(* Content-type: application/vnd.wolfram.mathematica *) (*** Wolfram Notebook File ***) (* http://www.wolfram.com/nb *) (* CreatedBy='Mathematica 10.0' *) (*CacheID: 234*) (* Internal cache information: NotebookFileLineBreakTest NotebookFileLineBreakTest NotebookDataPosition[ 158, 7] NotebookDataLength[ 400770, 7322] NotebookOptionsPosition[ 397506, 7209] NotebookOutlinePosition[ 397848, 7224] CellTagsIndexPosition[ 397805, 7221] WindowFrame->Normal*) (* Beginning of Notebook Content *) Notebook[{ Cell[TextData[{ "El hamiltoniano en las variables p y x\n\n", Cell[BoxData[{ RowBox[{ RowBox[{"H", " ", "=", " ", RowBox[{ FractionBox[ SuperscriptBox["p", "2"], RowBox[{"2", "m"}]], "+", " ", RowBox[{ FractionBox[ RowBox[{"m", " ", SuperscriptBox["\[Omega]0", "2"]}], "2"], " ", SuperscriptBox["x", "2"]}], "+", " ", RowBox[{"\[Epsilon]", " ", SuperscriptBox["p", "4"]}]}]}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"H0", " ", "=", " ", RowBox[{ FractionBox[ SuperscriptBox["p", "2"], RowBox[{"2", "m"}]], "+", " ", RowBox[{ FractionBox[ RowBox[{"m", " ", SuperscriptBox["\[Omega]0", "2"]}], "2"], " ", SuperscriptBox["x", "2"]}]}]}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", RowBox[{"H1", " ", "=", " ", SuperscriptBox["p", "4"]}]}], "Subsection", CellChangeTimes->{{3.7205526751782*^9, 3.7205527756706*^9}}] }], "Subsection", CellChangeTimes->{{3.7205526625216*^9, 3.7205526731794*^9}, { 3.7205527813238*^9, 3.7205527925774*^9}, {3.72055405091*^9, 3.72055405091*^9}}], Cell[CellGroupData[{ Cell["\<\ Las transformaci\[OAcute]nes AA para el oscilador lineal y el hamiltoniano H1 \ escrito en esas variables:\ \>", "Subsection", CellChangeTimes->{{3.7205526482396*^9, 3.7205526578708*^9}, { 3.7205528092558002`*^9, 3.7205528195959997`*^9}}], Cell[BoxData[{ RowBox[{ RowBox[{ RowBox[{"x", "[", RowBox[{"\[Theta]_", ",", " ", "J_"}], "]"}], ":=", " ", RowBox[{ SqrtBox[ FractionBox[ RowBox[{"2", " ", "J"}], RowBox[{"m", " ", "\[Omega]0"}]]], RowBox[{"Sin", "[", "\[Theta]", "]"}]}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{ RowBox[{"p", "[", RowBox[{"\[Theta]_", ",", " ", "J_"}], "]"}], ":=", RowBox[{ SqrtBox[ RowBox[{"2", " ", "J", " ", "m", " ", "\[Omega]0"}]], RowBox[{"Cos", "[", "\[Theta]", "]"}]}]}], ";"}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"H1", "[", RowBox[{"\[Theta]_", ",", " ", "J_"}], "]"}], ":=", " ", SuperscriptBox[ RowBox[{"p", "[", RowBox[{"\[Theta]", ",", " ", "J"}], "]"}], "4"]}], ";"}]}], "Input", CellChangeTimes->{{3.7205468760738*^9, 3.7205469765778*^9}, { 3.7205470226068*^9, 3.7205470247748003`*^9}, {3.7205473167278*^9, 3.720547317071*^9}}], Cell[CellGroupData[{ Cell["El retrato de fases: ", "Subsubsection", CellChangeTimes->{{3.7205556472116003`*^9, 3.7205556610636*^9}}], Cell[CellGroupData[{ Cell[BoxData[{ RowBox[{ RowBox[{"\[Epsilon]pr", " ", "=", " ", RowBox[{"-", "0.1"}]}], ";"}], "\[IndentingNewLine]", RowBox[{"ContourPlot", "[", RowBox[{ RowBox[{ FractionBox[ SuperscriptBox["p", "2"], "2"], "+", FractionBox[ SuperscriptBox["x", "2"], "2"], "+", " ", RowBox[{"\[Epsilon]pr", " ", SuperscriptBox["p", "4"]}]}], ",", " ", RowBox[{"{", RowBox[{"x", ",", " ", RowBox[{"-", "2"}], ",", " ", "2"}], "}"}], ",", " ", RowBox[{"{", RowBox[{"p", ",", " ", RowBox[{"-", "2"}], ",", "2"}], "}"}], ",", " ", RowBox[{"ContourShading", "\[Rule]", "None"}], ",", " ", RowBox[{"Contours", "\[Rule]", "24"}]}], "]"}]}], "Input", CellChangeTimes->{{3.7205555442836*^9, 3.7205556402356*^9}}], Cell[BoxData[ GraphicsBox[GraphicsComplexBox[CompressedData[" 1:eJyUvQd4lcX2xgtiw4qC9Yhiwa7Yu05sqNgQELuigKhHBVEUbIgdFRTsikoH RT0KggrBCSpYEKUXQVqoIUAS0vdOcjmZ+c33nzdnX+714Xm2b9Z8U9bMrJlZ a9aaQ+/q2qbzdvXq1et7Qr16//31/+Xwu2TCA4snPJCy4O/+CxeXBvzWEVcM POKKooCX1abfEPA7tfSVAX9Qi2cH7H+ywa84ugH3d98HvMDlH/AbrvyAv3H1 C3ihq3/A/jcrUzv1l/aCaS+Y9oJpL5j2xnzMyQbTXjDtBdNeMO0F014w7ZV+ y8rUj9pO/aW9YNoLpr1g2huPk5xsMO0F014w7QXTXjDtBdNeGZdZmcap9qO2 U39pL5j2gmlvPA9yssG0F0x7wbQXTHvBtBdMe2XeZWWahzpOtR+1nfpLe8G0 N57nOdlg2gumvWDaC6a9YNoLpr0iV7IyyRmdhzpOtR+1nfpLe2M5lpMNpr1g 2gumvWDaC6a9YNorcjMrkxxVOaPzUMep9qO2U39pL5j2gmkvmPaCaS+Y9oJp r6wLWZnWCZWjKmd0Huo41X7UdupvvB7lZMfrUU52vB7lZMfrUU52vB7lZMfr UVj3sgTn6LqgclPlis47HZfab9ousP7SXjDtBdNeMO0F015Z17MyrfO6Duo6 oXJU5YzOQx2n2o/aTv2lvWDaC6a9YNor+5asTPsYXed1HdR1QuWoyhmdhzpO tR+1nfpLe8G0F0x7ZV+WlWmfpvsYXed1HdR1QuWoyhmdhzpOtR+1nfpLe8G0 V/adWZn2obpP032MrvO6Duo6oXJU5YzOQx2n2o/aTv2lvbKvzsq0z9Z9qO7T dB+j67yug7pOqBxVOaPzUMep9qO2U39pb6ZzhO6zdR+q+zTdx+g6r+sg7c0g N1Wu6LzTcan9pu3K0t8H/5t8QpXV31YD/5txRVif9e+K+T3yv9UZWBzoYOju DFoQ6GDoE2vrvybQwdBza9uzONDB0IfW8uPHQAdDf9ZhAx0MfY7LL9DB0Me6 +gQ6GHq65r//bQ50MPTDHD8CHQy9pfsNdDD0+93fA137Ebr2n/KffoG/YMan 8hs641X5DZ3xq/yGDj/B8A8Mv+Ly6mXpuINOe8HUh3pTPhg6v9Az/V1/ab9+ R7v4u44j+hn+K6af6Q/oYOi0AzoYOvWBDoZO/aCDoVNv6GDo9Bd0MHT6DzoY Ov2l80DHPekYvzoPMs0LxgF0HSfwGwx/wYx/5Xdcn5xs5Td0xr/yGzr8BMM/ MPxSPpEfGDp/11/omk7/rnIEfkOnfdDjeZCsI5qvyiVdR1hX6T8w/QWmv8D0 F5j+AUt9c8DQpf45YOj0D5j+AdM/YPoDDJ/BOo7B2j72FbQPTPvAtAdM/cHU H0z9wdRf9Wcqb1XeUw+wykuVi2B+qRflqfxj30L7wZQLpjww5YEpB0z7wbRf 90kqj9g3MT7B8AVM/cHUH0z9wdQfTP3B1B9M/cHUH0y9wYw/3ffp/Nf9Oe1m vwpGHsbzOCcbjLwDs18Fs1/V/OEr6cHQqS90MPWlHaRX+a3yWuUzmPzB1Bf8 bS3/q63+Nq/le9oeXfu7qg5+szbfSvtDbfr5gQ6GPrb2d2ygg6FPr63PdAMd DL28djwsC3Qw9Etq+bY+0N3wqg7tApOev7/usKE9it24SxvaAx0MnfZAB0On PdDB0GkPdDB02gfWdvELXf+OPNLv4Bd/1/6sX/tZud3g6lsHa/9C7+6wUaz9 Df1LV14drPWpquVLWeA/84X6wD8w6amfYr6nfnwPJj31Vcz31JfvwaSHv8gp MP3F3+mXq1x/h/myfS15eR0Mf2gvdDDrL+2BDoZOfaGDoTdz8yHQwZSv44z6 0z7qC3/A0KkvmPqBqQ+Y8skPrOMfuvA/h1+VZ7SX8RX2R368gOl/MPNV9aDI e+avyivVu+g4IT31VfnE+kZ9w3rq6wumvmDqq/olxjP1ozyw6o+k37OU//yd X/jN9zq/4RfjIegjfHvAjA8w7QMzXjQ/ne86f8HUj/awHpMf45v6M551vqjd kvz5Hv6C4S/5gak/mPqDqT+Y8nV/RHns36g/5SN/wXpuyaQ3Y5+tegvo6A9V Hwad+oDjfXi9HN1Xs18Es18Eoy9UvQR09sV6LocO36AznpUPtJt9lNql4QP7 N9U/6flD9Utg9m9g5qvqIVX/TrspH0z5MV9yssGUD6Z8MOXrOZ3y4Zfq05VP GfR4Qd+s+g7oMn6y4valjYynrLi9aSPjKytuf1ran5b2p42MxywZj0FfrfoO 6PBJ9R/Q4ZvqNaAjR/ll3oL/qf1+S8Dda/PZGPBltfkVhvX837X0koCRE/o9 5bD+gFkfwPQ/WPXm+kv7M+m1MunRVc8L1l/GA5j+B3NeBXNeBdPfYPpzW3pO 1cOpXUD1/qqn1nqD9Zf2gGkPmPaAGa9g2rMtvazqEdWOoXYK1asr37XeYP2F /2DqD6b+29Ibq55T7SxqR1G9v44T5bPq5VVvDqb+YOq/Lb226mHVDqR2HrVL 6LjWcaF2BNXzg6k/mPpvS++uemK1U6kdSu0oOg/B1F/HCVh/qT+Y+m/LLqB6 bbV/qJ1M7T5g6q/zUMeF8lnrDdZf2rMtO4bq5dXup3Y9tVupHNR5qONax4ny XesN1t9Mdhe1K2SyS+q6w/rGOsj6Bh5bW9+xAXPeAHOeArMegiknk51jgl8v SU99dB0mna6zrPdgvgfTHjDnLTDtA9M+MO3TeoKpJ1j1SvxSbzDjTPVymg46 +XZ15Qc67QdD1/0L9Cvd/qcOnXLgF+kb1NZnna9vRTjvQYefYM5rYPgL7u5w 0EvAbzDnOTD8B3O+Uwzf7nPtCXQw7QXTXjDfL3L8DN/T32Do5Kd6LtW7QCe9 6jHBOs4ZH6QL53/fX/Qz51Uw/Qemv8D0D5j+AdM/YPoHTH+A4T+Y+Q+Gv2Da R3t03ELXca7yAb7Sfuhg6PADDD9IDz9C/r79YNqnmPxoL5j2kh6s9P+/4wS5 ybiFzrgFq14SPkJHXoCV78iHoI/0/FZ9JunhX5C/nn9g5jMY/oHhB/lzPgND Jz3zD3q8zqQDnfTwFTp8B0Mnfabv9FfnKZj+0n2q8ofzLPsBLT8+Hyd6cv5O OtUrqtzgV/U3fMc8BLM/ALO/ATO/1F4Pnf2P2keoH/ygXmC+hx/QwdDZL4X8 Xfl15Lva8+N5VRww8wqsdkGwtl/t9cwj6qvykfTUD0x+av9mXJOfyh/Skx+Y eqsej3EU7wfTsh9My7k+LefiRH/EPIrPbWk5ByX6omAf9P2l81vt3/F8Kw44 3j8m8/B/3z9K5Jfap9X+ofZwteeqfRw6+jK1H6m9XO1H0Gk/mPrQT6QHQ6e9 0IN+37dX7efwie/Vng6d9qp9HTrtVfmu9naV99BpL7i22lcgn2rCL3/n19Uj 7fXLuZ4/Vfah2nxWB/rxteXNDfRUbfpJgX53bfp//PyrtItdeaEeA9yvoR6U 59alKkN5bn1Imda1f1/k+7HCUD7pZ9fmNzSkpz5g6uPmb2Uol3pQL+rJ3/ke zK+my/R3+AOGP5RH/o+6+ln41ca1J6Sf5NoTcLy+pe1Bjh+hPKc/zw34XsfP kJ7y4AflUR/KA5M//CY/6JQHPR5P9XLYvzG/GJ9qfyM/0jPfSA+O+Vkvi/lI fpyn4Cd0tY+pvY7y+Z71T+cN34fzls9f/eqgM77hP/IgtsfmZOv5Df4hD6Az /8HwC4z9JMM9gBzGKe2Bb6yXrFdg2gdGvoE5r7BPBkOnfmDWGzD9oP62qp9X f1S9F69+qWoH4O+sv2DWXzDrL5j1F8z6C2b9BaseDnuN6rXUr0X1RuoHovYL tWOp/67aA9QfVO9Nqv1D/V/VHqJ+sGoXUb9RtTOon6Xq7dUvETrzAcx8yKS3 ZT6oXlT9plTPqH5Gao9Rvxy1z6gfi9pr1P9Y7R3qz6r3WtW+o/67au9Rf161 /6hfr9qB1A9W7SrqNwqd/gLTX6pXVz891VurX5val9QPTO1N6jel9if1M1J7 lPpPq31H/XH13rHar9T/WO1Z6o+s9i31T1Z7l/opq91L/Vz5O/2jdg71m1R7 mfoZqp5e/fLUnqZ+bGpfU78vtbepv7farxiX8X2A5F4EGH6rPQ46/Fb7HHS9 5w0/1V4HHX6qXQZ6bN9P7lGA9V50bM9P7u2C9R6/3kOGP3pPRP2n1d6n/tRq /9Nxpn7Fag9UP1y1U0GHP3qvRP0e1V6o95jVn1ztb+qfrH4Cal9Uf2y1N6p/ ttof1V9b1zX1385kx6Zd0PlO7Zbq56x2QPULVrua+tGqvVP9TtX+qX6aag9V /3e1J6o/tfptqP1U/cfVnqr+5LqvU//yTPce6B+9V6D+59pfyne1z6ofutpp 1W9b7Z7q56z2XPULVvuu+tGqvVf999WvU/3B1a9G7avq/672YvWHV/ux+sfr vRT1l1d7s/rPq/1Z/enVHq3+9WqfVn97tVer373ardVPXe3Z6tet9m31g1Z7 t8Yn0HOc+uGq/77ax6FzvgRzvgRznlR7kPrnkz/2DfS5pFM7ufq1q/1c6xf7 ++QGfYXYB7I4Vy92v8H+DZ2/8zu7lj406Afof/J14yUv6G/U70/v6dEf0Pk7 v/QHdOxV0OEndPgJHb5Ah8/Q1e8LvXSme4TwF0z/g9GXguEnmPrpPQUw81P3 Gao3ph3qh6j3FlVvQbugw1/o1AM68gfMeEIfB//5nvaRHv5Dp97Q1Y+Nv/Nb ++f/o/flF30h7UX/pb+0N9Pfscvwd9oPhk567KHQwXpfnHUD/Rz1RX6THvup 3hukXeiTuW+BfZX002qTTwv5Z7n0hvTIa8pDPlN/+guMvRRMfymd/JBz0Ok3 MHTSqx5b7dTI70x2bfhNv4DD/HTzLYxj7BFhPvr2M+5pv95P0HvDme7ZqN1c 7erMZ+YR/Ue/Ix/AzHfS0x7o3L8Akx/rDun1nozeUwHDPzDyTemMAzD9ClZ/ HL5nvKu/IHTaH8r39QfTf2DGM+Uz3h3fywPG/oK9ie/pXzD9r1jt/XqPINO9 A70HxDxVeab2B+ZFpnmTaZ4x7qAz7sDQSR/rMZL7G8w7xhOY8QYe6eRNsJ8w zvQeqPKN+sAnMHTqx9/53dbf9d6G3uuArxnsPVmx3SQV5jmY8Q3GHsX+Bgyd 9oCpF1jsQcGvSstTPbfe39L1Q/V20LEnuvzLwjlB5Rn7XMZ3uKfr5yf97Kud rfKF/Sj1Vz00/U594Qv1BVM/vVdJ/vQX+wbaAaZ8MOsv+xWw2jPB9B/fU694 350OmP0985z1n3qDmR+kh87+GQxd9bi0m/0X9kIw6z3zlfowX9kfFNS256+A 6Ue9d44cu7Q23YqQnvHE+E/Vfr820Nn/qz2Z+jL/6A/qj7ymfsxXygdTfmzP 3RD6hfKhg/meead20kz3cKkv9Wc/5uZHecCsP+A4LkhNHb/Wxe7v4fwK5pfx gH6A/nDjIS/IHzD8vtrxK+Cda9PNtHH/rAzzCHs440fqFfxa4/sPG8L6Qfnw l/LBlA+mfOQz5TMewIwH5oHKc9LH99lqwnkM/iC/wLE8TIXxS/+CdXyTnvkJ HX5Rj/h+aXKfQ/VStIf8aQ9Y7xeAaSf9wi/1YPxxnmU/xHgFKz3Wk+WG9oHh D/spHX/UL75vm9y3AMf3ZRP5zPoEpr7x+anCynwKfuv0D+semP2Q+h/rfQfo 7P/Aes6m3/53PO6a8L3eJ6AeYNYp5K3aj1kn1c6ldmLkN+st5YPhD+NP9R7U S/VFYPIDww+wnuPpF5Vn8In1iXqz3pIv+gSwm/+F/u+lYV3R9QT5xXoe7nv5 +QQd+QFmPMIHxhvyh/zB0JFnlAfmPK7rFZj6gOln+iuWF2WhPPhLeXF8zbzA B7Deo0BOkL+uF8xn8tf4GtBtbT5LfXmJfGA9oXzWB/IDUx7zP94Ppgz5u/5O B3kP/+Gf4jh+Q26Yn/BP1xuND6H3MBlf3O9DHsX3FJL4LOxDwcx/5CvyDTrj G0z/k57+hx+uXqlwPy7e/20QfV1e2F/F94mTeDzIk/h+fXGYl8hbxgvtje2C yfmD9SPu73I5b5ab+P4z+p5Cv/6UBHmgv7EevCikpz7wH/45/U5pGN+UB2Z8 uPV6eeAv9Wd8gdXuQL2oT3Ut37aY+DxWGfJ3/EzeoVB/LuQm40b9YKDTn+B4 ftbLidfnejnoO8DUG6z3xDnvQGeeaBws6olc0bjt1Bv7kvoDoX8jP41/rPoW jbesekHWl9h+k+jhoKPfAsf7xST+AfIoPvfWy4r3f0l8A8qL7TeJXoj0zNO4 /PwgX2kP9dZf8lM9faY4ByHulMdqx9Bf+AFGXwdGXqifqPppqt+lxl3QuAlq R9F6gPWX+oGRb2D2G2D6D0x71M81Uxw02qNx4DROmNqBlI9ab7D+Mv7A1B9M /cHUP1OcNuqvcergG/VTPoIpH6xx3jRuHfnpvg9MfpniwmmcO723C3/B+kv+ YPilfsqZ4s7BL427p3E+Mu3zab/WA6y/1E/9pjPFoaJ+GvdP7aBqd9R5rOMI TD8o37SeYP2l/moXBFN/ra/KObD+kl88b/PDfgdcS956DuF8A55d+/3QgNE3 gZfW/q716115sLfVJtu630a/Boaudq7/HW+2LGD2e6TX+Pns1+N43XoPLtHv gJ0+Ndfv19jPrg/7a8efdX69TPzrVQ8GlvU2xBlnf8D6rHZ+vmcfAJb1OcSl JT/dJ5Ce72U9z5H1PNxDJj/2o+pPTnr6Q/0VoKO/gc76r3Y16ifrf4iDy/d6 Tic932eyI5Ef+1L1N1c/P3Dsz5Sq02/aT3yvcaqCf7jnP/0G//WeqtpjobNf 1XtsKkehs5/VcaJxzHRfAt/jeKbJvVTSM5/0fEb6OL5isfgrF9fZB8Iv8oP/ Gg8MOah+p2oX130380v7Rb9nv8l85Xv4rN+TXu1CyCP0F3IeCffQSY+8Un0H 6ZmPpIf/qi8GMz9JL+edcK8POvNR/Q1Jr3HaYr1TVbD/gOX8FOJI8z39CmY+ qh+q5k9+zGe+R47rL+cF1hH+zrkcuhsvRYHu7HHFgc76CH1SbfpNgc45G7rq 4TgnK+b7TPdoMt274e/8buvv9Ad/p//A0LdlF89kR88UJwWsfnWZ7gXpvSGN 26H3WPSeC+n5O7/6d+YjmPkGZn8Hxt4PZr8HRv6BWS+VrvtI6My3/6/3SvQe SqZ7JnoPReNSQGceZYpjQf9pnGH1m9Q435nihGrcHI3LQv9mitOi/Ug9tV9J z9/1Fzr9z9/p73C+rq3v2DrnY9IjX6HTn9DpbzB0vQeUKS4LdI3LkikurMZx oT8z2d2haxyjTHGkNY6RxrXVexcat1fvadDfGndH52GmeUo7tB+h83f9Vf0B f2e+qj4BOv2t50Do9K/e49I4OmDoGrc8UxxsjWueKc6Mxs1WfYbGZc8Up535 BV3nCZj0me7dgeEnGH7yPfyDDoaucdtpn2LSaxzzsL4IVn0M9CBnRA4oXe8d gmkf6YPew+Mg/wWrvgd6kM+CM8UF0zgbeq6j/duKq69xrPTeqNp5trUOZlo3 4Sd0+A2Gvq15C4ZOev7Or/6d/gLTX2D6B8z813uYmexY0NUPYlvvAug7Dxon SuPeZ4oDp3FV9BxPf2ucOI3jr3HL1E6cKc4Z/R3mhR8PYOjbWmfB0DPJFeYJ WOel9rv+ki+Y/gfT/0rnO/o7U1w06BoXLdO7Beo3Q39rnDB950DjSmSK8wdd 771r3D+NC7ite+Ia1071q9Dpf9W3Qmc+Q6e/dR5mmqfaT/pLOr0HnSlOXaZ7 0Rq3TuPabStuW6Y4b5n8DDL5JWQ652U6F3K+5RzL3/West5LznSPGX0O52Qw +XO+1nOyxt2pJT9QE+zqsZ6uLGDO72DuJ4C5/wVGPw3mfiUY+z7lU29tF3Ta offw9J4G6dEDxPFbqgIe6L6T90iTe156zwd+xPc3y+rcA6Jc7gHE5ZcEDJ3v wfo99aY/+b5bbXmFdeJRQY/vG9TIffGacD+T8mfX/g4N9DYOh3t/9B/psVdA j+831tj4PkyNXzfy62DqD6a949x8CXTGB9+DqQ/jBTr3I/geTP7cm4COHYTv 1S7CeAMz3jS95kd53EOBrvcq0TMqJn18fyzRlzFO4D8Y/mUaZ+SndPjK96p3 o96M97gdZXUw7UC+QGd+6b045i/1Ij2Y/NAvxvkVBTrySr/X/GN5WBLozC++ Z/4ppjz6Azrzj/yYf2DmH+Uz36Azf8DMD/Knf+L7rflBX839JqWTH/MBOvMB DJ38GAfQwdAZ79AZ72DopGf+KJ36gdWPhvT8kh46mPHKus/4Vow+HP67+VYv i3JjfXlK9O/pOvHsyJ9569PLfeFk/dH7/6pv5zvSg5HX5A8/oVMf8gdrfrQD ehwHjXc108GPMF5fc7LB2Eti/tf4diW//D2+f13j9Rurwn04/CeoZ3wfXuWj +jOF8kI9Lne/hnqwn1M/cNX3axw1/h7HbywN+z7181f9vvpFq9+X3qeiXOqb yU7N+FH9v9Zb81M/d77n73oPjO9Jp/lrXDm1G2icNPLFHqf30zOda7F/670S yqU/NJ6c3uuATv/o9xqXQf289D6cxrHV/NXvXe0DGq9O/QD1Pht8pD/BsZ/B hjr3FtRvjPQa707v86lfoJav77Rp3Em1R2h++m6X2vnVPqHx9FSPlUnvxfhR +xH50P9gzo0aN0XjJuv9RL6n/zV/fSdM7w3ou3R631HjJGt5+u5dpjifrFua H98zHjWur9qv9F07vQej7/7qvRkdjxrPT+9vQmf8aPn6DrDe9yQ980zz03fj 9H4o6am35qdxHdV+pvECY37kZIO5n6D2MspjfIIZz2D1i2f8ahwZvY9KesaT 5qfv2un9VY3brfnpO8x6L1rvv2p++i6z3o/VOPAajxA9GONP7XEan1Dv20Jn vGh58b25ivA9cl7v6+o6qPEO1T4HXf22oGscSrXfQUde8j3jS+Ok8T3yU+11 pGd8gBmfGt9Q7w+rX7bGP9T7xRpXQOMh6v1jTa/veKs9jzga9Kdi5inyADr8 V0x6+Asd/oDj+0U52fH9oZzsTHHvFZNe383Vdw5oj8Y7VHuVxj/Ue3Vg1g21 /5E//FCscVDV3qTxDvU+N/nBL42HqHpsjYeo77iqvVDfFdB4iWov0viJ+q6z 3u/WdyX0Xqi+e6/2Jo27o35Kmn98bzfxS0Q+6X133Zdr/vpOqtqT9HuNS0x6 +pv0fE965qmm1/vufM/fNY6c3iuHrnFfWC/V3qRxYfR7fbdV3wXW+/8ax0Tz Jz99d4H1Uv0HND++ZzzqO8l6n1/jNuk9ZOYh41HjUqgfmI5XjT+p/g3QwztR Up9M73xrHH3Gs/pLkB/jUcvTd34z3QtG3qn/BfmF+xweM97VLyjTPSfqoX4b 5Bfuc3jM+FY/CeghDpJ8r3EVNY6g+ofwPeNT89d3imP7anKPWeOaZHqnRcvL 9G66vovA/FD/Fc2f/DRuit7jVb995gt8Y3yC9d4+84PvoWt8T/VP0Tg6Wl6m uIQad4zxr/lpHH7SM77Vvsz3zB+NE884iO9jJ/tEcHz/OpHDYPJVPx/KpxyN 9xn7yyZxChi/pNM4QHyXKW6mxilgvOq7QZp/priFjE/1T9L89F1rHX8ar0jj j2ocStVT6veZ4ljGceiKRY+V5KfvNsTvpBUEOy/p1M+K/OI4W8V1+pW/q3+W +kdofpniRKKPdvM9FewJ9BN6ZPTKou9Gz2ygi/45xAeK7w3lB+z87dd7/Xfy zjj9QP9o/FLVY2v8UtXzqpwAw1/tdzD80/il+q5XHEc+HfwAsJeBsVeBOcew n9FzEftu6OD4naqqjH4E+u4a/ARn8jPADgy/VY+v8UxVzxu/e5Fr1S8ROvzX cQmG/xq/VN8lA2Nv0XvEtIv7Pord+KsO8Q34HntMfE+pqo5dFzr2VOy0YPrb yYeCQGddjsdtlVU7sNqJ1S6s44l9FljjX0IHQ6d+2EXhR+ynUxjsqGo3pf4a j1HvIfMd/IeP8X2sKvGPTTDp43NNEg8mvvdUFe7RxPdDyvx7WUt8vctsHP+F e/Dr/HhOBYy8JB4I9WH81ZIfSOQfdMYTdOaH3iOGb2CNJ6fx4jQ+dHyvLz9g 8o31OsT7TQWMPyv2f42PFscZyLfxvjK3Tjyx+B7iOoP9E34oHf7iX0t6MPUF kx5/YjdfWCeSeFbx/ajE/sr8ieOVJX5d7INY31gfmSeMf+YFmPkSxx9P4i+5 elQF/hOPxpWfxANy36XNfxw2YMYj9SM9/QOO9WRJvD34xb2V+P044ov87flf FuisN9Ad/8vCfZE4rkMSH5L+onz4EfMxiffC3+M4NewLt4T7N6y76jdGPyqd 8cB4xp4ev+tTE/SYel+M7+N3KGrCeIrvh20Qe35hnXNS/P5pYbhXwTgCy/2M HNmH1Yn7zrqi+2KwxjFn3Oj7aupfqHZzMOclsPpdqR8P5yV9/5p8wZn0dGA9 9+l7anpPFbrGaZ/g+qHO+2nqn8g5Ef7ofQR9L039D/W9NPU31PfSMvmlwb9M fk2cN/V+gfoP6r15jauh76PpPWt9H039D/V9NPU31Dhq+h6a2l/1PTR9h1D9 B/U9NLXP63toan9n30K6TH6AandSvxPVEzN+yQes75+pn4K+f6Z6NH3/TP0D 9f0z9QfU98/Ufq7vn6m/n75nBh3+guGvvl+m/nLqh0N6vdcPf/T9Mei0V/3j 9D0x6LSPfWn8vkfyPhj0OF5GYteGrnHq1Q5Oe9X/bWztd0mc6O4OBz2e+seR H+2FHse3qPuuMvUHUx6Y/MHkp+8y6/tY+g6o+ovp+1jqHwad+gU+eAxd5xFY 7Ska9wk6f1f/HX3vSv1C9L0r9d/SuLz6brO+P6LvV+m7qepfpXE9wPAHnClO F3Tmgfqpalwsfa+K9IwD5Z/6x+h7U2pvgh7HlUzel1J/JX1fSv2T9H0pjSOr /km6zqk/kspd9cNXuaN+2xoXjfTsd9TPj+8ZJ2CN8wofMvmRUY72h74Xpf5K +l6U+idBpz/0fSj1N9L3oNS/SNct9YNWu6O2X+Pe6vtO6n8U3wvKD+uEGy5J HGq55yvvNdXVa9P+eN1IfuO4jsm+GxyPW43jmMQdjuM8Vga6xm2O/14Wyo/j OpeFX+oTnyuKAp31L44zmB/orHfxvjg30GlfHGenMJzraG88L0sDXeMux++6 lwmfk/NIfP+00MTnxHpZjEP6HTr6NH33Us8DpAv2Xb9+6zvS+o4V8hc68hY6 /IIe7J2eDr+gB/ulp9M+6IxT6NSfdlF/PYdB13Ma9YdO/aFTf+gaB4/6Q6f+ 0Kk/dOoPnXbpO6G6PsRxw5JzNv2o8e6gK5/JN17n80w8TlOy70rmqZ7D43Ff WeecyjjU98HiOEiFQd9JPWM5XRroGmc8/i6pL3ynfswLuVeYRf7Q0Z/V/oR3 YfAzTPw/8IvSOHiZ/BrVn5H80WOBocf+JoldKS63Inwff1ch98KL5Z20kpC/ +h1AJz++j8srrnPvXOMi0V7083G8qeReOv6q1A9/VTDjl/xStfycFOjdHT3Y 7dH/Qyc+Nljt/vhrKZ36Qaf90Gk/ej++VzstdL5HDwkmfWz3La/jzwhWuxjp yY/0cXnJO3/67hFY/Y7B0MkP+7bi2K+lIIwjvbet93KRg4yr+H2aJK4G9Dhe fXJvTu8NkT/9T3ow4xp7N3T6e1vzJp4nSdzKmJ8ldfwY4ZfGrWR/R3mMG/WL jcdB4r8OHf5DV7+DTPfOoWMPYlyBGUd6jziOu1Nc554d85H66T0k+kPpme4x 0T+k13sc0Kk/dI27F8cxqAr50V9qL4znbRKHM5735XX8inXexvfvKurMM7Xj x3KiPPjrxuUldn7S67ylXer3xLgkv3helIf08T2CkpA/8he+TnLyOfCR/gfT 37H/aKHEQywIfKf/2DfpPRH6ifrST2DSx3b4koz9rnb8OJ/y4B8bl5fY+aGT P+n+t99qWcZ0YPXLBcf+xFV1/q5+6ch19dPk74o1X/ZL/F3XCU/Pobx431MR 7HeMH/ZpYOjIL+jIH8XsU9kv8D3xlknPegJmfw1mfPI98guMPAEzPvme8Qlm PMXpy+V9i7rxBGgP7ef+BPIbTPvB2P81vgD73rj+paH+pKc89sHx+zJlhv2W xh+ATn7Q4/e8S4P8YX8Ojt9ZLgl0MHZD6hffG0kw/c/3rE9gxgPpOW+BGR9g xgPf017F8ft/BXX89UkPjtOXBzo4vrdYFTD6B9aR+H2/qhDPAzrnufi9n9xw TuB8iHzg/AjGvsw45XuNhwCmfMXxPfb8QKd+0GvhQPZXybt7tIf+QV/EfQLu G7AukJ77DuTrf8M9QMYL8pr7fMQ/V798viMf8qUcyie9pDNSnzp/53vkKHTa J/dBsigffV4cp6BG4i+nrdz/yCF/9IKUD5b8JQ5CwgfKk++D/oHxxv0J5Bv3 y+LzZ0FYL9jP6v0D6h/Lt5ogzzS9+lFrnFX2NZnicqpfHxj9LemJt8O+KY4z WlzHjw59k77Loe8tZbqXnymOrfqlM16Ql6RXvTf6F41PwniG36z38bpdFfiv 9zD1vK/6VnDc32VBXuk7MIwnzgN631HjYmWKm6V2z+619LHBDpIpzqfGxdQ4 mPoOE+tM8Kfx+VBvyuGcCmZcKZ3vM8Vphs54go59i/pg5yO9xpXjXARmnCqd 79nHQg/+Jp7OOIMOf9iHwR/4GN4n8nwO8a491nfdVY8Q7qV4usaxDu/ueDr8 oT7wR985Ib2+Sx7eFRA634d41J4Ohg5/oKtdnL9rvEeNE7utuKqxPS8/6Ac4 /9MO9HHs3/ge+cN6zPfEH9P318gPfQ35sf7H57TEb4D9Er/ID9Zr5IXqm+Ej +mbmPek1Hh7yDP4hP1O1f58U0s+u/R2a4f2WsjC/9R1K5GR87qkK9hS97xfH tyuS/d4GiSOeL+/J5YdzFu2Frn70tJ/yaB/ltXE4tJP5wPfcp+T7+D3DmrA+ xnb+3CB/wchn1heN06n3EVUfG8dtzQ/nCtLHcVzzQ/lgyo/Lw45RFMoHw4/4 PmNyv1H3b9gL+E71/Oht6N847nt+OM/F7zGUhPvM0OP3nkuCPh0645vzH+Mb OvICOv0PfZJLH3D8XniiT4UO/2O/47xAj98DLwn9AT2ON6j604Rfcdz3fLn/ nh/O3cwH6PALeQRGHsXvwSdxMOK4LbkhPzDlcf7UdQG7FvykfPgXy8eV4keZ G86J8fumZeF8xfdg2kN/qH40jrubH/LXeyzQkbdg9FHMH43DGMdtTMl9br0X nA56EOSWxiNUfaOeR5H/Iq+ykE/Ie+oLZn4r1nd54nd8KiUeX2UdvZvG3dNf 0sfxh6vCPo182JdoHDvV9/F35BD5InfUnqjvw8TvfFVIHKviOvZCfT8mjotW IP4W60L8OOQT37P/AEPne9YrjfPBOEO/Q3rmF3T4B25Sm+7n4L/H+CD/2F5U FbD6A6o+EHomu03sB1rXThC/01cl9+sT+xx0fZdE5SfyHHmGfCA9OH7/OJEH 4NgfukrqnQ7rqNoblB7HwSoO6WN7Qzro+6AzHhTHcWL+9jjR90Fnvwqmv2P9 z+owjzhfgqGrf5Lq/6Cr3Sj2T64Se0U6yN3YzlTXfhDHzU78CNVu4fLHfywt +aTDesh8ANOvcVy4JA4Y6ZmP0NlfguGvYo1bA517keTP+qTxhjVuBXTqr/Fe NS4adNoD346vxXPDeYD2kR6scYigsx/me9oLPb53m8T1UP2K4tjuszFgt6wl +rhYP0hctpXhvgryknU29h9MyT1B5FVV0Aeyv6H95P+3yz+c91gHyR//Q/bR fC/1D/pQykVfCZb6BEz74jhgldb155Lgn4Z8o31ufq8M35Oe+rJesE6TnvYy TuEP+zE9zyhm3SW97ueYv6RnnoOhx3a9mjDe9fxH+WDdD5M/+1/Wm1gfh39l TjbtRv6B2c/H727kG80vnD98e1mv4ve/S2U9Kwr7g0xxAdHXkp7xoHo0xZnu Neo9wTiebBKnBr2ExqnRuDYahyPTO20aJ1Pf+YJOes5B/F39fvSdbNJB1/LI D/5miqOI/hq6xrUbW0sfW8evRN99Vr+NbflJKF3jUoHVj4DxGY/7jXW+p/30 Z6Y4QcpH+Auf+FX/Kv27+mFxzoSf0DWOIOsJ+VH/THHZkM/kB1Z/JcqnveoH AJ3xrPEYVV+daZwwfjWuJnTqA6Y9qvfUe0jkx7kWHN5jdONS3jPNyY7tJYn/ k8YhYFyH+eXzC3EYPR0MnfaQH/wnfXgnyqeHDobfpAdDj98fzcmO3w/Nyab9 zDPar36WGseUeUq/gzUOQ6Z3hlSfTv7UF0x9wcxDlQPwhfmnfofqP0V65oX6 SSkmfaZ3spBDpNM4dvrOjvrBaDryY75l8puhv/V9MeScxkGGH+ovRTnMC/WP gq5xRhl36qcH1jiPmd4RI/9M70xpHEjap3ECSQ+d7zLFXYNfGhcaHL9fnPg3 qZzT77GjalxfztvokTivgsmP77m/Ax1+q91J/SZUDoDVTofcATMv9Z0u8mec aVxFsPphwXel6/e0Nz5fF4bzNe3ne9KTD+lj+09p2D+jzwBrXDyNb8G5PNYP J35Jtcn+z/02fUdZ9WrYD/g7v9v6exxnJ/FXAkMnPfWHjp4XTDuVzvfs+6Fz bovtIRUhver5YjtXUdDXQee8rPer1S4HHT7rO1YaB4N2gLUdWu9M7aQc6JQD hk56+A2deoDht9L5PtaTV2zz77XZJfeWwq9rd4K5H8Q5LY6Pk65jh9R7mPzy d76P39+om45zHOliv7wEq3+K5qffqR9L7M9XWuf+qL4jDp305MM5LG5XkdSn KKSn/zU/rU88/0sCPY6nlcTXIn+wpic/1o+Bbh6EcxX4xtr/+S30P3KS9sX+ gQmO72EWBTr6SH1nT+PdxN+XSlzL0pBe730yHzQ/tbfSfuoT+0uWhe/RY1B+ /H5LpY311sk90zhuYqXUJ7mXGsuFSrFjJfXRe/jQ/fysc/+Q+at2LX23Cz1f 3L6673ip3l39X5kX8X275N1S0rH+ko71E8z4Ij/GE/MArPbc+F5DysbnruQd PXB8L7xeDvoXvRcBVv8c6PR3/L5Pcs9Y3ymjPPW/0XsA+i6dvmOndh/o8FEx 6TnvxO+e54f09BP25LhfSgNmnpGeeQGdcRrXpzLgWB+4Ut5Bya2zP2VcpGrp kwKd/Sj0NrW/Q8P+bpJLHzD6WXBsby4S/9CiYG/R+Fsa7495Gu/3ysVum7yj lundNT8+suDHYjce6tiN1Y8EOuOR/tN32sDxPi1l43N88m4hWO2I0JE72H9U DoHRo/+/y826cpf1n/qpXASrv5Lmp3KY8adyGjkRv9tYEjD0uH5FUl5RoCM3 9Hstj/rE8XIrzVlu/Q32tbifE38kcDxuufdfGsYr44D0YPVn0vxiv+eisI+M 4+9Whu9if43ybfw9Feqn+ajfAuVqfvpd/K5gQs/0DuG23i3U78mfca7jn3mM fMd+Eu9HU7Lfq7tuxfu3lKwTqTr3XuL1v16O2G9kfa97T4by1F8njgtdEMYp 7dP1Ud+n0/MW9AmOXsf/lfMy3zPOqV+8LyqoE09a30cmP8pTvynGYTz/667r cfmpOnI3HpcpGW/JvR7+zv6HdoP1HQXo7Nc1nqq+w6X+L6wb6LHA0OEL6yGY +pAf9Yn9eXLDPR/0LawT8bsM2EOJ/5hgzhe0Iz4v8G4s58Lk3j/7XO5jUB/s l5Qf37fIC/NV36XkN46rkPipgPnVdLSTdYXv4LfGBecXusYJ17/H7+pxnykv nM/Y39AfyAPqGcfvx76eF+zrYPhDfnpPRP2bY/+zqmCPB9M/8IP6uPFKPIZ0 nTjqYOQA/IDO9/hT6XdgxjPlqp8U+brxvTrc1wKTP/NN44EiP2N9W0r0aalw v5b5TH+Aocfv3uWFcaR6Kd3HadyWWE+VCuuQ3neO3+HJC3JO33HSd3jUroc+ X98R07iOlIs+O9M7dtjD2cfAbz2XIl/j/VayzyW97ovj/UQqyAPGQxz/q1TO B6VBjql8it+BZz+QyDMw8ys+HxIXpMKgf2E+xvddysJ85TvuV1B/xhPjHzo4 fs8kuc9F+WNr048Ncn12LR4azvG0X+8nxvfOCsL6Cz/jONBFoZ/c3+FvccCu f0rCd6y74Pj7LaG8OH5+4h+i+oXYrpnoOeN4XynZj6meIBXmM/Q43lcSJ5P9 Ge9/k577YWDsZ2CJ85TD/Xjo2DXje1CFYf5r3KU4Hlgq7FuZB7H/R2m4NxC/ 05ob9otg0sf6wYQOH7F/wTfsg2DsknF83vwgn7DXUi/y0/c0kTvkH8dvzcnW eMD6zpjGyyVf9EZg8gfzPXISuRfH+S+s46cJZp6C4zh1OdmUD6Y8jY8KPfZv zcmO14ucbMoDUx58oTww7dV3e8DkDyZ/9RMEU2/WHdoNxp5IeuaD2v3Vrg5f WGfoB/RX+n6X2rf13Up9N1D93/RdOX2HC4w8Rp7F+rhSc3Vt+hWBTn3iuNG5 Ep8tN3yPPGN907iAqseM9Vkp0Rek5JxdN866vmPEuxHcx3frZFHAyHewk9ul AdMfjLtYHhWFeRzHDc8NdNYv9Vul38H6TmW4n+XpjBeN80t66KyPaqdgPUbO gmlnrB8oCnTWA/jJesv+gXXf/T2JD6f2LbUf6X1NvovvZ1eE8yZ03kOgHthj KYf9GzhOXxH2DdDZV4A5b1L+fPe94fs47lR5Hb1ffF83sW9Aj/1BSkI8EzDy B/0E9/uhc986jlOX2KvVz4D82DeTH/uQ7m58mUz3sibV/k4K+xb6h/MY7YEv YPZz8X66Irz/4eZvRbhvzvfwg/ELZv9Ee9hf0R7o9G98TqkO5YE5b6odDD7H 9vECOa+uCZj2kB/jh30t4wc695uh026Ns6T7Ya0v8zi2x6bCfU3kbhw/ImVj e2NK7HmpMB71nWlw7E9bFu7/abwB0tM/7M9Yb8HIL9LjvwKd9RbM/RhwGyfv wvik/Rrfh/Uovn+UvPsMpn3o0WgfmPaRnvZRHu1Tf3LS0z7otE/jDZE+1v+n JP5bKpy/kIdg5AL7qDhezQaj8V447/NbS/4/ehLGE3Qw6WqzuSId5Fvsr70q YN6z47yKfQH9EecJ8gdz7r69Nv8ZddLDDzB6TtJzfmVdI73r3uqAfXuCvoX0 1If00v6gr2H8aHxU8od/Ul7QHzn+rQ/85HxGeWD48bRrX9C/QSd/MPwgPfyI 76NVhvtrYOLZqP6MfRf9jfxAH8a+gv4Hx/7OFUHfw/iI4+jj774u6F/B+LvE /r8VQZ9M/eN3Y5P3q2gPGH0hmPlG/7L/if3TK4K+g/pyTovH/7ow3mO9RSro 92L+rDIx//LDekt/UF8w9SX/+B3b1eH9rfjebiqsZ//7vakEs9+L32MqC+0F x/6vyX0fN56r5X5QEi+HeYJ8U/0F+xnKB7PfBnNeAXPuQl9A/CLkKpj9Ft+z fwCzboLZf9CeON5h3fiOyBHaB0Z/oPvh+F0c/InKff021sG8p4Z8BbMfIT/4 zjqGPNL7+noOhs737BP5Xu+/g2e79TnUI1Wb76QwD5Af8Husyzesn6zr0OEX +yP4hT2A8co+ifU9jtexKax7nJtjeZMv79JvCvIGzPxgvY7fScF/syzo+Vmf WT/A7EcYn4wv9jexv1dpeC/Oje/SIO8Zz/Bb42Wwf2G+6vuJvA9HfTjfkz/8 b+PyD/sV9MfYueN3tBP/6vjd+E1BfwymfPgZv8OyKcjrD2vzHRPkMuON+cT3 8Jnv6YdYfuGfvz6sT/AH7L5fE/YbcXyVVJAD2MP03Vb2h/Qv+7/4XfdciSeS G/bD8f21ZD9N/5CfvmMTv9OSW6e/9F0XjacR7z/1HFssuCDsLxx/14T9Bftn 5iv+6+j3wfQ35xy+j+175L8p7HfZb6lcY71m/DI+wIwPfbeA/SPp0beAofM9 53HqyXijHX6chvGEPoX1EEz9Hb/mhPb1qP37vIDj+IbJ9+rfTX3Ij/qQHxg5 yDmTecX+AEz9aQ90/MFpD5j2uPVkTpB3nV35AZOe+oOpP99TX74HI7+Qz4wP zvuc/5DXzHfawXhgHaN/wZyXaF/8PkmpvEeavJuFfi+Ot1sk8XaLxJ+6IOgF 9Z1BtTOovyffx++lFoT68B3t0ndMwMwfjavHPGZdJ73GmVO9PHT1b1R/Rc6p rHdg5Bn50F/wlb/DV30njP4DM77gu+rl2Q+j76Yd6Mvj+LtFEn+3qI6dA/7x PeVBhx/QY3tzkcTnLZL4A0Vyv6RQ/IES/6NYv78q7K9Std9PquPfwnmJ9GD2 l5w/OBcwv9y8LgmY+Ym84l1Y6K4e5QGjJ2d+sb/WuIga95B5M8m1J8wv2k8+ nIs1Hhh81zho8XdlMj6S/Sb7EzDrG5j1bbbbP9XxM4jfn6kM+bGvi9+fKQl0 ziXxfZgtYb+Efi9+X6Y80BnP6BcYz2DiRcTr15Kgn4j9P0ot6zn737GOv3Xi cDKOGX/wH/6A4/vbiX6O/ohxKsxHMPVlvQKjb+G8z/rH+GY9ubD2d1bY/3Fe ZD0Ax/FaVoT1zeW/PGDmM/yFD2DuV8BvMPyO7RFJ/BLqyzxjfnKe0PvusX5+ ZVgvwYxf2s/+i/ayXoPjexwrwvpM+8Hxe/WpIM/AtDfeXywJ+jjuz5Gf37dh //P33tBXJnGksW9pHGr0pezX4Rf9Cw7nXte+sB9z8m15wNc5flkdL8xz5H9s fyI+S4KRA5QPv8FxvJ8VNt4PLQ+Y+tB/6IuQX+jrdPxxvmF+cD5mfYnjg62T +2rrA4au+aOfgk594ngxyfyk/2P7dUJn/KDvorz4fZfkPXa+j/2bE7rmB473 m2VBP8Y5KR5PNQGzz0G+wF/2O/E9jVV17o+BOe/FepEt4X6S63fuNyUYuzby g/FF/ZEH7DcXu3Uw6APoTyffl/r6J/HY4nhl68N4A8fnw+R+Z2zvI77ZUu+P kw5yGfmE3oj6xv7vFaF9yK+4/yvrxGlg38V+iPsA8Ct+V7Ms0NFfsN9DX8T6 xXwB098xvUjsNMl7IMgf9vFg6LH/ZoLZ/4R4YR5TDvrIOF795oCRl5QHJr/4 /mZVnTjcYI0LonGoocf6g/JwbgGzvtM/fKfxREnPeIjjyBWE8RH77VeEc1Ps F1BgVX8Lne/BrD+K4/iANUEex/bTVNgvsX6zv2R/Guvjk/iGGr81fg9xnWX+ s94iP9z57O9gP0Du0N/x+lMdzpu0j/0B85JzHPtL9A/wl36P9T/JPTLSM/7i 9weS+xLxO+irw36Ocx37ZM7F6Mfj83F5mH+ME8YreryUmy+Bv2D4S32R5259 3xj2X3G8vlRYv3W8Ik/4HnnC92DOI/Avjhsd/H/C/o3zLfsb5B3zl3ig7E+Q l2DGG/IZfjI+YvtsvSzqy/hAn4A8hH+xf35O9v8+DyWY/iY/0pNf2C94TPo2 7vuwXwEz3+AH9UM+kh5Mer6nPDDlkV+I1+6/Jz04tsetD+Mx3l+Vh/GLPAcj z1g/6f/4feuKMP8ZD6Tn+/i9jvKQ3tW3PPBb75Eyz9C3MH+QL9xfZn4iXyiP 8Ud+8D/Wfyb2GjD6JNLH+sWKcK6M75kVBPuGxl3ie9rP92DS05+kh7+kB9Of yHv2c+wH4/NDhdW4XbSf8uP3UcrD/on1lvME4xX5DUZ+o0+h37BL8D31j98r rwjtRz7TfsYr7Y/fV1oXzovsT/W+eHyPJIlDxnzXOBLIL+Qo5zbWA8YD9gb2 T+xPWL8oj3ozf+M4rYn+G/uKvq+GPDjNyc868Z2xf7N+g+PzQZncry8T+2RZ 0Eez/sfxG5N49Hq/CAz/kT9g5A/yn/WT8Ul/st6DWe+RT7G9vDyMv/i9mpUm tk+vEPm1MmDyA5NfvJ9baZBP6CORJ8gb1i8w51PuB4A5X7n1LB30+eA4vn06 nMfi82FdzPynfNZPMPlhf6M+nMcpP44PnGDay3mU9oLj8/iqII+gqz8d9aH8 +Dy9KmD2T4x/3g9jXsbjO8HMn/h+TGmwvzAf6H/GNxh9bxw/LLFXxvEB6uXE /vk1YXyxX4rH36agJ2N+L3bfBX09GHse8mFsLR4b2oc8Z/+DvY30yFPXn9XB Hkb53V1+Yb7G79lVBH0KmP0C+qLYHppg5gvygXYhX9AfIE/QuyDPWW/Y3yCv 2c8E/xdff+Yt8pV+BGs8P/qP8z/yIz4XlofzEfdZ4vuZqWA/ju83rQv6QeQP 60X8fkvKch5Cnsf3fyqCfo39FO2kv9F30t/x/YKqIE/pf/Kj/9lHMZ7YjzOf 4vvoKRvbcyqDvoP9VhxfWfVrabn/lviTsn7H+8FEP6b3BeP7GWuCvsW1K23j 83BybxI+x/diasJ8Asf3m2tsrA+fG/JlfoHRVyM/mcfwC8z4oR6xfWBu0P/F +7VU0KfG+ug1oXz4QX1jf4NUOI+yP0Sesl4yfpjv8X2UinCeUqznmXA/ymP6 K37/pUL0dYm8oN0axxT+Y79iXwWGf3F88rlW9+/0B5j6IQ9oH/I/9metl8N8 0nccGT9gykfexP1bFuRULH9XBsz+g/lEeuqLHIXfcVzT5DzO/g7M/przFvxi f6n6A8YL8oPxwn4lvl+1xvxvfX9a7vOmRd4n+kPaiXwH0z+x/mZJkM/II84f sX6hMuwnsUPSPvoHHN6R8+0lffyOWGWQD/AL/rIfYr1FHsT3nRN5hr6P/RLr B5j9FPwlPzDzn/Kxy4KZP4xX5D+Y8cz8jPfjeaH/4/NgRVhf4B/84j4d9aM9 tBeMnN008rJZQ16psbsN6lLvudGpIH9PWnfrY51/rgzzruzeT0q3/gsYu/s5 l8xt0fCqGtvtwZ1Oe+bvxB95y+fLzpv/fHifMwf7wup/7r20vG+NHXDb/A6D 7k38k2nP0AP2u+bMJ5LzIt/X26n2nHcemPk62Kffb/pZTaaftSrsC7kfkevL O/K1YeOueT8/0NHvn+Hr33u/U3ZpmV8U6Huc3/ayJ19P/JUn7jfkib0mJvtO 1pF1nn+DVl/R6cAJiV+i/81y46HGFu79VI9TP0+F/XDDRp3ym/6nLOB2Q26e +9nSooB3bPj9Wz8/nvg/V+7w5ZA1b+LXV2ovLpv354KJlQG/Nv3t4V2WpsI9 opW75ixquiGJk3fEUwd2OOOYLQFP7dX1nRbnbAwYfj9935jJ60aV2jnTth9c 8OT6cL9ivwWbdx0/tTDgZ29rbSpnlwZcNnvcqhM3J+8UdtjzuSN3aVcTcOqv HZ7f+53Er3LQ0s1HHPpMOmDa8faaD066+LQiO+KMAwePeass0MmnoM2gixpc VmgvHXuJ+WtyUaCfcteW7sMPzg+44alfXtnl+dyAWdda/7743NQnSRzwNh4H v1mf/6E1DXbp0LYw2MW4hzDY1+/VqS8dfkDP0kB/YuWIGVOHVQY8+u2/9n6/ cRI3pWfpgkMOWZXgQ376z/KrjkiHcU/715z/zen1B6+3F557yZ35R5YF+vP3 NLt54Htz6viP73Rqs7ZlE/Ls1d3GLnqy/Ypwzt5/pza3TRmZF3DZ63+uaXFa 4sdLeyp9ea1ff+2g77cvDfQTf1/0yu5npUxcXr2s3Xx5D/7nts7XDqwJdOZJ 2eQ+lzacsdw+3fH1Id0vTAe+X/TR7H1+vKIsYPrz1fPWDjhv7Qr7e+uzP8zu UBTo8OmXB/b4z7UFybsBXWcc9eySM1bYQ+Y+8WP7xnX93Xt5+tuN6lfkNVkZ 9jPIg/k+v39dfHx+0WEbAp3+H+zr88K8AYfdeExpoDPf9/nBte/OL8f1uP+u ykD/uvXps7q1T/aNA6b8uu+U/+M/f+dhsw6/7POagOHX59M/erLr63/Z36be eeVt45N3SLy8CdjLp4Dhz/JrzmxZ1nqmPcLJt0CHX40O3bn9ox1n2SZOPta5 X3e6p8OfA691+Xn5HeycXv4HDD8G/OHqf7JbLwL9pE/Kinq1qAm4tx8PzLuL /XgA/+H7H3yC71/w+74/wU19/4Ff9P0Fvsv3D3is7x8w/QOmf8DN/PyETxf7 +Qhm/Fbvfdi0K8fOCf06p0fuo+POn28+9POV9OS70tPb+fkKvamfr2DG49mN Xf7lfv5Cv87PV3ALP1/B3fz8DO8sevlLP3/s5S+YdWtXN7/DujLpuyZfv1Sc a0Z5eUz6y738BZ/p5S94Ly9/wWEennd3xU1fJ/xY7PHhXt6SHvk025ffz8tb 6E95eQtG3oJ7eXkLDnFH3i7POrp9vunn10v4nOvXSzD9+3Cf5i+ZUzaaI/36 CZ35d9ypPxwz5qF885tfT+P4Civtvx68IvXV6PzQD4d7TL3O8N8v9OttfC+h yPTx5R/g11/+/rxff+N7Cikz3bevwq/H0O/y6zGY/Qh8Zj8Cvt7vR8A7+/1I HN8hJ/vI/P8c9eDsIpPy+xPol/r9CXhXv78M8e38fjHIEb8fBLP/Avv9VViH GK9+fxXG66cd23Zq8VTaxPKzXtYzkfysl9U8kpf1sg6I5CP552Sf/VH3EW9/ vXVfV7v/rGY/mhXLx3pZtPNtX355JC/rZcXysV7WE3fuvct536YsvxU9J3R8 OHeA/eGN9OhLtq4DS95sfVHFR1v5+Ub5tceNSdkV7524/eUjUnbytYOWVe9d Zke+ldf9+l+K7O//PPnuxzeV2Q+nNvjX6Avz7T49Rra/+9Iym7f8sGuGvlhq nq1885CzTyqzWYdfM2jszylb/sYxbZsNLrJfnNuy5P1hZbZv0biZrffaYstu uPvEdquKwm/hh2f/c8WAfNt0vxaNN23tp5pl+zz+6XmD7YA5ByxtOL3Itj/5 urWrZpSaog5z7vyifZF946HJi1eNrzRL7q0YUFpvix2wZ9d+Y15N2cvv6WYG f7rBdn3+n8vuPjttd2xz9Tf77LDRZk/494U33F5m117ev6Dvw/m2eZdnXz34 nSJb/7zlMz7bKd+23y2nT9X8DeH3vgOenTZuzdZ9y5iRe7bcNd92S204bKeH 5tkrD7OHj66/0aYWjLj7rONKTZuVC5849M98+/VOpx45dEGNeWrUTq93/2GD /ad78SnDK1P2vUHtL6y5K9f+1PmB7c5sXGbHNHngmG+/W2lbvdwgO29Fmf3+ pvcHHdx+lX3dPr5d1fFbbL+bP+8+r9Eqe+zG3Tr+cMFGu/zmdQccf+DWcVI5 ++qvfpttr9hzj2739V1pV1381EF/jp9p1jdpMeOvvXPtG6ef8FqbduvNkhF9 V7x81yr74/T0vD8PLTKnzF+xy8x3V9pP8s8oaN4sZXb+fsI9LVettH1etFn7 /7vGDNzv90bF3XPt5zMab/zx0LRd1HvFwnYHzLO/buo67+0zyuzioz/cber4 Ofa+HzpcsOiWIrvl1VEXlb0521a89FneB2fNDb9D8869oNWfW8/x73U8Z9EF c+wpTVaedWBpnsm9t8OC286aYzu+eurq30pLzLIv1i0ct3ieffHI8+qfcV3K 5HbeM3XUpNl20fCsmeMH1ZgzBrS87ur5c+xBn2w/c9O4lP2o0cTmVf0G2A65 636f+k2ZPWf8l322O26M7Z51feXja4vsnk8+V3/G78Ps1IOfnzK9X7595+m7 77ym/lDbp/5Nn1zedJVN/Vk1M+uiL+wTA3ZfctXThebvu7r/Unrzp3bAD4sa z9863m8ZuOCZWdP725qx1x/9XU6lafdEvY7zPxlhfzrw+X9/fFyN+WvUk6+f 8tpndkvRof981TFtb7qnYN9eK/8wna7odtQvd5TZheNL/vrhzJnmj8KNvVbe XWTHbB6/5fjZs8zD52x3wwXNV5p2rSf968b6s03WuXvtsvtpG8wtJ7yxeea8 WabRZ5fc8PSJhWavHg9etd/k6abZTTfttvjiUtN9eJ+Z4+b9ZYYet/uWq56v NHdt7reiouUMM2T3Vls63pQyX/WeWLiwbJZZOfO7c+qlq82JM2+sbNX9D1O4 59V7Pj++xrTu9NRfpx0yy2y4ZVbXpvekbbe/+9x7Q7vl5uSpnR7a/coyO6jH GU1X37vCrH50RI9Ovya/bQ5s+vFrm/NMw5fL21X+vsJ8eX/h9vecWWimf/P+ Y2OaLzfrntq7fs9ziswFCxZ3nX7cSnPMhldeOPfcUtPrkNEtcnZeYV67esN5 b71QaUquu+T6ZT2Xmxmp3ucvvThlHvvygfYPl6ww279xZqPhNdXm3Uu+G3v/ 5ctNj9azvxkyqsb0mrox1eW9FeaErm2e3G+r3Dmj5fD3S4ryTN+GJ9/x3Blb 7Mb8jy6sGLjeTHit+KbFL2209VasuXVg2/Xmgaxla59v9Z5dkH3iN3eNyTOL nyn5+Ksuf5hfn99xYqOO680+P93wyM7Nlpvbrn9y8geXrDf3HXXQeVcPSn5/ umJdl68+LTTn1f/8xT9PzDMn3HTisjt+LTG/9Gt8/IeXrTfLFnRbXvl2qTn+ 1fdOnLUyz9z496MXrF1YaeZX9R6y3yV5ZtZxp5QvaVVjHt9j9vRuDfLM9/t8 3X9YXo1ptfKv8qqLNpjdWj93cUnjtO3w6qnHrhlaaM44bG5Bh0dmmlTuhk+3 zCk0X23fd78uxcvNkCbr5079uNBM/XnCdQdflmdeGvPA1QvHF5or633ecfei 5LfbbUU/7LV1/3VVkw4f/PpQoTnixGPevXfeVnm/+p3uzS4uMoN2PuPWtjdu Hb+P7tV4yqmFplHT6f2q90iZX18Zecn9eYXmp8JzF9z1eI1pt+8L9770U6HZ Jf/2C+79PmVfPCuv7aSt695zDeqfevG6Mrt+wfhz3vuzxIx66IOj2jXZYoc0 e+XQCxqVmu8ff/igoyf1s1NeHHp32dZ15vo+5SeVDU5+Lzj9xW9mz680B+Zv eb3vJaVm7bUrv84fnLIzmlZs3+eclBn28Jz+J+YU2d+65C79vLTSVHz099NP npRvr7r424btdkuZ92rOP+n9p0tN9uUz261slDKL+5UN/df7KVv/mEfP+nBu jZn/4MD0n1vXnRXVl0/8uE+NWX5o3/NLBm3dL2yX067F1n30nK79y/KKNtgX h20u7Dy5xjTY+4gv/y5baa/ou3fR8NE1psW7Ox8ystdPYT199cFp/770pip7 3eWjuj7UpNp2+vSlwpPKq2zP3desf6FHlT1v2Rll86+osk/2H27fGVBhHzz6 2IdGHl1tW1369aW/jC23PStuOqvjp+U265E+T+9ySrXdfRc7+6BbK+yYjget at27ys54ZF3R7/0qwu/x3zX767o3Kuw99x/90+zvym3lkJ9bnrdvsf3g2eev XLf1+/IuTVrtlVtsB2Wfdnnju6vshH7Xjlt6y2b7dpM9m+TvXG2H97zw2G9P 3Wwr5jX4ZsIrFbbPZdM+H73PWvvKg1OKJr9fZa899LGFr5UtsrOfeWRT563t aemwmeXxWJefeTPOz5T4/D6bUv5s1TmbzaFbBu+y14/lttzVz7zn6/eoa6+5 wLfXt8vM8u17xfHTtPb89PwzvTz/9p7VdErplVWm8KVXB33xfbn94dDrttz2 QoFdeV/ufqP2K7Gtbtnn7HGrV9vb2/ToeOTuJba9w6atx/OHVC3N/mSNOavj sO+6PVJsJ7vvzWr//S/39l333tIq23tBp092nFhsu7707eerS6ts848GrL6g TbGd5ujmGU8/InfYQyuOqzJLW/c++tqdiu3aeyc2/3jAj/bFm44csWXAYvtO m1PnX2en2PWf9Dx78NjFtovDpsDjv1x684pPb08d1vv1t3+0d/1wYJv8Nxeb SSN37Nz2qynm25I9uh8ycbHp5uvTzNXHNHfl20WufPOrr/+Trn7Gev4sc+0z vn/sga5/zD+OH/Y0xw9zds27r+b8sda+dMW0pevGlJu/Pb/O8PQ7PD+vdPw0 57j05lmfnv5v6vNnfBS68WHg12JfX98ec7BvD/OjpZsfxve3zXP9bTr6+fWY m1/mOD8fOrv5YP7w4+hXP66YT5+6+WTK/Pz40M0P83Q8/k1WPN7N445uXvb0 r/34H+jGvyl1+Zn3fH6M93fdeDd+vpoOvn67uvqYkb4+zIfz3Xwwe/nxne/b 6/lhLvX8ONfPh0fdfDB3OX6YRz0/+vr5c62bP2bthgf/vO6Z4HeStc7hoN/m /nKWOy/Y3/4seeP2aYuDngf79l1vj3/p6MtSwf/nZo/b/rb5/D1nbg7nVO4b n+bz+/PzT9+sf2xxoN/Y87Gnir5P4jcNGdnhgBceTvT61Ofk22/NGT2s1E5Z f1K9wQ2XBD0j9el1w3t9zmleFurTx+P6T7915Y3LNodzFfUxPj/OR7n3LP65 93FJ/KVTHN387svjXER5PV3+wf/nGY8b+PJIT3lZPj/yP8+fx3I8fzkfCn+N 8NfAX42ndLLPD/5Cv8HzFzzY8xe8/1mnn/PuDRvCPX7O+6tfe230gDFV9ozB mw7c5a6Vgc75f6Wnn+7o4X7+hh/+rrj5hg0Br7l7bd83N64M9p+1Dgf78TpP x57rcbjvh35iv9Wfzjzupyqz2uUf7rcf5+snONjD0E808d+v9PWDvm7vWzo9 MLravvjrLQ0f3KPGftJ96Y+77Lja3nva/dffc2Pazjl6z/Q57aebVQc+Pfis t9P2iNN7dOsyaropOOvUM3u/n7YjWjx45IPzl5lzJpd+8MWgtPX5GfL7yOfX xeVnht3YYeOAgoV23vpRzy/+qcJc5PMrdPmZa+7es6rsqfWm6bJBrd7pnDZr ff1ecPmBDbjRQU0fmzWo2vzxQetOq2embafSsrzDDllkjztsp6s3vlFuR24Z MGLjbwsDf9u6/O2hLn97hyvfFvv2YC/997EdLx//V8p+6OpvfP3tdf77Zr5+ T8Xfm/d9+s6+vWNdfvZBn99js65Zff6EDaH/qxvN+uvbV9aF+c59tOMXfbVm 7X/f8/bfd3Xfm57+e9ozxLeP/Hx7Q/6feUz6R933Ib2vT3Jfxrf/fl/e+Q2v fPz2NWuD/b/7Y//sN/TqdJgP37127mfNuiZxq3dqMXmH5h1TAb//zGsvNvw1 +KXkUG6LHqc8/tEONfag8Y3ObnNjWUj/UM8BPUadVRrwqy9UjLzp3OLwPfEr 5vzU85jr1lQH+8N11+b279Opyrbfa8vLc7urX05B+J77nW98td0lS9rWBPk5 4pqW/xm3vMYu/LXfkq3/gh4V+QN9Rpe8PvOmrgt07o/08/n58gId+YT9EL1d q7i+QV50uOHmm7Z/tCR8j1/DX7693Rx/Qvp/Of4FvOqvd/dtML0ifE+/HuX5 /a3rLyP9FfDDrn8Dfmb35llHXFsdxuekEa9+8ut11WH96flU49MPfCcd1peb by/eJ/VoVcDBTtiq8sRV/2yxr3zXq+FBg7GPFwd5u+/Fg5p8WL/YnnL15uZX XbUi0J/a8vYXHzw6J+BnHA5xTJDHB/rvG+/94DGPtEviQSH/hvvyX3XlBzrt Yb3q7+sH3w9w+QWM/vvdc798rsVfxeYNXz/o6MM/9PQ3fX2hn+naF/Drvj7g Jzw/qc8tnp/g3r4/4ni8KXvCsfPu7/lHlWF+It/H+/kJZn7G72SU2t0ffXHy btOrzYF+PkLv6ucj2I8v8SursCe48WXa+vlH+jvdeA7p4fs8N57NdDefAl3m Z+D3hTUV2X8ctHW9cvMzpJf5G/hvfHqZv0bmq2nn5x/1lfka+L6D54/nR0h/ gJ9/4FecvAr7S5m/od+O9v3l+yd8v4Ofj+CH/HwEe3ka8pf5bVbt8sg7j21M W37b3XfR0l/2TtvSo1be9/teVXbTQytu6D41bW9tdnHhIXekbe+P1l4/p7LM jhrz2Z893k3by864/rMlrbbYSb99dv3h49P299H9lxe9sNH2uuvIf0/+LG1H ZXW6787BBWbqB20aPL7vVnldMeHJW34oMcd1GXjqb1vXz0N/f/HR3fatNG8O a5d159ZyTjrv3D16bKgw0zo8P/j909J2fsVdT/U4c5357dRDPnio79Zx1n9u z2POr7CXX3pRu+WfFds+Ky76uEfDSnvbe1/1Ov6xErt+dfGei6+tsC+VTLmt Xpdi+8b4to/c+2Py+9qS3Bs//aok/B7eduCVZkuxPcYMrGpzckhn3vLpX3Xp zOs+/aPTm7y7y9wt5nH3S33MVXF9zJ2+PuMf//Lsn7uVm7dPPmifJ5ZusT9U H3Vbx1OrbZvDH9r80pMFtu8zi7KvWVhtm4447NqHDy20WZf+uuTGzlX2pHc2 vfHsdQX2ujf7fbjLqGp7/htthg85ZJM9eOkLF7f8uMLOv/LOynG9CmzznWYe 3qJ/uT3q1XbNO75TYIcMHJD9UotK276m+QH75G20l85v9u3oFiX20H79B97x UYE94KWdJ3bbuMXu+WPf+xYOL7Df/fNnr7mp5LfYjWe7i18HX79p71V241qb 3+PDfY/pW2DXHj987yfyF9vnPpqx+9eHFNiaY87foXTrfuLcw187vWB0gd2z 0XZza26cao+ZOqBFw/M229eG7rzfhIdzzEvLWtw5/JXNdoZLby726Ze5/MwL Pr8qP58a+PInuHqZib5+lXe99eCOpRvNdh1rf+1Brj1mZ9+eS1x7zRG+va/d dO5zeY9vMQubtZl80ayNdtrARlePv6HYXPVmuvXCrfU52vHPNPP8a+r4axZ5 /ua/vn6fpYeVm2tTfd9/N73R5jXM6n7yynJz9eYz2lzwxGb6y5zg+8v3r2kb 96852Pfv3A8XP/3dqrSZ/8wVh028ZZPt8NygWc/323pevXb6L22+2Gy/u3LO +TkNqu011zS54cwea+01x589vd2n1fbxPZc/1CFnnX1t2A03NNixyj79z/u5 Tc9fZ+++/LzWiy6pttPfnFn4kF1th48aeHeXeyrsA+99W7hfx7V20tdZzT48 vNJ++Hnjzr0XrbP7nfDchoaNy22zsw7u/nT1OnvfTnOOvvvrCtvruafLpk5Z bU8ZOe+QlYXFdvZRd33xyQdbz/UzSudu37vEFnXau31p/dV2+s1F+347rsBe fXjOqsUXrbP5z49vvui8teH30k+333HkjePNj983bHt28Sq7zv3dFHj6hiEr Bo0Ys8pscb/2d5efuc7n1zYvq7JRx81mrxsP+vrpC9bYk1x9zAJfn2VVv6TT jYvN6Qtadpm3dLU9wLXHNPbtGebabx7x7Z/o2m+G+vbvP6Xp56+MKje3TZ/x 5O0rVtt+jp/mMc9Pz39zXcx/86Tn/9jrv62X/iJtLr9ryZIvf1tlG158/Zie N1eZkvP2P2X0YWvsiNH9O9vW1TZnwx8TW877x35484EFuW9U2RYTl816a4cl 9ra/Dh41eXC1PXLtjJITpi2wV75efODLduu57rMvDuu/6B+7+vyvDsn6q9z2 3Nn0qflxif356+nzRx9WadNnzRp+a48FdshtLUf9fFOJ/XPnC9YMf3WpvXOX jj9vuqzYVnx97K3N3l1ijxubc/0dzQrsi727nXLa5sW25YsdusxsWWDnfrTh /B5t/rbnf3vBm2d2XmfXX3HaW636LLW3dn3zyL0WLQm/7dyv6eTxOS692eLT 96/f9LD+L642Hywt+Lrsp4X2GFeeGeDLe+am/7Q6a/lGk3fvH92OOnGB7ejq Z1b4+g129TeLff0fzm8+x3TdYppfkv32gBXz7R4TVrzZ/v5iM+C+Me/lz/vb rnX8MB08Pzy/TKnn1zfNRjYb8a9y80HBw2dv12qB3bjjuakpReXm6b6/DOsx 8m/4b5p7/vv+MVN9/5zz1M1nvp2bNgddkK7/cbOFdof/dG805OMq03KH2+6e sdti275L5eazzqq2K5/rPLxRu2m239BNDd7pUGW/2PDK8mtTP9vKH59o9M1V W8/DMy8u/+G0SbZqSv2ZZw+rsGcOPeW3DhdMsycMnHrwAx+V25ebX7j66men 2dsf/LvX/pO2nuNeOu2ANcdMshdeXrnuAVNiezXtO77V2F/spN71iq7bsdiW d11w5NLR0+xBn590anaXErvigM/P2f/cb23rccuKb31ns334ht9/+GrzT/bv ffu+OmqPdfbQ32pW7brvL3bClryCr95eZ+88YN92LXIm2OPeqj765fl/273v O6qsz2M/2XMdNnPudfiOvge1POz4xWbibyO7pKZOsQtdfuZcn18bV55p5cs7 cuimpy4auxV/0eCVE/eeYrNdfc0cX98s1x7ztm/P/BUFHXsfXmyem/vEgV+M mGxPdPwwd3p+pB2/THvPr+P//eEHY78pN4MW1Jx7zVuT4bf50PPb94fZ4Ptj 1ug5Xae/lzaDDrmj5RVfj7X7PTOux/kPVJmqN28dfm+5Df1zvusfM9ult+e6 9GZ/l96OdukN/T3V5W/u8P01zvWX8fWzR7r6Gfr7IFd/09T31weuv8wC1367 h2u/ob9vc/wxRzl+2kaOn+Zb338HuP4zi33/7uT6w9zt+su+7PrLdPL9N9zj y3z/fuD613zv8jN/7O/y8+WZE3x5bX3/Nnf9a+ivK3x9fXtMO9+eyb6/v3D9 DT/M3Z4fHRy/zD2eXy18f5/n+tvQX51i/pupnv++v8xRvr/o/8dc/xvk5z5O fppz3fy1O7j5a3Z089ee6uavGenl8Tduvhvk6QYnT814Jz/sM05+mE1OfthO Tn6Yq7x8XuLkjXnEySu7m5NXZk8nr2wvJ6/MUC+ff3LyzVzu5e8kJ3/NC04+ 2jlOPprjvbx+3MlP85aTr/ZFJ1+N8fJ6mZO/QS4jpwd4eTzAp3/Wy99lPv9W rnwzzJfv62/2j+tvXvD17+zl9W9OXsMf0y/mj+nu+TPN8dPM9vxc5+X1FU5e G+TrHr5/kK9n+/653fWn2dP350deXjdy8tp08fubHLe/Md+49dde4NZfs6tb f22+W3/N937/dLlbvw37p+5u/TYP+P3O/W6/Yw50+wF7ndsPmBF+/9TF7R9M tt8/ve32D6a/3w+tdPshs9LtR+wxbj9iTvX7pz/cfsXc5PYzdie3nzEz/P7p crffMUV+H5Tn90Wb/T5prd83Pen3U1Pcfsp0fm7vd4Y3+Nuk5pzwVqcj15jN fOd/2/v9026+vBV+v3SSr98AV38zz9f/AL8futG3v5vjj7nd8+dffn+1k9tf mXF+/3OR5/8ufv+z2fP/HtdfZpLvr9f9/urfbn9l2vrzzCnuPGPmu/2wneH2 w+ZOtx+2K91+2Fh/XrrW7afNK/68dKDbT5th/rzTyp13zCa3X7eXuv262ej2 6/ZCt183h/jz0xy3vzevu/OB/dOdD8xv7nxgL3TnA9PSn58OducJU8+fO8o5 h/hzSsqfW77355Tx/txS4M9Lfdz5xuTu6c5Hx7vzkZnizkf2eXc+MiP9eekF jye49KaFTz/In5+ucucnM33T7K7Tn1ht9ulT9t1tgzeZKl8vfnf0+sV8X79+ /jw0x7f3F38eusy39xB/nqrvzlNmoz//tPL8zPfnn8s9P0c6/pvzPP+P8+ep A9x5yszz552Zcf+aNb5/27nxYE704+Eif5462p2nzAZ/nu/jzvPmW3eetq+7 87R50OsDWrrzt3nW6wNududv09yf7w9353vTy5/be/hz/AB/zu/nz/39/Dm/ rz/3fzvynm97dd5od5/y+sBj+5eY3k8N/PP+olX23ZIJF21cU2LG9PjpsN07 /76Vf0POmPZ2ifmmf4Pv1z39l3mw2fanjD+txBTW37dpzjPLzPpb0o/s+m6J uev2649rvXS9ubXHx0+mt+6Dj3L1M019/SZ4fcFA376Nrv3mCd/+ot4dd+o4 oNqM2njBDzPvLzGXts/esqxrtVlSNO+kew8rNT1vPmJKA5u2HW+94sBxX1ab MW3af7J/WZntkHNy+xdnV5vOk5uNrs5fZd87tUnJ3lvpO26p6ZK99Fs7s94z Zzd5tto89M/t5ZN7jrLtZ/e6bUj3ajOi7/FbhrWabva6fM5Nuy6oNstvG9nk 0uemmzk3frN50tZz7dz/zL/v9cJlxk5pvqThsmrz9REbR66aVGK6HTHiqU7z q03Or6Obtd+6H1i717mXfnJ1tWn4af5l03K2jpf1Z9b/o2O1+XP0kOEFzSrN Y+ufHT6kQY059p/3m/xxTNqOXTRnWt7FyTsl9d66dMMeb1fZmS69fdylt7u6 /Kxx+dl99hg/YkFVmR12x5F7vfNPtf0sbr898ePT3jlrQaV95a+RzU7fPm1P cPoma72+adTUiR3vn1diN9+w7PPqimo71rXHPuLaY//9VrtbHm+3xR7zRvEZ nxVX2x+63bdjq4kldv64pa/+3T9tH3D6LXu41299eV7nu3d/d6M94PznJ7bb UG1zW/S+4NiRhbbfmDNbfN0obT/pPHJy+S9r7eDRuXssm11hh3Vbc+i++y63 O47885eea6rtCsdfO8Xx1+btP3Pg9UVzbf5FS+2462tsvdtr+8POdf1hW8X9 Z3OW1GIDXhv3n/3H5WfIb6Ar32zny18Q96998Kr9j/779Vwzqv5PfX59usx+ 5tpn9vPtO3BFh+HVB2+VP1eutTe3TNtfnD7QPOr1gfc6/pmjPP/GOn6bas9v xs9Dnt8b33h43ZVNt5izD3/v5KUXpm1Lp28033l9YxPX32aw7+9xrr/NA76/ d4nHm/0rHm/2+j3nd9pQUmaeuvGevqe9nLZPO/2mGe71m0e78Wi+9uOxrdOP mmKvH93o9KPmZq8fderjalPRcHPFv9+pslfN23fJp/U22meXvnhG8V6ldryX J3s5eWKPnnfGb6X3rrf/pO0X/RaV2BucfLD3Ovlgn/Ty5n0nb2yH12vli+3g 5Itt6LDp4vHjLr0Z5NM3d/mbZT7/2738ucvnf62rn3nK12+sq59p7Ot3sZMv NtfJF3uJlzcrPPbyx/7j5c8xvj1/u/LMrb49Hb286+rGjx3sxo/Z1bfH19/4 9hrfXtKb4T79Aq8Pnub0waadr/+jrv7G89c08vLa95f1/WXQZ9/k+suc4OXB y04emOO9PJjk5IFp48aHfdiND+PHhx3hxodB/lzg5RnyqZeXZ8iHOU4+GORD MycfzHo3vu2Jbnwb9Ol+fJthXh7luflhkEcPe/m60suTV508Mbu4+Wc3ufln /Pyzj7n5Z0Z7+bKzm99mmZcvOV5+V9wWyROzMJYPprGf36U+/6l+fvfw+a9w 9TEv+/p8GssHs8HP59N8ey/183mCb2+245eZ5fn1oLcXNPf8uieWH6atn789 ff885efvUN8/vn/N875/T/T2hSm+fxvH8sN86eVHF79eMr9v8OOljZ//RX48 IR++cvLBbN9707zG45N3P1i/at6sXb9CvK3DPv210fBBSby2Zh7zHenx2z7k lE1jJmyoMQ1c/iEdfs+HObr19LBuYpd9dvm1T08ckrb1ftvt2SvHVoX4ONjj Jp/6+OoRm9LW/qdDh0u2rwh07G+3HNF82kFfp+0+nYal936hONAbvPXEQ9fc XBDwr0t79W9w/6Jg/6e9h7r2WWmvne7Sh3hfPr+kXd4e1jYuP9CxZ33l65/j 6h/o8At+YBd7IuZHSN9lu+Mrdt55VbBz3ucxdj342dt9b+An/QQ/J7n6GPgJ HX7e6tpjmnh+hvgcnp/gaZ4/xB+AP9DhTzufX2PPH+jCH+oT6MEPfuFT/Z8Z mjY1vzp+QN/5nBmX39V4QRhHxK96t+Lodb9+WWX3cPTAl/Aegqdjjz154uQJ +zatMevOdvlRbog759IHe2z7H8a/3+7QGrPKpQ/1JP/3fPpDhrxyYpumW8+H 5xxv+r5fY5+bPHDpC52q7Z5dJoz7eFXKtv77nKwOa+bY+g+e8+xr11bZC/Z6 YeCcvEn21lf6n3Ziecr2HLjn9S+8PNF+1/SDtZ8XpuzBLj9zjc/vhBlP3fbP 8oX20GNnnLJpRIW5yudXz+VnNvSK/HfMEYN6H15d8qm96KpHT33/x5TZLS7P zPblTXTlaf3Ns67+ZjdXf9P2mHqFd7b6f8i66rCql6dvd7fY3WK3jnXtwL52 d3d3K9h57e4uzMG6eg3EAlFAUrr7BLz82M8szzkv/5xn2O/W7Mzs7MzsbAp9 qrCncWDXFLIaH2G+VADzlflL/eTF6eMjuV9UV42POqjxcWqh9PGR4KORGh89 AD66qPlS6kyFv9AlFu3R6yMW7dFHy/bIHu3JfNujvRTVns6TVCChv4fJJ1Xn kcmnYBr62+NDQusgHu/ZvdzUZIPOh+o+/85fvTYb2C3sctvUA6nss6bB0lmd U/nbjh+jns4I5vmzM9f9+0FGPjjbRg33VJ6ZwoUHLLp1fmYw2TncXud3P4WL DXTPneuEySp+RstbaZ+k/TVPgx7nep6s41laud+74zM1XsOFlnf26Xw8SMuP 51U3Ld9YP07DzVa3GnnoaZKGJR5jTJ9aT3J9iOVP76ofeFo5Q+5WpIMdZzYz ath7OX9rtCYjjkm/v1vsV6MjJWJ415vz9QpWS9Tfdyhbec7LLAkaDth9cNCd xGRdX+RV6sblLRZ/iNb/b9/gVn//YXEcl7DnpWPDGF3//sdZtUZdjdffyf+D ahsbv8kZwx0iK5f5+6+Md03EPlJF3RfU+fLuT33SybZFNM9t7N7ZPslLfy/x GV9yN1jyd5FYLtc+sGOHbW90uewnBd4U7LR1XYzeTwoCPr6uyfUxUYG0ZNvV 5Uu3RfFb2EdslH1Ex1N1t5yflssSz1EH422v8KfLgV8NTxnWcZvzgjh9b1Tk cRTwoe89Yn2xnrq+s1pvDd950cP7Y0KSbk/kd95Nan0KThowbvC/Jl0e2aVJ p+YXzBoWOVkb9PAW98tlHSS/h8BTAwq0HNA2Rcdd6biwfNnHN5sSzLbqPrf+ Xuj2W9XbmR+FRvBD3LeU8gTkCxF4Yf/1baMuJuv2V+E+ppRHI1+IwDXOuC/b 2ytefy94GbPgWrJdr2CujPub8r1+/xb5CQrjPqf8f9zBPb8/Ng7S7Qn9mf1G H39SIlzvTze7T8i6wC1c01+B/auS7KuHWuUjidL30u/i+yLIPyL9DYd9NkXZ Z2W8ulziiXL6q/4xf10O/Gh4d67CbtN3ROq4XqHP/Jiv6CVBWA/gX9fH+mh4 Wr3fO7cVjNPtCb3OBX5BH/p70I+Gm9s7Jow5m6Try31/Ke84rGgvx7FmXS70 GA16Kr7wXfP+czPyXt9ff/fHmOEmDZdOyF5j4UqDhq86dqw9MygjznrHiXyn Pztl5KkWek068SzG/44fn+p/rfKvmBRdf/6de7ZjX6Zq+Gz7sJ08JSNv57Qd xgVh3RMy8nhuPTQ0pnNGnp0GmRoW+9TJoGGRl5nGBZboU8SP93a8P7Tt5gy5 NiqubHDClzirvJpx7LD3f39+bNc6IXTvjgw6/BF8Y83cx1H6+7m7frfcftNX l8vvY/thNRNe+mh6rPYsJDChboB8r9+pQfsabrv54cMpq/7oe+lCf/+iPYxf fx84Pcu2ch0iMt4NUfjR5ecU/jQckaOC2bAj1irPZxydxHyxnvp7rD9Zrb+G uz/qt/RJ64y8oSL/ygDfEsdWC/PHepPVemfMp8+4sJW5zbo9ocdsJxW9OBZ6 nX2US8Y9jbWRI4bZexs0PL/dzFejs2a8nyV6QoS6/8D2y+/v3NI1Iy5Y5GN9 pxbT6/u583lDs9xDfma8mx3fb4/tkOcZ9zDa9nUZdWNCRp7gl5teTxhVLFaX Gxa6OW+4Ea3hvMMa3NqVHKe/Hxi54VDNrBly62vWadcqdgjW8LaT5h63wqL0 9zWvV6vWo2CghjWe3DKvevTXV/3/oivn9CG/7/xFtafvWQxS/WlY6CnPD1Uf 49XlmI+G6wx4EhV0OULHaYr8mg18AT/6e+Av413u3tvn/vcgVtfHeulyrKeG p3RInBQ7Ikl/j/XS5RXylSm4ulpGXvsUg6PNvmNGrWeczH3m8enNJg1frjCp 1uErGefaoj0rTuswLEPP9LOId3V6MsYintXpSeZ2x4oWbhOm6+9/Pv3m1Rt+ GraMb3V64mkRv+r0BN9rOwLa07DsD81CL47qnzP/U4F3hP0PztvWMt7U6Qnm o+tj/mQ1fw1bxpM6PckfdDxf0HGThiPerg5/u9qs4VTgU/Q0wafAV4BPgReA 32SfbQf+EDg/6F/gLMCn1N8Oepfyg8CvlNcB/Uu50H+Aon/5Xttl0L6Ghd5z K3qneqBnnTcR9Ckw5qfrAx9khQ8NTwW96nw0oE+BH0JeSZzyOsgrga9hv5Q4 953YLy3fITKzQe2XJPJL6l+EvBI4EfJKYE/sj9JeQ+yPAsv+mFnJa3oNeabf /4I8E3g09kvLvNJpsNo/aAjkm3zvCvkm8E/sn1Lfar+kmUof40T4y90gz6Q+ 2tdwJ+yX0p6s9xu0h/Hr7zE/DYdg/5T6wB9Z4VfDkdg/LfNgx9EpzB/rq7/H +mu4B/ZLqS/7ZVngX/ZLL9zXE/kn9YOwP0p92R9zqP1R3xeo0b/KpFrRf6gE 9Dedxxb6m8A20N/0Oz04X8i9Cn3PTemD+tyN/ZzOQH+T+gugvwl8HvqbwDOg vwm8GOcN6U/ORQcnGsZOcwukfdDX5PtaOG/I90J/o5U+rPXYfU2Ob4zOH0iD oL9JfdF7MyN/kn6vM3nvq7Vd086h0Ofk+0/qPMqF4a/fg/jqEBVfrfehxnd/ lS+zIUjvUwXVeUTLgWYo1/nPLPvTdLv4puP9g/t+6nt9su7F0J7OC4X5DYD+ qN9LwW8OdV7ReYTOW+JTf3cQ5xVpV/afAsAP1ous1lPDM3A+kfr63XWsh5yn O4IeQW+6fknolwI/gH4pcEucX6R90BtZ0ZuG5Twj3wt/xIB+hT9qNfhyv+23 KHqH87a+Z4rztsA+sN8IHq3sN4TzlP7+Mc7XAiO/kIYDYc/R98Qs7Tkk+Y/k +zictwV+AHuO1Ley52TkQdzSNGG8bxTVwPlb6neCvUfqW9l7ND+8b2lacDMl iiTfktS3sgfROtiDpD2r8zcN/V+11Vm0XtPgf/9ek6mtwItgL5L6VvYisrIX af75hPGVwXle2pN1f4j518R5XsqjunzvHVA8QPOF0M0TzAf41t9jPTQsv7WB L8kfZbX+Gp4Ke5P0Z2Vv0vzRDPTYCOd5qQ/61PBd2JukPSt7k94/MgP/DXHe l/qFYI/S+cVgjxJY+KUe6FvsmzLuSrBvCiznp9utF3cZdCqedsOeKeUdYc8U WOyxco6Ih71SylvDPivlRWGfFfjB0pWRJRtl4FH+/xz9oz9djvFo+AXsu1Kv Mux7+h4X7Hv6Ph/sv/J9cWV/zshPlv6diavA3+dqad8WmLwBb7f0N3C+jaf/ K7zcqO0U1/baT6s4McPPV+fXuZDjmw0adj/2IOb8XBP3vvKz4emKSfxowIYi kxYk6nIHz30hdQYnaPjjL4dHr+yT9O/yMfOrOqxI5M0n7H/NW5/EWTrd8r+/ P8OuXKZZviW3akZrmLIUj6gYG8vje14oMm1jkpRruYX6Gi7cp8jIFm2j6f3j 8KLnSyWxvRqPLn+oxqvhmXeezndsGE+pNZKTK6e177LkQ7xPz3iadKz4lhz7 E2X++vv8Cl8avq7wpeG1Nl0WtNtjoNh4k0/p7kn8fPbsiLAJJu6wa1fhokdi ucjNhV/eforgepU+OtQzxHLLcal2tYv9YNOdhMx/Hsdyz6Muv683iSYfp9Lz vq5M04Mf1N8ZaU4hQ6bnd1rsiuUlndtwxMAUOuHg7Nc8MIadw2etz+9m4hfN fhYoOS+eKgwIrFU6s4knBuSdf6VaPD0u8GVveScTZz6V4HHTP54wfm0nwfg1 LOst8Otlrdz3zzCx7eDoLnOrGEjWW8plvQUe6lb3av+tSdy8d9k/nzmZaid7 zhq7JJEdy9XIvOl5Msl6y/flsN4C1yz77uF/EbHcmcPuFH6bTCXneY20q+Kn 3/dy6Htxw62FfjyyUrtxc9wMlK2B//mxq/y4y+UDZV/6GaQ9LZeEPgRuOzbZ 7NY0mg4PWuDp1dxAO0AfUo75aXhyjksRZerF0/a+rYtOTJtPm5y1vtn8FU/P klzrBDwyCL7090IfVvjV8NOxG7/l2GGgsYH57DpmM9D0Shsf2PVKYfmF/44/ K/8d262dvv9OGr9NCZtd6dFUA8t6NFbrwQ2G99zW+J+MX7TPU1X73KrUoZgE h0Qelu/WiXqPDVwH6/FUrQdvHdfxSPJJA+d9kSOx9sVEoV+OBP1+VvzA48EP NjXDynxoFc3jHhWaOGq0gUnhk08ofLLz7/d3+vwVzatu/72/0+9E4Ud+A35U 114DdX74s8jX4K7yNXBd+E+rKf+plBPyOXAjVU51UO5f4u9PE96463z5yCeg 4wMwXppkOV46gvHKer5Q6yn4osHAV12FL3oBfAHP1MQS3zQR+D69vXinWvsS 6bz65WVK3tEGyLtZap1pNtZ7oKW/lvuq9aZJlutNzbDeX/OMWruon1nPr1id sOQf9VI0PNn5Xf8Li9LobWOL+qP8E0VeUw/I67U2Q2yKn43mc+OD241qlsB1 Dzl2mGaXpt/ddPf16hDLvZX84d+QPxs/hlWcV+gkZdluV+XifzEcCv1Fzklo jy6hvfKQP1OU/OFHkD/ZlPzh19uCnvwqnsqfDo/53q2xlm+cbCnf+DjkG+pT TtRH+zQd7U91vjHj0RITVW2zvUrNgbH8Qslbagt5m9vJrv+i24fZ48We9l65 PLk4p8PkCfgtxvNWjYeWov8jqn/6jvElqvHRdNUfV1D90UvI99aqP6oHfCYq fJLg85fCJ60D/k8rfNEn8MtSxS9UBPzySvELlQK/jVD0S+3Ab0chv7o02Tdm 6Vc/nnJ1VnKfArEUDH6Q9xGQr4SQr4QqlFse3KKsO007v2LF6H1JJPz1GflS hL9qIH6hk2qfpqH9Bmp+FIX59cJ+5YX5uaj50ALMR/Zj8D9Nw3pVAv5eYb2a A39v1HqQrMc37H+Cf9n/ZH2w3xHojYResmK/m6L4gdsrfqCf0F+6KX4g8JPe X8BPGha5PA18K/LZBfEVWyA/cyn5SSI/Q5X8pDOQAycgF5ZC/9mo5AHVhxyp Dbki8hvyhET+jlbyV2CCPCaRN/IL/YpWo33Id8pqOT6CfKeWkHcDlLwjkXfP sF+LPOkI/Ik86QL8ibwap+SV6AvUCPqCZ+ry5fbDM94JTt8GM+I36FKmAne3 PzDouIZMf12b/XFOtIZHv9lcweWXBxtbLajb9j8j/2zZ5+niU548uaZN2N/Z Tey1adefHFcS9bka/f2/d3cRH8I+mWv9Stpt0t9L/EbEhzd57WYb2anshg23 Fkdrv0xEk92O97tHsbw35q34S+9fKNfvkR3PM+ngGU7RfjyJIwujyiWjysZJ uT43K/NKCkWi/ATqi/4v9UNVOT3H+OQ8EIXxyfuzARif8D/KScrRvj5fSP9R aF/WQ86Fsh4CD0J8zUgVX0OlsD4Ban3oK9Znklof8sT6SH1v4F9gwX+Uwj8V V/E23E/F21ARxN/0BVwa+qDsd7mh//VW+h+/Kvt6xtAYXx67Y9z9ukuT+caN nyfjs/txjtGZ8j4JSeY526Iyn/nsQldnX9xSK8rErfKXiv5ayoc+fau9cG5t M59S86GCrRW9fVLzIcyHC6/fNX3Q+BDK7bfGY2lJM7/ukXf89zYptL5r6T9P Ag1c8PPUmo9aplAzG1OvrB8MUs5rVTnlV+Vsq8qpeIjHnEFRvpx94SzH2kuS qUxircZ/Z/PjXo9/PN8WmkxTMN4rarzUHON1VuOlSRivGfj/gPGOB/4LYLw5 1XipVoDj6hrjMu5J6PeDgzan3IhJ4eKQf4JfkY8Cy3w2Yr4FMJ8mmG8Jtb/w QrW/6HxZNbD/SPkc7D9VHXq2LJY2jl9qHFRTjU/Tpfx/qhofFVPz4bzAPyl8 8Ges3wqFL76G9bVR9KL1o9IK31RQ4ZvLK3xTD4VvrqbGo98dw3oz1ptaoz8X 4H8u+gM9CX3q+Mu8ij6pD84n/yr6pHGKPum6ok9KGZVOn7L/6PpfoO8JLPS2 BvQE/FND0BPGr9e1RunUd+P2SL5yE49U/EtTER8n7wdmHZqvbXhRE7uPPpqv ckGxs5tY1kPoxWo9uMrnjvP+1768f9Ya+reMF/F4hHg8suqPvqM/qY/+tFyU eUzH+oNeNF2IfmOLfGyi38wC/RUC/gdBPtRU+NDzk/fT8mI8rmo8ej5V8b3A Nk1ujwwZG8Sfj+67+rxNIk9Ydt3uo2sgD9kU/OHGyiR+WKT6qJjHgdp+kafx lkabG6TqOACx16RivxnTsOaAwGg/vd+9sr9wsffEeL0/dd+bpXzw02QNNwh7 WjbTrCD6Or7V65lFYnnRwJK+ZbuH0ITYY/vd7kfzKNjvxQ4r9vuiVvFJyMfI UxDvJHZLq3gnHedshHweifGK/Jbx6vfyMF6Bc6v5a7tgK3+n6Y5FYynP9fGe 7oUS6EtQ6Xpz2sTShPzjed/GeAq9NGb2uXfRer9yvDnWnC/tfOGRHFtpcJq+ fLfQ0XIj9kdTt8jxvmemJVDljns75Jti5l3letwILG9krzJFCzoPNXNV/7Co hucNfGnrzFKVaqbwkEV7Ar3ckuX+FB3F/amLqpyknKDvzlD6Lh/HfSt8T/ie B6rv6eeT3IeH2gdpfNSr+MYr230vTmze5+2q/vJuhh+V9TuUN+htGv2hPEGV U/Y583K1qJ5CXtW9/SL26vZpANr/J8f0dnZOgfRoVJh91oPJhPHQIYxH4lu9 VHwrvR61s+LJoVf53eIvd7+mndOWJt5nm79+Um27Isk/7iXyGsA1FUwVYp1u z/oZqvXd4s5FZ5x+FKX1g7N/LlWfGRJNq46VzFL173iyL7T1uLN/jP4NH9Oh NznE6u/lHbPLZyd5jo2Mo1Zulx6+vxij/y90bKvyU/H2WrWmuIQZ9X60Y3fH k01SDBq2ygfmpO8J5Fj/YUi7VK2n5VP5s/hgJps+R/0TdP3rp/aPHmxK1LDN XfPiLByvYav8YU5W+cKcrPKBOcl7g3tiBv2c553CVvm4nGSe+1fMGDCxYCpb 5ffiMqp/LU8xXg3fUOPVsFU+Lv2OrQP6F7qrBnzuVPjT9YFfDS9V+d803pD/ TcPC7yev8uY/pgTJX6ft7Fb55/T+ceZDjUYbd8TwMrRvlV9Ow9L+edU+PUH7 Un75TX+Hcj4JWi9/McX5uFtSooZHlr3/bdDjeA1b5X9sL3o51kfbKQaqfIiU P5NbYqdWsbr+q6sje3i4RWvYKh9ke0+1nvyPWk+sg8732F69pxfOB5v7lAhL TCGr/I7t5b3HXRiPVX7H9lb5GmU8Wi/GeDU8Qs1fw1cUvsgKXxq2yvfY3ip/ Y3vh+6OKn6gw7oPF4z7m61kDP1//N4wbhR+v9THAyLhvzLhvzA6tLj+52DWR +614Wb5A9TjO4vLlbM3fSezx559mO9LoYTHuT8vvooWrch4cnUY3SSNuuC6P 4eq4z1wZ+dSC4yZu79QyjW5cyiaXj4rlCrlv3B85Ip52+0+s2rJoLON+N+F+ N9sP2GZ3bb2BfgZcP0wXYzlu1dPTyzsaqWNh39D8aeUrK3C/ny+T6f0tv39m BMUw7pfzF8t8WhyMfFrNRq/b1uaXke1uuJ6KqxrJM9f9zFyquZl9plS/03Zm GON+O+N+O4ciX0BX5Pe6+HrT+tl2SVzF7tIkU/Fw3oF8Abg/z7g/z12QT2xX 5/uFf+yN5fxO1TIfnhbOuIevfy3pLYrzPn6c3etDBLsbb33/cTKMPyA+oATi 1fEdpSIv266Jjheape2nWdd51a6aJZKPzXZwCnGLovIHtoywLxfO1xZ2+Lbf P57iC35oZVckgiududLy4K0E8px2MvuAq5E8u9bGQ/6F42np4gEvw2eEMfIn EPIn8NSRL6t1ijZQ9d5X9pXKGcnZvSt7HN+QTCP7T8vsUi+M8/c+0XxHWwPN rDve8fqJcO6P+/stkZ/u+Z2I1gfGpNLmyZ6L6z6P4FlTYxaeK5tCvl/8Q3u0 DON3Hb0GzndKoSMbn1z6syackU+COyOfFvJJcAzyae2qlr+oeZ6R++862tXH 5Q9/ybc+yPGViZ2f3zw6tZ6/5PPiIcjn5Rj9oejuZ4n8eGKSqXrxAPZGfg5b 5AtL9Ll/qt6zGI6LST04PDqAkS+DkS+D/QosLl/uVSjfL/5lfs6Nfxh5NfRv j5sjPmUZGMA5fN8s3enixxMQX4R8HLxK5etg5OvgTC/drzu+uMo7PofX6Vgw gOe8sQ1fVfE/6vcxSy1jih9PWz30QmXbYOrT7M0696P+7Nu90c/Nq6JplOO1 Lk26BHDotqmHMq+Mojmtyr6s0cmPkX+EkH+EG3+kd93np+03dc96Vsv7hw0+ NR1eOcXRX4MXjS9z3pdbf7BZuPlEPL2pPazxqfH+jPwnhPwnfG94mddZHxpo 4YNm23LOC+AVJx/WL9Q2mTJ3mD+y4jJfnnM06JSnOZlCWnzu9NjoJ/nm6A3y zc0tc80+U/1UOna2qcus5gFc5K5x+x2XVPL6/sX524o/PGxy1+X/eZppXptp 1zId9OVPic2+P96cQsNHdh8bEOIn+be4mGX+LW6P/FvTRkwedDXEyJcrbo71 XurOF/3bLwvJaeY7qRXHBGX7zpK/Z4dl/i+eg/xfDafnLOJdO4lTnJ7OCrd1 Zcnfg/w3LPl7kP+GB5webRw6J5b/cNHmPi6ujHw6jHw6vHB7y0rueSLYMb9r 33mNXRn5d3gX8qF96TJvz9wF3jTVyL/sXrnxqcRDDReFB9PSFq82N535g2dF TBjSMFMgFak+4uuVPV8Y+YHoCfKzrV1q8v79PZou5mld4uxJd/akNrnn3o+i 4lVbPQiq/J17u7w/0sYrnrp0sJ0ds8SNIyvmqPLh3wRyXl/KvkGZX7znV472 ef/E0d+zymSqd+grv0Z+ngDkj6uQ22lUXPL/3qN6EHT1uDsPC9kVMHpYMoVu MGQdXvEr128Z0bV9AwO1dJrt4LHYVfLVUUXkq5totv3n8oRUWnK1Xuexmdz5 59PQo5eTzDTgetm+Y+2+csvOOzK/uZ1C79+c9/nSwlXyc/F85OeSfFveyM+1 eUELv+sn085FzWMHTLjlxCO2bm9od9jEbSvde3Hnxy1e8al3+xurzGxr2Hi3 RAl7lnxZdZF/bE31/SF5/g5j+jD4ykV6aiFfu+1xefLg9JDUHCY/bvl3+SdN jffZEfmwiiE/2v2K1zfvuhFEKxvUyV+v4zVGvi9Cvi8OyvN0WYMHBmqzbXNp v1oPuWy3Ak8mvknbbx83Gzlr2FmdD24L8lPF2jo3b3zYyK3Dey3Mee4lNRk1 /+aPmSbuMHpRq8Y93lHExdY1zjUz87ZhI5b07OZC/ZDPrTfyb9Vc6k8FbML4 fL2qVdcZXtGQfDW73Y2MYNu2hys71HQh5Hsj5Hsjm5ke29vWDKTH1boGbbjx WfKRUWvkI/NoXSD82z4DjTN1zt6k0H9kmD4urMqcZHJ82i+7l81nybfEpZFv yVRhWO+KT9Pk7fAKZ0Zc8aBGd4at37LUxHUvVlpuPvqbqE23B93rmbnBn+nV MjfzoT/IVzgO+Z5ubwvaW/pUIj+tfbrvpA1e9LPu+2Xn5iXx9aEH4nsEeBPy ATLyAZKXbYMeh71i2OiX+/HWl55knPDgbGfXWG45Yu+eMp+9CXkJ9S/yFxLy F1Jt5B/ciPxZ0WXblq1tF019vh+7c7Lfb0K+RHJBPi6nohX6ht1LoNPlRy97 ktWD9n1udqByYhxdKZrpxtzVPiT5BYOR76vU3R0tXG8a6Ovz4Ektx3rRqmVN 7q7on0zlB9Z60jfcR/KLkSPyi1W8tWy3U7FUsotZt/+uzW9akvXxK2Mafyz+ 1t7f75UP7UD+zvnIh/S5XaeyM+YY+ejKTS1+eP+hgNqtTlavmKanDVrQvnf7 IOrt7Pbi4EcT7z16Y6PtkWBaYOtW50Oa/u036vqQQ+EhhPyXXAz5mWxuJ3Y5 2j6RFyYUdXt3LpBOx+Z6tT5XEm9e2uzz4abB1GzvNv8Rafr1DceWRXrdC6E+ 8VcqPZ0XwzUKnvp+vH4gfa3Rs9+24bFsu+B3k5aZgmm6t2FacMs4HhvQbkri kxAaUrJ96Im1oVzb+dq/gyP/kPeSB69XXUvbx22rnWpaJpiuFsgzOe5hJK9+ vbjjlRqhlMMrv8O8AE9qe+ZYFveGIYQ8ofoX+USpF/JhIf8oIf8o7Z18z/G7 TzzFLa1x55hzECG/Kc1Cfi7kN6WjyM915ta+xecTk6nsEodVO94ESz4w6ol8 YH2Rz3Mh8oHVMY6uG34plUYsLjNq7+ZA8r92OvzE8hQKLHzgVz3/YOqAfLx1 kI9o8KuQ0K5njLwk/8pCu5tG0fPB+yI69Tex34nqRR38o+iF0/Cetqkm9s8d