new solution for week 1306/ SPOT2 January 21, 2004

X-Sympa-To: ids.analysis.forum Received: from hector.cls.fr (osis.cls.fr [62.161.32.21]) by hermes.cls.fr (8.9.3/8.9.3) with ESMTP id AAA08458 for ; Fri, 18 Mar 2005 00:39:44 +0100 Received: by hector.cls.fr (Postfix) id E03FD944B; Thu, 17 Mar 2005 22:39:56 +0000 (GMT) Delivered-To: ids.analysis.forum@cls.fr Received: from nmta1.jpl.nasa.gov (orange-102.cls.fr [62.161.32.13]) by hector.cls.fr (Postfix) with ESMTP id 3F145148B0 for ; Thu, 17 Mar 2005 22:39:55 +0000 (GMT) Received: from xmta1.jpl.nasa.gov (xmta1.jpl.nasa.gov [137.78.160.144]) by nmta1.jpl.nasa.gov (Switch-3.1.7/Switch-3.1.7) with ESMTP id j2HMdrQg029300 for ; Thu, 17 Mar 2005 14:39:53 -0800 Received: from [128.149.70.153] (mac01120073755.jpl.nasa.gov [128.149.70.153]) by xmta1.jpl.nasa.gov (Switch-3.1.7/Switch-3.1.7) with ESMTP id j2HMdqSm029934 for ; Thu, 17 Mar 2005 14:39:53 -0800 Mime-Version: 1.0 Message-Id: Date: Thu, 17 Mar 2005 14:39:53 -0800 To: IDS_Analysis_Forum From: Pascal Willis Subject: new solution for week 1306/ SPOT2 January 21, 2004 Content-Type: multipart/Related; boundary="============_-1101023301==_mr============" ; type="text/html" X-Source-IP: mac01120073755.jpl.nasa.gov [128.149.70.153] X-Source-Sender: Pascal.R.Willis@jpl.nasa.gov X-AUTH: Internal IP X-Validation-by: feissel@ensg.ign.fr --============_-1101023301==_mr============ Content-Type: multipart/alternative; boundary="============_-1101023301==_ma============" --============_-1101023301==_ma============ Content-Type: text/plain; charset="us-ascii" ; format="flowed" Dear colleague, following the latest email from Philippe Escudier, stating that this week was suffering from the effect of an important geomagnetic storms, I reprocessed the DORIS data using a new strategy that we specifically developed at JPL for such cases. Additional information on the method can be found in the following manuscript that should be in print soon: Effects of thermosphere total density on LEO orbits during severe geomagnetic conditions (October-November 2003) using DORIS and SLR data, P. Willis, F. Deleflie, F. Barlier, Y.E. Bar-Sever, L.J. Romans, Adv Space Res., in press You will see in the updated plot that the DORIS/EOP are now very close to the GPS/JPL solution (no bias no drift was previously removed). The RMS differences (over 7 days) between DORIS/IGN-JPL and GPS/JPL EOP solutions changed as follow: X Y initial submission 8.50 3.49 resubmission 0.95 0.68 All geodetic products for week 1306 (05016) for IGN/JPL as well as the relevant documentation were resubmitted to the CDDIS Data Center. In the new strategy the orbit is less dynamic and is more fitted to the DORIS data themselves (drag estimated more frequently with some constrains). This could mean that the IDS Analysis Center could gain some precision in the geodetic products (at least the EOP) but relaxing more the orbit and giving more weight to the DORIS data themselves. The final tuning of this relaxation need to be investigated in more details and compared between groups. Many thanks to Philippe Escudier Pascal -- Pascal Willis Jet Propulsion Laboratory, MS 238-646 Ph : 1-818-393-4748 4800 Oak Grove Drive FAX: 1-818-393-4965 Pasadena CA 91109 Em : Pascal.R.Willis@jpl.nasa.gov --============_-1101023301==_ma============ Content-Type: text/html; charset="us-ascii" new solution for week 1306/ SPOT2 January 21, 2004

Dear colleague,

following the latest email from Philippe Escudier, stating that this week was suffering from the effect of an important geomagnetic storms, I reprocessed the DORIS data using a new strategy that we specifically developed at JPL for such cases.

Additional information on the method can be found in the following manuscript that should be in print soon:

Effects of thermosphere total density on LEO orbits during severe geomagnetic conditions (October-November 2003) using DORIS and SLR data, P. Willis, F. Deleflie, F. Barlier, Y.E. Bar-Sever, L.J. Romans, Adv Space Res., in press

You will see in the updated plot that the DORIS/EOP are now very close to the GPS/JPL solution (no bias no drift was previously removed). The RMS differences (over 7 days) between DORIS/IGN-JPL and GPS/JPL EOP solutions changed as follow:

X Y

initial submission 8.50 3.49

resubmission 0.95 0.68

All geodetic products for week 1306 (05016) for IGN/JPL as well as the relevant documentation were resubmitted to the CDDIS Data Center.

In the new strategy the orbit is less dynamic and is more fitted to the DORIS data themselves (drag estimated more frequently with some constrains). This could mean that the IDS Analysis Center could gain some precision in the geodetic products (at least the EOP) but relaxing more the orbit and giving more weight to the DORIS data themselves. The final tuning of this relaxation need to be investigated in more details and compared between groups.

Many thanks to Philippe Escudier

Pascal

--

Pascal Willis
Jet Propulsion Laboratory, MS 238-646     Ph : 1-818-393-4748
4800 Oak Grove Drive                      FAX: 1-818-393-4965
Pasadena CA 91109                         Em : Pascal.R.Willis@jpl.nasa.gov

