(* Content-type: application/vnd.wolfram.mathematica *) (*** Wolfram Notebook File ***) (* http://www.wolfram.com/nb *) (* CreatedBy='Mathematica 11.3' *) (*CacheID: 234*) (* Internal cache information: NotebookFileLineBreakTest NotebookFileLineBreakTest NotebookDataPosition[ 158, 7] NotebookDataLength[ 346910, 6433] NotebookOptionsPosition[ 337586, 6270] NotebookOutlinePosition[ 337927, 6285] CellTagsIndexPosition[ 337884, 6282] WindowFrame->Normal*) (* Beginning of Notebook Content *) Notebook[{ Cell[BoxData[ RowBox[{"(*", RowBox[{"korelace", ",", " ", RowBox[{ "kovariance", " ", "a", " ", "korela\[CHacek]n\[IAcute]", " ", "koeficienty"}]}], "*)"}]], "Input", CellChangeTimes->{{3.8241805659813366`*^9, 3.8241805934787583`*^9}}, CellLabel->"In[15]:=",ExpressionUUID->"86be98dc-7e61-4bb0-9527-0d9647bf8c4b"], Cell[BoxData[ RowBox[{ RowBox[{"data", "=", RowBox[{"Flatten", "[", RowBox[{ RowBox[{"Import", "[", "\"\\"", "]"}], ",", "1"}], "]"}]}], ";"}]], "Input", CellChangeTimes->{{3.8241805992826424`*^9, 3.824180651638087*^9}}, CellLabel->"In[16]:=",ExpressionUUID->"27cb8892-1923-4345-967d-98d485bd8a05"], Cell[BoxData[{ RowBox[{ RowBox[{"datk", "=", RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"data", "[", RowBox[{"[", RowBox[{"i", ",", "1"}], "]"}], "]"}], ",", RowBox[{"data", "[", RowBox[{"[", RowBox[{"i", ",", "3"}], "]"}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"i", ",", "2", ",", "30"}], "}"}]}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"datk1", "=", RowBox[{"Table", "[", RowBox[{ RowBox[{"datk", "[", RowBox[{"[", RowBox[{"i", ",", "1"}], "]"}], "]"}], ",", RowBox[{"{", RowBox[{"i", ",", "29"}], "}"}]}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"datk2", "=", RowBox[{"Table", "[", RowBox[{ RowBox[{"datk", "[", RowBox[{"[", RowBox[{"i", ",", "2"}], "]"}], "]"}], ",", RowBox[{"{", RowBox[{"i", ",", "29"}], "}"}]}], "]"}]}], ";"}]}], "Input", CellChangeTimes->{{3.8241808004327936`*^9, 3.8241808744594903`*^9}, { 3.824350175469758*^9, 3.8243502657542953`*^9}}, CellLabel->"In[46]:=",ExpressionUUID->"5dbe865b-3a3a-431d-bf76-0cbc5010e283"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"primka", " ", "=", " ", RowBox[{"Fit", "[", RowBox[{"datk", ",", " ", RowBox[{"{", RowBox[{"1", ",", "x"}], "}"}], ",", "x"}], "]"}]}]], "Input", CellChangeTimes->{{3.8241807934090233`*^9, 3.8241807950830355`*^9}, { 3.8241808705346003`*^9, 3.824180892390315*^9}}, CellLabel->"In[18]:=",ExpressionUUID->"3f038b59-b423-47d2-8dc9-ef1682b48c2a"], Cell[BoxData[ RowBox[{ RowBox[{"-", "0.09512199245076138`"}], "+", RowBox[{"0.08387922796679`", " ", "x"}]}]], "Output", CellChangeTimes->{{3.824180881485989*^9, 3.8241808934326515`*^9}, 3.8243500381571465`*^9}, CellLabel->"Out[18]=",ExpressionUUID->"55b90cff-f393-48df-9a37-325d9bfa74f6"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"lm1", "=", RowBox[{"LinearModelFit", "[", RowBox[{"datk", ",", "x", ",", "x"}], "]"}]}]], "Input", CellChangeTimes->{{3.8241818279388757`*^9, 3.824181839472866*^9}, { 3.824182036399252*^9, 3.824182042719018*^9}}, CellLabel->"In[19]:=",ExpressionUUID->"58a22b92-93fd-420b-95ac-afd9e427e90a"], Cell[BoxData[ TagBox[ RowBox[{"FittedModel", "[", TagBox[ PanelBox[ TagBox[ RowBox[{ RowBox[{"-", "0.09512199245076156`"}], "+", RowBox[{"0.08387922796679005`", " ", "x"}]}], Short[#, 2]& ], FrameMargins->5], Editable -> False], "]"}], InterpretTemplate[ FittedModel[{ "Linear", {-0.09512199245076156, 0.08387922796679005}, {{$CellContext`x}, {1, $CellContext`x}}, {0, 0}}, {{1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.}}, CompressedData[" 1:eJwB4QEe/iFib1JlAgAAAB0AAAACAAAAicxEd6b1F0DmOI25nXbrvwiZPuoQ duq/uyqZ7psm+D+mabnBfOkJQD7cz6wUDrU/l9FahbUw+j+YLmZso1vmv4lG SE/hFx9Af9x556K0079SQfvUkl0HQMRdSYATa8Y/Vlqo+VrOHEAqyiCPDYzz P9LhhIiitghAs6RVubD0yD9io/sXLOsXQJa4hOBJnvI/nlj4boas9z8d2WoT DjbuPz+5Fc8mPx9A+7KwIoK3+j8ohFj2Dej6v6Cc9UdwqZA/QO5tb3YIAEAW MLHShYDnv4AC0cCZ2fO/04ed+fw07r8t0CMCyHQWQL+IM5+/oe2/sELPcdDV 7z/rSURsin36vzAfZS/Zf/2/P7IVhiBN479/D4t/bhoXQA4SXckiqNY/0Hfk GIENH0D/6yAPPzHwP8jKZx8luOG/XS4sRxEjur9Id25vY1Lvv2oJgnabJes/ 8Mf9SakaG0B0J1OGohD1PwCAb5DU4qE/z5QskG6S3j8a2hHheSLxP8s8A8HG uOo/9rdLD5xpHkDr526NaQftP8CALj3rati/t4qaEy9+77+oW6yrMvENQLWX JWDZitc/ze85i/dfE0BiVYDE6bWjv482CwgFdRdAtqLOgAPU07/ygOtr "], CompressedData[" 1:eJxTTMoPSmViYGCQBWIQDQEf7DvPuJQv+yruAONzzLR7JVD2aj+Mvyxz58Ga l5xw+ekXo1q3Gvyyh+t38/B/KC4Plw9y/H1lUiw7nB8WteJn1DkZOP/Sw5aO Rds44Pykxb/FdV4j7J8X8SOvbc13uPn2O0XPq9kjzNdoifjG++IX3H0O73Lz yzgY4PINTBcPzLz5GS6ve0GZ6USJGFx+g9P5wgtX38PNN5BP1b9Z/xeuvp6/ uz5PCuGeC+VPJBp5EfafOJUur7rjIVy9R3lefnLQezj/w/G/niulpOHqGRry J1x5tBBun9QtwYeVSh/h/G/bvfnnZMrB1R9o0LN9nXUDbt6K6DWrjT7ywuXP