Subject: illustration needed--found From: Denis Donovan <dmdonvan(at)IX.NETCOM.COM> Date: Mon, 20 Jun 2005 14:11:08 -0400--============_-1092831418==_mr============ Content-Type: multipart/alternative; boundary="============_-1092831418==_ma============" --============_-1092831418==_ma============ Content-Type: text/plain; charset="us-ascii" ; format="flowed" Many thanks to those who were kind enough to send so references, files or links for a graphic example of the 'spaces between words.' . However, no sooner did I sent out that request to the list than I searched (for what I had written about fetal auditory ability in the Word file of a long book on the cognitive psychology of meaning that I've been working on for some time) and found Jenny Saffran's example, below, which I had forgotten I'd stuck in the ms. It actually illustrates exactly what I had in mind. Others may find it helpful as well. Saffran, J. R. (2003). Statistical language learning: Mechanisms and constraints. Current Directions in Psychological Science, 12, 110-114. Denis Donovan -- ===================================================== Denis M. Donovan, M.D., M.Ed., F.A.P.S. The Children's Center for Developmental Psychiatry 6675 - 13th Avenue North, Suite 2-A St. Petersburg, Florida 33710-5483 Phone: 727-345-2400 FAX: 727-345-8808 Email: dmdonvan(at)ix.netcom.com ===================================================== --============_-1092831418==_ma============ Content-Type: text/html; charset="us-ascii" <!doctype html public "-//W3C//DTD W3 HTML//EN"> <html><head><style type="text/css"><!-- blockquote, dl, ul, ol, li { padding-top: 0 ; padding-bottom: 0 } --></style><title>illustration needed--found</title></head><body> <div>Many thanks to those who were kind enough to send so references, files or links for a graphic example of the 'spaces between words.' . However, no sooner did I sent out that request to the list than I searched (for what I had written about fetal auditory ability in the Word file of a long book on the cognitive psychology of meaning that I've been working on for some time) and found Jenny Saffran's example, below, which I had forgotten I'd stuck in the ms. It actually illustrates exactly what I had in mind. Others may find it helpful as well.</div> <div><br></div> <div><img src="cid:p06110403bedcb64184c0(at)[192.168.2.15].1.0"></div> <div><br></div> <div><font color="#000000">Saffran, J. R. (2003). Statistical language learning: Mechanisms and constraints. Current Directions in Psychological Science, 12, 110-114.</font></div> <div><font color="#000000"><br></font></div> <div><font color="#000000">Denis Donovan</font></div> <x-sigsep><pre>-- </pre></x-sigsep> <div>=====================================================<br> Denis M. Donovan, M.D., M.Ed., F.A.P.S.<br> The Children's Center for Developmental Psychiatry<br> 6675 - 13th Avenue North, Suite 2-A<br> St. Petersburg, Florida 33710-5483<br> <br> Phone:<x-tab> </x-tab>727-345-2400<br> FAX:<x-tab> </x-tab>727-345-8808<br> Email:<x-tab> </x-tab>dmdonvan(at)ix.netcom.com<br> =====================================================</div> </body> </html> --============_-1092831418==_ma============-- --============_-1092831418==_mr============ Content-Id: <p06110403bedcb64184c0(at)[192.168.2.15].1.0> Content-Type: image/png; name="P533953CD" ; x-mac-type="504E4766" ; x-mac-creator="6F676C65" Content-Disposition: attachment; filename="P533953CD" Content-Transfer-Encoding: base64 iVBORw0KGgoAAAANSUhEUgAABaIAAAFeCAIAAAD44P/YAAAABGdBTUEAANkDQtZPoQAA AAlwSFlzAAAuIwAALiMBeKU/dgAAACF0RVh0U29mdHdhcmUAUXVpY2tUaW1lIDUuMC4y IChNYWNPUykAs2HlZgAAAAd0SU1FB9UGFBILEtHzzckAACAASURBVHic7d0tfBTZ2v39 8Hz+gnGMA5lxGRccI8FxXHAgg+N2xIEEB25wIAcX3MGBBEccOCKDG9zE8dw3m1rN1Oq6 etdrV+/+fcU5NUm/VFft2lVp1lXXhZ3RfBvvpQEAAAAAAH727f++h/j/1r0WAAAAAAAA w+BrDgAAAAAAUIgL4720ilZOPnwY710AAAAAAMDW2r969ccSRSsAAAAAAKAkfM0BAAAA AAAKwdccAAAAAACgEHzNAQAAAAAACsHXHAAAAAAAoBB8zQEAAAAAAArB1xwAAAAAAKAQ fM0BAAAAAAAKwdccAAAAAACgEHzNAQAAAAAACsHXHAAAAAAAoBD/b90rAAAAxnXp0qW0 sLu7+7//e3p6mv7z69eva1snbI40bH6mIZTzrEvVT04ynlUSHXe//vprWvj777/Tgh96 rR6MmduvBr/2XM4hMzbGGOZppJFJmgMAAAAAABSCrzkAAAAAAEAhKFoBAKBwCoICHShR PMGziqRNoYWTk5NBHoyZ0k5c72p8Vyta/JlKA4A58LMGRSsAAAAAAAB8zQEAAAAAAEpB 0QoAAOvk9+T3e4zrMaf2q0UguapMWdnPwmtY8p/7M787uuTcJj0nQR08vee797EkBF69 ke8gf5Zoswe7Pnp3ffDqJ6mbw1Cf2neQ/6rVpu55O/0lG3CqzkG+5lqVYI/3lP+CwbHQ qieOP6vbjpacyW2loTb+WnZi8O4deq8EH6FbGyPtXz+IfJYLHhMc0cHJq2blzBY8d6lu