--============_-1101023301==_ma============-- --============_-1101023301==_mr============ Content-Id: Content-Type: image/png; name="eop_week05016_corrected.png" ; x-mac-type="504E4766" ; x-mac-creator="514B5054" Content-Disposition: attachment; filename="eop_week05016_corrected.png" Content-Transfer-Encoding: base64 iVBORw0KGgoAAAANSUhEUgAAAt4AAAJACAMAAACNJpFeAAADAFBMVEUAAAAC AgIFBQUKCgoMDAwREREVFRUZGRkdHR0hISElJSUpKSkuLi4xMTE0NDQ4ODg+ Pj5BQUFFRUVJSUlMTExRUVFVVVVZWVldXV1gYGBlZWVpaWlubm5ra3JxcXF1 dXV5eXl9fX3dCAb/BwX/CAX/Cwj/DAn/Dwz/EQ7/ExD/FBH/FxT/GRb/Gxj/ HRr/Hxz/IB3/IyD/JSL/JiT/KCb/Kij/LSv/Liz/MC7/MjD/NDL/NjT/OTb/ Ozj/PDn/Pzz/QT7/Q0D/REH/RkT/SEb/Skj/TEr/Tkz/UE7/UlD/VFL/VlT/ WFb/Wlj/XFr/Xlz/YF7/Y2H/ZGP/ZmX/aWj/bGr/bmz/cW//c3H/dHL/dnT/ eHb/enj/fXv/fnz/gH4AANQCAtQFBdQJCdUNDdYQENYVFdcYGNgeHtgiItkn J9opKdosLNsxMdw0NNw4ON09Pd5CQt5FRd9KSuBOTuBSUuFVVeJZWeJeXuNi YuRlZeVpaeVubuZxceZ0dOd3d+h6euh+fuiBgYGFhYWBgYmJiYmNjY2QkJCV lZWZmZmdnZ2hoaGlpaWpqamtra2xsbG1tbW5ubm9vb3/g4H/hIP/hoX/iIf/ iYj/jIv/jYz/kI//kpH/lJP/lZT/mJf/mZj/nJv/npz/oJ7/oqD/pKP/pqX/ qKf/qaj/rKv/rq3/sK//sbD/tLP/trX/uLf/urn/vLv/vr3/wL+MgeGBgemF heqIiOqNjeuPj+yRkeyWluyZme2dne6hoe6kpO+4tO+np/CqqvCtrfGxsfG1 tfK5ufO9vfO+vvTBwcHFxcXJycnNzc3R0dHV1dXa2trd3d3/wsL/xsb/ycn/ zc3/0dD/1NP/1tX/2Nf/2tn/3Nv/3t3/4N/BwfTFxfXJyfXNzfbR0ffU1PfW 1vjZ2fjd3fnh4eHm5ubo6Ojq6urt7e3/4eH/5eX/6en/7e3h4fnl5frp6fvs 7Pvu7vzx8fH19fX/8fH/9vbx8fz19f35+fn/+vr6+v3//v78/Pz8/P7+/v5v Srr9AAAgAElEQVR4nO2deZwrR33gf5JGmvt4c2jO9RxqHi+O17A2Z3AC4XSC uQIkHAmRD+4bJwbCscl7O++YNzfLOgnLAvGyjk1YEpZAACdrG7OZewwmDnE4 Qsjozfgmmmej5/pju6q6W9VSS+qrWq3W7/t5b7q6u6rPr0rVVaUuIAgSWaDe B4Ag8kC9kQiDeiMRBvVGIgzqjUQY1BuJMKg3EmFQbyTCoN5IhEG9kQiDeiMR BvVGIgzqjUQY1BuJMKg3EmFQbyTCmPQGxB/qdTeREqDiDOIW9Ds0oN7+g/l3 aEC9/Qf1Dg2ot/+g3qEB9fYf1Ds0eND7/M03P8BD37n5O+SBmxlfvE9b+6U/ IeQ+tugL9xWTfOmTV732M9/lMw/yFF/4Pp+9+VY2uXDTG6567aceFHekrSEX vvjJl7/xVm2f9+pLyS1fYJN/uJnP3n/zPcR8NPfefK8W9f7XP+boFN2BeocG L7n3rysvYtN/Ovak75IvKhovYf6df+rnCPmctuiSP+EJvnspn38hs/duPcWx N6lzjymX0IX3PJ0v+tPibrQ15PtX8OhXMUVvVBTN51+8lE1e/Dw++3nldcR8 NDcqN+rbuuJNzk7RFah3aPCi94OXKp+l0+crn6BCPe+WW265+ZPPUX6VLnv9 ZReo3leqyz7zmkuUl6tz5JZjymvuPn//F56jXEaz07uVK9S1t3z+TZcqb9Ql fuzpyp8+QO7/7MXKLcZudPGPKb/xnfP3/PEVyvPprKr3Ux5i67ne549qnwhN b+FoBL2/ePQfnZ2jG1Dv0OCp7P0F5eL7Cfm0csUFKtQr2LLHnqaohY/7j9IM +3PUNJX7nqWoefmDxzRnL7xceSGhel/JN/M95TJd4luUl7JFtygvNvai6f08 5TN89nnKlwh19jLltWwB1/vzilYG0vQWjkbQmzz9Sofn6ALUOzTY0TtDsVzz arV4ct+xJ9O8WBdKXXYTIa89Sssfut7kr5TLL5DfUV6uJXvoYvoRMPQmlyoP aRJ/giZWeexZzzV2wtd8XtEKH+RLbE83Kp++XPkOned6X/VL2mqT3uxoRL1v VO4lskG9Q4MNvTPC3xLOX6Z89gXKp2jQEOplyhcJ+Y/PpkFDb/JM5XvkqUWz 3qB8UtT7yUbu/WfKC8se/viaVyh/YVp6o3LTl5Rn0zIP0/uxY5/QVpj1pkcj 6v2Xyu9anqSfoN6hobbemZKpCfp4+AIW0oS68L+ffOxB8l3l1+lMUe+XKrc+ pjzpgp7sc8pvFPV+4PU0Gpf4wf+kXPKqm+4Td6GtuUL5vmmpqreq/B8TTe+/ UD8/HFFvfjSi3vcrv2x1Hr6CeoeGmnpnLEICr1Q07b6oPPXKK6984cWKoj7i /Q/lDXRZUe/XKZ+6V3makeqvaOH7buWS56o8XVFeQ4wS9vdfQus7nvIGwWW+ 5mKFfji+/1LGea73g5cc+2dN71cbG9f0Fo5G1JscU6TXDaLeocGj3vf/okKr PQgV6ugvqlz2YloL/Qn+GFjU+7eUm+5Tnm4ku1l5JdX72DNUnqIov/pAsfqP PHTL62gN4GfJgzeq3Kyv4Vp+l+7jSWpRnemtlmVeoul9yRv1bWt6C0dj0vs5 