MXvJ7mj6t9KtC8GXzRw0rdOHRm1jCPlmGflmqW+urScLLUvk/f9cCz59PIqO DtnzNIWS2Df4fo7dE6KpZN+TESWzJvNIn1fNL9eIoXLI35sT+Zkefi6Rx/le DFe59nHxpRlRVMl4u1GVo7G83XXqyZT+0dR2Tf5qSSvj+MLwV3u+NomBXz0K fvtIco/afTZL5TA2lt3jX21YFNk+ftzB768IrpalRuMSM6LpO/L7dkC+qbfD 4ypUmuPK7z5Oq8K5oykI+XuRD5iQL5iQL1jOV/oXeYb17+khkZfrHIqisA9D A5NuRhPyFRPyFZOHx9J/mqbpN667xpZtMSVNz0V+XuQ/pi+Nj+2ZM8VA2da7 dOuSPZok/66dZb4wKoN8YTNvBD449D2FdtmV6ja5djS9nFtz08DiiVyv9+9Y 2w9xdO5nSsXe0YlpesG9HTUvxlOT4w9TY5yT+PjSOTOdNyZQn/ZhT7e0iWWP CU3trm2Mp7YXszee2jGO33/o89phewJJ/mj5RZ5p/bt2c7WidlfjaZBtt7eT nsfTTOSP7o78VZI/GvmsqezVfHs6VDOS14DYmc9+xlHs4RNrj/1JppyTxqwa VzqB/ptef2FsXChnW13r9wt7A12zzDdEB5HPJyvyfSSf8+weucSHMtcrPHxL p1QalM3fUOVDIJu7VKzR/GoSD13x4lo1DuSFLtkrVsuWzK9V/icuovI/8dOB w2d6RL/kOzWWPh58PoUPW+aH4rOqnKTcBfWLIn/UPcv6hPcCtL1U/Im7mkZk y9/ByGM97+7r9OYn7EyJPAmwspMk6vpiN5H69qq+dT54XuV8o/5/a77Anmtm q/zvvFKVk5S3mns+ce9CP9pciGuudjPw/mu3FuWrFMShB9YtD3xnoJ4VFjZo 0tCs7yGKPSS4X36PZmnjSJrQrHzc3GRdLvauu/2995p6mtnqvVInsXfsgz1o yaY85vE5M+xn/92MGdoyZ7KGxY5zPmbXtUWrTQz7gR6H2FsEFnuLwLsrj6ji Oi1Jj0/6N0+NmvHzjIlv5av1+07ueF0uftF2cecXHfqYwlbvqzpZ2Vc4s1en T4YtGX5TsddI/69hrxH4v6mvb/54G6v7k/aGj5qyJjTRxFbvtzpZ2WvY6j1X p3eFZu9sPiZA9y/x9KE/p7Vb0SaFS1R4sez959+63Mq+o+3tQfi+pPpe29/Q voYxH20XKwB7j9X8dNy32Bf7YX5W78c6ZVL40+2LXe0g1hvrqdsX+5HAr2A/ Evi2Wk/dv9jlm2M9QQ+6XPudQQ9W79k6ib3pH9hv3yn6zLBPKvrVcLLiB92+ 1L8Efuil+EmXi93LB/wk/v9NkA/yXffvZR72XhzPt1JvefuvTdF0avr9Yn7p tyYNezidGWi4mEHHUeo9ZG0Plf7uwl4q8cv90T7a0/EBnqo9DaN/DRfIeqDj gtYROn5A6PVbn8nzMzeO5//8u7YcueiPLgda5X1lnU8lb7ag5lXNsfxGfa/j DVrWm55jiF8oCZ8UVP3p8mmqP/JEf4KvHmo+ZAZ+hA4wHw3fBj4FLor5iH/A aj7kjPlIucxn1bQrT4MuJJDVfOR77W8ogvELbDV+eb86I95a7KSwP8t6DcT8 MH7tf5L1E9gL6yew0NdW7B+/zAt+VIgwZuRzau1WdmyqQcMi/6VfK/lPiZD/ Ui7y/4GidzoA/4a0B3+BhsW/IfBOyGtpT+S1UfEn3YC81u+xgA5J8TdJ/gex F1v5X0j2F+lP9h+B/4V8lvaF7oYq+UWJuJ8i7ad6Kvkv9eU+SKB6D43eQD5L +UTsz13V/ktW/hl9HypMyWPKD/kt9cdj/5b6cr/DH/2JPA9G/QKQ51K/JO5/ yPgxPrKav6Yzkd8DMP/quB8i9bF+uj7WW8PX4B/S6w/5LO1byWfaAfks5SKf o7H+q3G/RPqX8R0Qfwf2E+lP9Kag810/n9qWSvDX6fJt8DcJnAD5Lf2L/L4K eu4O+S3lwp/+4AfoO3p8Mv6dWF/Qm+4P9KjhGlHXxnbOZeaZTY408G5vZud+ eX8NumPm11/aPnDeb+Lt47K0b7LKzGxbOfeo80YetSXzEfebZi6e4NGvq72J XVvmzH+lUSLbFdxe8vjoNP3OZVL/82n8d+FKOae1R0z8aOj47VM+pvFXZP3D 3q+M3OJr0/OTE5O46LYza8tPNPHjvVsmdp0Qw11nLP7H8YiZDeMDW01pH8e5 jpZ6fZCNXLbSsLYpaeetMum/Jp7Qgqfu8YjkqzY7zs9cbWS8n0mH8b7sjFfz x1UtlECzYpKX7Blplvdr6QLer53SvW/lya7JlGXP5J4LvI2M930Z7/tytDoP cGF1HuDS6rzAweq8wOvwnnCEek+YX+C800Cdd/gszjtF1HmH5bxzWp13eId6 35198b67g/LPsBv8MwnKP8Pt4Z9Zpfwz/Bb+GbxLrH9XqfMPj1HnHz6H940v qPeNuTfOV7/V+YrlfPVJna94gHp/npPx/nyI8i/x3/AvVVT+Jd4B/9J51T6d RvttVHv0Be31Uv2RL/obiHeU/8Z41+C8NgzjTRgyqf5A/xgyqF9eovxf1A7+ rw0K3xQEfAOfdB74BP6pCfCP8yaVBP7l/ebyWF8bnP/8sZ5y/suL9b7aukv8 4TOJZB9zx8WucCzvVP476gn/XTblvyNX+O/w/jQPUe9P83R1HuaD6jzMefFe 9kT1XjYPgr1jubJ3sBPsHX+UvYOfw94RqOwd/Br2jlBl7+BbORtXP+2Wyisv 5Nw571mo+Id4k6V/iH/DP/Re+Yf4MPxDeE+b8Z42F1TvafMb9Z42f1Lnfy6o zv/cB/aUQ8qewkdgTwlQ9hQuAXvKGGVP4WnK38UV4e/KofxdPAT+rgLK38VT 4O/C+9+M97+5inr/m1P909//Zldlr2B/Za/gB7DPVFP2Ga4I+8wOZZ/hNrDP XFb2GU5yOzepRZ0EHuP7Y3kl5zC+rvx5HAV/XmXlz2M3+PPmKH8eL4A/D++U 69/Dyr7CZmVfYVfYe8zK3sN1Ye+pqew9jPfPGe+fM95HZ7yPzgz7z3tl/+Gm 6j11xnvqXBfvq5sA31ff00d8fxXvrZ9Be5OMoZVzzv1OfSpzlYuZw7kH3lnv g/Efh30oDuMfkM9prdk1lIarXy6t/Kf0Av7TCgq/tBv4ba3wS9eA3/tqPagm 1mM23nPva7melFW9587usD95Yj2rTF63vfyBGMrexvvj5ZxhvEf5eykT/L3/ KHqjINBbcUVvNB701lvRJx0R+sR78UNA3wXwXvw70LcL7Ft5QN+P70/vMGRU IoV32xG1dX4YX1H+aSoB/zT4l8aCf50Uf1IQ+POV4k8KA38OVPxNq8DfrPib gsDf8l69yIsZsJ/th7zYWXC2w5XtRuozZQ6dvBTKszZ4dp3U0kR5+ve+Wzx7 OLdQ/nfqAv/7LOV/p1/wv7vUaZTk0SOVVxf48n5O1hB2LH5rx5mQVLbz/ZRk 7hjKvsoey/HKHsu1lL2Wpyh7Ldee3X9FyStG7tjl7OH4mBB2gT39tLKnsz/s 6e+VPZ17wZ7+j7Kn83zY04OVPZ3XbuL2paan8r6S7wrFzfMT/yYftfRvsif8 m8OVf5PnWPo3eSj8m3//XNQu8IeBXc2rT5XsHMLHlX2amyn7NJeCvX65stfz KdjrHZS9npvCXn9X2ev5WFizqGoVjVz84f0pXfx90/gr3X/Lsy39t2xob+G/ ZT/4b+sNrf979Nt4futQtO6RrsH8222Ot2F/Atfdfqj+Z98Q3qHs7VxgWbq9 nTfmbjh6fbNYNoUd65C8J5h7w19QT/kL+DP8BU2Vv4CnwV8wSfkLxD/Nt+Cf Nir/NLe39E/zc/inX3YPmnzzUppczHx1k3P9ED5tHzf01+ZwLuvzZ8SeAcE8 EP4HW+V/YA/4H+4r/wNfhP9hvfI/8LP3pu/OlWK4o6tPHpe09fFX/nUeCv96 mPKv83T416fVKNum99Fg/buhaT37/gODOercVp8t4/x5pvLXc3f464u/HLIg V0VvHjloxdN/OgfzfuXv4BzK38FZO68s63zPhX2K2X78VMSPNyv/P/eF/3/B i/T4ANqJ+IDJql+ajf7HqXgD+uOj4g3uKXxQZuDjnJovbcF8+yn8UBPg56fC Dz0Bfp4r/FIH4LdGeL7xz9qFU8CwoNJ1bfw5SsU/0CnEP2xV60+hWP8pan1p Bta3l6IHagR6cFH0QK1BD3UVvdFH0JuXojdqBHrbBf9OZtDbDl6WxVw3lvYO uzrveyH/NHpJj9cgf8RrnFT8QXvBH00Uf9Bj8EdJxU+0Fvw0RPEfeYD/TsE/ VBP892LizCzNiybSrWIzaz1w9OXuW7I+CfFJJB56+Gj5wf78SMWT0HXEk9RV 8oaaQ970VPKEjlvKEwqHPPmk5BFdhDzyU/KIXCCPIP9ojaX8I5F/kHc0GfLO D/6paMhDj3lxjc4ajHTs6OAOqeP8eI+Kl6EuiJf5quJl6A3iZbLual7obGoK H+3seHtGN29eYPfl7qkLafL3dbhx8iEfXqT8lbxJ+Su5gvJn8hTlz+Tg4Z9n l5ti4uU/104dMtCbjfAXj1L+Ym4If3EL5S/mdvAXN1P+YnY/297l3tFUbrG7 S7/erl8lnoAXIZ7gl4on4N6W8QT8BvEE9r1D2+zbaOCEfp0H/V7izR+Mq9t6 dTLy4uszB8+P9+Flyj/LTZV/losr/y2nKP8t276eMDd/z0S+uLBZuYCpPiz+ 6nfKX83u8FffVf5q3li9TeZm/YycNLGgscbjL2nni/T4CY5JvZ8ePzFcxU+w h2X8BNdG/ESt0G0bW7dO4CUVLto65fLhncrfzC+Vv5mfKH80f1X+aPaEPzyn f7o/nA3wh5Pyh/O47Y0D/kuI57hrQT/u/PrOfVQ8CLeyjAdhJ8t4EO6FeJAb M6KzTWkeze/vHl58pZo3B60sknlJqxhu6/Zr9vs6vhyu/Oe8VvnPeZ2KR+Gj iEfxUvEonBvxKP1tyh23jwzh3FuSBhre+XC9Yr4tbBJCOGXqGLeRLb7yWRX/ wjMR/zJXxb9wLsS/BCw6t3DCWx/9ezCkdbsezj58+ND4Vu7tvvJ3FU/DYxBP 46O+o2B8H735csg/Lb5R5i3pv9xXjYcKYDzX1HzJBfMNVPOlzphvJOIFpmG+ S1R8D51CfE+ywj/9Bfx7qPWholifmmp9aTXW9xniCx5hPfcgvuAB1nvqszHt 3IfHUOr2Cx0T937hgSreiD4j3qihok86Cvr8oeiRHoMebyl6JTfQ63bFD2Sy 5AdaCX4oifiFQND/CsQv1AJ/vI2Y/X1/s0QKrnkk3+t7X7mRipeiEMRLhSh+ p/ng97aKn6kl+Nmg+J+mgf8bKP6njuB/yBs6bilvSOQN5AtNgHyB/KF1kD9X PhYNf1HJRP6rfX4MLP2dp6t4MDpsGQ9GFxEPFhtTyfPmeBOvmhJVYqnvB5Z4 nCEqHocbIx5npIrHYYnHOaTicfh0nfyxvTYYeEykg09yl498Kn+P2PFDjXxj 9aPoH4mfOVnFz7C3ip/hXyq+hq+q+BpOvT2opqOTgT2WZxrveuKcxA+xeatF /BAvfqTih2og3ueFivfhgYj3aa3ifZhaF86Tv0koD6u3K9LlexqVqHgfDlbx PhK/xGZbFb80v1WWIe2q+fJAu8dl/s78hecqmEYDbqfao8lorwTih76ivbWZ h57oVs6fln0yu7RPa++hip+i4CEqfmqAGh91xfiqq/GTB8b/uvyG5+8dwqjo 6klj+2Q+zWtVfBYlvFfxWacUfmmlJX7pGfALfNJm4FPild4D31hfGof1DVfr RyexfjFqvWm+5XrTfKx32RPZXCLuGGlz4UfVzA67Jf6MalnGn1EhxJ8tV/Fn 1CpZxZ+VU/X5fMH0+rQF8WtVVX0aifi1uIrp9Uni1yolpdenTHcUffRT9EFC D1kUPZDQy7+KXkjosbPCF50GPZ5S+CKhP+CLhD4/Ir4L68E2q9LXg7AenKjW wzL+vfu6NkJPGxU90TpFD7zROZ0eCPTAEYoeqAPos4+iJyoJ+vyMeLSFoMfu iv6kPcqm6Iseg76OoT2Jx8uu4vFk/HQQ418HerqO8YN/6Dni5QaBPtsgXg74 prfLFL4lni+7iucT/NM24F/oY1chtb5YT3pruZ5UP1GtJ9afsmH940CfbRR9 SjwgQf6Q0OMQy3hA2oN4QNGPair9iEQfIqUPkehDD5Q+RKI/TVL6E11V8pLf KXlJkJd8UMlLkvjZ00peUjbogweUfKaF0AeXKPks8Ww8EPFsi6EfLkc8m+hH AUo/ItGHnJU+RKIP2Sh9iER/8lf6E/2n9h/+qPYfwv7DoWr/IQfoe1Fqf6OP 0Pfmqv2NsL8x9jfC/sa1EZ83HvrSb6Uv0V7oQ6T0IeoL/ame0p8oCvrTPaU/ 0XS1X3Og2q8J+zW7qP2aakO/m6f2f8L+z9j/aTf0Pez/9Bv6k7lKuv5E66Ff 7VL6FS1FfPEJpX/QTehr/yr9hYKhr7VQ+gtBf+FJiHdsCP3rj9K/aD70LVO1 dH2LzkMfG6f0MRoI/S2r0pfoJPSvhUr/oh/Qv4Yo/UvrWaJ3iR4melky/i+/ V1V71BftQZ8j6HPUTI2X3mO80BdpFsY3B/HSOZS+SCuhn20BfqCfEvRTgn5K 0E9pGvStWKzfYOhbj7F+ExR90DvQB/RpamVJD/QC9AD6IejTBH2doK8T9HWC vk6iX/0CfTeGfuUG+t6k+IdcwD/gD4oFf4CfyNOSn6gO+Kkx9MVdSl+U+FvC eYZwniGcZ0Q+kCvkg+hPByAPZkC/2gB5AXlE1SGPJP57CuQN5BN1tpRP9Bjy KRT641SlPxLOizQS8cU4L1ITxBfjvEiNEV+8Hva4rcoeRyNgb5uq7G3kAntb f2Vvo3mw1+1X9joqCnudm7LXkZc6L/MedV4mnJe5qzov0zfcL3mhzsv0GfbJ Jep8Tg9hn+yuzudUG/bIUYgfxfmcwxA/egL2utzKXkcrYZ+LU/Y5mgf7nJey z5Ej7HlTlT2PXin7BJ9T9gnqqewTaefTdPsEPcZ9l6vKPkFDYW90UfYOOgl7 Yy3Ew5pgf2ul7G/UFva3J8r+Rk1hr7uq7HW0W9ljeLOyxxDsMRyg7DFUH/bE F8q+Q96wJ1ZX9h3aDXsi7Dv0HPa4JsoeRxGwv01U9jcKgH1uoLLPUT1ln+Jf yj5Fkbifc1rZp+gV7IXNlT2LdsNe90vZ62gO7HWdlb2OxuP+ToCyp9FM2Nkm wu4W0EnZ64KUvY5Owl7XW9nrKPi5stftUvY6+ld9T1H4fgvu98C+RynJX3rf /O8LdStYYM60rWnrD3veS/R/Uo2XXmG8sC8S7ItUG/Y5b8w/Gfa5XZj/a4VP qgZ8+uH+EOybBPsmTQN+X8J+GOqdbj+kAbAX1kc8tyfshQ8Qz30J9kXYU2kX 7HMOoIcU2OdcQQ9NcB/pNugH9l4i0Fsb3EeCvZccYF/0UPZFgn2Z6iIeHfZl gn2ZYF+myYhHfwn73RXwRw/Y7x6BP57CfncC/HFK8SOZHRU/PsD9pzngN/An GcGfc3H/yR/8WRr2RdjrCfZ6skd8Pez1dA/x9Z6wzx2EvPkOe9xjyJd9sNe1 hPyBvKPNkHeQZ3TAUp6RyDP4H2iGpTykgZCHtrBX1lb2SrlvQGcs7xvQO9w3 gH8kbbzqvoHYMwNw3+A2/LnzlD+XZsN/6678tyT+273Kf0sv4O9drfy9tEf5 i7iT8hfRHOUv4kzKX0QtcV+zk/IX0Wzc1/yu/EX0Cv7rgcofJfHcvBvx3Dnh v+2n/LdUEP7bccp/S9Ph77VR/l56qvxp7Kv8aQR/GhdX/jQ6Bv9zP+Wfo0Lw P79S/jn6DP9zbsSfG+G/7a/8tzQP/tnZyj9LN+DPDVH+XKoCf+4X5c+l6sq/ yMbW6f5F2ov7pCmc7l+kufA/d1f+SqoG/7NZ+Z8J/kqGv5KGwk/aD35TG9w3 fa78pdQbftbu8Lseg784HvH4y5V/lrsp/yzdhT/4hPLfUnv4f5OVv5fmwJ/b E98/h//3A+4LTCu97t87f3zp7pXzBbvkDaPBGJf81oA/9yrGtxv3XVPWpt93 pRO471pa3XelavDHZlb+WDoIf2wk8JWq1oM6YT3gTyf40wn+dPoB/M/F/Vj4 0wn+e4L/nuC/J/jvCf57gv+ensA/GwR6ug7/bE7QE+INCPEGhHgD+hv0ingD QrwBIZ6BEM9AiGcgxDMQ4hkI8Qy0G/7YbuCv2fDHZgN/gZ/oM/ipFfyzLcBv dxR/k/A3+JfWgH/lPu8vS36nfeD3AvA/D1f+Z0L8CCF+hBA/QgG4L4P4EQqw vC9DIbgvsxPxR54q/ohWI77otYovIolH+qrikUjikdqoeCS6ruJjeJOKjyHE xzDiYwjxMYz4GCLEV5VU8TeE+BtG/A3FIN4qH+5fDEI8UqyKR6JKiD/aruKP SOKTBqr4JEpG3FA84oiW4v58WxU/RIMRd9QfcUiIP2LEH9GI8e1WPv0TyWNO LFv4wTmB/lb9Uxj6l/v2Q9Cf3Ld3wHiuIV5oK/CRA/FBLpj/bsQP/QX87FH4 J1fgH/gmN0t8E+K/CPFfhPgvkngofxUPRRL/1MDyvg0VtbxvQ4g/o7dTtwYd 8jLTKrcJJ3I8iqN2g78t+P0ghf4Zc3iS2704Wja3X46gCSm0NP03gTrWqTL/ 3INQXtIrdd/W7snU/dnUXxVdQvlnxZ57IksaaNusf6f/NdTMdt0uzJ5bLIVy 5C5RdN4dM/c50mpEth8p1CHvbs8PNc38xfbn7Oi5qbRq5d0GJ6qZ+cJ7z9hL M1LpYYuAi3fvmXl6oWvL93mkUItzr3KU+8fE4Wc+lqublEqLk4e2GH8pidsv WLsqT6MUOmXXON91nyTOXzdk6dZDKdRpwM+BTX0SuM4Wj1Lnv6edkzJPenpg TyLfdre72blqChlOverSpkQcH163oWdQWn3f1iFl+y6I43ljGt+Yn8b5PSot /mGf6M5f1yyImJg2/mO4b3Mb92mSbf4LGvfiFyVWv2T6FpJKM3YXeFo0TR+7 92D95KYVUsg7OPfOt/njqcPoLfvXbEil3JO+TO/gmJxG1/X2PeuaQps6jRy4 epKRnvV5E1fkmZlWdl3+u/guAw1LCXr0wWwm39B2e79uSqbx5wPuPTuWSifu 1zy69LCR22b6i9p+S+UuwN8PhT+2wg+vtsQnOwKfMxU+eerual+WFsx4t1bu 8zjkdS/9snMK+6v+eZLqn7eo8fILNV5eocbLQ9R42W3WHpPz0ET2Sen26Pja VK6T2vXU2+QErp3+m8JPLPHPVusj8ZecA/GXi/I2/jdTiwQ2fFp/4eeqVPZT +OROCp88S+GbHRW+eUWLBnWWHk/gUmGlJl+5bOSZKt6T5yLe89vsHYkhMaG8 6Uxk9MSnqbwv2/Zu0/dFc9Va337u9DRy9iJVr/9M9OXuW4vEnL2YypnOp9/f 4izq/hbnLpO+3oz15lYHc1U4v/TlE7mfYf854vmdfA81bLS8/8VCLwmon1o4 vT/qhv4+qfHRBozvlcofQvWRP2Scim+lS4hvXaDwQ0nAj9DffeBD6K8j8JWl lU+5o8YYut3YcOjzbyM/VPG19Bfia5NVfC1lR3xtORVfSxURX+uq1pe8sL5N 1PpSC6xvR7WeVAvr+UitN93Eem+xpHdeA3ofDfrxs6R3/razQ3/X3wmUvUbd rd4OJn6wftSwqo8TqXLjgmv33DbydxVfTL0RX9xWxRfTdcQXP1TxxTQV8cWt VXwx2SC++LjiJ2oNfuqu+Im8wE+QR3QO/PNA8Q/NAP80U/xGYeA3xEPTU8RD j1bx0FQK8dDgN33fRu4/bAa/Dcd+M17tN/wl+8/hb6p4UvJQpwPBM9P00JgP C2MPeVLvy332Xe6QwEPV9zQJ3yu5nMLLlXwWmFYAhvzmJZDf6I/QH0k892M1 fpJ47iJq/CT8mVXxJ2F9OIdaH8L6MNaHsD7cR60PtUD892m1PiTx31gfkvjv Qmp9SOSNE+TjcsibgZCPVvKJloP/iyv+J8R782zF/5RV0T+D/umhZXw5gf45 h6J/Ko348uKK/mmhpTyimZbyh3wt5ROJfKmk5Au9RD4gW8XPJPHqFxU/k0nJ C86K+6K5LOUNnbKUL+3NlvKDXkBe1EX7Ii/Oof39ajxUHeOxkjeUGfLhJvCT BHmQBfgoA3lgA3w4Qn50Bv6AfyoC/E9HvP0M4P8++LcC6EP4OwvoxxH8Ogn0 0BL8Whz08A383gv01Ab8fhn0NBnx+5lAn98t5RU1grxSciuFRD7dgD4g8qsm 9IVt4OdH4IeR4Oei4IdjlvKDsB/TT+gzVvKBVlrKExJ5IvrNwAo71n//ZtL3 a+RerNPPtiWeTkul0EVDDtGOFF0u+7fc/9D3cZU8oUw5/0cmhjZCL5Mhf+R7 ff8K3x8N6D7B5r5R3xcp2/TEz40dTDpfZIjqX98Pwff6/md59b3OnynjlfuI 9yrbLvjXw6zvA5uXXi6W+tmk76Mu3r8mYPf2FA2r8afo/bRW41l3ErIZ9L0v tK/vO6I+Wbcn92IWoVxguS/X8ti8c/tvGfW7oGdKl+zTfHmavnWx+B/Pwr46 b6d8L/iR+04n8P159b3G16R8DxcfL5TK/cdWpk/vUrlW9myDjp4M5O53Q29O SdvfJgTYPxpd05+fTZmz68ppI491Cr+bMjaULrkmrHnwxMxV1PfUDd8Hhs5y 7rfGrO+DlsP6CL4nqP5I+uuc+N3Z7ZFB31uWvJpNBz1wa1Ugnrv2XbH9dnKy vp85sWtNT/+kJA0bsl8/9Wdvgq4v9xwLVZ4V031cPFfLtDHw/fV4/f3zbA6f Ri+O0/DL4AaZTub20Pc9B54a9u2yV4zV/c84Kof2UF/fo6uu2tdwrkITwsrd SNT15V2ILpjPJDV+/X03NT8Nb+5b8m70JqO+51xzVOZBmeaaNPxh8dsGmfYZ NNys4/QeKTnNet6ZsyXtok7JGh60bFfPsh0NGpb7fReCjw+vuiyOxxRcXz3P wFT9nvag6df+RKWYuWf6uKO5ef/Fowa5pWi41K4GN/0qZpSPPvx4cXzLpIz+ cf9w0ZQ5b/LNi+f3wcfL/3GJ0+UyT1/n9wOLHY3nxC93/OtHGnT/Mr5Sdc62 TxgTzfw1j9Oi0cm6v2aPShxbMSRJwyUrN7j394UYjY9cMd1WL2odreFbhesa 39vH6v7l/42bjqqQEBvHkUOOujo7RulyadejxNfkn2died1IOzJ8SdDj0+sW 5ttgR4MY3vz7epHmsRn1IiY6RBS5FZsxPrfIvPdeZ7yjfmW7XeK6IZF6HHJ/ se44B/OhFlH6frkt4Emwjz1Q9jGZn75niflrGPPR933Vvcdo8sd8bip86HK5 D9gO+MD4dHtYP/293D+MxvqNUuuvy+X+3lasf7WVNmOa1YrVeRqlv1Wn/VpG PIzmcIUvEnwBnxr+qOhdjwf8oeFaij80DPrX4xms6F/Dcj/REfTfVPGPLvfN 6+ReLjRRj1fm41W6SuM/RWKE/vT4nBR9atj+/f6zk72MVu+/m+hgplxpZ4gY 4R/9PfiNrPhNw5IH4/b+pPY1B4cxlUo6ucXGpO+NLy839o9XPaOG86r3V/V7 5+Hq/VUNy76zsnG/+sHVo1jep5Xyi/s/FTlcNFW/j74kwa1CBf8MWO+THc4U cf0Rps/lLq+/Oy+5G8HThjV5WCaTWY9neNW2xyb+zoDb5s1Z/N2DFA2Pqd38 zq7nZp2nuVPhzHXiD6do2GW9Q/8yPhl5nIvgfV0Zr4znebGQ8fNLRvOXvoW7 ti+TqNv/nini9fykeA0fRD5R/U4j5FVQy2UXd12L4NHIFyvlwu8xhwb/+uwf wct9z318fcag8SHyKs+g1ccnjAvX+1eLH9c/DaodwXUvjxt2pEGS7v/e+AG/ +rZK1nCen6H767Y0aFjqLx3ea+X8n0Ecl2t+au4SBj3/lj67prrmTdLwDftT bxxKJGt4K/KbyviFL76VDSj4MWcEb3+9uUrpJQl6/DK/N0NG/cp5OFjLwe4H Jjf9cSiC+94KOdNnbaweXyXHWq9z/puRt6BXW5spvY7E6f5TkJdS+pfvRl2x 9bg+LIJvbOj4dfqCKP19YXVfgsbivoQd8kNVxH2JePhLeyl/qX7Hb/Xaapup UTi7jmkQwFVjdN4B9K/fHRT5F3+x0cXJd6MEP7pc5JEv8NNoXOy8s+XDdH5t jJdkvKAn3R/oTcOgH92+yMushxX9HEK+XykX+WIC/f11uzN9eprxzqLoH8Ox HpUV/nV/fdT6kNV66PHKfe73kB+QF/p7yBMNQx7o8eXDe85W8kTDIt82QZ6c a2Zz8sq+RD1+mZ9r9Ru52o4N1vpQP/DHfcUPZMUPGgb/aFjq7wZ/gB/0fG8q ftAw+EfDeJ9bj1/OCa8hP4yfsm8ocsCox3/UK7JqpTUmq/Uw0aoSn5tczxqq zzVekH+Qd2Ql7zQM+ahhyDc9PshDspKHGq5J/8ZOaWfW77SLPL/14mx8oTUB vD1T2/Oha5J1ucgnj7mFD7/NHcSzboyc2HdPqj5HiPysnNnr0cEFPpz7H/t3 E++buGZ6u/4csmzmlS4HzRoe4Z67pcecFA2Lnp9PvefK/81ZcctjRqrm7/EL 2pr+LpOix6Pz1mS/Yvy9NFDr7Y6OxW5tjvPjnl2emLu7Jer2z5QcU6LyswQN n646xGf1siTdXtB/J9wCy8RruN479235W2Sck2T+7eYce5dY1Zf3+U6z+eOX pNurUnnfpdMByRqOXxYTXcIjVrcn8nOWU8ygpfeDuIdh3YG1paJ1uezTbzLv rNHh+h+222lf9mG2BN2/fjcmvvvQ+WF+7FF085Z9I+N0fw2r7Ns58UC8hhud rt4kZ+5I3b7QycPJ4+9+zhfMtpFflvfaEqjLBc/Bpjtftlz154Sdzn9sm8To /mV8Qxtl/3F5pbeWy+XV+8rc/t9i/n1rRen+S+bsP/L5+RBdX/JlubWZlDz0 lq/Oj+UBuL4aj35XQPKFx2E8mI8ul/wt/2I+wKcuF3ntCnxiPXS5yOvVWA95 d7Se5XxI5iN5YVxAX6AnXQ560zDoSfcHevt//e/bEz06KNiXG6n10/Wxvhq2 V/yo64v+GQd+BD/rcpEvL8HPHVp3HhtWPVHnSRF5Gu4R+4/LFT+hX90f6FvD l4/GDej4V6qGwY8Z7+xC/j0GP1Z4ecO7V1WT7g/8rutDPpCVfNCwS+yZm+6O Jn2uufVtw+5Hh80aFnkVWbVL5+HZvLiFZ0zXaUHJulz0yUILPj6+WM+di24Y cSNHnImfpRe7cshiu56vv5o1/GGUzctaV1M0nCv/JpcxuVJZ8sS4z9zh+edH BhwfNX5mi/kZeb8K/Ap1bZEvUdev8fxrzgtB8Rqe/0/WL85/kvT3oi8uz+Od PamEO6+dlSnvm8Pxulz4/czgnvdWfnDnsdfvLJwxzqD56JZd089zBhs1LPLJ ftmwbD3mfNP63/qmHTb+nOzG79of8uxSOUmPZ2Pd11OP103WsPvpkVWX1zFo WM4dxiKV/+15+yvX/11h6O9CMbq8/eMHS2qMjdPjFfn2q9rxxEkJrlzYeV7F k/WidLnogwEfS/oHfPnBhX40Pntndqxu78e63RPG3IvTsMijDwualRzu8Ytd LkZtDqzqpduTdVgF/Nl0qhsWUzlU48Pmo2dSnbx/dHv7C2VODimWIYfQns77 I/nZ9qE9kT9B6B/tkbQn+mPTohb40eWYv24f+NKw8H/h6gpfoBddH/Sk4XWK PnR90Qd9QR8LFH3pcuHvp5iP6H9lnBX+gW/dPtZDw+An3R74UcM3FT9qWORN hWqKH0W/+gT6A73p9n8qetMw6FPD4C/d/qrxO0/N62DSeRdFX2oA/g5W/ExW /Kxh8L+Gh3bdsjliipnlHW/93k7jvGs+nn3Ip1xznil7K1mXN7TIb+X0pMrz d6suX4rU5WXHrO3+fXCQNazfCcf3Gi5ukQ/K6Uk1i/xOTk/Qv/4e49Ww4Du8 mRrvf3h/W+rLef/q+2MrZu/8RLUKZ3Iuv8bI79P//57eVQiZVW+aScMLhpyL 87U3aHgY8CPvmgt+BjVJ748EP1JuJW9J5KvkZRP5KrDIY4HHQb6JXnAb8k1g kW/rlXzT7yivVvRFIs+kPZFnAr+H/BPYSh6RO+SPlBeGfBJY9HbvPs27JNq5 UL7obfUPvg3V+KoKehB8lAM9aBjySeZTHvJJ2j8M+STl8s6STV+L/kj6Q/v6 3Xn0r2G0r/PiWfG/zE+XY/4a1nlPPyj6AX3o/kFPZEVPGj4N+pXxCP0KLPTb qbmiJ5EXL7CeWC89HpEfAov8EFjkg+BP5EMd0KPwv3wv8sKKPjUs/BP/dO1f uT96U16/pg7Lthr1PnEtukL9rfNNGn5xuMn5swcMGv4M/UXssLehvwgs/BSj 9BdqCf1FymfjfCV+F6vzFY3C+ami0pcoD85bAofhvCVwAvQVaX8h9BGBRR9Z ofYLWg99RI8H+sh5td+QLc5HMj6r8xFVw3lI+j+A85LAol9sbxO4u02gD7Vb WqF62SsxGn833m0ttYSiNdwB+oaMx0rfoCLQN6S8P85PMj4Z/yl1fqLGOC/J eLxwnhJY9I93av+nJJyHpD2r8xBZnYeoI85Dun3oLzI+0V9WA99lcF6S9nMb 0u1V/Bfi+22QD2SYsm9RT+QDqYL852hf5yEUvO1H+6LPhGI+or8cB/6vK3zr elgPDQO/un2sh4at9BmyOk8JPkjwAfrS9UWf+Q36An3qcit9Rve3V52fZP10 +1hfDYs8K/5M8TP4Vc8P/K3hq4q/NQz+1OMBf2sY5xMNi3wrq/Qh6oTzl6yv zn+rzl/CH3q84B8N51bnET0enEc0DP7W/VfE+Uv6g3zQ7YXivCUw5ImGO2zO 0bOzwaj1YO81awq2zpcB14L96LY6/2l5dledN8kB9iMpt7IfkfgHZJ9bCv+A wCLvbin/AH2G/V76Hwd7v8Bi7xdY9JFPyp5GI+A/ELtBO/gPBJ4Bf4PAV9R5 V/PvRNifZD4yvvvqvKv9tAFt7zbNfDKY5uboVudmXIIez/pvRScHf4rPeAcN 9idpLwT2J4FXwj8g+NDv2Cr/gNZ/lij7JbWGPV/ah/1Sw/Gw/wss9Vsq+yk9 gD9B5p8X/gSB68P/IPDqCo+67u8fq9ubPL9vG46O1nAC7F8yH5HXM5W9hXrB /iXlVvYvcoB/QeZv5V+gPvAXSH/a76rs21QF/gUZrx38DwK/t9+4d/KFcF2/ zKOXIRdigzXcFPYzGZ/Yzx4rexM1gf1MymW/CFL2KroN/4SmR+V/5Ru4n/AW +fA2qnx40r+W0+/U+DSM/kj60+uK/prBPiblMs/XGC/WR9fD+mkY66Hri/3s O9YD66nLtf8V69kc/g5Zr1vwd0j7Yj9LBn+sU/ygy8EvGgY/6P7Own4mcDf4 N6Q/0IOub+XvkPXXeAF9aBjyTdeH/NPwDtjfpH+xv8VCnkEe6nKR/68hDy/A nyHjFfn/XfkzyMofIfyq+wd/a/gW/BMCW/lDhF/1/MDfGs4H/4jAEueTV9nf 6Z2yv+v2If/0/NQ2k0IM+WeGv0Pmdxz+DoEFH2uUv0Pkt26/M/wTAkPea1j0 eQ/I8+nwf8j4Id/JSr5ruILdjAoX2pi0XTi47M4HM0YaNNySCxWd28+o4fzw f4seEwH/t8BW/m8KgP9bysciHkb0rNKId5H2ByM+RuAWiI8RGP4l3Z7sN07K v6T3m/1//mnQqUkMHd5TrVDOzom6vvP+TT79qiRoWN6/lPZE3w9R/kKS902l 3MpfTcmIr5H5WMXXUHPE00h/iGfQsOj7Uf2PdszaNZr69uwUfWxojC63h79Z +pf94qvyp9IGxM9I/zK+rip+hiIRLyPtbUE8jcCnuk+7sqFAqIblvRrpT/td lX+ZSiPeRvq7gXgbkXtih+r77ldr44lo6l+/wPCQy991+1bxOPpc2h/fD1Pf azlrFa+j9fNE4KuPwhdZjV/r2Vb+acGnLpdx+wOfmI/+v8jnE6An0I9uF/Sl YdCLbl/092zKP03/wD8t5SLvUkBvNRDPI/O0iuehrYjfkf6wvmTFvxpupfhX w+B3DYM/9XjA32TF3xoWebUZ/O2HeB4Zr1U8Dz1H/I7mZ8T3aHoIPbMt88VU DReD/1j6E3n6Cvy9A/E/0p9V/I/ID7KSHxqGvNGwxPfJvpgV8X0CD0F8n8DC 35dUfBOF1J0T2Sc8UdudP27KXabb9wQNj0H8ntQX+bJYxW/RB8TvSbnwr5+K /yKJ3xQ6FP20uYp3JMQ76v4Q75jxngTi86R9kR+NVDwaxSA+T8pF3/yp4tnI iPhP6V/0yYIqXpNeIN5T+quBeFCBn1XqFztyYxT5TvMreaFkPB2Z1+pir4VR 5DxlxesdHeLJWeFL8wnwqWHgR+st8v8o4Af41eVCf5uA30GIN7V8v0LHm8p4 dbsvEX+q40oQ72ZFDxoWfec+6AH0pMvzIF5V+hd9pBvWT+JTpb/JiF8VeCzi gx+r+GAKUvG/+r0Hq/hisor/pZSuJYqH3wzW+7I694bQi7Iv/FyzmDmxw+fd r6ZkvFNvN6mgOXFlMFX4fbTHgYkmXt2nwMV/u5q136zyXzXzbd2erOER8zpc ObIxScPZ7Rv/51IzXsP3Eis+exIcaw2T1fdk1R5Z9Zdh11bj0bB9UvSzM2uN 7JD+G8v2U1z3jmqVNs/03zh2rnrK7f7DCF5S9djsX4XieH9l46K7LWKoTtfO ud3Xxmm/hMvfpdc0O/VL+xEOHo939trvT0GfI312LXyhz7tip3XF9wIfxvf+ 6nttL4h75V/2S4yJo9J/42j9nGuxC66YeU36bzxNrD2kbo209bzyZPnCh2cT qGqeA73ynzfzvatuOy69iSduMzfX7wMmtllm+uLmmkBrsB5CR7IeArf53SzR tbuZl+w4ywd2J9P6Fu7fq/Uy89m10w2zvJIp09LEP4enpJ3nB14fuLCCkfrR 997lhpn5mlPt277nDDQS6ynt5cB6Cnwf6ymwsv/7sa3fobxBbw0k62tVX8Oy vlbj17Csr8BZ08k8iJMVX2v/5rKGfxXae87EBbacK7kuj4++TxCaPp73fCp8 9tsGaXgT2MWcPTL7jxRun/6dO411amY+Y5/ExvR2AynhgI3P19UGBn5orsIP Az90XeGH4wr9OTlpTzS3OZMnJOl+DB9U9MS1QE9Pb895TfWjuK/bwyETFsfo c3DuJt6/c3WP4yjy5ybhgVoOT8D6X1frz0+x3hXVenMV0MNjRQ/yPd3E9ygn R5SjPpVDfarS5+jtV0Yy7Ko1oOLJGN77vt8l791Gqnx6a36H7rG8XfEL7QK/ bFf8RLvAT1b8wOvBDxnxQqr8s+IHtuIHXg1+kO+l3A3fPwO+eil8kazPSLU+ dAD8WlPhl2T+18AvTphvCfBHNeDjNvhH6GWpohfKCXqR92qs6EPDJxX9aL/N cSv4E74XO+NCtJ9Dta/fw7kYYDDkvfRb6ymT0uW6J/UNbRPokMck/EgzLPmR LoMfe01cOuXp11/cf2j5YZFxCey38HqWQl9/0YpjVzK9SoP7obyvKqdBn1f9 fWVSENv2qW87tpWRzNm+T2/+MIjXrCzeY8IZI7kntPx2whjEnW5ve70p1Ei4 b8JX1H0TqmF5P4VG4D7KZZTLfZSuKBf+r6f4X/v9nMFvAp8APwq+Flnyr77n dBv4kv1I8NVP4YtN2M8En1b7GcVhP5Ny94pFsqTYpnCvmmsq9xxnkP0uw6+t 2tOwissJ4TfYH2PxvbSnzu1+VA7yDvgl4JcDFX6pn8KvtXwhA75fifX4je97 yHqo/Z6e4D7Q1qK1qvBbP1qfa9eDRu2NPArlD6EPqHjcQM4KvVLhMZXH+7kN jQtN5VPnx5Te+H9cHQVQ1U9TBTvAxu4AFbEQc+2/LQpiKwbY3WJ3K3ZgKypi YIvKii0qgiJKKiDd9Yr3Hh8ft3sMb4aZN8vd72Jvb29v65brpJ973D/XG6qk JLB0bF4xyTYHL1I52wEGi+9huvgejrjvMK+nzYJFU7KNv89VQNKIyEb1++XA +mWt7vfZp4DRStfgbotyoGe7J8+TQvkdpUyo5xJQb7Q6Fx403h+Q1DZbyjNL WrsPXzhXh48bp/wKa52Ht9svarko+A/2fKk4c9tNizcJ7i5guCRgsCFY8JEE tDh3ZInnijyI8+/z6KLHH7l+WMhvI/E/1zkmAZO0GEnlvH4G5VB34IH3w3vw u44a/BVz53PVwHjyy1Fh9MRRFw98+w4vgqvPiXmQg1/sP7hqeofC1FG/Up2e KTGJyr1FOYRT+VhRDg4X8s3mmyeQ/KyBlmbjjMqtiQHu70vV/f5Xs7PA7ZPF Bes3WfJecySx3EbN+BzYV/aPQ9D8LFpnvo9mwWiXpit8NVkAjxpZPdufBXv+ G7B2WME9MLSaiaPv9gJ5t2r3jjPfZsMYk+BZyblKXDV+zp7Ou7X4k+J1yxWP p8YWFE+9w9oxbfGrDNzw6ULVw5CP5bp9GK7Zl4ma9zYPSq/QY/Lh5QnDGmRj p2anOkT21aIxxdM+onhyvj941b3n09MtHwc7HBq51CMJjc4P3WDaKx9vUDwd x6tdp3g5hus1H3L+6q0kqPVk4c9VPfNRsyx1+7wmybK86sz2rSwPZkKqW8Dv wKV63CbGCy40Xo/5Cz1dwjOlXmjGg92XzvbOlnBU+029LdwzYd+tru29TLXI 8bAWFP//csm8MkO9c+HHg8h9oQe1CEFDlk0rkKPPRTebO+5KPnbd1H3KqZcq 6Vfr23ynyw7LHAl3D3n0IGpurtRDbX6Z8Lycr1rCJs52Mxzea6UfWcagzv27 XtdJmOl4P8Wz8HdePVYPGnspFxPovsn3xC9032T4weuhf78qVLI9vm8GUXzN nIn99vqvyJHlLIespHgh1vc0m7rNel5cJvq0z14wcUAMnig9NvXMhgx0Hjbb 5UFMLM6rfmjFf18zcfEP5cQ/375jWM7LYGXB/mD9z8ked7a1/5aDR14N67zs whuotWbPoLTlWdi4T3y/vns/SL0Xnw9VjYw6ejfJwmWdQgbsV0XKcj4vftP4 +6Y3rTd+YIYs53vVK8IP4UPeo/k+yfDjr4vMp3rmyu+ZL42heLM415NjHyjV spzvd80oXu6vCwZ13KyX5cxXza2+P+4VlIENSZ/K+yCB9KkM25A+leG+E6sP fzpdJ+NFeP0Xkv/7KdJfyngt0l/KeKb9TxWOV1Xye17v1xQPMIL0iVx/Xrs/ h/aa5Mj6/PtwdxfFzOgMPEv6QK7vWq7qr/kH02U99lv93E274p4+A8+1cexz MjdK1r/8/N5F7YZofG/c/91A03hcV+F8mEvzWLxgZ1Xi3eNE7Eb6QImfdufv pc4PwulZpQd9T4lHt6Qz7Xxqh+Fz2+3bvfslYw/SB3J9b0GPcIro0Vy8pwQW 9J7SD/HeEpRoIN5bGjk2f0PH1ERwOe962WVTGlrdc2vvcToepqgt7bPbpOCM k0f+fO2UIP2YWK8ekzTfbk6fJBxO+kXun/VGS7N7POprlsLrIctpvSTc6krI uqPDc2X7TG8hFA/E56410U886e8M6EXCRF8SXjVmW6+MG2rZPtNrQ4qXmhtb pZtdL70sZ33ac4ovY/ptPaaZs3lmHPYh+zbb7SLJvs1w/MgZKRvK6yQdcHyC OfmHkz+0vB8sJnsvf7+F7L0MD/EevfZFD5Vsj+k3mPyveZ+ddNJMn/crHjeQ fZW/dyL7KsNpZRrpNAezZXvM37aQPznj4Xjn8zsyK8fjW7J38vc1yd7JcNa8 m5PdNqdg+UaxEVuORuDhuKaRjkFp2LTigiU7GkTJfpapj77d8l88Rl/tPSWy /1/5/bDml6Ze/hiDIx83WHF/QSSOjzvR/ebVOOx8zriWY7VoVK7tFvusxW9s XKZ97ZbX/uIRQf+ARP+RYn/ALNofq8R+giu0n86J/QafaL8F5uXa1qj8B2r8 V3nED7N/kn/GED7Z7nSJ5l+L7Ks83ndkX2WY5ZEbhH/Ctyyn9SiKh0q8u3np 8wzp3877ZR7FR9D6y/pEHxKemlM/UfE9R37P++URxXfwfulD9Er0Kb8n+pVw +J5TE7IGqGV7ViU61PjWXyNh3i+TKX6F4mvk955P+1ksTNDJ+gcvVLoc+Kro XVXeTxYU31OB/OH43kn+MhL2JX84hhtVqmeyqYVOnpu9yN+Ly2+TvxfDNy+v 3zooNVnCbexeZCR4pMnva/r3qO3fI0aWjxX0Bt2I3gYLeoRxRI8HBD1DK6Ln DEHvUIPovdWdFi2GmsRLu44n+UNx+zReMJifhAkfYIAPCfceFTD17iy1bJ/X I5789VnPmTYn7O2mNhEcfwAG8QcSbk3+vHyPZ39ehtmfl2G2Z7J/MNszGa5A /qxcvwTZx7g87O2QpmWnxeCTa8O+37n4HuuV3mgbVjpG1g8R5RBA5Y42RoO7 rw2HYXXGf7J+eljCo80KYaD+pB7iy+ykLT/fJUj/ZfY35XKar4Q/kb8pw//I vsPfNyZ6Y7tbO6Ifhi1ovRnm9WGY1+cf+Rsn0HnA/lR8HkSK9WL/LDTwz5Iw y7dtX9nMt4wJAY4XYX9TjhdheCidF9wfnxe/yV+sPcVjcP10Og+4Pp8Hm8k/ Lpf4u75hIb3DUeLvDcR+gOT5pfY26Jsmv2f52PPJsg3hQ2NgJPH3AWI/wWTi 71Ziv0H/Xc+ezdkYJ7/PJ35fX/B76XfvcultfAXLKAgl/l1V8G+eT5F/L/FX bs+Av0o7w0LCJ8dP8PccP8HwNOK33B7z24fkDxpB/JPLOxD/ZNiAf8Jt4pdc fpj4JcPML63IX7c/yb98LrH8u5j8ITjekeWyERS/yPr1axS/yLANycPcHtOH L/mTLCD5l8tPkHzL8DWSX33FeQobSX49I85bqcecsO3NixGTkyCb5Nep4nwG d5Jfn4nzG9bce/r45LFQ2T6vN5Yx6xtwqSiuoQX5g44pG9lFk5QIa2yXTOy/ IQ06kbw6Xsircr2XCPmT5y/tDYQfCZuT/Mn98/r+Jn+x1SQ/cjmvZ2Pyp2P+ S/Id+//J9lm+5O95fZ+Sf2JfyqfA/ibrKZ8Cw6Z0H2Y5I5PuwwxLuxXZd5m/ sJ2f7MdSzmB+EtT8fknv5DQIonwF3F8w5Stg+CHdl7k/ppcfZL++KPLfYk3K f3tU5MdFDeXHnUf3af7e4D4NXcX6oT2tn4NYX1xO68v8pKm4b8PQM7/7h2/9 i/dWHvJ60i0N3tD9+5i478A8un/PEfdvyBj0c0RszVjZP9NnuaD/3m86nwUe dP+uKe7fMFC0Dw+o/QX7qv+7XStK+gN1emMR0Pl1FKw029Y/cGQO2Bwd2aT5 hiRZ/lwx9pdPUhLUmLuz6VfbHOic8rJ+iUUJEDiz+7uF1bIhhPIFcP3+dF/n 8TF/SqD1+UXx/lyf1kvCT+m+zt8b3NeZnmR9ojcJx9N9nr83uM9DNN3nuZzv Q9NHmr8o9yUb9lC+IPbDaEP5ghim/CkStib9EM+T7y9g5TXm38QcqEP5dLh+ Bcqnw/Br0ifx910FftGf8Osj8I9VCf/MV+v2d6txtmQOTKhW3bNDuxjpNyL5 2lCN5b+IbOjdbn6ZcTHJsrwH6au4P5avl9D8OT8M199N+WEYtqD8MAxvIX0X tyfoMQXbJ5YF40t5YB5xusYXcy3eD/nxPql/PpB+DUm/BmWEvhGUQt8IW4vr 9yBn3JwXMYl5Uk8S/OWdWes8jYSfre9sey0wDwdv+3x3oqUWNa4rypQp+H/Z RfvU6oJ1/f+7TCseKEh+02I9AQPD1J7kO7miPwm3O9/5hM0vDez65t64i7EW V9YO3+IVpAHfmyU+91fnIcfDMB9h+V/qZUj+Z3i2v9+Y66u02H+HjeXUf0o0 qRuztdSBPPzqtnf8w79K3Jk44dT5HUpZf/ugOQV/Cglf2Vezv/kxpfw97Ra9 Vn2x4HwMVPVc0V0p7xNcn+8TDI9x7b3lh08W9jtaoerovUpcPMQt+296kR5p z9danzZWTUHPFW3K17+jxCC4eKh1/xhZvmi4WevQQzF4teSbLR83KnH2oHl/ Bz+MQbPF6b8XDlVyf5Kv8n2B4W9/Pj8YOTAT1t4ff7z/HyUu2rypdvycTPgz yXrH60ZKnq+sv0PgQ8JBx9t4HFmlgCatbbObn1UyfmU5xy8wfIvuHwzvndHv rPqiBsq8LqO0uKHE307D6n+4rYESdyP6mPYpODf87y7wXqPFpj33NWttn42u wn6Krcl+mkz8l/e5Af/F9qee9p1nmwm590KiI/tmY7awHwOQ/XjcMgU2LJMv z413exNehNXMB//Tjj8Hd8pG+y4x/nHd86FDiq3HuRtZ0t46s9WqGa1WFcVZ brKoMnF5yyRpX3Wicoa3ULl/DZxhfFopv/vTImB5TQ+VhM/XazBq4uhcCa+z fPvVfJNCwm3nnz1z/6EKJ//K7zHy2EucYtrhQYynEtMa2kxLXPcEn03yNQt+ p8JnV7+aVbp7Emd1zTHv+K5o3I92D3TZVqvI7+Ls8/3zlo7LlHBwVMbMTc1y cHCQS93b117i7x6hrTx+ZmF+0ObP6Z+eY7BLz7efbXLwtP3ymuOnncD361z3 lKgWJr+fvqf+oKZtw/DCJ/fZee98uX3p10HjAYPxSHjQw7C+H5dngtuA5w22 93zC9z3oEpRnY5ru/+KcwA8Y4EfChF8J/xX4lXADT6tOL2bnwpk6nt3NejzB 7ZesdyXvUsDgnQMtWk5EbHe//N2yS3LBq0nqyMAnt/DF8YdzrvXVy+9LXelk XK5WvoQH37t/YV5SEax57WL6cLgelgT0V/l0fo6N4p9Xrt8yH2ye25aokPMY y5rssYtLzodIN1fLcTd8seHjc4d6jNPDbIewnsaVruI3og+mGxq/hJk+GHYh +mDY8si7hgvPqXBGi76xI7a+h3tJz5QfditxUKVepxUPPsDp6O+DB69R4e7P xk3V7b8B0wd/z/TBsBvRB8MvNpXIGl0mB78v/tUy8sZ7+JpnmWn/NAtHRK7e c/31O1gVOb/swrBsPJk9tcecMH/4SvTB33c9pm+9OzgUQ+a2Um5Z/QYqnD6y x876N86sHL55azN/7k/69TC9MPyY6IXhd6Ou/lB2zIQQv8W79mr8GD9ggB8J E34lHEX0wXDfwZqEhZALaxvseTT0/gdotmz9zK0rFFC5ZN92mza/gy9mVVQJ prkQFTthwLWRAcD0wd8zfTDM9MGww2xNuo2NHr5tc7pqav8expi+LudulA/p l2yG57Txg2gPv01PE/Jh1dfso45GbyAy+ZHd7Sp6eBs9XBOeGCDpjPiNhGcI fiP7IX5ThEcq3/bLplGvv3lSr7fS1GOCWaZGwntOOI++5Z+HdZ7fjflWWwG+ DpWzpvVNleWd6p0x8t2eKOFRP2uF3yyRihsid1rnVFXAZ/fBQaM/pOAMu+ZJ N2Yq4H5h//fRduGyzNEF69BRfC/lyNeifQm3+mn9STE3EcK1ePtASC6sqpyv bbA9T+qlzOonnmu7SCvht2Hfbld21UjYdsv84w8K5MNZKYubeM/VwMlPvdsG F8iPQ7vWjek/QwNVJ8XZJLtq8e1H3/TxBXJW0K0Ua+tNSvm9fqK30d7pCgl3 NzuVpTigRIdKXhfaPdfAFNe6j3oU7M8ug3cfziqTB99K363T8kqRnepByoJD eutMCe/LvpMx42EW7ir81cB9US7lYH/xvYTNWqfU+9I9Exy9TZ2mTtOASaUV SwfMyATTXg0fGFvlQb4Yn6z/U4xfwvkZzl+aLFHAwEsv1y8p6O+dwI8sJ3yC AT4lbDVp2N5OZ4p+o+e++vr2hgZ2LlVcqFUlD2pWeXTtl67g/JrWsuqJCD20 pvzyLSmfL9+v87UfJjRYmQ/33nnPXPAzF/LG/fHUF5RzvnQl5W9eM7G5rxEW rNfkIXUf3NGjMb1PMEK8T4DD3Q+cLZuhw9ZT8lb5TNFhz7/W9xOH6dDR/FNw x0g1vj0/9s35sTopD/kt9jh6p4NewrHNyy6NidFjn+b7Hjjd0eGnF2W3Po4r yrfv8/FGY4fnaoyu2mPghRF6rCjeB8Bc8T4A8nsGVcR7BtjEb+eqSrU0ePKK fZ/p77TY42/W5esn1DLPyYhRK02SD6kk3K3Oj4jFh9V49dwZ3aAINU781dZz zB4Vdh9RPy4Q1Tga//a+vVuFp0eX3g231bjMMbF52RMqOf6H3c4+6HZWLeFE eh9hnXgfAYfaLl4wW5Et+5td5mZavXa5uG9Uj+pOBe2PqGSzamHbXJw//Uqf EnfV2Lq+37NPadk4GFMeVP2oxm5uY6f2Tc3Ga6srfal/VY3DXZoaJeqyZX8v s6PiY3vkSpjjiTt27HCk6UI9WntP+H1vSlGewtXbH9cbXDJT4pftZKrT6rTp MTq80WfWvOkXM/DjmTFG62rpcMcp1/Dyfhl4M6pZSbvJOrxeObxFnxHpcj7O Lxvf0Kf8w1OdauRWK6AP5ie1utRclLVUj7Wz82e/iHyCASU2d6uxVY8+ffqd s81HtFzobNn7iB6XifpQk+o7ivbgJLXHfu61fJYFdHWS85H+Cvt/tmmx2TZd +p1X8WvYblnvdHDb8/vGlAQ1znzSbdXZmUVxK+lifWA7rc/MuwHtv3TOld8T /mEA4b+7wD94EP7niPWDw8XXD2bT+vmI9ZD90XpJ+LqgVzAjen0t6BuSiL75 /Ytsou8TC7ObzDyuluMbL+gTbIg+Rwn6hLNEnzaCnuEi0TPRp+yf6LfIz17s b5hB+5veH4HRtL9jK6w4sTpVCwniF1tm3J4+oJwO5nc+a/W3jw79R1cMG1tQ /833Xk/8j2txu/CnhVvCnxa9NlyzajdUR3G1anx99qfVg5Z6CRM/kOMhfiHh E8IfHsOEPzymRYf+mNgoVvpzsH/Ew3oND5ruysUjK980rezkB4OPXrJ+fzwX E0rWavBq8x9InqRdUfFkLrZI8+1VfldIUb5a0Z70f0iY8ORp6TexsCfw6qLr Frl4ivzxg6j/KvdWfv/4LQ2smnw90E6TjT+E/zQsI//prE0zy8501aNHam+f gAW52FO8D4MXxfsw+DV10bbKv7T4wTq0Su1luZhN/s/CD7pAriP/Z+EHnYtN LZpPbm+nk3baqU0+3ndor5ewv2gP3lB79D3soO+pfVBQ+5lifMDj60Hv1/D4 qH2JH+pfwo7UP+szmtP4GF7tX/Pp3tp6jLn5pYWzfzYM1xx5kftWj09+DrEI dMmBpfPff0y10uGvllM3X83OBsaXuxgPML7c6D2dagLfaCHwDQHkr75C4Bto fZDWByo/dqz42DFd5jHiPGOlhX8xKIV/sRyvuL8kyPpTLvZIb/IrHkfVsaof ukEFATduJjR4Hi/9uXsJ+pHfS39riqeYbDbRsqNbUZ6B7jPybS1q/AbtA0XJ uOdFcbAVaTwK8nfm+llEjyxv6c80eFROHS/jNkyJ/toSPn4R/S0gfDgRv+P6 HqFrnaqNTAf3av2/KsargPml1PPR+nL/02j9GV4m1gt+0HrResJTWk9ab/hH 6/2N6NFH0CMw/WUX9++HreTfz/IAj/cdyQsMl/q+zXVlGz26Kr40O7NCBQ3L Z5onjtLhyO/v+mc5q+D+mRlWs1vo5foQvyH9tRqI30g4hvjYX+JrxM+Q+BkQ P8PXgp8Bn+88Hj7/GW62K3R6l2Nq/JXzyOzKYhV8DTvg/Xa/Cj+JX/i222V1 wwJ4bfmbgctPqWA4yR9SfiX5RNoVSH45LuQX8Cb5J0KcD/w+EirofSSk85/H M4LkA4YXPHi5/GmHXCzRWq1uukMFqzu0/l3bKhdHJhx/4H9OBVCqZlrj7Gyc Nux6tXkF5XVbXC0DmdlYoXlagwqXVMDyC4/va1bheQ50nsMecZ4Dnecwjc7v E+L8hpVC3pBxuGyHyBHyBlwT8ga8FfIGkLwBHkLeKMoHIuQZ4POf7Sg0X0nv fP4y3FvMD2bQ/OqI+UFZmt9CgR/Ia1UMP2BH+JlO8gHPP4Xkh830/hWfp9wf n7cMEz3IX6IHWEn0QPQDYUQ/x+m85/4aCXqAI0QP7iQ/1KL3u/i85P4+0XnK cAOxX2A47ZeSYj/BEdpPFP8C7hT/QvtD/rag834u7Y+H4n0K6b+/qrj8wO+X gS29X8ZypuWNNr73IvWgfdMyvkNLnXwv4t58+0mzjfQS5vtAb3EfgH8CBoY/ ivuBpKca9iHly13QSjsc/78t9XdXtC/fm6D+JVxTfC/9tHi8HcT3yONj/1o9 jZ/hGRPC3L1vFNxz0h9vOJiowbFez3qsKpATL/SP3F7ukwZbDF1+uMaqArlj sNfTDXfysEXbwBjV6AI5pezu0UHl8vCGx40RWb0zcOP5xGAHOy3qTQO/Pdmb IP3ONJ4Zx6cbhWLl2Tdinl3RoP13v2d5UW9xUfXLYAlabF7v0I49QW/Bdq/5 zvA+WqnH+bOr1zddYy36RWhrlRr0UurvVaI9qEDtdY/0brPKMVT6Wyt3rWtW F9MhVGOR2n9EHtpUTXp8el465NYLevzrqAavi/GCC43Xc2VU+Wd1M2T71Svs D9xrkgNfV8/erUrS4K97R62SK+TAnxf/7dwaoEGThB6LQq6q4FqlHSX0qRq8 fab/714XVdCuvoXR2q8amZ+vHeFfR+vF+Pai9WTYIeJe9VVdM/DN09lbRqfl YtX2gVWO1MkgfbMCU15vLB3+OgHL7Sx3/IiHAu+K96Kw9ETxXtQo8V4UDqX3 om4Ouja97M90mOFXrkxShgIr7Z0S+NElHcq/uzPn30sljhX9wXvqbxz1/0rA YGf1n7nvjAS819BvkENPJdhZBqTbf3uOpYcfWt57lALK34w1OXHZGxdfK3kh eKwCblF/k0V/UIX6KyP6A5of0Pygupgf2eMUwPT3StAfMP2dFfRXIAeXapj4 Ui39wljuPt4lzbhy3zxgejwo6BGYXpsKegWmz/VivYHWm86XPPhQM/uJXh+C v760Ovv9qgbaCXqS/vz9i9Or1IdFCfoEK0Gfsj0rUR8WUP0soteygl6B6TNY 0Cd0JfrMEvQJTJ9rabxViR4/CHqEYKLHcEGPUIXo8aKgR/AkerQQ9AgZA7ov eeIWg3sjov+7WiCncDzPfBfNjCkN9ZgiymEXla81Wbp0hDYaf7sdDtH5qbCs 448nVnVi0LvBu2pl5qhQP/Ssl8+KFHS/8vZz4jg9jOnU/VGFcSnynbM06m+P aA/GOpe4PaXMWai7oFUf+8V6SCren4y3mSPGAxrRPlyl9t8/3r/+Vqgek/Mb XspZkI82Zcw+xwzVy3cMMwZ77tA0ypfw4bUN3g6v/Vna89wL1/E9JC8f/qWJ gxYzRX35jlI30Z6E/9Waeu5d13zY/XZ8QM1Nepy7zn9y7fH5MLBDTxv/d3r8 IMYDqTQe28IPQ9Csc037amo1UPsSHzxehmNF+7hHtA9zRPvYT7QPb2i+8aJ9 /l6+40TzlfCCJjue2A4v+m3X2dm27ho91Jvqo1rtWSDXFp8P8HwGUH/vaD5J 1N+m3rkv2zwqepeq1FDHxcOu6eHEopsll6RpsUKn3R13WeVLvz2DeCTw2PXx e+cwPSa4bcb0gvMJys4bdMBej3YN/gw7mZMv9R5ZznFl7RblQ9q+N/fOGueT PqfIL3Pg+aE1vlfTFtx3d/eIrpIo7bnlRf/ST8Qgngmpf6D+kfqHMaJ/6c+Z IfrHFNE/8RVZn8fL7WEitcfjz6TvDcZv2B/cLD4eMOgfDPqH2ZXzmiu9k7FM /JTmWToVDmzntHjU32Ts/DxvyPBuKpzWobVdfGaM9GMQ8mUMvG3ZfW4Tlzy8 c7uCn1KXiRVfBaSsjNDi0J5uLyzfp+HxUQfGO6zJx2zPPz2Dt2dK/LE8e4fi ecJIXk0v/M3HQeJ7OErf8/sQ+VRO+jgpJ3F72aSPS/7m8afFwgS8/fOee4lq 2egyb3JyXbMIXBc44MTLB0V+sGvpvRvW75Y1TujavOAeMJr8Hfj+/mjdpeFb XkdB9xU+W5Qjc3ANxaeEiPgUqR8uJ76X8Zub6H7L8U5q8j8wvtqig+frDNRP CvW365UPXc3CukeVzJTnuIF+EQh/kv4N4qFkPsS6Qt8HXUl/yesu8ycPCGpf fnjBfqF4Ji53pHgmhm+L9YQyYj3BYH1gQPH1gYbhj9v/aKnFOYvC1jgN0+E+ uo88IP3nKfPWpm8m54HlyKWX46/psOrDkbvDa+dB6jCv1c0StHh27L24F7M0 MMNjVJ3+Z3Wsf5T6WXdx3uNski8qi/MeS5N8wedLzz9e+ZbeSrQX8gSQPIGL WlssdW+thyEDvQZ+uK9Cuh/DSSHP46o419+f+urBd83jJpOdlRhz6sgRLehh b7/mYZGrlNjDJmMMrPLH9y4n9+nWpNE6HKb32jIwdHPu+Xuzv+DH7WW8TWcm 4vp3q07UW/kJb4ycUffZ5UTc1/dP/PahpzD4heXDGbeS0P+hZen5ZV+g7YAt tSdNTsLNfQrL4ReVnxDlMJrK34r2wY/aHybaB09q/8HVD+WG1M2X9urtpQNq fksqgt/U3T7/fJt8jL++/lDH/R5sv8V2xe23GFHcfotA9ttZQ5a0+jBNiSmP cr/5dA1Atr9OF/ZXPEX21yvC/oqNJ0yoFNZfgUuvbgl48PMb+gn7IpaPK7Qv YhNhf8SJwv6Ifpmpa6Ods9A3/VF22++ByPbXucL+imx/9RL2V3T1CakefE6B e4792hz4+SDbu7F8cXs3diR7t6nHgHEbLTOx+spFw2u//IxvhX0Vm38utK+i i2vl8OEbM9Fh5rIPiok32V6PTmSvNyZ77mphz0UT0R60Kd4elKT2Pov5wG2a z0oxfvhM4/8i5gc7aH6NBL7gAOGrKdlnOxN+PpN9ViHss7isz1jNuvgs2L9+ W8mvflcwRPgzwNPi/gxwxE74M9D6wW9aP1oveEXrdVesJ2yk9XSMSfB791AJ 3o/ubCnV5hZOFf4YcIP8MbyFPwacvSL8MaIDnnYvodXDsIDxmqHLvmCmyQiT 7Y/ywXHWhm+dGwXiaLIHV79caA/GKLIHnxD2YIwge3CwsAfjQ6JnvpcxPTMc I/rDVqI/yBL94SjRH9ufUVnc/owG9mf8TPZnmi9+elg4X6D54mUxX2D/k1ti vsD053KkkP7AkujteeNCeoMdRI/fdxTSIywX64XHXQrXC2i9kNYL2P+E1gt4 /4wV9ABED0j0AEQPmEP2+vVEv19mFNIv/Ef021bQL1Ql+levKKRX9i/APPIv MBL0DavIX4HaA1tqj/1XZlB77L8y4kW/JdoqW17Q/KC6oEeeD+wZI+bD9LmU 5kv4gzGHBf4IX1BV7F/GJ3QX+xe+0n46KfYT+2fA3OL+GXCf/DOYfocI+gWm 1wOXxfoxPU+m9XWi/fFO7A/2L4GZ5F/C++Ua+ZcQP4X+gp8C+8PovQv5KbA/ jI/gp8D+MBljC/kpZNF58V7wcxhO5wXxc5gF4jz4Lc4D+EbnAZ0XMIbOo7fi PIJeAgY6nyCb7D2sDzew94DJneyvJ6sEwJcNl3ratM6F9Ka7XDvW+CP151H0 PnSmeB8ahtP70EPEfR+S3p7dndIsCVZEjxigqJoLfp7KC5M12VL/fajpz/N7 bXIlbNy/8um2QUW/kUFLu+6/kA0N2xz8uNwxh/XrRe+siPsqBtB9lfQpSPoU 6f/aneSZ6UJ+kfLOTSHfSPh2iCpg4tss3HnY2bNqRz04p2TOSg7OwphrHf+5 j9DDwwOjHkROSsdjNUxqpJTTgxazhh5/GIqD+kWdfRKYD2MsqrzPmfUbw2w7 9Tx/Ll/6f9QW9lf4QfbZ9qTPHTu78P6JfP9cLeQLZPnin5AvkOULuv/IfDPk /4kvyf/zmJCfsCXJT25CXkInkpeqCXkKM0ieYnzwvYHkPQn/bbKnV65bFj4s 9cq+vWc+ehF+9gn84Ozi+MHeFt4m/X4XvZunORe6cb1VCo7q/6S8faU8/Dzf cmV2TjKW32T+5/V+DfZr02z5tSfJ6DI8/9ieIWoc6jM3rHFAMkY0HnYkvbYG eX2DSF/WjdZXTfoylqctlpVcaLIhH9XF1wMdaD1CxXqgW3F8o1vx+7+M29EL /w08U+H1sNKhP6DH9W6x1yAfE0X7wO3/J9oHbr+WiH+T9tVFwh8VTMkfdYPQ X8CP4voL8CH9BfuNt/NtNvqNWo/1S6x09/FMk/q4Jtmv7i8KLco73F/gDzYX xx+EEP48RLyeHM+Zd0b1bvRNgTor3R2cByrxgPCvBXfyr50j7ndQqvj9Dmzo fhcp6AHuEz08EfQAx4kenAQ9QBTRw/rp1Sr0fJIHm8QvPhX+0TCwuH80GJN/ dGNxP4CFdD/IOPBps6ePHkyXWW+y66tjeRyPkzzuRfYpzsflQ/5abG+2In8t hv3IP8tJ+GdhsuBPuFLwJ+lfMWvOzXCHnQpsS/rFskK/iBNJv7hI6Belf8Vs qn9k3fL6rZ8fAN+dl52VFxRYupzzhMcRHuBVcWvjTwcUWFK0B+WovbQbhe3B UmqvDPHbr4LfYnvyF+Px0/yK7OnEX1fT+D+I+cEcmh/hR+Yru0Xxm2y/cBP0 gNUEPcA+8re+LuhB3veJHoDv+1aCHoD0uUj6XDCh+1Yp0q+mEn6XEf/nfFpK 6v8n+XPzeOaR/3Z1sV9ghOegJvm6aJzvf61kCz8VvLOpVWWqWQzW2hv30m22 Chj/zgL/0IrwS+sF5wi/y0gf/Ev0J+03m2k/fhX7EcrRfiR9IjjQ/fAW6ZuJ foDoB5YJf3XZ3lzaP7q4YvgC0o9AL8Efpf1JJfgjDBb8Eb4I/ggVBH+EAbS/ 14v9DUNofweL/Q10H8UX4rwAuo/iLnFeyHgFzj/zk+IVGF5H+3I17VPan0j7 Ezh+wUjsT2hA9/dZYn/Ccjp/norzB/j8aS7OH6D7O6aJ8wbo/o6zxHkk1y/Z 5FdmqbV6GFMIX4YLN+t61F1S9O6HueDvkFKc/8KA4vwXDPgnmBH/ZHtURHH+ BQ+Jf7nSeT+rOP9ifMl8ToRPCXP8hU/x+UNrmv/p4voKMCV9RjLhg8578KH1 o/MedtD6udC68K+a+GVJWo8nxE/703qRfgVIv8L6UplvbCPpTxm2b3Rw288g rdTn8P+9Q3vVejkvH8aKcikPsNzxUpRj+LHhPe8NU+GxQfM6tJmvw7SNB8Zc qaTGLZPN69l4aNG32idFya5q+V3rToseKIyL4mX+Dbk4tLdHNs4ZvF1vt06H d2v7XCm/Jwfd1jlf231Wiw1m9Lw/93WO/F7kRcrA0HW/sEWeFvMpv9hWyn/1 l/KLUT4rdFU3r37BKA67b1u4ykqvle8qPvZ9d6fBGh1+bLHUfxvEyfb/Nmpm emxcrBzf0kLCiUW7u+MS9F+0Up9eV+jTcbfQ58v674U+H9NInx9Z3J6PK4rb 83HDu2Wv8/PfQKPOpZ3DrLUyP6Axtf+wzT6746XioMW87g6PCsYfJcYn7Qdz xfhgJI1PTfxkGMlb/sRPTEjeEnSbAT8If9EC/+BE+L8t8A9nCP9hYn3BldY3 VawvbKT1Zfph+mD6eUb08Yjs2Yxf3VqPGvmBWjl+1qevufwh7WNbBR6O9bcK qpgo7Ytlyz879nZdioyrFHGfKbBv8Zth154UnJ9kfywt7I9SP79WtAfHqD22 5y0leawinS90/kEtOv8OkTx0ic4/Gr+cF41f8k/CDx4R+AGmf8IPtCJ65/qE b5wt8A13iN4J3+BO/qEfyF9jE/mHXiR/DaIHJHqAP0Sv3L4BvUJS3oX7B06H oEJ/fcFMZw1MI3rl+kyvqYJeYQ7Zp7jcwD4l8yMakT3Ji+izGY2H/a8eiP0F b8T+knwlfkHH5UMdYmX7TL/2/RbEpX/TwpEpwY5uc1NkHCCvd3OK32P6DRL0 C55Er6cIf1FEz7MIv/UF/5D9pxD9rqf1CSH6Pkzr90rwK1mf+JUcL8tT7A/l H+ufUClIB7G7Kvk7ltWBluhbzu98HZcLM9Mwa23p2Wsdi95JN9K9jX/2Q4vm 2+Z0vlc9rYg/Fn73Dx8u+7vXaL8eL/b675VxcIy0H7aqnNIuPj0Yjz3IMnnp pcNGAoYjBPP6DEiu56lUFr0z5UXtXRbtSXvihpA530o4pYFTeMSLj9N0GLC3 i9We8DRpL3lQuJ5p0DJtcNfSj4veYdFqxfgtxPjl/t4k2kNqD76I9qS94rlo D9uJ9sAAH9CK8CHxXxwfcI7wIe2VZgFHxmYFYWq/SHwwNh+eifsa9hb3NahP +Dou8APMvwcL/MAVut/1ovqmhE/CLxjgDy4Q/rh/J7G+kC7WFwzwAy0JPzyf qapZ6JGqx5rOfVaZfSpYv0jjmLGV8rHNw0bOPc30+O5LTt9v9tHoUDaqZhmv oncQyZ6PGWTPZ3uj3cd15XRXw2D9Mgvb2GkF92vy3+H1Y3vHArJf+1L740T7 0IH8U9ifYAS1t1a0BxwvwOs3RYwfqovxQ0MxfjAX44eZN3dlWql0sLpyXOKO lTocIeIXoA3FL3Ql/wX2hxkv+sNNNH62t88m+z+NF8YSPsZQfZovGPjjQAXy x2F/hxfFvwerKqvjl1jqpT20W/7Jfa++xMOuIe8jE26pcJLwTwUH4Z+KN8m/ 85bw78RFc2ZV6meVXpQvmuqPIX/WQOHPKvkD+8ufEv7ywN9zeQcxHmlfrSzq 40nyr/fwVW3VdU/HhtkXK1R9rcIbYjx4l8ZD40MaH1xd09fiSad0zP1p9PDx XrVs7yj1/6+TX+7Nl4lSnuN8o57nylUYVD0f7T6l9zIJSJf+UXnF/R0wRnwv z3vOf3qDvm/T5GBAyRWpspz5t43q+JQzznosufHYsPF/0mVewURxfkNF8h/i PBtbissDwPLAj/fGFzPWJ8p4Vz7vz31p1XHHwSw08EfmfMfSnxvtfr1LVBW9 68323Z+U368Z+R9zfU+RvwApf4HMq2NC+QI731xZ7V7dCGjbpOLf/8c5faJ8 OWxn5fnUfpy8/PjedO5f2m3fr118on33VKmnZP5hQfkP2T/TmO2HlSz2bjmd Jr/XrGrW/eS/DAm7Un4IvcgPgRcof0QdkT9CzjtNvEeBlO8DKd8HUr4PpHwf PB8Z98L4rkzzaZpvVMHRLlPmNeP2Z1F+Ov5OI+aBziffH/JokCbPwY7TnmRm eGRIeBDln3go8kPI8/Bw7ITK1u7p+P3jgfCCP9kur1+qeL9Cju835c/L0ix9 WG540TvrTB9ttm3qd9k7Ho0s+r85cy1Wfrdp4bP1f998l/WvXy5X+/HyV7jj T/vpVwvmK/iuv7TnRpuUCsof/w7avnNtX75nOrYk/fonsv+uF+3Jc64v5b94 QvPj/AnNFg3Ju3cjBWdRPgyuHyTmK+mJ/QWyab58Pp0h/HC+BetOPua3lqZg R8qfwe0xfc0X76lguU53hs3eHiPz83F7M0R+Gcaf/J7lu87F8Sflbh7nD8qX VYHiBWR+LFrPMgFev175/UOt8L+X5brlFXNelf4t10m+Q93n0YtRfeIxROQn QspPhCOW3A9Z71CUB4/bCaN8c/zey7EK0XnBBeucmXJ8wjx9hBwHlyfcWHU8 1TkSc400uzs+DJHtaMV4ZJwD6yMiaDyMLxOaT5rIrwTNKZ8evx9zhvrPEP1L uYbL1dS/QvQv4x4IPxKWeVBE/ifJH9TF8S3rk70VBxS3t+I0sreSPRUjyJ5K 9lesV9z+iifJ/rrjp2vT8eYKme+N6aKlGW68W+a33P/eWWVPB7b4ir6Hgz9t +FqEZ/mO/IAp+6zbhHO5fJeH8ZlA5fpTwt64l+zpPP9R1J+fbbezLxyzZP62 fue+13w9RClh9meYRPY39lf4SPY19m/ILm6Pw5dkj1PMvfD/P5lvrbh/zasX 00X+NJwp8qfhDILn1xb51OS798fb7Gz/DvHiq8GvQjuFSz0zl28Q5XCZylkv Jt+FPVHse2lX4vLtJ4p9L/VqleeHX5mQlC7rVyGYyzfV7lhhUEqWzAPlXfuS S1VvpYRdfT/W8i04xzn/2vSmgc3+88yXMJ/ziWOenV0++jvsJPrgcqYHH0EP EEH56i6IfHQyj6Fpk3IOq2YGQkPKX8d2SMpvB5TfDiyDXF47VA+W+eB4PyaV qbKiZd9A+EL0wOX9iR4YZj73fmGVu6My/sJt0oczXzWgZzDgZ1CF+BnX5/Ev /tpqa7h1FNSj/Idc/p7on9eJ6f+boG8oeVbwP65P+TqB8nUC5esEytfJ7RW9 J1p8v4CC+A/l84SzcxpPPHLqh8zTw/jaSvneDPgPlDUW/IfHY8C/wDhV8C/u l/KTAuUnBcpPCpSfVN6HRhI+ab6yfS73pnx2BvyM8S3rNyN5g885pq+ZlI/M QN6AziRfyHOP5A+GUyhfKstpvD6lBT8HuxML52b4+Mvy6ivE+cTnoMH5BGUe CX+tUWR/531Ult7vq0f+WPfIfk/5huEF5Wuj9qUexeC8gUuUb/Ud5Yej/MZA +Y3B4DyS37+lfG9V6bxn/HH9mZRPjvvtIs53qEjnO89fTfIA489AnoQAkhd5 HQ3kRXCnfM3sh2kg30EcyXfF5V4p38Fvkv/ZT9FA/of3JN9z+4GP1txVhf/D 2Ikvxq1fVJQnlPKRwwAhv2NrIb+D/Wm/dj0U31i+g819vs67uqeThJmPnhlg 3Wd1RBEfdSP4Dd0XalC+M8pfDpS/HCh/OVD+ckgg+Y7nayDfgYF8B78ov7S+ fmF+aWhL+adbi/zTjH/ZnsH9Q67bPHpPj9uvQvnaCH8yjsxf4A/iCX9+dF9h /HN75pQ/zuC+Alq6n3B7f+j+wrAR3Qc5XxfFkwDFk4DBfRCO0n2Q9bl8X2V9 Yf0uF0J39NXKeKdqgQ18FcN0mLZrn9vtZyrk+MYxIl4LZ10p1eSKSx6+vnbI yL2WGnfMWXNTsSsPPbwq+ENdFfYrvXlyrLMWZ4+stsVSrUJbs/CHwxfpMNjq 8WJtMyU6WXtNaDJNh6qJmuSBN5S4K8P+i9dxLdateX5qcKQCOT5xg4hHw7oB ZT9Fr1PirBltq628oMKAoCvBhz1V2LHNZPPFdkqMfnV12QB3FZ6y3Gx+f4sS OV6wioinQ5vHGwe6n8lC9xLpx01/qFAR97i/45UsnPV6oVePiSp0qB33aEWd HNx9YVeLfvZKDN+04FTLajn42Dp0ecQmJcKNJRaa1pkwZv3v2RaN1cjxeONE PB6+bTJlg8dkBUwc5G7y7ZoKL90bNWPgNAXUfLnPvvV6Fd69VbvBnYm5sPzc urJnuyqx7dPG30YfVsOsBa3ffH+qQo63+yPi7XDw/HRTp70acB220W90jKrg 3rxIMeGOGrZENp/VxUmJd1Q+E37fUsOp007pz9YosUXMlaVRbXQYYbup9aiy OcjxzGEiPhY942Y4G13SoUOdc6e1Uwvu433qRJ6fq8OJ9QOGrWucjcf9Hy3/ 4a1FY48FUXeWZmHYJV3kiwtxaD3zytMlK3LwhXjvB8bQ+0iLdz3xjFXooPk5 19jeY3JwGMXfPhfxt8jxtwki/hbtjhsPipuiB4W2kZHn+4L7etV+fj4ltRi+ OXrjj6a5MHW8arNDAT197HQ3rUNHNfwaPayS9bY8PLZn/vRrnTQwd6nOL99J i6XmPbscZqsGW8p/cUzkF4DdXYf1clutRJ+JIRUVnmqoLOJn8Gzx+Bm0pPgZ zl9xSeRPgOBW/a+XPpWFu483nLp8uRpGBg02CTmXhUErhtRckqMGUxGvg68p Xofix5Dix6DMg7IzfxTQR+nCXzUMp/wLs0T+BfhYZaZ+5gQFdMx0K+nm/n99 ktOQZxMV4JP0vfmSj2qOd4KjFO/0dUVClt8Btfzl/AluIn8ClHMdNSFttwZQ b2E6eZYapot4K3hJ8VYOIt4KKN6P40ewvogfQdP6DVYHuunxyxnbWbEBWo4H QY4HWU35c+S7qJQ/h2HKDyPh+FHRXikX8zCwgdp4S/c8PEX5c0aJ/DnI+XM+ ivw5OIXW+7NYb5xD61tWrC/+pvU/KdYfY0Q+GTwg8sngmlu5zzMuaqQ+lPCB hA8Mpvw8PD7KfyNhzsfTTeTjwT1EP76CfpDp5wLFAzL9dKB4QMo3h9o7It8c 7Vc8QfvVVOxX3Ej79bbYr3iO9uvp/F5Wpzcq8OXgAPto0zwskVmYfweHi/w7 eCLuSKPd1rlyvGe7tgscOCRXzveToCfsJugJYwU9IQp6Qs4vxN8/pPxCDF9Z /uOg5ass/Do7JtJToUHONyR+Ncj7Yb/YD8j74bfYD0jxa/iheDwlxlA8ZeLf piMv71TgLs3RRt2slPhT5PvDBpTvj/glOhTnl1iH+OUdwS9xDfFLU5HPCGuL fEZoLPYbGon9hotF/kEMp/yDfQS/xrHEr033WIzt0z0BK/19MNu4rV7qrcya O/3adlyP5/S3gw+uTJD2ooTWJtruDp8xtu7GizYF5xLhT/qPEX4lTOODGsXH B2VpfIRv+ET4PiDwDa6Eb3uX1EMzVNmyPX43KJnet/sp1gMOFV8P+EnrUWKS yO/E33N+J4ZPCXqDV0RvnO9pCNEb0RN0KU5P8IboifnTSYoPdj+WtGzshyzw j1h/8vwEJdqJfJTQi/JR0nkLl+m8zRXnLcym83acOG9hW/HzFrzpvJ0q9if0 pv3Zw7bWVjdXlZyPsBOqoO2s92/rjdJglF/gw/uuShkvTPsZXtJ+5nxW/D3x NzDgbxLm/FV7id8wv31D/GUm8Vuk+OpxxG+vUXw15fOEepTPs46QX2A2yS/f hPwC7Ul++SvkFzhL8otBvB/zV/An/lpN8FP4QvyU+C3YEb8l/grfiL8SP4Wj xE+J34IR8duoU5bGg6/lwatRbn/01Qr2m8hnCp8on6mTkPfAh+Q9ku9gPsl3 O4X8B3dJ/iN5D4JI3tsp5DuoT/IdyX+gIfnv5olKLultsqW/YdJNx8XX/DIl bDJ4eJnNzbPwVotD91If52DE5Tv11iZl4tMJ9ZXtx+eigTyO7XwrJbnGxsIY /6hb1v6ZWMF6WekZKXGwWrF4SaV2mVgiaXLjsx8zpT8g9S/hsz06Wm05nglO b79+2zhPgVVF/3CteP/wnPpPP9stYohrCjSu3b56WmgW5uR+vzj/YAqMrP18 zeSILNxK+fO4/RWUP4/h8ilTe899lof7bJLsnh9S4G7Kp1df5NPDuSQvRQl5 ifOPSnsL5RtFK8o3OkbIW6gieYvy9cn5UT4/CZM8BhHUPsmLYE/y4jEhH0IZ kg+ThPwIk0h+nEDjYX90e+o/S/QPfcV7lpgr3rMEes8S6T1L4Pdf94r3LOEA vQ+7V7xnCXdIfrUV44ETJK+WFOOBFJJnx4nxQC6999lN5GsFfu+zBb1Hyfos N8qv3EvkV5bjzxHriXXFekK6WE8cLdYTbhG9sj9/SUFPEj4j6AeJfoDoB4l+ IJLo95GgH+hN+X7ZH7IvnV+24vwCPv+qUz4/kjexJMmbrE+rVTyftJwP37// Ru9KW1HAp6efvN/6pR7xTqOyY6YcyYKGIRbVUhY+xWD4r8LSW1nyfh5F9bP/ 1Fx3s+dFcP1RJ7L85yz4Us7GcdGVq3BYMX/O2Y9ZUFm0B3epveTfhe3BL2ov k/ZHA8KnjvbHIMIn59el91mB3mMFeo8V7lA+Ypk/hfIRM0znP4SJ85/xB8MJ f33oPVUl0d8xek+1AdHfXaL3EURfdD+C8URPdD8CI6I3er+Y6FTSL/3mwHjK D8z4H0v5gC3F/uT9AZm0P1bR/mT64f3JcCXBH2CL4A+cbxOIP8AC2r+/6D7F +awZP7cpnzXD/J4Nw9GC/6O34P9A/B+J/wPxf3wp+D/0p/v9LMH/ge//7oL/ A9/3vwv+D7vpfl9b8H9wpvt/juD/YEL3kU/iPgIl6T7iKu4j8v7C8e8sf6uF /A0sb68T8jawvH1ayNvA8jndp4Hzc/P8d1B+boY5H3d9cX4Dnd84TZzfQOc3 0vkNUaR/OCrOb85/iSQ/8H0Nn9N9bTXdX9h/JInk5a1CXgaWl+sIeRlYHl4h 5GFg+XmMkJ/hIsnPpG8Aks/wvZDPgPOF9xbyGbA+hOQzUJI+xFHIZ8D6kO1C PgPWh9wX8hmcpPvLEyFPcv5QJHkSPtD9pCvdd2PofvKM7rt8n+H5fxDyNkQL eRuuk3z5mcZvT/KlDY2f5cdNxccHpK/h+cF5mh/pe2AmzY/Wu+jdecpPzjCt B2yk9eB85fVpPVjfQ/cXYH1PVcL/PdL3LKL1ukzy/3sh/3N+V/rVAMv3+0j/ MILk+0DSP5whebIW0WMgyY/mxekPSP8FpC8D0pcB51fn+fH7Tgzz+04Mcz51 ut/y/oEDtH9ovwHdb+Eu6aOO0n6j+zXYUL5blsefkX7mL8nrvP4sf74k/kP5 9OE98R+WJ78RP2H5UUH8g/gLkP4QSD8J3sSvtpN8epP4E8uvzsS/4ki+9hPy Nef/hZHF8//CB8r/y/I16S+A5ekSpJ8i/RUcJv0V8Tcw4G/A/M3Avwqq9LL7 b32BHMj+RCyntU+OSm6/XYsftxqFW+3Llf5sSxaV7bw5tOgdDH5vdm5374uB S/LQwF8KK7nNLrHtRp6s3yn95Pf6d7QyX9Ipkl/mk/zL+RIN9HsYT/o9I88a E5bGs595DjYbUy68VbSe/BpyuBwMyoHLjel7ca/Lgeb0Pd+Dl9D9/jed71Qf DOrL93YrE/5Yv834ayfwBx8If+zvtojwx/UZf/MF/qAi4YvLGV/8fZ2aEUtL 9kgAozMTQ6600eN4y7Ct/kPjpT8hvyd9qdc/94TKemkXq0H6hwtC/yD9S+uL 9tBYtAdjRHvSn5Djga6J9sBAnwHnSZ/B/pZ16H3emuJ9XmnHiomYO1C1Jx9y 6b1e1v+zv5owY+rBwF8NzMlfjcsN/NWgktC3QDmhb5H2iOo0PtK3SH9QA/9n /ED+z+wfW367tcn3FUkSflqhf+2SJZJh2o5L+0ps1qFDVV+PO3+SoELsuukn 5utQuxFV9Qr4A+sDeis3xvXooZcwvS8Ow+h9caovz6Neor6Ef9N75ENEfTCi 8bB/qsF7KHjNt/b26575Mh8b77tqnQd1M96cjwb5gjgfEVL+HlRWGbJw8M58 +S64wXvGcEW0L9eL+UYN0T6Mn13dWO+UD91edjnYMkYPuaI9+U54aTF+6S+8 TeATewt8wjiBT6wo8Mn4kPya8WuAHxhM+PGZMd3t8JF/+Hl//PNmBfyEx9Nd jIfnBzw/L6r/WtSHCaI+GowfefwBoj78pvbfEOxP35u6DIgacD5B+kt2FvtV 8svxa1ZvyHqmkvz1m+fNoyUtciScXzwflvTTqx17M6DNGx2OpfxYvF/Jf1P6 h/L7OT3Jf5PylwHlL5P3xKbEz4kfSf7LeUHXiXxoTE9gQE/A9MT7+Rm9B3xG vAcs7cz+7/UK9eAksK0w+XnG40w0sG9jNPmHVab36wz8u6CM8G8oepeUyo+S f4OR8G+QehgDf0LpB2ZB9vEK5D9oYB+X/gVfEq1KXCwfLt8jIn4r+TWvH/Pj r7R+DDO+G1K+OMZ3s+L8X/JvxvdGyj9H+wsN9hfy/ort5lpx1PlMaU/1rb99 u9fqTDnepUmX3V6M1eHz9R9iR67T4BvK98p57jgfLMPWq2LeD2qrp18NdhEw dC0OYwcBQzjpp/+RvBy/8k4p0x9hsPbcrRJvcxSQt+B0o5DpyehY4tIwvxc6 bCD4P9Ym/k/8W8bvM732Iv4dRf7OXG7g78z5ayXe7lE+bYZ5/J1ovKx/6Lvq dpRV2Vj4z0Y5KVt/BCNLLcM+FrEwfd+xak4F/Jf58+TwkOmrQjMK5P3/erUb nCPjV2p9j2vbQpUj7eBHMn62rnc5G7o4roldqc6Q5/9yS/eZP/IyyV88F1qk 2U13aZ4FBzbtGpv1OAd8ayzPem6aBau3jrxpnpID61u+6n4uKBMmHr59sc7p XNjUtqZtCccc6NT3vfNClyxY2vpf9t5WOdDqBHqoSmXD+Y4/wgfsyIa4t8oW v27mgO7FlfUhG3Jg0KiP7+ZfzoX0dTZNzCdly/7fvwa7tPp/pBziXPgbAW9H 5Hx90FWBa8/mHg7ukSn1BVElzcNUrlrJj/7sPBxX5pZSwhvNssrsss/Er2s7 9qsYkI/GV6qfuGCahf+lmz7Iqp5PeMzClST/acX5Ls8jXu8OIj4Is1tYflm6 IBCnt5sx50y1fLxL8SAU3yH9Fsf5PDpt3yQf40V9cKT67CfmQOUlBt5e/HVJ ppQvPUpUebjviUbC6H/gYKufRfuKx7OR4tPaJNcrfbrTP3zWu/H1mp4KdCrV Vl2u3D/Jz1/RfmPY4H1HnEbvNzLfNni/UfoPf6P30M8L/xrJL01PYFDqvFSI 3/L1XbtmWRhP74nKd6PJ3+02+ZP2ovdCuZzx1fFhWMN62xPQiPyhmC/yeNYL fzKJP+vi9SUf5fGuLf5etSyf01fpnD1ZJfv9PWLf0k9PsiXM/X0X/n783jAY vE8s4T0XdUO9UjKkPyjvt97Zwj+14kQrr8PqHFm+vPfCt9OM9BJmvlHGrtC/ EU9v3r+z/EeV9P/cu0PtPqFHjoTp/V35/m04+fdwOfsRMew4buIE41W5Eq4+ rPG8vhP1Ep5L+GC8hhA+GGZ8/CD/x300Xy7n+fYT84VKNF8u5/kyzPM1EvOF h/8Nb73yjj9Wezw04ovLb2hwJ+Tiz52B8tzN+DCjwo+t/tBXMdY/z+k3NBLl 0u/M4P1vmEPv3fM5b/DePYSK9xvl+UnvP0qY3ouUMK+T15BZRit+pcIF8t/n cp7XQyp3I398Ll/XJ75f370fpD8T+51WFfEdsL1TyID9qkhZzvP5zf5jNP4r 5H/25b/XFl8mJqJtfu1tfWdlyfNog+AH0Jb4wWPBD2AO8QM+b5lf8vkfSfyS YeaHq+k+x/yJy28Sf2KY+JOUs4rTX4k+BvkV4WO7z3UehWbhF8WGNYsX5eGq vi9LPrimgNc/ooYO9MtDG7IvsL0mjuwJE8g+RPkQZXm/zscc1/6IwXmei9Qj q2RLv+c/Qh8v4ZkPlx0yO5Yk/X6HYZllTTckGpazP6bEu0F9eCzybeBdkW8D dpXq5NXhqAYrNa0VlfUoX/LtMn2q+453Lbg/NDrknTg2T8pH847ZT1pnn43m h3OsPXL0sOJZeee6o3Q4RzdzpVtDDZZesqycTYH8E9Xyb0zaUTUarwjtua+F Hn/3O3q+zWA1ui5sVrf+CNYfqBAWvPhy1Fwv4eaUz57ykSPlR0cjkT8e11D+ eHvyx6J4TPmeDMdPtqV4TIonk/lPJtD9muvz/dqd7utr6iX6uGA8ms9tM+L0 CTXeU5r4+j+Px+Un3BI8BqnRfv2v2a9942Ue428Uz8btrxPfgyV97yW+h8X0 PeeDdxb54JHzwVck/zXO0x5Iefw5Xzvl72f8QnRx/EIw4Zf892AU+e8lifdE cBe9J5Iu3iPBRHqPhPmwF71f4i7eL8FB9H6JFb0foRfvR+Cenxve3m6nk/qe kCP7vX0qFOl/yB8NfpM/2vHFxxY86vVG+ndzf+fvHY/wXhoi7U/bjtXOqh8U Dq0/OdZ9H/0YSl5c3qvRsXCOB5TvK6ym9Wku8Au8PoRf6C/Gi3n03sV3yret pvxb4yjf9mDKv6UifMQLfMjx3af8Xq+K4wMIn7BT4BOY3iPEekBpovcfYj1g GL1P1ULEd0JXeu/pEvl3OdN7TDvFez4wjN5jmkv+ZHyfekrx4q8pHwPf5+1I /8T6IgP9E3ykeGUu53hlC4ovbkXvDfUV7w2xvxzQe0/A7/10Fu/9AL/3c5L8 8Wh+0IrmN5TyfTMf4X1yjO637/ZfvzHCKVeW36Z83nwfXq98jHUHhmJL22rq 34+UODXi4bH+H0KpvhInrHwXsmX6W9zp5F4rXl30DmbMeodnVesqcP0WnW30 3RcyP0JPUR92UX2Oh/1XvL6Mn6T87RJuu2XCkPOHzkLaSKNX91pGQOABr5l1 vK6Dtf+eH+HlIzgfusyfUJ30EXxetYnosi7qv1A8VP7+9b2PlTCT5iPOHyXM pflsF+OT+cmjxfhAS/Ph9sfSfGj+YDAfri/vq28J33zecb58vg8fIX3QYNKv jSd9UGXSr7Gc1Z7ev7AT+hCpz/sRsdz3/ly9XL81mxs+MVmux7hJP5snm2sx +uHsU8826jHo6fKGDydrcdPavoOjV8fI+1/3pe7KoytjcK8ptt70S4MZheP6 Bj1H96t0L0iLgc1M1q7c5g83Zy1ZGeqrleU9RDm8oPIbohy+i/HI+a0W44EY MR6IEuOB72I8PH4wGD/EFx8/8Pg5Pt72lbXuSgF/5vlzfzx/g/7wB/VXrrCf AOxN84sR48dbND8u70Xz+0nlNH/oKvAF2wW+ICLfxWX/JMZ/iVd95odtnlBw P8pZFBaozM+T96UIixdzEwvgDVttL2t7/qN9mYcnbnutqtQkAZJPbHWJ99Og feDG8becE8BqpGX76d3z8BiVJ4hysKPydqIcQl+UPz1hf4JBPooEaHLuyBLP FXk8PilPXa441D+9dYJc/1OifUyj/nuL8UMmjZ/1TEHFxw88/l3VzZvhxxjY XO7wk4598mAy5dfm8XB+7Tcivzb0oPYzRPvSvz9YtA9rqH0h/+bBOrOUA4qk eBxnZjfspp0GLZxPfugaHY/Xf9VY1ae7Br+OD7JcNCBB8qcxQzVRjbsW3OvC 5w3/b48SO/yYalnqeTKWGRi3ffKxbEz453pDlZSEbRybV0yyzcFc05jYdn7R WPl29x097mTjM5EfG20oP/YWfeOsCT5/Yc7Hyw1WZebgwEL6i4I7zrH3KtzP wV2iHGeKcnhB33cR38MIUR9viPpgkP+bfuNl/js+P6oQ3K662dWyBfIZn4tn xuxTXhyuk3CZXOtP/QfoJR/OtB1zZ1nlEHmOOkTUSXOoG1b0DmnbRXde2he9 u7e1aY+ctqe1Ep5pVP9n5XU6CZel9pnPTab2GI7VN/59cM0jdB4wYqG16h8M 69B42gDr16jYMblDyZP/YMykmt0exMaiw5iVM1tWzoUUkoe20/l9sfQCx62v 4+U5lXZpvtu8KsFSf9LliendH23TQPHxlbd3x3zMG3mhS1CMHsw1WWkr7uiw TyfFiapf+T0QHb4T+h9px1sl9D/oQ/qflDsbFdv3ROKIgIRvO5Jz0VTks0PK H4pH1hfmx0POjzeB5PV7lB/vG9Ebnx/2RG8lBL3BD+qf9aDcP4r+oQ7150f5 Sp+tKZaPD2ZQPj7qT77vMEzkAwdvk/G/vp69Dqlnl4Y/K+CTP21W/Hr15Q5U q3k/yHZ1AV8V+JP2ik7F8QetB6xJXfwpQfIfzmfD8gDbl1qSvoryW0l7EOXL kvC/x+ZTV87+KPHN+Xr+tk+7F/0jFwNFudTHcb4eLjcX9014Qfon5gcq8/LW LwcqMPKoaZ0rB/9JeaDuE9Ef45f7+yPag2aiXOqhub9oKid9F3jT/Zb7U4v+ IIb64/O7POV3YnnCIL8TcP4wlgfrUT4whjkfWBjlAxpmXufG5ykhGKDf1z24 uwY0letpTy8Mkflinxr/cxz1QAfBjZw6/DyuhdlXM1Zcfc/2H63MDzOI8uek FdcnQqmBJz4ogj5LvRCfZ1N+Bp0arCk4h4vrE6GcqF/0rgKd75OoPufrGUj5 aPKSZ0bPttXjwI2722hW5GHbwvkFYX6Mk++cGTqcm+tU6urZYJyw4XSJRHcd bpz4Lq/1gp9Yt3bS6pkF8o0j5Wcxo/wynJ/FgvLLGLQHe6i9aaI9WEvt1RHt yXw1nO+F89VwvheNGC/0FePl8cMgGj/Ph8vri/5BS/PpK/oHO5rPKtE/mNF8 uL6OxjuP6k+i8S6h+rVpvOPE+Y0d6Xw/Yv+45DTjBLp/a7AFrR/btwzWDy1o vbjcYL2kfaoq2c8cSF5k+xnLI1m0v/4Kepfyehs4nGh/PhSyxyumRnbLlvfG T0++LOlqmo2lkyfmb5sWLvU8tes1XuO4LB5O9diaYBaSIfOeLNvSYhd0TMVf pC9jPS7ridtQ/odOpD/jctbr1iueb0KW+0Te6BxsnQzQ8nVuk/KZuI3ih/k7 g/hh5Phw1sNxfDjDjMdUER+OmUJfiKQvxOF0f2Y7nMH9GSNJvziY6rM+L3pl zKoHvYKxIukbWQ86RLQn7XqsH7pB7TWm+HEeH88ngfTJVheUWWvb58t7Aeur uxSPT5d6pyPUH6+jQX8y7npt8fhwqUdkegouHo8uy9+YDJ7uvi4IRsZMPG+Z Ew+mDpadpyQFwRZ1B1Xuj3hIJv0568N6CfrCdEFfEg/vBX1BTUFf0q/GIJ8N x+dKvXFPym9jQfGxXYh+M6l9nrcftV+b6Jfbv0j2W8N43ww6D6Jpf/B5cJf8 eW8L/1sk/1sk/1tcT/crttfvFfIxbiP5eEBHn4jQAbno87Vv0xbPC+RZ/dBF SptcXHF48ZM9UzS4r/fhNf3U2VAm7mmd6FEanNvtZa6nqwqGd27o+2qIBv8J e6jcr0sK90UmVnYJqDe64H7Nchv5H+Mk8hcm/2N8Sv7Cv2m87A/i+Ob2wtiu mXjverWNgRXigNutQP6wO4v7y0Mj8pcnf1tkf9utQ6ZoEiBT+neuJfndXsjv 0Jrk98tCfofFn3vtvh0XL8+/5X8L/Z+R/Z9tyxf6PyP7Px+neC2u35/w+Vzg E1oTPhcKfIIdxfvI9+PJbpkt4n1gD+HbWOAbOP6F63P8i7mIfwFej8FiPSDV YaDa+ECEvH+rNrmvHHsmvGA8Syf8fpiH3vYfXDW9Q9F51K9Up2dKqS+O/Oex PPVjOKS4l3Gyu+eLd3KrLGvkHQZThf4N8y8I/ZvZ1kL9B6aS/mPWwUL9B3Ym /QfLA8PFfRj+0nj4PpxB43kmxgP7iR53CnpEs55nRzmZfAdLs7VrmtbSyfuN v9mFDzmWOpy43X9vx09RYL9PPTd6lQ7LmWd8avooCiqbjm53dJEO40V/8v6e JfoD6g/X//fe80bNeNizyDfr5WkdfvLLHBSUGy39Ll5WLDWwTXo0/po9scbv mWoIvjKozfPqMVjhbBfvlvU10InG10GMDwzGB4tpfFPE+KAMja+SGB9E0/gY H0k0vseEj6vk32RH/jj25N9Unvxx+F4v6CYfDewVWH3I5sUKp3zcHPaxqWWM 1AP0ofpgYH8Fp9DJQ4euTJL5FIV+MQl3WfhuvzdHh3xfDCT8bxfzQyfCfyUx PzQh/FsL/CDhh/Er9eOvBH7hp8AvRgr8Qi2BX8P+4Az1t4jwWZH6q0L4HE39 daH1aGY2zqjcmhjpn1RdvdKn3ccweZ8Q8lE4HLbx8zC6n4cTLuSbzTdPkP5h 9j2NHl6qlQgqj8NDVWW0uLiK+s2eyYkkr2ixArUn4+epPVfRHjhQe9z/GGpP IdqDhdSe4N9aGCvKUV28HLl82mxbi71rEtD5ktGX+7WVlGfpH/rR+2D2lM+J z02244aT/ZDrfyJ9x41OVzYdOv4anH3qjkk5GgbGO75W3DsmG+q9fWuGkAu3 HaDL6+2ZkJswc6P9TQW0FfwRPEm/cYHux7xfWH6KJX9CJfkb8H2P75sLvT57 ta2oxY/vJyU9d41Exqfm1fakNqmJmLFuxZqBr7Rgcujkl833Ew3ysybiUy/H UpcK7h/sj+K1wqqRo7EOXrgPqf/GJAn5PsL9LRL9AVJ/jE+2j3wnfbwd2W94 Pm1ovqTPgYMkD4vxFPDfCvGr+rxhf1ElfC9s9zLuemV5sMGzPPxZ/HzAlaqY fU07ZeCAlUqLYTf0WNWh7bYlppl4o/bdTjo/HX4s4djqf11deUiUQRQ3UjIQ DYyuVewCwyhYYzM8emuXRGkkkQsdlHhiWpFiqR2KWVt2ICgaYRqICZoamOBK T9cNTUVMyivt2HU9wlpNV7e+dbdw3ozQXx+P33szb+Z93/ve/Obb2Ww0ie/J zEGOtQqFSfAPPc96fH2VJuD7Yf/l66X3K8mkL34n2bBhBLOyhkW9sDxiMuRm 95h4j1B/YvyryL9y5h9w//cz/8GV4VBG+BWGQzDhrWw8gg++FtV+u143iOH7 DuRWOUn4KfNedpj7BKo8rNVZyjm4wHAIYzjIles3753XQ/Oa8+1rfy2gL5NR y2SQnB++HDb0i/uvLrxgKN5zQOwXBhHfOUN8Hq8LfXLicq8nmbHsUEa3JeEr 8QVmsb5zuZwZmx9qF+snkkV877L4grQYdw2aBt0+nDZL4vx1Hn8Nw+Enw5Hj 3J7j3J6vZw+fOOoquzMjxsfjb2eyyJ8aNl4RP4eVDP9/Pjge1+elkO8ywJHV l6JjY/6IfMz1eXt8/nge3Hlxx5CswAYRNVGvOr0lDEge+RKxyQ5P0tzVqXIJ CxevdviWOPtui7NBzD/OxHdq5/TYUPM8eN2EBfUMF+03MRyQcG7P/eX6XG4h /UamD+lNLd4emUYs6b3fuq2Kn4dtxMDyNxWvE634QOt3fPvUiMgvapL583+V 7IuZPXB7f2YPuUxf5PtUpg+kT98tGmE39ZdC+FNqj/oT+d1NE5tUUWQQ+UKd cmremvQedA1V6Tfqx6FWikpYoZoW/J2jQ//GoNKBf/GfrPPxsmB4b2tkxclx ul8lPEYy2/+U4Gx6W/Tb7jE6/+c3dHV0Tn/WSqhTZZQczLHBucmYoo5IK8r3 6C2q0QVRF3H+pa7yu6JgVsJlzVO3+kZt0PjY5Yyn0o6L7uct/b9sAPF9VD8D 1c8Y+GM4r9jPgF0jIVtdZBbIT6tG7zaj4Idy7H799WkfoTBxolLmPws2nZPq hXoUSmMeWZJDF+AvSSiKSA== "], {{{}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, {}, \ {}, {}, {}, {}, {}, {}, {}, {}}, {{}, TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[{5129, 11049, 9007, 10973, 10972, 6150, 10953, 6772, 10952, 6771, 9777, 9776, 9774, 11379, 11378, 10258, 11318, 5993, 11319, 10047, 9792, 9793, 5539, 8106, 11253, 11252, 11251, 6128, 11386, 5593, 7199, 6725, 10928, 6726, 10929, 6605, 11003, 6817, 9554, 11166, 11167, 10067, 9862, 9863, 9555, 9865, 9864, 6867, 8027, 6007, 7209, 9578, 9579, 6696, 10566, 6697, 10889, 6539, 9365, 9366, 9367, 5145, 7414, 1028}], LineBox[{1005, 7347, 8147, 10718, 6616, 10717, 6617, 10887, 6695, 10884, 6694, 9569, 9568, 7201, 6006, 8026, 5594, 9998, 9999, 9490, 10048, 11147, 5407, 10049, 11145, 11144, 11000, 6815, 11002, 6738, 8939, 6741, 8973, 6740, 7133, 7132, 11374, 6113, 11239, 11240, 11241, 8102, 10593, 10594, 10000, 5950, 9491, 9492, 10252, 10253, 9771, 10937, 11651, 10938, 6736, 11519, 6737, 10939, 6144, 10935, 10936, 10934, 11518, 11517}], LineBox[{5279, 11123, 