Return-Path: Received: (qmail 9981 invoked from network); 8 Aug 2002 11:02:35 -0000 Received: from warrior.services.quay.plus.net (212.159.14.227) by mailstore with SMTP; 8 Aug 2002 11:02:35 -0000 X-Priority: 3 X-MSMail-Priority: Normal Received: (qmail 15442 invoked from network); 8 Aug 2002 11:02:16 -0000 Received: from post.thorcom.com (193.82.116.70) by warrior.services.quay.plus.net with SMTP; 8 Aug 2002 11:02:15 -0000 X-MimeOLE: Produced By Microsoft MimeOLE V6.00.2800.1106 X-SQ: A Received: from majordom by post.thorcom.com with local (Exim 3.33 #2) id 17cmjd-00064G-00 for rsgb_lf_group-outgoing@blacksheep.org; Thu, 08 Aug 2002 13:49:49 +0100 Received: from hestia.herts.ac.uk ([147.197.200.9]) by post.thorcom.com with esmtp (Exim 3.33 #2) id 17cmjb-00064B-00 for rsgb_lf_group@blacksheep.org; Thu, 08 Aug 2002 13:49:47 +0100 Received: from gemini ([147.197.200.44] helo=gemini.herts.ac.uk) by hestia.herts.ac.uk with esmtp (Exim 3.22 #1) id 17ckzl-0007jB-00 for rsgb_lf_group@blacksheep.org; Thu, 08 Aug 2002 11:58:21 +0100 Received: from [147.197.232.252] (helo=rsch-15.herts.ac.uk) by gemini.herts.ac.uk with esmtp (Exim 3.33 #1) id 17ckzj-0006oC-00 for rsgb_lf_group@blacksheep.org; Thu, 08 Aug 2002 11:58:19 +0100 Message-ID: <5.1.0.14.0.20020808100313.00b00a88@gemini.herts.ac.uk> X-Sender: mj9ar@gemini.herts.ac.uk X-Mailer: QUALCOMM Windows Eudora Version 5.1 Date: Thu, 08 Aug 2002 11:56:49 +0100 To: rsgb_lf_group@blacksheep.org From: "James Moritz" Subject: LF: Re: Jason Tests / Reasons for different soundcard sensitivity In-reply-to: MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="------------000307000908040405090704" Precedence: bulk Reply-To: rsgb_lf_group@blacksheep.org X-Listname: rsgb_lf_group Sender: This is a multi-part message in MIME format. --------------000307000908040405090704 Content-Type: text/plain; charset=windows-1252; format=flowed Content-Transfer-Encoding: 8bit Dear LF Group, I received G4JNT's test signals again last night, and investigated the sound-card effects a bit further. I found the difference between the two sound cards was this - one sound card was fed from the RX audio line output; the QRN crashes were driving the sound card ADC into saturation at the peaks of the noise. The second was connected via the headphone socket - the AF gain adjustment was such that the audio output reached clipping before the sound card was overloaded. The second sound card gave significantly improved results. So I played with the gain settings, increasing the RF gain and reducing the audio gain so that both sound cards were receiving heavily clipped audio at a level which did not overload the sound card ADC in either computer. This gave much improved, and equally good results with both sound cards - The audio coming from the speaker sounded terrible, but the improvement on the waterfall/Jason displays was remarkable - see the waterfall from SpecLab in the attachment, where the clipped audio is on the left, and "normal" audio is on the right of the display. I also found there was some improvement in going from 300Hz to 1kHz IF BW. The curious thing is that if clipping occurs before the signal reaches the sound card, the results are better than if clipping occurs in the sound card - I would expect the effect of clipping would be similar wherever it occurred between the IF filter and software FFT algorithm, but apparently not so. There were thunderstorms nearly overhead while I was receiving the test signals, but with the gain adjusted for clipped audio as above, the Jason waterfall was remarkably free of QRN and I was getting perfect copy, even though there were bright lightning flashes lighting up the room. So I rotated the loop again to get a marginal signal to compare the effectiveness of the normal and KK7KA decoders. To get a consistent comparison, I recorded some .wav files of different signal levels, and then ran the same file through the different Jason decoders - the results shown in the attachment are from around 2230utc I think, which was the end of Andy's transmission (or at least when the signal disappeared from my screen). The upper decode is produced by the "native" decoder, and is completely garbled, whilst the lower decode is using the KK7KA decoder, and contains only a few errors (the last several characters are after the signal disappeared). The KK7KA decoder seems to give consistently better decoding with a marginal signal level. Cheers, Jim Moritz 73 de M0BMU --------------000307000908040405090704 Content-Type: image/jpeg; name="jasontest.jpg" Content-Transfer-Encoding: base64 Content-Disposition: inline; filename="jasontest.jpg" /9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRof Hh0aHBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwh MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAAR CACxAZIDASIAAhEBAxEB/8QAHAAAAQUBAQEAAAAAAAAAAAAABgADBAUHAQII/8QAWBAAAQMD AwEFAwgFBggMBAcAAQIDBAAFEQYSITEHEyJBURRhcRUWIzKBkaHSQpKVsdEXUlaCwdMkMzQ1 RVRi8CU2RlNVY2VylKKy8SZEpOF1g4Wjs8LU/8QAGgEBAAMBAQEAAAAAAAAAAAAAAAECAwQF