yj/bvDSuQb1Dg6XemdpoMV+gvPES5W4aMkq7lN9klRuC3i9RFxw9aqy/kVYl 6oWTh64sVgxqPPjbytEH7mVV5Pqa5xQLJ8829CbPV/6c6f1l/pRJMZe9+d4E va9S7nF0gVyAeocGb7n3nyrPVXW6XC0rmIX6LeV/0Ymh94NHn3xefby8W1// y8qtwqPlPcqv6BK/+vVajGcqf3Ge1orfra95ufJ5PfXRot7fP/rU81Tv33qK OvOZV9EWpZuU11fT+0UlZXgJoN6hwZPe/3D0mOrKr7Gys0moTyqsHsPQ+78p V9HPwou01d9RnkEEvc8rl+sSP1O5ny97La1/4fA1NylXaPN/rhT1Vvf0m1Tv y+ghvIpWN5JP80amSno/TXnI4ix9BfUODV5qTi78EqsTfOBiqqJJqC/zKm5d b7Wo8Y+qppcpr2N1J997CmtPL1YMKpfqEr+WfVRYDYrR7UQrtvyKwnP2ey8V 9b7wLEVNfQ8rDH1S+a+EPux+voreF5SLK18Mn0C9Q4OXeu838uZx1eKnPGQW 6rGjz+Ernv6yl73sxZcrR1lZ5e6nKs9+3ec+9YqLn/Tf2ayh9y+oj41c4vOX Kc//1Jf+/BOXKMXOIZre3/sF5VfedPNnXv2kZ71M0Fv9JlD1/p2L6efmu8ol b7z1daytvkTvZ7yEoW7zn+j3iGRQ79DgodXybuWYVkH9IuVlZqHIC47Rv7xL 1dHLX6XVST/4a2zBM76spdf1fqbyu7rE97+CRXnap4vb0h86H7iK1Rm+6vwX RL3Vx9hLyTNfyYKf/gU1wuX/RMr01nghXfFn1S6HL6DeoUFSf+9blL+yXP7Y Pf/zy+erJ33gy392a4XKjfPfuaV6rd5Df3nrfVUjkFdeKr9LLOodGmT9nOHZ L/VvWz7y4NE/kb8T1Ds0yNL77gC6Lrngt59xoXYkr6DeoUHaj9Fe8/LacQLn oYuty0z+gnqHBg96P3777Y/w0A9v/yF55HbGXf+mrf2//4dNnrjrr2/4+J1a vJI4T9z2sRs+8vVHS7f78O0/Lon6k9v/VV/3sZ87OsYSLkiv86ag3qHBS+79 +9kPsOlPr73mR+SurMb1zOXH33obW/UevvAGZqU5zo/fwcLXfq1ks3+X/WhJ 1L/OflVf+Z4/dHaM9QD1Dg1e9H70Ldlv0un7sn9EfXzfnXfeecdX3p19H132 sbc9of798bXZD//w8R99VVtoivP4O67+2iPk4W9el73DvFlNbyGqoPe3rvlX EnZQ79Dgqez9rex1DxPy9ex7nqA+fpAt+/nbsz9SCxHXMCHfm/0GX/je7LdJ SZw7s7/PZu7QvgMMNL2FqILe5B3XOzzI4EG9Q4O3R8sPq2r+27XX0gxV91Fd 9reEfOQaWqT+O55pG2tNcb5C46n8/J3vNW/UpDeLKur91exPnB5l0KDeocGb 3o+/LfvN92e/ToOGjzdkv0XIW95Fgx+kQQFTnNuy77d+TDTrTaOKen+bloTC DeodGmzprT7hVVjz99mrs+9nIc3HJ+669tpHyY+yv0dn3p39qSm2Kc6jb8u+ +UN/+2+kDFFvHlXU++Hse2qdU71BvUODHb2z2n8rPpjVFL4r+9brr7/+/ddl s18j5BvZj9Fl111Nny9/+vuMx0vikJ9ef7X6uXnrx35asklNbyGqqDe59mpP dYMBgHqHBht6Z4W/pTz85mz24yx0V/aaN6u87XpaHvkj/kh5bZaa+CO6/Jrs z0riqPzsjo++WzX8m+TRv1a5XdumprcQ1aT3u7MWOX6oQL1Dg6Xe2dpoMd+f /fibr/4BDRmFZcpHWEWJWDh5F9dbiKPx6Mez1zzyE7pJvQLFXPammPS+Iftj d6caGKh3aPCWe38t+17Vxrer5Q6zjx/N/h2dfFCrHFG5pkzvD39MC7wz+63H 71D5AfnGh2hzz9/Skk1lvT+QLS3NhA3UOzR4Knv/yzXXqqr9XvYPSJmPrHrj tuy7tQV3ZMv0fmf2YR74SPYubdGHsj8ktB79K9X0fnv232ucU71BvUODl5qT J96V/Rt18sh11E+Tj3+vzbyXP2KSn7ylXO+PsE8FoTUoereTr1CxeZ5fUe8n rr6u9lnVF9Q7NHip9/641mpzW/atPzP7+PNreLb9L9dl3/OHt3/jw9e884Yy vR9/W/Z9f/PtO/7ozVmjG8mPrn7zx+/8aPat/16m9zuuZ6gxf6o1doYY1Ds0 eND7B1dfq9VhfCB7Q8lj4/uv5dNHbqAPjW/90OPfKn+0fPiD7CH17V8vLvrG dXQBLVuX6K3xAbriNkdHWQdQ79Agqb/3Hdn/p4Ue/+GdFSvyHvn72+40V4P8 7NuVY3M++JawV3uj3uFB1s8Z3iWpCPHoNV+tHanOoN6hQZbeP7haTs+n//yO J6Rs109Q79Ag7cdof3CDjxsz+Nl135axWX9BvUODB73z8/M5HlqfXye5ecby rrZ2+b8QsssWLe0Wk6ycGBo/vc5n9nmKxR0+O7/IJoW5i9Ljp/bFHWlrSGH5 RPo/LGr73NaXkkUe2Frgs3vzm8R8NNvz21rUvYsOHZ2iM/QjQr1Dg5fcewj6 2XQnEd8gy6AxwPzLt84RMqctSs7yBOspPn+E2bump0hMqXOHkKQLNzv4opPF 3WhryE4Pj55mip4AmOfrkyk2Gejls/MwQcxHcwJm9W31TDk7RUt257Ytl7d3 8SnqHRq86L2fgjN02gfTVKi+xcXFhePd0EeXXdRWoHoPqMtOjyVhWJ0jiwkY W8vvLXVDG/VjDbrVtYvzUymY1CU+7IidzJG9My2wYOxGFz8Bo+v5jVltB6re rQdsPdc7H9c+EZrewtEIei/Frc10xDyctlyOeocOT2XvJWjZI+QU9BSoUMNs 2WE7bKilgDg1ao6aprLbCWpefi6hOVsYZtn+GgzyzWxBmy7xIgyxRQvaFwPb Ite7V5Oq0AsrhDrbBuNsAdd7HrQykKa3cDSC3qRjwOE5WoB6Nwx29IaK92tU