(* Content-type: application/vnd.wolfram.mathematica *) (*** Wolfram Notebook File ***) (* http://www.wolfram.com/nb *) (* CreatedBy='Mathematica 11.3' *) (*CacheID: 234*) (* Internal cache information: NotebookFileLineBreakTest NotebookFileLineBreakTest NotebookDataPosition[ 158, 7] NotebookDataLength[ 1288365, 24332] NotebookOptionsPosition[ 1224090, 22961] NotebookOutlinePosition[ 1275145, 24025] CellTagsIndexPosition[ 1274456, 24003] WindowFrame->Normal*) (* Beginning of Notebook Content *) Notebook[{ Cell[CellGroupData[{ Cell["BirdSay", "Title", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.7560797572524743`*^9, 3.7560797587393975`*^9}}, CellTags->{"Title", "TabNext"}, CellID->362346026], Cell["Have a bird say an expression", "Text", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.75607976154831*^9, 3.7560797670521555`*^9}}, CellTags->{"Description", "TabNext"}, CellID->450900334], Cell[CellGroupData[{ Cell[TextData[{ "Definition", Cell[BoxData[ TemplateBox[{"Definition",Cell[ BoxData[ FrameBox[ Cell[ "Define your function using the name above. All definitions, including \ dependencies, will be included in the resource function when it is generated. \ Additional cells can be added and definitions can be given for multiple input \ cases.\n\nThis section should be evaluated before evaluating creating the \ Examples section below.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoDefinition"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Section", Deletable->False, DefaultNewCellStyle->"Input", CellTags->"Definition", CellID->608264297], Cell[BoxData[{ RowBox[{ RowBox[{ RowBox[{"Unprotect", "[", "BirdSay", "]"}], ";"}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"$bird", ":=", RowBox[{"$bird", "=", RowBox[{"BinaryDeserialize", "[", RowBox[{"ByteArray", "[", RowBox[{ "CompressedData", "[", "\"\<\n1:eJyNV2N3HN7Xjc3Gtt2kMSaNGieNPbFtszEaNratie1MNLF+sdHYfPr/Bs+7\ \ne9dZa9+79sHeh8rE8acJNBQUlDcrFBS/hKBX9l8DRH1cy83cxqa4Td8/zNsw\n\ hYxAaFRmJDlsVEr79XP2qWjG2fR0xvJZwhmeoiiuBxRWKxP28RyjC5c/flsb\n\ w5dJ8l0Tnu1D+PO4eGnPm57hjWhSKmm/3Mm3KHrddSw2cx4zAgM/aeiYIwVO\n\ /XSuEZeeRo9HGZWcCa8BWEMratt9wbCIGKT8Tv+vA1BBv93F/PPjfeIPRx6v\n\ fWZTE/ccSVd3d7/jgYu3u7u7hMTg3/XWOBFbDBrsqampP+wGMLSycnKNLS0X\n\ qfKY8JR6Hh6827Qy3BhQeQEvTL+VvhdczR4vEMzNzfHHizTw+z05KShMQr5G\n\ w1NCLVfr3G54bhG9droQYgT92mw0lzfCTwmGgttbrNKKe18UIETpy4f5akbZ\n\ gYmFacXTBwAG3bvzAFSv9Chfgn4hnD9HkOP7QZE6EfayRxjDOL3QfpEVk8eM\n\ vZqb+wlIlcHn6LOD5UFFQTk9Yt1u/cNhRD7nONKfDrVbSFEBY4YBXMDKxYAQ\n\ OlVT5KDyT+o8FZEB7O/Nq2AboXGQIH2AMoQXAv4of2QuQJdamRLR8QIpGnp9\n\ YzdCRV8WIB49679jGQsYB8wZUn40qiC5U/dvwVjc2cWnqNuxgL8u51+h78As\n\ Ra9W/rKq8QZF8N03NmFtFn0PE9PTFwLdzc08wCwiXw/SF9jfaCIEGF5mNDY7\n\ PjlmP3/ORWbSIvrfdZgBIol8DbuDTJcZBxh38WA5d3JzaSw943j8Xk7Kuk/F\n\ TWfOqKysrI7Hawvitly8FO4UdmPT1nsZOrNzctpNorBDyIQ8Yn8acvG7n6or\n\ F02sJO8CDLp9Ut2XR4eGCH1/hiK0EWifr3V61jUw3BfD/rf9wgJjhXDObqps\n\ A4GKL2ht5TuLQQtcCpJgCBqe6FiVaZRfEWM36pl8YS9SfctEcNjqmWLWR0ZB\n\ IV50Lsj1hqsVHGBkZGMzZ5MUkyoogtnuAaZCOYfYPkFrBpt3Txy4/INFgnAD\n\ +IgVR1XRNfugraSTK9bNUrdiawFgK0QsHVYWVM6plWTir/UD+gB+V+wFY9gJ\n\ LjiCQHW9S5H+Due2GsAgQhqY8Ll9oL+wrIOvwdfSDGZFnRV2884jAQZ97CUe\n\ HR19JDflJLQEne5LVIOlGRZUxHIz3S0SHMsGr8/g5fveXIn8i1EyqhM6rLYQ\n\ gfT34U4qqLse605mGnStWn3j1daR3ETofubvJH/bw7ExNCcZ2NimVri/Umof\n\ pjENX0hTttitFgaC/hWr6TkREVa1TeB8T0IsxhK96Dw7GtA6EGhG7Ctdiqbp\n\ iZHMkWb6zKo/MuoETDUh9hVEQGS57NMQJ8T44Un4v1uMbnayFb+wdQsii6jd\n\ WksJdn80NcyB1T9UUlYb6DznehmvL2ave3uni1WkIIT7I9I6BKR43QRKED8a\n\ FikoVoQmGX6ObCQ3vr8fBds1RxoNURNpdmWei1/bd7StLW2nDyUj088tU4PW\n\ 8WtnmjSlNhm5Qmd1a3u7zueEKLKzME0IyHSt+UxBe91AEaTuGxakYWlCLFT6\n\ CmNrhNm6vJjvVehgprkffNZmrnJndw/0ERoW7L/R4X+EQIB4sOmn3ZOVsHB8\n\ Kf/4fQHqUJauPSQv2k6o9x5GwrAkW1V2lmvfN+tHW3r1dZyXluH42kiwawsK\n\ azdZxFm/RlVfkZWhR6CLdNqn/3wusQ7sTEz41wTvMRRERNbnROhE2ghvySpC\n\ PIWQpiNLbe30BoZvcFCa+PJmGR5fbeFgrNDRBu/+AG/2x0dyF7CC8EB7mS3o\n\ Ytrh7PF7nR5/vz4UkxP0LZpHmSiZoXP7EHfQ18NtyzegkCnO3JI9Aw/sFSVs\n\ 7/zov/3hIbW449lWBJjd+zmQLRu7PPWjCEFt+TXHVFdp1TWipCpKYCSw3+Hq\n\ FIlkI3kNM+dyBXN8I+7/olO0AfmbqqUf07ITERVVvd7q+OhnxgvMHHdUIw7m\n\ pEtcJKhTaLPyGBpIkcT/LU9aJ42hIG0WLBSCRyx1LBJOWhcLM4+lA0BuDOnO\n\ 6dotLBoJQY6s/jdZm0K0/sXiC/B0/s1QvRa75/gRLKXGT+5GsIkQNi7u0DU4\n\ klA3cdgOaYBzcmlpCXKIzh9gbW2tPBENrRKvP9yJPQuBcIZRn/0rbZhgwKdV\n\ UGu4VxBuOu9ZPAQRElu6gWSuHnRQLNY4BlNsorF6Asv/AegS7nGAMbG53Oyu\n\ RpdhpaWjcxZXLSqyFOmj4VG6zFMXEUjLyUFPOeyTIuIX5dwMij1dlFv+h/Wf\n\ xwA2TNoYsZ0L+o+C4ORKLaiWIBqoRg1PRC/Erhmb1WWxiiC6GeQq7JBcattt\n\ FFS/Rgo1xIJHKzgEBFHqHQTYfNLg4l1mM2lcckUzkRR1wJqbjcYVzBiFJtud\n\ CjRphu/FONIQTWQ1i1YtWrb6CxT1wdXOoMQAVz6gnzToZNjcXpoVga6xT/Ah\n\ E+DNWOEDg0XY5rVtBdta1Kd+4CIA8aH/hBPB6euTWpKQhV96d94FtjpuIWTD\n\ fVXcCkf82CvBcJJeOB4ASKYVyA73312pJMLrP/2TooBz6nh1Uh8pMeqzguKb\n\ h4dD8m8DBVp3dI0I35nZIVMFHFDJ6aBu+EhW4A/YiQwavIhR6KpPNomaHuaf\n\ WIKRZj419IqY9qFDv5WhIqsjSj3vZeG9xgQ+SBH+cRBDk4qcDwLdv9yTLCOG\n\ 295ZLZ6EO8HAYusAuF2KiaWAhDf9ERRS0lIJ6OiYqJiYZ9/bNo/9OPzsnto4\n\ ZfeHPbeKrL6teZePzia9x7ACmIHjrqAeGnzgSbDbXODRydTMdKYIg734y9Nx\n\ FCyPiyA2Nhf5m7Hu2oD3OFOx3O1EXe/XUbgyQtbRF2wd0gppfjee9OXPp1OW\n\ 1A7JkiXGFGYtvoRpqSEn8mkaJ9xRVTQJFTRxle7ZZyM0qQzlUxyAnUVi1h+j\n\ n7oPwwRGD8J7ErNVY7s/vkVf7chQdD/N5YYMDEwfSGDj1sP9Rk5CEPdCMpHQ\n\ 7oghe2PTpzn3L+sIp/OSVHBHT3BHy7CioGy4R2708CRYj+I0FCJRBUiS99PU\n\ x3ve3Nw8nK/e/qPAI9eNEs40irVARVtXF4xnFo+i/1GXAIpTROa2pLyjZyL9\n\ HRVB7fZoQplPiuT8O9W2y/RHh1Y2vZu4u9v0g/ZJliwLCDXPm8+2yqP/kPuW\n\ l1RW1xco/SyvlpJF8wcXcVLOJSqy+f6e27N5L6rDagT2Kya522mzta793sHE\n\ 56JA8IcGrUylavTjpu+WGCXS0fUzDLS6ZXPYgMpkWj0Sbic9fxiTxGFXdvnH\n\ 3m4OH65MwM+851/C89X8rkbODz2nbyKLzxY3pISPqUeXiUcX5dNvhYLvsN67\n\ MQPLMzNbbaY/VY0BA2Z6gcoN3XjstFgpUGtfhp/8RBMYru5R+Y20Pp+PtC42\n\ f4kaiJ3/47ejj/XgVwzB+xssZ3b+AQ4tXrzxoXC/Nren93EXDtPZp+czyxYe\n\ 2YuOx3nPTbOSmkxFFqOGKYkIY6qmY9Bjlu6ibo60fAUJo7lB09u54kmUo3nE\n\ h+9qrpZFisXT0CuSfQ2naPBOs7Ak8vft/fPT08PnU9s6klcTJ0IT/a4nB5V6\n\ sRAJtkhTYdHoKGzqyYFu9a+fZqcvM6iG7xnCsO3F1sULa7waoUqOzVyh54R3\n\ gfeB8M+lDsU8BP0xWY17gdPez3HtVTchlgiR2XD1UULRswoIpK4uzqu3c+Q2\n\ QA+CiERkxgorY9DrsMgJkY7CD+hBFfJwFCxJk4P2r8zv+jdqgTO+3TruHehj\n\ jH1E5gSu5RdFio53HyyNBakLp2MIlOCLP9aOFUofM43dZYfqSVSu/s8t/L+T\n\ 4KaLKH7s7Bw8D1wYGCTvc1ZC2s1eDQMWJ9ZbuYuDqNpgTdJOyd5dTE4W3/jy\n\ y6k4VFDYKDWqeoKI94FIpWrLg8vFLehOaIyKjKOnn0mfp4crIdcP4s2tQdvC\n\ x2Idvj5dbZaYtpWk0qKCBGdxsIgb/wkb0wZv0zDSA+qB8p6KP8CIOt88x1x/\n\ Y0YLkukoM2WuqSsK5i+MCVZGqBA/WaktgyqgOptTGhvi4CTW6evmU3n1kyl8\n\ RRpMamWayTAMfmQHncNkXoOWH5voJ41pQ3Xo81G3BHyGZseRiyi0YWky4MSm\n\ BdroW65srvt9MxHIIP5gn/JewlvZVa4xKjI5p8IXzcXnvNRRUMaMuZcyaGT4\n\ 96kKd6EHBoYjqbDT44VB5ZYuqqmRKsaG0/HVukf8Q5/haPB77F5a+SrMTHr4\n\ pP3y+Dyu2yP7z/3OQf5MxpKH+NNzmRhPy9ehrCKYlAeV/ju7v39Fn65gTY3Y\n\ MDARXRMuxa7Ci5pwYrVNGAdgYyIZvCS7cloebIf1+MZx+PBGexkSjNTIejEC\n\ iIH6iDKaORCSUcffMo5M8f/RJgQU8btxmrtX+zJO4lwDV4wov5ALOb99vL+2\n\ BjztjFIEngo4bH1cT+cIjfTUKgsSen7wvRo63zqVxXmkQ0lCN2BNKtqJrdJ5\n\ pcloJ+lpJ9kOKTyW61xg55iWdpqVrhdheHbv0GccbIreiXFPiPilrfO/vEda\n\ /WnAsPCACxkIgou/RtpcqYe0MV0nm+7Rj440Seu/LRwjc8mnHUKFqGbLWqC5\n\ rdG+Pvy9vbkJGUHT/ueyUCNrHiLnImFEWPpeoBWn1tcvxT6fMYdVbVdmvfsf\n\ L7dmztW2dzhj4ean7qipJ5lP2WhNT9xqySafhL8EMclgkhNeBWq3DhYSkj1c\n\ euATCpWUhXPKOjVvqd0e/5BSuVq57PnM3S3/1nXctYaI2XNyeBje/BpaXtIn\n\ vbvtKB7Zj/I10alewSOeV9y4p984wELTRF4vhqv/wpSuR/TDAa5fQigYze6O\n\ ymmSLSzYWPSjYDPN4xBpuqmx6Rr1ASn+6hb9bh/VG+1POoUVw84rYNRTHCZ0\n\ JOCRTIaNZvti45BvS3h/+zgSIiBeT2uR7hU8s2DQJNclGX9nMyBFkBXFoETU\n\ apFsssHNXAc4asAJGfvWTmLzTYoupr+uQxIdXB0YaDtd3QmgrG9qdXdrdHdq\n\ bPFs/hL1vK34CUxwn0li4cWPjyMOxfqx8qTiYu7gXqPbQD06MFK9B5n0fqHR\n\ EkI+yXiNQ37CzKk8LP9mBzx/eAx8Dc7pponGAaxCtVNKR8F5yvqvHSqnXebs\n\ 8E8bWJkqRlJuTT7vmY5q2rEadutgU19HZX+h18tq8sgqbGOd2ByUtmLCQory\n\ mKgWkytQQKbUdvZ0bB0ervhFp+NdGas/HJIP4dqe4uonr8rTTBHTwMUmoW0h\n\ kFZKHNM6qFmvVK/WPz03Z/hKgPU9VhPCn1K6seiu7JGRlaW3vqKYSer5/oIe\n\ XbTEGVKwdI3DgPwdKY4U5oimq0LJWCZp6a2Yf7Oa/721648Y60rOLgVqWtR2\n\ 0eZHrbV8Ev5B2f44t2sKkc4wE9GzKz7etEGp7u8qcHQ6LjMvwQNbk+Bf3uON\n\ 4AT4iOe6AGnVdo2GQwGpRU2pu33Oq9KYCImXxnad51t8vNJ9Zm6XlIzVuYXJ\n\ t/ZV+PFnM2mqjBOCY/G8XaqFgWM7Ux+fF4bAl9sjrY/lFa2XcRi1VUOtZSxi\n\ eiok6OBCuBDlZmQ/toJdxGHknMpcalDKC7XGLC1qjsw6W7nKpKdTi+tD4wwN\n\ d9BTJi/DyPSii12z0fNhIfr6N6ZVblIDspdizU7ms8Il7XHCvvJKYh3zOD//\n\ Gj8/fSQvNUb8FaF1n3hndtYJBJ96u8GbsBRZjNql/i+Xjejwi+uLO6r1ZFz1\n\ kNdizQh7TFH6PxNx/hl5/Jxdgr4XXbTUSVyJT4zExnsgy8zT190iwTjNskrb\n\ 0HHxvzmNt8/QyL9165sJS7WClia1c5tfdKwV9OG8tmbnW8wkjBc1v3JbtnSW\n\ mTKAfJyqN3Bh+5DbLoKNc89awEuL4CWADROhzewwMBISq107vlZvoNPAJeYw\n\ AncV3131y8b+ooPY3EoSSs/mXtp4hC9FrgRXK4A7FqgQ3+FjbybJ0/bhR04P\n\ gAC4j/46S23hkzkwtUNxT5P9Yn+UI96U0yUxP9rC9uhzwm5p9uoHT4HHkbEt\n\ NCWBYZeVU9FxQhPQW36wG2GHcNLbP2SCNQhq1qbqPWy31lZtNnfDwPZgECja\n\ /dvwIshsqBgq3C82T1u95enEgGWCF3eYQZGnFfs1wrtmhXaruYrHB6zthJKY\n\ QXgiGEDQKVj9+PBbytCwp4HjITlEiaXlZGAYUu+MZCDVJ8FJ0TD/MlZdZ4a4\n\ zhNXU2xYg7oKGCfW0+TpFqlz6Rkd4l9uoM7n/WV1fh41kULEFINTOh2nJKc8\n\ pp+brZGercPJYb2zsJIxa/rdz9hciCxkTs8/M0N4YXB9kWFIxNvZ5D5+zh0U\n\ Dfp24w6au/8GLo7VzsMi0OJA7CMqAHDS0Il2MuKtPFdMWChmCRl7vCzcde1L\n\ wVfIopqUzWTgkpIDEJd9vp3kHydLSipmCPqPxhPEerfnCb89hGKOPiFyGVNQ\n\ /vJ7UsIrIDLCI7f6BRpCx2W1Paks8Ml3sKEBTYGbetWzq4zeYoW2EFjJ+yVG\n\ lJHVqg0aHUh01FsmB6bRcKhO2m+ZW9PUHRbN2JRpnprZwk5ZWMsVnr8LlwH7\n\ X+xPQTOyy4tQ9ozwKNhd5ZUatd4YXSrFR1PDz/xOGt7fSXdo9ugRJ7SOqquo\n\ zFn+6ArpUPInpYn4z09He+twHw95Xy5QPw1IRGC0YljEEEWMjvpeGtyQ4ATB\n\ XEM/8lC2hHk3BM6l/resFxREzdFHLKzNs6jxWaG23FpO0pcP3uzsKl/SAU4M\n\ YVIzRDAts9VuKuJrsOLppQe34h/S1gUWuL1jaHgYMytDlQ+btpi7wZEFXYfC\n\ 2hzIqvFe/KypYQqPDaFG5ZQzRB7Sqql+kfraZMVOny8AK3H9YyUMeLCWjd6p\n\ Dga1pz3gb+c0n1vrBaglNtIWlOUsEt3uYocMXpKW8LPYavetaKGvlfblU4YY\n\ OqNJTHmFZAdZ57GuvwdVnJ0Z3lYo12sC/VMN394LyT7CaCiwTRjxsVlUq8F6\n\ vTXNKk0L//1HSuqwM7d//40ZOMMBVqYKmhS/8rDhkkP5GHo6fPr6/HaaUwm2\n\ /636YvqX1/qeXUpzR1hfsil3+iY2BkOjVrulQLpEu2ESPE1KykAndJ1BoFlq\n\ Tgd5UOczXjwhRAnb9eS3QUclNMwRcI1vqCPElIu9ahwd+vQYv31cLNPLAO9s\n\ nq4IZUhXkDjikglkdRk73oCRfMVcbZu4+g2p9t783jaQYX72L058+7FLwnp9\n\ e+UevFYpsrFcUIwENG+ntaTXtAPXhZR2dh1p90roNFIFqgbcvMVK6ulKr67o\n\ vMJ7B5m+IPhgwaSDnB+cUOKuPG/rz35GbCTLaGpqKjsGhK8zighbWVtDi7U6\n\ VBWoBXNOsXx/QhWhN9S/OvefspZzVlo20L436N/8kWrwZC214ZfnYAA5GeLa\n\ fM95gHNmAMF9z6UV9Dqg17nHMFdOXORK0fgWPdU5sWSX1uG14iEY62MpLoSz\n\ VK3gVjbm4uLxcTMRqEIGjY8RDluE+3EVITadkzU5BPdEyLVB1+UQ4M7tTXzh\n\ RnkyywE6NrKmCCKIfsnaP9FxSBwLmlViSwR85Woz8/94+RsdUA5yyMIlBJor\n\ 48Ui3wS5izC6fUPUXhxUmZibczmofJChcc4gk9hr6n2baT6Zx16jg6tkWZl7\n\ 385OFQMrqTD/hXrc5qy2DX71PA3UzNGnaPDqcLXyxc7vNGtZ5+e0mBWz7JTd\n\ dvpD2y7/5T+a7GGM2GzsTOSR0V9pGgTVW5utC5WpGnObJsPzUthcVH7Y/Ugi\n\ lg0GhXqShTILdq2RtIdPd0BmZMt+3f5IKHlltH6iMtzBKBqZBNXsGnOg/vNW\n\ 7+jIaIECHn5IG4pdJXXjh4YTlIMkXefqKaY5QcnCT4ilsKe8/67ve6XpAZNP\n\ djHie6awe7LwPegN2OFIyqaCldjutLtwdVOGUvVSlNacrGu89+4NU/6JhGu0\n\ j/MIeovLAuMspzDUziNe8qMaXKGFH+6XPh0cRiL5yfaZihqNeUf+Ix+1dquN\n\ S4CXXJfJrQ1a/8Hr9bcYh+9Jj/R6Ifl/9OKEohpzHLjb7qat9th30q8XsH75\n\ J+F3VqWYxfjx1NTcO2FMPCCb16KlDmIiLFvzLJQQWlHhYzC1SbYRIecZwQGy\n\ nHeiP/vhOdiTaaqkSVYjcalHmPTQE6nn6ikqGVeGbTCovfLz5ZBEmYMijN0N\n\ cWKfuaU2Vv8u9C6sdn8Df8XXuL5T5cyd2T6rsELKXbystUR+2bR57rXLgTme\n\ 7Tou4hA/HHUYQBVfgkeNLKkmhoLtl++nVnCp7blNdIW1kOZYiiHfXSK4WRrO\n\ hfXe1JxnoIPJ82q52pmGSK9b6EcoTgMnk0Bexm9DhPb5ttw7x83NWs26szuH\n\ /oteEG6hxKGjSBh5qVARWc9PeM7Ckk1Em0T9vvOXVYYixHPB0rzf1fmYo9AP\n\ GvsLl7RBaqdDWZeyDTR3jzRKseaJ2s8ZKE/B1NB2ZHstGfP3HyECfKDZ8an4\n\ JrdKl6dDxdWGmuvntPpdNK/+N2QchkVbEqbpJD6onrfRPzF/2I2jL/rmYHKG\n\ JOrdLseNCCggTDNzhjv5FYtamBGiotX2S9lGOKCxcEcMHq7wgouAeDNzjGJN\n\ MXITIZDZRUCtWxve7RcBu0jDNxzvymTd7mwMv5y5kX9rtD/8w7/Yl/MMthnV\n\ 7O2vUPHkYiNILBaDBNq0vpMmGisDRuplTOZk9n18GHJUGB5QNhtqy/ZxbDf4\n\ QpzmWC3saY0a8st/j/meVGhqKjXKK1H0u0gzsga0zu/eiruMxubtT+kNthYK\n\ eRTzzP4q3WbShim65Q82nkmt4IbEOKAL8DqswaVSznOmGK42aBq+llZcVk7D\n\ hpJmKoSXLfm7v/eEJXHaKtODra0ZDGvHteWPil6L8TlbW8Zv5AkE+Nch0Go8\n\ Q2t7wxU3Rq+l+MPNXKp8/p1vfyujBHjDiObZQPXaL2zdMrGDkO92FuEeKUVF\n\ zbrZe9jXxi+3Tu4LBmlJ4hWLhbVC3Jb+2WpIOLc8rV/MDxnqVucI6vYhItWp\n\ NT4t/PY6STU1eDhIca5oAon6/lruCG0l9vWOyHpRnvsFzZ5mDFuZ7QOywAnJ\n\ qz6REuZZQl8yBaxIwwv84I3Q3wO/ibbAGP2E3xFBaKMsFsKUZ6Labfa1ljwS\n\ bA2/nB4GmPCyUF7AVDA29ivsHL7MgTeT1xaH1Id1+F7DfmmvWfjpAMewnMSX\n\ fPwucx50gqbcW2wBGrL1IZSYmNhuDPrI+BuhTF1CZukr8HVMpvwpk8sx08Io\n\ pCUJPdCg0bPik8diOQ2SLWau5DYerg+oAYuGYC4KpZqZ1yqXMyQEjSuJhlSF\n\ HAIeVXSWCx2sNB6/cJ6UT0F+lijm7Z+TO4og8OKVJYsOu0FzRxTAF6FdP5Si\n\ l3MbX/vZGdtaz3P+rBIvs3vreeIkSptMsUcekjTz49Rphzv08eFuZbYtJmlh\n\ iQET6HTqUrl1rEY5vr8NdWl6ySyAKo1xY+aKcLJ0M0t7Dz4s4l+9qOx0lNWq\n\ 2lZWzoAhUCyDo16HMFyYod0WwnAtQnsHHXPS0WYccVQIprqwNtCuZxXIE5PH\n\ 5+TToyIw+jHgNPVL9X4UgIVbsm40aAaPDZxnawGv14yNhG9NcqW0ayPocs/5\n\ qoJc7r5TNfA+95vWtic9qgMX1xnF+Tg4v02A3Y2r9WCPE/BXSa3KnrBCisOT\n\ RmOtjU91j80NOBS5IldfTgmqTKv+j95SFbX8Rz6jPN++knI0wk1cgWam5/nl\n\ XGsruuRciGtF1geNyN3dvr5Wwze1WBo1p6zhcHIT/X3Hi3PHHdYh+JwFYt6K\n\ RdEf9npRDxvwM/TtMjcnflAJCXSTcWz+lUADdNnlEYIzVdSVq+IuE2ftYrE8\n\ TNNcQMKfCI63niunsi+Xtmu4/uxyi3eh5yu2USWmk+dEly4B4Le6uo/5FXlj\n\ m6tWlwmkeMymK6xt6nyy8DzdZiW7hQqSD4OrkdMxN05k0pbA0ZBB/1v5piXH\n\ ZfXGcpCiZrdBapmC50P93iy2ANXAFr4akqkmbHoTRmka8SWz0nKZPQbISXyN\n\ LzW/whr1EkLGJICGt2sw4pBVG1l/Q++0Ij1iAGwyjVbXKiXT/PWDVzV6xDfz\n\ to4+TYAKnxEMa/gLBPLaaSy+B9HZ2nYMK0GDKm1SiLxdpfDh/i58EbeoRbTQ\n\ hKLbLCWFnPRp+eYL365X1+xo1t+TzivyBYCb8wJeMnaToiQiQvqGXOVzExru\n\ GThX2CYMrDr9K9W1KkvIWxQkBH70RUv3xaESzSg7oxyYQk5hC2ktwPwa5qI5\n\ SyeHVGmOrAoK8fByOCohCTdH7Qm9bU6oKhWYIFBHuVTuM3C2xck2U/cO4TRs\n\ KEPs8w11WNX2+GpufzfB1SjThmAyIo5GVe8/u73irle6e7f1/YgUFsyM7RBZ\n\ J7aSpYDUT+nFJzshdbhQLMLDY7OcDi8LjZpSFz2tc7dBjK9GyXhYF/J/Pvtk\n\ rNXDyvxTX4lLHAh5QFYVwzT5HJzWLqQyNQXDB3c1eUdd2acC4mh6PRKO8kSZ\n\ LgYeuCq2XpL4ijWCHT1VBRnCanm6ZMYX0mKk2IxWtMzszX7JbmzFabGz4bat\n\ 4KNiZRydG2NfQMrRZKuPu8WJyA2a1BL6vn4Hhk133rOwBBuUmFjvXyHD7WiK\n\ cPzW4tEeJn6kc0uZYHgD8Vha3/hPCWn7ql2/mdeN+lC7fLnMjwa/Xmr+8bQZ\n\ 4TQM1xs3uamsbhu9646/c5W6QHMm3Ko/P+jhZnuHpPi5Br/tFlXnqI9Lyels\n\ cSusuR4fVx8YPFe4Mi3247MrvBkxH4RgSiS8ZoYLzeFEJGt6ZwhxtTq1xR19\n\ WGd2Vt5yDsrzojmFrmCNsfvMBmpmCyfp4tlcYLgqE2L2Y/c6zeymrqbqQdeZ\n\ aeiljq/OkxlUG9+hDpIhT1ia3n7WXWGpFX37rca50MEm1BJoMUzoKmNRJ+Oc\n\ OPm/uWH1a/FkrZftdQoui3Llk0ymxquwEbKgl9nEicOnv3D6Rb9ypAresRLm\n\ UAA7zQ0DBUcHqXBvUJ4Pt2ZLOs2R8fdQGISkGhvmQLGR9DZgSTMHAeH7urr7\n\ u3JjjO7pyKW5TG5Msk/k33SLbz/jdREAWaSisBevAxK/eprOnVzTZSR/w+fi\n\ 9DLyeyVUk/zrc7q2MVS2m44E/Mv0E1Lpvi5Mv8Kg7iJ3uYfYVJKYr7cWQr6C\n\ kE58bJmeg+h6+E9Wv9CQv+kICmx9horzy1KONgPB6MBfkMWgOZN4XQlMslU4\n\ /Sa9aNPO3ZSPw2nImczvH51cDGqVARq5CxUgQRendXbyPwb1hh07BDf7VfPg\n\ AbttJayViXCAyLuBazS+tBLKYdQxOTbSF7uDAkXfw5638/z4OjVemMFzuQ9b\n\ HVG14bDfFbapsgI26CK6Ox4L4b7geQq2NYFVqvRN/di16xpzKlktc0TGRsMy\n\ 0nissFwgtG5bT6rwI+i8RiNJgaAHfd4jiaEP9rtfhiYVQFl3N4SuR62HXRip\n\ eT2/uFAJGfR2EJtpxSK2HX5jVZGa9cf23J1TvLmcRK+AuLKXXiRpL4dSGmnl\n\ L3Q/TPV/hjl6H1Xn/CUWClvGybrNwyXlvWUVrxJLqN6i85KcRZEtYr3EI52U\n\ 87SauRFfJgIT84CneIiCx33LNbs0r6WMpM/4k/TvkHoIH2a3+f+egeLugcef\n\ tr5MOnpQ5EjW9t27Y0fjSkj/S3ztfBiPf5N9YTy9jDVe9fC3we1Ydr3Qxi/f\n\ ml/UVjGlpjXoAij72BzswRdMmbGZXHt4uYxOmVYS+MZrLlJi/UZ7VFISoCYJ\n\ 16++YFdVU9D2owIa4n0dvNtJL9TzPckYlkRLnGoH3FQdq/s281+oWz7JUg6G\n\ BNL3T9w+/s/SK4grl3etH2r2SZ90cv/63PXzuJRn6tFJRAGmhea2XgpPrlIN\n\ Rr3TL/S94ymTb6B1JoemdCqI81Rwo1f+rCH4v44+yy8YBtxhEdchkuQRljXd\n\ ErnBMYULA2ZbV8NtQOjJ0KQX5bQLZrRsY/HIEwY0AKzoquXAZVoPpLI4D1u4\n\ jca2l0Pw7W6IlEU9ckAkQTh7NHDn18Y/rw0L+ASfqcdNgZvqGFLg9bxQgL5e\n\ 2884rvpFSiX2bwV3KfHCYtlctdPv049jTei3efEgFNwCv/wBUq80ZUVtmFZZ\n\ 5kxGF06SVeCK+KuqhX3lpRk0a8UvEYrKJa2tNufBlRhgJoQAF3LNwOGn4wRc\n\ fGIl+Q+tBX9AleV79j72uxJ4LW+sqObU9cX8CGFTUlrMlLhFyb6DXqSFz/AE\n\ PfToR4j8SntzGXAq4QameoToiStVhaQnSWWXvnn0BN/FL/h4v2Iel6ERLdRh\n\ Aebndx3P3uaPwcmcW4MiOIiHdJALz+BTFLspJq1NrSwmbMKX0qQCYyNLFeQl\n\ d7O1mteOq7iQelrLSRsNyUO+4Qi9/BALYnFMhRfoxYry197dVp69w6L6GZwE\n\ JgNRp23F6KI0Y4g/2dm2hZ/7u+LqtedhbZw7Ms3xxwhcNHSmYv3VBhHHZ+EV\n\ pZ9XNIxD9QVRCqGL6tKJwKZG7qyFIx1sUsJMpQ2TrQkK4Qrt+SMSW2ZH07iy\n\ oifGoAqMBJdropPH3H/KYq+O0a6Y6LC8oB9j7HIGn6G7K0LjZ0f8Mjqm1DC8\n\ aDDEcKhYHXaZ6bdHdJ0XY8onC4o5O3KDTDJyCSSeC0eiE5uvihdZ2105yP0f\n\ FYvPLHI6gfKulS5vJr658AkeaGR2dqIfT5j/YyvcsBw+VMo95fSNozH5skSs\n\ F8I3Hc1gkls4JMFp2SNVavSf0O1SoMbTg8GJtSD17GL8l4/WTq6Hp5QzoCpZ\n\ SblvfrVvfh6Ln3aq+3Idrnvewbnida6CZbxKdkRELPrHmdGntDP1BBA4HsH+\n\ FVIxmLdYJqrb7O+97Sb0X3bELv+7viFL7qp2g1bt5eSgbOrW2GZPGT/qbSyY\n\ fsVafHWl1AwG5p5sz3m1RJl2KW0xmFCX5y8IE9fSKE+H3ORoGBfjGRHh7eKx\n\ l+8BxOd8VxFOqXcaXN1WJHivMy1fRUPw/AXjSnWe8B0NGq6JfnLQvts11II0\n\ o/uw9C5SqcZeYxa21JoYet7NTK2q8k8LeUIRPqJSpUNg7dLmb4pE+MmWoTAF\n\ M4UvRP32jZw8L6X4fwOhI8g0HXn9E1sDj8ysC/WKiZjNyOPBRba0rFz9cK9Q\n\ 1k4/7bPPzVzujyYeNjRySpkz1+SC6TwK0LFiaxsuSRXsWuLOpZOgb/Zniyns\n\ 0MuEX/8Znmu3GzIGJ2kb5xkYXh7ylkhOmC0UXyXeD0aRgIAPbhY6nfkc2qU2\n\ geT1g1nFlR1NykSJLvmVmz6dLJMbjElDZ669dg4Xo3cN52jmbkCqQbEcxwAB\n\ HZBHNVN6DWP5dGy0ZGoQ8bx13kvew85XIbgug0at9vzipMH6dn5qamqk54E+\n\ PhiMKBhRrsanr0Uu9KcrEU0xzgOp5ZCLjt1tmBzmjT0WwMkddsnhkbEn2kPN\n\ aj+De3DtfXY6x9vdetW+Zbn0weT7aPTn7+tXx0++Z8cNdtHNwgpHeAn7vidC\n\ g6flJ4PZgrc+HV4/7hAl8WllA8jHhkCi+Y+7In8fwod7hfYJ/5v/PPcTb2/5\n\ 8OAno5uvPL7oRqb3hKBNqYQlmPjBERT6caubxcQI/2rZWcq9nu6vIOcCVKfK\n\ zlXRs24kq9yUDXdeQjfwbp/+kinEP+f0Bl1t2x0xkk8Sfpdg+WZf0FD3ghMM\n\ XZuYm7U0Juycr+P8sr7bSowvqobdACztpAWcnw80NY9IweBGONAufRTTWf02\n\ RsKUgCdk37+e8vpOkpsBuwXOtWwfEnmYz/5zUUXx0+vNqqhIn+jn2eWvV4Y1\n\ CKbH/g4PCJ/wtVIMm/DchEuZMUix6Ru6/Wm4EJj7k93v7PY/rSBnkGeHHLkw\n\ w9LXPvSmFnHJw0hA2M2OaZAqDDSsjXypL+MArhx8Vmd3mso/2bvbBj8jsIAW\n\ 4gKnfM2zSyg2pkiOipfqdxrw43cI68flM3V5jhwY4z/oLlM951vJMrtfTo6z\n\ ST+H4LRkU2ryeturYI3ZAEA9Ipi1N7dxjBCFxjuRvK7r2rfzoocSCkLQv82b\n\ oAvfQUotJl7YbU2XFC263yajdjImNy2MpVxYpuK0fA6hsus6+PDN81fER3b3\n\ 6/dT7rKkqs1skImRyfiD12ppurltYePCTgW8eJOGafIDQ/mngV95Kk/k94Wy\n\ pcVCviNfhS+7AAYJubJJ5T20J+M+SA2NASq0nYs52bsbeT4XSB35fFw69RtM\n\ DyjVOvj9s+huqPXZ8dP/xPYTvBWo5d+BTqwbXh1fGoq5HL1VETvm8mX9a7SX\n\ sU/pv1QmB5NPbxehH1pHkRXGWsiPhroAHanh33kYf6X95IWRASCiJuxMkx2T\n\ z1l0BUuTkEV/ynqYBH4fJ7Tlo5/gFvXZfe19zwelTsiR4As+lZfuEKFPWtkH\n\ iigcwZ93lAk/Bhy2yD5AQ2SLPSOkpKQMymLkBaasAH3gn8nkcoRsz7oBVj2j\n\ kiuOvwP0Dby8nkBny0zxuuFDsIve8+SPGkeX1sQfBi7q+IIz5E3bBSo2cSR8\n\ F2sg23+KKrE7zBT9MXoR8Pn6lMd39XsQeaiqVTlx6jbHCpYvxxgN5LDVo+i8\n\ 8JU2hG0jVFA6v0SvjsYKKs87e4bEJ0y7DU6bXyCqJoy/X3gXvLkZsFipwee4\n\ WcjvQYR2RbRFBvvXFG2fO+HWGxZTcDfoqw7UUzL7EqC6urodxiJ0YOVMlFTi\n\ ElrrClGCjYHhSCzghuGfbvX3mSWuu477Q52Ikkf3B2zWAwTJnRa58MJ14+Pj\n\ A9/2GP59GkOZuc8AeM4kjDLnjWyrhSvfgLI5kFq5i+JsElVZLNzN01vPT2bE\n\ L1RwS3DoysMSPaEx/FyFS6wDz1HkZ75MoVOCWzeWV5SYllJ1q8UoxzM/W+9m\n\ bBKla1Cto8pFBvspy5FYq51jZJh90VwuScc2o+Vbtl/3m2AwgeDQdzRMfmCO\n\ 7ctEzEnvw7RKeUxJF8p17BvecAU8eHcA72cAPIeOasP35zhK1RQr6A8pDrcs\n\ LHKaqOhsXLx2YXphQXpBl7mnSOSkdKvxp6i9eXhXHjyWm28sc1JNEzHmdAfR\n\ fooCOBGtAZ+f0I+UeLz/B/6sMuo=\n\>\"", "]"}], "]"}], "]"}]}]}], ";"}], "\[IndentingNewLine]", "\[IndentingNewLine]"}], "\n", RowBox[{ RowBox[{ RowBox[{"BirdSay", "[", "expr_", "]"}], ":=", RowBox[{"Interpretation", "[", RowBox[{ RowBox[{"Panel", "[", RowBox[{"expr", ",", RowBox[{"Appearance", "\[Rule]", "$bird"}], ",", RowBox[{"BaseStyle", "\[Rule]", "\"\\""}]}], "]"}], ",", "expr"}], "]"}]}], ";"}]}], "Input", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.756079780519718*^9, 3.756079806500869*^9}}, CellTags->"TabNext", CellLabel->"In[28]:=", CellID->778396829] }, Open ]], Cell[CellGroupData[{ Cell["Documentation", "Section", Deletable->False, CellTags->"Documentation", CellID->855965831], Cell[CellGroupData[{ Cell[TextData[{ "Usage", Cell[BoxData[ TemplateBox[{"Usage",Cell[ BoxData[ FrameBox[ Cell[ "Document every accepted input usage case. Use Enter to create new \ cases as needed.\n\nEach usage should contain a brief explanation saying what \ the function does for the given input structure.\n\nSee existing \ documentation pages for examples.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoUsage"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Subsection", Deletable->False, DefaultNewCellStyle->"UsageInputs", CellTags->"Usage", CellID->694807545], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"BirdSay", "[", StyleBox["thing", "TI"], "]"}]], "UsageInputs", CellChangeTimes->{{3.7560798182284946`*^9, 3.7560798354409356`*^9}}, CellTags->"TabNext", CellID->157543866], Cell[TextData[{ "asks a cool bird to say ", Cell[BoxData[ StyleBox["thing", "TI"]], "InlineFormula", FontFamily->"Source Sans Pro"], "." }], "UsageDescription", CellChangeTimes->{{3.7560798242513003`*^9, 3.7560798373218536`*^9}, 3.758653217634961*^9}, CellTags->"TabNext", CellID->231889230] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[TextData[{ "Details & Options", Cell[BoxData[ TemplateBox[{"Details & Options",Cell[ BoxData[ FrameBox[ Cell[ "Give a detailed explanation of how the function is used. Add multiple \ cells including tables and hyperlinks as needed. Typical information \ includes: acceptable inputs, result formats, options specifications, and \ background information.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoDetailsOptions"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Subsection", Deletable->False, DefaultNewCellStyle->"Notes", CellTags->"Details & Options", CellID->29639701], Cell[TextData[{ "This is a silly example of using 9-patch images for the ", Cell[BoxData[ TagBox[ ButtonBox[ StyleBox["Appearance", "SymbolsRefLink", ShowStringCharacters->True, FontFamily->"Source Sans Pro"], BaseStyle->Dynamic[ FEPrivate`If[ CurrentValue["MouseOver"], { "Link", FontColor -> RGBColor[0.854902, 0.396078, 0.145098]}, { "Link"}]], ButtonData->"paclet:ref/Appearance"], MouseAppearanceTag["LinkHand"]]], "InlineFormula", FontFamily->"Source Sans Pro"], " option in ", Cell[BoxData[ TagBox[ ButtonBox[ StyleBox["Panel", "SymbolsRefLink", ShowStringCharacters->True, FontFamily->"Source Sans Pro"], BaseStyle->Dynamic[ FEPrivate`If[ CurrentValue["MouseOver"], { "Link", FontColor -> RGBColor[0.854902, 0.396078, 0.145098]}, { "Link"}]], ButtonData->"paclet:ref/Panel"], MouseAppearanceTag["LinkHand"]]], "InlineFormula", FontFamily->"Source Sans Pro"], ". The same can be done for many other formatting constructs such as ", Cell[BoxData[ TagBox[ ButtonBox[ StyleBox["Button", "SymbolsRefLink", ShowStringCharacters->True, FontFamily->"Source Sans Pro"], BaseStyle->Dynamic[ FEPrivate`If[ CurrentValue["MouseOver"], { "Link", FontColor -> RGBColor[0.854902, 0.396078, 0.145098]}, { "Link"}]], ButtonData->"paclet:ref/Button"], MouseAppearanceTag["LinkHand"]]], "InlineFormula", FontFamily->"Source Sans Pro"], ", ", Cell[BoxData[ TagBox[ ButtonBox[ StyleBox["Framed", "SymbolsRefLink", ShowStringCharacters->True, FontFamily->"Source Sans Pro"], BaseStyle->Dynamic[ FEPrivate`If[ CurrentValue["MouseOver"], { "Link", FontColor -> RGBColor[0.854902, 0.396078, 0.145098]}, { "Link"}]], ButtonData->"paclet:ref/Framed"], MouseAppearanceTag["LinkHand"]]], "InlineFormula", FontFamily->"Source Sans Pro"], ", ", Cell[BoxData[ TagBox[ ButtonBox[ StyleBox["Notebook", "SymbolsRefLink", ShowStringCharacters->True, FontFamily->"Source Sans Pro"], BaseStyle->Dynamic[ FEPrivate`If[ CurrentValue["MouseOver"], { "Link", FontColor -> RGBColor[0.854902, 0.396078, 0.145098]}, { "Link"}]], ButtonData->"paclet:ref/Notebook"], MouseAppearanceTag["LinkHand"]]], "InlineFormula", FontFamily->"Source Sans Pro"], ", etc." }], "Notes", CellChangeTimes->{{3.7560808973396964`*^9, 3.756081002677278*^9}}, CellID->14293932] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[TextData[{ "Examples", Cell[BoxData[ TemplateBox[{"Examples",Cell[ BoxData[ FrameBox[ Cell[ "Demonstrate how to use the function. Examples should start with the \ most basic use case. Each example should be described using text cells. Use \ \"Subsection\" and \"Subsubsection\" cells to group examples as needed.\n\n\ Example groups can optionally be delimited by inserting page breaks between \ them (affects example count on documentation page).\n\nSee existing \ documentation pages for examples.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoExamples"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Section", Deletable->False, CellTags->"Examples", CellID->847663398], Cell[CellGroupData[{ Cell["Basic Examples", "Subsection", CellID->462042388], Cell["Have a bird say your output:", "Text", CellChangeTimes->{3.756079858620186*^9}, CellID->13078159], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"BirdSay", "[", RowBox[{"Plot", "[", RowBox[{ RowBox[{"Sin", "[", "x", "]"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{"-", "5"}], ",", "5"}], "}"}]}], "]"}], "]"}]], "Input", CellChangeTimes->{3.756079863200036*^9}, CellLabel->"In[31]:=", CellID->443871870], Cell[BoxData[ InterpretationBox[ PanelBox[ GraphicsBox[{{{}, {}, TagBox[ {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[1.6], Opacity[1.], LineBox[CompressedData[" 1:eJwtmnk0VP//x23Zss2dFksJlex7FNX7SpIiytYi+5ZUIntFEpJSRFFKkU+h LBVC3reIQpKthOz7zLztZsb2u99zfv+M8zjHzH29n8/n63Vfc8/Iulw87s7F wcFxn3z539+rI+bTq6tUwoI5uy4ynwGGwzbMdS5RCckWzU2pxQxwVKxnoYRF JZz3Ruqkf2IAmd2+yxdnqIRv6qYYn3oG+BKXyN87TCVk5Fb27hhmAH6139LE Dypx4rScp4A4Ape+PJN9Ukclqs31EtFmBP7aem0LrqUSgz25d79sRSA3nKWo 8ZlKROm70tXUETj6S2pnxnsqYWB1vlfGGIEHl52ORDymEn+aZos9ziOwzK94 1P4RlRCok3YV90PAI33KclcylZDmqc0rDkRArybSdvIuleAf0Bf+GE5eb+NL Z6dIsr7f4x9a7yFglHfebU84lSippXNMPEAgD9f1FL9CJZ7FLLTQHyFw9Wyt T1MAlfCINOH/mIGATPlYEH6WSoxeSfR0z0fglkVR6CYPKtHBp1nQU4TA9EDo VaYLlbi16nDhYDECVUJCNwrsqUSoMmbUUUHW56B2V8aSSshbbdyw7jsCjdPz 95bMqMTm39ItU/VkvTEw6Y8plfhuZjhf3ogAf4Fl6j0jKtGzk8trfSupD6d/ FoceldDdZdLQ1Y3ALqsc3lRtKhFEKVAy70WgJqvPS1ODSlxOqvfN7keg18RS 1UWRSoBq+zfUEQQupMYksLdTiST39IwdYwgsjldOJcpRCa6H8gHbJhDYcFe1 uEqKSix+d6r4w0Agq8dN3F6cSqRAF5V7kwhoaj4JnV1HJVzVLYI1phGojGzp iqdQid4w5tOPMwiYtQqC7SJUIrbB8JnyHKn39v3PPwlSicciW4Kj5xHwDArh tuUj/Z57oFC3gECk5GhtNAeV2OpVKCTERkDMZ4vSlmWMiDL8sE9wEYH0T7bx JSyM2OogZDxFspLoXYbFPEao2otu+byEQKnTV8vRaYyYyNzRELKMgHHRUlEE wggFr59HpFYQaObWWS9Bw4iU7PvpL0l2sjkXVDiKETIKgp/FVxGgZ7/oMB3C iJ3Xhz5cJjmU2WHQ34cRnFhf2EeS+Q9Tnob+w4jnvPXYCMnJjw9xUDsxwtgu MnSZZDl6uEvub4w4/G2+aInkgn0l1UatGLF/XKFikOS99xjyXU0YwZRQSvlA cl3f9luXf2CEY8Qmw4skn9A+MyFUhxFXMe1PFJKHox6Yv6whP/9+oWA6Wa9/ e33+3iqMcLtFU6SQzKHAjbVDjOC1MpW6QJ73boj+5QsVGHGHsq/nHamHVP2l dt6PGKH37lhgP6nXq02vdz37gBHVk1J9LFJf3Qu9aXpFGLFqZizDZpH5hBuX f77FCLN1MToDTAQsKRaOXrkYsck+V/oD6c8/l+jPHK/Iernu9Fwk/WOumbup +RwjMr6ZjD0j/Y62Uxn9nk7+/y0lnfVkHqivXQ+7pGFE3Ej3SX8yL2pmzSJJ SRjxUz9Sf5yGQEW6wCXle6R/C1xMLjJvpghvqYrHiMJ//sk8ZB7dEvMfzt7E iKPYSsCXwf/10zArPhIjTNRVK66ReQ7fKW2/PRwjRjYEj24l8572J17GNpi8 vpAxW6ETAQWl6kjGZYzY1uQyEPsHgQ9hi4PRlzBi8/eWj7/aEGiS9n5d4o0R f4ue6ko3IbDG3URL4gxGtFuvzX1RRebFQdNu4iRGBJ7mLbxBIPD0hNSVT7YY MSXp/cryE6mfGfrqbEnmaeCO/1uyvz20H57MMSLz5sIuDnmFgJbq9WtXcDKv e1JulGUhsCJ/LvPoXoxg8StYjZDz46EkoE/rYkTA7kGeNakIfOMciTBQwgjr OxEsy1hyvi02vRTegRH/7di5bfoGmde5srqeraT/zAce4eT8Yo3eXRe1mdST krHXgZxvSk26rxrEMGLa6VW0qisC8U+jf55ZoBAVjTUG63eT+XrkO6s+SyHU b/wwD9FGYFviKQmuKQphfM0657sqAp9uqrlmj1OIZ4Xmx9TlEGD4tM8zuilE h9TdShFBMg8G8tIR1RTCRZHzimw7A2zaKWZ0/DOFmHDZyWH2kwFG1die2yop ROY5TRHXbwxwXa6x8FsJhaj6wdVhW8YARQKBxpRcChFjZPKfTToDUP989Xlx n0LAbKdd7x0ZgFB+Hht1l0KoQRlKsx0D+IRfyfK4TSF2KVVe7bZggBp57S6l mxTiHYWx/RNggNCAjCPvgilE+Jj0ngxpBujHwpSqHSlE9arSLOsPHRSZa4wO qVKIt4USobI4HTg+X8vzTYlCnBdd5FjaSQdCc8NbcnZQiELVovpqZTrweJJu d0GWQiSkhBnLbqQDyQnB2vl1FOJAx/dQXjoNRMYOveRbEiNS4rvvxyTTwPGq NFfFOjEiq8uiLqljAmxrHfxXWyNGXOhTytNrmADzg2qnPKrEiPIFSlFt5QRI 5a2yzKwQI1itwZZ5mROg13Ri7+Z8MUJHb3Ik1mcCnG8yEKc8ECPMiBbNR+xx ENvd1cA8I0a0NW2Nt+MfB2For8+9AVGipkwp/BttBDxx1hvFu0WJiA6Rt8ud I6CiRcNtql2UEH59kGdb/QhYKdlqf7xOlCjXybU88HoEREYImK0rFCVCzm+5 3+o2AuIobcqProkSbskWwns7hkGats/EMwlRot9j45vQkiFQGpTmnW8hQnC+ /fVIyWwAHE20kVlJFSL2CD+YvTfwF5ikfzp6iCZINB0+a1nl2QCya0Pa/U8L EDGSOrOm5U+AQ9SD9T9f8RGoNCf5g28tvObE/XYtlZfIGsx+z9/7G3KoboFG N3mIgjuWcXcu9cErGwwdbl7jIYiPna+3xfbBhVWX5ZogHiJtjb51/tM+yGjO NjjszUOU/vUQeFbfBzuD1UotLXiIzn26esPb+mFx9d7CMxI8hBH3loY1bf3w vL19ZtAbbiKb9VZ2s/Ig/Hs7NSa3jYsQK/gh6Zk7DFu+yuQ5/eQiNM48qt36 aRg2rP7XtP47F0HJFXNtbhyGlf7FEhEVXMQp6WP6a6aH4YvTLbnWmVzEXh/a bkJvBHorCzct+3IRTls8JCKJEbhYFyFuKcRF4MMZYrSaUTjLw793DS8XMXtd QKS5fRQy9iU4l61yElZyYW9eDY/C3qL0nG0znESG1rHcHbxjsDqtbA+rg5OI HPqaeO7AGIz3nnV68R8n0R5rXcBVOQY3CXq9nt3PSXTGrtuq+nIcOlQ2xMvt 4SSSI9IPg/fj8Lmfpq/lTk5iv3Yt/76qcSjfydbN28FJpChd2szZNw7V8+5U uwpxEuCtZ+gTqQm4/+i7nuY2DqKkbqZK+s4EPJu4sr7Qi4Nw3jz5QNCZBvMO urL+OXMQyN0k9vF5GmSwa7uETnMQpnHevzaG0qCf6/1ML3MO4mp5G96cSINX dLZpymhxENUKbanmVTQo/SbpkfTCKvxg0ZVoK0OH53YqrenctAqffHxWElRH h35rPv4XKLoK/TPopTqtdBjaZnIY41qFS/TrrV3ddBgX4J5gOrIC3zRfAYxJ Osz5kCFRWrgCqw0nlNZvYMCxnRvVkg+uwLOx4R/P2zPg5JrsJo3dK7BbPdGq w40BmW06/g3KK3CalfxC/TwD8gceL+WmrMD3DLlDT64yoELxnf1+nctw/GgA JSCdAT11eewsfJfhBvzwzy0dDHiBN4k17rIM1woc26TTy4CB7bJPom2W4duC 7lqtEQaMDgR9n/SXYWLdsjyaZcDs4tBzKmuW4Ye4nnBXUQTfRguIfFtYgsFv NA3q1iNYbPuowHV8CS7JhKtLbUKwZv7DXNrPJXhKzKswTAHBId2pcIG0Jejp cvSFLo4gjTdC7mX8ElR8SctjGCM42y7yFQ9fgvqCDY33jiDIE6QiGOy2BKss HhxKskVwW4nng2G1Jdi+LvH1vXMIuur9e1VVtQjTvPhWzt5H0OOVnu3BkkWY /E0nLigZQW+J+9zfcxZh9sjr35dSEfRdNHJovL8InTS+5qk8R/AKfE3tcFyE 57u+rpTlIxiuwf35tNUijBcfslJ7h2Dkc/sL/w4uwnk+zRN3ixGMvSH6fUB1 EVIGZTzWfULwgUnANcYiG3b7FDrt+o7gw9JG5UuIDXdW6TDFGhBMU1TomOln wzxWmXp7I4IZazu1Wd/Z0BtIBcu3Iph5Racv7BMbKvqV3ixsRzCbfufuSgEb zvz4p6LYgeCbn/gY9yM2NDX9afivG8ECPC0l+jYb9mwuz5PqRfB94YyRQDgb Wsf45xr3I1iWlP1UxIMNO3NFHR2HEfzEw2F2/yQbhn/3p1iMIkgEnGRRzcl6 9r88rjxO+mMnZC2hw4Ysu5krr+kIfv/mzvlkBxsmbEKuRxCCDbvhW2kpNhy6 G9jWMYlgs5SfwDYuNjyge9a6YgbBtvj64uw5FvS4gDmJzSH4Z3mbm+IYC8af rpq2nEewp+d3pVoTC7I79XMeMhHst9T0KaxiQTmHpz/SWQgOf46T0ClhwUF/ o4B7bATHtAZrinNYsM8wJePiIpmPzL2Xdz9lQbxBxMJgCUG07qFsxX0WXLOg ETFD8vTNycZ9N1nwVHS89qNlBOfmTa98DmbB39KfvBRXEGR6Zioe8GHBT8be W/4jefHPUnuNIwsqOpvYkfsnXDG1jTK1YsFDpVQxL5I5y/M1Gw6y4FX/NNNc knlUBHqO6rNg+JMi7k6S+dJd4n+psuAlabBvgWRBkYrd1rIsuPhVjbVKskj4 +pH2dSx42PCKzhzJlMkLD07ys+BmGbXJdpLXOX8z7FpkwrIWW5WXJIs3yyIH xIQjb9eNOZIsZRT2pK+fCduG7svzkSz9vtXUrZ0Jee/yDKWR9ctuV1sY/s6E mk/fbiP3fbgtJSbr7CcmpDK6h2LI8+/g6ztGK2CS/tAU+kh9lIL1Vy9kMeGy KGDIk0x0H1UaSGHCo7mfxw6S+toaudrY3WLCxp2vmBak/rRXQRH1YeT7CzOl 9pP+RIrE54ILTJh0J8BqM+mf+OWM9ndOTKj8CmX0kf6+7XjPqWDFhCFHZnkS SP87srrtxHYxYa9f8LqX0wheEJyOjFJiwopskS/CU6SevrxvmZuY0OazfZwj mS8NA3WePk4mfJ7C5Vs5QeYxw0jdZnYBJh2ZTagfQ9Ce98Sp78MLsL/j18/P I2T//YooKKxfgMWduz6cHSD10Uvu3F65AGUCe85I9ZH98OQ1b1rBAgzYmadS /A/BXs9m+8jkBRj8MtvoP7Kf9Fa2Clg5LsC5hN23g8h+bHDdpVN7bAFuGyx9 5FePoMt3M0eDAwvwXdtgp+03BO8+CPiwVXEBmvrsEer8TOZVqdZ5dnoeml4/ ZtdMzocr9zrjvYbmoYq/kvXGAgSxeVTS9XsertCOpBnnIbjvs7jI14p5WC3m I+yQhWCynXdZcvQ8zJL93nMtifTn07UhgZB56GW9KUgkgfRHLkns2rl5aDjq fjEmjvSDXu7hYUlywkjCzusIHogSpupJzkNjh3AUeR7Bv2Oy+3KF5uHxOAbt jBc53yx0z25ZnYMLGaKecq4IPpZ0hHyDczDULrjX8wTZLwUF5/68mYPLoz3W Q4YIPu+2qg4xnINmqzm9b8QQ1BrUYrfqzMEoi1fdiYIIVo9TNDQU5mBtyKFg Nx7y/As/Hw+LzEEoxkj+scCASpiZv1XXLHzA09VX0s2ARQcPyKkGzcKZyH32 ky8Z0Mh864lY71k4fmh10/OnDNhqxXV34MwsfLSvvnLfQwacdyJYqQdmYVgs Vykey4AGYXt+8WKzUCabzeN0lgGr83UievNmYLPAeUsxBQa0KaYWG2TMwNBT e9zvb2HA4YrpiZSkGVhpfjFnlbxf8tcV2JmHzkDBMP/OzDUMaD6ool5mMgN7 +/N81/bTYbv49n9J/dMQi5u1sn9IhyPX1+8xEZ+GqyZ/K9VmaVDwaj5KEpyG jEOpKiGjNKgWbJrZuzQFs2sOeb3tosHAC1cFQ/umILeBtE9HNQ3ynh76k5cz BVtTbj3WekCD23Q+BGB7p+CX1/JhLDUadBm2zu92noT9Z0R9pGwmYHQfw0XJ ehLKNu6//uvgBMzpit0QdHASppdkpPjvmoDTzRVXxZQnYZShMC2M3F+4wk0f RZNzO4hHx+dp7zgEmmO/jgkjuLYs21jHcxyWJSsYj9rS4dvAmnPT7mOQ//SI K+ceOlw3ZyscbzMGbWWyIyVl6bDwiGEt1XgMTudsJcwmaFDjOiyibx2DioS0 QWE4Dd6meBY29I7CR+PrNENfTcAfaZGVhnajMABwbhZij8H8i3HbHch9UGOs Y1Y9ndwT2eaX9WoH4eVJVcWNUcOwS8F5VPL9ICxduH5mxXsYcqt7Z0xlDEJD XqWahl3DkHosbm1I6CA8vjX04dnWIfj3AENiSmUQBpyR1M9cOwQ9f7Qn3EsY gGW/ToVvCB2A5/M/qfUf6YcHyjoFlm17If5VUHObSQ/0fZ3PpFBboPyewBMS 9c3Q1mPr8+YrHyG6nRck5PcR1jZ0xGlblYIW/fVEm2kp0Ff9XGT5sAW4/NHa cNq0BXAFru9yk+gF2pmunb6d/8App5zmUp1eMFCQ32CytgcUHQbfhSx7QTF7 XILfoAe4bDlb/D66F7j6Tu85kNYDvnyruMcz2wsMAmXPtyj3ghtSbsZZjX1A jr/r1eJwL+D5XPR24MYAkHm4NDJh1Q/4hCyvuzCGgYp4QPN7niFwYscpQldg BOBna5xHxYdAzn63VcFtI+CdU+YmYdUhcDQk+Oq7kyNgKNCzS9FmCKQMZ4Tw fB0B/d912W+zhoD856lL2Y9HAa9jVWQnPgyMA5Ncxg+NA5BgmOFwfgSk3E9/ Xuk6Dsz0+LnSw0fAaN5/vYnXxsEph/09dfdHQPxAuYPB+3HQGLj6Z/bDCGi1 HDwVv2UCvBfJ94hYHgFuyjut1OZJLpdne98aBTd62438MulAVyZ3ateDMfDv 45HzwRV0UJ+q5K2fOQb0k4iUa210kPID26lSNAYmjXPG4vgYoKToUXrvzzHg kHs1IfMcA2ycmS2/LTgO9AO3dbaS38tHdR86D1wZB6w1uz9KuUyC3sXfU6dt JkC238yPpxcmQWxyLrR1mQDWPW/6ZcMmga7NlUb84gQoKJUTUngwCT4lxCb0 x04Aj3NCjjo1k4AaU1R9unwCtDb18JgrTYF3730OSW+mgYLH0ZbXpqfA7h5R o4IWGqinRo+IckwDZu52zgs9NDB8++a158LToMo2ZHHDBA1suhKVV60wDV6b O9xQ4qKDWPtI/rWO0yCog5Nlq04HTpuvEQ/rp8GAl+rlypt0EJZ81U6xYxq8 5ytXULlH6iB8lVE2PA0M/L3TotLooGE5bNM/zhnQoRb2cO4tHez6FxK8bdcM UDRpV/7dTgdizwI0CrNmgP1i7O1EOQZQ3hhQu79oBlhYcJW8UmaAgwmXHVrh DKB11Km/1mGAK+H+8Qt/Z8C/AX/kdZABRh0vje6lzAKNgY9z/V4MQMicz6i7 Ogsu/dGrKX/NAJ2PfPTsb88Cvn1Yr38hA8yL+TTSH82CM/LcI+s/MoAK57kl sfez4PFOo+yN3xjgUZ/XCbvxWbCWy8+aMsQAF1+4iQ3azgF+r3tzfyT/9/wt 9cld1zngtX7h5BcZBN5aNirs9p0DZ4PO73kkjwBjRc/w7q054F0z6yOghYDP 6bV+uyrmQLH8WgnOQwjEa+Er/d/mQE6cnuBRcwTyBALi7rTNgSixW2dijiMw UfLvRT9jDixfTtgM7RHwXlfUEi87DyTSonP2+yIQNzHsqKc2D6zWDFhNX0Yg 54sUrU9/HrRXxh+8G4LAmO9NHj3reYA9P7gUF4mA148TO/ui54GQ87XTD5MQ iM268/l20jx4LCzB+fohAq/CvpjrZswDmz/gb/ZjBEYUVTxuf5wHJ3P3bPbM RMAjejVlJ20e3Fqef8EqRCD6jM7WXuY8eBjx7LnPBwSydc7mx61ZAHnLKp/r SxEY6m+u7ZFeAEIlCaeOQgTcQDbz1rEFYNN8utKtHoGoDZ1ROg4LYM2bitu7 GhHIootSerwXwBubYG9mEwIDj0MUdaIWwAZZBZs97Qi4MM1O/SteALfX7itq 7UEg8uf14dgq8v120138/Qi8yC72025aACW5KUKKgwj0Wcvcjh1bAFHNngGq owhwqNhs1J5fACbyYnmUcQRkuOMyu7mYYEfss/6+CQScCmfKtTYxgYT17OGD CIGIWIVD3QpMYHczNfTvJAIZjmdaY3YygYP10MtT0wgQuolOWvuZYGZ1uL5m BoEe4Vpa11EmaD1eNiE9h8DK4GJwzGkmMMyK4XGdR0C6QmONlhcT3PlzY33S AgIO3mmbY64zgS6Q2lzCQmCxQ6Bx6g4TvKyaCshmI/DINOSafRoTHKY5x0cu IqDzcVStNpsJllRGHI8sIfBL4USP5jsm0E7in+RYRuDCo9qEJ5AJTtSc2JNJ siC/Hs7XwATLfIEHtFYQ+C8oe/LSHyaQ0xHkf0vygZH1z7sGmcDpc130hlUE em1vHjOZYoLNn4OJcyRfrZnlLFpmgrye3vdvSJbUdSvaJMgCl9w6XbtILn7Z 4hKzgQXmNM1+kPs/sFpvRJ2WY4HFr3JT5P4PJqOKquzVWSBq96mfsyTHz8pe rjVggT84y5Pc/4Gi2/1tWodYIFwZK88iuaaFo+2JNQvoDn75Ru7/wMXI9yaf Mwt0T+rcJ/d/sFrUs9PvPAs4+aWve0LW/0TOYrgrhAUSt+212kzyrsTKFJNo FhBxcDK/TZ6/jVPNpCiRBTjFHLmHSb38LqUvbHrGAqyvTwJUSRbpE3oVk8sC OS9js5xJfXMtr5yYLmGB/y6k34sk9T9ETPCfqWYB6VBn/XukP4Pqpz/WNrHA 9TKPF3FMBK4/qzur1c0CmuWHv18i/ZQW1ZdMH2MB2YzifGPS77Jrr+v45lnA Z7ujLS+Zh9kzscrdImxALPiNmJP5ufdjodNEig26C6+3tJL5Ut3rGV+0gw2u DVFvHCLz57HpID0GZ4M7vLc05sl8csd/SJ82YwMeUR8NDTK/GYvbjp45yQb/ vjYv2JL57vjLna/lxwYqjTl93mT+Aw/7O6ZfYwO7tmDeE2R/YGX9ovy32QDN 3ljQ7EXALPWzb3cmGzzfGmeU14lApV24VmwbG9CEvXPKfiFwupbRP93HBtJv BuxEfiLA1HVIOsNgA22pXd1HGxDQ3LB3VotvEWBpUoEpNWT/trI/dO9aBN2A TcHLEMAPeHscMl4Eb17J57OLEeh+17Hh3bFF8J7xRuvFOwQ2JJUGxXovAoff I7MleQjcOha4W/vJInDecuj5SjoCiQ1KPnmvF8EeL/34+lTSb5Oep9tLFoFq UYpIZDICBXsP8Yg3L4IB+Zqh3HgE/ihK/lziWwJXY/j0Zsj515/VyBm4fgl8 iOjbKRyAAG3LDR0ktwREX2oPi5Hzk2MDLbVv7xIwvnT5bJs7AgpclW41/kvA t+OQs5UlAlpX/R6C60tAXMb2ePlhBPYw5etK7y6Bbr5/mLAxApaMBPXc10vg j30cdmE3AkF/ndkJPUvA8+JyhLwsmeeiNfdOHlkGjuEr05dpDNCkWval+cQy iKac7Qsj7yd/X12YO+KxDFIlJUd8/jEA4+nvU/uuL4OcCDcz4SYG2HD79fat JcuAnnpf5FARA7i7mpfT5FbA82pia44fA/CsSx4OZ68AMP7jiOkAHWCMayIY 3yrYe447+MBfOpD95qWbRV0FFVJvdFV/0cG+K3uiv6msAtu2v9drK+kgZHBg O8VxFbgU3UZbUumA8V7L/UXVKnA4X2bmfpgOaEqjl1wOcuB/9n2+dv4ZDcxu 7L6Za8aBwx3C7+Qf0MAiT3Pq7HEOPKdik1FjLA0I9pR/jnbkwHldkxNHL9HA jqQESm4wB27QU/jhsBENuCzqFs7kcOBhhloe9f0T4Hf9zckoUU48u8Tjwsy6 CfBgX7qxzQZOHKpKt7rxToDjhe/Ttm/mxI8arjz9skDuaSkDB2qUOHHJuYq7 Rn/HQY2zYSrfQU7cMY7BZf90HBQvLBnGXeHEeV9sbJ6UGwcpWy8nJYxx4gaD hjdYm8eATZiLbloVFz73hbZR/d8wSElfx7vwnQvv2uLicqphGLTDmjarJi68 nUPFMKhsGNjyKAcId3PhUTv4x26mDIMTd2beRcxz4SrpYzJM82Fw6lmUpqci N95dw2GiXzYEnKqyVXQSuHFq46+RmNhB4LN2Qq7xFA/OuzFgdWGlD2zJrUnh HV+D3/CpohuKdoCwUiMr0cd8+C6LoRPth74B32yfYl11Abxk3yooDQyFQlx6 LmpDgvjKD8NXDGY9ND5vnayUJITflON5xCz8C8U/br5ovE0ELxJd4xpH9MMV 1/+kKMoieKbFbvO49n44KKL5rUtTBL8ynP3sCq0fFrgdkL0MRPBT3L17d4kP QBOxcy0vTongY89/ZQtcHICBnqV6HPdF8KXDvTf4JAdh23orjvJlEVys0u4Y j/sQLCO68qJ5RPF2oH5SO2QIZpzzOHl8rSi+xdu3//idIejzOaRoTFwU7zgg D1w/DEGe8xlu4jqi+JeUB3dqeYahTjX9W4C3KO76JGJNYsYwTPSLva/xWxQv aqpcaqgfgeyGvNLYblHcgVti46euEeiy41dP74AoHjh1V/0pfQRqd0mo3Z8U xbV4nDW0RUfh+AubISaPGP7mUfHh/46NwnihkesnpcVw86M2dW9bRmFjj0C5 5DExXFw7beds/RjkEn7SeNBaDJ/cwbF38u8Y1NVX6/ezE8P99V9wdo2NwacP jgvUnxHD7Yuk0iP5xuFF08d2Yd5i+G++HPG1+8eh2DuV2c4bYnizrJ0c5/tx eDzaQjW9WAzn/ub0n9HtCZh9ctL040cxfCRw5cDQwwnIUrnv0VYhhp9fmdMJ zJqAGS3Nz4SrxPB8jsd0908TkC5ji137KYZ3699FYYwJGFtuv+AwStZP4a0J M6fBysmzn2UkKfjjGqMTqSs0iFUL/tuzmYK3KwxabBSgQ/eHuewTMhQ8iKek 7AaVDoX20bXvy1PwJqP6ph0KdHjytm82pzYFd7AbsHxiSYez24Nu9x+h4F7D t200n9Kh0ukom6yrFHyuhdtsQJkBT14qxniuU/CZtcIT7ToMGBsz+tM1ioLn lpgJfdjLgEPvzA5vvU3Bb63fX6FhwYAZQuvBi0cUXKFNdvv2Swy4vvKlQsY7 Cq6WRx1eKmDAA62/h1aLKXhPIE9bcikD+o0LZDqWUXC9+xdHxQkGbNpwYfOW zxQ8ysrVs7uRAeMu6mJPGyl45xjSdpxgQA7Z2sXHYxS84uCpPEMZBNX1WKWL NAr+41XZjVB5BB3MlQNPT1Lwy97umukqCJaHJExKLlBwj2/aK892IRjYbDeU yoPhgZftR9IsEMwavfWCxYfhZ9YeZsvaINiyUu54ci2G21yw/JJ4CkENZZm/ 4hiGi783cNF0R3Dixmjjwy0YPu+OhbiEICiZJhm/IIfhignd9brXEDxUYGZq J4/hiazo4tlIBLO7Cqo2qGJ4Zv2ag6rxCDrtDClN1sdwvS+KM/fSEUw4khsw txfD3b/TXxc+R7DSuVvLxhDDQ74c6yl/iaDUXcM36w5heIRxXFn8GwTbhwVe JNlguPdeneEtFQjWWN968vEEhs/o+jschwgWf+F/2HOavN76L8qXviCY8pQv XtkFw9X39X7y/4ZgtFBM9DF3DF/jNH/Nrp7UI5T3epAXhh+QyLmzoxFBG9s1 gVUXMPy39kp8fAuCB6qjfMcuYbj1WpNQ2XYEdbR4zokGYHiG17W3L/4guE6E 2+l0GIYDzntDZ7sRbP3KcXgmBsPPeTW6rx1GsFo74oDEbQyXzfnqzDWK4Pvn q/vAXQw/wvModWgMwQdXV7RvP8Dw1y0qpb50BKMmrqoVPsRwrWOfnogjBC+f XFb4nYbhu1jVpXmTCFrtXNq89TmG339pn5Q6g+D+zDBx0ywM16jcZDk9i6AW ZRG7+B+G8yq/x/XmEZQLDxVOzsHw5Kcn3bwWEMToLL7yNxj+XNSy7CYTQa7T IVx9BeR5Pg4bJrAQnP7GXOJ9j+Fqm0PYUWwE+3WDF1RKMPw8x8UBj0UEm7MW po6XYbjXxT1LOksIfsGCaMGfSP8qnA8gkosi5oefEhhuEHGuPHkZwReMgL7q Kgy/lzbtpLCCYKL9XOd4DYbLaT3R+d/z9si6y+1idRjOfi+hi60i6Ldrtkn3 B4an/1FwP0uyS7Z/vX0Tef60pM95JB9bN/M1sgXDK/dpHCH3bYhH+hGv2kk/ rfo4mSRrTE6VNXZgeHtu8tD/nrfLOFz6MNuF4Qvuh+ZnSBZrmMyX7MVwzWEO nVaSOfR9c/ABDD/U0fw0g+TJ/1CWxzCGz2r/0z1Jcu/6i8/ixzD8q5bF0jJZ b9MNRmoRDcMppxzQXZKJqfMP/iAM/x5gKSZEcoEj/e7KNIZbpQY6BpDnz/jh c2vbPIbbblHrriP1uWdAu3GYheGRr3tvCZEc8frcNd8lDDeT4fHQJ/X13TgR nLKK4dlFkn7WpP4WM2Pn+9dQcfsDnpvMSb/2OZ/14heg4tjqv3Jl0k+1n6Mu akJU3OTIjzvzcwiK5I7YhWJU/BmPeIMlmY8Vcc/jGeupeM8xcf3eKQQZ0cNm NeJUvBm1d58m89ToMmSIbaHiByrP1G0k89fH8x8zWY6KF9isKZebQHA22ytf Qp6Kh5Xk860n8yoxMbFJVpWK62gHlecPIqhy501LlgYVD+VmbSf3abhP/WKc gg4V1+A3mRnpQdDNf3pB3YCK0xX7P336i2DQ+vdv3+2j4m4cKpCb7J+4kgB3 vf1UXDzMQFmzDcH8RWbzPlMqfuhJgNn+nwiyb6y+Mbej4rHGPHN7yX4Wlv/s 9usUFY8QzboDK0l/v0VK2ThQ8b9tcVkK5QgaC/Hesnen4ql1NicK35F6PxBy O+dPxdWY0krpmQhm6jZKokAqfvB7Pu/pZ+S8+JPwyy+Uit95XRXC8RjBzk1U EHqdikttZGlwJSIo/1JC8lYCFbe2O3Gwj5xvu006m4SSqDg6brC7i5x/ZmNP Yu6lUPGBq0k9lZcRvKQqM/cwnYqvOX7d1sAbwYoP8k3ZuVTcLPOqE8UaweM1 2tHVtVS8T+hl+c6tCLp7ze05VE/FI6uTR99sQjBYsGSmvpGKr2sdFxPZgGD6 UX3nljYqfk/R1CuaH8HRdnxP/wAVhzHJX+1oDMgO5ppxH6HivpNDTmJDDCgs Vf16bJyK5/2+JVfYzYBajiYbp6ao+CO9F+q55P3EmFOg8fIcFQ94lx/NU8uA JzLrophMKm6au1/qIGRAb+N4gytLVPxDlM3MxRIG/P/fP+L///tH+H/K0OsC "]]}, Annotation[#, "Charting`Private`Tag$14865#1"]& ]}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{True, True}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{False, False}, {False, False}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}, {Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{ "DefaultBoundaryStyle" -> Automatic, "DefaultGraphicsInteraction" -> { "Version" -> 1.2, "TrackMousePosition" -> {True, False}, "Effects" -> { "Highlight" -> {"ratio" -> 2}, "HighlightPoint" -> {"ratio" -> 2}, "Droplines" -> { "freeformCursorMode" -> True, "placement" -> {"x" -> "All", "y" -> "None"}}}}, "DefaultMeshStyle" -> AbsolutePointSize[6], "ScalingFunctions" -> None, "CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotRange->{{-5, 5}, {-0.999999987301805, 0.9999999723133323}}, PlotRangeClipping->True, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}], Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], Graphics[{{{{}, {}, Annotation[{ Directive[ Opacity[1.], RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[1.6]], Line[CompressedData[" 1:eJwtmnk0VP//x23Zss2dFksJlex7FNX7SpIiytYi+5ZUIntFEpJSRFFKkU+h LBVC3reIQpKthOz7zLztZsb2u99zfv+M8zjHzH29n8/n63Vfc8/Iulw87s7F wcFxn3z539+rI+bTq6tUwoI5uy4ynwGGwzbMdS5RCckWzU2pxQxwVKxnoYRF JZz3Ruqkf2IAmd2+yxdnqIRv6qYYn3oG+BKXyN87TCVk5Fb27hhmAH6139LE Dypx4rScp4A4Ape+PJN9Ukclqs31EtFmBP7aem0LrqUSgz25d79sRSA3nKWo 8ZlKROm70tXUETj6S2pnxnsqYWB1vlfGGIEHl52ORDymEn+aZos9ziOwzK94 1P4RlRCok3YV90PAI33KclcylZDmqc0rDkRArybSdvIuleAf0Bf+GE5eb+NL Z6dIsr7f4x9a7yFglHfebU84lSippXNMPEAgD9f1FL9CJZ7FLLTQHyFw9Wyt T1MAlfCINOH/mIGATPlYEH6WSoxeSfR0z0fglkVR6CYPKtHBp1nQU4TA9EDo VaYLlbi16nDhYDECVUJCNwrsqUSoMmbUUUHW56B2V8aSSshbbdyw7jsCjdPz 95bMqMTm39ItU/VkvTEw6Y8plfhuZjhf3ogAf4Fl6j0jKtGzk8trfSupD6d/ FoceldDdZdLQ1Y3ALqsc3lRtKhFEKVAy70WgJqvPS1ODSlxOqvfN7keg18RS 1UWRSoBq+zfUEQQupMYksLdTiST39IwdYwgsjldOJcpRCa6H8gHbJhDYcFe1 uEqKSix+d6r4w0Agq8dN3F6cSqRAF5V7kwhoaj4JnV1HJVzVLYI1phGojGzp iqdQid4w5tOPMwiYtQqC7SJUIrbB8JnyHKn39v3PPwlSicciW4Kj5xHwDArh tuUj/Z57oFC3gECk5GhtNAeV2OpVKCTERkDMZ4vSlmWMiDL8sE9wEYH0T7bx JSyM2OogZDxFspLoXYbFPEao2otu+byEQKnTV8vRaYyYyNzRELKMgHHRUlEE wggFr59HpFYQaObWWS9Bw4iU7PvpL0l2sjkXVDiKETIKgp/FVxGgZ7/oMB3C iJ3Xhz5cJjmU2WHQ34cRnFhf2EeS+Q9Tnob+w4jnvPXYCMnJjw9xUDsxwtgu MnSZZDl6uEvub4w4/G2+aInkgn0l1UatGLF/XKFikOS99xjyXU0YwZRQSvlA cl3f9luXf2CEY8Qmw4skn9A+MyFUhxFXMe1PFJKHox6Yv6whP/9+oWA6Wa9/ e33+3iqMcLtFU6SQzKHAjbVDjOC1MpW6QJ73boj+5QsVGHGHsq/nHamHVP2l dt6PGKH37lhgP6nXq02vdz37gBHVk1J9LFJf3Qu9aXpFGLFqZizDZpH5hBuX f77FCLN1MToDTAQsKRaOXrkYsck+V/oD6c8/l+jPHK/Iernu9Fwk/WOumbup +RwjMr6ZjD0j/Y62Uxn9nk7+/y0lnfVkHqivXQ+7pGFE3Ej3SX8yL2pmzSJJ SRjxUz9Sf5yGQEW6wCXle6R/C1xMLjJvpghvqYrHiMJ//sk8ZB7dEvMfzt7E iKPYSsCXwf/10zArPhIjTNRVK66ReQ7fKW2/PRwjRjYEj24l8572J17GNpi8 vpAxW6ETAQWl6kjGZYzY1uQyEPsHgQ9hi4PRlzBi8/eWj7/aEGiS9n5d4o0R f4ue6ko3IbDG3URL4gxGtFuvzX1RRebFQdNu4iRGBJ7mLbxBIPD0hNSVT7YY MSXp/cryE6mfGfrqbEnmaeCO/1uyvz20H57MMSLz5sIuDnmFgJbq9WtXcDKv e1JulGUhsCJ/LvPoXoxg8StYjZDz46EkoE/rYkTA7kGeNakIfOMciTBQwgjr OxEsy1hyvi02vRTegRH/7di5bfoGmde5srqeraT/zAce4eT8Yo3eXRe1mdST krHXgZxvSk26rxrEMGLa6VW0qisC8U+jf55ZoBAVjTUG63eT+XrkO6s+SyHU b/wwD9FGYFviKQmuKQphfM0657sqAp9uqrlmj1OIZ4Xmx9TlEGD4tM8zuilE h9TdShFBMg8G8tIR1RTCRZHzimw7A2zaKWZ0/DOFmHDZyWH2kwFG1die2yop ROY5TRHXbwxwXa6x8FsJhaj6wdVhW8YARQKBxpRcChFjZPKfTToDUP989Xlx n0LAbKdd7x0ZgFB+Hht1l0KoQRlKsx0D+IRfyfK4TSF2KVVe7bZggBp57S6l mxTiHYWx/RNggNCAjCPvgilE+Jj0ngxpBujHwpSqHSlE9arSLOsPHRSZa4wO qVKIt4USobI4HTg+X8vzTYlCnBdd5FjaSQdCc8NbcnZQiELVovpqZTrweJJu d0GWQiSkhBnLbqQDyQnB2vl1FOJAx/dQXjoNRMYOveRbEiNS4rvvxyTTwPGq NFfFOjEiq8uiLqljAmxrHfxXWyNGXOhTytNrmADzg2qnPKrEiPIFSlFt5QRI 5a2yzKwQI1itwZZ5mROg13Ri7+Z8MUJHb3Ik1mcCnG8yEKc8ECPMiBbNR+xx ENvd1cA8I0a0NW2Nt+MfB2For8+9AVGipkwp/BttBDxx1hvFu0WJiA6Rt8ud I6CiRcNtql2UEH59kGdb/QhYKdlqf7xOlCjXybU88HoEREYImK0rFCVCzm+5 3+o2AuIobcqProkSbskWwns7hkGats/EMwlRot9j45vQkiFQGpTmnW8hQnC+ /fVIyWwAHE20kVlJFSL2CD+YvTfwF5ikfzp6iCZINB0+a1nl2QCya0Pa/U8L EDGSOrOm5U+AQ9SD9T9f8RGoNCf5g28tvObE/XYtlZfIGsx+z9/7G3KoboFG N3mIgjuWcXcu9cErGwwdbl7jIYiPna+3xfbBhVWX5ZogHiJtjb51/tM+yGjO NjjszUOU/vUQeFbfBzuD1UotLXiIzn26esPb+mFx9d7CMxI8hBH3loY1bf3w vL19ZtAbbiKb9VZ2s/Ig/Hs7NSa3jYsQK/gh6Zk7DFu+yuQ5/eQiNM48qt36 aRg2rP7XtP47F0HJFXNtbhyGlf7FEhEVXMQp6WP6a6aH4YvTLbnWmVzEXh/a bkJvBHorCzct+3IRTls8JCKJEbhYFyFuKcRF4MMZYrSaUTjLw793DS8XMXtd QKS5fRQy9iU4l61yElZyYW9eDY/C3qL0nG0znESG1rHcHbxjsDqtbA+rg5OI HPqaeO7AGIz3nnV68R8n0R5rXcBVOQY3CXq9nt3PSXTGrtuq+nIcOlQ2xMvt 4SSSI9IPg/fj8Lmfpq/lTk5iv3Yt/76qcSjfydbN28FJpChd2szZNw7V8+5U uwpxEuCtZ+gTqQm4/+i7nuY2DqKkbqZK+s4EPJu4sr7Qi4Nw3jz5QNCZBvMO urL+OXMQyN0k9vF5GmSwa7uETnMQpnHevzaG0qCf6/1ML3MO4mp5G96cSINX dLZpymhxENUKbanmVTQo/SbpkfTCKvxg0ZVoK0OH53YqrenctAqffHxWElRH h35rPv4XKLoK/TPopTqtdBjaZnIY41qFS/TrrV3ddBgX4J5gOrIC3zRfAYxJ Osz5kCFRWrgCqw0nlNZvYMCxnRvVkg+uwLOx4R/P2zPg5JrsJo3dK7BbPdGq w40BmW06/g3KK3CalfxC/TwD8gceL+WmrMD3DLlDT64yoELxnf1+nctw/GgA JSCdAT11eewsfJfhBvzwzy0dDHiBN4k17rIM1woc26TTy4CB7bJPom2W4duC 7lqtEQaMDgR9n/SXYWLdsjyaZcDs4tBzKmuW4Ye4nnBXUQTfRguIfFtYgsFv NA3q1iNYbPuowHV8CS7JhKtLbUKwZv7DXNrPJXhKzKswTAHBId2pcIG0Jejp cvSFLo4gjTdC7mX8ElR8SctjGCM42y7yFQ9fgvqCDY33jiDIE6QiGOy2BKss HhxKskVwW4nng2G1Jdi+LvH1vXMIuur9e1VVtQjTvPhWzt5H0OOVnu3BkkWY /E0nLigZQW+J+9zfcxZh9sjr35dSEfRdNHJovL8InTS+5qk8R/AKfE3tcFyE 57u+rpTlIxiuwf35tNUijBcfslJ7h2Dkc/sL/w4uwnk+zRN3ixGMvSH6fUB1 EVIGZTzWfULwgUnANcYiG3b7FDrt+o7gw9JG5UuIDXdW6TDFGhBMU1TomOln wzxWmXp7I4IZazu1Wd/Z0BtIBcu3Iph5Racv7BMbKvqV3ixsRzCbfufuSgEb zvz4p6LYgeCbn/gY9yM2NDX9afivG8ECPC0l+jYb9mwuz5PqRfB94YyRQDgb Wsf45xr3I1iWlP1UxIMNO3NFHR2HEfzEw2F2/yQbhn/3p1iMIkgEnGRRzcl6 9r88rjxO+mMnZC2hw4Ysu5krr+kIfv/mzvlkBxsmbEKuRxCCDbvhW2kpNhy6 G9jWMYlgs5SfwDYuNjyge9a6YgbBtvj64uw5FvS4gDmJzSH4Z3mbm+IYC8af rpq2nEewp+d3pVoTC7I79XMeMhHst9T0KaxiQTmHpz/SWQgOf46T0ClhwUF/ o4B7bATHtAZrinNYsM8wJePiIpmPzL2Xdz9lQbxBxMJgCUG07qFsxX0WXLOg ETFD8vTNycZ9N1nwVHS89qNlBOfmTa98DmbB39KfvBRXEGR6Zioe8GHBT8be W/4jefHPUnuNIwsqOpvYkfsnXDG1jTK1YsFDpVQxL5I5y/M1Gw6y4FX/NNNc knlUBHqO6rNg+JMi7k6S+dJd4n+psuAlabBvgWRBkYrd1rIsuPhVjbVKskj4 +pH2dSx42PCKzhzJlMkLD07ys+BmGbXJdpLXOX8z7FpkwrIWW5WXJIs3yyIH xIQjb9eNOZIsZRT2pK+fCduG7svzkSz9vtXUrZ0Jee/yDKWR9ctuV1sY/s6E mk/fbiP3fbgtJSbr7CcmpDK6h2LI8+/g6ztGK2CS/tAU+kh9lIL1Vy9kMeGy KGDIk0x0H1UaSGHCo7mfxw6S+toaudrY3WLCxp2vmBak/rRXQRH1YeT7CzOl 9pP+RIrE54ILTJh0J8BqM+mf+OWM9ndOTKj8CmX0kf6+7XjPqWDFhCFHZnkS SP87srrtxHYxYa9f8LqX0wheEJyOjFJiwopskS/CU6SevrxvmZuY0OazfZwj mS8NA3WePk4mfJ7C5Vs5QeYxw0jdZnYBJh2ZTagfQ9Ce98Sp78MLsL/j18/P I2T//YooKKxfgMWduz6cHSD10Uvu3F65AGUCe85I9ZH98OQ1b1rBAgzYmadS /A/BXs9m+8jkBRj8MtvoP7Kf9Fa2Clg5LsC5hN23g8h+bHDdpVN7bAFuGyx9 5FePoMt3M0eDAwvwXdtgp+03BO8+CPiwVXEBmvrsEer8TOZVqdZ5dnoeml4/ ZtdMzocr9zrjvYbmoYq/kvXGAgSxeVTS9XsertCOpBnnIbjvs7jI14p5WC3m I+yQhWCynXdZcvQ8zJL93nMtifTn07UhgZB56GW9KUgkgfRHLkns2rl5aDjq fjEmjvSDXu7hYUlywkjCzusIHogSpupJzkNjh3AUeR7Bv2Oy+3KF5uHxOAbt jBc53yx0z25ZnYMLGaKecq4IPpZ0hHyDczDULrjX8wTZLwUF5/68mYPLoz3W Q4YIPu+2qg4xnINmqzm9b8QQ1BrUYrfqzMEoi1fdiYIIVo9TNDQU5mBtyKFg Nx7y/As/Hw+LzEEoxkj+scCASpiZv1XXLHzA09VX0s2ARQcPyKkGzcKZyH32 ky8Z0Mh864lY71k4fmh10/OnDNhqxXV34MwsfLSvvnLfQwacdyJYqQdmYVgs Vykey4AGYXt+8WKzUCabzeN0lgGr83UievNmYLPAeUsxBQa0KaYWG2TMwNBT e9zvb2HA4YrpiZSkGVhpfjFnlbxf8tcV2JmHzkDBMP/OzDUMaD6ool5mMgN7 +/N81/bTYbv49n9J/dMQi5u1sn9IhyPX1+8xEZ+GqyZ/K9VmaVDwaj5KEpyG jEOpKiGjNKgWbJrZuzQFs2sOeb3tosHAC1cFQ/umILeBtE9HNQ3ynh76k5cz BVtTbj3WekCD23Q+BGB7p+CX1/JhLDUadBm2zu92noT9Z0R9pGwmYHQfw0XJ ehLKNu6//uvgBMzpit0QdHASppdkpPjvmoDTzRVXxZQnYZShMC2M3F+4wk0f RZNzO4hHx+dp7zgEmmO/jgkjuLYs21jHcxyWJSsYj9rS4dvAmnPT7mOQ//SI K+ceOlw3ZyscbzMGbWWyIyVl6bDwiGEt1XgMTudsJcwmaFDjOiyibx2DioS0 QWE4Dd6meBY29I7CR+PrNENfTcAfaZGVhnajMABwbhZij8H8i3HbHch9UGOs Y1Y9ndwT2eaX9WoH4eVJVcWNUcOwS8F5VPL9ICxduH5mxXsYcqt7Z0xlDEJD XqWahl3DkHosbm1I6CA8vjX04dnWIfj3AENiSmUQBpyR1M9cOwQ9f7Qn3EsY gGW/ToVvCB2A5/M/qfUf6YcHyjoFlm17If5VUHObSQ/0fZ3PpFBboPyewBMS 9c3Q1mPr8+YrHyG6nRck5PcR1jZ0xGlblYIW/fVEm2kp0Ff9XGT5sAW4/NHa cNq0BXAFru9yk+gF2pmunb6d/8App5zmUp1eMFCQ32CytgcUHQbfhSx7QTF7 XILfoAe4bDlb/D66F7j6Tu85kNYDvnyruMcz2wsMAmXPtyj3ghtSbsZZjX1A jr/r1eJwL+D5XPR24MYAkHm4NDJh1Q/4hCyvuzCGgYp4QPN7niFwYscpQldg BOBna5xHxYdAzn63VcFtI+CdU+YmYdUhcDQk+Oq7kyNgKNCzS9FmCKQMZ4Tw fB0B/d912W+zhoD856lL2Y9HAa9jVWQnPgyMA5Ncxg+NA5BgmOFwfgSk3E9/ Xuk6Dsz0+LnSw0fAaN5/vYnXxsEph/09dfdHQPxAuYPB+3HQGLj6Z/bDCGi1 HDwVv2UCvBfJ94hYHgFuyjut1OZJLpdne98aBTd62438MulAVyZ3ateDMfDv 45HzwRV0UJ+q5K2fOQb0k4iUa210kPID26lSNAYmjXPG4vgYoKToUXrvzzHg kHs1IfMcA2ycmS2/LTgO9AO3dbaS38tHdR86D1wZB6w1uz9KuUyC3sXfU6dt JkC238yPpxcmQWxyLrR1mQDWPW/6ZcMmga7NlUb84gQoKJUTUngwCT4lxCb0 x04Aj3NCjjo1k4AaU1R9unwCtDb18JgrTYF3730OSW+mgYLH0ZbXpqfA7h5R o4IWGqinRo+IckwDZu52zgs9NDB8++a158LToMo2ZHHDBA1suhKVV60wDV6b O9xQ4qKDWPtI/rWO0yCog5Nlq04HTpuvEQ/rp8GAl+rlypt0EJZ81U6xYxq8 5ytXULlH6iB8lVE2PA0M/L3TotLooGE5bNM/zhnQoRb2cO4tHez6FxK8bdcM UDRpV/7dTgdizwI0CrNmgP1i7O1EOQZQ3hhQu79oBlhYcJW8UmaAgwmXHVrh DKB11Km/1mGAK+H+8Qt/Z8C/AX/kdZABRh0vje6lzAKNgY9z/V4MQMicz6i7 Ogsu/dGrKX/NAJ2PfPTsb88Cvn1Yr38hA8yL+TTSH82CM/LcI+s/MoAK57kl sfez4PFOo+yN3xjgUZ/XCbvxWbCWy8+aMsQAF1+4iQ3azgF+r3tzfyT/9/wt 9cld1zngtX7h5BcZBN5aNirs9p0DZ4PO73kkjwBjRc/w7q054F0z6yOghYDP 6bV+uyrmQLH8WgnOQwjEa+Er/d/mQE6cnuBRcwTyBALi7rTNgSixW2dijiMw UfLvRT9jDixfTtgM7RHwXlfUEi87DyTSonP2+yIQNzHsqKc2D6zWDFhNX0Yg 54sUrU9/HrRXxh+8G4LAmO9NHj3reYA9P7gUF4mA148TO/ui54GQ87XTD5MQ iM268/l20jx4LCzB+fohAq/CvpjrZswDmz/gb/ZjBEYUVTxuf5wHJ3P3bPbM RMAjejVlJ20e3Fqef8EqRCD6jM7WXuY8eBjx7LnPBwSydc7mx61ZAHnLKp/r SxEY6m+u7ZFeAEIlCaeOQgTcQDbz1rEFYNN8utKtHoGoDZ1ROg4LYM2bitu7 GhHIootSerwXwBubYG9mEwIDj0MUdaIWwAZZBZs97Qi4MM1O/SteALfX7itq 7UEg8uf14dgq8v120138/Qi8yC72025aACW5KUKKgwj0Wcvcjh1bAFHNngGq owhwqNhs1J5fACbyYnmUcQRkuOMyu7mYYEfss/6+CQScCmfKtTYxgYT17OGD CIGIWIVD3QpMYHczNfTvJAIZjmdaY3YygYP10MtT0wgQuolOWvuZYGZ1uL5m BoEe4Vpa11EmaD1eNiE9h8DK4GJwzGkmMMyK4XGdR0C6QmONlhcT3PlzY33S AgIO3mmbY64zgS6Q2lzCQmCxQ6Bx6g4TvKyaCshmI/DINOSafRoTHKY5x0cu IqDzcVStNpsJllRGHI8sIfBL4USP5jsm0E7in+RYRuDCo9qEJ5AJTtSc2JNJ siC/Hs7XwATLfIEHtFYQ+C8oe/LSHyaQ0xHkf0vygZH1z7sGmcDpc130hlUE em1vHjOZYoLNn4OJcyRfrZnlLFpmgrye3vdvSJbUdSvaJMgCl9w6XbtILn7Z 4hKzgQXmNM1+kPs/sFpvRJ2WY4HFr3JT5P4PJqOKquzVWSBq96mfsyTHz8pe rjVggT84y5Pc/4Gi2/1tWodYIFwZK88iuaaFo+2JNQvoDn75Ru7/wMXI9yaf Mwt0T+rcJ/d/sFrUs9PvPAs4+aWve0LW/0TOYrgrhAUSt+212kzyrsTKFJNo FhBxcDK/TZ6/jVPNpCiRBTjFHLmHSb38LqUvbHrGAqyvTwJUSRbpE3oVk8sC OS9js5xJfXMtr5yYLmGB/y6k34sk9T9ETPCfqWYB6VBn/XukP4Pqpz/WNrHA 9TKPF3FMBK4/qzur1c0CmuWHv18i/ZQW1ZdMH2MB2YzifGPS77Jrr+v45lnA Z7ujLS+Zh9kzscrdImxALPiNmJP5ufdjodNEig26C6+3tJL5Ut3rGV+0gw2u DVFvHCLz57HpID0GZ4M7vLc05sl8csd/SJ82YwMeUR8NDTK/GYvbjp45yQb/ vjYv2JL57vjLna/lxwYqjTl93mT+Aw/7O6ZfYwO7tmDeE2R/YGX9ovy32QDN 3ljQ7EXALPWzb3cmGzzfGmeU14lApV24VmwbG9CEvXPKfiFwupbRP93HBtJv BuxEfiLA1HVIOsNgA22pXd1HGxDQ3LB3VotvEWBpUoEpNWT/trI/dO9aBN2A TcHLEMAPeHscMl4Eb17J57OLEeh+17Hh3bFF8J7xRuvFOwQ2JJUGxXovAoff I7MleQjcOha4W/vJInDecuj5SjoCiQ1KPnmvF8EeL/34+lTSb5Oep9tLFoFq UYpIZDICBXsP8Yg3L4IB+Zqh3HgE/ihK/lziWwJXY/j0Zsj515/VyBm4fgl8 iOjbKRyAAG3LDR0ktwREX2oPi5Hzk2MDLbVv7xIwvnT5bJs7AgpclW41/kvA t+OQs5UlAlpX/R6C60tAXMb2ePlhBPYw5etK7y6Bbr5/mLAxApaMBPXc10vg j30cdmE3AkF/ndkJPUvA8+JyhLwsmeeiNfdOHlkGjuEr05dpDNCkWval+cQy iKac7Qsj7yd/X12YO+KxDFIlJUd8/jEA4+nvU/uuL4OcCDcz4SYG2HD79fat JcuAnnpf5FARA7i7mpfT5FbA82pia44fA/CsSx4OZ68AMP7jiOkAHWCMayIY 3yrYe447+MBfOpD95qWbRV0FFVJvdFV/0cG+K3uiv6msAtu2v9drK+kgZHBg O8VxFbgU3UZbUumA8V7L/UXVKnA4X2bmfpgOaEqjl1wOcuB/9n2+dv4ZDcxu 7L6Za8aBwx3C7+Qf0MAiT3Pq7HEOPKdik1FjLA0I9pR/jnbkwHldkxNHL9HA jqQESm4wB27QU/jhsBENuCzqFs7kcOBhhloe9f0T4Hf9zckoUU48u8Tjwsy6 CfBgX7qxzQZOHKpKt7rxToDjhe/Ttm/mxI8arjz9skDuaSkDB2qUOHHJuYq7 Rn/HQY2zYSrfQU7cMY7BZf90HBQvLBnGXeHEeV9sbJ6UGwcpWy8nJYxx4gaD hjdYm8eATZiLbloVFz73hbZR/d8wSElfx7vwnQvv2uLicqphGLTDmjarJi68 nUPFMKhsGNjyKAcId3PhUTv4x26mDIMTd2beRcxz4SrpYzJM82Fw6lmUpqci N95dw2GiXzYEnKqyVXQSuHFq46+RmNhB4LN2Qq7xFA/OuzFgdWGlD2zJrUnh HV+D3/CpohuKdoCwUiMr0cd8+C6LoRPth74B32yfYl11Abxk3yooDQyFQlx6 LmpDgvjKD8NXDGY9ND5vnayUJITflON5xCz8C8U/br5ovE0ELxJd4xpH9MMV 1/+kKMoieKbFbvO49n44KKL5rUtTBL8ynP3sCq0fFrgdkL0MRPBT3L17d4kP QBOxcy0vTongY89/ZQtcHICBnqV6HPdF8KXDvTf4JAdh23orjvJlEVys0u4Y j/sQLCO68qJ5RPF2oH5SO2QIZpzzOHl8rSi+xdu3//idIejzOaRoTFwU7zgg D1w/DEGe8xlu4jqi+JeUB3dqeYahTjX9W4C3KO76JGJNYsYwTPSLva/xWxQv aqpcaqgfgeyGvNLYblHcgVti46euEeiy41dP74AoHjh1V/0pfQRqd0mo3Z8U xbV4nDW0RUfh+AubISaPGP7mUfHh/46NwnihkesnpcVw86M2dW9bRmFjj0C5 5DExXFw7beds/RjkEn7SeNBaDJ/cwbF38u8Y1NVX6/ezE8P99V9wdo2NwacP jgvUnxHD7Yuk0iP5xuFF08d2Yd5i+G++HPG1+8eh2DuV2c4bYnizrJ0c5/tx eDzaQjW9WAzn/ub0n9HtCZh9ctL040cxfCRw5cDQwwnIUrnv0VYhhp9fmdMJ zJqAGS3Nz4SrxPB8jsd0908TkC5ji137KYZ3699FYYwJGFtuv+AwStZP4a0J M6fBysmzn2UkKfjjGqMTqSs0iFUL/tuzmYK3KwxabBSgQ/eHuewTMhQ8iKek 7AaVDoX20bXvy1PwJqP6ph0KdHjytm82pzYFd7AbsHxiSYez24Nu9x+h4F7D t200n9Kh0ukom6yrFHyuhdtsQJkBT14qxniuU/CZtcIT7ToMGBsz+tM1ioLn lpgJfdjLgEPvzA5vvU3Bb63fX6FhwYAZQuvBi0cUXKFNdvv2Swy4vvKlQsY7 Cq6WRx1eKmDAA62/h1aLKXhPIE9bcikD+o0LZDqWUXC9+xdHxQkGbNpwYfOW zxQ8ysrVs7uRAeMu6mJPGyl45xjSdpxgQA7Z2sXHYxS84uCpPEMZBNX1WKWL NAr+41XZjVB5BB3MlQNPT1Lwy97umukqCJaHJExKLlBwj2/aK892IRjYbDeU yoPhgZftR9IsEMwavfWCxYfhZ9YeZsvaINiyUu54ci2G21yw/JJ4CkENZZm/ 4hiGi783cNF0R3Dixmjjwy0YPu+OhbiEICiZJhm/IIfhignd9brXEDxUYGZq J4/hiazo4tlIBLO7Cqo2qGJ4Zv2ag6rxCDrtDClN1sdwvS+KM/fSEUw4khsw txfD3b/TXxc+R7DSuVvLxhDDQ74c6yl/iaDUXcM36w5heIRxXFn8GwTbhwVe JNlguPdeneEtFQjWWN968vEEhs/o+jschwgWf+F/2HOavN76L8qXviCY8pQv XtkFw9X39X7y/4ZgtFBM9DF3DF/jNH/Nrp7UI5T3epAXhh+QyLmzoxFBG9s1 gVUXMPy39kp8fAuCB6qjfMcuYbj1WpNQ2XYEdbR4zokGYHiG17W3L/4guE6E 2+l0GIYDzntDZ7sRbP3KcXgmBsPPeTW6rx1GsFo74oDEbQyXzfnqzDWK4Pvn q/vAXQw/wvModWgMwQdXV7RvP8Dw1y0qpb50BKMmrqoVPsRwrWOfnogjBC+f XFb4nYbhu1jVpXmTCFrtXNq89TmG339pn5Q6g+D+zDBx0ywM16jcZDk9i6AW ZRG7+B+G8yq/x/XmEZQLDxVOzsHw5Kcn3bwWEMToLL7yNxj+XNSy7CYTQa7T IVx9BeR5Pg4bJrAQnP7GXOJ9j+Fqm0PYUWwE+3WDF1RKMPw8x8UBj0UEm7MW po6XYbjXxT1LOksIfsGCaMGfSP8qnA8gkosi5oefEhhuEHGuPHkZwReMgL7q Kgy/lzbtpLCCYKL9XOd4DYbLaT3R+d/z9si6y+1idRjOfi+hi60i6Ldrtkn3 B4an/1FwP0uyS7Z/vX0Tef60pM95JB9bN/M1sgXDK/dpHCH3bYhH+hGv2kk/ rfo4mSRrTE6VNXZgeHtu8tD/nrfLOFz6MNuF4Qvuh+ZnSBZrmMyX7MVwzWEO nVaSOfR9c/ABDD/U0fw0g+TJ/1CWxzCGz2r/0z1Jcu/6i8/ixzD8q5bF0jJZ b9MNRmoRDcMppxzQXZKJqfMP/iAM/x5gKSZEcoEj/e7KNIZbpQY6BpDnz/jh c2vbPIbbblHrriP1uWdAu3GYheGRr3tvCZEc8frcNd8lDDeT4fHQJ/X13TgR nLKK4dlFkn7WpP4WM2Pn+9dQcfsDnpvMSb/2OZ/14heg4tjqv3Jl0k+1n6Mu akJU3OTIjzvzcwiK5I7YhWJU/BmPeIMlmY8Vcc/jGeupeM8xcf3eKQQZ0cNm NeJUvBm1d58m89ToMmSIbaHiByrP1G0k89fH8x8zWY6KF9isKZebQHA22ytf Qp6Kh5Xk860n8yoxMbFJVpWK62gHlecPIqhy501LlgYVD+VmbSf3abhP/WKc gg4V1+A3mRnpQdDNf3pB3YCK0xX7P336i2DQ+vdv3+2j4m4cKpCb7J+4kgB3 vf1UXDzMQFmzDcH8RWbzPlMqfuhJgNn+nwiyb6y+Mbej4rHGPHN7yX4Wlv/s 9usUFY8QzboDK0l/v0VK2ThQ8b9tcVkK5QgaC/Hesnen4ql1NicK35F6PxBy O+dPxdWY0krpmQhm6jZKokAqfvB7Pu/pZ+S8+JPwyy+Uit95XRXC8RjBzk1U EHqdikttZGlwJSIo/1JC8lYCFbe2O3Gwj5xvu006m4SSqDg6brC7i5x/ZmNP Yu6lUPGBq0k9lZcRvKQqM/cwnYqvOX7d1sAbwYoP8k3ZuVTcLPOqE8UaweM1 2tHVtVS8T+hl+c6tCLp7ze05VE/FI6uTR99sQjBYsGSmvpGKr2sdFxPZgGD6 UX3nljYqfk/R1CuaH8HRdnxP/wAVhzHJX+1oDMgO5ppxH6HivpNDTmJDDCgs Vf16bJyK5/2+JVfYzYBajiYbp6ao+CO9F+q55P3EmFOg8fIcFQ94lx/NU8uA JzLrophMKm6au1/qIGRAb+N4gytLVPxDlM3MxRIG/P/fP+L///tH+H/K0OsC "]]}, "Charting`Private`Tag$14865#1"]}}, {}}, { DisplayFunction -> Identity, Ticks -> {Automatic, Automatic}, AxesOrigin -> {0, 0}, FrameTicks -> {{Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}, {Automatic, Charting`ScaledFrameTicks[{Identity, Identity}]}}, GridLines -> {None, None}, DisplayFunction -> Identity, PlotRangePadding -> {{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, PlotRangeClipping -> True, ImagePadding -> All, DisplayFunction -> Identity, AspectRatio -> GoldenRatio^(-1), Axes -> {True, True}, AxesLabel -> {None, None}, AxesOrigin -> {0, 0}, DisplayFunction :> Identity, Frame -> {{False, False}, {False, False}}, FrameLabel -> {{None, None}, {None, None}}, FrameTicks -> {{Automatic, Automatic}, {Automatic, Automatic}}, GridLines -> {None, None}, GridLinesStyle -> Directive[ GrayLevel[0.5, 0.4]], Method -> { "DefaultBoundaryStyle" -> Automatic, "DefaultGraphicsInteraction" -> { "Version" -> 1.2, "TrackMousePosition" -> {True, False}, "Effects" -> { "Highlight" -> {"ratio" -> 2}, "HighlightPoint" -> {"ratio" -> 2}, "Droplines" -> { "freeformCursorMode" -> True, "placement" -> {"x" -> "All", "y" -> "None"}}}}, "DefaultMeshStyle" -> AbsolutePointSize[6], "ScalingFunctions" -> None, "CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotRange -> {{-5, 5}, {-0.999999987301805, 0.9999999723133323}}, PlotRangeClipping -> True, PlotRangePadding -> {{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.02], Scaled[0.02]}}, Ticks -> {Automatic, Automatic}}]]], "Output", CellChangeTimes->{3.7560798646519794`*^9}, CellLabel->"Out[31]=", CellID->8129617] }, Open ]], Cell[CellGroupData[{ Cell["", "PageBreak", PageBreakBelow->True, CellID->119259169], Cell["Birds can say words:", "Text", CellChangeTimes->{3.756079873084715*^9}, CellID->113439233], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"BirdSay", "[", RowBox[{"WordCloud", "[", RowBox[{"WikipediaData", "[", "\"\\"", "]"}], "]"}], "]"}]], "Input", CellChangeTimes->{3.75607987633261*^9}, CellLabel->"In[1]:=", CellID->120533573], Cell[BoxData[ InterpretationBox[ PanelBox[ GraphicsBox[{InsetBox[ StyleBox["\<\"word\"\>", StripOnInput->False, FontSize->Scaled[0.24054982817869416`], FontColor->RGBColor[0.368417, 0.506779, 0.709798]], {0, 0}, Center, Automatic], InsetBox[ StyleBox["\<\"words\"\>", StripOnInput->False, FontSize->Scaled[0.19596916504132997`], FontColor->RGBColor[0.880722, 0.611041, 0.142051]], {-14., 36.}, Center, Automatic], InsetBox[ StyleBox["\<\"language\"\>", StripOnInput->False, FontSize->Scaled[0.10123525587443113`], FontColor->RGBColor[0.560181, 0.691569, 0.194885]], {4., -33.}, Center, Automatic], InsetBox[ StyleBox["\<\"languages\"\>", StripOnInput->False, FontSize->Scaled[0.0900900900900901], FontColor->RGBColor[0.922526, 0.385626, 0.209179]], {0., -57.}, Center, Automatic], InsetBox[ StyleBox["\<\"meaning\"\>", StripOnInput->False, FontSize->Scaled[0.07894492430574904], FontColor->RGBColor[0.528488, 0.470624, 0.701351]], {-20., 63.}, Center, Automatic], InsetBox[ StyleBox["\<\"Cambridge\"\>", StripOnInput->False, FontSize->Scaled[0.062227175629237484`], FontColor->RGBColor[0.571589, 0.586483, 0.]], {0., 81.}, Center, Automatic], InsetBox[ StyleBox["\<\"example\"\>", StripOnInput->False, FontSize->Scaled[0.07337234141357853], FontColor->RGBColor[0.772079, 0.431554, 0.102387]], {-10., -79.}, Center, Automatic], InsetBox[ StyleBox["\<\"Orthography\"\>", StripOnInput->False, FontSize->Scaled[0.05108200984489644], FontColor->RGBColor[ 0.5833680111493557, 0.4126186601628758, 0.8290799721266107]], {72., 56.}, Center, Automatic], InsetBox[ StyleBox["\<\"English\"\>", StripOnInput->False, FontSize->Scaled[0.067799758521408], FontColor->RGBColor[0.363898, 0.618501, 0.782349]], {-86., -34.}, Center, Automatic], InsetBox[ StyleBox["\<\"morphemes\"\>", StripOnInput->False, FontSize->Scaled[0.05108200984489644], FontColor->RGBColor[ 0.838355547812947, 0.44746667828057946`, 0.0208888695323676]], {0., 96.}, Center, Automatic], InsetBox[ StyleBox["\<\"boundaries\"\>", StripOnInput->False, FontSize->Scaled[0.062227175629237484`], FontColor->RGBColor[0.647624, 0.37816, 0.614037]], {-5., -97.}, Center, Automatic], InsetBox[ StyleBox["\<\"University\"\>", StripOnInput->False, FontSize->Scaled[0.05108200984489644], FontColor->RGBColor[ 0.28240003484173815`, 0.6090799721266095, 0.7538800418100857]], {64., -75.}, Center, Automatic], InsetBox[ StyleBox["\<\"Philosophy\"\>", StripOnInput->False, FontSize->Scaled[0.045509426952725925`], FontColor->RGBColor[ 0.9874666782805795, 0.6948333914028977, 0.033839968642435214`]], {77., 69.}, Center, Automatic], InsetBox[ StyleBox["\<\"Semantic\"\>", StripOnInput->False, FontSize->Scaled[0.05665459273706697], FontColor->RGBColor[0.736782672705901, 0.358, 0.5030266573755369]], {-77., 76.}, Center, Automatic], InsetBox[ StyleBox["\<\"morpheme\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.8168067340273636, 0.3521386531945273, 0.3761554432877274]], {92., 36.}, Center, Automatic], InsetBox[ StyleBox["\<\"Features\"\>", StripOnInput->False, FontSize->Scaled[0.05665459273706697], FontColor->RGBColor[0.40082222609352647`, 0.5220066643438841, 0.85]], {-90., -54.}, Center, Automatic], InsetBox[ StyleBox["\<\"Encyclopedia\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[0.7989994773739094, 0.735166608597101, 0.]], {92., -50.}, Center, Automatic], InsetBox[ StyleBox["\<\"speaker\"\>", StripOnInput->False, FontSize->Scaled[0.045509426952725925`], FontColor->RGBColor[ 0.16397784358994957`, 0.7038177251280403, 0.6117734123079395]], {88., -29.}, Center, Automatic], InsetBox[ StyleBox["\<\"distinguished\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.8510135028964549, 0.47400900193096995`, 0.018912152606809424`]], {4., 108.}, Center, Automatic], InsetBox[ StyleBox["\<\"boundary\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.8878600487784333, 0.33792799024431336`, 0.2577332520359445]], {97., 0.}, Center, Automatic], InsetBox[ StyleBox["\<\"sentence\"\>", StripOnInput->False, FontSize->Scaled[0.05108200984489644], FontColor->RGBColor[ 0.8439466852489265, 0.3467106629502147, 0.3309221912517893]], {-79., -72.}, Center, Automatic], InsetBox[ StyleBox["\<\"particular\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.6536293927965667, 0.37163285420200276`, 0.6534265180085832]], {-96., -15.}, Center, Automatic], InsetBox[ StyleBox["\<\"considered\"\>", StripOnInput->False, FontSize->Scaled[0.045509426952725925`], FontColor->RGBColor[ 0.6753413537738198, 0.3589675436319385, 0.5991466155654507]], {76., 81.}, Center, Automatic], InsetBox[ StyleBox["\<\"ISBN\"\>", StripOnInput->False, FontSize->Scaled[0.067799758521408], FontColor->RGBColor[1, 0.75, 0]], {93., 15.}, Center, Automatic], InsetBox[ StyleBox["\<\"expressions\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.8774935098648088, 0.34000129802703827`, 0.2750108168919853]], {-91., 53.}, Center, Automatic], InsetBox[ StyleBox["\<\"language's\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.9107287510704583, 0.33890687339431275`, 0.20182187767614543`]], {97., -13.}, Center, Automatic], InsetBox[ StyleBox["\<\"constitutes\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.9637822400302223, 0.5764112001511111, 0.0977879519184]], {0., -111.}, Center, Automatic], InsetBox[ StyleBox["\<\"typically\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[0.6897400905885174, 0.358, 0.5753998606330502]], {-98., 0.}, Center, Automatic], InsetBox[ StyleBox["\<\"multiple\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.23716678280579248`, 0.645266573755366, 0.699600139366951]], {63., -88.}, Center, Automatic], InsetBox[ StyleBox["\<\"compound\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.6670481226429111, 0.3638052617916352, 0.6198796933927223]], {91., -60.}, Center, Automatic], InsetBox[ StyleBox["\<\"spoken\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[0.2187618985811806, 0.715, 0.5074848563512248]], {-65., 89.}, Center, Automatic], InsetBox[ StyleBox["\<\"spaces\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.7513196300394465, 0.358, 0.48066210763162087`]], {-70., -83.}, Center, Automatic], InsetBox[ StyleBox["\<\"written\"\>", StripOnInput->False, FontSize->Scaled[0.05108200984489644], FontColor->RGBColor[ 0.9324333565611593, 0.5282889043741062, 0.0921900209050434]], {63., 94.}, Center, Automatic], InsetBox[ StyleBox["\<\"fundamental\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[0.7042770479220728, 0.358, 0.5530353108891188]], {0., 118.}, Center, Automatic], InsetBox[ StyleBox["\<\"primes\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[0.6361597700445392, 0.7170733077827265, 0.]], {-104., 12.}, Center, Automatic], InsetBox[ StyleBox["\<\"alphabet\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.6319174318193065, 0.38429816477207124`, 0.7077064204517338]], {-50., 105.}, Center, Automatic], InsetBox[ StyleBox["\<\"Press\"\>", StripOnInput->False, FontSize->Scaled[0.05665459273706697], FontColor->RGBColor[ 0.9728288904374106, 0.621644452187053, 0.07336199581899142]], {61., -102.}, Center, Automatic], InsetBox[ StyleBox["\<\"classification\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.8335801463353031, 0.3487839707329394, 0.3481997561078282]], {66., 106.}, Center, Automatic], InsetBox[ StyleBox["\<\"2010-01-07\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.8781534541180211, 0.4921023027453475, 0.04333810870621905]], {-79., -96.}, Center, Automatic], InsetBox[ StyleBox["\<\"analyzed\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[0.7175796237092107, 0.7261199581899123, 0.]], {-53., -110.}, Center, Automatic], InsetBox[ StyleBox["\<\"Forms\"\>", StripOnInput->False, FontSize->Scaled[0.05108200984489644], FontColor->RGBColor[ 0.28026441037696703`, 0.715, 0.4292089322474965]], {52., -117.}, Center, Automatic], InsetBox[ StyleBox["\<\"smallest\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[0.428777913273419, 0.5052332520359486, 0.85]], {-57., 116.}, Center, Automatic], InsetBox[ StyleBox["\<\"depends\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[0.7658565873730018, 0.358, 0.4582975578876895]], {51., 118.}, Center, Automatic], InsetBox[ StyleBox["\<\"complex\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.922066817647527, 0.5213778784316846, 0.08286013588277422]], {-93., 98.}, Center, Automatic], InsetBox[ StyleBox["\<\"different\"\>", StripOnInput->False, FontSize->Scaled[0.045509426952725925`], FontColor->RGBColor[0.5407932311309059, 0.715, 0.09762679674248334]], {-98., -108.}, Center, Automatic], InsetBox[ StyleBox["\<\"structure\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.596786740995709, 0.404791067752503, 0.7955331475107271]], {100., -114.}, Center, Automatic], InsetBox[ StyleBox["\<\"introduction\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.6453361616656581, 0.37647057236169945`, 0.6741595958358548]], {-53., -120.}, Center, Automatic], InsetBox[ StyleBox["\<\"theory\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.8607200975568693, 0.34335598048862614`, 0.30296650407188447`]], {-106., 24.}, Center, Automatic], InsetBox[ StyleBox["\<\"tradition\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.9492067688690977, 0.5394711792460651, 0.10728609198218791`]], {96., 117.}, Center, Automatic], InsetBox[ StyleBox["\<\"concept\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.5788038738141875, 0.715, 0.049249615145579635`]], {104., -88.}, Center, Automatic], InsetBox[ StyleBox["\<\"single\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.9038177251280404, 0.3492734123079395, 0.18454431282010084`]], {107., 95.}, Center, Automatic], InsetBox[ StyleBox["\<\"inflectional\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.2198892179497479, 0.6590886256402017, 0.6788670615396974]], {0., 128.}, Center, Automatic], InsetBox[ StyleBox["\<\"fascination\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.9603267270590103, 0.5591336352950514, 0.10711783694067224`]], {2., -122.}, Center, Automatic], InsetBox[ StyleBox["\<\"number\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.9052934053395919, 0.510195603559728, 0.06776406480563275]], {-50., 128.}, Center, Automatic], InsetBox[ StyleBox["\<\"introduced\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.8949268664259606, 0.5032845776173072, 0.05843417978336459]], {-109., 61.}, Center, Automatic], InsetBox[ StyleBox["\<\"chapter\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.31827505306025683`, 0.715, 0.3808317506505822]], {-109., 35.}, Center, Automatic], InsetBox[ StyleBox["\<\"century\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.969373377466199, 0.6043668873309952, 0.08269188084126262]], {115., -70.}, Center, Automatic], InsetBox[ StyleBox["\<\"characters\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.845266573755366, 0.437100139366951, 0.03816643438841502]], {-35., -130.}, Center, Automatic], InsetBox[ StyleBox["\<\"Oxford\"\>", StripOnInput->False, FontSize->Scaled[0.045509426952725925`], FontColor->RGBColor[ 0.47401116530937026`, 0.47809330081437784`, 0.85]], {102., -100.}, Center, Automatic], InsetBox[ StyleBox["\<\"determine\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.15725938678540247`, 0.715, 0.5857607804549424]], {52., 128.}, Center, Automatic], InsetBox[ StyleBox["\<\"ways\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.9930578157165594, 0.7227890785827968, 0.01874389756528967]], {-115., -83.}, Center, Automatic], InsetBox[ StyleBox["\<\"delimit\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.37977756485605163`, 0.715, 0.3025558265468435]], {-101., 109.}, Center, Automatic], InsetBox[ StyleBox["\<\"Grammar\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[0.529922539669161, 0.44454647619850335`, 0.85]], {51., -129.}, Center, Automatic], InsetBox[ StyleBox["\<\"confusion\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.8926354502560807, 0.366046824615879, 0.15658862564020168`]], {-82., -130.}, Center, Automatic], InsetBox[ StyleBox["\<\"history\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.9986489531525362, 0.7507447657626809, 0.0036478264881522893`]], {90., -125.}, Center, Automatic], InsetBox[ StyleBox["\<\"sound\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.9784200278733908, 0.649600139366954, 0.058265924741844846`]], {-91., 126.}, Center, Automatic], InsetBox[ StyleBox["\<\"affixes\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[0.7678998606330495, 0.7317110956258943, 0.]], {94., 129.}, Center, Automatic], InsetBox[ StyleBox["\<\"added\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.6184987019729621, 0.39212575718243875`, 0.7412532450675947]], {8., -133.}, Center, Automatic], InsetBox[ StyleBox["\<\"e.g.\"\>", StripOnInput->False, FontSize->Scaled[0.045509426952725925`], FontColor->RGBColor[ 0.8857244243136628, 0.3764133635295058, 0.1393110607841571]], {124., -22.}, Center, Automatic], InsetBox[ StyleBox["\<\"Goddard\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.8633598745697435, 0.40996018814538476`, 0.08339968642435877]], {0., 138.}, Center, Automatic], InsetBox[ StyleBox["\<\"called\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.35558897405758294`, 0.5505288207539337, 0.8417067688690995]], {128., 46.}, Center, Automatic], InsetBox[ StyleBox["\<\"Chinese\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.5750747800184488, 0.4174563783225715, 0.8498130499538777]], {-112., 88.}, Center, Automatic], InsetBox[ StyleBox["\<\"root\"\>", StripOnInput->False, FontSize->Scaled[0.05108200984489644], FontColor->RGBColor[0.8996399512215667, 0.7463488834690629, 0.]], {123., -36.}, Center, Automatic], InsetBox[ StyleBox["\<\"verbs\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[0.5019668524892619, 0.46131988850644284`, 0.85]], {125., 66.}, Center, Automatic], InsetBox[ StyleBox["\<\"stand\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.8342400905885153, 0.4628267270590103, 0.0038160815296638794`]], {-126., -67.}, Center, Automatic], InsetBox[ StyleBox["\<\"make\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[0.9810598048862722, 0.7553955338762525, 0.]], {37., 139.}, Center, Automatic], InsetBox[ StyleBox["\<\"David\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[0.7132613816472081, 0.358, 0.5392132590042952]], {-127., 72.}, Center, Automatic], InsetBox[ StyleBox["\<\"given\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.4177882075393331, 0.715, 0.25417864494993975`]], {130., 11.}, Center, Automatic], InsetBox[ StyleBox["\<\"Classes\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[0.9307395679624266, 0.7498043964402695, 0.]], {-28., -140.}, Center, Automatic], InsetBox[ StyleBox["\<\"suffix\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[0.8493197142977551, 0.7407577460330839, 0.]], {123., 78.}, Center, Automatic], InsetBox[ StyleBox["\<\"John\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[0.5472001045252132, 0.43417993728487203`, 0.85]], {-62., 138.}, Center, Automatic], InsetBox[ StyleBox["\<\"consist\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[0.4567336004533182, 0.4884598397280091, 0.85]], {42., -139.}, Center, Automatic], InsetBox[ StyleBox["\<\"rock\"\>", StripOnInput->False, FontSize->Scaled[0.045509426952725925`], FontColor->RGBColor[0.7748409210981391, 0.358, 0.4444755060028629]], {129., 22.}, Center, Automatic], InsetBox[ StyleBox["\<\"units\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.8745421494417032, 0.39318677583744527`, 0.11135537360425793`]], {-131., -27.}, Center, Automatic], InsetBox[ StyleBox["\<\"certain\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[0.7277983389807635, 0.358, 0.5168487092603637]], {-62., -140.}, Center, Automatic], InsetBox[ StyleBox["\<\"koalas\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[0.6672593867853922, 0.7205288207539324, 0.]], {69., 140.}, Center, Automatic], InsetBox[ StyleBox["\<\"Free\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.8564488486273256, 0.42032672705901153`, 0.06612212156831418]], {-130., -39.}, Center, Automatic], InsetBox[ StyleBox["\<\"ed\"\>", StripOnInput->False, FontSize->Scaled[0.05665459273706697], FontColor->RGBColor[0.915, 0.3325, 0.2125]], {-132., -4.}, Center, Automatic], InsetBox[ StyleBox["\<\"ideas\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.8064401951137368, 0.3542119609772526, 0.39343300814377197`]], {-131., 45.}, Center, Automatic], InsetBox[ StyleBox["\<\"Anna\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.9046334610863751, 0.334573307782725, 0.22977756485604156`]], {-123., -94.}, Center, Automatic], InsetBox[ StyleBox["\<\"told\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.3103557220216354, 0.5867154223826917, 0.7874268664259625]], {-132., -51.}, Center, Automatic], InsetBox[ StyleBox["\<\"2005\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.19193353076984873`, 0.681453175384121, 0.6453202369238185]], {-99., -120.}, Center, Automatic], InsetBox[ StyleBox["\<\"2003\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.7896667828057927, 0.3575666434388414, 0.4213886953236787]], {73., -139.}, Center, Automatic], InsetBox[ StyleBox["\<\"unit\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.47929071933511125`, 0.715, 0.1759027208462221]], {129., -59.}, Center, Automatic], InsetBox[ StyleBox["\<\"extra\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.3383114092015346, 0.5643508726387724, 0.8209736910418415]], {-33., 139.}, Center, Automatic], InsetBox[ StyleBox["\<\"Core\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.9840111653093676, 0.677555826546838, 0.04316985366470745]], {-125., 98.}, Center, Automatic], InsetBox[ StyleBox["\<\"5th\"\>", StripOnInput->False, FontSize->Scaled[0.0399368440605554], FontColor->RGBColor[ 0.8613800418100862, 0.48092002787339083`, 0.02824203762907758]], {133., 0.}, Center, Automatic], InsetBox[ StyleBox["\<\"Cliff\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.26512246998569167`, 0.6229020240114467, 0.73314696398283]], {-133., 17.}, Center, Automatic], InsetBox[ StyleBox["\<\"due\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[ 0.6102054708420535, 0.39696347534213544`, 0.7619863228948663]], {134., -11.}, Center, Automatic], InsetBox[ StyleBox["\<\"BC\"\>", StripOnInput->False, FontSize->Scaled[0.03436426116838488], FontColor->RGBColor[0.38354466123747527`, 0.5323732032575149, 0.85]], {-70., 61.}, Center, Automatic]}, DefaultBaseStyle->{"Graphics", FontFamily -> "Helvetica"}, Method->{ "DefaultBoundaryStyle" -> Automatic, "DefaultGraphicsInteraction" -> { "Version" -> 1.2, "TrackMousePosition" -> {True, False}, "Effects" -> { "Highlight" -> {"ratio" -> 2}, "HighlightPoint" -> {"ratio" -> 2}, "Droplines" -> { "freeformCursorMode" -> True, "placement" -> {"x" -> "All", "y" -> "None"}}}}, "DefaultPlotStyle" -> Automatic}, PlotRange->{{-145.5, 145.5}, {-145.5, 145.5}}], Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], Graphics[{ Style[{ Inset[ Style[ "word", FontSize -> Scaled[0.24054982817869416`], FontColor -> RGBColor[0.368417, 0.506779, 0.709798]], {0, 0}, Center, Automatic], Inset[ Style[ "words", FontSize -> Scaled[0.19596916504132997`], FontColor -> RGBColor[0.880722, 0.611041, 0.142051]], {-14., 36.}, Center, Automatic], Inset[ Style[ "language", FontSize -> Scaled[0.10123525587443113`], FontColor -> RGBColor[0.560181, 0.691569, 0.194885]], {4., -33.}, Center, Automatic], Inset[ Style[ "languages", FontSize -> Scaled[0.0900900900900901], FontColor -> RGBColor[0.922526, 0.385626, 0.209179]], {0., -57.}, Center, Automatic], Inset[ Style[ "meaning", FontSize -> Scaled[0.07894492430574904], FontColor -> RGBColor[0.528488, 0.470624, 0.701351]], {-20., 63.}, Center, Automatic], Inset[ Style[ "Cambridge", FontSize -> Scaled[0.062227175629237484`], FontColor -> RGBColor[0.571589, 0.586483, 0.]], {0., 81.}, Center, Automatic], Inset[ Style[ "example", FontSize -> Scaled[0.07337234141357853], FontColor -> RGBColor[0.772079, 0.431554, 0.102387]], {-10., -79.}, Center, Automatic], Inset[ Style[ "Orthography", FontSize -> Scaled[0.05108200984489644], FontColor -> RGBColor[ 0.5833680111493557, 0.4126186601628758, 0.8290799721266107]], {72., 56.}, Center, Automatic], Inset[ Style[ "English", FontSize -> Scaled[0.067799758521408], FontColor -> RGBColor[0.363898, 0.618501, 0.782349]], {-86., -34.}, Center, Automatic], Inset[ Style[ "morphemes", FontSize -> Scaled[0.05108200984489644], FontColor -> RGBColor[ 0.838355547812947, 0.44746667828057946`, 0.0208888695323676]], {0., 96.}, Center, Automatic], Inset[ Style[ "boundaries", FontSize -> Scaled[0.062227175629237484`], FontColor -> RGBColor[0.647624, 0.37816, 0.614037]], {-5., -97.}, Center, Automatic], Inset[ Style[ "University", FontSize -> Scaled[0.05108200984489644], FontColor -> RGBColor[ 0.28240003484173815`, 0.6090799721266095, 0.7538800418100857]], { 64., -75.}, Center, Automatic], Inset[ Style[ "Philosophy", FontSize -> Scaled[0.045509426952725925`], FontColor -> RGBColor[ 0.9874666782805795, 0.6948333914028977, 0.033839968642435214`]], { 77., 69.}, Center, Automatic], Inset[ Style[ "Semantic", FontSize -> Scaled[0.05665459273706697], FontColor -> RGBColor[0.736782672705901, 0.358, 0.5030266573755369]], {-77., 76.}, Center, Automatic], Inset[ Style[ "morpheme", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.8168067340273636, 0.3521386531945273, 0.3761554432877274]], {92., 36.}, Center, Automatic], Inset[ Style[ "Features", FontSize -> Scaled[0.05665459273706697], FontColor -> RGBColor[ 0.40082222609352647`, 0.5220066643438841, 0.85]], {-90., -54.}, Center, Automatic], Inset[ Style[ "Encyclopedia", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.7989994773739094, 0.735166608597101, 0.]], {92., -50.}, Center, Automatic], Inset[ Style[ "speaker", FontSize -> Scaled[0.045509426952725925`], FontColor -> RGBColor[ 0.16397784358994957`, 0.7038177251280403, 0.6117734123079395]], { 88., -29.}, Center, Automatic], Inset[ Style[ "distinguished", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.8510135028964549, 0.47400900193096995`, 0.018912152606809424`]], { 4., 108.}, Center, Automatic], Inset[ Style[ "boundary", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.8878600487784333, 0.33792799024431336`, 0.2577332520359445]], {97., 0.}, Center, Automatic], Inset[ Style[ "sentence", FontSize -> Scaled[0.05108200984489644], FontColor -> RGBColor[ 0.8439466852489265, 0.3467106629502147, 0.3309221912517893]], {-79., -72.}, Center, Automatic], Inset[ Style[ "particular", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.6536293927965667, 0.37163285420200276`, 0.6534265180085832]], {-96., -15.}, Center, Automatic], Inset[ Style[ "considered", FontSize -> Scaled[0.045509426952725925`], FontColor -> RGBColor[ 0.6753413537738198, 0.3589675436319385, 0.5991466155654507]], {76., 81.}, Center, Automatic], Inset[ Style[ "ISBN", FontSize -> Scaled[0.067799758521408], FontColor -> RGBColor[1, 0.75, 0]], {93., 15.}, Center, Automatic], Inset[ Style[ "expressions", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.8774935098648088, 0.34000129802703827`, 0.2750108168919853]], {-91., 53.}, Center, Automatic], Inset[ Style[ "language's", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.9107287510704583, 0.33890687339431275`, 0.20182187767614543`]], { 97., -13.}, Center, Automatic], Inset[ Style[ "constitutes", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.9637822400302223, 0.5764112001511111, 0.0977879519184]], { 0., -111.}, Center, Automatic], Inset[ Style[ "typically", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.6897400905885174, 0.358, 0.5753998606330502]], {-98., 0.}, Center, Automatic], Inset[ Style[ "multiple", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.23716678280579248`, 0.645266573755366, 0.699600139366951]], { 63., -88.}, Center, Automatic], Inset[ Style[ "compound", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.6670481226429111, 0.3638052617916352, 0.6198796933927223]], { 91., -60.}, Center, Automatic], Inset[ Style[ "spoken", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.2187618985811806, 0.715, 0.5074848563512248]], {-65., 89.}, Center, Automatic], Inset[ Style[ "spaces", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.7513196300394465, 0.358, 0.48066210763162087`]], {-70., -83.}, Center, Automatic], Inset[ Style[ "written", FontSize -> Scaled[0.05108200984489644], FontColor -> RGBColor[ 0.9324333565611593, 0.5282889043741062, 0.0921900209050434]], {63., 94.}, Center, Automatic], Inset[ Style[ "fundamental", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.7042770479220728, 0.358, 0.5530353108891188]], {0., 118.}, Center, Automatic], Inset[ Style[ "primes", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.6361597700445392, 0.7170733077827265, 0.]], {-104., 12.}, Center, Automatic], Inset[ Style[ "alphabet", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.6319174318193065, 0.38429816477207124`, 0.7077064204517338]], {-50., 105.}, Center, Automatic], Inset[ Style[ "Press", FontSize -> Scaled[0.05665459273706697], FontColor -> RGBColor[ 0.9728288904374106, 0.621644452187053, 0.07336199581899142]], { 61., -102.}, Center, Automatic], Inset[ Style[ "classification", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.8335801463353031, 0.3487839707329394, 0.3481997561078282]], {66., 106.}, Center, Automatic], Inset[ Style[ "2010-01-07", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.8781534541180211, 0.4921023027453475, 0.04333810870621905]], {-79., -96.}, Center, Automatic], Inset[ Style[ "analyzed", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.7175796237092107, 0.7261199581899123, 0.]], {-53., -110.}, Center, Automatic], Inset[ Style[ "Forms", FontSize -> Scaled[0.05108200984489644], FontColor -> RGBColor[0.28026441037696703`, 0.715, 0.4292089322474965]], { 52., -117.}, Center, Automatic], Inset[ Style[ "smallest", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.428777913273419, 0.5052332520359486, 0.85]], {-57., 116.}, Center, Automatic], Inset[ Style[ "depends", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.7658565873730018, 0.358, 0.4582975578876895]], {51., 118.}, Center, Automatic], Inset[ Style[ "complex", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.922066817647527, 0.5213778784316846, 0.08286013588277422]], {-93., 98.}, Center, Automatic], Inset[ Style[ "different", FontSize -> Scaled[0.045509426952725925`], FontColor -> RGBColor[ 0.5407932311309059, 0.715, 0.09762679674248334]], {-98., -108.}, Center, Automatic], Inset[ Style[ "structure", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.596786740995709, 0.404791067752503, 0.7955331475107271]], { 100., -114.}, Center, Automatic], Inset[ Style[ "introduction", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.6453361616656581, 0.37647057236169945`, 0.6741595958358548]], {-53., -120.}, Center, Automatic], Inset[ Style[ "theory", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.8607200975568693, 0.34335598048862614`, 0.30296650407188447`]], {-106., 24.}, Center, Automatic], Inset[ Style[ "tradition", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.9492067688690977, 0.5394711792460651, 0.10728609198218791`]], {96., 117.}, Center, Automatic], Inset[ Style[ "concept", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.5788038738141875, 0.715, 0.049249615145579635`]], { 104., -88.}, Center, Automatic], Inset[ Style[ "single", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.9038177251280404, 0.3492734123079395, 0.18454431282010084`]], { 107., 95.}, Center, Automatic], Inset[ Style[ "inflectional", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.2198892179497479, 0.6590886256402017, 0.6788670615396974]], {0., 128.}, Center, Automatic], Inset[ Style[ "fascination", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.9603267270590103, 0.5591336352950514, 0.10711783694067224`]], { 2., -122.}, Center, Automatic], Inset[ Style[ "number", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.9052934053395919, 0.510195603559728, 0.06776406480563275]], {-50., 128.}, Center, Automatic], Inset[ Style[ "introduced", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.8949268664259606, 0.5032845776173072, 0.05843417978336459]], {-109., 61.}, Center, Automatic], Inset[ Style[ "chapter", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.31827505306025683`, 0.715, 0.3808317506505822]], {-109., 35.}, Center, Automatic], Inset[ Style[ "century", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.969373377466199, 0.6043668873309952, 0.08269188084126262]], { 115., -70.}, Center, Automatic], Inset[ Style[ "characters", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.845266573755366, 0.437100139366951, 0.03816643438841502]], {-35., -130.}, Center, Automatic], Inset[ Style[ "Oxford", FontSize -> Scaled[0.045509426952725925`], FontColor -> RGBColor[0.47401116530937026`, 0.47809330081437784`, 0.85]], { 102., -100.}, Center, Automatic], Inset[ Style[ "determine", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.15725938678540247`, 0.715, 0.5857607804549424]], {52., 128.}, Center, Automatic], Inset[ Style[ "ways", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.9930578157165594, 0.7227890785827968, 0.01874389756528967]], {-115., -83.}, Center, Automatic], Inset[ Style[ "delimit", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.37977756485605163`, 0.715, 0.3025558265468435]], {-101., 109.}, Center, Automatic], Inset[ Style[ "Grammar", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.529922539669161, 0.44454647619850335`, 0.85]], { 51., -129.}, Center, Automatic], Inset[ Style[ "confusion", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.8926354502560807, 0.366046824615879, 0.15658862564020168`]], {-82., -130.}, Center, Automatic], Inset[ Style[ "history", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.9986489531525362, 0.7507447657626809, 0.0036478264881522893`]], { 90., -125.}, Center, Automatic], Inset[ Style[ "sound", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.9784200278733908, 0.649600139366954, 0.058265924741844846`]], {-91., 126.}, Center, Automatic], Inset[ Style[ "affixes", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.7678998606330495, 0.7317110956258943, 0.]], {94., 129.}, Center, Automatic], Inset[ Style[ "added", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.6184987019729621, 0.39212575718243875`, 0.7412532450675947]], { 8., -133.}, Center, Automatic], Inset[ Style[ "e.g.", FontSize -> Scaled[0.045509426952725925`], FontColor -> RGBColor[ 0.8857244243136628, 0.3764133635295058, 0.1393110607841571]], { 124., -22.}, Center, Automatic], Inset[ Style[ "Goddard", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.8633598745697435, 0.40996018814538476`, 0.08339968642435877]], {0., 138.}, Center, Automatic], Inset[ Style[ "called", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.35558897405758294`, 0.5505288207539337, 0.8417067688690995]], { 128., 46.}, Center, Automatic], Inset[ Style[ "Chinese", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.5750747800184488, 0.4174563783225715, 0.8498130499538777]], {-112., 88.}, Center, Automatic], Inset[ Style[ "root", FontSize -> Scaled[0.05108200984489644], FontColor -> RGBColor[0.8996399512215667, 0.7463488834690629, 0.]], {123., -36.}, Center, Automatic], Inset[ Style[ "verbs", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.5019668524892619, 0.46131988850644284`, 0.85]], {125., 66.}, Center, Automatic], Inset[ Style[ "stand", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.8342400905885153, 0.4628267270590103, 0.0038160815296638794`]], {-126., -67.}, Center, Automatic], Inset[ Style[ "make", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.9810598048862722, 0.7553955338762525, 0.]], {37., 139.}, Center, Automatic], Inset[ Style[ "David", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.7132613816472081, 0.358, 0.5392132590042952]], {-127., 72.}, Center, Automatic], Inset[ Style[ "given", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.4177882075393331, 0.715, 0.25417864494993975`]], {130., 11.}, Center, Automatic], Inset[ Style[ "Classes", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.9307395679624266, 0.7498043964402695, 0.]], {-28., -140.}, Center, Automatic], Inset[ Style[ "suffix", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.8493197142977551, 0.7407577460330839, 0.]], {123., 78.}, Center, Automatic], Inset[ Style[ "John", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.5472001045252132, 0.43417993728487203`, 0.85]], {-62., 138.}, Center, Automatic], Inset[ Style[ "consist", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.4567336004533182, 0.4884598397280091, 0.85]], {42., -139.}, Center, Automatic], Inset[ Style[ "rock", FontSize -> Scaled[0.045509426952725925`], FontColor -> RGBColor[0.7748409210981391, 0.358, 0.4444755060028629]], {129., 22.}, Center, Automatic], Inset[ Style[ "units", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.8745421494417032, 0.39318677583744527`, 0.11135537360425793`]], {-131., -27.}, Center, Automatic], Inset[ Style[ "certain", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.7277983389807635, 0.358, 0.5168487092603637]], {-62., -140.}, Center, Automatic], Inset[ Style[ "koalas", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.6672593867853922, 0.7205288207539324, 0.]], {69., 140.}, Center, Automatic], Inset[ Style[ "Free", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.8564488486273256, 0.42032672705901153`, 0.06612212156831418]], {-130., -39.}, Center, Automatic], Inset[ Style[ "ed", FontSize -> Scaled[0.05665459273706697], FontColor -> RGBColor[0.915, 0.3325, 0.2125]], {-132., -4.}, Center, Automatic], Inset[ Style[ "ideas", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.8064401951137368, 0.3542119609772526, 0.39343300814377197`]], {-131., 45.}, Center, Automatic], Inset[ Style[ "Anna", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.9046334610863751, 0.334573307782725, 0.22977756485604156`]], {-123., -94.}, Center, Automatic], Inset[ Style[ "told", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.3103557220216354, 0.5867154223826917, 0.7874268664259625]], {-132., -51.}, Center, Automatic], Inset[ Style[ "2005", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.19193353076984873`, 0.681453175384121, 0.6453202369238185]], {-99., -120.}, Center, Automatic], Inset[ Style[ "2003", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.7896667828057927, 0.3575666434388414, 0.4213886953236787]], { 73., -139.}, Center, Automatic], Inset[ Style[ "unit", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[0.47929071933511125`, 0.715, 0.1759027208462221]], { 129., -59.}, Center, Automatic], Inset[ Style[ "extra", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.3383114092015346, 0.5643508726387724, 0.8209736910418415]], {-33., 139.}, Center, Automatic], Inset[ Style[ "Core", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.9840111653093676, 0.677555826546838, 0.04316985366470745]], {-125., 98.}, Center, Automatic], Inset[ Style[ "5th", FontSize -> Scaled[0.0399368440605554], FontColor -> RGBColor[ 0.8613800418100862, 0.48092002787339083`, 0.02824203762907758]], { 133., 0.}, Center, Automatic], Inset[ Style[ "Cliff", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.26512246998569167`, 0.6229020240114467, 0.73314696398283]], {-133., 17.}, Center, Automatic], Inset[ Style[ "due", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[ 0.6102054708420535, 0.39696347534213544`, 0.7619863228948663]], { 134., -11.}, Center, Automatic], Inset[ Style[ "BC", FontSize -> Scaled[0.03436426116838488], FontColor -> RGBColor[0.38354466123747527`, 0.5323732032575149, 0.85]], {-70., 61.}, Center, Automatic]}, {}]}, PlotRange -> {{-145.5, 145.5}, {-145.5, 145.5}}, DefaultBaseStyle -> {"Graphics", FontFamily -> "Helvetica"}, Method -> { "DefaultBoundaryStyle" -> Automatic, "DefaultGraphicsInteraction" -> { "Version" -> 1.2, "TrackMousePosition" -> {True, False}, "Effects" -> { "Highlight" -> {"ratio" -> 2}, "HighlightPoint" -> {"ratio" -> 2}, "Droplines" -> { "freeformCursorMode" -> True, "placement" -> {"x" -> "All", "y" -> "None"}}}}, "DefaultPlotStyle" -> Automatic}]]], "Output", CellChangeTimes->{3.7560798874872475`*^9}, CellLabel->"Out[1]=", CellID->619393685] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell["", "PageBreak", PageBreakBelow->True, CellID->199224021], Cell["How neat is that?", "Text", CellChangeTimes->{3.7560798872442555`*^9}, CellID->225856413], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"BirdSay", "[", "\"\\"", "]"}]], "Input", CellChangeTimes->{3.7560798922120943`*^9}, CellLabel->"In[2]:=", CellID->19164468], Cell[BoxData[ InterpretationBox[ PanelBox["\<\"That's pretty neat!\"\>", Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], "That's pretty neat!"]], "Output", CellChangeTimes->{3.7560798933580313`*^9}, CellLabel->"Out[2]=", CellID->823842285] }, Open ]] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell["Scope", "Subsection", CellID->964056545], Cell["This bird is a nerd:", "Text", CellChangeTimes->{3.756079901435794*^9}, CellID->649685796], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"BirdSay", "[", RowBox[{ "SystemModel", "[", "\"\\"", "]"}], "]"}]], "Input", CellChangeTimes->{3.7560799052446737`*^9}, CellLabel->"In[3]:=", CellID->836153427], Cell[BoxData[ InterpretationBox[ PanelBox[ GraphicsBox[ TagBox[ TooltipBox[ DynamicModuleBox[{WSM`Typeset`PackagePrivate`p = { InsetBox[ BoxData[ FormBox[ GraphicsBox[ TagBox[ RasterBox[CompressedData[" 1:eJztmmtMW2UYx4l+MX7xEj8ao9/8pFniIpqZrIrcF6AIAxGxZJQRLiO0hEtQ UGpRiSZyKZFLcZMwudPSCS1QRrF1g2MpKwS5DWhpCetgFFogpYAPvFnTtZTL 4bSU0n+ekrcP5zzneX/nfZ/37cl5K/YGmfqch4cH7QX4Q6ZkkNLSKFmhL8OX sBRaQnxK3DW/FHpcfFyaZ+zz4PwAPuHw2W3vuOWWW64rhUJx2ik4SGtra8nJ yeaegYGBxMTE6Ojo1dXV08rKkdLpdAEBAaiNYRj0nU6nDw8PBwUFLS8vn25u jhEiAH1PSkqi0WjQd+Q/VwS8vLwSEhLkcrm5n1gClw8TURfCISDg6+tLpVKz srLGxsZMfsIJ4P6vvWWqAxKJBDhkZ2ePj4/v4CIwt2gcVxvM7cXPZ8BgWTmU gOD+7JvXFbEsjUUEe5gpKyS4735+fqZkxGJxXFwccAgMDERHWkeYfrRp3Qvw e2ap36WpzA1FgGXlUALvfVF9+Zv5V2JmLSLYw0xZIUVFRYWEhBQUFMzPz5tz IJPJ6EjrCBfoKvF/Gxa9kIxtfJI3v2NDh9YBg3E7/dZi9/D6AaDsJDQLOjo6 IiIigINarUb+A2YBjNXbfToL58EEnFnm+wHgEBkZyWQygcM5ISCTyXJycnx8 fMydfD4fxoO3t7fLE4ANAOyC4L6bxgBIr9eXlpb6+/tDeXRtAtvG7a4f2hkM hmkWwA8EFosFfa+vr99xmjqQdxxZnw7dVNRMjv8kt7bhjIHu97ndFznKOw+B APQdbnpdXZ3pXOch8OBo2peAVr50L1SorHtobRNFI3cv8cR+Ag22kJqaat53 JBgJGxuWSx6Sgwn8+2e/6DM+bgLYV322gi8/WMKXlYMJ/H2tW/ghT8rDCCeA Ww4mMHDzfm9AO+rm0FOZOm7yuDABaSsmuro7C2DZgupEIpFgD9nU1AQeWLZI e0pPTz8PBNhsNp1Oh8aPe4IGdLyqqsrlZ8ERCTDyGKqWWYvTzw8BlUrFyWuS XOkUfdwhudJlMrF/5+h3g4Rn5YQEpqenBXX84QzsiVSzrtab29aGkfCsnJAA KD8/n/Cr25JzEti3EtpJzkZgSCKTcjEXJnDvW9GNjxKDSUGBpEDGp7l3fdt/ 8y4KIPmDJ5RE/sO7sufSHaFn2+2Q3wm/ui05mMCgQCpktAtbusCk3ZisRwqG vvZye6A9UCX5J0/EzPye8Kvb0hn6dWwnucYTkpPITcBNwE3ATcBNwE3ATQA3 gc3NTb1eb7e8HCd8BIxGo1wuHxkZsfUQ/gwJH4GJiQmNRrOysoJhWFtbW0tL C3pV4ywKBwGDwTA0NASN0dFRLpfLYrHKysqYTGZfH/EP8RygoxNA72BAQ6VS wR1HbyoqlcqpqSl0QE5ODo/HQ+1xtWFZv4U7q0da474vt9hDtghcoKtK2lfM DRFobGzs7OzkcDgxMTHl5eXNzc1CobBxT7W1teHh4Q0NDRm/dr8RP3sxwzLC Ee1n7srrVMVrFAXt5hK+CMcyUp7amoBxa6f4L236rUVzQwSKi4th2BcVFYWF hRXvqbW1tbKyErUpFAqUhS+/5ryTpnw7Zc4iwhEtlf341ejJl6Imrv6ygC/C sYzR+MRg3MYxeKhU6szM7qSAiTA5OQmN9fX13NxcVBIFsjXFY/zDuLqhl5pd jvt0x4jP52dmZkIDFkT08mphYSHUAa1We/LgMNEYDMbJ49hbUPwLCgpqamqA RnV1NUwH2CHgjrawsBD1VDDFgoODTV8FAgGBaROrwcHBiooKNpstEolgcYQd Au5QsMmcm5uDGlv1rMCp01lWKicUFAFCxj9sMIqf1cljnjn19/ejNzNLSkpO Oxe33Dp3+h9eeYMd "], {{0, 57}, {86, 0}}, {0, 255}, ColorFunction -> RGBColor], BoxForm`ImageTag[ "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Exif" -> Association[ "Software" -> "Created with the Wolfram Language : www.wolfram.com"], "Comments" -> Association[ "Software" -> "Created with the Wolfram Language : www.wolfram.com", "Creation Time" -> DateObject[{2018, 11, 28, 12, 13, 2.}, "Instant", "Gregorian", -5.]]]], Selectable -> False], DefaultBaseStyle -> "ImageGraphics", ImageSizeRaw -> {86, 57}, PlotRange -> {{0, 86}, {0, 57}}], TraditionalForm]], {0, 0}, {0, 0}, {86, 57}], { RGBColor[ 0.43137254901960786`, 0.43137254901960786`, 0.43137254901960786`], InsetBox[ FormBox[ StyleBox[ "\"IdealTriacCircuit\"", FontSize -> 9, FontFamily -> "Helvetica", StripOnInput -> False], TraditionalForm], NCache[{43, Rational[-29, 2]}, {43, -14.5}], {0, 0}]}, { EdgeForm[ RGBColor[ 0.5843137254901961, 0.807843137254902, 0.9411764705882353]], FaceForm[None], RectangleBox[{-10, -25}, {95, 67}, RoundingRadius -> Offset[5]]}, InsetBox[ BoxData[ FormBox[ GraphicsBox[ TagBox[ RasterBox[CompressedData[" 1:eJzN1VlI1FEUx/FJzT3TxkooKitaaHkoIYOKjAha6MESErJwyMSgkUahlRZ6 CqJoh6CihbaHiuihoH2lImgvMtozjTKzUtP09L3c86c/k+NGD/3hM/7nD/Ob M+eee031FWbOD/N4PEXRvGTmLs4IBHKXzkjkTZa/qCDfnzdvsr84Lz8vkO4L 52GKioC0fDWqX/iJH6jAG9zFaWxFAcajB2I8erUi3/mOBtShGl/wHg9xFjtR iEnohbh25tejBpUoxWNcxC4swlT0Rfw/yP+AJziP3Qhofn8ktCHf6b+TX635 pj+PcE5sf0z9U5CKTu3IN+tr+u+s71vcF7u+27FQ/vS/Lf1xanfm5zs+4SXu 4CQ2Ih/j0FNav77BtZvefxXb+xLcwBGsxVyMQndEt5DfKH/3vVZr/yx29h+I 7b2ZnSWYieHogo6u/MYQnJ7Ua1+cdS3T2m/iONZjASaKXdvOCHPlN4TgZNdq tunLR7wSu2/NvjJzuQLZSEMKYj2uSzOC1WnNNdqTSs1+LXbPXsZhrNPazdwM RJK7N5pfozW6mWdmDqvEzmKZ1m2yr+IYNqEYWRiptcd7gi793Sbnm/6t0nor tOZ3eI57uKI934ZlyMEY9EEiIprIN7NWrlnlqlRn5IXYM+a22HPgKLZgOXzI wAB4xXVmBuU/1Xko0TqfaabZm7dwCaewDxvEzuIczR6CrohDhxD55vPXxO6V 69rfCziDE9iPzVgDP2aJPecHo5vpubjmsYn8vTiIQ+oA9mCH2NleJfbsysU0 pKOfq+7wUNmab9Zppda3Wu/NsyKx/5NmYzrGYpjY88Xs0djm6nblm32drbOQ o/fmmTnLJ2A0hoo9F5ORgKiWcl355swYIXb/pem9eTYIvcXOtVdzY1pTc1B+ kv7eZOXV90maafoQ2dZcV364fj5KRapm1+1/uX4DOnc/KA== "], {{0, 24}, { 24, 0}}, {0, 255}, ColorFunction -> RGBColor], BoxForm`ImageTag[ "Byte", ColorSpace -> "RGB", Interleaving -> True], Selectable -> False], DefaultBaseStyle -> "ImageGraphics", ImageSizeRaw -> {24, 24}, PlotRange -> {{0, 24}, {0, 24}}], TraditionalForm]], Offset[{6, -6}, Scaled[{0, 1}]], Scaled[{0, 1}], {24, 24}]}, WSM`Typeset`PackagePrivate`appearanceState = "Minimal", WSM`Typeset`PackagePrivate`expandedeval = False, WSM`Typeset`PackagePrivate`expandedprimitives, WSM`Typeset`PackagePrivate`expandedopt, WSM`Typeset`PackagePrivate`expandedsize = {106, 93}, WSM`Typeset`PackagePrivate`expandedrange = {{-10, 96}, {-26, 67}}}, DynamicWrapperBox[ DynamicBox[{WSM`Typeset`PackagePrivate`p, Which[ And[ "normal" === "normal", WSM`Typeset`PackagePrivate`appearanceState === "Minimal"], InsetBox[ BoxData[ FormBox[ ButtonBox[ DynamicBox[ FEPrivate`FrontEndResource[ "FEBitmaps", "SquarePlusIconMedium"]], ButtonFunction :> ( If[WSM`Typeset`PackagePrivate`expandedeval === False, If[ TrueQ[WSMLink`Private`$WSMLinkIsLoaded], WSM`Typeset`PackagePrivate`appearanceState = "Eval"; Module[{ WSM`Typeset`PackagePrivate`cellobj$, WSM`Typeset`PackagePrivate`cellEditDup$}, If[ MathLink`CallFrontEnd[ FrontEnd`BoxReferenceFind[ FE`BoxReference[ EvaluationBox[], { FE`Parent["6a3fff13-4a1c-4f20-a1a7-215c449d45d3"]}]]], WSM`Typeset`PackagePrivate`cellobj$ = EvaluationCell[]; WSM`Typeset`PackagePrivate`cellEditDup$ = CurrentValue[ WSM`Typeset`PackagePrivate`cellobj$, CellEditDuplicate]; If[WSM`Typeset`PackagePrivate`cellEditDup$, CurrentValue[ WSM`Typeset`PackagePrivate`cellobj$, CellEditDuplicate] = False]; CurrentValue[ FrontEnd`SelectionObject, { GraphicsBoxOptions, ImageSize}] = Dynamic[ WSM`Typeset`PackagePrivate`expandedsize, TrackedSymbols :> { WSM`Typeset`PackagePrivate`expandedeval}]; CurrentValue[ FrontEnd`SelectionObject, { GraphicsBoxOptions, PlotRange}] = Dynamic[ WSM`Typeset`PackagePrivate`expandedrange, TrackedSymbols :> { WSM`Typeset`PackagePrivate`expandedeval}]; If[WSM`Typeset`PackagePrivate`cellEditDup$, CurrentValue[ WSM`Typeset`PackagePrivate`cellobj$, CellEditDuplicate] = True]; Null]]; Null]; Null, WSM`Typeset`PackagePrivate`appearanceState = "Expanded"; Module[{ WSM`Typeset`PackagePrivate`cellobj$, WSM`Typeset`PackagePrivate`cellEditDup$}, If[ MathLink`CallFrontEnd[ FrontEnd`BoxReferenceFind[ FE`BoxReference[ EvaluationBox[], { FE`Parent["6a3fff13-4a1c-4f20-a1a7-215c449d45d3"]}]]], WSM`Typeset`PackagePrivate`cellobj$ = EvaluationCell[]; WSM`Typeset`PackagePrivate`cellEditDup$ = CurrentValue[ WSM`Typeset`PackagePrivate`cellobj$, CellEditDuplicate]; If[WSM`Typeset`PackagePrivate`cellEditDup$, CurrentValue[ WSM`Typeset`PackagePrivate`cellobj$, CellEditDuplicate] = False]; CurrentValue[ FrontEnd`SelectionObject, { GraphicsBoxOptions, ImageSize}] = WSM`Typeset`PackagePrivate`expandedsize; CurrentValue[ FrontEnd`SelectionObject, { GraphicsBoxOptions, PlotRange}] = WSM`Typeset`PackagePrivate`expandedrange; If[WSM`Typeset`PackagePrivate`cellEditDup$, CurrentValue[ WSM`Typeset`PackagePrivate`cellobj$, CellEditDuplicate] = True]; Null]]; Null]; Null), Appearance -> None, ContentPadding -> False, ImageSize -> {Automatic, Automatic}, Evaluator -> Automatic, Method -> "Preemptive"], TraditionalForm]], Offset[{6, -6}, Scaled[{0, 1}]], Scaled[{0, 1}]], And[ "normal" === "normal", WSM`Typeset`PackagePrivate`appearanceState === "Expanded"], InsetBox[ BoxData[ FormBox[ ButtonBox[ DynamicBox[ FEPrivate`FrontEndResource[ "FEBitmaps", "SquareMinusIconMedium"]], ButtonFunction :> ( WSM`Typeset`PackagePrivate`appearanceState = "Minimal"; Module[{ WSM`Typeset`PackagePrivate`cellobj$, WSM`Typeset`PackagePrivate`cellEditDup$}, If[ MathLink`CallFrontEnd[ FrontEnd`BoxReferenceFind[ FE`BoxReference[ EvaluationBox[], { FE`Parent["6a3fff13-4a1c-4f20-a1a7-215c449d45d3"]}]]], WSM`Typeset`PackagePrivate`cellobj$ = EvaluationCell[]; WSM`Typeset`PackagePrivate`cellEditDup$ = CurrentValue[ WSM`Typeset`PackagePrivate`cellobj$, CellEditDuplicate]; If[WSM`Typeset`PackagePrivate`cellEditDup$, CurrentValue[ WSM`Typeset`PackagePrivate`cellobj$, CellEditDuplicate] = False]; CurrentValue[ FrontEnd`SelectionObject, { GraphicsBoxOptions, ImageSize}] = {106, 93}; CurrentValue[ FrontEnd`SelectionObject, { GraphicsBoxOptions, PlotRange}] = {{-10, 96}, {-26, 67}}; If[ WSM`Typeset`PackagePrivate`cellEditDup$, CurrentValue[ WSM`Typeset`PackagePrivate`cellobj$, CellEditDuplicate] = True]; Null]]; Null), Appearance -> None, ContentPadding -> False, ImageSize -> {Automatic, Automatic}, Evaluator -> Automatic, Method -> "Preemptive"], TraditionalForm]], Offset[{10, -10}, Scaled[{0, 1}]]], True, {}]}, ImageSizeCache->{{-0.5, 105.5}, {-50.5, 42.5}}, TrackedSymbols:>{WSM`Typeset`PackagePrivate`p}], Which[WSM`Typeset`PackagePrivate`appearanceState === "Minimal", WSM`Typeset`PackagePrivate`p = { InsetBox[ BoxData[ FormBox[ GraphicsBox[ TagBox[ RasterBox[CompressedData[" 1:eJztmmtMW2UYx4l+MX7xEj8ao9/8pFniIpqZrIrcF6AIAxGxZJQRLiO0hEtQ UGpRiSZyKZFLcZMwudPSCS1QRrF1g2MpKwS5DWhpCetgFFogpYAPvFnTtZTL 4bSU0n+ekrcP5zzneX/nfZ/37cl5K/YGmfqch4cH7QX4Q6ZkkNLSKFmhL8OX sBRaQnxK3DW/FHpcfFyaZ+zz4PwAPuHw2W3vuOWWW64rhUJx2ik4SGtra8nJ yeaegYGBxMTE6Ojo1dXV08rKkdLpdAEBAaiNYRj0nU6nDw8PBwUFLS8vn25u jhEiAH1PSkqi0WjQd+Q/VwS8vLwSEhLkcrm5n1gClw8TURfCISDg6+tLpVKz srLGxsZMfsIJ4P6vvWWqAxKJBDhkZ2ePj4/v4CIwt2gcVxvM7cXPZ8BgWTmU gOD+7JvXFbEsjUUEe5gpKyS4735+fqZkxGJxXFwccAgMDERHWkeYfrRp3Qvw e2ap36WpzA1FgGXlUALvfVF9+Zv5V2JmLSLYw0xZIUVFRYWEhBQUFMzPz5tz IJPJ6EjrCBfoKvF/Gxa9kIxtfJI3v2NDh9YBg3E7/dZi9/D6AaDsJDQLOjo6 IiIigINarUb+A2YBjNXbfToL58EEnFnm+wHgEBkZyWQygcM5ISCTyXJycnx8 fMydfD4fxoO3t7fLE4ANAOyC4L6bxgBIr9eXlpb6+/tDeXRtAtvG7a4f2hkM hmkWwA8EFosFfa+vr99xmjqQdxxZnw7dVNRMjv8kt7bhjIHu97ndFznKOw+B APQdbnpdXZ3pXOch8OBo2peAVr50L1SorHtobRNFI3cv8cR+Ag22kJqaat53 JBgJGxuWSx6Sgwn8+2e/6DM+bgLYV322gi8/WMKXlYMJ/H2tW/ghT8rDCCeA Ww4mMHDzfm9AO+rm0FOZOm7yuDABaSsmuro7C2DZgupEIpFgD9nU1AQeWLZI e0pPTz8PBNhsNp1Oh8aPe4IGdLyqqsrlZ8ERCTDyGKqWWYvTzw8BlUrFyWuS XOkUfdwhudJlMrF/5+h3g4Rn5YQEpqenBXX84QzsiVSzrtab29aGkfCsnJAA KD8/n/Cr25JzEti3EtpJzkZgSCKTcjEXJnDvW9GNjxKDSUGBpEDGp7l3fdt/ 8y4KIPmDJ5RE/sO7sufSHaFn2+2Q3wm/ui05mMCgQCpktAtbusCk3ZisRwqG vvZye6A9UCX5J0/EzPye8Kvb0hn6dWwnucYTkpPITcBNwE3ATcBNwE3ATQA3 gc3NTb1eb7e8HCd8BIxGo1wuHxkZsfUQ/gwJH4GJiQmNRrOysoJhWFtbW0tL C3pV4ywKBwGDwTA0NASN0dFRLpfLYrHKysqYTGZfH/EP8RygoxNA72BAQ6VS wR1HbyoqlcqpqSl0QE5ODo/HQ+1xtWFZv4U7q0da474vt9hDtghcoKtK2lfM DRFobGzs7OzkcDgxMTHl5eXNzc1CobBxT7W1teHh4Q0NDRm/dr8RP3sxwzLC Ee1n7srrVMVrFAXt5hK+CMcyUp7amoBxa6f4L236rUVzQwSKi4th2BcVFYWF hRXvqbW1tbKyErUpFAqUhS+/5ryTpnw7Zc4iwhEtlf341ejJl6Imrv6ygC/C sYzR+MRg3MYxeKhU6szM7qSAiTA5OQmN9fX13NxcVBIFsjXFY/zDuLqhl5pd jvt0x4jP52dmZkIDFkT08mphYSHUAa1We/LgMNEYDMbJ49hbUPwLCgpqamqA RnV1NUwH2CHgjrawsBD1VDDFgoODTV8FAgGBaROrwcHBiooKNpstEolgcYQd Au5QsMmcm5uDGlv1rMCp01lWKicUFAFCxj9sMIqf1cljnjn19/ejNzNLSkpO Oxe33Dp3+h9eeYMd "], {{0, 57}, {86, 0}}, {0, 255}, ColorFunction -> RGBColor], BoxForm`ImageTag[ "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Exif" -> Association[ "Software" -> "Created with the Wolfram Language : www.wolfram.com"], "Comments" -> Association[ "Software" -> "Created with the Wolfram Language : www.wolfram.com", "Creation Time" -> DateObject[{2018, 11, 28, 12, 13, 2.