y4xA6pNyhcrWuujUqGEBYmLepdUANCDsMhyYccydnxiKy7EeoAo7/Z/KEMgH46A XJlf38+LaEpBF2MjKfL8ZrnkXaT0SgOKhEPjzS4KS7WvOQJ6ck7OoGxFzBMaUgw7vcZVpCLK Z7LDprORIKtvEJ7ZMdkcEPj4nE1CbKoo0wpR8EkvB0MtiuZgW8t92YtK+ZTQ0rK85sLXQOF4 9lzOW6Y+EARhhmCbDmdlW1hxxeWaHtAOPVgOUjxNA8u6AGYVL/QxWwWQtHHtX6gCfLmJslCv OcApNXU0YCHuPA8VPsQ0Af0W8UQX0fPd+ztm5+AjJsJe6PNpp+IhCdQWnuKZItZZNJt6cra8 /9eCi6Qu2F4/WTx0PyDj4gJiqESULP76eV5s0huYvFoaL77ffQyRVu6e318Xf3WLl6576B7+ mzHtFE777vkHf2j0/fWtWzy9/P06fAltJt/vHp9eHueJ67hyxFEg3/UwGCm1Z+MCdsSUYYLz h5f0jwBB5myLwbbDloraF7TWBMegpkjefN6Jc+rosuZAzsw4HgVJjV1MTGglQwaXTH1w5hBR bU2POWJWc5WEq2WMRrvhC8kpmjUNYHz5vPDNUB/e22UfTWGxe/7Z9XP3go77hzlzeL92iXnS 3OaFNgWLUsMSA4PRCoKCoS2ZgkpcKrLY9jZUhL2cY3MEqiEderA9hyiS2t09PHbn3+Ofd8+/ saWuYyPnoVu8df/z8+mtEzsDQTK+4zvzEdi9QM7pB0SYth5OUUfPoluOGHNwy5GkriCyZ0Yo TeBkt9V2U1MBsGMhRSzH2B1WDd9Tx/kAnO21JgSTGDuEpsoUyqVhmDoPlPpo3iI+W/G4lbpq 9NEse3O0cfz0ZPPkjxhVSNiyvUGTRMpU1Y1jyT5zEk43IEuoaO/IF7QShu/w9klYo1jwqBXR 6xP1jbrMu2QreGMQUW/MbTPstlCiS7Iy2aHst3VMmAgLQwFHtkRjhmqJhJQ8niH2NbnyaRLv hoZjnw9o8zw9NCKwbMfG2xdYrtOgqB2Pd4+iSHnC4YcDCodJrgzztpSd8ud4QztvUnqlgTcQ SL+lEa4iWVS3B1v1+pfRYEe6zD8rqK/5WulYy4XkUMbQjhp5gHrUyETN4ULP5+ExQ+3MEk2Z 2s5ytkD2yKImXoC+HJSIvkThAVeNL4cwheMsiqRlVAaNayiZhnpmbGzKSqoqPJGKDXz0Kkam vc02RYpWpCb4jAHpY3ggaAzbsIlQXx2HyeoU4sOhKHkQZRSV5SRPTP0IH0YGa5NcJ7A6sS3T ZUmcCN1vijzBO4UeLG3TOnZmjU8NhzL2g+3Sd/DPxOIsHYRVS4FhuUsy4mFh6Xucra0tYXyo 5zp4pMlOl2ia7Ioa7lHMFoDIbCsbForo1o883HNBkIF93nTWIfFwuSGfMWEBUW/3eMPg0hZJ IsfhbbYl7TakNSRb35mHS2puENv95FFyJJsqrAuzTEhxCiu2+zEtRGqSdt5Je5rU4qS4JU19 0E49bCME1wZbbX24ZXRaNyZfuXgaTfn2B9gTbWzXajQL1p6SCP7juEsHx6y85WqmFyS/aZmQ E5FWzWTyqfUhD8b92X0Q14EG7udNx/8k3KWJ4KYaWtg/DIxaY8t/Pt6f7u+eF+ndBzt9oKbY cn8rb4SHU8OAQ6qTF6UoOUrIcWpcmDmO2wx5SIBihmP8VDiwAcNje9yoXgXDztcxZKMVKrSr QkMduchSOR71AOH3uKoNtX+VOUhCsicbBKjWYxey7RLW//VtmUh7f/6zraNS6cMRip5YBHYL yil7ewrwPnYodWx1+9DzK6nnroMGVYv640f3W7TIfj6fn348d//u3n6PO+nXgv7r6Xz/z9za LXhnkP+cOLxOrqO46vx/uOvVCp/P3dvL3blbZHAORKZ7UY24bMO0BqOS8dbgMkdZM+Bg1dIT YRPj1GFZJnmZl6eKJl/YUpIpDgA9+MJZiIKvEeQuQLGM3Wz6EObxLPqdxr/D1xcswQofk70G cDTey9bdEcQman4Qouy4QZWm9/hS/4ydDIs9lw1GndZbRb0nVLFlp7yQortLlYpPkVhdAVnL /pEKih28M7qP8NLBBSNHI7NLlW/Co4MxB4SNIbbwV97GTKiMpJsklCOdSjIvKzmiJiCEQQYC +MZ7M0o9LgJSRD3CbzsAD9tpbA3meke2GWOqljZk1dLqXWpaAOnDBtOkLm5sIgPUEFFJ5RRt fDVpAgCPJITQWBlmouOqflKZxCdc9Rh8kx6SLUlSzKrdk4ymNf3bPXH8dRAdbUPk5Z7sBrtd HqoVkZmI+PBBwzfxth82znImkQNTbWMdDiB1j01i2OGPD1qRjQOrzYA6oBZ83kNfZnPHnn7R 9KHPMj2bLvpI65pK1zf4MG2S3HBqkYY6biidCMLMk9Ni8GFyUoxdWZJRdkDCfGjgylL1MeEX fDyuvcxigrbchwh3dgKiTQUb1xxOAftTy3be+S6Zx45mpNhaxzmEOVv93TVmqxX4ish5QgXs ZC/lABGiKhDBXg6iMEHdYN46Q6AagayWS2tlWavZZ0lqufbSMUUr5zQ8wximrBPWnjEWacku