Bv/EADMRAAEEAQIEBAUDBQADAAAAAAEAAgMRIRIxBBNBUWFxofAigZHB0RSx4QUjMlLxJEJy /9oADAMBAAIRAxEAPwDJhqIxIQhs29plIVv7xt11Kyen8+oMmPEcjJeTdErdVkqaW2sEfbgg 1EdS33SdriyvzBSAB8Dn+wVGwcfVr0py+6Awp19HZUiGhRmN920XiFDDYG7cfTGDn7qm3hlx DgUu2vw1eYcTjP2bRUeHNDC0AxmnVBQIUsrCk/DaoVbyL5LW0Qt6BLG3aEOR96k/1lJz+NIi 4sLG7Hyv8rRujQb3Xmz3cIa9nntPSI+AB/hK0BIHuAP7qtp+p4zdqTCh2uGuNuJJ9rkKxkEY 27kc/YRUDS9wtkKU69c2JSt2NoiLSjHXPB4q9venbbPtYl22/W2O0hJX7JNXHbkcZ4y0Oc+Q NV4iXlaWvaa6HpfyW7NTosG0OJm2NcBtCIjgnqyFvOOlLaOcghKE7iccck1OsTFvEoPXG6wm Wh0Wphxasn3DaT8TQoFhsnLSF46Ek/2GpkJyM9JT7S1sZA8Xdq8XA8txrWB+u2F1X2v72sWT aXhxAx8vnhWmsHvbb7ubcc9nLTRSkocTnLacrCVcgLOVjk8KFM2SKtc1tuLdHWnFfoxm3VOf YEjr9tTdRNRGroyh6fNLvskZQPcoIS2WGyhOQU52o2pPH6PnTdp0zdbgoy4cSeY4J2ykN4HH nuJCR7+eKlkTOV2rqf2U6nGbU43asL9qeWmD7BJgyIsgDClvsNpWseWfowr8aClOlf6I+IFX NztSEpXITMU+RyordaJ6f7LijVM2tCFAqaC/cvOPwIrJ0j6AxSidznP+JSGWn5WURW3nVAZK UJKuPsHSmFIcZeKHm1hfmkjBqwaXEuDyGBETFUThPswUtRPpha/3V5utpetakF0OjvOUlwAE /YCasQ5zQ8H35LMsNXuF6gTI0fxOQo7ihnhZX/HFRu79rkkILTOVeEFWAPtJrjDsZDKitpxb +eDu8OPeMZ/Gm5EnvlgpbQ0gdG2yrA+8k/jV3ysEQBTtakextolBmXJQ0PNwHvEj9XP4VNg2 iC/MS18uRG0H9Mx3lk/BIbJzVOpCikKJ6+tSILSC+kvKQEZ57zcE/enmq2XvAArxUCiaCLLj p9duthMRft7rjrXcymW3m1N8OZb2FI5VlKv/AMvHrVXOYvNtWg3aG4BnIEha8A/AHINXttsd 4mxHVWy82thn2hlZ7uRsKF7HdiioDKcDeOcE7/OnNQi/RO5h3STFuKXT4X0ynZG09OAte3P2 fbTmufMI2u1E773/AMXW2DBdRAXrSGrnIinYsS0Qwt8jc4meWicZxw8VoPU/o01fdVKZuqyt h1ctPgU7JkJdCRnlKS2hHh8+KpGtPrMtYLUjPBCsFGc/BKh+NMzot0bK2vY0raQdpWIwyAPV e0VDOC0SGYj129VOtzGXse6i3aay9IWpt5bis/X3K2dOgCgVfeatNGM2l26j5XTHdY5VsdU4 jPGRyn3+oNCquDg/+1SYjimH21oW4lQOctnCgPdVJJOaTGcA2MdLwuWOSpNbsrZLLrOQ3cnb fY7PaJjTqSTGtLjkRSOQOVOIAJ+AzzWxWWFBvGmWHVxX2/aG/GH+8DmQT1JIVjOce7GOMV8v 2h+0zZRTKaml1XIeMtIXn3ZA59AMn0Br6n085Gt9ghQy6sbGgE988VLOBz15+zHHSvIm4eCB wZvYvK1nADWybKmslr1RYxIZlTWZcFJV3CQwsrxxjcVOKJHX1PnmowdeuVyelS5DcRC0hss+ zKWteAcEHcUdMngKHTPpV7d3LVZdONPpYLUGKUrabiPJYCQOgB3oGMZ43YPoazy0atteodXT 5dst8yWC02lL5a8bIwc4Ut0gDOeEJTkjJz1ri42NzYi9uWjuudzTIDQslS9H2BYvF4f78PyF uK7xyU0tAUrjcQElKTgk88k+orF+0GKuBql6E42336G2u8WhTqt6i2klRLnPPJwOACB5Vrem UuG7Xi4NXMRy6+tK2FxVIcTkghXDoJGcjOOemTWV69t09vX7kWY+mS4RHR3iDsyO6RtGFqVy BxlSjnGTXR/SiRM4NyQB097Lu4sNEhb2pH+ldFTvmyzKUyytbjQU0TMlNFIIGPCgKSf1fPpR LoXTZbvIkSLNaX4wTuRKJcckIWCBkqcaR5ZwAkURstmHowJVBkQxHYBzKmpZQAkDJKmVK8IA 9D8KCez+5/OOa+5DvDdgjtZSYMBpgFfi+tuXnjy+on3edHOmk1Pce1/P0+gWHNc5jm9PdI+1 pqaLpWzF+QVMIIKUKSyV5PkBgYB+OK+aYl1ivzDLkd04tT+8iYrvSU/a2oAcn31o/atBts6E mfGu826+zna+61KbdEdXOApsYCc564HTpWOW6Ml64JZjuyEZVhspSncT5fpAD769TgGgMdM7 rg/wrMaW6Wtza+kLMdKPXCJJiWZxuWBhDgiyAzg9dpUlKOox05xXe16RGZ0qiN7SqIt1SEtv JZJ2EZIGQRt4z95qHYIHaFGRCclvWz5O8O5lL+x0pz6hKgT7t2Khdr05l2yx4slQbWFIKUqK ApeCcqwVpwDj3/ZXlRkc9rXuuyNs4+ayFiarvdStE9ommrBpeFbrleG/amk7Vd2lbxcVn/YC uuRRgLhdL/C9t07OjNxlbgfaobqyfelKi2QfjkH3VjVg07ZUtG6C5MPzUgLbgQYjUxxJB4zk udSBzkYz1FbBoe7u3O2OLk26VGWFlH00MsbgMcbd6/I+7nOBWswAl+E2Be/irTxtFkeizq+N Xl/Wlmk3gQw6zJbHtDbU5IUjf5YbCQSOnixxyaLNcH5x2Fy2Out929tQpBaWPGHWzkLGQMAY 5HJUOeDQx2zzlsSYDiIDUkl8jD0fIKQPq5zu6+mKGJN41Je7cQmCbdb40fc4lTA2Lb71vKUF aeSFBKsZx4Tz5VMXD8TOWSw1p29hbNjD3tLzgdK+iauFrRoS9RBEuqYrpbAL0txbqEAnnZsQ PTzFFPy1qKOhubHvs/UMErG1uBDYU2PcvapSxnHTA6dTWV6hmiZNjttzFyHWhtwthtpA+CgR np6Cp0zUTiWY6bhGhy0n9FUuQ93RCsk7Q8EfZ0/Gux/A8S6FokcCW/5YG3mVpO6MSHSMD8L6 uZkmXbUvsoIUtsEIfbKCD6KSenwr5c7SNGjScqPJS4wtt9xQLbMdxoApxu4U4o4yeMHzrfoe qXUaaaly7Y/EQllO+Q8EMs4IAB4cVtB9Mn41iHac2/cb8iQiLG7kpSW33pLf0o2j9IKAIyD9 3xrlhmc3imxXuD5eH7rljjLmuU2w6wvqdKOtJuMWBEbQkBYRKcfA/wBk7jjgeXHwqg0nPflT XvbZ8xlspVvlB55GU+YKkq6dOoNSIF3TAsqo0mBbGQQOWropxKvX6NK18/dRD2W6Rj6qU9Mv EAPQ2XMNONIDHIH85Cgr8PtrsLIo43mqBI88/XK79TYmskb8/f7KsgsSvlB1+3OpuMFCgFdy iQ+oe7crYPXoRUXtFtXcW9h5i2w2EqXk93ELTw68LO4j04rUHp/zSU5bSYsSHHCPY2Jc1ppx zklRC1OqK+T1OzHTmsW1YmStanXbbDitqcIT3YGcc9VICUH9/urk4TmcXxPwj/H1VDxL5YXa m/D0z7rKG7bKfhSA5FdU28D16Zrduy213afBkT51xbLbyztQiWFEcD0UQk89MZrG7W409HML NpjqXlIektL3c/7QBx8TgUW6Pvrmh1PJU9HmBfJEaYjaR6ghwYPHTb8a7P6jB+p4XkMbfpa5 4tbbAdS0ZsKitIjy9PrlSWgEPSBcZgDqxwpeAzgZOTxxzSpQo/ajLgR5MfUlpZYdaS422sIW UJIBAKg0QSB5gkH1pV5/6L/59Vrrn/2P1K+e2IqZDxZkSkxx+ipaNw+BI+2n1x2oSVNPezyQ rIQpqSPD78A8faK0i4vW62wEm2aLuUdkrBX3ntSmlny8SJAGenkaDTqG1OzyHNJWltJXlYL0 wHHnnD3X7K93hp+adTW748/qVyyxiP4eqobfFW/cENtOMtqz4S8NyT6cAHP3UWXGLfbY060b LIYUnAclRY5bbUCPQo/hVS7Pta70hcO2Q4LW4YAffXjnruyVD7s0TXqLeJsRhFquEySvvB3c WLJlOoA9fpEgJ6jr61zyvfDIG0Ot3n6LpgH9s0fOkJMXT5Mk7xGliV+kpbifPpwUHy99PzZV +uxS3cJCmWgQSX0pYAHTyAz8MGpSdM6ihXJD13bnQD1D6mVuFR/2SnOffyKrL1cGZExt2JJf Wpv9N0KHPqAVH99dXNbKNROB7weyycKYST5bfNXTWiSizLvLUtqcy3kqbSy8lsjOD9IUpScZ 9fQedQYkCK5snR1R0uJV/k48iOhypefTzpx/WmoXreM6nlhQGA2y86g+nlgH7zVNZ5CjeEuu qWtatylKLoQSepO5QIz1/wDekchYNMlE9K6KWOjL2gN3RBqdxpuY3JRbG1JLTYX3iHAe8CEh Z3BeCCoEjBPBFULD0d+SpxUXuVdQG5Owf+fP76Pr5c7rGuzTSoMgtlppTaJEpx5ooDaQlQDB CeQNx65KvSgiYp83NbkN9DbrhJWGFLbSk85B3YI++qwx3b9NjfuD/KvxAo2CpRvFldZLc60T HCM+KNKYa/H2dR/GmRK0itSU/Il7yf8AtZn/APzU7Bs16uzTryGo01Led3fTUBQ+wuA/voef QpuQpKkJQpJIKUHIB++udz2ONBxOc+C5pA69Tgi+Xb9PwYAltW27tyeqUvPpdb9xJ7lHH31W LlW+fCUp61zHHk/VXHebQhPxSGf7RV/pzROpdR25UyDBYuDSDhO+YEqBxnAAWAPto3c0dq/5 uG3vacSpxQO1Lt0bUoc+QXkfcRVpn8qMVnORdEX+66m8t5LQdIrztYfkB0napDeeAfIVwNpe