vrfs/h4vDOf3m3FzsJaKOwAArROSNg== "], Function[Null, Internal`LocalizedBlock[{$CellContext`x}, #], {HoldAll}]]& ], Editable->False, SelectWithContents->True, Selectable->True]], "Output", CellChangeTimes->{3.824182049159159*^9, 3.8243500382105565`*^9}, CellLabel->"Out[19]=",ExpressionUUID->"3676664f-24f7-45c2-8431-ef10d652fd2d"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"parabola", "=", RowBox[{"Fit", "[", RowBox[{"datk", ",", " ", RowBox[{"{", RowBox[{"1", ",", "x", ",", SuperscriptBox["x", "2"]}], "}"}], ",", "x"}], "]"}]}]], "Input", CellChangeTimes->{{3.8241808964347568`*^9, 3.8241809254434824`*^9}}, CellLabel->"In[20]:=",ExpressionUUID->"b7050c0c-f033-4db9-aabf-4dce9f9cb68e"], Cell[BoxData[ RowBox[{ RowBox[{"-", "0.1116435256083413`"}], "-", RowBox[{"0.06750215916782429`", " ", "x"}], "+", RowBox[{"0.024131576672200297`", " ", SuperscriptBox["x", "2"]}]}]], "Output", CellChangeTimes->{3.8241809287882075`*^9, 3.8243500382418585`*^9}, CellLabel->"Out[20]=",ExpressionUUID->"f7f6850b-f37f-4954-8b9e-e4f147f8bc46"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"lm2", "=", RowBox[{"LinearModelFit", "[", RowBox[{"datk", ",", RowBox[{"{", RowBox[{"1", ",", "x", ",", SuperscriptBox["x", "2"]}], "}"}], ",", "x"}], "]"}]}]], "Input", CellChangeTimes->{{3.8241820643856606`*^9, 3.824182096145214*^9}}, CellLabel->"In[21]:=",ExpressionUUID->"432dec8c-03af-47b2-8d68-14bca8ee99d6"], Cell[BoxData[ TagBox[ RowBox[{"FittedModel", "[", TagBox[ PanelBox[ TagBox[ RowBox[{ RowBox[{"-", "0.11164352560834132`"}], "-", RowBox[{"0.06750215916782408`", " ", "x"}], "+", RowBox[{"0.02413157667220026`", " ", SuperscriptBox["x", "2"]}]}], Short[#, 2]& ], FrameMargins->5], Editable -> False], "]"}], InterpretTemplate[ FittedModel[{ "Linear", {-0.11164352560834132`, -0.06750215916782408, 0.02413157667220026}, {{$CellContext`x}, { 1, $CellContext`x, $CellContext`x^2}}, {0, 0}}, {{1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.}}, CompressedData[" 1:eJwB4QEe/iFib1JlAgAAAB0AAAACAAAAicxEd6b1F0DmOI25nXbrvwiZPuoQ duq/uyqZ7psm+D+mabnBfOkJQD7cz6wUDrU/l9FahbUw+j+YLmZso1vmv4lG SE/hFx9Af9x556K0079SQfvUkl0HQMRdSYATa8Y/Vlqo+VrOHEAqyiCPDYzz P9LhhIiitghAs6RVubD0yD9io/sXLOsXQJa4hOBJnvI/nlj4boas9z8d2WoT DjbuPz+5Fc8mPx9A+7KwIoK3+j8ohFj2Dej6v6Cc9UdwqZA/QO5tb3YIAEAW MLHShYDnv4AC0cCZ2fO/04ed+fw07r8t0CMCyHQWQL+IM5+/oe2/sELPcdDV 7z/rSURsin36vzAfZS/Zf/2/P7IVhiBN479/D4t/bhoXQA4SXckiqNY/0Hfk GIENH0D/6yAPPzHwP8jKZx8luOG/XS4sRxEjur9Id25vY1Lvv2oJgnabJes/ 8Mf9SakaG0B0J1OGohD1PwCAb5DU4qE/z5QskG6S3j8a2hHheSLxP8s8A8HG uOo/9rdLD5xpHkDr526NaQftP8CALj3rati/t4qaEy9+77+oW6yrMvENQLWX JWDZitc/ze85i/dfE0BiVYDE6bWjv482CwgFdRdAtqLOgAPU07/ygOtr "], CompressedData[" 1:eJxTTMoPSmViYGCQBWJmBhj4YN95xqV82Vdxh+Va17lrPzg6wMQ5Ztq9Eih7 td/dPE+y/+FTe5j4ssydB2tecjpIGMdOrPqtAlc//WJU61aDX/Yngz1lC/NZ 4eKdbh7+D8XlHWxSNkSHmfnBxYMcf1+ZFMvuEHDfYdMUfkW4eFjUip9R52Qc Jsw0fxn4zhMufulhS8eibRwOZw5d1GATU4aLJy3+La7zWtzh8p6wTecfINw/ L+JHXtua7/Z/1j9KW9zMCBe33yl6Xs1e3qG51+LS9SaEezRaIr7xvvi1/9zH k1Ur57PBxR3e5eaXcTA48PzcHvFRQAAu3sB08cDMm5/3s/K4dMUs+AEPH90L ykwnSsQc3HYeTa5qsYer3+B0vvDC1ff2FYW7Gm6sfg9XbyCfqn+z/u9+h7aJ +TsMueHq6/m76/OkxB0ktqesEVnnABe/UP5EopFX3qFrk/plfSWE+0+cSpdX 3fFw/3zmpxbT5l+Gm+9RnpefHPR+v53EtmMlK97BxT8c/+u5Ukra4Z9wyWPh r25wcxga8idcebTQvtnsadHkf8Fw9VK3BB9WKn20f/T4kXtv5Ce4+Lft3vxz MuUc/uWdVk987gM350CDnu3rrBv7XRP+SBxbeAiufkX0mtVGH3kdIss23XJl 0YGrP/vesvt7vLDD/RMmrdpl5nDxfjNuDtZScYdPu6I1Hhs6OgAASR/96g== "], Function[Null, Internal`LocalizedBlock[{$CellContext`x}, #], {HoldAll}]]& ], Editable->False, SelectWithContents->True, Selectable->True]], "Output", CellChangeTimes->{3.824182098852374*^9, 3.8243500382574587`*^9}, CellLabel->"Out[21]=",ExpressionUUID->"81bd7476-2616-4ea9-9b05-944224a11546"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Show", "[", RowBox[{ RowBox[{"ListPlot", "[", RowBox[{"datk", ",", " ", RowBox[{"PlotStyle", "\[Rule]", "Red"}]}], "]"}], ",", " ", RowBox[{"Plot", "[", RowBox[{ RowBox[{"{", RowBox[{"primka", ",", " ", "parabola"}], "}"}], ",", " ", RowBox[{"{", RowBox[{"x", ",", " ", RowBox[{"-", "3"}], ",", " ", "25"}], "}"}]}], "]"}]}], "]"}]], "Input", CellChangeTimes->{{3.8241809628362107`*^9, 3.824181043471914*^9}}, CellLabel->"In[22]:=",ExpressionUUID->"7420d16a-a1cb-4ecb-b352-3e2c71d7aefa"], Cell[BoxData[ GraphicsBox[{{{}, {{}, {RGBColor[1, 0, 0], PointSize[0.012833333333333334`], AbsoluteThickness[ 1.6], PointBox[CompressedData[" 1:eJwB4QEe/iFib1JlAgAAAB0AAAACAAAAicxEd6b1F0DmOI25nXbrvwiZPuoQ duq/uyqZ7psm+D+mabnBfOkJQD7cz6wUDrU/l9FahbUw+j+YLmZso1vmv4lG SE/hFx9Af9x556K0079SQfvUkl0HQMRdSYATa8Y/Vlqo+VrOHEAqyiCPDYzz P9LhhIiitghAs6RVubD0yD9io/sXLOsXQJa4hOBJnvI/nlj4boas9z8d2WoT