}, "Instant", "Gregorian", -5.]]]], Selectable -> False], DefaultBaseStyle -> "ImageGraphics", ImageSizeRaw -> {86, 57}, PlotRange -> {{0, 86}, {0, 57}}], TraditionalForm]], {0, 0}, {0, 0}, {86, 57}], { RGBColor[ 0.43137254901960786`, 0.43137254901960786`, 0.43137254901960786`], InsetBox[ FormBox[ StyleBox[ "\"IdealTriacCircuit\"", FontSize -> 9, FontFamily -> "Helvetica", StripOnInput -> False], TraditionalForm], NCache[{43, Rational[-29, 2]}, {43, -14.5}], {0, 0}]}, { EdgeForm[ RGBColor[ 0.5843137254901961, 0.807843137254902, 0.9411764705882353]], FaceForm[None], RectangleBox[{-10, -25}, {95, 67}, RoundingRadius -> Offset[5]]}, InsetBox[ BoxData[ FormBox[ GraphicsBox[ TagBox[ RasterBox[CompressedData[" 1:eJzN1VlI1FEUx/FJzT3TxkooKitaaHkoIYOKjAha6MESErJwyMSgkUahlRZ6 CqJoh6CihbaHiuihoH2lImgvMtozjTKzUtP09L3c86c/k+NGD/3hM/7nD/Ob M+eee031FWbOD/N4PEXRvGTmLs4IBHKXzkjkTZa/qCDfnzdvsr84Lz8vkO4L 52GKioC0fDWqX/iJH6jAG9zFaWxFAcajB2I8erUi3/mOBtShGl/wHg9xFjtR iEnohbh25tejBpUoxWNcxC4swlT0Rfw/yP+AJziP3Qhofn8ktCHf6b+TX635 pj+PcE5sf0z9U5CKTu3IN+tr+u+s71vcF7u+27FQ/vS/Lf1xanfm5zs+4SXu 4CQ2Ih/j0FNav77BtZvefxXb+xLcwBGsxVyMQndEt5DfKH/3vVZr/yx29h+I 7b2ZnSWYieHogo6u/MYQnJ7Ua1+cdS3T2m/iONZjASaKXdvOCHPlN4TgZNdq tunLR7wSu2/NvjJzuQLZSEMKYj2uSzOC1WnNNdqTSs1+LXbPXsZhrNPazdwM RJK7N5pfozW6mWdmDqvEzmKZ1m2yr+IYNqEYWRiptcd7gi793Sbnm/6t0nor tOZ3eI57uKI934ZlyMEY9EEiIprIN7NWrlnlqlRn5IXYM+a22HPgKLZgOXzI wAB4xXVmBuU/1Xko0TqfaabZm7dwCaewDxvEzuIczR6CrohDhxD55vPXxO6V 69rfCziDE9iPzVgDP2aJPecHo5vpubjmsYn8vTiIQ+oA9mCH2NleJfbsysU0 pKOfq+7wUNmab9Zppda3Wu/NsyKx/5NmYzrGYpjY88Xs0djm6nblm32drbOQ o/fmmTnLJ2A0hoo9F5ORgKiWcl355swYIXb/pem9eTYIvcXOtVdzY1pTc1B+ kv7eZOXV90maafoQ2dZcV364fj5KRapm1+1/uX4DOnc/KA== "], {{0, 24}, {24, 0}}, {0, 255}, ColorFunction -> RGBColor], BoxForm`ImageTag[ "Byte", ColorSpace -> "RGB", Interleaving -> True], Selectable -> False], DefaultBaseStyle -> "ImageGraphics", ImageSizeRaw -> {24, 24}, PlotRange -> {{0, 24}, {0, 24}}], TraditionalForm]], Offset[{6, -6}, Scaled[{0, 1}]], Scaled[{0, 1}], {24, 24}]}; Null, WSM`Typeset`PackagePrivate`appearanceState === "Eval", WSM`Typeset`PackagePrivate`p = {{ EdgeForm[WSM`Typeset`PackagePrivate`$bordercolor], FaceForm[None], RectangleBox[{ Part[WSM`Typeset`PackagePrivate`expandedrange, 1, 1], Part[WSM`Typeset`PackagePrivate`expandedrange, 2, 1] + 1}, { Part[WSM`Typeset`PackagePrivate`expandedrange, 1, 2] - 1, Part[WSM`Typeset`PackagePrivate`expandedrange, 2, 2]}, RoundingRadius -> Offset[5]]}, InsetBox[ Evaluate[ ToBoxes[ ProgressIndicator[Appearance -> "Percolate"], StandardForm]]]}; Module[{WSM`Typeset`PackagePrivate`md$}, { WSM`Typeset`PackagePrivate`expandedsize, WSM`Typeset`PackagePrivate`md$} = WSM`Typeset`PackagePrivate`getExpandedGraphic[ "Modelica.Electrical.Analog.Examples.IdealTriacCircuit", "6a3fff13-4a1c-4f20-a1a7-215c449d45d3"]; { WSM`Typeset`PackagePrivate`expandedprimitives, WSM`Typeset`PackagePrivate`expandedopt} = WSM`Typeset`PackagePrivate`separateGraphics[ WSM`Typeset`PackagePrivate`md$]; WSM`Typeset`PackagePrivate`expandedrange = Replace[PlotRange, Flatten[WSM`Typeset`PackagePrivate`expandedopt]]; WSM`Typeset`PackagePrivate`expandedeval = True; WSM`Typeset`PackagePrivate`expandedprimitives = Join[WSM`Typeset`PackagePrivate`expandedprimitives, {{ EdgeForm[WSM`Typeset`PackagePrivate`$bordercolor], FaceForm[None], RectangleBox[{ Part[WSM`Typeset`PackagePrivate`expandedrange, 1, 1], Part[WSM`Typeset`PackagePrivate`expandedrange, 2, 1] + 1}, {Part[WSM`Typeset`PackagePrivate`expandedrange, 1, 2] - 1, Part[WSM`Typeset`PackagePrivate`expandedrange, 2, 2]}, RoundingRadius -> Offset[5]]}, With[{WSM`Typeset`PackagePrivate`leftmost$ = Part[WSM`Typeset`PackagePrivate`expandedrange, 1, 1], WSM`Typeset`PackagePrivate`bottommost$ = Part[WSM`Typeset`PackagePrivate`expandedrange, 2, 1]}, { RGBColor[ 0.43137254901960786`, 0.43137254901960786`, 0.43137254901960786`], InsetBox[ FormBox[ StyleBox[ "IdealTriacCircuit", FontSize -> 9, FontFamily -> "Helvetica", StripOnInput -> False], TraditionalForm], Offset[{12, 12}, { WSM`Typeset`PackagePrivate`leftmost$, WSM`Typeset`PackagePrivate`bottommost$}], {-1, 0}]}]}]; Null]; WSM`Typeset`PackagePrivate`appearanceState = "Expanded"; Null, WSM`Typeset`PackagePrivate`appearanceState === "Expanded", WSM`Typeset`PackagePrivate`p = WSM`Typeset`PackagePrivate`expandedprimitives; Null]; Null, ImageSizeCache->{{-0.5, 105.5}, {-50.5, 42.5}}, SynchronousUpdating->False, TrackedSymbols:>{WSM`Typeset`PackagePrivate`appearanceState}], Initialization:>( WSM`Typeset`PackagePrivate`expandedeval = Not[WSM`Typeset`PackagePrivate`expandedeval]; WSM`Typeset`PackagePrivate`expandedeval = Not[WSM`Typeset`PackagePrivate`expandedeval]; Null)], "Modelica.Electrical.Analog.Examples.IdealTriacCircuit"], WSM`ModelTag["Modelica.Electrical.Analog.Examples.IdealTriacCircuit"]], Editable -> False, SelectWithContents -> True, BoxID -> "6a3fff13-4a1c-4f20-a1a7-215c449d45d3", ContentSelectable->False, DefaultBaseStyle->{ "Graphics", FrontEnd`GraphicsHighlightColor -> RGBColor[0, 0.46775, 1], ComponentwiseContextMenu -> {"GraphicsBox" -> { MenuItem["Copy Model", KernelExecute[ CopyToClipboard[ ReleaseHold[ MakeExpression[ MakeBoxes[ SystemModel[ "Modelica.Electrical.Analog.Examples.IdealTriacCircuit"]], StandardForm]]]], MenuEvaluator -> Automatic], MenuItem["Copy Model Name", KernelExecute[ CopyToClipboard[ StringJoin[ "\"", "Modelica.Electrical.Analog.Examples.IdealTriacCircuit", "\""]]], MenuEvaluator -> Automatic], Delimiter, MenuItem["Simulate Model", FrontEndExecute[{ FrontEnd`SelectionMove[ FrontEnd`InputNotebook[], After, Cell], FrontEnd`NotebookWrite[ FrontEnd`InputNotebook[], Cell[ BoxData[ RowBox[{ "SystemModelSimulate", "[", "\"Modelica.Electrical.Analog.Examples.IdealTriacCircuit\"", "]"}]], "Input"]], FrontEnd`SelectionMove[ FrontEnd`InputNotebook[], Previous, Cell], FrontEnd`SelectionEvaluateCreateCell[ FrontEnd`InputNotebook[]]}]], MenuItem["Show Preferred Plots in Model", FrontEndExecute[{ FrontEnd`SelectionMove[ FrontEnd`InputNotebook[], After, Cell], FrontEnd`NotebookWrite[ FrontEnd`InputNotebook[], Cell[ BoxData[ RowBox[{ "SystemModelPlot", "[", "\"Modelica.Electrical.Analog.Examples.IdealTriacCircuit\"", "]"}]], "Input"]], FrontEnd`SelectionMove[ FrontEnd`InputNotebook[], Previous, Cell], FrontEnd`SelectionEvaluateCreateCell[ FrontEnd`InputNotebook[]]}]], MenuItem["Show Model Information", FrontEndExecute[{ FrontEnd`SelectionMove[ FrontEnd`InputNotebook[], After, Cell], FrontEnd`NotebookWrite[ FrontEnd`InputNotebook[], Cell[ BoxData[ RowBox[{"SystemModel", "[", RowBox[{ "\"Modelica.Electrical.Analog.Examples.IdealTriacCircuit\"\ ", ",", "\"Summary\""}], "]"}]], "Input"]], FrontEnd`SelectionMove[ FrontEnd`InputNotebook[], Previous, Cell], FrontEnd`SelectionEvaluateCreateCell[ FrontEnd`InputNotebook[]]}]], Delimiter, MenuItem["Open in SystemModeler Model Center", KernelExecute[ WSMLink`WSMModelCenter[ "Modelica.Electrical.Analog.Examples.IdealTriacCircuit"]], MenuEvaluator -> Automatic], MenuItem["Open in SystemModeler Simulation Center", KernelExecute[ WSMLink`WSMSimulationCenter[ "Modelica.Electrical.Analog.Examples.IdealTriacCircuit"]], MenuEvaluator -> Automatic]}}}, ImageSize->{106, 93}, PlotRange->{{-10, 96}, {-26, 67}}], Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], SystemModel[ "Modelica.Electrical.Analog.Examples.IdealTriacCircuit", True]]], "Output", CellChangeTimes->{3.756079925488016*^9}, CellLabel->"Out[3]=", CellID->521518740] }, Open ]], Cell[CellGroupData[{ Cell["", "PageBreak", PageBreakBelow->True, CellID->244582541], Cell["That\[CloseCurlyQuote]s one smart bird:", "Text", CellChangeTimes->{3.7560799134274054`*^9}, CellID->169564055], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"BirdSay", "[", RowBox[{ RowBox[{"FindEquationalProof", "[", RowBox[{ RowBox[{"ForAll", "[", RowBox[{ RowBox[{"{", RowBox[{"a", ",", "b"}], "}"}], ",", RowBox[{ RowBox[{"or", "[", RowBox[{ RowBox[{"not", "[", RowBox[{"or", "[", RowBox[{ RowBox[{"not", "[", "a", "]"}], ",", "b"}], "]"}], "]"}], ",", RowBox[{"not", "[", RowBox[{"or", "[", RowBox[{ RowBox[{"not", "[", "a", "]"}], ",", RowBox[{"not", "[", "b", "]"}]}], "]"}], "]"}]}], "]"}], "\[Equal]", "a"}]}], "]"}], ",", RowBox[{"{", RowBox[{ RowBox[{"ForAll", "[", RowBox[{ RowBox[{"{", RowBox[{"a", ",", "b"}], "}"}], ",", RowBox[{ RowBox[{"and", "[", RowBox[{"a", ",", "b"}], "]"}], "\[Equal]", RowBox[{"and", "[", RowBox[{"b", ",", "a"}], "]"}]}]}], "]"}], ",", RowBox[{"ForAll", "[", RowBox[{ RowBox[{"{", RowBox[{"a", ",", "b"}], "}"}], ",", RowBox[{ RowBox[{"or", "[", RowBox[{"a", ",", "b"}], "]"}], "\[Equal]", RowBox[{"or", "[", RowBox[{"b", ",", "a"}], "]"}]}]}], "]"}], ",", RowBox[{"ForAll", "[", RowBox[{ RowBox[{"{", RowBox[{"a", ",", "b"}], "}"}], ",", RowBox[{ RowBox[{"and", "[", RowBox[{"a", ",", RowBox[{"or", "[", RowBox[{"b", ",", RowBox[{"not", "[", "b", "]"}]}], "]"}]}], "]"}], "\[Equal]", "a"}]}], "]"}], ",", RowBox[{"ForAll", "[", RowBox[{ RowBox[{"{", RowBox[{"a", ",", "b"}], "}"}], ",", RowBox[{ RowBox[{"or", "[", RowBox[{"a", ",", RowBox[{"and", "[", RowBox[{"b", ",", RowBox[{"not", "[", "b", "]"}]}], "]"}]}], "]"}], "\[Equal]", "a"}]}], "]"}], ",", RowBox[{"ForAll", "[", RowBox[{ RowBox[{"{", RowBox[{"a", ",", "b", ",", "c"}], "}"}], ",", RowBox[{ RowBox[{"and", "[", RowBox[{"a", ",", RowBox[{"or", "[", RowBox[{"b", ",", "c"}], "]"}]}], "]"}], "\[Equal]", RowBox[{"or", "[", RowBox[{ RowBox[{"and", "[", RowBox[{"a", ",", "b"}], "]"}], ",", RowBox[{"and", "[", RowBox[{"a", ",", "c"}], "]"}]}], "]"}]}]}], "]"}], ",", RowBox[{"ForAll", "[", RowBox[{ RowBox[{"{", RowBox[{"a", ",", "b", ",", "c"}], "}"}], ",", RowBox[{ RowBox[{"or", "[", RowBox[{"a", ",", RowBox[{"and", "[", RowBox[{"b", ",", "c"}], "]"}]}], "]"}], "\[Equal]", RowBox[{"and", "[", RowBox[{ RowBox[{"or", "[", RowBox[{"a", ",", "b"}], "]"}], ",", RowBox[{"or", "[", RowBox[{"a", ",", "c"}], "]"}]}], "]"}]}]}], "]"}]}], "}"}]}], "]"}], "[", "\"\\"", "]"}], "]"}]], "Input", CellLabel->"In[4]:=", CellID->65455867], Cell[BoxData[ InterpretationBox[ PanelBox[ GraphicsBox[ NamespaceBox["NetworkGraphics", DynamicModuleBox[{Typeset`graph = HoldComplete[ Graph[{ "Axiom 1", "Axiom 2", "Axiom 3", "Axiom 4", "Axiom 5", "Axiom 6", "Hypothesis 1", "Critical Pair Lemma 1", "Critical Pair Lemma 2", "Critical Pair Lemma 3", "Critical Pair Lemma 4", "Critical Pair Lemma 5", "Critical Pair Lemma 6", "Critical Pair Lemma 7", "Critical Pair Lemma 8", "Critical Pair Lemma 9", "Critical Pair Lemma 10", "Critical Pair Lemma 11", "Critical Pair Lemma 12", "Critical Pair Lemma 13", "Substitution Lemma 1", "Substitution Lemma 2", "Substitution Lemma 3", "Critical Pair Lemma 14", "Critical Pair Lemma 15", "Critical Pair Lemma 16", "Critical Pair Lemma 17", "Substitution Lemma 4", "Critical Pair Lemma 18", "Substitution Lemma 5", "Critical Pair Lemma 19", "Substitution Lemma 6", "Substitution Lemma 7", "Substitution Lemma 8", "Critical Pair Lemma 20", "Substitution Lemma 9", "Critical Pair Lemma 21", "Substitution Lemma 10", "Critical Pair Lemma 22", "Substitution Lemma 11", "Critical Pair Lemma 23", "Critical Pair Lemma 24", "Critical Pair Lemma 25", "Critical Pair Lemma 26", "Substitution Lemma 12", "Critical Pair Lemma 27", "Substitution Lemma 13", "Critical Pair Lemma 28", "Substitution Lemma 14", "Critical Pair Lemma 29", "Substitution Lemma 15", "Substitution Lemma 16", "Critical Pair Lemma 30", "Substitution Lemma 17", "Critical Pair Lemma 31", "Critical Pair Lemma 32", "Critical Pair Lemma 33", "Critical Pair Lemma 34", "Critical Pair Lemma 35", "Substitution Lemma 18", "Critical Pair Lemma 36", "Substitution Lemma 19", "Critical Pair Lemma 37", "Substitution Lemma 20", "Critical Pair Lemma 38", "Substitution Lemma 21", "Critical Pair Lemma 39", "Substitution Lemma 22", "Critical Pair Lemma 40", "Substitution Lemma 23", "Substitution Lemma 24", "Critical Pair Lemma 41", "Substitution Lemma 25", "Substitution Lemma 26", "Substitution Lemma 27", "Substitution Lemma 28", "Substitution Lemma 29", "Substitution Lemma 30", "Substitution Lemma 31", "Substitution Lemma 32", "Substitution Lemma 33", "Substitution Lemma 34", "Conclusion 1"}, {CompressedData[" 1:eJwVxWd6gjAAAFBNQoqCEVxhuMCFCG4RBXErbsUbeIFep8dt++N9T/t8Rx8Q i8V+/vwP2TiLEiCBkjDJcHEO84BnUjjFEoaANJvmBSQQEYhCRsyks3yWy2Vy uTzI5wu4UKAiFSQqEZnKnEIVokqqWiRFplQslcpMWarIlUqVVquapGk61VFN r9XqqI4aeqPRRM1yK9FqGcAw2nzbMKEpdYyOYJlWx4a23bW73V67p/Ttfn8A BsrQGg5HYDQY43F9kpxMHNNxpnDquNidzvDMnZvzmWd4Ix/78wVcLAIvCJZw 2VstV2S9Wq83YNPcbrbbnb+T97v9/jA+HI7y8RjS8OuET6czPp8v4eVyTV2v t+ztdsf3+wM/Hs/w+Xzh1yuiUfSOv38B2IAunA== "], Null}, { EdgeStyle -> { DirectedEdge["Critical Pair Lemma 29", "Substitution Lemma 15"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 3", "Critical Pair Lemma 37"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 2", "Substitution Lemma 3"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 16", "Critical Pair Lemma 29"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 22", "Critical Pair Lemma 40"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 7", "Critical Pair Lemma 10"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 15", "Substitution Lemma 18"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 25", "Substitution Lemma 12"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 13", "Substitution Lemma 1"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 34", "Conclusion 1"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 8", "Critical Pair Lemma 20"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 1", "Substitution Lemma 2"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 24", "Substitution Lemma 17"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 25", "Substitution Lemma 26"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 5", "Critical Pair Lemma 4"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 26"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 21", "Critical Pair Lemma 39"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 2", "Critical Pair Lemma 22"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 5", "Critical Pair Lemma 22"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Substitution Lemma 8"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Substitution Lemma 10"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 3", "Critical Pair Lemma 31"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Critical Pair Lemma 14"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 5", "Critical Pair Lemma 18"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Critical Pair Lemma 6"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 40", "Substitution Lemma 23"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 14", "Critical Pair Lemma 25"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Substitution Lemma 14"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 30"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Substitution Lemma 34"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 16", "Substitution Lemma 23"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Hypothesis 1", "Substitution Lemma 25"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 24", "Critical Pair Lemma 26"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 28", "Substitution Lemma 29"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 39", "Substitution Lemma 22"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 5", "Critical Pair Lemma 12"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 11", "Critical Pair Lemma 23"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 10", "Substitution Lemma 3"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 34", "Critical Pair Lemma 36"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 13", "Substitution Lemma 20"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 38", "Substitution Lemma 21"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 11", "Critical Pair Lemma 25"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Substitution Lemma 6"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 37", "Substitution Lemma 20"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 31", "Substitution Lemma 32"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 12", "Critical Pair Lemma 27"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 23", "Substitution Lemma 13"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 16"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Critical Pair Lemma 21"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 29", "Substitution Lemma 30"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 33", "Substitution Lemma 34"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 3", "Critical Pair Lemma 1"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 5", "Critical Pair Lemma 9"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 7", "Critical Pair Lemma 17"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 11", "Critical Pair Lemma 24"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Substitution Lemma 11"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 30", "Substitution Lemma 17"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 4", "Critical Pair Lemma 13"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 5", "Critical Pair Lemma 23"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 8", "Critical Pair Lemma 12"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 15", "Substitution Lemma 24"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 11", "Critical Pair Lemma 35"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 41", "Substitution Lemma 27"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Critical Pair Lemma 5"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 28", "Substitution Lemma 14"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 35", "Substitution Lemma 19"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 14", "Critical Pair Lemma 17"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 27", "Substitution Lemma 28"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 3", "Substitution Lemma 12"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 20", "Substitution Lemma 9"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 1", "Critical Pair Lemma 4"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 1", "Critical Pair Lemma 7"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Critical Pair Lemma 10"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 5", "Critical Pair Lemma 7"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 26", "Substitution Lemma 27"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 3", "Critical Pair Lemma 15"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 9", "Critical Pair Lemma 14"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 17", "Critical Pair Lemma 32"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Substitution Lemma 1"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 8", "Critical Pair Lemma 21"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 24", "Critical Pair Lemma 41"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 19", "Substitution Lemma 6"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 9", "Critical Pair Lemma 11"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Critical Pair Lemma 41"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Critical Pair Lemma 5"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 20", "Critical Pair Lemma 38"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 3", "Critical Pair Lemma 24"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 11", "Critical Pair Lemma 13"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 12", "Substitution Lemma 29"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 26", "Critical Pair Lemma 29"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 31"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Critical Pair Lemma 3"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Critical Pair Lemma 9"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 12", "Critical Pair Lemma 28"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 15", "Critical Pair Lemma 40"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 14", "Substitution Lemma 16"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 6", "Critical Pair Lemma 33"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Critical Pair Lemma 2"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 7", "Critical Pair Lemma 15"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 6", "Substitution Lemma 28"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 1", "Conclusion 1"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 25"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Substitution Lemma 21"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 4", "Critical Pair Lemma 18"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Critical Pair Lemma 20"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 36", "Substitution Lemma 19"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 10", "Critical Pair Lemma 11"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 27", "Substitution Lemma 13"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 3", "Critical Pair Lemma 3"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 5", "Substitution Lemma 5"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 14", "Substitution Lemma 7"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 2"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 5", "Critical Pair Lemma 6"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Substitution Lemma 9"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Substitution Lemma 15"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 7", "Critical Pair Lemma 38"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Critical Pair Lemma 2"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 6", "Substitution Lemma 7"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 7", "Substitution Lemma 8"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 1", "Critical Pair Lemma 1"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 21", "Substitution Lemma 10"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 33", "Critical Pair Lemma 35"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Critical Pair Lemma 16"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 18", "Substitution Lemma 22"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 4", "Critical Pair Lemma 16"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 33"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 19", "Critical Pair Lemma 37"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 18", "Substitution Lemma 5"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 9", "Critical Pair Lemma 30"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Critical Pair Lemma 8"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 14", "Critical Pair Lemma 19"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 18"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 30", "Substitution Lemma 31"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 31", "Critical Pair Lemma 33"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 22", "Substitution Lemma 11"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 3", "Critical Pair Lemma 30"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 10", "Critical Pair Lemma 39"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 23", "Substitution Lemma 24"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 32", "Substitution Lemma 33"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 17", "Critical Pair Lemma 31"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 1", "Critical Pair Lemma 8"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 7", "Substitution Lemma 4"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 3", "Critical Pair Lemma 36"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 15", "Critical Pair Lemma 19"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 24", "Critical Pair Lemma 34"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 32", "Critical Pair Lemma 34"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 17", "Substitution Lemma 4"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 6", "Critical Pair Lemma 32"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 41", "Substitution Lemma 32"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 16", "Critical Pair Lemma 28"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 9", "Critical Pair Lemma 26"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]]}, GraphLayout -> "LayeredDigraphEmbedding", Properties -> { "Substitution Lemma 4" -> {Tooltip -> "Substitution Lemma 4"}, "Substitution Lemma 24" -> {Tooltip -> "Substitution Lemma 24"}, "Axiom 3" -> {Tooltip -> "Axiom 3"}, "Critical Pair Lemma 11" -> {Tooltip -> "Critical Pair Lemma 11"}, "Substitution Lemma 18" -> {Tooltip -> "Substitution Lemma 18"}, "Critical Pair Lemma 29" -> {Tooltip -> "Critical Pair Lemma 29"}, "Critical Pair Lemma 37" -> {Tooltip -> "Critical Pair Lemma 37"}, "Substitution Lemma 17" -> {Tooltip -> "Substitution Lemma 17"}, "Critical Pair Lemma 21" -> {Tooltip -> "Critical Pair Lemma 21"}, "Substitution Lemma 6" -> {Tooltip -> "Substitution Lemma 6"}, "Critical Pair Lemma 40" -> {Tooltip -> "Critical Pair Lemma 40"}, "Critical Pair Lemma 30" -> {Tooltip -> "Critical Pair Lemma 30"}, "Axiom 1" -> {Tooltip -> "Axiom 1"}, "Substitution Lemma 27" -> {Tooltip -> "Substitution Lemma 27"}, "Substitution Lemma 3" -> {Tooltip -> "Substitution Lemma 3"}, "Substitution Lemma 9" -> {Tooltip -> "Substitution Lemma 9"}, "Critical Pair Lemma 15" -> {Tooltip -> "Critical Pair Lemma 15"}, "Critical Pair Lemma 7" -> {Tooltip -> "Critical Pair Lemma 7"}, "Substitution Lemma 19" -> {Tooltip -> "Substitution Lemma 19"}, "Critical Pair Lemma 14" -> {Tooltip -> "Critical Pair Lemma 14"}, "Substitution Lemma 34" -> {Tooltip -> "Substitution Lemma 34"}, "Critical Pair Lemma 22" -> {Tooltip -> "Critical Pair Lemma 22"}, "Critical Pair Lemma 6" -> {Tooltip -> "Critical Pair Lemma 6"}, "Critical Pair Lemma 3" -> {Tooltip -> "Critical Pair Lemma 3"}, "Substitution Lemma 26" -> {Tooltip -> "Substitution Lemma 26"}, "Substitution Lemma 33" -> {Tooltip -> "Substitution Lemma 33"}, "Critical Pair Lemma 1" -> {Tooltip -> "Critical Pair Lemma 1"}, "Critical Pair Lemma 16" -> {Tooltip -> "Critical Pair Lemma 16"}, "Critical Pair Lemma 27" -> {Tooltip -> "Critical Pair Lemma 27"}, "Critical Pair Lemma 26" -> {Tooltip -> "Critical Pair Lemma 26"}, "Substitution Lemma 21" -> {Tooltip -> "Substitution Lemma 21"}, "Substitution Lemma 7" -> {Tooltip -> "Substitution Lemma 7"}, "Substitution Lemma 11" -> {Tooltip -> "Substitution Lemma 11"}, "Critical Pair Lemma 5" -> {Tooltip -> "Critical Pair Lemma 5"}, "Critical Pair Lemma 23" -> {Tooltip -> "Critical Pair Lemma 23"}, "Substitution Lemma 2" -> {Tooltip -> "Substitution Lemma 2"}, "Substitution Lemma 13" -> {Tooltip -> "Substitution Lemma 13"}, "Substitution Lemma 31" -> {Tooltip -> "Substitution Lemma 31"}, "Critical Pair Lemma 10" -> {Tooltip -> "Critical Pair Lemma 10"}, "Axiom 2" -> {Tooltip -> "Axiom 2"}, "Substitution Lemma 1" -> {Tooltip -> "Substitution Lemma 1"}, "Critical Pair Lemma 28" -> {Tooltip -> "Critical Pair Lemma 28"}, "Critical Pair Lemma 31" -> {Tooltip -> "Critical Pair Lemma 31"}, "Critical Pair Lemma 17" -> {Tooltip -> "Critical Pair Lemma 17"}, "Critical Pair Lemma 33" -> {Tooltip -> "Critical Pair Lemma 33"}, "Substitution Lemma 20" -> {Tooltip -> "Substitution Lemma 20"}, "Critical Pair Lemma 18" -> {Tooltip -> "Critical Pair Lemma 18"}, "Critical Pair Lemma 32" -> {Tooltip -> "Critical Pair Lemma 32"}, "Axiom 4" -> {Tooltip -> "Axiom 4"}, "Substitution Lemma 22" -> {Tooltip -> "Substitution Lemma 22"}, "Critical Pair Lemma 19" -> {Tooltip -> "Critical Pair Lemma 19"}, "Substitution Lemma 5" -> {Tooltip -> "Substitution Lemma 5"}, "Critical Pair Lemma 24" -> {Tooltip -> "Critical Pair Lemma 24"}, "Critical Pair Lemma 36" -> {Tooltip -> "Critical Pair Lemma 36"}, "Substitution Lemma 14" -> {Tooltip -> "Substitution Lemma 14"}, "Critical Pair Lemma 38" -> {Tooltip -> "Critical Pair Lemma 38"}, "Substitution Lemma 30" -> {Tooltip -> "Substitution Lemma 30"}, "Conclusion 1" -> {Tooltip -> "Conclusion 1"}, "Substitution Lemma 25" -> {Tooltip -> "Substitution Lemma 25"}, "Critical Pair Lemma 8" -> {Tooltip -> "Critical Pair Lemma 8"}, "Critical Pair Lemma 20" -> {Tooltip -> "Critical Pair Lemma 20"}, "Substitution Lemma 29" -> {Tooltip -> "Substitution Lemma 29"}, "Substitution Lemma 32" -> {Tooltip -> "Substitution Lemma 32"}, "Axiom 5" -> {Tooltip -> "Axiom 5"}, "Critical Pair Lemma 13" -> {Tooltip -> "Critical Pair Lemma 13"}, "Critical Pair Lemma 35" -> {Tooltip -> "Critical Pair Lemma 35"}, "Critical Pair Lemma 2" -> {Tooltip -> "Critical Pair Lemma 2"}, "Axiom 6" -> {Tooltip -> "Axiom 6"}, "Substitution Lemma 8" -> {Tooltip -> "Substitution Lemma 8"}, "Critical Pair Lemma 39" -> {Tooltip -> "Critical Pair Lemma 39"}, "Critical Pair Lemma 4" -> {Tooltip -> "Critical Pair Lemma 4"}, "Substitution Lemma 28" -> {Tooltip -> "Substitution Lemma 28"}, "Substitution Lemma 16" -> {Tooltip -> "Substitution Lemma 16"}, "Critical Pair Lemma 34" -> {Tooltip -> "Critical Pair Lemma 34"}, "Critical Pair Lemma 9" -> {Tooltip -> "Critical Pair Lemma 9"}, "Critical Pair Lemma 25" -> {Tooltip -> "Critical Pair Lemma 25"}, "Substitution Lemma 12" -> {Tooltip -> "Substitution Lemma 12"}, "Hypothesis 1" -> {Tooltip -> "Hypothesis 1"}, "Substitution Lemma 10" -> {Tooltip -> "Substitution Lemma 10"}, "Critical Pair Lemma 41" -> {Tooltip -> "Critical Pair Lemma 41"}, "Substitution Lemma 15" -> {Tooltip -> "Substitution Lemma 15"}, "Substitution Lemma 23" -> {Tooltip -> "Substitution Lemma 23"}, "Critical Pair Lemma 12" -> {Tooltip -> "Critical Pair Lemma 12"}}, VertexLabels -> {None}, VertexShapeFunction -> { "Axiom 6" -> "FiveDown", "Critical Pair Lemma 8" -> "Triangle", "Critical Pair Lemma 18" -> "Triangle", "Critical Pair Lemma 3" -> "Triangle", "Critical Pair Lemma 17" -> "Triangle", "Substitution Lemma 3" -> "Circle", "Substitution Lemma 26" -> "Circle", "Critical Pair Lemma 38" -> "Triangle", "Critical Pair Lemma 20" -> "Triangle", "Critical Pair Lemma 19" -> "Triangle", "Critical Pair Lemma 14" -> "Triangle", "Critical Pair Lemma 5" -> "Triangle", "Substitution Lemma 23" -> "Circle", "Critical Pair Lemma 7" -> "Triangle", "Critical Pair Lemma 34" -> "Triangle", "Critical Pair Lemma 16" -> "Triangle", "Substitution Lemma 1" -> "Circle", "Substitution Lemma 10" -> "Circle", "Critical Pair Lemma 22" -> "Triangle", "Substitution Lemma 9" -> "Circle", "Axiom 4" -> "FiveDown", "Substitution Lemma 12" -> "Circle", "Substitution Lemma 31" -> "Circle", "Critical Pair Lemma 36" -> "Triangle", "Critical Pair Lemma 21" -> "Triangle", "Critical Pair Lemma 41" -> "Triangle", "Substitution Lemma 6" -> "Circle", "Substitution Lemma 34" -> "Circle", "Critical Pair Lemma 25" -> "Triangle", "Critical Pair Lemma 35" -> "Triangle", "Critical Pair Lemma 4" -> "Triangle", "Axiom 5" -> "FiveDown", "Critical Pair Lemma 24" -> "Triangle", "Substitution Lemma 19" -> "Circle", "Critical Pair Lemma 31" -> "Triangle", "Substitution Lemma 27" -> "Circle", "Critical Pair Lemma 1" -> "Triangle", "Critical Pair Lemma 6" -> "Triangle", "Axiom 2" -> "FiveDown", "Critical Pair Lemma 23" -> "Triangle", "Substitution Lemma 11" -> "Circle", "Substitution Lemma 21" -> "Circle", "Substitution Lemma 22" -> "Circle", "Conclusion 1" -> "Square", "Substitution Lemma 13" -> "Circle", "Axiom 1" -> "FiveDown", "Substitution Lemma 20" -> "Circle", "Critical Pair Lemma 39" -> "Triangle", "Critical Pair Lemma 32" -> "Triangle", "Critical Pair Lemma 30" -> "Triangle", "Critical Pair Lemma 27" -> "Triangle", "Critical Pair Lemma 37" -> "Triangle", "Substitution Lemma 30" -> "Circle", "Critical Pair Lemma 29" -> "Triangle", "Substitution Lemma 7" -> "Circle", "Substitution Lemma 33" -> "Circle", "Substitution Lemma 32" -> "Circle", "Substitution Lemma 16" -> "Circle", "Substitution Lemma 29" -> "Circle", "Hypothesis 1" -> "Diamond", "Substitution Lemma 25" -> "Circle", "Critical Pair Lemma 9" -> "Triangle", "Critical Pair Lemma 33" -> "Triangle", "Critical Pair Lemma 26" -> "Triangle", "Critical Pair Lemma 28" -> "Triangle", "Critical Pair Lemma 13" -> "Triangle", "Substitution Lemma 18" -> "Circle", "Substitution Lemma 4" -> "Circle", "Substitution Lemma 17" -> "Circle", "Substitution Lemma 24" -> "Circle", "Substitution Lemma 14" -> "Circle", "Axiom 3" -> "FiveDown", "Critical Pair Lemma 11" -> "Triangle", "Critical Pair Lemma 10" -> "Triangle", "Substitution Lemma 5" -> "Circle", "Critical Pair Lemma 2" -> "Triangle", "Critical Pair Lemma 12" -> "Triangle", "Substitution Lemma 15" -> "Circle", "Substitution Lemma 8" -> "Circle", "Substitution Lemma 2" -> "Circle", "Critical Pair Lemma 40" -> "Triangle", "Substitution Lemma 28" -> "Circle", "Critical Pair Lemma 15" -> "Triangle"}, VertexSize -> {{"Scaled", 0.012976425998969036`}}, VertexStyle -> {"Critical Pair Lemma 8" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 20" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 15" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Axiom 1" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Substitution Lemma 22" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 34" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 7" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 39" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 29" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 11" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 23" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 3" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 9" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 36" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 30" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 40" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 38" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 20" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Axiom 5" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Substitution Lemma 19" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 7" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 18" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 10" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 30" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 10" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 1" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 35" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 33" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 32" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Hypothesis 1" -> Directive[ RGBColor[ Rational[146, 255], Rational[10, 17], 0], EdgeForm[]], "Axiom 6" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Critical Pair Lemma 16" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 31" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 17" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 41" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 14" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 13" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 26" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 13" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 37" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 18" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 28" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 14" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 12" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 3" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 9" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 2" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 16" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 24" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 25" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 11" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 26" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 24" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 12" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 27" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 31" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 1" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 6" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 33" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 23" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 15" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 5" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 21" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Axiom 2" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Substitution Lemma 4" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 21" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 25" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 8" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 27" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 6" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 28" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 2" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Conclusion 1" -> Directive[ RGBColor[ Rational[13, 15], Rational[1, 15], 0], EdgeForm[]], "Critical Pair Lemma 34" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 22" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 5" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Axiom 4" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Critical Pair Lemma 19" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Axiom 3" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Substitution Lemma 32" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 4" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 17" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 29" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]]}}]]}, TagBox[GraphicsGroupBox[{ {Hue[0.6, 0.7, 0.5], Opacity[0.7], Arrowheads[ 0.007249642270711821], {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{0., 40.}, {-1.8733706994324848`, 39.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxTTMoPSmViYGCQAWIQjQpcHF4/+npeukXZ9mtP7J5/P50dWOflneXvNrHt ntK4PPqzs8ONJl0gcrA9LJZzUOyNs4OlSMKJ7zPcbGcIy3IZPHF20GT23/6s 3ddWAKThtrPDJfVaIAqy1QBRl5wdrv/Z4CFZEWb74OW1PxtOODssZHDed3xL lK3VRRDL2cEYDOJtwdRmZ4fg8zeOvp6faFsD0r7c2aFf7XvoDOFk22OFMscL 5zg7eM3/4jn/S7KtkCAQTHR2aLMEGZRiG7OBNXpDq7ODI9gjybbL/H8t8a9y dgA7Qz3Z9sM7IMgDuh9sb6KtZd9ji75kZ4e3YP/H2zaDvBnh7JAGBlG2Z88A gY+zg02y+Pr6eyG2R/Xi/u9xdHaYJS8G9LK/rQKIMnd20AMHkKvtTXA4OTuk gD1qYfuxJLsuQsXZwcUWZICcbcYbkEXODhuBzmSNVthr/3Ky3UthZwdFkDnb zfaWApUv4YG533Evd/EiZ0Y2ZwdIPHnshdDODgB2t7rU "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxd1wdYU+cex/GIgoMhEmRGlqycwwg7rJxfEvQqRbRepVy0rQNtcaJVsI5b ByogKKLYSqkoaqUoasFbpVJHHVAKdYCKA9k4UBzBwVBuOOc85IX3yfPwfJ+E k0/+70tCbOcsnTpPSyAQLB8kEPT+7L9C8MU+u6dX9jYzVvWmK2M6lPA2exG/ PuU949G8IFnnlRKJ+WEhi7KHQKrXwdxpUaJBN3HXm2UG8Ij4M+P+PSV2V1YZ tz00htWlq9uEFUocPR85OE1uCcG/dey++0OJMc1HQmMltqjS3hBpdUyJfR0z m5daOSDrvq/7qx+UmPHT3zeuLhAjssrp53eblHA8QF1s3yNG7YPio+s3KvE+ tlD34zkxilOv2tV+p8R1vfm/NjSI8bQlRFe4Von8FYqCHC0KCx77zRPFK5Ge O8FAZkVBlp4t6YpVYm3uqiunfCjMa1qz+ESMEotW3LyjM5FC7cNyS//ZSkTr RYzzjqSQvyE98IfPlLi3d1rN6XgKy/96GlbhqcQLya2E79ZTYDZf6djgpMS8 rOuB+kkUDrtttvMWKcE8GK81eyeF7CvikkZDJeJe+lWv3ktBElr4KE1bCaO7 B/+IOkAhotg2IbBTAf09yQWCXygIRSuzGtsUiHF69tuik2pfTL4kqVEBp9TS sn2nKYQfKoNLtQKi8cp2q38oWK4U79QpVOByWpprU5X6+pdd/E8cUcC1eH58 0n0KtwMMSyKyFIgovXLDoIGCzt3KgA9pCgT/Lz9oxWMKV/fF787ZrEDTRqsz RW0UjFK6KsevVmCSh1lIbTuFZ/u/7HiyRIG4C5l1TZ0UptUcHJIyV4EvJT+n lglohMpL37hEKvDbtO2v44Q0HqaVvjf1UsB2UoOtlTmNKWvyOoqdFBjW/dT3 uBWNYWtiw2eLFFg4O9fDyV7daRbvhoxSYOI6C6MkMY3w33NVR7QVODRZXl3p RuNuh0VIaKcca6pFCUO9aRwLX/a4tU2OCtP80fb+NK6eOVqX0ihHlv7rFLGM hqO0zMW1Wg6p6S0Lq3Aat7NbG2wK5RCHhzu9nUpD2H1ryOUjcvwc/5Au/oxG 9l8fCuZnyXFi12bn2Jk04obNfT5spxzIUY4xmk0j84z2qbzNcnx50GxEzjwa uveadcJWy6Hz/ZAX1gtolC4a3PJsiRz+64aWb1tC42bsF5+mzpXj3XTbA83L aVAtbye4RspRP9Hy1Pn1NGoEb/5y8JLjuElw+ZsEGosUq5pKnOSY0fndWVES jdVDffNiRHK0tTdu8E5Vz2eKm6XuKPXz68RYB++kYSya7XdMW45f3Ubu9s2g cWDhPx/DOoGWxbdrbfaq5yOLW/a8Dei+dE6rO4uGNCNyR2oj0C4p7S7ZT0O5 dGWkazUwM0I6su4YDd/0+BTnQqA2buhPqSdpfO5aaFR2BHh06+VnrqdoRI39 cfrCLGDFN+3M+dM03Fe4T9fbCSRMNpquPEvjvnXsqPzNgPmC0O+Lzql/3/Hz 5EmrAc9LWTp2f9I4vfXt+edLgOtRww+uvULjkTKoIHUuoJKkLfqrlMaLKLfZ rpHAqzvTwyZW0hg313+q2Es9fscen29v09h2U3W8zAm4Jv7JJPOuer4HgioW ioCV9e5tRx/QsLghzNcbBeyZdLr4eC2NWbO+Dc/XBtyWeG3MaaDxafa9OT+2 M1AoD8m2NtNoDK49er+GwfXy4a9nPqbxTZZglWUJg+oR0VljW2kMPSsriTrJ QJm+uP6ZisbM5V+VS+czeLBvSs7KtzTmXIx5vX4yg3024w0L3qvPa73L+xIp g62m4XROJw3rmydr9O0YZGz6WjWum8a1XW9ypuoyqIjO+PqnDzSiHbv+tadd BupsVXLuRxoPki6WV9fIcHyLY9RXPer9OjfBw6JEhqiS5Nt31R1/KW1l1EkZ hFHqN2qBC+azS4aIT7h+f2hy56HJMkTKuN7eKFXfZDD24nqsXe+SIVnM9W+z dNU3Gc7bcv1JdvvE7PZg5Fty/bCmdwUj0pTr5aKSZaKSYJwz5lpnxkntGSeD USckPcGo5buD9Wju5zzBaBSSnmA0CElPMJr4nsh6gtAiJD1BeCwkPUF4KiQ9 QVDx/RXrCcJdvjtZTxAS+3mCIOjnCQKMSE8Qxo/iOpT1BMLEkPQEIt+A9ARC T5/0BKJCh5xPIFRDyPkEYupg0hOI1kGkJxBnBKQnEMU9AsITgK6PAsITgFi+ OU8ARHxzngAI+OY8Aej5ICA8mvs5TwAG8W3PejT3cx5Ncx7/vuY8muY8muY8 /gM8/n0ebr809+9gPf59HpZj5z/A4z/AIx3gkQ7wSAd4pAM8Ukz8SM5HCqce 0iPFDwJyv6TI1CL3SwqJNvn35YeZw8jz4wczPfL8+GGBIXl+/KCyIc+PH245 kOfZD84UeX780OI6iJiPHww9SI8fDnuR59kXeT6kxxfmfqTHF2/9SI8vICU9 vmCk5Hn2hZzvVNbjC4WUnI/mfs6juR7n8elrzqNpzqNpzuMzwOPT5+HeD30G eHz6PNx8fAZ4NNfj9st7gMd7gMd7gMd7gMcbuVJyv7zR4E/ulzfaAsn5eKOU f/8+zXq88Y2CfD/0wsvxpMcLsjDS44XPp5IeL1TGkB4vXIolPV6oiyM9XpCs JT1eyF9PzscLUQnkfnnCeyvp8YQsifR4YlUy6fFEXTLp8URDMnl+PPEsmfR4 oiuZ9HjCcBvp8YTLNtLjgbBtpMcD32wjPR7Yv430qB+fQno8sCmFnI8H/kwh PR4YkkqeHw9MSCU9HkhPJT0S1KeSHgm8tpMeCbZtJz0S/L6D9EjwcQfpkcA4 jfRI8H4HOR8J8naQHgkovnfLnuySPXHHWv75is/2Lndk8j72ctvdkcy/Xl32 Au7wT+S6orx3ueHtFq7b2QPphpbNXI/pfTnL3DCC73EhvcsNM/nzsvCiyaKL Jm5o3MR1ButxReYm0uOKBL6bWI8r9vOtx3pcUZVAelyAzaRHfZ1+HheM30J6 XHCf70WsxwUbt5LzoeGdSHpotCeSHhqXkkgPjf0ppIfC61TSQ8GJ3y92u5dR CNrF9XjWo/6e9j3poTA4i+tdrEeMMwdIjxif5JIeMS6cID1ilP/NNcspd4aw imsV63HGnPukxxlF9VyznBBnGD0i98sZca3kfJzwsI30OCH8FelxwuXX5PlR /8OuIufjCEZFzkfTnMex7/HcfjlCpiLn44ggFelxQICK9DhAqiI9DvBVkR4H uPTz2EPcz2MPJxV5fuzh0M9jD/t+HnvY9fOM7WvOMxa2/TxjYaMi90vT3H7Z wVpF7pemuflomvPY9V2f89j1XY/z2PY159E057Ed4NE0Nx+bvufj5mMzwGMD q34eTXMeG4j4dl5302ndTWtY8L0qvndZw4zv0t7LiaxhwrcpewEr6POdubd3 jYEf34/ZP5AxOMe3P/uGKEJOO9fJib1LhLo3XFdvdFXfRFj1jvRYYkkH6bHE uS7SY4mFH7k2Yz0WyB+mRXjMcUaX6yesxxxLDLhmx9tohuuGXCexHjPcM+L6 LusxQ5qxFuExxavRWoTHFN0mXLPjFpmi0FSLmI8JUs1Iz2hcMCM9o/GSb24+ xjA3Jz3GCDAnPcaINCc9Qiw3Jz1CJJiTHiHSzUmPEX42Jz2jcIzvp6xnFE6b kx5DXOGb2y9DVPHN7ZchWviewn4AjkQ33y/bepcBjC20iM9DA7jz7cZeQB+7 +PZily6eFy9ev0L9fXqo4ca86HUjcOHgyUE31d/H//XHvRsjS4dD91rZJrMu GqqA4F+8hcNRISvWmfCOhk7SL5LKL4ZBR5WQPOs1jS1HrL9uzRuKM632I+c8 oxG7J3vyunc6qHPO2h3WTOPydPGjxBAdbMh7amFTQyOhudjNIF0bW6dVGngV qz9nWM9gLHsbN1W7QP05csRsUOg6LSgOZzxJP0Ijx9LH5XDJIHTPcq+6n0UD OxJPhRgNwo/iEKO6nTRWaAkznT8XwK6n8mD2FhobnuYWHZjSw2yvf5hosYZG 2LW9HasffWDqr0dfnLJU/foK36se/LebEVXMm6SYq/79PVdyS0y6mMzYxdVX /Wn+/423jKHPr09WudCY1EAVnehuZ6Jnms+9NobG1k1TvIu+VzEZLYdDyvRp jA69c2ej32tmf2XE9phuCiqf8wf1Hrxkkse6IP8JhQnbDSX5I14w4bcdojJu UQjvio65OP8Z87JV+cD2AoXOgjWq6eVPmNjoLVen/kIh9H/T/lkQ+IgpY56b Oe+kINN62dFT2MQcNV4tzVtOwVPn1ouJ2fVMUZHhRYsICpP/c3b4qG9rmA63 Xwu+DVQ/vlW4PN60mpmzYoZ+iR0F1z8LzUrMK5nOpJE3tPTUn7vFPl09PeXM +aUVH1zeieH033R5yO7LTIFDxq5xTWI47+4a9ltdEXPz6Pz0sEox7NY/HDnq 01zGRkvRKb8shoBf/wcuvwkp "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxTTMoPSmViYGCQAWIQvaB55YryZq0DDCDQ4OxwxIsrxO2W1gGTihcFpyqd HW5unl+x0F77QJfj2squImeH2/syxTo3ax9gjPGTcshydjiRnaH711TnwPTj p4NeJzg7LNo1e+/fYzoHfFtUlXvCnB1yVjMf70rTPaAyKbpbydvZQcFugecS Eb0DMh9zu9fZAe0rKnT1uqh3wHhhjLKBobNDiGf5rpo5+geyF6kHL1dydiis O3rvDbPBgbJFj+bvl3J2mBr1MtLf0uAAU+Xm0HwhZwdRy+XnUvMMDvCpzSrZ xuns8E7yv43BYoMDM1dO+zOFwdlB5e+HJeuuGxxYwrzyLdd3J4etj2rYHnIb HtAzuegu8dbJYdGpRYnH7Q0PWFjzc+995OTwakvStsRiwwOHJZLNf153cuhd uIdlwzLDA2fPgICTQ97mDW05NwwPHNOL+7/nIJDPa18WyG50QEFMk9l/O1D9 +vTLccZGB2416d5oWuvkcGqm1rwpMUYHPpZk10UscXJQO9N+7VOT0YGMN4++ np8NtN+tvqZymdEB+5eT7V5OdnKw5RScoHHc6EApSHmPk8N3YVtBhqdGB7iL Fzkztjk5XEhjBkaUMTS+nBwAyXPJHg== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-13.256772299473425`, 39.}, {-8.256772299473198, 38.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-13.256772299473425`, 39.}, {6.999999999384613, 38.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxTTMoPSmViYGCQAWIQvaB55YryZq0DDCDQ4OzQqs/70ExW68Aeq7bPsyud HRrs3r2qX6B5YLW3SsuFQmeH7g0+x4J4NQ+cMbq1cW6Gs8PyVo3i9ckaB2Q+ LK9hjnN2uL638ePUxeoH5jb3PmEMcnaQioxwZDurdiDgbdfLGS7ODnnha5IY HqgeMNJd0H3C1Nnh2o7a0JY7Kgfcnc+emqDq7BBQe0Zy0iHlAz36Qss/Cjs7 9BZp7syuUT7Q5RLsrsDv7JCVbVxy2lz5gOTWp6GdnM4OT9NfeW38onTAsvHk JR1mZ4f/6X62spuVDrxc8W8v1x8nhx3Z8d78xUoHNHRaxZW/ODnwF8uWtpso HfjJFXu/9LWTA2tdx67W74oHolzbRJkfOTnM6lkgzbVH8YDPbYZdp647OZyd lzpDpEnxwNkzIODkoNqtfr/CS/HAMb24/3sOOjloaJjN4xJTPKAgpsnsv93J 4WrpxKsnnygcuNWke6NprZODboll67ZtCgc+lmTXRSxxctBT1lt7oVvhQMab R1/Pz3ZyuN2U7yuRonDA/uVku5eTnRyMJv9N7bVXOFAKUt7j5GAScuObvpzC Ae7iRc6MbU4OB7r/A4E8NL6cHACe18ru "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJwlk39Q03UcxudqxqAmAyYKAvul7DuPHx4qghz3/nw/a8hZa6JAzBLjWHax QwM2xCQnoxShIUmoVCCpa+qJK7jI5OINnhfQJsEVyunVEb/JPI4WIQLXZq+7 9z1/PXfve557JDkH0/RcDocT7zmvXrBcsRdblMjxYqZgbouoL8hTorvqzfbl Egqjv95Qj2uVWFl7/Ku9hRR6f8tqHohTYtdqQ+dqA4W4gbD++CAlngsM843N pSB2PG0WzTLo/8xA4fThv1MMLgYVpQORpWkUyjfyPt9uY3B4anDRsYPCQnfs NctRBhP7mzg0mYJbazKqtAxujvNC4axtYvE5KYM2v55zwQoK/Ot1dMesAg0Z TVs+CqPwSq4lVdipwLLAdv6xQAo653VBtlWB0+xaEdeXQuKY6MwmnQIvjX6X uWoFhYnmW4Mn5Qp0zNf32+ZZyGUah3L/ikTBsY6y7hkWHHvwszutkdhRvCGv aIqFd3UVlU6f9Yihscb0L1hoSJh88Zu7chSeGKqtrGNh8zv8voA6OfqaoTS+ mgVm/FH/431ytK3UR2edYOFoyyciNSPHsZAU+8wHLMT+vHB+zT8y7G0fn14y sqBOWp/9dpcM9zyic2YDCzf/FepjamRYdmVfb0kOC1XczmuFb8kww731wGQm Czjzk9PplKIsxpsPC4WmBndqoxRT+iI9CbNgXTy07sf3pJh20CPrWBBYqEql kqJqldADC3N8b3FSDLnB2+vgsaCqmTyTPCXBe5qFS68tEHiy5pYHCb7/2AuB oKaPR7ZZJcizemSEwFlmv9+3+yVoirpfFnWfAOeA5x2nGJ/V1UJgRHQ7KqtB jJPbLruS7AQy/bkrns8XY4lfAD+0gYAuo0Lt2i7G4aslY65aAn9OvL7c+oIY xcEPc9KrCIScGtaaLkZgojbh+NflBI48aKroiIvAjRk18Ecpgfnbs7aXMRzn FKMXJooJfEp/sfukhuP57k1fdhYQ0OrU1T53wzBoyxHVoXwCy35PBmWnQvFB T1v4rjcItHK36l8yrsWHDibPvpNAfvJSwh1rMIqm+xhTEoGYDk36znsi/NB4 Vfd9NAF3ubKtUROE0btvLhVJCfxQfTq7yx2AAstigC2YQPXvZk1LjxA38Irq XxUQ0Bc9tRS4/PHwUERt3koCoPEOy///fXEI/AclLYbD "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJw11gs4VHkfB3BNplW8mIfaknjYJLdzJrWZ+/xmplrV65KErVi5jvSSS0ll Iwkt1jW3aVRLQrlkVxerfi+VtNUWrdtGLRW5Fc0oQu/IvN/nd57zfJ7nf875 /3//5znnGHkFO/lSVFRUEhTH7PlsbMnFiFhzVJlNtAgeGe4We181R41UGbcw UgR9P2v58MbNcehs1+XREBG8bGnIVwMLlFrXOvSLRXBv8JBWfaYFGm5M/ibB QwSZbcStvTILDG3fbvbESQTfZb8qpfxgiaeHNPc0bBTBP+ZnmhOfWmJSzM37 HjYi8ErfsV5lhxU6Z3v5/WIqgvsPNVt9X1jhkNWntWlLRPC4cGIp+ysCT+f0 91jTRHCrJ9/hqRmBYQtVswzVRZARL49cY0tgTLTdFldVEdhlLMhx8iLw5vRt SueUEN5S/yyxOUSgZczem8UyIUQ8t694kUjgH4t4UTgohH7DkxftsgnMy+Pz V/YIgdcYnvXjWQIl9GDVljYhjBiHXOsoI9BEx6DFtFoISV0NkqJyAjNtILqp WAgqkVfadlcRSBgeebVXIoSNck7A52oCR5oeUTTShLDbyXtbcg2B7Tbs9ktx QtiUapK64DqBg2L0tTssBNWKWJPAWgJXuXuUDQcJIbM8ilZbR+Ap3cUlyd5C +JCi4zx+i8ClP7/0sHITQkuBT/yzuwSu/RIhBC3mXFBvImb7ebfZVAgUnYZI zz8IpBIRw6H6QkjJmZj390PFehjuxTo0IWhfeM478pjAbef2y36lCuEU+wBd 0KJ4vrjqqcukAKbdbrRathKol2xoOzEiAL+Z8jW8DgIttGvtJb0CaLLYLjjw jED30dh+frsA3tdm12b3KedTLYCAEMYG9UECX9o+SGguFoCzt92x2BEC/baW y0MkAriW1rpPZYzAGlZHJC1NAClTLRrH5QT+tcRucVWcADp/2fiD2gSBt58v vOd4WACSeAufjCkCj2dppb8LEkBzcdzyb1RI1GR4hKV6C+CYqnPc1fkkBjbK A+luApjMTzTfr0Uq+yMAxovlmzV1SBwYLUhsNhVAX/fwuqolJP74dupjiL4A 5uV8HnbTI3HYYksMjSaAePVt4VQDEhnF8cZVVAEcZfY01hiR6LHnt2eOkwDd RtX9+0xI3LOzpeLdCMCl2w2tpmYk8tP/yU/tBXhjpJveZ0niR7UXZ+ntAMlO fWVWTBLXfekPQHjEK/EEh8SiMyanm4sB6s4FWz4CEv2kOhahEgDxk7jxsg0k Hvp2epSWBnBwwerGdFsS2716BqriAF6Ci/T4v0lMWNWw2OkwwK/R2kePOCoc XRA6FgTQf8fFM8qZxNb9EfMyvAGitM22JriReODDlvq1bgCXPc8ltPn+vz8A m07qP5oIIHHyoG1Ns6niei9mCBFEYt38grJQfYCfxj+EHAgl8UjHeh0dGoC1 wO3xo4MkWn/UGq6mAjwT7kxiHSHx/i3n0FIZH059mi66dozE1UYab4e7+MAJ FK3YfEKxHt1NjtaNfBhLMx8bTCDxv7mU0xGVfLjUkvfELUex/i/hQ+a9sHTO GRKD2sWuxQ580Ksvvep/XtH/qjOUYQYf+MgXdBYr9mdUVWxjzIfP9dZk5mUS J7Kl8SfV+bD7fmxMVjWJ54v27umU8cCt1ZrRfZ3Eb/UC5NbdPHj3mr89CEks l+eKUht5YDpV2ryxkUQaY3rrWCUPKF3+yTHPScxzSnTV8+VBNB/8tr8msXTA RyK150H4oS2drkMkDlpuK9dj8KA9/uSblFESXZfZJ6cY8aD8P7KMj3IS31bs Yk4u4sG4WWZH5gSJNe8ir7jLuFD5u+8N7ykSy/6++PFaFxeemQSs950h8cH+ fnWNRi4c9ZXa5X4mcUUlY8ilkgusW7NvabqyP1xYeMLZc4fCht30kEoHLpBP NsfsmEdH03t1ATQmF0ov9HipzKfj0ZX/ckw05kKkqiHVhUrH5e8NVi7V4IJ0 YMbfRY2Oauvev6qTc2DZ98d/mqdBR1FfYtbh5xx441AS7KpNxyaNXmv7Jg5o /hmm67aYjpLCmTpGNQfGpZPmFHM6+n+ZDweGy8ykcoKO2Xmr3T85cMB8vkWS +xo6Um9IlnFZHLhcOCNjKlxxuz7fwoQDB1ML208pxqffyOu9q82BE3f1bRzN 6Fidv3JUc5oNnZv8tU8Z0VFT7Hl7/gAbwmknfBhf0/GCob17URsbdqwKW7tr ER0j64dr399hQ3nw4ak2fRJ7Zr7bI7ZlQ8fyLNuwGQKrN/f4jNmwYUrfRH6u l8DLZk9abq5iw9dh5hSfBwQ+kOqWP9Rlw2qDouDr1wjUKrn03oDCBmuDLO75 iwQess0tvDLCgvVhk4EGEgLVojoxoZMF9BV/TVplKL4vm/bbnrvDAmN9k4HH yQTmFu1kT1WwIHzfAPOrJEK5Xyx4t3fOE4UOk4UOLMgJmHNKL0NRLNgnnvNK 49mwINB/zjWe6opiQZbfnLcUyDYXyJgw5Dvn7q7ZMCFI6VD9xhD9RiYsV3rB rkrqrkomyHzmnJc7Gyb0KJ3k/vtMZCwTnirNt3RaIA1iwl2lq6izN2DCVaVf vGmdqrRlQonSj9vvDBbYMEGqdFSzqaKYkK70wOzwZUxIVHrJ6w3xFA0mRCv9 5X9DhQn/A5944xY= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNlgs0lFsbx6WZ1MFxK5TbGHPJK1KMubg9M1OKOgYJ6SZy6SRfKIkwOC4n 0T1xiOhEdSqaDt2+5kmJk1RGIfo6HUq6iXInfaPpW+v7r/2uvX5rvXvv//6v vZ71mAb+yytYWUlJ6Q/5NzUXp54p35VKoNKUxEI4nKLggX3rb0zuFkJEsoKz jiSXrY0WgoVYwTW64bd0w4VwL1HBx3WMfrDeLAT3BAVrflsghOp4Bc9PkDET vIQwPU7B/7xpmahYLoTFsQrmNZ1UEjoJwSVGwbY2UxKC7XucEyrnZaM39sqY Qhj0VFnPknO/WuSXSEMhZJbtSexMIdAyQpSlpSWEd+8pcRFynjT0s60kC4FC HRA9TSYwcG7WiMeYAOYvG/pKlfO6oJ7Wvl4BKK1j7l0hJvDt2L9kB7oE8EdA Rq9XEoFqL0x7rNsEsG0r2yUvnsBvdiQCuKefuz0ijkBm/eMEWZkA5IHdE+wm cPvyR39FFgigoX10lW4sgRqX6XpaBwUQ8XFC7U0MgdNUnwRXpMnPb8oavLaT QNefnv8pihPASNJp9X07CHwVx1f5GCGAF+MrV6+LJrDl8OSanCABPF+SdN8i ikDD43MuWPoJQLxq+S63iO9+bASQk6+WoL+NwF3H0uQJC+Ck3t863VsJvJh8 uD7SUABV96T2kp8J7BhYN1tLSwD3JRcGkrYQOPrxn4AKsgC6ZOecVobJ7xtN vSAa48Mks3qufiiBsxONJ3p7+WAgeZTWFUzgj1otbjldfODtGEm5sJnACQvX fMs2PlRpWzhiAIF9o9VpiyV8SJEFdmdtJPBr7JyBpjI+FK+6Y+m/gUBhMLEh soAP6sdEOhbrCbx+c+i25kE+1OWRcifXEhiSFkevSOODbEPXlcf+BLpc/TNF FMcHi1fvYs+vIXCNf3lHbwQfHi8wbs30I/BkmJd1ThAf7rPimkN8CTR6KRFb +vHhvFLB9dur/pcPHzz0kydLveTv83RnkozJh42zxj+LPQm0q1GRRRryobV5 VoG/B4Gz0kvMtbT4UL3r/JC1SH7/T5fSK8h8UB58NZ3kTqDvDO4b0RjAlRWS 280rCWyqsfX82AvQGj/HrngFgSnM0zdzugA2pamt3eJG4Fbb7EVWbQBqval7 wly+v2cJwJLQi/fNhfJ8yksW6JcDWBlYhryyJ/BBg0paZiHAX7O+LP/NmsDS 3wIdfjkMoGljsnOFKYGx+hIv1b0AP+QefjuoTuAqwWidUTKAhOV/Jn/IHBfN ZRVcj5WfpxFdye0wR+3CkIcvtwPomT1Xbr5ujsON2ZvytgD0ZHuKlM3n46g+ 98xSM4D7mnAgeYKJjWcbrzkYADQb+vkca2Ji8FaR8UNtgC+VeSehnIlS/5vN E7MAXB6RosRiJrbHzuuoVQK4vCuvbrU/E6Oy6sK8e51BUO5bgiwm/pliK13V 7gyfNjkr39Jm4p7W+Ku/1jrD3VMer336GfjXr4W+QxedYUY+yWtzNAMDLrwU 5nk7w+UjJPGCtQzMueO77AjfGWwPkLQfLGXgDQObWmMrZ8jYR5rpasPA15KY f3PmOUP5r6TAQjMGqmVTrTvJzlCQQaI06DLQqszOyKDfCQLTSQKZGgNFypJf ujqcYDSNVH+JzMCfT+SG2N91goB00qXwaQz8Jf5lDbXCCVyySPJCyMCQb3KC kmwFj5wSjZ0SOUH0QQXndHHkwwluHFOwGXVKThBTqOCqAFX5cILy3xW8omjA tWjAEVZeVPDz/0zJEUKvKTjKsC7SsM4Rhu4qeMbaCvLaCkdgDP2/H0dYuGZ/ TuokHV93sus7RY5wb7MV78cxOi7reFrbznWEMf1O5eJPdEwTrdzoTnOE6zvP 9nB66FjgvP+Io4YjaMdnvGtrp+PBcyXB5WMOMDF/t6r4Hh2DD6fLcrodIDYp ablVNR11hnkdfTIHyEzML+kqpmNRizTpgdQBvM/TKaEkOo40vnVu83KA+d6r c83e0TDAHMSLwAEeeGzvb3tMw/cza2kalg6wpDTGKuMWDQvCd1tGzpXvtyLM 3aqShhHe6/N9yQ5Q4LrU80EpDTfj9q01ffYgLlRnh+bRMKFCUlzZYQ+2y259 HTlIwys0Bo9+1x6uugScS82mob5RPduowh6OFLzlquyjfc/HHjyCPgz47aWh SFT1ZEhkD5rVg3T3NBp272seJ3j2IMud3ti9h4bmJjfblOny9WS9t9RIGurO iAlP1LSHNUrWCcqBNKzkj1cVTvDANNM9PU1Ew+Gmn64EvOHB24Io8h9cGr6p 2ra9roUHVU4FYzspNMzs8/+76Q4PfjvRrFkUboaLy9O/Jm3ggXCT/njCMjM8 L21VCXXlQcSlJ7OfUs1wmv5RiqGtfP9DqhsqJqloXnnTtciYB35K11qmd1CR luWd2jeTB7O/vEhsrqbiyO8+jRqfueCTKfYxOUrF4mm1zC/PuGBUcnz96ygq Gp0oOnTlLhe2uJkfsfCkYmR8t7qgggvdz6yOlr8y/Z4PF3aU7X109I4p3jdf /fM5EReGftDJCCg1xbYhd/cvHC6Eq9RfmZliiumNq7TXUbnQUnAmOCfAFNvP B1XVqXLBtqE6u9/JFGW5iTwY5ED6oU/Wi41McXvWqRO1zzlw/9Makcc4BSsz n3T61nNgxvsPPSueUjB3v5bKcCUH9qksTIkJpnz3w4E9TREL+QIKOvNPXa8V cWAe5QVjpzEFy7yzDodwOdDQTW6iDZjg8WKD3uVmHLh27ELPorMmOJu+uiFc nQMkj2tHtDaaoEkn20I2zIaz2uZPbmub4OXW2+q7O9lw5vnYmeW1xviEPBq1 qZENypcX6hTHGGNyeKt/1hU22EY2f5LYGn33w4ZpYTckPk8NUYWk57HDgw3N TW5urDhDvLPR5xXFgQ3nLiRWifQMsWA3jRFuzobMSd+R3ysMMNszWdtHnw3h t1o0OC4GmP86/OzzmWzwHh6bILfNwxr71x/I43YgLL4j1QiZhyT3vmcNvXbA vmHjt7pvLgYZZ+6yfmkHlKWRuVGLNNHJlXvglaMdLHv4st219kc0fDHH89RC O4h3GCo5Rqjj4/JytSCKHXQ06WY0HFLFkNL+GlNNOwjb75LR82UWPnzYF/1i kgXGO9NKP2ydiTpWp02K3rNAObW5o/3ZDFx4U+vu+qcs0LpqbV3hQUaa2CbU sJYFK/UKi7fVTcfP0arTOy6yQFKob6nDV8b8vCmxwH7LNrexu0qYPdUeprKg 0rKhfeTOpNR5gdeMExEs0PtJeYENc0JaSZ4qYCwosxZnll4elb741u+xIKht SZ/rtmHpo7bad0VsFrgt8QhieA5KE+XtoYzJgnU7Sv7hBHyWvp36fS4L8sLs tybn90t1u5dkKKuxQMnUQF4P+6Tf+lUlFvwXVODOKw== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNlgs0lOkfx6Vkl1pZZd2yyqAdzzs2jJkxt98Mim6G/umiJIquxKYiqU2S 3Q1R65JFGrmEXJJSm18s2cql0UUq69KVatW4ROI/0p7je573vOd7zvM+7+d8 z+/5Pc8cL3/XTcpKSkp5imfsnR6ek70nnI5KYzpoB32DbpW/pNDxyd36svpg Owjw0+stukzHHy8sOHkq0A402+X8Ny10HPjDN9Fnqx3ccelM4ymZo0Xc/OsW G+zgEr7UTf/BHB/HSjUG3OygkpqS991KcxxOwvCri+2gJ5HpduaoOUbnR8w+ KLQDsfJ+Hbtr5njylvyxyFLx/ZaW9/0D5qjRq1Y5iWYH0bFXfsvWJth8O3j1 HX07UNIxKO+ZT3A389YL0LIDdaXhkAYngs+o0e0SNTsodHRvsPcgaHZx1qtR JcX/3nHKJP4EefXfrHUeEMPNjwmW8lCCtN1d1YI3YgCfIBGJJNian21a3yEG yXxZ58djBHcEOYV9eiCG5+p1e+efJGg1phIxqN0N6nz6O8ENf7/4WZYlhshd bFpKIkH3pQYtASli8Hwzk7symeD3FY1czeNiiBaoz9NOIXjOUCWrMEIM2pv1 u5v/IDh5+2V9SYgYPmxxOJyWpuDJepP0r58YrO2j5FtOE9RoPD0nxlsMf/c/ Z7PPEPzr+b1ixiox5GfWVJjlfOGxEgOnpTRo8jmCSo9z4mVmYnjxYNTvbR7B ewm0OYEGYriYKj33soBgsc+ZR5qaYshgSM3fFxI84WhaVaQihoLIkbdqJQTD +PkPXIZE8DinpM+ylKC/A1v3/VsRzDtZJdxaRtDX80ZkXKcIfndi1BVeJugT vcbYqlkEUy3ZOu7X/8tHBJtmGSRcqyIY4NtwXJYlAuG5tUeoGoJJ1eW6gSki iJcPPsuqJZiztO+m5nEReL6Vl1K3CJ4eDcssihBB9qlF/dfqCB56tDLHJUQE 2z5+OuveSHBJ+4H77/xEkDX9m9rJTQRHZgyQOG8ReMhCVpfdI5i89c88y1Ui ONGa5lnS+l8+ItC4YxJzoJ3gmi2up2RmIrjYXvVu9VNFPdTVCAMNRBA5I+So +IWivjxijb7VFMGhdY7LOV0ELQzP84tVRJBTy3AVvCEI6sYJrkMAQy5UhEsP wWmmr4n8LcCuQbvXgXKCcX5qo/GdAPoVgZEZ/QSbnu6fzmwGME1N+lk4iULr z/kAPOafGYyZQuEFWmipLAvgofi+W78qhRnlO7IDUwD08i2TAtUpHOlVnaZ1 HCAj9BJO0aCwumlRW0kEgF+Rb13etxQOu9mYrAgBOLgYKrZqU5gadrOl30+x 3iLx7wI9CgsWqU5K8gbYfX6H6zxDCsmV1wncVQBnq5rETubUl3wAwKFKf5sF hZM37NJsMgN4tWBf/iUrCtvPLdPZZQCQXvtxYD6bwnqtyoXamgBeN+0/3udR WJNYn3ZZBcB6iVtZlojCxKCXcLVXCFrLfiTSBRSifFO8aqsQRhpkq28vplA5 bxZrxQ0hDN7hg5ELhR6pA+aZhUL4Td22zdWbQp/PEsLFUfaQcAuFGsb6N/Kc hRDwbJ+6zJ/CZ498ritzhFBxVXnm13sofBnrtGLzXCGkRdRpPQujcJa46tAT dSHMgMdqPpEU+v3b5OTVJwCt14zBX2Mp7Evcl9vfKoDsqOpWt2QKzwrKpcm1 AmjQSb9SI6UwvC2GvaxYAAvULeI06yj01l96n+EtgKa+aV9VPqDweuZrsd5S AUw3Mo/+sZ1CU507q9/ZCKAvKoq27hWF8YFDeheMBHDEat6thT0UTindfMRL TQCVBqqHevooDP1HP2VYzocCB1OnlUMUDr3TWnvoCR/sCyKMQj9RGPZaUiOv 4cMRN5Ov1o9S+HWDrEVSyIc3ziqKxsz4kg8ftPJiosNHFHl2smo7nPkwWsiw /UaxXsmjh9UtHD4UeXQop7+ncK9kyfplND6Ylua+ZL+kcIko5gRfgw9eFyK7 m1sU9ViQsSl7iAdea4PVD96k0DLhiCz6OQ/m5R9wZJRRKBy2fdQj40Hx2eSM znQKPZ9UHKiv4IFhrImRr6J+t1Z3CZtdeaBhuSLBuJvgH3Ph4HzgQRh957vm uwRxcjVNg+LB1uDdjEhFf2jYHEwF6PLgruHmZYwigrdc1iWvVOFBuZ6DS72i v124tnNbZQ8XjHZMZ/kmEYw6X5Je9IgLytrXRz8cV+x/mqmtSQ0XvGZ5ngtX 9Odhg1rW7EIu4I4ujupv5Es+XLjnN+4Hpc5DUmcutPmP++hOtmJwoXXnuDee OyYuNASM+4ue6orBhQuB435RWq9TWq8tHPtp3Lc+GZMtrNk17gMNbgQY3LAF vaBxP9W9UMW90BaW75nIYwu390zksYWOPRN5bCH2i6d95rGFB7sn8thCWdBE Hg5Y7prIw4EFgRN5OCD3n8jDgSyfiTwc6Ll0Por/C8GENZl/TZZwILt0dG/b YcV5VB5T5mHLgca1Lao9+whmHzYR7jHhgHeB0Ga74vyMLPdxX6rJgY25FlNW rCeY4b58WvsnNsgkuQG5iwn2+3a7WHazoeD0+bDt1gQj/mEQ0UM2fEgRmp/S Jbi0cvap6bVskOQFDz8wMMeifxdu2OzIhkHXE44/jdCxhN+x8T2LDd+50PpO d9Ix1OhO0zVTNuSe/UF54206qifOLKibyYbi5VL/y5fouF6aJzdUZgNj1Ql+ RjYdgx2SpMVvWWB0YXCboeL+smpfCx5tYcER37tDVDwdRxx2Op6uZoF3IK2r 8Rgdt2Su4Q6fZ8GS3leKfOhf8mHBPcsF+xOi6LhQ3m0cJ2GBp2zNQsdDdKw2 yLVO5LHglcwsUXc3Hf/pSE/cS2eBn3W+v/omOsY7NDpb6bHgfX9X3WxnOnba s9fUqrMgSK+9WGJNx8a25jLWqA30p8YYSmfScaVu8eafe21g9+H+GTo9P2DI 26rtmd02EOubHWYxxxTpDh0ZHG8bWCS14M47ZIK/sp1uzV1qAwUzHjuRThpG fWB1DNjYwJW8/FyuPQ1pEQUvLhnZwPa90nVumcbo3pr3aJOaDdT+hF6hU42R McXq2oicCbdTJ5Xn+87F1H6ICX/ChD2Dvt5dtXPwXOn9Zb01TLgZLvewpM/B /4l6hyWFTKjhS/MifjXC5KQxMWFGWVvusY7v8di6qyPB4UzYODflr8IKQxQS 16mpfkwI/zPk7K6C2VikMlaATPA7Gip5WGCAba/uDxc6MsEk/HRlK+pjY3N1 dxqLCTn5r4YPP9XDMJnZfpkZEwZVV4ze0tXDrrHpukz4Lq7z7xJPXdR+bh+p PI0JSktOruVd1hm/ryox4f895PzY "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNl2lUE+cagCkKroigiAJW2QlLlpmErIQ3iZVNZccFcAEFQVvQKioqiwu2 CCiKXtlBqaCi4tWKC9TXahUUF0QqpSxlkUsRAQFRQPCGJD/mO19OznMyM3m+ ZyaZxDgowmuTupqaWqv8MfGcd/BC0a6D1qg2MeJk0JNkWQ0aNqhVGfo+fY8M /lo4K7H2nA32Hrq4pWKbDALsA2s462yxgKyIPrpZBnv+nHt5A9cOrWvRoC1Q BsQ4W3+1LR0PhqW5vfCUweHL5TpGYgaW9Em1PJbIgL995QpfeyZeCa9at4kj g/2ekwPUG5gY94Yp0zaXQcqOtyy94yw040aWLp8jg7U6Rg+c77LwQd3Nezmz ZHDb/1hYy1sWnurXsbaYJoMcb0fzZm0C0w/FD7Wpy2DmsM2QhE/gixQN87pR KWgu822YFkSgvU7Or+qDUkhcdveNfSKB1TPcioLfSeHMSGBnxTUCs2Nmjo20 SIHp5zAL6wjMCmu9XvFGvv38+nKjIhJXVTSFLs2QQlr32+cpd0hM173QvDhN CuTrzX61T0hsDDnyJDBZChtfBPn01ZFo8sceq7HDUrBsqqlobicx1C5ueHy/ FGLUyq6f6yGxODfDIXinFELtDfVEQyQOGFYO0rZKoT32Q3fRKInCszMWeQdJ YbBBLOwaJ/EQEVTWtFIK0yWT5CeKjaRiSOE3oZL3v7KUT/l6uUp+vM1IPqXQ RChZV2diSMGZoWT/Eg35lMISWyX/4j5S4D4igWqaknt7JoYE+iyVzEtpk08J 5Fso+aBd3QG7Ogk0mlF8rksgRMX7JnwKJdBrquSKCZ8sCew0pfikSmDIhOJz WAJRJhSfaAkMGlN8fpBAhIr5Ez7BEuhcTPFZJQHTRdQ+Emj5ltpHAsQiah8J LFDtr8ijI4FUY2ofCWSbUvsAiCyofQAiaRSfNgB7O2ofADWRktmKPgC+QPEp BNBZQvHJAiCdqH0AbrlQ+wCcdVPyeUUfgP5lSu5T9AEoXE7tA3B/ObWP3NeN 2gegxJXaB2CuK7UPwGkX6vUDwKP6aACMOCvZNXfQJXfQERpU3Nw4MRyhScXb Jw732BG+Ue2vqTiAI4ypOEQxHCFJ9f7DBRMLdIRUlW/yRF6eI2ir1mOiGI6g 7q7km+tnyKcjRHhSfcTg5aPkJoWPGK6sVLJieY/FEOevZA2FjxiGwqg+YhD+ oOTPCh8xqG1XsuJ088TgtFPJpgofMUzfTfURg3u0kt0UPg4wZx/VxwH89lP7 OIBBDLWPAwTHUH0cICyG2scBomOoPg5wIobq4wDXYqg+DlCvYheFjwhmxlJ9 RLAkluojgoRYqo8I4uKUHKrwEUGFikcUPiKYFk/1EYFjPNVHBOHxVB8RJMZT z5cQzsVTfYRQEk/1EcKNeKqPEE7GU/sIoWpXuNjqGznXzHcP8RDCiTW5w3mT 2SjJDmzpFArhLe0sK3w6G4cesBf2WAkB327vOKjLxgNOOepR+kKwStGZ32PE xi7LjNS4KUIwNI15VERjo/UmqydawwJIL7j14TqPjbKvzsULuwVQoHs/XduV jdyhUW7JPwKwSfOO3bKDgz6u0t+YAQLQPxAW3JLNwU7f+40nnQQQrz+rw7Cc g5N7/XfcJAQQ6iOZYviKgxf0dA+cWSiAx7xJj5saOFhT2aYpmCqAcw+9zUMb OZgwo1o9s58PY58Ikxs1HMT6v3bebeDDy1d55X/c42Acd3xd5iM+GPtmf8rM 5+ATY/F9QQkfbJw+HPe5ysZ/voztKWLz4eTqFcEHzsi/P5JtM1da8eFvw9ux 9QfY+F+NIM8qAz6opbA6An6Qfx425WRpzuTD16ulp6f5szHjUss+zS88aIp3 S/3HmY1Rf9n0P+3iQdak97UtXDae7tn3xa+OB/acrI1aVmwc63qdWfiQB1fm rXYIXsDGC8/Jl+VXefDTxyLN6E4SB6v9xFx/HnzDsvX3aSTRLFPr7vOlPPjl cs/OjlckTvF5cngRwYMft/T5MStJzPySlENbyIPQcNY4C0lsTvPVeD+FBwkX r215V0pirZHZnbB+Ljy32ZYbUELivrTPZbkNXHDsiUg/fEH++ugrrWOPuFD/ 4fLqkHPy/b2uF3NLuHBOUPWs4ASpun64kPapNUgjmcQL2i1L+9y5UBb8foU4 gUS3lBicLeCCfuy7VPcYObeKax6bcaHApdGGv5PEohkmsXqzuRDy4Hej0XAS N063ejg8ag8B3ZkbT60jMa7J4+yOTntIeLh50lRvEj8fyVqQUGsP7W60Ya/v SHyhOcOa/sAe4ryzti4aJFQ+cn7a3dbYTKC71r+0x+72sCr5pfPKpwR2HMpZ tpVvD1PSnTKP3iTQ5lnCc19Te0jq8fw7Op9Ag478qwe17KEzuXeqeRKBN1/0 9n78xAHDXYvNEqMIHP858lhxKwfMLrbbXlxP4MBcs5TCZxzQsBSZHnYlMC1y enfHLQ7g7aqHcXUs/LdYv6zckwMeYcWLLz9koUQ7zsnLkQOW2lH3t19j4ftB T4eNthyQXKIVVuew8F1gcvbAfA7kOzyurkxiocCV2KymwYGlj1ZI/PeysOE2 ZCf2sYHxHX48HM7Cl8W3RCf+ZsPaO4a9LmtYOM80Y6n+Iza8Mt9gV+jKwqtG b+8sKGFD1CrpHzsMWKo+bMhPK7VKncHCo+OOxffd2bDt2PMp678w8bXLiK8f nw1tzkeCWrqZKHE+FWxmyoaP2MLTa2Tii+HZtTZabLj0qTFxtIqJsWu/v7j1 EwmT3+9dlVbGRJ+oi20dLSSM5d3Nb77ExGWSiriMKhIy5mSHNGYwMfTeo/gj pSQM7O61fOrHVPmQsG6NEWeTjInGS9f/0uZOgm8oXZrAYKLN5r2CJj4Jb3LN 3emGTDxUVWruZ0ZC6yT1gEBNJtJ+1At10yahz+JItUUrA78NSBsvHyGAyH7d lXeTgeuPsLsvdxDwU3j3JFoiA/sHPzIMawj4mPLc6F4AA6sL6io1kICTzn+2 G+yhq3wIKD90qf6hWM7NB7xfuxNQ2b8+uWsSHeGZxkAen4CSE0NfjlbYYT+j d0mVKQG7N26lXUiyw71THF38ZhFgtPl3XamHHTZ5f/wqHmZBXvbnW35z7NBA TzcsoZ0F6hraRv+rtUW626lDti9ZIMvREA38xxYNh2K8WGUsUNtxfnHFQRuV DwvOR4TQL/Nt8LPFpcFIDxb06Hb86dFjjYffnd81R8SC+kBzg+v51jjzxure 5TQWhHiYfa7xtsbjcQ/8F89nwemu1sjrk61Ry7O9LHEqCzbbbjjkeYOGCeZl uskjTKjXyyWuBNFwdMw10LKHCR/OZ+2t1KbhlvrjWavbmJAQ8TbpYowpev0q 8dL2ZQL3EZfuhiaoX1qe8kHCBP97bp8N1U1wK62REUJnwsAa43dGS4zRe2Ye 53sDJnw5c0tzRcJirFynmaepyYTBfpPTa1MX4VmnxU0bWxlQ+3llZPy8b/F1 SfR3LaUMyJDNzpqcZYQWo4ZRB5IY4FzjtqDT2BCzLCZHOq9nQH3h9E6bogWq 32MMWPS17bwRfz4uuLt7bECTAe3zIgY1m+fh/lUFM0WNdLDpvfSyK10PN0zc Pm/SoedIhrAibC5izeXhDal0IFoEnNwVczD32tE3jhF0GBpJKo9w1lXdn+kg qD3+mr9SB19PbE7QYTxiafRY9Gy0qfp5lsZ8OsSd9g/cGaqt/D+oRof/A7QD ygY= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-22.000000000790465`, 40.}, {-1.8733706994324848`, 39.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJwlkmtIk2EUx+c0ryHaZVSirTQvdCFR3vd9RubpeYLwS9FFM00rY2ioOFOT ZsoyFEGJyj6s0uWsEDXJCyXmyrMWUqbNJC9liQ2V1Dk0cWm3tdUPzvl/+R/O l9+WlKwjcrFIJNpmH0dK5c72zaHoH/uhRNOWWraGw6WKJN2fFQZF/RrBJYTD 8puX6xIXGXj+fHk+J4pDgyRDLzEzCAoIlgzFcqhe6++5e4LBAHmxdYeCQx/H wSgDn4O31HkVHIYWDoQUDjAYT2jMb23gcHx66FfzKwb7Ti93mXo4lL3Tithz BpHJqmzXOQ4jHLQxcAu/VxDuwyOXpC/7XMfA4zH25Ufw+KiqeKm6ioFsZiT1 QxyPmoULF3OvM1D3z8bEKXm0JWrWnSllEJy2kmOp5nFwdLn7bAEDU7PTlFbP 4+bs0muXFAx6G1xqFJM8jvkdyG6UM5iKFdcmeAjo+0l2bj6BwbO3bp1Wo2D/ r627ImXwZlWKIfCrgNr2nknvjQwM9X7pRTYBhTDiFuTLQPM0stVVQvB7i9nL 4M7glNCk1m0nOHZ4cnHWRsE1sCSgBgha3AO7NFYKN5Q61nKMYOjwg8xRMwWX 6KPu86kEy3WZNq2JQpIiJuOkkuCGDmXut2EKt73vZlnLCfb1OqCQEjXh3FRF sHtXsk2np3BCWr8p6yFBqSTM+VA7BVX7XNueToIfi3eOFDdReC9uNa5/TXAh N70o/j6FeLE188cgwTSzacl4h8LqJx1XZ74QjJ6u3DtdScHi/zt8ykwwz1Gv oCCS4fE5K0GvnFrmVEoBPB3+yP77o6LwF5y/FK8= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxVlntQVFUcx/FBhpCKNRSIhpD4YuEu7NW77Ot770V8gIBIo4iPFQERBUNT UVkVH1iZOj7KF6IlD988TFBs6EQWmpLmA0gHUhGHlNAUSlCx3XvvOIff3N2d z8zO2c/5nPPHDo5dGBnf3c7Obq/1Zfv0iO9hfR9F7KQJwpKLiSezn7FEV+w/ 5Uq7CK8zBUP0jSzJG17dP/upCG91bXztDZaYEh76L3goYrXmXsriCpb0TFxY qr0rwreiCu+cZMlz3/iDb9WIYG/tvZ27iyVu5y79fe2SiO3p402G1SxJcjp0 IPsHEWOO/DH/ehxLmjwfnZ5XLCLcHDI7cRxLdnYeYjQ5It4rmdprlJYlPh+l +rfvE5FWcnBG1UiWROxsmjdrh4j02V5xvh4ssQ/vXZPwhYhBpXfcol1YIkZV L++bIWJWaW3GxD4scc4JjYxeJsIY67jH8W2WLDAmm4OSRZSXppl39GBJlBeX czVWRF2pR+19O5b8GnliYOcUESWxtj4s0QTYRsQ1hS3XhlofEX3myHwh1b0y 1V3EPIX7O9tGRIPC0wvtYwrtRayMkzk3vCMnvEOAJl7mJy22EdA7QWbtlgZu S4OAbnNlXqeqXauqFXA0SWZJ55SAxPkyp9t88gXEKFxp88kSkJFE+WwTcCtR 5hibzwYBCQmUzwoB3orvY5tOigC3WZTPHAHCNMpnqoCeYymfAAERPN1HQJie 8nEX8Go03cfqq6F87AXMV9N9eIz0o3xaeGSpZOakPjzKfeg+PJ740H14uKvo PjzCVNR5ZfHIVNF9ePyoovvw6OZL9+Exxpfuw2OrL92HR50v3cfq40f34ZHC 0H14CGq6D48Ef5mlPM486gPoPjwOs3Qf4OfRdB9gVCB9f4AOPd0HMI+l7vMp IH4C5ZMPPA2l7w/gEE73AfIj6D7Ab5NkzpP6AKsjqfucApyJpPsAKyPpPsDR cLoPUBlG9wE6J9J9gEkT6fsDlIfSfYBghSccaB1/oNWEphCZ/6yzjQl5Ci+y LVdpgkXht6QFTPhE4QRpTChQuD3HtkET5ivrb7bl5Uw4rPh4SmOCWdlPidnR +pjw9STax4iQKJnrJR8jVk2RWdpepRF+MTLbSz5GTJ5H+xixJlnm55KPEf6p MkvHzRkR/6nMXpKPEe8vo32MmLhc5hDJx4CeK2kfA/TpdB8D/kun+xigstA+ Bgy30H0MGGahfQzwttA+BnhZaB8DPBQeL/no37Dso8dAC+2jh7uF9tHDReG5 ko8ergp3SD76N78v++hh6OKjx4wuPnpkWujz0uFsFx8d2rr46KBbRfvoELya 7qPD9RN7F1R2asiAY2XndkZYmTMXD3yhIS4v7+/4Vm/9vkfU793bNOTj6MaW rSN0GBG39OLSZg2prjh3ebqbDhk9K/cuv6shWVyiysFJh5BuwWMcb2hIftnD fl+9DkTmtGcXRp7XkLZx4jK7tkCM6ndlyO0iDdnYkGoOaQ5E30v15Ru+U5MZ G0bszh8YiKb9mzqKs9Tk9cHPjoxwCcTMe+3OUzPVZN16c9Ndp0As2j3cfkmq mjzwK46q6haIwcTthsNMNRl2yNLS3KpFSnTVKpdQNQmtrziNB1pMiePt9+nU JOJuxtELN7Wou7N07i4fNfE/XnZ5/U9a2F1JznX8UE3+NSa7Lymwcp7xamo7 o/TRIj6tr7NrC0Mmf39qRm64FivKw8+X32PIM1wc0MhpYUx7/VdsDUOE1ryD Qzy1KModtNb+MkOCqkObExy1uB584ss8wpD2B2Wdh1s55MQccwg+zRCz9z81 j+o4eN3/oL3hCEPSdj5e5lfJIfJO27Q12db11CX1iws5MBGC34AdDCl/GeR0 dg8HcdOL7a83MuRCQEXN9nUcfnnVkp9pYUhwzgqnohQOZ/LdUwoXM0QTlnL0 3RgOrp+vb0xPYsg29f6isnEcmr7x7tM8myGzwnp55o3mMOxp96ZX0QzJzjn+ 4uZQDtXLXRcXRzIkTLPZOMGVQyuXVOAQypCFrw4/7O7EYY1fW1aPYEb5P8bh f7BFh7I= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNlntQlOUexxF2Ybk1Lr07uyCmooKjoKDgu/f9vu+rqxQEJnM0IEXlEslR MC+NqIAEXQ+B5hxvgShC5Q0VFTPpSTiBBjaicVaSNOyQHifAwkzDsd33Ycbn N3uZzz/Pfvbz/HZmJyxf/UqGu5ub2wHn0/U+PsPD+TqbuMkzB5vuV2bcCo8h P/aEe2Q9kjDpac+ineOiSaSj6cLwoAR1GekKc8wkD/pPWb/uk2CvtPeW/SOK TA0J2NDQLaF06a2h3TEzyLW8qyu72iUElGy0tsZOI4M9j4LDzkuYdiSlev/d UFKQWfJ+7SEJXf8tHhuhCSGFvusbknZKGOvTl9GxM5A8aP92d1SxhIllbUGj pEDS4jcc+XORBJ/XihxxD3Uks/9SUlaBhM71o6vqT+lId57e81y+hPwf1q0K 36Ij4/49Z+7N9RIUHxy3k0Qd4ZcMqK/lSsgtaQ7LidCRkFZ9zq5sCV9cOqSO 5HSk58r4pBnLJPyS/IbCT6kjOVvqLu5YJMGff+ocLYme5RoJh0d4c2eY8yGh XE+5LS+4NS9YQqOBcoDaNU5/E+XUemVKvVLCNTPlgwmPaxIei7hopTzY7xoR 7gJlQ9ltfdltEQUS5eIIx9YIhwgSR1nWOSkiKJHyJpdPnYjlSZRbXT57Rex6 lfGpEPHlUsopLp8SER2ZjM9GEe2rKA+4dFaJaNzA+KwQsb2I8VksovYg4zNL RO8xto+I4EbGJ1jEgia2j4itFxgfpYj6FraPgO4WxqdfgFszZb3cR0DIV2wf AeQzto+A6TVsHwFiNXNfewU82cf2EZB8gO0jIPVTto8ART3bR8CCL9g+Aua0 sn0E9A2zfQR0+bl+Z7qRPgJuBFGmfQT0h1KW86gFcFGUaR8BsQbKtA9QYaNM +wB3Jcp0f4CFdsq0D3ByLmV5n08CsfGMTx3glcH47AV+/ZAy7QP82cL4lADh /qNkrpX7AKUZlOV9XgWoLo965rMCqLe7P/NZDBRqFDLTPsBzlQqmD/CHRsn0 AaI3K5/5qIG2q0qmD9AQ6Cnzi1VDsVVDNjx8mfLNHtfYsO1Nymtcx7Xa8PY7 lD3lA2xYW0A5Ux4bUidXVOUMa8ma5IMtHok2hE+I2nLivpbknv3ozBKjDbfX 9O25clNLlhVPtm2YbENh0PE/L36jJWJjZkq82gYvXcXHe2q1hFu80O+nJ1as XVm62l6gJdeX31sw854VbVzFe5cStaTMMT1cuG6FkjveGzZGS2afHbvHv80K x+TQkuoJGjLzr3nLXp9vRfbGlLGOnzlyyd6b/htvxW8b8tfHHOPImrArV5tC nee/UFp+tpAjUz7hjnZwVtz5Z/7K9Fc5cq/u8O8vuFuRlJniNdvAkaZ5u2pO 9Ftwxis0ffp4juzb1E3e7bZg9Cs/FMU/x5Eye+786v9YkDY3P227h5MPJpuG j1mQ/JWrNzfSx4KqU5Qf1bgWwILB05Tl9dNbENdMeWKIayyo76Z8Os3X+bBg 3BPKsfJ9mbFzqqfMP8r3ZcaYFZTpfZnxWS1lel9mFJ7wkjlL9jFjtFIl82PZ x4x3klSMjxl39qkYHzMi/q9ifMxIifSWme6PCavf9GZ8TMg56c34mJAw6M34 mFD7qQ/Tx4Rz3T5MHxM2u/kyPibcC/RlfExQhvkyPia0jzD1MQLBvoyPEWkK X8bHiIhbPoyPEbujWR8j7j/2ZnyMWHLOm/Ex4sY6ypNkHyNypnozPkb4XVcx PgZcKFIxPga8O0nF+Biw/GsvxseAWRmejI8Bl58qmfsyoLGO8keyjwGDqZRl nRAD1o1j98cA+4CC8dEjq13B+Ojx/WkF46NHxVEF46NHX4eC8dFD9fGTsjB3 jmzL3tPZnKBHwHe/mCpVHBl6kDWwxKCHe0GzZ/rzHCn1bf+Sn+g8/0D5wFsh zs//vNX4sr8e5ZaEP27EcETsTM7e/5BHZNzToPJ4juQUl8yP7uVx6rt9r23L 5kjb+XkOjw4e49tmNd1+jyOLiqp16kYeeTGN5rePckR3eZt36gEe23+9M8X/ Bkd6io+oIz/g0aD7XzTx1JAdHZ05JWt55/c7nPbJdA2xHnIfk7qUx1Cr7XDN Qg1xBFuCG17iERBXqe1apyHpIVtz/2XgMUNq2x+1Q0N+OndFe2cKjxePnI8/ c1xDEu9OC2gJ5JH5/hZd1rcacuzz8qUT/HgUdvt4CL2akf+HPP4GIX1Ctw== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxVlgtQVNcdh3dANCo2+BiMiq0RUdNJzAK7d+++f/deHstrIdoquloUURQj 0fooumsaQkhiRaszmEYlmpi0WouIEomxMXMyItJgYjUdZRB5hGjNmoBaoLAC 6e7d0/afM/uYb3bvme9899w79+ncl+avCtFoNJX+d+B7xqpQ/6fANOpIQBjn 3rJlnwwPKPDmBXlXefEx178UfMH5YuSLn0V+p+AE57cnTh+j/UbB65wjAgfc UpDDee6O63N2XFcgcG7/9sZgdYOCMZxN197TKJ8qaF4Z5PjAqFFQydkTOPyY ghLO9RujLm+s8M/PecJ4/9inwMZ5aXWYq7pUQTTnP2X6PsjcrmAc5wdd/lGo YDA3yMY9neKelQq6OJc81/Tqc9l+H846VUhBB2d1OXMUjOLzNQR8ohQ4qM94 Be9TnzAF0/h6/xjw8cmoziM+XTKWryI+nTKeXU18mmRY1tI+MkYX0D4y3uR8 We0j46MC2kdGOWeX2kfGrALis11GLp+/W+0jI2sN7SOji/pky5i0gvjEy0AO 7SPDs4z4RMm45KJ9ZExdQnzCZLycTftI6F5IfLokFP4yyKLaR4JvAe0jwZNJ +0iIdtI+ElrSyfmqkHA0jfaRsCWV9pGQnUL7SEh10D5+TqZ9JCxOon0k/E6h fSRck2kfCTky7SNBx1nNM15Cukz7SKiUaR/gBYX2ASwJdP8AhYm0D+BJJfu5 BhhIIz7HAGsG3T9AipP2AaZk0j7AmUx6fQHjs+j1BQhZtA8QnUX7AF4n7QOU Omkf4Hkn7QN8k0H3D3A0g/bxr5dz6pGelCM9diRwbrsdGHbM5fzrwHSX7Yjk PFKdwI4IzqvVYUc654EPAgu0Q8N9dgfyinb8nK9/pjrsaOTrq10+1v+yo3M+ 9bFhM9+/raqPDR6+39XlXbbBx6+PMNXHhuVrqY8NC9cHuV/1seGrDUFWT7do Q9OmIEerPjbkbaU+NhQVBTlN9bFi0nbqY4Xgpn2s6HDTPlYMuamPFT1u2seK Ljf1seI7N/WxwuumPlZ8zzlF9bHgkZv6WDDwIx8LQj3UxwIt53zVxwILZ5/q Y0Gih/pYkOqhPv/noI8FDg89X2bIHupjhuChPmbM/ZGP+X/rC/YxY9+qv+0c 9nPG74c/mZFlxoczp83xhQqspazn7esmM16o6b/56An/fs5x+NyzzcibnFtx 70mBfR/ma4+aaMZD56LNt54S2Ibi0RlnNWb0L27KaYwW2MFrW22J3SYUiXd+ dU4rsHV90tkrrSZs8O7YeNQusM7ugtNpV00Y2lted+jif31MqPtne1nMbYEV bzkjD2ea4KoNP/pFt8AqY+pOOUwmfDY4eUT5Y4Hd23roZGKMCb3nQ2qKNAam XStaeiNM6H9wpco9LLA3Bw+6Fg0Z0XB4678regX2UHtx7IteI9bU/VDWckdg a0aeTo9vMuLGijUvma4KrMuT99OT9UYscpz5vPyEnhVva33LEWfE06eufXS3 XM/aLjan/2a2EecK8q/seUXPhPx1+5dOMeIp96Yndq/Xs9KVezf0jzFCbu9d 1+HSs4ZzKa2pj0WIB7v6dqXp2Yj8P7Qu8IoYOL7sz2UW//GF2zZObBLxWrhS 0jlPz5Z/2f3WzjoRzXWHX9s7U89efcPnrD0l4u6eqrMujZ73ETHf+XLHgl4d C7nwoHNFloh907+633ZPx2qUC7qbZhHvDFb+44dmHdvsa8yunyui6P7YippG HUvuiMp6frKIGG+39Pi8js3rPzV1wigR7/Zn1984rmOz7aXnCvsN8EYmP5O0 X8e0tRXPJN43YETi+YKUV3QsfVnf+v1tBkT8QlvRa41nE0bNnPHbJQa8fz1m 6YPweNYXIUjWJAM+VkYvDW+JYxZn8azqWAOyjjUfSvlLHGv/NPTzm1EGFAwd mHZ8exy7k3sh9sNRBoQlJd+akxrHUk1VrsRHAmYVf93cMCWO/STxRvKuFgGX qtZN3fVtLIsr0feV1gu49+XXBwo/jmW1PY2r9dUCdnckL960M5YdPBAYAk7+ fWjL7SWxLPB4uK1EgP31/HEP58Uy+7PzRx4uFOAIKf1ZVVgsO63ewASwhIWV k9q0wec9h//4jFs1s/6qZVebLt0/YhAwbvokofWAlt/vBbSf0cRLbi3zBv4+ RcDsJ987kZGjZZF3E94ICff/HttbEZqk5c+rAv4D0wT8CA== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxVlgtUE2cahhEBqyLegCLSrdqoQBEQksxMJoQ3iVVK1wuKogiCqFQBRQUT vCB4F7UiVm2lXUEFy2UFvBda6WctkGLFFhHQitBSQRQRrXhBxQ1Jzu7sd/5M znMyZ84zz/znZEZHxM5cYm5mZlaq//R+j1rSV3+UkplhJiG5ZkLZ4HFS4gcc vln6Uo0f7/2jps8sKWWlxDqFPFGj+WitW+12Kck3btHVtalx923gtT2XpNTT WtMwsUkNnXn6d2P7MtRRvigk6oYau/KyH2d+wpD1SM9Jm35Ww+25dlVPOkNB f3EHNd+rUXRvCK94zNC1MZum+xeoYZu0clr4NJbiay3jXh9R489T460GJbA0 TNTvl5tfqKEVp3816ShLipikMGafGletdDb9Kll6VrBigt1ONdqcT4UFPmGJ a6+RxCWpUZ4+e6+bI0cDRKcTAjRqLA05l56q5GjpHKtnhTFqVC3/dWviUo5m bvnt5N4INV5Wnfjns70cVeYNz3wYpEZN4cCghSIZ+WHzBOWHakjPdvS4TpLR 60ZpyO7RahwYvdu8aJGMnF40Bxx/V437z5sWdm6WUe7OFJuUQWqwTKdT+1EZ HU0bv1/eV43kxm+9j5OMLIaX3r74QoXLnbITdo0yumE9tcO6Q4WeKE28+o2M hibVlLs0q+A1LfqI20ieipcFRtrWq3D7WMDItgKeHlt4Ok3KUKExNqjt4Q88 tQ1+GTXsSxVO1n8z7kkVT9eyPIsj9qng36C63vU7T0cu11pJdqpwKtH50YsW noJjHsxKSVKhqXjuulePeDLLWJEZptFz2vX4N8942j8/vP1CjAo5lofv9Lzi acgxYvZHqOBrl3vhbQ9Pa1enbu4IUiH5VO/+kZO3YVQIzTdyYvV4/VIh8oSR K1Y56ZcKR44ZedjQ3lHBLNPI84ss9UuFvUeMnD29O2t6txL+Jn7U0TtKeGYY md3brF9KTD5q5C0T6jdPqFfC9aTA54wS84uMvKHX5xsl/E4bWdfr87USD04L fNL01zst8NmmRHCRwGedEqKTAp8VSuTkGJnr9VmkxF/HBD5zldi1S9hHialb hH2U6N4g7KNEqtbIhjxDlRgYJ+yjRGyssA9wMUbYB3gSJfBpBoZECfsArtFG Fhv6APnRAp9vAMQIfL4G7sYI+wDpy4V9gAUrjHzC0AeQmPw6DX2A91YK+wC2 q4R9gC3xwj7AtjXCPkC0RtgHkGqF+wf4UyvsA8QlGNk/4+nHGU990WLixobe 8YVirZFX916uwhcJJrYyXMAXJSaONIwvykz8Mqv3Bn1xxcSf9eZlffGLiccY xhc/mfh8+ED98sWFtUIfBY6b+I7BR4GdJjbcXoUCS01safBRoClB6KPAeRO/ MPgosMfEhsfNKrDYxB8YfBSQJwh9FLAz8ScGHx90aIU+PtBphX18kKUV9vGB p1bo4wMbrbCPD/7WCH180KAR+vigUiP08UGpiT82+MhxXiP0keOMRujzv9+N PnLUmPhTg48cLSbuNvjIMUAr9JFDrRX6yLFTK/SR/3c/GZ8Xj2kJQh8eVxKE PjyC/2//8NCsF/bhcT03f4TFW56+uDQ75r0ZPNK9syKHvOap75yAOWUyHpUO D1tEz3nK+2CeaME4HuHztqcrO3na5bq8tnUYj7Cu2E2RrTydiPosJsKMh649 96vPb/P0qrm45WqHDId9xW26a/rzDz2Z5HpHhuqHNlFWl3iavZnZoa2SYU7e gXovJU9+l6zdHSJlGHPcmRs+lqcAr3S3T6fLkGi126XrHZ7KnhfLz7IyLK75 Lre+XUZZQ2MWvB0tQ531d8UXf5XRg6SiNL+BMtQX7pyXdVZGmaodtalPOSy9 KErZ86WMSud1ut1o4LBVkuqn2aD/vyx7cMChgoO7g+6LheEykm9baxNcxOHe douS5jccLX4uOrs1nIN43Vjzjc0cXc4+4//Wn4N0+1d92Z85co4vOxMo4dCR F1k6tJCjgxHBj7a+z2HOve1eAw9yZLFq9ZvU/hziFK/DROs5SswYdGfN3ywm nyyfHLqQo+6HH6ZJG1j8LG5pOTeFo6SQq/bV5Sz63giGuztH/R88XuFXxOJX l/sT6HfW9LxY3GgKsw/+kaWFjRMDzk1nEby+vrMuhyWPq5faRByL0JezLnKp LF3xsPc8N4bFreDq9UlrWJL28xBFWrO4mTHLLXe+/v1llnU584xBoK6u6ryS pWTbAjvXJgZTaxYsyhnPUoi/7XCfSgY/Xb7XljiIpXe6FKUrzzKYEXe4eVsB Y/JhUHq6yyl2P0Mlq6Otp81gECHvfz5zDUP7HHNqd/AM2CE1BY5zGWoNdSob 7swA7nP6NXAMlcp1dY/tGGw4lPpDqyND9hfybcZYMmj3S66TvZJS5y/ly7K6 pNj3kfP02ltS+njjiLaEViki9+wYV1IsJdGV43sybklRXTIitM9xMTndinO4 7SGFxZ85K9s3iSnR5fN3PhNJERtYXXFooZjMD4q4u+9KYT3sUISZSkz/dnLO +6u/FE2OT+HygZjW0r/m7+6W4P6K9oihlmKKTt429WabBM42SbpvW70pOaQx qapOgq9f5K96/4o3lQTmP4n6SYIp7nELPir0JodlbdkFhRKUZF/81HKut6mP BCuvzx3YKvcm+7NR5qEzJDg2+GqA+WhvshyVXXCZl2BasCMfZOFNnnl20enO Eqw+g4q7LV50cOb3zB/2EgwbiWcndV7Ejjhs+6WVBB+mOegKc73Itie/zw/P xSi1q5Q/SPEi9z5dPbPvi3ElJzAwfJkXbRkTbx16R4yZ/t/aDPbTnx/h4lpz XQx72/ns6OqJNGBssuWGU2KkWS/ZsG7JROoekvx5XZoY5F17y9F8IrWOdalp iRcjO6VglnmOJ11dtL4iN1gMX5uOFs8gTyqo1CwfpRYj9dKBAycGe9Ku4JHl /u5iOE/5qLj8mAdFDF/2m7OTGJlLPTZWsR4k7gpLLbEWI7m1Vbv4D3fT+7wY /wHIL8+W "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxVlwlUE9cax5FFaaBQwCKLxSooixIhCVlmJvAlEUHBxrXiimjZZJN9UcGC ilWxaisUihtVUKgKFClq0c+GVUVRKQJCURAroCgWCaiPvpDkPaffuZM5v3Mm 9/7ufyb3TqZvjFjqr6mhodGoOMbPn/trKT65qKGsebBr66JOR1cupqUyN2eO SsBJTL7ZtJeLNZur118elMDUS7dEeU+4WFdR1RHyTAILH02ofubNw52hc/4q 7JDA5V/bknkyHk7Y/T4p/q4Ewt1WRhzw4COl45J9VyaBgPj4zBetfOT0/SG6 VCaBY77k0PIkAfZxOmOYpyRgMZK3p8qOQN+exSznwxK4vyWr9JiUQEeu/2Bl hgQm35i5pSaWQIsoS/2kPRJo1/riOvkjgbOyo1P9UyVgb/VJ/tg1Ar2Lwpbv 2CqBMbNQK8MnBB4+81HqjWgJ+Az5OYRNInHooIfevBAJEMWD9WYOJMZ8Zfvq uZ8E8rwt/2PkTaKx9Vmn6pUSuDfRdOOBJyRuNK3o/tFaAgvc7viZvCNxf7Bf +w5LCcha9I3/+ITCiG+0PbVMJCC5fzvq/kwKGXEnZ1kzJFDD/HSnAUHhurn8 hEcaEvDq73TfvYjCoIt1FCkXQ7Pu3ApiA4VM3WUx7Bdi+Cpd8+HsKAoLbR9Y 1XeJQR6w+vyqNAofmayg3j8Qw3vmlAXa1RQ2vbENaDsrBsnwzrX+dykMi4h/ HHFCDEJZc86Sdgpf+fd63MgUQ98Rfe36HgpXt27P7t0vBs/wWT/cfEHh2XpO c0OqGHy8bVauGqKwi2swFpcgBguniaKoUQonTGcY9YSJIcP81grT/1Cou8fO 0GyTGEp14464/0OhPCR4xNBH4d83/vwIka0sMbzrUvH2e7aKJgaDdhXXRk5V NDEYNavY2Gi8FPNpVPGaYh1FE0PTLRWflr49JX0rgpx6Fb8cGC8ReNeqmH+g W9FE0F+t4jTHllTHFhEkVdN8fhGBjpq3jfsUiCBPpuK6cZ9cESy7TvM5JILJ V2k+u0TQd4nmkySC+2U0n3ARNJxXsWDcZ5MI2gpoPj4i4GbQ81GMt4uejwg2 JtPzEcHqBBUr4zESARVNz0cE+hH0fADqQuj5AIQH03y6AbSC6PkAhAaqmKPM ByA+kOZTAFAcSPPJBTALoucDcCaIng+Av3q8fGU+AIs3q/iVMh+AwBB6PgBF ofR8ANIj6fkADEfR8wEQxtDzAfCJpT8/AB5x9HwA9ONVvPD40ILjQ26Qr+bO jvFyA1N1vlHj3dW6wRo1T1R24Abb1BygLDf4Ws2jp8Yn6Ab71ZwxHi/fDXLU PENZblCo5vINeormBtcS6D6u0KLmP5U+rvC3mpXTq3UFk0QV6yh9XGFvIt3H FYrUPKL0cQWZmpW3m+8KzWq2Vvq4Qnsi3ecDeyl9hNCUSPcRQlUiPR/h/8dT 5SME7r98hDA1kZ7PB1b5fLhe5SOEgH/5CKFYzQuUPhQYJdF9KNiXRPehwGor 3YeCgO0qDlT6UGCo/j29VfpQkJtM96HAIIXuQ4FfCt2HgpwU+v0ioTyF7vOB VT4kZKfQfUjAZHo+JCQz4lLjFOulpexgnkxKwvzzDR+1KdbTyWuFc9cLSDDf zMh0eEfhEudQfa41CUPCObZBcgrviD8jvD4m4aE9u/LwawoPH1xccVROwE3H aT6FzynMspiY7thFQPWCV/LzivW985Ew/+0tAm5sz8890UFhSLf8U50KAnas /q2r71dK7UPA9jKtl5PPUdj7Is3oipQA7fBrhQMnKfSaxOgnBQSYpL/8NCGT wgOlI6+fzSCg8J/vnEr2UvjzS6n97/qK/h/8/DY7WbE/XTU8UDssgBhDIoal 2K/2TONPH30kgPx88miSP4XzjOu7vrwpAL+jJbFRPgq/zN/vPboogGVLfb31 Zv3PRwC9yRFUyBQKW699sqNSqvj+5aPXd+tSqC8VnnYXCGCfTt/DdaMkvjd5 /sfYDAFk+i7f96qXxEKDz4x79QVQV9d+x7WNRDO3xlXacj58Lko763mDRPfT OucWP+bDiToPM4PLJDqJKvVu3+SDh6/D1G/PkthmLI/dVs4HizzmkrBgUu3D B6ng3BGNlSRuW8Nm1Ej5sEyW1blwHonHKmsbAgV8mAkDTG9nEqv2W5d4WfNB dqE4TduKxNd188siP+YD07izI5pBol2U84NWOQ8CAhOFOcMEBuzpNt/ZxYPQ Cyl58V0EFuqt27algQeufYP6+rcJHH53dOxYBQ8cdlRNCU0i1D48qJJ42+lt IvBKelhsk5QH0913vPPxUrzPhBcnnRTwQLxzw6EVbAKfW8yNa7DmwecTXvRq WBJYs7830MeAB3hlps4aTQJtqjql4lEu2JQxujf1ClD7uhFz3xMuePb9mGbZ KED/tBRNdiMX5q5vffp1uQA99ewbBL9xofzMrM4CiUDtwwVjG23eoI0AjWqS zLukXJg0RJX16wjweWAPo0XAhYNmd7/MesrHUa98wtOGCz8fQquhGj6yoirP sAy5sN5XT1+zgI+5bQ4rst66wKmvS6yu7+Yjd9eAW9xTF0geKf3SOYCPY5G6 wXfuucCAzLBsqTsf5ScSGvOuuYDj7bgc2Sme2scFDJJ2nw3aysOfzDUvrVjs As9SOhzSl/BQUK75TT7pAr90brWaZsvDmVRQs4+dC0Rn++10es/FgCLWyVBT F7A7d2DtlUYujmlt7H2s4wJNFloF105xsc99+HzFMAeiuq5uEiZwkRn5cvDV Mw5M0v79MMeLi7W7FpXubecAQ2wXmWrLQVltxxc+GzgwW3f6T9/UsfG73Mvc 9oUc4OeWXM0OZqNVfVKLwIUD7LFWWSmDjcGLrDiR0zhgyswpbSpiYbj96QWp H3GgZ/brvf94s9BpnaF52N9sOCF/7M0ecMbiZ2vznDvYMP9Q8EjEt874/GZG z50aNrSO7Mm46OSMPRPzujyK2VCx32fGXwNMZESvil00nw3RR0RcmzAmDvn6 fO/JZcPJiOOmD/sd8eJh28aEmWwQW0bJ9EIcUapXa/enCRuW/3CJKu+bg1jP PZYwgQ0tT2NT2zbPQd3bcU6eAyxonFjwfUL/bHQwS+/0bmMBMeIdfTB0Ns44 E1i0u5oFU64EWs0YcMDX282+f3OBBQFS+RHHLQ6Ykz1eLKhcPWvw7zf2mLHu t7HENBZcSJ3mUZ5qjzBn6cRj4Sxwre3KijG1xxLlBsiCQLst3cwSO3zc2/y+ 2JMFc/Nr7XuW2uGdlur+4zwWHILezVnvbDFZ+b7AgoPypnz3IlvsG7/cnAUO N/d2vPSzRdOn89I19Vmw4QrDMHOarfr/Dgv+C95pTPc= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-24.00000000077233, 38.}, {-19.000000000792, 37.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-24.00000000077233, 38.}, {-26.000000000707814`, 37.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-24.00000000077233, 38.}, {-10.999999999891713`, 37.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxdlQlQVHUcxzcIgYg8chwrROOsUZQ49sHb6/teZHG4CwsGSgEqpxyKZlxr jImT0xgDkVnck8uRJwOKCqF/ZRwoh0J0YD2gkGSMyjbDhmNy2n3vTfzpN//d nc+82bef93n/N/vy1h36FBuZTPa+5WX99I2ytbwHEZkwr+Nue/qp2r8Ywrf6 xf4wzcO36bSn8j5DLr46uKT2EQ9vN1OK6SZD3kud8Mua4HHZ+17O7isMSU7f cS54lIfsfB+cTzGkdF1K/YIhHmMDlXcajjDkUee13weu8dieH6pRFTOkzPlo Xe0lHp8338q8kcyQdI9fz2a08kjZFr4l/S2GFMqMvgFGHqYLcfbyYIYc98z1 m67iUdVR/27faobkHX6QkVjB43iKe/LaVQy5q3tmKPVjHvadP724aRlDbsUM Fizcx6O1w7Rvw3MM2WmM0G/K43Es2elLJweGfKXOTgrJ5mE+n59UYcuQLPcg Y/9WHiXnVpl+ljGkX39yxZNYHjPx1j4M8ReGxwubRd474G1ZFt84kXtyXSyL x+jbIi9ZbB0eH20UOb7FzrJ4xMeI3KCbMepmOCREi/zHQ+twOKQXOah0zLI4 /BIl8n4f04c+Jg41kZRPGwdOYoPVp4mDWSdyr9WnmkOzjvIp55Cuo3wOcHhN R/kUcnhaR/nkcBjRihxs9dnGoVtL+cRxKNPSfTgc1NJ95o6LfTg0SizkWczh Wy3dh8Oslu4DsLTPQ+CgjvIZA8Z1dB8gUuoVIPQB2qIonyZgNoryqQa89HQf IEBP9wE8JW4U+sx93yz0Ac5E0X3mfl/sA5Tp6D6Ao47uA3w2rw+wVkvvH2Bw A90HKJU4rG4ytG5Sg1iJfxy2jga+Eu+ynq5Hg+USLxBOoMEiiVOF0SBc4mmj 9QI1mJH4E2veIA1WSb5uwmhwQdpv7UlOlqVBr572USNC2u8jgo8aIdLzIVxe jxpt0vNkJ/iocTud9lGjK0vkKcFHDd+dIgu3O0iNdbtFdhd81OjYQ/uocTNP 5HDBR4WCAtpHhROFdB8VsovoPiqMF9E+KkwV0X1UcDDQPiosM9A+KrgaaB8V PCQOFXyUeMVA+8yx6KOEl4H2UWKRxGmCjxKOEs8IPsr/+ShhP89n7rjoo8Sz Bvp+KfD8PB8FXOb5KP7zE30U2Gyg+yiwUTac2P1ETk5U7q1riFTA61BGsfOs nMR2mN3GlQp8v/LrhJFJOUm7esnsvVqBsM6qfwJ/k5PbnRMOmS8pUJvAvbN0 VE7aanIzTzsr0OtYWVhwQ07M22OWP37Kwt80xKV0y0m5e8VC5RSL+rzkv4da 5ORIj09UiZlFBDsYfb1KTmxiPYb7Jlg4hpgbW+8FEtfvgsOOdrOway45ax8c SBL8XY1ddSzUqRXF/bUBpPvT6xMuxSzaP3Cxc14aQMIeRLte3sIi68+V67u+ 8CeT/g3qY2+ySLxYw4+u8SdX9lwNN/myKL9/eCa/34+0njzzRvgKFjZpDjkl +/1I751da2ydWbTwj6tt1/tJ/6cs/gW1bKow "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxVlQ1MlHUcx1EG04KRL8NUiCku3IzG7srjuee5u+/zUCDG64HcAQHFiy4J HOCgh7gcgYsWspXmECFCQYq2PBa+LIv+Bog2lgpBTESvwaiICBUYELq45/mv /e+3e9lnu+fZ5/95nv892zIPmXNWu7m5HVl5O79D4t1XPkOJmzJhiKM8V532 3ZNFCcWUPzpR3pr6SMLnlH/0ffuq75SEPsq1G/yfChmX8Jiyj/OAEQkhZpV3 2vqDbP0S9lN2/Dm0bL8u4Qxl/e0mt7BOCQ7KWud8IyExQeUy5+GtErSJKvcW +PUW1Eso26fy+nUr87GEFy0qp9o9Uu1HJexNVrkldqk5tlTCrVSV/5lemXwJ nekqczVjoTVZEjZlqlwRPPx+sFXCtXzGRytBKFRZWU6QhPbDjI+fhOeLGZ91 EmqLGR8PCWuKGZ8lESWHGZ9pEeMFKoc6fcZExOUzPsMiwtPZPiKqk9k+Ij6h Pa4rfUQkmNk+Ivpi2T4iPGLYPiKWotg+Itqi2D4iNkWzfUTY49k+IgIS2D4i Mtjr5Scin/opedaJiEli+4hYTmL7ADYL2wfoszA+Y8CUhe0DVFJ+SekDZFgY n1Yg0sLeP4DBwvYB9C73DxBG+ZzSB0iiPKP0AYpYnyyggfWxAnFWtg9w1Mr2 AS5a2T6Aw8reP4B7MtsHCKC8t3E2snHWhN2U7486x4QIyoXO0/WaYKbsqZzA hBTK+5UxoZLyYrNzgSa4p6h8zJk31IRBytuVMWGe7p+Lbzy98jIhL431MSI0 Q+V7io8RiW+qrCyv14juLJU9FB8jtuSxPkaMHFJ5QfExYg/db8rlDjUik+6X QMXH+P9+U32MOFmi8muKjwH2d1gfA4plto8Bf8hsHwMmZdbHgLsy28eAfpn1 MeCGzPoY0CmzPgZcoByp+Aj4WmZ9BJxz8RFwxsVHwAnKBxQfATWUlxQfAVUu PgLKXXwElLj4CDgos9eLR7qLD48YFx8eJhcfHu4ufXiMLt/N6HqiI1/V2Rpb 4ngcr3rriPe/OrLv25ntEwKPQL8v0+/N6khWzw8zQbt4VF86/fjlKR0ZuDK5 Jncrj5sp4usbf9ORLxoKcs978/jbo65UHtARx8HEZ+dW8Ri/3GLN6dKRdwOP +wgLelwuyp7/1a4jpb3B8ZUzenQ/4MvaB7Sk1rbt0qK/Hh8e62pt79CSnoJX q3N99Uh+7ubWtpNakrJx8dMN3nqENKcP18lakpQj/PJglR5eAYWjFWlaciHb J8JzjsPDmrW7ciQteW994XTcBAfHox1XjTu1pC0/+6fbgxwGo7sbn/HREpM8 caeqi0N//e/X7sxriF6zEFB8nsOQo2Z3w30NqTvlHA7fN7eftt3QEOfjVK7g cKAo4mxTh4aYXjB7fpbP4eeouOi1TRrSrmwIDrMhfac6ajTq83EPh5GAK1Vn bRpya7jnr0Ydh/LN/luG8jT0/4PDhP/D6KgMDZl0/nwzB69g/Q5Ps4b4Trzy wWovDjPhc/Xu4Rr6fOfwH+gi1hc= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxVlXtQVFUcxymD0CSffzAJZLLFKGAECIe7d3e/9yY4gI2B5a744L2CgAiO yDIKBeQ4jjqDiDG8tpGHow3oAIrBkKdQsUwDY4AhHiOWg6RFhAWo2O69d+rs b87eO59/7nzO59yd+1ZcemTiy3Z2dlmWn/XuEzHPciXUTpr3sXeiMiJ2IaFe jb76H2dErHHQD3S8Qahxde/SqkkRO0+uLfPwJLQhcdw3dVzEghJV0TENoa/s Sm8Juifi3deDrk5GEJrknfiFQ5+I289TVFFJhA5cufX47i0Rv8S3028/ITRq frW56qqILHif8iondMztt0vJjSLyituqPm8htHCm2se/RkSDrmH6uxuEeq7M 8J0pF1EL4xnfHkKForHk6GIRCafvl3ePEHpt44I+41ERD/HOr3UPCW2K7DUt +lREINbmNv5J6OLqjZFbD4j44NRT49Q/hA5q0mLWp1n2pzlhTn1G6HJ3UtMV J6KLe+Cx4gWhrZH1rnN6EcsOW/sEUT9pRDTly3zorodliZjKlbkzw8WyRPTk yLx0iXVERGbJvO2ivWWJyMiQuXbTbM2mWQE+qTL/8bt1BBw3ykxO3LcsAUdj ZC7w7s/37hcQFc74NAnIC5b5oNXnrABnQeabVp8KASot41MkoJZnfD4TUMoz PjkC5jSMzx4B/ZA5yOoTL+DtYMbHICBnK9tHQFo020eAIYHtIyAgSWYpzxIB jilsHwF3Utk+wJE0tg9A0hif+8BgCtvHwnEy+0t9ANcYxucs0LaD8akAmrex fYD5UWwfoN0gc53UB/hBL/OE1AcI1LN9gBdb2D7AkJ7tA6w2sH2AvQa2D1Bv YN8fYNjA9gEcld5h5qlQ85QOaxQeGbKODoLCmdbHdeoQobCD9AAdohQ2SqND gcIzNdYN6mCn7P+4NS/R4Y7Cq6TR4ZHS63LMa5alw/YdrI8Wbsr5D0s+WrwX K7O0vU4tTsfLbC/5aHEtlfXRIidd5mnJR4sR5f8iHTfR4q99MrtLPlo072d9 tFAdkDlc8tFgfTbro8FiE9tHg2Mmto8GrSbWR4OvTGwfDdpMrM//LPtocNnE +mjQrHCo5MPjgon14XHOxofHGRsfHocV3iX58Dio8KzkwyPTxoeH0caHh8HG h0eoiT0vNQJtfNRQ2fio/+sl+6hxI5vto0bFs8HojjlCvyw7ZK79UI1NR5Lz nJ4S+nHrxKoHvBoDK87tHJ4iNOH61QkPTzXElvLn6x4R2tM27piyQo38KGH7 8nuEnq/MSLngpEaVfVmO6SdCR3d/5PzkJTVKrtQaEjsIzXUvXsRPc0jal/B3 30ULd3pHFE5wWBbQu7nb8v0Y3aIauj3OwVWYqGscDaT23weFVXdwCKsrvPRq UCAN93OraTdzKE0szuuqCqDNJ7vHXfI4OOS52DstD6AY2+z2TSyHksk3Q9pL 19HHfrXa8xs4hNBK8Z7XOvr1/uvh/T4cnMdKZrO7/GljfXNwuCuHhbsd9xQW +NObP2d6zXPisDLkScW8EH/le8rhX6ZBs4A= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxVlX1ME2ccx+tbRTEgKsK0mqmEoVFDxJS7a3v93ondREHngIFWp7yqYFHA 2pYZRfdqBGFq1InzXTfnFMWxTSc+oAbHNnzB+Y4oZW4qKjIJAoq73t0fj788 7eWTpnef+1zzdERi5syU7hqNZqX08hxD3+8hvTNEI88k6Cpi7DuCGXLQ1jK4 sF3EwfKem9g4hliH/uW365mIa1MGWmsKGBKo/bZ5wr8idieu+n3ORYbUjU8v nVwnwqfPNPc/Q1jy/abhs25cFBFosu/JsLFkNVfZ+LhSRGVXl3dTNUuShsV9 sKZUhHf0fV1qKEei+Jv7tu4W8XzM2Ks3v+EItkffDi0UcQ4LI/lSjqw3zxs5 ep2I8lXtJYZzHJm6b9uwiM9F3Hp4u0/tFY7YajQ1eXkidCsHxvZs4EjbifVh DS4Rn5i2f3WhiSMPF70XnZIton+wq3JiK0csd8YM906XfJiDjWGdHOnrH76n dr6Ir5eNa/+jiyOM7+K68g9FnKj19DGQMHlEZFxQeMXld6QlIrla4aqlOmmJ 2HNW4QF+nhERXK7w7JJe0hLxtEzhfdM79k7vENB1WOGnTzwjYOZ+hZkCt7QE NBUrvGbc9dXjrgsIy6V8SgUsWKrwxx6fAwK0CxU+7/EpFtA3kfIpEpBjpXw+ FWCJp3xcAlbEUj42AUNjFGY9PkkC3o6hfOIFxMyi+whItdJ9BCTOpfsImDxP YTmPn4B+iXQfAeVJdB8gLoXuA1xNpXzcAL+A7gMkZyg8Ue4DbF5M+RwAjtoo n2LgSCbdByhcQveRrq/23S/3ATRZCjfLfYCCLLqP9Hk23Qdoz6b7AKYcug+Q m0P3AY7l0L8foD6H7gNolykcueP5lB3PzQhSub7OM2YYVc7ynK7KjKkqa+UT mGFVOVUeM5JUbt/ruUEzMlXO9+RlzMhTeaQ8ZmxRuWyet7TMKH3Dh8cVle/I Pjw6VJZvr4pHsF3hXrIPj2o77cOjU+UXsg+P8csVlh83w2O+yqNkHx5Fy2kf HqdVnir7mPBkOe1jgs5B9zEh0kH3MeGGg/YxoZuT7mNCkJP2McHopH1MiHLS PiYkqDxF9jHC6qR9jIh30j5GTHPSPkZoVU6TfYx4pvp1yD5GuB20jxG3HLSP EdcctI8RNx308zKgwUH7GND8Rh8Dur/hY0Cck+5jgECS796W9kvjf2NNs2cY cHHjF3nZ0n66RXd4668G6fttNvcZab/NbXiQuzbEgMv3A7Q1jzlyL+Ku++xg A95NXvOgyM2RmklFl9K1Blgzj+b7XuOIuf5lxMo2DoO8drdYznNEHzCKf/2A g218bCDzE0eOPepx6lEdh1euaPexM6zqw6Gi95KtJzey5Hz2xs8ap3N4ERJ3 Nj9F4uHTTt9jOey8o0kerWdJWlp+/7lBHH4OWeIo0LJkZ1S8K8GXQ0Tvvd1O XWWI/dKhl7UdLOAqfn18P0OaWtZu/vM+i5K8hCy7nSGvjrZEWmpZFA67ldDN wpBDPo2DecKiIWpEWaw/Q154fdR5/AcWzkX1rX4XwskEv2bfORtY1C8NyFiV H06qK1bUV7lY+Cf/FrhrRjg5PcRrUWsSi0FCa2d2YDjx0a0/8nc0i0avbf7t jXryy7kBJVsMLFafPJESWqYnFQEb0n3GsHgSH9P01jo9CRrQv8EyhEXIvbTv fkzVk8bjXw4U+7EIjWkt7mHRq//vLP4HZLX7tw== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-6.999999999953445, 39.}, {-1.7053025658242404`*^-13, 38.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-6.999999999953445, 39.}, {-6.999999999952308, 38.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-6.999999999953445, 39.}, {-3.000000000019554, 38.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJwtVQs01VkXVxGJJTPpk5E3l+pyuKTMfez//07S941QzRCScZFHJKY8Zrph uqtxo8mkKSMieQzudCdFHrGJDIlYXmtK5b00GCb0oO7375vvt9ZZZ+219zl7 /fb57bONA47uDVqppKQUwawPO3AUDD5BpQ9IFMKGlzYry67pY77r/vyGeCH4 7RLeFQRswp2XfIWHo4WgS3bY1vANcPyJ7vPZUCHQMm0/g+2G+J1BSryfvxCi Do3n2bOM0MBXpiX/Qghxdg5zD9EI71yUXBvbLYQqtwX9xyHG6PZA207BFQKn 0sLc19AER5c96pathTAe0rrGY9QEYzc773pqKIQdrgfvbQVTZL3vd0rVFUJQ V9d7bpYpbtvnuVy/TgjBCxa1SQumeM2q6Wy8mhC4Vb5Lb/eYYViSweQdBQ0T +jG1xUVmeN47eL14kYYwozCFVGGG629nabZO0dB4j2rK+9Ic58/X9WQO0zC7 +q36dJk52s10hM7205B6RTV0osECOR9QTsPMH/d5if9i4X6HwEGLYhq45O/i DZEsNHun6XIvm4boKyklJc0sLJCSGLUMGs4bptFcA0vsHnzgtyil4VLVctSD WEuULz5TT0um4UzYgINXtyVye4/EtifQ4G9nlD7MtsK4+Ojrt2JoMNHuSQ6T WmHAyGz6zgga9DKLnq/TJGgcm3cyby0Ni8cEQy4mBB+JsprOqdEwefNXH3cH ghrTj6aTlBk+PgtuLGeCXR/RbxIUFKhHfFz3cD9Bo96Z8fg3FOwYVysUfkXw Dae/Qvw3BeKWXtWUcIJ+NkshKS8o6FuXMJIdQ3BPi/e7zCEKhI0L25PjCf6+ tBAj76eACqnP1fuOYHKmxGtDOQW+314bkEkI6l1sktcUUeDf4uDF+Z6JP5G7 1/8KBZ/vjjcslRKU8jfyldMpMFoZYa2TRvCrKeuYIgkFg3PrJMd+IOiaODS3 O4GCZN0gU0xn7Lek+s9ICrROhK5ZkUFQ5L2pPVVEgUTdwNH+J4LncgtZbC8m 30cr/mOUTbDA5ZcbVhwK2PWLjz+9SvBzccvrNhYFxX2rLPbmEfT4rVHliD4F 3V6WVqJ8ghVDP/dpaFNQujNwLLKAYJyWe7hMhQJOdqX38SKCmU7D91zfAoQe Mkk58QtBXZHH8+kZANfU61HRpQQXv8/GtBGAIVO+dqiMoF3Z/UD2AMDlpQ72 rXKCvxEDD5tyAGkUdSnvNkFDwe3wziIAg5tWN1MrCc7fwYijVwC+xDPi41UE 2TngqZUOwM7yWfapIdg2Y295QwJQSBdsgbsEO0qyn+9JAGioCNQwqSe4rTsh cSYSQPwqM2dFA8FVQe2q50QAT5R3Dj9tZPyiH0+wvQAuuGWMj/xO/tEzB+DB oO2Lu20Ene8cONXNAuhR3XfgcjvBabXRzmP6ALKHrzgxHQRZ5t1m2toA+2yM EvY8IvhSw0wsVwFo3dq+ZXM3weuJ5ZVX5wWgdX/JZXUP877i8W+eDgrAbOnX ruFeghkfD7lsahHAmvax5vp+gs2CfANfuQCCPW8OdQ4SDP4fGL+ClVz+jGDl z5pnCtwEwL+YtSV/iODpatIwtl0AKnqaT3NGGP7NnetZJgLwTvs2s3CMYHrt i6TQtQKg/5o8WD3B9ENOkppsng81gi+2/DFJ8OyRjOK5QT40ietWrJ4iiOam AY4tfPArMx/izRCMbmM7iOV8UBY6smoXCI56ZHsPBzHxjQ6ykVcED90yL+C6 8aFjINu97Q3BAy3Ksgvb+WAkOaodtUTwodQpesKYD9UtJX/1LBOsfn9/3nEt H7Jz3f58/Y6gqWmJvWSeB21afspP3hNc83rEtnOQB6DT5yRWEAw5+fWUTgsP FPLKc88Y+7Nyn8ADch6UPPnwS9v+vz48sK9VeznBnO86OX7Y2Z0HCf567VeZ /DPOGZ+FfsqDU62OZ1mLBGsaji53sHjAe+VPTjH8HGbifojV4UHV5MWawlGC /u033gUo82Aut29rzgBBvu/6XenzXBjXNz0dxOihNbswfOU4Fy4d/KZhmdGj SnpweMUAF5RFz0ZFTD/MOux3lrVzQaovvXojkqnvhejA3lIuDKUsSzydCP4k s1U6ncaFVaXbLvuoE9Q+nb6x6hhzvyKqLPauDb7e8KP8ay8uBGgrJ85G2qB7 MKe5guJCvNSi1NjKBnWij3ueYnNhc/gAe+2UNf7byetwxydciCvfqCartMaZ usfz+Rpc8Be92KGaav3P/FLiwn8Bz7oylA== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJwlVQs01ekWP2mkiCXWZOR4dbyl/l/0cl77/M/UkjxL6XI9ik6SUmoackOK 0XS4SaJxRFLyJtdoimnnMafuoEKk6zQeSaekvFJK7r/mt9a3vvVb3/ftvb/9 22tv053hm3epsFisI8z6soP9LAMDZH1BnBjG2K++j2lm44TUr/ZzlBj+oezQ O1FmiKfPHS/wPSSGw5m1kVpXjbB+cdidxWFi+N4mb7dJlTFm6hqqU8FiCL5P R/SEmqD21wdiYEVXTb2aZ4pWx9osj20Ww5Qep/H3UlPsU3Z+qnASg9PV1C6v gKXo+PASSywQw7j5LCkz4KCD/ReIYSDQYl6CgoOXegoLxy3FoGZan5iWY4bb fzGLescWg5+krap7hzluC7t8iavD3Ke8k73NLDBrswWnQU0MsjgPXc0hC7Ry LZ2RztCQuPX39dOFljjju5ZcGKchvzzXzHifFS6JldcNKWkYS5kqj6asMfZX n8uRvTQUHc3wjDCnkO0a3e0kpeFsr01JGE3h5d5TLN1TNJy4xv7RxZ/C7JNV tkMnaYhuC7u+KIrC+eve+zTF0hDlb+Bfe5bC/hnvlNIoGmJdrI66FFO4or2t KSeChmRZ2rz6egqHb4TMkYXSkOfmN9ewm/FXri/K20HD7Z0JB/xGKKytHjx5 3ZsGnVxD8VYxQdOzTbo2ljS8LGrWLPIk+AMVr+phREPupFtjqT/Bm5eOD1h/ S4NDXL4kMJTgyGBDaY0GY9+5ZeLOYYLaM07BH+bQ8Nbr3v62YwQ5Q9pqb6ZE oJ+T2ZGaQNAi3+B85msRmFhzLVhSgt857Fn0rl8Ec8crggxTCX48/yFS7bEI ds2a6mnICDbssbKduC6C3lEvqWEOwfNlFeW5BSJgVS4P+TaP4CbHliubZCJo 5JUXjeUT7F0Yozl5RgQ26Z1bqgsIelk0PJcliMDhZn6QXxHBkkQZER8VwbNi /ScvSwgO2KmPDO0XwerQVTV+5QSnDRayTweJYNnk1HR1JcEJj7xby7aLYG3E DGfwBkH1FP3hJfYiaKrcH655i2B/0g9uty1F8NSmutCyjmDYqK9eEFsEcYoH bfa3CRbJmzfMWySC4nt3XpI7BH/RuNtzTVUEgW9+GjVtICioc+12ngbIdeMM zW0imN7jxxseAQgdSvuz6w+COXveqyYPANT91n0x+y5Bv2DD1XaPAVzUJHKz Vsae/uBGyyoAlX/p3Hlwn2DUTLvuvQKG9wV9c/ghwQo68myoDGDjap9UrXaC QuXDJo1UgK7oyd25HYweo72lJQkAZZWrkqw7CQb7XHF2PQrQ0rVkrLCL0cPM WPZ6P4DDSP4V026CSg+3vOQggIGJ9rwzTwiueLrSz247QFj8vlndvwi6JcqV y+wB7l20Zx3qJXjt1omEFkuA9b6c+OY+gq4P4j/sYwP01vASTAYIOjY2rtda BJDxn9gF4c8IHsjYGFqmCrDXc1jrxiDBvrSlrbIJIfinxKd/fE7wUM2ayB6F EA7spbPXvSCYcaGtzUAuhIsvbC0ilAQ9HMcVPhVC0Beb/M/zNcGQn1uXSyRC OGE3rRc/QvBtzc7WfHchNEbGO15/Q1A3JiNsYK0QFGa/0f1vCd7vCVuwdKkQ WshFSmeMoHFHf36ghhDO5ZBv6HGC84I/CHImBOCw/1DdwQmCSdKKLoVCAEXZ Qf+8NEkw13V+OFsugPd2Kn0P3hH0LGCp+lYIoPnl3eqSaYK1BvRrWiIArYM2 j/77kamXxMXjSe4CSFm5apP8E0Fbq8rvWtcKwHmFUi9vhqk/lo6/zlIBiHZv 4Pp+JijXXtewVUMAR564VI8xvMDbwilzgg/Pkz4lhMwSTHvUPdyt4MO5iK2l tQxP+nlL5RI5H45leNu+Ybj0SFq6TwUfsse+dOmVKPkKPgRDbVEgc/4oru5l qzsfVi1/URTP+J/Z/Nb99Do+aNUmsiRM/Iqez+lZHD4MKzOK1Zn/RRgpa2c1 +dBeY1BygMkf6pU31rznQb25jkomo8cfdz1KGwZ4cMM+ujSO0T+etB7h3OfB r33bymweE5zytDTtuskDvt2ZTqNCgru/xsOD8Ry7lYosgldeVIxOuvOAFeAt 6EwmyBur22vpyIPgUM2PC2KZfJ1I7pg244FxvXtIZDjB8CzjZQe0eUBJjBJN Awgu5B6O+OkTFzK2RXmpuhGc3XG6AJRc8EoLbOfwCDpr7/ozq5MLoewOlWPW BF+tn/M0s5ELHaPt/dqLCT5TCfxrTRUXYh6y15i9o/Cgk2ZXTQYXLmjHcvc+ pnCxydsAwxgumJVPvxmspbD91PyjIRIuGJX+2+vcZaafJ2wzv+DBhSR1wZ4j UgqTdJ/sKOdxYadcdbn0RwoT7dNWFNtwoWTged6jYAozB4+nSJdwQRLQJ9/s RWG99dWYLQu5cMZxUjZ3A/X3PGVx4f+kn3ka "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{5.528873011563348, 39.}, {-8.256772299473198, 38.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{5.528873011563348, 39.}, {-6.999999999952308, 38.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxN03tMU2ccxvEWVtFSJKUEWWEjqBPUlqKAoVuE532PRuYcDWq0ClEEuYxN JuKygUoIziUuUDExiIwlsHHzGowVL6DvIaKo4GVMgeBt0OkIEygCUSroWt4/ 1l9ycvL575sn5wQmfbs2xUUikcD+TL9/kVqKP/JxUCLJF3B07sidf1q9MWvr YMZ3OQKupsSsW/qhCn89FrctyxJwcbtb9k6lEvtzcv+maQLeRSVsXrHNA9Zw 9WhZvACdJsf10KAbgj0riqJiBUgPp/SKrVJoZirM2mgBL3po/7ln49GTAVtS 00MERChSn/wR8ii6dENJ1ZCfAHVbb8CE0cLenTRnim4CPnXt6GyRvGA9G/0D 82QC9G0/mEuM/cxS+3voQhcBqnmdFzMTB9ic8tW/Nk9R3JAPWNb4vmS7w5Vp q95QbCgwRyzJH2STO18XXR6huH4w4oxf6RCrj5tS+g1QeATu+FKROMxMnXNH 03splsbEq1y7h9mx92lLqroo2iff22+YhTnuHMV8G/fejqB9HbUUhjHu1iz/ 1qxyijX/cnsp7XeYwvcZd3y9LL7+AEXDPe5qg63KkEsRfIV7eMh+mRQZtdx6 kyXSlEyRb+Ler+0u0BopynROPWEUz9Xc+xw9QRQaX6cef4odQU49SoqaGKce GUXPHqceG8GMZqeeIQIfhePDsLJIR4+FoAbc0z3dBO1e0mnzfQiaYrn5PgS7 87hvTu9DMF7JzfchWH6Jm+9DENvCzfchCL7GzfchuHWem+9DEF4u/b/HSFCm cuoJI5hdvenmEy8rMxvPj+mDCXA2OfD7L6ys5ue11Z4fE4REBri3H7cy2S35 SrM3QZe+8MBj7Qh7oHr6Z5DC3tdworiua4Spvm6Py/iAIPF0ria09hVrvvvw 6p4pICpg0phdPsqeRtnUCa+Bbnedz64LYyyjUZ/q/goIzVZt17wZZykrjlQc HAQ+K7gfk9fylp1qYn1lj4CXCR79twslYsuN6Of+bYCLx8TeS29dxJNJ3nWe TUBS3GKLXCcTtxYvX5x9BpAvqlKzBW5in6Exc9VvgK0keV5n30wxrLJoV+FR ILz0qylDslxc/6N5GTUBDdqGOk2duyhM6BrTfwLyN37+yTdnFSL/34H/AB7i 7kc= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV1ntUTHsfx/FRSicnlMzM3ruydFGPRDRTc5/PnklRdCGkOrk05JpL8SQh t3M8dRIrurm1ki6UIiR0oYhC5GA4qYh4kksepFx6Rtsf+/zWnjXrvdaeWa/5 /vbae0YtWDl9oR6Hwzmje/14x/4BbbstueD8WHFqDDQLNlwh4GKBsnDa2/Vq KDoiF4z04YIOreq0jFSj02Zqd+5SLg6GiB8nLFPDpLKtxjCei0gJf6Q4TI2s C5J6aQEXV7tDTtkFqVFA+Bt73uFi795Bqf5+ajg8HL3VoYeLlmH8mxcnqUH2 XpjYasNDzvJdAeESNTbHDrOI8OfhZe5SJ/9xavRQttGm63S9wvzOJxs1fJx7 5i5M4eFq2m+pGwk1YsuS7i45xcNmB4+450PU2Fr6otGqjgczy1sJ4waqsWDM gNDtj3mIW/exLLBHBdKsKSqjk4c6wUVjzRsVjkdE8+Z38/ButvUmvzYVeLg/ SfuNh64We3MrrQrtf3zs6+vjweXHKlEhscz3UiuHjyKh5/u/clWwnRZqsE2f j93f0/dvOKBCvmrUjfZBfNxPdBxvv0cFKiNtxK9D+Ihr+1LwYIcKsTNqnrwf oTu/z3hEYowKNyKynfeP5EP/aWC450oVjDtFegaOfDTFPz9iqFFBVL9llrOI D35vcV1doAoBq/N+r1rOxzrtIeNnE1UY9Oe5M1ti+fjXzayuZHsVPIOsO5oT +Did7vWMtlDBtOm5jTaDj+GKlKevh6mw2FQ/bEU+H57nd3SmGqjg3bs+91Ap H35DCD300jif4tW17Aof4yV+Nu1vaJxuj8K9Rj7a5I5+8W00ZB2f9z5q4SOC OLZzrJZGuE9LdpIRAd7R884WJTRszYzaX5gTaLz9wacql8aarEJLy1EEtmjK /w47QMO3r8F7vBMB63nmDwz30Ch1WLnKSkzgdHUP8nfQKLRKSOhwJyBNWkF4 x9AQPLE5mOxHoOTyynmdETQmrxIfJUIIWIVyuIlhNDrq64/EhhOInT9S4hRI Y5VgUExnAoGTx6ILHV1oFKzSkMNTCbikpybcsKcxOuZrmFMWgQ6DMZIVFjT+ 9muYJS0koH03vszElEbdh6b3snMEeufkG50woPFpoZ1oYjWBGXSKg08vEJKd N5q6RaA15xP/zRvge9Giim4tgez4uoeJbcCjnXP7atsIHOo0XeakBRIT/nv/ rCEJQf/1A/TMNdWsNSWxaYQwrjEXaKhuTxRakKjb6H939QHAtHRJQPdoEvzl O8ea7gEqxBml5yeQWNT6MKF4B/DAO7p0s4zE2UeTunxjgKDX+gEeniSMgm+E vI0ApljJE4dMJxE0f8WtXWFAdrNNmDaExInXDh7jAoH0rtO17zaTzPXsAuhd 1Zy8Fk/iTr3XsUZ74LMwcHvpPhLc2Xkb1lgA0XQSyjNJ6N/zzjUzBba+/KX9 4XESKZOETiUGANfxWpRJKYkj/tfJvA9KuP5S1zn7Moml30qSOh4r0bJ1qE/Z TRKxu8aUOdUqYZ6WljbhIYnWgU6pq4uVaN90POf9d93v619KbNAPV7wyptCS 2VqU56vEctMicTqPgt3dWM17kRJn87alfbWlIPom2a62VmLO9WdBI1wocEdS Qw8MVmJWZGNcG02hSmRp8PWDAidyphqH+1Nw9aIXhTUrEBo2o/vwfAr/nvHH xMZaBRbnt3vuWkNhR8DbJZNPKtBoL/9eWEQhIzlyzRKNAvsWN6//TxWFJjLl gZmPAh3JPvSSBgq372UdL3JToCE/MWBaE4XImvQ3ylEKuB/bXyJ8QaG6PSaz 2lgBr33RodbvdC3zuCT5IEfzUtuZw7sprLn6xe/oYzkGOh5ONfqq+75t+331 a+U4f++lnV4fheYou/KAYjmqtg7Q3Zgtfs5Hjsl/Mt2T7dub7StHbTLTu9pE ukMOWTrTNtY/lhxHDjB9dt5g3SHHgENMTzn8QXfIEHCQ6ebHP5YMBzKYXmNR u9qiVoZH+5g2DC42CC6WIWoj0+H9HhnerGW6t98jg8FKtkeGc4vZHhkMw9ge 3ed/Y9qr3yNF1By2R4q9M9keKfymsz1SBHmx5yOFhwd7PlJcVbA9UtxzYXuk iLRje6TIHs72SLDwO4flkeDscw7LI0HGdQ7LI4HLXA7LI8EFJYflkeCxDYfl kWD/YKZt+z0SvP2ke9zo9p/x6M5/zjTjEWORlmnGI8bOW0wzHjHcrzHNeMTI qWaa8Yhx+zLTzH6JYfKzk/o9YgRdYrqfYy1GaRXbI8boKrZHhJxKtkcEt0q2 R4RHFWyPCP8rZ3tEOP2zmfmIsL2c7REh7Gcz+yXCtHK2RwT3n+3d73HDlHK2 xw3B5WyPG2LK2R43kBVsjxsCKtjzcUPWz2b2yw19Fez5uGFpJdvjhheV7Pm4 Ym0V2+OK4ZfYHldcusT2uAI1bI8rntaw5+MK+grTif0eV8y+wp6PK+yvsD2u OFHD9gjRVc32CNF5me0RIvMfHiEEF9keIYorXtkN/kJhQdSkdXl+QqRcL0od 26m7v44atqlLJsTTJu+Zmru6+/fyqxtpRyH2fq4MPVVMIWj24rVplBAFFr+e 5m6nUND6UfPJRIhxU5xn7plGodFo5dRgPSFGbBqrsjahUN9w17H2swCaC5wN 13XPkwyhrb6kSwBiQGHf7xEk5JJ5jSWvBPjoODnAUsPDKJHz18AaAeJrkutv ZpgjvSW0anKmAA/qkhammZkh27nTattmAc5tjHbvTRkKlaOWZ7RAgAn0RP3P 8YOxtsH6+ANPASxapw4aM8AIEssb2i5nAaKDrvnt7hmIZPO/MmdZCuBenN0y JkoPcWck+oYmAsQ9eVLSs4rD/H/mCPB/NE7bOQ== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNlns01HkfxzE3nulCIrFShBKK2rmZmd97ZiJ0GdWiUtguLhUltS7Lhoqu ltWWLmgjl2rFtq22kC011bKP9DzIQwibiCFyGTYPM53j9zkz53def/y+v9f3 9f2dObNg+74NuzTU1NQyJ76TV1xSb00y1ofa5MRIsCjg6k+fLumh/rs1e1Mj JNBbe7X5m39mw2yrwP9hiAQMV/UrI6LZqD9f3RsdIIHC+0FTfKAuxuymaf25 TYL+Uw0Z8w7Owimrzlt56yXordrUXPa1DhJi97bPXTnBNit+CrLXRi8rJc/o Swk6HRvLXSqm44mr91j+QgnGfLSdK0f+Ba2SysaXsySY/uZca+fmCV7TFi6c MfH8Ul5NbYUWakvrQhs0JejoHzU5u0ELIXo3/vpZQ4LCI/VlJl2aqJF6nfhl VAzfoJq7kec0oRn8LrOzXwxFgZxx7StNMPa7z/PoEiNynUV+urkmqt0zhgda xGh1jLzhr6WJ3SYye1mtGGtTusbHxxlYPjm3xUjNU3FUtWV0dY4Yg3IVy0K+ kIVcFmOn33slz9KZmGQxWqZ1K9mrgOZVcEyM/a0qviZVZEkjxZjR2aNkec/E BItRMr9XydzEVk7iDjGiE/qUfMSmLs5mkxi33w5O+SwXY7b/sJKjJ30sxTiV MDLl84UYei6KKR8dMQpuKKZ8aGJsv6WY8lGIsPArxZRPjwhjF1TrcSZ9WkXo iBme8qkTwdCtn9RHhE8v+0h9RLicr9rPU2UfEfqb5KQ+IqgHyEl9RHjqJCf1 EcE5Sk7qI0KMJrmPCPu7ekl9RPBz/kjqIwL37CCpjwh5Pw+R+ohQdFa1H2Ue HRG8XUZIfUS4+ucIqQ9wxIjcB/jEUUz5tAJzFipIfYBfKar7Vyj7AGG3SOeV A5SGDpPeHyDBbZjUB6hyHCb1AdI3qjhb2Qd4H6HiXmUfoOTuMKkPoKM9QuoD GJ5XkPoATtNGSX2Aq6GjpD6AdeUo6f0BWgzGSH2Axx4qds0YcMkYIFATr+Km xskhMDtPxQcml5MRiC1RMV25AAG/Ryr2Uw6BPX+oeCRrcoMEDItVfGYyL4fA gdsqNlUOgdAcFf/my5z4EJiXSvYR4sAxFb9W+gixb5+KlduTCaH/2Z+m9BHC 8OMoyUeID5m+g3GfGPj7eFhMrlQIu+7EV0wFA46hddl9HCHqquLzLn5gIMb8 xCuRqRBt65z9lnYw8GPGCYMLTCE8/V/OfF7PQELLqx1DAwIsM1yUvfs5Axu7 Iu5vfS3AAX+nxTpFDIwVB5o8kwkwV2p7oeQKA7Eeed/zCwW4K7xx77IzA3+9 KImS7xLghJVPyrjNhM/RLNoqqQCP3fKT9WYzoNbUnn6JI4B/Yeqd1wo65jbH OncvEGD/mnnjW97QYXs8XIPPFKB5ARF88jkdjrXPKhIG+LhnN6oRdJuOrZWH cqoa+VB8u6FEI42OA7ujftCX8ZGl5pi2OoGO+PzGM5sL+Ki8NjOsVEKHR61l jpcfH4f1bYpNltJRyIiOuizlY0msO/WsIR2mma3TGzl8vGg/LjWi03E9z8vL 2JSP4JWytDt9NDgate/cxuSDmqYt395Iw/DQYau0AQecle+UmD2joYywvtnQ 6ABjfvnFwV9pSPvw7p2RzAEZcbYfG67QkKz9e+uWAgf4dXs+bfChfT4vB3j0 Nd19sZoG07oI62tSB/Dj4iqus2mwK2jxaOM4QO8KQQkwoyGlJ63dzNQBTa5z tmnNnPBJya/bwXRAepxWfaKCCpd03WVZAzy4rdKPHG6nImNmZVdbIw8DqQKB 0wsqVr2tZ1rIeEgMO2wWXkyFyFyQ5F/Aw/I5tw65hlM/+/Bw5dCpniU7qMhy zz56TcpDCy0g68laKnjZKUXtHB6GZCvPG3KosNxkO25hykPz/QUyS9OJ+/d8 4xXI5CG95dPyHiYV/zTtqbg5wMUybkNj0EcKuu7M2NDXyMW5h7+XZ7+mwLbb +z1LxkVV9PmOVBkFsmNbL0UXcFHZY3DQ/lvKZx8unNf/ttl9BwVmSW+zs6Vc LEXhwoeuFNgnpaKTw0Xcfa3/httRkOwXsdzOlAvRowe7I+ZQINY9efhbJhdB ni/bH41pwOnc84XPBjigh6902tSigUtynpnhaw6Y5rqnWY81IDb5X2SwjIMo b6LIO1cDXPMbS54UcFCpG1IR5qTx2YeDGFO98vlmGmDc6fYcknLQZ3HUSfBR Hc/MCqk2PA7MFpRurCxWR/YvBXsZ5pyJ36FHXVUR6sj4+v338docPBz8YYaz tTruLtsZfH2MDftqm2L7/6jhvYmBZug7NnwzUwaSQtQgXKq5rbmGDenu8qLt VDXc9F4R9KGcjYs52gaF2QpC5cPGWCpVfmzdCHHQPzmwwo2NUgv2H/fahoiw bmJ1rICNZrfcRGngILFvOIR5zJoNnzmbPFc2DBBbjlterzVmg4h0Mrog6Cd4 ab6WETpsREeE1q8900dos42PBDLYWGFVuvjxOTlR576tJHecBduLs37Ml3cR 50fm17AULLSJ2wY9zTsIF9OASt0hFnwcDlZnnh57YDxm/W/3ShZ2xs169d1e 7bLsXR3rrXJYWFV9JN+j1qDsjfdF9+SjLOBwOK/Obn5Z1Vtx/cldLJyk2Og/ OW5WFqr2pknflYVPh3w6D+63KHueG+b3pT0LaTUzi9o6FpW9bKYE/23MQqC5 MErvg1VZUm784OLpLPhu7+QyTluXKf8fqrHwf0PuznE= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNlns8VHkfx5ERxlwQya1NZPcpIWacGWbmM2dSRjFdZIVSuVarkMvjum2q jaV0odJFT7m03Uyb2FKP2dIzXZTSPVTSbV+JZMolscz0ej3n+zrndV7vP87v vH/vc/44k1asXRCpo6WldWLkHL1in3Z7gY05tEZnvQSbzE43HbxtBkbX71ln UyXQ092g6k40wwfrM3JuggSXohJ9cg3NUJFjVZS9UoIawZZb0dvHwYXTPn1/ mARvt1zcnGswDnkTDdPXB0gQ4DMu/mOCKS74FKS5+EjwJT0vv+SmCerkSU4n +BI8nTylZfsEExT9eH5nz1QJBkRtodcCjQHB0pN61hKsqtz89SHTGI+DwM42 k6D7qMXSJY1slBO1vT8xJSiYtjtr8Z4RbrkVXq8ngTdfJ6xhJRsPZ6YH5AyR MG5aPHxWwoZXvOJa7ScSqp4DYeZT2Li3/ODlkA4SnSW3fn7PZuOguRm58gWJ ofvvwjx12Tiwzd775UMSVZJ3w8PDLLiNzhkSxX4azmhyzGyqILExUMPKeGtl /H4S8Us1bGI8MttJhEZqOEROC5FvIjFntYbLZAOlsjQSXnEa7uocmTUkpidq mLe1ndgaTsI+RcPZTo82OAWRiMqg+LiR8M/UcOaojyMJ60yKjzWJW+kUH2MS K1IpPjQSj5IoPgNiuMdTfDrFSPjmS4z6tItRGEHxeSRGlJTaRww9CbWPGL3Q 8FV1HzH4EmofMW5IqX3EqAyg9hGjPZzaR4xVKdQ+YmAbtY8YxV3UPmIM0Dso fcTItu+g9BHDmadhdR5jMb5KOyh9xOgJ7KD0AejLOih9AGlkx/992oETUR2U PoBfsIbd1X0A2mqKTwUwVEbx2Q8Q9PeUPsDJ4veUPkB4QKeay9V9gGCiS80f 1H2A/FkfKH0A7Z+7KX1GfJw/U/oAzjt6KX0A9xt9lD4j6z/pp3w/wMG6AUof QDf9i5p9S1TSEpUIeUaDan7WOjoiuCdqOGF0OaUIQ6c1rKdeQITiyxqOUo8I Zpc03F86ukER9tRpOH80LyGC7QUN26lHhIoaDVcvo48cI8/7Y5DiI8TV4xp+ qvYRYmmphtXbUwoxsE/DNLWPENEZVB8hRMdfaP8wwlXpCRblMiGy5xSOLR1k IUtYr/eWEIKzZJxxfB8LilMhrtPshJj3PMy24CMLKQ3EngS6EI/upThrv2Ph 6O4Qz1qVALf4oTPr21iYx6631HsqgJMJY8njByzEcRO4C5UCDATnpuI6C/qG UVsPywWoFlnPLNjLwnX5jsGAKAG6qnfIMnNZsLprSuyWCXD74paHhekstJln 0x4TAgQFDDU//okF84znEZZ2AmxM6wmVLmXhgs60wBC6AMEuMcEvZSw0HYt8 vE/lhQdJofeOiVkITczvbG71Qp/v7ev73VgICDtSaKX0wuXKy4LzDizUra64 FSz3ws0b+u5B/UxEq/t4Ia9iwrND75gQ6bNmlMm8IL30euPFViZK47ixLwkv DFvFOZxqZKKopGW8vZ0XTlWdVST8xQS7UHtGBN0LgXk1gfQzTJjPL6stVXmi /3DSm5RSJo7eVVa9avVEUV9Xwp+FTNRbr7RxVHpiev6U/obNTMROy/kUI/fE 3tnZsZmLmN/elye2+DsssJvFxJvphf8uk43cH/ZWGM9lQkKX/fqK8IQyrcFt 1RQm0r7s3DHFzhMWh+64MMyZyB0OL46heyK3sZcTTGMieXzdweMqPqwNRJL5 Kga8JGUlXa183J5bEfTxBQMtG8wPuCv5OFLskiy4w8CPD0x2p8n5sDyUGG9Q xPjmw4e3bWXq5mwGLtcn9ZfJ+CiJEKelxDFwZsWd3DcEH/brpq5rCWWAQKrl VDs+7ktjI876MOC3JPZoHJ0P+Vs9fx13Bj6dO+n+p4qHc7I+58u2DLgG8uu0 n/LQmSU27NNnYNjV1MdPyYN/8ouWQx+NsMyPaCyW83BmbLq3Q4XRNx8eyhyO n/TdZgTdoR/sj8p4qPJt7ndNNkL17MOcDwQPj5Pp/2oOMUK6pLFYaMeD5TFP 4SwYIaBbvnAnnYfEl6u56yYbAfNnL+tUEXjtsN9kBc0IZPgOhewpgcQ1DU0m r+kIdNyRWKMkYPnfweRNV+jIOjArw+E0AS3WEXJ4If2bDwGc0rcod6KjxFuW 3yQj4OmfUmijRceUKI8ne3kEujs7z0feMESv0tbvwmQCSwvWbsnaZgiT1bTX PCaBX2f0f42ea4gM2btSk34PxNz/zcpOxxAuSbdzZr30AC3Vse2E3ADOLVW7 7jd6IMSmwV8/yACpG/dcqav1QNVz2qaNx8Z+8/HAwLkm5Ue3sSif88T0s8wD 350QXj9eowdRVrjKke8B+xppXiVHDzOGtPUH7T2g29zDGDpJQ8aNs/4JbA/U jxfIdn9Hg+3rrKu5g1wsi3WYl56vCyv/JUnef3PR0nyCfUw1BmvHzF90+AEX 7uF3CyYHjoG1XnDMf+q5uHnYOLPil2GRxocL2S8xliUXvooWGOhk/jWPi3Fr ntWG/P1F9DFRZ+8iARdWK5OXt44dEHn/Hn3ebhoXkQlOdHuLPpFPuWvb9zZc fMjRPeds+Vk0tHoZI4bNRV3ll1VaTJUoaqBH+JzGxe12k0lFPd2i9fM7krZ/ 5UA6d1d1W2GXyC9e+kd6LwdJ70m3Sd+/EzUspqsO9nDQ1GJTKH3SU3dv3aLj xdc5eBW/zTeHMFD4L08xNC3j4LfoPXtN8kwVPLt4Y/1sDgY38MjBKxMUu6pJ RWoEB770qSXavhMVK2w7zGOkHBDruUHGRnaKQ4tjze66jvDp4fPOFvYK/5j/ 1Z634aDMors35JqDYq1vr8FEBgfrqw1ZRRMdFer/VS0O/gE5Nuj3 "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV1gdQlGcex/FFBAT1pLzvvoQioSjEYEG319/uRkQUESxBVwiIio4KI83I ISDNLi0WFA8LngIxUgJnQ4qUA8QCUQEVTVCSEwQR8IQEuIWXm3l95tnZ+c47 O/t5/8/MO6/1xiDPzZNYLFaR5jP2jTNa7cmWbLDGVowK0Y12Hi3abPie3vqx c48KDT0D0icdJKR1V5MMQ1Rw6AvN3l9NIi3pQf3O7SokPT+f9u4CiY1vG3K0 /VWY/GPkX3qRJHJarzg2rlPhgJ/O6yceJHb4+nq0uKtADYtd19uRuPL3ftMv FqtQHPXl/NQ+Aj6Om+NShCr4dhSkRpUSOBZckKycq8Lelvjf3E4SOD+3c/RL WxV2O28//zSEQLK2qL3FVIXlc7c8MF9D4Nv+f4h2/k2FwaNhO8zEBD6OfqH7 TFuFmK3p3zfNIhA4O3ex7aAS7bcf9TmTBMoCPAcXdythdXhmW6g+gc67M6xV 7UrwmqL53pMIvBe13zZrVuJ06sDo6KgJFo2tQiUWj9w4F8Qi0DwnlGq6rMRR lV7cHS0C/Ca3BaEZSuza+OKfXdoE3BzL9rJTlOhZL5k2pEvAnFc/eiNBCYO5 doUdBpr7eR9Y7BOhRFnzD2cKZhBoU+eenxykhLHPsSpvje/x7pjyXH8ltEoM nf4wJxD7TTe52kuJVi+r2LlcgvYsUkKf7bfBREogtHr74UZ7Jf6677lUezGB iwpHVrCFEnlx/S7DyzX3mxWaYmSkhC3HWa2lmVddzzfyfB0lvF4tiZnhTaDC 5qy+x5ACKw4M/st+M4Fs6d7377sV0HVUT3LdSWAv3vQltysQU7/ju/AwAvKv H5s4NSuwqPjrRH7yhKdQAXla86s9pwg4FwcnNV5WIOr6x0P/Pkegm+ViGJyh QNesxHjbbAJfmRQWGaUocPBZYsOhfM15dRVG5yco4NXyafPIDQJex1wDPSIU WGv13C2qgsDy/4bv6w1UIP7qggSDegK/2AtvpPgr8Dru49SLTZrzskohF3op UMaOFD/o+f98FHB7eev+gU8EAqp7rjTaK1AaX3DCW4tEsEISHmyhgLGeb5qb AYmVWaZnjI0UcNlSWellQmJyTzxVqKOA34WXc6ItSByz3te5agjwvpVfVTaL xDvxdGqgG5Dki45bzidhLfvq9Il2YDguIv24gMQch8ehgmaAddDS5fW3JDjj 8wHsXOyPZPqRyD+s+7jxMqCXHBpxaDuJE2tPzg7JAC756phcCiPxOu2NPZEC jNxoWdMTTeKUqre5KAEgMnqV2w6RKNp8U+gVAXTourUaHychGILrn4FA6FCn eVcmCTutBINMf6A0/L7eQA6J3RGJESovYHruppn3HpAT8wE2HBix8HxG4t7I /rVN9oCFuquX9zsJHduzjmEWgIvtvLMRfSTaMoOLTI2Al6/uzrRksbE6bEpv iY7m/9Ouhs+czsYT55I7tf1yqCWdWVFmbChXv2WZt8khaY3Mljqw8db41JWg GjkO79wYr+ax0RhbXVSTJ0fZ82eL/LawsWV8yVG5xcH+fRgb2lF+5fnucvg0 p9pb7mfj5yUxOWyhHElO5tw/0tnYc7fC+riNHKuDy909fmJjZa+D/dxpclw7 nbDbq5IN8aOCm20DMlzICfhx+BkbIn/f59kvZXC4ENCNATZcLzsdOVYrg/O+ BKmNIYWgs7PrjhTKsMmmcfDRXgrrvLkLKT8Z9t3JWGWXTsF6zUf9kGUyeAkm P5TnU9gZy/G8ypWhK2lKkF01BfGbHoNqKxmEVdkLGp9SSNzrwCnRl0HZ/Dux tIPC6mVtDal9UujWVpgf7KWQtcKo2fmFFPEnRYtTBymE7i/3bKmW4o7KPWXT CIWagW6pa54UR0vGHsymE/ORQl1M92CW+1CWuxS21+g+1i7QbCk6LtNtazO2 pMg8R3ex71TNlsIzne6lmf2aLcFoCt1tL8aWBFmH6A62qNllUSOBKo5uXXWe jjpPgtnb6Q4Y90gQ50/30LhHglA10yPBJ0+mRwJDV6ZHglug23XcI8Ygj+kR o86R6RFjng3TI0brsObxPEpNzEcMYR/d9Hw01/9DN+0R4/qvdNMeMX5ppZv2 iDH/Md20R4Tah3TTHhHON9BNe0S4Xk837RGhr47pEaGzjukRobuO6RFhcKLt xj0iTKtnekRwqGd6hHCvZ3qEiKxneoT4+TOPEEfvMT1CnJto+ryEWDXRSeMe IbImfj/OsREirY7pEcKmlukRYEUN0yOAWRXTI0BCBdMjQMh1pkeAE0XM+Qjg Xsj0CJCZzzwvAWLzmB4Bhq/RvWzcw8e0PKaHj4I8poePnnymh4+Yzzx8JNxk zoePDbeZ58WH3h3mfPjYV8r08NFQxpwPD13lTA8PzyuYHh4y7zI9PLhVMT08 5FYx58ND/UQfHffw8FMVcz48eFYxPTxcr2R6uHh1l+nhov4zDxfflzM9XJjd Znq4CKfuxQ4OUTirP/2HypVc9Dg6Te3opGAVPm/AT8pF/F/z0qsaKXTm1h2U OXKxMLHK8dQ1CsM5v3qst+Tiz9r+Ku9YCuqQELciQ42n5vYm9jIKLJ2YSHdd TUdb6lfoU+j+Tu+lwwgHQ73sQt87bMyK1w9TfOJgwczsjR+2snFpV6IsvZ+D iybGZtJsQ+QmkoG+9Rx8MjcWVDbo4lZQakjOJQ66OIILCfuH5E2Owyt2x3Hw 7tCU4aePfpP3lqxh1Wzi4PS6tk4jraelprYZ+9OXcpDrI66b2v+h1HnDw9fd Thz4mCzp2bZwpDRy2weqxpID6frpYddKtMtuuk6ytpnOActa7R0WoFc2/v7M 4uB/O2UUGQ== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{5.528873011563348, 39.}, {11.999999999376143`, 38.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxTTMoPSmViYGCQAWIQ7TCb8fEEWTEHBhBocHao/cT2T2WWmEP8iejDmyqd HQxSch981hN3sGiqOqxd5OwQ/sGk6+9tcYd23RiG7Exnh8/TYn87LpRw8DnF UFUQ7+zAGvHc+GCdpENnRIaBTYizQ5fxJePqEikH2xuTlM+5Ozu0asr9zm+S dsjwbAhWs3J2+Gp5unP+ChkHrjUGB1y0nR1updy8z/lc1kGZYUmmprSzwzx1 9tpTMXIOvmu32VwRcXYQmZDOm3ZezsHv4lHZ57zODjbzfk24YyfvoJ5zkSeJ zdlBNOgAu95qeYertTc5Xf85OZwPvWOhy6XgEMF2T2TCVyeH3KuFzw1sFRy2 st7XdX7j5PB4+QL+RXkKDs+q74TEPXJyMDqbsbFhnoLDu4xrnQ+vOzlEuZ46 c+aMgsPZMyDg5HA0vJWJ56eCwzG9uP97DgL1e0d9Pqyk6KAgpsnsv93JYaOi 5/wvnooOt5p0bzStdXLQvxnINi9P0eFjSXZdxBInh7iiEo0DExQdMt48+np+ tpOD7dsNrNEbFB3sX062eznZyeGcJ/u8vLOKDqUg5T1ODnwd5R9/PVd04C5e 5MzY5uTAsIIRGFFK0PhycgAANx25WQ== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV2AlQlOcdBvAV0SjghcgRQHdZjhU59gL23md3QTCSamlqVGYqaFFjEDA2 Rp3GqzXihQdRQVBQEK0JkXiEaY6KkyZYBQq28YhnNIlS26jxvst+3zvt4zvf DPOM8PLb5//u8n2qphbnFPgoFApbL4XC+xVVva6sjwyGwruWePDs1cYlzzuC kTMrOKN6gQcrj39gmbg7BL5+Bce65nhwaejTwVUNoQi6eH1d7UwPfOJ29D7a FobF3Xs39fuNB7d8KwIvhoUja+TOs/1zPPiw8Tv7pbURKNnelV+f7oFRtWj5 cc1w3Mkya06neLBiyuzu2n+NwDeaM0m7Yjz41cFTxqZuJYIcH7/tH+TB7TUT mmtjVQiNn/KBcZAHj8elrGvJV+HbzkU/V/T3YObTuZ8PqlJhkn7wWFNvD6yb Ap1lJ1R4/xdDDwU+cePtkCEhtn5RWBNTqtXccWPYH4vTw2xRcDUXfTH/uhvh ZxNbY4qisL93a67vZTdKI7Jr8rdH4bLfBv/jp9xY3FRiTy5W49zhOq2x3o1t 5gm3yteqse3nEv3DKjfGz/g6vWCPGnlF196YUu5GhflIWt1hNaINfqemr3Kj uGn0sVf/ocY1nFwwaKkbZ49PePLbK2o0bsnOmfROT159q/3aDTV+lzY7L322 G7NvBjvPPFDDqjTVd051o/zh1+NSn6nhm9MY+ex1N17b3TM4RTQM0nJjosjv nojrudyYInLrnIiey41CkQOHeJcb80XOberTc7mxUuRd4x7Vj3vkwjaRb/zk XS4cEtlUdqXncqFT5D8knl6WeNoFwx7yHHDBKfLvvZ7dLsSKfNTrqXbhKns2 uLCUPctduNdAnoUuZDSQp8iF2bvkbPZ6prlQUk+eiS6U13I/LpTVcD8u3NzO /bjQLLJUzxAXLm7nfnp+Xw33A+TVcj9A8w7yXAHm1nE/QPteORulfoCrH5Jn N7DxI/JUAx37uB+goon7AW6L3CD1A1wQ+abUDzCpifsBCvZxPz3+vdwPcH8P 9wM8eOH8APkvnB9A98L5Ad4Q+ZWaO2Nq7jgRIPa7eN67nAj6k5zf8m7X6sR7 4vf3lTZwQvGxnKdLy4m/7Jfzw3rvC3TiuwNyXuut1+REwUE5R0nLiTEif5Ln 33M5sf4AexywiP0uSB4H0kU/0strdWB/o5z7SB4Haneyx4EsMf8HkscBVMtZ GrfJgRWVclZLHgcit7DHAd9Nch4reeywlLPHjpYN3I8dm9ZzP3bElrHHjqtr uB87Nq5ijx1xK9hjR/0y9tjh966cx0geGybPY48NG4vYY8OhAvbYoEyX8wzJ Y0O4Rc6PJI8NA3TsseGuhj02dKnYY0NDOM/LipJg9lihDWSPFVcHsseKwn7c jxWNfbkfK2L6sMeKzt7ssaLJhz1W/LUXeywI6MUeC0oV7LHAqmCPBUoFeywY oGCPBaefK8hjwRKRoyWPBT4iyx4Lpj5TkMeMbU8V5DHj0BMFeczY+1hBHjMa 7ivIY0bZPQXNy4yOu3JeJ3nMmCqy/P4yY8xd9pjx3l32mBB6jz0mPL/HHhOs D9hjwsGn7DGhWLxeuR8TRom+ZY8JP/rwvEyo8eV5mTC5L7+/0hDUj+eVho7+ PK80rPDneaVBOYTnlYYLgXye01AfxOcnDfOC+fMnDeND2ZMGw8t8flKhjGBP KoKHsycVIUr2pKIllj2p+ErD5ycVf47nz8NUbEvgflJRlMSeVCRp2ZOC8zr2 pGChgT0p6JvCnhS0mNmTglgrfx6mYJ6NPSk4YOd+UnDSwZ4UfO/keRlxDuwx 4rCLPUasdrPHiJZ09hiRn8HzMuJGBs/LiMLR3I8R/xS5WfIYocnkz0MDZmWy x4CtmewxoDmTPQa0ZLLHgK5M9hjwUhZ7DMjLYo8B57K4HwMWjuF56WF/hT16 qMeyR4/EbPboETuePXrM+CWfHz3257BHD9/X2KNH7q/Zo8enE9ijg2oie3Qo m8QeHXxz2aPDpSns0SEnn/vRYe9U9uhwbRqfHx36F7BHh8HT2aPFk+ns0aJj Bnu0WD6TPVrkzWKPFqPeZI8WxYXs0SKpiPvRYkYJe7QInSvn9x3d5Y7uZKSL v6eff+ZdyeheIGdpu7Jk9FskZ39pg2QsWSvn9jbvSsKQjXK+Ix3IJERslnOk dEOWhBpxv5GR7l1JqBT3I28eCS48EpyEAHG/sknyJOJ+LXsSkSvub76XPIkw ifvVAMmTiIN17EnAgTr2JGB9HXsSkF3HngT8IPYvlDwJmLyT+xmFj3awZxQu 1rJnFH6qYc8ojK5mTzwSq9gTj+StcpbGPSceY0U/oyVPPBZXsCceHeL+rFzy jETqFvaMxCeb2TMSOZvZMxILxf2cxGnTYIPItyWP5n/fL3s0OCz2lzjpGnxT yfPSYHM19xMHnxfmFYewevbE4ds9fH7iYPmM+4lFZQv3EwvzV+yJRcjfeF6x 0LdxP7FY3cGeGER3sicGDzvZE4OBXeyJgaKDPdFQtbMnGvVtfH6iUdrGnmgc e8ETjaJ29qjxVgd71Dj5d/aoUdXF81JDcYbnFYXpZ3leUbh9nvuJQt0l9kRh 3hX2RKHwR/aoUNrNHhWO/ps9KiTcZI8K7Y+5HyXSnnM/Soz28SGPEg99fcij RPZLPuRRwtNfzhrpAW4ELvjJef473jUC4QFylp6/I0bgicgh0gbDgYFy3lrp XZFYJfI16Q0SiRaR5efbCFwWeVWpd0XgPyJ7n3aXJf7/32VPOL4cyJ5wrBvI nnBkiBwqeV7GowD2hKFS5G7JE4ZskeX/jwjFYJFXSp5Q/OAv5zOSJxTt/uwJ Qas/e0JwQmT5eTcEN/25n2Aoxf7y34tgvC6yft6tR1cHBGONyE+bssLmfzoM X4gs/XThMFwXeenu3NtfRg3DsAFytk8L2bf4QhBsIsvzD0K+yNK3FwRhmcgT KoZG+mmDUCuyQlpB+C/ZKQ2E "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV2AlQFGcaBuABxJMoh8CooDBMyyHHXAwzzPVOD+LFildETbwgolGOkWxE jRrQ1Vo1IjIgUfHEazWuVswaK0FdzIouAVaQCLrReCCL4hFvmKjZme6uyjd/ dZX1Fvjz9Pv1NN2EpudOmucuEolGuolEzn+xw+1ucXAARM5VYEH98Rdn33gE 4pv8tzeKllkwcXzOmlEhYmw0ucVWLLagYUmObHHeIKxO6/dr+AILEPnywjL7 YGw7N0SqmGnBV/Pck+aeDkJjvqL2uwkW9I/eeiT8q6GILEi9U81aoDK2rmhf GIJ9rXlZo5QWfHj08JeHt4dCX1ixYJzEgsKZVREz7knwalnd1foBFtRmjd2v DAvDqtWSe9f7WfA3zz1eobPDsH7OaXXvXhYERZyZK9kWBr+BRT++72aBpHlv ZUJjGIJ3Vlb+YGdxts/4pjm9pDjwW9fZic9ZPLxU/WinTooTcUXBok4WJ3ze vnycLYVWm3Gu4TaLXm2/P5i8SwqLeOn+My0sVh20GuJyGbw5VylT7WexNm7q U9smBqeeWRXdO1hEz6xJmneYwSc5HR/PtrHIjqtOqDzHQKHs25K5gUXKweTa P11h8AxXlw0oZHGpeuqbj+4yOFmeMml6PovbhU/rO54wyE/InpOUzaK8PcB0 rYuBIUSz/3I6iwdPalLV7xj0mHQs+F0ai8xdjsGJhkPJLRa7hLyyKdxxsGgQ 8sXFQY6DxTMh+/o4F4s+u/n8wQlPx8HCX8gHUu37U+1mBAr5yWPnMqO/kDVF dx2HGXZhvzUxratjWs1YRz0nzUgT8gqn55BjPyFfcnoqzKjZSTxbzJizk3jW mtFRQTzLzZhdQTw5ZpzfwWet05Nhhv8O4plmxhdf0n7M+Hc57ccMcTntx4yl W/nM1eNjRnsZ7ceMj8poP8CLUtoPUFJKPHcBtpT2AxTY+Kzi+gHG2IjnECC2 EU8F8LCE9gNcKKH9APuEfJDrB1gn5F+5foCcEtoPMKOE9gOoSmg/wKgS2g9Q XkL7ASJs9PpxnL+N9gO8Fc537O4XY3a/MCFJ6POXG85lQq3Qd55zu4smbNrG 557cBiZM3sPnTG6ZsHcfn7v3O0/QhIkH+LzJWa/GhLmH+SzhlgkNR/l8ak4/ x2FCxXHqMaL2JJ9vch4jpp3mM3d6F41IPsNnT85jxKMG6jGi/AqfuziPEbuu 8pkbt8YIUSufwziPEVUt1GPETz/xeRznMWB0E/UYEFBP+zEANbQfA64fph4D Fu+m/RjQVEY9BrzdSD0GPC6kHgOO5vN5DOfRQ5ZNPXqsTKcePUrTqEePaCWf 53MePTZH8NnOefRQDqMePQYGUo/j697Uo0dxXzovHWJ7Uo8OvT2oRweJG/Xo kCmi/egwU0T70SFNRD06TBJRjw4pIurRYbSIehKRJKKeRLAi6kkERNTzR+Y9 iTC4eBKhc/EkQiNkKedJhMzFk4hIF48WQ108Wvi6eLTwcPFoUf+7iHi0qBYy Py8tfhDyZs6jxWUh858vLTqEzHu06O/i0cDk4tFghYtHgwsuHg3a3Wg/Goxy p/1o8L2QeY8Geg86Lw3qPGg/GizqQT9fCRjsST0JaPGkngQc6Ek9CSjoQz0J KOlLr+cE9PCi80rAlffo/ScBIpfrOQEbfWk/avzZn3rUqBJTjxrpQdSjxvVI 6lGjMYb2o8YUOb0fqjFbRftR45maetTw0VJPPL5NpJ54dOioJx6VeuqJh11P PfHwNtD7YTxYA/XEo9hA+4lHl4F64rHCSOelQpCJelRoMVGPCn8H9ahwy0I9 KtxJovNSoWMknZcKz5NpPyq4jebzt5xHBb8x9H6oRNRY6lEiaRz1KJGRQj1K DJ5APUqkTKQeJXZPoh4lvKZQjxJb36f9KGFMo/NSwGM69SjQPoN6FGj7kHoU uJVBPQo8nUevHwWa5lOPAqs+ph4FuhZSjwJsFvXIkeby+0IOXQ71yPEoh3rk mGKlHjmOWGk/cvxipR45Xlvp9SNHp5V65Ki2Uo8MS6zUI0NfK/XIUJBLPTJE Z1OPDKezqEeGpizqkWFlNu1Hhm9yqEeGFcLPKzXetxnvx6Epj89V3ztXHE59 ymduu6I4RC3jcz9ugzg0r+NzfZ1zxeLqBj6/4C7IWKQU8TmYeyCLRfwWPo9M cq5YbBaexxZVB2RVB8TiA+F5oIzzxGD7VuqJQYrwPNbGeWJgFbIX54nB8jLq iUZrKfVEY3Ip9USj00Y90dgl5CzOEw2rjfYzArNs1DMCC2zUMwLFNuoZgS9K qScK11w8UQgSvNy4F0dhmpCTOU8U1pVRTxSOCtnGeSJRU0Y9kWgpo55I3Cyj nj++n+PURcBb6Pc554mARzn1RKBCeB/hOEkR+Hk7nVcEzu+k/YQjdS/1hGPN AeoJx6wj9PoJh+gM7Wc4ss/Tfhzui9QzHD/X0nkNx/V62o9j38vUwyCrkXoY vGukHgb/bKQeBtn11CNFah31SNH2I71+pIisox4pgl08UpxvoJ4wiF08YRja TD1haG6h8wpDezudlwQzOum8JDA8of1IsOkZ9Ugw5iX1SPDJa+oJRe9u6gmF l516QrHSTj2hyOym/YTAv5v2EwJRN/WEQNpNPSH4vJt6HP9f2D+Ce4EbhjYh L813rmHo/I3P3Pt30DBEv+VzILfBUCS6u3N5+zbnCsY5Dz53cB+QYEg9+cy/ 3wZhfk8+b/ircwVhXS8+O992V8cE4S+93YlnCNL7uBPPEAT1dSeeITglZDHn GQw/L+oZhM+EfJ/zDMJDIfN/jxAj4z0+r+c8YtwS8jXOI0Z6f+oJxMP+1BOI zwbwmX/fDYSPtzvpJwB+vtTjD7/mXjV73jGYPmi5b4bJH9fEg8Rr7Ay6Khtv 1LYPRMat+FcHnzNYot3z2+XNA3EsatYcrwcMmq/dW/Rp4kCceb1l6skbDLzX 7os93e6H4lGNrTsaGETrrlq2lfohfHDQ/y5UMQh/U3BUnOSHwty8QvlhBu6X 9s1Tv/TF7lHNh24WM6japct7dsgXq9qSj7bkMhjW1DTma7Mv5p7PPdg1gcEs 3bG3Q+/4IPn2+G1mlcNzvXaTZr0PYs1ta74exGDh8RH2d2ofiO/EZY5zY6D5 7j9sXqc3ev5LDq9OKe7YT80vOeiNV+33fV5elSJz8e0Fsxd448HYaf/1vCBF TXBq8jWZN249WVFh/IcUIm554/+O7GnZ "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV2HlUE+caBvCA7AiCQhAIyJrMsCdhCQmQJ4l1oQUVqqJS6wZqVcTlKqJY Qa0IuBUXqqitu724FHeva13bqlepCuKOiuKCSPCKVPGGmfnj9Ts5h/Ocw/ny m+f9MjkT31GTUzLMRSLRYDORqOMv1pk9Wu4lhqhjzTNg0ouvB19WuaEpOXHU olkGXI1dGbmgrDtml0dq504xIPOHk7kH4jyw4dmJ1Y/HGhB+7SY7MlCCNGXD uKPpBoR41OoWpXijYs6+A5/6GbBn75iH3Ub5oOysV95+nQEjU1MG+R73hcSe OVkjNyDs7YFPE9T+UPevmj3RxwCX1cvuGm8F4HWpZN9kBwP+/nX2oaEegcgb kNb6j60Bvz4xRt1PC4RF6aTFP1kasLpXa1r+qkAUpKVn9hEZUHa50Ed3NRCt vwQss2nTozJ3a4m3rRQZk893qm3W40FS8np3SHHplO7ssed6SHvPT1H8Swp2 9eqrex/qUZDZs2LcDim+f32WOVitR5HRfPLMxTKMvZw+KHezHm0DFm+dv1OG H3OODslcp4f458tvfzovw5vDH/5p/FGP+3f/++3RBzLMXeof71KkR4r98keP 38mgeR/mdXOeHlMYx3z3zgyC3nuXR87UIz4qUZXmxSBxqfFI+CQ99st72v4S zGDt4YoZF0bpUe31wWiMZiDJSaz6Z7AeFotFHnXJDOqMkUOclXo0p4VX7xvI oDDXePyQTI8Tnu5WWekMsocf/uobiR5jrx3f5jSaQdnG+Zbmzno0zvI6sm48 A1HCwGdbLU0+V1V8l2wG22ND3/Zp02HlZgflhBkMlv9oH/KiUYf9ARvW7pnD 4EifppKSRzpUljVMu1PAwD/9tltojQ4KZc6kwtUMzp5UX47Yp0PNydAzy8sZ 5Fval13drsM5lwFJazYxqB5TmZpdrkOrvM6+fIfp/+9GiJxW6JDt9rB9w24G fbN/WL9noQ5h55KkP+9nkCnZF9wvV4dIDVOw8ajp+usO/tqYpcPcWdld159i MP70Co+lo3XoMk9aXXaeQb+jhtmhaTqsHXlT06mWgZJbOjybI/9N9IBB52Wv N1XJdHg4bslzq3oGncZohk+V6JAf+Pyp60sG3SvFGV2ddfizsvfO0GbTPGbl H6q01OG407aw5FYG647MHpjaBgzRWubMbGdgN81S29IIrE/IWLjTgsWard7T Vz0Cih3PD3psx0I/4EJLdA0wooE5ndqDRWQHZx+QdnF++M5AFisS8xqrtgOy qMRycQgL95SpJdPKgUvhc6zLFSz+7NvVwXUFYDjsPiU2lsUm+TfZhxYCK674 3WrUsthim3pwaC5wYOoa7bFeLK5cM95rzwJ2bZm55ZckFr5F2uebRwOzx5yx 3vg1i/WK6Jq+aUDpv2v7P5zACv0AQ5N2HFFMY9FcvLbkugwY/KBXWG0ui3WD n1rkSoDFYw7uri5gEb7avdzfGWi89T91cDGLit7ylGuWQCFs/r5eykJak55s 9VaLQWXPZ1wvN/mt/KKn3tNi6MP10qBtLOBZOaz+ghYrPP3qbuxhUeLqcHLU b1oMHPNmwtkqU38Vnjb3R2tx4pjHfv0dFk5rXXK3Jmnx/PZj582PTf3tsW8a FqPFrdP9Fj55weLTC9F35r5aFGYNc7RrZjGtf8vTMjst3j+03uX0jsXSO0/G 92hJQIhk4Mj3bSwGLr/xetXdBPh4GYLPfmTx+4Qzsz6cT8DNx9fspnxiUZu1 xzp1bwKmpZpujKIgZHIrAS69+Ny6pV/bln4J6KPm89JHKtMrAV0i+Ozv17ES ME7G54Mj7E2vBAzy4fOXG1v6bmyJx3UPPt+727HiUS/m81TJhSmSC/FY7MJn q2F7LYftjcepbtQTj2ohv+c88ZC4UE88lrlQTzwUrtQTD5Hwfn05TxzaxdQT h6Du1BOHBe7UE4f93nwey3niYCNcXxvnicNfPtQTh1Yf6onDCh/qicOaHnxO 5Dwa2HhTjwb1ntSjQcRnHg1qHWg/GuTY0X40mGtNPRo0WFCPBofNqUeDRhH1 qFH0SUQ8apS0i4hHDeNHEfGocUrIvEeNk0LmPWr8LmTeo8ZZIQdwHjXOCZn3 qHFRyLwnFpc+Uk8srn6knljc+MwTi/rPPLF4KWR+XrFoEfIyzhOLD0LmOH6x sGinnlg4tlOPCh7t1KOC9LN+VFC2U48KI9qpR4UD7bQfFco/UY8KzmZ0Xiq4 dqLzUmGnJf18xeCSDT0/MZjXmZ6fGPzuRM9PDDr70vMTgzuB9DzHwCuInh/T /qFmpJ8YPIugnhhMV9LzE42sKOqJxs1o6onGrhjqicarGOqJxusYep6j8VHI SzhPNFxVtJ9oqFTUE40MFfVEYYOKeqLwQEU9UQiLpZ4oDFVTTxT2qOn9MAot auqJQrCG9hOFJA31RGGUhs4rEpka6olEmoZ6IqHRUE8kSj/zROKims4rEtc1 dF6ROBRP+4lENvh8iPNEQtST3g+VyOxDPUpsTqIeJQ6mUo8SPhOoR4nOU6lH CTaHepSYnkc9SjTm036UKFtI56VAdiH1KDCziHoU2F1MPQo4lFCPAu+K6flR 4EQx9Sgwqph6FLhfRD0KqIqoR46sxdQjx9xC6pFjwiLqkSNpPvXIYVtA+5Hj xjzqkWPP9/T8yLFyLvXIUZhHPREonkM9ESifTT0ROJpLPRHwyKGeCIyfST0R eD2DeiKwewbtJwJbZlBPBK4JeWVCQ2lCQziihf2O/adjheNvIXPbLQ3HDuH9 7bkNwvGV4L98qWOFYbRwfS3cgQzDcOH6vTouZ0oY1EI/X/TsWGFoEfKE0+KJ p8VhWC70uYrzhMIxn3pCMVHIjzlPKCqE3JnzhKIln3pC0LWAekKQWEA9ISgv oJ4QWAvznsh5QrBkPu0nGCELqCcY9QuoJxhHFlJPMGoLqScIvYqoJwhlwnnn xj0lCFXL+NyL8wThZSn1BOFVGZ9LOQ+L6xuoh8XPW6mHRf9d1MNC/SefOc4l Bqer+GzkPAz61FIPg6sP+MxxejL4up7Oi0HNc9qPDOmN1CPDvSbqkWFEMz0/ Mjxopv2YnmubaT9SLGumHimCmum8pCh/Q/uRor6JegJh00Q9gTB7TT2BqHpF PYHo1UA9AbB4Rj0BcHtKz08A5tVTTwDi6qknAEn11OOPffXU449JT6nHH3nP 6Lz8MeIVnZcfrjfSefnBs4n24wf5G+rxg0sz9fjhfDP1+CLRSD2+KDdSjy+O G6nHF6lG2o8Pkoy0Hx+UGKnHB04t1OOD6hbq8UHdWz4zeVWyvKoeULzjc87M jtUD51r5fLFjO0kPbGjjsxu3gTfOm5lzee1PHcsLrzrx+Rn3AfFCgyWfY7kb ogRHrflcVNixJBhqy+eaglDTS4IrdubE4wlxZ3Pi8YTcwZx4PNHDkc/dOY8H RjhRjzssnPncwHncsUnIXL2PuiO6K58Xc57uOCbkW5ynO9TdqMcNe7tRjxs8 XPjM1S1xwxwh8/2IscSVelxR60o9rvAW035cMFRMPS4oFlOPCyrF1NMNVWLq 6WZ6HqSebmgWU09XvBRTjzOMQn7OeZzh5EY9ToAbnZcTfnCj83LCPSH3574A uyC5O5+bGjuWI64Kmf8+dMQ4dz6HcRs4YJcnn/nfE+yRoZzne8X0fJ33cXih tsAOgbPaFqpMz+M9piX3nX3bFi9eZodqX7JwX2k2oz7BFvuXPnKrMz3vZ4zI ccyvsMHC4Slf+P7Bwq6msuuXATZITz9+4MNeFlb/7C3ouc0aqsKA8dNXshj8 x9ThkxTW8Khb9G3hNBYiQ+vWcxetYP7d0zJVMotPY3VDksZbYewTy1Pmtxmo B6dlHR9pieovt02uyGZwpvdf5rlZFhiw/uL2qC4M1sWuFc9f1gnXbk0ct+Gg DCdCzu2sOWuOYWalv9VnyhDh+9WxXEdzvO6mme/oI0OTODx5/EQzlDhn3HWt k+KDQ9a3W+6JIG9zOvWhQoo0K9um4AwRHlxOCD4zTwoRv/B/lDI0LA== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{11.999999999375575`, 39.}, {11.999999999376143`, 38.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-1.8733706994324848`, 39.}, {-3.000000000019554, 38.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-1.8733706994324848`, 39.}, {6.999999999384613, 38.