cCUKGfVagPxNGF27LdZW5l+bNs6I8dJyVLmR+B5cBf7hQmyY7RIW0pxRHhO8AJPvGDV4yJDp xXfquGqzSvmIcmLaS45bXZUYcqUmXubz6kI/jVci4xlR1tfJcJBPG8qXu+wlePwo6iQNfsaX SYD0Vy0qbDoQgsKCU4Bz4hx5cdazEqVv3425Ppis28UXvIJsNNY+63kdQGkY8lofZ5b7dIjz XJeoIdkfDzZafcKVr7sJc3hKTx1LfPXAV76J3dEQG5XeDVi56zgkt6WVKQf6yQR+Oay1p64O ablhLbRgKlxy86rAUlwJdDYHngjvM4B+r1Hm5YroqO8sPNR3Nwx3kh2QNoyP+aUD++qTx63H Q4nwxt2URPO10FpqVaTtV1aan6jYhFkErDelfZ3VZ6eJaVqSPsFC+qr9pSbclqZtFwfYx4Xm prbXeDPXC45IPPrinoL+nxOL89dndcWSEkInO7OOMNrSN32rqr1RMie0oQi2tYQngqivsBQ9 QC8riq8PDC59NsPrrj0W8nMa027Cppc/TLsVKIljuLLwB+lcuaXMn3juQPuxRL2e6dXcbm0Z emJUyOvO18b0pT4cjKiQk+VBsaCiduKpjEcjohSHFfdtSf31eaS1S5peW8hWXoyiQtALhQrj GSnckH+sDSaGV0bg3rsbpYQkB1u2WgX7TeujqBEeyRbtCggFxKRMUtgAY6FKRt+CsmiK3zbj p+Alu+PzZ0ncDiO4HTFA6lZw2oZzxyazO1pvmoblOlWC5RrE0ogqbivqiN4AwAEpJPOPOmYU a8y57onLlz+6UULUtoylK96dyFZH9lch4OKccpzgNFE976ZXS173SFrshfRdru2n9WQHIrjr Vwbbx3iJkMjBHnhYwfs99Vj+mEWvUa58GE0+qSElS1tJa7sDghJbaGeMZK1Dpx50PaE7O/Z1 /LF0gtwXuO6SpSkOYIHOGy2E+fhKMjzqBc502Pri4NM3qG3EV3e5h0OqCQUA7gcISOuc5PNc HF/4OjjGPxvfVZiICbQ04+qrZNgvy9SSvZ7BJYi/XCWXFuKdJPUOuDr/ALIIA8/Os81laJln 1IlUqzyoLCm2cokHeFL7pJX4skKyrccZ4BwQMYGgadtD12uc4z5MpUZDngLDCO5Kt3VLu45H Tz+2s/7QG7nH1W/CnPFSWUMBtOVBJQGkBBwo/WKcZP8AO3V3cNPrkLY+gC24pzdIZqsjp919 Ewrnb3NFD2FZlRgylHcRGEHeCACnBIGcH1FVfZlp6Hp52cu3Ot3EyCS7KZWyG2VAj6IhKipJ 89uCB9tRey52XJ02pt1uxxj3aUNuRmwtWNox3mF8k85Gasp7d6iTEsS5QkMOlLZNrbkMrGen 1FqUEj1yK4XOfAS3cXQrwXC6NwdobsVO1VpvT85E6Rd7TbozhSFmc4pDYX5ZK+uUj+cMdOa+ cZcGfp24FUa5Qlx1P7UGHObkIIzwSlJJxjzKa13Vup9QWO3KtMVEnesEsOh52Q6B6rU4gYGf eT76zK1aLfukwy7ldrVF3L7x9LstClhOeSQlXHPHUGvQ4QkROkOAe62ayRrWk2twTaIkaPZp U3Uy5SFOthqK63BCHFqIOEZbTzkeRz6c0u1a3wrhYO5udyj2yFvQTKcYDygfEcJSVA+nTyJ4 qwh2HTTGn2Bbe4id0lLqHW3XEZWBkFRQtJWM+WcUH9skyV8zI+yW8rK2wssNuNtr4PPKjwTj qT/bXKwt5jQOpHmuUlrnW053Rd2d2iz2/TLaItyduMZwFTTktASrYryCTyE8ef8AZVy/ZphW 4pvUl4ZS4rclppuMpLeT0SVMk7ecck4ArFexe3pmzFKN5lMlpJzDQkqaUAc+IEbfuJI91bo9 aG5KGAqTKBZUFICHVtjII+sGynI46E49Qa2ljdFIWkKZGmxWxWQ9qdltFtbgPTm5MuY86lsK ZlNsu458xHIx8AKDJUizR7VIblWO5qcSwSw6/cmnlJVvSSrYWgQAkKzwR5YGQpOr9q0Rcy02 ll1PtKTcEbUtpKSfCcJGXE5UeP0s/voP1JcbrprT7nyJBk2zEcKkOOOqSpCe9aGUqC1eIlYT 9bIClY6k1bhuIja1sFWSTm6FDcUu+EOMTpSSKGyydBbu1wbQlthKQOUqcQzxn+cQB+Facm26 tieyM2HSzFshlWS63Ibkkp453ndt8znGfuoJsuvNU/LDRXqK6qbUcFCpK3E/coq/dWysu6+k 259AumlpkVbZ3fKIeS4pOOSpAG0cHy49fOujj5XHSTVZAzQws45NLdR6nPcovhahE1liC5EJ krQnKQlx1vI+sC53eMjr5E0Pa30nbNQPW5i9yX4gaWVNus+JtaiBkEqSrONowD6nFU+nrxq+ zvR232bZItCiAHrW0Hk4AwlKcLTtHTHGKtrw/cbxrO0xDcbKiNGUXHIpwqQ4ceSCCUY9Qc81 4byWHD7duK2rt9lR0YY7Xppvmri2aStsS3uQlQGhGbSnEqREYSHk+eQjB8vMJ6+fSsocY01p i6PJg6kjz7k3kpbbsaXAg4/RUhSUgg/cQelGmsr7N0rbnkiLMcguA57sOJ2kq81l0kA54wis r0FqgWtUxESwfKN2e3LZcCC4scdDjxdeeCM138LGZo3Oe3fpe5677du6RktAcHbo009e9Sam vTXsl0dkbMlaFxWo6RhJ471Ie2E8nBAyeM072z2lmDpxmW7Bb9rXKA79BBUEkLON2wEpz5Hj nr5UTaXiXy62lq6T7alNwSlSUxZCgywnnBGdrqhxzyOp9Kgds64EixQI12jrS4p8KDsR5Dik YSrgJUUqUefIY9/lRjY/1AfG2qNCvyN1Rx1PGnGKPmsd0DZzfrt7M5Y27pGSU98VSe4LSST4 gQobvPjnpWmp7ObAb5NiQ22oyWEhbjbhQ8UZGcAKc3jz+sE8DqajaGtekYF7Qq0R7pcJTgAC nXIixGBONwzgkjOeB5e7nQb3e1WSQ77bKfdQpkKjsMwnEAEJOd76SpGT+GOBUcU+V0xbm62v 7LQPmjIZGPi8QPdIMbtOjEtpS5pgLWAApSZUVIJ8yB7Tx8KVGsDUOqF26KpvSrBQplBSXbth ZGBjdubzn1zzSrm0u/1H1P5V9fEf7egXyzebzcL/AHFcu6v97JICSsNBAAHQbUgAfdSt0V9D zclt+MChWU75DaSP6qjXQ3AeSvbMdTgZTujDk+nCjUJEVTyVr3tpCOTlQBPwHnX1PJEbQWC+ 3T0XICdSO4cSx3SaiY7fnGZLRypl2HFSFlPJAWX0jB5AJFSr8mwTZUZhcuWpwFIDceHHfKjj zLUvgcf/AHrPGH0MOArZakY8llQx9xFWLEJuWTIcbYbQsHahMlCCD79xP7qo2GWV2HAEdD+d lu2d5Ba3Y7rTXrB2YJsqFzZLse4ApS4GpBQ7n3tqW6B+7316WOx6IhKW7Xc5W48uJmIBPuIU 8n91ZLHUy1PIeShTYJGFKJH2YIzRBqA2ruG1N6kk3lwj/FFDjSWuD5r3Z/DrXP8ApzGAC4k3 4qfge0mq+aIL5oy3ahU2jQtrJUMqcS5d4qyRn+YHSR0PnVQ52WavtDaptxtyIkZCcqeXNjYA +1wZ54+2g0uJAwlrn+dnP9lF2ilT2nXnYRmMgpIddjDBA9Cdhx9460cx8LOZEbIz1VII+fIG Wia96EslvDb9+nXOJJW2gnK46w453aS4hOVjG1RKeT0AwT1NdbNH6acSuUnVbccJJ2sy48VS lf8A1JH34qk1bebhKnNR5j0xuOI0cojuSC6NncowvjjKx4z71nPNRLTZpN7eQmGpL6UYy2+4 G8DGTyTjH21owSmNz5pgD3r91cD4wA2yFe33R9ljWp66w9RNuLJOyGhpBwQDxvQ6pPl5Z60B FQSvxDd99E95mtW8uW4MbAkbT7JPLienQnBSfgPShl11ayOBjyzgmnDt5TTqdbrvYEKvFFhc NBtTO/YfY2voVvAwgjan7zt5++rhiVfUWNdvivQ0W9Y8SQpjcfir63n60PuW2YxFTJeYUllR wkqIGT8Ov209FlQksFmW1LUc5T3cgISPsKTV+ILZwBM2vRUhOh1FXNqXZ4KVrnTprEk5GIsR LoA9dwkIz8MVeyNN6fVC+Uhrx55YSFdymM13yRjOAFSRz7gTQQ8mLgdw4MK528qWPcSQB91O JtiEtpW9MZQTzsO4q/8AKkj8atNFLh0W3h/CgEuJB6Izj6pjwbYuILncrzBOQqPcbahKc44w 6l9Sk+Q4obev9veGxvStlQkdCHZefvL/ADU6PqG0wLQqCmwxH5RGEynAVk/YQP3fbQstzJJ7 oJUDnjNc7YWR6muGmz8z9PuplIIAabRzpTUOk7ZFlyL7YWnpIdaRGbjLcJShW8rUN6yngpR7 /F8aprs63dp5VEmtBndlIkIbZUkZ6Zyc9fXPurluWqfp+U3OcxHTKjpExWXFMHa9hsJ64XyS Rx9Hz1FMr013bCnzcIwYB4Xk5P8AVxmtYYLc58dm/GldnMLcZCkSD/gjbHeCZ3RwohCS2kdc BY8XUnzFcnwoz0ZpUKIltwJBW4mSlSR9mTj7T9lUWUxnlICg8nyUglOfvFcfbfZKStCm96Qp OfMHzrYyN/1yN+/1VzxBLSCN1ZrRMmNEyroyQ2nI76RvPPkAMnyrxaI8pMrvorzAcRnG9nvd 39XaR99VOFJxg8+6vbTrrRJbUsHocD76oZwHDW21gC0kWMLfNARV3D6G76jShgbe7gxkmErO TnlsIJ+Hv56Vodu0fCZhyGVqVsU4VMll19tSE+W5XfKKjjHIKay3sXTcZjj7qrZZZLLZA3ut JaeTznwlLZ3fafurQWtSW2yP3iLHtLcBcdze+22qMCokEhWEEJGQQfpVJJz5mvnpQ3mu1D/q tORdMBo7hdvl8cl6bdatzE6TKiOllwQpEdS21J4O4qU4Aeeh8XNVGnYki4OSrlcpsqI68EoN