Received: by 2002:a05:6a10:a841:0:0:0:0 with SMTP id d1csp559274pxy; Thu, 22 Apr 2021 08:15:06 -0700 (PDT) X-Google-Smtp-Source: ABdhPJz5MlM/fabIlBzsUhts5hnvHzODvrLeuTDAhOcVUotogfiRaizTRSDLv38Vf6h4DjsvSkDK X-Received: by 2002:aa7:cb89:: with SMTP id r9mr4585684edt.245.1619104506282; Thu, 22 Apr 2021 08:15:06 -0700 (PDT) ARC-Seal: i=1; a=rsa-sha256; t=1619104506; cv=none; d=google.com; s=arc-20160816; b=qkzE9FMJFW991sAJjMq9tElrt95QF6mhq3bOFqxun8l9d2pnSHae2tblkc7i0xq9th QmE76s/0l6e4qTHY4ho3wAxTEzKd8z73sVV4XVrJqwP3iBa2dXB1TB2ovUAQ2krNhKOk k+4/4AS9fc1NLLPSDR4BIL7qbtMeAOLasW6OxVfJpELr+QGg8GsMeQ3YyV+s68dk1Ef2 t9HKk1G4acoisSu0qH+BER2z0yABPrSusteslIPWO9Phf8k0tS5a8IoQ37lyegJ4cYs2 6CEN9O5gI7a1zrXZY2gAXP4LTCdmbO30JcdmvcGy/vQmRInI3/QJv1De4QpVDL2SuXbO F3kg== ARC-Message-Signature: i=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=arc-20160816; h=list-id:precedence:user-agent:in-reply-to:content-disposition :mime-version:references:message-id:subject:cc:to:from:date :ironport-sdr:ironport-sdr; bh=UstE8HEW9sWabNAQcaW3AtacAYQmrAVay58OJs9thiM=; b=DCLNiP9vU0vcaZS5jOqIFMnWhADrqItbZOI0+7WYd8Zu/+BhDaIlSoinxdivSgvtMY /W8g41B7PQxNdgtZDQ0wq1QYTbBIED89t9AmuBKWnD6iy4mtZtNFP6OUvaR4JzZr0pow 3XW9UBRgJodfRbyGctQsKcFYpgmyRTs76+TbPcYL9uJST3JeRQcGXVcrvZpBLrStEf2y tjdZCkBU8G6526ySgL9o7Po93IMPSo3dguKmF0m4IW1VewA2nh8omZLYYV2n8vDDR6DL fU28eDiaLWIwxn5hQ7NhzSwrRJVTRIIWJYzPlpMGOWK1+50kIianFdszWqTBAk3bWATn LeLA== ARC-Authentication-Results: i=1; mx.google.com; spf=pass (google.com: domain of linux-kernel-owner@vger.kernel.org designates 23.128.96.18 as permitted sender) smtp.mailfrom=linux-kernel-owner@vger.kernel.org; dmarc=fail (p=NONE sp=NONE dis=NONE) header.from=intel.com Return-Path: Received: from vger.kernel.org (vger.kernel.org. [23.128.96.18]) by mx.google.com with ESMTP id x5si2524184edv.369.2021.04.22.08.14.42; Thu, 22 Apr 2021 08:15:06 -0700 (PDT) Received-SPF: pass (google.com: domain of linux-kernel-owner@vger.kernel.org designates 23.128.96.18 as permitted sender) client-ip=23.128.96.18; Authentication-Results: mx.google.com; spf=pass (google.com: domain of linux-kernel-owner@vger.kernel.org designates 23.128.96.18 as permitted sender) smtp.mailfrom=linux-kernel-owner@vger.kernel.org; dmarc=fail (p=NONE sp=NONE dis=NONE) header.from=intel.com Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S237655AbhDVPLc (ORCPT + 99 others); Thu, 22 Apr 2021 11:11:32 -0400 Received: from mga12.intel.com ([192.55.52.136]:39553 "EHLO mga12.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S237441AbhDVPLb (ORCPT ); Thu, 22 Apr 2021 11:11:31 -0400 IronPort-SDR: O4lfcy4tDbAXj6xUqe6s4qWhy0avMpbY7xJgelg+Y9VnPhezZM/k8NYcFSO9nRlzpzBGj32Ep2 pAo5VxRtjH4w== X-IronPort-AV: E=McAfee;i="6200,9189,9962"; a="175388817" X-IronPort-AV: E=Sophos;i="5.82,242,1613462400"; d="gz'50?scan'50,208,50";a="175388817" Received: from fmsmga001.fm.intel.com ([10.253.24.23]) by fmsmga106.fm.intel.com with ESMTP/TLS/ECDHE-RSA-AES256-GCM-SHA384; 22 Apr 2021 08:10:56 -0700 IronPort-SDR: Z1oouhViEPEhwx4ThRJMbgNPcwSVpYHe2DmuWq4awl4X7Ww8SktPatfi/bAONavjkRZq/Y7zd1 3X4F52V7V01Q== X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.82,242,1613462400"; d="gz'50?scan'50,208,50";a="524675460" Received: from lkp-server01.sh.intel.com (HELO a48ff7ddd223) ([10.239.97.150]) by fmsmga001.fm.intel.com with ESMTP; 22 Apr 2021 08:10:52 -0700 Received: from kbuild by a48ff7ddd223 with local (Exim 4.92) (envelope-from ) id 1lZayi-0004D6-3B; Thu, 22 Apr 2021 15:10:52 +0000 Date: Thu, 22 Apr 2021 23:10:43 +0800 From: kernel test robot To: Srikar Dronamraju , Ingo Molnar , Peter Zijlstra Cc: kbuild-all@lists.01.org, LKML , Mel Gorman , Rik van Riel , Srikar Dronamraju , Thomas Gleixner , Valentin Schneider , Vincent Guittot , Dietmar Eggemann Subject: Re: [PATCH 09/10] sched/topology: Introduce fallback LLC Message-ID: <202104222322.VVzXZkQV-lkp@intel.com> References: <20210422102326.35889-10-srikar@linux.vnet.ibm.com> MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="pWyiEgJYm5f9v55/" Content-Disposition: inline In-Reply-To: <20210422102326.35889-10-srikar@linux.vnet.ibm.com> User-Agent: Mutt/1.10.1 (2018-07-13) Precedence: bulk List-ID: X-Mailing-List: linux-kernel@vger.kernel.org --pWyiEgJYm5f9v55/ Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Hi Srikar, Thank you for the patch! Perhaps something to improve: [auto build test WARNING on powerpc/next] [also build test WARNING on linus/master v5.12-rc8] [cannot apply to tip/sched/core tip/master next-20210422] [If your patch is applied to the wrong git tree, kindly drop us a note. And when submitting patch, we suggest to use '--base' as documented in https://git-scm.com/docs/git-format-patch] url: https://github.com/0day-ci/linux/commits/Srikar-Dronamraju/sched-fair-wake_affine-improvements/20210422-182725 base: https://git.kernel.org/pub/scm/linux/kernel/git/powerpc/linux.git next config: x86_64-randconfig-s022-20210421 (attached as .config) compiler: gcc-9 (Debian 9.3.0-22) 9.3.0 reproduce: # apt-get install sparse # sparse version: v0.6.3-341-g8af24329-dirty # https://github.com/0day-ci/linux/commit/dcb752591087d90fd4093094e42baf167fdcae7b git remote add linux-review https://github.com/0day-ci/linux git fetch --no-tags linux-review Srikar-Dronamraju/sched-fair-wake_affine-improvements/20210422-182725 git checkout dcb752591087d90fd4093094e42baf167fdcae7b # save the attached .config to linux build tree make W=1 C=1 CF='-fdiagnostic-prefix -D__CHECK_ENDIAN__' W=1 ARCH=x86_64 If you fix the issue, kindly add following tag as appropriate Reported-by: kernel test robot sparse warnings: (new ones prefixed by >>) kernel/sched/topology.c:106:56: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected struct sched_domain *sd @@ got struct sched_domain [noderef] __rcu *child @@ kernel/sched/topology.c:106:56: sparse: expected struct sched_domain *sd kernel/sched/topology.c:106:56: sparse: got struct sched_domain [noderef] __rcu *child kernel/sched/topology.c:125:60: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected struct sched_domain *sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/topology.c:125:60: sparse: expected struct sched_domain *sd kernel/sched/topology.c:125:60: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:148:20: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/topology.c:148:20: sparse: expected struct sched_domain *sd kernel/sched/topology.c:148:20: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:431:13: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct perf_domain *[assigned] tmp @@ got struct perf_domain [noderef] __rcu *pd @@ kernel/sched/topology.c:431:13: sparse: expected struct perf_domain *[assigned] tmp kernel/sched/topology.c:431:13: sparse: got struct perf_domain [noderef] __rcu *pd kernel/sched/topology.c:440:13: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct perf_domain *[assigned] tmp @@ got struct perf_domain [noderef] __rcu *pd @@ kernel/sched/topology.c:440:13: sparse: expected struct perf_domain *[assigned] tmp kernel/sched/topology.c:440:13: sparse: got struct perf_domain [noderef] __rcu *pd kernel/sched/topology.c:461:19: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected struct perf_domain *[assigned] pd @@ got struct perf_domain [noderef] __rcu *pd @@ kernel/sched/topology.c:461:19: sparse: expected struct perf_domain *[assigned] pd kernel/sched/topology.c:461:19: sparse: got struct perf_domain [noderef] __rcu *pd kernel/sched/topology.c:635:49: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected struct sched_domain *parent @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/topology.c:635:49: sparse: expected struct sched_domain *parent kernel/sched/topology.c:635:49: sparse: got struct sched_domain [noderef] __rcu *parent >> kernel/sched/topology.c:678:52: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected struct sched_domain *sd_parent @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/topology.c:678:52: sparse: expected struct sched_domain *sd_parent kernel/sched/topology.c:678:52: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:686:81: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected struct sched_domain *sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/topology.c:686:81: sparse: expected struct sched_domain *sd kernel/sched/topology.c:686:81: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:742:50: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected struct sched_domain *parent @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/topology.c:742:50: sparse: expected struct sched_domain *parent kernel/sched/topology.c:742:50: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:749:55: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain [noderef] __rcu *[noderef] __rcu child @@ got struct sched_domain *[assigned] tmp @@ kernel/sched/topology.c:749:55: sparse: expected struct sched_domain [noderef] __rcu *[noderef] __rcu child kernel/sched/topology.c:749:55: sparse: got struct sched_domain *[assigned] tmp kernel/sched/topology.c:759:29: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] tmp @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/topology.c:759:29: sparse: expected struct sched_domain *[assigned] tmp kernel/sched/topology.c:759:29: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:764:20: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/topology.c:764:20: sparse: expected struct sched_domain *sd kernel/sched/topology.c:764:20: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:770:33: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] tmp @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/topology.c:770:33: sparse: expected struct sched_domain *[assigned] tmp kernel/sched/topology.c:770:33: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:805:13: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] tmp @@ got struct sched_domain [noderef] __rcu *sd @@ kernel/sched/topology.c:805:13: sparse: expected struct sched_domain *[assigned] tmp kernel/sched/topology.c:805:13: sparse: got struct sched_domain [noderef] __rcu *sd kernel/sched/topology.c:967:70: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected struct sched_domain *sd @@ got struct sched_domain [noderef] __rcu *child @@ kernel/sched/topology.c:967:70: sparse: expected struct sched_domain *sd kernel/sched/topology.c:967:70: sparse: got struct sched_domain [noderef] __rcu *child kernel/sched/topology.c:996:59: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected struct sched_domain *sd @@ got struct sched_domain [noderef] __rcu *child @@ kernel/sched/topology.c:996:59: sparse: expected struct sched_domain *sd kernel/sched/topology.c:996:59: sparse: got struct sched_domain [noderef] __rcu *child kernel/sched/topology.c:1166:40: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected struct sched_domain *child @@ got struct sched_domain [noderef] __rcu *child @@ kernel/sched/topology.c:1166:40: sparse: expected struct sched_domain *child kernel/sched/topology.c:1166:40: sparse: got struct sched_domain [noderef] __rcu *child kernel/sched/topology.c:1468:43: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected struct sched_domain [noderef] __rcu *child @@ got struct sched_domain *child @@ kernel/sched/topology.c:1468:43: sparse: expected struct sched_domain [noderef] __rcu *child kernel/sched/topology.c:1468:43: sparse: got struct sched_domain *child kernel/sched/topology.c:1955:31: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain [noderef] __rcu *parent @@ got struct sched_domain *sd @@ kernel/sched/topology.c:1955:31: sparse: expected struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:1955:31: sparse: got struct sched_domain *sd kernel/sched/topology.c:2123:57: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/topology.c:2123:57: sparse: expected struct sched_domain *[assigned] sd kernel/sched/topology.c:2123:57: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:2140:57: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/topology.c:2140:57: sparse: expected struct sched_domain *[assigned] sd kernel/sched/topology.c:2140:57: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:59:25: sparse: sparse: dereference of noderef expression kernel/sched/topology.c:64:25: sparse: sparse: dereference of noderef expression kernel/sched/topology.c: note: in included file: kernel/sched/sched.h:1459:9: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/sched.h:1459:9: sparse: expected struct sched_domain *[assigned] sd kernel/sched/sched.h:1459:9: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/sched.h:1472:9: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/sched.h:1472:9: sparse: expected struct sched_domain *[assigned] sd kernel/sched/sched.h:1472:9: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/sched.h:1459:9: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/sched.h:1459:9: sparse: expected struct sched_domain *[assigned] sd kernel/sched/sched.h:1459:9: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/sched.h:1472:9: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/sched.h:1472:9: sparse: expected struct sched_domain *[assigned] sd kernel/sched/sched.h:1472:9: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/topology.c:1483:19: sparse: sparse: dereference of noderef expression -- kernel/sched/fair.c:861:34: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected struct sched_entity *se @@ got struct sched_entity [noderef] __rcu * @@ kernel/sched/fair.c:861:34: sparse: expected struct sched_entity *se kernel/sched/fair.c:861:34: sparse: got struct sched_entity [noderef] __rcu * kernel/sched/fair.c:10750:9: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/fair.c:10750:9: sparse: expected struct sched_domain *[assigned] sd kernel/sched/fair.c:10750:9: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/fair.c:4907:22: sparse: sparse: incompatible types in comparison expression (different address spaces): kernel/sched/fair.c:4907:22: sparse: struct task_struct [noderef] __rcu * kernel/sched/fair.c:4907:22: sparse: struct task_struct * kernel/sched/fair.c:5430:38: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected struct task_struct *curr @@ got struct task_struct [noderef] __rcu *curr @@ kernel/sched/fair.c:5430:38: sparse: expected struct task_struct *curr kernel/sched/fair.c:5430:38: sparse: got struct task_struct [noderef] __rcu *curr >> kernel/sched/fair.c:5905:80: sparse: sparse: incorrect type in argument 1 (different address spaces) @@ expected struct sched_domain *sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/fair.c:5905:80: sparse: expected struct sched_domain *sd kernel/sched/fair.c:5905:80: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/fair.c:6755:20: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/fair.c:6755:20: sparse: expected struct sched_domain *[assigned] sd kernel/sched/fair.c:6755:20: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/fair.c:6878:9: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] tmp @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/fair.c:6878:9: sparse: expected struct sched_domain *[assigned] tmp kernel/sched/fair.c:6878:9: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/fair.c:7076:38: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected struct task_struct *curr @@ got struct task_struct [noderef] __rcu *curr @@ kernel/sched/fair.c:7076:38: sparse: expected struct task_struct *curr kernel/sched/fair.c:7076:38: sparse: got struct task_struct [noderef] __rcu *curr kernel/sched/fair.c:7327:38: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected struct task_struct *curr @@ got struct task_struct [noderef] __rcu *curr @@ kernel/sched/fair.c:7327:38: sparse: expected struct task_struct *curr kernel/sched/fair.c:7327:38: sparse: got struct task_struct [noderef] __rcu *curr kernel/sched/fair.c:8298:40: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected struct sched_domain *child @@ got struct sched_domain [noderef] __rcu *child @@ kernel/sched/fair.c:8298:40: sparse: expected struct sched_domain *child kernel/sched/fair.c:8298:40: sparse: got struct sched_domain [noderef] __rcu *child kernel/sched/fair.c:8791:22: sparse: sparse: incompatible types in comparison expression (different address spaces): kernel/sched/fair.c:8791:22: sparse: struct task_struct [noderef] __rcu * kernel/sched/fair.c:8791:22: sparse: struct task_struct * kernel/sched/fair.c:10067:9: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/fair.c:10067:9: sparse: expected struct sched_domain *[assigned] sd kernel/sched/fair.c:10067:9: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/fair.c:9723:44: sparse: sparse: incorrect type in initializer (different address spaces) @@ expected struct sched_domain *sd_parent @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/fair.c:9723:44: sparse: expected struct sched_domain *sd_parent kernel/sched/fair.c:9723:44: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/fair.c:10145:9: sparse: sparse: incorrect type in assignment (different address spaces) @@ expected struct sched_domain *[assigned] sd @@ got struct sched_domain [noderef] __rcu *parent @@ kernel/sched/fair.c:10145:9: sparse: expected struct sched_domain *[assigned] sd kernel/sched/fair.c:10145:9: sparse: got struct sched_domain [noderef] __rcu *parent kernel/sched/fair.c:4575:31: sparse: sparse: marked inline, but without a definition kernel/sched/fair.c: note: in included file: kernel/sched/sched.h:1730:25: sparse: sparse: incompatible types in comparison expression (different address spaces): kernel/sched/sched.h:1730:25: sparse: struct task_struct [noderef] __rcu * kernel/sched/sched.h:1730:25: sparse: struct task_struct * kernel/sched/sched.h:1885:9: sparse: sparse: incompatible types in comparison expression (different address spaces): kernel/sched/sched.h:1885:9: sparse: struct task_struct [noderef] __rcu * kernel/sched/sched.h:1885:9: sparse: struct task_struct * kernel/sched/sched.h:1730:25: sparse: sparse: incompatible types in comparison expression (different address spaces): kernel/sched/sched.h:1730:25: sparse: struct task_struct [noderef] __rcu * kernel/sched/sched.h:1730:25: sparse: struct task_struct * kernel/sched/sched.h:1730:25: sparse: sparse: incompatible types in comparison expression (different address spaces): kernel/sched/sched.h:1730:25: sparse: struct task_struct [noderef] __rcu * kernel/sched/sched.h:1730:25: sparse: struct task_struct * vim +678 kernel/sched/topology.c 668 669 static void update_top_cache_domain(int cpu) 670 { 671 struct sched_domain_shared *sds = NULL; 672 struct sched_domain *sd; 673 int id = cpu; 674 int size = 1; 675 676 sd = highest_flag_domain(cpu, SD_SHARE_PKG_RESOURCES); 677 if (sd) { > 678 struct sched_domain *sd_parent = sd->parent; 679 680 id = cpumask_first(sched_domain_span(sd)); 681 size = cpumask_weight(sched_domain_span(sd)); 682 sds = sd->shared; 683 684 if (sds->fallback_llc_id == -1 && sd_parent && 685 sd_parent->flags & SD_FALLBACK_LLC) { 686 const struct cpumask *parent_span = sched_domain_span(sd->parent); 687 struct cpumask *span = sched_domains_tmpmask; 688 int fcpu; 689 690 /* 691 * If LLC's parent domain has SD_FALLBACK_LLC flag 692 * set and this LLC's fallback_llc_id is not yet 693 * set, then walk through the LLC parent's domain to 694 * find a fallback_llc. 695 */ 696 cpumask_andnot(span, parent_span, sched_domain_span(sd)); 697 for_each_cpu_wrap(fcpu, span, cpu) { 698 struct sched_domain_shared *next_sds; 699 700 next_sds = rcu_dereference(per_cpu(sd_llc_shared, fcpu)); 701 if (next_sds && next_sds->fallback_llc_id == -1) { 702 sds->fallback_llc_id = fcpu; 703 next_sds->fallback_llc_id = cpu; 704 break; 705 } 706 } 707 } 708 } 709 710 rcu_assign_pointer(per_cpu(sd_llc, cpu), sd); 711 per_cpu(sd_llc_size, cpu) = size; 712 per_cpu(sd_llc_id, cpu) = id; 713 #ifdef CONFIG_SCHED_SMT 714 per_cpu(smt_id, cpu) = cpumask_first(cpu_smt_mask(cpu)); 715 #endif 716 per_cpu(is_idle, cpu) = 1; 717 rcu_assign_pointer(per_cpu(sd_llc_shared, cpu), sds); 718 719 sd = lowest_flag_domain(cpu, SD_NUMA); 720 rcu_assign_pointer(per_cpu(sd_numa, cpu), sd); 721 722 sd = highest_flag_domain(cpu, SD_ASYM_PACKING); 723 rcu_assign_pointer(per_cpu(sd_asym_packing, cpu), sd); 724 725 sd = lowest_flag_domain(cpu, SD_ASYM_CPUCAPACITY); 726 rcu_assign_pointer(per_cpu(sd_asym_cpucapacity, cpu), sd); 727 } 728 --- 0-DAY CI Kernel Test Service, Intel Corporation https://lists.01.org/hyperkitty/list/kbuild-all@lists.01.org --pWyiEgJYm5f9v55/ Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICIyDgWAAAy5jb25maWcAjDzLcty2svt8xZSzSRb2kWRZ16lbWoAkSCJDEgxAzkMbliKP HVUsKXckncR/f7sBPgCwObEXiaa78W70G/zxhx9X7PXl6eH25f7u9uvXb6svh8fD8fbl8Gn1 +f7r4X9XiVxVslnxRDTvgLi4f3z95z//fLzqri5XH96dX7w7e3u8e79aH46Ph6+r+Onx8/2X V+jg/unxhx9/iGWViqyL427DlRay6hq+a67ffLm7e/vL6qfk8Pv97ePql3fvoZuLi5/tX2+c ZkJ3WRxffxtA2dTV9S9n78/ORtqCVdmIGsFFgl1EaTJ1AaCB7OL9h7OLEe4gzpwpxKzqClGt px4cYKcb1ojYw+VMd0yXXSYbSSJEBU25g5KVblQbN1LpCSrUb91WKmfcqBVF0oiSdw2LCt5p qZoJ2+SKM1hulUr4D5BobAqH8OMqM4f6dfV8eHn9azoWUYmm49WmYwqWL0rRXL+/APJxWmUt YJiG62Z1/7x6fHrBHobWLatFl8OQXBkSZ4dlzIphK9+8ocAda93NMSvrNCsahz5nG96tuap4 0WU3op7IXUwEmAsaVdyUjMbsbpZayCXEJY240Q3y1rhpznzdPQvxZtanCHDup/C7m9OtJXFi 3lrCJrgQok3CU9YWjeEV52wGcC51U7GSX7/56fHp8fDzm6lfvdcbUcfkNGupxa4rf2t5y0mC LWvivFvGx0pq3ZW8lGrfsaZhcU7StZoXIiJRrAWZRqzYnC5TMLyhgGUA2xbDVYJbuXp+/f35 2/PL4WG6ShmvuBKxubS1kpFzu12UzuWWxvA05XEjcOg07Up7eQO6mleJqIxkoDspRaZAHMGt I9Gi+hXHcNE5UwmgdKe3neIaBqCbxrl7/xCSyJKJyodpUVJEXS64wh3dL0ybNQrYAXYZJAQI QZoKp6c2ZnldKRPuj5RKFfOkF4KwSRNW10xpvrxpCY/aLNXmShweP62ePgeHPKkYGa+1bGEg y5+JdIYxHOOSmBvzjWq8YYVIWMO7gummi/dxQbCLkfObifsCtOmPb3jV6JPILlKSJTFz5TNF VsIxseTXlqQrpe7aGqccCEF7j+O6NdNV2midQWuZ+9LcPxyOz9SVAbW57mTF4U44Y1ayy29Q 9ZSGTcfbCsAaJiMTQUsU204kBSeutEWmrbuR8D+0RbpGsXjtMUyIsbwVTNHZCJHlyJz9Frh8 NFu8IwEV52XdQGcVLeEGgo0s2qphak+sq6eZ5jI0iiW0mYG9mz+QJnuQ38aCMecFZ/mf5vb5 z9ULzH11C+t4frl9eV7d3t09vT6+3D9+mU5wI1RjDp/FZkBvFwkkMpR7pnj7DJtPJORWRDpB oRpzEPlA2pBEyHlojGlqn7Rwx4WfowJLhEZbKvH77M/vOzZjZBpYqdCyGMSv2UwVtytNcD5s fQe4+WF4QPjR8R1wvXOS2qMwHQUg3AbTtL+9BGoGahNOwfEC8PmcYJeLYrqiDqbiIII1z+Ko EK4gQVzKKtk211eXc2BXcJZen19NJ2RxurF3jThRJIikDAcxIDjbgu2vP0zOgZmbjCM8JZcR gmV2xoAuI5IX/LP0DddIVBfORou1/WMOMWzsXYG1taApri0k9p+C0SDS5vrizIUju5Vs5+DP LyZmElUDnglLedDH+XtPerfgdlhHIs7h4Iw6GFhX3/1x+PT69XBcfT7cvrweD88T/7bgbJX1 4GH4wKgFlQL6xEqgD9P+ER16qlO3dQ3+jO6qtmRdxMCfiz2BYqi2rGoA2ZgJt1XJYBpF1KVF q/OZrwXbcH7xMehhHCfExpmSbe1o05pl3K6DOyYJ2JxxFvzs1vC/sCe7qxM0ZUJ1JCZOQU2z KtmKpMld7gAJ6jSgfLDpJCyl27qfRi0Sirt6rEqMjxQ2SkGy3HBF2941WNW+nA2bJ3wj4gXL 3VJAJ4uifJg4V+npQcBwo40B8EjA7AOFQS085/G6lnD8qLXB3HRUu70I6JvOdhMsMTimhIOo BiM1VBjDgaHkIcaMijXuibEJlXPy5jcroWNrGjoelkoCpxcAga8LEN/FBYDr2Rq8DH5fer9D 9xUEKFoP+De99XEnwZAoxQ1Hs8ickVQl3FXK7gqpNfzhBWKkqnNWwa1WjiZBm7dxLDUrq0Ry fhXSgHqMubFrrBAPrdNY12uYIyhlnKQTbqjT6UeoYoORSrASBDC88pgh4w36aF1vn5N7ZTmG oBgEAiw9MaZ/4BdbQ5K091Cyu2aDkfRVKdxQSub2yIsUzlNRp7O8PQz8Jd9aTlswiYOfIFmc XaylS69FVrHCDbuZRbkA43i4AJ17UpQJh3WF7Fpl1cHkwCcbARPtN5jaL+gvYkoJV36vkXZf 6jmk8xytCRqBWQfrRV639kNIYfYLrz76795tqtMT5z8ptMEYRfpfjdfoBjCUQaaU/DddoKqb VgoDVrE5cmemcekKEs1/c4cwctRASTaGnnmSkOrH3jKYYBd6ogYIc+82pXHrHUx8fnY5WBl9 2Lg+HD8/HR9uH+8OK/7fwyOY2AyshhiNbHCgJsuDHMvOnxhxtD2+c5hpzZvSjjKof4q5dNFG dmzXdSxrBudo/N9JEBQsWujAJ5N0pArbwwkrMEd6TlkmQ8WNxnenQLjI8jsIMQQErgKt0HTe pilYiMYWGgM0C722xsAGWtUIRstEsH9TUQSO3ujNgAg3itlzov3g9UB8dRm54ZWdyUh4v10t a8PrqCcSHsvElQfgf9Tgghgt1ly/OXz9fHX59p+PV2+vLt3I9Ro0/2A7OiKrYfHa+g8zXFk6 ssJc1BLNVVWhv2AjLtcXH08RsB3G40mCgdGGjhb68cigO/CxeroxAqZZl7g2xIDw+NoBjoKu M0fF3ZSFHZztB/XbpUk87wTEoYgUxr+so/ZtJs2Qi3CYHYVjYKNh7oUH5sRIAQwG0+rqDJjN OQ8zJzBcrWVpQxPg8DlxHfReB5SRetCVwghd3rrpH4/OXAySzM5HRFxVNmgJyl2LqAinrFuN gd0ltFEQZutY0eUtGB5FNJHcSNgHOL/3jllowtamsaurNNhZOmeJ3HYyTWEfrs/++fQZ/t2d jf/829RpV2v4zlNrgtzO0adgt3Cmin2M4VlXj/cBpq7O91rA2QfB7TqzPmgBArfQ12N4oPfh YNrcXjM8TR7b8LBRHvXx6e7w/Px0XL18+8uGZ+a+6rBBzp11V4UrTTlrWsWt1+AKZETuLljt hxwdZFmb2LLbJpNFkgqdEy0Ub8BIspk/bwzL7mDQKlpoIg3fNcAkyHi9ubZIiZey6IpaU0oL CVg59dJ7al5IQuq0KyOx0HpkgT75Am5t0SqvB+tFyRK4MAXvZpQUlAWxh4sEZhw4B1nrJRFh ZxnGED3zuIedcP1GEl2LysTcF9aRb1AQFRFwVrcZ+GraSF5RCTSwC4Jp2rB/3WLkGRi2aHo7 eJrQhs5MjRM9EQENSYcIzdjJr7D5uUSrx0yLznPFqjqBLtcfaXit6Uh7ibYlnbsEDeqbHKHk d83ngVdVBQq5F+s2THXlkhTny7hGx35/YOfu4jwLLAFMYGx8COhMUbaluXopiKdi70QmkcBw GLiYpXZsBQFy1oiLznNQkX5T7maCZLJ5MHSN/i8vgNO8cAuMDzfKXlrKg+7xcGepZvk+kxSj DvgYbFjWKqrpTc7kTlCN85pbrvTaJaUgzzwDaw9kBlg7CyyxA4FL5WSM/tRop4IGjXiG5hCN xKzkh/MZsreFnYPrMQ7EiiJdNnP5VC5JdVOn0KHYD5hVEkDFlUTnEMMbkZJrXtkYCiZVA5Zz 4xM9AMOzBc9YvA91QmkyiDRTDHjLFAEQM6A6By00R9n87/VDrz4db+jh6fH+5enoZXccX6vX KYrVDte7eKNS5LbnmN5wXxjAuzW9dwzmVjumTnxtJusC/8MXNJ74uKb5TsRw7UCyLO0f3OsH T0agDAeQN/oHY5UsdJEIBdvZZRHagMFhxzWzpUG6EbFrIcNGgeIElo7V3s3cBQiQ2sbGjvYj mzsbgyHypWiATXfbrhhhbY7oqV8Pb0TUoNwxz+4cuSiQWYtBn2Miu+VoRx5uP505/wLzBgOu 4INIzAoo1ZqA3cKe2iQ/5i22zi0uG+XJIvyNlqFoxFKQGjsD14fWiLjQE/6xMXPAhVpEtqWg RNpkffXb15usaPyv+d6zLXlKi9P8pjs/O1tCXXxYRL33W3ndnTle0M31uWPpW1GYK0zGu9Nb 8x2n5KOBo4dFOV4WWbcqwyCB49hZhBbZbAgE2vz6QpkP03mXtKQGGR0KuGgK3ZnzkPvAh8SA BV6DU+3BH80qaH/hOUG5bOqizcKcIUp3NMhKl4DaehuWcok8NWw9802iJblyqxVCAUktI6Tc yarw1ElIsFhyEJeJ8athibQjAuJApPuuSJoTYU3jZxcgvGpM03kK4YTDNmMmliRdIFgNzkq1 4Yb120vT6LoAF6RG3dS4uc366e/DcQWK6fbL4eHw+GJmwuJarJ7+wsJVx33snXPHe+y99T5B NkfotahNDNbRlGWnC87rOcR3RgGKqac57ZatufFlaGhfu3k+8a6HzbypeL5JOfekJlRcOG76 9jer4LFQTcSCT1FrJ6IPVn42Uxp+4AC32cHNfg3cai4trEzKdRtGIUqR5U1fp4dNajfKZCDA nQ2oODtj1MPQ1SxAZyjN+jPf1PUQJgK/4FjhSHWsuiUJYyjSOgkHLWoRgoJDNzDFN53ccKVE wqnwENKACJ0K2FwEC/ckYg3o7P1k9Vho2zRgdT0EywJPdN9vn6VYWt0G5iaDPlNWBZCGJQEk sffRBRlfTHFgNB0uZnKhYnOai2iRzHZoRAZwUZcimJQv8ukRWJYpbhRcuMYcbFQWMr4RZXYL UCS1daZYEk7xFG7IMPjnU8fIMpKqX7V7KcHxA1keLnpYoZC9KxNwc0SFS2xLHh5h3Gpw90ES N7lMZhykeNJiRSamF7YMvGJUS4vltoZja+4IAx/e5zj9IRCxfDOTukmXFuOUb/qN+A40BSUP h12Fv+GqPbgyVGCWG3hi2aoFYTr400OR3So9Hv7v9fB49231fHf71fO8hovg5JWGq5HJDZY7 YyihWUDPaydHNN6dpZIOSzFkIrGjf8ntk01QYmjmZ0FJSpSqpkTj++djbNW2EUtxknEHnIkv 7JE7Two/zm5ieQ8vq4RD/7OYjHMIVV+tvDm5ed66XPb4HLLH6tPx/r9eMhTI7B413ix7mAnx JjyIe1n3pA6EqOHROB5ahz74IJ0Rt+ww1ZwnoHVt0EmJinqBYAa6tHHM0ggNs+DnP26Ph09z 68vvtxCRuXhTcSZxicYNFJ++HvwrJYJiiwFmDqEAe5OMUHtUJa/axS4aTpvyHtEQIiYloUUN 4WTXdJ5WNBrT/2rEmq2IXp8HwOon0Bqrw8vdu5+dKA8oEhvIcIxEgJWl/TFBLQSjpednXpUa ksdVdHEGS/ytFYoOyGCiMWop9dKnIDG45sdDqshnUSyoidxdWVicXfj94+3x24o/vH69DdjK hHHdiJMzxs7NpPVO2hw0I8HwX3t1aV1J4JLGm+ZsKmaG6f3x4W9g/FUS3myeuHUy4AjJNHV3 PBWqNDoVvKClOEW67eK0L0KiA7dSZgUf+3JpbOX+4cvxdvV5mKQVPwYzVLfTBAN6tjxPs683 nieC6Y0WNu+GLQSH0Iza7D6cu3lOjQnN864SIeziw1UIBZ+9NZk670Hc7fHuj/uXwx36oG8/ Hf6CqeNVmgkiG4cIimpM/MKHDeaVDTgPG91nP1Aseo752iZRydP5tS1B4rGIjD7aR4cmf4UB u9R/fjfLzZoNn/y2tjJcioWOMRq1gcWK2SQsawYXoIv0loXv7gSsGOsLiOz6mhx5jYlPCiFr Gt53A1q2S6m6vrStbFANXCO0+alnTUDmlcVNr7pMjzn4lQESRRCazSJrZUs8qgFX3Ypx+8aI sPNBCDQYH+lrOecEYLT1gYsFZB9SLmebbmduX3jaYpZum4uG+3X2Y8GAHrPupjTYtgi71CW6 6v2DzPAMwJ6FG4fxDMy995zii2hLp1071T8efFa62DDfdhEsx1biBrhS7IA7J7Q20wmI0EbD nHqrqq6SsPFemV9YmkZwA3omaIiYUmJbWmBaUJ0Q4w8FZ6rfIoxSUqc23eTTWLeCcFS5bQeu Zs77EIOJOpFofL1AkfTcZW+DfRLQ50jDyfQioWcujLwFFH07mx5bwCWyXahg6fWkqOPOvscb 3gcTtLJIHHpq1zSPkeAEqq8CcsVtjzn55NMcZQF8F3Q9q0CZJPF3wHFX5ewtwxgTKxpp36// KwGIAPfNJcIxmkvtw1Ygbc+bpgwjZOB48QUciTZlQ9hbQLf80MvTGvO3XuGll3ip2oQElyF4 EOUVJrRQq2FpFMG1i3TEUPayAB5rSMOgo+FMg8SAMhgZihxKy9SI8WY/W0cyZOB4DMLK4WtA tRjsRM2L9dooCIjt4zvRoE40L22Jg8ChEQckcluFJKOeMSOY5JdXPjctwatCDK0InAOpAP1W U2Ej0a9TlbjUiUtCdNWjDTlWX4fTtFzfv7OdWwawwcJmCMb6zYmid1R8lYUiSYusD/K/n9n/ PZ4FdsjoQETCllRQ+43MNp6WU4I8QE/VfYNgESCu+zf8autUTJ5Ahc0tA5LNKdQ09Rp2Enyp Ps/mmxGjMQkWD2Uxoup1q6zDpn1Z+zxVPpzwYAIvY2Zf2rCKe/bydXbPl56m+GK5LzwHYRLU uLt3DR2EyWu03kcsN29/v30+fFr9aSvT/zo+fb7vg4CTgwZk/fGdYgFDZuuqef+EYaqdPjGS tyf4XRX0XERF1l7/i580dAWKoMSXIe59NI8jNNbkT19V6QWey+49n5lUMLAGo8vRe6q2OkUx WLSnetAqHr9EsvB8Z6BceAnVo/FkFSdrLXsK5I0tmLRao2Ycn6Z1ojRc5G4CXLkSFgeXJunW +LRksVdt3/6O6bEpPY3XiqwhBEnoaBWmq3PHZazsTTFVk2Z7Z6pjyuA1Eh0LVTpfsjCnbhtb 7eOa4mqr4RovII0UWMCNEsR8BySZSjonkmVM2Fht6aYz+HixKpwRcEnB6hqPjiUJnnRnA8OE MB0e3nQRT/F/6Bz4X6pwaG0ufqugc3fNU17ZiAL+z+Hu9eX2968H8z2mlSmoenEiE5Go0rJB QTPTOhSqF0jO9bREOlbClbE9GLjW/baRxKROWbsSYmmCZvbl4eHp+G1VTkHKeYL9VL3RVKxU sqplFIYiBqsVFA6nUBsbMZvVRs0oQp8WH6Nnbia6n7H75n+SDV5xAhXAsZUJpirBlixeBv1G KDaCNA4ea7wQHzMmreJ4RT3TmvgkTGyCHF34Livfm6ILcDXDxzW2TFmiVTQB19qt8e/TNGZv 7adEEnV9efbLlcf531E77mNIyUtZ86ee14GszMGUspGsaTfBy6tMZTEV9A8eRZdssVBixLkZ eATi4xJ9/T/e0hz3gOjqppbS4fGbyPVQbt6nXlHnje7fuTm5yAE2S/QNFsUQicSHGkMgzztF rpQfBAg+Y2MCYAY+9xpH4Vabpz2EDwUCUdvvpQCySwuWUXK3Dmvl7MPLbvZ1j8lSauulr5R5 kzKuF/MspGURNfRQ8dFwqw4vfz8d/8Rs3CTInIp+/PQBMQfQro71jL9A3nrhbwNLBKNNjaag l71LVblcngLzxqpDKuFilzSlZmr7yhm/EkTnbmp8bIv5VNCXWO5MJcqAqK7cj0SZ312Sx3Uw GIJNGd3SYEigmKLxuC5RL3xezSIzhQxYtjuq7txQdE1bVdx7qAHqG0SjXIuFiLxtuGnokgPE ppKuge9x07D0AHgsHaNfixgcGI7LSFEvBLcMdlyuC0SGC0BNXA9gv/s2qZcZ1FAotv0XCsTC uWAwbE8zOowOf2Yjt1GvRAeauI1c521QQQP++s3d6+/3d2/83svkQ2DQ/z9nz7Llto7jr9Sy e9GnLfm9mAUt0TZjvUqUbbk2PrlJTafOSVI5qbozt/++AVIPUgLsmlnk3jIA8U0QAAGwW3Wn hb9MT4tmraPCSCeiMEQ2wwH6eV9jRinB3i9uTe3i5twuiMn125CqYsFjB2vWRWlVjXoNsOui pMbeoLMYhMIrBu1Ul0KOvrYr7UZTkdMUSZPDktkJhtCMPo/Xcre4Jud79RmyfSroYCY7zUVy u6C0gLXDbW3Mdoa25VQwN98tDUhYxgYE51hacLmugNharknspriBBPYSR0w70Sc1YhhuGdOz UHHZG0VF+80nIVPDplQxKaPZmwlkDdoTuBoQWdgpEdl1NQkD2hclllEm6WMsSSI6bg0044Se uzqc00WJgo7VL/Y5V/0iyc+FyOj5kVJin+Yz9gQZ5QDquxxR6QXiDK/NQD0BFdYVEjcwfQIl 9BNZWF7I7KTPqmIyap50bjI8ce00WXHZcyAtmMMPe5hpusq95iUc21KQNlmKZIoRx8jHOarH suIryCJNcc/SzRRVbk1iOk91Rc2urK2VAS90C09WrgtPwm0yGmF9RakYN6KeJkqE1ori0OYg xrRgGt13Xdvo5tGTdppUI0wRWzRZWa9yX/R9eH9+ex/YKU2rD9VO0kvb7OUyh7M3B1VimDyi EcNHxQ8QrsjtLAyRliLmxovZahsmKGgLA1dyHG+LOVSIwTqrUibWh6KveLvDrRyMPGo6xM/n 569vD++vD388Qz/RePIVDScPcEoZgt480kJQ+UE1Zm+yvpnEB26cy/agSJcyHPu1I5Pb30ah V7nLFBoEH1cdCcUk45LF/srl2M22TP5fDUdgQh/uRpjd0jjqlG7ZHWZgQHW+7y1sGGhekrhp CoRKcssQG4is9hWo3S3rGt539Sl5zBTGz//z8oXw2LLEyj/F8Dd36BWRc7s0/NHkzfWV4EgZ 6w7tQ4dYoYvUK8ZAqPjBDtf5wdKz5JGh9eZDxLTbsEcI2jgtQhjXQ5LhIsZ4Fw5H5VYyAPSS r47U6YgotL7h5m38uoflqpw+LhAHXJrHCZo3myobPxB/NPC6ERa2xCt2ZnINDTOVBoe+Hfx4 I8WHJsYSyjLE/9CncePjhv6WQw6HsC+vP99/v37HTI+9y7I3QNsK/stFOSIBZhVvjVV8U2tM JFSP2hA/v7386+cZPQ+xOdEr/KH//PXr9fe76714i8war1//gNa/fEf0M1vMDSrb7c9fnzEA 2qD7ocGkwH1Zbq8iEUuYIeO+bQaCHaVPyzCQBEnrMny35s6VmJ61bkblz6+/Xl9+DtuKcfnG PYus3vuwK+rtf1/ev3z7wBrR50a0q2TEls+X5pxPdTL0O3YqikTJZHIUhRpIFr3n6MuX5gR4 yIf3GUd7o72XiXet44ExMHnvJdM/VWmx9RhbCwOp6ZhRYhoIBFksEs/7pyhtNZ1/sElP255d nUPu91dYGr/7Nm/P5sbVu4ZqQcbYG2MOWecSqa5K0VXidKT/yvjFdYPQ9YokgEPZ5mEhetl/ 0F60em1sD/yx03HTx84MbC5hMQWnd4nVDTZe5MelOpGWzQYtT6XU48/Q8Nx8C/oWuitRVisk EuaGsCG1rwR0YoiTIsUEgTKPCCD6dEwwG9QG2F+l3Kv2Uu48m7v9fVVubuIGpkG4x+ucH0O4 6/TSwdIxME3d9IxtTW6O/RY2jaharuKUpj0CnW+NT5VZatth6hFYbYYpGlcdkh0w+7KLgfhq BDdno6Z5XcnKlYG1QpkUg7VoGSvdq6s3Zg1gHKLXIpCRkceYE7/QNszhWDmIuBGXZm+Xacaz gX6/o3ImP/eiCPIt3jtUzMUJYLcJhpq57qQAtHdHJOqQbz55gJGHDcCaW3QP5q0b+J25wW35 ts0KEfuJxSwC7RsezF7ZDz2snZhh64LqxwK3gB8DABB7wX4NFJrDZjjsPgQOuaVVU4fGCNWM BtuSiXq1Wq4XlGTYUAThajbqDHpFX13/We96xtzNGAaWwnQ0gfZtXrX31y+v3928m1nRhGpb Y8AplZQw5MGtEPXy9mW897TMdF5i3LqeJqdJ6EePxvNwXl9BtKCWJbDu9GIWjPOJ2qTozs4Y 5ERWMYk+KrVNuey4KtLraahnk8CtCbhQkmtM8oQrUkWMAXsPfC+hAuBEEes1aPTCVUqVTsL1 ZDIdQsKJx56aQasAN2fygLQ0m32wXN4mMS1ZT6grsn0aLabz0K081sFiFRK0yAdgGK4yKqat HuU2uhS8otfKj6O72978akT8q463ZDaS4lSIzOUve6VBe1AHeQEBw4kei8Jmd/dM1kBgOUED RXkNA39ErfONhFM4dST1dhEY+FVU4cyxI3TAubdgLNhmNSC60OBTUS9WS+rL9TSqqa3foet6 5uQ6bcAqrq6r9b6Quh41UUrQvWaeE4/fUWeUNstgMtohTXjYX5/fHtTPt/fff/4wuXSbKM73 359/vmE5D99ffj4/fAUO8PIL/3RF/AoVc/JM/H+US7EVI/X08ep4aWIyMhWe9t1m66GV+Q4L /+4QVDVNcbJy+CmNmOxpMjs/UuxHRvvcEynw0k0kEcaoMGUZkrLS9QcoYHfQjEtsRCauQpFz 43Fzz5yl4i62TqPB3BKNtw4i0cvLXX3UB47KcNQDjyf7DpeU8iGYrmcPfwOZ//kM//4+rg50 FIkmWk8HaWDXfM8MU0fB3eT0BLm+kCN1s3nOhIgI1lCOOY6MVkCJndAIm6TTOTHMJUDu92uT m9fB6BsiPDVJDHZjd+S0YPlogjJveJhUkmHw0DW8qWNuI1nUqeYwKEgztscN7LFjTN897pg7 SWifHpoW+n7BXyBZMv5nR7qBAL+ezMyYx+mYr0+yopLDWpO8kXxds3yS5nRlqGJwyxME3gHK GsZegKe+/PEnPu6preVEOH7dniWmNZJ98BPHmI7+6pW/Uk9w0APfmoIK7y7YExzAsqaH8lLs c9LP0SlPxKKopJ/ExIJMRjDcpHcK2El/C8kqmAac01D7USKiUkElXgw86NNRTnqBe59W0nfp BG02Y0yczZFV6XudSMWT693pobwEFfBzFQTBdbAAHZEMvp0yN+RpfK13m3ttAXaRVcq7BBGP jMeq+10Z0R3A5ZR7NhdRJdwdfhKwCHorIoYb/DurwL6q56/nzYy+vN9EKfIueq9uspruT8Qt jErt8mzKFkZvKJsQC0Ve7kPuKrjvcGSTEzkfUbdbzjeNKdsTYwTpq+B9dFJHb1yr/TFDC2CG ScTpS0iX5HSfZLNj2I5DUzI0iXo8Di3DRC/2MtHKk+Aa0LWil2mHpqe2Q9NrrEefqBskt2Ug A3rtGnIg4hPjVO7t6p3EDModv6fbVF/xqSRaIMlIT1mn0tjn7NaJMSHzbrpfNXe4fUVJSHv2 aJhqJrWRUx5mCTEP3/SrXoZ32y6fmvdS+0E2kGtW4DsMGRw8mCPkOuQK45Jskg6SOe6P4uwm zHJQahXO65pGocritSwgE4fKJm2oRzdh1KAdrUwAnNmMquY+GR4yPWbG1k7zyU/pnbkFvf8k /WTt6Snl3En0YUfXrw8XyjDiVgS1iCz3llGa1LMr4zEDuPlI6Xax+nwTvT3faY+KSn8RHPRq Naf5kkVBsbS586CfVqvZSOWkK81H2yKLwtWnBW2pAmQdzgBLo2FIl7PpnXPa1KplSu+T9FJ6 WeXwdzBh5nkrRZLdqS4TVVNZz7gsiFY09Gq6Cqnt55YpK7QQe3KjDplVeqpJP0u/uDLP8pRm KpnfdgVCn/y/cazVdD3xGXd4uL86shOcqd4JYx90ppUl58P84LUYcxHeOc1smAb0ZKcy/z5v D7I0rFByYC8SbxC3ZMJ8t3CZaYyt94xM+d0T9jHJd346xsdETOuaFkEeE1Y4hDJrmV059CPp Uu825Ig2ptSTvx4jsQTej7d2dKEN/igY6fIxQqsj54JdpnfXVBl7Y1MuJrM7m6aUqD95koBg DAGrYLpmvKYRVeX0TitXwWJ9rxGwwIQmN1qJXrQlidIiBeHEu1DUeCwOFTfiS+km43EReQIK Mfzz32lhvPMAjnfy0T21TSvgwV6B0TqcTIN7X3mbDn6uGQ4PqGB9Z6J1qr21IQsVca5FSLsO AkZDQuTsHjPWeQTbWda0hUNX5rzxulelsPA/MHVH/7lzURSXVDJ3jLg8JG12i9AzOGOOG3W8 04hLlhfaD76Lz9G1TnaD3Tv+tpL7Y+XxYgu585X/BaaZBOEGIyU0E4tRDeyD4zJP/kECP6/l XjE5zxF7wvQVigzJdIo9q6dB3JyFXM9zbsF1BHRyfqdwe9HlFt5cfSHbTBQTB9PQiFrx7LWh SRKYD45mG8fMawSqYJi+8b3foE5A25L2F84n2EqfKFeu1/OUjvFAKZx4RLhxI9PtbQFhsSSw TqsSJmywKGi4phXOo940bu3GaO9OG6JA6aXHGZEH0NoYAxyiC7kTmnFXQ3xZJauAuf3t8bRJ CfEoNa8YuQLx8I/T5xGtij3Nys72KHB+9Wba1J7EFM5/7xp+3vDmBeycEyX9QlM3EsNFOWY7 AtuaRghUqzYzqFIrT59Cp0wmL2dRKp36YT5Eob1uSiElyMrsmLqKFoEuhe/m7uE6qYlCakUj 3AyELrxi6J8usSsUuShjP5aZb2s6c1dFaY0Ga5qjHT+pSh+vfCwvcBetqJAOE//Shwn0YryO iWvIn7/+fGdvO1VWHN3gefx5TWTs+JBZ2HaLrk0mkGSAsYkpDujXN8CkoipV3WBMY45vz7+/ YxrgF3zP9r8/W5+bvgP2M3wujouEsiSf8suAwEPLE6aV/jEEog/cD3dUuFgJ+8FBXja5cB9D byHAMTynKwdezOerFdGwAcm6b12PqQ4bqrLHKpjMJ2R9iFpSB7dDEQaLCVFb3ITBlYvVnEAn B2zMGL4rVM6ATTiXpD6qIrGYBQsas5oFKwJjFw/VsnQ1DafkcCBqOr01HKmol9P5mvw6jeit 2BMUZRBSukNHkcmzfatiiMCYRTSIaQLXalMEpsrP4iwuFOqY0RME4nwhyf6pR71gLl/6dsJm pTh/P2FpeK3yY7QHCFlLdU5mk+nNNVlXtunjj9EUdmWedWpJRAEKUk1+viEj4Pr5qw7mMYQR n8pt4uVWtDPPVRbacy/rgFeRFFzirpZkc6GMGD0ebSnw/8KzNPZoUHJEga+y3ammowPVkHEI 7mijy8A3vUeZPCmDJLc9ViZ44Pl3yWPsB1qgJUooflbJrglmRSmyAVvM5sq34JSav9mqrSOs 4xJtoKC8JtLUOsTAGpqvl7MhOLqIQowXBPYfHbnY6k+6rmshhsX5bLRpaTednmfYEIlugz+I AxHzO1ABCpbA5DLwdEMLMTKziGTEJIZwqVQBotc9qr3IQBwiX0/viQ4b+NF30cE02oXbwwZr JxJkLZCOKRbV9BPnVIP+5uZ3dYAY1VDI0g9LcPGrVZGuFhPn5HGxItbL1WzhNc9DL1fLJdX3 IdH6ZhHr4Zq6RcpZPX3SDxRXBpMw+FjNqMBc05pWwzzKI8gFqo4UFbbiEm6OYTAJpvSwG2TI jhnqEviKtoqy1TSgXwvm6OeT+Z2WRZdVVKUimE3Y+g3FLgioY88nrCpdWMc4tixDQvMUghDj Ycgxs/hZW9kNCo/dUARsHRg+ARuKRu5FWui94mqXsmJKxRc8Rc0NkMUSAQ4UbR1N8ZaYrKbR wLh6dnkeK+o2zeujivFVNLJ8lShYtQwj0Qt9WS4CGrk7Zk/cqB2qbRiESwabiIwdt4S+JnBp DHO9nleTCSXmjintyiGLAkk7CFYT+srWI4z0nDPSeXSpDgLat8Qjk8kW8/Kq4gO05sednqq0 XhwT85I3Pc2ZrBWzBdLDMghpFCgEJnCSna4YlO5qXk8o13qX0PxdYvAQXZH5+6zYdfEh7nyO q9WyrnlWcQbVK2DWurE45mmRa1WxfC+NgulyRdtKhoVZFvAh0kJkgyQiLOmUUh6GRKryPb+G LauO5YbyvBoS2i1OSiCIjtMIV1ww4UlUaeVXniAeGstGjcDIP5Cp7hS0y6u84NGfMHdNdHNU yEijEVWobhXydEG3AObaeDwPmGdtNh9EETDUdgff6oDQl4/wCvO3qkJOjoEpNQcXwy4AHU4m 9U35wNJQAvCYan6rmuXtGpZXRboQeqwjEszZV6ZQDFeBVokUZOY8j0jfOl50FYSMJ7BPlm4r Si8dEBXMcauPJS/2AXILqtP0QxK4rlcL0qjuDX2hF/PJkpV9nmS1CEPKwuVRGc8UVsDME7Up 1fW0nd8TV8t8nzayN7Og1aOe1wzbf8LErMrrS2NvUZpztFAzOpZr//n3VxM1r/6ZP6AJ24vV LN1IbyKYdkBhfl7VajILh0D4rx92a8FRtQqjZeAIkhZeiHJgymrgEdp3iNG1aJgANC8NKinF