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNlXtQVFUcx9dVigR5yMA4S9YEwrLryuxeMOHu63svxkAmS4yFj3jkY81C CAkoUIdIsociNCrE0KxOJIlmKFpOY8yxBMysVBQZkaIUGx6iIItJG7R7z/3j /Obs7nxm95z7uZ/dmX1mbV7aBqVCodjsfnheL9lnup9jiMIzZSL611F27so4 M/WOiKPZlD/e+27jmgIRCzIo/xCSczYkR8TyVZRrg+bP1q8XEfUSZX9pg4iT qZSjtl1Rb0sTMbqMct9Al6s5SURfImX+8kFFgkVEmUA5RhoRKSbKnu1X1CLa l1DuyH/SvUQMxFCeG+gZEaf0lNc0e7mXCF005S9skw22SQHLdZTvjXhGwLyF lOMqb7mXgEot5fcWdZcv6hZwciHj0+L+vLx/q8enUcArMp/3+NQLKNMxPtUC ynWMT4WAdTrGp0RABOuTK6Bdvl68x2edgMSFjM9KASoN20dASRTbR4Aiiu0j 4IiaspQnUECRmu0jwK5m+wClarYPcELN+NwC/KLYPkCn7BMr9QHitIxPI5Co ZXzqAZeG7QOs0rB9gEz5/ENSH8BXvv59qQ+wNoLtA2SHs32A1aFsH+DfeWwf YCSE7QMYgtnfD3A2iO0DfD6X8vOO8WTHuBVXAyn/0esZK1bIvMVzXIcVkTI/ Jh1gxaDMdmms8JfPe9TguUErHsjv7/bkjbOiWuYwadz7Ayh/k+3jXlZM+7M+ Flzyo/y75GNB5hzK0u11WHDIh7KX5GPBnVmsjwVtSsr/SD4WOBSUpa87zoL8 KaXE4ZKPBRaXkvGxYNYk5WWSjxnnHioZHzO2O5VMHzO4B0qmjxkHhpSMjxnL s2LVVdMcWfNy0tBpmxlTrefrMcWR4MOhaTHxZrTMJtmBLo7szeyruxZmRo6o KlA+4khn0f42h68ZGvv1ziAnR66Pmq9UT5gwVPiw/Ln7HDn4Wxc50mdCc35J Wc0gR3QBr1bfvWBC6arsi0/c5sjWlpsJ6adMmL+bT87t4MhGyceEyE0zxhyt HIk5tm+432bCUV/NLw9PcuQt7xfT/4434avi4zcKmziiLaw99PoCEzRNdSqV gyOp42/cyPM3Iazh9q7bn3BkuOLnsYlJI/Zv2GO4VsGRSc2396bvGPH+SJ33 cLH7+n3Rlz/qNGLM8vhczSaOvHmYq6khRkR+3dGdpOLkPkZsLbyw474XR9q9 OxsnbEa07qjZ5D1qIK1bEpdqeSOGbkbvrOoxkNQGYpwRYYRie1XvB20GUvyZ UFka4ObXzuSMHjOQuMyfjJ+6eAzWnYi9UGMg1XfSl64e4NEaUrA4qMxAyp+9 29jaxWNbz3+5FzcaiE/Kh/b2czwiBtL+dKYYiG6Rriy/hccLoVdLkyPd+1P3 ZfXX8Fjs3Pd0jsJAbIlvm7CdR19R7cWMXj1Z73ctpNzOI+VAT/lT3+vJr18e GWlKdZ+fnyUec+hJdbDrx+9MPPIGw33mVOhJ04r2/ce1PMJ8NL38Zj1R2Wdv 3KPiUduZe3rJSj35K/l87ApfHpcSnPUzE/X0/0vB438JYXpv "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxVlQ1QFGUchy8ZKFRUtMFU0PgIND/AO0527/O3ax9qEidhISIqCCqiBqd4 d4mIWjFmlKSmiJIfYGl1qIxlaL2ADFo2IphSUyJJpoSGdTCGQt3uuzO995+9 u3lmb3effXbvNjh1dXz6AJVKle9+SZ8Y6OV+1xGVNBtFbBxGuXvbgjP9dhGZ Iym/s6PgyHyriIdjKdcGZNUEZInQRlDePSJoYNQSEQFRlIfKG4g4yFMen9cU kRcv4sp0yjfuXH1UOUNE5cuUdZcPqKabREQnUdbII8IvnbK0eVOEiI6VlBuy A92LiG/XUB7uL42IT+2U51d6uxcRxespl8f1Ho7rFeDIo/znPWkEZCjruaKb 7kVAgrL95sktmya3CDiawficFDBgMeX1ks8RAROTKZ+XfEoFBCcyPtsF/JrA +LwpICee8XEIuGRhfFYJeBBHmZd80gTcj2N8EgUkvcL2EbAzge0j4O+5bB8B 2a9RlvP4Cxg2j+0joDGJ7QM4k9k+QGUK43MTuLyI7QPELqMcLfcB8jMZnyOA NYvxKQXGr2L7ACWr2T5A4+uUK+Q+wLlsyl1yH8CRw/YBunLYPkCSle3jPr6V 7QPssLJ9gGore/8At61sH2C0cn/NKnPNLHOZkaBw6y/SmLFD4Rxpdw1m/KSw j7wDN6+lnCGPGeNzKf9zWDpBM9Yp/K6UlzOjTuEQeczwW0f51KJB7sWMV9ex PibsV/i67GNCu8Ly6TWYMMFG2Vv2McHLzvqYAIUfyD4mWBWWLzdnwl6FQ2Uf E760sz4mXFD4JdnHiEY762PERTvbx4izdraPEQs8fIww2dk+RoR6+Bgx2MPH CJeN9THihsIzZR8DGm2sjwHExvoYUGVjfQzYpfBS2ceAIoV7ZR8DttpYHwMK bayPAW95+Py/nl4vPbZ5+Oix3cNHjxIPHz3O2Ng+epx49PPCun6eHCvJKyu3 6FFQuDzf7yFP5n7VFXLLoEd44Ccp1108Sav/pitioh4Hv9jbp+3kSXN1xxMr xujhShKSn2zjycf7slc4/fQY61PisDfzpDUz4anux9x8ujwxvY4njtAPhhoe 6NBjXdJzrZIn9obJc7Z06WD4vM/yePg0Eta+U5seqcMzU30D17u05Lva50dF hukwbt6y+Zl1WpIWfzd230gdJoSPGdpUrCV3irc1O311EHcHx5xM1ZLkLaFH M3p5ZDnfaPbTaMnX4Scu19zhUbFiQnubl5YMc3Czaq7x6Lr47PLIH6JJ3IZT I9LP8ZjdnJ/aUxFNNmgmTfnMySMpITN/a4OGtG7SZdeBx+kCy4cjj2lIzwjX xNtTeSwZFBNheU9DCs/rVONCeCTeD4qMXqMhxR8NubfUn8cujbezbp6GDC9d 3V37L4egps6KfrOGDKxeEBB1l3Mf/0rAb+Ea4uhrsTh/5DAk7Gx/7hANSU1r O4x6DmuvladU9ahJbWfu8HYnh/Dfi6bta1WTkj3ScFh89PjevAtqUiQ9Tjdz WGp78dCBKjXBpHif/as4TJtjifU9oCbH5R8oh++jL+6pKlIrz0cOU0KrCw/l qcmllvo/ymI4JAYGjb66Uk02yP9nHGY//Vfs7IVq0iF9fRQH30hdmE+8mgTc eu7tAYM5vD+ju9TrBTV9vqs4/Ae+uOQs "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxTTMoPSmViYGBQBWIQDQEeeyG0s8Oh+8skTP/Y7v3aE7vn308nhzSnas63 qip7u6c0Lo/+7ORQUA4C6raHxHIOir1xcqidnXTlw3ZH2xnCslwGT5wcvDP0 F+5t8bPlB2m47eSgoAQCYbYatZfUay85OWyefiHOqTrW9sHLa382nHByyO0K PHx/WZKt1cWFDM77nBzOgEGarTEIbHZykBXTZPbfnmFbA9K+3MmhL3OrrO+7 VNvjhTLHC+c4OVj3PbboexxjKyQIBBOdHDTKPv56zmtkG72BNXpDq5PDq31c xYucY/cu9f+1xL/KyQGsT6Zo7/t3QJDn5HBCL+7/Hsf6vZYgc5KdHGI+H1ZK TWjf26x7o0k3wslhJgjcnLUX7B5jJ4frLCoPuucX7++b4cnvq+HkYPT15P3u +ZP383Yt5o+RA5p3a110rfCy/evZHU0SRJ0cJgtsBMpv3l8kqFQbyevkcCet vtdr5b79kcvdXrmzAf1nsRCo/tj+pJPrqrUZnByixGr1/HjO7e8vjzJk+e3o ILB8JVD/5f33NnpyX/rm6LD7vSD726s39gdU1HBO/ezosOWsr0HFvPf7lTaf b0984OjgM4XBoGnuj/2l/+f/PnLO0UHp0IojagEMB7xj36bs3+fokHCbR+j8 a+YDS85sPxywwdHh4VQdhl2K7AfqfP+LVy52dFj6kb3/+UfOA7fvH060mOHo sOrdvH3hMTwHdjezLuzrc3T40vOxjyuR74CM5ZGr1W2ODg1n/gMB/wFw8mlw dAAAwqQQsg== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNlglQU+cahlMC1DGKqMji0g4IrTvOhTYbyffmaBXiAu4VUBABUa6CiIi9 WBVRUSsV5XLR6y0qq/Z6ZVEQbQE3wAWtFJVCAy5lR2VJYhKW3JDjDHzzZc48 k/n/ec57vn/OsQ8IWx5kwuFwEg2/wStb7r+y13nIm2deXLeliJ7ssfTI0DKI i1oStMjqEXWtWVKr6mLA2RHmsdjiBW1KKMjvamEw/s+3a/+Z/5Lm2i9+llLP wPeeKtr/aBMtsbSg9ioGq3c+2X+Y95aKffo6W+4x4EZJRAcnddN+rk17YiGD AquY7EhzNZ3+dP3spiwGt5PTeCcX6Mg05GlhYzKD8I7TAvvveunPEX9d3JnI 4Ptpq8L2H+mjzcd8ry0/xqBN/uxKXmQ/Zb8X1cbEMbi6YqLuqniAUr7aa6uM YaBgHJfG1w+QZN308OuRDIJte36etU5PScHCV/dDGSyqPjT+QqGeUpddCZ0W wOBEVENcy1s9rfvs2JjqNQwqVX16Q5GLsRj8o4flPVVfGppBq5Ll8u2TDc1g rI7lcWMHi4HapN/IPjlmhmaQNIblDE9duqdOhvefs/z+3WDJYObKsiDhjaFl qFnE8oHZNbGza2Q4fbF/yCdfhqTnLMcM+mTJcM1hwMgVgz5nZVAdHxjySZRh ja1+yOegYf9b+iGf72Sgb4yDAKPPNhkcilgWDvpslCHZ7RMjG32+laFpJtfI bD4y5F5lmc1Hhj12pkZm85FhoTfLxnjGyjBmF8tsPjI8D2OZzQc4O990yOcd sEHFHfJ5AzjGcod8aoCJ21g/V2M+wOWHnCGfLKD5a86Qz1ngqJ9+WD7Aib8P DMsHqE9i88005gNE17DPt9OYD+DDZ5nNx7Bfbu/Q8/oW4ETphs0PEDNFN2x+ gOJK7bD5Ae4c0g6bHyDeXTtsfgDL8SzLU5UeqUqCT5PGyA2KwSKE3GY5YnC7 coIwi2Vz4wYE150sBxuLkLOFZW364A0S5m1i+fhgvAJC08f/HYxFSPm4vsCf Z2iC/2HNMB8pROdYrjf6SOFUyrLx9sqlcGxm2czoI8WjOO0wHylS7nPn7+3V 04jM5XaXPaV44Opg2W84j4+b5480FUoRVLYycPcLPeXPlAhDHaTw//7fUBrO b8F2ceZrnhR3fdXpW3/UU20RLduikiBhQ1Bio+G8TzGVi0waJLj5Q4uZ71Q9 7fPy3nCpQgKv+r0mTxsGyCw1vCwgT4K6sLpzk+/3kybTetfzQAmujBT2tET3 08PmWl3IUglehVdO4M3qp+uxaT918SWIvJAy4sDrPiraFR4Qbi9BQOqZh15n ++i3MtmCxpES5G76fX3k2j4aCLOReynd4NvL3H5r10fzd3RtzVW4IcS7VfWL opfO/fYkd0S5G6riyrSv0ntpXHzehNU5bphjXzFgqtPRX/efnZkY7Ibz2cl0 p0xHNdvsbDZ7umG2962yoCQdTQmYd/WawLD+K/ekjgAdXUlbEcFxcMMx8czs NX/TUaKLfJkHzw1+oVtMskx0dHvsl8tOKMWQ3zNLq/1dS4y0bfszhRiLPfqP dGdoybLoVL5tuRibPngVvovW0pzYqdbeOWK47M/8xadNQ2lN8qqlwWIUC1oP vizWUFDsyLUnPcWQJhYkXzuloQmqEvkzgRg5Ry3e14ZoKEcammXjIIatU1eC l1RDrn6jwtbyxIjwXx9lbaWh9NVp588oRbjttjpjVtsHMnGaS3UKEUxv1Ew6 VfqB3B/kLZxULoK4pvEPj399oJgFM29654hwy+U/TrvHfSCB+rlfULAI3E7O 4Uutatr8Rd2MdE8RdphMPdxQqqbsvI3vXwtEGBfK/cI2RU3dZ8Iv2zuI8HL6 hY0rw9T0TcMnQf48EWqlhnfDAjVl7rWxTlUKYXpp4s0XU9Q0Lia3VKEQYl2o svozlYqOVD8JnFwuRGPsD8c3P1LRqCMRJj45QgTH94pnuas+zrMQ2eQK989V VFBd4ZPhKcQLlx36XpWS9l2YYtUoEKI78PruhY+UVPok8EcnByE0VdwrMy4o abfvT5XBPCFa96xKzdilpEvuDx5nKwWoCLosv75YSauSWk62KwQ4cZSXG2Cv pGjS2jmXC7CgI6wqXdVD4+V9G3fkCHAmulG+Nqjno48ACrGTedu0HoqPOP3U z0uAx7WHD4Q+6qZKO//2x2IBtq0afUfh2U1zfG/k508T4MbP1+4iv4v+J8ye YWEjwFXFvvgkdSd55k33qjcXYH37Nos/7DppdJnU0VHDR8hF/X8ni95Re2Rz ZkMbHxEum26FcDqouXhqjWUDH88jrbyTD7USN72nsLCaj2N3rXT9zi9p6y3n p855fIgXjZ/buOYxXY+LEG84ycc+2xrzDsX+kpdvb6oX7eRj0krn1hXnK0sa +3jcTm8+yNrOSXK6rqQiN8B/yTw+LsUqoldGvik5OqrUInAOHxdvSi9H+bWU TBvtaOE62bD+6xxns4SOksz8hPW/juKDo7U1vA46S9jvHz7+Dx9eaf0= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-8.256772299473198, 38.}, {-10.999999999891713`, 37.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-8.256772299473198, 38.}, {6.999999999384954, 37.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxVlnlUE+cah6OCCkIBsVgtKCETwZkEqYokgSTvjGjRa0EWcUEpqAgqi9gj 1V44UCO41Eq5IFXEsktYBAQXqFVeKArKUrEIKFdaZRGhF2WrghAuIfkj/Z2Z M+c5M9+c5/xmvu987N0hbn4zWSzWqalTeTWX5ci/lpkjazprofJEZ4PreXMc ObvrF8UoA02TP83WzzHH7xK+zfYaYsBzuNUl5645VpoEVpj8xcD63f/JXdZs jheMzXRtOhm4sqHWJPqNORooB7QxcCRXllCly0ariMeWEY8ZuH7iNqfLko1/ vm4eL6phYHfr4aru9WwUNaax1t5lICorJ+yBPxtXKVPCQL528YuR02wcnDVx pyubgej57flN+Wy8bBf68G4yA3p1/Fa/R1PPN8RuuxvHgGRl2p6cYTaWVG8L 6IxhYMk6gUvKIgtcStSN2oQzkKc1lPS51ALDOl7rZYYy0H2ocX26nwWWahen if0ZqD/9u1vhWQvsPEOUTuxkYJAfIl4RwsHGiQyb1QQD0uMeA/HfczCOE7py 9FMGMiKrHP3kHGyL79n/pTEDny4rt8so52CBs27LPl0Gso84Pvzidw7O8Wg+ ZjCDAadgj/G9HRzszdjktv0dDQqDN/U9bzjoKQnycfwfDQ93LJA+fc/BjRxB 5qOXNOQ5V7msUXCw2u2qmaKFBlatYnJykqPuh4Yzd1Qcrqw3mwarYhXXhJpW hybT8FSu4vlGU4mjITVNxV5F2l5F0TQcTVZxlstYpss3NOy7qOI3/VMJpiHg goqF5zoE5/bQEKG+L+O3Hudvo2HxFQ2fVTSM56h4+nNb0gBXVVyt9DGloaNQ xUbToaHrmoaPNg3rSzR8xgDmXtfw6Qcgr2v4dADkl2j4tAK4q9+/erofAJtQ Wf6qGQTe27D/bVc2wJUyo+IGLQJ7nC0SypMBSk/lGDbqEniJ8V6CcQA+7Rtr RMYE/pcwi30VA5D680jrvCUEFo14d9uGA4Sb5TKOFIHzb3CIvFCA/tkB2p0i ArX3HHT63B/gQ9gKdt8mAk9N2rrr7gIQBa6MG80i1P0AvHtR9l1cOYHsM3Ve elYAtfNHxqg2Aj03F9LbzQBuKDraa94T2BTd1rnIGKA4K8Yu4BMuXiRd1znr ANyf81xLV8TFjRHm9/+alEI/8Wp9wS4ujsg+Cyf6pcCfyJzwkHGRt/9J/trn Uoj6wWS5IpeLwzy9bRvrpeC+fE213pNluG86UhjqmkHXLrTECkoS3eMihXkL dRqsvCzxqmKwbEAohQu//CuYm2KJ5B8ntI4TU9z8gF3RYYm29UN7LxpIwchP 1vPBygof1Ujb7D5IYML/aOWTYCscbwzw3/VKAj5/yAudb1jhzZ5gHd0mCdjV LijaN26FM/TdKsQVEpA8PUY/dqKQ35AeUsuXwO7MTywdQyikDWvc+ywksFPv Ld8mjsLij8sOZJlIwNqI5ZlYQOG/249cH50rgeZip5SwagovH1DY9IyKwW3g gU5jG4WmP7v9eei1GK7Uyc5n9VE4XHe4Mr5FDI8cw5jhvylcluHdsrlqiren Gd6ZoLDEwWSpvFAMIj3tqXWQp+5HDGd8Y8/JFBT2vrSreekihjEfa9FHYxR6 tD2990wohlO6L2emDlKY6rLpS2dCDLbeuT2CHgrrpbEJYgMxsHae7Gt9RmF7 XrqffMwBemcdmxf1kMKm+JjH57odYGhLpJP1LQrz3ona3j52gMVuSekdqRT6 tZRHNpQ7ABzlmvtrUciq75W2ujnAD0u2/MjpIzHZCqI+AwdoXnxooLWJxK1z 7xEGfAeYHxRmfbKCxBWBx/ihixyA+TjA2foaiRYeu5K2ajtAgPE614YMElfj oYOVb+0h2l/fzv8iib5FJanX2uwh0ahi8n0cifnEMhH3vj1cNvLJk31P4gKz GjuzInu4v79XOOcsqe7HHgoOqHg0Uzlh7SHioIqnp6fAHmwCVcyxUGZqvJpv +sybOuwBglS8MWV4Q8qwCFLU3P5cGRG8VPNh5fJRLQKdYBXPnl4wRKAXrOkj Alawpo8IuoM0fURQqmZi2kcE4UGaPiLg/cNHCA2Bmj5C8A7U9BFC+0FNHyEM /6MfIYwZc3sfTfV3YEdW1azNQnA0fjLGjyfRuSz2lrdICL/5jx1ckkyioYwr /ZorhCSj8+J0OYklt/Z5fWEkBLlhVkhZKYlrtrrrvZgQwN97yZl760i84Nvn urJPACc/4o6kdZDY1mzNo58KYIf+eaevFCRO3DS7pF8jgCDfb8ZbTClUzCj9 6cdbApAPJBoVbKFQVrY8gXdJANcTw0q/PUOhvLsMK6MEELt50YDbbQoDTwcQ OwIEYL808jZb+T+n2ZYPugrg5kz5wn5DHjasYMedFQuA9SFeu9SWh4GrqCRL SgCmc9dGR3ryMDff/dmviwUwh7yR6PgVD2MuJbn66gkAfZT98NT7DQH8H78e A5M= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxVmAk4lHsXwFUkyZqQZhgzY2YoGussjDkzyJKLm1S45Gap216KkkQl2kiR pcVWcbmFNknlULZKSeXawm1DJMWtaPENM9/3zHeeeZ55fs+7zO+c9/zP+76j v2rTkuCpMjIy+lNkZCa+wWRcFPNQZjLswIwp5n+P+N36OSoEbzMxH06OyfMd FsJ1CzFXaa6v1BwQgj1LzGmziTOZr4WgwBWzysQB7UKYyhMzY3cTfXeTEExA zN19zd+L64SQZCdm7pNsGbs7QqA5itl8Iq4IYZ2LmCMnDs8TQrurmGu3EGq3 nBZCuJuY1dVEkSQErruYfYvlfItjhWAk4fPuY+fcI4RgJ9n/w6AoNgrhgOR8 nIRX7IRAIYw4i3mfccte4xUi5kn5mAvhuSS/yXToQtDnSPkQhNDMlvJRE8JH jpSPnMjXRspnTADBIOUzKIDbDmJmT/i8EkCUq5RPiwAy1kjXRwCqCRElmlMI WPl8n1NzngBuDvRX+8gSsDXqyEj0aQEk7/fkPVQgYITJLyzzJAFkeZVorVMj YPbratX3sQLoXCnnxZpHQM/sz9GXIgTgmuv+L5NOwISgrrjwTQIY1Dv2dbkl AT1Mog2cggRQ9bzG/y8HAp752eJN8hbAPw7xdwziCdgWoRTaYCaAlU3GKR2n CPgMerT20gWQrjD3h0kRAYVTUzkWBAEc7Hf+TKgiILmC0PJKVQBmOzD6wjMC bg/fMXxMTuRbFHn6wVsCWs8vOGw9BnApKcr5yFcCbmsryXo1CLBHtyauV4GI urGJZgdfAcxc5rm8W4eINvPtBAtaAELnbPJy8yCixWR9AJTX5sfvWUXEFxu+ dPbmAeR8XfPYYwcRHbt83B6cBjCtLDasSiLilji/mLYkgCt396Q+vURE75Dx cM04AKZMs3bsYyJOjQSzPZEAF8KuXGweJuK6OlKxxlYAdbr2srp5unhicdbH 5tUAO9Rk1X0cdXGXXMXnaj+A1Uk+R/vm6kn6B2Dp3geE3KV62HlmRdcsBoDq llOBqif00C2zy92XCHDK7/7vps/1MIZVt193NsAY5S/FfUokDAtRj1qmIMon jSx0NCPhwgV3rKfJiPI/7LT0zQoSequl7nIe5MPAd6LQL4aELV+2zQh7wYfr 73MUiwpJ2KWoqXukgQ9KJY0HKX36GDIZfOiJTvukwSTjdp93o7IefHiWJu/w OJyMkWW5RwK5fHjylRizBMkYse+47l4DPnRmtV84q0DBTTeuFwWo8eH7Mbh+ xZOCvitUYfyHLSyody1KOktB28DMx379trDeWeY4+x0FtVsD/SNbbeGOmq9/ vhUV35X5DfjU2QLvu2ZToZCOQ45pJop0W9jQkExfs5aO2VXKD1KItpBHcL8T fpSODlaKg4nqttDf53CyrZCOT3OOpo7K2QLbcmfRsWo6us44Wdv0hQcJP3sV MtroeDWEGjWvlwdDDinnP7+j48w77PKnzTzwUYzae+GzaH/lp1Hf7vLgkVtu 1p8/6Lh7+XDd8SIebFOTE81BhqQ+PKCsTkzY95OOnS9ZdS/deWC82oSrPEZH SntrdRuHB8fVXk7N+kRHc3fXlW5UHniEFPSye+moyE9M5qnw4I/guP4Wkc+l gpzg/DEb6FDeqRh9n466xw80Jby1gfxVe5xMSum4/F9u+1CTDTQGZOS8yqKj 77OKPY8qbGDovAFptSwdmxvf8VuW2ECkm1cqpZ+G5+ZDtCnYQK3r5o8tz2j4 58xqqoqxDTRkhZnEVdLw5Yadxlvm2sAxlzVuJiU0/NXLL2O5nA2ouTj8+iiX hp9x87qqIWtwy1RirU6n4aPiK1kl7dbg5FI5/jWJhh1UGtegxhrGXQIK9x2l oT6xjkUstoYN595x5I/QJPWxhjsSHj03MdCsQSVXzJPji20NfplippAnwhry 0sV8PUBR9LGGT0lidskccc4c4QI3XsydLyaCC9GRYt46MV5ruXBvo5inTw5U LvhwpH24EG8o7cOF4/OkfbiwU0XM1EkfLrDlpH240PS9T8qHA06f+6R8OJD+ sU/KhwM1g31SPhy4+r5PyocDLwbEPDbpw4Et78ScOOnDga1vxTypQ+ZAW3ef lA8HLrVK+7BhoFHahw0pNdI+bMi/Ke3DhrEj0j5smL+nT6o+bPDdKu3DhoMh fVLXiw2XfaV92ND2q5gXT/qwQMZZ2ocFZIG0DwuEXGkfFgBD2ocFm/3Gj/VP 5L+3t67MnQUN8sKTaYk0NF1xus6KwwJPeomzcjINk3pjgl+QWTD1lmuhawYN BebpmRdnsaC1WqPcM4eG9uyXYXmfraDDXmEn5S8apn35rf9+txUocIzelJfS 0GaLwg+tB1YQkBM+Tqimofn5nsKEa1bgqhFS2zL+Xx8r8OcUGnep0XGTXvRI r7sVRDvJeGYb0DGwYSxsmGMFlwXBLD1r0Tza3Pw+lmoFg9S2thVL6Kg8Y7Z3 looV8D7589zW0fFecvEN4TdLSP9z2H88lo5BmkWzNvRYwrTFafz1OaJ5d0TZ S++ZJUQ2u3YlIx1Xf32U5F1pCbqabZYXUhi4hvy8s3ixJfRNebAs/TIDwy9Z Rx7iWgJlaDSJ+pCBTzJKHMoZllDXHdLj+JKBO3usrO00LaH1qdryaf8ycG3y g9/I0yxhRf1Y9zJZQyzI3lSw4oMFCCv1Y4WqhmihQqG+bbOA9PIDdjXahjjz xZv6+9UW8NsNQ8JLoiEuULxxanqxBWy7MVPlpJ6hpD4W8EzC4n62AKMyMYvX lwVsl7C4fyzgsoRLJ/vHAt5I2Hmyf8xB6aaYxf1jDkYSFvePOVhLWNw/ohvo TWkfc+DflPYxB9ub0j7mwL0p7WMOLAmL+9kcmBIWry+z//2+2McMyP/nYwba /+djBsNl0j5mQA+KP4yi+tmMbWlW8DCDzlVTpoCovhnsqp9hXDOYc337Jg0V Q4zSX9510cAMGvzeNPOmGmLPVeaOS2pmMN3Hg3XrIwObP7nV7/hpClhw/Vji Cwa6tpc0zRowhe/u2q9KqxnouNE7eW2bKZQ6bzexLGBgfaGD8vF6U1i0586v RmV0lP3gW/PByxRCddfdDkyio2m7R0+O0BQC6gcNE0X3V9UnF7+8NzEFlWjn 1L/s6ZjTuPVLo44pRAl3yd3So+Pr1sy3i6ebwl+q+7fd/kbDlgGLav+PTDj9 LvB1cQsNoxTMTih0MMG1Ucfr5HUaNi9M9XCtYcLtyvyaDSk07FoZ9INWzISn b1aVPzT+7/pigkXG6+vKyjS8tuET5bw7E7gldXfdBw0wcvo9i9dsJnQbqbxM fGSAZcz2NAqZCQz5G2qPLxngugGWR6AiE9QW3V2ilGiARqFXry3qWwhne5jn XTaJtjP3b6ktXwgP+2UU4twNMF2166lTwkI4vcQ8qmqhAV6bXd1xP2AhRPuR ZwXVUbHh4USYwLmw0BTvfCruDqwkRGaaQHZdHTyKoyIYj91K3GoC4Z5k5aoQ KmoYhV+UX2QCVK3oHxYOVPzizR58NdcE8ma/VKZTqDh0i7eHOmgMcs5OwjQZ 0fYlcQH1VcbALr2cGv+CgqqEOcebUo3BwV9f5WsZBW20e2bDBmOYvrLz5smF FInPAug7fJUlO4OCwVNdDkVkLoALizh+M7vJ+E8+IfTg1gVgk7h+/p+lZOSh fdyowwLID3bL6U4QPZ85VdXcn7sABus7K4uDyZghSDH98X4+KN0iHpprQ8bT hbdrj1XNB1kbxW866mSMOmB9MDZ1Pjx1ztO41qOP9k3KYe3rRQ8Vh/9ZkWqv L/Exgu1WrfyuOfpIdel/cijTCOp/yz5x5S0JO2qzk+5vNYLIn5ylGqUk/Oww pHhkkREcnpcbMyWOhOvvNcNjHSP4eqVj3q5lJLSz82ImfzCEe7VvyTEGJIys WtfWds8QWi/uNab36qG6UIefm2EIPVUtg0H79VCxKsD//WZDCOleVm81RMRJ nYcM2B42fGrZHiIG0J4G5GQyIIBU0LhdiYiNbEEDI5QBjM6I1ckZBNSR1VIP cGRAbVFwwGWa6H0ifulCJwIDhClryx+XiN73qkep/3ykQ3rCwR0D1vNQtXz6 sFEdHR6cqkqdUa2DlX/sSjfIpEPLrTlzqb/o4OIny7WfhNEBRzKehQq0JfWh weuuBqM1V7XQ5Pd0+cJMGmy84xIQQdNCOarPmsWhNPA/pra9IFUTPeaofLjo SIPLXuQ/vsprorLljVNNBBqsV95tExQ+BwX7vDaWfTKAIzf1P7x/o4G9429D VtUbgKqPakyKpwZOK1wf25BlAN8GnD754Gw8sf9t/dgOA8Cyf7Q1jNUkPlRI Kf87aGi3Klq5dmoXZ1LBJanhsfZpFaQ1bri4MpQKHZVE+0auMp5asetQuyMV umZk0eRbZmHym+nFFCIVloYsDb8dqojq4aq67GEK2LZxrYaVZqKGUtoz7fsU yAjyDMy/MAPP5J15Wp1NgbVyZ3928OSxYJH+PH4EBd7+kuZ16G8ZyfUig0qL 5caz7j8rGJ12MTcyyfC6dp3DgfdjFYNasu4xoWRYtK6J+TD+SwUxQsmK7kQG y6o/mJv1RyquygZYFRDJcPmhqf3W0qGKq6Xf3GeO6EPkHK+WcynvKognuvc6 PtCHkq95Hvqlryo+nFR+/HuuPigcuPHyyoXWCqO7sRbekfrwEAnTaI6v+OL6 kCB5b4fOaG4/3/tWWY19FgkiRxP3Zst+4hcfaw+6vJ0Eo/HD3THWn/lPnM3y 5vxCgqoPaflnwsb4t3puH91II0GLcXTryLWf/M1ro7RvTyHBmexnZXcjp8CL 3J6EqXf0YETrUHlB1jRYb2NjGRapB0M7u7cU1chB0tkxynNbPUiu/bvjyaA8 ON8n++rJ6cHi/bNKtuXNgov5RjN+PawLKr8tOLRvnyrk7FoTF6mjC/Gm/vvu HVAHhl1HS/ZlIhytmme/208DOOOx39GTCGSV4IcX5TWhoyj4U+sPAthrcQnL YrVA2WvXzYFiAoy0ZZiHNWtD42DN0tH1BDD3iVNX/jYXSLudKsdNCSCTMn6D OKwD4v9/CPAfHvZTog== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-3.000000000019554, 38.}, {-7.999999999973568, 37.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNlHFME1ccx6+90hKcGZWu0Vm34JbVTFEDUzsbe997lDAWDLbIaGgwTDIW yejWERNFJDJaRWB1hhmhM2U4tJptpQxxysC9mm2gbqgQsNnQTehGJohzYDK1 m+tx/HG/5N7lk7yXfH+f/N5L3v6u9S05wzBZsU/4M18ISzxl5iodqV+K/KCh sOe/hwSugMj1H1f77TME/7SLfFH7Tkg7RVDXIXJT0rKEtRECU6fITwsHfiFQ d4m8Yu+gfu8ggeJrkX/7cyQa7CdYfF7kjddbmfQLBNnfiJwmVCfBUI/IlcJx P0Fknvucuj7nMYKK+f2L1LE6THD0nMj2YJw96CbYdEbkEzmP2nIqCErn+7k3 HSsHgc4v8quecYOnmMDmE7kmJfxBio2gZI8kTxrBrfdEnmtHH+v3bUkeXczX NkkeNUHgDUmeOIJvcyR5HvE4myXJM82j0SyyQcgzziMfkjxhHvvWS/3wWP6K 1A+P66ki98/54dGQKvXDw5om9cPjxXVSPzxYg9QPj7tGqR8eEWkeGw9vntQP j0Tz463GxyqaeGO193c9jzflU7l3p1RU6zIYL+h4eD4ajD4zrKLpG7doe9U8 jkwHcro6VbTp4c6VY0oeu3TV2VdqVVRz8XRFShRY92zWTP5WFT3fOMm23AcG JpRmu1ZF3Q5j3/oJgLi7TcMDSrrL2vzd7ChwKxjqYTPjqM61v8kVADJ3WE1P /lLQJ42HnM+3AQVXWq9dblHQe7eNXx1rBjQ32stLchV0sqy+IOoBdjZU6gcX KOjfG6pKTS6galI1tfASS5XQjG3fDaydtYSW1LP0pf2bQzscQO3JAv8DC0st CS/H5xYDdfLlvtZlLD344+mzz9mA45a2oxkH5HShYSx5NBUod/hepwVyOh4f 7vhQDySNZIcHVsupw16+dJMOqK5th5OV08/XnNl2JxHodf9Q4w/L6Cdu754j cUD/T4dbnQEZrerOjlTOcvi0SO296pLRlWXtrss3OWSaMspCdhk1vVAYTurj 0FuSsjQzTUa7R/N+tQU5MD9f+qxogYx6m4XiUNeF/psRhtbHrvvuGg7XtOey PJSh3Cqr0ufgMPLvmhXv+xjaIYyvnUNT6anig1UMvS3c39c4LC5Mjg4VMfRq +PvJlg0c8oa99y0ZjDiPeg5bhjRmdhVD7wjbl3BIyD80M6FhqPYP8wH5Uxz2 FSUIAzT//nD4H5JsvLs= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNlGtMU2cYgFukBZHRSgsdUFDASxnCGBS56el7PhAUBBS5iFokgBDHbRCV wEBhRBdRLlKZmzAqUnCJElExm4rykkWZt3FxICTcBsSJYxMXYOIcW3sOCX3z nnPy/PnOc54fxz4hM+KAAYfDidBeuifniu5mjBxm/GFdWe9pk0Rj9LnuHtM5 T6DZrrbHrs8Yq536zGv/IqBW7uneFLsc1yW/ck97ReB1sMnJpKnlOJCS+b3P rwQaXjTNV5WbYIvrgQv85wTuuW1x7CYr8Nbtx3/0PCbg69TFs+Sb4osV9era NgLWXWF1SQOmuMnh95sHrxOIW9s+29r6Ad7+t95NriEQkBt9P3yjGR51zHKf ryZAjliKqurM8Knq5cH9KgLRUu7I6QUzvBhm8jy5hEB+qqWTV6gAOZF9uYIi Aj8kRr9RlQrwRf32iNgcAia8dq/6NgFGUunxAekEssOj3yeNC3Cbo7emK0H7 PcRSMfBWgB0RTbYLMQQ4+3VdhOjBDIHIpsPxqmVC9G2KGOPKCHhe6i0KNRPi 3cGOvR/bEqjfvjrJdbUQ77RXqu+YE6j5Nspoo48QP9l3o6nRmIDD+cOpSbFC XHPF6cT0Ag1yUlhxq1CIlddmZd/M0vBL1eEjnleFmJcm+erCFA0LZ6Ns+yeE ODRY9pQ/QUNwxWhe3LA5BjJ9aOD4XR5bbyNCR6YPDc6+p04+2iHCL5k+NDwq LcwMPCbCTKYPDf2ep85WN4pwcJeuDw373C+/ffhAhJ1MHxoiikeru0dEGMT0 oeGOzPno9TciDGD60HDO4ZQ67b0IHzB9aLCO1/URL/ahwT6W5YKe9dqlYf0u ljuypNqlYUMYyyuZocElmOW9zTztajmI5Ybwd5rwdwAbtrD8+k/dAMgCWPYp G/cuGwdwWORil/4vXPoBkreyLNfp3AC4v1PP5xLA3Kd6PjUA8yqWzXU6ZwB+ eqLncxwgzYLLcKPOJw9gOJ3laZ1OBoB9H3fJJxHAM8xgyWc3QKOVoV4fAHGd oV4f7fskPL0+APcKeEs+K7W+PTy9PgCHJHyGg9Uz29QzCpCHsDwypBsFeGew nK07rkMBRYUs85kDFNCSzXIyMwr4rvPp8HFDMab8ODkas0MBH804fi4xF6O/ sk521U8BfqPGvS0yMb7zKN2cJlNAvyp/SrlVjCVBTavKLRWwTHCs3TxLjHPn uJ0SvgJadwojn10U4+a1JSH8vykw2OemUQ+JUfk6sGrPJAXPXUau5dhb4O45 ryviIQp8OqQFezMs0NVXWSHvoaDB8LfehKOWOPzWv8GjmYJgbs41u1wJOv/X 7TRYQcGau08E5XEf4spQIzvXQxTIvV9O33C1wtNj40VOeyjIz34YWTpphZq2 lKifCQX/pH7mZ1NujVETlV9LXSloXjOkUa6yQfWOAyFiKQW1NYIzkedtsNhw JP2mKQX4zEjbR7r4P6Tgf/eB/JA= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNlH00VGkcx2e8DMsWpkk24+ySJcQOqq107/zurS22VjXVIqGMxmZRySpb uwmlnFYhqZSyXkLKxLa7JnqeYhg50pFjcJRosxoveZ0T62XnpT/6nu+993zO fZ57Pvc8z73WwQcE+3QYDIa/6lBfGSXqkyFmaLIOMqVOhyeuGeCvy9x8miZp aPlK6NztYIDTHFrZ2aM0/K0ocKkuYGFTkcItXEEDKJUxWQtYuDz0wF+ru2k4 KNjOCjuoj2Nd9t1kyWnYMPeg06VKD4dIGgabG2jA07ypt5O6OMo490Y2oqHn 27LALDtdnGfdf39/GQ1Fb/lG69bp4KnpXN7yPBqWpRWvEdczca/NIbfJLBoa zisGwgKZ2C+9b39QOg3xPXNfHGYysbe3kVyUTIMgWdEqK2Ng6fbWWJOTNKxN Kp4fHsXAOHezwO+IyredL9sNDEySEXvWR9AQGFesm8VlYFiyKu9ZMA0ZxxXY zkA1X3DHataHBvezc+ogd01oKEnU8i/N9qrSUJik5bpDXFVpsE3TMttMHRoW 52nZX6yvKg1pVVrO3zKVt2WKgrMvtfxuSB0KTuhqFgKvSnmtKgWxllpOcG6L d26joDFWyxqdcgrGLmr5uNrnFgWut7UsU/tcUz2/Ussan1QK3su0rPE5RcHJ Z1rW+PxMgc1zLWt8Iino/HB/tdpHSEFp/Uc+vhT0XvvIx50Cp6aovZmjqvc9 t8T+P3sKIurrTgU8mUPgZ3yAY0VB6lJGhCBpDnVfURidYFOQMWC5KMZhDvG9 H02tMaTg+ELLRJl4FvnFnCc9ZwHo3JlyL6tZxGPvbC0YB+jPqC6YjJxBNdbs x9/3A8QMhu9uy59GnPxapm8PQG1b2KvuO0o0Jm4KkN0GqHS4wQrKnkBmNcbO yhyAzp0liY6Z46hKWfvZRCaAXUDarvWXx9CEJ9NW+hvAJf62MyU5o6hCItkk SgDgzfTNE5aPIKPNYxfajgKMZ/j1hzYOo77p4jHLSAC0YAMV0/UOCRq7D/OE AIp7yf4Vy4eQV1WmmbkvwFXX9JE49tsP+wcg0Gz3dd+4f1Gh9DXx3B4gdJtF QMLgGxRNfvokmgtQOlLHY+76B12+XiJfZAawcjTMolnag0xf14gq9QHmBEyO kteNsFXxUM04HzhLzTd2rOxC82kJm/OSDyVhpimRRp3I0F2yWlTHB2nEyHRh ZxsqHS4SPhDzoSUndEcotx4VHlvBJvz4kJ3idspDXo2yyvAT8hs+OG6hbdP3 PkQzh5q2DfL4EN0uUtoI/kRNFXtveXL5YHc0n/kdoxQZJR9p2GrAh4VDxkke 8lxU1mP6UH+UhJ8cdKZsBJeQrNr5RGgnCavEC1I85Alok/PT+TG1JHhTR4o8 5EK09vPRcFcxCVevqPL5cJVIExIeXbVYw2VFI3P9YblkKwleuYEuXNZFpBsi 0fMgSLC4K7vXdboALUuQDvQ6kbDrYpITl/UHOhdsduEhl4SqPSd1z3kh5KiT PfTIRDX+5Q/irtO1iBH8o+GIHgkB2yut/YueInZ87ItN0wSYn3nhyGW1oKBg WUTzBAF0slvBA5921KvjW5E4QgBIbXWF5u/Rm5AW0YiMgMqBT0xMnPTwq1S9 qMZcAq6/W2Z1IdkYt5zt67CIJ+D3+zM7OzhmGG2Oy3kuJKC1VBJA6nFwQUeD dMaTgAhR45fR6eb4tHvDxkxXAkLbV9w99tgCB/n8an/TioDHhuPKHamLsfuG NyEW8wiIGzdQfV7cD/9nAv4HssKisw== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNl3k4lGsfgO1ZS9pRNKflS9EwM2bGDM9vplOnhaYQonyo+NpLKkWFrGWp o9Oh4yBbyiFblsg7KIMQypqxhEiyjCFGjo+Zrsv8rmfmve4/5pn7ud+ZP971 TufNT0hJSEjUzr3mrxL/zL/JsyWEswOcz/BCFR3l2D1lNB3fKSYo18QUWR+R Ye/0FNhfHGUCr1Y+rG9Ukr1Bmx7N6WOCzoCthNuOfzHvTIl+/zYmDLtpbIhu +o7ZEXbTn79jApFpEWQWO4Jlx6n9BcVM6I+XcZChdWF3JOYuGUxw6E39OuYY iLimePfoGCZohl7yVPijG6UF3J44FcyE5WmbVY3wn5HW/hy+btDc/npH3QY9 +9HFwMSaaV8mpKguf6rtMYCiDQ/6frjFhL0WpmmNOoPoiU3+irxrTKiYkPVd HPwNhQ5xfZJcmbB1GnTKo4eQ+WTR25hTTDjnMBMrfWwYjV0+MhLvyITwTbR+ dvMwcnXJGcm0ZoIzb2p2dnYYEYTDhOQ3Ir5Rv3luMcHrnog5FzXnFhNGzUWs tnR+5nopi9guXXZuMSG4aFLIiSxBAkvAgEIXEQ8PzQ8DvOVFTAntnlsMaIv9 LuTbus0+us0MIGydWPDJYoCgbFzInvM+TxjQ7iPi8nmfKAa02I8v+NxnwDfb 8QUfPwaoXx1f8LnOAMes8QWfcwxgLxF9H3Xe5xgDjIInFnxs5nxSJ8X6MODi fvE+DBhqFu/DgBRTgZCFeZYyIPGpQKzPnP+wQKwPgJXWtFgfAGXK9IJPN4CE 0bRYH4DqNtHnicI+AA2ZggWfJwD7LgsWfKIA9DYIxPoAeGJi98sPgPqbiJOE fQAcC0TnHRH2ARjXmBTrAzD5P7H7ZQPwqJov1gfAXIEv1geAdHRMrA8AquCJ /X4AXM14Yn3mzvdlVMh7Y/h7YvgIDkSLuIM7PwimT4nYdX47DoI6lojlhBsg IDqK2Fk4CJKPiHgqYf6ACD7TRRwyn5eCYEBSxDjhIMhJGRFyjoPS3EKw22hE zMcEElOHhdwu9DGBClkRC4/HMYFs5pCQZYU+JhB58KuYjwnQJNcou/KGUQTN 5HkuywQEffH48ophpGIy5qhHNYE62eCzUv7DqOSs381KnAkU2daVaG8eRtmV fJlgZRMo+3wJ/0vqEPpsyRh3nTCGgaeXchRWDyEb5dOsW53GsCGh1vKDyzek OHpxWUalMbg33FG6HTWIpqWsGPIvjMFeW8Xf9Hs/iuJkPStxNAb5M5elSYv6 0fqHUX6CfcZAJkuTjm7sQ/pVHcorDI3hs3eO+puDn1HFyRugpm0MK03Dss8E 96KBc5e1eQrGwPkjRMqyoQeFf+T8kz1GB4F9hozHth5U/tyt9zCXDmlPBC+7 7ncjv68elV1ldOg5f3JjoGw3ehvKtTNNp4O7IDtc1b0L7Z+1KM88QYdNq/Lr v0h3oXM6VYtXseigZiNLKw/vRIXU/t4rFDrQX0VWpWzuRETdZLP69XRghAwu 3nKrAzXLKO/aokSHgH5Sk0xuO0pmL3vnwafB7uAlvIEJLopzwPoruDS47X7t vx9NuKiiZ3H4Mg4NKKmXtBpD25CmmVSNTToNvG7yzlq7taJw+tZjus40wL0L i75a34JG6ncNXWXRYAmtZqMKsQWxcVJLiyk0+LUkVXp1ZDOa2Xr0rTyOBuzj epQIyWaUMmS9lqVEAz/cgdKQs02o/BRP7gHfCO5PqyVOtjWiQ7HbApu4RtAz fIXbzGpE5mFyj9dwjMBn1uOMXlkDKiJ7HbRNN4LgMzu7D674gLptLX+YOhvB 0rbqoe777xHeIqf3HssIDlgb65qpvkcjXpf0PlCMYG97eHTIvXq0vudu40qc EcxcqGMmqtWjUs9Zro2SEZxaMrHmwcM61Ly35tdHfCr8ni+5wVazDtnvn1T8 yKWC23m+w/f4WnQo4AZeg0MFVf2a2tO6tQgbP/rCNp0Kx3YrfqG5VCNzRuXE bmcqtJoxb1zxqULoJcoLYVEhObhz0+u4t6gpKwGro1ChSqa3d0N5JVLXm1Je gaPCjhzWywheBZLbYhxrrTS3/2PtBC1cBYpKuHAtkk8B4hvr+HyrctQWGx7R yqXAM9x4rvM9DipbmzSjzqGAe/5k16Z3ZchOIznZNp0CbkVjpYsvvEafcp8n ImcKNBH5o3EFpchjOs/On0WBTtuOE2uWlqKKoGrNKgoFwvAvtFwvlKAqp2/9 qjgKfHpxWSu1pRh5+69mWypRoHVA+0SlaTH6yt8f9yefDNfe5YxUVLCRfNq9 sBYuGQqPkUtSDrBRawY3QJ1Dhr2snVkdJRhykDC8a5tOhkcKv2632vXq5/+d DCz1vZVn/ArRsz1a0wksMgyv2/7I/HUBYl25er+bQga3VWPRi6QL0KHBc1tw ODL0SD9svst4iQpSZEsdlMhA61n1W8etfOSdTbOP4RuCR577gGRRHnoqt3Sa yzWEBK+8krHpXISP84vU5BjCC3rTu2xqLloTEEm1SzcEQvz+q2HF2T99DCF+ u2tQ8Y8sZNtVuiSRZQjD1+IkThKykFqDQk83xRBW+3S0+Z3IRCEMSjcOZwjq u7esWx2egco3sVSclAxh6u2t11qF6ajMd7/TYz4JnDXKYqjFz5G/neGnTi4J 7qknea2TTEPyKXIh2hwSuP4Rs3WI/A8yu4Q5OaSTgHDJ6743I+mnDwmSP3ao 7VuVgHROBdk/ZZFA7mWhuf+ux8hyUktrnEKCB5p6cc7Rf6EuVZ3kPTgS9KZz NRKcwlFt1pOpJCUSLHJS3Xgn6zba0BWxTGWcCJ2Opkbv/FlYa8TMuEc7EdJW Hlf72+QOxmttiB3jEKGG81Djdtgj7PyT9cvdMohQtS0mv8kqCxP5EGGXnWpb EjMXO60x9i2RRYRG+ffHlagFmPmrsiN9FCLcIPVZyBphmKZpV6YOjghRF5Is K+OKMQ6HOXJeiQiycj6ZbamlmDn+6/JcPgGmbP1LqUVvsBK/Vm2JdgK4n88K 6HrPwZaXqy7fxyGA9w6F2fdDFdhv30OG/kwngHM0yFDdan/6EOBD4PZiXGAd 9ubZWbMkFgFcXJwCHWLqsQJBems/hQDrjVoO8/LfY7ut8Iv1cASYlXhAam76 gJ189bXvshIBpAt/11CbasBw+G4XNt8A9E43KMWubcIupK0MVWk3AM/FR+R8 djZjVhR/26McA+AlblLKu9CC1VfrVz9PNwBCU+nLzZbcnz4GoCMVlRER1I6V 9o8WJrMMYO/DpH3SnA7sBa84gkcxgPKKi68J/p0YzbdxagfOAH54Ps3+tK0L s/h7e2eUkgG8Pn79SmhTF/avcfW+Gb4+rPPuUSD7f8JMnJ/TT7Trg2J937k2 Sje2dGVj5geOPtyx9k28OdyNuZsx0vZl6AOhRefIVcfPP330Yfqe16CfcR+m krc2yOeAPmBTNTcWWfZjrdsvVhym68OtZStVfyR8wd5WO2we3KIP1PZD8cfw X7Ge+4Nx1DX6MHI4lGwyMYhpey6nMxX1Id4fq7o7MYT5BjfzZGfwsCXTTT8p YgRTKaVwfEfxcHNKdga9H8UKtEj5RX14OBi5bM+yrWNYWFx1eVYHHhRtAvHZ tgKMiWNkcl/i4VpIQJDDdQl2a32pnVwkHqRGLSajPKXZ1tmH3uhex0Os1dPj S4hy7LyyiSELezxYFgXU5MbKs38oPGl234mHdf8ZJj0sUWRvuunsE7UdD/+G dzx6FqnMJv1CGizSxMO45OEZ/sbF7P9Mqa3sVMaDhKvd0csuS34+7+Dh/0h/ j1Y= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{6.999999999384613, 38.}, {6.999999999384954, 37.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-10.999999999891713`, 37.}, {-5.00000000000847, 36.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNk31MTXEYx6/bKiFE3dbU3HtyFGouNS93cb6/U2SGUkNbNS+J2SpT/ohe iCWEUFbX6tKGMHTVFuOyXy0vCa28dOdO62XLomWZ2BqHc+6v7Z7vnrOzz37n OfvsOecx7NqfkK7VaDSQL+Xe6/NPDk81So6KyPJnPHYm1SYdElERxLi0oqgu OUdE/DzGLbqMZl2GCMsixlWzg6YYd4s4EcF4hrNBhDaKcWhBV0hBggjfNYx7 hz7+sa4TYdvE2NRZq4leLWI8iXGEMyI6djJW2rtCRAh7Gb84ECiXiPX7GM/y USJiZOI82eoul4iwNMbX48avxY0TuCcz/j6ihCA3jvGKcwNyERSD8fFw+7Fw O4HvJJVPI4HXiOTkfMWnjsDtM+OXik81gfat5PK5IHOz5PIpJvBoklw+hwmm 35VcPlkEATcYr1R80ghCayWXTxLBoFlSzYcgsUpSzYcgp1JSzYcgdoKd4/Eh aK9U+bjLfmaVzzgwfFnlMwKcrFH5DAD2qyofO3DjHuNI53yA1otvwrr+8rTw VYaJuwlkLjM1rvvN09ebjTZrDWAxx5SnDfM0sK3gYU85kGgbfs195mmmccvi O6eBCsvSHSfaeNpc0qQPOAakQLfx3H2e+nfUnuEPA3drK8tNl3ia5eGf05kN FLc0RZQe5GlbuO59YAawp952u/5xML22/dBo9UIgIT08viYvmN46GlXlZQAe tGrzgqKCKRdr/y34A+VvohYZ/3J0auOGmfAGBo84dnx4ytH0VnOflxvQ4OiZ 413E0Z2/CrtNowLGetemdEdz1HEvL3XMIcBaNpuL9OTo8oYFW6KfC+j/EpMZ 3G6guZpTT+dZBZwd+rTqepmBXjYrkc8vNm3z22qgpcp6HRfg1/+wsGOugQph CR6WLAGh3X0N74b19L7yeZLl8+wlPw1P9LTPuS9yf0Od+Oi8nnbYn327slx+ vznGUr1Xz/7HEAG6+ZM924ieflUeDxCQn/QjX5irp7rBmBLtNAHU6CYvup7t u0bAf3QqEEM= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNlntQFFcehScgTwVBDYESsigw040yyLPnPWcmrpooEBCNSgBFXgFENKCO rIAQHjEICxsTZVmlUKNrCIKg7PqIFw0S2QQJEQIaeZkAAwNqAkGJwA60f/Sp 7ur6qm7d/vqe+lX1sojdQVEGPB4vT3/PPnusZ/RxIbzZZKjhM+x/cbUdnwQ5 /bi2WaNGrfGV5vO+fDIz8l7bib1qhER6h63cwicm2wvOR8SpQc1rCr13iE9i NfvqqR1qvNm/7/uic3ziLLFy1G1WQ2Eu/erDNj6RlYd8U7Fejewkm6lkEwGp rN5SGadUY8zW7MYxuYAcjDXpcvFUI99w8UjbfgEpuxOzsctJDfsnyWblnwnI jQ+Obru8VM8mZ5KnqwXkU/HJAysWq5G7vkw4fFdA+L4lX8FcjfDrHzCxXQKS FH74xRhPjS+28gpTnghIyuWN76+bUGGbU6TP4ikB8RZZt0tGVEi1O+aqMqFI xcB/o7/rU8Fc9o/EGQuK9Nz2s5z6SYVTwUH7e5dQxLL/cs+qGhVERuNHk20o gr/tPtdyToXa+LBMni1F6gNSw5NKVbDMKwjOtqNI4fZOU6siFdZsy55nuFS/ f+XHpy9mqxDWpy7W2FPERpLvHnBQhc2OjVODDhS5Z9BbMZqognDJorWBf6FI m2ne0oKdKvxywynxkiNFXDccTnXbokLm/n9NWLpQpPmS3MPLS4Wd8tdio/gU mSj+Z2qrQIVj/vd+uCagiIv1SMMeexVsvzTxWURTZLObp5W1tQq6oAtFsa4U +WQgbluVkQpWa+oGvl5BkdvKz88ETALZHwmZ190owvOtGx0dBTZYWmXEC/Xf 29QkKngMRD4OuVXvTpHslz9kunUAyTsMp+y8KeLtpU8NsOM3/wd3fSliES7J HT0HmNuFvOYmo4jZmegnvaXArjbB3rdWU4Rv8J94i2IgT3B5pUUARSI0wpdJ uUDYQkOPI+/rz9OsqWzBIUCXb51+NUH//pojW3v2AkxZj83JdIp0pyTxdbGA 5O2k597HKFIWmGqyKhyQHXiavH4ZTaI/yfj3qhXAbg+qIFtCEz9hUUDaMkCU lqbtCaTJInuf4BNvAMVhv+eExtCkLjih7rAFkNaaE/3nQZqIOnw1jCHwslOU dzWfJp5+tFfKMyUWpJjpSkppUp0+38PmZyUunn5eVHqBJrq1S3SBd5T4Ncr4 4M0rNPn17FuRVJUS3i6aQ4/aaSK75uT+bqQSZyXdx9O7abI1v7R32k+Jw44L qh0GaFL7TcDOMkaJu+0zDXUjNHknUl7rvUwJTejVn/x+p4ltfNT9a+ZKfFYr 7e+eoMnyzsbbPmMKOPyc9WzXnzSJqYzMLH+kwML7xS8mpmgyMCS1MmhUIKE0 dvrQDE1OF/jtCq7SM2OkH3RXEj0XBZaKWH6ub/9MgAKer7jgsb5ukQIVr9Y7 LZ+NAkd8Wb6yfb7+UqDZm+X1p8bePjUmxwFPlrsezUaOHHeW99o37rFvlGNy BcvGIVVGIVVyfO/A9ZHjVmJhQdY0TXr7mG/7AuQoiBNKLCdpsuphZ8MDsRwe 1n0GZb/R5N2ADeH+znKcj7gwKBqkiUJZ+Kl8oRzjYbnDHQ9oMnOhPOr8pAxv GGvmZzTRpLg4p7WgXwarLenrhHU0GR+XPHzaKkNXcEn54zKauLbdTG++KUNa kYtjzDyatNwbUnYEyRAh3vS507B+Hl2R4QEZ/vBNetZxnyLm5g3OC91kYI7s E+bWU2T3Lo3bHjsZXLxi/YXV+vnZFFrynpEMxOOvgc2nKXKLJMXfeiqFaY4F E3OCItVVNWXVD6WYdq+feV5EkRZnvsTljhTl7tu/zDpKkTcdvmUcqqTwyx4S m+RTr85HiuqPWH4x15cUf89kme1LiqE0ltm+pLiuYZntSwqzD1l+Z64vCVri WGb7ksBqB8tsXxJ8t4llti8JMly5PhJUO3B9JIhaxPWR4Lgpy85zPhJs4HF9 JMh8oeX4iOE7puX4iJHwVMvxEcN5VMvxEWPNiJbjI0atjuXJOR8xXh9muXDO R4yYQZbndJaL8cUvWo6PGO3dXB8RJjq5PiKY/sj1EcHsf1wfEaIruD4inCzX cs5HhH3HuT4i6I5qOX2JYJDF9RGhdj/L7HwxME7g+jD4I5zrwyBnI9eHQc0a lktOzIbBfAnL+aHXpzVZDByFLKtWBhmfTGSgW87yJaPZDRgk2bLco21/WbWO QaUlyy0dDcOnGAZnjVhOaxUcahUw2DQ1OMdDs8vtGHw9zrJN/+pcgwUMekZZ nvvf4DH4Pylrq6g= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-7.999999999973568, 37.}, {-5.00000000000847, 36.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJwl03FMlHUYB/BDBISx44Q4SI58f7uCY+i6AU6Dlt/3rUkG7vQOFU8c3uFl 2CEFoiBndKchSeAgDhCmgOgVTgW8qaVQDzFA1iwhPHSpGLEyQ+aJ1GhMO3y/ 22/PPtvv+eu7hxlztaYFEolkpefNTyp/7slSksznUwHtn4ue+WJb17MiAR8c Fl1eY/1qa76AB4dE/yA398jNAtQ20fUhkQHqHQKEEtFBLxYERFhEqw4MRx/Q CuguFH3/L9dcx7sCVAWiE4daJG+/JUD/sej4FxFgMSR2DHpx9MY57biXSsDN zIcU5cfR5TsDW1+PFHDJGRQXJuPofE9109VgAa9sO+PdqOAoIsN5zrFIgCzj yooLyzjyOhtT+vgZj/KO1dcywFFm54zq2AyPSn3i1YbNHCWYw2qbJ3m8rD8j NedxdPBO5XXfCR5/uL1z2rIZ0dPvTtlP8zhYJrxvK2OUny4tlB3nYbArlr95 ktGWxwlJK2p4lIRX97guMTJ3xU15l/O4vbhVqe1n1NHlV2Wx8si3anTnbzBS up3Kpn081u2sW//3TUb9W1Y6PszhYerdH+HvYlT/T1X4uJFHt33W6TfEqHGg d/+CdB6n955K725jZJvzf9URx2PV5FhKynFGERt/W5QVzWOZuq8lqIrRtSJ5 nkLBwyak6QM+Y3RkV1vmsMzzX1lRkFTEyBDdMHTIh8f64dzpkzmMUjseDMT/ Bwxq5n6BkdE6H7swNgW0NsaFhW5mlBXVxB/+Hbh3Mbh7aSqjyhC/vthbgO+T oeSPYhglzNflBBwXm0tvKRitqX/6ku5r4OF2zc/pgYwelWmi9pwARqbvMve/ HKl83tlZaweMu1M/aRnjaDpwePTbCqD2RsNEdi9Hac2z++6VArlLBtPea+Vo zfdXkhdagcmU0Z+EEo5+zA5NjrUAQaY+rc7T30ST/15dITBq+vJ+cSxHRw11 I5YCIGukTFq8KZKiW44+GTcAm0J2TMXULqELbv3iSQ08fX6zfaE8nNS6WXX9 auBRfKkpwBVKJ/p2bfhTDVSHXp9LcoWQZG173m0lsGd5RdQxeTCl3e2v2R0O VBX3j7M6GTXaOi87pIDrudt4tl1KI6tyf7X6ApKCta+ZOwPF+5IA/wPClJjT "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-5.00000000000847, 36.}, {-3.999999999994145, 35.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV1wlUU2caxvGAorZaFTsISnIvhEgwLBLITpYnUbGLHaxarIoti8BY1lQG xK3urbal1qqopbXDqLi0CmrVsrvU1OKK0ym04I6KqHQUVIKVSe7NqS/fyTnw Pxdufrzfl3Din5g1OdldIBD4uwkEzq+CrM6enh5fOL8VLLHg9QPbflUPESI7 r3txV74FB+4FN4r9hJhn7CqLnmuBmvm479EIIXze6tp0K82C+nHHpg+bIMTf K7ojm5IsWJNwoWH4LCF8rYLlkpkWxOUcWXo2R4iluf1X1b5pwWuL8qZqC4RY VDfUUDrBgikLB785bZcQntnCnQ/1FuRaF+UFnRQiarbMtkZuwZWnHp6vXRVi qrVYsjzQgk+UUcZh3UIkTYntb/W1YL6vqGfJyyKkvRidNXWoBSV790zZKBMh daM1LtTDAp/2m1GTIcKMxw1nu7vM+Lnp7OGDU0UYH7rwZM19MyrzkmxVqSIE amaOzb9uxh81297LyBfhmXfu+KAGM3Tn+3lnfyfCnp/cl13bb8blvbtkpytF UPfLqFhXYkbCnoBj1XUiJGaceoQiM8p/zGme8JsIsmfeintrzbj7Z9HC1Nsi rD3y9tzClWY8mlK0VfRIhPVFHx80zTej0fZ+9Ht9GCh3lz5uyTRj43Q/6xtD GeRctenXJJkR8sJ21iZkMNlyYXnI22as3rR4y+6xDOLitimGRJqhER89/G4M g59nrxh0SGpGccGd+oYZDE69eVkQJzTjeLO9zSuFwayA7z3dPM34asgDd28r g6WNHqbtHmaES857Ny1goMm58NErdmCh7wZZ8ioGyx56t9+5DyzpRNT+tQze mdZo/eQ6YNh/8dXjWxic3urlGdoAbJluzFtRziDpabnY7wBQqDrZLjnB4Elq d/rxEuCXkK8Xbz3DQJtdbkwpAqboTwZ0/JeB1OtJ4YDPgcHJxsviKwxqYg/O 270SeLGkX1lwK4O+yvYrr88Hxrmzmwc/YNC5b+f5u5lAbe6HhXV2Bp/brkz4 NAmY3xffJvZh0bigMDr0beCTsjXFexkWUxYw90dHAsWrf2gVSFkMaPeT1Ukd 3rRNM4xjWBQHfxycLgQyp0k7U9Qs/OSzHgzyBPzfSPlhvonF0p6Ni7/zAMom vlWSP4HF2lDrN192mOAf21GdFMOi5d7ys783m5A5Z6xAO41FH6R86GszoWiV Ja3rHRZtAT51M0pN2HI+4atzeSxSuGVCht/txhUfsHBPGJi9PcaEJ4fT9Ykf sii7KE1u0ZigLGw/kfoZi7nVFeMDxSYEVmfP3VDIYry/zfMfA004HfLHhLat LGRPXz21u8OIwOsZljk7Hf6Ycen3m41QXW1NHFLGImjkIXuEzYiuwNm7mn9g YZm1NWdeqeP6jTbpP39lsezKxT0tyUYUNhRkPr7MIjPVf5wpxoiVkh3Z+bdY ZC+s2rtBY8QTmzys+x6LlezOttv+RnQek5csfMhiz6Srds1AIxZ47fj9z8cs bg2Z07Syw4CPagrqFnezUM8yrT3XbAB7tC23508WmzWzhw+3GWAaWdX8QQ+L ocW/Zk4vNSDD4HgjEvi55mPAuhC+u7bF2LfFGLBRxHfBdY3jYcD8oXwHiJ3L AL0H34fiBzoeBjR1C7h+dWuH46FHXAffl5qdS4/y+3y/L7RZhTY9ntzhu9/M Uo+ZpXrcu8l3KufR42kL33bOo4eXq3mPHpobAuLRI+G6gHj0WH+N79c4TxTO X6WeKHhdpZ4ozL5CPVGIviQg84lCVbOAzCcKGc3UE4XYZuqJQl4z9UThQjP1 6JB0iXp0CLtMPTrIe3l0mHuDenQ43EI9OtTfpB4dfrzFt4Tz6FBwm3p0GNNK PVqUtFKPFo9aqUcLYa/90uJmK/VoIb1D90sL7za+P+M8Why5yzfHEWvRr516 HP2AejQ42Ek9GnjaqUcDpod6NFg1jJ5nDWJ96HnW4BvXeeY9GiSK6XnWoCiQ nmcNJsn4fp3zqLEg1I141PALdyMeNQwRbsSjxhkV9ajhrnEj81GjW0NfX2qU a93IfNTQ66hHjeWu5uejQoGOelR4V0c9KnRoqUeFL9TUo0Kjis5HhUhXf8p5 VNimpPNRQaqkHhWqFdSjRLqCepQIUVCPEn0U1KPExUjqUWKY6/oTzqPELQX1 KDFJReejRIyGepS4pqP7pcAgI/Uo8LOZehRgoqlHgfJY6lHg3zPpfinw+F26 XwocSaLzUeBaCt+HOY8C+XPcyPthJBakUU8kbqdTTySOZVBPJOwZ1PO8eU8k BmRSTyTEmdQTiVcy6Xwcz59J9ysCFZnUE4H+WdQTgfgs6olAeTb1RKCvlZ6f CLxkpZ4I1GdTTwTeyqaeCKzPoh451vXyyDExg3rk+DGNeuTYkUw9ctxIovOR IzeReuSIS6DnR47CeOqRQxJPPeHoH0894TDGU084foqnnnDYk6gnHBOTqScc ilTqCce+OXQ+4ahOp55wJLjmtd7Y+oWxdQw25/BdWeFcY5CSzzd3u4IxOLmY 74HcDRy9ju8zp50rDPs38d3BHcgw2L/iW+T8c6xh+LqY7/HjnCsMX+7gO+3o 8PSjw8PQuYvvDZwnFLu/pZ5QlO/l+wbnCUVgKd+DOE8oHpZRTwiy91NPCNwO UE8Ith+gnhDMOMh3OucJgeR7Op9gPPueeoJx9xD1BOPeYeoJxpIK6pFhdSX1 yJBRxTe33VYZgqv5juY8Mhyrph4ZFDV8f8F5RmNJDfWMxo4a6nnevGc0BK7m OKeDcM51/4ecJwjfVlNPELa4muOMC8LGarpfQfhXNZ2PFJXV1CNFSzX1SMHU 0PMjxchaOp9AxNXS+QRiRS31BGJdLd2v59f5+Tz/fd4z6q/7855RqOw1n1EY 38szCm9UUY8Ev/TaLwn2VdLzI0FDJfVIMKmKeiTw6TWfAMh77VcANtdSTwAm H6P7FYDoU3S/xEiso/slRuwZOh8xxOeoR4wT56lHDFM99fhj7UXq8Uf5f6jH HxW/UI8/JjbQ+fjBo5HOxw97GqnHD/rfqMfxf+s36nHM8Xe+gxbVSxfVs8hy 9bw853J8DnH1T87bCVlcdLU3dwMGdldv2excIrg18X2be4GIMMDVWu4NUYjB rl7zkXMJMczVDctCHQ8hvJqoxxfDm6jHF95N1PP8ug/nGYm/uZr/fDESQ12t zP2f/dZLI/96/melr4yYVz4Cg1x9wjmO9BF4wdVLS2Y+PC4e8ZffmOS974NL Pujn6k5u3j7o6+qdzh9P9oG7q2M3vSx6MdwHAlcLuOWD/wMhpA2U "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-3.999999999994145, 35.}, {-4.000000000017792, 34.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-4.000000000017792, 34.}, {-3.586632052708353, 33.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-3.586632052708353, 33.}, {-3.586632052711707, 32.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-3.586632052711707, 32.}, {-8.000000000371415, 31.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-3.586632052711707, 32.}, {-2.000000000302009, 31.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxN1H9M1HUcx/GLQhmnA7n7/pBsKWC0urB2tu+P+/54ORIhXZRzZmKN+euS WKROsYGMeRSZhE5GzUvFTZrgclytzjld39sqsSsd0QYxw1AsQylOIQUvXHff zz/v977ffffc98ce+3z3/S5YX7VyU4rD4ShL7MmjY0fJwsovZkUc9gAf/BLu 8HQ4I6dmH9tbMG6icLRiunRDeiRv8uODNcMmCqxNuX3X0iLrrevZN3pMFK04 kW09MTPi37A3Z+tZE80ti4bTF6VGFl9v6Jx73MTM1ge1Z+IpkeiS/q6hRhOh l91/RZsckfza+ufPbzGR+dHV4rrv4taKlno1Wmzi8b/zN3om/7WUxv5vRvNM TLcU8ttOT1i9rU3ekUdNxD/LfG374XFrfJ8zumyOiezc/Z5nT9yxDm9ZtSct 1cRqp3Wgo/+29WOBf93T9wx89cax93575rZVf7lwTeiGgece8zp/6oxZ56pu 7vikz8ClouoF1ctjVt2ttV8PfWvgw8uVFwazYtYPL7XyTV0Ggl5XYl1i1mZ7 DHjGsuyebC+9315qIP006+ZhObEZWLyPdW5Ocgx0vsU6XO5MbAYq1rBe3jZR 0jahY9crrK8MJkdHz2rW2+Z1b53XrWPnm6xnlIVSy0I6gv1ZxKPj9zjrKduj IzDfRTw6Gpa6iEfH1QoX8eg4coB1ie3REA67iEeDZ9BFPBoeesRNPBouBlj7 bY+GjJOs79seDa5LbuLRMDDmJh4N5Rkc8Wg46WH9ou3xIbyMIx4fGso54vHB Xc0Rjw/BMEfWJ9FRjqyPD94hjnh88N/jiCdxPpMnnsT9T/HEoyJYxBOPCu9G nnhUbA7wxKPi4hhPPCq6MgTiUbHQIxCPioKlrPNsj4oLawXiUXG3UiAeBeEa gXgUpDUKxKPgn2aBeBQEDwnEo6DziEDel4JV7az32x4Fn55ibXNyFNScoR4F U93UI2POAPXIOD9KPTK4h0XikeF4VSQeGfEqkayPjNr3ReKREQiK5H3JyPhc JB4Z88+K5PuSEO4WiUdC788i8UjYPkA9EoJXWAcPJUeC/xrrptfPPXg3IGH6 D9ZLPCtnHH1bwroR1l+mJh8gYc8o66GRvv9CxRLeGWPd8+v3t9okCU/eYV3X m7+7N19CxwTrm8nL50qI3WXN//lCY8osCY4p1uz/LOF/x7dSwQ== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxTTMoPSmViYGBQBWIQzVDqqZqzkecAAxg4OGhzHD9oyMZ3gEdsg3frZ3uH G+7psgrT+Q8slrw+69oTe4f/kqJzpDcJHDjAVfr282V7B/9n7J27twkeSH7Z 6Xz3gL3DPY6eq/k3hQ70bRWdO2m1vcOaxoWNFlIiB5zyJX4JT7F32BHg0Sta KXqgRmxSVGKVvQNTWcMPtm9iB2xXN+2rirN36ProeZhnosSBNt1XqgkO9g4O zh3Zi4IlDxxe27d9pqG9w8+J21L3iUgd8FCTff9I0d5h090rGxOuSB0QmT71 jLWgvUOO2mP/zknSB1QZfvgv+W/noJbz0N7CX+ZATaJLpcxbO4dH68435nLJ HpDaXeWx5Kadw7x3a0U1j8ge+Mcze6/1UTuHGO2a31k1cgc0wpfeeLTezmHW lwrHSx6KB1YeXpR/WtfOYdlBcXWXfMUDH9lPBL9WsnNYp/Ve12Ci4oEQ/p1Z S8XsHNbr/w+dtk7xwIWbpVt+ctg5rLrgPr/suOKB+PR/Bi9+2jrM4z3JefG2 4gHOHUEPCl7aOvQ9a5q69LXigVOniw5Nvm7rUBFd6vTlm+KBhYvirgccsXWI yVkgsPev4oFJNmLyK9bbOlhJsgDjSenArJkgYOtgKQLh98Tu+VfZbOvQxA/h 2+sEsc3Ls3UQ5YbwN7JGb2CNtnV4zwbhP3p57c8GD1sHYWYI/8KNo6/nm9s6 NP5nBvPrLqnXXlK3dTD/A+G/AimXBPJ/Qvhiz1zamXhsHRq+QfiQ9GPrAADH jPpx "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJwtk39QkwUcxnceKYxt77uckwZt73ayOARGnonsffe+35bEoY5by9AkOZoE o7rYjOJXTFiGeuh0KqH5M1i2vIqJXoJafp0F2Q3zygQ85l2AGB56wGAQgba4 nrvnnj8+fzx3z92jNJeY3lrA4/HSwv4veR9kxb97VoC8eQEs2rfgWGmvAPvO zY4MBjnI3VXmMSwU4sD+KOq1IQ5m8z1rp9KESDSqjxi7ORiKaXDY3hOiuePV Td0dHMi9OuPlr4TYJ3dtGT7PQZO66Vz3sBDtp+566j7noPQj39fXUkSYuY7R tuzhwHX2BF1TLsI0xRnx1g85mPlpVb6wU4TZcQmapjwOtL8XOi9FEnhZ+R3f kcWBxBt1pEVPoCS380bqSg52v6GoGS4l0PRzbtW3cg4O93z5UvFJArcVv0/+ E8kBLGseSPERWMmKnNIgCw5OnK8NEFicmTTBC7CQlzjeVj9KILujS3+xg4Xb gxmPVLMETk+MVei9LOx9bmF4FxIL58XCcf7j/vsRJKY8f1D+mZGF8av36k8u DnNJpqKNYWG34fsZdRKJ0aTDgoksFHyzQ2PPJlG2bM1Mqyzc/yed+EUliZ8a 997aJ2BhYLj/wVEvifaGLVM5PBZ2dVTYzKMk/jZ+3hwZ0oG1jPfDdLoYD1kO St0PdRAxamkOvSPHS1G/NMAzOnhWnTDnvSrHKpdT431aB075Ro+BUGATOada zdeBqXfS7d+gwOU7l1h7njBQmBMRTD6gwJjJbqkryMDNBscBW6cC3968Zqn5 HgPORuvHjRMKpC5stq37I8yT7/f/KqBQGx0bb7jGQMRYV1JGLIVtOZ+sKGph oKaAKqldTWHR/D4MxBn0Gdl6Cs3N0li+kQEi0NoeyqZQE9ggLtcysFGyzV+Z R2HXYmWWN56BifHt1XesFKZnVvlaxQwMlff5l9RRWF62tXr7YxpSTu+8mHSC wjp3b4V0hAZ/Ze3LinYKC24ELpTdoeFK6Lr14W0KJZMlac3XaYiUvZneOEXh oZj904fbaZAV2eUlq5R4dKoq1XeMBrFmE7/LqsQVdy3r/66lYcT2aNZ7Womv +3PWs8U0nNG8GJL1KFHky0h1mWgwWIwh/lMqNF15YXpMR8Ot2Li5mmQVJvyo ducvp4Fd6+ZXv6LC+psxKwMyGpzBv+RPrCq0D0Z7igQ04NIH6Yv2qP7/Fw3/ AqcPgdI= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxNl3s4FNgbx3WhMRfmYosoGfdymTEugzHzakMsZl1KKEmxKpeKZIlKki2U pCQZJd0kI6WS8lZqlOxKq0gjlyi0CaNcuvxmt/74fZ9znvN8nnPe9/me95zz x9EJifYOna6goNAm7/+OCltd9SMqyKjwnwCKogsj+fFk/KlvaKppVACuDieE O23IKPF/FqjYJ4BJqVMDe4iE1MBK7RPPBHDZK6/TW0TCkf40l7z7AojNO3yg x4WEUUpeTz9eFgDvsl1rz1si7hbT7l0vFABZtK/aJ4WIFm/rZ3ekC6AvKNWa o0bE38vi/gzbLIAHw4buKYXKGKCgOeC9Qp7v5JLQ3S7K+LU8RbJniQDCFuw/ hpME/PrJp3Q1SwCFUVNvba8T0K81K7dTUwCzM3J9hnYQUNGLk0aYJYDmeP+2 Ti8CEkMck54P86HZ0iVBxYyAG0g3Ejxe8uEnDLKOVyMg0yM/ecMDPhTMLaLM VyQg27A33UzMh/yNJHldCBj2n+Tx1D2O1OkEvF6n97BUyIci6bCiI4GAmSGZ D79y+UBo9vI4RCdgt6Dot9VMPsx8f3rOTB0CVq5cVdxI4kMee3DdEQ4BlW7U bXcdc4C6Aj0rVzcCPvd9Ntrc4QBp5l7pWqEENGIdImyod4Cu/k1B1FQCTriN V6tcdgDy7liLmOnKeHN076cv6xyAkI4vlQyV0aH3PSvd0wHiFHvmDroq450m Yqoy1wF8p9rfaW9URteq9g+7dBxAtL7Uu2SfMjblrtk2THSAoF+93BPPyesd XTBnhYwH+8ob207WKePbxRlPrkp5YLR3wZT6K2WMo7JLiBIeWD93FXd+UsZZ rfsOLRfz4O7ByaOajkR8kTpU5hvGg4MaoWdd/Yh4rWp44oiQBzGmG9cGRBJR b+JDSyuXB2GPyY89dhNRy/0fx7lMHoR/dO3SPUbEkvI+h0ASD5JKmcUvLxGx Wlf68LjMHk4PHqHF1xFx1bmm3napPbysOmPysY2IWQ53sjUl9mBA8ZYtHyKi R8+lxgCxPbQmfAhdZUnClMYUd/8we0hWsjJMdSXhXm2fonyhPVx9NrH4cBAJ 12b6nGznyucH+TcyY0jImJMq1GLaw99LZu7blE7CIzWvL6wk2UNNt+tV3gkS vk/aWlkgswPr+6r2IxUknBtovf6l1A4c3i3TzH5AQk1fw8eaEjt47qe1XKOd hB/Cl74MENvBzjX0aZvnkX/cHztQ41Nju9hk3H1oh3aJ0A5kZp9dwpzJePXY OPM11w40LJ9t/xZAxqnEJ5t0mXaQ5lFIL4smo7ctUXktyQ54ib7K0alkvPXk 1OApmS1wb40HOx0jI8/puHqP1BaSGPs1WJfI+GfO6AFdiS0Qk0kc83tk3Hqr 1Gud2BZ2Dmc1tcyi/PBjC/olSiTTeRRMozBflAht4b5F4x8jFhS8syeF8oZr Cyvzu90NXClI/2uvwkKmLbxtd/atX03B5H52ZRTJFiI/TYha4yg4vWWn/lUZ FwbeTZn7ZVGwKDvW74uUC0E17jOXnKHgCm2Kq4uEC49C32mJblPQMNlt8pCY C2EVpaL5VJUffriwkebeNWmsgilquYnnhVx4uH3a1EYnFaw86ZkzxuXC9tGG d5tDVFBGySlzY3Jh19bSKvIuFXT2D3l0jsSFzulFK3gnVfDi7pp+1TEbOHL8 fLPCPRVkZp4k7eywgUJBvV5An3x+K401IbGBb++nPJeSVNHZgeyXWGEDHtuK BeOZqj/82ICv7zSlkauqOLP/zN8lQhvo7VsfYdShitdGcz/1cW0g+WjUDY8Z VNyZxvnLmCmPP1KWUTKHioEndwRGkWygc2i4XNOEiu5LEgquyKyBe9peVwxU 9I7WPfRZag3elfv6QpZRMYKZyHOWWAN73qsJzgYqHl+163i22BquHDvYmyaW 59t9MDdhnTWE3KBVFddRsXHHyJoFntZw60r3ywvPqaiRk61cbWMN9/fPCCjo p6LdrcgMFx1riOfHmsZPUpH9NW2gnmgNLx5b+vGJNPy2TKrLl1nBG2un5+/V aXi6bhP3rNQKiraXlP1hQENtN0ejmRIrmFW47IUKh4ab+zxHfcVWcGajea+C H+1HfazgWLyOa/8aGmo8os8pEVrB6Ydn1dsiaEiLd5r2mmsFdUF3fZq20dBt 01c9XaYVTNlsnvwzhYZ1lx1SQkhW4LzsCrklk4a7BDM0Tsks4VzV/n3deTRM ni3s75JawoKVn2I+FdPwto3OqI7EEsqcPtUzymkoKP7dOkRsCbJfm3mhT2lI P+8U7hpmCa9/3bomuYOGJ97107KElnDJZwN3Rz8Nw6f/MrOZawm+/hV3fpPR MHogXPAT0xJa1rh9sflGw8rTP9/zI1kCK9JqcEiZjhx2+4FjMg6EJm7Zf0CN jiMHzEteSDmwNWNax2xtOr5DmKEp4cCaou7uPcZ01K9TuRAg5kDxI4Wv5F/o +GKt/nKfMA6YLddW9VhGx4pWz4FcIQe6rl/+mLiajgYu44qtXA5Uj1RfObae jnblOuc1mHKewXU9E0PHAWrD0wCSfP2g8ZWTSXTkRsj2HJdZgFnpwbH9e+mo d+dEbbvUAoodIyih2XS8pCrZqSmxAH55zZTJcTq2+G16GCC2AOO6BVoV1XQs 4OiJ/MMsoILlobiijo5xgwVd+UILWNzh3TDSSMc9lF+ftnMtoP0xO2rXczo+ POYQq8W0gITP/f/M6KKj4GBo3UqSBTAjE90SBujY/0Fyr0DGhifz+3a/HqVj /c11W15K2ZBOW5i/+It8/x/smzQlbHB2csk8rMTABQc9pAFiNtziKCde1GMg y4j9YHUYG7baRqx6a8pAtSH12yIhG54Dt3qeDQPdFLQzXnHZ0O0ame0ODGwO /JmlzWTDYV9ST6wrA89NS7sQRGLDUDC9/Ig3A58M902ekLFAFpUyVhEojzcJ 05FKWVCUHFj1YJ08f8WM+VoSFowdODH8dyQDzXbWfggQsyDn7m9L/PczcO92 QmVfKAt2a+u0NecwMOY3dTUQssBgjpm5x3EGbsn76HGEy4Lfz2c515+Ur1ct Du7XYUHSs8XaS84ysOzxPHdbEgssCt1uYCkDm0SNC8j95pCncEaNX87AKIvP AaKb5iD+4suuqWCghZfE2STLHBJy/VTtKxmo/dns9eVgc8iUlF2qlnPj439l Bok/WOYqkjczKPnB8ySbtSSbzYBQ/52dlvwrMyj+wRvvzI64M9sM4h9+51x+ fw6/3xTSH33nmpv/yhT+avjOr7lZPdwsU/Bu/M7kqmBSVbApcJ7+vx8TyLwm TnKT+z9EHlqYLzKBf4JvDEycZ2DeE/HYrBgT8PlLMlZ/goFtmnTT2S4mcGv6 y8JrGQxcPkh/UqdpAiZTY7334xhIh8ouxvAiKLr+U8Oo/LzIc0eDZkgWgYa9 vacjj4GOvzcvzTmxCPJSwqIvzWHg1VVeonuxiyBG8crVnDX0H34WgrHoYpe5 GR1L4zYYPhAtBNq0ug6rcRqO/1745lrMQjBcNHmxpFb+vp+FU04tXQiR84Tu O1Jp2JbxMC91/kLoeX635q4zDSML8I/VY8aQHrDsa7QSDbcoenZaNBrDyhIl 2t57VOySbC74WmIMwdefyWYlUxF7Ft2+u8MYNFjOzB3WKvifncdGUGbBnSNN ouDMnwXq4UVGwCfW2hnXkjG4dPiCIM4IHlW9yFg7ScIOxdepPp5G4MXdT8kw J+F279lnio2M4GlWU82pICLys9NVWIpG4F19If/sXmVk3rW7Pd5jCA3VGmfz LxDQoNfk6pc6Q4CD87oTJbPQczJolH/OEBRaYzfUVX2r/V4fAyhXmN7ZGva5 lpy6KaJEZAD36bMSS9UmahPKq6YsYwyAp5Jqz8OxWnWhKCHRxQDoo/E6+9eP 1PaELOyP1zKA/JQGf5bO+9qOAT8X0xF9+Hv48M0HG97UEt4Y5ubV60MzxzO8 rbyzNtgvv7lapA8m2e9rmzqf1r6xL/+Ws00fFOj7Lo0f7RF896MHWVEWr/qT BgXiI+uya0R60FcaOeV4ZVhAmUw7kB2jBy/C7ib0lI4Juj9yJL8s1QO98KOR bSUTArPMjdzBeXogKX/3VPfUF8FIjWlPtEwXXs3vWr6mSQFYaQmStgZdUFLO +PKiaTr0vvXqNTqtC/6zP0mTm2cCvbeStypJF545M8fdW5TgekJRY5yfLhzd e2PLu0JlWDDQYHZcVxdI/qEhUbZk2EkIVzEZZYL5TX1J82kVaGmJjTB+wIRp fklNGZuosMB7ZGlOARPq1Ee26WyjQXBSZ/H6OCZ0MIf9DcPokOcnSLrowwTv rQlxhQ4MqOtUaQm0ZIIWNasx7QsD3qgLS7epMwFGF63uLFGD7/8vJvwPYSA4 hA== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV1wlQ02cax/EABaEiIigioIQz4U4IuY//b12LB1Xr0VYj2+JRsYqlsRqV li3ixeHVqjtVEI/1YOxW7aG2LtuijFcrwtodxe6qgEdBi3IpnrDJ+/63++Sd zDjfGQ0fn+dN/hoxK3fyO+4SiSTCTSJx/ipZMjYm50vfagk7QM+n+VunjvKq No/+94aLnQI+8V6n6hfz/Id511ceeNYk4HJU6blbuY0/5J1+MnZtrYDgj46s js+/Lyx+brLbjgqo/PpO4+hwT0xfOT7xxDYB9rzY9D5lAOTWhJyZeQIW2uom HT8WgqaCy+rsNwXMCD/uc8cvEoU9E4p/UgiIs604XaGSYcD3W+Zu8BJwSIg+ vfItGfo9tRbe9RCwI7K9OXOVDF9smvljS68FXcNuj4jfJ8OzFZWW4h4LDsV4 LL9XLUN7bcqNn9osqH9lXMeuKzJsWNzz+ZEmC6x5J9aOa5XhX0v69mp/tmBc zRRTy0MZTv1z9I9ZpyzYIw0amPdCBmtRfWjiYQtQ7BiURI657Dh6Ne/Heyc+ 3TvRgqwVvDfc1DleFlTk846KdB4LepbzPpbV3/GywGbnnbGze+zObjO8P+B9 /ZrzmFGVy3tR2Flb2FkzNubw9ppxxHPGETOqZ1GPGeVv837CPGZoMqnHjJJp 1GPGZ1Opx4zZr/EeyzwmtGRQjwny0dRjQvRI6jFhv4J3NvOYMCeB91PmMeGj WOox4W4E9ZjwxXDqMeH8MN7jmMcIYxD1GPFSIPUYEe1PPUake9P5GOHjRedj xKCXqMeITHfqMaJVQj1GnOiTEI8B9b0S4jEgVmzuMeDUCwnxGLBLbO4xYLfY 3GPAXrG5x4CDYkczjwFHxOYeA46/oB797z+Pe/S4+IJ69Ljm4tEjsJd69IgS m+9LD6XYG5lHD0FsxonUY0wv9egxuZd6dJjmMh8dMl3mo0NWL/X8v7lHhwO9 dD46rOijHh3uS+i+dGhxp/vSwe5JP19abPam90eLkb70/mhR6HJ/tKiV0vuj xY4Yep+1uB5H748W65PcyHy0OKigHi20KnqfNVCpqUeDCg31aLBMSz0aVGup R4OzWnqfNWgWez3zaOCno/PRYIyOejTYqqMeNbp01KPGLD31qNGspx41ao3U o8Y0E/0+VOOMiXrUCDHT+agx0Uw9asw3032lIdtMPWkYY6aeNPiaqScNF1w8 abhkpPtKwzcmuq802Cx0Pmnw+gPv48yTBvso+n2owqkx1KPCnfHUo8KvU6hH BekC6lGhz0Y9Kvgvox4VJrk8L1SoWUHno8Ls1XRfqdAWUU8qDCXUk4rcUupJ RW0p9aTir6X0/qQiqZR6UpFTQj2psBZTTyr61lKPEm+soR4lslZRjxJhhdSj xAfLqUeJG3Y6HyU+WUw9SpQsovdHiTPvU48S6bnUo4Dfe9SjQPBC6lFgvsvz VIEsl30pMG4B9ShQvoB6FJiUQ+ejwLyF1KPAbfHnb7G0bra0pvzurfq786TA V3zes7fbkIJvl/Duz94gBSEFvGsvOE8yRq7k3c0uZDJM4ryHO/86tmR4iPt5 ZZTzJOMzcZ8LTgblnAxKxvP1vLcyTxKUm6gnCapPed9iniR4buHtyzxJCNlG PYlYtZ16EnGsjHoScaicehKRvYN3DvMkonUHnU8CFBXUkwBTBfUkwK+CehKQ V0498VhQTj3xyBDfn63bFo+wnbzTmSceDbupJx6r9vHezDxxGHGQeuJQeZh6 4iA9Rj1xMNTxZpwLchy4zLuLeeTQXKMeOW4382acUXJ89Svdlxx77tH5yPDl feqRobGdemRQdtL7I8OuTjqfWBR20vnEIrGTemKxvYPuKxZ17XQ+sTj/gHpi UOLiiYF/G/XEIPMe9cTg51vUEw3JTeqJxu4men+i8VUj9URD00g90UhqpJ4o bG2knijkNlFPFKqa6b6icKeF7isSNXfpviLx7m90PpG42kY9kRj0gHoiMbid eiLQ1E49EVjaQT0RuNJBPRGQuuxLivEu+5LihMu+pJjTRT1SvNpNPVLYHvKW 51+S5V8Kx5VHvJctdZ5w5D3mfc75dmHhsD7lPZS9wQiscXNnvX2b8wzH5x68 W9gHZDjKPHnr2RdiGKz9eJcUOU8Ymr15NxQmOV5h0L3sTjyhsPZ3J55QpPu6 E08oJAN4BzNPCPL8qGcYbondyjzDkDGQNxvvzWAcEruYeYLh68/7KvMEY64/ 9QzF9/7UMxT+g3izcYcNxUyx+XyCMDWAeobgYAD1DEFoIJ3PYFQGUs9gjB9M PYPhN4R6AtEyhHoC8Z8g6gnEb0OpJwAXQqlnEB6E8b7LPIPQNpx6/HF6BN2X P5aE0335w03K+zX2AByIbLHb7zuPH/aLzZ+HfqgWO5m9wQAsFFvFTn9kflN6 bYfz++DmMzd7/stY+L7cvtRdjuk+p1JeP+eDsqkN59d5yhGyf3VVfaAPWrLK Gq75yPHqd+mVLW97Y+pW2575A+XoHOnZVf63frjRYZWpHN+Tvn88Wd72xAtF 9jeztSPk2PZd3r5fRnthclT2rKUyxzz2KwfM+YsnzvQcC6if4PjzD4cl2kM8 cOjC1XMZ0x3P++kXO8vedYd9eWtN6SzH/1/TV1tjvnVDeO9tj03zHZ+/Ksvs AC83VFrriqY5vrf9/vHUd/YUCQI27pt82y7H/PWLDiejT7CWzZup+VCO+q+7 17zV8EJY9XHw0Yw/O+bX9uGu13OfCxuNR8fHFDg+P3rv54Gez4S8OktCTcH/ 9vVEeEPsuobT93ZqHwsqsbtqIt9pbH0kDBG7H/v3ykPh0UWxK96rHVjaLfwi 9sN1f6rqXd4lnBTbeZtk+Z1Cpdjst2/pELaIPW3mhMXy6nahQGwJO+3CfwFN vtwt "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-8.000000000371415, 31.}, {-7.0000000004556, 30.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-8.000000000371415, 31.}, {-8.000000000398302, 30.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJwtkmtIk3EYxYcTZygaVFoqub1/Y0QtVIKa/t93jxWlGWqLfUixi2GGWRuG Mss0UjRIVmpeisw1nGlgVixvZT7YRaehTUzTiehGMlmR2YqpNFvSD845386H wxGlKeXpHjweb5tb/xLD+W4XIm8NGdxIKmz/FCnESyvCisM/OTCX10qOqoQY 3XrPYLdy0OZISMvuEOLx4AsZVhMHQXk6hdRHhH2y2scR3Rx4hVYKGs+JsCwk pGBMz0H+nFDd8VGEDc+cs6abHFwZjn+k2s+g36pkjCg54E9uqBpCBoc9XyV/ SORgo1dezEgsQWuvTjko4YCMBooPKAkqBP3H7AwHU7LvkvBygtN+nZn6AA7Y uFVF9ROC6okcw5I3BwcXDtXn9hFkMlzhtiUWnLuN60xmgpZ2+YxqngV5YFGV 3k7QMJjdWznOgqImZ5/jN8Ea3YnxpLcs8F5o13f/IXibBoQ2tbKws9TTvUsY nl2DhfovGk2Ri6DLsqffksjC06+SKL9lgg/NE+8mpSyk3J/10C4STEw6cjIh jIUHjmbbXhtBfsytO6w/C1d/ldg/TxLsbdGlNy1TcDxQ+1wbIKipLhnRzFEQ /CiI3dVO8NRKlHlhhILBfldn1RJkp3oKh3oorGiMW7SlBIl0E4pbKMSndIqL TxN8Mz2o/lZBoeFikf8iS1Di816ZfZmCt1Fsmg9x973m69vOUFBlNmaddzGY 7Cze3JVAwSJfnc21MLi1M24gP5pC6vXICF8jg808eZdrO4UZpyx5x3MGXUN1 NlkQhaw2cepoHYPBYRIF+FLgvZyXCsqY//+h8Bez0hNn "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxN1GtIU2Ecx3G3nSNWWiFhx1xeZqTQzaL03P0RUVakYdYLzZKotEBXQoWZ szKz+6gIbFCSaEQRKtkNDZ7ugka4UAtzmVZm9kK6gFOTtvP44vnzbOPLzrYP /wOL2WFP32UOCAhY63v4X0mCxfccTQKMSUbQsukXM1xRpHws+tK63zo8z7tr sqOiyPE6V+NQv46JMLsS4Ywk3oj83P52HbkLWjLOD84lfai8vfSJDqtpYPje 4rlkdaTV0VmrI7KydYZzm5XYGkc+t5/VkTd8oCGyKIIUmhd3xtp1mKZ+69jh mEO0Kc2ZbWk6+r5ElGQVhBNHS7W9dZGO4FRPw6GYcPJ8WsumIZsOx7ElNVU9 AlkZ+nhvbZiOpNIZGe+qBfK3+0CjN0hH4hrH09D9AvmYN5Hw3avh6Ifin9kp Ahl/lN67b1DD9MSgjsZ4gWxqK3x2uUvDl62xxbNDBeKp3ta18YUGU+obTzkn kBtqWNStOg2u9EDfXgSy2xgNM+20vTVpozVpGnaW0b7QL/qOhitO2rE2/2i4 cZn2g5xpvqPhzOT7a6v++I6KtMnPe3r8o+JXAe1C6+v91tcqCid/PzCrns+q V7HczRuda3hU5N6hPWp4VNhP8YxHxfo9PONR4d3AMx4VRxJprzM8Ctw2nvEo +BfKMx4F44E841Fwb5hj9qNg8CvH7EeB4OYYj4Lk+xzjUZDl5BiPAnsOx3hk HI7nGI+MIwMWxiPj4DUL45GRWW5mPDJCksyMR8aWMRPjkbHETXue4ZHhajIx HhmVD02MR8L8VybGIyFlwMR4JIzNMTMeCZhlYTwSDm+3MPdLQnA1bafhkTDS Tdvg2CSIIex+JLhXsPsR8Wwzux8Rwfkc4xFxt5hjPCJuHqPtuuofEcllk/cn u3miqEzE0xO0sTA98HqBiIUnaTfw/i8QUVpBu3ewc7w+RUTTKdpv378cqkoS 8ek0bYc7rsQdJ+LnGdo//JeHi+g7Szvs26oKc7AIco42/f8R8R/jWaNZ "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-2.000000000302009, 31.}, {-8.000000000398302, 30.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV1glMk3cYx/FWhjrft8zghYgHqFlbWuh99+XHoYIgqGMDhxpws8yhKGxO x5wScUs85jE1KnPBA40x0+GcsKjLK7gILjiNx3RGdDpEIXF4NAavdvT9vzHP /imQb6Dtp8/zNjR2zsLpc/soFIpjvV+hn5WFA3q/K04ppJOEO7NZdw0/sfTV EwHDZrEeqgnLaegQEFfAepX+2kr9NQHKGawNb7sGF7YI+Pk91mOkOwhw57Ke +rw253mtgG3TWJ+6dOhZ0SYBLdmsP9mTqvx6mYDWTNY+6QhYl8G6J3T3HAHd 6azX/+PovQnwy78fGxc6AnZmsa4v5HpvAjqmss6s8WfU+L24KPtutoWOF0Xy 6y2PaS6LafZiczHrvgV14QV1XlSvox4varexfiZ5vPhiN/V4Meog9Xix5gj1 ePFbA+sMyeNBy0nq8WD7KerxwHyaejzwnWFdLHk82N3MWhpvjge/nKUeD35o pR4PPr9APR6Mu8J6suRx4+B16nFDdZt63Mi6Tz1uVIdxZD5urOU4Mh83siM5 4nHj7jCOeNzIjOGIx41VoznicWFDLEc8LpTEccTjQrTczONCxwjqcWHWCOpx 4dFI6nFhz1jW4ySPC6U66nEh30E9TsyeRD1OVM6gHifEUupxwtdIPU7c+4sj +3JiazfrDZLHifI+vNQSJ86JZZE88ThxbDRPPA7EaHniceAnI088Diy28cTj QLWTJx4HHG6ezMeBsCSeeBx4kcaTfTkwagr1OLAgjyfvLzs6P6AeOzaVU48d virqsaP6NPXYUfYnT+Zjx+8dPNmXHfv8dD52KBUq4rHjVn8VmY8Nwlsq4rFh 9CAV8diwcrCKeGyIjlARjw35nIrMx4aWfqy/kTw2fBymIvPpfb4AnY8NqT10 X1ZUPKLzsaK9k87HisrbdD5WHG2i87FiedS8ohWBoPhYqb+1L8cKU0/eV6+e BcXP8g7H3nP03n9cR0nF46DY7evSa+Os8H0/aMjTe0GxwHA7bCHX+3xz/q5c dD0o/nr0273H/BYEPs36sfNsUIx8FOADbRYcvpS3q6g+KM68Px7pzRY8X94n 91pNUPxuRz/vljoLYlOqHu5MD4qGFwUvR/osULjP+SITg+KHvp6mkhwLkjqX RK+OCop7h10XGxwW3Miq4pThQfHfCOUTZZwFV+Z2Oyv8ATEta8HMyZwFOsvJ ff6OgFh7ftTLjX4z7jR0Zi+6ERAjdwy5eKXNDP/DJdYHlwPi6gPTbkY1mzH3 lm9GyYWAyAcujnm/zozWFfXHu/4IiGw+Zhz6kjW7fszIr2DNrh8zzi9mzfZl xpuLWLN9mTFwHmu2LxNuFrJm+zJhcR5rti8TrmaxZvsyQTGeekwQh7Nm148J 7QOpx4TSAdRjQl5f6jHhwBvUY8TMcOoxorw/9RjxQEU9Rpi11GPEGROdjxFF LuoxQpnMmr2/jNg/kXqMmJpJPQYocqjHgPpp1GNA+TvUY0BrLvUYEMilHgMi 3qUeA17m0vkY0JRLPQZ8JPcWoXOz0JmILvn5Tp4InUSkyy093PpEVE1nzUkP kIhi2X+uNXQSUJrN2i/9g07AsimsR4ZeTlkCNsj7npAWOgnYL8+jpHHo/Mah CWiazHqr5NGjPYN69Bggd7vk0cOWzpqXPHpUT6AeHa6mUY8O2jTq0WFjKvXo 0F/u+ZJHh+0pdD7xcKZQTzweJlNPPE4kU088ipOpR4uCZOrRvv69tO4yLdbI PVHyaNGUTD1aRMrPv1nyaLD0fx4NnqZQjwZrUqlHA4v8+i3m0NHgrtzRoY+r fTVYJ89veX4t72lTQytfv3OkhatxXO5G6fOnGmmTWNccWXs1aaEaTXK/kK5H 9ev9XA79uUmNXXLrWldHhEepoZD3qZCOGv8BNYr2xQ== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV13lQlHUYB/AdHBkTBssdTR0dR9qF5d773uWbiaZkKqCTUiqVx5QTIIeo iGuZXYIpaCpyKQrmAXIIRQ1oMoyAVIZ5Z4IKWjEmzMiR2vK+7x9fn3l3d76z 77z72ef5/d7ZnfZufNQKD5lM1uR+DL+6lo92P8saZEKFY8nUxuvREYP1F76b lNv1yAnvpNbanhd66w+WbrmyrMMJVdrC0KLcO/WuVn3t6jYnXAmDt1IHEuqX K/VWjxonfjzkPz9kcVd4ZOXmpcEHnPi9tLzx1oP+cEfqy8quTU44IoYePmwf Af1HQ5nat52Iq1ub0dbnBX1u0D4fkxPxsQURWz8YC9uTkpkbfZwYfzLGkV8/ Ft/nmXaFjHZi57E+v+rRcozI2OZbNcKJjujNHucj5XgxP+exz5ADniV9P1/9 WI6OJ3EvOR86IDscs6OrTI6NeT3xr3Y60Da3AI8uynEt3Sqf2O5AQlF758Bf cjzNjRg6d9aB7oK+tKeDctwfHKOKKHNg7sxn7pJjpVAO+Eh5oHjeYPE8Bx7M EnNWp9l9OHAjUsyv+A6XA/cWiPn0ci/34cCoJWKeXdDnPuyY/r6Y/7g5XHbk JIh57eSmxMlNdjzNELNnbPnI2HI7ZDViXiV47Hi9ScyDgscOj0vssUPzJ3vs uNjNHjvu9oh5juCxYc0j9tiwspc9NrT/yx4bMm9zf2xIvcH9seHZZfbY4N/O Hht6fmGPDTFt7LFicSt7rHjWzB4rXmtmjxX7m9ljRUsze6wYamaPFQEtYlYI HiuiWthjxYYW9lhQ2MIeC862sMeCzhb2WIBW9lhgbOV5WXBbOn+H4HGfL2WB 42tBdDN7LJh0nj1m7GlijxmNjewxo/Qn9pjhqmOPGXdruT9mmE+zx4ykSp6X +/PK2WNG8QkxRwoeE/K+ZY8JGSXsMWFOMXtMcO1jjwnhe7g/JgRk87zc73/N /XFfP5M9Jtz7kvtjxIbP2WOEeRt7jJi2lT1GeGewx4iSdO6PEUFSzhQ8RuxJ 5/4Y0bWJPUZMdbHHAHzCHgNmfcYeA4zb2WOArpA9Bow7IuZ+wWNA4DH2GBBf xv0x4G4FewzIrOZ56bGqhj16JNayR48TtezR4141e/QYquJ56aGp4nnpse25 9aPHoOSpETx6ZElZvB/qML2CPTqMq2CPDqMq2KPDygr26JBUwR4dYirYo4N3 BXt0+OYU90eH/nKelxYh5ezRwlzGHi0mnGSPFpVH2aNFXCmvHy3CStijxZQj 7NFCdZg9WkQVs0eDvEPs0WDkIfZokHmQPRpsL2KPBvoi7o8GjYXs0cBWyOtH g90F7NHgcj571HiWxx41vPPYo4bsAHvU8NvLHjXuPLff1fh0N3vU8Mrh/qiR uIs9atRJ94Mc5/1s5/0wdGeJ+Ye64QpDv7SfhMtlheGBdH/wEi4QhgZpP15o Ha5Q5G8Rc5+wIENxfLOYpwx/ncRQdEv7O2LGcIUiWtr/H54Zv+bM+FD8vUHM uwVPCKrWsycEx9PEfEfwhODiOjF7C54QXEthTzAWpbAnGI+T2ROMumT2BKNQ ymsETzCOJnN/gtCezJ4g+KawJwjZKewJwv517AnEmDT2BMJfysK4EwPRIZ0/ U/AEwr6OPYGwpIo5W/AE4MpzngBMSmJPAP5LYE8AXKvFLHBaVfhnhZh7BY8K X7zHHhUWxYlZ4MxQYcEynpcK6e9wf/xxKZY9/li2hD3+mLCY148/GhZyf/xw Lob744dfo9njh+4onpcfPKO4P34IXcAeJZbOZ48Se+exR4nrb7JHCT8p64RS Yv1cMU+sS3vS66nE1TfEnPFWsbf9pgLTpRwnXECBSun3a8NvJwbidioQKuX8 U19dDo9XoHoO71cFZki5ffh0rQI3Z4s5qPULn5ETFHBJWfx/ocD/YkS/Fw== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-1.0000000003634, 23.}, {-1.0000000003856826`, 22.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-1.0000000003634, 23.}, {-6.180894323932989, 22.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-7.0000000004556, 30.}, {-7.0000000004630465`, 29.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-7.0000000004630465`, 29.}, {-15.27349263178047, 28.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-15.27349263178047, 28.}, {-16.273492631788542`, 27.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-16.273492631788542`, 27.}, {-16.273492631796955`, 26.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-8.000000000398302, 30.}, {-9.000000000461341, 29.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-9.000000000461341, 29.}, {-9.273492631703903, 28.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-9.273492631703903, 28.}, {-9.27349263174608, 27.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-9.27349263174608, 27.}, {-18.273492631795932`, 26.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-9.27349263174608, 27.}, {-20.27349263179906, 26.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-18.273492631795932`, 26.}, {-18.273492631799797`, 25.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-18.273492631799797`, 25.}, {-18.273492631801275`, 24.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-20.27349263179906, 26.}, {-22.27349263181185, 25.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJw1lXs01WkXxxEy6EiukcatyeFcfud3O4cYW2a6GK+jNFSTwpTXMKYZkmrI uPYm9ZYKU8pUp2FGiHQkvLapxj33Yia83lBJ0sjtzGBoeb9r7fWsvfZ+9vqs /cf+WgTs37pPRUlJKXQ+Fl5i23jmkg0sKr2TPRj11ZY4ubI4tLLs0MyYBEhs MuYDi0bcJdKSQQl890YdWxxZTOB3xvE7JaAUsT/Pzp5FYq2Dvl+NBIrd3utz YFh833DhgwQyw9p3zhEseipkUoVMAvLhZpPDPBaxLW/a/4wE1EpnzXPWshh+ 1VU5KUoCSY99Q1MsWQx8p/n5RpN6FmYsupVFVhVKJeCwoc3G34jFVseunw3t JcDs+yPXXZdFxVCy5XlLCQyHb7v0VJPFew9SbPjaEtgbNv3XGtV5vsae8p5x MWT69dXpzTDoqBzb+1OvGFI/1F6aN87gsH/46VO1YtiofaTwzav5+uvbTSm3 xOBVvcwusZnB/BZn3/69YkiiRaxlDYNHG50mwj3EcHfnMrffKhk852C6VCEW wyv7q4F5JQyOGHf++6CFGFa1vj5xsYDB5KADp19oisHNaqJUls1gCHdUw+st C4f4t0drshg889kn00XdLPw4yiM0MhhUzCb6v1fNQvOXvocCTjOYo/eDi/dN FuRcK+5sJLO4Hxa2ioPjP/qawXB+7JVKKQsdjsXPdIMYDFObs/WwZ8HZQdk7 cA+DQSO9KiusWDgl3PLQxZtB9+dWXK1lLDxYJfOUuTNoPVZ3yX6SgT5lxZOT 6+f5OR1+l/oY6O/ZGj4rZvDGuvVhbAMDDbfy9SZ4DO46vKJVtYSBV/GG94fn 6EWe+dw0pchgjMa6rFx5rpQBGHK9vnaQxkcPc2JmJQz8b8Qp07KLxsQx36rd lgy0co+kqzfQ+HhZ/bcNWgzoXZxKa/sPjU1mo/kbx2mQrS+9cLyQxmCrxp3N PTQkmZdftZHR+NPqgJjAGhpu08oFN9NoTNEpWKVZRIOT+rMfU4P+z0PD7s3/ fRi8k8bfzA4GdElpuJxablf+CY2c6lbBbXsa/uz7tiLJkcYlAVH101Y0RIhX J9TxaJSPhEmyOTRwzl6LObaKRm6oPKJimoJf32rdrNCicXf3hnjHAQq+3+Vj EKqgcIuztb91CwUn6hILzj+nUO2sh05EBQWD8VfWzZ2lFnkoWPFst1VmNIXn gmtiW6QUdPB9yBeBFE5Nm944b08Bb3ty0KCUwtP6/gNFVhQYBk49OCuhcNfd dD6XQ0G6zxW3N+YU+r6sTJiaIuEGL3FiVoPC1OyuIfN+ErwHrtWWj5I4O9K/ 52oTCedjZ+7ZdpJ4qarvaVQZCYqmNP2/QshFHhLWbSltrvUg8YH6GeWnUhLS gvJ6XUUkVgR/mPu7PQkcw3CXYD0S3VO/+tzTmoSsHZoTjuMi/CbawtZFhwR3 Knym7JEIBTyfuTyFCPSv5fk8KxFh3GWdp2mDIpjMKVWtzBBhaLtbx5+tIhj/ KF3V9bAIRxs1Hj2pFIGS32Hppz3EIo8Iggwa8y/ICXzbWxel4imCL95OHj12 isCDTWsydjiIYMnMdKVpIIHDdOSdkDUioIRt3/g4Eei9vLJboiuCmeT4cw76 BN7yn1laNUNAhbmhZ3KHEFW5pFj1JQEFR9u2j8QK0S3QN0Sli4B2obPrFb4Q E1bGyMqqCWjIquKdEvAXeQgQ8nO3CeQ8jHR8cs/dk4CMu2y/oRMP41xCiuPW EbB0097fN96zw6QIPYmGDQFHOiiHqk12mNDZ7tFtQMBYwHWl+EZbjAoumFJW IyBs9I7g5BZb7PLeEDI8JITx6K/u97ZzsYD10zrwUAgxWr9WHfHh4qEDN1ou FAuB4/WBycUcS3xemCWpShZAW+RAW+eEBVZYJPaZhAggzkn+8uuPLdALW3Tb NgvAUJbh//k5c8w+mVj74gMBWPmsDPGrfh9Ljv+gsUdFAC+zrZvyA1fjsWLL JvIJH2IdvF4XqpuhAUfbbF8xHwY41+u/yDZFv7Rdf4wn88F4jcneR5tMMOQf +tKBPXwwiS66MzlkjDS1ID6EJmzutUk3QpMFu1Dnw/c5d1/d9zbE6O0ybcdu HmS+UOuv5xpggJbcT0vOgwMb7X5xWq6PVe/uPw8sf7H9l4mmHl4uPPHYeT8P cnaosgFGK/CdXUh5oMq5U68v0cX2hXaSB+LejzeTXy5Hu4bjHDVjHnx34TPf iH/qLPoXD/4GzGwZAw== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-16.273492631796955`, 26.}, {-15.273492631780982`, 25.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-15.273492631780982`, 25.}, {-14.273492631779277`, 24.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-15.273492631780982`, 25.}, {-16.27349263177848, 24.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-15.273492631780982`, 25.}, {-6.0000000002648335`, 24.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxN01tIU3EcwPFpdrNVdjMtdaTl3MWD6P9ctlJ/utJScms9mGjt0kXwkqk5 NHqIHEYqlrOGwWIme5IMQ1LMiH9meSElMdAKzZTyAs3CJTkKc9v/YT/O4c/n 4cf5nof/AX2R+qIvj8dj117XeePCgmxjLYV57pGBnHghuLv83xIHi+c93ita p+z8zoGF2Bg9fjN6nIMk4hihfLe2n4NJvceCQNcCB2XEKqdN6bRx4EeMR1tX dPUc1Oo8Lm1W+FRd54BPfMk9HJi0Hq+41pUcSInvzHB1MxwHnzUeR4S7Zq2P uEO7Ze3hoIg43eo4YXWwkEk8OeEaFtTEJSF9xSF9LGiJN2S3rc9uY2FK493D Ap983/07ShYSiOvcPSxcJXbnhLPwROvdw4KdOM3dw0CMzruHgXKddw8DPTrv HgaG9N49DAw+rEa+1RTOjWNnD6kYEGTkH1yqpLAidCxpVs7Au9LazZ8qKPw3 IsXQEsnA8Db7TEc+hWtTjcaiXQxECu62386i8J9b9QWMDwPjtpJytYLC8K2Q Wl2kYdJ6P3aHiMJ6TfDgwBcajgSsfH3jT2HNckOi+T0N0ZlpFrFDSnpoyLRl q2WdUswTmWuCVDRU20eqEiqk+PGSevSpnIbXdKtMLpfi3LeW+NhIGnyv/ciT OiU45lHp4IOdNKR2m/bt6ZJgf+NYxdwqgnsrluMOgwT/utyfHmZHMIf4vwfi JHhOlwKHJxAkF04JzItibM85lZk4hKC5OXjgTIsY+2nn74pfInAWbs1RhIhx meas6lwTgqSMKaayUYSfFY98eGFEUKowZQUJRLjXfCwsJR9B/cmIXt+2KGwd 7pI6TyOwFDQYktOjcFowxfuYgMDUNH1l7KcQ9xiaG6clCMrmA9pfNQnxptnA 5cD9CI6mhsX7ZAtxaF5NkIGPgPfcf7tZICT3C8F/C8l4uA== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxTTMoPSmViYGBQBWIQfSDhlSV7j84BBjCwcNgK5b+U3F3x97O5wzooX1yT 2X/7M3OHxVB+i+6NJt0b5g7ToHwDdSuRhBPmDl1QvoIYSIO5Qw2UH/Brif+v JeYOuVD+wctrfyZONHeIg/KLFzkzttWYO/hC+WlgYO4gaxde9LtT54DtFNZK rQBzh63X50rfaNY5MHeBQOdPK3MHft19pnMrdQ60drdPu6xm7qBvt+OAV7bO gc8hWQt3CJs7iHL37HkQAfTPnx0rVzCaO+ybbKkZ76RzIKO5eP3iD2YOOjcO sB1T1zmQ82LmppUPzBwSbiiGinLqHPiprbN510UzBweH4zOeP9GCusfMYd43 oZltS7UOxG+evC05wMyBz7PI71CK1gFlWc/6e9ZmDpPMn+6YpaR1YOvitgPX NMwcNA5l3+C/r3mAz92nykfczOH8C9a1irM0Dxizz1pjz27m0Ll6s9mFYM0D yk/ywzf8MHUI5SotlebRPHDv7tmqea9NHUxYvTKZD2scSPmyWYzrgamDyhwj oY4KjQNb1ZW0P181dfgYZfVtWYL6gdff9vNrbjZ1+MIQnfQuTu3AmrcR/AqT TR10+qaExRWrHvjG/VbzRqmpwzSm55e+zVU5cDKwJj4w2tTBLC7o+vZ7ygfU 97Nt6HY2deBaeC15oanyAb6QHul2PVMHodPFFZsXKR1oEOBd5Cxj6uB/R1P0 narSgeovHc4HeUwdDlz5YRm4XxGafkwdAKDUADw= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-16.27349263177848, 24.}, {-12.273492631611077`, 23.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-16.27349263177848, 24.}, {-16.27349263177979, 23.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJwtkn0s1HEcx2/kYUOn6Ih12JA0ft9v9ft9bXf4kM79IzfZWjiVTmyVhyy0 2ig9YaMlkzlPRcvT2appUu3jCi20zmO7uylZrJQWUVtYWK/tvfefr+29t1dS ekyyhUgk8lnLeudzi1pLBUHRBkHg2F86p4khmKtJ1tUsMFCYlTl9xwiqDrX6 yD8z8DjhyXZnErwyMJL8foSB9qgk8GYBQcm7ibQsPYNnBv+EpQqCNolvwEHH 4FKnulutIxibXWFqrGDwVdKu7u1d821XhAbnMVj6IqVkkqCtYuzUsIbB/T1t sqoVgukrkcdTlQyGzLXlg/YUS5SfNPOMgcZ8OFRwozjgZxh+4csgjo4GjfpQ 9K1x1g06M3hkcrnczFHUPmhdkFowyDR5uHcwikRZ2fBwToBb5Lvln2CKHy4a 8YZRAFdTnjwjnGKrIkNZ3yOAhWn8lfQAxduNcbLldgFUZH0fiic3EMDYm503 E0Fx09C9u1EqAc4V/fUtC6PYWVHIXZMJ4H2hoMxaTvH6ExcHRz8Bpu5s7gnb RzGFHpTNbhOgY0rbFeFPMdEq4KmLlQBV8YE5YinF03sfF5Yv8lAmevm7Xkyx tGuqSTPDQ/VQXPDyKsHX1V1uV408dBoWI6XfCLoaZealtzyofkxb27QTjK7r c2po46G5KvZ8SzZBdX9ayHQJD/qxkFq7/QRD4mnC87M8VNY15u50JvgrWnxm 1xEekua32K0Oc5jfZJvpH87D1m5DsXchhx9TdqRiAA/hbUVZ+kgOJcVRMbPu PPzskOvHxRx6OVVyLfY8eE7M5GgmA///h4d/6jUG7w== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-6.0000000002648335`, 24.}, {-5.470951125657507, 23.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-12.273492631611077`, 23.}, {-6.180894323932989, 22.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[{{-5.470951125657507, 23.}, {-6.409552330924616, 22.13722991432966}, {-7.677035030559011, 22.}}], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[{{-5.470951125657507, 23.}, {-6.738433825291856, 22.862770085670483`}, {-7.677035030559011, 22.}}], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-5.470951125657507, 23.}, {-1.0000000003856826`, 22.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-7.677035030559011, 22.}, {-8.873666583657155, 21.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV0k9IFGEYx/HRcC8KQa2CsJbWYQvc8P0jqacfGFIiTLne1mAL6iIY5qWg wBLKS1HH9tCCeA02Qfdg5F5qO4mYLVPUpiytveOxCF3WbGaeF3rn4R2GDzPv zJdhuq7fGr3RaFnWOe/wz4XNvf4rq10FK5hevP9EVu0rdw5+SagSufXsETtf lTjjkGcTzsOEI/HgM7knPhBNf5D484V8ss3fIDH3lXy5tmDXFiRkmVz4+Gr/ 2nOJ+nfy9Pxgw6N7Elvb5JvBSCxVyMF2WyL5g/y00uctiXyVfPqUPxKVHXI+ 3bycbpYo/SRfyv72lsAzRS5/80fgmEu+HStOxYoC49qRVK4plRNIumaPwJBr 9gj0uWaPQNw1ewSi2stBj8Chfv9w0MOxE+rhWFNmD8eiMns4RpTZw9GjvR/0 cHQos4fjuDJ7OI4qs+f/deph6Az1MIhQD4Md6mGY1s688Icho/3k6pu/d2cZ 3mqjezTycpJhW/t1k/8ABkt/ny1VqucuMpzQXnfe7WbPMwxo39+Ie4thTNv1 b29nmNBuq1543NjCMOOa/zPDP3+oZ4A= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-1.0000000003856826`, 22.}, {-1.0000000003947775`, 21.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-1.0000000003947775`, 21.}, {2.0551637700374954`, 20.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-6.180894323932989, 22.}, {-6.180894323932989, 21.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-6.180894323932989, 21.}, {-2.925516824096235, 20.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV1E1IFGEcx/GpUIKVQBApUSqDmX3feQkxKfuRFhmU0UnwkIZ1KMG2Lh6C loIiCyEs6xJb4aEOhiXYix2UDnowKAzyYrVpW+u6W7uzvsxS1s4z/8O/h1mW L8w883me2Z3tJ7qOnVwvSVJr4WN/R2KxYeusBEmMnRilXtgy2v3HNPCXutyz ofl53MDBr05fDsxcCswY6KdWlbqytkkDi9RbxQWF8+ecPpofaM4PGHhMPTY9 aLXfNFA67/T5hw3rrlwwEKE+JYaBNWpxebOBO9+c7p2rLRyF+eNO76i2R2G+ 706PtLkKh4El6kPRXFM0pyP7w+lPs/bQsXHB6XOVE+HKCR21SaeLW4eKWod0 RH5yj46hX05bwqPjboZ7dNRkuUdHT5Z7dPRnuUdDS5Z7NLzPcI8GKcM9GipS 3KNhNcn3R0Npkns0dND6BKdaQybBPRpeJLhHxasE96jIJbhHxekF7lERX+Qe FQ9S3KNiV5p7VDxJ8/1RsZbmHhV+2u9b9Ym++kQINdSvR+0RQhW1mK43hC90 vUtMEEKE7v92yh5BVFPbq2uKBpEib5W9nHAQMer9jfYI4jf1mfHyzvHyIEDX 3xaeAAZT3BNAA91/XngCkMhXIjwBVGS5xw+XyT1+pEzu8WMsxz1+RJac7hQe P9Rlvj8+vFvmHh+Or3CPD59XuMcHw+IeL65a3OPFS2rxuMNeTFIfEB4vnlnc 40U3dZ/weFBpcY8H91a5x4P8fx4PDtP6BGfKjR5avyk8biyZ3OPGDWrBaXTj iMmflxt7TL4/ClpM7lFw3+QeBWU5/vtRMExtiKGgg3zidViswEX7fbFloGT3 rIxH1O1iAhl1K/z9JuMNdfTp9Y97u2TsW+X/Dxkj1B/s03UZ22j/fFPXNhVt lhGx+PtZxj98x+Ad "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-18.273492631801275`, 24.}, {-16.27349263177979, 23.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-16.27349263177979, 23.}, {-16.27349263178064, 22.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-16.27349263177979, 23.}, {-14.273492631780016`, 22.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-16.27349263178064, 22.}, {-11.561691732461668`, 21.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-14.273492631780016`, 22.}, {-15.44021963792244, 21.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-11.561691732461668`, 21.}, {-11.56169173246326, 20.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-15.44021963792244, 21.}, {-15.440219637926702`, 20.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-11.56169173246326, 20.}, {-11.56169173246252, 19.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxVlE1oE0EYhqOl8dBaqTSxhrRNNkXt/u9OCVKkfUE9RAsRLwpBqEFj0UKo olQQrApFEQrFehMCkoOXQPVQqRVNQaiHelK0CO1BJdCAXtpLAgWzs9/hy8ss y8POzj7zzczGs/nzV/cGAoFU4/LugXjm0u1r+8oBmUEsxnyuHl6e2t0WGCcO D7Sk31YEOokfGesPjXWBN30+20eHusY+C5wl7pMvCGz2+nyuXkzXi43xiMtf S7XLcwLVHp9vvTy5Z+aeQI44JyMQJJavpwVqUZ9nfx9vNIERep5QvAh8J14c a2s0gTJ970xhJ1XYcVEnv80NLy4e0/xvRlcno6suxhM+BzMLrZkFFxWV+7j4 q/tckz4uRk3u46LF4j4uOi3u42LK5D4Okgb3cTCqcR8H745xHwfTTfVxcCHC 6+Ng9xD3cZAP+yx1FAelEPdxsBTiPjbmwtzHRrKb+9h4FeE+NiJHuI+N6wPc x8ZBnfvYOGDy+tjINtXHxn7b5/nhrWfDWxY6iN8ve7GQo/5yuFkLIRqvTQ5g oUI+X9a8mPjQ77M3u1TBRFXxucebzqSJK7T+p095MWHR/r6xEp5YCZsYpf3y XPoYWOrlPgbuEP+RPgZmiNulj4FIjPvoeBHjPjq64txHx4MmHx2/iCekj46k wuujYVrhPho+KtxHw7bCfTREaH8PCi8ahogj3nEPasgQ379YbD+xoeIucVYW WMV8gp9fFSXiwuunP0byKj4l+Pqr+En8zevuqvhHrK096WjtVhHo5/8fFf8B 3eDNuQ== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-15.440219637926702`, 20.}, {-11.56169173246252, 19.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-11.56169173246252, 19.}, {-11.561691732463885`, 18.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-11.561691732463885`, 18.}, {-8.873666583667045, 17.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-8.873666583667045, 17.}, {-3.9255168241054434`, 16.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-3.9255168241054434`, 16.}, {-3.925516824109593, 15.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-3.925516824109593, 15.}, {-3.9255168241100478`, 14.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-3.9255168241100478`, 14.}, {-2.925516824096576, 13.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{-2.925516824096576, 13.}, {-1.9255168240966327`, 12.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{-1.9255168240966327`, 12.}, {2.055163770040224, 11.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{2.055163770040224, 11.}, {4.999999999958504, 10.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{4.999999999958504, 10.}, {5.1619887228560515`, 9.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[{{5.1619887228560515`, 9.}, {6.737418070410627, 8.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], Dashing[{Small, Small}], ArrowBox[BezierCurveBox[CompressedData[" 1:eJwtk3lQlAUYxnGRK5dLvm8PdmG/j10NlcMBhUUDHggEHI5yhxTXAZYAMQ2j 5AwMEdBRQC7dQBJMdmAwjDgcCVQkori2DA0kQdHlSJRDwAISWh2emXfeef54 Zn7PzPvSYUf3RDA0NDSgnrd7dkvIYwXxxqplgReRW/3SrxG4bx83szhGg/Gl ysj4BgGrPdqXontoxNt6V2W2EtCW1mhJa2gEpEu5Iz0EwvyPWbbk0jiTaB5s NUDA9W2AxmbDvIQDYwTK5nxK53xoWHnWRcXOE0irkM7+ZEEjn5dhE7+WxKjH KQZzgcL+fO1OGUGip/uNKPTsO3t+QUQitTauIaCUgqP5wQmGAwn/Q78JhmIo FD4p6krxIrF95s91CR4UVAqhwydBar87O9GMTWFz1Notvx4mUTyuulvSK0D4 pveq5MdJLA8x68lEAXL/7qzrzyORH59fpDAXoLayxuusgkRQbWyab5s5sqwu vmoaV+eL3sgMgY/KJd3LJL5a3BVk62qGsOpy4SibhQuWWgtLI3z8cKE4Um8b Cw+F9xJWsvlwv5jJd5Cw4P+8rt/JkQ9WU5TnkVgWpk+Uc64O82DzCsNXi1lo USnEkmweTvsaTs+1qj1xQ2y3g4cNt3pjvCZZmDL+i+M9bopIvyFJXD17lYcL T+3O0bsTbPSTmTrerlz825vltn4DB/Pn19QGj3KQcn1juGMoBy+5zKLBHA7+ qJb7u33DQddlRXObmIPFxkcaWx9ykGat5BMqNl4OLCdpmnFhejOjsSuXjWaj +eamEC5yPujOn3BhI0ja2r6vnIvhscuVX6i59OWlAYUPTFd5SGTmNmqKrdW9 WK9XnF1JRC+23aLTePCVDxY4jBJovXcn9cN+Hmb5OwNP5qjvQFDj84stH6IK 0kMkJlA9cI578jQfg9s/DeU+NVH3k02nP+GD6nCrCjtngt3fCpXdzmZ4HlpA aziboOlaX+3+YjO4v5a1z0ysR9HGxx3W1oJVHmMoCzQtlosFqN7ha+UEY6SP ZVyJ06Lw/iZTT+EzIwiPJJekuFCQRWiq9sqN0LZ3ZKkggQJjSkevz8sIB6ta 7jTWUZBkBUS5/WMI/XCDyckpCt/d/7nzUIQh6tOVqfbWNAx+/Nzp3QEDBDPX JJ06TCPZ6aP6xEAD6C0pHjyrojEn+WynrE8fXIbimKXIAg1+15NjJpmwUfpF NxRaIEncNWjPYmJXSFl73n8WcCO+D670XwdZQ0nKTakQ2sOyFaX8HaT+7l4g rhVCeenp7YoZPVypydfR1BDha79tZXYH9NARmDXA9xQh/IWk7GifLmZv2zIz T4hgd9y9JfhjXVBTySUuDaLVf9fF/+4OrBQ= "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{11.999999999376143`, 38.}, {9.000000000192813, 37.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[BezierCurveBox[CompressedData[" 1:eJxV1wtQVOcdBfBLWu0MsSbBRAcT4i67vISFfb8f566QaFJHq5k2StJhLK8I siZp44Q2GU0bjXkQo9EookCDLBBF1ERja6VEBE1gUQzRMcUYtVo0sVXUMUyV 7n73TubwzZ1hz8y9d397vv/eWbSLQvOK7pEk6b44SYr9lZqiL6RkxF5Ky4M4 ElbyzbefPXD35SDeUvNb768I578YxEw1fza5vGNyeRCSmjdOSoo3Fgaxs1HJ 94kLgshXc/or/WmvzIuer+azQ1/9r21mEHXblOw+Xi/N8AfhVrNFrCC+blBy 7PL+tCDWqbn7+UeiRxCL1JzwQGwF8Zia89vGRY8goOZtc0Ya5ozImKvm/1yN LRnL1OysOh89ZHys5j8ZTr1mOCXjNHv2yLCo/j/GPGEZb6j5SMxTI2OgkTzv yZgaJs/rMp4Ok6dSxpoweSpkdKjZFfP8VsaVMHmeljG/ifuRsaKJ+5ERaeJ+ ZLiblSzqeUDGoWbuR0ZZC/cDmD/ifoDJ28lzHkjcwf0AF9uUbBX9AN/vIk8Y qN9NnhrgJ3u4HyBhD/cD9KrnN4p+ALua/yv6AX6xi/sB7m/jfoC6Fu4HmNLM /QDXwtwPkBXm+QG6G7kfoFPNT9TemFV7IwC9ev43g7EVwDk1vxC7XXcAP1Xf b7y4QQALW5VcLFYAX+1U8g8NsQ8Y+LG/d2L1OgN4U/18yWIFcFDNewvujR4B rNrFHj/OqdefER4/jqn3Fx+v24956vuPEx4/qsPs8eMf6nzfFh4/KtX5F9vt 9OPwh0rWCY8ff/mQPX7cr57/pPD4kLCNPT40NHI/Phxt4n58wG72+NCzh/vx Yelu9vhgaGWP78fnj+Lx4bsaJc8SHi+uvcseLyYsZ48X8hL2ePE7nZJLhMeL tp8reUR4vPhkRCKPF69dlsjjxZRBiTxe/L5fov3yoOZziTwevHlYIo8H8iGJ PB5IRyTqx4POoxL148GTX7DHg3U97Im+Xy97PCiJsMeNmxH2uDGjjz1uPNXH HjcqI+xxIz/CHjeqI+xxw65erxceNwzH2OPGn4+zxwX7Cfa4kDfAHhd2nWSP C6nfsscFxwWJ9suFVy8p+V3hceG2ul/K98uFbVfZ48Ib19njxNZb7HHi3yPs caJklD1OXJzI8+xE2SSeZycKp8SRx4m+qTzPTrQk8Tw7cXsaf78c2K/leXbg SjLPswNrdDzPDrh17HFgmo7n2QGjjr9fDpTr+PnjQL+OPQ4U6fn5Y4c+hT12 TEhljx2aNPbYUZDJHjtasrgfO741xNHz0A4ph/uJ3t/IHjvuMbHHhnMm9tjQ amaPDUUW9tiw0MYeG7LtcfQ8tGGFgz02zHFxPzZs8rDHhgI/75cVDTJ7rCjM Y48V9bPYY8XKBeyxwvEb3i8r8hfxfllxvYj7sWKkVMn7hMeKl8ri6HloQeES 9lhwuII9FmwKsceCsyH2WPBNiD0WDIbYY8HpEHss+DLE/VjQE+L9MqMzxB4z 9ofYY0brGI8Zy8d4zCgO8fyY4RvjMWO0gj1m7KhgjxkzK9hjwrEx/ZiQt4Q9 JjSWs8eE2YvZY0Ltc9yPCROfY48Jm0t5fkwIlrLHhPGl7DHiYgl7jDhfwh4j 7pSwx4jeUvYYMXeMx4j5i9ljxJdl3E80L2GPEfOWKvl9/9A6/1AO5r6o5AN/ i60c9LykZHG7qhx0VSr5XnGDHJxdreTentjKxsIqJd8QAxnNa5WcJH6QZePM eiXn5cZWNi5sVHJZR+wfjmws3azk9cJjwPIt7DFgUq2SLwiPAZl1Sp4gPAZU 17MnC+fq2ZOFO/XsycLVevZkYbeay4UnC0/Ucz+Z2FvHnkzcGuPJRHwtezIx ezN7piOnmj3RvEnJYrufn445ah+PCc90vP0Be6ZjaIOS1wlPBgo3sCcDd9ez JwN717MnA/PVLDg96ahS87DwpOOFDexJh6R6BCc3HbZq3q90PLSF+0nD1jH9 pCHSwJ40NDfz/KRh/gHuJxXdHdxPKpZ1sScViz7n/UrF673cTyrO97EnBX84 zp4UzO5nTwoW9LMnBZo+9uhhjLBHj7penh89ynrZo8d7Yzx6PBhhjw7DEfbo kH2MPTp0Hef90mHlKd6vZFweuvzDzjtafJZ4fc0XdckYSGy81H5Li1+N//s7 vcuic1NqOZpzRYtVaw2H+n+ZDM/A2q2jp7V46uAM09fZyfikoLMkp0uLg6tH T16cGH0OxB/Rt2/XoutGwb6b17TwnNgy0FqlxeLRkr6fndLi8b/mVd4t0+Kj 5gc1SR1anGxvT2jN1WL1cHGzbYcWWwo1gfpGDfa3ZiXkl2ixIPHSmaSHNBg3 7dXb8WlaTDqQduFxzTSU5eY/k/edBs8Uzb5WnPMorjza6Yvfp8Ga7MC/Nv46 CStbP61ZsEqD7VPutA9ufATeYefLlmc1+FizaoVt+GFM/D73xAdODRpnDWbU FT+Mkc3/bFmZqMHytaOfJg1PhSSWBv8HWIJO2w== "]], 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{6.737418070410627, 8.}, {6.737418070411195, 7.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{6.737418070411195, 7.}, {8.00000000021646, 6.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{8.00000000021646, 6.}, {10.000000000239027`, 5.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{10.000000000239027`, 5.}, {10.353993311167812`, 4.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{10.353993311167812`, 4.}, {10.353993311167471`, 3.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{10.353993311167471`, 3.}, {11.251489020744827`, 2.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{11.251489020744827`, 2.}, {12.251489020745112`, 1.}}, 0.3810409891907867]}, {RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], ArrowBox[{{12.251489020745112`, 1.}, {12.883315868909506`, 0.}}, 0.3810409891907867]}}, {Hue[0.6, 0.2, 0.8], EdgeForm[{GrayLevel[0], Opacity[0.7]}], TagBox[ TooltipBox[ {RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[None], PolygonBox[{{-0.3586266340426279, 39.88045791566612}, {0., 39.64137336595737}, {0.3586266340426279, 39.88045791566612}, { 0.3586266340426279, 40.35862663404263}, {-0.3586266340426279, 40.35862663404263}, {-0.3586266340426279, 39.88045791566612}}]}, "\"Axiom 1\"", TooltipStyle->"TextStyling"], Annotation[#, "Axiom 1", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[None], PolygonBox[{{-13.615398933516053`, 38.88045791566612}, {-13.256772299473425`, 38.64137336595737}, {-12.898145665430798`, 38.88045791566612}, {-12.898145665430798`, 39.35862663404263}, {-13.615398933516053`, 39.35862663404263}, {-13.615398933516053`, 38.88045791566612}}]}, "\"Axiom 2\"", TooltipStyle->"TextStyling"], Annotation[#, "Axiom 2", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[None], PolygonBox[{{-22.358626634833094`, 39.88045791566612}, {-22.000000000790465`, 39.64137336595737}, {-21.641373366747835`, 39.88045791566612}, {-21.641373366747835`, 40.35862663404263}, {-22.358626634833094`, 40.35862663404263}, {-22.358626634833094`, 39.88045791566612}}]}, "\"Axiom 3\"", TooltipStyle->"TextStyling"], Annotation[#, "Axiom 3", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[None], PolygonBox[{{-24.35862663481496, 37.88045791566612}, {-24.00000000077233, 37.64137336595737}, {-23.641373366729702`, 37.88045791566612}, {-23.641373366729702`, 38.35862663404263}, {-24.35862663481496, 38.35862663404263}, {-24.35862663481496, 37.88045791566612}}]}, "\"Axiom 4\"", TooltipStyle->"TextStyling"], Annotation[#, "Axiom 4", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[None], PolygonBox[{{-7.3586266339960735`, 38.88045791566612}, {-6.999999999953445, 38.64137336595737}, {-6.641373365910817, 38.88045791566612}, {-6.641373365910817, 39.35862663404263}, {-7.3586266339960735`, 39.35862663404263}, {-7.3586266339960735`, 38.88045791566612}}]}, "\"Axiom 5\"", TooltipStyle->"TextStyling"], Annotation[#, "Axiom 5", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[None], PolygonBox[{{5.17024637752072, 38.88045791566612}, { 5.528873011563348, 38.64137336595737}, {5.887499645605977, 38.88045791566612}, {5.887499645605977, 39.35862663404263}, { 5.17024637752072, 39.35862663404263}, {5.17024637752072, 38.88045791566612}}]}, "\"Axiom 6\"", TooltipStyle->"TextStyling"], Annotation[#, "Axiom 6", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[146, 255], Rational[10, 17], 0], EdgeForm[None], PolygonBox[{{11.999999999375575`, 38.57412953843092}, { 12.425870460944658`, 39.}, {11.999999999375575`, 39.42587046156908}, {11.574129537806492`, 39.}, { 11.999999999375575`, 38.57412953843092}}]}, "\"Hypothesis 1\"", TooltipStyle->"TextStyling"], Annotation[#, "Hypothesis 1", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-1.8733706994324848`, 39.42787092676233}, {-2.2992411610015675`, 38.69024377802604}, {-1.447500237863402, 38.69024377802604}, {-1.8733706994324848`, 39.42787092676233}}]}, "\"Critical Pair Lemma 1\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 1", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-19.000000000792, 37.42787092676233}, {-19.425870462361083`, 36.69024377802604}, {-18.574129539222916`, 36.69024377802604}, {-19.000000000792, 37.42787092676233}}]}, "\"Critical Pair Lemma 2\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 2", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-26.000000000707814`, 37.42787092676233}, {-26.425870462276897`, 36.69024377802604}, {-25.57412953913873, 36.69024377802604}, {-26.000000000707814`, 37.42787092676233}}]}, "\"Critical Pair Lemma 3\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 3", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-1.7053025658242404`*^-13, 38.42787092676233}, {-0.4258704615692533, 37.69024377802604}, { 0.42587046156891223`, 37.69024377802604}, {-1.7053025658242404`*^-13, 38.42787092676233}}]}, "\"Critical Pair Lemma 4\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 4", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-8.256772299473198, 38.42787092676233}, {-8.682642761042281, 37.69024377802604}, {-7.830901837904115, 37.69024377802604}, {-8.256772299473198, 38.42787092676233}}]}, "\"Critical Pair Lemma 5\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 5", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-6.999999999952308, 38.42787092676233}, {-7.4258704615213915`, 37.69024377802604}, {-6.574129538383225, 37.69024377802604}, {-6.999999999952308, 38.42787092676233}}]}, "\"Critical Pair Lemma 6\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 6", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-3.000000000019554, 38.42787092676233}, {-3.425870461588637, 37.69024377802604}, {-2.5741295384504714`, 37.69024377802604}, {-3.000000000019554, 38.42787092676233}}]}, "\"Critical Pair Lemma 7\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 7", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{6.999999999384613, 38.42787092676233}, { 6.57412953781553, 37.69024377802604}, {7.425870460953696, 37.69024377802604}, {6.999999999384613, 38.42787092676233}}]}, "\"Critical Pair Lemma 8\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 8", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-10.999999999891713`, 37.42787092676233}, {-11.425870461460796`, 36.69024377802604}, {-10.57412953832263, 36.69024377802604}, {-10.999999999891713`, 37.42787092676233}}]}, "\"Critical Pair Lemma 9\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 9", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-7.999999999973568, 37.42787092676233}, {-8.425870461542651, 36.69024377802604}, {-7.574129538404485, 36.69024377802604}, {-7.999999999973568, 37.42787092676233}}]}, "\"Critical Pair Lemma 10\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 10", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-5.00000000000847, 36.42787092676233}, {-5.425870461577553, 35.69024377802604}, {-4.5741295384393865`, 35.69024377802604}, {-5.00000000000847, 36.42787092676233}}]}, "\"Critical Pair Lemma 11\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 11", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{6.999999999384954, 37.42787092676233}, { 6.574129537815871, 36.69024377802604}, {7.425870460954037, 36.69024377802604}, {6.999999999384954, 37.42787092676233}}]}, "\"Critical Pair Lemma 12\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 12", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-3.999999999994145, 35.42787092676233}, {-4.425870461563228, 34.69024377802604}, {-3.5741295384250624`, 34.69024377802604}, {-3.999999999994145, 35.42787092676233}}]}, "\"Critical Pair Lemma 13\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 13", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-4.000000000017792, 34.}, 0.3810409891907867]}, "\"Substitution Lemma 1\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 1", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-3.586632052708353, 33.}, 0.3810409891907867]}, "\"Substitution Lemma 2\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 2", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-3.586632052711707, 32.}, 0.3810409891907867]}, "\"Substitution Lemma 3\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 3", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-8.000000000371415, 31.427870926762335`}, {-8.425870461940498, 30.690243778026037`}, {-7.574129538802332, 30.690243778026037`}, {-8.000000000371415, 31.427870926762335`}}]}, "\"Critical Pair Lemma 14\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 14", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-2.000000000302009, 31.427870926762335`}, {-2.425870461871092, 30.690243778026037`}, {-1.5741295387329264`, 30.690243778026037`}, {-2.000000000302009, 31.427870926762335`}}]}, "\"Critical Pair Lemma 15\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 15", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-1.0000000003634, 23.427870926762335`}, {-1.4258704619324827`, 22.690243778026037`}, {-0.5741295387943173, 22.690243778026037`}, {-1.0000000003634, 23.427870926762335`}}]}, "\"Critical Pair Lemma 16\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 16", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-7.0000000004556, 30.427870926762335`}, {-7.425870462024683, 29.690243778026037`}, {-6.574129538886517, 29.690243778026037`}, {-7.0000000004556, 30.427870926762335`}}]}, "\"Critical Pair Lemma 17\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 17", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-7.0000000004630465, 29.}, 0.3810409891907867]}, "\"Substitution Lemma 4\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 4", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-15.27349263178047, 28.427870926762335`}, {-15.699363093349554`, 27.690243778026037`}, {-14.847622170211388`, 27.690243778026037`}, {-15.27349263178047, 28.427870926762335`}}]}, "\"Critical Pair Lemma 18\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 18", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-16.273492631788542, 27.}, 0.3810409891907867]}, "\"Substitution Lemma 5\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 5", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-8.000000000398302, 30.427870926762335`}, {-8.425870461967385, 29.690243778026037`}, {-7.574129538829219, 29.690243778026037`}, {-8.000000000398302, 30.427870926762335`}}]}, "\"Critical Pair Lemma 19\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 19", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-9.000000000461341, 29.}, 0.3810409891907867]}, "\"Substitution Lemma 6\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 6", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-9.273492631703903, 28.}, 0.3810409891907867]}, "\"Substitution Lemma 7\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 7", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-9.27349263174608, 27.}, 0.3810409891907867]}, "\"Substitution Lemma 8\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 8", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-18.273492631795932`, 26.427870926762335`}, {-18.699363093365015`, 25.690243778026037`}, {-17.84762217022685, 25.690243778026037`}, {-18.273492631795932`, 26.427870926762335`}}]}, "\"Critical Pair Lemma 20\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 20", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-18.273492631799797, 25.}, 0.3810409891907867]}, "\"Substitution Lemma 9\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 9", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-20.27349263179906, 26.427870926762335`}, {-20.69936309336814, 25.690243778026037`}, {-19.847622170229975`, 25.690243778026037`}, {-20.27349263179906, 26.427870926762335`}}]}, "\"Critical Pair Lemma 21\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 21", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-22.27349263181185, 25.}, 0.3810409891907867]}, "\"Substitution Lemma 10\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 10", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-16.273492631796955`, 26.427870926762335`}, {-16.69936309336604, 25.690243778026037`}, {-15.847622170227872`, 25.690243778026037`}, {-16.273492631796955`, 26.427870926762335`}}]}, "\"Critical Pair Lemma 22\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 22", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-15.273492631780982, 25.}, 0.3810409891907867]}, "\"Substitution Lemma 11\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 11", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-14.273492631779277`, 24.427870926762335`}, {-14.69936309334836, 23.690243778026037`}, {-13.847622170210194`, 23.690243778026037`}, {-14.273492631779277`, 24.427870926762335`}}]}, "\"Critical Pair Lemma 23\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 23", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-16.27349263177848, 24.427870926762335`}, {-16.699363093347564`, 23.690243778026037`}, {-15.847622170209398`, 23.690243778026037`}, {-16.27349263177848, 24.427870926762335`}}]}, "\"Critical Pair Lemma 24\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 24", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-6.0000000002648335`, 24.427870926762335`}, {-6.425870461833917, 23.690243778026037`}, {-5.57412953869575, 23.690243778026037`}, {-6.0000000002648335`, 24.427870926762335`}}]}, "\"Critical Pair Lemma 25\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 25", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-12.273492631611077`, 23.427870926762335`}, {-12.69936309318016, 22.690243778026037`}, {-11.847622170041994`, 22.690243778026037`}, {-12.273492631611077`, 23.427870926762335`}}]}, "\"Critical Pair Lemma 26\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 26", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-5.470951125657507, 23.}, 0.3810409891907867]}, "\"Substitution Lemma 12\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 12", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-7.677035030559011, 22.427870926762335`}, {-8.102905492128095, 21.690243778026037`}, {-7.251164568989928, 21.690243778026037`}, {-7.677035030559011, 22.427870926762335`}}]}, "\"Critical Pair Lemma 27\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 27", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-8.873666583657155, 21.}, 0.3810409891907867]}, "\"Substitution Lemma 13\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 13", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-1.0000000003856826`, 22.427870926762335`}, {-1.4258704619547653`, 21.690243778026037`}, {-0.5741295388165999, 21.690243778026037`}, {-1.0000000003856826`, 22.427870926762335`}}]}, "\"Critical Pair Lemma 28\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 28", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-1.0000000003947775, 21.}, 0.3810409891907867]}, "\"Substitution Lemma 14\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 14", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-6.180894323932989, 22.427870926762335`}, {-6.606764785502072, 21.690243778026037`}, {-5.755023862363906, 21.690243778026037`}, {-6.180894323932989, 22.427870926762335`}}]}, "\"Critical Pair Lemma 29\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 29", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-6.180894323932989, 21.}, 0.3810409891907867]}, "\"Substitution Lemma 15\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 15", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{2.0551637700374954, 20.}, 0.3810409891907867]}, "\"Substitution Lemma 16\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 16", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-18.273492631801275`, 24.427870926762335`}, {-18.69936309337036, 23.690243778026037`}, {-17.847622170232192`, 23.690243778026037`}, {-18.273492631801275`, 24.427870926762335`}}]}, "\"Critical Pair Lemma 30\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 30", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-16.27349263177979, 23.}, 0.3810409891907867]}, "\"Substitution Lemma 17\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 17", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-16.27349263178064, 22.427870926762335`}, {-16.699363093349724`, 21.690243778026037`}, {-15.847622170211558`, 21.690243778026037`}, {-16.27349263178064, 22.427870926762335`}}]}, "\"Critical Pair Lemma 31\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 31", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-14.273492631780016`, 22.427870926762335`}, {-14.699363093349099`, 21.690243778026037`}, {-13.847622170210933`, 21.690243778026037`}, {-14.273492631780016`, 22.427870926762335`}}]}, "\"Critical Pair Lemma 32\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 32", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-11.561691732461668`, 21.427870926762335`}, {-11.987562194030751`, 20.690243778026037`}, {-11.135821270892585`, 20.690243778026037`}, {-11.561691732461668`, 21.427870926762335`}}]}, "\"Critical Pair Lemma 33\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 33", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-15.44021963792244, 21.427870926762335`}, {-15.866090099491522`, 20.690243778026037`}, {-15.014349176353356`, 20.690243778026037`}, {-15.44021963792244, 21.427870926762335`}}]}, "\"Critical Pair Lemma 34\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 34", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-11.56169173246326, 20.427870926762335`}, {-11.987562194032343`, 19.690243778026037`}, {-11.135821270894176`, 19.690243778026037`}, {-11.56169173246326, 20.427870926762335`}}]}, "\"Critical Pair Lemma 35\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 35", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-2.925516824096235, 20.}, 0.3810409891907867]}, "\"Substitution Lemma 18\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 18", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-15.440219637926702`, 20.427870926762335`}, {-15.866090099495786`, 19.690243778026037`}, {-15.01434917635762, 19.690243778026037`}, {-15.440219637926702`, 20.427870926762335`}}]}, "\"Critical Pair Lemma 36\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 36", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-11.56169173246252, 19.}, 0.3810409891907867]}, "\"Substitution Lemma 19\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 19", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-11.561691732463885`, 18.427870926762335`}, {-11.987562194032968`, 17.690243778026037`}, {-11.135821270894802`, 17.690243778026037`}, {-11.561691732463885`, 18.427870926762335`}}]}, "\"Critical Pair Lemma 37\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 37", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-8.873666583667045, 17.}, 0.3810409891907867]}, "\"Substitution Lemma 20\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 20", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-3.9255168241054434`, 16.427870926762335`}, {-4.351387285674527, 15.690243778026037`}, {-3.4996463625363607`, 15.690243778026037`}, {-3.9255168241054434`, 16.427870926762335`}}]}, "\"Critical Pair Lemma 38\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 38", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-3.925516824109593, 15.}, 0.3810409891907867]}, "\"Substitution Lemma 21\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 21", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-3.9255168241100478`, 14.427870926762335`}, {-4.351387285679131, 13.690243778026037`}, {-3.499646362540965, 13.690243778026037`}, {-3.9255168241100478`, 14.427870926762335`}}]}, "\"Critical Pair Lemma 39\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 39", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{-2.925516824096576, 13.}, 0.3810409891907867]}, "\"Substitution Lemma 22\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 22", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{-1.9255168240966327`, 12.427870926762335`}, {-2.3513872856657154`, 11.690243778026037`}, {-1.49964636252755, 11.690243778026037`}, {-1.9255168240966327`, 12.427870926762335`}}]}, "\"Critical Pair Lemma 40\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 40", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{2.055163770040224, 11.}, 0.3810409891907867]}, "\"Substitution Lemma 23\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 23", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{4.999999999958504, 10.}, 0.3810409891907867]}, "\"Substitution Lemma 24\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 24", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[None], PolygonBox[{{5.1619887228560515`, 9.427870926762335}, { 4.736118261286968, 8.690243778026037}, {5.587859184425135, 8.690243778026037}, {5.1619887228560515`, 9.427870926762335}}]}, "\"Critical Pair Lemma 41\"", TooltipStyle->"TextStyling"], Annotation[#, "Critical Pair Lemma 41", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{11.999999999376143, 38.}, 0.3810409891907867]}, "\"Substitution Lemma 25\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 25", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{9.000000000192813, 37.}, 0.3810409891907867]}, "\"Substitution Lemma 26\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 26", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{6.737418070410627, 8.}, 0.3810409891907867]}, "\"Substitution Lemma 27\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 27", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{6.737418070411195, 7.}, 0.3810409891907867]}, "\"Substitution Lemma 28\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 28", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{8.00000000021646, 6.}, 0.3810409891907867]}, "\"Substitution Lemma 29\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 29", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{10.000000000239027, 5.}, 0.3810409891907867]}, "\"Substitution Lemma 30\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 30", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{10.353993311167812, 4.}, 0.3810409891907867]}, "\"Substitution Lemma 31\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 31", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{10.353993311167471, 3.}, 0.3810409891907867]}, "\"Substitution Lemma 32\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 32", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{11.251489020744827, 2.}, 0.3810409891907867]}, "\"Substitution Lemma 33\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 33", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[None], DiskBox[{12.251489020745112, 1.}, 0.3810409891907867]}, "\"Substitution Lemma 34\"", TooltipStyle->"TextStyling"], Annotation[#, "Substitution Lemma 34", "Tooltip"]& ], TagBox[ TooltipBox[ {RGBColor[ Rational[13, 15], Rational[1, 15], 0], EdgeForm[None], RectangleBox[{12.547103208974047, -0.33621265993545824}, \ {13.219528528844965, 0.33621265993545824}]}, "\"Conclusion 1\"", TooltipStyle->"TextStyling"], Annotation[#, "Conclusion 1", "Tooltip"]& ]}}], MouseAppearanceTag["NetworkGraphics"]], AllowKernelInitialization->False]], DefaultBaseStyle->{ "NetworkGraphics", FrontEnd`GraphicsHighlightColor -> Hue[0.8, 1., 0.6]}, FormatType->TraditionalForm, FrameTicks->None], Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], Graph[{"Axiom 1", "Axiom 2", "Axiom 3", "Axiom 4", "Axiom 5", "Axiom 6", "Hypothesis 1", "Critical Pair Lemma 1", "Critical Pair Lemma 2", "Critical Pair Lemma 3", "Critical Pair Lemma 4", "Critical Pair Lemma 5", "Critical Pair Lemma 6", "Critical Pair Lemma 7", "Critical Pair Lemma 8", "Critical Pair Lemma 9", "Critical Pair Lemma 10", "Critical Pair Lemma 11", "Critical Pair Lemma 12", "Critical Pair Lemma 13", "Substitution Lemma 1", "Substitution Lemma 2", "Substitution Lemma 3", "Critical Pair Lemma 14", "Critical Pair Lemma 15", "Critical Pair Lemma 16", "Critical Pair Lemma 17", "Substitution Lemma 4", "Critical Pair Lemma 18", "Substitution Lemma 5", "Critical Pair Lemma 19", "Substitution Lemma 6", "Substitution Lemma 7", "Substitution Lemma 8", "Critical Pair Lemma 20", "Substitution Lemma 9", "Critical Pair Lemma 21", "Substitution Lemma 10", "Critical Pair Lemma 22", "Substitution Lemma 11", "Critical Pair Lemma 23", "Critical Pair Lemma 24", "Critical Pair Lemma 25", "Critical Pair Lemma 26", "Substitution Lemma 12", "Critical Pair Lemma 27", "Substitution Lemma 13", "Critical Pair Lemma 28", "Substitution Lemma 14", "Critical Pair Lemma 29", "Substitution Lemma 15", "Substitution Lemma 16", "Critical Pair Lemma 30", "Substitution Lemma 17", "Critical Pair Lemma 31", "Critical Pair Lemma 32", "Critical Pair Lemma 33", "Critical Pair Lemma 34", "Critical Pair Lemma 35", "Substitution Lemma 18", "Critical Pair Lemma 36", "Substitution Lemma 19", "Critical Pair Lemma 37", "Substitution Lemma 20", "Critical Pair Lemma 38", "Substitution Lemma 21", "Critical Pair Lemma 39", "Substitution Lemma 22", "Critical Pair Lemma 40", "Substitution Lemma 23", "Substitution Lemma 24", "Critical Pair Lemma 41", "Substitution Lemma 25", "Substitution Lemma 26", "Substitution Lemma 27", "Substitution Lemma 28", "Substitution Lemma 29", "Substitution Lemma 30", "Substitution Lemma 31", "Substitution Lemma 32", "Substitution Lemma 33", "Substitution Lemma 34", "Conclusion 1"}, {CompressedData[" 1:eJwVxWd6gjAAAFBNQoqCEVxhuMCFCG4RBXErbsUbeIFep8dt++N9T/t8Rx8Q i8V+/vwP2TiLEiCBkjDJcHEO84BnUjjFEoaANJvmBSQQEYhCRsyks3yWy2Vy uTzI5wu4UKAiFSQqEZnKnEIVokqqWiRFplQslcpMWarIlUqVVquapGk61VFN r9XqqI4aeqPRRM1yK9FqGcAw2nzbMKEpdYyOYJlWx4a23bW73V67p/Ttfn8A BsrQGg5HYDQY43F9kpxMHNNxpnDquNidzvDMnZvzmWd4Ix/78wVcLAIvCJZw 2VstV2S9Wq83YNPcbrbbnb+T97v9/jA+HI7y8RjS8OuET6czPp8v4eVyTV2v t+ztdsf3+wM/Hs/w+Xzh1yuiUfSOv38B2IAunA== "], Null}, { EdgeStyle -> { DirectedEdge["Critical Pair Lemma 29", "Substitution Lemma 15"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 3", "Critical Pair Lemma 37"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 2", "Substitution Lemma 3"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 16", "Critical Pair Lemma 29"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 22", "Critical Pair Lemma 40"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 7", "Critical Pair Lemma 10"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 15", "Substitution Lemma 18"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 25", "Substitution Lemma 12"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 13", "Substitution Lemma 1"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 34", "Conclusion 1"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 8", "Critical Pair Lemma 20"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 1", "Substitution Lemma 2"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 24", "Substitution Lemma 17"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 25", "Substitution Lemma 26"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 5", "Critical Pair Lemma 4"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 26"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 21", "Critical Pair Lemma 39"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 2", "Critical Pair Lemma 22"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 5", "Critical Pair Lemma 22"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Substitution Lemma 8"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Substitution Lemma 10"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 3", "Critical Pair Lemma 31"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Critical Pair Lemma 14"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 5", "Critical Pair Lemma 18"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Critical Pair Lemma 6"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 40", "Substitution Lemma 23"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 14", "Critical Pair Lemma 25"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Substitution Lemma 14"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 30"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Substitution Lemma 34"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 16", "Substitution Lemma 23"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Hypothesis 1", "Substitution Lemma 25"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 24", "Critical Pair Lemma 26"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 28", "Substitution Lemma 29"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 39", "Substitution Lemma 22"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 5", "Critical Pair Lemma 12"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 11", "Critical Pair Lemma 23"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 10", "Substitution Lemma 3"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 34", "Critical Pair Lemma 36"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 13", "Substitution Lemma 20"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 38", "Substitution Lemma 21"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 11", "Critical Pair Lemma 25"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Substitution Lemma 6"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 37", "Substitution Lemma 20"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 31", "Substitution Lemma 32"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 12", "Critical Pair Lemma 27"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 23", "Substitution Lemma 13"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 16"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Critical Pair Lemma 21"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 29", "Substitution Lemma 30"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 33", "Substitution Lemma 34"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 3", "Critical Pair Lemma 1"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 5", "Critical Pair Lemma 9"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 7", "Critical Pair Lemma 17"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 11", "Critical Pair Lemma 24"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Substitution Lemma 11"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 30", "Substitution Lemma 17"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 4", "Critical Pair Lemma 13"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 5", "Critical Pair Lemma 23"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 8", "Critical Pair Lemma 12"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 15", "Substitution Lemma 24"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 11", "Critical Pair Lemma 35"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 41", "Substitution Lemma 27"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Critical Pair Lemma 5"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 28", "Substitution Lemma 14"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 35", "Substitution Lemma 19"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 14", "Critical Pair Lemma 17"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 27", "Substitution Lemma 28"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 3", "Substitution Lemma 12"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 20", "Substitution Lemma 9"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 1", "Critical Pair Lemma 4"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 1", "Critical Pair Lemma 7"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Critical Pair Lemma 10"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 5", "Critical Pair Lemma 7"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 26", "Substitution Lemma 27"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 3", "Critical Pair Lemma 15"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 9", "Critical Pair Lemma 14"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 17", "Critical Pair Lemma 32"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Substitution Lemma 1"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 8", "Critical Pair Lemma 21"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 24", "Critical Pair Lemma 41"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 19", "Substitution Lemma 6"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 9", "Critical Pair Lemma 11"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Critical Pair Lemma 41"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Critical Pair Lemma 5"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 20", "Critical Pair Lemma 38"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 3", "Critical Pair Lemma 24"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 11", "Critical Pair Lemma 13"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 12", "Substitution Lemma 29"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 26", "Critical Pair Lemma 29"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 31"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Critical Pair Lemma 3"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Critical Pair Lemma 9"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 12", "Critical Pair Lemma 28"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 15", "Critical Pair Lemma 40"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 14", "Substitution Lemma 16"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 6", "Critical Pair Lemma 33"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Critical Pair Lemma 2"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 7", "Critical Pair Lemma 15"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 6", "Substitution Lemma 28"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 1", "Conclusion 1"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 25"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Substitution Lemma 21"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 4", "Critical Pair Lemma 18"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Critical Pair Lemma 20"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 36", "Substitution Lemma 19"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 10", "Critical Pair Lemma 11"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 27", "Substitution Lemma 13"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 3", "Critical Pair Lemma 3"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 5", "Substitution Lemma 5"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 14", "Substitution Lemma 7"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 2"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 5", "Critical Pair Lemma 6"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Substitution Lemma 9"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Substitution Lemma 15"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 7", "Critical Pair Lemma 38"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 4", "Critical Pair Lemma 2"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 6", "Substitution Lemma 7"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 7", "Substitution Lemma 8"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 1", "Critical Pair Lemma 1"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 21", "Substitution Lemma 10"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 33", "Critical Pair Lemma 35"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 3", "Critical Pair Lemma 16"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 18", "Substitution Lemma 22"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 4", "Critical Pair Lemma 16"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 33"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 19", "Critical Pair Lemma 37"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 18", "Substitution Lemma 5"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 9", "Critical Pair Lemma 30"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 2", "Critical Pair Lemma 8"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 14", "Critical Pair Lemma 19"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 6", "Substitution Lemma 18"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 30", "Substitution Lemma 31"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 31", "Critical Pair Lemma 33"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 22", "Substitution Lemma 11"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Critical Pair Lemma 3", "Critical Pair Lemma 30"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 10", "Critical Pair Lemma 39"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Substitution Lemma 23", "Substitution Lemma 24"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 32", "Substitution Lemma 33"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Substitution Lemma 17", "Critical Pair Lemma 31"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 1", "Critical Pair Lemma 8"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 7", "Substitution Lemma 4"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Axiom 3", "Critical Pair Lemma 36"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 15", "Critical Pair Lemma 19"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 24", "Critical Pair Lemma 34"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 32", "Critical Pair Lemma 34"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 17", "Substitution Lemma 4"] -> RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]], DirectedEdge["Axiom 6", "Critical Pair Lemma 32"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 41", "Substitution Lemma 32"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 16", "Critical Pair Lemma 28"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]], DirectedEdge["Critical Pair Lemma 9", "Critical Pair Lemma 26"] -> Directive[ Dashing[{Small, Small}], RGBColor[ Rational[167, 255], Rational[167, 255], Rational[167, 255]]]}, GraphLayout -> "LayeredDigraphEmbedding", Properties -> { "Substitution Lemma 4" -> {Tooltip -> "Substitution Lemma 4"}, "Substitution Lemma 24" -> {Tooltip -> "Substitution Lemma 24"}, "Axiom 3" -> {Tooltip -> "Axiom 3"}, "Critical Pair Lemma 11" -> {Tooltip -> "Critical Pair Lemma 11"}, "Substitution Lemma 18" -> {Tooltip -> "Substitution Lemma 18"}, "Critical Pair Lemma 29" -> {Tooltip -> "Critical Pair Lemma 29"}, "Critical Pair Lemma 37" -> {Tooltip -> "Critical Pair Lemma 37"}, "Substitution Lemma 17" -> {Tooltip -> "Substitution Lemma 17"}, "Critical Pair Lemma 21" -> {Tooltip -> "Critical Pair Lemma 21"}, "Substitution Lemma 6" -> {Tooltip -> "Substitution Lemma 6"}, "Critical Pair Lemma 40" -> {Tooltip -> "Critical Pair Lemma 40"}, "Critical Pair Lemma 30" -> {Tooltip -> "Critical Pair Lemma 30"}, "Axiom 1" -> {Tooltip -> "Axiom 1"}, "Substitution Lemma 27" -> {Tooltip -> "Substitution Lemma 27"}, "Substitution Lemma 3" -> {Tooltip -> "Substitution Lemma 3"}, "Substitution Lemma 9" -> {Tooltip -> "Substitution Lemma 9"}, "Critical Pair Lemma 15" -> {Tooltip -> "Critical Pair Lemma 15"}, "Critical Pair Lemma 7" -> {Tooltip -> "Critical Pair Lemma 7"}, "Substitution Lemma 19" -> {Tooltip -> "Substitution Lemma 19"}, "Critical Pair Lemma 14" -> {Tooltip -> "Critical Pair Lemma 14"}, "Substitution Lemma 34" -> {Tooltip -> "Substitution Lemma 34"}, "Critical Pair Lemma 22" -> {Tooltip -> "Critical Pair Lemma 22"}, "Critical Pair Lemma 6" -> {Tooltip -> "Critical Pair Lemma 6"}, "Critical Pair Lemma 3" -> {Tooltip -> "Critical Pair Lemma 3"}, "Substitution Lemma 26" -> {Tooltip -> "Substitution Lemma 26"}, "Substitution Lemma 33" -> {Tooltip -> "Substitution Lemma 33"}, "Critical Pair Lemma 1" -> {Tooltip -> "Critical Pair Lemma 1"}, "Critical Pair Lemma 16" -> {Tooltip -> "Critical Pair Lemma 16"}, "Critical Pair Lemma 27" -> {Tooltip -> "Critical Pair Lemma 27"}, "Critical Pair Lemma 26" -> {Tooltip -> "Critical Pair Lemma 26"}, "Substitution Lemma 21" -> {Tooltip -> "Substitution Lemma 21"}, "Substitution Lemma 7" -> {Tooltip -> "Substitution Lemma 7"}, "Substitution Lemma 11" -> {Tooltip -> "Substitution Lemma 11"}, "Critical Pair Lemma 5" -> {Tooltip -> "Critical Pair Lemma 5"}, "Critical Pair Lemma 23" -> {Tooltip -> "Critical Pair Lemma 23"}, "Substitution Lemma 2" -> {Tooltip -> "Substitution Lemma 2"}, "Substitution Lemma 13" -> {Tooltip -> "Substitution Lemma 13"}, "Substitution Lemma 31" -> {Tooltip -> "Substitution Lemma 31"}, "Critical Pair Lemma 10" -> {Tooltip -> "Critical Pair Lemma 10"}, "Axiom 2" -> {Tooltip -> "Axiom 2"}, "Substitution Lemma 1" -> {Tooltip -> "Substitution Lemma 1"}, "Critical Pair Lemma 28" -> {Tooltip -> "Critical Pair Lemma 28"}, "Critical Pair Lemma 31" -> {Tooltip -> "Critical Pair Lemma 31"}, "Critical Pair Lemma 17" -> {Tooltip -> "Critical Pair Lemma 17"}, "Critical Pair Lemma 33" -> {Tooltip -> "Critical Pair Lemma 33"}, "Substitution Lemma 20" -> {Tooltip -> "Substitution Lemma 20"}, "Critical Pair Lemma 18" -> {Tooltip -> "Critical Pair Lemma 18"}, "Critical Pair Lemma 32" -> {Tooltip -> "Critical Pair Lemma 32"}, "Axiom 4" -> {Tooltip -> "Axiom 4"}, "Substitution Lemma 22" -> {Tooltip -> "Substitution Lemma 22"}, "Critical Pair Lemma 19" -> {Tooltip -> "Critical Pair Lemma 19"}, "Substitution Lemma 5" -> {Tooltip -> "Substitution Lemma 5"}, "Critical Pair Lemma 24" -> {Tooltip -> "Critical Pair Lemma 24"}, "Critical Pair Lemma 36" -> {Tooltip -> "Critical Pair Lemma 36"}, "Substitution Lemma 14" -> {Tooltip -> "Substitution Lemma 14"}, "Critical Pair Lemma 38" -> {Tooltip -> "Critical Pair Lemma 38"}, "Substitution Lemma 30" -> {Tooltip -> "Substitution Lemma 30"}, "Conclusion 1" -> {Tooltip -> "Conclusion 1"}, "Substitution Lemma 25" -> {Tooltip -> "Substitution Lemma 25"}, "Critical Pair Lemma 8" -> {Tooltip -> "Critical Pair Lemma 8"}, "Critical Pair Lemma 20" -> {Tooltip -> "Critical Pair Lemma 20"}, "Substitution Lemma 29" -> {Tooltip -> "Substitution Lemma 29"}, "Substitution Lemma 32" -> {Tooltip -> "Substitution Lemma 32"}, "Axiom 5" -> {Tooltip -> "Axiom 5"}, "Critical Pair Lemma 13" -> {Tooltip -> "Critical Pair Lemma 13"}, "Critical Pair Lemma 35" -> {Tooltip -> "Critical Pair Lemma 35"}, "Critical Pair Lemma 2" -> {Tooltip -> "Critical Pair Lemma 2"}, "Axiom 6" -> {Tooltip -> "Axiom 6"}, "Substitution Lemma 8" -> {Tooltip -> "Substitution Lemma 8"}, "Critical Pair Lemma 39" -> {Tooltip -> "Critical Pair Lemma 39"}, "Critical Pair Lemma 4" -> {Tooltip -> "Critical Pair Lemma 4"}, "Substitution Lemma 28" -> {Tooltip -> "Substitution Lemma 28"}, "Substitution Lemma 16" -> {Tooltip -> "Substitution Lemma 16"}, "Critical Pair Lemma 34" -> {Tooltip -> "Critical Pair Lemma 34"}, "Critical Pair Lemma 9" -> {Tooltip -> "Critical Pair Lemma 9"}, "Critical Pair Lemma 25" -> {Tooltip -> "Critical Pair Lemma 25"}, "Substitution Lemma 12" -> {Tooltip -> "Substitution Lemma 12"}, "Hypothesis 1" -> {Tooltip -> "Hypothesis 1"}, "Substitution Lemma 10" -> {Tooltip -> "Substitution Lemma 10"}, "Critical Pair Lemma 41" -> {Tooltip -> "Critical Pair Lemma 41"}, "Substitution Lemma 15" -> {Tooltip -> "Substitution Lemma 15"}, "Substitution Lemma 23" -> {Tooltip -> "Substitution Lemma 23"}, "Critical Pair Lemma 12" -> {Tooltip -> "Critical Pair Lemma 12"}}, VertexLabels -> {None}, VertexShapeFunction -> { "Axiom 6" -> "FiveDown", "Critical Pair Lemma 8" -> "Triangle", "Critical Pair Lemma 18" -> "Triangle", "Critical Pair Lemma 3" -> "Triangle", "Critical Pair Lemma 17" -> "Triangle", "Substitution Lemma 3" -> "Circle", "Substitution Lemma 26" -> "Circle", "Critical Pair Lemma 38" -> "Triangle", "Critical Pair Lemma 20" -> "Triangle", "Critical Pair Lemma 19" -> "Triangle", "Critical Pair Lemma 14" -> "Triangle", "Critical Pair Lemma 5" -> "Triangle", "Substitution Lemma 23" -> "Circle", "Critical Pair Lemma 7" -> "Triangle", "Critical Pair Lemma 34" -> "Triangle", "Critical Pair Lemma 16" -> "Triangle", "Substitution Lemma 1" -> "Circle", "Substitution Lemma 10" -> "Circle", "Critical Pair Lemma 22" -> "Triangle", "Substitution Lemma 9" -> "Circle", "Axiom 4" -> "FiveDown", "Substitution Lemma 12" -> "Circle", "Substitution Lemma 31" -> "Circle", "Critical Pair Lemma 36" -> "Triangle", "Critical Pair Lemma 21" -> "Triangle", "Critical Pair Lemma 41" -> "Triangle", "Substitution Lemma 6" -> "Circle", "Substitution Lemma 34" -> "Circle", "Critical Pair Lemma 25" -> "Triangle", "Critical Pair Lemma 35" -> "Triangle", "Critical Pair Lemma 4" -> "Triangle", "Axiom 5" -> "FiveDown", "Critical Pair Lemma 24" -> "Triangle", "Substitution Lemma 19" -> "Circle", "Critical Pair Lemma 31" -> "Triangle", "Substitution Lemma 27" -> "Circle", "Critical Pair Lemma 1" -> "Triangle", "Critical Pair Lemma 6" -> "Triangle", "Axiom 2" -> "FiveDown", "Critical Pair Lemma 23" -> "Triangle", "Substitution Lemma 11" -> "Circle", "Substitution Lemma 21" -> "Circle", "Substitution Lemma 22" -> "Circle", "Conclusion 1" -> "Square", "Substitution Lemma 13" -> "Circle", "Axiom 1" -> "FiveDown", "Substitution Lemma 20" -> "Circle", "Critical Pair Lemma 39" -> "Triangle", "Critical Pair Lemma 32" -> "Triangle", "Critical Pair Lemma 30" -> "Triangle", "Critical Pair Lemma 27" -> "Triangle", "Critical Pair Lemma 37" -> "Triangle", "Substitution Lemma 30" -> "Circle", "Critical Pair Lemma 29" -> "Triangle", "Substitution Lemma 7" -> "Circle", "Substitution Lemma 33" -> "Circle", "Substitution Lemma 32" -> "Circle", "Substitution Lemma 16" -> "Circle", "Substitution Lemma 29" -> "Circle", "Hypothesis 1" -> "Diamond", "Substitution Lemma 25" -> "Circle", "Critical Pair Lemma 9" -> "Triangle", "Critical Pair Lemma 33" -> "Triangle", "Critical Pair Lemma 26" -> "Triangle", "Critical Pair Lemma 28" -> "Triangle", "Critical Pair Lemma 13" -> "Triangle", "Substitution Lemma 18" -> "Circle", "Substitution Lemma 4" -> "Circle", "Substitution Lemma 17" -> "Circle", "Substitution Lemma 24" -> "Circle", "Substitution Lemma 14" -> "Circle", "Axiom 3" -> "FiveDown", "Critical Pair Lemma 11" -> "Triangle", "Critical Pair Lemma 10" -> "Triangle", "Substitution Lemma 5" -> "Circle", "Critical Pair Lemma 2" -> "Triangle", "Critical Pair Lemma 12" -> "Triangle", "Substitution Lemma 15" -> "Circle", "Substitution Lemma 8" -> "Circle", "Substitution Lemma 2" -> "Circle", "Critical Pair Lemma 40" -> "Triangle", "Substitution Lemma 28" -> "Circle", "Critical Pair Lemma 15" -> "Triangle"}, VertexSize -> {{"Scaled", 0.012976425998969036`}}, VertexStyle -> {"Critical Pair Lemma 8" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 20" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 15" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Axiom 1" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Substitution Lemma 22" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 34" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 7" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 39" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 29" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 11" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 23" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 3" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 9" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 36" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 30" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 40" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 38" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 20" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Axiom 5" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Substitution Lemma 19" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 7" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 18" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 10" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 30" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 10" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 1" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 35" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 33" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 32" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Hypothesis 1" -> Directive[ RGBColor[ Rational[146, 255], Rational[10, 17], 0], EdgeForm[]], "Axiom 6" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Critical Pair Lemma 16" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 31" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 17" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 41" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 14" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 13" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 26" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 13" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 37" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 18" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 28" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 14" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 12" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 3" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 9" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 2" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 16" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 24" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 25" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 11" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 26" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 24" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 12" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 27" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 31" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 1" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 6" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 33" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 23" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 15" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 5" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 21" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Axiom 2" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Substitution Lemma 4" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Substitution Lemma 21" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 25" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 8" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 27" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 6" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 28" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 2" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Conclusion 1" -> Directive[ RGBColor[ Rational[13, 15], Rational[1, 15], 0], EdgeForm[]], "Critical Pair Lemma 34" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 22" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Critical Pair Lemma 5" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Axiom 4" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Critical Pair Lemma 19" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Axiom 3" -> Directive[ RGBColor[ Rational[71, 255], Rational[182, 255], Rational[109, 255]], EdgeForm[]], "Substitution Lemma 32" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 4" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]], "Substitution Lemma 17" -> Directive[ RGBColor[ Rational[15, 17], Rational[52, 85], Rational[12, 85]], EdgeForm[]], "Critical Pair Lemma 29" -> Directive[ RGBColor[ Rational[47, 51], Rational[98, 255], Rational[53, 255]], EdgeForm[]]}}]]], "Output", CellChangeTimes->{3.756079942774455*^9}, CellLabel->"Out[4]=", CellID->105418764] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell["", "PageBreak", PageBreakBelow->True, CellID->47835890], Cell["Have you heard?", "Text", CellChangeTimes->{3.756079951635166*^9}, CellID->201931260], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Row", "[", RowBox[{"BirdSay", "/@", RowBox[{"TextWords", "[", "\"\\"", "]"}]}], "]"}]], "Input", CellChangeTimes->{3.7560799549490523`*^9}, CellLabel->"In[1]:=", CellID->579512304], Cell[BoxData[ TemplateBox[{InterpretationBox[ PanelBox["\"The\"", Appearance -> Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle -> "Output"], "The"], InterpretationBox[ PanelBox["\"bird\"", Appearance -> Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle -> "Output"], "bird"], InterpretationBox[ PanelBox["\"is\"", Appearance -> Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle -> "Output"], "is"], InterpretationBox[ PanelBox["\"the\"", Appearance -> Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle -> "Output"], "the"], InterpretationBox[ PanelBox["\"word\"", Appearance -> Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle -> "Output"], "word"]}, "RowDefault"]], "Output", CellChangeTimes->{3.7560799586219177`*^9}, CellLabel->"Out[1]=", CellID->326631600] }, Open ]] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell["Applications", "Subsection", CellLabel->"In[4]:=", CellID->568056528], Cell["Create a notebook that prints messages in a really cool way:", "Text", CellChangeTimes->{{3.7560802832273893`*^9, 3.756080291746135*^9}}, CellID->79484806], Cell[CellGroupData[{ Cell[BoxData[{ RowBox[{ RowBox[{ RowBox[{"birdBox", "=", RowBox[{"Module", "[", RowBox[{ RowBox[{"{", "expr", "}"}], ",", "\[IndentingNewLine]", RowBox[{"With", "[", RowBox[{ RowBox[{"{", RowBox[{"b", "=", RowBox[{"ToBoxes", "[", RowBox[{"BirdSay", "[", "expr", "]"}], "]"}]}], "}"}], ",", RowBox[{"Replace", "[", RowBox[{ RowBox[{"CurrentValue", "[", RowBox[{"{", RowBox[{ "StyleDefinitions", ",", "\"\\"", ",", "\"\\""}], "}"}], "]"}], ",", RowBox[{ RowBox[{"HoldPattern", "[", RowBox[{"e_", "&"}], "]"}], "\[RuleDelayed]", RowBox[{"Function", "@@", RowBox[{"{", RowBox[{"b", "/.", "\[VeryThinSpace]", RowBox[{ RowBox[{"SymbolName", "[", "expr", "]"}], "\[Rule]", "e"}]}], "}"}]}]}]}], "]"}]}], "]"}]}], "\[IndentingNewLine]", "]"}]}], ";"}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"nb", "=", RowBox[{"CreateDocument", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"ExpressionCell", "[", RowBox[{ RowBox[{"Defer", "[", RowBox[{"1", "/", "0"}], "]"}], ",", "\"\\""}], "]"}], ",", RowBox[{"ExpressionCell", "[", RowBox[{ RowBox[{"Defer", "[", RowBox[{"First", "[", "x", "]"}], "]"}], ",", "\"\\""}], "]"}], ",", RowBox[{"ExpressionCell", "[", RowBox[{ RowBox[{"Defer", "[", RowBox[{"BirdSay", "[", "\"\\"", "]"}], "]"}], ",", "\"\\""}], "]"}]}], "}"}], ",", "\[IndentingNewLine]", RowBox[{"StyleDefinitions", "\[Rule]", RowBox[{"Notebook", "[", RowBox[{"{", RowBox[{"Cell", "[", RowBox[{ RowBox[{"StyleData", "[", "\"\\"", "]"}], ",", RowBox[{ "\"\\"", "\[Rule]", "birdBox"}]}], "]"}], "}"}], "]"}]}]}], "]"}]}], ";"}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", RowBox[{"NotebookEvaluate", "[", RowBox[{"nb", ",", RowBox[{"InsertResults", "\[Rule]", "True"}]}], "]"}]}], "Input", CellChangeTimes->{{3.7560801201767006`*^9, 3.7560801341632214`*^9}, { 3.7560801773248477`*^9, 3.756080202420024*^9}, {3.756080236760893*^9, 3.7560802501744776`*^9}, {3.7560802957219954`*^9, 3.7560803324118166`*^9}}, CellLabel->"In[1]:=", CellID->14441392], Cell[BoxData[ InterpretationBox[ PanelBox["\<\"Neat!