tXA3kaA5oi6UuuwsIeNxWv7Q9Sar0F4gU3oMctAC64LeJAUHmsTHaWKVw85e Yyd8zTzPtI09nYBT7cBK8VzvtOaWWW92NKLesyBm3wtj/WOrLLQ0MTC+xAKz ZGdyWZ+on73ZkePrptjzwzA0e2hetTQ1tVJAvUOHDb2h8rp8G5w5Aqdo0BAq DaomKXanDb1JJ2yR1qJZF8FxUe+EkXvPwZGyhz++ZhiWTEtPwNwydNEyD9P7 MHFcW2HWmx6NqPcKLUjpG05DvBXooRRGINEZh8ECTbAA6hlpE3IyDmqUcTF2 Xwxi9NNbXFVIA7TAYCvqHTZq6w3VVq5CDI6wkCZUYTmROEc2uLlFvYdg8RDi BT3ZHIwW9c5dRKNxic+1QXLkbLGqhcLXdMOOaamqt6o89ZbpvaR+fjii3vxo RL33oEfYRDpP1ttju2potEAOh6n6aWiZXN/XJ2oZPkfybEUxNi+cCKumYUg9 5zZAvcNGTb2h6lrVME27ZWgdGBg40gKgPuKdhovosqLeE3BqG9qNVKu0aL0G yV6VDoAxYpSwdwZiqhytFwku8zUtMfrh2Bli5Lne55KJXU3vUWPjmt7C0Yh6 k0RM/3rItyTV7aiPDmcOWxJ044Wk+gFMwwhdqU06YZOtaBNia3oLq5Kth+wK oN5hw0pvsIGWYi8JtNqD0JsbT6q0DdAyxDR/+BL1ntuFDmNHC1SeNUh0qKhf 8Go2aFT/kYOFiW51B2fI/gmVeX1NAqhCG3QfcbWozvSmVTOa3slJfdua3sLR mPTu1h9B1a8Y/viaL2xo30D9avEpzR5ctckBdB5QBmG7GJvrLaxa004zgXqH DY96H4HJZGyNhozSLmWcO1LUe0BdEI8b60+IZW/VkElBb8q5SYjntul++i0K J12G3ur+F5jeq7CurzWXvfneBL3TLNPlES8yQrzgPgHL6vocj0Yn68b5rhdj c72FVXPA6yQ7UO+w4a1wchJ61ZvdTr+1TUJN8CYXQ+/9eCKvfpuv6et7YFF4 tNyg5WEu8ajuUCcs5RdU1oqPlmf11MXcm+zEW/NU74lWdeb0CFXyLPWwst79 xsdE1Ju39gyo6pv0Vo9sgbNfqrewak5b1YZ6hw1Pem/FE6org6zsXCIUq58w 9D5Bq7NPGnXZ66ycYuidp6VyLnEn7PFl47Csb0yvU+nW5hegqLc6Gad6t9FD GGFZ+CmaFVfWux0OtNAG3+La4NKG9ryZhLxZ7wPgLaKby4VibL1wYqxa56vy MdQ7bHipOSl0sW/lXAtV0STUKp/R9VaLGtuqpm0wwepOtlpZ5l6sGKSmcInH 2UdFze7bwOh2YjTr8DxyOyXqXeiMxVKqqbQwdJyVMVg2X1HvQqzFCLbFqMJ9 sHnYGjtH6KdukJj1Vr9m6Ccml+gUYqt6nzKtOkyxVSfw0TJ0eKn3ntRaWuZo 87hJqMN4N1/RkU6n+9shzsoqa63QNXHm5HBLnNWUF/VuiR1qEufboO/kysJ0 EoqdQzS9t1qgZ2r+9Gi8My3oTcvAKTLVQj83G7Hk5OIEa6sv0btjgKFuc0dr FqXMQ+f84gB9Op2DzsXNs6n4ZqneG9B6dnO+nX5+i7E3oXvuUFx1Bjrm148n Uqh32PDQarkWS2iVEP2QNgtFjiToX96lKt4+otVJ7w/SWj/o4A2FRb071bKM JvHeMEvTfqq4Lf2hM5ema1pH8kui3mqGnyKdfN+nW2hSWrYu0Vujn66YK66Y p/GHaWHlTIJummbHZr3JSqu6onPJHHsoDudMq07FARIrvd3F62V9JZGAkdTf ewFWLZcfbp5dzVdPmludW9y0XpVfX9y1XqNxsFIjAhlOia2iha21c9qm1xZ3 LBMUNhfWymIf5EpWHSyvG21WqHd4kPVzhq6h2nHqwLn4bO1IXkG9Q4Msvddi PvQ89Z/JjkLtSF5BvUODtB+jjaV93JhfHLSsBLAX1Ds0SNO7cFA7TuAEc1Co d2iQpncTg3qHBtTbf1Dv0IB6+w/qHRpQb/9BvUODWW/EL+p1PxET5vtQbymi Q51uJ2Km5D7U24rIUJ+7iZRQeh/qrUVUqMvNRErB+4BEGNQbiTCoNxJhUG8k wqDeSIRBvZEIg3ojEQb1RiIM6o1EGNQbiTCoNxJhUG8kwqDeSIRBvZEIg3oj ESZIvU8l+WtGtkc6Eh0T7DV9I32Ms1XTIYhLAtQ738Hf2b2VivWmk9BGXU/E WygBvPgPaUaC0ruwMN0OXO+h2JI6P0DfNZ+Dk7USIoh7gtJ7n/1Ei+nN3/K+ Cmn6iu+l6skQxAuBFU5yuVwX0zs/xl4gv0JHBJkD65dqI4gvBPlo2SOMl7PW Ed8jZCo23RlvTe8FeBBIM1EfvekgJHTkszQk+sd7ILFVLRmCuKU+ep8daYek Wuwe6abDjMzqQ4ohiL/UqXCiPlXGi2NwG6NZIoivBK/3zhIfc6yv+Fg5VBwy G0F8JHi9zxgjXO9uTyyyYErM1hHEN4LXexO66fBNu4kkOQdsJKdlbcxrnSzS JEhXrg5l70E4cnZpNEnHxh6F3vm1ky2xNVO8rI2wrUgOE8zMZGdmAtubxwRR 25sc6qD3ARt4OEUbdwrjcTXYZra7ae5oAx0e6u2AvZWFTW1w4P3V5bJxhJvl jjbQ4aHe/uHprBs0caMedx2vmB1Q73AkbtTjRr0d06DXG/UONLEtIqe3J2Zq R0H8A/UOFtQ7UFDvYEG9A6VJ9Q6iPcsS1Ds4ItdqaRfMvZsE1DtIMpQ67bsp Qb0DJMNyb/Q7OFDv4KBezxD0O0BQ78BgVs8YISQAUO/AQL2DB/UODNQ7eFDv wKBSZ2YyBPUOjibVux7NOhn6D/UODmzWCZQMqxjMoN3BgXoHRwbrvYMG9Q6M jNZqiXoHB+odFNxqbNYJFNQ7IDSnUe9AQb2DQVca670DBfUOBENo1DtQUO8g KPo8UzKPSAX1DgDBZtQ7UJpU70BbLUWZZ8oXIZLAVssgMKk8Y7UQkQXqLRuz