fKSECRqBazm+BYeydq1dR6ftodpNOEdx0Kw6pbNeYW8gRqw7q07puk0zxQnWGbquje93J7y5 /QzrIUIrA9ewiR7wPhr/YcBqedcmUblour0B7Tm61EV6N3gtWctOMyNOflLDgSLV3KzwOIws e0WXAf6cgNNUye6Q6gdURedjO1jOuqd23LU+ZiavfLWIOgo9F03rKNBp5K6Vp4SjDrv/1oBF rbz94jBCHWubOtZa59Aj7BlrGtk+U65NWo+e5NOkIsIqPj+9fPvF+pVvjqvdhuNZ/X++PMC+ fO47tPhlcr/6dTYtbeAIbEiJyCWXNqwfzPgDNRhVRHPAVeW2xrZsQsCECfMwi7k9DXtfA8KZ yFq6jSyc+u3p8VE5E8vuHPoiMHh5DOnpNIXosez0TPcFdiBUyLI6NrDfJ+y0sFHuLhS8nEEZ r0JUHsyCHYjCqCZHguYOVujQyW9ADs456qrN5fv04wwXdO+LsxDypGl5d/77CQ5li/vXl7+f Hhe/QF+c794eu/OveFdwuxOFJPUGoUVhpsW4UdBlmBtutBSyPKk11zacGbz/yA01EXGRpa4R 5yuyIakm7ZGiqvvMOSg2hvg9uBMVQ20OW8lzajh03uYRJK2X8oLSE4dKFhHx8QQQv9usOCZt XrDTgWIZ6rE0SbdwYDVWFYiYBpcaQX8s1yo8GogOzWCzlNJMrla++kr0hi6tJbZYkYzxoBEh muNwbXk3jjSj9zcpIhXuRMd/Dsg/lhq4KrgkXenUzxFiKwfnMxoajKlgZ+VuzymkjbxKgp2N JbxwVldrPf3sCScApDue50gEqLzBEb9ZK/LDDKjs5icY2MTDSNGOHnmMS2yX2mM3kDpO9lTs 4SL72vcZtwzPUQ2FKGWz32CBQcVLttERO2kd+YU6KepUskcKYCWSJkz8ORQEhDgx3r+9vr/+ fV7sP350b78dF48/u/ezZDobNf8a6VCHXZXcKi6aPaBNqPzGrg53UM2p9wt4kqT/1lPNj1Ax a/MBTb4m7c3mD3u5Ci6QZWEjUy4lBRbEGYFsZELbcEUXdISGGJlKBEo2aO73GYvAdl2Di0dP EcbsnxPkq4zV+FoyPoRSrKWDXRvN6ZSc5Aha9l5A0N7qcjU8NNbCjI4drOyLjGzNVmGicyzV bjwnwJO6z+kaNc/6SJBCF3m2Ol8byPzGudh8ThRY3gqRMcetLTUb8wx7pRZHILN8Q8ADnQz1 q5kROUhlBxyuDT3W+0wtWi0L5owsK9MIiJhC6IMFpy0j2/GujKuB0HPUxUHDE9tGumpEOpjq sV91En2maXHITn/X2hTXuglCw9/m3FxlLeWTVI/csblsX8YEqWa29Rrs1D9Mb1Ep3nzNeMbh l00RVrEaAKRH/lk5unGux9wk8Gw1r9F4ToPouBt+DNF5ZpxHHCZygYvxXLoKURaHF6f1gSrG 1v9BdMlKSxY1IkA6l9jnpPVc279K0uDJsSQSLUg9RuKjcewngjTclBGq/zlfupS8KAomQzBV HbvoXEw9G4sYOq638hulqRS2cYqyeIbhronjiqoPlXVgYctKzr/zTAakiXWMvitX8OB2gBQh kDy6mZnDMbsJsGHKNgJzhYfdAQpsaYiNL/E3JZj5W+tzg7wx8Cz5VhHVSZG3CTh6CMcd8cCI TXXv594rfLT/irwY9/fdc/f2+r07KyaKkB2VLLawSutLD+pfnQ/JL9TvBc+Xu+fXR/CgfXh6 fDrfPcMRnBWql+AH8n6G/bYDlfclPnJJA/qvp98ent66ezj3qWVO5+S49h1LC6OmlneNm2B3 9+PunpG93HfGhkqF+paLr7cM5a/w6lwvQhzPeR3ZH4GmHy/nf7r3J0XS60Dd0XHICi3VyE68 aujO/3p9+8ZF9fG/3dt/Lsj3H90Dr2NkaLu7dhy0qE8y6/X0zPSWfdm9PX4suLaBNpNIbmbi B2qssB5kDGY04GfxS0ftNpXKK1V176/PYPi8quo2tWxLUe5r346P/JCxOzVgu2lp5qu6NcT3 uPv28wewfAd/9/cfXXf/j3xWNFBoh79WBKGQTtNxUsB730Z5kSf8ZI6qnwQv7f31vr2/+969 3TEYKwlxEQKXnTFXXsx/NcvBBT18eXh7fXqQaz6A9KrynY9kMKuTdhdnbB+snB12tIV8N5ui MDi75oTeUlqGuN1Y2ILbKL1pmzRv4D+nrxV28cv6plaf8gtIG+4yy/ZWN+0Wi2fSE21iD0Lf rpDv9w0bvMsNZsiRKXxpgZbgrhMbeLq+uRktW7zWlhzJVYI76tZCwWBBPGUCOYCXArdQ+Cqw DEWtAmwj0xOUUczGOSbMKgwC/0IlqRcv7RArlGEsy8bOrwNBUlLXdrFP95a1xGN5DhQ0tuwA C2QpESjBiBW4h8OduVA53EXbV/u+42InAokgWB9nLNme5FaL4DBgUhrYaEy3nuAQWZ41ryQD +0sEXMaM3JfDufeYE7eeF7XsGgMGNjZ6yyJP8prqiDg5aiDN85nDeApOzDEAkDHJbI2HFkuY w3AniMECN2Q8nOarHgETVlXgBsiBZkuqDFK7XyTaG57dD/hZ6Iw5RYG5gE3YotwID/XZl6XR