wy/4UNJnJwb29/d3qvVL/6/dOuym3ul6Fgue7pti5Y4eqpx2b2/vx9Lz5z//nDQHAAAA AAAoBF9zAAAAAACAQlC0AgDAOinWqSSnwqiLlL4Cohbi9XzvSt7KQYIAqiyCteIFGtXr 5HSUWPITRXabSz+0qosEtb37sEUc/sGXBLwzUtZeI6A1Dxof6Fl6r8UrVwvDFnEErVJ8 rOZY8sEzNlfQJyJ9cP/5UK1JfI9rPTXG9N4+Vp0PmD77KFg9bRM9ptWR6K/cc09dssfo 6S2mGr2jHW7Bp8vaieM3tfFtohVbecDmfIRgR+eUBuzajB1MXD7MJDh57TTMFSq12Fk1 s+10HX5/+wpbVYj4KTWYCXOOr5WWvH71k4taKz+mzs7Swmn2pt4Jt5I2aM7W9qc31b4F ZVDdBOU2O+/f/1g4PNwhzQEAAAAAAIrB1xwAAAAAAKAQFK0AALBOnvINbvAuu+fnO9XT 0v/n3/LdH+kFEc5/5bFzr91QILlVI4BPzQ8OYtJn1frsVUHi9OCeQfTFB//0Kf3/6cUf UeJzxXEtVa6dqK0UlSd06jPimz0tLPrm9Cta0XbzzHy3Tapn5Yw3WQz1ij542v57XkXV T85afaoGQ7dXzjlam1YjOBL9J16hllMmo9VbdPTI2VPNfV4WzSCqnZU/1fg84+PHP13w +uf2guM1WJFP1eC/aJF7LxhJlnyEaj3Pm1c4KAsa6kDetcnNm6Sc5pezZc9sO8vmVfHa HN/mwZsu3r1a8117TDAl9uHnCH3evWpsnFfT4EWdffSrNufWoMRPBTKX/n0C3Vk2ToID remwyukDlVPP4vOM3ubSf//7889JcwAAAAAAgELwNQcAAAAAACgERSvIMsidhLGJ/IbG jAFgWB4/DjqhLOzt/Xh6lWU9t2z/SkN14ggSvK3eoGOCut9t21fSVvpUpYV3r1xJCxeb 39r3XLA3g4qenJv8F0nZbA11WbnHe/YxCTLk/tY67nLKWFqtT9ODPbOdM2O0KmXSW+c0 6fh5PVY+JOcYr33AnHnGBZs6qHIa7wpHs3NQb1KzZOOrlqHTsd+tlGlJXxU93R/dpudU 03ANdnQwwvzVBitnG7+mKVlSXmQtV0Qz5J5dDPim9qf76yym3Ay+tVceO0G1XU5NnKim dc8r4KruMwlpDgAAAAAAUAi+5gAAAAAAAIWgaAVL9Ex7omw/7uRPDQswEIWZc25dHmTm OxStREHW5tVzPg9oPYNmMUMZ+929YEGbOtgvvrEGP6U2ffAJtvkEPIDtbUrSrxY7SE9p fywsdVa90d/WSGIRJq+S3jnXTq2y2U28E4T31BCNzLM27Rha0VyRE0HfrzbX16ryy9e5 9gGjjk4ZNTU6TLxbh6/neBfAHV7ZN6IXgPimGHz45dSzSKsSwqb6HZ/Z1LGrRQOXcHMF 1VhLGgZNNaNG7YGsOM5Le87+XbLxL80FKZrBckZOUNC3coQHT2lFk/uS4aeRc3CwQ5oD AAAAAAAUg685AAAAAABAIba3aEWRziCio1zQzZs3p1in2QjqEfJDd3ToKEwtqPbq1ava A3RMffnyJS3cvn279lxMwFN8on2kuObYLSrQinZQTnJ1EZXv8Y4XgzeqFpZEypXkr1b4 +vXracFHVDAgu/E6keC2/IOUb3SoBlq6DsHhFpxbg5Bw0wePossD0VsHbRQCrbLK+jhN 1UNLGgQMdL2hO/nr05143USbWbTdVsp+kZxeJN2Ow5w9pcPDZ7Bo4zRvilotg7/a27dv 04J2sx/pV69eTQv7thOXFL9Urzze5UqwKZomyRPru9HzlB11DrIRnkNlYqfNNRFBZxmV pe1Uq5X+P2rd1bx6+qtNnUd8ty7Gc1CJY0Vhv2YUBA1i8fq2TSTohxKcqoJCy8VObK6W HeSDt5sfmvnTP2nCv3fvxwJFKwAAAAAAoCR8zQEAAAAAAArRsWhFcZEr1X2SFSnUT75U GRiPSdd+3k1wj9xWr6zEy4cPH2q/unz5cocVm96UjVFyKlBqnTikaSRgDGPfLVwZdWVH RQcOtSpD8Tktukm49ZjwQOwgd/vH4JYcMlawIIvZOCNjnJ9+D95II+r9+/dpQQe73+R/ vGYfObHeYaO2QdxX1zw7VV56p8pLB6c8T1DnrKfeXU0Hmj54zyobpzN+ECZvxzZXwLe/ NnvKbw+7u3/mH9y3QPDurXZEh5XX6mlA+ojqeyS22VNeFRJUsQWfV1stfUD/dAffE+k7 y+pnVTbr7xiUuQ1VW6etrV2jPy4WNQLelWnVrl+UY2jCyWiy406tCmaxDiufvLOYcs+r uomz5iYd+snKYyCnECzn0+lw88O2qUlTpul7V3nhjNbcW1CpjCVnwllyAlWNj959nBnV 39pffdGEJeN1tJ6qLtz5d8EmaQ4AAAAAAFAIvuYAAAAAAACFuNDq0UqSKK8etCDZVZT9 8DD9f1PRSk6yzvNLOYUPwVvk3PF45g0jxmtlopRXkFPVr5oyt8FTMJ7BR4W/YDpAdACq aMU7rWxbi6LxeGOLVq1SXr9+nRZUYkCnFXQQlEFpIG1tTWKr2DDYXBiESua9u5A6rUwp p9OZrpHUEOSSdfQA0MG+jvpv33ZIcwAAAAAAgGK0uwWp/rlet/zR15b31Ki2cqX6tvK8 4btJfWfpX14GsY5W33R6o+PgTf0r2HneSXGobsNDfShPDdTubtjtXmsy5Q1WN1ewlYba gLWnL+4SVC3osN2Ue/duD98j3IIUGBaphFbYXBiEDyS/BekE/M8Wv0T3026rm4sDaIs0 BwAAAAAAKARfcwAAAAAAgEK0K1pxwd0NT6rblK5utF1RoEsNoodKv+fceXS8d1+pVVlB zkcIXqd2I8nMN5WcB6+sbvBh42u+bx/zhKKVZsENR1vdi9QjlB6zTPtIe4piogn4QdQq 2qoQrxfiEZFFHxpaBdzLlgA5sHHWeOn+s6Ai3h/jXRFy/kgB0BZpDgAAAAAAUAi+5gAA AAAAAIXoW7Qir1+/Tgs3b95MC/9UsTFlsVbmP/UAj5ypwqJViNTfOufp0wfeWhWSeOMS /1WrN82pZZCcBg35TRy8a4xW5jR72KA/HSkagcFNwmv7dyaR0bL1PArYI9PbkhZRBQwt n/2uXLmyvtUB0MUGzUVcNQHTIM0BAAAAAAAKwdccAAAAAACgEIMVrbx9+zYt3LlzJy0o i5VfMOL3OQ8ek5Pi7tlDRPeQD1YjKCFZuYZB1Unw+vv7+/HL7izbSorjep2IP2unzXZT mUntltHB/aK9SEcWn64aP+cXL+avjA8h3605vSpyhqKk1wmekvNGfQZSLDgK/N015v2W 4L6zag9Q6lIv4rn98T5vsOu7dScZRM7nFa1ezvDTC052Y/aeW7jDMdX/TXPU3qLnyPS1 8lLEoCIs55zlg8pfp9U6jyRnPXse7H1eOWf2azVoXc/X6fb0pg8+27k3+HTn5+dp4WJ1 GeCvk56ud9QjB6886jkYWumw63P23VCHZLBWwa4/OzurPTjYrbX30kjQQjBn6kDW6+tZ gZxhLENdlemqiepsDKLVmN8GpDkAAAAAAEAh+JoDAAAAAAAUYrCiFUWw3r17lxb29vbS gpJgK0Nx3uXh/fv3aUHJrlYtV/TW3XLdl61ZjN5doTh/jK9Y06p6qvnDhw9NT9FjXr16 lRauX7+eFrRhfR30gkEBjh4jL6r30luISlT0LG3bWmHCixcv0n/eunWrtp6LApxgv1Tj 52KbmgvxkKEerHKqa9eupYVgLHm1hbaknp52jd8xOygLyumk4w/uNox9s3uKXu/l49ml 1dDK+PDzo3XYA+dnOT1ifDX0mGGTor4yev2gfico6/MHS7c11/bPH0v6LMF06iMqmO2D D+XlbME47HmA1N7Cx3NTldZOuPG9iM/XSo3JdJbUTOszQ6tBNfiAaeIHcs46SLfVC4ai 19bVDnavAsiZ/Tz3q23uCXxtE5Ve+scMBpUEw1jrrNONhlDtlBd8zKBotNWhFIxMaTX3 amvrINIeUQWKNrsW0mb3RhX6LNpEQ/G94KUHQfHaynPrz5qennO69HfUYzzZ3mpPBdNU 0wXSTstrpNrg1CO15sE8o9dvVasSDOPBr8p8j+Q3KAScxo+mSh1uW440BwAAAAAAKARf cwAAAAAAgEIMVrQiarnyxx9/pAVPedUiYUF+1Stf/FlNd97eCdPgrXg+TRlj5dxUXyNN ITQP+b98+TItKObnWVz9RIFn0croMVoItpvW/LAqKjlpjgQHZTW+KVLiVC9yfHxce6Md bZmMnJ5XdzTFGv/X1atXaz/JKUjJyX96sLmWz/eIZvCOejVf4VrDmp2fsmc92xN4ujII 3/pYqqW+PaPuhj1wfhYETX3ByxBa1b71WZkghBxEx4OJy4dHTmhWQWLNqMHgr62VF3n5 