uU/uDJxjgBKdqjjIwAckn4z7rZoZiw5VuevftM5YdCrOho94CCcqWfowMA87hnyzVZZ7S3pq 9XCDKmofnSe7dUla2w44kbuQNxUrPIOcDjjNcfEN0wFzzZ8s12tSXMbA8sw7HmcqPZLb8m3y ewX588OEPtPOFtx1IOMJyXQojBxyke+g3U107NRelG52i8SZwSgvLjKDbaz3aTjlw58+mPdn 6xlwr5pGy6ymSo8W6Ku61uIH0bYQok4w2AU8Hy3c/bQXq2NHnaycb2Kgl1LCe7cbbTgd0gbv CvYCr63JABUcnqT28DwUz5C8tNEDO3n9kdZJJFHA37I/0zqfs6t8Za7fbbuy4pWER1S0JWc/ zT3gP3mjyEluXdWp0u7wrfIeH+DNvQG25yAccBa3FgjjoE9aHtO9n8OHZEOJlTor6gn6RlqG l36ueFI3kgjPmfhRDYr2q13pNsUnUl071KcumM25HaPnucSlJz9pGDWb5opeIaGDvvZP1QvY RncIP7S7Jb4ra342o2Jd4UMuImvQ21KbHUAJbSSfdmgjTd4049b2rff3JxkMyB3aYjjKEkDo S4op2jryFj1zWj9q9islyhSLzMjSUyozeEpZebSogkDySrwgnnIz7/TBrcmMb9D2sKUwHkb2 nSXdw3DIwlIJ48gK9XhJ3SRPib036eqtHI5rBWxwvr20MRX7I0pEiLNY2KIdYTnd1PCt6snp zk+tZf2qv26Na1xW4M9mSpeUuruaUtkA4Pg7056eafurUpyYTukpCQy2zDMVXhcQEJQnaeoW kgD4pPwNYL2gSGWYtvgW25t+BtIVFZd8C/LOEISgjHmNoPkK8/hh/wCXE1u58P3/AJVIGZJA 2RH2WaIt0yKjUJet0lO1YEVTBeVHWkgpPKz4uh4SDz761qxQ5DCJD8kQO9ecylcWGphQTjI7 wKUSVc+eKyns7RfrHa1fJ+kJZaX4lr+UEDf0yUpXtA6DPPp18ivSkZ60390zHI0V67OLeRHX dwpal43L2sNtJQT/ADjlSuPrHqdp5HycQ4yZz5+6UOBFhA3aBMQ9ra0W+8MtXCQ28AWwlthk oUojxbXFrHwUR7xVvrOwW6bYW4rkRph1pvDDUJDPKiptO0FzBJwcjGM7eD5VVdoA7ztPsCJb UV5JkI8TqC0lKe8GOSspV06eeeRmtEvbcyNbWhEbixitxtsvqVtDYKkp4AB3Ejw4yn6x5rhn eBypozht/j5KzptOgHbr5V1Xz/J0+mxXdjdAvSHdoU2koR3mc9cJUf7K1W32/UFzWXm1XiCy tJTukNvbWB5KKTN5PX9A/D1o+0qdLsz9vmpv7zRUSltLENKlcdTkkdD5Uwq4Wu5w7fPl6hbn OJCtpnmLF7rkfVSph0k5B6e7k8Y6XTvniZK4C9tz5/ZX4lzHxgxZHgFpUHSQatzceXPbvzCd q3G58RDi1cDGFZTjB55ya93uBGfuVqk2y6QosphxRPCXHlNn6wRk8DgE8HoKhr1Xpu82hyym Q1fJLqAVMNFtzeQB1JQlGeM8is31DfzpTUzahBnMoScbXZRfQlsJH1UbsBXIP1gAcYxXKBqe GR1ZBPbP5UcPw7qJfY3Pn77olu9ns16ckOmWNQXCMTsYbXGStJJ5yEtp28+Syrpgc1UdkzUu Oi4XBDyXVsBaHIEOC2pzIxwpZSM+4BdW4kyO0LTrr6592iW4fVIjpRvwMYz3iyRkdMck8UN9 nevLLoq2SIm9eXHiXFyVOoPuAQlC0jp1yDW8IfJHIzVsR7+apC13K0k2tes8y5SrXNcatD8C StXgEhhrOcdVIS6D96h1oQ7T7beNTaVjw4bcWTNZeQ49hxlnuztUFfXcOOSOAo9RzxXvTmr2 r1f5d7jRrg9HccShSI8hchDeE4Cu62bkZx5AVztzuBiaMjFplAU9JRhwtglPCj1Jyk/ZUwXz GhpwD5/JU5JippWUabsNzeuMf/h20qcWoJDCrsgE8/V43eueAfdzWw2jsyjP2/ZeY0eSVdO7 nyHARwRgkox59MVimi7xN+XEKcmNhxa0DdIdCT1xwShRB+Faba9TXTS06Y0xaJ0+JIcU67KU /hBURjhSmUAngdVKrp46SR3ENj1YAx0O/XwXcI3vgpnU7dfqjCJ2U6RbhMIkWGMp5LaQ4Ug4 Ksc4ysnr6kn3mlVRE1ZqWVCYkI7P/akutpWJCrpFy6CM7j9GOT16Dr0pVJ4Gfv6/yuHkv7ei +dYPsDSXkzkvrUPqFtYAqucSNxKB4SeBmj9fY92iKCR83UAJ8xKjA/fvrq+yLtGcbQ2rT7e1 OcbZMVJ+8L5r0DOx7dJ6I47ABALBCHkLUylaQoEoXkBXu4IOPtouXqSM7afY2orNsPOVR0v4 xzxy6cg/901Yx+x/tAjyEOjTmSkgjM6P1/XqS92X9pUgqLunWDu6kPRAfvCqsx8LC03avG8N ae6znj2nKW++GegBG7+2jmRItydLd07pq5Wx8EkOI3d0s4OCSvn7OaX8jXaBvz83cj0M6P8A nq4m9m3aDMtbURWnZJLZJ3Lu0dQP9XdVJ3xc0PDuvS1aBwa11rLXJD+3ui6vus52pUcVeWOP 7S6hEGAuc4E5Wh5tak5xk4DZ3fj9lXauxftBJz83gPhNj/noh012fdoWnXlPJ0s446RgKRdm m8D0wHMEe40dxhAc4ZJ7qOGDOYNZoIe1FN9kmsxpDDQZSwz9I0JCwPo0nYEOuFPhztxjy5A6 DzbNYMJgPW2aH0xHMgGC2G1gZzkpCkoP3Vb6h7Me0K/3ly4HTJZ3pQCg3GOvkISknO8dSCcd BnFMROyvtItz6XoNicYWBhWJ8c7vXquqzuiniDHGqzjutGcSYnnQcd/BC7tyZVFWwm0RZTeM JkLZcbcHvwhYTke/NUzLqIzgWpoOHP8Ai1A4/fmj2Z2Tdo01YU5p1pJ8w3IiIH3JUKinsX7Q j/yfH/jY/wDeVoyeOLLBn6rCR7pHWShhVxhOxS27AUPFkFlaUgH7UlR++oCnGdhAbHJyCeoH 34/Cjb+RjtC/o8D8Zsf+8qSnsa1r7OUq0s4Xf54uUYD7t39tUE9uJJvzUOeX4NLPWnQhzhtK vTOf7DVnMusmcWmwlOUcANhQJ/jRlH7I9dMJwdItOKzwtVwayPudA/CvT/ZLrmSrcrSSG1Do WbiyPvy4f7K6IuLDWluqkLRp3+S9ad0fp+7Wwy7kNRQlN/497uUBgH3EgnqR99AamGY05TbK 2pje7CDhY356DHhVmjy3dlXaDAlF35tlaTkEC4sJJHkNwXmoznY9r5cnvE6ZS2jcDsRPY/eX DXNGWteZHyar6ZwrO0Ftje0LbFNWqapbgjKEpkewnP0nhd+kwo/oYxnnHee+oUhcXuz3Dz6l E8pW2Ej8FGtDkdk+snbeplGkXvaS6hSX3LtHVtQArcgJBA8RUDk9NvHU1BR2P9oLKwtvTaEk DzmR1Z+wrrpdxLf8Wux5Z9Fns5AcZh6Q5taQpRHPCScfZSd3pX9bIHpWo23s67RIUkOu6Tiv JwQUe0RUA5B80rFRJnZV2gTnytelWGkZ4QxKjIAHx35P25rnZK2slblsfLoOygp12N8lpXti 98eMJCgsfHGBTNllSY05Ko0pEdaiQXHMFKePPNGUnsb1ys4jaZW2gf8AOXGOtX37gPwpj+Rj tCx/mD/62P8AnrWfi2yEEbUstRDrCMeyzVtvbuE52+3d1mRtygl3uY3wCUqCVK/q561oogWb UbUy8LgWqa2lQ7h1uep5tYCuSpJCUJPGcZPOeayW1dnfaPb2lsPaedfYWnbtF0ZSR8DvI/Cj fTi+02wW32D5jMusg+AouzSVhPPBK1ryeevTHGK8riYWariNg+ivLRbzA63Hcfyjhi4PWSxC fcI7bMfYlQjpcKy2OiUjblJPIGUnHnQVE1dKu92mPyYPyRESjLftqDHU7hOMndkDBB6FXwq7 VqbtKBZCOzlru0/4zfemFKX6YIwAfsI9woYvMHtAuFwfkwdAx7cJLe2RsuEZa3VAAAlYIPA+ PWuOXgjKzl6sHv0V+HMQf/dGFlN4usf55OyXGIkslatypDxkNEknkFCUcenBpi+TkL1NFcQ5 CdCER1d7FG1CfAk7AVFX1Pq/1enlVzI7Hu0KRJcf+b3K1FRBnMHr7y5mnpPZFrxUpt6Hpb2V KG2htFxYWStKEhS8lf6SgVY6DdgcCvZa9rKDegq1V8xcSOlrdj7E7ofeWo9zZWhGe6Sp7vc4 BOGW9x+xPvquvzUXSa4s+LIdZbUoNrcduqkgJPOxLbhKVE48yn4iq+HI10xaEQJHZt7SAz3S 1LvrG1Y9SggjPxzUGUz2gS1x3H+z9D60OJLgdvTZQ4gA8bErSCeeqtw93THiOhksED5rDdw1 bWntQ3VEnTVxu1wtNsivFvuw9MDbqn04OMlsqGMHjrz9tfPrdzfbnJfU2yptD4dS0oENA7s9 E4491azqbQ2rdQy1S29BPQXu72JS3eYqmk+hCdoP40Jp7Gu0DvdytPqUnzAnxwf/AF16nBNE LHPc74ndO35W73MIDWdPeVvceTqm56Wd9pRZXn3m/CbdKeSggggYIwofEK+7FZB2iW+/WlMS c8rDKMIU22t1RQeeFqJyT7yST6mrqJo7VESLb4/8njjiIiw4oO3qM73hwPJYUlI4/RAqXq7T +rdV2xEQ9nCoa2iC0tu9sFKPXwcDpxXJAJGcS1//AK7G+3grx8QGAsYKvr1vopvZ1ry3wNHd 1MdhR3WkuOhDLKmUkjGMFQCVKPx69etWFsut51WxLFsn22QnfvSWru6y8xk5woIbUAccDnHB 60B6U0N2kaYmPOt6ccW280W1obuEVOenmorH4URRInahAkSFMaRceafGVpmXttw7uem1aUpH PRKU+4isZeGL5S6rA2VJC2yWnJr6qnuC7jZdd2hM24Til+QhBCJ76gQVj/ZQc8YwEkHPJrVL 