eVxS42R/qzTAYcrCYdtgHBojlg8uNgTU2m99k9dRD+N+G8ROpNIfpRZyzfR87lhzO3gyc0vu wDI9BpMDLSN2RNt0JEY2V6nUqujim6h7D3vZ8O3z789f3jEXxzDst6q8589OXK7c9epaVBfH gtC8Cc0B7fsR/xXOu2zTiclRiXkUMHtEF5n2/Pvl8/fxQ5qN7cNEtkduLEWDWIXzCQm8xrIo 0cdZxiYNqPf+hUtnI6+9xdeigsV8PhHXkwBQxqTVc+m3eN9IWaJcosiGLzGNcbNNuQhZi5Jr ZmqESOq4d6my0niBOenMXWyJ7/6ksiMhK5J1JbOYyXToEgrzMuj1NHQ7o6bpjG+HMj2Lz3er KqtwtaKUVZco8Z6t9sZOxUTl+dbk+MGUTCOGnL3+/Ad+ChCzZE3YK5ExqCkKtMEp6/TkkjCu T5YEB3LoauJT+E8HOEBnwQ1L/cTE5TdorbaKieprKNAGruhcn20ZUZTVjANHSxEslF4yfg8N 0SZKF9PbJM158akSO9bb0Se9R9a45xT6LiWcOLfQZUHLaw16q2Eki3t1GCqVbRNZ3yON0A0O 38qJ1U6B1MOkK2mXH0oswZROptpOUsFEobYLAdbmuFVtELHP2wdrNI2qMrHXAuMVmsHaNcmU mOqz645Zw1n+lHOu3Uf0uKqYPNeYxgaWfnaDj2Ouos3AVA9HXVEC/ycfeCmNI0ovHSQFtSuL grv7byJQo3HkayteFqnCC4g4casxUJOsrHlgphdHDQYTNNhnnrgirZ+X9aPZem9uG7RWQwDw jAGoe8990CzMW4hv57rgzbjCPn/EuXkarf+iA9kn3FWOOWgIrPUQIhAYhUmAN2I29VKL9KiT ItNGOvgmfecIE8E6z3Z0qTX6bpW0vx1e2MEmZiK5z4LMaYVPPEjvEZDTwQL6XXAa5P/oSRsR t29oQXqBw3rbRXsZHezwe9shgn8FaVaSiXlivB8iYLPJxUve1EIwKZL7qvhIfG0/aFdBedSV eb6gy5lmfV7CiHAACv3wZHxIHWAgLJZyR4fFItpcqAMbdrQqBA/fnjYwfMXUfeUdgemxbpuV /vn9/eXX9+e/oEfYxOjbyy+ynXC+bKyiAkUmiczcpxSbQkcctIfTjy20+KSKZtOJ46LSIopI rOczbx/4qL9ulFqoDPn6uJkwuMNWmucg2i9ulJkmdVQksbskbg6hX0uT0A4VD6YOc5Pvrhnx /V+vv1/ev/14G0xHssu9V3haYBFt/XG0QOE2eVBwV1mn0mHmsX4VNH61D9A4gH97fXu/k6HR VquCOXOid/gFbXLu8PUNfBov58yrBhaN0ey38NeUkYkQr7jbE4PUTPZzi0yZZ1IAWShV01cj iM2M7YhvlA2Dgu1EPyRiFpDS8/maH3bAL6a0KtCg1wtaxkX04OgZ4opynBETmRq3RnSUjpPE Gk7577f35x8Pf2ACPPvpw99+wLr7/u+H5x9/PH/9+vz14Z8N1T9AGfoCe+7v/gaJkHk3DMnb 6FrtMpN1Z2joHaB1Qp9rA7JWSbtREu2TjEQylafQ366Nc4pXluG79v0S+5p5Tr6wA5QHmRbu M1DmNGl93/yVGAlSwfSIygMZQWlXSooXD4NSmaS78i84Mn+CAA40/7Rs5PPXz7/ePfbhDp7K 0bfn6J+Pptk2eR3TqDLf5NX2+PR0za0U6H1bCXRwO/HdrVR2GeY+Mu3P379Z7t403lmYfsPb 88E/hK1jXfvKjjfdW23vXRzOTHJhb+ir48YvxazV4VAZYJPVi5tEQ4L51TDV43gJY/4/NpS4 J8Ej5g7JKMeu0+FRH92coBE+VAGQ5pWGHhGfSbA+RT68F1QVileA2pP70cttiilI27ydDqgp 1IcZmdZaEIHVpZ/fcFlH/QE58nA2+U2N/u+XhIE6+H8be+rj4KzfeE+AG+CxQh0lcXxUEdwn 1vgPY1/SHbeupLnvX6FV16ZfF2cyq85bIDlk8oqTCOYgb/Lo2br36pRtuWW5+t3+9R0BcADA APUWsqX4gpiHCCAQsSaiDX2mmZTIqk6LlaYAI3JB/6q03i1henUbQeEH9pv+TUE6cEekuXY3 PFxYdcVKNQdaVcfOraosBzsin8q8HFI/F+dGoC2melO0chkwC91dmXclz/gAxNea4kmF8RFP 3QT2W4e8PkBcnG7p+ddX/aUv0q745taSxvg0TEvj02PzUHe3w4NsSC0tEHxWy5sYt4oYSx0l YtFO65UdP508go5j/6f5HfzYThVET7Rth/6dbTH6kGeo8si7Ono1p1XPJMlQ2mvW0c2NiHDZ t5Ux201ntKNf40UDpeMO6JFa4M/1EyUpP3f87vPXF+my0FSw8LO0KvEJ/b1UZI00R1BcXJAN qTARWyTFhnOKLOUfIqrz++vbWgcYOqjD6+f/MoFcRCm5G5/14RsTa1Sr91fI7fkONlQQAb68 oB9mkAtEqj//t/ZUb5XZ3FqmYje5vx6BmwiFo5y2A13qvGt+VOqKU5MatzOYEvxGZ6EBY5Tv uUhLU4+FYdyPPWoFmBmunecob1Jmuu6fayJnbOdEW+nVaef53El0e6EVqm0CJrpGMDx1lRP0 qxs6V73lBH2oC4LcsQo20XUybZpX7UDVd36wduPmkF3x7tnj0LPS4np5ZEqPed8/nsuc8oMy MVWPsBkJs/xVUY3HfnN3VRl6lr4n2mjft9dBvTmci8Kapm3oj9I8YxiR4379Gezk57wnU8yr +yNe1GCSRGPmsCEPfH/qKRvxefoI7010qUroJ5m2AfyGF249jSG1KPMqW6dX5ZdSlEfdO+cx dGr6kuerKBIG21Ae5pYXK0gPK9jPp593P16+f35/+0o9BLaxrCYEHuIxond4EFdJSHQpAjuH 6JmHUymMP07KoSiOaHn5qBNERGmMAzGG2Qpdb+JoC0OtFdrh6H/bSKXsH0yfOnK9MmeSmhTs kmqwYnnoJw8RF/uAiXg7U8aqAh6XTCMl8QjMWQ4gZYDdb08/foBOL4q1UqzEd3FwvU7ipFZx KUh/M8oGi2dHxjgWBR8FZPOj7GKL2ydgvAC3o8WA/zkufbiitgipd2t8vSnwCvKxutBXUAIt SQM5AQn3MedVT+yTiOvmTpKeN59cj3pIIYcHq1mYeTCu2/1pVcb1ha0xtFLdVZEgn69JSB9Z CfiSZjs/oE+lBMP61MEYCrdCvDUywzpTo04KOiBu/G1E0bxlY1y6ToDHFbcgyY32RQRdAd7c aNXGIwZf2UpdxG6SXI3BLvvHWD9u5ZDEqxxsR5QT6LukK1PZ4GWD7oKNzC/cjdIgUY8rNttp Ps0T1Od//gC50NAOZP9Y3+2OsBqXQDYDaJ2VWTy5sDjUcuOtB7m4PvA3xpRgIJ/3jnCRhLHZ P0NXpl7iOuaRjtECcuUrsnXLaBXvy09tw4wK7bPYCb3EyBiFwjA0iONhoE6suiT2r0aiSAyj cNV2+t43N2gc6U+iZYsIyW5jzKGhp605he2lJ94i618JIImsQ1XgO9fs9pHsrZaa4aG+JvS1 gcStL2gnGL1LrZKVFvgbSxjgpluOaS1aj4M5HtZHM2fjkkMOlsHmzEP2Jchz7cYyIcLcyRVs kymXXB59syG4+iz1va0W4m3GzmVlusVWwnlRjYTHD5uTCMQGNwpW/SXsnXb2FVAuJq459lPf TxJi6Je85dSRvNydeny+5q/3WRFiiDZXWVdLunDge2pMjF8RqIDPL2/vv0DJ3tjF2OHQ5wc2 tL25BrTp/alT904ytembizsJdu7f/u/LeIZNHAtd3CnqLroaaKl+WFgy7gWqRK0jiXKBoiLu paY+MSWrBeEHOqwBURO1hvzr03+rZqyQ4HgKBXqmXoTxFEqaiKglkADWhnwQqXMkWn1VAD20 ZHiURuSKHOrLCP3TyFogj76CVXkShxbetHTINVXncK2FIP1K6BwJXedQfQOoAnHi2ACXBpLc CehMktyN1Smij4xZERRhUjFYlX7OsZA3zooUJl37MxH8dWBa8CqFoxpSbxd6NFgPETr3IDEM A1Hp64MOb2S6lvrX6GyMRVS+z9GeBuOCqKe68jMdUyyLYJKpoLVN+anrqsd14SR9fZg7MWVM MipbxKjdsSzFKOqwpCj3MrChJDsvHL9ZRpGQG244Z0/a9cEICHZ6cgmJYs0wwiKioJHZWCji lT2aCR3QMgVEcUd9GDt9kl48x9XiD00IzpiImtsqgzrXNDqRlaBrgtuE8D31mGgqO6DqR9Ir bW/5aEpy/+DFV/UNjQHoZ6gmeMwe7GA23E4wSqAjcDQuvTCVF0R2Vxej5xYQCNnrc0fhmTG1 a05pSIaldPJvc8giNUmmVFf04pRXtwM7HfJ1NfGJcewEZAVGjDZk0ZhsIuFUz2mobjKBLgaj ltwjJpaSd1gidYBMkJiZztbHo06wni6oNnma6j0hlvO1JU8xONeDohr8KHQpehq4kVety4DN GIRxvEayfBCmIpIlCiNL7YU6t1lYaKAdWU0Y64EbUuNQ49gRbYeAFxLFRiD2Q6qwAIVGdiRP stuePcizS7bqjByR6iN/XmXqvR8QpR4V2Hg9UcT8kRtv4K4X434IHd9fJ9gPuyAMqUYX5iQg 63fUK86J6ZRy13E8shXlCcJ2C2W73S6k9bm+CYfITaxbz/FSq264xJ+3c6m91JPE0cDkqHvR lE9cnt5Bs6AeY43xCbPYdxVHQQo9sNITil6j4xXt5l6DKHlc54hsqe4sgG/NztX911A8O490 br1wDPHVJSNDIuSTXlJUjkB/aKkCrgWIPAsQ25LSQxnO0HHYLh5Ix1SKPI0jSxdey1vBmunG f7Nt7xMMgbPN4jof8hSsdsOjdXLMJasz9JbfHx6JCqF/LF6nZI2EV93NRsJ3b0Siw7Uj2yiF f1gJy4phvWlh64TTFgPMeERHI8XAoB59QDWz5FUFyypp3zKxTKebq4/L8B6akn53OPZH7IJ+ WqzLLA7YveJAJVvEoR+HtteWkmf0mWF6dzJT4umxJrqjGPiQnwYUD9fgoQrdhNdUyQDyHL7V WAcQxxn5aUyaDcywNDJt1sU5lsfI9YmZV+5rpj53UehdfiXoeIk17g5EV4abAxvtEHH2EcnK +w+D+lsaEOsSzMve9TyiMlXZ5OyQU0WTm/fWTiA5iFKMgK5HmKA0xaCzJT3c6xxENYW8GBIL NgKeG1oAz5KUF9i+iKiWFACRuXBLRG0jCHhE6yE9ciJy6gvMpWIsaBwRsekjoAu0CuK79BGM zkJNB4zSKzciCvB3lgyjKPggv0jet1DAVjUsUvCygHW+Q7pUnTmqa58f6EVhSKOQkLNADvb8 hOz8Poaly18DsIDqLkXncVRb3ocsDB9EsQYGSrFTYHJoAZ26/lZgYlBVdUJugegXdzOxxFKG ZLsMO2rm1TuPTmy3XYZd6PlEbwogoJYRARCLQpcmsR+RDYFQQNoVTBzNkMpT85LjSeMq8SYd YD4TQwiBOCaKA0CcOGSbILRzaBVn5unS2v4sfKpWkYQ7ahp1tfFCd/7E4q9VVQW8KKI+FVC8 tRXt8+rWFeQ+BvvyLS2KbivvsuHdqb+VHe/Ispe9H3qbqwZwJE5EjKay73gYOKQUWvIqSkCg +mA6e6ET0XeR2pYYU9YECoefUFvguNsQJZc7CV1ywDwnJq83dBZqO5YLNb0CIBYEm9oeHs1E SUJ+3UEzbI2Tro7iKBiIadZdc9hZieXlIQz4b66TMHJCwdIfOMHm3gksoR/FhGJ8SrOd5ixS BTyHXFCuWZe7ns2vgeT5VEXb+lJ3qekNju8H9W35TAYllRg7QKZ2fiD7/6TKDkC6rRcRL/lM tajOQRAhxKYcdJOA2moB8Fz9KlqBIjzk38gPYyAFcU1Vc0QoUVRie39HFBSUIzxmw6fL2pmR hnukiCMgn/LPOHMMA5eTbv1xXYNM9cFRS+p6SZZYPNoubDxOvK3lRnDE1NkJtHhCDZqyYZpB uEqnJSVA/O1FeUhjSlo71iklWg515zpEXwo6Ma4EnVyGAAksL2lVlu2y113oErlicKa0O41K 4SpdgKMkonwlzByD67nkADkPiUdGKpsYLokfx/5hXSgEEpfQ+BHYWQHPBhD1FnRiDZJ0XM3M twgKRwW7jdWPlMoVkX7EFR6YmEfiXEUiOQlNfkrXWRL2UeZqj/ermxzCMP9Wu85tX6fyoGF1 rmw8RzanJHpgMO7IZmy4d1x1VxSSKtPaeSRhkJiKdt8ycfCBDSV6jVc9oY9YXuc9VBa9l42X 4nhIxh5vNf+7YzK3xTqBS18Kv+23oS/190kTR5bL58SH9gxFybvbpeR041JfFHgQyI+sp67V qQ/Qmx3GqtGjfVOc8vKdVVWbssHiNGj67l8uilZLqgTIgM8rxT8fJKTVhcCNGihXSN1JGTMK sejzB2o0ZflZhTbbAiNRs4H2GTLx6Nbz8h2Rku8Ym+f9+Su+znr79vSVfLcvJhlv01s2cKpo yzQDVj9wrh+khix0FUdrms20zIJ16XEzMbp+imWeYsRBpDNyzQ6F/jIphhO0mdy0F/bYnvQA gRMovSYJrzG3vMGZS13tzewYz0Y8qsP0HCI98YJj1SeXp/fPf355/eOue3t+f/n2/Prr/e7w CvX//moY503pdH0+ZoMj256gLZQTb4tBbavFBkBeQc4YUVt55q+6blrmBY5cn/xY5/G2eaRl rr0I+BDCiXaE+6hLxgZ0y70y5CFYpZ3OGhhdu62H0qey7NGwjGo4AfBus9TVVRRNvTke335v NfeFKOJ007su42gSQSB4KulfqZbgA8b/cQmEpQ+nss/1FmXZeQxvY9SGVWWNrmWQTvYrMsSu 45oMI5zv01vqJ4GZrrgpSnJrsrzDSJ4gSVsiwEOyRTl06QejLj/17VQtonTlPoZMjKLhRQu3 2IGxArYbW5nLyHecnO/tDDnqX1YUKrsBglrjFbZ6AGpW47g5cOVzhXEQLM0KaphsELIQ4lDR 9a14c7Z2WOSsa77syqFZeNRjp4cz9jECTH68j2Xdqb1YvD8w00ZNxpbkJGlvMSRxbOsHQHcj qk7S9PhpVUEYwHkHyji9tE4NWu4cf7XCNGUaO7hSkGVA947Mc8ePptcNf/vH08/nL8sukj69 fdH2IXTknG7OJUjQcD8xmcnbEh8/RPOZdL14cQxa0HJe7jXvuFxxt4IsHF2qGF+lJUb1pL+e UJ0ow8MiJnykKl8uXbJio1SyhUk3Dd6nNSMKhGSDSRY9LS3cM06RQRQ0yEuJDYAXFeNaKDGV H4NI39KajuapMdLGdZJldNqyeLf7/df3z+hlYB0VeBqdRTZJbXN2SGPpkOyC0BKCGBm4H7vU IcEEepr9Fe5+8rEbGUZcfMQGL4kdQ4gUiAj6hM5RtPi0C3SsUj0uJkIinppjucAQDNkujN36 QoXzFGkbZqQLzYiTVszxA29a+E8E5ndkWtaSaovftjAYl+MiJ3xj7dLndzPuU0enM6o+3Z6J O8ccA5JMHzGL/kQ50/KMEL8XUqxnjVGgsNjbYbR++cukRR5B81c0w8hYUKuGrhKCBzbk6LqD 3w7c2jWp62tm0wpRdyyhAkZECQF1XuRRd/gIHssogF1Djxp5HNAJGC9TpaZIg8Sl4y0tfakU PpxYfz97UiNrXnWp+YJawzj5unpRhsVgSI8Dqo0lXQr0AC5OmKxNr/AZ2xrB1tXkVltMsUbN pv6NNZ9geW0zcvFEDtN5HNKEAbazmheSbJth8wODv/T5PFsqGwsBmiBb10TqwelCt7zlXBjI i+8ZTgLfrJq0B6euqWfUC1c1ExbSBDExiEPkqyYzE223bpW8KTx3X1NTMP90leFfzNUKidb2 OJdd3gvfsVYW0PdPlopPRvZL2SfKGJDZpJqODEX661egKjqZQuvfpOEQWmJTCfwetDZbilKB NduJ5+nKrZ0Kl0EcXUmZgNcheUUmsPvHBAa4cm3C9tfQcVYJsT26498sgQiKM3mVG+qXz2+v z1+fP7+/vX5/+fzzTr6lLqc43srJyyI6IotlV5HY5BxsenP6r2ejFXX1uAupAzoa8/3wigGN bPEvkbHq/F1gm6L4viIxZtCAnt9OOm10KqQe7HY8ch3LUwEZ6IeOFznFADLrI+gbi41kII31 Zlh7HjDVxXiOr5C1B/lKImaDjC/kCar2Ll6hejR19EdNIZpHvhGBbcFXHjRMR0Jr2XVC2ClT 1ZPxLT3xwaVyvdgngKr2w/UKMaR+mOxsq4rUuM0OtbscEfm06bFhB0ZZcAsR2HTNoBDXrTgB K8FISJdeYFS+Dl3HW9Pc1SZ8qXHXsVZCwPTt9QgHpGXECOJN3V9rmum0XEFoZ4sTQ+iskwsd S3K7HRWtSyzpIixWFrvJ1SjfhIzuMfRNYv6KvKuXa644ntTTNLyYidJJbzTKKel4JqvHel0E tfFC8u+mz3CbYjqnu35yO5NM56QLUJRXDHvTVgNTXbQvDBge4CQjdPBTnZOp4x2XuOJauJQG XfhA0DvQzjk0HlOCNMCIlLYWJlTEE3UxVKAs9HcJnfaoTG8nPWnpa8TQfBdk5YFFg8ZxSZRn 1I83y2P6cdER9aGNgfjkIAHtz3Pp0gDmWXxVGUyUvKOMN9aEfkiXWWDoMIMsgeUYZ2GQ+h89 8iR2Di2+zBfGklc73+KgQOOKvNiljEUWJth9InWvVhCQYmLXipADTDwetQwVKRVsFwYlBHJO