7OSrJ8F+8VHneemgQMYzmTkHSFPhQ85Tgo3ma/Xg3r20cGIfygekzpvBQSrBoJqM1wiI N/MKZuycIzEYijlHStqArcZhTlGbwvNaPT09p3+E1/Hp2AzOR15603T455wcxU8EwaHU arrLmXuD6hW9l0pUFMmunVNU5+J7s1V7voA/PTgK/MHBVVnwrKan5+ygVvW5OQVWvqP9 fNR0gfTzauRcM0jT/Byc34MabcmZVVzP0hLfpJM1SgO2E2kOAAAAAABQCL7mAAAAAAAA hRi+aGVxn3mls6xGoymmFSQePYgYCHouBIL3CoLEXl/jUepaBE6vpl4kfptuPUbbUzdv 96ydHqzHBLzYRIKnK1MdPLgWZfcMpMLbOevZSs+bXbd6uveqqO3fnEKDIBWZk3POeXDA R1dwm3qXfuUJ/LEPnJ/5pgjSpH6zeu3EofLMtZdt9Wrdhl+r9gFBftu3W+341Rtd8Wi6 FWG1qrTyUZdTLKAXzDkXiK+hrOyE5enr4GWD/bKbUerim8tbGOQM2smy0D4fek2Tr2fQ Qy3IwwdlHeI1oWnbthqHK0u6dpbNKhLMAz6oJOd8lHNtUxvhOR9BRSK+O/zBQ829Xofi fLrzB9fOR946JHj9bnwn+skr2EFBJ8H8WuycYqKc48XXKui/k/M6Ky+Qlv7ETxx+VdzE D6VWpwavsul2eRZoVUEGDMK7KW0n0hwAAAAAAKAQfM0BAAAAAAAKMXzRiuxWLTlOrTgi 5dM8zRjcQD4n2Z6fRo4pw6b0nTKZQZLfn15790Wlhn0E0UdQNYHfn1wrozv5B/1KtMKe JMxin9fjuIsypX/f2d4zzN1y1P7ZcjKQ0iGsHmuVh0x8L/ig9SYsXsGkoKM/q5v9KtX2 ofpJkDjVwNtv2I9+4LSSE1IN7lEvHhD1NPhIkX59BE1TQZHIZMMvtlixKkP+9vs6+1i9 WK25Sth8+PmgzWkd0nF2asOPwfyqn1a9bBbnNWsS4XO4dyAKNqko6+4foefo6qBVvZvW KmcYB2UdwRm56WBvlbdvVeagB3sNoB/+wflIelbSNbX6yjlrBNdgOXNvTgOsnKPJi2jy /fPPP7XnjpfZDgrogp3orXkkqJsISudqD/B1yNnmXonTratXtzOU3jSoeG2icL7oQG6V 2w+Ki7vNq0EzF2AkGvM6MQXNH7cBaQ4AAAAAAFAIvuYAAAAAAACFGLFo5fcqWPv+99/T QtNNvD3WGAjCgYq9dUs+B7dr7lkaUHuRs+onStb5G+kjHBwc9HlTD1W2+iwnFnbS63yo ipI8nX6peu/Wq7tUxl3cfQwoo+iBRunWaaUDvZGHmbWDPMfu/MGKSXek0Pu7d7U19Df9 +Ufxq/YsrMjZL8Gx4ys89v4NuieI30Dei/Va5eolZ8D45vKxdF4dKV+/r6qPVa3w9SoM +bWqolps82oLnDSXInqE0uuVVBjlU1A3fgwG7SHy+YYN+h0Ee0ojx4eQtw7x95KgsmCy MpYcQRFHztHqB3urmogm3SYunWJynq4Tk/ejGaogN43JYJB0S+Cv7L21s+wsNtSoyx8e wVw3uKD7jJftBKUQKkOToONS/hZo1Y1LghqQ8fgozW/v4iucU6/km9HP0T47tTpr++X3 UM3yAGQizQEAAAAAAArB1xwAAAAAAKAQIxatXLbIbi2WtvLG0T/z4K6/zlA1CB56zKF3 91vu1wR3EVc3lqFi9kEEuhXfJtetgc7YtE0U/Avu6x607eh5H/sOXSF867Uq1Ar43uwZ 0J2g50WNHzjB3cj9fuwy2QoHFnVbbXozKbGsD+6pZsnpRyPB5nKK/tYywL/88ktauF6V qKhqyYfaafP8vAi0V2seVHzsVDOhViW4UX7OoO02q3ew2FxtZkhtHP+8Plf4vOefLmh1 MayhZoyVVRg7eeU/HfjWC0odXdCiwveCHuMFBTkFuTnTe+11BinnWUrbTS3ABqe3WDSq W8U343idVkTbVpO5z2nBTgwmpaARYZOeU5xvrlbFL90mhD7HoHfRarUFgrO2l7H4mwYT V1DNOvNalVYXMFijRdFx8ywX/MnjR9kEs+XESHMAAAAAAIBC8DUHAAAAAAAoxIhFK6JQ TS0A1qrGJMiF6mW73Vba17Nb5C8/hOaRxUXMb+gkm2/8VmG5YJt0yFIORbteAdFWYeaV VUWxDsOjqW6rP/+8PXfH2JF+53vBk97SNJns9K5FGpZXCmi/eKA9aLSkhVYtdfwu/eqL lJMoruUYtZ4qSNnt2bmgeVZZEqq0ag4/iHIGrR+DwTDLp231zz//1Ba62avC+cEeD+pQ 9KG8bcdIE3XPGSNnQPoxPuxn6ZZId8HspJ/42b9Vt441Tm45HX+GWj1vXqM9cqVq89T0 FK9cmCCGrbUKrpS0cfRgrVhOuVOHbesN3XJepOdFY7cJQfOzT1xNe1x6XrpLzlk7pyeO m0NFbQ7vlKRx6CVX/pNzNTocf1W3nLa5jg4/fUgwMv3gCl5nQ5HmAAAAAAAAheBrDgAA AAAAUIgpilaa4nzd8o1BcrJnjwmn9GO3ZzW1S/AAmz7C2ypbPngfk25byVdVn26NRSve PyIIM+tXQdR2+o/gGeb1lloM22BFr5bTJsPl3LpcO9EPt+m3ZKvMdlB/l3Ns+p4Kbore 6pb+kl7Za2omOOSDRlpqtdAtVOknDm3J9JOhzkd6WVWd5DeJ2Fk2KqRV4LxVR57JBLOx C7btSEOx5zSoTe0VUiplCkprg24dHc7a3dL1rYw393YoM/EGdlN2DdO7ezskCXoiBJ0E 8wU1U6349dXgl9YB330r+Ykv57ndztrdNmm3ybyPoVqlaD3PraJWJ7hd1V5ZqQvG1rMi b3Fgn531XpeZIs0BAAAAAAAKwdccAAAAAACgEFMUrTTF+boF4YLbkveMgXm4q1s+ral9 gH/eq1evpgX1QVDQVCuj6hV/ut+K39PR/qG6Zdj87uXa/q9fv04LN//4Y6da17brmcOH S7BWLkiT6lk5sd4OUVi/X3ewwv7WetarV6/SwsHBQeZbZwr6UGjh5cuXaeHBgwfxqy1u cd9mHTxoGmzhoDpJfG/qMX4U9Ak2t5qLPLfvke+g/MRbDwTPcjmjN/3KN5o+ZlCOoXXQ g1W4dMke7MdvDr8JfKtDMuhO0vRIHzY5E4VmdQk2lx7sg8FbDwRvmlO41Ife2gsrcgTH nX+oYGAHdV5Ney3YZf6ToBtXTtbdywdyTnkejO9WDJIeHLT88HeUbkN98LlXbVP6VCd5 p5WhkvwBLz/J2YnBZW3+8RvUTLXa9Rq0165dW7nmrlutUFCNnuZGrwEP6vtyJqVuZ219 Om3knGcFs2WfP1uC8Ry0SmlFR+KV6gX9dU71mGphX+/eXIWKPnzYLCmFy3gd7aBf1XKl uIIj0hwAAAAAAKAQfM0BAAAAAAAKcWG8l/5WLZxUcdxaarHn7a9bFRrkvI4n3zyfpvfS yr99+3blW6QVC8pPPA3uGTlPu+kFfUuquiG4cbeHAJe0d6niixd+/z0tfP78OS34B29a 1WA926nSbp+qewIrXRncyNrf1Pe4P9gTtiu3ZKtwb/Cyvhn1goPXqoi2iXarr4Z+cvPm zZ1lMfsg2LmIPlbROO079SBwPkSDioOcQybnBTsIssH+1j7qtFsXxSDV5npdveCZ3Qc7 mJ08Aq03/eWXX9KCNrvGvGro0uu0mpSCldHLikZOzubS6ikH+6oaojmTWzDn1DZOt2Gj n2hgv3v3Li14UNnfQqt3XZFRdeKopogXx8dN6xPMeyO1cApKD3KqOby5Vc7qBdNm/l7L WSsfkMEuy1nzbjUXg1zb+EYLGnDkTCZOk5IWes69OScFzWC186Oe6y2ifB0m6L3SbSdq rymCromlg24nppwR7gdgz/N4q3Wurad4GaM3NvJqDp+4gjOLnr7bXMQhwWdpNY3U6FSo 8vCcwnB/TFDzEhXZVQ8+sREeHVbV4XnSrzPIltOFtAa2nxN9ZPpcpF8FB9Hm2tc157f/ +x6CNAcAAAAAACgEX3MAAAAAAIBCTFq0IildM1SYNicrOxQlfFR2cmpJIVH4p6nTSmBx n3P9aNAb5sfu3r2bFp4/f54WLlz4MVS+fftWe/DKVT06OkoLT548GXhFq7d+awUUmyIn eC/dOtR0VG1b1QjcunUrLbx58+Z///fGjRvpP711iI4Fz0lOoNUmncM6aLcGHUyUYVY+ 3CccPd1DpEF8sTFoatlUZWWVcPVD3u/rvpgzm2ewT9Wa7/kIV562udVUENDVOp+simIG BSA5clK+i+2WMZn7LpOeq9pHzltPeQAOsik8S+8Ved10uzgZ+5JmvPEzh7nX+cQ1QTC7 