yKh3oKDekinxeKbCckQKqLdcSi1GvQMF9ZZKad5NsV6FyAD1lkk1hVHvAEC9 5VGjbyD6LZ9o6X0qecCm2yMdiY4JNvzf4dxgqn+2JF4getfUF/2WTqT0znfw sXW2UrHedBLaqOtj0JZuh1FzxCD0ri0v6i2d6OhdWJhuB673UGxJnR+A43TI vwG6AM6Y4gbQnmXHXfRbKpFqtdyno6FxvVNsBPlVSNOx0uho23vQZ4or/6xt mYt6yyY6epNcLtfF9M6P0SH/yAqoRe4WZjpph7wYVfpZ2xQX/ZZMhPQmxriW lMO1jvgeydEcXKW/OLw8JQwlEyfxEJdEVe/BGMAyLaCMs9k0rIvxJJ+1fWvR b7lEVe+zI+2QXCLzMMlmh4PU24mz6LdUoqq3ylq8Q829x1g4yMKJI2NRb6lE Ue+dJdagQ/pgZxsGWbA7uEdLh8Ki3zKJot5nYIrNDcBuIZmioYN4jymexLN2 qivqLZMo6r0J3QV1sptI0kbLk2rwBJib5bMcCUfg3Fb0WwrybrGZOpS9B+HI 2aXRJJxVHU8lppYnoa9giiftrF24inpLJJJ6HwzTBswUa9zZalODvefM8WSd tStV0W95REtvg72Vhc1DLby9tF+6WtJZuxMV9ZZHRPWugZyzdusp+i0N1Ns3 3FuKfssC9XYI65dotcKDo6i3LFBvx1ifkCdF0W9JoN6OsTohj0MuoN6SQL0d Y3FCnvVEv+XQpHp7ac8qPyHvcqLeEohcq6VdPJz1zAwYb+LR8MNN9FsKqLdj Sk/IHzPRbxmg3o4pOSGfvES9ZYB6O8Z8Qr5piX5LAPV2jOmEnElZsU3I8ZYQ W6DejtOKj+OOnaxyNdBv/0G9HWLKgJ0biXoHCurtDND/UVwIWe1qSPVbfLV4 89Ckerut8Ics+59lJ+VGx6pXQ27+3XRyY7OOQ4CmBHrdVMddyYh6Bwrq7QT1 XLJq0Vt33MVmql8NucUTmRsPKai3E9RzyahWZ0B7wHSuOOodKKi3E4AKCAQ0 vxnO3jdQ42rI9Bv1lkGk9Kb60RPKgFZFKEhubwvVV6Pe/oJ6O4FazUooYHho lrzmFmpdDYl+o94yiJTevNI7A6UamiSvdsaod6Cg3k7IGK2WlhrWlLyW/ESm 36i3DCKmt3ZC1SysKLmpybPqPvwnQ5Gz6RDTpHq7bM+ypzenXHIQ/tfYh+9k WO7dXH5jq6VTjJoTuwlKJOcXPHi/6TZnJG07zKDezsjwmhOHuzNqVvQmzxq7 8Bu2yRlJGw8zqLdD3JZhs1luN/tbYxeuDqzmFlFvGURMb/cnxLtiaZJXi1hB QRvVLlW3iHrLAPU20mldsWpWj1dy0PWlpBvMzGSqbDqioN6OcX1C1G/tfw3D K+XfbvecoW+Jm6GbRb19BvUWUtKaEy19NcX91luvOWm6mu9o6X0qecCm+Yme eGv/Bg2O9DHOmuLVSe/S4nNlw6019JJ7o95yCFDvfIc2tk4vdAy3QWxJDSfi LZSSkdHc78PDAx5LXroga2m4r3ozqbUanybzOzp6Fxam24HrfYKNJH8G2gok xwb+K8VTe5anvhuWV8MiE7fu0+Jql/qmZipvOJpEqtVynxmiDfxHxyAupGCL rMGSRVxPZ+2/3qTccN/0LpZHZqpsOapER2+Sy+W6uN6tnWxBP6yTOfNg8hrh 05utExW3stDFpRQ2M1O+KPJESG9ijGvJ2WuJ58lUbLoz3preM8cLp97EZLiF hc4vpbiRGauFESe6em920pG205DoH++BxJYpnoez9vg6HBtXQzPcB73NFSXF o24ev6Oq9+F0PDalTke6N9W/s9Bliif/rCth72pUqDB0eClLLJ6puCa6RFTv 5Tbo2RBWdIKpeBJ2vYmV4Q6rJMvquMXvnGbxO5p6T0Nq3rRiSH3KFGgAvQn9 wbL5xxBCk6eNxGVLZqqvjiSR1HseerRcfHtikU1TYBpXvkH0JkImXuywYjut ecd2KtYjRyT17o1vawvOQUdBnSxDjyleNuvs5Tv+4ehqaApqP4Xg74CztQXL xndbDaORIahbHLzeh/HWNGeHjELv/NrJltiaKV69cm+nxWcxIe8mbktvK3PL RnSLuN6cKOq9qn+jqwXuwnhcnbaZ7a5j4cQZgt9a55Rs7c9HpX5Tpemawe9o 6W3F/urybumyRtG7qCAvl4DRx9D5byHKb0QT+B19va1oSL31n9kLVEtRht1u t1EC9Q43Jr/1/0SU3By9irEWNyLyfqPe4UYsfZe84qr4o03D8aq6OsvrowHq HXJMtSelxZGsqDjU+C2O5Y2IuN+od8gR/bO6lKxAXr04XiV11P1GvcOO4F+F S8kMz2RqOV4hdaT9blK969Nk6Q5T8bsCxvlUVLyy9pH1O3KtlnZpHLeJPb0z pptp4XjZg6nlDiIH6h1+TJWDlhH0GEJ2ZS6qlFQrVtpB5EC9w49mX1mvkZL1 HNMXsslxdiOazG/UuwHQ7bOu2itzs6TIaSqpNNnzJerdAFTT21rMUsOJKQu3 vZmGB/VuBPSO3xXXWCAazjPuqvXi0fQb9W4IuHzlff6qS1msLuR/qvmNersD 9fYB43dpZUtroBkOYvNm5V1EjibVu5GadRjF8RWKi2wKyb3mrxVvquYdbNZp GMr1dmKj3vWK5+SVBI+c302be9f7AJyjD90nzjuACm6ct/OfQjQqqHeDYNbb 8XvoWfmkpE3TeieRAvVuFDLeXoLJ35JSS/Co+Y16NwoZY0RNd0OIaHl3Scer sr24Pr5Qgno3CmxsMy+Dmxk3oqrg0fIb9W4QqNdsVHjX/gk3wtw9vGxH0QH1 bgz4wKusiOJ2E+YboRvuqrGoYUC9GwOt3tvL2GZlN6KS4BHyu0n1btBWS0/D ZlvcCL3JvsTwiPiNrZYNQ7HV0k+9iZ6Flwheuo8av8EPL6h3Y+BZ78qGilm4 aXem5O72Wm9CpHfNF3X4R+PpbbRaSik4lAteln/L2K18QqO3+aevkmlAvfVR 4SVtXXg9p7E7EdS7ArYujOmdBfIFb0S9idFqKQmz4Ki3PexcmBKhpfvdkHp7 