TLID0SGmQKUgchO1QVEc0SWdlLrNsiITiChUiRTtjsKSKNhZocgysEYd7YMuF1whfQ5icJFG 5AaPrsGZILXpmI2wI+ewVFM9uvHGgxXTk73OEZP25zpPsiOXljrtXOgcGuvCwI3IIndJEu4s BQLMEmBAZXqId+SBgMIDWrNrWRwE9mH/C28XH+YRkgu9qcfriGrquCCz61OiMOhtLLAYQGlc tHqvsqzfwlNsRXK1RIRTmU6fclvgOIXtDEt89C9xkW+uDR7V048CXWqqTR8wELrw1GwDMYLw 2bDDX1h6xrs9uoNFH9NK+FQ2oBPwzcJOZwtExiht0ktTPwQJeYCgsugPwlWkPnvkoFsfPShY dcB7a4dugFHq3SwRh8SdiFkSeEwSz+Kc0eCK6audhQvNw93IpyzINabIM56Y6CgsWNvzWtHy acz1yaZca/ErzCKLSjTY3tJnTd6WvKbPrzBSypj1dCpN06+FoiQIC1ICWJtw6hjpScKYkhXb l3vlSrVP1zsYBnDoiKSqsle06x5vm9I2A21lIZb9rclnQDOj6PE0cUJoowZkiSiWheG3s5r6 Qudt82jJlrPmsd1OFY0YOzLdGvSw+31GYtea/qaU/hXoJqjrzTYQrXou05x0tzOenWpKe45h iRBBr0l0eBbJM+KKRq2SQXmtBt35/YTvs/4sAmfxvMpTLYPRj/CXl6dJk37/68ezdhg6FpDV 4kJxXUaDkTWsag+34fwv8GJ8ywHUaZpZY+0Zekm0NUHW26DJXbCCG4UQ3p7Iss4Ob1fNM+Vx LrO8vWlB4sbmaoXThGoJYnd++fL8GlQv33/98+71B55dKNfoMp1zUCnr0ELTT8UUOnZtDl2r R6qQDCw7rx1wGTzyvKMuG7GbNwdy0IqchPHBrQLuFH5Tnt1L9NKgDzHlQJyqrTLWlBBoS1sY DU7wqKN1PrUXxPF0/e73l6/vz2/PX+6efkId8Dgef3+/+7dCAHff1I//TbFjEL2G8s4yTuQF wuvv7yKg0Jfn31++Q2JvT19eXoW7yCUI99ysmAAre97RwUkRPrL0vqc8tSFY89ILjRtDOYzT cmOKyMnBMtYN2mou6UPOwjjUDt3EXCqD2NF2I1F9QaVWWRG3avxklZD6xGRKRqUt09AApmRd 3yxJ3SfkEStiGd9rK50sCKh7pfjN2kS4T9xre+VCpiQnzOseZFptxUZiz/ocdgkqJ1F2tnNc sh90f6oacLsOFkP1sZSMxbET0ffsU0pFlJCeKiQuLweMtWR/KjzjvmChE2uSoNdQfTVMyIJk tVz+ygOZXi2s+20f8oO2tCzjRpov8fU6l7Iiv6VpSV+TTTzChneDQ3p+oVY/AWMElG86aYwd 9BdFvaUwj/urtk6q8NCZbTMh50E70ccmgJb20CHj2AJkJXADNJtqay9TvYxL0tP3zy9fvz69 /UXYeMl9fRhYejSLjdKSsEyRLxd+4dr45fnzKzrQ/V93P95eYYH8idFwMK7Nt5d/agnLJIaz vNsymmrIWBz43rrDAdgl5MveEc9ZFLhhukoQ6bqnnbFzeefTtznj6OG+7yRmzVMe+kFIjEeg V75HW76NJanOvuewMvV8OmKCZDtlzPUtjgAlBygNMflOeYH9ndkO586Led1d1w0hZPD9UNwA JUfPv9a/MoxIxmdGs8dhIQNdLVEvdTT2RV6yJgHSDVqck2IPAPQRzsIRJNQWt+CR7u5QA1BW 3/w4Cbx1246A+bHBtR8S0ivLjIaR2Z1AjCJzcN5zR/MJMw70KomgClFMdD3sLS55q6/iq+VO HHzDNF3NtZGO1SVm8LkLXVKfV/CQ6FwAYoeMCDfiFy9xglVhLrud/m5bodNWCQuD5ZpnmkpX 3/O2OEAk2Xm66YMyunHSPGlzipgqsRsTczW9eqGxCurCNzmdnr9vZOPF6xYXQGJfYsR0i23z MKbPkRcOP/hopvq7bY6dn+woF2Yjfp8k7pUYSEeeeObhrNZ6c0sprffyDRa8/37+9vz9/Q6j 5q6a8dRlUeD4LjOHoAQSX13ybGkuO+m/S5bPr8ADyyxed0/ZrrspikPvSG/624lJNSfr795/ fQcNyagYShboggP6UjN4MvilJPHy8/MzCBHfn18x1vXz1x/r9Ob2j33HX3dMHXo210ujwEEa ZY2tMIg4pdnounMSeeylmsMgGGU18jxwN4o8smlXHysiFWJMRuol1FsN1UWt4dQs5wbpr5/v r99e/t/z3XCWTb4SzQQ/BhXu1CBzKgYyk5t4IaFYznji0QZYJpd68rvOQr3INdBdonqa00Ch /7jWwgmYNCpVuEB1dhxrGvXgWU35DTbSIfeKyaerApjhfMhAXZ926KCyPQwubWGnMl1Tz/ES W32vaejQBkoaU6C5jdGKeq0ghZBbG1Tgsf3AbmRLg4Anjq21cGFRb9vXA0q9JFLRIoXedm0N LVBKTlgx+bYkxuw/SiS3N2GRwhZta94k6XkEnw7W/E9s51i8f+jT3nNDiyGbwlYOO5e0ilCZ etgUB+t48B23L2j0oXYzF5oz8OjpL/A9VDdQV2ZyadNXybVaKhbFw9vTjz/RypaItssO1N3H +QAqbK8ECxwJOAZvh+7E/+5GyroPIL+UA4a7bKlDnkyNTgJ/yADZ2b6kqFw7nkV61t3Y6So8 RhvRfVUm4eG5rlcfCzrPq8IS9BeZ7mt+O+ZVp9qoTfRiv0BEylC4GrbSoe3aqj083vq8oE8d 8JNCnECTHhQ0vqpl2Q1GRHYryr7GaNm2Wnej0qDQDhh4GN/MWSpkw/A7fsTDkxmdA6uNAt7d 65t198ckRAz6I2gdtKIwsfCyciPK7HJiwPDcuAnuEk2YX8GWQFdbJZYCY18rB9Jq+7QwEZk6 7VRWvSQ9A3HH3oeszmCmWOGmPZ1zZsfLncWuBMEz9JWl+c7QxWabnevLoaD3c9HxNaMd4iJ4 yiozOcbpayoxhw/ssNIV1EZLWY8uAI5ZTT87mpmqc2afSA9X+uwXsX2bHqmrGdESZT+I6IaK a2mkd6zJZ88k2cvPH1+f/rrrQAr+agwQwXhj++H26PggJDlRzIikYLGEzPKewzyvcrMBRxZ+ 4rdPsKndhjrswlsz+GG4o/yMLd/s2/x2LNHSCyT/TJ+/C8dwBpHocoJBVkUUD6yxsArQpdps dskiZecPmPKqzNjtPvPDwSUDZiysRV5eywZ9nru3svb2TI8moDE+ou+c4tGJHS/ISi9ivkMd RC/flFU55Pfw3873LMnOLCVI3S6lMSm8TdNWsBl1Trz7lJJd/1tW3qoBSljnDsqVVA/cH1nG +G3gjmqQqOBlc8hK3qEvpvvM2cWZGhFK6a2cZVj2ariHlI6+G0QXKj2FD4p0zEBY21F8nNX8 BC1cZTsj4oqSFsB7xw8fyLMlne8QhLFPZYR2E02VOEFyrFQ/zQpHe2ZYZDEtXEtZFKYoii3n yCT7znG3p1rNmqG83uqKFU4YX3I1WMrC1VZlnV9vVZrhr80JBnJLF7XFANPCHUc7oJn6jjIB Vth5hj8wJwYQjONb6A+cHr7wL+NtU6a38/nqOoXjB411OZefWIzR6IL37DErYTHp6yh2Sfez JC8eGVEt1rfNvr31e5ggmU8O/mkQ8ihzo8zS8wtT7h/Z9khUeCP/N+eqn6VY+OrtJlR4k4Q5 sN3zIPTyQnfdSvMzZt8gDe62gCQ/KEle3re3wL+cC/dAtbi096keYCz1Lr865EAembjjx+c4 uzjknJyZAn9wq9ySUjlAH8PU4UMcW5tDY9reHzTeZHcmM8XbGJZeAy9g952le0eeMArZff1B DwwZXj3BIL3wI+lyV2Ht8J7N8ZIBprdL5z3yBH495Gx7DgnW7qB5AFTQ/lQ9jrJCfLs8XA/k JnQuOSgY7RVn4s7b7ehSwWrV5TDMrl3nhGHqxfS5nSEQqbnt+zJTX/8ogsiEaDLV8sRz//by 5Y/nlQqRZg0G87ALh+kRBgO+dkJFwypZTJsnkBoRm0ovYoVX7rBOVcMucldDVEdPV5tIgLLS Da3bUrN56/zAMNoQ+obNuiuazh/y2z4JnbN/Ky6W9JpLtSjBWqeixtMNjR/oLxFka6Micut4 EpEekQ2ewBhVoIvBT5lE3good47+bGQiez7tzFziKByOvW/lGo5lg3FL08iHRnQdz6YNDi0/ lns23pGpjigINDALa+D0wQ/BSD2iWLPpLv0FDttp0QXkceSI8yYKoXvVNyrTl13mehyDH2p1 lCaCsPqx5hr5qid8E40T1VGGhmbdxmeRZ2SJOjZeJ4XuajVTIMvV7jyJ62PWJWEQqdq0fRnQ s8mHhp1L21kP69PucNLLXF/5ilDszQ5Ky74HreshrynvA1IZdr2T7ymiC9rnI3K8Jn4Ya44/ JghVB8/yDkjl8QNq6Vc5giRa51yXsLn4D9rp54T1ecc6OjDnyAG7Zqg/S1aQ2A9p01yhLe/b q7jUsR9U4TpHvV7Q5N68GcR51w2d793zaU8o3p6+Pd/949fvvz+/jZ4dFW272IOOmmGsnKVB gNa0Q1k8qiS1ZtNxmTg8I4qFicJPUVZVD9uCljICads9wudsBYDOfcj3oChqCH/kdFoIkGkh oKa1lBxK1fZ5eWhueZOVjHKvOuWo2ZIBMcsLEObz7KY+ehfnlulpr4gHQML4r1V5OOrFxbi1 46mfnjKeXmBJYcQcyG778+nti7T4XDuGwKYT840cPoB2NW2vgx8+gn7i0bcyAMMKoE4GpMBG Bq1Gn0yJDuSDFTwfmCXwPII5p1Q1HItapDps8IPe2ug/FW0FuUblbjY5NVLzaWCqlbQGC2hf nq1YGZu2DQtW5Qmor/TjfOz5VVB0LVP7ESc2+fDoWqI7StQGcdpKARF2ZhaxAdHSOpTO9pZr 8hYmXElbEgF+/9jTCxxgfmY5N8Us2zZrW/rOCeEBZCprRQeQj3L7aGX9vX3SWBNNWV+XDXVX gI1X8/SkuhgAmnG4i0NpD1vgdQjoA2HR0OJRvzag6xwVtLbOjcTqPTSB5SJZdKd5jqhgHOaI ExsJ8jp2aRWF3EvEYrR/+vxfX1/++PP97n/eVWk2PU1Y7sLG5PEIR5jrj09SloZCpApADfcC b3B8A6g57M2HwgkN+nD2Q+dBcVCHVCkoXHVWIRl4mmCPZNBAvYA65kfwfDh4ge+xQG0hBCbD Vst3rOZ+tCsOTmRmBxUJHfe+IJVxZJDyj170dqh9EHxUL4/TBmM25pzZwnE/ZF5Ij+aFSXpi +YCpu9D6/MJBPNVe8YhwmEuHLYB4THap1GiXC8jZEdQrqgVM3yZKThm+TjZCWmsg6U5i4VEi q1PNYY9TrWQjvVZQVRL+BxxG95oAdx/1Goj+FqdIGlOcULqWUhPWZG3PyHZfPUVdMOX9JJGv 1TefUrRz6DlxRV2OL0z7LHKdmOzfPr2mTUNnP7px+agEeUaudB+sZ1NZhNxOy3V496bN/vbQ klmtDAemFHh7apTbJ/HnreXceBih09HJO6wJperPVkulyYSv+V4ndan+we14yfJOJ/XsUoPw pBMhX7xp14l1ec17hJZRM2ZiJcKSejqUjXb6PsGivMQYEeXsZW2+6Z9ljw1DF47iIRkZHw2Y pmeKbZWND9bUjPs2vRVcJ57R4x7PBWjHyma4N+uxevemflkzPpg9Ip+e7E+FmRLPH074dMTW IsuzFK0Zeae3e3aq60ediVVta/R5PXTsrH9YD1yLqSaK1Jesup3cKNQdOwr+7hTQcaiwXND+ NWu8a2COitKsN8vcJKFXRFl47luuxEc4cDbxMgxCS2QjxHl5tLj6FPBQlldLJOkZFhogvYUK plOSWGy7J9hi2D3BFu85Ar5YAqsh9mnwfYuOgfh+SGJL0ERAU+a4FlMUAdelzfmpWD+uj4ec Vn7E1zzwEnuvABzZ4jkiPFwLe9YZ6yu20aIHEbjLClfscfNzmbwlIOWUvB2Wydvxum1oZUwu wHYsT4+tTz/BRbhsstLcqVawZWdfGLLfPkzB3m1TEnYO2HJc594+LkZ8I4GGu74t2uyMb2TA 3Z1vnzEIR3a4qBNbEDXc0jKL2DKB9iUElAB3pbyZ+MagEh7ukqu9XSYGexHu2/7gehtlqNrK PjiraxREQW55Uogjm+Uc9GBLIGEpezDLC3+Em9oL7YtVl16P9EmtEIDKbgCBz47XuW+vN6A7 e84Ctbivklusxc2SANEw4VzuN9pt6yhEyCAlS2ynCAr+wRYmzi1abl8dzlfPFuET0Me6oOI/ HLO/ifcimj9cMReYHJCkXD1/9T+MT0BCFg9+b7z8lKsBl0RTkk4vETnxvS4biZf1+jtRjYxu FynfCwbvibnqFf9M5lfv0ZSlEEhZyR7sZYQf1/OqdZmiotTUhpF8LAuMfaax79PM02yqJma8 KIjW5K7N1vkB8ZiteYe2yYU3A6JqZwZyJGURLhZNKP5lVYWJCkXbr2Tu0vLAWgoe5A2xWOS4 OLv/tsoH3egbLZXv272lROhKxFG9pmvowHjKaiITBOt2OK2/GzvKmPr0kStiV+KV37HM1qdy QFwKAn+AgjyAQvJ4g6U2bw6DFuMDcNAEiaY7rZIZo69Nb7H5j+fPL09fRRlWT7qRnwVouqWn wdL0JKyn1JpLoD9RY0Vg+hnTTCp7g8h1T2KCdsL1wZLwPq/uy8ZorHxou1tRmAnty8M+bwCw pIWW/P2j+VV6LOEv6rZPoKDNMrMWaXs6sN5MqGYpLHO2hECDzcr7/HFV/VSsWOSYEjA0zlDi 0creCckn74LrERZZVdNHIgybQ9uggZ5+YTxRjZbSss3xjcAGXDFah5Bgnrb0niVh6jWFQD5B A5kjut6XvTnMi742KFXbl+16bB3basipOKLio7Y9VPntyOo6N3r4XJ5ZlZVGJkOU+AYjFJic LPeP9EqI2ClFKwXKygDRC6tgeJvFyS9C5jAK9NiLG2gz8xKdXViSL4fcZP+N7XvqLhCx4VI2 R9aYlW54CctUa9Cr1Ij9Koh5ZhKa9twaNGiQ9VI0UfGPTmmSmV4owVuR2J/qfZV3LPNW0GEX OCvi5ZjnFdfIciZD99QwnIwlrYau6c1K1+xRhmUyWrXP5UyzNGxdoj/jthiM1EBwyXtzFtSn aijJcdYMlPgkkb486MmAFJDfmyl0rMFAnTCBKNMCwZE30BjNsPoyH1j12Nj2hA7W1SrNVl9J 8q2g/V6oLPOx8YeceGT8IU9ueQOgMqUldcwnOGDJExabqbHMokUeH1YTUSHbt6Sux2cPeno9 3jtmxtDr2zRlxliBjUn2p0YTJrYGEfY3TY5Bk1FrmYQbHAy/bCQy5KxekWD6gMSRG00CReiq 9Wrc17bBekBDbcZL5UpkJq2mJ69B4fytfTSzUOn26sFm2poFgwWX075/BHqExc6o+nDsT3wY z5FnRKWuin1CMe7Wcd/M/eQVn/LetileGEYs0zK/lCUIrKt1/FrCPLWkghmY7TXRtjb6T48Z yH0WawnRGSK89+14ojwwCPGu6ozRUacdKKXSPnV6Q09IqlMoQlqElqqUsbV0pWbINvIYzyu1 dPevQO3eXt9fP79+XQvJwvnXXslFePYad4a59B8kZrLN907TO0SygmiTKMVuNezFRG016Xeh olCTlbTrHjMrM83RiagSx7rkR6NwS5bCWhkY8FM6OzIJ+VKxzu54IQFOPN+tYVwV9pTJz+dj CKKG2GvtMS1vaPQFIp+0RVump+70TyHC1Kv16DxCK8/F+Q51vSQOBKquvEmXyVpSTTMFdVLI rEf5hvHbMc20vPWCaMEgxXdNA3tymt+a/DK5G51s2XR3FzjsVA+LSiJT5Hi8SS3Jd8TIVUAO ZVMOYmcqc64XRL/507F2OJhtByShC53SoSotTy4nvqzkGMz7ll9hPW1YZa4yqw8KTlmIjF3G RZ8d8l5EL5UnImqDonPUE2x+4vIQNu+/e/qkb6a5Iebx68/3u3RxT7mK3S26PIqvjiN6Vsvq ikNR9rdWBUHP9oeUdN07cxh3dSoduqjJOaMuYBe20ZZG76p8KtO3FbXHuOrQ9LdhIL4ZBhyC HJTrjECxrOsUC14R1KNi6KPD7fXkuc6xoxqt5J3rRleEbOMXhgZ8Tn0MwpePMRLtH7dku7Rz ec36zQg3p3BL1FErzGlksA7xk+t7G0XlVeK6Y1m172YAGos+Khb+LBMWRfj8xp4DJqGHv52o WozfiSjc6tbSLew8c8Zg9+nXp58/KftaMRdT2zwWl/3qqe5JBOeuzY4d9MB/IoMGZKb/uBMN MrQ9WmR+ef4Bu8bPu9fvdzzl5d0/fr3f7at7XE9vPLv79vTX5Fz26evP17t/PN99f37+8vzl PyHRZy2l4/PXH3e/v77dfXt9e757+f776/Ql1rn89vTHy/c/bO5i6yxNLFflAJedLdSdWGPw UQK9dyGih02eyCtHq4J4O7DskNt2AcliSU+sPZeedVTCnRmNU626GCtZn65mpgDajR1CcGwW WXBkGKypb6t5EHZfn96hp77dHb7+er6rnv56fpv6qhYDtGbQi1+eNQfYYuyV7a1tKrtf3+yS UsZpI+QZ+yZQpuaUDk2evvzx/P7v2a+nr3+DXeVZFOLu7fn//Hp5e5bbuGSZxJu7dzEkn78/ /ePr85fV3o7pw8ZedqDdW5zKznxzI22z2QwLlnSs3qZnlqEHrR6kBc5z1EwL216FD83KLGeG FDVSQZtKjXE4IcQQnaDVaj0jNa8tSFlfLchy2k6hQ37ojcLjVhWrYU8U4kr+GwF3rOlqzxPf YADxzW6bOOU8WfESnKv5ggNPDDdSOzpxHuseVcWyKAyUSK1LF07JNPO6VEN1jSQvMpuBZafh RF+hykKceW4T0qv80A76aaUgr2WE8Wwd/o/TiL4Hl2x4jEYfe4v2zYTeaJNRhqwUp+qGUIqX KOOrz2V0COqtLkCQYnxAD0KHlXdqkOfhv/OBOtgVFTUkGpiWoE2cy30/hszTC99eWN+XLXU4 Jr6Gnd6U6DiMNyEBFOV1OKmx/eRww4O94mLm9Aic1ImiSPOTaKqrsZKiaAr/e6F73ZvJHTmo JvCLH5IW4CpLEKneKE7y9vUe7YKEA7r1osJaLu8r5rHd/fnXz5fPT1/lrkIP7u6o9GTTdlIw T/PybJYdlUURe2djxvqOdo6yUQj1S7karPKTa8T2Gq4y4SsxMl7AmtFQDEcQK4cXUhdd1xrR Uba6Naca1OmiQCNLT2ns57eXH38+v0FNF0XM3AUn2f9kiaErsus34UkutkmkV+bFxhZRn8Wq vaL5xhLPGzPs5USFz4WeYC6sNRaFNuhAeA+fbdWF1VkY+pHBojA0+eB5sbH4jkQ0kTXHjIAS q+x6O7T3tDcoMZ//P2nPsty4reyvqM4qqbq54ZvUIguKpCTGpMQhKFuTjcrHVjyqWJZLluuM z9dfNABSaLDhSepuxqPuxpN4NPq58Bwb76bWgAqxbs6CeLaNvqrOaoC17fAW0ncHuWrwrp9l 67pZM1CVoc8158+cXWU8dOawuA2IMNs2YMsyN2vrHzMmzyz+ixmjYdUrFvD1vIcwrqe3/SNk yfjz8PR+vjcyikBdIOPFPQHIbrlq1ImGl8cmt1gais/V0XkHxOfaraxvNvkpR7O0WWWgHJkz c/xXzKdNamTtKi9t55BG1jNs5rlHsCv6YuMfsz8x0QgW1g+YQ44ftYRsk6IWhNGTfLagbREl +q6YZamdxwAFw/hFhNb/j9fPoMz42uAQEAKw67KG+tASucmYLqfMICRXpmmjBERItD9wwWXu MwaBtIkGRXouMlq7JGAdH5gbCcufYZ90H6/7XzKZKfj1ef99f/4132u/Juw/h8vDN0q0LWut IR5W6QPv4ISmmaE2of+0IbOHKSSlebm/7Cc1vPdGPIPsDUSLrDolS0EY6WCrYaneWRrRFySw /CrgJT6nAMGUvB8EiPpqr2vqAK6LmnVlhlTNPWzMXqhwycfT+YNdDg9/UdknVNnNikGqD86O b+rhfaIXtYtlxx3pynnN333kZhqIfhd6+tXOT2yRgxVha1zLPYNX3AnZs2Z3AJJoI4PSFbbr bQnGGGEEkK2rdWugZy2w0it4oyzvgC9dLYQsVowaHK4IKZso2LvbkSMTFGnauZ4lGLckWPmO F5JRvySe+VEQpkaP0zvPCLsrB5LVkc0v4koQUr51cp5ax3ED1w2M5orKDT3HR1F6BUJ4YZJA jwL6Y2CEEz0M4KlHnVcD2sE5AAXcmlBVYCHDqewWLqXgtmzQgkZpnYxeNv40oALUDNhwNAlN 6OjBWHpgKHLo1rVuGjPgPJcCjqaSAyNiKpskJH2ZemycJKOalA/qaJZCs+sKKufng5jYiAyX LNDSC3YHFh5Yqz5gyVSOApunmesFzElCs0N39aiqIfmjrbZZzhnw0afq/HBqTrLKZmxAuyyF bJ6jhrsqC6fu1joD49TTPVhlczb3T/h91Ab4SkfkwSnQJfPdeeW7U/PLKYQnVqNxzgkx/L+f Dy9//eT+LC7BdjGbKMfT9xcIn0uYG0x+upp6/Kz5z4sZBkHA+MvU1bYt6JeywG+YJUGkwK7K LE5mn5y9DLTIXztatie/UMnndaO23icVLWrfxaajMuTJ8/3bN5GApDudOYfy2VXRdkmIQ/cO s96dD09P6L7Wla3mzdfrYA2fWIRb87tsue7GK1Lhl0XadrMipd6OiJCIC4PwWbOxYFL+Zrgt u6+jY6En+Oy87Wl69fpVdXx4vYCw/m1ykZN2XZKr/UUmLlTs+OQnmNvL/Zlz6+Z6HOawTVcM 4hDZhicSdlqnsUn5GvxkdSky/sQ3LGhs1YENO2XviGdWeXDQlXQ4vsqwyGawn0erUmxMsmdp lnF+qJxBFFxaYVPyf1flLF1Rys6CH9E7fuiCYQPL2o2myhWokcINoNczStDIKFIQ22iOvKwF 0uaerJAQfg/y1urzJPtU5xHtTibQRRx69JEi0GXiTWNLAANJ4Nt8dhXaFgVbogvf/ZRga3Hh k6XD4NPKzWwWJtqWaV2iY5uzskQvihUVOLftMuXoogH4NRpEiZuYLjCAE6w62U5ep0RWYBlG sk5nm/k4JSz7usqEjFVzTbkTUCQ4UMUtjXLUrl7fFirG2GdkdsmvIugTDlhHCET8dG7oJETG OAd1xmY7UnGAUqPSNWLLPAjixLlaZGH4FQB5zxyNKZS/heP7b853zv8YCMPWJ5unC9dLokAT 811huzbtit88zYetrPkAWFaWpg1y37/OjW7QyyHLPe1SbNJWxERoRKz24xUsgyC3st8GuF2L VRFisHz58ScpY6kevbRRIdTX3YD717+MieZH6W49R7EPdAzNXWgU4tlKDL8f1nW1WgSM4Mm4 I9JWamicIFKEvK+L1UbvswLT9gYKOQNnRGyrrTDlqtlQPEXfWI0vLg3cB/X7JPG3ohZhJvi8 FbnSaaAa88aSNFJoemG0Y8nJ4eF8ejv9eZksP173519uJ0/v+7cLJdhafm2K9pbcmj+q5VrJ oi2+0jop/hZayIh6/fqAvBOl+VseMwRUMkvinCn/gJTtfKMFySdk/KmhU2q7UhHXJcuoRWXS lSz9O2Rg5PI3yIT+4cdkiReGOzIInyK4kX9Ht0yVuFOP1qpwJCcfrZGSb7q3i7JBwlmz04eH /fP+fDruL4iHT/mR7EYeTpqogJacg0ZVsvqX++fTE1iqPB6eDhf+5uLsLW/fbCxO3Ai3FI/U Sn0zn1WpN9qj/3345fFw3j9cRMI7svku9s32BcjintxjZd5bs2c/alduyfvX+wdO9gIJ5X84 O67+zOa/4yDSG/5xZSpcNfSG/5Fo9vFy+bZ/O6Cmpoku+xK/A70pax3SxG5/+c/p/JeYiY// 7s//MymPr/tH0bGMHFo49VFKxL9Zg1q7F76Wecn9+eljIpYdrPAyQ8bkeREnYWBZsbYKZALb /dvpGSQKP/xAHnM9lc2hz2b7g7KDlTyxNa+dl9EBzYRA+LzdjRxI1SZ4PJ8OyCwsFYmQLJtK UhtnOeca0hapqaqu2C3yOvYCSwTE3qXaqlNbsN28WaTAj2iKoVXJH0qMMzzXiwECSs478/cu hWDGUXDDeY4RbpZHkR/EwQgBYf4CZ4ZM+XVUbImr2xOEuupeh8djOEQ+dCOfaErFRLQ3JQk0 saAODxyyKT9wSXiQuGQ9KBizgjdZzvdIMKJv0ySJQ2IkLModjwz5fyVw+Z4YtcSKhoUeWeXS NeIaGXiWcyZ8qp/SGsZ3qCiIiCCyFfU/GwcQhC7V33Gc6TEBSuyg4BCo2nCM7DEV5KSlhPKK YJO5kTueVA42clL0iCbnBeLPqrwTYpt1h7MQArspVNirYtVRzF5TBuLgVqarb3/tL5R5c3+O LFJ2U3S7eZvWIqwDeQgZ1fRNbctql25LCEo9154A87KocmFAVGgR05Y1KKWAQ2XYBweCFyqM Hh5E96HjRcXTamXqzxXBl8oSxfcOvDgpjripy92yZKUf6SEp63nOoRE4HgCFJl3oZf0KfRs5 SCG+TaLBe+CTp0ZTS+GV/pxuOS85lGUmZs1HDuZWBX4AKlQ3I9W84MC80/P0KYBgi/R6FLht akaLF3oKmtvqsVWjidh6IP9g3drows1MePtq4t/juC174sWhPSg6w4Eeetzt7JMZkS8cbNgy DFH4S9LukgONEBmOhioNMjCYvzWavA8ff9RXZJWtd2Qqg7qoqhSSqIwdgaRGY7dcdxAdEh0I EkPKvNmmhUgp1OrqUT7fix2KF3DFiJgBu3XD6y91yU5PAeYi1xGayAV/jy7ElsnQOdAT9GMZ VcsXjr1X12r1SSAapV/CS4iFmlU32rqsbsCppFqvbzZayMeeEGIkcd5HE9pIOZdRyQAbBeHV UJBvPkhQFg8Ny8qQztdg0OiJwTDKRQlJMC6gZdOYiAwCrJFkeVbETkS2D7ipZxtcxiCM0i6j 3OcA391VkRM4lv7zOwb+2sIjapRNWtWkk51Oc1db2rnNKFZFI5jxB1+CI+lr2Hm55WcbSJ0s o6wW9S7TM4lII0rerpYfcnnHD9tVtc5uekuR7Pn08NeEnd7PD5QZEujrwO34A0P4NpoVaJ0X tx0oGkItpLj4uVONXSlnVW5ScihrMylqux5LYIMDjhWc6+hAMqsnEKZ6PRRMy2q21rbJcHnW S20umky7xFL+wmnTXQ3ljkZFhp17yT/KRtMFSV4IXpOHh4lATpr7p71Q+SE/557f+QEpbqe/ VLRFBY7SsrD5+mv3x9Nl/3o+PVAq3baA+AEQVJfkw4jCstLX49vTeGmIe11frAIgLlhKpSKQ K+1+kxARjXyB406YGACY2EEyfO0+6uZwtEPYZhXPTEbHOr2/PN4dznstS4tE8Gn5iX28XfbH yfplkn07vP48eQOTgT/5x8oN+dnx+fTEweyUoZnu39UEWgbwP5/uHx9OR1tBEi9lLNvm1/l5 v397uOdr5cvpXH6xVfIjUqmT/t96a6tghBPIQnicTarDZS+xs/fDMyixh0karRFIRqonCICf EEuNjNSnsJsZsBwiaGBw7dLfb1z09cv7/TOfRus8k3jtyudd7MYREreH58PLd1udFHaIdPG3 FteVkwc2f94WX/pVq35OFidO+HLS51ihdov1bZ+wbL3KizpdIQmOTtYULRyH4PpDbFVECVwa 4+zKdf/paLB1YU2qJ5hApVPGytshukQ/iJHX/HW8u+IWGTYU2y4T3KFcgd8vD6eX3peYsPKU 5Ls0z3a/81cApWlXFNvGEzZkZtE5SzkbRbEqikBZjWGgCoux6vxgGo2wnDVzgzCOiebApcEP 6WRbV5I4TgLKRPBKoWyvzLJWjqXHd6sQCZkVvO2SaeynIzirwxAnNFaI3nHJ3hSnyLS3I1EB 33Jgdk0Kymp+dbWaorjUtYIlqPekVk2r+ArdZdSzS8ODhwtRG8CL1QKydlFYsLpdr8AmucX4 G5BYABUGK2MXXQWoYeV/9QegVgYNfGiVwUYeSDydhPXRQXB1HNyTW7om99/RoiUyVUKkkWaP 05Iyp/m2Qun+FECpUgwg00PfCGDsjQCKSuuRBEO4G2o3zerUJfc1R3h6vkj+O3BGv3FPFQx1 dFZnfCsJE6SKhpp1aBhUU556iZ7AMvVRVuk6bXMnMgFTA4CzTIuP36nGfBCrkZN0s2U5Hfv/ Zpv9DknNqWOoznxPt6eu6zQOwnAEwOPvgWjoAIwiXFeC8qJwwDQMXcOBTkFNgGaAUW8z/snQ E5KDIi+kXmUsS5XduCbSvOFvb8pmFTCzNER6oP+PUpTf4os6BQuVLtWXfexM3Rbtodj1Avx7 6v1mqFMjSrYOiKmLinrjolPabIujgthSa6QvTPl7V0rBS9qmnN+rjEauBDada8wXBNaCRskO 9z1ODD2pMbZYt4kGrXMSo99TD+OnwdTo5nRKCXrTfBpEqKpSiBNS3QsUWA1nO4YlCYZlmcuX nIuBeTqFQ2LRIGixui2qdQN2J51MCHx94JecVdAWyXIb45zAkA5hK7pD23YK43oT3SO7zAti 3bIfAFjoJECWCOwSR2euBSbJ8ew41yWzuEmUZvgFAC9AQwaQb/HhB7FZ5FLXWJ01nBfRpQEc EHholwBoSpcG7WxX3Aj/jsjBX7UuVrs/3GEBDNWt0g1fytQZIxk5cx2IJ7LQNpRGTVfMre1L X0k4BXUItquwi1xjlbJccNf1OpcqCw3T1XxFYuKOf1PthOpEW07ior72UEtQ/x4dMMejM84C 3vVcPxnX6joJc8kZ7YslzAk9omDkssijl7Gg4NW61KxJZDzVuWoJS/zAnAuWRMm410y6idCV d1UWhHh9d3dV4PgOX8uWTy0EoL46RigjtXnkGktUCQ+3/br6p1Y48/Pp5cJf7Y/a1QZMSFvw u7UqiDq1EkrE8vrMX8fG5Zj4EVLoLussMJMVD0KYoQLJun7bH0WEBLZ/eTsZ/GxX8e3VLJWi hr73BE3xx5ogGni6IkoQ7wi/Tb5PwBDbk2UsMY7p9IsZ/mnANTWLHTKwBcty3zFYIwnrbZYQ 0GqsAQMsW4hhyxaNztqxhuk/b/9Iplv9W47mWEzy8vCoAMLwJTsdj6cXXXRCE+jrpmZq1pka ipTZsaYvN1Sqc7ysGUpJUbrxvLoSLDczfRzjilGxzugMjUOf2MDpUTd7qyq+q+7lXqAZw9CJ ELsX+jjrIkDIJw5HBJ5rkAYBfboJ1JSuJZx64F6jR8hWUAPgGwAHdzzygtZ85oVRYtjiAcTK FobRNDKfj2EchsbvBP+OXON3YDQZW/jlMI6d1qSd0s/f2HcQP5kk2EojA4PglMw336y7nfQp uQruWBB4pMdmx28p5PPI2asIO4vWkef71PXH+Z4Qp5QESOLR+ZI4nxPEZMJRwEw97X3Gryg+ ACfxsKOjBIehzj1KWOzjk09BI/KtJW+qfoYG48RP9s9gCfv4fjx+KMksPiZk1JDidlGsjP0q xakyh58VI2UmzJQ9IRIp8SGvqVHfpJceRIDbvzx8DLaW/wV3xTxnvzZV1ashpBpMKJTuL6fz r/nh7XI+/PsdbE+xuGYamvmbkSbNUoWMnPft/m3/S8XJ9o+T6nR6nfzEu/Dz5M+hi29aF3Gz 84B2iBWYGAUx+qfNXLMlfzpT6IR9+jif3h5Or3vel54HuL7dmBs5iXGiAtD16SFIXDQu4EV0 gW3LvKnRAIcFFkvPWb1wyZrm25R5/D2kn35XGD4VNTiWtDQb39GZVAUwOQV1by2+tutPBEdl txg7iRnbczz5kjnY3z9fvmlMWQ89XyatjF3xcrjgbzUvgsCwURcg2g4BhOyOzU9MIelIH2Qv NKTecdnt9+Ph8XD5INZX7fmudiDmyw6fe0t4rThkWoU88xxX+1TLjnm6g738jb+7gqFvvuw2 ejFWxlIipv32kBhrNBx5mvKz4gKO1Mf9/dv7eX/cc8b9nU/PaDshQaoCmTyLAMa0CkRhLXLb 0o0Qrw2/zeWroDQXMd+uWRLrfewhZjUDnK7opt7qnEW5ut2VWR14EZYh6nBTUE2RYAaSY/ge jcQeReoPHWFsXg1F91xt74rVUc62xiU3wEk2t8dRbO5Qzkc39ScrR68APrtwszxS0KuuR/oJ i/zR4/0G9mNpxfBi+z3fMd+lmZw034AIijy6Kx9tQP6bH3e6dLbJ2dRHqx0gU32Bpiz2Pbzn Z0s3Ju9HQOCrKKt54YQ04eIY3XuD//Z1gWYGkUdCo64oCqm6Fo2XNo6DeEgJ48N1HNrdtPzC In7U8MmmHRb6pxKr+O3nWvJ1IiKPEn4IlKubyf/OUsiBeQW0Teug0CN9taNALl0bOrog85Z/ 3yBDq4XfDIE1mbFC0sqS1Tq1WKavm46vEq3hho9ABKlB64KVrktmvAeErkdj3Y3vu4aiYre5 LZkpFOm564z5gUs9JwRGV7T1c9fxeQ8jbfIEIEHXL4Di2CLAY1UQksb2Gxa6iaeFJL3NVlVg KF4kzKdm87aohWBLq0BAdKvr2ypy8U76g38EzzMzw6oTCp8m0tXy/ullf5GqHO2cuZ4bN8k0 pmZUINDGS2+cKS0vVtrAOl1obxANSOoOBQJzdemCH29If5b5oRdoEHVCi7KCoaNRkB7kEzSE KTHQ/XpZ1lmYBL4VgYdiItFwemRb80Xu2OB0hQqH6vua1uky5X+YDAB1dYSlvrH8+teYboYo s94g0RciVHzSw/PhhVg4w21I4AVBH1xl8gt4ib088kftyx63vmylJSapzxfxCdtN01nU/WDi DlnoabQwRNdQQ4fpbqlb+IXzyiKszP3L0/sz///r6e0gnCBHd7O4MIJds2Z67X+nCvSaez1d OP9wIM0TQi+m5Ac544cBOrlA7BFYRSTIm0oCsNAkawLjStMwrq+X5oDQBLiIreiaCp4ilGzD GCs5D/ybXHAMn7qZuqMbzFKzLC1f/Of9G7BnBFc1a5zIqRf6UdR4WOQNv83jSsAMi428WvKz ms57kTecTSPTXja6bK3MGphBdLzXTeW6odUORKFpbpgj+fGpWy6wMNKNL+Rvw5BBwvA5zGF+ PDo6jXSdOpRksSUG1dyFgT4Dy8ZzIq3gH03KmcFoBMDV98D+i/QiGPO7XxnsF/BUHS8H5k/9 EG9ik1itqNP3wxFekrC9Hw9v0mt5fDIAj4c5szJPW2EburvVzUBmrodFnU25okLrtHPwm8Yc LWvnFlEB206NdaejQgszCPVRZwCwLr7jIW4k9Ctna7qQ/2B6/rFb8hQ9u8FN2fknbsryDtof X0EmSJ4D4gR3Ugj1XuspOrvMm+qh5viRWdY7ESJ/na03KF1wXW2nTuQiCbyE2TTBNX+aWFSy