From mboxrd@z Thu Jan 1 00:00:00 1970 From: kbuild test robot Subject: Re: [v2 PATCH -tip 3/6] net: sctp: Add SCTP ACK tracking trace event Date: Wed, 20 Dec 2017 08:48:47 +0800 Message-ID: <201712200840.wW0CtR16%fengguang.wu@intel.com> References: <151358473510.28850.10475072993963389604.stgit@devbox> Mime-Version: 1.0 Content-Type: multipart/mixed; boundary="PEIAKu/WMn1b1Hv9" Cc: kbuild-all@01.org, Ingo Molnar , Ian McDonald , Vlad Yasevich , Stephen Hemminger , Steven Rostedt , Peter Zijlstra , Thomas Gleixner , LKML , "H . Peter Anvin" , Gerrit Renker , "David S . Miller" , Neil Horman , dccp@vger.kernel.org, netdev@vger.kernel.org, linux-sctp@vger.kernel.org, Stephen Rothwell , mhiramat@kernel.org To: Masami Hiramatsu Return-path: Content-Disposition: inline In-Reply-To: <151358473510.28850.10475072993963389604.stgit@devbox> Sender: linux-kernel-owner@vger.kernel.org List-Id: netdev.vger.kernel.org --PEIAKu/WMn1b1Hv9 Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Hi Masami, I love your patch! Perhaps something to improve: [auto build test WARNING on net/master] [also build test WARNING on v4.15-rc4 next-20171219] [if your patch is applied to the wrong git tree, please drop us a note to help improve the system] url: https://github.com/0day-ci/linux/commits/Masami-Hiramatsu/net-tcp-sctp-dccp-Replace-jprobe-usage-with-trace-events/20171220-081035 config: i386-randconfig-x011-201751 (attached as .config) compiler: gcc-7 (Debian 7.2.0-12) 7.2.1 20171025 reproduce: # save the attached .config to linux build tree make ARCH=i386 All warnings (new ones prefixed by >>): In file included from include/trace/define_trace.h:96:0, from include/trace/events/sctp.h:96, from net//sctp/sm_statefuns.c:63: include/trace/events/sctp.h: In function 'trace_event_raw_event_sctp_probe_path': >> include/trace/events/sctp.h:31:19: warning: cast from pointer to integer of different size [-Wpointer-to-int-cast] __entry->asoc = (__u64)asoc; ^ include/trace/trace_events.h:719:4: note: in definition of macro 'DECLARE_EVENT_CLASS' { assign; } \ ^~~~~~ include/trace/trace_events.h:78:9: note: in expansion of macro 'PARAMS' PARAMS(assign), \ ^~~~~~ >> include/trace/events/sctp.h:11:1: note: in expansion of macro 'TRACE_EVENT' TRACE_EVENT(sctp_probe_path, ^~~~~~~~~~~ >> include/trace/events/sctp.h:30:2: note: in expansion of macro 'TP_fast_assign' TP_fast_assign( ^~~~~~~~~~~~~~ include/trace/events/sctp.h: In function 'trace_event_raw_event_sctp_probe': include/trace/events/sctp.h:72:19: warning: cast from pointer to integer of different size [-Wpointer-to-int-cast] __entry->asoc = (__u64)asoc; ^ include/trace/trace_events.h:719:4: note: in definition of macro 'DECLARE_EVENT_CLASS' { assign; } \ ^~~~~~ include/trace/trace_events.h:78:9: note: in expansion of macro 'PARAMS' PARAMS(assign), \ ^~~~~~ include/trace/events/sctp.h:50:1: note: in expansion of macro 'TRACE_EVENT' TRACE_EVENT(sctp_probe, ^~~~~~~~~~~ include/trace/events/sctp.h:68:2: note: in expansion of macro 'TP_fast_assign' TP_fast_assign( ^~~~~~~~~~~~~~ In file included from include/trace/define_trace.h:97:0, from include/trace/events/sctp.h:96, from net//sctp/sm_statefuns.c:63: include/trace/events/sctp.h: In function 'perf_trace_sctp_probe_path': >> include/trace/events/sctp.h:31:19: warning: cast from pointer to integer of different size [-Wpointer-to-int-cast] __entry->asoc = (__u64)asoc; ^ include/trace/perf.h:66:4: note: in definition of macro 'DECLARE_EVENT_CLASS' { assign; } \ ^~~~~~ include/trace/trace_events.h:78:9: note: in expansion of macro 'PARAMS' PARAMS(assign), \ ^~~~~~ >> include/trace/events/sctp.h:11:1: note: in expansion of macro 'TRACE_EVENT' TRACE_EVENT(sctp_probe_path, ^~~~~~~~~~~ >> include/trace/events/sctp.h:30:2: note: in expansion of macro 'TP_fast_assign' TP_fast_assign( ^~~~~~~~~~~~~~ include/trace/events/sctp.h: In function 'perf_trace_sctp_probe': include/trace/events/sctp.h:72:19: warning: cast from pointer to integer of different size [-Wpointer-to-int-cast] __entry->asoc = (__u64)asoc; ^ include/trace/perf.h:66:4: note: in definition of macro 'DECLARE_EVENT_CLASS' { assign; } \ ^~~~~~ include/trace/trace_events.h:78:9: note: in expansion of macro 'PARAMS' PARAMS(assign), \ ^~~~~~ include/trace/events/sctp.h:50:1: note: in expansion of macro 'TRACE_EVENT' TRACE_EVENT(sctp_probe, ^~~~~~~~~~~ include/trace/events/sctp.h:68:2: note: in expansion of macro 'TP_fast_assign' TP_fast_assign( ^~~~~~~~~~~~~~ vim +31 include/trace/events/sctp.h 10 > 11 TRACE_EVENT(sctp_probe_path, 12 13 TP_PROTO(struct sctp_transport *sp, 14 const struct sctp_association *asoc), 15 16 TP_ARGS(sp, asoc), 17 18 TP_STRUCT__entry( 19 __field(__u64, asoc) 20 __field(__u32, primary) 21 __array(__u8, ipaddr, sizeof(union sctp_addr)) 22 __field(__u32, state) 23 __field(__u32, cwnd) 24 __field(__u32, ssthresh) 25 __field(__u32, flight_size) 26 __field(__u32, partial_bytes_acked) 27 __field(__u32, pathmtu) 28 ), 29 > 30 TP_fast_assign( > 31 __entry->asoc = (__u64)asoc; 32 __entry->primary = (sp == asoc->peer.primary_path); 33 memcpy(__entry->ipaddr, &sp->ipaddr, sizeof(union sctp_addr)); 34 __entry->state = sp->state; 35 __entry->cwnd = sp->cwnd; 36 __entry->ssthresh = sp->ssthresh; 37 __entry->flight_size = sp->flight_size; 38 __entry->partial_bytes_acked = sp->partial_bytes_acked; 39 __entry->pathmtu = sp->pathmtu; 40 ), 41 42 TP_printk("asoc=%#llx%s ipaddr=%pISpc state=%u