HDDWBqZfPJhGfK30I/2wEwq9y6NI9hv1roQguCn/xty7AkFemFPJAzbNT/TE W/vZwJaHc4Op/tmSeKh3ZdjwgkzwWm/vbAAipXe+g4+MdtALHcNtEFtSw2PQ lm6HUXNE1LsquuC1394ZdsKit/aSGQ+PlYWF6Xbgep+AcfXvGWgrkGUYIHTU 1jOmuI3XaskIrvir/3rNWNCIeoem1VK7kp7qBfdZYqb3IOTVv4UUbJEeNtr2 HvSZ4jai2yRIvYkx+MGVml0AABlqSURBVAMLY6tlRezXnGiKu91RLpfr4nq3 drIF/bBOWrpYsJ0Jb4B620IX3PjXcIRCbyOPEGZc0SOOrb3XEs/nIM3C/bAj xkO9baILzqsMA9+9Z0KltzjjClHvzU6YJausFE5IWs3IBVBv+/AXSABpSL9D pDf4qffhdDw2Rcg8TLLZYdTbNfpQyPaGsw8XEdV7uQ16aLX3Koyx+SgUTmYo ddgvZLKsPwDqbUU99J6G1DwLbMMgm3ZH4tGyPvByiZqHZ1HvcuzWnID3J0td 73no0XLxQjJFJwfxHlM81NsBkNGGs89Aw7UWhEVvoebbw740vXvj2/qSMThJ aDuPuVk+y/GwpyYiA3pLvRpqmKsW1C2222rpPe/W9T6Mt6Y5O2Q3lZhanoS+ gileg9yicJDR670hU6wkbBDCorc/cL1XjR9GrBOy1aZOe8+Z4zXO/QkBmWIf Qv3LtWEMj5belmwv7ZcuapCbEw5Yxyr9Jw5G6bExDA+d3vhjtLDB9dbfQSE8 HTWA4eHSG39rGUaY1cUXCIm3KOyGh0fvAH8oj3o7I8P0Lg6ObLpNoTY8JHoH 9yN5RohvSCgp/RVzya0Kr+Gh0LtY6y39aDhhvRvhBUp+elmaF4XU8JDobZ5K J5S3ItRA2Zshyr5rw2h4SPQOOvcO460INWV6W7Ywh+uyhqfVEsveIQes3jto dcN8VsqjFSHRm2DNSbix0rtSFyF/DfdkRHj0ZnGx3juUlL4WwrTCKoGPhkdI b4KtliGl4stpK+ZHRcO9uR4tvQMB9XZK5XcvV/m+5V7r/93t19vbDUOhN5iR fkiot2OqvVq82j3Tc273V7zxc2/UO/RUfXN+1bvGq+eaXW/pxyGCejtD+xVz 5beLVyuhEG+l78bXO/CXfGGzjiuqvTy/8h3MAn1Riusr7t6L8DTrBGw4uu2K qmNDVPFbL3+7uuwRyL21mNisE3Kqj31S8fZ56B4emVZLHhkfLcNMjaF9Kt08 951nwePLO0OmNwmmXxXq7Y6aI1dZC17WtdDu/kD474qQ6Y25d6ipPTCb5Q0s W2AzCwfzHxeESW8se4ceGwMPWtxEq5tqx3AgoP1OqOH1xpqTRsDWuJpld7Ji jUqNjegvDso0uN6B13sHuK9IYW/Y2NK7WbPJviw16HbzxJmG1htbLRsFu6Mi m+9otZsrCl7aNSMiZe/g+5xgq6VLXPld/Y4aA2mW3f+MUXPiarDxsLRaYpeq hsG+Z8KdrHJHq9554+WdDnZrJhR6Bw7q7RYHnhlFjAqV4WaxrTJa4eWdLg8X 9UYc4UQ0pmZ5w2OFDLu8KMHeawhO9yqCeiOOcCYaF7j4mFijDFpqeEbT263d 4dC7PIrkzwTq7RqHphkZuN2HK7PgGaa3a7vDoXdpPxPpT5eot2uc6m1fbB1T Fl76dkOHhENv0+/jA6g7Qb3d47B0Yrzdw8lNLRruvsGSb8hLYls4aZT3WjF4 KnlQGhzpY5w1xUO93eNYb3ctM5rgGW9116HR2xDcw67yHcaoxEYwEW+hlIyM 5mEnzU5AevMsPKMN9+2WEOntkcLCdDtwp4Vgjg38Vwq2WnrAud9GzYlTWIOm a0nD0mrpC/ss798vCa7BkkVcdNsDjh8uPfzgJkuy7vUmUcq9SS6X69JKJMXg nHkweQ3U2wNOKzI8FDkzWZYY9eb0GGVvPTgVm+6Mt6b3zPFQbw84r6dzrQAd 7nsGy9465XqnIdE/3gOJLVM81NsLjv32oLfH929GXe+R7k317yx0meKh3l4I TG+2Iw8v0Iy+3hqdYCqeoN5eQL0FbPX3rjTjkIp6D9Hh5Yug3p5w/HDpfj/a 2w3dEiK9Na991Xt7YpHNpUyyo97eCEhvD31NdCKu9znoKKiTZegxxcty3O+o uWkEvYO6xXXVm4xC7/zayZbYmikeiu2JRtCbE3W9C+NxAGgz2416e8R5w6X8 nVgSLb2t2F9d3i1dhnp7A/U2qLfeVqDe3kC9DVDvCOL0B8Uu7qkfdqPeiBt8 cS+AXYREb8c/yPMG6u0R1FsH9Y4g8vX2Zw+h0DtwUG+vSPcb9XYPNll6pRH0 DkurpTk+Fk4aANl6+7R91BtxhWS/UW8PoN6eQb05qHckkau3X1tHvRFXoN4c 1DuaSPUb9fYC6u0dmXr7tu1Q6I2tlg0I6s0Ipd7YrOOZ8OsdymadIEC3fUCi 39HKvQMH9fYBeXr7t2XUG3EJ6k2xqXdQxW4G6u0H0vyOnN5BPlcS1NsfZOnt 43bDobfhdUB+o95+gHoTxwP/BeI36u0HqDexW+9tGZYG6u0Lcvz2c6sh0bvS jCRQb19AvUOqN7Za+kHI9Q5LqyXm3g2KDL993SbqjbgH9cZHywiDemPFYISR oLe/mwyL3sVmHdS7gfDf7yjqHXSrPOrtE6i3XV+D7FOFevuE73r7vMHw6O0H p5IHpcHDucFU/2xJPNTbL/z2O5p6+5Nz5zuMsXWM4Bi0pdth1BwR9fYL1NtO HB9KJoWF6XbQxosqBpdhgNBRW8+Y4mKrpV/4rKO/tYKhabUE4rnGe599QvZL gj1stO096DPFRbf9Isx6k5Dk3v4MO5LL5bq0Ekkx2NLFFrRDXoyKevuGv0Ki 3tUoG9cyB2k21w87YjzU2zd8FdL3ipiI670K42wuDetiPNTbN1Dv2lGk6T0P k2xuGPWWhZ9Kot5Vsci9x9gcFk6k4aOS/reBRlzvbRhkc934aCkL1LtmFL/e