DjbuPz+5Fc8mPx9A+7KwIoK3+j8ohFj2Dej6v6Cc9UdwqZA/QO5tb3YIAEAW MLHShYDnv4AC0cCZ2fO/04ed+fw07r8t0CMCyHQWQL+IM5+/oe2/sELPcdDV 7z/rSURsin36vzAfZS/Zf/2/P7IVhiBN479/D4t/bhoXQA4SXckiqNY/0Hfk GIENH0D/6yAPPzHwP8jKZx8luOG/XS4sRxEjur9Id25vY1Lvv2oJgnabJes/ 8Mf9SakaG0B0J1OGohD1PwCAb5DU4qE/z5QskG6S3j8a2hHheSLxP8s8A8HG uOo/9rdLD5xpHkDr526NaQftP8CALj3rati/t4qaEy9+77+oW6yrMvENQLWX JWDZitc/ze85i/dfE0BiVYDE6bWjv482CwgFdRdAtqLOgAPU07/ygOtr "]]}, {}}, {}, {}, {}, {}}, {{{}, {}, TagBox[ {RGBColor[0.368417, 0.506779, 0.709798], AbsoluteThickness[1.6], Opacity[1.], LineBox[CompressedData[" 1:eJwVx3s0lAkYgPFphuaUbSyzOzElt0mYJIbxIfO+0apOSC2b2ZOUKLNbEiqx W9hK67SMI9HoJiq3stLVpW+qSepE4zZiqJQ0LpHchW/bP57zO49p8L7NoXQa jeb9rf817fAuoyimfLBOs2GjnYqc2/PnVskAU/4bw5iduFRF9o5c125sZ8q7 nPzbbhmqyJvfsQKu3mfKWy89DOPSVaT7qrppryim/FGk7PiHhmYyONvHU9Y9 V57O8SLjopvJy+KNrQ612nLhthL7/LtNpLnKl5LIGPK4TwcM54gayfr6zbu8 i2fIym0m+dY6SrIJWakJT0bIL1vS2LZGz8np91W+DRwN+c/k2mqmu4Lcf1uV XHxRQRonRI5dfFlBFvTH6S9gtoL9bFZAnKaEnLBXZ9woGAQTeO3Q2HySvDZ6 9a2T6yRYPEqjndHOBRutorYBioZsrnCRx9rboBheHjgo10aeVovBgNZDuPDA 6qi+3XxEj4WzZZPVEKpRa9TJLBTFDQ3HKl+A46qtBwpy9LDvRI3AKr0eWoeY ngeb2egcLZPVJzVBdlvNu7MEBxtYG5Fe2QJNkSG5UqkBtl/xDRd0tkFJTFWZ gZyLvdv91psqOyC/lC8dX2KEOSHnSzccfQseAVsqd/sbY12h3o+hXzuBMvD6 NbPDBHPXjme6Z76HzA5xWNd8MywJZgRd4n8AmthzyZS5OVamSv9oz+uGib1u LhV+PAxnp95vd9PAQ2f27Jr9S9GsgOVdUdEDPwWqfiZOWiCr6haPa98HYm6e bsudZZiz7MUit5p+EKX4RonqLVGYFyIReQzAzWym2yaGNUYcClcxXg9CJ604 q9aWj/tDXj7Ou/cZOhfbntNftxz5nPynd6KHIKKhUpsRY4NOUc7qQvwCSpHV wsr0FbhGrMNlUV+gn/5X+esCWww/8jm29P4weP07vEP1+0rs80npEx4bgWSX jPKciZUYlr8nib96FKR6q6rd0+zQ+TpDQGeNAeXRsLTG2B51XNXz1tWOwQaz IJ/EInucZFbT606OQ5D3kJW+hwBd4iU6Qr8JUDdGik8oBRib4A0L9CfB+Nqk q1LigLorehOr30wCWhz66ENzxAeGMg1ZMAXPaV3dpaccMSIl+bDlrq+w2PKX s708IUbfEHCj7KdBVXj3IrNMiIe3GHUvH5qG8FbdfWKRE8qA22RRPAO1fnuH 4pudcEHjy3r6oVnI4Jc/PRVMYOLgkylvBwpUPdGn6aEE8o5fFmY7UcDJt90R s5tABfdopMaFgjO8K1M79xCo5Un0Jq7+9kZSG9eDBB47V9h614eCLN1d6T1/ E3hifeo9UwkF54b1gjxLCUzJDTg4ep6C9tIX/MoyAlc4O950z6FgcUTShN0d Auvq9AZS8yg43z+dZlRB4PdTz0Otiyi48OGjYkRBoNTXzT/oHgWXWqqsc18R eHrG1OFZAwVvM2LGDdQEOqTP7uOoKDDxEyhSOghsslQX7WylIEeZHxj7jkCO 32nz2TcUXH6WLt3UT2BW4Vy24BMF75J8Ap8OEEjge5/4zxSYec6zdhsi8FUz mVw7TEHuoyOPLccINJhzmB42RUFXvLP0wgSB5Wf8RbdnKODByNYfvhJowzF0 S6DRMGTmhlXyDIEz25nqZXQa5lVIxiiKwNqi0Zg6Bg3/A2c3V1I= "]]}, Annotation[#, "Charting`Private`Tag$19178#1"]& ], TagBox[ {RGBColor[0.880722, 0.611041, 0.142051], AbsoluteThickness[1.6], Opacity[1.], LineBox[CompressedData[" 1:eJwVlXc81d8fxy+ysyojlBG+7s3ISNc8J0SyCvmipCGlVEpFKiuhKIqyMsJX iGQks/d176eMlqwiRGRn7/m7v7/O4/k4j/fjnPfr/TqvI3Pyks1pVhKJxMdC Iv1/lem0LFpf56TpJza08bxtQhxDt4+6j3HSHIqcfmjEN6HhmTz2pg5O2vbp B8T5m02ocCO/Q2YZJ61gaPw0F25ChnpfViy8OGkzhc8/zdQ1opOJViYJ/Ry0 gTeV5ITubyjN0bpN8zM77dHtBlnRrQ1oR+vBdfcENlrzP13SxRfq0EWq9JRD KBvtaAHn+Nbddag8YbzP9CobTZbPozltpRYddHlYL2/FRrPT/dO3LaIW3Rr8 +KSHhY3mdyVesiy3BjUvmSg5urPSOsy5B+7MvEchUvqO+6kstNocjsFzyXT0 7ZuNm2XuKkSqT2iulpSihzCrVRi2Cq2x6qLZzqXoQF4cp+jpVbiqkUB+vKEU 0cO6srq3rQLwtXVJ2L5FhejciFfkCtyzEg7nm36DHucFeiZcWYZpUtiwu0ER srn32neAugjqNrn3+ThyUTPmjwx8PwPD4vY5RgKPUNwdL+X4tBkIjuMX726L RM4ffnx87f9/Dj0qEPsA9Zunc3Vrz4CcZ5XDpMg9tGhPDTJ4NQ12flQVhlIA 2n7h5LXlp1NASzIgS8wZg3t8yZFrZydAzC3xm5vXI1DpkFiK2DcBf44HJNn4 PIap7YFxGbITIM7XTrG9FQ3z+2NzXpSNQ8KNkXuPA5+ApEt1kmvaGGimhzjy BMbDmXDh4C6vUbCRtJYaz06Fld6qg40ig7BPixwVLpcFsgz2YpGPA2B8KPuH aFoWmKZZih7xH4BIC+OyrVLZ8Ph4Z2fvQD/w9NUb+onmgGLnyrnZ0j8Q9lTc u54lF+xade+KHemFMm7C9VJlPjg88vKqMuiEyzFSObOuRZBuzaZj8qID8jL5 DgonFsEYXzTpq0AH8JO56eMNRRB8v/BBd3c7GPop8rToFsPrO5Mv2O78AM9z XDtP8L8BruuXOsxqmqDPzDLfP7MELr9pvZ+bQoCG/Eh1S1oZaN0U9ZwNZoB3 i5na/s9lsIwdDhuco4N6krOT33wZ3P3UJtWgSYONXhltu83LQa2mzH0g+i3Y UPMjvo2XA+tDsfnW57GwnVxGVChXQs8OmYQLF6sQIz351pFb78AhLuXrz3RA XYapsvtS3sEZjkjW/0ZpyHPRPmiq+h10+vJRN8sy0GJu78U4DoC6Uzzp4xE1 KF7Zd0XwAcA38SA9O7UGFFn/+aqTKQ2yR29u4uNsQwlr39ld1avhYWu3jUFq G6ImUW5R91bDVdq+6Eva7Whu79kHQ9bVYBAjsKXx/E/UmpQR0ONRDY266cKx DZ1IMkUmR/G/ari973SEoGUP+lqjxL1FgA6e5bFK2fE9yLdWVaVQgg4nVes/ 7e3vQUZft40pKdJh/1ZVPi//30hnvNygFNNh09+FBy0FvajQZ1FWwZMOmTER kQki/YgoCJ0/VkuHOG5Q1TjVj3y36H780EiHcL/Jrx/z+9HB223avJ3M887a C67uH0AuJ74PkCfpoKMn/cjl5iDi8Poe8k6UAUoFNmoLNYOIztGrxivDACmF u9+itgyh5NQ2b00KAzYIDgvR84ZQaX9os6QeA772Fj2W6x5GPpWDDcbHGEB3 6FevUhpB2oEWttfdGFD8Wazp8I0RJGGR6Bl8kQEJb29vDt00ioxmFm9q+THA Ndw0Zsj4L9r6sKJlMpEB9iRfzaBHf1H3HW9VrnQGmF3LbRbv+ovq/LfLLWcz QMVFSNjCewwt31Puuv6WAQvqP5+8yh5HwwPWT943MKB9NSyhZ2YccU18oPzX yoBjronWPNITSF/iv7STHQxAqmZ2+ucn0Ej7U23vAQawvs9wTmeZRMfWrTdw rjDgSs7yL71/JpGGNCmvhURAb6TNyVaLSSTjKkoNYieAcCKd4Y6bROjwzdmr /ASEThzxvKQyhaI6xPiqtxOw0FI4xWU3hbaJsNb5yRJwtoL7WtqNKUS/YnNG XIGAAyFvb7QQU+jQE0XzESUCys/zr1wcnkI6R15FSe8iYOeh035cgtNI1zix VEODgI2Sm+/oHplGAf45+dNUAm6znGNvCZhGNd8++aXqEjDWTwu9mDmNZE3t