9317, 10996, 10995, 6510, 10956, 6779, 10955, 6778, 9783, 9782, 9780, 11384, 11383, 10263, 9684, 6058, 10131, 10795, 10794, 8107, 11257, 11256, 11255, 6129, 11387, 7136, 7137, 6727, 10931, 6728, 10932, 6658, 11004, 6820, 9625, 11191, 11192, 9623, 5457, 9621, 9619, 10098, 10097, 5607, 8028, 6008, 7222, 9587, 9588, 6698, 9585, 6699, 10891, 6627, 10726, 6625, 11471, 8708, 7839, 9257, 9256}], LineBox[{6486, 8773, 5387, 5266, 10776, 6650, 10775, 6651, 10894, 6705, 9614, 6704, 7935, 5935, 7234, 5936, 7936, 6873, 10125, 10126, 9672, 9674, 5474, 10216, 11569, 6825, 11013, 6826, 11015, 6762, 10950, 6765, 10948, 6764, 7237, 5618, 11385, 6125, 11248, 11249, 11250, 8108, 10872, 10873, 10132, 6061, 9685, 9686, 10264, 10265, 9786, 9789, 9790, 6746, 10943, 6747, 10944, 6511, 10941, 10942, 10940, 11521, 11520}]}, "2.4000000000000004`"], Annotation[#, 2.4000000000000004`, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[{5174, 7501, 5162, 5313, 6937, 6232, 8291, 5706, 8204, 7415, 9040, 10568, 6540, 9580, 10567, 10565, 10888, 5435, 7206, 9576, 7208, 8889, 8888, 5596, 10695, 10697, 9556, 11168, 5427, 8840, 5426, 9553, 9552, 6604, 8879, 10927, 8878, 5488, 8018, 8019, 6084, 9551, 6083, 10171, 10267, 10266, 8020, 8021, 6601, 9775, 6600, 10683, 8105, 5532, 9778, 6754, 9804, 9806, 9807, 8122, 9803, 9802}], LineBox[{5236, 7751, 8599, 7831, 7834, 6445, 8713, 5887, 8711, 7840, 6443, 10727, 6626, 9582, 9584, 5443, 10890, 5445, 7219, 8852, 7221, 8854, 8853, 6871, 10791, 10793, 9620, 9622, 5458, 8856, 8858, 9624, 8859, 6657, 8861, 10930, 8860, 8957, 8030, 8031, 6088, 9628, 6087, 10183, 11193, 5459, 8089, 8090, 6660, 9781, 6659, 10796, 8088, 5537, 9784, 6745, 9796, 9798, 9799, 8825, 9795, 9794}], LineBox[{6791, 8954, 8115, 9811, 9810, 9809, 6766, 9769, 5527, 8099, 10592, 6569, 9770, 6570, 7966, 7965, 5405, 9487, 8100, 6066, 7296, 6067, 7298, 7297, 8955, 8964, 6813, 11018, 6814, 10999, 6739, 11143, 9488, 11001, 5406, 8831, 10531, 11146, 10532, 9489, 10537, 10536, 6865, 8885, 8887, 7203, 9572, 7200, 5433, 10886, 5434, 11175, 10885, 9574, 6618, 10719, 6159, 7348, 8149, 5676, 8223, 6198, 7355, 7354, 8213, 7421, 8311}], LineBox[{6807, 8958, 8826, 9815, 9814, 9813, 6780, 9791, 5538, 8096, 9788, 9787, 9785, 6126, 8093, 8092, 5476, 11207, 9678, 10217, 11365, 6100, 11364, 6101, 8080, 8079, 5510, 8917, 10949, 8918, 6763, 9675, 11014, 5475, 8870, 5473, 9673, 9671, 10861, 10860, 5617, 8904, 8906, 7236, 9618, 7233, 7934, 10893, 5456, 9615, 9612, 6652, 10777, 9293, 7107, 8779, 7106, 8775, 6487, 7894, 7893, 5249, 5377, 8687}]}, "2.3000000000000003`"], Annotation[#, 2.3000000000000003`, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[{6271, 6969, 6273, 7502, 9134, 7500, 5161, 9084, 6939, 8297, 6936, 8290, 5705, 8203, 6193, 7411, 6192, 10723, 10725, 9581, 11176, 5436, 8195, 9577, 9575, 7207, 6619, 8890, 5595, 10696, 7205, 6606, 9356, 6607, 10693, 6533, 10689, 6603, 10674, 6602, 10685, 6688, 10045, 6689, 10882, 5992, 10172, 9549, 9550, 7197, 5425, 9548, 6082, 8016, 9716, 9718, 6117, 10880, 6687, 9805, 6686}], LineBox[{6396, 7746, 6398, 7752, 9223, 7750, 8598, 8600, 7833, 8606, 5883, 8712, 5886, 8710, 6444, 7082, 9254, 10732, 10734, 9583, 9586, 5444, 8781, 8851, 6541, 7220, 6543, 8855, 6870, 10792, 6872, 6655, 10784, 6656, 10789, 6545, 10572, 6547, 9456, 9458, 9460, 11118, 10103, 6803, 10988, 6019, 10184, 9626, 9627, 7240, 7939, 7940, 6057, 7943, 9681, 9683, 6124, 10874, 6680, 9797, 6679}], LineBox[{9089, 7431, 6242, 7423, 8312, 7420, 8212, 8214, 7357, 8218, 5678, 8222, 5675, 8148, 6160, 7353, 9013, 10560, 10561, 9573, 10559, 11174, 10558, 8143, 9571, 9570, 7202, 6615, 8886, 6864, 10538, 6866, 9333, 9331, 6516, 10535, 6514, 10602, 6572, 10596, 6571, 10600, 11035, 9323, 6792, 10960, 5654, 8101, 5652, 7295, 7144, 5404, 9486, 6065, 7964, 9692, 9693, 6112, 10276, 6140, 9808, 11263}], LineBox[{9247, 7823, 6437, 7076, 8688, 5376, 5248, 9250, 7896, 8700, 5916, 8774, 7105, 8778, 6490, 7901, 6489, 10770, 10771, 9611, 9613, 5455, 8818, 9617, 9616, 7235, 6654, 8905, 5616, 10862, 7232, 6675, 10850, 6676, 10865, 6567, 10870, 6678, 9477, 6677, 10868, 6712, 10128, 6713, 10901, 6054, 10218, 9676, 9677, 7289, 5477, 9680, 6063, 8085, 9688, 9689, 6127, 10285, 6141, 9812, 11273}]}, "2.2`"], Annotation[#, 2.2, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[{5478, 8082, 9690, 8084, 10134, 10133, 9679, 7290, 5649, 10130, 6055, 10120, 10129, 10127, 10900, 10866, 10867, 9476, 10871, 10869, 6566, 10863, 10864, 10849, 10859, 10858, 7231, 10780, 10781, 10779, 6653, 10782, 6506, 10774, 6649, 9313, 6648, 8777, 10772, 6488, 7900, 8780, 5917, 8767, 5915, 8697, 8699, 7895, 9249, 7077, 8695, 7075, 8690, 6436, 7822, 9248, 7821, 5233, 5364, 8586, 6386}], LineBox[{5479, 7961, 9694, 7963, 10136, 10135, 9485, 7145, 5562, 9852, 5653, 9320, 9322, 5291, 5108, 10598, 10599, 10595, 10603, 10601, 6513, 10533, 10534, 9330, 9334, 5294, 5130, 10714, 10715, 10712, 6614, 10716, 6157, 8842, 6535, 8141, 9359, 9014, 10562, 9012, 7352, 8150, 5677, 8209, 6913, 8215, 8217, 7356, 6196, 7422, 8220, 5710, 8314, 6241, 7430, 9090, 7429, 8306, 7508, 8385, 6279}], LineBox[{8120, 8014, 9717, 8015, 10170, 10169, 9547, 7198, 5592, 10046, 5991, 9327, 10044, 10043, 10881, 10684, 10686, 10673, 10688, 10687, 6532, 10692, 10694, 9355, 10691, 10690, 7204, 11469, 11470, 10721, 6620, 10722, 6188, 8893, 6622, 8191, 6621, 8201, 10724, 6191, 7410, 8202, 5704, 8278, 5708, 8295, 8296, 6938, 9083, 7503, 8301, 5734, 8371, 6272, 6968, 8369, 5324, 5175, 7579, 9161, 9159}], LineBox[{8824, 7941, 9682, 7942, 8087, 8086, 5937, 7241, 11648, 5620, 10104, 6018, 10099, 10102, 10101, 5274, 5394, 9459, 9455, 10571, 10570, 6544, 10788, 10790, 10783, 10787, 10786, 5267, 5388, 9446, 9444, 6542, 10569, 6491, 10730, 6629, 9296, 6628, 9255, 10733, 9253, 7081, 8709, 7078, 8705, 5885, 8604, 8605, 7832, 6394, 7753, 8603, 5858, 8610, 6397, 7745, 8608, 7742, 8520, 7669, 9188, 9186}]}, "2.1`"], Annotation[#, 2.1, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[{106, 9880, 9877, 10391, 10388, 11418, 7515, 7516, 6280, 7510, 8384, 7507, 8307, 6239, 7433, 8310, 5712, 8313, 5709, 8219, 6197, 7428, 9045, 6915, 8216, 6912, 8208, 8210, 7351, 9042, 7349, 5136, 5298, 9360, 8140, 8841, 6156, 7320, 6158, 7313, 10713, 7311, 8123, 10613, 6577, 9332, 6578, 10614, 6515, 10606, 6574, 10597, 6573, 10605, 10604, 6681, 10001, 5955, 9321, 10004, 10002, 5564, 7968, 6840, 6841, 5949, 8098, 6064, 7962, 9691}], LineBox[{106, 10406, 9922, 9926, 9924, 10424, 7661, 7664, 6356, 7670, 9187, 7668, 8521, 6354, 7744, 8522, 5854, 8609, 5857, 8602, 6395, 7055, 9221, 7838, 8607, 5884, 8704, 8706, 7080, 8701, 5378, 5251, 10728, 10729, 9295, 10731, 9294, 7905, 6492, 7910, 9445, 7909, 8791, 10797, 6661, 10785, 6662, 10800, 6546, 10808, 6666, 9457, 6665, 10809, 10807, 6706, 10105, 6020, 10100, 10107, 10106, 5622, 8039, 5619, 11647, 7238, 11650, 11649, 9316, 10530, 6509, 7944, 6508}], LineBox[{120, 9965, 9435, 9438, 5353, 5220, 7734, 7735, 6387, 7049, 8585, 5363, 9220, 9219, 7825, 8591, 5881, 8689, 7074, 8694, 6439, 7830, 6438, 7891, 8698, 5914, 8766, 8768, 7899, 8764, 7897, 8776, 10768, 10769, 9312, 10773, 9310, 7928, 6505, 7118, 10778, 5393, 5273, 10851, 6671, 10848, 6672, 10852, 6565, 10589, 6568, 9475, 9478, 9479, 11122, 10121, 6050, 10119, 10124, 10122, 5648, 7957, 5646, 7286, 6056, 8095, 6062, 8083, 9687}], LineBox[{120, 9404, 9401, 9919, 9917, 5194, 5333, 6999, 6307, 7580, 9160, 7578, 9137, 9136, 6971, 8373, 6967, 8370, 5733, 8300, 6234, 7497, 6233, 7419, 8298, 5707, 8277, 8279, 7413, 9080, 7409, 8200, 8891, 8892, 8190, 8894, 6186, 6910, 6187, 7342, 10720, 7341, 5135, 9358, 9357, 9354, 6534, 10555, 6531, 10676, 6597, 10672, 6596, 10675, 11048, 9329, 9328, 9326, 9855, 9854, 5591, 8004, 6861, 6863, 5990, 8121, 6149, 8017, 6148}]}, "2"], Annotation[#, 2, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwVkU0ow2Ecx7/bhVxcmGHDvDYuymkbOS2jHFitFm01tpTyUhZHtQO2Wnbg xkVKOThhRVI4CSU5eLs4ULhomGXls8On7/N8f2///++xhSYHJwySlqC4TOqv lYrQyyopVCG5ud+WS/PNksUCJmkLz4omuSfIu2+Vdu3SHribJA+0U7NQLznw nNCL14V2QkeDtEPtOX3s9DHUSUbI0yuPl2a+GT7ImSU3ChnOPrOUQ73k/qJh NAIeqzSOjtJrGx1D99EY+c5qZlG/Rk4MP4vvw/tD/WhPG9/GrEP+7wjSjdIB POH54Q3vHe7wHuEVbwR81DlqpG6b9EDfBLpIvzgYyVsm9sX8JH6W+DOaK8xH VwoxNAPXnPvIv0G9lcxBB1AXuythhylmfeMFyflBp/Gn4II5UfQKDREL8wYR OGbPJxCgdpP4EPsehlO8IBqAT/JW2XWcXW/wxi8t0hnxucJ7ci7lO03EXMSi eDOQ4r4O/32VXBg= "]], LineBox[CompressedData[" 1:eJwNkc0rw3Ecx98oGweledjM7InZPJZ/gINyQDNtDg5reShSc5A4ODhQykNC 07KRhv0HZNIyKVJqHBW7OTg4SI68Dq9e3+/78/l+f98+P+fY7HC0SNImHFZJ NdXSSqu0CpPt0gT01UvjeK1WmrJLP/QsNUv95CdN0iPrVWoRamUeqRwMYIQU 9Qx3hTgTd0lBfESWhM4WqQMiFumjQRql7uQePx6CAlmgUXrDlezT+M8peelP WyUfTpK56UngOd5fynqLWpy+dbyDCzXSAH4xS9305fGvTcqRD5JncTX+Irv0 Shdwy9vv4AZO2afgrE2Ksd+HPYiR7UKc/ADCnM86pBnuy+FpHCIL8z0jjuB5 chvvimI/dRsuoTbilqy8PwMVZMX0dNF/zowD1IKQZf3KjGP4Ce/jZ5wHB3dd 420yA+cWfNIi2JnzBvN3M/dlZujCVjILFOAdHqjfg4fzvcw/wf80k3/yBhPr K844qfVQy9RJ3ybq7I/hH38EVlk= "]]}, "1.9000000000000001`"], Annotation[#, 1.9000000000000001`, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwVkc8rw2Ecx9/cpewHZr++bMZmWombnHYhPxotREpxcLBitZv8yEIppSlW i7G1P4DDahYlshN3tVyV3VZO8nJ49/o87/fneb7P9/MYy7HIeoOkI1Q3SSWb NNIq1Toki1eyoi9qwyKlfdIt2QW8g0m7tI/e/dJmrxRHNvrtyIF2OqUAXqJd crLupw6iUJeUYl/ZxfeQyyq9QQOe45vapA/WZeppeh/gAN4TbHZLTaho5ltI DmmLnka4QE+MzM5949AFt8nmydY4u4g3jFeCZbSIn2RPqkfy9lHT44MH//fo lgpkN2R+vCxeEObgC9k9WY39ZoP7okf8MIxzfgJ98t2wUxrDq5Kdwh/2HJOd UNe5+wZK07MLPR7pmtrPrArwl548bGGGIbwqtZOZT7B2w1k4h545L8LeQd5g CGWY8yW6QhnyceZ9xv4s6ynqSfRN3wrzXUUVzqrwnq9wif+L8s6jzDlPfw5F qQ/JZuBegPeAf8eaUxk= "]], LineBox[CompressedData[" 1:eJwNkTtIglEYht/GaNU0tYt2v9AcYi2FUoqRILRUUEFDkEvYUkuhDSJEBC1F S5PY2g0kDQy6LNUUaTVIUwhp0J16hofnnPf7/s/jOfbJUGCuQlIMEgbp1SK5 TNKSTXJiQ720wHrCKD23SjdkBXyLV6lFIULN2iLZIN8lPUAOsp3SGew6pNNm KQMnMN4hjcFsjfRbJ4Wpz8OVVQrhbmZ/knubJB9UMt9JnqYe4JtLaoPka5z3 mnXZLq3jJ7yBHfQUWL9XS3EcI3szS704T7ZCdo9duA96yIOc85GZObiDFPUi /8dPnmJ/DAewQ54md5OPcp7vBukLIuQlvIw3azG/F8D7ZDNkSbxI5iVLNEoe PE32wd2O4AAYmRekp0gWpucFD2M//PEuPyD62ph3zr1fQIKeKr45aueMMMT9 bnG2bYhyZx72bkhSy/Ime7jMvgQh7tXLDB9kuPND3jWN/fTFmWuFAfr6wcJ6 ipoZm+Af4ApgOA== "]]}, "1.8`"], Annotation[#, 1.8, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwV0U8ow3EYx/HPTnKgzP5im/kTVuNCSnYhEhfW3FYk/+Zgyo1i6VckN6Vc 2ORAREmNEkLjQg5cXJykpEUUiXg7PL2e5/k932+/7/fr7YkGh02Spokbq9Ts kW7RWSA1lEpV5FbyZJlkwz67ZMZebGHWlSdtVEhbxIlTWsZT3MYY7uE5zpRI KUxSX7BunT3aiqVN/KT+IHw2aYfa75CesBIzCqUm+iG05EthtOMYa8st/KOL vcjXiFbycdZ0YDuxy+wCnvFtEd+oXwmD/X4wTm+V+WNcopfplRKYot6n/4gH 1DX0D/GZ+op+tVsK0LujN4UGUU8vhnU4h7P/El7OPI8evKf/yz9PEm7u45J+ mp6DuwwUSUecqxE7mb3mWwjf0c/3CP0h4pu6H79wFMM+KYs3CGI2duEK6wbR TG3iDXMwQj1A1JIb3HWcPdPkCRzhrh943yh2894p1kyQ53I+O7MvzP0BbUhV Gg== "]], LineBox[CompressedData[" 1:eJwVkUsohGEUht9pFhgpZcyPufwzLjMxI00sJKWYLDEuScpiSpEyUa4lO7Ox oSnZahZsmJISkYhiYUthZ2WjmIsoeSzentP7ft85/38+XyzeP22RlEDf5dKk Kf3AIZdkoy5CvdS3AakPJgzpqUpagzGyeFD6qpXyKIu2KqWeeikJWxqkQs6G YQFshkm7VEL/aLV07ZQG4QAy6ffqkRrpsY8f5r4d34pvhYJpn7TDmT24i6LU GzBXIa1zJw8jeF1onDlvqJN8nqwbRtCFQ3LAT7f0XCNNkU2gUrwUWSgk3ZHd k43hj6JfL/9N5idLkR2RdeCf4bfDY3iCRsgOyYZhkNmXyPPfg++y4K2QrSIb tZ/zAXTDToMwTP8y2ARf2KudO1dkbZzPsbsMesB/REn8VvxNWMyMZXa2hBbQ InsLsf85OAvTMA4P4Ax08V5u7jrRB99mMC8Lt3nfDPTyNkad9E59Tm0y75TZ f1RAUCo= "]]}, "1.7000000000000002`"], Annotation[#, 1.7000000000000002`, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwVkUsohFEYht9RSrlO7ozLjFGMS5oNM5MJ5ZKazb/S1GCwmuSyIJdI+ctl Y6HZWJmUjYZiKU2JhSR7haLspowiVuOZxdN7zvt+5zun79gnZo0Zi6QduCqV ktVSb7mUqJL6UGcda/xNm2RCitzWIH2i007JRb7qkpabpRWYg3VYg8VK+qK7 sETtNroFCc4c0MtDn07YZ22tkL6586KENfjwr/FfqO0okxz1UjZ3NqEuuCXz cia3Rmpjb1Azj4bwivAKYYP9ONpFv3P6jbA2yf30ecDzQAzvnuwIPSZLcyZI HsrU4N/ht7SS099qly6piZAVsH7lfBBS1HzBI9lCZn5kPZDGM9DhWikAf+RR 9h/0iqMGnoUZxdAz9qeQxczzHdIJfYrRONrO7EzueaPuHUY5c5N5I2pQk8Qb Q738gw/c4IduiFIziA7BD30G0H7YgwizPaRvGH1i9lPoJPzy33mom7cEmHNO I/9A/gz/r5JS2Q== "]], LineBox[CompressedData[" 1:eJwVkTlIwmEYh39FNhR0kZqVpR1ENaY2OJWS+N866VhSCJeuLYpC6KAcGtpc Mq2EKIJcImgIipYUGtoaGyKRCIqGaOlpeHjey/f7+33O8MLQfJGkGNRYpNVG 6dgqzeI03m2Wyqnv4Bi810tb+KRWWsf72GyWittZABOd0jikbNJolzQGgzAC wxBnvor5mRZg5rdJiuBv/AV91PvhkdiPbXyDC1txwcn5kKNnb+OMBumNPIlf sIM9m/Q2YJFzPmGNehS81D7qJDfuAS+1vJ0YF3COnof4mv/6Sn5Ffo+T5GXU L8lvyZ9bpRv845AS+ABS9OL4jt4AZ+4Ru3EWXHzbCv1T5sPsCmEf/WVmLfSm yCchQM/AflyK89y/CZfABXEGOthzhoP81oA0cQVnZCDGfWxDL3fvgSh3cYiP IPH/HpAEE7PnsNQtzTFfyY4A71iNDRyEJ97Hh0Pc+QPvPY1zOAt/CANTgw== "]]}, "1.6`"], Annotation[#, 1.6, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwVkU0ow3EYx7+7yNtBYsO8zViR14lEMQ5SymEOKzWxg5RQrkohy8u8pBy9 1JZS5CTKHIZatnKQg7k5aBqxHTg4+Th8+/ye7/f5Pf9fz9/imXZOGSSto7Q8 yVEmdaO7IqkHhmE7fMiXfMWS2SjlwHqrFKuRntETWqUvUC2FCqWOKqkTdaGl CqkFfx7fQb0A26jt3D9kTpjZNmb+/LNA+mXOOe8woVdyG5yh952zk7y/XOql 3w2TeC48R4k0Qj2MRsmOYLNZOoWt8Jj7J2iLvmu4DQ+4N0j2yPw+FMRzwRh5 iPMZ+S28QVkW3gLfUBQ/Ae14jSjOHQ+qLZXq0Ce5l7lzZCl8QyWLRV6yZbxv 3vcC9+mJwwRaIbOylwj8oDaa2Bl7G8C7x2vi3IDS+QebzEzipdAY+Th+hFmT MArdfMvF/8hmjxfs+xIFkZ/cxd793LmiDsAh6h36vuhPoSTa5dsfeHtwkX+S yXtzYQbcgBPs3AfX0CznP/0LW4E= "]], LineBox[CompressedData[" 1:eJwVkk8og3EYx78rCZsdhG3Mn+01mi2uDm4ull2wSCm1A0n5czYH5GIRcXMY amTtQJz8yzhYLpxGchmtJLk4ICWfHb59nuf7fd7nffv9Xld4omfcJGkVbZVL tgqp2CMFnZK5Tvqin4I/cAxGbdJTlbQIV5p5DlkapayPeRigv/dLDyiDTvBP UcwtJdi7h3aRmR3tzIYd0kctJPewsw8O4b3hvSIH/T4sgWaUrJZayK3UJuYP XFI8nzdIa2RJ+gTKVUrr8AWGYJCZB7vUS/1XI3VA4d3h/dJ/IzveLbTAUjTK vmPyNN41CnI+GTSIH8ffxrsxpC68nXxdLw3DEbRAHoZH5ENwNp/hlVHPU4f4 rknYDf2wFVnJBpgvZL+XvgAasI3nUtxHP5mTd6Wpc9xFDG6iMvJHeoNdKbiB V4QX9UqHnFUT573EHSyjOc7NoHejafIr7ugSRaif8W6YycIZ7iaCOjnjT74j AH3svuA/8MIz7s8Dz6EB3eiduX/cO1lj "]]}, "1.5`"], Annotation[#, 1.5, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwVkU0ow2Ecx787I8nLbDa2+c8ysryUnL0dlNqYt5MpSa3NyUU5EJFCjg5e ysvYJBcOc1gU1jaTi3aXcnGknHwcPn1+z/f5Pc/++z3OqWggYpK0Ad/lkqdO 6jVLKavUh39qyMFdKe17pGuyPXyD123SGrx6pZVGaRWcbskANyy7JB/ZgkVq YN1O3Qat9dzBuTt+KwWuKqmADXxIbq6WPlg/Uo/Rm8ZdZHnciR0OKVkh2WGC /RK71EI2xPlF7OB7l/AMvWXsTeMQDrOfJI/gPJ4ly+A0HFNnuSuGT+k/x2dg ctKDc3BL/oJLyZ6xGVvgl9qG77m3Hz9gU630Rv8ALuAg+Tv5Cd7m++J4BxcZ 0jz/44i+JmovJKh9zOwKFzPDS2zFHWSf1C5mH2Rt4EkcgifuGuFsN2/RAzHm HYcEHLDvZ+67nL9gHaQehi/6Isw5ClnuyvGumf87m6VR3tvPvAOwRTaIN/Ec vePUf21AVRo= "]], LineBox[CompressedData[" 1:eJwVkc8rw2Ecx99Oyo+LH2PzcxhhhYPDhKVkDiaUmiK/ComJP8CorSk3btzI YVwcRAgHI3PiNqQwVk5MKEm8HF69nu/783k+z7fnMQ9MdLjjJC1AIE1KskiJ MJot2TIkNx6H7nQpUiJdkN3jSzyTJ3nAS81YLJng2irdwBUcl0tBWCmQ9pi5 CzvQWiY5YcTIoYVSHLjpMdA7hkNZ0jC2csYPM99yJUeR1AzxnFVJ7ZAeJ/uD 1BrJmyDE+sksRWGO9TP+NPAv+B37cSxT8lH75Uw/M3wwSx6mXoMrqN1R6+cu olBFNkXPOfsiOdIDuMhvYYh8i/yALMyefewgP2XdSe0zX+rAr9jD/EXqG9Sq yabZt0k+SL6G+3AvttPThV3wwr07cBu9Kexpx1GySWY8YidugW+T9AUfvIWF OSf4FFbpSWBPoFRahwbufok7XgYvd1jHd+1/Ri3Iey3jGN+v4Oae65lhhyPe YZs3P8RO+uaZmwpp0EN2xtnd2EZvMtkfoz1iZA== "]]}, "1.4000000000000001`"], Annotation[#, 1.4000000000000001`, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwVkksohFEYhl/ZCKM0My5jXGbcySwMuYyNxUxEjWThEkqJUqRZsJnRSOwU UiMjhcHKbpSFSS5liZJkoWRnQS47jMfi6fnOe75z/vP/57cNTXSOJ0hagiuz 5MqXrnGaVWoslhzUKdTRUikVD2ZKyXgAN9E7UyEFIFQurcEqbEAY/NnSHt6H uSJpF0fgnHVb7HFDvYM/GL9DaQa9jMuypCdcjr/Jm8lbCqRWSM+RPPjERD+4 ciUnjhTSRz3FGg/epseND7CfbJE6wD4vjIP4E39BF/tdsDbGfJg8ySYNk43A A/kz+RF5DfkkmQ8eyR15UgNZHdwxP43vcTX5G8+bZxyktvDes9jKt1jAd+S3 8MuZA3BK5qbnDDvtrIdjnlGPO1hzSe7FxkrJBN8lrIU4RC2SmewQZ2J7FXdA ncj5QjjOHmPQxv3UMteODdABXthk317cBz+coQd3wzKs/N8r336de35hrzAe 5U6e+A9GcD//RYz/w0dt4L2N9L7S9wdo/1u4 "]], LineBox[CompressedData[" 1:eJwNkT0vg1EYhm+LGKpEi2rRvtrGVwdtYpNQPwCpwedEJAZfMYjPCEWCGgwS CZ0Img4Sk0lCNBKpJv4BFiRW0WparuHKdc79nOec9z3HGJkOTRVI2oFcuTTr lPJ4sFoyMy6GPsbJeqkf71VKL3YpgieozTRLR1bJQk/WI2Wgt1EKwWGVFGyS OuGXeQduhwPWm1n/TfbgkIbrpCFws+dXreRnjyvyVvqryQvJS3ApxKn7qMfw tSEN4BN8Cvv0/NmkHrIi1nTjT7f0AYvU5qGLdYkKyY4dkKmRbuh5xhfkZWRn OMk8Rh7Hu8xFvo3PmUfIx3HKxToIsm8CT1IfI9/kvC245z+XyQ3qo/SYqIXJ feRWxgFqT9ypgVPYiz0QYJ937tZGT5K8jZ40d/4Dr+RvECV/5P6OsYn9LmGF f14CP3kLLHB/YbwBq7AOa5C2SHO8mxMM9nZBlm+0cW4eR3nrHPbwRi4vb8f4 jnED597yDf/Ojlan "]]}, "1.3`"], Annotation[#, 1.3, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwVkk8ow2EYx79q/l2x2cawEWErmdwmuVDKyp+SXPzJDQc5GEoRtTBXRUlJ uWg1JEpsTWG1i/PCBXNwwtjKZ4dvn+f5vs/7vO/7/H720eneqRxJAXRtlFJl UmepZKyTLMiMIvhr5VIYDtdKaWq6qXFVSlartF4vhSzSEjyBG9AHA/AMLtRI p3CT3EH9coMUdUpxvFt4jx9DD8hkloIOzocJ+odKpCLkqaaOO7ziuU1SU5VU wD1aYCuKs+Zhj5u42CatUG+E43hWuIg/j8L0cqGx7Brysx7Fb6dXDHbAtkZp h3f6OWeXu++hfdSFf4d/iH9FfoMiyIufoZfNTs6aFz7Sd45eSc6aQD0V0iws pH6AWLx9CB5QOwjPoQHviPiS+ALlMuNSZnFMnzIYhM3sX6VPkrp+4j70ydxG 2PsDU+gLvZJ/Q2f2+zBvn0t6w4sz73f4x9o2zMAP+EufJEyTu9kzw5y3OP+J OIEmydN8/zz+h3xkQKu8+4W1Z/QP60ZfZw== "]], LineBox[CompressedData[" 1:eJwV0j1sjVEcx/EfizRplOpte9t6qdtouL1JJYI2JIKVoYPFJmbiJaJJCZHb iVjQUC4aiclUyRUGlupEI32ZRGKRKIkJ8e7T4Zvvc37/85xznv95uo8cHzq2 LMkYGluTk13J3bbk7KZktDepYoX84vrkY0cyLF/km+aMyE6Uk389yV/8xr1i cmhzUuOmLcl3buRvvHLJKFWS29b46nmcl5eSW9xsrUlu4tVYhaPem96YtJrT hg4UUTevnR9zgbebswPT65IBLjhfH7fw2+7kHabUOp2xC39akgVZrVNmj2G1 ovyc/ILnqlo/b8WndnXjBX3YyWXZK9miXjyVzXvvCX8wrsuf8R3jSfk4140n 5NfX6scG68s+c012VXYFj4z3832eQL9znVHfJXvg+wb5NJ/CGrWD5hzAPmvt 5T38y328d38/+Qceev7CJetc1osennM383izZN89yxV9HnXWKi7hvHybfITH +AVf4+d8g3vNrzhHHxrs8bqQ7LbPDA/4XwZRVjus9y/dzxT+Ax4hYI8= "]]}, "1.2000000000000002`"], Annotation[#, 1.2000000000000002`, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwV0j9szWEUxvFHWh38W3Bbl5bSP9dtb5qIpJWYKiYpgsVQgzYmNAY1tCJR Q9vBoqO7iMTsahokBpFYLR0k0kSIuMSfChah8bnDN8/7Pu8553fe8/46z0+c urwuSRXN25Kh3qSJlvclJYz3JGO4jmIhWXT+rDX51p18x6XtcnYnF+kX+68Y xBD6eaVSUqGHK0mv9SH+P/zFVf5ZuZN0uS9Z43UXk9FGPm/V2Q/M7/A9eqcr WUBBfyu7ki46ocf31iNtyZE9ybAeT9A67zRvsD05Q0/yzjm7Twd2Jg/ogYbK P6jOrLg5VBux/Lu0LmaBd0/fS+7/GDXff0qfYIn/gX7EMv8TreMFv9zhjmr/ QY/1Z/Vm1F1t9Iw1/hR/ujP5qa/XtOr8De1w3xvO2ulzusLbauaVvckx3kve fusSWszptnobyskvZ0Vz/E030y3YiJqZbqJj4scxYL9eny2Nd5U/arbTtMm+ GbPmP4cRXr+7HKfD3q/Pep7fKqaAm/wpuTP0nfptvFf6fOsfeSRuEQ9xVG6N XjCja2ImcUvMFW/0H86kYTQ= "]], LineBox[CompressedData[" 1:eJwV0TtsDWAYxvGnaGiChZ6e0p6LouiFuoYKg4TJIk4TtE2YRKScQZgIFpfJ YqADFhPpYBAJi8UlKjXo2qRoOnVsBwm/M/zzfN/zvO93rV64cmqsKck4XqxP iq3J8u6kGWNbkzqO9SVX6XfeJM73Jt/akjW8tbip51o5qW5PmuTLEOzZluzG q57khJqj1hkwv7ElOSs/g049CyWefFrdP1nfhuQ6Pc4b2ZSMYq49qW1O/tAF PRXeG32ttICJjfaSFY1XONv7avJavlrPY1mz7B1vvpC8pHN0lJ5WM0KHscq4 BT+L6unvLvvhb2dyztvM4KP1PuCze3/CSd40nvPG8ZT3BId4k436SnLfenVr PKSX6SXca/joaPh0yHlu0Ro9QI+obZcN27/F+ffxVtIBOij70uFMspI9pozn vf+Eu0+554zxD/qLzmKvd6x5zy7vukiXUOcNyQ77jzvOexe3sct8Jx75i241 g/6s37xfT8V/lbHf/IE9L8q/qpuVvfXmz2S9jf/DDhzU20PLzlmQldQurkva jJfc5T/8+lq2 "]]}, "1.1`"], Annotation[#, 1.1, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwV0tFrzWEcx/HPlguUKzM7OztnzsExNqUoh1xpfwAzzA3FlZ1yZBt33FiJ C6aIIheUK8UySm4UISl2zfUYUpTahrxcvHv3fJ/n+Tzf8/2dyuHmwLGWJNcx tzwp9SbV1UkZ69cm9Y1JD2/n2orkov1L+LIu+YavKLRzNfnRmfxExf6CrKK9 LnSijBIeyRiqJQdwek1yBvfbkmXY4F6/M8Mrk53c4N4udVyQf66QzHbL60gm rQs8bW+L9wd7kh3WAzzRp0c8ldmN9pK7fk8Hj69KzqJaTM7zsDtF9aPc4Kas l+qvcNz6OTf5mtyber71Hz3f4du4q/6G3+KZ+jS/xxP11nIy491FvLuS7MJr +UutP3hvD3/kQ+qf1B/yFK7obZJ/6f0U7jk3zgfNZ5M3NpvDnPwl5jNlr279 wjy2cYXHfK+T2Go2ddScm3HvM2bRkHNV3l4z3odBDGE/Hvs+LWbcige+5Tu9 tKndcP6Iu6PqE/K+e+cy/3HnL+bxGwtYjFEz6PefGeMmRnAC/wAbHl+c "]], LineBox[CompressedData[" 1:eJwV0UuIjWEYB/C/JRY2ro3bMAfjIGeYM1k4chenmFko5BzZuM9YGGIQEqWs saBssJJLY0PMKJaKWShp2GgyNRu5JuU3i1//73ue73ve73vfxr1dHZ1jktzg 7sSku5jsa0qeFJINi5NeuVHumpT0671k7IJkPOO4PiUZnpNck6dmJZ/mJ4Mc oZPDHKWLR2YclIc4wGtesXtRUmO/63PmjFj/vKxMT1Zy2TdcYol1qtOsvTBZ 65lnDUlDc/JUFvU26z2fmazRu+pf+lx/aExOyzfyrHwn3/JtctIjR6b6bvV/ c5OL5lzguPoJCup/1ZvkHvO+8N7sAT7P869sV/tIr9rDUWoPWK82wNDsZKuZ w/IrPda9MiO5Y25J/aT176nX1W/KW6zQv61fllX3Q/agIlcxwTtV76x2XfFO uzMY1N/k+XX2oqD33TnU7Fedkl4L3fZzm/09JjtkHy9YTivLaKPMfedUki0s 5fHo2bHFGVVpM3+HOWfs+U75W+8PP/jFT4pmtFq/TLNvq9uTGv8BDcBiXw== "]]}, "1"], Annotation[#, 1, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwV0klI1WEUxuHjdSMFbUyvc+nNBodapNDKFhVktCqoTIOoTYuyaJWZQTbY RFHYVqiwyKgWItSiQUVoEYRezaiMyhsJDdCwcZM9LX6833m/851z/ufe8j0H t7RmRcTIf/Iidi11KInYlIx4VRUxiTQmMI45dMmbro7IILs2IoGWoogfFRHf ccv9RnUacWOZWjUR12mmMqLT+a/a8+h8nMScOI8+8i6fbhavpt3qX8MZtSeK 9ceCVMRp8aw+DwsjbtMCuUmc4peY5aUZZ/V6oudj7FdvHT1AN9D3+hTJn6KF 9IgebRhYGJGLBj3G7aA+P2LNYnPq27zcbrAVO9GE0tKIc3K7kHTeVxCRkjui xgXeebTyD6kzps56dxN0Eof5l+X32NFF9z1LIi7RXnEf/wW9I37Gv0vT4qf8 7LKIReURZXjOb6Lt6nbgq37fsE3OdmTbTzc/Qfvl7eZ9MPdHrFJ3mn5Cjr2U 2WO/3AHUuzvrG36viPiDX/iJHfwZO2u2w6PezIjb6JC40d6H6SBe22WYt8Fu 16KF1+73OIZG7zvoAzn3UendTb/bcTomN41R3OPV8b6YJ9c31YnfmLGX5ojf Or9Dp7hI3glaTPvUr6Y1qMJK1GKv+0H/i2EM4aq8Ke+v0JRZK5AwTxZG9fws P4N/fbqBcg== "]], LineBox[CompressedData[" 1:eJwV0j1szWEUx/Ej3tpFqHLvrer77cutIhohpFUJg0RVxSBhoAaxUFejdduS kAqJVamFRRctItzBwGDVRbRsYmhDUhVvU+/gY/jm95zfOc/znP95/tU954+c WxIRb/FuXURPfcQUPUlPYUtDxPZNEZvpsUTErsaI3diBW/ybyFdG3LZnMhPx BBPYVxYxVBMxiCsobYm4wFtLs/QX7yee2rfMGUP8Xn4JXSqelBuxfp2KqKMP 5UabI+5hDHeR1kM96tTXomK9PXouTka08fegHVl9d+n/Iu2mc+4sOH+Wbi2P +NgUMYNOta3OPUTP1kYcpl1oc25HVcSqDRGr0SuXLlW7UV/WD7DTus+97bQN 4+oHxDesc/bPiofpd7qAbufsd9dz/Y7xn9VFvEAenfwv/Dz/vXgGn3CU31Dh TaojWvBBPkunaRN/3n05cb/1AJJmN0wTdIpf0PMQks56wy8xj4w5vNJLme8v xxqkkESRdyzGCfXH0YEfZraot2Z758ULqFRbhQqcdtcZM74qP5LWl/nt9X4H 7ctYP/aO28QTtJVeor/1sNz7JcT94mG6QrwSRfgj/xeX5ZJyAzT1/59w5lf+ N3TxXuq1oH4Ro3Kf+XfonLk16nlc/hHu6+2aHg+ou04H5XIoMscaXp/6f1HN c3Y= "]]}, "0.9`"], Annotation[#, 0.9, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwV01toz2EYwPFnpBC28R82xxnb7IBcDFFSRk1RDqltZROzodnajAtDppYa uWJm5VgzZ824kFCoKaxw4TBcaLkbN7iSj4tv3+d93ud93sOvX+bWPetrkyKi D8MSEUUzIpI4JysiG0tyIxZj+OSIM3kRHTiFdpzGz4KIq3wNt3Ii7qCxMOI2 7+XutIgGfmn+cEbEGPVjMQ6/ZkWUZUeU4rf4kPmEPQenRHSJK6zbwqO5kkdy BY/iE/rWcIF9qrmQ87B5UkQ+P+MN9tiEjag3LpsTUY4ia+dPjVjEPfa9izZ9 3yHN3b8663Hxl/93tfYz73SuEm/Q6C2WT1Rj/VrjBdMi1nHxTL3lz3InCt3h hV4L0aJmJT/Ro1XcoX5QzQH1Q9wmd07upndol7sxWw33GvfID3Cvcb/8ff5m 3CefNT1iXmbEG7kG/i6XK1cnrsWQPWtRJ1ePfrnX6HS2t5yRHtEkn84POdUb JeZGrDZO4VX8wP1HeKc2fWryI1Y4Q4s3PIIS+WXeYQ3fM3dUrvn/O1tTjlI8 N37qe+z3jQ6Ki+W2GVdhl9x23s0n9aj25pXiGq7CD9/lr77JcjuMk61NQSr+ mEvwBIxHi/lXvtM+tdf1+qRvk3iAW/k9f8Qx8QcuVfNI78fosq4bV7BUn0t8 GedxERfQ7L+ocdd/rk19Sw== "]], LineBox[CompressedData[" 1:eJwV0ktsjGEUxvEzSCpCLFyL6kxLp7QWREnrMmUiURti0QqmRYJEtEWIuCyQ poI0qixIW1KtEisJaqNCIlPpqjQs7CRW7c5lY8PP4p/nvOc553zne78vdah1 d0siIvLonxtROC+ibFVEGlERMQ1TUbMo4v7KiAfoRi96sEf9MP8NxtIRn3BS 70d6ivbyT9BRtWfM2Cl+Jne2JCIpviP3rlJdYcRb2kP7eN30l/MO/g9aR3/S m3qbzD6m9wBtpznaRi8siGgUN9vlOIbVv0Za/ndZxBrxalQvidhuzrnlEefR sCwiscJMPUHzqYgiO6yzw4vFEetpsXOBOd/LI54vjZil5x5vOu+9+sn5EUP0 FXL8fTgonk3raQMuqv+6MGKveER9khbwd3nuqHkfkMdT3ph96+SfOA9iAB3y D+Uz8tvM+pKMyNJx2mFuc5EdSiM2+I6nxZ3yJbQUV8XtaDCjhtaqT8k3qZ9p xn7vNYNW8zK8cXeU4zXis7iWvwWHPT9LtyLrrip5Ve6yz0717rLFHV13xzdQ IVeJK3a/jDa9l2iKHvG9kvQo7dC/2ffNYCO+uetJfRPY5Dxh1jVapPZlccQU 5wQCrfIj/q1W3l1zWujg/3+APqb9eIQBlPO7zLyNTrt34RYS3net96lCqfdN 8v/MMd6z/rqTfyiidiM= "]]}, "0.8`"], Annotation[#, 0.8, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwV0jtI1mEUx/HTkg4Nar2vWnkvLbtBNBddhjKNaikjGxyEChO8TFFgNOXQ 0mJBF1sthZKIDKIgole00sEhNNQysrxk5GWIPg5ffuc55zy/5/yf519U23Dy 0qqISOF9IuJZgZimb4zYszliviziDwpKI/K3RBzdEdGmXiC+QX9tj5jGT+xf H/G1OGICd9S+0UkclJ9RP0BnaSaPDGTyuKhvyjk/0Jsd8dhZL3Ijzqr30qfq V+2rtb5CO/m9lM8oieiyHtkQ0axnWP6N2U/hNHK3ReSgmu9xe08gz9n5mNB/ wfeM0/O0g0//1oghvgO0T08KH8SVZrwpLsqJqFj5/pWZnd1EGzHqng4VRuzK i7grv5vetm5HTTLiHr2PnebsUH+Ia3pe0eu0nW+V2rieMbTJPeD7yFxd6Nzk DugT9Mh/piMYkB+nY3gtX5wfUb8uYoFvoXiSbyvfhiLvI78kv4hGtRa5ZsyZ L0X70CL/jjbRQdpL2+zb55wk1rqLLDznmaRH3NUaephm0wTmxWf0VmMvpt1v vfnKvesiXcYSpsoj/uGy+ii/bvefZbZp+996xxla471maY+e3/Sc9Rwd9n/0 80vwSfjuCvlWPUlxQpzEsveq4rlEj9EhnoNIc8ZH+gmV8n/VF7GAWu9YwuMW rzLepUi3TkO3f6hOfbX7+mLvd3v/Aw9tjZ8= "]], LineBox[CompressedData[" 1:eJwV00tI1FEUx/GTpVBNJmTPGcexplJ6GFii4sKgRYtyEZSChqCCFFGQFJUL 21WQgbppFb2zZRmEQVFBQWRZtCgLUhc9FKpdgUL1cfHld1733HPv/f9LWo/s OTwnIt7i39KIz6sZyyKaUxEVy8XW80sjsusiltBdmyL61RWym9Qk+IuwEO2r Ioatf4m8NWJIYEB8i3w5KtnfN0Zso5O0W6+MXqdpgT0W45092+RaUcG/JLfb 2q/mucFutLaF30C/qdlMRzdEfMQp+VH7n6R3+HXq7tLt6uowyO5eG1HMLsHk 7P70b5mz4sfKiJpsxFx2Na1CrVgOP0GnzTqDreItep0p1D8dcYL+waOSiIvJ iCf0MabcZRttR7O68RXOxc5nN9IC+kksQafcVYceeexmOoEX9nmGEffwGvVi H3BL7BquiF1GrdgI3mS8JY4XRVzQ9xi9r28n7RU/JJZl97P7kDXredqDjHiP 2jTN6PUQfe6mH3uduRENqHSmHTSpV536XnP0oWv2/pFUP+ZeU3ScdpjvqngV vwbVmPEG0zgq/957ddJXaoYxIZ/1pl3e7jf/ulw9e5/YIPuBd2jiD9EB38qQ 7+KLXikz7RQ/qKaIfYCO65W0boymaKl8GW6yF5h9PnJnv1Ez3MZ+8XnyecjF WT3y9TpH085RhF/2/Ilye+b4B57L3SuOeGrtf4uRfuY= "]]}, "0.7000000000000001`"], Annotation[#, 0.7000000000000001, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwNkLtOQkEURRfxQYkJEqOQGFEUFLQgUPsDmkgidhYWlgI98hNW+gM+In/h Nyi296JIkATxUaiJrmJlzz4z+8yZWTqqVU4iwJ4wC6VF+ItDZhmKrvfnYCoF VTWqTst6AsZr0LH2pj6qp3loSVO+9E9J6MpAv70ArxswlAuzYRrO1fwqFKSX gbZ9XtS+fJg/KMCneuW5d7WqH6ttZ7p1zrK+Pq93v2s9lJksxOTZHjf2u5az nGvvu/Tcj/d/y6HzRM0HzhdKYLbmnA2py4N+ZPZePdbnzE747knZtXZnfkfd cpYV/+nX/9p0HXH/H0ejOUE= "]], LineBox[CompressedData[" 1:eJwNkD1LQnEYxc+li2OhaYIKokOF6d5nsElR0MF3HdNFAyfrM9jekpOgXKc+ RYGmDkaOloJNUVqCv+HHuef5Py+HGyjW4lVDUgwenZLHJfX8Uh9uoO2Wsj7p Hs2jOTiibp5LM2oH6BvaCNMPdVjgM/QZJ9JhRKp4pP8LaQdd9j8H+Q5Jr2fS GOynkgOOYclskpkVatH7iSbwH2iHfD9oCv+LPvG+RdP4DRokSwCc7JmydwJR 7rxw74HeL+6v4Yo83+Q0yVcg5x+zLfwd3MIcb2PPO3qNTzNboq8Ml9QWzA+9 0ggG/AsLmlDhfQ/R0jkh "]], LineBox[CompressedData[" 1:eJwl01toyGEYx/GHHC6WRo05bBjGHMspNZZszHmY2JwZscJmogkJVxTadqPE FXOIJKc5JLkxSWMMMQwpmeOVQyif5eLb732e5/c+7+n/TysqzS9pFRG/kNo1 YnX/iBQ6KSPiSUrEir4RyzEeE+SXyXfoEbGS5ojn02xaRNNTIw7w7UMv47Xy 6by3kyJGD44YhQq1bbxbUdYloqF3xEZazl/Ff0j+uD2cQHW/iFP0ZAvyDfQx auWf0ie4Ln/LvISeEXf1WZQWcY/Wyt/BF+t9xTcs5VmG9t0iDtpXO3qTf5Xc +0ERld0jRupdRZvFCep/9RhLx8hn0j/iGv42AyOyxG3pxSERF3AeO9Ijzjnn Onv72Nkd0GaarbY9mVftEuaLC9Bo/AIv0Yq3dcs8a+0WJ5qX6Q1y+CZixQD3 jiK8Vm/CKyxQK0SG/t/NH0h/0E/md3Luz3TPUOfQa5f9LTTeSa+YcxXXUIM1 ehWjDf/lljWdL8H5JtFE2lHfn87fRZxsj4t5l+C39611j0nym9xNZ1pKS/CS /4P3eU6b8Ao73X0Z/0PvlMaTr8dcvNOnXt86PLf/Z5gn14izcqdxRu40JvLn IE+vGXjnO9qiX6X+Vbjh3JutW2E8yrc1GmXi4fSw2hEMNS6h67EO09XL+fvQ MjqFFssPt84INLq/yeJcTFU/4I72Yx8Wus9qnmE8b91fIk+D7yjPW21wbwXq hZjDm4963od4hBk8MzEV0zENSc48ji8LueIpmIwH/PdRh9lqs3DM+ChKrTNW nN3yr+KNfRS7q73eIzfj///9D+XwnR8= "]]}, "0.6000000000000001`"], Annotation[#, 0.6000000000000001, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[{5576, 7988, 5577, 10024, 10025, 10022, 5972, 10023, 11046, 11045, 11399, 11398, 5971, 8930, 7128, 7129, 6075, 10156, 10155, 9523, 5970, 10021, 6146, 10020, 5969, 9520, 9521, 9522, 6074, 7127, 7126, 8875, 5968, 11396, 11397, 11042, 11044, 11043, 11602, 5967, 11316, 10017, 10019, 10018, 5575, 7984, 6851}], LineBox[{5634, 8055, 5635, 9993, 9994, 9482, 10241, 10242, 6106, 11367, 11369, 11368, 6037, 8909, 7130, 7131, 6059, 9996, 5940, 9995, 5941, 9997, 11237, 9765, 10110, 11334, 11335, 10109, 9646, 9647, 6060, 7952, 5942, 8912, 5943, 11371, 11372, 11370, 6109, 10245, 11603, 6038, 11336, 10111, 10113, 10112, 5637, 7953, 6886}], LineBox[CompressedData[" 1:eJwl0ztP1FEQxuEBRBMTxAJvUVmWRVABExsxAQoXb4WVlbFQrtIsi40GEhsL Cy1cCxQMjR9ANAoCaoKJggFsNGIUjSYmFhrdwsRLpz4bi1/ec2beMzP/s2eT nf1Hs0URMYvExohD2yMq6WH6ZktEdUVEdyritfXe9RFfExFNtF2+AydwtSFi CDO8Seyqj+hypkeuG8f4L1dF5FC3NaIWQ9YDtJV/mjeHK/pe5z+42Ry4LzbG k3O+OBlxUqwDz8WXxG+Kp8QzYlm8Fy+rjHgm/lSdD+rlxeasZ1Eh18vfQTvx xPox8vyfd0Z8QXlNxFoMmmtO7iJt9z17xP6q8QerN0TUVEdM6jmFlHU1ptW8 5x72beLZEZGmRWoWI/BKbgnDaq6wL0UJVmEl2vib9enR7xRK1kVsU7cWD9Qu 17eu0EfPMvXXoIW/FZfUfMjzw3w/8R2/8Quj/Au+ZRF9PJkC/HmMmecWlvk+ ua939IX7SPDM2390zxP29c6O0wn5uwVfbcQRM97W+479uPiwfCnfNTrl3Kj4 BTpof6OQt5/xe6SdS+t9Xm43XUCDGUe8iWEc5x/gH8QI/1l6Bnlvr49mkcFp 9KOF/5tcM33rnfY6k1Jz2fqA9X60oUr/Bd+6iHm8dN+NPJO8TY0R58z1qPCO G/7/F/4BX0162w== "]]}, "0.5`"], Annotation[#, 0.5, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[{5118, 7986, 5117, 7985, 8103}], LineBox[{5286, 5403, 8112, 8056, 8091}], LineBox[CompressedData[" 1:eJwl0l1ozXEcx/GPGzMPJ3vI4ybHw7EhXCnPylO5IblzYc40Np2RlSJyjbIm LXbnmkRKxgVX7lhNabJsp7VdUdpx5cpruXj3+X0/3+/39/1/f+cUy5dP9c5L 8gS7liWPNiQX2pKLOLoiuVdKdvOH+N28HhzjX6LjLUl1c3J/VTK4Pumne9cm e7BvizMe86+ov6P+jHu2tSZXxe/4fbSff40/qWdQfHx1MtqcHMIrtafpV7Vv nF/Iv6XDqCsmP+gEPvInaTuvDVN6zqJlTdKKKfkK/7a7x82bEY/Q6bk95H+b PytuWOlMl9KXW5O/7hjS0yT+xW+kNTqs57zdOvHH+xSWm+F9ltD69uSgujq6 n86nB+gCuli+qm4Rrek7p7+M1+5r5jehEQX1Pb63G9Pm1YsL/IV0RvzT93bq qXmXWVTt8Yn/md+hZ0LcJN+AjeIxb1Ok61Cxzwf5L7xRnLTjN3Twn/Kf8Ubc eYL33Pm73+U6vYEB+TFxnzm3zOsVP1S70w6b9Jdwk1/hl/kDeIC2ud8GR/hd 4u3qd+C9GV3qD/Pvlv7///4BeGVjgQ== "]]}, "0.4`"], Annotation[#, 0.4, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwlks0rw3Ecx9/iKpE0yVjWWjNxI0rcyM3VzcNJmZuE/eahqA2bkYfhH/Aw yUnKgZLHOGgUYuV5GQ6ym9cvh1fvfd/vz+fz/Xx/zdbqae5Kk+SHEafkgyEY hP5CqTZX2i6RwrCIF4GGAummWJq2SH3UhNEoGsyT0m1SCN3gvIZ/aSpnO/46 es15Dz/HKu2jDvxT/GPmnsAX9xyhh2ChxlomFUHcJT3BI8TpeyF/hWy7lJkv PfM76ZA+4R7vjbNRKv2y/7s5F/8b4mQJ831kKTIf2sv8LGZE3ewNSfIPcx57 xdAr+GGvFmo76UnACnWrcEZ2Aecm1Lt5zwH7Wdn9jp5uvpUHXPib5Le8P4bf jtcGGfgz+Fv4u/hNeHP0P/B9e/CXmLsMO2T13F/H3Qa1FWgEbwEC5H5opG8U HYNZ/Grqa2CKd3vRMBrh/SE0COXMmEAHyCbRebJxNABVeJXQwRyDeV5wstuw 8/9/8ge6OmX5 "]]}, "0.30000000000000004`"], Annotation[#, 0.30000000000000004`, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwl0b1LQnEUxvHHRXJPCcVQE8p7xVobGhpt06YWB8HyJbShliK3GoKMAqv/ QAcpCmqqDCNyE18ytDeo5qbc+0bDh3Pv+T2e31G98Vw0a5G0glufZLolA0WP 9DAshTBt8j4mbU9IW1h1SD3O+8iT3cQrz2fUCPkW2SYqI1LcRY5eFF3On1Cj f8WcG1yjT2/cK9lHJQcWeU6gwT2fhvSFH+YNkGJOkrN1auIviz32LmAqKE1i iH1PnJKNavdLS2S+mbVP5gAp3pPYYEaa2maHDlro4hF59s5wzzJcZJyIkf9A iTvKqJK757u8sP8zrGQvqJc4pd9m3zl2mOcz5/RmqU2Emf3O7/WGNfbaZU4B Ozhm7hFmODtEnbxJ/o69a1ggH2RWjvkG/QCqvv//7heEsE0Z "]]}, "0.2`"], Annotation[#, 0.2, "Tooltip"]& ], TagBox[ TooltipBox[ {GrayLevel[0], Opacity[0.5], LineBox[CompressedData[" 1:eJwl0L1OwmAYxfHDPfAhJJqgxpSg3AFQXJ1g4SNhYSIMOrpyAyQEdQMBgaEF BbwCSNyExIESNwyC1+G/YfjlpM/7tD15w6W7zK1HUh4jQ7LwdiTZbuIVY7/0 eS4tsEQ6KhW9UuBEKpM5nrOwYSHlk2qn0u+ltMMWf9jjnjOHnTWGGOGaWZ39 8BXvs2Mjz7yACt8P8p8ZPeb4vpCm9ImxMyGnzN7hnEk37K/IidsZj5xH2Hsg DbLNbED2UT2WOmTXnaOHF5h0+aBLkkzQ5ydIt5C0IeM8J5jPOY+TLfaf0cQT d/ZF1yRM9y7o2eC/FvdlY2gc7vcfba1Bjw== "]]}, "0.1`"], Annotation[#, 0.1, "Tooltip"]& ], {}, {}}}], AspectRatio->1, DisplayFunction->Identity, Frame->True, FrameTicks->{{Automatic, Automatic}, {Automatic, Automatic}}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], Method->{"DefaultBoundaryStyle" -> Automatic}, PlotRange->{{-2, 2}, {-2, 2}}, PlotRangeClipping->True, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.02], Scaled[0.02]}}, Ticks->{Automatic, Automatic}]], "Output", CellChangeTimes->{{3.7205556074236*^9, 3.7205556410396*^9}}] }, Open ]] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell["C\[AAcute]lculo del valor medio de H1", "Subsection", CellChangeTimes->{{3.7205528231216*^9, 3.7205528292076*^9}}], Cell[BoxData[ RowBox[{"Integrate", "[", RowBox[{ RowBox[{ FractionBox["1", RowBox[{"2", "\[Pi]"}]], RowBox[{"H1", "[", RowBox[{"\[Theta]", ",", " ", "i"}], "]"}]}], ",", " ", RowBox[{"{", RowBox[{"\[Theta]", ",", " ", "0", ",", " ", RowBox[{"2", "\[Pi]"}]}], "}"}]}], "]"}]], "Input", CellChangeTimes->{{3.7205469776098003`*^9, 3.7205470029498*^9}}], Cell[BoxData[ RowBox[{ RowBox[{ RowBox[{"H1medio", "[", "i_", "]"}], ":=", " ", RowBox[{ FractionBox["3", "2"], " ", SuperscriptBox["i", "2"], " ", SuperscriptBox["m", "2"], " ", SuperscriptBox["\[Omega]0", "2"]}]}], ";"}]], "Input", CellChangeTimes->{{3.7205469941348*^9, 3.7205470315748*^9}, 3.7205473238952*^9}] }, Open ]], Cell[CellGroupData[{ Cell["C\[AAcute]lculo de la correcci\[OAcute]n a la frecuencia:", "Subsection", CellChangeTimes->{{3.7205528383512*^9, 3.7205528456862*^9}}], Cell[BoxData[ RowBox[{"D", "[", RowBox[{ RowBox[{"H1medio", "[", "i", "]"}], ",", " ", "i"}], "]"}]], "Input", CellChangeTimes->{{3.7205471934866*^9, 3.7205471993124*^9}}], Cell[BoxData[ RowBox[{ RowBox[{ RowBox[{"\[Omega]", "[", "i_", "]"}], ":=", " ", RowBox[{"\[Omega]0", " ", "+", " ", RowBox[{"3", " ", "i", " ", SuperscriptBox["m", "2"], " ", "\[Epsilon]", " ", SuperscriptBox["\[Omega]0", "2"]}]}]}], ";"}]], "Input", CellChangeTimes->{{3.7205472076038*^9, 3.7205472288970003`*^9}}] }, Open ]], Cell[CellGroupData[{ Cell["\<\ C\[AAcute]lculo de la correcci\[OAcute]n a la transformaci\[OAcute]n can\ \[OAcute]nica que relaciona las variables AA de H0 a las de H1, llamadas \ aqu\[IAcute] \[Theta], J y \[Phi], i, respectivamente\ \>", "Subsection", CellChangeTimes->{{3.7205528500582*^9, 3.720552879215*^9}, { 3.7205529728836*^9, 3.7205529840758*^9}}], Cell[BoxData[ RowBox[{"Integrate", "[", RowBox[{ RowBox[{ FractionBox["1", "\[Omega]0"], RowBox[{"(", RowBox[{ RowBox[{"H1medio", "[", "i", "]"}], " ", "-", " ", RowBox[{"H1", "[", RowBox[{"\[Theta]p", ",", " ", "i"}], "]"}]}], ")"}]}], ",", " ", RowBox[{"{", RowBox[{"\[Theta]p", ",", " ", "0", ",", " ", "\[Theta]"}], "}"}]}], "]"}]], "Input", CellChangeTimes->{{3.7205470152218*^9, 3.7205470621188*^9}}], Cell[BoxData[ RowBox[{ RowBox[{ RowBox[{"y1", "[", RowBox[{"\[Theta]_", ",", " ", "i_"}], "]"}], ":=", " ", RowBox[{ RowBox[{"-", FractionBox["1", "8"]}], " ", SuperscriptBox["i", "2"], " ", SuperscriptBox["m", "2"], " ", "\[Omega]0", " ", RowBox[{"(", RowBox[{ RowBox[{"8", " ", RowBox[{"Sin", "[", RowBox[{"2", " ", "\[Theta]"}], "]"}]}], "+", RowBox[{"Sin", "[", RowBox[{"4", " ", "\[Theta]"}], "]"}]}], ")"}]}]}], ";"}]], "Input", CellChangeTimes->{{3.7205470670422*^9, 3.7205470758858*^9}, 3.7205473394094*^9}] }, Open ]], Cell[CellGroupData[{ Cell["\<\ Las ecuaciones de transformaci\[OAcute]n entre las nuevas variables de AA y \ las antiguas\ \>", "Subsection", CellChangeTimes->{{3.7205528869058*^9, 3.7205529007344*^9}, { 3.7205540979992*^9, 3.7205540998576*^9}}], Cell[BoxData[{ RowBox[{ RowBox[{ RowBox[{"Jota", "[", RowBox[{"\[Phi]_", ",", " ", "i_"}], "]"}], ":=", " ", RowBox[{"i", " ", "+", " ", RowBox[{"\[Epsilon]", " ", RowBox[{ RowBox[{ RowBox[{"Derivative", "[", RowBox[{"1", ",", "0"}], "]"}], "[", "y1", "]"}], "[", RowBox[{"\[Phi]", ",", " ", "i"}], "]"}]}]}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"Theta", "[", RowBox[{"\[Phi]_", ",", " ", "i_"}], "]"}], ":=", " ", RowBox[{"\[Phi]", " ", "-", " ", RowBox[{"\[Epsilon]", " ", RowBox[{ RowBox[{ RowBox[{"Derivative", "[", RowBox[{"0", ",", "1"}], "]"}], "[", "y1", "]"}], "[", RowBox[{"\[Phi]", ",", " ", "i"}], "]"}]}]}]}], ";"}]}], "Input", CellChangeTimes->{{3.7205470844552*^9, 3.7205471825994*^9}, 3.7205472354709997`*^9, {3.7205473004128*^9, 3.7205473005064*^9}}] }, Open ]], Cell[CellGroupData[{ Cell["\<\ Expansi\[OAcute]n hasta orden \[Epsilon] de las variables originales x y p \ como funciones del tiempo\ \>", "Subsection", CellChangeTimes->{{3.7205529083472*^9, 3.7205529384666*^9}}], Cell[BoxData[{ RowBox[{ SqrtBox[ FractionBox[ RowBox[{"2", " ", "i"}], RowBox[{"m", " ", "\[Omega]0"}]]], RowBox[{"Collect", "[", RowBox[{ RowBox[{ FractionBox["1", RowBox[{ SqrtBox["2"], " ", SqrtBox[ FractionBox["i", RowBox[{"m", " ", "\[Omega]0"}]]]}]], RowBox[{"Normal", "[", RowBox[{"Series", "[", RowBox[{ RowBox[{"x", "[", RowBox[{ RowBox[{"Theta", "[", RowBox[{"\[Phi]", ",", " ", "i"}], "]"}], ",", " ", RowBox[{"Jota", "[", RowBox[{"\[Phi]", ",", " ", "i"}], "]"}]}], "]"}], ",", " ", RowBox[{"{", RowBox[{"\[Epsilon]", ",", " ", "0", ",", " ", "1"}], "}"}]}], "]"}], "]"}]}], ",", " ", "\[Epsilon]", ",", " ", "Simplify"}], "]"}]}], "\[IndentingNewLine]", RowBox[{ SqrtBox[ RowBox[{"2", " ", "i", " ", "m", " ", "\[Omega]0"}]], RowBox[{"Collect", "[", RowBox[{ RowBox[{ FractionBox["1", SqrtBox[ RowBox[{"2", " ", "i", " ", "m", " ", "\[Omega]0"}]]], RowBox[{"Normal", "[", RowBox[{"Series", "[", RowBox[{ RowBox[{"p", "[", RowBox[{ RowBox[{"Theta", "[", RowBox[{"\[Phi]", ",", " ", "i"}], "]"}], ",", " ", RowBox[{"Jota", "[", RowBox[{"\[Phi]", ",", " ", "i"}], "]"}]}], "]"}], ",", " ", RowBox[{"{", RowBox[{"\[Epsilon]", ",", " ", "0", ",", " ", "1"}], "}"}]}], "]"}], "]"}]}], ",", " ", "\[Epsilon]", ",", " ", "Simplify"}], "]"}]}]}], "Input", CellChangeTimes->{{3.7205472432166*^9, 3.7205472775912*^9}, { 3.7205473087492*^9, 3.7205473141226*^9}, {3.720547348483*^9, 3.7205474089494*^9}}], Cell[BoxData[{ RowBox[{ RowBox[{ RowBox[{"x\[Epsilon]", "[", RowBox[{"\[Phi]_", ",", " ", "i_", ",", " ", "\[Epsilon]_"}], "]"}], ":=", " ", RowBox[{ SqrtBox["2"], " ", SqrtBox[ FractionBox["i", RowBox[{"m", " ", "\[Omega]0"}]]], " ", RowBox[{"(", RowBox[{ RowBox[{"Sin", "[", "\[Phi]", "]"}], "+", RowBox[{ FractionBox["3", "4"], " ", "i", " ", SuperscriptBox["m", "2"], " ", "\[Epsilon]", " ", "\[Omega]0", " ", RowBox[{"(", RowBox[{"3", "+", RowBox[{"2", " ", RowBox[{"Cos", "[", RowBox[{"2", " ", "\[Phi]"}], "]"}]}]}], ")"}], " ", RowBox[{"Sin", "[", "\[Phi]", "]"}]}]}], ")"}]}]}], ";"}], "\n", RowBox[{ RowBox[{ RowBox[{"p\[Epsilon]", "[", RowBox[{"\[Phi]_", ",", " ", "i_", ",", " ", "\[Epsilon]_"}], "]"}], ":=", " ", RowBox[{ SqrtBox["2"], " ", SqrtBox[ RowBox[{"i", " ", "m", " ", "\[Omega]0"}]], " ", RowBox[{"(", RowBox[{ RowBox[{"Cos", "[", "\[Phi]", "]"}], "+", RowBox[{ FractionBox["1", "4"], " ", "i", " ", SuperscriptBox["m", "2"], " ", "\[Epsilon]", " ", "\[Omega]0", " ", RowBox[{"(", RowBox[{ RowBox[{ RowBox[{"-", "6"}], " ", RowBox[{"Cos", "[", "\[Phi]", "]"}]}], "+", RowBox[{"Cos", "[", RowBox[{"3", " ", "\[Phi]"}], "]"}]}], ")"}]}]}], ")"}]}]}], ";"}]}],\ "Input", CellChangeTimes->{{3.7205474399519997`*^9, 3.7205474807808*^9}, { 3.7205504698459997`*^9, 3.7205504858636*^9}}] }, Open ]], Cell[CellGroupData[{ Cell["\<\ C\[AAcute]lculo de las constantes i y \[Phi]0 a orden \[Epsilon] a partir de \ las condiciones iniciales (ser\[IAcute]a largo de explicar)\ \>", "Subsection", CellChangeTimes->{{3.7205529586242*^9, 3.7205530433445997`*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Collect", "[", RowBox[{ RowBox[{"Normal", "[", RowBox[{"Series", "[", RowBox[{ RowBox[{ RowBox[{ FractionBox[ RowBox[{"m", " ", SuperscriptBox["\[Omega]0", "2"]}], "2"], SuperscriptBox[ RowBox[{"x\[Epsilon]", "[", RowBox[{"\[Phi]0", ",", " ", "i", ",", " ", "\[Epsilon]"}], "]"}], "2"]}], "+", " ", RowBox[{ FractionBox["1", RowBox[{"2", "m"}]], SuperscriptBox[ RowBox[{"p\[Epsilon]", "[", RowBox[{"\[Phi]0", ",", " ", "i", ",", " ", "\[Epsilon]"}], "]"}], "2"]}]}], ",", " ", RowBox[{"{", RowBox[{"\[Epsilon]", ",", " ", "0", ",", " ", "1"}], "}"}]}], "]"}], "]"}], ",", " ", "\[Epsilon]", ",", " ", "Simplify"}], "]"}]], "Input", CellChangeTimes->{{3.7205474932718*^9, 3.7205475052826*^9}, { 3.720547568074*^9, 3.7205475698086*^9}, {3.7205477102757998`*^9, 3.7205477621702003`*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"i", " ", "\[Omega]0"}], "-", RowBox[{ FractionBox["1", "2"], " ", SuperscriptBox["i", "2"], " ", SuperscriptBox["m", "2"], " ", "\[Epsilon]", " ", SuperscriptBox["\[Omega]0", "2"], " ", RowBox[{"(", RowBox[{ RowBox[{"4", " ", RowBox[{"Cos", "[", RowBox[{"2", " ", "\[Phi]0"}], "]"}]}], "+", RowBox[{"Cos", "[", RowBox[{"4", " ", "\[Phi]0"}], "]"}]}], ")"}]}]}]], "Output", CellChangeTimes->{ 3.720547660928*^9, {3.7205477241466*^9, 3.7205477327132*^9}, 3.7205477629189997`*^9}] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"PowerExpand", "[", RowBox[{"Collect", "[", RowBox[{ RowBox[{"Normal", "[", RowBox[{"Series", "[", RowBox[{ RowBox[{"PowerExpand", "[", RowBox[{"ArcTan", "[", RowBox[{"m", " ", "\[Omega]0", FractionBox[ RowBox[{"x\[Epsilon]", "[", RowBox[{"\[Phi]0", ",", " ", "i", ",", " ", "\[Epsilon]"}], "]"}], RowBox[{"p\[Epsilon]", "[", RowBox[{"\[Phi]0", ",", " ", "i", ",", " ", "\[Epsilon]"}], "]"}]]}], "]"}], "]"}], ",", " ", RowBox[{"{", RowBox[{"\[Epsilon]", ",", " ", "0", ",", " ", "1"}], "}"}]}], "]"}], "]"}], ",", " ", "\[Epsilon]", ",", " ", "FullSimplify"}], "]"}], "]"}]], "Input", CellChangeTimes->{{3.7205478176958*^9, 3.7205479204491997`*^9}}], Cell[BoxData[ RowBox[{"\[Phi]0", "+", RowBox[{"i", " ", SuperscriptBox["m", "2"], " ", "\[Epsilon]", " ", "\[Omega]0", " ", RowBox[{"Cos", "[", "\[Phi]0", "]"}], " ", RowBox[{"(", RowBox[{"4", "+", RowBox[{"Cos", "[", RowBox[{"2", " ", "\[Phi]0"}], "]"}]}], ")"}], " ", RowBox[{"Sin", "[", "\[Phi]0", "]"}]}]}]], "Output", CellChangeTimes->{{3.7205478774772*^9, 3.7205479206364*^9}}] }, Open ]], Cell[BoxData[{ RowBox[{ RowBox[{"Phi0", " ", "=", " ", RowBox[{ RowBox[{"ArcTan", "[", RowBox[{"m", " ", "\[Omega]0", " ", FractionBox["x0", "p0"]}], "]"}], " ", "+", " ", RowBox[{"\[Epsilon]", " ", "Phi1"}]}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"I0", " ", "=", RowBox[{ RowBox[{ FractionBox["1", "\[Omega]0"], RowBox[{"(", " ", RowBox[{ RowBox[{ FractionBox[ RowBox[{"m", " ", SuperscriptBox["\[Omega]0", "2"]}], "2"], SuperscriptBox["x0", "2"]}], "+", " ", RowBox[{ FractionBox["1", RowBox[{"2", "m"}]], SuperscriptBox["p0", "2"]}]}], ")"}]}], " ", "+", " ", RowBox[{"\[Epsilon]", " ", "I1"}]}]}], ";"}]}], "Input", CellChangeTimes->{{3.7205479433066*^9, 3.720548041028*^9}, { 3.7205483708204*^9, 3.7205483725842*^9}, {3.7205489057307997`*^9, 3.7205489118696003`*^9}}], Cell[CellGroupData[{ Cell[BoxData[{ RowBox[{"exp1", " ", "=", " ", RowBox[{"Collect", "[", RowBox[{ RowBox[{"Normal", "[", RowBox[{"Series", "[", RowBox[{ RowBox[{ RowBox[{"I0", " ", "\[Omega]0"}], "-", RowBox[{ FractionBox["1", "2"], " ", SuperscriptBox["I0", "2"], " ", SuperscriptBox["m", "2"], " ", "\[Epsilon]", " ", SuperscriptBox["\[Omega]0", "2"], " ", RowBox[{"(", RowBox[{ RowBox[{"4", " ", RowBox[{"Cos", "[", RowBox[{"2", " ", "Phi0"}], "]"}]}], "+", RowBox[{"Cos", "[", RowBox[{"4", " ", "Phi0"}], "]"}]}], ")"}]}]}], ",", " ", RowBox[{"{", RowBox[{"\[Epsilon]", ",", " ", "0", ",", " ", "1"}], "}"}]}], "]"}], "]"}], ",", " ", "\[Epsilon]", ",", " ", "FullSimplify"}], "]"}]}], "\[IndentingNewLine]", RowBox[{"exp2", " ", "=", " ", RowBox[{"Collect", "[", RowBox[{ RowBox[{"TrigExpand", "[", RowBox[{"Collect", "[", RowBox[{ RowBox[{"Normal", "[", RowBox[{"Series", "[", RowBox[{ RowBox[{"Phi0", "+", RowBox[{"I0", " ", SuperscriptBox["m", "2"], " ", "\[Epsilon]", " ", "\[Omega]0", " ", RowBox[{"Cos", "[", "Phi0", "]"}], " ", RowBox[{"(", RowBox[{"4", "+", RowBox[{"Cos", "[", RowBox[{"2", " ", "Phi0"}], "]"}]}], ")"}], " ", RowBox[{"Sin", "[", "Phi0", "]"}]}]}], ",", " ", RowBox[{"{", RowBox[{"\[Epsilon]", ",", " ", "0", ",", " ", "1"}], "}"}]}], "]"}], "]"}], ",", " ", "\[Epsilon]", ",", " ", "FullSimplify"}], "]"}], "]"}], ",", " ", "\[Epsilon]", ",", " ", "FullSimplify"}], "]"}]}]}], "Input", CellChangeTimes->{{3.7205480708052*^9, 3.7205480780254*^9}, { 3.720548286457*^9, 3.7205483581306*^9}, {3.7205484010316*^9, 3.7205484342799997`*^9}, {3.7205489452462*^9, 3.7205489641558*^9}}], Cell[BoxData[ RowBox[{ FractionBox[ RowBox[{ SuperscriptBox["p0", "2"], "+", RowBox[{ SuperscriptBox["m", "2"], " ", SuperscriptBox["x0", "2"], " ", SuperscriptBox["\[Omega]0", "2"]}]}], RowBox[{"2", " ", "m"}]], "+", RowBox[{ FractionBox["1", "8"], " ", "\[Epsilon]", " ", RowBox[{"(", RowBox[{ RowBox[{ RowBox[{"-", "5"}], " ", SuperscriptBox["p0", "4"]}], "+", RowBox[{"8", " ", "I1", " ", "\[Omega]0"}], "+", RowBox[{"6", " ", SuperscriptBox["m", "2"], " ", SuperscriptBox["p0", "2"], " ", SuperscriptBox["x0", "2"], " ", SuperscriptBox["\[Omega]0", "2"]}], "+", RowBox[{"3", " ", SuperscriptBox["m", "4"], " ", SuperscriptBox["x0", "4"], " ", SuperscriptBox["\[Omega]0", "4"]}]}], ")"}]}]}]], "Output", CellChangeTimes->{{3.7205483416818*^9, 3.7205483749206*^9}, 3.7205484375182*^9, 3.7205489133048*^9, {3.7205489480727997`*^9, 3.7205489648422003`*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"\[Epsilon]", " ", RowBox[{"(", RowBox[{"Phi1", "+", RowBox[{ FractionBox["1", "2"], " ", SuperscriptBox["m", "2"], " ", "p0", " ", "x0", " ", "\[Omega]0", " ", RowBox[{"(", RowBox[{"3", "+", FractionBox[ RowBox[{"2", " ", SuperscriptBox["p0", "2"]}], RowBox[{ SuperscriptBox["p0", "2"], "+", RowBox[{ SuperscriptBox["m", "2"], " ", SuperscriptBox["x0", "2"], " ", SuperscriptBox["\[Omega]0", "2"]}]}]]}], ")"}]}]}], ")"}]}], "+", RowBox[{"ArcTan", "[", FractionBox[ RowBox[{"m", " ", "x0", " ", "\[Omega]0"}], "p0"], "]"}]}]], "Output", CellChangeTimes->{{3.7205483416818*^9, 3.7205483749206*^9}, 3.7205484375182*^9, 3.7205489133048*^9, {3.7205489480727997`*^9, 3.7205489651126003`*^9}}] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"sol", " ", "=", " ", RowBox[{ RowBox[{"FullSimplify", "[", RowBox[{"Solve", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{ RowBox[{"Coefficient", "[", RowBox[{"exp1", ",", " ", "\[Epsilon]"}], "]"}], " ", "\[Equal]", " ", "0"}], ",", " ", RowBox[{ RowBox[{"Coefficient", "[", RowBox[{"exp2", ",", " ", "\[Epsilon]"}], "]"}], " ", "\[Equal]", " ", "0"}]}], "}"}], ",", " ", RowBox[{"{", RowBox[{"I1", ",", " ", "Phi1"}], "}"}]}], "]"}], "]"}], "[", RowBox[{"[", "1", "]"}], "]"}]}]], "Input", CellChangeTimes->{{3.7205484577556*^9, 3.7205485080559998`*^9}, 3.7205489364886*^9, {3.720548975417*^9, 3.7205489890608*^9}, { 3.7205490197567997`*^9, 3.7205490220968*^9}}], Cell[BoxData[ RowBox[{"{", RowBox[{ RowBox[{"I1", "\[Rule]", FractionBox[ RowBox[{ RowBox[{"5", " ", SuperscriptBox["p0", "4"]}], "-", RowBox[{"6", " ", SuperscriptBox["m", "2"], " ", SuperscriptBox["p0", "2"], " ", SuperscriptBox["x0", "2"], " ", SuperscriptBox["\[Omega]0", "2"]}], "-", RowBox[{"3", " ", SuperscriptBox["m", "4"], " ", SuperscriptBox["x0", "4"], " ", SuperscriptBox["\[Omega]0", "4"]}]}], RowBox[{"8", " ", "\[Omega]0"}]]}], ",", RowBox[{"Phi1", "\[Rule]", RowBox[{ FractionBox["1", "2"], " ", SuperscriptBox["m", "2"], " ", "p0", " ", "x0", " ", "\[Omega]0", " ", RowBox[{"(", RowBox[{ RowBox[{"-", "3"}], "-", FractionBox[ RowBox[{"2", " ", SuperscriptBox["p0", "2"]}], RowBox[{ SuperscriptBox["p0", "2"], "+", RowBox[{ SuperscriptBox["m", "2"], " ", SuperscriptBox["x0", "2"], " ", SuperscriptBox["\[Omega]0", "2"]}]}]]}], ")"}]}]}]}], "}"}]], "Output", CellChangeTimes->{{3.7205484994035997`*^9, 3.7205485085718*^9}, 3.7205489905945997`*^9, 3.72054902244*^9}] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell["\<\ Las condiciones iniciales para i y \[Phi] a partir de las condiciones \ iniciales para x y p, m\[AAcute]s la condici\[OAcute]n inicial para p si el \ dato es la velocidad v.\ \>", "Subsection", CellChangeTimes->{{3.7205530540326*^9, 3.7205530952441998`*^9}}], Cell[BoxData[{ RowBox[{ RowBox[{ RowBox[{"\[Phi]0", "[", RowBox[{"x0_", ",", " ", "p0_", ",", " ", "\[Epsilon]_"}], "]"}], " ", ":=", " ", RowBox[{ RowBox[{"ArcTan", "[", RowBox[{"m", " ", "\[Omega]0", " ", FractionBox["x0", "p0"]}], "]"}], " ", "+", " ", RowBox[{"\[Epsilon]", " ", FractionBox["1", "2"], " ", SuperscriptBox["m", "2"], " ", "p0", " ", "x0", " ", "\[Omega]0", " ", RowBox[{"(", RowBox[{ RowBox[{"-", "3"}], "-", FractionBox[ RowBox[{"2", " ", SuperscriptBox["p0", "2"]}], RowBox[{ SuperscriptBox["p0", "2"], "+", RowBox[{ SuperscriptBox["m", "2"], " ", SuperscriptBox["x0", "2"], " ", SuperscriptBox["\[Omega]0", "2"]}]}]]}], ")"}]}]}]}], " ", ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"i0", "[", RowBox[{"x0_", ",", " ", "p0_", ",", " ", "\[Epsilon]_"}], "]"}], ":=", RowBox[{ RowBox[{ FractionBox["1", "\[Omega]0"], RowBox[{"(", " ", RowBox[{ RowBox[{ FractionBox[ RowBox[{"m", " ", SuperscriptBox["\[Omega]0", "2"]}], "2"], SuperscriptBox["x0", "2"]}], "+", " ", RowBox[{ FractionBox["1", RowBox[{"2", "m"}]], SuperscriptBox["p0", "2"]}]}], " ", ")"}]}], "+", RowBox[{"\[Epsilon]", " ", FractionBox[ RowBox[{ RowBox[{"5", " ", SuperscriptBox["p0", "4"]}], "-", RowBox[{"6", " ", SuperscriptBox["m", "2"], " ", SuperscriptBox["p0", "2"], " ", SuperscriptBox["x0", "2"], " ", SuperscriptBox["\[Omega]0", "2"]}], "-", RowBox[{"3", " ", SuperscriptBox["m", "4"], " ", SuperscriptBox["x0", "4"], " ", SuperscriptBox["\[Omega]0", "4"]}]}], RowBox[{"8", " ", "\[Omega]0"}]]}]}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"P0", "[", RowBox[{"v_", ",", " ", "\[Epsilon]_"}], "]"}], ":=", " ", RowBox[{ RowBox[{"m", " ", "v"}], " ", "-", " ", RowBox[{"4", " ", "\[Epsilon]", " ", SuperscriptBox["m", "4"], SuperscriptBox["v", "3"]}]}]}], ";"}]}], "Input", CellChangeTimes->{{3.7205485898487997`*^9, 3.72054860941*^9}, 3.7205486663992*^9, {3.7205487621586*^9, 3.7205487768114*^9}, { 3.720549010403*^9, 3.7205490591338*^9}, {3.7205492293458*^9, 3.7205492352748003`*^9}, {3.7205500957448*^9, 3.7205501566162*^9}, { 3.7205502137658*^9, 3.7205502139706*^9}}], Cell[CellGroupData[{ Cell["Verifiaciones milagrosas:", "Subsubsection", CellChangeTimes->{{3.720553100146*^9, 3.7205531040313997`*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"PowerExpand", "[", RowBox[{"FullSimplify", "[", RowBox[{ RowBox[{"Collect", "[", RowBox[{ RowBox[{"Normal", "[", RowBox[{"Series", "[", RowBox[{ RowBox[{"x\[Epsilon]", "[", RowBox[{ RowBox[{"\[Phi]0", "[", RowBox[{"x0", ",", " ", "p0", ",", " ", "\[Epsilon]"}], "]"}], ",", " ", RowBox[{"i0", "[", RowBox[{"x0", ",", " ", "p0", ",", " ", "\[Epsilon]"}], "]"}], ",", " ", "\[Epsilon]"}], "]"}], ",", " ", RowBox[{"{", RowBox[{"\[Epsilon]", ",", " ", "0", ",", "1"}], "}"}]}], "]"}], "]"}], ",", " ", "\[Epsilon]", ",", " ", "TrigExpand"}], "]"}], ",", " ", RowBox[{"{", RowBox[{ RowBox[{"x0", " ", ">", " ", "0"}], ",", " ", RowBox[{"\[Omega]0", ">", " ", "0"}], ",", " ", RowBox[{"p0", ">", "0"}], ",", " ", RowBox[{"m", ">", " ", "0"}]}], "}"}]}], "]"}], "]"}]], "Input", CellChangeTimes->{{3.7205485453372*^9, 3.7205485801717997`*^9}, { 3.7205486750476*^9, 3.7205487427234*^9}, {3.7205487840592003`*^9, 3.7205488330466003`*^9}, {3.720550163217*^9, 3.7205501747454*^9}}], Cell[BoxData["x0"], "Output", CellChangeTimes->{ 3.7205486979582*^9, {3.7205487297026*^9, 3.720548830137*^9}, { 3.720549043288*^9, 3.7205490612906*^9}, 3.7205492362586*^9, 3.7205501757976*^9}] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"PowerExpand", "[", RowBox[{"FullSimplify", "[", RowBox[{ RowBox[{"Collect", "[", RowBox[{ RowBox[{"Normal", "[", RowBox[{"Series", "[", RowBox[{ RowBox[{"p\[Epsilon]", "[", RowBox[{ RowBox[{"\[Phi]0", "[", RowBox[{"x0", ",", " ", "p0", ",", " ", "\[Epsilon]"}], "]"}], ",", " ", RowBox[{"i0", "[", RowBox[{"x0", ",", " ", "p0", ",", " ", "\[Epsilon]"}], "]"}], ",", " ", "\[Epsilon]"}], "]"}], ",", " ", RowBox[{"{", RowBox[{"\[Epsilon]", ",", " ", "0", ",", "1"}], "}"}]}], "]"}], "]"}], ",", " ", "\[Epsilon]", ",", " ", "TrigExpand"}], "]"}], ",", " ", RowBox[{"{", RowBox[{ RowBox[{"x0", " ", ">", " ", "0"}], ",", " ", RowBox[{"\[Omega]0", ">", " ", "0"}], ",", " ", RowBox[{"p0", ">", "0"}], ",", " ", RowBox[{"m", ">", " ", "0"}]}], "}"}]}], "]"}], "]"}]], "Input", CellChangeTimes->{{3.7205488408984003`*^9, 3.7205488463129997`*^9}, { 3.7205501803412*^9, 3.7205501834028*^9}}], Cell[BoxData["p0"], "Output", CellChangeTimes->{{3.720548844362*^9, 3.7205488470306*^9}, 3.7205490666112003`*^9, 3.7205492370552*^9, 3.720550184059*^9}] }, Open ]] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell["A otra cosa", "Section", CellChangeTimes->{{3.7205531091054*^9, 3.720553110369*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"\[Omega]0", " ", "=", " ", RowBox[{"m", " ", "=", " ", "1"}]}], ";"}]], "Input", CellChangeTimes->{{3.720550240334*^9, 3.7205502476982*^9}}], Cell[CellGroupData[{ Cell["\<\ Comparaci\[OAcute]n de las soluciones a orden \[Epsilon] con el resultado de \ integrar las ecuaciones can\[OAcute]nicas num\[EAcute]ricamente y con la \ \[OAcute]rbita no perturbada del oscilador lineal unidimensional.