\"\>", Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], "Neat!"]], "Output", CellChangeTimes->{{3.756080318194277*^9, 3.756080336364688*^9}}, CellLabel->"Out[3]=", CellID->726535153], Cell[BoxData[ GraphicsBox[RasterBox[CompressedData[" 1:eJzs3Ql4FOXBwPHZ2d1cBAh3gAABBMIRDCCKARRBMSoIyiEeQLhy7G5CEA9O I1SLlbNaS21LU7WWqigqJNlEW6pVqtXPo1VRQVH7afDAr2olCkn2e2cmu9nM Hrmzk83/15Emu5PZySb4+H/ed94ZuHTl1RmyJEmro8QfVy+59aIbb1yydk6c +GRe7urszNwVyy/LvWlF5oobJyw1iwe3WyRpm/hH+bjSrcLtjOr06dM/qn5Q latOuX3v9l8AAAAAgBdPLnkCSuspra20zhLBpZWXJ8Qqa9PVmRZonjrz7jLt Rb9z+xYAAAAA4MWTS97J5ok1T6lp5eVdaoECzTN85l1nni7TXvQbt/8AAAAA ALx4csk72bRY8y41vwNqfgPNe/jMU2eeNNNe9P9UXwMAAAAAvv765MmT3p9q xeRJNk+seUpNN6Cmm/eoCzTPpWeeOvMMmWlddlL1lepLAAAAAIAXrZW0btJ6 zTO45ik174vUfDNNF2i64TNdnXm67AvV5wAAAAAAL1oreXpNV2p+B9Q8mRY8 0PzWmdZlJ06cKFN9BgAAAADworWSiCat1/yWWpBM0zWa9wiaJ9A8daalmXjR Tz/99H9V/wYAAACA9u0TN+1TrZVENGm9JjLKU2qeTPMeTdM1mm4QTRdo2vCZ d51pXSZe/eOPP/5IdRwAAAAAoNIqSeSSlmwioLxLTRtQ02WabihNN8tRF2ii 9T7//HPvOtPSTLz0hx9++MEHHxw7duwoAAAAAEAlEkmEksglrddEQHmXmsgr EVm6TNPNeNQazTfQPMNn4lDawJk4vtZl4nXff//9995779133z0CAAAAAO3b O27apyKURC6JaBLpJAJKizWRVKLUgmea1mjesxy1VRy1ETQRaOLLxUHEocQx PWkmXk689Ntvv/0v1T//+c83AQAAAAAqkUhaK4loEukkAkobXPvwww8//vhj bUDNO9O0lR69Zzx6D6JpCzl6Au3f//63qDNxNJFmIgbFS7z11lviFd94443X X3/9f1SvvvrqKwAAAAAAlUgkrZVENIl0EgElSkr0lKiqDz74QMs0UVvatWlf f/21Z5lHz1Ca1mjeg2gi6LRAE6H33nvvifQTDSgO/tprr2lF9vLLL7/00kuH Dx9+8cUXX3jhhb8BAAAAAFQikUQoiVwS0STSSQSU6DXRU2+99ZbIKy3TPv30 0xMnTvgdSvOst++5XbXoOBF0n3322UcffXTdskw2NjY2NjY2NjY2Nja2Ztne fvvt999///jx4//+9791Q2meq9J8l3MUHSeCTnzJsWPHxEH+AwAAAABoMpFX b7755rvvvvvBBx988sknn332mW4ozTPdUTfRUXScCLqPP/5Y9B2NBgAAAKDZ HTlyJNSnEAIir1577bV33nnn2LFjH330ke9VaZ7pjt6Npk10/PTTT8WXiL6j 0QAAAAA0u3BqtENuQT7WiLx69dVX//Wvf7333nvadEfPAo+6RvNe0VFrNBF0 H374oXjfaDQAAAAAza7dNtorr7zyz3/+89133xXB9cknn/iuHKJNd9Stui86 TgTdBx988M4779BoAAAAAJpdu220l19++c033xTfvm4R/kCNpt262tNob7/9 No0GAAAAoNm5G+21n46Xxv/0NZ/nH0uX3Pw8HfRZ5ZBS+mP+v6LZvoFGEXn1 0ksvvfHGG4EuSfM0mnYxmvgSbcEQbVFHGg0AAABACwnaaGpQuSvLJ7mCP+ve xfuggUKwBdQ5jvb3v//99ddfF6l19OhR0WieS9J0y4YEarS33nqLRgMAAADQ 7II0mtJgtR6qtU/wZ70P4nlQ2cMn41pI/RvNc5e0+jfasWPHaDQAAAAALSFw o/lpLq+Hgj/r/1HdqFqLqrPRDh8+/Nprr4nU0hpNu0takEYTD9JoAAAAAFpa wEYLeDWZulfwZ2vzHLo1x9GCC9Jo2tKO/2EcDQAAAEAotEKj1Ry8Fa9H89Ys 42hcjwYAAACgFbRYo9Us+ajs5hlC87euo+RPM36PzX49Gus6AgAAAGghLdNo fi5cCz7RseUC7T8ts64jjQYAAACgJQReM8TfzMWax4I+W7vH3EuFKE8HuRyt hQLNLxoNAAAAgDGJRvNkle+6jrqm8noo6LO1F3CsKbY6Ku0/rXZvaxoNAAAA gDGJRvMMYPlZS79WUtV6INizPuNons/qqrRWQqMBAAAAMCZ1rqOaV37WZFQX +KgVZd67BHlWdz2ad5YZotJoNAAAAADG5L4eTWkpf8viV+ebv3G24M/WrOvo 77K19Gb9JhqMRgMAAABgTJ5Ga1doNAAAAADGRKPRaAAAAACMg0aj0QAAAAAY B41GowEAAAAwDhqNRgMAAABgHDQajQYAAADAOGg0Gg0AAACAcdBoTWk0FwAA AAC0VzQaAAAAABgHjQYAAAAAxkGjAQAAAIBx0GgAAAAAYBw0GgAAAAAYB40G AAAAAMZBowEAAACAcdBoAAAAAGAc9Ymv9PR0Gg0AAAAAWkF9Ak1DowEAAABA S6tnoNUn02g0AAAAAGii+gdanZlGowEAAABAE9Un0Hw/pdEAAAAAoCXUJ9CC PEijAQAAAEAzCt5o9XycRgMAAACAZhGk0Rr6FI0GAAAAAE0UKMT8Ph78WRoN AAAAAJooSIs1FI0GAAAAAE1EowEAAACAcdBoAAAAAGAcNBoAAAAAGAeNBgAA AADGQaMBAAAAgHHQaAAAAABgHDQaAAAAABhHmDWaONrLL7/8/PPPv+RDPC6e ba73DQAAAABaQng0WlVVVWVl5Xvvvffmm29++eWXFRUVvvuIx8WzYh+xp9i/ ye8cAAAAADS/sGk0EV/iRevcU+wj9qTRAAAAABhTeDTad999949//KOeO4s9 xf6NeBUAAAAAaGnh0Wjvvffep59+Ws+dxZ5i/0a8CgAAAAC0tPBotFdeeeWb b77xffyvf/2r74NiT7F/I14FAAAAAFpaeDSaeN1Tp075Pu630cSeYv9GvAoA AAAAtLSwabTy8nLfx/02mtiTRgMAAABgTGHZaH/1x/MsjQYAAADAsMKj0V56 6aUGjaOJ/RvxKgAAAADQ0mg0AAAAADCO8Gg00WINajS/kyEBAAAAILTCptEA AAAAIDzQaAAAAABgHDQaAAAAABgHjQYAAAAAxkGjAQAAAIBx0GgAAAAAYBw0 GgAAAAAYB40GAAAAAMZBowEAAACAcdBoAAAAAGAcNBoAAAAAGAeNBgAAAADG QaMBAAAAgHHQaAAAAABgHDQaAAAAABgHjQYAAAAAxkGjAQAAAIBx0GgAAAAA 0EIOHz58wM3pdAZ50INGa7skk8mzBSLV3urU0P1bVvV5SJ5TkWVZkqSePXu+ 8sqr4h2orKwM9Q8BAAAAqC9RZPV5kEZru0ySOew3ybvX3I3Wq1f8K6/+j4tG AwAAQJtCo4U9WTJ7tkCNU599mrJ/C2+ySVJG0ZRNVv7UGq1z57iXX/6Hi0YD AABAm0Kjhb3hnRKS3NuwTn39bkn12Kcp+7f0NqJj76Ede/WK6RxltiqDaZLU vXv3W2655auvTop3oKqqKtQ/BAAAAKC+aLSw94sLsoNv9wb9tOn7t/CWpZzA 5JwdF2ReMei8LhEdzSZlEO3ss88WvzYuAg0AAABtDY0W9k47Dob39qPj4A+5 xf+78tHMUVd0lztaTGat0cRvlItGAwAAQFtDo4U/e0mYbzaxOT/MevjKfueZ JZPVbBGNNnr06M+/+MJFowEAAKCtodHCXqWjqLW2Ym2rqP64lV63ylH8g+3A X+dtPb/7UFFnZlkZRxs3btwXX37potEAAADQ1tBo4c9R3Cxblb1IbNUfq2Uk Pq20F4utylZclV3sUjany1ZSZS+pdJRUOZwusb+9sCqnsLnOwc9ZiT9znN9k Pl4wdeVZcX0l1Tnjz/vrc89XVLCcIwAAANoeGi3sVakh0xyb6LLCKtFctkIl x+xOV67TtbLElVfiWlXiurGkapXzR/uB/2Q8/umSP753/Z6PlxScynlSDbSi 5jsHn80uGq3k8xV/Wjdmfq+Yrtoy/FfPmRfqdx0AAABoJBot7DUoeWqNT7k/ EFulvchlO+ByFLryikWOnc49WLbs4dcW3PvMrDv3z9jw0PSb7p+2csfkzM0T blgzbn7O6FlLky51jEwrmJrzvyserrAXuhqUXQ3ZlBPLLT2+/KEr+50fZY6U zUqjzbxyNlMcAQAA0EbRaGGvSQWkZJrTlVPiWll6JvfAl9mP/mvxb/48Z+vD l976k/ELFw6ZNrVPyriug4fE9ulhjYuUIiySZJUks3JRmNJK53cadHDGplNZ T4uDtGijvbN0z+jOg8UrWszKwvtXzroq1O86AAAA0Eg0Wthr0CCa+PNMjvax 05VbXJVT/L3tqf9d9od3Fv3m2bl37b7IkTX8somdhvaV47pI0bFSZLQpwipb zSarJDZZbJKyiT5TG214bN89U2/8b+aTrpyWbLSckrcW/+bsTmqjWZQFQ2bN vjrU7zoAAADQSDRa2GtQoCmbspq9U3xanv3kpyv+UHz1navHXHVJQsrQmPje lk5x5uhIk1lrMZNJbCZl2EyWLLIpUjZHWSI6WKK6WDr0iOjc3dLpuoSJry/8 5Y85LTLX0eU1jvbesoLzuiQpizpWNxrjaAAAAGiraLSwF6RxdAskqis3Fruy i360HyizP3Lwys3Lh04f2zGxV1THaLOsjI5JyhiZ2SRFmOQIyRxliuhgiu5q ju4f1XV0XP/J8cNn9ZuQPmz6qpQ5G869/r6pK//n2nt/yN6vLO3YMoNonkY7 vuzBS+PHWWSL2SIzjgYAAIA2jUYLe3WMmtUMnxW57MWVOcVf2B47MGOTfdSs 8T2Gx1liq7tMNlkk2aJOZ+wgRQyJ6X1Zwjmrk2ffd4Ft3xXrC2dv/svVdx2e t/1/Ftz71g33H11c8MmSP/zfin1ncosqxJZT6P8Vm6fRil25JWXLH14ybHqX iA5WdY6l53o0Vg4BAABAm0Ojhb26Gs1ZZS+psJW4HCX/ydh38Mo7b06Zf1Gv lDizUmeyLFvEP8oyIKaE6B6TeyenD5u+ecLiBy696dm5d72/6Lf/zd7vynvG tepZV96zygcrxVYqoklZZsThVG6dFqQKm2VT194/mfnYjglLB3XoaVJH+xL6 99t8x0/Ky8tD/d4DAAAADUajhb2AEx1F3djEVqRsjtL3FxfsSs2Y1ndsB1OU cp2Z2WRRLzXrJEee231oxvC07ZMyn5iR/84N959yPOlaXVqVV+rKeabKVlpp K6q012zahMkqu9cL1TvQGtdxIgbLbU8/N//uyT2GK5ekWZVL0oYMG/pZWZmL oTQAAAC0NTRa2AvcaE5RZ5WOwu8d+99Y+Mtbx14zyNrDLOpMGTYzmSQ5zho7 umvioqSLH7l0zVcZj1TmOCsc6qZcs1biEnVmL61wlFY1x7r6uo6rf9ZV75/j /DLrkcyhl3aSo0zq8vspY8d88823LhoNAAAAbQ2NFvZ04eO1QoiyeOO3Oftf uGZH+rCLupljLSaz2aQs2djZ0mFkzIBFgy7Zm7buk8w//pD9dKUSdKVV2aVV tpIqmxZlRe6tqfMYvZaUbHCpudSbuIlOPJ399O8uuXFEtwHqyibKONqLhw+H +r0HAAAAGoxGC3u1O6jQZS9UF1osdDkOfpf5xF/m/OzqQZM6W6ItJuWeZhZJ jo/oOG/wpD9dsfGDZX88lfGkMiXS4az0NJFd3Ro+j7HORqsUp5RdeNpWeNpR 6F1twRuw5qnswjcW7p6ZmKrcJc1kMlvMI0YOf+utt10MpQEAAKBNodHCnp9G sxW6coq+zn7sTzM2XhY/Lk6Otkoiz2SzJA+N6r35vIWvXXfP91n7K3NKXTkl jZt82KBAc7nr7/ucA28s2P3JoofUJUe0cKtvo7lsRSdz968759rulo4W2SJK rUeXLi+//A/xDlRWVob6hwAAAADUF40W9vSNZiusyin6KnPfny5fO7F3slW2 ipyxmuRIST6346Bdk7PeX/ZgpaPIlS36SBk+cwVIqmZsNC3QTtmeci642z50 xr7pG86sKq1UH9QPlgU9wpncwqdn3H5RfLJsssomOTY66tK0y19/400XQ2kA AABoO2i0sFc7c4pEo/2YV/S3ebuu7DNOdJn4n1kyd5AjpvUe+cC03M8z9p7J KalUFuQvEkFXZx81vc6UTW2xD5f9fmlyWrzc+ZYx8z5ZsfeMvUhddrJel6Qp 35fdWZVd+O8Vf8g9+0qTZDGbLdpNtx944CEXQ2kAAABoO2i0sFcriOwlLvsz R5c+cMs587uYO1hNyhr7na0xaf3G/2nm2m/sj1bkHKiqfblZCwVa9SnlFCov Zy/9POOx3ZNtibE9RVVN7Z18YPbtyiCa7Zkqe2kDzsFW5FpZ8pupK/tGdTfL slmSIiKjn9j/pItGAwAAQNtBo4U974qpdJSU257+3dRVwzv2jzRZJeUmaNbL +ozbP3vT13n7K+0H67z+q7nH0YrEnz/Yny6+8icTOw+LNkVIsqmHpdPt5173 neNJV3apy17SgJMRuZfrfGHe9lmDUiNlZRzNGhG1YWP+l19+GeofAgAAAFBf NFr4q+4X5dbSp3Odh+bdfdXA882SWVnFUbYkRffbO33t9/anqpS5hc4qe0kr NJpnnK7K7jy9sujV6+9ZNuzijtYY9d7Zyt3NZgw898Xrf15hU27i1sAjO08s 3/uT8xZ2NkWZZEmWLWZLxM9/fq+LoTQAAAC0ETRa2KsZRLMVfZ6576aUuV3M 0SZZuVd1H0undeOu/WjRg64cJeJc9taoM++XqLSXfLLs4bsmLO4T0dEsCk25 g7ZyFVlip54/S11+ynbQ5WhgM9qV6Y5Pzsof2rGPRRxMXeBx2/YdLhoNAAAA bQSNFvYqHCVncpwuh/OU/cD9F61KiUs0S5LJLMdYrJf2GfPyvJ1n7AcqlRVC WmXszK4sA6Ku2eg84yg5nVu8b/qacV0TIyVl+RKl0ESnyZJVkuYlnn98SUGl ciu3BhxfuSQtt+TVhb+8fvAF0VarpBbf1u3bXCztCAAAgDaCRgt7Z3JKKpQm Kvo845GFiVNjJKvFItJFHtq5728vv/G/mftcOcW+a+y3YKnZ1QvHsot+yC38 x/yfLx44JVqyRIg4E20mikppNCWsUjr3f3jajd9lPe7Kach0R3WJyJMrHrn/ guyeER3FcWRZHpU86qGH/xDqnwMAAABQLzRa2KvIKXHZi3+wPfnCNbtSewxX s8XULSIuc0Ta8cwHRLtV2ooaNp+wqaNpTvGiFfYDH2b+4ZaUeb0jupjMSpRZ Is1DRwzq3C1WWTHfZOpkjrxu0AUfLnvQcx/teg6lVdrE8Yv/Pnfb+M6DRfUp t+aWpEWLF4X65wAAAADUC40W9irtpa4c58nsx+6ZZBsSGy+ZJBEtY7ud9cTM Df+1PVGZ46y0O1sn0NzjaMpSjd/Zn/jtlFXJXQYqdWaSZKup/5A+C5dfPfb8 4ZZoszKmJknDO/dzzr7zx6ynG3T8SluJa+WzR5bsmT/wwhhrlDJ7UpIyM/iF AQAAQNtAo4W9qqwSV+6zJ5Y9vGzQ9G7mWJNZmVF4Vf/z3l/64A925fZkrbbe vvuStGfOZBW+cO3OS+KTrcrykiLRTN17xs1ccPHNm5bPW3xpfP8e6lCa1DOi 003JV3207Peulc9UKgtOFgY/yepxNGUF/tIPlz+UO3pOz8jOkjqOlrGCXxgA AAC0DTRa2KtwlLjszrdv+NW5XZKUdTnMps6W6FWjZp3MfboiR5kW2Jr3RFNv kF1yfOlDjqFX9LJ2UhZyNMnRHSPHTx6dd9vyjVvtN962NGXCCGXsS5asJsv5 nc766/y7K3OLq2z1bjTxQU7JicxH7pqU0S+mm6QOyWUs5xcGAAAAbQONFvZ+ zC3+PuPxvWm3DIjtJalGd+lfMCX3lONglcPZauNo7nuiOb/NfuKRWRtGxSYo V53JFsksDR7df8XNC9bdnblhW+aGu20zFlzUs3ecklayuae1008nLvn3sodd jtKquhafrGk0h/P/Mh8ruGT1WbE9ldiTpBU0GgAAANoIGi3sncx47JOlD946 dk7PSHWdQ0ma0f+cf8zdXpF90DdwWnwQbWXpsfSC7OFpXSOi1V6Ue/XvNWvx pbdsXbF+R8aG7SLTsrNvvS7l3CT1SXO02XpxnzEvzN/lWvmsy1ZUc/PrwJvW aKey9h+YmT+8Y2/lrmuSlJGRFeqfAwAAAFAvNFrY+/ucu99Z+OtZ/c+NsUaI XrFKsm3UzC8yH62ytfg90Wrqz15Y6XBWZReX258qmpU/JravLEsm2WIySeMm jbpxc8bardnrt2Wu35a1bmvm2ruzLpszJbpThCwrV6vFR3T+7SV5P9ifctXj XmkurdHsxaftT/113s9Gd07Qhg4HDx68Y+fPuY01AAAAjI9GC3u/TF3x8qJf XthteIRsNptMXc0dNp2/+MeVRaLRtFtXt8YsR/FCdqcrx/nBkt9vOGdBN1O0 eh80uWevuFnXXrJhe+46pdGytO22nfYlufOHjh5kNivzHWMk6+rRsz9YtMeV U337szpey91oz1+zVWs0i9Uq/jw/ddK3337n4mbWAAAAMDYaLewtHTbtwHU/ m9B1iFU0mmRKiOq648KMyjyny9Yag2jVm71EWfQjr+SZuT+7oNeoCFkZ0RMF NuGCsx3rlqzfZvMEmrbduGnZtBkTLRHKpWQRpogrEs559uotVSudDW60OKXR zBaL+HPqtEtoNAAAABgfjRb2JvceufWi7DGdE61mi8lkSojssvOCjMpVyoqO rTSIpjRaqSu75Ifcg7+dtqqX1NFkssiyKS4u5uob0jZuX7lWmeWY6Qm0dVsz N2yzzV18eXRHq8kkySZrUoc+D1yyWiReVV1dWdNotqeem3+3No5mtiqNNvmC Kd98862LRgMAAICx0Whhb0jnvnOHT07u2C/SHC2CJyGy667JWZV5Ja3TaFXV 14iVVOYU/+/S3986dk60cscyk9UqDx89aEne/I07cteJQNu+wrvR8nc4Ftvm xPfrZjHLkkmKkiK2TlimrD9Zj3NWr0crOZX9ZNHsO0Z17K00mjJp0jRr9tXf nzoV6p8GAAAAUAcaLezFmKOHxMYP6RgfZY4UvdP6jaaOozmrVjr/fNVP0xLG RpiUy8wsEfLUyyfm3b50/Tb7el2jbcu8bYc9a/W1yWOHREQoQ2Ci6W4cffWJ ZXtd7rmOgU5bvfbN6XKUfp352J5peWd16K6tGXLlzCs/PP5RqH8UAAAAQN1o tLAnmcyx5qjesV0jzBGeRqtqrUarPr6txJVXsntabmJUD7N6U+mYzpHXLJ21 Ybt93das9dszla2m0bI2bM/Ou23RRWnjI2OU5T6skjw7ceKLc3bUeT1a9Wvl lH6W8fBPUhf1iYlTl96XMrNZex8AAABtA40W9kwmOUK2xEbGWGSLZDL1a91x NG0x/EpbyZmcwtvPvaGDZJZNJnOEud/QPstXXZe/y1EdaF6Npmzbs9fetfya JZd36BytNdrYrkP/NO3WKkeRy+HUDhvwzG1OV+4zHywryBiRFhcRI8lKpC1d vjzUPwcAAACgXmi0sGcyiTIzmWVZ+VMyxVs7/mzisoq8Uld9xqSaaRONdmLF XnvyDOXqMpMUGWMdO3m4fd11G3fY1m3L1C3qqA6lZdy2w7b8xmvi+nQWZy/L cq+IuJ+dt7hiZZHLXlihLsLvez9r7eMKu2i00rcX/eqyhHOiLFZt2G7FihWh /jkAAAAA9UKjhT2TGmmSEmrKIokxknndOdeUK7HTao3mrLAXv3Xd7uuHTDGp Uw+jYiMuuGz8ytsWbdievc4n0NRxtMz8XTb7ukUDR/W3WC0iLyMksyPpsv/Y n3DZCs/kFFfkOH3H0WoaLa/01YX3nhN3ltlkFnGqNFpGRqh/DgAAAEC90Ghh T9LyTCVZlERaNuLiTzMfFo3mynG2wnRHsZ22Fz5/9dbL+49XLw6TYjpGXXr1 Bas3LxWN5ifQlC3zth1Zq25fknrJOR1io7WvumrAhDcW/eqM/YDLUVLpKNUm Pfo2WqW9yJVb/Oz8uwZGx2uLOirf8grmOgIAAKBtoNHCXkyHDtpQmvKPenHW Zf3G/G3Oz5SWyanr2q7m2ERMnckpfOqyjZN6jdBqK7Zz9LwlM9Zs8TPL0dNo G7dn3vLTFbNvSOvatbO2NuOkniMen5F/yvGUy15SlV1aFaDRxDf1feYTf7jk pl6RXasbTTY5VuaG+ucAAAAA1AuNFvY2bd5sUu8yJsnqUJokjew84P4pOacc B1324kqldEpautF+zCm6f+rK5Lj+slpbnbrFpOfOXbu91q2ra2+29dsz123N XJJ3TY/4LspQoGQaEdfvFxdm/df+ZFVOqRKY/uY6KvdQyyn9NP2PG85b2MXa QXzP4kuXrcj49LPPQv1zAAAAAOqFRgt7j+57TGkcs2xSlw2RTKbucsdbkq/+ zvGky1aormbf4o32Q07h3ROXJ8b0kNVI7Nq7U+Yt16/fmS0qLGCjbcvYsD3b sWFp7wE9JaUv5UExvX52/uLvAjeasikTHUtfnX/v7AHnR1kiTLIy0fGeX9wn 3oeKiopQ/ygAAACAutFoYe/osaPXXn+dtgS9KB3JbLJI8pzE1A9XPFBpe1pE TZW9xPfarrqyq2arT6OV5x5cM+6aLhGxsiyJUkwY3NO+buH6XVnBG23jDlve 7ZkJg/tI6jTNAdE9bht/7Tf2/S5HaVXgRqvKK3l85sZBkd1ls6hS5RbYd265 S7wPlZWVof5RAAAAAHWj0dqDjz7+eM68uR07d9IG1MSf5/UYWjhr8/e2J5Q6 szW40dybs8rrbmXuzem9Kc/and/nPJ05/HLlwjDZFBFpHTHmrJwNi5RGCzLX sbrRMvoPTZBkpdH6RnW9ddx8ZWlHd6O5X8VTi8qDX2U+dvfkJZ1MSp1ZLBHn nnd+kbNEvAlVVVWh/jkAAAAAdaPRwp42fvTxJ5/0HzBQGUozK5HWJyZu3dhr vs54vHLln884/KxjH3wQTdSQciFbdukZxzOVduVuZdpW6bNViMdtxV9lP3bd oMlKIcrmqJjIcyaNXJW/dOMOe8BG254pnhI73Lh52aCRCbJZskimrhEdcpJn nXTsq8oRhy3yfpXqV7cpd7h+Y8E96cOmdTJFSCbJYo189NF9LgbRAAAA0HbQ aGFPGz/64ssvUydOlpWVHWWLSbln2OTuI1674Zc/5jrP5DSozoqVRftt6gfZ 4uMSl/3PNZuyJL5uEzuUfpnx6LyBk5RVFk1SdIeocy8YfePtyzZstwWc67g9 Q1nacYdt1ealSSkDLVblRtQx5ohlQ6d/Z3vcZXtW/1raq9v+7Mo99HTahrFx gyxmZRzNGhG17/EnXDQaAAAA2g4arf048u57EydPMkmSRb1lWJ/ILhvGzP94 6QPKCvz2mqvM6nUxmk0ZeqvMOXAy5/ET9n2fezbbfnV7Qt3Uj+37v7Lv/zDr wTmDlEaTZCk6Nuq8C9VG2xGs0dZtyxQRt/ony5PPGWKJVK6ms5rM1wyc9GHW 77+yPf657fEv1IO7X0V59S/ElvvE5snpsVK0+CZF1kVERO3906MuGg0AAABt B43Wrrzxr39Ouegi7a5hZpM8vFPCg5fd/J/Mx10OZ2VDhtLO5JS47EXfOp7Y OObai+JHTU8Yc0lCitgu7Xu22Karf17aN0XZElLSElKmJoyJj+mhroQvRXWI PGfSKHWuY5BGy/Q02pgJIyKirdo9uONjuk3rO2Zav3GX9h2Tph1f3S7pq7z6 9L4p4kyGduovS2ZtCUvZbH3k0cdcNBoAAADaDhqt/dA65R//eOXyy2eIfBEN EyFbL+o9uvDK/HL7k5U5Reoaj0VVQUfT1Kecp5WJjkVf2Z+c3nesVG/a3dki oyNTzhu+cuOSjTuCrr2/NWPDtqxVty89K6mfMkHTZDFrX18PsjKXU+rUqdPN t6wpKytzsWAIAAAA2g4arV05c+aM+PPurdvUNQ+Vq9OipYir+5337FU//TH3 SVf2gUqvwbKgo2klrlXPfHNT4ZUDJ9SKI3FE9ZZkXo/IGm0gTGm0KEvK+OE3 b87M3xl4HG2bbcO27DvuXbXmjoze/bpqhVf7VUzaqJxWZN5MyrPKU73i448e PebizmgAAABoU2i0dkUbTnrqqQOjks/WBrZMFkuMZFlw1uTnrvvZjzlPVuQU VQW+91n1miE5JV8uf+TpGbftnnHzmO6DY+M6nDV8wIizBw8ckmC1Kvck6zOg T1LKoOEpg/sN6i0ro1/VgaY1mtVq6pfYe8a8aas3L9mwPdtvo23caVt525Jr lsy4cu60rt07iq/q0i1ucFI/ccxBw/pZI5UMjO/Xa9SYIX37dVPvy60d3b2p L9S5c+ef3HGn+OUJ9bsOAAAANACN1t5omVbsLB2WlKQsl2hSbirdwRK5cOiU V2+497T9gMsnyryXE6mwF7nynj18zc4h1p4RUpRsksdMTMm+ZfHGrXnLcq+P jY0Vh7v6+hkbtzk23G2/ZslMa5RZWc1RfSEtnZRJlpIcEWu+IevK/F0O36G0 tVsz8u/Jnr/sCnO0Sb0PtVXsf/b4UbabbrhtmyP7phs6d4sVx5m5YNqdP795 9vypypqPksk7Az1DaZFRMX9izRAAAAC0KTRau/WXvxwafNZQdSV+EUJSV2vs iiFpRxb97oy92GV/psrurMwp9K6zypyiMznFYnOt+svfr9keH9lVyS5JGpua bFt/bf699uWrr4/p2EE8dPXCGRt/nrdxp2PBslmWSItJslQ3mlpp4lNRbRFR 5sUZMzfd41i7bcX6bZkb1HVCRKCt2569dntm/i/s85ZfLkeqg2JKo0nJ5w63 rV142z0O29pFndSRtdkLpmz51eqZ1011H9kr09yxZrFGsq4jAAAA2hYarT17 7vm/nTUkSVKXeZQleWBEr9Wj5n6w7IGKHOUOaC5Hkfdo2umcUhFu5banv1t9 oOjaOxMiuijr4Vukcy5Izl573fqt9uWrbujYrYMcLc1ZdMW6u1euuzt3fvps a4RoNG2RRU9HyZJkEo22cOlVG7fmrL1LuRWackM0pdGUtRzX3CU+yJ6z+HJz hFk2WSxRZilCOjt1eNatC9dvs2fefH1cr46SWTTaRZt3rb5i/sXKdMrajVYz rzIi6uGH91ZUVtJoAAAAaCtotPbJs8ph6TPPatemma0Wi8i0mF4bx87/IPPB qtySCrvXpEd7sSuz5MxNpX+8Yt2V/c6b1GdktMkqRZkmXnreDba5M6+deuHl 49PmTJ2XPmP+shnzll6RdvWFEy8Zf9aIQWZlOUbZMwVRu2BMmfFoMfVL7DNw RMKMa6fl78xbvz17rXpbtI3bbGlzJw4c0bvPgB4i66IiIy+eOXnB8lnXrpg1 64bpUy4/99I5F85ZPOOapbPSrpp40WXnDx89VJL9FZo2r9JsTRkz7oILL9q5 8+ehfLsBAACAeqPR2jPt2rTCIufYMeNF0URY5EjJNKxD/I5Jyz9dvvfMymcq 7UXVl6TZi39YWfyHtLXjug2pXk1RBFC0fP2Kq26+w5Y6dUyHztZhYwbdckf2 pl03zk1PGzSsb1SsVbaatUX+ay4YUxdoVP7PvUxjXHznK66dum6rba2yfsiK /O32MecP9SzkGNsxavmqa39yz82rbls+Oe282C4xQ5IH3LQ5a/M9eeMvGCle IrpDjFRzfMk70LQ7pGmvsnjxklC/2QAAAEC90GjtnLYu/dMHDqaM0e50Zoow mcZ0GXDfFMeJFY9W5jorHYVVotSynd+vOrhk6FRlxM1iVVfkMJksksixW3+a MWHSGPF4z/5dV962bMPd9nkLL03o39PTZbVW9DC5b3KmfmS2Kg01LLn/+rsz 12/PXLMta+P27HMmjdCGwCTlhtfW9Nz5t+2wrd60ZNLF54pHuvfp6Fi7aP02 26gxQ9XDmJW5lL7XpLmDzWKxiN0yMjJcXJUGAACAtoBGg5ZphYXFo5JTrNZI q8lklczndRm2Z+rqr7Mfr3QUuexOV86zrtWlmaOuUC9eM0XFRPSI7xY/oPti +9zVm1ZMuWxCtz6dRo4ffOMdy2/bkTtzwcU9+/TwSTPdih7q/8xKsI1MOWvD 3dkbtmWuUxotS2u0qJjI7vFd+58Vv2zVgvztOatuS5868/wefeKGpySuum1p /o6c0eOS1JujWWoazacFTe4FHrOyskL9NgMAAAD1QqPB5R5g2vf4E1ZrlEge yWqOkCwX9kp+JG3NN9n7yrOffHvxr/+29N6ZQyaqC3GYEof0mX1d2jVLZi7O mrfQNnf+iplzl1x2zbLLb3Bctcgxf8z5o2JiowI2mjrR0bvRhicPufXO7HV3 Z6+5K1vE2vjUZPFg73495txw+fwlV1yzbOYi29yFtnkLMmbNW3L5gqUzltjn LrPPGzysn34czd8Lao02Z86cV//ntXeOvBvqdxoAAACoA40Gl7vR/vrc8926 9zSZrSbZZJGkGJN1akJK0ew7Xk3ffXHPsxOiusRZo0VTdYiNOGfiyNWbVtx6 R/aIlIFjL0jOXLtw7dbsFavmd+/XJapTZGSUVa6+6CzwSJq2cL+sNFpCYt9r V8xatnL+YsfcRdlXJY06Szx41vB+t/4k+8bbl4+ZmBTTPWrsBSlZtyxef7ct ++br4wd0i46NtEZp91yro9HUJpRiY2PjunQ7P3XSF1986XJfiAcAAAAYEI0G j1Onyh966OEePZVLycyykk8d5JirBl54z/SVA6K168uUK8liOsScd8HZazZn r7/TMWBY/Mhzk+xrFt22PXf5ymvFU5KbnwvR/LaaJEVGRnbr3rVnr649esV1 79k5OiZCPDhkeL/1P7XftGnZyHFnSVYp+ZxR9psX5W/Pyb5pYccuHTyLhKiv 43/tfVPNHiZtXZHBZw39rKzMRaMBAADAwGg0aDzZ8uCDD/Xt21e7aZrom06R XVJ6DOloVZZP1JZotFgs3Xp2SUoeNDx5cIfOMZ26djxreMLIlEEDh/S1Wi21 Cqw+m8kk+RPbMWpY8sAhoxI7dYuVzJbO3boMHt5v+JjBg4b1j4iyVJeXZKqj 0NyZpn4v0rCkkWVlJ1w0GgAAAAyMRoOHp1wKCgoSExOVHBNpo2aQRao9m9Bd UsqtySTZE1ayev1XI5hls7pZxKZ8Jtc6rEm2SvpXUW+6pg2QudfeD3J8bXXH pOEjy07QaAAAADA0Gg3eqlTig/vvv3/AgAFKpokYktUkkgKMeIVU8ME4ncTE weI3zUWjAQAAwMBoNPjSlhD51f2/6dsvQVJuVWZWBq5MJrMk943pntp7+PR+ yWl9k9P6jLkkYdz0hDGe7ZKElEv6NnZL8Nr6pkxPqN6895meMHp637PVx8eM 7z2yR4duVmVtSNlkli1Wy8jkUZMumJw6cVLqxMm6bdLkC8efO+G66xf+3//9 x0WjAQAAwMBoNPilVUzBA7/vGd9LFJCydKJFWURxar8xf5y99sPsP3xlf/yr 7H0n7Ps+d+z7QvzZAtsX4siOx722fV/aHz2Z/chX9kc/yX74wZm3TkwYpUx1 tCgzHiOjox57fN+PP/54UvkV+sZ3E3X2/fffh/p9BQAAAOpAoyG4h/f+sVvP 7soFYyaTZDZ3MnW4qv+E4nlbv7A/6XKUuBzPuux/bsWt1GVzfu94+oVr710w cHKsKdKkXRFnlrt27/b8354P9bsFAAAANBWNhkC0obQqV9WfHn2kZ69esnt1 xBhrxKT44dsmLju+4sEfcosrbcVVtqJKe7HYqsRmc2/2Zt1s4oWKKhwHv7Xt c867a27ihXFmZZ1/i3KLalO3Hj1+/+ADp06dcrkvqfMr1O8oAAAAUDcaDUF4 uub3DzzYt29/pYmsEZJJjpTk4Z0SckfMfH7+tu/tB1yO4qrswkp7kSu7tMpR WulwuuyF4sFGb1U5hVWOoipxHFtJlV1szqqswsq84s+zHvvdtNWX9xvfzRwt TsZsVVZr7NW7957fFehOGAAAAGijaDQE56me+3/92wGJg7QFEmWzRZbMPaQO sxLH/3pa3vElv3fllLjsz7iynVW24gpHcaXorEZtLvXPypwi5WORZnZnpaNU OXhu0b+W/PaOiUvP6Z5kVq5Ak8zqcvoJ/fv94r77dKcKAAAAtF00GuqktI+a P/f+4r45c+efM/48JdNkk0U2RUpSSuf+N4+bc2DG7e8t/l2548mq3EKX3T3X 0Z1dtcbIaheZn6fsxRUizezFlbnOH1c5Tzqe+OcNu/dfts4+4vJBEV2VG7ZZ zeoUR6nfgP4/v/eempMEAAAA2j4aDQ317LN/Tho+RDIrnWaWLREmOUayJndM yEu58olZG99Z+ttv7U+5ckpduSWuHGeVOqbm2TwVVr1po2ZeT7kcTnXU7Fnx wVeZ+15b+OvfX37L4uGXDI3uFalcD6fculq7MVqv3r3v+6UygqbdKQAAAAAI DzQaGkQbrnrm2WcHDxkqm62i07RbW5tlOdYSObJDQtaoKx6fufHd9N+ULX/4 28zHfrQ9WZlbqCSbo6RK3ZQKq9nE46UVOc7KXJFmxS5bYXnW019lPP5p5sNv 3nDfby7Omztw8sCorp3lCKtslpShM5PVGtkrvk+fvv1/u+d3oX4zAAAAgOZH o6Fx/vKXvw4ZmmS2RERERsomZQl8ZQKkSe5q7Tgsps/UHsm2EZf9elrOK9fu +jL7kW9ynvrO/lR59lM/Zj/9o+PgD46D5fYDYvvRdvAH+4HvHU9953jya/vj 7y/73cErN+08f/myoVNTuw7pH9O9sznKKrrMJJtNckREhMUSOWjw0IOFRe+8 c+TUqXJX0CmO4nyioqLy8vLKyspa8Y0BAAAAmoRGQ6P9/aWXnSWlUy+5WL08 TVZmIlpM6miXMrrWwxqT1LnP5J4j5gyYlDvqqvzxC3dMzHgo7Wbn1Xf+ef7d zqvueOqK2x5JW/vAxTf+8gLbHWOvWzF0elrvMWO7Dhoc27ObJbp6cRKTyWwx KzfRlqQLp0xxOkv+/veXPCcQ/Bo0yY1SAwAAQBtCo6GJ/vbCC7/45X1Lly3z NJFJMllEWZlN6tiaZJGkLtZOCTE9hnTsM6b7oAv7JE/tN+bCPqMn9hxxXveh KV0HJsUlJMR0i5YtNV1mtlgtVtn9yOLFi++7777n//Y3z4vW5xq0+Ph4yQul BgAAgDaBRkOjVaq0j4998IEjZ6UjJzfb5ujTt5+njGQRaxar2aSs9iFLJuWG 016b51NltqS6p3dVxXTouGjxkpV5q95//6jvK9Zp586dko+4uLj8/HzxG9Ui 7wgAAADQZDQamqiqqqqiosL7kZ/c8dPpl142+6o52ir9DTJmzDniC2fPvvqK GTPtjtzv/vtf7ZjiJRq6un55ebluKI1SAwAAgPHRaGgJFepo1/N/e2HsuPEj R41OHj06ucZor83z2OiRo89OThn77J//4qp9oVlTbnzmdyiNUgMAAICR0Who ORUVFV988eUX9fO5ulU0683OggyleZeaSDmxZzO+LgAAANBoNBrCW/ChNA+R cpQaAAAAjIBGQ4uqaqBmP4H6DKVRagAAADAOGg1hz3cobfbs2XFxcUFKbffu 3aE+awAAALRTNBrCXnl5eWJioq7RxC9Vfn5+VFRUoFITX1JQUBDqcwcAAEC7 Q6OhPdi/f78uwcRvoHi8rKwsLy+PUgMAAIBx0GhoJ1JSUnRDaZ6n6lNqe/fu DeHJAwAAoP2g0dBOBBpK86iz1ETliYOE6vwBAADQTtBoaD+CDKV5HD9+PD09 PVCmUWoAAABoaTQa2o86h9I8WrrUxK/0oUOH9u7dm29IO3fuPOTGnQgAAABa GY2GdqU+Q2kedZbalClTRMXU53XFL/zu3bvF0SZMmBDkgMYk3rSsrKyCgoIj R440z48BAAAAgdFoaFfqP5TmIcJEpFyQhAlUauXl5Xv37l2wYEGQa9zanPj4 ePFubNmyRQRsS/yAAAAAQKOhvWnQUJqH+I2tf6mJD8IszfwS32M9hxEBAABQ fzQa2ptGDKV51FlqycnJw4YNa8kwMpykpKSCggIuWwMAAGguNBraocYNpXmI 394pU6Y0pWvi4+PFERYsWBDq1UECEucmzrD+V8/FxcWtWbOmrKyshX5kAAAA 7QeNhnbIdyitEXP2xJfUv9QSExNF9ezcuVP88rfAN9SyxHe6ZcsWUbIiLess tYKCglCfLwAAQNtGo6F90g2liU8bd5zgpSbSLC8vr/5zKY3v+PHju3fvTkpK ClJqaWlpDKgBAAA0Go0WUsc2596bKrYHjgXa4/kH1B1yS55vzfNqB4qLi3Vl 0ZT7nYlSi4yM9D7a7Nmz2+KQWf2JNzDIpXnx8fFih1CfIwAAQJtEo4WUaLS9 D52oa68Tryym0VqALjEaPZSm2blzpziILMtdu3ZtP+vSi+80Ly8vLi7Ob6ml p6eLv7yhPkcAAIA2hkYLKRotlMQvYTMOpZWXl2/ZsqVM1Ywn2SaI733NmjV+ My0pKSmcpnoCAAC0AhqtidxzEdXtrlc+rvWkeyqjCLE3azrr45K97vmNukY7 +dBd/g5Fo7WY5h1Ka+fE32u/i4rExcWRaQAAAPVHozWBmmBel5KpveZpLjW4 qp/V4kvrLOXjxSUn3Ueotf/mN93HerOkJtNotBbTvENpEH9V09PTyTQAAICm oNEaTSkyn7U+lDGy6rZSCq5WcwVvtJodXC7dl9NoLYmhtGYnOtf3CjXxSPu5 TA8AAKApaLRGUrrJ36VkNY83sNH0vIbVPI2mHOTe2ls9LmdDUAyltYSysjLd 3Q0k9U4EZBoAAECdaLRG0g97eXjSrGmN5n18xtFaGENpLUH8tSXTAAAAGoFG a6SWajT3siGsGdKKGEprIYEyrR0ufQkAAFB/NFojtexcR+99mOvYGhhKayHH jx8XUabLNPFuh/q8AAAAjItGa6zaGeVW15ohXqvr69berx19XsdhHK01MJTW cvxmGm8vAABAIDRaEwRfez+QgONoXgtFBhhHQ0vSDaWJrCgvLw/1SYUJkWm6 W6eJT3l7AQAA/KLRmsZrXMzPPawDfolXo3nG1GofzZ1+7ntk02gtzncobefO naE+qfCxf/9+3dubl5cX6pMCAAAwIhotJD4+oZ8kCSPQ3X+ZsZ7mtWDBAl2m cWNrAAAAXzQa4FFWVhYVFcVQWgsRb6/u3taszQIAAOCLRgO85eXleUeE2Wy+ 5557Qn1S4WP37t1MKAUAAAiORgO8lZWVybLsHRGpqamhPqmwMmXKFCaUAgAA BEGjAd58Vw5JTk4O9UmFlSNHjjChFAAAIAgaDfCmW4F/7NixoT6jMJSfn+/9 JicmJob6jAAAAAyERgM8fNcM4VbLLYH3GQAAIAgaDfBYs2YNqw62Dt3aLGlp aaE+IwAAAKOg0QCPpKQk73DYvXt3qM8obB05csT7rY6KihJ/zUN9UgAAAIZA owGa48eP66qB9QZblK6ICwoKQn1GAAAAhkCjAZqdO3cy+6416VYO4Q0HAADQ 0GiARnffLiY6tjTf6Y6hPiMAAABDoNEAoby8XLfS4PHjx0N9UuEvMTHR+z0X /1oI9RkBAACEHo0GuHxuXc2Kjq0jPT2dsUsAAAAdGg0QCgoKvGMhKysr1GfU LuiuARTJFuozAgAACD0aDXD53K5LtEOoz6hdYPgSAADAF40GCGlpad6xUFxc HOozahfKy8u93/a4uLhQnxEAAEDo0WiAy2fxirKyslCfUXsRHx/v/c5zJ2sA AAAaDRDi4uK8SyHUp9OOTJgwgaUdAQAAvNFogCDVFurTaUcWLFjg/c7v3bs3 1GcEAAAQYjQa4KrdaImJiaE+nXZEt/x+QUFBqM8IAAAgxGg04Pjx4zRaqNBo AAAAOjQaQKOFEI0GAACgQ6MBNFoI0WgAAAA6NBpAo4UQjQYAAKBDowE0WgjR aAAAADo0GkCjhRCNBgAAoEOjAaFvtKO7UiUpddfRQE/pnzxalJGa6jnh1NSM oqPeT7kfzxBfVJQhPsooqnXE6j1Sd2kP++7Simg0AAAAHRoNMHCjVRdarSfd 1Zaxq0gjmis1wyu33E8pj6eqLecVYNpXpyo77PI0WqrnAK2ORgMAANCh0QDD NprWUxkZGd5PVo96+Rtz83McLdpqAizIiF1o0GgAAAA6NBpg1EZz11iRd6MF n5jo+6zuEb+vdHRXRsiqjUYDAADQodEAYzaaGlfKY7We1D7xTHP0cvSo53n1 ErUM94THuhtNvFTIhtZoNAAAAB0aDTBio3kKzeWn0fzy6rCjoswyMqqvRat7 rqPyGI0GAABgFDQaYLxG8yo0/ZP+5jrWmgypU4+5jjQaAACAkdBogNEarVah +WRVHZecHd21y3s9EX2TBZxVybqOAAAABkGjAcZqNF2h+ckq7Q5oNQvs+yk6 v08edT/ivp5Nu4SNRgMAADAUGg0wUqP5FFqA6Yk1d6qWUnUL8R9Vb4zmfjLV M6zmeymb1mXuO6aFZrIjjQYAAKBDowHGaTQ/hdbMtzTzczAaDQAAwFBoNMAo jZbqv5VoNAAAgHaFRgMM0mhe0w99n2y2hFInQtJoAAAAxkWjAcZpNL8LdzRv o/k5vno3tV1FNBoAAIAh0GhA6ButHaPRAAAAdGg0gEYLIRoNAABAh0YDaLQQ otEAAAB0aDSARgshGg0AAECHRgNotBCi0QAAAHRoNIBGCyEaDQAAQIdGA2i0 EKLRAAAAdGg0gEYLIRoNAABAh0YDaLQQotEAAAB0aDRA/ILRaKFCowEAAOjQ aIDgnQlxcXGhPp12RNdo+/fvD/UZAQAAhBiNBrhqN5oQ6tNpR6ZMmeL9zh86 dCjUZwQAABBiNBogJCYm0mghoWs08W+GUJ8RAABAiNFogJCUlORdCkeOHAn1 GbUXcXFx3u98WVlZqM8IAAAgxGg0QFiwYAFXRbU+0cJcCQgAAKBDowHCli1b vGNhzZo1oT6jdqGgoMD7bZ89e3aozwgAACD0aDRA2L9/P7HQ+rKysrzf9p07 d4b6jAAAAEKPRgNcPpPu4uPjQ31G7UJKSgqLOgIAAOjQaIBGt3iF+C0N9RmF Od2tw6OiosrLy0N9UgAAAKFHowEa3c2U8/PzQ31GYe7QoUPeb/iECRNCfUYA AACGQKMBmr1793onQ0pKSqjPKMzpLkbLy8sL9RkBAAAYAo0GaMSvWVRUlHc1 HD9+PNQnFbbKysp073ZxcXGoTwoAAMAQaDTAY8qUKYzstI6dO3fqFmnhYjQA AAANjQZ46KY7sopFyxFR5v1Wb9myJdRnBAAAYBQ0GuAhikzXDtyxqyXo7kYn WrisrCzUJwUAAGAUNBrgzXcOnvj1C/VJhRvdnNL09PRQnxEAAICB0GiAt/Ly ct1aFllZWaE+qbAi/u5LtYlHQn1SAAAABkKjATp5eXm6iDh06FCoTypMiASe MGGC93vLbdEAAAB0aDRAR/y+6a5KS0pKYvGQZpGfn6/r3/3794f6pAAAAIyF RgN86RZ4FERchPqk2jzxF1/3rjKIBgAA4ItGA/xKS0vTrT3IZVNNUV5enpiY qHtLjxw5EurzAgAAMBwaDfDr+PHjusVDGPRpivT0dN0g2u7du0N9UgAAAEZE owGB6Nbhl1glvrF0N0QT0tLSQn1SAAAABkWjAUGkpKSQaU1UXFysG5GMj4/n ptUAAACB0GhAEL438xLy8vJCfV5thm+gCXv37g31eQEAABgXjQYEV1BQ4Jtp LPNYH+Kt8w00BiIBAACCo9GAOpFpjeD3TUtLS+NOcwAAAMHRaEB9+C2OvLw8 isMvAg0AAKDRaDSgnvLz8327IykpSfw+h/rUDKSsrGzBggW+b9Ts2bMJNAAA gPqg0YD685tpUVFRW7ZsCfWpGUJBQUFcXJzvW8Q1aAAAAPVHowEN4jfTJPUO 10eOHAn12YWM+N6nTJni950h0AAAABqERgMaKtBokXhwy5Yt4tc11CfY2sR3 7bt+I4EGAADQODQa0AhlZWUTJkzwWyWiVkSYtIcxtfLycpGrSUlJft+H+Pj4 /fv3h/ocAQAA2h4aDWi0IONHwpQpU8L1Zs2iQPPz80WFBfre8/Ly2uF4IgAA QLOg0YCmELWSkpISKFWExMREESwi1o4fPx7qk20q8ddWpFmggTMNC10CAAA0 EY0GNFF5efmaNWuCDKh5T/+bPXv2li1bDh06FOqzrltZWZk4T1GXosumTJlS 5zfI+pYAAADNgkYDmoUoGlEoQab/hbf09PQwGCgEAAAwAhoNaF579+4NtJxI +ImLi1uzZo3o01C/6wAAAOGDRgNagvgNT09Pr88EyDZq9uzZBQUFLAwCAADQ 7Gg0oOWUl5cfOnQoPz8/LS3N7y3V2pbExMQFCxaQZgAAAC2KRgNazZEjR0Tg pKenT5kyxfhXrokiE+eZlZUlGrO4uJguAwAAaB00GgAAAAAYB40GAAAAAMZB owEAAACAcdBoAAAAAGAcNBoAAAAAGAeNBgAAAADGQaMBAAAAgHHQaAAAAABg HDQaAAAAABgHjQYAAAAAxkGjAQAAAIBx0GgAAAAAEHKHDx8+4Ob7LI0GAAAA AK3vm2++odEAAAAAwAhEoGmjab5P0WgAAAAA0Jq0QDt9+jSNBgAAAACh5Qk0 F2uGAAAAAEBIeQeai0YDAAAAgJASgfPiiy96FnV87rnnfPeh0QAAAADAOGg0 AAAAADAOGg0AAAAAjINGAwAAAADjoNEAAAAAwDhoNAAAAAAwDhoNAAAAAIyD RgMAAAAA4yguLtY9QqMBAAAAQKgwjgYAAAAAxkGjAQAAAIBx0GgAAAAAYBw0 GgAAAAAYB40GAAAAAMZBowEAAACAcdBoAAAAAGAcNBoAAAAAtJrDhw8fcHM6 nb470Ggt6djm3HtTxfbAsUB7PP+AukNuyfOteV4GV5QhqVJTM4qO1mPv1BoZ Ra1wfobE2wAAANAG+eaY3wdptOYjGm3vQyfq2uvEK4tpNG/uRtNCbVcdmVZr 7/YbJ7wNAAAAbRCN1upotCY4WrQrtT6VpsZJnSXXXhxV3zQaDQAAoG2g0ZpZ TVspcxo3v+l+/M2S1JrHvRvt5EN3aTMb702965WP/RxHmfq4uORkK51/G1A9 OBS0wMKo0cqEJh6CRgMAAGhLaLRm1rBGUwKt1j6eTGvOcbSj1WNPXnMFdVd1 +e6hn1RYjzA6uivDfRT16NqXuMvg6FH14iivU8jYpbuwTNnD87TyrHZW+rbw XJkW5Fwa3Wiv78kQNhWV6R7RPVj2+p5NmzJq8Xpaedbz8J6i18uK1E/3vK57 sbKiWkfxfgH3DpsCPdUQNBoAAEBbQqM1swY1Ws2DGq8vadlG01+h1PRG89uB Xq9R68oofy8QcA99W3jtF7g6mq/RPIlW86BXgflrtJqv0NE1ms9+NBoAAABc NFqza/BcR29ew2p+G005yL21t3pc2ubpp5ok83SO/r/bfXZ1q6PRjta+TMyr 2DyNpo6Meb7ac2GZewfPK1cfwfN87XOp3YIBK6y5Gs0TSTUPuh/atOd1v93k fn5P9e6vew5Ru9HciRbgMO6jvV60RxmJa/A34o1GAwAAaEtotGbWlEbzHlZr iXE0r/9IPxpg6Y1GNlqQV6hjrMuzR80ZuWdA+jtC9WPiNLSvDpRhzdRotYa6 tAerEyzwwJan4Txl5am21/3s5jMBUn+4stdfb+oFaTQaAABAW0KjNbPGNJp7 2ZAAa4Y0mb/YCdBczddo7q8IVAa+Y3mBJjv6hp96FkEjrXkarTrR9uzxejDg TMaa3Aq0S2MaTd2taTMdaTQAAIC2hUZrZrUbLdVrbUZ3ggUaR1NKrWb9xrY1 17EhjaYtHuI/wXTriuh3qH0SwSKwORqtpqJeb1ijqYNfezbpFxWh0QAAAFAf NFozq9Voex96U3yqiymvRlN2romsj0v2+l3Xsclr7wdaESTV97/a62o03zU+ tAf8JJxvQnmv2+g+g6DrROrORf8iQSKtGRqtOsZqPgw417Gu6Y9NmetIowEA ALQ7NFozq3uOYq1xNGV87YFj6of1GEdrJP+N5rdg6mw09bmjvnt6Gs6zpr++ oGpPZVQX/9fPs8zwXlbE55I53w4MPLjX9EZzz3N83aWbAKm/3qysZvGP6mOU act8lHk+3ZTh23D1bDTt4HVdtFYHGg0AAKAtodGaWb0aTR1Z80qz1FqPqOHm NU+yyfTh5Vkz0WcWoVeH6Y7hLq6MgDsGuJxMt2yj96IgAU7Tf0r6XeXE+/o0 39NtQqPt2eM9NBZksUd/Exn9Pq9PvMB7+DkfGg0AAKAdodHaAd/BsUDTCOtq NKV6amYs+sxU1F1p5n2k2os4BjrRol0ZuttcBxxVC/SteZ1u0IvntCe9P1b5 WcnR342tlSXxa9+mutZLqE97rdq/aU+RflStGRot6DfiuyONBgAA0DbQaO2A 75ohunuTtYjacx1rXrImI5Qk29UyZ6A1mji6wmdOZc3NtYM2mqeMfBut6eo3 1zHopW5BvxFtj6PqG7Arg0YDAABoO2i0diDQmiF+/qtdmwUZdCmP+tJfj+b/ LFooHGqNC+pew/vEfJYdqWk0ry4KXaMpS0Qq/D4V9Bvx3qPlgxwAAADNh0Zr B/zUkTKN0M9lYZ7/pm/MpVz+j1XrDtS15jIGOIdmUT2AVORvHK1+jeZdZC3R aO75kE241KzuRgv2NgAAAMCIvvnmGxoN3lpwHM0wvFeDDH7bN4MLm28EAAAA GhFohw8fptEAAAAAIOS0QDt9+jSNBgAAAACh5Qk0F9ejAQAAAEBIeQeai0YD AAAAgJASgfPiiy8ecHvuuee0x7Vr03QPetBoAAAAAGAcNBoAAAAAGAeNBgAA AADGQaMBAAAAgHHQaAAAAABgHDQaAAAAABgHjQYAAAAAxkGjAQAAAIBx0GgA AAAAYBw0GgAAAAAYB40GAAAAAMZBowEAAACAcdBoAAAAAGAcNBoAAAAAGAeN BgAAAADGQaMBAAAAgHHQaAAAAABgHDQaAAAAABgHjQYAAAAAxkGjAQAAAIBx 0GgAAAAAYBw0GgAAAAAYB40GAAAAAMZBowEAAACAcdBoAAAAAGAcNBoAAAAA GAeNBgAAAADGQaMBAAAAgHHQaAAAAABgHDQaAAAAABgHjQYAAAAALeTw4cMH 3JxOZ5AHPWi0lnFsc+69qWJ74FigPZ5/QN0ht+T51jyvUDu6KyNVk7HraCt/ NQAAABBSosjq8yCN1jJEo+196ERde514ZXG7a7TUjKImH6UoI5VGAwAAQFtD o4UUjeYfjQYAAIB2i0ZrIvdcRHW765WPaz3pnsooQuzNms76uGSve35jTaNV P1h72/ym+gU0WuPQaAAAAGiDaLQmUBPM61Iytdc842InH7rL86z6cXVnKR8v LjnpPoJ7fyXEAoypNUOjFWVIkhQke9TnfXk1Tl1HEGElmii15ktFZfkNpNq7 SX4zKkCjaWdZ+yvErlKAM6PRAAAA0AbRaI2mFJnPWh/KcFj1aJpScNUDYcKb JXU0WvU+/jKtTTRadSvp+HyBzws1pNHcr1LzNUEKjUYDAABAm0SjNVKgYa+a xxveaNVf7nnW+0H1a5WD6OZD1uNyNkXdo2B17Vl3o2Vk7Co6etTrgVTfr3A3 lv8hNu/dAr2Ud6Xpi83nlGk0AAAAtDk0WiPVNJeOJ80a1WjuHWqN0LXCOFrd e9b/CBr//aQepe5yCn49WvVBioIXGo0GAACANolGa6QWbDSXPtPaUqMdPVq0 K8M96/H/2bsTwCjqg+/jM3vkIkC4AwQIIBCOYAARDIcIilFBUA7x4IYce4Tg yWmUalE5K1pqW5uqtdQDUSDJJtpSbaVva9u3fZ8+5bHUUtvHJyriU6oQjmTn /c9udrPZO8kms7v5fp4pz2Z3dua/sxNnfvlfvkEr3K2EGDPE3WIyxFpkNAAA AMQcMloLtVFbR7/bj4m2jo5VGsPZXv/NGSOU0dyd38hoAAAAiDdktJbyjFqN Qo0Z4hzgcZ/v2Ps+FXNeQz5Goh4tnNE6gme0pi80XdU16GLQrmYRyWgNRdnr r8Nb0/XIaAAAAIg5ZLRWCD72fiCB6tHUrblDn2O6NFcui6KM5pHCTnqlNucb G7epNnrc2wZtHT1263dYEs81yWgAAACIOWS01vGoF/Mzh3XAt3hkNHedmseP xe7J1NxzZLd1f7SmIS5ARsvN3+ud9TzW9JMDvSrZ/Gne2Pve1XlBR3YkowEA ACAGkdE08fGn3o0k21iEMpoaeU66xwTJzfeKQJ7jhaivVpz0v/mWZjR/s6EF SWlkNAAAAMQgMlrH0NyR8zUuR6gxQ8LdGRkNAAAAMYeM1jH4rcfSIMGEn9Fy 91Y4tKSIJ51vVTdCRgMAAEBsOH78+BEX31fJaHEn3IzW0HKwzWrc1PAVTn1e Q8pqXUZr4bsBAAAAzZw9e5aMBg/hzTsGAAAAoA2IgOasTfN9iYzWYbV1PRoA AAAAv5wB7dKlS2Q0AAAAANCWO6ApjBkCAAAAAJryDGgKGQ0AAAAANCUCzvvv v+8e1PHdd9/1XYeMBgAAAADRg4wGAAAAANGDjAYAAAAA0YOMBgAAAADRg4wG AAAAANGDjAYAAAAA0YOMBgAAAADRg4wGAAAAANGjsrLS6xkyGgAAAABohXo0 AAAAAIgeZDQAAAAAiB5kNAAAAACIHmQ0AAAAAIgeZDQAAAAAiB5kNAAAAABo N8ePHz/iYrPZfFcgo8UTSZbdSyBS0yWk5q7fthrKIbmLotPpJEnq3bv3Bx/8 VhyB+vp6rb8EAAAAIFy+cczvk2S02CVL+rhfJM+85spoffqkf/Db3ylkNAAA AMQUMlrc00l69xIo44SzTmvWb+NFJ0tqLZq66NR/nRmta9e0X//6NwoZDQAA ADGFjBb3RnbJyHItI7r097tkhbFOa9Zv62VU577DO/fpk9I1SW9UK9MkqWfP ng8++OAXX5wRR8But2v9JQAAAADhIqPFvWemFwVf9gX9sfXrt/FSqBZgmnX3 9IJbhkzqltBZL6uVaFdeeaU4bRQCGgAAAGINGS3uXbIcje/louXoheLK/173 asGYW3rqOhtkvTOjiTNKIaMBAAAg1pDR4p+5Ks4Xk1hsfyt8+dYBk/SSbNQb REYbO3bsZ59/rpDRAAAAEGvIaHGv3lLRXkulc6lreNxO+7VbKi+Yjvx80Y5r eg4X6UyvU+vRJkyY8Pnp0woZDQAAALGGjBb/LJURWezmCrE0PHYkI/FjvblS LHZTpb2oUlEXm2Kqspur6i1VdotNEeuby+3W8kiVwU+pxL9W29mCg2Uz112R 1l9yuGripJ+/+15dHcM5AgAAIPaQ0eKe3RFkIrGIXFZuF5nLVK7GMbNNKbYp 66qUkiplfZVyb5V9ve2i+ci/8g9+svLHH979/Mcry85b33QEtIrIlcFnMYuM VvXZ2p9sGre4T0p35zD8ty9YpPVRBwAAAFqIjBb3mhV5mtRPuR6Ipd5coZiO KJZypaRSxLFLxUdrVr/8+yX73p73+KE5W16aff9zs9btnlawbfI9GyYsto6d tyrrRsvovLKZ1v9e+3KduVxpVuxqzqIWrLj61JqXbh1wTZI+UadXM9rcW+fT xBEAAAAxiowW91qVgNSYZlOsVcq66svFR04Xvfofy7/30wU7Xr7xoW9MXLp0 2KyZ/XImdB86LLVfL2NaopRgkCSjJOnVTmFqVrqmy5Cjcx49X3hYbKRNM9qf Vz0/tutQsUeDXh14/9Z5t2l91AEAAIAWIqPFvWZVool/L1udj21KcaXdWnnO 9NZ/r/7Rn5d9752FT+y/zlI48qYpXYb316V1k5JTpcRkOcGoM+ployQWnVgk dRH5zJHRRqb2f37mvV8XvKlY2zKjWav+tPx7V3ZxZDSDOmDIvPm3a33UAQAA gBYio8W9ZgU0dVFHs7eJH2uL3vxk7Y8qb3/8vnG33ZCRMzwlva+hS5o+OVHW O7OYLItFVqvNdJJBJyfq9EmGhE6GpG6GTr0SuvY0dLkrY8r/Xfrti9Y2aeuo eNSjfbi6bFK3LHVQx4aMRj0aAAAAYhUZLe4FyTheAyQ6Rm6sVIoqLpqP1Jhf OXrrtjXDZ4/vnNknqXOyXqfWjklqHZlelhJkXYKkT5ITOsnJ3fXJA5O6j00b OC195LwBk1eMmL0+Z8GWq+9+dua6392570LRIXVox7apRHNntFOrX7wxfYJB Z9AbdNSjAQAAIKaR0eJeiFqzxuqzCsVcWW+t/Nz02pE5j5rHzJvYa2SaIbUh l+lkg6QzOJozdpIShqX0vSnjqvuy5z873fT6LZvL52/72e1PHF+063dL9v3p nudOLi/7x8of/e/a1y8XV9SJxVruf4+RyWiVSnFVzZqXV46Y3S2hk9HRxtLd H42RQwAAABBzyGhxL1RGs9nNVXWmKsVS9a/814/e+vgDOYuv65OTplfTmU6n M4j/qcOAyBnJvab1zV4xYva2yctfuPH+dxY+8Zdl3/+66JBS8ray/h2l5B31 wTqxVIvQpA4zYrGpU6cFSYURWRxj758peG335FVDOvWWHbV9GQMHbHvsG7W1 tVofewAAAKDZyGhxL2BDR5FuTGKpUBdL9V+Wl+3NzZ/Vf3wnOUntZ6aXDY6u Zl10iVf3HJ4/Mm/X1II35pT++Z7nzlveVO6rtpdUK9a37abqelNFvblxcTaY tJs9dhR2QGtZjhNhsNZ0+N3FT03rNVLtkmZUu6QNGzH8f2pqFKrSAAAAEGvI aHEvcEaziXRWbyk/Zzn0h6Xffmj8HUOMvfQinanVZrIs6dKMqWO7Zy7Luv6V Gzd8kf9KvdVWZ3Esap+1KkWkM3N1naXaHolx9b1yXPixrmF9q+104SsFw2/s okuSHcPv54wfd/bsvxUyGgAAAGINGS3ueQUfjxFC1MEb/2099Ms7dq8YcV0P fapB1utldcjGroZOo1MGLRtyw4G8Tf8o+PGFosP1aqCrthdV201VdpMzlFW4 lta2Y/QYUrLZSU1xTOImcuKlosM/uOHeUT0GOUY2UevR3j9+XOtjDwAAADQb GS3uNc1B5Yq53DHQYrliOfpVwRs/W/Dk7UOmdjUkG2R1TjODpEtP6Lxo6NSf 3LL1o9U/Pp//ptok0mKrd2cis2NpfjvGkBmtXhSpqPySqfySpdwztQXPgI0v FZX/Yen+uZm56ixpsqw36EeNHvmnP/2nQlUaAAAAYgoZLe75yWimcsVa8WXR az+Zs/Wm9AlpumSjJOKZTi/phif13TZp6e/vevpc4aF6a7VirWpZ48NmBTTF lf7OWY/8Ycn+fyx7yTHkiDO4hZvRFFPFmeJDm666s6ehs0FnEEmtV7duv/71 b8QRqK+v1/pLAAAAAMJFRot73hnNVG63VnxR8PpPbt44pW+2UWcUccYo6xIl 3dWdh+ydVviX1S/WWyqUIpGP1OozJUCkimBGcwa086a3bEueMg+f8/rsLZfX V9c7nvSuLAu6hcvF5YfnPHJderZONupkXWpy0o15N//fP/xRoSoNAAAAsYOM FveaxpwKkdEullT8YtHeW/tNELlM/J9e0nfSJczqO/qFWcWf5R+4bK2qVwfk rxCBLmQ+an06UxdHFvvb6h+uys5L13V9cNyif6w9cNlc4Rh2MqwuaernMtvs ReX/XPuj4itvlSWDXm9wTrr9wgsvKVSlAQAAIHaQ0eJek0BkrlLMb59c9cKD Vy3upu9klNUx9rsaU/IGTPzJ3I1nza/WWY/Ym3Y3a6OA1lAka7m6O3P1Z/mv 7Z9mykztLVLVzL7ZR+Y/olaimd62m6ubUQZThbKu6nsz1/VP6qnX6fSSlJCY /MahNxUyGgAAAGIHGS3ueaaYektVrenwD2auH9l5YKJslNRJ0Iw39ZtwaP6j X5YcqjcfDdn/K9L1aBXi3wvmw5W3fmNK1xHJcoKkk3sZujxy9V1fWd5UiqoV c1UzCiPiXrHtl4t2zRuSm6hT69GMCUlbtpaePn1a6y8BAAAACBcZLf415Bd1 aulLxbZji566bfA1ekmvjuKoM2QlDzgwe+M581t2tW2hzW6uaoeM5q6ns5tt l9ZV/Pbup1ePuL6zMcUxd7Y6u9mcwVe/f/e36kzqJG7N3LLt0zUHvjFpaVc5 SdZJOp1Bb0j41rf2KVSlAQAAIEaQ0eJeYyWaqeKzgtfvz1nYTZ8s69S5qvsZ umyacOffl72oWNUQp5jbI5157qLeXPWP1S8/MXl5v4TOepHQ1Bm01V5kmV16 P5m75rzpqGJpZmY0q80d35xXOrxzP4PYmGOAx527ditkNAAAAMQIMlrcq7NU XbbaFIvtvPnIc9etz0nL1EuSrNelGIw39hv360V7LpuP1KsjhLRL3ZlZHQbE MWaj7bKl6lJx5euzN0zonpkoqcOXqAlN5DSdZJSkRZnXnFpZVq9O5daM7atd 0oqrfrv023cPnZ5sNEqOxLdj106FoR0BAAAQI8hoce+ytapOzUQVn+W/sjRz ZopkNBhEdNEN79r/+zff+3XB64q10neM/TZMamZHx7GiigvF5b9Z/K3lg2ck S4YEEc5ENhOJSs1oarDK6Trw5Vn3flV4ULE2p7mjY4jIM2tfeW56Ue+EzmI7 Op1uTPaYl17+kdbfAwAAABAWMlrcq7NWKebKC6Y3f3nH3txeIx2xRe6RkFYw Ku9UwQsiu9WbKprXnrC1tWk2sdM685G/FfzowZxFfRO6yXo1lBkS9cNHDena I1UdMV+Wu+gT7xoy/W+rX3TPox1mVVq9SWy/8lcLd07sOlSkPnVqbklatnyZ 1t8DAAAAEBYyWtyrN1crVtuZoteenmoalpouyZIILeN7XPHG3C1fm96ot9rq zbb2CWiuejR1qMavzG98f8b67G6D1XQmSzqjPHBYv6Vrbh9/zUhDsl6tU5Ok kV0H2OY/frHwcLO2X2+qUta9c2Ll84sHX5tiTFJbT0pSQT4nDAAAAGIDGS3u 2QurlOJ3Pl398uohs3voU2W92qLwtoGT/rLqxQtmdXqydhtv39Ul7e3LheW/ vHPPDenZRnV4SRHR5J690+Yuuf6BR9csWn5j+sBejqo0qXdCl/uzb/v76h8q 696uVwecLA9eyIZ6NHUE/uq/rXmpeOyC3oldJUc9Wv5aThgAAADEBjJa3Kuz VClm23/e852ru2Wp43Lo5a6G5PVj5p0pPlxnVZsFtuecaI4JsqtOrXrJMvyW PsYu6kCOsi65c+LEaWNLHl6zdYf53odX5UwepdZ96SSjbLimyxU/X/xUfXGl 3RR2RhMPrFWfFrzyxNT8ASk9JEeVXP4aThgAAADEBjJa3LtYXHku/+CBvAcH pfaRHMZ2G1g2o/i85ajdYmu3ejTXnGi2fxe98cq8LWNSM9ReZzqDpJeGjh24 9oElm54q2LKzYMtTpjlLruvdN02NVjp9b2OXb05Z+c/VLyuWanuowScbM5rF 9r8Fr5XdcN8Vqb3VsCdJa8loAAAAiBFktLh3Jv+1f6x68aHxC3onOsY5lKQ5 A6/6zcJddUVHfQNOm1eirav+64qyopF53ROSHXlR12dgn3nLb3xwx9rNu/O3 7BIxrajoobtyrs5yvKhP1huv7zful4v3KuveUUwVjZNfB16cGe184aEjc0tH du6rzromSfn5hVp/DwAAAEBYyGhx71cLnvrz0u/OG3h1ijFB5BWjpDONmft5 wat2U5vPidaY/szl9Rabvaiy1vxWxbzScan9dTpJ1hlkWZowdcy92/I37ija vLNg887CTTsKNj5VeNOCGcldEnQ6tbdaekLX799QcsH8lhLGXGmKM6OZKy+Z 3/r5oifHds1wVh0OHTp0955vMY01AAAAoh8ZLe59O3ftr5d9+9oeIxN0er0s d9d3evSa5RfXVYiM5py6uj1aOYodmW2K1fbRyh9uuWpJDznZMQ+arneftHl3 3rBlV/EmNaMVOpeH95hXFi8ePnaIXq+2d0yRjPeNnf/RsucVa8P0ZyH25cpo 792xw5nRDEaj+Pea3Kn//vdXCpNZAwAAILqR0eLeqhGzjtz15OTuw4wio0ly RlL33dfm15fYFFN7VKI1LOYqddCPkqq3Fz45vc+YBJ1aoycS2OTpV1o2rdy8 0+QOaM7l3kdXz5ozxZCgdiVLkBNuybjqndu329fZmp3R0tSMpjcYxL8zZ91A RgMAAED0I6PFvWl9R++4rmhc10yj3iDLckZitz3T8+vXqyM6tlMlmprRqpWi qgvFR78/a30fqbMsG3Q6OS0t5fZ78rbuWrdRbeVY4A5om3YUbNlpWrj85uTO RlmWdLIxq1O/F264T0Q8e6hc2ZjRTG+9u/gpZz2a3qhmtGnTZ5w9+2+FjAYA AIDoRkaLe8O69l84clp25wGJ+mQReDISu++dVlhfUtU+Gc3e0Eesqt5a+d+r fvjQ+AXJ6oxlstGoGzl2yMqSxVt3F28SAW3XWs+MVrrbsty0IH1AD4NeJ8lS kpSwY/JqdfzJMMrs6I9Wdb7ozYr5j43p3FfNaGqjSXne/NvPnT+v9bcBAAAA hEBGi3sp+uRhqenDOqcn6RNF3mn/jOaoR7PZ19l+ets38zLGJ8hqNzNDgm7m zVNKHlm1ead5s1dG21nw8G5z4X13Zo8flpCgVoGJTHfv2Ns/XX1AcbV1DFRs R983m2Kp/rLgtednlVzRqadzzJBb5976t1N/1/qrAAAAAEIjo8U9Sdan6pP6 pnZP0Ce4M5q9vTJaw/ZNVUpJ1f5ZxZlJvfSOSaVTuibesWrell3mTTsKN+8q UJfGjFa4ZVdRycPLrsubmJiiDvdhlHTzM6e8v2B3yP5oDfuyVv9P/svfyF3W LyXNMfS+VFDE2PsAAACIDWS0uCfLugSdITUxxaAzSLI8oH3r0ZyD4debqi5b yx+5+p5Okl4ny/oE/YDh/dasv6t0r6UhoHlkNHXZVbTxiTV3rLy5U9dkZ0Yb 3334T2Y9ZLdUKBabc7MBS26yKcVvf7S6LH9UXlpCiqRTQ9qqNWu0/h4AAACA sJDR4p4si2Qm63U69V9JTjd2fnLK6rqSaiWcOqkILSKjfbr2gDl7jtq7TJYS U4zjp400b7pr627Tpp0FXoM6OqrS8h/ebVpz7x1p/bqK0ut0uj4JaU9OWl63 rkIxl9c5BuH3nc/a+bjOLDJa9X8u+85NGVclGYzOaru1a9dq/T0AAAAAYSGj xT3ZEdIkNaipgySmSPpNV91Rq4addstotjpz5Z/u2n/3sBmyo+lhUmrC9Jsm rnt42ZZdRZt8ApqjHq2gdK/JvGnZ4DEDDUaDiJcJkt6SddO/zG8opvLL1so6 q823Hq0xo5VU/3bpvqvSrtDLehFO1YyWn6/19wAAAACEhYwW9yRnPHOQDGpE Wj3q+k8KXhYZTbHa2qG5o1gumcvfu33HzQMnOjqHSSmdk268ffp921aJjOYn oKlLwcO7C9c/sjL3hqs6pSY733XboMl/WPady+YjiqWq3lLtbPTom9HqzRVK ceU7i58YnJzuHNRR/chraesIAACA2EBGi3spnTo5q9LU/zk6Z900YNwvFjyp ZhlrqL5dkVhEmLpsLX/rpq1T+4xypq3UrsmLVs7ZsN1PK0d3Rtu6q+DBb66d f09e9+5dnWMzTu096uCc0vOWtxRzlb2o2h4go4kPda7gjR/dcH+fxO4NGU0n W9YVa/09AAAAAGEho8W9R7dtkx2zjEk6R1WaJI3uOui5GdbzlqOKubJeTTpV bZ3RLlornpu5LjttoM6Rtrr0SFlRvHDjriZTVzddTJt3FWzaUbCy5I5e6d3U qkBJHpU24JlrC782v2m3VqsB019bR3UONWv1Jyt+vGXS0m7GTuIzi7euXpv/ yf/8j9bfAwAAABAWMlrce/X119SMo9fJjmFDJFnuqev8YPbtX1neVEzljtHs 2zyjXbCWPzVlTWZKL50jJHbv26Xgwbs37ykSKSxgRtuZv2VXkWXLqr6Dektq vtQNSenz5DXLvwqc0dRFbehY/dvF++YPuibJkCDr1IaOTz/zrDgOdXV1Wn8V AAAAQGhktLh38q8n77z7LucQ9CLpSHrZIOkWZOb+be0L9abDItTYzVW+fbtC xa7GJZyMVlt8dMOEO7olpOp0kkiKGUN7mzct3by3MHhG27rbVPJIQcbQfpKj meag5F4PT7zzrPmQYqm2B85o9pKqg3O3DknsqdOLVKpOgf349ifEcaivr9f6 qwAAAABCI6N1BH//+OMFixZ27trFWaEm/p3Ua3j5vG3nTG+o6czU7IzmWmx2 j9nKXIvNc1FfNdvOWQ8XjLxZ7RimkxMSjaPGXWHdskzNaEHaOjZktPyBwzMk nZrR+id1f2jCYnVoR1dGc+3FnRbVJ78oeO2paSu7yGo6MxgSrp50TYWtShwE u92u9fcAAAAAhEZGi3vO+qOP//GPgYMGq1VpejWk9UtJ2zT+ji/zD9av++ll i59x7INXook0pHZkK6q+bHm73qzOVuZc6n2WOvG8qfKLotfuGjJNTYg6fVJK 4lVTR68vXbV1tzlgRttVIF4SK9y7bfWQ0Rk6vWSQ5O4JnazZ885YXrdbxWYr PPfSsHeTOsP1H5Y8vWLErC5ygiRLBmPiq6++rlCJBgAAgNhBRot7zvqjz0+f zp0yTaeO7KgzyOqcYdN6jvr9Pd++WGy7bG1WOqtUB+03OR4UicdVivmnjYs6 JL7XIlaoPp3/6qLBU9VRFmUpuVPS1dPH3vvI6i27TAHbOu7KV4d23G1av21V Vs5gg1GdiDpFn7B6+OyvTAcV0zve+3Lu3fRTpfjY4bwt49OGGPRqPZoxIen1 g28oZDQAAADEDjJax3Hivz6cMm2qLEkGx5Rh/RK7bRm3+ONVL6gj8Jsbe5mF 1RnNpFa91VuPnLEe/NT8+mfuxXTIsbzhWByPzYe+MB/6W+GLC4aoGU3SScmp SZOudWS03cEy2qadBSLE3feNNdlXDTMkqr3pjLL+jsFT/1b4wy9MBz8zHfzc sXHXXtS9fy6W4je2TVuRKiWLDyliXUJC0oGfvKqQ0QAAABA7yGgdyh/+4//N uO4656xhelk3skvGizc98K+Cg4rFVt+cqrTL1irFXPFvyxtbx915XfqY2Rnj bsjIEcuN/a8Uy2zHvzf2z1GXjJy8jJyZGePSU3o5RsKXkjolXjV1jKOtY5CM VuDOaOMmj0pINjrn4E5P6TGr/7hZAybc2H9cnnP7juWG/ureZ/fPESUZ3mWg TtI7h7DU6Y2vvPqaQkYDAABA7CCjdRzOnPKb33xw881zRHwRGSZBZ7yu79jy W0trzW/WWyscYzxW2IPWpjlesl1SGzpWfGF+c3b/8VLYnLOzJSYn5kwauW7r yq27g469vyN/y87C9Y+suiJrgNpAUzbone8Pg05tyyl16dLlgQc31NTUKAwY AgAAgNhBRutQLl++LP59asdOx5iHau+0ZCnh9gGT3rntmxeL31SKjtR7VJYF rU2rUta/ffb+8lsHT24SjsQWHVOSeTyjc3JWhKkZLcmQM3HkA9sKSvcErkfb adqys+ixfes3PJbfd0B3Z8JruhfZWSvnTGSeZPVV9aU+6eknT/5VYWY0AAAA xBQyWofirE56660jY7KvdFZsyQZDimRYcsW0d+968qL1zTprhT3w3GcNY4ZY q06veeXwnIf3z3lgXM+hqWmdrhg5aNSVQwcPyzAa1TnJ+g3ql5UzZGTO0AFD +urU2q+GgObMaEajPCCz75xFs+7btnLLriK/GW3rHtO6h1fesXLOrQtnde/Z WbyrW4+0oVkDxDaHjBhgTFRjYPqAPmPGDes/oIdjXm7n1l2LY0ddu3b9xmOP i5NH66MOAAAANAMZraNxxrRKW/WIrCx1uERZnVS6kyFx6fAZv71n3yXzEcUn lHkOJ1JnrlBK3jl+x55hxt4JUpJO1o2bklP04PKtO0pWF9+dmpoqNnf73XO2 7rRsecp8x8q5xiS9OpqjY0fO6KQ2spR0Can6ewpvLd1r8a1K27gjv/TposWr b9Eny455qI1i/SsnjjHdf8/DOy1F99/TtUeq2M7cJbMe/9YD8xfPVMd8lGTP GOiuSktMSvkJY4YAAAAgppDROqyf/ezY0CuGO0biF0FI6m5MXTss78SyH1w2 Vyrmt+1mW7213DOd1VsrLlsrxaKs/9mv7tiVnthdjV2SND4327T5ztJ95jX3 3Z3SuZN46valc7Z+q2TrHsuS1fMMiQZZMjRkNEdKEz+K1JaQpF+eP/fRpy0b d67dvLNgi2OcEBHQNu0q2riroPQZ86I1N+sSHZViakaTsq8eadq49OGnLaaN y7o4atbmL5mx/Tv3zb1rpmvLHjHNFdYMxkTGdQQAAEBsIaN1ZO++94srhmVJ jmEedZJucEKf+8Ys/Gj1C3VWdQY0xVLhWZt2yVotglut6fBX9x2puPPxjIRu 6nj4Bumq6dlFG+/avMO8Zv09nXt00iVLC5bdsumpdZueKl68Yr4xQWQ05yCL 7hylkyRZZLSlq27busO68Ql1KjR1QjQ1o6ljOW54QjwoWrD8Zn2CXicbDEl6 KUG6Mndk4UNLN+80Fzxwd1qfzpJeZLTrtu2975bF16vNKZtmtMZ2lQlJL798 oK6+nowGAACAWEFG65jcoxxWv/2Os2+a3mgwiJiW0mfr+MUfFbxoL66qM3s0 ejRXKgVVl++v/vEtm24dMGlqv9HJslFKkqfcOOke08K5d8689uaJeQtmLlox Z/HqOYtW3ZJ3+7VTbph4xaghenU4Rp27CaKzw5ja4tEgD8jsN3hUxpw7Z5Xu Kdm8q2ijY1q0rTtNeQunDB7Vt9+gXiLWJSUmXj932pI18+5cO2/ePbNn3Hz1 jQuuXbB8zh2r5uXdNuW6m64ZOXa4pPOX0JztKvXGnHETpl973Z4939LycAMA AABhI6N1ZM6+aeUVtvHjJopEk2DQJUryiE7pu6eu+WTNgcvr3q43VzR0STNX XlhX+aO8jRN6DGsYTVEEoGTd3Wtve+AxU+7McZ26GkeMG/LgY0WP7r134Yq8 ISP6J6UadUa9c5D/xg5jjgEa1f/nGqYxLb3rLXfO3LTDtFEdP2Rt6S7zuGuG uwdyTO2ctGb9nd94+oH1D6+ZljcptVvKsOxB928r3PZ0ycTpo8UukjulSI3b lzwDmnOGNOdeli9fqfXBBgAAAMJCRuvgnOPSHz5yNGecc6YzOUGWx3Ub9OwM y6drX60vttVbyu0iqRXZzq0/unL4TLXGzWB0jMghywZJxLGHvpk/eeo48Xzv gd3XPbx6y1PmRUtvzBjY253LmozoIbsmOXM80hvVDDUie+Dmpwo27yrYsLNw 666iq6aOclaBSeqE18YVxYsf3m2679GVU6+/WjzTs19ny8Zlm3eaxowb7tiM Xm1L6dsnzRXYDAaDWC0/P1+hVxoAAABiARkNzphWXl45JjvHaEw0yrJR0k/q NuL5mfd9WXSw3lKhmG2K9R3lvuqCMbc4Oq/JSSkJvdJ7pA/qudy88L5H1864 aXKPfl1GTxx672NrHt5dPHfJ9b379fKJZl4jejj+T68GttE5V2x5qmjLzoJN akYrdGa0pJTEnundB16Rvnr9ktJd1vUPr5g595pe/dJG5mSuf3hV6W7r2AlZ jsnRDI0ZzScLyq4BHgsLC7U+zAAAAEBYyGhQXBVMrx98w2hMEpFHMuoTJMO1 fbJfydtwtuj12qI3/3P5d3+xat/cYVMcA3HImcP6zb8r746Vc5cXLlpqWrh4 7dyFK2+6Y/XN91huW2ZZPO6aMSmpSQEzmqOho2dGG5k97KHHizY9VbThiSIR 1ibmZosn+w7oteCemxevvOWO1XOXmRYuNS1akj9v0cqbl6yas9K8cLV50dAR A7zr0fzt0JnRFixY8Nvf/f7PJ/5L6yMNAAAAhEBGg+LKaD9/970ePXvLeqOs kw2SlCIbZ2bkVMx/7Lcr9l/f+8qMpG5pxmSRqTqlJlw1ZfR9j6596LGiUTmD x0/PLti4dOOOorXrF/cc0C2pS2JiklHX0OkscE2ac+B+nZrRMjL737l23up1 i5dbFi4rui1rzBXiyStGDnjoG0X3PrJm3JSslJ5J46fnFD64fPNTpqIH7k4f 1CM5NdGY5JxzLURGc2RCKTU1Na1bj2typ37++WnF1REPAAAAiEJkNLidP1/7 0ksv9+qtdiXT69T41EmXctvga5+evW5QsrN/mdqTLKVTyqTpV27YVrT5ccug Eemjr84yb1j28K7iNevuFC9JLn46ovnNapKUmJjYo2f33n269+qT1rN31+SU BPHksJEDNn/TfP+jq0dPuEIyStlXjTE/sKx0l7Xo/qWdu3VyDxLi2I//sffl xjVk57giQ68Y/j81NQoZDQAAAFGMjAYnd2x58cWX+vfv75w0TeSbLondcnoN 62xUh090DtFoMBh69O6WlT1kZPbQTl1TunTvfMXIjNE5QwYP6280GpoksHAW WZb8Se2cNCJ78LAxmV16pEp6Q9ce3YaOHDBy3NAhIwYmJBkakpckh0horpjm +CzSiKzRNTWfKmQ0AAAARDEyGtzcyaWsrCwzM1ONYyLaOGKQQWramtCVpNSp ySSdO1jpHP2/WkCv0zsWg1jUn3RNNivrjJL3XhyTrjkryFxj7wfZvnN0x6yR o2s+JaMBAAAgqpHR4MnuIB4899xzgwYNUmOaCEM6RySSAtR4aSp4ZZyXzMyh 4kxTyGgAAACIYmQ0+HIOIfKd577Xf0CGpE5VplcrrmRZL+n6p/TM7Tty9oDs vP7Zef3G3ZAxYXbGOPdyQ0bODf1bumR4LP1zZmc0LJ7rzM4YO7v/lY7nx03s O7pXpx5GdWxInazXGYyG0dljpk6fljtlau6UaV7L1GnXTrx68l13L/3f//2X QkYDAABAFCOjwS9niil74Ye90/uIBKQOnWhQB1GcOWDcj+dv/FvRj74wH/yi 6PVPza9/Znn9c/FvGyyfiy1bDnosr582v3qm6JUvzK/+o+jlF+c+NCVjjNrU 0aC2eExMTnrt4OsXL148o55CZ30Xkc7OnTun9XEFAAAAQiCjIbiXD/y4R++e aocxWZb0+i5yp9sGTq5ctONz85uKpUqxvKOYf9qOS7Visp2zHP7lnfuWDJ6W KifKzh5xel33nj3e+8V7Wh8tAAAAoLXIaAjEWZVmV+w/efWV3n366FyjI6YY E6amj9w5ZfWptS9eKK6sN1XaTRX15kqx2MVici3miC4msaOKOsvRf5tety16 YmHmtWl6dZx/gzpFtdyjV68fvvjC+fPnFVeXOr+0PqIAAABAaGQ0BOHONT98 4cX+/QeqmciYIMm6REk3sktG8ai57y3eec58RLFU2ovK680VSlG13VJdb7Ep 5nLxZIsXu7Xcbqmwi+2YquxmsdjsheX1JZWfFb72g1n33TxgYg99siiM3qiO 1tinb9/nf1DmVWAAAAAgRpHREJw79Tz33e8PyhziHCBRpzfoJH0vqdO8zInf nVVyauUPFWuVYn5bKbLZTZV1lsp6kbNatCiOf+utFepjEc3MtnpLtbrx4or/ WPn9x6asuqpnll7tgSbpHcPpZwwc8Myzz3oVFQAAAIhdZDSEpGYfR/zZ98yz CxYuvmriJDWm6WSDTk6UpJyuAx+YsODInEc+XP6DWsub9uJyxexq6+iKXU3q yJomMj8vmSvrRDQzV9YX2y6ut52xvPH/7tl/6KZN5lE3D0nork7YZtQ7mjhK AwYN/Na+pxsLCQAAAMQ+Mhqa6513fpo1cpikV3OaXmdIkHUpkjG7c0ZJzq1v zNv651Xf/7f5LcVarRRXKVab3VGn5l7cKaxhcdaaebykWGyOWrN3xIMvCl7/ /dLv/vDmB5ePvGF4cp9EtT+cOnW1c2K0Pn37PvtttQbNOVMAAAAAEB/IaGgW Z3XV2++8M3TYcJ3eKHKac2prvU6Xakgc3SmjcMwtB+du/a8V36tZ8/K/C167 aHqzvrhcjWyWKrtjUVNY4yKer66z2uqLRTSrVEzltYWHv8g/+EnBy3+859nv XV+ycPC0wUndu+oSjDq9pFadyUZjYp/0fv36D/z+8z/Q+mAAAAAAkUdGQ8v8 7Gc/HzY8S29ISEhM1MnqEPhqA0hZ193YeURKv5m9sk2jbvruLOsHd+49XfTK WetbX5nfqi1662LR4YuWoxcsR2vNR8Ry0XT0gvnIOctbX1ne/NJ88C+rf3D0 1kf3XLNm9fCZud2HDUzp2VWfZBS5TNbpZV1CQoLBkDhk6PCj5RV//vOJ8+dr laBNHEV5kpKSSkpKampq2vHAAAAAAK1CRkOL/er//NpWVT3zhusd3dN0aktE g+yo7VJr13oZU7K69pvWe9SCQVOLx9xWOnHp7in5L+U9YLv98Z8ufsp222Nv 3fLwK3kbX7j+3m9PNz02/q61w2fn9R03vvuQoam9exiSGwYnkWW9Qa9Ooi1J 186YYbNV/epX/8ddgOB90CQXkhoAAABiCBkNrfSLX/7ymW8/u2r1ancmkiXZ IJKVXnbUrUkGSepm7JKR0mtY537jeg65tl/2zAHjru03dkrvUZN6Ds/pPjgr LSMjpUeyztCYy/QGo8Gocz2zfPnyZ5999r1f/MK903D6oKWnp0seSGoAAACI CWQ0tFi9g/PxXz/6yGJdZ7EWF5ks/foPcCcjnQhrBqNeVkf70EmyOuG0x+L+ UW0t6VjTM1WldOq8bPnKdSXr//KXk757DGnPnj2Sj7S0tNLSUnFGtckRAQAA AFqNjIZWstvtdXV1ns9847Fvzr7xpvm3LXCO0t8s48ZdJd44f/7tt8yZa7YU f/X1185til00d3T92tpar6o0khoAAACiHxkNbaHOUdv13i9+OX7CxNFjxmaP HZvdaKzH4n5u7OixV2bnjH/npz9TmnY0a83EZ36r0khqAAAAiGZkNLSdurq6 zz8//Xl4PnMsdRGd7CxIVZpnUhNRTqwZwf0CAAAALUZGQ3wLXpXmJqIcSQ0A AADRgIyGNmVvpogXIJyqNJIaAAAAogcZDXHPtypt/vz5aWlpQZLa/v37tS41 AAAAOigyGuJebW1tZmamV0YTJ1VpaWlSUlKgpCbeUlZWpnXZAQAA0OGQ0dAR HDp0yCuCiTNQPF9TU1NSUkJSAwAAQPQgo6GDyMnJ8apKc78UTlI7cOCAhoUH AABAx0FGQwcRqCrNLWRSEylPbESr8gMAAKCDIKOh4whSleZ26tSpFStWBIpp JDUAAAC0NTIaOo6QVWlubZ3UxCl97NixAwcOlAIAEMX27NlzzIW5aYB2Q0ZD hxJOVZpbyKQ2Y8YMcc0KZ7/ihN+/f7/Y2uTJk4NsEACAaCYuo4WFhWVlZSdO nIjMhRmAP2Q0dCjhV6W5icuQiHJBLliBklptbe2BAweWLFkSpI8bAAAxKj09 XVwft2/ffurUqba4ZAMdGRkNHU2zqtLcxBkbflITD4hmAICOQ1z1wmxYAiAc ZDR0NC2oSnMLmdSys7NHjBjRlpdBAACiVFZWVllZGd3WgNYjo6EDallVmps4 e2fMmNGaq1h6errYwpIlS7TuCw4AQAjiaiWuWeH3p05LS9uwYUNNTU0bXcSB joCMhg7ItyqtBS00xFvCT2qZmZniGrdnzx5x8rfBBwIAoD2Ia9/27dvnz5+f np4eMqmVlZVpXV4gVpHR0DF5VaWJH1u2neBJTUSzkpKS8NtSAgAQK06dOrV/ //6srKwgSS0vL48KNaAFyGjomCorK72uI62Z70wktcTERM+tzZ8/nyozAEBH IC6pQTprp6enixW0LiMQY8ho6LC8Ligtrkpz2rNnj9iITqfr3r07oxADADoa ce0rKSlJS0vzm9RWrFghbue0LiMQM8ho6LDESRjBqrTa2trt27fXOESwkAAA xBBxNdywYYPfmJaVlUXjfyBMZDR0ZJGtSgMAAIK40/M7qEhaWhoxDQgHGQ0d WWSr0gAAgJO4eVuxYgUxDWgZMho6OKrSAABoI4cOHfLtoSaeoeM2EBwZDR0c VWkAALSdmpoar/luJMfcNMQ0IAgyGkBVGgAAbUfcyBHTgGYhowFUpQEA0KYC xTQGQwb8IqMBClVpAAC0sVOnTolQ5hXTxPVX63IB0YiMBihUpQEA0Pb8xjQu uIAvMhrg5FWVJi4itbW1WhcKAIC4ImKa19Rp4kcuuIAXMhrg5FuVtmfPHq0L BQBAvDl06JDXBbekpETrQgHRhYwGuHnNtslf9gAAaAtLlizximlMbA14IqMB bjU1NUlJSVSlAQDQpsQF12tua0brAjyR0QBPJSUlnpcMvV7/9NNPa10oAADi zf79++liAARCRgM81dTU6HQ6z0tGbm6u1oUCACAOzZgxgy4GgF9hZrTfRQgZ DVHOd+SQ7OxsrQsFAEAcOnHiBF0MAL/IaIAnrxH4x48fr3WJAACIW6WlpZ6X 3czMTK1LBEQFMhrg5jtmCBNrAgDQdrjyAn6R0QC3DRs2MMYUAADtyWu0rry8 PK1LBGiPjAa4ZWVleV4m9u/fr3WJAACIcydOnPC8+CYlJYkbP60LBWiMjAY4 nTp1yusawehSAAC0A6+/kZaVlWldIkBjZDTAac+ePbS1AACg/XmNHMIlGCCj AU5es7TQ0BEAgPbh29xR6xIBGiOjAUJtba3XuFKnTp3SulAAAHQUmZmZnldh caOodYkALZHRAMVn6mpGdAQAoD2tWLGC1iyAGxkNEMrKyjwvDYWFhVqXCACA DsSrV7iIbFqXCNASGQ1QfCZnEVcKrUsEAEAHQoMWwBMZDRDy8vI8Lw2VlZVa lwgAgA6ktrbW80KclpamdYkALZHRAMWnq3JNTY3WJQIAoGNJT0/3vBYzkzU6 MjIaIKSlpXleF7QuDgAAHc7kyZMZ2hFwIqMBgtSU1sUBAKDDWbJkiee1+MCB A1qXCNAMGQ1Qmma0zMxMrYsDAECH4zX8fllZmdYlAjRDRgNOnTpFRgMAQFtk NMCNjAZESUa7fPnymTNnampqPmkO8bsjfjtqa2s1KTNizIeHn3zyycMfal2M aMYhUjgI0AwZDXAjowHRkNG++uqrzz//XESt+vr6Zr3RbrdfuHBBhDvxm9JG ZUP84N47JA6RwkGIA2eOH36+QdAv8sPG1Y6fabfSBUZGA9zIaIDmGe3cuXPi zBdpqzUbEb8sZ8+ejVSREJ+49w6JQ6RwEOLAmePPi+/w+cNC0OwlspzgWJeM BkQXMhqgbUarq6sTJ39zq8/8Er8mFy5caP12ELe49w6JQ6RwEOKAI6OFG7ua tXLbIqMBbmQ0QNuM9m+HiGyqtrb2zJlouMwiWnHvHRKHSOEgxAEyGhDzyGiA thktgpVfdXV14tck8OsVn3aT/vnMSf8vVuV/1E36tCrAj6qTX1tz/9lN+six /NO69+u/Nnn1S2uu46XcLxvedXJvriTl5lcEL3SQuwNnax3vF898qHa0eLKB 2tnijM+bvN7S9I7zzIeHXW93dMHwvR9Vu3I4Xz/e+HSI/To203S//jb8vOcz fu6E1cJ57iTgbVOTFT2K47NN51FseMb1qvsTOo7Bh0GOVug9epW5cXOBng/w wVv5tbbnIQp2NPx99ibfo7+zK/jWHMfG/ZpaluAfvYVnuIcwD0KIb615J4B3 kdrnJGnWil7/IWn27nz/GxH4rSH/4+D9fXgdwKalC37ON1nZ+VizgE5GA9zI aIC2GU2c/K3siebpk08+CfxiKzOaeHvup89UfF0llr2fzhJxLP9r12sXn1ED 2j/VV/dGKKM1JLSmL7pim7g/cWi4ZfNYJdSNk+OxawMN3eqb3r40dORQVzh+ /MNw9xuJjNZwa+25F/8hzbs4jvK4NtR0q35+Uj+x660N93XeH8TnNjPYHsUb PIvsfneg53130fqvtX0PUdCNB/8e/ZxdIbfmynnuU/bw4SAfvWVnuJ9thDgI ob+18E8Af0Vqh5OkuStqnNECH08/B9C7dMHOeTIaEJXIaIC2GS1oqors1lqZ 0YKsf/JLEdlm7b3YghIHyGgNf+Y93OSmxvW3X98KrMaVQtw4+b7svKX1f7vS jP22PqN5FySwhvcFbJnUWBTfFOhzp63+dd7ng3gXI9QefVcN+ryfe93Wfa2B 9tY2hyj4xoN+j34+Rxhb8/fBA+2iRWe4/88Q9CCE9Uvh85LfEyCs2u82OEkC Fi+8ddo9owVZ37cs/s8D/+c8bR2BqERGA8hoquZltJNfWx3NGhuaO0Y8o7nu W5vc1AS6kWjyfFj1aE1ufYL8SbkZ+211Rgu/C1AYazoL82HT3QV8a4hmUc0p m3fg8/98iNtLP8838364TQ9R6PvwIM0Q/Seo4FvzOThNG6qFLEDIMzzMD+Fb 2xLql8Lj+cAnQIB3tflJEs5HDraOphnNX2IO+V+tQOc8GQ2ISmQ0INoy2p8e fdS5iMd1tbViCf5M8K15iEhGO/n1M/n/bOiS5m7GGOGM5r79CBkefF8I727P 0XbssKs5WIg72LD229qMFv5dUkNbJFfDOA9nvAsdqD4s5AfxU+xQe2zsNNW0 nZS/58MLp836WtvvEAXfeIjv0eflEEUN5wvzu49mneE+Qu82vF8Kx+5CnQAB itTWJ0l4HznIOhplNL+/aOH+ZSlAFSwZDYhGZDSAjKYKJ6NVudOZz4AhEcxo Hn8gbouM5lhJvc85fLihp06olmDtktGC3795cnfU8+G5r4hntGB7/NB909h0 HIPAz7dDRmurQxRi48G/R/8ZLfjWmpvRHJtt1hnuI1IZLawTIECRyGi+Wwp0 PMloQDwiowHaZrSamhqvydHaNqOJeFVV0bj81RXZwhjX8UvnOCFN0pnHS5HJ aE2a8DR9Mfz2Ts1qqhfBto5+mpj5binAbVj4t0n+Po7X3V/Dj+r/C1GkcD5I iD367yoU+PkWN2ML/2tt00MUxtEI+D2G9xeAkFsLO3n4WzvcjBb0IITzrYV5 AgTYWpufJMGLFHqdlv2nxrvO1F2zGzqjBT6ezWrr6HvOk9GAqERGA7TNaGfO nKmtrY3Ipi5fvix+jwK/rma0j7wWd3tFfxmt8VX3261+h2mMWEbzujf0unUI e9wAP/Ulnltp8jdo79uT1owZ0mS/DX+y9t50wNuwIHdgXgLEQT8tybxCof8/ o3sVy+eDhNpjoPvSwPer4Xzw5n6tofYdwUMUfONBv0c/Z1d4W/MtTeAo0Pwz 3FsYByGMby3cEyCcKqm2OEmCFin0Os3fXcNhbSJQ+08/v4ZBihhORgt8zpPR gKhERgO0zWhfffXV2bNnI7Kpc+fOiV+WwK83u63jR91yP61qXN85TkjD8PvP 5P/TGcr+6hqKf1b+l466uYuugUSaPfa+zx1OoJZhIcffdrTycqzkO2i4c43G sck9Xj3jesa1gzNnwt1vw9/ID3vv9rjjT9eNu/KJA953qk/6H7O9KWebJ7+f wd+NpNd9YOPRCVgqR2cX32aLQfboscEm9+h+ng/ngzf7a23PQxR04wG/x4Bn V7O21jhjWZCM1vwz3PvghXEQQn9rYZ0AgYrUHieJz0duflvH5p2TzWzr6PVr 6P94+j+AfhsoBDjnyWhAVCKjAdpmNLvdfvr06UuXLrVyO/X19eKXqK6uLvAq LeiPps5brYa1hjqyxgFDnGOGXHTNjOa5uAfkb2ZG8/M3aL+3DiHm+3W9pXH6 3ee9J+ptMhWuc1Lgxvf6/yN3yP26778ap5JtyFdNZhQO2ivHz14CV6t5bNZz Nd+j6LkX12PfWZF91ndt36MC0v8e3UfUz2sBng/jg7fga22/QxTiaPj5OGKF oGdX8K35lCVUoGjZGe57QEIdhFC/FGGcAAGL1E4nifdHDn+d5u+uBf3RvH4N /RzPAAcwaAMF792R0YBoREYDtM1oggho4vy/eLElTQWdRDQTvyPnz58PulbQ jNYqEWjr6LeVkBa3DlF0u4K4E6Gzq3n90dqmDJGkWZE+POzMz608pOHvrY0+ Zfi9aMN8u2bIaIAbGQ3QPKMpjq5kp0+fPnv2rMhZQevCmhBr1tbWil8T8esT Rqe2KM5oPi0HPV8koyFekNH80qxIrkqo5531c2Q0zZHRADcyGhANGc3pq6++ Er8C4lT/JDxizTNnzohfE6+RIQPwN65jVUXLa+88NHZPa67Gljp+7o80uXVo 0nEGiKjInF2tq/SJwjNc0yI1NiBsj4zmMxdeRD61zwF0dd9Te8sFb3/pmqAh Ok4JMhrgRkYDoiejtTF/4zp2y/3SMcTHxYCTVrcxV0bzex8RRX/ebQMhexXF qw77wSMmxg9gOCdAe58kjo5fbVwkf+M6NvY0i+zndU6Q5xD0P6BnGleLTFps JTIa4EZGAzpMRgtKq4zWkcX4nXbLddgPHimxfgCbP0BHVGjTIkXh59UCGQ1w I6MBZDQAADRHRgPcyGgAGQ0AAM2R0QA3MhpARgMAQHNkNMCNjAaQ0QAA0BwZ DXAjowFkNAAANEdGA9zIaAAZDQAAzZHRADcyGkBGAwBAc2Q0wI2MBpDRAADQ HBkNcCOjAeIEI6MBAKAtMhrgRkYDBM+LQlpamtbFAQCgw/HKaIcOHdK6RIBm yGiA0jSjCVoXBwCADmfGjBme1+Jjx45pXSJAM2Q0QMjMzCSjAQCgIa+MJu4V tS4RoBkyGiBkZWV5XhdOnDihdYkAAOhY0tLSPK/FNTU1WpcI0AwZDRCWLFlC G3gAALRy4sQJ+oYDbmQ0QNi+fbvnpWHDhg1alwgAgA6krKzM80I8f/58rUsE aImMBgiHDh3i0gAAgFYKCws9L8R79uzRukSAlshogOLTxCI9PV3rEgEA0IHk 5OQwqCPgRkYDnLy6KouzVOsSAQDQIYg7Pc9LcFJSUm1trdaFArRERgOcvKbO LC0t1bpEAAB0CMeOHfO8BE+ePFnrEgEaI6MBTgcOHPC8QOTk5GhdIgAAOgSv zmglJSValwjQGBkNcBKnWVJSkuc14tSpU1oXCgCAOFdTU+N1/a2srNS6UIDG yGiA24wZM/g7HgAA7WnPnj1ew3bRGQ0gowFuXs0d6bMMAEBbE6HM8+K7fft2 rUsEaI+MBriJROZ1pWB+FgAA2o7X/KRJSUk1NTVaFwrQHhkN8OTb4kKcfloX CgCA+OTVy2DFihValwiICmQ0wFNtba1Xz+XCwkKtCwUAQBwSd4NSU+IZrQsF RAUyGuClpKTE65Jx7NgxrQsFAEBcqa2tnTx5sufVlmnRADcyGuBFnG9evdKy srIYPAQAgAgqLS31+ovooUOHtC4UEC3IaIAvrwEeBXEp0bpQAADECXEr6HWd pRIN8ERGA/zKy8vzGmmKRvIAALRebW1tZmam10X2xIkTWpcLiCJkNMCvU6dO eQ0ewp/4AABovRUrVnhVou3fv1/rQgHRhYwGBOI1Dr/EmMAAALSO14RoQl5e ntaFAqIOGQ0IIicnh5gGAEBEVFZWerVRSU9PZ9JqwBcZDQjCd+oWoaSkROty AQAQY3wDmnDgwAGtywVEIzIaEFxZWZlvTGOYRwAAwicupr4BjaYpQCBkNCAk YhoAAC3m9zKal5fH3KNAIGQ0IBx+ry8lJSVcXwAACIKABrQAGQ0IU2lpqe9V JisrS5zPWhcNAICoU1NTs2TJEt9L5/z58wloQHBkNCB8fmNaUlLS9u3btS4a AABRpKysLC0tzfeiSR80IBxkNKBZ/MY0yTHD9YkTJ7QuHQAAGhNXwxkzZvi9 VhLQgDCR0YDmCvS3QfHk9u3bxemqdQEBANCGuA76jt9IQAOai4wGtEBNTc3k yZP9XoPEtUlchqhTAwB0HLW1tWVlZVlZWX6vjOnp6YcOHdK6jEAsIaMBLRbk r4XCjBkzmJoTABDfTpw4UVpaKlJYoKthSUkJLUyA5iKjAa0hrk05OTmBLkxC ZmamuDyJsHbq1CmtCwsAQGSIGzkRzQJVnDkx9DHQYmQ0oJVqa2s3bNgQpELN s7HH/Pnzt2/ffuzYMa1LDQBAuGpqasSV68CBAyKXzZgxI+QljxGPgVYiowER Ia5f4noUpLEHAAAdwYoVK2g6ArQSGQ2IrAMHDgQaTgQAgHiVlpa2YcOGmpoa ra/DQDwgowFtQZzhK1asCKcBJAAAMW3+/PllZWUMDAJEEBkNaDu1tbXHjh0r LS3Ny8vzO6UaAACxKDMzc8mSJUQzoI2Q0YB2c+LECXE5W7FixYwZM+i5BgCI FSKRiStXYWFhaWlpZWUluQxoa2Q0AAAAAIgeZDQAAAAAiB5kNAAAAACIHmQ0 AAAAAIgeZDQAAAAAiB5kNAAAAACIHmQ0AAAAAIgeZDQAAAAA0Nzx48ePuPi+ SkYDAAAAAE2Q0QAAAABAWx988MFZB/GAjAYAAAAA2rp06dJxB/GAjAYAAAAA 2jp79qwzo4kHZDQAAAAA0JbIOJccRFAiowEAAABANHDWppHRAAAAAEBzzoBG fzQAAAAA0Jw7oCmMvQ8AAAAAmvIMaAoZDQAAAAA0JQLO+++/f8Tl3Xff9V2H jAYAAAAA0YOMBgAAAADRg4wGAAAAANGDjAYAAAAA0YOMBgAAAADRg4wGAAAA ANGjsrLS6xkyGgAAAABohXo0AAAAAIgeZDQAAAAAiB5kNAAAAACIHmQ0AAAA AIgeZDQAAAAAiB5kNAAAAACIHmQ0AAAAAIgeZDQAAAAAaDfHjx8/4mKz2XxX IKO1pb9uK96XK5YX/hpojfdecKxQXPVee5YrilTk5zbKr2jXdwMAAADa8o1j fp8ko0WOyGgHXvo01FqffrC8I2c0qVELMlpr3g0AAABoi4zW7shoITlSVu7e k63ayMm9uWQ0AAAAxB4yWoQ1Ziu1TeO2P7qe/2NVbuPzDRnt46oDuc52jx5L w1s8Mtp7L+xbXnWmvT+IlshoAAAA6LjIaBHWnIzmWDlAnVpk69GceSVwYnG9 7sMdlBoaEAYJTicr9ubnNm4mNzd/b4W/lU82Wc3vFgNktGMnpDG/EEvu8+ca t/b8751P5h/z+5nIaAAAAIgxZLQIa1ZGa3jeX0yLtYwWYAs+6zfpLNbMjCZe 2PwLRyI70fA5/v5xriOgSZu/CFAiMhoAAABiDBktwpqb0Rre4tOa0W9GUzfi 1TYyjK5tSuiMFnrF0BktPze/4uTJxp9z/Q3a4Ypo+X6r2Jqs5X9X5/Yuagxl DZFt0cf+6+vIaAAAAIhBZLQIa0FGU5156Ymmo/G3bz1a6BVDt3VsshkR2SQ/ GS3McgTtj+aqO8vf7Gz6+Pu9fw/yUchoAAAAiDFktAhrYUZTvGNaTGa0k44+ aU1aMjbdUCQymtLYMc2rb5q/j0JGAwAAQIwho0VY04yW6zE2Y+4TH3zc8HyQ cUI8hxOJfFvHkF3BWpHRvPfhb8yQyGc0n6FCvPZFRgMAAECMIaNFWJOMduCl P6p9zZqGKY+M1li55vNSZMfej1hG83iPV2pzDwaS6384x+Cb97OzgBnti3xn QFv0+ybjh/jfFxkNAAAAMYaMFmGh2yh61qOpdW3u/OWYLs313iht6+h87aSf NV2Rzf3Okycr8kVea0k5gmU0z6EdGx77GdRRIaMBAAAgRpHRIiysjOaoWWvo eub60athpMePERAyG3kPiR8oo+XnB1zRZ1R9j5cDju3fzLH3vWdDc40f4q9X GhkNAAAAMYmM1iFEKqOpuUmtHmuIV/leMUp9yWMW68ax+COT0fzNhuZKbb6j O5LRAAAAEJPIaB1C2G0do6MczoyWv7dCdTKs0f49d3LS8T7nCJNaf2IAAACg mchoHUKAeizfAFPhWNGngizS5QgnowUuZAitezcAAACgLTJahxBuRvMYnLGN QppavZUbKjk11IRVtKoerYXvBgAAADR09uxZMho8tXE9GgAAAICAREA7fvw4 GQ0AAAAANOcMaJcuXSKjAQAAAIC23AFNoT8aAAAAAGjKM6ApZDQAAAAA0JQI OO+///4Rl3fffdf5vLNvmteTbmQ0AAAAAIgeZDQAAAAAiB5kNAAAAACIHmQ0 AAAAAIgeZDQAAAAAiB5kNAAAAACIHmQ0AAAAAIgeZDQAAAAAiB5kNAAAAACI HmQ0AAAAAIgeZDQAAAAAiB5kNAAAAACIHmQ0AAAAAIgeZDQAAAAAiB5kNAAA AACIHmQ0AAAAAIgeZDQAAAAAiB5kNAAAAACIHmQ0AAAAAIgeZDQAAAAAiB5k NAAAAACIHmQ0AAAAAIgeZDQAAAAAiB5kNAAAAACIHmQ0AAAAAIgeZDQAAAAA iB5kNAAAAACIHmQ0AAAAAIgeZDQAAAAAiB5kNAAAAACIHmQ0AAAAAGgjx48f P+Jis9mCPOlGRmsbf91WvC9XLC/8NdAa773gWKG46r32LFfzndybK0lSfoXW 5Yh7FfmSKjc3v+Kk1mUBAABAWxCJLJwnyWhtQ2S0Ay99GmqtTz9YTkaDU0NG cwa1vcQ0AACA+ENG0xQZDS1zsiI/l5QGAAAQl8horeRqi+hYnvjg4yYvupoy iiD2x8ac9XHVAVf7Rr8Z7cxLT+zb9kePJ8ho8MdRpcYhBwAAiDdktFZwRDCP rmSOvObOXGrUcr3qeNyQs9THy6vOuLbQfhntZMXe/Nxcdzu53Py9TXo0OV72 eNXjRUcAa6iycQQDz8fOkODMaB7N8Lw336SRnueKe5sWwqOITq4Q4ny/1+rO vTZdxYc7xvgJkp4fx+tZv+kn1KcIvYuwjoOfY+G7gr8jAgAAgJhHRmsxNZH5 jPWh1pE11KapCa4xav2xStuM5p2hvNKL3+SQ63q5BRnNe/vhZJNQ23C+3vgG r4QWXxnNZzX/hfT3AgAAAGIaGa2F1NzkrytZ4/NtkNHUjexruoTRnU1pTD+e tWNqvdnephVQja82dHfyDGDhZLRAG2jKfwJqSGBiE4Ejh2dK805sofcQiYwW 3qcIYxch9uL6dIEHb3S+e69Yj5AGAAAQV8hoLdSYuby4o1kU1aOFahTnfN0r LXikjWZkNP8b8LM7n+fVZ8NIGw37rwiS0OIhowV8k+d+1NcdD+iUBgAAEEfI aC0USxktWI2TQ+DQ5HxXyzJak7eF3J3/ho5BWwEGTiZxktECl8Dj0BLSAAAA 4gwZrYXaoK3jx1UfuFeIaFvHUHUyMZbR3Gt23IzW5MgGOswAAACITWS0lvKM Wo1CjRniHOBxn9+x9xvG5H+ialuE69FCZjS/rRK92zo2bMGz3aRPRmu6k0D7 DRIJvZ7181xDu8y9Qcf6D5rRfEcyiXhGC2MXIfYStATeWwyzmSgAAABiAhmt FYKPvR9I8LaODSGufTOaK1k0DlHhZ8yQhm24WhqKVzyjnbtyyzUsycnAPcYC 5A9XrzivYUd866Q8g6P/GBM8o3kW0rMnXuCqvPCTZohdhFPK8F5rUiJmSgMA AIgjZLTW8agX8zOHdcC3eGQ0d51akxXcGc01R3ab9kdTAuSTpq3pPOZWy/eY Sc25jvcqgbNNkEThZ1h63yjiPZR+M1Jgwxu8C9lkioFQGa1pGQONThloFyG3 EGBkfsnry/D+1IQ0AACA+EFG08THn3o3kmxTfhrg+VuroukU1x7D9DcMS9FQ ueYcTjC/Yah8j1U8XnC81rxRF51laJxIu+k82n4/RKCUFiyjibU99uK/kEFK GE5GC76L1mW0AB85dF0pAAAAYgQZrWNouPX3nH3Mc340DQrTppU+rd2D9tVS 2pcAAAAAGiGjdRQV+X4a8mkTAtosfwSohGr+rkLPIN3WyGgAAAAdzfHjx4+4 +L5KRotPjvZ3Hp3K2jmChGglGPE9tGZXvl3T/I56mduKTxF8C+LVXDIaAABA x3P27FkyGtpL22e0iGrSPc/v1G+t+hit3wIAAADijQhozto035fIaEBwbV2P BgAAgI7GGdAuXbpERgMAAAAAbbkDmsKYIQAAAACgKc+AppDRAAAAAEBTIuC8 //777kEd3333Xd91yGgAAAAAED3IaAAAAAAQPchoAAAAABA9yGgAAAAAED3I aAAAAAAQPchoAAAAABA9yGgAAAAAED3IaAAAAAAQPSorK72eIaMBAAAAgFao RwMAAACA6EFGAwAAAIDoQUYDAAAAgOhBRgMAAACA6EFGAwAAAIDoQUYDAAAA gHZz/PjxIy42m813BTJaPJFk2b0EIjVdQmru+m2roRySuyg6nU6SpN69e3/w wW/FEaivr9f6SwAAAADC5RvH/D5JRotdsqSP+0XyzGuujNanT/oHv/2dQkYD AABATCGjxT2dpHcvgTJOOOu0Zv02XnSypNaiqYtO/deZ0bp2Tfv1r3+jkNEA AAAQU8hocW9kl4ws1zKiS3+/S1YY67Rm/bZeRnXuO7xznz4pXZP0RrUyTZJ6 9uz54IMPfvHFGXEE7Ha71l8CAAAAEC4yWtx7ZnpR8GVf0B9bv34bL4VqAaZZ d08vuGXIpG4JnfWyWol25ZVXitNGIaABAAAg1pDR4t4ly9H4Xi5ajl4orvzv da8WjLmlp66zQdY7M5o4oxQyGgAAAGINGS3+mavifDGJxfa3wpdvHTBJL8lG vUFktLFjx372+ecKGQ0AAACxhowW9+otFe21VDqXuobH7bRfu6XygunIzxft uKbncJHO9Dq1Hm3ChAmfnz6tkNEAAAAQa8ho8c9SGZHFbq4QS8NjRzISP9ab K8ViN1XaiyoVdbEppiq7uareUmW32BSxvrncbi2PVBn8lEr8a7WdLThYNnPd FWn9JYerJk76+bvv1dUxnCMAAABiDxkt7tkdQSYSi8hl5XaRuUzlahwz25Ri m7KuSimpUtZXKfdW2dfbLpqP/Cv/4Ccrf/zh3c9/vLLsvPVNR0CriFwZfBaz yGhVn639yaZxi/ukdHcOw3/7gkVaH3UAAACghchoca9ZkadJ/ZTrgVjqzRWK 6YhiKVdKKkUcu1R8tGb1y79fsu/teY8fmrPlpdn3Pzdr3e5pBf+fvTsBjKK+ +z8+e+UiQLgDBAggEI5gQFEIoAgeEUFQDkEFwpVjNwlBPLijVItyBa9SW2k8 aqmKgBy51FJti//WPs/T53n6lIei0upjo2JQRAhHkv3/ZjfZ7M7eySazybxf z/exye5k5jdHlvnkN/ObTWPvX33N3NyRM5Yk3ZYzPK1ocu7/LX+t2nLEGlTs CqbkhuWVn1r26p19xkUZIvUGOaNNv3MmlzgCAACglSKjtXlNSkByTCu15pZZ V5RfyTt0OvuN/1708/dmbX3ttkd+NGbBgkFTJvdKuabzwEGxvbqZ4iKlCKMk mSTJIN8UJmelcR0GHJ722IWsg2ImzZrR/rZk98iOA8USjQZ54P07Z9yl9lYH AAAAGomM1uYF1Ykm/nsl1/51qTWvpDa35Lz57f9b+su/Lfz5u7Of3HVTTtbQ 28d3GNxbH9dJio6VIqN1ESa9yaAzSaL0oiS5RD6zZbShsb13T37gh8wD1tzm zGi5ZX9d9POrO9gymlEeMGTGzLvV3uoAAABAI5HR2rygAppc8mj2peLbquwD Xyz/ZcndT6waddctCSmDY+J7GjvEGaIjdQZ7FtPpROnkbjO9ZNTrIvWGKGNE O2NUJ2O7bhEduxo73Jsw/j8W/ORSbrNc62h16kc7sbTo+k5J8qCOdRmNfjQA AAC0VmS0Ns9HxlEMkGgbubHEml18yXKowvL64Ts3LRt86+j2iT2i2kcb9HLv mCT3kRl0UoROHyEZonQR7XTRnQ3RfaM6j4zrOzF+6Iw+Y9OH3LoyZdb66+57 fvKKf5v/7MXs/fLQjs3TiebIaKeWvnJb/DVGvdFg1NOPBgAAgFaNjNbm+ek1 a+g+K7ZaSmpyS742v3lo2mOWETPGdBsaZ4yty2V6nVHSG22XM7aTIgbF9Lw9 4dpVyTOfv8G89451R2Zu+s3dTx6bs/3f5j371/tfOLmo6LPFv/x2+d4recXV onKPeF5iaDJaiTWvrGLZa4uH3Nopop3Jdo2l4340Rg4BAABAq0NGa/P8ZbTS WktZtbnMmlP2Xcbew3c+8VDK3Jt6pMQZ5HSm1+uN4v/lYUB0CdHdJvZMTh9y 66axi16+7cF3Zz/594Uv/pC935r/jnXlu9b8d+UvVogqF6FJHmYkp1R+dJqP VBiSso29X5n55o6xSwa0666z9fYl9O2z6fEfVVVVqb3tAQAAgKCR0do8rxc6 inRjFlUsV0753xcV7UzNmNJ7dDtdlHyfmUFntN1q1kEfeV3XwRlD07ZPyNw3 reBv979wIeeAdVV5bX65NfedWnN5jbm4xtJQ9gsmay1OCwo4oDUux4kwWGU+ +P7cLRO7DZVvSTPJt6QNGjL4XxUVVrrSAAAA0NqQ0do87xmtVKSzmpwj53P2 /2XBTx4Zfc8AUzeDSGdyt5lOJ+njTLEjOycuTLr59dtWf5Pxek1uaXWOreR7 1sqsIp1ZyqtzymtDMa6+IscFHuvqps8tPZ31eubg2zroo3S24fdTRo86e/Z7 KxkNAAAArQ0Zrc1TBB+nEULkwRu/z93/+3t2pA+5qYsh1qgzGHTykI0dje2G x/RbOOCWPWlrP8v81cXsgzVyoCuvzS6vNZfVmu2hrLi+mnodo9OQkkEnNavt IW4iJ17OPviLWx4Y1qWfbWQTuR/tD8eOqb3tAQAAgKCR0do81xx0xGo5Yhto 8Yg15/C5zH2/mfXU3QMmdDRGG3XyM82Mkj4+ov2cgRN+fceGT5b+6kLGAfmS yJzSGkcmstgq+OsY/Wa0GtGk7COXzUcu5xxxTm2+M2DDW9lH/rJg1/TEVPkp aTqdwWgYNnzoX//6P1a60gAAANCqkNHaPA8ZzXzEmlt8JvvNX0/bcHv8NXH6 aJMk4pneIOkHR/XcdP2Cf7/3mfNZ+2tyy625ZY27+DCogGatT3/ncw/9Zd6u zxa+ahtyxB7cAs1oVnNxZd7+tdfO72psb9QbRVLr1qnTH//4J7EFampq1N4J AAAAQKDIaG2eMqOZj9TmFn+TuffXU9eM75ls0ptEnDHp9JGS/rr2A3ZOzPr7 0ldqcoqt2SIfyd1nVi+RKoQZzR7QLpjfLp23xTJ42t5b119ZWV5je1HZWeZz Dlfyjhyc9uhN8cl6nUmv08dGR92WNvU//vKfVrrSAAAA0HqQ0do815hTLDLa pfzi383ZeWeva0QuE/9nkAzt9BFTeg5/eUreVxl7ruSW1cgD8heLQOc3HzU9 nclly2KfLn1pSXJavL7jw6PmfLZ8zxVLsW3YyYBuSZPXy1Jam33k8+W/zLv6 Tp1kNBiM9oduv/zyq1a60gAAANB6kNHaPJdAZCmzWt45ueTlh6+d28nQzqST x9jvaIpJ6zPm19PXnLW8UZ17qNb1drNmCmh1Tco9Ii/OUv5Vxpu7JpoTY7uL VDW5Z/KhmY/KnWjmd2ot5UG0wVxsXVH288krekd1Nej1BkmKiIzet/+AlYwG AACA1oOM1uY5p5ianLIq88FfTF45tH3fSJ1Jkh+CZrq91zX7Zz52Jn9/jeWw 3/u/Qt2PViz+e9FysOTOH43vOCRaFyHpdd2MHR697t5zOQes2eVWS1kQjRFx L6/093O2zxiQGqmX+9FMEVHrNxScPn1a7Z0AAAAABIqM1vbV5Rf50dKX80qP ztlyV/9xBskgj+KoNyZF99lz65rzlrdr5WsLS2stZS2Q0Rz9dLWW0ssriv98 3zNLh9zc3hRje3a2/HSzaf2v+8N9T1eb5Ye4BTnn0i+X7fnR9Qs66qJ0ekmv NxqMEU8//ayVrjQAAAC0EmS0Nq+hE81c/FXm3gdTZncyROv08rOqexk7rL1m /j8WvmLNlUOc1dIS6cx5ETWWss+Wvvbk2EW9ItobREKTn6At30WW2KH7U6nL LpgPW3OCzIwW+XLHAzMKBrfvZRQzsw3wuG37DisZDQAAAK0EGa3Nq84pu5Jb as0pvWA59MJNK1PiEg2SpDPoY4ym23qN+uOcwiuWQzXyCCEt0ndmkYcBsY3Z WHolp+xyXsneW1df0zkxUpKHL5ETmshpeskkSXMSx51aXFQjP8otiPnLt6Tl lf15wU/uG3hDtMkk2RLf1u3brAztCAAAgFaCjNbmXcktq5YzUfFXGa8vSJwc I5mMRhFd9IM79n5x6gM/ZO615pa4j7HfjEnNYrtxLLv4Yt6RP819elH/SdGS MUKEM5HNRKKSM5ocrFI69n1tygPnst6y5gZzuaNtiMjK5a+/cEN294j2Yj56 vX5E8ohXX/ul2vsBAAAACAgZrc2rzi2zWkoumg/8/p6dqd2G2mKLrktEXOaw tFOZL4vsVmMuDu56wqb2ppWKhVZbDn2a+cuHU+b0jOikM8ihzBhpGDxsQMcu sfKI+TpdB0PkvQNu+HTpK47naAfYlVZjFvMv+XD2tjEdB4rUJz+aW5IWLlqo 9n4AAAAAAkJGa/NqLOXW3NLK7DefmWAeFBsv6SQRWkZ3uWrf9PU/mPfV5JbW WEpbJqDV96PJQzWes+x7cdLK5E795XSmk/QmXd9BvRYsu3v0uKHGaIPcpyZJ Qzv2KZ35xKWsg0HNv8ZcZl3x7vHFu+f2vzHGFCVfPSlJmRkcMAAAAGgdyGht Xm1WmTXv3S+XvrZ0wK1dDLE6g3xF4V19r//7klcuWuTHk7XYePv1t6S9cyXr yO/nF94Sn2ySh5cUEU3XtXvc9Hk3P/TYsjmLbovv283WlSZ1j+jwYPJd/1j6 knXFOzXygJNHfDeyrh9NHoG//NNlr+aNnNU9sqNk60fLWM4BAwAAgNaBjNbm VeeUWS2l/3P/T6/rlCSPy2HQdTRGrxwxozLvYHWufFlgSz4TzfaA7LJTS17N GXxHD1MHeSBHnT66feSYiSPzNy7bsNXywMYlKWOHyX1fesmkM47rcNVv526p ySupNQec0cQXuWVfZr7+5ISMPjFdJFuXXMYyDhgAAAC0DmS0Nu9SXsn5jLf2 pD3cL7aHZDOyU9+iSXkXcg7X5pS2WD9a/TPRSr/P3vf6jPUjYhPku870Rskg DRzZd/lD89ZuyVy/LXP9FvO0eTd17xknRyu9obupw4/HL/586WvWnPJaf4NP NmS0nNJvM98sumXVVbHd5bAnScvJaAAAAGglyGhtXmXGm58teeWR0bO6R9rG OZSkaX2v/dPs7dXZh90DTrN3oq0o/zi9KHtoWueIaFte1Pfo22PGotse3rp8 3Y6M9dtFTMvOfuTelOuSbG8aog2mm3uN+v3cndYV71rNxQ0Pv/Ze9ox2IWv/ oekFQ9v3lJ+6JkkZGVlq7wcAAAAgIGS0Nu/DWVv+tuBnM/peF2OKEHnFJOnN I6Z/nflGrbnZn4nWkP4sR2pySmuzS6osbxfPKBgV21uvl3R6o04nXTNhxAOb MtZszV63LXPdtqy1WzPXbMm6fdak6A4Rer18t1p8RMcXb8m/aHnbGsCz0qz2 jGYpuWx5+7dznhrZMcHedThw4MAdhU/zGGsAAACEPzJam/eT1OV/XPiTG7sM jdAbDDpdZ0O7x8YturSiWGQ0+6OrW+IqR7EgS6k1t/STxS+tv3ZeF1207Tlo +u494mbMv2X99ry1ckbLstfGQsvivLmDRw4wGOTrHWMk06qRMz9ZuNuaW/f4 Mz/Lqs9oH9yz1Z7RjCaT+O+41Anff3/OysOsAQAAEN7IaG3ekiFTDt371NjO g0wio0m6hKjOO27MqMkvtZpbohOtrixl8qAf+WXvzH7qhh4jIvRyj55IYGNv uDpn7eJ128yOgGavBx5bOmXaeGOEfCtZhC7ijoRr3717c+2K0qAzWpyc0QxG o/jv5Cm3kNEAAAAQ/shobd7EnsO33pQ9qmOiyWDU6XQJkZ0Kb8ioWSmP6NhC nWhyRiu3ZpddzDv84pSVPaT2Op1Rr9fFxcXcfX/ahu0r1shXOWY6AtrarZnr t5lnL5oa3d6k00l6nSmpXa+Xb1klIl6tv1zZkNHMb78/d4u9H81gkjPaxBsm nT37vZWMBgAAgPBGRmvzBnXsPXvoxOT2fSIN0SLwJER23jkxqya/rGUyWm3d PWJlNbkl/7fkpUdGz4qWn1imM5n0Q0cOWJw/d8OOvLUioG1f7pzRCnbkLDLP iu/TxWjQSzopSorYOnapPP5kAG223Y9WdiH7QPHMx0e07ylnNPmiSd2MmXef v3BB7b0BAAAA+EFGa/NiDNGDYuMHtY+PMkSKvNPyGc3Wj1Zau6L0vbt+nJYw OkIn32ZmjNBPnjo+/9El67ZZ1iky2rbMjTssWavmJ48eFBEhd4GJTPfAyLu/ XLrHWn+to7dm2+59K7XmlJ/JfHP3lPyr2nW1jxly5/Q7Pz31D7V3BQAAAOAf Ga3Nk3SGWENUz9jOEYYIR0arbamMVjd/c5k1v2zXlLzEqG4G20OlYzpG3rNk xvrtlrVbs9Ztz5SrIaNlrd+enb9x4U1pYyJj5OE+TJJ+ZuL4P8za4fd+tLpl 5Zb/K+O1H6Uu7BUTZxt6X8rMZux9AAAAtA5ktDZPp9NH6I2xkTFGvVHS6fq0 bD+afTD8GnPZldwjj153fzvJoNfpDBGGPoN7LVt5b8HOnLqA5pTR5NqevebJ ZfcsntquY7Q9o43uPPjXUx6pzSm25pTaZ+u15eZSa947nywtyhiWFhcRI+nl kLZk2TK19wMAAAAQEDJam6fTiWSmM+j18n8lXbyp/VPjl1bnl1sD6ZMKUYmM 9uXyPZbkafLdZTopMsY0euJQy9p7N+wwr92WqRjU0daVlrFxh3nZA/fE9eoo Wq/X63tExD11/aLqFcVWy5Fq2yD87s+ztn9dbREZrfx/Fv709oRro4wme7fd 8uXL1d4PAAAAQEDIaG2ezhbSJDmoyYMkxkiGtdfeUyWHnRbLaKXVlpK/3rvr vkGTdLZLD6NiI264fcyKjQvXb89e6xbQbP1omQU7zZa1C/uP6Gs0GUW8jJAM OUm3f2fZZzUfuZJbUp1b6t6P1pDR8sv/vODZa+OuMugMIpzKGS0jQ+39AAAA AASEjNbmSfZ4ZiMZ5Yi0dNjNX2S+JjKaNbe0BS53FHXZcuSDu7dO7TvGdnOY FNM+6ra7b1i1aYnIaB4CmlyZG3dkrXx0ceot17aLjbb/1F39xv5l4U+vWA5Z c8pqcsrtFz26Z7QaS7E1r+TduU/2j463D+oor/JyrnUEAABA60BGa/Ni2rWz d6XJ/2+7Oev2PqN+N+spOcvk+ru3KxQlwtSV3CNv375hQo9h9rQV2zF6zuJp qzd7uMrRkdE2bM98+MfLZ96f1rlzR/vYjBO6D3trWsGFnLetlrLa7PJaLxlN rNT5zH2/vOXBHpGd6zKaXpezIk/t/QAAAAAEhIzW5j22aZPO9pQxSW/rSpOk 4R37vTAp90LOYaulpEZOOmXNndEu5Ra/MHlFclxfvS1tdegSk543e812l0dX u5Z53fbMtVszF+ff0y2+k9wVKOmGxfV57sasHywHanPL5YDp6VpH+RlqueVf pP9q/fULOpnaiXUWP7p0ecYX//qX2vsBAAAACAgZrc17Y++bcsYx6HW2YUMk na6rvv3DyXefyzlgNR+xjWbf7BntYu6RLeOXJcZ009tCYueeHTIfvm9dYbZI YV4z2raM9duzc9Yv6dmvuyTnS/2AmB5PjVt0zntGk0u+0LH8z3OfndlvXJQx QqeXL3R85rnnxXaorq5We1cAAAAA/pHR2ryTH5+cf9+99iHoRdKRDDqjpJ+V mPrp8pdrzAdFqKm1lLnf2+UvdjVUIBmtKu/w6mvu6RQRq9dLIikmDOxuWbtg 3c4s3xltww5z/qOZCQN7SbbLNPtFd9s4Zv5Zy35rTnmt94xWm1/21vQNAyK7 6g0ilcqPwH5i85NiO9TU1Ki9KwAAAAD/yGha8I9//nPWnNntO3awd6iJ/17f bfCRGZvOm/fJ6cwcdEarr9Jap6eV1Vepc8nvWkrP5x7MHDpVvjFMr4uINA0b dVXu+oVyRvNxrWNdRsvoOzhB0ssZrXdU50eumSsP7Vif0eqX4kiL8ovfZL65 ZeLiDjo5nRmNEdddP664tExshNraWrX3AwAAAOAfGa3Ns/cf/fOzz/r26y93 pRnkkNYrJm7t6HvOZLxVs+K9KzkexrH33Ykm0pB8I1t2+ZWcd2os8tPK7FXj VtXidXPJN9lv3jtgopwQ9YaomMhrJwxfWbBkww6L14y2PVO8JSZ4YNPSAcMT 9AbJKOk6R7TLTZ5RmbO3NlfMtth5KXVLN8tPuP7LvGfSh0zpoIuQdJLRFPnG G3utdKIBAACg9SCjtXn2/qOvT59OHT9RL4/sqDfq5GeGTew67N/v/8mlvNIr uUGlsxJ50H6z7Yts8XWZ1fJeQ8lD4itKTFB+OuONOf0nyKMs6qTodlHX3TDy gUeXrt9u9nqt4/YMeWjHHeaVm5YkpfQ3muQHUccYIpYOvvWc+S2r+V3lsuxL N79nzTt6MG396LgBRoPcj2aKiNr71j4rGQ0AAACtBxlNO47/74nxEyfoJMlo e2RYr8hO60fN/eeSl+UR+C0Nd5kFdDOaWe56q8k9VJn71peWvV85yrzfVvts Zfvasv8by/5Ps16ZNUDOaJJeio6Nuv5GW0bb4Sujrd2WKULcqh8tS752kDFS vpvOpDPc03/Cp1kvfWN+6yvzW1/bZl6/FHnpX4vK27dpYnqsFC1WUsS6iIio Pb9+w0pGAwAAQOtBRtOUv/z3f0266Sb7U8MMOv3QDgmv3P7Qd5lvWXNKa4Lp SruSW2a1FH+fs2/DqPk3xY+4NWHULQkpom7rfbWoW23/va13ilwJKWkJKZMT RsXHdLONhC9FtYu8dsII27WOPjJapiOjjRo7LCLaZH8Gd3xMlym9R03pc81t vUel2edvq1t6y0u/tXeKaMngDn31ksE+hKXeYHr9jTetZDQAAAC0HmQ07bDn lD/96aOpU6eJ+CIyTITedFPPkUfuLKiyHKjJLbaN8Vhc67M3zfZW6WX5Qsfi bywHbu09WgqY/elskdGRKdcPXbFh8YYdPsfe35qxflvWykeXXJXUR75AU2c0 2H8+AHr5Wk6pQ4cODz28uqKiwsqAIQAAAGg9yGiacuXKFfHfLVu32cY8lO9O i5Yi7u5z/bt3/fhS3gFr9qEap84yn71pZdaV75x98Mid/ce6hCMxR9sjyZxe 0dvZO8LkjBZlTBkz9KFNmQWF3vvRtpnXb8t+/NmVqx/P6Nmnsz3huS5FZ++V sycyZzr5XfmtHvHxJ09+bOXJaAAAAGhVyGiaYu9OevvtQyOSr7Z3bOmMxhjJ OO+qie/f+9Sl3APVucW13p99VjdmSG7Z6WWvH5y2cde0h0Z1HRgb1+6qof2G XT2w/6AEk0l+Jlmvfr2SUgYMTRnYZ0BPvdz7VRfQ7BnNZNL1Sew5bc6UVZsW r9+e7TGjbSg0r9i4+J7F0+6cPaVz1/bipzp1iRuY1EfMc8CQPqZIOQbG9+kx YtSg3n262J7LbZ97fdkW1LFjxx89/oQ4eNTe6gAAAEAQyGhaY49pJaXlQ5KS 5OESdfJDpdsZIxcMnvTn+5+9bDlkdQtlzsOJVFuKrfnvHruncJCpe4QUpdfp R41PyX540Yat+Uvz7ouNjRWzu/u+aRu25azfYrln8XRTlEEezdG2IHt0ki+y lPQRsYb7s+4s2Jnj3pW2ZmtGwTPZc5feYYjW2Z5DbRLTXz1mhPnB+zduy8l+ 8P6OXWLFfKbPm/LE0w/NnDtZHvNR0jnHQEdXWmRUzK8ZMwQAAACtChlNs37z m6MDrxpsG4lfBCGpsyl2+aC04wt/ccVSYrW8U2sprck94pzOanKLr+SWiLKu /M2H92yPj+wsxy5JGp2abF43v+BZy7JV98W0bydeunvBtA1P528ozJm3dIYx 0qiTjHUZzZbSxLcitUVEGRZlTH/smZw125av25a53jZOiAhoa7dnr9meWfCc Zc6yqfpIW6eYnNGk5OuGmtcs2PhMjnnNwg62nrWZ8yZt/umq6fdOrp+zU0yr D2tGUyTjOgIAAKB1IaNp2fsf/O6qQUmSbZhHvaTvH9Fj1YjZnyx9uTpXfgKa NafYuTftcm65CG5V5oPnVh0qnv9EQkQneTx8o3TtDcnZa+5dt9WybOX97bu0 00dLsxbesXbLirVb8uamzzRFiIxmH2TRkaP0kqQTGW3Bkrs2bM1d86T8KDT5 gWhyRpPHclz9pPgie9aiqYYIg15nNEYZpAjp6tShWY8sWLfNkvnQfXE92ksG kdFu2rRz1R1zb5Yvp3TNaA3XVUZEvfbanuqaGjIaAAAAWgsymjY5Rjksf+dd +71pBpPRKGJaTI8No+d+kvlKbV5ZtcXpokdLiTWz7MqD5b+6Y+2dfa6f0Gt4 tM4kRenG33b9/ebZ0+dPvnHqmLRZk+ekT5u7dNqcJXek3X3j+FvGXDVsgEEe jlHvuATRfsOYfMWjUdcnsVf/YQnT5k8pKMxftz17je2xaBu2mdNmj+8/rGev ft1ErIuKjLx5+sR5y2bMXz5jxv23Tpp63W2zbpy1aNo9S2ak3TX+ptvHDR05 WNJ7Smj26yoNppRR19xw402FhU+rubkBAACAgJHRtMx+b9qR4tLRo8aIRBNh 1EdKuiHt4ndMWPbFsj1XVrxTYymuuyXNUnJxRckv09Zc02VQ3WiKIgBF6+9b ftdDj5tTJ49q19E0ZNSAhx/PfmznA7PT0wYM6R0Va9KbDPZB/htuGLMN0Cj/ T/0wjXHxHe+YP3ntVvMaefyQ5QXbLaPGDXYM5BjbPmrZyvk/euahlRuXTUy7 PrZTzKDkfg9uytr0TP6YG4aLRUS3i5Ea5i85BzT7E9LsS1m0aLHaGxsAAAAI CBlN4+zj0h88dDhllP1JZ7oInW5Up37PT8r5cvkbNXmlNTlHakVSyy49v/Lw 4sGT5R43o8k2IodOZ5REHHvkxxljJ4wSr3fv23nFxqXrt1jmLLgtoW93Ry5z GdFDV/+QM9tXBpOcoYYk9123JXPd9szV27I2bM++dsIwexeYJD/w2pSeN3fj DvOqxxZPuPk68UrXXu1z1ixct808YtRg22wM8rWU7vek1Qc2o9EoJsvIyLBy VxoAAABaAzIa7DHtyJGSEckpJlOkSaczSYbrOw3ZPXnVmey3anKKrZZSa+67 1lXlmSPusN28pouKiegW3yW+X9dFltmrHls+6faxXXp1GD5m4AOPL9u4I2/6 vJu79+rmFs0UI3rY/s8gB7bhKVet35K9flvmWjmjZdkzWlRMZNf4zn2vil+6 cl7B9tyVG9MnTx/XrVfc0JTElRuXFOzIHXlNku3haMaGjOaWBXX1AzxmZWWp vZkBAACAgJDRYK3vYNr71j6TKUpEHslkiJCMN/ZIfj1t9dnsvVXZB/5n0c9+ t+TZ6YPG2wbi0CUO6jXz3rR7Fk9flDVngXn23OXTZy++/Z6lU+/PuWthztxR 40bExEZ5zWi2Cx2dM9rQ5EGPPJG9dkv26iezRVgbk5osXuzZp9us+6fOXXzH PUunLzTPXmCeMy9jxpzFU+ctmbbYMnupZc7AIX2U/WieFmjPaLNmzfrzv/37 347/r9pbGgAAAPCDjAZrfUb77fsfdOnaXWcw6fQ6oyTF6EyTE1KKZz7+5/Rd N3e/OiGqU5wpWmSqdrER144fvuqx5Y88nj0spf/oG5Iz1yxYszV7+cq5Xft0 iuoQGRll0tfddOa9J80+cL9ezmgJib3nL5+xdMXcRTmzF2bflTTiKvHiVUP7 PPKj7AceXTZqfFJM16jRN6RkPbxo3RZz9kP3xffrEh0baYqyP3PNT0azZUIp NjY2rlOXcakTvv76tLX+RjwAAAAgDJHR4HDhQtWrr77Wrbt8K5lBL8endvqY u/rf+MytK/pF2+8vk+8ki2kXc/0NV6/elL3uiZx+Q+KHX5dkWb1w4/a8ZSvm i7ekeh5uRPOY1SQpMjKyS9fO3Xt07tYjrmv3jtExEeLFQUP7rPux5cHHlg6/ 5irJJCVfO8Ly0MKC7bnZDy5o36mdY5AQ23I8j72va5hCZx9XZOBVg/9VUWEl owEAACCMkdFg54gtr7zyau/eve0PTRP5pkNkp5Rug9qb5OET7UM0Go3GLt07 JSUPGJo8sF3HmA6d2181NGF4yoD+g3qbTEaXBBZI6XSSJ7Hto4Yk9x80IrFD l1jJYOzYpdPAoX2Gjho4YEjfiChjXfKSdH4SWn1Ms62LNCRpeEXFl1YyGgAA AMIYGQ0OjuRSVFSUmJgoxzERbWwxyCi5Xk1Yn6TkR5NJekew0tvu/2oEg95g K6Mo+Tu9y2x1epOkXIrtoWv2DrL6sfd9zN8+umPS0OEVX5LRAAAAENbIaHBW ayO+eOGFF/r16yfHNBGG9LZIJHnp8VKV7844hcTEgeJIs5LRAAAAEMbIaHBn H0Lkpy/8vHefBEl+VJlB7rjS6QySvndM19SeQ2/tk5zWOzmt16hbEq65NWGU o25JSLmld2Mrwal6p9yaUFfO09yaMPLW3lfbXh81pufwbu26mOSxIfU6g95o Mg5PHjHhhomp4yekjp+oqAkTbxxz3dh771vw7bffWcloAAAACGNkNHhkTzFF L7/UPb6HSEDy0IlGeRDFyX1G/Wrmmk+zf/mN5a1vsvd+adn7Vc7er8V/m6G+ FnPOecup9p62vFGZ/fo3ljc+y37tlemPjE8YIV/qaJSveIyMjnrzrb2XLl2q lA+hs+4l0tn58+fV3q4AAACAH2Q0+Pbanl916d5VvmFMp5MMhg66dnf1HVsy Z+vXlgPWnDJrzrtWy3stWOVWc+n5nIO/n//svP4TY3WROvsdcQZ9565dPvjd B2pvLQAAAKCpyGjwxt6VVmut/fUbr3fv0UNfPzpijCliQvzQbeOXnlr+ysW8 khpzSa25uMZSIqpWlLm+LCEts1hQcXXO4e/Ne0vnPDk78cY4gzzOv1F+RLWu S7duL73y8oULF6z1t9R5pPYWBQAAAPwjo8EHR6556eVXevfuK2ciU4Sk00dK +qEdEvKGTf9g7rbzlkPWnJLa7CM1lmJrdnltTnlNTqnVckS82OiqzT1Sm1Nc K+ZjLqu1iCqtzTpSk1/yVdabv5iyamqfMV0M0aIxBpM8WmOPnj13/6JI0WAA AACglSKjwTdH6nnhZy/2SxxgHyBRbzDqJUM3qd2MxDE/m5J/avFL1twyq+Ud a3ZprbmkOqekRuSsRpXV9t+a3GL5axHNLKU1OeXyzPOK/3vxi4+PX3Jt1ySD fAeaZLANp5/Qt89zzz+vaCoAAADQepHR4JecfWzx59nnnp81e+61Y66XY5pe Z9TrIiUppWPfh66ZdWjaoycW/aIq50Bt3hGrpf5ax/rY5dJH5prIPLxlKakW 0cxSUpNXemllaWXOvv+6f9f+29dahk0dENFZfmCbyWC7xFHq06/v088+09BI AAAAoPUjoyFY7777XtLQQZJBzmkGvTFCp4+RTMntE/JT7tw3Y8Pflrz4veVt a265Na/Mmltaa+tTc5QjhdWVvdfM6S1rTqmt1+xd8cU3mXv/fcHPXpr68KKh twyO7hEp3w8nP7ra/mC0Hj17Pv8TuQfN/qQAAAAAoG0goyEo9u6qd959d+Cg wXqDSeQ0+6OtDXp9rDFyeLuErBF3vDV9w/+m/7xi2WvfZ755yXygJu+IHNly ymptJaewhhKvl1fnltbkiWhWYjUfqco6+E3GW19kvvaf9z//85vzZ/ef2D+q c0d9hElvkOSuM53JFNkjvlev3n1f3P0LtTcGAAAAEHpkNDTOb37z20GDkwzG iIjISL1OHgJfvgBSp+9saj8kptfkbsnmYbf/bEruR/N3ns5+/Wzu2+csb1dl v30p++ClnMMXcw5XWQ6JumQ+fNFy6HzO2+dyDpyxvPX3pb84fOdjheOWLR08 ObXzoL4xXTsaokwil+n0Bp0+IiLCaIwcMHDw4SPFf/vb8QsXqqw+L3EU7YmK isrPz6+oqGjBDQMAAAA0CRkNjfbh//tjaVn55Ftutt2eppevRDTqbL1dcu9a N1NMUsdeE7sPm9VvQt6IuwrGLNgxPuPVtIdK737ivblbSu96/O07Nr6etubl mx/4yQ3mx0ffu3zwrWk9R43uPGBgbPcuxui6wUl0OoPRID9EW5JunDSptLTs ww//n6MBvu9Bk+qR1AAAANCKkNHQRL/7/e+f+8nzS5YudWQinaQzimRl0Nn6 1iSjJHUydUiI6Taofa9RXQfc2Ct5cp9RN/YaOb77sOu7Dk7p3D8pLiEhpku0 3tiQywxGk9Gkr39l0aJFzz///Ae/+51joYHcgxYfHy85IakBAACgVSCjodFq bOxff/zJJzm5K3Jy87LNOb1693EkI70Ia0aTQSeP9qGXdPIDp53K8a18taRt SudUFdOu/cJFi1fkr/z730+6L9GvwsJCyU1cXFxBQYE4oppliwAAAABNRkZD E9XW1lZXVzu/8qPHf3zrbbfPvGuWfZT+oIwada34wZkz775j2nRLTt65H36w z1MsItjR9auqqhRdaSQ1AAAAhD8yGppDta2364Pf/X70NWOGjxiZPHJkcoOR TuV4beTwkVcnp4x+973fWF1vNGvKg888dqWR1AAAABDOyGhoPtXV1V9/ffrr wHxlq+qQPuzMR1eac1ITUU5MGcLlAgAAAI1GRkPb5rsrzUFEOZIaAAAAwgEZ Dc2qNkghb0AgXWkkNQAAAIQPMhraPPeutJkzZ8bFxflIart27VK71QAAANAo MhravKqqqsTEREVGEwdVQUFBVFSUt6QmfqSoqEjttgMAAEBzyGjQgv379ysi mDgCxesVFRX5+fkkNQAAAIQPMho0IiUlRdGV5ngrkKS2Z88eFRsPAAAA7SCj QSO8daU5+E1qIuWJmajVfgAAAGgEGQ3a4aMrzeHUqVPp6eneYhpJDQAAAM2N jAbt8NuV5tDcSU0c0kePHt2zZ08BALQ2hYWFR+vxsBIAaA5kNGhKIF1pDn6T 2qRJk8QpSiDLFQf8rl27xNzGjh3rY4YA0OqIz9WsrKyioqLjx4+H5pMaADSP jAZNCbwrzUGcdYgo5+P8xFtSq6qq2rNnz7x583zc4wYAbUl8fLz4wNy8efOp U6ea4zMcADSCjAatCaorzUEcsYEnNfEF0QyAxomPwQCvNAAAKJDRoDWN6Epz 8JvUkpOThwwZ0pxnPQDQmiQlJRUVFXHbGgAEhYwGDWpcV5qDOHonTZrUlJOW +Ph4MYd58+apfes/ADSG+PgSH2KB32AbFxe3evXqioqKZvpUB4A2howGDXLv SmvEBTniRwJPaomJieKUprCwUBz8zbBCAKAa8WG4efPmmTNnxsfH+01qRUVF arcXAFoBMhq0SdGVJr5t3Hx8JzURzfLz8wO/lhIAWrVTp07t2rUrKSnJR1JL S0ujQw0AfCOjQZtKSkoUpw1Ned6ZSGqRkZHOc5s5cyZdZgA0S3zG+rh7Nz4+ XkygdhsBIHyR0aBZivOHRnel2RUWFoqZ6PX6zp07M+g0AFht3Wr5+flxcXEe k1p6err4913tNgJAOCKjQbPEQRjCrrSqqqrNmzdX2ISwkQDQ2omPx9WrV3uM aUlJSVwNDgDuyGjQstB2pQEAvBH/9HscVCQuLo6YBgAKZDRoWWi70gAAPoh/ zdPT04lpAOAXGQ0aR1caALSk/fv3u9+hJl7hTl4AcCCjQePoSgOAFlZRUaF4 AIpke1gJMQ0A7MhoAF1pANDCxL/sxDQA8IaMBtCVBgAtz1tMY3RcACCjAVa6 0gBADadOnRKhTBHTxAey2u0CAJWR0QArXWkAoBKPMY1PYAAaR0YD7BRdaeKc oaqqSu1GAUDbJ2Ka4tFp4ls+gQFoGRkNsHPvSissLFS7UQCgCfv371d8Aufn 56vdKABQDRkNcFA8XJU/5AJAi5k3b54ipvFgawCaRUYDHCoqKqKiouhKA4CW Jz6BFc+2ZvgmAJpFRgOc5efnO58hGAyGZ555Ru1GAYAm7Nq1i2vOAcBKRgNc VVRU6PV65zOE1NRUtRsFAFoxadIkrjkHADIa4Mx95JDk5GS1GwUAWnH8+HGu OQcAMhrgTDEC/+jRo9VuEQBoS0FBgfPncGJiototAoCWRkYDHNzHDOE5qgDQ wvgoBgAyGuCwevVqhhQDANUphm9KS0tTu0UA0KLIaIBDUlKS81nBrl271G4R AGjR8ePHnT+No6KixJmA2o0CgJZDRgPsTp06pTglYDAxAFCL4o9mRUVFarcI AFoOGQ2wKyws5NIaAAgTipFD+EwGoClkNMBO8VAeLnQEABW5X+6odosAoOWQ 0QChqqpKMYzYqVOn1G4UAGhaYmKi88eyOHNQu0UA0ELIaIDV7dHVjOgIAKpL T0/n8gYA2kRGA4SioiLnM4GsrCy1WwQAWqe4TVhENrVbBAAthIwGWN2exSNO DNRuEQBoHVc4ANAsMhogpKWlOZ8JlJSUqN0iANC6qqoq50/muLg4tVsEAC2E jAZY3e5Mr6ioULtFAABrfHy884czT7IGoBFkNECIi4tzPg1QuzkAANnYsWMZ 2hGABpHRAEFypXZzAACyefPmOX8479mzR+0WAUBLIKMBVteMlpiYqHZzAAAy xfD7RUVFarcIAFoCGQ04deoUGQ0AwhAZDYA2kdEAMhoQ3ipPHNy9+ym73QeP VardHrQcMhoAbSKjAWQ0IJydOFiXzU6cOHHMHtYOnlC7UWghZDQA2kRGA8ho QPiyJbTdzn1ntldIaRpBRgOgTWQ0gIwGhC1Pgazy2G5CmlaQ0QBoExkNIKMB 4cpznxk9adpBRgOgTWQ0gIwGhCs5je12GyTE1pHm/jLaIDIaAG0iowFkNCBM eQljZDTtIKMB0CYyGkBGA8IV/WhaR0YDoE1kNICMBoQrz3eekdG0g4wGQJvI aAAZDQhXntMYY4ZoBxkNgDaR0YAwyWhXrlyprKysqKj4Ihjid0f8dlRVVanS ZrQ07YUTr2Pv042mDWQ0ANpERgPCIaOdO3fu66+/FlGrpqYmqB+sra29ePGi CHfiN6WZ2oYwor2M5iGQuT/VGm0XGQ2ANpHRANUz2vnz58WRL9JWU2YiflnO nj0bqiYhTGkwo8krvVsOZQePnRCO2b8hoWkFGQ2ANpHRAHUzWnV1tTj4g+0+ 80j8mly8eLHp80H40mRGs8qdabZoZiPCGgFNO8hoALSJjAaom9G+twnJrKqq qiorOXtt07Sa0aBZZDQA2kRGA9TNaCHs/Kqurha/Jl7f/njn552kz5876XMe J394LuPzKdInnWw1JfXLMvfpi7+U39p5yemnzsg/kvGDconFX05JrZuVWPSU jB8+rn+rLEO88mWZcuk7UyUpNaPYZxMVOcXT+BGKJOM2SbBz8JCMHB07u481 LOfEwd2O3p6ndu8+eMJHYvY2sduybM2rf6X+Xad+JfkaQF9r73eJrm84zc7b 6543iHwV4m4Pcw90IzcH73sksPa4bgGXDjw/62tfhtNOOlHpusgAGxDcYRb0 rm9YFcd78m52mY+9par9YYCMBkCbyGiAuhlNHPxNvBPN2RdffOH1Pf8ZzR61 pM9zd/5QVizqTG7q58o4VhevPumUesYRuGxzVmauuhdTv3yuuGFuucXOM2m9 Gc2em3bLN0gdqzt5tr9Uf9eU/cYprye2Pif2tWz7cBnifLv+R+vOrr2vXQBL FD/geN0+P/sb3l53X4Ry7nXxxalVKmQ0nxs5gPacOOi2UvUhzf/61s3N6S46 WZAZLejDLOhd39BO54YePEhGAwCVkdEAdTOar1QV2rn5y2iXnku15SbXCWxh yvmn5MmmZHw5peFF2ys7z+S6TPZDrq1n7WOrZ54zWmDUz2gefqJuksAuNfU3 sfy+ffbKJdedUB9z7QZxHefQ04l6EM3zlpycX/ewAd3m7tqqls9ovlfZb3vs W9pj6wJeX5cfV+y6xhy3fvdj8Lve0xiZ9paGyyW1ZDQA2kRGA8hoNrZONEWX mYfXbd/mFttzmf1FOY65vlJ3PWSu9w6xtpbRgoobAUxsT2kn5OW4TOj5R13b 42GawJunDHyeX/dwLZz7OB4ur7d4RvMzc3/t8fHjAa2vx8tjg+xHC/4wC3rX e97b7gFTRWQ0ANpERgPCLaP99bHH7CW+rq6qEuX7Fd9za+Ano3lNVXU9Yk4z kbOV/IX9RfkH61+pvwDSvqz6ayad65J9gjaW0eouB6u/mMyJh0FcApvYc2eG lzNu9x4gxV1NASyx4a4k1+vaPL3uZ3kepmrpjOZvlf20x9dTsgNa32bJaH73 Y9C7PpDjSWVkNADaREYDtJXRGnLTSdcus4Aymu16SPvXcoeaHLLktNUQ1uoy YP0dau5Vl8vaYkbzyNMADgFNHPKM5muJJxwpzHX8Ee+vt1hG+71P4h8Ozz/m b5UD6UcLz4zmez8GuevJaAAQpshogLoZraKiQvFwtGbNaK6JKfXLhm61gK51 lPNa/ddyXvN00aPtS0+JT85l9R1tIc5ovq/vCiSj+ZxD46519HqaH8DEdd/K /+N+raPna9OCvdaxYYme76/y/nqjr3VszBWYXhJGnf/6r//y8nN+NrK/9vjo SAvhtY5BHrd+j5zG7Xr3dSGjAYDayGiAuhmtsrKyqqoqJLO6cuWK124Fq9u1 jh+f/CE31Xk8kADGDHHqKat7K/VzxeAh9T1uLldIur9iHxzSxw1rPnhKWO5d UL7GFAx2DoGPGeLzlYAnbviuUnFHmsfeNcXpvqfRLnwuMZBRQny9E/gYGj53 U4j53sh+2+M9oAa0vgFmtOCOW79HTtC73mNU9NA0FZHRAGgTGQ1QN6OdO3fu 7NmzIZnV+fPnxS+L17c93I+meK6Zv7H3lZ1fts4y51ccd6vZ353SMPb+Gdc8 6BjA3zUSNn7s/YO2IcOPnXAbjL6y/qX6e3Lc78LxMwfF9O4zdJyV2wZKdwxh 7jOA+JrYQ+sU6a2hrY7Wuuc4xUOw/C7RaYYu3TIeXvccWgMYe9/XRg49X6sc QHs8rFTgY+8HeK1jEMdtIIdZ8LvebV0aHpVGRgMAFZHRAHUzWm1t7enTpy9f vtzE+dTU1Ihfourqaq9TeBozxNbz5fSkM/FKmdMzrDvJTzRzXP3op2tMprjE sa6rzkMcq4t79RPUxcAmPR+t4YnBuxse+Ot2O47t5DSYOSiW6H5/j3NUOeE4 wVWeJ7vzMrF775Kn25zcHzvsNn39/Bvm5aN5zvNzfs/L65562Pw8J9nvRm4W Xlc5wPYoVsplDj7XN/D70QI7bgM7zBqz661W96OJax0BQG1kNEDdjCaIgCaO /0uX3G4FC5iIZuJ35MKFC74mCiyjtQJBn0D6GqSvUUI+Q8CdeocZGQ0A1EZG A1TPaFbbrWSnT58+e/asyFm++sJciSmrqqrEr4n49fF/U5uHjGbr9vIwTkh4 I6NBE8hoMjIaAG0iowHhkNHszp07J34FxKH+RWDElJWVleLXRDEypGcuY+/v /NJ+r1mjB1dUkfoZzepycxbQPFQ7zMhoAKA2MhoQPhmtebmNvf/5lIwzZd4e aR3GGnEC2TD4xbFjxyqDvd0mrG7PCQdskDYunPYvGQ2ANpHRAK1kNG1zjMwg 90sEewoaTqesYYEN0raF0/4lowHQJjIaQEYDWodwyg5oGWQ0ANpERgPIaEDr QEbTHjIaAG0iowFkNKB1IKNpDxkNgDaR0QAyGtA6kNG0h4wGQJvIaAAZDWgd yGjaQ0YDoE1kNICMBrQOZDTtIaMB0CYyGkBGA1oHMpr2kNEAaBMZDSCjAa0D GU17yGgAtImMBpDRgNaBjKY9ZDQA2kRGA8hoQOtARtMeMhoAbSKjAWQ0IJyJ ZLb74InKSjKaFpHRAGgTGQ0gowHhrPLY7qdkuw/u3k1G0xoyGgBtIqMBZDQg 7FWeOHbQHtXIaJpCRgOgTWQ0gIwGtA6VJ0ROI6NpChkNgDaR0QBxgJHRACAM kdEAaBMZDRCczwHi4uLUbg4AQKbIaPv371e7RQDQEshogNU1owlqNwcAIJs0 aZLzh/PRo0fVbhEAtAQyGiAkJiaS0QAg3Cgymjh5ULtFANASyGiAkJSU5Hwa cPz4cbVbBACwxsXFOX84V1RUqN0iAGgJZDRAmDdvHrc8AEBYOX78ODcLA9Am MhogbN682flMYPXq1Wq3CAC0rqioyPmTeebMmWq3CABaCBkNEPbv38+ZAACE laysLOdP5sLCQrVbBAAthIwGWN2uqImPj1e7RQCgdSkpKQzqCECbyGiAneLO dHGUqt0iANAu8U+/82dyVFRUVVWV2o0CgBZCRgPsFE9KLSgoULtFAKBdR48e df5MHjt2rNotAoCWQ0YD7Pbs2eN8PpCSkqJ2iwBAuxQ3o+Xn56vdIgBoOWQ0 wE4cZlFRUc6nBKdOnVK7UQCgRRUVFYoP5JKSErUbBQAth4wGOEyaNIk/2wKA 6goLCxXjOHEzGgBNIaMBDorLHblFHQBUIUKZ86fx5s2b1W4RALQoMhrgIBKZ 4sSAx/EAQAtTPLAyKiqqoqJC7UYBQIsiowHO3C+wEYef2o0CAA1RXHaenp6u dosAoKWR0QBnVVVVihvVs7Ky1G4UAGiFOD2QXIlX1G4UALQ0MhqgkJ+frzhD OHr0qNqNAoC2r6qqauzYsc4fvzwWDYA2kdEABXG8Ke5KS0pKYvAQAGhuBQUF ij+R7d+/X+1GAYAKyGiAO8UAj4I4c1C7UQDQlolzA8UHL51oADSLjAZ4lJaW phhYjHsiAKCZVFVVJSYmKj51jx8/rna7AEAdZDTAo1OnTikGD+EvugDQTNLT 0xWdaLt27VK7UQCgGjIa4I1iHH6JIaABoBkoHogmpKWlqd0oAFATGQ3wISUl hZgGAM2npKREcdFCfHw8D60GoHFkNMAH9yf1CPn5+Wq3CwDaAveAJuzZs0ft dgGAyshogG9FRUXuMY1hHgGgicSnq3tA41oFALCS0YAAENMAILQ8fq6mpaXx MEoAsJLRgMB4PJ3Iz8/ndAIAgkVAAwDfyGhAgAoKCtxPKpKSksTxrHbTAKB1 qKiomDdvnvtn6cyZMwloAOBARgMC5zGmRUVFbd68We2mAUC4KyoqiouLc/8U 5R40AFAgowFB8RjTJNsTro8fP6526wAgHImPx0mTJnn88CSgAYA7MhoQLG9/ ChYvbt68WRyuajcQAMKI+GB0H7+RgAYAPpDRgEaoqKgYO3asx1MOcSoizjro UwOgcVVVVUVFRUlJSR4/KuPj4/fv3692GwEgTJHRgEbz8cdhYdKkSTyJFYAG HT9+vKCgQKQwbx+P+fn5XHIAAD6Q0YCmEKciKSkp3s5DhMTERHE2IsLaqVOn 1G4sADQj8S+7iGbeOs7sGAsXAAJBRgOaqKqqavXq1T461Jyv7Zk5c+bmzZuP Hj2qdqsBoEkqKirER9mePXtELps0aZLfz0CGwAWAwJHRgJAQpyvi9MPHtT0A oFnp6elcSwAAgSOjAaG1Z88eb8OJAICmxMXFrV69uqKiQu0PZgBoZchoQHMQ R3h6enogF0ACQNszc+bMoqIiBgYBgMYhowHNp6qq6ujRowUFBWlpaR4fqQYA bUZiYuK8efOIZgDQdGQ0oMUcP35cnL2kp6dPmjSJO9cAtGoikYmPsqysrIKC gpKSEnIZAIQQGQ0AAAAAwgcZDQAAAADCBxkNAAAAAMIHGQ0AAAAAwgcZDQAA AADCBxkNAAAAAMIHGQ0AAAAAwgcZDQAAAABUd+zYsUP13N8lowEAAACAKsho AAAAAKCujz766KyN+IKMBgAAAADqunz58jEb8QUZDQAAAADUdfbsWXtGE1+Q 0QAAAABAXSLjXLYRQYmMBgAAAADhwN6bRkYDAAAAANXZAxr3owEAAACA6hwB zcrY+wAAAACgKueAZiWjAQAAAICqRMD5wx/+cKje+++/7z4NGQ0AAAAAwgcZ DQAAAADCBxkNAAAAAMIHGQ0AAAAAwgcZDQAAAADCBxkNAAAAAMJHSUmJ4hUy GgAAAACohX40AAAAAAgfZDQAAAAACB9kNAAAAAAIH2Q0AAAAAAgfZDQAAAAA CB9kNAAAAAAIH2Q0AAAAAAgfZDQAAAAAaDHHjh07VK+0tNR9AjIaAAAAAKjC PY55fJGM1nacLN6ZkSrVSU3NKD6pdosAAAAAOJDRtOXkTkc8ayBymtrtAgAA AGBHRtMSR0JL3WnrPTtZXP8CKQ0AAAAID2Q0DamPaKk7T7q9RkgDAAAAwgIZ TUOKMxwXNzakNEIaAAAAEE7IaNqhuBetfrSQuuTm3LkGAAAAQC1kNO1w9Jjt LHYM7CiC2k4yGgAAABA+yGja4XpV48mGoEZGAwAAAMIGGU1D3K9qPNnwqDTu RwMAAADCARlNSzzceuZprEcAAAAAqiGjaUr9yI5uz0cjogEAAADhgYymMYq7 0EhoAAAAQHgho2mPPFqII6ilZti71AAAAACEBTIaAAAAAIQPMlqL+3hT3rOp ol7+2NsUH7xsmyCv7IOWbBcAAACAMEBGa3Eio+159Ut/U3350SIyGgAAAKA9 ZLQWR0YDAAAA4BUZLcQaspV8TeOm/6x//T/LUhted89ola8+6TSxy3zkSx8X lVU2c7sBAAAAhAUyWog1Q0YDAAAAoB1ktBAjowEAAABoAjJaiDVrRpNn8qxr BXBrGwAAAIDWg4wWYvSjAQAAAGgCMlqIkdEAAAAANAEZLcRcM1qq09iMqU9+ 9M+61xsy2j/LPrJNwLWOAAAAAGRktBBzyWh7Xv1P8a0iTCky2h753SfLNjX/ 2PuTfJo3b17TFwEAAACgichoIeb/GkX3ax3lTrTUvGa/1lHyKTExMaRLAwAA ANAYZLQQCyij2XrWXv7Y6UWXax3lCyOdrpMEAAAAoB1kNAAAAAAIH2Q0AAAA AAgfZDQAAAAACB9kNAAAAAAIH2Q0AAAAAAgfZDQAAAAACB9kNAAAAAAIH2Q0 AAAAAAgfAWa070KHjKaikztTJc8yitVuGwAAAAArGU1jyGgAAABAmCOjaVRx hi2ape48qXZLAAAAADgho2kUGQ0AAAAIS2Q0jSKjAQAAAGGJjKZRZDQAAAAg LJHRNIqMBgAAAISlpmS09PR0H1nM27tktLBARgMAAADCz9mzZ5uY0bwFMR9v kdHCAhkNAAAACDMioB07dqzpGc09i3l7nYymvuKM1IydxSfJaAAAAEB4sQe0 y5cvhySjOccxjy+S0cJEXTIT2Sw1lYwGAAAAhAlHQLM2ecwQRSLzG9DIaCo7 WbwzI1VqQEYDAAAAVOYc0KyhGNcx3RMf05PR1NeQ1MhoAAAAgMpEwPnDH/5w qN77779vf91+b5riRQcfmcs9pvmemIwGAAAAAE3kO3Z952+cEDIaAAAAAISQ 3+T1nb/HpZHRAAAAACBUAglfASKjAQAAAEATkdEAAAAAIHyQ0QAAAAAgfJDR AAAAACB8kNEAAAAAIHyQ0QAAAAAgfJDRAAAAACB8kNEAAAAAIHyQ0QAAAAAg fIRhRgthkwAAAABAs0KV0b4HAAAAADQZ1zoCAAAAQPggowEAAABA+CCjAa3F ycJxkpRRrHYzAIQcv90AAGdkNKC14CwOaKv47QYAOCOjAa0FZ3FAW8VvNwDA GRkNaC04iwPaKn67AQDOmj2jFWdI0rjCk37eUU4lf9+gMf9uuc5BOR/bP4d1 5OW6LN9rY4Jth+s/uu5bwukV1+YqNpiXreF50za6td73VMPKeGmh+4+6n2/4 ecVp9mJOIdsFHhuvmFEAm9fPtgl66Q3z8jBn75uibou5zM9li/g8xtzfdVlz 24x8HocB8v2rV79+yj3pfa0VzXZe+7pt4ZhXMEeR29YI7ghv5CHh48cC3gK+ Ph7df1N8vOLycih2vfOKuM3BvgDFfvf9W6Z8xefnttsUntbC9r77LBv5ueJt b7p/2AXwIeP3txsAoCnhmNFs/5y5nEOH9lxIca5Q/2+il4zWhNPzoDKaIjQE sDU8tawJrfV79uj0pqJRTc5oLvOrO50JyS5wzE655Z03ov/N2/gWeDgxdTlN 9JybvGyK+kPVdcv73BG+f8tcflT+2vtxGNwq+wn748aNC3ytvf86KLZHcEeR y/fBH+Gh3jiN2wJW14/HAJrp9cdDsett3D5QXdZJETuCyGj+Prf97kSr4+BT /kyoPzMVH3aBfcj4/e0GAGhK+GW0EF3x4XW5bn9IrZvYS0ZrSnOCyGjeGu9r 8d66YEL8N2HP77gsqakZTfme6z5q8i7wfgIW6OZt5Cmrl6X7mrPPTeFpfn52 RJN+yxq32r5/yv5ucaFLSPO51v67Au0/GeRR5G//BrFhgxBoz4u3LeBzx/n/ rQv4d6mJf+zJyMjwlI4yMsYFdny6vxvk57bTUhXXT4wrLMxw+Y1yeSH4VfW7 NwP9kPH72w0A0JSwy2ih+kcpgPzj7UWVM5rzX4N9Lr2lMpqPZjp1YIQyo4Vs FwTQpRPQ5g1tWAkmo7mfxXm8SNDrjmj8b5mXK9b887mxHG8WO5/EBxqgfB5W QR5FLr3YwR/hzZzRGrXj/P7WBfir1Ohd79RYl/3rWLLHjB1QRvP7ue1/Jzq+ Kc5wmqv46mShMjoGt65urzsvNeAPGb+/3QAATQnPjOYu6H+lWmFGq78YyPP9 Ne5bQ92M5nyS3dSMVr/uod4F/s6jA968jTohD2iDej4qvGyKlsloHo7DoPjY WMq2Ki7r8rzWgWa0II8ivxnN9xEe4owW4Bbw/fEYWEbz8ena1F3v1FbXJTu+ U65/c2c0l8PM8XV9SKv/38aGtIAzWiAfMmQ0AICz8Mxofk7uA9HKMpqXv1z7 vYmrbfSjOb/g0PRd4PcHA968jTkh9770AObseVOELKMpApJyuY3sQfGwSO9N 9XrUuK114BnNx0zCqR9N8tS+wLaA7w3QiH40RWd2E3d93fo55ufymeqxy7wl +9FcM7dLX18jQ1rj+tG8fMiQ0QAAzloko3k+Kwn0T+WNOxlyX673W0sUdwI0 Y0ZzWbD3TgVvs7C6nbUofqipGc3/nvK4JPeWuN9b4bb6vnZsaHaB/x8M9MQ9 NBnNeQs7z9lnG93O4pRTK9vp9RgLttehsbz+6im3iI8T48b1o/mYScCXU3qe s+8NGwTFkrzv/sZ8PPrfPD5+PBS73i2cuP8uKVrQuKPX+X3Pn9se5qD8Q1xG oXjTrYstKO6Huod/cAL9kPH72w0A0JSw60ezKv7lDdG5kDPlv4V1/9C2SEZT LMb13/GG9jqNseZ9a9TN0K0nKtT9aFb3syfF9+4tqe8PcF2/ccp7Q5xnoZh9 w7dNy2h+TnB8b97m6Udz5mEnet8U9VtVsW38HGM+DmyX3wL5a+/HYeC8bSwv Sd5xBu1trYPIaMEcRa5vB3aEe/7lDYbbxmloV0BbwOfHY8DdjJ5+PBS73ktH qY9PVLeM5n0j+/vc9rMTPRwOyj0csqs1PHVf+v2Q8fvbDQDQlHDMaFbXS34a 91dEP2fVigV4PiNS/pU02H8sPZ6NOC1Z0T6XxXm7BtD9NM7+Y7bByZrUWn85 xHVruHUQObXkZMOqO/1Qw0VFHufhepWXIoc2cqUCi0m+N29A28ajgM7j3Ted t03htD4uE3jIHV42sud84Hubhy6jee3m8LfWwfSjBXEUubfH/xHu/Ze38Run 4TAJZAu4raUi4Dj9uNffHe+frk3c9co/itTlHh9dZ55+y3xtZF+f2x5WwdtS PbS1UX8JCjCjuTfc0wz8/nYDADRFxYwW/FTBCG6O3qcOXT9aS2iufjRVNWGl QrU9GrdtWn7/h8U+DHUjQjO/MLmxx31lAmhYoFsguEtBQ8+tnbaQVhiaq9cD WmALCzyjBTkDAADIaH6mJqOprkmbsdEXpYUgozVl6Y0TFvuQjOaD575MP6vX SjKa514tlyucGxoVkiNE7eOdjAYAaDbqZTSXf6jDKaO53ZfRijJaU1obvqcL TVip+h93u3QtuL8bNGHbeFi6/FrzHBY+2xm6U+MmNEK9+SmOopbaGh5aobzC LtALYgObu9uh1lIfQZ7+IOF221fDqw2XdzZ+L6j9mUVGAwA0GxXGdfT0r3Pz ZDRPi/U+tZeM1gRh8qf7AHndU22B660+nu50cROijOZx6c21YcMmo4VydZvn PFbFjBbkgdhKzuQ99xl73syOaclorWDPAgBU0ewZLTBq/1Ol9vIRfkKY0VpM a2lnUNrkSgWFLeBFq98wrX4FAADNJkwyGgAAAADASkYDAAAAgHBCRgMAAACA 8EFGAwAAAIDwQUYDAAAAgPBBRgMAAACA8EFGAwAAAIDwQUYDAAAAgPARqow2 dfZ8iqIoiqIoiqIoqolFRqMoiqIoiqIoigqfIqNRFEVRFEVRFEWFT5HRKIqi KIqiKIqiwqfIaBRFURRFURRFUeFTZDSKoiiKoiiKoqjwKTIaRVEURVEURVFU +BQZjaIoiqIoiqIoKnyKjEZRFEVRFEVRFBU+RUajKIqiKIqiKIoKnyKjURRF URRFURRFhU+1WEb7pJMUklJ9i1EURVEURVEURTVfhUlGO5UY98+RiaLEF2Q0 iqIoiqIoiqI0W6pltK6GU33af9oz6pPOOlGfp474cuk9osQX8ruddZ/GR4kJ xGRkNIqiKIqiKIqitFPqZLQu+lP9On5xxw2fXTfk025GEcS+ylpw4b1SUV9l LxTfftrV8NmYwWICMZmYmIxGURRFURRFUZRGSp2M1ln3zxF9vntm63fPb/9m Tf5Xmfd//8rPr3z2jyuf//P7V18U336zZoV467tnt/4zua/c0RZIRnv6I6uT D592eXfbH63WL97O8fGK48f/+Fzj33Vf9Kq3P3e8If/Icx9arZ/vWx3Y3ln9 xheBT9zYsrfQdePUraPbZrQ3yeqyRt42qbLx7rvAeeOIKZ0nyNknFvPRNqeJ A3nF9WD44o1VrhPb9l19yTuiYe28t8T/3g/4eAh6pZrUKnkFlW3wPcNAD0KX OTuxN9t2hHhrif/FURRFURTV+srzqYEXqrc2wDpx4u/bnn7O72RimjOVZ0K+ dLWudfzs+qSLH31YXfnNlc//UXXs/Yv//qfLn/z98qcfiy/Et+LFmjPfiAnE ZIFc62gLFE7n5PZzUadzcn/n1croFMS7tlNlpyzz3IeubzU0o/4MOawymi0U WBWJpuG82jnXuKU522ZviBhBZjTbIurnb4+EzZbR7KvjPLFzRvPVEn/HRhDH Q5Ar1YRWKQ48MbH8te8ZBn4Q+v47gyKjuSzU1y6jKIqiKKrVVuDJqxVlNBG+ Ll+s8h3TApmmcaVaRrt20IX3SkVGq710qebc9xd+++63OzZ/+/RTF95/T3wr v3jmGzGBmMx/RrNlB2WPj+tZup/zarc5BPyu7Yz0jx73i3uHQt3Jc1hlNHld /vjRhx66/7748I9fKBOZ8pTeZfWDy2jKreqyuUKc0Wzffu7SHqeM5rMlfo6N II6HIFeq8a3y0gbfMwzmIFRkcz9Hl8siWqRrmKIoiqKolq02mdGm+otgzRfQ prZsRvu0R+Q/Bnb5fOzQL6ZO/HrF8ov/8ZEcxy5evPzx38/tf+PMlsdE/fD2 3sunPhEvirfEBGIyMfHnY4f9Y2BX8eMeM5qXc3WXv/Y3V0bzGA89NcDni96q BU5o69pjS2oNB1jdJnVJOp5b7rzxm5bRXCYIaUaryyzy9K79O14yWjDHRhDH QxMzWpOPyQBWJOCD0NY71qifdd0LFEVRFEW1hWqrGW2q9yDWrAFtastmtFN9 O4i0dTo/47vnd/xw5MCl//nvK5//8/InJ384vP9s0U+/fW7bt89sOfvSz86X Hb786cfirUt/+28xmZhY/Mjn44aLHw8mo/no4nF7pWnnw+5sE7eGjFafZVy3 oWPTObfWS8vlOTQqo9VfbucxR4cyo9n6BOWvXfajy/1oPlrSiIzm5XgIeqUa 2SrvOdHXDIM+CO2XjyoukXWtADq4KYqiKIpqA9WGM9pUT3GsuQPa1BbOaP06 fpE2/nzxARHBLp88IeeyHT/+7umnvhdfPP1U5aOPVD62+tudT5598fnvCjeL t84WvSAmExOLHxE/KI/x6C2jeTjVbLmM5j5ISGAZzXX8DS8xs1EZze+cnVak odfGpcvMtgrO2zDU/Wgem9oMGc15uU7dhc8pL+/0NhxKE/vRnF5p1Eo1olXu qxbAavo8lrwdhIrQpywyGkVRFEVpo9p2RpvqGspaIKBNbeFrHeMjP7vmqsqC hy/8/rdX/u+zsy8+J4LYt08/eebx9d/97JkfDr31w6F9373wTOVja+TXRUbb /RMxmZi4cuNDn40eKH68SRnN5czQ9Z6dEN6P5iUdOC8obPrRnBvvtCynVfAe wbxsZN8ZzedNTG79aC5n8m570Gc3kGMVFPuuIYr6CjL+977XY8nX8dDElQr8 rwqBdZA1sR/NeQW9TEBGoyiKoihtVJvPaFPro1npO++0QECb2uJjhnwaH/XZ dUO+27Xzyr/+74fiA9/veUmEstMPZJ1787Xqym9EiS9OrzKffeHpc7966XzJ QTGZmFh+jFp8lLcxQwLOaN4H32vKHUkusctD9HMZXs/qs9/B0yooJ5bn6Rjk vGnnuq7r5Vgp7+uuvAtJETECyGjK/KIYxMPxbf1oky6j0H/+hXJceq9b0vM1 nPMVl3E27FPvLfGS0ZTHkmJ6j8dD0CsVbKtc95rbuI4+ZxjUQehaXjs0yWgU RVEU5aU83RvhleqtDWR1Qj5lGJY9oIn/tsCy1MpoNWe/qzlTeW7fr0+vzPhm 40MXflNee+VK7eXLFz54r/KJDacftPyw//WabyvFZCHLaGIa1+dDNbzlzPVp U77frVuW8iFobs2of++NVSG4H02sr3jR7YFfQZeyW6fuzjJFT5CnMd4buJyZ N2wW1weEuWw0+1vOvZCukzm1Tczc6dFa9nedN7WP1a8LAp62dt1qKvrRPLfE 19730RIvx0PwKxV8q/z8rNcNHuxB6L6+njolvW1/MhpFURRFtamyaiCjteF+ NPlax9EDKzc+VPWH92svX7LW1p4vO/zNmhVntv7o3BuviRerfndUpLZvn936 zfpV598pFhOIycTrlQUPf3bNVU251tFP+RyOr7ED4nmsQDKa46zYy+lx/Sm9 93uOAjvSPD2w7MN9jV9Z3/1oLVr2ILDPYxyw74K3fd601Ux7P3Tl+4gNQfk7 CD1sUvdpPPwO8og0iqIoimp71eYzWtu+H80xZsiVf3xac/Y7e6/Zmace+/bZ bWd2/LjyiQ1nHl//7c4nv3vhmTPbHr/wu6NiAjGZmLjpY4b4qfDKaC4dJa4T 1z/TynbRWuCPqQqwJWKGLpfeOTZvYB0f4ZbRPvdyANgOmC8CzTgazWg+DsL5 OU8/536XpcfGeL/WVNWtR1EURVFUSKttZ7S2P66jY+z9n+w4X3a4+suK8+8U Vz6+TiSybwr+f3vnzhtHFcdRJaGgQUJJKCiC0vCSAhUPiYIPAB+ABmgQAqpQ IaWiQhRRGhA1BQgJGhReCRIpAIkkch72xsraY+9jln3NOvau43i9dmyF384f X8azs87GHmeDfY5Osbu+M14/ij26d+58pNcbx9/Vg7lTn8x9+nH3Dtca8OtP Gnz3vfe32WiJK98S76Vlf5cdbrT/3kOfwbbccVt/+tgVee43eafnRxs4B3ob bWifxtcXWya/7XubiEzxr5+im//HpmXyP2HCnRr6futwYeeGK/JY6IiIiLjb 3MWNthfuj9Z7D+ulv/64+e1Xt878sHj2x1s/f9/1zOnFX04vfPf10vk/I/ew flYHbnYP6+02WtKx/T/x3pdG+/dH69do28yf5Dm45I04NnzMvss5Ey6/2vqb 3Lobrnrr9+NvcR7qwWi0mDvUaF0T/wnX9z+JX3PX972tDyXQEBERd5+7tdE2 D7EdzbT7vGeIs/TCk+1zZ5ez453MlZXc1Fprzj7DrTVnV6YmOmNX9CUN0LDY gUP/Y712Hxvt/2W/u1TvsuuPHshGQ0RERByau7LRBkmwncu0oTXay890Rs6v BrXlqYn277+t5Dz7NK8HeqoX9SUN0LAHsNEQEREREdG8cy8M/d0O6OSkN0h8 aczc7Fzq3304jXZwn//cE63PT7a+OHXjxPHgvTdvfvPlalCXeqCnN058qC+1 PjvpHzuiwTQaIiIiIiLuEYfTaIf2d/d4fP3V0otP5Q8fyB0+EHzwdvvcWRm8 /5ae5h97qPTS0xrQ3cvx0H4aDRERERER94iDN9ri4uLCwsL8/LwabXZ2VgO2 s9ZRIVY48kj3ztThNNnfrxyrv/OG1IPuKwf35R9/WAM0jLWOiIiIiIi4d1Re XbhwYXR09Pr169PT02q0crlcq9UajYY1mqJMabYYYo2maos2mg7cSqNttHD0 Uf/5o1IPNh859N8YIiIiIiLizqm8unjx4tjYWDabVXD5vu8aTSHWbDYTG03t pgEamc/ndeD2G21wh/4bQ0RERERE3DmVVyMjI5lMZmJiQsFVKpUqlUq9Xp+Z mYk1WrvdtkvS9Io1mkYWCgUdOEijISIiIiIi4l1VXl26dOnatWuTk5MKLncx mhotejFaO8Q1mtpNAzSyWCzqQBoNERERERExFZVXly9fdhuGxC5GizWaLXe0 3R01QCN93/c8j0ZDRERERERMReXV1atXbcOQUqlUrVb7LXRcWlpyjabXNcC2 39eBNBoiIiIiImIqKq9GR0ftYjQFV+8kmjXaUogtd7SdQzQgCIJyuZzL5Wg0 RERERETEVFReZTIZz/NsoWNsEs0tdFSgdTodW+5oV6XZJWmVSkVxR6MhIiIi IiKmovJqfHzcLXS0STT1V6vVii507ITYVJqteHSXpCnuaDRERERERMRUVF5l s1lb6Fiv122VY+Ik2vLysmWam0qz5Y6KOxoNERERERExFZVXnuf5vm+TaLbK MXolmk2iLYfEptI00u6SRqMhIiIiIiKmovIql8u5SbToKsfYJNrKyko00/RV 290xCAKdBBEREREREVOxVCrVarXoTasTA+327dvRTItelaZMq1QqCj3f9wuF Qj6fV/dNT09PTU15njcZMgEAAAAAALC3ya5jT62VFE1KJwWUSqpYLNp++7aX 4+aBFms0tw+/jtKxOkOj0ajX69VqVb1WLpd1ZtWfqq0YUgAAAAAAAIAI1kqK JqWTGkolpToLgiB2NzSVl7tpdbTRVldXezPNZtPm5+d1eLPZVKzpbNZrOrOS Td+iGlIBAAAAAACACNZKiialkwJKJRXbxdFtEpIYaNZosUyLTqjpDK2QZojO PBtyI2QGAAAAAAAAIlgrWTdZmtn2IG6HEDd91rvKcXWdWKZFJ9RsT36LNWFn jlYbAAAAAADAHsdazGHFZPVkJeXqLLq+MTHQ1tbWejMtNqHmSs1izfWaSzYA AAAAAAAwXC5ZPVlJRevMTZ8lBpoRy7TYhJqVmos112su2QAAAAAAAMBwueQC yl16Fps+6xdo0UxLnFCLlVpirAEAAAAAAMCtnjTrrbPEC9Bcmv0Dlpmh4Q== "], {{0, 0}, {1164, 1165}}, {0, 255}, ColorFunction->RGBColor], ImageSize->NCache[{582, Rational[1165, 2]}, {582, 582.5}], PlotRange->{{0, 1164}, {0, 1165}}]], "Print", CellChangeTimes->{ 3.7560804779092913`*^9, {3.75608184954681*^9, 3.756081859163489*^9}}, CellLabel->"During evaluation of In[4]:=", CellID->853689942] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell["Properties and Relations", "Subsection", CellLabel->"In[5]:=", CellID->754506620], Cell[TextData[{ "The output of ", Cell[BoxData["BirdSay"], "InlineFormula", FontFamily->"Source Sans Pro"], " is an ", Cell[BoxData[ TagBox[ ButtonBox[ StyleBox["Interpretation", "SymbolsRefLink", ShowStringCharacters->True, FontFamily->"Source Sans Pro"], BaseStyle->Dynamic[ FEPrivate`If[ CurrentValue["MouseOver"], { "Link", FontColor -> RGBColor[0.854902, 0.396078, 0.145098]}, { "Link"}]], ButtonData->"paclet:ref/Interpretation"], MouseAppearanceTag["LinkHand"]]], "InlineFormula", FontFamily->"Source Sans Pro"], " which can be copied and pasted:" }], "Text", CellChangeTimes->{{3.7560812163853436`*^9, 3.756081244667432*^9}}, CellID->498896398], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"BirdSay", "[", RowBox[{"a", "+", "b"}], "]"}]], "Input", CellChangeTimes->{{3.7560812059906836`*^9, 3.756081210418536*^9}}, CellLabel->"In[1]:=", CellID->40134163], Cell[BoxData[ InterpretationBox[ PanelBox[ RowBox[{"a", "+", "b"}], Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], $CellContext`a + $CellContext`b]], "Output", CellChangeTimes->{3.756081247170349*^9, 3.7560813112212477`*^9}, CellLabel->"Out[1]=", CellID->88360206] }, Open ]], Cell["\<\ Copy and paste the output from above into another expression:\ \>", "Text", CellChangeTimes->{{3.7560812546650996`*^9, 3.7560812587449665`*^9}, { 3.756081320065979*^9, 3.7560813235698724`*^9}}, CellID->700044620], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Sqrt", "[", InterpretationBox[ PanelBox[ RowBox[{"a", "+", "b"}], Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], $CellContext`a + $CellContext`b], "]"}]], "Input", CellChangeTimes->{{3.756081269225634*^9, 3.7560813031795287`*^9}}, CellLabel->"In[2]:=", CellID->33037086], Cell[BoxData[ SqrtBox[ RowBox[{"a", "+", "b"}]]], "Output", CellChangeTimes->{3.7560812722475348`*^9, 3.7560813113122673`*^9}, CellLabel->"Out[2]=", CellID->420312669] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"BirdSay", "[", "%", "]"}]], "Input", CellChangeTimes->{{3.7560813499040112`*^9, 3.7560813526249237`*^9}}, CellLabel->"In[3]:=", CellID->465151328], Cell[BoxData[ InterpretationBox[ PanelBox[ SqrtBox[ RowBox[{"a", "+", "b"}]], Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], ($CellContext`a + $CellContext`b)^Rational[1, 2]]], "Output", CellChangeTimes->{3.7560813559998183`*^9}, CellLabel->"Out[3]=", CellID->638814548] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell["Possible Issues", "Subsection", CellLabel->"In[7]:=", CellID->92483860], Cell[TextData[{ "It\[CloseCurlyQuote]s very tempting to ", Cell[BoxData["BirdSay"], "InlineFormula", FontFamily->"Source Sans Pro"], " everything:" }], "Text", CellChangeTimes->{{3.7560813944645653`*^9, 3.7560814028732924`*^9}, 3.7560814408900657`*^9}, CellID->47491018], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"$Post", "=", "BirdSay"}]], "Input", CellChangeTimes->{{3.756081405845196*^9, 3.7560814099300623`*^9}}, CellLabel->"In[1]:=", CellID->238955758], Cell[BoxData[ InterpretationBox[ PanelBox["BirdSay", Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], RH`BirdSay]], "Output", CellChangeTimes->{3.756081422149647*^9, 3.7560814570425167`*^9}, CellLabel->"Out[1]=", CellID->141061132] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"1", "+", "1"}]], "Input", CellChangeTimes->{{3.7560814261265197`*^9, 3.7560814263455315`*^9}}, CellLabel->"In[2]:=", CellID->508643742], Cell[BoxData[ InterpretationBox[ PanelBox["2", Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], 2]], "Output", CellChangeTimes->{{3.7560814272295084`*^9, 3.7560814571365147`*^9}}, CellLabel->"Out[2]=", CellID->52298612] }, Open ]], Cell[BoxData[ RowBox[{"$Post", "=."