cwnd=%u ssthresh=%u " 43 "flight_size=%u partial_bytes_acked=%u pathmtu=%u", 44 __entry->asoc, __entry->primary ? "(*)" : "", 45 __entry->ipaddr, __entry->state, __entry->cwnd, 46 __entry->ssthresh, __entry->flight_size, 47 __entry->partial_bytes_acked, __entry->pathmtu) 48 ); 49 50 TRACE_EVENT(sctp_probe, 51 52 TP_PROTO(const struct sctp_endpoint *ep, 53 const struct sctp_association *asoc, 54 struct sctp_chunk *chunk), 55 56 TP_ARGS(ep, asoc, chunk), 57 58 TP_STRUCT__entry( 59 __field(__u64, asoc) 60 __field(__u32, mark) 61 __field(__u16, bind_port) 62 __field(__u16, peer_port) 63 __field(__u32, pathmtu) 64 __field(__u32, rwnd) 65 __field(__u16, unack_data) 66 ), 67 68 TP_fast_assign( 69 struct sctp_transport *sp; 70 struct sk_buff *skb = chunk->skb; 71 72 __entry->asoc = (__u64)asoc; 73 __entry->mark = skb->mark; 74 __entry->bind_port = ep->base.bind_addr.port; 75 __entry->peer_port = asoc->peer.port; 76 __entry->pathmtu = asoc->pathmtu; 77 __entry->rwnd = asoc->peer.rwnd; 78 __entry->unack_data = asoc->unack_data; 79 80 list_for_each_entry(sp, &asoc->peer.transport_addr_list, 81 transports) { 82 trace_sctp_probe_path(sp, asoc); 83 } 84 ), 85 86 TP_printk("asoc=%#llx mark=%#x bind_port=%d peer_port=%d pathmtu=%d " 87 "rwnd=%u unack_data=%d", 88 __entry->asoc, __entry->mark, __entry->bind_port, 89 __entry->peer_port, __entry->pathmtu, __entry->rwnd, 90 __entry->unack_data) 91 ); 92 93 #endif /* _TRACE_SCTP_H */ 94 95 /* This part must be outside protection */ > 96 #include --- 0-DAY kernel test infrastructure Open Source Technology Center https://lists.01.org/pipermail/kbuild-all Intel Corporation --PEIAKu/WMn1b1Hv9 Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICFuuOVoAAy5jb25maWcAlDzZcuO2su/5CtXkPpzzkIy3USZ1yw8QCUqISAIBQC1+YTke zcQVjz3Hy0ny97cbIEUAbCp1U6nE7G4sbPSOpr7/7vsZe3t9+nr7en93+/Dw9+zL4fHwfPt6 +DT7fP9w+N9ZLme1tDOeC/sjEJf3j29/vb+//DifXf14/uHHsx+e7y5m68Pz4+Fhlj09fr7/ 8gbD758ev/seyDNZF2LZzq8Wws7uX2aPT6+zl8Prdx1893HeXl5c/x08Dw+iNlY3mRWybnOe yZzrASkbqxrbFlJXzF6/Ozx8vrz4Abf1rqdgOlvBuMI/Xr+7fb77/f1fH+fv79wuX9xLtJ8O n/3zcVwps3XOVWsapaS2w5LGsmxtNcv4GFdVzfDgVq4qplpd5y28uWkrUV9/PIVnu+vzOU2Q yUox+4/zRGTRdDXneWuWbV6xtuT10q6GvS55zbXIWmEY4seIRbMcA1dbLpYrm74y27crtuGt ytoizwas3hpetbtstWR53rJyKbWwq2o8b8ZKsdDMcji4ku2T+VfMtJlqWg24HYVj2Yq3pajh gMQNHyjcpgy3jWoV124Opnnwso5DPYpXC3gqhDa2zVZNvZ6gU2zJaTK/I7HgumZOfJU0RixK npCYxigORzeB3rLatqsGVlEVHOAK9kxROOax0lHacjFaw4mqaaWyogK25KBYwCNRL6cocw6H 7l6PlaANkXqCurYlu9m3SzM1vFFaLniALsSu5UyXe3huKx6cu1paBu8NUrnhpbm+6OFHtYXT NKDe7x/uf3v/9enT28Ph5f3/NDWrOEoBZ4a//zHRX/iftxtSB3sQ+td2K3VwSItGlDmwhLd8 53dhIpW2KxARZFYh4T+tZQYHO6u2dDbyAS3Z2zeA9DNqueZ1Cy9pKhXaMWFbXm+ATfg+lbDX l8c3zTScvdNdAef/7t1gMztYa7mhTCccDCs3XBuQLxxHgFvWWJlowRpkkpft8kYoGrMAzAWN Km9CAxFidjdTIybWL2+uAHF812BXxKsmO0tH4bbCUSl+d3MKC1s8jb4idgTyyZoSlFMai8J4 /e5fj0+Ph38fj8HszUaoQHU6AP4/s2WgAdKAdlS/NrzhNHQ0xIsM6JHU+5ZZ8EqrkCuN4WBE yXdiTU66YXcyTokdBS4Imt9LO6jO7OXtt5e/X14PXwdpP3oO0Cyn8YRTAZRZyS2NyVahDCIk lxUDBxfBjKgoIjCvYPRgy/vx5JURSDmJGK0T7grCCQ28d5aPgQ2hqTQ3XG+8ca8gMiG36Oxo jIF4JQML7G1LZIKNYtrwbt/HEwvXdNMVhji/DGMWIxuYG1yCzVa5TI17SJIzG+hxiNmA/83R /ZYMvdo+K4lTdTZzMwhJ6sNxPrDntTUnkWguWZ7BQqfJIORpWf5LQ9JVEv0NbrmXVnv/9fD8 QgmsFdkajDMHiQymqmW7ukFjW8k65DwAwdELmYuM4LgfJfKQPw4WmDuIkFBOHL+cK/IRsWre 29uXP2avsNHZ7eOn2cvr7evL7Pbu7unt8fX+8UuyYxetZJlsahsJDIqEO4oIedz/wuSolhkH WwEUlNqjS4Og1p3TcRwCffQ1GhbT7CbRuGNhZOnUI6RwDNBZMzPU6dT7FnDhXuARnDMcA7V7 44nD4QkIX4+aEt65LLsjJ18AiXzQzJfZAkMQYn0XP0C4XV8EZl6su3RjBHGHMYBLiTMUYB5F Ya8vzo6WX4varlvDCp7QnF9G5rqBKMdHLRD05l5jqOhwgfYACJoaEwWID9uibEyQAWRLLRsV yQD4lmxJH60j9mueIlAiJw2Vx+oo0+iAheb8JkzxOnjONyLj4fY6BIjZhGD3m+C6IKaLjLKR qGIdytvF4zro2cEsgwqRr+oZjzGWG07T7E2BAbXSHLxJzLNe2OJMZ1Gi+m1c1KjzOIrUrILZ vK0OYj6dJ/EcAJIwDiBx9AaAMGhzeJk8XwXMy475A/owx1pMvevkZBIyTMMo1U0iGlaDGxU1 +NHAZXgpF/l5UBLwA8EmZFw53+vS8WSMyoxawxbB/uAeA9aqQBy8XYkCJ1yL2G0FkZ6AqCoQ TQOZVoVGcPCCyZF3iMmXb0f+s1ixOvInPgg8eo/IQKTPbV2JMLUJJHzMjsFHQP7UFg25zaKx PEiy3SOodcBAJcPtG7GsWVkEEut27gDHBZ1LLygtMCufGA6xqpAEGcs3wvCeeanRWjCtISyk LMKKZ2slgVXokiGsC/i8xpn2lRlD2uRoB/gC3BtwBPUAzBCVs/Skjseo41ZsIl0BaaSkJIzj tcsyCtrSujJFTpoUrwYwvD3GYcdhKjs/uxo55a6Apw7Pn5+ev94+3h1m/L+HR4hLGEQoGUYm EFUN3npi8q5ygEjYfrupXBhN7HBT+dGtC10iAe/rWGGubkq2iHSsbOgMx5RyCsEWICJ6yfvk bZoMPRE6/VaDRsqK1mHLK+cwWki2RSEyF+yEaikLUUYBm7NVTgaDt5WeMJKMHtaxyNkfVfLd 1EkHc6QzgFnwejjgfmkqBfH9gofKC1EghNNrvgfLxcsCaw4DdijoDNExruuquqAjoPnoCDOM Naf2yAvgkcDXaep4RBK0oNxgaAUBHcSwW5aWKQToLkYysCeboNZp4clDNbckAjwVPcBDsY5T UP4lMrVD6uxIV1KuEyRWXeHZimUjGyIlMnAcmEh0SWHCDqxrgtm2otj3jn9MYLjt6gFEBAjh xx4iGUzcnMdytbFkj5ovwajVua9xdwfTMpW+aFZSbwd0aVjlcKstaDFn3u4muErsQAIGtHF7 SL0/mECA20bXkF0BD0QoyKmVIw5mxXSOgbGL+yzHmmASFQ6TEOv3hkx3fMmbKhVHx2ZKpTxf IZHwUTralNHJeWHywX5WKSyQpwz3UF/Wm8DlspmoHWPByZcV+kIhsXnDMzS5LdgLG8U4E3A3 cgmRniqbpagjsxCApwwBUDhmov66A0nixxhJufKUBkSjTqPQhALOtimZpjOWETWoiKyXxNJ2 hbUIYBq48lRWPNeFI/HSUmjMH1LzRWbtlDGpsSLEuxsALManGiTz7gAVz9ADDXhANSVYMLSl YM0x/CCshsM4Dze+LBlfUSUEfAemn7RY8aiP8eFLte8L67Yce5R+byvypPCOatE4u0QXwWpw HcD5LWh96GIhTYfotLtsuRwhWNa57qiAUcvAZxUFnQIOm97gW7tzpyuvSCNdzsLKvrast7v/ FzEVuYxcgQWfYoNBoZOfRKXDvQBN0Gi8nGnqKHfqYaNswt+XZHLzw2+3L4dPsz98oPnt+enz /UNU7EKibnPEog7bRzVJWJ7iSKY6In9d7HJ27w/+kfSyper/IcVV+1NqHDvP7j3/iqMWB6k1 RnSQTIWmwSUJBqPl6/Mgo/FqTKWknYJb8CrgGyQ4uCi1QJ9HSYmpz4OwrnYXgbCwApvV1EQF 6Xinx6zECEJX24QCTYy7psjdNK6WPE2itwnBUPRxgqKen+4OLy9Pz7PXv7/56ujnw+3r2/Ph JWwnuEFNzydufSCemug0KDiDUIL7us6wB4fCenePx+g3wVfK+dEgegPjUYiwjgZBDKpVHukF juU7C3YHL467FJzcNlL6KUpFhtFIwKphlqEw1m9AmqKtFiJcv4f5+GyyAwPckoissa9twZlb 