\ \>", "Subsection", CellChangeTimes->{{3.7205531236768*^9, 3.7205531484274*^9}, { 3.720553251034*^9, 3.7205532694636*^9}}], Cell[CellGroupData[{ Cell[BoxData[{ RowBox[{ RowBox[{"x0", " ", "=", " ", "0"}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"v0", " ", "=", " ", "1"}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"\[Epsilon]pr", " ", "=", RowBox[{"Rationalize", "[", RowBox[{"-", "0.03"}], "]"}]}], ";", " ", RowBox[{"(*", " ", RowBox[{ RowBox[{ "\[Epsilon]", " ", "es", " ", "una", " ", "cantidad", " ", "negativa"}], ",", " ", RowBox[{ "para", " ", "conservar", " ", "el", " ", "significado", " ", "f\[IAcute]sico", " ", "del", " ", "hamiltoniano", " ", "dada", " ", "en", " ", "el", " ", "problema"}]}], "*)"}], "\[IndentingNewLine]", RowBox[{"\[Omega]pr", " ", "=", " ", RowBox[{"\[Omega]0", " ", "+", " ", RowBox[{"3", " ", RowBox[{"i0", "[", RowBox[{"x0", ",", " ", "p0", ",", " ", "0"}], "]"}], " ", SuperscriptBox["m", "2"], " ", "\[Epsilon]pr", " ", SuperscriptBox["\[Omega]0", "2"]}]}]}], " ", ";"}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"p0v", " ", "=", " ", RowBox[{"P0", "[", RowBox[{"v0", ",", " ", "\[Epsilon]pr"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"p0", " ", "=", " ", "1"}], ";", " ", RowBox[{"(*", " ", RowBox[{ RowBox[{ RowBox[{ "se", " ", "comparan", " ", "trayectorias", " ", "con", " ", "la", " ", "misma", " ", "condici\[OAcute]n", " ", "inciaial", " ", "en", " ", "el", " ", RowBox[{"impulso", ".", " ", "Sise"}], " ", "elige", " ", "p0"}], " ", "=", " ", "p0v"}], ",", " ", RowBox[{ "se", " ", "comparan", " ", "trayectorias", " ", "con", " ", "la", " ", "misma", " ", "condici\[OAcute]n", " ", "inicial", " ", "en", " ", "la", " ", "velocidad"}]}], "*)"}], "\[IndentingNewLine]", "\[IndentingNewLine]", RowBox[{"Phi0", " ", "=", " ", RowBox[{"\[Phi]0", "[", RowBox[{"x0", ",", " ", "p0", ",", " ", "\[Epsilon]pr"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"I0", " ", "=", " ", RowBox[{"i0", "[", RowBox[{"x0", ",", " ", "p0", ",", " ", "\[Epsilon]pr"}], "]"}]}], ";"}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"Module", "[", RowBox[{ RowBox[{"{", RowBox[{"x", ",", " ", "p", ",", " ", "t"}], "}"}], ",", " ", "\[IndentingNewLine]", RowBox[{"sol", " ", "=", " ", RowBox[{ RowBox[{"NDSolve", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{ RowBox[{ RowBox[{"x", "'"}], "[", "t", "]"}], " ", "\[Equal]", " ", RowBox[{ RowBox[{"p", "[", "t", "]"}], " ", "+", " ", RowBox[{"4", " ", "\[Epsilon]pr", " ", SuperscriptBox[ RowBox[{"p", "[", "t", "]"}], "3"]}]}]}], ",", " ", RowBox[{ RowBox[{ RowBox[{"p", "'"}], "[", "t", "]"}], " ", "\[Equal]", RowBox[{"-", " ", RowBox[{"x", "[", "t", "]"}]}]}], ",", RowBox[{ RowBox[{"x", "[", "0", "]"}], " ", "\[Equal]", " ", "x0"}], ",", " ", RowBox[{ RowBox[{"p", "[", "0", "]"}], " ", "\[Equal]", " ", "p0"}]}], "}"}], ",", " ", RowBox[{"{", RowBox[{"x", ",", " ", "p"}], "}"}], ",", " ", RowBox[{"{", RowBox[{"t", ",", " ", "0", ",", " ", RowBox[{"10", " ", "2", FractionBox["\[Pi]", "\[Omega]pr"]}]}], "}"}]}], "]"}], "[", RowBox[{"[", "1", "]"}], "]"}]}]}], "]"}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"xsol", " ", "=", " ", RowBox[{ RowBox[{"sol", "[", RowBox[{"[", "1", "]"}], "]"}], "[", RowBox[{"[", "2", "]"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"psol", " ", "=", " ", RowBox[{ RowBox[{"sol", "[", RowBox[{"[", "2", "]"}], "]"}], "[", RowBox[{"[", "2", "]"}], "]"}]}], ";"}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", RowBox[{ RowBox[{ RowBox[{"g1", " ", "=", " ", RowBox[{"ParametricPlot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"x\[Epsilon]", "[", RowBox[{ RowBox[{ RowBox[{"\[Omega]0", " ", "t"}], " ", "+", " ", RowBox[{"\[Phi]0", "[", RowBox[{"x0", ",", " ", "p0", ",", " ", "0"}], "]"}]}], ",", " ", RowBox[{"i0", "[", RowBox[{"x0", ",", " ", "p0", ",", " ", "0"}], "]"}], ",", " ", "0"}], "]"}], ",", " ", RowBox[{"p\[Epsilon]", "[", RowBox[{ RowBox[{ RowBox[{"\[Omega]0", " ", "t"}], " ", "+", " ", RowBox[{"\[Phi]0", "[", RowBox[{"x0", ",", " ", "p0", ",", " ", "0"}], "]"}]}], ",", " ", RowBox[{"i0", "[", RowBox[{"x0", ",", " ", "p0", ",", " ", "0"}], "]"}], ",", " ", "0"}], "]"}]}], "}"}], ",", " ", RowBox[{"{", RowBox[{"t", ",", " ", "0", ",", " ", RowBox[{"2", FractionBox[ RowBox[{"2", "\[Pi]"}], "\[Omega]0"]}]}], "}"}], ",", " ", RowBox[{"AspectRatio", "\[Rule]", "Automatic"}], ",", " ", RowBox[{"PlotStyle", "\[Rule]", "Orange"}]}], "]"}]}], ";"}], " ", RowBox[{"(*", " ", RowBox[{"Naranja", ":", " ", RowBox[{ "\[OAcute]rbita", " ", "para", " ", "el", " ", "oscilador", " ", "lineal", " ", "sin", " ", "perturbar"}]}], "*)"}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"g2", " ", "=", " ", RowBox[{"ParametricPlot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"x\[Epsilon]", "[", RowBox[{ RowBox[{ RowBox[{"\[Omega]pr", " ", "t"}], " ", "+", " ", "Phi0"}], ",", " ", "I0", ",", " ", "\[Epsilon]pr"}], "]"}], ",", " ", RowBox[{"p\[Epsilon]", "[", RowBox[{ RowBox[{ RowBox[{"\[Omega]pr", " ", "t"}], " ", "+", " ", "Phi0"}], ",", " ", "I0", ",", " ", "\[Epsilon]pr"}], "]"}]}], "}"}], ",", " ", RowBox[{"{", RowBox[{"t", ",", " ", "0", ",", RowBox[{"2", " ", FractionBox[ RowBox[{"2", "\[Pi]"}], "\[Omega]pr"]}]}], "}"}], ",", " ", RowBox[{"AspectRatio", "\[Rule]", "Automatic"}], ",", " ", RowBox[{"PlotStyle", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"Opacity", "[", "0.9", "]"}], ",", RowBox[{"AbsoluteThickness", "[", "7", "]"}], ",", " ", "Blue"}], "}"}]}]}], "]"}]}], ";", " ", RowBox[{"(*", RowBox[{"Azul", ":", " ", RowBox[{"soluci\[OAcute]n", " ", "a", " ", "orden", " ", "\[Epsilon]"}]}], "*)"}], "\[IndentingNewLine]", "\[IndentingNewLine]", RowBox[{"g3", " ", "=", " ", RowBox[{"ParametricPlot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"xsol", "[", "t", "]"}], ",", " ", RowBox[{"psol", "[", "t", "]"}]}], "}"}], ",", " ", RowBox[{"{", RowBox[{"t", ",", " ", "0", ",", RowBox[{"2", " ", FractionBox[ RowBox[{"2", "\[Pi]"}], "\[Omega]pr"]}]}], "}"}], ",", " ", RowBox[{"AspectRatio", "\[Rule]", "Automatic"}], ",", " ", RowBox[{"PlotStyle", "\[Rule]", RowBox[{"{", RowBox[{"Yellow", ",", RowBox[{"Opacity", "[", "0.8", "]"}], ",", " ", RowBox[{"AbsoluteThickness", "[", "2", "]"}]}], "}"}]}]}], "]"}]}], ";", " ", RowBox[{"(*", RowBox[{"Amarello", ":", " ", RowBox[{ "soluci\[OAcute]n", " ", "num\[EAcute]rica", " ", "de", " ", "las", " ", RowBox[{"ecs", ".", " ", "completas"}]}]}], "*)"}], "\[IndentingNewLine]", "\[IndentingNewLine]", RowBox[{"Show", "[", RowBox[{"g1", ",", " ", "g2", ",", " ", "g3", ",", " ", RowBox[{"PlotRange", "\[Rule]", " ", "All"}], ",", " ", RowBox[{"AspectRatio", "\[Rule]", " ", "Automatic"}], ",", " ", RowBox[{"Background", "\[Rule]", " ", "Black"}], ",", " ", RowBox[{"ImageSize", "\[Rule]", " ", "600"}]}], "]"}]}]}], "Input", CellChangeTimes->{{3.7205502620532*^9, 3.7205504391654*^9}, { 3.7205505249536*^9, 3.7205508167052*^9}, {3.7205508549528*^9, 3.7205508691196003`*^9}, {3.7205509656848*^9, 3.7205509729146*^9}, { 3.720551003333*^9, 3.7205510116478*^9}, {3.7205510522374*^9, 3.7205510846848*^9}, {3.7205511236062*^9, 3.720551131466*^9}, 3.7205515111712*^9, {3.7205515476182003`*^9, 3.7205515730592003`*^9}, 3.720551614304*^9, {3.7205516720242*^9, 3.7205516868199997`*^9}, { 3.7205518643292*^9, 3.7205519253101997`*^9}, 3.7205519815246*^9, { 3.7205520235298*^9, 3.7205521566216*^9}, {3.7205522068101997`*^9, 3.7205522124292*^9}, 3.7205522452218*^9, {3.7205522845914*^9, 3.7205522856054*^9}, {3.7205523672258*^9, 3.7205524098882*^9}, { 3.720553158047*^9, 3.7205536612414*^9}, {3.7205536974912*^9, 3.7205538762349997`*^9}}], Cell[BoxData[ GraphicsBox[{{{}, {}, {RGBColor[1, 0.5, 0], AbsoluteThickness[1.6], Opacity[1.], FaceForm[ Opacity[0.3]], LineBox[CompressedData[" 1:eJxUmnc8Vf8fx82IhlUqGkoaIhpa6k1DySgZCUUpJEWiKA1UsiohMzNkZO/1 tvfee8/r3ntklO13vn/+/OPxehzOfY/P+/16nsc9QvdMbzxgYmBgoLIwMPz3 +/9/JsG2V+7xl2+msPNngsnkKgEfuM9ufPftLSxlNCfmk/r1mvHmqt8OwJ7r 0/CM1G8zz3ud//YFnr6Vr1pDaoXahzWKWe4wtPNa0MsVAkorJwUe/PaCnbxH r9UuE9D9b0LHINAPjHf4t7OQOtZoX6aiWyAs3bwmI7BEwKn4i+JO+cEgJSLx nmeRgExW51SdzFAoOScTTpkn4E2ANYdgUhjEhAVGhM4RsGFz6rmS6AjYE+Pi ePYfAdu9Fwxv/YwEE0JfKX2WgOZcfr9G/2h4eTNohneGgHL0Mbd0jQO1kMrp x5ME/L73NaiqIB6I7MvXTOgErJEdkqrJTYCnRhc8FagEfDJ28PNPTYIXZbvG Y0YJyO80eGuYmAxlJbaL4sME8DVYnd0RmwKnhvUYvw0Q8K9+r4VCWBpkBQ79 WegiwGeMxpQXlA4uKgv9DB0EKL666C3onwHZ8mZ1oy0E7NL/w+z0LQuWrkcn a9YR8O2NwG6BNwgXnE7/LcknwJNa7K4lnQeMXdrHmnMISBE1LfPKyIPdBfIu RRkEBPIt9vYl5QPHx9c+cglk/vbqz4MiCoEm/SKwLYAAjUyn1LvCRWDfpCM0 6UNAjOlR7Y3BRZB2mqFvzIOAPrCiivkWQ0rBkX1vnAhoMb9DM3YuBbfahMcn LQhIOiK90Y6tDF4L73yg9YSAMq3mKlv7MoigpRXeNiKgK/TVyVOvyiHpeXs1 uw4BvOPfQl8+rAQ9ztt5k7IEpF5RiO6RqQXmU/mN69nJep2+HOBWXAsjNmEe Qat0WGdVIMC1tw7S1C/0bPxHh+H8vasGkXWgf4jt6PthOgQ6O/4SS6iHix4c q0V5dJAqXArsym4EwZ0nPsWb0SGpzWGSWG4EF1nGYi4DOqT2frlLPdcE8ael Titr0+HP8fJXgXlNUGAjt6p3iQ5mrUGWIwXNoDH1XGOUnw4PthsypBW0Qvt9 gxq7VBo4+w9knmJqA9GZiN/ZkTQ4zaS3HCTbBqxfqvyb/Gmgb6sxJ5DXBm4+ f4cD7GgwbjfZk5XVDvYdFRUBijRI4HgUfP93JyRo+nnc6qCC7R9avrFVLygu xYRLdE9AidZzL+b4XnAd7PF8VD0B8inS9TajveA1Y1zulDMB/X/3VrCJ9sHD Erazz39MgMmbFwfavPvI/nhuYdaZANoPf6ubT/vBGArXMTdRIKs6QWKbSz+c b9lDcSyggKbGkGFleD94/dq0+W88BfIeHBmf6+yHUep44BtXCli+lbvx+tIA JDVXmNy4RIFUjsVavk2DUPRBsZovfhzKhBf2JokPAp/vXdZ5/3HYdNLx1rkr g1C9tzu+0HEcLi69md72ahAuyxbHrtMfh91Vm8UpvYMwHML7wJRvHIzVUtoq woYg7EIts6P5GEzMM6yMC43Aoy89Gv6Co3BM9G/Mu5Mj8GPvabPhNaNQf3n9 BqZrI8B4ocVyy58RKK4z+Fr0agRi5N75SBePAE9n7Dm5phEY0WN1e2syApu8 j1YfsB0F29Gzc0xpw+Dp/yz27vdRyNPWq50JHIZ8Fv0pu+hRCKobptR/Ggb7 g7dVbJtH4fzg6GVlrWFg9+0/9Wj/GNz/ksV5Y2kIOBZ+PxkoHwOW68xOPtJD IFjPdCiiewwCXfpOXBUeAvbrsjxqf8Yg/s7u76OcQ3ArZPsGgy3jcCbPOH+s YxCCGKvSjR6MQ/mdIwZsVoPA5DBd37YwDjixkF0ROwAd/ptixngmIGTNmnbe jf0wb9fV/094ApzUL7tfmeoDlVVuqzGpCRhWPnfYuLkPbAL/WjzWmoAK4tdn C78+kL37zo4laAJOPvF9FynSBxOaMnT1vVQYl+Y5e+9ZD5xtDFt4epwKZvlP qj6e6AHNMd5jTy5RYfFY10XHxW7YtplzZM0DKtRD6ep++24wVFLRSAuhgsDr oxs6v3bBnj25d1i30GCXn7DjpfAOeBHZtVlQhAbPHtxJNjLqABNXWyr3MRrs /JjH9+RgBxwQep/ge40GcSG1Lrti28Ev1GdqxwcajDStZz+U3Aa7Om8oDY/T 4P2ROGaBrBZ4PBlXPTJLA43cws92r1pAYvM+2xJGOkgfS8iuO9MCXyJmFHZt pUNpePCu3dnNEGh0j1lajg5OnIUTQVlNsKiozLHWlw6PkhpWlFIbIKu2Ulom lA52ASqePtYNUFT1SO1WDB20NlqyNEo3gKTlk42SuXSYkvTT5iqsBwlf63zL Pjosv6+2zqqpAy+JEweyxugweUj7ro1bHTwNqpccmKQDLU6MUUytDnbMxLE2 MxAwFaeekp1YCyIPhHoVdxJgJXJ7J1dJNfziZLEIECGgIflYhO/VapDMmzap FyPgh0CLAXttFSRnVj3pPEP6FO38sy+tlbB/S870Gw0Cjny6ufHWaDn4T7uO d5B7MuPt5VCOR+WwtXXXhi36BAipqp4NpZcBp+PeyuOmBOiurzZxni2Fqxkv zVY+kHudu237JaYSkN6teULfmfRNbgc56Q/FUPzw3OqvrwTIvy2R38FeDKH1 Tq9bfcn7sdZW/lxfBFwv3KPwNwFuYleOl/MXgNBRVUI0kfTpi/sihX3zQSB7 dYN1Krnnuc/WPxHMh+8T6jUpuQTUXpY6VL8rD0yuHehJryZAjpF9f5pKNuT1 RTuJ1hNwNP+jroV6FtgEh02/aSJ9Jutc1uZbmXCFkZNe2vFf/XRwg146GAXJ W+d0E9BjxaRpoJ8G+y3Dkt37CLgiqTsbbpAKxYK/JQZIH83amb1z1CQZlnh2 m2iNEfCqMv7HmGkShDrJKSVRCOA0vsDUap4IZpuq6qmkL3ut3SmXZJkAApvt /60hCLD7xHDvjVU8fCzQymb8Q4C57KMf5n9joWDv3R3dU6SvjpzgqFiMATnz qsTjf8n77bd+sHdNJAiGLN2pJ7mhV31WK7MvHKKKKkWukJxxUtBn/FjWT6i6 6cjuu0CAre9nZy/PEHj6JI6plOSSUy4CWUOmQaCZOMBbS3KLSYf08FkPfwh+ MHU6keQa09P8t9yueMOB+23PzUgO+sHWXFK25A5Fwhkla0lO4qi/ernh7hcQ zRw88IbUNy/8LKeXf4SGxvrAalKzW46u9OvbgH3uvv1zpF72VFV2NjSA4vvJ Bcuk3iKmZPX5z03kufbUtIfU2qmDCx8OvcChUDtxX1KrRSdUyYm/R5d9Jxgk SZ1mOaJytMQFq8+wD4eQ8YidFVZZjf2Gd3p9ugkyXum9fg9rF77jnt+ZFH5S e2zftfxezg9lOvXX/8dl4xM+mwW+BeLCqQy5ebIenk2OeiX0YHxyZK13Ilmv VOl+e2O+n7haVMV0meSypyGsr/6dCsc4h4hPqWS9608UVRrr/kLpn4aijCSX eZWxLeW/j0KmFlaayDQB1753ui1ExmCGYVjtPrJ/eUef8PLUxuKKhEczM9nf NRJOzMwv4zHG/SpjFtl/0T9h8w9dEnDR6pG6Enk+HhzRjcsOSERb5aKmTJLT wvftHpuPT0JHpv1395Fcdvjh9KR4cwo2Hg2xEOklILFW+4rwaCqaTR/JYyA5 rXzuveTqXBoalcpvuNxMAPcN3nI9wUw0xm9bksjzfiOwZHVILAu3sVgZL5Dz cLugvU0eslH7renfbSVk/HPwPv5uLu718zo1Q3JbbSZTX5w5om+hQ8svktsY iu2timXzcJ9RjuTPZAI60rJDDW/kY4roL6ahIAIWyrZJpJkXIrMPzy9vPwIG Nb699VgoxLn9jo37v5PcFBWRp2VXhEcDups7SU4TdVwTFuhWjD/NDp53NSfg S8CRjvnYUpQKbq7bYULAxRfvfNZLlSFDt4agywMCtn3eaMSaU4Yx7TrsCzfJ +VjmKAqoKMcSKWFeYXJffWj98NxwqBJzt+Syph8lICJoLm2LURXuufv4woFD BDQ+s9WLmqjCVubG/FBBkmO/e/4wmarGWn1vnF+kQ2smY63OSi3eKY1ZsZqm A6tnasQ7mTocmVWsa6bQgSVwW1OebR3e3lOssr+dDoUGErVrWepR/OvqoGQy HSLOm+qnsjXgpsy6qoAoOlS+fLjV7EoDiqdI+YwH0eHudmnrTY4NKPRgC/tW VzpQA/s27+ZoxCsbuy379OnAJ/d86jRnE/qcMK4Q4KTD++Od2YfWtmDZn25l k1UalAX0fXl7pQWNolQt/aZpwPP7l0+GQwsmuC91eXaS/nRO8eQAayum/db7 ukRy36N/fv+WGdpwk+n28h8yNCiX6HLePdWOnl/fjPYcocHljiKessMdyDlo 5LwqTAPBynGr6487cI9EanAvOw1sz56vZx/rwN0fduQL1lKBe2/7Wa6uThR9 0c3mo04F81e3Gs/lduN5leeT43JU8NzZqDU5243ax5lf7TxJBdU5/sH3Yj24 KqIRd3IbFVbkZnZo+PfgqJjkob0kRxr/KjNyt+pFLb6TDtO3J2Dl+MsHYZ59 uMVE6Y2n0gSEXohKcozvw+v/wti3n50Aqe78jtuVfZhvsby5W4DkC88OhWaG fozl6O/Z3UaBGykuI8vG/XhwStK9UYHkQtNcn53SAygulPOk5RQF6s2DHs+q DyAjPhrDfRTgK3axyzAdwEaOG0tyzBToY2/hXBc6gPSX5t/3ZYzDHtmjI63s g3gzcPb++V3jYMatfHG2bhCZ0w0b73aNQmV8d3LAjWHUTtAU9iwehZ9FV5rW mAzj3w2thr9jR8E7qembxodhrPvWI+76bhRUFo68jEkbxtYV64B1e0ahYFa/ QVxgBF2TJp/u1h+B0Y5AdsvuEUw8RTxIuDoC760ftMrPjuBt0chFkSMjENhf 8IFl/Sj6tArZlDCMQF7OnU2i0qMYknVwpN1/GBg6dXhP+4xivZaa/qO6Ibi6 uvXTFeUxbAbVsqepQxCfz0x5cn8MAw34/fT8hyBpKNnR+uUYbkpJZJgzHILO byd2nAkfw5lr2tzcK4PAPXVm2GRpDH+56ZeuERmE2qWkIMvQcdzw7vXv9gf9 YNaw95hVJwU5m8aauRX6YbY0+EkulYIPu11bT0r0g3td/8z4MgXLXbfUqy70 wafkqKDJnRNo0DXslOfaBzlvtgVm3ptABanDL7fq94Ihm0L3kcEJrHylLvlG tBd8azfylkxNIE4arRRO98C9+dSvZ5moaFPrlDZt3wPTfY9E2ndRsegApo+H dEOjVCpfvg4VFR6sEnqdnZDWe2T35VoqPh18c/hPcCc89WEY4O+m4hOGdWwG Rp1wKP4qYxWFipZeSfdWZjogb4Znfw8rDU221HNNrusA9fixoF+naXjCxLxg 7ck2mLit9acigIaGtBqblaVWSKZ8/VQZRUOl3x9MOvNbQWAMkmJTaajPndKi rNAK778uugvW0FDPjFtu9+0W8Hm4Cp6LNLR7MH8rzqYJQjofOU9ep2NzvonX M9kmWJ9tJT+gRcfBjQofhdc0Qftvny1p9+kY8eKlltKXRuCOSitaa0XHu/v+ bMwPagCt97VqN37Q8ZPlR84/9xvg9o99ftrhdMyqTXuz8UAD3DAKjbocR8dQ Y6X4LeTzJ3vQduayPDqGuD2yu5dXBxuUuxKNBug4L/jNZt37Orj8V1nLgULH 8ItJ6eGX64BhmuL4aYqO+7dZZt76UQsFklL6R5gI3PCmQGldejUUVd8/vGcX gSqyH6rOjZVDrZjgpmcaBB53l5eqf1wOv3QujafqEPjBf7e+wnQZjJrkt3Xd IzDzvWL73HIp+Lfcnqp5QuDsq0mmSzwlkK/J/0zhA4H33EWu7/YqBufKVftA JwIPZG5dOyFQDNQ5q/fNXwi8PcftIbO3CBi36ciM+hDYsXxngv1EAYhpDewM jiGwcJb1mXJWPtzl/LCfJYHAUz/mee0hH2gHdi1dSSEwsqvBOutyHuymbpp5 kUPgwoUK9XdeCKOpoVz38gmk7jrl9ygwF6Iufh0TKyZQwIhiOxGbDXMnD2Qb VxEYV/5oyTY1CyLcifjOWgLXRCatW8nJBPGgK6rijQTumjwcElWVDjddhD2s 2glMzDRh7G5MA83vvw6ZdRE4zfI2aq4jFWJi8g3kewl0OHTgCzGWDBsjp5OD hgjsentTMqAjCXoFuH1VRwnc9PyGi1RVIuz7F5w4ME7gVOuH2oycBJILSxeV qGR9tloePBAXD+r55eaedAIN2S18OGXjQH6TwKaMSQIrK9ZUBe/5DanBan3p UwQ+/fzW+snYL/j9Km5M8S+Bel0dSZEV4bBjrEqo/x+BTdrC2pUxP0GltuKV yjwZX7F+bfPnEPDu5pz9sUDWoyPTrNIsCMwZBVxKFglc97T43O0wfzj2OBoq lwjcanDjBfNDb3ju7b0hZpnA+1e6FD4f8gA92ZF/RisEXuS1X2Dp+wJlj/MW GFcJfMcy411u4ABbTF5tfkHqG6ZylNGO1yDQ5H61jNTdnfyXpOoewhuH2O+z pJ651G3HIHodlRK9F1ZIvb5/oOP7sgXyVV5+PvTf3yf/Zhads0MG9/a14aQ+ xlx33fKpM8Zv8ki5QOrjwzcfXp91Q9qvYescMh5v+1DmBsnveJB6/ybvf/rF ndTTT3yxt7RO+RIZP59yet6HqACMNeG6q0rmN0JjkLz5LBiNbhz9cpbM3/NK O/WmWyjWSj3tYCbrs3csNel8XBheFjx4MXyOQDOh93s3VUegzJWRamGyvgnf 5QaqKJFoL6th/XaWwPl+ISdD9hhUqLlxJXWaQDnQyhnYG4vHprqky/8QeNJP dEOAUDwuTGy/lU6Q8e1uDD0pkYDrjxoG2tMIZCgigz6XiDMWR3hEJwhce2Rn 4RGlJHT5JpQcO0agu5mlTMvDFJxuyPp6dZBAzWYWFxarVAz0f1Z/r4/A7W3n grd+TMOJT0ZKN7sJ5Ch2N5kOzkB6bBdLcwt5nv1+G11sy8E3N60695SR8++a P+AwnItql53u7CgicDn4c8KvKcQJHTfpWSTQYndRxbk1+Sgcryp4Mo3AHPnc 7AM7C7HZ9MQ/np8Enmk1VpIIK8RHfUbdkwEEiiy0NuwSLcIezstXosl5Fqf3 3cuRKkbhxo7ClM8E0lc6xJoUS/GBbSXj7hcEpoX4VB8uL8VeN+e060/Jfqa9 lbC4VIZnZN+m6D0i0NJPWivlbDka66kGC+uS51FneZFTrBJdR6wHpC+R89Xf ax70qxLfz9baPT9HoEv3jaGtwlVoXsP2w+0EgVJ3bZsytlXjvLOolskB8nz6 CmLQmlrsXzqUlcxJYO7p8Z5rtrWYKxlFW2Am0Cf5yom+xVqsTRVt3L1Ex445 i1sqVnUY5crQwk+lo+fd6wPXTepRsqfc26uCjvJXm7dyqTRi08CZe7O2dHx/ Z+mdumsjeiVy/9Ai97vNpYM1DuWN6K2ixhvyhI7Ko2aHE2WbML3oVFsr6Q9b dyWH8ks2o6fpt6ZeSTqOCVhcnOJsxQtT0W+MO2joJ9oaRpFrxZXvknvmSP/Z JhUuX2XbilU7An8ZFdJQIO+D+dV/rfhC7ZX9VDQNh2fFWA71t+GygGl21Csa ikDP1RvxHRhs756QtomGmtz6gZ70DnwxvIXQYqMhz6ugtZmHOjH2kXhH1xwV Rad4mcJ+deJFmaxFm04q6jib5C4GdGGXkPNliUAqhlVLZz350IOS9gk3zUm/ zlpHUwjJ70GxjW9d2bmoqOdh8zlxuQc1JAtd3qxO4J96701Glr2oSS06ytEz gWJJ8c1fJPtQSFlVJsRnAofv7cktEOjHSMmA+BGOCbyrbrQt8WQ/Oh7cnWw3 R8G/BX8SXNX7cW/TfP7qMAWjtxhtWPulH9vnSlR+5FHwuiLL4DrGAXQ/4vDD yIKCwQ6M1of6B3CVjUNKtWUclaNZLlO/DmHflZmlre/HUO3wgHBU1BB+H3FA 4ydjKH8jdq9K0RAe7G15GaQ5hkedI3Zo/RvC1XBJ6axDY+jmWtqupjOM4oXC HvGNo/iifPu+ZqERbHscqhAvOIosB9p3bDk9glydO/fpsI5imVXg2/M3RpCe VOpEp43gznNW3Ep2I9ire+9Gae4IpjA6fZXqH8GS3tuooDuCrHP9+y/6jiLr taJraX7DuNSV++BPPMmFBaVcbXbDeDBkxuR96Sh+YXRj7X84jCYfQ55rz4zi y0L2+egTw6jo+aegQnEMs54p8R5oGMLnG0NWvefGcO0V29I2piEcsfogff0M Bd/+NetpUx3A9d5Cf88qUVCdQmnhOz2Ahu/H9Xh0KSj1KOAS7BrAzXqWrKZ2 FKR9lRzXpfajrJxw/GwpBXX1RFkb7fuxfJaP46DyBB5TkI/4HteHKXVfGF/d IfsapFtT7NGHCo8VQxOeTODxy7yMw9Z9+FHwbETt5wn8vL55cvpCH05LP2aq rp7Ac5Hyob9je1HlasIwylGxep0115e/3XgvcN/D++pUnM2IvsGG3ZgdfjWS pk/Fb/Bt9p5DN36xzd0X+46K5Zh7tJi/G0FWyn84nYqSuXrPzpzowmMRQgm7 hWko37zuwY6nHRhNa4haJ0nDEsKPdeREBy5pN7t2nKXhlGrfI4+VdjwUHNQj dJOG7xLPGoQ7t2MOL8ut259oeO7vs11hP9vQxGW91eth8n5nJY3ONbTgyBk1 3a9/aKj2L+WQx7cWrL5Ze9d2mYa2nLfu191oIX3Cym6Zj47/QiuVlhua8V+P e77OeTpGrlWclWhowsaap1y6SnRk1+g7W+DWhAfZfXhAk46yzznPSas0odPu 36tej0kO1L7vOFHbiJczm8RivtPxks2za1DVgAzXWkp8g+h4ykjj5g7nBlzr QUk2iKLjk329d8fkG7DzLv/97zl0tNI9HX6utB7f3knsVyW58MatLyxLeXXI 84LR8txekgN8Ay//vVuNtoVldsuHCDwtcEhWq7sKndZkyfkcI/DEHvfPPzSr 8NO35hqDCwRKRPC8KVKuRLccrzlNcg87Crnt+3mqHFl01GqXHpB7/E+oFG9y GTKXpgm8NiEwglnvmoF4GSb2iM7xWBMYziaxmLm7FNe+i1j89pXAoWL1OnGO Ymz6qJu59TuBt7z+Yo19ER70vZJu40fglr655zeXC1Gy2PxWaxiBG4fX+e+d LMDar4uTNVEELto1njZ5WID8PRfjQ+JIX2S6zxQwkI8dHw2+9qQTWBOo9qS4 KQ+VRSvD5UguzNAQuZitlIenCPY6J5ILS79eVpB1RVz/bfRyRDmBlJ29PUZm Obh57eo1iTYCf1++myl5PAPdaA2hsp0kR5Zlnzh4Mh2tnwS4Hu0hP8+dqZHj TBo2WP/gzyB92NivQf6TTApKb9NNVBwh8PO+1i37LiSjwadjbXmkb0vFplMT LiXhnV0uWVdJn68qGHH6cjUB9T55WOiRHCApoyA/pBiPK+dy4jRITkBVy3GV gFjkYeJ/JEZyxAhH84ackBi8EVj/c2iG5K4X5/5xRkShwN8z2jYk93Wc1/CS if6FW+YLXWZILvFg6hzUiQvH+ri/J5RI7nt5JbT+XtJP3HTynfZHkmtqUvzU 1dJCULlU9G8gyT3864vvH80KwqTowTW+JBcJfro/xvzmB95QSnCxILmJR3T9 lP0HH1xzOOfjYRJRPomM1lFcPFGFUJ6pIPVN0yem0h5uuEG+ukmO5LJzPYZm 81LOyMKXuy+U1GrXkkR1L9mj4aUSai+p4zXPVOlHPEfRycg9y6Q2Nsr/VblR G89fUqxa+I/zquwvr4V7kOIeN9JG6lwd/yPTTNYQfWXW3IvUfU+SnYWfvYfT xO2nUqTOLP2pmnXfBY5JyA+kkPGY8Q+sFxD9Bvn1x0s2kVre76FDyZ7vMJya v12DzEd/sENUR9AXhnsix5+T+Z58lMPVxhcATvcrDlqR9di7tn2v35pgUHy9 Y+AWWa9rNmesM5hCQc0qj0vwP47+bbm+eOUnGOeMp+WS9S5Ic6RlLYRDUeVU myzZjw+7Pgv7//0FS7+DP4+TnC5ZdbSIix4DxWPuIhvI/oq4WF8IHo+FO2kr 53jJ/vPLvAl1NI+HV56H5nMpJPfzBbFUPE6EBodjgQ/I8+NMqTC99igJDGrP 1VCHCYyB6OR8o2RQtztV709y36FblEEj/VTYuNYwqpjkvsqoqA4/vTQI2MzN X9tBnle74cK02+nAS4tMtW8irx+xdQi/mQkyadWEeD2Bvyzmn7xQy4Iklray zGqSkxYF9cVUsiHf+46RRQmZ35VEl4tXc8H3PptUSAHZTz6uulA5hH1pREJ8 LoGHXee3mwvlgUataJFpKoFHtY+p223Ph+KUypLnJCf29tlqNfEVwvCpuw/P B5JcXzf3ZMG/EB7bsJuOk5yo171avZZ8DpwpfpldTnLivd2ps/3HiiF/JJW/ 6TnJ1Qa+aQaqpbBpwNrxlRk5X+KpE8UdpfDX6oXHykMCgzJP2K69VwZzjLc8 vMjnVM9nW++cMSsHT0/DLZtlSK4uuVdy0rkSLkg5HfY7SaC9cPdEJHcVpJr7 7FqSIFD3npvbglcVwKfpJBUhAr2+IXHiZzX0Tv0JUmQg8Lv8gxXurFoo5vXc 55RGR0ZlGk/PZD3w3nTXrv9NR2ePDXfpRxpAP/Ewx2woHTcpT/qPWzRAQ9xm 1oYvdDx60DomcK4BHq/Rzxp8QMcjHRnNjKuN0PZy/4oZJx25H8atarO1QH2u w5cPqzSsUVn+9u9yC3w5pfrgxTQNTV/waFl/agGBZdHN0yQXbtk5qSm+thUi Cz23K/6iYUVf6qz62jaoPxBd6SZNQ+1poVktlg7YUPFDr1Cchsrp7Uo85zvA ML1Gv2kXyX1D+poxbztgwvnCtAcL+XmZG80cFjqAqlg95VZB+u37yUMN9E7Q MNta7XiditFRXgZv6ruhTrGvJ0OGiicqEqgy63tgffdnowoJKipGZo71X+mB w8XjB11JDryi7nIyF3sgSPewgV/NBD6oOjDfFt0LImI9y5SLE3jhI1ESm9sH CkWOEqJHJ1BuW9VVi84+2Mwzw6YkNIHZOforInN9wOhDmTm+TEHjvdkWqpL9 8O0s20pAEgWzHd7tLg7ph3M4QvRuI69r8tII2wG44s4lktI4hhZYe8xZYghS X+07W4hjKJ01fX7+yhBcKJW5mhE9htvyt/1QvTsEu4dMPG7bjyGnxGhLldsQ TK3e2egoOYavzozV1PwZgul9QbteO47iqdDr75d+D0OW58Q4r8Uo5to0GggX D4NWyP0J9zsk9z3aLHyiaxjGF19Trh0dRc+Nis2CHCMwEGS2L7NzBD/kcvwc uT8CGoei1Iz3j+CtHsUivc2j8PWGuW8A9wjGHBJfFT00CknrEs1yFoaxYZgv vU92FI48d9uXVTWMKepJ19Y8HoUisb1HMkyH8b3z1WooGIVsbRHvxoQhfCQc zaxlNAZWAlfChPcNolQWZVNQyDhcq26XT+EcxM8/W8PZ08Zhz4/HhyUmB/C0 7L1O1cpxeCB8/8xw+gAWbihscJseh2MGhlXX5Afwl+jxl5HnKRDIGV133qAf bTIj+Y91UiA3b8Hio3w/DtGPXM+mUWDX2Ws6qYf60X7au3wvwwTE2iS/6Jwi OdCXTdRfeAIuX9r47tybPpydt7nPZzIBtSIdIhx7evHA17k1QrMTkPb2Kdup 0R60Sjmfl8RKhRcyIoEXo3uQ7VveS5HNVBBbN8A6faSH3Ae3f0VLUWGv8L4T yTLd+MzjSv+R51T4fmGlk0WjE2mJYYJ7CSp0dFz33bmlE91zT5rELVNB4Pm2 hwIdHfiZszN4yzoa6MuZq6bd7sBbR0NeO+ynQWK54e5P+u0oPNJ2tFmXBhe1 7FSqHraiS8mm5d1lNGjw+7lDTbwVO5LMOQsaabDD5Wh70VQLuY8KH17opcHc xhrme69a0FPjyxh1lgZ3ZnXj3Zyb0crtRUq7EB0uvU/IWIhoxJCIx3u4LejQ NWN6U+xRI9adHOCte00HzWyZYEXxRvy7kz3azIEO3wKcRW8kNyBBlYzQ8KXD pizGvLdYjzp79jQk59LBgJLjeyysFu++vX84kZGAnM3Bz40O1OKsidU1h7UE 7I8wVn79uwarMsWcz3ITsO/TwV6FlGpkPTcqpbSLgGm9MxxOhZXoaXPu65w0 Af3yavKNcpW4e1E8p/kCAU+Zz99jrKjAnNPple5XCXiu9ItnQ105Fq7rMk+8 ScDkliiOfx2lyFG157i1GambE5Mtbpeit012hs5zArL5ZbZ39pbgsGkobZcN ASOJnDvuDxXj6+0fFRUcCAivOPXVglqIfJbeSvv8CShB995LTwrRhKswcWMw AW4nJ1qZSc57xpft3xZGgNWf65mXp/ORcVqUyhlH3r9EjWfhD2LW+nuL/5CA DHFVxdfzuWhV0xZQV0hAxETr0ABDLi5Hyvc6lZL5Hmoe09yYja63p/f/rCHA u0VW4tHmLNQuvCvK3ECAlKbAZ/3tmTj74HjOhWYCXHj55DhE0/Fvaprdw04C LuXRbDIl0zBl5H28cg8BIvoR9monU9FZe+bupn4C1u/fmSV/KRmHa09cujxC gLiTbHm4QhJqBPCaJ44RkOnDce+PSiJaqwVvWaUQkJ4lRNy4E488p/dUSBME nA4usGsti8UtDez1Yn8IyP2hkjzRFIMdIvbyDP99D0mIqgz1RWHEUqNk8gwB u19FnCik/kJ7Na1P8n8JOIVH5JzmwjHr8TeFvH8EpLKrap9hCUP10k0vt8wT sDkqRL1tYygaCfnx3Fgg+y1Ry6svEIyqb/7yPl4k4PHpw+OZSgE4vGfr64dL ZH3FPH9/u++L6v7cSpeXyesXHY+ovPqOR9M47desEHA1ruv4gts3POR0fUcE qfP1KZTdKq6Y8VRux4H/vvcVdL9z/M0HzOB+audC6uq8Fx8MNF5hn/rTq/Wk Pl/EpPxVzxA3m7M+/0fq1Z93DnPGXYPUAXbWVVLb7p7Zz+b/DBJMLP6Nkvpw Wi/f+mBb+Lz9jlIiqW1KmNNZLRzhgcL8mjukxrBxhmehX8HX47vwBBlPuvKB M40uHhDUGxp+i9S/LjRU7XzuDQ5aMa6RZD6qGexzarr+YP1Ss6ODzNcuxP7t CeEgEFh87Eoj62F8ipsnZUsIVHfXRvST9eoVG1ETWv8T6o3eHEwj66kmoPjw JWM4aIl4bX4yR0DQ3wCz3NkIsBxUe7yGrP9Aq7LLxHgk9MRulHg3S4CO1ezH +frfIEZ9sso/RcDcYdnIluI4aE9T3yg1ScDbdIWkiq54UDyf63acToCM8a7t mnWJ4NXQMds2TsBEkdFVlookGGLK6rQZJcA5z9LxR2EytJ+3lGYaJoBpd5et e2oqWLzmtkroJfsnMXybHpcG6kfXanZ2EWC/wOt2JDId3hqvyRlpJ0Dx0sEL z/wygTnktVBIIwH8LNdLs97kglR2clR0MQF9XZUdOi4IeUrd2p/zCdBSLzlG U8yDxWBDRaUcAnhEk7cf1cqHY7JTK7rJBHDZNxfXPisE15reU+1BBPx4lxDJ uFAIWvNLFgF+BHjGzG/c/q4IulYkt8l8J0D+3DzbBpdiWOw7mbXFmYBEjeT9 ZSGl8MWmlmPXMwKWTl4MOb6/DL4p/7pS/t/3xnfvjDv8LgM67cbeawbk/J2c cGhLK4dyX7O2SU0CGt+9CN1aWQlOZcWLLuQ+01LyiPGeqAXLl2lGh5fpMPBn 2fLjiToYkPyiHj5DB0pUuqq4dR3sY35ptDBBh7vfo4XklupA5HrOvtMddHgR yPbPlbEBmD/Ni2xNoQOHpKfiOfYmCDkj/e7OfTqYvHzfknClCWjcZ9JibtHB NuuK0wbHJvh3s7SgTZkOgRpuSnZrmyGg9OmnipN0EMqO1VFY2wKt9s2HNnPS oeS6TKEwSxuYrNFRuhVJgxoTO8uWc21wf/ThsMEPGlwKkr9nZt0G+mGKFjfd aLDZOIZVh94GbObzYf1WNCgUaJdY19oOyq+Yov3kaBCllKgSENoJHIZMBxK6 qKAYFjKV3tUJp/tF/k3XUCFh+dr59E1dsFTp+HFbPhX2/bDYcN+hC/K4Xuzk DaNCV2f3BeOH3bCen5ad9IgKGlXPaxj290LZbdEtOD0Bri9bHijq9oJDTab7 xaEJYDb5c9r6ey8Y6AenxjZNwIARx+Bppj5I3hN7WDJlAnw7np57adoHOUzH gictJqBcormLKtcPPHw3TQwJCrTUtslQxgZg5v41lci6cVCzmHNyZxmEoQds 2teyx2HbHVa6yK5B+B7Gl98aMQ587v/ect4cBLVHvgxf34xD4jo5vbLCQbC0 iRsPOjgOyr6rtbPeQ8DQviHl1usxeFdvvCKZNARzOfodEoZjsF68UV2jegje BFGGJq6PgQOLPNtNxmFotbnEtUF4DL5/8ZE4bjQMv9ae+s5aPgpRsYmtVyVH QKff50Xb+lHg+XQ7dVF+BD5+sDizMDsCip8cxr/dG4HIv+mujD0jUKwg3vXM fQQ+J3Iq5v8egZFaof6l6RGoPqEgza44As8+BQFv/Cgs3XGLr7Ifhjkuw1vf ecfh351W1qW+QRBL4l73cj/JZfXZNh9KBkF1JKZe9uw4eFQIMcxHk3n3fTn1 2mAcvrzXDwl4PgjRWq3LQSTHzXp3uY9yDEJtk0LNJzUKzNzZ9tTp8ADw1mQK hxpSQELPNLmAdwDur2kSDXpJgZCGzpGRf/1gadXyTzaIAmfmCjymsR8u312S 2U2hQD87j43QtX5Yq7qj8YLVBAiZZ8xTHvaBKGXY963jBMgvNnRNKvZBo7xX vb/vBKwf7o0YOtwHXc+64FX2BATfKKAdmugF3v0P+UpWJuD8TUN2JYZeyNvA nmj/mgqbWTWmDgh3g0FFloOIPg0ir21e3qfWDny17YpOpjTYfrVk5Na2dvjD yRJW/4oGR1pCvj3ra4PrhQd7OTxoEOsVyKVr0gZJjz4eFymkwY+0vjJB+1ZY m/bU768AHU6fs3G9H9MMnsPD5z6L0EFfPYdB7GkzbN8eVcQuSYevM+LYd7wZ BmhFyuGX6KAwVsTEiU0wUN1zxe4xHRqWKVSzukaQsr/9OSWNDv0676uSiXrY 4K3f8jyPDjnIP6OYVA83xLeabCunw22ii7npeT08rr2uy07ujfKy0OK45Tro HDSxe7NAh6e+J0/95KiDdOtgNRUmAj4xznJb+NUC4Uk7toaD5KKuWFFboVro DRRm2ryVgNlDkz9lxWqA62ANa/VxAp6tbPUyulAFLUPJb+LIvRbsQyNiyirB KFu9+hnJaVrL+yxalCrh+AusD75OgAOPUXvHzQoQ435Y+u0hAbHU2M2pxmWQ MeJ01t6UgJ35PuUSRClo+atoqluSPi7xXdfjWSmIC5o+CHhHgFK5Ks8WmxJo 8M67XOhJgHT+u/AdLkVw4YUqHiT3+Nl13P6mrEXgn0VReULueZphcVPkm0K4 5vsg3jGK9KHXxLMuswIoL60xu0tymupC9bqW8Xww+3z5+CbSJw4lByll3cuH qw+PpXCRPuKg9O+QgloebFmxMNAkfcbO+dQyzQeh7+QdNhvSh9QCJrOFnHNB lfEj681qkqPMpnV3P84Gi9S2WxvqCRh/Whb153YW+BsvOQc3kfW5vbU/WDkT wu6FWGuT3HZKsbYv8nA60DfbitmR3PZ+spWHZVca5CeNx70nuW07azDjRa5U sPrSzLOd9NU1j9ePWU8mgRPPCjWR9N1DS+flzfsSIX794idhKgHRqVqn1esS YFeQ7aIv6dvOAs0yqBsH1QXzVYGkr3vfNF3lgd/A/3KPxjuS0zyfCTpc2hEN RWu7PaRJTtM543n+1vIvcKeKOTSRnJBjkeJ/vSscrFvkRP97vy9olzWDeNZP iE21fetFcsem7Pm2aZ8QcM24a1dAcslJ20duP62C4NJV9yPlJLdMXjt+8EOs P+jwUT9Hk1zjqFQfEPTIGxhYH31/SHLPpZFvN4P2e8B+xZNXmFf/40LmmzyV X+Dr7bBQq//e9xN+PYgXHcDmz6Ff5aTmH19lDbd5DVdZn6n//Y/TFNW/qvca wWDnxegVUmsJHlZ/aXkD/yx7Rw6QOsR3a8q9KEuknPpyPYTUwnbLghHa9kgJ NQs6S+oEnvuDawacUd8zzieZjCesMOTtnmPf0DtmVJqN1Jqme/vFX3zHqcpu p+P/cdkaEdyV6Yv8W9+9BzK/Qza/z88skVy6OHxwL5l/aMCzqw2BwSix/frb EbJerRruppvzQ1H9wX57e5LDJlWf7704EIYhC4wnl8h6x7z+y3CL+Rc6gU/g dZLDDGfXet0QjsKYusasdyRXizUX24hfisEEu7zPLiR3e9P1LlMexOK4rtc2 C5LLyy4KlMheiMcnBQkGLSS3q3jeexyin4jHVY4eUiG5/kQ/I3vysyQ8tUUg JYLksJQcOec4+2Sc33dn+xjJYdPbVKx0Q1PxQJIMcwPJYZe3hlhxJ6Uh14xX hhfJYQF6iZ9/FaTj4oUX4ankc0ihyZODtv2ZOPP+u8S1WgLOLHF5pvZkYX5y F5RVElC1cdm4rjMbA1SmF7WLyPvVjTz53ZyLtwNjVTnI+bJ7b5I9p5+Pk5e+ mkaQ8+fX9cyUfyAfL32hHt4bTcDaj72mwnoF6H5gfXwB+Zy17LL0gE2nEPeL vz3y0ZWszzNWh8EbxfjyHG12/ycCxoTMWAzrirHHdeJ9jB3ZP1vdiSalEky7 ZCqg8YLcH1l3WJ9cKUXJb+IVR3VJbv+T3+kgXY5LadpfdxwggF3MiqDtrEb2 GxGddUJk/478Ze/xq8bej5U372/7733YY83x/DVo8Xgnw2HO//bhsN/Shlrc vPXAiCrJZR/rJfI3vqnDCwY0vsEwkqsO22/gM2rAfQ01QjH+dJjqatjGGtaA Q+sUBzXc6cBVGJA02N+ArFkHIlXekdfryn2MtBtx66NHV7s16RAQox3upNSE odu+eaiz0MnzVWS6KNaCydUZSc/naZDsNffRxqgFTRwPqryi0+BT9HflsZAW tF1fLnG4jQY+L0a53vK3ol8ud+z5KBqkNsiohq62Yllyk8pueRp8HlsJ/F7Z jsu2FZbvpGlw6l5z3y+WDpxrzK0sOEwDI/eD+iFnO/DEyePnZjbRQD4yWvVq XAd+2iHoxdlPBXpj7pKhWyeKxY9I85tTwVvz9Yfo6904oH/KKFefCj3jxr+3 fOrGsedx7lfVqeBvZI4PsRvtVrbu5jlJBZmPr2pTxXpwzm/DT92lCZiV3zb8 l70Xk/aylDO8m4Bj666nTer0IcfXrJ3Fzyiw+3oY3zLjAF79m8f+S48CLsEh PZPbBzAhUtrosRIFHGCHbt2pARzc1d4XKEKBe+dr1tx4OoCnN0YIhLeOw6aF ched3gE097E7rXBsHDTv1P54ljaILGVyFN2d40AzOXmXr2EQF8MvWWlyjENs R85UAHUQHwtedJ3tHQMaTW3tU6Eh9P13XWrAcQyYl5IqWJ2GsD3oV4Fv2yiM r/kr1KYxjHrU6tC5/FEoUTzLxW42jGfrTSlnokehT4p/eafjMK6d27Hh2etR KJU9eY8taxgTzW69Dd81CnzyvMoJ20fwrccnykmS12TiPcNu9Yyg0KvQ4rKG IQj6LE6RVRxDhz7Zi/mZQ3D/RJ10sd4YFp/tcw0LGQKTd3OVEpZjmCgg2Sdp PgTay2rX836MoST3X34driFg9wwsz6WN4YezmeWc8oNgcq3p837Hcbw0ECVS dXgQGrW/fxLxH0ctSf9a682DMB9v5swZN47vCpWNfgwOwJ4zHfecmsaR0u5g wv56ANpda7Vu7aDgwcWdafYx/XB+fX7Dod8ULLqyw1X4Wz/s+Zj851suBccq bp5PftEPWpVhKz21FDzeEJoQdL6f3KcHAvdPURDir1nHt/bBq1v9+98dn8Av ToI7Pyz3gjpBFT6SNoGuQb9Pt9h1QU6OlfzxcCpq72c7bn6pC8RPM/QapFCR lvSsisbWBSxntNxeFFGR4ulKfe/SCY7SoWxSA1R8ujoTd9qjA27l/dDbK0hD 64vGkUwBbSS35z9FRxpqY0Flxp028HrqydX5nYb/Tsoxq+9sg9LEv+VNoTRM +Puw6WRQK5ik8Kjcy6HhUL7sXE5QCzjr8m0botOQKv3SfMW/CdSze+89V6Bj Y/bisa06TaCbcZv9sQYd566m/xQUaAKhBzNUmbt0ZIwoTunxboQEsb+y757T 8UrT1vKb7g1wfby2XDuQjiwdATvzVBqAy9R205lIOjo+yLPm5WqAbUxmsv8S 6Til0vfAxqUepnq/rl9TQscbvQO3dd/XQd9Rlys2FDrurZrk2n++Dt5+TDOQ nabjppsrl7NXayFbXJVrcJGO2itDR/f9rYH+2ec9WesI9C3cKqnZXwUSK17a BYcI3Bkh8CImoQy2Db1iFzAgkK3V+Ny2Y2WweGyqU8qEwLjRnDbT1FLAi6aK R80JfMj/w6YpswT05BOp1a8JNOf7IutWUASVKVFOju4EtkoE6SlcLILjryvC Ir3J/4/Rlv1TXAgDCs6SUT8IvKWZIcNUXgAWZ3kdFCMIrC3xWXu5Jg/SAreF b8ogsHP3P7bH1/Kg4PzF/JM5BI6kGLxgDUbodXPaL51PoNaWNpuVnzmgu2Jf OVhG4InA85trwrOBK8Nt1aGKQNt1ity2v7Jg072nZuvqCOTarSfsGZ0Bov7p CyktBM6tzz85F5MOH72t1ne2E1j/6FHE+dg0MNTLutbXRWBY4R1Xt/gUeBnc quE8QKDBTAGjd0IyyOWybZYcJnA3e1iFY2ISvJg2nE8dJVBZjVn9aHICyI4U 7tanEviSDny05HiQ7eC770gnsEN/Su7QozjYrimT92WSQNlJS2Zdk98g4C9z /PkUgQ2usjoWj6Phat7hfOkZAs+HRV578iQS9HMv3xucJfDn0vYuZdMI8Hk6 sNn4H4Hv0vYxbDELAylv6+66OQLHtAwzK81CYW9zeDL/AoGm9d/WmjwNBs2E PX7nFglkbhlpmx0MAPYf5V8uLRFomVFaODPkC2OTbm6Hlsn6OfrXtw1/h62E Z+A0qZ9oqTGEj3wD4aINGb4rBCoep/jl1bhCioN6t9Aq2Y/th5/y130AmbOD nI6kFjRxnY8PeQVfm65frCP1b1lNqvhVQzh48ObHf6SeS3+bJXVPBd3Zauv/ e39u56swG3ENC7TakyAyQurhCoHX3QfsMFVo84ffpD5ddMfLbb8TyrhL0dRI TU/VK/PkdcOxWWPdLjKe0Bbb1HoeT2RLFu26QGqHHGbvOW4fZBLmvu9Mxq9q TH2yhvsHJjs0/ksk831r+jtg0SEIUzkVvDPJeqR8LbbTdwjB9yWmciFkvVi2 0YbSP/5E17RbzMbzBAqxPSiZ/xCOvCUyddxkfR/V2O0X/vALZ9Am1ucvgVEi VhZi9jF4QmTqp/w0gfZZ29eyWsWi3wa+a6/+EMiU5xGrKxWPggMnlD8TBBr3 XtOjHEzEAUZ2Vc0JAo8YPmfbvDcJjQB1No4TSDM+pnR4ZzL+kvtcGDFC1lNh 04wIbyoWi1cn2PST+QZIWTKvT8PHykfPZfQQyH+A3lS+Jh1D4n9ItnYSaHOG 4SnXQgZ+pMdqpjUT6H6te8S4Nwf/sL1eYifng9KjvM+mLRdrTv/hUykikOeF Y4VpPeKnqcLfL/MIjJRPOfe6Pw8daHdMzdMJ9L73L0u2oQBvC5UGzYQTOLXh dZucciFefJ57QD6EwFzDDSanKgrRwzBP9S05z+IvDQWH84vwX8v9H1/J+X+x yy1EPr4EOZp4v1x+Q85PhveL36KleDX9RUSkFYHr/hSvXwwvRXXlrk80cp98 LRT6qfKjDLe7VWRvMyTwtm68c++nCtzq99GJU5mcd/oem/fMlRiwYupsc5m8 3iD2euObSqR9+fq+VoZABap9R7N5FY5LnbAWOErgNTPNg/zaNeh7JVxEcTOZ 3/Opkt6mGtxeyRFavYHA+eWqciflWpRby6MsyUaghpIbf+GuOtz+Vlcp8B8d dYeNuph46/FOiWfR5lY65krbbrk704A663u+vPxKx66SeAvl4434sTMqXuMj HUedlHaIPG/Er++MNbhs6Og9OHHM/V8jmu3X0BU0pGO0FfsznfkmHD37MMX7 DB15+bhDH821YNzhtAdiPTS04JfM6DzRirZvRP1G62ko92Cfp+SLVnwwqS/0 rpiGBmqf3rnOtqKZrKqmYgwNuznUbq1MtuG2j82MqlY0XHvGWODjQAdGBdko inDQ8DDNXF5yVydaZ8qYVy1Scd9bzcac2514wjq0Q4VGxQKOwiHrtk4cCGxO Xqilom01m8nzqi5UcZu8W+JOxaauiKmLsT2oInUyTm0TFWXu5JrFifajYMLw ahXDBFrT9/KZyfXjo6X1lmkEBbmEtqbvvNuP+yXFHjr0UPCLUrS3wvd+pHFw 8bRlUdCx2Ky/YbUfTd/fkDtnScGrChF/PtUOYNw7DxexwXGU2a5rITY+gM4s rPxWdeP4tPyHNjIN4u33G89E5owjD+6Yjjo+iJxJ3L7oNY7mARedAnwH0X+R Ly/36jgKpNql9esN4YDhYV3+mDEcZ7Tsu249hCzrlx80eY0h17DUULTbEDLk Mp+2th/DR753BfcWDGGV4JTPS60xtDoqnSK0exhLn86Z3mEbwxm+iQXxnmEs yP/5PFtnFL8mMcfMXxrFQ21T8QZ/h5Gnk05xuD2KH9Z99FLvHkaBg8oHFy1G 8ebCq9OiRcNowyhy7mvoKMpJLB9wdhvGM58uVj5dHcVchbChXaLDSIjOP1pM GEPmBY+6nFtDSHv870J16Rj6mN+8LQJDKP23ztquewxNM7k/vBAewlyOAd/v 7ONYc75rVxN9EP2YtJfu3R7H3+KRhLXdIDZWb1p4zkjBJ3xmpu5hA3io4cyJ Z5so+LPz+i0PxwHcNJp6XeUABSkiRa1vHw9gU8BiduJ1CrYGXuDjPz6AFd88 GNgDKLhxzYEdVwv78TprYsvYkQmMtdfQ7O3sw7ju7ccmL1LRLfTh4/vL3bh+ m9/3JDUqhnhx9f3K70b7lMePbt6n4o8nHuJVH7oxTsZRRMaeip/C1xjHr+/G 9x6uzB5I6vYbsX8FutDJfaVJ6ggN7d74vkk50oElmwTfzQMNf14OPss2245N ez96+SnRcIdXGa90WjsSixE1r41oGFk5sOX6mXaMYZjKSfenoeCeTZsOnG/D uzrn+ZdWaDjWZB7febUFh+Q3ZsRy0LFPv8nwLWcLnhq7Pwyb6ejeWO7GUdWM J79cjlo+RMffbWc12xSbUWHu/odhTTrGTuab3SKfv4rv0rY569Px132r1zLr m/Cs25q2DU/oGGbJeZy7uhEttU75xtvR0WhzfYGZYiMqNrMx6ETRkU48kpC4 2oD5ws+//Umio5fPmLHJ2gakfB+fup9Dx/VqBZ89yupxQ/bE9FAtuSf22idF ytXjwYq17VdIbktfn6ZDyNYhK1NlgRe5x2w/xPldM67C/Wfnpj+eJnCXcyP3 faISr7KJ9d+UJTnlgtD/arjzcKjXLwDgWrUICQmXqAjdirrdSI4lJVGkRSKF 4pLKWt1EEpVCVLZws1zZs2/hIDKENEayFGbGMpj5kvUm+r398fvzPPPHfOec 93vO5zzP+4yHlft7tFM91xZH+mRhnXYvn3cDtkTIu1WSPvol98iZ9U9oWNq5 mF7mTOGccIXBeVEaNsoefhPtRiFLndsXGlmHSV8uic+RPm1V92g8++U7LGHO njJ+Rubqvea0kdc1mH3V6NrJKOIUu0CB+7tqcOmzWo5WHIVtgfs7BYveYmbI vuEC4rhF0vIx/eXVmLFRwEEvg7gqvMn3D51q1KpN3ZWbTeHZINtCt5oqdOvW SNxFnFfYvXisrKESu5aPaf26/7bsmtAgzbgSzcqm1msQ590UlZAPjEdcWFXh WkvmWEuvYK1sZjmyRc3tHYnjKgQlfP6rLkHF7k8PAojjqKZzm3bQinHd+IFG P+K41dKyb42ainDe0DNTjjhuqWxJlV57ASrz0/Sr2cSdihv5ZbvzMXapwpQe cdyR0A1iA715KKXgHDJM5vSrrWXm+4ZzcMye4SFEHHfPIcTjPS8bfygfcBQj jmvKCD4ePvAad7i/c/xB5v5VFf0PnlQm8hn4edQQF1gFfTHQmE1HnYzKB87E cWtUhV4x+dKwJpWZMEMccbEo/aPLyhQcNnaqtiHO6NkZm81Zm4y/ZXzvzyIO KdBhqxhJJqFkz1GBbuIU6mC4ygv5BFRbdWD3MHHMCZ+uiM/KL9HWgmHZQZyT 6dCZI3ApBo35JfxTiYMayhWzjDwjUe6EfoYFcZJzpOGUe8AztHyS/XGUxLOP l5k/DH+CzhKNk9bEWZbTlkeljB+i9qmtYvkk5mSdtF/t7IvpVW5qHBJDy2v1 tg1uiL1/G/38dZ/N0HHNykZDpA5ttZ0m8fkLNMeMJgfYG33Ps/nX/TjXh/fl FL1gycPCgPskbgr4i5Yy4Q/CjMXPfjnScqYgIL01CLYdboyLIc/zUMgxi9YR Bh/fPn01S55//Vr/E6n14eC86gFjE4nnis0XOQi+gLuJ54OVye+tozM7+M3+ gbWR6p8ESD5aZsP4qt/Hw8Yb5pkNJH8imQpNI9xEOHlmm5gdya+j7hn2glAy mLYZC3WQ/G86Od4+q5oCXfw+sUqkPuEKdPV2szRgPk6vOknqt9hm4UWERwYY eQ/dtiL1PdIX/eTPiCyyN7oztInr3hbPnrCwzAY1QT2L6GGSn7RzhnG3c+H+ bnqw8BCFcRPv9eWC8yDP5LCDDdkbBgwXZoPi8iFXyUQ8qofCrfObM2WxEMQb ro/fJueVLRaho/uhCKZli7y1yHmOvNmYf7inGI58dqs4TiduX3hnvfhnKeQI MG4kN1PorbRoW45gGdwOXTvV1kBhsefIT5Aph8hn2Qdo1RSuitbhzGoieOiB 3KMKCt0n5A2FFSrBImoZXamUwuOL1peEZlZCn8yZmu/k/dSU+vCfRVkVtB/7 4TsSQ2G+UenW6c9vQVR/xfOgCLJHld0Y6beuAX/zkpTVYRR6rp3xrBiogeI5 45EXARQ6TOb7Kk7WwvZBgYg1V4jj1T7F0dbQgHjV/gnpR0GL7/Rwn9LA+av8 Neo8OX+hDJmZDfUg2tJ/QNeMnKeSgj15Wxpg6pHZl317SP+hb5Gt2tcIf1zf rR+/ndQrViJlqrIR2B4GW1gKFKqIv3BeebAJirW8XH4Q5zGlR441HmuGpvTV +wKmyF4+XezavrMFlkfkyfxM5+G9tsk3qkAHgQwXk88JPJw5w19q6EUHRpaE 2NMoHk480LI0LaGDysN1XpnEdZc2Y7TCrlZwWT5R72nNw4QLcbbDWxhg5xO2 1m41D22Wmfom8H8CGXOPpWf5yLzA1rs39T7B7NF4ld1TxG2XuPYaPp9AWRf0 gojztnm+oG5MfwILtW+MrtdcTFlR48VktUOPxL2mSSMuOiwy3LC7tAMw+YSn qDb5PGJjQdBkB3zwtRVZv4uLssqTD5u2d4K46cTpWgku1j3Xn1lI6IRTWYoP 65ij6PBA5al8YBcctFprd8VlFOtOJ5VpmH2BhXVetLSbI8gGCb4w+17YrDnW GP7XCD6dMum7cLcXyhb2vXI4M4LZfQ/45GN74XyyulTF3hHs72OFudJ7oYpu XqQ6PYyDqyS1j2v2wY4It9rDl4exIEeycEqACUppRdHRFsNooygTX67AhO/N Nw3oBsSBToN73bWZkJXh7jK9eRjfKWQLZLoxYTTfrnNdNwdjNy2NNuxgQsmV L+dy9TnYk9WqvDGeBcO1eewbahysNxILqCthgd6m11aKshzUP+O0xpLOAsVb XFfN2SFcdzFY12gJGz7sdN19OHUINX7uKz1oxwbRr6sy55cP4cyTZcUh8v3Q Gl7bcDZnAAfzM8MZIQNAX2j4ahc1gOvHL75sezUAQ35VwSd8B7C0t+2PchwA retvtw+ZDCDd9VEkUANQqCruxOL1o/9+mxOCxoMwUG0trKvQj5y/1CvKlgyB 6huppiqBfhQfVdomKTkEG4ccWUoTbKx1bfG33DkEH84zQ/KQjUKrTkaGWA5B nCJjXfZpNjq+D/DPyBsC/uqSm/Z+LBQcD9LOsOSA2WtVv78dWDjBOjdp5MIB vqorFdeNWTgybSzy0Z8D5h75eqrrWbhczG2nXxYHaqU29iWmMvGjiu2Nxwsc 0FSSc0to6ENbDe1C2ahhMJtXEqiZ68EQ3/KCvKIRyBLhjfXU9KBdvNep63Uj oHH1r6ruoB48J7i9QbZ9BAJrOD9uyvbg4feaXJnpEZBhW9AMdL6iyPL8Wwy1 UXC698jW3qcbx8LCeoRejUJCkq93+sFuzI+ef7OhYBSO/ZilWtd046hr313+ t6MgHTyZT3/RhRdzM6OCv46C5I08ZlBhJ9ZGRbgfFuVC8fENP1UGP+OG/Nf3 Lv3NheBUg8YPGZ/xuqswMyWAC+E5LR5nXT+jSMGgZXMYFyxYqKsy3476GsG3 qtO4sF+Gj6wG7bh6aF78aAcXvOljbc/3tKGdwMzU0E4ehKr5OdC/MzBcV7D9 9D4e8I70uX+vYGCzdcfmVH0e1KNO/5pDDHS6YfD12xke1AUnPzE41YqZTYIF cr48kHVPytZ2+YhJY5MF7HoehEgmrFb//SOWP7u81K2VBz7T4p7SnBYclUqq 6OrmgdyR+Np/z7fg85X/GGhSPKDmvBjhsc3Yerbfa68IBfodjwsNRZsxskzz W6QkBZv9LnI7AptwvD/Cq1Wegst2LTOPrzfi9XL7lE9qFBQZP/ty+lgDagd+ OypqSsG/3/OqZ2vq8flEqtUBcwqO3krc/7dGPR6X/3PPUWsKCpZciZTbQkMv 6dfy1GUK2hZJ24j+V4sJ5SZLLwZQ4GG3zqPRuRa7itJv2TymIOCiu4MjswYz 3M1uq4dRsMNCK9Li/Vs8tFpriXssBWXnpUtkYqpQuKnQSjKXguPXkp0khKsw bf6SI6uQghW9SqbzfpXId+Rpk/8bCozzPlSKt1cgv/r0nVM1FGz/vKLSqaIc U2qc392jUfA1tsQr5t8yXGzCMnrcSEFj69z9cLdS9Ew0XanIoMB7MtfPxqIE xf5Ytqe0nYJXrUoRQjrFWGe3LVShiwKaiNEFEcFCFIo0qw7so+BnsOE7x8l8 DJt98OQumwK+ivR/Ujvz0Ls05rbZIAXsy3FrepNz0MqiNfnOKAW6yl6mnY+z MboyububR4HAy8SWO/1Z+OBlyWaRcQrmfAROKOZkYGyXhdfGCZKfxO1f0rzS MPT9ij7+KQo+Wu2UFjRIQWd9FxPaNAWLzllXma1LxnMxLrQLs6SeTr/f9v6a iMZJ4ocY/1EwLvk7X2hqPBrmxzTIzlGQK/zbtBQnDhNSrpoe+EG+T2rv/jHv aOxkK3fqzFMwxnflzyTRcLQ+GWUrsUCBSn3Kwf1poTh1rWC0jsQVzweifH0C cZlGqrvJTwp61PvNHdJ88Rk0f88hsbWK929uaS64Pi7Te5TE/JaiuxSSq8r+ /391/wPFgo8P "]]}}, {{}, {}, {RGBColor[0, 0, 1], AbsoluteThickness[7], Opacity[0.9], LineBox[CompressedData[" 1:eJw0mnc8Vv/7xxENKpV20ZRRipaRXEokofJpEA0NUlGoZFUyUwrZe68I2RmX vcleGbdxG/c4J6tk5He+f/zuf+7H83HO45zr/bqu6/1+XY/H2XXnidZ9Lg4O Djo3B8f//v//Zzm748LfaRLM7VbNn1I3hoOtMVIMiivWPoySVrcFawWVzjyK +3Zm1W3/6wgbi4VUTCl+/vGz8mp1N3gRYvByGcVtzHan5xc8QaXM6OnrKRKS 39Lm22a8YWP3u4OdkyRolIYSohH+sOWkQtp6ihM9ksoenA8G+RmBRakJEo5l 5E6fswqDEy1J66TGSfA7HDzUrBkBGy6WEmt/kXDN+9/gxT1R8C5K2KuFICH1 75k4/BMNjWUZSyzZJKidSacL1caC930ThUUmCTp7H180DouHiambyoYMEmxM jW2bVJNgpZlnXvcwCQb6+2KHtyfDt/X6hxhDJFS/fmNg9jIFhDe+Nu8cIOFW IcFSV/8GV6+kPL/RS4LERV0BkeNp8DVp4fjETxLmlyUFT+5Ih/6w1Q0POknI v+FyWn8yAyxb+tznmkkYy+fi5+zJBFuud3mbGkkgmYqR7uVZUPa1omJDPQnd m/QcbfxzoPFypWNWBQlhdP/2Zwr58Hb2T79HDgmHV+e4vhEpgCuzLefzM0iw 3sJX/mINwpTN8vjqVBKaiLVb1pgWgsme36rv40n4+NPxkPjpYmj+qP0sypeE 2pnfYxcziyF8KLeuz5MEbs/00w/FS+DYYO6RBTcS9hDbrMzXlYLEjp9Heu0p 1tsa29ZfBj27rIxlTUjwdZOec7lSDsZevF6OD0jY62GnuL+qHHgq+YfT7pDg 9CBQWSGlAkJ4PglmXSXh4FqxEi/bKog0IK9qnyRBxeuwXtb6OvievWM3Lw8J 7AQV3X73OvDNWVzfPk/AmLnG8omV9WAR73/FboqA6tLtcWXcP+Cs06Ye40EC HpxxrPaybICN2ZwdsUhAlEsWj+L9Jthfb2MbY0pAbC9H9pOIJigVpP85b0iA +xzn/k99TbDt+UalH3oE1HWKGQXpNEOn7CrTJ2cJ0HHx7BhTb4Firw3Sm7YR gGZPYrZLtsGk/XbpVXlsSLHLSznwuA3aN7jf8kpmA1OMt1Q0rg3mRqvn/0aw 4Yjx8LqhHe3gGipVcvsdG76kOcXcXt0Bdy7algdfZgNR3NZ2YqQT9h1o1qAN sWBsIda/1KkHTmoo5w2ymMDR5Fi6Ia8HGPp3jz3uYUI1H0+a5ngP9BbUDXfU MUHmxv5lFrq9cP3ghPCtr0w42JSQF3iwD8ZXm9vvNGHCczMRtSUPaBD985rT 21EGnDA4btNjR4PqJydLL7czQIJ9fTA+kAbs2Mz1K8sZEFoiPbT5Bw1MrWtE xCMZwNx3PUP9WD/gaYcMYT0G3L1xKnTyXz/UTYaUilSNgfzmdK2hTQNwxCJG QStzDNInrziUSQ7AlGRx0Z3IMUh1PT+pfWcAFFxw73HbMfi+y+p3YekAiNb1 How7NAaue/SlbJ0GIS+jWq7y0yi8lLxgMzA/BH+DBq8/PzkCXy2W+8sJ0KFJ eFx1XGQEfml5m74Ro4Pbjl6Tq+tG4Ml/wqyWK3RIfZuf1D08DLxR53aFJNFh Tc3pVT8/DoOmyrl7ATrDULa1Xzuliw4XKmitRSbDoL/EtqmyhA709Et6rfbD 8Dg1O78mkQ5JP98rFCYNg+rRfSc8XtGh30jZMoJjBHzFz20U3EWH91q9dLuI EdC5taRS7c4QVNiN37yZOQI7zuyUWq82BP/5XDwvXD0ClV1HbldJDcGYQPlG s/ERoLGYD/5wDMH1Q2Vx3DAKHZeW+94LGYQyw8Q7f1pH4aD8tIZv6wBwtT40 uDsxBu4XDcO4jvdDPcPsTS03Ax5EXb0vuaUf/JrEPDZvovLwM/nnuXkaHDqh LKhzggGX/o7cUCymgVmtmvfLtwzYlBusCho0IOnbN23iY8K4X6KKEvZCxxZa VPg2Jjg9qW08Yt8LzN++WqsOMCEy5v7IokovND/jC3ZWZ4L9P6/S/fU98EzW hcb9gQnzifJtnV3d8B9niRwvDws2bNfzqWV3QfqUeL+/AAsCdPrMfJK7wHmJ z+/lu1lgJSsDiqZdMOYmutxRgQXbt3+pPDrVCbtVb3FPPGfBD9bjz/EzHRCS ZvHrXS8LVB9tus013wZvreTZ3EwWyDGqPrFz20DJqLH1xh8WmDlHqudbt8Hy P35r4vnZoB6yL4hvrhV89VNKIhTYsO/Oy/5HMy1wacj+4xofNtz7obXpFdEE XvJXhFND2XD9tfslmdQm4BZLZh6OZ4NSak59r3kTXKs2q+rMZYOj4lf38ZlG +IK2e9P62KC3a1bqGFcjHHQK8tAdpfo86aOddmkDzOzpzxr6xQaexMH1D50a gPuF8IwfJwHLPxuu0OFtAHHDLbXOuwioGJJ06NpdD7G3Ax2PihGg8Fbzo0BM Hbz2z3UrkiSA17j3kIRYHayrPKxtAwTM3DmuzH2oFkTn7jia6xIwsadg40XZ aqgdp+vvukPA0dlZmaDcKlhu1nww+QF1XUWHv+5kFSzyeZs8fE7A3/OnGb2n KsG91E7/phsBbM7o3kbVclivXhrI+5mAD68+7tOqLgPF4wvPfPwIuHTFRC33 fBkcn3zepx5JgOCKX/JqmqUw9Yo35EgWAbfMlz830iqGjbJbOn7mEvDjTbgS NBdBkkPF47uFBHROOu3gulwEXkSd85oqApQvXtt66UohJK3uy+vvoNbn0lCo /DUPdPc2cDl0E6DinZvT9zUXwOLFYx4aAUW7PoFe8nd4bvTyc/QwAe9ZCwc5 U7IhcS5WuXSMgHlZr6z9KVmwjX6Up5hFxRfPw3cyJRP2nH/sd32CgDg/Va3N Kemw6WvknWnqHFAg7hoMJafBYX0tkSd/CKC5MRwDk7/BrPa5gYq/VPxzukUK yalweIPHp8U5AqJ/aIv9+JoCBmlG+zf+I0C6/1RwoF4yOHGc/8bHQcKjqD0O FrpJ8DFB8NnnJST4f+782qwdD1XjTS3K1LkkeX9ZvM6BWFDU61BvXEqC1j/Z uOLFKLBx2tZ5bDkJE8/O3FvbHAEOWu0vzFeQMAIS3qoxYbDuz+c9rrwkhNZf Gm6dCAJYJdJjyUdCiIGY8W8/PzAISgs/vZLyIZkDh2YUvMBmb8KTIYofVr+A oqpPEBhTqXxrFQmdOsp6Dzc4w78vW/ekUUzWfD/MLrKBk+f/LqVR/HD5pwcl qQYwuZ9vnE6xpOQ80aeojQEuZ/pLKRZYLrFRzdICuw+OtNtQ3J4xYbTD1AG3 v3rbuopi4iqX9BthN7x/b7LLgnr/pc63Z3tZnhitc2/sOxVvkNzbiiEVXzyl o8HVTq2nzUZKvD4sEP90movUUuv1qrb+5zUbiltLGdcDKD0KZyrGtohH4C6D daGnlpFQ8PZ5UNPVKPxk6Pe7iNKz006qz9Q+BiW/W9zbxk1CdPbm2ankOAx6 N8PU4CJh3cKrYzrdCSgtluKuQ+XH22mqM3B5Et7nsLuqQOXPQu685Pejybjz ecCpeSq/D+fqCrVTUnC65eXVz1T+NYjo91CeihrydP8lVH3k17gIrun+hutt ptdoUPVzXct2W9V4GoZHtyc/IghwPRD6i9ieiQ1p/w0qMgmIyapep3M4CzdF VuiTIwS8CFghHXM2G23uS13voOq58OEWoSHT7+i64fDAuh4CONoSJZqcctFR QLFxXyflM6p7OoID89BTpnPJzwYCpiIfhVSWFuCRvTXXrGspnxIfsUy4E3G5 m++R6QoCbLU2tya+KER+nbKY5wUEVE7tFop0LULL1n7nhHgCmpc4OdmnliCX 4zLhzVEElPQ2/VyUK0WNngD/WyEE7FTdMHmntBTDN6odt/Ek4PG79/ldbWUo GG7kyn5JgLYiW+TVbAVK/fGX2G9G9d+w6rigfSVqSvPzKj0iwPvKpoOhfFWY 4sUdzXmDen/e1E2l7dVIWIoSuQoEfPd6fIxDvhYn1nqemThOwJO4s093FtVi nOdoGPchAmZdRg4IqdThY76BmHwhAtRI2fTkC/WYOmrr83aeDa94TQc/SDbg z/U0JYNUNviRMiGKCk1ov7/T/F4sG5JSBgT8Xjehpl9/GgSzYZ1twaPOwiYs e0b76ubChrqT9p82KzWjiqt53LsbbBDxsdJ8o9KCJ1xW7RbgZEONm92TNNU2 5LYgXZlTLPA7+8Hc0aUNo4SvqkaMsuCG1KpI+co2TJg7vOXLDxZM9Ezp6Zxt x+WPR94dCGLBG5rL4TNnOtBNJoxjySEWxG16mRMq04XW7lNpCfJMGPhxy9t6 RS+eT5qw/SzBBFTgqtM/1YvElswUfSEmBPcPL4ha9iLz/N2Er4sMyF5wN9UZ 7cXPQnJGq4oYIPNEMEO+rA8nncNPTygwYE/7w2mTPBrahVy+Jn+QAfND0So3 2mn4+TmPqrEgAx6yTz6Sm6DhrLOdoMPcGASvflZRKNKPr6K8FVwo3xW1omtx 1qMfzdPo1YsiY7AzNPQ2/90BTPWiry7ZMAaPniUu7bMZQJXNWdkmS8bAL2M5 GegzgBeXNUa87h2FyB/dwj1V1P0MG1/Xz6Og8bnuvdWhQdzbddZI9+8IGGx6 /WHln0E8+OLBx5D0YVhTnXyT/YKOKT3lcl3Bw5A7FXProDsdy2ez5hechiFz Zg/n1Xg6jiqqnfunPQzB2/bnav+k48zy8AL6HB1ylLjExRSG0W225a/xSTpY f2290/dvGPclDs7JCdOBKWWs8GrjCC4YrD4+sZIOrHv2u7gOjuCX5pafO7qH 4MTIuuBsvRH0zeVPsrYcggLua9U92SNIFBy5+1/KIEwKP3019WgUfT9//NPs MwjvTe5ih90o2unwjiraDsJ+RT+vMN9RfHp//j7t3CCoK+6J6ioeRX3pXHfZ gQHQ2u46O71pDHuM7O+a8Q/AL8+gjVl5Y2g6Nq3O0KOB8hK2ejvJQKH9if78 SjR4Xd6zqomDieNSC09FxGhg8XfjcOpaJl6W33zlJqMPPvZJRe08wsSb+72N lLb0gXNLWXP2Mya+y+LLuWzWA9pFw4qVE0z8Gx7rueJkDwRXDm5ZzcVCvZcS DTHLemDGZviYzFoWKvoZnA0M6oZTv+N5ZA+xcEBwT4tp2U/wrvyRwjRiIXOk 4DWXQBecv7x5kreLhTlLnRuudHfCB/M3jz+NsLDv9N1cr+hOOHu/4cmfKRZu uqIp1ibdCc8EHMZM+dnIfttAf6zbARqzbxz4ldi4r+22y4bQNlg6WOAyFMVG Jb8MtqxhG9z8Et4elMJGqYzq5RqH2iA9PmWtTB4bc1eZ71HEVjikdWDPpmY2 /rfW7cSt3hZYFb+99MUiG/cu19z3ZUszZC5Z6Z2uReAJxQyuX/1NECBqsMpA j8B/PoZ7RBKaoOzpHoG5+wS6Jz4ffCzXBL0S4Qk/XhLY/iHgmO71RgjSDjy3 O5jA2dt3V0rvboR1c7cek9EELn+V7LKU0QDnjrwfDv1KIJYV7LSj5kFbp7KK BCTQsbd6b/OhHxDt4ehhSCNQ78netPqCetjtGFSsOUqgbUyNUrpGPXCGFG3d 8ovAGR7bUoVHddB86pvYtUUCaSE10dejayDz20Oxl9tJNFE9YzmzoRLqw60P n7tEYk2bhExeZAVsZafevH2NxKZo+3NPpCrA26Ff//oNEi2kX3yLUi+H/0r2 dP9+QOJeU0W88raU8uWpEo2vSBT+fO5oMH8piDz1CflnT2LoNXOftqAS6Lfx Kl/9jsT9PUeMd2ZR8/rEW4l2TxIbo00ebWEWwo3HT/8siyYx7aD2pb8WhSBx ubZQLZ5Ep1VhWXXchTAdkrfvaRKJlhmj/gnyBVAYn5h3J4PEi/KHYd3VfKj1 4B05lEOit0aQ+f0neeCyKyeiL4/Eae4TGxvDv8Oy80klwyUkbtkkU834ngMZ srN7FCpIHBMd85tozoauJzF8L6tJXM0pu+YHTxbInxR48LmBxPki/YUooUwQ yLDveNZMYtneKx8fSWdA8YG0Cpk2El0v7N9T9yANRP94b33wk0SP2VizfONv wKFjXbq0l8TwT0WZIWapoNYeHv+WRqLK6rh8U4sUoA/9rfg5QOIbvpoEk5mv YDPlLriOTqLq1UJfGmcSfDf3iBMeITFlMLtHju8LDJSfNtw4RiLv6tD+r4Kx 4CBlYPmJRaJfm1lrzb5oCMv/U7WJILE4Xehj+6FIqFx8qWpLUvnQ3xLTLBMO 4pNFk/iLxPPLbz2xtw8BlWcV1X3jJPbN8X9X8Q6A2wqBtd0TJBreunh7KsYH jo49msmcJHGr5y/vT9me8HvYQcNkisR114QEpb3cwPWtZg3XNKWHrNLc8SxH WN2rYfqM4uuKkzpq6daQOb4XSig2e0zc2TllCA2unkdJis8SaanBnJp4/LzZ pRmKaVyW7s+szHEoLs+7l2L/iCuVWgF2+IvtxBlBsVTCvyk9i3eYJ7PE+zTF juYtR8QS3PGxzZuLhVQ80Fyu5+Pnhel2D49uo/j28/qiCSc/7B45d+o/Kv6H m44fOvE8CFfvK7V4QK3v67l3MplSYfjvQ2DHdWr9w7uD44tEIzBLNfmeOKWP nVzIxYIdUdh8Z257O6Wn1e0DnxM2xuDPUj8ufTaJeedy2xxWxeHyE/kbK5kk Kqt/fHOeOwGPWeReX8kgsWF7+vT87BfcvX5Jg8QoiQUeXIG+40nI7b/z5YFh Eh0erGvdMpqMyrb5l5cPUXo5CXKfIlMw+ECYYVE/iUJHzqobMlLxKV/it2t9 JLZtLj3kTEvDU7Qbf7d1Uf0T9+Dg65/puDda9++5dhJvbTu126AtA2mnDstd aSEx8J7m14WaLNx/RsdlST2JvdF6X+Uzc/Eb0yICkaoP54tfvVPy8EfE9an2 XBITjApE2hPy8VEgI7gui8TdZRNn1oQirqiM5bmUTOJd1Rnh3SVFSB/b7JYd ROmzXkmIDsXoWbWVM8+XqmeJ2lX+ecXIOfOLEUT1Mxdzv0RTRgmKz92Q+uNM ojrNqNc2tgxzw9yXrzYlsTDwwGHjbeX4IxiCDR6RWDFc9Vn9UznO2o9C+H0S 5+IXhLteVOCFUtHCPB2qfjWfc4soV+HaH7dF3RRJXDmzW8UtuwqnjRXifstS 9Xmjo5u2vxrDNAyvnz5CougD8QTNdTXIrHxu9EaYRMkcs10nemvxNsu12Hc5 ieaCT424LtWh6HuRewKc1H7Hz3kmvaQOf6Rsv2P6l8DTcZ/U2+LqsXXnj3ct YwSKGNDGuWUb8OL1qAMyVQT+Mbgn8WuxETW17A5ZvSXQa9mra59lmvBJkYWp kCWBt7dtnhE1bcILjveeRz8hMM5heEh8oAmnNcv7dKnzYWil/G2HkmZcePN0 5aOj1P685fG++/at+Cap+e2WPjbOpC+f2ZLbisnSb0zZ1PkjXHDsSsFEKy7T /RoaVclG/aJlUy36bXil9FxPXiobi5LOuR6FdrSM5WjzfstGyxNufz1/d+A6 2cvN40Js7JiKcymQ6sQInn8aw2vYSF56KdX8uBP7AwtSc7jYqKXr0po50IlF fA0PFugsvMo743C7rgtHNy3yziawMHjDyb88Id24TeHR6ZaDLAwrVbSKbu9G 9f667HwhFmbRLm8VX9uDmvyf/zqtZmHNjYvp/fY92KZjtymHzURVyWrJJQ96 0d74nWVwAhMD/vH/friBhm6mxyefCTFRZO1u3ctSNNzUb+lyZyUTX4RWnDqo QcMT0/FsyVkGmvOfWp3mQMO6KTB52srAjes2zs5TPjKB+9VJG1cG8v2rjnxW 24/nGPtl24kx5OVz2cJjNogmNws/7AkfRc3Za4Nn3g9iiu9N88z3o2h17H6U adQgyo2dT5Z4QV0Pln7n0TaIW6UTrKvURrHrS9fZEdkhbFh2tyB7YgQ1XpnT 6uaHULfDaee7kyOY2vwmv249Hbfdz/n0aN8InvP/7JB9gI4N2pWZR/hHUEFJ X0NTj47/vnC5PqcN4/nd+w9bfKejsvPjn0V2w0gMHPYNNxvGaW/l/zyRjpIu J9MV3w3jVdu51z9j6Mhwl06uDB3GBddmBt9HOu4+nZPnWTuMU8rX+ndTz7Ua WB3HJzyCc9vv7jvwZwjfFX4xfdY4gvEi0WIlokPY7vNz8RTl+1QE7blKrAZw rdSw8hOxMYwoqODn0R/Anu6mvw4nxtC4RN376NkBNPiPdtbo1hg+CN70UE9g AMH5c+W6mDF0K9w30pjQjw0rCmeaDzLwTMCeIaM2Gsotkw6yAQZuWVG99FMu DWl3X4iuvMhAy4ABycgwGppHjwT1PWXggpkLl/9DGnb8Gbp/JZWB6YladKu5 Phz4c+b8Awkmpg8v28h5uhclHpkFP5Nnoo5JResZ3l7s0Fzy0OA8E+Pe20wY NfXg9gjtrbMPmPik2GG7zp0ebF1q8KIvgok1PV2SjW+6UbNOxPwT5Ss/6HC1 a2d3YauAzPUxqi7bM2XO1L7qQmaJnZHIARY2xve77FXuQnq2T8oFFRb+10ez cWjsxPRzW7I0LVnIh1+uLh/rwEGFvJrpThY6Wbq6agm0o7R6o9XbYRZix6Dd geY2FLMe5WBPsHCJgEczw7MN3/a/k9blY2Oymm3GhnVtuP6rKc1fjo2ewgY1 B/hb0bVooX2dChvr9lYypepbsG9w+veDS2w8FO1RLejWgleuOV1LNGRjxIqB mQTeFlz8q2bg5snGobpFv0juZjx0+Md1dhAbnZl9+0eKm5Ar91arWCwbC3my WQJ2TUgz0F0jk8vGHn+1I+ILjegTzO0d28/GNNNyS62pBlyuNXqzRITAs7m+ x5Pz63CXzSWlwUP/23eOesZI12EPb5NfrzSB9tatZ6xSa/Hpz9DrhmcJzGss k86JqkF6QEgY3iMQ9OuEYt9V4cVDYuY5jwjcJi0y58lVhflVwWc+mhF4ylRC 5bZ1JVavkUypfE3g0acu2eGPK3BTiaH6az8CZT57rGzSKMNG97bMCyEEdk/W XP9ZVorx5dw4G0nga108WXOyFI36jtjSKN/rkxuorS9RgqmLB4W2pRNoLXuz e3l0MQqZ9x6WzCHQ6o7rB//txehB6LiPFRN4zSCbz5KvCF8NXSt3qyBQvJEQ qXpbiNtNTNRW1hIoeZi5gXcKUWzFja1+LQR2am6zd2zIR/0VGn/GBglMPjhn 1eCcg0rOkUPCI9S+r9P1IMg5G4PNkssUGQTusKXv1XTOQuvTmzQFKF997KqP uqFTBjYxvJnVE9T9Sgd/Njimo2cmv5H+NIGX1zbb7nVMQ5ph6IT4LIFpl8tV Ptqn4oqHPr9vzBO4zGa/R8zbFPxLqFU/+UegdPbHJ9eXJONIsOzD2xwkCiwO +atwJmGtyqbmQ1wkPpY5XS6wmIA94w2cvUsoX+pTvKV0Pg75iPeTD3kon/jq W47ObAw+6Y2ObltK+YhJ15q2P1H4rTx9wy7q3IvjIp6dnI7AxxudT6mtIJEh Ffnz00QYvknbI6LFS/maCpHzYX3BeGNJdakMH4kHP3wa5+jyR7XJ8c3/KH5m XvxbucUb/RbP745YSeIR8yOx5vUe2CJb1Ld3FXV97d+Q7R7vcUjD/KITxedX Jb886miPIk555uUUd0XqMkwmXqBl/aFzdIoxbszU1EgXT2X6NQxQLJ63ZYW1 9R3QM51bgRQv2T/tUHfFEvg7vKYtKS7kdpTpz3QA1v2uzwIUg2iEa1nxB4iQ tqK/p+KZyPX/pGzoCZXLdJkDVLxaYwZf1xv7QLR4UMxmivdN72mtMQuAdhfv zRLUegW17mUZvAyB1f7tp3dSerjpPnf4pRAOkdr7RSaWUT5GrEMh8FQkSCp5 VkRQesrMTt+TOhMNO86p7DtM6R0VtrIxRSUWRMpylMOofCxnvL6x6Vw8NF4r btxM5a96fd8pD40k8K6+cmYPlV/7oqcXwi4kw6sL0fYrqfzPjGhPlcelgLV2 3wvrPwS2BLM3vEr4BvfuvzvMSdVPgZiXivyXNMg0Nam+T9WXQorVM/qXdCiL /hFWwyLwt0v/m6nETNglXz1aS/mU5SEH5LWTsuDt2/kdScMEahRc/BqRlA3h Fx6Y8lJzolaqjdlI0ncw1O/2ce4mcJ9aWERfUi4Ecy8UDXYQ+HihXfl7Uh4o /9t0WraRii+tJnJdUgE0pPJEHa4j0CDvgMLHRITbz5yE+Sgf9OGbBc/UlUIY T7aL1Ckk0OJZ2L/NV4pg+6tlN4yTCGyN6Kh/o1UCxp2NPJOxBHa5maxT7S6B RxVnb2pFEEjUp738fb8UDl+lq4X4EHhx5YtFHssyqLHI1H1sS61HY6tiT3AF BLvFVBa+IHCn++6B6n2V8FZ2hQpJ+apDAjYXA5Ir4Uv5cGyXPoGJN9czfxZW QXdZ8yeWEqXPaMHn9v4acA6TWiogT8V/J2ZdkVEt3Pz+bVGA8l1N6us2Oo/X wrfS2O/Reyh9px/xxXDUQ7C60AZeTgIFVwilfVzdABuNsm/R09n4/NMORUmR JlhyM3g0N4GN+eqdggNGTXD63elVJmFsrN6RtsY2sQnkdftf3n/PxuF1y349 lmqGSIOkNZG32CgaFJq5X64FLMb1yh5xsrHXksHTp9IGioH89TzTLFyvY204 79wGR6tNq21GWaj0cF/3QmUbPJlVmuf8wUJhy3+lX9TaweDpyYFHASw0XuvL 90W9AxISnuo0i7Pw18m3LZNqXZDLHy76YTsLzTbvi1n2rgsEU8JS9lK+bC5r gjlX3gWTbpcvTv9i4qTGgWyH0z9BUkw0eFMGE3clnw3il+mGZfv3G1tIM/Gp 4oB33fZeaPQP55ARYaLTQ86fFdq90L1HcrpzIxMDXf0VQrx64S7/RtPiaQbO VNb+18vXB8sGbCpFvzEwuCbnftRMHySW2/LdE2bglaMK0s50Gmjbn+FVFWAg 8Ue19ApXP2hIF0rzczKwf2f9f2t29MNdlpfP2e4xvHH0yZyqdj8YCW5Juesx hr4yZ+dLq/rhQpryqnu/R3HlUEBCbdwAJPks33Y7cQRbY663qV4dgrFUL5tr fiN4b0uVS7DJEIj35UjKOozg70tJgT1OQ5CcZzebqzuC13q/vNuRNQSljIW/ RStG8Gnjse1xG+mgKHFkalh/GLPnG3flNNLhSJrG1Cf1YXwNZmE5o3TY9O39 +F7pYVw6uV0kapEO2bdmNQVWDmOl9aHZ4xLDcMjhP2fuDDq1T/vaXHIehnP/ apwuLqGjZhyXhar0CFz5kj5bxhpCmwqfZTT1EfjRoLdNrG0IK/oF796+MwIL G1b/yI4bwtbwt4e2uY0Au61zikNjCD3pggIW/SPQrJjRc95zEPls2viyHUfh +mrlTJc1A3iw5E7gUO4Y4P6tD1qm+zHGPbabs2EMlmzf77j6Zz/2dSmocw6N we3Yay6a0f3IfJ9vGMPHANP95F1O2X7sKAk2ddZhwIDK5eYLN2j4iC9N24tk QPj6Pwsep2jo/4rDu4aTCVYRM19KhWmYZj/eOijABGqEODDzsw+93O/vzJJm QlXZgdfGc724wu7I7LAtEwTDuAV+He3Bht/XNW9ws8DC9a9v5Fw3qkxqcASv Z0H3kusy8sXdaCW15lveXha0MI/VCl7oRvfuwo7AMyxQU59QiDf8iW8Nf3q1 v2WBpKFZ62avTrRSZajL/GXBvvOnh07odKKoZs8x02VsaMX7XKpCnbjPPPXk uw1sOO3ZdW97XAe+7fz04qoUGwLub3bI+96OYb35B+4ZsiGBFlnC392KbMu4 zafr2HB8SFm2L7IVKyxWzft3sOHZQ+PF4EetOMBJd28ZZEPJPUFFxmwLZsbO fBn/ywaOyS5a8eYWrNoQll29lwAzq8askEtNaD1htXT8GQGX3l9pttzchC+u rxV8+oqALYZfFc72NaJFYum9RmcCCoQkinIeN+IQ2fFQLoAA7t4tPlzODZjb +fpjdD4BuweuPfYzq8PfVSEPu/4RILX2m27pv1rsl9zx0HIpCTkPb2V1udZi sdDxI7OrSDim67uzMqIGlxr58YVvJ2HkvO6X5MYqrNjvKG8vQ8Ig7z1S5kYV Nl0zJA8BCavpCs+TRysxuVLyVIEyCS48e7/eX6zAU8IjSa+1SNjDuBTBcaAc WRVrRL0fkhBPTyhZyCzDDpMMDc2nFJeZTjBOlaForz179DkJNl6GP32uleL5 bYuuxW9I+Gdo/E7hbTFqHDxev9SbhOL/4srKVhbjKvfzV2r8SagWlm4C3yJ8 OJMobRpCgpzKs9xViYWoNhzKoR9Lwi7Rh6VHE/KxUNVYtSGLBHrqxdd7S/JQ Jfntsw+51PW/6UIc3blo+ObX+v1IQveodYDtqu94UyUijr+cBNMHxwt27stB +yZO3ytVJNTN7LzyTSEbh9m/SNtaEsY4bY0in2RilElIx/MmEq6ZrpTgdsnA zk277ym3kqDtw/vrSlg6avzAS3/aSUi7s3axvuEbOgTknefqIaHrtZj7n9FU dBdwvazbR4I6Z1OCAGcqrrupme3TT8KNZ/f4tO58Rb+jb1zT6ST4KR9cf9Yz Ebc2cv/2GSEhX7lZUbQ4AZk6XzN1x0iYTVzR+ns8Dism5Wu4mCTsPXpjffqu WCSrHA9/YJEQREid1r8UjXl85sw/bBLW7aoIX3wTiRcZS6aVSRKO7JJ74Z4S jk4+6povflH63F7HI14Yiv8UXvx2GSchJOOAgOCOINRajSzbCRJ8ci4Hzdv6 