d+00IODYJ1Eerk/T6OkvEyIaE/C14GLE88lpJJOYrNNuSACOfc+vKzqD6Dec o9eMCXh9S/JRs94MunnzzheSKQGPTeufcIbNoF2DG0aTDxDAqiwj9jxvBqnY Hv+iY0GA1yafBJ2mGbS3Rza62JKAvvkvks0LM+jiYwudjdYE2HXKp1zYPote u3Uy9h4k4D39lgyn8SziOtaievgQAVpZTemp7rPoho+mn4kNAZkPKAo6kbOI VLL0StiWAFGvwKym4lmUIqJIpzM5zOEH5UL7LLJNqHxracfUV181j4M0h6T3 lkaWMNl9R4hqqvwcYuOVOLDK5HauzgJt8zm0Ot/XL3OYqfeYhmaT5xzi5xJx k2NyRdP9Eo+nc0hL91XNBiYrlfVQOSrn0PVHebwMZv2zZGpFSs8c+sSzRd2F yXzBkfranPOI+qJHp415Hz/3fmhUmkeVbiIKakwes9I39LCZR/+aFU67Mftx 0Ywh2H3mEbf1m3RfZr8NW0dMUpLmUaO3lJYHUw+8vreOyphHBYyJHF2mXgV9 ceaNg/MoW53MOsTUU7Z+/PN5/gVUQtTqXmXq/Tjf5CC75gLquPH1307mPNie JDUmOy4gURt9ezkzAq76zthR/RfQOctNe8yY8+tzMf/+LWMBNZ+3WjLfR8Dh fWmO5+sXkF3eZIqSEQEfKIs/N0wsoL9CK/+MMP3xYjaze4/uIjpubPKLRY+A qYJF7wPHFlGtzeeGMG0C9C5aCDgHLqKwGZ3NU1oENPZP6gfVLCLRqbr759UI 2JZu3BIzvIj+WI7ATRWm311iPV7wLSF+/el9F3cSsPZdL/GT7RI631JivCRH gFlMpPqv60so1e9KVbQMATEHf9dNxi8h1YotoQLM90OuC10Q6V5CR8c28r0S YfqpvPHwCY9lNKz3qTeEg4CU6/J/vSKX0XhAZa86KwHD6j7BIYXLyNIhWrN6 lQH+L7cVvVxYRqLVM7XBMwzIeXZWcC54BXX7hlS+6GbArEPFC66sFVTo+NLI 7ScDsDA/kvjI3P9YIsHJzIuWB0UXsNAqMj0X+G68ngEk/7X6+0mryDzyz5ej RQww1z10Mom2ika4UKdyHgOezqcv5veuokFhf72eTAbs9DRTbCGvodGhwr9j 8cw8OxFzV6pkDVF8h8QzmXmXZ0TBxV/WUaDu49Q7hsz8Wr/1/cPkOoJhu6ob OgyQ6Trz1oOHhJ2U1yg26gzwSCi38lcm4TiPDYvZzDxm3Xz8doYXCVs0/XKZ XaOD8oaX7WPrJPxwb6PDchEdRnnfdExtYsGvE17cRtl0yNkMXXPyLPjfTM2K 48l0UNjR9HvNnAUbtFwL0Amjg7Th8jB/HAt2fhSjYe7E/F8CzJdVdrHi3iAj vZ75amgIPbyqbsSKr26IGZ0brobISJd1LXtWHEZ99maosxo2pnixoVus2Ly0 6ZEboxrY3yXyWteyYmmRX1eqIqphYXlE4tJxNrzF/Mz3X2LVUMI2t83Li8mz 6ptruKvhGi9J2juEDccdKjkTvkSDKfEtcv65bFhDts/p5U8ajGjrKUUusGGa TIf7/mc06PKO0MuP2oB3JOhT5kVoQEwrOY/T2LFYd4S7VV8VTPQXD+U3suOg q6fQMlSBRLvedc8+dqzS8czgfGIVXKFZRE5ycmADeWpZzKEqkHrgUT1txYGt kgVT+CoqwVchV36hgwMrKpkpxwZVgJrjzjHSIicuKflhy91XCkctinyrebjw XCG3vURpKYQhXc4gSS58MSgpcCK8FLrkzaXZMBeWTfxr16deChFT52zYQ7mw Z5Hq6OTttzAYnlPCLcyN6/11OzO4SiD5Hdl/kxoPdg29XOc+UQj7Qhsybhjy 4FH5dyJ/qgph1Nq7vtuWBzdXKI/KhxeCTg8hnH+dB1d+vqa6IFcI39mO55pX 8uCOe9mivw4XgKDZ07ZgU168q8ag08MxH4KaWDXnnTfiWu17F0Scs+D04M/B n/f5cXdCM2jyPoZMp16iKokfB5yqjrgxEQX9n4ZTU17z41SbKD777EhwK1h0 ONXKj2kOphuyNMLBzVe0blhGAGMpeaVbKkHgttE2e7FUAJNSxeMyP0gjTbE/ xeFegpg2sgennYhGu/WOXst+LoS72RU9fj94hTaOJGf55AhhMeHl/t9q+eh3 fM9P0yIhPNH6Uu9Iaz6Kmncz7CeE8HFt20rHqNdouPCywI5BIczFHrA1sLMA JZNDs5+pbMKSR9McNt4pRpyihZ2RFZswlZtneMtyGWqb5DS53rIZ5+YXKnl/ paPE9trf8VQRvM7zen94cANqvuKaHhUlhjc4s+zkfvwD5ftUFYnRxPGCicvH Z8HdKKtgZ9T89m14plG95PDzP8jI4d/KM4elcGja1gPkvmG0LmbhFNspjQ8E 28fyR02g2E7Hs308sjiTt/J4fN80IjmabF/asQN3KRrlZevPo4UL+joVdnL4 tefa8T2yy6hae/Oa8WV5zJ0bSPvNto72ObfaUsMU8P0KrYwXISzYUTxD4HvJ PzinXF/A9QcbNnh40MvgmyKWKBPTfSbDgQsTOfUPsVFwXrTKrtYqLtxDyo37 rLoTSz/NqNb25MU9kqrPNu1Xwo1F8ybtm/ixZ2MlO5uPMl46ipbmQgVxgwFZ tDJaBZdP12V+WBHCo6x3yruyVXFMzu62RZ/N2OL19InW87vwtn7dMk4FYXxf 50n584VdmL/O5UrzexEcJaT3wfCRGm5fawj1jhfD60aN8rVS6pjXujV/zVkc m8u6WAW9VMdjO4UL7ypKYhfLSfImIw28f6TRPYyyHf9suuIY0qCBrTuAZ2qj NJZ6sajb4K6JlZ69teiUkcFYwXvAirQb+6/brTnpyOJ6Ul9/QcRurJWdlFts ugNLKtrHD8tp4bHZgDHFq3K4NedtCmeRFv6unXYlIkYeX2wTuORosAe3Bz2c zCpRwJ/tLkwGtOzBLVVRxwsW/8FPdpbXRJykYtPCC3V9KmTcOnQ1hvU0FUfy 6Pk4aZKxSJbqCZ8zVJxrE1/ZoE3GT+X+WzrlQcWnC0kcYMzkbVHKutepuDM/ KDHNiYzjBNyih+5R8Via7be7IWT8bFrIxaSAii+7k89WdpFxR8GnnZVFVHyl sqXWuI+MJT1DF9RKqNhsXRA+D5Fx0ujKo20VVHzLTtOjZ4aMk/8MEDMEFffp qdQJ8FJw6vcqSvoPKv7KPv4gbA8Fdz/xmRf7ScUq9vdNxfUpWNpOg3jYScUn nxY/zTWk4OcNWc6+v6n4UP+b2UZLCk6ri446NErFu4jzJQquFPw71Mq5ZoyK UbSfZJU7BcuacFP0J6lY1kZazO4SBafT/RiKc1R8IUWw4Y4vBfcFaEclL1Bx i7JLhGQABcuhmaNblqlYKFev681dCnZdfUW+v8qsF89+bx1OwRkV7nPr61TM 5ZNhOBxFwf8DmX54Yg== "]]}, Annotation[#, "Charting`Private`Tag$19178#2"]& ]}, {}, {}}}, 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]], ImagePadding->All, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotRange->{{-1.8437129832618204`, 7.811671481800942}, {-1.6556495885057483`, 1.669801841267314}}, PlotRangeClipping->True, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}]], "Output", CellChangeTimes->{3.824181006237868*^9, 3.824181045601217*^9, 3.8243500384958057`*^9}, CellLabel->"Out[22]=",ExpressionUUID->"5f143463-546b-42c7-af06-bbef2790a403"] }, Open ]], Cell[BoxData[ RowBox[{ RowBox[{"datk3", "=", RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"data", "[", RowBox[{"[", RowBox[{"i", ",", "1"}], "]"}], "]"}], ",", RowBox[{"data", "[", RowBox[{"[", RowBox[{"i", ",", "3"}], "]"}], "]"}], ",", RowBox[{"data", "[", RowBox[{"[", RowBox[{"i", ",", "5"}], "]"}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"i", ",", "2", ",", "30"}], "}"}]}], "]"}]}], ";"}]], "Input", CellChangeTimes->{{3.824181106665169*^9, 3.8241811421724124`*^9}, { 3.8241812256065536`*^9, 