yXmgwONZDdjBJ3huudxUJN4lMfewRAqGC6YLfJVgrwOQKmesEarGDx7AuvedjuYuqbOv4P07 3lubKBOLLThAIYxLsnKc6Xnb+7fuLL34HNdKDTN83ZC0DRtCRfZvaSHnXkxQM+2Kaqp577uF O9Bs4yF9kOEegmlwMj7oxoyzWZKmYV4006tvqXbitrfdF3WZ4m6IgkAdQUXKTtJNYaHT/D48 JrCIS/br9Aae5DI1vjlIT9gHwrasErY5SBSDd78lkOsqbRSEV8JsaxQ9v95/k+/Owypj+8K/ u7cOtsAPbNv9qIYqIBHqBA5l0DKwlrJv8Se5zxsBZnjf9wIlp5GKZostJkuJqGKH6cDAYE88 3LFDoqFRRgzSpBH6QlamIK6yf9BQbLVD+g5Qlm4ylXCoG45K4i8NVd5kVoAm55NoojhKfLZw 4xwAu0Y3UzIRBbtfG5WGVmwpPGEyWjQHsl2SkfyKiHsHWlSOdlZSCxc/m3Pg7y7JlXYyzJei Il8Mup1Sa2kHIZsS0pjsDBJq4EnptaYVTW42MQ5Ex+iKnLOstMcreKS32XE/aBpDPbekYcuU 4dqRyyiCB1lUF1BxYp3n4tbmAe0vl+hna4OfHK9tSG7gvZnB/AYUwr3yEr71HJNVVCJodyHq azPQ3EDqTkyiwpn5Y841ut3lB0OH9iT7Cr1767E5LTG+OcWDxA54ihrKYd5jA2MDkSRL0/S1 J2wC8qKjY7o4UAjXZi6e+QpHpkIj96s0g/+xeb620duoKoHnVHtClbbS+rC5/J1EAa3AB1EB b4SGDQ55eexenu55Ht25AYEd/pOcRG20G321PjCcSLFmxtnuRm6IjkYlqRMFBv6NtVQHp4oM DJHsB6o6OoBYUCsVKhxEpFK0hh4J+SJuadRvXr4btiVZ9/B0V3ffoIBJ6PJ8CDYiiFKHdWRW 23B2w9VYINlsyKpxTZl7WpLtNGIj6REyCd/SC9ViGri9QpHU+ysUm7i8QsHWiisUO+cihWVf EKBl91W4LhRGKuR3oaT2z3J3RXCMKNvuou3uIkV2hcW17gGSJO9J8MZ7vmdYl1QqNCWIRrP2 LxSz9udKaqQcRXyBW9/4T/GbpICR+GyWvYC6rMCc4uIg4BSjAuMtYjRXBRxYjmsoIrB8x8gb kJ+TfcBmUWMJgSN2bOaGcpoozC41lNN8bgYSpCWsSFWCr3EaEX4skYjCOL1SM84px1+3zMnF GP4s8efmaE77SeUWtFeGeOAarusur1Mot7DZCS1AagZxhdpdTCO0F3jUoQ+FNnQddiCR90wc zMspIzqkV0SKCssv7S6KWnZEVq+rGDzLegS+Hei/XC2t9UUCb2mhPqxjyV4j7VMYNEWhgtZf Se8waSagSpD/EcoarBhsRriDTRATWmeWzqGxoF17cmo+gKYTVClYiHLtoQ/WxpL1xvVfcTDS jjVmBpDQHspNB/fEgV7lXXnoMYZSBn7S+6ovTNeETkgtAT9JQksGZmfRpQLfTcBpzx71RQMC VSwK+ULpDD9hhbGyZz35kLL+YXMqVHolTf+070xFiaAh9QE8Y9W2APyLRynE81cb2XOZsxZi VBIbxtlYRYGYmsZQvbAYBmsdKFkZUjorqy/fcpdzoK3k7ykz0pYQOhTMi+SozSX7rZhKethN yUTdRLIvCJwt+wiZ2nk1yZKj+bRafQ1RF0tA+XRtWzOLQRWEvhOi1q4eqxyiJqCNAR0M6GJA H62JvwrNlglBsLlGEJmtH5zANzhujnh8rh3xa5NRRmAtpLVrG20sOrtMWExuaw/rDEhohEFd vFj/ioTWuPVyRK/xvluvzVajah0uvZ3BMxrMiHumhXrTorCC0HF2G5U7HOUYUBCWhf0qoht4 XqIRiIEFX8IkV13C1iWOZWNamuNlc2gfrH3EiZfgbVhl3spwdzCQsF035Uwi9NkGdSJ7ZS0N TATWlrD4xA5kK8dAJncI2ZJjovezgLbbg7tatmVl8JelZRV/ooTerUQHiX6bTXwCx8rM4L+e wa49Iww+S7g2tEVUKcLC6Ej9XoMXNczqWq2HCAUmW/cuA5OQdO90oiXJQQAypwk6e6uO0cAi g11+TRSQrVVeFGVUWeE3xjJNnaEjeU+TrD0E4mGDZF6irz/f7ru5KY8/e2wL6cWYgJRVsUkU 1aBVxK3oslR6S7X4xnitCmbmOUlPEIdHkkekf385vVsjO0gBUVQjYmQZn9jGfWNkuK3rrFqy UTr7kDTlqmmMH/KYHJ5eEbDna6AqDufMmZauiJE3w7qEdc7sM+HIZfrsWENPzgvLyyjzsaZM mi9io7R1HV2gCmm2tr2lsfy+2+P/Y+1amhvHdfVfSc3qnMXcsZ6WF7OgJdlWR7IUUXaU3qgy iac7VZ2kK0lXTd9ffwFSkgkKcp9TdRczHQMgCfEJkuCHdYtq4Dg90OFVyaXjzFepaHIhl1P9 i1bOplFhPFy7zvfQ8+vUpiJc9FY5KECXsJm98lWGsXx3tOP2PJgzPJefpnuJvf3m0RoQ1czF haj7euc25bAU9cNMVtGCbHyAdVwWeEpsY1mcRZoCXzBm3M205slmUgv9qthVt8a2Gu8nN00x 