MVimdyGZojMH8R5TPNTbP1DvmlGk6U3G4KT69wSYm+WzHPc7Qor4JqXvbToh adbxjXK9d1OJqeVJ6CuY4qHYPhJOvTlR15tstanfB73nzPFQbx9BvevK9tJ+ 6SLU20980lLGL9tCoTdUmZMC6u0nqHeNKPhT4kYG9a4VR3caf2vZgPjjpZR3 AoVDb5/6xNoG9fYVX8yMtN74+voGBvW2EzEwu1Fvf0G9a0cLNPfGJktf8UFN GZXeoWm1BCx7NzLh1JuEJffGmpPGBvWuGgXrvRsb725KGsgkHHqbZlDvxsOz nVHWO3BQb59BvcME6u0zXu2UNcga6o34AOodJlBvv/HoJ+rtJ9is4zfe/JRU KxiaZp2AQbf9Jox6k6bNvet9ANHDk6Got6+g3r7jxVBpdqPeiD+g3uEB9fYd 1Ds8oN7+495ReXaj3ohPoN6hAfX2H9Q7NKDeEnBrqUS7m1VvbLX0n9Dpja2W iH+ETm/StLl3vQ8girjUVKbdqDfiG+5ERb19B/WWAeodElBvGbgSVardqDfi H25URb39B/WWAuotl1PJAzY9nBtM9fPRokb6GGdN8VBvKbhQVa7d0dI736EN qDMGbel2GKXBRLyFUjIyWnDH1Eyg3vIoLEy3A9d7GQbUv0NwhpAcG/ivFGy1 lINzWaW26USp1XKfvWKW6d0De+rfPegjZA2WLOKi23JwLKvkzDtCuTfJ5XJd XO+WLragHfJkzjyYvAbqLQfUWyp8MMscpNlcv6r2VGy6M96a3jPHQ70l4VRX 1NsJXO9VGGdzaVhX/yf6x3sgsWWKh3pLwqGusu2OpN7zMMnmhlW9R7o31dAs dJniod6SQL1loufeY2yuv1ju7gRT8QT1lgTqLROu9zYMsrlu9dFSY0jNyAVQ b1k4Ela63ZHUu5BM0ZmDeA/ZnlhkK1JgGlce9ZYF6i0RrjcZY205J2CWnIOO AqHtPD2meFlOgEfWLIRG76BucR303k0lppYnoU81exR659dOtsTWTPFQbGk4 URZzb2doepOtNgDoPaeGCuNxNdhmthv1locDZeXbHTG9i2wv6YXt/dXl3dK1 qLc0UO/6g3pLA/WuP6i3PGxLG4DdqDfiM6h33UG95YF61x3UWyI2tQ3CbtQb 8RvUu95gk6VEQqN35Fot7YJuS8Set4Fk3s2ae9f7ACKNLXNRb3mg3jJBvesM 6i0TO+YGYzfqjfgO6l1nUG+p2HAX9ZYI6i2V2u4GZDfqjfgP6l1fsFlHLjXt DabJEpt1EBnUsjeozLtZc+96H0DEQb3rCuotF9S7rqDekqnub2B2o96IDFDv eoJ6Swb1rieot2yqGRyc3ag3IgXUu46g3rJBvesItlrKporCwdUKYqslIonK EgeYeTdr7l3vA4g+qHf9QL2lU1HiIO1GvRFJVNIY9ZYO6i0f1LtuoN7yqaBx oHaj3ogkUG/fOZU8YNPDucFU/2xpsAjqHQDWIqPersl3aGPrjEFbuh1GS4JF UO8AQL39pLAw3Q5c72UYIHSo1jOmoAC2WgaApciBVnpHqdVyHyhM7x42xPYe 9JmCAuh2EFipHGzmHaHcm+RyuS6ud0sXW9AOeTEogHoHAertM3xcyxyk2Vw/ 7AhBMR7qHQQWKgdsdyT1XoVxNpeGdSEoxkO9gwD19hmu9zxMsrlhWBeCYjzU OxDKZUa9vaDn3mNsTi2RCEExHuodCGUyB213JPXehkE21w15ISjGQ70DAfX2 F653IZmiMwfxHjEognoHQ6nOqLcnuN5kDE6qf0/ArCkokOUEeGTNSabqrFSC usV10Hs3lZhanoS+gikogGIHQx315kRSb7LVBgC950qCRVDvYEC9JbG9tG8R 1EG9AyJTcSYYoqp3dVDvgEC96wHqHRCodz1AvQMiUyEcFKg3IpOMZTAwUG9E Jqh3HUC9gyJjEQqQJtUbmyyDIlMWCIzItVraBd0OjAyZoWDuHSCod2BQq2dI nexGvRG5oN7Bg3oHRwb1DhrUOzi43vWxG/VGJIN6Bw7qHSAZ1DtgUO8AoXrX ye5m1RubdYKjbnpjsw4iH8y9gwb1DpAMpU77Rr0RuWRIZiaDj5ZBgnoHhuo1 1RubdQIE9Q4KZvWMEQoa1BuRCepdB1DvoEC96wDqHRSodx1AvYMC9a4D2GoZ GHXs742tloh0sMdg4KDeAYKtlkGDegfKTN32jHoj0kG9gwX1DhTUO1hQ70BB vYMF9Q4U1Ntf9oY7kkOnWXCkj3HWtB71DhTU21e2U9A3GOcDEifiLZSSkdGC P6ZmBvX2lQE4Q8jBACwRkmMD/5WCrZaBUie9I9pqeQBJOs7fMgwTskYdLwPd DhTMvf1knXpNSCHRRciceTB5DdQ7QLQ3xNaFKOq9DX10cgjxApmKTXfGW9N7 5hiezrpBEzfqcdfxitkheL0LLTE6kuUcwB5JQ6J/vAcSW6YYDXq9Ue9AE9ui Do+Wp6BrbmEonlRz75HuTXXBLHSZIjTo9Ua9A01si3rUe59MAMRP93YaCzrB VDzJ2gjbiuQpQbB7C/nhyd+bHOrSalnY3CiQlrQxPwTr4upmuaMNdHiot10O 51boZAOOk+2JRbYoBaZx5ZvljjbQ4aHetkm00b+DsS1yDjp4FXiPKUIWaRKk u1YHvcdheHNzFEbV4Cj0zq+dbImtBX8USDNQB73zaVAZpfl2YTyuBtvQbkQO dXm03Fla3NWC+6vLu1XjIoh76qI3ggRDuPQ+lTxgU8tu4HYTk7Nd8ZaeFTd7 3uzTmXez59xIe7x9NOdmz6Ze8DbJT/TEW/s3aPBwbjDVP1srQaXUwlE4T2ze jsPE2yMdiY4Jh1fMAaHSO9+h1RBadgO3m/g4tI6NtsCyi8QroGPVUbfWns+l oHWoBVr3ayWwSiz2grfHQS90DLdBjHa6HIO2dDt7WneTWrh4jhObt+Mw8VYq 1ptOQpujj5YTwqN3YWG6HfhFtu4GbjPxNnTt02r1nlpprBIXGPmOnkMXicdh