obOYleSVSYoXCOGabi+M+spftHqKBJk/Msfen/BAo7T54ASK7XyCQ14dfY/y Z5rLRadJMN59Z6J53B7P3pU78Y5iBX/xvuM3LfH7MmK2huL6yLTXD1Lv4wlB 5BmneGqp9qFkAw14bf9Zd4biH9smXt04bAYbVxvM91P8lOSUZ+m+AUMHldEk ih9X02+GhDhDcbjODj2KazbeFlLs/wjZGzrDWVQ806pKMsNrP0OAg8DTWxTX 14QI70jzgVUuj13TqfVkqm/UUr0cAL+S9caZ1Hq1lHRkbk0Hwzl702geiufd XsRL1oSBrZ1GLCelz79cgdUxgREQsifuTx+l5+aj651XP46C8R4N3zCCBO4r DxsfyMdA0K6dzkqU/p4zI/FpK+PA4uaGykoqXw902X82JH0B8XdfTlmNkvDE VG9Y3DYJ7t6NsIkZJuEiT97l/RqUD1z/YFXGEKX3XZ+GZy9SweHY5DFLGtXP odestW5+gzUjmQ0Heyl9fV/f2KOSBtMzyhXlP6nn9YFC0IYMYMQk1Ae3kWDI jvtzeiEDPE6KDHY3k/DWZNPNrqFM0JLKv/6vgYRvp4/GdKRlQ2fiI+vRaio/ 7V6qnJfywNNnolAnn4SrxzQTM8/nw7IbrxjXc6h67a6a/E+lALr5Dl6UzSAh 4M5n83DBQrh8YqzHLZGE9i83Uthri4H/QvtDH6p/DRq+m3V/LAZ0zuu286L6 Wc6/O5evBN5FxcarfaL6Q471T42nFDyZRw2eOZBwUOdtT8ifMlhokWWJGpMg j+/llz0rh3jhD1mLBiQkVywQer/K4duQDHf6bSrfJ6rD6kcrgP5+qXTGfyRY J997ih1V0DvfELKV2s8qh173WqTXwa7OsvwXswRsCJAveHuoHixX3b0lOkFA nZii8LOEenhwKZOeNUaAMz2mfnnYD2i/4ZL/tIOAd4um6b9LG0DcfPSRWjoB N5xZ/TspH2dtEPM96j4BcvwjtwtHmyDq990LMroEcK5tDLsg3AyLZhLnEy4S sOvDk1fyIc3w61ZdkNgJApIErAzOfWqBgscxqT6rCVgh7iS6YNwGXjmjV48k s8H/wecIh+g20Lkk1e4SyQZ91oYfs91tkJAyF17kywbteLtX3863g/qB6BM9 r9lwZFafcU60A1wcsxzyNdkwknD2BNHTCSUyaizxERYIuk0vV1vfBWs2NXjk dLJg5zZVSw/KB6aw3XccqGXBrlotq4HMLlDqSxXKT2GBXEGIvfPHn3DCKrzn 00sWbE968SFVtgc85y8pcy1hQfpzN3aySQ+UGt9JbJlkwucXMRU+kT3waKd8 2vshJuhe2LhFcFUv7NetaowtY8J4rsr7pX29IJnk+c3fiQkSK08G8AMNLPR4 bzxZwoSLIjXZc839ELs+7NvpsTGgPeXoGyT6Yee47eTR1jFo0zut9X3FACTY nNu2omgMRN1CfKRgACq3bHh6zW8MOGRsm5XjByBEstHoo/IYhGb6jAxbDsKB ZPffFgGj0BezNSPy8yBYbza44+kwCqeSImLUkwbh+2Gl5e4mo6DQ+fnhHdog 3E7ZpXfs9CiouvfF+CsPwfXfZyLFR0egt8/QZPNKOtxKmdnbcnAEhp5q7HPe SwcR6VX8EptG4I+FekufPB2YcezEh4vD4FC+zFnTmA7cXA2GXj+GoVeP10Kw jg7ib4qDokyGoatWmveuyzCUPTD3rY+lw5D2q7AA1gh8Dr97mWfZEJSs+7Iy nHMU5Ke8o6JZg/BaPEzg48ZRMDX0ZB1sGoQnO6XNtimOgv8K7Zb5oEFYHcMz s+gxCvftEgTfSQ2CU8BJjxbJMSjnjO+2uToADzPDO46dGYNt/j6C3+UGoNPk Van1tTHIS3ITGRAagB3+v1Zn2I5B2Q8n/snhfmgg5bZ0VY7Br/dGjtte9MPv iVVJzZTvu6kYvDvCnQa+Oo/WmD5iwOttW+8FmNOgtspUdtyGAQ8jxfVfX6VR uhc88A9lgNkvXv4122lQcO3yFqdBBnxMN/4Uqt4HafaLW7LvMyFuaSNnDVVH h7iLfxVqseCEkG9Akn8nhAw5lnjfYsHPjquRdrc6oSxr62nNxyx4dOOMywnh Tti9unHKyJEFmRz//dBP6QC+vSs2qWWy4N4Oo6xXZe1wacWqhaB1bOB+bugt wWwF4/XC2ZGCbFh5j3fKKrkVJv9dnfkgyoa9IREDqeatkGH5pWSpAhvWJfro 98y1QLvYqxRvyvflD8i8l+JrAZmcXbgugw0zHHNC3PuaQFxgyQ65AjZEhBhv XTbWCKr9H3iUKtigwH/S5s+XRtghzjrwl/KFL5kVj8OlGuF1zd/r07NssDsU 3b1TvgF8ji+/L7KEgLHvH6r3L/yAceRwluMjQHTS13vK7gfsks7rXbKNgOD7 Af/tfV8P7UtmrXfJEnDzp+Nl3qBayBD9NnBdkYDcp/WbZnbUwqyT7L9nZwkQ Zuz5VBlZA2qeGcLnrxBwuzclQOBLNfhHLFu0fULtY/16R29nV4Lha7fm3OfU viNaFW16ohJ8Rjt5uqyp93+SbzQqqAADVbZuFuU7g3Ku660pLYe1ncuLp4IJ oOn8enGmvhR27ttnExVJwLeq+JXzyqXwdAc9/mA8AYFBSfkB+SWw4mzysaY0 Apaq3lzpnlgMa4p3vGZmE3BAaeDPyJ5iUBufX9dH+VY3S70AscAiuOXUNXm5 goB/mwvCH78rhIFTtgfbawjoKGu48oSjEBKw8eORBgL22ukW5BEFUN1MhlhR +/IkzWnP8uo88JkKUbjfTcC4ZdzGl1m5YKhUMyhGI6B8w/fpsqjv0KL8btep EQK0Vdm5HK+zQUb4XOJnBgFMrSrlX4+yoLplYGchm4CnqjycJdqZYH9VLDlm koBqa/v/Nh1Oh/zQS/m3fxPQclfuU6BQGrjT1UKmZgiYeXNMeTnfN0g51lYa v0DA+Z1VrYoVybBt5ChnzSIBn96yOYJDk+DUhn8LZZyUrxFZkd1i8QVGFbWy ApaQsK0yLZxxIR4yXYPEzvGQsLin/F6/SCy4l3te+t/3dq9/XY7LXYwCe7dj B44sp87F/C8CNu0R8EejIdNkBQnLfp7VFE4Og7vX/xL2vCSscYhZNF8VDAa/ PZrM+EhgjCuEWeb5gdqd8lsn/ve9HUOx/vYjLxgdWuXdQ3HiQn3nwa3uwNMi bqpDzQX1Gi/3NXk4w4pA8cmvFH/5b+mB/3ptYV/h/a29FMcpR7p9lzKCwZHX w8MUM0NU34R908LN7YbXqiiOqWCWiUw8R1Xza8aOFDt4LD1aHmiPt4qaRbdR nLj+n/5thQ/IGkh0daXerzgxTH/01BO/rv33uZmK96fMlVH3Ih8M8ZdQ+U2t 530j/6j/ukA83ciKmKDWuzVinbfd3VB0XyOTWEnp4TxYe2FXVzhujbl67+Uy EqT7N3Q/4orC7OquOk5Kv6DOxopg8Rj0+BzOvMdN+cCK4EfpWnHoPtBUGM5F gv/+8zuTrBLw3JX+i9kcVHy76AqOEYmoctg1NI6ao+JtMnbKVX/FvMutKWbz BKixoz4NvUxBlB0+4PWHAJFTR4yPhX3D+LpD4cwpAr5rlwnnpaXh2Y17mNsp X2FscD1cvCIdaRIKG1exqLmvbZNfDjsTV9jLLakdJeBYKteTdo5sVNZ513OP TvWLjVVhu0AOZi6deLa3l5oLFSc/WMnm4gXJiGm3LqreueJV2mXzcMhGVb+t jZoD/xst3iCXj33fh9dx/yDg8qvR3CNyiONBzsHNVH/5P+WgPwwqwqE4u8PH cghQGrylvXZ7MTamjjCeUz5mn2TRg6jAYpweOzXslUDAdGCc4seAElzgXzl9 zpuATvX/pvV9y/DnjjKP6E8ElD47+PLmxnL84jjjS3tHwNCXNl0l73KUy6lb Nm1L9ddnafFSzwrc7pzt4XePgJOGFQc+f6DmyEJ2T/N+aj/atSJq3KoO2++8 XbOfmoMTufZpH5upw1n6rtt3thNwiCtUQOd5Pc4d1nM1XUm9L2TIXeHJD8zJ d34jwKTmcKsd4TkpDXiXI/KUWQQbSvNfebqENqHIN7/8Rj82iBXUT/H1NKFx xOyJdZ+oOb9FVNV6azPu3l77+rg1G7KVrIu2ezfjvpQVrFVabLjGcYHr3rsW fPPScf+yWRZoCauq1Rq3YQfTXyCHYIHVd9rvorg2zEn1OKE5yAI7pVHPsME2 jOA19thN+abaQVbyJp12vKddrfo8iAWJPw7sHTndgeiouNAkzQL/omVhHWu7 kEt31aMicRaEjp86fvp8F/402H/aS5DyVd92iXg4dGFMy1PrES7qfPvdLNP7 uwvflTWpqdQyobyuhvtQ108MP/Pl3B8dJmyT+MFrHdiDq3u/Nh07T/mqkxa3 djb3IFeeHf91eSaIbNUMj+XtxQmDk3P/CTHhlz1ro65lL8qOBC7y9zPA0l16 /sKVPnRS0j+ep8+AqNwnY+H2NNQWIXY6XRwD9Yj3An9EB/BvT5fLzpNj0Hlt q8/wmQFMV1u4Eyo2Bnqy1TGFtweQZzOdocY1Bg7SXH+P+A0gvfRMjt63UTho bLth/dJB5EoL3eC8ahS6Klcph/UM4h1zP3OLmRH4WOvxTXxmEGUfyp7SHBwB KYGv7cHrhpCx5nxScvYI/L3e2n7y7BDana3WVr4zArf5E8P1k4dQV+BzfEfK MOwI4Ly105qOjmGmVyBgGBreq1wV86Kj9JIjrz7aD0PCSealLUl0dL23tWb4 CuW7pk2JpF46ytTLTr/9S4f4xzLsGMVh7P/Bm+5E+bX1IfKLRYvDmOR+rCn6 2yAI60rRJo1G8XUxB7k6cBB01+wTkHs1im5CEkcN7QeBS2T2l6HnKNLsfkfS /xuExNIvhlbfRzF26t1qwakBuA9Hbr9cMYZVM1IJblIDEOvr0lAVMYaaW/Om pjcPAG+QZsnbjDF8Np+w8QLHAFhsFL22u3IMzzGjz7fU90NbgsGeDewxnFuY vSfxqB8Wrp4LrjjGQMuJc55S4TQw3DA3plXMwA/qo9VpzjTYHStQb9LMQH3J f29FTWjAaTlw7+kQAxkz17vG5Gjwb1uR2d6lTMxj3+QKie2DgnCZj5qqTMxe f+2H+dJe6FsevTa0gokSp5V2vf/WBSdUNUU7U1lYqRG8dcXLLngVpa6VXcjC U52mPSYnu+DJhleFL36w0NggOXeiohP6zQSPeLBY+HxNftbAzw44kGs1LyfM xoHzE7sDFtvAHxeYV93Z2Ktg8zu1pA3+02ed3hvMRs+ZIfMM5zaQE3u2viGe jRIP7G+94W+DOb3Iv8XFbJR6+MzvgFArTO1X8lo/ycbRevc1AjLNMJVYmHVD g8AX1fzZnHNNwObRjVqlTaB2/a7yvvwmWM08fC/wDoFVwo84Hik1gQX/NZmL FgQKXTx4oVSjERqEqo4KhRL4X2yD29E1jWC9iHm5cQSOS1lz+zQ1gMX6kobj 3whcF3zsjcS1BpAtLrYuKyUwo6mdZYT1YHPm87zSKIGOkvjioVI9FD2d4Kr7 RWBZy4cllyrqYIPcpatH/hLY8juf0VhfCzP7meW+K0iUsxw5k9xdDX/vBvGi KIl5r3K2yU2VQyd+0LO7TWLA8oM6Qq/L4frfwvumBiTa1NXPj68oB/GPP1pO PyaRdce5+8GOMuiK29v8zoLEXv8GDDlXAjN7LLtjP5DYUho1vqylGFJso0Ij PEis9V+jdfdmMfzt04975UPiHRkbjgmzIjgZImHTFUpdv/bafPw4AlF5t25n KonTYb6rZ9UKoKSsVU84g3r+4lEX1s18sFV4sokvh8Qt32ObPZxy4eS2EC6r QhLHBa8tUQn4DpxnUiSWlJKo7n26bjgpB0wMBl8aV5BYLOk89qslC/4tRt2n 15Go9/ySn+5oJrCtjbgmG0h8x3cyIGMuAyZ+fc/obybx5oNwTbnd6eBaYXLt TieJxDktPYNjaSBUjaemfpL4pdjX3EH1G8z9s5Iz7CUxpbDL3N8kBZaZ8178 NUCiQ+Aakz1LkoHzrqPRUjqJBid1ny6IJsH7vizXhWEqXkVZ1WLNL8Afd/Bb 6yiJ7Wu2XzB/Fg/8j916PzJI7GhT7l0bEAsnKz+uFmOR+C2kVjMUoyFciftU FJtEedfgv9vpkbBao+0ZB0nd//e19AfeCCiS4Y4/+YtEscLN+sShMNitENWt O06iZnJX8LuEIGh8Prhad4LE5Xvqv+2a9oPqdh44MUniYFBiaix4Q5OsweN5 iq1NmWpCrh6wqPHCJ2SKxOOdGTfWxL+n5sGCvF3/+14uQmdbw0kH6A7s7XWk eOMu5g2uaEt4bvthvppij/cGA5FB98H3lveGcYo1fZco+O+6iElHesT+9/1c H3ExalufGQqU3JSlUWwSkhDT3/UG1yTvPxNPsX7WaWUxFRece/pY7T+KJYV/ aNxK/YSfrt9W76XieTnPKQkfP+MrnxtqahQnrUl2K1TyRTGxxjO+VPwm+9/z S/0NQI9xBfkyar1z+3h5Pn4NQYeEU1ItlB621tk3GVLh+JPpureU0ivQY0TJ bmUkbj4wuNGb0jNF1kaHdyQKVxaLrThLkOgrjyoORTHYMnx5vpPKB2/79zPK LxJQWzZqLGKMROn+mz9Onk3E1tjGAwMjJF5xXRq2e/NXyle+jF9C5Vtxvd6/ 1u4U/Kfpe5ndT+L7J5b/9pWlIlRNOWb0kdhkX+79KOkbJsX5/b7VQ2L388n5 Wtt0fBptFKTbQeK9dyucRu9nYDtzX2tiK4nhU9mbpzUy8c8vtcu0JqpeHeg1 vYLZ+D2yUYKoJbFS8vXLgbxc3NVU6xqNJL69o3HzWVQeSmgKHVmRR+LFrPb9 E+/zUf3GxqMXsql+WLGZ8fU64rLoFLW3KSQKJ2mbuFkXoVDfya2OVH8ev2w7 PU8UYbpAb9tcAIkfhBY6b90pRiuicMkVqp850ruN/6mW4AOrzNyvVP+HBVuH eG8oQwme30s5XpKYdsab8HEpQ0Pd+FhXMxKrnnz55zJXhgHOka1/qP3E/Wvj KoX+ctx788OYpT6J7LGO+IEvlRiS3WUgeI7E1jTnvNtCVUgrbhvOO01izX+V Y7XuVbhnn9dGkCcxtDxOweR5Neb+OOzHPEhiY4TWs5qTtfhKYiaRvo6q798z /1KSa9FxxY0jgXwkXpOLnrbbVYcTZg4eR7hJXD3eXTvEXY8eD0oYK6cJPLXk VkRU9Q9kyjon3Wkl0LdHTYIW14i6n55GhLoTGJB10bCb3og168u+FDgRaHO1 8GzV7iaMGn/fmWtD8R/apmdBTfjfTsOyiw8IvKKz99uyT5TPS1jbRT9JYEld /rmpp614pZlUKBtg43b5V0RfYiv6trMY1W1s5GmJDcgebcV1J9quJFezMa6v frvk7TZ047b/vP7b/77bmT8npdmOVvPrBy+9ZmNYTl3/2X2duG1mbjhcgI2/ Shs5Rm93otmFTc1+PGwMFm+6bxrYib9FPWWf/GHhpVVxK2FNF269ujP+excL 2xRk1+FMF24Iefq2LpSFP66dTd1W1o0CRqaryD0srBD05K3YS0NevtUiLuuZ aNYgcMBXgYYiokuXFixhosZu/hkdbRpKGN2X7JxgoN3Oe8JZ72nopGoaig0M LGgnWLXjNLz3wPC55nsGyh7Rr9HM7ceDvx0b3syNIWu+cN3Jln68VVIotW5s DPcc3qy9nd2Py5eernnXNoaOEvpPk4QGsGPjtuH9qWPYp5/Wt9FuAKdCrlud vD+Gw5eUh4nTg3i3KtAsqnIUo/wkNWnXB7Ew02cqLH0UHbsmFwvNBvG3l1+W Q9goll9QbL4QMYi9a7+rcL0cxeiLTdJhHENI30KzbBceRXmxi8OTOUMoeqRb YNZmBD8dy+SMERrGN4Kr6VFbhnEwBpZvPT6Mk2eXhRdyDOMi79Y7LzSG0WzT 9M7iEToqj6s6jFgPY/14d/uLDDoKFrLSYtuHUUfad3PCBTqa2OsY2bmOoLr2 9JaLr4fw6lHeWw/DRvClg+1Uy70hhGMWr2QzR5DnsfClU2pD6He2JvVd/whq LPjxNK4fwoDcJEni+CiOtaV5/YgbxK+nx2bju0fx+LFNXndrB1CZ8Iun/xrF 8+J2biYpA+j9fIchDw+lm/VW9h2vARSyqHD9dWAMX4iResv1BtD4kUmvqfUY jsaEWZ5j9KO4aq0utwADk2lK44Vc/WgfeKrn/X4mGhtfqehW7cWmLZHdBSeY WLF0O3N0ZS/K1emLN59nYkNZvndjQw8GNhorhT5i4rnW7x9ltXuwUenV8+J4 Jj6e9XN6dL8bryX1fRHcyUL3y7FLvCy7sGOmfpXOQRbSkne1uJzowmvNd7c+ k6d8nsmRtzcXOlGAeNmgqs1ChoeRV9KbTjT+8h/Pw48sfHmjzWjAsQMP7eNo fzHFwgRtY9Vh1zYs1Vn7JZyDjWcSFOt4z7ehwIJDWsJKqg90ZPPW87Wh9lIm 77W9bHw5Yc3V5dqK4VYVbzZqUT7Q8tOtw9T8pc/lFSl5g41H9d7ddVVtwV39 TC3RB2yMVlwrXr2sBVdcN1yWYstGk1CNg1xOzSi9b2O0UCwb22jXjfTsmtCg 8NTyPalsJOrN2mahCU9kbb7JncvG2nN3jOz/NeJot6j/jXo2qi+YHrts3Yin zr268YDylfsemfTNmzcgl3jio4bj/1fDmYZTtX8P3FhkSHULqWu4GaIrN5EG rVApolJyUH4kuUIRuehIaBAZqsOV4sh0JdeQjMmSXEfmIUNCnJP52DuOIRH/ 3Yv/y8+zX+y91ndYn/U869kEPjVV9D/3rh4d16hISO8n8NZlqbtyxvXISTtm sv8Q5Xlbw4XKauvwfr6Si+YpAqWPuZxOb6nF/mH9pUfuBPKmXv+p2VeD9TPr Dfq8CLSefC4r6VCD2VJJLBF/AnM9DA5/4LDwtNiNv5ZuE1gspyG3YbQa61ac OeX6lLqn9rHmA6aq8MIjy5TCZwQO6JXUM72rcI8lY3wgnUBtY9TKmn2HGbED hl25BD7Y6VVy53slrnXwN0gpILBdRGPQkl6JSQbO0ualBC7rieauWXqLvokR 6kbvCDxq8O+Ok/xvUZCcpP2cf1u09ZtqD67AfYZ8BkV1BB7M83E4KlSB0sdf KmW2EVgp+LRsUaIcWW2/+oqxCTxTTE+1ky7FP+9vKLcYJLC1dPs6D9kSnKYd ue9HeXGBRIK6s1wxPjOIzXIiCAy8akJfJV+I5d4d0+qTBH42MawrVihAQ+nH eU08Ap8k2nNPKL1Czfv6fxV9I9BhWq7ZUPklBu2Y+uv7dwIfBj3KSFTJww/r m3o2/SDQbC/nxohqLtI7Dib/ukxgOC28zNAiGzcf/V61zEdi/xWlVMbpLNx1 p96gQoDEdJZbXc2ZTEz61rjenqo7NQfoRwdoGSjqarr/szBVpzSidfpt0jHq l8pi/ZUk0j6u+Yd1NhXNU0eDr4uQGKf2oOCxXTJ+Nc2Jj6M8vkzhrS/NPgmP v9ddYqwicW5qREq86ilKXul+4UHVOVennfNHWHGou00jWUOc8h5D727XWgaO P/z6+T+Km2bZX3wbonGpV+0CSFBeVfzmwUjSPUyZEdGMo7gsudq9Kj0I5b0W 9zVTLGC48oactRdeS0mLHqZYaq2ja+MWU1x7r1etj2KjIf3hDnkXYPTkC7+i WPGRR7DjLTq4iF9RdaE4a2p3o92+OxC/937kD+r9OR+TA711IyEYcK8nxTc/ a+/RkXkEEU+ntldR3+9W3aW8af3foDjMYXCo+OhMnZI55yfwv6L5kB4q/p64 37zzSpnQ36S3nE3l54Lqar7kFckQ8OekiC2VP60QH8H27alQqogp/VR+XUPP yJK0dGDMhrYClX+jlUTsRFAGlG4LivOl1kdENq+lITMTNhopz4dR64dHzeUj 2rJgqk//m88SgceK8tvVFrNBp6jv8b5F6vxIhykff5gLybU3Ok7PEWjcGzJ0 u/Ql4KLc9X+mCXRbrjQKbMyHL1sC2tuo/cbjXdG0Z7+C9daLb0vGCdQQ49m2 iRZB7Zi4vRe1Xy9W7Jo7v7kYBPSr61ZQ+1k9sL75g1YJDH4yVn3dS+BQlOqU tdVraNh+SrnnI4ErUlUYly6VgadwhEQn5SmxJ7lqtIA38M5vb5lNA3WezaTY VckI9g37H3FqCNSUdshLsqkA0fyIa4d/9pFOXqxaTgVcNjO7GU+dz0K74tbP M2+BHs5+TU+jvGXOk29BpgpUj7d+66D61Nxh/dDbz6oAvD5Hi8UTuCl2KW12 63+Q5BO2LBhJoJwDZ0XYnmpYx1D8TdubQLaEoJKjTQ1MiqwMcaDuo2viU3JS 7BqwOcJkXrpI4AsLLd9El/fgw+w9+LNvfsgbenvWtxYSag1rYnYTeJ4MizJj 1IOIVhjjyR8E3v+WH8Xb2AAJ4zbR9K0EemiINVx71gDLbAHLZhkCTUJueYpn N4KjAKu9YmYCZw6cPFJ8vhmeNf1I/ZAxgYfeDxob+bTCm4Xl6IPMCSw4p/aV zG+FDZHPaTExE6jTcTw5dLIVrI/HlX4MmkCXX2WUAtza4OusWzRJm8D8beZ3 XR0+gPKU1Sk7/gn8kbx/g4pxB2zN9K/nzHDRXiHe/lpIBwwKrN9pOsZFpuij 11nYAXV1h2UrWrloeXjpeeuuTtjlkWV+MJmL/E5RzGmVLlitnHOTtZeLOvdF VWz5uiF/dnTSm6qHkjn+DyX3dsNi7ViEsCLF4av3pV/rBh+7G/HNwlz0+3bZ KmisG7a5XrGVahzHM7mSmv2tn6DLSf/xUetxZGLMF/HEXvgxLX7T0HYMTQRU ZI9E9sNKgzeK7SZjWLPpZsZvz/uh7Vhtk/meMXTVeelFvOsHxLvZczJjeHP/ KtrJ+X44IKa7Sql9FM3d0mOPOg6AlVOLHHFkFJN+qVUntNmQUXc1bVF3FO30 HrzNM2ODUch8KW/LKKZ4Foo4OrPBoWAr9wnfKJJR0Uci49mw5niLXGfhCG5Q V5sT4uOANy0kVFJ+BH/n7vjHjsUBSV0j/zwxytParA9NfeZA5Pfo0P3fhnFh UErx6jcOnNn0wV66ZRh7XKd36W79AoxttPrqoGGMtGL4Ntz7AgrPz6/T/jyE 6V16hsrGg5DNHdSYCxvEja+Cdw/nDQEn9vfoHV6DKFX3/UrB+yEw0JBZQbMd RIUdV067DAzB05gD/zpoDKK+zrbqIKlh+C3+j1ivWsoP6xT/veo+DAo8BcgR +oK0MCvBA0ojENbCC3wyzsGLxzYI2emNwFVLfa5XKwdlXgiBvfkIiN92bxhl cjBUJ1Rsjf8IOGQPnZ3YzcGhmgGmYvMIDP5H8DwusdHS1mon12cUdm+6/HT7 CTaO7VrXaRQ+Cl2mtXd6dNi4WV7U6QZzFMZGC9L4+dl4vWWE94Q1CiPhTzLp sQO4cNim3GfDGOR4Oj2zKO/HszL/uxWfPQaqY+trq4T6MFP+hOavNeNQslY3 V4byNNfX5zfEdI4DcYqv/PSTXoyU96v6OjQOiT6Nm+/80Yuy8XoGZ4S54GxZ dLvtbA/uFA/8s+sAF9QC+xwO5XQj/2pHhZyXXHCstkrQpjxuSV+mza2CCxVX LdQljLrRfVXnA8lGLriONC8Hd3zEi78HiyyNcCF5nbtQ4GIXyoWm5IdvngCC FeHPOdiJRbmPN1sHTYDCyeGxBIlOdEvteWMRMQHy7aJvDnd04FXGj/fbH0/A wkVV4wvOHei80oifkTsBZ0Wua30IbcfrWjsnBfsmoFqrm8ytacPC+EoLf20C ZtUftDtHt6He38/j0/UJCPM/uE6K1obl8cdYBcYEbBn794TOcCtKvLDKpdsS wBj3/9Ip1IpWnpWTL4II8I7d+0+afjOaXakWCKshwMj03LOqhSaM8chJ6mwh gLfATFCgN+FglPllvk8EuLuuvhtMb0R+ubc+HC4BnkvnKhau12NxIPcMIUlC B6tfIG6hDncrLIT/Ik0C4Xu7ZeP1OnQOZ+SulychPqxwud2vFpd5fC8yNEl4 LpwuquVTg+Lb3ydKHSPBVHdCRnKGhSof9tyTOEVCuJjS3Q4vFjLtxbcNWpPg XXPOSc2zGiNy+oK2OJOw38PBvvdSFQYOu7DYgST4XSSYcqPvkPZSrOHVbRJ4 JqKCR5zf4VBM5VmHcBLs1LzWujtWopn3kLBJLAnnG0ocZmwq0DptfJaWScKJ KpcYxzxEw0TlqqVs6rkmXb4iqxxTCyZmbuSTYHZKT1ItpQwPRM77SJaRUPT6 kKlO4mucv0sv31xBgkvQ3smtj0tx5w8x25VVJGB3nHJDZDEm9JjcdqkjgW/P rrCAe0U4UmImzm6k4vfWEpK9VYghw4KfdraSEF36Y+AXv1fITHlh5NJFQpSU +sa/vPIx4b1gl8knEuR6LkrVuL9EbfuejBU/55HUInp3n89FdxPLWXEOCRdj gyRLirORdvnyZatBEhyj9m3lZGWh29/zsvRhErIuHerlJWUif7bInP8oCexr xxa5jAz8vapJ8PQ4CdvN31g1h6bjmFTa/pUTVLyyVRVMeipmjfOlMwgSCist RM55JKNRTYDeIknCRz2VZdELSbhNu2taf5KEBtu/x0/kPEXFRuKj9RQJFeWm ft6xcShjVjl0nEfCYMUX4+AABj7yurZRYZoEieqEuYAL0Wi91sy7luJ3Yt9P dMSGoqtwLs98hoQ/bMqm4y/cxOs7VON+zp+ZSkxrJ1/wwKS75xyGKJ7nmFtI TbLL/v//cf8HkxT4hw== "]]}}, {{}, {}, {RGBColor[1, 1, 0], AbsoluteThickness[2], Opacity[0.8], LineBox[CompressedData[" 1:eJwkmnc8V//7/4W0NDSMkhWSREmy6qrIqFQq0VJKomhQNFAyGmZGvFPIFrL3 uOy9984er3GOhr2+5/P7vf7xut/O7fV0jcc1nrfbEb796MJdVhYWlj52Fpb/ /f1/H8/i7P//ZQI2P/EurOYxBw73HvrEMgmdypcnCnlsYeD1utYiit/HB7aU NDgB8a828TnFgku9twJ43KCab4vdRoqXvjzK/yntBS4lYUfeL5GQYstn5NDg C+fZg8mBRRLcv2wX1Hr6HzjyPvURpJi/aOrpIvc3eC4UJXV0gYSQTMd/tdeD odmwJePoPAmeFUeXt0iHwPSjH4rCcyQU0oW+nlkOhVf76PHDMyTsvfTO1bo+ HCKEH/K7TpPA4cPi5f09EmQfLLzeOkWCypjY4yCLaJi79KHT7h8J3Wtj0uy3 xsFbrTMvZydIsDz695vu8E/YR7YVriFJkDI+Ib32WgLkFGWsXmCQkHjrx8+I vUlwVUbM23mMikfpEY+BLclw2ZCjS2CEhMtgcJVrIRk2zIyK/zdIglW1tMzJ 6lR4/0Gv4WAvCQlbLs5opqTBYUHlg5e6SLjfyJA88jUdXp6rDLrcToLLDtPT /x5kgm/q56AVjSSMdBjSXdbmwtce7UcTRST0GHx/sOJPLsChhRvC+SRM2bJp 3e7IA3eLXfflckhg+F8q+30xH3ZGtYywpJDwbcWo/LhwIdxV8y85GEIC91TW a03fQmjb0PP32Tfq/N7/aF9WF0Flo6veF3/KX8NDfTxkEQjriFd9cCdBqPbD NdPsEsgxPJzD9oKEaEZHvr50KWRnq/zWsyTh6PeKFIXvpVDn3fjc3ZyECkFy tty5DE7qbvsUYkjC5kyxJmGdCpg+mnfzniYJbXHuLg8GqiHiZYTGvU0kVO4f cay9UQMGyhE2sJoEiQ4JIb6OGtD3fSsxuUxA79GrjnfqasF7lJd1liDAjnxg e+tGPSSWJn24U0WAatxRUUH1RlhseHyj0paAKzncnX/fNkLR9q02tpYEbPj1 YiwDG2F6R4j7BlMC1i5nSm5RbIKr0yIplRcJGOHYsJp1bzMU/1JYEbubgP9C ZEX91rVC0mhE/vYKJiz6eLlf1mgFzm+irxNzmPAg6W0qq0Mr1JocqhVPYIKu 6cJpoblWWFF35VTcZybwhqUI3h9tg6cRCROSt5nAszZYjz2vAwKHvtb9+cOA 0StHaiOu9EAU5y7a+gU6vJ1wty1274EL67O5Ihl08N2flFJZ1AN5nateivbQ YS7kwrjHvl5IeiQN1bnU8zVHU6aXe2GrW+pCvS0d5PoSHVed74MDz1QvZc3Q QH1O7FKtaR8IJq579W2UBo2BlgXvHPpg4/G85LutNDiUenlNY1ofTHAK+IYn 00BF/6p+AX8/PBe9Hz9kRgOjFRvU/g73g+nlt8tmneMw6dUIbUv98Ixnxfao snG4qB0qHsszADonZA5WpIzDvjApdQmtAXjlMBCa6z4OegnyhcYxA2Dz7PvZ J8fHwfLPiP6Q2SD47L6ntTlkDO5c8xARGByCObt1F5PPj4KSYzi39ewQ2NHu 2R5RHgXmO919eRuHwbBqoSRBbBTEMFqPW2UYJm7pzVyYG4EHb63j6d7DcPhL 2N93ISOwjghd2HxsBOS27tQtIYaBI3/q43HdEbB61n6O1jYMLFraHtfvj0CL 99Zvs/nDUNvAcNfzGYGupJ22bV7D0HhQ4ZXB6Ajsvqhu43VoGJIlqjP9P4zC Lp3PDB7rIbiSJSH+9tsouGS2xdMNhkB+ZabB5cRRCHuctjVGfQjWDD2ozGsf Bf0FKT7mtiHYk5UX7io+BrmTa4zfJA+C6vt63ZV5Y/Cp9ofFNG0AAlTLrdO6 xkGIobpUdbof/tK3cSkQ43DS76jisnQ/iL5fHPvKQoPXxc8ZOzf3w30Nhc6N YjTQDlE9JtDeBzOeMaZ+VJ726V07In2nDxyrOKw3T9Hg4pqwnTr0XugsMQ/J 5KDD+UmJ+JPxvWBmOCxygocO92sZutsseyFod1jU1GE6yJ4wZKjP9QCtxvoV zZoOrmoz0XMcPdA5ubt36DcdnvIH1w/wdcG4eneLNwsDXg/JXI/u6gTdy2Y3 RTYyYMLezfjct074muyU1bOXAUz3/7iVhTpB//W9T5V3GFAnrZnjL9oB//7J nLxbw6B0Zxoau7sNzLIlGlk6GRDgPrbbbbQV9BT8Lr8cYUD+z7MVOpGtcPTZ pnGOZQYsz0X7vBdvhT0dXDEO0kyqP7v9SNnVAp9TJfWnnZmgEzyQpcXXBNHZ nSfTPJlwybHD/m9XI9hKBl+4/IUJK5L3SH4IbISh29HuinFMWJfAKvpiVyPI iJhMfmxggo1xfZ+FVAOgjtUxnU4mOPZUtr4l6mHjXu5DMwNMeC/wPONNQj2Y zGv2jf5lgmIej5qGXD04Tu0LPbOVgMQ7WsfXW9WCo55NEDc/AdNmPfu3z9bA idD2uvxdBHSs/si5yqYGnu6Y/ZQqS8CAtbPXW/tqmGl7yip4joAudyWJjS6V 0MZym3NclwD7DWcb9qyvhDpj6T6v6wRcblv6IOFRAUnnU3OdqL7l3rtCo9mr HKru/1Qataf63MymzL/+pbB8qtz25zsCiKlPUUe2l8J/h24r67oR8MJCtf9R QAmEehovHfMnwPrlitMe34rhm9SQm2csAbvZzCvKgwvhvfQBjwuJBIwLTFbd oeaE+Oqg7L+pBJjSj+nQvxcAf/S+h015BETsZ7IUhuRD5WzV/lV1BLw+v+q7 okYubM+ecyloJMCYKeOtq5ED36Qrm6+2ElCzaR3vRY1sKPa6wS/ZQ8CHYMM9 0+qZkJD2g+tWHwFW9773BKlnwNW/P/qfDhKw9T7/U2n1dLDe2bakNE5AQ9sZ vxUnU+HAUdcTDDoB77+VntZUS4HDvRxnbag5IHKJXfaFajLs9XPhp08QMCcx dsP3RBIksd6MVvhLwH2tS4PfjifCw6wS0miSgKQByVbvYwnAqs9OfzRNAJ/a V58Ju5+gGrODKTxPQLMnB6fIyx/gOUuvpy0QwHmB6Ht+JgrECxYcXJcI2Lgo 8i9BIAIE92iyrGIhofU3na1mIhR89Mvh6goSMjw9a+sKv8NVdqkjzqwkTAp+ lH2+Jwi6+T5Pf2Qjoa/t2o09NV+oePQ8MmEnwXzvxpCMx5+hjKczQmAlCaLC U457t3pBkM6db3EUi9iVbN34yAVYx89f2sZBgi33WfOw1LcQ6fyyWpfipv2X FNRmLOFkUzrHI4r1N3YEye5RAx/rPjZDigXrtN9Odpnjaf7q4r0UZ4wPvXTc /waF7184VUedX1V0gX96/D3WrDnte5riFy/5BcIbPJEjzC0imLLPJWPWRFHa Fx37f9vVUvZzcT+iJX38DxfvnxNsofxzcJUU4Bz9hpLjtu9TKP9j1zIxSPg7 5rPrZptR8VFt8S0JPReKz41jMxap+K0IHbnhYRuOa9Kv2d9bJCDkcVrpzZhI 3BOkxP2Div+AUveRzR3R6Fkm9LxkloCcJekVYRyxuJCuFpVJ5Wt56tzpzXI/ 0XO5K8aZymdrwdE9cfsT0DD5w0cpKt+/JpdiVTQScfOb2dMxlB7+ebNfTLuR hJqb26ZZKb089H+Qy/s0GesUP+47MkbVW0nNPa/gVDSVSC8VHCbg5wgLIyIt DXk8WEy7+gl4cHNlbmB1Oh6z9hvt6aT0rvmnRnYmE9kuqDSJthFglrj5QvX6 bLyvFzui1kTAljtPY1R35WCaz9fQTdRe8uLTA+NS7TwcEHt6PaeUqgcORc66 24gnfEquHS8kgLWra1W7cj7KZDueacsgwPkKf/fL8wXocXdtw8EwAthUIDTl eRG+a9sQ8iOQgNsydafesRZjhOLlVfNUPY/9y4k/5lqMdM0rZRJUvbOnqXPc DSrBeGZfdCa19/SeFZU3LC7DP0px0UtmBJhwpfDqaZejs/mW+J3GBPiJVRlK t5aj0qI+G02PgDesojZ2oxXIEHphkKtIQE/1J2Gv1dVocVPnxuwBql9N/VTk cK9G3WFRaS5JAtZsY03U21KDLqK3XjXzEaC/xlPec2ctPi3Vc4qZZgKtV5Zz F2897ulkry4jmCBwV6NV62o9Wsm7mOcPM2E3L0/b9a/1eIKdZ71GExO8BRJO qgs14AufhoaYWCbA7eOXBHY3YqUryRoXwgQj9iidQJNGdFSrEXfxZ4Lkqqs8 q380YsC+bK9eBya4apoU+0k14V7nVRuH9JnA9zhCJGh/MxYPakq/WmDAhv48 i7VyrRh5nPP3pQkGzGybbWJ92orPP2fOcw4x4DSf6JG+5Fa06FzS4K1iwF+P 7SxaB9vwW6HZ5UA/Btwy2Ctfub8dq1992WkryYDrh5frTol34mX6hi4FBTq4 n7pld3a2B2nvsq7s2kMH9SYR14sHetG+/dClv3x0iOPJMVU07UVv0WfcavM0 cJaxT4lo78UPwi8uxeTQ4NxFEesVab8wce0ViFCigcKzy3S11D6cNc398XcP DVpsoq8fr+9D32Vvbgk+GmwLH/WQovfhzlMVF9Snx+Ge6sqWWqF+pBf+3HIt aRxyJYdXHXPpxzL2jjfzu8bhRYCDd971AdTMj4oo5hoHn+N1wgFWA2itdey2 1fIYCGyw6TPyHMD9RezsPp1jsPal6ScsGkANTd/GLI8xWFCMkPXYM4i+Skbf ayZHwfSYyvzb34O4c0Ppx4LEEXgzo8zJbzGM31NtXdYFjIArjSls6jKMsqPD v484jkCmoGvt17Bh1L6e+uL65RGQOb9gn946jCMZtUqOs8PQnZRyL11xBH/M NVV+VR6G9z8Vr1XOjeCN5cKrtruG4UTGRPTTzaNYXdD3QnMdtf+pXVlgkxzF XNsGMrBzCBwkP59t0B/FosII+/PPh4AmLsInmjqKX431rYbiB+FMYneFr8kY 7rGtkrT7PAhxx39ed7Ibw1nhhc/stoNwKP3kW32fMXzBvVOgXWsQXGpG5aJx DBVjNnz9NjAAd9YOrvizdRxJJ4UF3DQAe3pWf9yYNY7o9uzd2Vt9wOWn00Qy aVjsEpLtq94Hmpu4j00t0fBgWERxnVQfRB4xa+nfSMd9mcqvFf/8gsIeoRMm B+j4h6bvqCTyC5p1fn/bb0nHAzefnguy7QH2bpNHob/pyJS0Ffiu2QORLqmr p1gY+GipoctlSw8MPTszL7WJgboX7zL4o7shQtkwT0OagVuarvyRbeoCh8u3 XsqYMjB8Z/Lc1V3U3rbDITu3g4EXOUVfsDE7wErogfP5UQZauP/l8k/rgL02 pX9K/zEwMfmYvrNWB6yEa+8MNjJR6L+8VzYP2yHg8a3Aw6pMPJm0ID+b0gqD btdefghnIueBJ2wvbVthQwvnvE4iEze1NzPHT7aC9NE/7xdzmMjm2tnt19oC heUBkYtNTBxYNWV8YLoZPFmUyGAWAvulLD84HmqCL/x5SmaXCFQ+G0vsWWoE DeVH0TIGBDoOCY8VlDYCrBuobL1H4BZ+J9VKvUbo3Ryzrv4lgd5mdmePv2gA u3WC1eZBBFbQmKveHG+A3csHeM9GEXhJXjAuaU0DZJxWHeBKJDCo/4Pxv//q wVB1uUW1kMD6Hj+Pbss6qOU96HB+kMD9J/KFQtjq4Iyb5qozdAKdDpceuOBd C8YR0m2Sfyl7IxK3WybVQOHjbg0vVhLX6k7N5ZNV4LyhmrZKiMQXzSmuzcbl 8DLRZPdHXRKdelmtTCbLYOZuoHLGNRKL87UW6A5l8MTkjk6FIYmxv1bvLgou hR8r1j3yMSdR1WvzaFZHMei/2vm7xoFE3l1c4c33ikGSr+PTlg8kCtagc99k ESgc+75ZxZ3EcNbwiTquItBOV40+5E9iAmfz0jatAlAX1+qp/EGi0hv/lxWt +dBH69u/O57EdIUFzydG+XDiosFZ42QS2/llvY4v50HI16ku12wSdzN3cOls zwPV4nfqT5FEAcuDKmcO5cIffvqjo0UkFlZ1rl/9IBuQ2PrvZSWJOnIDZIVT Frz+qaPFrCFRw45j8kVwJnhLaV840UCi9IDPr4iWdFiYMHvq00bi8icrFrGJ NPhnu+r9p04S584aZXuvTQPHy9pqT3pIPMbr+PAkpIBBVk9s+wCJtsUvIleo J4OXSe6az8MkrpLQj/h5Jgk4QzSb94+RWHvBb7/2xUTYnKK5LppGIl6KX9d7 JQEYdOe4JQaJHDb754ryf0LP5+rMAySJ9kd8fJJrYkGKdVD6xG8Sqzgbd5wf jYLZs5Fn5/+RWHrVVYDlXwSwVY1OhU6RuIH3P/ZAlnCwVxFgk5yhfm80pr93 fShkTGyxcJslceHm/Yhovu9AynmdqJ0jMVhXYELuTCA8uHzbkjFPonelW+KS 0RewCNFmG1sg0cOALTLZ9jNoGe/8nb9I4jmdmyOXP3uBPPlF2XqJxIFStnVt N9zg9UeP/rXLJIrGfJYbd3cCU6fi/lcUZ357RGt+/QqU9rEpV1K8oTRwwKHo HijUbWVMUsz4pPSucUAblVsX/i5RXLJJucbyqiU2HFe8OExxW1kOD9jY4+H3 v9ZGU2xzZsRT/vQH9HVcyX+K4jIbvy3r3Txx2+aCd+WUPeIdLW1Pnvrgr3US 50Qp7orLeF16zR/5tc9b3qDsNzKvnFyl+hX/JZybtKT8Syw+5cW3LRg9Nqu0 3qP8z1K88CpkdQjyaO/lUaTiw1l3bO/OhVBMUT6YOUrFczT3Gs97Mhw9Mk1z LadJ3AFjKf0DkVj/fUi0Z5JEK5e9LyRaozGoLnNiF5Ufpe77HVcrYlBcYFlY 8w+JEffpp6xz4tDNpDJTa4LED4/+nLCJj8fFDwcyJQgSOz7d3iHXkICBN04J D9NJNIcnltNFSbjt/ZjM1AiJf6u61FVzk/GI73/tp4ZI3HJn/u3rtBS0+U+X sOkncaf+bYnSqDRkfZJj+qKLqq85C3kr1yxcT5ovNVF6Hz4l6ibjlI1sF1ff 2UrVQ/jj65xNtjlYqKlwVraUxIsyiTdbHuahYetMCUceVW/r3GPbdxdg7t9r XzbHkkh0/DfbGFqADjdZvSGSOo9dUR4FCzFa3m7fqRAq3/c76A94irBny2fd GT8Sbxg1aK7jKEFXjvKGDHsSnX3FeTVelOA4S/05RRsSczJPkJaMEvRTj14I sCLRd3HGMKixFLPcQyZXPSDxh6HtNrnAchxb/3Ts5QUSL2yX/EVsqsAAg8pb 68+QqLl2Yq2/QwVqJPjte3uSpPr9xKEUk0q8deB+22YFKl+bhn3XylajWUQS Wb+D6l8Wr6Rkwqoxd87Rw2oriRPnbF8Ddw0mrHwavcRJ9Y8gxiqRuRrU3f7K IG2RwJbLwbeG8+vQ0P24TnEPgbZTvm6c4Q0YvafQ5aY/gbwJCW9NehpQT5H1 nowHgXz2mV/StzVip4/1zgEnAh86GdpLOzei2ku9wxMWBFZ2BWm9NG5CrnXH e+NPE/hj0rbytmgLPoi+87dwmokGLRnruq+14BX7qLQiBhPtTcZCT3q34PfE yyWR/dR8Mt/EP76iFeefJ4zzVTFR4RS5/KC3FdceDD0X+ZWJrvtVFRV82pGz teHLQyUmrq8vNTlQ146Hcn84+0gxsSLVNGXr2g5c9Sf77n8CTMzIVYr3f92B a2/oSR1jZeL5MI1vHqadqD4osoutnIE6ZnHebIrdKKpS2maqzUCv2g0N9hbd uL3jbafjEQauWhGoMRLTjV0zoxGv9zFwQ8dy3y2BHnz2RKF963oG6t8brdjG 2ov9O6qOYCUdwYv4ql78C3cW2O4QPkbHS4f22K9d+IXtz1angDQd7S9JnW3n 68M5Un418NPR6V7yIR2dPmwYt5Pqm6bh0faXLh+xD8+MZ9z5GUfD52dLFhb9 +7G5qNjx4xYabnjFDFs4OohLATbNheVjeCJr+a6m/iCq39xr9jZ5DKduJafb PxlEcl+7nHjgGCasqvmQEzqI+i/sY7ZbjmFInNmFc6uG8ONX04eZO8Zw7qlP QXXlEDoc/KPdd28U5x8ckRwYGEIUrApinB/Fm82ftw7ODeGt9H8WvYqj+C46 bDxCchinJ0QWLdaN4k/5/f9kPwwjo/TUsdtxI9h5T8wBTozgwfICm4eMYRTf 8fzFov4Inrj1T6i3aRiDWUJ6wx6N4IviHaVy2cN4Z3PJ4/ivI2g3e8DSjzqH qXFwc8LkCHL1ETNyYsMISdc0T4SOYuNZxzujekMotvyjuYQ+hkIbdw+PxQzg teVTVwSXxtCi58czda8BzCg6nWC4aRwvqV2R//R8AGX2k4+D5cZxzZegGEJt AFuzlWzZbMZxwi9tZ3V3P27LrinR4qDh6mcyv8TX9OPPLPNoUR4aJm4t4L1D 9OF4l1nNyG4qDydFN7k39WHE9tUWQlo0tOOtCEj41oe/YmUeGn+koW76417J A324Pk4ue/dqOvJd23Bq249e9DPiEnrAQ8fHdSPWtha9GHBrs7qPOB0Ft6qb lir1YtALjZd+anTcorjvyXwlpavnNPabr+movCNm48x4Nx6ZePazl6SjiWet 3gORLpzNbH5quUjHXaueXJsd68Qj8kYejLWULiNmXR/Ed+I1KSUTFzEGSme6 3VxU7kS997r2L64wUKZK9nDPxQ7c3pR3jCOHgXvXeukU2LWhJus/mxaqDnyf Cm2PO9qG3Z5yaW9bGOj08N1bm6VWLPY+l2NFMJCFi/VWmW0rzoYdNCik6urg lqAP2161IF11baWdJBOj50dcxZVa8GRD1wNeeSYee6r9cedsM+70kCMHzjBx MCslPM+qGTvqtJIanzPR5tIJ7tbHTagsnm9u5cBEPBXlJCjThA0b4jKn3Jio E6dhqsNsxPVpgymuIUzUcwitfmTaiCMKPtyclUx04hjGoFsNePb3m2camwk0 XPfcQvRzLZpt99oSs51AhbP9aZs21eLHi0traCIEylao/mr7UIOBjffSZ2Wp PTU7+MGsTTXKrZ3zMdAhkOtAUnyAYSWuKhY6H6BPoMnGfLknnRX47aLFn6Sb BJW3nFrxixU4NjCebmFO9cUI3S45tXK00bJqkX1HIGv1LxdCtBTXKcKVk24E /taWZ7Z+LcHprs6rst4E1rSL+YVtLcFEyd6QgEACjS6FG/xhK8aRGrKWJ4zA GJpgheWrIlTbIqH2MJrA6ebV3D1/ClHD8lZLdDKBKRNzE6b9BXjBaW2bewaB SWVElbt+AV7XOcDUziWQ+dthV2BdPnKxlMpcLSUw9rIfY/ElYoLsCYMfrZS9 J+9Gp+/PRpWAg1LCnQSGangZCe3PwkmzNYVWVN+3l2HtMpPJxCr9GwfyqL17 2O/h2dR96ag/286SMELZy1nzLFkqDcmNco5vxqn4nJWN+29vKu6IdfDKJQg8 uKslWGRPMgplPNsi+ZvAv9FP35XtTsINGifknlF7Ojnc26gvnog7+cfIwEkq Xw1q/m2iCeg0d/d45DSBHtU/Oz6o/0Sb8Kxd7rMEHjniUaWqGosqfUOfLs4T WDbmuv8X/MA580Hn6QUCdxetOWigEoUkV+riiyUCm/LvLRYqROAFD/3fncsE arWsztp4KAyvR1df376CxNX/znqrHwjBIlJeWYG6JziynE0z3ReMPZGZH+XY SLy1Ji596sJXHOA8cGYjOzXnv781nj/lj6V1Xm/KKd57z615+IQP2nxvlri1 ksS6qSM3spQ8cVaWcbKV4gc9azLmjN6j9KG6dkkOEhdbwvWNL71BriuWAzco lhC8HfHm3WP0OVd75xHFRnvuqMe/58PYipYbNym+Ku2naG31CE4/f92wj2Jm 28fZ992v4S5nAXZS53/rS5jsWHoHhLznHmOKY613FfxY5QmdUQMb6yn72KSb DrVt9AH+LT8teSmWm7ZaZPL4Q6T4mC5Q/gkcDsyhCX6Fhz7O6WqU/+27GS5D W4Lh3vrX/0lQ8aHpdF4p5AkBhxNlCzQqfodPG35x3REG6UOXBlyo+B4sKRc8 LhgB02E7T6+j9oaLT/RzekSi4JAcj4IplR93Fv0Tt8R/gLHq4R/hVP6aRTc6 lu6JBRsHy5B8Kr/bPEsubtj3E/bwCO/xovSgq9f+5ytfIniYN2drUnrx4JP+ zrkjCapCX/T1UHryNh5IM+FPhtAk3vlQSm+Hfg9U9AukQhxn41IzpcfNesyg BcE0MNFaiB+i9PrEv9F9WSgdas1F5IMpPb9ajDbJFMmEsdYe3jOU3u9oXZV6 uCsLPMQ+FLdS9cBZYJjFIZoNt62kvd7XEdjt8GekVzQX5mdHC+KrCDw+rWjA L5YHC3c3taaWESg0eklHUQxh65xUmQESuKr02E9nr3z4Jr7BTTSOwMEN7hOv PxVCXeRUYUckZQ/rLe/UHUXQ455w1SSEQIvTemxN4UXwbsG7kcuPwHvhBm6F mcVAaAqt97MjcKO8+C7DvlJ4ufz8De9zAl/quXIXmpaBq0xWtuUTAlUebXu4 8m8ZKNcpVKTfIfAtp03w/pUV8Lphbs5anYpvzTpLDokqWOR9YFJxlLp3P5wb vZdQBczXWvyT8gSq7hx8GKFQDYKvvT93iROosdd9TYZmDbxetd9zhJ1Av87s xu336oC1R7mANYuJ7ad2TYvWNkD2Dj5NlgQmBneNPefmaoQ++fyDHeFU/96n pfr7YiOcfFTwaecnJnav+G1m2NEImweGG//cZSIn0/bArsEmKPhqnDOwmpoP FZ5mw79bwPb20HjwAgOvqCUZnTzYCj3p9j3KEwzMlK/89OFpK7yZOf14dRsD n4h2nsydagU/qV98yyEMtNaxflUx2wYfxUavvJRjUHUlfFd2rgMMXAK+XhJn 4FGXos8fFDrhvK230wZeBmrOWF0vsOqEhe5PicLzdLxl3u7Q8KcTHj8Kpbo2 HbP3Td0yG++Cx+3nDfep0rEqLTxPu74HNMJL7m84SMd/fHIFrpy9oK5QXl8v QsftfAdmIzUp9o2XmFtBR4fmTSwW+b3A+8BXdSCPht1BX3dr//wF5o4yrCIH aRinVj5qUdAHK232xosL09B6+f07o94+mKjy/7RhIw3dOuVkTsz3wdyta4/f 08bxsWjD5gK5fti+8tN2ieBxrFOIa6iI6IfCe0f3H+QYxzeLVgyG8wDUubGt u5I3inVasjOR8kPAEuub/uTHKHrHtlsKnBuCvZta2p5+HkXh38evvbk3BKp7 k34pPRzFI2t6uTn8qecHVdkq+Eexr61wkHtmCITyYs+stBrBADaLMaWUYehZ PymRwzeMGU0Pxmd2jEKBSsGIHtswPrOfGUs+MAqbC5rt+hlDOC1uXqqnMQo5 +eM/8nAIXyZi3RWLUTh03ZIINRpCjn2DnCfLRmFR7BWrbMwgcpdsL4s0G4NU ISN3PqkBvFps1yIePg5XRQ4e9+UaQD+t36rmmePgG2jgvzzVj7/zhBd9a8aB ES+TE1zQj0/tGYtuk+NQW/DXm/dyP9J7pli51WhQYkX7Ov+qD7NF7B9bddHg fqLi2Se3+pDPWTy7nUkDo/536W1qfRikPCnDz0KHQ/vUD1mv78OY7csX1UXp wOIWMLJa5RdW8uhHiz2gw+h3y1Pjz3tw1v5u4oq/dNAZ23t17bEe3Fr7Me0h GwOCt+4Z3bSqB7s+Lfdnb2FAnWT6kzqfbryqNPZ06iADekOcuPniu5BddO9a ugUDRkw41m771YGWrEJECY0Bg89Ft8WEdaDBJ9kx6VkGHAoKeCN5vwMfvm6T sl7FBCnlq09G/rVjvey4QfguJrhUZltcWdOOQzfWzlhdZcKhwfL/bkq3osIk v+FwAROsjh31DJxqwdzAsWazGiYoqHutqslrwXM3Q3a3tTPhXOyXw7NnW/Bd y3GNSyQTWt65NHs/bMYNxt025HYCvteYxs//aMTJ1nqFEDMCVqxeXtC0aMQO s5UBF60ICBi/mv1esREjFVddG31NgOfktaN9ZQ1od/tyV6oXAT3WClr/Buvx 3FWDfUQaAZy5a4PjD9aio9SEf+ksAYe/fbAvzK/B9TFxI19WkKBofGwItWvw 6tryfTprSPijf8z31b1qLNCddr/DS0Kb+Worli+VeGbalhQ4REKOb7vEE/FK 9P0tacCqQsIq92SBuqQKJO/JfCk7QYJE7VnJS1XluFdD9P70ORLWf7URcp0v RW019lm6CQkv9FeefvyuFL29kw17HpKw/buIsdqWUvx2zck64SkJV1J+FedK luCt5mdf5l+TUPa3xGFJvwh5e+rPiPmS4Cms6/VgqBDX3euM2/WFBFE/Vqh6 VIgvjBsC2IJI2HjYtuKOcwGKq5lvMIkiYXNdAhuHMXV9WkzqKcwkwSMgrT3l TR6mKUjJZuaSAJIya84F5GKn87rdXgUklCueIDTqs1H5xiSNXk4Ct2dBVyQt C5OMbdLMqknIvGj7eZI9CyWcbu+oryNhtMZy+LpiBr5jO/njaCsJI1e8k6wv puOPodx6rQ7KvqWMvLfmaXisx/3D4W4S1JT6Vpp9T0FFHtmYrH4SvkaWvjid nYxtHW82nR8igb/dJnBnSxJeSxNaUT5CQto+EbOvqxPRBc/Y3qSToC4xpX1K JAGfmOuufM0k4ZZwWVin9U9MOhzFZU+SUBOauZczJhZpBg7Bd3+ToBkXZSrZ +wPTd4klSP2lfr/lhZ88VzSmlFYdbf1HgkrMRuKAWiS+eZ966vYUCUGndCJ2 WodjWrRQY/00CUOlIrNz0aE4ef90k/AsCW8mTQSrur9jO+fTM7pzJISONZzx 2BiMM9mbVB7Mk2BvUX7zk+NXFPgz+P3OAgmR7asXJ8b98cx1SbujiyQEej3s gXO+eKtNqGGe4jMybOZvUj6hwjH2gIAlEva/Cpa5f9AVky25uncuk+D7Jc87 f9ER4886+bylOCRxNIfL8xWu/fm1uILidA3tIEGt+xjy0MfsL8Vu5+dXxD+S g8vm0a7LFPcrfQxbc/cRsL3jFSMoLrgSKs4uYAcf/AXkkeIDPB8D09WcocRu Bi0o7orPkDV46Qa+3IOFqyn+IDX8akbPC9pVdoA9ZZ/jXMvH1D++YF7bI9dN 2T8rK9Z5x+0/2B91L4yP4hUaFYssEt9gReSkmyLlf+fFbrWThsGQF1n8W5mK D8/gv9WvpUPg5DuueiEqfkUf9vjGzofCUxG+PWMzJDx48yy5ujwc9lzmXfxE xV9quWlfr28kqC2fPiNA5YcVjtX+uh0NIXMT3G5U/ujPUw3qZWJASEztRu8f EhjHfF6/qPgJlQ4PDSQoPTjvf9fCczoB/Ho38wtTelnH+mXm3oFEMIqNvbpA o/Th9fj30GIS7DJIuXOV0puxmKvrpqFkiBL6KtszSNWDSBxKV6aAzhZzlxOU XiVXxj8/9jkNDqnnDaZ0kVC98g1L1L4sOLmh3FyBqoeipUcuTeLZcFqgyMix igRZiZNW44I5oCiaWRxXRsLpOyKaDVx50LeNvcofSRAjBS2OzOVDbizP8fo4 qp4MZrKeWBXA4/eMulXRJIjnqW/y/1MAkrf9e/nDSNgk/+tsJq0QXLYznH/9 R8KU1BYO1c5iMG749KLMgcpXsYD/gm4JcJsct6bbUvq+MrkivKEEXr4b42Na k7BgcC8nv7wUDjmuMvrwgIQEoe0mvGnloPeYDBPXIeFQhM9zpms1bKIFhs1s I6GBwZ56Z1UNCMBhh9n1VD2W1KkX2tfA4dhHBu0rSZjJcKuSt6oFuRvKQvsn CXCWkeufka6Hn/RRN81GAuZTAvx2b20E1W+6hqLOBFTCKW7X842w1uL+u9U2 BMTeYtXvd22EKfYQiaonBPB+UdG8sbIJtI7LLtGvU+fd9m3xmWwCXt7h/q8H CGCV8HjU2NgCr012EIXNTLhz0mDdwbWtIPByUcGogglsp+7dcDjeCt07revG cpkQ0fDQ6E98K3Qkv135NYIJM7qn8tld22D+hHxIjBU1z9aP5tUf6wCdw2PL 1lxMUBLIU+e27oB8aLK/wE7NNwXCSTOuA/4qfR3bNM2AC+e/37fg64S+73wu it0MKHPV8mid6ATm1UUZ5XAGrOYf2JYW0A27Tl/4uFqWAbX6t80S6rsh/V3U otguBrizaJn4rOyBW3teLO/eyoDzu3448D7qgTaLD30dk3RoTL+ZsO54L2xb MrKaSqdDtGSGwJO+X3Du31LfzsN0UGqz+jbm1A9PzEfX2wnT4MXn7/TB4H4w XR3QnLueBk2sG9Vrs/vB+NU+3V+z45DKGvv50W+Kd15rKmsYhzjbktG+awPw KreW3P+G2ncu7Tt/a98g7KgtXP2sbQwOBDVeVNEYhGMrNud0FIzBGe5QWGk4 CCbdE8bCsWPgNZSifsNnEN4KVf658oZ67v/9sMjcIEw6d4PF7jG45Hq9pq9g CAplTztcejwKTdtEB192DsG/gUz1v/qjsPB4TfzynyHYsUv/mdXxUdir+aa7 fNcw/CyZtJTcPAp0KcNUXcdhWEqx8j2dNAKGJtmflY6PAO+Lu4bvmMMgnuR5 SSl6FC7W1Ix8OT8ESkZy/+zzRuHGq6Sip9T+uUzb0ZLQNArvP5Lyh/mHoDbb q7Vokfo/5lWnrEYH4a+2mHL2+TFYG2O1qc9mEIocBuIaf4+BzrEClpehAzBz esuM3cpx0PN12UZ7NwAin4RsNvGNwxFtc2c1swH4L1M1ZQDGIUtz/VSG3ABw fW58dsx1HHJ2dd8MLe6HU1tVy0oEabB5W8CUf18fcKhnzaQdoEHcwVecuUV9 UPmp09xFlQbGx6uNaiL6oDjwQ3iPMQ0E3PQuJ5v1Af2TcveuWBq4Kjary5C/ 4FG84sLOA3TQdn9/N29LL1xRVG5nE2XAJtGYffEnOqFfRadI9gADVO80FaSv 7oRpM1uvk0cZ4LvnnUZ4bQe0aRR7cuszIOl+Pc/+qx1Aez81d+cjA3Y8a722 7nE7jKmcmAwYZ8DyNe7fnH6tMLKRPMoyyaDqnJn35loruK71O6LBwgSHiGtH ewRbodJNYIMtNxMK180c14lqAW+zqXGn40w4vkOIsTejGQ5lTbIsfGJCT/jN q31NjfAwbL78bQATuBvp1vOfG+Hsk04xehgTjDiMuNmuNsKvkhLjW+lMWHXh W0v7rwZg9pTbd3UyIY+15Uo4rR4kDNeZmw8y4djC7Vd74+ohlmFm10dnQq/3 CH/wo3owldnfbbrABLP6iLyYsTq4NSrFspqfgDN3K3P+zdbAj/09/t93EXDu osPMlG0N9ET+GduxlwD/aCXZzhUUy05YJykS8F70Z+DJNdXAOBpTc1eXALeH 9Et53JVw9tXcNzaqD82nd75o/a8ClNdNptnfJqDLt+tLE38FNOzuchF4RMDI pb9NdiLlYPzRPrKD6nMuJ/RSI6VKwcQo/MuEKwGFb57664WVwEJtz0g/taeO 1b0NZuwoAduLrrcvBhJAeN0vKV9bDGDGatcUSoDpMhzielsEClvcKvdFE+Dw cOnR8dlCcF7TV/s4mYAONWnGtdECiNeLsriSQUB8WMAbDYMCyDngJMifS4DA zLjTzpZ8kHpnYyZTSsDz1hObeZwQeCINs11bCbA56DzNppgN69VqPdQ6CUi9 sXw8UiwLlEzO7WztIcBKbjuH5OZMYKp6KDsPEbCpXFSjiZYGmnPaGWGjBAha cd5faE0F50PCpV9pBEQlOV1YW5QCd/KrnvBNEKDE8bC140sSSFpuXh34h4Bt W4OkAp0T4VSxAf/CP8r+ktuJZywSYLhsZdzBaQKs+V6+rMn+CQJe1zPUqD2d nnRHp8srFngPZ6jIzFP+K370LzH9AVOV5gp/FwiI9Jhk8TgWBZ2GjdGeSwS0 +MYpK/FEwPhGZY//vX/nJJU1W8EMhZPjCyN61J4vKr+Lcaz4O3Cxmsfbs1J7 v2T/O9VDQfD4Yd+IIxs15y5eMurt/wJOJ2JdDNmpvf5HfJ2e+2d46iX2lYea c4m/WaVSlbzAwOI7dyTFJl3ZadM1LmAy9XR2Iwe1dxQEv74t7gApspMnLlB8 +HgU8/7iU7irbP3bnGLOz3qr0h5pQ6DoebY7FN8re7jIpvoAHVhbrA5QXPdz uXx8wg7lx6+e6qDOt3nS9nGb0HvsZMjbXKV4t60wT/UdT/QSzlubStnH81Rn 5Yt0H3wbcPLfGGX/l276Ps51/2H1Q5HDU5R/WZN90m8MvqF3fHRDN+X/edtN TaPtwWj0zaHwKxWffonLPi9ZQzGVe5lTfpkA5ecFnyf3hmPA54b0qEUC3BX2 7b2sG4nRTYUV/6j41928H/6fXTQ+dvyitX2OgL+DWldyI2PwxQ7+n7+puU82 Hcz9MhuPfQ91g0P/977d1scfd3Ml4rlNPjtkflPn62W+NBNLwvc8x8ob6QTI btA4n6idgi9oKqvoYwRUWV//8NMwFbOHb9C6h6n6HXSW/vQsDe1l9mZo/yLA MTrHaMW3DJQazPm4ppuqn+fBTxQDM3Fmm8eqsHYCTFLWFegGZaHBR3buZw0E eKw0qpX/noORPvFJMTUE1I+W3pz9notP439sLKggYKLma2dASB7ORgYLvS+g 9oqgUr48nXy8czb0lyJVP+sr3f90NeRj4ueVzyqp+hJTdfYe1SnAa4EzCu/j CfhKf76iVKcQ9+3JbLcKoO6dux5re54vRrsuXCP0mYDz/XEH1tcXo3en5uUo TwJkZgXdLc+V4HMZ+pPLTgT8tzXFe067FFU0ktkkzQlYs0Jow6BWOXKUGW7J lCegelQ8LFKlGiMsor5dkSHgvlBfiU1WNRZL+bF17ibgihjfhKxCDS6pWHm9 5CXA6NHOE8eoe+7FPhtOlRkmvHZ+wTm2pR63DLv+rUpkwpm88fDdKxvxp7/b 7cdRTJCL0eCdP9GIiSvvfp4MZELsxkJG1ptGNGTEfApxYcKRuoSspflGdNoo lvX+DhM+8k71efxuwtSSnaTPeiYI6AiuC25vQaVXDjRnVqqfe/cU0ra0okRe Mf0atSe5BL4tFjjXiu/NGSfj+xjwcvZ8yvGSVrzOV+e0mMiA/esFp80S2hD2 nk7QOseA4cQ6vt1vO6h7ntrBZycYYHJq/XV6dgfuPqI743iIAW+IWzq+kx34 ljfaX2cHA0YJ9if/mXTic+0gw+/DdPg2fEX9unYXHuxpYEo9o8POwNepX7h6 8HFF1p4IYzrEtD3+EaTVg2VTyvPs+nSwK+/tdLbvQVcr7yxLJTrYzEZtn5/o wbfp5nt5l2hgmQnaz2p78VqUY7fnGxoUd9zkLzjehxcU7s8PWYwDy7jWbi1a Pz5N6zDKuTkO/zV2vnzCMYB/xxwPPz8zDl7LSu8cRQbwdGm73zexcSi1kD93 /+oA5v6yw5DWMdCmpR05UDGA3HP7C5IOjsHyO/rvTyGDePDOvepfAmNwISPI Xy93EDc7CGn9XTMGbHPPBDnaB/Gy6RX+2l+j8NiS8+bO9UO481ZA7eWPo+Di 8ir4gNUQ6lpxvm/oHIF72XIrOlSHkdOzQPNZ8QgEZb1MF7wxjK9eeXqu+DkC UZcu+GhbDaNRTuXR5jcjoCm20cAgahh1/5sruys2Ajf9177XWTeCmaeFBPXu D8OHXU/GTKpHUHFh7snNoUFontqXmqQ0hqlPV/ux1QyCqn/n+cPnxrBHR236 cyq1T6Zx5ofeGcO3hYMtLs6DUDbm3nzQdQwNFNewJ+4eBNuU8Snp7jG8slVv hOXeAOzR1pZ4az2O3eXpz8PPDkCUR/Hsq4/juPJVw7SS/AD4vdzkdf3bOIq3 2YsprhwAiVjhnobCcdS9u1XIKaQfaDJrNFw4aRjrORFg0dkH0+q0DKkAGkrN 2ujIFvSBb4DwXtdYGu64uva/ocg+yBDZYdOQS8O97C81hJ/1wZTk+Tfr+2i4 SCNYlzb0wRm7kVdau+g4J9+8If1NL3AWWSWUhNFR5xXrhZ9yXTBuORb/0puB DuIOjalzndC4WlQlOoSBb35dVwjP7wRRLtET6YkM/LN/OkLlTCeYb3/+8Ukd A3M1KpIv3e6A9ruBqTfWMPHc0p8Yg49tkOtxGddYM1G4rmia5VwbVJNBkpKO TFRzvP7PfUsb2B4pP73nExNjzxf8efi1FcyO5dgV/WDibberQSfjWqC5OVjP uJuJY/0cH95UNcHsGc/NNxQJ/Mr1+uOsexM07sqruqNG4FoXs37DC02gk9Hj p3mOwJQTXM9WdDRCxhUr1VgjAvt23nvxdrgBChRj+jvdCKz+89DMJqoBvmey SzX4EejQj6/vPWgAxjP9o+HfCdR3DmVw/a6HiQlL35EUAje41P99NV0H+q8u 7anpIHA/q7qwu00dHHv7vSphgEB1pyx25xV1QEZKzD6hE6gwMhkssa4WfrRq drkuEHj3y1rukzurQd7iwwrRnSSOL53bp3SkHFR2N7A16pH4qMRvmqeiDBpO /tLZbkDiSYGa3KFLZXDn7i0FNSMSlQ8+/u+MWSnQbOSzVR6TGJPc3mLwpRhK 7ksczncmsbT8RleuWDG8VXvdtdWVRMsowXcbEotA7cmN+VOfSGyvshVzLiuE RwJWwdcCSFQoCKps+5sPyceddm34SaKa1qpzNXb50LHPQeNhEomeYX+F09fk w1ER3+r4NBLfJC1uaDyaB9ftshmteSQGm958f+dSLhhtOWifU0jiRN1mjT7T HNBY52TqUEqiSnKaSqBPFsjb2Umk1pAoKFdV1hedCV7iH2YEG0jUMX9xjAsz wMhVbqNZM4nJxWe8j46ngYJR98qoThKvzWikqyylQsuHqQG/HhL9DDJv7t2S Cs8YHssmfSQ+nIDWbpVkKI0+8OfnMIk9Sc8mgnWSYC4sqWTXGIlOLbd36xsn wmGBsKYXNBLrQ3mE2V4lAN4t3J7IIPFso+aqk4Lx0FxV8V8FQVL6kqWZa8ZB WrDVuaIJEo+v33D47ZMYiJJzUgr8Q+LVLdvBoigS8jszYqYnSezb7up1nhEO pm6XZaymKX++PHkjuC0MJI5pDLbMkJgnTr/UdyQEjqhqlHLPkdilx3fdxzgY GCOb2xTmSZx+r1j8QuAbPH1lvFVlgcRBDinjtEf/Aa/Oko3QIonCeqfl+/N9 gS/j88YRivUi26sXuLwgg4VR6bpEou4pSUeeUldQeJUVt3WZiu/xrdeFTZyA Ny4vzZbis9sm7ilstYGBlAPDZRQf8y/7JpdwH3gaAhT/UuxkEfi56Zg8mrDn pixTbOJl3HZQ6DE66ejqMSm2yHl94Fy3HQpki4rkUBzwhstastoZh1Tp28wo Lv7be2WnpDs6EyYHFyl7PGxlPi4WeWFa7o1Xjyg+Lzuk8sviM+5K+UAUUvZ3 zkZJJwp/QbvmWLdpyt+ww3wVj+u/obXwuyvrKfbePZblhsGY9639AjsVH3qD 3Lm2zyHIfsbwZfcsiZ/PHGvd8jAM56T7632p+G4UvxSyUiUCb3TXhx2m4j+2 aGY2tiYKf1lRGyyVn22eTxay2qKxnLj+TOQfiR/9NbfbhMeggdwdywdUPpWb 2t0kLeNw/PD+1s9UvvkXVguWHIvHhPHngWGUHjzZ/3R3myfiOj6d2/co/fjK /ox+fykJZaxP3eSn9HU6ePM2CeVkLNfyLk6m9Nd3sc8AVqei7tq6mg+UPrkk 6eZ53zPwlMsdkSZK31FvNVdMvcvEk54nggIo/bP8PqvK/zALv36J9lOvJZEz 45aerFIO8m1xWalWRqKrR9c1ywZEo545gZ50EvkCbr95dy0fL+u9KMhMJlEy 5JD0qdp83G5n9e/5/95vFZrviU0uwHoxE+6gCBI14sW6e22LkF3ivfdHbxI7 fse1nZooQt8L19hs3El8yhUoG327GM0aQnnPf6Dylf22QlmjBOk/eiDYjsTD wm/exW8swyGroIW+eyRGlJoEhtuX4Tc1pdVjhiT681s5u/wtw00R3l0N10h8 tfz3tVhbOV437aFrnyNxNmT/5g/fKlGl9fTBMTkSs+r+xPzbUIWm4lcXV0pT 9kwVvdV+U4VVPj3JHLtJXNB//63kdjWacAXNJPCS2PBQ275UvBYLH7oYRs8R WEWIXTZsqUcP/d8N+zIJTHxmcEVqcwNuOWzclRdPINug7eHxsw04HrWwVTqC wP/AN/xweQPOGmcoR3oRKBwpdEA4qxHzZby0V96n5ofR65NTX5rxHieH3PPN BO78qN9R3NqMe5gOBhMcBMbXR1bbb27BxYGqkxrz1HzyqP5T8qEFT0kPmX8a ZKLd8TGRJ9atuEJTj98/iYm/2XbtEjrXjpXz3Y7PTzFxBeFYlvmhHY0cGRr9 Kkzs06gRO1rcjlckwp/vkWGiVbWMMIdiB34SWb6ov4WJa0K5XFyFO3HZvknz QCcDf7f8Gz9KdCHrPK2305Cav/e4/3k8/YUnpuo2m16h40+LSLYrUb9wn5NI wEotOpbvC25f3f0LL4unaL5ToCNrZeUKd+E+XLWsq6HEQ8dbQr5XVr7vw31R PSq3mmjoyZG98eGFfrTax2qQrk4xW5i/zYN+PMo6eSFWjobRc9v7bRz7UfB7 m9o7ERp+4CdVL6T1Y5lTz01ycRw3cbfqafMNYMEwu/zH5HEkeGqZZt0DGNrx 4dUM3ziGdUckfPw3gEq1WH2JYxxTEpde+3MOYtbPH/z+f8bwSOO9NgeVQeS2 2TTbVDmGO5pLHn0OGMRjqofuibwcQ+7zlobel4dQmTZ8U6J5FGU/Hq3eg8O4 9lmA6VWrEWy4uB7GWoeRzlhf33hjBIXCrw55EMOYv7DfZf/JEbSdHVL4snME L2/Ruv11ywha7xqW9Hs5gvzGrBoK8cNI2+e7fsv+UeS60FTp1z+Er/3E111S H8XhZaHAJ2VD2Dx0l8Pm+iiyVBDPZOOG8Mhbrftv3o9iq0ZQhOnzIZSTFuXW +zWKrw4YHUqk9lWf5yIWO9+PYajj8vm8g4O40Uidmft1DB3ZM6e38Q7i/Cen w6qJYziz5uSTywtUnH4fiJvvoPzO/X7eq3gATS2WtYUkx/HC0Fnp2YsD+NSP 8+2OknG8e6VPJvhhP1rzeoT8HaLh1nVH5i0lfqHUFDwNnKQhhH3NnmD0otj8 Zr69HHTsVdmLmom9OOe5+uG4OB2L583CXRR7Mdjp04lpYzr+DYp0MtLswbRb PPbQT+loSuhs0M0urDmpHDhH0pHj1sGKCWHqsvdDrNV3iY6/VjX1CA91Yt3K wxJmOxioG6ozvou6n9wMi7nge5GB3tOPheIfdmBFe6hYYS4DH8ezZwpatWFQ hoWBRSUDrVIzu13k29Dd4+L2FW0MtPuQvKN7qhUvrFxfmEkycG/bP15Jqo6e qcbe8hVkon+ExDlHqxa0+75Sd+A5E7dySAZaPm5CP4dYrccOTLzXvbVKTaYJ 3UbNrne5MdHT/HjFErMRe3gW3mqGMHF2rtdY+kEjupZGm9pUMLH5h9EzR6MG JNcprFXmItDWMP56SEQtmuUKurHxEaj1fxWaeTiV2xfHpRJFKUSE0r3KED9l vKUVKiXRqEJR1C1UCqVMdZLrhgxRSXWSDoUMIR3lLEMoZMwUwjkOxxneN4SQ /N775/fZz7P3Xuu79rM+63l2rcq1+9p1mPa/86zMVQS+0C2o9Mr6jMxit8mn +hT3lQT+YBbU4heVHK8ltgTOqS9pFpZVY2to7e/O/QQSN8eThrdX4/5LDzrC jxK4Z5lf8tePn1B+s5vxzdME2r5y9HSq+4i2huXrJoMJ1LimpavZXompHo6P KkMJPPFggayTYyWa8IZGfG5T3OpjA/5dFRgafFjxfAKBD9duvHOu9wOm71Fz 6nlJoNI4v3D/YBnmGi/npmcReLno0sP2M2WoJHtnmUMegdftcdKGX4oJOTpb dr8nUMRV2TkhLEEL7xNrcmoJ1DPTyZxkF6Pp8yR5/wYCLwSJkvn97zFrzms/ 9S8E/m0rM/F+4B2mH0o+J91JoHaI/YgUn4lXHGMn9n2j4useyA0TvMWDjIi2 y30EthZVzB0SFmKt1ueQ44MUV/OsYk+SBZh9UWfTaj6BsRuPDAR8z0eDlWUb yoUEeo48FgsZzsOUgsr3z4cJlCtNK9wxmoudr3db9o9S3FzTe07mRw5a6pvw xccprg70MA0dysb1ZRf+6Z4k8CfDcN2oIAODJtS8E6cJTLYZ+PFL+BJfupee MpwhcOVov6FAlIaP/o08k/Wb4nTvBskSgoFxumX+C8RIZGsujQkiU7BS7vk9 mEOiWeAS/p/fk9F3vm+ZgziJful/e13uo2Nblc8v27kUt6z/vDaEnYQ6q7nb NOaRmGW7arsH5z5mtEk9aqX0TIPB3M39dzEud424x3yqz0sxLIY/ReNKP98r XZQOdk9l7qz5B2/xzH/9999MJ2pZu0xiCEo2lcYcp7SybPHRRuML2DthYXSe 0q9uLyjfdlcJdq4S4ztT2sbcw0vc1RuClm7J/u+/W/b+XwbNetfB7YPGnHpq f+AsUVf7Gg5RjekPbSmd69AjziiLgeJl2oEp1P30V9yS0lRKgIITPxjNVDyC 0Ulm5LlEMHtwTKmbijc1hZXeXPYYFsYwm5HKR8yIFnNqUTIINJzbA6h8Rf/1 +MBl4xSgaydqLp0lUD98kuxwZQDv+gdWCJXvJrOQDo2INAifNUiuovxof3Xe ya7gJWy7blTHo/xKt5AsPdqTAZ1dGjs4E1RfPhR5yFIqC9KC9kkVjhE4UTGS S1uRA6cTWMrulP9zyg3k9urlggtroY0NQaDbO6WpF4fzQLXu2dWb1FylE9Tc bOCVD8dDDyvf41Hv17paK/l6AVzsC2+ypuawk7TYkfUvC6EijDU9QNWrdZEv c2fxW0ippzFdqHp2Cmc+39bIhLm7tJZ/aybwrG9UzNef70DS/0Mlp57AT0f1 uReli+GJtat+eQ31Hk8ekeCqsyC4YpHtknJKF27I0F1TAtZr92Z0U9zxYp2Z W/rOMpjavlj+dTqBPSrakU2NZWAzmxPgyiDwu16oFcexHD5uWe65+yGBEQFh ue+8PoBnV1CZI43ALjXrNqPoSniX8lBVLJDA2fcmJdGKVWD/LKwmxI+qXxc7 Ti29CgI1MlwXn6HOm//cgsj+CBLZKoYeuwmM69hr9a6uGo71HONzrAhUc83p W+lQA+M96b6mmwn031sU5dxdAwoq49sv6RLIFIvz9xHUwtjPHXTtRQSuTc4J Es2vh00DffbvS0UYst8uvySxEWTmeA7FvaU45asiq7GtEaZO0aRsskV4Z54w tF6hCa7Pf/WH4yMRnnG+sTMmtgmWu6wrmusnQhPu9BP18GbwSzo3HbFKhLWv Fu8wv9gCU4eOHPVREKF0ccSvaWquB1MFp80LRSjHtvZM4beAq6dDrM+oEAtu 23hnuLVC6HAfy/+DEO1SA2QTD7aB73azUdJViG4sib/yDTqgMqUrf4rqP7u9 ZcT6vDpg+tflE7wdQtR1DHw6kkatH4lp8tIVYqLmZHC56lcIKD/gt3JcgBot fykqSHbCvOVzq7RCBaiXz+u0bOsCqU3yz+gRfDRfr22tpN8Lx68oF4cF8DGu jq1katMLPK9jhQc9+dj1+NZp61O9oB/GTmXY8FEy8bi0YVIvWPd8nVWVpHSr +zNLiT4InhlQDQ4ewlb5egn1jj5wDWCHfPMawkuZmzK1R/ug69Fvm7VOQ3hP 6ezWP2TYEH+efuOSyRCmip9v6d3KhuCq3I0jBA/zdMfkg9LYMOTM+JB5lIdh NSli6y9yoE56cSx9Bw8XTmm5SN/mwJgi7VjgRh6ahToZtD/jwPUXDS4/pHlo Re7vNPzCAb/IAX4vaxD3TMeRs0b9wPifcHW52iBmljucrR7rB9rbLzfd67mo eslWmHRqADIULpSMFnJx39/fx8uDBqCAUTrj9ZSLdYHnRxsTBqDL2V1c7SIX 5TT1TtIrBsBN1YcftJSL80Dff2bNIPBaPIX77fqRfoIfm9s5COahu1fFGfXj aPw22vqRQWA8uONbvLIf1coc+FGSPHgsVJ3Xwedg0y71+mlDHtyXvXZmbRgH ubWpL/+N5MHiCuLOFiYb98QVJzgZD8HUXM2r9nQ20js1HRR2D8HWqM1JdrfY WKBqtu21yxA0XBmQVtrHRonaLw4J4UNgvvWIfedgHxa79Cj+bh+C8ZSti7Yu 60MPTpJgly8f1N06mz69+Ya58rIS++IFVHkuqM2nfcN5N0hDnecCeHJGuvUf u2/I2R7nzs8TgMefctwBbjcaLX1zX7FZAJcPqHjckevGc8ahkrqyQqCdOsvL 8uhEo5lU4YZbQrg218Rrg1EnDtKUCw/fFcK0VJJG8uxXtLJ49tE1WQghtARy a/xXnKTT4tSLhbCnWsE/+n0H1od6/Gs3KgS9exWL46TaUbXlbs5ZRxG4ZxnS eprakONgql53WgQPJmW0VB614XiLt+lyHxHkTITXHdNrw0KJqu37IkSwxfRU msL+Vsz+vK76YpEINLVcZ/3vfUE1qzXeB+UIqD37tAmPf8EmfzULUpUAHe/7 FROaX5AWG25wbh0BjR6qxZsKm9HI3uXQMnMCWC6vm5XaKM7aKMsXO0VAZKTN Czv5RnzivMv+bDYBWz+mb1tLzWugsJduzCTAaunJtu8JDahVaerRU0bAOedl 7YcVG1B9imlT3kLAiEmA+s8NdWh2U6DbPEmA3ooduyrzPqNEab5tgDgJiey2 DdcMP+PVaLHk3wtJ2BfdopxgVIseScfr7qmQED3yTf65cTVmJwnuSG8iQb8o TO7Vm0+Yc/s6I8qSBK62WBDd+BOmhyrg0C4S+GdEpyyNPyLDIZi94QgJjycd TkcZVqLgibi5pA8J3VkGcUReBbKW2rNcr5KgUsdr3ryxArulViyNDyFhIOPi +WcGH1Dd2n1ZRAQJt832tD5ZX4Z24fdbmckkjJUF0vwySzHRatiEl0pCkc49 7madUjxckWs+nEFCbfKVePq6EsyJ3ax9t4CEFjfv0Ct2iHL3hxfqFpEgYZfW Er+bhVfa2TfpLBIso5T6bmx/jzWh9huWV5FADFq5HLB8h7T0ghMrakhoUFzg JANF+OnGetWJOhIM55kc2GL6FmOL1upatpJwpDJertCwEDta469md5Dw44xX h4rBG7RQHtox0UVCnLPnTKZWPo5HrDy0nEOCSd5N9c4/81DabyBaxCUhfmyi 7ufq19gw5bWFziNBmFoiklDLRcY1xjEdAQnBNq3HJJRzULTvFj9WRJ1XcVL8 u04Wynybw24iSXjJifdhrslEz0BZC2KY8lNuBXe+3AvMfcDUyh8jQftttWvk wlT8vGTs1fEJEuzTbWZm5zxH3fD5sZyfJLj8EeJ/cjIZ0/4abrKcIsGp9NEq T4rTFF1ZPoHTlH/65vPH65PwiIGPT8wvEtLnZSqfZd1Hy0GFpuAZEnQKCrqq Mu9iblFmtPVvEpI899zRMY7GoH7zTD6l/w8Ny5Kr "]]}}}, AspectRatio->Automatic, Axes->{True, True}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, Background->GrayLevel[0], DisplayFunction->Identity, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{Automatic, Automatic}, {Automatic, Automatic}}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImageSize->600, Method->{"ScalingFunctions" -> None}, PlotRange->All, PlotRangeClipping->True, PlotRangePadding->{{ Scaled[0.05], Scaled[0.05]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}]], "Output", CellChangeTimes->{ 3.7205505822206*^9, {3.7205506290834*^9, 3.7205506779974003`*^9}, { 3.7205507652178*^9, 3.7205508172511997`*^9}, {3.720550857638*^9, 3.7205508695095997`*^9}, {3.7205509660592003`*^9, 3.7205509736166*^9}, { 3.7205510038634*^9, 3.7205510120534*^9}, {3.7205510530797997`*^9, 3.7205510854024*^9}, 3.7205515117328*^9, {3.7205515481642*^9, 3.7205515736052*^9}, 3.7205516147096*^9, {3.7205516665174*^9, 3.7205516872724*^9}, {3.7205518655615997`*^9, 3.7205519257782*^9}, 3.7205519820706*^9, {3.7205520243576*^9, 3.720552067888*^9}, { 3.720552130385*^9, 3.7205521577292*^9}, {3.7205522073718*^9, 3.7205522136324*^9}, 3.7205522459082003`*^9, 3.7205522865414*^9, { 3.7205523683334*^9, 3.7205524104342003`*^9}, 3.7205533078761997`*^9, { 3.7205534114561996`*^9, 3.7205534652125998`*^9}, {3.720553498678*^9, 3.7205536624602003`*^9}, {3.7205536983024*^9, 3.720553876859*^9}}] }, Open ]], Cell[BoxData[""], "Input", CellChangeTimes->{{3.7205510946446*^9, 3.7205511564118*^9}, { 3.7205513609588003`*^9, 3.7205514539074*^9}, 3.7205515683148003`*^9, 3.7205516690446*^9}] }, Open ]], Cell[CellGroupData[{ Cell["\<\ Comparaci\[OAcute]n fina entre las soluci\[OAcute]n num\[EAcute]rica y la \ perturbativa: izq. las dos funciones en el mismo gr\[AAcute]fico, der., su \ diferencia.\ \>", "Subsection", CellChangeTimes->{{3.720553886375*^9, 3.7205539449634*^9}, { 3.7205540206661997`*^9, 3.7205540214628*^9}}], Cell[CellGroupData[{ Cell["Posici\[OAcute]n:", "Subsubsection", CellChangeTimes->{{3.7205540267200003`*^9, 3.720554031557*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{ RowBox[{ RowBox[{"Show", "[", RowBox[{"#", ",", " ", RowBox[{"ImageSize", "\[Rule]", " ", "400"}]}], "]"}], "&"}], "/@", " ", RowBox[{"{", RowBox[{ RowBox[{"Plot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"xsol", "[", "t", "]"}], ",", RowBox[{"x\[Epsilon]", "[", RowBox[{ RowBox[{ RowBox[{"\[Omega]pr", " ", "t"}], " ", "+", " ", "Phi0"}], ",", " ", "I0", ",", " ", "\[Epsilon]pr"}], "]"}]}], "}"}], " ", ",", " ", RowBox[{"{", RowBox[{"t", ",", " ", "0", ",", " ", RowBox[{"10", "\[Pi]"}]}], "}"}]}], "]"}], ",", RowBox[{"Plot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"xsol", "[", "t", "]"}], "-", RowBox[{"x\[Epsilon]", "[", RowBox[{ RowBox[{ RowBox[{"\[Omega]pr", " ", "t"}], " ", "+", " ", "Phi0"}], ",", " ", "I0", ",", " ", "\[Epsilon]pr"}], "]"}]}], "}"}], " ", ",", " ", RowBox[{"{", RowBox[{"t", ",", " ", "0", ",", " ", RowBox[{"10", "\[Pi]"}]}], "}"}]}], "]"}]}], "}"}]}]], "Input", CellChangeTimes->{{3.720551698784*^9, 3.7205517053244*^9}, { 3.7205517430552*^9, 3.7205517476572*^9}, {3.7205539495352*^9, 3.7205540157813997`*^9}}], Cell[BoxData[ RowBox[{"{", RowBox[{ GraphicsBox[{{}, {}, {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwU23c8ld8fAHCEUiQZUfbM5nK5Rs6HIqNChb4qJElDKqSUFNmJpEGySqkQ yog42RVlR9l73HsfqzJCv+f3l9fndcZzzudznuee9x+kXL32n2BjYWHxZmdh +f/f6nPRFUeCM4y2P/16359IN2rnaeuYLQ1GciIYvTp6E5VEbm2uK72HJoNd 6a5H7yLVz2V780ufooUPibs+H0lD7h68t1+UvkUqrx++T3fMQ2toNOX00iqU 9+b3jPT+CtSc0uCfUtqK/P751XWrN6ONmRLHrv3XhsIdBO84FDYjy9yLu/+b b0PHfklzRRq2oOqPwgL8Wt/R8LrGRG7zVlQ84JYd+qoT3an9HmF6uB2lyqz0 eSb0oLjdJ3tPnv+BilsfSCeXDqFgZxz2M60fCZezGWnwDaOz1N+K+kP96HLm uf8q3YcRi0sCB5IdQHoBZrGjfCPIuYHmoJkxgErk/6yoeYyi3zHh0aHpg+jD FbsfWGAC/bUNnz8SMYxE3Sp+2Z6eQIf2rarRqofRtX2qm4bxBHrOi2Ifrw6j HTIcu9edmUQnqM6n5i6MoPKGd+9sKuiotoDh+3b/KKqQEIgd8CTQ6lfV5val MSS9/sZr7yoC+efuOmqnOo6CftFrOUSmkEBpeiByHkcmn6tWFKun0HiwpfOe inHk+v49VS96Gr04rFwhdH0CxeV47WQrnkZb/zMTff96AlU+lbOtH5xGj+aE m4o6J5D0nbtnj9Jm0Jqchb1VGpNoyPXU05tDM4htuYV9uHMSCRySyLPcOIvi 6g179VjpaNfe9nJ+vVm0o7j9Ze92Onqma/wz484sulzYELDxEh25cYvwfdGb Qw+X9W261zJQPGuj+D23OfQrO5zruhIDVf+5pXIkZg4t74TrrnsYZIqndxPD c8jI+sFzZjQDjRR8ur459hdqnC10HF3LRCyeLgUcxb/Q8czqkEfSTLRVdoG+ 0PcLsf2YPJdkyEQ2cQr/9an/RslTncfun2Oi0xY4psXhN3rWWewUHspEISwO tTWBv9HiQiH35ydMVHIuVCur8Tc6kJGho/GFidrkxE+nzP9GlihDxK6Piaa6 C1LjJP6gMl5n3+o5JpK1GuG54vUHrXpJnAjcSiAjtoBdZx+S7TxUl88qBPrv vcBVZ/wH9axIpzsaEeiOwq5xU955tMDzaM7amUCZvV3ierrzaOriQFP+OQJV 3fe2U3GeR5JHFc45BhCod8+G2xJh88ja0NrYLIpAC2ueVm5+M49Mbhh99H1E oM2l+oscHfMIP/rpMv6MQKoXW9QXV+fR7d/rEp7kEsi1n/VJ374FdMYq98XX GgJde5jQ2nJpAUlMhPntbiTQw32a62uTF9DDo2OsbJ0Eyuf4DO9rFxDhPM2+ 0keghg8uflnEAoIX1Ua0MQKNei9kpwgtopeTIZ5vmQRiVY4djjNaRKYDdtbn 5ggkOqiwLdR9Eamb2Kd7LBBIJwHbXrmziG5VZ8qmLxPIxsYh/GzhInKR8Irf yjKFzqydKnfuXUTCbp55zWxTKLQ89Pd+ziVEv1LnXMc+hVJ9xVXM1JYQk6b3 4i/HFCpRKXTVs19CL5UWY89xTqH2ob0JKteXUGbnDnlJMp5OHGmUeL6EfBp2 nN9E9l+/P4CT/9sSSoxRv4zWTCFZLsEdnH+WUPpri93Z5PPRxyzvRbG/aMur ytH/Vgjk6LfrFcP0LwoWaHY2XSSQj1p3f5/nX1Q0Ll3n9Yus34j3ltb7f9GN BzLHfxAEepm0YV9t2V/UkFkYFjROoOoDT2+9H/mLrr7B4WcGyPqtNyjN4llG 5/SlS+J/kPWraJlJoS6j4B8VXqtNBOK/cnr7vaPLKFE0aCWzjkBqGmzOoSHL 6N49s6L4MgKZjyXcv5K9jKy/zU5X5JP1TNZsONu+jPgpbv80XhAowO4zm8vK MjJsrrcfTCTrV7XgZbZ3BdECZMw23iDr5x/7XM93Bd30/c0feYFAY5rbe1Se rKDfl/ziLV3JeqU6WPIzV9Dus9YiScYECr1WKNt/exUxdop6xc0zkfk207L1 71bRypO/WtlDTMRV0mpH7VpF3RF9FiKNTHR7fjo0UvEfkqhsfzr+lInuXVSe 0K79h0IFzub4mzLRQb6Sm87Mf8g3Wf6ljgoTbTgky2O6ngWmIt6/ttzMRF// 5Gd4abKAF99o2/VuBrLRbvpeHcgCKwWfNmqfYqC84C0yjvdYIFOiIKXBkoE2 tzp5TT1nASFBnf01ygzUdoG5dus3Fsj5djG+i05HDm/W63mJssKWb8NBH9zo yEnJ9LHIe1YIWlrkc9SfRPjK7bGcBlZICai9G7R5Ekl+btXa1c8K4vtvZYlP TqDBk64N59ayAZ5oHCl8OIFOZASuVNmxQcXl9fq3GePorGSJ87lZNoj8Z2yy EjCG/IXUZauU2cHnpMtCtcUwOvMv1JHVmB2KegS6XDcOoyPjvbHInh14xkoU Y1uGECq5s1J6gx1mSsX2pP43hNidiO/v2tnB9FHVi0+ugygmIzvieSAH3GT/ j6fOtR8901aZimjlhNryJ71cVp2ocb9iic1VLrBI8j952a8YFYrOssvGcMGq T7q6hFUhShotsZ5P5wK+Y3e5z4m/Q6f894w8+cIFfZcZOXvC36A16V6b6CLr IfaKy/pPWklId6bAPaR4PZg77Tu7/vMznBJjwl/yewMkcs/pF0XV4tD/NjhF c3HDoYO8VutT6vBZmbZMFzFuqE4c8lvN+4T1ik4YrTXlhmOlZstF37/g1t7w UwfjueG9hvCN6a2NeK1aIyYoPBB8jj5NrWnFXg2Hz8qc3wh3/f7Y9sx04VF1 alpKyEZ43jJUkHK1Gx+5t/H7tscb4a1VwPZv7D3Y0rECCdRuhJ47dVHHBHux /Lg8P4coLyjWZMLNLf24d83s+9E6XnBny2OJlhzEdifrCdceXvC2yAhZcR7E DV+eyfTN8kK9W3HT2pRB3PPpdS194yY4XphmMbhtCNfHOGkM622Cng8jlf7k L/ELseo17TGbIE8y4v2joRHs2qghfi9xE4xrrpWu3TaKxW8+odlmbALna85n vQ6M4vjhS55fSzaBZNNxabWKURz0WrGjZmQTiHT/Pa/wYAw76cW8KjTgg/CF WPHTshN4K/1vtY8ZH5zrz9t46cAEbk/y6KPY8sG2Y97O/Tcn8B4WE4E37nzQ 1OAk/rl7AuvX/Qp4cZcPvLJDZt9HTmIhO0fbR2N8UDSRzZtUQ8elH3ftkp3l g/diKR0iE3TsoqKum7vMB46n7ysNbmDg12vYxT7xbYbcl0Ov91gzMORnj88b bIYrj4QK3L4y8KjYo65gs80w1P5FkY/OwFERQd94bTdDyZeR5JW1TPzdxeGd gvtm8L5e6HoXMfEZXtYbDrGb4VbcOpPgDCbedJV+cShxMwhckwnaWMbEhaPt J7wyNkPj9ZkfTa1MzFL+yiqsZDMsbzGo/bPKxM8V7xvx12yG+JYbdof4CWx1 P1AzpXEz3K1jn2XIE/jB2YNbioY3wxllnvrXVgQ26DRav3NqM3B+xaltRwjc v1Nx5dviZqgbunxd1ZPAoW/4px3Z+eEd7/OCgmsEVt62Oji6kR++Tb97eDaK wE2h4+0XRfhBVIH/km0CgS/NtnxaleGHZ/vV0o8/J/DHzy9yhPT4wRi5KfKU E/gENS4tfSc/JPxLgqefCLw+7Vq82j5+4Lkv+J9bC4FzuU+GlRzih4faVCmb LgLbXbb1NzvOD2r8x3e7DxF4acjAs8WTHxpOcPo/nyRwqrW8i9Nlfjh1LPTk phkCm5ZuOjAZxA/L+pblT/8QeFL+r+mlaH64ofBexeUvgWPiRmhsj/iBflj/ mOk/AmuvNirfSeeHq0KX1h9gm8I/T5WIb80m9yNe8TucfQoHtj/je17ED3Y/ CeUxjiksaxzDTqnkh5Ozzz54ck7hL1lX5ssa+CGOJ6JIlIy9hN0mLTr4QagV VH6R4wVu7etpH+AHrckLSr/I+d9P0ZqOMfhBaamiQpRlCjsdlqli/uEHvVff Wc8tE5i9jqfwCqsApKfZLY3NE/glZSGTg1sABBbdSyNnCbwvefDxXSEBYJNe 8bNnEPgX19c7YlICkPNF/LHVCIETfItuvlQWgDWmvfGnewhsNJDmQ9URAMbg 3va3bQQe3nP7ZAUIgM2fwAaFegJHFF9y3GslAKLNoZO1HwmsJnts7w87AdCr 8Um5W0DgthgrOOEiADGyRw6HvyTwlb9UrZnTArDe2PrO6yQCi5+UlA/wJftb a778e4fAp4x+b7gfST4v0U9C7gKBw7cKR5yJF4CrawuPiLoSOPOPPqdJsgBQ uw5edNpP4PGcGyxTeQJAU3pZXKNB4HVRTwNqSgUg0uk/CkOcwNtP1i49rhEA obPOQi7cBPaQ4P5t/kMAJm+5vqGMMHH4X7WLEkMCMFPpURDXxMSZHbZTvxkC 8ED23pxJKROPxzycSGcRhE4OkzcP7zCxB4tM77KCIBQ2KOxUViXHd5sebtUU BFOFYUV5fnJ8sUfnSwNBUFHYc+nyAgOPn89psbcWhOV2/gn5CgY+OaBXl3tJ ENp7Vdg/WzKwe6VNrluNILS2KpdtBToOTfZWNWgUhF79k+HconT83P/BK74f grD3o9ibk/OTeJTS/aycIQhHTu2Uds6axCeenkwQFhCCc1xu8pd4J7HbretB Da5CcL/Mb//p0nF8yyXtX/pZIWjOTOS9c2ccPzOsvnblkhBIXvPx0jg2jod/ cfnJRwqBWoZt6h/2cXz8xP0zN/KEQJ1IwrlmY9jVLOugNssW6PseMSH6bgRb enWY9a3fAgvhIi0nr45gyiM2vUjBLRCNZnOpJiOYbfKQWL/SFrAxP5B17Nsw fhrNMRpltwX4QmcE1QaG8HCbk9/Qqy1wR1VVmDI7gN2P8yXG2QnDWRUDvqak LnzqxqW+6VciEPLa5UkrpQo3iPw8PPpOBKQ5FU/3iVZitbc7OrvKRQAdyfBJ 56zAv0bYm2tbREBhtezFx/wyfN3qXmXSkgiczd3q7rnwDscL5WaYW24FdfNf Yvvyo/DHrIkzqRNbweuRmmZ/KEYyZnvH789thXdaoi/+/viIQvty3aJWtoL7 Ze/0ndMVyGrz5aOX+LZB8SsT6vy2avTdj9N6j942kCjwXnfO6xOim8hQFsK3 Ae190f49N5uQ0I8jC9bbRWEg/OXs0e5O5KpitJefIgp/RMfOHjzyA70JlEj/ biAKgVsjo/u7fiBz+UGro9aiUOXHvvLmx0/k730y5fQlUWAZXagabexGvTwX zUKqReHRrxc8+vv7kdKxA4/Nv4nCcsfeBcs7/cjvnfb0hk5RmDfZqr/5Sz/a dHg+IY4uCts/pZwshwFkknmNmbJZDLal3ec8qTSInpuExZe4iMGuSk3xWuYQ mr3vMRFwWgz2X7l8+pHsMEITFkbGPmIQXOrIueHwMOqM4R6vCxODsNGrUfW1 w2h9z12D9hwx8Fj+4xKXMILO+SUNTi2LgRGnybW/SmOo5EuA7ltOcXBmvf1B 8fAYWivufPvSJnFQ1lSvH4gcQ6nVUjorMuIQO3nvw8T4GGrhexGx3koc3iXK 1GumjCPdrDwNuQRxqNjo0+M1N4H27Hm89OGpOFys2kBZFJ9ELoxb1QdzxEFW 509Oj8UkilQ5dOhWlTiEXLJwyHsyibqzVgOHmOJwkG86xH4HHc3sGbe4uiAO ezkvNkQdpyNOZjM//xoJkBMKTOGNoCN11YwXJsIS4Gi5o325mY6Csq0a00wk IKpWfMHkMAM93EtN0NsrAQ4/0fnKqwyUxRQ/3uxAjnc/03frMQO1q87+YfGU ABdL7kdfOxlo8mvXx0d+EiDdLnTE9g8DrXrWRGoEScAtQ3tufn4m2p7zSNzl oQS0ciTLW1ky0Y59QePzaRLAm2iwAbsx0X7iTH5MlgRYJ8o2n7nORFfVkBmu kIAeTgOXM2+Y6FvOiKc4g4wtnU3G1xJoaF+jbuEfCeAO/7bAKUr60a+b5QWL JFw2j/xur06g2C21X4w2SEJcktqh0AMEShwreRO5SRLWtuvLurkRKKPoTfx3 QUn4rD19xsuHQCUOCU7nJCWh/KRZz4Y40ksKd3aWyEnCFoOxpccpBGqcD9rO qSwJ/DesDjpkEehnnR/Pfg1JWCC+HN9RTKDhh2dnn1AlgRvKnu6tIhBx8ljH hL4kJCr73wn7SvpK1/4DFSSBceq/5MnvBGJbZ5V201QSLN7m771EepanE4V+ tZSEv7hHSIn0rHCm9hkRG0nY8bLIh4P0nPRlRZsTdpLwqe4C1zrSeyrm4tQ8 R0noyk8r1iQ9qCPMv3XFmVz/3pUzQaQXYXztP/MTkvD+qj7PEulJq+LlofjT kiAoyRv6iPSmffjMp34vSRAW1/x4lPSoy6HRbBVfSdjwn32GBenV09u74i77 S4LOO22JI2Tsu9DoVx0oCQObg7bcJ/vf+FR9ZFOIJBw49MvvFzlf5KP3xkci