}]], "Input", CellChangeTimes->{{3.7560814314373465`*^9, 3.7560814336172943`*^9}}, CellLabel->"In[3]:=", CellID->473599708] }, Open ]], Cell[CellGroupData[{ Cell["Neat Examples", "Subsection", CellLabel->"In[13]:=", CellID->540091361], Cell["Have a bird say a bird:", "Text", CellChangeTimes->{{3.756080780066501*^9, 3.756080786394287*^9}}, CellID->591190485], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"BirdSay", "[", GraphicsBox[ TagBox[RasterBox[CompressedData[" 1:eJwkumd0G2earTvr3D/35/117lkz021LJJFzFaqQKiEVUMg5Z4AgwJxzzlGi JCZJVE4MyjlZVrIsyQqWLNlyjt1u22272x3n9jl9P/aAH7FALi0K3Njvfp9d 4KZ0rbv8f/zbv/1b4/8N7typVqqhIdXu+X/AF76axkK+Jpc11zTl8rkGRfr/ At8cBp9Z8LnxmPEEtDa30uiUUTYR6VAYHDa3Ox72RgLekNfndzudVtptoV1W M2NzE/YA5M6LvHU8Vy3LUcumM0IqgmA2LaGzGEi31RBym1N+ayFkb4g4a8L2 iF3vMFv1ZgeutxostNtvSyRDmVQoE/WEnSY/TXkotYtU2zGlTg4jMrGAx+Gx 2QKxSKxQKA00ZnWTrpDOG8FtHrWRkWsIOYqiMolKJjEqICepCJvIlFUXN1Mh o8aEQQSO68x2eywXae2tnplvWjrQuOtI865jLbsOt+4+2nXg1NDaxcHj54dO XOhdPd535FTX3tXOXUfaFw80bl+unllI9Iy7U1WkwcITC0tZpVwuVyaR6HDM YjGbLCYDrbd4vEaHV2Nyw5RDSjhQrYW22mORQCrqTYXdUb/D76C9QCuLWc9Y lbaA0JXjeurZrnqWq45rzvEIp0Stx3GC0RNORht2mNM+Ju8x1XtttW5L3Ky1 GYx6s5U00YzD5gt644lgJuZP+hxBi8GrIzykxkOqbZhCJ4cQiUjI4/J5PJ5Q KEaVMKVX0HbcEdL7olp3CKPtKkKHIigikSgkIh0iNStlTgwN6TVhI+ahUBMG EzhGGMzmcCbU2FWY2Na6+3DHgeMd+9bb9612HV7rOXx8YPXU4Pq5ofVzfasn eo8c79p/tHP5cNvSgea5PXVbd6Z6xpzpKo3WzBeLS1llLDZbLBJplAq7zebx +50ej8PrMTu9mMmJaO0y3ALhRr3JGgz5MnF/NuJOBZ1Rt9nH6M0mRm1ySywp rqua7WtmeRtZ7mq2KcYlHEKVTqFS0YTGbTSEreaUg8nb6SobXbTSMSNlN+j1 JrOWoZ0eWzjiyaQC2Ygn5rJ5acpJYS5M7SZUNhzVwjJEJBRy+Xy+gC+QiBUa iDSozC7CGdF6EoQzRJidGpJWIggwlUoq0sISGpFZVXIgl5dSeiiFUQXhmAbT 03p/wlvTmh/b2rR0sPvgqZ7Dp7qOHu8+dqLn6PHeo8f7V04Orp7p2xBqpXPv kY49h1uW9jXv2FM3s5TsHnFmqgmDnS+WlLHK2BwOeDYKOWyxWAPRuDccs7o9 ZpcHtzgQnUVOMrCG1hoZp8sWD7nLY/502Bt2ml0m8Pva5OaQgMmxnfUcbwvb 21zmqOSYomzSwQMDpFBpVQo7QbqNVMSkS5r0GSOZoDQ+irAaDHqj0WClfQFn Iu7Ppf2ZkDNkN7sMpA1X2TVKJ662ahRamRRoJQJPji8UyhCZWotoGQ3jodxh nS+mdUZJi0dNGjWoCpdJMJmYhKRGBGIUcotSbscUVg2ilUvVqAbTmilnyFVs zgzNNM0DrU73HTvXs7LWuwKEAnKt9xxa6zm43n3gaMeeQ+279rcu7mncsath 267qqflk14g9WYkbHFyRqKSstIzN4vD4cljOWB2BWMYfSwOhGI+PYhwqgwUh zUArUmtwO8zxgCsX9adDnqDdZDMbMKNVxgQFtnKuu5nraWS7a0vtBTYdZuEW HopBckSJIiYcc1BYwEBETVTcSIW1mEdHmo0GrcHA2JlQ2JOO+zNxbzxg94P0 ojBaCTMqxIYpTUqEgmFEKhGKxTyJTICoYIJWm1yYzU95wnpvlLIH1UarmtRp FEq1RIxJRbhEpIWkBkRmRCFaARtRGQFJFYhGSdCkzW/N1MR7Jmq37m7fs9K/ cr5/9VTPkfXuwyc7Dhzr3H+sbffh1sV9zXPLDbNLDbOL9VsWa6YWimOz0dY+ WyxPGJxAq82sEmAsNk+AKNRmp88XL/fGcyaPF2hlsDtx2qzS6hGMwAnCYdbH /c5cxJcJekJum8lEo3qLyBQQ2ICvKlmOujJ7ZQmTKdN6OQqDSKaQSoEVIFKB WHCVT4+HaDJEbxgsyBjcNqvVbnW6bdGIKxXzJELOoMfiNOnMpFqPyhilHLiL wcAYo4gclsGoBFGJ1QSsN6sZD2bzEXYfaQVxalNojUoNAUMQLOKrhHylkKeR CAlIRMklWrlEh0IaSAohSkijwxg3HauItA2Vj87Wze1p37vafeBE134QXGst u480L+1rmFuu27pUNbm9any2anxbcXRLcWRrcXhrqLGTCaY0FMMViTezwBBy 2XwRqiFN7pAnU/Skixav3+rzmd1ug5WhaANGEhRBmPVk0GXNhfzZoMfvthlo E0xaBHofxxRnMRG2McM2JIFQfNwqUeIoLFfIYDUEUSgMtPLq8KBJG7YYYlZT 2EIHndaA2xHyOlNRVyriTABTORgbyHstbtLIwezYCaUFU9AaFYljKg2B4JRS R2Nmm97uNboDRqePsroUpBFS4RJIKRSJRDyOjM+B+BxEyFOKeGAecViKIxAq lYikkFSJKfUWyp/y1nTG+6cqJufrduxt2Xm4bdfRlqVDTXN7a7cuVk1tK4xu Kx+aKh8YKx8Yzw9OVAyNl/ePB+pazf64ijCyheJNZZzNLC5YyXIVSYOXt7za W15r9fodwaDV57U47QazidJqKQLXk5jbaox5nHGf0+Oy6kwWGWnjEK4yfaBU F2BRHrD+IJLWaPV6HckQaiuOMRjGEBqnnvCbdVE7HXeYY3YmZjPFneaEx5bw ORJBeyLsiAfBf+z0u1wOq9lm1jr0mItSOwiF04hbGJPBbDFabDan1+n2uvx+ TzDkcPtpq0OBUSIZwhfJQIKwuRwelyXksqRctkLEB6OHI1I1AsFiCV8kESEq hDJT7rir2BrqHE0PzxanFuu2L9dt3w1yqW5mvnJsa3F0qmJoOjcwnu4dBgco lukdyXQPB2paaH8cwXUsofj10rJNZWzgK0iJG10hd7bWlas1Ob12f9AR8Fud DqOJBr5Sq5WYGjVqNV6rye+0OGy0FmhF2YFWJVovsBMPN0M4TRt0Xqs+7qQz biZuN4ZM2qBVH7EbY04m7bFkvNa0yxx3GJOAuHz2uNeaCjpScXc2G83ms5lC IVORz6RjCY8jyhjCZirsNgeCfn8kEohEo/F4NBaOBj0xv8vvtDO0SaXCBUAo Lp/F4XC4PB6HI+SyZRtaCShERqJSzb+0ArAhgBUQZlQzPjpW9Df1Rbsm0kOz hcn54sxC7cxi1ehsfniyYmgy1zeWBfr0DKf7RrIDY9me8VzPeKi21RiII5SR JZC8Xlq6CexCnlCMqPTOqCNR40hVMm6vxe9zBLwWl0NnotUEjigVcgRWoTCj o9yM0W4xGswMqnNwScdm0lZGWESYUUMZvFamGHC2pLytKU9D2FHwbpBVxmdN ++xpvzXqMIYs2pQXDLIn43dl/I5c2F2Ri1Q3FFv6e9vHx7qnpjoGOupqyivT 0fKYN5+OFGuKhdqaQk1NRWVFJhvO+G0Zl9ln1pkpjQqWi4QSLk/AYfP5XJ6I z4VEfFTMVwN4QGU6FUSgkBxMp0DAksj4sEZKMBpXjMnW+5sGop1j2cEt5SPb KkZmK4a2lA9Olw9MZvtGM90jue7RXNdornss2zkKTrS+wxxOoZSJI4KAqYBW pTwBV4aoTC5LtALEvsHuYNxuq8dtcTq1RlqJYTIEFUtlkEyqIzQus8FpMZrN No3eJaQcZZiZqzFLcTOFG0OMuRjytKYDbUlfY8RZH3HVJn3FpCcXdSQD9qjf nkmGqguZ2kK2kI7l4r7yuKepqdA+0je4MDd+9NDk2srI7oWesb6u/vb2zuaW xvrW/u6O4cG2/r6G1vrqmnR5wpcOWD1m0qBBQBZJBCIhXyjgCUQ8HiQWqGAx icooRGpQQzSOUAoYlYoFAmEpX1gmhARKCjLYcXfCVt7oq++Jd42leqeyA1sy gzO5/qls71iyazjbM5ZtH041dEeqWyJ1LdGG9kCxgQmlEMrEFsGbWNzXWewS Lp8rlcOUmfanzP40ZqApmtabzTrajGsNcpVGDClEYgSSygmNGixEr83stNu0 Jjuks3JwE09pFKsMKiXu0mIxK51xmjJ2Q85tynsZoFVVNpCJulMpX2VdVXt/ f+fwUEd/d0trQ01lqpALNnXWDM/Pzh09tvPSpeUbN+ZOnNp6+PD47sW+2cne ybHBLTMjC3ODs1u6xobbBvvr2psrqguJZNjpsFC4BhFLpQIhQHsgCSIVUihk 0qA0hpgwhNagOqCVTArgrIwjKOGKSsUwHyURgxNzRU2pGiBXpH0k0TWR6Z1K 944nOofiXUPJrqFEY48PBFGi4A6Xu8JZWyijdflh0sgSw6+x2K+xyjazOaWA Y1QkxnjAJMJqtYIglAQB7uVqXAyr+FIFX6oWwRpcjbnM+ojbGfA4aatZobcI cJqDaPkwLpcrGEzhpjC3DvPTeNSmT7nMVXHgKx/oeuXV6ebBvoEdS2O794zu XOgfHWyoztQUku2D7ZP7lnaeO3vk9p2j997e/8b1pQvndpw8MX5gz/DuhYk9 u6f27p1a3j22c2l4YbFvy7b2kcmGrt5CfX0wHgZMC1atXCxSy2UEIlMKeCiX rZFyNTKQWixSLpWLhbyNJBNs5vBfYwtKBHIOjEtIK+6IMelaf313uKk/0jIQ ax0IN/UFG3s8tW3ebJ09mNZb3Fo9oyNNhN6CUkapimCJpa+XsTaxSks4HBYw qxxRkAbMYJOgKKRSyZRKmVIlQRRCSMmHVDxILURwtYawm3RhNxP2OGw2BjMY RBotT05wZSoZJNfJZSYFDHjSSSljNn3azRSS/mIikI36cnUVjROj/bv2Th05 NnXw0PDEWC7uTcc83UMdI3u27bp4YfXe/bX794/cubP3+tWdFy5sP3F82+qx 2WNHpg8emNq7Z3zn0sTizunF3SNzu/qmtrUPjNS0tiRTcbvJoEMgowIh5bJc 1Ltr+9C1y4fevn18oDMlYm2SicF0Clgc/iY299dlnNc5ohIBxIExCWHRWMN0 OG/N1DnzLc5MkyPdaI9VWYJZozumZewaAkMBcoiFcrEMtAeBGN7M421iszaz ywA1iMRCGJJolCiF4TyplC+TCSBIjCACCOFLUK5EwZOqpHJgK1Ck9QGHIey2 eGw2gN9SDSlAMJ5cKYMQQiYDLcOkQpw6ddSuLw/Yi6lALgyWlzOVz1T3DnRs 2T4yv9g/NVVZnWlvSV8+f/CzTx/cvH/mzM0r63fvrj24t/bWW0fv3Fl+4/ri hQvzp09tW1/dcujg6NJC9/RU5+ho7/hE3+xsz9R0W/9wU0dnoVgRCXrtekoH Cw/PDf7ty9tfndny2emt//XN47/8/Kwiay8pKeXzpaXsDa1eZ3NfY/NfBx7j STkyTKikFXoPYYuRzjhhC1HWAGEFFdiBG2xaUk+iSrVUKudzJFyOiMtlcUBS sTaxy0o5LL6Ai8IyrRrVqVGtRsURi7mgWUhlfCnMlcA8CcITo3yJQgSsBrBM q3NbdCEXA7aegaYRUi9WaEEHAVppZLAOltEqxG0kY25TZcJblQqkwFK1Gz0B b6RQXdk50NzR19BStX5uzw+/efLPf/7jn//86z/+9xd///t3D1/eO3v/7trb bx27e2vfnZvL168tnDszs3oUmKp7ZrK+oyNXno0l4slMJl9ZXVXfXKypSyQT kZDXYaJ3jdWeaAs/W2h72hM66FF8fefwHz+7+8PHt2k9srkU/KYCsMI2byQz /7Uy3q/L+CV8mCVWciFcqtRLNQaJWgurtZAaR9SYQU2ZlIQRRrQSiRoMNY8r AejG44LRK+WAH8WWANYFlVOLuQ0kQ2o4YilXLP3XvexfB8gF86UISHgUVesI rROAk4MO2EyM2YTpTDLcKFThUhQQDURAEpBaQYsxG3BUp4L5qCfkMrkA5lto uz8azdXkqor37l/+5fPL756b+c2LG399efEPz0//7cX1/+/r+7/8+dtLj24f vnVr3xtXd106P3/m1PSxQ0NLO1oHuvMVOa/FpFWgWqXSrDf4ff5gMOQDy9ps rIjYV3ozC0X7tBu92eA/nWHe2lb7+bmt/+fTt08fntlU8is2D9QTLqBuIBQ4 m9iC11mCTRsGA/tRXCaWgCziiGRCsQyVySkUtSvkLoXciUJ2BCJBa+eBDsgD WpWw2AB6pRIBgUB2SuOjKY+O+G+tuCIpXwysJeNKJBtHLJGAPowoSTVm1ZF+ Kx12WOyMhaJtsBYwg16q0qIoolXCPjOV9FqBSpXxQCrkDHitDvDvXHaLM+D0 xy9cPv35lcVbixX/+OcvP335zs2+0Hql6XBAcbsz+cnWtq9ur5568HDnuXPb 1o9OHDk4snO+c3SgrqkmDX4Qo9Mq5RpYAl4SAMdGnd5sMIDy1ZVy7Kj1bs+7 55LWYUpSh7JO98Q+WRv46enp339xz2DE/+PXpWUc3msl7NdZvA2JuMLNHMFr Zdx/PRaUcnmgEYNMY3P5Er5QC0FelTxAKIKkwqWEdFKxXMADGbWZzQa+4vJ5 wFc4JLXhSpcOc1IYEIovlgrAkUhFEqlYJJEAupLIYBkEkBRXqWgS95jpoN3m sjsNFrfS5EB0VlhjJAjcSWsBkOeiroqEtyLujwN5fHaPz5vIVZhc/p6h/h8/ ufHejsJbc/m39gy+fHxxMkOPu+XDNmSLXbGN4DzZ1vDHTx/sP3lscOdc78xo 63BrS2d9Q31FeSYcD7k8dtpAqDAlooRhTIXhGKnCsK0V/qWosTdAbrHjXTpp QLJprT34fLHhd1d3//Xbx/dvrwkh3r+/tulf8c7ezOX/uoT1WgkL2KyMzWdz +BsXEjl8ALQsNhc4SCOROFCFH4wGqXSpEYNMCvP5LC4PoAIQXMDnA74Fdd2s QBg1atMo2QB3JeAmlYnFqFRGQigFoTpIAZBUJYcxBaLVKEHVdVssHofL7Azg jpCa8eKMi7HbI15HJuQC1L3BjWFP2O/w+ZzBUMQXjIUz0Ttnlp/MFi7UMjvc ymGdOKYW2KWlPQzc50KmMtpTLb4Xs63frUyd2DXSOdDb3ppvaUx0NWU66rNN 1anK8kg87HY7zUY9qVYqIBh0GBQgQ7cTb5aUJVFJSlRK/fp/DXmovRn9/jD5 Zm/mi8sH/vGbd65d21/KY/+vX7/2+kbCs3+1ueS1klIwUFw2yCK+TMADVUjE BxHOZ7M5ADIwscQEyWwoZEFgDUA4vpANHMjml260Ax4qFuOQTA+WL7qx9NlC IU8ilkkAUYmNkMyOIk4l6lKgJrmckMtBfyfBCiAxi8VmdfhM7jDhilLuiCUc CybjuWS4IuEvTwTiYZffbfG6LOGQJxEH6WJfPzl3faRyu0M+ZBB24+xmgpPF RWFMTvFZcYS1nNLd708eC2nX2pJDXdV11dnGfLA16+/IBdoroi2FeEMxXpGJ BIMeo9mAKpV8kDMCEYIopkO6boxFlf6nRyHYX2W/2epb9GiGLfC0HX20rfU3 t/f89du79+6sCEXc1zaDyCr7dcnm10s2l5aV8tksVCQkZBJKKlOKZQKBiANq OIst5HJgPk8h5CnEYqFQzOELS9mA0ARlXL5YwEPEEgz0F7lMj24sfY4QyCyE xGIKglwKOKBGI4QqiCkcSrkWluGwTIXIlRo1qad1NrfeE9aGE9ZsRbCyKldb rAINOB1MhJ0eEOkOk9/viMc9hXzwrXcuffbG/hEdr98q6zMIR0yyXWnrsebE 2d7M+mBhKmS8Vh3cahGfbAo8Wt9aVYjHwta8z9zgtTT6rQ0BW33YWZn0ZJMB j8dF6HUQioL8LAWvs0xS79BOulQ1JuGuqsDxase+ML7oJ7bHDAsZ5mhz9Lf3 jn777vo/f3d/eanz33/1a1DoXi/dvKm0pIRVIuGyMKmYVsgZFCGlYrFIwOHz WCyQ4Gw+QAUeV8AH0yko5QlLOMJSjgDMqFDAh6XQhq8giV4O62FoI6wARYjE ZlQRIdQpLZXSkgmSCGBqsxwipNCG9ZUqDaXHrDbcF7TU1oZ7uvM9vY29XW2t DeXpUMDNuBxGl5MBYRWL+a69eeLHF2+uFd1jHvVkiBizy4ftyFSA2JEwHK51 X+6I7ovgU3ZtPSHcV2E4t709GXL6rFSCIcst2oJdXwlQzaKNOw1hv83lspE6 SipHWAJxCYBMngjsmyYHuS1iHA8QPYx0xAZtcaEzAfxoU3C1OXx+qva3bx/9 /tH6d5+c9vvx//nv/1nCLt1ctrH/ESGPgqRGdOMdDT0sQkUCcGNzOByQYlyu mMcX8PhcYCquqGTjCIGvuHy+RCxB//syrEwMPClDMaFIoBZJLLA8pFElCDyG 43Ec96uVDATjYgkklQKeR0m9wmbTpdLB3uHcxPb6ufm+pYXW3s5EMuL3Aqo3 MIzW4dSdOb3vmycXVpr9u2O6y52JgxXWSZcShPmkXz0TVG8NqLZ70UmLpBVn D9rlg3Eb2As+j8lvxP61jJRxrTqlV6cNWNRMeaw6m1mn12vlqJLNFwGt2KCa QTCJKeutumGXatCvHvdpADyM2NHpAL6/xrNU6719oO/7l6d++fDCwwtb5RDv P17fDKwjEnA1ErD1xEZEYkZlOkiiAkMo2HgbhM/ZMJVUwJcIBHyBqIwrfp0n fI0rLOEK2Dw++JAKAc8LUTFfIRYqcAMEnCbe0MqvUoY06qBKHcWwgEplkf4r 7sB+lCtRrUnjCdhr6kMDk9mJbc1Lyx07l8vbmoKxqNvrtlj1RhrffWDLxw/X z49k95TTFzvil1pCu7PGKbd62CQbc4nHUvrBrHm0nBnOMRM+sj/rrGqoiidA f9I7N1Y27McVIUwRxtAYqYoaND6LFpCDUadVqDCeSLbxrqEEViqUajWuJzQx oyak0zhxxI3DMVrd5SG2JA3b8va9baGPri98enPvz89PHJlr4rJKuGweJOSR Er4eBlpJDXIIB/nM5wp4HOCljVCSiJQSCSICgSVm8UWv88Wb+KIyvogNvLYh qUDM58mEfLlQhJA0AiO4WGqUSu0KhVetChNEUqfzq1V6qQwRi8VSiUSp1oCi Hc14mjtiQ5OZ0S2Zkalkz5CvstKZiFvdXhJXzWzre/Xo5Lmt1XvrHee6Ypf7 UvNRHdBk0AI3G6GMxxROppLVdRXtHbU9PY3d3VWd7dHK8qDPYadxRiV3KGGA On4N6lcjQQ0SIhQBE+kyG2gtAbJdKleIIbkcUeIYRhEYRRJqpUopl2vkciOu 9ln0eYexO2iaTFmWGvxvLDa9ujz3+a3lX14e3zWYk/BLEAmPlAoouRiXixEp sBAYMBZgBj6HK+HzFRIhCTY+oCQJxJHISqRwmUTOFsNskYQn3JhVkVAgFQog oQimaAV4sQRinUTCyMFzVjpR1I2gdgQhJRI5kAo4Vqu3RSq8lc3+9u5o32iw e9Bd32arqLKXF2zprEpP9fQ3fPTsyo1dXYe7Iif7k1eHcweqLEtp8xCN1umF UY/Ll6uP1NQn65tzrR21/UO1fUMVrW3BXMpmNelVcq1MTEMiRiq0QmInAnkA 4qoRF6Gw6DQ6QqNRq5QqFQKepVJJgi1DqAlMoUYhtVxGonIL8BhjqA646v3W jrBxLGs52p94cWLqs2tz390/9P2DQwPVbpTDwaQCtUwEi3lCAJscsADLQFbx uTywEcH3KTlMyFFErpAoMbYaL1VqSuRoiQxmyyQcIdBKKAE5LxIpaZsSpwDB kBKRDUHdao1XrQ6qNQ4U1cogdIPfYYM3mGgZSPaMhLoHvM2d5nwR80cwX0gf Tigt1vr2yhfPzz1cnzw7Wjw/Xjw/lNtf6dhbYZsJ6Wp00qiVCoQToXxtor4x 29JR7O5rGBqtB1o1tYSSCRNtIBGIkkr0UpFRIjTJxDZYapdvAA8DkAZH9Tiq xdQkriEwDanW6HCcwtQaFFbCUjUsI1C5CVOFDVTBZa4LWKodVG+cWWrw3F7q fHFy8rNr8z88XPns+lJrwiJhlcAgkABmcVilLNbmspJS7gaay0V8NSQFdEQi qEKNSUgdx0iX6A2lBMlWY1wE5otFYiEfEgvlEjHu9lNWB05qjCjsUal8amUQ 14RxzKlQ0AiigiFMZ3BXVOXHZiq3LcQHx5h8Ue0JQVa70uaUmEz59uqXz668 d3Xh2tb6M33Zq6PFlZbgznJmR45ptqJhI+rzWIORaDBfDYSq7B2sGx5uGpto Hp0otraFknHQMUHhomRSo0zCIBsS2RAZ0IqRSy1KxEKobHrcZqAsepLRkhad zqgFtgKmglVymQqWkYCoMZVfh8eNZMZExnTqOo9hS4XtwnTtk5XhD85MfXvv 4I9Pjzy/vsWilb3+6/8EoAVUer2sZFNZSQkwF4cDiwQamUSLykngW51ObDXx 3E6ux813OLgmE5vCRCpQX2QKWKySQ0wq5wwmHYzZpyPiOiqpxZM6MkrhdlSu Q2BcrTK7/L5CXbJvsHLbjnj/sCGdR91+1OkUkdpgbeHFq9vv31t9sDJyfVv9 lbHKM53JY43+xSzT7yeKOnnWqIk7zBFwy1eVt3bXDQ63TU93b9vWuWW2aWgo WSzYHTYdpiA3ZlBqVcjsSsilQhwI5FChoKt6TNqwk4l67CGXxWuhnbTepMUJ lRw8bSAXrpDrVQpGo3KSKj+p9GOIQyWL65QjGfuRgeyDI4PPV0a+urHw7cOD vzxbPb27VSQq/c/XS15nlb5etvm10s2bWWX/3WI0UjCDUhJFEIMe9rqFsSg3 HuOFAhyXk21lBCajnCRRjRJVocHapmCiEHQ6klZjpdWUp7U5Wpc2am1qdKO6 anFTMGrPVrqamsL9fc6mVm0iq/L5xIyJiXgfvHv1g/tr756avrOn5eZc042Z 2lNd8SMN3i1RopFBq42aSgbPuCyJWCxZqCt29tQPDbTPTA7sXBhYXGgeHcvW 19k8Li2uBABjBFohYPokVpnIrka9tC5oN6UCrkIqUpmJ5uOBmM/msRjMlEar RjQIjCEwicK0WmHHVS5M6cZQjwZxaeRuhaTBbdjbnb653Pl8dfz90+Nf3975 w8OjPz85NjeS+4/Nr/+qpBQIBaxVwmGBFoMIga/EJCRWKyDEaET8AXEmLcxm +fEYNxjg+Nxcpx2MD2TUS7R4rKElkc1URFw1gJmdTBWjL2e0aVrrIjWECsFo vT4aN5dX6Is5R1sD01hH54uEPwRbTedunPzu5bXnZ7c+WR24s7Pl1lwTSKrV luBy3tTrVlUbVXUMVmUhs25bJp6qqG2q7R9smpjo3DozuHPnxL59nVu35Jqb LD6vBlMoZaKNy0ecUh0kclFqr1nnYQypoLsyE2uqLm+tr6gqj6UAstoMFj2m x5XAURtaKeUmXOmg1C5C6cZRL65wqWE7KglrkbmWyPkdDY9Xx16emfr8+tzv 3j74+/vHvn5zsaLc9P/+6t9fLy0BMF/GZoGCgwj5aokQA/tLJVcadLDPK0in hLmsMJPiJaLsaJgXCgqBXDa7wExnKvON+WhnzN7stTQ7zPUOQ9GiyxiogJ6y GnUkYyYDIX2+3NxU6+7p8Pb0+5q7dPHE7vWdv3z/4su31p+fnXl0rO/5yvBb S22n+1MH63zjEapIK3KkolKP5s1Exu3IJTJVTW3NI+NtM1t7tu8YXV4eXd7T MbM129puCYYUGhXYTSqltLWtfN++sdX1bfNbO2a2dbTURNprMy11hcaaTG0h kYt7w27GYdYatRqg1Ya1lHKdSs4QqJNSugjUhaF2FeRQyCxyQXeSObOt4fbB vpfnZr+8sfO7tw/++Gj954eHHp7swzDxr17bzOVsXG6QALgSCZRigUoiRlFQ YwiJ2yFMJ8XlGV4qzk0muPEoLxzmBfxct5PntKVCrraIpdtPd/lN7V66xW1o dOmLjDZK69w2k87GUMGQs7klOTNVtbhYPb+cGZvecnTvdz999M3LNz5+Y8+L k2PPj488Wxm6Plt7si+5p9peZwccC8dUUAKDY0Ys6XJmE+l8fVPz0Fj37OzQ wsLIzp19c4sNo1Px+hYmEFGSeCLtmpionp+sPLZvYH4sv2e++fLlxen+5Mxw Yai3sq0xX1+IV6aDqX9dqLHSlB7/17UaBNLIpVqFzKSGzQqIUcI2FWJXQGap LG7Q7B3OXdnV8mh19PPri98/PPTDOys/P135+fGBbf0ZNrsU0Dgk4iL/AnJE zAO1GoZhMGV8G8OLRoBQPKBSLMaJhNhBP9vvYfk9fKejwmFu9xmHfKapqH0q 4RiLWYejTLNHnzBqHWaD1mq2ZnLpsfG6/Qf6Tp7qOX5h8uThL759/vtvnn70 5r5nayPvHxt690jf3eXW89P5td7QVMoMMscsE/s2OBz16rCg1RqJxTMNzfV9 g92z20d3LQ4uzrXObMkMjHjrG1zpWDzhmRyqPDhX31XjrM86GnLW4f7s8lzd se0N4+2Ruenqqb5iQ3mwOhPOxtxRv9VjNZi1mEYJw5AIgUQqQJioRKeQGRWw EYHojQ4rxiFBX6Xz7I6a2/t6Xp7Z+vWtPd89Wfnp5cmf3l395Pq2uJ+UiHlq sNqkQqVUgIh4cpFACkuFmIprMrA9blY4yAmHWEEPK+Dj+L1sn4cDjsNWYKgu j2E6aFtK+nbnAstp/2LS0+enkwbSTJE6i8ldKOYmZ1oPr4xfujJ14cKjV49/ +eH9z+4f/uDM2KsTY08P9LyxvfrsZPbMdPZgdzhhUJICrhkS2wGK46hDh7nM Fn80Cii0tnegc3y0f8dM9/at1WOjgeYmf21qbKZ6qiNWk7dUxc1JD+W3qpwG uc2I1Bcdw/XemVrnYKW7NWPJ+rRVSV91JpCNusIuxmIgMEAMkIAn5UpkQlQm 1sAyHJQXMJiwDJUKQXPJuOljI/nri60Pjw5+cm3h+6erP786+/N7p354uGd1 usJAwQQqJRCpQiyQCwCR8sWQhKdEWVqSwzBsh7PU5SxzO1leZ5nXxfa4OB43 x+WotWv7vPTWsG13yrc/6z9UHtqb9U8ELRlaSyFy3EA5yvOZienWw2uD6xdW 7978/rtXn7199MMz45+cnXrv2NBbC43XZgqXZysvbS9sqffr5BJSLDDJJTYN DEpK0GEOuryhRDJWXVnX1dU9Mtg7PdY8NphtbgxWJLsma/ZsL0w1WFurXdVZ RqsQttaFCwkm7iQiFixrQqfy5pognbKqKkNGlxapTniLyUDc77CbAZOiYljE lnJ5Er5YIpRJRbBMLJdLEbkMPC4TcQk1tLXevzaWf3Ox+cX5ma/u7v3DyzM/ Pj/xw+P9H50drM7QGlhAQGJEwJUJQHcGrU/EgqEyjZql17NM5lKGKbFbWE5b qcNa6rSxXXaOw97tNU5GbIsJ54Gc93DedzDr3p12jgSYrJGiYEhNYZZUMtY/ VLN9cezYysffPPvy0ZHnx4ffPz787HDP3fn6m9tqbi/U35irvbClUB+zGxBU B4lBS7VhirjLlggFs+nyqua22oH+5qHB7rGh3rGBus6m+vaq+YX2YysDN0+M 7RlM7xjJXVobbMk7m/LO1eWuHf2ZkUr/QNHNoHwXKbcpBY1xY8qiCpv1NZlo JuBy2I0EjUsphKOWcpRSLirhySVCRAqOSAGBuWKpxRxcXJ2xLHeFz89UPTjU 99H5rd89PPLLi9PfP13/6Z3Dlxbq9SoBKmDLhVywWfg8LkcsKIVlJQp0M64p 0ZEleqqU1rMYms2Yy6xMqZVhMeYBn3k+5T2QDxwp+I8VfIdzrr0Z96CXrjTr LBqVVqe1xkKRppZ8/9jNx2989/G1986MPz82+ORg19352lvbKm9sqby5o+bG bPXx3mQuHfTY7IxGSUFSk1oZsFrCnkAylavp7O6a2T69e9/2owdm9i50Tw5s mes4uFC9tSe8ZzQzVGlvztKLw8n50dREdzTKoFGzLEZL6+M6RsEJg2VqlA8k DM1BvUcLN1bFMnGfy2vRO/SonRLaCaGF4BpVPIOSr0UFFCo2qMUWTOIk+D6d LWna3uDY3xE6N55/Z2/nx5e3/fR05ccXp394/9QPD5ZaKkxc1iapkC3gsTig SIsEJZB0MyLfrFaWUlgphZfoiFJaV0Yby0wmltlUZtR3uegdUe++8sBqTWy9 OrJWGd6f8Yz66HqL3g8G0Gr3xFOOfGHm0PIXH9x8dGzs3UPdj/d33J2rub2t 8s0thTdm8lenyq+MZ+a6ywsdzW6vW6tWqqUi0NwtWgpIF02kKptaWocnth44 cvjapbU3rx6+dGJuqm682TXXG9o5nMg7NS6NcKDa1Zymh1u8GYcqadcsjeZG 6n2NcVOQ4Mc0vHq7pj5MMypOyoUXMkF/xMOE7UTMBifBcYjCtNCvF3l1Up8R iViVWY+6OqhujGnqwq2Vtp01tv3t/isT5Q/3d766tPX752s/fnDyl1fHr+xt V8nK+NwyIe9fb1QI+Ztl4s0ovFmFluKqMhIHcpXqSSBRGW0o1Ws3E1iVUdvv MO0IevZkggdywYMp/+6wc8ija7Dq44wxHAj5slXJnvbn799+dnHh9vaqt3ZU 3pqtuDlTcWMqf2M6f30yd3UidXooObV7rnZ2xur3KpSwUsrXozAI9rDTnA76 aooVrQN9E/uOHbp6/frz907dvTbaG1sYDC8MRMYbnRkrgvN/nXPovLgs40CK HqzSgU1WuadqvK0RKm0UFmyKtBnx62QGmMegnNq0L5GNuDJefcGrqAugzRGo zi+tdMmrPEi1H29NmwZrLOONzFSzYarR0xYfLZj3tXrODiXv7Wx4utr/xc2F Pzxf//39gz/fXGpLm0pZpUIRlyfgckW8UkhcogBaISWYkoVjpQRWqiVK9bpS o65ES2zGFEEFmiGQegPZaTUM2ulhl3nIbe526BrsxnKXMxmPRmoq7z5849Pb x+7uar4zW3VnW9Ub46k3xtLXRtK3pireGM9dHYwcnWndc+16y8xWu9+tUcG0 Co4YsEqPqS1sb/Uz9XFnW1PF2I5thy5fffP9j+5/9tGeI1PjHf6RBmd7Wld0 KMww36GW+gjIJmfHKEkezJoZbbYresJUiw+LqvlFuypqVGC8UjcOFQKWVDbo Lw8wNUGqPaHqSam6k2hXDO2KY71Z42itbbbTt2fYtXvAPN+mm6iMFF07qpzn gFaL9U8Od75Y7fvm4tRP95b/z/1966MZLg9otfGHSgKJsAwWl6BQiRotwZVl hIZF4WXAWlqqVEuySJyFK21SqR2SOOWSgALK46paI9FkM3Y4TE0eWz4aCCcz K2v7v3569u0jvfeWGu5sKd7bXnVtOHGuI3B1MHFzLPfmcOZcm3vlwNzS9Tdr BobdAaeBREM01Ra1bamOzDenpiv9XRGmKsS0NObmVg5fef7y5e9/unDvzYgV yvvRnnJzT9JcblNaIJ4N4dtk7AQFFXVIvxefimnHQ8RIkKqxadxqHoNwSSGL hrhRM5HPh315v6nKT7XFVb0pVX9G2ZfSDJWToxX0dINjod+/f8K9Z9A630aN V2qbYvU509E2963txacHO57sb31vqf7j5fYfDw/dmi6SqFgs4kvFArFUzJFL 2Up5qQYpJZQsUs3R4hwdCSiCRRECLQFRuEkqMUkktERilog9cjiGKQtmbaPb Uhf2RJPhmtbmDy7senq07+397Q931d+fr747W7g9XXF9IHFtIHF7NHelJ3K8 L3r2zpW9N242jo6FIj4LhaRt+uEK30JrcmdHBtwP5dxZCxWwa5sn+g++eePJ d9+dvXs9aYUHqp07uuIDWbotqIxTgoCGl6TEjTTS6VCOhDQHKs0HKpnhENES pZJmuYcQ6mUcUlwWMKorciFv2k0XPGRTEOtOqPrSyv6UaiCDjeR1kzXMbJN9 oc8612Xd2mAZrzJ3JsI5enul5fxw8sHOuqfLzXensufzpneqPDdHyq0Ay4RA JKFMJhLBYoES5uFqkZaE9FqYNkgMeoFex9eRcpNByxj0UpFJJrFAErtc5kbh EKYsN+saAvb6TCRXkc8U8/vaY/f3tF2bKb85nbk3W7wznX+8o+69xZanu1qe 7u14tK/56tHpi8/eO/LG9Y6ZKW/IS2OytIXsTtpH8t6JQnC6JtCdsGZpwopD uZryHSfX73z+6dUHd4te1XC5ebLSMRClunx4p0c9EqGmkrqlgnUupVtIUqda PWv19gGfpj9hrnPjjIRtkXJMMrZZJY2HncGI05F1a2sDmpaosjsBtAJHDeQa ypEjRWq0mhmv9E1UA/JwFL2V1b6Jgu1Ag/PeXOXbWyuu9gTO1VpPx8nTPXFa IVaIOKhMAEsFsEwgUUgRUqU36Ux2k8Vl0VpNcoNeTusou8XjsRthKQ2JrIjU iUBOFPZplGmTti7oqC9P5isKgfJ8TWXy1EgC7LtLfcGbo8nHO2pe7mr55vjY 796Y/+Gt5R8f7v/qzvLVa2sgt3tmJoN+p14uiunUNS661mVo9Bg6I0yzj87R uIOE05no9Mqh6++/uP/p+x1FR4dPM+DHx1zqAY9mJKhZyJBrbf7THUHg2JON 9ivdgat9sdEQkcP5eUpEcsrGA9p2BiUgocdmcDpMlrBZV3BjjQFlZ1TRFVX2 xNDeGNod1fQlTYNp70guPpQLNAS7xhv2LrRN1dl31jBXegOX2zwnq80XGh0X 6qxHW4I0LMIlPI2Yr5DwYSkfQaR6Sh1wM6moJxf3efx23EJrzEaDjYl4nW4D adHILZAQpJYVktgUUNBIFIP21opYc00+UygGUrnhGvfp7uDNseyL5eaPj/V8 dnzou8uzPz7Y/5dna39+vv6Xl2s/P12/d+P86OR0wGIywyKPWp7Q41kaz9Oq ClpZbSHzNOFVQ+WpyNSBvWfu3X36zWcjfVU9AfWOpHE+iM+HNdvj2HaP9Hi5 4UQdc7HFcbXFeaPTc2+2MF9Oh5ESg/C1qIL/sD0y6SOVUp6RVNNGXO/W0nE7 UeVRtAXRjjDSHlR1hojeON2fCg6lyoczqabg2GLHpWs7j+9uPDQQWiga9yc0 xxKaUxWGM7WW0/XMTM5kg0VWWGKSighQoqVcFSw2azUJn702HarLhYJhN1CJ MFCUkfIwhupcIuaxOBWwWSwCnZeBxX6tujJo7ypEOmvSmXTGE0llc6mlInOi zf32jupXh7u+XB/6/tLWn9458ucPz/39o4t//eD831+d+69XFz9/+3RPbUYj KHFq5H5MHlDLwxooScJFoyZvwGI4UluenNy5uPbGGw+/+PTI6b1DWXo6gm9x IfNexa4QttujOORVHk+QpwvGq62uxxPph1tyV7sDnU4lyd804tUc9cOTDiWG CNWgLyslRjNOBxldhUdd71E0+4nWgL03HhiIpQdTNYPZqobgtt1DL15curHS f26u5mCnb66o3wO0imMnc7pz1ZZTdUyzAw9p0BAh9yql9Ia7uGpQ0DA06jQW o+7KuCfgc2lpvYJQKzQKvRqdXZhu7aoDwOLCUFrKN8kE4KUrBmw9xVRHVTqf CydzuXxTT39VbGeWWG9x3ZrIvdjX+sWJ4e8uzf1h4/Ls8T8/P/W3987+/fmZ f3x44U+vzi50ZGlBmVUudKMyLypOkEgljRf0mpRO0VSZmdq5sHLlytUnj28+ f3Rka/tizrTVjW53wkse5bJbddCjPJfSvdHpfziRe2cq92Ai92SmfEvCYJFx l4vOc0XbznJLjCF766IeF0Vo5CYfTec9xiovUx8MdiSyQ9naoWx7f7a+OTQ2 WvP1lw+e3dxzcb5mfSC+XGeZS2PLMfWRiHo1ga9ndVuTdLVFV8VoK2msQqfw oWKdmK8W8QhI5DRq4l5zzMeAFqKgcL5KzpeJxGLe6XtX9509Mr2lryHrDxnU djXkJZU5t7k9F+6qirc3ZrsHuoeWliYXd+2o9+/KUavtzhtjqQc7ql/ubf/m 1Oh3Nxd+fnT0z09O/O3Zmb89O/33907989Mrl3Z0OSGOHeKHMTinV1UYsZxO lTCrG+srppeW1i5fvnDvztUnD/Zs75qIYksxfJ9fucur2hdQHo1oT2atF+vt bw3Enk0X7w7F3h6JHa+i54um272RZ23RLr/egwn6c7awATPgCovL4Mu5443h 8u5U7UCucyDf11/e25Fsawg+vb/20ePVmwe7zgwnDtZZ95RTexKqA1HFoRC6 ElMfSOCtPrLRpW/1GJttVIMZS2GwFRaoRWxUxDJgsMtC2u0UTmuBUCWQsASQ Kp9z//OXbz6/v3b6wJbRtsaUL2IlgzSWsuubEt6+qvjEYP3cru2HL144cfv6 keMHZ+pcu4va403O893+W5O5pwt1nxzp+ubqth/u7v/l0dpfn53+63tn//Ly 9D8/vfz+5T1VTson4xVoosJMJChFIWjp7Gndsrxn5dLFi2+9efHh3QvnT/T5 lG0G8bAROuTG9zvQNow/REn22GS77NKViOZ8QX+/O3BvIHp3tvxKLTNlkVNC TtaurHFgAQ1io5Rer7mqJtrWne3qz/cNFcZ7K8bb080F5/6d3Z+8vPDGwZbT Q6Gjzc7lgm5vBt+bAlohB32y1YhqNqQtWDUNTm2TS9fooOpoTY6Qu1GRRgLa dBmlkNp0aruZIHQYSLFNIu5mPmczu+z5bz96+PG71++cPbR/y2RHVVMGkIsx ZiWrA9aBYmx+snv91OrVh/ff/uDdN589Pn764EyteamcXKmznmz3XOmPvD1Z /vGBri9Ojn9/fdcf31kFRf5Pz07+8dbefzw+8of7R+br4nFCGsVkGaehrSU/ uW1q/siRtSsXzt26eu72tVuP783XR8LcXwdkJdvtyq06YVywKS7k1CrYA6T4 YEj1ZpPtYXfw7mD0wlDoZn94OK6lIX5nwNTgIL0k5NYr8hF7b3NupLtivLcw 1Z2fas92lrvrUpanbx+9c2r89EB4pdl+oNayq5w6kNLsj6CHwsiRoPxwTNPs JCpossZCFA3Kok5ZSSkqCIUPkWhELDmvjJSL7VqNx6KzmvSwGtksZG/islhi 4cvffvLk0/fuPLpy7uKBA3smJ0aaa/OhuI3M2XWdSc/8ePP5i6tvv3zy3lcf P/3sgzsv3jl2enGq0rac0a7U2850eC93BW8PpZ7M1nx6aOA3l7b/5vLcN6e2 fH9m4rsTvb+cG/v7w4PPr+5eHqzqasgMjfXP79+7/9SJU9cunbl+8dy1C1fv 3Tox2ztg5DUb+QtBbCVMjFCCLjV3SC/d7ycvZHV3O5wPB6O3h2MXRiK3xpKn BiLtXt1wyJLRwi5cHDSqCkFrf21qsi013Zocr43UhwxteffpldnHby6eHY+v NjkP1pr3VugOZsjDCeWxCLIeQg9HkbmkIaSSxHE4RSJxDZTQwGkcTqplDkig ErEk3FK1VGAHZdZuCrktJhMlVUg5sFjJ0B98++nzz1/ce/fW9TunL15b239k tr+3Ou0xxk2apqBlrCOzur5w59Hdl199/OFvP3384dNL96/v3Dc1UWHakyVX 65lTTY6zza7L7d57Q5ln840v5xs+XKz7dHf9V3uaf3ek4/vjXf/70YF/fv/o j1+/8/lHj95/+fDh/TcunDx8eM+OU8d2Xbl09PKpnTtj5IRNdiCue9gRPZkx HvTI1+LE2Qh2Jat9s9V+s9d/ayR+fiB8ZTD+9rbahYK3zaHN6FEvBQOt8j5z W3lwsDrQk7E2hozHlga+++bBly8vnZqtPtLiOFxlOlTQHcmRx9P4agxdCcuP +KD1HNnhIwxibkAlCaqlIZUsrJLF1LIAKjWKBQo+W8JnISKuhVJHXEwy6PL7 bIzbTDrM7vLsR99+9v7XHz395Omjl/cePrtz+cbJ+bnhYsIVMaqr3XRvMbB3 cfj67Svvfvrq499++urLD24/evPYhaNbpnqHy+m9Oe16tQUQ0ck65kKz+2Zf 7MFY5t2Z8udbyt+fLXyyo/jb3TXfrbb/6dbW/3p/9e+fXPzHp+f+64vrf/7i 1sf3168dHD++ve3kwtDR5sg2J7wa0T3pjb87Vn4yoNxv4l2KERfS5KU65lK7 +42B6Nku3+WB2IPZ6hvTlV0+orDxRzJqr14RtZJVQSbn0LQkmOe31v/41Ztf PNh3a6V/tTN8tMp8rGhcKepXC9rVLLaaUB7yQ6t+5HBBb1FyKRHbp4R8KllA BQXVUFgp88ilBCiGPLaEx4b5XL0KSfhdlblkJpeI5uL+fKqiu/OzH776+NvP X/3m4w+++uA9MIyPbx06tqujLhM1YxVOfWvcvjjecu3a2UcfPnv1zccfffnq ycsHp64dn1meHZntn6lx7w5rDgOArLWcqnWca3ReaXPd7gu83R96OBB50hd6 ORD5ejH/x7O9P90Z+/Gd+T892vuHe0t/err/b6/W/vbhuc+v7zo9XL2jPjQf wVYCmmdt/jv1rgMuxbyev+KSnIgo1zLYmTrmXKt7vc12uS98eyz33t7282O5 aiPiVcFWjdxBKqwquCZue/X20T+8WH95fuj9O/MnpjMrNZbVCt1qUbtWoFbz +GpWvZ5WHQ3BF7LkaAKXiUpJMcsECVxAKyAUBodVkEUmQMVckZAtAlqJ+Bgi 8zjMhWK6prEq11gTrq0o7279+LuvP/3+y4+//ezVNx+9/PKDx68en7l8fGKw Ne3S50DbjdhmB2sunF959P6jD7766MMv3n/26smVO1dWL51Yu3n16sPbh7qT uyPISg29Xk2fqjKerTVdbLJcamCuN9rutrofdQc+nAh9u1z5+zMdP9+Z/eur 03//8MRfnhz66dbSD+cG/3J19HfrA4dawqN+1YIPOhxWbg8gIwF1FwNNGfhr QeQUaD3gVBnX21wXO/1vTZS/u7v1+2vb39rbXu0kjVIRxOV4ac1nj1d/erjz ydb4e2v9D1eHDrVYjtUY1iq1q5XkWpFYz2OnsprjacWpGLpWoUuEaB2u0KES g1xgR0V+pTiIyXxqyCDjw/wykYAFiQVqVKbDFDarIZ6OFOqL5S1VsbqKcE3+ 0ccfALk++e7Lj3772Qdff/z885c33r4+NztSjDiyVqohaJ3sKZw+te/Bg+sv 3n/84Wcvn3/0/Pa7D24+e+fuqxfv//jjpz99tTZVvRRFjlXqj+eo9QrqdA19 stp4ptp4vsZ8vcXxzoDnw+nYV0sVv1lr/ene8p/fP/GPjy7+14tTf7ow+vlM 8qOJxBfLdTtbYh12eTslysFlBWnpiB6ds0q3mf5/pt77q6m1axf+C843znnO efezH7dbSnrvvfdKQkJC7733Lh0EQUAEBMWCYgFEAQXpIioiIEWlSu8gTVCx 7eK34n7PN76MOTLWyA8rWVfmvK5r3smaN6rKkVPpzK4OkNdEWDXHGp7n+Ezd TF5pzf04fOHP5c6ikpjw/JDJhvztmvg3BS4vMvRPcz1rw9S1weJ7IeK7wcK6 QEFtAKfej/3Ag/nQk97mzS0Kt/UIdXfxsrWzVzsY5I4qgSOP4sQxFePPP0Yi SXgki0GUCNlquchosHJ1d3Dzc3cN8jR6OakcrB88636zsji3sza7tTSzMT++ 8vbp8LOLgNa56VwUrEAb2ZnkgPq7l5911Pd314wOPpmenR6eneifnxrbWFt4 v7/17Y+dzx8eXkq56Ea548WtCxA2hErvBYkbg4HClDWGA2kmf5GkH8t2nDjn uXg/6/3zix9Grx8OXD9qLd65Ev4602HxjMfi3ZSUGNdMIydfSSlXUW/bcm+5 8ssNrHJ79jVvSaWXuDpE3Rpn+yTT801V4kpL3v7jM89qT6bkBPSUBc8VuL/J dBhKtWmLV932F1cBeRgguhckuhskqA8W1AfyHvpxmjwYrR70+nCrUzlRyaci ozLDozIio06GRIV5xngZ/HRiI5ugouEENCKHgRVwqGqF0KBT2Bk1jm529m52 ti62Kr1KYiUtuXH1+eTr6a3Vt1vLbzcWxlZmHr/sKSs77etoZSumeap4eSf9 m5qqnnQ1djWVPe24OTE1+mZxenBxburd1srRx7WjD+ufj7b//PbkQdkVL/pN b05tkKg2QHA3CPjA4nqgNoPFdwOF7TGqp2mGV9eiN1tyD9rydxtPbV2NWqkI HzvtMZXjWhClCylNqblTmKsklutYV21Zt71kVb6Ki67CUjvWRWf+3TBda7z9 8zOBo1fjPg9eGKpJ8fDVlyU6jMVpR1IdX51y7T2pA7Ko0oN9w4tX68u/FyBs DBE9CBE0B/M6A3iPvNlNfrzSCPf8rJhz5zLySrMyLuRklWdnn005nR2fmuDv 56SylTAB/6mWszUKvtFa5uqoc3bU2Tnqbex1amulRCkVKSRBSbHNzx+PrS6+ 3Vqd2lx8tTTV8rSloCDZWSu24dM9FNysePeHXbWDo73PH93svnd2oO/hq9mx oeXZsXdrM/s7C4f7c+935g/2d/7449Vg+404zQ1fZn2Eoi5EXO3Hu+XLrwkV 3wwS1seoOhJ1PYU+09Upc5Wxs+dDJrNchxNtR04az/pK+A6y+It5cx9Xi/x1 ZWrqTXt+hT27xJ6db03L01ArPWT3wvQtiY7P8gLnqlLa87193UV+Ia5FHrzZ dLvhVNv+FGNntOpeqOS6J+emJ6fGm13jxWoI4j8I4TcHsrsCOI/92KUe0ii9 Mj/M/ezp2ILzOWdvnD9fc+nC7UvlV4uLSjJzTsclxAe4uehdXazdnXXujlo3 J72jo85gp9XoNVKVXCCXsCVCnZP9tab6FzMTkxvLU2vz/ZMjdU13kuMDjFK2 jZDpoeBlxXi2tle/nhx91d852FDU31E19Ob5y/k3/Qszo2vLE++2pnfeze5u zu29W/v6BRDTxgL/W0GMhnDhvVDxjQB+hTerwpd/I1x+N0Z996RxsCJiJN9/ JMuzN1bfH2t9N1ipdJTanAx8PNn7anPSNsT1tKv4nJGbqyBnirHpImyxkX/L 17o+0rYhxuFWiM1Ja0akr9Wj+8UiOSXLiTWT4TB40vAkwfo+QOahomtu7CpX 9jUnChC13qz7QdyOYH6PP6s9WhptzfMTMhOc1Rmxntn5ibmX8s7XVFy9f6uq 8ebl2xfKq0pLK88lZ8eHRfsEBjp7eRrd3W0dnW30ttZWNjqZRsOVycg8Hl8k zqko6xgZGFmaGZ6b6Bp8dulGRbC3UQv0RwKGu1KQGenZ2Hht4FX30IvbA7fS X90vHHxU2/vqRe/s1MDC7NDS4uvVlTfry2Pry69XFqbWlt7MDjVdi7sTK7kX JaoOEVZ48YpdGBU+gqpwxY1obWeBz8tcv5cZHo9P2j7PdHAz8nmehvzaK4sH CzUvGiUxnlEuskJHaaycEsZDpitpZ/W8yy7yUntRjpZjZMByU1z/3B989qCI yEbH6xmTaQ798frHCZr6EGGVN+eSIwuISgfKTRf6HR9aczCrO0jwPFx4O1jm RMO4s4mhWnG0n0NSeljmudScslNFN89VNt+oar5Vea/q2r3rJZUlmflJUTE+ vn6Ont4OTq4Gvb3eysYg1VizZUoCh89ksqNPpVc/ausZH3kyNlTf3ZZfeMrN RqrhUoC8crcSZkZ637lR3nb/6qM72W1F4e25gffPxj64V9Ux9KJvdvrF7Nu+ ubdPp8bbhgfahl60P2ntab3V03SluSyiNtP+Xoz6eqgw34tR6s6+4Ce6HKFq zHQeLAjsS3MfyHIvDbYmCumu0f4dAz0TG+PFbbcE/gZbIT1NJwjm4wI56GgR MVVBO2VFz9dxXDiEADftcE/lVteFnrrTDCHZWoh/kagbjNd3xqpq/XiVLrwi PaXQmlQJNDIuzDuezNZg9uNgXne8NlxBNeBh7mxSsEYS6eMYFeuXdDo2veBk 2tnU3Iunr9y9crW+CoCrovZKceXZk8nBQUGuvv4ujq42WqNWbWOQWemZEiWG xRNRGCFhIWXV1+739zQPPLl6pyo5NsJWylOzqUBeuar4pyJ9bpRl113OuJ7u cyHUcNpBkG7kl6SF17XWPZl43TM93v56uPZJ1/m6m0UXSy+WZNedS6gvCqsr CL2e4XMxWn81Rl4SxCn0YBe48sr8ZdfibJ6cCXia5fMs29NZy2WpxXnlhc+n Bl7MvkypPs92VQPtcI6fPkpBj1KxouW0VDWrRMuLVDDofGpzXXFbVf7b8uSJ 9gqFlk+lwO4HyHsTrZtC5Ldd2WUOjGwV7rSKeM2FVe3KvufF6ghlvYiXnbLl S+EQayLGgUny00iDfezDY3xikoJPZkamnD6ZfDruVEFKSVVpWU1F2Y0LBRfy UrNjwyK9/QNc7Z31Kq1SZaOXWRuZMjWGyVPQGIG+3gUVpTc7mm+2PjhXXhTq 56nhsVRMmjWX5qYRZEa4n0sKungqoDLFM89DGSyjujExSW7aGzWXOkcGO8ZG ax4/OnvrenjaSQ9Pp3Bvw9lI52uZXhVJzmeCrbKCrcvzYytzAvNdWLmOnEIX YX6Q/EGO57MzgRXxHgQe3t7PvaG98fF4X//ccHJVKc1ZGRfkciXZpzDImOos y9CJLhqE+ToG0MxGJfhMjTTUX8nfaLiw9KLG00uNJkCLXMRPEgAFlF2wpebq iLlaQqGedMWZftuZ2eDB7I0VXA2UcPBILgoixSN0dJKTjOvprAkOcw8N94yI 8U1IDU3OCE9NDUnLijxdkpVbkptVmA6wVlRCUEAwQFjWCpVEqdVIrA0suZrI EegFgtDggLyykoq7d0pv3DiZnuxiq1MDHoPDsBGyvGzkSf6Op0Jc0v31eX7W uR7aMAXHg0GIdVbfqr7UOTz4oL+/pLo6IDlBZrTmcjm2CkGEk1V6gF12gC7J S5OV6H+tprKj7+mN0qQcB3auk+CkI6MyTvvsbKCfgwjNZ2SXFT5709vysnt0 eaKw9hrNQxsRaF+d6VeR5H4mWFfiJDvvIJWw4Aq99MWzuvWZDjmfV5UW/H6y Mf2kF4IEC1TR26KtKr0EAFBpMnSRLbXMkXXRgXHTi9uVoH2QbKPj45h4FAsD 5wHtMI1gJ+N5OmmCg1yjY7zi47zSk4KzM8KT4/0iQlwiY/zjUqMTM+Pi02Nj k8KDw7ztHLQqpUimUvLUVmyZNUMo9bTRxybEFly4UHjlSmJ2rru3n0zMl7JJ Wh7bIOR5WClSw3wzIr3CHTUhSlaCThijFflwifGu2jt3KjsH+m61tcTn5aiN RiqdSSZRODS6RiJ2t1YH2ChjvBwLi3Mbutv6ZyaejfWVxtvn2LOj1IRcD9GD bG+xgCJzsK7vuf98cmDg7ejbdwt3+zoE4c5yd2lRrMP1dN/zMS4ZLnKNgEwT UG7cLnk3/3RjsvVF66WRrsurQ7VV5UkkNlbBI9wKlJ+1p6WrsTlK7EVX1iV3 DsDkTwq839QmZIUB9lykEzEERDQHg1DQSY5qUaC7TUyQa1pcYEFm6PnsqKLU 8OQwD39XnaPRysnFztPfwyfYxy/Ex9ff3Q5wVmqJTCHjK9UMqRVLLAv29Us7 nZ15tjAuM9fZJ1go0dAoLAGNYsWm2wh4DnJxQkzw2cLczOSYIFthsJSeoBHH qjkZAcbbty7UPmw4ffG8jZc7iUYn4MhoNAaJQZPIZD6XqVeL4uKCr9yp7Bjo HZmdfDE7WX0997QLL82Wk2Rgnw6yJ7EYURmxL8aeDc2Nzu+vze2uvFqe9D4d z/fQOumFYT4Aq7JFSgHPWlBcfmp18fnS66aNyZbNieb5gZrZF7d67p+TqBk0 BuIs4DEcWbkaQoUjsy7aqj7d7smF4Kn6jMGGvMwYj5PBLl56qZJF4hNQchre RcEPtlMneNmmh7sWpftezIk8ezI42sPooOSJGKY7JRUqGWCobOz0tg56nU6p UAilMolQrGALTYOGguPi0/KLotPz7D0jeHIjisBEY6k0IlPMZMm5PCuRNCYm pvLmrTv19SX5qeEGUZSSk+GsKklyvXn17Pmys8HhYWyBAIZAodFYFAYLR6MQ GAyLz/Lw8ci/UFb3tPPFzPjQ7OTD/icXrhcVhFvnuIhjVERHFZuplF2vrxyZ 6h9dfLNwsD61tbB+tHOlo44opmBoCAKHwFZw7Dxtbt69tPd+enGydW26fWO6 bXG0cW6w5m3f7fEnFd5+GjQeEaWhlrlwr7gLmqP1/SVBL2tOjjXnLD0619+Y X54dWZQQFOlqrRUxeHiknIZzknMinDUp/vaZ4fZ5ca65Me4nfQ2eWoGUgqIg wGQUnE3EyzlMOZ8tF7AkAoaAx+TzeRyugMkVcYUiz4Cw8JQz7sFpXIUzkiSB YJgwLB2Fo5MITBqZyeeIAiOjr9bcaX3+/G7TnYxYrwArZrKb4nKmX/X59OyU aKNKSSSSESiMKanQGDgKgyOR5TrrqPTkC3frWl8O9k9NPhrsv3i3KiI+NDPQ Js9FGKNhCfg0mwCXwfEnE3PDY2tTb3cWJzZnJjdn+2aeByX6OHtowmM9Sy/m DL1s+7j/dnt9ZGvpxe5K/+ZM99Kbpvmhupnnt+b7bp7Jj8AzMH5qZpkH706o or/Ad/JOymzXufknF5afXRp6cLauOOlGTkSSn41GyOBgEVIy1kXOiXHRZAU6 FYS75ITYx7haeWlEOg5ZQkCK8UgrEs6GSjTQiTZ0kppK4BJ/ToohkahUOonK tLJS6excbDxOCqwC0FRrEEZgiWJCkHQIhorAMtB4Dp2j8ok4eel2fefA05ae joL8U4FGWbKL/PaZiPrSxDOxXjo+B4vGobFYACs4EgVHY3gSiW90VNGtG43P nvaMvu7sH7pZ35iUmSwWsTysWBcDNVEGMZ3PyDyXubAxNjE/Mr4+Nbk+/Xp5 bHC899lAQ1/f3fFXzasbL3e2x7c3X2+tDu2tv/qwPfV+/dXWfN/yVMfCWPP8 aMP8y7rHPdVCO7FRw7rkLWpOtxu6Ej718PTso/NLvVfWBq69vJdblRN6MdU3 ylUpZRCZKJiUgvNQ8eMd1dnetmf8bZOdFT5qjg2XYkXD6hlEDy45TEKLUbCj FGw/Ps1Ax/PwpluWTNWCRhEIaMBscIRGmtQDQTNACRoITmSJYoEQdDCcCkMx EVgelacNjD116c6D1hdPHnS3lZYVRXvYJzmrb+dGtl/Ovpoe5KLkkXE4AoGA x+MxGAyOTNQ5OKQVnK3p6Ho08qrr5cs7ra3niosCXGzJKJi9glMRbdTIqAKN pKGzbnL+5djc0OvVsfGV8fHl11MLQ/2D7fOro6vvRnY/zC+sv1peHj7ce7v1 bnJ7e+pg/+3h++n3m0MrM50bS/2zb5o3t14FpAbI9ezLUbres97jVTEL7WcX H1csPqnY7L/afTUxL1SX6mPlKmdw8Cg2Gi6jEjytBGkumtIg53NBDkl2ImcB SUlEa2lYDyErTsHPMkjzbJXZRnmCSujGo4gJQIkDDyQSBuWyKWdPRyEoCgRN ByXbQEg6S6wIjOaCkQBcNBCSCRwzxDZhSdlX6hsf9j2613H/fFlhrL97uEF2 Ps6r9XJ6Q0lCoqeOQwESlUin0QBWpzHp9q4up86W1rV1PXzSe+fhg/Kr5WnR ge5StpKA9lJxCmKMFAHeK8Tjxavu19PPN/cXl3fmh5dHrzXfKrqS1/z4TnCy v9pZbeerD84IKLqS0/W8UeQsVrmpuoc66lqq2p892P+8fvBxc36q+9PB2xtN lSwd60yszejFkJna5IX2goXu84s95et9l65muAXr+D4asZpBYGDgTDRcTME5 SriJtopiH7tcL5tIndCeS1WRMA4sYqhKmG5UZtsq8+yAUKRqxcFihoqEJyKR UBgUh0UD7XptbQWYaAOnGOEUWwjJxgwjsUQLICgOCMguNAeCFYg0rgnZhdcb 7t/vaa1urjtXfCbKz9VbLUhx09bkR7ZfSa9I83Ow4tMoBBqNSqPRmGyO3sE+ JTv71t2Gmqb7Fy+X5qVFxjgp/aQcdyEzVCsM9NLhRZTiq7mjAFnND15rvdn5 sjMoNUgfaJdXnuER5pRVkobnE+NSw7LOp52uyM4pTw/MCIrNjcm4mMN3EKOk pMCMsL1PG2vzve93JmZWx+RuVu5+2pGb8TP1aXOteQuPiuc6i2cflfo6SJRM ooJJ5uFQdBSciUIICFhA3D2knBidLEIjdeYxrKh4DY3gJWJGa0z/BU2xFmXo xDlGeZZeGq3g2tCpZASAFVxqbci/XNXZ1wcn28NItjCyEUwA8kpliRaCUGwA KDCGiyCIVLZ+yfml1xsba9saL9VU5eWfCvNxchQxApW80miv1ouZTeVp6YFG IZMEPCgUKpVCk8vkYWHBRedyS0rykxPDItwMgSqhv5wbppVEWMsFIrLCUdLe XT072Vtw+TREiMm+eiYqO+L9l7XdvWmlnWxqY9Q3wbur98Gl28V5l/Mr6i6E nYrc+bA0tjYm99S0jnRKHSRDE8/3N4Y3V0e+fT+IL4jh6Pn3y0JXOnKmW3Lf tp6Zbct/eS9LwCOy8QgmAU1CwQlwKA2N4uDxIjJRySQbBQw7LtOKSZZR8FY0 kr+MG6cRJWikyTpxikaYphVnWktilTwDg05DISk0dnBW0c3+1y1vpqAURwjZ Dko2Qgk2IKwKjBWBgDLEmAJHUxjcQlILz1+uu3vj/t3zVy+cTEn0dDJY8RkO PEaKi646L6zjataVjFAHlQCPw+FxRCyGwCDT9XJFkJdDuLeTg0aqEzKNfIab hBNhLfPVKqhMUmJm2OvB5pH+hxGp/q29DRX3Lpwqz/z2997oxGOOkjG5BGAV 0NxVU3o9v+BKUXntBfcYr79/HGx83OQ5KIbmh1/PDi1vTQPKuLb68svfB09G OuQOspg4++XnxTMdhdMt+bOdhfdKglA4sFzE5VLJBCwai0YScTgKkUAm4GlE HJOCZZHwbCJRQMCrmdRAhSBeI4nXyKNVojAJN1wqCJOL/SQCNZFCxWIlGtuM K3WNb2ZaJmfAZAcIyR5CsIHiNWCMDIwBsOIBQEGxfBpP5+AddTLvXEnVjXNX L2XkZgUE+WuVcgGTpGWSgqwEhTHO9aVJV7PCXHQSLA6LwOCQKBwBQ+SSaBoB Sw+wHQnHI2HlVLJewHaQ84TAKVXcu43Fr4eanj6rT86N+v5jt6SqIDoranVv tnuwmSWlLK6Ne8b6dD1/cP5WUcGVs8U3z9sGOf3x94f1jxsMo6DrTe+PHz8O P20CNbi+OvDx6+7+p7XE09ECg+BBTdZm/5WJttMLbXmpwfrfQCAXTw+DrYHJ pONMk1/wWCwWg8WgMaZRdoBwY9EYMgYtppK9ZYIwlShAyrdn0azpVGs6TcOg KagUrmmSG54t1YfmXChreVz5+AWUbA8hGiB4azheC8EqwRgJGA04Bw4cL2IK DUb38Ki0nLT8/Ni0VC9/PyuNhkmnEUxTPdFGHiPEVp0W6BrlbiNg0+BoNBxl CjQSTcTgft7tgqbh0HQclonHcch4HhlPpGC9Qtz6e2vHR5obWyozihI+fd9I OhOP4WIHXj++df+K1lG+tz/nEunybLir7HZpZmlWeW2FY5jbl78+fvhjL/ti GkXDr22v//bHwdrK89Wl3qMv+5+/bD8Z6hA6SJx99HODtXM9Ja/unjJac36x OOEZFODm60vnsDAAMFgs0FPAMSgYGglDoeBINBJp+qx0AlZHpzlwaToKHiA0 EhqJM91iD0Ob7vBFwJBYFInB1do7hCeGZRfBSEYY0QgnauF4NRyrgqJlEAzg SEUIgpjMsZLpnJ18A90CgvQOTmKFksZgoZAYGBSBgqNoGByfSJbSWAwCEWoa GAUHXoahMCjT31QJDIC5KGQiFkfCYmkEvIiKd5CyxGJ2yYXM8ZEH02PtldUF JZezd9+/dQpxvNty69tf2+lFKV6+hu13Yw6Bxs7eh+W3y2KyY85Xn/eI9Pz7 x493hyufvm7dbL7FNIrffVjd2hhYWXzy9fPe/v7Kx88bgC7QrdhZGeELzyqf 3Mz0DXb412//0tk527l5YslEGAYF/xk/gQICDQOuAo6EwWEYJJyBw/AIGAYa gQNegEOhcAgMDobCoWAYFAKDgRAwSwQUhsXSeXw4yQZOtIUR9WCiGkxQQwhW EJwSipPDCRIMRUoXKPkKFUcspXF4eDIVicLAYaaxSGBTwMBQCBgKBUGgllAo +OccJCgCcO94AuAdWGwWg0khU7h0so+1vCjW/0FJUkoCoLxn+h/fmHzdUnY5 4/a98qX1Eb23fmCo4+vn1aD4wLyCxNXFbrdQQ0fvw7Kqc34x/vlXC08WpEws T72Zebm6vzCz81Yf7LC2v7iz8XJl9tHR0faHDxvv3y9PLb50irYX6IRleWG9 D4rOXcg4ZvYLFei+FCoIGgHFoiEYNAyNgaLQ0J+TiqBIOAQJhcIAMKBwBAwB WCgEFAyHAMdEFIKFxRCB7/1nAoBgwOswSyjYErg+EpBUQGrpISQALg0IcKQE DRingODFSKIIC1QtlY4mkIDiMv1jHo4EchMGQ0BgCAAiEHAGKMTcdGD6JsBQ JAiGhqNxZDqLzmSzmGwRj+VnlNzKjR1prtocuj/cUdFYX9jdWjHxuunytZyy y6c7ntyxD3N89KJhZrFf66Uvriurb7ns4KPrGekqvHjKwcdYeruEqKQztNyK GyVecd6vll/ZhTqvAlitDSxPtn/4vPPpaHt3f2l7b66jvx44g8iGV1oc/ejZ PTIddwICxpDJCCwGjsNBsVgwCg1CmkZgwRAwEgHDoVMoGAwcDgMj4CA4xAIG Ap6RCCgfj9GwGGxTsZgGrIFgP8N0AIOQbH+GEUK0BRP0YII1GMAKD2Alg+O5 CCINjiNC0VgYUOCmBtk0VwSodMB1gCEQICxhpgDAB0FhlhAYCIYAsMKTaQQK g0Sm6STc06GOz2uLVoYf7kx0rw7f63t6Y2aqa3Ls4a07Z508jTkliSw1C8sj 5l/KDUkJsfY0Bib4Xa0++3Kk+UX/vaeDrfMro1fvXIg5HT040moIsPVMC9T4 265szWwvv1gef/Dh0+anL3u7hyub76a2tt9UNV0T2EtVTrKHXbWB4d6/mB1D ENAILAqAC4pGQRAIkImFwBwyziAT2klFQioFjQHQQ0BRCLFcauuid7CVBzla u2slbBIRAkVYQIGSMY0OA+ACDqAUB8AzQMhGADEwweb/YqWEEuUoshBN4SBI AFxAYwScFQOoCQnoZ7BYIHctTFjBfqIEAQGgAeeEms4JQ2GRWNNEOwwWbyPh liYF9lafHWurXHlSvfj02rOemxMTnTMTbRFJbmoP7dMXjbeqi1ofXh4datzf mVpeGDrcm1ueaevrPD85Uv/paPnd1szB/srB163NrbE3UwNhGeHJRSn7hyvv FvtXxhsPD5aPvn3Y/7i+f7CwMNH9fn8+5VyCwEXpmeBj5WFtSQQIwzT6CoKA Aw+k6T4SmJhOdLeSuVkprPhcCgEHQ6MsYDAam5l5OvtG7ZXqW8W3K8/GhHvQ SUQQ5P8m1U+gQADDkOzBJAOYrAeTDWAS0OlYA5UIJqrgJDmaKsbSRGgqG0UC 7AmegscCCusoF7kqJDQ80hwMAkOQIDDMVIw/Kcs0ug2BBPIKCDACEGesUcY/ Fe58NSuoKiuq8UzEs4r4wf76kZHmydGmyqqsrt6a9ZWXO+svFybaB7uvr073 r8z3Pb2b21mVOth1dXGqbXXhxcry662Nt1ubbzfXxj4ebADm4dtfe+8Pl7eW BpdeNbzfn/vy/cvhh80Pn9aXZ59tr0/Ozr1IyY9n2ks5zkqqiGlm/rtpaj0Y jITBgHpj4jA2Yp6jUiJjMZCm+7uAD4wwg0JV1tZ3H9wdGOl63tf8qLsuNt4P 8BRAJgBUYwkABYNbANcIMBvZFgKQFYCVqQyNELIOwApKUMHJUhRDjGfK8FQ+ lmSaGiugEt3l3Nww17KEwAC9HIOAW4AhIDDUHAwxg0BMZzOlKxyKwsLRWCjS NPnHKOVFOSki7MX+Klawhn0t3r33cW17W/nL59XDA3emXzdvrwzvrL/+fPB2 bqJ1oO3i5vLIztbo29GWg725zb0ZoLle2p5Z2J6Z3Zxe3l/++Glv//364Zd3 JqyWB5Ze3Xu/N/v1ry8fjnYOv+xsLA9vb02trA2/Gm8prDwXmZtCYJKPnQB8 FhgJBuMAskHAWDiToeIRCHAY5DjEEsgoMNI0zc/aYKyqqWx7dLep+XZt7UUP LwPcNKcaYcooONIChgCUy7RNAEmLpWoIVGs8XY+i6KCA0QKSiiBHksVohgTH kBAoXCyBhsMRZCxKhKPsVm50x6Xc4kgPPglvDgIBcJmDof9gBTYNEAZqH4MA UguFJGHRznJBiod1ipNVhIYXbRBWxnoM9j9qe1LXdO9cU2Np7/O6jvbKutrC e3eL6uuKLpTG1t3OXF8Z2d+buXHvMkPOERjkfHs100ZGtRZTbaSXGm78+eP7 x897Hz5uvlt9ufy6YXd76stfnz99ff/h8967zYmttTc7Bxsve28eHE5euXUV UGxzSzOIpSUBDOYhEGwMggr4ZQSg2SBLMKBK4H8mHoMRWI6AHxjmH5MQFpcY FB4RJBQLAXBAgMTDEZZwlCWgkTAk8PDwCElOiMuMT0wODvN39pAJbTBEGZoo RZPEaIoITxPiSEwMjoTD4ORMcpSL1ZXU4Du5UbkBtkIS3hJkGtxtAYaanv9v QJGAxQK0AEon4iPttDfTIpqKUpsKTtalBtUm+U3MvBmff9358MrQYGNwvK8Z 8A1TUBYYsCUO8ivcUu1u/XbhecuTegQbexxu/jsOcgwHPo6FHCcgzBn4EwzM pfobX/7+9vHTzu7q8NLr+p3N8S9/fvn8/eDj0e7+7uwGgPPBztvJJ6Mv6zLT Yih4JBhiAbe0ZCLhOjLRnsWUUAEKg5iDTMPWLCEAXHAIAo3C0ylcKZ3HptBJ dCaFwWSisPif9GsidhAUSCrAUqBwaHT3w/szI4MTvT1jTdXPbpRfSYtz1Gux BC4Kz0eTeCgiE4UjI9E4HAojpuKdZZxwO2WMk8JexsEiUT+/nZ8Q/ST2f8oQ jDRNtSNgcGIqI8ndWF+Q1H+jcOTm2bYzMZfCHWfXZxbezb5+2dTUUgkmQn/H QE4Q4MexMDMiAkLH/wcFjs2O8U30PYaFwNlkGAOPZJEQbDKCR4cJaMcoCImX 4eDPT0ef9/fWh1fH6jdXX37989OX7x8/Hb3f31/eWH99cLi1sbM0OdGRHuku IWDwcEsiFMTHI53Z9BCZSMsgwwGT83OWhYUJK+DTIvEMAV1kILH4AGwwOMo0 JR6JMmUU1MRUQFIBF4VEIMlY3OLU8N7y23fTI9tDTRs9d9/UXahMD9eIBTAc AYmnIbBkBJoAR2BxKLSUjrfh0fQCujWPwsUgwJZg0wSbf1QV4HbIT88AVDUS TSJTeRSKjkePcVJdSQluL47vPJdQGecRJCU86+t693F9bLi5/FLObzAzOBlH FrFpUjZeRAFTMb9Bza1cdc4Rbv8C/fZvBOTcjYqB8Rd948+vP7yBEJLMmFh9 hNfht49HXw52N8fXJ9rW5p9+/X74GUi0Lx/2DtbXN8bfH2zsHG2/XRgOdpZI CSgaHMRCw8R4tB2D6iVgqygEKBhsmr1jmqH9k2ChECSWSKDQMQS8SSvhKAgS CUYiIKZxrNCftgoBXB1gAyh4wuJI+/pI21pfw9rTO+tP7s13XHl8ITHZWUsm 42FYCgKLBZgHIGwKEWsrZkUYpXHOVoFavg7o1REoII3BP2kKCEuA538eAwLI 4QptZWIPlSDcXp0VaF+W6Hkp2jXTWWmkgaqunN0/2nkz3FpSnvE//vMvjpLT 0n27v+/Bg7bbUDruGAYSnZcYlRlGEdFZakHT4wcHXzf+/vGpd/IJTEyz4FB1 4V6H3z99+nK4sz29PtW+PN169Hn38x8fP337+P7TzubW9MbO3P7R7uBQp4aF YmLgRDiYiUXysSgxEa2g4DmAhweDzCHg/7YBJtsDQkAhGDiEgIBwMGighTPN fQLc/M+5T+amUjVdFIAhCUeY661f6Lw213p1oaNqvuP66/qi7gtxxSHOWg6T zeRwWWwSHoVFQXhUXIBWVBhodznWqyTMxV8jJ5s2+4D8f1iZnAOgrYBYYPFi iZWT0dlZo/K1FsW56bNDPbN87OKMYg8ervxM6saHzak3j4pLE/FMnG+w0/ib 7rX18Ud9rXgl+wQbX1RVPDX39Fl/49Bo5+rqm+YnDYU3S+JKMzE6oaWS4ZQQ 9O3v7yasdmY3Z7uXx+4fHm0dAVX57eOHz/tbO4ubuwu737bPn0tnQC3wGAQS aklAQKlIGB0NY+OQZKSJ2AEEQCZ7aRqYSUHBCEgYDQ5REtBuYpa7gCkjYqlo FA7IEIBhTKVqKhwk4C7R6K4b517Vnp2oK37bfHG6/cJAdU57SWxhsBHIIp2Y 56BSqLkswPYrGERvK162l/ZilGt5pFuE0YqKw5tcqIn9YEAfBTxbwOBmUDiG QFdZO3kGRts5OUgFNAelKNLeJtxO46sV2TGwufHhM5tvhwfuP+260vPo1sRo R2NTpXuYh8JVB+aT1V7G5vaqJ89uvxxseDvxeG97MiQp8H9A/2PBJVqKaXxv w+vN+Q9fP3w42t/dW9pa7FscvQsY0aO/j44Ayvp6sLW3vnOwDnSLzgYpEwkj YYGWxRINh+DhECzUkoqCU4H8gEEtAfmGAk4QKSCSpFQCl4wTEDEGFiXOqEmw tbblM2UMspxBo6BMA7fNfwrWz6UJVKSTujzKpTLRp/F0TFdZentZ6r2coAwv jZJD0Iro3gYrZ5VERiZo2VRbEd1PxT5pq0i0lbuK2FQsHmRy7yZi/yelAXmF YEhUrtTWOyL61LnAxCyFwZ5JIap4bIOYDRCdCAePiwt+szjy9NH1nvZLj5rL e9sv5hVG/e/j/8cMDgbR8Lfb74yPPx6b7Hoz3DzxqmN3azwsJfT/sThuTsZa MggUK9HYytyXP74CWO3tr+1vjs2P1L57v/D57y8mrL592D54d/Dl/fOBLi4R zifiSWg4BgHBIIAeFYKEWODhUDIKgQfaHKDAoBAGDuss5ofYSP21Ii8ZJ0jB zbOzKnSziTKIQvXCCDu5jkcEHOw/WAEXCEeg3aXsJIPCXUS349NCbJSnA+zP RdiF2ctZFIyIQQR6Ab2Iy8WiVQyyDZfuxKN5ipneUqaBQ6FiCYA5t/gpf/8k KhiJQ1N4XJXRKSwh+2ptUXVLTO45kUoKGC4iAUMmILGW5nda6iaXRrrbTFj1 dl2fHLp/viLtONwMhkcfg1s4BHr2jfdOjHWM9t5bmnz2bvXV3YeVGcWpwYlh FljkvyC/W3vZHX379PX70YePOx8OV5dG7m4uvTz668vH758+fgWanb2jPw+L zqWTwRYcIgGFhGLQCCIOECagPTZHQUE4BJSIRGIBowmDqOjEkw7awkD70iDH Ul/bHAfZZU/dnTDXqhj3y3Ee5REu4ToeCQUxM23+AoUAxhSOuhrnXxsbGCDh UlAQBhZuJ6CH28jshDwSFscg4VR8DodOJKJNswHVdJI9j+4hZnoIaTomiYmj wlEEk7bCfkohFIHA06kCK6Wtl3f8qYJbD6q7B4prm4NPZlLoVAgEkEwIncWc WJ99+ebR40e3OlrOdzWff95Vebsqs6Aw2t5F8xvE4n8e/0/YyZCxsbY3Y48W N8aXll/NL73cPZyqa752AmVxHAehq7ib+2t//P0VMJ9A17w51b74pu3T1w+f vh8dfjl4f7S/ur1otBIS4FA0BlA0KAaDolGoNAoJAQcDXT4KDqQZHAOH8fA4 NyEr0VaV72u8HO56NdQp30VeaCeuCXftOBXVkRdfkxSYYJQwsYAIQv5ZcQKw uhEb2HYq6oyT2ltEdePhAxScII1Aw6bhUWjAgDIpJBIRTcTAOTiMnII38Gje Ml6wWhgo41szOWSToyBCEVhAWxEYAoEmFlg5Ke19fRJySu8+uv1o4GZ7d97l O64BESQK7djx3+29PV4tTTW0Xet5XvP0WU1H26Wm+2UdD84/b7+YkR70O9Ti Vwszv0jf4svZYge1wKB8/Kzl4+fNze231fevmmMhgAeT2FkBevft78+fvh0e /Xm0szKw8Kph//3m0fej/U97R398qG+uAcwaCYNGwk2rBHAUikKhMJl0AC4c YJIsLREQEBWPseNxfeQiTwkvWMbOdlQXe9unGWXxGk6Zv7E9O6ozJ7YqyjPF Tqlk0mBAGUIBNYQgkKhTLtbXo72vBzqetVOecVTmumhS7JWeEhYP6ABhSCwG S6aQuTSqxDQjjqhlkJxF7ACNJEan9FKIBTQ6EkOGo4lwNAHog0gMCU9hL9W7 e0SnldQ9ut7Wd6mxoay64UxFtX9kPGCIk7MyNz5vt/c/6B5suHbzDIVHZsvZ 7Y9vjYw0Fl/JMsOCf7E0c/J1jEoO/bfF77/BLSMzEwqulQQnhGpdDRYkwKzi GCr+xu7anz++ffvr697B6sry4M7m67395Q9f3u9+3P3843N4nL+F+Qmgbwcs JZDqYIBl8DgGiyHk84RsNoNKpJJwSi7XSSFzlgn1LIoNHRui5Kc6aKK14igr UZGffUNK4O2T3mf9DGmOGgOXjYDCzU3+AQZBIHJdrcsCnGrC3MvdtIXOqkIv fY6bdaRSYE2i46AAlmg6k2ujsnaUijR0opKMU9MIBj7DQy5ykwgkdDYaS0Zh SSgsGUdkkelirtQos3ZzCT1ZcLOlor4np6LiVFlFeUNLaXVj1Mmcq7ert492 Xrx53N0PYJVvjjQ3R4FsPQ16dyNBzALhEf+2NLP1MEYkhfwKMkfTSBZo2HG4 5X8g5scRYCSD9BsO6hHmc3i09+2vL7vvN5ZWRnd3prc2xrd25ncPtz59/zT9 bp7KJpm21cCgTY0eHGVhWjWCEykUkVCo12rsjHqttZVIJJAIuLKfc9iMHIqv jBeplYQqeFFqUbarriTY4UyIIclZ5Sbn0PEIMBhmwsq0igIvcNOfcdZe8tZX uGvO2EnzPLSF3oYknUJLpMIhpm3lOByJo8HZx0arZ9MA7yHAIXk4JNAMKphU HoODJ9DRGBIaS8HgmSS6mCnSSqycnYKTUs7fTi647hYWYe/jn1B0vrjuQVnd w6Ynjxa2ploeX2/rvlnXdAlOQACKbgaHHINYmiFh5oD5waBqG27e77pB4BL/ bWH2OxT0O8TyPyCL32CQ/wMyU7nbLbxbAJpBwG2uvVvZe7+0vj6yMPt8a3vh /ae9na8HRi/nX//zGwRovuAoEAwJhqOB1LL8uY8ghUo1GHROTvZKKzWVwSD/ 3KlNAQgWn+4t5QbJuX4iepiSl2SnyvCwTnVX+6g4XAJg8k0rAxamlQETw8dJ uTESVq6d4qKHId9eleGgyvcwZtlpdHQ6DGra9ITJERoMjq56KwOLpiDi2TgM HY1kYFB8CoHN4lHpPDQOsPcUJIFJZIjJTAlPZnQJTY/JuuAemkBgsVFEskxr CEvLOn31Rv2jJxufNp6+qGt8eKnt2R2jp+3/PPbL7zBLEBYOxaOPQ8xDIn3m lobejD1sa6ty93dxDHCJSgpLSAqJTfQPDndpf3Rv+3B1c395fOr51Kvut8PN g91X+zoq3rxq+/b3h6uNN/7Xf/0LDPSnYIglBGHangOGsDBJj6kLRmLQMrnE 0cmOL+LC0XA8niRhMlQsio5Pd1XwApW8WJ34pJ08w02b7mWId1G7iBl0FNq0 Lvf/WxaI4DPiZNxkrSjLqDqpFoXIuMFyXoRcoCaTUEgECoWUyDUeYdH+3j4O PK4Uh2VhUQw8mkvCixkUsUDM5snxVDYcS0LgaRgyF0vmsKV6z5jTcacuGtwC oFisBQQBQWAZPLFMZ3fhVvXXHz/e7a32Dtxve3z9YXtVdIJv2EmvnOLEWw3l D7uqh0cfvRyu73t8fXykfXKy9+Vo59hIy/jQw9GXD6amenb25nY/rM1tzEzP jYwPPBzoujn0+OarvtsDz2t2DpYLrhT965f/DZCwuSXIEgSzgAJNBNISCBNc cCSWoLY2BoeEODrZkGgECpWp4LKs+QxrLt1RwgnRSlIcVHk+xlx/+1Rv2xgH la+aJwJcBxyoPsjPOfAmrU9Q8OMUvEgpOwp4VvC8+DRrEtqGhJLhsGgUgkAi 2nkHxOaeD49Js7OSSUk4IQ4tohDkbLqcx1RI5XyRjsaVIvFkBJaKxDHQRKZY 5xyaUZaQe1lt6w7D4gCsQDCAZoGPjWnq6v7893fAC23uLvcPtfY8rRkZbXnc ea2x9kxDbd7LgXsTr1vaarLaa08PAf3p5tupqb7hZ3VjQx2Li6OAPz842pxb mXi79GZ9a+H94bvPn/e2381t7y3tHazsHq5VNd3+5T+/mFuAzCxBZhYgcxBw gTALMNBWIIGAIDEqnSEqMTk0Nl5pcOMo7ZRAEnBoSgZFy6I4SzkhNvIkZ0OS qzHKSRvnaBVsZ7CRqTlMFhSNNAOBTaeCwFM10gAe1V9AC5VxUxys4+00XgyK AxYhRiAQcCgGj1XZuQYk5AbEJDvoNVouXW0at0ixlgp0GrVOp1eq7EUyOxKN hyWyMDQ+TaQ0+kXHFNwMTMrnSNUgFNIcbFrWMAOqgkB6s7Ky//Xw6K/PR98/ rW8u9r9sedpb9+Jp3dPOqsG+huHR9tbGwoaLsXfKYp7cr1hen5yY7J2beb6x OfHxaOPgcGNl/e38yuTM0pvl1cmNtZGPR9v7HzZ3D9YXV2cWNxeGVscxOMzx 42bmlmAzS7A5CAa8NYCVpaWJbcAIjEBt75aU55lxUR97WR14UWsXImVROFgM F4fl4HESCkHHodtL+N56ebibo49/hjHwjMIhgsqVm0NgZqaTwOPVQi8WKUjK CdUIC+KjLuUVJ9nbeOIArIAEhEJhUDITcOLOegdnW63GRS11knLsREwnncrF 2dXewdXaxihT2nJEGgZXwZLoZUZPz+hTAekXrN1DkDiyOeDqTT+EIc1BEDyD MbG+snX47vDrISBkX4Hsejc7OtoxNPRwaWF4cb6/rfniw7uFI333l5aG5ua7 p2cHlpdf7+7Mfjha3TtcXt1aWNicnVubXlqdfLc1vTL3fP/92qdv++vb89ML 4zsfd/rHexAYzLHfLcxB4BNgiAkuc8vjEASUzEbLXFhO6bKg87rUOofTbcZT nVapnTK/AglfyEXDqYAHQyLISDgHj9dy2V56pV9YknNqky7rkfXJOrFzOoaj tkBizMBQI51oRyEEStmROsnlsrOtj0bz407q4GYsoG+CI0y7VxAIPKFMq9Eb tFo/oy5IL/NQcJ10Ck8vd28/Pxs7g1BmJZAZuRK9UGmntvW2cQtWOfjQ2EIw GNAg03o1oN0nLEFUHmvu3frup/3tD+++/Pn5+19fvv3x8f3B1tbm7MrScN/j mr6n95ZX3xx+2pqfH5yZ7l1dG9/dW/j0aevw4/LK5vj67urG3tr2wcb+4cbG 0vDc6MPd3eW1neXZlcmdL9trn9/5hLj/+ut/WYChQMmcAFlaIHEIhhXdMV4d X2N7tte5bMD5fL+xoEeT9VCd8kCe3CYLvsCXObLxWAoKRkbBqBg4n0LUiWWO LkG2SVWG3B6bvKeGnB5N4j2eVyFJHQIm8YVYpBiDsGMQ/GXs8nN5z8YWbtY2 2AjZBKgl2OKEuZkZCoc3OHuEJyYHB/sGO9tH2VmFWsu8DOrQyJCY+DhXdzc+ T0CmCslMBZ2npPNkVLYIQ2KYWMISZmnaxAcJiNAvvx+3c3Pd+7I7vTQ4v/lm 7+jd5z8/ffvr218//gQ6u7m54bWV8fdHm++/7+5/2t57v/YeiP3lTx/fvd+f m5/vf3ew/unv71///uuPH3/89ePvHz9+7K71bm4Mb33ZXf/2rn38mS7I+Rjo dzOI5T9rUziRgzrygnt5T2DNZNj9RZ87E/YX+6xOt0jjb7F8C3kBJaK4O/Ko 6yxdOJnBJwEdCgzOQCHFPInCNlQTdUl9ukcB5F5aky6z0zqjQ5vSqoyqY7rk 8TBoHhyiZxFj7ZVZyRH1vf3dr2cKKq4FBIbbGJwA+RKpNaFJaYXXqwuvXEtN SozxdAg3yCLdbBPjE6NjEnx8/WVyQB4JECQOgsYCATCDqQTAIAsQ1IQVDAG0 2L+DwAyJeOFgZfj5tYGnFQvTQN31bL4b//hp9cu33T9/HH3/8efh148Hn/c+ fH6/d/Bu/3D76MvBlz933+1PH33f+/7nyuH24P7W4Nra87Hx1iftV65fiC26 lh1TlCX30FtwUCfIcBAK+jsYbIlCM+1inEv6I1vXQjtX/R/MOt8aUZ1p4QRf pLmcItkm4q1jWN5nJcl3xYk1PO9CqsodR2KTAFniqAUu6bLYWqucDquzfaKU ZkHkbXVSk1VSk/ZUu3XhY6vMNpVKTYOBHOTsgrTAMzlhxbeutLyabh2dru0Z uNnZW36v7dzt+2V1zVWt3ZUPH50pK48N9Y1w1CaFecclxoclngxOiPeMjFTr jSgs7gQIZA5Itqkxh/xcfjc11KYAnCESc8zCXOdp1/r0zrPmjOed+WMvr6zO 1c+8vjn95t7SfNfsdOfq+uTh592jr4d//zj668fh3sFE99Mb7Z03q2/nZ2d5 +/moHF0EUhWZxkFDCdATBPgxAuIXHOQEFQUXkOBSBtAYm0FABJWTY+HjwPpF /3vTTldf2pb3WZ1pZ4VfITnlURyyKE6n6C5nxOHX1alNquRWQfBFssoPSeQi 8RSqVYAwtlGZ81xbMGBdOCiIb+CGXpPF3OGHXhNFVFvldhrOPgmKSyWjUVIW LiXVvaQ0sfjahYYXo4/GZrvezHRPzj+ZXXk0udD6Zqr+xdDt7t7S2rr4tITo IN+k+Ni4rOSQtISo3NO512qTSy7JdHpz4GFpwurnOoZJZE0BYPXTQgN97K8g EEJA9gi2tbYXS1XMkrLo+w2ZT55UPO+/MTn9YGr22cbe9PuP05eunUpI80w9 FQTopzn4+DGLY8cgFv9GQYH4DYcyI+AsqAQQAw9lEuA8KkxABwupcBXHDI8E Ean8wBLH8/0OF5+rc9uU2S2a7C5FUgPf7zzT/zIvqJLtX8H1LheHVanTHlql tDBdcyAMlTkcDcJgsVJvXvg99ZlB66Ihq4IXotgGYfhtUUw9K6CM5lYkCq/R Z3UWXqpUiOU0BMjbKMnLCb3eXN8yMvVoYqF7YqFnaqnn7crjt0tAdE7M3Ont L71Td6q4IC4lMTIhLjkvN/50ZmpJ/tXmtuvtTwJTUyFoFACWJRj609v8t70B sALKELA3AIMhyGRLMv6/QBbHoKB/gy1/Q0DgeDiJQyJwCFK9AMvAsMRUiYb3 G+S3//rt1/9YWFoA2oI2jcOGktBgGgZMx4GZBBCTAGYSYRwSnEtGChlQERMk pJlziRAuGW/lxY+tU2Q2ChNvCRKqRfG3pQl1QHpw/ErFkbd5odeZvhVsjyJh cIUsqZEfUokQeRxHEk/AESfgaBhHzwy4pi0c0Z0bssrrE0fVA+mkTGsXxTfR fc5T3M9IIq/X3q0PiU6QEND2AlZWWkxd97OOycXOqcVHU0uPJpc6p5a63i4/ nlnpmpy/OzB4rqY2LS83NiU1JiXtZE5OVmlx3pXLFQ2NN9u60s9foPEFZidM 9uafMCUV2LSqDGAFQqAhCDSSQoIxqBAiDoRHg/EoS7Rpps0JGOQ4FPyrxYnj YBAg+MfMfrfE/MSHgAGTfgYFB6JhIWwCjEuG8SlQLhnOo4BYBDM61oJFtBTS 4AqOdZBb99iwbWIhx6eQH1DC8S3h+pdx/Mo4gReZvud5gZeFEbe4oddp3ueZ bmfYPmc54TeILnkgjhGEZZghyScQOEuKgOB0RpnVazg3rMp+Kom5L4mqU6S2 q/KeC6PqyE45HN+LNVWXTl+qsVXJbMW8lPz86hfjrVPzbVPzXdOL3dMLT+dW +pbWn8+v9Ewv3H0xfOb6zdjUpNDo6PD4xIRTaTnni/MqLhRdu3i9pamwqlpi Y/zt998ByTYZXdPPrABfwf9xvBAk0gICBhOx5hScJR4DIqBBOBTQA0JxQP4j TBOTsAgLNNwSZfrBAIJBQrAoMBEDJmNBJKwlGWtJxJiR0b/goP8HD/4VD/kN A6JaSzguWo+4IP/8k3HXC+uGOwB1rOp8gbeOpLuk0VxP0Z1zmB6FDP9ypt8F bugVTmgVI+AqEyhDv1K2Xwk99BLR+QxS5AIncs3RBCDAeB7CKkIY/8C6YNDq 1FNxQosoplGS8FCV0S1NaGJ4nOP4VJTlhqVfvGPv6C5l0N0joso6+5rGl1un ljumF3tmlodW34292x9d3346u3yv/1Xh7XsJp08FR4T4BvtHxIZnn87JKyzM OpN9+f69yodtPgnJIBjshLmFmek3uH9I3tRyguHI38zMfcP97aK8MDKWBQrx G9j8NxjoV7DFL+bHf7H8/VeQ+b/Nfz8GMje9Dvr9mKXZv0EW/4Zb/hfk+DGY OYSGw4oZBB7BNdIjq+Lclebqs9eKno492fy6f/jHx5onjQElycm3zk7tzC59 /sB3D8Nqwmj2qWRDCs0pl+ZbwQyt5IZXsgGUgm7wou7yo2oEMfe4sbU0jyKU xAWMY5khcRZoLIyqRqtjORG1ilPPlJmPpcmdkqQWftQdRUKrLK6J5l7I9bmQ F24MDQm0UtkwKBSWROGXXnj1yej98aXmyflHs8tDGztvdt6Pbu71zK7cHXhd cq8l5lypb0y0o4uLk6tTaHhofGJ8TGLs+drbTS9HihsfspSK383MzCH//Q8H AC5AEI+bW/CEgGHYGN162zX2NCotzNpda+2uV7vofZKiglIiotMirexVcp04 Ijmi4Hqpxs0m5lR8ZVN1ZkV+TIpnzf2L/XOvu3rvzC8Pfvjxff/vTysHy6/m nm5/2jj889PLtdf+xSdrn97vGe/9/uNHwOkCEN+TZB1LtI4m26cz/C9zI24D wYmqFcQ/kCR1yVLaZcnt4vj7DI9CuMDOEkO3QBJBaAZC6E91PQ+8rjz1TJHR KUlpUaU2aOMrrKIuKcJq6O7FTPfS7Ah9pLtKJuBTGUwWV6yw9UysuH21f/zO 6+mmydne5c3Rd/vD7/b7FjcbRyZKmjsSyipcY6Ktbe0lcpm1Tgsg5h7gVd5Q 3z07d+vFS4W763/MT5yAQE78zCsgQHDEL8d+K75W8cePvzc+785sz/QMdzT2 NrWP9PTODb3afDuyMDgw0fN44GFVQ3n3y66PP74sv19eer+48+fB4uHy2ELf 64m25d35NzOPxqefLr/fWN5fX95bHJt7tna4vPN1b+fPj5oY1/q+tqWDta9/ /3mlvcOcbYdX+KGVwXTXMwCf8yJu82Lq+In3pelt0sxuWVaXLKNdEFNHcTgF Yest0WRzJM4cQ8eoEjhBtfKTLfJTT8QpbdLY644JJe6J2YaweEVgMd2znOhc XJTkcjrR2c5oS2VLuEKJwuDmFJ+Zcae1su913ehUy8xy78ZO/9bu4Ppuz8J6 df/I6aqaoNR0rWmfCDaDwRBJJO5hgdW9T/tW1++OvJK7OALkDNTgCYiJ2wG+ OmEBIjIZT94Obn/ZWXu/MjzdMzzd1/u6/+nbl/O7C2+Xhl+8ap1aeTU+O/jo WXXfyIPFrcn1g9W5rbml9xuvF0f6x7se9918+frB6FjL26WBtY+b6wcb6wfL E3NPl/fmNo+2//zxI/9msT7Gff2P/cMfX/7fkq7zq6nt2/4Rb7z7fvfpVSC9 n/ReKIGEJHQI0pFiLEhRpEgROzZAUBFFUGkCekVpQUB6l5aEkAIkISFUafZy eeG+/WF/OmeMc+aYa+61xp5rrG61Asr1QnB9ce4n6GG3OXGlrPgy7rk618xG twutgottwotyflYTO7GMEJACZXmB0AQ7BMoOQ8aK0zlx9a6ZLfzMRm5ijSCu IDgpPfSkLPR0gufpfJbsMSms8E56aMn1iGsZx44GBbFZHL73Ee9jyTG5Rbn1 8opBRd3UbLN2vm3O+G7e9G7eXP9Bfa2i+kRGmkdgIIXBxAF4OpN1+nJOi3pm an2zbnycL/U+eOiA/b5dxxZ9tlQB9Z8Df8XEnZiyKAYU3e/H6ns+1E5q+2dM U6P6Eb11dsGiGFe1qQzjGsP4jKZzWtehN03rzGrT+sLS7rLWqhxRdnT1Vw8P Vqtn5OY1lWV3aWnbsry9OG8esWwuWHaXt3/t9GvHqCHCJuX7te87+s01svgI jCrGuoQTAy7SYh+wTj/jpNS6ZLxxyWxyy24RXpDzM5qYpx4DfucgDAkIBTgg UGAsjSDJ5J6q48Y/Z8Q+YMseiRIeeR5PPBIVFHI6XnzqJju2lBxy90Kc77Pb UVU3Q/MyYwQe3i5ewZ4RcT7Hk0NSc7IfVz3s6qsZV9bbclGF5sWk+sG7/rjb RZ5HQ12EAjKNjidS2C6OOWWPe4yL6q3d+ulpYZD0gN0B25H3r7bDwAjUH3/+ mXY5a/3X1pRuZGC8tW+kYWji7YiyfWFdN7+mNazMaBf69UtTc+ZJtbZTYxjU GcZ0ixM2Blp3llXGsWmdLQab1dq2OdOgeW3WumO2bJisH+cX16ds9LN+Xvu6 91WxPOuXGpNbXzxl0W3+89s97Kgdig5n++H902nHSjgJVazkGqfMBv4FuZtN iC51OGe1ceOf4v1SwBSBAxJwgKMd0FSieworsoQWdAvnm0mOuidKq3Y/liYJ ChaEhNCCzgABOYDP5RNHHB/ei33w8Gh6Vrjf0RihNFoSccoj6rRraIz3yTPJ j6rudQw+HZqsHFU+HZy6UtcSlHqJLZLYApDCYNgkziM46Mbr1h7zysz2p78V Kt9j0QfsDu3zat82AHWAIQ7+dTg0QPrp12eDVWtYUik1A9OaHvOa3qbMxnWd cXVGM9ezYJ02LisVM3KNYcBkmdCbx5e2zGuf15d2DbrFEYVarpvv1s4PmFZU S5vG5Y+L1jWd7Xnr9uLHn5u7P3dUSzNRVxIetVa/Her4ubd3KjvzD1vqxvYl Sy9z46t452qdz78VXuvyyB/2yh/2uDPkkTvAT35B9D0LIjrZsAIhsA4oKs71 JOVILskvE/BMYx4vFeS0ClKr+LG3ueE38AFXEaLjKOFpPz5w/VrwvTJZYqJf YEiUKOyEMPSEZ3SC5OgpSfTpqKuFl+vkRe1DJd0f7rUPZlU0+CdkMN0kFCaf zGCznXk+YeHn8u8+6+tr1OqLmptEof773hIoxAbX/19tHzxkV3j/7o/fPza2 rQtmpXVtzryq3fq6sbK9uLimtW7OzRn6F5YVtupGqW5Tz3UbzGPGZcXKjsW8 btAvfZjVvlep5Bp9l0rbbbCqTGu6xVW9wayaMystm4b17xtrn9e+/PoSni17 1l47saj6+OtbWfOr/7GDwWgeBN8LjBPF3PhS5/R64fVOyZ0hSf6wZ96g+Eav U2I1RnjsMI5mj8DZsAJjqVhXGSXoNkGaSwq6wTlTJ7k26JE/Jrre75T1jhL9 HOWWgODLJDx8WrxH0dWjGdEeUi8P9+BoydF4z6hESeQJ8dFTIdm30p/+nfvm fWH7YFH7YHblG9+kbI5HANNRwOFyXF15YncnicTFL8g35HhkUFQwm0uHw/fv au33re9QBzAEAkcMTox++/39++/PH3eWzUs604p2cV1vWpldWtOs7RjmjENz lsmlDc2stl230GtYHDVZFeYtw8LKrN40qJltnZ1pVs7aaqzuhSWlaU1rsr27 qtFZppTGMY11xvrJure3d6n8TnhW3PKvTcP20rBhCkUmH8YyMIIowpELxJBr lKPXqbKb7Phyp7RG/oVW56wW5omncNeowxiSHQxjK+3BGAqGLyMduU4JK6TH lrDTG4XX+7wKp7wKp4V5H5hnWzG+V5GiRHcaPiGMX5AszTriFsDluLh784Nj RVEJ4sg4fpDMNzEn4UFtTm3breauos7hnBetgak3uaIgjiPficsSuXA8XXnO NBIJCWURsGJHliuHQQRw0H8d3TZS/e+hvzx9xeufV7/88+3bz08//vm6+2Vj dcdiXNMal9XmVc3qlmF+cWJucWJte14316Ob7zWvTNk4trg1r7cqtAsDalWz aurNpPKtStNtWNJYNhbmlyaHp16395a3d5UPjzbYzoJve18ftVbwY337FhXz 6yb9zoJ3VNgfh1EInj/GTYZxP4ESRiGFsWTfbEZU8b7ax94nBV1HOgaAMQQw AgDDcVA0DcENxwfkMGLuOZ2tdUxrdc5+53apU3itz/X6APd8ByG0AClJckTD pXxastQ1UcwKJJG4VA6RJ2R5+Dn7BLl4h3hHJchuPMqoaL7Z0nWjuTuuuFYo S+fwPdlsNodBFvAYQh6DQcSSARSftz+HS+zMYtLJWAwavG81hBwCwcuqC/qH Sm2Y/N778eX356+/PtsCcHln0fxxzryut35cmDdNaOZHN3eNSytTc4bBxZVp 07rasKHRLE6oZttUk/XKqTeKmSaNvs9gUc7oR3sGX7V3VU5Mt2kWhpfWtctb po1vq7kVeREX44o76hZ3VtXrqpvl9//rwCF7EgtCdYXR3OEsMZJ3BOMWCbhF 4Z39yS4SPM8VT6Vh8UQkjoDEAigcGUGTEMRxRBsPowqZsue80y+4SS956XLn i73cjPekyPtocTIFAmUiYWI8LpBECMUDfBwRINCwNBaRzWO4CN2DosIzbic+ eJFZJ08orfc4e5noLiUxGFQcjoLdnwjJxKHISCgFBeMQsHwG2YVN4tJJeCwO ikIcPGxHZHPHZnrkzXly+cO1HdOPvZ9ffn3a+bb98dOqeX1f6jXzg1OKFrW+ b2PHtLKpVet6Vbo+pWl01jQ5axyb1TRrFI1qbceMulWhah2daOwdahgca9EZ J9Z2zKu7S8s7ttTUuPx19Ub13YvlN59114xbtLMrUy/ktQfADnYIIhjPARN5 UJorgilE0pzQtl/DAhgcxrZhARwWwGNwODQOiwEALIGOZvLhjsFg1xiE8ATg lUIOyWfGVrITm+hJr4lBd3DiVDoaSUfCPSgUPwIhkkiUEEhoHB5BJKPJdByV zREFeBw7H3KhKPzGM5/0B3T/WDjVEYXGUFAoJzzOj0c56s6NFbJkQrZMzA1z Y3nzKI4kwIYVHI3+869DEqlUa5kdGq5/1VDQ8K5sZcf4e++fL7++b+yuzVk+ 6IyDE9ONI6MvBoYrpmY7lOqO/sHayZlOhXFkem54QtutmG6cVbUr1e2z6rbR kRfvO8uGR1/bCGYTNOumYWXLYtkw6ld0ph3LsGnSM176ZrKpTdmtW9O/7q4F Y9F/QQEI4AgmOEPJfDiFhwEI6H/nnyL/fwLvvwtjW2gMBsABAA6DBxBUAZR1 BMrwcaCKYNxQtCAe5ZmK9EpHOkWiXWVMwCaC6HCBMMbVNQQP+BEpJAyAxBMB GpNAZhLoXJZ3qCjukuRckbMslyCOgREYAAbtw2ekHhHlH/etyoh9eel4w+2E 1qILL24kX48L8HSkYVBIOBJ18JC9o9Bt9cvWp69b5lVdS2dFTf3VCeXL3R/L qzt6jbF3YXFYoWwb6K9sbMhtfZs71F/+/n3ppKZjcmFoRN3TP/x6qKdqYrLl w/jb0WFbTdCwYJO1j6bljbnVbePytmn107J12zK/NqddmZvbMXHD+Tdq8kYW J/UfjfKx1wCDdMAeAcawIQALiqXD0PvtJDAYHA2D07A4Eg6DQsBQ+yNTEXA4 zLbtt/nh0DAyB+YUjnQ6CqZ6Q2h+cHYwhBUMono6YJhwjpSGx2FAIBGRKGNy wgDA3xaBcAyGymN6x/IjshzD0/gxOaKEAnFquWPsFaJACscSuGQgJUJckhpR kR3ReONkZ9GZ3rL0wcorvRVX3txLSYv2YxHx8P3rG8R/Dtk/b3rxc+/n999f VrfNbZ1V93KjSvJPdnfe18y2WCxKg3mitbGw7nFaU+XFnvbitqaCUUXTlGls cLyp733F2PCroaHa/p7qvt7aaVWnVtelnW3XKFuGekpbX1yanG42bS/Orc/p VvW6LYN3ojTxYU7TRNfKz832iQaqE+OAHQSEZYABBgSDA9u+B4GEQWACEkEm EoS48JzxaDYKQUMiyAg4DY2iodFYJBSCBZBcP7TwLNxZhmCGQxn+DhShA8Cx QxLAZDGTSEY5gOhQSDAOiCQT/HCAEwpLZrkKE+5LCzr9C5q9br3yufpKcr6a GXYezRQgUFgRi3rxmG/ZhZiXuafk+YmdhWe7H6UPVFzoq7rYWZpdeDZSzGIg Ech9RzcK+0T+9/TcgHq+f3nD8PnH7qxyoPhK/MU4UUNNhmbmnU2jplXyN88z /y7L7JQ/ePPqWl9/zYfp933ddUM9FSODtb09T3u7yjoa8t8WJzUWxtbnRVbl hlTeiu19+3jBMGHdtX78ubX2fV21rJGmhOU1lZa2Vm/vfelRtZG4tD8PgUAY OgTLAKHQIAQcBkdQUfCTYk5hdOCNcN+zYsdTruw4Cf+UhyDeW3BKxBOQMHAY GE7m4dyTUeJUqGMYmC4E4eg2oOyQAITkziFSMWAIAIU5IbH+BEAK4EPwFIkw wPv8s9CSruDidr+7b/1u/i1JK6dJzyLITmgE2otFPxMgTg8VX4n2KTkbXpMj e3ntdGNBUvP9lJbilIJzYW50si0K//jzjxPJSeZPluGJd3rT5MqGbnN32abt poXx8uKsSxmhZffjJkZr5lcVkxOvW2uvdbU/amq+MzTysq+/rl1e0v++rLu1 8G1lVsP9+L9vR9ReCn5+KbKmJKO9oVg91WlZ0yzYamvrlHJhVGUcX/22cexq Qv7bx3VDDead1c7JNiQJe9ABDsYwoBg6GIEAwSBICExIADL9BcVRfkVRPnnh 4oIY73tJoY/PxZYnR96LFkfzaRgkzB6DR7nGor2ykJI0KDMQhKbZwbF2CAyY 6MoiUtAOEBQUSoEjRRiMLxYXQqL4+Uf4ZFUE3W2T5jV5X6v1uFQpSCmhBZ5F 0PlkHMGfQw90pAopKHcySuZGz48W54QJz0qdr8i8HmaG3kkKdmeQkPtdQbAn lY+3v21Yt6zLG0aDaUqjHdYuTK1sWte2TeMT7548yC6+EdPd9XBK0dTT/aRv oKJZ/nBgtK6j83GnvOhdY15d+bm6PFntlYjn2Ueq7iS9lz/TafpNxkmTRTGp 7x9TvVfph3Rmld6q+/zPt7K2Gr7Mp9swaN4xP39XcwgMOgwngAiOYBzT4V/7 PRwC8aDgs/0E96J8Hx4PLIsPeXYmvDItpj7r5MvM42XxgYkePDKABqOQCKoI JUxFe91GOMeAcAx7OM4ODkAItkOeirWHoKFQMgIpIhDEOJwniegREO6VVuJ5 +YX35XqPnCq380+c4gvowSlYFx82lRYt4MZIeN48QiAbn+7r/CIlIjdaIuXi j/s43TkXdDcl0ptHZzOJx09HnUyWGbdM3/d+/Nr7tffv+r239/n3l43d5aVN nWFFVZ535m6yT3v9pabqjP7eR3J58fikvP3dk5aaCw2Pkl49TKi8HvnoYvjz ovTezmq9tn/ROL64OKmbH9KaJoyrOsuWcWnbbNowrX/+WPLmqeNJ74K2pyvf N1JuZ/33gUMQgA2liUB49j5WICgSDPGhAWckjue8HTP8nG9GepaeDq8+E/E8 LaY0OfL+SWmClysJt9/KBAJoIE4wTJQAdvS3x7JACII9AoCRXagIDAYEtoUh Awv4s7jeAMGTQAyMSPBKKXVLe+R6rtjxTCE34S7reC495Bxtf9qDS5rU/WFy xO3EIzcjxeVJYf13Ul9fOVGUEPgwNfLNvbNPrxw7GSw4kxRe9aqkqqMmsShT dutM4v3M7Ge5BW9Lmkaa9Bblzs+tza+b619WZmcGCjMiHpz3qX94urHmoryt qH/4ZWdn2bNb0S/vx1fmHyu+El5fnTcy3qqcblZMNM3OvFPNtPd0VI5/kKv1 wzrTpGFVu7Rl+br3rUPVb+9JEKWEGX5uuUk9/zh4CIznwVneUBJ3v50EAqei MUFcahiX4k5AOWPAPmRkogf7Yoggkk8N4BBOerDDRTwCDg3GsWFUTzDBCUQV OJAldlg2CEG0R+Ax7ID/A+WgPlI= "], {{0, 133}, {100, 0}}, {0, 255}, ColorFunction->RGBColor], BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True], Selectable->False], DefaultBaseStyle->"ImageGraphics", ImageSize->{66.66666666666325, Automatic}, ImageSizeRaw->{100, 133}, PlotRange->{{0, 100}, {0, 133}}], "]"}]], "Input", CellChangeTimes->{{3.7560807916450987`*^9, 3.756080793611037*^9}}, CellLabel->"In[1]:=", CellID->43203752], Cell[BoxData[ InterpretationBox[ PanelBox[ GraphicsBox[ TagBox[RasterBox[CompressedData[" 1:eJwkumd0G2earTvr3D/35/117lkz021LJJFzFaqQKiEVUMg5Z4AgwJxzzlGi JCZJVE4MyjlZVrIsyQqWLNlyjt1u22272x3n9jl9P/aAH7FALi0K3Njvfp9d 4KZ0rbv8f/zbv/1b4/8N7typVqqhIdXu+X/AF76axkK+Jpc11zTl8rkGRfr/ At8cBp9Z8LnxmPEEtDa30uiUUTYR6VAYHDa3Ox72RgLekNfndzudVtptoV1W M2NzE/YA5M6LvHU8Vy3LUcumM0IqgmA2LaGzGEi31RBym1N+ayFkb4g4a8L2 iF3vMFv1ZgeutxostNtvSyRDmVQoE/WEnSY/TXkotYtU2zGlTg4jMrGAx+Gx 2QKxSKxQKA00ZnWTrpDOG8FtHrWRkWsIOYqiMolKJjEqICepCJvIlFUXN1Mh o8aEQQSO68x2eywXae2tnplvWjrQuOtI865jLbsOt+4+2nXg1NDaxcHj54dO XOhdPd535FTX3tXOXUfaFw80bl+unllI9Iy7U1WkwcITC0tZpVwuVyaR6HDM YjGbLCYDrbd4vEaHV2Nyw5RDSjhQrYW22mORQCrqTYXdUb/D76C9QCuLWc9Y lbaA0JXjeurZrnqWq45rzvEIp0Stx3GC0RNORht2mNM+Ju8x1XtttW5L3Ky1 GYx6s5U00YzD5gt644lgJuZP+hxBi8GrIzykxkOqbZhCJ4cQiUjI4/J5PJ5Q KEaVMKVX0HbcEdL7olp3CKPtKkKHIigikSgkIh0iNStlTgwN6TVhI+ahUBMG EzhGGMzmcCbU2FWY2Na6+3DHgeMd+9bb9612HV7rOXx8YPXU4Pq5ofVzfasn eo8c79p/tHP5cNvSgea5PXVbd6Z6xpzpKo3WzBeLS1llLDZbLBJplAq7zebx +50ej8PrMTu9mMmJaO0y3ALhRr3JGgz5MnF/NuJOBZ1Rt9nH6M0mRm1ySywp rqua7WtmeRtZ7mq2KcYlHEKVTqFS0YTGbTSEreaUg8nb6SobXbTSMSNlN+j1 JrOWoZ0eWzjiyaQC2Ygn5rJ5acpJYS5M7SZUNhzVwjJEJBRy+Xy+gC+QiBUa iDSozC7CGdF6EoQzRJidGpJWIggwlUoq0sISGpFZVXIgl5dSeiiFUQXhmAbT 03p/wlvTmh/b2rR0sPvgqZ7Dp7qOHu8+dqLn6PHeo8f7V04Orp7p2xBqpXPv kY49h1uW9jXv2FM3s5TsHnFmqgmDnS+WlLHK2BwOeDYKOWyxWAPRuDccs7o9 ZpcHtzgQnUVOMrCG1hoZp8sWD7nLY/502Bt2ml0m8Pva5OaQgMmxnfUcbwvb 21zmqOSYomzSwQMDpFBpVQo7QbqNVMSkS5r0GSOZoDQ+irAaDHqj0WClfQFn Iu7Ppf2ZkDNkN7sMpA1X2TVKJ662ahRamRRoJQJPji8UyhCZWotoGQ3jodxh nS+mdUZJi0dNGjWoCpdJMJmYhKRGBGIUcotSbscUVg2ilUvVqAbTmilnyFVs zgzNNM0DrU73HTvXs7LWuwKEAnKt9xxa6zm43n3gaMeeQ+279rcu7mncsath 267qqflk14g9WYkbHFyRqKSstIzN4vD4cljOWB2BWMYfSwOhGI+PYhwqgwUh zUArUmtwO8zxgCsX9adDnqDdZDMbMKNVxgQFtnKuu5nraWS7a0vtBTYdZuEW HopBckSJIiYcc1BYwEBETVTcSIW1mEdHmo0GrcHA2JlQ2JOO+zNxbzxg94P0 ojBaCTMqxIYpTUqEgmFEKhGKxTyJTICoYIJWm1yYzU95wnpvlLIH1UarmtRp FEq1RIxJRbhEpIWkBkRmRCFaARtRGQFJFYhGSdCkzW/N1MR7Jmq37m7fs9K/ cr5/9VTPkfXuwyc7Dhzr3H+sbffh1sV9zXPLDbNLDbOL9VsWa6YWimOz0dY+ WyxPGJxAq82sEmAsNk+AKNRmp88XL/fGcyaPF2hlsDtx2qzS6hGMwAnCYdbH /c5cxJcJekJum8lEo3qLyBQQ2ICvKlmOujJ7ZQmTKdN6OQqDSKaQSoEVIFKB WHCVT4+HaDJEbxgsyBjcNqvVbnW6bdGIKxXzJELOoMfiNOnMpFqPyhilHLiL wcAYo4gclsGoBFGJ1QSsN6sZD2bzEXYfaQVxalNojUoNAUMQLOKrhHylkKeR CAlIRMklWrlEh0IaSAohSkijwxg3HauItA2Vj87Wze1p37vafeBE134QXGst u480L+1rmFuu27pUNbm9any2anxbcXRLcWRrcXhrqLGTCaY0FMMViTezwBBy 2XwRqiFN7pAnU/Skixav3+rzmd1ug5WhaANGEhRBmPVk0GXNhfzZoMfvthlo E0xaBHofxxRnMRG2McM2JIFQfNwqUeIoLFfIYDUEUSgMtPLq8KBJG7YYYlZT 2EIHndaA2xHyOlNRVyriTABTORgbyHstbtLIwezYCaUFU9AaFYljKg2B4JRS R2Nmm97uNboDRqePsroUpBFS4RJIKRSJRDyOjM+B+BxEyFOKeGAecViKIxAq lYikkFSJKfUWyp/y1nTG+6cqJufrduxt2Xm4bdfRlqVDTXN7a7cuVk1tK4xu Kx+aKh8YKx8Yzw9OVAyNl/ePB+pazf64ijCyheJNZZzNLC5YyXIVSYOXt7za W15r9fodwaDV57U47QazidJqKQLXk5jbaox5nHGf0+Oy6kwWGWnjEK4yfaBU F2BRHrD+IJLWaPV6HckQaiuOMRjGEBqnnvCbdVE7HXeYY3YmZjPFneaEx5bw ORJBeyLsiAfBf+z0u1wOq9lm1jr0mItSOwiF04hbGJPBbDFabDan1+n2uvx+ TzDkcPtpq0OBUSIZwhfJQIKwuRwelyXksqRctkLEB6OHI1I1AsFiCV8kESEq hDJT7rir2BrqHE0PzxanFuu2L9dt3w1yqW5mvnJsa3F0qmJoOjcwnu4dBgco lukdyXQPB2paaH8cwXUsofj10rJNZWzgK0iJG10hd7bWlas1Ob12f9AR8Fud DqOJBr5Sq5WYGjVqNV6rye+0OGy0FmhF2YFWJVovsBMPN0M4TRt0Xqs+7qQz biZuN4ZM2qBVH7EbY04m7bFkvNa0yxx3GJOAuHz2uNeaCjpScXc2G83ms5lC IVORz6RjCY8jyhjCZirsNgeCfn8kEohEo/F4NBaOBj0xv8vvtDO0SaXCBUAo Lp/F4XC4PB6HI+SyZRtaCShERqJSzb+0ArAhgBUQZlQzPjpW9Df1Rbsm0kOz hcn54sxC7cxi1ehsfniyYmgy1zeWBfr0DKf7RrIDY9me8VzPeKi21RiII5SR JZC8Xlq6CexCnlCMqPTOqCNR40hVMm6vxe9zBLwWl0NnotUEjigVcgRWoTCj o9yM0W4xGswMqnNwScdm0lZGWESYUUMZvFamGHC2pLytKU9D2FHwbpBVxmdN ++xpvzXqMIYs2pQXDLIn43dl/I5c2F2Ri1Q3FFv6e9vHx7qnpjoGOupqyivT 0fKYN5+OFGuKhdqaQk1NRWVFJhvO+G0Zl9ln1pkpjQqWi4QSLk/AYfP5XJ6I z4VEfFTMVwN4QGU6FUSgkBxMp0DAksj4sEZKMBpXjMnW+5sGop1j2cEt5SPb KkZmK4a2lA9Olw9MZvtGM90jue7RXNdornss2zkKTrS+wxxOoZSJI4KAqYBW pTwBV4aoTC5LtALEvsHuYNxuq8dtcTq1RlqJYTIEFUtlkEyqIzQus8FpMZrN No3eJaQcZZiZqzFLcTOFG0OMuRjytKYDbUlfY8RZH3HVJn3FpCcXdSQD9qjf nkmGqguZ2kK2kI7l4r7yuKepqdA+0je4MDd+9NDk2srI7oWesb6u/vb2zuaW xvrW/u6O4cG2/r6G1vrqmnR5wpcOWD1m0qBBQBZJBCIhXyjgCUQ8HiQWqGAx icooRGpQQzSOUAoYlYoFAmEpX1gmhARKCjLYcXfCVt7oq++Jd42leqeyA1sy gzO5/qls71iyazjbM5ZtH041dEeqWyJ1LdGG9kCxgQmlEMrEFsGbWNzXWewS Lp8rlcOUmfanzP40ZqApmtabzTrajGsNcpVGDClEYgSSygmNGixEr83stNu0 Jjuks3JwE09pFKsMKiXu0mIxK51xmjJ2Q85tynsZoFVVNpCJulMpX2VdVXt/ f+fwUEd/d0trQ01lqpALNnXWDM/Pzh09tvPSpeUbN+ZOnNp6+PD47sW+2cne ybHBLTMjC3ODs1u6xobbBvvr2psrqguJZNjpsFC4BhFLpQIhQHsgCSIVUihk 0qA0hpgwhNagOqCVTArgrIwjKOGKSsUwHyURgxNzRU2pGiBXpH0k0TWR6Z1K 944nOofiXUPJrqFEY48PBFGi4A6Xu8JZWyijdflh0sgSw6+x2K+xyjazOaWA Y1QkxnjAJMJqtYIglAQB7uVqXAyr+FIFX6oWwRpcjbnM+ojbGfA4aatZobcI cJqDaPkwLpcrGEzhpjC3DvPTeNSmT7nMVXHgKx/oeuXV6ebBvoEdS2O794zu XOgfHWyoztQUku2D7ZP7lnaeO3vk9p2j997e/8b1pQvndpw8MX5gz/DuhYk9 u6f27p1a3j22c2l4YbFvy7b2kcmGrt5CfX0wHgZMC1atXCxSy2UEIlMKeCiX rZFyNTKQWixSLpWLhbyNJBNs5vBfYwtKBHIOjEtIK+6IMelaf313uKk/0jIQ ax0IN/UFG3s8tW3ebJ09mNZb3Fo9oyNNhN6CUkapimCJpa+XsTaxSks4HBYw qxxRkAbMYJOgKKRSyZRKmVIlQRRCSMmHVDxILURwtYawm3RhNxP2OGw2BjMY RBotT05wZSoZJNfJZSYFDHjSSSljNn3azRSS/mIikI36cnUVjROj/bv2Th05 NnXw0PDEWC7uTcc83UMdI3u27bp4YfXe/bX794/cubP3+tWdFy5sP3F82+qx 2WNHpg8emNq7Z3zn0sTizunF3SNzu/qmtrUPjNS0tiRTcbvJoEMgowIh5bJc 1Ltr+9C1y4fevn18oDMlYm2SicF0Clgc/iY299dlnNc5ohIBxIExCWHRWMN0 OG/N1DnzLc5MkyPdaI9VWYJZozumZewaAkMBcoiFcrEMtAeBGN7M421iszaz ywA1iMRCGJJolCiF4TyplC+TCSBIjCACCOFLUK5EwZOqpHJgK1Ck9QGHIey2 eGw2gN9SDSlAMJ5cKYMQQiYDLcOkQpw6ddSuLw/Yi6lALgyWlzOVz1T3DnRs 2T4yv9g/NVVZnWlvSV8+f/CzTx/cvH/mzM0r63fvrj24t/bWW0fv3Fl+4/ri hQvzp09tW1/dcujg6NJC9/RU5+ho7/hE3+xsz9R0W/9wU0dnoVgRCXrtekoH Cw/PDf7ty9tfndny2emt//XN47/8/Kwiay8pKeXzpaXsDa1eZ3NfY/NfBx7j STkyTKikFXoPYYuRzjhhC1HWAGEFFdiBG2xaUk+iSrVUKudzJFyOiMtlcUBS sTaxy0o5LL6Ai8IyrRrVqVGtRsURi7mgWUhlfCnMlcA8CcITo3yJQgSsBrBM q3NbdCEXA7aegaYRUi9WaEEHAVppZLAOltEqxG0kY25TZcJblQqkwFK1Gz0B b6RQXdk50NzR19BStX5uzw+/efLPf/7jn//86z/+9xd///t3D1/eO3v/7trb bx27e2vfnZvL168tnDszs3oUmKp7ZrK+oyNXno0l4slMJl9ZXVXfXKypSyQT kZDXYaJ3jdWeaAs/W2h72hM66FF8fefwHz+7+8PHt2k9srkU/KYCsMI2byQz /7Uy3q/L+CV8mCVWciFcqtRLNQaJWgurtZAaR9SYQU2ZlIQRRrQSiRoMNY8r AejG44LRK+WAH8WWANYFlVOLuQ0kQ2o4YilXLP3XvexfB8gF86UISHgUVesI rROAk4MO2EyM2YTpTDLcKFThUhQQDURAEpBaQYsxG3BUp4L5qCfkMrkA5lto uz8azdXkqor37l/+5fPL756b+c2LG399efEPz0//7cX1/+/r+7/8+dtLj24f vnVr3xtXd106P3/m1PSxQ0NLO1oHuvMVOa/FpFWgWqXSrDf4ff5gMOQDy9ps rIjYV3ozC0X7tBu92eA/nWHe2lb7+bmt/+fTt08fntlU8is2D9QTLqBuIBQ4 m9iC11mCTRsGA/tRXCaWgCziiGRCsQyVySkUtSvkLoXciUJ2BCJBa+eBDsgD WpWw2AB6pRIBgUB2SuOjKY+O+G+tuCIpXwysJeNKJBtHLJGAPowoSTVm1ZF+ Kx12WOyMhaJtsBYwg16q0qIoolXCPjOV9FqBSpXxQCrkDHitDvDvXHaLM+D0 xy9cPv35lcVbixX/+OcvP335zs2+0Hql6XBAcbsz+cnWtq9ur5568HDnuXPb 1o9OHDk4snO+c3SgrqkmDX4Qo9Mq5RpYAl4SAMdGnd5sMIDy1ZVy7Kj1bs+7 55LWYUpSh7JO98Q+WRv46enp339xz2DE/+PXpWUc3msl7NdZvA2JuMLNHMFr Zdx/PRaUcnmgEYNMY3P5Er5QC0FelTxAKIKkwqWEdFKxXMADGbWZzQa+4vJ5 wFc4JLXhSpcOc1IYEIovlgrAkUhFEqlYJJEAupLIYBkEkBRXqWgS95jpoN3m sjsNFrfS5EB0VlhjJAjcSWsBkOeiroqEtyLujwN5fHaPz5vIVZhc/p6h/h8/ ufHejsJbc/m39gy+fHxxMkOPu+XDNmSLXbGN4DzZ1vDHTx/sP3lscOdc78xo 63BrS2d9Q31FeSYcD7k8dtpAqDAlooRhTIXhGKnCsK0V/qWosTdAbrHjXTpp QLJprT34fLHhd1d3//Xbx/dvrwkh3r+/tulf8c7ezOX/uoT1WgkL2KyMzWdz +BsXEjl8ALQsNhc4SCOROFCFH4wGqXSpEYNMCvP5LC4PoAIQXMDnA74Fdd2s QBg1atMo2QB3JeAmlYnFqFRGQigFoTpIAZBUJYcxBaLVKEHVdVssHofL7Azg jpCa8eKMi7HbI15HJuQC1L3BjWFP2O/w+ZzBUMQXjIUz0Ttnlp/MFi7UMjvc ymGdOKYW2KWlPQzc50KmMtpTLb4Xs63frUyd2DXSOdDb3ppvaUx0NWU66rNN 1anK8kg87HY7zUY9qVYqIBh0GBQgQ7cTb5aUJVFJSlRK/fp/DXmovRn9/jD5 Zm/mi8sH/vGbd65d21/KY/+vX7/2+kbCs3+1ueS1klIwUFw2yCK+TMADVUjE BxHOZ7M5ADIwscQEyWwoZEFgDUA4vpANHMjml260Ax4qFuOQTA+WL7qx9NlC IU8ilkkAUYmNkMyOIk4l6lKgJrmckMtBfyfBCiAxi8VmdfhM7jDhilLuiCUc CybjuWS4IuEvTwTiYZffbfG6LOGQJxEH6WJfPzl3faRyu0M+ZBB24+xmgpPF RWFMTvFZcYS1nNLd708eC2nX2pJDXdV11dnGfLA16+/IBdoroi2FeEMxXpGJ BIMeo9mAKpV8kDMCEYIopkO6boxFlf6nRyHYX2W/2epb9GiGLfC0HX20rfU3 t/f89du79+6sCEXc1zaDyCr7dcnm10s2l5aV8tksVCQkZBJKKlOKZQKBiANq OIst5HJgPk8h5CnEYqFQzOELS9mA0ARlXL5YwEPEEgz0F7lMj24sfY4QyCyE xGIKglwKOKBGI4QqiCkcSrkWluGwTIXIlRo1qad1NrfeE9aGE9ZsRbCyKldb rAINOB1MhJ0eEOkOk9/viMc9hXzwrXcuffbG/hEdr98q6zMIR0yyXWnrsebE 2d7M+mBhKmS8Vh3cahGfbAo8Wt9aVYjHwta8z9zgtTT6rQ0BW33YWZn0ZJMB j8dF6HUQioL8LAWvs0xS79BOulQ1JuGuqsDxase+ML7oJ7bHDAsZ5mhz9Lf3 jn777vo/f3d/eanz33/1a1DoXi/dvKm0pIRVIuGyMKmYVsgZFCGlYrFIwOHz WCyQ4Gw+QAUeV8AH0yko5QlLOMJSjgDMqFDAh6XQhq8giV4O62FoI6wARYjE ZlQRIdQpLZXSkgmSCGBqsxwipNCG9ZUqDaXHrDbcF7TU1oZ7uvM9vY29XW2t DeXpUMDNuBxGl5MBYRWL+a69eeLHF2+uFd1jHvVkiBizy4ftyFSA2JEwHK51 X+6I7ovgU3ZtPSHcV2E4t709GXL6rFSCIcst2oJdXwlQzaKNOw1hv83lspE6 SipHWAJxCYBMngjsmyYHuS1iHA8QPYx0xAZtcaEzAfxoU3C1OXx+qva3bx/9 /tH6d5+c9vvx//nv/1nCLt1ctrH/ESGPgqRGdOMdDT0sQkUCcGNzOByQYlyu mMcX8PhcYCquqGTjCIGvuHy+RCxB//syrEwMPClDMaFIoBZJLLA8pFElCDyG 43Ec96uVDATjYgkklQKeR0m9wmbTpdLB3uHcxPb6ufm+pYXW3s5EMuL3Aqo3 MIzW4dSdOb3vmycXVpr9u2O6y52JgxXWSZcShPmkXz0TVG8NqLZ70UmLpBVn D9rlg3Eb2As+j8lvxP61jJRxrTqlV6cNWNRMeaw6m1mn12vlqJLNFwGt2KCa QTCJKeutumGXatCvHvdpADyM2NHpAL6/xrNU6719oO/7l6d++fDCwwtb5RDv P17fDKwjEnA1ErD1xEZEYkZlOkiiAkMo2HgbhM/ZMJVUwJcIBHyBqIwrfp0n fI0rLOEK2Dw++JAKAc8LUTFfIRYqcAMEnCbe0MqvUoY06qBKHcWwgEplkf4r 7sB+lCtRrUnjCdhr6kMDk9mJbc1Lyx07l8vbmoKxqNvrtlj1RhrffWDLxw/X z49k95TTFzvil1pCu7PGKbd62CQbc4nHUvrBrHm0nBnOMRM+sj/rrGqoiidA f9I7N1Y27McVIUwRxtAYqYoaND6LFpCDUadVqDCeSLbxrqEEViqUajWuJzQx oyak0zhxxI3DMVrd5SG2JA3b8va9baGPri98enPvz89PHJlr4rJKuGweJOSR Er4eBlpJDXIIB/nM5wp4HOCljVCSiJQSCSICgSVm8UWv88Wb+KIyvogNvLYh qUDM58mEfLlQhJA0AiO4WGqUSu0KhVetChNEUqfzq1V6qQwRi8VSiUSp1oCi Hc14mjtiQ5OZ0S2Zkalkz5CvstKZiFvdXhJXzWzre/Xo5Lmt1XvrHee6Ypf7 UvNRHdBk0AI3G6GMxxROppLVdRXtHbU9PY3d3VWd7dHK8qDPYadxRiV3KGGA On4N6lcjQQ0SIhQBE+kyG2gtAbJdKleIIbkcUeIYRhEYRRJqpUopl2vkciOu 9ln0eYexO2iaTFmWGvxvLDa9ujz3+a3lX14e3zWYk/BLEAmPlAoouRiXixEp sBAYMBZgBj6HK+HzFRIhCTY+oCQJxJHISqRwmUTOFsNskYQn3JhVkVAgFQog oQimaAV4sQRinUTCyMFzVjpR1I2gdgQhJRI5kAo4Vqu3RSq8lc3+9u5o32iw e9Bd32arqLKXF2zprEpP9fQ3fPTsyo1dXYe7Iif7k1eHcweqLEtp8xCN1umF UY/Ll6uP1NQn65tzrR21/UO1fUMVrW3BXMpmNelVcq1MTEMiRiq0QmInAnkA 4qoRF6Gw6DQ6QqNRq5QqFQKepVJJgi1DqAlMoUYhtVxGonIL8BhjqA646v3W jrBxLGs52p94cWLqs2tz390/9P2DQwPVbpTDwaQCtUwEi3lCAJscsADLQFbx uTywEcH3KTlMyFFErpAoMbYaL1VqSuRoiQxmyyQcIdBKKAE5LxIpaZsSpwDB kBKRDUHdao1XrQ6qNQ4U1cogdIPfYYM3mGgZSPaMhLoHvM2d5nwR80cwX0gf Tigt1vr2yhfPzz1cnzw7Wjw/Xjw/lNtf6dhbYZsJ6Wp00qiVCoQToXxtor4x 29JR7O5rGBqtB1o1tYSSCRNtIBGIkkr0UpFRIjTJxDZYapdvAA8DkAZH9Tiq xdQkriEwDanW6HCcwtQaFFbCUjUsI1C5CVOFDVTBZa4LWKodVG+cWWrw3F7q fHFy8rNr8z88XPns+lJrwiJhlcAgkABmcVilLNbmspJS7gaay0V8NSQFdEQi qEKNSUgdx0iX6A2lBMlWY1wE5otFYiEfEgvlEjHu9lNWB05qjCjsUal8amUQ 14RxzKlQ0AiigiFMZ3BXVOXHZiq3LcQHx5h8Ue0JQVa70uaUmEz59uqXz668 d3Xh2tb6M33Zq6PFlZbgznJmR45ptqJhI+rzWIORaDBfDYSq7B2sGx5uGpto Hp0otraFknHQMUHhomRSo0zCIBsS2RAZ0IqRSy1KxEKobHrcZqAsepLRkhad zqgFtgKmglVymQqWkYCoMZVfh8eNZMZExnTqOo9hS4XtwnTtk5XhD85MfXvv 4I9Pjzy/vsWilb3+6/8EoAVUer2sZFNZSQkwF4cDiwQamUSLykngW51ObDXx 3E6ux813OLgmE5vCRCpQX2QKWKySQ0wq5wwmHYzZpyPiOiqpxZM6MkrhdlSu Q2BcrTK7/L5CXbJvsHLbjnj/sCGdR91+1OkUkdpgbeHFq9vv31t9sDJyfVv9 lbHKM53JY43+xSzT7yeKOnnWqIk7zBFwy1eVt3bXDQ63TU93b9vWuWW2aWgo WSzYHTYdpiA3ZlBqVcjsSsilQhwI5FChoKt6TNqwk4l67CGXxWuhnbTepMUJ lRw8bSAXrpDrVQpGo3KSKj+p9GOIQyWL65QjGfuRgeyDI4PPV0a+urHw7cOD vzxbPb27VSQq/c/XS15nlb5etvm10s2bWWX/3WI0UjCDUhJFEIMe9rqFsSg3 HuOFAhyXk21lBCajnCRRjRJVocHapmCiEHQ6klZjpdWUp7U5Wpc2am1qdKO6 anFTMGrPVrqamsL9fc6mVm0iq/L5xIyJiXgfvHv1g/tr756avrOn5eZc042Z 2lNd8SMN3i1RopFBq42aSgbPuCyJWCxZqCt29tQPDbTPTA7sXBhYXGgeHcvW 19k8Li2uBABjBFohYPokVpnIrka9tC5oN6UCrkIqUpmJ5uOBmM/msRjMlEar RjQIjCEwicK0WmHHVS5M6cZQjwZxaeRuhaTBbdjbnb653Pl8dfz90+Nf3975 w8OjPz85NjeS+4/Nr/+qpBQIBaxVwmGBFoMIga/EJCRWKyDEaET8AXEmLcxm +fEYNxjg+Nxcpx2MD2TUS7R4rKElkc1URFw1gJmdTBWjL2e0aVrrIjWECsFo vT4aN5dX6Is5R1sD01hH54uEPwRbTedunPzu5bXnZ7c+WR24s7Pl1lwTSKrV luBy3tTrVlUbVXUMVmUhs25bJp6qqG2q7R9smpjo3DozuHPnxL59nVu35Jqb LD6vBlMoZaKNy0ecUh0kclFqr1nnYQypoLsyE2uqLm+tr6gqj6UAstoMFj2m x5XAURtaKeUmXOmg1C5C6cZRL65wqWE7KglrkbmWyPkdDY9Xx16emfr8+tzv 3j74+/vHvn5zsaLc9P/+6t9fLy0BMF/GZoGCgwj5aokQA/tLJVcadLDPK0in hLmsMJPiJaLsaJgXCgqBXDa7wExnKvON+WhnzN7stTQ7zPUOQ9GiyxiogJ6y GnUkYyYDIX2+3NxU6+7p8Pb0+5q7dPHE7vWdv3z/4su31p+fnXl0rO/5yvBb S22n+1MH63zjEapIK3KkolKP5s1Exu3IJTJVTW3NI+NtM1t7tu8YXV4eXd7T MbM129puCYYUGhXYTSqltLWtfN++sdX1bfNbO2a2dbTURNprMy11hcaaTG0h kYt7w27GYdYatRqg1Ya1lHKdSs4QqJNSugjUhaF2FeRQyCxyQXeSObOt4fbB vpfnZr+8sfO7tw/++Gj954eHHp7swzDxr17bzOVsXG6QALgSCZRigUoiRlFQ YwiJ2yFMJ8XlGV4qzk0muPEoLxzmBfxct5PntKVCrraIpdtPd/lN7V66xW1o dOmLjDZK69w2k87GUMGQs7klOTNVtbhYPb+cGZvecnTvdz999M3LNz5+Y8+L k2PPj488Wxm6Plt7si+5p9peZwccC8dUUAKDY0Ys6XJmE+l8fVPz0Fj37OzQ wsLIzp19c4sNo1Px+hYmEFGSeCLtmpionp+sPLZvYH4sv2e++fLlxen+5Mxw Yai3sq0xX1+IV6aDqX9dqLHSlB7/17UaBNLIpVqFzKSGzQqIUcI2FWJXQGap LG7Q7B3OXdnV8mh19PPri98/PPTDOys/P135+fGBbf0ZNrsU0Dgk4iL/AnJE zAO1GoZhMGV8G8OLRoBQPKBSLMaJhNhBP9vvYfk9fKejwmFu9xmHfKapqH0q 4RiLWYejTLNHnzBqHWaD1mq2ZnLpsfG6/Qf6Tp7qOX5h8uThL759/vtvnn70 5r5nayPvHxt690jf3eXW89P5td7QVMoMMscsE/s2OBz16rCg1RqJxTMNzfV9 g92z20d3LQ4uzrXObMkMjHjrG1zpWDzhmRyqPDhX31XjrM86GnLW4f7s8lzd se0N4+2Ruenqqb5iQ3mwOhPOxtxRv9VjNZi1mEYJw5AIgUQqQJioRKeQGRWw EYHojQ4rxiFBX6Xz7I6a2/t6Xp7Z+vWtPd89Wfnp5cmf3l395Pq2uJ+UiHlq sNqkQqVUgIh4cpFACkuFmIprMrA9blY4yAmHWEEPK+Dj+L1sn4cDjsNWYKgu j2E6aFtK+nbnAstp/2LS0+enkwbSTJE6i8ldKOYmZ1oPr4xfujJ14cKjV49/ +eH9z+4f/uDM2KsTY08P9LyxvfrsZPbMdPZgdzhhUJICrhkS2wGK46hDh7nM Fn80Cii0tnegc3y0f8dM9/at1WOjgeYmf21qbKZ6qiNWk7dUxc1JD+W3qpwG uc2I1Bcdw/XemVrnYKW7NWPJ+rRVSV91JpCNusIuxmIgMEAMkIAn5UpkQlQm 1sAyHJQXMJiwDJUKQXPJuOljI/nri60Pjw5+cm3h+6erP786+/N7p354uGd1 usJAwQQqJRCpQiyQCwCR8sWQhKdEWVqSwzBsh7PU5SxzO1leZ5nXxfa4OB43 x+WotWv7vPTWsG13yrc/6z9UHtqb9U8ELRlaSyFy3EA5yvOZienWw2uD6xdW 7978/rtXn7199MMz45+cnXrv2NBbC43XZgqXZysvbS9sqffr5BJSLDDJJTYN DEpK0GEOuryhRDJWXVnX1dU9Mtg7PdY8NphtbgxWJLsma/ZsL0w1WFurXdVZ RqsQttaFCwkm7iQiFixrQqfy5pognbKqKkNGlxapTniLyUDc77CbAZOiYljE lnJ5Er5YIpRJRbBMLJdLEbkMPC4TcQk1tLXevzaWf3Ox+cX5ma/u7v3DyzM/ Pj/xw+P9H50drM7QGlhAQGJEwJUJQHcGrU/EgqEyjZql17NM5lKGKbFbWE5b qcNa6rSxXXaOw97tNU5GbIsJ54Gc93DedzDr3p12jgSYrJGiYEhNYZZUMtY/ VLN9cezYysffPPvy0ZHnx4ffPz787HDP3fn6m9tqbi/U35irvbClUB+zGxBU B4lBS7VhirjLlggFs+nyqua22oH+5qHB7rGh3rGBus6m+vaq+YX2YysDN0+M 7RlM7xjJXVobbMk7m/LO1eWuHf2ZkUr/QNHNoHwXKbcpBY1xY8qiCpv1NZlo JuBy2I0EjUsphKOWcpRSLirhySVCRAqOSAGBuWKpxRxcXJ2xLHeFz89UPTjU 99H5rd89PPLLi9PfP13/6Z3Dlxbq9SoBKmDLhVywWfg8LkcsKIVlJQp0M64p 0ZEleqqU1rMYms2Yy6xMqZVhMeYBn3k+5T2QDxwp+I8VfIdzrr0Z96CXrjTr LBqVVqe1xkKRppZ8/9jNx2989/G1986MPz82+ORg19352lvbKm9sqby5o+bG bPXx3mQuHfTY7IxGSUFSk1oZsFrCnkAylavp7O6a2T69e9/2owdm9i50Tw5s mes4uFC9tSe8ZzQzVGlvztKLw8n50dREdzTKoFGzLEZL6+M6RsEJg2VqlA8k DM1BvUcLN1bFMnGfy2vRO/SonRLaCaGF4BpVPIOSr0UFFCo2qMUWTOIk+D6d LWna3uDY3xE6N55/Z2/nx5e3/fR05ccXp394/9QPD5ZaKkxc1iapkC3gsTig SIsEJZB0MyLfrFaWUlgphZfoiFJaV0Yby0wmltlUZtR3uegdUe++8sBqTWy9 OrJWGd6f8Yz66HqL3g8G0Gr3xFOOfGHm0PIXH9x8dGzs3UPdj/d33J2rub2t 8s0thTdm8lenyq+MZ+a6ywsdzW6vW6tWqqUi0NwtWgpIF02kKptaWocnth44 cvjapbU3rx6+dGJuqm682TXXG9o5nMg7NS6NcKDa1Zymh1u8GYcqadcsjeZG 6n2NcVOQ4Mc0vHq7pj5MMypOyoUXMkF/xMOE7UTMBifBcYjCtNCvF3l1Up8R iViVWY+6OqhujGnqwq2Vtp01tv3t/isT5Q/3d766tPX752s/fnDyl1fHr+xt V8nK+NwyIe9fb1QI+Ztl4s0ovFmFluKqMhIHcpXqSSBRGW0o1Ws3E1iVUdvv MO0IevZkggdywYMp/+6wc8ija7Dq44wxHAj5slXJnvbn799+dnHh9vaqt3ZU 3pqtuDlTcWMqf2M6f30yd3UidXooObV7rnZ2xur3KpSwUsrXozAI9rDTnA76 aooVrQN9E/uOHbp6/frz907dvTbaG1sYDC8MRMYbnRkrgvN/nXPovLgs40CK HqzSgU1WuadqvK0RKm0UFmyKtBnx62QGmMegnNq0L5GNuDJefcGrqAugzRGo zi+tdMmrPEi1H29NmwZrLOONzFSzYarR0xYfLZj3tXrODiXv7Wx4utr/xc2F Pzxf//39gz/fXGpLm0pZpUIRlyfgckW8UkhcogBaISWYkoVjpQRWqiVK9bpS o65ES2zGFEEFmiGQegPZaTUM2ulhl3nIbe526BrsxnKXMxmPRmoq7z5849Pb x+7uar4zW3VnW9Ub46k3xtLXRtK3pireGM9dHYwcnWndc+16y8xWu9+tUcG0 Co4YsEqPqS1sb/Uz9XFnW1PF2I5thy5fffP9j+5/9tGeI1PjHf6RBmd7Wld0 KMww36GW+gjIJmfHKEkezJoZbbYresJUiw+LqvlFuypqVGC8UjcOFQKWVDbo Lw8wNUGqPaHqSam6k2hXDO2KY71Z42itbbbTt2fYtXvAPN+mm6iMFF07qpzn gFaL9U8Od75Y7fvm4tRP95b/z/1966MZLg9otfGHSgKJsAwWl6BQiRotwZVl hIZF4WXAWlqqVEuySJyFK21SqR2SOOWSgALK46paI9FkM3Y4TE0eWz4aCCcz K2v7v3569u0jvfeWGu5sKd7bXnVtOHGuI3B1MHFzLPfmcOZcm3vlwNzS9Tdr BobdAaeBREM01Ra1bamOzDenpiv9XRGmKsS0NObmVg5fef7y5e9/unDvzYgV yvvRnnJzT9JcblNaIJ4N4dtk7AQFFXVIvxefimnHQ8RIkKqxadxqHoNwSSGL hrhRM5HPh315v6nKT7XFVb0pVX9G2ZfSDJWToxX0dINjod+/f8K9Z9A630aN V2qbYvU509E2963txacHO57sb31vqf7j5fYfDw/dmi6SqFgs4kvFArFUzJFL 2Up5qQYpJZQsUs3R4hwdCSiCRRECLQFRuEkqMUkktERilog9cjiGKQtmbaPb Uhf2RJPhmtbmDy7senq07+397Q931d+fr747W7g9XXF9IHFtIHF7NHelJ3K8 L3r2zpW9N242jo6FIj4LhaRt+uEK30JrcmdHBtwP5dxZCxWwa5sn+g++eePJ d9+dvXs9aYUHqp07uuIDWbotqIxTgoCGl6TEjTTS6VCOhDQHKs0HKpnhENES pZJmuYcQ6mUcUlwWMKorciFv2k0XPGRTEOtOqPrSyv6UaiCDjeR1kzXMbJN9 oc8612Xd2mAZrzJ3JsI5enul5fxw8sHOuqfLzXensufzpneqPDdHyq0Ay4RA JKFMJhLBYoES5uFqkZaE9FqYNkgMeoFex9eRcpNByxj0UpFJJrFAErtc5kbh EKYsN+saAvb6TCRXkc8U8/vaY/f3tF2bKb85nbk3W7wznX+8o+69xZanu1qe 7u14tK/56tHpi8/eO/LG9Y6ZKW/IS2OytIXsTtpH8t6JQnC6JtCdsGZpwopD uZryHSfX73z+6dUHd4te1XC5ebLSMRClunx4p0c9EqGmkrqlgnUupVtIUqda PWv19gGfpj9hrnPjjIRtkXJMMrZZJY2HncGI05F1a2sDmpaosjsBtAJHDeQa ypEjRWq0mhmv9E1UA/JwFL2V1b6Jgu1Ag/PeXOXbWyuu9gTO1VpPx8nTPXFa IVaIOKhMAEsFsEwgUUgRUqU36Ux2k8Vl0VpNcoNeTusou8XjsRthKQ2JrIjU iUBOFPZplGmTti7oqC9P5isKgfJ8TWXy1EgC7LtLfcGbo8nHO2pe7mr55vjY 796Y/+Gt5R8f7v/qzvLVa2sgt3tmJoN+p14uiunUNS661mVo9Bg6I0yzj87R uIOE05no9Mqh6++/uP/p+x1FR4dPM+DHx1zqAY9mJKhZyJBrbf7THUHg2JON 9ivdgat9sdEQkcP5eUpEcsrGA9p2BiUgocdmcDpMlrBZV3BjjQFlZ1TRFVX2 xNDeGNod1fQlTYNp70guPpQLNAS7xhv2LrRN1dl31jBXegOX2zwnq80XGh0X 6qxHW4I0LMIlPI2Yr5DwYSkfQaR6Sh1wM6moJxf3efx23EJrzEaDjYl4nW4D adHILZAQpJYVktgUUNBIFIP21opYc00+UygGUrnhGvfp7uDNseyL5eaPj/V8 dnzou8uzPz7Y/5dna39+vv6Xl2s/P12/d+P86OR0wGIywyKPWp7Q41kaz9Oq ClpZbSHzNOFVQ+WpyNSBvWfu3X36zWcjfVU9AfWOpHE+iM+HNdvj2HaP9Hi5 4UQdc7HFcbXFeaPTc2+2MF9Oh5ESg/C1qIL/sD0y6SOVUp6RVNNGXO/W0nE7 UeVRtAXRjjDSHlR1hojeON2fCg6lyoczqabg2GLHpWs7j+9uPDQQWiga9yc0 xxKaUxWGM7WW0/XMTM5kg0VWWGKSighQoqVcFSw2azUJn702HarLhYJhN1CJ MFCUkfIwhupcIuaxOBWwWSwCnZeBxX6tujJo7ypEOmvSmXTGE0llc6mlInOi zf32jupXh7u+XB/6/tLWn9458ucPz/39o4t//eD831+d+69XFz9/+3RPbUYj KHFq5H5MHlDLwxooScJFoyZvwGI4UluenNy5uPbGGw+/+PTI6b1DWXo6gm9x IfNexa4QttujOORVHk+QpwvGq62uxxPph1tyV7sDnU4lyd804tUc9cOTDiWG CNWgLyslRjNOBxldhUdd71E0+4nWgL03HhiIpQdTNYPZqobgtt1DL15curHS f26u5mCnb66o3wO0imMnc7pz1ZZTdUyzAw9p0BAh9yql9Ia7uGpQ0DA06jQW o+7KuCfgc2lpvYJQKzQKvRqdXZhu7aoDwOLCUFrKN8kE4KUrBmw9xVRHVTqf CydzuXxTT39VbGeWWG9x3ZrIvdjX+sWJ4e8uzf1h4/Ls8T8/P/W3987+/fmZ f3x44U+vzi50ZGlBmVUudKMyLypOkEgljRf0mpRO0VSZmdq5sHLlytUnj28+ f3Rka/tizrTVjW53wkse5bJbddCjPJfSvdHpfziRe2cq92Ai92SmfEvCYJFx l4vOc0XbznJLjCF766IeF0Vo5CYfTec9xiovUx8MdiSyQ9naoWx7f7a+OTQ2 WvP1lw+e3dxzcb5mfSC+XGeZS2PLMfWRiHo1ga9ndVuTdLVFV8VoK2msQqfw oWKdmK8W8QhI5DRq4l5zzMeAFqKgcL5KzpeJxGLe6XtX9509Mr2lryHrDxnU djXkJZU5t7k9F+6qirc3ZrsHuoeWliYXd+2o9+/KUavtzhtjqQc7ql/ubf/m 1Oh3Nxd+fnT0z09O/O3Zmb89O/33907989Mrl3Z0OSGOHeKHMTinV1UYsZxO lTCrG+srppeW1i5fvnDvztUnD/Zs75qIYksxfJ9fucur2hdQHo1oT2atF+vt bw3Enk0X7w7F3h6JHa+i54um272RZ23RLr/egwn6c7awATPgCovL4Mu5443h 8u5U7UCucyDf11/e25Fsawg+vb/20ePVmwe7zgwnDtZZ95RTexKqA1HFoRC6 ElMfSOCtPrLRpW/1GJttVIMZS2GwFRaoRWxUxDJgsMtC2u0UTmuBUCWQsASQ Kp9z//OXbz6/v3b6wJbRtsaUL2IlgzSWsuubEt6+qvjEYP3cru2HL144cfv6 keMHZ+pcu4va403O893+W5O5pwt1nxzp+ubqth/u7v/l0dpfn53+63tn//Ly 9D8/vfz+5T1VTson4xVoosJMJChFIWjp7Gndsrxn5dLFi2+9efHh3QvnT/T5 lG0G8bAROuTG9zvQNow/REn22GS77NKViOZ8QX+/O3BvIHp3tvxKLTNlkVNC TtaurHFgAQ1io5Rer7mqJtrWne3qz/cNFcZ7K8bb080F5/6d3Z+8vPDGwZbT Q6Gjzc7lgm5vBt+bAlohB32y1YhqNqQtWDUNTm2TS9fooOpoTY6Qu1GRRgLa dBmlkNp0aruZIHQYSLFNIu5mPmczu+z5bz96+PG71++cPbR/y2RHVVMGkIsx ZiWrA9aBYmx+snv91OrVh/ff/uDdN589Pn764EyteamcXKmznmz3XOmPvD1Z /vGBri9Ojn9/fdcf31kFRf5Pz07+8dbefzw+8of7R+br4nFCGsVkGaehrSU/ uW1q/siRtSsXzt26eu72tVuP783XR8LcXwdkJdvtyq06YVywKS7k1CrYA6T4 YEj1ZpPtYXfw7mD0wlDoZn94OK6lIX5nwNTgIL0k5NYr8hF7b3NupLtivLcw 1Z2fas92lrvrUpanbx+9c2r89EB4pdl+oNayq5w6kNLsj6CHwsiRoPxwTNPs JCpossZCFA3Kok5ZSSkqCIUPkWhELDmvjJSL7VqNx6KzmvSwGtksZG/islhi 4cvffvLk0/fuPLpy7uKBA3smJ0aaa/OhuI3M2XWdSc/8ePP5i6tvv3zy3lcf P/3sgzsv3jl2enGq0rac0a7U2850eC93BW8PpZ7M1nx6aOA3l7b/5vLcN6e2 fH9m4rsTvb+cG/v7w4PPr+5eHqzqasgMjfXP79+7/9SJU9cunbl+8dy1C1fv 3Tox2ztg5DUb+QtBbCVMjFCCLjV3SC/d7ycvZHV3O5wPB6O3h2MXRiK3xpKn BiLtXt1wyJLRwi5cHDSqCkFrf21qsi013Zocr43UhwxteffpldnHby6eHY+v NjkP1pr3VugOZsjDCeWxCLIeQg9HkbmkIaSSxHE4RSJxDZTQwGkcTqplDkig ErEk3FK1VGAHZdZuCrktJhMlVUg5sFjJ0B98++nzz1/ce/fW9TunL15b239k tr+3Ou0xxk2apqBlrCOzur5w59Hdl199/OFvP3384dNL96/v3Dc1UWHakyVX 65lTTY6zza7L7d57Q5ln840v5xs+XKz7dHf9V3uaf3ek4/vjXf/70YF/fv/o j1+/8/lHj95/+fDh/TcunDx8eM+OU8d2Xbl09PKpnTtj5IRNdiCue9gRPZkx HvTI1+LE2Qh2Jat9s9V+s9d/ayR+fiB8ZTD+9rbahYK3zaHN6FEvBQOt8j5z W3lwsDrQk7E2hozHlga+++bBly8vnZqtPtLiOFxlOlTQHcmRx9P4agxdCcuP +KD1HNnhIwxibkAlCaqlIZUsrJLF1LIAKjWKBQo+W8JnISKuhVJHXEwy6PL7 bIzbTDrM7vLsR99+9v7XHz395Omjl/cePrtz+cbJ+bnhYsIVMaqr3XRvMbB3 cfj67Svvfvrq499++urLD24/evPYhaNbpnqHy+m9Oe16tQUQ0ck65kKz+2Zf 7MFY5t2Z8udbyt+fLXyyo/jb3TXfrbb/6dbW/3p/9e+fXPzHp+f+64vrf/7i 1sf3168dHD++ve3kwtDR5sg2J7wa0T3pjb87Vn4yoNxv4l2KERfS5KU65lK7 +42B6Nku3+WB2IPZ6hvTlV0+orDxRzJqr14RtZJVQSbn0LQkmOe31v/41Ztf PNh3a6V/tTN8tMp8rGhcKepXC9rVLLaaUB7yQ6t+5HBBb1FyKRHbp4R8KllA BQXVUFgp88ilBCiGPLaEx4b5XL0KSfhdlblkJpeI5uL+fKqiu/OzH776+NvP X/3m4w+++uA9MIyPbx06tqujLhM1YxVOfWvcvjjecu3a2UcfPnv1zccfffnq ycsHp64dn1meHZntn6lx7w5rDgOArLWcqnWca3ReaXPd7gu83R96OBB50hd6 ORD5ejH/x7O9P90Z+/Gd+T892vuHe0t/err/b6/W/vbhuc+v7zo9XL2jPjQf wVYCmmdt/jv1rgMuxbyev+KSnIgo1zLYmTrmXKt7vc12uS98eyz33t7282O5 aiPiVcFWjdxBKqwquCZue/X20T+8WH95fuj9O/MnpjMrNZbVCt1qUbtWoFbz +GpWvZ5WHQ3BF7LkaAKXiUpJMcsECVxAKyAUBodVkEUmQMVckZAtAlqJ+Bgi 8zjMhWK6prEq11gTrq0o7279+LuvP/3+y4+//ezVNx+9/PKDx68en7l8fGKw Ne3S50DbjdhmB2sunF959P6jD7766MMv3n/26smVO1dWL51Yu3n16sPbh7qT uyPISg29Xk2fqjKerTVdbLJcamCuN9rutrofdQc+nAh9u1z5+zMdP9+Z/eur 03//8MRfnhz66dbSD+cG/3J19HfrA4dawqN+1YIPOhxWbg8gIwF1FwNNGfhr QeQUaD3gVBnX21wXO/1vTZS/u7v1+2vb39rbXu0kjVIRxOV4ac1nj1d/erjz ydb4e2v9D1eHDrVYjtUY1iq1q5XkWpFYz2OnsprjacWpGLpWoUuEaB2u0KES g1xgR0V+pTiIyXxqyCDjw/wykYAFiQVqVKbDFDarIZ6OFOqL5S1VsbqKcE3+ 0ccfALk++e7Lj3772Qdff/z885c33r4+NztSjDiyVqohaJ3sKZw+te/Bg+sv 3n/84Wcvn3/0/Pa7D24+e+fuqxfv//jjpz99tTZVvRRFjlXqj+eo9QrqdA19 stp4ptp4vsZ8vcXxzoDnw+nYV0sVv1lr/ene8p/fP/GPjy7+14tTf7ow+vlM 8qOJxBfLdTtbYh12eTslysFlBWnpiB6ds0q3mf5/pt77q6m1axf+C843znnO efezH7dbSnrvvfdKQkJC7733Lh0EQUAEBMWCYgFEAQXpIioiIEWlSu8gTVCx 7eK34n7PN76MOTLWyA8rWVfmvK5r3smaN6rKkVPpzK4OkNdEWDXHGp7n+Ezd TF5pzf04fOHP5c6ikpjw/JDJhvztmvg3BS4vMvRPcz1rw9S1weJ7IeK7wcK6 QEFtAKfej/3Ag/nQk97mzS0Kt/UIdXfxsrWzVzsY5I4qgSOP4sQxFePPP0Yi SXgki0GUCNlquchosHJ1d3Dzc3cN8jR6OakcrB88636zsji3sza7tTSzMT++ 8vbp8LOLgNa56VwUrEAb2ZnkgPq7l5911Pd314wOPpmenR6eneifnxrbWFt4 v7/17Y+dzx8eXkq56Ea548WtCxA2hErvBYkbg4HClDWGA2kmf5GkH8t2nDjn uXg/6/3zix9Grx8OXD9qLd65Ev4602HxjMfi3ZSUGNdMIydfSSlXUW/bcm+5 8ssNrHJ79jVvSaWXuDpE3Rpn+yTT801V4kpL3v7jM89qT6bkBPSUBc8VuL/J dBhKtWmLV932F1cBeRgguhckuhskqA8W1AfyHvpxmjwYrR70+nCrUzlRyaci ozLDozIio06GRIV5xngZ/HRiI5ugouEENCKHgRVwqGqF0KBT2Bk1jm529m52 ti62Kr1KYiUtuXH1+eTr6a3Vt1vLbzcWxlZmHr/sKSs77etoZSumeap4eSf9 m5qqnnQ1djWVPe24OTE1+mZxenBxburd1srRx7WjD+ufj7b//PbkQdkVL/pN b05tkKg2QHA3CPjA4nqgNoPFdwOF7TGqp2mGV9eiN1tyD9rydxtPbV2NWqkI HzvtMZXjWhClCylNqblTmKsklutYV21Zt71kVb6Ki67CUjvWRWf+3TBda7z9 8zOBo1fjPg9eGKpJ8fDVlyU6jMVpR1IdX51y7T2pA7Ko0oN9w4tX68u/FyBs DBE9CBE0B/M6A3iPvNlNfrzSCPf8rJhz5zLySrMyLuRklWdnn005nR2fmuDv 56SylTAB/6mWszUKvtFa5uqoc3bU2Tnqbex1amulRCkVKSRBSbHNzx+PrS6+ 3Vqd2lx8tTTV8rSloCDZWSu24dM9FNysePeHXbWDo73PH93svnd2oO/hq9mx oeXZsXdrM/s7C4f7c+935g/2d/7449Vg+404zQ1fZn2Eoi5EXO3Hu+XLrwkV 3wwS1seoOhJ1PYU+09Upc5Wxs+dDJrNchxNtR04az/pK+A6y+It5cx9Xi/x1 ZWrqTXt+hT27xJ6db03L01ArPWT3wvQtiY7P8gLnqlLa87193UV+Ia5FHrzZ dLvhVNv+FGNntOpeqOS6J+emJ6fGm13jxWoI4j8I4TcHsrsCOI/92KUe0ii9 Mj/M/ezp2ILzOWdvnD9fc+nC7UvlV4uLSjJzTsclxAe4uehdXazdnXXujlo3 J72jo85gp9XoNVKVXCCXsCVCnZP9tab6FzMTkxvLU2vz/ZMjdU13kuMDjFK2 jZDpoeBlxXi2tle/nhx91d852FDU31E19Ob5y/k3/Qszo2vLE++2pnfeze5u zu29W/v6BRDTxgL/W0GMhnDhvVDxjQB+hTerwpd/I1x+N0Z996RxsCJiJN9/ JMuzN1bfH2t9N1ipdJTanAx8PNn7anPSNsT1tKv4nJGbqyBnirHpImyxkX/L 17o+0rYhxuFWiM1Ja0akr9Wj+8UiOSXLiTWT4TB40vAkwfo+QOahomtu7CpX 9jUnChC13qz7QdyOYH6PP6s9WhptzfMTMhOc1Rmxntn5ibmX8s7XVFy9f6uq 8ebl2xfKq0pLK88lZ8eHRfsEBjp7eRrd3W0dnW30ttZWNjqZRsOVycg8Hl8k zqko6xgZGFmaGZ6b6Bp8dulGRbC3UQv0RwKGu1KQGenZ2Hht4FX30IvbA7fS X90vHHxU2/vqRe/s1MDC7NDS4uvVlTfry2Pry69XFqbWlt7MDjVdi7sTK7kX JaoOEVZ48YpdGBU+gqpwxY1obWeBz8tcv5cZHo9P2j7PdHAz8nmehvzaK4sH CzUvGiUxnlEuskJHaaycEsZDpitpZ/W8yy7yUntRjpZjZMByU1z/3B989qCI yEbH6xmTaQ798frHCZr6EGGVN+eSIwuISgfKTRf6HR9aczCrO0jwPFx4O1jm RMO4s4mhWnG0n0NSeljmudScslNFN89VNt+oar5Vea/q2r3rJZUlmflJUTE+ vn6Ont4OTq4Gvb3eysYg1VizZUoCh89ksqNPpVc/ausZH3kyNlTf3ZZfeMrN RqrhUoC8crcSZkZ637lR3nb/6qM72W1F4e25gffPxj64V9Ux9KJvdvrF7Nu+ ubdPp8bbhgfahl60P2ntab3V03SluSyiNtP+Xoz6eqgw34tR6s6+4Ce6HKFq zHQeLAjsS3MfyHIvDbYmCumu0f4dAz0TG+PFbbcE/gZbIT1NJwjm4wI56GgR MVVBO2VFz9dxXDiEADftcE/lVteFnrrTDCHZWoh/kagbjNd3xqpq/XiVLrwi PaXQmlQJNDIuzDuezNZg9uNgXne8NlxBNeBh7mxSsEYS6eMYFeuXdDo2veBk 2tnU3Iunr9y9crW+CoCrovZKceXZk8nBQUGuvv4ujq42WqNWbWOQWemZEiWG xRNRGCFhIWXV1+739zQPPLl6pyo5NsJWylOzqUBeuar4pyJ9bpRl113OuJ7u cyHUcNpBkG7kl6SF17XWPZl43TM93v56uPZJ1/m6m0UXSy+WZNedS6gvCqsr CL2e4XMxWn81Rl4SxCn0YBe48sr8ZdfibJ6cCXia5fMs29NZy2WpxXnlhc+n Bl7MvkypPs92VQPtcI6fPkpBj1KxouW0VDWrRMuLVDDofGpzXXFbVf7b8uSJ 9gqFlk+lwO4HyHsTrZtC5Ldd2WUOjGwV7rSKeM2FVe3KvufF6ghlvYiXnbLl S+EQayLGgUny00iDfezDY3xikoJPZkamnD6ZfDruVEFKSVVpWU1F2Y0LBRfy UrNjwyK9/QNc7Z31Kq1SZaOXWRuZMjWGyVPQGIG+3gUVpTc7mm+2PjhXXhTq 56nhsVRMmjWX5qYRZEa4n0sKungqoDLFM89DGSyjujExSW7aGzWXOkcGO8ZG ax4/OnvrenjaSQ9Pp3Bvw9lI52uZXhVJzmeCrbKCrcvzYytzAvNdWLmOnEIX YX6Q/EGO57MzgRXxHgQe3t7PvaG98fF4X//ccHJVKc1ZGRfkciXZpzDImOos y9CJLhqE+ToG0MxGJfhMjTTUX8nfaLiw9KLG00uNJkCLXMRPEgAFlF2wpebq iLlaQqGedMWZftuZ2eDB7I0VXA2UcPBILgoixSN0dJKTjOvprAkOcw8N94yI 8U1IDU3OCE9NDUnLijxdkpVbkptVmA6wVlRCUEAwQFjWCpVEqdVIrA0suZrI EegFgtDggLyykoq7d0pv3DiZnuxiq1MDHoPDsBGyvGzkSf6Op0Jc0v31eX7W uR7aMAXHg0GIdVbfqr7UOTz4oL+/pLo6IDlBZrTmcjm2CkGEk1V6gF12gC7J S5OV6H+tprKj7+mN0qQcB3auk+CkI6MyTvvsbKCfgwjNZ2SXFT5709vysnt0 eaKw9hrNQxsRaF+d6VeR5H4mWFfiJDvvIJWw4Aq99MWzuvWZDjmfV5UW/H6y Mf2kF4IEC1TR26KtKr0EAFBpMnSRLbXMkXXRgXHTi9uVoH2QbKPj45h4FAsD 5wHtMI1gJ+N5OmmCg1yjY7zi47zSk4KzM8KT4/0iQlwiY/zjUqMTM+Pi02Nj k8KDw7ztHLQqpUimUvLUVmyZNUMo9bTRxybEFly4UHjlSmJ2rru3n0zMl7JJ Wh7bIOR5WClSw3wzIr3CHTUhSlaCThijFflwifGu2jt3KjsH+m61tcTn5aiN RiqdSSZRODS6RiJ2t1YH2ChjvBwLi3Mbutv6ZyaejfWVxtvn2LOj1IRcD9GD bG+xgCJzsK7vuf98cmDg7ejbdwt3+zoE4c5yd2lRrMP1dN/zMS4ZLnKNgEwT UG7cLnk3/3RjsvVF66WRrsurQ7VV5UkkNlbBI9wKlJ+1p6WrsTlK7EVX1iV3 DsDkTwq839QmZIUB9lykEzEERDQHg1DQSY5qUaC7TUyQa1pcYEFm6PnsqKLU 8OQwD39XnaPRysnFztPfwyfYxy/Ex9ff3Q5wVmqJTCHjK9UMqRVLLAv29Us7 nZ15tjAuM9fZJ1go0dAoLAGNYsWm2wh4DnJxQkzw2cLczOSYIFthsJSeoBHH qjkZAcbbty7UPmw4ffG8jZc7iUYn4MhoNAaJQZPIZD6XqVeL4uKCr9yp7Bjo HZmdfDE7WX0997QLL82Wk2Rgnw6yJ7EYURmxL8aeDc2Nzu+vze2uvFqe9D4d z/fQOumFYT4Aq7JFSgHPWlBcfmp18fnS66aNyZbNieb5gZrZF7d67p+TqBk0 BuIs4DEcWbkaQoUjsy7aqj7d7smF4Kn6jMGGvMwYj5PBLl56qZJF4hNQchre RcEPtlMneNmmh7sWpftezIk8ezI42sPooOSJGKY7JRUqGWCobOz0tg56nU6p UAilMolQrGALTYOGguPi0/KLotPz7D0jeHIjisBEY6k0IlPMZMm5PCuRNCYm pvLmrTv19SX5qeEGUZSSk+GsKklyvXn17Pmys8HhYWyBAIZAodFYFAYLR6MQ GAyLz/Lw8ci/UFb3tPPFzPjQ7OTD/icXrhcVhFvnuIhjVERHFZuplF2vrxyZ 6h9dfLNwsD61tbB+tHOlo44opmBoCAKHwFZw7Dxtbt69tPd+enGydW26fWO6 bXG0cW6w5m3f7fEnFd5+GjQeEaWhlrlwr7gLmqP1/SVBL2tOjjXnLD0619+Y X54dWZQQFOlqrRUxeHiknIZzknMinDUp/vaZ4fZ5ca65Me4nfQ2eWoGUgqIg wGQUnE3EyzlMOZ8tF7AkAoaAx+TzeRyugMkVcYUiz4Cw8JQz7sFpXIUzkiSB YJgwLB2Fo5MITBqZyeeIAiOjr9bcaX3+/G7TnYxYrwArZrKb4nKmX/X59OyU aKNKSSSSESiMKanQGDgKgyOR5TrrqPTkC3frWl8O9k9NPhrsv3i3KiI+NDPQ Js9FGKNhCfg0mwCXwfEnE3PDY2tTb3cWJzZnJjdn+2aeByX6OHtowmM9Sy/m DL1s+7j/dnt9ZGvpxe5K/+ZM99Kbpvmhupnnt+b7bp7Jj8AzMH5qZpkH706o or/Ad/JOymzXufknF5afXRp6cLauOOlGTkSSn41GyOBgEVIy1kXOiXHRZAU6 FYS75ITYx7haeWlEOg5ZQkCK8UgrEs6GSjTQiTZ0kppK4BJ/ToohkahUOonK tLJS6excbDxOCqwC0FRrEEZgiWJCkHQIhorAMtB4Dp2j8ok4eel2fefA05ae joL8U4FGWbKL/PaZiPrSxDOxXjo+B4vGobFYACs4EgVHY3gSiW90VNGtG43P nvaMvu7sH7pZ35iUmSwWsTysWBcDNVEGMZ3PyDyXubAxNjE/Mr4+Nbk+/Xp5 bHC899lAQ1/f3fFXzasbL3e2x7c3X2+tDu2tv/qwPfV+/dXWfN/yVMfCWPP8 aMP8y7rHPdVCO7FRw7rkLWpOtxu6Ej718PTso/NLvVfWBq69vJdblRN6MdU3 ylUpZRCZKJiUgvNQ8eMd1dnetmf8bZOdFT5qjg2XYkXD6hlEDy45TEKLUbCj FGw/Ps1Ax/PwpluWTNWCRhEIaMBscIRGmtQDQTNACRoITmSJYoEQdDCcCkMx EVgelacNjD116c6D1hdPHnS3lZYVRXvYJzmrb+dGtl/Ovpoe5KLkkXE4AoGA x+MxGAyOTNQ5OKQVnK3p6Ho08qrr5cs7ra3niosCXGzJKJi9glMRbdTIqAKN pKGzbnL+5djc0OvVsfGV8fHl11MLQ/2D7fOro6vvRnY/zC+sv1peHj7ce7v1 bnJ7e+pg/+3h++n3m0MrM50bS/2zb5o3t14FpAbI9ezLUbres97jVTEL7WcX H1csPqnY7L/afTUxL1SX6mPlKmdw8Cg2Gi6jEjytBGkumtIg53NBDkl2ImcB SUlEa2lYDyErTsHPMkjzbJXZRnmCSujGo4gJQIkDDyQSBuWyKWdPRyEoCgRN ByXbQEg6S6wIjOaCkQBcNBCSCRwzxDZhSdlX6hsf9j2613H/fFlhrL97uEF2 Ps6r9XJ6Q0lCoqeOQwESlUin0QBWpzHp9q4up86W1rV1PXzSe+fhg/Kr5WnR ge5StpKA9lJxCmKMFAHeK8Tjxavu19PPN/cXl3fmh5dHrzXfKrqS1/z4TnCy v9pZbeerD84IKLqS0/W8UeQsVrmpuoc66lqq2p892P+8fvBxc36q+9PB2xtN lSwd60yszejFkJna5IX2goXu84s95et9l65muAXr+D4asZpBYGDgTDRcTME5 SriJtopiH7tcL5tIndCeS1WRMA4sYqhKmG5UZtsq8+yAUKRqxcFihoqEJyKR UBgUh0UD7XptbQWYaAOnGOEUWwjJxgwjsUQLICgOCMguNAeCFYg0rgnZhdcb 7t/vaa1urjtXfCbKz9VbLUhx09bkR7ZfSa9I83Ow4tMoBBqNSqPRmGyO3sE+ JTv71t2Gmqb7Fy+X5qVFxjgp/aQcdyEzVCsM9NLhRZTiq7mjAFnND15rvdn5 sjMoNUgfaJdXnuER5pRVkobnE+NSw7LOp52uyM4pTw/MCIrNjcm4mMN3EKOk pMCMsL1PG2vzve93JmZWx+RuVu5+2pGb8TP1aXOteQuPiuc6i2cflfo6SJRM ooJJ5uFQdBSciUIICFhA3D2knBidLEIjdeYxrKh4DY3gJWJGa0z/BU2xFmXo xDlGeZZeGq3g2tCpZASAFVxqbci/XNXZ1wcn28NItjCyEUwA8kpliRaCUGwA KDCGiyCIVLZ+yfml1xsba9saL9VU5eWfCvNxchQxApW80miv1ouZTeVp6YFG IZMEPCgUKpVCk8vkYWHBRedyS0rykxPDItwMgSqhv5wbppVEWMsFIrLCUdLe XT072Vtw+TREiMm+eiYqO+L9l7XdvWmlnWxqY9Q3wbur98Gl28V5l/Mr6i6E nYrc+bA0tjYm99S0jnRKHSRDE8/3N4Y3V0e+fT+IL4jh6Pn3y0JXOnKmW3Lf tp6Zbct/eS9LwCOy8QgmAU1CwQlwKA2N4uDxIjJRySQbBQw7LtOKSZZR8FY0 kr+MG6cRJWikyTpxikaYphVnWktilTwDg05DISk0dnBW0c3+1y1vpqAURwjZ Dko2Qgk2IKwKjBWBgDLEmAJHUxjcQlILz1+uu3vj/t3zVy+cTEn0dDJY8RkO PEaKi646L6zjataVjFAHlQCPw+FxRCyGwCDT9XJFkJdDuLeTg0aqEzKNfIab hBNhLfPVKqhMUmJm2OvB5pH+hxGp/q29DRX3Lpwqz/z2997oxGOOkjG5BGAV 0NxVU3o9v+BKUXntBfcYr79/HGx83OQ5KIbmh1/PDi1vTQPKuLb68svfB09G OuQOspg4++XnxTMdhdMt+bOdhfdKglA4sFzE5VLJBCwai0YScTgKkUAm4GlE HJOCZZHwbCJRQMCrmdRAhSBeI4nXyKNVojAJN1wqCJOL/SQCNZFCxWIlGtuM K3WNb2ZaJmfAZAcIyR5CsIHiNWCMDIwBsOIBQEGxfBpP5+AddTLvXEnVjXNX L2XkZgUE+WuVcgGTpGWSgqwEhTHO9aVJV7PCXHQSLA6LwOCQKBwBQ+SSaBoB Sw+wHQnHI2HlVLJewHaQ84TAKVXcu43Fr4eanj6rT86N+v5jt6SqIDoranVv tnuwmSWlLK6Ne8b6dD1/cP5WUcGVs8U3z9sGOf3x94f1jxsMo6DrTe+PHz8O P20CNbi+OvDx6+7+p7XE09ECg+BBTdZm/5WJttMLbXmpwfrfQCAXTw+DrYHJ pONMk1/wWCwWg8WgMaZRdoBwY9EYMgYtppK9ZYIwlShAyrdn0azpVGs6TcOg KagUrmmSG54t1YfmXChreVz5+AWUbA8hGiB4azheC8EqwRgJGA04Bw4cL2IK DUb38Ki0nLT8/Ni0VC9/PyuNhkmnEUxTPdFGHiPEVp0W6BrlbiNg0+BoNBxl CjQSTcTgft7tgqbh0HQclonHcch4HhlPpGC9Qtz6e2vHR5obWyozihI+fd9I OhOP4WIHXj++df+K1lG+tz/nEunybLir7HZpZmlWeW2FY5jbl78+fvhjL/ti GkXDr22v//bHwdrK89Wl3qMv+5+/bD8Z6hA6SJx99HODtXM9Ja/unjJac36x OOEZFODm60vnsDAAMFgs0FPAMSgYGglDoeBINBJp+qx0AlZHpzlwaToKHiA0 EhqJM91iD0Ob7vBFwJBYFInB1do7hCeGZRfBSEYY0QgnauF4NRyrgqJlEAzg SEUIgpjMsZLpnJ18A90CgvQOTmKFksZgoZAYGBSBgqNoGByfSJbSWAwCEWoa GAUHXoahMCjT31QJDIC5KGQiFkfCYmkEvIiKd5CyxGJ2yYXM8ZEH02PtldUF JZezd9+/dQpxvNty69tf2+lFKV6+hu13Yw6Bxs7eh+W3y2KyY85Xn/eI9Pz7 x493hyufvm7dbL7FNIrffVjd2hhYWXzy9fPe/v7Kx88bgC7QrdhZGeELzyqf 3Mz0DXb412//0tk527l5YslEGAYF/xk/gQICDQOuAo6EwWEYJJyBw/AIGAYa gQNegEOhcAgMDobCoWAYFAKDgRAwSwQUhsXSeXw4yQZOtIUR9WCiGkxQQwhW EJwSipPDCRIMRUoXKPkKFUcspXF4eDIVicLAYaaxSGBTwMBQCBgKBUGgllAo +OccJCgCcO94AuAdWGwWg0khU7h0so+1vCjW/0FJUkoCoLxn+h/fmHzdUnY5 4/a98qX1Eb23fmCo4+vn1aD4wLyCxNXFbrdQQ0fvw7Kqc34x/vlXC08WpEws T72Zebm6vzCz81Yf7LC2v7iz8XJl9tHR0faHDxvv3y9PLb50irYX6IRleWG9 D4rOXcg4ZvYLFei+FCoIGgHFoiEYNAyNgaLQ0J+TiqBIOAQJhcIAMKBwBAwB WCgEFAyHAMdEFIKFxRCB7/1nAoBgwOswSyjYErg+EpBUQGrpISQALg0IcKQE DRingODFSKIIC1QtlY4mkIDiMv1jHo4EchMGQ0BgCAAiEHAGKMTcdGD6JsBQ JAiGhqNxZDqLzmSzmGwRj+VnlNzKjR1prtocuj/cUdFYX9jdWjHxuunytZyy y6c7ntyxD3N89KJhZrFf66Uvriurb7ns4KPrGekqvHjKwcdYeruEqKQztNyK GyVecd6vll/ZhTqvAlitDSxPtn/4vPPpaHt3f2l7b66jvx44g8iGV1oc/ejZ PTIddwICxpDJCCwGjsNBsVgwCg1CmkZgwRAwEgHDoVMoGAwcDgMj4CA4xAIG Ap6RCCgfj9GwGGxTsZgGrIFgP8N0AIOQbH+GEUK0BRP0YII1GMAKD2Alg+O5 CCINjiNC0VgYUOCmBtk0VwSodMB1gCEQICxhpgDAB0FhlhAYCIYAsMKTaQQK g0Sm6STc06GOz2uLVoYf7kx0rw7f63t6Y2aqa3Ls4a07Z508jTkliSw1C8sj 5l/KDUkJsfY0Bib4Xa0++3Kk+UX/vaeDrfMro1fvXIg5HT040moIsPVMC9T4 265szWwvv1gef/Dh0+anL3u7hyub76a2tt9UNV0T2EtVTrKHXbWB4d6/mB1D ENAILAqAC4pGQRAIkImFwBwyziAT2klFQioFjQHQQ0BRCLFcauuid7CVBzla u2slbBIRAkVYQIGSMY0OA+ACDqAUB8AzQMhGADEwweb/YqWEEuUoshBN4SBI AFxAYwScFQOoCQnoZ7BYIHctTFjBfqIEAQGgAeeEms4JQ2GRWNNEOwwWbyPh liYF9lafHWurXHlSvfj02rOemxMTnTMTbRFJbmoP7dMXjbeqi1ofXh4datzf mVpeGDrcm1ueaevrPD85Uv/paPnd1szB/srB163NrbE3UwNhGeHJRSn7hyvv FvtXxhsPD5aPvn3Y/7i+f7CwMNH9fn8+5VyCwEXpmeBj5WFtSQQIwzT6CoKA Aw+k6T4SmJhOdLeSuVkprPhcCgEHQ6MsYDAam5l5OvtG7ZXqW8W3K8/GhHvQ SUQQ5P8m1U+gQADDkOzBJAOYrAeTDWAS0OlYA5UIJqrgJDmaKsbSRGgqG0UC 7AmegscCCusoF7kqJDQ80hwMAkOQIDDMVIw/Kcs0ug2BBPIKCDACEGesUcY/ Fe58NSuoKiuq8UzEs4r4wf76kZHmydGmyqqsrt6a9ZWXO+svFybaB7uvr073 r8z3Pb2b21mVOth1dXGqbXXhxcry662Nt1ubbzfXxj4ebADm4dtfe+8Pl7eW BpdeNbzfn/vy/cvhh80Pn9aXZ59tr0/Ozr1IyY9n2ks5zkqqiGlm/rtpaj0Y jITBgHpj4jA2Yp6jUiJjMZCm+7uAD4wwg0JV1tZ3H9wdGOl63tf8qLsuNt4P 8BRAJgBUYwkABYNbANcIMBvZFgKQFYCVqQyNELIOwApKUMHJUhRDjGfK8FQ+ lmSaGiugEt3l3Nww17KEwAC9HIOAW4AhIDDUHAwxg0BMZzOlKxyKwsLRWCjS NPnHKOVFOSki7MX+Klawhn0t3r33cW17W/nL59XDA3emXzdvrwzvrL/+fPB2 bqJ1oO3i5vLIztbo29GWg725zb0ZoLle2p5Z2J6Z3Zxe3l/++Glv//364Zd3 JqyWB5Ze3Xu/N/v1ry8fjnYOv+xsLA9vb02trA2/Gm8prDwXmZtCYJKPnQB8 FhgJBuMAskHAWDiToeIRCHAY5DjEEsgoMNI0zc/aYKyqqWx7dLep+XZt7UUP LwPcNKcaYcooONIChgCUy7RNAEmLpWoIVGs8XY+i6KCA0QKSiiBHksVohgTH kBAoXCyBhsMRZCxKhKPsVm50x6Xc4kgPPglvDgIBcJmDof9gBTYNEAZqH4MA UguFJGHRznJBiod1ipNVhIYXbRBWxnoM9j9qe1LXdO9cU2Np7/O6jvbKutrC e3eL6uuKLpTG1t3OXF8Z2d+buXHvMkPOERjkfHs100ZGtRZTbaSXGm78+eP7 x897Hz5uvlt9ufy6YXd76stfnz99ff/h8967zYmttTc7Bxsve28eHE5euXUV UGxzSzOIpSUBDOYhEGwMggr4ZQSg2SBLMKBK4H8mHoMRWI6AHxjmH5MQFpcY FB4RJBQLAXBAgMTDEZZwlCWgkTAk8PDwCElOiMuMT0wODvN39pAJbTBEGZoo RZPEaIoITxPiSEwMjoTD4ORMcpSL1ZXU4Du5UbkBtkIS3hJkGtxtAYaanv9v QJGAxQK0AEon4iPttDfTIpqKUpsKTtalBtUm+U3MvBmff9358MrQYGNwvK8Z 8A1TUBYYsCUO8ivcUu1u/XbhecuTegQbexxu/jsOcgwHPo6FHCcgzBn4EwzM pfobX/7+9vHTzu7q8NLr+p3N8S9/fvn8/eDj0e7+7uwGgPPBztvJJ6Mv6zLT Yih4JBhiAbe0ZCLhOjLRnsWUUAEKg5iDTMPWLCEAXHAIAo3C0ylcKZ3HptBJ dCaFwWSisPif9GsidhAUSCrAUqBwaHT3w/szI4MTvT1jTdXPbpRfSYtz1Gux BC4Kz0eTeCgiE4UjI9E4HAojpuKdZZxwO2WMk8JexsEiUT+/nZ8Q/ST2f8oQ jDRNtSNgcGIqI8ndWF+Q1H+jcOTm2bYzMZfCHWfXZxbezb5+2dTUUgkmQn/H QE4Q4MexMDMiAkLH/wcFjs2O8U30PYaFwNlkGAOPZJEQbDKCR4cJaMcoCImX 4eDPT0ef9/fWh1fH6jdXX37989OX7x8/Hb3f31/eWH99cLi1sbM0OdGRHuku IWDwcEsiFMTHI53Z9BCZSMsgwwGT83OWhYUJK+DTIvEMAV1kILH4AGwwOMo0 JR6JMmUU1MRUQFIBF4VEIMlY3OLU8N7y23fTI9tDTRs9d9/UXahMD9eIBTAc AYmnIbBkBJoAR2BxKLSUjrfh0fQCujWPwsUgwJZg0wSbf1QV4HbIT88AVDUS TSJTeRSKjkePcVJdSQluL47vPJdQGecRJCU86+t693F9bLi5/FLObzAzOBlH FrFpUjZeRAFTMb9Bza1cdc4Rbv8C/fZvBOTcjYqB8Rd948+vP7yBEJLMmFh9 hNfht49HXw52N8fXJ9rW5p9+/X74GUi0Lx/2DtbXN8bfH2zsHG2/XRgOdpZI CSgaHMRCw8R4tB2D6iVgqygEKBhsmr1jmqH9k2ChECSWSKDQMQS8SSvhKAgS CUYiIKZxrNCftgoBXB1gAyh4wuJI+/pI21pfw9rTO+tP7s13XHl8ITHZWUsm 42FYCgKLBZgHIGwKEWsrZkUYpXHOVoFavg7o1REoII3BP2kKCEuA538eAwLI 4QptZWIPlSDcXp0VaF+W6Hkp2jXTWWmkgaqunN0/2nkz3FpSnvE//vMvjpLT 0n27v+/Bg7bbUDruGAYSnZcYlRlGEdFZakHT4wcHXzf+/vGpd/IJTEyz4FB1 4V6H3z99+nK4sz29PtW+PN169Hn38x8fP337+P7TzubW9MbO3P7R7uBQp4aF YmLgRDiYiUXysSgxEa2g4DmAhweDzCHg/7YBJtsDQkAhGDiEgIBwMGighTPN fQLc/M+5T+amUjVdFIAhCUeY661f6Lw213p1oaNqvuP66/qi7gtxxSHOWg6T zeRwWWwSHoVFQXhUXIBWVBhodznWqyTMxV8jJ5s2+4D8f1iZnAOgrYBYYPFi iZWT0dlZo/K1FsW56bNDPbN87OKMYg8ervxM6saHzak3j4pLE/FMnG+w0/ib 7rX18Ud9rXgl+wQbX1RVPDX39Fl/49Bo5+rqm+YnDYU3S+JKMzE6oaWS4ZQQ 9O3v7yasdmY3Z7uXx+4fHm0dAVX57eOHz/tbO4ubuwu737bPn0tnQC3wGAQS aklAQKlIGB0NY+OQZKSJ2AEEQCZ7aRqYSUHBCEgYDQ5REtBuYpa7gCkjYqlo FA7IEIBhTKVqKhwk4C7R6K4b517Vnp2oK37bfHG6/cJAdU57SWxhsBHIIp2Y 56BSqLkswPYrGERvK162l/ZilGt5pFuE0YqKw5tcqIn9YEAfBTxbwOBmUDiG QFdZO3kGRts5OUgFNAelKNLeJtxO46sV2TGwufHhM5tvhwfuP+260vPo1sRo R2NTpXuYh8JVB+aT1V7G5vaqJ89uvxxseDvxeG97MiQp8H9A/2PBJVqKaXxv w+vN+Q9fP3w42t/dW9pa7FscvQsY0aO/j44Ayvp6sLW3vnOwDnSLzgYpEwkj YYGWxRINh+DhECzUkoqCU4H8gEEtAfmGAk4QKSCSpFQCl4wTEDEGFiXOqEmw tbblM2UMspxBo6BMA7fNfwrWz6UJVKSTujzKpTLRp/F0TFdZentZ6r2coAwv jZJD0Iro3gYrZ5VERiZo2VRbEd1PxT5pq0i0lbuK2FQsHmRy7yZi/yelAXmF YEhUrtTWOyL61LnAxCyFwZ5JIap4bIOYDRCdCAePiwt+szjy9NH1nvZLj5rL e9sv5hVG/e/j/8cMDgbR8Lfb74yPPx6b7Hoz3DzxqmN3azwsJfT/sThuTsZa MggUK9HYytyXP74CWO3tr+1vjs2P1L57v/D57y8mrL592D54d/Dl/fOBLi4R zifiSWg4BgHBIIAeFYKEWODhUDIKgQfaHKDAoBAGDuss5ofYSP21Ii8ZJ0jB zbOzKnSziTKIQvXCCDu5jkcEHOw/WAEXCEeg3aXsJIPCXUS349NCbJSnA+zP RdiF2ctZFIyIQQR6Ab2Iy8WiVQyyDZfuxKN5ipneUqaBQ6FiCYA5t/gpf/8k KhiJQ1N4XJXRKSwh+2ptUXVLTO45kUoKGC4iAUMmILGW5nda6iaXRrrbTFj1 dl2fHLp/viLtONwMhkcfg1s4BHr2jfdOjHWM9t5bmnz2bvXV3YeVGcWpwYlh FljkvyC/W3vZHX379PX70YePOx8OV5dG7m4uvTz668vH758+fgWanb2jPw+L zqWTwRYcIgGFhGLQCCIOECagPTZHQUE4BJSIRGIBowmDqOjEkw7awkD70iDH Ul/bHAfZZU/dnTDXqhj3y3Ee5REu4ToeCQUxM23+AoUAxhSOuhrnXxsbGCDh UlAQBhZuJ6CH28jshDwSFscg4VR8DodOJKJNswHVdJI9j+4hZnoIaTomiYmj wlEEk7bCfkohFIHA06kCK6Wtl3f8qYJbD6q7B4prm4NPZlLoVAgEkEwIncWc WJ99+ebR40e3OlrOdzWff95Vebsqs6Aw2t5F8xvE4n8e/0/YyZCxsbY3Y48W N8aXll/NL73cPZyqa752AmVxHAehq7ib+2t//P0VMJ9A17w51b74pu3T1w+f vh8dfjl4f7S/ur1otBIS4FA0BlA0KAaDolGoNAoJAQcDXT4KDqQZHAOH8fA4 NyEr0VaV72u8HO56NdQp30VeaCeuCXftOBXVkRdfkxSYYJQwsYAIQv5ZcQKw uhEb2HYq6oyT2ltEdePhAxScII1Aw6bhUWjAgDIpJBIRTcTAOTiMnII38Gje Ml6wWhgo41szOWSToyBCEVhAWxEYAoEmFlg5Ke19fRJySu8+uv1o4GZ7d97l O64BESQK7djx3+29PV4tTTW0Xet5XvP0WU1H26Wm+2UdD84/b7+YkR70O9Ti Vwszv0jf4svZYge1wKB8/Kzl4+fNze231fevmmMhgAeT2FkBevft78+fvh0e /Xm0szKw8Kph//3m0fej/U97R398qG+uAcwaCYNGwk2rBHAUikKhMJl0AC4c YJIsLREQEBWPseNxfeQiTwkvWMbOdlQXe9unGWXxGk6Zv7E9O6ozJ7YqyjPF Tqlk0mBAGUIBNYQgkKhTLtbXo72vBzqetVOecVTmumhS7JWeEhYP6ABhSCwG S6aQuTSqxDQjjqhlkJxF7ACNJEan9FKIBTQ6EkOGo4lwNAHog0gMCU9hL9W7 e0SnldQ9ut7Wd6mxoay64UxFtX9kPGCIk7MyNz5vt/c/6B5suHbzDIVHZsvZ 7Y9vjYw0Fl/JMsOCf7E0c/J1jEoO/bfF77/BLSMzEwqulQQnhGpdDRYkwKzi GCr+xu7anz++ffvr697B6sry4M7m67395Q9f3u9+3P3843N4nL+F+Qmgbwcs JZDqYIBl8DgGiyHk84RsNoNKpJJwSi7XSSFzlgn1LIoNHRui5Kc6aKK14igr UZGffUNK4O2T3mf9DGmOGgOXjYDCzU3+AQZBIHJdrcsCnGrC3MvdtIXOqkIv fY6bdaRSYE2i46AAlmg6k2ujsnaUijR0opKMU9MIBj7DQy5ykwgkdDYaS0Zh SSgsGUdkkelirtQos3ZzCT1ZcLOlor4np6LiVFlFeUNLaXVj1Mmcq7ert492 Xrx53N0PYJVvjjQ3R4FsPQ16dyNBzALhEf+2NLP1MEYkhfwKMkfTSBZo2HG4 5X8g5scRYCSD9BsO6hHmc3i09+2vL7vvN5ZWRnd3prc2xrd25ncPtz59/zT9 bp7KJpm21cCgTY0eHGVhWjWCEykUkVCo12rsjHqttZVIJJAIuLKfc9iMHIqv jBeplYQqeFFqUbarriTY4UyIIclZ5Sbn0PEIMBhmwsq0igIvcNOfcdZe8tZX uGvO2EnzPLSF3oYknUJLpMIhpm3lOByJo8HZx0arZ9MA7yHAIXk4JNAMKphU HoODJ9DRGBIaS8HgmSS6mCnSSqycnYKTUs7fTi647hYWYe/jn1B0vrjuQVnd w6Ynjxa2ploeX2/rvlnXdAlOQACKbgaHHINYmiFh5oD5waBqG27e77pB4BL/ bWH2OxT0O8TyPyCL32CQ/wMyU7nbLbxbAJpBwG2uvVvZe7+0vj6yMPt8a3vh /ae9na8HRi/nX//zGwRovuAoEAwJhqOB1LL8uY8ghUo1GHROTvZKKzWVwSD/ 3KlNAQgWn+4t5QbJuX4iepiSl2SnyvCwTnVX+6g4XAJg8k0rAxamlQETw8dJ uTESVq6d4qKHId9eleGgyvcwZtlpdHQ6DGra9ITJERoMjq56KwOLpiDi2TgM HY1kYFB8CoHN4lHpPDQOsPcUJIFJZIjJTAlPZnQJTY/JuuAemkBgsVFEskxr CEvLOn31Rv2jJxufNp6+qGt8eKnt2R2jp+3/PPbL7zBLEBYOxaOPQ8xDIn3m lobejD1sa6ty93dxDHCJSgpLSAqJTfQPDndpf3Rv+3B1c395fOr51Kvut8PN g91X+zoq3rxq+/b3h6uNN/7Xf/0LDPSnYIglBGHangOGsDBJj6kLRmLQMrnE 0cmOL+LC0XA8niRhMlQsio5Pd1XwApW8WJ34pJ08w02b7mWId1G7iBl0FNq0 Lvf/WxaI4DPiZNxkrSjLqDqpFoXIuMFyXoRcoCaTUEgECoWUyDUeYdH+3j4O PK4Uh2VhUQw8mkvCixkUsUDM5snxVDYcS0LgaRgyF0vmsKV6z5jTcacuGtwC oFisBQQBQWAZPLFMZ3fhVvXXHz/e7a32Dtxve3z9YXtVdIJv2EmvnOLEWw3l D7uqh0cfvRyu73t8fXykfXKy9+Vo59hIy/jQw9GXD6amenb25nY/rM1tzEzP jYwPPBzoujn0+OarvtsDz2t2DpYLrhT965f/DZCwuSXIEgSzgAJNBNISCBNc cCSWoLY2BoeEODrZkGgECpWp4LKs+QxrLt1RwgnRSlIcVHk+xlx/+1Rv2xgH la+aJwJcBxyoPsjPOfAmrU9Q8OMUvEgpOwp4VvC8+DRrEtqGhJLhsGgUgkAi 2nkHxOaeD49Js7OSSUk4IQ4tohDkbLqcx1RI5XyRjsaVIvFkBJaKxDHQRKZY 5xyaUZaQe1lt6w7D4gCsQDCAZoGPjWnq6v7893fAC23uLvcPtfY8rRkZbXnc ea2x9kxDbd7LgXsTr1vaarLaa08PAf3p5tupqb7hZ3VjQx2Li6OAPz842pxb mXi79GZ9a+H94bvPn/e2381t7y3tHazsHq5VNd3+5T+/mFuAzCxBZhYgcxBw gTALMNBWIIGAIDEqnSEqMTk0Nl5pcOMo7ZRAEnBoSgZFy6I4SzkhNvIkZ0OS qzHKSRvnaBVsZ7CRqTlMFhSNNAOBTaeCwFM10gAe1V9AC5VxUxys4+00XgyK AxYhRiAQcCgGj1XZuQYk5AbEJDvoNVouXW0at0ixlgp0GrVOp1eq7EUyOxKN hyWyMDQ+TaQ0+kXHFNwMTMrnSNUgFNIcbFrWMAOqgkB6s7Ky//Xw6K/PR98/ rW8u9r9sedpb9+Jp3dPOqsG+huHR9tbGwoaLsXfKYp7cr1hen5yY7J2beb6x OfHxaOPgcGNl/e38yuTM0pvl1cmNtZGPR9v7HzZ3D9YXV2cWNxeGVscxOMzx 42bmlmAzS7A5CAa8NYCVpaWJbcAIjEBt75aU55lxUR97WR14UWsXImVROFgM F4fl4HESCkHHodtL+N56ebibo49/hjHwjMIhgsqVm0NgZqaTwOPVQi8WKUjK CdUIC+KjLuUVJ9nbeOIArIAEhEJhUDITcOLOegdnW63GRS11knLsREwnncrF 2dXewdXaxihT2nJEGgZXwZLoZUZPz+hTAekXrN1DkDiyOeDqTT+EIc1BEDyD MbG+snX47vDrISBkX4Hsejc7OtoxNPRwaWF4cb6/rfniw7uFI333l5aG5ua7 p2cHlpdf7+7Mfjha3TtcXt1aWNicnVubXlqdfLc1vTL3fP/92qdv++vb89ML 4zsfd/rHexAYzLHfLcxB4BNgiAkuc8vjEASUzEbLXFhO6bKg87rUOofTbcZT nVapnTK/AglfyEXDqYAHQyLISDgHj9dy2V56pV9YknNqky7rkfXJOrFzOoaj tkBizMBQI51oRyEEStmROsnlsrOtj0bz407q4GYsoG+CI0y7VxAIPKFMq9Eb tFo/oy5IL/NQcJ10Ck8vd28/Pxs7g1BmJZAZuRK9UGmntvW2cQtWOfjQ2EIw GNAg03o1oN0nLEFUHmvu3frup/3tD+++/Pn5+19fvv3x8f3B1tbm7MrScN/j mr6n95ZX3xx+2pqfH5yZ7l1dG9/dW/j0aevw4/LK5vj67urG3tr2wcb+4cbG 0vDc6MPd3eW1neXZlcmdL9trn9/5hLj/+ut/WYChQMmcAFlaIHEIhhXdMV4d X2N7tte5bMD5fL+xoEeT9VCd8kCe3CYLvsCXObLxWAoKRkbBqBg4n0LUiWWO LkG2SVWG3B6bvKeGnB5N4j2eVyFJHQIm8YVYpBiDsGMQ/GXs8nN5z8YWbtY2 2AjZBKgl2OKEuZkZCoc3OHuEJyYHB/sGO9tH2VmFWsu8DOrQyJCY+DhXdzc+ T0CmCslMBZ2npPNkVLYIQ2KYWMISZmnaxAcJiNAvvx+3c3Pd+7I7vTQ4v/lm 7+jd5z8/ffvr218//gQ6u7m54bWV8fdHm++/7+5/2t57v/YeiP3lTx/fvd+f m5/vf3ew/unv71///uuPH3/89ePvHz9+7K71bm4Mb33ZXf/2rn38mS7I+Rjo dzOI5T9rUziRgzrygnt5T2DNZNj9RZ87E/YX+6xOt0jjb7F8C3kBJaK4O/Ko 6yxdOJnBJwEdCgzOQCHFPInCNlQTdUl9ukcB5F5aky6z0zqjQ5vSqoyqY7rk 8TBoHhyiZxFj7ZVZyRH1vf3dr2cKKq4FBIbbGJwA+RKpNaFJaYXXqwuvXEtN SozxdAg3yCLdbBPjE6NjEnx8/WVyQB4JECQOgsYCATCDqQTAIAsQ1IQVDAG0 2L+DwAyJeOFgZfj5tYGnFQvTQN31bL4b//hp9cu33T9/HH3/8efh148Hn/c+ fH6/d/Bu/3D76MvBlz933+1PH33f+/7nyuH24P7W4Nra87Hx1iftV65fiC26 lh1TlCX30FtwUCfIcBAK+jsYbIlCM+1inEv6I1vXQjtX/R/MOt8aUZ1p4QRf pLmcItkm4q1jWN5nJcl3xYk1PO9CqsodR2KTAFniqAUu6bLYWqucDquzfaKU ZkHkbXVSk1VSk/ZUu3XhY6vMNpVKTYOBHOTsgrTAMzlhxbeutLyabh2dru0Z uNnZW36v7dzt+2V1zVWt3ZUPH50pK48N9Y1w1CaFecclxoclngxOiPeMjFTr jSgs7gQIZA5Itqkxh/xcfjc11KYAnCESc8zCXOdp1/r0zrPmjOed+WMvr6zO 1c+8vjn95t7SfNfsdOfq+uTh592jr4d//zj668fh3sFE99Mb7Z03q2/nZ2d5 +/moHF0EUhWZxkFDCdATBPgxAuIXHOQEFQUXkOBSBtAYm0FABJWTY+HjwPpF /3vTTldf2pb3WZ1pZ4VfITnlURyyKE6n6C5nxOHX1alNquRWQfBFssoPSeQi 8RSqVYAwtlGZ81xbMGBdOCiIb+CGXpPF3OGHXhNFVFvldhrOPgmKSyWjUVIW LiXVvaQ0sfjahYYXo4/GZrvezHRPzj+ZXXk0udD6Zqr+xdDt7t7S2rr4tITo IN+k+Ni4rOSQtISo3NO512qTSy7JdHpz4GFpwurnOoZJZE0BYPXTQgN97K8g EEJA9gi2tbYXS1XMkrLo+w2ZT55UPO+/MTn9YGr22cbe9PuP05eunUpI80w9 FQTopzn4+DGLY8cgFv9GQYH4DYcyI+AsqAQQAw9lEuA8KkxABwupcBXHDI8E Ean8wBLH8/0OF5+rc9uU2S2a7C5FUgPf7zzT/zIvqJLtX8H1LheHVanTHlql tDBdcyAMlTkcDcJgsVJvXvg99ZlB66Ihq4IXotgGYfhtUUw9K6CM5lYkCq/R Z3UWXqpUiOU0BMjbKMnLCb3eXN8yMvVoYqF7YqFnaqnn7crjt0tAdE7M3Ont L71Td6q4IC4lMTIhLjkvN/50ZmpJ/tXmtuvtTwJTUyFoFACWJRj609v8t70B sALKELA3AIMhyGRLMv6/QBbHoKB/gy1/Q0DgeDiJQyJwCFK9AMvAsMRUiYb3 G+S3//rt1/9YWFoA2oI2jcOGktBgGgZMx4GZBBCTAGYSYRwSnEtGChlQERMk pJlziRAuGW/lxY+tU2Q2ChNvCRKqRfG3pQl1QHpw/ErFkbd5odeZvhVsjyJh cIUsqZEfUokQeRxHEk/AESfgaBhHzwy4pi0c0Z0bssrrE0fVA+mkTGsXxTfR fc5T3M9IIq/X3q0PiU6QEND2AlZWWkxd97OOycXOqcVHU0uPJpc6p5a63i4/ nlnpmpy/OzB4rqY2LS83NiU1JiXtZE5OVmlx3pXLFQ2NN9u60s9foPEFZidM 9uafMCUV2LSqDGAFQqAhCDSSQoIxqBAiDoRHg/EoS7Rpps0JGOQ4FPyrxYnj YBAg+MfMfrfE/MSHgAGTfgYFB6JhIWwCjEuG8SlQLhnOo4BYBDM61oJFtBTS 4AqOdZBb99iwbWIhx6eQH1DC8S3h+pdx/Mo4gReZvud5gZeFEbe4oddp3ueZ bmfYPmc54TeILnkgjhGEZZghyScQOEuKgOB0RpnVazg3rMp+Kom5L4mqU6S2 q/KeC6PqyE45HN+LNVWXTl+qsVXJbMW8lPz86hfjrVPzbVPzXdOL3dMLT+dW +pbWn8+v9Ewv3H0xfOb6zdjUpNDo6PD4xIRTaTnni/MqLhRdu3i9pamwqlpi Y/zt998ByTYZXdPPrABfwf9xvBAk0gICBhOx5hScJR4DIqBBOBTQA0JxQP4j TBOTsAgLNNwSZfrBAIJBQrAoMBEDJmNBJKwlGWtJxJiR0b/goP8HD/4VD/kN A6JaSzguWo+4IP/8k3HXC+uGOwB1rOp8gbeOpLuk0VxP0Z1zmB6FDP9ypt8F bugVTmgVI+AqEyhDv1K2Xwk99BLR+QxS5AIncs3RBCDAeB7CKkIY/8C6YNDq 1FNxQosoplGS8FCV0S1NaGJ4nOP4VJTlhqVfvGPv6C5l0N0joso6+5rGl1un ljumF3tmlodW34292x9d3346u3yv/1Xh7XsJp08FR4T4BvtHxIZnn87JKyzM OpN9+f69yodtPgnJIBjshLmFmek3uH9I3tRyguHI38zMfcP97aK8MDKWBQrx G9j8NxjoV7DFL+bHf7H8/VeQ+b/Nfz8GMje9Dvr9mKXZv0EW/4Zb/hfk+DGY OYSGw4oZBB7BNdIjq+Lclebqs9eKno492fy6f/jHx5onjQElycm3zk7tzC59 /sB3D8Nqwmj2qWRDCs0pl+ZbwQyt5IZXsgGUgm7wou7yo2oEMfe4sbU0jyKU xAWMY5khcRZoLIyqRqtjORG1ilPPlJmPpcmdkqQWftQdRUKrLK6J5l7I9bmQ F24MDQm0UtkwKBSWROGXXnj1yej98aXmyflHs8tDGztvdt6Pbu71zK7cHXhd cq8l5lypb0y0o4uLk6tTaHhofGJ8TGLs+drbTS9HihsfspSK383MzCH//Q8H AC5AEI+bW/CEgGHYGN162zX2NCotzNpda+2uV7vofZKiglIiotMirexVcp04 Ijmi4Hqpxs0m5lR8ZVN1ZkV+TIpnzf2L/XOvu3rvzC8Pfvjxff/vTysHy6/m nm5/2jj889PLtdf+xSdrn97vGe/9/uNHwOkCEN+TZB1LtI4m26cz/C9zI24D wYmqFcQ/kCR1yVLaZcnt4vj7DI9CuMDOEkO3QBJBaAZC6E91PQ+8rjz1TJHR KUlpUaU2aOMrrKIuKcJq6O7FTPfS7Ah9pLtKJuBTGUwWV6yw9UysuH21f/zO 6+mmydne5c3Rd/vD7/b7FjcbRyZKmjsSyipcY6Ktbe0lcpm1Tgsg5h7gVd5Q 3z07d+vFS4W763/MT5yAQE78zCsgQHDEL8d+K75W8cePvzc+785sz/QMdzT2 NrWP9PTODb3afDuyMDgw0fN44GFVQ3n3y66PP74sv19eer+48+fB4uHy2ELf 64m25d35NzOPxqefLr/fWN5fX95bHJt7tna4vPN1b+fPj5oY1/q+tqWDta9/ /3mlvcOcbYdX+KGVwXTXMwCf8yJu82Lq+In3pelt0sxuWVaXLKNdEFNHcTgF Yest0WRzJM4cQ8eoEjhBtfKTLfJTT8QpbdLY644JJe6J2YaweEVgMd2znOhc XJTkcjrR2c5oS2VLuEKJwuDmFJ+Zcae1su913ehUy8xy78ZO/9bu4Ppuz8J6 df/I6aqaoNR0rWmfCDaDwRBJJO5hgdW9T/tW1++OvJK7OALkDNTgCYiJ2wG+ OmEBIjIZT94Obn/ZWXu/MjzdMzzd1/u6/+nbl/O7C2+Xhl+8ap1aeTU+O/jo WXXfyIPFrcn1g9W5rbml9xuvF0f6x7se9918+frB6FjL26WBtY+b6wcb6wfL E3NPl/fmNo+2//zxI/9msT7Gff2P/cMfX/7fkq7zq6nt2/4Rb7z7fvfpVSC9 n/ReKIGEJHQI0pFiLEhRpEgROzZAUBFFUGkCekVpQUB6l5aEkAIkISFUafZy eeG+/WF/OmeMc+aYa+61xp5rrG61Asr1QnB9ce4n6GG3OXGlrPgy7rk618xG twutgottwotyflYTO7GMEJACZXmB0AQ7BMoOQ8aK0zlx9a6ZLfzMRm5ijSCu IDgpPfSkLPR0gufpfJbsMSms8E56aMn1iGsZx44GBbFZHL73Ee9jyTG5Rbn1 8opBRd3UbLN2vm3O+G7e9G7eXP9Bfa2i+kRGmkdgIIXBxAF4OpN1+nJOi3pm an2zbnycL/U+eOiA/b5dxxZ9tlQB9Z8Df8XEnZiyKAYU3e/H6ns+1E5q+2dM U6P6Eb11dsGiGFe1qQzjGsP4jKZzWtehN03rzGrT+sLS7rLWqhxRdnT1Vw8P Vqtn5OY1lWV3aWnbsry9OG8esWwuWHaXt3/t9GvHqCHCJuX7te87+s01svgI jCrGuoQTAy7SYh+wTj/jpNS6ZLxxyWxyy24RXpDzM5qYpx4DfucgDAkIBTgg UGAsjSDJ5J6q48Y/Z8Q+YMseiRIeeR5PPBIVFHI6XnzqJju2lBxy90Kc77Pb UVU3Q/MyYwQe3i5ewZ4RcT7Hk0NSc7IfVz3s6qsZV9bbclGF5sWk+sG7/rjb RZ5HQ12EAjKNjidS2C6OOWWPe4yL6q3d+ulpYZD0gN0B25H3r7bDwAjUH3/+ mXY5a/3X1pRuZGC8tW+kYWji7YiyfWFdN7+mNazMaBf69UtTc+ZJtbZTYxjU GcZ0ixM2Blp3llXGsWmdLQab1dq2OdOgeW3WumO2bJisH+cX16ds9LN+Xvu6 91WxPOuXGpNbXzxl0W3+89s97Kgdig5n++H902nHSjgJVazkGqfMBv4FuZtN iC51OGe1ceOf4v1SwBSBAxJwgKMd0FSieworsoQWdAvnm0mOuidKq3Y/liYJ ChaEhNCCzgABOYDP5RNHHB/ei33w8Gh6Vrjf0RihNFoSccoj6rRraIz3yTPJ j6rudQw+HZqsHFU+HZy6UtcSlHqJLZLYApDCYNgkziM46Mbr1h7zysz2p78V Kt9j0QfsDu3zat82AHWAIQ7+dTg0QPrp12eDVWtYUik1A9OaHvOa3qbMxnWd cXVGM9ezYJ02LisVM3KNYcBkmdCbx5e2zGuf15d2DbrFEYVarpvv1s4PmFZU S5vG5Y+L1jWd7Xnr9uLHn5u7P3dUSzNRVxIetVa/Her4ubd3KjvzD1vqxvYl Sy9z46t452qdz78VXuvyyB/2yh/2uDPkkTvAT35B9D0LIjrZsAIhsA4oKs71 JOVILskvE/BMYx4vFeS0ClKr+LG3ueE38AFXEaLjKOFpPz5w/VrwvTJZYqJf YEiUKOyEMPSEZ3SC5OgpSfTpqKuFl+vkRe1DJd0f7rUPZlU0+CdkMN0kFCaf zGCznXk+YeHn8u8+6+tr1OqLmptEof773hIoxAbX/19tHzxkV3j/7o/fPza2 rQtmpXVtzryq3fq6sbK9uLimtW7OzRn6F5YVtupGqW5Tz3UbzGPGZcXKjsW8 btAvfZjVvlep5Bp9l0rbbbCqTGu6xVW9wayaMystm4b17xtrn9e+/PoSni17 1l47saj6+OtbWfOr/7GDwWgeBN8LjBPF3PhS5/R64fVOyZ0hSf6wZ96g+Eav U2I1RnjsMI5mj8DZsAJjqVhXGSXoNkGaSwq6wTlTJ7k26JE/Jrre75T1jhL9 HOWWgODLJDx8WrxH0dWjGdEeUi8P9+BoydF4z6hESeQJ8dFTIdm30p/+nfvm fWH7YFH7YHblG9+kbI5HANNRwOFyXF15YncnicTFL8g35HhkUFQwm0uHw/fv au33re9QBzAEAkcMTox++/39++/PH3eWzUs604p2cV1vWpldWtOs7RjmjENz lsmlDc2stl230GtYHDVZFeYtw8LKrN40qJltnZ1pVs7aaqzuhSWlaU1rsr27 qtFZppTGMY11xvrJure3d6n8TnhW3PKvTcP20rBhCkUmH8YyMIIowpELxJBr lKPXqbKb7Phyp7RG/oVW56wW5omncNeowxiSHQxjK+3BGAqGLyMduU4JK6TH lrDTG4XX+7wKp7wKp4V5H5hnWzG+V5GiRHcaPiGMX5AszTriFsDluLh784Nj RVEJ4sg4fpDMNzEn4UFtTm3breauos7hnBetgak3uaIgjiPficsSuXA8XXnO NBIJCWURsGJHliuHQQRw0H8d3TZS/e+hvzx9xeufV7/88+3bz08//vm6+2Vj dcdiXNMal9XmVc3qlmF+cWJucWJte14316Ob7zWvTNk4trg1r7cqtAsDalWz aurNpPKtStNtWNJYNhbmlyaHp16395a3d5UPjzbYzoJve18ftVbwY337FhXz 6yb9zoJ3VNgfh1EInj/GTYZxP4ESRiGFsWTfbEZU8b7ax94nBV1HOgaAMQQw AgDDcVA0DcENxwfkMGLuOZ2tdUxrdc5+53apU3itz/X6APd8ByG0AClJckTD pXxastQ1UcwKJJG4VA6RJ2R5+Dn7BLl4h3hHJchuPMqoaL7Z0nWjuTuuuFYo S+fwPdlsNodBFvAYQh6DQcSSARSftz+HS+zMYtLJWAwavG81hBwCwcuqC/qH Sm2Y/N778eX356+/PtsCcHln0fxxzryut35cmDdNaOZHN3eNSytTc4bBxZVp 07rasKHRLE6oZttUk/XKqTeKmSaNvs9gUc7oR3sGX7V3VU5Mt2kWhpfWtctb po1vq7kVeREX44o76hZ3VtXrqpvl9//rwCF7EgtCdYXR3OEsMZJ3BOMWCbhF 4Z39yS4SPM8VT6Vh8UQkjoDEAigcGUGTEMRxRBsPowqZsue80y+4SS956XLn i73cjPekyPtocTIFAmUiYWI8LpBECMUDfBwRINCwNBaRzWO4CN2DosIzbic+ eJFZJ08orfc4e5noLiUxGFQcjoLdnwjJxKHISCgFBeMQsHwG2YVN4tJJeCwO ikIcPGxHZHPHZnrkzXly+cO1HdOPvZ9ffn3a+bb98dOqeX1f6jXzg1OKFrW+ b2PHtLKpVet6Vbo+pWl01jQ5axyb1TRrFI1qbceMulWhah2daOwdahgca9EZ J9Z2zKu7S8s7ttTUuPx19Ub13YvlN59114xbtLMrUy/ktQfADnYIIhjPARN5 UJorgilE0pzQtl/DAhgcxrZhARwWwGNwODQOiwEALIGOZvLhjsFg1xiE8ATg lUIOyWfGVrITm+hJr4lBd3DiVDoaSUfCPSgUPwIhkkiUEEhoHB5BJKPJdByV zREFeBw7H3KhKPzGM5/0B3T/WDjVEYXGUFAoJzzOj0c56s6NFbJkQrZMzA1z Y3nzKI4kwIYVHI3+869DEqlUa5kdGq5/1VDQ8K5sZcf4e++fL7++b+yuzVk+ 6IyDE9ONI6MvBoYrpmY7lOqO/sHayZlOhXFkem54QtutmG6cVbUr1e2z6rbR kRfvO8uGR1/bCGYTNOumYWXLYtkw6ld0ph3LsGnSM176ZrKpTdmtW9O/7q4F Y9F/QQEI4AgmOEPJfDiFhwEI6H/nnyL/fwLvvwtjW2gMBsABAA6DBxBUAZR1 BMrwcaCKYNxQtCAe5ZmK9EpHOkWiXWVMwCaC6HCBMMbVNQQP+BEpJAyAxBMB GpNAZhLoXJZ3qCjukuRckbMslyCOgREYAAbtw2ekHhHlH/etyoh9eel4w+2E 1qILL24kX48L8HSkYVBIOBJ18JC9o9Bt9cvWp69b5lVdS2dFTf3VCeXL3R/L qzt6jbF3YXFYoWwb6K9sbMhtfZs71F/+/n3ppKZjcmFoRN3TP/x6qKdqYrLl w/jb0WFbTdCwYJO1j6bljbnVbePytmn107J12zK/NqddmZvbMXHD+Tdq8kYW J/UfjfKx1wCDdMAeAcawIQALiqXD0PvtJDAYHA2D07A4Eg6DQsBQ+yNTEXA4 zLbtt/nh0DAyB+YUjnQ6CqZ6Q2h+cHYwhBUMono6YJhwjpSGx2FAIBGRKGNy wgDA3xaBcAyGymN6x/IjshzD0/gxOaKEAnFquWPsFaJACscSuGQgJUJckhpR kR3ReONkZ9GZ3rL0wcorvRVX3txLSYv2YxHx8P3rG8R/Dtk/b3rxc+/n999f VrfNbZ1V93KjSvJPdnfe18y2WCxKg3mitbGw7nFaU+XFnvbitqaCUUXTlGls cLyp733F2PCroaHa/p7qvt7aaVWnVtelnW3XKFuGekpbX1yanG42bS/Orc/p VvW6LYN3ojTxYU7TRNfKz832iQaqE+OAHQSEZYABBgSDA9u+B4GEQWACEkEm EoS48JzxaDYKQUMiyAg4DY2iodFYJBSCBZBcP7TwLNxZhmCGQxn+DhShA8Cx QxLAZDGTSEY5gOhQSDAOiCQT/HCAEwpLZrkKE+5LCzr9C5q9br3yufpKcr6a GXYezRQgUFgRi3rxmG/ZhZiXuafk+YmdhWe7H6UPVFzoq7rYWZpdeDZSzGIg Ech9RzcK+0T+9/TcgHq+f3nD8PnH7qxyoPhK/MU4UUNNhmbmnU2jplXyN88z /y7L7JQ/ePPqWl9/zYfp933ddUM9FSODtb09T3u7yjoa8t8WJzUWxtbnRVbl hlTeiu19+3jBMGHdtX78ubX2fV21rJGmhOU1lZa2Vm/vfelRtZG4tD8PgUAY OgTLAKHQIAQcBkdQUfCTYk5hdOCNcN+zYsdTruw4Cf+UhyDeW3BKxBOQMHAY GE7m4dyTUeJUqGMYmC4E4eg2oOyQAITkziFSMWAIAIU5IbH+BEAK4EPwFIkw wPv8s9CSruDidr+7b/1u/i1JK6dJzyLITmgE2otFPxMgTg8VX4n2KTkbXpMj e3ntdGNBUvP9lJbilIJzYW50si0K//jzjxPJSeZPluGJd3rT5MqGbnN32abt poXx8uKsSxmhZffjJkZr5lcVkxOvW2uvdbU/amq+MzTysq+/rl1e0v++rLu1 8G1lVsP9+L9vR9ReCn5+KbKmJKO9oVg91WlZ0yzYamvrlHJhVGUcX/22cexq Qv7bx3VDDead1c7JNiQJe9ABDsYwoBg6GIEAwSBICExIADL9BcVRfkVRPnnh 4oIY73tJoY/PxZYnR96LFkfzaRgkzB6DR7nGor2ykJI0KDMQhKbZwbF2CAyY 6MoiUtAOEBQUSoEjRRiMLxYXQqL4+Uf4ZFUE3W2T5jV5X6v1uFQpSCmhBZ5F 0PlkHMGfQw90pAopKHcySuZGz48W54QJz0qdr8i8HmaG3kkKdmeQkPtdQbAn lY+3v21Yt6zLG0aDaUqjHdYuTK1sWte2TeMT7548yC6+EdPd9XBK0dTT/aRv oKJZ/nBgtK6j83GnvOhdY15d+bm6PFntlYjn2Ueq7iS9lz/TafpNxkmTRTGp 7x9TvVfph3Rmld6q+/zPt7K2Gr7Mp9swaN4xP39XcwgMOgwngAiOYBzT4V/7 PRwC8aDgs/0E96J8Hx4PLIsPeXYmvDItpj7r5MvM42XxgYkePDKABqOQCKoI JUxFe91GOMeAcAx7OM4ODkAItkOeirWHoKFQMgIpIhDEOJwniegREO6VVuJ5 +YX35XqPnCq380+c4gvowSlYFx82lRYt4MZIeN48QiAbn+7r/CIlIjdaIuXi j/s43TkXdDcl0ptHZzOJx09HnUyWGbdM3/d+/Nr7tffv+r239/n3l43d5aVN nWFFVZ535m6yT3v9pabqjP7eR3J58fikvP3dk5aaCw2Pkl49TKi8HvnoYvjz ovTezmq9tn/ROL64OKmbH9KaJoyrOsuWcWnbbNowrX/+WPLmqeNJ74K2pyvf N1JuZ/33gUMQgA2liUB49j5WICgSDPGhAWckjue8HTP8nG9GepaeDq8+E/E8 LaY0OfL+SWmClysJt9/KBAJoIE4wTJQAdvS3x7JACII9AoCRXagIDAYEtoUh Awv4s7jeAMGTQAyMSPBKKXVLe+R6rtjxTCE34S7reC495Bxtf9qDS5rU/WFy xO3EIzcjxeVJYf13Ul9fOVGUEPgwNfLNvbNPrxw7GSw4kxRe9aqkqqMmsShT dutM4v3M7Ge5BW9Lmkaa9Bblzs+tza+b619WZmcGCjMiHpz3qX94urHmoryt qH/4ZWdn2bNb0S/vx1fmHyu+El5fnTcy3qqcblZMNM3OvFPNtPd0VI5/kKv1 wzrTpGFVu7Rl+br3rUPVb+9JEKWEGX5uuUk9/zh4CIznwVneUBJ3v50EAqei MUFcahiX4k5AOWPAPmRkogf7Yoggkk8N4BBOerDDRTwCDg3GsWFUTzDBCUQV OJAldlg2CEG0R+Ax7ID/A+WgPlI= "], {{0, 133}, {100, 0}}, {0, 255}, ColorFunction->RGBColor], BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True], Selectable->False], DefaultBaseStyle->"ImageGraphics", ImageSize->{66.66666666666325, Automatic}, ImageSizeRaw->{100, 133}, PlotRange->{{0, 100}, {0, 133}}], Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], Image[CompressedData[" 1:eJwkumd0G2earTvr3D/35/117lkz021LJJFzFaqQKiEVUMg5Z4AgwJxzzlGi JCZJVE4MyjlZVrIsyQqWLNlyjt1u22272x3n9jl9P/aAH7FALi0K3Njvfp9d 4KZ0rbv8f/zbv/1b4/8N7typVqqhIdXu+X/AF76axkK+Jpc11zTl8rkGRfr/ At8cBp9Z8LnxmPEEtDa30uiUUTYR6VAYHDa3Ox72RgLekNfndzudVtptoV1W M2NzE/YA5M6LvHU8Vy3LUcumM0IqgmA2LaGzGEi31RBym1N+ayFkb4g4a8L2 iF3vMFv1ZgeutxostNtvSyRDmVQoE/WEnSY/TXkotYtU2zGlTg4jMrGAx+Gx 2QKxSKxQKA00ZnWTrpDOG8FtHrWRkWsIOYqiMolKJjEqICepCJvIlFUXN1Mh o8aEQQSO68x2eywXae2tnplvWjrQuOtI865jLbsOt+4+2nXg1NDaxcHj54dO XOhdPd535FTX3tXOXUfaFw80bl+unllI9Iy7U1WkwcITC0tZpVwuVyaR6HDM YjGbLCYDrbd4vEaHV2Nyw5RDSjhQrYW22mORQCrqTYXdUb/D76C9QCuLWc9Y lbaA0JXjeurZrnqWq45rzvEIp0Stx3GC0RNORht2mNM+Ju8x1XtttW5L3Ky1 GYx6s5U00YzD5gt644lgJuZP+hxBi8GrIzykxkOqbZhCJ4cQiUjI4/J5PJ5Q KEaVMKVX0HbcEdL7olp3CKPtKkKHIigikSgkIh0iNStlTgwN6TVhI+ahUBMG EzhGGMzmcCbU2FWY2Na6+3DHgeMd+9bb9612HV7rOXx8YPXU4Pq5ofVzfasn eo8c79p/tHP5cNvSgea5PXVbd6Z6xpzpKo3WzBeLS1llLDZbLBJplAq7zebx +50ej8PrMTu9mMmJaO0y3ALhRr3JGgz5MnF/NuJOBZ1Rt9nH6M0mRm1ySywp rqua7WtmeRtZ7mq2KcYlHEKVTqFS0YTGbTSEreaUg8nb6SobXbTSMSNlN+j1 JrOWoZ0eWzjiyaQC2Ygn5rJ5acpJYS5M7SZUNhzVwjJEJBRy+Xy+gC+QiBUa iDSozC7CGdF6EoQzRJidGpJWIggwlUoq0sISGpFZVXIgl5dSeiiFUQXhmAbT 03p/wlvTmh/b2rR0sPvgqZ7Dp7qOHu8+dqLn6PHeo8f7V04Orp7p2xBqpXPv kY49h1uW9jXv2FM3s5TsHnFmqgmDnS+WlLHK2BwOeDYKOWyxWAPRuDccs7o9 ZpcHtzgQnUVOMrCG1hoZp8sWD7nLY/502Bt2ml0m8Pva5OaQgMmxnfUcbwvb 21zmqOSYomzSwQMDpFBpVQo7QbqNVMSkS5r0GSOZoDQ+irAaDHqj0WClfQFn Iu7Ppf2ZkDNkN7sMpA1X2TVKJ662ahRamRRoJQJPji8UyhCZWotoGQ3jodxh nS+mdUZJi0dNGjWoCpdJMJmYhKRGBGIUcotSbscUVg2ilUvVqAbTmilnyFVs zgzNNM0DrU73HTvXs7LWuwKEAnKt9xxa6zm43n3gaMeeQ+279rcu7mncsath 267qqflk14g9WYkbHFyRqKSstIzN4vD4cljOWB2BWMYfSwOhGI+PYhwqgwUh zUArUmtwO8zxgCsX9adDnqDdZDMbMKNVxgQFtnKuu5nraWS7a0vtBTYdZuEW HopBckSJIiYcc1BYwEBETVTcSIW1mEdHmo0GrcHA2JlQ2JOO+zNxbzxg94P0 ojBaCTMqxIYpTUqEgmFEKhGKxTyJTICoYIJWm1yYzU95wnpvlLIH1UarmtRp FEq1RIxJRbhEpIWkBkRmRCFaARtRGQFJFYhGSdCkzW/N1MR7Jmq37m7fs9K/ cr5/9VTPkfXuwyc7Dhzr3H+sbffh1sV9zXPLDbNLDbOL9VsWa6YWimOz0dY+ WyxPGJxAq82sEmAsNk+AKNRmp88XL/fGcyaPF2hlsDtx2qzS6hGMwAnCYdbH /c5cxJcJekJum8lEo3qLyBQQ2ICvKlmOujJ7ZQmTKdN6OQqDSKaQSoEVIFKB WHCVT4+HaDJEbxgsyBjcNqvVbnW6bdGIKxXzJELOoMfiNOnMpFqPyhilHLiL wcAYo4gclsGoBFGJ1QSsN6sZD2bzEXYfaQVxalNojUoNAUMQLOKrhHylkKeR CAlIRMklWrlEh0IaSAohSkijwxg3HauItA2Vj87Wze1p37vafeBE134QXGst u480L+1rmFuu27pUNbm9any2anxbcXRLcWRrcXhrqLGTCaY0FMMViTezwBBy 2XwRqiFN7pAnU/Skixav3+rzmd1ug5WhaANGEhRBmPVk0GXNhfzZoMfvthlo E0xaBHofxxRnMRG2McM2JIFQfNwqUeIoLFfIYDUEUSgMtPLq8KBJG7YYYlZT 2EIHndaA2xHyOlNRVyriTABTORgbyHstbtLIwezYCaUFU9AaFYljKg2B4JRS R2Nmm97uNboDRqePsroUpBFS4RJIKRSJRDyOjM+B+BxEyFOKeGAecViKIxAq lYikkFSJKfUWyp/y1nTG+6cqJufrduxt2Xm4bdfRlqVDTXN7a7cuVk1tK4xu Kx+aKh8YKx8Yzw9OVAyNl/ePB+pazf64ijCyheJNZZzNLC5YyXIVSYOXt7za W15r9fodwaDV57U47QazidJqKQLXk5jbaox5nHGf0+Oy6kwWGWnjEK4yfaBU F2BRHrD+IJLWaPV6HckQaiuOMRjGEBqnnvCbdVE7HXeYY3YmZjPFneaEx5bw ORJBeyLsiAfBf+z0u1wOq9lm1jr0mItSOwiF04hbGJPBbDFabDan1+n2uvx+ TzDkcPtpq0OBUSIZwhfJQIKwuRwelyXksqRctkLEB6OHI1I1AsFiCV8kESEq hDJT7rir2BrqHE0PzxanFuu2L9dt3w1yqW5mvnJsa3F0qmJoOjcwnu4dBgco lukdyXQPB2paaH8cwXUsofj10rJNZWzgK0iJG10hd7bWlas1Ob12f9AR8Fud DqOJBr5Sq5WYGjVqNV6rye+0OGy0FmhF2YFWJVovsBMPN0M4TRt0Xqs+7qQz biZuN4ZM2qBVH7EbY04m7bFkvNa0yxx3GJOAuHz2uNeaCjpScXc2G83ms5lC IVORz6RjCY8jyhjCZirsNgeCfn8kEohEo/F4NBaOBj0xv8vvtDO0SaXCBUAo Lp/F4XC4PB6HI+SyZRtaCShERqJSzb+0ArAhgBUQZlQzPjpW9Df1Rbsm0kOz hcn54sxC7cxi1ehsfniyYmgy1zeWBfr0DKf7RrIDY9me8VzPeKi21RiII5SR JZC8Xlq6CexCnlCMqPTOqCNR40hVMm6vxe9zBLwWl0NnotUEjigVcgRWoTCj o9yM0W4xGswMqnNwScdm0lZGWESYUUMZvFamGHC2pLytKU9D2FHwbpBVxmdN ++xpvzXqMIYs2pQXDLIn43dl/I5c2F2Ri1Q3FFv6e9vHx7qnpjoGOupqyivT 0fKYN5+OFGuKhdqaQk1NRWVFJhvO+G0Zl9ln1pkpjQqWi4QSLk/AYfP5XJ6I z4VEfFTMVwN4QGU6FUSgkBxMp0DAksj4sEZKMBpXjMnW+5sGop1j2cEt5SPb KkZmK4a2lA9Olw9MZvtGM90jue7RXNdornss2zkKTrS+wxxOoZSJI4KAqYBW pTwBV4aoTC5LtALEvsHuYNxuq8dtcTq1RlqJYTIEFUtlkEyqIzQus8FpMZrN No3eJaQcZZiZqzFLcTOFG0OMuRjytKYDbUlfY8RZH3HVJn3FpCcXdSQD9qjf nkmGqguZ2kK2kI7l4r7yuKepqdA+0je4MDd+9NDk2srI7oWesb6u/vb2zuaW xvrW/u6O4cG2/r6G1vrqmnR5wpcOWD1m0qBBQBZJBCIhXyjgCUQ8HiQWqGAx icooRGpQQzSOUAoYlYoFAmEpX1gmhARKCjLYcXfCVt7oq++Jd42leqeyA1sy gzO5/qls71iyazjbM5ZtH041dEeqWyJ1LdGG9kCxgQmlEMrEFsGbWNzXWewS Lp8rlcOUmfanzP40ZqApmtabzTrajGsNcpVGDClEYgSSygmNGixEr83stNu0 Jjuks3JwE09pFKsMKiXu0mIxK51xmjJ2Q85tynsZoFVVNpCJulMpX2VdVXt/ f+fwUEd/d0trQ01lqpALNnXWDM/Pzh09tvPSpeUbN+ZOnNp6+PD47sW+2cne ybHBLTMjC3ODs1u6xobbBvvr2psrqguJZNjpsFC4BhFLpQIhQHsgCSIVUihk 0qA0hpgwhNagOqCVTArgrIwjKOGKSsUwHyURgxNzRU2pGiBXpH0k0TWR6Z1K 944nOofiXUPJrqFEY48PBFGi4A6Xu8JZWyijdflh0sgSw6+x2K+xyjazOaWA Y1QkxnjAJMJqtYIglAQB7uVqXAyr+FIFX6oWwRpcjbnM+ojbGfA4aatZobcI cJqDaPkwLpcrGEzhpjC3DvPTeNSmT7nMVXHgKx/oeuXV6ebBvoEdS2O794zu XOgfHWyoztQUku2D7ZP7lnaeO3vk9p2j997e/8b1pQvndpw8MX5gz/DuhYk9 u6f27p1a3j22c2l4YbFvy7b2kcmGrt5CfX0wHgZMC1atXCxSy2UEIlMKeCiX rZFyNTKQWixSLpWLhbyNJBNs5vBfYwtKBHIOjEtIK+6IMelaf313uKk/0jIQ ax0IN/UFG3s8tW3ebJ09mNZb3Fo9oyNNhN6CUkapimCJpa+XsTaxSks4HBYw qxxRkAbMYJOgKKRSyZRKmVIlQRRCSMmHVDxILURwtYawm3RhNxP2OGw2BjMY RBotT05wZSoZJNfJZSYFDHjSSSljNn3azRSS/mIikI36cnUVjROj/bv2Th05 NnXw0PDEWC7uTcc83UMdI3u27bp4YfXe/bX794/cubP3+tWdFy5sP3F82+qx 2WNHpg8emNq7Z3zn0sTizunF3SNzu/qmtrUPjNS0tiRTcbvJoEMgowIh5bJc 1Ltr+9C1y4fevn18oDMlYm2SicF0Clgc/iY299dlnNc5ohIBxIExCWHRWMN0 OG/N1DnzLc5MkyPdaI9VWYJZozumZewaAkMBcoiFcrEMtAeBGN7M421iszaz ywA1iMRCGJJolCiF4TyplC+TCSBIjCACCOFLUK5EwZOqpHJgK1Ck9QGHIey2 eGw2gN9SDSlAMJ5cKYMQQiYDLcOkQpw6ddSuLw/Yi6lALgyWlzOVz1T3DnRs 2T4yv9g/NVVZnWlvSV8+f/CzTx/cvH/mzM0r63fvrj24t/bWW0fv3Fl+4/ri hQvzp09tW1/dcujg6NJC9/RU5+ho7/hE3+xsz9R0W/9wU0dnoVgRCXrtekoH Cw/PDf7ty9tfndny2emt//XN47/8/Kwiay8pKeXzpaXsDa1eZ3NfY/NfBx7j STkyTKikFXoPYYuRzjhhC1HWAGEFFdiBG2xaUk+iSrVUKudzJFyOiMtlcUBS sTaxy0o5LL6Ai8IyrRrVqVGtRsURi7mgWUhlfCnMlcA8CcITo3yJQgSsBrBM q3NbdCEXA7aegaYRUi9WaEEHAVppZLAOltEqxG0kY25TZcJblQqkwFK1Gz0B b6RQXdk50NzR19BStX5uzw+/efLPf/7jn//86z/+9xd///t3D1/eO3v/7trb bx27e2vfnZvL168tnDszs3oUmKp7ZrK+oyNXno0l4slMJl9ZXVXfXKypSyQT kZDXYaJ3jdWeaAs/W2h72hM66FF8fefwHz+7+8PHt2k9srkU/KYCsMI2byQz /7Uy3q/L+CV8mCVWciFcqtRLNQaJWgurtZAaR9SYQU2ZlIQRRrQSiRoMNY8r AejG44LRK+WAH8WWANYFlVOLuQ0kQ2o4YilXLP3XvexfB8gF86UISHgUVesI rROAk4MO2EyM2YTpTDLcKFThUhQQDURAEpBaQYsxG3BUp4L5qCfkMrkA5lto uz8azdXkqor37l/+5fPL756b+c2LG399efEPz0//7cX1/+/r+7/8+dtLj24f vnVr3xtXd106P3/m1PSxQ0NLO1oHuvMVOa/FpFWgWqXSrDf4ff5gMOQDy9ps rIjYV3ozC0X7tBu92eA/nWHe2lb7+bmt/+fTt08fntlU8is2D9QTLqBuIBQ4 m9iC11mCTRsGA/tRXCaWgCziiGRCsQyVySkUtSvkLoXciUJ2BCJBa+eBDsgD WpWw2AB6pRIBgUB2SuOjKY+O+G+tuCIpXwysJeNKJBtHLJGAPowoSTVm1ZF+ Kx12WOyMhaJtsBYwg16q0qIoolXCPjOV9FqBSpXxQCrkDHitDvDvXHaLM+D0 xy9cPv35lcVbixX/+OcvP335zs2+0Hql6XBAcbsz+cnWtq9ur5568HDnuXPb 1o9OHDk4snO+c3SgrqkmDX4Qo9Mq5RpYAl4SAMdGnd5sMIDy1ZVy7Kj1bs+7 55LWYUpSh7JO98Q+WRv46enp339xz2DE/+PXpWUc3msl7NdZvA2JuMLNHMFr Zdx/PRaUcnmgEYNMY3P5Er5QC0FelTxAKIKkwqWEdFKxXMADGbWZzQa+4vJ5 wFc4JLXhSpcOc1IYEIovlgrAkUhFEqlYJJEAupLIYBkEkBRXqWgS95jpoN3m sjsNFrfS5EB0VlhjJAjcSWsBkOeiroqEtyLujwN5fHaPz5vIVZhc/p6h/h8/ ufHejsJbc/m39gy+fHxxMkOPu+XDNmSLXbGN4DzZ1vDHTx/sP3lscOdc78xo 63BrS2d9Q31FeSYcD7k8dtpAqDAlooRhTIXhGKnCsK0V/qWosTdAbrHjXTpp QLJprT34fLHhd1d3//Xbx/dvrwkh3r+/tulf8c7ezOX/uoT1WgkL2KyMzWdz +BsXEjl8ALQsNhc4SCOROFCFH4wGqXSpEYNMCvP5LC4PoAIQXMDnA74Fdd2s QBg1atMo2QB3JeAmlYnFqFRGQigFoTpIAZBUJYcxBaLVKEHVdVssHofL7Azg jpCa8eKMi7HbI15HJuQC1L3BjWFP2O/w+ZzBUMQXjIUz0Ttnlp/MFi7UMjvc ymGdOKYW2KWlPQzc50KmMtpTLb4Xs63frUyd2DXSOdDb3ppvaUx0NWU66rNN 1anK8kg87HY7zUY9qVYqIBh0GBQgQ7cTb5aUJVFJSlRK/fp/DXmovRn9/jD5 Zm/mi8sH/vGbd65d21/KY/+vX7/2+kbCs3+1ueS1klIwUFw2yCK+TMADVUjE BxHOZ7M5ADIwscQEyWwoZEFgDUA4vpANHMjml260Ax4qFuOQTA+WL7qx9NlC IU8ilkkAUYmNkMyOIk4l6lKgJrmckMtBfyfBCiAxi8VmdfhM7jDhilLuiCUc CybjuWS4IuEvTwTiYZffbfG6LOGQJxEH6WJfPzl3faRyu0M+ZBB24+xmgpPF RWFMTvFZcYS1nNLd708eC2nX2pJDXdV11dnGfLA16+/IBdoroi2FeEMxXpGJ BIMeo9mAKpV8kDMCEYIopkO6boxFlf6nRyHYX2W/2epb9GiGLfC0HX20rfU3 t/f89du79+6sCEXc1zaDyCr7dcnm10s2l5aV8tksVCQkZBJKKlOKZQKBiANq OIst5HJgPk8h5CnEYqFQzOELS9mA0ARlXL5YwEPEEgz0F7lMj24sfY4QyCyE xGIKglwKOKBGI4QqiCkcSrkWluGwTIXIlRo1qad1NrfeE9aGE9ZsRbCyKldb rAINOB1MhJ0eEOkOk9/viMc9hXzwrXcuffbG/hEdr98q6zMIR0yyXWnrsebE 2d7M+mBhKmS8Vh3cahGfbAo8Wt9aVYjHwta8z9zgtTT6rQ0BW33YWZn0ZJMB j8dF6HUQioL8LAWvs0xS79BOulQ1JuGuqsDxase+ML7oJ7bHDAsZ5mhz9Lf3 jn777vo/f3d/eanz33/1a1DoXi/dvKm0pIRVIuGyMKmYVsgZFCGlYrFIwOHz WCyQ4Gw+QAUeV8AH0yko5QlLOMJSjgDMqFDAh6XQhq8giV4O62FoI6wARYjE ZlQRIdQpLZXSkgmSCGBqsxwipNCG9ZUqDaXHrDbcF7TU1oZ7uvM9vY29XW2t DeXpUMDNuBxGl5MBYRWL+a69eeLHF2+uFd1jHvVkiBizy4ftyFSA2JEwHK51 X+6I7ovgU3ZtPSHcV2E4t709GXL6rFSCIcst2oJdXwlQzaKNOw1hv83lspE6 SipHWAJxCYBMngjsmyYHuS1iHA8QPYx0xAZtcaEzAfxoU3C1OXx+qva3bx/9 /tH6d5+c9vvx//nv/1nCLt1ctrH/ESGPgqRGdOMdDT0sQkUCcGNzOByQYlyu mMcX8PhcYCquqGTjCIGvuHy+RCxB//syrEwMPClDMaFIoBZJLLA8pFElCDyG 43Ec96uVDATjYgkklQKeR0m9wmbTpdLB3uHcxPb6ufm+pYXW3s5EMuL3Aqo3 MIzW4dSdOb3vmycXVpr9u2O6y52JgxXWSZcShPmkXz0TVG8NqLZ70UmLpBVn D9rlg3Eb2As+j8lvxP61jJRxrTqlV6cNWNRMeaw6m1mn12vlqJLNFwGt2KCa QTCJKeutumGXatCvHvdpADyM2NHpAL6/xrNU6719oO/7l6d++fDCwwtb5RDv P17fDKwjEnA1ErD1xEZEYkZlOkiiAkMo2HgbhM/ZMJVUwJcIBHyBqIwrfp0n fI0rLOEK2Dw++JAKAc8LUTFfIRYqcAMEnCbe0MqvUoY06qBKHcWwgEplkf4r 7sB+lCtRrUnjCdhr6kMDk9mJbc1Lyx07l8vbmoKxqNvrtlj1RhrffWDLxw/X z49k95TTFzvil1pCu7PGKbd62CQbc4nHUvrBrHm0nBnOMRM+sj/rrGqoiidA f9I7N1Y27McVIUwRxtAYqYoaND6LFpCDUadVqDCeSLbxrqEEViqUajWuJzQx oyak0zhxxI3DMVrd5SG2JA3b8va9baGPri98enPvz89PHJlr4rJKuGweJOSR Er4eBlpJDXIIB/nM5wp4HOCljVCSiJQSCSICgSVm8UWv88Wb+KIyvogNvLYh qUDM58mEfLlQhJA0AiO4WGqUSu0KhVetChNEUqfzq1V6qQwRi8VSiUSp1oCi Hc14mjtiQ5OZ0S2Zkalkz5CvstKZiFvdXhJXzWzre/Xo5Lmt1XvrHee6Ypf7 UvNRHdBk0AI3G6GMxxROppLVdRXtHbU9PY3d3VWd7dHK8qDPYadxRiV3KGGA On4N6lcjQQ0SIhQBE+kyG2gtAbJdKleIIbkcUeIYRhEYRRJqpUopl2vkciOu 9ln0eYexO2iaTFmWGvxvLDa9ujz3+a3lX14e3zWYk/BLEAmPlAoouRiXixEp sBAYMBZgBj6HK+HzFRIhCTY+oCQJxJHISqRwmUTOFsNskYQn3JhVkVAgFQog oQimaAV4sQRinUTCyMFzVjpR1I2gdgQhJRI5kAo4Vqu3RSq8lc3+9u5o32iw e9Bd32arqLKXF2zprEpP9fQ3fPTsyo1dXYe7Iif7k1eHcweqLEtp8xCN1umF UY/Ll6uP1NQn65tzrR21/UO1fUMVrW3BXMpmNelVcq1MTEMiRiq0QmInAnkA 4qoRF6Gw6DQ6QqNRq5QqFQKepVJJgi1DqAlMoUYhtVxGonIL8BhjqA646v3W jrBxLGs52p94cWLqs2tz390/9P2DQwPVbpTDwaQCtUwEi3lCAJscsADLQFbx uTywEcH3KTlMyFFErpAoMbYaL1VqSuRoiQxmyyQcIdBKKAE5LxIpaZsSpwDB kBKRDUHdao1XrQ6qNQ4U1cogdIPfYYM3mGgZSPaMhLoHvM2d5nwR80cwX0gf Tigt1vr2yhfPzz1cnzw7Wjw/Xjw/lNtf6dhbYZsJ6Wp00qiVCoQToXxtor4x 29JR7O5rGBqtB1o1tYSSCRNtIBGIkkr0UpFRIjTJxDZYapdvAA8DkAZH9Tiq xdQkriEwDanW6HCcwtQaFFbCUjUsI1C5CVOFDVTBZa4LWKodVG+cWWrw3F7q fHFy8rNr8z88XPns+lJrwiJhlcAgkABmcVilLNbmspJS7gaay0V8NSQFdEQi qEKNSUgdx0iX6A2lBMlWY1wE5otFYiEfEgvlEjHu9lNWB05qjCjsUal8amUQ 14RxzKlQ0AiigiFMZ3BXVOXHZiq3LcQHx5h8Ue0JQVa70uaUmEz59uqXz668 d3Xh2tb6M33Zq6PFlZbgznJmR45ptqJhI+rzWIORaDBfDYSq7B2sGx5uGpto Hp0otraFknHQMUHhomRSo0zCIBsS2RAZ0IqRSy1KxEKobHrcZqAsepLRkhad zqgFtgKmglVymQqWkYCoMZVfh8eNZMZExnTqOo9hS4XtwnTtk5XhD85MfXvv 4I9Pjzy/vsWilb3+6/8EoAVUer2sZFNZSQkwF4cDiwQamUSLykngW51ObDXx 3E6ux813OLgmE5vCRCpQX2QKWKySQ0wq5wwmHYzZpyPiOiqpxZM6MkrhdlSu Q2BcrTK7/L5CXbJvsHLbjnj/sCGdR91+1OkUkdpgbeHFq9vv31t9sDJyfVv9 lbHKM53JY43+xSzT7yeKOnnWqIk7zBFwy1eVt3bXDQ63TU93b9vWuWW2aWgo WSzYHTYdpiA3ZlBqVcjsSsilQhwI5FChoKt6TNqwk4l67CGXxWuhnbTepMUJ lRw8bSAXrpDrVQpGo3KSKj+p9GOIQyWL65QjGfuRgeyDI4PPV0a+urHw7cOD vzxbPb27VSQq/c/XS15nlb5etvm10s2bWWX/3WI0UjCDUhJFEIMe9rqFsSg3 HuOFAhyXk21lBCajnCRRjRJVocHapmCiEHQ6klZjpdWUp7U5Wpc2am1qdKO6 anFTMGrPVrqamsL9fc6mVm0iq/L5xIyJiXgfvHv1g/tr756avrOn5eZc042Z 2lNd8SMN3i1RopFBq42aSgbPuCyJWCxZqCt29tQPDbTPTA7sXBhYXGgeHcvW 19k8Li2uBABjBFohYPokVpnIrka9tC5oN6UCrkIqUpmJ5uOBmM/msRjMlEar RjQIjCEwicK0WmHHVS5M6cZQjwZxaeRuhaTBbdjbnb653Pl8dfz90+Nf3975 w8OjPz85NjeS+4/Nr/+qpBQIBaxVwmGBFoMIga/EJCRWKyDEaET8AXEmLcxm +fEYNxjg+Nxcpx2MD2TUS7R4rKElkc1URFw1gJmdTBWjL2e0aVrrIjWECsFo vT4aN5dX6Is5R1sD01hH54uEPwRbTedunPzu5bXnZ7c+WR24s7Pl1lwTSKrV luBy3tTrVlUbVXUMVmUhs25bJp6qqG2q7R9smpjo3DozuHPnxL59nVu35Jqb LD6vBlMoZaKNy0ecUh0kclFqr1nnYQypoLsyE2uqLm+tr6gqj6UAstoMFj2m x5XAURtaKeUmXOmg1C5C6cZRL65wqWE7KglrkbmWyPkdDY9Xx16emfr8+tzv 3j74+/vHvn5zsaLc9P/+6t9fLy0BMF/GZoGCgwj5aokQA/tLJVcadLDPK0in hLmsMJPiJaLsaJgXCgqBXDa7wExnKvON+WhnzN7stTQ7zPUOQ9GiyxiogJ6y GnUkYyYDIX2+3NxU6+7p8Pb0+5q7dPHE7vWdv3z/4su31p+fnXl0rO/5yvBb S22n+1MH63zjEapIK3KkolKP5s1Exu3IJTJVTW3NI+NtM1t7tu8YXV4eXd7T MbM129puCYYUGhXYTSqltLWtfN++sdX1bfNbO2a2dbTURNprMy11hcaaTG0h kYt7w27GYdYatRqg1Ya1lHKdSs4QqJNSugjUhaF2FeRQyCxyQXeSObOt4fbB vpfnZr+8sfO7tw/++Gj954eHHp7swzDxr17bzOVsXG6QALgSCZRigUoiRlFQ YwiJ2yFMJ8XlGV4qzk0muPEoLxzmBfxct5PntKVCrraIpdtPd/lN7V66xW1o dOmLjDZK69w2k87GUMGQs7klOTNVtbhYPb+cGZvecnTvdz999M3LNz5+Y8+L k2PPj488Wxm6Plt7si+5p9peZwccC8dUUAKDY0Ys6XJmE+l8fVPz0Fj37OzQ wsLIzp19c4sNo1Px+hYmEFGSeCLtmpionp+sPLZvYH4sv2e++fLlxen+5Mxw Yai3sq0xX1+IV6aDqX9dqLHSlB7/17UaBNLIpVqFzKSGzQqIUcI2FWJXQGap LG7Q7B3OXdnV8mh19PPri98/PPTDOys/P135+fGBbf0ZNrsU0Dgk4iL/AnJE zAO1GoZhMGV8G8OLRoBQPKBSLMaJhNhBP9vvYfk9fKejwmFu9xmHfKapqH0q 4RiLWYejTLNHnzBqHWaD1mq2ZnLpsfG6/Qf6Tp7qOX5h8uThL759/vtvnn70 5r5nayPvHxt690jf3eXW89P5td7QVMoMMscsE/s2OBz16rCg1RqJxTMNzfV9 g92z20d3LQ4uzrXObMkMjHjrG1zpWDzhmRyqPDhX31XjrM86GnLW4f7s8lzd