504caQyscerorLbOORNOTkXJyjda+l7dDLs3F+eajPqRnFN/cOXgulxL9G74suW86NvL T7SFNTyCXkKndlGnv2QL2EEUrQAAAAAAgDLxNQcAAAAAACjE/1vLuw4bk5sgdLekN4ry +eO8e6sKl8G9ePEiLahoRR4/fpwWHjx4kBaaGseoxkGJuMGLVk4nrFcSpbw+VbmvPneO nm9kNHsE6nFKfHrsLbin9+BabdJF3rJ6ltdorKx3cN5exAOE+5bw9J8434AjbdJTS/AG BXo9RUdQp5lwMSllP73bkZg1UVePafVJ9Mp+7Kxx0shJg0+5eoO8lxdYDfURur3O2Btw vNef5+lsLdcJPd9rpFWd5w6KrVxnf0C3c+Ksjousyw87+wSXXsFjZBOHx1YJrjf8Vzkn a/1Cuz54sN5CNdTnm9A3hzQHAAAAAAAoBF9zAAAAAACAQqynaGVT6Pa2i8qUKrSjOycv gtzN2bCxk2DeGGU8Dx8+TAsqWnHpg0/QZWNRaDDlzYFtR6d4YYfShjEoRXbnzp20cHx8 POo7enWDNpC3MJigaCXn3tE6fqMGGQ35wKDOxR/jLgavn1EBMVTByMrX8V023jzmdRk9 q/ZytlKfoiSZYDyvZ5ZrUMJt2G2/60S/ERFcAAX7ce7LOAP6fJVTouK1DDnd0BZvUfV6 E7X/CPhZrPZeBZxZxqMzlFs0/cwoNtlpvhLWDgoqU3QFqDedyV89MdIcAAAAAACgEHzN AQAAAAAACkHRSmRPWayed/sfh+pH1BhFrUymbNSysmRmb29vpLf2cokJKFx3cVU3h0FS 8Tt5DTjkrIoUvnr1qs+byt+2kWvFC0sKBKpNpDTjxSnT4KqAaN7sreov9r8nBk+qj9Cz bKTbhlBq0eOL3pLDeRnRSv44jYTBpxdPz05hrd2sOpiyXVHJbL8vpqnmbDA2lxcdA+sV lNbmnwR9vsrptNLz9H1erd5udUWUM236tfrKazBOc5JTTdnq2mlRea1xWF0ta7/oes/3 75JC9fYXJ/vVy56M/NcBaQ4AAAAAAFAIvuYAAAAAAACFoGglovCNZ7xy0vjnuqXwoB0K Hj9+XFuQnDTa4G1ZVDKjF6ytxqdPn9KCVjjo0iJv375NCwpTHR4e1h4zZf+OQHr3Jamt oSKyGa9z48aNtPDmzZvar46OjtKCappa8Sycl7HUVSusrNvX6jCZMnjv7+VlRFmtPVLV 1fidg3rS4XBq1ToKGZ5nb/YOKdP+huq00kqfTklTVNkoX1r9YA4tVzaO7ynvL0BMukia yjR/6RQ2wZyGTTH4PBA1fdOsPvLkM/jLBvWzAVW46CpqcYL/vgWCQ5JpOaKa5TYP9sag 4pf3QafRxWOs+KV2LbekL2F1N4NL3fnL2gAAIABJREFU9pRhkeYAAAAAAACF4GsOAAAA AABQiO0tWlncabYKU+kGwjlZrMVjmh98RSnZVQFsFZKomiPIQqvBSjeqMZGhqldW+uuv v9KCPqYqU96/f1/71evXr9PC06dP04IXrVyquopMSSNH6ay0s4JSDg90DU5b0mkDdita 8SBZShW2iixesmTdiMH76pWX3J7aqmkmK45QfnWC/KV/KI3AnFt2N76sDrfRNtqUtSo/ v2v7Z6zubjM4jRztzb89C93DUJ2h5iYd7IN3HMDG0fFy/erVtNBqqOcMGAL2m0vzqnZi zgTrf0p8tRaNOZUpg0xHwSw3aRczc6rLRW2l6lfMwk207yaordNb5JRu+e0CtKBf+Qsm Pg7HnjNJcwAAAAAAgELwNQcAAAAAACjE9hatLFS3e20Rwc+TH0JTIcnNmzfTwgQBM++Q kqNPss5brly7di0tqBJnr9odd+7cqa2n8yDcWqTM1ZK2L+O3jZiyX4mkJGerohXx/h2D O7c7gXulhv572NYe0WHb6obY/QQRx/y9ps9yUrWYURY3+AgrI4ux8TqtDFs4FjSs0eur w9Hx8XH/d9xZGkiuyog6NAEKOkMtaVFUDRtNubMN53vpzTrPDSXauOKmoWYVzWneFaLb kbhxW3JTeNo/p/zEx4kmc02AJ9W1xH5zTXowyIY9r/lnGbsoZkDaI3NbsfnQ3pzg78FW RZ361f7+flrIn2On392kOQAAAAAAQCH4mgMAAAAAABRi64pW1nu34RrvmRLkeRSBzqHW LQqGBcHpW7du5b9yjpW3BVZbEPVV8ZVR9cr169ebXseD6EF0aqiUtQfJGu8k3Cmd1WqI ThAA07Yd5LbPS0p7OsmJ+waDoWnf7TRv/2C/BK82pZHevdWn67YOE2zAYV85qIPQ8fLq 1avar1T+8+zZs7SgCVB1fK1KCNUdTJn5nAkw/SqYPIM3OrfDTUfiJysS6ZbJ9xXTTz58 +JAWoimoR2cB70owbC+bQthWGq+D2LB2dfZpfkxOVNu7quXUzy45HKzzV36Blbfu6rkX +h5366P9oupU7egd22VekRe0zVpyLVfN4eO1G2taB9+/G1TuoT1yYi05Em/VgVb7V39V vXz5Mi1M1kNzp99Q9BE+bDUfaQ4AAAAAAFAIvuYAAAAAAACFKLxoRW0FlIrp1h5iJIou 53j69Gn+g4PuJM7D1dKtnmVlfkkZyBs3bjQ9Rm1Z/vjjj5Xv6KUQi1ugV485GTp13PQx eyYJxwsiqu7pyZMn+c/y7LdHdvN1e27QFcIDb36M+0fISSb3f0oZJvh0c9iAQUI7iHO7 IHOrp2t+vn37du0nrYKmixNccyTYJ8DaGnpPHL2sfqWfXKm67SwoMb74waXar5Ycv82C W777th0p0e05dkWC55apXmMTnDkctq2cWocUpxF+sRpRp3ZC8dZdWZrryC7qIGred/Ug d3Prrm5TWavjbvXqTcjbqWhH79qGvWJTd/DpfJtctKNs7KMg5/U3oGXPqlpC9eyQPteZ GyTYd61m8vfv36eFbtcSa7RkhHe6cmhCmgMAAAAAABSCrzkAAAAAAEAhNrhoJYj6+L3f Z1Wropvqew5HXUXUKkW5I3UeUTWHC2pMupWfBPUsLr8mQh9cSeCegnjb6dDJt41L6orq nrT9c1JtPkpTyHNJfD3DbhX3PYkf9503PshpqeOJ4snypVtCM5gmpYODg/WtzjCChLaP w2AgBXPReH2+Tq2PgBa8U1Jt1YNgtp83c44g/5jjlVGMfURvwP3/q2PwvPnCYDIb13tF dNjq9HFmFWHSrWhFY8nz+VmbK7uFUM5UFvykY683e52cSgpf1ab5M5hD9MaXqhc59wv+ 6if+4FY9U7Trp7+WiPZLj/ZSE8vfbn7Z5oNkcxtgLQZo8wHYbRbd3Kvcka4cSHMAAAAA AIBC8DUHAAAAAAAoxKRFK015qsWt4P3mz/arICPnv/KbKq+Rkt4PHz5c+WC/WW5O3U1Q Y9Kq/CSgEJFXwWidWzXyGIQGzMnJj2IIpdqCeodut6fuUwHRqmWDu3r1alrQHdS7OT4+ TgsaXdqb+pXoY6pKJf1ExVMa2A8ePFj51ou71jfnfr1GQHS/9EvNPRe8v9LmpvgmoJnh 73+3IdB/Hh4e1h6pGezRo0eTrecc5AykoLpBNYlamCBj7NNdq5B2vuCzDP4x/QXnn9Ze yUdXTmRXj1EFWfrJlGUjmzLTqvzEN2vUIMnadmhTe3mXihq8XVGrjbMkuD6n1h7iQzRI 4+tXe3bp5UNocaH1/X81mv0CTGuw6BVl66nX12VHt0r2Nc4zOftl5gdgK8GscnZ2lhbU Z+qkW/Oj9fHV9c/barBdu3YtLegAaXVlPgfB6O1TyEOaAwAAAAAAFIKvOQAAAAAAQCEm LVpZmadaElKyRFwQ48y5rfQE1HDk5s2baSFFlFt1FdG9uG/cuJEWVI4xE14FM1Kcr9VO XNzDPCfua8/y0bWkT0GPQZVzn/OAxoBGxZs3bzqshj6mXmdJFYxVJ+lZ//nPf35+oAZ2 q2hc8MGD/PCe7anFjdP7bdtto72m/asKlC9fvuz8NCRUtPL69evaiygnqYI17Tv1XtF8 qHf8oLeuXvm4evrVqpojpyyr24Sz8lk957Gg04p3mFIZmjdfaEXr7DNYz1fOFxxu3Y7E oDKlyIN9ZbOJTGlTaL9PcOWQ061j8CKaWmlzTuXp6b/r8n62qHfIqGXwx/hPWtWq+M5a 0kFMBTINL9Jq4uo5ywW1wFHxgLZS9emC2an2V4BqZrut+VDNFguYZzZFsKkXrY6q8bNX /SToRDkrPox7ntT81N/tynxWgkKe/BMKaQ4AAAAAAFAIvuYAAAAAAACFmKJoJT80uySi k3HL2clCuZk8v52KVloFkPTcVqUu66UQkZLYg3j69Gla0DbJimA1x2iDuqcgfDtsWLFn ZHSoUaHX8YPobVU14JurFgvsdgN56da5huxoT+/fv6/9pNYB6v79+7UH+Db3gib17hGN