gKJidXf8MsO8tYB4lOMviILcJEQ+9tQsaIx+R2emuq0Li4+Q9A+5/hgCRWmgPlLGdWlzYNrV RbVbVhBlmP+mq1ZUXTbDNfZ2l0dcZ35HiSAAM2fVbt7VZieknWu1oGMRCwq5MKz4qmHMmlDk SqAcNiy9E0Eak9DsnbBAsBTp7io8JRwgktQqKULZfpk8fDu8Ehn52i/ghPJ/lT3Zcty6ju/3 K1x5mqnKPWU7TuJMVR4oiermsTZrcbf9onKcTuI6sZ3ycs/JfP0AICVxATuZh1TcAMSdIEBi sV1FxlxZriMY4akVSOdcdfgFWvpyg7lQ+PUBDF/2rHm8xiRtWnZ9Yt7RnQghhNcztNqw46tJ eoWLLnWj+2guvb486F4+PZGd+jICJoC2m8PAAo6lAm0gc9AUUn1Vmm+WC4+0HM/qSlDmBkRy 0wUlYipjTHPX120r3Ry0Njr7dQmdAknYSl3l4ERx4YQARSQufVVuT8tzbCS/TqnPWxjouedR umYrxuPTqqSEE7+mwnGJ9QiWPeWNsG4PsCGiadZ1JccyK99pz2ELW6eyqPHZuc3sdK2IIgMg nQrDH18LpVgWATQm5yy12K2TAnMf24ItQmfegU/xSe1+siAlaKy2p5e7Judv0C8BhsN5dMsK CQX9KVMumlPWNw47w98YCZIV3RNXxk8ioaUQo92T9fbZPWKGKTq67/RzgROPaerRHrJ5swvn PRHzlAS7dQn1MTGmKmtrO9+AAYyJqoBFAd9JYzj7CPK+mrJMvvp0iyErX3/72/zxn/vP+q9X 8frm2HH2lM5RR5bJYP3oKzhGrdOSfvrnpQGiGVuX2ZmKW/Sx7ZpRosObBdcftLpk/WazOXh+ vL4hmdVn/l1vNQB+aMdzNIFQrj3NjIL2jdz6QwrvIRlBXT20wIkA0tVOxL8FN8c9ZbE5Ztay zfxpJ/VrZ2cYWGQZz2gToj/8btVzUd5mdNevwwaADjTwjWCTl8/oRfqZHqHC+Zk+wogy9q08 +XA2uPI8I6gANaVZsQoay1U7E3a+tupTpBecu/FMZeznHNVtRsJ+OjmM4EqRrrf1MYNNWpWt nNigpil5K+WVNHimUaYtTUshRlEIb4OeaTd89nwifJZzdmJ556wX+Dklph2rOuPagiQmU7br SWUh1kPil2owgrKU860EKhBqOJGRUImkOCJeuXXKHW+9nN1F4U/O188Gz6cBRuqHwd3S8PqX h0x+gwHNsFfvPxw7wXoNuDs6YXVKRLv5hBEyBykMLyODdsK5VzfOyanDMI0XqqtbTyy1niRq NtZJoUoMuPLTBmj5Ie1bx9qfLiXh74o/oGFlmhyf8xdHhyfj+SCykX8zAgWF0JmMXPXMDuSg EIHQ12A+Mm5IndSBFASHZB83v6gOjhPERJ5u01yfRG3Dc/sdlEYSXGx/zRR2uBw3dZuZeMVL 3RcCrzt64OodOkx0tvwvt+hvbp99E2RM0MceJtXCYaRQcr13QjOiUyhabV9G8Jh7p0rby6ZX bv5rQFyAuN9z0nbemTAdiw+oD1AaQP6iTrEiDE9rUOdD3Tt5pwiAYanJJZwWE/qN8CI1Zugx X2xEW/FXQxrvxaXUwL6VTlCc87zsxwvu4UZjjr0C0t5SNzHHdN6dOBmjNGx0o8XkMD4jmxqz htEvxKWTUW2BAffOVAvbaoT/7GZzJKLYCNjsOaiX9WZvVSOKcVu2QsrStHWDYVvoLUw4dTHS mFLCENVNGPQ7vb755oaSyjvaL7ztmqbWwvfT7uXzw8EX2HPBlsOQB6MbQ4FAZ5EMu4REHdme RQI2mJmurCulsyXaKGA0RQbKqv8FyMOU7d3kjFgiFsu2sqfTE2z7snFbTAB8M1FwPqR8ZldN sxV9z5uwa7zCszkST3w9rGCHJewiBJk5z8a0lcJOkTansl+plah6pQfJDuOC/+m1but14XzZ nLvTIbBhUHpZco0BRoARxWwqSyuYqrN+23uUfjuh+jTEH1gb6dxTasjIG5JQ5vQq589R/BK3 uYkTn1Vs5wwRrhGQioHIbXumOpEAAx+yxgpEYtfB3W+uWnLEAz5eW0oiHgL+T+ytU6Eff9v0 H8RUmKi1LBr7pOqGqrVVTf17XHVO9I+0kwQbz9rEeSQ35FMfVQWEcHDjyYSxsCLiifkoGss8 lc2a562p8mJ2wW/arR13E0NYjCW9WVqm59KJ+4NUGykwIBBuDj6fHVENTQrFxfHBbraRwVXx AuXv0Bc8aqMNrLDLSLhiIvyN9nWbai9NnYkxshcEbVMW9aHhJ6sq7K1QdFNk6I+vbp8eTk/f fvj30SsbjSkViGmf2M9xDuZ9HONabzi4U9ZuyyM5dttqYZzLaw/HO0G6RKxdsEdyFK/jHZu1 zCV5E+975PDwiDiTHY/kXWTkT999iAzdB9fg2sX9ek4+vInNCTr9Rmbr/YnbTNCTcKmNp5HW Hx2/PYyOPSA5ORJpKKMAX1UwlxMiNpET/g1f3onb1wn8lqd+x4Pf+zMxITj3Iac3kVYdRZp1 5LXrrFanY+sPCUG5C11EliKFgxkUILcGBKcSU+z5fdEYUDOGlgtrMpO0teiVqNjPL1tVFJFr /4loJaRH4hOALnLm9h/BKsXE4VnYHVUNqg/B1HklKn/UEAeK8ZmKHFJIM/Q5r4JnBZv+tVKp k7PSAMYKow4V6kr05Fs43Q0vd4f1uDm3pURHhdYuf7ubl0d8KQ/ypuBRZovXl6j0nA+Yi5xU CEswl22nQGQEHRHIQFdc2Vq1VoBlNhU4dxZ+j9ka9GzZUgdi5q4gE4CmPGal7OjNrW9VyoeW nWj3ItlzkFhJrwWkri5E7wTRpACTFOm0gn6g1o3aFoktqZ/oPSDjVHwQMFF/13fO9tcoJ1Ei dXzhz6QWBbnnF5PAYRkdYUmIRVd+fIWOSJ8f/r5//fP67vr194frzz9u718/XX/ZQTm3n1/f 3j/vvuLUv/7048srvRrOdo/3u+8H364fP+/I6mRZFf9asoQe3N7fotn57f9eG8+oab2BIodd SM9gaVZOxwiFkaJwzKycXuzVtSbFe1g7+5e1jiPtmNDxbswOqf6yn8VAXKz1dF2ZPv788fxw cPPwuDt4eDz4tvv+w/Z208TQp5Wwk/E64OMQLkXGAkPS7ixVzdpWBjxE+AlKxywwJG2dNCMz jCWcBcOg4dGWiFjjz5ompD5rmrAEDJ4dkgLjFSumXAN3AmoZlJ9FkP1w1pEoO1NQ/Co/Oj4t BysakUFUQ1EE1AgMm97Q/0EJ9B+zKIZ+LauU6Q+2MN6fTpWzJUbz8un77c2//9r9PLih1fz1 8frHt5/BIm47wdSTcQ9VBifTNGixTLNw9cm0zTrnUn5qZ8mqhGZMhvZCHr99e/QhKHBBYTDv 6XVAvDx/Q9PLm+vn3ecDeU/dRWvXv2+fvx2Ip6eHm1tCZdfP10H/07QMpmXFwNI1HH7i+LCp i0v0SmB28kp1sFKY/k4o+KOrFCj7MqJVmuGR54oPrW2GdS2AV15MM52Q6+ndw+fdU9i7JJyr NE/C3vXhtkqZvSDThFktRcvdgBpknXOfNGnCy3MGv2Xj5k88Q15uWtGEG3IdnZ0FRcO/Dy8u thwrERlIff3ACWrT4GCYxmlW1pgeNDIppZ3ucGLVpQinaovz51NeaMrJdnn39BzW0KZvjpmZ J7B+I2Z4Ueq4P1lQmK0CGWDQvC176iSFOJPHSQTeBXUYOO1ppsn90WGmcmZbzTjTvvjMrNZO XvBpDcYWy7wUMGXAu5PwwMlOgsLK7C3TxFLBZiUDJz7ivWbBZYYumMFZvxZHzDpEMKzhTnKO TQvN8dt3moor9+3RsUH63dBfRr7hwG+4Jpb72oaPQkm9CqreNLoKvzSavJFmeATuSas3fPG4 /fHNeRaeWW/IxAA29orl0x1bg79c602umPU0IYJ03j7eLKtgrwnMLqBEuAkMIrYeZ7w+X4CB /T7lcZxUZzFxLqwtHLfcCW7Vv+eUB0pmtyPUbr8/RBkznQB7M0pQiyPf5Fr2CuoyB3oUERsY ECkbHV03PLgJQyfML0dgInZmK1aiNVF7JYdyT4X9pmaXrYHHVu2Ejoyuix7fbMRllMaZWL1t H+5+oLeEo07O85oX+okskDeu2Oj9Gnl6wjGR4mrPyAByHZ6zV10/S9Pt9f3nh7uD6uXu0+5x CvPBNRpzSo9pw6lYWZusppybDIYVADRGH7KBjI64lH/UWCiCIv9UmLJIomV0c8kUiyrTCArs nvcWj3BSSn+LuK1iWWxcOlSM4z2jI0FVua+xf7/99Hj9+PPg8eHl+faekb3Q8Z07EwjepuH6 Nu+yF1L7zBsRhvt8EmOMSfc+ml/UojkQW4BG7a3DfP2LKhYtyyd00VZVwZ5yCPdsL6DjGDfC Z1GrpVD1R0d7Wx2V2Jyi9g3OXALba1/H44hmCckfjjWnBInusiwlXl3SvSe+vC7tspDNkBSG phsSl2z79vDDmEq8O1QpmjXNNk2LHcZZ2p2ivc4F4rEUTcNdeQLp+ymX8VKU3kUYV+ILadJP B1/QoPr267322rn5trv56/b+q2XUS+YCY98OnbnmbR0rqBDfYerk5c5T4+W2RzvQpXuxW9y6 ykR76dfHGdPpgmGvYQarro82baEgfoJ/6RZOhjG/MRxTkYmqsHVkMpV/nINqxNgR5jsW7dhi 0mnXokaQMRnTrUSB5Ix5ca2lMbmPgFBdpc3lmLfkcWBfktkkhawi2Er249Ar+1l4QuWqyjAz JQxTYr+IpHWb2bsMul7KsRrKBNq4gPUlvyjCgjEjsKpL0YQoD0xcAC050rLZpmttXtHK3KNA 85kcxVZjQ6rsns5lwKaDY7qqe/36YLOJdExT1Tv3dOnRO5diVkctmOqH0ZEw0zeeEIJa9PRQ w3JKIgAWIJPLU+ZTjYkJf0Qi2k1s92gKmD2+alesSx2RN7Ve9YH9mZsFm9x6vp0vBBYjHlFl dbm/8yCxUbrE1jHiRCgaWvvwK2TCcPQXjvnUlT5kPCgIimwZJPAtdd5ZcL5OEAWZJhKYo99e Idj/7V5wGBi54DTO8WowSkSEfYMXrGPfguzXsBWZcjFPLHcbYdBJ+ifzUWTqls6Pqyvbu89C JIA4ZjHFVSlYxPYqQl9H4Ccs3EjwHm+xn+/mg7irUwX8AOQM0bbCsrlFngLcyPag0SC0Fhsd LoXwzO5RJeGc6iiTwAisd9WvPRwioAh6/vNtAREnsqwde9CXHMabUVj7tBAterysSZjnOGGN ji1IPFTza6x1Bm5U3ReJW+xUHCzLuvBQpfNQgKBGtsDuCRVcyGS7L9cv35/RH/r59uvLw8vT wZ1+vbt+3F0fYHjB/7GkcyiFstGXySUstY+HAaLDWzSNtLmjjYbmoKWBiOQZdYtSkTx1DhHr T4UkolCrqsRxP3WHBFWXuPXcNN8JzAfoey2XWqdbFXqJWly4GcbWWWrZuX2eFnXi/mJsAqoC DeCsMosrfPheAKo9R+nYKrdsFEYPW7imSvLMtlRWGTm8gGThbBjYRNNeu8i6OtyBK9lj1JU6 zwTjCovfUH680T6c52XdoOOZ8+46owbtCDDmxdCtPWOFmYie8MvUw9Dr9UbYCSMJlMmm7j2Y lhZB+sF0MYcLCmVM1lMvEAPdR/dJriboj8fb++e/dACDu93T19BAg0TMMxohR3DUYLQg5N88 tW8ciE6rAsTIYn7ZfR+lOB+U7D+ezOvB6AxBCTMFpiWfGpLJwp7d7LISpUp9PwEHrL3NLCm9 TGrUimTbApWTHQup4R+Iw0ndSXuwowM4Xzjdft/9+/n2zgjxT0R6o+GP4XDrusxdQwBDh4Ah lV6OsBk7HUURbyuLsgNxlT9hZ5JsI9p87IEz0wug9TTPFUjUvADhU3EWho1Y41rAHUNNGxNS a+YyVhlwmbRVDftQR6mqyWfk4+nRh2Pb0AU+gfMWPVBL3vKnlSKj53igYopeSwwUgOb3sBlt dqV7BYoiWUWVqitFn1onro+h5o11VVyGI6jPznyo9CfE7sc3x1wCLM0SjMuR5+9jF6bNmDGN lustvWibv7s0/2VnyjRcJNt9evn6FW1e1P3T8+MLhoS0neTESpEvRntu8fcFONvbyAqH/uPh P0dLL2y6aKx709XOn4/ZzFvPlT802gifCEr0XNuzXueS0MaIWxiCpDeY2DNYnHZd+Ju7m5nP jaQTFShQlerx6PdaStj99aWdcOyUfmty3HHSPgrhCKEPRyBcGTuouVzb04dM2uS2x9wDEVdU XTISkqDB+35hMfWm4u+Q6OqoVl1d6XsVpmjYx3l0nbQ1bBYxmoPSnw9Ns9mGBW84gWy+T+jR Ft+6kKDf3qFigEw+WF1DnWDkg4hNYjEkExm3IghPLg+eOGSmGCSXArhAWOmE2TNbms0MXUy6 7UDayQyVrEBbXUs2c6M3yBfl2KzIADJs1QUfn8b/8DcqUW0/CGZxG0R0meh8hWQZyCwyzUtR oOaOIC3Waa+eDkYYxG7U+wrDjks36sU0DyHV/p0vOuEbjC4INNXwJPmUhkVjw3tqjUWHLBQl q3phSaAIOjcMXsV+gQvrI0Q9oLsnN1MarypE+8XRYvp45AKXLnl1UC4jGbsosEYmx6AxzvcE Yc/EgNEF22KNEYJC5RPoD+qHH0+vDzAU/ssPfZSur++/PrnMsgLGASd8XbOLyMHjIT/IRTfV SNJkhn4B493k0CxJxRYBpM77EDm3BYVnTO9W2oRUB3cZHCX2W4mGyV6tlLnWXrUzBXEN6hJM ftmwNGHHlsZYZNSY36ExDT6ypxZrGNcYF6cXHcfGNucgvoEQl9XO8YOrz0wAu572LwxtGQ+i 1+cXlLfs49Xhsp4Oo4GuhkCw6ShYzI+Zsv0VjYN/JqUfh89nfq2UZdMHKx87Zckb//X04/Ye 7QOhv3cvz7t/dvDH7vnmjz/++G/rMQL93qncFamwsyvkrFrWF7abu6VzIqIVG11EBaMfazYR 4IDEZQK8t+/lVgYyZAeDgd/78Aj5ZqMxcB7Xm0bYt26mpk3n+LlqKLXQ49fkximZk8Igop0R fY1qbVfI2Nc40vR6bi4MOPZDTYKthhEXRvc+Z+mkfeEwr77c+Yy7DugyXfxGgHIXRIv5/6yj qUgKoYP3SHkhbFcQFz5WpfKHPvyGzh4dk2eGkb4GEzQOVSdlBntOvy4w57iW4iLnwl9aKv98 /Xx9gOL4Db7oOceCmSUVufOmDUivhUHN3b5NS1EaFCivLI0WK0cSjEFmxbjDgQDvsLFIP/xa 0xbGquqVF1he27WkA8fmzL5OB58HAGg0HZ8ml12dSEcZ6hi498Wi9wMOdAbrO2bwkQiFPtL9 57P3+MgthhZO5Gt5zvj7UnvJwchx72YH3x0zj/WcG8GxJdnUvcJdwwlYaFG+l1NwQovXALRK L/vaOnbJHGbZCyFrrij6NKDaj64UOt9d7MdCb5s1TzNdzeXeNmSQ40b1a7wLDhQfhswE0MCL yt8hF21QqkGXFOsGqsWXaI8Ew07QCkFK0FSrQCfL0QTKv7cGvoH3a6ZoD5maqnykHj18LRi9 odLtTN2zi66J5+QbBkjJr4jeMVTARQK6PD7W4I2VP09WUeZupNvYzwRGSsCrfXYggvomVdqv yBCG629eHI4YS7f35huW13mrk9doSZcNCZyxNT0EprJauTosdBpE4zxewPyp11ctzgVbYlMI i3a5HCtVHbCbpZ9m2+rVyB3xZvF0FWix6zpcVRNiVnfdGU7gCISFAdyZQhH57ncT3Ng7QL/0 B5JrygDUiVzysE2czWxKH85Td5cVbNowl9sazWxMMHz+/NNDpTdCGH/SJaOFvPcZzd4aM52j KpjqREFPcjhMe6ewF3BsNcG5tBwhVoUxYoZ0jlVFe4aylXfsBqb3FO84tQYbt+7oy4F4aKsM 2No6VUdvPpzQAyTepnCXVwIT7dkzSYBRDNtMdY1+zFk2p0Zacxa5MrPp9MtQtG5DpR/g74Iy GKHOJVhvYHVLcUaLwxok8zkFrvOhbVN2+BiqJPOJ/mXHm5pqUhkoPcFQNSrLM26UMMXEvuEZ oMB4vy5yTJOB0QDLDG28EmZw/Dik+2q7YF2hDZLTqm3UeD7I4Rd3fhQbVJnresfmQItYmmIB U5R+F0PS6T+n7zjp1NMngjMp1DdCGina4nJ6qsRgwItdzum70Twr0lk2NPxXkbKyZBX5gKLh bTPbI89o/EVCL9aeuDGfLFxsImwlWrpggFjOtGo5BmvDOQ63p3zYfYsi8kw5Uwz0HzP5M4V/ AJmXWnoXxtufSJScRuyzmqAySFzbp1yVap+RmR4wekdqnICqzYB+56ivh02YDsZqo0Pxgmjv vAxNcP3cSXwnkp7UXcr2+3+/e3pGFRuvodKH/+wer7/ubF30bOD59aRM4ut43ZoT0wlf0JQ8 0UJR5yTSxsuze1vJXkckZei4J2B6T2SalQtVdIVwg5MCTL8axV+kvAL3BlrA4nK8HnErcQuY nhX3MbOztL4ILug7EKHqi+lQs/azoV7mDsn0kyqZAogWn8y4CokSn7TboSSHH/tlWyNBBhBw vJF50sfDfzDB16ElfoBKQlK3voMjRxOmHuCuvnXK3nUYhFbQxir/B2AaCYqdPwIA --pWyiEgJYm5f9v55/--