6fJ4adfVlWQarrme7+O45vBt8AmPW1BlMmJ2fSXEBe/+MgoUzYGb6wZToITJkM24Kbg1Ix0r v8mYPoHe9KLJWHTboUu15K3iLvJwkBY1b9aObPtchfJnnndrVTOECroD26S5MExlA7sm4zhF NDFUucNNIOM1x0xbDvzS7EoqXJJyGoVsQ1/f3ZDDIWuVGROKLF+X5lEHfE6BlPMj3t77pCt2 B3JEUxcCplsPZ7v6FvoqJmMravRonZVATByYbG3+0AzqbkyrRQK94KXaXKL+yzT0oXVchWdS mdkeuBZWSWx9OQ6puEhuhpLPK0aYgf271cLUspvRRpULRcbDNV59en79OH1/e32Yrvx1ihFx +oteq9mP1QHG/3AHPHpQTzLThXx/fv/C5F+B8ufPVD/Ve2abpg8CaWwkm4OEC1xZpDxbFsQt UnP0S2T2jJN+i1Hr6IeIGLMTpyJZxlf/kj/fP07PV+XLVfz16fu/0bf74envpwcD1U07Vz9/ e/2ibw6nFaYxwWKxP5pROXqquvUT8lCTDUEP+d5ioM1sv+GOWc9IY1rEbFFOHa0nOqc/8mpi TE/bG0X/xtkHZyhighssuS9L3nLuhSpXqPRs0zA6nSe6laP0ykydBqLc1IMtvH57vX98eH22 vmxiz07cJo1v76OTmPXIZqvfb7TVH5u30+n94f7b6erm9S274Wv15pDFcZfut9neMLvxVE3m 5S2hGEZyJQTuN/eyzFPzscOvitVYHv9TtHMVoSqzaKOCbYpJSu0zAOb1P//wn9eb3jfF1rTe NHFfpWZlMtnoZ/nGbQMzePpZlM6r0OFrQa5NkaqOBW9rM14OkmVcWfciSGWuYYbH/5xCStWb H/ffoDvY3cycpXHjKjBk0NpaNnAC7mjQQ02Xa85FTPHy3Dy6VKQqQcyZvCJPAxXnpsgMDi0E 5kcu3mY/labFJAHMr5joUhoFDpVaXymLyq2Y3OR8Vv30RT/mNt5LqeccyhBVbQ4ItkVod++t Sc7OHCyLbU1iwKnJRdvVM3OF2p2A9XAs80Zs1aPfKrf2jYOYNxHjjWKUZxHu1R5tnAVVR2yf vj292ENyzKrNYPFsu2N8YPs3k5iq8bnhYVr/syXxnFdVoPfzpk45f8S0beKzX1L6z8fD68sQ ZmgSPUsLdwKMLIrZPjDq7DP6vNn0jRQrn8LS9JwZP/aeW4jW8QMV99tOiFGhvIC73TgLLJeh CU3WM6pmH5ALjp6uhwHeayAsxyRZ3USrpScYVWQRBAtuA9XzB8Rm0+goyppgwawbp8thrWnY J1Swj8w2xsKkHbO6fWoiyg5b0IJ4FvZHr7JmD8wyU6sM4WYOmw05ARhpXbzmRBG+aI7eL7cc F1EdYV09FCa0KfKv0YMfpSi5B4oCI6bXkHD1nxvJpqEfM5QqMdLMKOKaInIIwGe2dc/oE/BV aWiZHtP9+F75V4+SyWulgcjdL4ukzT3zFrAn0PceA5EA0Cri0p0QWCn7nc+6EHP3qMDinSKB 4ZugDfo31XRdxDASdVQZnjovbz9cSYTLXuokwqMwJ9Ax62TB+TFozupcniI4C9qtZNMr4OGL kxkexsq8xEekPot/3cpkZSqqCNO3vIRrvQQeefGna4dgmRax51LUZbH0A+pjoEkzeQ5cC9ZY LMPQAt4VkR9w0yFwVkHgdDQ6W0+1sgASH/mhaGPoRty8D5yQwBjIWHgEN0Q215HnuJSwFsH/ GwJApzAZME5lI+iYXi5WTs1fHuJrepd3j0HWiqtKBBcIQ6sId8XdjCsGGffwO7KS+kvWrydZ hgu7FKDAYiTiFLHfRJ6n3IpF5KyBihAB4UxxyzDqHKKrhWaHlBV/P65YHNQrIjNES5LryvXo b39Ff5sQoiJZ+SFJn6mHH2AGGUS9xaY0tUUWhQgSt+ectW0rd9EildMYmFFEM8PTLfVugJLj GB2xHYuIKMR2iYlY4eS5rawyz6bC/pjmZZVC/23SmAeCHW5yzdLwtiGv0Si0SkS7pWjdYOYr d1nke2QG2rVLh+vD2V64bUtLHc7SKLFol4mthobrnVEir2J83EKzAaI3KTBvYtdfOhYhCizC KrQJRtdBg3bhWgSHBAPSlIgSXPP5FxK8kKDr4hu20OHHRRFXnjsD4IM83+WvWJC3Yptj8I9H f16wzhGJknYIdSYmRW01BGxKQ3c10xB7cVhqeGFyDWdLn88alYPEXV3O5FfvgyZ0rEHU4/1S WpVCTpaqUvUijL86xUQ+C+ElsZKbedSqBZKN8hojq57Jodo0BYxASlJXn2rcmiqqC/l4ETl8 /Qxs9hp7YPpy4Ro9S5Md1/GiCXER4au1qWwkF8GUHDqIxGSRIQPq1aipy1XAGW6aGXm+b2cT hZGtn9Tw1nbmOoYO30GA3+SxH5hD67gJnQWt/X4X3w61/9+C+WzeXl8+rtKXR/ryFYzBOgUL xY6AQrM3EvcH3N+/wS5/gkkTeeyKuitivwdsGI+kxwx0Dl9Pzypaj1RgJqY1g3fLXbXrMN5Z aWy4NCP9XJ45xm4gDXnXqlhG1AzPxM3cqIFsszrDKWRbecTpUJo/j5+jVWt+3ORj1Cfunh57 