JeH7SWMlf9YpFO+RI58ZIwlB30IU5VcJlEx7uuFXvCRQZGQ/LJDrzVz3aBol SoLV51LDWXI/bztvt0elSIJjE52Df4pAS/1P/l17Jgk2rtEm7aRfTSZyFM+9 lIRjK0UeXaRfI2fwAeccSaCarK+U+0mglsWmAJu3knCxWfrRu2YCbWUbfGFc TObDKlU7/BOBjq2fa6aUSUKFrdRAajmBprcKygvWScI23Zex6ZkEosnI23A2 SIKxXYL+7SQC3VDW9Z9vkgSX10VXP8QQiNfwv28/fpL7My7aNedNIPtdpxe+ 9EnC/qfaPH/J85S856r0h2FJ4A0UJqzsSC8ffXIpmZCEJ2NW/vVaBLp0Iic1 Zk4S4u/ruv+VIlCZJ/5yY0ESRFkq6Zd4CbTn+oD4cTYpEN9L33VgnInOpMjV KQhJgdljLWrhXSbKf6EzI7xNCnbZOD108GeipTe7t62XlAIZzk1cVq5MFPnx lBdDUQp2hokVKGswUeZA9pa8HVLgfdcnhVnFQNMT5cbpJlJQzJpvqfeCgXRn G8/c2y0FvzazNvdGMFAt2yz2tZWCCxePdRnsZaARGR0P/RNSwP1kXd+RBjqS di8vrrotBa/sPR1Q9iQ6fa5x8N1dKWhUGuN6GzqJ8i/1cz9/IAUfsEThPedJ ZBzGdiw8VQr6RS0V03jJ71emGdfed+T6D+gNbj41gZ5Mfvvve5cUPPQP2RzG No7MRdzKNQekwGG9RphP4xj6tXtROnpUCmp6z91qfDyG9mTIMHbOSMFQ17uL 7ZQxtOx8+XoepzSMXvv36qDjKHJsl3p6W1Ma6i5pXq2IHUZCH30YJmHSkOm7 VelAZj+qJLhsk29Lw1Lg0SNh7v3onFhKweJdaahl2zZwXLYf1fh/vp6bRLan 1o/pGfUhH6o4n3i+NGSXf7t5XaoHtbyqoy52S8OdPyg1uKET3bm/NfANRQZY 6jaM3nvQiNTTiMYZXRlwv7la+s33G2rKqpTU3iEDw2KnfgQc/Ir4qk9XFu+W gVY72sC+TfUofraEo/II2W50occuqBYlWB++3RYqA8sSBz0dXpagZ1xJCYs/ ZSD0YsTTsqfP8PsAsXc7g2XhqErP5oc1bfhBBY+lcrgsiG/6sknVoh37cKz2 bY6WhcAT6RfONLRjjejeDYMPZMG7enGho/k7zkxKOX7jlSyk6SUKKnd24kel UvxlzbJgMgPekU3d+PKi3EUdSTk4Xmreyq8+iO13CK0Tl5MDPkUFk2mPQax9 kzOZQ0kObgrmqvmlD+LpdWOf27TkwEbEfuK6wBD2EM6U8t4tB1dvLn7c92sI H9JVan5zTg4wf1N9ftoI1rm69eRDbzlIL7v+Pbp9BAvg9SvXL8uB+bnH2cvr RnGTGX37viA52LLHnCv23Cg2t8+6wbgvBz59n9AJ7TGs66umoVgmBxLrbK1v vxzH/n3pLFcr5eBIWmpiwY9x/MFiS3NDHbm+BdPaXVwTGMRZLp5vkYPmZzGD 0e4T2Lyu+W3RmBykrAZ+fCwyiSM1zW5xMeVAx2Hjuepdk7jhccnBw7NysC8v 6KSp1yS2Of/09+qyHOw94+NnUTmJD4n46pptloejklXNyi50nBg8sfbRFnkY cIkaHQ+h427m0c4JUXn4XZoSP/OK9G6l2ZVoBXlwCkwv65ul41NnhEvbDOUh bPsRCw5/Bs5qvx0lbyIPsd5P9X8nMDCBWI9c3i0PzcHhm+XeM/BFgcnlbfvl 4dHbxgT0m4H9y0qNjp+Uh47bDf92uDHxBwUN3oKz8nDF6JrEhutMvHr3WR/n RXlw1+bz3PiQiYPco2+8uiYPFJaJ4vxaJq5uYrVdvikPz2doIbY9TMxpcElq X5g8yC3cNZCeY+JIXufKmbvyUBNbuWwnSuCGK61xOx/Kg8Ln+v1F6gTeOLz7 +P0keRA6bqy424TAccUa7Hov5GHbunYm4UZ6RzqjLTJLHrzfyypw+BJYKFok oztPHjqFd/mZ3SLw42NsZjc+kO33wvh3pxK4t/6SUEuFPMSHu6lzZBNYUoc+ KlMnD+eW08bpxQR2TXUu8m0gnxfn1LRUReBn69vC6prl4Qmj2E/zG4FHfcwP iXTIg8CbRq+YDtI7fR+2n+mWh9vXKiwE+gl82kJz8cOAPGxZyHqAxwic9Tbj 88Yxeaiuzh2LJQhMiG1NdGHIw4sQ+tewXwTWCL9zOn9GHhp7rv58ukjgi7Ns Buzz8hBV2Z45vELgd0f8Ntgvy4OVRq6YJesU/lNL73rBqgD7+Ox3tK2ZwjRN l6xFTgWINtTkDia96/+47ZoVtwKwRby+Y0/69gOHxd4nfArw7Kva531kbJj5 wzVeSAH0fiTn3ST7l1qevhy1TQEe/T3x6Dc5nz5zKTpIUgGKiK03X5HPK4mJ enpFTgEizh70Sl0lsB5F9P15JQXgUH/p3rFE4OK2rG8n1RVAcvrNaWvS7zS/ HcNO2gogf5rnzjrS90Ui3xbt9BRgW9Kw1Bo6gXU+OPHuNVKAoxl7w9AwgQud pmR37VSA8hpnifJuAlNZb+gbmCuA0A6KVSDp33dPN9lQ9iqAjlX3mWDSv9pm aScU9yvAjLrv4JcKAr8d17wq6aAA4soCm+yLCJyveuD5xmMKIOxWIaBH1pvS NFTK4U7mR2o1++49Audd9GlePq0A1b+eBKmHEji36P7ypI8CyJpzfzU8RWB1 R/nNg1cUoMHjamr2fwTOWS5U+HFdAZJ3liu6WxA427hzf124AgQqqEjlyRNY ZdjDozxaAS7k8szsEiDrHboYUBCnAOZz6voyrAR+Vb/15dMkBbj+/Onfik7S q3ZH/wXmKoAYrePWk0Am3r7AFPArUAAlo/HYxJNM/CLxutK5ErJe3gsfx/cx 8fO+FLsj1QrgfsFx77VtTPz01OBrWqcCnOf/7ZeYxcDS3N4V6j0KwMz5cdAg hoHTc9Z0yA8qAL1d+Qj1AgOnzsmyCTIUQG1tWICeFgMnB5w8NPNPAWRKRfnT 39CxuOSC5zj7duCbbrBSiabjJ5XhwX1c22Hp6Ndx4dN0nLT2Vc5X/u3QMP8m WFyajhPuMthfKWyHRDvZvH+Rkzg+40Keq/V2eOKxzx2MJ/Dlc6Gs1Qe3A0v0 9TWDfBP4sO5jWznH7XAyWWl5aGAcS3+unhlz2w7m39pVNt0Yx7mMLRRP/+2w Ye6lr2HBGG7QKs/3y9gO1Wzj0aHso5i9cv2723+3w7eb58s27BrE45ES7ASL Ioi1mX45wD6I6w9oH7TmVITszgqGbvUAjhs5+ouPTxGuBL981WUygCW58rQf yivCKwWN01UG/djQxqEgzVYR2KOs95obdGOf3qeFhS8Uwa9M4pT54Va859b8 7GqWIoRrp0TvbGjBckpW6rvzFeFtsIjoqGEL/u47+6LjA9n+XZdTVawZ6/IY Jyw0K8KNs4OTcu++4iWD3qv6y4pwKs8nwSOmGt9IEDYut1GCALbt6uwHY3H0 wej6mkUlaAowanQ53ozSKSt73q4qwe6fJgaJE82oeJPnt9Q1yvC5419YpFcL Gm7Y03yVRxnqqyacQv1bkb4pd4emlDLobZ2Cl7fb0Tg1avCJuTJscug4dT3l B9q5JWLR96EyVF6Wgo7CfnTo94L/8SRlUN24k3t5lrx/tHos26Qpg35+nmer 2gBKjDH/p/xaGXbvfHcwPmMATa9dxzFYrgxJdqwXdGMGUfJC6KZ9o8pws4Pj fJ3tMFr8cUtBnqoC15dKjZcixtDF3stDAfoqkHTtwlB22RhiDJ5NaUcq4K3V 5dM0PYb66Qe3hFiqwIWTgbyH7cbRpxXZtcPOKhDfulfswJYJZMImUmVwQgXc 4s3OWplNoA+cPIH3TqvAJs34I898JtAb3t9/THxVYOaWt8KFxgn0QKpmNC1S Barr/901DZhEm+Tfpy/GqAAXe6fQ5hekT5WynWzvq8D7+yfOajZNogCt+99Z UlWg1C1in6skHbmZnqh1LlABSx4b22PFdNRr8V9QUYkKVJ1VL3/UTUeH9u01 4v2oApfd7ocIsTDQHgdqYfkXFYAFlfHeXQykdYrjuVi/CjwfVX/tX0P61HPx mO+ICmxl7LH/MMRA8heZYl8nVcDpqO8hPVYm2nq1/f613yqgFFqwu1+PieID P9u2LamADH77Yq0dE228VcajwqIK9e6Ru054MRFbdEZI13pV+JkWsa08jYmu 3U0w1tqkCrv0D84XvmeiP/ejVyIFVSFm38qNgSYmmkj29dWXVIWSx7HLdctM 5Pr0lGacnCoIZX8VC+IjUPeLo8wJJVWwpt+xOi1HoKZc0xMJVFXYmbJTucKS QJYFelIz+qpwlRnBrXaE9Od71R5zUIVbIkuHas4SyKhcKiHVVBWSYnZsD71G oKJKQbsFS1WY5Nr42CuKQBp1XHw2Nqpw5U2V8M0EAr2qX2l4YacK2XVlCiXP SZ+0jexycFEFLQVb/jTSP8I/frC8OaEKEo6ty3s/Eyiu5+sHzjOqMPT9zF3J VgJxD1ZcdjqvCnv4YxyEuwkUOlqgXeirCvIhee3awwRiob+c5rmqCpC+O86X TiD/qSdZJ26ognt/Df/PGQL9mrvrURaiChYmz/uPzRPIcyFEVjBKFfzlahO5 lwkkS30gtzlWFUprNl1K/Ufm58Jzed77qjC4yBnlzTaF7uUUKnAnqgIlnNYZ wj6FLOm127lSVGFGh3qkg/Qn6/YORc5nquDWcFvQg/RpsduY0pqXqtC0sZGN RsZeafPKLDmqcK06Sno32V++d63qSr4qvH673/s+6dWercJqS0Wq8Cz97Zz0 /73qsF19/gPZ7mCUPkX62SqepvGrQhU4EoIC/pJeZWs215ypVQUnvT/hZr8J 9J7nPwpRrwrsgk4szaRXz1ue0qI3qcIY+/6djycIpBB2RXu8XRXO2izmZQwS qLcqgjryUxXmja5mTZNevc+SqDPYpwqMLf/irrWQ/tvxSrdvWBVypbNqLMh6 rPEvoXVPqMLz5y+fHSJvhyWFX/R+EKqgTRePffmOQBfmfup/n1OFMl2tccOX BNquQTdoXVCFjFYeHv4nBHr4coPRVzY1oNZX7YgIItC+0W3oy1o1YG+cUlPy IRCnjArUcatB36YLk7wnCOSTtMekQkgNZBKPRGftIpBNTLRZgZIaQAtNzOgv E61teLI7X10N/rV7/RUeY6LydTnmb7TVIDjn2w6jFiZSCfpm+dJIDUZ2DC+d fs5EXL681k/2q0Em773Yk2ZM9DFPwibRQQ2+8PHtzlFhosuEuu3DI2qg5nyl 1GwzE42etDlw153sn/g4/3wXA1U63nUI8VeD1WkluZoTDHTlYdqhoEA12JY5 ZVloxkAabXn/Bd5SA2a8az2rAgMl7205fOWOGrxRiYnMGqGjq8Dv4pmuBvO5 LY0XDtORtvx9D7svaqCnrrb2u+Ik6kfDdnqNatAofiqgkXUS3f5Pa6dYmxrs NLHau+PHBBq+3Sw20qMG+x9ud7gaOoHi53hafWbUYPbsY+4XP8fRr4+hO+KF 1UFOzNuPeXoMvTt8eXOruzqU51xIXNYeRi6+df8Kz6iD83CSv+rqEOKOEWIm nleHIW3NA/9qh5Bb5bs6V391CHl9LjrKYQgJKM5cm41Wh5kUWUFPn0Hk8+fU GF+BOog+8DoUldyPEj+pOmWyaoDpM3sNi6s/ULrHlovW7BrQ+Oft+b3TnejV OtbQP5waMK/MLP7u1olKzNuyd3FrQPrStte39nSgn5/8V/qFNODwkFn9U6F2 tO1zXZKIigakGX998/BRE0r6fKwr0l4DkoPEnK4nl6HkL/cPeb7WAPqBo8d8 T9fimlAe3rFsDdCJuN8QElCHGSYhNS65GnAnS2ADLfYT1iv1oRws0ADLNcfl z7/7gtteH+A2wBpQ2e2jmDf/DXNF831c16oBQtbfdrzNb8U+1tEKz5Y0YPZv Z+BqTxd+vIGjV2xFA8SGWk34jnbjyrpr8Q//aQClY9fc865uzAtnWaPYNeHW 1V53m44e/ErDquvCRk1Q/bo7zeZTH+7n44pB0prgyt3Dur9uAFu13frz00IT 1s7UWzjtGcHPnhp9idijCaWLwsnNISN4+eLCE5q1Joy3XhKsLR/BOXxnTR8c 1IS6rLFOJfVRvNn6QLytsya4p3I4vOEaw52fpSiffDRBJ1Nsnu3ZONZM6OLw 89ME82V148y2cRzpcf+HnL8mhHu0ceWxT2CDtVw3gwM1QeJw2tKI6wRO3jXd aBSpCXZujPjXWyaxGy73LEjRhGvNaUvix+i47M5lY7d0TTjVEc2jHEbHQk4U Qf4MTaicPhYYmEXHdcsZH86/0gRBj9fb/v6iYyX96A0qBZpg3SQQwBfAwMFc u/t+FmmCN/PbfuoTBu7uZHkbUaIJou7o2/0PDBzt5+M4hjUhPSbUc+0iA0+/ O/wy/YsmhNQH24R7MLHFLcEA26+aINQVb382iInTDzTasDRpwi6rvjtBj5n4 wKzJwtF2TZgecs43rmfirIrleu5OTbDPa3s7PsDE7HcLU0p/asJzkwcby+eZ uFBdabdIvyZMLF1bnpIkMO+/oa2fBjXhbW1/hqU2gT2+PSEujWiCSurG9kYz Aot48j1om9SE4RrTGTvy/n/RsP5UMFMTLJJg9eAVAn/ZELKDMq0JbyYmBK6G E/jaq4XhmN+aoDgiTNV/RmDr8WY1yoImxK7U70rIJbC0/OvLbUua4BDKLSv3 gcB/jt+qvLSiCXlijdY9tQT+nHaUW4SFApXH1plWNBE4qU/HvpSNAh+ms240 /SDwebFNqUc5KNDskRe4fpDAOw9PTPxbSwEFj/X43ATp24RKrfT1FAj5DdXL UwSe+P44YBcPBXYasTu8+03gDwK+daO8FJiMiTx6n/RZ7P59fBGbKbBvTLM8 hfTb8ViFw8qCFADjQ86tpO90vrFkfN1CgXuJhxU02Kfweu6fhNdWCohNJywX kD7ssXhL2yxGgVyjCzVupB9zw24HvZOggEQw8jAk4+CaEw320hRAJa71hmR/ +zVIaFGWAkP9tPYTpCeVjIVdHitQwJLW71vEMoVXrs+83KFEAW/h5wOapG+b PnyZ61OhwC3b0VPtC6S3l57uCFKnwNWiLS7pcwT2owWEyVIocEQ8TzCBSWDL S/bNtdoUkHNU7H4/SmCxd+rbTulS4LvRPDtHH4GnZ9ad2KBPgfOpdwf8vxO4 Sn0wJ9uQAnP7vaq2fSXwA8/SBWtEAWeltctjlQQ+9TreZNaYAm+XGrv7SD8a Tnjejt9FgZu+rhVrsgg85CYp+cOCzOeVv3Itd0mvpi+eurqHAvuLcwWuBxM4 sr/lrZg1BRzzvn055EN6/kjIbteDFFiKzD795ACB1yQ63WV3oIBdnXTVOhMC f+/Q7Xr+HwXGfU99zFAnz9OByXN0JwqYDrSG+q0jz9PdquLoY2QsdvlT9hwT SzcmsWm4UUBQaqxLuJeJP1taP/A5RYHL9sP4bi4TC5m8K1vxJvORnHJeZQ8T TwRGr029RIGkpltUBU0m/lDmbmtyhczPNYPDzoJMfFxPZCT0OgWo2idEbncx cK7Gde5NERQ4avj0+5IT+T6fc7DPjyLPV6xiN5sRA9tnaaQevEOBrKPyEftF GXhFYUgr4R4F1Pl7Lb59p2NLCfPD0slkPf9klR3dSceGV97sfphKAfuFNckn JehYrVVIm/spOV+HIXfX0iTeHDbC/ecFmS8L85w1uZP4BxFU/jmPAiOlFxsC +SexR3mZ1IUaChTkml42+ziOHYXlNo7WUeDjmTyFkHvjeM/F20uOXygQOBr7 3MR9HGvIH27d1UgBrsOZyWj9OJ6PXrgl/IMChbaD1z32jOHQo1rjmEGB9qEy 0cKSEXy5KLFNe4o8T/QIj6jQEXyaj63i5QxZX40fFn9sR/C+mqaEe38osEUr 7Enc2DAWVD1ndZJFC2oUDFJ4Ng7jZ8uZORsFtOBGKdq912IQVzwW9z1qoAXU cE7L2xw9eHjdp+trjbRA9PJIoF9AN1536UJ4HmhBft1R/uZfXdjGpvoxh5kW iMvEv+8e+In72U9XZttowXD1rrD8gk7Mcq6Ad/WEFviecNogtrsNG8GeV8mx WjA7ENWSuqcWfxi+0tc3ogVpQk9CL6uWo1XPvKgj41qwg5PnhJTqR2Q8P677 Y1ILVOazq0x3VqBarkOxLVNaIBwYEFByrgo1qekY1yxqQVLHcktHRR0auTyb /opHG75Gm3t7KzWhjTxn3H2p2lCTE0R7E9qJbB6kb57V1YYQ1ajAQ1w/0D2J n+Xn9LXhpVeW7v2oH0iYYrHFA2mT36smk/I7P5G0g8InRwttUPyUXRQc0410 04YU4ag2/BgTuWBs2I9cqEeY60O0Qc3+Mv+JySEkpvqW92qYNuRq1YarSg2j n7LrKfQIbdjiduzhA4dhdFCg+FL9HXK+uSj6rqphZD7Hz3L7kTZs/TFlT78/ gjTy6jfzZGmDemeEmqzCGGJmSlMDcrRhf3Ttxn0OY+hV6hUHZq42cB4U28oW NoZkYxWSvhZogwJK2rJmZAwJewXL3cHaIOb5N8r48ThiUTWg8bZqQ/n33OSb UxOoTDbOMbBdG7yExMpfbplE/qIT16Y6tKGo57mVGZpEvzY8rGjs1oYL4edu d9yeROOTs5axo9pg4Hy3kCZFRxmDFp4sE9owxcN8ObCLjlx/psacp2uDM+On 8e+TdNT9eV+bzbQ2lDaNhzlk0VFT5qujfEvaoHSs/d6oKgNFp7LeuLmsDWej v/BX7WEgy0eH0mdWtWFdcsUqyxkGqg7jHGteQwUX0TUCTzIYqNjd9XwcDxWU nObU9fmZyNfpfRzbJirUB2xZ5lBlIor9poKLm6kwPdCprkzej7NMyxf3b6GS v6fyDQGXmChNdmswvxQVAnOWJZQbmShW/W1lsQwVpvz1E5xHmOiG/h42J3kq bGi9K/JpiYmcbK7fzFSmQkT/iQBNGQLtPbylYq8alazXtzANHQIZuueyzGlQ 4aeV0pizOYG2XhsM3KFDxhGxs1anCcQVdhUP0qjw+ap5F6c/gRbuCvwLM6AC 67F/HUQ4gcaSso1Ujaiwx0TCec1DAn1/YXa9BaiQ5zM3uvMZgWry+8r8dlJB d2/dyJtcAr0ru7wiakaFYcnRZrMPpC9bX107aUWFbzwUq7kmAt3s3fmBex8V RJp/V68lPXR+ovtvng0VMoY0OUxJLzn/8jVwOEAF00HXyFekp/b923h12Y4K 6RO3N9GmCbRjfWZJ2iEqPNt+yYtJekxF0HjJ7DAVaqw5Ar8sEUhU8qce4ygV bvBKbWlcJdAGZe8rd12oYC2cy/uX9N4Slfu9znEqZG1NgH2kLychY6HrBBX4 6ypvfiK9+MPKiHbTgwqrX/lfnyI9+cm+w0/+DBXG+i7Ga5Jx0bHzRfWeZH5v O4hJkv2fn+WaP3+eCo2VvMeppC/v+6XrCHlToZwqkXaBZQrdCjK4VOpLhey/ O/jbSf96R7cVuFymgp2y7G/nBQK5PvL8zXGVCme7IoI2zxHI9ikn9XUAFV5J K8wzGASCnBQfmxtUqNvy7s7UCIHU39Pe/Q6ign/z+K2tvQQSr26eSwyhwlX3 AMFz7QTiaTytBeFUMJd5GjRZT6DlH2u8RyKp4DbmaBFbQSD6cFJ+ZDR5PrWy OVwKCfRzijqrHkuFsnvDBxxfEaiYw+OC/30qfK1T2dIcQ6AXm1jzJB5RIaag pXrfTQI92JY4XZ1I5p8R5rt4gUC+mg1evKlUsDhjadtpQyA3wxNv3qVT4e6k aAkPItDB3avEfxlUQFLR3y+qEIhyVOPcs1dUOLVu/XIjO4GkPD5nW2ST42vs iM9TTLTJ25VJvKFC6qZA9/kfTESEx5/VK6BC6JnxkunXTNRzTzWrt4gK18NO 3ii/x0QNybX04BIqYEuT5Cp/Jnr1buH0N0yF4LebZ/3I98u9/8ip41+oYCss p/a6jYF81t6y6mqgQmzw+1OuxQwUpPZa9UAjOf5h0m7vxwz05NrijEkbFUql XP5mODNQm/ADf+leKqjU5M+c7acjE9vGqIEZKoi6XDeMqp5ENpf/eP73iwoV gpXabsmTyClFzKb5DxX+eiRnvfSbRFeYZwQq/pLnMdLoWuD2SZQbse5JKocO nFdkmFwLnkBilcY5ziI6QN/FzJ6UGEdKEx6xHdt04MycUI3azBiibYq9aC2u A0nN3T6/K8bQQadeHSSjAxc2nD+wyXUMRS75Y3FVHYB0SeNnSaNogfKuqQd0 oPpL8oGo5WHU9lR+7rCHDuw2fC0femEACfTGzK47owNmC2+yRzQG0EHhxZkC Tx04urSoNj7Vj1pv10/zeuvAaO+9XT1n+1GL73miKkAHZDm/91+s6UVNu0sm lO/pwAORtfE+gT/RV/re/r9lOrBZkE1gNL4Z1Wr5fn3MrwsPHedupnDdxbKR Z722CenCo7Wrr4vaEnBw/3G+x8K68PeJNfWddRqG6P12iWJkf+9512CRV7hk VL3nkYIuvO/Ko3a0FuDshEnGfQNd4J7izsx+UYXj/zlzxx7XhfnZXJkNXi14 1s4hh9ddFxyt5ql3/7Rg26x9NjEeujDw7KtLXUAr3vjfjvg7nroQ17N9j35U Gw7P3yoa7acLQdp+f2bTvuOrJ9qVI6N0If6S46lzH35i13pLq1tvdSFw94Po SxYD2CD22PH5Al0IkeK9GXxrAAvYXb56ulgX7N+uvQN4ANf2Zry2KdOF8Jon njVag1hxloVbrE4XqELu91qFh/C0cFFDwU9dUKsUd/vcPIw/93wd3t6jC1/u PBjQWDuC09OHlx/36cKrl63sFMMRfFBls2rQsC4Yz52I+vtsBBchz+h9hC78 4U15H3xhFF93l9k3xkoDP5YuV8XfY9hBWd/dkZ0GptOud27IkPexaZvrXzlp EFaqnetoO44Hr1zPebuBBgG9HNpxr8exafSPjTcEafCl7A/H2H8TWHz/tPzc FhqY//o0onZrAv8RWovct9Ig2G3gC5E9gTNTtb32SNAgKeTbf83/JjD3u5hG YUUa3GxcvracNIlHLj8fi1KmgcjP41f6Kidx+Y6yf6uqNNixQX5YfXwSn6+b VB+h0MC1n3uEX5OOW3+axuYZ0sCAbf2fulI6zko5kimLaODCY//hVzcd33Lz /vjQmAYWa04HhqzQsQ6ROh1gRoMSUUPHb4YMnMi6bGNpQwN1xfyF7rcMnPHj YOjsfhr8J+P2wa2FvE/nZZcm2tFgPXXvRaVpBq495ixPd6RBx7bV9WcUmbhZ r/jwvaM0OPZm8NHQLibu5uO7a+BCgz0dul73nZl4tqLyb9QJGogf87RKjWPi lYRtmtoeNPC+eXr5zysmXnfRx737NA3WvOXbE1TJxOLS8s0q52nAfFglTpli YsWl65ztF2mgdckp8CA7gbVbOgwCfGnQrW935oUwgS2CIp5/9afBgS2hrV1G BD7oONjlG0AD+X8dtaU2BHaiGPCJ36CBnWeB1udjBPYZZFw9F0KDkWsmHqdu EjiwxDRPKJwGRgTXi6UY0j9xyaPlkTSYD7m9t/AJgVNNbGx5Y2nA+k/r48tC Ar/e+jK0KI4G+5iViv0VpJ9mWT8436eBz6hhgFEDgSu+OM6sfUSDbyJRZ6rb CdyQ/lY+N5EGxYUPMi70ErjDn/vIoSc0iGGYd5uS3hvcf+IuSyoNciYjPwLp QaZSeW1mOg0u9puucSW9uMC2ZdkmgwbUFVe7l6Qn13R5aS6+IPdzvv6kEOnN jW8/uae9ooHqKQ96JulRkSipJItsGghvkbnrQnpV9rh/88wbMv/Tw1w7SM+q G7RyJubTgP11qpgR6V19fhVDkwIaqBknjh4nY1P6rQuTRTQ4deXS3Ryyv01V z/O4EhoEbv1pKU56+vBjnW79MjJf9FPoLeltd+8YviFMrjf/y2NP0uMXrMbN oippMKqTdnsv6fVrMsbXtGpo4IHijA6Qng/7m5DXVUeDyjiT3uuk9+NaZ0eD v5DxvP2jpnECJ722ElX5SgMdqk+C+QCBXwQ/s21rJOvFhzaOdRI4//BK6LUW GrQfG1fNaiTwBy37D7LtNNivRb32qIbAdRvezDR0kO+rVNeTrBICtwytVfD9 SYNZx6e6EzkE7il1OSLWQ4MNGx2IfekEHr/3/m5NHw2sTmH33ngCr+48syw4 QoPtLS3qAX4E5hKt1iwfo0GR4aYv0ScJLPBL9KT7JA0Ocim8/2JPYKVn35oL p2iQEMSh2EAhsD075YXDEg1ejhyKZhtg4hsLwoEtyzToMpa35Gtg4peMf/Z7 /5H5/3gbexYy8XLbV86d7HpgVexszh/BxE8zTrmrbdQD0XdF/7bLM3FDgo3R y016IG8wnlO2gYn/ROsKyfLrQZXP3jUvyPfR8hJHrYiwHuxPM6VfLWbgabM0 OQ5pPZDd3fxkHzDwVoPwlUBZPZjfEPrphSQD71T3al+S14NXv+tSnFgY+MGW HSHTynrwhb1hYKKM9O5453AXVQ9OciyUPCC/LxERm57lW+jBTUZw4onlCZwf MH9VdY8eXHgi5abSOoG7L/QeyNynB5PTnEonXk5gDcesNckH9GCku46FcnAC f1cyPx5xVA/07yQruzwdx9INgdIuF/Qg1vmd/n7FMfxh41QqT4IeeLPmS9f0 DGFhIeEHZY/1AJWGGfSmDmFvMeMoz2Q9eD2/zi3s+BBWUrnn+/UpuV7bbWZ3 xwZxgoWuZXSOHoT+614unBzAl24FznFX64EkbwpPfVkf1ljiNeOe0oO/4jWr NkIdOGNEg77eVB/kuVlY4i7m42uHr9jn7NaHT7rCdw5I5eL9zRUVtpb6oC2y djIh5TVe/bD/0SNrfejbd2lY6lA6to/3MZV31AfKx/HG4VVDxLmzOMXYSx8O Ba1b75WVjzxS0cHLCfrAbZqkV1Vaj4yEwvG2JH34q1C44XNvAxK43aSEk/Wh bbf1AUvWb+ij3zFWzmf6cDSZW/ugdBMSsQ7OuZejD05ycgdFXFvQl5XadW+q 9EGSUmZb3vQdKR/eVzbC1Ic9rqFOJ+z6kCRTtv7wtD7cojo9E2jqQwKBfzub Z/Wh81bY261y/Wg1PfNX2bw+vCoRsHdJ7kfNk2wqD1gN4EiI59H/ogeQn39R opmgAcSeLBD+fHgIneW+k/lhiwEYF2yzXhs/hFyS3QopWw0gIK5laax+CFlW 8rWISxiA4Vk6W5T+MBJbT17YtxvAsSE/qjr/CKpKkLz8wtAADkv9B1m5o6hY eT5EDBnA+NzXJLfBUZRV9vXePWMDuNibb57JP4YeDPi/CTQzgKQU7YF6nzF0 SrF91MHGAKQ2GDse0RxHvO8j7Na5GUCt+ES6W9wEYrdyOX7d3QBudkrMKHyY QAvdOhd+eRhAzWy7rMvIBBpkGb7d72kAXOvM5hV1JlGBuVF1sR/Zn9FzbLVp Eh3unKWcijIANsWo5NBJOgoK2OAkcMcAKnIFhPJ5GChTWjYCxxqAefVJZ2kN Bvpz1q5P8IEBrHkW86T+IgPFsRZHVaYaQF1ToYnwFAO9f95U6PnUAGQOi04Y czNRv9XEgPBzA+ir/GmWsZ2JVB9spXm9NoCzHGNvBZyZ6JNSwPC2QgP4faBP 1q+SiaYa7/PWFRuAUW22vTV5PxfyzdG/WGoAg/W99ofI+/tx3Bf76aMBeDPn 9i4IEyjSbaHUu8oA4qiaatHk/T+Xi29MvNYA9G8ET+8jfbB6wGSHb70BHEgZ srV3JZDcoqOH5Ddyf+/UbydeJNCeZO979U3k+vfx9K0LItDFnbfLL7UawHD0 tkepsQRKGH82IfXdAJ7FLbIfSybQx+gyga+dBhAcYOZt8ZpAo5Tv6HKXAfw7 l6bxXxGBtAPWPvjWbwCpsivf6A0EOiwtWXFlyADSpPPcPb8TKKiOxpAdNQDb RdP1An0Eyjxru6Vp3ADuSyvc6BslUCPfaZOrdAP4T/jjnUYmgf4UBnnKEwYQ dPDa8tD//9/0yONHzdMG8MumLkZ0kUA7Wd9VXZszgMdh3LxXVgh0+nkDofCH PG8Xi2CR9OFdqxGR1gUD2BalRU8i/Vg8vbLr+l8DqLRitB0nfdl3X+i84qoB 6Krtrd5L+pPTQP1xG4shuGZVBDqSsWr/7trANYZwo0asL4LsfzDEZUaJ0xAy n53l6Sbn81e6Ivp9nSFcexy1z5b0b1rj3d03NxgCg/W/0QlyPZ98Xl1U2WgI k+pvhZ+T6yVEqp50bDIEj4DLiqG/CCSIuz4F8RvCAZOwI5EEgQzdfs2pChlC 8vey3/ljBDrOxSPxQ9gQ9OKWaCz9ZL1z5CxvbTMEwa/bTl/sIFDeASNfdXFD kOn718D1jUCdC/apPyXJ+SRDMmqrCPTviVd9iAy53oPH4GUxgeR3hv/RkDcE h3o2an7W/738fk+YsiFMhT3Yqh9HoERKix9FzRB2SuwMLgkm690xmd6jYQjE 5jVUNx8CbZQWXdTSMYS1+ZrHdQ6Q/hyqrM2jGUKz35zYAxPyvDw7Fa9uYAgq byJ0d2gSSFahSF0ZDOFCTvbkcW6yPuNHVzJNDMGtRrxweIGJ3rxkr5c3NYTl NsLlzTAT6avsd5e2NIRYrw1s8iVMdIO5oJW6h9yfiHN761MmqslJYRW3NgR7 PLKj8TYT2Wgyk0QOGsJro8Tw/CNMdEInvHWTE1mvgjXbTH8x0Kt5tbQ7LuT4 6f05VzoZaLq4/Rz3cUNIfT9rueYDA/kbyKxf52EIz/tYu0RuMlAslMO/C4YQ vqavxncNA32w/JXNDDGEPXrs9F8Tk4iN+/HVM+GG0DF3S3Mt6dPdX40tJiIN YWNWAv3mk0nUYh0zPBxjCCKNm5QK902i8YNK27oTDKH6l2YPejWBBJxdwr9k G0LJOZuHvLvHkaPkWnvzXHK/Zb9o1sLjKGUgW6Y23xCsjyS08EyMISW3v+UV RYZQN5f4kydiDMGpB7+LKwyB5d06jp1Vo+iMd4Pri3ZD6BSv1WySGkFKT+Oe C3caApv8wtsqxjCabDk0GfHzfw3XezTUaRgHcDZLY2UtqU4tRanIUrqoNO/7 KKSL0sWliwa5jmpWUZHcushWqEQ5cp3sEau7WtGDRClZhdOUkTTjMmZ+G9HV tPv++Zzznu/zvOc857zvZxmcSi623HhHRoV28vBdb5bB8Q7fDOc1rB5Ux8/r Z/XjU5/+2vOOCkW2ufdG2T5rZfpVid/SkLCzr5un8+FeQnFkc9lrGrjTe/Pn cD6kPYsbeR9VTz2LfG/nRPDhY2XaZ9NND6lrf8gE5wN8KIlKKBmYU0etRVEv z8TwwXa6R+v+jho6HJ21fU4SH6I71aqWfRX06NmOgB3ZfEiqTQqd7pVLxTW+ kXX1fBAlZdhWhlVhhlZou/AxH7RvjcZYViGeWBlu/8tTPuytETmN0anBXU0J X3xa+FCBWn5Dng9wgaTg8KfXfNA0rdBMHGrAB+9lx6wG+WDkVnG0Ofkf7J4a mpE2hUBbz2Z/qVCCQ7H/XeSZEjjnMFKvo5TgmM7zlxKnEfgjJ3Vt7a5XOCO7 VhxhQcBEZ2aRdNdrDJ70601vWwLNkhmLdgZLUWnQ3DxtBYG7ir0HivK7cFQU +OKiMwGLqxnWJp1dOK75W7uhKwFlRsd+l8lv0eb07E4tNwI7/BMNSs68xXBe orLPk0ChBm99ekw3ftRcyLsuJNCyLvRSkaMMtf2e6FntJrA8NUKSdVCGE6v9 DApFBJY4Cy5bXZXh4tiUiecjWL886c8Tp8jx0Ndei6hYAvVfGmZ8VclR40PW csezBKxI2/282F402DjPpSKdwKn8A7o5Zb1odr1h1fxMAvxVN45M7ezF5aJh d4tsAleEWY7FDn14dMBNwCsiUDGlo+rq+z7kyTRiWv4mkPKvKGaVowLzbE6a plcSOJy5gPy+W4GLo4xrPJFAzp6gmq4LCgzRt9LuqCMgMrlxM1OlwEeLN6X1 NBMY1zP0yjJlAH2PSO2KnxOIl+3ZHHZrAD83BbeFtRH46VwK7ZMM4KydMZMH XxHoDlHYp5gr8fjpy+Jvcpb/Yreb4IoSTV/arrzfRyDVxu+9e6MSy80r+uMH 2Py623LD+5Uov/PMRnuQzbdyArfEQoUxP2xpefSBwCGj1cc7HVU43u3dvpMf Cdz3uRlQ6qNCp+5Pdw1GCfyZ3OWHzKcd1onbXnwnUBqVYP9DqQojDuh9P69J QaxlWBNap0KxntmKKToUrMZW+hQMqXCZV4lcyqNgnHpjVvhYDlvzF57I06NQ 1rTRyNeEec1+dZOFIYXclNVVF504zEpoFfWNp7Bg0tcl3cwPdk93GJZMpFD6 pq3QJYTDxgn9t3ZPpmx/CzzrD3Lo77fPa64JheqwgDLfExx+LVF/GZpKQW+l mY5xJvPTx6Ts2+YU3BXSym4xh7Uns98unU3BpFx4taGKw63tM4+qrSh4jziJ pY84HJp2fWb1bxQUlvODdF8w74Y5PE6cS8FasHSDWweHZuUPw5znU4jME9Rc lnF4V8Ndf+wiCs6CH8cbKTl0X/PqWuNiCoHq3q70Iean8wGbTjtQeD6tYNwc 5tP4Lm5kPaGQamVxrG2Uw0lzoi4YOlLIO+Rvl858ei1yjEPbCgq6kWs0gplP XatPSzNdKHtPWiRuzJtvdCfFb11F4ZNMXuzKPLrfo8DcZC2FBJPobV6s1s+z fvhmHYWIxDhJFDtfpCgPLtjA+kf06l9jeWSho27gZtbPo7CH/QewPe5J6Swv lpcjXuPFvLyn0WO9YguFM41BTo/YvNrGXYOl2ykMqp/auzFv5wiE6SIBhbhl F/J72H0XXRleZOdPIT85WZ0u5/DZcKxkOIAC9vk1eEs5DKK8mDvBFBx9uqPt WjlUJ58zjRayfMWTc+aNHP4PnQ0GTQ== "]]}, {RGBColor[0.880722, 0.611041, 0.142051], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUmnk8lN8Xx5FsKfuSLCP7zjAMI/dIK7K0h0pEKCkRKWmVlFQo0jdbSkIq W8iNRAvZZcmSfZl5rNnl9/z+8jqv+9xzz/l8zszc98sj7+Kz242DjY3tHCcb 2///lp+OKHW6nmoWtkv0U7xgilnT2sZfk0XXUf0RN+b8pauoMFyqrrIoCkUf 1HuSfekB0vr2cde7ohS0qnxPqeClJOTuIXD3ZdF7VMpwKWu48BatotM1kos+ I/O36u8Wz5SiuoSqoISiBiRi8krvwK46tC5N7tilQ41o/cVxz4TGOmSZ7bv9 0GwjqnGpuf3UsR6Vf5IUFdFvRvn6md9fezSggj/HM0PTW9BOScvXrZebUKLC cpd3XAdKEhQytIhrRQUNjzY+K+pFF/5kRggXdiPJEg4zXaE+tG3L/icJi90o MO30oTL3PjQbtUW7xvQPMg7edn9AqB+tuuBcvq7kDypUnlnW9hhAxNfMLR1F Paj4wr5WLDqMTirkv6ak9CHp46XT9l7D6FhIK89yRx+6ZKMl2IeHUaC0W/0R yX60SWH1dp6TI6i1LMf+9Z1+VFKVk2NXOoouKy4kGZwaQKVyovf/eBNoQ7fN qI/IENrId+X1uc8EorKIwcqtQ+ja9GjF6vVjiEvphlVYwBDa/O3zslr5GBL6 ubyJ0TqEXD58oBlHjKNiDjt545hh9DDLx4KjYBzpvXz8OKVsGJWlKNn/6BlH F5O2vfYYG0Yb7z04dZg+gUrZJTmXto2gXhfPlKu9E8hYvePremIEiR6Ue2u5 bhIpz4Qf1RAfRVt2NZWIGE+ioc7Tb8M3jaLnRuZtqfcmkZNU4CnN8FF0nH+9 0HfjKSQx2/W6XoqJotlrZKOOT6H5nZtOqG5iovKZG5pOkVNoR1Ql7dMRJlL8 M76d6JtCD1tkXmYnMFF/7tfLwvenUTzFOeSMJAuxeTvnri6YRjEBztKtVBaS UpwbneuaRuW3Uo9FWbOQ3UOVQ106f9Hb8iWd+WAW8tqJI+sP/EWunAXM5BgW usl2oOJLyF+kakr/8CSDhQpPh+pn1PwldRBXO9vCQo1Ksl4Js3/RkNNWHRsW C439zk18KDeDXIU515xnJ5CiVf/aCz4ziLezwDpFhUBmHMFbTj2eQVMBW7e/ NCbQoQ+iF4/iGeTkkQNTlgS6p7JlaKvALLoq+jDR+SSB0jrbZY2NZpHq9Nua K0EE+hxzbp/m0Vm0qcgwciCMQJ3Wa+7K3ZpF9+hb9z54RKC5VSllwm9mkc66 pidXUggkXGQyv/rXLBq5WNL//g2BtHzrdeb/zaKvAZUl6kUEculm/6/LZg6t VTRz+1NDoEuP4xrqz88hUYsdnpRWAj220eOreDaHpJexR9IfAr1b/Q0+VMyh 6n1FgseHCVRV7ByQQcyhnNBgMY9xAg2cm8tMEJ9HF1YuUzNnCMSucb/vodk8 4kv1U9dfIpB0j8qGUPd5xLDZXznPNoYM47D9hXvzqP7S8Ta21WPIzu5A2Km8 eTRmr2W6g2cMneQeKznaOY/ai+9X1fCNodCS0L+7uRZQbO9n38f8YyjRX1Zz m/YCulO+RyZh7Rgq1MxzMd6/gFIFVcoGyLipd1ec5uUFtLQp5MhpMh5/0l8j 92IBOdXPzdDI/Xy7g7lEfi4gZn/4401kfkVesU1cMwtosuPmnpvcYwh9yjg3 L7OIRo4+2LqWcww5BGxJZ25dRM7BryKbVgjkp/27u8t7ES1IbnDsXCD96z8n 0RCziE7eDGlR+UugV0/X2FR8XERcR/PRO4JA5XtSbnzoX0TLiX01wYOkf3yM ooy1S4g261oT3kX6V1o/kUBbQuw2X+60NhNI5IKXatThJSSW9PmQVzWBtHU5 jobeXEIKa0xjNpGf6x2DcTEXMpdQqYRi0p4C0s9nelWnmpbQnkMhgxkZBAre 943DeXkJjWzZ27ozkfTv85zPtl3L6OAlqxd2N0n/gu6/MPZfRp1NUqFF5wk0 qKfaofnfMkrLT5Y6dYL0K/GApQhrGR0e7c5N3Eag0Et5it13/6Gi295+nkss tGPD1o98Of8Q8x5yvzjEQryFDfto7f+QWSTVtauBhe7OjoeGq62gaz8Cziam sVCUr8awQcUKOhFM/yhtyUJ7hQqvHmWtoM+e4h8bdVlozUHFtVv52CBpccG0 X5yFqmfepfroscHOE5mOIn+YyM6gtrk8hA1QesOVEm8mentdQsEhig0MD8Z9 3WvLRMINR3zGXrDB0JdkKytdJmo8y+KW+skGMef16YfHR9GBN3zGPtLs4D3x lkvfcxQdUd8av/4DOyjGWnO9MBtB+MLdwawqdjA9/PVQhfgIonxr0N/SzQ4H r1z0O0QMo54TLlWnuTlgouOCaEf8MHJLDVn+vI8D9qfNyV0eH0KnKIVHT09y QP++C29srw6iIHEdxc8anNBaw8tZYdmHTq6EOrCbc8Jf37FPmgJ9yGmo8z7a zwmFz14xKQ29CBXeWy66wgkaCdUlBYd6EecRojmniRP0Gak+Lcd6UGRq5u0X IashqTJayP1oN3puoDl2u4EL1D09Bj8ZtaCa3WqFdhd5YXJNS/mPtHyUJz3J qRjJCy4qTnA6MBc9HSi0nU3mhdnffxU/bH+PPIOs+//7zgtnFl0sW75nolXJ PoKj6/ngzAneEzwXYpHRRK77zQI+cF/LPczW/wInRG4WKfy7Bq6+OLnzpk4l Dj205kgELz9wiEeHXtryFZ9SaExzluEH9zJOfoFD37BxvpsZ91Z+yOmJ15y6 8gM3dIZ57o3mB/nSij36P2owt3YNJqhr4VVEck3WxkbsU+V4SuHMOvhDuMnk 7v+NB3RoSQk318HjpM67X7t/Y6eodc0b4tfBBj2tD+ZeHdjSoRSJVqwDwzc5 hw5c7MTKQ8oiq6UFQC762Ytmy27cuWryw0ClANzwyhGZ3NOD9534Qbh0kOu7 igv2RvXgqu/PFbomBSBq2uf2rvoe3PH1dcXoOkGQusPatWDTi39EHtHtMxaE htroKH6LPvxSpnxVU6QgxGkosc6JDmCXGl3ZqCeCoOXC0epgPYBlr/5Ht08V hENoPxReH8DRfee9qwsFYa5QUbZ9fABfe63260u/IKiFPE8+Wz6IjxhHpucx hCDD702Bo+0wlhpdLPfbJgTEs5KFseBh3PTUo4tqLwSm5yoWul4PY2u2zaJv 3IXA5+7XY1WrR7BJ5XTwywdCoL/g2vry7QgW3+dgHzsoBLc3c0ytDI7iok9b tihOCsHA3Ut5g3xM7KypY5S9JASidOnvklpM/HoVp8xXIWHIOcwbZe/DxPAu c2iWIQzTSQd/zo8w8YBMbPv1bcIgfdpBgIeHhe/cvvZTwF4Y/J7ZJe5TZOFm 5wM5Ku7C8DS4SiPdgYVPCrBfOXBfGLoa7pVKlbCw4MVR394nwvCdI0NzdRML 5w00ufmkCsOGBxujlEdZmK0k3epWoTBIfJXJ4RMj8Au1GDORL8IwYyPw/ocq ga1iQvQSaoRhKNbd8BODwI9O7ZXI7xMGilZWOhwlMKPFjM9iTBh+ZutQfvgQ uNtCbfnnvDA8N3RTCA0hcOgbkXEHThFwz9635uw9Amts+NczsE4EgrwDje48 JXBt6FCT73oRGKysFGh8ReDzk/Vf/ymIwLPf9ZxWeQT+9O1llrixCFgupVBL qwjsRnuYlGwhAhd62QNxM4H5ki5Fa9uIgHnlianhLgJn85+4VXhQBIr+6ZvD EIH3BdoHbXMVgVD1N1xlYwRe6GV413uLAH+f+OTpGQIn2io7HwkUAeqxl4Xb lgi8tUhwz8g1EbjD95yyk30Mjygvbj0fQZ7HcZTlv3oMRz7sp3PEisD1eDRV xTOGDf7VaNxLFoH84sq1NmvGcJtnoaxUpghw6MfKz/OP4ZCm50Iv8snniXPS P9eOYUXzSE5qmQgc1tj8t4qMv2dcmP1YJQKnbwpk/CWf95E8PrLzlwg0z6y1 3EHmE71h09H0RwTopVF/ysnzPozRa48xRWDJfP29k2Q9RxwVPrNmRGDiLc3P lKyXs3Jt3gV2UVhT96TUiOznFXUubTW/KHCFCGQeJvu1edYT/0BcFGQ2e57P IvWY5q2+JyMvCv+Kb7irk3rF+edffaUhCrlim2rqSD3N/iT50QxFgcPWZU0q qXef9d0TpSAK1o+yLj8n/bhdcN5hl5UoGIYVxtSWElhb8diu1n2ioHp6/Isa 6V9jpBW4OYtCQMDliGzS3wuLNP0JL1HoGt9+zo30X/YERTnYXxQsg5u4dpLz 4Wn2d01MuCg8v2KQ+IycpzApydsno0XBz7ZZneZM4LQZE67Nz0RBIGV1pYQd gYeyrrCNvRUF7uDzDz9rEZjnTkrwlyJRmI1yZ7u3gcCqJyoW4r+IwrGj8ssv eAjsIcf/d0erKPy+zO9a2c3CYYvavnK9omCbvJ5R+4OF037Zj/1lisL2nNAQ 9TwWHop8PJzMJgaPXP94NYexsAebQueSihg4pP6r26hM7v+91bFBTww0jrwY qV5D7i/waHnFEIMLG6jGdeNMPHQmq36/rRgoyJRBXwETn/hjXJl9XgzYvRJv HzBnYvcyu+zjX8TAOrw56ojBKA59dk6LUSMGe8NkGDyCo/hF0KN0oVYyTijb sWF0BA9Qfz8vYYrBlzwRn2sJI9gt5UScpKg43DHYcSuAfQQfv3H5WpWLOFx+ uTF8w+shfMM5aSX5lDgsZ7moTgUP4eem5ZcunBeHaJ/dbTvshnDfNG+Acrg4 vJPa+vfc1CB2dYs5eeWtOFjHHCwf0x/ELtsy9hqwScCnU/51+c/6saXPr21d fBKQpXv7QbJbP6bGchiHi0lAjk09RUCzH3OMHJTpVpeALdmeM375fTglYvXA nX0SIG286/qLr724r/FIQG+6BIxbVVrRm/9gd1ehJw/3ScIusVNPTPe1Y88r 57vG09dDZ8h7x6+OZbhqfZvjQM56+DhiOpxtUYq1329qaS9ZDzoWKf32Gp/w dD9nXUX9evDqNT+YMFWEL1tFlT1dWA9RzxbvnFd9j6PFs1N3WEpBi+4+BTWH QPwpY/hk4rAUbHx8SGJH6yeksG3XUMyUFAQ5yZhfnChFoV3Zx+8sS4Ha009z rryfkZVw4OHzQhugYVPYWQv6F9QcwGVrbbwBloLqzfMffEOjmxWoc2EbYFZH 2+m5RB0Sb3Was1WVhtajlYG2F1qRi6bZLhGqNIzb+O0Lnm9Fb0LkkpsZ0vD5 LEe3yYU2tEO5x+qwrTQonpaucwhoR0HnTiR4nZcGC8ak0YB3B+pc67vtZrk0 NMes8EwkdiP1Y3vid/yUhr5VV18M/+5GATkG42tapEHg9zGJGMk/SNBxNu7h qDRwZq9evXLvD9qcdomVICwDhztw/VxAD3qx+VZ0obMMHNjNe83WuA9NxngM B3vJQFqDz4Nanz6EhneamfvJgMhfy8NEah9qieQfqrwlAzuSuKMXBPsRX8cD RlOWDITu4HPR7ulHpwOe9owtycCxLy/u/fAZRIXfg43ec8nCyGK6ydmEQcQt e/TueUFZWDFcd/a/n4MosVzecFlBFszthvlvaAyheqGXt/msZAFWndh8vGsI GWW81VWKk4XjKsmhO7RHkLV1/EJxiiwouzpU8x0aQc7MG+V7s2Qh3OvnQaXr Iyhc8+DBG59lwWK31bJT0wj6nfEvpJclCz+yrNNfnx1FE9ZDOy/OycKS7gO1 1Y9HERerTkRklRx8Lbf9k140inS0Ul9ulpQDE+Vj9k0cTHQt06omabMcOCdl /AgJY6LHu2hxxrvkQDqHdU00jYkyWLKudQfkYGKvQu5IBRM1aU3OsHnLwdsU k4T9HCw0Ut3+KTZADo6aTU0My7LQP+8v4brX5CB18cHfDyYspJoVK+v8WA64 w/ffX3OGhTbZXBuaTSLzRSbOh99mod3EyXeRGXKwpuFAweZkFrqojbbhUjmg OE2qH6hjoZ9Z/d6yTDn43HVi87wSgXptaozyZuQgY1/oVQrJs5cCfrO9ZKNA ubnft0ArAt2XqPhutoYCAu5Lbh+8CfRksPBNuCAFVt9I2JEYTKDU/DfRzWIU EBGwtcu9S6DCA3FHTlMoQNDf7TiRRvKSyj2LQiUKRH/g5V+VS6Ca2WuqXBoU eN/dEvf9E4HaKgPW7talQN9Gv7MffxCo7/Gpyf9oFNBSltrQ3kQg4sSxX8Mm FLAk2FUV/s9XRvuLaUCBjuUT1BiSvzh4rJKubqVAi+eTDt0xAq1tQaHVlhRI +b2q+S/Jb5JpBifX21GgMZRW17tIoI2BanZu+yhwfnEsYoHkV80dsrS3DhSY /6veaEzyq6GkiNTyUQq48kj7J5H8CkPcKzvcKGCga2qlt2YMWRUs9UZ7UYDP 3tpkmOTP/WETX7t9KLAYdVDnG8mnzgcHMjX9KbD+dSGljoy9VNsfBgZR4Nyc 1Dp2MvafqwkoD6FAfOwZtkNkvitfy50Eb1IgyI6Nr5U8Lzz2g7lTOAXwEYdt V8l6oj2ylNMiKeCkd6DNnn0MPaOnrJmOpsC7FeFpS5LH03hix9ETChyzHPp+ iuT19y13m+4k/N8/z4R8Uo+F7v9WLj2nAKUw/f37IQJtHs5SO/2KArsq8yX/ dhMofALvOZpFgYSrMZKXWghUP18bbPeeAuzJ6pw7awgkxdHz0ryAAslKRvpO Xwh0jG+qjvqRAitmVpx5hQQalxJTFqukwN3WRFWUQiC6grIdVxUF5pIKHHwe EeiKhlHQbC0FbqZ7MwfDCCRgeuhnaxsF6iqAlnOSQPu3eM197yLzl86s8DgR 6Jn1xY3FfRRQzDpsn0bOn/bh/84/Iyiw8Grh71dVAp13y0qMnKLA4bavkVbi BProjb9fmaNALP3Apg2rCGR9+Y+sK4c8vG1//fx5GwudTFCqVBGXh4qC2Fd+ V1no3UvDCckN8rD+iUuRnycLLbzZvoGPIg+m7sSGr3YsFP7J04epJg++ROLu UzIslPYnU+LtJnkwa5q/Wp7FROPDJebJm+WhzULnZ+ADJjKarDkZtV0eEg3D V4WdY6IKjknsby8P5x7Z7yuiMVG/gqGHiZs8HFLbXRH1bhRtdC8p+HxXHiq/ 99itiRxBXqdrenIeyMNy6X7T6RMj6N35bv4Xj+ThRJxtiiWMIPNbHMfCEuWB uuEh19axYeScto13V448pLatzoveNoz+G/l5qLldHt4VJUVXtQ+iHeuPl+j9 kQc7xt0dKmmDaHr7/MaIAXlwG1/jOXZuEFmnKjAtJuThhXiNag3vIFo6Gnj5 LddGeIGP3l7RHkAOTfIpd/U2AjL2vl3i3IfEP/kxN9/aCNniY5TY093oXoxU yBuqAkzdcpFJP/wT6SQRNRNGCqD51HDR1aQa1WaUUQw2KQC0iS1EiVchoXKv soLtCmB07JKAd/U3FD1ZuLrMSQHaZ7Klk2hfUJyt493GUAU4/59qU8NwPnrO +zRuvk0BvpbdtdmZkY63iJ0ZYXQrwHOpl1Ple97gfsoWxuV+Mv+SfsjB5bdY mc78zTGuAByTh0w2p+ThV+6mFP7VirDhH+dI5zDGWZ9/v5DVUYTHUWeuO2l+ wx+CZXIsrivCnNjI+Kv4JvyodK2lRpgiOOW0ilySa8Z+q/91CUcoQsWA9tRY cjPWjehc0/NIERhNln/fpf3CaU8TXK+kK8KhYVbe0TetOLZIXuRjnSK8XJ7V kHjZgQPnlXwNKUqQGRMeUvSoB+/fJM4jq6QEyCQt36S2Bxtc5Xq2Wl0JzD8h Q2feXjzOM/itUV8Jzsr0uccG9WIPyTT5c9uVYMhgVuLRwT580Ei97s1pJTj1 Zaj8NvsANrwodeLxOSVIizjR/9lgAItivuXLgUqgw9uRFXFiANduG1W1uaYE Sq328d9/DOAd+zOuMGOUIOgix9Oye4PYyF9bV+2jEqy9t7/eb3kIB3Uls10s U4LtdX0drzWHcfFOibqqSiV4vaRXssVxGIMsm++ZeiWobpjeEpM3jHdU1r3P HyT7u3tC5rrbCA7X23aDl6UEAs563k8iR3BVfOFex0klsHosEsz1YQTbnUn5 +29JCf4VVvzXzDuKD673N9omrAz3ZAzUNFNG8ZPrw9yxEspQJyyTUlI5in+z DrcMSyvDR98vbXGjo9i5bNuFCBVliI4f61PUY2LPk5JFjabKYPnNfv+J90yc 0XT3jvJmZXALUAxfX8/EBGJ3CtyuDNf/trTxkvdnX9GRpQ27lSHzW+FighoL B30sMnM9oQyUnfc7r0axcLGKrkDuKWXQvpZ+mjODhf89eN7F5asMOQUTSsWf Wfiae8SV9EvK4BgWKF05zsLltez2S1eV4cyamEBJLgJzMc7L29wi8xvV0uKl CBwucLRs4oEy1KpKueuZE7jqQsNDi8fKsA2JGlnsIfC6vu2uMU+VYc8tA6Xr xwn8sECX0/ilMoRYfz0bfoPknY2pjeEZytAhYOFrF0Vg8Yj1qb/fKoNV/4ZG 8yQCxx/j2HalWBlytdOcnxcSuPPHefH6UmUY8RPxE60gMMVwdEChUhlaMr0L M2sJ7JJ4NN+/Shkadr8v8Wkj8HO+xluVdcqwT4ZHzKGXwAN+Ow6u/6UMmsRn h1OjJO90Faue/K0M7s8uG76YJLDXTr354j/KUJkvdZB7nsAZ71O/rRtUBg/h msDIfwQmZKSeODOV4dk+HUezVWNYN+ye17sJZTjuoP9DhHsM+05yMDhnlaHJ e9MzAb4xnOMUsGb/kjLs95V7r0fy6kzFaPtLdhUI6pSdvEDyLF3POWOeSwVK Ymeth8g4KL7xkhW/CsS86Si5RMbFq3fu+k9IBRxYwdZG5H7TtFaXaHEVIIae L24m8xdZegXe2aACp+I+zdwnzzdhLURco6jAls3EAXnOMVwYeSflgpIKcHL7 w/QKgY2p0h/OqKsAy7ushXeRwAWNGT9P6KiAoIK7nctfAtMDNvUdMVCBiiX+ zmWCwPnrf87vM1aBA5sv4t+DBDYsPiKwy0wFmLRQ4xWSd/OOjClusVCBbz38 sW6/CExjv2LC2KECjnrjWoI/CZyTImhH3aUCipv59q18JrDBtiQ3td0q4C+k dFr/A4HfD+ldpBxQgb1u490ZmQR+p7XnxbpjKrB7V1T02WgCU2t7i1a7q8Di WE/Fx1ACv/X1q1vyUoHLhoU0+0ACZ+fHLI34qYB9V+Rf20ME1nFQFu65oAK9 Hy29i3cQOGspT6X1sgrcnRw87WtE4Ezzlt2VYSrw6afD84/CBNbs8/AoiVAB hscu6t4VFs4InQ/OfagCvzmM/xmOsnD6D6lXKU9VQGXqwI6+TySv7ju8EpKt Am2W6z5NubKw6hxLNCBXBQYeX9TksGLhl08uq58uVAG2EKljrnos/KIrYZ9T uQp0F0w3yC8xcYpnz2t6iwrYGPzofnWbiTfynyvV6VABrseWHp4nmTg5a9Uv 5R4VeHHDJum6NRMnTilyiDFVIN7pbFAVPxM/Cz5xcGJFBY4/QDw1N0exLGXO e4hTFWZuKRhfdxnF/5WFXe/iVQXJ60L68Waj+Cl3ela1iCqEps85Lk6P4LgH TM50FVXYxRe4JcFhBEennn3rYqsKmy4cc3rEN4wDT4eyl+9VhR7ZQVOXtiHs aBRvr+SgCqbOg/sjXw3hjd/KJwaPq4JL5g170W1DOJspQfUOUgXZD+teLgYM 4ir9kncBqaoQ2Z+e2fKpH3OW8eXcXVSFh9cSvaum/uChcDlOgk0NnnEqP9z1 /g/+scdgry2XGqTyZy96+f7BD/sPTwsJqYG8ghtxdawbU3jfGjxWVoOErbeP vPjehU3tDuQm2atBJduXY6rX2rFfZ0pe3ks14Atv1zoQXo+tb8xO/stQA57p QwaD83VYSd1KZ/s7NTgScekIxbMON/tPvvxVrEbqyTkTt60WG601j5urUwOR WonwucUfeIHRedFkSQ12e5nf5Swrw1fiJM1L7NRhnYPwoPCO7Thib8SPL/Pq IMxWzjNyrh4lU5et3/9TB/gRZeu2UI8KBL1/Jq7SIH+PhI7ev9KA+qqs6y6u 1YATrR8FmHcakclW/l968hpgpVhzx+9ZMxqi3en5b4cGpMcIEjHZbchC4va8 /2MNeP/iQ5AH4w86+HcuyPWpBiiIOfQpBfxBpxs8luySNOCvs6fgg3d/0JPI HSsarzXALbxk3UnVHjTOzbO6p0QD4mqHeLgEe9GzuVBBmwEN4L0Xnxdb3Ydy mmceMEY1QIZz7c9bq/rR9xx3EbVxDeA+Idi01rgf/T2zTZxzQQNqRt5NtiT3 I+vh1dKFazVBb+sbsDg7gOZbb6go0zRh+0eL+6pzg8i3M7A32EQTynQ6hMvV hxCz51RCE9KEFq9Ss29OQ6h7dK/ETUtNIMz1b/PiIfR1WZG776gm8H8fNNS7 NIw2c6z/zHDThGy7mxbDr4ZRMdfakCgvTTh3jkt7uXkYvRH4O7PZXxPodZJT ejoj6JH8l4GkcE3QXct9NunXCBJU/pA8H6kJzumtYXxsoyhcPfOIfYwmvDvF iipTGUXB+jHNbImaUPCfvut6/1F0fKtbxdFcTZB9c59C52aizp2HruUXakLG AQMmocZEB212mQl80gSrtjdTQ1ZMZH2AllfyXRMMgxW3J0Uwkb7n6hcy3ZrA Lb3B4R83C2V4zx/z79cED249WroiCyn7smSqRzRBwnS/RCSwkNTFpphLfzUh cqPNoRV/FooO+WbfuKAJqZ1VIWGRLLTuxse1mmxa4C4/bbItjYU4IlJvtvNp QSPF0c7xFwtdehBnri+oBVBXl5XNYqGZmIjlcDEtCBiJSzck7//Dz/z9TSha 8NI3qL1Wg0AuKZ56D5W0oChg1f5eMwL9fnmYNayuBc0yU3Mb7QlUm73VLY6m BdwaJxKVzxHIMtdYfsJEC7Rym7SHr5H8+kGrYwdoQUjc6/mmBwQyK5GPS9yq BVF/5h2ZCQTKLxPbN2epBU6CPz9oZBJIt5JXyM5OCziqt1yJ+kCg9B/LVS/3 aYH1lXglBZKfFGsnwlYctID3D6i1kXz1rLF/ywFnLRA91SdS0Eryamsr2xs3 LfhSfiOguIdADzuqi7lOakHxwqWxgREC8feUBh45owVe7+5TjCYJFDqQa5Dn rwWtWrMFGXMEYht9Nb72ohbs0Hc7s/0fgYLG/stwu6IF+TViPNyrxtD01AOP jze1IGyqznKUawx5z91UFLujBXGDM/zTvGNIkfZISfi+FtS8Ul29iuTb32df KAvEaMHp0krf3SS/RmXlqfA/0QKTRxw7e8jYcrRClTeBzFd96No7MmZX/aXG 9VwLPLsSKZ/J/QXHB9VXvSL761/WFCV51ydpVoMtSwt+JA7lp5K8q9zJrbX8 jsyHVVsDSN7tkJLUXsjXgrzdDW/CSd6NPqCqM1usBZ1h2106Sd61iqbrTpdq gUC8uuy5WZL/63boTVRoQcSCi+TOCQJ9WHuISvzQArUPwhHOpF5nLD31R2u1 wEXnAf5A6qly64LBUJMWmP9xXdjbRqDOz7dp/W1asC7FMJJaR6AYtieGPV1a ELxS37y7kuTJTelGXX1acK9bXC+vmECFed+NWwkt0I+gfdqeSqCzU20mzVNa 5P284df5WAKp6o4yGua04PyzsMqRcAI9frXGrJpDG3pfXYIUbwLZDGxA37m1 IbfVvnfoMIG4FDShkl8bmo5aP/DfRSC/p9abS8W1geWsecddnUB2kRHbctW1 Ieje228f2lmIu+q/7e90tCF5x29PywoWKuHJ2vHGQBvG1PtyVLJZSPPaT8tX Ztpw7PXlBz9I3uX1F7D9b7c2hN2cfFwrzUKf3srZPTmgDYfiJR53srNQIKFj /9hJG/J6bVxhgIkGTtjteeCuDfHntx5elclEZQ4PDtwM0oY3A6drUqhMdOFx 0sFrIdpg1ajM6y3MRLqNbw+F3NCGKwf0bj2cGEXPdtU7XrinDX3VfAMzmaPo Iog4eydrg0DUIfo2uVFkoBzjse+7NgxvPuAj2j+MulHfPuMabYitfFjCXTyM 7h7St5Bp1IYJO52FMw+HUd/dOpn+Dm345tJ6OH3TMIqeWtvgN6EN+34ueXVE DKHpT6GboiV14Pdydq6P+CDKcQwUbnDXAbGhL1N9db3I2b9yJe+kDvh6bJUx eNKL+CPFWU/O6EBH5SsxJZdedLwsp9IlSAfqJyTXTI73IFG1iUuTETrgPtQg eJSvB/nNeA4K5eoA8TXPskirGz35qnUkjV0XUv7wa/SFtKBkDwlfW05dWN+c K2Yy9Qul87CHznDpQl6yp4WE+y9UuKMxcwu/LnzvzpD1s2xGbV+DlrvFdWFt mF+HwLpGtOFb5dP1mrpg2XBDZxV3DXr67Vh7+H5dWFn9657peAF69j3moPdr Xcj9z87Xefkr/hK6VmAwUxdkX/3TOyr0HTM33/zinK0LaUrnn08o/sDGRX7U vbm6cHR2X3WJZTVufL2Hn4F1IapN+KnJ11rMGyH0iadBFySudK/iZ2vCfrYR Ks8XyHw+wrl3lTtw/JrVnTLLujDyj/V25XkHLqu8FP14RRdCo1PdRjd2YgE4 xX6HUw8c/pbPyMt04XRdq/az6/RA/Hwl5ejNbtwtxBuJNurB+Y59J+WO92Cr xhszbTv1yPtKkLPq7378PMXs+21rPTgsnc8fKjqAl3zn/qPb6oF5ku2eI9YD OEvo1NZHe8n9r5xsAgoHsLDtnmj7o3pwi7shQuL+IG75Jk/96qcHe3RHSoPk hrFeXPvqgAA9mBl2iX9pM4zDPWJalYL04E/buu3U4GHM4Oa9ej1ED57K2xo7 tAzjZ1vGa8zC9UCysNP2S+gIPo5LvHMT9GD6a/VEfNko/ngv0Px4sh68g6hT 3QOjWPwIVUwkVQ/E1GapnnxMXLmUWnwmXQ8MOH5NmtsysbpJxBrNXD0oaZT8 PlzDxNd5t3e15evBosYkpzrBxL9b2N7fLtSDWPPq2pQ1LBwR4OcwiPUgbetO M7SFhcdzHF8lf9cDYuDv8vRrFt55QyzYvloPOuxnZf6Q/Jm8p8aOrVYP6Hnj zcttLLxncvPc4SY9yHY6pvmF5M+M0qUf/C160FJUNuy9gcCcD/ISitr0QKtR 9ZqFDskjOurb13frgdzAaM/ZvQQWWOmV+tqjB1xyXoLf3Ajs8fM/4ny/HgQ/ cu7deZ7An/47UKY0pAdbj194PnWTwOu9hR41jugBxexI6heSP3xNf3heZ5H1 nakGnEzg72tubqKO60FqVWZb1xsCX0qf64v8qwdVvx9XRlUS2HaoTps6pwcp 5fYJM3UE3qj8OrBxQQ9CH1DsQ9sJPON6o+z8sh60jzj6b+4j8Lekw/zr2ahg U2iYqc4k8NMuw/1FHFT4bPM92WyKwGdkBBMPr6aCy3kK72WSRy0ch4dXuKmA I0yfDpE8Kh5Xpp/MRwW/awryl0keHW6OD96ylgrWlT1uZiQPFov6Vw4IUKGT /shcjeTF+7tthG4LU8Fw4lS0GcmTrvdVHDXEqPCeN3P7ZZI3DX+ypVZLUOGA Zd6u//MoH38b4SNFheEvq5L/z6MdO9/ThWWokOmiuZNB7s++dfdajhwV7tr2 2CmS+a9/cavav5EKzW4TNUbk+ftXIfF5RSpUBJgO+JP1qZtLOserUCHx7ofi TrL+5csTrzapU+EXn/dNX7K/2uLvU12aVHCuc72oR/b/fCFl0zUdKniaZ/Rs IPUJoAffUqRS4YuxDQ+V1M/y/P66CgMqRK7evNmP1FcmR2eDpxEVNMF9rIfU f3yCx22NCRUY2X4Bl0l/Puv0ZGWaUkFbesZyezGBH3kXzdkiKgRL0Xo3ZRPY 83X05klzKsR065S5pBDYdNj7bvQWKjQI3/bNiyFw73EKpXUnFZQv5j5lBpDz ljzvedGaCvKV3vtrTxA4vLv+vYwtFdpuqR3r309gXaeb2132UuH2N82tL6gE XvXkyAPOA1SQW/s8cY8cgZt/GbW/OEQF09/29rQ15DztGTk9eoQKsV/erIvr ZmHbB58LIo5R4bmEaIf0dxbeWPOUQ/c4OQ/0vust71j4m6XtIz9PKsjK/dFb vMrC4ptzPi6fo0JGgdgdPgkWHg6J4E48T4XD6X9dPBeYuPiju/3mC1Q4zuZy iaeDiV2N1/eHXqbCfPq0On8iE2frXuYXvE0F4XXT7VYyTGwpt8Nx4zMqeO89 tqHh7wg2vfBm++NEKmTxmviF1o5g7QZxA/4Usn+biCep6SNY+FY//8xLKmy3 kDXRPDyCW4lrJd/eUqFDZmd7cNEw9ij5KH/2CxVWMS8d3ntkCDtIKq0bqKTC I1vXvsO6Q9ja9+6Cw3cq/D30Y/0Q+xDWVXZs2FJDhbCUs8I3UgbxbMTcDclW Ktyy4JZi/zOAQw/rD2EmFSyTR9dYbuvHgflPGg3GqFC3TkudS6gfewlxlL6a IOdhR1vAofY+bPOlNi5qhgoBzE17f5zuw2Jap61OsOmD5JOW8VUPevHzpbSs daL6kFOh9Jar/A8ujZf1P8zQB38BphX9dzvu4/l6mdtMH0695EpX3d2Oec6f DXsL+tC9eHw+vLIN29mVx6/epg/H3FcXvctuxd2cXmWZdvrwRKJ4aeTSL8x2 Olfgn5s+GGcxT9at1GMzsE5/dp88/9NfyT3hn3Fx34Wurn5yvWeb/3+yZeif 99s7TkP6kEDL3aRh+BmZzw4ZtY7ow5vrHx08d5WjCt6D9+vH9OEVZ/FYb1AF qtU2NP8yrw9X/l2Xs637jvoDJ5PT1xpAFcNWf/h9HVq39qS7P80A3qiF113j b0N2j5KFJ40M4PsGgYy4e20oSq6t5LSJAfxr3d1AF2xHktSdEh7IAC67rTNY LfwbbTyg8tVhpwE0CaoX3RboREZJvWpw2ABi9SUrh2e7kTPNicV30wAWVuXI 5sX2IRmt9wIXbxnATUOcHfizD7Up8lFHbxvA9UaoaCL5c69owfkf9wwg6ObK 8CHvfrRjSoTtbqwBsFruyrsyBpDu2x/CazMM4GoZQbEoG0SstI204CwDKHiU EMc9MYjSEy8cYGUbwJRz2i07uSGkeF/laXWuATQ/MnLxChpCkj7Xle5hAxjv OFsaqz6M2LQYdIEGA8gffr+m+OwI+qj40CGkyQCyWhiW6rEjKEh6+NLYLwNw PaJ2jKdkBE2veVxa89sA0q08LAV4RtHQyKTl/QED8DstRFGJGUWpPTu92YYN oEuoaONU3ihyaUuMPDNqAGHKdR+UWkbR7282jXbjBmDC8t5RKMlEtWnph4UW DOC3yX64/pCJIhLZr1xdMoDSgnlF9zdMZBl7MHninwFU37li9/IHE5Xf4hqs W0WD3bzmr4CDhQrcXc48XEuDWy3tabknWMj/yIeHHII0MHU2YJ4JYSHqfsFc X2EarC4Jtb3+iOTTrSXzuyVosC883yK9jIWSFKWui8jTIO2X6LtRYQLd13lf VqBAg/nGzu/1ygS6YmLNcUSZBvafO2WYxgQ6Ynf5apoGDdT+Ptn+jry/73KU KN2lTQPn0Gv/HT5NIFP3bLYpXRrEHVLQpF8mkNSlnpBNhjSI2BtgExhPIN5b F3EPnQb/OaxL/Z1GoLkHoiu3GDRA4VaF3rkEGnyaaaZlRsa7XVdrlBKo+eW2 y/VAA//dTlyiVQT68q7rY4AFDWzOyW5TbSZQzsfAZeltNPg7c2X/iS4CpXwV 2lS2gwZvrhyorx0k+bEh/dIJKxroCV4+fHyMQFc7LYr5bWigTvQ+l58h+Wj4 9+JbOxpIhcUc4SH56ui0P+PAHhocMf6yU5LkL5uVdReX9tEgaKVe257ks018 aYVJB2lwSnJP1zuS3zTFzBe2OdLg6G0Rw00k30lT2oyZh2nQfJciMU7y3xqN cxceONNg82Clzw+SDxdo/B8MXWkQIh9vWEPGI5A61+5Gg+S0MycXyedbrczo Vz1owKp3lbAj833d/ytA+SQN+r81WFeT5+UfO5P/w5sGnw8dUzlH1vPiFO/s mTM0+PRi9Ic5WW9MQLKh+DkafPh6x8OY7OfGNcb5In8a7LKJNHAg+z0X0Zjr HEgDr7SzZ56TerjEev9dfZH0J6TRTXKIQPYpXLTXwTS4On3+RB6pJ2Ql+Nld oYHiT426y6TeOh/oOX+vkfPw6Ce3L+mHbHnd1JObNJh9aXThPunXUuuqc/3h NDDTODpu94pAo31P34VH0MDKesu/KdL/tjHapM59GnyZljlQHkGggtUeZ4Ni aCBhIewwRs7PS0H2t3Kx5Hy4tdlbHSHQow1Pxsuf0OAk2w+dX9YE8ter8hFI pAEOPPDoqgqBjpu6vclJpkFRTv6bJBEC7SWh/1AqOT/vn9RO/yPn/7Du6efp NLgcczzFqIGFiLDoU8a5NGg8e/npTl8W6ojSyujMp8G/SI+vGw6yUNWzitHr hTQ4WzBRoLqJhdJz5rx+YhqkfJzePcvJQu7dTp6u32nAoRXYdusOE/lx37Bq ryL1/hJYfNmbia5pv9baU0ODERVvhXobJvrv0vzE5kYadM94lTwUYKJGyUdB GztpYJ1g3Bh3exRttq+582eCBvXHNuwqcx5BdoEz3oemSf0o0qd5jUfQkQQZ u7oZGtx/f6AbC46gC6yToqWLpB8CH/pCSoZR9m2e/xJXG0LYf8qMsyLDSKbM POvoekPgsrt1cPvzQaQ+7HH/1wZDCJ4+Uq/gN4jogvd9bWUNIXNx6tBNi0G0 90inIVIwBDFEM+voHkDhC0FYVssQBJZytvOID6A5ak5tBxiCsOIrmYiTfagx RXnK0cMQemKvOHpUdyPRzshJnpOGIB0t+SXyTjfaKzk/kettCLHJb5Kcdnaj hrs/xgXOGULS2+So9ltdqN7/DPE5mHw+/pawmVcHqt1eOKwRZQjP8uuyrwi3 ourRXd2LHw0hF9EFdvLUogp9/+p4ESMoSjnjIbvnBVYMP+WzQdwIHnj5crzH 6fh6t6tQvKQRrLm6Mtei8QZDxO59T2SMQO1e88ft7Dm4cECnI1bFCKhp1fZ1 DcU4M26EGcMwgvVhJjrcupU4euUo/31XI5BsDJRNMGjEk/sOZAm4G0FW5f2w vqJGbJ9hYxfpYQTzx9Jmf25uwusObYq+520EDY/O3wizbcZh76SkIwLIdZ3g v1uOt+CLbk0a4XeMAKrzyu4G/sYuPyytbrw3Arfy3FtB0j2Ycf+Y62yuEax4 MFOT9vdg0X2BF70KjEDrppmu7/0eXNGZ+truoxFwC/6e4l3Vi9Um2fhlKo1g VDBzkdnbi8cl86ty24yg8eZy9taofvyto7pPtcMIytSjORwr+3Fyct9SfJcR BL+6y1i12I/3agprXeszgtN5x8q4jg3gfOQdYUMYwdTO0rZ3KoP4sruCzSA7 HZw/83478WwIH9AwcXfgpAMIbt3N+YO8b43bXa7mokN7yqp0mdkh3HPhctb7 NXTYE1N6tnTXMN4a0bruihgdQh48iUqbHsayu8eVpyToUNh9JpdLZgTPiHMj dyk67AJTk19bRnBaooGPtRwd+lrdT3x/OIL5cyJrJNXocHDxYH2zyijuD3wx eEeDDrRXpy6mWo3ikk0fV/5p0aFia17179Oj+EzliE4/lQ51ZWfqrrwfxQ1t W++/NaWD5Epv72UaE2ckOKUpIjqYvPS2PreXiW8cP/fpsTkdfjv636n0ZWJD InE8eBsdhu54nLuTycRP2JfsLO3o8DNqh7HbBhZObd0bOrmbDh4TchvdjFg4 +21m0ZN9dPB5t9k7YTcLVxw7qjzqQIeJxF8FJaEsXGdc4Bh1mA4v73x8mJTA wr+FhB4wnOmg0yh6rTCfhSdLyxbvuNHB7Ffri/B+Fl6O26Bn4EEHxYmoSbTI wjy+fu6/vegwfef+FRVBAstuVK7TPEOHdJH3g7eNCKy2cJmryZcO0i7XJVZZ Etig/hcj2J8O7LekjV47EnjntdsvqoPooPZT3vbmJQLvdehp9w+mQ+v7rD+5 dwh8hMoQkr1CBxmJM7HCT0ie4YveVnGNDtlTRs1PXhLYr4d58fRNsv6YLC6b HAKHFG59Kx5Ghyc6x59pfCL55eGzgZJwOlR7/pHS/0HgGK/ZDSci6LB+MI/j eBOBEzfb2QvcJ/UpvtP/sZPAr6VeheY/pMPYL3UnGCR5aJK9+GgMHf7tjeQZ JQhc+t1hgjuWDomFYzEf/xK4Kvm9cvYTOvBs/FqQv0jgX0H8Tgf/o4OwRa92 K9sY7tnt9oAtkQ6cbi5YfvUYZqmXVKQl06Fer9zkAc8YnuOQWLJLpcN1r5Eg lTVjeFW7j978Szq8vijr2kfy6Lr3X92T0ukwOC7aXUny6vo78k93ZtIhv2Js sO7/7xO7BtVNvKGD+RMUxEHGOowGrifv6PAub1XiITKfiYim6eZcOlizvTr5 izxv6+iNsyP5dNj6kXv+IlmP3eeOFw8L6fDX1Nl7O/sYdow3/G3ykQ5rj+yf JX9/sfu5SKFeTNYzPfpzzwyBz1oNbbtTRodAoSBazBjJdwrml/S/kJ83jVf+ /0i9bi3GvW2vpMNVTY/eyC4CP2yYHLj+nQ6N7j3tO5sJ/PL6c/vGGjo0dCYI GJcS+J3jcuilejqcWveP6pNL4GL9/cWKTXR4n6X3tiaNwPW93Cr+baSfm/wn hCII3FHk7CTTQQcuB8/e6WACD0V9ePCliw5iFr8iOU8T+J/FySWxfjo48Yi2 ZFgRmFe6XK9kkNRn0G54mzGBRaelT7iP0MGzMD9BUJnA6s9/1uWN0UGhydnC cJmF93NSXx5YoIPc6K2NvUksfGVOMqR+iQ7PZDi+fQpn4VfMlf27VuiwL/Kz zZgvCy81VnNZcBrDtRZ0arM5C6ekerprrzMGL9Eg+7YmJq6KszN7JWgMx4OW NA5+YOKZCCNxRRFjKB9ZctB+SvLo+dUV6yWNoV/2YMPgUSYe35aktHqjMTkP eRyZXaNYihG2HKJoDPKveqhrSkaxhY5P04KyMTStsvD6Hj+KH0lsujmuYQwH XkrEn9k3ik2HWvraaWQ+nujY4NIRfPu24PN3O43Bx03M+V3wMH4XPHtRy9oY tsTur83ZPYx/n+3ck2ZjDG36bA80VYaxrkPGqmd7jEH30uLFqz+HcLP6Dtfb h42BOehbPCg+hDdWhWx0PmsMFs/C/v6JHMDF68YS18YZQ0lDbHy6Zi+WFJd8 9DHeGD4mnZTeQvTgczLmd7yfGcNPwn/xzJserK4Z5V+dYgwtGueN7ur24Lid RpYRWcaQefGo3JLWH3z+RsgUf7kxdLS9yn6r3Yl1FwS28Y8Zg37grBN2bsKp /bqjfFtN4Jvo4YIa/1R8yfHC/qztJnC/03jM41si3l1XWmpvaQLufDlPPY1j 8b/i3bGxtibAfUChsUnsPN4f7bdV2cEEvgyKe1j1JCAui4IEcx8TuHaVw+d3 ciHySER7A+NM4MNCpo11WQ0yEw/DG56aACtReyHJtxaJ3q1Vx89MgE1jUbBm VR36FHCMneu5CbyJp9joKdWj9bbXs6KyTOCp4wPOz66N6PtyBc+bzyawZSK9 zb+6BWk42nzsZ5lAxuM/0reedSMKS/GH47gJ0H53fuNoJ+8jIYstdZMmMJfz h1dX4g/6l5w2/XHWBPZW5ryNu/cH1Y1waD5iZ4ARsjp17UIPCgjKf7JNjAEt Aqpc3mZ96BT/vbRiCQYUC1RPH/TvQ87PjudRpRjQNeVW2/W6D1mWCdXLyjHg vdBoVIFEP5LhIy/gqgxguzKmf3qkH32OowS+NGXAv6P9wulBg6hAY/amDGKA JXrjG5c+iDI+VkdFmTPA/vT5Ff62QfToT9CbkG0MKE+RWnfRaAh5qjUNHLBj gNmGswetmUPoSNHr6erdDMht3XXGUHIY7d51jWPLPgbMFh8vjrMYRqZndWR1 HRiwNistriJ2GAl8uL2P5zgD9PdGhEWbjiBOK2fXy+4M+MZo36NwfATN/TY8 O+3BgKV0837KnRHUw9Z3t9ubAWH/7A66/hpBuTvMygsCGLDn83/KvR6jyLFl kup5hwGNDD2HytPk/TZ4zRHRewyo9zdo0ItkorSNirfxfQYsXvX/1Z7FRDOn 9nWJPWLAyapbx4dHmUhG+DRfaSwDtGR8fSx5WWhLfijtVDwDDmaL8A0osdBD 9oI7ZYkMcMzgR1+dWOjDi9o87xQGuLzKjeIPYKFuq+E/ki8YoIYWmaH3WUjr kRTd5zUD9Bzl/NaXstBX9eC+DXkMMK5SnouTJNBYTYxAZQEDrkbPOPtqEkjc P8vEt4gBMw4lahcQgVxx1/2vn8g4r+35OlcChR+fKzr3mQHUO6fq4s8RKJtX aFC2ggE7Z5/t3nudQP/2bN7k/4MBjx5df7klkUBK8w4elJ8MSDv+lXExk0DW z85F/ahlwEO5+dS2DwTytbhbcr6BAbufzzi5fCFQ3NDzYflmBtj0fOsWqiXQ p4iPotUtDCilvy8caiXQALUZBbYzwKmEHjzQ8//3dwkvhU4GcJ/RL+cbJZBB MPejn90MqLVoN9g3SSDHjZTSC70MWJGpD/4yR6BrlXSm4gADslO1Djj+I1Da KXuJ2iEGUGZDromvGkM1Ql6bL44y4LNe1/cZrjE0k3fNW5lgwNvuUc4lXpJX neJj68YZwGnavE6Z5E8L9pzPl6YYIL/Zpdbv/+/vvqgiVGYYMPdyxGSIjB9Y 9a9vmGNAW4LLzitkXDC+vOXyIgMMzu9n20Tu74oRP6P2jwEnOEe9ZfnGEBdD J76RzRQi59tfKXKPIa3u7RUhq0yhdD6wyZasb+9N5wl1LlPYH520IfH//69V vyDdzGMKc0KfssXmCZRU82D71TWm8N+Gz/XZZP9f/dJ9NdeZwmeG+LezpD7E +s///RI0BS9GXN/BXgKJ4fav10RM4abToxD3NgKZHp+e0hI3BXG//OUnpP6u vGvlWiVNgX1g/scM6U94lpLljQ3k+s0k56BCArXM7U9so5jC1F7jvgXS75X/ fH7cVCDXR+6w5h4SSNkibEZX2RSOJw1MUG78n6c/WN/SMIWQxQvXJ8h5ekKt D6Bqm8Kj4Pe+8btJv3+NJHfomoJGVRXFFwi0bqP0vL6hKbTuoXSkrSd5tbes 4i3dFE75fgr14SLn5blntA7DFEzoUr1XJllIUSVfRwNMoXLkv9ehX1nIRHO3 +0ZLU3h78fZjg1MsdIU1p59obQoJpooV7ntY6EtWArusrSlkDmrqjxizkJ0e 6+n6vaZwP+HEpSGSX90MwxoEj5gCqhUZ6HjIROmz2kn3nE0h73XJQo4fE40X NJ3mdzWFK4KPUf8+JgpiKPDxeJgCT/b1d/vEmeg+lMDKWVNQ7KjPiIkcRcWW 05msm6bAOnnSP578fuHgj794MswU3LqVZu6T3z/bq813DoebgrngjolJkRFU bxvZ1xdJ7j8X95K9dBgN7VXf8DvOFD7ITA35iA4j0aPOYd8zST3NRi9WJA2i k+eqXF42mUKj18R6H+c+pJ7y8IVkiyksCrZc/6rWh0bqD47cbjOFvWf9dn+a 7EVe1P6zp7pM4WTKSs7962Q8sXxFb9gUDrVte9qe2IO8fHQS/tdwvUdDncZh AGdZmo4kR25F2FUOiiJsNe/7lSgkuiARUZaIWRERyqVUIglTkh2y2lKbOZTK 1oshd3JdYhCNMOPnWrml/f35/PU85/nvU7q0C/RdtX53qB/Avv6pPc2/MGGF 0GWR1dqNvU8ePTIXxARXSe/QoN0V2Cn/xPPsECbEfunXslUux/tGfRUtw5ig 5zqt8qiHYH1WeNetSCaMNoY1qBiW4tmITDe9BCbwV49VHW/j4vjU3lPuWUxI e6lWIOMeSPLKT5yrfMeEtwaWvbpGPJIhebrTr5YJRnG8Tq5bJbm6N8h0TQMT ZF/J1XddriJnGmPmj7cwocEq6sdEZzUx7s6N+tbDhKrfZAUPghsIb/LTZd0p JtTrJO6Srm0lgxtOZ6SsQxBb3X3dM6uHTEf/uMtQR+D681SM+fpeItGXfj9W A8GRNcz+3Hu95NesirwQbQRC0U2x/jt84qO8vuioAYJreml/Tt7oJyK55mYN CwSh/9guXHnykSyxvNvuWiKwr9tvxP/8kaxqXuyU34fg2RtFAV9rkGxJ0umT tEPAl9dc7GIPkiBGrGjECYH4Iq80KWqIfBXfzuD6IRhQPDv81ERApDzrZXQD EDSpHeAt+wuIUpmn3AMWghXxM3ODHAExi05WSg+h+z39cjwYw+TCwmft8GgE S31DXuIdw0RsJnO3eSqClMC5qTzHESJ3aKvV6zQENdcvFkbHjRBNbrW1ERuB dIbZZHvhCNnNmnXQzkJwsPjgmSnGKIkX2nkw8hH8nSqhWvl8lDA+iUW2vEJw 616xbf70GOFsSVRP+xdBiF317Ng6ITELX1vuRBCw7V0Cg/YIia+srlRvJQJR nZMG87aQ1JgdThluRnDYlhLmbBKRE3H8bY9aEWxlm3lU24jIXKNPh38HAq4h p08zQEQ2nYxUnfqAACX5qf/xTESuJP2VtyhA4Dsnx7DRHSfqXQZ7344gMKxS Vpi0GicvtF6PXhIi0FnN0C3zGieCkqYtUlMIuhQKkrvZ4yTyJ5eWmhkEw/X/ RWtwx4mC3VBw4lcEC8Gb39yoHSd7Br+9lFtCcPlcR837b7RX9WNd25YROLy3 upi/ivZgmMxyujiGRzxPp/taFMmT0bRYJ43BwMKYM2ZNkV3OBQI+A0OJeNde 7EaR9pztVzkyGJJyTCO4ARSRMLVp1JbHEGkQ5SikvZEZ084aUcDwjvcqlptF kW0N7vIFShgc+25apD6mSJ3iaHGAKgZmacXMjRKKeHkGOxuq0X2h4fMcHkUW Cr7PT2/AEFh5qKqxifbQ14Ss51oYSt3DWuW7aX+Yy+Pz2hjeKhXkswYpUpGY 9XGHDoa0TLfWoTGKHOvcGP9dFwOnqWgycJoi0xrcjWWbMQh6sx/KzdO+9d9Z G2uI4Vo7/2HNMkU0X1T5WxphyBPKPM2QmCAvxRxkV5hgWH/saVSENO092w+F dWYYOhr0hcErJ8hI+qnDSTsxWLGELbG0Ny8NUF/sEQa766DykPaksl74HXlz DLgkqmiAzoXnJHZ2WGDwyJ+8b0DnfWVJfLYV/df5oYHbtDf7VypfOmaNIaHg 3s1VjAkS6pirpbYfg0+mc00W7U1Zjn5V/wF6X4pNsTntzfyxFz65BzG8PstO WKL9jLabr/Q+gsF4yTqmkfZ158X6J5ucMexIPyAspv0dWOdoP+aCQbbcV7Vo mCJSawemnrhhkNTRCazhUyTbwy+N5YFhGPU6fGmjiMnjWZNtXhj6kq+Y7qil SNNsdPfsKQy5nPoc9hvat5gRWeKD4ULyoIoslyLfr91Wj/DDcBrijLMfUOR/ DKMLCg== "]]}}, 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, Automatic}, {Automatic, Automatic}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImageSize->400, Method->{"DefaultBoundaryStyle" -> Automatic, "ScalingFunctions" -> None}, PlotRange-> NCache[{{0, 10 Pi}, {-0.9704476850332168, 0.9704476500239698}}, {{ 0, 31.41592653589793}, {-0.9704476850332168, 0.9704476500239698}}], PlotRangeClipping->True, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}], ",", GraphicsBox[{{}, {}, {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwU2nc4FVwYAPCb7OyVEQmp7L1zDiIkoygZGWXv7H2N7HFx7WumQpKKknWs SFGSVGRklCJJKbS+8/31Pb/nHec94+I+fQec/U65UBEIhN/UBML//+33zeyx S7iqTZCzEs1nk+96yTz+aqM9ARBu6l9rMGNFbWn8zwfb8wChfvxp48n9SHqo 8+Sd9iuAsIfuQdRxWeTqzppxvf0uIOSTHtPLA7RbTU2yur0PEEi7lLtfm6Io w5mftj/7AUHd01HI1hz9sE7s51YcAMQDHFoehhboU/iofWr9I0C4qnkXCJ1G Y+3uJP/iEUBoTA5pbT6DnlcMR1S0vwAEioa8Z4Q9Yqnd7xR1bhwQckSnpo6f R8ZNl46f+4nt69tA5HBA/d28XJyKE4Dowf2l0MwRtb67eDOp/jUgTtc+YHvs hDY/3s+7YPgGEAd/LFeJOSOFDcYI+P4NIMj2kxOjnVED1W2DnQNTgOjbd0VE 4gKqFP0z61M8DYjJi+M3fC6iaUnzAWPVGUAk/dJ88eAi4le60nDoJXZe3Ys9 1C7IuLqmw59+DhCCCtLJuS7IXfyprMPZOUA8h66MTbig5Pqf1SevYatd+/iH 1xX13zFOlTj2DhANpO/8LXBF8ypBv3nzsCdTrJ6NuaJd7WV+dPPY1Tf4Ipnc kHbfutVi7DwgMEIxk3A3ZHecf2js6TwgupZ8cWpwQ5FP9LR6BBcAQYo/R2na DbW+KBApb8f+EbdGo+aOeLuotOXYFwFhksXJ38UdhdX6nut1xf6peOMwyR29 zp0MsuzA/vPg4ZFWd6QebUB6z74ECDUNh3ym3VGJ250bYW7Yt5+yrfxzRzsW QoOMndif+X0q93sgG620eQrHe0DgMXifpeWB2sR//JFxx95WO3j/jAfiZ3fm 6+nErvbv4vX1QBG/RpROc34ABKZs4zvxHmhySd18yR075nFsHNkDaY5e9Qrt wrb9HZVwxQNR2tiTGbiWcT8R/Qe3PNDvmujqUg/sRYFi8QceyC77Y6c0wtY+ UvUUeaCOcKs3iOsjIPg/l2nu80D7LvZ8t/DEZpCfetPvgaJMpdkWEfYYk7gu jr9VK5YM4f4ECPx7er50eaCjojTH6b2wgzKtlu97oHLmAOeSbuyutxT5Rg/0 9+fbaCmeFUCwzBN7XuWBzs8bFnd5Ya+P047keqCu4eZm8x7sVl9mqTgPJHRf eHSeZxUQErJfbnp7oNiqjJUgb2xXaT5FfD5z6Vu0dL3Yt5/7reHzgyEXRYr3 fsbvU09T9oAHqnQcPSrpg13xXfgPlQcinNA619n7v20tnebdUc9+LtI7nzVA EOQ4wF/ijkQYiTcC+7BbterTLrmj+O8rAzR8XwBhw+PdE0N3pDvU9+dIP/YR 47sza25o7E0h0wzTOiDoH9ft7nJDVM9O8l9XxV55E1iQ4YacHzxQVs/E5r4u 5ijihnIb/fSoWrH3mlpEfnJFvVcOWjyZx164KT3V5IpEsnK87dW+4vM6vf+e mitacPa4EreArSrD2K/sgris9982ZtkABLKEadzXi+jYyZddnOrYN8SL6Rou ohpVncmrWdiLF26sCV5EF5n42B+rfwME4k6N7Q9ntNTyKIaD9B0QhqXrxNIc EcHHsYWmFVvhWWkBdET8YlsrW7PYifbBS58dkHnuoXOzspuAIF5/nDJ4HrX5 Jik2PMOe+f1uMc4OZR06tqzP+hMQOJi/nztgjWpnpoTUVbEvUVX9KT2L+vID raQcsDU6hHR5z6Kt3Vd6OW5hTwpIt3CfQc5zu8pmTbcA4dhtgchDliiqsPjF WAj2p7vEhdunUaGpPONAOTYjuD2ifRoNdziGNqxhL3cF3HQ4hVSKkUV41jb+ eecf6tVpjszNz6Z438MWcokywz8/vei+dDnMYDNdyPTeMkOVwUJSBjI7gBAm 4/k60xS1Sd1zVj+DvV54v3/uJHq5cLJYKgbbPJ/mndpJxHgqmpbzKbbhOZ/o rRNIjIH7KO0PbDi0Lud4AoHuhsBtwV+AYPJKI3LEGAXJvJ2b9cFm6pkzazNC WUuBe1/kYze0+71UN0J1lD2mA53Yy6+p5roM0QyjZnsD829A2PeN1ur1cbTV M/a1Qhl76zmzv/dxxBnueTjPHnuVnTaA5jiSkaNySLqMDWdehl4xQIYfivPD b2I/Oviw28AAOZfLD3u/xCaUeVd+0UfRVkNUjn+wW58eYCzXR3f6tvwMTv7B 7+F3BZFBHw1HkK6pB2MHxeU/engMfZA/PC1Vhj1MdZM36Rii+og4hR9ii+mG nDI+hvZVnjXm/Ixt/Vv/EscxpHL2C5GW+y8gsP3azJrRQxYsyfe3tbCZMqrf NOoh74dCa6sXsRerR6IT9FBS1D2xuQxsrb363HZ6yFBAv5OxGbujj3VITQ8x tL2wUp7CTuE2ceHVQ4+tndccqP7h87gsRdnRRRk/15PSjmBnHExRmdVFpgWx +1vMscdVsjkHdBGbMkvrbCj26uvow7d00dgLijljBbbYUxNiiS7KuyT5UWkA O/GKvGaKLrJkb4tz+IytJo3MwnTRHmsxZn1GAiQ8GqDR99RF3te9zk0KYh+7 f7bWXheN/Lhz1U8e2/2soMApXSRjsPOVWh9buC7y1HFdlJWvo11ijW3tv81z VBeZK41O9Mdi0z+XfHREF91O2Ctqk4etNk+6IqyLOF6c9/tyDduw787SXl0U KHKtPbEN218xxoZVF40HfKbjf4pNqaDKptVFyj1KlrfeYTv2fd3/RwcVsEVV HtvE3hdxrm1DB/1w6Ft9Q78LEvoVtQU+6KCztxjV/fZhW2cqsU7qoNa/Fpep 5bB/798JeKKDeE2LnxfrYTcVMMu066DwsjlB2bPYNfsMtOp00OTqIc9+T+wg ++jifB2kqeV371wM9uiY+U6sDqKk36P6koOdcd1ul7sO+jP5xzTxKrZllo3D SR10XkK/lO8BdkqI8XNZHYTCMz40Dv/fL4ZOmFUHCQ+9UDw2h73c+nb/CkRx vALEN9+w7V7zNfVBNO/mPOxLR4XvY/R6WxFEevfreKkFsL3jyxQ9Iaqh/Xqx WAZ7ef09jRpELldj//RZYddGBchmAzTwfcDonAe2dWpQGztA4sdYCtaisN1H GlnTtVFyntV8Agmbl75keucoWp6nyPDVYG8Fa7xzPIqMFBYjGu9jd5NOLnVo ofo4yUG9J9hs3BE9LFrIW7jNwXcD+/WdNo88DTTit6thN+1uSCAZqGY+VEcy yHCriA+7luActqqG1u1fkfogdljB4pW9qsjiptC0teX/jvgRIqCC7vx2ObLm hu3/+KoypzIKLP3ew5uN3b2U8G5aAY1/0mRprMaeOwSymuSRkkaCjd497CL2 zNgQOfTjNfs3n+n/19++q3tfEkXwyIr1SVJDgnlSQRubMPL6l2SzSwe7+/qp di0+ZLc8QwJnsCs3J+x5ORBoy/rTTsQmaCzcurTcRX1+baL5JTasfrKbTgj8 MDBg/vbp//jD4XvBouCDbLmePIEGv8e65/10h8HjXaZNNyWw53zW6QbkQPbV m6nXYrEJHw7M0GkCYhZN9yIZO+xIUWLXUXAp1P6HSD12OX83ly4ElkbMFyrG sd/724kL6QH+z95aRUdoIUFbQKZcxgjUKEl9SX2BTbFS/ml4GhQIJh58tIxd ZaguLW0Jkmnf2tL+xfZPmZTlsgKer9MfxR+mgwRukXiTT2eAbNRKVWQ0tlw9 TG+xAW199ZY+h+ghoeuS7V4bJ/Ds1JE280gGOMd4ypL80gPc27dBLZbNAIl3 h5YFz3gCyvs2s5/VDBAm+H+jTHgCjwiTpbLHDHB9otDQ4JUX2F3tx7bCxwgJ Oa38f176ANWvLa6XWxnhetjDpbuz/kCoPea29TAjLDrRdWltXwCgvnz8t+Qc IyTFPlQdOhcAnvO+yRmj2wMJukNTx8cCgBf83bH/7B5oHnTNr6PzEqjI1uVs 29wD57Q4n/WEB4Gkc3vOZzIwQahc5H+8MQh4i47XOgpifxdL5JgPAur3XbTp 9Jmg46caRtfjweDFTIqHJZkJEpjHgm3oQ0BbrUXzoVom2G0iXOCmEgIqL/H/ 22nHcY+U8ZQLIcCHtoFctcAEiVHX2f+0hQA6mWdoTYEZEocGb6qeDwVrPwsZ ew2YISwb2QxODAXjPY5W+TbMkNAXTVVRFwqqrDY+acYzw+795ey566EgZX+7 MmsBjn9Ts7TiCAO+HxOI83W437QC3YZCGNCM5uZJfY6t/ujVDf8wIHJ8xtFu CdcfebncnRkG6Nmv35Ddxuulq1tU1IWBlzVqOhPCLBAWb0+UT4eBDt9dGXVK LJCoxqt6ezMMVKs9nogyxPFG1rf+TOHAb9jWW9SfBRLGp6c2lMPBe1nlqorL ON5xt0vZOBzY5bFMCJTiuM225KJdOHjx4wNjUROOR0ba7fiEA2ObHsA1gM1j GBkYHQ56OkuCSFMssPug4A2j9HCgdiCojukr9n1rppDCcHAr8eRMCi0rhKye fetV4UB8WZyTZh8rJER+2LlTHw7KThAM4+SxNa5kdNwOB1y33kT9MWCFRP3d H5nvh4N0jru3w+1w/AJz1bW2cEAVkvF+MwDbMSvgckc4CH/jInApGecnJJnU Yq9rAfM1CrYexwWm9nDgVsl72fMONtdT2Ubcb2b3xoP3g7ietTku9U44sHJ7 suY8jT0Rl158IxwMP64Rnd3AXhy0fVsdDkT2ggZpajZIWMnmtiwKB9OPbgys sLBBou2ng1QZ4aAogvddHR+2fXL6B3wellKXf7mJYfefXKT2DQdsM1+5xWVx fZFDpA0+zyfZ5+UW1bF/pZ5dNgwHSTpPjKuP4fwjQsaNiuFA95uqi6MZtoT8 3xv7wsHfmppYIRucX3wYvNsdDh6cYS95exHHqZsuW3wMA0H0Mc0lftiBIjv/ hsOAXNunp9YROF/7BcuXxjBwXbB/98ts7CCap8U+YcD5mZxQXgnOFymKtjUO A0JxZWoWV3E82umXx8EwQF4M8Rlpw/YOnoueCAXmBQvJ6Q+xz20nZjaEgj2G 5tVGo9hdru3/iKEg/saRVw+XsFMsxnkPhgJt+4KvCeu4v9gNh8HvIWCbZTeT 7i9slicly70hwP/SW9jFxg6Jqn+yymxCwHn17Pp7muyQwKHNOhIWDPhXfvUH GWBDB9ofWsHgJcV9VsEC57Ol1o38CwImBF2uW67Yz2abq+KCgMbg9+jrOTjf WdzvW0gg4LGysSj6gO0hVf9VPgC0dx87JraB8wvu+3557w8cpWRVm37j+LRr n1mpP7ixm1rwETsHJFBN5gZS+QN45+byT03sSAZdvnwf4MW6i3iWhG2rkxRb 6A7YIlcuLZRg30tKqf/hBu69f+nidxXbhEP+gZUb/t5SfyK5DVugaf4zpyso 8Lbce38Ru2VX1Sz5Augeut7Io86J9xsRy+FuD1yUc6uq9bC7B4d81ewAY1UU WcYU2/1ijdIeW2AVZhFhcAG7SaYo5r41+CT+Sz8kE3uj5UScpCXgSjSdfvkO m8su+a3ucfDgi9qo0yq24X57eU19cN5WtO/zD+w5oaghdT1Qp7BVS8PEhX8/ yh7LLNQG2u+qgpRVsB17DJw4ZYGH9uae/DRsYo38d7fDKIWfN9WLjO1P/CUY KINqf2jQ6pZjy/WE2ygroOVGIuHLbewUj3x5djXkvp9p0/ANthqvtfxNHeRO EJ35fYgb15fV9B8wQa695k0XH2Kz5NWfCjuLksoDpTWfYXO55JXQW6NrEQX1 7G+wN3TuDRdZo/cKb2u6VrFlXBxcH5xDLlfcinm5eCBhoE5V+48tupgYEz/s jL2Xx+qRqSNyNmiwVCLshYT9nly8Li7I2O+VwSwjtrE1CT50QQpFVOpp3Nhv 1veTxF0R1SdrwTkJbKaijy2rruhKJs37dCvsTZOa3GR3tDh+PnShHrv8ncvw thdyvcBekmvFC7sHH96dXgxAphlaGUcdsYdr7+05fAmptLjFLHtiT9R5NXld QrR0Xc7aROxz7bRnvl9C1+s9JT/V80L4ulToM2MQWv7a16FD4IMwkd7N3zAE eRBDZtfr+eBc0FVl93cRaJhv0vZ9Mx+s9E4QHD0YiWTuHn091cUHCSJ6c+ye kej7EvXzgTE+OHqj5yfXRiSKOZHXS9nhgyTBr1U+/6IQmafpqqExP0xyyOMN ZIxFP29ximhb8sPmLMfsb0axyMYotFzxPD8805jg+SMlFu2P0i4UusQPSQK2 0feoiKj+3XDK92J+yHTN5mZXJBF1N3z0qvzID2sbxVZj7eOQqMHJ5fxv/NAx g6NyOzQOJc02XUz/ww/ltMYu0uTGoRMcYfYh7AKwSf5cf19/HJoIpTUzUReA o/ar+Xli8UiN3fOJjp4AlJvgEzmhGY9K60eOq54UgHMWIgYxFvHIcZoMRZwE IPFPL49RVDxa0RVV2ErB8VdPZXY9iUemb5MaP+di50j8kJuOR03BnyQWKAKw m+Z4Yf9aPAqpvS36tEkAEo5bnmdhS0Cvdbgr+9r+j0vuQvsTkOZU2L4H/QLQ 8cFo0COZBERggdw1rwWg8Ga78YRxArpw/UpO8TzuP+Ix9/xsAhqAdCzZqwKw Um5nnOtiAjo86ZmW+APPt9TURfFLQOmBT2kjCPsgtGgX94hIQGtMCgl+jPsg YVeMenhiAjK/lv/vItc+KOw22/IkMwHdBduRNkL78Pnpfz5fkIB43thtmR3G +bNtfXLlCchZSvskpwLuB66xC15NQLdi91dPaO6DxGVGM+MbCej3GOFnsf4+ WLnb3qylKQEZis+fsDfD/Yf/xtu0JCByeF+l8DlcL8C9pfwgAb0brtlccMb5 y5Uheh0JSEY4yfi6N15/UfMrsSsBRQS6VXiGYNdKxK4hvN8Bw+/SRFy/Y/4t vTsBcfJLGH1NxfMFlfZbYzv67Clvzvt/3puslji/oXt1I7QM9//bUhTVmYC2 OJ8e17yO+3U4j4y2JSB9t1uUv004P+/fgOn9BJTbRvra04b7qzebfL+TgGaY