78ZaF6SRqfVqD2ESZOXgOJdNlDcAy9hGxEWWHja5oTWkhv08Q+K9qbrccsIQH6dNfCuxwJE0 KZmCwV9IaZMyRHX1cU6uWH04gbAmm8RVFZXIVXPX+jJQgq+yoqmEoCc6ok/jaVnrsVc0dj3x YuufJuAfaXimGyM5jXO+lU/U36utqPF2MJvYSIe+pAsjFS/ZxLxLDnZ/uTs/gW1L2ilX2V6L 3SS/N4Jll+3FNHKCdxmksxOj0OZOaGznYWIb5RQUi6hdI4y/NpiHJOX5NE6BBwUTWIcmZTBK mAVh9Bbj0LS7ca6+ZpoqRoMaxIAuZZlfpWC5SeytqEXVVC4SKyB5LffXH0K8MwaZLSsT5Q/d hRfG8Lzk9N0AzAhuzb9WUHXqwO6Uo560HgO2lyAHRWKNHiNcAF9xy8i5miqL4CvFbVqnycNs tnYtRyaMDhS4zkpZl/1QZq5Db2QJppC50kA69sSwPsLrYwXMby13txCJCCiMx7MRUMgx2GWx BLmQPTByh5priUVWvEnoemvQQmMORXsBJzlZxA0fVgRlza9Pj/evT88+9BwYEpQROoGvUTVp ZzMi1kxRNfQxYYaVtihZDWmce5db0s06/nFIVvaQa4RtkvETkp3PF+kpcaMKsbuM2mesBCuw YMRa4uN6fBbIepijUWRAKjJQPd8IMViwHuhfnrZyRxp4+VMTu2zNmbiCpSYqsQLOpKhG0O6h lngzD26eimU85iq6Se+A8yv6SnRTGVVCnHT5T2hM6chSuCe4iBYdoOmwEck5HeUsgWWQt3J7 ffbXxzP/T/KeRJ4F0BZ8gN6rtLuzAAPgsYzoZHTh8TTaWeO+ZwkbZgLTK0qU67IPMbEJpeHX x72eHNtvqmJ1w+JruOOOPI664vKD49la50H9uKDYN0zna+VpMYZXizicjMDdpKNidp8pLhuV cCwXJmM6DyeOqw5drOr7E3F66prCyYeybgvOf1wd9cqzc4EXNGFdsAP4W5gsvtOgYJVYapbW T9RqD8Ysz3VrJ1u/fbQusaATzFY1YaF3iP8Npa19F56rOPk2oVxfX539fIxrTpfRKGzLyi3b xx0xFFnlbyKn6ze+9G5XqsVLDKqYmEzrVNZFZ4HbD/uN14GkZiVndU881K0mUuIbJSVtfm8W DWV1b0yVtP72nbrAapV0GvXETjOoYkkn5K4FuL+/mSo0wJlyrbGa4O4pvB3roo4hq8XrEofB S5c1nef5vHXT15gHd+uCsLTtCTSwXYDhW1VM0yU8tJnKUmrm/A0GwO0C8m1QE60bleoEEqHO YvpZ9eo3kPoJJib33YZY6dlezwcVZnbV8qopR/pXWU3Xuh2vx7ea0SbhNKcKKF1kVImo2sQL qhzbXR9EduumPT87o5l70158mERdxqOi6c4Ck3pzfR44OV/DWGnsoouMCd9xOj3PNDMrd8tD eVQwagLjV5AdjU71vPOpQRHU9Yyinpwa764/YfxF5JK7a+9NbmSs0rmr0S0SDe5PWuZ4M1jm dtxQ4g7bu+Ne3lYgf6W7p/Nx8dOfh+cZxMW3Xw5fD4+vruDGMiVmT9/wE57gwr+rngcOsft2 YdS21SPMWoDt29ehEQHvWXKuIggWY3vo4EEqMKBr7qqFFC+rhHiqmgQof2d5JN7+6kPsoLp/ oqyehVeg+NTH4O6UzVB7DXle4bcx3d0ADlHhtzAO0vUP+I24lMAE3xQN6pr1N6tLMifwc8Uc 9StCzFwYP3+C0nzTyg3YWJFz6sMTpOFZ32w82g2jNcfhFsxC/Laf2uiisTYMHRxwA9uQCaxg 9ZgLExVtxLkigeZwsFE3Qc8IXxA4Zl40Om7ljZEJXKgqFYphHrZcapAQOxplV1xX4R2u33pj rATxNaDARfoFSEpx6t7Hr+F0vVEQkuXp26Q4QsimT1ZlKGdy6hM+0LK+eJFsXtaWgfmaFN7O II2qBV6yF2P5W5ENTyGnKm5XMh8NhJiiwdZ7bAnYQtTVyrqkRHVQW6b4qNGjh3e9BoluAILk Ya5sMZnYu6Hjrn2F9y1SgTCll5M6i5GT/HB/xzpsCnqHTEUBQd+pPiueD/95Ozze/T17ubt9 SIomvd6RI8Wnh8PgPlxLeB63OfWwdik3bQmxO925F1JVvI66uZ34Y5BsBrpMNqokpcSHL902 3EYXby+9q5v9C4R8dni9+/HfQZtbFp0yqsFSYpBH14Ucuqr84wmSXGi6OOnRrA7KrAjCFWOI nyGG9QsnlO5blGR4Vi8uzkq8lhNhmx2gOPqgKCdDIIt1G0HgJDTtC7oBwO5fJt+SM6OqZA3T +/F0qQ4z5aSPJE7DDIvbLGMsellPM711Rzz0N0+sCDo4WgcUnWp29OS2So7LiBGA/DoJce6g TCqLk1FPhvbOJ2VdABh/CujsuW0WMYTZREww/Cq5+z5xLFgirNkjQOnkhRQzIk9m7Jqkhui+ cwCofKkZyQ8v918et7fPhxmisyf4w7x9+/b0/BqpKPB9G8sSANy3eWMo3p4ew1+Y9Penl9fZ 3dPj6/PTwwMEw5+e7//rO12PJPzx07en+8d4TeBr3ve1RWfSw4/md+J8uCrars3yuNLLn/ev d7/T2wlPbgv/CnAYlkc1864/hrJ8/uvurqMvHEBlbhmmJpHXcJCV9l6e1BxZqonIsBT0hVrN 7YcPZ+fEBpY8NHdYFK8jScXCWPhcZYLFx4AQkF6Wt5mgbTXOkfCqO4Yf7m6fP81+e77/9CXu OtjjXQ91mvn8p4ufg3rmx4uzny/SDeM9TVo61HAeuZAjQGuN+OnifAzHqqA7BNnY68sw9ewI Om3Xu9buWldRId/+OB/IBK+XoqbN4ZFsws4MqzYV9rDEVzg9FmsqVJDS4yvcZ5vlfNPrgr79 dv9JyJnx+jBSgoBNH37ajdmUKdPuCDjSzz+Se4QRS15fnNim3jmSoH/MVUv2plj0++Z/He7e Xm9/ezi4H8+YuUun15fZ+xn/+vZwm6TUC1EXlcU2vGFKeMiijxM6IpNpodIeWoZSkFJ2wKEX yIMrMdGSgMtNVDy6ksRl+jl41wwkZFTHA33u+VAfXv98ev4DwsVxIUGxbM2jJhF8BslmgX9p arELXwKfHQn5CrYk+2WK8NsffML7EDQKCRR/jyIBxV/7OJBpFqBQpcj2CcJXwKNYwA9AZTeg 71Obw/bcpEIGPMQmfMooV+HH5FWWMEzUIU+F8h8NxB/XApTlGwxp8tZdrEYxncBO30VrNfhJ Vx0lWd3PrLBf3ZVApsj81a0nZnaiobMn23C9kIYKtY4kWclMFE4ARtUqfW7zVaaS90KwK73S 8yNaMz06CKEE/VGfR0KeD4axaqhuHk/R2qau43AH+efehzriPV67yLWIP7Xwc20sVWRFXJMH CwXwQjaxfLRslQC4UWPIWEuE30InrCHQiXG6uMOQQK8veBXmLz+i39tIKU5PsOA8HTvWiNZm igIjywiwZlsKjCA4aewKD3Qfp4Y/l0edIlCL0NkfoVlDw7ewxFbGpYsjcgV/UZdIR7yxmSIm Xe0XJSPgG75khlyp3pxaB2vM3QXveGh5cosbXktiJ3seyuURLMpS1FIYApVn9Ltm+ZLc1mJB x6z9/SEcx0m8O7CTFI7LJykcv/+BoqZ/iaQn6OXjJJHjzYm70oRHPVgniyfonpXX7+4+fXkX s7jKPxhBRYdgtOax7dvMO8eDbUbFxJDuC2L0nG3OIm1AdZyDGSNrO4gaGbT5tEWbj00arl4J NU9AItQgP3TS8M0noP9o+ub/YPvmJ41fiHUs7j7DTr5KdK8DrmR0LIa8o3eo0WYQ6J1LPAfA OuKpqZLQIZkTIizsZzejiSc9ph/Gl/O23FK+tsdCAkL+iAe3o3oEwPBnovD6cvImGJ2CsqoL SYr9FJGbSK32LmODmKpS9E01kKYfWR1BoXvxyShWQSDAhgTj9fA8/ZN7wwywqKa/zBxokBUi /qWzBOV+DeQUPvkJozFBKSPTUxdoUmp3g0/trXC/f3H8YZYYDHP6fHEAH2UqXKG7pkMVoU/p SOJnJDdisYV/lYfHU2BDUvgrOgiJL+8Q8n+UPcly4ziyv6KYw4vuQ0WL1P4i+kCBkIQytyIo ie4Lw+3yTDmeq8phu2eq//4hAZDEkqBrDt1lZSaxL5nITcjFQmQM1NxIv81aLvpAvUAA7lBu uQDfswbX1AOBdqu225eZ+gUJkMHInLLL/UfncLbQcpoDtX46l04EDRgVGngGVu0EEdNule6w ARGCCbaw2mHK5cJvpeT9Orv//vXPx28Pn2c6YNwoe5qfdrC93U/f7l7+9fAW+qJJ6iNtTFtn ZLcZdMjxMEGeclLhvewpTu5J5VO4Z9YELehBHJNjjCyj6Xu1inX1k3XqMZ+gKA72KkVJgkfN SAQiueNEgpE1+NbDKKu6bG+nK3W8xVESUuWmljpAI65vcMWr3AX69e7t/svEkm4ghlua1s1t FWqIIrJioSB4FRJnmkQczZZnG0ZTnSfxKSGu3O2R0Es4vg5Gz8lP01KCPUxihHx6LODM6k/T CapsEu3yoyiJ4B6P01Obxc10IUMM2Kmhkb35ucER3NU7hf3MsaQpJYvo2MEgdMUhEPsJoS35 9Fovr0XwFFQU7sMfRnLT6E031Wx5Q/7s6tRn2M91EvR9+WQLa0re266cvLN0IFwWfaeM/t3z HaraMSNFiNRh+bPDBZfZz9KeF7jTFZisUVwU6i6OZCIAUsYIFXThQcWJwgr2RTnJR7GOtFld +Ozt5e7bK+g4wUn67fv996fZ0/e7z7M/757uvt3Dm/rroAN1qoMQBmWHPwCYFOfUfjcdEEl/ 0qEFC9Q7BSen0Lewsjxlm+zvq7jQgE978fsTsGJVyGuNmYsoXEbc/l0z4jftgD+4KGR5wV8o ZPl7vwaA1S4wRQaEo+8XCkVTt4TiU88DyNESH5sD5hQ8Lqmt8c3d8/PT472UEGdfHp6e5Zca /b8TsuQoI6X0UCdSojY89wRcHQc+vBe7FNwSB8gJQqOqN33ABwUNJTd4NAZFCm5mTtVSWEAq 7puU1LjIhBYmRU2lGbBhHqHRWGsCBYpV/msHwDWz5i6QAYPzJiZFXbnPBia2aVzNg0CpDybK LY72266Ca8bUaRJOJOoNll8nV7exnJJzzZpbFy6G3ZfoB5TfD59G9wY5df69/m+X/Tqw7NeB Zb+216Sz6NfuphiXD36bGKs9TKAXPhbCcFzfTtWhmr3lbr2JrkPreu0sbAxBz2y9DOBguO35 NpAgE6Ery6A5ZYGSoQsnmqSu0tMgyfFzeY1uOLwINFCtpkCFeI2b2JZra1/aYGc7rZ39pIyo