se0N4+2Ruenqqb5iQ3mwOhPOxtxRv9VjNZi1mEYJw5AIgUQqQJioRKeQGRWw EYHojQ4rxiFBX6Xz7I6a2/t6Xp7Z+vWtPd89Wfnp5cmf3l395Pq2uJ+UiHlq sNqkQqVUgIh4cpFACkuFmIprMrA9blY4yAmHWEEPK+Dj+L1sn4cDjsNWYKgu j2E6aFtK+nbnAstp/2LS0+enkwbSTJE6i8ldKOYmZ1oPr4xfujJ14cKjV49/ +eH9z+4f/uDM2KsTY08P9LyxvfrsZPbMdPZgdzhhUJICrhkS2wGK46hDh7nM Fn80Cii0tnegc3y0f8dM9/at1WOjgeYmf21qbKZ6qiNWk7dUxc1JD+W3qpwG uc2I1Bcdw/XemVrnYKW7NWPJ+rRVSV91JpCNusIuxmIgMEAMkIAn5UpkQlQm 1sAyHJQXMJiwDJUKQXPJuOljI/nri60Pjw5+cm3h+6erP786+/N7p354uGd1 usJAwQQqJRCpQiyQCwCR8sWQhKdEWVqSwzBsh7PU5SxzO1leZ5nXxfa4OB43 x+WotWv7vPTWsG13yrc/6z9UHtqb9U8ELRlaSyFy3EA5yvOZienWw2uD6xdW 7978/rtXn7199MMz45+cnXrv2NBbC43XZgqXZysvbS9sqffr5BJSLDDJJTYN DEpK0GEOuryhRDJWXVnX1dU9Mtg7PdY8NphtbgxWJLsma/ZsL0w1WFurXdVZ RqsQttaFCwkm7iQiFixrQqfy5pognbKqKkNGlxapTniLyUDc77CbAZOiYljE lnJ5Er5YIpRJRbBMLJdLEbkMPC4TcQk1tLXevzaWf3Ox+cX5ma/u7v3DyzM/ Pj/xw+P9H50drM7QGlhAQGJEwJUJQHcGrU/EgqEyjZql17NM5lKGKbFbWE5b qcNa6rSxXXaOw97tNU5GbIsJ54Gc93DedzDr3p12jgSYrJGiYEhNYZZUMtY/ VLN9cezYysffPPvy0ZHnx4ffPz787HDP3fn6m9tqbi/U35irvbClUB+zGxBU B4lBS7VhirjLlggFs+nyqua22oH+5qHB7rGh3rGBus6m+vaq+YX2YysDN0+M 7RlM7xjJXVobbMk7m/LO1eWuHf2ZkUr/QNHNoHwXKbcpBY1xY8qiCpv1NZlo JuBy2I0EjUsphKOWcpRSLirhySVCRAqOSAGBuWKpxRxcXJ2xLHeFz89UPTjU 99H5rd89PPLLi9PfP13/6Z3Dlxbq9SoBKmDLhVywWfg8LkcsKIVlJQp0M64p 0ZEleqqU1rMYms2Yy6xMqZVhMeYBn3k+5T2QDxwp+I8VfIdzrr0Z96CXrjTr LBqVVqe1xkKRppZ8/9jNx2989/G1986MPz82+ORg19352lvbKm9sqby5o+bG bPXx3mQuHfTY7IxGSUFSk1oZsFrCnkAylavp7O6a2T69e9/2owdm9i50Tw5s mes4uFC9tSe8ZzQzVGlvztKLw8n50dREdzTKoFGzLEZL6+M6RsEJg2VqlA8k DM1BvUcLN1bFMnGfy2vRO/SonRLaCaGF4BpVPIOSr0UFFCo2qMUWTOIk+D6d LWna3uDY3xE6N55/Z2/nx5e3/fR05ccXp394/9QPD5ZaKkxc1iapkC3gsTig SIsEJZB0MyLfrFaWUlgphZfoiFJaV0Yby0wmltlUZtR3uegdUe++8sBqTWy9 OrJWGd6f8Yz66HqL3g8G0Gr3xFOOfGHm0PIXH9x8dGzs3UPdj/d33J2rub2t 8s0thTdm8lenyq+MZ+a6ywsdzW6vW6tWqqUi0NwtWgpIF02kKptaWocnth44 cvjapbU3rx6+dGJuqm682TXXG9o5nMg7NS6NcKDa1Zymh1u8GYcqadcsjeZG 6n2NcVOQ4Mc0vHq7pj5MMypOyoUXMkF/xMOE7UTMBifBcYjCtNCvF3l1Up8R iViVWY+6OqhujGnqwq2Vtp01tv3t/isT5Q/3d766tPX752s/fnDyl1fHr+xt V8nK+NwyIe9fb1QI+Ztl4s0ovFmFluKqMhIHcpXqSSBRGW0o1Ws3E1iVUdvv MO0IevZkggdywYMp/+6wc8ija7Dq44wxHAj5slXJnvbn799+dnHh9vaqt3ZU 3pqtuDlTcWMqf2M6f30yd3UidXooObV7rnZ2xur3KpSwUsrXozAI9rDTnA76 aooVrQN9E/uOHbp6/frz907dvTbaG1sYDC8MRMYbnRkrgvN/nXPovLgs40CK HqzSgU1WuadqvK0RKm0UFmyKtBnx62QGmMegnNq0L5GNuDJefcGrqAugzRGo zi+tdMmrPEi1H29NmwZrLOONzFSzYarR0xYfLZj3tXrODiXv7Wx4utr/xc2F Pzxf//39gz/fXGpLm0pZpUIRlyfgckW8UkhcogBaISWYkoVjpQRWqiVK9bpS o65ES2zGFEEFmiGQegPZaTUM2ulhl3nIbe526BrsxnKXMxmPRmoq7z5849Pb x+7uar4zW3VnW9Ub46k3xtLXRtK3pireGM9dHYwcnWndc+16y8xWu9+tUcG0 Co4YsEqPqS1sb/Uz9XFnW1PF2I5thy5fffP9j+5/9tGeI1PjHf6RBmd7Wld0 KMww36GW+gjIJmfHKEkezJoZbbYresJUiw+LqvlFuypqVGC8UjcOFQKWVDbo Lw8wNUGqPaHqSam6k2hXDO2KY71Z42itbbbTt2fYtXvAPN+mm6iMFF07qpzn gFaL9U8Od75Y7fvm4tRP95b/z/1966MZLg9otfGHSgKJsAwWl6BQiRotwZVl hIZF4WXAWlqqVEuySJyFK21SqR2SOOWSgALK46paI9FkM3Y4TE0eWz4aCCcz K2v7v3569u0jvfeWGu5sKd7bXnVtOHGuI3B1MHFzLPfmcOZcm3vlwNzS9Tdr BobdAaeBREM01Ra1bamOzDenpiv9XRGmKsS0NObmVg5fef7y5e9/unDvzYgV yvvRnnJzT9JcblNaIJ4N4dtk7AQFFXVIvxefimnHQ8RIkKqxadxqHoNwSSGL hrhRM5HPh315v6nKT7XFVb0pVX9G2ZfSDJWToxX0dINjod+/f8K9Z9A630aN V2qbYvU509E2963txacHO57sb31vqf7j5fYfDw/dmi6SqFgs4kvFArFUzJFL 2Up5qQYpJZQsUs3R4hwdCSiCRRECLQFRuEkqMUkktERilog9cjiGKQtmbaPb Uhf2RJPhmtbmDy7senq07+397Q931d+fr747W7g9XXF9IHFtIHF7NHelJ3K8 L3r2zpW9N242jo6FIj4LhaRt+uEK30JrcmdHBtwP5dxZCxWwa5sn+g++eePJ d9+dvXs9aYUHqp07uuIDWbotqIxTgoCGl6TEjTTS6VCOhDQHKs0HKpnhENES pZJmuYcQ6mUcUlwWMKorciFv2k0XPGRTEOtOqPrSyv6UaiCDjeR1kzXMbJN9 oc8612Xd2mAZrzJ3JsI5enul5fxw8sHOuqfLzXensufzpneqPDdHyq0Ay4RA JKFMJhLBYoES5uFqkZaE9FqYNkgMeoFex9eRcpNByxj0UpFJJrFAErtc5kbh EKYsN+saAvb6TCRXkc8U8/vaY/f3tF2bKb85nbk3W7wznX+8o+69xZanu1qe 7u14tK/56tHpi8/eO/LG9Y6ZKW/IS2OytIXsTtpH8t6JQnC6JtCdsGZpwopD uZryHSfX73z+6dUHd4te1XC5ebLSMRClunx4p0c9EqGmkrqlgnUupVtIUqda PWv19gGfpj9hrnPjjIRtkXJMMrZZJY2HncGI05F1a2sDmpaosjsBtAJHDeQa ypEjRWq0mhmv9E1UA/JwFL2V1b6Jgu1Ag/PeXOXbWyuu9gTO1VpPx8nTPXFa IVaIOKhMAEsFsEwgUUgRUqU36Ux2k8Vl0VpNcoNeTusou8XjsRthKQ2JrIjU iUBOFPZplGmTti7oqC9P5isKgfJ8TWXy1EgC7LtLfcGbo8nHO2pe7mr55vjY 796Y/+Gt5R8f7v/qzvLVa2sgt3tmJoN+p14uiunUNS661mVo9Bg6I0yzj87R uIOE05no9Mqh6++/uP/p+x1FR4dPM+DHx1zqAY9mJKhZyJBrbf7THUHg2JON 9ivdgat9sdEQkcP5eUpEcsrGA9p2BiUgocdmcDpMlrBZV3BjjQFlZ1TRFVX2 xNDeGNod1fQlTYNp70guPpQLNAS7xhv2LrRN1dl31jBXegOX2zwnq80XGh0X 6qxHW4I0LMIlPI2Yr5DwYSkfQaR6Sh1wM6moJxf3efx23EJrzEaDjYl4nW4D adHILZAQpJYVktgUUNBIFIP21opYc00+UygGUrnhGvfp7uDNseyL5eaPj/V8 dnzou8uzPz7Y/5dna39+vv6Xl2s/P12/d+P86OR0wGIywyKPWp7Q41kaz9Oq ClpZbSHzNOFVQ+WpyNSBvWfu3X36zWcjfVU9AfWOpHE+iM+HNdvj2HaP9Hi5 4UQdc7HFcbXFeaPTc2+2MF9Oh5ESg/C1qIL/sD0y6SOVUp6RVNNGXO/W0nE7 UeVRtAXRjjDSHlR1hojeON2fCg6lyoczqabg2GLHpWs7j+9uPDQQWiga9yc0 xxKaUxWGM7WW0/XMTM5kg0VWWGKSighQoqVcFSw2azUJn702HarLhYJhN1CJ MFCUkfIwhupcIuaxOBWwWSwCnZeBxX6tujJo7ypEOmvSmXTGE0llc6mlInOi zf32jupXh7u+XB/6/tLWn9458ucPz/39o4t//eD831+d+69XFz9/+3RPbUYj KHFq5H5MHlDLwxooScJFoyZvwGI4UluenNy5uPbGGw+/+PTI6b1DWXo6gm9x IfNexa4QttujOORVHk+QpwvGq62uxxPph1tyV7sDnU4lyd804tUc9cOTDiWG CNWgLyslRjNOBxldhUdd71E0+4nWgL03HhiIpQdTNYPZqobgtt1DL15curHS f26u5mCnb66o3wO0imMnc7pz1ZZTdUyzAw9p0BAh9yql9Ia7uGpQ0DA06jQW o+7KuCfgc2lpvYJQKzQKvRqdXZhu7aoDwOLCUFrKN8kE4KUrBmw9xVRHVTqf CydzuXxTT39VbGeWWG9x3ZrIvdjX+sWJ4e8uzf1h4/Ls8T8/P/W3987+/fmZ f3x44U+vzi50ZGlBmVUudKMyLypOkEgljRf0mpRO0VSZmdq5sHLlytUnj28+ f3Rka/tizrTVjW53wkse5bJbddCjPJfSvdHpfziRe2cq92Ai92SmfEvCYJFx l4vOc0XbznJLjCF766IeF0Vo5CYfTec9xiovUx8MdiSyQ9naoWx7f7a+OTQ2 WvP1lw+e3dxzcb5mfSC+XGeZS2PLMfWRiHo1ga9ndVuTdLVFV8VoK2msQqfw oWKdmK8W8QhI5DRq4l5zzMeAFqKgcL5KzpeJxGLe6XtX9509Mr2lryHrDxnU djXkJZU5t7k9F+6qirc3ZrsHuoeWliYXd+2o9+/KUavtzhtjqQc7ql/ubf/m 1Oh3Nxd+fnT0z09O/O3Zmb89O/33907989Mrl3Z0OSGOHeKHMTinV1UYsZxO lTCrG+srppeW1i5fvnDvztUnD/Zs75qIYksxfJ9fucur2hdQHo1oT2atF+vt bw3Enk0X7w7F3h6JHa+i54um272RZ23RLr/egwn6c7awATPgCovL4Mu5443h 8u5U7UCucyDf11/e25Fsawg+vb/20ePVmwe7zgwnDtZZ95RTexKqA1HFoRC6 ElMfSOCtPrLRpW/1GJttVIMZS2GwFRaoRWxUxDJgsMtC2u0UTmuBUCWQsASQ Kp9z//OXbz6/v3b6wJbRtsaUL2IlgzSWsuubEt6+qvjEYP3cru2HL144cfv6 keMHZ+pcu4va403O893+W5O5pwt1nxzp+ubqth/u7v/l0dpfn53+63tn//Ly 9D8/vfz+5T1VTson4xVoosJMJChFIWjp7Gndsrxn5dLFi2+9efHh3QvnT/T5 lG0G8bAROuTG9zvQNow/REn22GS77NKViOZ8QX+/O3BvIHp3tvxKLTNlkVNC TtaurHFgAQ1io5Rer7mqJtrWne3qz/cNFcZ7K8bb080F5/6d3Z+8vPDGwZbT Q6Gjzc7lgm5vBt+bAlohB32y1YhqNqQtWDUNTm2TS9fooOpoTY6Qu1GRRgLa dBmlkNp0aruZIHQYSLFNIu5mPmczu+z5bz96+PG71++cPbR/y2RHVVMGkIsx ZiWrA9aBYmx+snv91OrVh/ff/uDdN589Pn764EyteamcXKmznmz3XOmPvD1Z /vGBri9Ojn9/fdcf31kFRf5Pz07+8dbefzw+8of7R+br4nFCGsVkGaehrSU/ uW1q/siRtSsXzt26eu72tVuP783XR8LcXwdkJdvtyq06YVywKS7k1CrYA6T4 YEj1ZpPtYXfw7mD0wlDoZn94OK6lIX5nwNTgIL0k5NYr8hF7b3NupLtivLcw 1Z2fas92lrvrUpanbx+9c2r89EB4pdl+oNayq5w6kNLsj6CHwsiRoPxwTNPs JCpossZCFA3Kok5ZSSkqCIUPkWhELDmvjJSL7VqNx6KzmvSwGtksZG/islhi 4cvffvLk0/fuPLpy7uKBA3smJ0aaa/OhuI3M2XWdSc/8ePP5i6tvv3zy3lcf P/3sgzsv3jl2enGq0rac0a7U2850eC93BW8PpZ7M1nx6aOA3l7b/5vLcN6e2 fH9m4rsTvb+cG/v7w4PPr+5eHqzqasgMjfXP79+7/9SJU9cunbl+8dy1C1fv 3Tox2ztg5DUb+QtBbCVMjFCCLjV3SC/d7ycvZHV3O5wPB6O3h2MXRiK3xpKn BiLtXt1wyJLRwi5cHDSqCkFrf21qsi013Zocr43UhwxteffpldnHby6eHY+v NjkP1pr3VugOZsjDCeWxCLIeQg9HkbmkIaSSxHE4RSJxDZTQwGkcTqplDkig ErEk3FK1VGAHZdZuCrktJhMlVUg5sFjJ0B98++nzz1/ce/fW9TunL15b239k tr+3Ou0xxk2apqBlrCOzur5w59Hdl199/OFvP3384dNL96/v3Dc1UWHakyVX 65lTTY6zza7L7d57Q5ln840v5xs+XKz7dHf9V3uaf3ek4/vjXf/70YF/fv/o j1+/8/lHj95/+fDh/TcunDx8eM+OU8d2Xbl09PKpnTtj5IRNdiCue9gRPZkx HvTI1+LE2Qh2Jat9s9V+s9d/ayR+fiB8ZTD+9rbahYK3zaHN6FEvBQOt8j5z W3lwsDrQk7E2hozHlga+++bBly8vnZqtPtLiOFxlOlTQHcmRx9P4agxdCcuP +KD1HNnhIwxibkAlCaqlIZUsrJLF1LIAKjWKBQo+W8JnISKuhVJHXEwy6PL7 bIzbTDrM7vLsR99+9v7XHz395Omjl/cePrtz+cbJ+bnhYsIVMaqr3XRvMbB3 cfj67Svvfvrq499++urLD24/evPYhaNbpnqHy+m9Oe16tQUQ0ck65kKz+2Zf 7MFY5t2Z8udbyt+fLXyyo/jb3TXfrbb/6dbW/3p/9e+fXPzHp+f+64vrf/7i 1sf3168dHD++ve3kwtDR5sg2J7wa0T3pjb87Vn4yoNxv4l2KERfS5KU65lK7 +42B6Nku3+WB2IPZ6hvTlV0+orDxRzJqr14RtZJVQSbn0LQkmOe31v/41Ztf PNh3a6V/tTN8tMp8rGhcKepXC9rVLLaaUB7yQ6t+5HBBb1FyKRHbp4R8KllA BQXVUFgp88ilBCiGPLaEx4b5XL0KSfhdlblkJpeI5uL+fKqiu/OzH776+NvP X/3m4w+++uA9MIyPbx06tqujLhM1YxVOfWvcvjjecu3a2UcfPnv1zccfffnq ycsHp64dn1meHZntn6lx7w5rDgOArLWcqnWca3ReaXPd7gu83R96OBB50hd6 ORD5ejH/x7O9P90Z+/Gd+T892vuHe0t/err/b6/W/vbhuc+v7zo9XL2jPjQf wVYCmmdt/jv1rgMuxbyev+KSnIgo1zLYmTrmXKt7vc12uS98eyz33t7282O5 aiPiVcFWjdxBKqwquCZue/X20T+8WH95fuj9O/MnpjMrNZbVCt1qUbtWoFbz +GpWvZ5WHQ3BF7LkaAKXiUpJMcsECVxAKyAUBodVkEUmQMVckZAtAlqJ+Bgi 8zjMhWK6prEq11gTrq0o7279+LuvP/3+y4+//ezVNx+9/PKDx68en7l8fGKw Ne3S50DbjdhmB2sunF959P6jD7766MMv3n/26smVO1dWL51Yu3n16sPbh7qT uyPISg29Xk2fqjKerTVdbLJcamCuN9rutrofdQc+nAh9u1z5+zMdP9+Z/eur 03//8MRfnhz66dbSD+cG/3J19HfrA4dawqN+1YIPOhxWbg8gIwF1FwNNGfhr QeQUaD3gVBnX21wXO/1vTZS/u7v1+2vb39rbXu0kjVIRxOV4ac1nj1d/erjz ydb4e2v9D1eHDrVYjtUY1iq1q5XkWpFYz2OnsprjacWpGLpWoUuEaB2u0KES g1xgR0V+pTiIyXxqyCDjw/wykYAFiQVqVKbDFDarIZ6OFOqL5S1VsbqKcE3+ 0ccfALk++e7Lj3772Qdff/z885c33r4+NztSjDiyVqohaJ3sKZw+te/Bg+sv 3n/84Wcvn3/0/Pa7D24+e+fuqxfv//jjpz99tTZVvRRFjlXqj+eo9QrqdA19 stp4ptp4vsZ8vcXxzoDnw+nYV0sVv1lr/ene8p/fP/GPjy7+14tTf7ow+vlM 8qOJxBfLdTtbYh12eTslysFlBWnpiB6ds0q3mf5/pt77q6m1axf+C843znnO efezH7dbSnrvvfdKQkJC7733Lh0EQUAEBMWCYgFEAQXpIioiIEWlSu8gTVCx 7eK34n7PN76MOTLWyA8rWVfmvK5r3smaN6rKkVPpzK4OkNdEWDXHGp7n+Ezd TF5pzf04fOHP5c6ikpjw/JDJhvztmvg3BS4vMvRPcz1rw9S1weJ7IeK7wcK6 QEFtAKfej/3Ag/nQk97mzS0Kt/UIdXfxsrWzVzsY5I4qgSOP4sQxFePPP0Yi SXgki0GUCNlquchosHJ1d3Dzc3cN8jR6OakcrB88636zsji3sza7tTSzMT++ 8vbp8LOLgNa56VwUrEAb2ZnkgPq7l5911Pd314wOPpmenR6eneifnxrbWFt4 v7/17Y+dzx8eXkq56Ea548WtCxA2hErvBYkbg4HClDWGA2kmf5GkH8t2nDjn uXg/6/3zix9Grx8OXD9qLd65Ev4602HxjMfi3ZSUGNdMIydfSSlXUW/bcm+5 8ssNrHJ79jVvSaWXuDpE3Rpn+yTT801V4kpL3v7jM89qT6bkBPSUBc8VuL/J dBhKtWmLV932F1cBeRgguhckuhskqA8W1AfyHvpxmjwYrR70+nCrUzlRyaci ozLDozIio06GRIV5xngZ/HRiI5ugouEENCKHgRVwqGqF0KBT2Bk1jm529m52 ti62Kr1KYiUtuXH1+eTr6a3Vt1vLbzcWxlZmHr/sKSs77etoZSumeap4eSf9 m5qqnnQ1djWVPe24OTE1+mZxenBxburd1srRx7WjD+ufj7b//PbkQdkVL/pN b05tkKg2QHA3CPjA4nqgNoPFdwOF7TGqp2mGV9eiN1tyD9rydxtPbV2NWqkI HzvtMZXjWhClCylNqblTmKsklutYV21Zt71kVb6Ki67CUjvWRWf+3TBda7z9 8zOBo1fjPg9eGKpJ8fDVlyU6jMVpR1IdX51y7T2pA7Ko0oN9w4tX68u/FyBs DBE9CBE0B/M6A3iPvNlNfrzSCPf8rJhz5zLySrMyLuRklWdnn005nR2fmuDv 56SylTAB/6mWszUKvtFa5uqoc3bU2Tnqbex1amulRCkVKSRBSbHNzx+PrS6+ 3Vqd2lx8tTTV8rSloCDZWSu24dM9FNysePeHXbWDo73PH93svnd2oO/hq9mx oeXZsXdrM/s7C4f7c+935g/2d/7449Vg+404zQ1fZn2Eoi5EXO3Hu+XLrwkV 3wwS1seoOhJ1PYU+09Upc5Wxs+dDJrNchxNtR04az/pK+A6y+It5cx9Xi/x1 ZWrqTXt+hT27xJ6db03L01ArPWT3wvQtiY7P8gLnqlLa87193UV+Ia5FHrzZ dLvhVNv+FGNntOpeqOS6J+emJ6fGm13jxWoI4j8I4TcHsrsCOI/92KUe0ii9 Mj/M/ezp2ILzOWdvnD9fc+nC7UvlV4uLSjJzTsclxAe4uehdXazdnXXujlo3 J72jo85gp9XoNVKVXCCXsCVCnZP9tab6FzMTkxvLU2vz/ZMjdU13kuMDjFK2 jZDpoeBlxXi2tle/nhx91d852FDU31E19Ob5y/k3/Qszo2vLE++2pnfeze5u zu29W/v6BRDTxgL/W0GMhnDhvVDxjQB+hTerwpd/I1x+N0Z996RxsCJiJN9/ JMuzN1bfH2t9N1ipdJTanAx8PNn7anPSNsT1tKv4nJGbqyBnirHpImyxkX/L 17o+0rYhxuFWiM1Ja0akr9Wj+8UiOSXLiTWT4TB40vAkwfo+QOahomtu7CpX 9jUnChC13qz7QdyOYH6PP6s9WhptzfMTMhOc1Rmxntn5ibmX8s7XVFy9f6uq 8ebl2xfKq0pLK88lZ8eHRfsEBjp7eRrd3W0dnW30ttZWNjqZRsOVycg8Hl8k zqko6xgZGFmaGZ6b6Bp8dulGRbC3UQv0RwKGu1KQGenZ2Hht4FX30IvbA7fS X90vHHxU2/vqRe/s1MDC7NDS4uvVlTfry2Pry69XFqbWlt7MDjVdi7sTK7kX JaoOEVZ48YpdGBU+gqpwxY1obWeBz8tcv5cZHo9P2j7PdHAz8nmehvzaK4sH CzUvGiUxnlEuskJHaaycEsZDpitpZ/W8yy7yUntRjpZjZMByU1z/3B989qCI yEbH6xmTaQ798frHCZr6EGGVN+eSIwuISgfKTRf6HR9aczCrO0jwPFx4O1jm RMO4s4mhWnG0n0NSeljmudScslNFN89VNt+oar5Vea/q2r3rJZUlmflJUTE+ vn6Ont4OTq4Gvb3eysYg1VizZUoCh89ksqNPpVc/ausZH3kyNlTf3ZZfeMrN RqrhUoC8crcSZkZ637lR3nb/6qM72W1F4e25gffPxj64V9Ux9KJvdvrF7Nu+ ubdPp8bbhgfahl60P2ntab3V03SluSyiNtP+Xoz6eqgw34tR6s6+4Ce6HKFq zHQeLAjsS3MfyHIvDbYmCumu0f4dAz0TG+PFbbcE/gZbIT1NJwjm4wI56GgR MVVBO2VFz9dxXDiEADftcE/lVteFnrrTDCHZWoh/kagbjNd3xqpq/XiVLrwi PaXQmlQJNDIuzDuezNZg9uNgXne8NlxBNeBh7mxSsEYS6eMYFeuXdDo2veBk 2tnU3Iunr9y9crW+CoCrovZKceXZk8nBQUGuvv4ujq42WqNWbWOQWemZEiWG xRNRGCFhIWXV1+739zQPPLl6pyo5NsJWylOzqUBeuar4pyJ9bpRl113OuJ7u cyHUcNpBkG7kl6SF17XWPZl43TM93v56uPZJ1/m6m0UXSy+WZNedS6gvCqsr CL2e4XMxWn81Rl4SxCn0YBe48sr8ZdfibJ6cCXia5fMs29NZy2WpxXnlhc+n Bl7MvkypPs92VQPtcI6fPkpBj1KxouW0VDWrRMuLVDDofGpzXXFbVf7b8uSJ 9gqFlk+lwO4HyHsTrZtC5Ldd2WUOjGwV7rSKeM2FVe3KvufF6ghlvYiXnbLl S+EQayLGgUny00iDfezDY3xikoJPZkamnD6ZfDruVEFKSVVpWU1F2Y0LBRfy UrNjwyK9/QNc7Z31Kq1SZaOXWRuZMjWGyVPQGIG+3gUVpTc7mm+2PjhXXhTq 56nhsVRMmjWX5qYRZEa4n0sKungqoDLFM89DGSyjujExSW7aGzWXOkcGO8ZG ax4/OnvrenjaSQ9Pp3Bvw9lI52uZXhVJzmeCrbKCrcvzYytzAvNdWLmOnEIX YX6Q/EGO57MzgRXxHgQe3t7PvaG98fF4X//ccHJVKc1ZGRfkciXZpzDImOos y9CJLhqE+ToG0MxGJfhMjTTUX8nfaLiw9KLG00uNJkCLXMRPEgAFlF2wpebq iLlaQqGedMWZftuZ2eDB7I0VXA2UcPBILgoixSN0dJKTjOvprAkOcw8N94yI 8U1IDU3OCE9NDUnLijxdkpVbkptVmA6wVlRCUEAwQFjWCpVEqdVIrA0suZrI EegFgtDggLyykoq7d0pv3DiZnuxiq1MDHoPDsBGyvGzkSf6Op0Jc0v31eX7W uR7aMAXHg0GIdVbfqr7UOTz4oL+/pLo6IDlBZrTmcjm2CkGEk1V6gF12gC7J S5OV6H+tprKj7+mN0qQcB3auk+CkI6MyTvvsbKCfgwjNZ2SXFT5709vysnt0 eaKw9hrNQxsRaF+d6VeR5H4mWFfiJDvvIJWw4Aq99MWzuvWZDjmfV5UW/H6y Mf2kF4IEC1TR26KtKr0EAFBpMnSRLbXMkXXRgXHTi9uVoH2QbKPj45h4FAsD 5wHtMI1gJ+N5OmmCg1yjY7zi47zSk4KzM8KT4/0iQlwiY/zjUqMTM+Pi02Nj k8KDw7ztHLQqpUimUvLUVmyZNUMo9bTRxybEFly4UHjlSmJ2rru3n0zMl7JJ Wh7bIOR5WClSw3wzIr3CHTUhSlaCThijFflwifGu2jt3KjsH+m61tcTn5aiN RiqdSSZRODS6RiJ2t1YH2ChjvBwLi3Mbutv6ZyaejfWVxtvn2LOj1IRcD9GD bG+xgCJzsK7vuf98cmDg7ejbdwt3+zoE4c5yd2lRrMP1dN/zMS4ZLnKNgEwT UG7cLnk3/3RjsvVF66WRrsurQ7VV5UkkNlbBI9wKlJ+1p6WrsTlK7EVX1iV3 DsDkTwq839QmZIUB9lykEzEERDQHg1DQSY5qUaC7TUyQa1pcYEFm6PnsqKLU 8OQwD39XnaPRysnFztPfwyfYxy/Ex9ff3Q5wVmqJTCHjK9UMqRVLLAv29Us7 nZ15tjAuM9fZJ1go0dAoLAGNYsWm2wh4DnJxQkzw2cLczOSYIFthsJSeoBHH qjkZAcbbty7UPmw4ffG8jZc7iUYn4MhoNAaJQZPIZD6XqVeL4uKCr9yp7Bjo HZmdfDE7WX0997QLL82Wk2Rgnw6yJ7EYURmxL8aeDc2Nzu+vze2uvFqe9D4d z/fQOumFYT4Aq7JFSgHPWlBcfmp18fnS66aNyZbNieb5gZrZF7d67p+TqBk0 BuIs4DEcWbkaQoUjsy7aqj7d7smF4Kn6jMGGvMwYj5PBLl56qZJF4hNQchre RcEPtlMneNmmh7sWpftezIk8ezI42sPooOSJGKY7JRUqGWCobOz0tg56nU6p UAilMolQrGALTYOGguPi0/KLotPz7D0jeHIjisBEY6k0IlPMZMm5PCuRNCYm pvLmrTv19SX5qeEGUZSSk+GsKklyvXn17Pmys8HhYWyBAIZAodFYFAYLR6MQ GAyLz/Lw8ci/UFb3tPPFzPjQ7OTD/icXrhcVhFvnuIhjVERHFZuplF2vrxyZ 6h9dfLNwsD61tbB+tHOlo44opmBoCAKHwFZw7Dxtbt69tPd+enGydW26fWO6 bXG0cW6w5m3f7fEnFd5+GjQeEaWhlrlwr7gLmqP1/SVBL2tOjjXnLD0619+Y X54dWZQQFOlqrRUxeHiknIZzknMinDUp/vaZ4fZ5ca65Me4nfQ2eWoGUgqIg wGQUnE3EyzlMOZ8tF7AkAoaAx+TzeRyugMkVcYUiz4Cw8JQz7sFpXIUzkiSB YJgwLB2Fo5MITBqZyeeIAiOjr9bcaX3+/G7TnYxYrwArZrKb4nKmX/X59OyU aKNKSSSSESiMKanQGDgKgyOR5TrrqPTkC3frWl8O9k9NPhrsv3i3KiI+NDPQ Js9FGKNhCfg0mwCXwfEnE3PDY2tTb3cWJzZnJjdn+2aeByX6OHtowmM9Sy/m DL1s+7j/dnt9ZGvpxe5K/+ZM99Kbpvmhupnnt+b7bp7Jj8AzMH5qZpkH706o or/Ad/JOymzXufknF5afXRp6cLauOOlGTkSSn41GyOBgEVIy1kXOiXHRZAU6 FYS75ITYx7haeWlEOg5ZQkCK8UgrEs6GSjTQiTZ0kppK4BJ/ToohkahUOonK tLJS6excbDxOCqwC0FRrEEZgiWJCkHQIhorAMtB4Dp2j8ok4eel2fefA05ae joL8U4FGWbKL/PaZiPrSxDOxXjo+B4vGobFYACs4EgVHY3gSiW90VNGtG43P nvaMvu7sH7pZ35iUmSwWsTysWBcDNVEGMZ3PyDyXubAxNjE/Mr4+Nbk+/Xp5 bHC899lAQ1/f3fFXzasbL3e2x7c3X2+tDu2tv/qwPfV+/dXWfN/yVMfCWPP8 aMP8y7rHPdVCO7FRw7rkLWpOtxu6Ej718PTso/NLvVfWBq69vJdblRN6MdU3 ylUpZRCZKJiUgvNQ8eMd1dnetmf8bZOdFT5qjg2XYkXD6hlEDy45TEKLUbCj FGw/Ps1Ax/PwpluWTNWCRhEIaMBscIRGmtQDQTNACRoITmSJYoEQdDCcCkMx EVgelacNjD116c6D1hdPHnS3lZYVRXvYJzmrb+dGtl/Ovpoe5KLkkXE4AoGA x+MxGAyOTNQ5OKQVnK3p6Ho08qrr5cs7ra3niosCXGzJKJi9glMRbdTIqAKN pKGzbnL+5djc0OvVsfGV8fHl11MLQ/2D7fOro6vvRnY/zC+sv1peHj7ce7v1 bnJ7e+pg/+3h++n3m0MrM50bS/2zb5o3t14FpAbI9ezLUbres97jVTEL7WcX H1csPqnY7L/afTUxL1SX6mPlKmdw8Cg2Gi6jEjytBGkumtIg53NBDkl2ImcB SUlEa2lYDyErTsHPMkjzbJXZRnmCSujGo4gJQIkDDyQSBuWyKWdPRyEoCgRN ByXbQEg6S6wIjOaCkQBcNBCSCRwzxDZhSdlX6hsf9j2613H/fFlhrL97uEF2 Ps6r9XJ6Q0lCoqeOQwESlUin0QBWpzHp9q4up86W1rV1PXzSe+fhg/Kr5WnR ge5StpKA9lJxCmKMFAHeK8Tjxavu19PPN/cXl3fmh5dHrzXfKrqS1/z4TnCy v9pZbeerD84IKLqS0/W8UeQsVrmpuoc66lqq2p892P+8fvBxc36q+9PB2xtN lSwd60yszejFkJna5IX2goXu84s95et9l65muAXr+D4asZpBYGDgTDRcTME5 SriJtopiH7tcL5tIndCeS1WRMA4sYqhKmG5UZtsq8+yAUKRqxcFihoqEJyKR UBgUh0UD7XptbQWYaAOnGOEUWwjJxgwjsUQLICgOCMguNAeCFYg0rgnZhdcb 7t/vaa1urjtXfCbKz9VbLUhx09bkR7ZfSa9I83Ow4tMoBBqNSqPRmGyO3sE+ JTv71t2Gmqb7Fy+X5qVFxjgp/aQcdyEzVCsM9NLhRZTiq7mjAFnND15rvdn5 sjMoNUgfaJdXnuER5pRVkobnE+NSw7LOp52uyM4pTw/MCIrNjcm4mMN3EKOk pMCMsL1PG2vzve93JmZWx+RuVu5+2pGb8TP1aXOteQuPiuc6i2cflfo6SJRM ooJJ5uFQdBSciUIICFhA3D2knBidLEIjdeYxrKh4DY3gJWJGa0z/BU2xFmXo xDlGeZZeGq3g2tCpZASAFVxqbci/XNXZ1wcn28NItjCyEUwA8kpliRaCUGwA KDCGiyCIVLZ+yfml1xsba9saL9VU5eWfCvNxchQxApW80miv1ouZTeVp6YFG IZMEPCgUKpVCk8vkYWHBRedyS0rykxPDItwMgSqhv5wbppVEWMsFIrLCUdLe XT072Vtw+TREiMm+eiYqO+L9l7XdvWmlnWxqY9Q3wbur98Gl28V5l/Mr6i6E nYrc+bA0tjYm99S0jnRKHSRDE8/3N4Y3V0e+fT+IL4jh6Pn3y0JXOnKmW3Lf tp6Zbct/eS9LwCOy8QgmAU1CwQlwKA2N4uDxIjJRySQbBQw7LtOKSZZR8FY0 kr+MG6cRJWikyTpxikaYphVnWktilTwDg05DISk0dnBW0c3+1y1vpqAURwjZ Dko2Qgk2IKwKjBWBgDLEmAJHUxjcQlILz1+uu3vj/t3zVy+cTEn0dDJY8RkO PEaKi646L6zjataVjFAHlQCPw+FxRCyGwCDT9XJFkJdDuLeTg0aqEzKNfIab hBNhLfPVKqhMUmJm2OvB5pH+hxGp/q29DRX3Lpwqz/z2997oxGOOkjG5BGAV 0NxVU3o9v+BKUXntBfcYr79/HGx83OQ5KIbmh1/PDi1vTQPKuLb68svfB09G OuQOspg4++XnxTMdhdMt+bOdhfdKglA4sFzE5VLJBCwai0YScTgKkUAm4GlE HJOCZZHwbCJRQMCrmdRAhSBeI4nXyKNVojAJN1wqCJOL/SQCNZFCxWIlGtuM K3WNb2ZaJmfAZAcIyR5CsIHiNWCMDIwBsOIBQEGxfBpP5+AddTLvXEnVjXNX L2XkZgUE+WuVcgGTpGWSgqwEhTHO9aVJV7PCXHQSLA6LwOCQKBwBQ+SSaBoB Sw+wHQnHI2HlVLJewHaQ84TAKVXcu43Fr4eanj6rT86N+v5jt6SqIDoranVv tnuwmSWlLK6Ne8b6dD1/cP5WUcGVs8U3z9sGOf3x94f1jxsMo6DrTe+PHz8O P20CNbi+OvDx6+7+p7XE09ECg+BBTdZm/5WJttMLbXmpwfrfQCAXTw+DrYHJ pONMk1/wWCwWg8WgMaZRdoBwY9EYMgYtppK9ZYIwlShAyrdn0azpVGs6TcOg KagUrmmSG54t1YfmXChreVz5+AWUbA8hGiB4azheC8EqwRgJGA04Bw4cL2IK DUb38Ki0nLT8/Ni0VC9/PyuNhkmnEUxTPdFGHiPEVp0W6BrlbiNg0+BoNBxl CjQSTcTgft7tgqbh0HQclonHcch4HhlPpGC9Qtz6e2vHR5obWyozihI+fd9I OhOP4WIHXj++df+K1lG+tz/nEunybLir7HZpZmlWeW2FY5jbl78+fvhjL/ti GkXDr22v//bHwdrK89Wl3qMv+5+/bD8Z6hA6SJx99HODtXM9Ja/unjJac36x OOEZFODm60vnsDAAMFgs0FPAMSgYGglDoeBINBJp+qx0AlZHpzlwaToKHiA0 EhqJM91iD0Ob7vBFwJBYFInB1do7hCeGZRfBSEYY0QgnauF4NRyrgqJlEAzg SEUIgpjMsZLpnJ18A90CgvQOTmKFksZgoZAYGBSBgqNoGByfSJbSWAwCEWoa GAUHXoahMCjT31QJDIC5KGQiFkfCYmkEvIiKd5CyxGJ2yYXM8ZEH02PtldUF JZezd9+/dQpxvNty69tf2+lFKV6+hu13Yw6Bxs7eh+W3y2KyY85Xn/eI9Pz7 x493hyufvm7dbL7FNIrffVjd2hhYWXzy9fPe/v7Kx88bgC7QrdhZGeELzyqf 3Mz0DXb412//0tk527l5YslEGAYF/xk/gQICDQOuAo6EwWEYJJyBw/AIGAYa gQNegEOhcAgMDobCoWAYFAKDgRAwSwQUhsXSeXw4yQZOtIUR9WCiGkxQQwhW EJwSipPDCRIMRUoXKPkKFUcspXF4eDIVicLAYaaxSGBTwMBQCBgKBUGgllAo +OccJCgCcO94AuAdWGwWg0khU7h0so+1vCjW/0FJUkoCoLxn+h/fmHzdUnY5 4/a98qX1Eb23fmCo4+vn1aD4wLyCxNXFbrdQQ0fvw7Kqc34x/vlXC08WpEws T72Zebm6vzCz81Yf7LC2v7iz8XJl9tHR0faHDxvv3y9PLb50irYX6IRleWG9 D4rOXcg4ZvYLFei+FCoIGgHFoiEYNAyNgaLQ0J+TiqBIOAQJhcIAMKBwBAwB WCgEFAyHAMdEFIKFxRCB7/1nAoBgwOswSyjYErg+EpBUQGrpISQALg0IcKQE DRingODFSKIIC1QtlY4mkIDiMv1jHo4EchMGQ0BgCAAiEHAGKMTcdGD6JsBQ JAiGhqNxZDqLzmSzmGwRj+VnlNzKjR1prtocuj/cUdFYX9jdWjHxuunytZyy y6c7ntyxD3N89KJhZrFf66Uvriurb7ns4KPrGekqvHjKwcdYeruEqKQztNyK GyVecd6vll/ZhTqvAlitDSxPtn/4vPPpaHt3f2l7b66jvx44g8iGV1oc/ejZ PTIddwICxpDJCCwGjsNBsVgwCg1CmkZgwRAwEgHDoVMoGAwcDgMj4CA4xAIG Ap6RCCgfj9GwGGxTsZgGrIFgP8N0AIOQbH+GEUK0BRP0YII1GMAKD2Alg+O5 CCINjiNC0VgYUOCmBtk0VwSodMB1gCEQICxhpgDAB0FhlhAYCIYAsMKTaQQK g0Sm6STc06GOz2uLVoYf7kx0rw7f63t6Y2aqa3Ls4a07Z508jTkliSw1C8sj 5l/KDUkJsfY0Bib4Xa0++3Kk+UX/vaeDrfMro1fvXIg5HT040moIsPVMC9T4 265szWwvv1gef/Dh0+anL3u7hyub76a2tt9UNV0T2EtVTrKHXbWB4d6/mB1D ENAILAqAC4pGQRAIkImFwBwyziAT2klFQioFjQHQQ0BRCLFcauuid7CVBzla u2slbBIRAkVYQIGSMY0OA+ACDqAUB8AzQMhGADEwweb/YqWEEuUoshBN4SBI AFxAYwScFQOoCQnoZ7BYIHctTFjBfqIEAQGgAeeEms4JQ2GRWNNEOwwWbyPh liYF9lafHWurXHlSvfj02rOemxMTnTMTbRFJbmoP7dMXjbeqi1ofXh4datzf mVpeGDrcm1ueaevrPD85Uv/paPnd1szB/srB163NrbE3UwNhGeHJRSn7hyvv FvtXxhsPD5aPvn3Y/7i+f7CwMNH9fn8+5VyCwEXpmeBj5WFtSQQIwzT6CoKA Aw+k6T4SmJhOdLeSuVkprPhcCgEHQ6MsYDAam5l5OvtG7ZXqW8W3K8/GhHvQ SUQQ5P8m1U+gQADDkOzBJAOYrAeTDWAS0OlYA5UIJqrgJDmaKsbSRGgqG0UC 7AmegscCCusoF7kqJDQ80hwMAkOQIDDMVIw/Kcs0ug2BBPIKCDACEGesUcY/ Fe58NSuoKiuq8UzEs4r4wf76kZHmydGmyqqsrt6a9ZWXO+svFybaB7uvr073 r8z3Pb2b21mVOth1dXGqbXXhxcry662Nt1ubbzfXxj4ebADm4dtfe+8Pl7eW BpdeNbzfn/vy/cvhh80Pn9aXZ59tr0/Ozr1IyY9n2ks5zkqqiGlm/rtpaj0Y jITBgHpj4jA2Yp6jUiJjMZCm+7uAD4wwg0JV1tZ3H9wdGOl63tf8qLsuNt4P 8BRAJgBUYwkABYNbANcIMBvZFgKQFYCVqQyNELIOwApKUMHJUhRDjGfK8FQ+ lmSaGiugEt3l3Nww17KEwAC9HIOAW4AhIDDUHAwxg0BMZzOlKxyKwsLRWCjS NPnHKOVFOSki7MX+Klawhn0t3r33cW17W/nL59XDA3emXzdvrwzvrL/+fPB2 bqJ1oO3i5vLIztbo29GWg725zb0ZoLle2p5Z2J6Z3Zxe3l/++Glv//364Zd3 JqyWB5Ze3Xu/N/v1ry8fjnYOv+xsLA9vb02trA2/Gm8prDwXmZtCYJKPnQB8 FhgJBuMAskHAWDiToeIRCHAY5DjEEsgoMNI0zc/aYKyqqWx7dLep+XZt7UUP LwPcNKcaYcooONIChgCUy7RNAEmLpWoIVGs8XY+i6KCA0QKSiiBHksVohgTH kBAoXCyBhsMRZCxKhKPsVm50x6Xc4kgPPglvDgIBcJmDof9gBTYNEAZqH4MA UguFJGHRznJBiod1ipNVhIYXbRBWxnoM9j9qe1LXdO9cU2Np7/O6jvbKutrC e3eL6uuKLpTG1t3OXF8Z2d+buXHvMkPOERjkfHs100ZGtRZTbaSXGm78+eP7 x897Hz5uvlt9ufy6YXd76stfnz99ff/h8967zYmttTc7Bxsve28eHE5euXUV UGxzSzOIpSUBDOYhEGwMggr4ZQSg2SBLMKBK4H8mHoMRWI6AHxjmH5MQFpcY FB4RJBQLAXBAgMTDEZZwlCWgkTAk8PDwCElOiMuMT0wODvN39pAJbTBEGZoo RZPEaIoITxPiSEwMjoTD4ORMcpSL1ZXU4Du5UbkBtkIS3hJkGtxtAYaanv9v QJGAxQK0AEon4iPttDfTIpqKUpsKTtalBtUm+U3MvBmff9358MrQYGNwvK8Z 8A1TUBYYsCUO8ivcUu1u/XbhecuTegQbexxu/jsOcgwHPo6FHCcgzBn4EwzM pfobX/7+9vHTzu7q8NLr+p3N8S9/fvn8/eDj0e7+7uwGgPPBztvJJ6Mv6zLT Yih4JBhiAbe0ZCLhOjLRnsWUUAEKg5iDTMPWLCEAXHAIAo3C0ylcKZ3HptBJ dCaFwWSisPif9GsidhAUSCrAUqBwaHT3w/szI4MTvT1jTdXPbpRfSYtz1Gux BC4Kz0eTeCgiE4UjI9E4HAojpuKdZZxwO2WMk8JexsEiUT+/nZ8Q/ST2f8oQ jDRNtSNgcGIqI8ndWF+Q1H+jcOTm2bYzMZfCHWfXZxbezb5+2dTUUgkmQn/H QE4Q4MexMDMiAkLH/wcFjs2O8U30PYaFwNlkGAOPZJEQbDKCR4cJaMcoCImX 4eDPT0ef9/fWh1fH6jdXX37989OX7x8/Hb3f31/eWH99cLi1sbM0OdGRHuku IWDwcEsiFMTHI53Z9BCZSMsgwwGT83OWhYUJK+DTIvEMAV1kILH4AGwwOMo0 JR6JMmUU1MRUQFIBF4VEIMlY3OLU8N7y23fTI9tDTRs9d9/UXahMD9eIBTAc AYmnIbBkBJoAR2BxKLSUjrfh0fQCujWPwsUgwJZg0wSbf1QV4HbIT88AVDUS TSJTeRSKjkePcVJdSQluL47vPJdQGecRJCU86+t693F9bLi5/FLObzAzOBlH FrFpUjZeRAFTMb9Bza1cdc4Rbv8C/fZvBOTcjYqB8Rd948+vP7yBEJLMmFh9 hNfht49HXw52N8fXJ9rW5p9+/X74GUi0Lx/2DtbXN8bfH2zsHG2/XRgOdpZI CSgaHMRCw8R4tB2D6iVgqygEKBhsmr1jmqH9k2ChECSWSKDQMQS8SSvhKAgS CUYiIKZxrNCftgoBXB1gAyh4wuJI+/pI21pfw9rTO+tP7s13XHl8ITHZWUsm 42FYCgKLBZgHIGwKEWsrZkUYpXHOVoFavg7o1REoII3BP2kKCEuA538eAwLI 4QptZWIPlSDcXp0VaF+W6Hkp2jXTWWmkgaqunN0/2nkz3FpSnvE//vMvjpLT 0n27v+/Bg7bbUDruGAYSnZcYlRlGEdFZakHT4wcHXzf+/vGpd/IJTEyz4FB1 4V6H3z99+nK4sz29PtW+PN169Hn38x8fP337+P7TzubW9MbO3P7R7uBQp4aF YmLgRDiYiUXysSgxEa2g4DmAhweDzCHg/7YBJtsDQkAhGDiEgIBwMGighTPN fQLc/M+5T+amUjVdFIAhCUeY661f6Lw213p1oaNqvuP66/qi7gtxxSHOWg6T zeRwWWwSHoVFQXhUXIBWVBhodznWqyTMxV8jJ5s2+4D8f1iZnAOgrYBYYPFi iZWT0dlZo/K1FsW56bNDPbN87OKMYg8ervxM6saHzak3j4pLE/FMnG+w0/ib 7rX18Ud9rXgl+wQbX1RVPDX39Fl/49Bo5+rqm+YnDYU3S+JKMzE6oaWS4ZQQ 9O3v7yasdmY3Z7uXx+4fHm0dAVX57eOHz/tbO4ubuwu737bPn0tnQC3wGAQS aklAQKlIGB0NY+OQZKSJ2AEEQCZ7aRqYSUHBCEgYDQ5REtBuYpa7gCkjYqlo FA7IEIBhTKVqKhwk4C7R6K4b517Vnp2oK37bfHG6/cJAdU57SWxhsBHIIp2Y 56BSqLkswPYrGERvK162l/ZilGt5pFuE0YqKw5tcqIn9YEAfBTxbwOBmUDiG QFdZO3kGRts5OUgFNAelKNLeJtxO46sV2TGwufHhM5tvhwfuP+260vPo1sRo R2NTpXuYh8JVB+aT1V7G5vaqJ89uvxxseDvxeG97MiQp8H9A/2PBJVqKaXxv w+vN+Q9fP3w42t/dW9pa7FscvQsY0aO/j44Ayvp6sLW3vnOwDnSLzgYpEwkj YYGWxRINh+DhECzUkoqCU4H8gEEtAfmGAk4QKSCSpFQCl4wTEDEGFiXOqEmw tbblM2UMspxBo6BMA7fNfwrWz6UJVKSTujzKpTLRp/F0TFdZentZ6r2coAwv jZJD0Iro3gYrZ5VERiZo2VRbEd1PxT5pq0i0lbuK2FQsHmRy7yZi/yelAXmF YEhUrtTWOyL61LnAxCyFwZ5JIap4bIOYDRCdCAePiwt+szjy9NH1nvZLj5rL e9sv5hVG/e/j/8cMDgbR8Lfb74yPPx6b7Hoz3DzxqmN3azwsJfT/sThuTsZa MggUK9HYytyXP74CWO3tr+1vjs2P1L57v/D57y8mrL592D54d/Dl/fOBLi4R zifiSWg4BgHBIIAeFYKEWODhUDIKgQfaHKDAoBAGDuss5ofYSP21Ii8ZJ0jB zbOzKnSziTKIQvXCCDu5jkcEHOw/WAEXCEeg3aXsJIPCXUS349NCbJSnA+zP RdiF2ctZFIyIQQR6Ab2Iy8WiVQyyDZfuxKN5ipneUqaBQ6FiCYA5t/gpf/8k KhiJQ1N4XJXRKSwh+2ptUXVLTO45kUoKGC4iAUMmILGW5nda6iaXRrrbTFj1 dl2fHLp/viLtONwMhkcfg1s4BHr2jfdOjHWM9t5bmnz2bvXV3YeVGcWpwYlh FljkvyC/W3vZHX379PX70YePOx8OV5dG7m4uvTz668vH758+fgWanb2jPw+L zqWTwRYcIgGFhGLQCCIOECagPTZHQUE4BJSIRGIBowmDqOjEkw7awkD70iDH Ul/bHAfZZU/dnTDXqhj3y3Ee5REu4ToeCQUxM23+AoUAxhSOuhrnXxsbGCDh UlAQBhZuJ6CH28jshDwSFscg4VR8DodOJKJNswHVdJI9j+4hZnoIaTomiYmj wlEEk7bCfkohFIHA06kCK6Wtl3f8qYJbD6q7B4prm4NPZlLoVAgEkEwIncWc WJ99+ebR40e3OlrOdzWff95Vebsqs6Aw2t5F8xvE4n8e/0/YyZCxsbY3Y48W N8aXll/NL73cPZyqa752AmVxHAehq7ib+2t//P0VMJ9A17w51b74pu3T1w+f vh8dfjl4f7S/ur1otBIS4FA0BlA0KAaDolGoNAoJAQcDXT4KDqQZHAOH8fA4 NyEr0VaV72u8HO56NdQp30VeaCeuCXftOBXVkRdfkxSYYJQwsYAIQv5ZcQKw uhEb2HYq6oyT2ltEdePhAxScII1Aw6bhUWjAgDIpJBIRTcTAOTiMnII38Gje Ml6wWhgo41szOWSToyBCEVhAWxEYAoEmFlg5Ke19fRJySu8+uv1o4GZ7d97l O64BESQK7djx3+29PV4tTTW0Xet5XvP0WU1H26Wm+2UdD84/b7+YkR70O9Ti Vwszv0jf4svZYge1wKB8/Kzl4+fNze231fevmmMhgAeT2FkBevft78+fvh0e /Xm0szKw8Kph//3m0fej/U97R398qG+uAcwaCYNGwk2rBHAUikKhMJl0AC4c YJIsLREQEBWPseNxfeQiTwkvWMbOdlQXe9unGWXxGk6Zv7E9O6ozJ7YqyjPF Tqlk0mBAGUIBNYQgkKhTLtbXo72vBzqetVOecVTmumhS7JWeEhYP6ABhSCwG S6aQuTSqxDQjjqhlkJxF7ACNJEan9FKIBTQ6EkOGo4lwNAHog0gMCU9hL9W7 e0SnldQ9ut7Wd6mxoay64UxFtX9kPGCIk7MyNz5vt/c/6B5suHbzDIVHZsvZ 7Y9vjYw0Fl/JMsOCf7E0c/J1jEoO/bfF77/BLSMzEwqulQQnhGpdDRYkwKzi GCr+xu7anz++ffvr697B6sry4M7m67395Q9f3u9+3P3843N4nL+F+Qmgbwcs JZDqYIBl8DgGiyHk84RsNoNKpJJwSi7XSSFzlgn1LIoNHRui5Kc6aKK14igr UZGffUNK4O2T3mf9DGmOGgOXjYDCzU3+AQZBIHJdrcsCnGrC3MvdtIXOqkIv fY6bdaRSYE2i46AAlmg6k2ujsnaUijR0opKMU9MIBj7DQy5ykwgkdDYaS0Zh SSgsGUdkkelirtQos3ZzCT1ZcLOlor4np6LiVFlFeUNLaXVj1Mmcq7ert492 Xrx53N0PYJVvjjQ3R4FsPQ16dyNBzALhEf+2NLP1MEYkhfwKMkfTSBZo2HG4 5X8g5scRYCSD9BsO6hHmc3i09+2vL7vvN5ZWRnd3prc2xrd25ncPtz59/zT9 bp7KJpm21cCgTY0eHGVhWjWCEykUkVCo12rsjHqttZVIJJAIuLKfc9iMHIqv jBeplYQqeFFqUbarriTY4UyIIclZ5Sbn0PEIMBhmwsq0igIvcNOfcdZe8tZX uGvO2EnzPLSF3oYknUJLpMIhpm3lOByJo8HZx0arZ9MA7yHAIXk4JNAMKphU HoODJ9DRGBIaS8HgmSS6mCnSSqycnYKTUs7fTi647hYWYe/jn1B0vrjuQVnd w6Ynjxa2ploeX2/rvlnXdAlOQACKbgaHHINYmiFh5oD5waBqG27e77pB4BL/ bWH2OxT0O8TyPyCL32CQ/wMyU7nbLbxbAJpBwG2uvVvZe7+0vj6yMPt8a3vh /ae9na8HRi/nX//zGwRovuAoEAwJhqOB1LL8uY8ghUo1GHROTvZKKzWVwSD/ 3KlNAQgWn+4t5QbJuX4iepiSl2SnyvCwTnVX+6g4XAJg8k0rAxamlQETw8dJ uTESVq6d4qKHId9eleGgyvcwZtlpdHQ6DGra9ITJERoMjq56KwOLpiDi2TgM HY1kYFB8CoHN4lHpPDQOsPcUJIFJZIjJTAlPZnQJTY/JuuAemkBgsVFEskxr CEvLOn31Rv2jJxufNp6+qGt8eKnt2R2jp+3/PPbL7zBLEBYOxaOPQ8xDIn3m lobejD1sa6ty93dxDHCJSgpLSAqJTfQPDndpf3Rv+3B1c395fOr51Kvut8PN g91X+zoq3rxq+/b3h6uNN/7Xf/0LDPSnYIglBGHangOGsDBJj6kLRmLQMrnE 0cmOL+LC0XA8niRhMlQsio5Pd1XwApW8WJ34pJ08w02b7mWId1G7iBl0FNq0 Lvf/WxaI4DPiZNxkrSjLqDqpFoXIuMFyXoRcoCaTUEgECoWUyDUeYdH+3j4O PK4Uh2VhUQw8mkvCixkUsUDM5snxVDYcS0LgaRgyF0vmsKV6z5jTcacuGtwC oFisBQQBQWAZPLFMZ3fhVvXXHz/e7a32Dtxve3z9YXtVdIJv2EmvnOLEWw3l D7uqh0cfvRyu73t8fXykfXKy9+Vo59hIy/jQw9GXD6amenb25nY/rM1tzEzP jYwPPBzoujn0+OarvtsDz2t2DpYLrhT965f/DZCwuSXIEgSzgAJNBNISCBNc cCSWoLY2BoeEODrZkGgECpWp4LKs+QxrLt1RwgnRSlIcVHk+xlx/+1Rv2xgH la+aJwJcBxyoPsjPOfAmrU9Q8OMUvEgpOwp4VvC8+DRrEtqGhJLhsGgUgkAi 2nkHxOaeD49Js7OSSUk4IQ4tohDkbLqcx1RI5XyRjsaVIvFkBJaKxDHQRKZY 5xyaUZaQe1lt6w7D4gCsQDCAZoGPjWnq6v7893fAC23uLvcPtfY8rRkZbXnc ea2x9kxDbd7LgXsTr1vaarLaa08PAf3p5tupqb7hZ3VjQx2Li6OAPz842pxb mXi79GZ9a+H94bvPn/e2381t7y3tHazsHq5VNd3+5T+/mFuAzCxBZhYgcxBw gTALMNBWIIGAIDEqnSEqMTk0Nl5pcOMo7ZRAEnBoSgZFy6I4SzkhNvIkZ0OS qzHKSRvnaBVsZ7CRqTlMFhSNNAOBTaeCwFM10gAe1V9AC5VxUxys4+00XgyK AxYhRiAQcCgGj1XZuQYk5AbEJDvoNVouXW0at0ixlgp0GrVOp1eq7EUyOxKN hyWyMDQ+TaQ0+kXHFNwMTMrnSNUgFNIcbFrWMAOqgkB6s7Ky//Xw6K/PR98/ rW8u9r9sedpb9+Jp3dPOqsG+huHR9tbGwoaLsXfKYp7cr1hen5yY7J2beb6x OfHxaOPgcGNl/e38yuTM0pvl1cmNtZGPR9v7HzZ3D9YXV2cWNxeGVscxOMzx 42bmlmAzS7A5CAa8NYCVpaWJbcAIjEBt75aU55lxUR97WR14UWsXImVROFgM F4fl4HESCkHHodtL+N56ebibo49/hjHwjMIhgsqVm0NgZqaTwOPVQi8WKUjK CdUIC+KjLuUVJ9nbeOIArIAEhEJhUDITcOLOegdnW63GRS11knLsREwnncrF 2dXewdXaxihT2nJEGgZXwZLoZUZPz+hTAekXrN1DkDiyOeDqTT+EIc1BEDyD MbG+snX47vDrISBkX4Hsejc7OtoxNPRwaWF4cb6/rfniw7uFI333l5aG5ua7 p2cHlpdf7+7Mfjha3TtcXt1aWNicnVubXlqdfLc1vTL3fP/92qdv++vb89ML 4zsfd/rHexAYzLHfLcxB4BNgiAkuc8vjEASUzEbLXFhO6bKg87rUOofTbcZT nVapnTK/AglfyEXDqYAHQyLISDgHj9dy2V56pV9YknNqky7rkfXJOrFzOoaj tkBizMBQI51oRyEEStmROsnlsrOtj0bz407q4GYsoG+CI0y7VxAIPKFMq9Eb tFo/oy5IL/NQcJ10Ck8vd28/Pxs7g1BmJZAZuRK9UGmntvW2cQtWOfjQ2EIw GNAg03o1oN0nLEFUHmvu3frup/3tD+++/Pn5+19fvv3x8f3B1tbm7MrScN/j mr6n95ZX3xx+2pqfH5yZ7l1dG9/dW/j0aevw4/LK5vj67urG3tr2wcb+4cbG 0vDc6MPd3eW1neXZlcmdL9trn9/5hLj/+ut/WYChQMmcAFlaIHEIhhXdMV4d X2N7tte5bMD5fL+xoEeT9VCd8kCe3CYLvsCXObLxWAoKRkbBqBg4n0LUiWWO LkG2SVWG3B6bvKeGnB5N4j2eVyFJHQIm8YVYpBiDsGMQ/GXs8nN5z8YWbtY2 2AjZBKgl2OKEuZkZCoc3OHuEJyYHB/sGO9tH2VmFWsu8DOrQyJCY+DhXdzc+ T0CmCslMBZ2npPNkVLYIQ2KYWMISZmnaxAcJiNAvvx+3c3Pd+7I7vTQ4v/lm 7+jd5z8/ffvr218//gQ6u7m54bWV8fdHm++/7+5/2t57v/YeiP3lTx/fvd+f m5/vf3ew/unv71///uuPH3/89ePvHz9+7K71bm4Mb33ZXf/2rn38mS7I+Rjo dzOI5T9rUziRgzrygnt5T2DNZNj9RZ87E/YX+6xOt0jjb7F8C3kBJaK4O/Ko 6yxdOJnBJwEdCgzOQCHFPInCNlQTdUl9ukcB5F5aky6z0zqjQ5vSqoyqY7rk 8TBoHhyiZxFj7ZVZyRH1vf3dr2cKKq4FBIbbGJwA+RKpNaFJaYXXqwuvXEtN SozxdAg3yCLdbBPjE6NjEnx8/WVyQB4JECQOgsYCATCDqQTAIAsQ1IQVDAG0 2L+DwAyJeOFgZfj5tYGnFQvTQN31bL4b//hp9cu33T9/HH3/8efh148Hn/c+ fH6/d/Bu/3D76MvBlz933+1PH33f+/7nyuH24P7W4Nra87Hx1iftV65fiC26 lh1TlCX30FtwUCfIcBAK+jsYbIlCM+1inEv6I1vXQjtX/R/MOt8aUZ1p4QRf pLmcItkm4q1jWN5nJcl3xYk1PO9CqsodR2KTAFniqAUu6bLYWqucDquzfaKU ZkHkbXVSk1VSk/ZUu3XhY6vMNpVKTYOBHOTsgrTAMzlhxbeutLyabh2dru0Z uNnZW36v7dzt+2V1zVWt3ZUPH50pK48N9Y1w1CaFecclxoclngxOiPeMjFTr jSgs7gQIZA5Itqkxh/xcfjc11KYAnCESc8zCXOdp1/r0zrPmjOed+WMvr6zO 1c+8vjn95t7SfNfsdOfq+uTh592jr4d//zj668fh3sFE99Mb7Z03q2/nZ2d5 +/moHF0EUhWZxkFDCdATBPgxAuIXHOQEFQUXkOBSBtAYm0FABJWTY+HjwPpF /3vTTldf2pb3WZ1pZ4VfITnlURyyKE6n6C5nxOHX1alNquRWQfBFssoPSeQi 8RSqVYAwtlGZ81xbMGBdOCiIb+CGXpPF3OGHXhNFVFvldhrOPgmKSyWjUVIW LiXVvaQ0sfjahYYXo4/GZrvezHRPzj+ZXXk0udD6Zqr+xdDt7t7S2rr4tITo IN+k+Ni4rOSQtISo3NO512qTSy7JdHpz4GFpwurnOoZJZE0BYPXTQgN97K8g EEJA9gi2tbYXS1XMkrLo+w2ZT55UPO+/MTn9YGr22cbe9PuP05eunUpI80w9 FQTopzn4+DGLY8cgFv9GQYH4DYcyI+AsqAQQAw9lEuA8KkxABwupcBXHDI8E Ean8wBLH8/0OF5+rc9uU2S2a7C5FUgPf7zzT/zIvqJLtX8H1LheHVanTHlql tDBdcyAMlTkcDcJgsVJvXvg99ZlB66Ihq4IXotgGYfhtUUw9K6CM5lYkCq/R Z3UWXqpUiOU0BMjbKMnLCb3eXN8yMvVoYqF7YqFnaqnn7crjt0tAdE7M3Ont L71Td6q4IC4lMTIhLjkvN/50ZmpJ/tXmtuvtTwJTUyFoFACWJRj609v8t70B sALKELA3AIMhyGRLMv6/QBbHoKB/gy1/Q0DgeDiJQyJwCFK9AMvAsMRUiYb3 G+S3//rt1/9YWFoA2oI2jcOGktBgGgZMx4GZBBCTAGYSYRwSnEtGChlQERMk pJlziRAuGW/lxY+tU2Q2ChNvCRKqRfG3pQl1QHpw/ErFkbd5odeZvhVsjyJh cIUsqZEfUokQeRxHEk/AESfgaBhHzwy4pi0c0Z0bssrrE0fVA+mkTGsXxTfR fc5T3M9IIq/X3q0PiU6QEND2AlZWWkxd97OOycXOqcVHU0uPJpc6p5a63i4/ nlnpmpy/OzB4rqY2LS83NiU1JiXtZE5OVmlx3pXLFQ2NN9u60s9foPEFZidM 9uafMCUV2LSqDGAFQqAhCDSSQoIxqBAiDoRHg/EoS7Rpps0JGOQ4FPyrxYnj YBAg+MfMfrfE/MSHgAGTfgYFB6JhIWwCjEuG8SlQLhnOo4BYBDM61oJFtBTS 4AqOdZBb99iwbWIhx6eQH1DC8S3h+pdx/Mo4gReZvud5gZeFEbe4oddp3ueZ bmfYPmc54TeILnkgjhGEZZghyScQOEuKgOB0RpnVazg3rMp+Kom5L4mqU6S2 q/KeC6PqyE45HN+LNVWXTl+qsVXJbMW8lPz86hfjrVPzbVPzXdOL3dMLT+dW +pbWn8+v9Ewv3H0xfOb6zdjUpNDo6PD4xIRTaTnni/MqLhRdu3i9pamwqlpi Y/zt998ByTYZXdPPrABfwf9xvBAk0gICBhOx5hScJR4DIqBBOBTQA0JxQP4j TBOTsAgLNNwSZfrBAIJBQrAoMBEDJmNBJKwlGWtJxJiR0b/goP8HD/4VD/kN A6JaSzguWo+4IP/8k3HXC+uGOwB1rOp8gbeOpLuk0VxP0Z1zmB6FDP9ypt8F bugVTmgVI+AqEyhDv1K2Xwk99BLR+QxS5AIncs3RBCDAeB7CKkIY/8C6YNDq 1FNxQosoplGS8FCV0S1NaGJ4nOP4VJTlhqVfvGPv6C5l0N0joso6+5rGl1un ljumF3tmlodW34292x9d3346u3yv/1Xh7XsJp08FR4T4BvtHxIZnn87JKyzM OpN9+f69yodtPgnJIBjshLmFmek3uH9I3tRyguHI38zMfcP97aK8MDKWBQrx G9j8NxjoV7DFL+bHf7H8/VeQ+b/Nfz8GMje9Dvr9mKXZv0EW/4Zb/hfk+DGY OYSGw4oZBB7BNdIjq+Lclebqs9eKno492fy6f/jHx5onjQElycm3zk7tzC59 /sB3D8Nqwmj2qWRDCs0pl+ZbwQyt5IZXsgGUgm7wou7yo2oEMfe4sbU0jyKU xAWMY5khcRZoLIyqRqtjORG1ilPPlJmPpcmdkqQWftQdRUKrLK6J5l7I9bmQ F24MDQm0UtkwKBSWROGXXnj1yej98aXmyflHs8tDGztvdt6Pbu71zK7cHXhd cq8l5lypb0y0o4uLk6tTaHhofGJ8TGLs+drbTS9HihsfspSK383MzCH//Q8H AC5AEI+bW/CEgGHYGN162zX2NCotzNpda+2uV7vofZKiglIiotMirexVcp04 Ijmi4Hqpxs0m5lR8ZVN1ZkV+TIpnzf2L/XOvu3rvzC8Pfvjxff/vTysHy6/m nm5/2jj889PLtdf+xSdrn97vGe/9/uNHwOkCEN+TZB1LtI4m26cz/C9zI24D wYmqFcQ/kCR1yVLaZcnt4vj7DI9CuMDOEkO3QBJBaAZC6E91PQ+8rjz1TJHR KUlpUaU2aOMrrKIuKcJq6O7FTPfS7Ah9pLtKJuBTGUwWV6yw9UysuH21f/zO 6+mmydne5c3Rd/vD7/b7FjcbRyZKmjsSyipcY6Ktbe0lcpm1Tgsg5h7gVd5Q 3z07d+vFS4W763/MT5yAQE78zCsgQHDEL8d+K75W8cePvzc+785sz/QMdzT2 NrWP9PTODb3afDuyMDgw0fN44GFVQ3n3y66PP74sv19eer+48+fB4uHy2ELf 64m25d35NzOPxqefLr/fWN5fX95bHJt7tna4vPN1b+fPj5oY1/q+tqWDta9/ /3mlvcOcbYdX+KGVwXTXMwCf8yJu82Lq+In3pelt0sxuWVaXLKNdEFNHcTgF Yest0WRzJM4cQ8eoEjhBtfKTLfJTT8QpbdLY644JJe6J2YaweEVgMd2znOhc XJTkcjrR2c5oS2VLuEKJwuDmFJ+Zcae1su913ehUy8xy78ZO/9bu4Ppuz8J6 df/I6aqaoNR0rWmfCDaDwRBJJO5hgdW9T/tW1++OvJK7OALkDNTgCYiJ2wG+ OmEBIjIZT94Obn/ZWXu/MjzdMzzd1/u6/+nbl/O7C2+Xhl+8ap1aeTU+O/jo WXXfyIPFrcn1g9W5rbml9xuvF0f6x7se9918+frB6FjL26WBtY+b6wcb6wfL E3NPl/fmNo+2//zxI/9msT7Gff2P/cMfX/7fkq7zq6nt2/4Rb7z7fvfpVSC9 n/ReKIGEJHQI0pFiLEhRpEgROzZAUBFFUGkCekVpQUB6l5aEkAIkISFUafZy eeG+/WF/OmeMc+aYa+61xp5rrG61Asr1QnB9ce4n6GG3OXGlrPgy7rk618xG twutgottwotyflYTO7GMEJACZXmB0AQ7BMoOQ8aK0zlx9a6ZLfzMRm5ijSCu IDgpPfSkLPR0gufpfJbsMSms8E56aMn1iGsZx44GBbFZHL73Ee9jyTG5Rbn1 8opBRd3UbLN2vm3O+G7e9G7eXP9Bfa2i+kRGmkdgIIXBxAF4OpN1+nJOi3pm an2zbnycL/U+eOiA/b5dxxZ9tlQB9Z8Df8XEnZiyKAYU3e/H6ns+1E5q+2dM U6P6Eb11dsGiGFe1qQzjGsP4jKZzWtehN03rzGrT+sLS7rLWqhxRdnT1Vw8P Vqtn5OY1lWV3aWnbsry9OG8esWwuWHaXt3/t9GvHqCHCJuX7te87+s01svgI jCrGuoQTAy7SYh+wTj/jpNS6ZLxxyWxyy24RXpDzM5qYpx4DfucgDAkIBTgg UGAsjSDJ5J6q48Y/Z8Q+YMseiRIeeR5PPBIVFHI6XnzqJju2lBxy90Kc77Pb UVU3Q/MyYwQe3i5ewZ4RcT7Hk0NSc7IfVz3s6qsZV9bbclGF5sWk+sG7/rjb RZ5HQ12EAjKNjidS2C6OOWWPe4yL6q3d+ulpYZD0gN0B25H3r7bDwAjUH3/+ mXY5a/3X1pRuZGC8tW+kYWji7YiyfWFdN7+mNazMaBf69UtTc+ZJtbZTYxjU GcZ0ixM2Blp3llXGsWmdLQab1dq2OdOgeW3WumO2bJisH+cX16ds9LN+Xvu6 91WxPOuXGpNbXzxl0W3+89s97Kgdig5n++H902nHSjgJVazkGqfMBv4FuZtN iC51OGe1ceOf4v1SwBSBAxJwgKMd0FSieworsoQWdAvnm0mOuidKq3Y/liYJ ChaEhNCCzgABOYDP5RNHHB/ei33w8Gh6Vrjf0RihNFoSccoj6rRraIz3yTPJ j6rudQw+HZqsHFU+HZy6UtcSlHqJLZLYApDCYNgkziM46Mbr1h7zysz2p78V Kt9j0QfsDu3zat82AHWAIQ7+dTg0QPrp12eDVWtYUik1A9OaHvOa3qbMxnWd cXVGM9ezYJ02LisVM3KNYcBkmdCbx5e2zGuf15d2DbrFEYVarpvv1s4PmFZU S5vG5Y+L1jWd7Xnr9uLHn5u7P3dUSzNRVxIetVa/Her4ubd3KjvzD1vqxvYl Sy9z46t452qdz78VXuvyyB/2yh/2uDPkkTvAT35B9D0LIjrZsAIhsA4oKs71 JOVILskvE/BMYx4vFeS0ClKr+LG3ueE38AFXEaLjKOFpPz5w/VrwvTJZYqJf YEiUKOyEMPSEZ3SC5OgpSfTpqKuFl+vkRe1DJd0f7rUPZlU0+CdkMN0kFCaf zGCznXk+YeHn8u8+6+tr1OqLmptEof773hIoxAbX/19tHzxkV3j/7o/fPza2 rQtmpXVtzryq3fq6sbK9uLimtW7OzRn6F5YVtupGqW5Tz3UbzGPGZcXKjsW8 btAvfZjVvlep5Bp9l0rbbbCqTGu6xVW9wayaMystm4b17xtrn9e+/PoSni17 1l47saj6+OtbWfOr/7GDwWgeBN8LjBPF3PhS5/R64fVOyZ0hSf6wZ96g+Eav U2I1RnjsMI5mj8DZsAJjqVhXGSXoNkGaSwq6wTlTJ7k26JE/Jrre75T1jhL9 HOWWgODLJDx8WrxH0dWjGdEeUi8P9+BoydF4z6hESeQJ8dFTIdm30p/+nfvm fWH7YFH7YHblG9+kbI5HANNRwOFyXF15YncnicTFL8g35HhkUFQwm0uHw/fv au33re9QBzAEAkcMTox++/39++/PH3eWzUs604p2cV1vWpldWtOs7RjmjENz lsmlDc2stl230GtYHDVZFeYtw8LKrN40qJltnZ1pVs7aaqzuhSWlaU1rsr27 qtFZppTGMY11xvrJure3d6n8TnhW3PKvTcP20rBhCkUmH8YyMIIowpELxJBr lKPXqbKb7Phyp7RG/oVW56wW5omncNeowxiSHQxjK+3BGAqGLyMduU4JK6TH lrDTG4XX+7wKp7wKp4V5H5hnWzG+V5GiRHcaPiGMX5AszTriFsDluLh784Nj RVEJ4sg4fpDMNzEn4UFtTm3breauos7hnBetgak3uaIgjiPficsSuXA8XXnO NBIJCWURsGJHliuHQQRw0H8d3TZS/e+hvzx9xeufV7/88+3bz08//vm6+2Vj dcdiXNMal9XmVc3qlmF+cWJucWJte14316Ob7zWvTNk4trg1r7cqtAsDalWz aurNpPKtStNtWNJYNhbmlyaHp16395a3d5UPjzbYzoJve18ftVbwY337FhXz 6yb9zoJ3VNgfh1EInj/GTYZxP4ESRiGFsWTfbEZU8b7ax94nBV1HOgaAMQQw AgDDcVA0DcENxwfkMGLuOZ2tdUxrdc5+53apU3itz/X6APd8ByG0AClJckTD pXxastQ1UcwKJJG4VA6RJ2R5+Dn7BLl4h3hHJchuPMqoaL7Z0nWjuTuuuFYo S+fwPdlsNodBFvAYQh6DQcSSARSftz+HS+zMYtLJWAwavG81hBwCwcuqC/qH Sm2Y/N778eX356+/PtsCcHln0fxxzryut35cmDdNaOZHN3eNSytTc4bBxZVp 07rasKHRLE6oZttUk/XKqTeKmSaNvs9gUc7oR3sGX7V3VU5Mt2kWhpfWtctb po1vq7kVeREX44o76hZ3VtXrqpvl9//rwCF7EgtCdYXR3OEsMZJ3BOMWCbhF 4Z39yS4SPM8VT6Vh8UQkjoDEAigcGUGTEMRxRBsPowqZsue80y+4SS956XLn i73cjPekyPtocTIFAmUiYWI8LpBECMUDfBwRINCwNBaRzWO4CN2DosIzbic+ eJFZJ08orfc4e5noLiUxGFQcjoLdnwjJxKHISCgFBeMQsHwG2YVN4tJJeCwO ikIcPGxHZHPHZnrkzXly+cO1HdOPvZ9ffn3a+bb98dOqeX1f6jXzg1OKFrW+ b2PHtLKpVet6Vbo+pWl01jQ5axyb1TRrFI1qbceMulWhah2daOwdahgca9EZ J9Z2zKu7S8s7ttTUuPx19Ub13YvlN59114xbtLMrUy/ktQfADnYIIhjPARN5 UJorgilE0pzQtl/DAhgcxrZhARwWwGNwODQOiwEALIGOZvLhjsFg1xiE8ATg lUIOyWfGVrITm+hJr4lBd3DiVDoaSUfCPSgUPwIhkkiUEEhoHB5BJKPJdByV zREFeBw7H3KhKPzGM5/0B3T/WDjVEYXGUFAoJzzOj0c56s6NFbJkQrZMzA1z Y3nzKI4kwIYVHI3+869DEqlUa5kdGq5/1VDQ8K5sZcf4e++fL7++b+yuzVk+ 6IyDE9ONI6MvBoYrpmY7lOqO/sHayZlOhXFkem54QtutmG6cVbUr1e2z6rbR kRfvO8uGR1/bCGYTNOumYWXLYtkw6ld0ph3LsGnSM176ZrKpTdmtW9O/7q4F Y9F/QQEI4AgmOEPJfDiFhwEI6H/nnyL/fwLvvwtjW2gMBsABAA6DBxBUAZR1 BMrwcaCKYNxQtCAe5ZmK9EpHOkWiXWVMwCaC6HCBMMbVNQQP+BEpJAyAxBMB GpNAZhLoXJZ3qCjukuRckbMslyCOgREYAAbtw2ekHhHlH/etyoh9eel4w+2E 1qILL24kX48L8HSkYVBIOBJ18JC9o9Bt9cvWp69b5lVdS2dFTf3VCeXL3R/L qzt6jbF3YXFYoWwb6K9sbMhtfZs71F/+/n3ppKZjcmFoRN3TP/x6qKdqYrLl w/jb0WFbTdCwYJO1j6bljbnVbePytmn107J12zK/NqddmZvbMXHD+Tdq8kYW J/UfjfKx1wCDdMAeAcawIQALiqXD0PvtJDAYHA2D07A4Eg6DQsBQ+yNTEXA4 zLbtt/nh0DAyB+YUjnQ6CqZ6Q2h+cHYwhBUMono6YJhwjpSGx2FAIBGRKGNy wgDA3xaBcAyGymN6x/IjshzD0/gxOaKEAnFquWPsFaJACscSuGQgJUJckhpR kR3ReONkZ9GZ3rL0wcorvRVX3txLSYv2YxHx8P3rG8R/Dtk/b3rxc+/n999f VrfNbZ1V93KjSvJPdnfe18y2WCxKg3mitbGw7nFaU+XFnvbitqaCUUXTlGls cLyp733F2PCroaHa/p7qvt7aaVWnVtelnW3XKFuGekpbX1yanG42bS/Orc/p VvW6LYN3ojTxYU7TRNfKz832iQaqE+OAHQSEZYABBgSDA9u+B4GEQWACEkEm EoS48JzxaDYKQUMiyAg4DY2iodFYJBSCBZBcP7TwLNxZhmCGQxn+DhShA8Cx QxLAZDGTSEY5gOhQSDAOiCQT/HCAEwpLZrkKE+5LCzr9C5q9br3yufpKcr6a GXYezRQgUFgRi3rxmG/ZhZiXuafk+YmdhWe7H6UPVFzoq7rYWZpdeDZSzGIg Ech9RzcK+0T+9/TcgHq+f3nD8PnH7qxyoPhK/MU4UUNNhmbmnU2jplXyN88z /y7L7JQ/ePPqWl9/zYfp933ddUM9FSODtb09T3u7yjoa8t8WJzUWxtbnRVbl hlTeiu19+3jBMGHdtX78ubX2fV21rJGmhOU1lZa2Vm/vfelRtZG4tD8PgUAY OgTLAKHQIAQcBkdQUfCTYk5hdOCNcN+zYsdTruw4Cf+UhyDeW3BKxBOQMHAY GE7m4dyTUeJUqGMYmC4E4eg2oOyQAITkziFSMWAIAIU5IbH+BEAK4EPwFIkw wPv8s9CSruDidr+7b/1u/i1JK6dJzyLITmgE2otFPxMgTg8VX4n2KTkbXpMj e3ntdGNBUvP9lJbilIJzYW50si0K//jzjxPJSeZPluGJd3rT5MqGbnN32abt poXx8uKsSxmhZffjJkZr5lcVkxOvW2uvdbU/amq+MzTysq+/rl1e0v++rLu1 8G1lVsP9+L9vR9ReCn5+KbKmJKO9oVg91WlZ0yzYamvrlHJhVGUcX/22cexq Qv7bx3VDDead1c7JNiQJe9ABDsYwoBg6GIEAwSBICExIADL9BcVRfkVRPnnh 4oIY73tJoY/PxZYnR96LFkfzaRgkzB6DR7nGor2ykJI0KDMQhKbZwbF2CAyY 6MoiUtAOEBQUSoEjRRiMLxYXQqL4+Uf4ZFUE3W2T5jV5X6v1uFQpSCmhBZ5F 0PlkHMGfQw90pAopKHcySuZGz48W54QJz0qdr8i8HmaG3kkKdmeQkPtdQbAn lY+3v21Yt6zLG0aDaUqjHdYuTK1sWte2TeMT7548yC6+EdPd9XBK0dTT/aRv oKJZ/nBgtK6j83GnvOhdY15d+bm6PFntlYjn2Ueq7iS9lz/TafpNxkmTRTGp 7x9TvVfph3Rmld6q+/zPt7K2Gr7Mp9swaN4xP39XcwgMOgwngAiOYBzT4V/7 PRwC8aDgs/0E96J8Hx4PLIsPeXYmvDItpj7r5MvM42XxgYkePDKABqOQCKoI JUxFe91GOMeAcAx7OM4ODkAItkOeirWHoKFQMgIpIhDEOJwniegREO6VVuJ5 +YX35XqPnCq380+c4gvowSlYFx82lRYt4MZIeN48QiAbn+7r/CIlIjdaIuXi j/s43TkXdDcl0ptHZzOJx09HnUyWGbdM3/d+/Nr7tffv+r239/n3l43d5aVN nWFFVZ535m6yT3v9pabqjP7eR3J58fikvP3dk5aaCw2Pkl49TKi8HvnoYvjz ovTezmq9tn/ROL64OKmbH9KaJoyrOsuWcWnbbNowrX/+WPLmqeNJ74K2pyvf N1JuZ/33gUMQgA2liUB49j5WICgSDPGhAWckjue8HTP8nG9GepaeDq8+E/E8 LaY0OfL+SWmClysJt9/KBAJoIE4wTJQAdvS3x7JACII9AoCRXagIDAYEtoUh Awv4s7jeAMGTQAyMSPBKKXVLe+R6rtjxTCE34S7reC495Bxtf9qDS5rU/WFy xO3EIzcjxeVJYf13Ul9fOVGUEPgwNfLNvbNPrxw7GSw4kxRe9aqkqqMmsShT dutM4v3M7Ge5BW9Lmkaa9Bblzs+tza+b619WZmcGCjMiHpz3qX94urHmoryt qH/4ZWdn2bNb0S/vx1fmHyu+El5fnTcy3qqcblZMNM3OvFPNtPd0VI5/kKv1 wzrTpGFVu7Rl+br3rUPVb+9JEKWEGX5uuUk9/zh4CIznwVneUBJ3v50EAqei MUFcahiX4k5AOWPAPmRkogf7Yoggkk8N4BBOerDDRTwCDg3GsWFUTzDBCUQV OJAldlg2CEG0R+Ax7ID/A+WgPlI= "], "Byte", ColorSpace -> "RGB", ImageSize -> {66.66666666666325, Automatic}, Interleaving -> True]]], "Output", CellChangeTimes->{{3.7560807945590296`*^9, 3.756080804017726*^9}}, CellLabel->"Out[1]=", CellID->147191055] }, Open ]], Cell[CellGroupData[{ Cell["", "PageBreak", PageBreakBelow->True, CellID->85785237], Cell["Have a bird say a random bird:", "Text", CellChangeTimes->{{3.756081739631364*^9, 3.756081743344248*^9}}, CellID->521933704], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"BirdSay", "[", RowBox[{"RandomChoice", "[", RowBox[{"WikipediaData", "[", RowBox[{"\"\\"", ",", "\"\\""}], "]"}], "]"}], "]"}]], "Input", CellChangeTimes->{{3.7560816720585585`*^9, 3.7560817354965053`*^9}}, CellLabel->"In[1]:=", CellID->3495078], Cell[BoxData[ InterpretationBox[ PanelBox[ GraphicsBox[ TagBox[RasterBox[CompressedData[" 1:eJzs3Qd8FEX7B/BJTyCEhN6lCoh0BcQCKCBNQTDgq4gCAorSBBGBwNEEKYJI tQFJaKETSKGF3osICBb8Y0EFlI70zP+Z21xyCbnNZm/vZpP7fT+f500kV+Zy e3nvd/PsTLlu/dr39GaMDQyk/2nf9cMm77/f9aMOofQf4X0HvtOrb4+3WvYd 1KNXj/cbdPOhfzxEl/2bvvFlAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAOAmeag6UX1DdZzq BtVtqt+pllO1kTc0AAAAAAAAAI8QRHWNimdRK6kCJY0RAAAAAAAAILcLZkr+ Pks1maoFVfmUepFqH0vL6HMljREAAAAAAAAgtwugepPK18HPfag2MCWf36Uq 6J5hAQAAAAAAAEAGYk7dNof+rOSxAAAAAAAAAHiq+iwtnz8neSwAAAAAAAAA nmogU7L5faoikscCAAAAAAAA4InE+eZ/MyWfL5E8FgAAAAAAAABPJNaM28iU bH6eqoTc4QAAAAAAAAB4HG+qKKZk81tUTeQOBwAAAAAAAMDjiGy+gCnZ/DZV a7nDAQAAAAAAAPA4Yr/zaJY2b45sDgAAAAAAAOBe4nzzpSwtm7eSOxwAAAAA AAAAj+NHtZIp2fwmVQu5wwEAAAAAAADwOAFUa5mSzf+jai53OAAAAAAAAAAe R2TzOKZk8ztUnagKqVSgnGECAAAAAAAAmF6AE9d9lCnZXGu97dRIAQAAAAAA AHKfElTxVLFO3AbyOQAAAAAAAIB+Yv22s0zJzOLc8SC5wwEAAAAAAADwKGFU MUzJ5f9ShcsdDgAAAAAAAIDHaUx1hinZfD1VMZmDAQAAAAAAAPAwYv23z6iS qa5T9aTykjoiAAAAAAAAAM9Sm+o4U+bMD1BVlTscAAAAAAAAj/Mw1ftUy6hO UF2gukt1kWovlYWqiKzBgcv5MOU5vpNSH1L5yhwQAAAAAACAh5rMst7r6gpV M1kDBJepRLWHKc/xKap6cocDAAAAAADg0fpQfUXVleoJqgpUpZmS1cZS3WBK frtMVVjSGMFY4pzyfkx5bsW55uKcc+ybBgAAAAAAYG4dWNo8elfJYwHnlaCK Z8rz+QdDXwQAAAAAAEBOkZel5fN+kscCznmJ6jxTnssoqlC5wwEAAAAAAIBs aMrS8nlDyWMBfcKoYpjyHP5LFS53OAAAAAAAAJAFsf91IFUIU9Z1F/PlIs+J XDdP4rhAv8ZUZ5jyHK6nKiZzMAAAAAAAAKDJdfbg2u2HqLrLHBToIj5rEeu+ ifXfxPPakynrwgEAAAAAAID5ZZbPxT7oIufllTguyJ46VMeZ8vwdoKoqdzgA AAAAAACgk8ji1ahGMmXvc5HzDjOl9x3My4fKQnUnpT6k8pU5IAAAAAAAADBM TarbTMnoQyWPBRyrRLWHKc/TKabsXw8AAAAAAAC5y0qm5L6d2bzes0w5Dxpc R5xTLtbxu0F1n2oCVZDUEQEAAAAAAICrTGdKPj+TjeuI9d9Fj/Vpqg4uGBMw VoIqninPzR9UzeQOBwAAAAAAAFxsA1My4P5sXMePKWuGX2Bp65Q9ZfzQPNZL VOeZ8ruNogqVOxwAAAAAAABwgsjQwVlcpgVT9ugSOXCsjvsowJSe69sptxND VVbH7eQ4nHMfqrJUT1C9SNXz1KlTE5OSkhYvWbJk5+zZs0/MmDHj10mTJv0z bty4G6NHj743ePBgbl8DBw68/f7779/64IMPbkRERFyif7tcrVq1/8TNBwUF 3e3Wrdvh9evXLzh27NjIe/fuvUz38ThVEdmPHQAAAAAAALKlGNW/VDOo2lFV pipKVYbqOapZTOlRF9n8HFVBJ+5L3HZsym2JfCkyez4nbs9UKBMXpWp69+7d gUePHl0WExPz85QpU+707NmTv/DCC7xu3bq8TJkyvESJEtmqYsWK8QIFCvAi RYrwggULch8fH+u+d4GBgdaf2V9W3P5jjz3GX3zxRd67d+97FovlHOX/fTSW eSdPnuxB46tNhTX4AQAAAAAAzEfk84z7nWdWP1JVN+g+m1IdS7nds0zpgfcx 6LbdhnJuKNVLp0+fnrd06dI/hwwZwlu1asUrVaqU7Qyuls29vb3TPRdeXl48 NDRU1+2J7N65c+fkYcOG/T1nzpzNe/bsGZoy3+4n+dcJAAAAAADg6byZssa6 mMveTfUb1S2mzG+foVpD1ZUZvwa72JNb5HLb+dMHqZ42+D4MRzm24j///DN2 yZIlPw4dOjS5SZMmhmXxzErkcGaXzUVWL1y4sKH3UatWLd6lS5e7I0eOPLl0 6dJJ165de0TyrxkAAAAAAADcL4ylnZsuMqjofy8vdUQZUCYveOvWrfdiY2O/ 79OnD69YsaJLM7l9FSpUKF0+z5cvn8vvs3r16rxHjx7Xp06duvHgwYPt6PH7 Sn4KAAAAAAAAwH3EXmxi3TiRQ0VW/4wqROaAKJfWOXbs2PoRI0bcE3PM7srk mc2h+/v78+DgYF68eHG33rc4n/2VV165TVl9x4kTJzoiqwMAAAAAAHgMsSbd Uabk9D+Zm89Np/zpRfXCoUOHDr/77ru61nPLrfXQQw/xN9988868efNWX7ly pZK7nhMAAAAAAACQxnZuulgvXuT0Q1SNXH2nlMvr79y582iXLl14yZIlpedh M1e9evX40KFDT27evDnc1c8LAAAAAAAASBfKlHPTxXp1tnPTKxh9J2JftF9/ /XWt2AdNdu7NaSX6C956662LK1as6C96D4x+bgAAAAAAAMBURC+17dx0sRe7 ODc9v7M3KvLkvXv3ukdFRV0Ta6LJzro5uURO79q167mYmJjXnX1eAAAAAAAA wPTEPnDfMiWn/0PVj+k8N52yebHff/99e3h4uPRsm5tKnKPev3//3zZt2vSE gc87AAAAAAAAmI/Yr70L1d9MyenfU7XIzg1QNn96x44d52vXri09z+bWeuSR R/iwYcO2fffdd2EuOAYAAAAAAADAPIKpLFQ3Wdq56RWzutL9+/ffnTVr1j2s y+6eatas2a25c+e+4dpDAQAAAAAAAExAZPKM56aHZryQONf81q1bE8WeabIz q6eV+CykV69eB6dPny51P3sAAAAAAABwi8ZUR5iS0/9lyrnpYp82kc29r127 9kW3bt2kZ1VPrpYtW16LiopqKO8QAQAAAAAAADexnZv+F1Ny+kkfH5/W58+f n9+hQwfp+RRVgteuXfv+J5988rbcwwQAAAAAAADcJC+zOze9SJEi1pKdTVFK lS1bln/44Yfz5B4iAAAAAAAA4C7bt2//uEKFCmIenXt5efE8efLwYsWKSc+n KKXeeeednbKPEQAAAAAAML3xTOmPFvW35LGADpzzDhaLJVnkwEKFCnF/f3/r 8+nt7c3z588vPZuilOrWrdtu2ccKAAAAAACYVh2quwz5PMeibF5j6dKldzJm wdDQUO7j42N9Xn19fXmBAgWk51NUCd6lS5dNso8ZAAAAAAAwHbHe97dUyVR7 GPJ5jkPZPOjIkSM/lytXLtMsWLx4cZ4vXz5rv7u4eEBAAM5NN0G99dZbi2Qf OwAAAAAAYCrDmZLJ51BNZsjnOc7169enNG/ePMs8WLRoUR4UFGTrkcC56U5U tWrVeLNmzXh4eDjv0aMH79mzp7XEfnZt2rThderU4aVLl1a9DbFH+vvvv/+h 7OMnh8pD1YnqG6rjVDeoblP9TrWcqk0W13+Y6n2qZVQnqC4wpYfoItVepqy1 WMQF4wYAAAAAcOQRpryn/ZMqP0M+z3E4502GDx+enJ1smfHc9JCQEOscu+zM a8YqWbIkb9y4MR80aBBfunQpP378OL969SrX4tatW/zo0aN8yZIlfPDgwdbb yXj7FStWTO7SpUsT2cdRDhNEdY2lnY/jqFZSBTq4jckarn+FqpmrHgQAAAAA gB2xb7atn719yr8hn+cgoq999+7df5QqVUpX9gwLC0t3brr4b9l52AxVq1Yt 3rdvX75ixQp+4cIFTVlcq19++YVPmzaN161bN/X+GjRocCM8PDxY9vGUg4jf lThuzzLlb1YLqvIp9SLVPpaWsec6uI0+VF9RdaV6gqoCVWmqelRjmTIfL65/ maqwix4HAAAAAIDNAKa8/1xl92/I5znI7du3x4gea2eyqJg3F/Pn9uemFy5c WHpGdmeJ8/Y7derEZ82axU+cOMGTk5MNzeSZuXv3Lo+NjbX2wosxtG/fHmu6 axdA9SZT1s7IjA/VBqb8LRM96wV13EcHlpbxu+q4PgAAAACAVmKeScwPif7N knb/jnyeQ1DEqzh79uy7RmVUTzo3XfQbtG3bls+YMcPafy6yskzbt2/nTZo0 Se7UqdMHso+rXETMqduO52d1XD+v3fX7GTguAAAAAICMNjPlfWfvDP+OfJ5D /P777wmVK1c2PLuKufPceG76I488wnv16sUXLVrEz549KzWPZ0acq26xWM51 7ty5uOxjK5eoz9Ly9XM6rt/U7voNDRwXAAAAAIC9Hkx5z7mLyivDz5DPcwCK cw1Gjhzp0jyb089NF2ujt2vXjk+dOpUfOXKE37t3T3YE1+Tvv/+eI/v4yiUG MuVv2X2W9Trsol9erCMXwpR13cV8+b8p15/nwjECAAAAgGcTvexivSOxZvsj mfxcbz4X6yuJfY12Uok9nSdQvcuUPY5qUIXqHC9k4syZM1vLly/v8oyb085N f+KJJ/iHH37I4+LiNK+xbkLi5PeWso+xHE6cby7+honjdomGy19nD67dfoiq u6sGCAAAAABAFjPlveckpqyBnLE+S/n5Obt/89dwu42Y8n72PHO8V9FVpuxT vJ4pe60PpXqd6mmqslR+zj+83I+y2zPDhg1za+4V56aL89FZynNZvmwJ3r9n Iz6if0Pe9eWyvFWjwrxCOff3wIs9yMWe41FRUfzMmTOyc7WRRAN+AdnHWg4l 1ozbyJRjVfw9KqHhOpnlc7EPuvh7mNc1wwQAAAAAYHtZ1nv+ZiyLjvsJo6pL Fc6UXlExnx5DdZAp73sd3Zf42QmmvL8W+yJ9SNWFKeeCijXtfHSMJVc5ffr0 prJly7o1B5cpXYKP6PcYXz6jLq9TVTk3PTSY8QIhyvPWthHjd/b58nNbS/A9 Cx/iM4cX5T3Dw/gTdYrwkiWNG4c4h/zVV19NXdft/v37ugPw7du3zd7zvkD2 seZAWIYSe5KVtyvRl1PXrsR+ZU0zlFgbPdyuyhk0NrFnZBRT/pbcosruvvIi i1ejGsmUtTPF7RxmjvdQBwAAAABwhrvyeVaCmPJeXrxX75lyHyKPi1x+mil7 ImU2ljtUfzIl54u8L3K/yP/iPb7IAvldMFbToMxW6eOPP052Vy4X2XpIj2L8 +t4inB9k1rq3n/Hpg3x4YED658bS04//us4n9XK2ur0viP+4rgyPnlSVv96+ kjXra7nvmjVr8g4dOvAxY8bwtWvXGjo/Pnv2bOta9eKcenHbjoh13S9evJha Yl2506dPp6vjx4/zgwcPptaOHTv4xo0bU0vcfkxMTGotWLCAz507N12J/dAn TJiQWmJtAdGn/8QTT4i9D8UxLuZx52aoSKa8BmwVy5TXj63EuSYH7Up87nU6 Q4nX0kW7usmy//fBiOphwMtDZPMFKbcnzt9p7eTt1Uy5HXF7Q528LQAAAAAA Pcy0PpzaHLzIFY7e64uMIbJHrpuDv3r16lzR0+2ObF69ajG+NyokNWf/vt6H j+oZzDs+G8qHdw/mdav6pPu993rJn/frmI+/0iyUfzE0D7+xw+uBrC4q+XAI v3qkGf9572C+Ke5r6x7gttq1axc/efIkv379umFZPKMrV66krnsnSnwvzuUX VaRIEWtmt5V9T38OLJEt7bO3WO8sYz4/wtJn+B0sfcaPZ+k/AxCV8XOCKUx5 bdpqFFNec7YaxJTP4OyrE0s/f15ew+GvRrymo1navLmz2dxmZcpt7jTo9gAA AAAAssNM+TwroudUbQ5ezLXrmYM35Vp2FC0LzJ8//7Y7snntR4vyX+MCrXla 5OyxvYJ5z7YhfNVkP35yOeM/rGB840zGK5Vh3NeH8fZNWOq/f7fEi381NIB3 bh7Kl4wN5MkHHszo6epYec5/6cz5+Zmc3zjI+X3XZXPh8uXL6fK5WJu+bt26 1nrmmWd406ZNU6t169Y8PDw8tTp16mQ9392+Bg0aZJ3rttWoUaPSzYVPmTLl gfly+/l0UfHx8enm3MUcvG0+ftOmTdtonLVY+h5yUWINNPs+cy3rRORG4nzz pSwtm7cy8Lanp9zuGQNvEwAAAABAq5yUz7Uwag7ewpTPAGxz8L5ufAxWFC37 PPvssy7P5g+VKc6PLs1rzc6n1/ryzs+H8nkjAqzZOzt1YpkXH9E9mA/unI9f dzCXnnnRZX9oxPntX12W0T/99NPU/valS5e67H4M9LK7j7ccQqwpaZvjFq/Z Fgbf/oaU295v8O0CAAAAAGiR2/J5Vuzn4EUPvOjH1TIHL0r0DLttDn779u2n 3TF3vmaa0tN+JtaHd3o2lG+e5ZuauU8tZzzSEsA7NA7htSoW4DXKK1WrUgHe 7pkQvoB+djImfU4X2f6tF/PzW3s0ZPTDwZyfm8Z58h2XB94csD6cvX+oihp9 TOVwYs/ytUx5Lf5H1Twb1xW5PjiLy4isn5xy+2P1DBAAAAAAAAyX1Ry87T28 y+bgKZvV+uCDD1yezd/uVMiaky9v9eadngvlidPTsvmqSX78iWph/KFi+Xig n98DjzfA19f6s8erhPGlH/uny+jTBwXxD7vkU8/mP7Xi/NZPsnNwlu7evslv XP2XX7rwOz//+w/83O+nUuvCnz/zqxf/4rf+u8bv3zc8+69x+kjOPUQ2j2Np 56uI89kLqVTG9deLMeV8/BlU7agqU4nPP8pQPUc1i6V9Nif2mizo0kcDAAAA AABGUZuDF2tm32Da5uA/S7mubQ4+zHYH165dm1q1alWXZvOajxTjN/cqfe1j 3w7mXwwNTM3XU/oF8iqlw7ivj4+jx5F2PjddRlz2k/eC0mX0vh3z8c2z/B/M 5SeqcX51i9FZVodkytVXrbn7zzPH+OnjO/j3B+L4ke3L+P6NC/iO2Bl8y7JJ fNPSCUrFfMI322rZRLuaxLcsFzWZb187g+9N+JofSlrMv9u1ip88mMB//m4b /7/vd/PffjrIz/7yHT//xw/8n79+sd6vyP0i/6to69pDOcd4lGVvrby3M1y/ mMbr/UhV3bUPBQAAAAAA3Mw2B/8CU+bQszUHX61atbtiLfF8+fLx0NBQXrBg QV60aFFD8/nBZVWtefmnVb781Wahqeu9RY3y55VLhXFvL68Hxucnsni5crz6 ww/zsnQb3t7e1n/3ostWLhnK5w5JO29951c+1rXf7+xN6XM/HMT5n6M4v6+a Rw135/Z//PI/f/Czp7/lPxzZTPk7hu9cN5vy9gS+YfG41Nq45GO7Gk+ZfHxa Nk/J55tU87mS0W2VtGJKSn2q1MpP+daVU5VaJWoa35ZSO0SuT/yGH966hB/f t86a6f/4+Qg/98cP54/sWVXWrUeuOTmbz8VebM8y5XW4m+o3pqwtJ/rkz1CJ XoWuTJmnBwAAAAAAz+JwDp4y+RmxxjhzkD1EJvbz87Oud5Y3b14eEhJiXfes cOHCmjP80Hdrps5nf/JesDWTi0x9dLEXr1mhYKbz5j50vzUol+/bvZvfu3uX L46K4lUpq9v//NFyBfmhKK/UjP7RG8F8+xcpc+i/vefSHH7v3h3K4WetufbU wUR+YFOUNRMnLhyt1KIx1tqwaKxSi8dqyOcPZvTM8rn9HPqD+XyKw3yemtFX f2ZX0/n2Nbb6nO/bMP97dx+cAAAAAAAAwNi///47txzl3mLFilkzd4ECBaxz 6MHBwdZM7u/vn26/sIwl5rLFzwMCAnhmc/D16lTk9w4Xtmbme/sZb/dMGD+2 VMnUk/sG8eIFgjO93eDAQD7OYkmXiVs0aWKdU7ddpmhoXj6qZ57UfL5ykh8f 3jVYyecn6xuSw+/fu8uv/Es5/PS31n70/ZsWUB6ewuOjLDwhWtSotLJlc7t8 nprRF6fP6BnzuaM59Ad73LXn89SMvirDHHqGfJ6W0T+31pFtywZJORgBAAAA AAA8FMVP7yVLllzUMgdevHhxa94WuVvkbzGPLvK4yOVi/t0rk/50W4WFMF63 KuOtnvTij1bw54M6M/7ZQMbrVc3H/RzM3Qf5+/PXwsNTc7JYD73uI4/wILq/ 0oXz8urlQnmDamF85gdpPe7fL2P8Jcr/qWu1Z1NycjK/fuUCP/vLUWsW35Pw lTVLx0eNzKRs+dySLp8naMzn6TO643yutcf9gXyeRY975nPoSj7fFffFtZ/2 xoVIOiwBAAAAAAA8DkXSem+99ZYh55fb8nuhQoWs/e9iHv3FFjV4i4aMP1Ke 8bxB2Tqf11oPlynDX+3QgU/8+GP+fKNneI2KD1H+zs/H987D10315Vvn+vC9 87zTrRPX7ukw6zy9NaMn31LN4tcunbPOix/fu9Z6TrbI1plncY353H4OPWM+ 19PjrpLPXdnjrsyhx6yWc1QCAAAAAAB4nqtXr35SqVIll6zXPn50P86/K5Vu LfUVEwN4305BfPZHjA/vznjBkCDVfO7v68tLFwrllUqG8cqlQ3mVMvkfrFKF 0uXzzi3y80tJ3sp93rtoS+P8v2uXrGuZ/3Q0iR/cEm3NudqzeOb5XF+Pu+N8 bqYe9+1rZ9z7bkdMXYmHJwAAAAAAgMeIjY39xRXZfGTEIM5PNnhgr7M93/jx 4d2CU7N07YoFMl23XWt5UVUvVzBdPm/fKIzf2yfuz4sf2PSNNYuK3OxcFs9q Dn2US3vc1fdZ09jjnjGfZ9HjLmr/xvk/c868ZBybAAAAAAAAnoJzXnLEiBGG Z/OIYQM4/6HRg/uQp+yt9l54vtQs/XqLfDxvYIDufC7OUQ9vEpIun7d9Sjn/ /Prugi7K5ObpcVffZ835HnfR8//tjmUDZRyfAAAAAAAAnoLyeffGjRsbms0n jHyN8+NVMs3mom7v8bLOb9v2Pl/xiR+vVDJUdz6vUCI/XzTGPzWbb5jhywe8 ks96X79ueNwt+dzoHnfVfdYM6XF3nM8zm0PfHffl1YOxc/PIOEYBAAAAAAA8 wbFjx9YZlcsrlC/Nv41/mfNDAQ6zua0iugXz1ZP9UjP1C0/m5yF5ArOdzYOD Anjzx0PTzZ1//G5eHv+ZMob9K7u4IZ+bpcddJZ9r7nHPPJ+LOfTD25Z+Leco BQAAAAAAyP0WLlx41tlcXu6h4nz0e0X4zf2Fsszl/EhBJTfP9+P9O6X1uB+I 9OaPVy7A8wT4a87mgX5+vE6lAunWbv9usRfv9Gwov7bdi9/YHUY5eYSb87nR Pe769llLn9Ed77OWnR73Xevn3Nq7aVFRWccqAAAAAABAbsU5zz9p0qS7enN5 +bLF+ch38vN/k7KeLxd188jjPGnpUH5xR2nrf/cJD+Gxn/qmZus933jzp2qE 8RKFglXXixN7rBcrkJc3rBbGd37lk27ufPy7efjicUHW2/8utq2bsnn2etx1 n4NuP4euc581rT3uGfO5LaMfSlocK/OYBQAAAAAAyI2uXLkyrWHDhtnO5aVL leADuoTyPxN9NOVyUfcPBPJtS/pas2xi9DD+d1IV/n9rffj/moXy/ZFp898n Yrz4hHeDeK2KBXjFkiE8X1Cgdf03UcGBgbxCiRBeo3wBPvbtIH58qVe6bL56 ih/v3ia/dd32f7aVd2M2V8/nWnvc9e+zprHHXW2fNY097lR3D22MrCr72AUA AAAAMDGxblNLquFUK6l+ZWnzjTMkjgtMinPebMiQIcnZzeadXyjIT67w1ZzL bXVyffN0eTYhKoKf3Vyd753nx99olZ8fjk6ftb9fxvi6T3356F55+HsvB/Pe HYL5qB55+FrK4CdjWLrL2taEe6VpKP9nkze/tTeYb140yM353EGPu1o+N0mP u/o+a9Mz5nN+KGnhHtnHLwAAAACAiTVmjs/TRT6HdCibh61YseJidnL5YzWK 8oSZgdnO5aIu7yxJefzB88DFueG/bazLt8z2550oWyfO8H0gd2upr4cH8Nea h/IzsT787v4AvntZDwnZ3HN63HesmXF//5bo52QfxwAAAAAAJtWY6iLVJqqJ VK9Q/cWQzyETlM/fatKkiaZcXqZ0CW55J4Tf2OmtK5uLurC1AmXT4Q5z7f9t eMK6J/obLfPz0T3zput3VysxZ/7ey/n4kC75rOvB3dvvz/cu7yYpm2cvn5uy x13DPmupc+hbok/IPo4BAAAAAEzKJ5N/O8OQzz2OxWLxDg8P92ncuLFvz549 /eh7/5YtWwbQfwfS90F169bN//fff0/Tks1bNSrET67UN2eesX7bVEc12x5f 14bf2efL46YF8NdbhvL+r+TjXw0P4Btn+lrXZxf97zu/9uHrp/nyz94P4j1f DOHvdgjhx5YovfaXdpTk25e+JzGb6+xxV91nzfked9V91jT3uD+Yz6mSj+1e /ZLs4x0AAAAAIIc4w5DPcz2Rx0X+fvHFF/NR/s7frl270NatW4c9//zzBV56 6aWCL7zwQiH6eWH6vkilSpX65suX759HH3305mOPPeZw3faHKxTn62aX58kH vAzJ5rbas6K7arbdtrSPNceLHvU/4nz44rFBfFSPYN6vUz7+TvsQPui1fPzj d4J54ucB/Mo2ZT7/9t48/FRcM+v57PKzuYN8bnSPu0o+1zqHrneftQznof8o +/gHAAAAAMghzjDk81xJZPLmzZvnpTxemHJ5iTZt2pSkDF6qbdu2pSmPl2nV qtVDlNPL0vfl3nzzzepvvPHGjHLlyl2nq3Jvb2/u6+tr3aOsbNmyvEKFCqm5 vEqVKjx6Rji/e7iYobk8rc+9oqaMmxg9nO9b8QY/HtvG2vv+15Zq1vXYL+8o wa/sLG49n/2PzTX5kTUv8w3Rw0yQyY3ocXecz7X3uOs9B11fj7uo73atbSv7 9QAAAAAAkAOcYcjnuYroT6c8XpSqImXwh+lrZcrgVVq3bl2Vsvkj9H01+v7R Tp061RwzZkyfiIiI7fXr17/vlbKXeJ48eXjRokV54cKFeXBwsDWjixL//vDD Ffl/3zX+1hW53L5se6zl7nJun7X0Gd1xPjekx111n7Use9z5waRFp2S/LgAA AAAAcoAzDPk8xxPnkItMLnI4ZfJa9H1t+r4O5fC69PXxNm3a1KNsXp++b9C3 b9+OU6ZMiZo6deoFuiz38/Oz5nIxZx4UFMQDAwO5j49P6tr+4nsxf/7888/z 9957j8+cMf3M+nkvLLmyq2hi8kH/m67I5z8lNDZBfnZXPncwh657nzVtPe7q +6wZ2+O+I3Zm8nd7VrWU/DIBAAAAADC7Mwz5PKfySjl3vBrl8Sfp61OUx5+m 75+h7xtRJm9M3zeh75/t0KFDK4vFMn769OkHZ86cmdy+fXvrfDjLZK898e91 69blHTt25EOHDuWzZ8/mc+fOTa1Zs2Zdony/4/3337e0b9fq9VXTKwy/vLPA Bn7Y/5ZR+fzqzqImyM+uz+dG97ir7rMmucf90JaFWMsdAAAAAEDdGYZ8nqOE h4cHp/SsN6I8/jx934K+b0l5vBV935q+p2/bvEDfvzhw4MDBlKUTKWPfsOXr Ro0apcvjYr68evXqXGT2wYMHi/ydLo/TdW9++umn31K+X9yzZ8+RdNs96KZ7 0v30ou/fpu/foa/vvv6/lv3jvqgy6da3tX5IPujndEbfsnigCTK0u+bQXdvj rr7PmhE97lnnczGH/u2uVc0lv3wAAAAAAMzsDHMun1ejKmzYaCBTYh80saZb y5Ytn2zbtu1L9H0HysQvUzYOp+870ved6PtX6Pv/de/evd+ECRPWUs7+xz5n 22rAgAG8Tp061vnx4cOHPzA/PmfOnJuTJ08+TD9b3LVr11F0u/3odvtTDaD7 eV/Efvp+EH3/AX0/mL7/8Lnnnvukfv36y2vXqnF0aL//3U5a8j6/tL2UU/lc rOsmPz+7K5+bscfd8T5rWnvcM+Rzfihp8THZryUAAAAAABM7w/Tn8wCqZJY2 F3uRSvSwbqSaS2Wh6knVlCk5PsTp0XoYcU65yOQid1O9Tv/9Bn19k7JxV/q+ G33fneqt9u3b9x42bNg3U6dO/Z4ydnJmuVyl7tH1fhwxYkTc22+//Tnl/2F0 m0OphtH9DKf7iaDvR9D3I+l7C30/qnnz5p82bNhwVa1atQ5XqFDhbIkSJQ7V rFZxQ9Tng+/ZsudPCY2cyuenE580QX52fT53a4+7zn3W0s+h6zwHPfU89BVN Zb+uAAAAAABM6gzTn8+DmZLBv6RaTyXmxv5lmZzTnFL3qM5S7aVaSfUZ1WCq zlTPUFWkCtT7QHILsUd5u3bt6tHXzrb+ccrEvUUPOX3/Hn3fxzan3bNnz8kT JkzYM2vWrP+ykceTP/vss7OjR4/e2bdv36gOHTpMoNsbQ7c3ju7jY/o6nmoC ff8J/ftE+n4S5fG5Tz755MYaNWocL1OmzJ9FixbdHBISEuHn5/c4DTnvmGHv JSUu/jjZPnseXt3JqXx+fmslE+Rnd86h6+tx17/P2kTnz0HPfo87P7R10Xey X2MAAAAAACZ1hrnm/PMwqrpULzBlDt3ClDl1Mbcu5tivMsc5/ibVaaqdVDFM yfEfUoVTPUVVnsrH4PFKJ/Yjp2or+sgz9o9TDaHvPxLz2h07dhwXERGROH36 9PNaM/mMGTOufPzxx98OGDBg7SuvvDKLbmsK3danVFPpfqbR18+optP3n9PX mTSOL5s0abKubt26eytWrPgL5fHvKY/PpGG2oMprG3Pv3r3aJyyffVOZB06f O5OW9Hcqn9/cG2KC7OzOfG7Rls81z6Hr22dNa4+7+j5rjnvcd8TOSj62Z1Vj aS80AAAAAADzOsPkrQ8nMrzoexf9rl2YksFFho+lOkj1J3Oc4W399AdTLj83 5fpdWFo/fbD7Hoo+Yl80MVcu5sTt+8epRqfMaY+1zWvTZeePGzfuyOzZs29n lcfpMncnTZr060cffbS7W7duy9q2bTuHbkfUXLrdL+jrl1Rf0e1+TV+/oa+R zz333Lo6depseuihh04VKFDgx9DQ0HklS5bs0rx589IxMTH+GcceEMAqb4tb eGPnulnWPJhZ9ryzP8ipjJ4YPcwE+dn1+Vxrj7vuc9DN0uNuzecz+eGtS4/I eL0BAAAAAJhMAapCdvUbU7LuVxn+Pa+jG3Az0e8u5svFvLmYPxcZXMyni3l1 Mb8u5tlF37xahredEx9JNYEp8/liXl/M74e576GkEWuwt27duqk4r1v0j1NN zmxOu1OnTl8OHTp01/Tp0y9lkcfvUR4/S3n8IOXxWMrjkXR9UVF0u9H0dSHV IrrdxfR1CVVMs2bNNtSrV29bxYoVTxYpUuTXokWLrq1du/bw/v37P7tmzZrK q1atKpuQkFCcqkBiYmLepKQk38wey6VLl8rGxsa+HbMkesXq5ZFnNsVG3dqV MP+eyH//bCvvVD7ftrSPCfKzvHyeW3vcd67DHDoAAAAAAPmbqc9J22qOrAHq IOZ2S7D0/fQih4s8LnK5yPB3mPZ+enHdfix9P723EQN9/vnni1M2fpUys8jf os98dsY5bTGf3adPn43jx4//P8rd9x2dQ/7pp5/+O2LEiO/ffvvtre3atVtB t7GMrrucagXVKqrVlMfX0Ne1VLF030kNGzbcWqVKleOUxf8sWbLk1qeffnoW Zfoe69evb7Fu3bomVA2p6lI9Spm7ElUZyupFKauHxsTEBFkslsx+D15UVai6 lChR/KsB73b9bfHXE65vXfVZ8q8bH3cqn+9b8YYJ8rN7Mnq2etxV91kzS4+7 43wu6mDSQpyHDgAAAACeLjfmc63s++ntz4m39dNfZo5/H7eZ0m8vLmd/Tryt n15keD9Hd1yxYsXGVatW/bply5YLHc1rv/rqq7GUt09+/vnnma71Rnn8UkRE xE+9e/fe//LLL2+g662niqOKp9tKoK+JVBvotjbS102Ux3c1aNBgR6VKlX4s XLjwnw8//PCOjh07Rk+dOnXk2rVre1N1pxzemSqc6kWq5ymPN6Z6gjJ57dWr Vz8SFxdXgaoUVWGqEKqAlN9hl4CAgM+bNm16ZMI4y58bYhee37954X8i/9nn zv/b8IRT+fzo2pdMkJ0l5XMT9rjr3Wctsx53637o25ZgP3QAAAAAAMiMmBsu TiXWJG9L1YdqPFPm4ZOofqD6j6nPw/9MtZ0qmmpinjx5RhQrVizBy8vLug8d ZdrrzZs3X2+b16ZcHdurV68948aNOztnzpx0c+UzZ868O378+PMDBw784fXX X99Ll0+i2kq1ja63nb7uoNpJt7WLvu5u0aLF0WeeeWZ/jRo1TpYqVeoC5fGT HTp02DZp0qQFlL0nUY2liqD8PZiqn+hJp+pK9Spl9Q5UbSiXN1u/fv0zVPWp akVERNSvVq1aj9DQ0Mm+vr7x9DiO+fj4rNu4PuaH/Zui7onMp5Y7Tyc+5VQ+ PxXXzATZ2T35XN8+a0b0uOs9B32qw3yudQ79wKbI7936CgcAAAAAgNxGzCHb +ulFD7zohRc98fbnxN9lKbnd39//FrPL8TVr1jwWHh6+86OPPjozffr023Z5 /N7YsWP/6d+//+n//e9/hylz76PaT3WA8vhB+nqI6jB9f4S+ftuqVaujTz31 1I5HH330WPHixS9UrVr1R8rxRymPb6WcvYJy90Kqb6hmU02j+oRqNOXwYVSD KKv3oepJ9QbVK0uWLAnv1KnTB9WrV58RFhYW6+fnd4wy+S7K45+nPM4Stl8A 59zn6tVzDX/+btv8I9uW/iFyXma586d4J/dAT3jKBNlZ4hy67h53x/lca4/7 A/ncBT3u1v3Qd658zZ0vXgAAAAAA8Ax169b1o/z8WosWLTY2atTocL169U4U KVIk3Z7wvXr1uizOK6dKnjBhwtVBgwb9+cYbb/xImftYSh2nOkH1PdVJqlNU P7Zp0+ZkkyZNNlO+31G6dOmzJUuW/Jsy+h8RERFnli9f/i1l7z1UW6kSqdZS LaOKpuz9FdVMqk/pv8dTWag+mjdv3lDK8zNq1669IjQ0dJ+/v//PAQEB8ZTJ I2icz1KFaH3c5879VOHEvnVzdq6bfcF+r7Uf4551Kp//tvExE+Rmifncfg5d 9z5r4zXlc0k97mIO/TcXvRwBAAAAAMBDUYYuk3Ju+VH7nN2yZcsfqlSpcr1s 2bL3O3bseOejjz662L1797Pt2rX7hX5+mkp8/T+qM1S/Uv1GGf93yuO/P//8 84fq169/oFKlSn9SJr9Eefz68OHDby9duvQyZey/qX6l+pHqGNVBql1UW9au XRtPeXw11VL670iqLz/55JPo8PDw9Q8//PD2PHny/ER5/Iifn98sGvorVA8Z 9XvYETu95q71c1ZRXrwl+tOdyed/bqlmgtzsvnyur8fdcT7PCT3uO2Nn8RP7 4wYadfwBAAAAAIBH86I83Tklj6fL2q+99tpfH3zwwZU+ffpcomx+jv7tL6q/ qcT356kuUP1D9S/VpRYtWpxq0KDB4YoVK54rU6bMxbZt214bM2YMX7ZsGaeM bau7VNep/qX6kzL4/9HXU1RHqfZT7ViwYMG2d9555zDd1rFChQr9HBwcfIpq hbe399tMWd8t073SjBQ715Ln7NZ6a53J5xe2VTBBbpYxh65vnzWtPe7q+6xp 7HE3YJ81W+1N/PpS0jxLoKuPSQAAAAAAyL1atmwZ0qZNm+hMsvZFkbepLlNd obpKdZ3qBtV/VDepblHdpkx+rl69er+XLl36MuXpfwYMGHB/3rx59nk8s7pN dZXqAtUfs2fP/q13795/NGzY8DTl8T/y5cv3Y0hIyAIa4utUFWT9fihjv6ol h1/cwviWOYz/lZj+3y9tL2WCzCwjn8vpcde7z5rWHndH+VzMoX+3c2Vu3DMi t2rDtO0D8qak8QEAAACAh3nxxRdri/PC7bM21R2qu1T3qO5TJVPxjEWZ/GLN mjWvVK5c+XL37t1vf/nll1nl8dRatGgRj4iI4HT/V0uVKnUuf/78vxcoUGB9 QEDAIKasWefyuXGt+CHWIqts/kcc48ULKe/n8+Vh/PDCtJ9d2VnMBJnZvfnc 6B531X3WDOlxd5zPs9Pjvmv9nJs7N3xdIsuDCswA+RwAAAAATIMydoOU+fEH srejat269a169er99/jjj18Vc+QLFy7MMouvXbuWT506lb/11lv36tevf45y +L9hYWGnQkJCZohhMLs11c2I72Plssrnn/RJ/57+nZfTfnZ9dyETZGZZc+gy e9xV8rmLetxFRj+UtChB8iEL2tjy+XWqQioVIGuAAAAAAOAZKGs/ldKvriWT 36VMfrtJkybXxZz38uXLVfP44sWLrXPj4eHhNypVqnQhf/78fxcuXDghb968 g5kyN+4n+/FnB+fMi3L2FUfZ/NhSxsuVSJ/PJ/ZN+/l/u0NNkJdl5XOje9z1 7bOmtcddfZ81bT3u9PXurvg5T0g+bCFr9vkcAAAAAECKNm3a1Mwqm4tM/vjj j9985plnrgwbNkw1k8+fP58PGTKEt2zZ8nKpUqXOh4aG/l6wYMHVfn5+Peju HqHylv2YncUPsbiMufzOXsY/fINxXx/G/f0Yb1qP8cerMf5eR8Zv7U673K29 wSbIy+7P51p73HWfg24/h65znzWtPe6q+6xl6HEXtXfD1yfE5zqyj1tQhXwO AAAAAFJR9s6Tshd5Zpn83lNPPXWX8vttsd76mjVrHsjiq1at4pMnT+Zdu3a9 XqtWrbNibjwkJORAYGDgeLr5llRhsh+jK1DOfsM+m/+wkvF61ZS58hqVGD+6 2HHv+939ASbIy+bJ51p73PXvs6axx11tnzUne9x3rpuVfGhzdA/Zxy2oypjP /amC5Q0HAAAAADwN5fDxtjzeqlWrW08//fT1unXrXg8PD785bdq0B/rUx40b x7t163a7QYMGF4oWLXpBzI0XKlRonZ+fX2+6uepUPrIfkzvw3awAZe0byQcY nzaQ8aAAxr29lfnzm7vVz02/v9/HBHlZTkZ/oMddLZ/niB53zfmc70n46mJi 5KS8so9dcMiWz+9R/cjSzk/5jyqJ6g3mIX/fAAAAAMD9KFPXe+qpp36tUqXK zbCwsGT6mvzaa6/xd999l3fq1Ol6o0aNLtC//V2wYMF/8uXLJ+oM5fFV3t7e /enqT1J5dNY4uojNbN5AeQ9fuijjm2Zp3wM9IXqECfKyeebQc12Pe8Z8npLR D2yOjpR93IJDWtZv304VKmuAGeSn+ohqD9U/VLeofqWKpxpAlUfe0AAAAAAg u4KCghoGBwdbROXJk2c4/VNPu2pP1ZCqLMN6xZnp7OXFLtNX3rM941e2ac/m ojYsHGqCvGzefG7KHned+6zZz6FT3dmd+EVD2QcvZOppqi+pWlOVZ8rfPZHF mzIl89oyerysAdp5luocU/8soaK00QEAAAAAuEcBqhimvP+9YOnBFmUnl9tq 08LBJsjLcjJ6tnrcVfdZc77HXXWfNRf0uKf0uX/PuSXHr5HogeaytOzbROI4 RO/SzZRxiD58sa5BVabsSyn2w3idajlVGVkDBAAAAABwg1ZUfzHlffEaqiI8 iflS3j6U3Xy+ZfFAE2Rlk+Rzo3vcVfK51jn0jPncyB73netm8/2bFoyWeyiD DvlYWi6eImkMomf9NEvrtffoc4wAAAAAwCOJ98Bi7iyZ6ipVF/sfUt6uQnUT +VxbPtfX4+44n2vvcdd7DrrRPe6zRd1IWjW1rIRjGZyznynZeIWk+++Vcv+3 GebHAQAAAMDzPEb1PVPeE29lyvn4D+CHWH/k8+zOoevbZy19Rtd7DrrGHnfV fdb097iLjL53wzdJ7juMwSCHmPK3YLmk+9/F5H4+AAAAAAAggx/VBKq7TFkX uR+V6jnD/AD7Rns+f98EOVl2Pncwh657nzVtPe7q+6w53+Oums/t5tB3xc66 v3/DvDddfyiDQQoyZd5a5OOJEu4/wO7+36WqQDWP6izVHaace7OKqpmEsQEA AAAAuEplqn1MeR98mOpRLVfiSSyQsvdBLfk8aYln53Oje9xV91kzpMfdcT7X OoeeMZ+L2r1+7vm4aEuIKw9m0MSXKkjl52Lf8yUsbX24J90xqAwq292/WL/g mt1/37H7XtRUCeMDAAAAADCSmB//kOo/qntUFqbMo2vGj7BKlL9/yzKfLx5g gpxshjl0mT3uKvlcc4+77n3WlDl0qgNbopcYfyhDNhWiukA1naot1cNURZky R/0KS/u8TmZveQO7MYi/T2ItjK4sbY24R6jW2V2mp4QxAgAAAAAYoRTVBqa8 r/2J6gm9N8R3swL8ENuIfK4ln5uxx93xPmuG9LhnyOe71s26e3hL9HNGHcig i8jnanuJ20r0j+eRNMaGGcbyWiaXEX0AtvUyfqfyctvoAAAAAACMIfYLvsyU 97RinfZ8zt4gj2E+lMMnOMrn25b0/VF+Rpabz93a465znzWtPe6q+6xl0eMu Mvru+C/PxsZaZOU+UHJtZ6a8/o8w5Vxu0TN+nSl7jEdSNZU2OkV1lpbNf2OO s3dXu8tVc8/QAAAAAACcJtZ7imHK+1ixxlILo++AH2KvUR7/J2M+P7DizaHy M7Lscq7HXf8+axp73NX2WTO4x33X+jl8/6bIaKOPP8hVxN8rW+7eoHK5+naX a+WGcQEAAAAAOKs1U+bIxHvYlVSFXXVH/AgL5QfYXMrlybZ8fmFnicqUTy86 m3HHDHqND+zZji+fO8QEeVtvPrdoy+ea59AnuLTHXX2fNb097ta59Lu7E79o 46rjEHIF8TlidvJ5S3cMSsV1pn6+gH3tlDRGAAAAAJBHrKUkeliTqS5Shbvr jvkh9jxl8yPWjH6ElY2PHvmZM/n2tZcapb63LVOyMF87b7gJMnf28rnWHnfd 56CbpcddZZ81+zn0XXFzz2I9d1Ah9lPL6tzybiwt81Zx07gcyU4+nyVpjAAA AAAgh9gT6TRT3gtuoSrj7gFwzrwpp3fmR1mRxEWWKpRPk/Xm22KFw9K9v51m ecsEmduYfJ4jetx17rOWfg49Qz6n2hP/ZZS7j0sPFiB7ANn0DEt7zXfO5Of2 68P97MZxOSJ68gupVF+W9njqSBojAAAAALiXP9UEqrtUN5iy75Ap1jWmnJqk J9uKnnYfH+/UbJ43TwCPmT3YBJk7+xk9Wz3uqvusOd/jrrrPmuYed53noKdk dPq3u7vj5raTfWx6gJpMmYduJnsg2ST2dxOve7G/2pssbT35qiz9/modZQwu m3YwZaxHZA8EAAAAANxC9HfuZ8p7wINM2SPYNBKiLB2zk2dFBn+ibhXr++/i RcJ4k4Y1+LNP1uBTR3Y3QdY2KJ8b3eOuks+1zqHr3WdNa4/7rgxz6JTPz6HP 3aVqU11iSsZtIHks2SX2lxDnattyuDhX506G//5I2ui0q8zSxvyu5LEAAAAA gGt5U31I9R9T3ruK732ljigTB+f29KOcelZLlp007E1euGCI9f3sc5TJV375 kQnytfP53Oh91rT3uOs9B931Pe6i9iZ+s0z28ZlLiXnmc1Q3qZ6VPBa9fKh6 MWX+WayjIf7GiV6AhVT1JI4rOyYxJZuLv9GhkscCAAAAAK5TimojU977/cCU 9YxNKz5y5Hi1DBs7P4KHt3mSe3t78bx5AvnQPuEmyNUunkPX3ePuOJ8b0uOu us+acT3uSp/7nHv7Nix4SfbxmcuUY0qOvUXVXPJYPJkfUz4jEX+jsd4CAAAA QO7VheoyU3o8P6MKkjucrG1YbClBGfVOZtl13qf9eJWKpaxz5lXp6/yp/UyQ p92Qz+3n0HXvs6atx119nzV5Pe5Kn/uX/25a8HFB2cdoLlGCKWumiXUo2kse i6frwNJ62xtJHgsAAAAAGE9kmBimvN/7g+WwNZ8opy7LmFuHvNvBuu6bl5eX dS+1dfMjTJClXZPPje5xV91nzSQ97qr7rKXWXL4v8ZtY2cdnLlCU6hTVfaZ8 hmdW+Zmyprkp1q90oXim/K3+SfZAAAAAAMBwbaj+Ymm9kjnuXMaEBZamtry6 6quh1vPL6Z95gdBgPn5IFxNkaHfNoevbZ01rj7v6PmtG9LjrPQd9lsN8Lvrc d63/4k3Zx2gOFkb1LVP+PvSWPBY1eVnaum8tJI/FlUoz5XMS8TiHSB4LAAAA ABhHvJ+dy5Re9n+owuUOxzmUU4/OHPc2L12ikDWbP16zEl8y6wMTZGd35nMz 9rg73mdNa4+7aj7PosddyegzryetmtpY9jGaAwVT7WFKFuwveSxqxDh3MWWc wyWPxdVGMuVxivMMikkeCwAAAAAY4ymq00x5nyf2/M3p7/O8GjV4NMbfz5f7 +vrwXp1b8LhI2ZnZvfncrT3uOvdZSz+H7jifG93jvjtuLn2d/e+WmE8qyz5Q c5BAqs1M+RsxRvJY1Ihx2taz/FjyWFxN7KtxhimPdbXcoQAAAACAAfypJjBl 7uU6VU+W88/VFOfOr2LKnub3p4/uaYK8LHMOXWaPu0o+l9jjnprR4+ae2hjz YX7ZB2wOEECVyJQcOFHyWNSIdczXMGWckyWPxR2eZ2nrwrWRPBYAAAAAcE4V qv1MeW8n9v0tL3c4hniG6jemPKbIJZ8PnCk/J8vO50b3uOvbZ01rj7v6Pmsa e9xV9lmzn0PfHfeFuM7eNV8Pzif5uDUzX6oVTHlNzWHm/fxO7GG+nCnj/IKZ d5xGWsaUx3uWKY8fAAAAAHIe0RP5IdVNqtsp3/tKHZHzxLyZ6AO4R3WJpZw7 v2Hh8EqUU+/Jz8py8rnWHnfd56C7scdddZ81nT3utoxO/70uKcmS018DriD+ VixgSgaMTvlvMxLjms+UcS5inpFVCzPl77d4zOMkjwUAAAAA9BFr/W5iynu6 o1Q15A7HEOWo9jLlMYk1ocra/zAucuRC+VnZXPlca497xnxueI+72j5rhvS4 O87n9nPoVMm71s2J4dxi1vwpywymvK7EXotmzryfM2Wca5nyWZ0nGMiUxyzW 88wNvU8AAAAAnkacW36ZKXvxiLnmQLnDMcQrLO0xWVgmfQAJUZY68rOyvIz+ QI+77nPQzdLjrvMc9HQZ/YF8Lv797q7YmZM594i+aC2mMiX/rWfKOhVmNZYp 44xj5h6n0b5nyuPeLHsgmXiRaiVTzjW6xZRerf+jWkzVROK4AAAAAMxArJdm O09RvF96Tu5wDCH2gotkaedeqj4myqrr5Wdlc82hm6nHXe8+a+kyuso+a1p6 3JWae4fuaya3ePw8utiTTLy2tlIFyR2Kqo+YMs5tVHkkj8WdGrK0deH+J3ks 9sTno6LXgtuV+Ow0OcO/TZc1QAAAAADJXqD6mynvicTe5iFyh2OImixt7kjs BVc4qyvERUY0kp+VzZ3Pje9x13sO+lSn91nT2uP+YD63ZvS7O9fPmWHx3Iz+ AVNeW2LtSDP/vbD1dx9g5h6nJ7E9J6LEmoLVmXK+gehrqM+Uz3tsP+8oZ4gA AAAAUgQzJY+LeYsLVB3kDscQou+4H0tb164fy8YazZRXE+XnZTkZ3bged8f5 XGuPu+o+a5J73EXtif/SmtF3rZs1NyYmxsznXLtCL6b8zThMFSp5LGrEuTpi nMeoCkkeC6TZx5TsfZxlvl6B6Hv6K+Uyy904LgAAAACZijHl/ZHt3MTScodj iNQ9zal+pKqb3RtYHx1RnfLqffl52QT53JB91sZryudm6XFX32dtbrp8bsvo W1d/tixmpiXY6IPZpF5lSi+y6E3JsidFItHPLcZ5kqqI5LFAeuLzEvE3er7K ZRJZ2noBAAAAAJ5A9OXGsmzOL5uY/Z7moidA917VlFcXy8/L7s/n+nrcHefz 3N7jbsvoVPe3rfls26ZF44oadTCblNiPUOxN+AtVKcljUSPWHbvDlLXGzDxO TzWPpe0Nktn5IWItgz9TLjPKjeMCAAAAAOdluqe5MxIXWap45n7ozu2zprXH XX2fNY097qr7rBnQ466+z1rGfM73JHxFl5n9ffxiS1lnjz+TasWU80XEOosV JI9FTUuWNs6KkscCmXuI6jxT8rdYq70yU3K6WDeuNtWGlJ/9xLBmAAAAAEBO orqnuTMoq86Xn5dl5XM5Pe7q+6w53+Oums8197g7zuei6H5+27B4zItGHYcm 0YjqP6asIfmw5LGoET00N5gyzsqSxwLqSlJ9yZR9L8Xfb9HvcC/le5HdpzFz r20AAAAAuZPY66cT1TdMORdcvLcUcz+/M2VdnDYuvn5OluWe5s5IiLJUpMx6 V35mdm8+N7rHXXWfNUN63B3nc61z6Pr3WfvigXxunUdfN/tK0vIpY+fO7eln 5DEpyeNUV6j+ZcqeCGZlG+dFZu5xGkWsobadqpvsgegkPj9ZypT/v+IZSvz/ 2HyGcxMAAADAvcQ5dtfYg+9NMtZKqkAXXD+nytae5s6gzLpUfmaWNYcus8dd JZ9r7nHXew66cz3uqRX35e2tq6cui/vmIzOvoZYV0Wsszhm5StVA8ljU2MYp /h6aeZxGEZ9Fir/r4m/g55LHokc9pjxfYvziM4bGVGFMWW+wBdWRlJ+Jc9DN 3K8BAAAAuYtY79mWMScz5X1J+ZQS/bG2PWhs650Zff2cKNt7mjtjXeTwqvEe t5a7q3rc9e2zlj6jO95nzZAed9V91rT3uIvam/A135v4dfK2NdNPJiwc1daV x6mLVKU6x5R9Cp+VPBY1VVjOGKdR7LP5HJbz1vYU4xX78onxi/+Pymx/NfF5 8ncpl4l339AAAADAwwVQvckc92WL9y22dXLuMmXvMCOvn5M4tae5MyizrpGf md2bz7X2uOs+B91+Dl3nPmtae9xV91lzYY+7NZ8rGV1c98q2VVOnJsXkmD3Y xLoO4hyZW1TNJY9Fjf04n5c8FncQa6gtYMrf9IUs87XPzU6sLWj73Ph/Kpd7 O+UyYv/6vG4YFwAAAIAWYk7c9l5Gz9yQs9c3A/G5wmrmxJ7mzoiPtLSSn5nN kc+19rjr32dNY4+72j5rJulxt8/nexO/oX/7+h7d36H46IjH3Xn86lCC6mem fKb3kuSxqLEfZ3vJY3GXGUz5O7iMZT7vnBM0ZWn/n1RP5XIt7S5XzQ3jAgAA ANCiPkt7j6LnPGtnry+bWI9ZzI85vae5XhaLxTsuauSv8nOzezP6Az3uavnc JD3u6vusGdHjnr1z0NPyuZLR91HRbZ/fvHTC9MRISxF3H8saiP3bf2DKmouv Sx6LGjHOU0wZZxfJY3GXsSyt39tf8licYf//SR1VLtfD7nJl3DAuAAAAAC0G MuX9iXgfquf9vLPXl8XwPc2dERdlGS0/M5tjDj3X9bir7LOmtcddNZ8npM/n oui/79JYj9Hv91VusZilR7kA1bdM+XvRW/JY1Ih1xGzjfFfyWNxlCEtbSy2P 5LE4S5xbLtZnF49nG8v8PCXx9/9gymX+cN/QAAAAAFSJvm6xj694j7JEwvVl EevbuWRPc72UvdYsyfJzs/nyuSl73HXus5Z+Dt1xPtfb456a0TfMs9bu+C+u bV01fdGmhZbykg9xcV78Hqa85vpLHouanDJOIw1gyuMVeTW/5LEYZRJLmxsX 63yKc5bEeiris4enqHbY/dxTnmcAAAAwN7Hm20amvD85z5RzLd15fVlcuqe5 M+KjLbvl52b3ZvRs9bir7rPmfI+76j5rmnvcdZ6DbnCPuy2fWytx3v3tqz8/ Q7+biNhFlkISDm0xn7mZKX8rRku4f61yyjiN1J0p66OdoJJxbLiK6M9fxdLv Ayr+5idn+LecuD49AAAA5D6i3zWKKe9PxLrETdx8fRnctqe5XglRlqHyM7Pk fG50j7tKPtc6h653nzWtPe7q+6xp7HHPmM8zZvQN86m+uUtj+oF+nx9sjJng rnlSMWeZyJTX3UQ33aceOWWcRhLnZovze36hKil5LK4i1h8UOV30sIt9OcT/ X51hSr9XU3nDAgAAAEhlv3+OeL/S2s3Xl8Gte5rrtT7S8pj8zOzefK6vx91x Ptfe4673HHT39bir7rOWjR53Wz7fv1Ep+vlNGsPBuChLu4Nz5/q58JAWvSkr mPK6m83MO0+ZU8ZppFZM+fstPqusIHksAAAAAJ5K7JcTzdLmvbObrZ29vrvZ 72l+i7lxT3M9OGdelFf/lJ+bZcyh69tnLX1Gd5zPDelxV91nzSw97o7zeVpG X8D3b1rAdyd8eYke17aEKEvHuOl9Agw+nO0/x4tm5t1HO6eM00iNqP5jytoh D0seCwAAAICnEnNES1latm7l5uu7m/2e5mI/pzpyh6MN5dX58jOzjHzuYA5d 9z5r2nrc1fdZM0uPu85z0NNl9Az5PCWj798UKa5/efuqaTtETo+JsRi1r9ZM prz2Ypi599G2jVP8bTPzOI3yGNUVqotM6SsCAAAAAPcTPawrmfI+VMwlt3Dz 9d0t457mwXKHo11C1Iiu8jOze/O50T3uqvusmaTHXe8+a+kyuso+a1n1uNvn c1EHqOi6l+hxJFJOb3Fwbk9n+t6nMuW1t56Zex9t2zjFOS9mHqdRqlFdoLpG 9YTksQAAAAB4KtG3upYp70NFT2NzN1/fnTLuaf6y3OFkX2Kk5VH5mVnWHLpr e9zV91kzosdd7znos5zeZ01rj/uD+XxBaj631uYocbsX6LEmJUaNem3nmk/y ZfMQHs6UvxVJVEHGv0IME8FyxjiNUpnqHFM+XzXd2pgAAAAAHkJk6zimvA+9 Q9WJKXvoOKpAg6/vThn3NH9I4lh0i4kJ96G8el1+ZpaRz83Y4+54nzWtPe6q +dwkPe72+dxW+xLnXd22ZvqBxEWje8fFfKxlTcUPmPL620cV4tpXilNs4xR7 YOeVPBZ3EH8Lf6O6S9VW8lgAAAAAPNmjLP1er1nV2wZf311Mu6e5HpRZd8nP zO7N527tcde5z1r6OXTH+dwsPe6O9llT63G3z+cHN0fzg1uixWWv02M4tGHh mH7rFw5z9LlXL6bsLX2IKtR9r5ZsE3+jbON01x5zMhWj+pEpfxs7Sx4LAAAA gKfL7fk8457mz7r5/l0iIXLkVPmZWdYcur4ed/37rE3Uls89pcc9Yz5PyegH tywUP7+1Y+3MU/S7nJOwcESTmJgY23pqrzEl/4k9DE25d2EK2zhPMHOP0ygF qI4y5fOIrpLHAgAAAAC5W47Y01yP+MgR3eXnZVn53KItn2ueQ9e3z5rWHnf1 fdY09rir7rNmQI+72j5rWfS42+dzWx1KWpRMt//3tjXT45o3qjORKes9/EJV SvJLR01HpozzNFVJyWNxB7FugO18n36Sx2I0M587AQAAAOBpctSe5npQVm0s Py+7P59r7XHXfQ66G3vcVfdZM6DHXTWfa+5xX6C5xz2TjM6nTxjMfX19eWj+ 4DsTh3Uds2mhpbzs144DraluU52hKiN3KG4h1gHZzJRsPkbyWIwmPpcVa9C/ JnsgAAAAAJAz9zTPrrhoSyn5edk8+dw0Pe5q+6wZ0uPuOJ9rnUPXv8+ath53 W30xLYIHBPjzAmH5+cqoT8XPb+5aP/vUpmWfzI+PHvHSmq8HZ3fdd1dpzJR9 J/6iqiR3KG4h9rCw7bcxSfJYjFaVKdn8OlUDyWMBAAAA8HQ5dk/z7OKceVFW /U9+ZnZ/Rs9Wj7vqPmtm6XHXeQ56uoyu9xx0jT3uDvZZc9TjHjl7DM+bJ4iH 5AvmS76ewA9tXcwPp9aS5H0b5/21dfXU7fFRoz6IX2CpIfGl9BRTsty/VDLH 4S5iPYDlTPkb+QXLXX1FYl1C8fdf7CPSWvJYAAAAADxZjt/TXI+EKMv38vOy CfK5CXvc9e6zli6jq+yzZkiPu+o+a/p73BfOHcfzBefhefIE8gWzRlv73EU+ T8voS5TatoR+tvgWjffU1hVTZiUsHNUkJmaAO/cZF701Yk+Hq1T13Xi/sogs Pp8p2XwxU7J6blGEpa1B/6rksQAAAAB4slyxp7kelFfj5edl9+dzffusGdHj rvcc9KlO77OmtcdddZ81N/S4L5s3kYeFhnB/fz8+e8pQJZvbKpN8fnjbUmsd 2bY0me7n7Pa1n29NXDy6b2Kk5VHOuSvndh+hOs+UufMnXXg/ZjKdKX8nY5ny mWZuIfqk9jPlsb0reSwAAAAAnixX7WmeXZRT58vPyyaZQ9fd4+44n2vtcVfd Z81DetxFNl+7cCovUrgA9/fz4zMmDkldI+7BfL7YLp8vsV5XjGcnPcYt9Duk 33ky/c4u0u9zBz23PdZGDi9n8EtHfKb3B1PWjmxm8G2blYUp+XULlTt7FFwt gKWtczdW8lgAAAAAPFWu3NM8uyinTpSflU2Sz+3n0HXvszZeUz43S4+7+j5r RvS4O95nLeMcelzMdF6qRFHu4+PDJ43un24Nd1sdTFpovR+Rw8XvR/zuxXOo 9lzTc5i8KWbCZXrONsUvHBEeF21xdt8s0V/zK9VdqnbOvwpzhMFM+Vu5gyqP 5LEYSfTnr2LKY/tM8lgAAAAAPJXYO+cky4V7mmdXfNSID+RnZTn5XF+Pu+N8 7jE97ir7rGnvcU/L5+90e5kXKhjKAwP8ubeXFx895G3rOej76PK7aAzicYnf m3genH3eE6NHJdNzeYme37UbFlpaJVks2e2XKcbSzlHubPwr0pR6USVTHaLK L3ksRpvNlP8fWErlLXksuVkTpqwpKD4LF3sQivNCNlL9T+agAAAAQLpcv6d5 dsVHj3hDflaWl9Gd2WdNa4+7+j5rGnvcVfdZM6DHXec+a+nn0B3nc0c97pGz RolslFoVy5W0/t4SF45yyzFAz/klOgZWb4ge8ZKGl0sBqu+YklW7uvBlaSZi nTTxWcT3LPd9jjmaKcddApW/5LHkZlOZ3WucKWvj2//3SuZh55UBAACAlUfs aZ5dCVEjWsvPybLzuZwed/V91pzvcVfN55p73HWeg67S4y6uvz32c+tj+2RY t3T5vOYjZaUdD/TcX4iPtETHLYpoZLFYMs6lin3W96WMs6+bX6ayiD0sxH4W /0dVSvJYjPY+S1sPNDf165tNf5b2+o5iyroNgujDEJ+P30752adSRgcAAACy NGIesqd5dsVFRjSSn5Pl5XOje9xV91kzpMfdcT7XOoeud581rT3ume2ztjdx nnUMm+h3ZP8cxM6PoExezvr+PSjQn48d3NkEx4X12LiSEGlZETdvxAvPP1FN zJuLHCfGOVLuK9ZtWjAlO/1JVVHyWIz2JlN6IERPQEG5Q8nVAqkuMuV1k+Tg MgNTfi7WcshtxxkAAAA8SOz/I9b8Ef2ZHrOneXbER0c8Lj8Lyc3o8nvcVfK5 5h53veegu7bHfTfdhnhc4vfq6DmIixzJv/jkXb7iiyEmOB7S19p5w3ntauVF luPVKz+0ftU8S6js16wbPE11g+ofqkclj8VorZnSX32GqqTcoeR6Ys1V29z5 8w4uI84ruJFymVFuGhcAAADI4bF7mmeH2CNadgYyRz43usdd3z5r6TO6433W DOlxV91nzbked3E98ZgTpD+/+mvd/Aj+RN0q1nzRpunj1s8REiItd+hnmxOi LF1yaVavy5T9JsXnmbUkj8Vo4nOH/6j+pqokeSyeoBtLy+elVS53NOUye90x KAAAAJDCo/c0z451Cy3lZecg2flca4+77nPQ7efQde6zprXHXXWfNTf0uIvr icer/F5lP7f6Ky5yBH/2yRrWbNGicR1rNn/wciOSKacfXB8ZMYS+5obe3Eeo LlBdp2ooeSxGE581iP9PuEr1uOSxeAr7fF5G5XLHUy5zjXn4eq0AAAC5EPY0 z6b18yzFZGchs+ZzrT3u+vdZ09jjrrbPmkl63MW/i8cRn8Ve5DmhRBZv/kwt a65o1OBRvn7BCC3H0X3K6HsTokb02xhpUcsiZiX6jf5gyr4WzSSPxWjlmPL/ B+KxNZE8Fk9i39/eysFlxDnqN+0ul9v27wMAAPBk2NNch7hoS4jsPCS/Mulx V8vnJulxV99nzYge96zz+W7K5ltXT1M9vzynVdvm9a1ZoX7th63r1+k4npLj okYeiY+2DFm/wPKw7Ne4BuLzhF+ZskZXO8ljMZrYr/5npqxDn9sem9kFMaVn wXaOWWZz48NY+r3W1PrgAQAAIGfAnuZOSEqy+MrOQ/LLg3rcVfZZ09rjbsvm 4jbE70H+82dcvfpSI2tOqFu9Ao+dN9yQ26Ss/mt89MjP4iMtT3Fuur9NRZmy 36Q4F+h1yWMxWhhT9qsXz2kvyWPxVINZWvZeQVWdKeu2lqAaypTPhOz3Q8ea fQAAADkb9jQ3AGWI27JzkdzSu8+aSXrcde6zln4O3XE+f2AOPWVNdvnPm7HV teNz1ozwaOUyfPXXQ11zP5EjT9KxZhHrMsp+3TMlv37LlL+fvSWPxWhiT/Pd THlswySPxZOJz6NmsfRz5PYl9j0db/ff2IseAAAg57Lf01zsoRYkdzg5F+WF y7KzkfzKZo+76j5rzve4q+6zprnHXec56Co97jvo8uLxy3++jK0erza35oNK 5Yrz5XPds8+b5Hn1YKo9TPn7OdTN9+1qYj3QtUx5bJMljwUUjamiqU5R/Ul1 mGoMldgD4ROmPFd/yBocAAAAOAV7mhuMsumfsvOR/MpinzUjetxV8rnWOXS9 +6xp7XFX22dtWy47z9xW/bq/wL28GH+oZGG+dNYHUsYQFznyd1tWt1gs3i5+ yYs1uTYxJRN97OL7cjfxOUcUUx7bNwznOuUEB5jyfC2VPRAAAADINuxp7gKU D07LzkjyS2+Pu+N8rr3HXe856O7pcd9p7WefxHP6nmmZ1ZB3O3Bvby9eqnhB vmjGIOnjSTkWf06IskxIXBhR1wUvdzG3bDsnaIoLbl+26SztXGcfyWOBrNVj Wa/xDgAAAOaEPc1dhPLAKfmZxAzl3D5r6TO643xuSI+76j5rxvW471w/m2+0 7mcu+7kxvizv/4/7+njzooVCeeS0AdLH4+CY/CU+cuT4+AWWGga81MW8vOgx FlnoK5b75pY/ZMpj285wvlNOIPZYOcGU52w/U45PAAAAMD/sae5icVEjj8nP IWaoLHrcde+zpq3HXX2fNff3uO9cN9P6mOQ/L8bXmA9e476+PrxAaDD/enIf 6ePRUrbz1XXOq4ssLvq9xd/RJSz3zS2/RZXMlPOasYe2eYj58YVUHZmyB2px qmpUfZlyvrk4HsV5alVlDRAAAACypRbDnuYulyD2ajZB/pBfxve4q+6zZpIe 98z2Wdu59nPrY5T/nBhfk4Z35QH+fjwkOIjPHv+O9PHoPFb3x0eOGBC7YJjW /aimsbS/o36u+2siRThT9jcXe3gUkTwWSK8xc7x2u6hfGfZdAQAAyAmwp7kb 0fv9A/LzhlnKPT3u6vusGdHjrvcc9FnWyyUszH3rwImaProHz5sngAfnDeQz x/aSPh6D6kRc1IgPNyy2lHDwEo9gShbaynJf33dzqttMWRO8vOSxwIPEHqgf UW1hyny5eK4uUO2gGsDk7Kcm7rMl1XCqlUz5jMD2ecGMbNyO2ANhJNV3VNep rlAdpBpI5W/geAEAAGTDnuZuRu/v95ggY5ikzNzj7nifNa097qr5PHaW9bK5 NZvPmdCbh+TLw4MC/fmnI7tLH48L6j4dvzsTokb0i/vmI1uv0SCWdn5viLy/ Mi4h+vyvUl2kqi55LJBzNGaO5/O15vPSVKftrifWxUm2+29xnkWYkYMGAACQ BHuaS0Dv6bebIFuYpNzc465zn7X0c+iO83l2ety302UTc2k2/3Liezw0JC/3 9/Pl44d0kT4eNxzH/3Vu30jsW5Xs5eX1LVP2mc5NqjBlHlbMWzaQPBbIWRoz 5TMdscfgRKasPfsX057PxdoNR1IuL47Bl5hyzojYt/ANphyT4mfrDR43AACA O9n2NBefP2NPczeLj7RskZ8nzFTO9bjr32dtorZ87oIed/Hv4rHJ/90bX/On 9uOFC4ZY12ofOeAV6eNxR4l94yiXW/eNWzhj0P+zdxbwTZz/H7/BGDAfY8zd x/5zN3TIxoa7DncrpZS26dWNKnVvpJK6JWkLFBk6YAMGE7bRMfvN3Qff//M8 17RpSdrIJXcp38/r9Xm1jT5Jrnf3ztd+IJcl6fP8npV6XyOSbuGE73H/JR4l 8VpQ7idzvRGbOOv5fA7XGid/ycz100yuH2LXClEoFAqFkla0ZnA/hzPNJZNO xddLzRPyspkc94743OoYun1z1qzNce94zlpHOe6J5DV0zV5wms0ecMO1faA7 YXOflZMkX48r3PHcOP5z8v8eZ1Dx7lo3ROuf3uWEfOLpEq8F1XXUxFnP543N t91h4XraK+dk822UYiwOhUKhUCgXaion9FTBmeYSipyr66RmCnnZ+hx3u2vQ XZjj3uGctarN0FAQKoP3XHwXpayH227qx+LIHgvHSL4eVzjcezZcdNGFcNUV lubGsW37LPn9jEHlf4xs4wp9Dn+b1PsgK0X7cRm/y10u8VpQXUtNnHV83pMT ZgXQ23p1cLv45tt8JcbiUCgUCoVygXCmuYxEztUrpeYKedkyn8smx72jOWs2 5LhvLY6QwfstvotTveCOW69jOaZLZo2UfD2u8CY/YW7cZXRuXKi5uXGm2zXb tgmn8//plf6/k59leg0/rjGH7yX1/siCKBfRemH6mYZKvBZU11MTZx2fP8y1 5q6/0sHt5pvcro8I60OhUCgUypm6jWvtrbKV2NJMIJSLxM7NZcAX8rKNOe4d zlmTS457Wz7fTu5vkPx9Ft9lGd5w/103sXPj2RMHS74eV3hz0EI2N472po/j 53e+Tbf9/umsXh3wH7n+H7I9fG1Q+6fo8/kXAGQz07IbcQEnHDPSOZy1KRf5 EN8j9SJEUhNnHZ+P5Fq5+6EObjfC5HYPirA+FAqFQqGcKZqjeITDmeayETl3 L5KaL+TnTuasySTH3d45a/Q29PVI/z6L68psH3ik/+3svHjK6y9Kvh5XOD1i GVxx2cWsNz3Nb7e0PVvcpk22a/L7GeJ/yG3/0qsUn5DbbqpT8lLzRTIncI6W M9/bC+V6jeeEz6RQ6oWIpCbOOj6fxLVy910d3O5Fk9t1lb6MKBQKhera6in1 AlCtIufiuVIzhvxs75w1MXLc7a1Bj7VyzloCW6f077G4rs71g2ceu5edE49/ 5TnJ1+MK58Ssgr59LoceF3aHkPUzrNiWzbO5ue2aXPafXs3/bVDxv+lUCh3h 9al1ynWXuHj3xHMC4xiIL3Lxc6PM60ZOmLNCa6v7SrwWsdTEIZ+jUCgUCoWS icj5d7LUnCFPi5njbpnPrc1x73DOmg057vS5pH9vxXUNYfMXnryfnQ+PHPQ4 6JTSr8nZpr3pr+93FetN77vKUm96+9i8XW7IWXLdP4TV/yD+njyuqk4dMLKR 553dz3MNJ/ANneN+mZOfC2W9qjnhc3ld6oWIqCYO89tRKBQKhULJROR8O1pq 1pCnO8lxt3vOWphVfO6MHHd6e+nfV3GtUypg6IsPs3PhQc/9H/tb6jU529b1 pheFzdt871SXH/wfue+f5PF/JY/9AXncAIOK7yiOaK9mE58lPsF1nRhtVxD9 XOj/mkrqhYisJs55/eGuFmF9KBQKhUKhziPp1f5BUvOGPG1vjrtlPpc0x708 nq1Z+vdVXL/+8lPsPPjFpx6A2ryuz+Yladb0phefzdtt12fJ9f+Qx/rNoPL/ kTxnpS5PMXmPNqa3CLskGqP8hxOY6SYRHg8ljm4h/on4M+IrJF6L2GribJ+v tr6D2+F8NRQKhUKhUHbLoOI3Ss0c8rVjc9aszXHveM6alTnuHc5ZiyfP1fXy 2seOeIZx6hMP3wXVOb6Sr8fZLs/cCA/cfTN7zTPHDbS4zTqZzdu4viD0TJ0m 6E/yXD8ZVIr/6ZX+OfX5gQPs7P/+AvHvxF8T3y3mfg7lkOhn2cAJOQ0vS7wW Z6iJs47PqbY337bRwvX0vTrJdc08AxQKhUKhUC6QTs2vlpo75Gtpc9w7nrNm fY57YxecpTZ7wmDGqf93361QkbVR8vU421U5vvDYg3ew1zxx1PMWt1dXsnnb 75zCzpLb/G1QB/5CGP174v16Jb+yMZ+3Nj+d5g7T+OyvxE86a3+HsksLOYE3 s6ReiJPUxFnP529wrbnrL5i5fprJ9V3xuwwUCoVCoVBOFjmfXyg1e8jX4ue4 dzhnTZQc93P5vD4/RAbvpXieP/Vldv57zx03QGn6BsnX42zT/nfPPn4fe82v Dn7CQv87Sdm8zfZMLj9D7vOHXh3wA1nbZ7QHZZ2Kf66DmPrtxF8Q/0U82FX7 PpRVupP4N+JPiS+XeC1iqQ8n9DUw+jQn8HRmu8vNzSugM/6ONN/+G+IxxD04 Ifed1uf/yrXOHEChUCgUCoWyWQalYqbU/CFvyyHHvQM+7yTHfSu5j/TvoXhe 8cYouOACDu689TpWiy31epxt2u9uyPMPMTYfNuBR2bN5+5yQLYVh/5Dn+Jms 7xuy1iN6Je9bq/G51WQXdB3xR5xQ1ztGkp0gypLo9ynbOCGvvSt9b/I/rjXG 3ZFTLdyfbr+nTG53hhPeI+Pf73DCdwAoFAqFQnWmi4knE2cTv8sJdX5/c0K/ lxLiUVbcn/bu8SUu44Tv043HI2vywlAylEGlGC81g8jbzspxt2/OWltGtzxn TWD0WLZO6d9Dcbx+yTjWs/zmG/pCQdI6ydfjCo8a+mQn/e/ky+am2zO57Ex9 YcjvenXAtzoV/7lB7Z8TH7BgLHltRznhGLJY2j0hyoyWc8Jnkyz1QkSWo3xO RWf+8cTHOOFc6hfiQ8SenBBLR6FQKBSqM9G+usa8q45MubuXhccY2MH9kM/d VDq1YqTUDCJvW5/jbncNumkM3c45a+Zy3Ldow2Xw/onjjSsmQrduF8B111wJ qvg1kq/HFZ782gtW9L/rgM9lwubtt2eyXf5dk6v4qf89t9Dvh+GFpx9o2KoJ vrWzfRXKpaL9+Sh30l5n5vK8USgUCoVCOaZLOYGjaY3fJuIRxHc0+3Xi/Vwr a6dZeIyBxD8QbyGOJJ7CCfNDkM/dWOTcfqDUHCJvW+Zza3Pc7Z+zZmWOu5k5 a6wnnJqXwfvnuAPXTYMLL+wOV191GWRHr5R8Pa7wnElD2P74wQ7739kfO5eK zem23FAUAc892Z+9vrEjn/+XrPVrsv7T5LUU1Obxoxob+Qul3i+e56I11ns4 IW/7eYnXgkKhUChUVxXNt5pDbOm8hx6P6zmBtf8lvtrCbdqriUM+d2sZNPxT UrOI/G2GgTricxnkuNPnkf59c9yRPnPgoosuhKuuuAQyo5ZLvh5XeMG0YYxd 7769o/53zstrdyab079fHvA4e30jBj3JLqfbMbnfn/X5Qd+S1/aZXsnvMaj4 5Tpt6DVS7x/PU63lhON6nNQLQaFQKBTqPBeNqRtj6Nb2gmnikM/dWnVK/kGp eUT+dq8c922lUV1inlp8wAK4uHdPuOzS3pAUsljy9bjCq+a9xvrf3XLjNVCU 7GnF9uiamnMx2Jx6yphB7Bjz9GP3Q31RRLvtOJpu2/+S5/tJr+Y/06v9T5HX qTaoFK+CVmvu+2GU+OrPCX30P+CEnjMoFAqFQqGk09NcK58PsfI+TRzyuVtL p+ZvkppJ5G9756xJk+NO1yD9e+aYE4MXwSUX94LevS6CWP95kq/HFfZeNkGo se93FagT1lqxLcqjH5y1bL5o5ihhZv39t4M+P+wcNjfNBaHeVhz1J1nr1wKn +zfq1IoFNZqwq6TeZ3Zh0TlhtMcZ7aX/jMRrQaFQKBQKxXEeXOuskH5W3qeJ Qz53a9Up110iNZe4h23Mce80b9g8n+81ZMHumpROc9wtcQ3lJOnfK8ecHrEM rrjsYriox4UQ7j1L8vW4wgEe0+DC7t2gX98rIC9utcVtUG5s3hmfG7fbdUsm sd77d912A1Qrgztlc9NaDXL9Pw1F4d+T1/ipQen/HnkPYmqV/BNS7zu7oLw5 4XgeIfVCUCgUCoVCsXpz48yRQhvu18Qhn7u9yPnu31LzifzdyZw1MXLcCeMc 21sJv/zwlVCTa02OO/2dXkdvQ+7v7j3hcmJWQd8+l0OPC7tDyPoZkq/HFY7Y ONukxn6Fxe3P3djcuM36e8yEbt26wfX9+kBxusImNm87LzDuLNnOfyPr/YK8 Fx+R96VWr+ZnVGatv0zqfWgX0P9xwrxVOi8M54OhUCgUCiWtaM+4Bk7g7G+I b7Dhvk0c8rnbi5y/fyM1o8jf9ua4W+ZzczH0D9/ZBlRN7+3tkM/pbQ3qQDZ3 y/xcbPczzem+vt9V0L17N/BbNVny9bjCxhr7Sy/pBcmhlmrs3ZfNo/wWsN77 fa68DNSJ3mZyPyz3OGzH5oIr4pnJbf9qKAr7Wq8K+Ein9D+iV/sHGXL9+ku9 L3VT0bz2t4n/IX5U4rWgUCgUCnW+qxuxihMYm/aEGWTj/Zs45HO3V50m6EOp OcU97NictbYsZJ7PPzt5mPH52bNn4FBjvtlcYfo4xjXpiMsyNkBR8jooSfWC sswNUEWZXelezJ6fuA5uvO5qlgO9bvFYydfjCidZVWPvvmyeGrkKLu7dCy67 pDdkxnh0yuad8nkzm7c6gVwX/x953u/rNAEfk/fpfeLiWpVifGMO30vq/aob yZ8TjuNBUi8EhUKhUKjzXJTN8zjhuEzz2l614zGaOORztxfh871Ss4p7uJMc d7vnrLVy0A9ffwpG/fXHL7CzcnMbPt+iDW9mtrZro3F0bYonFBJON1qb7Aml 6V5sfnZNrh/olVK/f+atTVkPt998Letbvmz2K5KvxxWmNfZXXn5JJzX27svm eQnryeu7FHr27AGJoSscZ3MLfE69szKB/Z+Q+/5eXxD6mZ7WqCv99xtU/MYt Gv4OqfevMhet46czVQ9yluevolAoFAqFcr7orBo11xo3t4fNqZo45HO3FznH r5aaV9zD4ue4t2chyuSm+vqz99uwT30HvdmNsXRTRje1HGPsZRnecO+dN7K+ 3oumD5d8Pa5wbuwquObqy1k/OP81Uzrc3tyRzQtTfaBf3ytZnULIhrkuYHOB z43eXhb35xZt+JfkfXuPvI/H9Wpeq1cqJu7RxvSWel8rM9Ecg+Oc8P38wxKv xVV6gfh2qReBQqFQKFQ70e/Ii7hWNn/Fgcdq4pDP3V46tX+K1MziPnZejvtO whsAZ6G9Trylb2Egg5nYeXtX554bS7dkKWPslVk+8PADtzE2nzZ2gAw+W+d6 44qJMGb406z/HZ2j5kP+7mg764zP5cjmlbkBcNvN17E6Be+VU13O5tS7qhIF V24+01i66Ye6guCThNHf1an8d+iU/OqtecE3Sr3PlYlCOOH47Sf1Qlyky4k/ Jz7NCTX3KBQKhULJQfSYVMYJx+Q/iUc4+HhNHPK520unVvhIzS7uY+fluB/d XX4Om1OdOfMf7K/PIWwUZfU6O4ulSx1jp4/92P/dydh84qvPy+Bzda7XLhzN XqvRsyYM6nAbczh2LgGb16qD4f67b2Gvb8XcMdKyudHVSczkMX8lr7eJvK9H BfsX6NT8BF3CivO1V/nTnJDXfoA7f/La0znh/2+61AtBoVAoFKpZ9DykihOO T38QDxPhMZs45HO3l17Jz5GaX9zHzstxP/3hQbN8TvXbz98xvrF1vVXZvlBk ZSzdEq8Xp3pCWfoGqMzeCLV5jsfYaZz+uSfuYxz36pAnQCfTungxPei5/2vD 50tmjbRi+3J2Xrt4bF5XEAaPP3Q3e21TxwySFZsb/WZ1Mo2p/03W+6VBE/Au eZ/f0at5g0GtWKDLDr1G0p2wa0Xz/N/jhO/o75d4La4S7X17lrhO6oWgUCgU CtUsyuY6Tjg3pDNUJhP37cCWet/2aXe7082Pmdnu8kuc9DpQTpBOzQ+Tml/c y47luJtnpHD4/Zcf4OzZs8zmdOrEbrvWq1Mq7IqlWxtj19kw342uZcjzDzGO Gz7g0fOCzalN4+e07jwlbInZ7Uo2Nec2sDn9e/ALjzZ/3/I0u1yObM5cI5hc 9u+20uiv6zWBxw0q/7fJ+32QOMWg4Ydqtdru0u6Rna5NnLAtrpd6IS4SPf95 n/g34tukXQoKhUKhUC16kDOJ3VjhxRYe539W3j/VSa8D5QQRPn9Aan5xL5th qI743IoYOp2ldubMmRY+N8/oZ8Bc73ZrXZXj41As3ZY6dp2Z56csPmyAwHEv PdO/y8xtt9a0/nzK6BchxuwsNRmxead83srm1KOHP8c+0wHPPkzuEyl7Nn+z JoV5d7PJY/5CXusn5P0/TD6LQ+SnXpenWLElf+O1Uu+bnaCXiM8Q7+KEGS7n gxSccF6yQeqFoFAoFAplIuRzlEXVaDZcJTW7uJetz3G3ls+/PHWU8XlnjE75 xpG103ryEsLRzmD0zmLstDca2dzgqUfuhmrai07yz1Eudic2b8vncyYPY5/p Ew/fA/WFEW7H5rtrU1tMbv/XtpLozw3qwHfI5/IW8W6Dkg/Q5/EPSb2PFkmX En/CCfVt90q8FleJ5u/TPrhvc+dPnT0KhUKhUKguIL064G/pOcVdbJnP7clx 36PLgH///aeFz9szuimnH95eKMprqMymsXTnMrqpJ7wqxFgfvPcWNu/cUoz9 /LP7svmyN15nn+k9d9wENaoQyzXnbsDmgtOY99SmniHP/119QSitUT9AZ6kT lxo0ATPLc/grpd5XO6AETvj+fLXUC3GRLiDeQfwf8VMSrwWFQqFQKBTKJtXl h3wpPau4k23Mce9gzto3X5yE//77r8WWOJ3q5JFG0V5DTZ4flKStdzqbTxv7 EuO4++68EfLiVrXG2FM8oTSN5sR7QzWNsUv+mbp+G3JXNvddM53NULvlxn5Q nhNgdz842bG5zuh05p2ViT+R9+YDg4rfR61XKXaS7TREr/Z7Uup9to2i/WBp f7Tt3PmT1z6XE76PSJJ6ISgUCoVCoVC2qqEgbI/0vOJO7mTOmpU57u/sKoF/ //23DZ93xOjffvmR6K+lnPBxkZPYfN6UoYTjOLjjlmshO3qFKHXsXcPuy+bh PvPgwu7doV/fK6Eozc8JvdrlweZG79Vn0Mv/Iev8ok4TdEiv5vcwq/wz9Er+ FTeY0XYZ8SniX4hvl3gtrlI/4u85Yd755RKvBYVCoVAoFMpm1eeHZEjPLO5k e+estbIUZYY/fv+V8bnRnTH6f//+w+4r9uuh8WvKxmKy+aIZwxmb33T91ZAe uVS0OnbpP3sxtx33YvOE4GXQs2cPuPyyiyE7dp3L56hJweZtbMg8u7Mq8buG ojA6Q303+RzfNKj4er1K4VmvCbpb6v24BaVxQhx5qdQLcaHUnPCax0u9EBQK hUKhUCh7pFMrVkjPLe5m+3PcKWv8+vP38M8//zBbYnRznH5wm8Ypr4eyL803 F4PNV80bBd26XQD9+l4ByaGLReV+94+xd8DnMmbznLh1jMt79+oJyeErZTfj 3AVs3sa7a1J/Ja/5I/IZEk7330U+053EGXVKxWs5ObylGaWu1khOyGs3cEI9 9vkgmstP2bxC6oWgUCgUCoVC2SuDSvGq9Nzibu4kx90CV+2sTIQfv/sK/v77 7xY+t4XRT53Y47TXZCAuz/R2iJ+9lo6D7t27Qd8+l0Ni8EKn5M234fXmOvbK THfgdftj51KyeX7yRvJ5XgE9elwIm/wXyY7NO+Vzkdl8nyFLcF0W+TvjH7Lu z+ryg/eT/58dzS43qPj5tTn8dRLu1q8i/oL4R+IbJVyHK3UJ15rLf7PEa0Gh UCgUCoWyW3qV772dsUV6xDJ44akH4Pkn7oeUsCUyYB2pbXuO+776HPjlp+8Z mxttK6P/+fvP7Hmc+dpo7zh7Yul+qyfBRYThrrz8Eojj5zmdzd0rxu68vHZn snlppgJuvK4v6wfnu2aG+7F5p3xuP5sLzmbeT0ye63vy/h0hn/N28pk3CuZT dWp+WCPPu3q+Vw4nxJHnufh5pVQ4d371qEehUCgUCtVFpdXyF5HzyLMd8cWN 113dMuP+un5XgU4pNe/IwdbNWaMMdeKtOvjjj9/hr7/+YjZldGs53cjoB7Yo XfL6aF16WfoGq/rH8R5ToedFPeCyS3pDpO8cydhcnjF219eci8HmVXmBcOdt N7D/+dULxnVBNu+Ez21gc+b6HGZy39/Jaz9JPtsdeiW/jWwDWw0qvoTF1LUu iamPbd5X17rgueSiR4n/Jd7LnT896lEoFAqFQnVh1RUEf2+OLQqTPWHOxMEt bE5NY2nlhHWk52Op3XmO+x5ynv/tV03w559/Mhv53F5Gp/7843dc+jrpdzFV 2T4sJm1ubnrohplwce+e0LvXRRC8frrkPG6Ni1PXQ1nGBjYLvjbPr0uxeWd8 bg2bGwrC4JEH72L/77MnDTv/2LxTPjfP5q3Opdf/+2Z10hfkc9lHtoEt1DqV ol6n9o+o1fAvabUTuzthV3418Zec0L/8Bic8vhxF38cDxP8QPyTxWlAoFAqF QqFEUUNh+CFTrkgIXAgjBj4GvXr2YOfoPXp0b+Hzwc8/JAM2loMt57jTOvPT J99mMfM//viD2cjoHXG6NYz+919/MhaT5DVTVs/xhfIMb8a4m/zegMsvvZjF zgPXTZOcu+11UbInlNB57JkboTrXV6T8EPmxeWd8Ttm8oSgCnnuyP/tfnzDq JWRzG2LnRjanPtBgdN5ZsoavyXt8UK/2b9Cp+Hod6/vO5+uVinm6bO9rRNyV 5zfvp2eK+Jhy13JOeM3RUi8EhUKhUCgUSizVF4UmalPWw9zJQ9lMLI7FyTl4 tP8dwK+dCjW5CgjxmgnB62cQdukKc67EY3RT9tqty4Avmk7A77//zmxkc1sY 3RpOP7q7XPLXnhO9Eq6+6jJWc86vnQLFaeudNktdCrO8+PQNLC++msbZbdru 3Y/NBUfCsAGPs///4QOfaGb29nyObN5Z7Lwdnwvekkfv9/uOyoQPyWdO897r 9GreQLaTKp3Kb12N0vd+B3fjEziBU0scPiC4j27ihH5wnxBfLPFaUCgUCoVC ocTS8zddd/U+ylnkdzZHaeKo5yEzaoXkDCh/C/y1n5x/f3X6Q/jtt9+YjXzu LEb/+fuvmhlQmtedF7sa+l19BevVrlgzpfU6Ja1b92O92Uos5MO7s4tShN5z tM89zSOoNTuT3T3ZnMbOp44dxPYBTz16H9QXRbRh86q8YNBpQs3zObJ5p2wu WCm4Ie8/st7PtmjDdwuM7q83qHidXsln1qn5CTo1f7mN+/Brib8l/ppYzHi8 3FXGCd9JjJR6ISgUCoVCoVAO6lLihcQHuea8dRor37hiIuMO6blX/qasdWi7 Fr767GP49ddfW2xk9I44XQxG30u4QYrXrdnsATde14fNOPch20tnt6cMW5Xj A2WZG6AktWvF2BmzE5cY69mzfFgPOmH7cC82XzxrFNsP/N99t4NeE2Y2r704 wx+iFIsgJ369HbFzZHPqt4zeqmImz/UDeS/fJnwuMLrKv5YwewXxhloN/4iV +/OK5v34JOccLmSpMZzwmrVSLwSFQqFQKBTKAT1MnEb8Myec29A+QuFXXXXp g4Qf/pOaed3BlKMO7yyBL0+fhF9++YXZlM+tZXRHa9I//+SIy197Ucp6uO3m fqz2Ye3C0XY/Dq2RoBxL4+yUa0tSvboMtxc1m+bHl6RtMIm1k9cuUzZft2Qi 6/tI+7VXK4M7rTlXbd4AG1dOg4xNHgKnOxg7P1/Z3OiDW9VwoD73N/K+HK/L D6S16TXUOqV/tU7FJ9flB7zWmMP3srBPn9q8Ly9yzSFEFrqCE/rg/UAs5Zx5 FAqFQqFQKHtE6/LaxMqJDxHPIm4556svCP1UavaVq2nsc48+E95/ezt8/93X 8PPPP7fYyOjtOV1MRjfH6f/88zfjJle9B7R/2h23Xse2nyUzRzrlOWgvdcqy lNtLM7ygOGW95LxtL5+btycUp3pBWeZGqMz2hRrK7KoAqNcEScbm/LpZ0K1b N7i+Xx8oTldY3Q+uRhUKEX4LIdx3IeTGbwBDQaRT8trPBzZn3tbsreoze/QZ X5LPYS/lc1qfTm1Q8oV6Nb+0Thl0u8m+ndZf/0j8FSf0bj9flMAJx7HFUi8E 1Ub0XIPWGvhyQu3Bp1zrOUeiC+6PQqFQKJTc1Z8TYuX0/I0e335r/vtxczcm 5/vVDnOsJpDwRKhZ0+uk5mxb3FgWx+LkHx3fD99+/SX89NNPbWwrozsj3/3D d7a55L0oy/CGB+6+mZ0nzRw/yKWfgzHWTmeh0f7qtGdbSdp60Mqwtr1jNm9l 9PbWEmYvTfduZXY1+T/Kdz6bxwUuYf39+lx5GagTvW3u1W4ojICksFUQG7gM UiLXgHKzN1TkBjs9r73Lsvk2TRuT+/xG3oMTdflBevK/UEnz3g0avtyg9g+o U/HPXXDBBTXN+/bXXXRMkYOeJT5D/CaHs87lpoGcySzWdraGrx29PwqFQqFQ clQP4onEDcRnOeG4doQT4ucd9hwyqAPXn8Pbap7NW9peQc6VdTmwb2sRvLWj Ag7t1sORA9vg3bd3w4mjb8GH7x+Dj05+AJ988gnzqVOnWtzU1NTiTz/9lPw8 BR+ffA8+PHEYTryzG47sb4BDuyph35Z82FWbwbiYxqtdwX70OwP6fHv0WXBo ezEcP7QVTn14BL4hPP7DDz8w//jjjy22h9Gdme/+5x+/MUZz5ntEuZj2JqDb 0qTXXnApm3dqpbG+3bc1V56wO539Jk82N8/nlsxi7RmEeVu4PYh91yUGm6dF roaLe/eCSy/pDZnRHg7NUcuJ8yKMvhQK0hRQkRcCuQneoErcCNtK41xec95V 2PxQY36rt2nO7K3L+mJbafRug8q/nHrulJdZPtQdt1y3v64g+GYnH1fkInp8 O0r8Nyd8/4ySlwZyQs3BFuJI4imckNthC587cn8UCoVCoeSk24jDudZj2R9c B7Fyc9Ln8Q/trtd8e/BNHRw5uAuOHzsMH37wPnz44Ydw8uTJFn/00Uct/vjj j1tsZHNrGN3Up0+fbvFnn33GfPr0p/DJyRPw3tG98M5ePezfVgi7atIYS9PY oTXsRjmG3n5XTSrsrcuFg4S/j+2vg/eP7oZTJ4/Bl583wbfffgvfffddi7// /vs2NjJ6R5wuBaObcvr7hxqcxr/VuX7w7GP3MjYfN/JZ6XncBtMZ5nT9VTTu TtidzmynvddpLzdaGy5mvbsz2Jw55VzTOYg0h6Aiy4e8PvI6VbSWPYTxuLVs npewHq68/FIWO48JWCLKjPNqdRjEBS2HzBhPSN/kwbi8NDsI8ppj6rLqB+dO bE69vYD5MPFbW/J+KEhRHOvVs8c/V1x28R+FSeuqdCq+xKDmg/V5fs9qtdru zjjAyETrOeH4FiL1QlBmZW7ba+Ks52tH749CoVAolNS6kGuNldN8P3oM+4h4 FfGV9jzg+++/n/HBBx+A0ZTNjbbE6B1xuiOMTv3555+38RdffMH8+efk+tOn 4HTTR3Dq4/eh6ZMPmD/79BP44vNP4auvvoT//e9/8PXXX7f4m2++aWPK5kY7 yuj25LuLxei///oTy4MWm29pXPqFpx5gbD5i0GOMd6VmblHdHHunufO0vzyL v2duEBg+zXqGdyWbt/X6NtamEm7PoHXtflCTFwB6dTA0FIWdw+bFGX6s1pzO xgv2ekMUNjfNZ0+L8oCceG8WQy/NDmRx8/LcEFAl+UB+ioJxuyz7wbkBm1Mf aiyApx//P9bPLyZo9bfk89lJ+Zxs08XUhNPTdSrFdJ02tKvNWbuTE753fp+4 p8RrQVmvJs4xvnb0/igUCoVCuUI0l5HGyj/nhOPWP5wwY2Yo52A9HuHzucRg DaNbG0s3ZfSOON1WRqf+8ssvW/zVV1+1MeVzoy1xuiVGb8/pYjK6M2awHd9f K3rs+eUXH2FsPuCZBy3M+T5/TGvgW1nel+X8l9OYfKY3y6kvzfBmuegC03uK xubZ0StAGb+6UzZvYXSz9oKSdJoj7wf5yV5w603XMrbzXjFVdDY31ptXKcMg PmQFFGcGQHbcBthaGsdi5tvJdeokX8iMWQ9l2cHyYXOr+VxaNj+8vRB8PRaw /8sxrw6CwzuKmA9uVf1A3stDdfmBZXo1ryXbbBHZZgvrlAE+OjX/jFY7sSvE 1A2cULM1UOJ1oGxTE4d8jkKhUKiuqQs4gb+rif/jhONVE7EX8fViPcnx48f7 Uz4Xm9HFjqWLyejWxtItMboc8t1//ek7UfvvvT7sKcYATz96D8sRl5qP5WWe WZhvbmbGOe2dQH+qAtjtdMS11EoeqvP82Zw16hqaf0+Yn15GXZVD6+j9yPut aOPk0KWQFrmi+fpWV1Jn+53rHDq3ztfEfsyFKRvgnjtuZJ/rrAlDGK9X55L1 sZr2MNhWHCUKm5vWm1MOL0zzB21GAPtpGjOvUoVBZqwXpER6QENJrBuweXs+ dz2bV+XHQ+9ePeG6a/vCLl0uY/O3jd6pJX8X/k1e5wdbiyPraL931vNd5V9A HK1TK0bWKaMuEetY4WJN44RjnlLqhaBsVhOHfI5CoVCorqW+nMDgH3LCMYqy uSixcnMCgAsIm39vZHRrOV0KRreW08VkdHtq0l2V7/7ufp0o/Dl19EuM4Z54 6C6ozvGVAQ/LyZ2wuSaQWewZ51WEo5NClzX3hrO9H1x9YTg8/vA97HOdPHog i5tbjJ2LxObGOvOK3BDG4PXFMYzXK5VhbeLmO8htKKenRq2DovQAN2HzTvjc CWxO89qffLQ/y31Ii/U7h81N/c7OYvo4v5D35diWojA6ny2fWqfyz9Mr+ZU1 Sv5BTvjO1x1Ej4HfEn/DnV8z5LqKmjjkcxQKhUJ1DVH+phz+Fyccmz7jBE6/ 0dlP/N577+lN+dyZ+e6uYnRH891dVZPuSL77b7/+zBjNEf6cM2kIY7gH77uV 1WNLz8NysjRsbuzVTn9Pj1oFZZkKm9ic/j7kxUfZ5/rKkKea69Dty2u3d775 9vIEyCBsri+IYrXo2fEbYHvF5nNy2g1F0YzVkwnPl+aEuCebd8rntrM5tdeq N9hnOHH0sE7ZnHmX0SVnyRq+2lmVuMegDiwi27BasH9UnZof1ajlL3X2McVB ZXLCMXCOxOtA2acmDvkchUKhUO6rPpzA4O9xwvGI1trR3m+0B9xFrloE4XN/ YqB2FqNby+lSMLqj+e5SzmD7+Phum7mT1jtHK+bCG5OHsvP/u2+/gfUHl56H 5WRp2dw0Zp4T6wH5yd5W92ofPfw5oY/Asw+R+0Q6rebcmhlqtB5dk6pgTJ6f Sra9jACLOe0VeWEs7p4Quga2lMR3ETbvhM8tsHmFJg569eoJN994HeyuU9rC 5u1c/A95LSe3l8XUke1apVfzSp2KzzaoFcsMuX5ynFc2mGs9DrpLvB/VVk0c 8jkKhUKh3E+PcUJd3Z+ccByiuXy0/9s9UiyGcPkwI59by+hyyHeXgtHlNoPt r7/+hJ2Eg6zlzmi/uXBx757QvN3Bzdf3ZbwuPQ/Lyc5lczofzVo2N8bNKZ8r 4z07ZfO5U4azz5XmttcXRjiNza2ecU64vE4bDenRnrCtLB7qimIgK3YD6As3 Wcxp30V+ZidsJPfxAmWSglyf2jXZ3AKfH9yWDw/1vwe6dbsAshMD7WbzI2+W tvHhHUU/kffkCNnGSgw0713F5+qVfGidSvGyTpcgh/7ovYg/4ITj4t0SrwVl v5o45HMUCoVCuYdon56FxAe5ZjbiWmPlkp4bEY6+4sSJE/9ZYnR7atLllu8u BaO7agbbF6fetZo9X3q6fwubUy+cPlwGPCw3d8DnIsTNi1K9ITtmjdVsboyb axK9oCBlo0U2Xz53tJAPcceNUKMKlp7N2/VqVyb5shg55fLirCDISfAhlyd3 mNO+vSKJcXpKlCcoExXNcfSuy+bUa5bOYJ/jtAmvWMxrt5XNj+wuYz7KXHqG rLOJfF5bDZoApV7tn6NT8cl6tWJ2XbbPzRIeivjm/ZKvhGtAOa4mDvkchUKh UPLWQ8RpxD9zwjHnB06Ild8v5aLai/D5HmJwlNFxBps0M9j2E46whj3HDH+6 DZ+HeM2UAQ/LyfbHzm3JaS/N8AXF2umQGr4SMjethuq8gA7Z3Bg3T49aY5bN /dbMYH3Ebr7hGijL5mXH5saa87KcEMbplNG3VyRC7mYfqFJFmOHzc3Pa64vj ISNmA3NxVkiXZPPi3E1wUY8ecOvN18MeO/PaO2Zz6nLBe8rp5f8dbMw/rU5R 7MmIWlFUp+IzDaoAr1qV4mWDlu/jwkPQA8R/E7/LubC2C+UUNXHI5ygUCoWS n3pz58bKDzdfdpmE67IowuaBlM+NtjXfHWewSTuD7ZefvmPx1874k87HHvz8 Q3DbTf1g9oTBMuBhOdl5ee3m6s2rcgMgMWQp+9wKaP56gmeLVZu9mNXEefGe hL+nw+oF40CTtOEcNg/3mQ8Xdu8O/fpeCYWpvg6zuSrR2ylsbqw5byxPgKw4 b9hSGs+4XJcfBUkRHuDrMQcMRTGd1pxTHtcXxUJGrDdzaW54l2DzA1s1cN89 t0O3bt0gLyVYtLz2tnzeyuaCK5iPEe+t0/xdmBH2aXr0+t21eYps8j+RYVD6 B9QpA16r1fjc6sTDD60z30l8hvhpJz4PyjVq4pDPUSgUCiUf3UkcT/wjJxxf fuOE2PnjUi7KGhEOH3D8+HGwhtFxBps8Z7B9cmKvDBjXXS1NP7haVSBsDllm 1Qw1xdoZMG3cYMLgPi1sTu/bs2cPuOzSiyE7dp0ocfPYwGWwZM5op7C5ac25 OlkhxM6bY+b0b68VMyDMbwkkhnuw21hTc76tIgk0qQGQs9kPsuN9yWNluB2b H95RCMsXTGHf5c6e+rqT2LxjPj+2t7LFNdqUv7PjFacqc4P15P8jjVqn5IMN Kn5SpYq/ixO3d9t8Tjhepon4mCjp1MQhn6NQKBRKWvXghBpyWktOv/+nx5Wj nBArv0LCddkkwuYXEf8mNqPjDDZXzmD7E/YR5pCedd3NtrN5VvQq0Xq1l2cp yOOtNc/n7XrB1RWGg+fSSTBzwlCID1oKl192MfTu1ROSwlaKmtOem+AN08cP hW2lcU5hc2PNeYUynLA138LoNIc9UrEU0mLWQ1r0eogPWQPleeFW15zvqk4D ZZI/5CYqID3GGxorU9yCzYuyI6FHjwvhrttvhv1b1K5n83Z8Tv3u3iqoK8uE UmXc73rt5vd2lMdX6NT+KdQGwup6TcBEXa4v/U7aEVa/gfgn4i84NzpeotqI 1kH0NfFpTjgPymx3+SVOuj8KhUKhUEbRfD9aR/4lJxxL/uDcJFZuSYTH6yif d8Tocsh3xxlslmPpP373FWNC6ZnXXWxf3Lw6zx/SI1eINkctM3oNy3e3dsZ5 xqY1cHHvXtC9ezeW3+6MenNVog9MGzeU/e4MNjcyOZ2lRvu/7ahMbslpzyXP HeS9EHZWpUCVKhKyE3wgM24jedxUq2vO36zNgDzC6jSmnp3gBw2liefwudRs vr0mC2q1iXDvXbfBhRd2h4LMCNmwOfM+wY01eVCuSYQtVZnf76vP3retOFJt oD3lVP5JejUfpFPzEyirA4CtrF7ACcfPyU44pKFco/9xJj1NOnCqk+6PQqFQ qPNb3blzY+Ufc8IM834SrksUHTt2bJ2RzzvjdJzBJt8ZbB+8vU0G3OsOdiyn vU4TBInBSyBz00ooTPFyaMY5NWVua9i8NFMBN13fl/WDWzZ3NMyeNAw8lkyE hqJI0XvBZcR4wqJZrzuNzY3eVZMKWYS/64tjW3LaKZuH+SwBdbI/43HK7iyP PcEXKpSRNtec6wrjGK9T52z2hzd1mR3yubPZPNh3OYuZc838sWDWOFmy+bv7 qgXvr4YdehWo0iOhoTKbPuYP5L07sK00WkMYPVGn8t9cq+J5Q17A6K2aYPr9 dWesPqr5tVc5+9iGcqqQz1EoFAolhSh788Sfc8Jx4l9iLfFQ4m7SLUtcEQZ/ 7N133wV7GB1nsMlnBhv9ua8+Vwb8K2eLU29Of0+NWA7lWX6QE7uWzU1LDl0G qgRPm2ecp0Wt7pTN6dy0e++8iZ2vrlowjsXNqdVJNB99CKxdNIHNPe+Yz23r 0x7kNY9w8kKnsblpL7iCtACoVEW2qTfP3ewHvmvnwG5jfjvh8ZqCaFZvnrLJ C3YQjre1H9yO6nQhtk4eg7J6fUmibbFzEXLar7u2bxv+qCqIlzWbUx/fX8PM 8t5VCXBkTyUcP1BLn/sr8p7v3FoUka1X8gl6tX88YfZQnSpguiE/sL9Wq+3e 7nBzKSfUGf9KfItLD3QoFAqFQqHcVfS7f8rflMPp3Bd6DtXECbHy66VblnNF +PwUZfT2nC51Tbrc8t3lPoPtl5++ZzwnPQfL0eL2gqvK9Wdsbho3r87jITfO gzlj02pIi1wFyWHLm72ijZOII33nw7rF4ztkc0NBGDzy4J2M5WZNfLmFzU1z 2vMSvGDK6EGwav440OWH2RE7N98LbtbE4VCpDHUqmxvj5tXqKChMD2xTb05j 6RGKpZCfHtQmbr5Hn0n4XQGbwz2gKDPY7n5w5apNkJvEgzI5EFSpQYzfHY6d d8Dm1LTWnGtm8+7du7Ncd3dg8xYTLq8qSgEDYXX6+4kDOuZjeyu+f2urch/Z NnN1Kj7OoPSPNaj8Q8j/2jRDrl//Rp6/kLzmyObXvk7K4x0KhUKhUCi3EO1D Qhn8A044f/iP64KxcksiXL7ZyOf2xtJxBps8ZrB9/smxZhaVmoflZPNsnh6x HGpyFXb3adckrofitI0257Sb1pvHBy2BCaNehOIMv3PYvKEoAp5/sj9jufGv vmiWzU3z2lVJ3jB78nCYOXEY5MZ7OTzjXF8QRR5ruNPZ3Oj64jhQJinO6QWX Gr0BNgWuhJ3VqefktFdpoiEjzofVm79Zm+5QP7iyvCgoyAyFoqxw0GaHw5u6 LHHy2ncYXQS5yUFw2y03wjV9rwJ+wxK3Y3Oj9zcWgzY3Do7tq4ETb+marWcm j/n9wS2qvTXq4FzeY6o6wmd29sBn+zdecMEF/110UY93J/bvj7POUSgUCoVC WZIxVv4XJ3D515zQ/+1OKRflahEGH3Hs2DFwlNFxBps8ZrAdP6CXARPLyaZ8 3jZuvkkxD/Tkp70z1NIiV9rN5sa4uT4/FOZNHQHrlkwg1xn5PBKGD3yCsfng 5x9pnq1mXT84Q0EEbFgxFaaNGwKrFoyH8txgm9nc6IUzX4N6bbRZPheTzY1x cxozpzXp9HamMfMqTRSE+CyBCmWUxZz2kpxwlr+uTOaFyx3s1V6liSXMvgnK VdFQptwEO2oy7c5rN/L5YSlmqInM5sa4+fH9tZCfHQ1HyeMY2fw9ow8aiPVn qgqTPu/Z8yL6fTfblkcOerxRr1aE1qoUb+jz+Iea4+ooFAqFQqHOb13FCbHy E5xwznCWE3q/0R5w5+X3+gcPHuxB+PxHVzI6zmBz3gy233//jfBOhgy4WA7u OK+dsrnPyslQkORp13zzjE2rHGJzU28OWQ4jBz8FqkQvmE7YmvxrwlOP3gf1 RRF292ovyQyAlfPHwexJw2Hx7NchfZMHNLZweuczzkM3LiT38bQ6du4ImxtN b5dBGH17VXKbXnCN5ckQE7wakiI9yXWpFnPat1UkQ24i7QnHs/7tYvVqry9L IaweQ1g9GirUsVBTmNDK6bawead8Ln82Z26Om+dnx5hhc8G+65e2qbd/6tH+ X5P/hUTyPxmpU/tHEAfQ+eoNyqD7kdVRKBQKhTrv9CgnzEL7hRPOFb7jhFj5 PVIuSi46cuRIIeVzoy1xOs5gc48ZbN9/+yVhyFAZ8LF82dyY116e6QMJgQsh KWQJpEUsZ3POc2LXQE7MGijL8OlwhhqtLReDzWl8vCI3EHxWTYN77xJqlPvf exvoNWGizVGrK4wivL0A5kwZAbMnj4Clb4yBcN+FUJjmD7WaiBaXZAVCfPBK WLt4Eox/dQB5nARR8tqtYXPTGWpZ8T6EtZPa5LTTyxPDPcHfcz5E8SvJ42Z0 mNNeqY4GdWoQ5KeHwD5ynZhz1PY3qBinV2gEVxK/qc9xkM074XOZsTnlcl1p JnnO6nPYnDonJaINny+dPx0qClLPHttX9fn+hhwD+d+JJXwerlf6h+mVfr46 FT9GVxh0J8/zXb6uDIVCoVCo81SXEC8kPsi1niMYY+W9JFyX7ET4fOrRo0fB GkbHGWzuMYPti1MnhBix5JwsnouSPWFz0ELQKcVhc2NeuzLeA0oJp7ePnRem bICMqJXEqyA1YgWkhC+HpNClhONXEI5fDVNeH0Bu4+0wm1flBcH1/fq0cMwV l10CL7/0GCSGrhB9xnljeTxMHTsUNvkvgew4L/BfNwcWzx7NZqqNHzUA1iya CPEhK6FGHe70mvNz+LzdfPPsBF9orEg+J6e9MCMYSnPCIT7MAzLjfKA0N6LT evMyZRQUZoYRZo9x2hy1hrJUwuxxUJkvWKdNEo/NO+Vz17M5dY02jdy/9hw2 f+9gHXMY7wGDXnoGVi+dA8f26eAdwvLK9Cj44HADfHCo/j+y1pP767Kr6wtD Ngn93/1DdCqFny6Pn1CXw9+HcXUUCoVCobqE/o8TYuU/ccL5Lp3nEk/8gJSL krMIc/chfP6v2IyOM9ikncH20bE3JWdqsV2bp4A4fj6UZ24Uhc2NTJ4avszq vHaja5QBMHvSy+C1bBL7+xw+t4LNqQM9Z7eJMz50/+3scjo7bdLrA6E8J0DU Gec0n33d0skQ5ruoTU57XdEm8FkzEwpSFa5nczN8TuPmNI6+qybtnHrz2oJY 5vy0IMbrBRkhzJ3ltG+vSgNtVhhocyJgO+3ZLvKMc9O4+b4taqjKjxdckMBs KE1xec25s9j80I4ywufpFtn8/UNG1ws+LPjovlqoJvdjjE799hZ6/Z/kdR7Z rUsrqFMHhBqUfLBe7R+kUyt8alWK8XpV0L1mZrahUCgUCoWSr3pz58bK326+ 7DIJ1+U2OnLkSDXlc6MdyXfHGWzymcF2ZHeFpDxdme0DmVErRH/cpOBFUJSy XhQ2p85PEvqxW8vmpnnt6VGrYNwrz0Nm9Bob+Dyque9bFGTHroNu3bq18Pn4 US+2xMsrcgJb5qc1aKNEYXNjvfmKeeMgN8H7nBnn6dGesHHNLGisSJCUzY15 7XTu+R5D1jk154biBNBmk8+gNAmyE/xgtz4TKtWbQJkcwGac7yW36yinXadN gJLcSCjNjYJdtVmisrmluPn+LRqoLthMnMh4vUITD2WqONAVJ5P7FLu85tz+ uHk6i53byuZGJt+3rQTqK3IZm5v6w7e30uv/Iq/r6F5DRiH5fw3RqfhAg9I/ QK9UeOvVAWP1Kl/C6hOR1VEoFAqFkqfu4IQ68v9xwrnt75wQO39cykW5o955 550Zpnzuqnx3V9Wkyy3f3VUz2Gi/uH11OZIyenGqF8QHLLAiL902JwQugBjF PPK4CofY3Bg3p7nstrK5Ma+9Lj8UVs4bDXMmvQx6dbDVsXPK59S+a2awfnBj X3kBdJrQc3Las2M9YcqYQeDvMYv97SibU28vj4fJowebnXG+lVwXtGE+pESt k5TNqSmbq1MDzPaDo4yenx7M8topq9OZazRuTuvN6d90vnmlpvOcdkNxIpuD rs2OaNOrXUw27yhuvtugAm3OJijIioT8TBNnRYE2Lwa2VmWR25W6tOa8PZsf 2lkOxcoEKMiOgcPkd3vZ3Oja0iw4/pahDZszv2P0NnL/hl+O7CrZt7s6KYv8 f/OCFf46lcKL1qvX5vH3IKujUCgUCiW5aD0arSGnteRnOIHLj3FCrPwKCdfl 1jp48ODFR44c+dWZjI4z2MStSbc23/3nH79jMVcpGZ0ydMd56fY5JXQJYfS5 7LFTw5awy+xhc+r0yBV2sblpzDwjajW8MuQpNtvcWjY3zjbvbMY5/QzTo9bC nMnDwWv5VKjXRtnN5kbPm/4qbC2JtTjjvDw3FHjPuVCQ6i8Jmxvz2reUJkKl KspsP7j6kkSW507z2g3aBBY730dz3Jtj59UFcZC9WcG8szaz05x2XdFm1qe9 TBUNWyvSnM7mneW007g65fNydTyUaxKYa7TJoCtJIz9ToLowCWoKk6G6KBmq yO/U22vzyGOUO5TXThncUJoJhrJM0BPXV+a09mp3kM1ZTjv5WVmUZpHNqU8a faSR3u6XHbW5b2XEeBWH+86JK83YEGhQKfz0Kr+1ujzFSH0OfxsAXCD1sbSL aTDxduLbpF0GCoVCoWSqWzkhVv4lJzD5P8RKDmPloonwuIowOlBLzeg4g03c GWzfff0ZY0spGZ2a9nejTC3eY/KQFLKYxcyrsoVe7AlBiwirL4Wc6FVshpo1 bK5J9GR94hxhc9Oc9mCvOTBmxHNsXppYbG6a165O3ggzJ7wMc6eOBFWSj11s Tnl85oRhsMOY395BvXlm3AYI810MJdkhLmdzY9xcnRposVf71vIkVn9OY+f7 yd8FmSEsf900r53+XpAZSjjdH/KSA2BvXa7FmnMjkzdWZTBOL1fHQlVBvMvZ 3J6cdnr5Lr2KrDcJytSU5zdDqSoBipXxoFXGgTYvljgO9KUZUEe420B+VhK+ p7Fx6vL8JJa73lirOiev3dwctXP5vHM2N7pam2EVm7fx0e30cb+pLEjYnRS2 Kifce3YstWrz2kCdWuFB9gmv12t87wbAPvAOis6j/YL4B+IbJV4LCoVCoeQj mrfWPlb+CSfMML9WwnV1SREWH2nk8/aM7mhNutzy3c/HGWxfnDrOmFRqRg/2 nA5xAfMhLXwpFCZ7OsTm1AVJ69jjtI+b1+T5Q07MasiNXQO59Gfc2jbOa3Y2 ua44zVs0NjfGzXXqEFgyexRMGzcYqpWBorG5aV67Lj8C1i+bAlPHDoENK6ex OWrm+XzzOd64aibr3W5LL7iceG8I9JoP+Wm8S9ncONu8UrXJYq/2reUpUKHe 1BI3p3nt2uxws3ntBxqUhPeDISeRB01aMBzYap7PTWPnB7aoIT89FDTEBZnk 865Ilx2bO7MfnHVs3gmft6s331KtImsy2MTm1B+1eAd9ri8O7SioyYn3jAte Pz02wGNaXJDnjJjqbL/ldfn8YIMq5Hqpj61uqhxOOOeaJ/VCUCgUCiUL9eME Bv+IE44P/xJriYcS43fiTlJjY+OF77zzzv8cZXScwSbfGWxyYfRNfm+wn3Rm WnLoYlZLTmvUc2NX2cTnNG6ujFsN2lQvu3LaaT57DL8Apo8bBMXpPqKxuWnM XJmwHsaMeB781sxgf4vF5u3z2vM2e8OzT/SHKWMHs3lp65ZOafHKBRNg/vRR 7PI3poyEGROGQZT/UjbrPC/RB8rzQm3qBZeT4AOR/stAlaxwCZtT76rNaJ6l ZnmOml6bQLy5JW6+W5cFypTADvPa99TlktsEMRdkhsFb7fncQl57Q3kqaHOj oFQZA+WqWNhbp0Q2tyF23iZ+biebMx8T/PGxnWfeP2j4iHy22vJsvyDv5RMS PBaNSfJbPTm2VqlYplcHDNGp+ZukPs66icZywrlXrdQLQaFQKJSkonVjlL8p h//NCceGTzmB02+QcF3nld5+++1kwuhAbYnT5VSTLod8d3ebwfbpyXdsno2e HrEMEoMXQV7salH4nNahZ0evPOdyGgennE7z1FPDlzLT2+W0c0LzbSjXazZ7 mK05t4bNjfXm1Xk8LJg2AhbPepXcN1g0NjfNaY/yWwCjhz9Hfi4Unc2NriuK gtEjXoDy3BAoTPNvcZUyDLZXJJzTq526OCuIMXpRRgD5PbAdn3dcb16UEQRR /HKID13DbucsNqem+e179FkW2dwYN89PD2Fcbho3p/PUaB16Z3PUKJtX5ccx 0xr0fQ0qq2vODSXJrB875fXivGjYXpONbN4Bmx/cWQk1xZnWxc47Z/M2Jtf9 fmxf1d7durTk6lyFN792avSGpePjI31mhdUq/RbrlPzgrXnBmLNtXn04oY7w ew7PvVAoFOp81dWcwOAfcAKTnyWu5gRWx76sLtahQ4ceMvJ5R4yOM9jcpybd HKeX5GfC8jmv2szVZRnekBm1nM1My9q0gs0jt5fRadzc3rx2cr4N86a8DDW5 fvb1g7PQpz0vzgMmvz4A4gIWicrmxpx2Nu98/RwWT49SLBKVzY057dWqMJg2 bqjFmvP2vdqp64tjICtuA9RqIkGbEQjKJF/YSa7vmM9b4+bbK5IIp6+ACL+l kB6zgV0uJpvXFsZCSU5Ep2xujJurUgLPyWmvL00mlwdZPUftrW35UKaKYfXn lNVpfNyWmvO60lQozIqEgqwI0KSHsRlqFvn8PGLz9w41QI2W9ptTOpTXbuTz 9mz+8bu72pjc7mfy3ry5V5+elB2zQuG/dkpUuPesMINa4UG8wKBRDKrO80FW b5WaE87FZkm9EBQKhUK5XMZY+Z+ccCz4hhP6v90l5aJQLIa+R0xGxxls8pzB Vl6UBWOGP83qt+3hZNqTnca2aR057dFG49n0J421U3anc9Xamz6XkM++EKpz fO1ic2NeO82FHzviWYgPWGhXXnt7PjeNmQd7zYbp4waznHex2Nw0Zk4vD/Z6 Aya+NgC8lk+B+sIIUdjcWG+u8JgNWbFeVrG5aV57cWYQ4/QdlYmgSfUHdYo/ WUuCTf3gSnPCINh7EYT5LoHM2I1Qp42zm81pvFyTGgiV6mir2fyt5trzHdUZ 5+S076nLgdykAJbTbuuM8+r8BJbPXpAVDg3laTbXnDdWZxNOD2fOz4hg3laV ZYbPux6bnyC3rynJhPKCVChVJzNGF4PNO+PzT959U/BxwSePbP+avLf1dYVR keuXjIsNWT8zlOxP1uqVijUGFT9Lp+afMWTyfaQ+Bkuo8ZxwPlYq9UJQKBQK 5TJdSryK+DjXGiunvd9oD7iLJFwXykSHDx+eRRgdpGB0nMHm2hlsb++pgWlj B4D3sgmi5K23srsw95yyuymf0/i7/Y9rfsa5z8rJMG7kc6BN22A3m5urOa/J C4Sls0fBqvljyPWhorF5+5z2rJh1MH3cEHhjygjC1OscZnPqem00zJ8xyiY2 N+a0bymNg+x4b8LVsYzLq5ThoE5WQHlumE394Oj12swQSAhdA2F+SyEzbiNk J/hCXqICijKCYUdVyjlsvr0yBYrIfXLoPLQEP8hN9Ie9dTk2sbmRyQtpLbmF OWp0zjmNp9s747y+LJXFxJUpIVCUHUVuX2hXzbmhNI3NOC/KiYZSZSyUqeKg qiAR9tRrzPO5zNn8+AE97NDnQ1l+MlQVpbEZ53UVudBQrRSY3I5e7fayuTk+ /+T4bjh1QjB5/M9qi5L065dOzizL9F5H2Hw1tUGlWEVYfVJtDv+INom/VOrj sQtF+/7QOMnXxNdIvBYUCoVCOV+PEKcR/8IJXE7rmmis/F4pF4UyLzoLnfD5 j5TRreV0nMHmPvnu7WewnTy6izDuJJhOON0xfj7X65eMY49bQtjZsccyz+ZG l6R7E8YdSJ5vvChsbprXnhK+Aia99hIkhiwzz+cizTfX54eD75oZMH38UFg8 6zXIT/W1i80pj9Na81mThtvM5qY15yVZQVCQ2tqnXVcYDRryd3FWiM394Pbo aW+3cCgi99VmhUJjRTJUazaxy2jPtzLioowQKMuLhO1VqWZnqNnC5tRFWeEd 1ptXamKZbWXz9nHz/Vs0kJ8RDqq0UFCnhYFem+xwzfnW6mw247y6MBkq8hOh XJ0AJco4wvExbD5afUUm7N9W1I7PxWNzevn+bSVs5nmpOhFKVJuJE5np34KT BGuSoIT8XaYRmHx3g5Yxe/t6czmwuSmfnzqxh5lc9q8qPepDQ0misj4/cC3l c72SX0mtUytW6FSK6QYN/1RDmtcVUh+bnawiTjg/myr1QlAoFArlNF1MvJD4 ICfs86nf5IRYeS8J14WyQocPH4428rnYsXQpGB1nsHWc737q/begIMkTxo18 FnxWTBSV0dUJa2H8K88yVqdxdbHZ3DSnfeOKSTBmxLOgSvAQhc2Nee30b59V U2HKmIFQkOJtQ+zcvj7tVaoQ8Fw6GcaPegkWzhwFMfxSwu8RVrE5/XvhzNdY fru9bG6sN6/TxkB2/EbYUZnUEjffTn4vSAtgbihJsKsfXBVh85KcMCjODiM/ w8nzJJxTc27kc3vYnOa3N9D4eAe94CiPb61II2wdZjebm8tp31KZAer0MOJw ZprDLmY/uCO7K2CnXsnYXUt5PdfoWNCVpBOGjgdDmTDbvMXlWW1M55vXlWez Wed6cn0ZYexqclkZ4Wx6GeVxyuaU0RmzO9gLTq5s3uL39kJVcTZ89O6uP98/ ZDhAtrMkgypgVa3SjzG6QcUvNygVywy5fpP0+fxDdcp1l0h9jBZZkzjhHK1Y 6oWgUCgUyil6kBNi5T9xwv7+1+a/H5dyUSjbdOjQobsIl591FqPjDDb5zWCj jE45N3DdNHh92FOwOWihqJwe5fsGYednWH26M9jcGDevylXAwhkjYOqYAVCe 6eswm5u6VhUM86ePhHlTR5DfgxyMnXdeb7528STYuHI6xActh3nTXoFJowex 3m9L5owG/3VzIMDzDWY6Q23JnDHkNq/CzInDICVircNsblprnrvZB2oIU7eP m+sKY6AkOwS0mcHn8rkNNedbSjezODo1ZfbCjBAoV0ax3PaO+NyUzXWE8fOS A0CdFmwVmxu9r0EJ2Yk86wfnKJubi5vTvnC01txYe76V1pzLqh+cc/u0uwOb M5Pfa8vyoOm9fczkvj8eP1DTEOi1IG/k0GdqY/zmKQxsThu/lOyLFteoFK/q Vb73arW8u9fmXUf8LfH/iPtKvBYUCoVCiacenNDr0zRW/g4nxM8vl3BdKAdE mHybKZ/LPd8dZ7A5nu/+1ekPoYFwKO39tm7xWFabbhtPd2za733Z7Fdg6AsP s7i62Gxu6vzE9TDuledg6exX2e0cZXPTnPaCZG+YMOpFWL9sknCZA3nt5vm8 Nac90m8RY/NGcl3rHLVNLbPTEsNWQ5T/ElDRnut21JtbM0eNcnlJdijh5kCz Oe07q1OgMD2IzVvTE2Z3pFe7MW6+pSwZNGlBUJARTLg9kvD6JihXtZpyuDI5 kDiA/aR83qYfnJV92mnMnM5Vy0kMIPdVi8rm5uLmhrJ0yM+MbHFJXix5/BKZ 9oM7P9i8qdmGSo3A5+8L/vT9/dRnSzUppx+4/95fn37ioSNL54xOqsjauEyn UiwxKPnF+jzFoto831G1efw9B9PSekh93LZDlZxwzjZa6oWgUCgUShTdzgl1 5PR7V7p//53DWHmX0aFDh0aY4/OukO+OM9gsx9K/+bIJthF+NPL0xhUTYca4 gRDpM0fUuvTnHr8PJo56nnC0h+hsbprTHuHzBrwy5EnYHLxEFDY3zWmPD1oK 4155AUI2zBWRzc+tOc9N8Gaxc4HRzee0J4Ssgg0rpkNM4DLYWhIrKpsb4+b1 xbGQHe/TYU57Q+lmwtWBLH+9rjjeLja3N6/dUj84i3zeLqddlRoCu3Q5TmNz c3Hztxq1oM2LYX3iqAuzo0FXnMquk3M/uK7G5pTL66vz27N5i4++tRVeHzXi 7A033AC3337bXy89++ib/NrpwXqVYpFgfqFeqZin1yiG12j4OwD4blIfw63Q dE44dyuQeiEoFAqFckgXckINOe27foYT9u3vckKs/EoJ14VyggiLH3YFo+MM NnnNYPvu6y9gZ1VSG2be5PcGzJ0yFBbPHMHmqjnK6Kr4NTBi4GMwYtBjsGDa MCjP3Cg6mxtz2g2aIFi9YAz0v/dW8F01VRQ2N81pj+EXw9Sxg8B7hTArTUw2 N8bMlYkbYfm8sWb53DRuTvu6bVw1E0I3LoBi8rtYbG6Mm++sSoHMWG+rZpzX aKJZP/bCjGDYzvq1y4jNLdSc52eGs3i6K9jcUk77vi0FUK5JIN4MVYVJUFOU wurIj7xZLgs274zP3ZHNqfUVKrNs/ukHB5g/enc3TJ8yASijU994443w1OMP fz59/Ms5JWley3RqxQJqg4qfT/Zd03Q5Ps/osr3l2gv9JuIfib8ivlritaBQ KBTKPt3CCbHyLziByf/hhPnlL0i5KJRzRdh7hiU+xxls7pXvbusMtl9+/gne ebPsHK6uzPZh89jo7PQJrz4H/NqpJmxtm2ke/fypL8Mbk4fC5NdegLnkpzbF yzKfOzDfnLpWGQAjBj0B9999C2wOWiIKm5vGzdM3rYVXhjwFTz96H3gumQQl Gf6isLnRU8cOtcjm7fPaa9ThEB2wHAK85kFGzHrIT/V3mM2NppdrUnjYbRo/ 7ySnndaWq1ICQJnkD1vLkmTJ5tT0stzkwA753Jlsbimn/ejuCta3XV+a3sZ1 FVnkvpWyYfNO+VymbF5bpoTjhxstsnmL3z8A61YvbWF0o++44/Z/hwx45kCg x0xFzqaVKyqzvBfQeLpOzc/VqQMm1yn9nq7M33it1Md0E1Vzwrnca1IvBIVC oVA26QJO2HfTWPl/nLAvP0XsxQk9RVBdXAcPHuxBOLypI0aXc006zmBzvCb9 wyM7oTbPH2py/c7h62pyGc17nzluIEwifL1o+nC76tUjNs5mc9jUCR7ksQbB 1DEvQWr4Upti57b0aVcnrocnHr4bhg94HHiPGex6R9ncNGauSd4IwwY+wWal zZ40DOZMHs5mp6Vv8gBdfphNbK4viISYgKUwY8LLEOaz0Co2N81rNxRuguRI D4gNWkme3xMyYr1AmxnYls9tYHNjTjv9qUr2t7kXHLU2O4zNOFcm81Cp2iQb Njfmte+pU0KZKtau2Lkz2LyjnHbK5g2V2WAozRBcltnibTV55La18mHzTvnc 9Wx+9EAD6MqtY/PTH7zFTH9funDOOYxOfdNNN8GwIS99NnfqK3kLpw8LI/vF eHX8msUGleINvZKfo1MGvGbI9+tfncZfLOGhfQ4nnM8pJVwDCoVCoWwTzcei DH6SE/bh/3JCrHwosTvUVKFEFGHuNZ3xeVeoSccZbJbz3X03boCr+1wJE0a9 0CF/FyZ7strymeMHMWafP3UYY29r5qoHrpvOTGPmVdk+4LFwDEx49XnWp47G 5x2JnZurN68vCIU3Jg+DNQvGsrlp86YOh5xYD4fZ3JjTTn/OmzaSxdS3lUSD OmkjhHjPgwUzXoVp44bA1LGD2U86P43OQ6Oe9PpAdjll8dmTR7C+cCvmjYPk iDWwpTjGZjY3zWtvLEtgnJ4d7w2GohjIS/RlMfXC9ABoLN/cAZ9bnm9epY5i NeaO9IKjfeAKMkKgOFuYhb69Kk1SNjfGzbXZUaLltUvVp/3I7io2R622JJ3N VKMz1CoKUtgctVLVZjZXrVGnhqN7a2TA5p3wuYhsTv/eWV8KW2oKYe/2qg5z 2tuz+ekPBX9Kfl84b5ZZRjf6kYf/7++ZU8YcGDbwCdXDD9xeNWLgoxmq+DUL 9WrFbJ2Kn1WbpxhNWV2rXdPbhYf0mzlhvs5p4q4+0x2FQqHcXTRWTvmbcvhf nMDldP9NOf0GCdeFkliEsS8h/P2dqxkdZ7DJZwYbfS/GjxtnnM0A9919K0wd /RKEe8+Gqhxfi8xdkbWRzVWjcfXZEwYzbp/y+oss1k57wxk9fexAxuI50SvP yWlPj1wOcyYNhcmvvwT82mnk+fxszms3x+c0n53+Pvn1AVCVG8DsuWQiTCN8 vGjmq5AVvdZuNjea/j2dMLi1Oe2U4b1XTYeEkJWwldzH0oxzW9ncNK+d9nhL DF8LmhT/lth5eV4Y671O+7PTWWnUW0sTLPL5rupUqMiLgOwEX6gvSXCoT3v7 uLmuKB5K8yKbHQX1pUkuZ3PK5dqcKJfUnEvZp/34AT3sqiuAysJUKFZuhhIV 4XbC7nT+eak6SfibMDx1WX4y7NDnw7F9Ohn2g+uYzY8f2gaGSjWbn0bnnBsq 1OS5d1nsBdcZm5/+8CDzxyf2woAXn++Q0anvvuuus7NnTPx8/syx1bfd1G/3 Xbdd3zh97IDI8vQNcwxKxcxaNT+tPj9wQK3G51atVtvdiYdzep5H8yHPEr/s xOdBoVAoOYjmKU0mzuaEXmm0j/nfxJ8RlxCPsvJxLiX2Jz5K/Bvxz5wws8yD 2FkzNvtwAoO/zwnn3nS/TfffNK/dmccJlBuJsHewNXwu93x3nMHmWL57UVER XH/9dYzRaR7nZZdeCj17XgSPP3wP4+/QDTOhJG2Djfnt1vWDo79vDlrEWH0a 4XmPRWNBvXmdXWxuWnOeEbUaNq6Y0iavvTKHB7/V02DmBPpcg8Bj8QTIJLxO e79Zy+aVuYEwe9JwiA9aZnO9uTrZB8J9F0Ji6GrQ5UeKxuamOe1bS+MhO34j 6AujzcbNa/Kj2GxzU+cl+kEOYXKa164r6GyOmji94BorU6GMcHqZchMzZfYK dTR57DxR2Xz/Fg0U50aDJj2MWadNkrzmXE694Ojfuxu0UKPNYKze1intnMpc bnRBGtRV5MGerSVwdL9B9Jrz9w43wq6GUthRVwzb67TkZwn5Wcy8VVcEb24t P6fe3FE2P31S8K4tFXDbbbd2yujGfnKvjBjyx7oV8/c8/vC9db0u6vHD9f2u OjzspUdT82JXz9WpFNPr1AGTKavXKX1vB/FZfQEnnOdlify4KBQKJTfRvKRf uda535ZcRtyrg8ehOUcfm9ye9kY/a/L3YeKrRFw37etGY+V/Nj/+t5zQ/+1u EZ8D1UV08ODBK6yNoXeVfHecwWY+lk7XvHjxYrioRw9YtmwZ1NXVQXBwEIwY Pgz6Xt0HLrjgArj15uvh5ZcehSUzR0K031zC7F6izzhXJXiAx8KxMHP8YMbs K+a+BglBi6Es09dqNi/N8IOJr70EsQGLO8xrz433BK/lU1gt+dypIwRuHzcY ZowfyvLVqRc2e/70V2D+tFdg6ZzRUEz7w9nZC47GzOl880i/xbA5ZCWUZgeJ xuamNec0z12TyltVc95Rr3bbYueO1ZvvrcuF4pxINgNdQ1yQGdbM79FQqYmF qvy4do5nLs6NYtakh5L7hgo/iVXk96LsKPK4Spf3anc4di7nXnAmcfOj+/Sw e0sJGAinlxemQ0V7FwmuLMpoa21mixv1hbDdoBVcZ3Qx7G2sJFy/y6Z+cGKw +WcnDzF7rFpiFZ+b+tWRwyA5PuzLRXMmv3npJb2/6t6t29/XXXPl4ZdfejhF mbB6jl6lmKrPU4wl+73Hq/P5viIcxm/lhJjPp8SXi/B4KBQKJWfRmDflW9rX fBPxCOI7mv068X6ulbHTLDwG/Y70ba6Vk8cS9+AEnp/NCbF0el2tCGulc9AO cm1j5XReWk8HHxvVxUU429cWPpdbvjvOYBN3BtuuXbvgkUcehhuuvx4KCwvh 7NmzQEXfJxpn9/DwgBeefw6uuPwytv+79pqr4alH74dxI5+DVfNeg1j/+SzW LtYctdIMXwjfOBdWzhsNc6cMY/XkMycMYfnrRtN68/nTRsB8ch39fdW8MVCQ 7A3KBE9IDF3OnBK+EnTqYJvy2sWaoWbK5qY57QWpCogNWM7q0FMiPWBbaZwo bG50fTGN2fu7iM0t8LnE9eZSzFFzWl67zNhcbr3arYmdW8vm1PXVhTbzudED B7wAWamxf/ltWPXuNX370Fln0OPC7r/edsu12yaNejG0NNNrmk6tmKxT8WNq lfwTdrI6zWvfygnnfEPEPC9AoVAomYpy7RxOmAtuTpS967nWPmvm5kzO4VoZ /iUz108zud6efevDnPDdwM/Nj/E9J8TK77PjsVDnqWgdOuHsr9yB0XEGm2tm sNHbxcTEwNV9+sBjjz0KW7duBXOir7m+vp7ddv78efDUU0/C5ZcJ3H7VlZdD //vugKEvPcbq0Gk/uBjC7gXJ6+2eo9ZZ3LyjXu30djSXPSlsBXN61BqoKwy3 Oq+9PZ87yubGePn28njIjtsAFbkhkBXrBWmb1kF6tCc0lMSKMuOc9owryw2V hs2t5HNkczHz2pHN7Y2dm7I59VZDid18bvTzzz0DmamxUKhO+/nZJx/94oIL LmD5k926dfurX98rDw154eHEvLhVM/RKxcRaleLl2kL+nsYcvqOcTFMt5YRz v1SnnSCgUCiU+4nG1I18PdjM9Y3N1+2wcH/63aexl7q18zBoTbxprJz6EPEs ruM8exTKoghvr7KVz+Vek44z2ByfwUZfw+rVq6Fnz54wfPgw9nlbI/r6aBw+ JycHfH19YcqUyfD444/ClVdewfZZvXv3gjtuvRGefrw/vDr0KZg9cQh4LhkP m/zmQV78WtCpAkRlc3P94BqKIiA3fj2kRq6C7Nh1oEnyBuXmDc287mDs3Eo2 N81pL8sJBm1GAPt9B3Feog9hdU9mTcr/s3cncDLWfxzAf67ckis5Imd7uK+S agnpIBJJJVLSRRHK1SZK6CDkKkWoFeVI5JhdN60Va6Xr30QHid115Pb9f7/P M2Nnx+6aZ+aZeWZmP+/X6/NSzI5nTvOZ3+/5/Uby5SZ7tcf5ZzNG0dK540zr 5ptXzKJ1X029lOXz36Uln76jZfGc8dqa7QtmvqFl1qSRNHPiCM5ImjphKL33 xqBLGT3sucsyYtBT9MqLvTlPZGTAk5dl6MA+9MaIfo701zOyP73zxmCaNG4o fTh5FH08dTQtnD2Bvvz0PVqxcCqtXTKLNnzzCff9z8K4m7v3c3Rzb8fO9+3a SJ3uu9fnfu5M0yaNaOqkcbR+zVLq/mCntPz58zn3ttW6+rVlSia2uqXe+3Mm 9u++cu7IzivmxLZaOTe2RkpcbHZrFNVQ+hzMXzhFA/RRAQAgFDRT2Y9/y/i7 8/13SA7XMdFxmb+v8HdFKX2sPNVx+ROO/29k+KgB3HCXLZiUlLTfnx09mM9J xx5s2c93l8jj0q1bN8qfPz916tRJ+39vyfElJibSokWL6O2336Z+/frRPffc TZGRN2rr0vHTUTvXvUzpa7T15Js30Tu8zGl/4cmO9PqgHjT1jefosw9ecexv brybZzenXdZ++2TSEPqUu/q8KUO1Xz+fPlzbR828ee3ZrwW3YNqrtCru7cvG zdcsfI/mTJH120bQPL7M5zNHaXuozZs6kr6aM1YbI3dmydy3uM/Hauefz540 jNYuft+jbr5m8WSaN30UvTt6AA3p35N6du9Ad7e9jRrWj6bKlSuZ1lOCJTVq VKNaNatTowZ1qflNjSnmtpvpnjtbUuf72lH3Lu3piR5d6LmnHqGBzz9Owwc9 TW/GDuD+/zJNmTCSPv7gTVrw0du09LOp2h7lW9csCMJufoV+jm6eZTf/KXkT TZwwmurXq+uX512D+vXovQljKGH1UnrskQcvXHVVAVmT6NKaRtzbj1epWG7t /e1uen3RzMEPrJg/sv3yj0c0WjwnthyRNqYjZD/cjUqf197Smk8NAABBS9Zf d675Vs7tz+qpjPfcu3O4jidcLlfK7c/kXHU5h3yjy2V2KX38HOuAgKm4n/f1 tp8H2znpwTDfPVz2YHPm5MmTtGPHDq2fS0/v3r279niaTW4DPxfpq6++oilT ptCIESPo8cd70V3t7qTo6EgqV66s1t+VNu6k9/jaNaTHR9M9dzSlHl1ac4+/ n0YP6UlT33ye4mYMp2+1eezG91GTrI4bT/OnDuMuPEzbJ03+W8u04fTFrFha x73dm3nt7v08/stJ9NHEl2n1wncNzWn/ev54WvjhaPrio9Hcz9+ldV9OzvJ8 c23vtDnjaNqEl2nUy0/RM727UucObejW5o2pJndVq/tyOEQ6f726Udz3m1Dr li3ovnva0ENdOtCTPR+kF57tRcMGPUNjXh1A7701jGZMGk3zP3ybvpw/hdYs mU2b13xOu7nLB8d6cLmrm+/cupqmvPcmde18n8drtvuaunWiadwbsbQ5YQU9 9mg3KlAgv+u6wZe6+vUVyqzpeOfNo774YFDnb+YMv3vl3BH1rr666CuOy7xv 4UcGAIBgJOebH1T6e+RnWfz5XSrjfbZuDtfjOkc+2uX3ZWz+N5VxfrusE99W 6d+bApiOq1Fe7tnbfenowTzfHXuw+T7fXTq6ZMuWLfTAAw/wZ8oC1Lp1a1qx YsWldeQC4ezZs9p9u23bNlqyZAlNnTqVRo4cSb1799Z6fN06UVqPz5s3b6Ye X7P69dS0YSS1ub0Rdb7nVm3N9oF9u9CowT1p0ujnaM77Q2jpJ697PKd9ddwE +mz6SFrwwXBaMG0Ed/jhNHfyUPp40sv04buDtfPIJTPfcWawltncw+dO4Y7/ wUj6bEasloWzXrvCenBXntMu/XzOlFdpfOzzNPDZR6jHg/dS21a3UP26kdq+ eVb3V+TKuYH7YVTkjdS0cQNqeVtzuveu1tTtgQ70eI+u9Hzfx2jIi0/R6JED adL4kfTR1LEUN+d9Wrl4trZH2u6ty/0/rz3Eu/nPyZvpmyXzacLYWOrJvbhR w/qWPt4RETfS6NeG0rYNq+i5p5+gq666Ksu9gvg97EzZ0ldvrx91w8f836cL Fcx/4J0Rj0WtWDEJawADAOhkzThZH13eN//hVMjiMl1VxntrjRyu61aXy93s 8vvS/3/ijORU9P2QAa6M+3VzzsVAdPRgnu+OPdiuPJYukftdzk+/+uqr+XNm BE2fPp3++++/gPX0Kzl37px2/2/fvp2WLl1KM2bMoDFjxtCLL75Ijz76KLVr 144aN2qkzd8uUqSIy7hVfipbphT3+SrUpGE03dnqJurSoRX16taOXujzAI0a 0osmjn5e6+FLPhmtdXZvx82NrNUue5fLXuVvj+pHr7zQk554tBN1uCuGbm7a gKpXu8HybolYnxtuqKp9P3VL86Z0V9uW1OX+e7Vu3/+Zx2n4kOfprddfpqnv vU5zZ71DX302ndYtn0ffJXxFP3Bv93XsPJi6+U+7N5Jt5Rc098P3aezoYfRE r0fo1ltupusrV7b8McoqtWrWpFcGv0jLv5xP97W/69J3i9mldKkSie3vaPLa Z5Nfuu+bT0c0+Xp2bPnY2FiM3wBAbiXvf3OV/h55WmV/7o+v/RzAEtyv5/na z4Ntvjv2YDN3DzbXji6R45swYQJ3gxuoTJky2ppwcttCzalTp7THTZ6/sv/7 vHnzaOLEidoc+2eeeYY6338/3driFoq4sbY2Pp8/fz7n+k78ebkk3VClEtWN rkUtbqpP7bjTd24fw53+Lur3RGca+sKjNHb4UzRl7Is0d8pw7vVvZOynxn18 7eKJFDfrdZo2YTC9MexperHvQ/RI17upXesW1LhhHapS5XrLOwQS3qlZozo1 bFCPbr9VH7d/qGtHeqr3IzSwfx96bdgAenvsCJo55S36fM4U+nrRbFq28COa P3sSTX//TXrnrZH0riPvvz2KZk0dxxlPH34wgS8/leLmfKBlxZef0DdfzuHM pYRVX9DGNYu1JG78mnZvX63lh522bLv5L9zvkxPX0tb4ZRTP/XvhvBn0waSx 9NrwQdSndw+65642VK9utOX3pbepWrUq9Xu2D302d5b2OKgcOrokX768JyqW L72mQ5tmI+KmDWr3zfzYums+eSOr/YQAAMKVdPNPlP6+eIZzTw6X9XV+O4Al uE9X5H5yPFQ7ejDvweba0YNtvrvRPdjcO7qMm8vvyZ7pLVq00Mag7777bq3j yp+HK7lP5Xm2adMmWr58Oc2ZM0fr9LGxsdrad4888jC1u7Ottk9d9erVqHz5 a6lkyZLanINSpUrRteXK8efy6yzvBQiCBE+uv74y9e71KL015lWqVKnCFXu6 0s9XT7++YtnlXe69ZdCyD4e1+HresCpx2a//DgAQDmS/809Vxrh5Tt1ceLM+ HL7zhKDA3XqYGf082M9Jxx5s5p2T7trTJfI4yjh69erVqXjx4vTYY4/RmjVr 6MKFC1ZX6oA6f/68dp/Lc0ee/+vXr6dly5bRrFmz6I033qABAwZQz549qWPH jtSyZUtq2rQpRUdHU40aNfgzOsbMESQ3R+bjv/Tic1S61DUedXRnChTI/2+1 yuUXPdI55jlZU27FR6+U5bejPNn8kw8AEIrkfPPPVUY3z6lvO7nurzY4h8t5 ur8aQMBs3ry5MPfq3wLd0YP5nHTsweb5fHdnR5fInPH4+Hh66qmnqHTp0to6 ZYMHD9Z+T9Z5gyuT+16eJ/Icl3Pppd/PnDmT3nzzTRo4cCA9+eST9NBDD2nz FWJiYqhZs2ZUp04dql27NlWrVo0qO9aGu+46jNMjSKilRIkSWuduc0cMlSlT 2lBPlxQqeNVfNateN79317aPfTvv9Zqr5ryE/dIBINTJHmeydrq8z51S+nx0 T8U7fs6WzZ/Ld5k/Oy4z1/tDBDAf9+iWZqwVZ/V8d+zBFtg92LLq6M6eLtcV FxdHnTt31sbUZY53ly5daPbs2drtgcCQ54C8flavXk2ff/45TZ48mV577TVt rb9evXrR/fffT23btnX0/GiqXasWVa1ShSpWrEjlypXT5uVfc8012q/ynYus OVC+fHmqyF2iUqWK2txcGfeTdffkV/n/SvyzVvccBAm1lC2r7ycp5wu92O8Z Sty8VtsPURns6M4UK1rox3oRN0we2a/bHVhTDgBClIyBL1X6+9p/St/fzIhe KuN9sUUWf97d5c/beH+YAP7BnXqmmf3cvaMH23x37MFm7nz3rDq6M3Idsi/b 888/r83lljXWZG639MTExMSA7tcGxsljLc9Led3I47V27Vptz/q5c+dq+92N HTuWXnnlFXruuee0tfLbt2+vrUsgc/dlDSzp+UWLFtUed4nsKxXTojE93OUe 6tX9PurJ6durKz3T+0Ea+Nxj9NLzj9HIIX1pxKCnaHD/x2nk4KfptVee1TJ6 RD8aN2ogjR/1Er0+7Hn+75cuZeLYoTR5/HAtb48ZQm/GDrgsYzmjR/Sn4YOe 1jPYmWf08O+98ExPbQ9z17zoSJ9e3bQ9zp/s2e2y9Oh+P3V7oH2W6dLpHm0d tqxyT7s7KOa25tmmaZOG1Lhh/SwTHRVBtWrVzJTajsgaCFZ3TsSzyHwX2cNS +nm9enVoc8JK+ucP/jcseTtVrlzR644u4es8V+qa4ptubRYxYtb4vtG2uNhi FnzEAAAwSrr5CqW/l53lPMgpk0MKZXEdcs76LpWxD1tHpY/Hy3U/xjnu+LOV frwdAF7bunVrCe7UB8zu6OEw3z27jh4M892DaQ+2rOa7O3P69OlLkcd0/Pjx 1KpVK62rSX+Tc7JlXXhZe00uA+FH1iiQsUHlQ9fwNAUK5KcSxYtlm5JXF6dK Fa7NOhXLa4moVY0ib6zOqZFl6kXXppub1s8xrW6/ie6841Y9rfXc264lde10 V0buv1tL7x5d6InHul7Kkz1lH/QeNPD53lpGDX9By5uxg2jiWyO0zJryJs2e No4+mT6eFs+fyvmAViz6iNYu/1TL9oSv6Lv1S2jX5q8v20MtadNySuLfl+y8 lBVaNq1dROu/jaMN3y7MnNVf0Jrl87W12TPWZ8/I8kWfUNzcD2jhp85My5SP pr2Tdaa/Q1Pee4MmTng9y4x/YySNjn2ZxjgybMgLNOSl5y/lmad60TN9H6dn OX2f7EmPdu/iSFd6sEsn6tjh7ku5s00ruqPlbZzbtTRt0oiaNm6k/Vq7di0t NWvW8Hsnr1y5MtWrW4dat4qhOtGR2vO2a+eO9Pfve7Vu/s8fP2kZ/dow014X +fLlPVbp2tJf3XNHw0dWzYkthzF1AAhispa6kfe4vtlcTxXOby6Xu8C56PL/ 33NK+etGAPiKu/Q9/ujnwTbfHXuwBa6j59TTz5w5ox2j7Fc+bNgwbc20YsWK UaFCheiWW26hQYMGaeO0mA8f+uTc+UB1cyTnFC5ciK4uIeeclKDKlSpoqV6t CkVH1tZyU9MG1OLmxnR325bU4e7W1O2BDtTzkQfoqd4P04B+T9LgF/vSmFcH 0bjXX6HJb7+u7a82d9Z7tHjBTFoa9xElrFrI/X4xfb91Ff2QZDNlj3PJ/h+/ 0/OTM4l6ftZz4OcdmfNLkpY/LmWnnl+d+V7Ln878b9el/PXb7kvZzz/z4+4t WpKT1tP2Td/Sd5tW0ybb17Ru5Zd6VumxXcpXer51ZgklrFlOO7as1ZLy/Wat hx86sI++XbFI278xMqI2/fHbnkzdfINtBTVp3NAvz4OiRQrtbdag5oh5E/vV jIt7sbACAAguZvVzUZwTy0nmnOQc4+zgDFL6WDpAUOMuPT+cOjr2YLNuDzZP O7pr5LLbtm2jd999l7p166aNMfHTUlvf/N5776WhQ4dq57XL4yrrpUNwk3MX ZN67zN1VQdBNEWtSpEhh7TsB+S7ghqrXU52oG6lZkwZ0+603afP7u3ZuTz26 P0BPP9mDXnqhLw1/+QV6c9QrNIn7/4wp42n+7Cm0dOHH9O3yBbRx7Vf0/bY1 tG/XBr90c/d+ridZjz2Z/rbvyZzfU7QcvJS9evY784OWQ85wJ3fmj/8lU1Tk jdrrY94n0+mjGZNoQP9ntPXhyl9bLiCPTYH8+Q7VrlZx6oiXujVbHTfkagUA AABBhTvxtdyl//VXR/e0p2MPttCZ7+7JHmxGOrqs9e7MuXPntPtS1jGXPcoe fPBBioyM1MZiixQpop3HLmuaT5o0ib755hvtMcRa8cFBuvkTTzyBbo74NcWL F6MyZUrR9ZUrauup1YmOoCaN69OttzSjtnfcTvfe1Yb7fwd6uFtn6tP7UW0u /OABz9HQwf3pzVFD6a0xI+iDSeNo+uTxtGDONPr80xmXEjdvFq1c+rmeZXpk vHzr+pUZ2bBKyzZHNqxdTt9+vVDL1199RgvmzqQZU9+hCWNfoxFDX6L+zz9F vXp0p7ZtWlLdOpFUtGgRy+9DSd68ef6rWL7UF3173H3vyrlDryPC3HcAAIBg wR26406T13MPt3PSsQeb7+ek59TT3Tu6MzJmLpG/Q/Yfk73F+/XrR3fccQfd cMMNlC9fPq27y15jsi75008/TW+//bY2T16eN3Jbwf8uXLhAPXr00NYXUEHQ PRAE8Sx58uQ5yz09bmj/Lm2WxY2uOH16H1lLCQAAACzGHfodf/bz3HROOvZg 826+u2tHz66nS6QLOiPXIY/z8uXLtTF16e6yV7jsD+7sinJ+u3R5Ocdd9n+T deXHjBlDH3/8Ma1cuVJ7bsrjJMcNxsljIucmoJsjSOgmX7686c0a1Xr5m09H NPlmQWzVFZOexzmaAAAAFkpMTCzAPWVrIDt6sM13xx5sgduDzch896w6untP l7nVzriS+0uedzJfftq0aTRy5EhtH/B27dpRVFSUtte3cvmMWrhwYW0v8Lp1 62rr18ke7n379tXWsxs3bhxNnz5dOx9eev2WLVu05508bnI/5EbyGHXq1And HEHCJJUrlP145bzYpl/PGdYYPR0AAMBaO3bsqMFdJt3fHT0c5rtjDzZz92Dz Z0f3pGPK/SnPpfXr19OXX36pzaN/6623tDXlH3/8cbrvvvu0OfWNGjWiWrVq afslFS9ePNPnWplrX6pUKW2uvezZ1LBhQ2revDn/XCv++Q70wAMPaOfOyxz8 IUOG0IgRI7S9xGU+vvT+Dz/8UOv+ixYtotWrV2v7jsv+4/y6vPQcdD5ewbCH vDxO99xzD7o5goRZalWr+LaMo389J7bxyrmxDdd+MqxiXFwX2VcYAAAAAiwp KalHIPp5bprvjj3YfJ/v7u+O7gu5v+SxlOfad999p3XrJUuW0Oeff6717vfe e0/r4dLJ+/fvT3369KGuXbtShw4dqHXr1hQTczs1bFCfGtSvx93+Bqpa5Xoq V64slbz6am0dbJXD5+gSJYprl6tcuRJVrVqF6kRHaddza4tbqFWrltS+/b30 QOfO1KPHo9rfK3+/HMerr76qHZOsmy/HOHv2bO27AfluQo7fZrNp3w3I61Se 9/L8dj5HhDxucuzo5ggSfilapOAO6eaSVfNGNNIyJzZ61ZzxRRUAAAAEHPfl BeHc0bEHW2jtwWb0nHQrOrq/yW1xPj7y3JLn4e7du2jL5g0Uv+5bWvLl5/TV