Lxlc7sf7M1t+2XUzAUk4nS41fIrzdx5n3LiegEKbldb3vMY2eG9xvzIB9dPx 6D97h/O7us7PFSUgNtufxbkrOP4z/NwhUgKya3y9ZrWJ+1OfqstISkB1u9r0 +P7h+MldoWxRCUi3NupzBYcg/v2SzRiI7zPrl73uhX2CEL5VpbfA9z1lCgrF xbE3andOGCWgoM1dOjfVse/RSeRLJKBuw4V8fz1BSMji0nrHl4CYKf2fFE/i eFXSpj59Arqmm0xucxSE3dSLm9bz8Wgj3/1jtCdeL3+ik+FpPAIfjbR1gnD9 RZaOl63x6HU20/JgMq5vWhPpTY9HYguftdJzcL4Vz6eFwHgUoPIsx7QU92tr bBS1jUeM0zmaLxtxnO7FMcKheHRGLpBU1Ir7ZdQ8K98Tj64kWC7Z9uJ4icvL 81/ikJbE3uz5l9hH32QYN8ch31DK/JffuN8j2WJqpTjU9jha9S6tEOyu7kqe ZY9DdEIOGSFsQpAQ3BP6cY2IKvsPqPwRFYLQ+xw3+RoRjbFfT2U8geOik6Nl TESk2nBb7mCxECRaMBVaekcjE5PSnY4rOD5pdn2EPho5rib2WzZiK/Kvjl+J QmlS1taJfdiznwkvXkaitw1/Yxc+4/p2U5lciQgUf/PEsyrd/ZDo+XnAozwE PW1c8hFa3Y+/H5HpCey+aMH0meq9H9iVI/dT+HxQVOhbwnWCMP59vP1x44A3 Iu0deKy9Bzt6aIRZ0RO1nS0+7yuMLffcy8vWFTG/Bkkjxtjm6iYxhfbo7uuM l+kV2FC6UTaPC+3Mlf2LqsEm8FoGDK5r635sPOJbh03spSU83gfGtkejze9i p0T2VNgpgnV+bnHuQWytkAOVmfpAxr4spHwN2yCymp7mDKh9d3Pv7aMHIEG5 I0LwiAtY/9ilU62LPdMZH9XtAlQ3nnnlHce2fBsycsYVDFBtoGAL7L9TrElE N7AkquKu4YJ9N/Ae75AHEHHtau3LwF5IT6NV8gVln56em5g6AImXZr9q2wcC Q76LXfLvsBM+WFRcCwTfj2+LZL7H+XKht5nXA4HJVdFVva84Xj6/IZYQBH47 hMXcphXB5znzjFQfDGxeHriSIY/dLzQftisM8HQHreomY0fdyk+cjgK9awwW 5RkikOgk+sRXOhr4Cla0bOdgk8/YFEdHg4cRQzFNFBHYHUO1dEsoBgQpC7EL 3cGOlAqyvxALxuoHlbffikDhib2TxjtEkJXPH3tLQRSOruelUbISgGzV2rOv qqKw8nQMU8O9BDDa0CusdFQUQg2lzbKZBMDe79nbelwUdhshAUGZREDeaKPp tROFJCI1k8mTRFBsZpsxniQK5bjsevb9vgw0bGWneTJE4eGwF9M8B5LApOtu mXM5otA/7ITiI/0ksC/mxrPpUlG4yGVkqZOVBMobfnF8aMJmhoyyAsmghoFS vD0pCul1mBtkRFLAMW7/T5pzopBY8y+AQScFLAkf04xZEoXDohyLLg4pQFxt 9S3VOu7fe2SRXJIC6ly1hJloxGDTMwrVBcZUYHyJLcCUUQw6vj518L1YKvgU vdhDYhWD6/eQ2DPtVCCVn3GBm18MdtshQp9/Kmjse3tNSFYMCtORxh8MpwKz Z00/HZVwvdQU+vUuFaxPJhpeUReD/im1F5J+pAL5DalPh47h/PW/KW6CaWDs D0HT00gMsnnVvGmRTQOXGF6mN5iKQULs0wgtnTTQLBwtLX8O549K/HrrlIa/ z1jEBJ7HjndtWvNPA5uqB5+1XMDW0EJHYtNAgd72/i13MVhJfLk/IyMNqJiN +Gv4ikHi46kTnMVp4JVNVU9UIJ7vSIVWR00aCHMN5kBhYhAe9/ZIuJUGeC8Z XdgVg/2aY+DigzTwIFqwWS8B5yuW9dj24v49zMaSKXj/yd+d5obSQBDN31mO TDE4d5gkTxpNA6eM1oJ3cvA8uavGrhNpQC5zZs98Ad4Pn0iaw1QaYHn+tGqo FNefzz4bOZsGVrmQ6u1K3H/2xXLrfBp4bH1rpOgqjsNUpr1LaaCWUnGBWI/r fwZLkN+ngaS57G23W3i+mQU9mQ9p4KIYMdusGceDBL7P47iuu/9B1Qe4Pnp3 wC1cL9zg2C7Uhd27lE5aSAN/v5hb0Pbh/HzrO/FzaeCtos6Hz4N43u6TX+Le poG2UPnol8N4njSD1dRXaaCo/QBn53N8nhnveAqfp4GQf+x1NRP/z5/GWvcY 34ceFciYwvXTyR0In49C8sZ44Bz28x+1k/j82J7Me9ou4fOpf0C7jc93jeUF Qe8TrhfMbOK7mgaGT/UVSHzB86jpSmni+0mZvNK7vYW9acMTHpMGXIXI1u/+ YKe/+kPySwPHnBPXHlEdhMSzM42VDmmA8OkifxETNr9JZqlWGpiRtmqKZT8I CbujmhKOpIGOAH0DNx4cH1SXPs+N73v74CUVYezcELaVj6ngzFEeeqGD2CeO OZaNpQKlONpyGglc3/RpQacNv1/6D0PjigchpI+74JCUCp6avHLoUDsIuyeH 1ic8U0EDaXDzylHsTYvpo6apwJ239kDgcZw/5Y1esqcCA7ui+zYmuP8+Plva jRQgVplyUtcCew9LofjzFDB3yCOc3RabR1tSPSMFWKtKPL/li+u9pAy6NpOB SiS/W2Egju9SaksYSQZciPFPTBhe74GrOaxJBqMGK4dN43Fc70J8jWkyMDzT QFzN/z/fjeVsYRJQDZaRO9KJHenUI7yTCCJmqwmRvbh+Z89zUmci6DDa+3x4 EMcZd/36E5sIoBDhkv8Y3j86Ufx6VyIwHHx+9/4HHE9YUH+1HQ+s+YJVDTjE ITQBb7m7iSCis137gps4/n494/SlKhR0HJJjbfHGnjxQeP13CPibUzNLe0kc Eg7p+r89EwLiXTOJ9VE4ztU/KM8YDNJYHXq/5mDTDN9o9rkESp2oDIgdOF+3 VPikvSfooDE6WcZ+CBJex2gxVx8HWrVvnMk82OPavIdp9EC7sWdYugB25dr4 xqQWaMtOvxJ+ELvpOgPH0YPgPt/TbSt1bOGnxpyK6uiO9OlrLE7YGdJ2hOyz qNbK/l9sE7be50f9dV7o8NZnrtAW7GPXvC8WeaPrJTESvm3YNd+nHS77oGuz FVZ2/dhJrS7hNn7oisf8DbXX2DlfyCfCAlB5tJv113+HIHGW7Hv5YxAiXw24 7Wx2GM8T+oPaKhKF+Sbt6rfEZr1/YgFFIlvVUouDNochkbui6pREFBIZ6v/6 4SKOB5JqP/+JQk2rexV8InD8B+WkW2UMGlbsuhN69TCEJ4+zhq0QEXUvY3PG L5z/7N+3F6yJaDltP/Ua4Qjsnv1Gl6WTiJ6cVrI0oz0CCVSBx7QCE1Hukv13 dnZsHl52v4lEJMxwW6lQ/AisVHnXxkK5jLTMz7ZUWWAftwj4I5qMgmau3Lt3 Hdsnyf2QUBoySfy58bcB17PVHk4/kYYOSpyQPX4Hxx+X370floYmgjeuv+rA PupH6zyWhlSZdYq3nh+BowN1TBPx6WhHcyZS4/cR6B+g9AJOZKCxd/Kt8bsk YBO9dpH8vwx0I/ny98e0ErAyPTJi8FAmsnsh5WPLLgFH52a+TYRmok7PyPNR 4hIwzERHXIAzCxGLeXW6zCXgudkZ2WTFbGQNvKNpz0jA1leW2/pW2Uh+CT0w tZWA+mEBuiEh2Whezk1h1kUCmpYyvBW8n430HrWIEiIl4NvbseQ8XhLa58vg aEiUgIcddhrpDpHQd057CumyBDzGCkzFlUmoxoGa+wBJAgofUVm0Mych2p+n aHWv4vmdAj5Fx5PQDOWablq9BEwZoVLlziKh+7o7MWO38LwFyknHi0nIPavq p3Mb3s+FWvmgRhKCSpuKN5AEZLuvv+jVSkJ8k4b+3/olYK3u3q2fPST0+OD6 csIzCajWVpA88IKEqp/oHRwex+sVtIvRvCWhyIBCJ65JCSh3mew8ukBClntX yuxm8f4flg0dXCEhqU7tyZpFCbhss6uOaoOEqC/k8nz+iM/XMonn4hYJvaV/ f0r5C/b3NUbDvyTU3KieHf1dAhKvqRTc3J2DMi0znzzcxvsVsy7Ko89B1Qp/ TO7+lYAkVlb920w5qJXN52nlbknYzS0cYM+Wg56uvTXLopeE/g0FJQWcOWhx 2OR5JDOOn9NhtuXJQTv1Hac8OCThXIrUfC1vDmJNlRo/s1cSVlLJ/Ivmz0Fi bhSrY/skoXlAHM9rgRykoc/0Sv6AJBSuIjQ278tB5qJR1vvFJeFoMrMkh2AO ct21+oZJUhJC8Vv06zgeNWtruyOL829MVpzEzul88vaDEo7HE7glcL9rpZrn X6rj9dw5rRP5clBH+I3ZXm1JKEdVLWa7NweNnRVwatKThMRfVFQ3uXLQsnL6 fJkhzv+YpxfGnoP+cv66kH4Sz0fYw9DOnIO4NjyXwk5JQkLnlHYgQw6SGJ10 dT2L6yOOVJRT5yDQaLx82k4SkiaVz2v+w/eT0eah44TPZ9xHyGibhDw9JVZk XPF8nUOZg/h+CsQZ1xj8JSFb6iMdrkUSaqCO8PsZhPslr3+fmyKhnvmP64vh eF5qORUB/B5Wy4e+oQRcT1owf4FIiCpaPfhmCs6fjVMxbSEhXtu6HyWZeL5J lody9SSktzd1O7gQn08XzelDuSRkvbkVcYGC72dmjkrzMgn5vnD/bV4lCR1f bZ5pDiWhkmzDf5I3cHzBUOeVDQk1+bQS+Zpw/2uZysQTJPTwxGEquhbcv7k/ M1OThNbp6Gnmu/B5OXz5PcaHPx/vQ5Oe9eH1alevMNDjz1f/B7rORzj/zYlr eivZ6DhxkLFoDJtFZP5DWTYq30piM32PXe1z1eJ7Fmqe+JGjuYLXu/dV5NVA Fnrc7Mp5ZB07QU9bpCgLbfob8FDv4Pn2Ww3tUc1CJh9p9rUxS8Fuvk9SOq6Z yHkwuOw6hxQkrpa+YJTNRKFXl4Ty9+L47lM0NT8yULXTwwP+B6QgHMx9bxSf gbbfJB4SV8a+s16Vl56OLs2ELURr4Pqh1cl0/XS0Ou9d8RLg+JvMcIW/aWhu xXLvZWPsih/e5V5p6NEfMbpFBylIKI92TVJNRQUHHr6vSsO2He35WZCE2MQf VG9n4/XzPYj7tJNQmsTN8xb5uL5r853R4mUUrZg/QajEBlkSD6Uvo4v6LgMO Lbg++PDo3ZYEpOhBc01wDsetR9pWKomowWfbKXgJz/eC9kGoJhGJX/osOPIJ 287Pf7Y+FvFHvsyP2sRWMB1OYY1BVJlXL08xSuPvn8i95GkEGm3SdylWxp5/ mNOmEIR8ti6Lcadjayc6LT61RWLKBQc5SNiHH8kKPbRGbwOuibPmY/Nmxz3r tELGKwOHGSqw7Wxyi7zNkPgMnfSfO9jrrY724jJopi9VeWkSe0w1VSPqNDDP zjRokZCBhAG95NOJfoBuuOz4HVkZSGwcGDJ08wdd9I2Gt5Rw/LFO8LE9AUAq /qlxnbbM///+dqfZ7BJgCGY1KzuFzaZvHvUkCPTa5Jy9HIHrD9HM1JPCgZJ4 vrvVYxznat90kYsDc2DRSv2ZDOweyW/5EhAHMs4p6gmO43zL3wNcd+PAYsZz waVpGQhFRk5rK8UD8jfmF0Ffsa9fd3NXSADfu5OOknllIRxL9vfffxk024Zx vHDFrv9a//FhCnAMHvx3zwv714zV2b8pgCmb53OJvywk6kw5Zaukgou9zYPO EbKw29s33/FaKuA68jVqIxN7XporLgF/f/jh8YG9BeefUPTdrZQBSh5Jn6/d JQehpVpdpXc2qHbfe8mMWg528/Q7eFVng3r6XUk/aOWg8OGAprVX2aDNcPzm MSY5SCz7OkB/gAQmH0X8meORg3PNB6e1U0lAYGiQwieF62NvEp0scoCYx+2m bhk5aMhwMzjNIwdIMZT2u8nLQTV1wRcxcTlAy8h3tUVFDrZunuwebMoBdkNc Wqd05GBYkph5D1MuoAw5TaWdkYNRG3xH6R7kghqPE1/kz+H16uOrHUZyQQOD 8u43tnKQLMxyyO9dLv77kl7ykJMcDBHOUrlJnwfeDjVG9HnJwT11GXbRp/PA okdRlqevHORpi1RxcckDqwzx1ewBcjBn+uTHnyF54LeR1WOHEDmoMbjOurc4 Dwg+/sX3mygHx9kHrjK9yQPinkvSVxLk4OTZbRuB5Twgw/hMxzgJr8e/8Hzg Rx7QNq72KEqXg5bpVHyrHGRg8Ck9GmTJQe9Qu7vOwmRgmhac854kB7fkO6n9 pMng/GPDB0oFeD8K8Rd0DMjA1VNhZKoInwfflv/uU2Tgy7jvXXypHEz89lru tD0ZxBh/oX9eKQdH6zQ1cy+RQdKn1/vCrshBNrYAoegoMshK65Xbfw33L7DK /HyZDMof51v73JCD5qYlydaFZPAwiZn1w0183/8MJZ+Uk8Gq7uWHjk2436M9 T4avkgHHv9+Rk3fk4OFCm1jbBjJQbw9SsGyRg7WVharBd8jAMXR1eeS+HFze PdO6txWvr3ix4nibHCQsnKuDnWRw88uUVU8Hvv9XWjlrPWQwfuM0kybC76cv KVh4gAx23J70NvfIwaYvk9Ivh8jggJheuEw/nq/Qx3nPCBkYzrXJ1g7IwfW1 Q+k9z/D+KQrvDwzJQf+PU2ubz8kg37qeUvoEv7/55OprL8igg0vkNPdTnH+x PuX5OBnMjxYzZI/i/tXXzINekgFDJns3/Yv/z0fUKQNbzig1JP4lPu87/np7 sc/Q7JL+/Qrv/1mFLheuj+4JWwiexOczLNIcP0YGNdHrxV/e4v0cNWp1GiWD x+ru5h6z2AXMGk143q+bs7QL7/A8HJtr3o/JgPfO2U67RTnoeIbqbAHer7bv s8CJ93j/k20dEr1k4CJxXML8I47vB8qH8XllvO+aG1rBVgmpzLhPBneqVQr1 1rDNTeqsbpPBm/ONJzvX8Xpj1APEejIgCIhTq37D/RpA3J4rZCD+qqytaRPn G99i2iwhgyCzzEM1OzhfofD0QgoZlO6hmRH8g/fXUfX1fQwZ9A5GkQv/4f29 3CN+PIgMWKH3rnRqeehY5vaXF78vld8L96npsIe1dqeYk4Fdq61vDIM8FDY4 7WyqRwb1ciemAljk4fqXAOpJcTJ4vtqbs8ImD4l1p06U7iWDrVoNQxdOnO86 SHWTjgz0D0i0WPPKwzn2UdrepTwwx86QDURwvgi/7E38+aJ7StR/IIbjWvPX Pifiz1Pa1i+FQ/IQdjx8G+mXByKplt3FpXC+QClHjG4e4Pk2oMusIg8rY99S 08zlAq1b2ttJavKwW+mkXvXDXHDB694tgiaO29ceTK/PBU0LV/d9B7h+fmsc XsoFJ8YTf0wayUNC3uOXuts5oOaK9uNUE7yeZf+LzIkc8PvSVpmaGZ7/Bl87 3d0c0MjurV9giefLr2jMwj+/OMxOky0ccHyx4Q3tCAm8Hjqg8CgI19OJ3N2Y zgLyxVM0oaF4Pa/2jInYLJDmnv/mYASOF1BMzYSzgCYdQ1xCLHZFwA1W+0xQ fmz9mXYant8/v8N3IB1cRF0+LRV4vpk/j486pIDOrDCdi9U4/5RNz9nPyYDn vAI351Wcz2W65B2RDAZ/X+3wr8dOfv+4JScJSGhk7pFqwRbYpcN5LxGsN9vW VT/G9ZNJdpJTRBBVv7WYvYnnex4JhhoCgNnycxmFLezUBd2bjf5ARPxG2PgO Xl92D5e0kx8YqrJn4iMo4O+v1jLuHl6Ap7hXsZoR+0vGvF3cBdCUnBHfvB/b /QKPPgBg4aKw8Bsj7P6/+qlLHuhe9bZHpAm2/FfdrpteKG1u7K6gGTbxyFWP QB8kZ3f5uLOlAiS2OnbnRvqjqNOffFfOY08wc2h9CUQ8us2dfwKxOzb6N0gR yHi/oa1IOXbccm6tcwLSCr91vLAS96uPvGTcmoBkXvAoMV3BPjfvZceciDiS l5h+XFeA3YlxjNMtiejNWnzX0G0cj3czjiIkIfeuzgMBD3E/Kfk7SVEpKMle cRmt4nxnkhK1QCYKu18yrvQFW0S10MwpE3myU/XUfcX5sm2xStczkenD0eK8 H7hfrcWpMfksxC3te8KNoAih15UiL91sVPO7tpGFSxESi7X7xmrx39OlQsH2 mor///9y70B+LlqkfxRDp42957P95+ZcRB8SkHIbKkLhzowKp/FcZG7eX0pj oAhHn6wsV3DkoTlqz96b5oqwcjytNiwjDxF8W1j/uijC7kCBnw+CyEhs6jxf rbsiZEMPvK6TyMjQkF70lBe2/VrF6QYyIonYqlzzV4Tm+koG7+bJaP8rgr1p pCJsdeC80WiSj7ShSX05Ca/HcnvYh6MAOd/cvGuYh+MXBiR6jhSgJP6Kzo18 RWhd61LXDQvQ0+9fRw1KFaFJt6hpt08BOl9X+HPtKl6P8ubn9b4CFM+js6u4 FntgyV77dQG6lvCJUe+GItTlWjkaslqA1uyPChU2KcLm4gjOfs5CFM2xcAy0 K0LLmcBvjfaFqDI2w/RjpyLceXyP95BfIepfVbbO61aEniG7+JSIhYhpMMXr w0NFWMZ//R1NVSGSU1IIznmkCFlt2HUGmwqRZdVUjOYTfL78YhU83YWIEimT mz2qCNXOyPNYTxei7uVXpeovFOFhxhduBiuFaNEq7urCS0V4TE9SrH2rEEnJ jbeqTilCpcAJaVmOImReFt37bloRjnvwbx4RKkJBjIeG0+cU4fdOLqYrR4pQ x2L47OwSrr/fm80AitBfn9vpdst4/5E6D00Ni5DOz2XVN58UIe/FqNZ9FkUo kSi8aPUZv4+FI5UB54rQAIM1aeyLIkyR+p5zwqkI0edla5ltKEJHkU1irXsR OrFvcPnJdzz/ipZWkl8Ryrr6l2z4UxHSM74+OR9chEZlVHQebuP3o6p+sS2y CHG0+nzW+Y3XX62JY44rQlY6V4u7/irC5bGE8snLRajo8Vt9zV1K0D82OUU4 rQhNnubauL8b2yzy3XRmERKcPlGuRKsEi0xFhdhzipCja4LxbXolOGpx5HJr XhGq/tL2Q3qPEuT9wyszll+ElsI2quuZleD6rCfBrrAIHaaSMDvEpgSFBSvu nC4qQp7pTr+ucOB6Zvehe9g3uYqvC3MrQSLdUkE89nrZ6OmyvUqwUvCudjOu VzhET+DnV4Jsjzh2jAqKUHATaCjYh60hJ6hHLkKt6qHWnPtxf6b55+V4vp3e RmrSAewbOUx2WUVIy+R9E5MY7l8ykx6O9xf7UtA+VRzHqS1fb+L99563YqA9 ogS7P8ode0YsQtTLGS3xkjiuq7eyG5+fQUC/0z/p//Mn7uQEFaHUnV/MUXJK EBbfMQrxKULDCYptWwpKkHRL+fAtlyLEwuzlGqyM528MJanb4/dSUM2xoaoE zRe1H3FYFqG8/ZNdvhrYV13b1I2L0EQtu9eKlhJ07NelacTvhVfBaK87wOfz eJbTT6kI2bQT+xZ1sMV/7Ys6XITKjrX6OR3D689fER0XKEIiZw89sjHC86f1 qzoSitDFufNBr04oQcK/FrOcr4XoukeBsKUpnu/9z0i6efyeo2jCT55WgnLa RTzt+POgWrVwBNorwbnQIcQYXIgiJAQmOhzwfu9pX1V2LEQdd0/Fqzvj9eg/ OFCMC5HuQM+kghvu/9xVSECwEJmsVKQfDMD14/N8g60FKCvolWp1IJ4nhJOt vawAPf/DsigUgvc332+1EFeAzrDFaPFG4vyr9H3PjhcgR2W7z4yX8f08CHY7 8DgfCUrfZY1MxudnI/zvYl0+mhRjVFhJxXHmtaml5HxkydUa8iQLz2d86WmF bj4y/MZJyCjC/XcqTm83khHNiqfI7xJcD+9ckU4ho975nmPeZThurfSo2pGM tMb8Uk2q8fys/aqnWMlI7vYTDuYGvD/jMpOZC3noc62IcnQjnl/qgK28ah6q rww/+7kJ9ytzuj3CkIfESIcoIy14/k3P0x8bchGvX8LBLIT78z9tfP8pBxGk NdVYX+D5HJwrTx4noU6xXJvYlzj/+OsEdjYSitj3MerLK7y+ZKXj5aZs9H1P Yc+zt3j9p/4xX0ay0PKnDWPS+/+927HkVwYara23Z9/B+/dWEZY8lIqqxPgT OA8o43kZk8TWiYgke7e3VVQZEuN5PIbtiIioYUJ1XlwZEkTDxKlyY9F585i4 Wkls8zR+FxiN+KPmY4+q4PxzLt+kC8JQ7ov6KLcTOH6ByoQjwBclxmuGtAdj E1vaIlaMQGDmeItjGPYEjQtDqAVwLvLZpInE7rrvqf7dCsDGiiBzIrZBHlvk u/Pg95vdgUtp2OIdv6yBOwiWH/ZjrcTWDw+3vxEEXOfsPC48VobdLzRWxg3j QRBd4ompYexgWfOV1ngQL3ND+vQzvL/NqT1GhxNAWdT2V91xHL9nfPQZdSIY 5y2IEJnB/cKMzg82Xwa6Fs/S333F+8lFrzU3UoBgr06jA58KhOrR514uZwGJ j+6kVwIqkNj+72aHbjZQYyNdMhNSgd2Rym20lGxgeX5GBYjiePq5687iJJC2 E4GEpFWg8ECQdOwLEthSaB6dhrjfRHPXwP5cMH5F/Jutuwqs9LZ0eZBABlwz 2Rv0Xjh+eZWjE/99bsm7/bXFB8e3jOsC8PeVFxlP1lkDVWBTr7n1F8F8MBbs v9YXjddrer9ocjcfjB5v+yiZh73/jKL2swLAFi/68XW+CiRpxX22/loAzDsy li8XqUBzn0ZBUc5C8EzO4cNsGe4/tlu/x6oQPOWjXsqrVYGjYavuXK8KwcjK yblfndhWZSajQ0WASfz+bG23CnS0oYoufF8ETByFZ6368LxiWw927y4Gw+Mb 07ce4f32GVY/0cDuLJy68ALHxSNMf1wtBkxbhCm2CRX4yKYyaxgVAxMFz8nO 1yqQLaTplPabYvDkmtabvTMq0P/00cB1xhLwOPvdxJNlFShVcE4wyqMEMD42 nghbUYHUTb+i9xJLgDF188uDayrQndnyvX5BCRgKSxqP/aYCx9Ndmyx7SsAj J8kxxb8qcCgg1oCZoxTQU8jP5wiqsNJzUpLzYCkwnPgzmrlbFRqA1okK1VIw aDz67AO9KuQzeUMwtC0FA4rBI6WcqnB29bNpGaUUiKV5+wnwqMK0kffWjfWl IGHuAnspryq+X4dko9ZSADNPWZUIqsIQCy953rFSUL5g9JNPWBWKzXSEGc6U gj/qOsXFIqpQa/142O+PpaDtvex00SFVuCjv57/8rxTwHj0UyyuhCgmtHab7 GCkgNE/oQJGUKuxY/Mw9zEkBEx+5+/bKqsIGh6CyH/so+Cc7s0uhvCqEGSPV JQcpILeAmm6vkirkfV/+8J40Bayv/qotUFGFpDdsSUbKFGCq982YR10Vmtsp 6lloUcDN4k+r+Zqq0P2Rt/qwLgUwrb/L4tZWhfQD34ithhTgafBGLh+qQqKh JROXKQU8ooyOcenh/hTC9benKED822AQWV8VdresfWM9SwGJRoiHyxDHz+l6 37ChgIWKe615xthVPYYN9hSg++OmDedJ7HSJ62yOFFBpcvV3rpkqXN4zVvjK iQL+VlPKOU6pwlpG5V2ECxRgv50Hcy3x+mcOlKRgd5ilz7OfVYVqcveW/bD5 r8Un5pxTheu3gnSanSkg7He4OLudKvT3chw4jfu9OhXwiHQen2e7nKuJAwWo 1Ll7sjnhflu5U6V2FED+58BEuqAK2ThiGsA5CtiwOtvI6orP82HhEWUrCrBo MDXPdsf5z2/4hJtTQBOVwQaLF+5HN+nPcIICWM4dJWf54HryVOLCMQrwvqWk wuKPfeTob1ptCnhCI/U685IqHA2K2bqkQgESdqIRzME43tV0QVyGAlLu8O/L DMXz3ndY34/v7z09RxdThCqc487iOy9AAfoODI4ZUXge/gGRWTYKqGkhUDHF 4vvU1OatoqEAKqatK+lxqtBRgONZ1XYpcHT+or8nEff/mL00s1oKulrff0hL wu/ToqTParYURLq8lExLx/fl+TB/qacUTLYPjzBk4fms/kTu3C4Fahz9fqkk VdjE1vBNp6oUfO+6czclH+efs9VyjS4Fp7jrreiL8PuxbnPW8SwFt72qfiaX 4M/ThNHgiTOlwJeXpJlcgeffvrm0LFkKhn2Tp2mr8fl9eR0Rxl0KJB/GxCbV 4PnvJ9LJ/y0BywE+fZfr8PyST5a4RkqA8xPjE4l38XqUL3qxjiVAk+R04WcL 3v+X2tJ+vRLAZRUW6dmK+2tMGiiJl4CBmas3zDuxzYYGScvF4MgGgUlwENef maWXvlAMqO7vFSMN4fXX31g2g2IwGSmjtXsY+0R3sKNAMcigsfP+OIrzhebO HxktAuu894dbJrGDXpemyhaBoemRxcPT+L5j7+4/RlMEqqsXf5fO4nl39r8S nywEllIc0vGLeP8uYbOucYXgPvDJNF3DBsfFFh8WgBhXUdMPu9SgsP3rh8OH 8sFZSQ1XG2o16PhPLypsnQzk1s1jRmjVIJFxWt2hlQzmw2Ma7+5Rg92TIfc/ 6JOBfuYbFiK3GqwMiWiWt84DTM3Zz3iPqMG5iMs3jG1zQMmu3+bG5jj/eslB tvlUcPWNZdLGKeyEb758MBU03b7ZXmKlBuE5h07tshQw4OQgvmKD1zNwClmx TAYbPb2/0l3UICFFcKqgLREYxadeG4nA9poa6RyPAVtUe3+bX8U29Uk+GOMM dk/5yW9fx27gufaj1AGw3H3kWlWPHcR67uNRGyB2IeL511vYGbWePdxmwLxv +lpuG7b56tOVeyroekKNxfgzbA7Fir833dAZaoXrZ3ew9aPdW7JjEXGLN3bs N56XlcFI2JKI6lb/nTn5D+9H0kSBMktEv8dHaPWo1SHc+Emn+j0OXbnq4SrD og6Jq27ZNzgT0bpB1UEaERw/fH/A9XAK4tdM+RMrhuMtr90PXk9BerJ+L3fE cTxYy4n5YCoq2Hv08rqkOuy223vTQigNaS2/XpxSxvnC/4oMaTNQaipbzR0j 7P6q0qcN2ehO9M9IaRN1WHnVMXyDhYTeBsycrjVVh4TqV8Kc+O8zOZuG3eWn cZwno5jtHglNSBheSLXH/YeClpizc5DIcKyIYwCOHwm7Si+ThzpYvlQyF2Pf O7hgLlqAeHl4CzpL8XxyCQt6pwtQoKBOuk85jgs4cYzEFyAJqbzgkSs43lUz XjVXgIqNVI0zG9WhcGTTLdvCQhSSGPuNqV8dyh07/Sz/axEaS69d7hhQh+vS h4msAsVIOu/5tPeQOiSdbQg4cKwYLVaJPhp+qg7nZhJdWPOL0Wk0SMl4g/fL 2B0ioVCC5HZYDZi+YHtP7uM/V4oydqlrdnxVh02jPtP7okrRB3pnOe/v6tD8 3Ls398pLUfneZv7hbTwfbUfk3flSxKxs/SWdWgOyuf6+VudCQe5acYuadBpw nb6C6fRlCurXq3+zwqAB5yZZ/qbXUFDUqd99J1g1oLUwXXb9Owr65FdZtIdf A6bskv1TdKYMGYQOZbbv04DLVLFe9y+VoeqYjXiv/Rpw61N7oGNWGTqXeczn iZgGhO/OZpzoL0OP6pd10mU1YGtfapyjRDkSu8OuqqmgAZvmmL826Jaj2Aca UitKGnB1W/5FhE05UnmUwXNCQwM2Z/KeKUopR1eX5FYY9TUgLZ1Bdu1MOYqy DT/TeFwDEkQ+n4vaKEennvf0WBhrQKrDNqqPaSrQ345TRUVmGvD34MLppxIV aFyhdLfWKQ2ovq+nJU6rAtXXLvjOWmrAAZk+z7qTFegMOUhf3EYD9h97NW7m W4GkGDubhuw0YIxcj+fj6ApERaTZ5+OgAUOXw0XvZFSgRq+CjbsX8XkGH4no ra1Aie9m7M+6aUAb1eDbH1oqkM3ZQ0M7HhowolNNPbC3AtHqtVbo+GnA2t8f 8lreVKC3rYQ9SwH4fL1/WrkvVqA7MkYhKUEakOvSP53wtQqUUpPzTjJUA0p1 i9O9/1mBzvNPmjwL14ATkoNcZwiVSIkk0nopSgMa9ss4XqSuRIy0XqI8sRqw 0miKWZC+Es1F3s16EKcBya3FF2P3VKL7X39t2yVqQKYU04I0lkqU5XbMhZCM 19v9tesoeyW6OJ0xeiVVA5qrZy0UclYijdMvNY9naEATBsuvhdyViG1I8Pqn LNwvsaZDa28leq/typGVowG1uBUIl3krUUdzY7Q8Gd/vfTE7P75KlCvxc3m8 APdvMLTawXavBJZhxfg+JwwsxfgrkTZPChKgaMAoN0r1Co5zZYxKoHL8HtQo GmbYn3bxFThX4fMa5kwyxf27Q5120dZoQNKnitFlnkpU8LnOu+6aBnxtH2Ag iOfzvrDxyqQOvz+bgW+fOCqR7hsNvfUbGvBRhV+/OVsl4jNLaMxrxO/9tlPC SeZKtN7/hE/1Nq4/f2pylqESDWhwXZ68qwGFe50taGkrEaXJbj36ngY8TDdh inZVokviV20PPNCAjgb10hw7FciQ8nmgvx2/v2/F5X1fKpAQh4qCexc2U1Ag Cd/n4z8D9Lf68PvfmMoKe1KBKgNZg04N4Pfy1jU4p7MChXw8O7v5CNvhzGJ3 YwUSebncovUUn39j7XXbrAq0ZSx/YG5UA8p91g7rjapAT7vDMxJe4M/nTttj Fc8KFNHAeOHxa9z/EWDV0q1A5iKnn/pMYZ/y8B6QqkDiRaXq7DO4X1ia9Cme CjSWIMVmvaAB/f0mor3elyNJW9POpc8asHt0+G5mRDkS/iz2xHYd709ma5PF oRxxxf56/XwD74fa4Ek9/nz+ra793vkT98/fFSRJV46ef6KSKtilCR01708d uFyGBqLeqDNRYwv1h5s6l6E2lqbj8bSaEFaytGRql6EaBfsLvnuwuTf/6n6n oNCI+yUG3JqQwGDVGG1JQd5MWbUde3G9meQ9JQkKciy/eE+BH+dLed/Z+VuK jHvZx4T2a8K5xu/771wtRYKM3gw/D2PnfXs6+6EE9RULh13XwvXjyRZtoBi1 Sv68LAhwvfeRjhLaYtTQOZKXp4PzfwW8LhguQgXvIm7FGuD1L3dTlqyKkMeR l+/P/lfBuYdDmb5x3CmiVpTKplDJ+E2TUYmWeed+Oi1py6w0iWJQGkZmUYnQ kOSUhoaMw5hXsoW0SaXEK0onh0itrKRyFpvIocjv2T8/1/e5v/f3ue/nut75 azjWSK6sVDNz4CI1727sntkHMV+LLpnalkKp7OB5hnvh896+e31nJNREm4X/ KB/7qQb9pFsqoT4odCZ0HMHc4LqcQZNQt2zZD0uDcP/WbxfTppIpl5Yv67zj MTtXHV0cI6Yiw+a46iRaI8OciUvjTDF1ZYVRLCW2RpW+QmXXovPUmO+edwtT cb8lGhX+NolUsmJpfJUcc9fxhTOCeOoJPaxT7zZm7fbGkpgzlHmYWmp9B+a0 ef8WlwRQLisMHwR/xHw9TDyH4U9FPt74yagbs1thz282QqpB22fzyQHMPj8b sGjelE9e7RBtDLOVwGv07T6KbEiyiZjDQgqy2tW0AC5orlg6ud4C8+Lrs6tr QsHxY1XNjY0sJCqOlO5YEA7SXG8J0xrrwWWWdNdTYES7w1yNsN7/udp+XARW DAevFXYsVDkeKncOPQ2HLGJearmyEOJMWtfti4H8cVMykYdZT7uLMRwDn0tf +c31xH62/a8jz8ZCiPVKjdl87NcTb6BxIw7EqALN+GNdqr5FdSIB7tuNXhs8 w0IdBT/fNC0Q49/jGScFMdjP74Pg8ZAYbOo2be+LYyF58Hq7d2uToMn+fGfn eczhA7vEt5Og15Gu1yZlId771rM/7iaDjhsv5tk1zGp5viuvSkAQWOvx5yvc X5T6bQUjDeiXkvN0W3A/uZKKl1sa9Dc59ce24jxql7qtktPAZ12Xv+87XL+S xsgcwzw8LVrbh/t1lfN33JOCj5CZXTaFz9NT/LLXZAA9++sHxgwLGaJLd8yc M6C/vsxYpkggQ5djS/ZFZ4CPqW2RSJVAZnb124RvM8B7kFe+TYtAL7rmFt2L zgS+IPmfhpVYF0zmjj/KApMMJ4NNxgSS21UZaH7Kgt5n+p7FJgT6w2qFtEJb Bnx6Qb9kDdYnlEf7XWRwuK96cp8lgRS86st5AzLwOvx1cacdgTr0jn3KH8sG 44tlLnt2EugJw1xVb44cumsismvsCcSRa5fkL5GDl7Em7aojgVpUR8JNfsHc ZWzh50qgidalv2QFyuGQp5PjhD+Bmk0EU9Nv5cDN492SHcX5l1Vz7QfkYNvH X7QtiEBcs+Uh+yfkwBAGtySFEqj/88HSP7VJGA1J37/6LIGssmicXkRCd3lO eWMsgZ5qRqoq/UZCi0KB/okEAm3IZnk2ckm4H13W8TCJQDPujLREAQlRyW0H XTMJVHf/2KmAJBKOv+p8pJJNIMn0rnxaOgl83UHjApJAjukuhQk5JPwmm+4d zyPQgbGsNo9iEtjvZ9nJrhLoh1+vY9NdEsyMNAu2FhJo9/eRDUOVJOjk6x9J ukGg8N6eCFo9CaqDxvWWJQSatA39sbmZhAkmk9l+m0ChQlJFrZWE/gBLcdRd PC8DXkTAOxLabsEw/T6BdBYlOER1klA/YePQWEGg2l0vpq36SKi05twMeoD3 wTkblTJIQnG4k47+QwLxmzOMLwyTkPuAd+xhDYGW/NWjvf4rCakq3q99nhKo MlfH/egECTE2/pbatXj/7aeXcL+TEBIXnHannkCMZBbz72kSfOsiJg80Esh2 6YfgsRkSXLXinFWaCeSkXFxerJgDnN3JZfmvCRSD4i5rKOfA5tT0pb+/IZCY MVE1hdn8TU7Y+D8E0hJyzp1VyQHjpQXtWe2YrcD1KmZdt5uw9T1+n1s7TvIw a+SUyfs/Emh/hM2CQlw/1VmtmNSN3/vf/iHxSjkwRKv1sOwjkMoR075phRzo 8GmufjtAINarwBNKOF/TtTajqCECZZ6uXJ42RUL1584z9GF837fRFeWTJJSs H+x+MUKgXsZltYAxEvKOf7UJGsP+t/okN7+QkHZ3+sqySQKZmF9qEw2REDc1 S+PhdwLpqrHXt+B5h4KmwOcHzrtu6NkdvA+/yEW1WopspGsUUrwM78thNi3x gCob/eU90nO8iYStO5j/Kquz0efWloXez0mwSLTk5M9hoz8WdRq0V5OwRMd2 /rgWG3W8qfPceZOEuXs5gVkL2Gjj89IL2/JJ+CF1at6yiI1sPxkm3JeT8MHA O1Wsx0b8WbStyxNI+BI+I1XXZyO0q/3vuggSlNtTsiIN2YiTKkhRCSLBKLMq 9+gq3M/U/qUGj4QN352uDNJwnkKtDy27SfjV+d8CLzobf1+efVxjQ8Jh3aU3 nZhs9OJcyA4Bg4QTQcW3G9ey0ZXf35U76OP38tr2np059i+1IKh5JORLjj1g /cJGYo9NCUbDcvik1dBguAXfxzphzewiOUwJD72UbmMjebG7QCFTDj81fH89 35aNzHxzPh6PlYPpOZN2lZ04j9rA1XYPOfirR37q5eL6y9efp86TQyRf97P7 PlzvcKt0+ks2JD8uGml1YSNe1Yj6k0fZUHLmn2+1PJx/6usdW342jCluUL/h g+sVf17eJ5eBqvvzufQjbCRqXGsd5iuDxZXuWpeE/837bICGpQw2hicuTjnK Rob0tLXzn2bByW89q4LDsV9eaHVPRyYojKRv3pSMea7XweiOdNByWPvrPQn2 o01X6mSmw/Ibj7evv4jnL30qvsZNh83CUc6qTOxv3sed9VQKUQM73dTzcP3b oaj4nDRQ71QIbbyL84tSeqWrU0FuGq8vuY/PV3CbuA0psDF44QMuhfMY7Jct DEgBviZdte0hvv/1FMm1Egk82bhb3N2A/a74GigxL0D0ucu537twnnVPe4u+ nQdlS7u6VfMBIcsrc70cIyE9olnYqwNI1NnPbAqMgHW1rvMLFmM9/9RQT7II PNwD95otw7rlmbhV8jCois98b2WC2frLCe3E4yDqGPpqzwakUOGmJ2nkge7q 4LT5mzCzgyyUpM7w1zFl61dbMOd72Fkn7YZ3Groi5+2YReZFa2gWwN6wSeOQ I/z3fynFz5y41OtTzwtpezGHLCis3HqA8nu2x75/H+bT6j/+t9CDkrn5SIRu mKXTZZxhPmWRP2qxzgNz9TelGmdfqn40/M3oQczLbFNXPRBSXqAeeucwZs+e U2bJ/tR07AX9EB/MOntymZsDqf8Dgb5VaA== "]]}}, 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, Automatic}, {Automatic, Automatic}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImageSize->400, Method->{"DefaultBoundaryStyle" -> Automatic, "ScalingFunctions" -> None}, PlotRange-> NCache[{{0, 10 Pi}, {-0.031449446952519194`, 0.035191815142400995`}}, {{ 0, 31.41592653589793}, {-0.031449446952519194`, 0.035191815142400995`}}], PlotRangeClipping->True, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}]}], "}"}]], "Output", CellChangeTimes->{{3.7205516995192003`*^9, 3.7205517055896*^9}, 3.7205517485308*^9, 3.7205519308794003`*^9, {3.7205520413656*^9, 3.720552072962*^9}, 3.720552413601*^9, 3.7205539017988*^9, { 3.7205539671848*^9, 3.7205540167642*^9}}] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell["Impulso:", "Subsubsection", CellChangeTimes->{{3.7205540338970003`*^9, 3.7205540351294003`*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{ RowBox[{ RowBox[{"Show", "[", RowBox[{"#", ",", " ", RowBox[{"ImageSize", "\[Rule]", " ", "400"}]}], "]"}], "&"}], "/@", " ", RowBox[{"{", RowBox[{ RowBox[{"Plot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"psol", "[", "t", "]"}], ",", RowBox[{"p\[Epsilon]", "[", RowBox[{ RowBox[{ RowBox[{"\[Omega]pr", " ", "t"}], " ", "+", " ", "Phi0"}], ",", " ", "I0", ",", " ", "\[Epsilon]pr"}], "]"}]}], "}"}], " ", ",", " ", RowBox[{"{", RowBox[{"t", ",", " ", "0", ",", " ", RowBox[{"10", " ", "\[Pi]"}]}], "}"}]}], "]"}], ",", " ", RowBox[{"Plot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"psol", "[", "t", "]"}], "-", RowBox[{"p\[Epsilon]", "[", RowBox[{ RowBox[{ RowBox[{"\[Omega]pr", " ", "t"}], " ", "+", " ", "Phi0"}], ",", " ", "I0", ",", " ", "\[Epsilon]pr"}], "]"}]}], "}"}], " ", ",", " ", RowBox[{"{", RowBox[{"t", ",", " ", "0", ",", " ", RowBox[{"10", " ", "\[Pi]"}]}], "}"}]}], "]"}]}], "}"}]}]], "Input", CellChangeTimes->{{3.7205515977358*^9, 3.7205516002162*^9}, { 3.7205516378487997`*^9, 3.7205516559346*^9}, {3.7205517100355997`*^9, 3.7205517388422003`*^9}, {3.7205522758358*^9, 3.7205522764452*^9}, { 3.720553937249*^9, 3.7205539374206*^9}}], Cell[BoxData[ RowBox[{"{", RowBox[{ GraphicsBox[{{}, {}, {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwU23c81d8bAHCVTVZ29sy+XPOi81BZCYmWQpQQKpXKyldRMouUJqFkF9o5 QjKzZ2Vv996PpFCq3+fnH6/n5XPO53mec859nfcL8l7HnY+sZWFhuc7KwvL/ 77VBie8PXMzdfGvyH/lFoO71Xb0Lby4iLxOKVT4Zv74q2f7xTSoq0ZTa9uQv ga7ybTdMz7iHpD7a/VxdJZBWw7sdz95kI0vHNR65vwgkzLM7KiM/D8npelx5 uESgVXvms6iMImTC/Tds8TuBgq1rFqhbnyKGPdXqDkEgH1/+hMdvytAZPus/ 6bME2h/npryR+hw5vZh5MTVOIIf8x5VJ+S/Rr5KmhMRBAlk2fd+zVuEN+u55 7/qVXgIZ0tG3Mxnv0Es9/uG+VgLdYLf6cJqzCnGkcSdFfiQQvxj9mvbW9yjX ee/785UEWmdsrPHwTQ26sL9//8l8AoXbDC65LdWiFyOXhIIeEOjn3ku1ItQ6 dCYteKEqlUCz59sOxuXXow9ijHa/UAIdvhqivmWyAdWzMA2rAgg0eFtqaVW+ CT2Wup4Y6E6gjje+KScyWlCvR8xqCyKQfTPfQfXuT+gWGMT/p0Mg76AB4WDO NpSYuWc5QYZAXyOjRjS2tqPvkm2Rhb+YqP1Bc+iDN52o4uwhLFrARHx5sofC 93UhsVTbwGs3mMiuNNh631IXen+c18fnAhPVVokLb6D2oH7/indyO5no5cjh otj8PvR3279XI3QG+jHzItXbph9lfvsvzKSDgfQWuENhsh+VnWp+znzOQIVr n1r9kv+MZM3wqVORDJSp+GcoMOMrCnC5wv6djYG+ajjV2RkNopmAwVdbJulI Uj+7ULV7EMnpRXb9+EBHdg9z3p7gHEabLlwNjrpIR7XP7OLUt44glpKWoc1L c+hlZ7rC/TdjqGPY9uHc+1kkXrl2M0VwHJ2/tmIpeWMWncsL2lftM45G0r1v 3D46i0wirFImBSfQatKEVBr3LHqt8vOPtu8kSrLfphJrM4Pennftx8IzaIH/ iOKe3Ckkdfj94k7/GTQhsBdLB02hcActgXE8g04dT8iwNpxC5ops1pzHZlHy o6zvDbWTqLK5vNzp/Rzay/9xb/HABHovK5wyEshE2wc6gtTnxpACd1TBqRom WrzCyvExfwxFL87VsUkQ6BdN1uar3xiybKj5o1ZLoM+3N2yJmBxFXq9eGZgk zqNP42v+vewfQWNeftn/jX1Dd7eVbNXYNYQmKuojhVIWkdxw+XfNpW7EEuhZ wfZyES3s3L8wf6QbSSotzy0PLSI9BanDul1dyOm66r4hnR+ICIlXNijpRK+D YqmFrT/QWFDJ58ce7ShJdev0Nv4lZBhwViV7fwMyzMA7zyetoN9gN34+Lw/F hj9XGk74iy7E29gPibdhm43b3nGX/0XLMlTzIwVtmOt1p6vB57+I2G6mcMW8 HScszcdeVfuHdI084m96duDUYI0Z/bp/KIu1XTMqqws76bf11F5gAdPsG6ez ePqxu/q2OxKv1sAvnhNXqyqGMT6fMFXcvAY4ZxV/1PwYxnINndStw2vAJnTB 6IjBCB496tUcxLEWXqvLD4aVjeAjuRf+1LiuBY2LL2y78kdxgNxrj6CFtfA7 j3VVImYctxxfU7iOfR1o8qyZ8Kwcx9rYZvmWxDr46VjxQXdpHM8f7E2pgXXg 6N/IG3h0Ap+6s/hePHkdjIMth4blJA4V1VGq0WCF+dOPfvcOTeFj/2L3r7Fg BctOvRpfkWl8YHowBe1mhZIdUmZudtMYvU768yaKFTbuvh3p+Wwas7oze8q7 WQFzKCh/Cp3BP62s1n+fZYWE4b79Owpm8JTO/S26LGygAb3Jyp9ncOMah9Ii dTa4uzP27RfjWZycWxT36AIb2D2et91On8VRSWxV42lscH5dKs9ZsTkcfPbg T4V8NlCVmINFiznsYrve+0EXG5QIXjk+lDaHJRkBZrfU2IGrh1PxkB4d8/TU BvdsZodLuZ/aWPbS8Wql1BNhF3bQUD17cS6cjodSmkWuRbLDerX/WB7U0nGO viYR18kOZY4ZCv7bGThd+pJy/TQ7tGT9x+5wjIEvs39xY//LDtHy+NrZqwzs 3xdfH72JA8LuZaKMOgbWCZ/LCovgAIv+ozHshkwsd2RL36vrHPDwkngQhxMT Cznc4Vt+zAHtqDDX1o+JF2W3h53u4ADLy5rUlAwmfl2T7xKoygkPEnRUJL4x cUHh2vgCM05wqq/7J8ZG4Ls39r+f2ckJvx6va3ARJ/CFo9zaPuGcIF0uPRFr RuATTl6Hc65xAvs15xthOwjsZfL69ugjTmgM/kIUHiTwVh5/Do92TqjNve9e G0Zgw8X35vcmOSHwUE/HkzgCq36VOP35NydIKC58aEwnsHjdyXwJQS5Q1/bg UM0mMHdJw/AeFS5wdbjpU1lM4N835cXSTbnAwVG4LOUVgelR53d0OXFBw6rj 23s1BB70a78o5MMF4Qq1OyeaCdzqrPbaKYwLpBJmLY92E/i51AKrUjIXNEpV HM79QtY3+dpx6SEX9L8sFjQaI3B06cXbjc+54GPSGqrUDIH9Qu0n7jVywaer rG9cmAR22ipCOTnIBQJY++7wAlkP32Do1gUuKDFfqsc/CSzV9+iDGDs3tIh3 UxdWCLzu4XGBOQluSPJCrWdXCTx7zNitUosbhLWKEp3+ErjNYM2jaxbcEHX1 xqHwf2R+/xrmD7tyw8dbx81/k/G9huumxn7c0MFxUryFjC+lusXyRHCDt93Q r2/keP+DSu2DKdwQzts97/eHzE+VsfFZDjco/wpgN/hNYKNvFT4xL7nBC7+3 3rVMYJk3kU/3NnODCSezqnaRwKwx1qsaw9xQEsUbGTdP5ucgYP3vOzc0dBnF Z80RuF28/1oHBw8klF5d5J0k8MvRrC+5G3mAQ+RAXdMQge8X+que1+EBRs4R scE+Mr8QarD9Fh7QOXOXd2s7gY/B6lvZPTxgTV9t+lNPYGfuDxzf/Xmg9MTF MJ4qAht3JTrXRfLAjK+mReBzArP5yk4HPOKBEofeR1pZ5PrqTuvBax7Q5+q4 nnCDwB2/SyM2fOKBM+3DmkDunwfJlhte/+CBB6KLEo+CCBy7j8c9kYsXPD21 J/Z6EjhAsSvPU5oXyqRWNh/aSWCTF0c2c2zjha6pR5mndAks95923MBeXmA7 /U4tUo7A7NuXOosCeCE5sGnLEB+BOwev+Lmk8UKuj5bWoxnyvOTtLFfN4wW3 1d4o3h4mzgyW/PfrDS8ovgqLbnzPxIHshWlZY7xw3GCS3fEmE3Not2Km3nqo EGvefYnGxMylm9zVVuvhWW3tgWfyTNz13tP1xv710FGm/I/GycRZrguzptHr waFzNfNgJwObRoiIxrWvh4zIxes/DjHw8Wa3AMUTfMC9fGr9kCcdT+oYZD2I 4YOs1PtrV2l0fCCVr2fjHT5Q2lEV4ClMx3b73yPhOj4Q+NrVtvbDHFaZVtnA JsUPReeDqbXSc3hw3cKryY/8oHp2TSNL8Qx2PdrE9PrKD25HQ4pWw2dwc2OO 4tACP0i+WnvbYfsM/lpfUDfHJwAqx6yVVyamcVOyO2XcRAB2mq95ErdhGj+W rl3XnSwAh7b+2PnQaRJ7tVJkUm8LQKWjY2KiyCSW+e+e8c5cAQjXGM8b7Z/A aeMhgS2vBaDwkgfR6jmBowvUej9MCEB3SqD64NFx7G6SnP/cVBAyEypn5Q6M YlHX/TtvTQlCWFiRfV77Z/ymautWpQVBmPigDL2bP2NPTR2j0lVBKB26Vmdf MIAL1rFK1wsKwaajCrGS0f0YnhVNL5kKQeNEVHuRai8+xr8mak+KEEgIqIrL 7e7AVQ2Pi0VNNoCzTMu/vFdV2G/zD54bV4UhjL2Iw27lI7oiKR53LE0YvrkY 0cKVGlDeTxq75X1h2CimKy3m2Iimi6NYiKfCQAustDn2sBn5yvL+sOkXhl9O m6qPZLYhXxbFwVVVEZiauRtE0+hGPtVOpYc/iMCTDZ2q3Z+/otj7p7RMW0XA q8wg6PKhQfQoND1fsF8EhiRnlmMnB9Gk3pecSroIfIiOCPFiDqEj2UczxIVF 4W1VRN69X8Po8KXI6GYvUWjaGpUYwyTvO1aFLvosYsA8qJla/t8ksjveazXE LQYtfv7Y7s0k0ru11uSqiBi4/nEUtl2cRGtn90oPq4vBre37lc4fnkLZiWyT 8a5iIHvl9a6L5tNovMv97Fi+GJRP7Xpv0D6Dmv/E+SVViAHfZdvIdyyzqFyl ws2kSgzEvVV6buvMokvneCC5Wwws19qFOMfPImWpl5ymLOLw8PI/s7u0OeTj LXj7uqs4nNX6oNt5lo4cEswSzD3FQT/2zX+2d+nIsOJo5LS/OPzbxTXDUUVH 7ByVXpujxMFbq1pkP3nffZzvrzGbLw6/3yuqw2UGSum8IX2jQhzauvlrx3IZ 6NxqFT9UicM6puy2xhoGsnEQW7zRLQ4J8aVvD/5hoOlvNW8tWCRAS9z0Y9JR JmqTJIrp3BKQ/XsHGy2KvJ9vkcy6KSIBrw1ClxRvMdGVGydiGOoS4Dm8Z/ez D0x0ovLO2VsGEmA+q7zg+pmJ9k7V+W0BCdgdYZVpOM9Em0ykHTJcJaDj5Mtr RWIEEvCyga2eEjDPqcq6RZ1Ay1dP6RH+EjD3gI3YYEag+i8NotuiJGAXx4sN Rw8SqJTtB+f8VQkIun394zTpl1vacr9v35CAWxlyYzlhBPKLChmaz5eA84eO bGtKJ1CzxIDbZLkETFimcfo+JJB2mXnf50oJ+PD4TemeIgJds89yaa+XABnW Axy3XxBocYK1va5DAtpLN3zWfk+g3Rd8d7z9IgHdu9fxiTYS6JV4c8PTSQmY usiIdewgkNQzHavH8xKQ9CFN83M/gSK3p1bf/SUBTk/eTLwcJtDI+M/N11kl 4eVbpYzpSQJtjdz/5jKfJNgnXtfypxPokVilUYS4JKTlfYwz/0Ygrqfy5cEK kiBxNzbN6weBAuxiKL6aknDoxzX9/mUCfRqbLjxoKAlnC0R3Zv0mkG6Evdou kIS/4t+/vv5DoDTR0lwbO0kQvV35VZn071LJBoXNLpIQmD62a5SM99uevU91 l4TSM81b5sn47eiApJqvJFx9MFbqSMay4ZtvygRLQn5Y6n0W0svRIg83CIdL wpuTVgLrSC+PF7OlcMVKQsCMD9eeFQJZ2/jx/kuWBF87j8RVMt/8keYrixmS cGA148F3sp71YRS22WxJOGKXa2XGINAJ4bT/hookYTO15k7PFOnNoqU/XS8k 4bK9OK4eIZCBtVto43tJuNXb1MbymVzf4cqfuEkS6kXYvqV0ko45r3CqolsS jtvMoVNNBKoqnDmWOSMJ4Slus9qvCKRotWP6xndJuLZJP5azhECxQ6WH4/9I wvnXu9v1cwi0XejcwRDBjfDgWBNLbAKBigs+9x/buBEmwxK2F1wg9+M2tPuQ 8kaof/ydSymYQD1n2R3tTTbCjfP2fQKuBDIW9G+y2LIRZKhXvWO2EehOfou1 0Y6NEKbDvs/BgECeX9NA4dBGYIrtPD8oRKA5S0W95SsbQUer5M5f8nw4fIkt ZlzfCI89z9ZLP2Wi0jOz6mN3N8KPuFyceoeJQvKeKn4q3Qj2G55ciQliIhY+ EMnp2wifXKMnrvIykffj7GsZoxvhZULJB/8FBqoDDr5k+kaQMDzhm9PLQPGn PrGHskjBM3+OXpVMBhLtP7DsuEkK2mp39YaoMZCX5uYdG/SkwH8maaidm4FK Lsg+7DElf370+vprc3RkozK6/aCjFHiUtn0yL6Cj0FNHH/iHSEHrwXsT7op0 NLg+2CqmVgquKEuJWi3NIvVDu+7YfJKC6qN/BlRaZ9HZcv15nj4pWL8DrM48 mkUCbksZ1+ekQFJiufPgrllkmRfOeCAkDaVrzT+fejSDHlleTnvtKQ0f482r juhNo4UbvjMR/tLgtwOORq6ZRmjGdrPFaWl4LRRUIdg2hfqSeac/XpYGdX0l 6cJjU4j76zXT7mJpqMtmLDTenURBZ++OEqvS8OC6d1X81DgyKnxKUc6QAZGE +BOdKiPI3v7Or7fZMpBPCF4YHhlGnvRLtS7FMhDCpiQWdncYXdXcu/dSjQyE ee+O8BAYRl8K/14YY8iANadcidbkVxRdtL01y1IWqtw1dpdv70efiicCZeiy sNpgxkw0bkVlfQnd8Q/k4MDSBy9r9jL8a/jev/AcOeB5sel2gl8FtpwpVgt6 IgdE25iDY/ML3LHSFuFUJgdKjadUNqS8xfOSIioiH+WgWsdA6QJHDdY+eC/k PlMONqOL4ZNBzThvpEjsqbk8CL9n69i5pxfPz1RaPLSUBx17/hHqRC82Wmg9 lmotD+KT+L/Y4D5ct3YBn9kpD4rnH3efiO/HE4qGvrQj8qAffmX3muefsYJP 5cuaBHlYZ7n0xX1uCN+b/bSv57M8yHg0zB4fGcM2EocrdUfkYTnGSihMfhwv Wq8oJE7KA8fgyKtVz3Fsn6tI3/JNHnz2D544ODiOVz3ORT5lV4ALA2rs/h0T eH+3fHaCrgKgZ4tqIfenMDvrC45pQwWQ/aTpYtY9hZ/p2QdsMVOA3+y2g148 05grJcTgl5UC9A/2HGs+M41f2jV9PHpAATiuTw3NW85g0arTdMvLCjAT6u8U +24WVzO5dt5PUAD7Sjfv5plZHCT9oGLlmgKk37lfcUhkDn8IbYgsvasA3ave XiH+c/i0gYygzDMFaAps66Tw0rHc4bIz518owGb5uJk+0qvN120Gut4qQHBX SlID6VXF+eDs+I8KUKOdYvXfQzruyP9osPJFAQ67aXkYajFwZP+B2y6jCjCv dGgXnwMDq3Mu/C2ZUoB7HczNakEM/N8RqXqfBQUoOZHkoVzIwBS5k/u7OBTB f333f8qyTPzFgR3rrFeEDYFGoqzkffhKxB3FeCFFiJmvEpF3YeKhgQ90C2lF 2HXjzm7hWCZOuiF5oURPES5enpbsGGZinSxm6zcjRagbURAz+sHEbYXVcvrm isAvGi0+yElgwVr/6pfWZCy22jGvReBnrZs3/LZXhN++5sNuiPTHZ6HD5s6K YPdg/jaHE4HTFl6zVR9QhJydMdWyxwms/zdpN6uXIizwPMyIjyBwN5f3Y6uj ihCX1P7HMJ7AISJGy1cCyOelsl7L3yKwqDyPbdNJRYhauXdnew6BX2gOZaw/ qwgevq4B5SUE3mtcNusYrggRhS7Lbq8JnOHoltAVqwh+7z1O+LQQmOam81U0 QRH2LcR/ryd9OuCzTnvfNUVoUcn19ftK4LDg3sg76Yrwyiz4pfU46cvIgtav dxThfsz4J+9ZAr+NuyAnl6UIf50ZN98RBD54Y9dJr0eK4PYz4p8L6bu/marV OQWKYPz+8je15f977bfQVKkiiLKt7jMjfYhetnqrPVeEcxualRJIPw7XZJcf e6MIQ+Yz5hKkN6Naz7IVVynC8trh62NkLP95++75D4oQqpmrOEfG1ZOyj/Wa FGHTGOO3Dhl7LXxfOt2mCE7cmarPyPnW/f1o86JbESAm69lJ8n05XHczVgYU YZtRX14Qmc9WkROzpsOKULROXfQJme+E3FbTyAlF+NgSzi5PejRWUzyhapbM 59zzmB6yXhVj+pe184rgGF/7oIHsx8ctVVrbfiiCyLC53y+yX76OaZGXfynC ZPA2Hr8eAnO6+bY2/CP7wVh6KvKJwE98zOR42ZSAdeVkHMsHAtsFC5x04FaC UNT2Tu0N6d+I8fcp/Eqwy18n7FopgTVvJHiLSCpB+AZvC+kMAjdnepbvkVWC 3+MnHlokEDiwUJ/ttpIS3P77dnNuJIGLa748ktFRgocJbDSNQwR2bC1d8tRX gthd+6gOpD/nBy7ZZJsowdiTlpSnQGDdBc1Z1a1KUFAmWUSTJn37h8XU31YJ fCpPsx/iJnAwV3d8oYMSWHAsLNf/ZOJyuQgt3X1KkGpYMOjewsQumjsjT7kr wVK2YGLiCyb+YaTcWuGtBMVvHzr9y2RiQ8eWE7QgJfj0XmKq6CQTv4qQLt9y UQku9WiybOVm4vT36+00rihB9eRzCJtn4NNsf4eEEpXgbNH2nYI95PlNHOQZ TVeC4x5rjrk9YOC8uw+8o/KV4PzGFNEz6gwcO5y8crRECfKurD4o4WHgw0pR yY7lSuDlsNRlTyc/bwo938hUKkHA6oYdTwvo+NYb+Q3v2pXAU+thE0WRjkP+ CT7J6SHnk1fQTP43h122rEUJn5Wg/WvoHZfPc1igadTfbUIJFsb7HcWuzeEr A9nVK8tKwJe7tSTpxyw+t6IcbCinDEIZ6u+/PJzBu81FOWWUlUF9eBv9z5kZ rP8f+302dWWYiIPSazYzeJ5zqqGLqgzWHPPOwvRp7CueJ3/KWhmui6xS72lO 471G6u0lQcqQKxP3PCZtEhud0aaovVMG4ZojP5vYx3Do0EOWsGplOLHkL/a9 dhS/tRVrb/6oDJP5z6tvR49ikGEJPtGhDDL5SqHBqyPY5mN72YspZThb2PQ7 eHYY75U4Y2QlpAK+67cYBHp9xaHv3mz2PqoCQbpGK86MTvyWzXbHPUFVCEzc XbdrQwgyy+v3ShNVhb4ZrcIOuyT0xs7/XPxGVVAQ+hmc+eEWep0cn31eWRVE K+fbWdc+Qi8kPq24mqjC8YzuxOt3y9EzrV2P+A6pgqugZaT0lxqU53rw34VS VdAXSH/9x6oTbVpmCJ+tUIUaCzlfk/5O9Ph2pHrQa1XwzT1qvurfhR4NPXA9 UKsKC8PsfVyJ3Sjbb7TAuE8VeNfWaEw29qL7EUf3fvunCqXrk+zq1b+gtNyT T70cN4H4B5WeKr1RdC4odk2tyyYoWy7cfDJkFLkZ3dmpvH8TlF7pOJn1ahQp NNR+mzq8CTKf9geGbh5DpXQxvcDQTTCjYeE6bDGOmqmVz87mboJA+vSCovYk Kl3tWNufvwmeJO9IF/KbRKkfppxppWQcfzvHN3sS7d8j+H319SZ4fEm2eJvo FJoOPUyNbtsE+/NSNe8vTiHWau7yhN+bwOrs/qhn12fQ9FVZViaLGtg61X64 UDODmnbpuziyq8EGjqA1Wd9n0PWJg4uCgmpQa2IW8nnnLJLjeqp/U0UN4s2N LUTY5xBrx4dLyxpqQNQtbziqO4embg907dNVg81N36TZDsyhYk3WM1JmahDF MamnUDKHzJz2VGTtVAPfmDsTDfZ0JCcRwLZujxp4K42t8Qmmo3WjUa6HD6iB HSprsb5JR42n8n+oHFWD18jRpn+Qjvbe/GNQGE7m97XWWO4IA5l5CsWuj1aD 3VwauPsSA8mqqfYEXVaDLVn02KZsBpp87RSie10N/Mv/upwZYqDTg9nPnz9W g1xmosjTHUxkf2lp4W+hGhjVpViM+jCRsvp2HetnamA/dOPI7gtM1HNm4XHv WzVIfCbdzlbMRMUbrcZlq9WA67ObIdQyUez7DDnfj+R88hta3/QzkdF6i4zl djXwtFjuO72W9EVZWjf0qoEX//SlpyIEmt47LRj3RQ1y2njHtTaR3slJviox pQbb2wbSxu1IL9mN1R2iq4HH8E9nGTcC2c4brsv/pgYil7XupfuTHjIdDKOt qsEL07Zii8ukp0Z0X0avUYedG0tGT6URqOByzGIjuzoozyaHjWUS6JJWP2UD rzroH1UwTikk0IFOzUA3QXUQuFlBnCf9q38+6km2qDrEHeKIzCT9yyvbNTG3 UR0Ci7sr15HeGq9VVdCXV4erRwYTs0mPvfMPcw9XUYenQUN1F0ivpQu03q7V UIeip+nbbo0SKOi5Qi+vrjrYi1ZP0KcJZHUgZIOroTocuCR7MYJJIJm1jY73 TMnnxwJWbL8T6Odj6YQJUIeujQLKzksEat1xsl7LSh1m7h/+fuMXgfK+17KG bFeH4+5d3iKkd6MyxC0qndShKvZJSBvp1b0oIIJ9N1nfVm3Nj6RndSfwKwc3 dVCtKby0Qsbc8Rt+pnuqwzed41FHyXiUclRv6Ig60J9jWUFy/Oue10Gqx9Th 5KVpr5+kr6+H8xUcP6EOX2qpdmKkd/0VvKZenFGHSzlz3adI726pr1BkCVMH tuP/uHhJ70oFcXnaRKnD4szUmuE5Ai1uOHg3JUYdEj+eGSUmCNT8qrSv76o6 cJdfaDMdIlCOB6uIfIo6PHL7Ml/TS6Bwtr07/W6ow11/L98rrQRyLShIfHpb HZQSp93i6gjEvuTMbpmrDiPvHO0snhFo8O4jy6v55HooDSYtPyLQC8tfkR0l ZP8Kukfptwnkm5S15PVaHdbtKUlOjCIQ6P+gFmByvi/WoTTStxIDNie+16qD MJtGlLI3gRqV56cvtqrD8Kd9HC8sCfSwaYtyc5c6LFT4SbvrEijs5M1DwgPq AC3257bKEkjz3eaBnHF1WC8hotK2zESJLolNH1bUSU93PKM/ZKKHen/sy/6S 9fRniWknMtFLgcBPmes0wOVRzIHGECYab7ZvD1uvAbOa7MvCNkxE28bbqyuv Ac8PdaWsjjKQk2L4XlkVDZi/VSovW89APmvo/bwaGjDVTn38oJCBrr1r+jKl rwEfL9+Ie3uKgaYN4kfv2WjA71fXIk79oqO/G357x+/QgJ8VJ2NSB+hIeMF/ 4pyzBvDrfjgt8pqOULHd9K4DGrByp53b4iwdpatwM7lOaIB56pEG69k5tEUs buXMTQ2YODv4KqtsFu39sRzqfVcD4vo92zZdnUVBnb6rTlka4PwXi0p5zqLb yTb/NAo0QObomIcd9yya5+BkG63UgKuJPtJf9syg+8uxAg6TGqDKmH0a1zeF VvovqaoYaAKzM2ggM2QcBQ+eG4ugaYL/fPS+UKNxRB8NeNCNNGFAiSu2cWkM Dc+5iMXYacLNF6dxV8gYqv+jxDHuQcZJt7reBI2idPkPk1lXNWFt284YO+th RPVjeyQ9rAlKDuYVlxx7UeByjJJIvBbcmbhgXnfoCVIySFcWStECBcU9/SyJ OejLyUcq/De0oNH9mPPZ4w+Q3VzdJq4HWhA9x3yUR7mCVAY5tP480wKZV+6j 6Tdv48GaOIOJAS34KX+tYu/CK+yUnGhVoa4N9pfaWUJ+tWKO5nvWz3S0wXnf 5LWb19twJWexTYm+NqSz8HUnqrZjzehPdk82awN1g6yqiVMH5jrD73jPWRus owQPqd/twtX7r+2JCdWGV2qzpuc39mN9lRu+ro3asA9fyDjZNoyH0birSas2 XJZPo9IERnDCPuoW6S5tEBa6pZ3pOILHE9qlJ75qQ0PIAhdqGcFp39d3nv6m DSe/OHHl1ozixapY8zRxHbjl9/HQyp1xnDnQrX5OWgdu3HpjtKab9O2ikvgB BR2A2C8T19dP4BzVmgVFTR24G/HJ0TFiArsk/XtchnTgAtsO/vV7JnG52zmh Th8dYAeO8vKFKex55uO/58d0YAdhWDCgOI15k0UZt0/oAIV6iz/UZRofri7/ 6BWqA+cdvhbKl09jYbVv4QuJOnB591jfasAMrrIE/57rOsDz48zNnowZHHAg ec/rmzrw5dwaXsW6GVybrKUXnaUDBhMmVQLSs/j0T78pwQodcLApr1KrncVy Aq+6frzSAe1JG++L9FncrMZZ3V+pA9L7TtbbCs9hpYOP7mbV68Cxm8MCkl5z uKtmdKfuFx1odbClVvycw7frtdzz1lCgdSJx1X4dAz/0FQt2ZKXAp5n68bdK DJzPuSb2JzsZ/7eF5/Q2Bn5t01W0lZcCxwJSGyouMfBAfeifYVEKFKU9sD77 i4FHfQ8LXpGgQIfyVltBUSae5XRQ1pGiQEPYBjYmhYl/2cjviJCngGu+9X+B h5l4Y8PHuxKaFJCrrnc/V83ESn5PS6u0KXD30JzKxj4m1uS6U3tUlwJ6WEzh D52JzWyD6BWGFAiYMeaOECY9NbOH5aAJGScUqEiqEtg+zkKY1YwCj5Pl6YvG BD7QIGzmbEHGV7rcvPYT+LDfX8eVLRR4tftf6KIfgQO4pr0zrSjgMfdXs+Yc gU8/aT9rbUuB93p2mp9iCRxu+yaeuZ0CbBJ7qSJpBL40k/PghgMFnK8+WL2Z SeCEuKQys50UKJO7Zbm7kMB3Gw59vrqbAn/3NXhdek/6z287obuPAsniwt+/ NxK4kMtgXb8bBbYd1ne930ng8icyYlHuFODafdLn4mfSt7acGqqHKFDNLsSa PUrg2plvmz95k/1KPsjzZ5r0WNxn5zM+FCjgvLPvGpPAXWoffKT8KJAfL9js 8Z3AXxqKQ2uOUWDFzwZ8lwg87ncryT+IAiee92bm/yIwnSv6oeBJCgSlXJpT Ib26+OTY85enKJCefEf2618Cr9q6NnqEUCB+u5/Z/3//yjq7eZD9PAUIN5rF EhnzXt20UBRGAZ+9blpuZCysLsTuGkmB633iLCvkfNKNvyVWoyggchq/bCP9 q+I/oZV9kQKp1Xd2j5L+1eZutbCLpcD6R24DWj8IbJj/0vXbFQpYL57aU0b6 d7PdQ79b8RS42TvBDJ4jsNVsfARKooCZ1r/3ARMEdrh65tpkCgVOd6xfyBwk 8G51j9zEVApE5nhk8vcS2L3R5pV+Ojk+ypL5kvSvj79ey+dbFPizhfXPXdK/ QdxSI9F3KDDftMB4Q/o3JJ/th9p9ChT+cBsVeUrgSDuCsz2TAiqXXv7LzyU9 PtsndS6bXJ+iPdFhpIeTrlZTZB9R4MxP2+LLpIfvN97YG1hAgdXh40IuJwj8 IXY9/1QRBdjp2/Nlvch+W8Z88CylgOyOVh2LXQQ2eXNaz6WCAgm/hUZiqQT2 PEufbnlBgaF3IWEFCuT7qIcfWL+mwDWfuDEVQXJ9C3bxmmIKDGpS9yqS+//X 0abq8vcU2Ghkw5dLng95pS3ntWspILHN4GtkLRMH3dWblG+gQIXaA3Gz20zM lShYxdlJAfPon7aT5kxMsY0Lie6mgC8n8OspM/FutjVaq70UkE7++7yPh4lz IuYziC8UqDIgrhr3MvDmoNZTPZMUWMOv4+ToQ3rZMVE15xcF6kdyBbf40PEd HrZB6T8UOFjwYnfIFjqu/hiedvMfuV8vs5fxytExPwSsiWfVhRmPXZQjvXM4 n7L980k+XXD8ceJ5z+Y5PCzIlYwUdOFd3vzEzm8zmONT1LZXSrogpr/gx/5h BmtfXf6tp6oLz9oWPdRuzeCwtdO+Kpq6IO6V0fLObAaLfq+zXG+oC6qW2/Ya XZjG27su/Ryw1YUn22IzzWcncU725sY4e1242Mrt01w6iVeDl+8ZO+qCjFHG 9fchk7hYMGBbuosunJC+4DPOMomFHHel7fTQhWs/ewr0+SZwX4O8Xv1pXbi8 MFBtzTeGD+PKwIoHuqD85lVYo/tX/C7pnMXhh7owclfxcmjTFyzqrieyIVcX RI7sO+tp9AV/XM19eyJfF7jtE9S/8n7G6rREHs0KXZjn7RpkK+nD8+VuTx42 6oKKUL1UQWcnDs9fHk/+oQuLvWb0lbM12HG6XVtvWRe+njz3Z1S/GiuoFJzr +qVLnu/QTQ7fqnBD1kFeCRY9KDdT3HKn/S0WzaimPuTWg/ilTr7GR89w6eWE 6HJZPSjRLhvuVQ9HY4fl5Ppt9SBPYmH1mv4H9Pzhil+YvR5oaoXP7wupQ1eH O8qkHfWgb9e/17EvPiLKgRhrLxc9ODVZn0Y3akThu2aD5tz1yPvYztsrOq1I 1LL83Z9TeiDQ13Xtc2gXspO1cVO4rwen/0jim61fkdn5EuubmXoQorRWT991 EGl3iurzZuuBau2PyzIDg0jo8gTvz8d6IJ2z9W77yBDqZ0ZXNjzVgyHdPCfd xWHkW/lO/uQHPWhgkTo4OjWK9osr801+1APm1j9CoUpjyD444df+Rj3guZxj ne05higqbp1bW/Vgl7z6ptzeMbSUuHxJvF8PSm3/zG6pGkexB6nTmK4HRyd8 XzNDJ9G5F7e79Ak9YFvz7btA6STyF1z7/sk3PejvcD38bHwSOXxoy0j9qQdv /W5OBdlPIRGtoO1HWaiQ2n18d7nINMpZzSvmE6ZC2IuJe5lJMyh9t8Cdi6JU 2O1GNG17M4OulJ69vCxOBffvwzVuUzPo2GErz1FpKkSryvzuMZ9Fes1jgs9V qdBWcXx2cWwWvb8jc+agKRU6f/evVRemo3HO+kiOzVSwWXQMPUejI86Qk1ee AhXWhOXsFfSkIyen2jtsVlQ4ovNFXvYJHQ2z+lcXOVEhFO9hTddjINbgDc17 dlHhvFHtOsVdDLRp6G33mt1USKpNmFkMZqATr/hnXN2oMBVwa/VwKQOxBFXw /z1CBcEdHk5HFJhI6bO7RJ4vFazi6U84zZnIxoZT0fkYFSIO+bnSdzNRioKb 4aMTVBDFQlPBV5ioPJkVnE5RgfNNCSGcyUR9q0W2v85QQc5YOvnHcyaS7WU5 6BBGhb77dr0nRpnIcmu+z3IEFXj+hD7kXmIin6e7TjyMokLihwO2I9wEKo5/ dPFnDBV80ngStlBI/y47JmZeoUIkX1b8JwvSk0dW0u3iqWAnqCt+w5lAm8E+ /34KFbYmi9V0niSQV9GPMptUKmSc79+9nfRRrOSDdws3qEBvDPD6k0ig/Ms2 H+/eIvtPu5w5Q3rq0+K3Nqs7ZH5Rg038jwm0cOjOwPw9KqS7bHpwnPSYaOvW 8duZVGhgHO3lfEcgmhmTsTWbChWGG20/k35zf3JziZlLBaX1x3omSd9Fi1qs ycijQvZw/iGNPgI9ujjLvaWACu/ltFvySB82zqcKM4qowGVu89t9kkDMg+Yy N0vJfuTaf9pBJ5BQ06SqRRkVdtUnbTpD+tPQOEV3roIKJ0S96F2kT/fnmpje eEkF5l+J1QDSrxFCY1vRGyrs/8ZFM18lUOaFBIeZd1RY2/Iyfhvp31q6wd7U KipwjLMQMaSPp/cNHTKvoULJy6mAv2TM+/HKsakPVPiv8T++EjKm6OuduVZP BbaMsS83yfEuWZ8jTZuoUJ0tP/KSnP8cX8yViRYqWPo7KQmRfr8bpn09uY0K 3AGXSrJ/EqhquveOSSdZ/6aO+MAFgrzN/5c71k32U9ah+jiDQJw16iWJfVTw a+M9kD9FepPS9dLoM9kPnks+0iMEcroXUT3ylQpn9mdxNvQT6DS3anP8MBXE psOCi9oJdOtsW7fBGNnvLq2uxnoCvR0/PzQ0QYWmze0H5TGB/gY+jT8wTZ4H Dm5lvwoCWSxNG/XPUkG8pWxpXQGB6rj2pnQQVNju+tWNmkbmk5ps5rhAhdnb 903rLxNou9TH6aZFcj+O7aopDSVQm7ahxYcVKsReFDgV4U6uz8tAhsUqFf4d vSvm5Uh63iI3o/IvFe7c0d95BxFoYJfwwot1+hAfl5TPK0OgiXMLD/PX68P1 Uk6O7x1MtGmtuqOqgD682yx25FIlE/nHH/qdLaQP0Q6mjwKeMNH8vbZd98T0 gc699ZdlBBP9qi5mTZHXB0tajp+gNBOZ2U+W8irpw5v3j+je65joQrf0wTgV fbgZcve8wAx5/qcTKqI19CHVEweff8ZAfOuP+Zwx0AfVP6c1bpqT/k5/KLRg pA/LwRS7OhkGSpUdqAyi6cOOna827PpHR+J6tmK+SB+Ca/j5rlTSkcIe1fr9 tvoQeS82+IQBHRlljanBQX1Irg03qWabQ6HqG3veeuhDvla1iMjXWfS2zDna xEsfbJwkx1tJX1vWvR/QO6oPgZTW41Ees8h+7kG88kl9+OI9Oj9aMoM8DQ4w uGP04buSe9ghg2kkrVXGH3ZZH8QyHB6ksE6jASVuvbk4fRgHNkzrnEIuwi9D mpL04fhyYcK641PI5vsGloRb+pARPJ8dlTmJKE+bhNYX6sOtzvoEDvo4YtEy Nebv1Idurvr435oj6J3S9f0XuvXh0fkSl2TGMAqVmgknevXBd8PaN++LhtEi z833rV/0wUBT5iuH1jCanl2wS5nUh9H8rsn/HAZRW17+QcFf+sAmL92+VWwA ZSlJXtwgbwCTbtefsJm3oxSdsuqXigYgtiGnW/BBG4qi2a91VzEAxfzK1/ks bcjdKfK/PA0DiFuvbKUa04Ikw0cvmBsawPenDxVOXqxH1zvzw49uN4Bw1UGJ PbVv0aVo05A3Zwzg2vJ82MGjefhUYleF5zkDCHwhbPs4tgh73Qr8wRZmAAHP ovZcc36KofjBaacoA2DkRNxKPv4cr/avOzVx1QCex1m7tztV4TO6zcf5Mw3g xcr5TJdjjdhn+ICfd6MB6F8F9GFtLz7NcWn752YD6OE8ptiZ0oujtQu0drUa wEsbw6+7ZPrwvfCVb5ZdBrCwS/lLplE/7hJPD1UYNICqEvZj/N6fseXO1viR bwZQ9FnixY3bQ9jp3M/AfYsGEK/0fEqLfxi7P5B2av9pAAfDNnI8cxrG5xnH hN//NoB8KUPWWx3DuDSO814mmyFYGNJvlrePYOlqi2IPCUOYy+rZsebtGFaf 8U3p3WgI9utEq3ctjWFjgZRgRxlDqLq/6qCnN45d3AcNkaIhVBodb0p6NI6v /grFMlqG0BzAEZcdN4GX9crbvoIh8ERtN99mPIXZ939+5rqFnF+99kPrsSks /N/aGy3bDEG30u9l1/0prNPqtO+dnSFQDrOq262bxj7HGCN3XQyhTvKHe8OH adyVrfLdzdcQ5jdtK9lBmcXCg8kLnMcMweFax/oc91nsIr7yrSLQEDa8+rxh R8Is7kxomuc/ZQh3LpxWSJ2YxR1nTjBrIgzhv+kt7l3Jc1iotJ9xIsoQ9lw0 c899OYedZy0Z0hcNgUiu73w/PIfb3UXoZ68YgjN79ES/Nh23Wb+e0Ug1hFmW CxtOVNOxQLTiTN8NQ5gx+LI/doKOnd4mTMfcMoR1jt6/RjgYuJXiMTV0zxC4 D42/8LFj4E8SrBOpeYYQGujjk1bHwHwugeNQYAhamh/zasYY2CGpZ4xRZAjT nKmGVBYm/rT2yah1mSFsPzdg1m7IxC1zO4Z/vzMEGUvT579Jf/CqvBjKqzKE LKF1M7LPmNjeU27ItcYQhp7SbkXVM3Fz18LXknpDqEH0yz8WyOf5D3w90GQI 977FLnJykJ63/fCF65MhKHd/s9wjSfr33c3P3p2GwL7lkkP2ZtKjyyyfBXoM YVvPzhOZjuTzev4D7/oM4XehqXmvB4GbHpn1iw0awjXD0qz5CAJzj+T21Q6T /VwYvtcRT2C7jfx9J8cM4fC6UD7GLQI3Jo/0NE0bwgG1b5KNpeTzjXY95+YM Qfazt2UC6UU71vJuZaYhBNV2/44hPXl1s3R3x7whvKz+pfKC9GbDudiuC98N wb8sNluW9ChnGdGp+dMQfp7S2olJr9ow9nb2LxtC68hD/nTSs1dUqztifxuC x8DtymzSu/WHNDqofw1BzLTBfJr0MOfdtPZhFiPwGRkJ8Ca9bNPzpy1xnRG8 zr+lIbJCjhc42kZjN4KLp7P2/SG9/dGurXWK0whG2kL7NpKeZ48xaU3jMQJj ce6HJ0ivW+GHnyz4jEAuqfP9///eOnaF5xNTwAgyz+Mt78i4jnqm5c4GI6iU f06tIMcrXQ04vlHUCLJuSRVzkr6/OOwteEfcCK5+Vwor/EXgUUO3MsmNRmAt +F9O5hKBIdHZ9ba0EeS1jVInvpM+HrNdkpAzglCBVb1QgsB/TCwyMhSMIK4k ssBjlsAHUoxNJZSNICdB6vGNcQK/ntT5ekvVCO7HXtaRIvslbq56QVzdCBzj lJy/9xD4bKqM/C1NI3jC6KJubCVwz4xIjZiOEfxUuL82rY7A+rD+yE1dI2CP vEo/+I7A19NZOcT0jeDBrhzZ82UEnqf/zks3NIKk5R8NE3kELsqYpd8wNYK0 df5m5dfI/TQ/kiSy2QgsNmR5isYQ2N+qn3IDjOD0NpPyxrMEVvn+8XTaNiNI PPw8S92NwJdssaiwjRFw/S652bOdwGMPnr9MtTMCzitfz3abEjjTPnf1uqMR 2B2fVGiRIPDfh3fvCzkbwXhV6Y06cn8fXEmF6y5GwNNVaCj8g4klH0VfurbP CBY/btlV1MLEaf88eFO8jWAoW0d1OISJF1z3FPP7GAETN5pe8mDinYUOTsm+ RqBXki9zwZqJ+faZpyUFGkF5THRlqAgTX3kmKZV41gg2vei6mv6EgSc5hSp5 Q43ApEDW+k8CA2/z4PJMCDcCAwUUVXmcgdfyLmfH/2cEbya2uTlTGTjsSLfG 1XgjyD3xy7XlGR0PvGlu4Uoygntyv8pFrtGxsVDt8bgUsv7tSm/eBtHxYuWz sis3jEDMZfag2iY6DhJPMb38gKxH4qt3cuoc9mqy236pzAjS9d7+Vdgxi01T DnkvVZD7kaO57z8F8vPS9VyY/0sj8KUZRTktzeC6wdwCp3dGMNzBdggezGC1 BRZe6Y9GYOX9KTlqehrPi79orhggz8e3kzamh6ZwpI+iw9QaY5A1RL1OC2N4 jwbNZz+rMZyq4f3P98UYpsw7RbawG0OsnLAVf/gYHj0fWVzGYwwRuVLv+FjH 8LbEfr4oEWO46Kcvs8Q3innLk1vF1Yzh4c1qqTTBYXx7zaqTnZMxfDi800r3 cS/O7XeJXXA2hridyZx7+Xpx6dOiN7ddjUEnPDhi8HQPrjvkoTK33xj8Tu5l 3wjdeOF99e/4I8aQrbpgVdfagW2j4x61hBqDVf+CqkBJE15eK7bqlGsMfTKa 7lHGRXjd5+O6K4+NIWPR0/XEhjzMV1bvk5VvDBz7TL2fMx5iJe/Q9m8lxvBo q31FvsU17FTz9dH118ZQ6icnaffjJnp8MWdnV6sxNCmu5dub8BrtZtV7vOeX MWz6/krlXiV5H1kWv9CxagyFTbt1bju3oyf0f7t3/DMGKBt5rjXZjla7Wti3 sJqAM5GTws3bibJz/Xy0+UxArkMsxdS5G81bZSmzKZiALMtKcOyHfhQXJ5Dz zNYErli+mKkSH0HPIpbCtOxNQPmQpNK/vSPoy8nBXXkOJhB42vVUz60RRNlf uO7+LhM4fsbinp3YKOpRt/GOO2gC9nzPHRT5x5BC8wUFz5Mm8CptzCViZhzZ V/n8GjhlAgV0Z5FShQl0pnxHh2uICQgE/wo/6jaB6u9ujN4eZgLJq+4Mj6YJ dDzwxYhhjAnU/MzO25c7id7yEZnrM0zgn3FI0EWYRuKi4unv7phAn6X1zbQz 0+iUtEV84H0TMAmS/29N/jRS10w905JtAkJDhaqzAjMow9bILrHYBPikLYt7 e2bQopMnMn9qAnTVyJbH7LPIaW+cPqPMBForaS2NBrOI8+hnmR2vTMAXFSqz XZ9FIZcufOetNYHwWFqDruUc6ojPm35bZwJduYsKkQFzSCu1/WtAgwn8chRb I5o+h8azFOubP5mA/wzzg9LUHNqFP95N6DeBi7bFjNwoOiqum79m9sUE2EUs DQ1z6Yj7k8Rl+qAJUPL+/sfTQEfVX46dtB83ga8/F8Ki+RiI8ovfipcwgbPz Lb7JKQyUsMbE9O03E3hbVmRiUMJAU5xelIBFEygeeYElWxjovli5ZPOKCRg5 2ux5yE76Q+Yrf/gq2U/JXXu3KDDRbhV2Ns1/JrBrn92gvDkTrTfYS8Sz0kBJ TSDzxgkm8jX7b9yUgwbmL44SanFMVLslv3+OiwbCz97NrmQyUbjzas12fhrE T4Xwbv/ERLPHM2/xSNJAnSVKIleWQFZnGxLfSNHAxpZfmluPQA8jF6KPydKg 0+TZf4+3EGhf4tbAJiUa5DICXa8eJlB5WqBXmCoNVGSVjFtPEUjgbvoeDXUa XOva5L09mkD1+dMW8To0uPJ47/npuwRSeiZoZKpHA0eqfB/nEwJdeEXTnNOn QYDsKR+PctJvVd7yd4xowKIoPThXSfq7PkF0O40Gzz53/SsivXm9tYLntxkN PNe8zs8lPcrsGWQpQDRYXt1c10F61W6Q4+d+Sxps5usxMSA9mztBmePeRoOF 09/ozaR3w93O7y62poE33+vLUaSHndvfv99pR4NT+aMxJ0gvb7Lm1vphT4P9 /7Tb7pKe/vvW+dYtRzLfGi9HNtLbXXp31pk5k/UUWtCfkB7PzxsLGnIh+30y Ofkq6fUoGc2B6D00yP7Ir/CY9PzutNPbVPbT4JxDZNL//59ak/tdacMBGujt vNObSsZro9ikAj1oUJSoL3CYHN/3Y8dlAS/y/Qte20+Q8xcfS18oO0yDvEB0 9+UKgS6NDB7cc5QGnMxREXMyv/17VBt++dFg9pBP059vBKK0HNe/H0AD/GK0 9RedQOxbXj6wOE6Dn19PGOqT9X95ycIzcZIGa2rUhPKHCfRM2zbkymkaOLmq hBwg+3cl59qIxlkaOF+8cGY72V93yQH71vM0uC3qq3iW7L9+isLL4HAaFK+N yhwi14eb/Zii6AUa7HHrU40h1+/Ft98rBy7RwP1k944r9wiUdHTrEZbLNDCu xL6TKQQ6/DWhLTuOrCf9TGz0RXK/NEg/nk2iAYWrtfqMD4EmN/sIJV2jQZ3e y4Mtuwn0trw4QjeNBpPsy9+9rQjkm4lczmXQoKqFncdRkUCbRa/gjXdp8MT1 Jm+OAIGEE9rU8X0a7NY13mTyh4mqzh5aw55Dg9SGsf3KXUyUzngS8OQRDRzE Um0iSP8HeC/02j+hQeLJ9D+ieUwk4XixOLWYBlOBo/6C55lovrZJwugpDTSy WleCPZmojiYcM1BG9mfd/j9i1kwUrJLrJv+KBrEhyfzaQkzU+KeOs6SGBpb6 PP43HzBQ5in+0851NIiQCumV/4+BQmb2DP2oJ/dn8PO574cYSKF7usLsEw1+ rd46e1KegUILub0b+2hQXySgPHaTjjTcHN5NMGjwMCZU1sB7DskxlJrc5snz bnOtab/ZHBK+8LuvfYEGPO56UzPCc+jvw7zFd0s0EC2q57eunUXts2s109eY Qunu+8v8UrPobOiL21YipvDKpy4isXQaBfAm5b0VM4W3P8ovZ0dNI8/7h5/r SZpC5oDxVR2naWRXLdghI2sK3Cvj/YWMKSTNHcC1tIl8PunV+z0KU6gmQ+7c YzNT8CJV5XxqAr3UWIqRRqbwen5B0tx0AhW+a0lNtTCFwEbnjqK1Eyh9JLTk gpUpXC+2M1dJGUd+at2Te5xM4Z5gb05a7hjifxXnynnYFHYmO9ieeTOC3PoW 9PziTUHJ6HRmr/FnFB3B4y6cZArR7sdDQ7MHUJ6CUhxOMQXdD01V3usH0M8A 1yGRdFOY6xI1khjqQ9fXvIyvzjSFbT4ZThGhPahePWJ843NTWDnHwvc2rR3p R3Ckfxo2BUv2zBX+rneIT0FqhWpoBmUb/mkeRI3YZay67qmxGfhvLvgNgU04 I8cvTcfUDE5V308Nu92MlVRf6GiAGZxt0ZHqW/iEaZrOPgp2ZvBu9aiXXks7 PmJ4pVPA3QysCvR+HPTowW/tFosYMWaQny/hnSs6RN7/7oQdu2IGb/KHYrzu DmHrFgvbmatmYHfvxM1SgWHc4Zg8Pp5sBhuHG+rj04bxtIv6xi8ZZhBY1MqW cHMEC3t4XmksMoNdhc+bQuPG8LFTzV6Pu82gb2cIn7jwFFbPvv5IvM/sfw3X ezSV6R4HcLVlImMhos6cTWPsGiO7dGRne97357Yy3Qi5VYjcQ4whjkijCU0m Rm4hlz1GdjmVW0Z63JJyOzpSUzvsks1mexMil3GeP79rfdfzrPV7n+dZ7wc8 WFEpkfskWPrMVZryyhweyyzX2MVKcJDx+/DTQ+awtbRxMWaQ5OmV87vGzeGN YMOlK0VjOCiMe6Nh2RyWeWHB40pSbHBj7q3hqjno1epm1JtIsbSngVO4BsGp R85Lnz2lOMjItvK8AgLFgC+FHfekOFDm1WijiuD0BzftlCMTOCA443WvHgLP lT80VyMm8fbrrjoWHASBVrcen8+cxGNP2T73tiO4XZhlFlAziQMMhNLMHQhC M064+s1NYv/x1s9upgjWFb26rhYqw5zNqahzL4IYrYfOVankf9vWPtHcHIGx feLL2jIZ9isXrdexQHDh613WYhHJ/nNaI/sRMKoo5L7FFOZkNxw7eghBXXlZ xHG3KTzannij3Q6BYMFjxePMFPbjqGy76YTgUHWRVnw+6Tv3B21xQZDjdEyU e5f0L+ZVXnZDwI0yKlZvJ/33nD2hHggOc/lbt8hIX1MWM+SFQIKaXMpXSd+6 qtHeB0G6eldShhqD/QS0ze4ABPxllfqY3cQ7/etSBEFkv+R0fpQVg0dZXV2a IQgyOnYJux0Y7Ovj6rQQjqDP0dv2lzAGO5d51RRGImj/VbtOJZ54dTxgk000 gqaiwOxu4m0zw/DoiRgEqW7tBR3E24ZhMS/T4xBs6CgpWBUwmH0vcS8vAYFW quRMBPG36lxK3mAigovo3LQu8fdsbN7x7y4hGGaQ907i7dHGksa+FDJvAzOF dOLDl3JC9tlfEPR0f4sNiR+fWlUlsH9FUBU958ci3n7wc8NwWzqC1UcXX2gQ b1c+abUIzkSQ4twq9SLeLlLuKlHLRsB5nBUrmSV+tOtn3c9FMG0k9SpfIN7L EJ3yyEfwWTMssZR4O+r5yCP5GwiafdLfvCQ+DtCWcYTFCNTfHo+zJZ52PzZ3 6YgAwX33N6c+knywcGVsvgxBfDa7cIBkSrxuf+FNBEbehtw54u2d36gIrW+R +Sap6xwm633tv0l5ohJBVIcoUky8rVHBDkm/S87DfJbpf4i3FWScHtNq8j1f HwytI95e4HK5g7XkvNNKuotTDJZGmF5NqkcwIH3lGD3OYFENPW3wAMGL+m5V 7jsG9yzsc+h7iEAzPitgq4jBTXz7quhmBDfdM1IP9zP4XryrBrsNwcEInrC2 k8GCZq8f29oRNEhW/3ZrYXCWfOBA0BMEd954/sm7z+DkfeGmal0IRqN61Rxv M/h0d+LnE30IWOw//fjXGOyhmuou30/uW7het2Iyg+0dMxoqBhCMfTxbrBFL /P5Xybn51wjObHjkO0x8zflKOFgwiMBfVvmwmPha27OKthYjMOfl+hSZMXh5 pHVN+igCvY2mG102Mbj1w8hFg2ky7/3X5qvbpnD1btnof2cQOBv8fS64cgqX Rc3ti/5E7m8+N9g7ewqnLq9TaltC4FNTorjRfwo7rN+WdkKBgmfCtUWpKzJs fYDLsBQp4K8N/cJeLMN70kztKzZQoJRsl+PWJsNbNGzV51Up0ILr6fxkGX6r E5h19R8UlJp4eR34QoY/xq/mKrIpuHR0nkmTTGLW4LWCC7oUCBwka3c/nsTf 5LcIIvUp8PXmlBUmkfdE+6sqVy4F1GLrgMbCBJ5U7e3VtaJgdNVrVqVFipfD fP+Xa0NBgYiPBDlS/GXv0oC6LQWzde//JQiVYqMr2wflD1Gwo+9mokRbisMV L0yOOVMwZvdM7Te/cfxpjYni3SAKjKN+MjCTSLDCyU5lgxAKGg6EWA5VS7BW 00nV0jCSBxImlhMlmBefpnUtkgJLvecby7ZI8L8XJfox8WR/I/6dLptRLDeT Z2mRQYFe1VMjp6QRrDgiF9dXT/I7OeHZimFcZHSZnfmAgtqUw20tJ4cxL0az 2RmTeVRJNmdqD+MAFQMFURsFB3+IvFuuOIQ7eI5XR3spmJp3vyB/R4R/vvK7 YOk9Ba+aN890PX+BWab7u/XVaRDvHVf96ftOnJfYHzamQcNiq0XmxOITbNzl oS7UokGj02QkTdiBvU/+4LLznzR8UF4vvq3Ujlsu54vNttNwa0c5y7e5CZ8f npqzo8h6m56dEfuWY+3vYnLULWg4a3+8YUm5FN/5kcV/bkVD8UyOvJL/dTyk pH3e/XsaBuuDu/jL0ZgysVDydaJBblHfhg4ooQcSOm9tc6Hhcp9OEK/5Dzr0 6VE7qRsNvb8f4cdtvk0XegZlhnnSMCmuSSh6V0XvqZjdY+xNAytvpoKXVkv3 zMb/NXuKhkMJIlt9Xj3tRyvG1fnT4HPsqLGDuIFeSfmNHRtEg/STJQhTHtL/ ByUwK2A= "]]}, {RGBColor[0.880722, 0.611041, 0.142051], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwU23k4lN8XAHDJTrRI1uxkH8Y61D1JomQpIrShsqUdCcnXGqUkRQslJUnW QriIErJkyZZ9HTPzSoRS/d7fX57zeO+559573nE/zzxk3U7vO87OxsYWx8HG 9v+ftX7Xq13/y9y2YV7aZnmBQJ1rOr7OvfsPbRV+LZ9BxmXXxNs+vruNpkfv Z6XPE+ia4B795JSH6L/f3CPf5wik8alib8G7DDRP7epKniWQMP+BsJTsLFT9 K/tmApNAK1asgrCUV+jrR4ZE/zSBzu16P0c1y0fJRbXRweMEOuEpFP/8XSHS 0pWeODNEIOdYF0UJ6hv0nZGzp7SXQNbZzytvZJcgt4LRFocOApk2/nBkl3uH nqX9izf/TCB9Bvp+MaUCKezjSI+rI9AdLvO6CzxVqHNH5RbFCgIJbWLc0jSr RvVmtZYbigi02tBQ7cm79yhHeA2TmUagYIuBRZfFWvRZMaymN4lAP50iajdS PyDJWxldkrEEol9qPRSbXY+cNTzCHp8mkMc1f9UdE5+QmWTzlbFjBBpIlVxc kW1ELdFRt0L2E+jLO8+bZ1I+o8i6yYECXQJZNQkeUu1sRhckzO7bKBDI3a9X +BxPK3rq4eKzYwOBvoWGDauZtaH9Muye2gQLtaU1BaW9a0c6bpuPaqWxkGCW 9LHggx0ovYGdej2WhXbnndt1cLED2RXkZ5mdZ6HaKlHhDdQulJMRsVJtxkIl wx6vorK7UV/A0TOrhphoYfrtbXeLHtSvIXDaoI6JdOb4gmCiB/GuYR1peMFE Oez55r9k+5BD16tfPGeZKF3+z+CplG9I/2/1/M9FBvqmZvtht8EAmrnCbyvX zUDiuhk5yp0DSHX4clHuWwba/eRp+RmeISQdJjPMuMBAtQW7Y1XNhtENmkWQ 0NQMKmlPlnv0bhTxJ+XyhebTkWgl+zbKujH006rP/2oEHQVm+R2sOTGGTLR3 p3cdoCOjEPObE+vGUX68kHLQ8jQqU/r5R9NzAvmqm8zX6E+j8ksOPVh4GimU XmnblziJJD2q5+28p9FjK/O4H86TKNhaY+0YnkYB7hdlluQm0VZ5zl08PnS0 J4hPUCd/AlU2FRXZVs8gQfso1xsfxlG1tPDN4VMsxGx91iLfNYrk+MJenn/P QmcWN/x5fmcUhc/PfOAUI/vGd+vSM/tRZPrp/R+VWgJxvNUrk2gbQW6lpXpG 12fRt8QN0oK1w2jUzSvj6uh35CcrFaSoPIjGi+tD19+cRwPdqXyljZ2I7dTR Ys6SeeQVSGil0jqRuMLSzNLgPHpAr5tdzupAtonKBwe1FpDb6Yo+04h2VOYX Rc1pWUD1nrt8nfXa0A1ls6mdQovozvFN5a68n5B+Cra7dGMZxX99eG1LzHMU FfxGYSj+L3qbvSHXQrsVW0jsrOAr+osuabntPf++FfOWtTvo9f1FBovHrI0d 2nD84mzUNZV/KHy/r1lywBd8+5zatO6HfyjwSLy/5NsObKvb2lV7hQ0ypHVL Ujf34MOqO++Lla6CsK3l++nlQxhfip/MbVoF8jLfdjetDGGZT+1Us6FVsGv1 aLCVyTAeOenW5MfNDopMCQO5smF8PPPKn/cO7MD75rLB37wR7CtTdsRvjh1+ ExGHXK+N4c+nV+Ws5loNWvxqk9Hvx7Amtli6J7YainYt5G1dGcOzh77efA+r QVTVP3CH7zg+f3++WjRhNcgp3Hp3z3wCB4loKbxX4wCVt5lWwaOT2OdflPOq 7RwQl0hdPSc6hV2nBm6iAxxwXUsq8NPeKYzKbvx5F8YBqZp2E/eKpzDHYVZX UScHrLC2f0sJmcY/zc3X/KBzQHLePb8/r6bxpNajHdpsnKAthRpLv03jhlXW ea9UOYHJ+lNnaEzHCZmvYp9d4YTEs4vDVBYdh93grBpL4oTxoTeft4vN4HMB h37KZXPC4Ef18vQdM9jeco17Wgcn3KjSErZOnsHiTF+Teypc4Nhd9MWaysD8 XbXnurZxQW25cVeTEwOvVEq+ELbngpMbIw3uhDDw4M2mjbdCucBw9fWN7HUM /FRXnYht5wK7Nc93GO5h4mSpCMX6KS7Y+8tLfMGbiaO5+l24/nLBqeCTtT9j mdi7O64+fAs3mCme3Pyhjoldqkf/Vm3lhsUwmbTEESa2yjbW+7ePGzQ2BSY9 /svEWsEzjy+HcMOG9JM5EbosLHN8R3dpIjdoPeOtdrRm4fXW9wWXnnNDVNR+ TZ+TLDwvvefyhS/c4FSySsHuLguXvc+2P6XMA3yCGl0CLBZ+mcMe99KEB477 VzA7VxH4wR3n6mk7HuiaaZjqEybwlZN8mieCeUDOZKv4Q0MCn7F183h6iwfk u78+cbQksJtRWerIMx44l7evcO9BApvxe3MfaeMBMc/ftBl/AuvPV299OMED 5ids5RMjCKz8TexC328esC5ounj+FoFFP5zNFlvHC4Pzt+ZvPCQw3+tPQ45K vCDkduP4WBaBf9+V3ZRszAv/FV9KPF9IYEbYpb0dtryw1uWLhUkFgQe82v5b f4IXXtX2Htz2gcAt+1TKbC/zQjsrOfVSM4HfSM5xKCTwwnoX+YoLneT6Jsps Fp/wwi+5Qv+aPgKH5/2X2vCGF9JklV65DRPYK8hq/GEDL4i+1rJ0mCCwrdlG ytkBXqBFOuin0sn1CA4Emc3xQlwdy02bRWDJ7md1m7j4gE9Wvkr8O4FXPzm9 dkaMD1iy9O0HfhCY7mPoUqnBB7F3+QZH5wncqrfq2a3tfJCuIH7r/QJZ379P sx4OfKA1G2y/QMYPPyUaG3rxwVDg8S2XyDjitksUfwgfiMV1CNqQ470PKbQN 3OSD0oMpAgFzZH3KTImCp3wQXWqn8p0gsMH34hORJXwgf8X7dAWDwJvfheY7 NfHB6X/SjL4pAnNE7lpRG+KD/QWhr63GyPqs1+7694MPri26NwkNErhNtOfW F25+OPon1Emxh8AlI4/7MyX4Yb7ezvf6FwI/yvFWvqTFDy1HdOQtGsn6/Knn rHbwg9t6q/sO7wnsAyvl0o78wDaZvlBcRuB9fHXcP7z5gaXAf8Arn8CGHdf3 fQjlB5F/20ZPPycwp6f0lO8zfnj+QUYjgOwHhvaUDpTxQ7h77M7ASAJ/+Z0X sqGZH6QU9Uw/BxI4LcF0Q9kCPxg7x+DzhwgcdZD/8HVeAfh6mL+wzprAvvId WUelBICz8PoZX0Rgo7fHt3HvFAAd7jM2pZsJLHNVM7bXSQC2jUn+PrKGwFx7 Fttf+QqAeIpnpOtvFm4fiPGyTxIAkWkJH6dO8n3JsitSzhIAc+9Hnk7VLJx+ Tvzfr3dkPs6VmNc5LHyKKyfp8agARHe+vutxlYW5NVswS2cNCNGrDs3LsTBr 8S5fjfka0KS0fH7Ly8Id1Ucd7jivAXMOu8udBBM/dpijG4evgecaqx1ly5jY OGSjSGzbGgh80GDCs4uJTze5+MqfEQQn3eyXUaYMPKGl9zgtUhAcQ26s1pBk