KPn28Da13g1lACmkfN0d62QPfiVlcIuB4IZvc5uHhF9duj/CsxKxraUUqtdLSMWnfKkFjQJa bfADfkowO6IgvQ4YZZI59Xvt/InqpLJQ1cnsZVyjwXAbFSB+VKZAuK6cio+BQcONqRrcbwdE PhSxr1l6xLniS5YU3XYeR5+QtqmlMI6RXhqD2UBfr8kGiR+xuRxb64cOTzDCkiYxo8lBzNuk qjJqg1mV2syq+AkOqqblSRuvjFYklWksdipVP4Zur7PyWqH2SIxSCuOxMk+nAdYVmf5DRo5l 8PRhe5watOqCQOoQy2eowtIneBGV+2EhRm/SAqIv8RISPJgF7MW6SMD9EXu/LitaXJS94FjS RbWQ+xBv8V5yaS5/yQkbiJBqwJ+TlVjBNsJ/0dfqAVvznleZ/UomId2RlzaNXJJWEDUJFZcT YhJRmA/LJ9tpXE6CHKWAGgAeOhdiAjkIkkr5YH1cEI7b1uvo0lJrVKNRbQ0Kz8xFbrsW7Dpv Ozvi7v7TkKJBG1zN3h5e3xwjfVntTeOoIQxkWpeCVSoL5sTiOyV5naR4exPTK1isPHURGcaV RbcnmMsuYI7Xvtni1yx9+Pfj/cMsHWz8rFIuBN2qEtV6zeCZB7K0RAAgSUZARAL1qP0AAdiM okd1BU+ZtleSLKsjgUgzEks2G8xvEXDswOBfM1wygHN/aCua3EjrZZeWf0xs90cDCJa9OMKP ig1YmvPRjtaDM7RFrtWt2dhAr28uCQTT9EvMWh/Iy4Ob08AAd8S33YXJ4BAbEIIV//Pu/sFb Tie2iCLcHFkOP6ni1QRehaBScbewZbK3LS8hiDFNMbZuD3oVYydLNQt3Pu4D8eIXe4PlA1FO LU9/Pbx9//72ZfZZ7S3PflZ8fCJs33BlfGwWKuDnpA7WKdBpk+Hxk/pSF5iuXSOzM7Wtt/uP oFK/KZcTupYEMq8vmVUKADpuWVML6JVptfbIQgm2ua1DxuqH7obgLBZvaprkKpwqNqUgfdVn Sx66MshRZWp7rrRtOtvAV4Ls3BDkcAQmIbJuGMl9RNJlIMejPfSfwQKlWQlhA8TNDYm+uF92 RygEFdZxq7uyOGNENQXHEyqDu4PVKD2me4QMwkD1YSWBRAaSRuhEV+tkJElZbWQxMCoVP2iW QcRWsWOtcNkWkcwDB3HbWI1Q9Iy/ndrCQAez6QxDVKeJn+pvQMPMmUVnbC8RYbbPsOjvISqi JkEQNYGYFrDsLC4Tw3enCV5TUg6hMsYSw1S//+Pr47fXt5eHp38g9eY0EJ51oAhcogN+9C1G yuZ9WAfn7Le/lp6AU3XwJpFKOUiFqLIBzsdtmZvpA+VPXarMQzfGrK0PN8zkuNRv76zWYFZU Z/zg1ATHCuWmgAnbedbHu0pzzsEvnDQqGugE4iYJO9hXKDtMePtKdNAURmLP3DwCaAWqQgQC Jn5Nc+s2p8fCkRESZ4pDwLGQJ4K5D+p4BFOFHYuYaVgPAzU4JnRB8is7EssRgtzRzBVKxDjZ dlOQA1P2bUBoVzaHyx3zCD7ea/CsdH0lzioBwIlmlSl1W+AOrOuNY1RU3OSV7fXbwwSbfy4C iQ+apEiTLBhLTtZ4YLUSBmXuo7FBh6t0tjLbOJCywgvqq66BnsJo+1COCrru9htFd4ckyyDq s7GjExnU4TL4thiPDpkQ/wM4B2qMnuT6anZBL/6BKawp9z+D+1p/K9Z6XgYcT/ktNwKpoiRD zrPqPMGCmlTg8+lk5hPXpuW0o353zMxhpWHcDH2hYdfIA+W55cCmyzOz74GTmUxemkI2q4Md 4zBRIScH05nBLVvxrsZmEP8UXsB4YJx09DzsNmiMRSp+QBAAGUFQcHEmV2GilGe1jI0l4259 iIIFyFQWMuSLbSPlE0LA80C8ASDug7z0zbJKSuqNQniMfnX38vYotXrPdy+vxrlyFj9mubJ+ kwlcGtApKwe0WXb3tyUMQB1lWTnDATUyYA3FrKk3j35y6iT/rS7z3w5Pd69fZvdfHp99AUN2 6sDsIj/SlBJnPQJcLNkhgaTVc1ECvGnpUOiBCYaIVN0+KW7ERZ42py6yC3ew8SR26bbAwQfi 3CKNCASu9SkXmMth33nmdEbCYmyYWCCUb4/eTtUCYREUL+sOfi5uwtSHi8si8aHnhmXOnkpy B1A6gGTPlU2KXFr53fMzGDjo9QT+k2qB3d1DWHBnfZXADLR9RDJ3/Z5uuTrprMHQYG13GhgU vifdsW3db5UXNESiOWQJqsSXPcrTzbr1OsrISQOtMinfx3UgGJfs5M12vmxrNBCwatM+7mRz 3JIFd/L28BT4LFsu58fWGTHCXID7xDNCZcq2W8FOhHYl8LoqHp89DDIExwVydtReyVkCGe5C TR5sG/vVwh+e/vkBfOXvpLWvIAo+eMjic7JaRV6lEgoZ0w4Mjcs90jisLGAgAVQ/+hi4u9ZM uTeyw22Ipmy8ZZrHq2qLvR1KJDlV8eImXq3tEjlv4lXmrdosPKbVyduh4j8XBvHqmrKByGcg R5nxFTWW1jJ/AWCjWFuepI+v//eh/PaBwP712F9zIEpyNJyq99KyVEipXf57tPShjRHDEpY5 ZC2ihNi96KG222yPQWj35BQoYU+8rcVzJHmo+21KIc8VUqhC+NtNImHbeDsZEKW8N8BwF1jv 4HkhaQX/VwZE9KERjN+UMoj6ZB/E1CyRVpLkQDEwX60WLYKA/1l5nAcMlpVQMiQFBbzH8mSV OABm/6P+jWfiMJp9ffj6/eVvfM9LMrvaTzJgKsKGCH5Xn0rWdthGP35gp5Uml8LeUvoLQcJ5 TAtd6SvW5qgtsL0aHJT3Yg/Vn/fMA3TXTCbX4adSSGfOPpUEe7rXTh/x3O4OYCEJBu5S0lMc szO1E0yUmPzsRsFTaajsZ7QQoDOzpvcwIe4xW9k6UgtBMmDHZ9DIsD/oW4pBhEQS0cgjR+P6 aGzSbreb3dpvtjgMlz60KJ1OFnbow6Ia3rjkaxjC+GvDUDOsQlHpYIVKIXjJqRErR3FXj6/3 vlgl+C8hcXKxLPgiu8xjM51TuopXbZdWZqY9A2iLjSaC23FmhESd34JQiGnd93mXcDM20kmI 7yb7xI8QbIgYI9mwQ+48o0vQpm2tC54RvlvEfDnHFRZC8MxKDhlfILxqQKCWh9qqyw9HM/6G CR0eV0Hq3TgUMsmITuTIa8ve4yTk5AxfuUmV8t12HidoZAvGs3g3nxuXpoLEhjKwn9ZGYFYr BLE/RZuNHeVHY2TluzmuBjvlZL1Y4cbTKY/WWxyljQh0dOmAhrU6mRGpznyvFfLdgSe75dZq rDgUGzFj4oquFjrUEv6wgnM/VqSmxnEUIjHsU2/XUVoBI/7qRqBS8C5pYmOJjkDLlkiDVRBR fFEqijxp19vNCmm6JtgtSLtGit4t2naJi5+aQsid3XZ3qijHGF6y30TzfnONQyKhIXN2Ayv2 Mj/nSmDvD6Pm4cfd64yBSuGvrzKp7OuXuxfBso+m7k+ChZ99FgfU4zP8aaaF7+zJMc8rOICw 6weM6RKQUivLiRpu1NyM6TiAupxi0KY1wIYdTN8x9g1ErJwRwZG8PDzdvYk+vdqH7kgCj1qK Ae5xnLADAr6UFQIdCzpByLIQkkDwKqSaIP335yHnFn8TPRBC+BAO+BdS8vxX99Ua2jcU1y8t crLDFreZTGqGKxkEMjmc+2fRsgqE6BJkGdsjE6wyKabDeyEH0xst+3nbE5DgGG8tIoAFE4gB UlslYYres51JU/1WeqajEoCGojQuK49Hx/VbTQOldBYtdsvZL4fHl4er+O9XzLvjwGoKymRU 7axQgqvgVoqXHDRokOJDD3PQjQZ5S9Zr5Pmvt+CoSmWXuWfEz14xZsEOBwg+bavBFQasmSzz HAVWmRZurGdqhcmTpmatxgwPnU8QtNoy+bA/KgWH7phr2RjQK6FRfBwyTmpKi679PZrHy2ma 2983661b38fyFlerKTS9IINBL/sxXLeakZAsrT64obf7UllYDNX3MMGiVatVjL0r2CTb7dgO B7PDMM3NHq/wUxPNN3hYd4MmjtaTbUq1fWC93q6Q6rMbVb0L17I0BpZrj2IfNSRZL6M1jtku oy3aT7Uyp/qQ5dtFvEA/BtRiMfWxOFs2i9UOr5rgO3skqOooxowSBoqCXhs7xvCAAuNR4AXe qYMnOT8XOAc2DrxOmRjW14zlNeU1uSa3yDSIevDpbvK4a8ozOQkI2pcWlulUraQueUeJd+zA 5raO1lLmPeOBvG0SqyTWCQJl6wztnSDak3y122D+TwpPbpMq8ZsGCfBc3sghufC2bRMsnKXC 25tH9+m2SCoIaKcFP7fLA1qw7mjVwzkI7qHY3aoIpF+JxfQpiBQJEkJJgj+AmVSsaigevcWg EpLmNQksW4PsZi9+vEdUQYAn9DlcE6kV0V0TUuZLd43JhaAuD0OmHYHwYFWBxZatYzYpkpRv tkvMi8em2mw3m3AZArt7r4gmB/7YVBih6K5ZhCs6izOYtYRhGnWTcH+Oo3m0wKsit1vS5Mco mofwTcMrT5hBSHBBAiG03vB8/NJ9lkAonM2DkXA0w7VJmSa7+SoOlZPCVqzxtwWT7pTkFT/h nKVJR2kT6DZk7gLOt3+gw0haspjbAYVN9OH8kTUcM+YyqY5lmbIWr+AkRAE7fYiJZRkTSwh/ zTDp+Jrfbtb4S5HVknPxBy7XWJ2+aQ5xFG/eG9jMtiq3ce9PoDxNuut2Hnji8mnfX+mC24ii 7TzCB1vwG6uJ2cxzHkXYhWUR0ewAueZYtQyW412N2NQWtDWvKauAm00U3B+Cq/FMobAZgKwc zaqdr/E65N81vHNP4K8sdKTL8w/HXdNmu2lb+4XVIhBMY9SG+gcXEqi4S87QwGn2hEaLzTZw wsq/meDQF6GqGk7k7sfe1h26eD5vJ85HRbGcQq6mkMHLBkL1oRezuftZRs0IgTbO43gsdBPF qBmHTZQfTJMjC3eWOS0X4cuFt9v1KrhXmoqvV/MNJn+YZH/QZh3HgYn+41DWJDAxdXnK1UVs fq2ZY8Y9hnm7rfKtmOqycFhxhRZMRrQMy9v7PIlWc/8zumjnOofQBHNZEV7dBLxWVYPVcu+q a/1uYXkuRL5AWjLdlyoJxDuU6GMVJ35PpAS6F1cW7vI70jQsa0ZRFSslpZAbdaq/VwaBawUj 1aAWVLobTSbOYyBBpqth0nKxCeSpHt4deAWeYJIyWNFN23zcuetFAnU/ZQhLvxEyeYeQsvGL V9Hc0sR9snMoSB7NMe5WYWvanMdl4TbyjL54VeSwmq8XYjnlZwS3XW08Vl/OW11CSmbQQJWu