ggKfiV+fn19fzDflvIBpthey/9bhZb2+mpDVkG7M1LT1ZTWm0n409mZgFNgd1uZ3TDO29hBU GZ5H7HSL189FPd6S7r7Qk+91p+Nt22ARWlhEgTfzYg9ZbC8Ahu8S+y7wfcvABAq/9Q2ClYtA 3mZQt55qETyLYAJqwO/Q9Wt72xvo9+Hk99RwDcJVOLM9AuYyIDtz+B3R36Fj/aZ6LZcLqvhy RW1hj8KXRZGJIZJUZYM4/wZF+j4FzRyMHRDjTKEG5m0rckGDsJUz9kHoenMs0QYOB/OPjMjs AWBk4DtFSli5ZI+mVkoRMyRrUW0QMBJWNRcDHVhLATCCYMlZM5q59BzHzgkajNgjenWwKs9A GrswkEbcuscfz88/+wNfe0HQEbG65FAUd2wRkwxUDhuM+3x6efg5opv9L8YhSBL5R5Xnw92o 9iDYIvbX/cfr2x/J0/vH29NfPxAOji4mKytihuWEMJOFjuD99f799HsOYqfHq/z19fvVv0CF f1/9Par4bqhoTi8bnwSzUISlY86K/23eQ7pfVA+ZBL/8fHt9f3j9frp6n6yH6lxuERElkeR4 1g5VE/kdrjrbC0kebS39gByUbZ1w8ts+CFM0MoltWiFd2EqYcmcaTW/Q6XlOdfAWpjI9gV1p lPHNH3Ip1vwZmGIzR2BZs/WGd9vWqJq2jF7cT/ffPr4a1stAffu4qnX4upenD9qQm9T3yUyq CGb0I9F6C8eKJ6VpLjsw2PIMpqmiVvDH89Pj08dPppsVrmc+CEp2jTkx7dASXxiHE7tGuuaE qn/T9upppKV3zcFMJrPlwkTfwt8uaYiJyv1DdpjgMALK8+n+/cfb6fkE9uoPqILJyCGHwT0p ZEaOz8La9LyIjIvMGifZeZwYFmnWjxTuYqUtZbQ0FRsodjYjnc/oumjNxT3bH3HkhGrkUPAe wmItCVPCskD64ZPLIkxkyy8R8w1iDkKszy7PrCudgXq+BtJRX56+fP3gZsRPSSet03WRHPCI g7X+chxBRifIwX5YGLdHokrkyiP9BCnk2dx65ywD67fZK2IwDRwKqoekGUMFWB4bHgoYoTke 8HdIT6m3lSuqBXvxp1nwbYuFeY91A3tiBz7bmPFGS17m7mphHvtQjhmATFEcCsT3SQrYtrNe nFUNG3RnmrEODUatvZoHsM+P0HB+bLpNida3gal7Gv+4aF8KxPdjMi8rRB03FKzgU1QwNDI/ OY4ZlAR/k+dwzbXnOeSsvzscM+kGDInOjmcymSCbWHo+BVBSpCXfk4ZabaBxgpDrUooTGd+A hKV5JQcEP/BIJzvIwIlcDqLvGO9zuwU0bQba5pgWebhgI8hp1tLcW+ehQ0/eP0M7QbM47KxD ZwjtT3T/5eX0oa9RmLnjWj1JfSa/SY8W14sVf/zY3wIWYmvEsDKI7J2hYlBbR2xh7qKBSL3A NQE8+/lWpeUtmaG8S2zT0Jn0l10RB5HvzUL62nL8+jNI1YVn2S2UM7PkWELDqjM4YnEtqdv4 HKL4nR5+FAdyMkMEe8Ph4dvTy6R7GOsYw1cCQ/yxq98RSPjlEbZaLydaOr5bqOtD1YwX/FbD 4P4xr3ov9lHEWmdRiIjM3PrLO7mRJJv+G3hN+yX1BWxG2Cg+wn9ffnyDv7+/vj8pbO7JYFEL h99VfbzVccz9Oguyufn++gHGwBPjhhC45jSUSBj69vVC4F/Y6/sRe02gOMR5B3f3/Et+5Die dTJgTYZKZuGwh8VVvnAWJLD2zGezVQLNY1qseVGtnAW/EaFJ9K737fSOthYzza2rRbgoSDid dVHNeCrkO5iFDZTjpJJkTdtVtFmyuMLqYPEAqtwhuALq9wS/VVPnXAyADTMke9cuA4Jrq3/T ibenWSYsUj0+JkU/Z1Z1Kjk3wSYgu7Zd5S5Co7jPlQArL5wQqFID0ZriJi14tntfEKncnKCG ppXeyl5pzdWQpOu7yes/T8+4hcIx+/j0rrHwp8Md7bvAtH7yLBE1/L9JuyM5kSrWzpxpW2Ws 22S9QYR+es8m6w0LYizblUfjTAOFh+zDLAwTFQ0Rb0FhtI954OWLdrrSjW1wsXr+M4R6Yx/i SvYduwavp2P7F9nqZef0/B3Pveg4P3denKMXAlactOCd8PEsdRXNeLWAeVB0GOaiKLV3Kjfo 8na1CB3zoEJRzKi8TQFbktD6bdw3N7BYUX8zRWEtTDzycKIgJEsaUwuD/L4hcHPwE0Y7Z60g J0sMLGskyNusiXdNGlMyduOq3G/tnJuy5BxPVJKU+hErcQyFiZEKOeu3SDsdPU41KPy8Wr89 PX4xHWDPvRiEY7Fy4tbndlvIbmBz4puDAWgbcZ2SAl7v3x75/DOUhz0tmVvGhBPXXKLZbHjY 6raYZJfVN1cPX5++G5H3hs5c36BDtvHYI+82meFritE1a4Fy58/8pB4hClNseEEI9liMwtCY ZsOMbCiOv+PvBRD0YyI19l8/QsMWVBnL7e9ssdjp4yuEHtTSk3J2kdaVd4/5vK9kt83YM5v6 ZnwID1WQpOQlJj7HAwnZpLwNWShV0WSeOu5iznFZrLP9XODfEkYH+ltU8Q5Gy0zAVlPIGpRn