sUV4vnodFb6dVr2Z9JgLFy6khW8fP/54VtXdIFifHCuf1eplNenduXMnLbyz0p6gCEvb baiKv5KOizlUpnS76X23t/CfBKcq7/HRJCjJHE9OGUsrKz/vkg4drU5MOkir11eVRKt6 h54fc89mOe8g1qTV1Uu3s7bvBb9yCD5CR99XdZiaExTBx5gPyCmnu1ZKOkePLZi4fEc3 bVjSHAAAAAAAoBB8zQEAAAAAAAoxaaeVPjYo56OSjcuXL3d+7tz6quRQdmiklc9pvpBj DsURQ72sWqUEP8nhufrxQto1G3RoT6c6lH6pgtNq23R8fJz/MioYefnyZVpQUcnK2Sko tfhpNeu50GAgaVoIHqPoqW6lrvqoekp1HrQFFkVANp5z0rOq33n8+HFa2Ny7oxdpLdPU sG+63pl28HfXYZUa0wR34M9pYaMmLLttWq64nh09/OnDdnab4HWG/QiYki4Ynj17lhZa XW+MTYe2CsoCZY86v7S7fft27TE5W0DXG7JxFx4rPyZpDgAAAAAAUAi+5gAAAAAAAIXY mKKV+VP4R2kiDxGttIm1KpPJSdFvG2+5Mn1rHu0Xjd6//vorLTypOmigFSWoVbuhogbV s9youpy8efOm9nSNAVUwpWZPP1t5NAUB756WFHFYwxF189E91VXQ96EaXd57ZXqDJ2OH Ks0DyqZDr3YMag7R5KkyisXjrIFO2RF3IIdOzV5Eee3atbTgBbBqLqmz9kgXft2aHxVJ e0pVRd2KTfzvhY0rWlmJNAcAAAAAACgEX3MAAAAAAIBCULQyGL+/t/KQKfe1iJ0DM6Po 2t27d9OCEon5lLefvnCmMF7WoUy16lmCXRY8XVbWpExaI5aRGF8U9M2gVkVyuqi0Qmne 9DS0VNs1XsUWJrMk2W7zDLUqKEpVNvLrH3+khVZTmR8O+rtGRSvv3r2z9/xUe/BIqFUR 31PdLkX0OgVfeJDmAAAAAAAAhSDNMSKlOXTPHvTBP7xMoM/38fo+uOAvhgf01e67qX94 2d/frz1YN9/Sg2Wkm1Z2+wftnv8MnvPPNRcuXEgL3759a/rJ5tLt3LSjy7sl2Nxo0A6e zcEc6DaKul0fN/pFAfzE97W6TtBUptuQ+63Kc+h8pIXDw8PaY3S99/Tp09pPtBqKmvrT kU/BQ+3Wg4ODtODXTjnX4XpMwQFG0hwAAAAAAKAQfM0BAAAAAAAKQdFKO0o/ihLFQUlF wXGgKSkRp/jc0dFRWiDXPRTd2PL333/PfIqPfMqLWvGovMKoOUYqEer2suPVK2lQBZUF 01ev+FAfaguMfTs3YEvoUFrcxhjYWMHlgf+t4feD11Gg62fVswxVteev8+XLl0FeGTW6 3jg/P6/9Shcnan+h28c+efKk6XXKQ5oDAAAAAAAUgq85AAAAAABAIShaaUfpR90GXwUU KqkQGk+MRIk4qoHGo17oK9GeoJtWpT2tOsYPUjTU7eAavF7J79neythlLLs2t3M4ALOi SYlqSpTNz0c+5nVm93oWb/GW4/Llyx2ehXyqM7p69Wr+s/wPz+2s2iPNAQAAAAAACsHX HAAAAAAAoBAUrWTRjWpVovL8+fO0ENxAWFmxf/75Z7x122ZrqQbSmx4fH6eF69evT78a G0GpyJcvX6YFHTgzoYYyKtJRdUOfegc9V5FRrwHx+6UH47lV0YrzV1bZXf5TuulZxNHt 6ZPNDKej1c3pXKM9RT8pANgG3S4/ck6W16vCh729vdqvfvvtt/z3Eqryx5ZTQezVSQ8f Pqz95PDwsM9q3Lp1Ky3cuXMnLRwcHPR5wWmQ5gAAAAAAAIXgaw4AAAAAAFAIilYijx8/ Tgse/lFMKyhaUZ75l19+GWHtsJ5OK0rRK0ye4oUfP35M/+lRwLL5fey1ZdbSE6dVVVF+ QxnxYpMgVtqq5iJ48Pv379NC34Bo9RY3btyIHzjULmvV3WDKSplBmrD4ne0HRz+pQahL moLZ2u+ErrcEXZAwf36Bkc/Ptl6desGmu1YToL+FahlauXv3blpIl2e3b9/u8CKQlWXI O8v2nX6iMaA/e0XVspo/O1w2rxFpDgAAAAAAUAi+5gAAAAAAAIWgaKWjnCS2QkR0WtkG Z2dnaUFFKwoffv78OS3k5MpcnxDjBJ4+fZoW1BtC2Tb96v79+5Otz+DJ5LT9+5Q2DMg/ ndrZHB0dpYUnT540PT2/M8hakvybV6DRpiSnGx1E2iO0XOkgKC+6WrUeaFVghY3D/sVM tCp9HVurSyZd5mkhx+XLl5t+ldp26AHPnj37+ec7G9LOY11a7Y7gWv3Ro0dpQddg+kNG ZSy61Lx3717tlVUErYuTlQ0oh/r7aCXSHAAAAAAAoBB8zQEAAAAAAApB0coSr1+/Tgve YEUU0cmJQV65cmWQFcOcBSH/LbmTfxB9nEnw3ptr6Pgt4Cb8JycnTb/yJjgdTDCMu71F z53YpyhpyoKyzavomYfUY0UNVsT3HWdqYGu16tHW6gV1YgrOMjOvTZZuJ9mgJWXT63O+ k8GrOXwnXrt2LS3o79+gnaj/2auafX/l1Ijn1atX6T/9EBj72ps0BwAAAAAAKARfcwAA AAAAgEJsb9GKIjQpUdNZkLf55Zdf0sL5+Xmft8BGCMqXlP6aSbeONdqgIOKw9SwTVHwE yUa/w/ZKus+25Ow7Na3oZoOGx/S0E7Wgu6MPUgL2+++/116WW9yjAOo8pZlcV30qT8ih UmU1Gvjrr7/Sws2bN9PC4eFhv5XF2ugEqh394cOHtLC/v9/0LJ3ygqJRGbYyJadkXmu1 JaXTJUnlljvLKi4HpylRk6R3YxEdIPqLRpeLK/+g9kNg7AZYpDkAAAAAAEAh+JoDAAAA AAAUYnuLViZArUrZFAJMmSvlyqhMCcwtOamcak7idKXg003QyUUhw6AyJX81FD78VhWS KJitoglXOyhaveOovMnOllPuVAUvulm609Z78+ZNWujZg2A8vqPzb1N/8eLFUdapLJt7 KGkkvHv3bpAX1OSW30jiZ9qSOcURyHd0dJQWdKpSdVJQiOenb+0OFfR9/PgxLbSqVZmD mZyIZexShQJMucv8vXLefZAirLH/KCDNAQAAAAAACsHXHAAAAAAAoBDbUrQyVF8VzIoS iUo9KYCtHa2cqm633pNuKdwUteqZ4xr2XtxzM1QrDYVI//zzz7SgFL3CkPqJ8vkSbOSm X3V4ShkudIoUtspblr0Bx/Pw4cPaT3wCVLi69qu3b9+m/1Sc+8qVKyvf0Sc97bvPnz+n BU25+pWO+pygstdEZFVJ2HjrMKiUP9dzNYeoWgeyudUrQXXS3bt304LXOumQ0aHUKnjv R4p0OC368O65FzoedzOguU4LPk1pT+kxapfz8uXLtKD9K3M4MemzbHQbMm/cVuPlrtiS TeGdKBczj8Z8j01BmgMAAAAAABSCrzkAAAAAAEAhCi9aUQiNWpWyeZxvvJv3cjf+Prrt FwXvVXmkDKQKUjQGcrL3QE2Q0A7i3DMR5JlXRp39kAxOlzoSnUL+QWJ8cJuSqx+PtkBO Lwl0cPny5aZfDXWZkfM6+UN9yqlMdV6aGdZ4JP7zzz9Nv9JVgaopNV91KwaZrJFiUP6p X2njq2XP3Kz8E8zPLHfu3Bltddbv9PQ0LdCiMaCh3+cCgjQHAAAAAAAoBF9zAAAAAACA Qmxe0YrqUBRWV9RH7VQePXpUezDK5pnPVvf27/leyNcqIKqb3isZq43fKhi/0bcox3zM rVZF/vjjj7Tw+PHjtKCzoWLMR0dHtV+hJHO4LX9JNUSqVfny5UvTY3RmuXnz5soXVKGl YurSrWPLSFq9vp9bW6XxX7x4kRZ0rr9//35a0OZKnVCCVkcqP9GLONUa68G+F1qZvng5 2C/eIqoA+/v7aUG7VaNFg0GdsEpSRm+dDnz0DnJSI80BAAAAAAAKwdccAAAAAACgEJMW razMUwU3f9avgpIB5Vs84o6yPXz4MC0o6KgQqQJvGgwPHjxIC6p7un37dlo4PDwcdT3n 37JhDpSuV0ZRggybb0m2LbaNItnTCw63wY/EIg929RpQEluNpQKaEnU6S1SspOz3eDZl 4wc9U1xQq1Lb1Ds/FYJ9/vw5Lah8zM9iOTal/KfVNbbXlfsIf/r0ae0n6cHanqK5zp/i epaoyKYM9QIEu+x6NVVqd2xcGYsfOEWe1IbSZz4kzQEAAAAAAArB1xwAAAAAAKAQ8+q0 khPRCe4960lCbJtbt241/coDq36Dbr9Tt8abXpn2PX2oJYQqU1Rn9OnTp7QQZFCHip6i AN0inSuftYlJ0WDeUynExtm2EO/5+XlaGKTYVvt9yuoVCeqOe/Jee6lsJ6crgepQfAt7 jcnx8XFa6NbvoNWzcpqSqDrp69evSx/Q6ujodih5F5VWH9PrynMu2lWSDCSn1ahTiYoG 