S7okUuyd2kHBBkuiVWibAXa98Itw14e8SDpUKdPv1zZbLFu3Hxrsnow20mFkvflIgDMM1iz4 OrHBwIZF/LVParcJvCT6ROiSujafC/QQ1Jd4LQ6ik5JLUfR6NY3eGOih+XXOFKfvvZqe7l4+ /wcylrDfyhk8mVqq1trkVhAtuUMhf3ZsO1/GLlD831afKzBptjHZRHMXXiW19WqioYRV3Cs6 Y3sFNXQuAK+TK2beIHFa5YKUJkAQ08svLoE8Vhy7NxVevdPZDTmHOI1jklM3algP6wq+WuGm mwNJhrGsA5bm52h+E6GFH8RVF3nLgHy5e7m7h2gLnsK9aazNesGYUMh3sNt2VWO6UenMgyGg Ttker9b2SCeZTj1SpEkdSon9R5njG1XIOxw3T5QW24I3Cpy4w2uf6C+uLaYXJwm3ibpxcNri 7+Xx7sk39dHdlAlmiXl0a8Q2Xs1RoKipqqk04O6tjN2F2lNWBR5hwaQ5gOoQe9cyiQSIl6b3 p1WLnXDMRNE2wdgFq2iOl1rU3Vmali8xbC2WDcvpFAltG1qkNhdi4vOkuPXTzSCE0g9Auweg JaW0kfFobFsRlLTmAf2dOSMcY86sCq+hptRNvN1ifKpJlKmck/ioMOy52aIo26TX7hTfv30A oKCVq1zqxX1tpvpayOiLyEnSZGImmg3TnDE7YYmD6tfo+4WMSytyKGw5zwAGN8BH0wpIwzgh RVshTVWI9xvKSbRmfGNbc7u44Fu5R4g/zGkysYv2tE6TDBtbfUN+bJKj62CNEmqH6CAOJlru OG/HmkT75JzK7DRRtIrNXMUILTKWLjk7tOt2jQtEmgQMed7poOnuOsKC6wJwYpmpzrrLrK5i 7wMBG9flIvaaKA4FsW+nGwnKXCsNogEnTZ3BtWYzYAIA8T2KxnI3l5CAgFZVuD74dCFaaT+W rqOoeGMEyWhBj5Fmdhy4HOwbmJYPHYR0mpLNOljxihUyKZh2qUIxQ+BOqyppQxAskzsJBwDE GR5jXGL7dKhhCikQlgfM+vR01SnOx1YMIJXBjpWCuzCbNOKl8c9UoeDggRV8pNZAj4iLGVTD BMOEok20s1sXF9yErV7szDhqoE9kxLKbLIvb0SJUGbfO7sOMKeTqlpp2W9aBeA0QXWg5D+Ru HwmWmCjHSR2b0mN+VRk6B7T0qnEN3yuy3SzWP4I+05w4KspTZcargl/wfGPnn++BWDLRkSop jjLEu5/tsN/p5KgnyQQw7r5tKqj1aqcJA/odjRW3kdKi+TUAiglIQU0218QW50vZuMiCExuA FI8XS+q9Dbg0kB7VjoU+dKtZLP6oTDNIF+M8aLtY+wGUZtJ61hxAcdC4tpkDrmVZdovldITb 3Tdgsp8tVGbveDKrMqClpQC4EFgnWkzCHmUSCVmnLeseAczPbb8587+e3h6fnx5+iH0JrZVO M1iYX/VZaFf06Kwhy8V87TYRUBVJdqslGr7OoviBfSxGZuLDPGtJZbqFA0I7advpZwHBc+t6 lWs+g+TKgzcgDMTwnAIGkY5pZUVmohABD+dwtXqQZCxaLTCT2gG7XrgtEsDWBebpxvS9GmEd X263sYfZRmbkD7mFlXrNah7jqL5LofLGJa8Ya7FHC3kGyMd8pyEaKNq4M82o5FwwvlrtfOB6 Mfdgu3XrNkXccIGGCIw4KvoJhT3mC++yXJIzc9pf/359e/g6+xP8wLUv6C9fxSw//T17+Prn w+fPD59nv2mqD0JuAifRX935JmKBTe2UlEJYm/9n7Em220Z2/RWt3uk+7/YLZ1KLLCiSktgm JYakJDobHbWtJDrXsXxs59703z+gikMNKKUXnbYA1EgUClWFgRn1yoJbQVI+SgpJUygZpQ01 iV4+Cm4R37d1LHrQIkG2cqxWAZXZXvm08k7IpBgz2tJ4JonH0dCqFRJ1sSGEF+eAspVMpADW YZClUZZlP0G7eIYDLKA+8AV6ejy9vFPZjFl7qiOQADwW/eOq1MM2RjutvX4/tH3/xgVo367A P3KbvaWXltuqV0ZiMegiG3Uh6SwjqDep1zkDLeHV+2GCBCXeL0johM6Kgw36iZmM8xEne/Cj 9lGe3vpYsIPU1AxKsSA/HwoThLAuZ//niYNlHIjvRSwH7mHgXYsng4K+CUSKJE4zOtk6H9uw TuTmMKF3os/EgUWlMLalygQJWZShdSwKw2UfEGwxA/OGzNGK3npd7IiphyeY7uMHx7A7dMGU oU1iRyB6LUcGt9sKtPPlEg/Y6oA7dEc1dGhcnFKJz/ebT2V1XH1SNNGRPwYXs55RFLaA/xST atbFIgucjjwDYBl5DY0gpmZT8OYemBb9vDZtvRUXaVVKn3zdUMKqkuN+wU99hXA1ompmD08X 7peiZZeHYjDt6L11pyRLElBFyl/BpdZ6XC/J6B4ORL0AH/vzFQMDnd6vr7rS01bQ2+vDvyn1 EJPS2X4Uca8zbaTZM0tNXa3v0a0CzeaNSerer1DsPAN5CsL7kQUZAYnOGn77P3OTyJzUSPMN 3pkIc5dvuPYrEMBfE2AIY6MhuFCkKmS3MvxwPvWuB2NgR7ex6EeggajpbJ+8OB0I9C16wMB5 sa7v93l20HHsRkEHL+AIJZ3TxrrizWa7KeK7jMBlaVzD7n2no0B87rOarHGVlfkmp2ssskPe LHb1ipq2Zrep8yZjXnLU+xhwrRT7iwd9SMRDXE+DF/q9qBPOcvgpDQoaqwqTqzdK9T1nKFBm IW9N5ynuE/799PICmiJrQtMDeGfLVHTr5DYVBx5CenrKEtol9SeRLhcjCTBIcb/p2BRqdZaL KGhIux2OhhUl5uBiwH0X+f4oK0AA/NGPEh+cb4x0GdpR1GldyNsoJFcF/wAG6/QBqUZTHRV4 1pHzzxcQMspJrA8MwrxMzHXz70ltJRPa0UfTww2uxvxFGY+3YpQCEaq+TPU4tOOgDUi5mU6V J05kW9pMlMtUnwltHkS3XQ6t88/bTaxAF+ncD+3ysNc6mNSwU7LXFfIQwmmYO7LK6YMRsQb0 tUaYkdncpq8ARQraSohRcFsTUxcRKxt+DeD53NO3bTii/IrL+NHb1N6ijTqVD0qQ11t1ASsa Vw/Lj3kKf9iUxT238UkT17FHmYRa1U1mYC93c1vrElsKtgpNXDeKVM6p8mbb1Aqwq2PbE73F xShuBxsVrKGP9h//vfSXLZPeNw4caPvw5+jvtKU+5ESSNo4XScYbIs4+0AfQiUbdF8T+NU+n /4g311CqVyVhHy6lwfWqJL/vV8HYR9GmVEZESudFFIvotlAy19LENuXaJVcXGFty3F82EFnU lZZUi2sbGyAdz2QK4zyEhpdAiYYMYyRTGHsXZRZ1xSWT2JLdL3sXOsZ72mGNY+uMzvHGsRjw txAut0WoGgOqSmOOF3iI29Mhb4h7dw8eiKfhMqHH4dSTAIaP1AotYjxO35vnVyKwjUUp46uB oFmIYZfXmLymloFlvIknoNbC4pMTdh0lJMY+KNuPALdFg50Bjo4JoeWZMURdDOOIQnUYy2C6 qWOgTDS3CERRRaET6nD18WqkbxM38GnPDKEx2/NDylFEIAnDYE50CObYs31icAwxt2iE4xNj QETo+tQwAOXDhNzoYVMuXC+kynLbdLLw8IlW8W6V4Vw5c8/Wv+BgSKZj6ta3qO9Xt3PPF8T6 +iAlHGE/j/tcOilyYH9xp4TF4uY5p3dQqynbsz5qyiJvd6tdLZgBayjJiWLEpqFr0+EbBRLv n5BQUR4ngtK2HJvoHUP4JkRA9xlRlCm1ROHSzc0djwhIE6dt2Nl0RBpAuTZ5sSRQeLahVs8m +wGIwDEgQlNVoU92sEnCgHSyHijuojYrK6rsnW0h6kbZZVza/lrfBqaAPVWRNSXl1zV1cGFb 1JiaKlPN+npM21W3BpQ2ARVvCGMAUVyWZkUBYqKkmuqN3eP01gjGY4kCz/07UPQXVL145LV8 ykREpIic5You7buhT+sRA83gTHK760s4KZfkJC9b0HV3bdySoacGqlXh25FsHDciHKsh53QF ypnJPHKkoI2vOXqdrwPbJb5wvijjjOgMwKusoz6QT3Eevo70S0It0EahDv0z8RxqoLAqatsh g1pMoYI2WbzK9Dr5nkMwFUPMiV7jy7rtE/yNCMemq/Ich+w6Q3mGXHciDRkeQ6YgusT8OCnR h4jACojOMow9pzrLUMGtHQYp5sSXY+fa0CFELQa54tKCai4I3Pnt1Yc03i0mZhRU9DOGMHeW +vRlUrkW3dk2CXzqoDLtHIlqgNp/uzKgD3gTAZlCSkC7BMuV9C4FcErNFNARVVlErYMyIhuO DA0bLhkngrnJqHQkuPWdAU12Z+47rmdAeNQqZghiYXBzNFI5QZRHOnoPFJs24TcTeaOErx8p khbWFnUUFynCkOgZIOAMSCwuRMwtj+7yMvLn9LmkKpUXZ610s25t6spBwFMaAIDdnyQ4oahH kxRdXSjhzO/emvAM9mXpxktAOLZFquGACg6OdUvlacom8cKS6m2PmZNynmMX7vxWn0FH8IOu 09IjSniHkFgM4ZJqetO2TejfHlIZBLRKmya2E6XRLw4VjW1Rux4LRuIQ4oQhQkofh/mPKL7J N7FjzWl4R+kbm9h1qIraJCRXQ7suE4OT70hSVnDeuTERjIDkK4a5NYdA4FlUdwFObzf7PMb8 Hr84NQBVEAWxXvG+tZXkYhMmclxaLAwkhwgUXpv2a5ko5naqt8sQjglBTh7D3JI1QFCEkd82 htKADDakVcxEA6tqvSR7BZiMRA3BFwg40zZumLuN/I4Gp+YjXXtn2eSJl20kUqgVDkC7sHqV bdAZsLeNx0NXfH8sm4+C48dAzi48zPWzyPUYuOjY1rlsSjFQDGFvV9s9SJqsQldzQ2AUosQy zmvuDnajE2IBlvOnqbh3wc2q+ztgnpplS16r9qXkjuhzKg2NRqO507G3eSLQUq8JvNJX4TKL 2VNMX1t4Nt8v6+zTgLoxuqzEHN65HNqNRzdlzSZFTEqQPvb4NjmmLcjTbbNUDSQlgqmPE9sD hetZHRqQvH6nXDZ7Ap2d2boYRiBlquNFAr1IP6RkraMGRxIdoqZhHMCb7SG+3+6kx/oRyR1t jiyzT7bB5UE71I4FmAWDdpd4OL0/fHu8fjXGcsQkp0TfJTBLsJaX2VaMStBfpehF+1gBNCJw RcTEaYhySGecYZxp3GKsGmEe+TsHVV3/1HGjOm6rRhb+nOc1Pvnc9AzqjQhvNZEeyOrxPOh2 3a2SLDyEPn9xwlNk8lkYK4zTfQxsCTwJCLKzcZGXaI+uEgjoEJQrtWJ2qRVlhlJN5duWBaqO