k9vuD8YXVCK+xkHCrSgKNRN+NHWZ5+Qht+KIZrdc0dpW5FY6bMwozV6ndW73FkXXz4Pm02l+ f7k+Tb+TCf/sV7PRgWg2b9xW5N32dpprLvYNC/fbs/W92zSd8pSZTab9aBTAVyfq9TQ5Oshc +JjxafZsCfotRymNnavBqKjDieYgkvVsfvoGa6qo2kwVlRPwll8vVMYYyeSSBEJVXOCP+J+z Cg6D1P7ecfBu80Nq9+DPd3tjcukxMQaw2B7x9XykSNk2ZKy2BHd3V/LHX+/qDcd52kXE5xpm KMT8/8kQuyKrMhVR5sxG8nCtiw8NymZLmQpH2jhcA5J2KNIQ/pSMT2LHMmzmKrNh/3tGsFAc 3rRRemNHjtYKtIZpmlGk27a5EqKf0PMcV/ySqSICpraO/UBqt4p7WU0lpioBZTuxF3x4CEyg 4ZrZIjWq8kxwjBG1Q6H46PacpN7LS/V1lvDsovfSnXynxdaR7ZKJ0gopRjT8GBwl+I8yvrqv ELOmBryMsq5JQHKTOe3ZA0fC0KSRyglX5Ec++CVKqdcz+Nby5oLiRdbC1G72fZJH/0p9Pn3/ uh3Hx087KS5HuITjqJ9LLTNYXfal7t+k5vTS0h3rtg9KmrL8GqwaOjj0035vGSA9zg9gftRs X1Mr7S+aXctcqL9juj50UBroeGiKjOo4cKNWRayZ1m/Vis6N9gUszzMWDJGyx8VEylKUjvKi 8i59CUJwTDoiUg8bOSW2cjJVau/ryfRaiKralfsUMR6hryxoXmWc5iV6aNVJKmlCZUD1Xcsg 92gEN4idOcPF3uIy9JuisltA0y9MOEoA542dpd7IkGgfb9KiKfUpBZ84i9miNVM1768UkFYz 1EKBFEyq4AyhpmZJyhvenKpRt0uK7BJ/OiopP5HZdO4aRaZjdmQ1d1U6qY/e8k8qDfA4Ux29 lJqylBwtomersolawzPBfrKga3lQHV1ncWnd0fmqOUUvIAZvNKK4vE3mvKUwSl1YwNCREX22 HQ9Uhe+3K/7M9898+p1NtvMXy4vThD7/Bwn4wW35UEY9LHZWfle5B6pDInqDzCIXkRMydFGE GLZRD35L2U9L10m72+wzd3cKk8qw9aJmI5jCVValHm2hBkoeIzcadL2zwUVqfh3VMmlRzBzf EZvWSIpYD/EMpFsRszs5YYxw0Nj/kwmeOKxy+6Qu7QhgM4EVE2EAwOyP+OCe/tRXOTZR7c+z iSySy7g0ART7d7np5iBTW3ww0lPEhDHQVCgXszNfQCgmPrBRJXGHdLAG6fLGHPVUvlHFmDux YdJR4ly1DwJaCaICGnbWx/Y1poYJhsEihY3jeK4wnVp7VOqMz6eaA6TKUI9Wdcj9UUKFbSsW QkS/8JgkVbg+E2W0M9bt1cfb/YM6r7dPwjT01fkHAvfB+rYW0jznOjMQRMo42ESGcueksrI8 1HE6IotwvB1MYM06FYaprAdgs6NAU5o2G9l9FNg2fIyzUUA2HDbFyIZVY6pKVzXUQWmgJ2Dw bdlBydT2kCvu/s91h7+6YlsP5wLznE5QtyIFQ1XVYBxZDsITlsLFMj9gzHoQlXOuY5ZgfKwY BfHkYPisaRn9MeUvCsji1LddPQdeIeJdW7oMV8cPnHz6pk7Tz+mZOyrV6wJVk6QMPoaZdZ1u s9JwvSg3PF0Rk00+pXRic2CoJDo8qcOimtYie7XQpOPDBviToHIMNxgGeZxxDnmTwSe3Z583 w2OBw/YoDvisaLtcufymqedLx1+wt93AVpAQP03KCP859ZqYqCwzE+QMf3VDXEiDnGeFvtkw CD1AjsZ0ISO3hr/3acyjBUKnQBHuYzSK3fmmnF5RaB/1JwzJrGwD46bzKPBms0mhMfE1sTQP j5FUygyqMTbgjdMWL3E2xJVmoHVrjR9bcafUmyxPO+Rn9C4JUYLwgd8dkeAykF26j+u7CqOZ mTkA45jWWcNt7jdyXzbZxpj+k5FgVL0izV/ebISWYAq4OZQNAUtUBIz1qvZEqlXxETZnwNbA 7eVvRb3PTFBnTVazuE1sYAoxaJui6Y7GXbUmuFaquDEaURyaciP9zjS1NI2QcLHuTFCP+ECB mzTQHIhwljG0SS7uSPozDeaqJKuhq3fwz7lETkDktwIW9U2ZE6AwQzTbJ2nLcooUvrys7oZJ Jb5/+Hoy+v9GxjCBp3RaU6QLC2ifiT5Ifj/9eHy9+htG13lwnU1vfC3O1o7igK2XJ3VqBBe7 Tuu92QKWOaz/GVrpbPlPlTDGVyZjNbQQcjVlQ6RCZ70t62tTyrAyTW9Z+AEVsxEwXf/529P7 axQFq9+d3wwDMcfHbUlaIcyT73FXOURk6RH3JMpb8n6URChin65aIi79AoMTzHLm9YrYACCW iDOXceheyJjfl1tCnKeIJTL7WWE4y1nN6rVi39JQkWBxITl3lkFFTPgHqheNWI+8TJbY7zpu XSdpHRIxw2Y5dr5CxhnrLWGUaTXrQHZ5sjenOo82YkpwTl8mP+RLXPLkFU92ZhV05jrZKBDY Sa/LLOo482RkHqgWYDvjvlXs7ZyQEadgEfIn0WcRWFwPNXc+N4rUpWiymRLu6izPWW+CQWQr 