7f4sCJHkuKDPTa5LeU00vK0j64yjopShu9PLxFOTTdIdpM19p9eibcl1twOb/bEOFR95cfVm vd70x2rakgORbrpxC093hkMzmGkoXvbO9QDnj8KCkA8DdkdK1khdKGtoAVmvNTK5ryHX5qP2 q6tts56ExbprD7acuOKhpTkA8FPeJOfLOMdTn0Am2yRCTo5kQrNd34XK3m5bK3iUgnJTh5pJ wB1AIHoPMO/kZ7Qsk/N4e4e2x8f+uraF2Ya/gwnGGdNyUKcHjUi6RQD1+0dfWumGBjYWwF5+ HNqGubtsFpsLX+kXrLHbtUWfOkIbSn2KM2VPt+X1So9PcT086zzU12cTq+M/AalxGitODd3V shIGP556DnOUn+w11r7Ku0G1XBExrSyHFoJIDlxaT+KHUn8au9QaI19qMsuTdHr79rOFpvDR 3Zx13LUcceRB99YN4dkXEB9AjO34W3DyMY0kGit3tbjdwsUd1L0d9LrQytlYW2TjoDgZHvwP hWO9nFlgjUl0TP0+/bJbBThbqytLaTkkJ8G0cYPX0oltd17RYFjatrvZwyvu2w3uavLKEnjB OFFZJPvJoasdi7QrAl32PSk9suqJUlu9xENgcdG9u0dDyB5nOaq+DU0t9lc7HaWuARsq7W20 yLhIt7kNMlCk96H5ncoX05US2SOD+iD9lBXazqaHcdFoEWRElKMhCStLrTmfAvlOUZ9OU7fr e+rS2yu1i1h/bpP2wur3AzLjFO0en0ezNDOs9L9p+tFNql6VbZWjqETmCPPpleR99V4ThzCR 0yqgBz9Tjt+Fj8RtmTKSh95bCFHBXjcRn7uK1TS3Zfc7pFLsO/suW/AIVHnqSRnPBQEKAPHI PrQ832N9oqHErGnuUnI/wyP+etS0krtG0vaDCe0Muasq3BxV9aSBxgAJKlBI9wwPdXoTlrmA tybzj1WjJdDcDKhJ0dLjJDCu0gtFobC3uB2Y4xneM4+ApURovOvihJe7O3lOkeNSNStoSVeZ Cc8DPl5Uqj9fxQ6D0Vv1T/dq8iXbVrsNMl4WhgKPCXkOBWPLOCac+V9S/wCsWH/93+NVF8Ux coIjOq+jStKsD3Cqa36VTNhtSG2FbScYwT0J9/uoxrTuVzo0TP1UsZS7Y/1Hf41323VY6u2P 9R3+NAlm1XMEJKxFVICTjhWMeWOlXcbVjy+JEJxhGPrkggfhUFh3CIg9t1X/AM5Y/wBV3+NL 23Vfm7Y/1Hf41QTdVOspHs0Qv5GSonakfcKUXVbrn+Uxiwc8YOQr4cU5bqtQr/23Vfk7Y/1H f41z23VXm7Y/1Hf40PP6tkNuqSzbnHUDoskJz9mCacTqYqZK1R1Icx4WiRkn7qFjkV97bqvy dsf6jv8AGue3arzjvbH+o7/Ghv52zS2Sm1LCh0SVj+FPxdTrcSTJjlg+eSCP3UMbhuivVTtV JTuL1jA96Xf415Tc9ULztesRx6JdOPxqsuUxmfbXGXMKQ4MHpxVE/bn9OW9y4N5S0CgrPUEZ wDz6ZoGgtJ6qUYG5aoSBuesQJGeUuj+2ku5apbTuU9YgPel3+NB+ooS22PlecQlaUoDaVJx4 uoT9+T9lNagtT0Kzu3O4JW73CUjbjGCSB/bVtDcZUI0Tc9TrztfsRwecB3j8acE3VRGQ7YyD /su/xoG05bVzoiLjA3tlRKCASrByAR+Iq3sWpRMiBS1AKzz0P9lVkaGnBREKp2qkAlTtjAHU lLox+NNou2plglMiwnjyS6f7aoL5bZFwaXPkBbkdtBWhCc4KRz5fCqfTVs+VYSbnDbUy4FlJ AGenGM+ecVYRtrJUo8TO1UoAh2x9P5rv8a8KuWqEkhT9hBHUEO5H41SWe7TJLj8QpLr7J2LI HQgkc8e78KrE6fTcHnpAdDy0uFLih5K9OD6EVDGB25UIvM/VOcB2yc/7Dv8AGvXtuq+fpbH+ o9/Gg3S2oXpTeHVDAOD0I/dRUm6IKeoHHurM7qU+J2qv+dsf6jv8a6J2rFKISuyE46BDpz+P FQ03NO4c17N1SNxDmOOcHH3f7j8MEirpmuLlDkLZcm2fLf8AjVJiSlNtcZ8bgTsQMEElRGBy cDpaRrtqWWwl+NJsLrCwCh1CXtq88gg55BBBB8wc1CgLt409bmbWENsNZZ7vkqQEHalJSfEF AJKSDyDkHnNV2n31wPlFoIWzEM5a47axggKSkrIB8i6XiCeoII8JFERJ7bqvjLtj/Ue/jXpu ZqjvUF5VnU1kFQbS4FEeeMnGajfKiDjnHHoK8/KaQThf7qKESNT3DHaW6lAWtOSE9BxXJF3Y jMl511tttP1lrVtAPvJ6fbQ9NuBTGjlJzvB93l/96oH83K/MOSgHYbCN7TSuQXcjkjz8xiil Gfzts3H/AAtb8KzgmQge/wA1c8elL512gHBulvHxkI+H871rOGI85Ui4yyw+mQ3dQiKhSVJT 3BWkZ7v6hTsJ5I4A6+Ygok3q4+xsrcdWw9EiylvMQ0ILa1OpSpOSnnwYWQrP1PIZTWnLxuqk rVhquzlOflSB0z/lKP41z52Wf/pWB/4hH8azmczcYk64mOJTYKHXku+ytrW+4llgIzuQU4Ki 5wnGfh9XxYZ9/fjNy7lDLbzkxxhUZdsSUtI2FSThKQsncAn6x3biBg4NOX4pa0tOqbSs4Tc4 SleSUvJJP41O9vScEYIIyCBmgXT78hcRabhFHtLLpQpQaSQrgHKVJSkEeLg7U46HJSVKsJMt MJTTSM8jKhnO3J86zIo0rIhlX6HCKRKkx2Crp3jqU5+zNMDVdnzj5Vgc+XtCP40G2qK0q4S7 hNZLst5ZG5Q3BKM8AfcKhX966G5Jk2m1BaIDIcWCFNh8qWnclI27VkJQRyT/AIw4woJBlrbw oWgfOuz9BdIGeuPaEfZ51z52WcH/ADpB/wDEI/jWWxWrvbmbs/GiEmRPllhkxkkFPdKUhxAU jJ8aUAZO0jyGd1SWZ17j6y9ieYcetLTi97xgoJUO7BCdyUYBC8gcZJJyScJq3KPdRa0n52Wc /wClIHw9oR/Gn4t/hTVKTFlRnykAnunUqxn4Gs/sXtjtyQ/NDpS7bY6lMvRUoSHPGF8bBhQz z71Y8hgj7qO4424thLfdHcCE7KqRRpSiGRdhHa3qQVZWlGEjnKlBI6n1NdRdQp6Qjuz9Avu1 EYwTtCuOfePSgu4XPcy2B0Mlkjnr9Imnk3BQmXZIPHtmMZ/6tFQiKnb22yZQWghUZgPrHHIJ UMA56+A1IVNUjKSBuwPLpxQJNuCi3qBR5PsSAeevicqzmXLZKWM+hJ+wUpFZNX66TXX1wLbF MZDqmkuS5amiopO1R2pbXxuyOT5U77fqDP8Am60D0BuTn9xQj8uu2nR7k9iFInPpmSkojMcr XmQQccHpkk/Co1g1vcL1OUxM05MtTaGysvS0nYSFAbQdvXBJ+yiIugXy+3C2xZzVttSW5DKH kpXcXApIUMgEdzweRxTjt8ukMtOT4EBLCnm2VezzFuLBWsISQktJBAUoZ5HHrWdXUe02bSSY UCa7c0wmhEmNKKG4ClNt5dWRwQAE+AghWMcFVTYrsyJalRru+HZyrvHIkFxJMsd80QpKAB3Y wnGwZxtPJzmilad7d/1P/nT/ABpUIi6jHKwD6elKiKiQ8t5G9KSpOcEjy4FFdlvEW22BpuTh KmwtSxjoMk/uxWQPT30ICo7uM8kYqrkzbpMQWVvqDauCAMZHTmtBorKi1qem7BZLdo6Pc7i/ IkJeaTJW2nKgArBwEgc9R++rFxdknaFnXCFEcipMV8tNLSAsFKVeQzgZGaymFdLtbISI0WRh pA8KSnO34cV4kajvz7LjLriVJcbLavB1BBH7jioFVui0ez3iyDTMH5ywFxFux2wlYbLyHfCP ECjdjyyDip06y2S2XezLbluiM/LLRYcXvRktLKcZGRzjzx7s1k7N3vTMZttDxKG0hKQUDgDy 6fCo8iTdLk60Zclag2QpAxjaR5jFSSO6m1oeu7Zc3L7BTY0O+x914i0vb9JuOQeR5Y6/fVvq BmFFjaaSVITJduMdp/jkjaQv8RWZLvV7bSEpk78DGVIGT+FRDKuUm4szZLqlusEFGRwMHPQe /H3UJB2Ki0fdqQEB6zfJkhxnvO97wNr27sbMdPiauNUNxGOzYT29vtSmY6lK88lSMmsvuM2f dn2ly1BXdElGBjr1/dT027XF+3+wKWFRylKduPQgj91RfioRNBuPewklax05o6t1ytt50t7D NQhY7ruHU4646fuBrI4rndsJTjOPQV7XPlRUKVGc2lR5B86htdVKLO1DUTEly2WZhKSFKEpz jnAylP711f6yujd70NMYgpSt14NlCUjGQFpJ/wDSax4e1TbgqXNO5zATkgjjr/Gp65U2M3ti u4R6YyKYvKhanoqbGselG2ZY7tadzxSfIcfwFAGmG5bdrEsMrMZQ37/cCQaG5Mu5zkFl9090 eqQMZohg6qvNs078jRe6ETY4jCmskBRJPP2mpOkHCI4tWtJMSCEKtqpsZJ2traKQR7iCf981 dw9TwodldlSILVvCApxTCQnwJGeTtGMn+2sUZmTokZKGnSCOgxmo0l65zwlqQ8otA5CcYGfs FT8ClarpXUOn02B1+TLbiTZ7jjz6kkBYKlqIwT0wCMelX2mJFgtlsdZtktT7C3StS3FhR3ED IzgegOPfWKNQmkshJxjGDjzp1MyZb2C3CXhKjuI9/wDuKqNPVQiOSqzWi9Ij2OYZMVTIWoqU lZC8nIyAMcYq0TcAUZ3Cs8tkYsKKlnknPJJxV2mQUjg8VGOilEwuA3Ad5Xv2/B4WKFRJO7Of wrvtR55Gai1KJVvsLbfT3bX+Eja/uTuDo27cKScg8DHSkia2w02y2pKG20hCEpBwkDgADoB7 hQ17SfUVwyVE8E/YKWiKjP6eIVz28Z4UM5oXMk8c/fXRJVu8qIi65z9sKAc8kHp9lVaLopK9 