YA/MPJPkr4QZbpZ5WyUOORvZrt5SfR/W2yKENqQK8VJIzqd9iJeYgJSuIHAtK2sWSh0Z6r/K cHMYiqmWFhRJZ6mXiEJDiXVFfMB1BcTHzeAsJzm3NaADq0PtbYQlGDsD2q4M3Oz77zB2LbD4 AGkNa5GAxmGZPuwiCR1PaRaUQF8dPh42BtMcc1tA5IaLUJ+pkQSVTLorg8qktgzwKAyXxhoB Pyfw4wpM1p91Ls0qOBK5xGebonTLk57PLbdTYUlo2ZEMLDEKoTMsr8Gk5I+/Tm/nx0lAYzht yQYCQ2YkNyViW00Bwsd6qtfz++X7+frjfba6gqx/vorinhDpqBwQu5NAIGo8m+22+khtWAb6 Cl05qd7THRnq/wUVq1X4fBgVc9s0+aKYInVfny8Pb7Pm8nR5uD7PFqeHf788ncSA742YXpRV keTrLXsFH6ua+HjCU2uGYdHt8RcVDCSGOjCr9M0aBgJT+bzIZOs/hPbRzw32j4ukjMX2BLD8 68h7luQG6hEvtj8hQIkztd53kCo69B0W7TEpqWOERKY8j3McaYzNHOG+/Hh+YKkKjem8lqmi vjGIYuKGsLhxQ/EKvCrzRLC6m/Z/pI1bJwotzW9DIGHxeC3x1oFBKcs8VmNXOZYWXUDsshpx WADKrpIiQnH+YGNCXc0ljZcHrBwtFOvrlUXaGVUg0DqivsUNMPE5dYS5Gkwy7kAYPqN1SsK9 CXyjgwOF4sy5btGDqMkT6kYVkUDPPRWl9viW8mkX13ejWxVRQVElspUvAhoRMJ2PcPb109eA OSbr9kBHntAJU/Q7McwDp+5jkZDwwSybGDBDKx5fEtmf8eYzLHPQjWi3GaS5y8qqoK6FEMkD AiofnQN9tU8MHJB2+OyL9+YyCgNNFjIyByE88ig26NHRXI4bOYId+l1uxM/pF40JT6bcRGwb uHO9zWyzdOxFSXND9pn55ZKpuZYpO5rIEyIYNwmqSx+rTnmt1gkMjM+aGo1ape7XbdMZvAY5 urfUkQslfuuTrx6IbbJEi9zM4LkXBt0tKd2UvuxeOwJvjay5u4+AtTQpiboydT5bdL6lJ8qJ FxiX52bv7ptEvpJBaIvZVl3X7zCYqekDIWFRuXOPfjTk6CiMTKzXonvbTm26igs4vNEXd1UT 2JZvCJ7MTLsMFuFUTFJ5wIwgoqynJ/Rc26QRHnmGnBLDGGEO3F+0HAUmCTMYussLajBup6H6 FjliGl3sAg6koeGivT0UnuXqHCQSBJZ3k8UOhe2ELqEiFaXr6+twiltknrPSuG4GhxRR71Ed GASgljtAQJk3+qTxwkIMLMGGWfq2pa1XhBqYkqNvym6GNq0fQHrqNqYHYp6gNzS/nkAKeDHA VfWovzjTeIx7RohN19kKr3zJO+9kkqcDNQFQQqbUyRBiljJQYliWPUgpM8WMpe5t6mO2kWO8 1se8NEXirUHLy5SMEkI5jFYmRtEGGA/DpzTQx0UxtVFnGCeLlqv4PtDWWVx+JndgQB/yzWKL GVDzWh3XaltXxW5lTImBJLt4Q9tqAbZtoSiZJgHmuYBzOVqaS8PXk2WOQAzauGnKvG3p0MNA J85lmaV5zEzfuYP+dET7fn68nGYP11ciNRQvlcQlS8I2Fp7WB8PDkIstSLP9QEItFEaZ5qsc 3ZsmUrWHdYyeOMammrT+ZSO4OowVILImVzJHb5mHciE/5am4Y7qneHifpxnGcRZuezho7xWw e+wWGHEsFsXEhFZhcbpXPRQ4Ypl3GFo5x4S1wAErecFyGrxCaO4yTEpDHeg5UbvbSFHJsI9l VjrwnzIGxPD81hjVOYG/GqVXi90SvSoJaFrCR1MHgYh9yV7KdIyjSLIJDj3bVkTTDmsFP09O tOTcasrUPQc/8QSGH5p6iLAN6XzStiwn5RBPQqDHzHJxGlewZpuPdiBXhpk+8IDIvi2txDGy DCP0YJJino8OTnzFlrh+Yctav29hrMwYRJEFXAycXt5/UJKg55kDaFueypLtIYh0Jvy8BfY0 dKtv5sPp+fR0/frh299/vV4eZ+3e1G7S2UQLSef4EWmqPeDF7GcT7LgoQNCCJE6pOgF/a3kz grLKVnrZRRt5lL7BsU0ch7br6cV6BC2WZBKJKQUU+ybiZ798vbyfnnBG8SQX86AtAhsgI8X7 ELSro7hLTGCV03vibUNdDCDBYpeuslZZuxOCgh3FKBoCON6rrfeICm+rTe07CUqprEu2lRyf g8KqshVpYG9vt44MS0sYta/Qtbbav6olj77xRg8lx8XARokmh9D1tqLTCDBJs8o2Si1puqjz dGWAHssm5+/aMh5UBhg/Jcl2FQarVnh/4lWvGB3mb+ahRMJxH9HpBCrmEdeTaHtiXqoCG/7l nj46ELd1GoESF3az5mPgaQ04pfYdbwxQ0L1VsmHx9Vm6z4+zskw+4FPCEC9JNAgoG/bKgEHp BX2d6T3j3qDA2yz2Q186mvSKUg4HaOr4O6HFjFtjx1UEjwclw3gVMIE5+0tvnPUqoKyl+9ZB NIVWsKZKLoOI9FngeH7q/WhMOoz46OdsWfYb3Oy3pp2x9z4pdNhUGRn8eVDr0EpTiBnOani4 fv+Ozxa8+usLPmK86duS43qi9Vi/H+6pvV8UQTeEE6n0MSHvBQbwcS8wEmOvPN7Al0tbOa7P iLmx0zBlr63GRKV8Pzk9P1yenk6vf08x3N5/PMP//wU1PL9d8Y+L8wC/Xi7/mn15vT6/n58f 335X9Q7Uges9CyHYgHqatOqI8AzFzsbc/ujH4+U6ezw/XB9ZW2N+4zcW8ub75ae0svqP0viu aPfNoXDA5jbXrOI6bcZq1fIwqQFPm8pTJF8ez1eRWIBiJ05SH2X8+VmGJqfv59dTP2VC1FaG XD6d3r6pQF7P5TuM/D88kTPGxxvRbII+cCLg2JdXmB18bRuItIGFvrOexFVaz9hnlCstL28P 5yd8yr1iRMbz04tK0fBvPvuBD+zQ3Nv14fjAx/aoZJPm3105awhAjEJXiXuUiGvTOHJEBw4N GXZGpA1Y24idR6JnkoRkUs1UkiENJcvWkR8UZZztGirtEscSDaxlXJ+ijcR5RlzZFVDQbwzY xPOaSDSr1ydPuiAVy0ZR3QTQsHZ2Hz6oYzOv5OmK4e0dVgpmM//t7fQOrHV5P/8+SQlZK23a hRXN57KEBGAgOT1y4N6aWz8JoK1TBqDH6aSB5FTFVDOYN/EbMlgUpY3LjcKpQT2wWFz/O4N9 HhbgO4b8Nw4vrbs7ufaBVRMnTYcGAP5H809mC3YgzxZTebH+tq6t6LGfC5g+N6CA6lT7a9tz iKl2xMPU8FEs6qM46ufDpWpFrj5uy4oCnVRygUPgPmvsbq6WZ9yWt6mtdYKj2NzYeqtQf6fS xzp78eIBAdRmBzhe5Zm2gTWt0AETaV3FuFExa2X88C1srv+Ak5oKRJhSWxF4PEiENs+eytOt 6xM84vrkV/K0T78HbgrVuUmdyLOzWp8d+X6AnScb2wKlh36mQIJVFVXNnUIxzlHSrzrj7CDL ROoH4INxyAlSFxFn5FGOxW0DbW5Au/82i2Gnuzycnj/cXV/Pp2fQT8ev9SFhsgA0L2PPNl2L 2RMVFTApXV8VW8UqbV1XJe2hyqGULVuLWstMwvFoXk16m7smKln4/M8/LJr21w4CFagHT39z LePtQ1UU8lwAYFRGsmQI/DwoQbMvoCUxUSiXKjaLtaOMH2CV+mHzBtaDOlEMSFKqHAB8EQT+ z/EUcr0+vWE0Rejd+en6Mns+/1eaAvmWbleW9xT3rl5PL9/QcE676opXwrkAfqDdsAJoVYDs i96DyCMZ4pT4hQjagG6Yx2olTU4dfRkGg0w2ch17vYJsucyTzJCJDi1VVq2o+6/iYyxGp+8B 7PS+qnbsrlRANYe8xTiNW8E0OhWjRcEPTEmbg8jNZWgKM7Tr9CjuDMdChpQlDT3CiWWJVxYy +g5OVTwyug5fLkjUkj0EiC4dGnK7z2p+aW2LqV6QoNjG6RH0rfS4zOsSA+lSV0aYKLVVRrLC EKxoLWjorgm3Lz8KAb37Q80M1qZyNhCK8Ej5oSWm2x3gTV7Y4iXyAMckQKiZz6NORsIxPlOn icOYT07VSo81iIVFAGyjrb04qWa/8UNlcq2Gw+TvGDr5y+Xrj9cTnvLHs1WZzorLX6946n29 /ni/PJ+lVQ4s1JCXkdD+ZrvbZ7FgyNMD+tO9T4IHs96PLo0uxbyUQissQFUhpy5mczoX3TkH CEiVak0+5o0USVy1uzo7ZnW9pdPdjKT9/Gsz/fj6/cMFCGbp+a8fX79enr9KAnIoftCaUCnU e9oB3hxAuKKDCJ+b7eLPLJFdB3VSngokjUlnkpGaXOUMVWwPxyLbZwVPmMcCgTYEHe/SflHE m7tjto/FZDJsPa2yUl1hh9WyU3vPoSARElKQsiVdxlJIjh4WyPnEeqgbGNK+IH6XUv5nbDE1 GpuUq3jlkDE9EZvkdb1rjp8ylWE/dYUMWGyTtTKDfXYkWL4yvIp5ePde0Xh7eTr9PatOz+cn RfQwQpAPTbXASL4s3vaYAFlpXr0/H4uPGKm5HPb61y+nh/Ns8Xp5/HpWWubv4HkHf3Rh1Gnf c503OfyzIMP7MImdb+6lfawH9HvZIqcwcDBzP7U6ps6quJLfsQdU04b+/zf2ZM2N20j/FVee slVfdi3JsuWHPIAkKCLiZYKUpXlhOR5lxjWZ8ZSP2sy//7oBHjgamq1K4qi7iRuNRqMP21zL PmFUIspAGzEC8JSTSSuuXh6+ni7+fP/rLww976YiSq14PuORpQ4wogY4MeMiya1g9AArq1ak RwuUJLH1WznygdTPfMsCLBT+TUWeN5bOcUDEVX2ENjEPIQq25VEubK8tjWvglK7Fgefopt5H R9I+BujkUdI1I4KsGRGhmuumQmVej69h8LMrC1bXHM2uOJW4A3tdNVxsy56XIOeVzpC12Qw3 q4ngj0aQiwQooGltzgkip+fWgz1OG09hV0KLzTQXSk6Ku8gZBxD1dExqs+KCofkyGWQJG+4f hfgNes1pycZuTStyNcqtdhXzl/PnMWmN95COy0DxOavAuli6v2H206rHsPJVWXrL7whManlp s2sTjuuc7qrOvWd+xECygtmgTBLUYpatu5xghBc0H8DFhbuJLgsx9ga1ArPhfG5tgqrGBNk6 kYkxxYtkdBcwyhqvJC7ItTecEaGEGTMFvTAasWdOiQgKJpEc8V59HsVUX2Aybsy4eQjYLNw1 gCC4J9G59XAL8s3l+oaOvK02SiCwLzZxlKitdmuR+lzfNQXZN4LuzKyw9rgwVd4TKDBRzM60 