Wp0fhovc7FnoBW+TEzCu/j0DbQWyDAOEto6dsZ1YTC0chfPEQtB54iHqeGEA jjvYtyPCo/c+yzXZRbbuBm4z8TiwcslF6eoprBNzJlrsP+4KibuBfstuMNWc JhZ7wdtkEPLq30IKtkgP69Wwx/tiOk5ddv5OEgtB54lTrLPRKti/Vw4Jj94k l8t18Yts3Q3cZuLeVg97ZqyAkyJwMfEY0EbYk+CgTGUkFnvB26SVd9rph3XS wlO1M3Ecpy49f0eJxe04TZwfm6OhFSdXzBkh0lulh19k627gNhOn+neHO9rT 264SUw5aO21/0ZoSb8TaT21Mpxxk/cXEYi94R+y1xPM5Lfvrd5wt0NTCUbhM bAo6TXy41hF3eKftE0q9rbuB20uch55U/Eg3xJ1VnQi3d8LZU6mQeJF9yzss WPHEYi94J2x2qlnfKivN0utmOwsVUgtH4TKxGHSaeDAGjq+3fUKpt3U3cHuJ NwGGzxGyAK2OssHi7T1IHHG022LilVSs/3gfJJz5rSUWesHb53A6HpsiZF6r cBl2preWWjwKV4nF7ThOfHakHZJOH7VsE0q9NTqd5WQ88RbEWa1HOzgqnhT3 PA2LThIKiVPMro14ytUHq6wXfG2W26CHVh+vwhibd1Y40VObjsJFYtN2nO+Z kLV4h6PkDgiz3kPOMiO9cMKv1ZizQoKx58OkMzuLiTe1b5sj9isRTHsu7QVf k2lI8danbRhk024Hj5bF1OajcJzYvB1HiXeWeINOn/OqBJuEUe8K3cDtJSbJ GLtmvS4lW3BQbW1OvAL9bG7IzfeG0AveLvPQo38wkik6OYjbr+sXUgtH4SJx yXYcJT4DvIQyALL6HYVR7wrdwO0lJhfBKUJbhuy3MwiJaa7vvP8iT7wPMVqY Oki1uEgs9IK3S2/c+BiNsXawE06e74TUwlE4T1yyHUeJN6Gb3qTdRNLhJmwT Rr1ddgPXEu8n48dX5zthwU1iQtqc1swR4YOVmlie7nBUa24kFnrB2+Mw3prm 7JDdVGJqeRL67B+6mFo4CseJS7fjbM+DcOTs0mgSnHUuckAo9XbXDVy/Qzs9 auIWZ3YXE0Ovs4RC4sKU+nQICYcdCrTEQi94e6wa/WPUJ5StNnXae87+Xk2p iUO9hcSl23G254NhOk3N2d+1Q8Klt4G3buA7S5vOs2A/OFg9u+a6e5DQC94F 20vO22VCwN7Kwqbt/j3OCaneCOIHqDcSYVBvJMKg3kiEQb2RCIN6IxEG9UYi DOqNRBjUG4kwqDcSYVBvJMKg3kiEQb2RCIN6IxEG9UYiDOqNRBjUG4kwqDcS YVBvJMKg3kiEQb2RCIN6IxEG9UYiDOqNRBjUG4kwqDcSYVBvJMKg3kiEQb1d sDtPWXL2wsuDM1PaWCrb8/qwVgfz8zbf9bni7L2zexdJfC9lA4F6u2BOe4Nv 0slwYB3GO4JzLbFNHhq3O2BpvpW+JNh6EHkhONLHOEtIj7OxnKIK6u2CORhY XFw8PZaEYdsvWt6Gvh098mntJeKbsaTNV3JfRMeaqDCIvBBMxFsoqutLjgdN iCSotwvmYIJNdzvB9pvXV0DIT3t5ul67g8DvxWnubD2IvBDMQbEI02F/6O8I g3q7QNebrEI7zZE3Twyf3FADi7OsOL43Wxw6cGliYHyJTWHwtJFVb8VTB3Qz fAz4rdmR41q5Rd8SWZolO5PGcKbjcfpueutB5IXgmjAa3KyzAawiCurtAkNv 0qmqVuiFVFccuvPkJEzThceN0XUKI5DojMNggQzEIRYvjs8xpW7hIBVn49Gc jEMrsIy5uCWShgVgY2AxUmxIQetB5IXgnDCA3go/liYH9XZBUe8hWFRLC5Pq 892QWt7IxZiAXXF9AJITdLCcw2Fq2opp2LLDjtjWBB/kbxn6ciTP4hS3pOrd MrmuDyeyoY1bySgZRF4cT34qNt0Zb02zCpo9h+PKRRPU2wVFvSfUHPZUP7V5 lZat+2mJYNuQ8bAlQQsaBTqStllvNXpnrJM9anbCJovTRsQtpWGkGPm0MNZm 6SDy4njyaUj0j/dAgg0emIhh3SDq7QZRb/aMeLi93E9z3rM0Dz5ujDm4AXx4 emp9id5kFPgAmgfQeUAZ5GVlfUtpWCnGnTZKO+WDyIvjyY9000/KLB8duVva WKgNBOrtgqLeA6qFhcUjANBONcsn1NJJV4uebc5rYwxPwHKZ3lta4WFdGAdP 2FIacsW447rrFoPIW4wn38keNtOw6ec5NyaotwsMvffjibyab/bMruTWWcXf MGzvFIdenTcGld4s03tbq/vegJ4Fzr64JZPeE8DHYLcaRN5iPPkh1n7UL22g 9gYC9XaBofcJGKKlC1qGXmAqL8PxE7Cqx9vQcuikql4lvQ+AjQdPNpcL4pZM ep/gtSCWg8gLwe0JXiGZYkOwtoPrETajA+rtAl3vSYhvkx3mcGGQlYELqa6u NiPeYWuMVnWv0wy2kt6kh+W1ObVYI27JpPcqDNOJ9SDyxeA56KAfj2W+mZiz oe2jCertgjnoSKfT/e0Qp2WFNpjemDvSBoO0MDABYuvkHHQubp5NxTer6L0B rWc359vV4rm4JZPeh/FuUnEQeSE4Cr3zaydbYvSZdUf9YkFQbxfwLlXx9hFW A7feqobT+QFWCN6AmFhhcYaOMt9Ks+eKepMVNT10Lpm3ZNKbHEmQyoPIF4OF 8bgabGM1Msv2+wtEGNTbO4erq7SuZJsalo+Z+3rk1xZrPuEVNhfWyrckslAs zxsIg8gXg/ury9qnaziF1d6ot9+cErp9+EiX05LGubiTzrqRBfX2k6X51i4p G16LOewgNdlhu6tulEG9/aQDWtbkbHnM5u8eNA5aVmpHagJQbz/ZXM/XjuSK grNKbIfRIwvqjUQY1BuJMKg3EmFQbyTCoN5IhEG9kQiDeiMRBvVGIgzqjUSY /w8/FuXhbDq7oAAAAABJRU5ErkJggg== --============_-1101023301==_mr============--