0lqmu3a+H7/cUSFHcA2Qf0IhzQEAAAAAAArB1xwAAAAAAKAQJUdAAQAAUDYVP378+DEt qPzk2bNnaUHlD+r0oYi7ilYokQCAzbWoZvle2EKaAwAAAAAAFIKvOQAAAAAAQCHm1WkF AAAACKhK5d27dzs/dS5Qz4V79+6lBW9qQJsDYOOouYaOcfoeYiXSHAAAAAAAoBB8zQEA AAAAAAoxYtFK7Wan/+vCheWNXZREkqZH7iy7n7YefP369bTw5s2bla8DPH/+PC0cHh6m hVu3bqWFV69erWedts/9+/fTgg7tu3fvrm91sO0uXbqUFv7++++0wHmkbMGVg/9qPDrp aATq3QOqv/j69evPP//8+XNa2N3dHWwVv8s5HL7ZVZ9f5nWjmLqC62lzaQd5oF2nGNGh rcdoQU1YZPDeKz2z9+npQ+0F/1XOK+dMkvv7+2nh+Pg4LVy9ejUtqMHNb7/9lhZ0DXb7 9u20oI0DJKenpysfE8x7ar2k63wN4wnUDrTgeNHRwYWHtDuh/Hu7keYAAAAAAACF4GsO AAAAAABQiJl1Wvl36nKps7Ozpl8pPicK/ygsh20z85qIVknRAii/+vr167SgIOKTJ0/S wqdPn9LC06dPp107AGsWTIn+KyqMmnzNuJqawFC1KqJCntor6+c6xajYRGeWx48fpwXv tKKBdPny5bTw5cuXQVZY66k31SlPtSpBJLupKGlKvno63HLqCLTmWlBBgQqHdT3guyaV Een6TRUHPelDUaq8KTTYupUQ6oieslal6bDdtiv/oXQ4oZDmAAAAAAAAheBrDgAAAAAA UIhJi1ZWpk1OrerEgz1Ku+VE+LyMBUVSZYriqbpNt9dEKB7pqVTlXafPMSpHN5Ow8Uje vXuXFnRDdac9pQXVGele2aLCNN2nutvt61GkDtFQP2vMNl+qrhAPHjxICzpSbt68mRZU AqYMf/qAeu5aSsNatVfLebr/qsMeX+/cq9Vo1RtF6+wz4fQGL1Hp4ODgoLYgOky0oHPE nTt3mp7ltc96us41OlWpY4j3Z9Ge8roMp+uWldVY652dNFbV4ULNU4LKINHm0oKonuX9 +/dLn6IHuKOjo7Qwk7rX2Z5BNoJKVHI6TwVUjzYHZV/ntxKcNRbHS3UZs1MVr+UjzQEA AAAAAArB1xwAAAAAAKAQ8+q0ovybh1iCWIsihTmJpkV1QxUpvJARIERJVJkS8ESZsqMK XirCenJy0n+ttqRTgAdZe1afdStM25QSoU1Zz7npcCv1Ke++Ph4dDqpVaXrM4CNK5+jf f/995ToETw9+MhJdePhk0u2W/t1obuw2p62xRHcOtSrd5BwFQY2JD4+cziOD7Kmcuq3B Ba8cXL1Lqw9eq2dRHUrORJ2zW4M9pY/QqgDWV8xXgxP6HGjjT3DSb3oDvbUfL7MdG1rV gYvC9HltdwwylZHmAAAAAAAAheBrDgAAAAAAUIh5Fa10o/uKeyJOZSzKFj579iwteFcX bC6Pld67dy8ttLprvWgsaeR4vO38/Lzty+ZEsIqMNXpLCKVAc3KDrXZiTjJWj8mpPEpr OOXu0JymirySSplajfCcJLDrEAvfxLZcvs46UnRXeWW/degl6lOgF1FXKb+zvYaftwzw Oe3jx4/tP8qI0hr6EbRX3bNdZYwz6c2U04lD1lgwsrm1Ko8fP04L6oeiKdc7rQQdPQI5 80kwEwazXKq28HNitzKWNRaLtaJeNt1od2g+zCkv0vlX2yTowed73Oeczb2o80s4fTrN nzpftJrBmgzVYGW9OuzvRT2LKtkztqeepRGuQ2aoq0cdMh2GcVAIpj/Gd8epISLNAQAA AAAACsHXHAAAAAAAoBAlFK3kUOrJ408KXCmNhk3hOTqnnJVSqTkUVgxcuXIlLbRqKLCS kma6m/HmBh3V2Mh3UKubXWubaEHdHHzjaI/nBE2dB4lTGLWkspGdMC9dK9JZ+cilvwoo 3JuzXzwJrEDs9MeF4uszOTZVdiEdot05AePFQWqjQodbt/LAweXvkbOzs6Zf+YadgDfz wmQGidnH/JAJCluCMbBLc8D2dEWn+UF7PGfXa5fp74Vu/aQ2V1Cw8Pr167Sggq9B/qoa /Nz65cuXtLApE+xJRl2VSlSeV6f+G9U2zynLaiXnSNFV9927d9PCixcvhl2NtkhzAAAA AACAQvA1BwAAAAAAKMS2FK0EtiRyVqRWNzMfnG4EnaJcitjlNCPIoU+3ueUS40X6g8C5 6E7OilD6lvR2OdrsSqUmKnoKerK0omC8Pos2V4cmPjt5TUlUdqGso7aJxnOqPvjtt9/S fyruqwyk7pWtbaVcopKK+nTBBDuTaqz8KUKp1ymPTZXmXbt2LS28fPkyLWgn9qEhEXSU 8Jl2to1pFrepr2bd2gHr87OopnUtzWJapejXaJ6dOFpRH6LBBXNaziHTrVsKanxK92NK 5zXNe7pOCCphVZqXcwUSrFhOTejYWnUx0wfPKYWY519VOupbVUyvkXfcU2dA5xUuQ40o HRfaXMFUprOtDqt0caircV1nToY0BwAAAAAAKARfcwAAAAAAgEJQtLJIAmPjzCTcuzob pgfMOyM3uCATOFRcMAhe9hweteC6coOedW+VO9WDPRivV7548WKHt9BdzRUX9FVV2YVH T5vCqPr5+/fv83+lTzflDbe7Dar8+ovxsu45fCMjR31UzKNUytFpZTIeqh9qm6tYbyYX J9sp2Pg6ynIeM9S1hPjp29enQ62BRm/Q/s9HuGr0VJXg66DmKWqW1/M8nn+xVMY06EWU HbQqER285VlOCZIuj72j5Vralv2MNAcAAAAAACgEX3MAAAAAAIBCULSyCG4p6a2UNebp /v37aUE5ujnwXNngt0Zf4025uwnWs+fNrvX04L7fOUm/bvdLb3qjofpuBP1fgrcIPu+9 e/fSgg6ZV69e1R6jepYOocduO3GoVOpkPQi0iWSCQ9IrZRQQRY7arjmda48Yyhymp8u/ O3fuDPKCa+nRgxqd5vwSURcMfrrs2SWnpw5XEUHnC72Id+sQn3D+rjbOhea5KGea8nOW +oVpj6jGNnUPmdXF/Nxomvr8+XNaUCM8jWftaP0l+/jx49rreM8Udc3zx2hQ+WWP89WQ tU+JpDkAAAAAAEAh+JoDAAAAAAAUgqKVBSKj6EOZQAXMugmC8YMXR4wduc/ptNLtrRWN G/y20gXwTdqqNid/j+Q8Moj75jzdi5uGGqsdSl08izv4ISmHh4e1haOjo2HfYkvUZiGd 6L2f0UxwKTK2J0+epIWTk5O0EBQ/oiSpRGInvHLQKcYT+IGedbhNvFGFOl+or0orwVB/ m1EO6Sd0/7x+EeunTm2uyfqXaa02t4dLt2lK7XK04PUsotFVTBkRaQ4AAAAAAFAIvuYA AAAAAACFoGhlQXmeN2/epAW/CS3mYFP6jHQTBOOH4jffHjxyn+TsqW4Bws1tNjHe6G0V mh1kUEVvVK1MkMDPWU+TUhRzAAAcEElEQVR/RHB7+UCfbizRLhttb3qmWltSSXvkqO0+ jZ9//vlnHauz2gRtHZCwqbeNLu8DKg0ILjP8pDBSIYQ3qtDVmuoLAt61bfD6rJxLGi9j aVUQNAhdWo9UXrQWwQzmn1c0BtSWRTuovCmRNAcAAAAAACgEX3MAAAAAAIBCULSyhDpl HB8fpwXd6153NtZN2skPT2+eSbNSW34oW9hhqAd7arzcoFY4p2HBsCUkfbZVLGc9NXF1 S6U23fA8eOvgjU4zoo85H0qvs9upVmUQGqKevP1qj+k5onSuCe5z3rOX07aZ5/kiQKcV YHo927f5qWoOM0+rJmtTUrcj5PNTgzoHuaAOxS9pWl1WbdYfO6Q5AAAAAABAIfiaAwAA AAAAFIKilYh6r2jBPX78OC08fPhwinXC/Dqt9Gni0M3e3l5ayLnVtvObbzuNeZVudejG Euyp8fKca2zCEnSuUaHB27dvV75Oq6CpXlllDq9evcp/uii+mJ+Z37Z0vdf1eNuXnk2L guxoUMaCwNzOF0206+eQdQe2zeBXDtPXV+bMdTpr5zx4qMlTl6zoQ3VVOX90aJt7letX a4SnhZySZxUc6cFzPmeR5gAAAAAAAIUgzdHX4D2osdKcvzichlqpd/unY91Ad1iPHj1K C/oWWT9xa25d3vxvFCOt2Js3b9JCzi7TrY6l1apMtknLa7G+VNatUgc6EWxbQAbi/7CG sW1K0gdz0+124z1zuCv5id//JX/ws7Zfb+hsqDtqB4n4ySivuiV/QeSUI0i3LKGy3nNG mgMAAAAAABSCrzkAAAAAAEAhKFrp69q1a2nhxYsXtV8p1ZYSXLONR3qqLecuiWs02y05 