rCF9HBhdxG0PbgFW0WZRknq8Rzjb61hjFrECBsxBZzyLY/OqjQgh3d/9ytv4CrqgHRZw4wna uhAXOq/g0BCBZu2Ojc1wV4ktcA4g3fBQHYoi2PV9VSVVZfOBfbu5NhUryHRBtnKc6BQ7o7It KxZqfx6zphClOy0DFEQUVqDMTQmzFk3cydZ8ooUyxryPZrna4zqnTdAn/Dawz0asPSajU4Ox 1SMQ0A/t1dpbD2PI1MCIg7Dc2QaiuPM57PyyKgISCaqclw7PHWDKNGabuFx2xAZnPmoqlsiM c2fXdlW/W9xeHkjoJQl1hsp5HVSjd2O+bkybus/jxJf9EKgsFgfzZrNniMuv0svL5dWyvaSY gKIoJEjY29RUJCp4u1+tL+/2NhRO4Nvl8uADV7aXIoLbpFpeUdknELnfbpdXqyW7sosyMpgZ UHnNr1fFpdPA5FZHWLYqZYVcXd+m20vKXWPoLyzPXWq+DiI8O2xWZrTheeCd8fXwc56PqSXG rCk/BqItM4kfXHrEqHCpFKIuNrdXi/4+tyOizgSSZayheelMFExyYLTAd0C1kJsNGfHRobkJ FDC6cZ0tAUbwenVLF1C19DXdGIjZV8pvm+Nya0yplabOaMseBuMmrylclFwvLskFBKLsIS5N 8+EtkxhKdYZkiZ0pCi7agcRfVVdaN0sl1Gdw2/QU7pkTN1okc8j0tuHltqXYLpA1zEgO1BHF DCvea4b8fnrERxFsjnejwA/ZFQbrMLqNsLgxEyxNoD5NHai9GxRIdtJtHOvgskgf8WoIeL4T 9L0P0To/0hm0gF+U8kBhlaGA26D4WMPFgLYmRDyM97ZS6YsCxXLUtTuDgeZFVt5ohH3Y8aMN 2vJiMAQ2gamdIhJh8KXSIwVbuTuGmnfP8tYO6qAqOTZK/R/4SMSW3lCBWgfQ3osysy/vuqml hAstbfyPBHnsZDpQQJ64gLLaV27hqOHCNRooWomgRdVJp6kFOyoXAre4QqArfJWSMV4QX2Ei cnfWii5vhZoOt7yypZ2fEQeCAaezfCC2hpszrO28aijFlKLgLcMMUHZbaljwcD6SQEf7ZWLO XRBNOl00WQTMGKUGMUksfyqFyBl6sZQilg6iEQVzuiaZcLyvNLSQXUlffxUe45Bj9vFA22TL eY5OTNxpApRa5z6/AqE9UNIWVbpMmsqCCeQxBFmwpv2jOg5VjMeFAdWfWHW3Yk85SypUVUvu 7pk2g43n8Y42a+C2obPhBErr8FDpa7lyv70XIuB8h9iDKIvKbsIH3lR2H0cI0b8PxwTOkoAv nRo1FcWwzzrKI0KdJnk9GRSqNM/USavSR5u2252M+iqDy4alR7TxniyPQBAVsj5jss/sfUF7 FXY6qMzYPiTChhln7wSvP/94fXqEszl/+EEnnlaFZfTRV1a1wh9iLvYkBWJ11rdQUN6WZfvK 7Yj9PUM3CPrjY81pvQ1+iH5bcO2m9ywSdLlK7Uo3rLunxrYoLIlembR3jPbLK+J+eFPT9nPK Ol4byGeY8ZvMXTu73xVxUJeEOJlkpr/HBLLdQBAMMlmVDS33qO1sh0YpeZsWNuI+kokNaUVa 9C7Qz3eiSnXcyFVFumUxxc+RII5ubP0gAvfKIbIIBJpAig56IK6bKqfuAKrZlcxExPyRKtqd 30gcjQNIBZRcUYAQ1orY/mqAhSIEqdSO8u3p8Qu136avu1KylGOup67wDWrMUsKLyS1TzVdh mccOmD+USFL2KzvF4oRv1mT88pLfqwPZuDTDL9dbcob1ozhkYqIGJYIShOE+u0cLg3LLJ6NQ jFBJDJP6kNnWDhYK7vtXa+bUpK7dlxTQOoFGMB2bX2ExCMrS/6jk7dWGzBml0PcNq53adeLG JQ11bpwKRYBUSI0rvwcAXgd7kMMVngjXPeFMa7EZuCKA127r83rjBDAZwbReYFgffI+ON2Z6 2nksbDcgEx7Ohj1RXQeCaeg5GQIZwM2bzFQ+EdmpHRVY62hCH4GQsVheycvN2l3wyXJjx31Q 4CFkkryitRd6DNvV+tZfd4NCJrhadZoXpxltzDDEiQvN4/Xt4uCPN+6T9T+hKpTOxd+0yprx z7+fvn35dfEvJXI02+hiCDv7jlkkKfXAxa+zWGm40+jBQyG78FqHNjnhScYIipvIT/WKDWlf nj59svilHgfgSlvr6dQE904ybQtXAS/LqtZr44gvWuqyZZFkHISKiLM2UAX5qmNRxGHmOJKw GCR90R4DdRCcZkSNsRjnzJtP39/QCPj14k0P5zy/5entr6e/39BkTlmcXfyKo/728PLp9OZO 7jS6GOZB6PcSsnMqOEMAWQ9hHGfbzDjmGFpQgNxNKWkE/LcEgaA0JJkZpkNgF+wMUldgVmlQ 8ENtUp2tf6iLF4Gy1Ptigf9Xs60gA8Mb1CxJhqEkmz6je41MabqizWIWaJDCBeVUg7DkdOEA n8zdpgoajFDQHKj7Hweu2rO2wpgBMm46w35Wobz7E0LNshWVNvbxo1ubNI4Rnq64SG5MPwoF 5DfWY/4AWy9dmNgsNzfr2ofe3qw9WttpYoAtfRhfLXzoYbVx6dZX/rfQnmsX2GyW1z7lmmjN euHDblYmrGnj3sqvjgBMbXK9WWx6x8oFcUpGpC20YP/pSD0eDwdU1KW+t6o8lhgk2lQOy3sF tXhDd0iErHNGX3GVYRx1x7ZdgzvMUC2oTG2IqdH9c8tLnZzbQCToLj4hrNIYp14dEQMcIq7k yi5JPWH6L06IApmUEkjVV01nyukIKtLrpROuoZn81YlitOXi75Pf6MsbOoa6N5DBvtG6cM2w YTt6qAiNwavSg4uyNmPGD9CiMI8rAzga1xmxngaXz8eX59fnv94ush/fTy+/7S8+vZ/gKjUr cmal0LHmDa3i0CiMegcsmfbsAdkywKwPm2vDr35q3nRuYQTyQtiQLDF0fCyHU1LZFtp0sgOB jdWt5XWtUxhGopIk0C5CIcgifLJ7FXwc2LGonQRRE5oFhPSJIJSKYGhgtdnQpreIbqLWtuvp /hCt7Ibm01YMA4nKEULGry9EXvVNuhO5mawkXmB4RGsIsnoyfJlXBabcaHgefOGpsQxahSEF 0fCZHzGJimxvauAiVzNjxoy3wfJ4biREwlnNknMksmtSWHqrYJtRVN9hISp5ht/sKSljwmpH TtJR0Mu8uidLViuZGsppR9TCng5cTFFRGZtEV4LwNuvKhDdRlZt+vHIsYWb7nN2FO1vVsKOb 8CSN+qWo9dfPgMqYaSI6Qp29Dj2Li5qIvwv/hQN52e8D4UA1lXr821tCtEbsne0yFFrTsqnK TVL4sUzRfKdp6SfV4bUkPETFobB7q+up2A4EUmFtpbGsOzKdkHr+7bdFd/B71JARzYdrNj6B xK5xar33Lg/zAIia1jkOuwPNlFd91LWhKH0jHUVkV9aVosXqjDWaH3oM+WyawswFg5ADey8h n4yw5UwbfU0fjCraoPJ7IqhFTUnhcdZUBZ8aY2VaR0wlCUY0oWpMI0gflWOI8MFVjap6oMjN 4TGAwEwIBMxNa6c4R8QuUu+JZ58l43yHvmkgiOw6g91mmMwFcJhDoGZmrKMhtArgRkEj1mFV 4r+fH79oS+v/Pr98sdyqpm8I8xuKSor1ikyMZ9DEScxvTF80EyeVnXVsT5BR/rKo5SKQ+X0m Kw/0gWGQ1Afa4MgkEfFqSR+T97IWJWaS8sR+PZry+f2FirAPxcpGXXFM326A8n3rQtXPHiux KCPYbSPlfBy1BW5QEUhLkmm9ELDtnxAUbUf3eKJoi44k4MVAIAOP/qhCjSp6BQkY9I6KJakD xJy+Pr+dMN6MP6A6GipsoylOTfP96+snSjff1IUcBXDfGKiKL36VP17fTl8vKtgTn5++/+vi FVWAfz09Gk8X2hvx69/PnwAsn2P39TJ6eX74+Pj8lcI9/bs4UPC794e/McSRgzMYdHkQvWxY QU9NFYhgXxdjUrNxbIafVK6UMf2ZSs2mDD37qtRKHVtwnsnggoFclpUx6fVqUqKFiwTWZAro Mxq1S04uN+truH2LPXc74b0nzf115Qt+wDN1LID/84ZJUkJJwjSxo2YcgJOcs7q6vfawfhD9 GbFamdGcZ/gYX99GNO3m9mZlabcGjCzW60t6jw4U4+M2pUCaKGIjR4b5rFYFzMkEWV7ZGloU +AFCe2sDtHd4a9eDCOCf27oKWK4gQVtVlIZDfQsLz65GqQtdH9o9iAIhSaK+LzweIJo75T5N RANAn02MBsoOfdn8vjAY74DZr3q4t9FDByt75zZkYl9SxWmkAt1qHGuzGzpd94A/yMUlzVU1 QcSbPGBCqAlEcaDjdms02iiJu3MEdbxwHhcdioLLgOyp8bWAi0ucBa7imkbzpHMEyCXP4Fsx pAg4Q/PhWJ7racu3DVyfajK7Y2oaMsCPPmU7rsMazLd7fOVvxF6QLhGIxfSgfA5Xa31JCJ9q 3aIdjHz/81WdXvOiHfRuaCYzNyyKi36HMeGBBywH1LwpsiPKRf1yUxZ9JgWl6rNosBCrAJX+ ktHCVxFHftNPL389v3x9+AaMGGTRp7fnF3/3Ncy8k1pXZX0cf/v48vz00Twy4dRqKhHQ3DBK 71juC9MRXLb2Dx1DxAbJqmvQk70qZeUkr5qx04tZQAU3EabKjz14+Wq9PDhtZisuJ+i2tSwx J7gkTagnNFxnqSpaqgrnESKtLQ9D+NUXW0y/2mKs8nhvifMuupZuggKfdMhgGaIbS2qA2XoJ HLQjqRT+wkqlpV2Bn722CwydnwZFZj7xIFxaFs4gi1R1Pa7Q9Onlq/Jc9YWNxBKv4GdfpQEv w9FdGxZqQUbMH5SOViaSJE4iRh09cC03jQDhp353ckAxK1UOQVRUlyA78FQAZ8tzJzy+jGEI RJS2mCXAKDa97+N065ZsQg0fc+OeX21BAKViqsxDlaJyF6VDXKWscR7adZig06eXh4u/xtGf 4iEOk/L36UIzTVMOjqGzvL+vmmR+P52mGZPBYUyB2NCd8QMKHmb3RkgfqWTDttu1gI4h2EqI iWI25pc4BvBQFi/j5ljbMWpS6TrjJy5AaICSsY0P2UQ3r68BNnQbpaxCgOQN7I1YPndd1Vry qQLgqw4aQihOodRK1BHSAHagh+ktdU+dgkJvt3dp0fZ7y4pHgyh7F1VU3Fp6O4x3msqrnnxh TWGYenMqY208P32NsYAw+TeRfTh+ePxsBVuQaimZs6XXFtr0SB+cgRRUgYBR+CjvJXpE6FAr fS6kf22uX0/vH59h9f998lY5Xph1P+ezG0G7QPYbhUTxqTUWvgLi6xI6Bggry7ZCAdPIk8aM 