zailQOAQSKrb46pEK1pUQlWwkj7sVN0Npt7U85yY4vZb4b4Q6kJGXjwdgz04wVHHQgA5JKCK V8uSwRmQ/wBOuT/7U23dnI7KGI7y2mW0hCG0HCUJAwAB6YqVpjTVsveqtRWu62MxF21UYpaj 3aW5t71KlHK+8AP1UkYSnGSMHGahfNFy03uAm92WI7bbjMERhu23WeuQyVBSkqUVOBKkhKFb iAnjxAcbTfS7ZQnhfJKekl0H13H+NIXyV/rTxHoVn+NEknROhol3hWp9qWmXN7wx0C5TCVhA yrkOYGMjr1oN1VYYUDXUfTlnZtccPQEykuXe7Tkbld6pGxJS9yTgEDHkahrSTSlT/l+Xuz7U 9+uabVdFLUVKWpRPUnOastY6b0hpbTsiabfMduHcOKYjt3GW74kgZUoB0fRpKk7lcdRjkgGX bNG6Td0VDv8AcYclpC7cia+WrjLISC2FqwkOk+ZwOfiaaTWpFSN3d5kktuqRkdUkivRvks9Z Tp4/nGrm56Q0ejREzUNrjSZDaLe5MjKXcZe1YDZUkkd6DjpxwfgaFo9jgWrRlx1NfocC4xGm 21RBZLvNKVlSighalukAbikZTnHi4OAKkNcRai1YfLkpPPtLo5/nH+NL5dkgAe1PADoN5/j/ AL4FSLDo62t3RFn1TAjpuL7SpLPydd5gSGgpCMLSt3IVuWMEEhWFD9Ebi7+S3SRHMOb+1JX9 5VSCN0CCBfJRH+Uv496iP7aSr0+sYXJdUn0Kj/Gjj+S3SX+pzf2pK/vK5/JZpH/Upv7Ulf3l QpQEuaHNu/xBKgsA5OSDkfiKc+V1d465sb3OOh1RwRk4xj4cDijn+SzSP+pTf2pK/vK7/Jbp L/Upv7Ulf3lEQIq5laJKVIR/hKQlzg5wMkY9Oprr13VIeUtYSkqABCQQOBijr+S3SX+pTf2p K/vK5/JbpH/Upv7Ulf3lEQI3OhqaLcqzW2VhxTgVIj7yFKOVEfHjPwFekzLOMf8Aw1Yxjn/I h1++jn+S3SQ/+Rm/tSV/e0v5LNI/6lN/akr+8oiCF3C1PuBx3TlkWtKEoSVRAcAAAD4AAD7K TdxtzT6XY9jssd9HiQ4mMErSR5p99G/8lukv9Sm/tSV/eVEu/ZtafkSRHsjPs9wIK47siQ89 4hjwkrUfCcEeeM5AOOSIOFzOOp+0HNKgqTd4kSW9Gl+0NSWlqbdb7patiwcEZSkpODnkHHpS oivjdWozCW37LHyPJTgycDPQjNM/OKAD/mRgfFSfy0b6E7NHGUOXHVzTE2Y8CBEeSh5ptKgg 5O5PDgO9PBIwrgnrRmdC6PAydLWP9ntflooWLfOSAP8AQsf7Fp/LXPnFbzz8isfrJ/LWynRW j05zpWxYAyT8ns/lp0aG0gQP/hWxc/8AZ7X5aJSxU6jgf9DM/Den8tJOpIA/0LH/AF0/lraT obSHUaVsZ/8A09r8teTonR6f+Slj/Z7X5aIsYOpLef8AQsf9dP5a5847eD/mVj9dP5a2saE0 f/RSx/s9r8tI6F0fn/irY/2e1+WlpSxUalhA/wCZ2Mem8flrvzkgZz8ix8j/AG0/lrZBonRx c2jSlj/Z7X5adGhdH/0Vsf7Pa/LRTSxj50QyNptDJHoVp/LXPnRDxj5HZx6Bafy1tB0Lo/H/ ABVsf7Pa/LS+Ymj/AOitj/Z7X5aKKWLp1NCT9Wzsj+un8tJWp4a+tnZP9dP5a2j5i6P/AKK2 L9ns/lrvzE0f/RWx/s9n8tEpYmdRW/zsscf1k/lr185IQT/mdjH/AH0/lrZ1aH0en/krYv2e yP8A+teRojR6iANKWMc/6gz+WiUsY+cVvI5szH6yfy135ywMY+RmP10/lra/mJo/+itj/Z7X 5a4NC6PPTSti/Z7P5aJSxb5zQP8AoaPj/vp/LXk6kt5/0LH/AF0/lra/mLpD+itj/Z7P5aXz F0f/AEVsf7PZ/LRKWKDUlvT/AKFj/rp/LXv50wiMfI8fHpvT/Cto+Yuj/wCiti/Z7P5a8q0P o8HHzVsWeuPk9n8tEpYwNUQR0s0cfBafy0jqaAf9DR/10/lrZfmTo4HHzVsRI6gW9r8te06H 0erONK2Pj/s9r8tLKUsX+c0D/oaP+un8tIamgD/Q0f8AXT+Wtp+Yuj/6K2P9ns/lpfMXSH9F rH+z2fy0s90pYsdTwP8AoWP+un8tdTqeGk7kWiOkj0WkfuTWzHQ2kAf+Ktj/AGe1+WvQ0LpD +itj/Z7P5aWUWAXW6ifK9plONtpCcBIPASOfwGefWtt0Uxcrb2dx91tcFwS086iG64EKWoqW UJJP1CoFOQRlOcHpVxD0lp22zW5dvsVrhyW87XY8Nttacgg4IGRkEirlISBhOAB6VClZlpNv V7Ovbzc7ppIw4V7LPeLFxacMXuWikcDle446dPfXizu65e1QmfetFIWh54Ntum5M7YEcqSTt QCdysjcVDBUQBxtTjUeKiyp8OCthMqSywX3QyyHXAnvFnolOequDwOeK05h7JVqFKcms3i3t R7WJEVwumRLL6R7MQnw4QeVFR4OOnnQnr61XG6yDChaKg3NT8QsovLz7SFRFKKgMBQ3nZ4Vj afM45rQhilhO7PGaq11Gwiz3W/Z/I1LAVLZutzanxre5HZjNSdjTyik8Kz/POAo5GQBnGKtt K2q6ac0DEhuIcnT48MKTHedSFF3YD3O8ZTtCspB6BIA6Ci3ivClJR1IxjqTVjK4t0nZKVQVS n9KOqdsiDLciKK7Up1CkqcKTlor+qQTwTjGD0oW0hpy5Ro2opE2xxLc1dNvcWLvkmO3ta2nJ QkpHeH62EngDOT1P94KSTwD78V0KAJP9tVDjRFbpSzjSGnLujVDV1kWGJp6DFYcZat7DrTpW tZTudKmwAMhCE4wfqeXFaUnOOfwptLiSTgU5kDzo9xcbKVS7Srwpe3yB+2vKnQlBWoYHrmqo naVMNS2HVvNtuoUthWx1KVgls4CsKHkcEHnyIp4KGM5qUXaVLIpZHrREqVLI9aWR60RKuFIN dpURRlRWFKJUyySTkko5NKnT1NKiIB1zqPUOm9zcKOZSbniLb3A42lUeWrIAWCMFspG8HnlK grgjFFcJWvbFeX13LUctFljloicm0MyW3MNb3S4hspdQ3uBTuAOM43DG4lGrdLXPUcqDi8Qo 8aBNanMMmCpZ3N54WoOpBTycgAH0I82ZegW7xJVNn3y5h2Rj25iC+uNElYG07miVkZQlCDhQ +rkYNdLXNDR64VUN6+FmkXeC7p/fI11KaakWx+M+raGRuUVhSlBrYUIcG3qd3TkmrJyTqVXa yLKxqd0Wsw03QsLhMK8HfBCmN2AcEZwrORkdcZNhcey6zzb2bvCn3ayylsoZWLZJDIKEgADG 04ACUDAwkbBgedSHuzmE5rAambvV7YmBaVd03My0UhQWW8KBV3ZUCSjOOTjAxgHtrdFX60m6 isl/sE2Jf1C3XC7RoLtv9laUAFKO494Ru5CTx5Z6jHOd6Zvd2nxLNq2RLdXfJOpGbU5JKykO RVNglktgbNuTnhOQrJGDWsL7PLc9q+PqGVcLnKcjuF5iFIkB2O0sjGUIUklODhQwQAQMYAAq WvRNmXqBm8FC0rbV33sqSEx1SMkmQpsABT2CRvOT0PUAiWStDQCPRChrTkjVLnaLe7fL1O5K ttnUz9AuCyDIS82VJBUgApKDjJHBx0TQdo/WPaLdpdsnBy4T7aFqXcFOWpttkMhW1RacQNzq gMnakBW5OAFc40m1dnkG0ajevbN6vbrrxJdZemlbbo2lCQvjcoJB8OVEg81d2DT8LTVnbtVt SpMVpa1NpUrcU7lleM9SBuwM84Azk80dKwA0L26eGUWNWHX51DriGhc3u5Lr8osy/bloS2l0 pbSw2lTOw4S2hxKVjxuBBKkkqQTDQEjVt1u1weuerBJiWq5yLe5FFvaQZOxOAoqHKeVA4Gfq 4J5NFFm0ZbbHHfYhuyQh+I1FX9MUkBvf40lOChRK1KJTgbvEACSTWaf7NoWm7um4RL7fnPpF uusPywpp5S07VFaQkbj0OeuUpOeKh72EHSKRT+0C/StOaGud0hn/AAptsJZJx4VKUE7gCCDt zuwRjg0M2C56mtWuINl1NqB+S7MjqcbbNpbSw6oJ3KDTyFBQKcHO9IyAeBuSa0V6HHkxnI0h lp5hxJQttxIUlQPkQeCKE4PZnaYVzbmm43iQY7bjUNl6coohpWnYQ1jBThPhBJJ6dSARnGWh pBVigXVOpdaaPmXaC7qlM91q0tTmHjAZaKFGU20QRgg+HcMk48XTIqygam1XqrVnyGi6L0/P i2nvJrTcRt1LcpLwCh9IjKkqbUlQ2qIGRgqwckjHZXYkWy6xJT0+c/c0hD8+XI3ydqSkpAXj gAoSenOBnIAAvkaWtbep3NQtM91cHoyozykcB1BUkgqHmobMA9cHHICca8yMDbKqsth23WWv uyeXLkagE1U9hSWoC4rTO1xuQCCHE45IbUMHjx9RjNFvZoi0QU3W2Q7O7ZbjFdbM63mWqS22 Vp3IUlZJSdyeuMEEYPAFX8PSFvt+lfm7CemRoQ390tmQpt1rcsr8Kxg8E4Gc8DBzznul9IW3 ScV9qCXnnpLheky5Lm999RJ5WrAzjJwMY5J6kk1kkDg4IFG18m8NaZlXGzXty2vQGHZKkpjN upfCUFW07wdp44I9eQeKDpGp7/pzs4Zvt21AJ0q8tR0QlqhIaRBccQpRWopCt4A5wEknZjGF cahcILFzt8iDJBVHkNqadQDjchQIUMjkcGqCZoOyT7ZZLdMbdkxLRs7lp10lD2xvYO9SPCry PTyx0JBqx7QAHBSUAxe1Se6NHvtKk3FDipkW6x4EYOOSnWkI2KQFIQQDvS5gYwFEH6ppiXrT VErQGotSxbvJguW68uNIjOQ2SvuCW0htQKfCpO/qcngg+4+i9m2nLfqtnUUCMYctoABEchLO