T37zy5xbkHbYyLpBo2Jvt27davsiazeHOKPfgvS0TdB0sgOkZ7p+U2pevMn8eDZlm2yQ 3d3dda9CO4yByejQ5qICrQS3Gw/0LDeu8Ut3v07wsgLNh/70bvzY0Z9FE5wx8+kCdc0V 03Pi55ryZkLSHAAAAAAAoBB8zQEAAAAAAApB0UpfupOw7pz89OnTtKBU29HR0c8/nxv1 gJBBAnUzsXERrMFjft7jo2enlXS3cA14HQJakCAVuZa0sOrIxCt6FPvcLSjQOFLvBiUe fScGu1W3YdfG95vV57SFn55Sr27j5pntkaaaeY6on+lo2rgqG2Br6Upmd/IGSX7pnkPT iz/dz2JeP+sXqF744JeCmJWgr0p5JZOkOQAAAAAAQCH4mgMAAAAAABSCopURKYndlGdW ZlvlLUUmnxWLunr1aloIOrksEoBVss4D7Tdv3uzw7psiCMa3EuQGczqtiEoMVPGRhqtK YHqG3KbcQTrQxCt6po+e9uTbf7IgouYrHZJqOBW8o0bUkydP0oKqqF69elV7zKwC/BPc N16TJLaNKsvKiw0Dpep2tPa57ElVw0vp6sXrc3PoWVq9O3fu1B6jc71O360uyDEHuszQ WHr9+vX6VmdcpDkAAAAAAEAh+JoDAAAAAAAUgqKVwXiQTGG2plSbAvO3bt1KC8psO28J 4Q4ODla+zvSUj/ICAadSCyXi9OD79++nBX1MBJ4/fz7SK3sZUQeqd5hbVVEBnVZyat+8 /kLVUrX5KgjlqtvOgwcP0oKmwVYJ/EePHtUWZkXbc6iCMqejlXvUby06rQBbYuVpMag6 +fjxY+PTqosWr8/NoZknWD2t2MbV1umaZ27XnNPTBZs8e/YsLZS3cUhzAAAAAACAQvA1 BwAAAAAAKARFK4NR2FjJKMW2042Ig0KSnJC5Kj6Ojo7SwtOnT2uPOT4+TgtBVcjgcqpp 8mlTeGVEkW1ohhLsBd9uZ2dnK19QiUQ9Xf1Zaqm2bvulvGjcqH7t1//F95Hujv7w4cO0 0NRGREVnfi9uL+LQ0Nq4RGsgZ6zqMSrbUUVPQIcttSqg0wqAdAbpVnWCgC5XZlsxvUYF n3RIcwAAAAAAgELwNQcAAAAAACgERSvD83vYplsTK/Ldsw2KWpC8ePEiLXgiXRFoPWZw ymbn9E/pgDhZK8Fe8O2YU2Zy7969tKAwm+oRTk9Pf36kgvetzC03qE/Rszykg5zd0TNS ePv27dpPdL90NTdRuVOawVQBp0fqXtzidS7+Wbx2Y3MbSTTV9ez89KHevXuXFnIGku8X YPopCMBMRI1UgHGo3af3DN10pDkAAAAAAEAh+JoDAAAAAAAUgqKVWeiW21dM2puSPH/+ PC2MV7SiTg3D8gYf6KsaXQcHB2khqBrQUFTdU1ONlbJtXqW1iVT1Mz0//FsNfnXAEe3f +/fvp4WgkYf2o+5D3lSFpAoL3QTeJwGVwGgd7ty5kxZUBjWTMqUOvLOMq5V0LaU6IBqs QHTu29wDBACwccq4jF+KNAcAAAAAACgEX3MAAAAAAIBCULQynSCI3q1AIycdPThF3NXw ZVjcZD7o5tCTemeImmvI0dFR5qt5B41WFMymOilnCwSP8R2hmggtBFTKtJKKWVS04jz6 WEAYkiGKCejcx0kQAIalS2uqArcKaQ4AAAAAAFAIvuYAAAAAAACFoGgF7ZydnY36+rrb vDo1KGCmX5Utp5vDUCl6T0cHJQZ607Rr1FOjJwKEPT+/2iphJBqiOQVl+9XEpYoh74QF BLbkTDcH1KMBW0KX1jrqufjcBqQ5AAAAAABAIfiaAwAAAAAAFIKilbUiMNlMcTK1dHn6 9On6VmdetHHU/ELyG2fs5KWjVT10//79n3/Ss4PGluQGtdECp/0y6oeHh32ejnw5BWU7 1XhWY6Pffvut9pDz8/NB1wtFodPKZGj4BQAFI80BAAAAAAAKwdccAAAAAACgEBStrJPC 6jm1A1sS8nfqbnDx4sUOTy87jPrmzZvaTxSVz5GTjlbDCC0MYkuGsUquBkeDlenldFqR 09PT8dYE5dFlwJbMjQAAjIo0BwAAAAAAKARfcwAAAAAAgEJQtDIdr0xRqvnhw4dp4dat W01P39oYq7ZbtxA4AeBATrXUSDa3CEudTV68eDHZm/qeosHKZDRWszqtVOiXgVY0YBg5 ADAs1Zxu3DUn+iDNAQAAAAAACsHXHAAAAAAAoBAUrUxHNRfqWLG7u1tb2NvbSwufPn2q P71Kre9Wgauye4jIzZs308Iff/yx3jUpD+noDtbS4uT61atp4dGjR9O/+5brlnENKsLO zs56rA4Kt8ZaQgAokmpON7diGh2Q5gAAAAAAAIXgaw4AAAAAAFAIilamo6DUkydP0oJq VYQws7t+/fq6V2FSuh30BNaYjr60+bVXrapXWn3MJZUp1eZ68OBB/utgGNW+G+rY3Nwx j/FoNvYLAwAA0BZpDgAAAAAAUAi+5gAAAAAAAIWgaGU6x8fHaSGIpCrMfP/+/bTw9OnT Pm+q9PvDhw/7vM5kiHPrdtATmEP/jiJvdq3jV/QxfVNrQtCvqEyZl2rftTo2gzZGb968 6btKKI4GDJ1WAADojzQHAAAAAAAoBF9zAAAAAACAQlC0Mp2Dg4OVj/HUuopWulVz6HU2 pWgFk1pf/w6N5yKLVtRNyQWbmlqVeTo/P+/wLC890FDftu5RyEGnFQAYiRqlFXnNiSak OQAAAAAAQCH4mgMAAAAAABSCopV5CVLrnrNS65Zbt27lv0XP3isdamda3Tf+7Oys7esD wHguXryYFpR6zXHFOq3QRgoBOq0AwEjUKK3simnUkOYAAAAAAACF4GsOAAAAAABQCIpW NoYHnr11S04Wa/reK79aeNtphf/888+RVwezoD1Okh8zp04rSr3mOLPSA5UZAoGcMyYG wdkHAApGmgMAAAAAABSCrzkAAAAAAEAhKFqZO+Wcd3d3mx7z/PnztDDP+wbrvvFBQPTq 1atp4fr161OsE2ZjnoMWkG6dVpyXGQKiEyVT4mSonQSAgpHmAAAAAAAAheBrDgAAAAAA UAiKVuYuJ+d8eHg47Js+evQoLQzSjUV9CgIfPnzo/0ZLbVwYtWcwflPkdAUC5qBbpxWg FTVYodMKAAxLl9Zcc24V0hwAAAAAAKAQfM0BAAAAAAAKQdEKlnjw4EFa8KKVN2/e1H6y sirkzz//TAtBZcrbt2/brWK2jcunEYwHZkWdVoAJqOUKAGAQurSmYnqrkOYAAAAAAACF 4GsOAAAAAABQCIpWttfx8XGHZ12/fj3zkcqD6SlemaISmP39/Q4rg82l4bFxrXCwbTRE W3VBun71alroNtNia9FpBQCA/khzAAAAAACAQvA1BwAAAAAAKARFK9vr4OBgkNfJv1Wx lyfkl8CgVNzsGjOnIdquC1L1rKFmWpRNDVaYEgEA6I80BwAAAAAAKARfcwAAAAAAgEJQ tLItxrvb/2kVta3xEpWDqkRFDVawtTQ8SGhj5s7Pz9e9CiifGqzQaWUy9PkCtoQapXHN uVVIcwAAAAAAgELwNQcAAAAAACgERSvbotXd/sdKclZRMRqsgNwgNsXFixfTglKvwHj+ bqgDxeB0GqJ6BSibGqVRMb1VSHMAAAAAAIBC8DUHAAAAAAAoBEUrWEJRLvVnuXXrVv7T UyOVK/O4XfzGhVG3JBhPbhCbQp1WlHoFBqdald3d3fWuCQAABSDNAQAAAAAACsHXHAAA AAAAoBAUrSDSqj+LzKqRysbVRBCMB2aFTiuYwK9VmSedVgAA6I80BwAAAAAAKARfcwAA AAAAgEJQtIIsqXnKUrot/IcPH6ZaHWw8FRNtXCscbBs6rWACdFoBgJGo5nTjKtnRB2kO AAAAAABQCL7mAAAAAAAAhaBoBVlymqfs7+9PsCYoDAFCzJw6rQDjodMKAIxENacqlObi cxuQ5gAAAAAAAIUoIc3x9u3btKCv6A4UPeC7uhlotYP8wQqS9Pzm9eTkJC28fv06Ldy+ fTst+C3ftBrv379PCw8ePOjz7qjZli/UX7z4sVD9U+3OwUH9MY8f/1i4du3HQkZ4CpPR WNU9zIDxKNYRqcbkq+pUpYk0J3o5rFevXtV+cuCz3Cxt7Q2wdTl0enqaFpTG5Q64WNAB 8ujRj4XDwx8Le3trWB+gJdIcAAAAAACgEHzNAQAAAAAAClFC0crR0VFaUAzvzZs3aWH6 9Cbc4yqTr0oQ30FKTv7P//xPWvj06VPTg7v566+/0sLTp0/Twl4VuvOUpq/ztaqggEGF Fu7erf/k27cfC4qDPnzY+BjMgMoBdA8zYHC682hOHd/bDx/Swq1bt9KCTmfv3r3LfJGh aB3k24bMYNpK21a94pdDz58/TwuHqkoAqnlmpxonO9XfWTvVlTkwZ6Q5AAAAAABAIfia