3.8241812263399553`*^9}}, CellLabel->"In[23]:=",ExpressionUUID->"c057abd7-a297-47e4-8b50-7638655aa1eb"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"rovina", "=", " ", RowBox[{"Fit", "[", RowBox[{"datk3", ",", " ", RowBox[{"{", RowBox[{"1", ",", " ", "x", ",", " ", "y"}], "}"}], ",", " ", RowBox[{"{", RowBox[{"x", ",", "y"}], "}"}]}], "]"}]}]], "Input", CellChangeTimes->{{3.82418116007648*^9, 3.8241812007146606`*^9}}, CellLabel->"In[24]:=",ExpressionUUID->"de969488-0423-4709-b2bd-a3f19ac9788b"], Cell[BoxData[ RowBox[{"0.2147491166338567`", "\[VeryThinSpace]", "+", RowBox[{"0.021873811613322563`", " ", "x"}], "+", RowBox[{"0.07489964296035968`", " ", "y"}]}]], "Output", CellChangeTimes->{{3.8241811792274666`*^9, 3.824181231324602*^9}, 3.824350038527069*^9}, CellLabel->"Out[24]=",ExpressionUUID->"466cbae2-3591-4a2c-bd4c-d846e2506aae"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"lm3", "=", RowBox[{"LinearModelFit", "[", RowBox[{"datk3", ",", RowBox[{"{", RowBox[{"1", ",", "x", ",", "y"}], "}"}], ",", RowBox[{"{", RowBox[{"x", ",", "y"}], "}"}]}], "]"}]}]], "Input", CellChangeTimes->{{3.8241821253127513`*^9, 3.824182168072093*^9}}, CellLabel->"In[25]:=",ExpressionUUID->"cd355dbf-75f2-4bcb-97a6-d7985e97cfa3"], Cell[BoxData[ TagBox[ RowBox[{"FittedModel", "[", TagBox[ PanelBox[ TagBox[ RowBox[{"0.21474911663385665`", "\[VeryThinSpace]", "+", RowBox[{"0.021873811613322556`", " ", "x"}], "+", RowBox[{"0.07489964296035975`", " ", "y"}]}], Short[#, 2]& ], FrameMargins->5], Editable -> False], "]"}], InterpretTemplate[ FittedModel[{ "Linear", {0.21474911663385665`, 0.021873811613322556`, 0.07489964296035975}, {{$CellContext`x, $CellContext`y}, { 1, $CellContext`x, $CellContext`y}}, {0, 0}}, {{1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.}}, CompressedData[" 1:eJwByQI2/SFib1JlAgAAAB0AAAADAAAAicxEd6b1F0DmOI25nXbrv+K75e5F Itc/CJk+6hB26r+7Kpnumyb4P8XcZB8IwvA/pmm5wXzpCUA+3M+sFA61PwaF OrLSt8M/l9FahbUw+j+YLmZso1vmv3FqNhnSNuw/iUZIT+EXH0B/3HnnorTT v9g8WidFk6a/UkH71JJdB0DEXUmAE2vGP9/KCx0DaOc/Vlqo+VrOHEAqyiCP DYzzP8mykdU2q9M/0uGEiKK2CECzpFW5sPTIP36+o5K8jd0/YqP7FyzrF0CW uITgSZ7yP2bEoRi5ouQ/nlj4boas9z8d2WoTDjbuP1wnDdEw49a/P7kVzyY/ H0D7srAigrf6P6mbhCLAtZW/KIRY9g3o+r+gnPVHcKmQPxSeXQqpOOk/QO5t b3YIAEAWMLHShYDnvwpktBbPfPg/gALRwJnZ87/Th535/DTuvzCcntN+GuE/ LdAjAsh0FkC/iDOfv6HtvwPG9FnDZuY/sELPcdDV7z/rSURsin36v7XInJbj DNI/MB9lL9l//b8/shWGIE3jv4/Po/RADM+/fw+Lf24aF0AOEl3JIqjWPw4Q GRIWEsy/0HfkGIENH0D/6yAPPzHwP65rl7jXFeI/yMpnHyW44b9dLixHESO6 v8q4Z/40ote/SHdub2NS779qCYJ2myXrPySR4R0fv+Q/8Mf9SakaG0B0J1OG ohD1PxcRIlYgd+M/AIBvkNTioT/PlCyQbpLeP+75bhNZhLW/GtoR4Xki8T/L PAPBxrjqP63Hpyf5nNo/9rdLD5xpHkDr526NaQftP6v5/WsRd+0/wIAuPetq 2L+3ipoTL37vv9t9Jyd2IQDAqFusqzLxDUC1lyVg2YrXP9375yTIxeS/ze85 i/dfE0BiVYDE6bWjvyQDynIZT9c/jzYLCAV1F0C2os6AA9TTv9IEFLaqFeU/ QvFiQA== "], CompressedData[" 1:eJxTTMoPSmViYGCQBWJmBhj4YN95xqV82Vdxh2cWvTvnlr3eDxPnmGn3SqDs 1f7dWjPfzVb7YQ8TX5a582DNS04Huzvn14jwbYWLT78Y1brV4Jf9DL20nMXR z+DmdLp5+D8Ul3eov1P5fNGWy3DxIMffVybFsjscifVsEM4+BjcnLGrFz6hz Mg5apxT6eXs+w8UvPWzpWLSNw2HzktCdG76cgIsnLf4trvNa3GHajpYHnvM+ wcXnRfzIa1vz3V72ZpYwn9k7uLj9TtHzavbyDr83bVBq2v4LLq7REvGN98Wv /QvmfHUvWDkBLu7wLje/jIPBQcxg46XWhudw9zcwXTww8+bn/Zfb5/78Y/IO Lq57QZnpRImYw/4O4/n7F76Fi29wOl944ep7+9eeLjldtb/g4gbyqfo36//u t98k2qbg+xguXs/fXZ8nJe7AJxR7UmnFNbh7LpQ/kWjklXf4/1qB397wA1z8 xKl0edUdD/fH6um4CyrvgpvjUZ6Xnxz0fn8WZ1PZbNXXcPUfjv/1XCkl7VCi Hty2SOArXJyhIX/ClUcL7c9P0ZmQN+keXFzqluDDSqWP9qdtmA8e2/EKLv5t uzf/nEw5h9fP83oz2d/CxQ806Nm+zrqxf3vXLGH9uvdw96yIXrPa6COvw9bp qgk3u67D1Z99b9n9PV7YISm04cjLrYvh6vvNuDlYS8Udti0618B85fJ+AIt2 Dc4= "], Function[Null, Internal`LocalizedBlock[{$CellContext`x, $CellContext`y}, #], { HoldAll}]]& ], Editable->False, SelectWithContents->True, Selectable->True]], "Output", CellChangeTimes->{3.8241821718627787`*^9, 3.8243500385598955`*^9}, CellLabel->"Out[25]=",ExpressionUUID->"9ad1cb4b-9d72-484d-9614-ff7befc23b2a"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Show", "[", RowBox[{ RowBox[{"Plot3D", "[", RowBox[{"rovina", ",", " ", RowBox[{"{", RowBox[{"x", ",", RowBox[{"-", "3"}], ",", "3"}], "}"}], ",", RowBox[{"{", RowBox[{"y", ",", RowBox[{"-", "3"}], ",", "3"}], "}"}], ",", " ", RowBox[{"PlotStyle", "\[Rule]", RowBox[{"Opacity", "[", ".5", "]"}]}], ",", " ", RowBox[{"PlotRange", "\[Rule]", RowBox[{"{", RowBox[{"0", ",", "2"}], "}"}]}]}], "]"}], ",", " ", RowBox[{"Graphics3D", "[", RowBox[{"{", RowBox[{"Red", ",", " ", RowBox[{"PointSize", "[", "0.05", "]"}], ",", " ", RowBox[{"Map", "[", RowBox[{"Point", ",", " ", "datk3"}], "]"}]}], "}"}], "]"}]}], "]"}]], "Input", CellChangeTimes->{{3.824181250988055*^9, 3.8241813060041113`*^9}}, CellLabel->"In[26]:=", CellID->280137527,ExpressionUUID->"2c9f55fa-3aee-4a71-b1f6-419135967f31"], Cell[BoxData[ Graphics3DBox[{GraphicsComplex3DBox[CompressedData[" 1:eJyVnHlYDf0b8Eur8NhJSotsKXuFMAdZEj1aEIVIlC0SkiihEkIqUVGJtGrv VKfOad/X076hqKRVi6XU69Lc97y/8XRd7/v8M1efZ8y55zNz5nzn/t7fW/qo qZbRGB4enpMCPDx8v7dVRpYZw8NCHNjykP/t3Kfas92Z/y/O3v6PlLMs71/8 mHnY05gzA2w63/HnOL1/8SN/9v/yF9f/w2v+4iP/pa2j83Mj+xN0fmrk+MiX Baie2y1gS/w7Eg9yqVXv7kl6OhPGI/EjD5vq+cFN0ZNIHjlfBnD3K/Kz7Zt9 CY0RP8gNPjumb4ryh3+PXGr/Z9Mhm2A8Lnile6Zz8Ezn4JnOwTOdg2fgjDI5 rlvtKQI8AzcwVz00Tc6RAM/AmbPe3bwR6kaAZ+B+g7tOD871JsAzcOPTwTOY XX7oGbh8rUjyhcQA9Ay8V93k1FLHUPQMvLqu0fFiUDh6Bp40faoBd3IUegb+ fNcmxeUWMegZ/NE90zn8DVspXtctXOXrBHgGXikpM//0gkcEeAZuMFxv2ch5 RoBn4Oad+ScUFHzRM/DVh+WnfP7xGj0DHyxwZPllBKFn4EdfmK8MUwtDz8BV K14K/xMWgZ6Bz5/IrTs1Ixo9AxfZNiYy2yoWPQNvvb7cYUFjHHoGXhBjcPC2 Ggs9Aw/teLCi8W0SegZP5wRkJArWuOJ1Bf79Y/35LdznGAdwRsMuw0NKfugZ tsJawRPE+ALQM/C8ZBFmWWEIegae5b4qfLtGOHoGHlhkaPc6KhI9A78n/FiP f3YMesb4GSnLjt5gomfgWhbdApzmePQMfFWYVI2ERiJ6Bi7a8m/Y1Sg2egY+ +ICdcnpCMnoG3rF4X4gHIwU9A6/P7HiScyEVPYOPSlX5serjg9AzcM8ox0jB qrfoGfgy594lH7QiMD7g03Lm8hNxUegZtv282lWekrHoGT93jW3oz9tx6Bl4 /Pnwm7ptCegZ4wl4rxujlYSegXO6hGY66nPQM/Dwey944x4ko2fgvguV25pT UtAzcJe0gvIZ/anoGfgtg+PJWxalo2fglwZ/BZnrZ6Bn4MfdXd1ePshEz3De lqmNNyoSo9EzcP2BKfsUZZnoGfiGlZvkHzvGo2fgMqfO83Z3sTBu4Pwvvcs1 9rHRM2wvtDfvKa/noGe83+9YMwSmpKBn4HvmzVy8aksqega+LTl0uqFFGnoG vvrgVh7noHT0DHzRj7pWTn0GegY+2/ViWefkLPQMfNzyCZw5W7LRM/BfeX6B uyxy0DPwduN1rlZBuegZzs/h2HLrO32J6Bm4osaywB4FDnoGPr8100XmSDJ6 Bi5qd9ha0yUFPQMfK/PNxCYzFc8H+M9EJ523P9PQM2y/7J9P1CtkoGfgtX2J iyYcyUTPwAse7Zm2ziULPePzXqF96GRmNnoGHpZ96/PTnznoGbivkXhplkIe egbuzBuV9M0gHz0Dv+WlHjDfpQA9Azdf0/h4T2YhbTyUti7XlkjympFK/O/4 IG0da07Fmzy1NOJ/fxfT1oXEn308YJWOnoG/2Ct4XS4sAz0Df/jVy3h/YyZ6 Bn7DSVHbYUY2nidwM7n89bFqOegZtoYZxxY2WeWiZ+B7jg5OmR6Wh56Bbx16 /GtzYz56Bq78bHGL2YxC9Ax8useRz0WyRegZ+ASTkEPGSUXoGbig8g/u8L5i 9Ax8iH+L2pNu5ByIV1u7iXVpRSZ6Bq7aec3/lVEWegaueHe6c6l7NvU7RPIF C0Ks+PJy0DNw0VTVEyuGc9Ez8LGHazWPrMhHz8B//ryw7qFRAZ4/8C9u4xaw 3QvRM2zPPi0W/mZUhJ6Bnzghcd1puAg9Az+saNIz72kxegauyxdtnLiiBD0D 313MU6+TV4Kegau92KndZsRFz8A3nnHPujmMnANxVc+9n/CvRi56Bp7Lln19 /UYeegbO0mM9DInKR8/AQ79pX61tLkDPwIuy+yJuTyhCz8CznmxcKOFfhJ6B c4zue0UxitEz8LiVVVN2VhejF+ARvPMcGi+U4N+wDSw898tyAhc9A3/pxTKb 4s9Fz8A9Twm3BDBK0TNwlzU6BzdWl6Jn4PeFvEsqL5ShZ+C3y75sOzehHD3j 70PvyviFJwvRM/BFWUYlQRpF6Bm4jFv4ts0tRegZuNixX6zqG8XoGfjUFWor zGaXoGfg43lc/cdGl6Bn4PwF78V9NLjoGfigh7zz6hYuegbeb2IhVHSjFH0B 71BOszoxuwz/hm2TwKSvQ1Fl6Bn4e67eCTeNcvQMvNLHv1ahpRw9Ay8y7dFM v1GBnoFnrScy9WdXomf4HPOjZ2p5Uoup9yiSn14Wp+muX4KegRsN8Wcu7S9B z8AP5e1el/mAi56B733mGX5oUSl6xvMzbpnfn1KKnoFvV1rleV+/DD0DZ/Db TJ7XX4aega8pybVjPShHz8BXeM8c1F5UgR6By501PP8lpQL/hu3cdW+bbPUr 0TPw2SIDemL9legZ+LTKrcXhD6rQM/Dxr523qi2qRs9wPGYOR6+9iIuegYe5 jy++dbIUPQMPOK67VZy/DD0D913llxDpVYaegT8b07VMXbkcPQN/XKTyuqGo HD0Dv/fcfrblyQr0DPzWae7DyfyV6Bn4tbWSggFelegZ+CXhU1cZylXoGfjZ 8piuiqIq9Av8hN+Y46Ynq/Fv2B4206gR5K9Bz8B1Gc92P/fCPAvy3f80pSsq 16Jn+HeDK6bVVNWXoWfgvTwGu89blKNn4G0FQenCUyrQM/Amz29rvYMq0DPw +pObw5S3VKJn4OWrH8wrrK9Ez8ALBWueHbeoQs/As0rnTxqaXI2egXN8zW67 BlWjZ+Bx55J+ym+hni/AIzaInEurp74PwAPH7/2kZ1GLnoH7Vvsc6Jlch/vB 1vNNe6FjUB16Bu5yac0WmS316Bn+/waPEwcy2ioIWr6OoWQSWXjQrpKg5esY S5WHVfskqwhavo6xUEA9/l5cFUHL1zGkuG5LZbWrCVq+jjHLp8Evoa2aoOXr GFNMl4hp21HjNuAi6y0ftErWErR8HYNvXAa/bVwtQcvXMQYrJ1vO0q6j5+sY va8Pdoa11dHzdYx284Bj2+3q6fk6xqdNfVXvJN/R83WM+kkb/70c946er2Oc Mt161H7Re8L50Dt9WTVBDmwhXwT+6dxl5G8G8IUf+HYuWhSOxwcues1DSVc/ Ao8P/06swLDMYwX+XiCXaE4UK/pUTsDfsI3bvD5n53A9cvRwteeWNB8VPz0v Stufw5COf+YtFkjfn7HWdsJ05zX4O4WfGy3XeEt05ztCqSF4srOsEAe2cHzy bwbwqPvfb74xeUvfnxEc9Wlm+IMKgrY/Y/tko0yFALwuox4f87qJmrcLdwXh 8SFellO8svxUKn74dxn8TL/Hhe/o+9OvL8ZfMm177CmNMHo8jCXJzmvVTaj4 4d8F93le0JnxHr8vE97dEdveSeVjhb/vTotf2fVXnha+Ryqrx+3z7BRADt8j k0f3Hnd1UvcbfI/cWycUqXZR8WvOOuf9XLyOoJ8XPAducAWM1Duo/KfiwCF3 jQq+v/Ki8HwIk7f3edExBjk8H+pvC9f3dPAhh/PRtry18Fs7z1/flx2bBCu3 1AyzgTuLers+v9/G1mUwvm6qpjz0yngc0u76wL4+Ofrba2/Kg3607nOpnfns lw2LfomcoDzIb7p0VVQrnsiOfD7GVIE63+SrzffEC2uIzltThbk9FE8ZOF0b weHlwBZ4jNU+Cc6KIXZL3ocPM+yp823mLbsh9vE7e8Lzvc2Wu6jzFbXXajJ3 7WGvNM1tq59Kxf/oUudl3YlCnMv7bxa3rqQ8yK1ZEihgzM/xkvtervGT4qNd r9HiH+26j+Zh5L+/75/RfI52H452XUa7z0e7vqPd/6P5HO1+G+26jHbfjnZ9 R/tejHafjPZ9Ge36/v9+L0a7f+bMCsofHv57nsgwr6Z0ePjv+Tjg9P13D4sy h4d//TW/Bpy+f/Wf/b79tT/wv+an/nxu91/71/75u3lUDseZskMrKcX+MvHu D68YZR6QyaJz2B+Ooxx8YaXZw3sE7A88gpzP4o7s/9f3Djjsv/sgf0f2tBdE +UicyM2LpsnfSXxJHBk5XzyOE2fZs3kCTshhf8JswZGQLn+iYsQb7t/wcr1y jfET5LD/hGlr3YrnBhO7Rq4L7n+l+ajP3MIXyGH/tgOvP1kuDiOOjlx3/H20 n54mECPmhxz2Lw5ayjNhSwQhMXJf4f46seVrq3e9QY7zgINMsReHogi4D+n3 P9xvwJ2kK7v0npsTcF8BH3oSk5c0+y4B9w9w9wc2RQt6XQm4f4Av4b5ae+7A cwLuE5wXu2ukpW/wEu8T3F/Bwt7msT9ed+A/yPk1uL7As855dWf9eIvXF+dP xuo+vjQjAq8j8GUHPoQIL4vC6wV8RtDJrGdqMXhdcF5voKdB3pCJ/oF/2Hnt