YNfbgl0S9wVBYlK7U3xhBu92rkbCHwRBVWCLQevTGaw0pbSBU1IIGCU5+mW/ 6Xhg9VzpxEchkHx5sto1Zho7nGxkuX0TgpPUKMGpA9O4qeGp/OCcEOwK0N3R oDCNv9W//DAjuBYeykhP3a2cwo0JhyljRmRskNcZSJ/Ez6VqV3cmrIWrx7ol TipMYLcWyubbqWvhjzJn1tzUON589aGhXeZasI9S9pnOGcdJY/6nPpethdjy 2AObqeM4/KXK17rxtZAod164xXAMHzZKyH5jvA54Dk/cfqY6gkUcnO3uTa6D orXXYOZkH35XZWamMLcO/nh8UfnS0YuPqmsZ5K2sg+adzqzV23vxy9UcUvXr 1oPB1VEJx009GApeTS0arwej8/dXK5d3YR+hVWGON9fD+YSk+J7pNlz16Xmu iNEGuP+AY79mPcZe2xb471wThiTrvtSe4noUIy4a65MkDMTOr68Ehj6hrJ80 LtNHwmD1WfFFJm8jmsoNYyPyhaFPI2qG6fwZeUoLLFj0CMNvT7FL8b9akSeb /MCK8kYoOvS7bSWsE52osc3zqNsIeVkn+3dtGUBRj85rGLdshIsqiwrHXg2g Z0HJ2et6NgKuyTL6qD2IJnT6n1YyNoLRxWhlA8khdDzjZIqosAjYhPnd8d08 jDwiQsOb3EQgi93324DQKHIzz7HXZdsED2r1ni8/nEC7T381H+TbBA3/xFz0 vk4gnXvsRtc2boJpl9T6bqFJxE53khpS3QT/djFT7K5MoozrnBNxDpsg+iDK nDwwhcY6DgeMZm+CWLuu1JTJadT0J9brRvEmWBvncrFShI6KlIpdjKo2wbeI MhfDnXQUEcgPCZ2b4MBez13K6XSkKFnCY8wmCiavTK927Z1BJ9zXpSY6iMK1 ZNGFvGgGso43id96VBReRK/KevuSgfSLT4ZOeYuC7+OVU5wtDMTFXem2LUwU Jlw795/fwETPs73V6NmiwMdzwC3yNhPdbL8jdadYFPbebPXKz2eiwJUqIagS BY/9cQbSLUxkYb1p/k6nKEhvP9NWwc1CU9/fl29nE4M00zcPF0+zUKs4kcvg E4PFoiFHuRjy/r5D/PHdjWLw+LzAw2vk/T/mzplIpqoY2Fq9WF7XRN5LK+8H 3NMTgxhDFpUyzEJOkx+8doAYnNv+Zdu1BRbaYiRlneIgBn8k7hrOShBorZsF mB0VgwiROO/fGgRaunZeh/AWA7hl/AMQger7P4nsDBODq5eyyi4dIVAe5wLP 7DUxiK3b4urrR6B7mjK/U++IweTlcbF7wQTyCvMfnM0Wg+uL93tTkgnUJNbr MlEkBpkix3bmPCaQZuHW7r5KMeDd4HR1bQ6Bblk9tm+rF4Pc/lq3D8UEmh/n aPvwRQz2j3VWfa4k0IErnnvL+8n16z25qPSRQKWiTZ/yJ8RgY6Hy4dZmAkkW aJk/nxWDLl9L58ZOAoXuuV3z4JcYbJNuttrUT6DhsZ/bEjnEwf3zYYmiYQKZ hTq/ixYUh/1XInMfTxDo2aZKgxBRceCVy/k+SCcQb75s0Tk5cXgVK9HuxyKQ 7+5Iiqe6ODxN/rXD+juBmkencg7pi0NAyF7D0B8E0g6xUtkP4vBHe+HZX9K/ SSJ5mRa7xaFzITe2hfTx4usNctvsyfn5hL/NkrGzZcAj6mFxOBOVku5GxuUj veIqnmQ9Nje7FMjx0sHb7m4+Jw4jeooRBqSfwzc+2SAcLA5L+sfyUwkCjeVy 3uSNEodTgype1gwC7bLwEviXIA732reX7psiUPZwU8x8ijhwB1kWPB8l0JrL FE56hjiYfMIn9w4Q6Ixw0tXBV+Kww3D17I5u0qOvFv90vBWHyrZ9HnFtBNLb 5RLUUC0OEl4tQ/IN5PkOVf7EjeLw8HtwxJoaAv26JHe+uFMcqn/uOGtRSqCq nGmf9GlxEDqwvbwgk0Dy5nun7vwg66tr9h1JJVDUYJ5H3B9xMMxV5vdIINCe 9YGH/NdJQOvChq5D/gTKfdnX4yMhAfQPp3y7PMl+3IkOHFOUAOMShdrHzgTq CuCysTKSgJ3qH15qmxDIcJ134/YdEjAUrlPxU41A97M/7zLYKwHixpy3hch+ PvotCeSOSQD3munXWxdZaMZUXmcpRgJiVUbsk56zkHV/VC4zkZzfv0qcLZGF 8i7SVUcfSEAc5zGTmsss5J+VL9+cJwHpfRSxPXtZiE0QNj7tlgDh6J9JQVNM 5P4841bKiAT4/5G98vQzE30AbsEEBjm/QrX8lgImijvfzBXEJgnhzEsx2y4x kUiP65LNFkngxQdmiv8xkJv6tr0bdCRhj7P5wcNDDPT6ivSTLmNJ4A9YXPGu YiALpZE9h2wkYSHAR7QwlIGCzp9M8/aXhN1RkgWC8zNoYM0588haSTgpQj8R WkNHqsf237dolgSX/uacghQ6CijSneXvlgSa9k13hzN0tNZlMSVxRhIuns6U n5agI9OsYGbaeimIyRV+fsR3Gj0zjU4qOyoFjY3tftt/TKK5O57TId5SkF03 9qSiehKhactt2y9IwbS/VENxwiTqThCY+hgtBVtSheulVCcR37dbxp25UiAQ pic25TSB/AIejBArUsCd79C6N20MGeTkUxRTNoOh/OUSy69DyMrq/q/yjM3Q 7P8vbebWEDrKiKi1z90MJh6S1VJWQ+iaupNTxPvN0DHuaHc+dBD15/y9Msrc DKvSv5xbvf0bCn+1p+WxqTScFrvc3vO4GzXnjp/azJAGi1v1G4d6P6PC7vjO uDQZCHi//Z3982L8a+jhv+CnMuATbCrymqcEm07nqvi9kAGZ88/DAr3K8Jfl 1hDbQhmwEa6wlFbBeFZ8o9LGjzLgmatcmWxTizUPPfR/xJKBy0El13/mfMZZ w6825W+VBRP7pUJb+lc8O125/YmpLGzzKZ8+HNCNDeZafG7vkoXDvsfv963u wR/Y5/BFO1lwig5t3SDRi8fl9T1px2WhzhLpbTHtx3InKkvex8tC6oFYZUnD IfyQ3nywq08WXse9TpmTGMMWYh6V2sOyMFPw4uQplzE8v2tZ7vqELNSaP8WH UsewVaY8Y8d3WeBPuLF8T2QcrxwJDM3nkoOyrDFhW54J7NwpmxGvLQeV1LKq iJZJzMXxlntKXw5OcE40v+ScwgU6Vr47TOTA6arPLh3jKcx701/vl7kc6BfL pjo9ncIluxs/nnSVAzDu/zTtN41Fqi4wTKPloLuJekxpjI5rWLx2j+LlgLZt SLdcaAb7SaUVL9+Sg87cJa102gyuC/oUmvdADnzOu/+wvjGDL+htXre5QA4S zgWKaGkwsIxH4cVLb+WA90qmj9R+Bm5KtOjtKJcDu38xQvsDGVh+9lxG3Ec5 cHn4WfNWFQN/yf6ot9wvB+clog3NLJg4tMc11X5EDt5v97d18mRiVZ65v68n 5cDt6Ap7bjQTXz0uWX9iTg4WIk0LJGqZWD0pX71mUQ7CpVQDdIaZuLvG/JbU H/L5BMaJmD9MTJE569zBLQ+Hf9OjCCoL91tzYa018uB6v/Xxv70sHBNyXz5u vTzwufWUW5F+HeytY2yXkoexJ9aL90m/3rgjfuW1jjzsPLsmYhXBwlqPWS3f DeRBZIJ7wy120lc5NTK6W+Xh+4kpy2MbCbyu1rumZJc8PGXY7qkh/VrQsm3D byt5cGEzOrWP9Ou+vvUeW/fJw2M7PC5L+jVproyzxlUe6Hu9C0JIv+r+vXGA w00eqG55l3lJv3byuj83PykPuXmtke03Cey/0WApxlceFk/GJ/U9ILCILL9l 41l52CZsdVqW9Otb9cGUNQHyoF0pOfy0gMBOhoV0m2By/dRXJcfLCby0I9o4 8ao8xF3aU+9eR+AUG5f4jih5eHdqZPzRZwLTXLS+icTLQ0LCIl2E9GvvidWa B2/Jw7/lrKJG0q+Xz30NvZ8sD+uuvZSvIP0qGfqy5dt9eRDXtZScIf1aHntF RuaxPOyIORLlMEPgQ3f2n3V7Jg/4xOG9K6Rf/6Yr1zx9KQ+6Y+ZHB7//33e/ 10/myUPa4ez8v6RfUUmLu8obeVB7/8LAmfTo0PuMIp938iDDuTDznYzDWgI4 c6vkQfRDQ2MdGcv27TkwWycP+VpLXztJr9ZMSD/XaZSH0r/dwnJkPre5H4sX Wsn1Ycdr2bOkl/9+tHjbSda/lbXjNJPAT3kfpCz3ysPGzc9sz0wT2GzjGbrx kDy4vRV7/4r06riMmXHouDx081/MVya9GqUuGl9FJ8/7j7/eQDeBlQwZ/eyz 8qCcf863rY3AH3dUaexckIcacbuAVQ0E9rRJCo3+JQ8PqhOD/KoJ/OKEiYwA pwL8CN4hyJZL4N3n1p615lOA1tJ3ywoZpI9DxqpvCimArmnu7ei7BFa/E+++ UVwBapxX53OFErgp/WiRo7QCrO+NzpE/Q+BTObqcqQoKwHu71fzKMQLnvu9/ tllLAS4quZ35sZ3ANi15i0d1FYAr1vyOgDaBZ3sjLDKMFGDXRY2I49IE1p5T pyubKQCNYSbcvczCX/6wGXtbKoDL0b+ec+MsfI63My7HWgGoAR2svW0sXCQT oqF9UAG2NGZubshkYXt1u9DzhxXgU+D91JkbLLxgoNhS7K4AFh9eztgEsLC+ zeczND8FSBRN6hvZycKlIVJFO/4j569YPId6mTi5es1utRgF8PYePBOEmfgC 59/B9dcVIF1DwFX4Kfn+Xh/gH0lWgOa2910nfJg460Gae1i2AhT5Da9LmmPg qKGE5ZOvFeDLz2nRji8M7KEQlmBTpAD9ntUiAQXk51HO0XebKxUgWVnaYOo0 A997J7uhok0BSpbmQ6NHZ7D/v3UvnnYpQEjLp1Sicgbb72BH8X0K8O81uopT ZvDaxhFvl3EF4MsKd0jZO4NjejNqlpfI/OzdJy1y6ThwWfGcvowi2D79EGZk P40PbBXh2ayoCEwnydoLStNY9yrXI05VRXgRpzcnvzSFZ3kmP3VQFeHqhcX4 4ZQp7CmaJXt+lyJsdtgzO9c1iZ0MVNte+ylCZwvDaofhBDa4qElRqVAEmsFj noVHIzho8Anb5RpFIJYnFb1dR3C55aa2po+KUK7qIu0uNoJhM9u5M1/I/BYO ZpO3hrHFx7bCt5OK0EX/fe9kyBB2ErtoYL5eCTqvTJSlX+nHQRXvtrmfVAIP 6v7x9L9fcDmn5d6H65ThX9ChIKWIJGSS1eOWJKIMh1LrH8ZsfoTe7fYOjJMg Yx+9J2L9GagsIS7jkqIyELbFsiYXXqG3Ys3LDkbKMOHz+undvSWoQGP/M8Fj yjD3qiL8XnYdynI49O9KnjJk3TcVLpXpQFuWmMIBxcpwOnbBeDm/Az1PDVX1 K1OGbo/OR+WmnejZYJqDa60yTH0orcVuXSjDa+SlYbcyfPJ7e9DlQTd6FHLS 6fs/ZSh7t09E5Ec/Sso8m+9mswVEpjYqJMePoEC/qFW19lsgiMPHMaplBLkY 3LdTdN4CfP0zOfPrRpHcp9rvkx5boCZ5tdzOO6Moj7FJ51TQFnhz5M7P6Dtj qIlaWRCQuQXmSmRkjS9PoLyVL+w92Vvg3VdPAbviCXS7bnIfLW8LhEy1djWx JpCz47ofK2VbQFp/JmP2yCSaCvKghrduASl/tnO1tCnEUcNXFP97C0Tc7q+J bptGU9ekOVhsKmBgpr7OYxUdNe7XtbfhUgENASo9kUJHieOH5tetUwEnXSnh sXg6kuHN172rpALqIQLbDLfOII4vdRFLairwZMjxTfzJGTSZ2ttxUFsFFldP T6jdmkG56hwXJU1UoGFwecR8ZAaZ2DoWP7ZTAUOpJ35fLzOQjJgv52pHFSit c33tlc5Aq0fCHDxcVcB0Kxc31DJQw/nsBaWTKnC8fYz9DS8TOd39o5cTrAJ2 KRluhXFMZHJ0fdSacBWIktt6Zl82E0mrKHf5RavAuI6ZOKWeiSbKbP21E1VA jPds39NVLHRhIOPNm+cqMDRdqOnhw0JWEYtzf3NU4MPh6w8C/mMhRdU9WrsK VOBT+HvfplQW6ro49/xrObkeu8enDT+yUK6E+Zh0jQp4xtR/su5noajqFBnP jyrwWcq08+ksCxms2Z6y1KYCU3W/LwluIv1RmNQJX1Xg7tuPB2VVCDTlNLUu tl8FNugtBJyjkR56mnBNbFIFHns9VGomfXJm9+iHYwwVSLqqLNntRSDLWf3V 2d/J8zisKi4dSHrJeOAybUUFQhJk5N0TSW8Na5eEr1KFqlOa+UceEehldOR8 A5cqnG8e3XvvBYEiNHooGwRU4cn5TbUCRQRybVc/5bJOFdT/2o2UVxBI91LY iwwRVchzagzK+kAgAemO8RkJVThp4+neQnp4rFZZTldWFcodSi5qdxGowvvy 4WAlVbge9ONGM+nh5LUtqbVqqpATt5TwbIRAfm/kvgpoq4Kr155DpZMEMnf1 3+CgrwoHrm0Y5CJ9uZm9weahsSow88RXJZD+/PlcKn4cVOFRW2OBHenTlr1n 6zXMVSFTTWfSmvRr1o9aDv89qlB6eykpivRtWIro9kpbVbD77vlmiYydkG8I 1wFVCGX5WGaSsfY4LrV2UYWk3hibeHI8X9yGn8lHyfXj8c+vyPwjlJM6g8dV ISt712feWQKVdZX5KfuoQpjSBud0sr7EYMGXp8+owp5pq4izpH+95dwm315U hXVFqUdCSP/uqC+WZ7usCmc9zFbXfiOQpB/vUYswVfhmoHdt51cCzW849OBm pCosoj/r2VsJ1FSa1919TRViuNvx8kcCPT3CsVH2pio8PXnnjTomUDCnk53X HVWQiP8sc7+YQA4vX17PT1WFh0r5ajtfEohrcR+XaaYq9N2ppFslEWjgwTPT a9mqMFlcz/8ymkBvTX+FfnlN5g83e74ziECeNx4vupWpwl5XE1vtQwQC3QXq S6wKl9u8p8L3Ekis1+LMj1pVCHjpv3b9VgI1KM5O/deiCtpXeG3oYgR60rhD salDFeSs/xPU5SbQ5bN3jwn3qkKLbv3r8h8spF6xrffpmCpsob/fEN/AQtft rzfWLasCbZVimuZpFnqi88eq8C95PoHv2rc4sVDJ2lPN6avVQGNof38IsNBY k1Xb5TVqwPXuBTtNiIVoOwW+asuqwf6asFCuTCaylQ92klZSg+s3C0RHY5jo xCpGj4CaGtww/sqz2ZeJblU09k/qqgGHF30ij8JEU3pxIw8t1KDr6R/NgwUM 9HfDb/e4vWpw62Phov4tBhKe8x4P3KcGqRazRwNOMxDK3T2131UNjP39AuRU GShZiY/Fe0YNvsZLSVHvzaAdm2KXL95VgwOBRec7HOnIaWEpyP2BGliHBT1X 1aAjv3bPFdvHarB7xjyaRX5epiZY/FN7qQZD/ocjal5Mo1luHs6RSjVowD0f C+am0KOlqLXWE2pgYWdzIch7Ei33RCgr6anDs1sihdeXRtG5gcDREJo6zAvc nvQuGUWMEd+0TqQOq25fOVATMIqGZuw3Re5Wh3s75Q0m5kdQ/R8F7rEj6nCa 54+V1vQwSpatm3h8TR2+1xg9v+I/iKhenM+khtThP/8o2mqFLnRqKVJhY5wG bKqOPT5xKA0p6CUrrr+pAT/zIvwUS+6g/rPPlITuaEDARPyXCvkYtHvmwxbe NA0oNZps3MkMxkoD3Bp/CjQgUeXM3NDUMzzwPlZvvFcD5Fx/FdbkVmLbhOvm xaqaoLARv969uQ1zNz3cVaClCWcv5kUmFrThSp5ci9e6moAkBlz8zL9g9fDm 3S+2acLwD6pmh2875r0oZPNwnybM0Mwclwo7cY3zLcfIIE14qCrdmbelF+sq 3fF0aNCE269oUa93D+MhNOZg1KIJj5e+z2XEDuP4g9QdUh2aEOtR2ketH8Zj 8W1S49804YH76ISM2QhO+rGm/cJ3TQgwC1jiNxjF81VRW5NEtUD+/KzCOp5x nN7bqRoopQV7PUc5lWEcW80riLrKaUHMl50ztQHj+Kny+zl5dS3QP2HqlDQ+ ju1v/HteiLTgJHE/1v3dBC5yCVzffkILgg44tvdbT+GjFz/+e+OjBf+MebwX QqewQIIIM/WMFkx1PxiKzJ3CHjVFH92CtEAu63svn8A0Flb5Hjx3XQtmS7ZU xVdN4ypT8O5K1IJBrnW/9jCmsa9rgmPZXS049vWxefAmOq5N0NAJf6wFjWo/ Z9V96fjCT6/JdcVasGO3n16p4AyWWVvasVCqBRNHZe7N6M3gJhWemp5KLXA8 ZCgS6zqDFQ49e/C4XgvcGTHP2bNmcMf7ETvtfi0Qld704psBA6fWaxzOWkUB geBn7Nk0Jn7iuemcDQcFWivvGFY6M3E2z6qon1wUQN+7f24KYuIyi45XZgIU sLrAuJXyhol764P+DIlQwKsorKNWiYVHPD3WxYhR4BPHmep5YGE6j7WiliQF 2ur9co87s/AvC9m9IbIUiF/zIZEnjoUlPn18IKZOAWeQzd05ysIKXvl5VZoU GDJVzjqzyMLqvPdrT2pTwEdkaXMPH4FNLP0YxfoUODyWI3BMi/TTtCPbISMK 6G9T+3IFCGwVu12Yw4QCe8rT83ttCez6Sdhk33YKPLQ3iNpxmsAeXn9tlndQ oORAx5RtCIF9eafc080poMR2EFKuEfjCi7aAXZYUyGfy75UkPRRs+S6OtYcC 88t/vvQ8IXDE9NO0O9YU2KXEndr2isDxsTcKTewoMJz7/tTqEtLXKoEfR/dT oGvPLanTpL8efDrWd+0ABU6nxQcLkz576rWH0D5IAb32G8d+kH7L4dVb3eNC ATUPtef8PQQuerF5U9hhCmyTzlU7RPqv3JJHTfkYBcKsxdomSR/WTn/f1uxO gV+bFEJekn5siu3bd/EEBc4LGollkb7sUKk7IelF1jN/IfEb6c/+T7lB730o 0FKU2bOH9OmY170b3n4U0I2xHJ0j/crgDX+y7iwFmAduPP9C+nb+hc+bkvNk PRZ2cjNkvGLp0HDEnwI90Zv3m5AxB33bANclCpiC9tYPZD6Ba1vmXl0mz/vj +ckY0tfCquu5HEIp8JY9zDWC9LdUw2+xlTAKcC6nZZfQSb96j2tk/EeB2bTm UUXS75p8Ldt3R1Ggo6tEqmmIwPrZJQ7fY8jzvVt59mUvgbftfuJ1L44C5k7z K+/bCWxOjwtBNyhw4InC0MYmAltfu3hr4iYF+L+2ocfvCXxA9Ujm9dsUMNli aHaijMCHGyxKdZMpwFNlI3Y8j8AnvHU+992jgItoC+thJoH9+CSHw+9TQPWq xtLaVAKH7iZ42tLJ98HRKPpZGOlverdkYAYFjtUVRH06R+Ab12oo0s8oUH3t xStlDwI/arjjdOolBSA9LCHZjMB1UWuEJl9R4JLG7YQWXXJ/TSPrjuZRoHuN v/JhBQIbvbugY19Mjhc0MwhZReCjAYypz28psCGzz1SQYOEoqkfarjIKeMc+ WfOzj4U7Xu4XMMYUsLZp3dJYSL4/Jxtriqop8OhslULpIxaWVdhxSbOW7A/+ Zf1/MSzs90BnQvYTBUTfpInccWFh3uvrqnjaKaClWV0yt0T61jLWP7yTApF1 LbtyBpj4AOcqjZWvFKC/nNKofs/ET0NmU4h+cr+nv/T+jWPibX4t57smyH45 8Nr7qzDpZZvryk9/UeCc8/ubF3kY+D4/54DUH3K/3+T9kBubwTUfg5Pu/iP7 6YzubV08g4XAd1Uchzbo79ipF31+BmdT9vSdFdQG43Txq3866HhoHW8CktOG IxssjnRensbczWE7SxW0YfQW14KU9TTWvLb0W0eZjM86CXyVnsaX2ac8ldS1 YeDe+T2PqqewyI8Ppmv0tWHZIvxp6t9JvKcj4mevpTbonSsylD8ygZ9mbGuI tdKGhBPxHPYKE3jl3NJDQxtt8Jv7PcOaGse563x3JttrQ8qab8WeZ8bxepv9 SXZHtIH23/RgUuAY7v4kq1N/QRsWmtxfK5wewR648lRxmjbsvTIkdXVVPw7O XhpLWNCGVeyHT2wMr8I2U22aOktkviSZQr2QSiyn9DKw45c2BPdHNJ1eeIc/ PT4kIMamA/4HpmrfjL7BIik11Cd8OlDWX6w/c+4FzouODy+S1oEfs/xxKg8e oVEPGZkeSx1wN3q85pdgPXrzZNnrspUORCf4i2VZf0LXhr4UStnoQIPjyR0v rjcgimvkLjd7HZjzTNb7j/czCt5P95s5rANa3htvdf5uRSKmRRV/zuvA/eQB /d3tnWi3tIWL3CNy/Lzr1yf8g8jk0utdd9N1YPjRtX1uCYNIs11EVyBDB4zw rzV6vENoffS4wM/nOhDAHfdCPm4I9bDCKz/l64Dnx3rni9eGkWdlhezZOh0I V+K0r7w4ipxFFQUnPurAwukN5VvzR5HVufhfzg06cFRNSMmKMYooSi7tZi06 oO6/T3ndsTG0eH0pQrRHBxat5V6L7xxHUYeoU5ihA4eOZp3V+DmBAt+mdugS OqCZEnZ3veok8l7HXv3iuw5YnEiYuHBoElnXtabc/qkDX2bM2V/VTKKNGn57 TrJRIedH8r+WqCn0dCUrV1CYCrk7YsbWL0yj5ANr7/8nQoVn/nZszjJ0FJMX EL0kSoVrzUnfhPbQkY+H+dERKSrcV39aVvuIjnSaRte9UabClDp7y1Y0g6rv b754yJgKdgT/YLM7A43x1Idyb6PCHc/vP67EMBCP/9mYfKCCsFu43qUcBrK1 rb3PaU6F85bbbbfPMdAQh3fNK1sqvDWTOyB8kYk4zm1octxPheFZPvkft5lo y2B556oDVBCQqsgXLmCiM6VC0w4uVEj8rpsvxWAiNr9iob/HqWDdl+Zn4MhC Cn2HxbI8qfDzFv2Y5BkWsrDgkd/nQwXH61MVKIaFbsq56D87Q+aL9viC3rBQ UQIH2J6nAlfQ7mcSTSzUvfLK8tdFKmx/+kJMd5iFpL+yHbK+TIV/0bKmYrwE MjXLPrEUQgWLR+M64xIEOpG//8yTMCp4RZyhMTQIlBv37L+fkVTgfDZKybYh vbpkcz09hgoVvVsuHz1C+u/4cvLuOCo8rJhItPUj0Dawyn50kwpiBv8JfIsl kNurhUKL2+R+HSamApMJFCWeVjF3hwq3gqei9z4hUHa0xccH96ggEuKU5/yK QM3z31vN71OhK+mvevpbAs0du987+5AKA+d8m6SqCSTSYjaWmk4F+Uerj7V/ IhDNhMU0y6CCw+ofVVVtBDr84u4iK5MKfIW6H8a7CRQusn1VShZ5Pm1x1qaD BHr2H51vx0sqaJWEG3eNkX6avS3MfEWFvt1e5x5PE4h1aOvmu3lUWAnd35/B JND6xgnl7YVUmNgkeoL8+4v0DW9qzxRTgf2uDZv1DwI5ZxoZ3ymhwruj+9MW SK+GrB81Q++oECOy1biD9Gz6lXjr6QoqmChNtEyTcS1Dz+l2Ffn8jUlXfTKe Ojh4bOt7cv97U8ZLyXwCH2N8JuvI87LeePbCdwJRdHUu3qqnwkFbHb4TLALZ P+4LNW6kkl67hm/QCRQoGBkz/pkKQgIBGaxxAj24rJmY0Eru/0uRpsghAlVN fb1v1E6FqCHL/fa9BHn7vpo52kkF79E3B5zbCcTzXvX19W4q6FU1LN5tJJA6 paPEoI8Kv9Teuax5TyDbhyE1w9+ooHkt5mVZKYEu8Ck3xQ1R4b08m3D6awKV j10aHBynwpNdOgsbUgj091R+nOsUFa5zfRsNvk6g7YtTBj10KnwSOORseJVA H3idbn4hyPWWPst7foKc/3aCic0cFejWuWyuTgTaI/lxqnGeCp+5BErdLQnU qqm/vW6ZCrH2be5+KuR5lJxibl+hQv9aysBZUdLb2zNTKv9SYZmrp/UTF4F6 9wvPvV2tC52ybLaBZL+PB849yV6jC3UKB99032ChLeyqNsprdSHJ8sNATCAL eccd+52xXheCNEspN4+x0OzD1v0PN+nCw8qzY5naLPSrJpfjpqwunNHYYLr8 iYlMrCbyBBR0YUh50NEvl4mudEodilXShRmzKaFtieT7PhVfHK6mC6hy5Ajh yESCa3xOXNTTheevHnJl9ZGfF8lP1s8Z6EKhE/GI7R0D3ZburfSj6cIbc13Z khQGEtWx3OSJdGGL/G1zcwcGknNUrne21AW8jT16tnYGGTweVYFDuuAoGJq/ IZqOglQlusqP6AKIF9954UpH5YX7wo3cdMH1nnPoC206Mv1Q3atzUhd+LG15 RO+ZRlYzaXGKZ3Xhq9G9rFj5aXRUz5XJF6kLwQbi21Y/mERSGoVCl6N1IUQ8 t+OZ1yTqVeDTmYnVhQWFY071+pPIXrjEv/GGLmwn/NfFtkwgix8b2OLv6ULs w31+Ur/HESW/cf2aHF2Ybi+fCDEeQ2waxoZC7bqQ1eCxoOo1hCoUEp2vdJLz baqWydsyhIIkp4OJr7pAG7JLzG8ZRPP8d6tb+nXBtzhQWbdhAE3R53bfnNAF r/St4dxv+1FrVvahdb90QVece9HnXDd6rCD+3wZZPbDo5mcV8rWgm1qFNSXy esBvH3GQ+/NnFEazYj+spAetYi+Kr99oQodtQ69mqelBvK+WuoNQAxIPHrmy VV8P3L30jSt56lBie3bwyT16oJTqtmVtXTGKCDf2f3dRD2YfvKeYyhbi89c7 io8G6kGm3C0Zndxi7Hbv1ALnZfL5NXs04mklGHLTLtiG6cFaM/49hnYVeKVn 9fnxa3rg9lOZc0fZe3xRu+m0ULoe1FPuK4xUf8Ynhly93Bv0oPT+tFTs7W58 gTtiT1+THnRG7sqvku7B4ZovNfa36MEvrYe73V/24IfBy99NO/Rg4PvBtd+q enGHaHKQ3IAeNAuH3LEa68emdi1xw9/1YHms4fLWyCFsG/jz1MF5PZCNPp75 u24IH06Tsm37qQeU56Z3HLmG8SWmj3D1bz3I090Io5HDOC+W52E6pz55n31T IR82gqVqtuceEdOHaNe4PvmjY1h12vPmVwl9MB1VoUinjmHDtTfP2WzWh5xX k5kZ7WPY/vCAPpLXB76LQtt37BzH134F4c0aZPyaX7BCbgIv6RS1fgN9+Pz4 uF5m3STmcu4rcNihD5VCO2tyFiex8FX2O5936kNyjaO+usoU1mqxPVixWx+u FWWwJVybwid8mMMP7PWhsKtbvMF8GndkKP1w8dSHIpp/q91TOhYeSJjj8dEH L0e5Xz2tdGwvuvy9+JQ+/BYXZC9YoeP2+MZZofP6cP74oZm9+2bwl4tnWO9D 9IF+c2BYYmEGr8/rYZ4J0weB+b2pvJIMvI9uypT6Tx/eOq0ogykDtx3eyAiI 0Yej/wUkR8QzcOuusmm12/ow4LcS6SDKxGvD5ae77+hDRjftxgUjJrYtj5+K vKcPEf+WorsOMnEL5cjk4EN9eK/XW3D0HhM3i3GM387Sh71HzBKCBVhY0P7U GLzUh/u1ka8eK7Ow9Y2uUeYrfTh2f/08hykLN7O/GNlVqA84ljHx3wUW/jyz d+h3hT6wTvTXO7SysIDS28GsKn0QFBo+c3icha2Oygw6vNcHi8Ar0Y+XWbip Y+7b63p9kDLlONcpTXpPyPWba6M+fNBojKnTJr1tWdfP26wPq+mjt1mmpEcr 7va5t+vDz3ouI7ob+fwSW9/aLn24OcylX36WfF7Hu7eim1xPuwmz7grpZ9/2 Hu8+fQjbzCfOfZ3Ajc9MejYN6MO7SHz5SgqB+YYzu2uH9IGrKKVTk/Tabgmh 7rOj+tDJU8kSJj3XkDDc1TilDxTz+RsRpP/4GnZ3Bc7og8eOmrdrSB/u5ijq VGTpg+WlvaNNpB+vbZPq/DKrD00HpRjVpC8/BUZ1XPmhDxzNiXkM0p88hUS7 +k99GHeZWL+X9KkF06m9Z0kf9MKUlkdIv8Yo13yJ+q0PZ7fq780lfVt/TO0L 9a8+iAw1ruSS/uV5kNQ2xGYAn5ZOL4+RPrbo+tN6fbUB1MQHG9qSfo5Ze7KV xmUAWcGShbNk/HF3a8skjwHslNtz4gMZc0UatSTxGwCnYse+NtLn5vhJ83ZB A/CK3B+yjswXtczfzFprABcG9VhRpO8/UC9+vr/BADpGS/K1Sf8rXPM9LSFi AMPZ23gOTxP4vyH3dfdFDeAHm2ltzxiBR/RdCsUlDKDpcfXS00ECw/V9DqlS BhDH++wd7iE9O2q5KCZjAFoRNYqq5H79MdqekiJnACpHu/aNNRLY9aahsZii AQTtuHGMRe532YTWt3vKBrApI/K8xTsCi25VviKqagD9Lhav5vIJHHB7s+w9 dQMY9bXXZz4nsC6sOX5X2wD2XeUabb9F4MRkDu5NugaQFHbBoyqSwLOM31nJ +gbwSL5q9k8ggV+l0Bl3jA2A3WIP16lDZD/NDt/YuM0A9t805EyzJrC3eQ/l DhhArIXHLzlEYKUfHy8k7TQAz7I1HbKbCRxhiUWELQxgz8dz5g8FCDya9qbk 9m4DEFqiN/j8YuF0q8yVRBsDeEhP37W6g4X/PnnwaP0+AwjfenSiCbPwoeXb kGhvAC23Tcbo2Sws/iw84tZBA0hte+SreIWFk/4dEbjpbgCv/Tl806RZeM7B MVfohAF07/r2QoSLhe1yrG0TPA3gZtR8wPgMEwse3Jp045QBWBoFpMYVM3FM gbjk9QAD+C1/Ipp7OxNP8KyvFAgyAMSjjS3kmHjnEd6j8cEGcO4wf8w4OxOz CyxlxF01AP3IQgHdGga+fLxT7VqcAYwFXj+sZ8TAve+aPvPeMIAlDpEI940M bLi+9nTsTQPQSObfMDc7g+crCwpj7pD7+3yTBPXZDPYTvWkcnWYATgciDzrx zmC3xt17IgoNYDN7pdfXgmlsfPOY+2KxAXAl0w9bRk1jYYfAy94l5H7zutdp HJzGHwYyX9pWkP38qs3M7s8UVpljE5D6SJ7ntIKbBJrCs6Jvm4p7yX65dXwm 9sUEDj0hbz25yhDOjQj++y4zih3VaCecOQyhJOyCZdLYCKbM2oZ+5jKEho8v LjQ8H8Ejl0JzC/kNIczE4PKi+gjeeb1HMGyjIXjbMpwDdYaxQFFCi6iKIZR3 7LEJOzCAU1et2O62NQQvjZcKee86cWaPfdTcPkM4n9/CpynbifPyX71LdTAE OZ2UjeJRHfjDsSNKM86GIFQn/dfKuh3PVdf8jjtuCB8ETDYldrdiy/DYZ5+D DKHAIZYrKe8jXmLftGKbaQi0Te8bctVT8eq+09rLzw2hVqA9K7IhAQsW1p94 nG0IG+r2V6Rd9McK7kFt318bgrzxst3i2HVk+/7bs8QyQ6h5OvnmJmcOev7f U7uOFkN4WZHRvcWkGh3g0Hnu+MsQNK+Gr5PN+ILClkSvfFkxhKDeBXE/vXb0 gvHvwN5/hmBZesNn18d2tNLxmWsHhxH8KC/1uzXdgTIyvU5oChqByqmPHxS3 fEWz5o8VOeWM4HeZl9XFa30oNnbt0wJLI8jZY8m5ODGMCkIWL2tYGUH4UdEH zYojqP/swP4sayMIzPS5YOwxgijOOasf7TcCff5NyS2DI6hL1cI99pARqL/8 s7aibRTJNV2RO3rWCHqP/y67nTaOrKpO/Oo9bwR+rsqvlL6Oo4tFe784+BvB q1U+MsaCE6j+gUT4nstkffdahceCJtDpU2+H9SON4HqP1cdN1pOoXJBIX5Ni BJxvbbM2900hURHR5Ir7RmD+4oiZgeA0Oi+1Pe7UIyMYfKujmwXTSFX99sXP GUZQwK8SeyNjGqVYGuy+nmsEQewHzlofo6N526Noa74RrJtkfedLoCNbp1hd ZqER9AmmGW0qpyOek32b95YagV3Yfl0J4RnkH3Hlh0CtEVxycA19824GfYnL mir/QOY/yFnRNTqDNG63ffP9ZAQSXwx8ED/p/cfy9U3NRvBtzbHaCUcG2o8/ PojvMYLy9Ue0A6YYKPfD7C2TfiPIpDMSa/mYiK9ZLJoxYETeDzMN7dWZqKbf 56zVmBEIh5bfMjjFRJRfQuYChBF0/ty7dWWcieJXGRmXfzeCgT5Nd0t2Fprk caP4zhvB1xuW79ulWOjRpiLxpmUj+Hk4m+3RPtIfm78JBa8YwZGHSy39Pix0 QImLU/2fEewajKw4EMFCa/SciDgOGuxc48v1q4CFPE2ujhlz04BbYfCi3CcW qt2R3TPDS4NEhXdqEQMsFLxv5f0eIRoINy9VfSe91H1QsfT3Ohoc5B/qXBEj EPWYde5LYRroNmo/QOoEop9Ov8cvTgNPkWOd3tYEMg/4dP2dJA2GZpIf7TtM oCehc+E+0jRAboN1Z06R/ouUCJSQo8FN9ii2ussEOnjd7FSjAg0ut/dx28QS qCjplNtlZRpcy6WmCCYTaO2DZEc1VRpUVw9cXP2EQPXZU9vjtGiwheaoGk/6 X6FgnYGxDg3ESx7fkyb9f6WUpj6jS4N2JvXKJOn/3ip32fsGNLhbsKVwlPS/ fn28yB4aDX4rxKwR7iFQYksx/28TGnz7b6dPIOl/VtcA20tEg30mW1+tJb28 e4D7p7MpDZbVqSX//3/jzHHKDN9OGoRIt13oJ/0f7HLpQO4uGqRumCpiJz2+ r6262m43DXqXzCfcSa9v2cWnsWBFgyOrP/35R/r/b/m+e/dsaHB9ZOxHF+n7 Dp37q0320SDZMad2ioyzs0b9Bu1p4Pu38bTe/78P36zeG+5IAz3LuKVyMt+B pAs7lZxpYJzbdPwKOZ86X0XeJ1ca0HgEa4JJ/7OHcUqeOkIDARUviWLS/90L e6PXutHA9lHSf1smCJTrkzxX6EED/qwxoa+k/yOGBw45niTrP2rVU0X639lR +dMvL3L/Nh5ZGSf9T/l8WveRLw1qvtilmDcRiGtHSdr20zRwFvvTPkL6v7+E jX/8LA0aGwfay8oIVKBp6R9zgQZnzSRrm/MIFPP01rBaAA1+3o9o3/yMQIfF e61aLtEgTfK27stUAunelCs5F0yex/BZqQs3CMTH5SMvcoUGG56ufLx0lUBv v/9edo0gf78o6GpynEA3TpodZ4umQWzgcOOyA4E8vsW3ZsTSQD52hXdhJ9kv n6Se02/Q4D+PQaVn8gTyTEf2gSk0mLlsSFnpZKFtIjFY4gE5f9aqnflVLCQc 36qKH9HAqjv357NsFqoKOLaK6ykNtjloDDsEs5CYzX+5t3PJ8SVNV5tFSP/X NooZ5NPgz0DRuju/megDTTiyt5AGJzYKcaUPMtE5pUwX2VIa0H/27YnMZKKG Px94Xr+ngQc3Dn24hYnSzwtd2PeBBkYZyxZ3uZnIf9pxcKGeBk5809t7x0nP d04VmzTTIGxg/YVt6QwUlMPn3tBNno+nf9FtAQZSc7GuGGfSoPNeysPNtXQk w1RodJkl+9P+8zTbfToSvvK7u22OfF8Nj2vZnKWjv0+y5isWaeCz0lKqI0lH bXR29eRVxrC20WKtus80Cgh6m2q+0RhWt6vqZrIm0fsUmcDnJsZw9Uw9+/7E MVSithgphYyBKYFmzjmNoZyKz7dvbzcG6203V6Q2j6Hk4aDXV8yNody95YR4 1ijyUumccLQ1hvxMnvzmNyNIqDTWgcfDGJbRi2zTqiHk0j2n4xVnDFo+VRs7 xXpQeAj/YeEbxrBtZd8vzfBulCWnEItvGsOC7/y3gemv6Kevw+DGZGPYOrM6 3/ZtF0pcVRJXk24M1Hqbg6zdHaheNWRM4o0xxPnKm3vmNyPdEO7k5iFjsPzv nKdUQRESlJNcpuqbQFF/UOvz9GZsP1rzId/QBObrZd/aN7bglKdeSVrGJpAS bfQtLagVKyi/1VIDE3icbrXGOaMN09T3nZDbbQLFYZf+vSDa8XH9mPa1h02g 0ag2p/xMNy7fPf+KGWkCJ49z9I2HDpH3tfuXfWJMoLSq4oxF1RDe9Xm75fQ1 E/hU7rVh16ph/MUmYWwswQSanhc1rw8fxlP2qhL9KSYgO9T7tzx0BAsfORrT 8MoEvI2kj2q6j2Gf801uzzvJ+resaH9umcSqGYnPRLtNIIo7WUl31RSmf3Gi x/aagMg3geyNOlPYW2f8rO+gCSjmbHxplkjG3/+EaU+bwOIz6lkjq2nsfVor 7d2KCdg1bv2BM+lYNW1hRP2fCTyRjB852UzH9OZ3So9WbYU2giYZ8pOOvTUt csO4tkJ68/8qtvdwqLM/DuDs4LeKViJTadqn3Ya0rX55hHK+34/Boq0f5S7J /da2ViWN1YhVllJMFgmVhJpSbq1yOe6/yjRUUqSp2WXc5lIbshnas3+e53k/ 3/Oc8/18nnNefxxptsxhEkfJA5sc9RBUHAqzEA5O4sj9/Jc9XyGAzqAdC+My bHrBZ40dG8HTWajZoC3HYw9ZIdWmCHrRwfBGEzmONBNM5GxE0DZ7+pJmiBxH jLf/7WuFQMR1yF3/RI7ZKzJQtw0Cw9xLiSEycj92dku2tUWQdf79S5WmAodX DH2+xg7BmnGFxw4rMo6YNhrejsAl84i6O1+B2XkNezx3Iojre7H/WLkCS7uS L3a5IrDBfls1GkmevcTkmgeC2rOht9f9SfJefdErvRHc+ia4Dk+T/ImCylO+ CDIrQwdq/6PE4SPsLT8GIBAsPuFzaz3xhqGc+zoQQQf3pkmtjRJLHWqa3EIQ rPKcmNd3IflS2tEiEoHxJr+uV2Ek36eZXhqNwF/2hONyiOQZQqHhAQSDRdJB 3eNKHBbi4zEbi2B0qjjrcp4Se5UF1hUfRvCxklnofoV4cjxyuWM8gthzqf+D SiWpx9j4SS6Cs+q9hyLqlfibGO6L7EQEFp1XX95vVWJWdbKNdRKCYxn7fUMf KrHedHqBOBnB3SS6w+aJEn9mzZ9LTUUQzJ6ZcSb+m0oo8N+QRuZzZ/ZmEx9K m0qaHqcjSAqR/NdgRIlfqAlYR08j0M9Hn/USXz60r0linUWwt+q+WSfxZ+PJ hjcd2Qg8qoX574lPKx+02+3PQVA0CGgP8eslHWHJ0jwEK57e11ER3/Jd+xj1 5xHU69Z+evbve2D+UGhAIQJ13/ml42R85Nlwp8ZFBJzy7fbk/MORTDlbcBlB trY89x75nt+e6bRdpQjqxG+WcYm/dxTPj30oI+uzFHX8RHxOSTS3F19DYBKq XX+Z+H3T10sEDjcQNPSc+7SY+H5txHKdyUoE7EnjqlvE/wbXWQeyq8j/DWNI Tw8Sj8vZIqtast5Mr4YrxMOz5ubm4jsIeJLnu6aIhycOWmWl3kVQNqh6xCMe Hqqj35k1Irjy6q23/T0lFs067X7cjOB5cN4qzm0lbtnmVhPfioD5/Rnnn68q cWlrYFxHF4J8g/xbRZlKnKsR1R/9gPSDfcmeNFIPvzrFWi0Vkv33eedx46AS //Ao+e+9jxEw2vttr3kocYBehp9GH+kXI0FDsoMSu7nzG673I+g87lSRa0G8 PVBy7MNLBCWbjxrGf0Hqz1ggLhIjWK2m4WivUmDmvhraQYIgbZsr7BxTYNVw u3q2FEFB9fha42YFbn87fMLsHQKzB5zNVYEKXGshl/a+R4BFAireSYHLjkw7 xc8gKJwMPsvbqMAZKs1FHXNkvyY5Wu4f5Hj35yZn9mpRcEd/IHptihw7fG+u ZGhTEKdKLVYn/b7ljJXb9cUU2EVW8Nn2crzSwFn/gx4FIXVNLg7qcvzHmqjc rFUUpCcWYclhGf6L9+m8NouCYtkvObzdMswQ/1aU8iUF87krNHnmMvx1YVvp 4XUUXI3r3lo+OokjmMY1PuYUSOK/ourcJrFMr6fnS3sKtupN/+WvNYFVMWFP zztSwKmzrIwbHMe6PXP9+s4UJKxfyFHdHMffZpqKNXZSsGCry/FxH8ex2imy MS8KVk8FRe3LG8Mz6pbaVdEUlHowPyVojmKtoG4dswMUdC4Yl/7RK8VGLUF6 V2IoEPlvSPn/BSm25p0x+u0wBcOSAVPdTVL888fRdVweBYGh5SVlu0ew2vsC jh2fghUnl71Zmvwn1h5WS3x8l4I8UXfO9PLX+NK3p1g5jRSwFQFupilibM01 bPXCFHhs3JiSIHuFI5eYaQ11UHBBZdac2TyE71u7Z0l7KKg28m4b9hnEJzOv ls6NUMDPN2KtjH6GGVbbH63Tp2Hora2ewLYLFyT3xYwZ0LD+pre/jqwDbxYG 6AuMaLjruSypt6AdBwcd8t60moZwsaS6YqYFt50qlGw1pSGy7p6V/67f8fE3 imlXioYnlf2jkhdJmLmBm69vR4PxztFHnJYw+nYcY9szexp2+a4MjxJm0K8X MY/7udCwyGVkVVrgZZqytFsU5kFDFc1LX/CtofuTum+YeNMg9E2ytGDcoX98 6Ok64UuDv/5RyzZBPV28LzonZh8NZrKfPC9+bKK3XJ/asjmYBqO256JgtxZa NMUbmAqlIYdifjdX0kqH09qJv0fQEGdYbvLFdBs9n36OlRBNwwO15qyc7zro fwD9MPMq "]]}}, 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, Automatic}, {Automatic, Automatic}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImageSize->400, Method->{"DefaultBoundaryStyle" -> Automatic, "ScalingFunctions" -> None}, PlotRange-> NCache[{{0, 10 Pi}, {-0.9999979768439893, 0.9999999999992779}}, {{ 0, 31.41592653589793}, {-0.9999979768439893, 0.9999999999992779}}], PlotRangeClipping->True, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}], ",", GraphicsBox[{{}, {}, {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[1.6], Opacity[ 1.], LineBox[CompressedData[" 1:eJwUm3c81d8fxy+VEJkRWcnKJvviHJSsRCElsrOTzGvd7Oy9rrhWSRQlWTlW GsiIvlqSECkZZUX9zu8vj+fj9XqP8z7nfD7384fDjlfOuNASCITA3QTC///2 +KR0Xoyu1CYwziAHZgswxjz630prNCAYGdGe2G8BWhJ5h5+1ZgFCcgZBnc0C JO43VsktuAkIinmxElwWQObFk1MPWssBoUjFipXfAnDusyIXVFcBQruX209R C7BtsviAXFALCD0xwh3yFsDvZPfKseP1gHBP/mOYlgVwdWNJvt36EOdvOC1r YgEu3LARPXSsEcdnh4xftACm1bfbU6ubAEH+z2DIFQug27d6jla4FRAKo4j7 YiyAynewHFDwBBAkOg+QCy1ADp3+U3/6DkBwpua/fGABWLi/Z8ge7wSElkMS P/stwC41Namy1m5AuJWU/57OEoQZTKzbrPcAwmgQA1XMEqxZx/QcONYLCA/o ilUNLMG3kCHbG9XPAeHNKFt5uiVwTgyU1Jt9AQj0L4DPY0swUci3vn24DxDq jnJvfLIEI61u6b4FA4BQoUQkqlgBk/79tpJjrwDBwGjqk5MVcPJ5x+lHPwQI I0EbPFlW4GME+bPU8WFAgL8pMmtWYLikn1TS+hoQ6KTi2l+dA/urBB3Czo8C wmJ6ij+9NTCq8zt5fh3zJOkRSc8a9HQc5OQ49gYQLqQ6RD2xBk2fnWvjqscB Qb9IK6vjPKAe2fnkXfARELxqko9s2ICm17nCxa1fAOGZCSXP2x4cbKfVlmeb BoTo4wL9+fYguMrnfJcr5koXnt/d9kA9XD99lm0GEIxp3/zmcQAtYms7sm6z gCAsxKDY7QB42Rx5Op9gnmWMf/3dAZD+DCid5fgKCIk3vx/mcgTEoUrPoHbM Y6N/oi87grYQy7eIcx4QXlnNmO92AnzOnb/MPTAf72FTknQCYaYyrNMI8/Y+ 7pDTTkDryJ6T9J7fsC6dN5PnBNr7GxrMOhfw+WyF24LOQOCx0NAU13dAKA+9 tB86g8jS5AV/L8x+3Q81LjkDGOgsXMD9AxDmzog9LXQGnYKc6Z+9FwHBjkG6 hM4FCDOS717rxhyTscQg6AKifi307uH5CQjrrz6fVnEBui+6d472YP7vy8cE Bxcw8jaPaYJpCRDeamrGBbgA2sFTvLdVMa+y8/kkuADH5mZl9RTMy+aLn6pd QOa9K3q0TZgDoxdPt7iArnJR874pzHtpCEHPXcBK/nu7bOZlQJDZkjQdw/2k ZnjZqmH2Gq2cnHQBZ6JPksScMHc9nFdZwP0F78T/TME8Bo5a/nIBD7wf5jQ1 YS4csSFuu4Avju7l179g5mY3nKF1BZzWgvVG+1dwP7+yjehdwfFTY+0c6iuA nKTQb8fkCvx1k/o/OGF2EuJlZ3EFFao67ypTMZ9VPenI6gpGpde/+jRjXtJ7 aYN5t3Dtb9VpzP487PTYr8TttIuGZRWQP5e2eOF8zkw8bC/VVwFBs4OShOtl 0wwKZDljPTF/3HGXK+hZi5G+mIb1Rs2f33G/vxY0NERbMDM/eS702wWIfF46 uTiN/aSXz1fwei3e3LJ8zPILEG60WLl8dgExfRedyBqYi/bnxeJ5NXSwXzV0 wXyGpd4Wz3Pm0fMI9nTMpbtSfjW7AIK3/aM9Tb8AucdL2eGuC+AV2VjY+IT1 vkN3mykuwCxT/Pwnud+A3Lvrq0iIC/AwRGkj5zBnqT6UcXUBsYRzvU8jMZvv 9eI+4wJafOKO1QxiZt7V8FjMBYyKCniUrP/G979OJpLFBfz88IiaKbgGyA46 PwzWnYGI8QxzyBXM358dX+p2Bqnix+dOsKwDWEWTX2juDKom3guoq64D8uRx vruKzqA755ql9KV1/LzRuvue3Rls7CrvYr+P/f3Sgk1DTsBxkubmJ9MNQG0M VB7XdQIqBcg8JHUTLOX2Fh7Y4wjMzM4leDVuAmp7a23NOwfgufdn+6WJTeBm 6UVqu+8AqAEC0vqyW2C6/XaNm7UDYDwTTsfxagu4+Wqa3K2wBxOMxNYa5m0A m20WLGztwEbnyHKJ8jYgSN+6x/bXFnCEeEhk2W4DskS1fEaxLTD4WpATUov5 32w616eL4EH3xhX9UzuAbOrR/++SDegnpd9SD9gBBKlyfUeCDfiqIPFR+ibW T7xo+Uy9APio54w4fmCeP+fpOnUeqJz7SaY78BcQ8thcEqPPA/P98Y83Nf8C 8kt5TgbR88DrqcDid2esN3633+y1BnFhjSKTyZjVBPsc3K0BiUtOpFtqNyQ8 Z9uKF9YCnv/iLtDoYDbY2kMw0gQX5ybSgRXmpf17J68SAWhJ3WklY97obtTq Vge77RbfNIxhnlP/12GrAtIqa2/citwDCeQKL/INWUBO3dMxnY25442WcI00 8AuyXROu/r++wNvwTBJYGDI7lYxiXvpBMvomBnh/eGnmH6XDfkPy70f8oEJJ +ueN15gJCodDfm605/LHiD6f+z9Pzu8h0qF4ug82dH8xU8t+VfOwIo/xpOdR EnshYZJOTtyZF8mFLZSGhv+fM3el80sgIRe98eZMzPJffwxtSSJ2U8r+jduY 67KTAr7KoF+CxqH+I5jNgqxCNhRQS3e1hbc4PSRU/eIgO6qhuzW0SXc1MVun GaWzaqCinAud8+aYhT4/pXlGRJGXGWVdwzCPo13nTAE6vs9j76VhzDVryanO emjwzNEWs1AGSBAJMC1tNEaNfCu7RdIY/t/vyeIuE1Q023J6vQxz2LlFz5FT yJ1kMnPzJeZxn7PPdk6jXWVXWBd4GCEBXq/m1TuDVJcfucY2YY4g36uTOocE WiPqrfsxZ7MV3Rk+h3bHntyWmsTcVHToZog1Gj74NmNk7z7cvyu32uB55Am3 2wTPYU5lbKpJu4hK0nQ5Wn5jdm7zvKDogOLO77NLYWCChBs0RxSzHJDXkdEq e37M99w9X/1yQOqPXbT3nsBcNqli3uKIXk8kuFtkY04LZ+s65Yz2yg6iRUVm SLgls28z7TK60m/jdcR3PyQ86H7hYO2DZuWUS0tiMRtxsf575YMuZu1/c4iC mcE1Ne/EFWR0oRNw9mK+5vbGhMcXic2JcezhY4Fk+0nHv7uvooldK82zzzDv mTXZPeKHLC/3LTp+ZIGELZ7g04zXUP/LiiOfVrA+L3RZSvca+vj8bu/CflZI Pi6aXVx3DfWl2clPq7NCwruoKvcEf3Sbv2fXWBpm36v7KfyByHFQXiCrEPsn OSr9TgUiges31cwrsZ59ZqI4LBBlTwd6D7RgnW3ao388EEXdPfrf0xnMh1V3 EuODkLZt7nL0EvYnPV0k1gehzf27mHT/YP4tJSf0Lgj5+n2A7axskMD1osfn aDCyU0+rbiRiNuH2knoSjHgX/vT467NBMs8X3sefgtFYkdsnRXPMEcxeZ2lC kAlBl/O+K2aq4mq7Tgiif3BP1vsq5lcBLDfsQ1C30yFDqTCcL7W/4nxECNJ4 9iv8dgYbhMdm/1toDEFrwQ75LkWY+b42FQ6HoHrJVw+O3Mbxugu+6gshSCL1 9teSNjbYUXTo7IVDJDQNOGntnmGdMGL6WYGESpbJfHwjOH43ecThJAlxWV4w z/+K/fXv6PWukFBrx/HjIiu4vsZ49onrJGQvLadat43jg2eZVTJJiC6fR1Jz LzvsMNPxYy0jobu7dvM/Z2OHMKw57V0dCZldWWSx4GOH5Br7FwXtJLT2bpx2 UowdEmRufTDvIyGKfvdvTwXsHzg+v/s/EoIPaufWiZgrLoY8/ExCs/z576P1 cfzO4xsXF0go6UbUKxZzXG9AI3NnlYTkf3t1Umxwvs3Q1Mw/JPTG/lyDuCvm 5/vYuWhDUWi/zu2HvjifVeSLuL2hSEhNuhCEYhZ5R7uwLxT1lnOl9MXifGHy JgYsociThYZ8Lh3XO0qdLmMLRayhC35fCrH+9/XTHfZQ1Dg75nKlErP93doL HKHI5kyH9Z/7ON/UbokWrBPaq43jW9ih/VJ1/iEcf+tojjbHU3Y4metwInx/ KDLOiVQoGWSHQox8fh8YQ9ESwUNE6h07pM5K2GrQhaJcLwvux9M4vmL03E1C KCKOazPq/cS6h2Yn4xYJTeod3Xm1iflC/P74FRKKu8+xdGE3B4TnK8YOfCMh qUN/p2b3c0CC2+Hx5kkSGoqbG/Pj4YBCkof2B7whocCVked/j2D9il69AZ5/ x4vb97jUOWA64cILjQck5KKcWVqmxwGpHJN3LlaQEGNpWLasKc6/1neXmkNC lsHmJH0nDmh/7Et1aQAJbX0heo94c8A6tvB+V2cSop4Ws7cLxvn5fa/YnSGh b2J/TgSmcEBfyTr3ZSkSSsucUaPN54DPjXnFMrlJSOnvoFRqGQcUeYucfGlJ KHKsgu3WYw44IW54anMsBHHGmH4c+4z9GbasNf4hqPmn2pDDdw44p1YJ6y6E IDubI90/1jigWpNrGjsMQXcUN6r2MHHCpQE92l0MIUj7c6m/sgon7DjktMyS HYzctX/vy0nkhEK7XrisZAShBN6DNzyzsS7499p+vyBUtaZBp1uM9d7ciGHz IDR3j0z4WY+Zc8PagjUIuQky/TZ4ywkhQb+t9kYgciMcmdgWPwDhatF/+b4B yLXLrM756QHYoSMqWst3DcUVX5MhDmKOsa3zXvNDt0i51WxvD+D377wc65Af mlX8UNH+HccvnBdZi/JDLuWXCw5yckHyi0vBgV+vIueYiKh+R8yLE79v1/gi R/0aCyUCN35+uzJwnvBCRlf+0//EiHkn5z7lmydSzKdVTzyAOdvOqCHNE9F+ s+aflMR8eTszYNwDlafsmU2yxOw2HGPu7I6mR+2CvlRjHnOPeuvkivp3brin PsJMu5t9neCKGsQe2ah3YH56ODv2pguKCd4H08YwcxoLDI86I1G+Jnoi4SAk FIrqHddwQq5ObIWZlpjFRm7FtV5CpsmayVr2mL/RJpt8sEMqjy5HzHlgflc4 y/DHFtHtbXfUJmOmuyQWpngR3a72kPpWjVkg2dk30RrNLXe36RB4IGHaYq1m 2Ay5kwM/LVVjJqw1OD/a0O7neWcz2/B/TnBxDeYGsg+1xt+3Y+4wVl/zEwG/ ZnYP945gXnJaHKY/BiKMs7qKtjAbSDQ6xemCbK66SgMjXkiIMhCsqjkDOmrm PanzmL01eGXDnADX24sbpyX4IPlL1N+ASX/gKK19ikMRc9pJkW71AHA/UrDs DRGzY/Ap+qwAYCA2ZWx7mg8SlIsUbU4EAtK1yyUegVjv8uzgqQoCE8x++rE9 mNP3FvznRAKSDmcpBq8wPzzBzd1CAkENSkv7xjHPM1svs4QCVpv1gswFzCMW R61bQoFuVdiPEnZ+PH9JTl7GcHBLNz67xR7z308NEpmRYCXHbT7cgx+SP3XL OE5GAjBvqK3jzw/hL7HRLS4yGE9jmnsWj3XyrF6OExkwfswgjt3DvEjv07hB Blby19LzmzDb7ktj478OyqMtZmy6cHzQ0Ye7dK4DTUnutKkxrNs3R+XGXwc+ QUVTP7dxfdfgXWEsUaDlZbjqQzoBCGNkre3lo8BegUvJgawCsOO2VsVrsyhA 7TmssnNEABJY+o9cTI8CI2y3bzAaY51bSS2MIRoIuCRMDFjg+H37NX3FooFn k/uxDDvs/xqk+1E3Guy+JP2R2w+zD82mGCkaqNbUy4sWYL8q726fqWhgYkLZ aivHumpxj+pONLD/HtNjcU8Akk3nrltyx4BEaWvrmG7sFymSDDCMAcX9OsJ8 r7Bf/N6Taw4x4KGX1PeH4wKQKic/gIJjwIeav5FffuD+6GtvnKyMAcsmc4ah G1j/THCKaYkBdD+GOTh2CUJ7tMLNNhgD5GQqb+sexHz0hCD7Wgw4PpB69Z2w IBSKXJcn08cCa+9gop+MIIRikhUKvLEgqtZ4sFQX69X0VmbEWJB3SrlA/ZQg nFTT9+g0igU1PwSchs8JQuqzLxFB52PBmMzKGsEb69a1F5v9Y8G3gfcd+UE4 32WNBP3rseCv99NE+ShB/Hsr5/qhlFggcS9fwD4Pc5TdhbyyWKBlGjW3Xorj u0/VqtfEgjOLng/SarBu3N7F+ygWuKZahok/xv03db1QfxILQmWBPurE+o2f oLAnFqS/kmA914/7ecIlDvpiQYUP+7vFN7h/h9hpyeFY0Lx/uzzusyBMV+fQ v/QmFry6N+Mt8B33l6QX//FdLPhiOqjauCYI684GWt2aiAVhQR8ItwlCMD3r 6Lvmz7Eg7uTwzMoeIUhmMmrknsb1uHtfau8TgkKvMtnQTCwo/NpyP5FVCNoL /ym8NxsLKh/fz35zQAj3F5kyg7kuviJE+JAQZP26wXwZc8u5AjsfISE4xO7P qoLje8RT9VpEcb2XRQcsv8SCwfUoCTopIdgho6vbOxkL3j0LYj4jLwSpr5hd kj7Gguk8r5WbykJwsuP4duXbWLB42eG/eQ3cz0IGkXssFmyoWrUpQyE4zv2W bXIwFtDSG5dePyEEm/ayy9G8jAXM4yBuwEgI0r+QZAztjgUHq5Q8ecxw/y2s bKZtsUA4+KiZi6UQXHr9ji+8IRZIGwgo118QgtkvPk8y4v1ROcjBu3NJCB48 eZe0ifcPzu39Z+AiBHfbBHw3KogFxk3bX7I9hKCHq8oRmrRYYG89WysdIARX Th8+VR4cCzwk3mcGk4TgmtbSTKZXLAjYGAzqiRSCnmf3URYvxYLE/Gadi4m4 Hp3Sh+XjseDhePJYUglej/1Etwc+r1uTN/+FVeD5Sr2a5NiMAbrz94763BGC CWz8qYbzMWBkcyjc7KEQtDY34nV4HgOWeA+IHXiG1/dNvCTkegxQOyJmRteP 568iZYF8YgBZSpW0PoT1B1tDZTYxgEXz/Ku37/B+/F5N1FOKAbK2NwOLF7H/ 4VkOms/RINDlHjVtFe+n3ryIQV80eOKNXpI3sP+PRpPKI3zfIz4LONEehtSm tjiuBPy8KBF9Js51GAq9HbvIKxkNqj7XctdrHYYElzPaHy5FgaX5dp0y3cNw 8nP5AYcTUUB1ZdAz6+Rh2PG8TqlcMgr00q6gAHOcr/fzhUu/roOZIypuGi44 34O3b97HXAfCru1N3cmYXb31ZClkcPPbq/Nv3h+GZAOua+d0woEBj3O7wmfM Ibn1kpth4NfJTeGUWcx2Sp+j6sKASeWR73rLmM/wWvfwh4HtS8ER9XTCkMx/ 2XbvKglcGDtcnqyAGXU4GscHA64O/++68ZjXq5zpza6BrkUG8+JkYUhYB11z 637Ah7/k0WYG1ksYZLRK/MBT0ouIuiKsG7dGGny/CvyVBdgEHmB2pLU4HOkL RqqfKW9+wMzScf4tsydIzeGNvK94BBJiXhuO2F0EcqWLg8uqmKn0L9cfXgBD NV1CSlqYe0r7HenOA7Yej66mk5gl795ZKrME2Sste7ouYj64nIWCToGC0zbJ o3GYCUetOjW2tSsYigo232G2V3Su27ZFzeH8DXrRIpBcnFyoTxuMcjuZjaQS RCBBun3hMjkY+e/5+4k9BesLqIT0NxjJp0zsm8rFPNQrYLQVgqqKSpzI1Zgd rc5FLYWi/NbDHE+GcbxFodWt0UgUvCnqpyIkCsnyOweHqqKRlRYXvYCoKISD DoxGU9FI6Tpd8R5JUfx9i6KuHIpBS/RfX4wew/56kYj65BjkdrDq8LWTWOeX /57uEYusVSWH7/tgbuC4XMgaj1RCeS/nXRPF7yvLBXW9eMSJGHcigjH78ZAs A+LRkP6ChGkU9t8ao87/F48MrGrI33Ow/udIJ1NuAlINkJU/+gTXWxO+2vr7 BiJ9KiOEduH+7JG9pnAiajPkHu5/hnXGyTdzpxIRFCD4+Y5g/fL4tYGyRGTw bPjh46+Y3ZYejusmoUQF/RiGH9g/1B3Q55aE+iktFjYrWGf2mvySkoTMfMt/ /93GOhkqXhlLQtY8Aar67GL4/mUYp51PRoXR83vzucVgR7/OK8vgZPThh+34 PJ8YJL9/16uSm4zsu/RDUsTFILX7Y5beYDIqk241/CSN/QwRnz2+JaPpXDle BUUxKDTPV1K+OwW5ex5sHdXE/Ct9VEUlBdWMJSeJ6WJOUW5IPJWCFgHNxeCT YhB6W6jNOaUgP85v24fO4HpF/jQvU1JQQ4TdgPc5MUiwVgDmpSlobW7kJrqI eWr90NzDFER60qrtdBnHd0aG6b5JQW3i8iyPvLCuMiq8azYF/c2o+ETnh5mP +/HArxQEtw/WWQdhv/AJgRLaVBTlmkKuDsP9FLpt+7Okop4hGvPt65gH//Kd OZSK6IiBh03jxWDd7PF4dbFUZFD5bbkkWQw/n9/fkpFPRYksl7qWM7C/hvGC vHoq6g95namXh+fhLrKuq5OK9k+fdMopwusx2jF3NUhFZqZtx76WisEhliud haapKLNJfrf6bZx/eEFk8mwqGhWuHE2swfGJAt+UrVMRVwpP5Yd6zN/y2Sk2 qch6PSVA9rEYNPN/Y7/fLhVRHGj1yW1YP7z6IONSKproC+Qa6cT9GAF5CftU JKSyMHvkmRjMr2OzGMW6I/XS44B+MRi802qUj+MrGEfjnw3jfLyk9YCLqWjW 38Ca5z8xSL/jvuVzPhVJfGqT8PyA85GTGmMsU5GHocJm22fsP/PsXJNZKqp5 WPli/1cx2BS2Pc5onIoW+XkL7b+LwV/xHIzhx1ORfEKqx4NlMWgwzpXLopWK /FZoibvXxWB75diRHqVU1HAxaJ/VthiM4hM8UCyVitZ6F97fphGHVV9ivEsO pyI1BfuaTTpxuEe9hfclVypq22N46iabODS4n8ZW/jcFaVa9dczmEodTRk5p 2ispqNXIIzjpkDiUvzFfJjqTglrSkspDRMWhszE7+Pg8Bakr8jX7SorDX++5 ztY3p6Cm0ZpXl+XE4e42bb7xOynoMc+rTUt1cdiU9apRIiEFqbTZsZzSFof2 YzrFloEpqNHup8hxPaw7DCl8wOe1oZzVTPGUOAzm1z/1RzMFPZA5e2u/gzgc etF8su5rMlIc+tK6x1UckgPGTo0PJaN6P//hbQ9xaHbyCL9HczKqe5yz/c1f HPq+HRV/k5CManXGzzxLEIcdxpfOfhVKRlWWtv8i63C8T4ayp2oSktj4wRn0 CPPvKtIWdxK6XRgh6dMiDgmLj2WYNhLRrU8llhd7cHz7xdwnjYmo3H3qrtq4 OKTmpbRXyiai4vDL1sv/xPF9yQluZriBsiuv1juelsDvl+ehZwPiULBPHE2P hQTsWI6S0z8Rh2xUKeaiF7D+xqL3FWccEn7Rs/zVGbNBCGPtg1hU951b0Zsk gb93mSzn5mNQ/7H2B0GVmA+vpvSdiEa7uxgbkv9IQILgfp1Sj0g0lyi4e5Fw FL+vNh+KrkSgvrNKFqfpMKdEOf4KjkCZM7a/2NgwG4UvmcaEIyGGeqU8saP4 eSboEZERijTNzj0qNcf6nHF0T1wQ8p8ob2y8jZn4R5TnoTcyiVlf+VuDOS1/ +0KOFxKVNJY7+QBzeLnM3kBP9CZg5fZ/bZg9SqKLFd2RKrNOwcYw5oSYXaUF zmiLOBGqsY05+TZ1TtcKkQsO6rSbSULChOR18n1zkGKR0vd0E7PVkzcMn0JA meKOycO/kpBcKb9aGkUCTazer6i7pCCZ48tBKBYKpvtNhkOZpSBhRe0eyTsM aJxg+k/hMNbrB48y/IkAc8pJUzcNpCA03FOZRRcF9LhvbAbkScGOL5GJ5qtx wPr3BsmpCLNprnoiiAc+r922zUpxvq7jE05J8aAwzeCf1F2cj0Xz89rhBLC0 l37PVDvWfY85WRrdAMUbcaymszh+fdZ1MDoJNLxZyyAuYA4ayMh9ngReNrhy HF3C/vZgjyGmZPDbV59r9xbO53qHKTUrGZjM7+FrYZaGsCQ7+WZBCth8GyMu piwNCZmsb17EpAG/ieAv4RrSkPxxI/RDdxr4PuVVMgakoRBRcXkPTTqYXLDg jjWShpNAlnFYKx083xHZO30Jxz/1XU2vTwe6tDzdRBdpaJ9yM91oIB200TFH Znlg7vtYFD+XDu6z/F7TDZCG1Dc3OuP4M0Du4aezpYnSUH74porV9QzAKtZc tpkmDZf0QgUW8zNAomStnXmONGTdYmfcvJ8Bwo/lvCFQcT8avTOeHzLAmuqN TOtKaVjHeCh7dDkD+GqGm9ZV4/5u0fTW02UC5xMuvZceYT/c9/GpbCaYMDwf 9bgF59+ovbOpkwmsTU9ps3RIQ1/v2n6KRSYwOafc2P4S9/ernkYoOBMcc99z i38S1yd53+VuygQ13psOATPS0Ky5YL60NxOI+f3gH/iG8zVcpc8fzQS8oWM5 Yb9xfdbN+aeLmSA78oX56Bb2l1h1/tnKBPtjnjBLE2Rg+vvi2wV0WYA2pTL2 PaMMXLJKtKHjywJhGQU6x1gx3ztvNSqaBdZyUnYSD8hA+5hGwCCXBXwLrzdP 8crAuf18hrdUs8B8cUCAhpAMTLhMd74GZAHHcneFTFEZOCl9l5nvZBb4cNv2 x7ykDOzwbEG/T2UBqxrzOzryMtDtpnisukUWGKo74VKgLAMPOm0d+3o+Cxg9 Uj+8rCED6+rFXP7aZYGeZpmPBlAGUvm8giKcsoB2++EC6gkZaPCTmOl6OQs8 7jpguWGE9SGhqEaPLCD/jIHNzEwGCp25/vOKdxao7tvpv20pA/NLm45mX8kC IkPLCf8uyED/3yNnRK5mgeLRmePn7GVgk/pl58N+WeDg27eE+y4y0ISxRDEZ c+bHgTY6TxlYtFfvigtmpqnOYDtfGRhj0FdTi+PjZh8pNQbIQPL1aw4uvlmA sHBniTlUBq7EnfmW7JMFSD9v1riQZeC9fv9UEa8s8Gs1w+1JrAw8s/w+Vto9 C3hvxIocSJKBgoyBB2654P6Uc0XZ02Wgac7R4x8c8Pyu3hJjyZGBqQsi7vm2 WSDrXqM4U6EMPK6qYf7eGs9roVeCoUQGyh2/2lt5NgvQSPx3lK5CBv68p5u5 gefd5PxVctcdGdjG/TpyFO+H2MRemZ0HMpCu8DqtlEYW+Mh7UHbrsQzc8rIy uq2YBbLPScitt+F5jb7kr5PE52PYQGG5VwY2XBqN9uTJAs3M5xUX+2QgPBvw WYgVnwcj92MLQzLQq4y4/zI+TxPdN5Rn3uH9m6vYvL2cCXIIhSpTn/B++0jS V8zi861VrfppGp8H1uUbx95ngpbGl+pvF2WgmojAU9buTJB3Z5/2AK0srHv6 rXk2JROYzh4CL/fKwvTvG79KIjMB3RFp+IxJFgb3rB5f880E/kUmup1csvj9 Hno+9EwmMEtL0X8kKQsn5Vx+b7Fmgr39N08+kJOFS52lmvf/ZYB2+nsG95Vw vmoab/rFDCAd9crojjb2M5perXuRARgCWE7fPCMLYbWU06ewDNB1IeNcLAnz frOskNfpICSv1DoqUhYOEbsufm1LB/Kj9ecjY2QhoS6ohO5WOig+NWITkioL O35nF1wMSgehkMPeuwzrS3kyaVzpQEksx83ypSwkp7bKhqalgkkwbak+iLk3 4L8rF1JB8vljevyjuN5NC4MFkVQwnTzMP/MR51MiagY1pYDsVebX/svYT1P4 ovVtMvjVEaeVfVAOdjjqvlzag5/HNsHsr13lIOHmntG9jPHAPuDZv0ZPOUiW PttwvzcOMKVx/Sj0xbrPUZ1fUXHAuavhmSNJDkIPrljjrVjAeXQ5bCUFc6H1 8OaXGOC/5v6V7RHmcLLsx/IoUPhcxq6KRh6SBYyZou+FgjI3br/Tu+Uh4brH 7B1CKKimp4lbo8N60+OXv81JoMVgtPY4E+alaOnp5WDw7jlpZ5IL+yfSfHvF AsGhF8+KeKQx84Oa266+oOiFw/tEK8xTiXHHhMxB8csca++7mO2oQZ0TAehp HDPL11qcT//SReaqQPRdN/apfR3m8hLpmKtBSL3VX9HiEWaXwK+ju0PQ6N2z TESE45/71HNLhyGGFLYO+tdY32V5alrzOvI/nSJesYV5rFTN/lo8ouzbM8G/ Iw+hwZPO8dF41PUsLDvvH44vjP21VyUBsUAvmqTdCrBDOr47Yj0BVcsbv7+6 XwESTuRYngpMRJNsDGlAWAGSz4lWH76UgoxHY9beGWL20dgyccpAFeXaL2+Y YBYYkGNKy0Dbfhs31U7j+Nyq1xYtGegem9eJXAsFOLmlwxnIkonYT5/NNr+E 2eNe+ObDTOQpwOxGcFSAQrGOt6feZ6KeH73E+84KkNqqumK0KwsFJGt8YfLA /RmgjiSzLDT+4rDic38FCB9M+zhOZyGFgvd7goJwPcqVmW97s1GiW85bURLW t7niP0tmI+JehuvRkTieMn6Y60o2Kj6+NKidiP2EPu3LS9lonaO6/EeyAqz7 EVIkx5KDzL44BRWl4fqc6kxnZHIQTdR/AlvZClB+bOZD5eUc5IzavR+V4PU+ yfqYM5qDnqQG6ziXKUB7q376Y4s5iMtO8QBHJeat04rie3PRs+3KNt9qBTgU WJzEqJqLhPovpQvW4vx05wtXT+WiYAqP86v7mMdahY865yJJjZR90o9wvRsX jCNSc1E0w8lP7x7j+PlXrSVluejDOOHhjRa8nvS476yNuSglyP/CV4Tr9bjf /vwuF83qy8rmduF5As0u8D0XaXPN0Zx4ivNv+nd/285FSw02d8peYn/dvVAh vjxkGHMg3HwA+zdStm5J5qGys4NmhCFcX+5Uqb9aHtoSviFyfwTr3iU/Ek/k obMruhu2Y3i+rO2EBfM8VNO53cc0rgDVrhnX5tjmod0ZjSWt7xSgRCAHKckt DzXKSZ7kmVSAB3PZRc+H5SGWf194n08pwLlni/fkY/OQ26ubi4EzCpC+eF/j mZQ81HHzXJfoHM5vFODbnp2HeLzZcke/4f5rM9/6UfKQn2afe/QPvH82q05X SvPQy32xWopLuL+DztWPbuWhI++12T6v4PpCLQv6d/NQWPXGdNpvBZh/f01W 5H4eOj03LKu4oQBjNHUEdR7kIWGxu8GjWwpw/CNie9CQh9acYroCdxRgw9aZ lKDGPPSi1JaJh6AIN/IXNjIe56GiTypWrbSK0GTRtZimKQ/58rNSbfcowqEk 79perOvZzM//26sI3U5ban/G8VwFXcfKGBVhk8j0gPmjPDT/hhJ+nFkRzuWd GOV5mIfaOAOezbIowrP7aM5p1OWh9DOmbDfYFaF770Pjhpo85JQubiN1QBH2 U5VKEqrykMorQuUAtyIME7iu1lSehxiZ3i1e4VWE8sF3/+gV56GPhg/V2PkV oWHL837p/DxUF58c1SCoCE+Kfsq8lpGHop+69FsJK8I7v15r8CTmIatdgGtT RBEyNlu3CETlIUmdg/YUcUVoF+nsEhuSh3Yilu9oSSpCffE/T0x989BQ28vV T9KK8N3znthQ1zxUsVWuFSWnCDXZ5FKYLuYho0Cr4V4lRSg0rMp5CZ8X/ga5 Q+6qeD7uSw3C6nloaZneZZ+GIlwqUPtoKp2Hcr1bN04DRUivkXB1ljUPfXEW EnprqAjHd4Jj4etc1Fi26R5qgpn99cmrXbkocXLkIf9pRZguCPU463OR/MXY k44WeH84vOgeJeeisLPffBbs8LydX2ona+Wi0xndTSkOuJ9orbEgiVwkPFhE K++sCFmXV75PseeiF0anc/3dFfH3yD2S6iy+v7oNT3auKeL3PcXsW1wOmo9M 2UsNxH62o5cmvXNQ2xNXc90QrOtpcNtZ5CAndZ6ZuAicPw5p/BHMQXXyEUys NxQh9QCbyHh9NjISNLARLlaE9gGCMfUdWUgz5P7JPCqOvxVPP1WWhWRfcykx lWOu+AOaY7IQe/wM09ptXK+Wy9vmZBZ6uxjV/qIe569nP379eSZya39y+OpT zI9FPka0ZqA422Nz6Dvu/8nEYO1gKgp+XDiq9FMRQsbZL27kVOTBRtt5Z1kR drx3TqXKpyLTp0MFWWvYHzt5Ny4tBR2Q8TG+TDgGYdwzw2/6yahiu+refs5j sIOpvCqj6AbqpAgE2BKPQfKnMCbV+Wg0Tf88Yq829nPYuk1cj0b0gVcT6iH2 94SorvNEIzOzHsoefeyP1i9IMohCk7s9umrNsP90qV92CRkRfB6x/HXBusBJ IRZ3EtKGJtXF6ccgYey2pyGDG2qbDvn0aQbr2aGnG+iugb/e9UkX5zAHknOF 1q4BnfU51bffMIvb33014w96GazTR35ipjGljD0NBEOyKjpPNzFH5JXEx5PA TPBKWTWzEv7+npLKprsO9jN7ugYoK0HC5GvlF6EJwCy3jH1FFesZ+kMeywkg S/Bdu4+GEuyo1C1tc70BDioacrsBJUhml/h01SwRCJ8Tf37BEOv3uT9vCSYD 1dIvR6Etzpda+6/0bhqwV774gzFWCU7eC696JpUF+GUesoTG4/yvWSzU8e/d dyKMigs3sB4ePWqSmgUsOJsC+1JxPtFO19M/s4DBKgchOR/nK2t56FqTDeTr +9iZa7D/d2SnElsu+FElrBx+Twnan2AsbCLmgmpqyLkfdUqQusx2st0lF4ik ixcNPMLxXF+UdZpywcEr0aKpCNffrD4yZZUHCDJENZbX2D9zuZ+dlA+eiGRe iBzD+on+8FlKPiDxzYf9/A/ndxchCjzJB7/25XUOfsD15TSkm3fywdy3FaP0 WSWYftvX8FZQAaicMvQmzOP4h+e3C7MLgOM7aprvAs7vMmO/XFcAPrwwHTVb wvFca35tXwvAUFW1LduWEmT1ti9NOVUIUqg05OvbSlDIQN3ZxqUQGOVbly3/ VYJmn81orocVgp54uq/Du5QhmZ6HfqyqEFyPtGXQpVOG6TzuF3e1FwLtoAap B/TKkErL5XRjpBA0uTr6ZjIrwyVio2PBZiEIsGvOpGXF8XJVRw4zUYCiFesj P3ZlaMZAJ7nNTwE1J9o3z3BjP7PfWgWgAHetA3zdPMpQaPBSu+9pChBT9tI+ xofrneqTSbGjgFIR3miOw1jf7pVoJVFAutzDrqYjyvBghkDqVAIFkDVMaO3E lGHd69K/WrkUcOXEjM6uo7jeN8mIgTIKsDOLuF4lpQzn9tYOpt+jgFM23J2n ZJVh/t7PQfHNFKDpWkdYlVeGBsKbqK6bAqSuGsL8Yzi/qU3TvgEK4A2bitRS wes57kjMG6MAhvhQNKWmDDe+PGA6+5ECNjI4/8UTlWHCsb45OE0BX4tqtWW0 cb38iSGHbxTw5rZ+xAhUhiJ3KvIbf1LA0wefngTpKcPpqzML4BcFNDwJ3uHT x35mG/O/6xRQ/pxNq8tAGWb75MmsbFFA5uvqsMvGytBaefHpoR0KuD6h18Zk ite711Ev9C8F+M5/+FNvpgz9z+Y8Yv1HAZd+BRDPnVWGiZkJYR+wbvpvf+i2 pTIcYc778gnHazFWtZRaK8MpdZnvh7YpQPqAzpa+jTJMXjOMz9ikAD6hd+rf bZUh444zRWeNAvZJXQvJsFeGJhpee2VWKGBLmalZxUkZXmDqqrT4QQHfYOXG exdleGaKeLr5KwW8NdZWu+6mDH/LHp6w+UwBz63+CxLzVIY9CpIKWu8o4LGD 7+M+b2V4KLnAy26EAm55Maz7+ipD2RdthM4XFBATRQxsDVCGxVHSfacaKeBa yugj+2Bl2HLo0FLIXQpwzPf+vScUz8vj6LmFEgqA90r8zci4/zCVl2VxFCDX rNbwO0oZFv1bTV0IpgCBnuHVwlhl2KQmxhzpQQHbb3ddm0lUhvYuu1RTjClg YbroQWKKMqS/dZGDkUgB734qr8ilK0N5B73AN0cpoGmP21VSDp53qMuCwx4K CFDov8JCxfvdxHDYq6EQOGu63G8oU4ZVXx8nJhcXAouTfxfPVypDCek7cQwJ hUDRVt6nohrXM9n/hPd8IVhMyPZSf4TPd8Dn3oerBeBjlkzNxGPM314zD48X gP7i3oXoFlxP/ny85ZMCUN2w4fEKKUPW8F0sxTEFwHXyorvTS3y+D2Z802Iq AP57Y4zf9+P7NPjs4/hiPoiSvStzdhDfF3+fN2tD+eBm2Oay7qgy7Jgw1OvO ygejB3NJwhPKcNLM9fYIRz7QNR9M+ryM802377X4mwvMgte8z//C/jPfHz1+ mwvsSvjNhtdw/6SZnvqGXBDyw5Oz8w/WCV9CL7vngrob9Depe1QggZXYPD2Q A/i7dO5d4lGB5LN5jeYx2UBy3i39v0MqsONvaJf3+Wygxprud1oA6x8dPkrK ZgMLuwkVcATznb0NqW+yQOIWCQnIYP/JBKr8kSywodgw9BGqQKh2fNe/uxlg tFxs1cYN17t63ISeJgVwTqSt0Htif9wyR2hKMrA4uLn8yBvrpPxkIk8yeJ3c t8RyDXOgusYD2SQwEuC72B2O8/FWz06a3wBDJ1vmpbKwHm5TcjEkFgwsnJr8 8wSzW6YZQy0J9B4LGKBwqELCN62d69EOSCTR68ohLswdPz5WVjuh6EknNspB zHkrU40jLgimnLEs5MfM/0wzWNQDtczKfcwXV4Xk7mXChPtVVFvw7XsOEesv bFkoR0go+98lpnQnzCZ9L2WHYtGK5bl7LK7Yv8cu1NkmDpnXmJqluWGWSKx1 n41D+89rZad6q8IO3te0L/7Eo4QHvHwpQaoQ9lW87ziSiEJdxqQSkzAvab3f cUlFjn1GxjEPcX6W3hI/wyxETHdwWn+E9SOymizxWYjTMjjUo0kVTh6Ku3Cu Jwv1TlTeNXuC/bdj4r5oZaOjKwQm/mfYryL3qFI6By0dfNz/6B3uZyepVGoN /577ODAt8RFzyaeDdjL4e6ZsepvyCecTnDrG65yHLKTZZaKmcbxRobvIUB56 DLxTTBcx956j8JflowjXI6ZfadQgNYCR7r1UITonpeF6YbcatD9Hvxp3oRDJ L5lFDNCpQTK3sUxhQiGaCom493Af9gvWas5NFaITKW/3kw+oQaEju9zH0yhI 4MyS2Cq3GiT8+WwW0kxBa1x7gSsvZlE9voApCqqiKl0xEcT5vg/RhCgWIaaG tMGDRzFX5ZRHvCxCM8G3viZJqcEhbbHVp4tFqF3ryb+/MmoQIut5S/abyPfZ N7kZRTW4tMMzZnzuJnr97kR6vaYaZFW4m1I4fhPVlFysEgFqMN3X1evw+k0U 43ytI08H5/8oorDIWYxUFqlL4fpq0Eyk+eJZ02JUSLNtZmSmBjsCnHjZm4pR 5VuLuJUzeP00W+9LRopRXX1ta6El7oeaHa7/vRj1OlwSW7iA1/80MXqSrwQN qzfZZNnieszrB0aPlaAPbGwZRHvsbz83P2lYglY6u/4kuWCudfije60E7RQc UlByw/lvJXTnxJUgej9/1w8eanBDpWV6O78EcRgNUGK8sT6U4BxYXYIEhMWG pX3VoO8+J29Cawk6uhVBN+aH16N3eIjysgQpjfxHDA/A8cNKfYZvS5Bh1I1b AyTcH5/Jvs+rJcjiwtT7gHA8/yqz0L5/JchOkcgmQFaDJvFlV1z2UJE7Y7Z+ b5QalJj/VnqFkYr8p76H+sTi/RRm1N3NQkWRLSfquRLwfPSlxY5wUFFiZvFs e6IaDMvN3t/PRUU5HuuHLqeowQ/POW7/5aEiqq6ZOUu6GkyYO5LTwkdFd3nv xD3OVIMWv5E1QZCKGldo2i7lqEFNbbmyISEq6nx5YXlvvhoczb/8W0qYivrL HorVFapBdqOLL9iPUNF/JKaL1jfV4Ddu8o1YzFNnXDIIVDWIHhvkxWD+Idne W1WmBv+4PzRmxbxBy71tVqkGiVkvNyRwvl3vryhs3laDbgrSC69wvf0Pn7uW VqtBl8l0T1rcD0/S4SLDWpzf7WxHN+5XxIk0vHxfDfJdFZHj4KUiOeJrusIH ajDq49dry3i9GhzSmrqPcH8r/85ewvM4sRBz9dtjNRj9fTewxfMy6/54K7MF 57vy350FPE8bisoHjSdq8L81MdZ9dFTkei2N7QtSg81J679bCVR01XhOP6lL De7eMBnZ+V2Cwo7ohB17qgazn7/fc2e+BMX/Kah//0wNFvUNjJA+lKDM1yuz 0S/xftVzlvm/KkG3oyvMRwfVoLTdgZTZ+yXogc1OXNiIGhThuBLoWFKC2o5Z tYmMqUGmoz9vMqeWoJEve8UD3qnBui9a71bdStDHVvuL/B/VoIE+rae8ZQma y2rOePpJDR7M1TlRAkvQXz3P7QMz+LztKufmOVCCGPh6FNq/4voq3/XE/xYj zl98l12/qcHxz4niPrPFSLLi1XDjT3xe45x07jcUI6vdirfPbeHzPJlQo21Q jMgbByNHttXg5PelZm2ZYnTn+z+rU//w/bEfMqKwFaPt0QE6vd3qkPWdyWdv fJ/LK91dZferw/S6TY9yu5toSb9UdI+wOuyo3Zf3w7QI8RITdiJFMO+ciHCS LEJ6clfGtsTUoe9mcaXhniKUy60VuySljn8/zLD74OeR5tz49HtldTgEE+7b HqKgGzdYKx4YqkOyiI5fd28BehC+Hipjog6pC+jfYkEB+nB14myVqTq0P9wr TPUqQPIXanYVn1WHk00PeEtYC9AbSQOnG7bqkFC0aqB2Nh8J90cK219Vh0Ii W139+Pu9bf9PKnMB7q/jNPHy2Sx0kOtg7hMK5gGmckvOLHSNXyfJuxiz0lHH N6OZSFI6K2CgHOfLjpVLtshEBYaqRin3cH+1YY7jphkoMCZylalHHT8PrxnI OKQi+S0WfaafWM+jEVK2iUWVM/ILjCc0IEG6OkJQ2wCF2YRY3TuJuemorzub Jjoz3NlpboR5sv8Gk5cA+tt2Jj//NGb66HXvZgissv1PiF3ATIJO5gRbQKfX VKJzBbPplHp91VXgRgUWwQUaEAZkP2y0iAbaXAnoUJEGJOt6ztRvRwPO5CFJ VPx/tnJMrogBHUEONHQV2H/gpvfEaizgOR19L+sezge8T7SkJ4CXO73097ux X3Xfa1J7CpCyMX0y80MDUgv4NYemsoDQD5E+myUN/HsxQk1TKhtwRv4ZH17B +RorNq2uZYO/ZVW/nqxj/QAXSqTNAcPfaKVzaYiQ4F/PGM6XC4JIjwv1DxBh R6DfMQatfODFlFrVxk3E77cNoSOR+cC+2LlRkRf7Pw5GdnbkA6MuthEBQSIU clkoDdEtAPyM+AeyBPY/+hpeBwpBd4FQ8G1NrG//pF8ULAJNUuux/ICI+yWt nThfBGqeDGRl6RDhZLR501ZGEcj9TLofqY/rX3AfJNHcBO5Hx2bPmREhOXwg pH38JrBrvftr4Az2mwvLzjMVgzOnomiPW2K96ASLKywGmlflBOQv4PyVp5QN K4sBS/MNS3pn3O/CndGzriVgt7G9U4Qr7k8MGrZll4CNDypXf7nheIZu5NpV AqYI08mT3thvSK+NmKngkYF2T1MQEeaL353Vd6SC6necI7Ik3J82ddAnkAqK vRY+VYThfB1uTXKJVJCQnv8n/TqOv1VjHVhHBTbjK4ruSURYdanYknODCqLC 99lxpuJ5sH8hXGQsBVXCIjdQOl5PZwuXOF8pWPOy/HQglwh9T+XJH9cuBfzs Poyd+URIb7ayN9u0FBx/HKfsRSFC+ayeFUe7UpBJ05TURSXC9CWTlqCwUtB8 a6jRu5wIDaqa+NoSS8Gk8fzng7eIcNywb3d4fimQyeVVu3KXCIfEDcICHpQC C+IxJ957eF53yyRr20sBadI49Wkd1jXZShxeloLnkuHThxqJsOhA4DkwWQp+ DuawPGsiwhizYdLlb6WAK+Cehl8rjk9rFWX8VQo0eZ+58LcTYY9im4/YTilw Qp/Sn3fgeVyqvNS6pwwkOm+0XuvG6ytbEXrBXAbqGNi+CvTi9S39sDA7UAb+ ntXVCugjwuevmV73C5cB0c0LbkKv8HrvrDZ1SZQBk+JrWX1DuB7tH+NjsmXA Ty+5PfA1EW70md0UOFYGCuYq5g+/IULFs3FVMaploCPlCefAOBEyrrBYuhDL wKziGxD8Hu8n97OgDu0ywDy+6HFkgghXYnxGc3TKgFL43txXk5j32AjP6JUB G2GhzpAvRCiRJP/i3okyEPVM7bvILBF+/O9U9Kp+GajyMucemiPCWwtTww9P loFBNg/d0AUirCQ0Sy9hXmuM8hZbxOdLtWPXHcx8Fyn5w0tE+Em+uGMCx+vR NHSHrRLhI1et5xk4v8et/kXxNSL8w2kb1oXrZxjP8LzewOcn+rDWVdxf09LO 8Yg/RBh7vcKjGPf/KYfL9+hfItz+FOtqhNdHR5SjjBI0YV9HaE4AXr/M5Mne yF2aUGKtqFkIz8ci1n5Zkk4THjvOcN8Ez48kGcL3hl4T5n8hfNnE8y0dzDh5 fZ8m7EWFfRJHysBz/2o/6f2aUNWuf/4tXxlY5Om++R+rJkyQ//2SmasMaDr/ WpXh0oRTur/PEPaWAScGZsG3BzXhlqS3fcffUpB4T9Qo5pAmJJ+WoKFbKwXj G1bUd0KasGPYnyL6pRT8u3mlL/aIJrSQKG2jeVsKxPQS1uTFNCETC0/c5Vel +Hu62SReShMmD4apDj8uBfuF+TaPqWjC3SI/UyRj8fn90tVbr4bXJ/nuh2lw KSiocM+WI2rCbUVzCqtnKRARfywnBTWh9GDl5pXTpUBD+oyrsBGuL5g818ZR Csg/No5RTTTh+OmBzZldpeDpvRIagdOa0OxF7VD9KhWYKfwo4rHQhG4u9Q3H RqjARSXhNasdruef3PYb3/fqddnSVHtNiL8TfQyDqWCpacyHyUkTwpmItJMu VEAiHmGkd9OEdYImH05qU0E6bIf/rmpC3//yVR6Ml4A2o1+1P2Kxn3ZF1sWv GNAyUUI9E7Du+aR5RrcYnBzQMZxP1ISTP49EDrIXg5HTadPTaZpQaM36yWTd TTBnIXnoQwGer5XrYcHZIsB5yT7hZS32l7Gl+KlQgOe1fsfbY1h/3+JbEZgH JMszbx0c14SEWELFqmoe+DZi/e3GO+yf1+IZ28gFHoozV70+Yb8QzT6rEMzL O2SFedyfHuFEeEAO8LgiV9K6rQmpRiObQxeygJtn5vvBI1oQbly9N4BSgIuT tcXGVS1ISDITqGD0B1a37B8V+2MuZCH7lfkBg3k3rhNBWpBsHZJio34VSF8J Gc8Iw7rEDq32Cy/wi1R4USoeM6/zO28HBxCT+cHZrgjz5Grvk3l9VNFpH9DT i+Mz5h+K25FQ7m73Nx4vsL7eb3d/PBQlnLyqytaP9WMsV+zOhiOvgeubtsNa //9/2+BEETJSelsWvv7+/7oKhwVvNOpemo6VXMbsRLVYJtxAU4LuuemHtPH3 5rmDSqcy0UrEvwIGAW0oxO/ts68sE+2ayLkZJaQNJ/0fN5esZSKRoq4Kf1Ft SMi39fxRnIUuH+R7aC2nDanGrJyrC9noO+vgoJCeNiT/DpeBgXlo+4rL64IT 2tB+oWdy+GkeYh7884bdANcbXN5e5cxHsikSE7tP4fyxmatf6/PRVYao73NW 2B+yb3/AbAFao1FmqPfQhh0Kzt4zqkWIzqGPSdIbczHDy6zIIsTd4cBafgXX 10qTrO0tQmoRqdw5/liXcrvEf/YmCt36KhoSgfWTIQ86nYsRYbVQVycT85Df gogSFbGeUdBvycbrdWDa6j5DRYfrnxkey8Pxams6dFepSPfKLzPRIuw/bGF8 tYaKYhZOXWK4pQ3rnuWoIIFSxDBNCBtu1obBT+4zTPwsRVTZJIHsNm0oL7nc Oc9YhtRCDnRaIW04NMCW4i1ahtz2S9J96NGGCY+MC/+zLkPP1c6mzw7i9dMI Ev42lSH76I+Kd0a0oXUYGMgbLEMbA5fHPMfwPPalt9ycKUPiTmG8y++0odub O8cXWcpRXEplxZ8ZPE8jtqpc23IkMC53sn1OG1a9WhiLv1KOGoVb5skL2nDu l1/BJ3I5mnn8SpZuGeevyJtvLS1HYbTnh5+vasPnmSO/tOrLEeepL9eS1vD+ PR/dEe4oR8en1ptYt7Wh2tWSGO4P5eiDdJTN67/a8Pvqqon4fDnyD2L6m0MD IHVT/27h7/L/NUD2sVAHYBwXm7fpVhedMuHmZF5KzBVXnudyzEtxVrpFOS7R HGmMSiZ6l+mPYlkzZM9ozoziMps9sl1bSluLoxoni44/bOyySabfn9/ts+8b k5tfrJcToO3EkcUuN+LjGsPCjAugytAxHC8hnngZ+ajNDfBajo+/yo/Y4WjS uEwM6O7fZ58dQfyiZqLY6i7wma8slQri8E9ZYoMEsHCytmHjJPHY3qX+ov2A DdbYAXMisS6nVBPmDRg41DTorib+a9jaWPMBTPkV9e9NOvHT9YfNA1LAPN8n 7/sziIOUYrghA8y1r0iQaIlH65p/RgcCziUHt/7QEWeYA+5tBQHOzyxO7sgj XvPtCxgJBdR9mf5de4X4sV7x4U4YoLVn8V1pAbGf0aSPiwC0lN1VsZ540E4t cpYDTmWRtrCQWJ38vXfsGKDU8fX6LUFbG3PP1CsAK7hmaEXgq+dW/qTGADop pyJMgp9n8M0msRIwyRRt3RbyesscFJOxgLJdXzNbhT4JI/Uzz+MBp9tgD10i trh6VmckAsaPlDSKsonL09ul3qcEXldXZMkkFrWFmCwpwh8Xe0IkGuKOZWN+ exrg8vas3phGHBOpdL18Vth33zw+nExsvv2x+6AGcOf8rN2hOOKrY+mpy+cB l6paDjvHEDt6zK12XwAM6pSqTsuJW7QFDcVawEr3csNWKLG8yyYP1wGem7i+ sE9G/NlW9c2WC2jc7HzQ7kWcBy6Vb/MBRa2rUU27ibdqnx2oKABUe5SMbjoS /wdVlK0x "]]}}, 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, Automatic}, {Automatic, Automatic}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImageSize->400, Method->{"DefaultBoundaryStyle" -> Automatic, "ScalingFunctions" -> None}, PlotRange-> NCache[{{0, 10 Pi}, {-0.03989016901415378, 0.03570509477549536}}, {{ 0, 31.41592653589793}, {-0.03989016901415378, 0.03570509477549536}}], PlotRangeClipping->True, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}]}], "}"}]], "Output", CellChangeTimes->{ 3.7205516007934*^9, {3.7205516386443996`*^9, 3.7205516778761997`*^9}, { 3.720551710801*^9, 3.7205517392166*^9}, {3.720552055703*^9, 3.7205520756452*^9}, 3.720552278599*^9, {3.7205523461226*^9, 3.7205523715636*^9}, {3.7205539286368*^9, 3.7205539381538*^9}}] }, Open ]] }, Open ]] }, Open ]] }, Open ]] }, WindowSize->{1440, 830}, WindowMargins->{{-8, Automatic}, {Automatic, -8}}, FrontEndVersion->"10.0 for Microsoft Windows (32-bit) (July 1, 2014)", StyleDefinitions->"Default.nb" ] (* End of Notebook Content *) (* Internal cache information *) (*CellTagsOutline CellTagsIndex->{} *) (*CellTagsIndex CellTagsIndex->{} *) (*NotebookFileOutline Notebook[{ Cell[558, 20, 1170, 35, 218, "Subsection"], Cell[CellGroupData[{ Cell[1753, 59, 251, 5, 35, "Subsection"], Cell[2007, 66, 1001, 30, 123, "Input"], Cell[CellGroupData[{ Cell[3033, 100, 112, 1, 34, "Subsubsection"], Cell[CellGroupData[{ Cell[3170, 105, 772, 21, 70, "Input"], Cell[3945, 128, 127088, 2161, 375, "Output"] }, Open ]] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[131094, 2296, 121, 1, 43, "Subsection"], Cell[131218, 2299, 393, 11, 47, "Input"], Cell[131614, 2312, 349, 10, 46, "Input"] }, Open ]], Cell[CellGroupData[{ Cell[132000, 2327, 141, 1, 43, "Subsection"], Cell[132144, 2330, 179, 4, 31, "Input"], Cell[132326, 2336, 344, 8, 31, "Input"] }, Open ]], Cell[CellGroupData[{ Cell[132707, 2349, 340, 6, 43, "Subsection"], Cell[133050, 2357, 462, 13, 46, "Input"], Cell[133515, 2372, 605, 18, 46, "Input"] }, Open ]], Cell[CellGroupData[{ Cell[134157, 2395, 227, 5, 43, "Subsection"], Cell[134387, 2402, 908, 25, 52, "Input"] }, Open ]], Cell[CellGroupData[{ Cell[135332, 2432, 195, 4, 43, "Subsection"], Cell[135530, 2438, 1746, 52, 129, "Input"], Cell[137279, 2492, 1585, 47, 94, "Input"] }, Open ]], Cell[CellGroupData[{ Cell[138901, 2544, 234, 4, 43, "Subsection"], Cell[CellGroupData[{ Cell[139160, 2552, 996, 27, 50, "Input"], Cell[140159, 2581, 579, 17, 46, "Output"] }, Open ]], Cell[CellGroupData[{ Cell[140775, 2603, 823, 20, 48, "Input"], Cell[141601, 2625, 422, 10, 31, "Output"] }, Open ]], Cell[142038, 2638, 933, 27, 92, "Input"], Cell[CellGroupData[{ Cell[142996, 2669, 2021, 51, 69, "Input"], Cell[145020, 2722, 1003, 29, 50, "Output"], Cell[146026, 2753, 880, 24, 52, "Output"] }, Open ]], Cell[CellGroupData[{ Cell[146943, 2782, 821, 21, 31, "Input"], Cell[147767, 2805, 1223, 36, 52, "Output"] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[149039, 2847, 269, 5, 43, "Subsection"], Cell[149311, 2854, 2545, 72, 120, "Input"], Cell[CellGroupData[{ Cell[151881, 2930, 115, 1, 34, "Subsubsection"], Cell[CellGroupData[{ Cell[152021, 2935, 1206, 29, 31, "Input"], Cell[153230, 2966, 202, 4, 31, "Output"] }, Open ]], Cell[CellGroupData[{ Cell[153469, 2975, 1116, 28, 31, "Input"], Cell[154588, 3005, 157, 2, 31, "Output"] }, Open ]] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[154806, 3014, 91, 1, 63, "Section"], Cell[154900, 3017, 180, 4, 31, "Input"], Cell[CellGroupData[{ Cell[155105, 3025, 355, 6, 67, "Subsection"], Cell[CellGroupData[{ Cell[155485, 3035, 8935, 223, 644, "Input"], Cell[164423, 3260, 79567, 1319, 615, "Output"] }, Open ]], Cell[244005, 4582, 186, 3, 31, "Input"] }, Open ]], Cell[CellGroupData[{ Cell[244228, 4590, 304, 6, 43, "Subsection"], Cell[CellGroupData[{ Cell[244557, 4600, 107, 1, 34, "Subsubsection"], Cell[CellGroupData[{ Cell[244689, 4605, 1332, 38, 31, "Input"], Cell[246024, 4645, 75586, 1264, 255, "Output"] }, Open ]] }, Open ]], Cell[CellGroupData[{ Cell[321659, 5915, 103, 1, 34, "Subsubsection"], Cell[CellGroupData[{ Cell[321787, 5920, 1442, 39, 31, "Input"], Cell[323232, 5961, 74222, 1242, 257, "Output"] }, Open ]] }, Open ]] }, Open ]] }, Open ]] } ] *) (* End of internal cache information *)