AwAAAAAAFGLSohUVAqR0pd+L+0XVleBQGcgqUhg04Dg/P6+9jiog9IKqSsiqOKje4qi6 t/DNmzebnq71eWs3PNev0i2sg/tXaz11J/92fT10n/Mq9brzxx8/FvxmyFUxyGJBK1Zt tyXNIPzpelO9xb+fpbuva8vIs2fPaj+5evVq9fKfar/SZtT4CTqkOA0GhTPlUbV/9Tq6 2bjyw74a/nFWDio91z+47+hJuzmopEI9PuzQG8m2pIVtIA1G/VkaDsB/sVYIi2YuGs96 He6gvg2UPa7i6ztPnrR4ug7b4+MfC5q4ck5emue/V1i0fnqJ1GAlq9OKuXjxYlpIpzxN sK0aZ+isrRNxcLb1Biv+K51SdSLWgl/mefsPv0rsdhmARFvYL4d0caLhp42vbR6U7uZc vUtwyaQHqyPevXv3dlpe7OmzBJfuUa+i6nL0RTW5LSnk8RmsetZONeaXTJL+OjqI9AH1 9KY3kqC8SNO7qk70R4Fe0C8YtMLaZeNdwExOl9aFd/cbikZmdSQurhA2agOS5gAAAAAA AIXgaw4AAAAAAFCIC+O99OJG29U9ty9c+Nfbff78OS0oYKYcnRJiuvmzcnSqblADDv1E ebzAcRUeC8KQD6vGB8q5KUenZ+l19KZajaY31XOV7rtblQwo2KkCnLOzs7SgGN4iZ6Vc mUdb1QhAAWDl3xRdU9bd+zuI3yb9999/LCjwprzcf//7Y+HOnR8L36NNOftFN4f/+PFj WtCOzqllCJqwKDSr0eXJSdG2Va3KjRs3Vj5LavtX1ANIA1uP0csqivmh2kGL8OfgNzxX CE2x0vv3fywouK6Ro9toj9NZpkPtz0a6YHOsd1rxA9kPQN93Ki25cuXHgjapv4UenFMS lXZ9kbujH50j2hUVzk2a3IKZrTrtLglF++lD46SawxfjWT8RVckpgK0odTXvLWxIt46h 6Jy1CM9nZPt1qmqiV1tyLVG5YNOUzj46H+mCTecsf5ZTZajqHbTCeosnVRbaq3W+VWdk lQ/oqkm/6pOg9mpoP4+XRD1xgoIj+dZw6b7z02DQRY5eUHv8wfdik/97ulXB6PpZY/K3 336rvUXt8vu/1XWm6lBEQ0JjVW+0ZK2qqduPoJxC2sWoqy7RF9fGiwdVE5cfILoOr0rM Fk+vXXHpSttf3/mxoGkhmOe1nq3eS5PSpnVa0fDQUUD1yoLGiUaOdrSGusaJirDmOVvq uPs+wklzAAAAAACAQvA1BwAAAAAAKMSknVZUmpGqGF6+fJn+0xNiChepaEWPuVcF4QJK xIlCSiph8PIBr1VRTYRXH3jRQWD/33dOVsROiSkVLChi5yu8iEnr03l4zBPFGYU8Cx5A UpBJaaUq+7e4H74yTrp39/cMqm8i7cTnVUj1jvZmc0pQe+H9+/dpQXtK9+IOwr0+YLRi nq4U77SiQaVfaT+mfbQIu1afRaNFA0Av4hVSOSVXHWnbat+J8p+6hbL2+Mg1CxoM5AYj 2neqVRFVBGiXaUGBZO1Er1XRYFClmwoK0pxD0UpFY/WyttUmUlVIGic6K+nnqrvUSPCO XTqz6Cc6+3hdlU8mXpmicjlVymTE6cuW02klyNWnM6ZOMTrfee2tTmHilSC6GPvPf/6T FlRhqsoFrzjQr/RZfJb3yzynWhVvUrZZd/ufCV2BeFnu/aqC9aGVM6u4WP13gmLev6oj Wq1wxC/GNEplUYlcTUep5kVrpaIVrYMGklem6GPq6b5WomPqY3VB/ruVop9WB8hut35k alrhp5LaCdfP+EG9TPUXyk7zobTgjwl6uOgS0dcHJfEJVgNSf+uN90fKmEhzAAAAAACA QvA1BwAAAAAAKMSkRSsfqoxZCqH5zZadR9q8NMApBp8T/vR3VxYuuJG4CiiCohWl79Jj POanjFzwRks2jt/9PuemygG9oIfZqsKiBQUamxu1fPoebdqrQtHaRKrLuFLl/S5Wt5v+ WrWYccEWzunGosHgr7OIoGfEX/V0L7KoVbi8sr2gDx7saOUtg5Y9HWmFFUJT9iy4S/8Q 97FHX81z45K7uIsKUjRbeg8mhVH9LTKmza2iQ/5LTp+a2apN5prAVb1ilXqLY98LSVTG GIxDnb6DAiif7pQGn+dd3Eej80hOHZ8/ptafRSdHXXh4xe4LqyG60Hzsq2BBglNz8Kta 8fLOsss8UeGnPPLSS7TnO2hRXmRDS3UoujjRWPILVI0T362qQ9HVuxeYN3UOWlT1Vs/V RbioMsXrbiT4c0MfXNeu3ntlyTWnBqTe1Evz5M8/fyyoP1rT3GiHW3QlpncMila0nrrg 12exo2xH5UV+UkCRdEGoc33wt573UJsx0hwAAAAAAKAQfM0BAAAAAAAKMWnRSi1z5a0l FNpUfM67n4iiY+fN9Q7eL8N5DlmRTgXqFPtUDE+3aw7qJlZWHygRpxydFpQS1G2lF3R3 dAXVFPxT/NhDaIGgWYwH/BSK89vp++2aG6hWRXL2VE6JSsDfIqemSbSzVq6qP2DRu0cj qrqVt/oNaUQFocq+1E5FDRSURvOEpKLjuq33oDwOina+ffuxoIlUt1v3dlRebaFjkFRq ts3utLJyR1eT0qK8RbO9P1fnGs3/mrh0z3Y/eWnQ6iymV1ZWVnORxrMmrqLpfNSt08oV xeC/W1lcuZQ6pOxW63BUZd2HmqjVbkN9XnSZp2Yfujj0Ut+gU0YHW3v2yRkMsm+XiNpB GmbedkclUYeqkrArXt/+ajuoN31c6wHRfCXmnVbUu1BVNqrW6XahtaSgTLV1uprS5KZf aQPqylxnZHWqGlvQGiYYDAVVsOpvPbr7LaGDVGNVRWd+MwT9Pa5fdWs8NAnSHAAAAAAA oBB8zQEAAAAAAAoxbdFKJWX4PY4YRIm8aEUP9QqIVpSBVHJSOTeVqDypQrOtIo61G6cv qbupXk1ZO+XotA537typv67fxlnRuMFvQq77Qv/++48F5fHEfrKXNlf16byqaMktuJtv xd8zVqoAsK+G9njtHvXdVkMPUERTodxF0VOVnFQ9lMKfGmMjFq1osytdqQy5Pp0yilM1 lSBAGFGA0Ful+JGoGbWK7EZ0OHgqlTKWfysk2a7Sj9TLQFWHHkD1pyjRqlGnUimddDRx qfykqkFYUCGnFqzVwqJ1y3gz4bzlFBT4tKkOF0ffi328R4n3VdGFh06F//nPf2o/0esc eou3ZnovnVJVLHCrGnh3bQbLqdYJerh0sLW1k/55dU2yV+XPVb6th3qXnJzt5nVG2onP q7I4DQYNmKOqZi0NxQPru6RrYw1Rb7DiP1E1VrcLrSWfN4jr51R8NF1z+rSsaj6v0+92 5a85RGVBOilofi6o3ZVqTrUTufhc0NlBh4wXpKgucqNazpHmAAAAAAAAheBrDgAAAAAA UIj1FK2kW20ryX/foq1KzSmHec96B5xWwc5W2TOPgyo+96a64/GNlOldFnjTXaD1LC+9 WUm3pFZA1POlSpMqJfjzSvxYUK5MKV/FSq2LzYIHYoOIrNJKihYr1abEqeL0tU1R5cHU NUatZ7TRzqouHh8/fkwL3cqCAhoe/61W40KVJNToUoy21e3HJZXDePpNI0qv7yNKSVHF 57z1z2B0EKkWSSNHfI+Pg9xgFm0cBVa1g7x4TbtMeddgHqDTSrYpjs0JaFSkceKtsqSa jXf82NTZR11UvKuX+rN4nFuDVievoAZz5ClobnT2yanL8Msez/8nwbWEGlLorXUpoooA FRHo9Z3OYl6Q4s0vAnrMtWvX0oIuFYJ6UnSgi5ML1TWA6lC0E79VNa2aAPUrPVijIhi0 15t7DvoLqiWKLpZSuYqXXGk851y666p7yZzWrF0pk44vnXb1p41mwvweiOrAoos0VY6L Xt8PrlYN8jTleqWM/3nFBUORdD2gPms+3kSXATNusCKkOQAAAAAAQCH4mgMAAAAAABTC IuvD+bZY+hY8DBiDWtXkdFGZFYUzW93ZfuNs7g7C1tqSYxNrwZQ4PRXFqDzBO3oAKIBO 3yqVomK6TKrz+v7lA2kOAAAAAABQCL7mAAAAAAAAhVhPpxUAW05xwXY3MwcmxxDFBFp1 WgEA5FOjNGpVtgppDgAAAAAAUAi+5gAAAAAAAIWgaAXAOhEgxMxpiCr1Cgzu119/TQuq XgEADOLy5ctpQVWoXHxuA9IcAAAAAACgEHzNAQAAAAAACkHRCgpHl4R5IjeIjaPUKzAe Va8AAIDOSHMAAAAAAIBC8DUHAAAAAAAoxIXxXvrbeC8NAAAAAADws2//9z0EaQ4AAAAA AFAIvuYAAAAAAACF+P8BUYzyvqgkNeEAAAAASUVORK5CYII= --============_-1092831418==_mr============--