V5JVPHrGeLwERTXdWOgZnmeCatvsZ3h7EeAZ35O2xlgs5XuJnoHPbskK0Vby R8/AW+7UNFw2CULPwCMXd8z09HyLnnH+87jN/PfN4egZ+KvYsRvNeKPQM/C7 5PwaeAZutl/8ktsqJnoGrhv46uFCjXj0DHzDwJKg+BMs9AxcdiczfeeNJPQM /HaB1DnTXRz0jPOPl4yurT6QjJ4x/ycZ6Mh7IgU9w+/My6YNG0yJt+gZuHLa mzi1uHD0DHzO9BWlNSWR6Bk4//GEjjNt0egZeGuM6lgeQSZ6Bl4oVDDXWTIe PQOP1t23QXYNCz0D9yDn18Az8I2/otbIKnHQM/CoVz+2tm9KRs/AF2hs0In5 NwU9A3/Wb3vEWj8VPQOf8CLz7HaTNPQM3GbbeKvJl9LRM/Cezt13qm0z0DOM FwymnfE0qYhFz8C3GPXHDHTFoWfg8jHWxfdFWOgZ+BShsW2SsknoGfjgYjW+ qjkc9AzctPT+JN/FyegZ+AerEolTq1PQM3Adcn4NPAPPytdb/UszDT0DV7nk vSXjUDp6Bh4655PWg1MZ6Bm4dOYiA12LTPQM3MX07Bnp21noGbiQaKRl66Ns 9IzzlZxv9pHPc9AzjONiD9Tl3RfioGfgcnwy1XunJaNn4F5Bx5slpVPQM/BJ OkG9LQqp6Bn4zcFO3oi1aegZeL/fqolXt6WjZ8wv7roirqqTgZ6B15Dza+AZ 877PxyiXn8lCz8BTtm5TfWGZjZ5x3rDzrqaxfQ56Bv7mSdGh5S656Bn4bMb0 0z+989AzcKeW/VdSQ/LRM3DeR8/t7sUXoOeR80hbt2Hxrdzjc9PQM/Awblbl 0mXp6Bm4rNWEpu/rMtAz8CeyWj3JapnoGbhIvhvP3b1Z6Bn4tYs1E3QMs9Ez 8E4JqdkS53LQM/Cj5PwaeAZefjZA8e2dPPQMXG1mxyYLt3z0DJzFXrF748sC 9Ax8mfHlgyJhhegZuJbwoWiTQ0XoGfhdfZ51BR+L0DPw9DDflBWnitEzvPdk DMjlEEQWega+2s+0QnhnNnoGHrwz6mOxbg56Bi7Z9737mVEuegbu7LV+2NAs Dz0DF9hqO17BOh89A7/ckTGr/24BegbeSs6vgWfgbyUXiqVpFaFn4C0XcrwX VhWhZ+AyWacX3D9cjJ6B64lPDO3+VIyegbueC1+193QJegZekKadEP+1BD0D F57Vv1HyChc9Qx5uV15xlqheHnrGeS7zGeUfTuSjZ+ArJfQaA80L0DPw1+kv ui7cKETPwCcof70+Z1sRega+9a6LwM38IvQM3Pqd0r1m7WL0TJ9fA8/Ae+yv Pg0zKEHPwOVrJaSmN5egZ+BGyzivr5zhomfgL24dVajv4aJnzFNW8kdtsixF z8CnKPiv9ecpQ89YH3dDLXmcfRl6hrzmSQ1Wo4VKEXoG7ud76GRdchF6Bl7X z9O9cXsxegY+Q/3l5dcFxegZ+O4XW4ZE9pSgZ+COPc23TGtK0DPw1G2O40qP cNEzfX4NPANX6ioQ9Tpbip5xflj1/AvevlL0DDzAfer841fL0DPwxrbo4Bze cvQMXGKj7sqlDuXoGfhe159xj/+pQM/AH3z2ZHx3qUDPkCcOiZloaKRWgp6B N4tEfM4uLEHPwKUO65xbspeLnoEfiOzvd67lomfgj4WeXvt2tBQ9A8/XU+HX /1yKnoELhdU5ckzL0DN9fg08A7fUlXG/Y1WOnoFHBqfN6RhTgZ6Bt/OceKV1 pwI9A5+/Z6x87MRK9AzcICAoYrZbJXoG/vTXrjU24lXoGThXs4v90bcKPUPe vXuOYYPmvlL0DHzxBQGTmLpS9Iz1cZn+nWLHytAz8Oezd1yybi1Dz8ArTNsG G8+Vo2fgk9Ocbm7/Vo6egauLLhcJuVaBnunza+AZeBLn4sxLjpXoGfi3aaLP qydVoWfgy03iZYknVegZ+MlE/aCXEtXoGbjf5OHlwn7V6Bl4nZEP87RcDXoG PjN+M1EcVoOeYR5D0T7myAajcvQM/GyNbovvl3L0DPzN0oGzQmYV6Bl4w02v vlPfK9Az8NmVhFXR9Ur0DFxHvmGMokAVegbuZHPrztO7VeiZPr8GnoHzLsp2 O+pejZ6Br712SiJzTg16Bm5ePMFv8asa9Aw8dF6Y3MPFtegZePMVrfDe8Fr0 DFyqoFd5/+o69AxcT+ZJUmJSHXqGfP7lzrEf5C5UErQ8GyN8c/CJBz8qCVo+ jdH6RKOjx7qKoOXNGLJtXea6gtUELT/GOMh4PMC6V03Q8mOMJy6KttJTa+h5 MEZxS4Ww3dMa9EyfX6PltRiqj8Rn/Pu6Fj0Dv/YpyTNSvo6ev2LErjkyVzSy jp6nYnTd5wu0WlNPz0cx5BpeLfvArqfnnRiGSttjt2x9hz7/d7xM5Yu6qie/ iTlD5ZPBZ4qnhe2ZGoqDTxfavBvtfuO8oOX3pMjPjbl3sLPr+zP00E1+buZw zQGDzS/QQyr5uSfXKDQ2Z/igB1fyc3vN2twl216ih+NSW5VrYgQ5VsFBGvsm v0YPq8n5I76mk/wPlN6gh0ciF39ud+b963wVnTa9jTkzhtP96szrra+08f4R 2h1w50zNGE6Qouu+iVMvUffP5EnHZNX4OB02mbbHn9/E+yeIe2lDTQwfh/9E 2v4tK+/h/WPlWifqLMvPefjaQHTKMWf685DTRcuPPSbjtBTeYVb7JYTK25DX jdeHf5qjcBh6UyLjT1v/sWPe7HD0JkzGf6c6NTtZIQK9VZPx77r80u8gIxK9 QfyTpt20/qEVhd/Ta2T8ZWFHD7gaRaNP4e/XNGTVBtlXLbwd1t96it/T4Kvq fM6yv9gOX+b0Bhd44fcUtupvC5Y6jfdBz722TafP1AyxS1ruf0pf/hI9uwtG SdfEDLP3y+zy+LX3FXqek844JavGw3mvN15T0cofPXfa+W+pieHhGLvmCp7x CaD/vrPtaPmxcWT8O1+ZKXkrxKLnUDL+SZu0Jq9jMNGzFhk/t355W4VWHHru J+N3vzo584JRPHp+SsavL9rtM9EiAT1D/FLRRVZBjiz03EXG/1EzbN82r0T0 3PHn+9LHPnj9S5Lt8hD0PDJv3M9uiA00j9/7Fj2PzIt+Y0d/XzX9R2IYeoat heu0LpeicPR8/fO2q2dqvrNVVvTmLGuMQM/SZ6Yvq4n5wR4q4L7K64tEz+ld DR+3O/9kp5yKtDEWjqb97vSy3Wj5sW4yfr2tnJVaRmz07ELG/7D7X6FvKhz0 vJqMv5vN7lVN56DnWjJ+HaelDc4ayejZmow/Wv9F4fuKZPQsQ8Y/c/HExCVH UtBzBhn/lR/XA61aqTxkwJ/r3s5eZ5Cqf6EoBj13/bm+HWyeX77KExtj0bP4 n+vYxU57ajslqI+Jnjl/vtfdbHulo+1bheOpfC/kI7kbsxrEEtDzyPf0K/uf c9Ivryuw0PPI97GHXTKe97oYIxE9m5B5Jy1afiyMjD+6x07UtiAVPfeT8c9M 6Rco2peGnueQ8Vs8PN4j8SENPaeQ8dccKn9/6mQ6ejYi41+vsLUgricdPUP8 LwaiE4SuZaDnYDJ+3px5AXsEM9Fz25946tk7eCcfmCfMRs9Jfz73A1voX4tn BhM46Fnwz/Eb2CYSLfahbhzaOOojO/fLvouDksnoeeT3ooktH595dEdAMnqG rZOD8m73FSnoeeQ++czu2uu/vimBykOehvoaWn7sBxn/ujSFmXqtmeg5lYz/ ubMXf8CFLPQsQsbPc2TC1/7BLPS8m4z/6NJr71TtstHzEzL+tF9tec4Tc9Bz HRn//Dz9+PfuOehZlozf4Vme/xKZXPS87E/8QWx5zbdBX16komedPzyB7SQp +XTNojTif+cf09hd7U529hFp6Pnkn/1z2VqsoQtlKunoOe3P+RazIx3PHpmb no6etf4cp5Q9fX+9xnmNDPQM28sLNNaxKzJo+TEmy4CWH3Mn4091KZ2+SpDK j9mQ8c8zVOWzfZBH5SHJ+O2WR3UViuaj50tk/K3Dc+slfPPRcxYZv3rB49xT iwvQsw4Zf4gnX1xcVAF6biDjn3jqwmuhDYXo+T0Zb5T03sC0hEz0rDlyHGJG V/qTKVuy0PPI86GYuJykeNugIAs9Hx2Jk6i698osdF82elYdOS9CRW+6weD7 bPS8e8QD4bno9q4dJ3PQ8+oRb8TQt9617j1UHtIA8l20/BhsX0WsdxScTOXH tpLxlz/tswnZQ+XHmGT8QjdCLus8K0LPe8n4VxsbnR2oL0LPKmT8Jv9KGPnO LUbPW8n4nymV6akZF6PnOWT8eRL3tbqCqTzk3JH7nFD5OvjGqyIXPZM+CC/O abcvBnno+fHI94gYdqq9uaY1j/jfefOPxJGDO8/bX8hHz/wj31MiZTHrUNlg PnpOHPleE7I/F++ca1eAnttHngOEXZbHmvMTC9GzIZl3YtLyY+Jk/J/FHo3t mUPlx2A7a4wazzNDKj/2gIxf/TPPN8abEvS8nYzfqojZ3txWgp7HkPGHxJ77 6LSci55ZZPz1zxfWKF7ioudWMv6Jdu+La+OpPCT5u0OkpLz0v9RTiJ5HxsNf