87HjTWmOrsMW2qK226QA856j1d6K5sDalja0ybotrMkoDTx4aGzvPpKN06/+QPl2u2Bf6Ddc 6EDLC7po2AoYnytEN1LlxgDAjynw0C9Pr8+bzfr2t8UvJhqTxqgxv1pZyc4s3M3qhq7KILlZ Bz/frOnQNA4RaXlpk5yr46dN1FYAgc+vKS2jQ7K0R9bArIKYqzNVrn9e5XWw4Ntgwbcryv3T JlmHh+I2oKS0ia7oS6TdyBsqWB2SCFnhWuw3wVYslmvqHcSlWdjjw2QshA0aq1rQ4CUNXrkN GxE/69GaLu+aBt/Q4NtAF1YB+FUA7jRmV4lN3xCwzu0tJoyFG2MgRMxIEfO8JS91MwEc211T UcXHTcXaUBCaiejYiDwX9IPUSLRl/KckDQ94h40UAjrDSspgcaIoOztkjzVQP+tJ2zU72tUf Kbo2NaOw5oX1Yzqv1Tm8O718O/198fnh8YsOvTYeXHjf60Vzl+ZsK90UMN9fnr69fVFRzT9+ Pb1+8g2JlBi1U1p38y1FXUbRM1BHRxuPk5tJ1ATZDjejR3E16QgwetNQOlwpmCleDmlxrA7G z1+/g5DxG6avugAZ6PGLDgn/qOFExH4dlE2UqRkzcoJh0rAu5o7eecLKOg+8cxhECQiW6RVJ tU2iXtuE0Oe2TtShJFMosW54zNqAEchAWnSy1QHtKJESJDpd2u+Ly+U0yLKFFgD/g/v/sbDz vHGWqGIBSZTXlSCSYrrLIqpyW4LDaa3uSzpviRobU9rKoB7eSN1wdx7GlEYg6RSY6MXSbjg4 PVRVmVNGrLr7Kjwfb/wZTSvUfdxztsP7RsA6WPmxorBoGqoZwMnud8ixcvmPoaE16XS2tuDo oHg6x7XTvixW0ERzoPmhRddeKxamKgWxY44rp7cTalw5Q8MpiRvrgGFDqxrzJmjD4UreS2Bm dkQehwZdDoN9VrQNT91eNBVcSFnvRF904jtSYDNoo9P9kSIF7n5mA49k6j0xYHdpEaKY/T+Q NXGnFv3/QAprEZYicNOupN1EbXJ7Nn9fOHspZ5E/GAjtc1j4ROnqFX9YkwUvkMovYMQEW4dK 9R1c/JkVVlHHwyz88vYY5JKpe+WZEQKqhnaKnPD1Vp1olFXM6DA60E4Rc+wi/EA6Q9BV9T4F DF5QO0bTZGKbWZpcYyzVgOANPs2re4/jOUh3ujJ8HnLv2Io5XOTPj1/ev+tDL3v49sn02aji XYeJZFpYKOYNGd3sg0hU9DtI59GLoDCU/HCA1wwDKxlk9WBB9FOafs/yjs+LeKY02hwszaVx S9OthXt3iU620jp4NBOfUIoBVB3sp6URdtlo+ESoaiKWRJB2aNXlSHh/B4cYHGVJtbUZKdJi QqKKtEKz8G6ZGjn2weiBhB2WnAlbp/EoxoTRSodEtEh/q3c+L5PpcHdWM7Zqx3ntmP9q5yM0 YJlOvYtfX78/fUOjltf/u/j6/nb65wT/c3p7/Pe///0vV6JrWpCFWn7g3uEw2su48JncaeH9 vcYBn6zuUccb3PFKx+oklcTQnIQaFQEg0pm1qa9xNInyB3L1VC7R1JOZkTQmbIUvk2PCKm/l UYX0aZfnapLc8ZhbaIFHz5Kc+7ihl5jMdDp7pddFYBAqjjRiia7Ow+2FXLbvKQYHw/YrpFmZ kgVhNtBRmPMEFqMOUHvmyNjpYzQ4wfDvHl/8pHeMod7TE7/ECHY5OBlqWqGU4ltorzrnqxgu I3ArBrHR1/iCQEGKh2rxAdIYQ2P0ZygKJMjWe1dcQkRowmyiwJsh4vjd7MJkb627QexulMBt 6BeGYdDBxoED/aElfWNfFTSRUQZv8VXmJ1Sa0xMVpEzkg7xkQLSU6uxxhVCBBPhdZ42rwqS4 nIM1Evchl2Je36jCdW4vOdwJy/hIWxErbznjc8/5CyNUKJR15u+RL5S68vPYbcPqjKYZb+jp uDPDyP5etBnmNpduPRpdKPEXCOLKCsqEJPgWgLucDL6ujVCHD3UpDjtplCmN00Rda2wfEw2y tqhLU7OnyrxL0VvsHf7AnLeD0ZE3PkZRai3dA6Hp+O6VN1pQuAUNhERwa6dHwen8yUwCswU5 Kp3hjmyg4dTF4R4Wpl/bsAz1nElvLmTJ6sEzmEaMd3NiwHgfAYOH0Qaul+IrvSVAWTj1gBx4 XVJoVgLbQGXL8B13H6g0VZ5PeJIxDpX6g2SYXaB8FBzFDqqKuF5lxmg50PmgsHYV+ao4zPbQ BWtGx8lpWYNZX4PsHl3GvArmdyw48ibfcPqdbNqpfQSsKyvoIK/mJpnorLPJIAg12lofGAAW tnvtOD2Om0iP52huac62Cq6OgYkWq9srlR3cvfnNUwBIlH/o2CbN+zelm2xPr2+2ChaT3qK0 ANcW23ZQYaRjjTyvsJm1g7h05oiO2oYHZS6lEsPBmYjMFmiR7/pqksioAcZWZvyQdEXtt75V UzWEWg99vQOytjIOSgVV2t/UAUaiLaztj8CuM61IFKjBZCytne1Yt9QKsqJAaC2CBXutP5NP R/fOeYzWjRnV1XZZllqB3ly8CAyxUvOAuIDKMDjOmm40wZiZCUP5nwz+hueg0nnstomlAsLf 5/QjXSRZqTV74oNiedbSaJTSFbeNJiyrvoQbBcXKEG9+65dMDogmY7nYlgXszzM0gYoNVQ9a 1vVC6jPXDNKGbqaDZK8uTKYjC2dNfhxeIcz2m/A+iba0raFFpWKBJRH94qRcXVvcQJ7hGEFz 5hZzT1vAJlUHG8HT8rr38TxK807SAS0H74jWjctprrLpdPCFEnToxm2hwpL1l4fN5ayjcHEw OwsaN2ytJY3Fg31OlTThVGWmKeKMCLyoTBS6vvM0AXFiVCRZTZz7PFwq1SMX3tCtszyuw6ZH mJW6wE0jSpBzHElHlwpbJWBAP1w0C3GOn+NCGy4mtfXGq13v8EgItq4r7wVaxoZfXCaKbees JO0Cc3p8f3l6++E/1+340RSD4DSBIxMlcEDgGWPqPTzyFsMt8sSBDtZsHhx+9UmGGSp0QFZT 38DjrhHtEcMTSGWSDQeceakcCSzmPH6EhtVKSZ9V1Y7UnA2UtqXP9P1gzUOLkyPRHEDkTAXK YtG5LCnL7pLrQCuYiEZfdpnjtu6RUcImbH604tNmxZa6phWx+hJTsLi55Ui0buov/3n98+nb f95fTy9fnz+eftOZ5n4h+i8LFv9kiGAJV8eAYnOkYTVszCKQ7myiOrKCduHDhb9t6Jg6I2+Y FxMzVAou9vdfJtsrtVyngBLxy4/vb5jm++U0594z3PwUMczhlplhDC3w0odzM5iPAfRJo3wX izozJ9DF+B/Z4pcB9Ekb61o9wUjC6dnLa3qwJSzU+l1d+9S7uvZLQK0r0RwzFc4AS/xO85gA FqxkW6JNA9yvzDaptakxx5BiN6M21qbapovlpuhyD4HSFAn0q0d2dNfxjnsY9cdfSkUAzro2 42Xsw2EteTkoB5wUhV/QNu/G1E54lI2bhb2/fT7BDezx4e308YJ/e8TNAyfMxX+fMIHv6+vz 45NCJQ9vD94miuPCryi23i9HyozBP8vLusqPi9UlZa03tp7fiT2xKjIG7Hs/tjtSrrzI8l79 VkX+eMWtP04xMfk8jjxY3tx7sJqq5EAUCIfmEMJRx9d/eP0canbB/CIzCnigKt9ryjG/MFyn /RqaeGVnhrIQ2oUkPDOKiljQAIXxyKktA8h2cZmI1F8mJMcblwfRxiKhzAUn5NrfUgLWDEYK EVSXmyKBbR4uEfG2jeuMWK4po9AZvzLzaY/LOmMLCghlUeD1wh9pAK98YLEiGtlumwUZfXXk T7WuQB+YT98/257w4/HmL2eA9S1xbAJ4vfF7gvBSuPmUR2TZRYKooomvPGAE11M7QrCD8KKS jisQBO48F/7REzM0DAt9JFt/QSHU72JCjFKq/hLzssvYB0YJoONsslwyavVo+DDGIeZKSlwT W+Xn6uVNbXll2/BeSr4kJ7jl/siCME5O1QAPDfqIXs+nE1ovvpxeX3W2YXfc09zKfDJy6w+V B9tcLYlhyz+c4SiAzOa4BQ/fPj5/vSjfv/55ernYnr6dphTIbqEYhBJuqg0Zu2tsehOhWqvs /MWEmIHnuyVrHAsoIkyiuKU05waFV+8fAtO54A0ZLi6kMNUzOxq3g/IaFiCTIelyoqDE2wlJ iuFYtWOwOmLuqXFUjmmJGyGEIlNpyc4MJZBkIi37m1szGiOFHbpFVZLKHFgLZlobVlCtI6Od rzeOfcF7gPe236KBlDXizxd8x3w2MMBBXN/crv+JfeFjJIjtJJUu9noZRo5l79NA46fy97QP JlHZzyn9kCMDDZPHAvPDwb0b9R5KTfWDQNZdlA80sotsssP68raPOd75BRoqD66QhrpmF8ub yeqbxuqXADOxixRb1DPUXDsk7nmjyxdzGI349PKG0VFAdH9V8ZRfnz59e3h7fxmMwK2XFu0A ZSqDGuup1cdL4/I9YPmhRXfiubPe9x4FdOQD//3q8vbaUMNUZcKaI9GYWcmgi4tyFYFJTpqu kPp1tzcuKcNDg/jA3KcCICMXyz6rUFBAC6Eh+0Y473MkSmz89EKjbbae/nx5ePlx8fL8/vb0 zRT8I9E2HINkWlY688vEjKceA1UPTAvN8Ulctk0Z18c+barCuQibJDkvA9iSt33XCvM1ekSp N6FUNPrJycdjaE5RWU9RI8oBT48QKQpiKlFRnQv7ZIiBXYnW4kfx4tqm8O8XUFXb9fZX9sUF byyUKfSAgQ3NoyOdMNYioeUHRcCae70JnC8j0j42dmTe2AyxLqLp4jYTWN5erEtEq0dUxXRs qcRq88unMvoyhoBoEEhMqqjGcrJGaMJ9+AdMdg4nsC2QKagnpoF8RpSMUKpkJYaR9Fck/eED gt3fg8bDhqmAGLVPK9j1lQdkZibJGdZmXRF5CFnrnNM2NIr/MOdsgAbGf+5bv/0gLLvCCREB Ykli8g8FIxGHDwH6KgA3RmLcx6b2e1xRHA1bq7yy5HoTiqWaOzcyk/dFat2W0nj0GTBoMiQ5 LmwK1u+KmoRHBQlOpQG3XviNRrNEHPSrv+JJVZOYPIlJWcUCWK/i0Y3pf4W8DHicbd+OIHzy 6y3ep95eC8tFH60kyqqqe8ea2SJQgZVpc2dlTKxEA4amicZ03plHRF5F9i/CqLTM0WHb4Db5 B4x5awBgUEwL8ySx7aNQjWNUWtTCCuldYa4yvoWjuzGGL63wnulZbSF084+5dBQIIwVITF1o 8W+5PeOBJjEGDhm3ajqKJI4jE8YaVtZICa9NAyzMAMf7Ena+lethsOkwxvP/AeYgwkxqmgEA --PEIAKu/WMn1b1Hv9--