0jyLp1pvYQW+npJho5CDNcMw9oes4XRQnw/6XfzO5lBfWwGyDYlDsyGv7mHjj72cXbmIEaif UJ8efryhy9frd/RbNZZGDO5oLkx3uCTfHFKMba/WTPOULK1lBusGmDMgiAF3eFDxpsZLkETl xrt4aAOPETnr0SU7MDFhLzVEtR3WyjQ+oBXYJUUq1c1xU2cxReTuRdglWcXj3ok6SfdQPtqC aDmA+QEmaR8ifsxoIsYdhDSgYawkCmgQDUlpHjUwbDDCm92fv/3x/tfTyx8/3k9vz6+Pp9+/ nr79X2VHttxGjvsVV552qzJTtuN4s1vlB/YhdUd9pQ8felEptmKrYksuSd4Zz9cvAPYBkmhN 9iWOADRPEBdB8nW1+9BbsFoBsw4rFgpJqvTqA54Tfdj+sfn4vnxZfnzeLh9e15uP++WPFTRw /fBxvTmsHnHeP35//fFBs8Jstdusnk+elruHFeVODizR3k/6st29n6w3azzetP5r2R5c7Y3o GNMMME0ly7PQtK8BhRu7OJR983OZ6ztidJRHafsbSsUmdejxHvUH/W327y0tZMO8Nxt376+H 7cn9drc62e5O9Hywl0uJGLo3VQV/boSDz114qAIR6JJWMz8uIuPeeRPhfhKpKhKBLmnJ/Y4B JrR4tLYOw1wFjZgVhUsNQLcE3Jd0SUE8qqnQ8RZuPnqkUaNenPkpvtClPPA48Wpz8WVBkzy8 rfEhCyR2WjOdnJ1/SZvEQWRNIgPdntIfgSGaOgKpKPQTm+Imtrx9f17f//Zz9X5yT0z7uFu+ Pr1zp6Sb4UqNdzpweSf0jX2yHhpIiqnHlkGlHKYAsXUdnn/Gx6i7CxrfDk+Y1H+/PKweTsIN tR3PUfyxPjydqP1+e78mVLA8LJ2F5/upOyV+6tYbgeJS56dFntzhWThh9U3j6uz8i9DRKvwW Xx9jqxCKBtl17UyJR4f2UZDv3ZZ7vssIE89tee0uAb+uHLrQ9wROScqb8TnKJ55TdIHtssu+ FRgf1LF5z3TH4lE/xnYxKgB7p27c2Qmrip6x01sCy/3T2Jilyh20KFVCi6XhvdaU3SmU1f7g 1lD6n84lbifEMSa4vUURe4zCS9QsPJc23QyCSq69PjsN4sn4x1NR7DN+d4RhID4Q1yHd6Utj 4HPK1JFkUpkGsHzGS0S8la3XI84/y8+HDBSfxFPN3QKN1JnTWgBCsa7ajNRnfg3lAP7k0qaf XEIMwXn5VJikelrKN0a2+JviM729rSXy+vXJOAnWyyFp/gFq3YztUGSNF4+859NSlL7se/bc l99MZGej40KVhuA2KYlBVVWPvM83EByd5CA8ookn9Fdgnlmk5kp+UaybMJVU6hj3dKrBnX7j HYgeWBZGEl3PKxcSS4RHNG19k+N4OyzWwtts1k5g+duXVzwpZVje/dhNEn0RvSP/55KP3CK/ XLgLIZlfSLDIFbHzqu4vYy+Xm4fty0n29vJ9tetuqZFaqrIqXvgF2p12eUHp4f5z1siYSJL9 GiMJPsJIuhMRTg1f47oOMTmy1BFj16xcKL7NZyF0E0ax1WAiSxYr0ZTixodNRY6DXQ9Wvmjf P+E+y/P6+24JPtJu+3ZYbwR1irdNqNA1JQgO0kJEtEqqy40W+sSoxruERHrl9SXZwz6QyKje lGRtOUYmojsFCUZxPA+vzo6RHGvoqGE59OKI9YlEvcKyxzOSTDhV3aVpiGEOCoxgMhv/lKGL xktaqqrxkNCxU328t+QHmeB7ev58v37c6INm90+r+5/gQLO0DNom4AGd0ti+cvHV1YcPFla7 VH5Y1vEk9o1HNMYoFjRBF6f/vmRhnzwLVHknNGYI/OjigCH9WRJXfZhK3t/5hYHoavfiDKum rbzJVX9dy9iaS+IM7zotVTa18szU2LanF4OxgW+2sdHpjiRkeHCijhNji6gMOHfia4MhuJyp Z7yUoqNnKnHLLPx4EWNam5EVU3Q38jOm9cHxApFpgM4uTVngL46YrP4irpuFWcCnc+snvq47 aZ8f4wUjBlg69O5ke5MRXAifqvJG2c97GBSe+P4g4C7t4mQL2meheFjZvU8xELATitpv4Jux QVwzUTPkkKksyFM2KkLdoNEpyxuPcQ9VIBQzS2z4HMUOKI7EWH8EHSyKrh/znJfB4BdCjWQx yHC5JWBLLNzCCSzVejtHsP17cfvl0oFRDmTh0sbq8sIBqjKVYHUEi8hBVAUoSQfq+V/5rLXQ kfka+rbw5jEPgjFMMk+ViLidj9Dn7trmseyOofDS9CpP8pRnDnEolnrGhtTzmZUDPyiLrqbL 6Pm+MWU+XKvESldQFT50BNLnOoRBLRUztCI8iZobSaEahNklC0MiITzgA5JhgwGCZPaDTAG9 COAnqsSMvyg0z7/A9EVUXnWX+UQ7yUtH2slUftEIJIiFSSiEyhCV5VmHwIcWChPrU690dGL1 Y/n2fMCD8If149v2bX/yogPey91qeYLXKP6HmXPwMSrHRerdAaNdnV06mCIscc9MTcHEOWUi rMNX6NfT17Jc5HRDWZL0M0o0T5GaOCUdQEUSlcTTLMXB+zJ8iwOEFrCTm9EpqmmieZyN6Teu 