Ni0HwYwMhQzjzQkjGVbmbt2ZWW7W+dBMu5RWJs9c95MaTtStagncFJIKVJyhKhkEg9COlaiS K8BRSpZkrV69TQNJR9U9zMZtjk+TcRbWlKk5eCEpLR4Tt55CufTpQvPkXPU8tCtTW6632x2i VItjrFoRgyZbZ4fcbSUlKShQ6KOFJ4xuwdMd0JGes0SCq83oSIiHENXFM5SZO1xYWoKUBhYO 1I8QPA9eaZV2b2hOkG9NQ5dwgQgve85EeCHZJKSlXeqKTuCgeRjyAGAAKgSMH/PVKWWWCRK1 tI0/E1Be5DcCBZnbi46F92sOIfdZS53nGCkBtW45+p0yomnHdcX9GiLBOhasXHuciL3Tdqbg JkPy1pfU33pcUCQVJwTn6xSrHU41S7dntju+no1nLK4TEZKkx3YZDbraVAhaQog5CwSFZHiz k81Wz+ySwS50CXElXG1Kt8cR4ybdIDW1IKiTkpKtxK1ZOcnPPJJNxNEXWRhKUROrdR6Mslrf 1oxHfYknEuey4hK4q1E7UFoY70jgkt8gBXB27lDCNbal1SvWF2sepTAtdmbLseOYLbxeSG14 VuUkFIX3e7ocb8eVaDaezmz225t3OQ7Mu09ppLTUi6ve0LbwtSgU5GEnKscdMcYJUS3rDs9h aqjPpRMlW591P06om1KZSgAEF4YysJIGORjJxjPGYdHq29+SZWZa1euOsGWr5A3vTbXZ4j8p DTqo6YDrmJBeb3Kws7UbSPLKDlRT4bS5a11Lc9bTotmvV2atAREdjrgWJExKEPMoXuczhYBy TwCThXHGKLrh2XW68stCZNehOlpLUlFnSIzEhCD9EFtK3hQQMAZz9wCRJn9mltl3N+fDut4s 6n2223WrVL7htfdp2IJG3jCcDAwOBx1q4ljqq2/hEH3G4a3hdpdr0kzrRakzYgkKlO2yP4VB KyrCQBkEtnHIwFY5xlVdee0zVNpjatDrim2mLm5FtU0MJO1aHk7mSnaUkd0SQpWDwrBJ6Gkr slt8q5s3I6k1Kia00GkSE3DLgGMEhaklQzkkgEDxHAA4q3ldnmn5dsusB1hfc3GYucs78rZf WkBS21HJSeCec/WI+qcUEkQIsXjt4pSza3671lI7T0Wpuap+Ab1JimOuK0ltLDZ8W13AJUlB JIzkYT9bdiitFvjar7Xbk5cWypGmmIojsB1W0vuHvg8MYwQEhGDndgZ9KvfmDb0Wu5w2Js9p c64LuPtLbqUPMOqxnulhOUjGU+Z2qUM4JqXPscsakavlsnbH+7ZiyIz+5TDjAdKlKATgh0BS tqiSOoIG4mqPla4/CKwiz+yah1dedfT4Kbxc0QY92fYGyztORUttknYt/goJHh6E8p55qx03 c9WWjULEXWd/cHfr7hppy2oEd9aivZ3clBACsIB2rSCQcBOSCL5rs6hx9QuXiHeb3EL0r2t6 HGlhEd1wkFW5G05CiDnnPPUYGHI3Z5bWLw3Pfn3KY2w6XosCS+FRIqs+EttbQBtHhT12jpzz UukYTgY8kWN3Ttd1edK2FyPImRpjiXxIlLgtdzLIWAgtEpIO3ocAcnz4o60Vc772htuKu00R 7axDTEnWvu0lyaXGlHvioBKmkKC0lGOu04PUm9k9k2nJlhs9nlrmvxrU44tpZeCXFha96kLK QAUkgDjBwOCOtWzGirfEVZXoz0hiXaWERWpDak73mEgAtO+HC0nAOMcHlO01L5YtBDG0e6UV nsHTkqLftQxdE2qXaIMKLJhuuplKzOlFlBaQEunLW0ubg4OCOhANCd01HP7O7HBtmn4r1mmu tlu4Ikq3qcfR3YL7aFlSQhWFJStIwsbuPAMfQ0O3JhOSlJkyHkyHi8UvvKc7skAbUZ5CMgnb 0BUccYAobPoG12a6XWcXJNwcuaA08bksSCEc/RhShuKMEAhROQlOTxUMnAPxC1KD7JYZOmtX P6Rsd3fhIf0+mY5ISkOAzQ8Ed8EOFQTuAIUkYyMDqAR3Tl31xN7LZWp2roLncXilyHD9ibSE JbeIdT4cFe5CTgcHjA5orgdndqtsSczHmXLvpLPcIlqlq7+KyDuQ0ysfUQk87eQeitw4qTpH RUXRsR6LDuNwksuAJS3LfC0MgEnwJAATkqycdcCodI3T9OiikCO3iJ2hXSSm/wARw6XtllYu Uxgqx3UpxHepIUjDi0hpSx0AynOM4Nd0LAe092WX/UdvL8Nc1iRNiQ3fEiGlAc7ogqHiJTtJ VwFDbx5k0j9n1liafu9kj+0NwrpIW+6ltYbLRXgBLe0DakADA59DkEiiEW6H8mi3CIx7GGu4 9n7sd33eMbNvTbjjFQ6RtU0Yx6KaQBphmyaD7OTqmQZZcmw2Zk+RvU4664sZTgHgEqcIHTOQ VcAkQrxrnVUSzW27P21MJuTeozbTMJ1uYuTFLZUtKSnIJUQdpGCc4wMbia6as1zsMc2yRNjz LdGbabhr7oofQhO4bXMHacJDYCkhOecjzpiXoK0SZEZTTsqKxGlx5jUWOtIYbcaKyNjZSQgK 3+IJxu2g9SSYD26iXC0WSWnXus9S9orlijXxy0xnZUhLQkW9kuRkoClJQtJHUBO0jOeTzRvY Z2pb3I1JppGrUrnWmSyU3dqIyoKStB3NKZxt8KkrBwrdnGemDMmdkFgkXuZeo867QblJfL5k Q5QbW2ohQXsO04Cisk/AYwMgyWuyyzRtLrsMWbco7LzxckyGXwh6SCFAocUE4KPF9XAHA9+d HyREYFfJRlUdo7S5MDsrtF6ugM+7TXFNNBzDDbig8U+J0I2N4Tk5VjIQr0Jo90vNvM+0+032 3tQJi3V4joeDhQgHCdxAxux1wTnrxnalm2aStNt0yxp8RkSrc0nHdSgHQ4d2/coEYJ3c9MZ6 AYGJ1otEeytPsxVu9w473iGVL3IYG1KdjYP1UDbkJ6DccYGAMJHNN6R1QKzpV53CluFZqy4e ppVwnk0qIvnrtOuV1v8ArtLWn4lxuC7ChBachsh1LEkqCypWEq3DCUp2kjxJPoQVctKv9pGv tQPWly3mOpuA57W/3wdQ24ylQU2gYSokDkL9E8jrWodnEW6uaYbut7uLcqRdG25SUtx2mg2l SRgkpSCpZATuKum0AZxuUS26xWizF35LtcKCXiO8MWOlvfjOM7QM4yfvPrXUOJDR8IVdK5aW HYNphxH5S5bzLCGlyXMhTxCQCsg5OScnkn41NzXvYgJ6dBSCE8YGeK57CleM0s172p48P3ml sH82moJSb3Ut1ObUeacc4586gi5wDcTA9qj+1Ja79TPeDeG843EZyE54yQBUgpSl5pZr1hP8 2koJA5GOfjUaglLwFA+dLdVZB1HYro6WbfeLdKfCd5ajykOKCR1OAcjqPvqVCultnvyGYk+J IdjK2PtsvJUplWTwsA5SeCMHHQ1N+CUpWaWacKEDyrgSn+ac+lRqCUvGaWad7tOOleSlOMgD 7TSwlJvdXc1GhXCHPL3sshqR3LqmXe6WFd24MZQrBOFDPIPIyOKl4GcbeaWlLzmlmvZSkeVd CEk9KagibzSzTikJHkK8hKecpxjr1pqCLzmlmvYQnHSueDOMVNhF5zSzTgQn0rhSkZpYSl4z XNwpzanpjmoMu7Wu3yWI024Q478hW2O06+lCnTkDCQTlRyR09cUtKUrdS3VHdnw48uPEfkR2 pUnd3DK3UpW7t5O1OcnA5OM1JRtUyFkDpnIpfglJZrm6q2RqKxRbiLc9doDU4rS37MuSkObl Y2jbnPORUj5Tt6bi3b3JkVM11JUiMp1IcUnnkJzkjwq+73U+SUpeaWa97E5+r9uaW1OelRYS l4zSzTobT5ivJCR5fvpqCUm91dzUZVwhC5C39+0JndB4sFQ392TjdtznGQRn1qYUp8gPf7qm 0XjNLNetqc9Bzx1r1sTjpmosJSbzSzTvdp9K4UpHlk/GlhKTeaWa9lCf5ufgaW1Hp9uaWEXj NLNe9qMgY5Nd7tPpTUETea5up0pQD0qBcrnb7S2l2fMiRGVLDYdkPBCdx5A5IGcZ8/LzqbvZ KUvNcKsDNek7FjgpPP6JyP8Afg04G09cH76iwib59KVe+5R6K/WNKosIvmy8pgG7aT+ULTFu jXzRhFLEm5JgpCskBW9RAJ6jbnzz5VfXaDp20S/lOVKjT7dFYjOw7W5qJTcu1jaCsM4cIcJT tWMLGQkJTkYNXbd30dE0rpiPfLMm6T02WKte23CSqLG2curUU+FtKhz1xkeHmpc7U/ZTEkNs TWLWlbTDZZbValq7tpxIdAA7vwghZVjyKuecgdTXO0tFFQd0O3HRml7jrHRDogOGPf2pMqV3 7qkrkK7lLiSsIVtSdyiSEYHOOmANsjNdxGbZHeFDaQkFxZWrA4GVEkk4HU5JqgtszTc6OJkR MPuLNuZZlKYDaIyS2lRLalDhBbUg7k+EpIwcVStdrtgl3kWy2w7pdFYbWX4Ebvm0oUEkrIB3 hKd4CspyCCMZFZO1yAADZTgIQ1BZ9Fq7XtPJjPRe+lS5ZuPcz1bkyAApvO1eW194SABtyrjH lRPZL1Egdqus4lwurEcPOwfZGHpARvcLISrYknlR8A456U3f7v2fW+9yo9ysMZ59lQXcZSbU HGoynAFgur2ZJXnjGST1wakPX7s2u+ql2uU3bZN574xyZUDJLiSRt7xaME8YHOOABWpstFg7 KLQJCkJsemntSuS1udo8iQN0OW8oPr3vJQGfZspJQpvBCSnICgUkbU4qNT7YjV0djR2EaqTr Jx2MkMhUstFJU2Qk+JSCopxxgkjFaVqYaMvOnJmoRNbtcmO73S7xEZU3KjPAd3sWkAOHghBQ oDwkdOFCwa1Noo6mgwn5sORqBLSGmpj0Yd45vSCkh4ICfGleRtIB3YAHAoHncA+/slII0fpr Qr/aRfo0YxHY7Xs6bW23NKg6lbSi+E+P6VJ5CgdwxkHjik7Juci42Xs+fdS2Yd8KN6ZRQ4YM