ogX00cwpNGvaRHpv/BgaN2YkjRw6gIYMfJb6Pd2Lnnq8O/V4qBM9eP89dN+9 renO1rdSy1ub0c1N61PjBtEUFVGTatW8gSpXuo6uK19O2x8rp7Wmq1SuQO+/ NYQ+mhxLU98eSuNee4FGD3uWhg98kvr3fZiefrwr9ezegbrc15Y63BVDbWJu ouba3xVFEbWrUdXrK1D5a8tQieJFtf2gs/t7EAQJXPLly5sWc3Od51y7uYyh S76eHVt/2fTYIgoAACAw5N+cuzjDOYs5v6uMf7MmG7ielpwvOH9yznD+4azm PGTmwfqTzWYrxN15e6A6uqc9HXuwhc58d3/vwRasY+mh7Pw5vq9Pn6TTJ4/R yWNH6NjRvynt3z/o6KHf6eD+ffRTynf0w/ebtT2mNscv5/9eT7//uJ1++2EL /S9lI/2yO55+/t5G+xJX0b4dq2jPtuW0Z+sy2rVpMe3a8AXtTPicdq6Py5Tv 1y/Us2EhJfGfr1/xCa1aPJ2WLZhM82eNo9lTRtMHb4+g8a8PpNdeeZZefvEJ 6v/0o/T4I53ooc53U6d776C2rZpT82YNqEG9CO791alShWupdKmSVKRwIcu7 DoKEQmSvtRLFC2+uVa3iO+OH94zJqpuv+GREA8nquLHYMx0AAAIlRmX/75en /fxdt5876/b/0vvzm3nQ/pKYmHg99+ZDwdbRg/mcdOzBZu0ebOjowe/CBX6M zp3Vvgc4c+oE/Xcilf47nkrHUw/RsdSDlHb4Dzr6z3769+//0b9//UqHDuyj g/v30l+/JdOf/9tFf/yyk/b/uJ1+/3Eb/S9lk5af5XuB3Tb6ceca2pf0rfb9 QMq2ryll+9eUvGUJbVm9gNYum00rFk6nuNnv0McfvEFT3xlJb48ZQrGvPEeD X3iCnuvzMPV+tDN16diO7m5zG93eoik1aVSHom6soc0nkL5fongxypc3r+Vd CkG8zIX8+fL9W6jgVT+XKlls7fUVy35cL+qGUZ3vuemxuGmv3Kyt2+445/yy cfN5sfW/+XB4bduXsSUVAABA4MRwjnLWcMZxunH+Vvq/a5708xdUxr+DcznV HL8v3zX3V/pYuvzZO2YetD9xT27Lvfl8qHb0YD4nHXuwBW4PNnT03E0e9/Pn z2qR7wXOuuSMhzl7+j86d/a09t2C5N/D/2ivG3n9y/uGnKu/adMm7dz9pUuX aufyS2bMmKGd3z958mTtfH+JrAsoawBIZE0ASc+ePbW9AnKKnO8fTJF9DLM7 1kceeeTSbXOPcw2ErDJq1KhL95OZGTp06GV/18CBA7M8vocffjjHx0HWiszq /rj99tvPNGrU6J+aNWv+WrJkyZ8KFCjwPf8zmuhjtih9/p0zCzlxkrx5836S L1/eWQXy5fuwYIF8MwsXLvhuiWJFXitTqvjAiuVLP13jhuseaRhdvdNdrRq2 eqHX/dKza3w77/WakmWzh2uR35Os+Gx4dS0fD6/+zezYqmvjhlVcM3/otWs+ eaO0nHMeGxubN4AfPQAAAJyyWpvUrjzr54WU3u3lsrZsLjPQ8efnODW8O8TA S0pK6hfIfu7e0YNtvjv2YAu/PdgAAAw6wlnGieW055S3+t9qAACAXMKuPOvn rVTG2Pmd2VzmKs5Jx2VeM+n4AoI7+oeB7ujhMN8de7CFzx5sABB6XF/vzte/ 873A+d7gwXvBac5GzkROD061K/+rCQAAAH5iV57188dVRj+vnMPldjkus9WM gwuUxMTEIjsDvF5cbpvvjj3YwnsPNgDwjHundnZp1zhf566vf/fv77KKXM6D Xn6I9LHx4Zy2HJxzDQAAEDzsyng/vz6Hy+1xXOY4J48Jxxcw27ZtK80d+Yfc 0tGxBxv2YAMAz7j3afdO7fqadO/Uztez6+vbk7ivK5nVOpPOPp7D6xzz1AEA AEKLXRmf3353NpeRc9RPuVwu5PYo4U58A3fkv63o6J72dOzBFjrz3bEHG4C1 chqnzml82tOO7K+4f48nkeOSY5bbkY0zhHnqAAAAoc6uPOvnhTlpjstuUlmP jQ9Tmfc6yWoevJy7HpdFpmcR2cttrFvGcIZkkWc4fdzSk9Mli7ThtHbLLZxG kocffviRTz/99OSCBQto2bJll2XNmjWUkJCQKRs3bgzKsXTswRY6892xBxuA Lrv5387nues4dVadOrtevWrVKpo2bZr2vpRV/w2WyHuDHK8HfTyFM4fTn9OC U/QK/44DAABA8LMrz/dXG6wyuvciTh1OAU4FzlClr9vuuh96xSyu43mVucOH dYoWLUolSpTIlNKlS1OlSpUuS0RExKVERkZqadiwId10002Z0rx5c2rbtu1l 6dSp02X75HTv3p169+5NTzzxRKYMGDBA23vHNcOGDdP2/pG8/vrrWsaMGUOT Jk3KlPfff58+/PBD+uSTT2jOnDmXIt9nyL5L7omPj6f169dfyoYNG2j79u2X fc8g3y0E0znpZuzBJt9dvPDCC9p+S/KdBvZgg3CW3Vh1duPUzh7t2qf91Xnl fcv5vlyhQgXtvcR9Tou3cf3+zdu4zlXPxjnODs77nO6EsXEAAIBwZVee93MZ M5+qsu+jBzhvuvx/EQPHcU0WkX5fzS01lWOc2y0x6vIxcZmHn9X4+ZPq8rF2 2b8905h8q1atlvbq1Yvc8+CDD1Lnzp0zRfaLbdOmzWW5+eabqVmzZpnSoEGD TF3cmaw6u3R5934vnT+HxyDsUrhwYbr66qszpVSpUlSlSpXLEhUVRXXr1r2U evXqUePGjem22267LO3bt6cOHTpokcdPIo/tY489linymEu/lkjXdka+z4iN jb2U1157Tfs+Y+LEiZcix+S8HXI82IMNQomza7uOWbs+/1z7tFld18zO6xp5 zbu+r8j3iWZcr/tcGU/iOj6ewzpuRzlfk76GW0tOsRz/BQUAAIBwYVee93On GM6nnH2cvzhJnNc5sgbsW47r+8PMg7TKzp07+1t1LroZ89137NhBW7ZsuZSt W7dqkTHtb7/99lJWr15Ny5cvp0WLFmlZvHixlvnz59PHH398KTJmLpk+ffql sXRnJkyYoPVT94wcOZKGDBmSKdJvn3766UyRHizj/ZKHH374UuT7j3vvvTdT WrduTbfeemumyOfvJk2aZOrnklq1amXZ5a+99loqWbJkpuTPn9+v3zXIuD72 YINgIM8D184tzy3Xnm12P/Z3571S+vXrl+m12K5dO+2cG/c1Hv0R1/HxbOaq u5433oVTIVD/xgEAAEDQsSvj/Twn3zmu73OTrs9y3ItfDOWOjj3YPJ/vLn+n ++2R2yzfcyQlJV2KPCay5oDNZtO+63BGvudYsmTJpTRq1OhSH4iJicEebBAw 8rg6x71dx7r90X8D0XFd43pOiaeR94BBgwZp3/d17NhRm4tUtWpVWrhwoVfX 574WhTNyfPI6ltdoDuuq/0v6mupDCOeNAwAAQGZ2ZV4/b6oyxieyW+M9JHEn G5EbOzr2YPPtnHT5O9977z165513tL8Te7CBmZwdXB5v5znc8vwJVOc1O9l1 XjPi+lqVfPXVV1StWjUqXry4dh6LvIe4X+ZKcfZx59rq2YyNy4tL1nGbTlhT HQAAAK7Mrszp52U5KY7r2s7J6+P1BR3uxaOs7uie9nTswZZ9R8cebOjpoUge M+c4uDw35LkTbJ3X7Li+zvwRec+SdSdkLF3W4pS1K13/3P11L8ck97tzbDwb JzmrSd9vvDWnhNX/dgEAAEBQK8Up45L9Su/Us9x+P6v5djI+Po/TlVOPcx0n itNP6eeby/WkciL8egssxP34Pav7udlj6diDLTT3YHPt6JjvHl7ksXGeDy7P FTO7sL8775Xi3nn9HdfXb1aR1/j48eOpTJkyWkaPHq29B8ifyf0lr0d5veXQ x1M5yzmvcG7jGFkXFQAAAOCg8mwtq2lZ/GzMFX7md05Dvx69xfizVx7ux+9Y 3c+tmu9uRUf3Zr57KO3BFohz0jHfPXjJYyOPozzm8vwIh87ra1xfe77E/TWd UzZv3qytF1GwYEFt7w15f8nGn5zPOM9x6nLCbq4YAAAABJQv/bw05xXOOqWP l5/hHOZs4LyojO2nFtK4Ew+xup+7d/Rgm++eXUcPtvnugerovs53D9Q56ejp /iP3tbOLy/Mj3DuvN3F9PZod19e93CfyOpTXkrwehDw2ss57njx5qGzZsnKO ugyay7rqYzntOeWt/rcHAAAAALKWlJTUlzvyBas7uqdj6a4dPdjmu2fX0YNh vrsVHR17sIU+ud/k/pbHSR5reY6Ee+c1O+6vV18i97Ozj+cwV/0/zuo33nhj QYECBdKU/l31HJX1+V4AAAAAEGS4G3fnnLO6n+em+e7ZdfRgmO9uRUfHHmzB wTk27uziuaHzehLX154/4r6Pg0T+XnkM5HUjz/ccnr9HOHGc/pxGnPwub+/X clYovaPv5TSw5B8ZAAAAADCEu/HDubmjYw+20DknHXuwmUfuG7l/5TGT50O4 d15v4j6vxZe4fxfnGjlm1z6eA9l3fAnnJc5NnAJXeHvPw+nPOe3IEBWGe5MA AAAAhJukpKQO3I9PWN3PvZ3vjj3YsAcbxtJzJrfbtY+He+cNVFxfw9nF/TUv r095XV1hrrr4i/S13J7lRHPyePkWH83ZrfSx9NWcCqb94wEAAAAAfsH9N5q7 sd3qbu6PsXTswRY6892xB5t55H5y9nFPu7HVfdebzutr3NeM8Daur3dn5Fjl 9SevE3lOy/MwG/KkTORM5HThXGfyW3xhzkSld/R/OB1Mvn4AAAAAMFliYuJ1 3I2/s7qbWznfHXuwhc58d+zBlpmzj8tj69q1Pem7ZnZes/pudp3XrLi/Vn2J vPblOuW1Ka8heU4711XPhhR16ePOtdXLBehtviPnX4W14wAAAABCAvffotyN v7K6m2fV0YNtvrsVHR17sGEPNic5drlv5DGRxz8cO69ZcX2tmhU5Rue54/L8 zWFsXJzmrObEclpziln4Ni9rx32jsHYcAAAAQEjgz455uBvHWt3NjY6lYw82 7MEW7vPd5bjlvpPH05s+HOyd1xn315iZcX0texr5OXkdyutF7v8rjI0Lba8z zhBOC04Rq9/X3TjXjjujsHYcAAAAQEjgLvziziBZ2z03zXfHHmzYg82VHLPc j/JYynMoXDpvdnF9zRmJ+/drvkSOQ15/zj5+hXXchIyPr+e8zmlL1o6PG9GI 86PC2nEAAAAAISEpKakxd+Pfre7mVnb0YJ7vjj3YwnMPNjleuT/l8Taj/wZD 53WP6+stp7i+Rn2J+2vfNXIfyetJntvyXPPguSB7ncne4304UZx8Vr9X+wBr xwEAAACEEO7oZTlrre7mvsx3xx5s2IMt2MfS5fbJ4yLPlXDovEbj+hr1Z+R+ kteWPL89OG/caT9nDul9vJrV78l+0klh7TgAAACAkMC9syB39GlW93J/jaVj D7bQme8eTnuwybHJ/SvPjVDuvMEauQ/kNSivCXmOynPGw8f2N848znOc+pzc cm52ZY5NZawdV9/awwEAAACAnHBH78bd+ITV3dzK+e7Ygy105rsH4x5s8nfL fSbPBav7a7hFXofympDnqzx/PBwbT+Uso4y11Ytb/T5rMawdBwAAABBCduzY 0Yi78U9Wd/OsOnqwzXfHHmzYg03I9cl9IY8vxrV9j9yHzjXV5blooIuLg5wv OS9xbuEUsvo9NUg1Vlg7DgAAACAk8OfjYtyFZ1ndzY2OpWMPNuzBFsj57nLc 8ljI88jqThuqkdejvFbkeezca9zA4yHruMk+Z+M43TnVrX7vDDHua8e1t/Zw AAAAACAnSUlJnbkbH7G6m+e2+e7Ygy1492CTv0fuR3k+WN1tQy3OMXF5fslz QR4nD53h7OJ8xhnO6cCpbPX7Yxi5n3NEYe04AAAAgKDHXbhiMK3vjj3YsAdb oPdgk9+X45bHyOqOGypxnisuzx0P9xgXxzjfcT7lDON05tTm5Lf6fTAXkO87 4hXWjgMAAAAIevz5OA/34T7cj09a3c+9ne8eqI6OPdjCZw82+Vm5n+Sxt7rv Bmuc54rL804ee3ksrjAXQYp6Cun7i4/l9OA04lxj9fscYO04AAAAgFCSlJRU j7vxNqu7uT/G0rEHW+jMd/f3HmxyHHK/Y623yyPPe3keyvPDg3Fx2Vf8G9LP D3+M04RTwur3MbiiJpyfFNaOAwAAAAh6MpbOPb0H9+PDVvdzq+a7Yw+20Jnv 7ukebBI5dnncsnuu5LbI816eh/K8kMdF7rOspv+7jIfLHmZdOFGcq6x+rwKf yD500xXWjgMAAAAICdyBK3E//tLqfu7e0YNtvjv2YAvuPdjk5+Q+ksfa0+90 wjHy/JbnlzzeOazdJueHb+HM4PTn3MG51ur3IvCrzirz2nFFrD0cAAAAAMgJ 9+GW3JF/tLqjezqWjj3YsAebRH5O7jN5Drj38tzQ0Z3rt8ljJveF2znjznPE 5zh6eAucH56rXc9JUFg7DgAAACAkbN26tQR34gnckU+HQkcPh/nu2IPNu7F0 +Tm5z+Q5kNPzI5w6uvs8dbdzxmWg/HvOJ5wBnFacUla/p0DQyaf09eLOKqwd BwAAABASZC827sjTOedzW0cP5vnu2IPttPb/cr/I88DIcyQUO7rreurynYSL XznLHOeJt+dg3S8wqinnZ4W14wAAAABCBvecZtyBNoTCWDr2YAv/Pdjkdshj 7e33OMHc0+W5Kc8heezkvnNZw03OFbdx3uLcz7nB6vcFCBtYOw4AAAAgBCUl JbXmHvR9sHd07MEWfvPdpZvLdcrjY8bzI1g6utwe53njchsd543/x9lI+n7i GBeHQHmAc1Rh7TgAAACAkJGYmFiAe9BjnL3h0NGD+Zx07MGW0dHltiUlJWWK 0edHMMx3l+eSPJZyf7qs4/Y/zmeO88Vl7Tb0IrCKrB23XmHtOAAAAICQw/2n Bfeh1VZ39GCb74492Myb7y6/L/fpjh07LsWTjh4sY+nynHGOj8vcfEcXd11H vZjVr2MAN1g7DgAAACCEcRdqw1lndU/HHmzhtQebXJ88lomJiVpCoaPLc8K5 lptjz/GfObM5j3NqW/1aBTAAa8cBAAAAhDDuQ004H3MXOhVsHd2bc9KDbb57 btqDTa5THs/vvvvuUj937+ie9nR/dnR5jsjjJPfNqVOnzl+8eDGJe/hEThfO dVa/JgF8VELp56Jj7TgAAACAELVt27bS3Ite4vwSih09HOa7Z9fRg2G++5U6 ulyvdG/p5s742tG96elZPVec67nJ7Tt9+vQF7uA7OOM5d3FKWP3aA/CTLkpf O+6i0td6xxoJAAAAACGG+0pe7kx3cTdattPkPdRXrlxJM2fOpI0bN/o03z1Q HR17sHk2li4/I4+jaze3uqPLYyT3i3x3cOHChR/4eT3ZscdZKatfYwABVIWz QWHtOAAAAICQt3379vLcj/pztvrazWfNmkUFCxaUz4hUqVIlSkhICMh8d+zB lrmjmz3fXSKPCz9XsuznV+rpZnV05xi5HM/58+cPcif/hLv4I9jnDEDlV1g7 DgAAACCscC+q6OjqG73p582aNdO6uTOxsbFBMd8de7D5Nt9d7ivp5s5409G9 PSdd/m65b/h4jp87dy6OO3kf7uPVLH6pAASrZpxfFNaOAwAAAAgr3I8acF+K 5V8T+deL2fUp6VqTJk2i+vXrZ+rmEpnnbmScNBjmu2MPtswdXY5h27Ztl+JJ T/elo8tzQB4HuY0nT57cf/bs2Wnnz5/vhHPIATwmr5W5CmvHAQAAAIQl7sCl uDt14T49h39NlR4lXW3QoEHaPHa+CJUoUYIef/xxateuHVWvXp0GDBhgytpx obgHmz87eiD3YJNf5bHZunWr4Y5uZL67PK5yv/HxXDx16tTG06dP9+dgjBzA N09xTnIucG6x+FgAAAAAwA969OhRulmzZtO4j6fz/1LZsmW1nu6+HpynwR5s 1s93z66jy7FKN3fGzI4uj6ncX3Jc//33344zZ84M40Ra/fwGCDMRnHc5eaw+ EAAAAAAwlayJHcs5rPR5kz9zekyZMkXWl+vI/Xoi/5qc01z4QHT0cJjvHix7 sMlj4NrPfe3o8rjJ7ZbrPnXq1G7u5YP416oWPqcBAAAAAABCSUXORM5xpffy FE4PToGsLsydrij37BaOdebiOP+Y2dOxB1tg9mCTn3fv5t70dHks5X6Sv+vk yZM/c2JPnz5dO3BPXwAAAAAAgJBXizOHc0bpvXyL0tcZMrRnT1xcXL6kpKR6 nKe5g3/E2cU5F+j57tiDzdgebHI7tmzZ4lVHl7Fyub/k7zx+/PjJEydOzOG0 JaJ85j9NAQAAAAAAwlZDzjKlrylEjv9uYeZfsHnz5sI7duy4ifv4sy6d/Sz2 YAuec9LlfpR+7syVOrr08n17k+ivPw9oa8txH/8f5yX+72vMfO4AAAAAAADk AjcrvYtf5JxX+th5g0AeQFJSUgXu4e25lw+RteJlbzfOaezBFvg92GQNt82b N1+xo+/Ytop+2R5L/2y9idIS8lHalhpHjv8+7YFAPm8AAAAAAADCgKzpK3PW Nyp9rPyc0nt5lJUH5Yo7YImdO3c2557eh/M+d3Ibd/R/sQebf/dgk3PHpZ9n 2dHXL6Tkdf3oD1sEpcWrrHI43abaWf3cAQAAAAAACAFyHrCs8bZT6b38P6Wv AVfFyoMyQsbauYu35Qzkjv4hZzv/93HswWbOWLqzm+vZRFvWzaRtXz9BPyyP pIPf5s2ul7vmYppNjaU4hXPOAYJfEc5dnOGcxZzflf5vg2Syhz//IOcjzh6l 77sua5cc4HzBudf8QwYAAAAIeQU5/Tm/KP1zV6rS90wra+ExmYp7+jXcw1vw r33414nc1VdzRz8UbvPd/b0H2+bNG2nT2um0ZemjtO2zmrRvcSE6vNajXp45 CSr+5Hp1ndXPC/CYrz1N1pUcwFmo9L0eZD9GmZdzlLNV6e835cw+aPBZjMp4 nN1zpce9sMrY3yOnyPOpkPmHDgAAABBy5DO39HLnZ+2/HP9f3MqDChQiysud vAZ38Y7861Du6wv4v3dxzuSG+e6G92D7azclLYqirXOLe9/LM+f3Y/Ha+gYQ /GKU9z1NTMjh551J57Qx+bjBNzFK/w5lDWccpxvnb+XZ417Mcbk/lf74y7kt 1RzpwNmmMh776eYfOgAAAEDIkLWzY5U+hiWfjaSf91H6OHquZ7PZ8nMfr8N5 jDORu/h6/vUY9mA7THt3raE/1zfxtZe75nyqTcUSGdufDwIuRnnf08TznFmc Xkpfc7I6pzKnKWe00uc9y3WlqTCatxMGsjoPxa48e9zl35OenPw5XPe3KmON k9JeHSEAAABA6Kqg9PPJjyn9M9FepZ9vXsDKgwoFMtbOfbz23r17u3HG8X+v 4RzNlXuw/fM3HUkZxN3a5/Fz1/nua06sUdda/ThDtnzpaZ7orDLGUnuZcH3g P3Zl3uPeTmU87q1MuD4AAACAUFBT6euvn1b65yA531PWZ8eYpY/kvHbu5S24 p/fnX+dwUjgXg+mcdH/twfavfeGJ9Hj1p4lj6QeOrVO3WP2YgsfsyryeVlRl 9LT+Jlwf+I9dmfe4N1MZj/sdJlwfAAAAQDCT/dDiOBeU/vlH9jFvYekR5QLc 1StwL+/M+ZDzVyidk25wvvuxYzZVhjv6UhM7+rm0BDWESNvjD4KbXZnX01qr jJ7W3ITrA/+xK/Me94GO65J/o7A+IAAAAISrm5TexS8q/XOPjJ03sPSIcjHu 59U4fbiXL+OcCYY92L788ktq3rw53XbbbbRmzRqv57sfOXKksnRp7tR9uFuf NKunc+dfkrZBWycBgpddedfT5LxkWa+7hNLXdZfx8iOO65pt4vGBf9iVOf1c zjc/6Liuz3y8LgAAAIBgJHPWN6qM9Xakl0dbekSQyY8//liGu/nD3Mnn869H rJjvLpcrXbr0pXWzS5YsSc8++ywNHjyYhg0bdiljx46l8ePHa5kwYQLNnDlT y6xZs2j27Nn0xRdf0MCBA8cofezz9p4dVJeV76uf42co2vqxou/nZ+THxYrs yzLy71rP1ndPX6fNf4XgZFfe9bQTKmOs3JkdnN5mHhz4jV353s9lzbjVjuv5 R+lrowAAAACEA1m3SdZ426n0zzr/KX0NuKoWHhN4iDt6FGcI9/PVnHOBmO8u +8blyZPnSntdWZZCVykqWdyRYoqKFtL23frVJbJ/dqJL5Dup1S6RuSNxLpHv qaa7RF4fYx2J5QxxiYzl9nGJvLa6uES+A2vtEjlfpJFL5JwS5x5S0jmucUm4 7Y9gV+b1c1kbXh6XoiYeH/iHXfnWz2Xdk7mO65A1UVqac1gAAAAAlpI116U/ /KL0zzmpSu8aOIcvRHFPr8R5Vro6d/Oz/tyDrVu3bpe60SOPPEKbN2+mtWvX 0sqVK7WsWrWKFi5cSJ9//vmlOMfPJdOnT9fG1MeNG3e6WLFiz/L1PKdcem7z euqzZ7uqUy90VyTp00lRz/YZeeAORR1jMtKysaKYRnpua6iofq2MRFdXdG0p dSJvHvWb0vv5H0rvc86cUiZ+P+DHnHc77oMq5+8dElTm7x0Wq8zfO8xQGd85 TFMZ3zlIRqvM3zu8oDJ/7/Coyvy9w10q8/cOnvRku/Ktp8nfId9nvKr0vc/l upKUPvcdgpddef+4Szf/xPHzZzj3mHdYAAAAAJYoovQxPrvSP+P85fj/4hYe E5iMO/Y13MUf5X6+iHPS7PnukmXLltE333zj87pxhw8fbp/VbTiSoCqnxasE E9eO+/HoelXXi7uzsMo8ji3j2s4xbumHruPfMh7u2lPltrn2WBlPd+258tpz 7cGxKqMjy3iw67i9jOO79msZ53ft3zIPwLWfS1937e/yWnft9/78LqGGB/er XfnWz13VU3pfk+sbasL1gf/YlXePu8z1+lRljJujmwMAAEAok14Rq/Rz9eTz ze9K7wfhNmcW3HCXLvzLL7905F7+KSc9CPdg+yC7Y6c4lU/WY+dufdakjn5K 1qIL5P0fxEqqjO8cZK2tai6prTJ/7yBrort+79BBZf7eQfYcd/3ewZPv++zK vH4uFjuub6NJ1wf+YVfGH3c53/xzldHN7zb/sAAAAAACQsb6ZBzumNI/2+xV +hheASsPCqzBXbwQpyNnHnf0Y0GyB9u+Kx23rPPG3fpXs8bSU+PVnIOrcK6y xezK3H4+yXF9dpOuD/zDrow97vJvlfO7FzkXpZ1/DgsAAADAr2oqfT6sjDXI 55ptSp9rm9fKg4LgIePq3MU7cTefzzlp9h5sBjr6hX/++afYlY736Gp1NXfr +SbOd997ZJ02Px2sYVfm9vNvHde33aTrA/+wK88fd5nftdRxeVm7tK3/DgsA AADALyKVfm6q7Fsun2nkHNUWlh4RBL1ff/31au7mfTibzRhLz66jZzffnX+/ kafHmpqgenC3PmFSRz+eHq8e8ud9C9myK896moyfXun7GxlTvei4vtE+HxmY qRSnjEv2K/1xmuX2++7zWaSbr3Bc9iznQbfLuwfrAgIAAEAwuUnpXfyiI9LR G1p6RBCSZB147uhDuJv/Gqhz0g8dOmRoXOyYTd3I3TrJzPnuBzZr68CB/3jb 08pzjii9x3dU+rnx13Ku59zBmar0/ibXdUjp59JD8JB9BjxZU3Ca289Fe/hz zvT18+0AAAAA8ITMWZf1kOTzyTmlz2mPtvSIICzYbLb8//vf/9pzH1/FHf2i 0T3YDM5372L0+GiFKphmU2O5X18wqacnpa1V1f1xX4LG255W3sOf+4lTx983 AgxDPwcAAIBwJ/vMyBpvO1XGeXmyBlxVC48Jwhj38Wq//fbbWO7oR82a7/73 n79Run0mnd33AB2yb3zY22PjXt2G87dJHT2dY/i7AvCItz1N1sxopfQ95zYr fdxd1tWQ9z07Z4nS14/HXhQAAAAAEEhyHqbsXfSz0j/Hpip9z7RyFh4T5CL7 9u0rzp28D2eft2PpBw/soBO/DKOLKY2J9kRqObuv/Rxfjuv4JlWOe/UKkzr6 xdR4NZFS1FVm3W8AAAAAABA2inD6q4z1lP52/H8JC48JcrHExMQCdru9N3fz /3na0Q/bl9KpH3txH4++1MszEn2cUqJK+XJMRCpPaoLqz/36jEk9/bu0BHWD WfcZAAAAAACEtGuUPj7+j9J7uczrlF6OfZshKLj09P1ZdfQ/DtjpyK8f0dkf 7suik7snYpQZx5RmU425W/9kUkf/Nz1B3W3GcQEAAAAAQEiqoPTzyY8pvZfv Vfr55gWsPCiA7Mhe6tzPX+akOXv6gd9/onN723jQyy/lKCVWu9qM4zm8URWX NdlNne+eiNcfAAAAAEAuUkPp66/L2kfSy7cpfX32vFYeFICnuJdX4H7+lbOj n9z3lJF+LnnNzOORtd44qSb19ATu/RXMPD4AAAAAAAg6kUrv5c49fGUf8xaW HhGAD+x2+8Pc0Y///Vs8d+4oz/t5SlQa7a5zjZnHkrpWVUmNV5tM6uj/pCUo Q3u1AwAAAABASLhJ6V38oiPy37dYekQAJtm/f380Z8uZHzr9a2gMPTky1uxj IZvKn2pTsWnm7JV+Xq6LCPNaAAAAAADCgMxZ36j0sfJzSh87r2PpEQH4CSVH xxjq534YQ3dKjVctuV//YdJY+toTNlXeH8cJAAAAAAB+lU/pa7wlKb2X/6f0 NeCqWnhMAAFBeyI2Gevoka/661iO2VSZ9Hi11KSO/sexdZjzAgAAAAAQIvIr vZfvUXovT1X6nmnlLDwmgIDivn2f4TH0nfVL+u14SOVJS1B9uF+fNKGjn8N8 dwAAAACAoFZE6XuV25Xey/92/H8JC48JwBLShyk5MtnYWu5RI/x9XMfXq0ju 17vNGEuXMfn0zaqUv48ZAAAAAAA8JmN+sZx/lN7L9yu9lxe18JgALEfJEY8a 3Gst1Z9j6JeOy6YKyf7mJs13/z3dpq37CAAAAAAA1rlO6eeTH1N6L/9B6fPa C1h5UADBgmwx+blz/2aso0cMD9TxcUfvxP36iAkd/XRqgvadHAAAAAAABNb1 nOmc00rv5duVvj47zkUFcEMpUc8ZHEM/Qj/XCNg5IUcSVGXu1wkmjaV/mWpT fh//BwAAAAAAFaH0fdHOKr2Xy97lLSw9IoAgR79VLcSd+29j+6FHDAvoMcap fGkJagj367MmdPSfUtepeoE8fgAAAACAXKSZ0rv4Bc5Fx39jfyUAD0nfNjyG vq928UAfZ/o61Yz79a8mdPRTmO8OAAAAAGAqmbO+Uelj5eeUPnZex9IjAghB lFjtam3/NGP7ob9ixbEe2apKcL+eb8Z899R4NffgKqwTCQAAAADgJTmHXNZ4 S1J6L/9P6WvA3WDlQQGEOtoT9ZbBMfR/rRhDd0pNUD24Y58woaf/cNSmoq26 HQAAAAAAISi/0nt5stJ7eZrS90wrZ+ExAYQNSo6+llKi/jM2hh71spXHfMym buR+nWRCR/8vLUH1tvK2AAAAAACEgMJK36v8N6X38n85QzgBWz8aILeglMgP QmkMXTvmFapgmk2N5Y59wYT57nP+SlRFrLw9AAAAAABBSPZAiuUcUnovP6D0 no5zRQH8hHbXqcad+5yxjh41xOrjFtyv23C//suEsfSkdJuqYfXtAQAAAAAI Atcp/XzyY0rv5T8ofV77VVYeFEBuQXsi5ofaGLrT8U2qHPfrFSZ09GNpCaqr 1bcHAAAAAMAi13Omc04rvZdvV/r67HmtPCgIKjLv+C7OcM5izu9Kf65IJnvw 8ydcLn+lbDT52EMGJUfX5c590eB+6IOsPm4nIpVH9k7jjn3GhJ4+nVLw3SAA AAAA5BoRSt8X7azSe9FqTgtLjwiCVYzKvk+b3c+nmnvooYWSI782OIZ+mFKi ill93K7SbKox9+ufTOjo36UlYH8IAAAAAAhrTTnLOBc4Fx3/jV4OOYnhHOWs 4YzjdOP8rTzv56U5ZXJIP5XRzxuae+ihhbt2C4P9nLjTv2T1cbs7vFEVlzFw Ezp6WmqCut/q2wMAAAAAYDKZsy5zh6UDnVP62HkdS48IQkW+LH7Prjzv51ey wXFdO024rpDHnXtDqI+hO6XZ1APcsVN97OgXU+PVREpUBay+PQAAAAAAPsjD 6cLZofT+c0rpa8Bhzij4yq7M6ee1VcbY+bM+XldYoOSIewyPoadEDrT6uLOT ulZVSU1QG30dS0+PV+sPb1QVrL49AAAAAAAG5Vf62uvJSu89aUrfM+1aC48J wotdmdPPxzuu5z+l7+0HShtDTzLY0Q9SYqOg3T+cbCp/qk3Fcs8+72NPP5y+ Tt1p9e0BAAAAAPBAYaXvVf6b0jvPvxzZI7mElQcFYcmufO/nMl/5kON65ppw TGGD9kQ9ZHgMfU/Ui1Yf95WkxquW3LH/8HW+e5pNjaW4LM+7AAAAAACwmow7 xqqMrnNA6T29qIXHBOHNrnzv551Vxtz22004prAh3ZM7988GO/rfwTyG7nTM psqkx6ulJqwdt+6ETZW3+vYAAAAAQED5uvezUwfHz+9X+l7jci64jHMv4LT0 8tiuU/r55OmO49mn9Hnt2DcY/M2ufO/n3ziu42cvfnYAJ5GzjvMtJ44zjzOd 8x5nLGcoZzCnD6en0tdiuIfTWun7GMha8dU4lTjXcAp6fUv8gJIj+xofQ494 werj9lRqgurBHfukjx39UNo6dYfVtwUAAAAAAiZGqWz3avakm8i54HFuP+fc 28z19yYZOKbKSu/lzn2ltyt9ffa8Bq4DwBd25Vs/l+fwBcd1vOzFz4/i/Kr0 czjSVPavUW+S7rheuf4flP49wHrOas4XnM+U/j3A+0r/HmCE0s8j6ct5Qunf A8j3cfI9wM2cRpwanCpK/x7AozFu+rlGQe7cfzq7d/rWG+nxTiUpin97+FNl 6GJyNmPomysVNnxvWuT4ehXJHXuXjx39nJzbToT3PwAAAIBcIEb5tvfzQJXx uX+R0vc0k/NuZYy7GSfe5c+7XuG6IpS+L9pZx+XlmLB3OVjBrnzr5686fl72 +jNrjrK8pqT/yni4jIs34DRRek+WcXPpzT2VPp4+SOnj69Kv31V63/5U6d+l yXi8jMtLL5c1FqWnH1T6+4D792q+5ITjOv/H+cnx921S+vcAX8qxtGhQZNvT D15DQ3qXoYfuvjrTzy+eWDmb/dAj+pt0fwYE2VQh2T/N1/nuqQlqefpmVcrq 2wMAAAAAfuXr3s/bHJfdk811yTnizr7/RTbXIXNxl6mMcXf5b/RysJJded/P 87r8/FfmHVLAyTi1fB8ge37J9wFRSn9dyvcBMp9Fvg+Q803k+wDpzLFK/z5A 5r7I9wHyXZt8HyCv541K7+cpSv8+4C+lnwNzqY/Xv7FQpn7+/tDy2Z+HHkJj 6E6pNtWRe/a/Pvb0/cfitTkLAAAAAJB72JXn3cS5x9nHOVxmleMyK9x+X3q5 jKM5e/lSpfDZE4KCXXnfz+9UGT3zXhOPKRxd89OKGu/+urIGrZ5ZhUoUy6vd b1UqFKCDCbVy2g/9easP3BtHElRl7tgJvs53T0tQQ4hUHqtvDwAAAAAEhF15 3k1mOy67S2V9friMc/3luMxrbn8mY2wyhibjbdW8PFYAf7Ar7/v5QsfP/qmy nlMCLmhX3XLcuU9K7z6yqTZtnFuV/tsRcaW14v4KxTF0QYmqAHfsNzgXfJrv Hq/mHtmKvSUBAAAAcgG78rybyJpQ/zguL2u111Z6T5d14+T82G8dfyZrWLt/ lnSeRwsQbOzKu35elnPG8bNjTD6msMV9+33Da7mnRD1n9XH7Ii1BtUqPV3/6 OJb++1Fbrj0XyKy9R9y96XI9B308RgAAAAAz2JWxzzgVOTNVxjrTsr7becd/ S3eX/aBKmn6UAOaRdbfKuET2CZTn7yy33y96hetxrpco52vguycPUXJ0Ze7c Zw129JAdQ3eS8W/u2PN87OjnZb671bfFAjHKZb0Ct3jbz2VPwnMK/RwAAACC i10Z+4wjY+afq4xxQ9ecVPq56ZXMPkgAE8nncE/WJJ92hevZ67jcWr8daZii lKg5xvdDj3rW6uM2g2Ov9OM+9vR5BzarkP6+wqAY5dveI+5kztf3Sv9ubYtC PwcAAIDgYVeef8aRNd5SHZeXPZRjlL7ms8zzbcfZ6fgzOQe9lvmHCmAKM/p5 c5fLPeTPgw1HlBwdwZ37gsGOfkD2Ubf62M1wdL2qmxqvUnzs6GsPb1TFrb4t AeLr3iPuhquM1/gEhX4OAAAAwcOuPPuMI+sHJzkuK/usZfV5qRBnt+My35h3 iAAQbrhvLzE8hp4c8bTVx20WGf9Os6lpPnb0bbl4n3S78q6fRyp9/pd8j3y1 Qj8HAACA4GJXnn3Gqa48Gy/sqzLOyb3S+bsAkEtRSlRT43PcI/eHyxi6E3f0 1qnx6i+vO3qCSjy4Kle+19qV8X4u65k657Pf7/g99HMAAAAIJnbl2Wec1iqj nzfN4XJ3uVwuyoTjA4AwRXsibMbH0CP7Wn3cZnPslX7El/3XrL4NFrAr4/38 RcfPfOnye+jnAAAAEEzsyrPPOM1URu/umsPlnnS53PUmHB8AhCnaE3WnV2Po KVFXWX3sZuOevT+7/n3ga0VPdlJ0c11F7w7Idhz9QatvQ4DZlbF+LnssyBqm 6Urfh8QJ/RwAAACCiV159hlHzi0/6bhsgtLPR3dXgJPouMwf5h0iAIQr7tqJ xvdDj3zK6uM2W077oz/bNfPahbc1UNQxJiMPtlH00J3qeIEC6kP+8+mOTOKM dctrnCFu6c/p45YenC5uaa/0eVSukf3YG7lFzu+u5pbrlL6WqGsK+XiX2ZWx fr7Wcfln3H4f/RwAAACs5Mvez+NVxmfE5Ur/LCbnghZR+ue0DS5//oI/bwQA hAfu2l28GEP/PdzG0LmHH8qun7e/zaP9BsIhzxu4y+zK837unNe1SV3+3TL6 OQAAAFjJl72l5PPwl26Xu6D0teDcfzar8XUAgEyIVF7u2z96sR/6k1Yfu5ly Ov/8q7cVFSygv7/WqKxo/9eZ//zQakX2ZYr2fqFmqIzxaRmzdh/HlrFt9/Hu W9Tl4+L3qsvHz2VM3X2cXcbe3cfjY9Xl4/YTVca4vjNyznycW+40cJfZlWf9 XOaypyl9zfbILP4c/RwAAACsZMbez52U3tNlDrt85jmt9M9Knyn9sx0AgMdo T8QTuX0MnXt2ek5rwO3+TNHnYxX9+U0O68QlqPetvh0BZFee9fMFjsvJ/K9i WWSi488Pufxe2DyvAAAAAAAAjKDERgW0vm24o0c8YfWxm4X79Qkf90KXddxH WX07AsiuPOvnW5Xxefax/jhgAAAAAACAUEApUQO8GEO3h8sYOvfr077287R1 6g6rb0cA2RX6OQAAAAAAgOloV92i3LcPe7Ef+uNWH7sZUuNVio/9/NiBzaqw 1bcjgOzKs35+JTj/HAAAAAAAwA337de8GEP/VebHW33svuJ+Pdinfm7T1mEL Z77sPZIT9HMAAAAAAAA3lBJVivv2cS/2Q+9l9bH76uhGdT337Ate9vP//l2r rVMezsxY2zQr6OcAAAAAAABZoD1R73oxhv4L2WLyW33svkpLUGu86efpCepV q489ANDPAQAAAAAAAoh21a3EffuM8TH0qJ5WH7uvUhPU417081/+sWl7ggEA AAAAAACYipIjP8qNY+jp8eodg9383LF4dbPVxw0AAAAAAADhiXbVrs19+4IX +6H3sPrYveXN2Hm6TQ23+rgBAAAAAAAgvHHXXuTFGPrPoTiGfnS9qst9+4TB fv4N2VTI3VYAAAAAAAAILbQnqokX/ZwoOeJRq4/diLQN6ho5h9xgN//hyFZV wupjBwAAAAAAgNyBkiNXh/MYuox/c9dea7CbH061qapWHzsAAAAAAADkHpQS eYd3Y+iRj1h97J7grv2W0fXg0tapO6w+bgAAAAAAAMh9KCVqsxcd/adgH0NP S1BduW9fNNLPUxPUQKuPGwAAAAAAAHInSo7o5NUYekpUd6uPPTtHbSqa+/Zx g2PnH1l93AAAAAAAAJB7Eak83Lf3eDWGHqfyWX387lJtqiR37Z8MdvPtZFOF rD52AAAAAAAAyN0oJaqnV2Poe6IesvrYXRGpvKnxapnBbn7oSIKqbPWxAwAA AAAAAFBiowLct+1edPS90omtPn6n9Hg10mA3P3NsnbrF6uMGAAAAAAAAcKLk yH7ejaFHdLP62EX6OnUP9+0LRvp5eoJ61urjBgAAAAAAAHBFiY2KUErUP6E4 hp5uUzW4b6caHDufYeUxAwAAAAAAAGSH9kSN8HI/9K5WHfPBVaood+3dhsbN 49V6SlQFrDpmAAAAAAAAgJzQ7jrXcN8+5kVHT7FiDF3Wnue+vcjguPmBEzZV PtDHCgAAAAAAAGAEpUSO924/9MgugT7W1AQ10GA3P51uUzcF+jgBAAAAAAAA jKKUqPLct0950dH3BHIMPS1BteW+fd5IP+c+3yNQxwcAAAAAAADgK9oTMcO7 MfSoBwJxfNzNb+C+/a/Bbv5+II4NAAAAAAAAwCy0u0417tvngnEMnVLUVanx apPB9eA2yM/587gAAAAAAAAA/IG79hderuW+g5IjelNiI7+sj87dfI7Bc85/ St+sSvnjWAAAAAAAAAD8jfZE3elVP8+Y676PkqPrmnlMaQnqKYPdPPWYTd1o 5jEAAAAAAAAABBL36xY+9XM9R2hX7dpmHM9Rm2rBffusgW5+Pn2dutOMvxsA AAAAAADAKib1c8lGX4/l8EZVgfv23wbXgxtoxv0AAAAAAAAAYCUT+zn5Mobu zXpwnBlm3hcAAAAAAAAAVjG1n6dE9fT2ONJt6j1D3TxBxVOi8svadAAAAAAA AACBZm4/j3zFm2NItameBsfNfz22RpU2+74AAAAAAAAAsIrJ4+cvG/3709ap Rty3Txno5unH16tIf9wXAAAAAAAAAFYxuZ/3MfJ3H7OpMty37Qa6+YVUm+ro r/sCAAAAAAAAwCqm9vPk6BiP/944lY/79mqD55wP8+NdAQAAAAAAAGAZ+uHG 0tytT5k0fl7e07+X+/YYQ/uo2dSnRCqPP+8LAAAAAAAAACtRSuSHJvTzXzz9 +9Js6gHu3BcNjJtvJZsq5M/7AAAAAAAAAMBqtDfiJt/ntkd+6snfdWSdiuLO fdzA2PmBEzbl8bg8AAAAAAAAQCjjjr3dx73VHr7S33F0tbqa+/aPBrr5ydQE 1SAQtx8AAAAAAAAgGNCeiCd86OcXKKlG2Sv9HWk29Zmhc84TVI9A3HYAAAAA AACAYEGbKxXmnv2vl/183ZWun/v2UIPrwcUG4GYDAAAAAAAABB3u2W9718+j nszpetPj1V2yd7mBfj4fa7UDAAAAAABAbkXJ0dW1uerG+vkZ2l3nmuyuM22t qs59+6iBbr7twGZVOJC3GwAAAAAAACDYcN/eZrCfr8juuv5KVEW4b+8yslb7 yfXqukDeXgAAAAAAAIBgQylRV3HSjO2rFn1/dtfHfXuekbXa09arhoG8vQAA AAAAAADBiPZGtDY4dn5UOn1W15Uer/oZ6OYX09apzoG+vQAAAAAAAADBiPZE TTG4LtzMrK4ndZ26nTv3OazVDgAAAAAAAGCMrJfOnftPY3PbI9q4X88Rm6rE nfsg1moHAAAAAAAAMI72RDUxOLf9EMWpfJmuY4UqmJagtmKtdgAAAAAAAADv UErUaGNj55HT3K8jzaamYa12AAAAAAAAAO9x595jqJ+nRN7h+vPczZ8w0M1P pCaoBlbdVgAAAAAAAIBgRD/cWMvg3PaDrnPb0+NVE+7cp7FWOwAAAAAAAID3 KDnyJWNj51FTnT97fJMqx517P9ZqBwAAAAAAAPANd+4NBvdVa6n9nE3l5869 Dmu1AwAAAAAAAPiGUqLKc+e+YKCf/8UdO6/8bJpNTfC4myeorVirHQAAAAAA ACBrlBz5uLGx84jJ8nPctx/EWu0AAAAAAAAA5uDOvcRQP98bcdvRBFVH1mDH Wu0AAAAAAAAAvqNddYtSStR/BtaF++P4elWWO/dvnq7Vzt38fqtvJwAAAAAA AEAwo+SITgb3PJ/EnXuVp/Pa0xPUq1bfRgAAAAAAAIBgR3siPjbSz09uKfmR gXPO52GtdgAAAAAAAICckS0mP3fuI55284vJNx6W+eqertVONlXI6tsIAAAA AAAAEOwoOTrGyNj5mcTrzng4br4fa7UDAAAAAAAAeIb2RL1rpJ8f31gEa7UD AAAAAAAAmIw792+edvMLu2p60s0vYK12AAAAAAAAAM9RcnRdI2Pnp7+79spr tcerkVbfLgAAAAAAAIBQQilRIw3Nbd9UGGu1AwAAAAAAAJiMkiN3mDa3HWu1 AwAAAAAAABhGP9xY1cS57ftP2FR5q28TAAAAAAAAQKihlMjnja3bnu3cdqzV DgAAAAAAAOAl7txrPJ/bXgNrtQMAAAAAAACYjHbXuYZ791nP57aXy66fv2H1 bQEAAAAAAAAIVZQS+bCxue2FsurmC7BWOwAAAAAAAID3uHPH+Ti3ffuBzaqw 1bcDAAAAAAAAIFTRb1ULce8+7sPc9oNHN6rrrb4dAAAAAAAAAKGM9kbc7cPc 9tPHElRzq28DAAAAAAAAQKjjzj3d87nt1TONnacmqB5WHz8AAAAAAABAqCNS ebl3H/R4bvv2jLnt6fHqHauPHwAAAAAAACAc0O4bbzY0t31DIee4+XKKU/ms Pn4AAAAAAACAcEB7IsYandueGq9SjmxVJaw+dgAAAAAAAIBwQSlR+zyf215W +vnRYxtULauPGwAAAAAAACBc0O46NxqZ235sQ8Hz3M/bWH3cAAAAAAAAAOGE 9kQN8bSbn/++usxrf9HqYwYAAAAAAAAIN5QStdnTfn52R4VEq48XAAAAAAAA INzQ3ojruHdf9Hh++/c1oqw+ZgAAAAAAAIBwc/776ycZOPd8r9XHCwAAAAAA ABBuUteqKueSqpzxvJ9HjbD6mAEAAAAAAADCycFVquix9Xn3UHKEx+u20w83 Yj81AAAAAAAAABOlxav5J7eU8Lyb74n83upjBgAAAAAAAAgnsj8a93M6u6Oi 5/08OXKo1ccNAAAAAAAAEC5SbSqGu/m5tPg8dDG5tuf9fHedalYfOwAAAAAA AEA4OGJTlbibH5Kx8xObixoZO99h9bEDAAAAAAAAhANaoQpyL98m3Vxy5rvy nvfzlKiXrT5+AAAAAAAAgHDAnXyGs5tLLuyu5Wk/v0i7at9g9fEDAAAAAAAA hDru40+6dvPjGwsZWLc94jurjx8AAAAAAAAg1B1bp27hTn7WtZ+f3l7WSD8f bPVtAAAAAAAAAAhlhzeqCqnx6i/Xbi45v6ua53Pbf7ixqtW3AwAAAAAAACBU UYq6irv5Jvdufmz9VQbGziO3WX07AAAAAAAAAEJZerx6x72bS05tK2Vg3fbI gVbfDgAAAAAAAIBQlZqgHsuqm0vO7azi+dz25OjKVt8WAAAAAID/t3cn8FHV 997H/yCyh5CFkLAou5kZNkFFERUUcQUVQXAXF0SF2t72drFbnj69T7drfWx7 rb22t9XWLtHaVlu7uEwSshMm6wA1WqO4L0AAQVA49/dLzpghzHISZnKyfN6v 1+81k8nMmXNmwjDf898AoCfaVWTmSA7fFymbNxcd15E1z0vdPhYAAAAAAHqi Hc+YVMnh26K1ne8rG9mBsee+z7h9PAAAAAAA9DRWvjlOMvg/omVzrYOB8U7z +SGrduY4t48JAAAAAICeZmeh+b+xsnlzQX/rcEOu03xe7PbxAAAAAADQ0+x6 3lwpGfxwrHz+QWmK877t9Z673T6mXm6o1EVSX5F6QuoVKcuuHzl4/KVh949V NyV4vwEAAAAAUewpMl7J37tjZfPWvu1jDzju277Fk+P2cfVyC030TE0+BwAA AIAe5v1yMyLWfHDhZQVzdznM50VuH1cfsFBqh9SzUt+VWi31pul4Pt8rlRmj BiV4vwEAAAAA7ViW6ddcaP7oJJt/UJr6WAfWVVvv9rH1AcdFuK3JdC6fAwAA AABctMtvvugkmzcXmI1Wg+f7DrP5x1LZbh9bH9VkyOcAAAAA0KNI5r5Isvch B/n8nff9Zpxk7xedtZ97/G4fWx/WZDqfzwdKDU/ObgEAAAAAItm10UyS3P2+ g2z+8a5Cc64V9Poc921v8Nzp9vH1YU2m4/n8Y6kXTNt8cPuk9BzLjSZyH3oA AAAAQAK8UWWGSu6ucdSvvdB8XR9j1Xu+HC2Pb3lystX0j6mhnz+yAlNGuX2M fViTSez87TrP38hk7CgAAL1RXl5e/6qqqqFbt27NKC8vH1dZWTleS65P1aqo qJi2adOm6VqbN2+eKTXXaQUCgVmhx4Ztw6Pbra6unmA/V3ZtbW2W7EPqtm3b UhobGwfJ9ePdfl0AAJHt9JtfOcnmUk9blumvj5HcXRkpm9+yfGRLjuvf31g/ vCdbb3vO5cPr65qM83x+ltRDUpdITTKt87RrFl8s9VfTltH/mowdBQCgJ/L7 /YM1A0vmzZWsfYZk5IukVkhdL1l5rdz+qW5cd8p+3iL7ea1cXymXS+VyiRzP OXI5Ty5nl5WVeSTfTwwEAmMk84+U4x3g9msOAL1Vs9+sd5jNX24uNen6GKt2 po49P9w+m7/2/DQna2dTHStvB97OSJqM83wez09M234tSsD2AADokTZu3Jgm efUMybDXdIOM7Uatkyx/ndRyzfNSCyS7z66pqZkWyvH5+fmMiQOADthZaM6W 3H3QQTb/sLnInBZ6nI4nj9R2vrsi1xo6uP8n2TI15Thr6JB+f5Lr+VSna5zz dzSiJpO4fJ4itd/e3r0J2B4AAD2KZs5NmzadL3l0QzfIyN29NmjbvNSVcn2R XJ4s2f3E4uLiFLffRwDobt57zoyV3P2Ww7XUNoQ/VvL536ONPX/i/vHW9KmD rNNnDbEKfjGhzK3jwyeaTOLyuaq0t/f7BG0PAIAeQ8d2d4Pc2xtK29+vkrx+ Xii319bWDnP7/QUAN1h+M2BXoSlwOB/cHy3L9PvksdWzR0oOP+hs3nbfbW4e J1o0mcTm88329h5P0PYAAOgxJFNO6QbZtteWvL63yeXl5eXlC+QyV+fUsyyr v9vvOwAkk+TuBxyOOf/XjmdMavhjrQbPaofrqh20tuZmuHWM+ESTSVw+1/fz gL297yZgewAA9CiSFfvZY65dz7J9pTZt2nRXIBBYXV1dfb7OWS+3naBz8rn9 twAAibCr0NziMJsfaC4wp7Z/vNXg+43DfP43N44PR2kyzvK5zsU6JMbvdY6X 35q2+eHOTMTOAQDQ0wSDwYGSGVe7nVv7elVWVq6Ry0skt59aVlY2Qa4Pdftv AwA6QvO25O79jvK533yx/eOtoG+g5O5mR/m83nOLG8eIljn2M8PqVdOap3/a 7vb2Y7z0tnelfiB1mdQ0qdFSk6VWS1WYtmzO2HMAQK8mWe94naO9pqZmrFzP lZojefBsuVwi2fwyez0y5ojrZmWvFbe0vLz8dLk+iTHtALqrPUVmlOTuVxy2 nf8jtM55OKvBd4HDtvMDVt2MNDeOE+Yt42zdtgfbPS7T4eP+IMX5aQBAj6Tz r2/bti1FslyOjiXX9b0lx51Z1brm93JdMywQCKzrZD4kr3fDkve0pZ1d+8ZL bh8nfwMD3f47BNC3tcwHV2Cec5jN39xTYrIibifoe8BhPn+6q48Rn+hsPtf+ 7deZ1jXOq6XelDootVfqBalHpBYnf/cBAOg8bS/V7K3rcFdUVJwi1xdpe6pk 8Kvl+q2dzd3y+NsjlfzuDh0frSXPsz5GRtTfbQhdup1Z+3htqKysvE7XyZP3 Y6Zcz7Ysi7XaAXQZydzfdZjNDzU/by6ItA2dw11y9+uO8nnQu6arjxEAAPQd mqe0LVTHHkvGulDnD9OsHCOT3VnVuqbXbXatDav2P7eUbPNmyXDX67Z1vLnd vn6pbGdJVet63mfqOQDNeLrumuzPVLnPePldjlSmVKrOYxZqr9f+1nKZq/eX bZ6ij5fr58r1i+T2G7tBbu2zJe/Fej2HI++frvc2vba2Nkv7Wrj9dw6g99n5 vLlMcvdhJ/l8Z4G5P9p2rKDvNIdt5x/qGmxdeYwAAKBv0Myk83hre3WMvKU5 fI2OEZf7rZDMtVQzsK61rWPIdWyy3GeO5jDZ1lRde1tqTChTNzY2DsrLy+vy Nb00E8rzz5N9XBXn+KguKPn70X4Rq/UcSk1Nja+kpCSLdnYAx2KH30yX3L3H Ydt5tfW0GRRtW1bQ+x/O8rnnqa48RgAAgN5Gzw8Eg8F0+/zBGdpuL3VTnDZg Mn3yM/t6Pe8jdYGOZ9dzO8xBB8CJnX4zUjL3Cw6z+b49RcYba3uSvRsc5vMb uuoYAQAA+hKd28xuZ58s2X225EOdU/4SbefVvvh6XWqe3i75cVWsMfFU4qqy svI2ubxcakFV63z/mZZldXkfDADdk869vrPAPOUwm1s7C83dMbe3NXeaw77t +63GKSO66jgBAABwpPD5ySUnHq9j4rVPv2T15VWt4/Bdz7N9obR/vFxeo+Mx qlrX5xtfWlo6xM2/DQDuaC40X3eazaX+onO/xdqeVe/9nMN8/qeuOkYAAAB0 jLbpSlYfrXPU2eP4r3c7x/bBulVe9yt1PgTtIy+ZfYrclun3+we4/fcBIPF2 +82lOg+7w2z+3rvFZky8bUru3ugon9d7r+uKYwQAAEBiBIPBgdq2K3WqPT99 Z9eho46xdM0A7eegc9LV1tbOkdsmV1RUZDAvHdAzNfvNFMncOx33a/eby+Nt 0wr6siV7H4q/pppvn7XtpJSuOE4AAAAkT3FxcYrkwmmSE8+SjLiSuedcL12z fY22u8v1JTpnoK4/UFZWNkHze/iYBgDdw/ZSM0Qyd6AD2fxXTrZr1Xtucdh2 /odkHyMAAAC6nvaLl3yYLZnwNMnsV2le7AaZlQoreW9ul/foOqnl9vzyem5F 2+B1vroTNMdv376d8e9AF9Dx45K5n+jAmPNtb/3dOFoLQrL3k87GnvuuTvZx AgAAwH06z5nmPsmEF1cx51xPK22Lv03y+3Xy/q2Qny/RsfDV1dXzNc/L7R7J 8hPleo7cNrKxsTHq+ssAIttZaD7bgWx+YFeRmeNku1btzGEt/dad9G0P+oYn +zgBAADQvWjfasl5J0muW2rPWe52/qQSXPY6fbdq+7zdx/4SHSNv97M/uays zCNZfoL2sdBMr+dvLMuKOf800Fvt8JsFkrkPOs7nhebLTrdt1U9f7nDe9seT eYwAAADo/nSuOR0XrTnO7UxJdY/SuQukbrH/JlbqeRy5XCI/nyOX8+Rytub7 2traiZL3x2g/fLk+LD8/nznx0ONI1p6oc7B3oO08P95aauGsBt/Dzsaee1Yl 8zgBAADQs+ic8JK3LrLbXl3PiVTPKyfZ3p4n76h8T/s9upo9H1y102zeXGAa 3vEbx33QLf/CAZK933eQz/daVXOHJvNYAQAA0DNt3LgxTXLT2Tp/mdt5j+pT tU7y/Bq5vEb75OvagXJ5vv4tVtnZXsfay22TampqxsptmbpuAXPho7Mkcz/Q gXbz3e8/b3wd2b5VP32hw77t+ck6RgAAAPQOkn+Olxzkk0y0qhtkN4qKVRvk 73StZPcbpFbLz5fbfUHOlZ/PlMu52m5fXV09VX53Qm1tbZaOu/f7/YNpt++b dvnNug5k8492FZolHX0Oq8F3n6N8HvSuTMYxAgAAoHcqKSnJsucXW9cNshhF JbrW6Xr18vd9tfydL5efL5E8v1guF8jtp8ptM3VORfn9iTqnXl1dXZr8bihj 7numHQXmrI7MB9dcYD7V0efQMeqSvZsc5PM99G0HAABAZ1iWdVx5eflUyStX dINMRVHdojo7p57b/577oj1FZpRk7lc6MFd7p+ZVtxp8s5y1nft+m+hjBAAA QN8jOX20rsNNmzpFda7sOR5uDPXJl1x/oVwuCq2DF762vc4Loevguf3vviez gmbgzgJT0oF+7dZOv/l0557L+3Vn87ZPX57o4wQAAEDfpW3qdrvgRaynTlHJ r3jt9TrWvn1bfV5eXn+3PyvctqvQfC9CBm+O2be90FzTmeeS7B1wkM+brZcn DE70cQIAAABKc4DkgzlS17idYSiKOqLulLx+s1xeIzl+uWT4i+T6IsnvLW31 2v++urp6go6vD82d5/bnSSLtKTQeyduHI83LHrP9/HlzTkefy6o9aaLDedsf TcaxAgAAAO1pX1z9zq9te7SrU1TPrFht9Tovfk9Zy36X33wzSgbfFyOfH9rx jEnt6HNZQe8GR/l8i+fyZBwrAAAAEItmdfn+7pXv9EsZr05Rvb7u1LXs7fnw rwgfVy+Xc/SzQC4n6zr2W7duzfD7/cOlBiTr80fnUpes/VJH286lajr1fA3e Zx3MC7fLapwyKNHHCgAAAHSUfDdP1Tmt7e/utK1TFNVSyZgLf3ehmR8lf5fF zOd+87mOfrZJ7k6X/P2RgzXPf9n5T1AAAAAgObZv3x7qB3+hPZ+16xmBoqie VaG58OVzZJWe95OfL6tqzfVnv1c0Nv/o/D2gbIe/37YYa56//m6xSeno55lV 773O4bpqy5LxeQoAAAAkio5b1TYx+V49T75j6xxWtK1TFNXpqt5c+ukdBYP2 ts/fr28866/R1zzvd+iljTd8QdePlM+hs+Rz6DQday8/z5LLKfoZpevd6Rx6 7cfaS/Z+jL7tAAAA6I107TYdo1pFXqcoqhP1Yvnn7z9qTvbCgfveKFnwt2j5 /PWi+X/v4PPcoX3y62oK1hxumL4/Xj7/qP6Ux2tra7NKS0vTt23bltLY2Dio O86pBwAAAMSieb28vHycfB+eJ3W5FHPNURQVtd4snlPYPn+/VZRb+X5R5quR svn7BSnv1lQV/Ftnnuu16i//xEnfdr1fpMfbY+9b+ulLXSPXVwQCgWU69kfq 3MrKyvnahi+fgVO1Dd9eBy9p8+oBAAAAHaFtTvI9NlO+u86UukDqJrfzAEVR 3aXK795RMHTXUe3jxec9GWUtdGt7yQV/6Ozz7albWhovmx+qn/XB5k3Fn0nk cdr9im6Vz7+WOfXk52W6vr1+JkqOP0fy/Ok6r578LlfXuJfLHO2fr+tq6Gco bfcAAABIFp3LWduX7HGjK+S76B3u5wSKorq6Gsu/dN/RGbzf4TdKFv05Wt/2 YOX/fK1zz1d+96GG2bvj5fO9tZeUu/26RKh1uh5eVWub/ZVy/VLJ8efrnPkV FRVnyGfqHLl9ulyfJnn/RLlfTjAYTJfP2RE6v2d+fv5xbn/uAwAAoGfQtiH9 LinfKXPtNZpWSt3ZDb4TUxSVxHqjeP4/juq/Xpix/Z2iSXUR+7YXjni7s8/1 SvX37nPUt73maw+6/bokquy1MfWzVNe7Xyufr6GMvyJ8XTxtv5e8r+tpeqrs de/lMrO4uDhFPpsHuv1/BAAAANylmX3r1q0Z+n1R11+y12G/ze3vuxRFJa7e L0x//aix54XTy3YVDjgQKZ+/uXHWxs4+V3PdqmfjZfPDDbP3Jrpvey+pDZrv JdffILVafr48EAho//xz5eczKyoqTtH2e507v7a2dlxRUdEozfZyv+Pd/r8E AAAAySPf94ZKnSCl/TnP1++KzBlPUT2v6iof/mqkMeZvb/SWR+vb/krpdb/o 7PN9XH/qO/Hy+Z66pWVuvy69rew59W6R7H6t3W5/qVwult8t0DXxqlr7TY3X PlQ6T77b/8cAAADg2Ghbe11dXZp8z5scCAS0Hed8+d53lT3PsuvfTymKOrqa Nl7xm0gZ/O3CqYEo+fxw/abf3dOZ52rc/NB/OJu3Pe8Bt1+XZJf2eQ+fg15q pfZP0vZwzc06X111dfV8zc7JrqrW86zTQyU/T5ZKdfv/FAAAACSHzo2kYynt 734L7HmTb5Dvhuvd/p5MUX253imaVBNp3fN3C8c0Rh57nvZGZ59rZ/1NT8bt 2x6cvbt6c/mn3X5d2pd8Xq3XPK1rX1RWVl6r5x41T8ttF9t9iBZqH3PNuxUV FbMkX3t1/k1tk5bH5+g4IblM1bZp5okDAABAd2RZVn9dm7isrGyCrmtkf8e9 rKq1TWmD29/JKap3V/ndksU/OCqDF2U1RR97fnJRZ5/vQN2ZL8fv276sJMHH eaf265a8fL1k51VhmXqxzqmhc7LJ9ZNramp8mqerWsft5EhlSqX6/f7B8jlF ngYAAECfpm1MuvZwRUXFRP3+bGf3ZTp+soq14CjqmGtL2be+HSmDv1eQsT3a 2POXS276WaeeK/DYV6wG3+G4fdtrv/FfYY9bFzbXua5ntlTXKpefF4XmQ5Of Z8rPubW1tRO1j47k8FFVdq7Oy8vr7/bnGAAAANAXlJaWDpHv5FnyXXyy5ndd n0hK1yrSsZzr3M4+FNXda3vJpY9F6cP+ZuR83u9wXdUTX3SybZ2PTOcal+s3 6vyRu+pv/HH8edu979ZtfDSN+ckAAACA3kW/41dUVGQEAoETdX246urqU7UN Xuctlhy/Svu8VtGHnuq7dcdbhZM3RcrhOwqHvhHx9oIh23R9bp1HQvuCy/UJ cjlOz5PpOBW/3z88WraW/P103Lnhgt4fd/XnBAAAAIDuQeecl2wxTPOF9o+V zDJDap7meLm8RGqlzmMnGZ/2eKrLS+cjs88j3Wivd/3JHN9yfUlo3Wu5Pk/n JbPnX8wNn5fM7mOSqn/nmp3Dx1JL5n4lSj/2iLc3F5r7OvXvrHHKCMnfH8bP 575zE/evGwAAAEBv5ff7BxQXF6dI7snWLK/zM8v1UyX7LJDr58nlJfLzcrm+ Wud4Zl25vl2hub7l7+FqHTttj71Youd+5Pr8UJ6uqKiYpn085Hc52t9D/8aC weDAZP897yg2J0TJ5nt3FpiI7ec7nzeXdea5rKB3pYN11d6y8g3zsAEAAABI Gm2zLC8vH1FSUqJt9OMkk02SLJYrNUMzmq5xbLfXL5G6xJ5ferW9/lwo5zMf nns5W8dR6xxlK/X90Xm/5XKBzk0WWita+3jLZab2787Pz096tk4EzdpR8rmu t/ZRxP7tfjO9M89l1Xt/FT+f+/4r0ccIAAAAAMkiGfD4UN7X8b523+Ucuy+z 5sSpmhl1TmvN/lWtffW1//Mi7Qut/aJ1/L19DmCFngew58PX9exutdt873I7 E7udx7UPhD1XgUfbtLuiPburSd6+J0o+r4w2d/tOv1nY0eexgr6BUrvi5vO6 3HOScJgAAAAA0OOFzgVof2u5nqrrVun5AD0XoKXnArRvtt2G3NIXQPv76/kA uX6WXD/PHid9eVXruOlrtR26m/X7v1P26Sqp5dpfQbN5jPuu02PQNf70fIcc 2ylymSuXY7Zt25ZiWVaPWstL8vajHc3nOwrM0o4+j7XFs9hB3/bXLcv0qNcP AAAAAHoLbZPW/uB1dXVp9fX1ozXzS/6dYo/rn63z7ZeXly/Qdn+pC+X2Zdrm L5n4Grl+s2brBOb0G+0xBpO1X4KORdBxCPI8s+zzDRfoc+t4gxj9CzbY+6Xn Ii7UfdfH61wFRUVFo3Q9brdf83CSt6uj5PCKaPm82W9Wd/R5JHv/MG4+r/f+ IBnHCAAAAADoGqE5+zT/Si4+oaamZlpFRcUsuT5PMv45mqu1L7/ddr/WYVZf J7n6HF07rLS0dEik59W50PWcguZ5PZcgl3oe4UI7m6+RWh+tvV7uf51k/cvs uddPKysr89jj11PD51ZPJp2HTfL2/oh92AtMMGr/9gKzpkPPY5l+VtD3moN1 1c5K1rECAAAAALofzb+hOfjtefpa1tPTfG33wz9qHT27zfxCuf/J2pddzwk4 eJ5+2jdAHp9jzwmgjz1bMv/F2p/eXjNtQ5Tx77fY97nYHieg+X+yPdfA0ES8 Drs2mknRMrjUq4lqP7fqcuc6WFPtNfq2AwAAAADa07Zx7ZNuz6u3MlI/es3Q OrZes7Nm9s62e+v4fp1/Tvv22+P459n9+a/QdvZoffjtddFX2/ug/QTm6nkA zfC6//Ged4ffLIiRz/dF+91uv7m0I8dnNXi+4SCf///OvHYAAAAAgL4lLy+v v2ZoOz8vsXNz+zb29fbtS+w1zTO0DT0Rz68Z3s7des5gun3eYIlmeB03H6kv vT3P3Y32fXSfztTH6nkA3bfmoiGrY+TzFxI1f7vk81oH66qdmYjXCQAAAADQ 9+jcdvaadtrevTTS2PZAIKB95Vdq+7a2bSeqb3ok8TJ8+770r5Zc8ZuoGbxw 8HPRfren0Hic7pNVN2OSg3nbX9Ex6sl6XQAAAAAAfYuurab52J6bTturb4jU L10y+/X6e53XXcfAd9V8cPKcxweDwXSdQ0/nx39744x7o2XwNzeeXLSroN/h o35X2O/AC/WFHh1Tr2Pr4/UPsBp8n4mfzz3f74rjBwAAAAD0XbqeWllZ2YTy 8vLTdb72SOu+61ptUqt0bTedx13XmuuKfZO8/flo+fy9wlE/2llw3Lvtb3+3 aPyW9n36da760Hpy9hz2M/UcgBzzCCvoK4ibz7d4Tu+K4wUAAAAAIFxpaWm6 ZFhtg14UCASujrIO2zrtly6/P0PnmHcy31tH7Sw0d8cYf/7v7z5nCooe6mc9 9NUBbXO3F5prZd8ydf46ubwj1hp1weo/fUny+aE4+fxl+rYDAAAAALoD7Xde U1MzVudfl+uX2OuuReoXf7P+3p6nfVx+fv7AY3leydu3Rcvnf73f/NuE8Rl7 x4zJsWbmpoduD+ia6aHH63h3e+33s2Wfr26/v2/XfupRB2uef+/YX0EAAAAA AJJD12eXHD5F+4tL9l0RZY21DXKfa+X3i3UNd8nvo3QMvNPn2FFglkbL5y/9 2SwfNyZz95gxY6zx40ZbFQ/327vDb6ZH2s62bdtS7DXojti//XXn1zlYV+20 xL1qAAAAAAAkn2TeVB2frnPB2+O974q1xpuuy67z1UWbw21PkfFGXeO80MzP nZz2N83nWvPnpPws0jZ0nnh7jvoj9qO2yv+5ww3TD8TJ5y8m9xUDAAAAACD5 dO45ycYn6vpu0eaeszP7Wv293k/nqquurh5ZWlo6xHp54WDJ4nsjzg/3nBk7 Zcpw7ykzMvZrPs/Kynp56NChOWHPPcAegx5x7Pkbtfc85GDN8++4+foBAAAA AJAsOm+6rsXefq3zKLl9/TuFY+pCmbzy4X7WfZ89Xq/vtyzT0k9+yhQzIjU1 dW1mZuZDw4YN+7b9HJl2G33Ube+vv8AfN5/XTz/F3VcLAAAAAIDk0r7wOo+c 1KWSpW+LlqObNl7xm6anjDXbk2qNycm2vNMyNJ9vjbZdXTtt06ZNR/WrD6s7 qysLTpX8/V6cfN7Yla8HAAAAAADdgfZpl+yca88l1zYnfNWzn33rmUF7J56Y 1TLO/MTxWdZLf8l6pv3jtS+9Zv1Ybebah751zXPvWfH7tnu/5cbrAAAAAABA dyFZ/dQj2tBLrvz1/DlpVmguuHu/uuBZXTctdH8dsy7ZPGobvK77VltbOzF0 f6ve+58O1lU72Z2jBwAAAACg+7DngLczduXd1y7L3hHK58suPfc5nWsuGAym H3m/o9d309/L/Y5Yh13nZY+Tz19w67gBAAAAAOhO8vLy+gcCgWWhrJ33lU8/ MG5sziHN57m5ua9I7r471jjzzZs336Rz0bXfrrXFM93BmuffdOOYAQAAAADo jnSNNMngK0KZe/Xq1b8bP378Hs3ot9566y+ijDG/S+edsyyrf6RtWg2erzhY V21WVx8rAAAAAADdmT3v2ydrpT322GP3rFix4onFixf/PUI+X1lRUZERa3uS zzfFyedbuurYAAAAAADoSXQttlhrsNlzwJ2jfeJjbceqnz5e8vfh2Pnc842u Oi4AAAAAAHoKy7L6Sf6et2nTpvWx8rnk9zXa1h5zWw2eO+P2ba/LndFVxwYA AAAAQE8guXuo1OWxcnm7OeGWxtqe5PO/x8nnwa46NgAAAAAAeoJAIHBivD7t UTL63Ejbs6pnj5T8fTBmPq/35nXxYQIAAADoPYZKXST1FaknpF6Rsuz6UQe3 lSr1JakyqfekPrS391epz9jPBSRVqD+7rl0eZX72FZLdz4iWz+1+8DlHbbfB d3X8vu0zct04ZgAAAAC9wkLTlsfbV0fy+blSb8fYltaURO00EElxcXGK5Osr o2Xv6urq8yW/H6f31fngYswVd7P2jQ/fthX0/TZO23m9O0cNAAAAoJdYKLVD 6lmp70qtlnrTdCyfnym1337MC1K3SXmkxkhpX+HrpR6XOiGB+w0cQfL05M2b N6+NlrnLy8sXhN9f29klr18co5/7cr1Py30bpwySDL4nZj4P+r7mzpEDAAAA 6CWOi3Bbk3Gez7WN8SX7/kVSwxK2Z4ADfr9/gOTpRbHGlFdUVJwR6bHalh6n vX1+y/2Cvgvj9m2vPemkrj1yAAAAAH1Ak3Gez2+373vA0D6OLia5O2Pz5s3X xhhLfpdcxlzvrLGxcVCcbUyyGjw/itN2vq2rjhkAAABAn9JknOfzEvu+v0/m DgHtlZeXj5b8fGdYf/S7IuTra0pKSrLibcvv9w+Xx6+JnNEr1h1u8L4ep/28 uiuOGQAAAECf02Sc5fNBprXdXO97l9RkqZ9LvS510LSOY/+D1PnJ2lH0XTo2 vF3f9HXy87II48jPcrI9bYuXx9/e/vFNNffeG7dvO3PDAQAAAEiOJuMsn59k 2uZm/4bUnrCfD5oj526/L8Z2lkpV2VUp9UxY6bxy+XZp9v+JXT+Q+rZd/0/q C2G1TmqtXddKrbRrmdRiuxaZ1rnrQqXnFibZpe2taXaxJlw3VlpaOiQQCKwO y9O3Sh6/qV3GvlXb2p1sT7Y1RvvE11U9/YW6qr98Uau5btWz5HMAAAAALmky zvL56aYtf38stVtqjWmbI84r9eew+6yNsp1VpnWOuZfs594RVoeMiblmW1fW x+327V9h+11r2s4xFJu28wu69nt+WP23aTvHcK9pO8eQZ9rOL3zWtJ1f0FoZ VheatnMMOh956PzCLNN2fkErLawGRHndE+0yqT9KfUsqpaMPtl6eMNiqm5Fm BX3ZcjlJ1xK36nLnWls8p0stbpmjLehdaTV4Vsv1tZKJ11kNvi8cqp/55Q/q Ls5vrrvqmT11y0q09tUvqdpXt2Tzh/ULt35Yt3DbwYb5Lx9qmN0gWfqfUi/Z pX3Wd9jVHDeDxx5/XprwVxMAAAAAnOfz+ebI/HpthPtoNtxi/367VL9j2C/N /aHMmW3asuhUc2Rb+HmmLcNebtqyra7zFsq8d5gj29w1U4aysh53KEM/bNqy 9RPmyLb9qrDS+cFCWV3794cy/G7TdecPnNS+sH17O2yfX2x3PP6w43wy7DV4 NOy1eTDsNXvItJ6/aHme4UP7PyjZ+gzJrTdZ9Z5/lwx7r2Tph+XyaakiqYCd kd+V2n9M2bg7VND322h/tAAAAABwDJqMs3w+w7TlvldN9Oy9Jux+vsTsYq8w xLSdb9C14kPnG/Q1Cp1r0DbyxWGlYwFC5xtuMG3nG+42beca8kxbbta637Rl 6kdMW9Z+yrRlcG3zD8/nQdOW3d8wbZk+NN9AzFp8xjD3M3OXlu87Cfy7AAAA AICQJuMsn2eYtkz2jxj3mxd2v4sTsH9wz0DTdk4h/VTvcF/xIxN/VP3YpL2T xg1seY/79zfWb743rhtk5i6seu/N7r4tAAAAAHqpJuN8fbXXTcfy+UXHunPo Fga8WXDSIqu1j3pLRt1ZdpL1q2+PtQKPTXI7LzdbQd9ruia5XH9R6oWWnxu8 b1sNvh1SH8rPie1Tv8VzottvCAAAAIBeqck4z+c/N/HHlt9s2vJ5bgL2Dy4Y MWLE1PT09HtHZ40qmXBC9v7vfe6EwwnItvvt7PySXFbJZU1Lrg76/iXX37Oz 9sdyqc+12643WrN2y2P0vnVWg2eT1Tqmvdp+7I4uOx/A3HAAAAAAkqfJOM/n Z5u27H1dhN+Hzw/3YoL2D10sLS1t/ejRo3eOGTPGCtXFC3NiZdZ3WrJyg+cp uXxULn8t9Qu5/ZGWy5afvY9L/a31ft5XE96m7ThfT/+wpTr5+Pfq73qgqqrq BLffIwAAAAC9QrpUZljpXG+ap3/a7vZhUR7/e/v+Olf5TaZtzXCPOXJ9tauS svdIqtTU1LnZ2dn7wrP52DFZH3unjmoufHjCo1a99x7J25+XfP01yavfkuvf l8t8uz17tyuZO04dbpjx4UcNp7/+Uf1pbx8OztrX2e18WHfWi5s2VawPBALn uf0+AQAAAOgV3jLO1uZ6MMrjda3r4rD7HZY62O7nLyVv95FMGRkZ39ZMLhl9 d2Zm5i9PyB55Y+DxSVdKHv+mZNRnrWNdO7zL2slnHPi4Yd6rH9Wf/tqh4Cnv JqDd/Z0dtbdMtyyrv9vvEQAAAIBe41jzuTpO6napjaZ1HS7N5zomXdfLPi1Z O47kS09P//Po0en5v79/4gbJpU9KLu90e3OXt5PX+z461HDKi4ca5r5wqGF2 U+Kyvu8dqy53rtvvDQAAAACgb5AMesYvv3vCk1ZXzrd27Nn545Y543S+uXpv vdx2KMHP8bK1NXea2+8NAAAAAKB3sxqnDLKC3tslh251PWs7r0P2mmo6d/sL ScjkofqjVT99tNvvEQAAAACgd5NcfrKdb93K2Qek3pTaIlVstfanf0T2636r 3ptnNXg+bTX4bpTblklOXig/3yq3/4+dy5O5X1tlH1a6/f4AAAAAAHo/q/ak iVbi+7HvaMna9d5Cq3VO9x+2zPMe9K2VfL1csvYiqVlyfbzcNjzuPtZMGyvb ulnu+1urdX30ZGby92XfHra2eM62LNOvK94DAAAAAECf1T8lJWVNRkb6Y1de MPqdDubXvVaDZ1NL7q73/qcV9G6QPLtU8uyclhwd9A081p2z6makSXa/tGX7 rWPJk5nH5Xi8z0n9H9n3BVZ+y5yHAAAAAAAk1bBhw2ZmZGQ8n5OT07qm+dgc 6y8PToqWXV9qyeFB3xdb8nLdjEnJaFNubUf3XivP80CS5nY78piC3t9Z9Z67 5XlPsfwLByT6eAAAAAAAiGXEiBFTs7KyXtNcHqqcnGxr1cWjD7eMtW7w/Fry 8eckJ59rVc8emYx9sKrmDrUafGe2jin3Pir1ShKzuK7R/qQc0z2SxZfIcaUn 45gAAAAAAOiItLS0b32SzbOzdi08PbPgU9dnrbNqZw5LxvNpX/eWNup6zx1W 0PuzlvXPGrwfJTGPfyTPUSDZ/yu6Rhxt4wAAAACA7igzM/OpnJycj9PT038+ ePDgicl4Duuf0zIlH39esvKzUvuTPHZc63XJ5D+VWmFVTUpNxjEBAAAAAJBI aWlpT6Wmpq5NxrYty/S3c3lzkvP4wZY28qD3S3I5mznWAQAAAAA9zeDBgyck Y7vWyxMGSzZ/KomZvFHy+I+tLZ7LrW0npSTjGAAAAAAA6OkkP/88wXn8n5L3 /7tlTveaaWPdPj4AAAAAALqp41JSUm5OS0t75I6rs+89xiy+u2WsetD3zZZ1 1GtnZrl9cAAAAAAAdHfDhw9fmJGRURlaP33Bqdn7DtZ4nGbxQy3rm+t8bvWe W6wtnuk6bt3tYwIAAAAAoCeRbL4yOzt775Hrp+dY3/ns2Lcke79/VB4P+t5p GZde7/myFfSeZzVOGeH2MQAAAAAA0NNlZmYWhXL5qFGj3k5NTX1g8ODB58iv WtYZt6rmHm9tO2mMVT99plU3Y5LLuwsAAAAAQG80PCsra3d2dvYHI0eO/OGw YcOy3d4hAAAAAAD6oNGZmZnbhw4derHbOwIAAAAAQB82ZNiwYbPd3gkAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAABLtfwFLfqEE "], {{0, 717}, {1000, 0}}, {0, 255}, ColorFunction->RGBColor], BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True], Selectable->False], DefaultBaseStyle->"ImageGraphics", ImageSize->{333.33333333333417`, Automatic}, ImageSizeRaw->{1000, 717}, PlotRange->{{0, 1000}, {0, 717}}], Appearance->Image[CompressedData[" 1:eJztXQdcVFe+vmXuNHrvXXoRUGyABRsqCEoRCyB1yp0ZwC6iRGNioqBGY1zT jCbG2CswoIlpu77dzW7y3u7Gt8km7uZtNrHFNEWF4b5z7gUcLl0ZBsbz/Y78 hmG898w93/33878++SXziwkMw5aLwY/5eaunLFuWtzbNGvySoVmukGmKCmdp VhTJipaNyyfBm79v/QdfMwhDHmiZEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ EBAQEBAQEBAQEBAQEBAQEJ5wXLlyZf/+/UuXLp08ebKzszPWFby9vcFf5XJ5 ZWVlXV3d7du3jT1rhKGIxsbGS5cuAZIkJiZaW1t3yaVeAciWlZUFOIlohgDw 6aefAukkFosfjU7dITU1FXHsicXhw4fHjRs3sIziAQjANWvWfPfdd8b+rgiD AbDQW7Zs6c6CMhCAYLx69aqxvzqCoQAMKiBD+qL7APGARgMMBAZYd0cDFAV/ BaIPWGjAnu/1sOAD4ICD+HURBgnA6YuMjOxh6YERXlpaCqjyyOIFmG2AZkFB QT2cBfz18uXLA/rNEIwJIC56kCpA5gBGDeDpAI0Bx3rQuYDDyMIf7gBqqztb HZANmECABgY6NdC/wEnsTogB4p06dcpAp0YwNMDKdhmkAm8COTZocqMHmQm4 PThzQBhAAJXU5WoCIWY4SdUdwBmB2kXsMgF0ySuj+2jdSVHEruGCLnk1RFwz YPtlZWV1nl5qaiqwzYw9O4SeACRD54UDHtmQWrguJ5mYmDikJomgjy6XDAgx Y8+rCyB2DSMMI15xABPu7Dkiu2uo4dNPP+1SDxp7Xr2grq6uM7sGNn6L8Jjo nMQZLrd/Z3Y5OzujYokhgh07dgxTXnE4depUZ6PL2JNCYK5evcq768eNG2fs SfUb4F7gsWvv3r3GntSTDnCD668IoBmwu4w9qX4DOIbe3t68LzL4WQOEdgCL l3ezD2WXsGdcvnyZ912Go/g1Ddy+fZtXuBIUFDSs40Kd8wioOsIoKC0t5S1E D0WhwwLgvuCVACHBNfgAq8Cz3uVyubEnNQDoHKAbjqbjsAYv4AA0o8nUbfLK b4ZXIGW4A4gsnpUFmGbsSQ0YeGEuIJxRBHXQwHMMwcUf1tZ7Z/BuHLQVaNDA UxlDP1fYX3RW9yZ27wxNAJuKZ8Cb3u5RoAF537Gurs7YkzJ98LRhZGSksWdk EACH17Ql8xAEL902fMPvPePSpUv6XxMFuAYBvJ0LQ6Hi3RAAet+0XZWhhitX rvDsW2PPyIDgFaEN91zDEAcv5pOammrsGRkQPHPLlGJ3QxBbtmzRv9pr1qwx 9owMCF61v2nfR0YHbxOfaRcG8LQ/MDKNPSNTBq87h8kXy/F8FpTxMRx4pZjG no7Bwcs7oCoIwwHrCGNPx+DgUQs5iYbDk2Z78OLDpm1bGhG8KCJQjsaekcHB oxbwGft7hCdBtj8+rl69iqjVr/+OeNVHIGo9gtRC6CMQtYw9I5MF1hHGno7B wQsRo04jhgMvhGjs6RgcvL1jKK5lOPBCpiYfneYVyZvMrqUhCF6HB9Mu621s bNT/sk9CHM+I4O2YNu06E952V1Mt1R4i4NWZmMaO6e7A29eD9roaFE/UjcyL PKCOWwZF51YPprdTrB08nwW5h4YGrxjAVO9lXh0guKGMPSPTB88CMdW2n7xe W6b6NYcUeJlEU91FxaunRSmewQHvspueTuysDVGwdHCwZs0a0/YTeeE7pA0H DZ27bZhS+aVpf7uhj9TUVP2LHx0dbewZDRh4BvyTUDs0pNC552d4eLixJzUA AFYWT2SZdjJrCAJoDYIg9JdgwoQJxp7UAIAXtUNN2wYfPEOXJMldu3YZe1KP C+Dq8kQxElmDjM6GrgksAfhSvEJH0/N8hz54eVvT0Bqdn0mNkoaDjM4GvAmI rM7PrUMdJgcfvLAD8M2Hu8i6evUqr1DZNOTw8EJnkTXcw4mAV7ziGRP4UsMR PJE13A3dLnmFWrQNPkxMZN2+fbvzI7MB00x+m9IQhCmJrO54ZcJFs0MWpiSy gFxCvBo6MBmRBe4IXmgUY/cYIl4ZBaYhsoAS5AV723mFoqPGggmIrMuXL/OC V4hXRsfAiqzGxsYtW7Z8x2IAJ9nzGXllse0ICgpCvDIiBlZkcRuCCIKwtbU1 tHkDjl9aWtrZsuIAlCOqeDci6urqBlBkXbp0SSQS6R8N8NYQD5AC0+bdEfoA mtG0G6EMC/Cc9EcWWYBUvCo7fQDHH4iXx9dNQEzt3buXt+GIh8TERBQUNTo6 1wM8QuP0nknVmWNZWVlAafZdlIHjA+MNyKgurXR9AM2IthMOEfBEVn+Ta0AK 9Z1UXQKwBRwBkK2yI8A74H1ey76eSQUseSSshgg6i6y+KyzwyR5MHYzdoxEY GPiIhOsPgHIEkgpVyAwpPJrI6pVUQNq0a1XwAsgfXi30QAEcGT33ZAjiEUTW lStX+k4qfQCRcvjw4QHhGFCgYA7A9EJZmyGLfokssI5dJlB6JVVnAAIDFw8c re92FJiqXC4HWs/kn6BnAui7yOqVVGDdHycOdvv2bcBJINP0bXjgP15qAzKi hhf6IrIMTSoE00OvIgu48KWlpT3YRYhUCF2iB5HVK6m8vb3Ro0YQukR3Iqsv pEKBboTuAExi3vYWILKAIQ0sZ0QqhMcBr/8tR63uKlIwNohkeq0mTQ8t/cSA TwCIrF7Tu/qkAjxEjj9CX9BZZCFSmQCam5uvX79xvW+4xo5mnW4AJ9AXkQU0 IyLVMALHkA8/+jh6VExoWER4RET4Q0Tojfb3IkIjRoZHRl989z2GVaPth3oc LdmzyAKkApY8qvUdsgBLD6ST/jtPb352xsxZqfPSRseM7aOR046oqNHgP6am zp+TlEyrNL/8+it3THCK/nKsB5GFSDXEoWPBvf7HV1+p1CUqtUahVLm6ebQv IkEKSAFF4iSJEwSGExiG6432Xwkc5z6pTwCpmUVObl5JadkXX3zZ+Yy9okuR hUg1jPDRxx+/+NKe/IKC9uXDMRywBJAJkgbDBBhmQ1m6Sx38LVyj7H0nuYYn eERNco2IdQwZax8QaesTZO3uLrWTEIJWNuKAiAJKQBFt7+Tm5u7Zs+fDjz5q P2lfCMYTWWKxuLS0FBVkDgtc/q/fa+sbEqZPw9hNUiQgkwDH2O7FQEA5UNIg K9d4x5A0rzhN2LzKmOztscVvJq7Uzn/m3cyt2nmbz8zZcCRx7YFpy16aqNwc vagoYEaiS1S0ra+fuaOdQPKQZgIg8+BBJ02erNXWX778X+0T6FlFIlINU7z3 3vv+AUGkQCgUiaA6YyUUgRO2lEWg1DXBIVwZMuvlqeo/Ltx5Q3HkJ/WZX+gz jYoz9xVn76vO31Odb6TPgXFfef4efe6O6swvqtM/0Ce+KHj9/NyNO8YXFgQk TLD195TaW5FiCsMpoC1xQigUCgQiX7+A8zW1n39+5e5d6NP1wC5EquEFbikv XLzo5x9AkBQrnyCpSIIwF4hCzdzlYXNOJK//36WvfFd46GfZsfvK0zpNDaNu YFT1LexgVFq9Ad5vaFZrdRoto65jlDWN8rM3i098Kzv030v2vDKtNN0n3kds a0UIKYJk5SFOUSInZ1dXN89XX3vd2BcDYYBx8eK7QcH+GAm1IEkIhDghxahw C/fSyLknU9Z/nv/qz/QZyCVNPaPWtqjqdHqjhRt022B/1f8T5Ju6ntFcBC9u yo7/OfvlN2avyg2eHiBxEsEm7jjBMhlwzMnFZc9Le5i+2V0IQxNQUrHCaveL e9LSM7mQAkHgAgIXYViklefKUWnnkp76e+7rjarTLUBGAc4oHzKH6Tha9EbX f6Lrmmmtjq4Doux+mfaW6uT/LNl7alY5HTLbV2hLAilJkQL2gRQeXp4v7N71 cJIIwwrtS7bv5Ve9vH3bQwoERjpgZineMS9PLb2a9wYUNfQFRqEFpGrWF1D9 HBzBdOpa+JrWtgCOAaUJ5VjtX/Je3RybP9o+iPUWMFIA/Ud3T48X9+zhTRVh 6KN9sd44cNDNzRNGEighhhMijAi2dNeEJH+YWXWHPgf5oKjR0bWMoqFF1aAD So2uYToJpb6PFnVNiwqwS8so61toMLQt8hpdad01+bHXpy6f7RFjR0IXkqQg u4BmfO31/bwJIwxlcMsEdOE7R484OjkR7ANrYCSTEsY5B1fFFlwtOnhPU6cD uk9ZC/UXZz4p2wY9oEMJTlTbrDr/s/K4NuO5dO9J1qQUUh1qRtzOweGNgwfu 3r3L9FhrYewritABhw6/bedoD+x1EtjPJGmJm83zHFeXse06fZqB7t5Fhn53 EEcDo9TeUZ39eOHuLJ94c1yEsx4qmJ6tvd2HH31o7KuF0Du4e3z/gTccnZ1g xJLAMQFYRDLBI+rt1LVfK966SZ+4qTj+PX38mur4dfDTAOM6OLLqhN44foM+ ektx5CZ99BvFoYPJq2Pdw2CeSADD/iKJ+NiJ4/fv37/1ww8//vhT53H79o93 7twx9nV90sG587/Z94qbhztrtMMEIA6IhRFuUvsJLsEzPMIT3cITXaOmu4+a 4R7VPqa7R053e9ThrjfcIme4tw79z8xwj5jhNpJ9PyrGJdTBzI7CcBiQIAkB JQgND4ubGD8hNm5CbDxvxMVPihkzbtHibEAwBplkxkC7TbJv3z4vLy9ozICF IwCxgNhqjSgNKbCzAqzv09S8vf3+85//MIhag472C75//35un4KAhGEkmG5m FxHjVlFvITlLp33tYMbnkQBMOXYIwIC/ER0OixNs2L/DWWDslJ0axiXB8R5P LWAjFUHBod99/z2DqDW4aL/aBw++6ebmhrX6g7ilyCbSwd+CkoIV5CLhYJns HG2Cwn2Dw/3MrKSWthYjgt1DI319/N0oSoC3A+vb6EbgmFuIA8N9/MO8Le3M MVJgZWfjF+wRHOXnG+gpFAs4LnE/8HbCd4O274IFBoV+9x2ilhFw927jm28e cnB0xNicIFgSM0I6z2fSrhklXhJHdjXhokvNpGMnjlyzSbHuGZVXoHPomCB6 Tc6Gak1hyULwp4eiBufWv6c159ZdJBLZ2ds6Otk6OFnbO1pJpELwpn+wx7pn 6RUbC0JHjcAoLHx0GL0yp7JarViRbWFj1nZo7jw9kauVhOzM/UYE/IdNVSNq DRo4u/39Dz60s3fESQooGyAXpDiV4B5Zm7r5k6V7pzmOdBfbWFMSyDdz4ejY 0OUbi1ZvVoRE+kRPDJetzV67TVFUlmnvYSO2FInEVKtl1hOlcK4EEKy4u7fb wqKUgpLMXFV6jmJeUNgI8OaIYI/VTyuWPVUYFRsktRdHT4yUr8pdt1WpWLnY 2ctOYi6ixASroEkoTTuq687sMjc3t7axGz8h7vr1Gwyi1iCCo9bxEycpSgyN HIoUYoJJTuFHEtf8pDjeqDj9t9yXP8rfnewfC5aJEuLe/q6pixIX5CXnyjOy lemZRcnpebMWFMxeopqXo8qMGh8mNRd3L7Pa7Tbo3YGPBYf7r35GUb5VseY5 RcVWRcyEcPCmi4dD2pLZmXlzFhQk5yjTs5UZWcUpGXmzs/KT8uj0AjrDL9CD PUUv1CLYbGNaWtonf/rz51f+19hX+skCV9leU1MXFh5JUSIKxymMHGsT+FrC 8h8UJ3SqWobWMuqLzPIGWdgc1m7BxVKhg7Ods5d9Lp0OxNfkWePsXC1DY/yW bS7csF2TnDXN0dWhW2q1qrKH1AqNHAEYVVElK6+Sr6+Wj44LAW+KpSJ7Z1vP Ec4FZVlAD5ZtWJqQPN7B1To40rtsQ37ldnXEKNiOGFjo3VKrzbYHH5PL5ca+ zE8cOF6dPXc+MiqaM5GEOB5l47Vnsur7oqM6jVanqmmByUHtnbLzeQEJkFqw tBimV4DWTF+auPrZ4nFxUeB9R0/bkg0FFVvpjOyZ7p6O7dTqxLFWUwyApOC6 B4Z7rtsqW1ctWwOppeCoxRaDYWIzaqkmc8N25fKNeXHTxoB37F0tVGtz1lUp w6IC+FKrKwpzvmFxcTGDym8GEZzJUVOrjY6KAddfKCBEGB5o5rw9rvDbwsNN JRdgxrmt0OVeSd1biWtH2fm3hR0IUkIsLpq3crNyQkKUmRUVGOW7arNi485l gG++gW5ic4qgSKytwOohrVrNsFZr39rZas7ChPJtyrXVinVVRZXVdNT4AI58 nJ9YWLbw6V0ryzYUxieONbeR+od7rdgk37SrNGZiKDiFxEyKPTz+Q3a1We+t IYvc3DxjX+wnBe1WbMOFi2HhIzG2ikCAET5Sp/XRmV/JDrZo6ptpvVoXuo6R 1TetaHh7Tvlcj7FxrqESoDbFeOzMsUuU6ckLEybNjklMS8hYmpRZkJSRPydx /qTY6TEjQnxhZTsbgtJbfZaZAtzD29UnxD1p4dTKHaXrqhVrq+TrqovXVykT 02N9QlxcvRwAZ8Qi0bTk+KzCFGDnpyyZMXn2mJlpk9JykxbkpyTOi50ya3xw RAAbXOvSpIOiLzJq1MRJU3bseMGYl/vJwwcffjTCP4gL+wAp5CN0Wh6W/lXB gWZYS1zHwLKWhzVUD9QNLbS2UXn2l+Xnahc+4y60AYtHCbDRE8MVaxet20YX li2xsDMjJFhazpzyrSXlWzWZS1MpIWsL4foKCypToZjMzp+3fpt67XPF66qA NiwGChG8qKhWrnkOvFCk5c4mhSRwVQViEhNiIycEy1dnr6uiZSsXWztZYCSW mjVl087lczKnsYnzrqlFCcWHDh1u7s8WM4THx3vvXfIbEYAD8QH3NGC2lHmR f+KVnNebgICiL8AaPFg09bD+U6eubVLXgcGUvXd5QbWzyJaLH0RPCFeuW1i5 my5cvlhqYQbemp+dtP6F0vU7VFkFKQIRoJaA25bRFnQAxg8JqJVbnLxxl2pt VRFkFBRZgFHyciC+qmWVL9IZhbMJEcsZGIrHwscEK9dmb9ilUq7NsbS3AO+k Zk3e8pvlyYsSOttZ7TEvASU6/M5RBllZgwLOvqrTNgQGBVHsihMEbiYQZQdM /mTJ7gdcXV/Hmk99gjUD66v04u8W7PCnHIWYmMCJqNhIxarc9dtKCzSLzc3N weHmL05aX6UC9vyCvGQKyByMbKUWp6TgT0JoTi6Rz63cqSrfBhmlP9ZuK67c pcgsmENKWNazWZ6RMWHKFUs2VKkUK5ZY2ZmD4yRnTX3mhZWpmQmsPdVBWLU7 hiKx9B1ErUEBx6szZ85x9hXnQUkxQdaI+A8WPX9ffbqZqxzuqo69nWmMuv5G 4ZGzSRv2Jq2MsvcztzYbEewVMtLPx9+doiAVXL1cgyJ9gyP9PHxdoLZqTfe1 KSkKWFkuSRlTl2/Kq4Cmu7zzWL9DWbIhb0Fe0tz0qbasjLKxs/YL8gDH9A30 oEQwa+Ps4RQW5e/mYfdQHXZMHllZWT29+Rm0UXpw0NTUBH5u3VbFpgJhmleC Ced7jL0479n7mtOM4pyuo7DqvoK9nim78NOKmrk+Hbqgs4ljsuM7rQnidmqJ xILImOCVm2SVO5SdRVbbUFZUKTbvLluzudjFw7bdYdQ7C96esOZlottFlpOz 85df/oNpC7AgGA6cUvjDH/44e3YSFxMQEtQUl4iauZWN9Gm404FmR4/UYv+k fQBeKGpv0qdnuEVjfUYrtSSiyLHBJevz1m9X9ECtdduKgQFW9lT+iCAPWNeD Q1ezj1U9HLUsLS1Xrmp9NBLK7Bgan/3lfyZPmYKxLiFQXcGW7gdnrfxRdoJR afu4B4djXRPcv1P7s+rk+qiFU5zDWosA3SNnuo0EYwb7c6ZbJBzukYnukQnu Uc5SB07OiM1Eo+PCyirz12/vXmpVy8pZb3H504VR40KEEooTes5Su6luUVM9 Rs10i0rkjs8OrpJwBqwVjAqw9CQwknNKCZI6cvQYg2wtA+PK//49Nj4O56qw MMxVZFMRlfmv/ANwIyrdwVbvlV2MUstAn/HcLfWJ7/WrjpWn2HGSHexr+tRN +tTX8oNpvnGsQMEk5uKxkyKWPVVQ0RO1itupFT7aXyCC+o/CyQU+cV/L37ip PHFNeeI6e/C2s7AFz2BoTm6KX2qOScCXBDwWCsXIQzQcOF1w/caNCbHx0Eph ww3gssfbh/x5yUv3Ndomdf82CcLwqZJ9oQCv6ztsi2A32ncc4AMNN4qPZvhA apE4JjETj5nIUqu6J2qtq5IBsVa2KT8o0kcAXVlMSgoLAmb8ojzBKC/yz8Wd Xfkuo7l0NrEi2tpXQML8DiUUHz9xkkHUMgy4q/qvb77x9PLB2EJ3sEyuUuvy 6AU/FJ/QlbzbBHsv9HcXaq1OpW1RNDSpLuj0tnTpOo1mdp/XTcWxRb7x0Nwi SLEUKMRQViHSQDT1oBDBB5ZtKvANdQeegQDDbYVm6vCUW6rjLWoYA9E/S+vZ lbVAs3+WtWtp4FRLXAgjaJTo6NHjDKKWwfDPf/0rLSPdwsoSLi7bUGisQ0BN yqY7ypNgLVqUsMXHI2121rKDt0FVv1uIltsEfUd9VhY8m4T+Ii4UUSFRI9QV Oet2yrulFjDjq4qB1Cp9qtgzwJ1N5RBuYtvVozJ/pMGcG1rY5GbbWdpVOXzz puzY1vg8S1hxBrxg4Zix42u19Qyy5A2AL//x5cLFi7iiO7C0QCcJMCLNe8LX RQd0yrOsV9hvanXXw6GbD2sbNefXjFpgIzQHmpggcHc/R7o8G1KrBw+xlVoy dz9XNtxKeEkcNsQs/Ik+1U6tLk4Hvk5p/Ynk9b4iezbcCgn2zJbnGCS4DICj x49xworb8AUWyZ6wWBU+/xfVaUZZwxrw9f1SiP0dgFr31DVbYwu9pQ5cGYSt i6Vs1eJ1O3oMPlQVV1QrVBX5Ll6O3E3hK3V6fnzuL/TpFnWDrntqMZqGTzJ3 p3qNF8MmOtBh2fUibAqBolsDjo2bNkElyDUMZVc21Mpr32T1XdV5YJBDk8nw 1Lqvrt2XUBJu7clFOS3tpEs16WvZfHS31ALm1jZZXukCB2cbNmCKh1h7vDhJ /mv31GK4Nibqhm+Xvl0xNtuGMuO6pRYUFX/L7hFDGFhIzczwtnJ0nFWLszyi Pkp7Hq6O+qGlZFBqNalrzsxaH+cUwsU8za0kGXlJa7Z0xys5dA+rZaueLUpd kmhra8UFQuMcQ04kVd5VnQFuaQvsW8JX4m15KO0d2cm3pq9wEtlyETxwT6lK NMZeBxMEppe7xWD3IKwgZNq3skMwhtBGLcPxihsP6JoP52+b7RnDUUtqIZ45 f+LyTfnd5RABtTZsl5c9lTdh+mgzcwn3v+Z5jfss5zdNMIFeDzsjdUMteMto 6i5mPucjccbatokVFBUaex1MEG3ldyy1CFyKkeWjFzSW1DL0wFOom6Ftpuv+ umjvYv/J3K4tsblw4qyYkg05gFrl3QQfKncq6fIcnzBPAQWTnUKMVAXNgu6h sqZJXdes7iJg0laboWVKGz7J3j3aegRsKs4mfYrYAmaEgQWnDMnWpg24M2Xx fGxBc2nDIFKrTqes/77oMB2exJVtiaRUdHwwXb4I5nq6MrfKq4o3bFcWLltg 7WqFselmJ6H182Nzm+EdUdOshlEsRo9OfGppGv6W85tZ7qPFsGU9S62iImOv gwkCrIyQEJiLpAIC9prxENnujJfrSusZmr80hhicaQ2oBcytp8YsMWOze6SQ 9AhwLSxbVLlTBSsAudFBainWPle4IG+2mRVs0UZhRLRtwDtTV7ORq97sQyWg 1oWvCvYXhyRaC6Vc1CW/ECnEgQeGk+ak2MXcVkjCALU7S62WQaQWu9z1TGn9 3qkab7EDJ0akVqIF+SkV1XT5NjmPWkBFAkVZuiFnSmIMkG8ctVK9Y3+btr2l L5IWnEvd8J/iQ09PyHGVWnPFODIF2iw28JCSEn9zZ38LZzEpaqfWoEmt1kFr W0q07857NtE9WsjmAwRCImF2bOlT+euqaLY2vkiPWsCGp+XLF4ZH+wuFMOYJ 9PiyiPnfFxxuV+LdTZthz8WoGn6QHXttaukIM3vOu5ybPPfrq/809lKYGvyt 3NKD48MtPESkBGiHwacWqxPrdeq6f+e/sTo6DUyChO3fieAI37zSzPXbNeU8 am2TVW5X5SrTnD3sBGxETowJt40rgDGrPsxZB1NL9XcVp2tTN4dZuGCtm0rw lNT5d9iOlAgDhXiX0G1TFFFW3hQJ28i4i2x2TCzWlWkHVSHSDYyi/p7m/KtT y5wwCxwXAK/C2lo6f0ni+uqStVUdYqeAWhVVyvTc2RILinVqqSAz1wPTlwMl 3qLs0+nAV3ugPPNB5tYIK9h6juumGz9x8k8//cygZOLAIT9w6rlFz4+z9acI 2C3LXWy7fVKxrlTL9LZMAzlowIp6wI0L6c9PdAoTEtDqA6Jk3MSRqvI8Nq3T wUNctrFgalIsUJqAEkJcOMd99MX5W4BK7dXWekgt+syHC7ZFWLPUYjdQJ0yd /vPPvzCIWgOHlyYU/T7npUl2wULYOBK3Jc02js+9X1LLtk3upVx5wAQXTIJr GbX2q7w3KkZn2eESGIQgCEcn65SF0yuqNeXbHsZON+yg8zSZARG+bPkPfJTG 8ojUr3JeY9R1/aYWK7UEFPQFxk+IQ9QaWFxO2/p59sspnmOksOU79LaUYcnX ZUcBtQZHZLHUqmHru+oa6TO1KZVR5m7swxGBgsZGxYUt21S8FlJLxmnDtVvl s9ImSyyFsD0gLnAWWr06vfQefYaha/pyLl0btd7PeJ6jFoCfn9/2HS+g4oeB xa3iY9/kHwT2s6PIgq0gxpI8R/8hvbpZcb7z/W7YQdcxJQ3/WLpfEZxoK+Qe S0c4eTql5M5cta1o3fbiimpgZSkUqxdFjgli/0hKSGqaa9THmTuZkouMsrZz mLTz0LFZy7vyU+eSK4MtXLj4f3ExCj4MPO5r6u4UnzicuMrL3Im7hSNsPPdP 1txVnYcZXrqujxvEBkB2sYv+s+LkkZSKMHN3mHsiBBiJ+UV4Fq3MKt8KeCWr 2KpMypri6GINo18E6UhZPhub938Fh7garb6cgqPWbdmx/dOXjzB35PZ6FBXK jL0OJohmWJ2u/duS34yxCYL930ncSiApC0u5pTkLM3GDRa2HgktVfzX/TVXA HCfKks1BERILUUx8ROmGwvXb6GUb8iPHhbAbrDEKF4y3HPF+5ladBgZCW1Q1 PU/yIbXU9d/LjjwXV+whteOa1RQjahkALXL4DLjvCw4V+M6wI81hHhHD5nmO /SL/4D26ZtCk1kPBRV9oktd8vHDHdOdwCuZ94BMF7B2tk7OmrdxYmJE709nT gd21iDkKLVeEz/tnwRsMbMfUZ2oB9moavi58UxMBbAArjK0GLC5C1Bp46OgG 4JrdUhzbFaf0N3eGXj+GRduNOJlc8avypE6t1dH923bxuOyC9dJ1v9AnX51c Fm4Dd4LAXjYU7unvml04P3p8sEDC9ojAsGArD23qM/flZ/t1fJ2yHhhmV/Je y/SZJKXEXF2rrBhRa+DRDLej1t1Tnv54wc4JDsHs5mLcTmgtC0m8KjvA0LU6 5WCEIPQEC9DCtc30ua9lb62KzHAR2nBtJwUiMiDEl2sVAvSkJSla5Dvx64KD QLv1SyrqlFDLX06virHyA26ogJVaObk5xl4HE0STur4ZqqHaa8VHsr0TpBgF uz1gRICV26uzl/0qO86oOdN30KQWa3Epau9pav6Q+UKuz2QJzCjirc+vhvEu yLRIK89DU5f9Ij/B1Sv2dbCBr1tFR/ZNVDgKLbhN+mHhYW8eesvY62CCAGZ8 Eyyc096lz+2bUhZp7U2yuzCkAmqma9TvM3Y00ed0vTlfAySvWrfHsqEnbZOq /oGm7viMNaNsvUVsB0u2pw20uykMy/AefzVvv64PsSz947coaxlN/SfZLy32 myihKK6iZlt1FYMipQZA+8UHiu+a7PiKyHQb2LgKCglXgWX5qIX/zDnIBrph 3ekghCD0TwGM828KDj03LtdVaEFyHdhYMnhbOj4/ofCu8jz7MPT+zAp8i5L6 0ymVARausGEcu1msqno7gzaLGQJt1xwoiwca7aWMrfN8xpPQNcMEhCBI4nF4 xto79Bm4KEotTPYNXowLFsA8KKn9ZPGugsBpFpSUfcIANOCTfMb8dvELzUr2 GcH9O7L2+8LDT4/NtsLFONzzKCAFwhde2M0gahkA+ldep6pvVJ59PaEs2MJT BNvDA8+fmuU66lTqxh9KT+no84MZ42rf73yPPls39+lYq0AJLgQqzEFg+dSY RXCbpKKBofuzkQ2GHbQfZ1Sn+E4QwZJa2POhYn3ljRs3jL0Ipgl9QQEdf/rC l/kHVo3OtCHNYGshEreipIkeMe8kr/2JPtqsPqdfdm7gTWTsM6Zh69SGa8XH 9sYrvWHwHEtwCT+X+hSs+VFegNU4fT+mEmrDVxJK3MT2JNtCTiiSnDx1mkEi yzDoQC0gJZQ190trP8rYOdd1lAjazhhQjmaEcKpL6IGpmmvFh4FHCVPJ0LCv MagEe3hk1q37uuCN/PBEZ8JqVVTGN0WHm6CC5hpB9036AdWpqPm/orc0I+fi sM+TgCtdPnDgTQZRyzDouI41cDO+uvam7Pg7s9fGuoRTbH9jCicAzcZY+O6M l39RcBA+PEUBN1Z3DkoMuChr9xzvKs9os7bSAUnHZ1Q0lTVwBQx8EvZ4hCZN zdmkp6Y4hxM4ReCEuUQ8M3H2p5/9N4PcQ8OATy0asotR1/6gOPZO0vpZzqOs CQkFGwYBDUIEiF02jc3+86Jdd+SndOqG9nCl4ZQjo8eNO+pzn2Xt/SbnTXDe 9oRgz9Rq/xOjrL2lOVU+eqG9wELAOoYONja///0fGCSyDIYuqAWDRTWM6vwv spPvpT0/3zfOSiDhnqIkwAhnoUWGX9w7c9Z/VfD23eLTbETiYTtK+GtHY+zx KdfGohpGUfNAWfNAP1fYW5X1wz8paj7L3pvsPYHNHOGkgAwJDf7rX//GIJFl MPDkw0MysKnDn9WnPl6wfWngFDvSXICTJPtcXiuBWajUK8d3+uHE8m9kb99T nIV5RmUD7LSgrG9RcgGB2rbxuOzSJxJvy2pfDC2W9toHirOvT18WYufFFQ75 Bwb89ne/M/a1N3F0q4YgW2qBrLijOvVZ9kuroxf4Ug7wUdME+wwBjLCmzCNs vXOCph2ZueZm8RGdWtusYgdM09QDpunohmZVF209Hkct9p1UHf67WntDfkQW MNOSEHORscjoKLTJwtDonlqs/wUcdli92fBF7v6dE4qnukWb4WLu4agCtkbC khCNsQ8oDk6sjpOdTKr8fMm+u6rTzPKGllJgiV1oAQRja+zbBxebbaE7kKSP PHk06QdbwynPfpC5NZ5NvpMUyUkt9CxgQ6O3RYQR+GbYc7L+x+Lj5+c+szIy c4pTpDVpzuV2BWwTdrgVSOIQ7xK+NHDGpnG5B2auuJj+3Bc5r/6qOMWUXmDK LjKlF+GLEjAaGE09a4drdfTj0qb3Afvt1N+SHds+Lt/XzJErV3b39Ni0+enG xkZjX3sTR1/lA5tD1KnrriuPnUvaSIelxDgEWwu4Ehe2Yg8DfhdBYYQZJvSX usxyH708PHXPROXxOetqUje9N/+532VU/ylr91+X7Psyd/83eW/dLjrepKlt BkNtwPgYW/hX/13hobzAGTZCM4pNQc5Nmdf63ZHIMiR60D6dDPtartzlPn3u O/rI+bmbCgNmRFt4O4ktJFxfQY5mOCbECSFGinGhGS6xJSWeYtsIa8945+AU j3FArJVFplWMWbwnoeRPC3ffA2Ktz9ULj0Qt2GHyasHBmc6jBDBjCA2tlNT5 xr7qTwT6uEZ6blo998SBRsXpb4veqpv/zPKoedPdIwOkzi4CS2tSIsJJ6EYS rU9aggYZgQkIXESQYoHQTCC2EZg5CK3sBZaL3GM/zX7pvrqXwuNHG23lypBa fy/YP9aGfbCjgGSpNc/YV/2JQH8Xi3tCAWyaralrUdfdUZ75d8Fbn+e8Aoyr vVNU8uBZsZYBboS1DSYxx0QSXAgfA4xTGBhQW3LdQzGuUCrY3O21hGW/yk73 r5yvv1JLXf/X3FdGWvqx3bxJJLUGDY+1cBzHgE1e0tCkOXdDcfQvua+8m7bt 0MzVT8dkZ/tPTXCNHGXr52/u6kBZizDYVoaCNj9bsoNh4y19zydtvCs/+6h9 6ftGLU3D5/mvRVix1GIjD+22FoJB0V8t8zDzoqcl4QoqzzGqGqa0jllW/0Bz /ruCQ3/O2n0h5ZlTSRVvzlixb2rJ9njZpnFL1ozKVEek5AfNVIUm7k9Q/7vo UDNtEIWoT62rhW/O9RgvJoFOhpROnpuKDPhBwMCtI1sLAWxyZQ37dB6gMbVM CezJxpTVA761lGmB/f9j8Ylv897+++LX/pW3/676dAs0tAxZHc0GH64VvVMe lekkteUU8fy0DGNf9ScDnZzBRxvc0xLbRBnLlrYH5cDeRAr2aVAKLaOsB46A DhYew5070D1kzXgDjRY2FP+T7MT+hJIR1m5clmd0zNj3P/iwuRllpQ0LHXxU 0+CMOm40t74epPMCdt1Tnns/Y9t4+wDoJLK7w0aNGnWdLS5FmtGAgJWlJj2U MFrytfzQXI+xsN8g+7i6iIiIa9evM4hahsQD1XnTHvdV5+9p6v5dclQWNsee sBDgUGqNHDny2rVrDKKWIfHiREXPY3ePvz7+5w085HAC8ertE2VzfMfawE1n BEet27dvM4hahkSwpXtQ2wi0dOtyBPXhM4/zeUOPEAuXAAsnJ6mVmKS4R1zZ 29uvWrXq5s1bDGKXwQCf8d028G5GXz7zOJ838GAjDjiXBYA/2WINzMrKGhUw GxTGXvfBGHoPuII/OGo5OTn/8ZM/MYhaBgOXRW7NJXcDrOPoFf39vGGBtT3g qm0qHLUcHR3/+MdPGEQthCcV4C4w9hQeBf8PGlDSYw== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{2018, 9, 13, 13, 53, 6.8032932`8.585294160850474}, "Instant", "Gregorian", -4.]]]], BaseStyle->"Output"], Image[CompressedData[" 1:eJzs3Qd8FEX7B/BJTyCEhN6lCoh0BcQCKCBNQTDgq4gCAorSBBGBwNEEKYJI tQFJaKETSKGF3osICBb8Y0EFlI70zP+Z21xyCbnNZm/vZpP7fT+f500kV+Zy e3nvd/PsTLlu/dr39GaMDQyk/2nf9cMm77/f9aMOofQf4X0HvtOrb4+3WvYd 1KNXj/cbdPOhfzxEl/2bvvFlAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAOAmeag6UX1DdZzq BtVtqt+pllO1kTc0AAAAAAAAAI8QRHWNimdRK6kCJY0RAAAAAAAAILcLZkr+ Pks1maoFVfmUepFqH0vL6HMljREAAAAAAAAgtwugepPK18HPfag2MCWf36Uq 6J5hAQAAAAAAAEAGYk7dNof+rOSxAAAAAAAAAHiq+iwtnz8neSwAAAAAAAAA nmogU7L5faoikscCAAAAAAAA4InE+eZ/MyWfL5E8FgAAAAAAAABPJNaM28iU bH6eqoTc4QAAAAAAAAB4HG+qKKZk81tUTeQOBwAAAAAAAMDjiGy+gCnZ/DZV a7nDAQAAAAAAAPA4Yr/zaJY2b45sDgAAAAAAAOBe4nzzpSwtm7eSOxwAAAAA AAAAj+NHtZIp2fwmVQu5wwEAAAAAAADwOAFUa5mSzf+jai53OAAAAAAAAAAe R2TzOKZk8ztUnagKqVSgnGECAAAAAAAAmF6AE9d9lCnZXGu97dRIAQAAAAAA AHKfElTxVLFO3AbyOQAAAAAAAIB+Yv22s0zJzOLc8SC5wwEAAAAAAADwKGFU MUzJ5f9ShcsdDgAAAAAAAIDHaUx1hinZfD1VMZmDAQAAAAAAAPAwYv23z6iS qa5T9aTykjoiAAAAAAAAAM9Sm+o4U+bMD1BVlTscAAAAAAAAj/Mw1ftUy6hO UF2gukt1kWovlYWqiKzBgcv5MOU5vpNSH1L5yhwQAAAAAACAh5rMst7r6gpV M1kDBJepRLWHKc/xKap6cocDAAAAAADg0fpQfUXVleoJqgpUpZmS1cZS3WBK frtMVVjSGMFY4pzyfkx5bsW55uKcc+ybBgAAAAAAYG4dWNo8elfJYwHnlaCK Z8rz+QdDXwQAAAAAAEBOkZel5fN+kscCznmJ6jxTnssoqlC5wwEAAAAAAIBs aMrS8nlDyWMBfcKoYpjyHP5LFS53OAAAAAAAAJAFsf91IFUIU9Z1F/PlIs+J XDdP4rhAv8ZUZ5jyHK6nKiZzMAAAAAAAAKDJdfbg2u2HqLrLHBToIj5rEeu+ ifXfxPPakynrwgEAAAAAAID5ZZbPxT7oIufllTguyJ46VMeZ8vwdoKoqdzgA AAAAAACgk8ji1ahGMmXvc5HzDjOl9x3My4fKQnUnpT6k8pU5IAAAAAAAADBM TarbTMnoQyWPBRyrRLWHKc/TKabsXw8AAAAAAAC5y0qm5L6d2bzes0w5Dxpc R5xTLtbxu0F1n2oCVZDUEQEAAAAAAICrTGdKPj+TjeuI9d9Fj/Vpqg4uGBMw VoIqninPzR9UzeQOBwAAAAAAAFxsA1My4P5sXMePKWuGX2Bp65Q9ZfzQPNZL VOeZ8ruNogqVOxwAAAAAAABwgsjQwVlcpgVT9ugSOXCsjvsowJSe69sptxND VVbH7eQ4nHMfqrJUT1C9SNXz1KlTE5OSkhYvWbJk5+zZs0/MmDHj10mTJv0z bty4G6NHj743ePBgbl8DBw68/f7779/64IMPbkRERFyif7tcrVq1/8TNBwUF 3e3Wrdvh9evXLzh27NjIe/fuvUz38ThVEdmPHQAAAAAAALKlGNW/VDOo2lFV pipKVYbqOapZTOlRF9n8HFVBJ+5L3HZsym2JfCkyez4nbs9UKBMXpWp69+7d gUePHl0WExPz85QpU+707NmTv/DCC7xu3bq8TJkyvESJEtmqYsWK8QIFCvAi RYrwggULch8fH+u+d4GBgdaf2V9W3P5jjz3GX3zxRd67d+97FovlHOX/fTSW eSdPnuxB46tNhTX4AQAAAAAAzEfk84z7nWdWP1JVN+g+m1IdS7nds0zpgfcx 6LbdhnJuKNVLp0+fnrd06dI/hwwZwlu1asUrVaqU7Qyuls29vb3TPRdeXl48 NDRU1+2J7N65c+fkYcOG/T1nzpzNe/bsGZoy3+4n+dcJAAAAAADg6byZssa6 mMveTfUb1S2mzG+foVpD1ZUZvwa72JNb5HLb+dMHqZ42+D4MRzm24j///DN2 yZIlPw4dOjS5SZMmhmXxzErkcGaXzUVWL1y4sKH3UatWLd6lS5e7I0eOPLl0 6dJJ165de0TyrxkAAAAAAADcL4ylnZsuMqjofy8vdUQZUCYveOvWrfdiY2O/ 79OnD69YsaJLM7l9FSpUKF0+z5cvn8vvs3r16rxHjx7Xp06duvHgwYPt6PH7 Sn4KAAAAAAAAwH3EXmxi3TiRQ0VW/4wqROaAKJfWOXbs2PoRI0bcE3PM7srk mc2h+/v78+DgYF68eHG33rc4n/2VV165TVl9x4kTJzoiqwMAAAAAAHgMsSbd Uabk9D+Zm89Np/zpRfXCoUOHDr/77ru61nPLrfXQQw/xN9988868efNWX7ly pZK7nhMAAAAAAACQxnZuulgvXuT0Q1SNXH2nlMvr79y582iXLl14yZIlpedh M1e9evX40KFDT27evDnc1c8LAAAAAAAASBfKlHPTxXp1tnPTKxh9J2JftF9/ /XWt2AdNdu7NaSX6C956662LK1as6C96D4x+bgAAAAAAAMBURC+17dx0sRe7 ODc9v7M3KvLkvXv3ukdFRV0Ta6LJzro5uURO79q167mYmJjXnX1eAAAAAAAA wPTEPnDfMiWn/0PVj+k8N52yebHff/99e3h4uPRsm5tKnKPev3//3zZt2vSE gc87AAAAAAAAmI/Yr70L1d9MyenfU7XIzg1QNn96x44d52vXri09z+bWeuSR R/iwYcO2fffdd2EuOAYAAAAAAADAPIKpLFQ3Wdq56RWzutL9+/ffnTVr1j2s y+6eatas2a25c+e+4dpDAQAAAAAAAExAZPKM56aHZryQONf81q1bE8WeabIz q6eV+CykV69eB6dPny51P3sAAAAAAABwi8ZUR5iS0/9lyrnpYp82kc29r127 9kW3bt2kZ1VPrpYtW16LiopqKO8QAQAAAAAAADexnZv+F1Ny+kkfH5/W58+f n9+hQwfp+RRVgteuXfv+J5988rbcwwQAAAAAAADcJC+zOze9SJEi1pKdTVFK lS1bln/44Yfz5B4iAAAAAAAA4C7bt2//uEKFCmIenXt5efE8efLwYsWKSc+n KKXeeeednbKPEQAAAAAAML3xTOmPFvW35LGADpzzDhaLJVnkwEKFCnF/f3/r 8+nt7c3z588vPZuilOrWrdtu2ccKAAAAAACYVh2quwz5PMeibF5j6dKldzJm wdDQUO7j42N9Xn19fXmBAgWk51NUCd6lS5dNso8ZAAAAAAAwHbHe97dUyVR7 GPJ5jkPZPOjIkSM/lytXLtMsWLx4cZ4vXz5rv7u4eEBAAM5NN0G99dZbi2Qf OwAAAAAAYCrDmZLJ51BNZsjnOc7169enNG/ePMs8WLRoUR4UFGTrkcC56U5U tWrVeLNmzXh4eDjv0aMH79mzp7XEfnZt2rThderU4aVLl1a9DbFH+vvvv/+h 7OMnh8pD1YnqG6rjVDeoblP9TrWcqk0W13+Y6n2qZVQnqC4wpYfoItVepqy1 WMQF4wYAAAAAcOQRpryn/ZMqP0M+z3E4502GDx+enJ1smfHc9JCQEOscu+zM a8YqWbIkb9y4MR80aBBfunQpP378OL969SrX4tatW/zo0aN8yZIlfPDgwdbb yXj7FStWTO7SpUsT2cdRDhNEdY2lnY/jqFZSBTq4jckarn+FqpmrHgQAAAAA gB2xb7atn719yr8hn+cgoq999+7df5QqVUpX9gwLC0t3brr4b9l52AxVq1Yt 3rdvX75ixQp+4cIFTVlcq19++YVPmzaN161bN/X+GjRocCM8PDxY9vGUg4jf lThuzzLlb1YLqvIp9SLVPpaWsec6uI0+VF9RdaV6gqoCVWmqelRjmTIfL65/ maqwix4HAAAAAIDNAKa8/1xl92/I5znI7du3x4gea2eyqJg3F/Pn9uemFy5c WHpGdmeJ8/Y7derEZ82axU+cOMGTk5MNzeSZuXv3Lo+NjbX2wosxtG/fHmu6 axdA9SZT1s7IjA/VBqb8LRM96wV13EcHlpbxu+q4PgAAAACAVmKeScwPif7N knb/jnyeQ1DEqzh79uy7RmVUTzo3XfQbtG3bls+YMcPafy6yskzbt2/nTZo0 Se7UqdMHso+rXETMqduO52d1XD+v3fX7GTguAAAAAICMNjPlfWfvDP+OfJ5D /P777wmVK1c2PLuKufPceG76I488wnv16sUXLVrEz549KzWPZ0acq26xWM51 7ty5uOxjK5eoz9Ly9XM6rt/U7voNDRwXAAAAAIC9Hkx5z7mLyivDz5DPcwCK cw1Gjhzp0jyb089NF2ujt2vXjk+dOpUfOXKE37t3T3YE1+Tvv/+eI/v4yiUG MuVv2X2W9Trsol9erCMXwpR13cV8+b8p15/nwjECAAAAgGcTvexivSOxZvsj mfxcbz4X6yuJfY12Uok9nSdQvcuUPY5qUIXqHC9k4syZM1vLly/v8oyb085N f+KJJ/iHH37I4+LiNK+xbkLi5PeWso+xHE6cby7+honjdomGy19nD67dfoiq u6sGCAAAAABAFjPlveckpqyBnLE+S/n5Obt/89dwu42Y8n72PHO8V9FVpuxT vJ4pe60PpXqd6mmqslR+zj+83I+y2zPDhg1za+4V56aL89FZynNZvmwJ3r9n Iz6if0Pe9eWyvFWjwrxCOff3wIs9yMWe41FRUfzMmTOyc7WRRAN+AdnHWg4l 1ozbyJRjVfw9KqHhOpnlc7EPuvh7mNc1wwQAAAAAYHtZ1nv+ZiyLjvsJo6pL Fc6UXlExnx5DdZAp73sd3Zf42QmmvL8W+yJ9SNWFKeeCijXtfHSMJVc5ffr0 prJly7o1B5cpXYKP6PcYXz6jLq9TVTk3PTSY8QIhyvPWthHjd/b58nNbS/A9 Cx/iM4cX5T3Dw/gTdYrwkiWNG4c4h/zVV19NXdft/v37ugPw7du3zd7zvkD2 seZAWIYSe5KVtyvRl1PXrsR+ZU0zlFgbPdyuyhk0NrFnZBRT/pbcosruvvIi i1ejGsmUtTPF7RxmjvdQBwAAAABwhrvyeVaCmPJeXrxX75lyHyKPi1x+mil7 ImU2ljtUfzIl54u8L3K/yP/iPb7IAvldMFbToMxW6eOPP052Vy4X2XpIj2L8 +t4inB9k1rq3n/Hpg3x4YED658bS04//us4n9XK2ur0viP+4rgyPnlSVv96+ kjXra7nvmjVr8g4dOvAxY8bwtWvXGjo/Pnv2bOta9eKcenHbjoh13S9evJha Yl2506dPp6vjx4/zgwcPptaOHTv4xo0bU0vcfkxMTGotWLCAz507N12J/dAn TJiQWmJtAdGn/8QTT4i9D8UxLuZx52aoSKa8BmwVy5TXj63EuSYH7Up87nU6 Q4nX0kW7usmy//fBiOphwMtDZPMFKbcnzt9p7eTt1Uy5HXF7Q528LQAAAAAA Pcy0PpzaHLzIFY7e64uMIbJHrpuDv3r16lzR0+2ObF69ajG+NyokNWf/vt6H j+oZzDs+G8qHdw/mdav6pPu993rJn/frmI+/0iyUfzE0D7+xw+uBrC4q+XAI v3qkGf9572C+Ke5r6x7gttq1axc/efIkv379umFZPKMrV66krnsnSnwvzuUX VaRIEWtmt5V9T38OLJEt7bO3WO8sYz4/wtJn+B0sfcaPZ+k/AxCV8XOCKUx5 bdpqFFNec7YaxJTP4OyrE0s/f15ew+GvRrymo1navLmz2dxmZcpt7jTo9gAA AAAAssNM+TwroudUbQ5ezLXrmYM35Vp2FC0LzJ8//7Y7snntR4vyX+MCrXla 5OyxvYJ5z7YhfNVkP35yOeM/rGB840zGK5Vh3NeH8fZNWOq/f7fEi381NIB3 bh7Kl4wN5MkHHszo6epYec5/6cz5+Zmc3zjI+X3XZXPh8uXL6fK5WJu+bt26 1nrmmWd406ZNU6t169Y8PDw8tTp16mQ9392+Bg0aZJ3rttWoUaPSzYVPmTLl gfly+/l0UfHx8enm3MUcvG0+ftOmTdtonLVY+h5yUWINNPs+cy3rRORG4nzz pSwtm7cy8Lanp9zuGQNvEwAAAABAq5yUz7Uwag7ewpTPAGxz8L5ufAxWFC37 PPvssy7P5g+VKc6PLs1rzc6n1/ryzs+H8nkjAqzZOzt1YpkXH9E9mA/unI9f dzCXnnnRZX9oxPntX12W0T/99NPU/valS5e67H4M9LK7j7ccQqwpaZvjFq/Z Fgbf/oaU295v8O0CAAAAAGiR2/J5Vuzn4EUPvOjH1TIHL0r0DLttDn779u2n 3TF3vmaa0tN+JtaHd3o2lG+e5ZuauU8tZzzSEsA7NA7htSoW4DXKK1WrUgHe 7pkQvoB+djImfU4X2f6tF/PzW3s0ZPTDwZyfm8Z58h2XB94csD6cvX+oihp9 TOVwYs/ytUx5Lf5H1Twb1xW5PjiLy4isn5xy+2P1DBAAAAAAAAyX1Ry87T28 y+bgKZvV+uCDD1yezd/uVMiaky9v9eadngvlidPTsvmqSX78iWph/KFi+Xig n98DjzfA19f6s8erhPGlH/uny+jTBwXxD7vkU8/mP7Xi/NZPsnNwlu7evslv XP2XX7rwOz//+w/83O+nUuvCnz/zqxf/4rf+u8bv3zc8+69x+kjOPUQ2j2Np 56uI89kLqVTG9deLMeV8/BlU7agqU4nPP8pQPUc1i6V9Nif2mizo0kcDAAAA AABGUZuDF2tm32Da5uA/S7mubQ4+zHYH165dm1q1alWXZvOajxTjN/cqfe1j 3w7mXwwNTM3XU/oF8iqlw7ivj4+jx5F2PjddRlz2k/eC0mX0vh3z8c2z/B/M 5SeqcX51i9FZVodkytVXrbn7zzPH+OnjO/j3B+L4ke3L+P6NC/iO2Bl8y7JJ fNPSCUrFfMI322rZRLuaxLcsFzWZb187g+9N+JofSlrMv9u1ip88mMB//m4b /7/vd/PffjrIz/7yHT//xw/8n79+sd6vyP0i/6to69pDOcd4lGVvrby3M1y/ mMbr/UhV3bUPBQAAAAAA3Mw2B/8CU+bQszUHX61atbtiLfF8+fLx0NBQXrBg QV60aFFD8/nBZVWtefmnVb781Wahqeu9RY3y55VLhXFvL68Hxucnsni5crz6 ww/zsnQb3t7e1n/3ostWLhnK5w5JO29951c+1rXf7+xN6XM/HMT5n6M4v6+a Rw135/Z//PI/f/Czp7/lPxzZTPk7hu9cN5vy9gS+YfG41Nq45GO7Gk+ZfHxa Nk/J55tU87mS0W2VtGJKSn2q1MpP+daVU5VaJWoa35ZSO0SuT/yGH966hB/f t86a6f/4+Qg/98cP54/sWVXWrUeuOTmbz8VebM8y5XW4m+o3pqwtJ/rkz1CJ XoWuTJmnBwAAAAAAz+JwDp4y+RmxxjhzkD1EJvbz87Oud5Y3b14eEhJiXfes cOHCmjP80Hdrps5nf/JesDWTi0x9dLEXr1mhYKbz5j50vzUol+/bvZvfu3uX L46K4lUpq9v//NFyBfmhKK/UjP7RG8F8+xcpc+i/vefSHH7v3h3K4WetufbU wUR+YFOUNRMnLhyt1KIx1tqwaKxSi8dqyOcPZvTM8rn9HPqD+XyKw3yemtFX f2ZX0/n2Nbb6nO/bMP97dx+cAAAAAAAAwNi///47txzl3mLFilkzd4ECBaxz 6MHBwdZM7u/vn26/sIwl5rLFzwMCAnhmc/D16lTk9w4Xtmbme/sZb/dMGD+2 VMnUk/sG8eIFgjO93eDAQD7OYkmXiVs0aWKdU7ddpmhoXj6qZ57UfL5ykh8f 3jVYyecn6xuSw+/fu8uv/Es5/PS31n70/ZsWUB6ewuOjLDwhWtSotLJlc7t8 nprRF6fP6BnzuaM59Ad73LXn89SMvirDHHqGfJ6W0T+31pFtywZJORgBAAAA AAA8FMVP7yVLllzUMgdevHhxa94WuVvkbzGPLvK4yOVi/t0rk/50W4WFMF63 KuOtnvTij1bw54M6M/7ZQMbrVc3H/RzM3Qf5+/PXwsNTc7JYD73uI4/wILq/ 0oXz8urlQnmDamF85gdpPe7fL2P8Jcr/qWu1Z1NycjK/fuUCP/vLUWsW35Pw lTVLx0eNzKRs+dySLp8naMzn6TO643yutcf9gXyeRY975nPoSj7fFffFtZ/2 xoVIOiwBAAAAAAA8DkXSem+99ZYh55fb8nuhQoWs/e9iHv3FFjV4i4aMP1Ke 8bxB2Tqf11oPlynDX+3QgU/8+GP+fKNneI2KD1H+zs/H987D10315Vvn+vC9 87zTrRPX7ukw6zy9NaMn31LN4tcunbPOix/fu9Z6TrbI1plncY353H4OPWM+ 19PjrpLPXdnjrsyhx6yWc1QCAAAAAAB4nqtXr35SqVIll6zXPn50P86/K5Vu LfUVEwN4305BfPZHjA/vznjBkCDVfO7v68tLFwrllUqG8cqlQ3mVMvkfrFKF 0uXzzi3y80tJ3sp93rtoS+P8v2uXrGuZ/3Q0iR/cEm3NudqzeOb5XF+Pu+N8 bqYe9+1rZ9z7bkdMXYmHJwAAAAAAgMeIjY39xRXZfGTEIM5PNnhgr7M93/jx 4d2CU7N07YoFMl23XWt5UVUvVzBdPm/fKIzf2yfuz4sf2PSNNYuK3OxcFs9q Dn2US3vc1fdZ09jjnjGfZ9HjLmr/xvk/c868ZBybAAAAAAAAnoJzXnLEiBGG Z/OIYQM4/6HRg/uQp+yt9l54vtQs/XqLfDxvYIDufC7OUQ9vEpIun7d9Sjn/ /Prugi7K5ObpcVffZ835HnfR8//tjmUDZRyfAAAAAAAAnoLyeffGjRsbms0n jHyN8+NVMs3mom7v8bLOb9v2Pl/xiR+vVDJUdz6vUCI/XzTGPzWbb5jhywe8 ks96X79ueNwt+dzoHnfVfdYM6XF3nM8zm0PfHffl1YOxc/PIOEYBAAAAAAA8 wbFjx9YZlcsrlC/Nv41/mfNDAQ6zua0iugXz1ZP9UjP1C0/m5yF5ArOdzYOD Anjzx0PTzZ1//G5eHv+ZMob9K7u4IZ+bpcddJZ9r7nHPPJ+LOfTD25Z+Leco BQAAAAAAyP0WLlx41tlcXu6h4nz0e0X4zf2Fsszl/EhBJTfP9+P9O6X1uB+I 9OaPVy7A8wT4a87mgX5+vE6lAunWbv9usRfv9Gwov7bdi9/YHUY5eYSb87nR Pe769llLn9Ed77OWnR73Xevn3Nq7aVFRWccqAAAAAABAbsU5zz9p0qS7enN5 +bLF+ch38vN/k7KeLxd188jjPGnpUH5xR2nrf/cJD+Gxn/qmZus933jzp2qE 8RKFglXXixN7rBcrkJc3rBbGd37lk27ufPy7efjicUHW2/8utq2bsnn2etx1 n4NuP4euc581rT3uGfO5LaMfSlocK/OYBQAAAAAAyI2uXLkyrWHDhtnO5aVL leADuoTyPxN9NOVyUfcPBPJtS/pas2xi9DD+d1IV/n9rffj/moXy/ZFp898n Yrz4hHeDeK2KBXjFkiE8X1Cgdf03UcGBgbxCiRBeo3wBPvbtIH58qVe6bL56 ih/v3ia/dd32f7aVd2M2V8/nWnvc9e+zprHHXW2fNY097lR3D22MrCr72AUA AAAAMDGxblNLquFUK6l+ZWnzjTMkjgtMinPebMiQIcnZzeadXyjIT67w1ZzL bXVyffN0eTYhKoKf3Vyd753nx99olZ8fjk6ftb9fxvi6T3356F55+HsvB/Pe HYL5qB55+FrK4CdjWLrL2taEe6VpKP9nkze/tTeYb140yM353EGPu1o+N0mP u/o+a9Mz5nN+KGnhHtnHLwAAAACAiTVmjs/TRT6HdCibh61YseJidnL5YzWK 8oSZgdnO5aIu7yxJefzB88DFueG/bazLt8z2550oWyfO8H0gd2upr4cH8Nea h/IzsT787v4AvntZDwnZ3HN63HesmXF//5bo52QfxwAAAAAAJtWY6iLVJqqJ VK9Q/cWQzyETlM/fatKkiaZcXqZ0CW55J4Tf2OmtK5uLurC1AmXT4Q5z7f9t eMK6J/obLfPz0T3zput3VysxZ/7ey/n4kC75rOvB3dvvz/cu7yYpm2cvn5uy x13DPmupc+hbok/IPo4BAAAAAEzKJ5N/O8OQzz2OxWLxDg8P92ncuLFvz549 /eh7/5YtWwbQfwfS90F169bN//fff0/Tks1bNSrET67UN2eesX7bVEc12x5f 14bf2efL46YF8NdbhvL+r+TjXw0P4Btn+lrXZxf97zu/9uHrp/nyz94P4j1f DOHvdgjhx5YovfaXdpTk25e+JzGb6+xxV91nzfked9V91jT3uD+Yz6mSj+1e /ZLs4x0AAAAAIIc4w5DPcz2Rx0X+fvHFF/NR/s7frl270NatW4c9//zzBV56 6aWCL7zwQiH6eWH6vkilSpX65suX759HH3305mOPPeZw3faHKxTn62aX58kH vAzJ5rbas6K7arbdtrSPNceLHvU/4nz44rFBfFSPYN6vUz7+TvsQPui1fPzj d4J54ucB/Mo2ZT7/9t48/FRcM+v57PKzuYN8bnSPu0o+1zqHrneftQznof8o +/gHAAAAAMghzjDk81xJZPLmzZvnpTxemHJ5iTZt2pSkDF6qbdu2pSmPl2nV qtVDlNPL0vfl3nzzzepvvPHGjHLlyl2nq3Jvb2/u6+tr3aOsbNmyvEKFCqm5 vEqVKjx6Rji/e7iYobk8rc+9oqaMmxg9nO9b8QY/HtvG2vv+15Zq1vXYL+8o wa/sLG49n/2PzTX5kTUv8w3Rw0yQyY3ocXecz7X3uOs9B11fj7uo73atbSv7 9QAAAAAAkAOcYcjnuYroT6c8XpSqImXwh+lrZcrgVVq3bl2Vsvkj9H01+v7R Tp061RwzZkyfiIiI7fXr17/vlbKXeJ48eXjRokV54cKFeXBwsDWjixL//vDD Ffl/3zX+1hW53L5se6zl7nJun7X0Gd1xPjekx111n7Use9z5waRFp2S/LgAA AAAAcoAzDPk8xxPnkItMLnI4ZfJa9H1t+r4O5fC69PXxNm3a1KNsXp++b9C3 b9+OU6ZMiZo6deoFuiz38/Oz5nIxZx4UFMQDAwO5j49P6tr+4nsxf/7888/z 9957j8+cMf3M+nkvLLmyq2hi8kH/m67I5z8lNDZBfnZXPncwh657nzVtPe7q +6wZ2+O+I3Zm8nd7VrWU/DIBAAAAADC7Mwz5PKfySjl3vBrl8Sfp61OUx5+m 75+h7xtRJm9M3zeh75/t0KFDK4vFMn769OkHZ86cmdy+fXvrfDjLZK898e91 69blHTt25EOHDuWzZ8/mc+fOTa1Zs2Zdony/4/3337e0b9fq9VXTKwy/vLPA Bn7Y/5ZR+fzqzqImyM+uz+dG97ir7rMmucf90JaFWMsdAAAAAEDdGYZ8nqOE h4cHp/SsN6I8/jx934K+b0l5vBV935q+p2/bvEDfvzhw4MDBlKUTKWPfsOXr Ro0apcvjYr68evXqXGT2wYMHi/ydLo/TdW9++umn31K+X9yzZ8+RdNs96KZ7 0v30ou/fpu/foa/vvv6/lv3jvqgy6da3tX5IPujndEbfsnigCTK0u+bQXdvj rr7PmhE97lnnczGH/u2uVc0lv3wAAAAAAMzsDHMun1ejKmzYaCBTYh80saZb y5Ytn2zbtu1L9H0HysQvUzYOp+870ved6PtX6Pv/de/evd+ECRPWUs7+xz5n 22rAgAG8Tp061vnx4cOHPzA/PmfOnJuTJ08+TD9b3LVr11F0u/3odvtTDaD7 eV/Efvp+EH3/AX0/mL7/8Lnnnvukfv36y2vXqnF0aL//3U5a8j6/tL2UU/lc rOsmPz+7K5+bscfd8T5rWnvcM+Rzfihp8THZryUAAAAAABM7w/Tn8wCqZJY2 F3uRSvSwbqSaS2Wh6knVlCk5PsTp0XoYcU65yOQid1O9Tv/9Bn19k7JxV/q+ G33fneqt9u3b9x42bNg3U6dO/Z4ydnJmuVyl7tH1fhwxYkTc22+//Tnl/2F0 m0OphtH9DKf7iaDvR9D3I+l7C30/qnnz5p82bNhwVa1atQ5XqFDhbIkSJQ7V rFZxQ9Tng+/ZsudPCY2cyuenE580QX52fT53a4+7zn3W0s+h6zwHPfU89BVN Zb+uAAAAAABM6gzTn8+DmZLBv6RaTyXmxv5lmZzTnFL3qM5S7aVaSfUZ1WCq zlTPUFWkCtT7QHILsUd5u3bt6tHXzrb+ccrEvUUPOX3/Hn3fxzan3bNnz8kT JkzYM2vWrP+ykceTP/vss7OjR4/e2bdv36gOHTpMoNsbQ7c3ju7jY/o6nmoC ff8J/ftE+n4S5fG5Tz755MYaNWocL1OmzJ9FixbdHBISEuHn5/c4DTnvmGHv JSUu/jjZPnseXt3JqXx+fmslE+Rnd86h6+tx17/P2kTnz0HPfo87P7R10Xey X2MAAAAAACZ1hrnm/PMwqrpULzBlDt3ClDl1Mbcu5tivMsc5/ibVaaqdVDFM yfEfUoVTPUVVnsrH4PFKJ/Yjp2or+sgz9o9TDaHvPxLz2h07dhwXERGROH36 9PNaM/mMGTOufPzxx98OGDBg7SuvvDKLbmsK3danVFPpfqbR18+optP3n9PX mTSOL5s0abKubt26eytWrPgL5fHvKY/PpGG2oMprG3Pv3r3aJyyffVOZB06f O5OW9Hcqn9/cG2KC7OzOfG7Rls81z6Hr22dNa4+7+j5rjnvcd8TOSj62Z1Vj aS80AAAAAADzOsPkrQ8nMrzoexf9rl2YksFFho+lOkj1J3Oc4W399AdTLj83 5fpdWFo/fbD7Hoo+Yl80MVcu5sTt+8epRqfMaY+1zWvTZeePGzfuyOzZs29n lcfpMncnTZr060cffbS7W7duy9q2bTuHbkfUXLrdL+jrl1Rf0e1+TV+/oa+R zz333Lo6depseuihh04VKFDgx9DQ0HklS5bs0rx589IxMTH+GcceEMAqb4tb eGPnulnWPJhZ9ryzP8ipjJ4YPcwE+dn1+Vxrj7vuc9DN0uNuzecz+eGtS4/I eL0BAAAAAJhMAapCdvUbU7LuVxn+Pa+jG3Az0e8u5svFvLmYPxcZXMyni3l1 Mb8u5tlF37xahredEx9JNYEp8/liXl/M74e576GkEWuwt27duqk4r1v0j1NN zmxOu1OnTl8OHTp01/Tp0y9lkcfvUR4/S3n8IOXxWMrjkXR9UVF0u9H0dSHV IrrdxfR1CVVMs2bNNtSrV29bxYoVTxYpUuTXokWLrq1du/bw/v37P7tmzZrK q1atKpuQkFCcqkBiYmLepKQk38wey6VLl8rGxsa+HbMkesXq5ZFnNsVG3dqV MP+eyH//bCvvVD7ftrSPCfKzvHyeW3vcd67DHDoAAAAAAPmbqc9J22qOrAHq IOZ2S7D0/fQih4s8LnK5yPB3mPZ+enHdfix9P723EQN9/vnni1M2fpUys8jf os98dsY5bTGf3adPn43jx4//P8rd9x2dQ/7pp5/+O2LEiO/ffvvtre3atVtB t7GMrrucagXVKqrVlMfX0Ne1VLF030kNGzbcWqVKleOUxf8sWbLk1qeffnoW Zfoe69evb7Fu3bomVA2p6lI9Spm7ElUZyupFKauHxsTEBFkslsx+D15UVai6 lChR/KsB73b9bfHXE65vXfVZ8q8bH3cqn+9b8YYJ8rN7Mnq2etxV91kzS4+7 43wu6mDSQpyHDgAAAACeLjfmc63s++ntz4m39dNfZo5/H7eZ0m8vLmd/Tryt n15keD9Hd1yxYsXGVatW/bply5YLHc1rv/rqq7GUt09+/vnnma71Rnn8UkRE xE+9e/fe//LLL2+g662niqOKp9tKoK+JVBvotjbS102Ux3c1aNBgR6VKlX4s XLjwnw8//PCOjh07Rk+dOnXk2rVre1N1pxzemSqc6kWq5ymPN6Z6gjJ57dWr Vz8SFxdXgaoUVWGqEKqAlN9hl4CAgM+bNm16ZMI4y58bYhee37954X8i/9nn zv/b8IRT+fzo2pdMkJ0l5XMT9rjr3Wctsx53637o25ZgP3QAAAAAAMiMmBsu TiXWJG9L1YdqPFPm4ZOofqD6j6nPw/9MtZ0qmmpinjx5RhQrVizBy8vLug8d ZdrrzZs3X2+b16ZcHdurV68948aNOztnzpx0c+UzZ868O378+PMDBw784fXX X99Ll0+i2kq1ja63nb7uoNpJt7WLvu5u0aLF0WeeeWZ/jRo1TpYqVeoC5fGT HTp02DZp0qQFlL0nUY2liqD8PZiqn+hJp+pK9Spl9Q5UbSiXN1u/fv0zVPWp akVERNSvVq1aj9DQ0Mm+vr7x9DiO+fj4rNu4PuaH/Zui7onMp5Y7Tyc+5VQ+ PxXXzATZ2T35XN8+a0b0uOs9B32qw3yudQ79wKbI7936CgcAAAAAgNxGzCHb +ulFD7zohRc98fbnxN9lKbnd39//FrPL8TVr1jwWHh6+86OPPjozffr023Z5 /N7YsWP/6d+//+n//e9/hylz76PaT3WA8vhB+nqI6jB9f4S+ftuqVaujTz31 1I5HH330WPHixS9UrVr1R8rxRymPb6WcvYJy90Kqb6hmU02j+oRqNOXwYVSD KKv3oepJ9QbVK0uWLAnv1KnTB9WrV58RFhYW6+fnd4wy+S7K45+nPM4Stl8A 59zn6tVzDX/+btv8I9uW/iFyXma586d4J/dAT3jKBNlZ4hy67h53x/lca4/7 A/ncBT3u1v3Qd658zZ0vXgAAAAAA8Ax169b1o/z8WosWLTY2atTocL169U4U KVIk3Z7wvXr1uizOK6dKnjBhwtVBgwb9+cYbb/xImftYSh2nOkH1PdVJqlNU P7Zp0+ZkkyZNNlO+31G6dOmzJUuW/Jsy+h8RERFnli9f/i1l7z1UW6kSqdZS LaOKpuz9FdVMqk/pv8dTWag+mjdv3lDK8zNq1669IjQ0dJ+/v//PAQEB8ZTJ I2icz1KFaH3c5879VOHEvnVzdq6bfcF+r7Uf4551Kp//tvExE+Rmifncfg5d 9z5r4zXlc0k97mIO/TcXvRwBAAAAAMBDUYYuk3Ju+VH7nN2yZcsfqlSpcr1s 2bL3O3bseOejjz662L1797Pt2rX7hX5+mkp8/T+qM1S/Uv1GGf93yuO/P//8 84fq169/oFKlSn9SJr9Eefz68OHDby9duvQyZey/qX6l+pHqGNVBql1UW9au XRtPeXw11VL670iqLz/55JPo8PDw9Q8//PD2PHny/ER5/Iifn98sGvorVA8Z 9XvYETu95q71c1ZRXrwl+tOdyed/bqlmgtzsvnyur8fdcT7PCT3uO2Nn8RP7 4wYadfwBAAAAAIBH86I83Tklj6fL2q+99tpfH3zwwZU+ffpcomx+jv7tL6q/ qcT356kuUP1D9S/VpRYtWpxq0KDB4YoVK54rU6bMxbZt214bM2YMX7ZsGaeM bau7VNep/qX6kzL4/9HXU1RHqfZT7ViwYMG2d9555zDd1rFChQr9HBwcfIpq hbe399tMWd8t073SjBQ715Ln7NZ6a53J5xe2VTBBbpYxh65vnzWtPe7q+6xp 7HE3YJ81W+1N/PpS0jxLoKuPSQAAAAAAyL1atmwZ0qZNm+hMsvZFkbepLlNd obpKdZ3qBtV/VDepblHdpkx+rl69er+XLl36MuXpfwYMGHB/3rx59nk8s7pN dZXqAtUfs2fP/q13795/NGzY8DTl8T/y5cv3Y0hIyAIa4utUFWT9fihjv6ol h1/cwviWOYz/lZj+3y9tL2WCzCwjn8vpcde7z5rWHndH+VzMoX+3c2Vu3DMi t2rDtO0D8qak8QEAAACAh3nxxRdri/PC7bM21R2qu1T3qO5TJVPxjEWZ/GLN mjWvVK5c+XL37t1vf/nll1nl8dRatGgRj4iI4HT/V0uVKnUuf/78vxcoUGB9 QEDAIKasWefyuXGt+CHWIqts/kcc48ULKe/n8+Vh/PDCtJ9d2VnMBJnZvfnc 6B531X3WDOlxd5zPs9Pjvmv9nJs7N3xdIsuDCswA+RwAAAAATIMydoOU+fEH srejat269a169er99/jjj18Vc+QLFy7MMouvXbuWT506lb/11lv36tevf45y +L9hYWGnQkJCZohhMLs11c2I72Plssrnn/RJ/57+nZfTfnZ9dyETZGZZc+gy e9xV8rmLetxFRj+UtChB8iEL2tjy+XWqQioVIGuAAAAAAOAZKGs/ldKvriWT 36VMfrtJkybXxZz38uXLVfP44sWLrXPj4eHhNypVqnQhf/78fxcuXDghb968 g5kyN+4n+/FnB+fMi3L2FUfZ/NhSxsuVSJ/PJ/ZN+/l/u0NNkJdl5XOje9z1 7bOmtcddfZ81bT3u9PXurvg5T0g+bCFr9vkcAAAAAECKNm3a1Mwqm4tM/vjj j9985plnrgwbNkw1k8+fP58PGTKEt2zZ8nKpUqXOh4aG/l6wYMHVfn5+Peju HqHylv2YncUPsbiMufzOXsY/fINxXx/G/f0Yb1qP8cerMf5eR8Zv7U673K29 wSbIy+7P51p73HWfg24/h65znzWtPe6q+6xl6HEXtXfD1yfE5zqyj1tQhXwO AAAAAFJR9s6Tshd5Zpn83lNPPXWX8vttsd76mjVrHsjiq1at4pMnT+Zdu3a9 XqtWrbNibjwkJORAYGDgeLr5llRhsh+jK1DOfsM+m/+wkvF61ZS58hqVGD+6 2HHv+939ASbIy+bJ51p73PXvs6axx11tnzUne9x3rpuVfGhzdA/Zxy2oypjP /amC5Q0HAAAAADwN5fDxtjzeqlWrW08//fT1unXrXg8PD785bdq0B/rUx40b x7t163a7QYMGF4oWLXpBzI0XKlRonZ+fX2+6uepUPrIfkzvw3awAZe0byQcY nzaQ8aAAxr29lfnzm7vVz02/v9/HBHlZTkZ/oMddLZ/niB53zfmc70n46mJi 5KS8so9dcMiWz+9R/cjSzk/5jyqJ6g3mIX/fAAAAAMD9KFPXe+qpp36tUqXK zbCwsGT6mvzaa6/xd999l3fq1Ol6o0aNLtC//V2wYMF/8uXLJ+oM5fFV3t7e /enqT1J5dNY4uojNbN5AeQ9fuijjm2Zp3wM9IXqECfKyeebQc12Pe8Z8npLR D2yOjpR93IJDWtZv304VKmuAGeSn+ohqD9U/VLeofqWKpxpAlUfe0AAAAAAg u4KCghoGBwdbROXJk2c4/VNPu2pP1ZCqLMN6xZnp7OXFLtNX3rM941e2ac/m ojYsHGqCvGzefG7KHned+6zZz6FT3dmd+EVD2QcvZOppqi+pWlOVZ8rfPZHF mzIl89oyerysAdp5luocU/8soaK00QEAAAAAuEcBqhimvP+9YOnBFmUnl9tq 08LBJsjLcjJ6tnrcVfdZc77HXXWfNRf0uKf0uX/PuSXHr5HogeaytOzbROI4 RO/SzZRxiD58sa5BVabsSyn2w3idajlVGVkDBAAAAABwg1ZUfzHlffEaqiI8 iflS3j6U3Xy+ZfFAE2Rlk+Rzo3vcVfK51jn0jPncyB73netm8/2bFoyWeyiD DvlYWi6eImkMomf9NEvrtffoc4wAAAAAwCOJ98Bi7iyZ6ipVF/sfUt6uQnUT +VxbPtfX4+44n2vvcdd7DrrRPe6zRd1IWjW1rIRjGZyznynZeIWk+++Vcv+3 GebHAQAAAMDzPEb1PVPeE29lyvn4D+CHWH/k8+zOoevbZy19Rtd7DrrGHnfV fdb097iLjL53wzdJ7juMwSCHmPK3YLmk+9/F5H4+AAAAAAAggx/VBKq7TFkX uR+V6jnD/AD7Rns+f98EOVl2Pncwh657nzVtPe7q+6w53+Oums/t5tB3xc66 v3/DvDddfyiDQQoyZd5a5OOJEu4/wO7+36WqQDWP6izVHaace7OKqpmEsQEA AAAAuEplqn1MeR98mOpRLVfiSSyQsvdBLfk8aYln53Oje9xV91kzpMfdcT7X OoeeMZ+L2r1+7vm4aEuIKw9m0MSXKkjl52Lf8yUsbX24J90xqAwq292/WL/g mt1/37H7XtRUCeMDAAAAADCSmB//kOo/qntUFqbMo2vGj7BKlL9/yzKfLx5g gpxshjl0mT3uKvlcc4+77n3WlDl0qgNbopcYfyhDNhWiukA1naot1cNURZky R/0KS/u8TmZveQO7MYi/T2ItjK4sbY24R6jW2V2mp4QxAgAAAAAYoRTVBqa8 r/2J6gm9N8R3swL8ENuIfK4ln5uxx93xPmuG9LhnyOe71s26e3hL9HNGHcig i8jnanuJ20r0j+eRNMaGGcbyWiaXEX0AtvUyfqfyctvoAAAAAACMIfYLvsyU 97RinfZ8zt4gj2E+lMMnOMrn25b0/VF+Rpabz93a465znzWtPe6q+6xl0eMu Mvru+C/PxsZaZOU+UHJtZ6a8/o8w5Vxu0TN+nSl7jEdSNZU2OkV1lpbNf2OO s3dXu8tVc8/QAAAAAACcJtZ7imHK+1ixxlILo++AH2KvUR7/J2M+P7DizaHy M7Lscq7HXf8+axp73NX2WTO4x33X+jl8/6bIaKOPP8hVxN8rW+7eoHK5+naX a+WGcQEAAAAAOKs1U+bIxHvYlVSFXXVH/AgL5QfYXMrlybZ8fmFnicqUTy86 m3HHDHqND+zZji+fO8QEeVtvPrdoy+ea59AnuLTHXX2fNb097ta59Lu7E79o 46rjEHIF8TlidvJ5S3cMSsV1pn6+gH3tlDRGAAAAAJBHrKUkeliTqS5Shbvr jvkh9jxl8yPWjH6ElY2PHvmZM/n2tZcapb63LVOyMF87b7gJMnf28rnWHnfd 56CbpcddZZ81+zn0XXFzz2I9d1Ah9lPL6tzybiwt81Zx07gcyU4+nyVpjAAA AAAgh9gT6TRT3gtuoSrj7gFwzrwpp3fmR1mRxEWWKpRPk/Xm22KFw9K9v51m ecsEmduYfJ4jetx17rOWfg49Qz6n2hP/ZZS7j0sPFiB7ANn0DEt7zXfO5Of2 68P97MZxOSJ68gupVF+W9njqSBojAAAAALiXP9UEqrtUN5iy75Ap1jWmnJqk J9uKnnYfH+/UbJ43TwCPmT3YBJk7+xk9Wz3uqvusOd/jrrrPmuYed53noKdk dPq3u7vj5raTfWx6gJpMmYduJnsg2ST2dxOve7G/2pssbT35qiz9/modZQwu m3YwZaxHZA8EAAAAANxC9HfuZ8p7wINM2SPYNBKiLB2zk2dFBn+ibhXr++/i RcJ4k4Y1+LNP1uBTR3Y3QdY2KJ8b3eOuks+1zqHr3WdNa4/7rgxz6JTPz6HP 3aVqU11iSsZtIHks2SX2lxDnattyuDhX506G//5I2ui0q8zSxvyu5LEAAAAA gGt5U31I9R9T3ruK732ljigTB+f29KOcelZLlp007E1euGCI9f3sc5TJV375 kQnytfP53Oh91rT3uOs9B931Pe6i9iZ+s0z28ZlLiXnmc1Q3qZ6VPBa9fKh6 MWX+WayjIf7GiV6AhVT1JI4rOyYxJZuLv9GhkscCAAAAAK5TimojU977/cCU 9YxNKz5y5Hi1DBs7P4KHt3mSe3t78bx5AvnQPuEmyNUunkPX3ePuOJ8b0uOu us+acT3uSp/7nHv7Nix4SfbxmcuUY0qOvUXVXPJYPJkfUz4jEX+jsd4CAAAA QO7VheoyU3o8P6MKkjucrG1YbClBGfVOZtl13qf9eJWKpaxz5lXp6/yp/UyQ p92Qz+3n0HXvs6atx119nzV5Pe5Kn/uX/25a8HFB2cdoLlGCKWumiXUo2kse i6frwNJ62xtJHgsAAAAAGE9kmBimvN/7g+WwNZ8opy7LmFuHvNvBuu6bl5eX dS+1dfMjTJClXZPPje5xV91nzSQ97qr7rKXWXL4v8ZtY2cdnLlCU6hTVfaZ8 hmdW+Zmyprkp1q90oXim/K3+SfZAAAAAAMBwbaj+Ymm9kjnuXMaEBZamtry6 6quh1vPL6Z95gdBgPn5IFxNkaHfNoevbZ01rj7v6PmtG9LjrPQd9lsN8Lvrc d63/4k3Zx2gOFkb1LVP+PvSWPBY1eVnaum8tJI/FlUoz5XMS8TiHSB4LAAAA ABhHvJ+dy5Re9n+owuUOxzmUU4/OHPc2L12ikDWbP16zEl8y6wMTZGd35nMz 9rg73mdNa4+7aj7PosddyegzryetmtpY9jGaAwVT7WFKFuwveSxqxDh3MWWc wyWPxdVGMuVxivMMikkeCwAAAAAY4ymq00x5nyf2/M3p7/O8GjV4NMbfz5f7 +vrwXp1b8LhI2ZnZvfncrT3uOvdZSz+H7jifG93jvjtuLn2d/e+WmE8qyz5Q c5BAqs1M+RsxRvJY1Ihx2taz/FjyWFxN7KtxhimPdbXcoQAAAACAAfypJjBl 7uU6VU+W88/VFOfOr2LKnub3p4/uaYK8LHMOXWaPu0o+l9jjnprR4+ae2hjz YX7ZB2wOEECVyJQcOFHyWNSIdczXMGWckyWPxR2eZ2nrwrWRPBYAAAAAcE4V qv1MeW8n9v0tL3c4hniG6jemPKbIJZ8PnCk/J8vO50b3uOvbZ01rj7v6Pmsa e9xV9lmzn0PfHfeFuM7eNV8Pzif5uDUzX6oVTHlNzWHm/fxO7GG+nCnj/IKZ d5xGWsaUx3uWKY8fAAAAAHIe0RP5IdVNqtsp3/tKHZHzxLyZ6AO4R3WJpZw7 v2Hh8EqUU+/Jz8py8rnWHnfd56C7scdddZ81nT3utoxO/70uKcmS018DriD+ VixgSgaMTvlvMxLjms+UcS5inpFVCzPl77d4zOMkjwUAAAAA9BFr/W5iynu6 o1Q15A7HEOWo9jLlMYk1ocra/zAucuRC+VnZXPlca497xnxueI+72j5rhvS4 O87n9nPoVMm71s2J4dxi1vwpywymvK7EXotmzryfM2Wca5nyWZ0nGMiUxyzW 88wNvU8AAAAAnkacW36ZKXvxiLnmQLnDMcQrLO0xWVgmfQAJUZY68rOyvIz+ QI+77nPQzdLjrvMc9HQZ/YF8Lv797q7YmZM594i+aC2mMiX/rWfKOhVmNZYp 44xj5h6n0b5nyuPeLHsgmXiRaiVTzjW6xZRerf+jWkzVROK4AAAAAMxArJdm O09RvF96Tu5wDCH2gotkaedeqj4myqrr5Wdlc82hm6nHXe8+a+kyuso+a1p6 3JWae4fuaya3ePw8utiTTLy2tlIFyR2Kqo+YMs5tVHkkj8WdGrK0deH+J3ks 9sTno6LXgtuV+Ow0OcO/TZc1QAAAAADJXqD6mynvicTe5iFyh2OImixt7kjs BVc4qyvERUY0kp+VzZ3Pje9x13sO+lSn91nT2uP+YD63ZvS7O9fPmWHx3Iz+ AVNeW2LtSDP/vbD1dx9g5h6nJ7E9J6LEmoLVmXK+gehrqM+Uz3tsP+8oZ4gA AAAAUgQzJY+LeYsLVB3kDscQou+4H0tb164fy8YazZRXE+XnZTkZ3bged8f5 XGuPu+o+a5J73EXtif/SmtF3rZs1NyYmxsznXLtCL6b8zThMFSp5LGrEuTpi nMeoCkkeC6TZx5TsfZxlvl6B6Hv6K+Uyy904LgAAAACZijHl/ZHt3MTScodj iNQ9zal+pKqb3RtYHx1RnfLqffl52QT53JB91sZryudm6XFX32dtbrp8bsvo W1d/tixmpiXY6IPZpF5lSi+y6E3JsidFItHPLcZ5kqqI5LFAeuLzEvE3er7K ZRJZ2noBAAAAAJ5A9OXGsmzOL5uY/Z7moidA917VlFcXy8/L7s/n+nrcHefz 3N7jbsvoVPe3rfls26ZF44oadTCblNiPUOxN+AtVKcljUSPWHbvDlLXGzDxO TzWPpe0Nktn5IWItgz9TLjPKjeMCAAAAAOdluqe5MxIXWap45n7ozu2zprXH XX2fNY097qr7rBnQ466+z1rGfM73JHxFl5n9ffxiS1lnjz+TasWU80XEOosV JI9FTUuWNs6KkscCmXuI6jxT8rdYq70yU3K6WDeuNtWGlJ/9xLBmAAAAAEBO orqnuTMoq86Xn5dl5XM5Pe7q+6w53+Oums8197g7zuei6H5+27B4zItGHYcm 0YjqP6asIfmw5LGoET00N5gyzsqSxwLqSlJ9yZR9L8Xfb9HvcC/le5HdpzFz r20AAAAAuZPY66cT1TdMORdcvLcUcz+/M2VdnDYuvn5OluWe5s5IiLJUpMx6 V35mdm8+N7rHXXWfNUN63B3nc61z6Pr3WfvigXxunUdfN/tK0vIpY+fO7eln 5DEpyeNUV6j+ZcqeCGZlG+dFZu5xGkWsobadqpvsgegkPj9ZypT/v+IZSvz/ 2HyGcxMAAADAvcQ5dtfYg+9NMtZKqkAXXD+nytae5s6gzLpUfmaWNYcus8dd JZ9r7nHXew66cz3uqRX35e2tq6cui/vmIzOvoZYV0Wsszhm5StVA8ljU2MYp /h6aeZxGEZ9Fir/r4m/g55LHokc9pjxfYvziM4bGVGFMWW+wBdWRlJ+Jc9DN 3K8BAAAAuYtY79mWMScz5X1J+ZQS/bG2PWhs650Zff2cKNt7mjtjXeTwqvEe t5a7q3rc9e2zlj6jO95nzZAed9V91rT3uIvam/A135v4dfK2NdNPJiwc1daV x6mLVKU6x5R9Cp+VPBY1VVjOGKdR7LP5HJbz1vYU4xX78onxi/+Pymx/NfF5 8ncpl4l339AAAADAwwVQvckc92WL9y22dXLuMmXvMCOvn5M4tae5MyizrpGf md2bz7X2uOs+B91+Dl3nPmtae9xV91lzYY+7NZ8rGV1c98q2VVOnJsXkmD3Y xLoO4hyZW1TNJY9Fjf04n5c8FncQa6gtYMrf9IUs87XPzU6sLWj73Ph/Kpd7 O+UyYv/6vG4YFwAAAIAWYk7c9l5Gz9yQs9c3A/G5wmrmxJ7mzoiPtLSSn5nN kc+19rjr32dNY4+72j5rJulxt8/nexO/oX/7+h7d36H46IjH3Xn86lCC6mem fKb3kuSxqLEfZ3vJY3GXGUz5O7iMZT7vnBM0ZWn/n1RP5XIt7S5XzQ3jAgAA ANCiPkt7j6LnPGtnry+bWI9ZzI85vae5XhaLxTsuauSv8nOzezP6Az3uavnc JD3u6vusGdHjnr1z0NPyuZLR91HRbZ/fvHTC9MRISxF3H8saiP3bf2DKmouv Sx6LGjHOU0wZZxfJY3GXsSyt39tf8licYf//SR1VLtfD7nJl3DAuAAAAAC0G MuX9iXgfquf9vLPXl8XwPc2dERdlGS0/M5tjDj3X9bir7LOmtcddNZ8npM/n oui/79JYj9Hv91VusZilR7kA1bdM+XvRW/JY1Ih1xGzjfFfyWNxlCEtbSy2P 5LE4S5xbLtZnF49nG8v8PCXx9/9gymX+cN/QAAAAAFSJvm6xj694j7JEwvVl EevbuWRPc72UvdYsyfJzs/nyuSl73HXus5Z+Dt1xPtfb456a0TfMs9bu+C+u bV01fdGmhZbykg9xcV78Hqa85vpLHouanDJOIw1gyuMVeTW/5LEYZRJLmxsX 63yKc5bEeiris4enqHbY/dxTnmcAAAAwN7Hm20amvD85z5RzLd15fVlcuqe5 M+KjLbvl52b3ZvRs9bir7rPmfI+76j5rmnvcdZ6DbnCPuy2fWytx3v3tqz8/ Q7+biNhFlkISDm0xn7mZKX8rRku4f61yyjiN1J0p66OdoJJxbLiK6M9fxdLv Ayr+5idn+LecuD49AAAA5D6i3zWKKe9PxLrETdx8fRnctqe5XglRlqHyM7Pk fG50j7tKPtc6h653nzWtPe7q+6xp7HHPmM8zZvQN86m+uUtj+oF+nx9sjJng rnlSMWeZyJTX3UQ33aceOWWcRhLnZovze36hKil5LK4i1h8UOV30sIt9OcT/ X51hSr9XU3nDAgAAAEhlv3+OeL/S2s3Xl8Gte5rrtT7S8pj8zOzefK6vx91x Ptfe4673HHT39bir7rOWjR53Wz7fv1Ep+vlNGsPBuChLu4Nz5/q58JAWvSkr mPK6m83MO0+ZU8ZppFZM+fstPqusIHksAAAAAJ5K7JcTzdLmvbObrZ29vrvZ 72l+i7lxT3M9OGdelFf/lJ+bZcyh69tnLX1Gd5zPDelxV91nzSw97o7zeVpG X8D3b1rAdyd8eYke17aEKEvHuOl9Agw+nO0/x4tm5t1HO6eM00iNqP5jytoh D0seCwAAAICnEnNES1latm7l5uu7m/2e5mI/pzpyh6MN5dX58jOzjHzuYA5d 9z5r2nrc1fdZM0uPu85z0NNl9Az5PCWj798UKa5/efuqaTtETo+JsRi1r9ZM prz2Ypi599G2jVP8bTPzOI3yGNUVqotM6SsCAAAAAPcTPawrmfI+VMwlt3Dz 9d0t457mwXKHo11C1Iiu8jOze/O50T3uqvusmaTHXe8+a+kyuso+a1n1uNvn c1EHqOi6l+hxJFJOb3Fwbk9n+t6nMuW1t56Zex9t2zjFOS9mHqdRqlFdoLpG 9YTksQAAAAB4KtG3upYp70NFT2NzN1/fnTLuaf6y3OFkX2Kk5VH5mVnWHLpr e9zV91kzosdd7znos5zeZ01rj/uD+XxBaj631uYocbsX6LEmJUaNem3nmk/y ZfMQHs6UvxVJVEHGv0IME8FyxjiNUpnqHFM+XzXd2pgAAAAAHkJk6zimvA+9 Q9WJKXvoOKpAg6/vThn3NH9I4lh0i4kJ96G8el1+ZpaRz83Y4+54nzWtPe6q +dwkPe72+dxW+xLnXd22ZvqBxEWje8fFfKxlTcUPmPL620cV4tpXilNs4xR7 YOeVPBZ3EH8Lf6O6S9VW8lgAAAAAPNmjLP1er1nV2wZf311Mu6e5HpRZd8nP zO7N527tcde5z1r6OXTH+dwsPe6O9llT63G3z+cHN0fzg1uixWWv02M4tGHh mH7rFw5z9LlXL6bsLX2IKtR9r5ZsE3+jbON01x5zMhWj+pEpfxs7Sx4LAAAA gKfL7fk8457mz7r5/l0iIXLkVPmZWdYcur4ed/37rE3Uls89pcc9Yz5PyegH tywUP7+1Y+3MU/S7nJOwcESTmJgY23pqrzEl/4k9DE25d2EK2zhPMHOP0ygF qI4y5fOIrpLHAgAAAAC5W47Y01yP+MgR3eXnZVn53KItn2ueQ9e3z5rWHnf1 fdY09rir7rNmQI+72j5rWfS42+dzWx1KWpRMt//3tjXT45o3qjORKes9/EJV SvJLR01HpozzNFVJyWNxB7FugO18n36Sx2I0M587AQAAAOBpctSe5npQVm0s Py+7P59r7XHXfQ66G3vcVfdZM6DHXTWfa+5xX6C5xz2TjM6nTxjMfX19eWj+ 4DsTh3Uds2mhpbzs144DraluU52hKiN3KG4h1gHZzJRsPkbyWIwmPpcVa9C/ JnsgAAAAAJAz9zTPrrhoSyn5edk8+dw0Pe5q+6wZ0uPuOJ9rnUPXv8+ath53 W30xLYIHBPjzAmH5+cqoT8XPb+5aP/vUpmWfzI+PHvHSmq8HZ3fdd1dpzJR9 J/6iqiR3KG4h9rCw7bcxSfJYjFaVKdn8OlUDyWMBAAAA8HQ5dk/z7OKceVFW /U9+ZnZ/Rs9Wj7vqPmtm6XHXeQ56uoyu9xx0jT3uDvZZc9TjHjl7DM+bJ4iH 5AvmS76ewA9tXcwPp9aS5H0b5/21dfXU7fFRoz6IX2CpIfGl9BRTsty/VDLH 4S5iPYDlTPkb+QXLXX1FYl1C8fdf7CPSWvJYAAAAADxZjt/TXI+EKMv38vOy CfK5CXvc9e6zli6jq+yzZkiPu+o+a/p73BfOHcfzBefhefIE8gWzRlv73EU+ T8voS5TatoR+tvgWjffU1hVTZiUsHNUkJmaAO/cZF701Yk+Hq1T13Xi/sogs Pp8p2XwxU7J6blGEpa1B/6rksQAAAAB4slyxp7kelFfj5edl9+dzffusGdHj rvcc9KlO77OmtcdddZ81N/S4L5s3kYeFhnB/fz8+e8pQJZvbKpN8fnjbUmsd 2bY0me7n7Pa1n29NXDy6b2Kk5VHOuSvndh+hOs+UufMnXXg/ZjKdKX8nY5ny mWZuIfqk9jPlsb0reSwAAAAAnixX7WmeXZRT58vPyyaZQ9fd4+44n2vtcVfd Z81DetxFNl+7cCovUrgA9/fz4zMmDkldI+7BfL7YLp8vsV5XjGcnPcYt9Duk 33ky/c4u0u9zBz23PdZGDi9n8EtHfKb3B1PWjmxm8G2blYUp+XULlTt7FFwt gKWtczdW8lgAAAAAPFWu3NM8uyinTpSflU2Sz+3n0HXvszZeUz43S4+7+j5r RvS4O95nLeMcelzMdF6qRFHu4+PDJ43un24Nd1sdTFpovR+Rw8XvR/zuxXOo 9lzTc5i8KWbCZXrONsUvHBEeF21xdt8s0V/zK9VdqnbOvwpzhMFM+Vu5gyqP 5LEYSfTnr2LKY/tM8lgAAAAAPJXYO+cky4V7mmdXfNSID+RnZTn5XF+Pu+N8 7jE97ir7rGnvcU/L5+90e5kXKhjKAwP8ubeXFx895G3rOej76PK7aAzicYnf m3genH3eE6NHJdNzeYme37UbFlpaJVks2e2XKcbSzlHubPwr0pR6USVTHaLK L3ksRpvNlP8fWErlLXksuVkTpqwpKD4LF3sQivNCNlL9T+agAAAAQLpcv6d5 dsVHj3hDflaWl9Gd2WdNa4+7+j5rGnvcVfdZM6DHXec+a+nn0B3nc0c97pGz RolslFoVy5W0/t4SF45yyzFAz/klOgZWb4ge8ZKGl0sBqu+YklW7uvBlaSZi nTTxWcT3LPd9jjmaKcddApW/5LHkZlOZ3WucKWvj2//3SuZh55UBAACAlUfs aZ5dCVEjWsvPybLzuZwed/V91pzvcVfN55p73HWeg67S4y6uvz32c+tj+2RY t3T5vOYjZaUdD/TcX4iPtETHLYpoZLFYMs6lin3W96WMs6+bX6ayiD0sxH4W /0dVSvJYjPY+S1sPNDf165tNf5b2+o5iyroNgujDEJ+P30752adSRgcAAACy NGIesqd5dsVFRjSSn5Pl5XOje9xV91kzpMfdcT7XOoeud581rT3ume2ztjdx nnUMm+h3ZP8cxM6PoExezvr+PSjQn48d3NkEx4X12LiSEGlZETdvxAvPP1FN zJuLHCfGOVLuK9ZtWjAlO/1JVVHyWIz2JlN6IERPQEG5Q8nVAqkuMuV1k+Tg MgNTfi7WcshtxxkAAAA8SOz/I9b8Ef2ZHrOneXbER0c8Lj8Lyc3o8nvcVfK5 5h53veegu7bHfTfdhnhc4vfq6DmIixzJv/jkXb7iiyEmOB7S19p5w3ntauVF luPVKz+0ftU8S6js16wbPE11g+ofqkclj8VorZnSX32GqqTcoeR6Ys1V29z5 8w4uI84ruJFymVFuGhcAAADI4bF7mmeH2CNadgYyRz43usdd3z5r6TO6433W DOlxV91nzbked3E98ZgTpD+/+mvd/Aj+RN0q1nzRpunj1s8REiItd+hnmxOi LF1yaVavy5T9JsXnmbUkj8Vo4nOH/6j+pqokeSyeoBtLy+elVS53NOUye90x KAAAAJDCo/c0z451Cy3lZecg2flca4+77nPQ7efQde6zprXHXXWfNTf0uIvr icer/F5lP7f6Ky5yBH/2yRrWbNGicR1rNn/wciOSKacfXB8ZMYS+5obe3Eeo LlBdp2ooeSxGE581iP9PuEr1uOSxeAr7fF5G5XLHUy5zjXn4eq0AAAC5EPY0 z6b18yzFZGchs+ZzrT3u+vdZ09jjrrbPmkl63MW/i8cRn8Ve5DmhRBZv/kwt a65o1OBRvn7BCC3H0X3K6HsTokb02xhpUcsiZiX6jf5gyr4WzSSPxWjlmPL/ B+KxNZE8Fk9i39/eysFlxDnqN+0ul9v27wMAAPBk2NNch7hoS4jsPCS/Mulx V8vnJulxV99nzYge96zz+W7K5ltXT1M9vzynVdvm9a1ZoX7th63r1+k4npLj okYeiY+2DFm/wPKw7Ne4BuLzhF+ZskZXO8ljMZrYr/5npqxDn9sem9kFMaVn wXaOWWZz48NY+r3W1PrgAQAAIGfAnuZOSEqy+MrOQ/LLg3rcVfZZ09rjbsvm 4jbE70H+82dcvfpSI2tOqFu9Ao+dN9yQ26Ss/mt89MjP4iMtT3Fuur9NRZmy 36Q4F+h1yWMxWhhT9qsXz2kvyWPxVINZWvZeQVWdKeu2lqAaypTPhOz3Q8ea fQAAADkb9jQ3AGWI27JzkdzSu8+aSXrcde6zln4O3XE+f2AOPWVNdvnPm7HV teNz1ozwaOUyfPXXQ11zP5EjT9KxZhHrMsp+3TMlv37LlL+fvSWPxWhiT/Pd THlswySPxZOJz6NmsfRz5PYl9j0db/ff2IseAAAg57Lf01zsoRYkdzg5F+WF y7KzkfzKZo+76j5rzve4q+6zprnHXec56Co97jvo8uLxy3++jK0erza35oNK 5Yrz5XPds8+b5Hn1YKo9TPn7OdTN9+1qYj3QtUx5bJMljwUUjamiqU5R/Ul1 mGoMldgD4ROmPFd/yBocAAAAOAV7mhuMsumfsvOR/MpinzUjetxV8rnWOXS9 +6xp7XFX22dtWy47z9xW/bq/wL28GH+oZGG+dNYHUsYQFznyd1tWt1gs3i5+ yYs1uTYxJRN97OL7cjfxOUcUUx7bNwznOuUEB5jyfC2VPRAAAADINuxp7gKU D07LzkjyS2+Pu+N8rr3HXe856O7pcd9p7WefxHP6nmmZ1ZB3O3Bvby9eqnhB vmjGIOnjSTkWf06IskxIXBhR1wUvdzG3bDsnaIoLbl+26SztXGcfyWOBrNVj Wa/xDgAAAOaEPc1dhPLAKfmZxAzl3D5r6TO643xuSI+76j5rxvW471w/m2+0 7mcu+7kxvizv/4/7+njzooVCeeS0AdLH4+CY/CU+cuT4+AWWGga81MW8vOgx FlnoK5b75pY/ZMpj285wvlNOIPZYOcGU52w/U45PAAAAMD/sae5icVEjj8nP IWaoLHrcde+zpq3HXX2fNff3uO9cN9P6mOQ/L8bXmA9e476+PrxAaDD/enIf 6ePRUrbz1XXOq4ssLvq9xd/RJSz3zS2/RZXMlPOasYe2eYj58YVUHZmyB2px qmpUfZlyvrk4HsV5alVlDRAAAACypRbDnuYulyD2ajZB/pBfxve4q+6zZpIe 98z2Wdu59nPrY5T/nBhfk4Z35QH+fjwkOIjPHv+O9PHoPFb3x0eOGBC7YJjW /aimsbS/o36u+2siRThT9jcXe3gUkTwWSK8xc7x2u6hfGfZdAQAAyAmwp7kb 0fv9A/LzhlnKPT3u6vusGdHjrvcc9FnWyyUszH3rwImaProHz5sngAfnDeQz x/aSPh6D6kRc1IgPNyy2lHDwEo9gShbaynJf33dzqttMWRO8vOSxwIPEHqgf UW1hyny5eK4uUO2gGsDk7Kcm7rMl1XCqlUz5jMD2ecGMbNyO2ANhJNV3VNep rlAdpBpI5W/geAEAAGTDnuZuRu/v95ggY5ikzNzj7nifNa097qr5PHaW9bK5 NZvPmdCbh+TLw4MC/fmnI7tLH48L6j4dvzsTokb0i/vmI1uv0SCWdn5viLy/ Mi4h+vyvUl2kqi55LJBzNGaO5/O15vPSVKftrifWxUm2+29xnkWYkYMGAACQ BHuaS0Dv6bebIFuYpNzc465zn7X0c+iO83l2ety302UTc2k2/3Liezw0JC/3 9/Pl44d0kT4eNxzH/3Vu30jsW5Xs5eX1LVP2mc5NqjBlHlbMWzaQPBbIWRoz 5TMdscfgRKasPfsX057PxdoNR1IuL47Bl5hyzojYt/ANphyT4mfrDR43AACA O9n2NBefP2NPczeLj7RskZ8nzFTO9bjr32dtorZ87oIed/Hv4rHJ/90bX/On 9uOFC4ZY12ofOeAV6eNxR4l94yiXW/eNWzhj0P+zdxbwTZz/H7/BGDAfY8zd x/5zN3TIxoa7DncrpZS26dWNKnVvpJK6JWkLFBk6YAMGE7bRMfvN3Qff//M8 17RpSdrIJXcp38/r9Xm1jT5Jrnf3ztd+IJcl6fP8npV6XyOSbuGE73H/JR4l 8VpQ7idzvRGbOOv5fA7XGid/ycz100yuH2LXClEoFAqFkla0ZnA/hzPNJZNO xddLzRPyspkc94743OoYun1z1qzNce94zlpHOe6J5DV0zV5wms0ecMO1faA7 YXOflZMkX48r3PHcOP5z8v8eZ1Dx7lo3ROuf3uWEfOLpEq8F1XXUxFnP543N t91h4XraK+dk822UYiwOhUKhUCgXaion9FTBmeYSipyr66RmCnnZ+hx3u2vQ XZjj3uGctarN0FAQKoP3XHwXpayH227qx+LIHgvHSL4eVzjcezZcdNGFcNUV lubGsW37LPn9jEHlf4xs4wp9Dn+b1PsgK0X7cRm/y10u8VpQXUtNnHV83pMT ZgXQ23p1cLv45tt8JcbiUCgUCoVygXCmuYxEztUrpeYKedkyn8smx72jOWs2 5LhvLY6QwfstvotTveCOW69jOaZLZo2UfD2u8CY/YW7cZXRuXKi5uXGm2zXb tgmn8//plf6/k59leg0/rjGH7yX1/siCKBfRemH6mYZKvBZU11MTZx2fP8y1 5q6/0sHt5pvcro8I60OhUCgUypm6jWvtrbKV2NJMIJSLxM7NZcAX8rKNOe4d zlmTS457Wz7fTu5vkPx9Ft9lGd5w/103sXPj2RMHS74eV3hz0EI2N472po/j 53e+Tbf9/umsXh3wH7n+H7I9fG1Q+6fo8/kXAGQz07IbcQEnHDPSOZy1KRf5 EN8j9SJEUhNnHZ+P5Fq5+6EObjfC5HYPirA+FAqFQqGcKZqjeITDmeayETl3 L5KaL+TnTuasySTH3d45a/Q29PVI/z6L68psH3ik/+3svHjK6y9Kvh5XOD1i GVxx2cWsNz3Nb7e0PVvcpk22a/L7GeJ/yG3/0qsUn5DbbqpT8lLzRTIncI6W M9/bC+V6jeeEz6RQ6oWIpCbOOj6fxLVy910d3O5Fk9t1lb6MKBQKhera6in1 AlCtIufiuVIzhvxs75w1MXLc7a1Bj7VyzloCW6f077G4rs71g2ceu5edE49/ 5TnJ1+MK58Ssgr59LoceF3aHkPUzrNiWzbO5ue2aXPafXs3/bVDxv+lUCh3h 9al1ynWXuHj3xHMC4xiIL3Lxc6PM60ZOmLNCa6v7SrwWsdTEIZ+jUCgUCoWS icj5d7LUnCFPi5njbpnPrc1x73DOmg057vS5pH9vxXUNYfMXnryfnQ+PHPQ4 6JTSr8nZpr3pr+93FetN77vKUm96+9i8XW7IWXLdP4TV/yD+njyuqk4dMLKR 553dz3MNJ/ANneN+mZOfC2W9qjnhc3ld6oWIqCYO89tRKBQKhULJROR8O1pq 1pCnO8lxt3vOWphVfO6MHHd6e+nfV3GtUypg6IsPs3PhQc/9H/tb6jU529b1 pheFzdt871SXH/wfue+f5PF/JY/9AXncAIOK7yiOaK9mE58lPsF1nRhtVxD9 XOj/mkrqhYisJs55/eGuFmF9KBQKhUKhziPp1f5BUvOGPG1vjrtlPpc0x708 nq1Z+vdVXL/+8lPsPPjFpx6A2ryuz+Yladb0phefzdtt12fJ9f+Qx/rNoPL/ kTxnpS5PMXmPNqa3CLskGqP8hxOY6SYRHg8ljm4h/on4M+IrJF6L2GribJ+v tr6D2+F8NRQKhUKhUHbLoOI3Ss0c8rVjc9aszXHveM6alTnuHc5ZiyfP1fXy 2seOeIZx6hMP3wXVOb6Sr8fZLs/cCA/cfTN7zTPHDbS4zTqZzdu4viD0TJ0m 6E/yXD8ZVIr/6ZX+OfX5gQPs7P/+AvHvxF8T3y3mfg7lkOhn2cAJOQ0vS7wW Z6iJs47PqbY337bRwvX0vTrJdc08AxQKhUKhUC6QTs2vlpo75Gtpc9w7nrNm fY57YxecpTZ7wmDGqf93361QkbVR8vU421U5vvDYg3ew1zxx1PMWt1dXsnnb 75zCzpLb/G1QB/5CGP174v16Jb+yMZ+3Nj+d5g7T+OyvxE86a3+HsksLOYE3 s6ReiJPUxFnP529wrbnrL5i5fprJ9V3xuwwUCoVCoVBOFjmfXyg1e8jX4ue4 dzhnTZQc93P5vD4/RAbvpXieP/Vldv57zx03QGn6BsnX42zT/nfPPn4fe82v Dn7CQv87Sdm8zfZMLj9D7vOHXh3wA1nbZ7QHZZ2Kf66DmPrtxF8Q/0U82FX7 PpRVupP4N+JPiS+XeC1iqQ8n9DUw+jQn8HRmu8vNzSugM/6ONN/+G+IxxD04 Ifed1uf/yrXOHEChUCgUCoWyWQalYqbU/CFvyyHHvQM+7yTHfSu5j/TvoXhe 8cYouOACDu689TpWiy31epxt2u9uyPMPMTYfNuBR2bN5+5yQLYVh/5Dn+Jms 7xuy1iN6Je9bq/G51WQXdB3xR5xQ1ztGkp0gypLo9ynbOCGvvSt9b/I/rjXG 3ZFTLdyfbr+nTG53hhPeI+Pf73DCdwAoFAqFQnWmi4knE2cTv8sJdX5/c0K/ lxLiUVbcn/bu8SUu44Tv043HI2vywlAylEGlGC81g8jbzspxt2/OWltGtzxn TWD0WLZO6d9Dcbx+yTjWs/zmG/pCQdI6ydfjCo8a+mQn/e/ky+am2zO57Ex9 YcjvenXAtzoV/7lB7Z8TH7BgLHltRznhGLJY2j0hyoyWc8Jnkyz1QkSWo3xO RWf+8cTHOOFc6hfiQ8SenBBLR6FQKBSqM9G+usa8q45MubuXhccY2MH9kM/d VDq1YqTUDCJvW5/jbncNumkM3c45a+Zy3Ldow2Xw/onjjSsmQrduF8B111wJ qvg1kq/HFZ782gtW9L/rgM9lwubtt2eyXf5dk6v4qf89t9Dvh+GFpx9o2KoJ vrWzfRXKpaL9+Sh30l5n5vK8USgUCoVCOaZLOYGjaY3fJuIRxHc0+3Xi/Vwr a6dZeIyBxD8QbyGOJJ7CCfNDkM/dWOTcfqDUHCJvW+Zza3Pc7Z+zZmWOu5k5 a6wnnJqXwfvnuAPXTYMLL+wOV191GWRHr5R8Pa7wnElD2P74wQ7739kfO5eK zem23FAUAc892Z+9vrEjn/+XrPVrsv7T5LUU1Obxoxob+Qul3i+e56I11ns4 IW/7eYnXgkKhUChUVxXNt5pDbOm8hx6P6zmBtf8lvtrCbdqriUM+d2sZNPxT UrOI/G2GgTricxnkuNPnkf59c9yRPnPgoosuhKuuuAQyo5ZLvh5XeMG0YYxd 7769o/53zstrdyab079fHvA4e30jBj3JLqfbMbnfn/X5Qd+S1/aZXsnvMaj4 5Tpt6DVS7x/PU63lhON6nNQLQaFQKBTqPBeNqRtj6Nb2gmnikM/dWnVK/kGp eUT+dq8c922lUV1inlp8wAK4uHdPuOzS3pAUsljy9bjCq+a9xvrf3XLjNVCU 7GnF9uiamnMx2Jx6yphB7Bjz9GP3Q31RRLvtOJpu2/+S5/tJr+Y/06v9T5HX qTaoFK+CVmvu+2GU+OrPCX30P+CEnjMoFAqFQqGk09NcK58PsfI+TRzyuVtL p+ZvkppJ5G9756xJk+NO1yD9e+aYE4MXwSUX94LevS6CWP95kq/HFfZeNkGo se93FagT1lqxLcqjH5y1bL5o5ihhZv39t4M+P+wcNjfNBaHeVhz1J1nr1wKn +zfq1IoFNZqwq6TeZ3Zh0TlhtMcZ7aX/jMRrQaFQKBQKxXEeXOuskH5W3qeJ Qz53a9Up110iNZe4h23Mce80b9g8n+81ZMHumpROc9wtcQ3lJOnfK8ecHrEM rrjsYriox4UQ7j1L8vW4wgEe0+DC7t2gX98rIC9utcVtUG5s3hmfG7fbdUsm sd77d912A1Qrgztlc9NaDXL9Pw1F4d+T1/ipQen/HnkPYmqV/BNS7zu7oLw5 4XgeIfVCUCgUCoVCsXpz48yRQhvu18Qhn7u9yPnu31LzifzdyZw1MXLcCeMc 21sJv/zwlVCTa02OO/2dXkdvQ+7v7j3hcmJWQd8+l0OPC7tDyPoZkq/HFY7Y ONukxn6Fxe3P3djcuM36e8yEbt26wfX9+kBxusImNm87LzDuLNnOfyPr/YK8 Fx+R96VWr+ZnVGatv0zqfWgX0P9xwrxVOi8M54OhUCgUCiWtaM+4Bk7g7G+I b7Dhvk0c8rnbi5y/fyM1o8jf9ua4W+ZzczH0D9/ZBlRN7+3tkM/pbQ3qQDZ3 y/xcbPczzem+vt9V0L17N/BbNVny9bjCxhr7Sy/pBcmhlmrs3ZfNo/wWsN77 fa68DNSJ3mZyPyz3OGzH5oIr4pnJbf9qKAr7Wq8K+Ein9D+iV/sHGXL9+ku9 L3VT0bz2t4n/IX5U4rWgUCgUCnW+qxuxihMYm/aEGWTj/Zs45HO3V50m6EOp OcU97NictbYsZJ7PPzt5mPH52bNn4FBjvtlcYfo4xjXpiMsyNkBR8jooSfWC sswNUEWZXelezJ6fuA5uvO5qlgO9bvFYydfjCidZVWPvvmyeGrkKLu7dCy67 pDdkxnh0yuad8nkzm7c6gVwX/x953u/rNAEfk/fpfeLiWpVifGMO30vq/aob yZ8TjuNBUi8EhUKhUKjzXJTN8zjhuEzz2l614zGaOORztxfh871Ss4p7uJMc d7vnrLVy0A9ffwpG/fXHL7CzcnMbPt+iDW9mtrZro3F0bYonFBJON1qb7Aml 6V5sfnZNrh/olVK/f+atTVkPt998Letbvmz2K5KvxxWmNfZXXn5JJzX27svm eQnryeu7FHr27AGJoSscZ3MLfE69szKB/Z+Q+/5eXxD6mZ7WqCv99xtU/MYt Gv4OqfevMhet46czVQ9yluevolAoFAqFcr7orBo11xo3t4fNqZo45HO3FznH r5aaV9zD4ue4t2chyuSm+vqz99uwT30HvdmNsXRTRje1HGPsZRnecO+dN7K+ 3oumD5d8Pa5wbuwquObqy1k/OP81Uzrc3tyRzQtTfaBf3ytZnULIhrkuYHOB z43eXhb35xZt+JfkfXuPvI/H9Wpeq1cqJu7RxvSWel8rM9Ecg+Oc8P38wxKv xVV6gfh2qReBQqFQKFQ70e/Ii7hWNn/Fgcdq4pDP3V46tX+K1MziPnZejvtO whsAZ6G9Trylb2Egg5nYeXtX554bS7dkKWPslVk+8PADtzE2nzZ2gAw+W+d6 44qJMGb406z/HZ2j5kP+7mg764zP5cjmlbkBcNvN17E6Be+VU13O5tS7qhIF V24+01i66Ye6guCThNHf1an8d+iU/OqtecE3Sr3PlYlCOOH47Sf1Qlyky4k/ Jz7NCTX3KBQKhULJQfSYVMYJx+Q/iUc4+HhNHPK520unVvhIzS7uY+fluB/d XX4Om1OdOfMf7K/PIWwUZfU6O4ulSx1jp4/92P/dydh84qvPy+Bzda7XLhzN XqvRsyYM6nAbczh2LgGb16qD4f67b2Gvb8XcMdKyudHVSczkMX8lr7eJvK9H BfsX6NT8BF3CivO1V/nTnJDXfoA7f/La0znh/2+61AtBoVAoFKpZ9DykihOO T38QDxPhMZs45HO3l17Jz5GaX9zHzstxP/3hQbN8TvXbz98xvrF1vVXZvlBk ZSzdEq8Xp3pCWfoGqMzeCLV5jsfYaZz+uSfuYxz36pAnQCfTungxPei5/2vD 50tmjbRi+3J2Xrt4bF5XEAaPP3Q3e21TxwySFZsb/WZ1Mo2p/03W+6VBE/Au eZ/f0at5g0GtWKDLDr1G0p2wa0Xz/N/jhO/o75d4La4S7X17lrhO6oWgUCgU CtUsyuY6Tjg3pDNUJhP37cCWet/2aXe7082Pmdnu8kuc9DpQTpBOzQ+Tml/c y47luJtnpHD4/Zcf4OzZs8zmdOrEbrvWq1Mq7IqlWxtj19kw342uZcjzDzGO Gz7g0fOCzalN4+e07jwlbInZ7Uo2Nec2sDn9e/ALjzZ/3/I0u1yObM5cI5hc 9u+20uiv6zWBxw0q/7fJ+32QOMWg4Ydqtdru0u6Rna5NnLAtrpd6IS4SPf95 n/g34tukXQoKhUKhUC16kDOJ3VjhxRYe539W3j/VSa8D5QQRPn9Aan5xL5th qI743IoYOp2ldubMmRY+N8/oZ8Bc73ZrXZXj41As3ZY6dp2Z56csPmyAwHEv PdO/y8xtt9a0/nzK6BchxuwsNRmxead83srm1KOHP8c+0wHPPkzuEyl7Nn+z JoV5d7PJY/5CXusn5P0/TD6LQ+SnXpenWLElf+O1Uu+bnaCXiM8Q7+KEGS7n gxSccF6yQeqFoFAoFAplIuRzlEXVaDZcJTW7uJetz3G3ls+/PHWU8XlnjE75 xpG103ryEsLRzmD0zmLstDca2dzgqUfuhmrai07yz1Eudic2b8vncyYPY5/p Ew/fA/WFEW7H5rtrU1tMbv/XtpLozw3qwHfI5/IW8W6Dkg/Q5/EPSb2PFkmX En/CCfVt90q8FleJ5u/TPrhvc+dPnT0KhUKhUKguIL064G/pOcVdbJnP7clx 36PLgH///aeFz9szuimnH95eKMprqMymsXTnMrqpJ7wqxFgfvPcWNu/cUoz9 /LP7svmyN15nn+k9d9wENaoQyzXnbsDmgtOY99SmniHP/119QSitUT9AZ6kT lxo0ATPLc/grpd5XO6AETvj+fLXUC3GRLiDeQfwf8VMSrwWFQqFQKBTKJtXl h3wpPau4k23Mce9gzto3X5yE//77r8WWOJ3q5JFG0V5DTZ4flKStdzqbTxv7 EuO4++68EfLiVrXG2FM8oTSN5sR7QzWNsUv+mbp+G3JXNvddM53NULvlxn5Q nhNgdz842bG5zuh05p2ViT+R9+YDg4rfR61XKXaS7TREr/Z7Uup9to2i/WBp f7Tt3PmT1z6XE76PSJJ6ISgUCoVCoVC2qqEgbI/0vOJO7mTOmpU57u/sKoF/ //23DZ93xOjffvmR6K+lnPBxkZPYfN6UoYTjOLjjlmshO3qFKHXsXcPuy+bh PvPgwu7doV/fK6Eozc8JvdrlweZG79Vn0Mv/Iev8ok4TdEiv5vcwq/wz9Er+ FTeY0XYZ8SniX4hvl3gtrlI/4u85Yd755RKvBYVCoVAoFMpm1eeHZEjPLO5k e+estbIUZYY/fv+V8bnRnTH6f//+w+4r9uuh8WvKxmKy+aIZwxmb33T91ZAe uVS0OnbpP3sxtx33YvOE4GXQs2cPuPyyiyE7dp3L56hJweZtbMg8u7Mq8buG ojA6Q303+RzfNKj4er1K4VmvCbpb6v24BaVxQhx5qdQLcaHUnPCax0u9EBQK hUKhUCh7pFMrVkjPLe5m+3PcKWv8+vP38M8//zBbYnRznH5wm8Ypr4eyL803 F4PNV80bBd26XQD9+l4ByaGLReV+94+xd8DnMmbznLh1jMt79+oJyeErZTfj 3AVs3sa7a1J/Ja/5I/IZEk7330U+053EGXVKxWs5ObylGaWu1khOyGs3cEI9 9vkgmstP2bxC6oWgUCgUCoVC2SuDSvGq9Nzibu4kx90CV+2sTIQfv/sK/v77 7xY+t4XRT53Y47TXZCAuz/R2iJ+9lo6D7t27Qd8+l0Ni8EKn5M234fXmOvbK THfgdftj51KyeX7yRvJ5XgE9elwIm/wXyY7NO+Vzkdl8nyFLcF0W+TvjH7Lu z+ryg/eT/58dzS43qPj5tTn8dRLu1q8i/oL4R+IbJVyHK3UJ15rLf7PEa0Gh UCgUCoWyW3qV772dsUV6xDJ44akH4Pkn7oeUsCUyYB2pbXuO+776HPjlp+8Z mxttK6P/+fvP7Hmc+dpo7zh7Yul+qyfBRYThrrz8Eojj5zmdzd0rxu68vHZn snlppgJuvK4v6wfnu2aG+7F5p3xuP5sLzmbeT0ye63vy/h0hn/N28pk3CuZT dWp+WCPPu3q+Vw4nxJHnufh5pVQ4d371qEehUCgUCtVFpdXyF5HzyLMd8cWN 113dMuP+un5XgU4pNe/IwdbNWaMMdeKtOvjjj9/hr7/+YjZldGs53cjoB7Yo XfL6aF16WfoGq/rH8R5ToedFPeCyS3pDpO8cydhcnjF219eci8HmVXmBcOdt N7D/+dULxnVBNu+Ez21gc+b6HGZy39/Jaz9JPtsdeiW/jWwDWw0qvoTF1LUu iamPbd5X17rgueSiR4n/Jd7LnT896lEoFAqFQnVh1RUEf2+OLQqTPWHOxMEt bE5NY2nlhHWk52Op3XmO+x5ynv/tV03w559/Mhv53F5Gp/7843dc+jrpdzFV 2T4sJm1ubnrohplwce+e0LvXRRC8frrkPG6Ni1PXQ1nGBjYLvjbPr0uxeWd8 bg2bGwrC4JEH72L/77MnDTv/2LxTPjfP5q3Opdf/+2Z10hfkc9lHtoEt1DqV ol6n9o+o1fAvabUTuzthV3418Zec0L/8Bic8vhxF38cDxP8QPyTxWlAoFAqF QqFEUUNh+CFTrkgIXAgjBj4GvXr2YOfoPXp0b+Hzwc8/JAM2loMt57jTOvPT J99mMfM//viD2cjoHXG6NYz+919/MhaT5DVTVs/xhfIMb8a4m/zegMsvvZjF zgPXTZOcu+11UbInlNB57JkboTrXV6T8EPmxeWd8Ttm8oSgCnnuyP/tfnzDq JWRzG2LnRjanPtBgdN5ZsoavyXt8UK/2b9Cp+Hod6/vO5+uVinm6bO9rRNyV 5zfvp2eK+Jhy13JOeM3RUi8EhUKhUCgUSizVF4UmalPWw9zJQ9lMLI7FyTl4 tP8dwK+dCjW5CgjxmgnB62cQdukKc67EY3RT9tqty4Avmk7A77//zmxkc1sY 3RpOP7q7XPLXnhO9Eq6+6jJWc86vnQLFaeudNktdCrO8+PQNLC++msbZbdru 3Y/NBUfCsAGPs///4QOfaGb29nyObN5Z7Lwdnwvekkfv9/uOyoQPyWdO897r 9GreQLaTKp3Kb12N0vd+B3fjEziBU0scPiC4j27ihH5wnxBfLPFaUCgUCoVC ocTS8zddd/U+ylnkdzZHaeKo5yEzaoXkDCh/C/y1n5x/f3X6Q/jtt9+YjXzu LEb/+fuvmhlQmtedF7sa+l19BevVrlgzpfU6Ja1b92O92Uos5MO7s4tShN5z tM89zSOoNTuT3T3ZnMbOp44dxPYBTz16H9QXRbRh86q8YNBpQs3zObJ5p2wu WCm4Ie8/st7PtmjDdwuM7q83qHidXsln1qn5CTo1f7mN+/Brib8l/ppYzHi8 3FXGCd9JjJR6ISgUCoVCoVAO6lLihcQHuea8dRor37hiIuMO6blX/qasdWi7 Fr767GP49ddfW2xk9I44XQxG30u4QYrXrdnsATde14fNOPch20tnt6cMW5Xj A2WZG6AktWvF2BmzE5cY69mzfFgPOmH7cC82XzxrFNsP/N99t4NeE2Y2r704 wx+iFIsgJ369HbFzZHPqt4zeqmImz/UDeS/fJnwuMLrKv5YwewXxhloN/4iV +/OK5v34JOccLmSpMZzwmrVSLwSFQqFQKBTKAT1MnEb8Myec29A+QuFXXXXp g4Qf/pOaed3BlKMO7yyBL0+fhF9++YXZlM+tZXRHa9I//+SIy197Ucp6uO3m fqz2Ye3C0XY/Dq2RoBxL4+yUa0tSvboMtxc1m+bHl6RtMIm1k9cuUzZft2Qi 6/tI+7VXK4M7rTlXbd4AG1dOg4xNHgKnOxg7P1/Z3OiDW9VwoD73N/K+HK/L D6S16TXUOqV/tU7FJ9flB7zWmMP3srBPn9q8Ly9yzSFEFrqCE/rg/UAs5Zx5 FAqFQqFQKHtE6/LaxMqJDxHPIm4556svCP1UavaVq2nsc48+E95/ezt8/93X 8PPPP7fYyOjtOV1MRjfH6f/88zfjJle9B7R/2h23Xse2nyUzRzrlOWgvdcqy lNtLM7ygOGW95LxtL5+btycUp3pBWeZGqMz2hRrK7KoAqNcEScbm/LpZ0K1b N7i+Xx8oTldY3Q+uRhUKEX4LIdx3IeTGbwBDQaRT8trPBzZn3tbsreoze/QZ X5LPYS/lc1qfTm1Q8oV6Nb+0Thl0u8m+ndZf/0j8FSf0bj9flMAJx7HFUi8E 1Ub0XIPWGvhyQu3Bp1zrOUeiC+6PQqFQKJTc1Z8TYuX0/I0e335r/vtxczcm 5/vVDnOsJpDwRKhZ0+uk5mxb3FgWx+LkHx3fD99+/SX89NNPbWwrozsj3/3D d7a55L0oy/CGB+6+mZ0nzRw/yKWfgzHWTmeh0f7qtGdbSdp60Mqwtr1jNm9l 9PbWEmYvTfduZXY1+T/Kdz6bxwUuYf39+lx5GagTvW3u1W4ojICksFUQG7gM UiLXgHKzN1TkBjs9r73Lsvk2TRuT+/xG3oMTdflBevK/UEnz3g0avtyg9g+o U/HPXXDBBTXN+/bXXXRMkYOeJT5D/CaHs87lpoGcySzWdraGrx29PwqFQqFQ clQP4onEDcRnOeG4doQT4ucd9hwyqAPXn8Pbap7NW9peQc6VdTmwb2sRvLWj Ag7t1sORA9vg3bd3w4mjb8GH7x+Dj05+AJ988gnzqVOnWtzU1NTiTz/9lPw8 BR+ffA8+PHEYTryzG47sb4BDuyph35Z82FWbwbiYxqtdwX70OwP6fHv0WXBo ezEcP7QVTn14BL4hPP7DDz8w//jjjy22h9Gdme/+5x+/MUZz5ntEuZj2JqDb 0qTXXnApm3dqpbG+3bc1V56wO539Jk82N8/nlsxi7RmEeVu4PYh91yUGm6dF roaLe/eCSy/pDZnRHg7NUcuJ8yKMvhQK0hRQkRcCuQneoErcCNtK41xec95V 2PxQY36rt2nO7K3L+mJbafRug8q/nHrulJdZPtQdt1y3v64g+GYnH1fkInp8 O0r8Nyd8/4ySlwZyQs3BFuJI4imckNthC587cn8UCoVCoeSk24jDudZj2R9c B7Fyc9Ln8Q/trtd8e/BNHRw5uAuOHzsMH37wPnz44Ydw8uTJFn/00Uct/vjj j1tsZHNrGN3Up0+fbvFnn33GfPr0p/DJyRPw3tG98M5ePezfVgi7atIYS9PY oTXsRjmG3n5XTSrsrcuFg4S/j+2vg/eP7oZTJ4/Bl583wbfffgvfffddi7// /vs2NjJ6R5wuBaObcvr7hxqcxr/VuX7w7GP3MjYfN/JZ6XncBtMZ5nT9VTTu TtidzmynvddpLzdaGy5mvbsz2Jw55VzTOYg0h6Aiy4e8PvI6VbSWPYTxuLVs npewHq68/FIWO48JWCLKjPNqdRjEBS2HzBhPSN/kwbi8NDsI8ppj6rLqB+dO bE69vYD5MPFbW/J+KEhRHOvVs8c/V1x28R+FSeuqdCq+xKDmg/V5fs9qtdru zjjAyETrOeH4FiL1QlBmZW7ba+Ks52tH749CoVAolNS6kGuNldN8P3oM+4h4 FfGV9jzg+++/n/HBBx+A0ZTNjbbE6B1xuiOMTv3555+38RdffMH8+efk+tOn 4HTTR3Dq4/eh6ZMPmD/79BP44vNP4auvvoT//e9/8PXXX7f4m2++aWPK5kY7 yuj25LuLxei///oTy4MWm29pXPqFpx5gbD5i0GOMd6VmblHdHHunufO0vzyL v2duEBg+zXqGdyWbt/X6NtamEm7PoHXtflCTFwB6dTA0FIWdw+bFGX6s1pzO xgv2ekMUNjfNZ0+L8oCceG8WQy/NDmRx8/LcEFAl+UB+ioJxuyz7wbkBm1Mf aiyApx//P9bPLyZo9bfk89lJ+Zxs08XUhNPTdSrFdJ02tKvNWbuTE753fp+4 p8RrQVmvJs4xvnb0/igUCoVCuUI0l5HGyj/nhOPWP5wwY2Yo52A9HuHzucRg DaNbG0s3ZfSOON1WRqf+8ssvW/zVV1+1MeVzoy1xuiVGb8/pYjK6M2awHd9f K3rs+eUXH2FsPuCZBy3M+T5/TGvgW1nel+X8l9OYfKY3y6kvzfBmuegC03uK xubZ0StAGb+6UzZvYXSz9oKSdJoj7wf5yV5w603XMrbzXjFVdDY31ptXKcMg PmQFFGcGQHbcBthaGsdi5tvJdeokX8iMWQ9l2cHyYXOr+VxaNj+8vRB8PRaw /8sxrw6CwzuKmA9uVf1A3stDdfmBZXo1ryXbbBHZZgvrlAE+OjX/jFY7sSvE 1A2cULM1UOJ1oGxTE4d8jkKhUKiuqQs4gb+rif/jhONVE7EX8fViPcnx48f7 Uz4Xm9HFjqWLyejWxtItMboc8t1//ek7UfvvvT7sKcYATz96D8sRl5qP5WWe WZhvbmbGOe2dQH+qAtjtdMS11EoeqvP82Zw16hqaf0+Yn15GXZVD6+j9yPut aOPk0KWQFrmi+fpWV1Jn+53rHDq3ztfEfsyFKRvgnjtuZJ/rrAlDGK9X55L1 sZr2MNhWHCUKm5vWm1MOL0zzB21GAPtpGjOvUoVBZqwXpER6QENJrBuweXs+ dz2bV+XHQ+9ePeG6a/vCLl0uY/O3jd6pJX8X/k1e5wdbiyPraL931vNd5V9A HK1TK0bWKaMuEetY4WJN44RjnlLqhaBsVhOHfI5CoVCorqW+nMDgH3LCMYqy uSixcnMCgAsIm39vZHRrOV0KRreW08VkdHtq0l2V7/7ufp0o/Dl19EuM4Z54 6C6ozvGVAQ/LyZ2wuSaQWewZ51WEo5NClzX3hrO9H1x9YTg8/vA97HOdPHog i5tbjJ2LxObGOvOK3BDG4PXFMYzXK5VhbeLmO8htKKenRq2DovQAN2HzTvjc CWxO89qffLQ/y31Ii/U7h81N/c7OYvo4v5D35diWojA6ny2fWqfyz9Mr+ZU1 Sv5BTvjO1x1Ej4HfEn/DnV8z5LqKmjjkcxQKhUJ1DVH+phz+Fyccmz7jBE6/ 0dlP/N577+lN+dyZ+e6uYnRH891dVZPuSL77b7/+zBjNEf6cM2kIY7gH77uV 1WNLz8NysjRsbuzVTn9Pj1oFZZkKm9ic/j7kxUfZ5/rKkKea69Dty2u3d775 9vIEyCBsri+IYrXo2fEbYHvF5nNy2g1F0YzVkwnPl+aEuCebd8rntrM5tdeq N9hnOHH0sE7ZnHmX0SVnyRq+2lmVuMegDiwi27BasH9UnZof1ajlL3X2McVB ZXLCMXCOxOtA2acmDvkchUKhUO6rPpzA4O9xwvGI1trR3m+0B9xFrloE4XN/ YqB2FqNby+lSMLqj+e5SzmD7+Phum7mT1jtHK+bCG5OHsvP/u2+/gfUHl56H 5WRp2dw0Zp4T6wH5yd5W92ofPfw5oY/Asw+R+0Q6rebcmhlqtB5dk6pgTJ6f Sra9jACLOe0VeWEs7p4Quga2lMR3ETbvhM8tsHmFJg569eoJN994HeyuU9rC 5u1c/A95LSe3l8XUke1apVfzSp2KzzaoFcsMuX5ynFc2mGs9DrpLvB/VVk0c 8jkKhUKh3E+PcUJd3Z+ccByiuXy0/9s9UiyGcPkwI59by+hyyHeXgtHlNoPt r7/+hJ2Eg6zlzmi/uXBx757QvN3Bzdf3ZbwuPQ/Lyc5lczofzVo2N8bNKZ8r 4z07ZfO5U4azz5XmttcXRjiNza2ecU64vE4bDenRnrCtLB7qimIgK3YD6As3 Wcxp30V+ZidsJPfxAmWSglyf2jXZ3AKfH9yWDw/1vwe6dbsAshMD7WbzI2+W tvHhHUU/kffkCNnGSgw0713F5+qVfGidSvGyTpcgh/7ovYg/4ITj4t0SrwVl v5o45HMUCoVCuYdon56FxAe5ZjbiWmPlkp4bEY6+4sSJE/9ZYnR7atLllu8u BaO7agbbF6fetZo9X3q6fwubUy+cPlwGPCw3d8DnIsTNi1K9ITtmjdVsboyb axK9oCBlo0U2Xz53tJAPcceNUKMKlp7N2/VqVyb5shg55fLirCDISfAhlyd3 mNO+vSKJcXpKlCcoExXNcfSuy+bUa5bOYJ/jtAmvWMxrt5XNj+wuYz7KXHqG rLOJfF5bDZoApV7tn6NT8cl6tWJ2XbbPzRIeivjm/ZKvhGtAOa4mDvkchUKh UPLWQ8RpxD9zwjHnB06Ild8v5aLai/D5HmJwlNFxBps0M9j2E46whj3HDH+6 DZ+HeM2UAQ/LyfbHzm3JaS/N8AXF2umQGr4SMjethuq8gA7Z3Bg3T49aY5bN /dbMYH3Ebr7hGijL5mXH5saa87KcEMbplNG3VyRC7mYfqFJFmOHzc3Pa64vj ISNmA3NxVkiXZPPi3E1wUY8ecOvN18MeO/PaO2Zz6nLBe8rp5f8dbMw/rU5R 7MmIWlFUp+IzDaoAr1qV4mWDlu/jwkPQA8R/E7/LubC2C+UUNXHI5ygUCoWS n3pz58bKDzdfdpmE67IowuaBlM+NtjXfHWewSTuD7ZefvmPx1874k87HHvz8 Q3DbTf1g9oTBMuBhOdl5ee3m6s2rcgMgMWQp+9wKaP56gmeLVZu9mNXEefGe hL+nw+oF40CTtOEcNg/3mQ8Xdu8O/fpeCYWpvg6zuSrR2ylsbqw5byxPgKw4 b9hSGs+4XJcfBUkRHuDrMQcMRTGd1pxTHtcXxUJGrDdzaW54l2DzA1s1cN89 t0O3bt0gLyVYtLz2tnzeyuaCK5iPEe+t0/xdmBH2aXr0+t21eYps8j+RYVD6 B9QpA16r1fjc6sTDD60z30l8hvhpJz4PyjVq4pDPUSgUCiUf3UkcT/wjJxxf fuOE2PnjUi7KGhEOH3D8+HGwhtFxBps8Z7B9cmKvDBjXXS1NP7haVSBsDllm 1Qw1xdoZMG3cYMLgPi1sTu/bs2cPuOzSiyE7dp0ocfPYwGWwZM5op7C5ac25 OlkhxM6bY+b0b68VMyDMbwkkhnuw21hTc76tIgk0qQGQs9kPsuN9yWNluB2b H95RCMsXTGHf5c6e+rqT2LxjPj+2t7LFNdqUv7PjFacqc4P15P8jjVqn5IMN Kn5SpYq/ixO3d9t8Tjhepon4mCjp1MQhn6NQKBRKWvXghBpyWktOv/+nx5Wj nBArv0LCddkkwuYXEf8mNqPjDDZXzmD7E/YR5pCedd3NtrN5VvQq0Xq1l2cp yOOtNc/n7XrB1RWGg+fSSTBzwlCID1oKl192MfTu1ROSwlaKmtOem+AN08cP hW2lcU5hc2PNeYUynLA138LoNIc9UrEU0mLWQ1r0eogPWQPleeFW15zvqk4D ZZI/5CYqID3GGxorU9yCzYuyI6FHjwvhrttvhv1b1K5n83Z8Tv3u3iqoK8uE UmXc73rt5vd2lMdX6NT+KdQGwup6TcBEXa4v/U7aEVa/gfgn4i84NzpeotqI 1kH0NfFpTjgPymx3+SVOuj8KhUKhUEbRfD9aR/4lJxxL/uDcJFZuSYTH6yif d8Tocsh3xxlslmPpP373FWNC6ZnXXWxf3Lw6zx/SI1eINkctM3oNy3e3dsZ5 xqY1cHHvXtC9ezeW3+6MenNVog9MGzeU/e4MNjcyOZ2lRvu/7ahMbslpzyXP HeS9EHZWpUCVKhKyE3wgM24jedxUq2vO36zNgDzC6jSmnp3gBw2liefwudRs vr0mC2q1iXDvXbfBhRd2h4LMCNmwOfM+wY01eVCuSYQtVZnf76vP3retOFJt oD3lVP5JejUfpFPzEyirA4CtrF7ACcfPyU44pKFco/9xJj1NOnCqk+6PQqFQ qPNb3blzY+Ufc8IM834SrksUHTt2bJ2RzzvjdJzBJt8ZbB+8vU0G3OsOdiyn vU4TBInBSyBz00ooTPFyaMY5NWVua9i8NFMBN13fl/WDWzZ3NMyeNAw8lkyE hqJI0XvBZcR4wqJZrzuNzY3eVZMKWYS/64tjW3LaKZuH+SwBdbI/43HK7iyP PcEXKpSRNtec6wrjGK9T52z2hzd1mR3yubPZPNh3OYuZc838sWDWOFmy+bv7 qgXvr4YdehWo0iOhoTKbPuYP5L07sK00WkMYPVGn8t9cq+J5Q17A6K2aYPr9 dWesPqr5tVc5+9iGcqqQz1EoFAolhSh788Sfc8Jx4l9iLfFQ4m7SLUtcEQZ/ 7N133wV7GB1nsMlnBhv9ua8+Vwb8K2eLU29Of0+NWA7lWX6QE7uWzU1LDl0G qgRPm2ecp0Wt7pTN6dy0e++8iZ2vrlowjsXNqdVJNB99CKxdNIHNPe+Yz23r 0x7kNY9w8kKnsblpL7iCtACoVEW2qTfP3ewHvmvnwG5jfjvh8ZqCaFZvnrLJ C3YQjre1H9yO6nQhtk4eg7J6fUmibbFzEXLar7u2bxv+qCqIlzWbUx/fX8PM 8t5VCXBkTyUcP1BLn/sr8p7v3FoUka1X8gl6tX88YfZQnSpguiE/sL9Wq+3e 7nBzKSfUGf9KfItLD3QoFAqFQqHcVfS7f8rflMPp3Bd6DtXECbHy66VblnNF +PwUZfT2nC51Tbrc8t3lPoPtl5++ZzwnPQfL0eL2gqvK9Wdsbho3r87jITfO gzlj02pIi1wFyWHLm72ijZOII33nw7rF4ztkc0NBGDzy4J2M5WZNfLmFzU1z 2vMSvGDK6EGwav440OWH2RE7N98LbtbE4VCpDHUqmxvj5tXqKChMD2xTb05j 6RGKpZCfHtQmbr5Hn0n4XQGbwz2gKDPY7n5w5apNkJvEgzI5EFSpQYzfHY6d d8Dm1LTWnGtm8+7du7Ncd3dg8xYTLq8qSgEDYXX6+4kDOuZjeyu+f2urch/Z NnN1Kj7OoPSPNaj8Q8j/2jRDrl//Rp6/kLzmyObXvk7K4x0KhUKhUCi3EO1D Qhn8A044f/iP64KxcksiXL7ZyOf2xtJxBps8ZrB9/smxZhaVmoflZPNsnh6x HGpyFXb3adckrofitI0257Sb1pvHBy2BCaNehOIMv3PYvKEoAp5/sj9jufGv vmiWzU3z2lVJ3jB78nCYOXEY5MZ7OTzjXF8QRR5ruNPZ3Oj64jhQJinO6QWX Gr0BNgWuhJ3VqefktFdpoiEjzofVm79Zm+5QP7iyvCgoyAyFoqxw0GaHw5u6 LHHy2ncYXQS5yUFw2y03wjV9rwJ+wxK3Y3Oj9zcWgzY3Do7tq4ETb+marWcm j/n9wS2qvTXq4FzeY6o6wmd29sBn+zdecMEF/110UY93J/bvj7POUSgUCoVC WZIxVv4XJ3D515zQ/+1OKRflahEGH3Hs2DFwlNFxBps8ZrAdP6CXARPLyaZ8 3jZuvkkxD/Tkp70z1NIiV9rN5sa4uT4/FOZNHQHrlkwg1xn5PBKGD3yCsfng 5x9pnq1mXT84Q0EEbFgxFaaNGwKrFoyH8txgm9nc6IUzX4N6bbRZPheTzY1x cxozpzXp9HamMfMqTRSE+CyBCmWUxZz2kpxwlr+uTOaFyx3s1V6liSXMvgnK VdFQptwEO2oy7c5rN/L5YSlmqInM5sa4+fH9tZCfHQ1HyeMY2fw9ow8aiPVn qgqTPu/Z8yL6fTfblkcOerxRr1aE1qoUb+jz+Iea4+ooFAqFQqHOb13FCbHy E5xwznCWE3q/0R5w5+X3+gcPHuxB+PxHVzI6zmBz3gy233//jfBOhgy4WA7u OK+dsrnPyslQkORp13zzjE2rHGJzU28OWQ4jBz8FqkQvmE7YmvxrwlOP3gf1 RRF292ovyQyAlfPHwexJw2Hx7NchfZMHNLZweuczzkM3LiT38bQ6du4ImxtN b5dBGH17VXKbXnCN5ckQE7wakiI9yXWpFnPat1UkQ24i7QnHs/7tYvVqry9L IaweQ1g9GirUsVBTmNDK6bawead8Ln82Z26Om+dnx5hhc8G+65e2qbd/6tH+ X5P/hUTyPxmpU/tHEAfQ+eoNyqD7kdVRKBQKhTrv9CgnzEL7hRPOFb7jhFj5 PVIuSi46cuRIIeVzoy1xOs5gc48ZbN9/+yVhyFAZ8LF82dyY116e6QMJgQsh KWQJpEUsZ3POc2LXQE7MGijL8OlwhhqtLReDzWl8vCI3EHxWTYN77xJqlPvf exvoNWGizVGrK4wivL0A5kwZAbMnj4Clb4yBcN+FUJjmD7WaiBaXZAVCfPBK WLt4Eox/dQB5nARR8tqtYXPTGWpZ8T6EtZPa5LTTyxPDPcHfcz5E8SvJ42Z0 mNNeqY4GdWoQ5KeHwD5ynZhz1PY3qBinV2gEVxK/qc9xkM074XOZsTnlcl1p JnnO6nPYnDonJaINny+dPx0qClLPHttX9fn+hhwD+d+JJXwerlf6h+mVfr46 FT9GVxh0J8/zXb6uDIVCoVCo81SXEC8kPsi1niMYY+W9JFyX7ET4fOrRo0fB GkbHGWzuMYPti1MnhBix5JwsnouSPWFz0ELQKcVhc2NeuzLeA0oJp7ePnRem bICMqJXEqyA1YgWkhC+HpNClhONXEI5fDVNeH0Bu4+0wm1flBcH1/fq0cMwV l10CL7/0GCSGrhB9xnljeTxMHTsUNvkvgew4L/BfNwcWzx7NZqqNHzUA1iya CPEhK6FGHe70mvNz+LzdfPPsBF9orEg+J6e9MCMYSnPCIT7MAzLjfKA0N6LT evMyZRQUZoYRZo9x2hy1hrJUwuxxUJkvWKdNEo/NO+Vz17M5dY02jdy/9hw2 f+9gHXMY7wGDXnoGVi+dA8f26eAdwvLK9Cj44HADfHCo/j+y1pP767Kr6wtD Ngn93/1DdCqFny6Pn1CXw9+HcXUUCoVCobqE/o8TYuU/ccL5Lp3nEk/8gJSL krMIc/chfP6v2IyOM9ikncH20bE3JWdqsV2bp4A4fj6UZ24Uhc2NTJ4avszq vHaja5QBMHvSy+C1bBL7+xw+t4LNqQM9Z7eJMz50/+3scjo7bdLrA6E8J0DU Gec0n33d0skQ5ruoTU57XdEm8FkzEwpSFa5nczN8TuPmNI6+qybtnHrz2oJY 5vy0IMbrBRkhzJ3ltG+vSgNtVhhocyJgO+3ZLvKMc9O4+b4taqjKjxdckMBs KE1xec25s9j80I4ywufpFtn8/UNG1ws+LPjovlqoJvdjjE799hZ6/Z/kdR7Z rUsrqFMHhBqUfLBe7R+kUyt8alWK8XpV0L1mZrahUCgUCoWSr3pz58bK326+ 7DIJ1+U2OnLkSDXlc6MdyXfHGWzymcF2ZHeFpDxdme0DmVErRH/cpOBFUJSy XhQ2p85PEvqxW8vmpnnt6VGrYNwrz0Nm9Bob+Dyque9bFGTHroNu3bq18Pn4 US+2xMsrcgJb5qc1aKNEYXNjvfmKeeMgN8H7nBnn6dGesHHNLGisSJCUzY15 7XTu+R5D1jk154biBNBmk8+gNAmyE/xgtz4TKtWbQJkcwGac7yW36yinXadN gJLcSCjNjYJdtVmisrmluPn+LRqoLthMnMh4vUITD2WqONAVJ5P7FLu85tz+ uHk6i53byuZGJt+3rQTqK3IZm5v6w7e30uv/Iq/r6F5DRiH5fw3RqfhAg9I/ QK9UeOvVAWP1Kl/C6hOR1VEoFAqFkqfu4IQ68v9xwrnt75wQO39cykW5o955 550Zpnzuqnx3V9Wkyy3f3VUz2Gi/uH11OZIyenGqF8QHLLAiL902JwQugBjF PPK4CofY3Bg3p7nstrK5Ma+9Lj8UVs4bDXMmvQx6dbDVsXPK59S+a2awfnBj X3kBdJrQc3Las2M9YcqYQeDvMYv97SibU28vj4fJowebnXG+lVwXtGE+pESt k5TNqSmbq1MDzPaDo4yenx7M8topq9OZazRuTuvN6d90vnmlpvOcdkNxIpuD rs2OaNOrXUw27yhuvtugAm3OJijIioT8TBNnRYE2Lwa2VmWR25W6tOa8PZsf 2lkOxcoEKMiOgcPkd3vZ3Oja0iw4/pahDZszv2P0NnL/hl+O7CrZt7s6KYv8 f/OCFf46lcKL1qvX5vH3IKujUCgUCiW5aD0arSGnteRnOIHLj3FCrPwKCdfl 1jp48ODFR44c+dWZjI4z2MStSbc23/3nH79jMVcpGZ0ydMd56fY5JXQJYfS5 7LFTw5awy+xhc+r0yBV2sblpzDwjajW8MuQpNtvcWjY3zjbvbMY5/QzTo9bC nMnDwWv5VKjXRtnN5kbPm/4qbC2JtTjjvDw3FHjPuVCQ6i8Jmxvz2reUJkKl KspsP7j6kkSW507z2g3aBBY730dz3Jtj59UFcZC9WcG8szaz05x2XdFm1qe9 TBUNWyvSnM7mneW007g65fNydTyUaxKYa7TJoCtJIz9ToLowCWoKk6G6KBmq yO/U22vzyGOUO5TXThncUJoJhrJM0BPXV+a09mp3kM1ZTjv5WVmUZpHNqU8a faSR3u6XHbW5b2XEeBWH+86JK83YEGhQKfz0Kr+1ujzFSH0OfxsAXCD1sbSL aTDxduLbpF0GCoVCoWSqWzkhVv4lJzD5P8RKDmPloonwuIowOlBLzeg4g03c GWzfff0ZY0spGZ2a9nejTC3eY/KQFLKYxcyrsoVe7AlBiwirL4Wc6FVshpo1 bK5J9GR94hxhc9Oc9mCvOTBmxHNsXppYbG6a165O3ggzJ7wMc6eOBFWSj11s Tnl85oRhsMOY395BvXlm3AYI810MJdkhLmdzY9xcnRposVf71vIkVn9OY+f7 yd8FmSEsf900r53+XpAZSjjdH/KSA2BvXa7FmnMjkzdWZTBOL1fHQlVBvMvZ 3J6cdnr5Lr2KrDcJytSU5zdDqSoBipXxoFXGgTYvljgO9KUZUEe420B+VhK+ p7Fx6vL8JJa73lirOiev3dwctXP5vHM2N7pam2EVm7fx0e30cb+pLEjYnRS2 Kifce3YstWrz2kCdWuFB9gmv12t87wbAPvAOis6j/YL4B+IbJV4LCoVCoeQj mrfWPlb+CSfMML9WwnV1SREWH2nk8/aM7mhNutzy3c/HGWxfnDrOmFRqRg/2 nA5xAfMhLXwpFCZ7OsTm1AVJ69jjtI+b1+T5Q07MasiNXQO59Gfc2jbOa3Y2 ua44zVs0NjfGzXXqEFgyexRMGzcYqpWBorG5aV67Lj8C1i+bAlPHDoENK6ex OWrm+XzzOd64aibr3W5LL7iceG8I9JoP+Wm8S9ncONu8UrXJYq/2reUpUKHe 1BI3p3nt2uxws3ntBxqUhPeDISeRB01aMBzYap7PTWPnB7aoIT89FDTEBZnk 865Ilx2bO7MfnHVs3gmft6s331KtImsy2MTm1B+1eAd9ri8O7SioyYn3jAte Pz02wGNaXJDnjJjqbL/ldfn8YIMq5Hqpj61uqhxOOOeaJ/VCUCgUCiUL9eME Bv+IE44P/xJriYcS43fiTlJjY+OF77zzzv8cZXScwSbfGWxyYfRNfm+wn3Rm WnLoYlZLTmvUc2NX2cTnNG6ujFsN2lQvu3LaaT57DL8Apo8bBMXpPqKxuWnM XJmwHsaMeB781sxgf4vF5u3z2vM2e8OzT/SHKWMHs3lp65ZOafHKBRNg/vRR 7PI3poyEGROGQZT/UjbrPC/RB8rzQm3qBZeT4AOR/stAlaxwCZtT76rNaJ6l ZnmOml6bQLy5JW6+W5cFypTADvPa99TlktsEMRdkhsFb7fncQl57Q3kqaHOj oFQZA+WqWNhbp0Q2tyF23iZ+biebMx8T/PGxnWfeP2j4iHy22vJsvyDv5RMS PBaNSfJbPTm2VqlYplcHDNGp+ZukPs66icZywrlXrdQLQaFQKJSkonVjlL8p h//NCceGTzmB02+QcF3nld5+++1kwuhAbYnT5VSTLod8d3ebwfbpyXdsno2e HrEMEoMXQV7salH4nNahZ0evPOdyGgennE7z1FPDlzLT2+W0c0LzbSjXazZ7 mK05t4bNjfXm1Xk8LJg2AhbPepXcN1g0NjfNaY/yWwCjhz9Hfi4Unc2NriuK gtEjXoDy3BAoTPNvcZUyDLZXJJzTq526OCuIMXpRRgD5PbAdn3dcb16UEQRR /HKID13DbucsNqem+e179FkW2dwYN89PD2Fcbho3p/PUaB16Z3PUKJtX5ccx 0xr0fQ0qq2vODSXJrB875fXivGjYXpONbN4Bmx/cWQk1xZnWxc47Z/M2Jtf9 fmxf1d7durTk6lyFN792avSGpePjI31mhdUq/RbrlPzgrXnBmLNtXn04oY7w ew7PvVAoFOp81dWcwOAfcAKTnyWu5gRWx76sLtahQ4ceMvJ5R4yOM9jcpybd HKeX5GfC8jmv2szVZRnekBm1nM1My9q0gs0jt5fRadzc3rx2cr4N86a8DDW5 fvb1g7PQpz0vzgMmvz4A4gIWicrmxpx2Nu98/RwWT49SLBKVzY057dWqMJg2 bqjFmvP2vdqp64tjICtuA9RqIkGbEQjKJF/YSa7vmM9b4+bbK5IIp6+ACL+l kB6zgV0uJpvXFsZCSU5Ep2xujJurUgLPyWmvL00mlwdZPUftrW35UKaKYfXn lNVpfNyWmvO60lQozIqEgqwI0KSHsRlqFvn8PGLz9w41QI2W9ptTOpTXbuTz 9mz+8bu72pjc7mfy3ry5V5+elB2zQuG/dkpUuPesMINa4UG8wKBRDKrO80FW b5WaE87FZkm9EBQKhUK5XMZY+Z+ccCz4hhP6v90l5aJQLIa+R0xGxxls8pzB Vl6UBWOGP83qt+3hZNqTnca2aR057dFG49n0J421U3anc9Xamz6XkM++EKpz fO1ic2NeO82FHzviWYgPWGhXXnt7PjeNmQd7zYbp4waznHex2Nw0Zk4vD/Z6 Aya+NgC8lk+B+sIIUdjcWG+u8JgNWbFeVrG5aV57cWYQ4/QdlYmgSfUHdYo/ WUuCTf3gSnPCINh7EYT5LoHM2I1Qp42zm81pvFyTGgiV6mir2fyt5trzHdUZ 5+S076nLgdykAJbTbuuM8+r8BJbPXpAVDg3laTbXnDdWZxNOD2fOz4hg3laV ZYbPux6bnyC3rynJhPKCVChVJzNGF4PNO+PzT959U/BxwSePbP+avLf1dYVR keuXjIsNWT8zlOxP1uqVijUGFT9Lp+afMWTyfaQ+Bkuo8ZxwPlYq9UJQKBQK 5TJdSryK+DjXGiunvd9oD7iLJFwXykSHDx+eRRgdpGB0nMHm2hlsb++pgWlj B4D3sgmi5K23srsw95yyuymf0/i7/Y9rfsa5z8rJMG7kc6BN22A3m5urOa/J C4Sls0fBqvljyPWhorF5+5z2rJh1MH3cEHhjygjC1OscZnPqem00zJ8xyiY2 N+a0bymNg+x4b8LVsYzLq5ThoE5WQHlumE394Oj12swQSAhdA2F+SyEzbiNk J/hCXqICijKCYUdVyjlsvr0yBYrIfXLoPLQEP8hN9Ie9dTk2sbmRyQtpLbmF OWp0zjmNp9s747y+LJXFxJUpIVCUHUVuX2hXzbmhNI3NOC/KiYZSZSyUqeKg qiAR9tRrzPO5zNn8+AE97NDnQ1l+MlQVpbEZ53UVudBQrRSY3I5e7fayuTk+ /+T4bjh1QjB5/M9qi5L065dOzizL9F5H2Hw1tUGlWEVYfVJtDv+INom/VOrj sQtF+/7QOMnXxNdIvBYUCoVCOV+PEKcR/8IJXE7rmmis/F4pF4UyLzoLnfD5 j5TRreV0nMHmPvnu7WewnTy6izDuJJhOON0xfj7X65eMY49bQtjZsccyz+ZG l6R7E8YdSJ5vvChsbprXnhK+Aia99hIkhiwzz+cizTfX54eD75oZMH38UFg8 6zXIT/W1i80pj9Na81mThtvM5qY15yVZQVCQ2tqnXVcYDRryd3FWiM394Pbo aW+3cCgi99VmhUJjRTJUazaxy2jPtzLioowQKMuLhO1VqWZnqNnC5tRFWeEd 1ptXamKZbWXz9nHz/Vs0kJ8RDqq0UFCnhYFem+xwzfnW6mw247y6MBkq8hOh XJ0AJco4wvExbD5afUUm7N9W1I7PxWNzevn+bSVs5nmpOhFKVJuJE5np34KT BGuSoIT8XaYRmHx3g5Yxe/t6czmwuSmfnzqxh5lc9q8qPepDQ0misj4/cC3l c72SX0mtUytW6FSK6QYN/1RDmtcVUh+bnawiTjg/myr1QlAoFArlNF1MvJD4 ICfs86nf5IRYeS8J14WyQocPH4428rnYsXQpGB1nsHWc737q/begIMkTxo18 FnxWTBSV0dUJa2H8K88yVqdxdbHZ3DSnfeOKSTBmxLOgSvAQhc2Nee30b59V U2HKmIFQkOJtQ+zcvj7tVaoQ8Fw6GcaPegkWzhwFMfxSwu8RVrE5/XvhzNdY fru9bG6sN6/TxkB2/EbYUZnUEjffTn4vSAtgbihJsKsfXBVh85KcMCjODiM/ w8nzJJxTc27kc3vYnOa3N9D4eAe94CiPb61II2wdZjebm8tp31KZAer0MOJw ZprDLmY/uCO7K2CnXsnYXUt5PdfoWNCVpBOGjgdDmTDbvMXlWW1M55vXlWez Wed6cn0ZYexqclkZ4Wx6GeVxyuaU0RmzO9gLTq5s3uL39kJVcTZ89O6uP98/ ZDhAtrMkgypgVa3SjzG6QcUvNygVywy5fpP0+fxDdcp1l0h9jBZZkzjhHK1Y 6oWgUCgUyil6kBNi5T9xwv7+1+a/H5dyUSjbdOjQobsIl591FqPjDDb5zWCj jE45N3DdNHh92FOwOWihqJwe5fsGYednWH26M9jcGDevylXAwhkjYOqYAVCe 6eswm5u6VhUM86ePhHlTR5DfgxyMnXdeb7528STYuHI6xActh3nTXoFJowex 3m9L5owG/3VzIMDzDWY6Q23JnDHkNq/CzInDICVircNsblprnrvZB2oIU7eP m+sKY6AkOwS0mcHn8rkNNedbSjezODo1ZfbCjBAoV0ax3PaO+NyUzXWE8fOS A0CdFmwVmxu9r0EJ2Yk86wfnKJubi5vTvnC01txYe76V1pzLqh+cc/u0uwOb M5Pfa8vyoOm9fczkvj8eP1DTEOi1IG/k0GdqY/zmKQxsThu/lOyLFteoFK/q Vb73arW8u9fmXUf8LfH/iPtKvBYUCoVCiacenNDr0zRW/g4nxM8vl3BdKAdE mHybKZ/LPd8dZ7A5nu/+1ekPoYFwKO39tm7xWFabbhtPd2za733Z7Fdg6AsP s7i62Gxu6vzE9TDuledg6exX2e0cZXPTnPaCZG+YMOpFWL9sknCZA3nt5vm8 