45LcM38N2oVt2qmauwz94qnzNPa5vPCT+aJWRsQNTwuDgSedjE+LGO97G4Rm7E0Cxht5HFAG X1WX5vEcPEck75Xk3lc1FQeiRuvGVJ393RiWcWJu/nR2HkFfd+vN4ae+DuJltX90dwnJ8NFP 5hrmjAb7+DyF+KCrTrxdJPk0AeMm6ZNK/jVK8a2Jw/rqoh9NEHK4ke+U0FN4eV53DQnCRBkp X8FdpvCVPCHLR6Jw7pdnlmXq5Whah2UJH8j7rqPj2Dv16+fVb4f1S2th7on0XsN37qiHGe1c pA1uxkYhveTeoiYghUNKJ4M1fn7BGgosUeCD2Nhk+Ri5CqhYoGGSNsSbBjDHCqQq38zQ4wLW NxqSmGWUqtpnJoyNoTYt8iy5s8sASepDk0M1oyehtFAdrPFfHR0aS4o6rO87fg5W398eH3Hr L97sD7s3vIyRP6qopjBz4BzwuwsYsN9/1AN+dfrnGU9cHOjANY+VtOjbHlZcdZHmgwGZTfnj iO2vvnj8Pbo3RciZ8XngSa1lWPhvHWcN3p5RqwqDHBHYlkwPNF5ly5l2Dn5pVM0uYyZb6LAL Pez2buwn94UZiXO4tMH5w4voR/aJdYFISBJfPjWDxeQ3mfwOOyKLPK7yzPIWTQwobHAXMiu/ dIx4HpbyCZ6hvbDSJH9IE4BID32+02KARWfIpMB98yMN6MhG3243yTAvcKwteOI1MjaxTTya CEXT5S2PUbWyrBPfZ3aDq0RJuyW0jFpWA5MxAelh1/B3cHwFEGYuT3RQ4ezy9PR0hNK0ECxk n6QwmYxWhdm1+B5W5ghQyphoUJcZAQsQ60GLDLNAS/nR2bpO7WKvU9roahN1bFTpCcBiCt7e 1OG8LE/Tpj1aULlsp19SpKwNSc/7ZBEjF+mVRAsJrT8VBKY3N1OA0z0mJjBTPAYp4fBHhNem 2MEsoj/Jt6/7jyd4Y/nbq9Ya0XLzyM0XRY/Ag17KC36olYMxSb5hQUGNxPWTNzWXn1U+qTF9 vSmOPeCkUYsIj4CCHDa4U/NRj+orOTtn1aBdQ84WI6Q2ScGjMdq2U6zYm2+goUFPB7lsD+ES WOjuiTri+IjrZDNQ3w9vqLNNod8l4whoe7ZxRGZhaN+tpsNuuM8+6KZ/7F/XG9x7hwa9vB1W f67gP6vD/e+///5PFpHDEwtU9pQs5qZAb5PHz/Jr8dyCRpTqRheRwfDIATxCo0tqryx0aps6 vA2dNVdB//AzR33K5Dc3GkNPaVMGmV3TTWXkdGsoNcxylxAWhIVEqsHWfGinCCqGOTmiddrx 0xshrQqTnUxqFKycuinDsYDJ0N/BeRv8m/+DC7oC6xKfyQM5YklAkkaEHGBkxsKoLZoM9wZB SuuYnDs2M63iRmTTT21LPSwP4MqDEXWPAWbj9EA7dHElnwdqDYq/wVcSS3aSHaPqGBbm7+Ci as4WAdiI6PTgHa6OBWas+JF+mFX5JYwUmJ8q6W95A+vBEAPmsvJZYIVzgxELBfsDr5obYxPE H/uWJnbku/Bb1R++GW4pNJpsrcFvrR9TWmGhLC90TcwCIuNl0mTaQzqOnZaqiGSazkWdWCyq C9BMnZL5BfobNwbYmFJ5GH9ZWB/rz3xT/FA0wX6amJ7YJXpj6wf9DDDd2/sEnZazokj43AAh D4IVYL+mwHTgVdGnYFpn3B526uviM3ZFLaEr0vvhMlQqapbuG/kQmDlfcjSADDaXoEXjHXRg JQ5Ntey90Q+jm0TVYg9hFKtMFVWU16OIzq22RlrPtAfiCy+uK/MJnkA1dJyBCymvV/aBWgKV gUxRuAenvxSzOXpikKEdmVDpsVG+y+pIs594Ty31S3NnnKEI5sUPTLXwQqgoVaVkWHM27ekG F6CrQyUUccYO8UraxQfsAOKncATUIIZYLWPE7rqgaJblk1QKL37juosAfDDM6885WkfJpDgi p9LhercMQc9ZBPikuN1UCl+4hZVFWmFkNYYGj5eof/GjhS3ieoJ3nwfhNfxT3C0olZLUzcv6 frf9/rz8ayVpHdMAYCKjl/3i9zx0Wq/2BzQ40Ob1t/9d7ZaP7FL0WQN+jxHeQYDWHeJpBI03 51jDwtt2UgQcrimdojyEs1stjwHKvGwXhD4mPsSRJ6Qgxunl8ylhjQP96x9o96Zvwbi/CJ6g n193zMnvMwVdRnJaW9s6U2gwXmdBbdhh2mfB/f5KvnmWCNI4wzgGuz6AwPgJHySvswXJ7Bw1 Ojzc71r0VmkH5htqI58aO2adxdKtfh1LMee825EQo0LUhyi8DZqR65B1J/VGgT59IgrTlqry eU4UQWcArvNbp1KdDDFWlhfXetPL/AjAwESJnMVHFE0TS5ckE+7W2kokIJ4DnuCZ4RerpBI3 22sMO43XZufxclwcKItXklnq1AI9kk/C695gNhcdTTZL8oqJDcGklSinGNk1u54hzgKsg2kn e0wncZmCuyI+8XlX+XViSpnBB6MMmR4l+bQ8j8XiSt29bsfFZCM68kTJQPZopWHqg4lzlFUp R0aMM3VFxJaUBZCre83TQbLcdo4QtWk/Q7gE3cA0ripcPkHuN6ltjfwPe2uuBdp6AgA= --M9NhX3UHpAaciwkO--