dtLrIWGzypST4SMHLSfMEgwVI7Obfq1uzG32qNe23UBpKbcEbF4SpG1ezaFYII5zyAPKmW+0 fs0lX2NNM6Cbik90zMehuJU2CSMBxSAEg71Z5AwTnzqdbibDScJQQVocw9Faoahuv2PUDLjM pcB60MNOy0KbSpeFKGCkrRvSAVLzgJB2gmmNCwrXH7Q7BIamW96PLYkOwIsFSFPw1raCi1KU RvUEpLqElRJ8A6ZIGy26xWO2Pl+22aHBeKe7UtiIhsqHBKSUjkcDPrt8xT6LBZWZq5zVpgom LUpZkIjIDhUc7juAyeFK+O4561Tnb43CUsT7JIdjlw5Httpixz7BJMq4KvW0uslW1SXI6VAo TtV9YjA2JV1INFnY7AsUaTqRy2LbLjVzeYbS1KKkmKCO5JTuIUPr7VnJxkZo1GktMMub2tPW 1ta0LbUUQ0DKVZChkDoQVA+4488VNtmnbPaXzIt9rgRHVpKVOR4yG1FJOdpUkZxwD8QPhSSU O1VeUAooW7X7nfrVo1MiwrlNu9/iS5Ga3KbY7twqUTglABA8QwU8EGgRq6RdLvXqzdn9uel3 BMFlSJcSSiciSkLSlTq0DJQtClrASjIysqUnaBjeFgKGP7M1V27TdktD5fttpgw3VJ2qcjRk NKI9CUgccdOnSqxyBjaIQ5WSdlE22Q9L3+wXeNMjW/v3vapk5r2ZkJIaaLK17vA4c8o68nk9 SNXNmM3dp9s0fMZbho1BajbFtvd8wh9TLmVg+LPjCdx8X1QCOAK+hFWK1riyIq7fEVHkrLkh pTCSh5ZxlS04wonAyTnoPSvDWm7Iwwhhm0QG2UPiShtEVASl4cBwDH1sfpdavzxqLq3SlhEe 1QdW/P663yKt+7WuA0lS3nNpblNxlocUA2QlXja4HIwnPurWOzPT9us+j7fKgtOIduMVmTJy +taVuKQCVhJJAJz1AGcD0olVZ7ctUta4UZTkxCW5S1MIKn0gYAXx4hjIweOakxozENhDEZpD LLaQlDbadqUJAAAAHAAAAwKpJKXDSMf8UgLN+26yQZ2hJV0ksbpdvSn2Z3cr6PvHW0r4Bwcg eY4oS1JZ7Xa+x7R5YgNlidcIUuUyqSW0vLWwd+XFKwgHpngJ5PlW5ToUS5xFxJ0ViVGcxvZf bDiFYIIyDweQD8RUOVp+0zoLUKXbob8Zn/FsOx0qbQcEDCSDjg44qYpi0AHYKFjtzs9tc0tp mQWbRDtDapj67HL1Ee6kL4SjunwSkqBBVwQAVkHqo151jB0rfOymXfrbHfVMs2y3R3X3AVx0 pfSA3lsltaUpcwFeLIUMqJzWufM7TYjpjfINq7hKlLQ2YTe1KlABRAx1ISkE9SAM5qV8gWj5 JTafk2F8mpVkQxHT3X1t31MY+tz8ac2qISl7sdpg2G0sWu2td1DYCu7R3ilYyok8qJPUnzrM O163adk3XTz9wcjJmKuEZiUFSSgiEVL3lQ3cJznx44ORmteGBVVO03ZbpKTJuNqgTHkJ2Jck RUOKCeuMqBOOTwMdTWcb9L9RUlZamHpiVryUxfbkhizWuHD+bzblwLDYaLYUXWlhQUvBRjdu PTk+FOA2QuQ7Z5OpL5brVPuN8te1KpMpEd6JtCmkvJZXy4pYQhYUgA+EhOAed/k6S09MLRlW O2v9y2GWu9iNq7tsfVQnI4SPQccninZWm7JPZjMzbTBktRU7Y6HoyFJZGAMIBGEjASMDHQVs 2YDoopYEW7E5Yr05qTYHmtO25Nm9pUQrxR8juR5/SpGSAQPHnhSqvp0Cx3DXmhnrsWkXu4NB y8JEhTDyHxHbLO4Agtq3AYACdx6elbHcLFaruWTc7bCm9yCGvaY6XNgUAFY3ZxnAz8BUeZpT T9xlOSp1ktsqQ59Z1+G2tZ4CeSRk8DH3elTzwTde6pKWT6zjW7TnaBP1NcJen7lDWWBOtDwa XMACEtgtoUFYwFBfVOQAD61V6zlW9Gu39TF+NBNru0cTYEhSfbZXcqRh5lJ52lKsAApSUtBR yThO3u6aski4C4P2mA7NC0rElcZBd3J+qdxGcgAYPupyRYbRLmsTZVshPS2NvdPuMJU43hW4 bVEEpwrkYPFVbNVYQrGp0e0Su3K7NXS2Ikhb8JDEgXURXYqiynaW0b0KdJVt+oSRjjJODaxb VpZPb+pMRbAX7EuUe7mnd7f353p4V9baVbm+mPLFaRN0np+4SXJUuyW2RJdxvffiNuLVgYGV KBJ4AHPpSGk9Pib7YLNb/au873v/AGVvfvznfuxndnnPXJqTMD32pRSf1A/MjaXub9tSpc1u G6uMlKN5U5sJSAkdTnHGOaxS3SrdY71Y7pOzeNTXJ5HtT7VwbEuLIWNpjGKrCEpx9GScFOVD wYQBvigVNlO7BI6gVTnSWnjcDcPkW3CYXQ+ZAiN953mc792M7s85655681lE8NsEKxWN6Ivt yY7S2Jd8s95N3nW5Measwu78apACXlJ42tBAbSVADlJ4867rNnTEXUKZGl5sdyRc7fd1XIxJ peDuY6ljeAogDfuUAAOR0yONz+Tofyh7eIrAmdz3HtAbHed3nOzd1255x0zUCNpWwwi6Ydmt sfvkFp3uoiElxB6pVgcpOBweOPdWpnBdqrpsopYlbPlTUuoNH6d1a69Nbkxn5G8r2JfiOMIW 0lSkEKKkuMkqCv0kpOSMGjDsq0raYd01DcI8VxqTBvcqDHKJDgSGEhO1Ck7sKA3E+IE5weor SE2i3IMUpgxQYiO7j/QJ+hTjaUo48I28YHGMCnItvhwu89mjtMlxwvOFttKe8WeqlYHJPmai SfUCAKQYULUmmrRqm3Nwr1EEqO26HUoLikAKAIzlJB6E/fWUaLsNui9hl1vUZlSJ0+1zRIcQ 6va4El0J8JO0YAABxkZPqa24845xioaLVb2rcu3NQozcFaVJXGQ0lLagrJUNoGOSST65NZsk LRXiFJWFabtlsuXZjeUWz2OwT3I0ZmRMcvu9l5KinJdSlX0alYWnapIPjKQSCQJYd0te9H6i 02xCUl61xXp7EZqeZUVDiULw8w8PEoELQSlXGSfDkLNa01pDTrCHUM2O1NJeSEubILad4Cgo A4HIBAIBzyAadi6XsMGPJjxLPb47EtITIbZjJSl0DPCgBgjnoeOT61qZhdqKVF2ZaatNk0pA nW6N3Ui5QY70tfeLV3i9mc4KiBypXT1+Fee1WDZpuh5xvC2090247D7x/ugZIaXsx4huV1wn nPpRjGjsQ47bEdpDTLaQhDbaQlKEgAAADgAAdKj3O0268sJYucGNMZSreluQylxIVgjIBHBw Tz76xDzzNZTosVTFsSbL2d2uZMKNP3GNIeuDargtDCnQ0hR3HcAnDvO3IAUTgcmoIjR59rRd HnIFytWnr7LhwIE2ehlt6OpLamkpeWSFBGNwCuqQfJODtfzS0/7F7CbLbjD7zvhH9kb7sLxj dtxjdjjOM44rvzT098nJt/yJbjCS73wj+yN7AvGN23H1scZ61tzglIV7IpTsjTVwVlKoIu0k QFNRSw0pgqBy2g8hG5S+MnHIz4a0YVEiQosCOiPDjsx2EfVaZbCEp8+AOlSd1YSHU8kBSvdK vG+lVFNrFoCrnp1Om9UxrPMukVWlWIKGYKN60vDa4CseSDjG4bsenTIxKtl8tqdEW1zTd5kO 6ekGRMXGiqeaUHHkPbG1DhRSkFJ5A3AgEgZrZtEknQGm+SP+DI/Q/wDVpq9USQBx7jjkf781 1tlI6KtLI+0uFqBD7l40xb5Mpq9W72Ke01EX3gH1kOrRwreUkoBUnKAnHmnFfqPTzVl1PFd0 zYtUPXy3ohsMSUtf4FJ2pQgFxYIIHd5QrBSnI58ydtO0Y2kgefTmueuD59KhshAApKWF65te oJmq50q7WGbcHYq23LN7Fbw7EcaDmVIkEDechP1d31iojwqGZKnbkxa9aacOkbxcJF2u0pyK 6YeIuHCEocK1cDbt3g4x05HUbWef0levXqen7uKROfrYPxH31YTUAKUUsItViu51zD1bcLFN ehW8MRZDrkZxciU8ljYZIac8a0pcCTkAKxtONwVgt1NcJmpL9ZLRB07ek/J18ZkuzHoYbjKa aKypSV55yOnTPlgkA6UMAcZz7zXABkZ6DyA4PxzUGWzdKaWU6uN01Zr/AEs1BsF4bbtFyWXp MiJsZWgLQStLmSkp+iURnGcpx1FUjsiXqvXbNy1bpfUZtkVRagxW7W6trbvJDj4KiTgFO4IH i2jrjady8JwSAT6kUgTwVHnPUfHNS2XSKA6UopY7p2xvN6xjXq7WiYzYUNS37RBdiOLVAcDu /wATaEBKVKBUUA5PCACSlOHtG2h6LqNu83a33JuEj216x29MVxIt6O8WpaXWkJ8K1JV4OuRw MkIA14lIIKcpUBjIrm47QkE4HTnzqpkJvClYx2V6cmw9TiTd7VcGQiAsWxMmPkR2jIWVNrWU p+lySoeqVH1AG2bvLJOOKZyMAcn4nr9vWvW8+ZzVXnWbpE7upbqa30t9VpE7upbqa30t9KRO 7qW6mt9LfSkTu6ub6b30t1KRO7qW6mt9LfSkTu6luprfS30pE7upbqa30t9KRO7qW6mt9LdS kTm+u7qa3Ut9KROb67uprdS30pE7upbqa30t9KROb67uprdS30pE5vru6mt1LfSkTu6luprf S30pE5vru6mt1LfSkTu+luprdS3UpE7upbqa30t9KRO7qQVzTW6ubqUie3UqZ3+6lVKRD+iP +IGm/wD8Mj//AMaavqVKtQpSpUqVFCVKlSoiVKlSoiQpUqVESNcpUqIkK7SpURKlSpURKlSp URKlSpURKlSpURKlSpURKlSpURKlSpURKlSpURKlSpURKlSpURKlSpURKlSpURKlSpURKlSp URKlSpURKlSpURKlSpURKlSpUReaVKlVEX//2Q== --------------000307000908040405090704--