Nac90m8RY/NGcl3rHLVNLbPTEsNWQ5T/ElDRnut21JtbM0eNcnlJdijh5kCz Oe07q1OgMD2IzVvTE2Z3pFe7MW6+pSwZNGlBUJARTLg9kvD6JihXtZpyuDI5 kDiA/aR83qYfnJV92mnMnM5Vy0kMIPdVi8rm5uLmhrJ0yM+MbHFJXix5/BKZ 9oM7P9i8qdmGSo3A5+8L/vT9/dRnSzUppx+4/95fn37ioSNL54xOqsjauEyn UiwxKPnF+jzFoto831G1efw9B9PSekh93LZDlZxwzjZa6oWgUCgUShTdzgl1 5PR7V7p//53DWHmX0aFDh0aY4/OukO+OM9gsx9K/+bIJthF+NPL0xhUTYca4 gRDpM0fUuvTnHr8PJo56nnC0h+hsbprTHuHzBrwy5EnYHLxEFDY3zWmPD1oK 4155AUI2zBWRzc+tOc9N8Gaxc4HRzee0J4Ssgg0rpkNM4DLYWhIrKpsb4+b1 xbGQHe/TYU57Q+lmwtWBLH+9rjjeLja3N6/dUj84i3zeLqddlRoCu3Q5TmNz c3Hztxq1oM2LYX3iqAuzo0FXnMquk3M/uK7G5pTL66vz27N5i4++tRVeHzXi 7A033AC3337bXy89++ib/NrpwXqVYpFgfqFeqZin1yiG12j4OwD4blIfw63Q dE44dyuQeiEoFAqFckgXckINOe27foYT9u3vckKs/EoJ14VyggiLH3YFo+MM NnnNYPvu6y9gZ1VSG2be5PcGzJ0yFBbPHMHmqjnK6Kr4NTBi4GMwYtBjsGDa MCjP3Cg6mxtz2g2aIFi9YAz0v/dW8F01VRQ2N81pj+EXw9Sxg8B7hTArTUw2 N8bMlYkbYfm8sWb53DRuTvu6bVw1E0I3LoBi8rtYbG6Mm++sSoHMWG+rZpzX aKJZP/bCjGDYzvq1y4jNLdSc52eGs3i6K9jcUk77vi0FUK5JIN4MVYVJUFOU wurIj7xZLgs274zP3ZHNqfUVKrNs/ukHB5g/enc3TJ8yASijU994443w1OMP fz59/Ms5JWley3RqxQJqg4qfT/Zd03Q5Ps/osr3l2gv9JuIfib8ivlritaBQ KBTKPt3CCbHyLziByf/hhPnlL0i5KJRzRdh7hiU+xxls7pXvbusMtl9+/gne ebPsHK6uzPZh89jo7PQJrz4H/NqpJmxtm2ke/fypL8Mbk4fC5NdegLnkpzbF yzKfOzDfnLpWGQAjBj0B9999C2wOWiIKm5vGzdM3rYVXhjwFTz96H3gumQQl Gf6isLnRU8cOtcjm7fPaa9ThEB2wHAK85kFGzHrIT/V3mM2NppdrUnjYbRo/ 7ySnndaWq1ICQJnkD1vLkmTJ5tT0stzkwA753Jlsbimn/ejuCta3XV+a3sZ1 FVnkvpWyYfNO+VymbF5bpoTjhxstsnmL3z8A61YvbWF0o++44/Z/hwx45kCg x0xFzqaVKyqzvBfQeLpOzc/VqQMm1yn9nq7M33it1Md0E1Vzwrnca1IvBIVC oVA26QJO2HfTWPl/nLAvP0XsxQk9RVBdXAcPHuxBOLypI0aXc006zmBzvCb9 wyM7oTbPH2py/c7h62pyGc17nzluIEwifL1o+nC76tUjNs5mc9jUCR7ksQbB 1DEvQWr4Upti57b0aVcnrocnHr4bhg94HHiPGex6R9ncNGauSd4IwwY+wWal zZ40DOZMHs5mp6Vv8gBdfphNbK4viISYgKUwY8LLEOaz0Co2N81rNxRuguRI D4gNWkme3xMyYr1AmxnYls9tYHNjTjv9qUr2t7kXHLU2O4zNOFcm81Cp2iQb Njfmte+pU0KZKtau2Lkz2LyjnHbK5g2V2WAozRBcltnibTV55La18mHzTvnc 9Wx+9EAD6MqtY/PTH7zFTH9funDOOYxOfdNNN8GwIS99NnfqK3kLpw8LI/vF eHX8msUGleINvZKfo1MGvGbI9+tfncZfLOGhfQ4nnM8pJVwDCoVCoWwTzcei DH6SE/bh/3JCrHwosTvUVKFEFGHuNZ3xeVeoSccZbJbz3X03boCr+1wJE0a9 0CF/FyZ7strymeMHMWafP3UYY29r5qoHrpvOTGPmVdk+4LFwDEx49XnWp47G 5x2JnZurN68vCIU3Jg+DNQvGsrlp86YOh5xYD4fZ3JjTTn/OmzaSxdS3lUSD OmkjhHjPgwUzXoVp44bA1LGD2U86P43OQ6Oe9PpAdjll8dmTR7C+cCvmjYPk iDWwpTjGZjY3zWtvLEtgnJ4d7w2GohjIS/RlMfXC9ABoLN/cAZ9bnm9epY5i NeaO9IKjfeAKMkKgOFuYhb69Kk1SNjfGzbXZUaLltUvVp/3I7io2R622JJ3N VKMz1CoKUtgctVLVZjZXrVGnhqN7a2TA5p3wuYhsTv/eWV8KW2oKYe/2qg5z 2tuz+ekPBX9Kfl84b5ZZRjf6kYf/7++ZU8YcGDbwCdXDD9xeNWLgoxmq+DUL 9WrFbJ2Kn1WbpxhNWV2rXdPbhYf0mzlhvs5p4q4+0x2FQqHcXTRWTvmbcvhf nMDldP9NOf0GCdeFkliEsS8h/P2dqxkdZ7DJZwYbfS/GjxtnnM0A9919K0wd /RKEe8+Gqhxfi8xdkbWRzVWjcfXZEwYzbp/y+oss1k57wxk9fexAxuI50SvP yWlPj1wOcyYNhcmvvwT82mnk+fxszms3x+c0n53+Pvn1AVCVG8DsuWQiTCN8 vGjmq5AVvdZuNjea/j2dMLi1Oe2U4b1XTYeEkJWwldzH0oxzW9ncNK+d9nhL DF8LmhT/lth5eV4Y671O+7PTWWnUW0sTLPL5rupUqMiLgOwEX6gvSXCoT3v7 uLmuKB5K8yKbHQX1pUkuZ3PK5dqcKJfUnEvZp/34AT3sqiuAysJUKFZuhhIV 4XbC7nT+eak6SfibMDx1WX4y7NDnw7F9Ohn2g+uYzY8f2gaGSjWbn0bnnBsq 1OS5d1nsBdcZm5/+8CDzxyf2woAXn++Q0anvvuuus7NnTPx8/syx1bfd1G/3 Xbdd3zh97IDI8vQNcwxKxcxaNT+tPj9wQK3G51atVtvdiYdzep5H8yHPEr/s xOdBoVAoOYjmKU0mzuaEXmm0j/nfxJ8RlxCPsvJxLiX2Jz5K/Bvxz5wws8yD 2FkzNvtwAoO/zwnn3nS/TfffNK/dmccJlBuJsHewNXwu93x3nMHmWL57UVER XH/9dYzRaR7nZZdeCj17XgSPP3wP4+/QDTOhJG2Djfnt1vWDo79vDlrEWH0a 4XmPRWNBvXmdXWxuWnOeEbUaNq6Y0iavvTKHB7/V02DmBPpcg8Bj8QTIJLxO e79Zy+aVuYEwe9JwiA9aZnO9uTrZB8J9F0Ji6GrQ5UeKxuamOe1bS+MhO34j 6AujzcbNa/Kj2GxzU+cl+kEOYXKa164r6GyOmji94BorU6GMcHqZchMzZfYK dTR57DxR2Xz/Fg0U50aDJj2MWadNkrzmXE694Ojfuxu0UKPNYKze1intnMpc bnRBGtRV5MGerSVwdL9B9Jrz9w43wq6GUthRVwzb67TkZwn5Wcy8VVcEb24t P6fe3FE2P31S8K4tFXDbbbd2yujGfnKvjBjyx7oV8/c8/vC9db0u6vHD9f2u OjzspUdT82JXz9WpFNPr1AGTKavXKX1vB/FZfQEnnOdlify4KBQKJTfRvKRf uda535ZcRtyrg8ehOUcfm9ye9kY/a/L3YeKrRFw37etGY+V/Nj/+t5zQ/+1u EZ8D1UV08ODBK6yNoXeVfHecwWY+lk7XvHjxYrioRw9YtmwZ1NXVQXBwEIwY Pgz6Xt0HLrjgArj15uvh5ZcehSUzR0K031zC7F6izzhXJXiAx8KxMHP8YMbs K+a+BglBi6Es09dqNi/N8IOJr70EsQGLO8xrz433BK/lU1gt+dypIwRuHzcY ZowfyvLVqRc2e/70V2D+tFdg6ZzRUEz7w9nZC47GzOl880i/xbA5ZCWUZgeJ xuamNec0z12TyltVc95Rr3bbYueO1ZvvrcuF4pxINgNdQ1yQGdbM79FQqYmF qvy4do5nLs6NYtakh5L7hgo/iVXk96LsKPK4Spf3anc4di7nXnAmcfOj+/Sw e0sJGAinlxemQ0V7FwmuLMpoa21mixv1hbDdoBVcZ3Qx7G2sJFy/y6Z+cGKw +WcnDzF7rFpiFZ+b+tWRwyA5PuzLRXMmv3npJb2/6t6t29/XXXPl4ZdfejhF mbB6jl6lmKrPU4wl+73Hq/P5viIcxm/lhJjPp8SXi/B4KBQKJWfRmDflW9rX fBPxCOI7mv068X6ulbHTLDwG/Y70ba6Vk8cS9+AEnp/NCbF0el2tCGulc9AO cm1j5XReWk8HHxvVxUU429cWPpdbvjvOYBN3BtuuXbvgkUcehhuuvx4KCwvh 7NmzQEXfJxpn9/DwgBeefw6uuPwytv+79pqr4alH74dxI5+DVfNeg1j/+SzW LtYctdIMXwjfOBdWzhsNc6cMY/XkMycMYfnrRtN68/nTRsB8ch39fdW8MVCQ 7A3KBE9IDF3OnBK+EnTqYJvy2sWaoWbK5qY57QWpCogNWM7q0FMiPWBbaZwo bG50fTGN2fu7iM0t8LnE9eZSzFFzWl67zNhcbr3arYmdW8vm1PXVhTbzudED B7wAWamxf/ltWPXuNX370Fln0OPC7r/edsu12yaNejG0NNNrmk6tmKxT8WNq lfwTdrI6zWvfygnnfEPEPC9AoVAomYpy7RxOmAtuTpS967nWPmvm5kzO4VoZ /iUz108zud6efevDnPDdwM/Nj/E9J8TK77PjsVDnqWgdOuHsr9yB0XEGm2tm sNHbxcTEwNV9+sBjjz0KW7duBXOir7m+vp7ddv78efDUU0/C5ZcJ3H7VlZdD //vugKEvPcbq0Gk/uBjC7gXJ6+2eo9ZZ3LyjXu30djSXPSlsBXN61BqoKwy3 Oq+9PZ87yubGePn28njIjtsAFbkhkBXrBWmb1kF6tCc0lMSKMuOc9owryw2V hs2t5HNkczHz2pHN7Y2dm7I59VZDid18bvTzzz0DmamxUKhO+/nZJx/94oIL LmD5k926dfurX98rDw154eHEvLhVM/RKxcRaleLl2kL+nsYcvqOcTFMt5YRz v1SnnSCgUCiU+4nG1I18PdjM9Y3N1+2wcH/63aexl7q18zBoTbxprJz6EPEs ruM8exTKoghvr7KVz+Vek44z2ByfwUZfw+rVq6Fnz54wfPgw9nlbI/r6aBw+ JycHfH19YcqUyfD444/ClVdewfZZvXv3gjtuvRGefrw/vDr0KZg9cQh4LhkP m/zmQV78WtCpAkRlc3P94BqKIiA3fj2kRq6C7Nh1oEnyBuXmDc287mDs3Eo2 N81pL8sJBm1GAPt9B3Feog9hdU9mTcr/s3cncDLWfxzAf67ckis5Imd7uK+S agnpIBJJJVLSRRHK1SZK6CDkKkWoFeVI5JhdN60Va6Xr30QHid115Pb9f7/P M2Nnx+6aZ+aZeWZmP+/X6/NSzI5nTvOZ3+/5/Uby5SZ7tcf5ZzNG0dK540zr 5ptXzKJ1X029lOXz36Uln76jZfGc8dqa7QtmvqFl1qSRNHPiCM5ImjphKL33 xqBLGT3sucsyYtBT9MqLvTlPZGTAk5dl6MA+9MaIfo701zOyP73zxmCaNG4o fTh5FH08dTQtnD2Bvvz0PVqxcCqtXTKLNnzzCff9z8K4m7v3c3Rzb8fO9+3a SJ3uu9fnfu5M0yaNaOqkcbR+zVLq/mCntPz58zn3ttW6+rVlSia2uqXe+3Mm 9u++cu7IzivmxLZaOTe2RkpcbHZrFNVQ+hzMXzhFA/RRAQAgFDRT2Y9/y/i7 8/13SA7XMdFxmb+v8HdFKX2sPNVx+ROO/29k+KgB3HCXLZiUlLTfnx09mM9J xx5s2c93l8jj0q1bN8qfPz916tRJ+39vyfElJibSokWL6O2336Z+/frRPffc TZGRN2rr0vHTUTvXvUzpa7T15Js30Tu8zGl/4cmO9PqgHjT1jefosw9ecexv brybZzenXdZ++2TSEPqUu/q8KUO1Xz+fPlzbR828ee3ZrwW3YNqrtCru7cvG zdcsfI/mTJH120bQPL7M5zNHaXuozZs6kr6aM1YbI3dmydy3uM/Hauefz540 jNYuft+jbr5m8WSaN30UvTt6AA3p35N6du9Ad7e9jRrWj6bKlSuZ1lOCJTVq VKNaNatTowZ1qflNjSnmtpvpnjtbUuf72lH3Lu3piR5d6LmnHqGBzz9Owwc9 TW/GDuD+/zJNmTCSPv7gTVrw0du09LOp2h7lW9csCMJufoV+jm6eZTf/KXkT TZwwmurXq+uX512D+vXovQljKGH1UnrskQcvXHVVAVmT6NKaRtzbj1epWG7t /e1uen3RzMEPrJg/sv3yj0c0WjwnthyRNqYjZD/cjUqf197Smk8NAABBS9Zf d675Vs7tz+qpjPfcu3O4jidcLlfK7c/kXHU5h3yjy2V2KX38HOuAgKm4n/f1 tp8H2znpwTDfPVz2YHPm5MmTtGPHDq2fS0/v3r279niaTW4DPxfpq6++oilT ptCIESPo8cd70V3t7qTo6EgqV66s1t+VNu6k9/jaNaTHR9M9dzSlHl1ac4+/ n0YP6UlT33ye4mYMp2+1eezG91GTrI4bT/OnDuMuPEzbJ03+W8u04fTFrFha x73dm3nt7v08/stJ9NHEl2n1wncNzWn/ev54WvjhaPrio9Hcz9+ldV9OzvJ8 c23vtDnjaNqEl2nUy0/RM727UucObejW5o2pJndVq/tyOEQ6f726Udz3m1Dr li3ovnva0ENdOtCTPR+kF57tRcMGPUNjXh1A7701jGZMGk3zP3ybvpw/hdYs mU2b13xOu7nLB8d6cLmrm+/cupqmvPcmde18n8drtvuaunWiadwbsbQ5YQU9 9mg3KlAgv+u6wZe6+vUVyqzpeOfNo774YFDnb+YMv3vl3BH1rr666CuOy7xv 4UcGAIBgJOebH1T6e+RnWfz5XSrjfbZuDtfjOkc+2uX3ZWz+N5VxfrusE99W 6d+bApiOq1Fe7tnbfenowTzfHXuw+T7fXTq6ZMuWLfTAAw/wZ8oC1Lp1a1qx YsWldeQC4ezZs9p9u23bNlqyZAlNnTqVRo4cSb1799Z6fN06UVqPz5s3b6Ye X7P69dS0YSS1ub0Rdb7nVm3N9oF9u9CowT1p0ujnaM77Q2jpJ697PKd9ddwE +mz6SFrwwXBaMG0Ed/jhNHfyUPp40sv04buDtfPIJTPfcWawltncw+dO4Y7/ wUj6bEasloWzXrvCenBXntMu/XzOlFdpfOzzNPDZR6jHg/dS21a3UP26kdq+ eVb3V+TKuYH7YVTkjdS0cQNqeVtzuveu1tTtgQ70eI+u9Hzfx2jIi0/R6JED adL4kfTR1LEUN+d9Wrl4trZH2u6ty/0/rz3Eu/nPyZvpmyXzacLYWOrJvbhR w/qWPt4RETfS6NeG0rYNq+i5p5+gq666Ksu9gvg97EzZ0ldvrx91w8f836cL Fcx/4J0Rj0WtWDEJawADAOhkzThZH13eN//hVMjiMl1VxntrjRyu61aXy93s 8vvS/3/ijORU9P2QAa6M+3VzzsVAdPRgnu+OPdiuPJYukftdzk+/+uqr+XNm BE2fPp3++++/gPX0Kzl37px2/2/fvp2WLl1KM2bMoDFjxtCLL75Ijz76KLVr 144aN2qkzd8uUqSIy7hVfipbphT3+SrUpGE03dnqJurSoRX16taOXujzAI0a 0osmjn5e6+FLPhmtdXZvx82NrNUue5fLXuVvj+pHr7zQk554tBN1uCuGbm7a gKpXu8HybolYnxtuqKp9P3VL86Z0V9uW1OX+e7Vu3/+Zx2n4kOfprddfpqnv vU5zZ71DX302ndYtn0ffJXxFP3Bv93XsPJi6+U+7N5Jt5Rc098P3aezoYfRE r0fo1ltupusrV7b8McoqtWrWpFcGv0jLv5xP97W/69J3i9mldKkSie3vaPLa Z5Nfuu+bT0c0+Xp2bPnY2FiM3wBAbiXvf3OV/h55WmV/7o+v/RzAEtyv5/na z4Ntvjv2YDN3DzbXji6R45swYQJ3gxuoTJky2ppwcttCzalTp7THTZ6/sv/7 vHnzaOLEidoc+2eeeYY6338/3driFoq4sbY2Pp8/fz7n+k78ebkk3VClEtWN rkUtbqpP7bjTd24fw53+Lur3RGca+sKjNHb4UzRl7Is0d8pw7vVvZOynxn18 7eKJFDfrdZo2YTC9MexperHvQ/RI17upXesW1LhhHapS5XrLOwQS3qlZozo1 bFCPbr9VH7d/qGtHeqr3IzSwfx96bdgAenvsCJo55S36fM4U+nrRbFq28COa P3sSTX//TXrnrZH0riPvvz2KZk0dxxlPH34wgS8/leLmfKBlxZef0DdfzuHM pYRVX9DGNYu1JG78mnZvX63lh522bLv5L9zvkxPX0tb4ZRTP/XvhvBn0waSx 9NrwQdSndw+65642VK9utOX3pbepWrUq9Xu2D302d5b2OKgcOrokX768JyqW L72mQ5tmI+KmDWr3zfzYums+eSOr/YQAAMKVdPNPlP6+eIZzTw6X9XV+O4Al uE9X5H5yPFQ7ejDvweba0YNtvrvRPdjcO7qMm8vvyZ7pLVq00Mag7777bq3j yp+HK7lP5Xm2adMmWr58Oc2ZM0fr9LGxsdrad4888jC1u7Ottk9d9erVqHz5 a6lkyZLanINSpUrRteXK8efy6yzvBQiCBE+uv74y9e71KL015lWqVKnCFXu6 0s9XT7++YtnlXe69ZdCyD4e1+HresCpx2a//DgAQDmS/809Vxrh5Tt1ceLM+ HL7zhKDA3XqYGf082M9Jxx5s5p2T7trTJfI4yjh69erVqXjx4vTYY4/RmjVr 6MKFC1ZX6oA6f/68dp/Lc0ee/+vXr6dly5bRrFmz6I033qABAwZQz549qWPH jtSyZUtq2rQpRUdHU40aNfgzOsbMESQ3R+bjv/Tic1S61DUedXRnChTI/2+1 yuUXPdI55jlZU27FR6+U5bejPNn8kw8AEIrkfPPPVUY3z6lvO7nurzY4h8t5 ur8aQMBs3ry5MPfq3wLd0YP5nHTsweb5fHdnR5fInPH4+Hh66qmnqHTp0to6 ZYMHD9Z+T9Z5gyuT+16eJ/Icl3Pppd/PnDmT3nzzTRo4cCA9+eST9NBDD2nz FWJiYqhZs2ZUp04dql27NlWrVo0qO9aGu+46jNMjSKilRIkSWuduc0cMlSlT 2lBPlxQqeNVfNateN79317aPfTvv9Zqr5ryE/dIBINTJHmeydrq8z51S+nx0 T8U7fs6WzZ/Ld5k/Oy4z1/tDBDAf9+iWZqwVZ/V8d+zBFtg92LLq6M6eLtcV FxdHnTt31sbUZY53ly5daPbs2drtgcCQ54C8flavXk2ff/45TZ48mV577TVt rb9evXrR/fffT23btnX0/GiqXasWVa1ShSpWrEjlypXT5uVfc8012q/ynYus OVC+fHmqyF2iUqWK2txcGfeTdffkV/n/SvyzVvccBAm1lC2r7ycp5wu92O8Z Sty8VtsPURns6M4UK1rox3oRN0we2a/bHVhTDgBClIyBL1X6+9p/St/fzIhe KuN9sUUWf97d5c/beH+YAP7BnXqmmf3cvaMH23x37MFm7nz3rDq6M3Idsi/b 888/r83lljXWZG639MTExMSA7tcGxsljLc9Led3I47V27Vptz/q5c+dq+92N HTuWXnnlFXruuee0tfLbt2+vrUsgc/dlDSzp+UWLFtUed4nsKxXTojE93OUe 6tX9PurJ6durKz3T+0Ea+Nxj9NLzj9HIIX1pxKCnaHD/x2nk4KfptVee1TJ6 RD8aN2ogjR/1Er0+7Hn+75cuZeLYoTR5/HAtb48ZQm/GDrgsYzmjR/Sn4YOe 1jPYmWf08O+98ExPbQ9z17zoSJ9e3bQ9zp/s2e2y9Oh+P3V7oH2W6dLpHm0d tqxyT7s7KOa25tmmaZOG1Lhh/SwTHRVBtWrVzJTajsgaCFZ3TsSzyHwX2cNS +nm9enVoc8JK+ucP/jcseTtVrlzR644u4es8V+qa4ptubRYxYtb4vtG2uNhi FnzEAAAwSrr5CqW/l53lPMgpk0MKZXEdcs76LpWxD1tHpY/Hy3U/xjnu+LOV frwdAF7bunVrCe7UB8zu6OEw3z27jh4M892DaQ+2rOa7O3P69OlLkcd0/Pjx 1KpVK62rSX+Tc7JlXXhZe00uA+FH1iiQsUHlQ9fwNAUK5KcSxYtlm5JXF6dK Fa7NOhXLa4moVY0ib6zOqZFl6kXXppub1s8xrW6/ie6841Y9rfXc264lde10 V0buv1tL7x5d6InHul7Kkz1lH/QeNPD53lpGDX9By5uxg2jiWyO0zJryJs2e No4+mT6eFs+fyvmAViz6iNYu/1TL9oSv6Lv1S2jX5q8v20MtadNySuLfl+y8 lBVaNq1dROu/jaMN3y7MnNVf0Jrl87W12TPWZ8/I8kWfUNzcD2jhp85My5SP pr2Tdaa/Q1Pee4MmTng9y4x/YySNjn2ZxjgybMgLNOSl5y/lmad60TN9H6dn OX2f7EmPdu/iSFd6sEsn6tjh7ku5s00ruqPlbZzbtTRt0oiaNm6k/Vq7di0t NWvW8Hsnr1y5MtWrW4dat4qhOtGR2vO2a+eO9Pfve7Vu/s8fP2kZ/dow014X +fLlPVbp2tJf3XNHw0dWzYkthzF1AAhispa6kfe4vtlcTxXOby6Xu8C56PL/ 33NK+etGAPiKu/Q9/ujnwTbfHXuwBa6j59TTz5w5ox2j7Fc+bNgwbc20YsWK UaFCheiWW26hQYMGaeO0mA8f+uTc+UB1cyTnFC5ciK4uIeeclKDKlSpoqV6t CkVH1tZyU9MG1OLmxnR325bU4e7W1O2BDtTzkQfoqd4P04B+T9LgF/vSmFcH 0bjXX6HJb7+u7a82d9Z7tHjBTFoa9xElrFrI/X4xfb91Ff2QZDNlj3PJ/h+/ 0/OTM4l6ftZz4OcdmfNLkpY/LmWnnl+d+V7Ln878b9el/PXb7kvZzz/z4+4t WpKT1tP2Td/Sd5tW0ybb17Ru5Zd6VumxXcpXer51ZgklrFlOO7as1ZLy/Wat hx86sI++XbFI278xMqI2/fHbnkzdfINtBTVp3NAvz4OiRQrtbdag5oh5E/vV jIt7sbACAAguZvVzUZwTy0nmnOQc4+zgDFL6WDpAUOMuPT+cOjr2YLNuDzZP O7pr5LLbtm2jd999l7p166aNMfHTUlvf/N5776WhQ4dq57XL4yrrpUNwk3MX ZN67zN1VQdBNEWtSpEhh7TsB+S7ghqrXU52oG6lZkwZ0+603afP7u3ZuTz26 P0BPP9mDXnqhLw1/+QV6c9QrNIn7/4wp42n+7Cm0dOHH9O3yBbRx7Vf0/bY1 tG/XBr90c/d+ridZjz2Z/rbvyZzfU7QcvJS9evY784OWQ85wJ3fmj/8lU1Tk jdrrY94n0+mjGZNoQP9ntPXhyl9bLiCPTYH8+Q7VrlZx6oiXujVbHTfkagUA AABBhTvxtdyl//VXR/e0p2MPttCZ7+7JHmxGOrqs9e7MuXPntPtS1jGXPcoe fPBBioyM1MZiixQpop3HLmuaT5o0ib755hvtMcRa8cFBuvkTTzyBbo74NcWL F6MyZUrR9ZUrauup1YmOoCaN69OttzSjtnfcTvfe1Yb7fwd6uFtn6tP7UW0u /OABz9HQwf3pzVFD6a0xI+iDSeNo+uTxtGDONPr80xmXEjdvFq1c+rmeZXpk vHzr+pUZ2bBKyzZHNqxdTt9+vVDL1199RgvmzqQZU9+hCWNfoxFDX6L+zz9F vXp0p7ZtWlLdOpFUtGgRy+9DSd68ef6rWL7UF3173H3vyrlDryPC3HcAAIBg wR26406T13MPt3PSsQeb7+ek59TT3Tu6MzJmLpG/Q/Yfk73F+/XrR3fccQfd cMMNlC9fPq27y15jsi75008/TW+//bY2T16eN3Jbwf8uXLhAPXr00NYXUEHQ PRAE8Sx58uQ5yz09bmj/Lm2WxY2uOH16H1lLCQAAACzGHfodf/bz3HROOvZg 826+u2tHz66nS6QLOiPXIY/z8uXLtTF16e6yV7jsD+7sinJ+u3R5Ocdd9n+T deXHjBlDH3/8Ma1cuVJ7bsrjJMcNxsljIucmoJsjSOgmX7686c0a1Xr5m09H NPlmQWzVFZOexzmaAAAAFkpMTCzAPWVrIDt6sM13xx5sgduDzch896w6untP l7nVzriS+0uedzJfftq0aTRy5EhtH/B27dpRVFSUtte3cvmMWrhwYW0v8Lp1 62rr18ke7n379tXWsxs3bhxNnz5dOx9eev2WLVu05508bnI/5EbyGHXq1And HEHCJJUrlP145bzYpl/PGdYYPR0AAMBaO3bsqMFdJt3fHT0c5rtjDzZz92Dz Z0f3pGPK/SnPpfXr19OXX36pzaN/6623tDXlH3/8cbrvvvu0OfWNGjWiWrVq afslFS9ePNPnWplrX6pUKW2uvezZ1LBhQ2revDn/XCv++Q70wAMPaOfOyxz8 IUOG0IgRI7S9xGU+vvT+Dz/8UOv+ixYtotWrV2v7jsv+4/y6vPQcdD5ewbCH vDxO99xzD7o5goRZalWr+LaMo389J7bxyrmxDdd+MqxiXFwX2VcYAAAAAiwp KalHIPp5bprvjj3YfJ/v7u+O7gu5v+SxlOfad999p3XrJUuW0Oeff6717vfe e0/r4dLJ+/fvT3369KGuXbtShw4dqHXr1hQTczs1bFCfGtSvx93+Bqpa5Xoq V64slbz6am0dbJXD5+gSJYprl6tcuRJVrVqF6kRHaddza4tbqFWrltS+/b30 QOfO1KPHo9rfK3+/HMerr76qHZOsmy/HOHv2bO27AfluQo7fZrNp3w3I61Se 9/L8dj5HhDxucuzo5ggSfilapOAO6eaSVfNGNNIyJzZ61ZzxRRUAAAAEHPfl BeHc0bEHW2jtwWb0nHQrOrq/yW1xPj7y3JLn4e7du2jL5g0Uv+5bWvLl5/TV ogX00cwpNGvaRHpv/BgaN2YkjRw6gIYMfJb6Pd2Lnnq8O/V4qBM9eP89dN+9 renO1rdSy1ub0c1N61PjBtEUFVGTatW8gSpXuo6uK19O2x8rp7Wmq1SuQO+/ NYQ+mhxLU98eSuNee4FGD3uWhg98kvr3fZiefrwr9ezegbrc15Y63BVDbWJu ouba3xVFEbWrUdXrK1D5a8tQieJFtf2gs/t7EAQJXPLly5sWc3Od51y7uYyh S76eHVt/2fTYIgoAACAw5N+cuzjDOYs5v6uMf7MmG7ielpwvOH9yznD+4azm PGTmwfqTzWYrxN15e6A6uqc9HXuwhc58d3/vwRasY+mh7Pw5vq9Pn6TTJ4/R yWNH6NjRvynt3z/o6KHf6eD+ffRTynf0w/ebtT2mNscv5/9eT7//uJ1++2EL /S9lI/2yO55+/t5G+xJX0b4dq2jPtuW0Z+sy2rVpMe3a8AXtTPicdq6Py5Tv 1y/Us2EhJfGfr1/xCa1aPJ2WLZhM82eNo9lTRtMHb4+g8a8PpNdeeZZefvEJ 6v/0o/T4I53ooc53U6d776C2rZpT82YNqEG9CO791alShWupdKmSVKRwIcu7 DoKEQmSvtRLFC2+uVa3iO+OH94zJqpuv+GREA8nquLHYMx0AAAIlRmX/75en /fxdt5876/b/0vvzm3nQ/pKYmHg99+ZDwdbRg/mcdOzBZu0ebOjowe/CBX6M zp3Vvgc4c+oE/Xcilf47nkrHUw/RsdSDlHb4Dzr6z3769+//0b9//UqHDuyj g/v30l+/JdOf/9tFf/yyk/b/uJ1+/3Eb/S9lk5af5XuB3Tb6ceca2pf0rfb9 QMq2ryll+9eUvGUJbVm9gNYum00rFk6nuNnv0McfvEFT3xlJb48ZQrGvPEeD X3iCnuvzMPV+tDN16diO7m5zG93eoik1aVSHom6soc0nkL5fongxypc3r+Vd CkG8zIX8+fL9W6jgVT+XKlls7fUVy35cL+qGUZ3vuemxuGmv3Kyt2+445/yy cfN5sfW/+XB4bduXsSUVAABA4MRwjnLWcMZxunH+Vvq/a5708xdUxr+DcznV HL8v3zX3V/pYuvzZO2YetD9xT27Lvfl8qHb0YD4nHXuwBW4PNnT03E0e9/Pn z2qR7wXOuuSMhzl7+j86d/a09t2C5N/D/2ivG3n9y/uGnKu/adMm7dz9pUuX aufyS2bMmKGd3z958mTtfH+JrAsoawBIZE0ASc+ePbW9AnKKnO8fTJF9DLM7 1kceeeTSbXOPcw2ErDJq1KhL95OZGTp06GV/18CBA7M8vocffjjHx0HWiszq /rj99tvPNGrU6J+aNWv+WrJkyZ8KFCjwPf8zmuhjtih9/p0zCzlxkrx5836S L1/eWQXy5fuwYIF8MwsXLvhuiWJFXitTqvjAiuVLP13jhuseaRhdvdNdrRq2 eqHX/dKza3w77/WakmWzh2uR35Os+Gx4dS0fD6/+zezYqmvjhlVcM3/otWs+ eaO0nHMeGxubN4AfPQAAAJyyWpvUrjzr54WU3u3lsrZsLjPQ8efnODW8O8TA S0pK6hfIfu7e0YNtvjv2YAu/PdgAAAw6wlnGieW055S3+t9qAACAXMKuPOvn rVTG2Pmd2VzmKs5Jx2VeM+n4AoI7+oeB7ujhMN8de7CFzx5sABB6XF/vzte/ 873A+d7gwXvBac5GzkROD061K/+rCQAAAH5iV57188dVRj+vnMPldjkus9WM gwuUxMTEIjsDvF5cbpvvjj3YwnsPNgDwjHundnZp1zhf566vf/fv77KKXM6D Xn6I9LHx4Zy2HJxzDQAAEDzsyng/vz6Hy+1xXOY4J48Jxxcw27ZtK80d+Yfc 0tGxBxv2YAMAz7j3afdO7fqadO/Uztez6+vbk7ivK5nVOpPOPp7D6xzz1AEA AEKLXRmf3353NpeRc9RPuVwu5PYo4U58A3fkv63o6J72dOzBFjrz3bEHG4C1 chqnzml82tOO7K+4f48nkeOSY5bbkY0zhHnqAAAAoc6uPOvnhTlpjstuUlmP jQ9Tmfc6yWoevJy7HpdFpmcR2cttrFvGcIZkkWc4fdzSk9Mli7ThtHbLLZxG kocffviRTz/99OSCBQto2bJll2XNmjWUkJCQKRs3bgzKsXTswRY6892xBxuA Lrv5387nues4dVadOrtevWrVKpo2bZr2vpRV/w2WyHuDHK8HfTyFM4fTn9OC U/QK/44DAABA8LMrz/dXG6wyuvciTh1OAU4FzlClr9vuuh96xSyu43mVucOH dYoWLUolSpTIlNKlS1OlSpUuS0RExKVERkZqadiwId10002Z0rx5c2rbtu1l 6dSp02X75HTv3p169+5NTzzxRKYMGDBA23vHNcOGDdP2/pG8/vrrWsaMGUOT Jk3KlPfff58+/PBD+uSTT2jOnDmXIt9nyL5L7omPj6f169dfyoYNG2j79u2X fc8g3y0E0znpZuzBJt9dvPDCC9p+S/KdBvZgg3CW3Vh1duPUzh7t2qf91Xnl fcv5vlyhQgXtvcR9Tou3cf3+zdu4zlXPxjnODs77nO6EsXEAAIBwZVee93MZ M5+qsu+jBzhvuvx/EQPHcU0WkX5fzS01lWOc2y0x6vIxcZmHn9X4+ZPq8rF2 2b8905h8q1atlvbq1Yvc8+CDD1Lnzp0zRfaLbdOmzWW5+eabqVmzZpnSoEGD TF3cmaw6u3R5934vnT+HxyDsUrhwYbr66qszpVSpUlSlSpXLEhUVRXXr1r2U evXqUePGjem22267LO3bt6cOHTpokcdPIo/tY489linymEu/lkjXdka+z4iN jb2U1157Tfs+Y+LEiZcix+S8HXI82IMNQomza7uOWbs+/1z7tFld18zO6xp5 zbu+r8j3iWZcr/tcGU/iOj6ewzpuRzlfk76GW0tOsRz/BQUAAIBwYVee93On GM6nnH2cvzhJnNc5sgbsW47r+8PMg7TKzp07+1t1LroZ89137NhBW7ZsuZSt W7dqkTHtb7/99lJWr15Ny5cvp0WLFmlZvHixlvnz59PHH398KTJmLpk+ffql sXRnJkyYoPVT94wcOZKGDBmSKdJvn3766UyRHizj/ZKHH374UuT7j3vvvTdT WrduTbfeemumyOfvJk2aZOrnklq1amXZ5a+99loqWbJkpuTPn9+v3zXIuD72 YINgIM8D184tzy3Xnm12P/Z3571S+vXrl+m12K5dO+2cG/c1Hv0R1/HxbOaq u5433oVTIVD/xgEAAEDQsSvj/Twn3zmu73OTrs9y3ItfDOWOjj3YPJ/vLn+n ++2R2yzfcyQlJV2KPCay5oDNZtO+63BGvudYsmTJpTRq1OhSH4iJicEebBAw 8rg6x71dx7r90X8D0XFd43pOiaeR94BBgwZp3/d17NhRm4tUtWpVWrhwoVfX 574WhTNyfPI6ltdoDuuq/0v6mupDCOeNAwAAQGZ2ZV4/b6oyxieyW+M9JHEn G5EbOzr2YPPtnHT5O9977z165513tL8Te7CBmZwdXB5v5znc8vwJVOc1O9l1 XjPi+lqVfPXVV1StWjUqXry4dh6LvIe4X+ZKcfZx59rq2YyNy4tL1nGbTlhT HQAAAK7Mrszp52U5KY7r2s7J6+P1BR3uxaOs7uie9nTswZZ9R8cebOjpoUge M+c4uDw35LkTbJ3X7Li+zvwRec+SdSdkLF3W4pS1K13/3P11L8ck97tzbDwb JzmrSd9vvDWnhNX/dgEAAEBQK8Up45L9Su/Us9x+P6v5djI+Po/TlVOPcx0n itNP6eeby/WkciL8egssxP34Pav7udlj6diDLTT3YHPt6JjvHl7ksXGeDy7P FTO7sL8775Xi3nn9HdfXb1aR1/j48eOpTJkyWkaPHq29B8ifyf0lr0d5veXQ x1M5yzmvcG7jGFkXFQAAAOCg8mwtq2lZ/GzMFX7md05Dvx69xfizVx7ux+9Y 3c+tmu9uRUf3Zr57KO3BFohz0jHfPXjJYyOPozzm8vwIh87ra1xfe77E/TWd UzZv3qytF1GwYEFt7w15f8nGn5zPOM9x6nLCbq4YAAAABJQv/bw05xXOOqWP l5/hHOZs4LyojO2nFtK4Ew+xup+7d/Rgm++eXUcPtvnugerovs53D9Q56ejp /iP3tbOLy/Mj3DuvN3F9PZod19e93CfyOpTXkrwehDw2ss57njx5qGzZsnKO ugyay7rqYzntOeWt/rcHAAAAALKWlJTUlzvyBas7uqdj6a4dPdjmu2fX0YNh vrsVHR17sIU+ud/k/pbHSR5reY6Ee+c1O+6vV18i97Ozj+cwV/0/zuo33nhj QYECBdKU/l31HJX1+V4AAAAAEGS4G3fnnLO6n+em+e7ZdfRgmO9uRUfHHmzB wTk27uziuaHzehLX154/4r6Pg0T+XnkM5HUjz/ccnr9HOHGc/pxGnPwub+/X clYovaPv5TSw5B8ZAAAAADCEu/HDubmjYw+20DknHXuwmUfuG7l/5TGT50O4 d15v4j6vxZe4fxfnGjlm1z6eA9l3fAnnJc5NnAJXeHvPw+nPOe3IEBWGe5MA AAAAhJukpKQO3I9PWN3PvZ3vjj3YsAcbxtJzJrfbtY+He+cNVFxfw9nF/TUv r095XV1hrrr4i/S13J7lRHPyePkWH83ZrfSx9NWcCqb94wEAAAAAfsH9N5q7 sd3qbu6PsXTswRY6892xB5t55H5y9nFPu7HVfdebzutr3NeM8Daur3dn5Fjl 9SevE3lOy/MwG/KkTORM5HThXGfyW3xhzkSld/R/OB1Mvn4AAAAAMFliYuJ1 3I2/s7qbWznfHXuwhc58d+zBlpmzj8tj69q1Pem7ZnZes/pudp3XrLi/Vn2J vPblOuW1Ka8heU4711XPhhR16ePOtdXLBehtviPnX4W14wAAAABCAvffotyN v7K6m2fV0YNtvrsVHR17sGEPNic5drlv5DGRxz8cO69ZcX2tmhU5Rue54/L8 zWFsXJzmrObEclpziln4Ni9rx32jsHYcAAAAQEjgz455uBvHWt3NjY6lYw82 7MEW7vPd5bjlvpPH05s+HOyd1xn315iZcX0texr5OXkdyutF7v8rjI0Lba8z zhBOC04Rq9/X3TjXjjujsHYcAAAAQEjgLvziziBZ2z03zXfHHmzYg82VHLPc j/JYynMoXDpvdnF9zRmJ+/drvkSOQ15/zj5+hXXchIyPr+e8zmlL1o6PG9GI 86PC2nEAAAAAISEpKakxd+Pfre7mVnb0YJ7vjj3YwnMPNjleuT/l8Taj/wZD 53WP6+stp7i+Rn2J+2vfNXIfyetJntvyXPPguSB7ncne4304UZx8Vr9X+wBr xwEAAACEEO7oZTlrre7mvsx3xx5s2IMt2MfS5fbJ4yLPlXDovEbj+hr1Z+R+ kteWPL89OG/caT9nDul9vJrV78l+0klh7TgAAACAkMC9syB39GlW93J/jaVj D7bQme8eTnuwybHJ/SvPjVDuvMEauQ/kNSivCXmOynPGw8f2N848znOc+pzc cm52ZY5NZawdV9/awwEAAACAnHBH78bd+ITV3dzK+e7Ygy105rsH4x5s8nfL fSbPBav7a7hFXofympDnqzx/PBwbT+Uso4y11Ytb/T5rMawdBwAAABBCduzY 0Yi78U9Wd/OsOnqwzXfHHmzYg03I9cl9IY8vxrV9j9yHzjXV5blooIuLg5wv OS9xbuEUsvo9NUg1Vlg7DgAAACAk8OfjYtyFZ1ndzY2OpWMPNuzBFsj57nLc 8ljI88jqThuqkdejvFbkeezca9zA4yHruMk+Z+M43TnVrX7vDDHua8e1t/Zw AAAAACAnSUlJnbkbH7G6m+e2+e7Ygy1492CTv0fuR3k+WN1tQy3OMXF5fslz QR4nD53h7OJ8xhnO6cCpbPX7Yxi5n3NEYe04AAAAgKDHXbhiMK3vjj3YsAdb oPdgk9+X45bHyOqOGypxnisuzx0P9xgXxzjfcT7lDON05tTm5Lf6fTAXkO87 4hXWjgMAAAAIevz5OA/34T7cj09a3c+9ne8eqI6OPdjCZw82+Vm5n+Sxt7rv Bmuc54rL804ee3ksrjAXQYp6Cun7i4/l9OA04lxj9fscYO04AAAAgFCSlJRU j7vxNqu7uT/G0rEHW+jMd/f3HmxyHHK/Y623yyPPe3keyvPDg3Fx2Vf8G9LP D3+M04RTwur3MbiiJpyfFNaOAwAAAAh6MpbOPb0H9+PDVvdzq+a7Yw+20Jnv 7ukebBI5dnncsnuu5LbI816eh/K8kMdF7rOspv+7jIfLHmZdOFGcq6x+rwKf yD500xXWjgMAAAAICdyBK3E//tLqfu7e0YNtvjv2YAvuPdjk5+Q+ksfa0+90 wjHy/JbnlzzeOazdJueHb+HM4PTn3MG51ur3IvCrzirz2nFFrD0cAAAAAMgJ 9+GW3JF/tLqjezqWjj3YsAebRH5O7jN5Drj38tzQ0Z3rt8ljJveF2znjznPE 5zh6eAucH56rXc9JUFg7DgAAACAkbN26tQR34gnckU+HQkcPh/nu2IPNu7F0 +Tm5z+Q5kNPzI5w6uvs8dbdzxmWg/HvOJ5wBnFacUla/p0DQyaf09eLOKqwd BwAAABASZC827sjTOedzW0cP5vnu2IPttPb/cr/I88DIcyQUO7rreurynYSL XznLHOeJt+dg3S8wqinnZ4W14wAAAABCBvecZtyBNoTCWDr2YAv/Pdjkdshj 7e33OMHc0+W5Kc8heezkvnNZw03OFbdx3uLcz7nB6vcFCBtYOw4AAAAgBCUl JbXmHvR9sHd07MEWfvPdpZvLdcrjY8bzI1g6utwe53njchsd543/x9lI+n7i GBeHQHmAc1Rh7TgAAACAkJGYmFiAe9BjnL3h0NGD+Zx07MGW0dHltiUlJWWK 0edHMMx3l+eSPJZyf7qs4/Y/zmeO88Vl7Tb0IrCKrB23XmHtOAAAAICQw/2n Bfeh1VZ39GCb74492Myb7y6/L/fpjh07LsWTjh4sY+nynHGOj8vcfEcXd11H vZjVr2MAN1g7DgAAACCEcRdqw1lndU/HHmzhtQebXJ88lomJiVpCoaPLc8K5 lptjz/GfObM5j3NqW/1aBTAAa8cBAAAAhDDuQ004H3MXOhVsHd2bc9KDbb57 btqDTa5THs/vvvvuUj937+ie9nR/dnR5jsjjJPfNqVOnzl+8eDGJe/hEThfO dVa/JgF8VELp56Jj7TgAAACAELVt27bS3Ite4vwSih09HOa7Z9fRg2G++5U6 ulyvdG/p5s742tG96elZPVec67nJ7Tt9+vQF7uA7OOM5d3FKWP3aA/CTLkpf O+6i0td6xxoJAAAAACGG+0pe7kx3cTdattPkPdRXrlxJM2fOpI0bN/o03z1Q HR17sHk2li4/I4+jaze3uqPLYyT3i3x3cOHChR/4eT3ZscdZKatfYwABVIWz QWHtOAAAAICQt3379vLcj/pztvrazWfNmkUFCxaUz4hUqVIlSkhICMh8d+zB lrmjmz3fXSKPCz9XsuznV+rpZnV05xi5HM/58+cPcif/hLv4I9jnDEDlV1g7 DgAAACCscC+q6OjqG73p582aNdO6uTOxsbFBMd8de7D5Nt9d7ivp5s5409G9 PSdd/m65b/h4jp87dy6OO3kf7uPVLH6pAASrZpxfFNaOAwAAAAgr3I8acF+K 5V8T+deL2fUp6VqTJk2i+vXrZ+rmEpnnbmScNBjmu2MPtswdXY5h27Ztl+JJ T/elo8tzQB4HuY0nT57cf/bs2Wnnz5/vhHPIATwmr5W5CmvHAQAAAIQl7sCl uDt14T49h39NlR4lXW3QoEHaPHa+CJUoUYIef/xxateuHVWvXp0GDBhgytpx obgHmz87eiD3YJNf5bHZunWr4Y5uZL67PK5yv/HxXDx16tTG06dP9+dgjBzA N09xTnIucG6x+FgAAAAAwA969OhRulmzZtO4j6fz/1LZsmW1nu6+HpynwR5s 1s93z66jy7FKN3fGzI4uj6ncX3Jc//33344zZ84M40Ra/fwGCDMRnHc5eaw+ EAAAAAAwlayJHcs5rPR5kz9zekyZMkXWl+vI/Xoi/5qc01z4QHT0cJjvHix7 sMlj4NrPfe3o8rjJ7ZbrPnXq1G7u5YP416oWPqcBAAAAAABCSUXORM5xpffy FE4PToGsLsydrij37BaOdebiOP+Y2dOxB1tg9mCTn3fv5t70dHks5X6Sv+vk yZM/c2JPnz5dO3BPXwAAAAAAgJBXizOHc0bpvXyL0tcZMrRnT1xcXL6kpKR6 nKe5g3/E2cU5F+j57tiDzdgebHI7tmzZ4lVHl7Fyub/k7zx+/PjJEydOzOG0 JaJ85j9NAQAAAAAAwlZDzjKlrylEjv9uYeZfsHnz5sI7duy4ifv4sy6d/Sz2 YAuec9LlfpR+7syVOrr08n17k+ivPw9oa8txH/8f5yX+72vMfO4AAAAAAADk AjcrvYtf5JxX+th5g0AeQFJSUgXu4e25lw+RteJlbzfOaezBFvg92GQNt82b N1+xo+/Ytop+2R5L/2y9idIS8lHalhpHjv8+7YFAPm8AAAAAAADCgKzpK3PW Nyp9rPyc0nt5lJUH5Yo7YImdO3c2557eh/M+d3Ibd/R/sQebf/dgk3PHpZ9n 2dHXL6Tkdf3oD1sEpcWrrHI43abaWf3cAQAAAAAACAFyHrCs8bZT6b38P6Wv AVfFyoMyQsbauYu35Qzkjv4hZzv/93HswWbOWLqzm+vZRFvWzaRtXz9BPyyP pIPf5s2ul7vmYppNjaU4hXPOAYJfEc5dnOGcxZzflf5vg2Syhz//IOcjzh6l 77sua5cc4HzBudf8QwYAAAAIeQU5/Tm/KP1zV6rS90wra+ExmYp7+jXcw1vw r33414nc1VdzRz8UbvPd/b0H2+bNG2nT2um0ZemjtO2zmrRvcSE6vNajXp45 CSr+5Hp1ndXPC/CYrz1N1pUcwFmo9L0eZD9GmZdzlLNV6e835cw+aPBZjMp4 nN1zpce9sMrY3yOnyPOpkPmHDgAAABBy5DO39HLnZ+2/HP9f3MqDChQiysud vAZ38Y7861Du6wv4v3dxzuSG+e6G92D7azclLYqirXOLe9/LM+f3Y/Ha+gYQ /GKU9z1NTMjh551J57Qx+bjBNzFK/w5lDWccpxvnb+XZ417Mcbk/lf74y7kt 1RzpwNmmMh776eYfOgAAAEDIkLWzY5U+hiWfjaSf91H6OHquZ7PZ8nMfr8N5 jDORu/h6/vUY9mA7THt3raE/1zfxtZe75nyqTcUSGdufDwIuRnnf08TznFmc Xkpfc7I6pzKnKWe00uc9y3WlqTCatxMGsjoPxa48e9zl35OenPw5XPe3KmON k9JeHSEAAABA6Kqg9PPJjyn9M9FepZ9vXsDKgwoFMtbOfbz23r17u3HG8X+v 4RzNlXuw/fM3HUkZxN3a5/Fz1/nua06sUdda/ThDtnzpaZ7orDLGUnuZcH3g P3Zl3uPeTmU87q1MuD4AAACAUFBT6euvn1b65yA531PWZ8eYpY/kvHbu5S24 p/fnX+dwUjgXg+mcdH/twfavfeGJ9Hj1p4lj6QeOrVO3WP2YgsfsyryeVlRl 9LT+Jlwf+I9dmfe4N1MZj/sdJlwfAAAAQDCT/dDiOBeU/vlH9jFvYekR5QLc 1StwL+/M+ZDzVyidk25wvvuxYzZVhjv6UhM7+rm0BDWESNvjD4KbXZnX01qr jJ7W3ITrA/+xK/Me94GO65J/o7A+IAAAAISrm5TexS8q/XOPjJ03sPSIcjHu 59U4fbiXL+OcCYY92L788ktq3rw53XbbbbRmzRqv57sfOXKksnRp7tR9uFuf NKunc+dfkrZBWycBgpddedfT5LxkWa+7hNLXdZfx8iOO65pt4vGBf9iVOf1c zjc/6Liuz3y8LgAAAIBgJHPWN6qM9Xakl0dbekSQyY8//liGu/nD3Mnn869H rJjvLpcrXbr0pXWzS5YsSc8++ywNHjyYhg0bdiljx46l8ePHa5kwYQLNnDlT y6xZs2j27Nn0xRdf0MCBA8cofezz9p4dVJeV76uf42co2vqxou/nZ+THxYrs yzLy71rP1ndPX6fNf4XgZFfe9bQTKmOs3JkdnN5mHhz4jV353s9lzbjVjuv5 R+lrowAAAACEA1m3SdZ426n0zzr/KX0NuKoWHhN4iDt6FGcI9/PVnHOBmO8u +8blyZPnSntdWZZCVykqWdyRYoqKFtL23frVJbJ/dqJL5Dup1S6RuSNxLpHv qaa7RF4fYx2J5QxxiYzl9nGJvLa6uES+A2vtEjlfpJFL5JwS5x5S0jmucUm4 7Y9gV+b1c1kbXh6XoiYeH/iHXfnWz2Xdk7mO65A1UVqac1gAAAAAlpI116U/ /KL0zzmpSu8aOIcvRHFPr8R5Vro6d/Oz/tyDrVu3bpe60SOPPEKbN2+mtWvX 0sqVK7WsWrWKFi5cSJ9//vmlOMfPJdOnT9fG1MeNG3e6WLFiz/L1PKdcem7z euqzZ7uqUy90VyTp00lRz/YZeeAORR1jMtKysaKYRnpua6iofq2MRFdXdG0p dSJvHvWb0vv5H0rvc86cUiZ+P+DHnHc77oMq5+8dElTm7x0Wq8zfO8xQGd85 TFMZ3zlIRqvM3zu8oDJ/7/Coyvy9w10q8/cOnvRku/Ktp8nfId9nvKr0vc/l upKUPvcdgpddef+4Szf/xPHzZzj3mHdYAAAAAJYoovQxPrvSP+P85fj/4hYe E5iMO/Y13MUf5X6+iHPS7PnukmXLltE333zj87pxhw8fbp/VbTiSoCqnxasE E9eO+/HoelXXi7uzsMo8ji3j2s4xbumHruPfMh7u2lPltrn2WBlPd+258tpz 7cGxKqMjy3iw67i9jOO79msZ53ft3zIPwLWfS1937e/yWnft9/78LqGGB/er XfnWz13VU3pfk+sbasL1gf/YlXePu8z1+lRljJujmwMAAEAok14Rq/Rz9eTz ze9K7wfhNmcW3HCXLvzLL7905F7+KSc9CPdg+yC7Y6c4lU/WY+dufdakjn5K 1qIL5P0fxEqqjO8cZK2tai6prTJ/7yBrort+79BBZf7eQfYcd/3ewZPv++zK vH4uFjuub6NJ1wf+YVfGH3c53/xzldHN7zb/sAAAAAACQsb6ZBzumNI/2+xV +hheASsPCqzBXbwQpyNnHnf0Y0GyB9u+Kx23rPPG3fpXs8bSU+PVnIOrcK6y xezK3H4+yXF9dpOuD/zDrow97vJvlfO7FzkXpZ1/DgsAAADAr2oqfT6sjDXI 55ptSp9rm9fKg4LgIePq3MU7cTefzzlp9h5sBjr6hX/++afYlY736Gp1NXfr +SbOd997ZJ02Px2sYVfm9vNvHde33aTrA/+wK88fd5nftdRxeVm7tK3/DgsA AADALyKVfm6q7Fsun2nkHNUWlh4RBL1ff/31au7mfTibzRhLz66jZzffnX+/ kafHmpqgenC3PmFSRz+eHq8e8ud9C9myK896moyfXun7GxlTvei4vtE+HxmY qRSnjEv2K/1xmuX2++7zWaSbr3Bc9iznQbfLuwfrAgIAAEAwuUnpXfyiI9LR G1p6RBCSZB147uhDuJv/Gqhz0g8dOmRoXOyYTd3I3TrJzPnuBzZr68CB/3jb 08pzjii9x3dU+rnx13Ku59zBmar0/ibXdUjp59JD8JB9BjxZU3Ca289Fe/hz zvT18+0AAAAA8ITMWZf1kOTzyTmlz2mPtvSIICzYbLb8//vf/9pzH1/FHf2i 0T3YDM5372L0+GiFKphmU2O5X18wqacnpa1V1f1xX4LG255W3sOf+4lTx983 AgxDPwcAAIBwJ/vMyBpvO1XGeXmyBlxVC48Jwhj38Wq//fbbWO7oR82a7/73 n79Run0mnd33AB2yb3zY22PjXt2G87dJHT2dY/i7AvCItz1N1sxopfQ95zYr fdxd1tWQ9z07Z4nS14/HXhQAAAAAEEhyHqbsXfSz0j/Hpip9z7RyFh4T5CL7 9u0rzp28D2eft2PpBw/soBO/DKOLKY2J9kRqObuv/Rxfjuv4JlWOe/UKkzr6 xdR4NZFS1FVm3W8AAAAAABA2inD6q4z1lP52/H8JC48JcrHExMQCdru9N3fz /3na0Q/bl9KpH3txH4++1MszEn2cUqJK+XJMRCpPaoLqz/36jEk9/bu0BHWD WfcZAAAAAACEtGuUPj7+j9J7uczrlF6OfZshKLj09P1ZdfQ/DtjpyK8f0dkf 7suik7snYpQZx5RmU425W/9kUkf/Nz1B3W3GcQEAAAAAQEiqoPTzyY8pvZfv Vfr55gWsPCiA7Mhe6tzPX+akOXv6gd9/onN723jQyy/lKCVWu9qM4zm8URWX NdlNne+eiNcfAAAAAEAuUkPp66/L2kfSy7cpfX32vFYeFICnuJdX4H7+lbOj n9z3lJF+LnnNzOORtd44qSb19ATu/RXMPD4AAAAAAAg6kUrv5c49fGUf8xaW HhGAD+x2+8Pc0Y///Vs8d+4oz/t5SlQa7a5zjZnHkrpWVUmNV5tM6uj/pCUo Q3u1AwAAAABASLhJ6V38oiPy37dYekQAJtm/f380Z8uZHzr9a2gMPTky1uxj IZvKn2pTsWnm7JV+Xq6LCPNaAAAAAADCgMxZ36j0sfJzSh87r2PpEQH4CSVH xxjq534YQ3dKjVctuV//YdJY+toTNlXeH8cJAAAAAAB+lU/pa7wlKb2X/6f0 NeCqWnhMAAFBeyI2Gevoka/661iO2VSZ9Hi11KSO/sexdZjzAgAAAAAQIvIr vZfvUXovT1X6nmnlLDwmgIDivn2f4TH0nfVL+u14SOVJS1B9uF+fNKGjn8N8 dwAAAACAoFZE6XuV25Xey/92/H8JC48JwBLShyk5MtnYWu5RI/x9XMfXq0ju 17vNGEuXMfn0zaqUv48ZAAAAAAA8JmN+sZx/lN7L9yu9lxe18JgALEfJEY8a 3Gst1Z9j6JeOy6YKyf7mJs13/z3dpq37CAAAAAAA1rlO6eeTH1N6L/9B6fPa C1h5UADBgmwx+blz/2aso0cMD9TxcUfvxP36iAkd/XRqgvadHAAAAAAABNb1 nOmc00rv5duVvj47zkUFcEMpUc8ZHEM/Qj/XCNg5IUcSVGXu1wkmjaV/mWpT fh//BwAAAAAAFaH0fdHOKr2Xy97lLSw9IoAgR79VLcSd+29j+6FHDAvoMcap fGkJagj367MmdPSfUtepeoE8fgAAAACAXKSZ0rv4Bc5Fx39jfyUAD0nfNjyG vq928UAfZ/o61Yz79a8mdPRTmO8OAAAAAGAqmbO+Uelj5eeUPnZex9IjAghB lFjtam3/NGP7ob9ixbEe2apKcL+eb8Z899R4NffgKqwTCQAAAADgJTmHXNZ4 S1J6L/9P6WvA3WDlQQGEOtoT9ZbBMfR/rRhDd0pNUD24Y58woaf/cNSmoq26 HQAAAAAAISi/0nt5stJ7eZrS90wrZ+ExAYQNSo6+llKi/jM2hh71spXHfMym buR+nWRCR/8vLUH1tvK2AAAAAACEgMJK36v8N6X38n85QzgBWz8aILeglMgP QmkMXTvmFapgmk2N5Y59wYT57nP+SlRFrLw9AAAAAABBSPZAiuUcUnovP6D0 no5zRQH8hHbXqcad+5yxjh41xOrjFtyv23C//suEsfSkdJuqYfXtAQAAAAAI Atcp/XzyY0rv5T8ofV77VVYeFEBuQXsi5ofaGLrT8U2qHPfrFSZ09GNpCaqr 1bcHAAAAAMAi13Omc04rvZdvV/r67HmtPCgIKjLv+C7OcM5izu9Kf65IJnvw 8ydcLn+lbDT52EMGJUfX5c590eB+6IOsPm4nIpVH9k7jjn3GhJ4+nVLw3SAA AAAA5BoRSt8X7azSe9FqTgtLjwiCVYzKvk+b3c+nmnvooYWSI782OIZ+mFKi ill93K7SbKox9+ufTOjo36UlYH8IAAAAAAhrTTnLOBc4Fx3/jV4OOYnhHOWs 4YzjdOP8rTzv56U5ZXJIP5XRzxuae+ihhbt2C4P9nLjTv2T1cbs7vFEVlzFw Ezp6WmqCut/q2wMAAAAAYDKZsy5zh6UDnVP62HkdS48IQkW+LH7Prjzv51ey wXFdO024rpDHnXtDqI+hO6XZ1APcsVN97OgXU+PVREpUBay+PQAAAAAAPsjD 6cLZofT+c0rpa8Bhzij4yq7M6ee1VcbY+bM+XldYoOSIewyPoadEDrT6uLOT ulZVSU1QG30dS0+PV+sPb1QVrL49AAAAAAAG5Vf62uvJSu89aUrfM+1aC48J wotdmdPPxzuu5z+l7+0HShtDTzLY0Q9SYqOg3T+cbCp/qk3Fcs8+72NPP5y+ Tt1p9e0BAAAAAPBAYaXvVf6b0jvPvxzZI7mElQcFYcmufO/nMl/5kON65ppw TGGD9kQ9ZHgMfU/Ui1Yf95WkxquW3LH/8HW+e5pNjaW4LM+7AAAAAACwmow7 xqqMrnNA6T29qIXHBOHNrnzv551Vxtz22004prAh3ZM7988GO/rfwTyG7nTM psqkx6ulJqwdt+6ETZW3+vYAAAAAQED5uvezUwfHz+9X+l7jci64jHMv4LT0 8tiuU/r55OmO49mn9Hnt2DcY/M2ufO/n3ziu42cvfnYAJ5GzjvMtJ44zjzOd 8x5nLGcoZzCnD6en0tdiuIfTWun7GMha8dU4lTjXcAp6fUv8gJIj+xofQ494 werj9lRqgurBHfukjx39UNo6dYfVtwUAAAAAAiZGqWz3avakm8i54HFuP+fc 28z19yYZOKbKSu/lzn2ltyt9ffa8Bq4DwBd25Vs/l+fwBcd1vOzFz4/i/Kr0 czjSVPavUW+S7rheuf4flP49wHrOas4XnM+U/j3A+0r/HmCE0s8j6ct5Qunf A8j3cfI9wM2cRpwanCpK/x7AozFu+rlGQe7cfzq7d/rWG+nxTiUpin97+FNl 6GJyNmPomysVNnxvWuT4ehXJHXuXjx39nJzbToT3PwAAAIBcIEb5tvfzQJXx uX+R0vc0k/NuZYy7GSfe5c+7XuG6IpS+L9pZx+XlmLB3OVjBrnzr5686fl72 +jNrjrK8pqT/yni4jIs34DRRek+WcXPpzT2VPp4+SOnj69Kv31V63/5U6d+l yXi8jMtLL5c1FqWnH1T6+4D792q+5ITjOv/H+cnx921S+vcAX8qxtGhQZNvT D15DQ3qXoYfuvjrTzy+eWDmb/dAj+pt0fwYE2VQh2T/N1/nuqQlqefpmVcrq 2wMAAAAAfuXr3s/bHJfdk811yTnizr7/RTbXIXNxl6mMcXf5b/RysJJded/P 87r8/FfmHVLAyTi1fB8ge37J9wFRSn9dyvcBMp9Fvg+Q803k+wDpzLFK/z5A 5r7I9wHyXZt8HyCv541K7+cpSv8+4C+lnwNzqY/Xv7FQpn7+/tDy2Z+HHkJj 6E6pNtWRe/a/Pvb0/cfitTkLAAAAAJB72JXn3cS5x9nHOVxmleMyK9x+X3q5 jKM5e/lSpfDZE4KCXXnfz+9UGT3zXhOPKRxd89OKGu/+urIGrZ5ZhUoUy6vd b1UqFKCDCbVy2g/9easP3BtHElRl7tgJvs53T0tQQ4hUHqtvDwAAAAAEhF15 3k1mOy67S2V9friMc/3luMxrbn8mY2wyhibjbdW8PFYAf7Ar7/v5QsfP/qmy nlMCLmhX3XLcuU9K7z6yqTZtnFuV/tsRcaW14v4KxTF0QYmqAHfsNzgXfJrv Hq/mHtmKvSUBAAAAcgG78rybyJpQ/zguL2u111Z6T5d14+T82G8dfyZrWLt/ lnSeRwsQbOzKu35elnPG8bNjTD6msMV9+33Da7mnRD1n9XH7Ii1BtUqPV3/6 OJb++1Fbrj0XyKy9R9y96XI9B308RgAAAAAz2JWxzzgVOTNVxjrTsr7becd/ S3eX/aBKmn6UAOaRdbfKuET2CZTn7yy33y96hetxrpco52vguycPUXJ0Ze7c Zw129JAdQ3eS8W/u2PN87OjnZb671bfFAjHKZb0Ct3jbz2VPwnMK/RwAAACC i10Z+4wjY+afq4xxQ9ecVPq56ZXMPkgAE8nncE/WJJ92hevZ67jcWr8daZii lKg5xvdDj3rW6uM2g2Ov9OM+9vR5BzarkP6+wqAY5dveI+5kztf3Sv9ubYtC PwcAAIDgYVeef8aRNd5SHZeXPZRjlL7ms8zzbcfZ6fgzOQe9lvmHCmAKM/p5 c5fLPeTPgw1HlBwdwZ37gsGOfkD2Ubf62M1wdL2qmxqvUnzs6GsPb1TFrb4t AeLr3iPuhquM1/gEhX4OAAAAwcOuPPuMI+sHJzkuK/usZfV5qRBnt+My35h3 iAAQbrhvLzE8hp4c8bTVx20WGf9Os6lpPnb0bbl4n3S78q6fRyp9/pd8j3y1 Qj8HAACA4GJXnn3Gqa48Gy/sqzLOyb3S+bsAkEtRSlRT43PcI/eHyxi6E3f0 1qnx6i+vO3qCSjy4Kle+19qV8X4u65k657Pf7/g99HMAAAAIJnbl2Wec1iqj nzfN4XJ3uVwuyoTjA4AwRXsibMbH0CP7Wn3cZnPslX7El/3XrL4NFrAr4/38 RcfPfOnye+jnAAAAEEzsyrPPOM1URu/umsPlnnS53PUmHB8AhCnaE3WnV2Po KVFXWX3sZuOevT+7/n3ga0VPdlJ0c11F7w7Idhz9QatvQ4DZlbF+LnssyBqm 6Urfh8QJ/RwAAACCiV159hlHzi0/6bhsgtLPR3dXgJPouMwf5h0iAIQr7tqJ xvdDj3zK6uM2W077oz/bNfPahbc1UNQxJiMPtlH00J3qeIEC6kP+8+mOTOKM dctrnCFu6c/p45YenC5uaa/0eVSukf3YG7lFzu+u5pbrlL6WqGsK+XiX2ZWx fr7Wcfln3H4f/RwAAACs5Mvez+NVxmfE5Ur/LCbnghZR+ue0DS5//oI/bwQA hAfu2l28GEP/PdzG0LmHH8qun7e/zaP9BsIhzxu4y+zK837unNe1SV3+3TL6 OQAAAFjJl72l5PPwl26Xu6D0teDcfzar8XUAgEyIVF7u2z96sR/6k1Yfu5ly Ov/8q7cVFSygv7/WqKxo/9eZ//zQakX2ZYr2fqFmqIzxaRmzdh/HlrFt9/Hu W9Tl4+L3qsvHz2VM3X2cXcbe3cfjY9Xl4/YTVca4vjNyznycW+40cJfZlWf9 XOaypyl9zfbILP4c/RwAAACsZMbez52U3tNlDrt85jmt9M9Knyn9sx0AgMdo T8QTuX0MnXt2ek5rwO3+TNHnYxX9+U0O68QlqPetvh0BZFee9fMFjsvJ/K9i WWSi488Pufxe2DyvAAAAAAAAjKDERgW0vm24o0c8YfWxm4X79Qkf90KXddxH WX07AsiuPOvnW5Xxefax/jhgAAAAAACAUEApUQO8GEO3h8sYOvfr077287R1 6g6rb0cA2RX6OQAAAAAAgOloV92i3LcPe7Ef+uNWH7sZUuNVio/9/NiBzaqw 1bcjgOzKs35+JTj/HAAAAAAAwA337de8GEP/VebHW33svuJ+Pdinfm7T1mEL Z77sPZIT9HMAAAAAAAA3lBJVivv2cS/2Q+9l9bH76uhGdT337Ate9vP//l2r rVMezsxY2zQr6OcAAAAAAABZoD1R73oxhv4L2WLyW33svkpLUGu86efpCepV q489ANDPAQAAAAAAAoh21a3EffuM8TH0qJ5WH7uvUhPU417081/+sWl7ggEA AAAAAACYipIjP8qNY+jp8eodg9383LF4dbPVxw0AAAAAAADhiXbVrs19+4IX +6H3sPrYveXN2Hm6TQ23+rgBAAAAAAAgvHHXXuTFGPrPoTiGfnS9qst9+4TB fv4N2VTI3VYAAAAAAAAILbQnqokX/ZwoOeJRq4/diLQN6ho5h9xgN//hyFZV wupjBwAAAAAAgNyBkiNXh/MYuox/c9dea7CbH061qapWHzsAAAAAAADkHpQS eYd3Y+iRj1h97J7grv2W0fXg0tapO6w+bgAAAAAAAMh9KCVqsxcd/adgH0NP S1BduW9fNNLPUxPUQKuPGwAAAAAAAHInSo7o5NUYekpUd6uPPTtHbSqa+/Zx g2PnH1l93AAAAAAAAJB7Eak83Lf3eDWGHqfyWX387lJtqiR37Z8MdvPtZFOF rD52AAAAAAAAyN0oJaqnV2Poe6IesvrYXRGpvKnxapnBbn7oSIKqbPWxAwAA AAAAAFBiowLct+1edPS90omtPn6n9Hg10mA3P3NsnbrF6uMGAAAAAAAAcKLk yH7ejaFHdLP62EX6OnUP9+0LRvp5eoJ61urjBgAAAAAAAHBFiY2KUErUP6E4 hp5uUzW4b6caHDufYeUxAwAAAAAAAGSH9kSN8HI/9K5WHfPBVaood+3dhsbN 49V6SlQFrDpmAAAAAAAAgJzQ7jrXcN8+5kVHT7FiDF3Wnue+vcjguPmBEzZV PtDHCgAAAAAAAGAEpUSO924/9MgugT7W1AQ10GA3P51uUzcF+jgBAAAAAAAA jKKUqPLct0950dH3BHIMPS1BteW+fd5IP+c+3yNQxwcAAAAAAADgK9oTMcO7 MfSoBwJxfNzNb+C+/a/Bbv5+II4NAAAAAAAAwCy0u0417tvngnEMnVLUVanx apPB9eA2yM/587gAAAAAAAAA/IG79hderuW+g5IjelNiI7+sj87dfI7Bc85/ St+sSvnjWAAAAAAAAAD8jfZE3elVP8+Y676PkqPrmnlMaQnqKYPdPPWYTd1o 5jEAAAAAAAAABBL36xY+9XM9R2hX7dpmHM9Rm2rBffusgW5+Pn2dutOMvxsA AAAAAADAKib1c8lGX4/l8EZVgfv23wbXgxtoxv0AAAAAAAAAYCUT+zn5Mobu zXpwnBlm3hcAAAAAAAAAVjG1n6dE9fT2ONJt6j1D3TxBxVOi8svadAAAAAAA AACBZm4/j3zFm2NItameBsfNfz22RpU2+74AAAAAAAAAsIrJ4+cvG/3709ap Rty3Txno5unH16tIf9wXAAAAAAAAAFYxuZ/3MfJ3H7OpMty37Qa6+YVUm+ro r/sCAAAAAAAAwCqm9vPk6BiP/944lY/79mqD55wP8+NdAQAAAAAAAGAZ+uHG 0tytT5k0fl7e07+X+/YYQ/uo2dSnRCqPP+8LAAAAAAAAACtRSuSHJvTzXzz9 +9Js6gHu3BcNjJtvJZsq5M/7AAAAAAAAAMBqtDfiJt/ntkd+6snfdWSdiuLO fdzA2PmBEzbl8bg8AAAAAAAAQCjjjr3dx73VHr7S33F0tbqa+/aPBrr5ydQE 1SAQtx8AAAAAAAAgGNCeiCd86OcXKKlG2Sv9HWk29Zmhc84TVI9A3HYAAAAA AACAYEGbKxXmnv2vl/183ZWun/v2UIPrwcUG4GYDAAAAAAAABB3u2W9718+j nszpetPj1V2yd7mBfj4fa7UDAAAAAABAbkXJ0dW1uerG+vkZ2l3nmuyuM22t qs59+6iBbr7twGZVOJC3GwAAAAAAACDYcN/eZrCfr8juuv5KVEW4b+8yslb7 yfXqukDeXgAAAAAAAIBgQylRV3HSjO2rFn1/dtfHfXuekbXa09arhoG8vQAA AAAAAADBiPZGtDY4dn5UOn1W15Uer/oZ6OYX09apzoG+vQAAAAAAAADBiPZE TTG4LtzMrK4ndZ26nTv3OazVDgAAAAAAAGCMrJfOnftPY3PbI9q4X88Rm6rE nfsg1moHAAAAAAAAMI72RDUxOLf9EMWpfJmuY4UqmJagtmKtdgAAAAAAAADv UErUaGNj55HT3K8jzaamYa12AAAAAAAAAO9x595jqJ+nRN7h+vPczZ8w0M1P pCaoBlbdVgAAAAAAAIBgRD/cWMvg3PaDrnPb0+NVE+7cp7FWOwAAAAAAAID3 KDnyJWNj51FTnT97fJMqx517P9ZqBwAAAAAAAPANd+4NBvdVa6n9nE3l5869 Dmu1AwAAAAAAAPiGUqLKc+e+YKCf/8UdO6/8bJpNTfC4myeorVirHQAAAAAA ACBrlBz5uLGx84jJ8nPctx/EWu0AAAAAAAAA5uDOvcRQP98bcdvRBFVH1mDH Wu0AAAAAAAAAvqNddYtSStR/BtaF++P4elWWO/dvnq7Vzt38fqtvJwAAAAAA AEAwo+SITgb3PJ/EnXuVp/Pa0xPUq1bfRgAAAAAAAIBgR3siPjbSz09uKfmR gXPO52GtdgAAAAAAAICckS0mP3fuI55284vJNx6W+eqertVONlXI6tsIAAAA AAAAEOwoOTrGyNj5mcTrzng4br4fa7UDAAAAAAAAeIb2RL1rpJ8f31gEa7UD AAAAAAAAmIw792+edvMLu2p60s0vYK12AAAAAAAAAM9RcnRdI2Pnp7+79spr tcerkVbfLgAAAAAAAIBQQilRIw3Nbd9UGGu1AwAAAAAAAJiMkiN3mDa3HWu1 AwAAAAAAABhGP9xY1cS57ftP2FR5q28TAAAAAAAAQKihlMjnja3bnu3cdqzV DgAAAAAAAOAl7txrPJ/bXgNrtQMAAAAAAACYjHbXuYZ791nP57aXy66fv2H1 bQEAAAAAAAAIVZQS+bCxue2FsurmC7BWOwAAAAAAAID3uHPH+Ti3ffuBzaqw 1bcDAAAAAAAAIFTRb1ULce8+7sPc9oNHN6rrrb4dAAAAAAAAAKGM9kbc7cPc 9tPHElRzq28DAAAAAAAAQKjjzj3d87nt1TONnacmqB5WHz8AAAAAAABAqCNS ebl3H/R4bvv2jLnt6fHqHauPHwAAAAAAACAc0O4bbzY0t31DIee4+XKKU/ms Pn4AAAAAAACAcEB7IsYandueGq9SjmxVJaw+dgAAAAAAAIBwQSlR+zyf215W +vnRYxtULauPGwAAAAAAACBc0O46NxqZ235sQ8Hz3M/bWH3cAAAAAAAAAOGE 9kQN8bSbn/++usxrf9HqYwYAAAAAAAAIN5QStdnTfn52R4VEq48XAAAAAAAA INzQ3ojruHdf9Hh++/c1oqw+ZgAAAAAAAIBwc/776ycZOPd8r9XHCwAAAAAA ABBuUteqKueSqpzxvJ9HjbD6mAEAAAAAAADCycFVquix9Xn3UHKEx+u20w83 Yj81AAAAAAAAABOlxav5J7eU8Lyb74n83upjBgAAAAAAAAgnsj8a93M6u6Oi 5/08OXKo1ccNAAAAAAAAEC5SbSqGu/m5tPg8dDG5tuf9fHedalYfOwAAAAAA AEA4OGJTlbibH5Kx8xObixoZO99h9bEDAAAAAAAAhANaoQpyL98m3Vxy5rvy nvfzlKiXrT5+AAAAAAAAgHDAnXyGs5tLLuyu5Wk/v0i7at9g9fEDAAAAAAAA hDru40+6dvPjGwsZWLc94jurjx8AAAAAAAAg1B1bp27hTn7WtZ+f3l7WSD8f bPVtAAAAAAAAAAhlhzeqCqnx6i/Xbi45v6ua53Pbf7ixqtW3AwAAAAAAACBU UYq6irv5Jvdufmz9VQbGziO3WX07AAAAAAAAAEJZerx6x72bS05tK2Vg3fbI gVbfDgAAAAAAAIBQlZqgHsuqm0vO7azi+dz25OjKVt8WAAAAAID/t3cn8FHV 997H/yCyh5CFkLAou5kZNkFFERUUcQUVQXAXF0SF2t72drFbnj69T7drfWx7 rb22t9XWLtHaVlu7uEwSshMm6wA1WqO4L0AAQVA49/dLzpghzHISZnKyfN6v 1+81k8nMmXNmwjDf898AoCfaVWTmSA7fFymbNxcd15E1z0vdPhYAAAAAAHqi Hc+YVMnh26K1ne8rG9mBsee+z7h9PAAAAAAA9DRWvjlOMvg/omVzrYOB8U7z +SGrduY4t48JAAAAAICeZmeh+b+xsnlzQX/rcEOu03xe7PbxAAAAAADQ0+x6 3lwpGfxwrHz+QWmK877t9Z673T6mXm6o1EVSX5F6QuoVKcuuHzl4/KVh949V NyV4vwEAAAAAUewpMl7J37tjZfPWvu1jDzju277Fk+P2cfVyC030TE0+BwAA AIAe5v1yMyLWfHDhZQVzdznM50VuH1cfsFBqh9SzUt+VWi31pul4Pt8rlRmj BiV4vwEAAAAA7ViW6ddcaP7oJJt/UJr6WAfWVVvv9rH1AcdFuK3JdC6fAwAA AABctMtvvugkmzcXmI1Wg+f7DrP5x1LZbh9bH9VkyOcAAAAA0KNI5r5Isvch B/n8nff9Zpxk7xedtZ97/G4fWx/WZDqfzwdKDU/ObgEAAAAAItm10UyS3P2+ g2z+8a5Cc64V9Poc921v8Nzp9vH1YU2m4/n8Y6kXTNt8cPuk9BzLjSZyH3oA AAAAQAK8UWWGSu6ucdSvvdB8XR9j1Xu+HC2Pb3lystX0j6mhnz+yAlNGuX2M fViTSez87TrP38hk7CgAAL1RXl5e/6qqqqFbt27NKC8vH1dZWTleS65P1aqo qJi2adOm6VqbN2+eKTXXaQUCgVmhx4Ztw6Pbra6unmA/V3ZtbW2W7EPqtm3b UhobGwfJ9ePdfl0AAJHt9JtfOcnmUk9blumvj5HcXRkpm9+yfGRLjuvf31g/ vCdbb3vO5cPr65qM83x+ltRDUpdITTKt87RrFl8s9VfTltH/mowdBQCgJ/L7 /YM1A0vmzZWsfYZk5IukVkhdL1l5rdz+qW5cd8p+3iL7ea1cXymXS+VyiRzP OXI5Ty5nl5WVeSTfTwwEAmMk84+U4x3g9msOAL1Vs9+sd5jNX24uNen6GKt2 po49P9w+m7/2/DQna2dTHStvB97OSJqM83wez09M234tSsD2AADokTZu3Jgm efUMybDXdIOM7Uatkyx/ndRyzfNSCyS7z66pqZkWyvH5+fmMiQOADthZaM6W 3H3QQTb/sLnInBZ6nI4nj9R2vrsi1xo6uP8n2TI15Thr6JB+f5Lr+VSna5zz dzSiJpO4fJ4itd/e3r0J2B4AAD2KZs5NmzadL3l0QzfIyN29NmjbvNSVcn2R XJ4s2f3E4uLiFLffRwDobt57zoyV3P2Ww7XUNoQ/VvL536ONPX/i/vHW9KmD rNNnDbEKfjGhzK3jwyeaTOLyuaq0t/f7BG0PAIAeQ8d2d4Pc2xtK29+vkrx+ Xii319bWDnP7/QUAN1h+M2BXoSlwOB/cHy3L9PvksdWzR0oOP+hs3nbfbW4e J1o0mcTm88329h5P0PYAAOgxJFNO6QbZtteWvL63yeXl5eXlC+QyV+fUsyyr v9vvOwAkk+TuBxyOOf/XjmdMavhjrQbPaofrqh20tuZmuHWM+ESTSVw+1/fz gL297yZgewAA9CiSFfvZY65dz7J9pTZt2nRXIBBYXV1dfb7OWS+3naBz8rn9 twAAibCr0NziMJsfaC4wp7Z/vNXg+43DfP43N44PR2kyzvK5zsU6JMbvdY6X 35q2+eHOTMTOAQDQ0wSDwYGSGVe7nVv7elVWVq6Ry0skt59aVlY2Qa4Pdftv AwA6QvO25O79jvK533yx/eOtoG+g5O5mR/m83nOLG8eIljn2M8PqVdOap3/a 7vb2Y7z0tnelfiB1mdQ0qdFSk6VWS1WYtmzO2HMAQK8mWe94naO9pqZmrFzP lZojefBsuVwi2fwyez0y5ojrZmWvFbe0vLz8dLk+iTHtALqrPUVmlOTuVxy2 nf8jtM55OKvBd4HDtvMDVt2MNDeOE+Yt42zdtgfbPS7T4eP+IMX5aQBAj6Tz r2/bti1FslyOjiXX9b0lx51Z1brm93JdMywQCKzrZD4kr3fDkve0pZ1d+8ZL bh8nfwMD3f47BNC3tcwHV2Cec5jN39xTYrIibifoe8BhPn+6q48Rn+hsPtf+ 7deZ1jXOq6XelDootVfqBalHpBYnf/cBAOg8bS/V7K3rcFdUVJwi1xdpe6pk 8Kvl+q2dzd3y+NsjlfzuDh0frSXPsz5GRtTfbQhdup1Z+3htqKysvE7XyZP3 Y6Zcz7Ysi7XaAXQZydzfdZjNDzU/by6ItA2dw11y9+uO8nnQu6arjxEAAPQd mqe0LVTHHkvGulDnD9OsHCOT3VnVuqbXbXatDav2P7eUbPNmyXDX67Z1vLnd vn6pbGdJVet63mfqOQDNeLrumuzPVLnPePldjlSmVKrOYxZqr9f+1nKZq/eX bZ6ij5fr58r1i+T2G7tBbu2zJe/Fej2HI++frvc2vba2Nkv7Wrj9dw6g99n5 vLlMcvdhJ/l8Z4G5P9p2rKDvNIdt5x/qGmxdeYwAAKBv0Myk83hre3WMvKU5 fI2OEZf7rZDMtVQzsK61rWPIdWyy3GeO5jDZ1lRde1tqTChTNzY2DsrLy+vy Nb00E8rzz5N9XBXn+KguKPn70X4Rq/UcSk1Nja+kpCSLdnYAx2KH30yX3L3H Ydt5tfW0GRRtW1bQ+x/O8rnnqa48RgAAgN5Gzw8Eg8F0+/zBGdpuL3VTnDZg Mn3yM/t6Pe8jdYGOZ9dzO8xBB8CJnX4zUjL3Cw6z+b49RcYba3uSvRsc5vMb uuoYAQAA+hKd28xuZ58s2X225EOdU/4SbefVvvh6XWqe3i75cVWsMfFU4qqy svI2ubxcakFV63z/mZZldXkfDADdk869vrPAPOUwm1s7C83dMbe3NXeaw77t +63GKSO66jgBAABwpPD5ySUnHq9j4rVPv2T15VWt4/Bdz7N9obR/vFxeo+Mx qlrX5xtfWlo6xM2/DQDuaC40X3eazaX+onO/xdqeVe/9nMN8/qeuOkYAAAB0 jLbpSlYfrXPU2eP4r3c7x/bBulVe9yt1PgTtIy+ZfYrclun3+we4/fcBIPF2 +82lOg+7w2z+3rvFZky8bUru3ugon9d7r+uKYwQAAEBiBIPBgdq2K3WqPT99 Z9eho46xdM0A7eegc9LV1tbOkdsmV1RUZDAvHdAzNfvNFMncOx33a/eby+Nt 0wr6siV7H4q/pppvn7XtpJSuOE4AAAAkT3FxcYrkwmmSE8+SjLiSuedcL12z fY22u8v1JTpnoK4/UFZWNkHze/iYBgDdw/ZSM0Qyd6AD2fxXTrZr1Xtucdh2 /odkHyMAAAC6nvaLl3yYLZnwNMnsV2le7AaZlQoreW9ul/foOqnl9vzyem5F 2+B1vroTNMdv376d8e9AF9Dx45K5n+jAmPNtb/3dOFoLQrL3k87GnvuuTvZx AgAAwH06z5nmPsmEF1cx51xPK22Lv03y+3Xy/q2Qny/RsfDV1dXzNc/L7R7J 8hPleo7cNrKxsTHq+ssAIttZaD7bgWx+YFeRmeNku1btzGEt/dad9G0P+oYn +zgBAADQvWjfasl5J0muW2rPWe52/qQSXPY6fbdq+7zdx/4SHSNv97M/uays zCNZfoL2sdBMr+dvLMuKOf800Fvt8JsFkrkPOs7nhebLTrdt1U9f7nDe9seT eYwAAADo/nSuOR0XrTnO7UxJdY/SuQukbrH/JlbqeRy5XCI/nyOX8+Rytub7 2traiZL3x2g/fLk+LD8/nznx0ONI1p6oc7B3oO08P95aauGsBt/Dzsaee1Yl 8zgBAADQs+ic8JK3LrLbXl3PiVTPKyfZ3p4n76h8T/s9upo9H1y102zeXGAa 3vEbx33QLf/CAZK933eQz/daVXOHJvNYAQAA0DNt3LgxTXLT2Tp/mdt5j+pT tU7y/Bq5vEb75OvagXJ5vv4tVtnZXsfay22TampqxsptmbpuAXPho7Mkcz/Q gXbz3e8/b3wd2b5VP32hw77t+ck6RgAAAPQOkn+Olxzkk0y0qhtkN4qKVRvk 73StZPcbpFbLz5fbfUHOlZ/PlMu52m5fXV09VX53Qm1tbZaOu/f7/YNpt++b dvnNug5k8492FZolHX0Oq8F3n6N8HvSuTMYxAgAAoHcqKSnJsucXW9cNshhF JbrW6Xr18vd9tfydL5efL5E8v1guF8jtp8ptM3VORfn9iTqnXl1dXZr8bihj 7numHQXmrI7MB9dcYD7V0efQMeqSvZsc5PM99G0HAABAZ1iWdVx5eflUyStX dINMRVHdojo7p57b/577oj1FZpRk7lc6MFd7p+ZVtxp8s5y1nft+m+hjBAAA QN8jOX20rsNNmzpFda7sOR5uDPXJl1x/oVwuCq2DF762vc4Loevguf3vviez gmbgzgJT0oF+7dZOv/l0557L+3Vn87ZPX57o4wQAAEDfpW3qdrvgRaynTlHJ r3jt9TrWvn1bfV5eXn+3PyvctqvQfC9CBm+O2be90FzTmeeS7B1wkM+brZcn DE70cQIAAABKc4DkgzlS17idYSiKOqLulLx+s1xeIzl+uWT4i+T6IsnvLW31 2v++urp6go6vD82d5/bnSSLtKTQeyduHI83LHrP9/HlzTkefy6o9aaLDedsf TcaxAgAAAO1pX1z9zq9te7SrU1TPrFht9Tovfk9Zy36X33wzSgbfFyOfH9rx jEnt6HNZQe8GR/l8i+fyZBwrAAAAEItmdfn+7pXv9EsZr05Rvb7u1LXs7fnw rwgfVy+Xc/SzQC4n6zr2W7duzfD7/cOlBiTr80fnUpes/VJH286lajr1fA3e Zx3MC7fLapwyKNHHCgAAAHSUfDdP1Tmt7e/utK1TFNVSyZgLf3ehmR8lf5fF zOd+87mOfrZJ7k6X/P2RgzXPf9n5T1AAAAAgObZv3x7qB3+hPZ+16xmBoqie VaG58OVzZJWe95OfL6tqzfVnv1c0Nv/o/D2gbIe/37YYa56//m6xSeno55lV 773O4bpqy5LxeQoAAAAkio5b1TYx+V49T75j6xxWtK1TFNXpqt5c+ukdBYP2 ts/fr28866/R1zzvd+iljTd8QdePlM+hs+Rz6DQday8/z5LLKfoZpevd6Rx6 7cfaS/Z+jL7tAAAA6I107TYdo1pFXqcoqhP1Yvnn7z9qTvbCgfveKFnwt2j5 /PWi+X/v4PPcoX3y62oK1hxumL4/Xj7/qP6Ux2tra7NKS0vTt23bltLY2Dio O86pBwAAAMSieb28vHycfB+eJ3W5FHPNURQVtd4snlPYPn+/VZRb+X5R5quR svn7BSnv1lQV/Ftnnuu16i//xEnfdr1fpMfbY+9b+ulLXSPXVwQCgWU69kfq 3MrKyvnahi+fgVO1Dd9eBy9p8+oBAAAAHaFtTvI9NlO+u86UukDqJrfzAEVR 3aXK795RMHTXUe3jxec9GWUtdGt7yQV/6Ozz7albWhovmx+qn/XB5k3Fn0nk cdr9im6Vz7+WOfXk52W6vr1+JkqOP0fy/Ok6r578LlfXuJfLHO2fr+tq6Gco bfcAAABIFp3LWduX7HGjK+S76B3u5wSKorq6Gsu/dN/RGbzf4TdKFv05Wt/2 YOX/fK1zz1d+96GG2bvj5fO9tZeUu/26RKh1uh5eVWub/ZVy/VLJ8efrnPkV FRVnyGfqHLl9ulyfJnn/RLlfTjAYTJfP2RE6v2d+fv5xbn/uAwAAoGfQtiH9 LinfKXPtNZpWSt3ZDb4TUxSVxHqjeP4/juq/Xpix/Z2iSXUR+7YXjni7s8/1 SvX37nPUt73maw+6/bokquy1MfWzVNe7Xyufr6GMvyJ8XTxtv5e8r+tpeqrs de/lMrO4uDhFPpsHuv1/BAAAANylmX3r1q0Z+n1R11+y12G/ze3vuxRFJa7e L0x//aix54XTy3YVDjgQKZ+/uXHWxs4+V3PdqmfjZfPDDbP3Jrpvey+pDZrv JdffILVafr48EAho//xz5eczKyoqTtH2e507v7a2dlxRUdEozfZyv+Pd/r8E AAAAySPf94ZKnSCl/TnP1++KzBlPUT2v6iof/mqkMeZvb/SWR+vb/krpdb/o 7PN9XH/qO/Hy+Z66pWVuvy69rew59W6R7H6t3W5/qVwult8t0DXxqlr7TY3X PlQ6T77b/8cAAADg2Ghbe11dXZp8z5scCAS0Hed8+d53lT3PsuvfTymKOrqa Nl7xm0gZ/O3CqYEo+fxw/abf3dOZ52rc/NB/OJu3Pe8Bt1+XZJf2eQ+fg15q pfZP0vZwzc06X111dfV8zc7JrqrW86zTQyU/T5ZKdfv/FAAAACSHzo2kYynt 734L7HmTb5Dvhuvd/p5MUX253imaVBNp3fN3C8c0Rh57nvZGZ59rZ/1NT8bt 2x6cvbt6c/mn3X5d2pd8Xq3XPK1rX1RWVl6r5x41T8ttF9t9iBZqH3PNuxUV FbMkX3t1/k1tk5bH5+g4IblM1bZp5okDAABAd2RZVn9dm7isrGyCrmtkf8e9 rKq1TWmD29/JKap3V/ndksU/OCqDF2U1RR97fnJRZ5/vQN2ZL8fv276sJMHH eaf265a8fL1k51VhmXqxzqmhc7LJ9ZNramp8mqerWsft5EhlSqX6/f7B8jlF ngYAAECfpm1MuvZwRUXFRP3+bGf3ZTp+soq14CjqmGtL2be+HSmDv1eQsT3a 2POXS276WaeeK/DYV6wG3+G4fdtrv/FfYY9bFzbXua5ntlTXKpefF4XmQ5Of Z8rPubW1tRO1j47k8FFVdq7Oy8vr7/bnGAAAANAXlJaWDpHv5FnyXXyy5ndd n0hK1yrSsZzr3M4+FNXda3vJpY9F6cP+ZuR83u9wXdUTX3SybZ2PTOcal+s3 6vyRu+pv/HH8edu979ZtfDSN+ckAAACA3kW/41dUVGQEAoETdX246urqU7UN Xuctlhy/Svu8VtGHnuq7dcdbhZM3RcrhOwqHvhHx9oIh23R9bp1HQvuCy/UJ cjlOz5PpOBW/3z88WraW/P103Lnhgt4fd/XnBAAAAIDuQeecl2wxTPOF9o+V zDJDap7meLm8RGqlzmMnGZ/2eKrLS+cjs88j3Wivd/3JHN9yfUlo3Wu5Pk/n JbPnX8wNn5fM7mOSqn/nmp3Dx1JL5n4lSj/2iLc3F5r7OvXvrHHKCMnfH8bP 575zE/evGwAAAEBv5ff7BxQXF6dI7snWLK/zM8v1UyX7LJDr58nlJfLzcrm+ Wud4Zl25vl2hub7l7+FqHTttj71Youd+5Pr8UJ6uqKiYpn085Hc52t9D/8aC weDAZP897yg2J0TJ5nt3FpiI7ec7nzeXdea5rKB3pYN11d6y8g3zsAEAAABI Gm2zLC8vH1FSUqJt9OMkk02SLJYrNUMzmq5xbLfXL5G6xJ5ferW9/lwo5zMf nns5W8dR6xxlK/X90Xm/5XKBzk0WWita+3jLZab2787Pz096tk4EzdpR8rmu t/ZRxP7tfjO9M89l1Xt/FT+f+/4r0ccIAAAAAMkiGfD4UN7X8b523+Ucuy+z 5sSpmhl1TmvN/lWtffW1//Mi7Qut/aJ1/L19DmCFngew58PX9exutdt873I7 E7udx7UPhD1XgUfbtLuiPburSd6+J0o+r4w2d/tOv1nY0eexgr6BUrvi5vO6 3HOScJgAAAAA0OOFzgVof2u5nqrrVun5AD0XoKXnArRvtt2G3NIXQPv76/kA uX6WXD/PHid9eVXruOlrtR26m/X7v1P26Sqp5dpfQbN5jPuu02PQNf70fIcc 2ylymSuXY7Zt25ZiWVaPWstL8vajHc3nOwrM0o4+j7XFs9hB3/bXLcv0qNcP AAAAAHoLbZPW/uB1dXVp9fX1ozXzS/6dYo/rn63z7ZeXly/Qdn+pC+X2Zdrm L5n4Grl+s2brBOb0G+0xBpO1X4KORdBxCPI8s+zzDRfoc+t4gxj9CzbY+6Xn Ii7UfdfH61wFRUVFo3Q9brdf83CSt6uj5PCKaPm82W9Wd/R5JHv/MG4+r/f+ IBnHCAAAAADoGqE5+zT/Si4+oaamZlpFRcUsuT5PMv45mqu1L7/ddr/WYVZf J7n6HF07rLS0dEik59W50PWcguZ5PZcgl3oe4UI7m6+RWh+tvV7uf51k/cvs uddPKysr89jj11PD51ZPJp2HTfL2/oh92AtMMGr/9gKzpkPPY5l+VtD3moN1 1c5K1rECAAAAALofzb+hOfjtefpa1tPTfG33wz9qHT27zfxCuf/J2pddzwk4 eJ5+2jdAHp9jzwmgjz1bMv/F2p/eXjNtQ5Tx77fY97nYHieg+X+yPdfA0ES8 Drs2mknRMrjUq4lqP7fqcuc6WFPtNfq2AwAAAADa07Zx7ZNuz6u3MlI/es3Q OrZes7Nm9s62e+v4fp1/Tvv22+P459n9+a/QdvZoffjtddFX2/ug/QTm6nkA zfC6//Ged4ffLIiRz/dF+91uv7m0I8dnNXi+4SCf///OvHYAAAAAgL4lLy+v v2ZoOz8vsXNz+zb29fbtS+w1zTO0DT0Rz68Z3s7des5gun3eYIlmeB03H6kv vT3P3Y32fXSfztTH6nkA3bfmoiGrY+TzFxI1f7vk81oH66qdmYjXCQAAAADQ 9+jcdvaadtrevTTS2PZAIKB95Vdq+7a2bSeqb3ok8TJ8+770r5Zc8ZuoGbxw 8HPRfren0Hic7pNVN2OSg3nbX9Ex6sl6XQAAAAAAfYuurab52J6bTturb4jU L10y+/X6e53XXcfAd9V8cPKcxweDwXSdQ0/nx39744x7o2XwNzeeXLSroN/h o35X2O/AC/WFHh1Tr2Pr4/UPsBp8n4mfzz3f74rjBwAAAAD0XbqeWllZ2YTy 8vLTdb72SOu+61ptUqt0bTedx13XmuuKfZO8/flo+fy9wlE/2llw3Lvtb3+3 aPyW9n36da760Hpy9hz2M/UcgBzzCCvoK4ibz7d4Tu+K4wUAAAAAIFxpaWm6 ZFhtg14UCASujrIO2zrtly6/P0PnmHcy31tH7Sw0d8cYf/7v7z5nCooe6mc9 9NUBbXO3F5prZd8ydf46ubwj1hp1weo/fUny+aE4+fxl+rYDAAAAALoD7Xde U1MzVudfl+uX2OuuReoXf7P+3p6nfVx+fv7AY3leydu3Rcvnf73f/NuE8Rl7 x4zJsWbmpoduD+ia6aHH63h3e+33s2Wfr26/v2/XfupRB2uef+/YX0EAAAAA AJJD12eXHD5F+4tL9l0RZY21DXKfa+X3i3UNd8nvo3QMvNPn2FFglkbL5y/9 2SwfNyZz95gxY6zx40ZbFQ/327vDb6ZH2s62bdtS7DXojti//XXn1zlYV+20 xL1qAAAAAAAkn2TeVB2frnPB2+O974q1xpuuy67z1UWbw21PkfFGXeO80MzP nZz2N83nWvPnpPws0jZ0nnh7jvoj9qO2yv+5ww3TD8TJ5y8m9xUDAAAAACD5 dO45ycYn6vpu0eaeszP7Wv293k/nqquurh5ZWlo6xHp54WDJ4nsjzg/3nBk7 Zcpw7ykzMvZrPs/Kynp56NChOWHPPcAegx5x7Pkbtfc85GDN8++4+foBAAAA AJAsOm+6rsXefq3zKLl9/TuFY+pCmbzy4X7WfZ89Xq/vtyzT0k9+yhQzIjU1 dW1mZuZDw4YN+7b9HJl2G33Ube+vv8AfN5/XTz/F3VcLAAAAAIDk0r7wOo+c 1KWSpW+LlqObNl7xm6anjDXbk2qNycm2vNMyNJ9vjbZdXTtt06ZNR/WrD6s7 qysLTpX8/V6cfN7Yla8HAAAAAADdgfZpl+yca88l1zYnfNWzn33rmUF7J56Y 1TLO/MTxWdZLf8l6pv3jtS+9Zv1Ybebah751zXPvWfH7tnu/5cbrAAAAAABA dyFZ/dQj2tBLrvz1/DlpVmguuHu/uuBZXTctdH8dsy7ZPGobvK77VltbOzF0 f6ve+58O1lU72Z2jBwAAAACg+7DngLczduXd1y7L3hHK58suPfc5nWsuGAym H3m/o9d309/L/Y5Yh13nZY+Tz19w67gBAAAAAOhO8vLy+gcCgWWhrJ33lU8/ MG5sziHN57m5ua9I7r471jjzzZs336Rz0bXfrrXFM93BmuffdOOYAQAAAADo jnSNNMngK0KZe/Xq1b8bP378Hs3ot9566y+ijDG/S+edsyyrf6RtWg2erzhY V21WVx8rAAAAAADdmT3v2ydrpT322GP3rFix4onFixf/PUI+X1lRUZERa3uS zzfFyedbuurYAAAAAADoSXQttlhrsNlzwJ2jfeJjbceqnz5e8vfh2Pnc842u Oi4AAAAAAHoKy7L6Sf6et2nTpvWx8rnk9zXa1h5zWw2eO+P2ba/LndFVxwYA AAAAQE8guXuo1OWxcnm7OeGWxtqe5PO/x8nnwa46NgAAAAAAeoJAIHBivD7t UTL63Ejbs6pnj5T8fTBmPq/35nXxYQIAAADoPYZKXST1FaknpF6Rsuz6UQe3 lSr1JakyqfekPrS391epz9jPBSRVqD+7rl0eZX72FZLdz4iWz+1+8DlHbbfB d3X8vu0zct04ZgAAAAC9wkLTlsfbV0fy+blSb8fYltaURO00EElxcXGK5Osr o2Xv6urq8yW/H6f31fngYswVd7P2jQ/fthX0/TZO23m9O0cNAAAAoJdYKLVD 6lmp70qtlnrTdCyfnym1337MC1K3SXmkxkhpX+HrpR6XOiGB+w0cQfL05M2b N6+NlrnLy8sXhN9f29klr18co5/7cr1Py30bpwySDL4nZj4P+r7mzpEDAAAA 6CWOi3Bbk3Gez7WN8SX7/kVSwxK2Z4ADfr9/gOTpRbHGlFdUVJwR6bHalh6n vX1+y/2Cvgvj9m2vPemkrj1yAAAAAH1Ak3Gez2+373vA0D6OLia5O2Pz5s3X xhhLfpdcxlzvrLGxcVCcbUyyGjw/itN2vq2rjhkAAABAn9JknOfzEvu+v0/m DgHtlZeXj5b8fGdYf/S7IuTra0pKSrLibcvv9w+Xx6+JnNEr1h1u8L4ep/28 uiuOGQAAAECf02Sc5fNBprXdXO97l9RkqZ9LvS510LSOY/+D1PnJ2lH0XTo2 vF3f9HXy87II48jPcrI9bYuXx9/e/vFNNffeG7dvO3PDAQAAAEiOJuMsn59k 2uZm/4bUnrCfD5oj526/L8Z2lkpV2VUp9UxY6bxy+XZp9v+JXT+Q+rZd/0/q C2G1TmqtXddKrbRrmdRiuxaZ1rnrQqXnFibZpe2taXaxJlw3VlpaOiQQCKwO y9O3Sh6/qV3GvlXb2p1sT7Y1RvvE11U9/YW6qr98Uau5btWz5HMAAAAALmky zvL56aYtf38stVtqjWmbI84r9eew+6yNsp1VpnWOuZfs594RVoeMiblmW1fW x+327V9h+11r2s4xFJu28wu69nt+WP23aTvHcK9pO8eQZ9rOL3zWtJ1f0FoZ VheatnMMOh956PzCLNN2fkErLawGRHndE+0yqT9KfUsqpaMPtl6eMNiqm5Fm BX3ZcjlJ1xK36nLnWls8p0stbpmjLehdaTV4Vsv1tZKJ11kNvi8cqp/55Q/q Ls5vrrvqmT11y0q09tUvqdpXt2Tzh/ULt35Yt3DbwYb5Lx9qmN0gWfqfUi/Z pX3Wd9jVHDeDxx5/XprwVxMAAAAAnOfz+ebI/HpthPtoNtxi/367VL9j2C/N /aHMmW3asuhUc2Rb+HmmLcNebtqyra7zFsq8d5gj29w1U4aysh53KEM/bNqy 9RPmyLb9qrDS+cFCWV3794cy/G7TdecPnNS+sH17O2yfX2x3PP6w43wy7DV4 NOy1eTDsNXvItJ6/aHme4UP7PyjZ+gzJrTdZ9Z5/lwx7r2Tph+XyaakiqYCd kd+V2n9M2bg7VND322h/tAAAAABwDJqMs3w+w7TlvldN9Oy9Jux+vsTsYq8w xLSdb9C14kPnG/Q1Cp1r0DbyxWGlYwFC5xtuMG3nG+42beca8kxbbta637Rl 6kdMW9Z+yrRlcG3zD8/nQdOW3d8wbZk+NN9AzFp8xjD3M3OXlu87Cfy7AAAA AICQJuMsn2eYtkz2jxj3mxd2v4sTsH9wz0DTdk4h/VTvcF/xIxN/VP3YpL2T xg1seY/79zfWb743rhtk5i6seu/N7r4tAAAAAHqpJuN8fbXXTcfy+UXHunPo Fga8WXDSIqu1j3pLRt1ZdpL1q2+PtQKPTXI7LzdbQd9ruia5XH9R6oWWnxu8 b1sNvh1SH8rPie1Tv8VzottvCAAAAIBeqck4z+c/N/HHlt9s2vJ5bgL2Dy4Y MWLE1PT09HtHZ40qmXBC9v7vfe6EwwnItvvt7PySXFbJZU1Lrg76/iXX37Oz 9sdyqc+12643WrN2y2P0vnVWg2eT1Tqmvdp+7I4uOx/A3HAAAAAAkqfJOM/n Z5u27H1dhN+Hzw/3YoL2D10sLS1t/ejRo3eOGTPGCtXFC3NiZdZ3WrJyg+cp uXxULn8t9Qu5/ZGWy5afvY9L/a31ft5XE96m7ThfT/+wpTr5+Pfq73qgqqrq BLffIwAAAAC9QrpUZljpXG+ap3/a7vZhUR7/e/v+Olf5TaZtzXCPOXJ9tauS svdIqtTU1LnZ2dn7wrP52DFZH3unjmoufHjCo1a99x7J25+XfP01yavfkuvf l8t8uz17tyuZO04dbpjx4UcNp7/+Uf1pbx8OztrX2e18WHfWi5s2VawPBALn uf0+AQAAAOgV3jLO1uZ6MMrjda3r4rD7HZY62O7nLyVv95FMGRkZ39ZMLhl9 d2Zm5i9PyB55Y+DxSVdKHv+mZNRnrWNdO7zL2slnHPi4Yd6rH9Wf/tqh4Cnv JqDd/Z0dtbdMtyyrv9vvEQAAAIBe41jzuTpO6napjaZ1HS7N5zomXdfLPi1Z O47kS09P//Po0en5v79/4gbJpU9KLu90e3OXt5PX+z461HDKi4ca5r5wqGF2 U+Kyvu8dqy53rtvvDQAAAACgb5AMesYvv3vCk1ZXzrd27Nn545Y543S+uXpv vdx2KMHP8bK1NXea2+8NAAAAAKB3sxqnDLKC3tslh251PWs7r0P2mmo6d/sL ScjkofqjVT99tNvvEQAAAACgd5NcfrKdb93K2Qek3pTaIlVstfanf0T2636r 3ptnNXg+bTX4bpTblklOXig/3yq3/4+dy5O5X1tlH1a6/f4AAAAAAHo/q/ak iVbi+7HvaMna9d5Cq3VO9x+2zPMe9K2VfL1csvYiqVlyfbzcNjzuPtZMGyvb ulnu+1urdX30ZGby92XfHra2eM62LNOvK94DAAAAAECf1T8lJWVNRkb6Y1de MPqdDubXvVaDZ1NL7q73/qcV9G6QPLtU8uyclhwd9A081p2z6makSXa/tGX7 rWPJk5nH5Xi8z0n9H9n3BVZ+y5yHAAAAAAAk1bBhw2ZmZGQ8n5OT07qm+dgc 6y8PToqWXV9qyeFB3xdb8nLdjEnJaFNubUf3XivP80CS5nY78piC3t9Z9Z67 5XlPsfwLByT6eAAAAAAAiGXEiBFTs7KyXtNcHqqcnGxr1cWjD7eMtW7w/Fry 8eckJ59rVc8emYx9sKrmDrUafGe2jin3Pir1ShKzuK7R/qQc0z2SxZfIcaUn 45gAAAAAAOiItLS0b32SzbOzdi08PbPgU9dnrbNqZw5LxvNpX/eWNup6zx1W 0PuzlvXPGrwfJTGPfyTPUSDZ/yu6Rhxt4wAAAACA7igzM/OpnJycj9PT038+ ePDgicl4Duuf0zIlH39esvKzUvuTPHZc63XJ5D+VWmFVTUpNxjEBAAAAAJBI aWlpT6Wmpq5NxrYty/S3c3lzkvP4wZY28qD3S3I5mznWAQAAAAA9zeDBgyck Y7vWyxMGSzZ/KomZvFHy+I+tLZ7LrW0npSTjGAAAAAAA6OkkP/88wXn8n5L3 /7tlTveaaWPdPj4AAAAAALqp41JSUm5OS0t75I6rs+89xiy+u2WsetD3zZZ1 1GtnZrl9cAAAAAAAdHfDhw9fmJGRURlaP33Bqdn7DtZ4nGbxQy3rm+t8bvWe W6wtnuk6bt3tYwIAAAAAoCeRbL4yOzt775Hrp+dY3/ns2Lcke79/VB4P+t5p GZde7/myFfSeZzVOGeH2MQAAAAAA0NNlZmYWhXL5qFGj3k5NTX1g8ODB58iv WtYZt6rmHm9tO2mMVT99plU3Y5LLuwsAAAAAQG80PCsra3d2dvYHI0eO/OGw YcOy3d4hAAAAAAD6oNGZmZnbhw4derHbOwIAAAAAQB82ZNiwYbPd3gkAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAABLtfwFLfqEE "], "Byte", ColorSpace -> "RGB", Interleaving -> True]]], "Output", CellChangeTimes->{3.756081692872864*^9, 3.756081756612796*^9}, CellLabel->"Out[1]=", CellID->428876372] }, Open ]] }, Open ]] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell["Source & Additional Information", "Section", Deletable->False, CellTags->"Source & Additional Information", CellID->318391102], Cell[CellGroupData[{ Cell[TextData[{ "Contributed By", Cell[BoxData[ TemplateBox[{"Contributed By",Cell[ BoxData[ FrameBox[ Cell[ "Name of the person, people or organization that should be publicly \ credited with contributing the function.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoContributedBy"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Subsection", Deletable->False, DefaultNewCellStyle->"Text", CellTags->"Contributed By", CellID->757508554], Cell["Rick Hennigan", "Text", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.7560805016195064`*^9, 3.7560805039474545`*^9}, 3.7560808169383*^9}, CellTags->"TabNext", CellID->832483124] }, Open ]], Cell[CellGroupData[{ Cell[TextData[{ "Keywords", Cell[BoxData[ TemplateBox[{"Keywords",Cell[ BoxData[ FrameBox[ Cell[ "List relevant terms that should be used to include this resource in \ search results.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoKeywords"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Subsection", Deletable->False, DefaultNewCellStyle->"Item", CellTags->"Keywords", CellID->246422893], Cell[CellGroupData[{ Cell["bird", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.7560805065463724`*^9, 3.7560805096542616`*^9}}, CellTags->"TabNext", CellID->123227828], Cell["bird say", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.7560805065463724`*^9, 3.7560805116702003`*^9}}, CellID->737928356], Cell["nine-patch image", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.7560805065463724`*^9, 3.756080520540908*^9}}, CellID->453776788], Cell["9-patch image", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.7560805065463724`*^9, 3.756080527381688*^9}}, CellID->23822048], Cell["custom frame box", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.7560805065463724`*^9, 3.7560805369703875`*^9}}, CellID->580037425] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[TextData[{ "Related Symbols", Cell[BoxData[ TemplateBox[{"Related Symbols",Cell[ BoxData[ FrameBox[ Cell[ "List related Wolfram Language symbols. Include up to twenty \ documented, system-level symbols.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoRelatedSymbols"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Subsection", Deletable->False, DefaultNewCellStyle->"Item", CellTags->"Related Symbols", CellID->911170439], Cell[CellGroupData[{ Cell["Framed", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.756080544971129*^9, 3.7560805574387145`*^9}}, CellTags->"TabNext", CellID->79477165], Cell["Panel", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.756080544971129*^9, 3.7560805598136344`*^9}}, CellID->1786201], Cell["Labeled", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.756080544971129*^9, 3.7560805731992054`*^9}}, CellID->143754847], Cell["Tooltip", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.756080544971129*^9, 3.75608058584479*^9}}, CellID->934352842], Cell["Style", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.756080544971129*^9, 3.756080586833769*^9}}, CellID->589392240] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[TextData[{ "Related Resource Objects", Cell[BoxData[ TemplateBox[{"Related Resource Objects",Cell[ BoxData[ FrameBox[ Cell[ "Names of published resource objects from any Wolfram repository that \ are related to this resource.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoRelatedResourceObjects"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Subsection", Deletable->False, DefaultNewCellStyle->"Item", CellTags->"Related Resource Objects", CellID->217060377], Cell[CellGroupData[{ Cell["Circled", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.756080594842511*^9, 3.756080598537364*^9}}, CellTags->"TabNext", CellID->960273585], Cell["Minesweeper", "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.756080594842511*^9, 3.756080595770479*^9}, { 3.7560806406589947`*^9, 3.7560806429309206`*^9}}, CellID->377337373] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[TextData[{ "Source/Reference Citation", Cell[BoxData[ TemplateBox[{"Source/Reference Citation",Cell[ BoxData[ FrameBox[ Cell[ "Citation for original source of the function or its components. For \ example, original publication of an algorithm or public code repository.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoSourceReferenceCitation"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Subsection", Deletable->False, DefaultNewCellStyle->"Text", CellTags->"Source/Reference Citation", CellID->967310595], Cell["Source, reference or citation information", "Text", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellTags->"TabNext", CellID->343081869] }, Open ]], Cell[CellGroupData[{ Cell[TextData[{ "Links", Cell[BoxData[ TemplateBox[{"Links",Cell[ BoxData[ FrameBox[ Cell[ "URLs or hyperlinks for external information related to the function.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoLinks"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Subsection", Deletable->False, DefaultNewCellStyle->"Item", CellTags->"Links", CellID->593846556], Cell[CellGroupData[{ Cell[TextData[ButtonBox["Bird", BaseStyle->"Hyperlink", ButtonData->{ URL["https://en.wikipedia.org/wiki/Bird_(disambiguation)"], None}, ButtonNote->"https://en.wikipedia.org/wiki/Bird_(disambiguation)"]], "Item", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellChangeTimes->{{3.756080735970933*^9, 3.7560807443856583`*^9}}, CellTags->"TabNext", CellID->485448166], Cell[TextData[ButtonBox["Birds", BaseStyle->"Hyperlink", ButtonData->{ URL["https://en.wikipedia.org/wiki/Birds_(disambiguation)"], None}, ButtonNote->"https://en.wikipedia.org/wiki/Birds_(disambiguation)"]], "Item",\ CellChangeTimes->{{3.756081574273733*^9, 3.7560815907252035`*^9}}, CellID->472790593] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[TextData[{ "Tests", Cell[BoxData[ TemplateBox[{"Tests",Cell[ BoxData[ FrameBox[ Cell[ "Optional list of tests that can be used to verify that the function \ is working properly in any environment.\nTests can be specified as \ Input/Output cell pairs or as literal VerificationTest expressions if you \ need to specify options.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoTests"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Subsection", Deletable->False, DefaultNewCellStyle->"Input", CellTags->"Tests", CellID->16051757], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"MyFunction", "[", RowBox[{"x", ",", "y"}], "]"}]], "Input", CellLabel->"In[3]:=", CellID->667877521], Cell[BoxData[ RowBox[{"x", " ", "y"}]], "Output", CellLabel->"Out[3]=", CellID->993233288] }, Open ]] }, Open ]] }, Closed]], Cell["Author Notes", "Section", Deletable->False, DefaultNewCellStyle->"Text", CellTags->"Author Notes", CellID->795110225], Cell[CellGroupData[{ Cell[TextData[{ "Submission Notes", Cell[BoxData[ TemplateBox[{"Submission Notes",Cell[ BoxData[ FrameBox[ Cell[ "Enter any additional information that you would like to communicate \ to the reviewer here. This section will not be included in the published \ resource.", "MoreInfoText"], Background -> GrayLevel[0.95], FrameMargins -> 20, FrameStyle -> GrayLevel[0.9], RoundingRadius -> 5]], "MoreInfoText", Deletable -> True, CellTags -> {"SectionMoreInfoSubmissionNotes"}, CellMargins -> {{66, 66}, {15, 15}}]}, "MoreInfoOpenerButtonTemplate"]]] }], "Section", Deletable->False, DefaultNewCellStyle->"Text", CellTags->"Submission Notes", CellID->843283583], Cell["Additional information for the reviewer.", "Text", CellEventActions->{Inherited, {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]], PassEventsDown -> False, PassEventsUp -> False}, CellTags->"TabNext", CellID->920818074] }, Open ]] }, Open ]] }, WindowSize->Automatic, WindowMargins->Automatic, TaggingRules->{ "ResourceType" -> "Function", "ResourceCreateNotebook" -> True, "TemplateVersion" -> "1.2.10"}, CreateCellID->True, FrontEndVersion->"11.3 for Linux x86 (64-bit) (March 6, 2018)", StyleDefinitions->Notebook[{ Cell[ StyleData[StyleDefinitions -> "Default.nb"]], Cell[ StyleData[All, "Working"], DockedCells -> { Cell[ BoxData[ TagBox[ GridBox[{{ TagBox[ GridBox[{{ GraphicsBox[{ Thickness[0.022222222222222223`], { FaceForm[{ RGBColor[0.87451, 0.278431, 0.03137260000000001], Opacity[1.]}], FilledCurveBox[{{{1, 4, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}}}, {{{45., 22.5}, {45., 10.073999999999998`}, {34.926, 0.}, {22.5, 0.}, {10.074, 0.}, {0., 10.073999999999998`}, {0., 22.5}, {0., 34.926}, {10.074, 45.}, {22.5, 45.}, {34.926, 45.}, {45., 34.926}, {45., 22.5}}}]}, { FaceForm[{ RGBColor[1., 1., 1.], Opacity[1.]}], FilledCurveBox[{{{0, 2, 0}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {0, 1, 0}, {0, 1, 0}, {1, 3, 3}, {0, 1, 0}, {0, 1, 0}, {1, 3, 3}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {1, 3, 3}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}}, {{0, 2, 0}, {0, 1, 0}, {0, 1, 0}, {1, 3, 3}, {0, 1, 0}, {1, 3, 3}, {0, 1, 0}}, {{0, 2, 0}, {1, 3, 3}, {0, 1, 0}, {1, 3, 3}, {0, 1, 0}, {1, 3, 3}, {0, 1, 0}, {1, 3, 3}}, {{0, 2, 0}, {1, 3, 3}, {0, 1, 0}, {1, 3, 3}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}}}, {CompressedData[" 1:eJxTTMoPSmViYGAwAWIQLcESxqe7SdlhqnN3zvPblg4w/omyffOl/K0cEp9e ULq9U9lhT8lkCZZrVg6VL9UMOd4oO1SLrHN/GGXtcKUCKOCh4sDDpN0udtPa 4fnvlR8v8ao6ZIE12ELMrVZzmAIymNfOAWj43PfpGg45YIV2Dguk9O+qsGlB 9M+0h9gjpgOxh8fBYePc98uPees5MICAggNE/TF9B6Bl574rO0DcMcsAwmd2 cNCM6T/0VcPQAeQsjh6oeWWGEPt97R3UDTnWyMwyhKh7Yefw5S/QB22GEHe1 2zlIg5yTaAh3by7InUKGDmBnLrR1cOkGudzAYZHrts9/Q2wdHi+dfUShwMBh Q1HGxLcytg5BO+RaXwsaQN1r6/BdA2jRVn1oeNk6aIEcWq4HcccvWwfTuF2e PEy6UPPtHIC+CH68VBvOP70QaNFeLTg/T6j5wKlELYdPl3yTBCLsIOGkowVx 71tbhycg93zQdAjonZ4ndNgGzgern2ENVw90TZVInhUkfqy1IO65ZQl3L4wP iW99B/NOx4SnEyzh4Q+W32XhcBUc0PoQd7dawM1D568H2cdnCOd/A9nzVc/h I9hdWg4ZoIg6oueQD/Kfoh40nSD4fkDfWpboQOw7oYDBh6mHxIcy3DxYek4A peOfCD7MPTA+zL0yUSnW9/sV4Hxw/DgpQOL7igUkfi8qwsMHAHSDTZ8= "], {{19.051000000000002`, 14.242}, {19.051000000000002`, 27.594}, {23.828, 27.594}, {23.828, 26.543}, {21.426, 26.308999999999997`}, {21.375, 26.258000000000003`}, { 21.375, 24.219}, {21.375, 17.535000000000004`}, {21.375, 15.602}, {21.426, 15.547}, {23.828, 15.315999999999999`}, {23.828, 14.242}}, {{24.578, 18.75}, {24.578, 23.078000000000003`}, {24.578, 23.539}, { 24.953, 23.914}, {25.418, 23.91}, {29.746, 23.91}, { 30.203, 23.91}, {30.578, 23.539}, {30.578, 23.078000000000003`}, {30.578, 18.75}, { 30.581999999999997`, 18.288999999999998`}, {30.207, 17.91}, {29.746, 17.91}, {25.418, 17.91}, {24.953, 17.906}, {24.574, 18.285}, {24.578, 18.75}}, {{31.328, 14.242}, {31.328, 15.315999999999999`}, {33.684, 15.539000000000001`}, {33.789, 15.602}, {33.789, 17.641}, {33.789, 24.188}, {33.789, 26.227}, {33.684, 26.281}, {31.328, 26.512000000000004`}, {31.328, 27.586}, {36.113, 27.586}, {36.113, 14.234000000000002`}}}]}}, { Background -> RGBColor[ 0.9882352941176471, 0.4196078431372549, 0.20392156862745098`], AspectRatio -> Automatic, ImageSize -> {45., 45.}, PlotRange -> {{0., 45.}, {0., 45.}}}], StyleBox[ "\"Function Resource Definition Notebook\"", FontFamily -> "Source Sans Pro", FontWeight -> Bold, FontSize -> 26, FontColor -> GrayLevel[1], StripOnInput -> False]}}, GridBoxAlignment -> { "Columns" -> {{Left}}, "Rows" -> {{Center}}}, AutoDelete -> False, GridBoxItemSize -> { "Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"], "\[SpanFromLeft]", "\[SpanFromLeft]", "\[SpanFromLeft]", "\[SpanFromLeft]", "\[SpanFromLeft]", "\[SpanFromLeft]", ItemBox[ TemplateBox[{ StyleBox[ "\"Function Repository \[RightGuillemet]\"", "Text", FontColor -> GrayLevel[1], StripOnInput -> False], "https://resources.wolframcloud.com/FunctionRepository/"}, "HyperlinkURL"], Alignment -> {Right, Bottom}, StripOnInput -> False]}, { ButtonBox[ TagBox[ TooltipBox[ StyleBox[ "\"Open Sample Notebook\"", "Text", FontFamily -> "Source Sans Pro", FontWeight -> Bold, FontSize -> 13, FontColor -> GrayLevel[1], StripOnInput -> False], "\"View a completed sample definition notebook.\"", LabelStyle -> "TextStyling"], Annotation[#, "View a completed sample definition notebook.", "Tooltip"]& ], ButtonFunction :> (Symbol["System`ResourceFunction"]; FunctionResource`DefinitionNotebook`Private`showProgress[ FunctionResource`DefinitionNotebook`Private`\ viewExampleNotebook[]]), FrameMargins -> 0, Appearance -> {"Default" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PImSfFdud67eiMoKtcDiuDUEiHzNk/zXY0h Qj0E1RgCxYGymFreFmq9qzVCVw9BtUZAWTQtIPdgmo9qF8SFkGABWVFlgE89 GAHVILREyLyrw2sFBNUZAlUygAGpWsiwhUy/kBViZMQLebFPThojJSWTml8A +GMDZA== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.3408331`9.347418435291374}, "Instant", "Gregorian", -4.]]]], "Hover" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PIhRulnuv6fbBMIArKBIri0vAmX+Zas9TvL CK4egoAiQHGgLKaW7yk6f7JM0NRDUZYJUBZNC9B2TPPR7IK4EBIsQMavTEM8 6iEIqAauBejOP9nGBLUA1QBVMoABqVrIsIU8v5AXYmTEC3mxT0YaIyklk5pf AJBwAV4= "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.3758572`9.34780490414085}, "Instant", "Gregorian", -4.]]]], "Pressed" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PKxLfr3teNw04BsoAguLW9ilL5vnPr3ypG/ E9L/ZJtAEJANFAGKA2UxtfzYveTvjvlwxcgIKA6URdMCtB1oGlb1UF1XjkBc CAkWIOPPw2t/26PwaQHKPrwG1wJ05/9fP/CohyCgGqBKBjAgVQsZtpDnF/JC jIx4IS/2yUhjJKVkUvMLAMWzMVI= "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.4378565`9.348488185213698}, "Instant", "Gregorian", -4.]]]]}, Background -> RGBColor[ 0.9215686274509803, 0.3411764705882353, 0.10588235294117647`], Method -> "Queued", ImageSize -> All, Evaluator -> Automatic], ButtonBox[ TagBox[ TooltipBox[ StyleBox[ "\"Style Guidelines\"", "Text", FontFamily -> "Source Sans Pro", FontWeight -> Bold, FontSize -> 13, FontColor -> GrayLevel[1], StripOnInput -> False], "\"\"", LabelStyle -> "TextStyling"], Annotation[#, "", "Tooltip"]& ], ButtonFunction :> (Symbol["System`ResourceFunction"]; FunctionResource`DefinitionNotebook`Private`showProgress[ MessageDialog["Coming soon"]]), FrameMargins -> 0, Appearance -> {"Default" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PImSfFdud67eiMoKtcDiuDUEiHzNk/zXY0h Qj0E1RgCxYGymFreFmq9qzVCVw9BtUZAWTQtIPdgmo9qF8SFkGABWVFlgE89 GAHVILREyLyrw2sFBNUZAlUygAGpWsiwhUy/kBViZMQLebFPThojJSWTml8A +GMDZA== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.3408331`9.347418435291374}, "Instant", "Gregorian", -4.]]]], "Hover" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PIhRulnuv6fbBMIArKBIri0vAmX+Zas9TvL CK4egoAiQHGgLKaW7yk6f7JM0NRDUZYJUBZNC9B2TPPR7IK4EBIsQMavTEM8 6iEIqAauBejOP9nGBLUA1QBVMoABqVrIsIU8v5AXYmTEC3mxT0YaIyklk5pf AJBwAV4= "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.3758572`9.34780490414085}, "Instant", "Gregorian", -4.]]]], "Pressed" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PKxLfr3teNw04BsoAguLW9ilL5vnPr3ypG/ E9L/ZJtAEJANFAGKA2UxtfzYveTvjvlwxcgIKA6URdMCtB1oGlb1UF1XjkBc CAkWIOPPw2t/26PwaQHKPrwG1wJ05/9fP/CohyCgGqBKBjAgVQsZtpDnF/JC jIx4IS/2yUhjJKVkUvMLAMWzMVI= "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.4378565`9.348488185213698}, "Instant", "Gregorian", -4.]]]]}, Background -> RGBColor[ 0.9215686274509803, 0.3411764705882353, 0.10588235294117647`], Method -> "Queued", ImageSize -> All, Evaluator -> Automatic], TagBox[ GridBox[{{"\"\"", "\"\""}}, GridBoxAlignment -> { "Columns" -> {{Left}}, "Rows" -> {{Center}}}, AutoDelete -> False, GridBoxDividers -> { "ColumnsIndexed" -> {2 -> True}, "Rows" -> {{False}}}, GridBoxItemSize -> { "Columns" -> {{Automatic}}, "Rows" -> {{2}}}, FrameStyle -> RGBColor[ 0.9941176470588236, 0.7098039215686275, 0.6019607843137255]], "Grid"], ActionMenuBox[ ButtonBox[ TagBox[ TooltipBox[ StyleBox[ TagBox[ GridBox[{{"\"Preview\"", "\"\[DownPointer]\""}}, AutoDelete -> False, GridBoxDividers -> { "Columns" -> {False, {True}, False}, "Rows" -> {False, {True}, False}}, GridBoxItemSize -> { "Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, FrameStyle -> RGBColor[ 0.9941176470588236, 0.7098039215686275, 0.6019607843137255]], "Grid"], "Text", FontFamily -> "Source Sans Pro", FontWeight -> Bold, FontSize -> 13, FontColor -> GrayLevel[1], StripOnInput -> False], "\"\"", LabelStyle -> "TextStyling"], Annotation[#, "", "Tooltip"]& ], ButtonFunction :> (Symbol["System`ResourceFunction"]; FunctionResource`DefinitionNotebook`Private`showProgress[ Null]), FrameMargins -> 0, Appearance -> {"Default" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PImSfFdud67eiMoKtcDiuDUEiHzNk/zXY0h Qj0E1RgCxYGymFreFmq9qzVCVw9BtUZAWTQtIPdgmo9qF8SFkGABWVFlgE89 GAHVILREyLyrw2sFBNUZAlUygAGpWsiwhUy/kBViZMQLebFPThojJSWTml8A +GMDZA== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.3408331`9.347418435291374}, "Instant", "Gregorian", -4.]]]], "Hover" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PIhRulnuv6fbBMIArKBIri0vAmX+Zas9TvL CK4egoAiQHGgLKaW7yk6f7JM0NRDUZYJUBZNC9B2TPPR7IK4EBIsQMavTEM8 6iEIqAauBejOP9nGBLUA1QBVMoABqVrIsIU8v5AXYmTEC3mxT0YaIyklk5pf AJBwAV4= "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.3758572`9.34780490414085}, "Instant", "Gregorian", -4.]]]], "Pressed" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PKxLfr3teNw04BsoAguLW9ilL5vnPr3ypG/ E9L/ZJtAEJANFAGKA2UxtfzYveTvjvlwxcgIKA6URdMCtB1oGlb1UF1XjkBc CAkWIOPPw2t/26PwaQHKPrwG1wJ05/9fP/CohyCgGqBKBjAgVQsZtpDnF/JC jIx4IS/2yUhjJKVkUvMLAMWzMVI= "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.4378565`9.348488185213698}, "Instant", "Gregorian", -4.]]]]}, Background -> RGBColor[ 0.9215686274509803, 0.3411764705882353, 0.10588235294117647`], Method -> "Queued", ImageSize -> All, Evaluator -> Automatic], { "\"In a notebook\"" :> (Symbol["System`ResourceFunction"]; FunctionResource`DefinitionNotebook`Private`getResource[ ButtonNotebook[], "Preview"]), "\"On the cloud\"" :> (Symbol["System`ResourceFunction"]; FunctionResource`DefinitionNotebook`Private`getResource[ ButtonNotebook[], "Cloud"])}, Appearance -> None, Method -> "Queued"], ActionMenuBox[ ButtonBox[ TagBox[ TooltipBox[ StyleBox[ TagBox[ GridBox[{{"\"Deploy\"", "\"\[DownPointer]\""}}, AutoDelete -> False, GridBoxDividers -> { "Columns" -> {False, {True}, False}, "Rows" -> {False, {True}, False}}, GridBoxItemSize -> { "Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, FrameStyle -> RGBColor[ 0.9941176470588236, 0.7098039215686275, 0.6019607843137255]], "Grid"], "Text", FontFamily -> "Source Sans Pro", FontWeight -> Bold, FontSize -> 13, FontColor -> GrayLevel[1], StripOnInput -> False], "\"\"", LabelStyle -> "TextStyling"], Annotation[#, "", "Tooltip"]& ], ButtonFunction :> (Symbol["System`ResourceFunction"]; FunctionResource`DefinitionNotebook`Private`showProgress[ Null]), FrameMargins -> 0, Appearance -> {"Default" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PImSfFdud67eiMoKtcDiuDUEiHzNk/zXY0h Qj0E1RgCxYGymFreFmq9qzVCVw9BtUZAWTQtIPdgmo9qF8SFkGABWVFlgE89 GAHVILREyLyrw2sFBNUZAlUygAGpWsiwhUy/kBViZMQLebFPThojJSWTml8A +GMDZA== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.3408331`9.347418435291374}, "Instant", "Gregorian", -4.]]]], "Hover" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PIhRulnuv6fbBMIArKBIri0vAmX+Zas9TvL CK4egoAiQHGgLKaW7yk6f7JM0NRDUZYJUBZNC9B2TPPR7IK4EBIsQMavTEM8 6iEIqAauBejOP9nGBLUA1QBVMoABqVrIsIU8v5AXYmTEC3mxT0YaIyklk5pf AJBwAV4= "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.3758572`9.34780490414085}, "Instant", "Gregorian", -4.]]]], "Pressed" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PKxLfr3teNw04BsoAguLW9ilL5vnPr3ypG/ E9L/ZJtAEJANFAGKA2UxtfzYveTvjvlwxcgIKA6URdMCtB1oGlb1UF1XjkBc CAkWIOPPw2t/26PwaQHKPrwG1wJ05/9fP/CohyCgGqBKBjAgVQsZtpDnF/JC jIx4IS/2yUhjJKVkUvMLAMWzMVI= "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.4378565`9.348488185213698}, "Instant", "Gregorian", -4.]]]]}, Background -> RGBColor[ 0.9215686274509803, 0.3411764705882353, 0.10588235294117647`], Method -> "Queued", ImageSize -> All, Evaluator -> Automatic], { "\"Locally on this computer\"" :> ( Symbol["System`ResourceFunction"]; FunctionResource`DefinitionNotebook`Private`getResource[ ButtonNotebook[], "Local"]), "\"For my cloud account\"" :> ( Symbol["System`ResourceFunction"]; FunctionResource`DefinitionNotebook`Private`getResource[ ButtonNotebook[], "Cloud"]), "\"Publicly in the cloud\"" :> ( Symbol["System`ResourceFunction"]; FunctionResource`DefinitionNotebook`Private`getResource[ ButtonNotebook[], "CloudPublic"]), "\"In this session only (without documentation)\"" :> ( Symbol["System`ResourceFunction"]; FunctionResource`DefinitionNotebook`Private`getResource[ ButtonNotebook[], "KernelSession"])}, Appearance -> None, Method -> "Queued"], DynamicBox[ ToBoxes[ CurrentValue[ EvaluationNotebook[], {TaggingRules, "StatusMessage"}, ""], StandardForm]], ItemBox["\"\"", ItemSize -> Fit, StripOnInput -> False], ButtonBox[ TagBox[ TooltipBox[ StyleBox[ "\"Submit to Repository\"", "Text", FontFamily -> "Source Sans Pro", FontWeight -> Bold, FontSize -> 13, FontColor -> GrayLevel[1], StripOnInput -> False], "\"Submit your function to the Wolfram Function Repository.\"", LabelStyle -> "TextStyling"], Annotation[#, "Submit your function to the Wolfram Function Repository.", "Tooltip"]& ], ButtonFunction :> (Symbol["System`ResourceFunction"]; FunctionResource`DefinitionNotebook`Private`showProgress[ FunctionResource`DefinitionNotebook`Private`submitRepository[ ButtonNotebook[]]]), FrameMargins -> 0, Appearance -> {"Default" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PImSfFdud67eiMoKtcDiuDUEiHzNk/zXY0h Qj0E1RgCxYGymFreFmq9qzVCVw9BtUZAWTQtIPdgmo9qF8SFkGABWVFlgE89 GAHVILREyLyrw2sFBNUZAlUygAGpWsiwhUy/kBViZMQLebFPThojJSWTml8A +GMDZA== "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.3408331`9.347418435291374}, "Instant", "Gregorian", -4.]]]], "Hover" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PIhRulnuv6fbBMIArKBIri0vAmX+Zas9TvL CK4egoAiQHGgLKaW7yk6f7JM0NRDUZYJUBZNC9B2TPPR7IK4EBIsQMavTEM8 6iEIqAauBejOP9nGBLUA1QBVMoABqVrIsIU8v5AXYmTEC3mxT0YaIyklk5pf AJBwAV4= "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.3758572`9.34780490414085}, "Instant", "Gregorian", -4.]]]], "Pressed" -> Image[CompressedData[" 1:eJxTTMoPSmNiYGAo5gASQYnljkVFiZXBAkBOaF5xZnpeaopnXklqemqRRRIz UFAQikHs/zgAHikgeB0uTTzC1PKxLfr3teNw04BsoAguLW9ilL5vnPr3ypG/ E9L/ZJtAEJANFAGKA2UxtfzYveTvjvlwxcgIKA6URdMCtB1oGlb1UF1XjkBc CAkWIOPPw2t/26PwaQHKPrwG1wJ05/9fP/CohyCgGqBKBjAgVQsZtpDnF/JC jIx4IS/2yUhjJKVkUvMLAMWzMVI= "], "Byte", ColorSpace -> "RGB", Interleaving -> True, MetaInformation -> Association[ "Comments" -> Association[ "Software" -> "Wolfram Mathematica 8.0", "Creation Time" -> DateObject[{ 2018, 10, 9, 12, 3, 39.4378565`9.348488185213698}, "Instant", "Gregorian", -4.]]]]}, Background -> RGBColor[ 0.9215686274509803, 0.3411764705882353, 0.10588235294117647`], Method -> "Queued", ImageSize -> All, Evaluator -> Automatic]}}, GridBoxAlignment -> {"Columns" -> {{Left}}, "Rows" -> {{Center}}}, AutoDelete -> False, GridBoxBackground -> {"Columns" -> {{None}}, "Rows" -> { RGBColor[ 0.9882352941176471, 0.4196078431372549, 0.20392156862745098`], RGBColor[ 0.9215686274509803, 0.3411764705882353, 0.10588235294117647`]}}, GridBoxFrame -> { "Columns" -> False, "RowsIndexed" -> { 1 -> RGBColor[ 0.9882352941176471, 0.4196078431372549, 0.20392156862745098`], 2 -> RGBColor[ 0.9215686274509803, 0.3411764705882353, 0.10588235294117647`]}}, GridBoxItemSize -> { "Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings -> { "Columns" -> {5, {}, 5}, "Rows" -> {2, 2, {}, 2}}, FrameStyle -> RGBColor[ 0.9882352941176471, 0.4196078431372549, 0.20392156862745098`]], "Grid"]], "DockedCell", CellFrameMargins -> -1]}], Cell[ StyleData["Item"], DefaultNewCellStyle -> "Item"], Cell[ StyleData["MoreInfoText", StyleDefinitions -> StyleData["Text"]], FontColor -> GrayLevel[0.25]], Cell[ StyleData["ErrorText", StyleDefinitions -> StyleData["Text"]], ShowCellBracket -> False, CellMargins -> {{66, Inherited}, {0, 0}}, CellElementSpacings -> {"CellMinHeight" -> 0, "ClosedCellHeight" -> 0}, FontWeight -> Bold, FontColor -> RGBColor[1, 0, 0]], Cell[ StyleData["WarningText", StyleDefinitions -> StyleData["Text"]], ShowCellBracket -> False, CellMargins -> {{66, Inherited}, {0, 0}}, CellElementSpacings -> {"CellMinHeight" -> 0, "ClosedCellHeight" -> 0}, FontWeight -> Bold, FontColor -> RGBColor[1, 1, 0]], Cell[ StyleData["ButtonText"], FontFamily -> "Sans Serif", FontSize -> 11, FontWeight -> Bold, FontColor -> RGBColor[0.458824, 0.458824, 0.458824]], Cell[ StyleData["MoreInfoOpenerIconTemplate"], TemplateBoxOptions -> { DisplayFunction -> (PaneSelectorBox[{False -> GraphicsBox[{ Thickness[0.07142857142857142], StyleBox[{ JoinedCurveBox[{{{1, 4, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}}}, CompressedData[" 1:eJxTTMoPSmVmYGBgBGJJIGYCYpfunOe/V2o6MICBjAOM//GSb5KAhKLD46Wz jygUaDjIRKVY3+dXgahzUIPTMHGYOpg+XObKgtSfF4Xze6fnCTUf4Ifr/w8G bHDzn15Quv2z7o89zJ4nIHUbPtnD7IHxYfbA+DB7YPph9sDMh9EwcZg6mD5c 5qLbC3MXTD/M3TDzYf6C2YMrHGD2AAAVXK28 "], CurveClosed -> {1}]}, JoinForm[{"Miter", 3.25}], Thickness[0.049999999999999996`], RGBColor[0.627441, 0.627441, 0.627441, 1.], StripOnInput -> False], StyleBox[{ FilledCurveBox[{{{1, 4, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}}, {{0, 2, 0}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {1, 3, 3}, {1, 3, 3}, {0, 1, 0}, {1, 3, 3}, {1, 3, 3}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {1, 3, 3}, {1, 3, 3}, {0, 1, 0}}}, {CompressedData[" 1:eJxTTMoPSmViYGCQBGIQ/Tcg88iZOhmHGu7Xx3YXKzm03fzoEzpdGs7nS6q6 eve8lMOjwkBdpVlKDtNeMcWlaUg5rLeT+/XumZKDfHH3s3cNkhD1xsoOydvP axnrSjrM0+V9eXcqgi+2tCUhlFcFzu+R+XP9TIsKXD/Y/GcqcPPB6g1V4fZ7 3Ng+uaNGFe4+sPpFqg4w98P4b+wjNu/OlYXzwerN5eD6T8maTZx5Ww7V/Hp5 uP0GLXO+/78oD3cfjA9zP4wP8x9MP8z/MPNh4QOzHxZ+MPfBwhc9/AFZSbHT "], CompressedData[" 1:eJxTTMoPSmViYGCQB2IQLeF07vf/KwoOe35VvNh9m88Bxg+bItQUGsrtcErW bOLMbHEMPky9Qcuc7/8vSjp80F0j/f4cP5xvEy11afdrATjfN0f78Zk/gnC+ thfnwVVSwnC+lOWP9TMtReD8Z6xHa9LMROH8SRvy1QUFxdD4EnA+p8bzeR0a knD+ooMNFkpCUnB+XK3Nl7tnpVDt65RGlfeVQXOfLIQvKe7wQ+xab3k5gn/0 8aIolz9yDinbz2sZ35VzWG8n9+vdKQWIfKK8Qw3362O7pyP4EP3ScD6Kf4B8 FP8C+Q3z48QYLETgfLD7RIXhfHD4fhaE88HueSIA58PiAz1+AUR/638= "]}]}, FaceForm[ RGBColor[0.627441, 0.627441, 0.627441, 1.]], StripOnInput -> False]}, ImageSize -> {14., 14.}, PlotRange -> {{0., 14.}, {0., 14.}}, AspectRatio -> Automatic], True -> GraphicsBox[{ Thickness[0.07142857142857142], StyleBox[{ JoinedCurveBox[{{{1, 4, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}}}, CompressedData[" 1:eJxTTMoPSmVmYGBgBGJJIGYCYpfunOe/V2o6MICBjAOM//GSb5KAhKLD46Wz jygUaDjIRKVY3+dXgahzUIPTMHGYOpg+XObKgtSfF4Xze6fnCTUf4Ifr/w8G bHDzn15Quv2z7o89zJ4nIHUbPtnD7IHxYfbA+DB7YPph9sDMh9EwcZg6mD5c 5qLbC3MXTD/M3TDzYf6C2YMrHGD2AAAVXK28 "], CurveClosed -> {1}]}, JoinForm[{"Miter", 3.25}], Thickness[0.049999999999999996`], RGBColor[0.5, 0.5, 0.5, 1.], StripOnInput -> False], StyleBox[{ FilledCurveBox[{{{1, 4, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}}}, CompressedData[" 1:eJxTTMoPSmVmYGBgBGJJIGYCYpfunOe/V2o6MICBjAOM//GSb5KAhKLD46Wz jygUaDjIRKVY3+dXgahzUIPTMHGYOpg+XObKgtSfF4Xze6fnCTUf4Ifr/w8G bHDzn15Quv2z7o89zJ4nIHUbPtnD7IHxYfbA+DB7YPph9sDMh9EwcZg6mD5c 5qLbC3MXTD/M3TDzYf6C2YMrHGD2AAAVXK28 "]]}, FaceForm[ RGBColor[0.5, 0.5, 0.5, 1.]], StripOnInput -> False], StyleBox[{ FilledCurveBox[{{{1, 4, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}, {1, 3, 3}}, {{0, 2, 0}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {1, 3, 3}, {1, 3, 3}, {0, 1, 0}, {1, 3, 3}, {1, 3, 3}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {0, 1, 0}, {1, 3, 3}, {1, 3, 3}, {0, 1, 0}}}, {CompressedData[" 1:eJxTTMoPSmViYGCQBGIQ/Tcg88iZOhmHGu7Xx3YXKzm03fzoEzpdGs7nS6q6 eve8lMOjwkBdpVlKDtNeMcWlaUg5rLeT+/XumZKDfHH3s3cNkhD1xsoOydvP axnrSjrM0+V9eXcqgi+2tCUhlFcFzu+R+XP9TIsKXD/Y/GcqcPPB6g1V4fZ7 3Ng+uaNGFe4+sPpFqg4w98P4b+wjNu/OlYXzwerN5eD6T8maTZx5Ww7V/Hp5 uP0GLXO+/78oD3cfjA9zP4wP8x9MP8z/MPNh4QOzHxZ+MPfBwhc9/AFZSbHT "], CompressedData[" 1:eJxTTMoPSmViYGCQB2IQLeF07vf/KwoOe35VvNh9m88Bxg+bItQUGsrtcErW bOLMbHEMPky9Qcuc7/8vSjp80F0j/f4cP5xvEy11afdrATjfN0f78Zk/gnC+ thfnwVVSwnC+lOWP9TMtReD8Z6xHa9LMROH8SRvy1QUFxdD4EnA+p8bzeR0a knD+ooMNFkpCUnB+XK3Nl7tnpVDt65RGlfeVQXOfLIQvKe7wQ+xab3k5gn/0 8aIolz9yDinbz2sZ35VzWG8n9+vdKQWIfKK8Qw3362O7pyP4EP3ScD6Kf4B8 FP8C+Q3z48QYLETgfLD7RIXhfHD4fhaE88HueSIA58PiAz1+AUR/638= "]}]}, FaceForm[ RGBColor[0.999985, 0.999985, 0.999985, 1.]], StripOnInput -> False]}, ImageSize -> {14., 14.}, PlotRange -> {{0., 14.}, {0., 14.}}, AspectRatio -> Automatic]}, Dynamic[ CurrentValue["MouseOver"]], ImageSize -> Automatic, FrameMargins -> 0]& )}], Cell[ StyleData["MoreInfoOpenerButtonTemplate"], TemplateBoxOptions -> {DisplayFunction -> (AdjustmentBox[ ButtonBox[ TagBox[ TooltipBox[ TemplateBox[{}, "MoreInfoOpenerIconTemplate"], "\"More info\"", LabelStyle -> "TextStyling"], Annotation[#, "More info", "Tooltip"]& ], ButtonFunction :> (If[ MatchQ[ CurrentValue[ ButtonNotebook[], {TaggingRules, "AttachedCells", #}], Blank[CellObject]], NotebookDelete[ CurrentValue[ ButtonNotebook[], {TaggingRules, "AttachedCells", #}]]; CurrentValue[ ButtonNotebook[], {TaggingRules, "AttachedCells", #}] = Inherited, CurrentValue[ ButtonNotebook[], {TaggingRules, "AttachedCells", #}] = MathLink`CallFrontEnd[ FrontEnd`AttachCell[ ParentCell[ EvaluationCell[]], #2, "Inline", "ClosingActions" -> {"ParentChanged", "EvaluatorQuit"}]]; Null]; Null), Appearance -> None, Evaluator -> Automatic, Method -> "Preemptive"], BoxBaselineShift -> -0.5, BoxMargins -> 0.2]& )}], Cell[ StyleData["UsageInputs", StyleDefinitions -> StyleData["Input"]], CellMargins -> {{66, 10}, {0, 8}}, StyleKeyMapping -> {"Tab" -> "UsageDescription"}, CellEventActions -> { "ReturnKeyDown" :> With[{FunctionResourceTools`BuildDefinitionNotebook`Private`nb = Notebooks[ EvaluationCell[]]}, SelectionMove[ EvaluationCell[], After, Cell]; NotebookWrite[ FunctionResourceTools`BuildDefinitionNotebook`Private`nb, Cell["", "UsageDescription"], All]; SelectionMove[ FunctionResourceTools`BuildDefinitionNotebook`Private`nb, Before, CellContents]; Null], {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]]}, ContextMenu -> { MenuItem["Cu&t", "Cut"], MenuItem["&Copy", "Copy"], MenuItem["&Paste", FrontEnd`Paste[After]], Menu["Cop&y As", { MenuItem["Plain &Text", FrontEnd`CopySpecial["PlainText"]], MenuItem["&Input Text", FrontEnd`CopySpecial["InputText"]], MenuItem["&LaTeX", KernelExecute[ ToExpression["FrontEnd`CopyAsTeX[]"]], MenuEvaluator -> Automatic], MenuItem["M&athML", KernelExecute[ ToExpression["FrontEnd`CopyAsMathML[]"]], MenuEvaluator -> Automatic], Delimiter, MenuItem["Cell &Object", FrontEnd`CopySpecial["CellObject"]], MenuItem["&Cell Expression", FrontEnd`CopySpecial["CellExpression"]], MenuItem["&Notebook Expression", FrontEnd`CopySpecial["NotebookExpression"]]}], Delimiter, MenuItem["Format as Template Input", KernelExecute[ ToExpression[ "System`ResourceFunction; \ FunctionTemplateToggle`DT`FunctionTemplateToggle[EvaluationNotebook[]]"]], MenuEvaluator -> Automatic], MenuItem["Format as Code", KernelExecute[ ToExpression[ "System`ResourceFunction; \ FunctionTemplateToggle`DT`FunctionTemplateLiteralInput[EvaluationNotebook[]]"]\ ], MenuEvaluator -> Automatic]}, ShowAutoStyles -> False, ShowCodeAssist -> False, CodeAssistOptions -> {"DynamicHighlighting" -> False}, LineSpacing -> {1, 3}, TabSpacings -> {2.5}, CounterIncrements -> "Text", FontFamily -> "Source Sans Pro", FontSize -> 15, FontWeight -> "Plain"], Cell[ StyleData["UsageDescription", StyleDefinitions -> StyleData["Text"]], CellMargins -> {{86, 10}, {7, 0}}, StyleKeyMapping -> {"Backspace" -> "UsageInputs"}, CellGroupingRules -> "OutputGrouping", CellEventActions -> { "ReturnKeyDown" :> With[{FunctionResourceTools`BuildDefinitionNotebook`Private`nb = Notebooks[ EvaluationCell[]]}, SelectionMove[ EvaluationCell[], After, Cell]; NotebookWrite[ FunctionResourceTools`BuildDefinitionNotebook`Private`nb, Cell[ BoxData[""], "UsageInputs"], All]; SelectionMove[ FunctionResourceTools`BuildDefinitionNotebook`Private`nb, Before, CellContents]; Null], {"KeyDown", "\t"} :> Replace[SelectionMove[ SelectedNotebook[], After, Cell]; NotebookFind[ SelectedNotebook[], "TabNext", Next, CellTags, AutoScroll -> True, WrapAround -> True], Blank[NotebookSelection] :> SelectionMove[ SelectedNotebook[], All, CellContents, AutoScroll -> True]]}, ContextMenu -> { MenuItem["Cu&t", "Cut"], MenuItem["&Copy", "Copy"], MenuItem["&Paste", FrontEnd`Paste[After]], Menu["Cop&y As", { MenuItem["Plain &Text", FrontEnd`CopySpecial["PlainText"]], MenuItem["&Input Text", FrontEnd`CopySpecial["InputText"]], MenuItem["&LaTeX", KernelExecute[ ToExpression["FrontEnd`CopyAsTeX[]"]], MenuEvaluator -> Automatic], MenuItem["M&athML", KernelExecute[ ToExpression["FrontEnd`CopyAsMathML[]"]], MenuEvaluator -> Automatic], Delimiter, MenuItem["Cell &Object", FrontEnd`CopySpecial["CellObject"]], MenuItem["&Cell Expression", FrontEnd`CopySpecial["CellExpression"]], MenuItem["&Notebook Expression", FrontEnd`CopySpecial["NotebookExpression"]]}], Delimiter, MenuItem["Format as Template Input", KernelExecute[ ToExpression[ "System`ResourceFunction; \ FunctionTemplateToggle`DT`FunctionTemplateToggle[EvaluationNotebook[]]"]], MenuEvaluator -> Automatic], MenuItem["Format as Code", KernelExecute[ ToExpression[ "System`ResourceFunction; \ FunctionTemplateToggle`DT`FunctionTemplateLiteralInput[EvaluationNotebook[]]"]\ ], MenuEvaluator -> Automatic], Delimiter, MenuItem["Make &Hyperlink...", "CreateHyperlinkDialog"], MenuItem["Insert Table/&Matrix...", "CreateGridBoxDialog"], MenuItem["Chec&k Spelling...", "FindNextMisspelling"], Menu["Citatio&n", { MenuItem[ "Insert Bibliographical &Reference...", "InsertBibReference"], MenuItem["Insert Bibliographical &Note...", "InsertBibNote"], Delimiter, MenuItem["Set / Change Citation &Style...", "SetCitationStyle"], MenuItem["&Insert Bibliography and Notes", "InsertBibAndNotes"], MenuItem["&Delete Bibliography and Notes", "DeleteBibAndNotes"], MenuItem["Re&build Bibliography and Notes", "RebuildBibAndNotes"]}], Delimiter, Menu["Sty&le", { MenuItem[ "Start Cell Style Names", "MenuListStyles", $CellContext`MenuAnchor -> True], Delimiter, MenuItem["&Other...", "StyleOther"]}], Delimiter, MenuItem["Create Inline Cell", "CreateInlineCell"], MenuItem["Di&vide Cell", "CellSplit"], MenuItem["Evaluate &in Place", All], Delimiter, MenuItem["Toggle &Full Screen", FrontEndExecute[ FrontEnd`Value[ FEPrivate`NotebookToggleFullScreen[]]]]}, ShowAutoSpellCheck -> False], Cell[ StyleData["Notes", StyleDefinitions -> StyleData["Item"]], StyleKeyMapping -> {}, ContextMenu -> { MenuItem["Cu&t", "Cut"], MenuItem["&Copy", "Copy"], MenuItem["&Paste", FrontEnd`Paste[After]], Menu["Cop&y As", { MenuItem["Plain &Text", FrontEnd`CopySpecial["PlainText"]], MenuItem["&Input Text", FrontEnd`CopySpecial["InputText"]], MenuItem["&LaTeX", KernelExecute[ ToExpression["FrontEnd`CopyAsTeX[]"]], MenuEvaluator -> Automatic], MenuItem["M&athML", KernelExecute[ ToExpression["FrontEnd`CopyAsMathML[]"]], MenuEvaluator -> Automatic], Delimiter, MenuItem["Cell &Object", FrontEnd`CopySpecial["CellObject"]], MenuItem["&Cell Expression", FrontEnd`CopySpecial["CellExpression"]], MenuItem["&Notebook Expression", FrontEnd`CopySpecial["NotebookExpression"]]}], Delimiter, MenuItem["Format as Template Input", KernelExecute[ ToExpression[ "System`ResourceFunction; \ FunctionTemplateToggle`DT`FunctionTemplateToggle[EvaluationNotebook[]]"]], MenuEvaluator -> Automatic], MenuItem["Format as Code", KernelExecute[ ToExpression[ "System`ResourceFunction; \ FunctionTemplateToggle`DT`FunctionTemplateLiteralInput[EvaluationNotebook[]]"]\ ], MenuEvaluator -> Automatic], Delimiter, MenuItem["Make &Hyperlink...", "CreateHyperlinkDialog"], MenuItem["Insert Table/&Matrix...", "CreateGridBoxDialog"], MenuItem["Chec&k Spelling...", "FindNextMisspelling"], Menu["Citatio&n", { MenuItem[ "Insert Bibliographical &Reference...", "InsertBibReference"], MenuItem["Insert Bibliographical &Note...", "InsertBibNote"], Delimiter, MenuItem["Set / Change Citation &Style...", "SetCitationStyle"], MenuItem["&Insert Bibliography and Notes", "InsertBibAndNotes"], MenuItem["&Delete Bibliography and Notes", "DeleteBibAndNotes"], MenuItem["Re&build Bibliography and Notes", "RebuildBibAndNotes"]}], Delimiter, Menu["Sty&le", { MenuItem[ "Start Cell Style Names", "MenuListStyles", $CellContext`MenuAnchor -> True], Delimiter, MenuItem["&Other...", "StyleOther"]}], Delimiter, MenuItem["Create Inline Cell", "CreateInlineCell"], MenuItem["Di&vide Cell", "CellSplit"], MenuItem["Evaluate &in Place", All], Delimiter, MenuItem["Toggle &Full Screen", FrontEndExecute[ FrontEnd`Value[ FEPrivate`NotebookToggleFullScreen[]]]]}, ShowAutoSpellCheck -> False, GridBoxOptions -> {BaseStyle -> "TableNotes"}], Cell[ StyleData["Text"], ContextMenu -> { MenuItem["Cu&t", "Cut"], MenuItem["&Copy", "Copy"], MenuItem["&Paste", FrontEnd`Paste[After]], Menu["Cop&y As", { MenuItem["Plain &Text", FrontEnd`CopySpecial["PlainText"]], MenuItem["&Input Text", FrontEnd`CopySpecial["InputText"]], MenuItem["&LaTeX", KernelExecute[ ToExpression["FrontEnd`CopyAsTeX[]"]], MenuEvaluator -> Automatic], MenuItem["M&athML", KernelExecute[ ToExpression["FrontEnd`CopyAsMathML[]"]], MenuEvaluator -> Automatic], Delimiter, MenuItem["Cell &Object", FrontEnd`CopySpecial["CellObject"]], MenuItem["&Cell Expression", FrontEnd`CopySpecial["CellExpression"]], MenuItem["&Notebook Expression", FrontEnd`CopySpecial["NotebookExpression"]]}], Delimiter, MenuItem["Format as Template Input", KernelExecute[ ToExpression[ "System`ResourceFunction; \ FunctionTemplateToggle`DT`FunctionTemplateToggle[EvaluationNotebook[]]"]], MenuEvaluator -> Automatic], MenuItem["Format as Code", KernelExecute[ ToExpression[ "System`ResourceFunction; \ FunctionTemplateToggle`DT`FunctionTemplateLiteralInput[EvaluationNotebook[]]"]\ ], MenuEvaluator -> Automatic], Delimiter, MenuItem["Make &Hyperlink...", "CreateHyperlinkDialog"], MenuItem["Insert Table/&Matrix...", "CreateGridBoxDialog"], MenuItem["Chec&k Spelling...", "FindNextMisspelling"], Menu["Citatio&n", { MenuItem[ "Insert Bibliographical &Reference...", "InsertBibReference"], MenuItem["Insert Bibliographical &Note...", "InsertBibNote"], Delimiter, MenuItem["Set / Change Citation &Style...", "SetCitationStyle"], MenuItem["&Insert Bibliography and Notes", "InsertBibAndNotes"], MenuItem["&Delete Bibliography and Notes", "DeleteBibAndNotes"], MenuItem["Re&build Bibliography and Notes", "RebuildBibAndNotes"]}], Delimiter, Menu["Sty&le", { MenuItem[ "Start Cell Style Names", "MenuListStyles", $CellContext`MenuAnchor -> True], Delimiter, MenuItem["&Other...", "StyleOther"]}], Delimiter, MenuItem["Create Inline Cell", "CreateInlineCell"], MenuItem["Di&vide Cell", "CellSplit"], MenuItem["Evaluate &in Place", All], Delimiter, MenuItem["Toggle &Full Screen", FrontEndExecute[ FrontEnd`Value[ FEPrivate`NotebookToggleFullScreen[]]]]}], Cell[ StyleData["TableNotes", StyleDefinitions -> StyleData["Notes"]], CellDingbat -> None, CellFrameColor -> RGBColor[0.749, 0.694, 0.553], StyleMenuListing -> None, ButtonBoxOptions -> {Appearance -> {Automatic, None}}, GridBoxOptions -> { FrameStyle -> GrayLevel[0.906], GridBoxAlignment -> { "Columns" -> {{Left}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, "RowsIndexed" -> {}}, GridBoxDividers -> {"Columns" -> {{None}}, "Rows" -> {{True}}}, GridDefaultElement -> Cell["\[Placeholder]", "TableText"]}], Cell[ StyleData["TableText"], DefaultInlineFormatType -> "DefaultInputInlineFormatType", AutoQuoteCharacters -> {}, StyleMenuListing -> None]}, Visible -> False, FrontEndVersion -> "11.3 for Linux x86 (64-bit) (March 6, 2018)", StyleDefinitions -> "Default.nb"] ] (* End of Notebook Content *) (* Internal cache information *) (*CellTagsOutline CellTagsIndex->{ "Title"->{ Cell[580, 22, 544, 9, 70, "Title",ExpressionUUID->"f0b5cf7a-d8f8-4b77-adf6-debef2ba4ce3", CellTags->{"Title", "TabNext"}, CellID->362346026]}, "TabNext"->{ Cell[580, 22, 544, 9, 70, "Title",ExpressionUUID->"f0b5cf7a-d8f8-4b77-adf6-debef2ba4ce3", CellTags->{"Title", "TabNext"}, CellID->362346026], Cell[1127, 33, 568, 9, 70, "Text",ExpressionUUID->"4c6ba972-e82c-4484-ad35-095fa48fa93a", CellTags->{"Description", "TabNext"}, CellID->450900334], Cell[2600, 69, 17549, 287, 70, "Input",ExpressionUUID->"1a19da9d-ab4c-4859-b577-ded6dd3adcf7", CellTags->"TabNext", CellID->778396829], Cell[21118, 392, 201, 5, 70, "UsageInputs",ExpressionUUID->"c9227ae9-7d85-428a-8d3c-5e273a05c8d4", CellTags->"TabNext", CellID->157543866], Cell[21322, 399, 305, 10, 70, "UsageDescription",ExpressionUUID->"783876ac-8298-479b-9c34-cbe1eb07cd8c", CellTags->"TabNext", CellID->231889230], Cell[1209567, 22582, 562, 10, 70, "Text",ExpressionUUID->"0376990c-3f5a-48bf-8b98-f976cb017394", CellTags->"TabNext", CellID->832483124], Cell[1210816, 22619, 529, 9, 70, "Item",ExpressionUUID->"e641d9f2-e9bd-4728-9569-a50f3775591e", CellTags->"TabNext", CellID->123227828], Cell[1214153, 22696, 528, 9, 70, "Item",ExpressionUUID->"c56fcbcf-9472-4956-aa2c-e1f0914e609f", CellTags->"TabNext", CellID->79477165], Cell[1217490, 22773, 528, 9, 70, "Item",ExpressionUUID->"15550528-4c9b-40d1-8f67-efaf1df7aa65", CellTags->"TabNext", CellID->960273585], Cell[1219391, 22820, 496, 8, 70, "Text",ExpressionUUID->"7d3d1ae7-315b-408a-a141-fe6327c7e10e", CellTags->"TabNext", CellID->343081869], Cell[1220546, 22854, 726, 13, 70, "Item",ExpressionUUID->"481f5d26-f68d-4a12-8fef-44b7a5d216ec", CellTags->"TabNext", CellID->485448166], Cell[1223567, 22949, 495, 8, 70, "Text",ExpressionUUID->"4e671e52-d349-4002-99b2-8c7225ca1a40", CellTags->"TabNext", CellID->920818074]}, "Description"->{ Cell[1127, 33, 568, 9, 70, "Text",ExpressionUUID->"4c6ba972-e82c-4484-ad35-095fa48fa93a", CellTags->{"Description", "TabNext"}, CellID->450900334]}, "Definition"->{ Cell[1720, 46, 877, 21, 70, "Section",ExpressionUUID->"2bb1cd95-1598-4d59-bfdf-7d952a7c1316", CellTags->"Definition", CellID->608264297]}, "Documentation"->{ Cell[20186, 361, 99, 3, 70, "Section",ExpressionUUID->"e4406fce-bb0a-4e4f-a70e-a8ee1abe6ee1", CellTags->"Documentation", CellID->855965831]}, "Usage"->{ Cell[20310, 368, 783, 20, 70, "Subsection",ExpressionUUID->"1cd872fc-a385-4117-8a1b-fddcc67a69c0", CellTags->"Usage", CellID->694807545]}, "Details & Options"->{ Cell[21676, 415, 814, 20, 70, "Subsection",ExpressionUUID->"a4e19097-325e-40ab-ad05-d523835d68bc", CellTags->"Details & Options", CellID->29639701]}, "Examples"->{ Cell[25066, 522, 913, 21, 70, "Section",ExpressionUUID->"f05ca0c7-8412-4306-9faf-8f4d97010576", CellTags->"Examples", CellID->847663398]}, "Source & Additional Information"->{ Cell[1208732, 22555, 135, 3, 70, "Section",ExpressionUUID->"db56e403-53fd-433e-8a67-ea5215dc527d", CellTags->"Source & Additional Information", CellID->318391102]}, "Contributed By"->{ Cell[1208892, 22562, 672, 18, 70, "Subsection",ExpressionUUID->"1c3c4ec2-0ddb-4426-a268-956481ca2066", CellTags->"Contributed By", CellID->757508554]}, "Keywords"->{ Cell[1210166, 22597, 625, 18, 70, "Subsection",ExpressionUUID->"beb4a593-2cb0-4437-80e2-1f4ed299617c", CellTags->"Keywords", CellID->246422893]}, "Related Symbols"->{ Cell[1213466, 22674, 662, 18, 70, "Subsection",ExpressionUUID->"a6b680e0-fa39-4296-a97f-17811b21cb7b", CellTags->"Related Symbols", CellID->911170439]}, "Related Resource Objects"->{ Cell[1216763, 22751, 702, 18, 70, "Subsection",ExpressionUUID->"2d64b14d-fdef-4f0e-9955-2e5b795c9af6", CellTags->"Related Resource Objects", CellID->217060377]}, "Source/Reference Citation"->{ Cell[1218633, 22799, 755, 19, 70, "Subsection",ExpressionUUID->"99c3c727-8178-477b-b7b3-45c2434b64e0", CellTags->"Source/Reference Citation", CellID->967310595]}, "Links"->{ Cell[1219924, 22833, 597, 17, 70, "Subsection",ExpressionUUID->"acf1f5e6-d5d6-41f2-b521-c96346d8e587", CellTags->"Links", CellID->593846556]}, "Tests"->{ Cell[1221636, 22882, 767, 20, 70, "Subsection",ExpressionUUID->"957b6949-17f9-4035-af13-6d8c5831c62f", CellTags->"Tests", CellID->16051757]}, "Author Notes"->{ Cell[1222692, 22920, 127, 4, 70, "Section",ExpressionUUID->"f8e3e233-41fd-4603-ad34-c666b16b6cca", CellTags->"Author Notes", CellID->795110225]}, "Submission Notes"->{ Cell[1222844, 22928, 720, 19, 70, "Section",ExpressionUUID->"27137d9f-30ae-40d7-bc11-2c6dd7abf74a", CellTags->"Submission Notes", CellID->843283583]} } *) (*CellTagsIndex CellTagsIndex->{ {"Title", 1269659, 23895}, {"TabNext", 1269824, 23899}, {"Description", 1271611, 23936}, {"Definition", 1271785, 23940}, {"Documentation", 1271952, 23944}, {"Usage", 1272114, 23948}, {"Details & Options", 1272285, 23952}, {"Examples", 1272458, 23956}, {"Source & Additional Information", 1272643, 23960}, {"Contributed By", 1272837, 23964}, {"Keywords", 1273012, 23968}, {"Related Symbols", 1273188, 23972}, {"Related Resource Objects", 1273380, 23976}, {"Source/Reference Citation", 1273582, 23980}, {"Links", 1273765, 23984}, {"Tests", 1273928, 23988}, {"Author Notes", 1274097, 23992}, {"Submission Notes", 1274274, 23996} } *) (*NotebookFileOutline Notebook[{ Cell[CellGroupData[{ Cell[580, 22, 544, 9, 70, "Title",ExpressionUUID->"f0b5cf7a-d8f8-4b77-adf6-debef2ba4ce3", CellTags->{"Title", "TabNext"}, CellID->362346026], Cell[1127, 33, 568, 9, 70, "Text",ExpressionUUID->"4c6ba972-e82c-4484-ad35-095fa48fa93a", CellTags->{"Description", "TabNext"}, CellID->450900334], Cell[CellGroupData[{ Cell[1720, 46, 877, 21, 70, "Section",ExpressionUUID->"2bb1cd95-1598-4d59-bfdf-7d952a7c1316", CellTags->"Definition", CellID->608264297], Cell[2600, 69, 17549, 287, 70, "Input",ExpressionUUID->"1a19da9d-ab4c-4859-b577-ded6dd3adcf7", CellTags->"TabNext", CellID->778396829] }, Open ]], Cell[CellGroupData[{ Cell[20186, 361, 99, 3, 70, "Section",ExpressionUUID->"e4406fce-bb0a-4e4f-a70e-a8ee1abe6ee1", CellTags->"Documentation", CellID->855965831], Cell[CellGroupData[{ Cell[20310, 368, 783, 20, 70, "Subsection",ExpressionUUID->"1cd872fc-a385-4117-8a1b-fddcc67a69c0", CellTags->"Usage", CellID->694807545], Cell[CellGroupData[{ Cell[21118, 392, 201, 5, 70, "UsageInputs",ExpressionUUID->"c9227ae9-7d85-428a-8d3c-5e273a05c8d4", CellTags->"TabNext", CellID->157543866], Cell[21322, 399, 305, 10, 70, "UsageDescription",ExpressionUUID->"783876ac-8298-479b-9c34-cbe1eb07cd8c", CellTags->"TabNext", CellID->231889230] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[21676, 415, 814, 20, 70, "Subsection",ExpressionUUID->"a4e19097-325e-40ab-ad05-d523835d68bc", CellTags->"Details & Options", CellID->29639701], Cell[22493, 437, 2524, 79, 70, "Notes",ExpressionUUID->"afe39bb9-bd0c-4ac5-8964-a0d6e473ee54", CellID->14293932] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[25066, 522, 913, 21, 70, "Section",ExpressionUUID->"f05ca0c7-8412-4306-9faf-8f4d97010576", CellTags->"Examples", CellID->847663398], Cell[CellGroupData[{ Cell[26004, 547, 56, 1, 70, "Subsection",ExpressionUUID->"f54b5277-221b-4ab1-8db3-ea009ea37d06", CellID->462042388], Cell[26063, 550, 105, 2, 70, "Text",ExpressionUUID->"3c1af23a-4cde-48c8-98dd-e99e09027488", CellID->13078159], Cell[CellGroupData[{ Cell[26193, 556, 316, 10, 70, "Input",ExpressionUUID->"679e32a4-5f68-4ff1-92a7-c7eb5637c8f1", CellID->443871870], Cell[26512, 568, 46905, 809, 70, "Output",ExpressionUUID->"82947af4-87f4-4e72-953a-43abebcb619a", CellID->8129617] }, Open ]], Cell[CellGroupData[{ Cell[73454, 1382, 64, 2, 70, "PageBreak",ExpressionUUID->"532301e0-da0b-4b22-a839-3a0d340d1a3b", PageBreakBelow->True, CellID->119259169], Cell[73521, 1386, 98, 2, 70, "Text",ExpressionUUID->"c3276b68-d74c-4b9b-be7c-4b86900a1094", CellID->113439233], Cell[CellGroupData[{ Cell[73644, 1392, 236, 7, 70, "Input",ExpressionUUID->"fab5bd14-fbc3-433e-a82b-c448c2f0c4ba", CellID->120533573], Cell[73883, 1401, 63404, 1408, 70, "Output",ExpressionUUID->"a4ef1d7d-7fb9-48f5-9dd2-e9c84fdddda0", CellID->619393685] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[137336, 2815, 64, 2, 70, "PageBreak",ExpressionUUID->"a34c395b-37fe-4e43-b34b-ab5ba8561f56", PageBreakBelow->True, CellID->199224021], Cell[137403, 2819, 97, 2, 70, "Text",ExpressionUUID->"5e7eaa5d-4f09-4958-bb68-47a88b5bc7bd", CellID->225856413], Cell[CellGroupData[{ Cell[137525, 2825, 172, 4, 70, "Input",ExpressionUUID->"81980cf9-4941-46b2-8adc-e134a37c0476", CellID->19164468], Cell[137700, 2831, 15768, 265, 70, "Output",ExpressionUUID->"06504299-dc17-4840-9ff7-1694d204a438", CellID->823842285] }, Open ]] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[153529, 3103, 47, 1, 70, "Subsection",ExpressionUUID->"03818228-3725-415d-95e1-2cea2a091f1d", CellID->964056545], Cell[153579, 3106, 98, 2, 70, "Text",ExpressionUUID->"adfdd2d2-43e5-4864-b1f2-56d97111e1e4", CellID->649685796], Cell[CellGroupData[{ Cell[153702, 3112, 255, 8, 70, "Input",ExpressionUUID->"33b4eb19-6351-4a3f-9109-c47944d441dd", CellID->836153427], Cell[153960, 3122, 40705, 773, 70, "Output",ExpressionUUID->"180f017f-03a0-4a5a-bb8f-21708f62cfd4", CellID->521518740] }, Open ]], Cell[CellGroupData[{ Cell[194702, 3900, 64, 2, 70, "PageBreak",ExpressionUUID->"7e3f3c61-e689-4536-8e76-91023bad11ed", PageBreakBelow->True, CellID->244582541], Cell[194769, 3904, 119, 2, 70, "Text",ExpressionUUID->"fd6ed50d-5cc1-4ac0-991a-9d238045d039", CellID->169564055], Cell[CellGroupData[{ Cell[194913, 3910, 3286, 96, 70, "Input",ExpressionUUID->"8496cb24-e87c-4bcc-9a6b-004c4b60eeba", CellID->65455867], Cell[198202, 4008, 347768, 7424, 70, "Output",ExpressionUUID->"3476f518-8ea3-49d3-831c-f4a7a1284498", CellID->105418764] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[546019, 11438, 63, 2, 70, "PageBreak",ExpressionUUID->"172d549e-cf93-48fa-ba3c-323ef633c524", PageBreakBelow->True, CellID->47835890], Cell[546085, 11442, 93, 2, 70, "Text",ExpressionUUID->"2fa96919-ea72-48da-967c-86330da2038b", CellID->201931260], Cell[CellGroupData[{ Cell[546203, 11448, 240, 7, 70, "Input",ExpressionUUID->"22b45fb7-c924-4554-b0d4-99aca7168918", CellID->579512304], Cell[546446, 11457, 78327, 1299, 70, "Output",ExpressionUUID->"efe8d271-19f3-438c-94af-c5c3e7aa7b11", CellID->326631600] }, Open ]] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[624834, 12763, 77, 2, 70, "Subsection",ExpressionUUID->"48416b85-3205-4ab6-b842-9e90388e8a57", CellID->568056528], Cell[624914, 12767, 163, 2, 70, "Text",ExpressionUUID->"614b9369-68c9-4b43-bac8-ff5bea933efc", CellID->79484806], Cell[CellGroupData[{ Cell[625102, 12773, 2682, 68, 70, "Input",ExpressionUUID->"6747998d-4e34-4ea7-a527-fd0e7c30ebca", CellID->14441392], Cell[627787, 12843, 15762, 265, 70, "Output",ExpressionUUID->"a04d26b5-b5f2-4c7b-92a7-3416ad474076", CellID->726535153], Cell[643552, 13110, 85309, 1403, 70, "Print",ExpressionUUID->"69442a45-824e-4757-aa2f-48b35e974387", CellID->853689942] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[728910, 14519, 89, 2, 70, "Subsection",ExpressionUUID->"f5be1f46-a412-4b4b-a5d9-a6513c9ea663", CellID->754506620], Cell[729002, 14523, 720, 22, 70, "Text",ExpressionUUID->"45b00b0c-4ab9-4b4b-a157-b4c6f3e0f974", CellID->498896398], Cell[CellGroupData[{ Cell[729747, 14549, 193, 5, 70, "Input",ExpressionUUID->"210ba1bb-d59e-4c7b-8159-5d4f2dcd5a46", CellID->40134163], Cell[729943, 14556, 15797, 266, 70, "Output",ExpressionUUID->"9ded54ca-149c-45bb-aa3d-5ba6bd2347f0", CellID->88360206] }, Open ]], Cell[745755, 14825, 226, 5, 70, "Text",ExpressionUUID->"991071e8-d3de-4dff-90d8-4aef095063ff", CellID->700044620], Cell[CellGroupData[{ Cell[746006, 14834, 15842, 267, 70, "Input",ExpressionUUID->"3b61d169-9f4e-4e5d-958a-33cdb2070982", CellID->33037086], Cell[761851, 15103, 173, 5, 70, "Output",ExpressionUUID->"6ff874e7-87ac-4761-92ca-8d35121d3d08", CellID->420312669] }, Open ]], Cell[CellGroupData[{ Cell[762061, 15113, 173, 4, 70, "Input",ExpressionUUID->"bddb7222-27a4-4bf0-9286-963ea2c6415a", CellID->465151328], Cell[762237, 15119, 15807, 267, 70, "Output",ExpressionUUID->"e0ab9cdd-ac71-4d47-8635-7c7449b5d82e", CellID->638814548] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[778093, 15392, 79, 2, 70, "Subsection",ExpressionUUID->"3383a350-7cd3-47a1-8d3d-437d66a3f6fe", CellID->92483860], Cell[778175, 15396, 281, 8, 70, "Text",ExpressionUUID->"c63bf7fd-5803-4977-81a7-559a8d8db52f", CellID->47491018], Cell[CellGroupData[{ Cell[778481, 15408, 170, 4, 70, "Input",ExpressionUUID->"006fdcf0-977a-4b7d-9f20-018670d077b7", CellID->238955758], Cell[778654, 15414, 15759, 265, 70, "Output",ExpressionUUID->"b7f47032-0648-4c67-a468-d0b04c45fd51", CellID->141061132] }, Open ]], Cell[CellGroupData[{ Cell[794450, 15684, 162, 4, 70, "Input",ExpressionUUID->"b3c0ad95-0efd-4d21-b509-21ede1f81993", CellID->508643742], Cell[794615, 15690, 15747, 265, 70, "Output",ExpressionUUID->"61c8482d-a103-4c6d-9eeb-2b5efaca8dca", CellID->52298612] }, Open ]], Cell[810377, 15958, 162, 4, 70, "Input",ExpressionUUID->"2fa1f4c6-e006-42c2-90ca-cc21840a75d9", CellID->473599708] }, Open ]], Cell[CellGroupData[{ Cell[810576, 15967, 79, 2, 70, "Subsection",ExpressionUUID->"9673a8aa-789d-4f79-9e40-2e4863aa85b7", CellID->540091361], Cell[810658, 15971, 125, 2, 70, "Text",ExpressionUUID->"6f64cb1b-bfb8-44e8-848d-ed8c3bc5d191", CellID->591190485], Cell[CellGroupData[{ Cell[810808, 15977, 51259, 846, 70, "Input",ExpressionUUID->"21fbcf51-e76d-4a7f-9e48-47cb48026ba8", CellID->43203752], Cell[862070, 16825, 117699, 1942, 70, "Output",ExpressionUUID->"35b99132-f476-4b76-b03f-f79e801171ab", CellID->147191055] }, Open ]], Cell[CellGroupData[{ Cell[979806, 18772, 63, 2, 70, "PageBreak",ExpressionUUID->"86875f46-c052-40c0-85c5-d0631612b8ad", PageBreakBelow->True, CellID->85785237], Cell[979872, 18776, 132, 2, 70, "Text",ExpressionUUID->"68570881-c1af-49a9-81ea-e7e51f741652", CellID->521933704], Cell[CellGroupData[{ Cell[980029, 18782, 306, 8, 70, "Input",ExpressionUUID->"f3d4524c-4b1d-49f0-8931-d852912a74fd", CellID->3495078], Cell[980338, 18792, 228321, 3755, 70, "Output",ExpressionUUID->"e3cc8b24-68a5-4fc8-942f-77204002755e", CellID->428876372] }, Open ]] }, Open ]] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[1208732, 22555, 135, 3, 70, "Section",ExpressionUUID->"db56e403-53fd-433e-8a67-ea5215dc527d", CellTags->"Source & Additional Information", CellID->318391102], Cell[CellGroupData[{ Cell[1208892, 22562, 672, 18, 70, "Subsection",ExpressionUUID->"1c3c4ec2-0ddb-4426-a268-956481ca2066", CellTags->"Contributed By", CellID->757508554], Cell[1209567, 22582, 562, 10, 70, "Text",ExpressionUUID->"0376990c-3f5a-48bf-8b98-f976cb017394", CellTags->"TabNext", CellID->832483124] }, Open ]], Cell[CellGroupData[{ Cell[1210166, 22597, 625, 18, 70, "Subsection",ExpressionUUID->"beb4a593-2cb0-4437-80e2-1f4ed299617c", CellTags->"Keywords", CellID->246422893], Cell[CellGroupData[{ Cell[1210816, 22619, 529, 9, 70, "Item",ExpressionUUID->"e641d9f2-e9bd-4728-9569-a50f3775591e", CellTags->"TabNext", CellID->123227828], Cell[1211348, 22630, 511, 8, 70, "Item",ExpressionUUID->"8b242e14-4a59-456d-ba6a-ad0ad9e5fd3f", CellID->737928356], Cell[1211862, 22640, 517, 8, 70, "Item",ExpressionUUID->"3d729355-eea1-4a18-9dd0-32ed3ccd7ea2", CellID->453776788], Cell[1212382, 22650, 513, 8, 70, "Item",ExpressionUUID->"ab701e38-95b1-4338-af86-6cefe0d31906", CellID->23822048], Cell[1212898, 22660, 519, 8, 70, "Item",ExpressionUUID->"07368303-6bea-48c5-8e19-b8444571b25b", CellID->580037425] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[1213466, 22674, 662, 18, 70, "Subsection",ExpressionUUID->"a6b680e0-fa39-4296-a97f-17811b21cb7b", CellTags->"Related Symbols", CellID->911170439], Cell[CellGroupData[{ Cell[1214153, 22696, 528, 9, 70, "Item",ExpressionUUID->"c56fcbcf-9472-4956-aa2c-e1f0914e609f", CellTags->"TabNext", CellID->79477165], Cell[1214684, 22707, 504, 8, 70, "Item",ExpressionUUID->"e358a645-38f5-4588-9172-1464956bbdd7", CellID->1786201], Cell[1215191, 22717, 508, 8, 70, "Item",ExpressionUUID->"f535f1ef-5868-40f6-95eb-15ea2efa0033", CellID->143754847], Cell[1215702, 22727, 505, 8, 70, "Item",ExpressionUUID->"96864973-fa0d-4fef-bbfa-32f35e721b86", CellID->934352842], Cell[1216210, 22737, 504, 8, 70, "Item",ExpressionUUID->"5fc9eb99-7992-4c28-a240-a952a695a1e2", CellID->589392240] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[1216763, 22751, 702, 18, 70, "Subsection",ExpressionUUID->"2d64b14d-fdef-4f0e-9955-2e5b795c9af6", CellTags->"Related Resource Objects", CellID->217060377], Cell[CellGroupData[{ Cell[1217490, 22773, 528, 9, 70, "Item",ExpressionUUID->"15550528-4c9b-40d1-8f67-efaf1df7aa65", CellTags->"TabNext", CellID->960273585], Cell[1218021, 22784, 563, 9, 70, "Item",ExpressionUUID->"cc6650ca-1e43-49e6-bdc6-4d6bdfa97f31", CellID->377337373] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[1218633, 22799, 755, 19, 70, "Subsection",ExpressionUUID->"99c3c727-8178-477b-b7b3-45c2434b64e0", CellTags->"Source/Reference Citation", CellID->967310595], Cell[1219391, 22820, 496, 8, 70, "Text",ExpressionUUID->"7d3d1ae7-315b-408a-a141-fe6327c7e10e", CellTags->"TabNext", CellID->343081869] }, Open ]], Cell[CellGroupData[{ Cell[1219924, 22833, 597, 17, 70, "Subsection",ExpressionUUID->"acf1f5e6-d5d6-41f2-b521-c96346d8e587", CellTags->"Links", CellID->593846556], Cell[CellGroupData[{ Cell[1220546, 22854, 726, 13, 70, "Item",ExpressionUUID->"481f5d26-f68d-4a12-8fef-44b7a5d216ec", CellTags->"TabNext", CellID->485448166], Cell[1221275, 22869, 312, 7, 70, "Item",ExpressionUUID->"7c33cc10-3e0c-46ce-b083-06bbe0916f77", CellID->472790593] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[1221636, 22882, 767, 20, 70, "Subsection",ExpressionUUID->"957b6949-17f9-4035-af13-6d8c5831c62f", CellTags->"Tests", CellID->16051757], Cell[CellGroupData[{ Cell[1222428, 22906, 129, 4, 70, "Input",ExpressionUUID->"279a5a08-85e4-44bf-b557-cb2cb542c7cc", CellID->667877521], Cell[1222560, 22912, 93, 3, 70, "Output",ExpressionUUID->"da990f34-d462-4dc3-8e47-b779ea756cc7", CellID->993233288] }, Open ]] }, Open ]] }, Closed]], Cell[1222692, 22920, 127, 4, 70, "Section",ExpressionUUID->"f8e3e233-41fd-4603-ad34-c666b16b6cca", CellTags->"Author Notes", CellID->795110225], Cell[CellGroupData[{ Cell[1222844, 22928, 720, 19, 70, "Section",ExpressionUUID->"27137d9f-30ae-40d7-bc11-2c6dd7abf74a", CellTags->"Submission Notes", CellID->843283583], Cell[1223567, 22949, 495, 8, 70, "Text",ExpressionUUID->"4e671e52-d349-4002-99b2-8c7225ca1a40", CellTags->"TabNext", CellID->920818074] }, Open ]] }, Open ]] } ] *) (* End of internal cache information *)