CeesOzuObqDyY4Ywfn+7cePYm0W0+eVuotfth3JYZhF6Jn83iXnXw5fsG1+M nsnfWWKvkcm8od3F6Dlw5HeNsNspLf7KlcpDqpN5p5+0/NgbMn6Fmx8d3slT +TF+Mv6DJz2t7c5T+THYOmnqXFKIKUXPSWT8nNXjz5T+LEXPYmT83ZJphleJ MvTcScYvLWR1QOYWlYd8Q8av3bFSMzuLykOmjYxDCD+1eVx/ISo/JjUybiHK ltVla+yk8mNWI+McQkjUldP3sAQ9V5LxKg/vjPUsK0HPiiPjKMK4iT90sxgX PT8aGXcRz/JZfq2HuOiZHGcSOVHmHo9ecunzy8QGWn4smYz/3Bdl4by1VH5s Dhm/T0nnkJl1Ofq1JOMvifPvm5VWjp5hy+dzuI0jXIGeV5Hxr3KY2XhiVwV6 hviNTAur/nGm8pDtZPxue+2LosupPCT5XsBoCbfQcplO5cckRsbhjFlPl6mp HKDyY24j43Zih00L0fC8FD1/HRnnE1dPeCvdaSyl8jZkvMEaugrLFpZR74Mj 7xFEneIk2YrTZehZaOS9g/hHIkvsejiVhyTrEBi2tPxYOxl/lPZde+Z2Kj8m Tsb/ae3m64fvV6JnFzL+GTID5oIllei3i4x/29jIUyEzqtAzbC26Th7V0atC z4Fk/G8qZPYPvKDykIJk/NVJ1f/6fqTykOR7LkNeLK/YZi6VHwscea9k6PPe ylpgTOXHKkfeQxlOLSrsguBy9Dwy3hvDYBf2RF/sLkfPq0becxmdMUHB4koV 6BnilXpu+DLVsgI9k+/7DK3bs5+dZFN5SLKuhpFBy49ZkvF/S6gXfLWXyo8F kPEvfOn2S92jGj1XkPEfcNTo/fquGj0LkPE7nhf88lS2hrqfyfgTdJM+MExq 0DNs24hLlc0hVB7yIRn/nAVLCp2+UnlIIb+pbdudhRimtpKaZ5ZT+TGoh/U2 qdg27RKVHzs2kidhFO9+sCEhvhI9k3XHjDGrtykeHa5Ez5yRPAxjpeTw4rGq Vei5cyRvwzgmGCsT5kDlISFe1/azs/blU3nICjIfJUzLjwmS8a+VXWH36BiV H1tFxn9qXKvV6oBa9GxIxu/51efCu/Za9PyIjL+gav9JuxV16BniH+JMPqJw uQ49d5DxL32Tva80oY7uE/NCcD4iJL8nKRefoReI12U2+e+8tk+sebMvEo9D 5rsYG3q9uwdel+P+WC/w4IbGVZ56gnZ8hpsET2ib4zt6PRjDy7F1fWDeO3pe FOOE60WvA6TlGznJZnl3F523xOsLeTPYH67valq9N1zfsTQ/cL/973w7dRxd xcBFB5cK/HUcA0OP+tcTBf86jtK1T3uUQqnjYN6GVjcL948Z+9r2tUV/108S QeUiNk5UfSnc59uqMtnZZ/+vOlWYpxOKM5/6L+UNPCv82+vdlk/Vf472uaPF Odr5juZntHhGi3+08x3N52jnBfcNPT8M9w2dQ50cnUNdF51jnRaNQ90MncN8 LXAZ/v1Pcht8cT4SeNOF2I32b/1x/gx4aOP0tk1WwTjfAzx20Vp1a78wnJ8A 7nHERKpOJBLrOOn3M3igc/BA53BewIvXa5S8kfHEehfMjzrdnjqp3hfrM7Ce YqgxMTfQH+sJgK8+u8nY/nIwzn8DHzq7+460bxj6Af7+tfUha+FI9AM8rT50 Zd3ZaPQD3G9GvbBKWSz6Ae6gMaHeXSUe5xtw/tZuXWS/D/Yn4cD96LNAb5Nd 3g2svwT+Xss/Z/ksT6wXBL56VsQDnSpfrG8DPugwae2k1/5Yj4Xvzd/Pfsw1 C0afwDdFHc9MfRGGPoHLtrl6SgtGok/gwrLp561PR6NP4K16vVvrSmLRJ/C8 x3PFVdbEo0/gYbla3e4vWOgT+EM+24x+ATb6BB7vVblLLoaDPoEHrjm3ev/n ZLwP4Xt/e+r6GB0f7GuEPPll/binpb7oGbjaTQ+DSWeD0TNwhx9WAse9wtAz 5nWWB1en8kWiZ3w/Nql5K30yGj0DX+Ijctu6KBY9A59UteZAnVI8esa8/iST pSpeLPQMvHy7O/9TPjZ6xno3TuPpgSgOesY8n/7VfXItyegZ+IbvUzbtn52K noEvcwmUd9BIQ8/ApZZtmhl7I53qk0M+d99eShE9zhtJ9dUhef6Gx5uFPcKo /jkkfxTa3Z56Iprqn0Pyi01SqdIFsVT/HJLvm7Pb3XpVPNU/h+Rr9lqfqXvG ovrnkHy2U+gmFV421T+H5EMNHXfzIjlU/xySd123uzTQlEz1zyF5g9icI3Ji qVT/HJKXxESr79+VRvXPgXye1i4lB5t0qn8OyaM6PkrFRmZQ/XNI/trRalxT E/ZvQe42f1r/NLFs9Ay/ex6Gx8ulV+DzBHncYmXetNxY9Az8modrkLU7Cz1j PSk3zaZuKAk9A/cR+BnoFcFBz8CdfR655n1KRs/Ab65fZDMgmoqegZtXcU7K 7UxDz8CPX9Tds986HT0D3ze5i3CIyEDPwLeH2MvFfspEz8DXqklObxLNRs/A 5T7FDE/bmYOegYvf0GjdbI39W5CPl2gqNYvIQ88w7lBdKJBzNpxD6zfCZMWT /UbAP+z/SrQmyXowibYeg8nKJvuWwHWB/RXTPKO8PibT+pYwWUG0viWw/wKD VS/yZqbS+pkwWV60fiawv+hg7p2BHWm0PidMlhOtzwmOT90NzeWup9P6nzBZ 1rT+J7D/z5UDh/aHZ9D6ojBZ52h9UWD/L4XOag4fM2n9UpisI7R+KbB/3Sm5 VbEzs2l9VJgsbVofFdi/QChlTtOOHFp/FSZLldZfBddbvNw/dvr1XFrfFSZL kdZ3BfYPJ7p7Nofn0fqxMFnTaP1YYH+fGod6s4/5tD4tTNZ4Wp8W2P/xZals n5mFtP4tTJYArX8L1geNrd1vPK+I1teFyfpF9nWB+xbG3cumB9jLNVB9ooAz rkz2GgjNwPsQuEw4w2z/dKqvC/Bpuyr1HbZTfV2A83823RZ7lerrArz/ltCK ptA8vE+AN0m9EJ/ekI/3A/BKlpKQ6nSqrwuuw5BvtlgjS/V1AX7w54qOokSq rwvwPVnXDY33UX1dsH7HLadyuKsYrwvwrcdmaDxxpPq6ACdWHE1dIkv1dQGu zBO6OiOR6sMA74v+464ed7Ck+kQBjzFtvLp/Ww56Bu7uP0UzNiQPPQN33Byo 0vQ+Hz0Dt3q3cf70aYXoGY+feFrYdy7V1wXn4e8yr6357Qc8Y5z7+XuK9lJ9 XYB7L9htbPzbD3jGOPs86obvlKBn4I9Sm7WezKX6umD8j1ZmLfntBzwDtz1s vT5jL9XXBfhVhdyIg12l6Bn4hYEZC/vuUH0YIJ8hMWbXlqYpVJ8o4PLHow/E vsun+puRXOjfr09E5lJ9XbAeXGLDBF9WEdXfjOTfW+/YrvntB/ubkbybWfat qLOY6m9G8s920meMf/sBz8AbdM40DMtQfV2A18jE7XvC4lL9zUjO7eLPX/Lb D/avIXle0u5NGZ2lVH8zkqff84w9+NsP9jcjeeKBFvk+GaqvC/CYhat877Gw Tw7y0H7rmbJ7qXWDkB9Ss5o4xXcP1ScKuGZoqqcIi+qfA3zTDj37Nb/9gGfg KqL+g0UOJegZ+Mqmr+eNf/sBz8DlozY0Dydw0TPwebaO+k/2lKJn4BK7y4uX /PYDnoHPmCOzLcOhDD0Dn9h2hnXwtx/wDFwoPm55X0I5esb1AQ4C/vf2UHWW wL/v0RSX7aTqAoF3z/V6lOBArd8H/rm7RVBbpgo9Q77t1mUL3mJpqk8U8HsB 8vfWOFD9c4Bf25J2yfi3H/AM/NLUSW3DOqXoGfjZD3pHnnRQ/XOAn3jrX77k tx/wDNzgWo96hnQ5egauq04kH/ztBzwD15x1V6lPh6pfx3VXzeVB9zqoemvg m6JlpGV/+wHPOM9586xbgnQVega+UjN+nHZCFXoGLi8peKNVB/vkIJdt1+y/ 0VGNniF/yTH70DXcjs8Z5Fl+rleNdaj+OcCZDIXjT+yp/jnAI/65UrPktx/w jPn+2rTdGfFU/xzgvoGTMg7qUOuCgHtY6Kv0tVPrWIC7bH0Tds+e6p8D/N60 3nmyv/2AZ+C3GwiPhHiqfw7w62F3J2n/9gOegV+6XnG7tZ3qnwP87M65Azfs qT4yWE8tZnpuljT2yUFu0BL/KSy+Fj1D/nXgzI73S+KpPjnAe1Tc9mRoU+sq cd5pbEPOwXZqHSDwTxUKjD47qk8O8LpXV6LvSVWhT+DlF9LlZOOpPjnACzdO 9k7QpvrkAM+ceHC6djvVJwc4p+6NY6sd1ScHeFxQ7/ANqVr0CTz8CuPirHiq Tw7wgG33WsO0qT45wF9Orzy8vZ3qkwPco3Fu2Tu7egLqLOn5PagXpHOob6Nz cn4aeanSg5ljRa2JRnIcA7yQrC+F+gDgi5QmyKxS8yVgPhvr6V6dyuuc7k/A /CvwmOk5l4IaggiYLwSesMnlYeS+MALmt4C/sEw1mpwUQcB8DHDriK9rTWWj CaiDhLyZ2WxXjfPzLAmo2wNuNP/oG67MQ6KbrNMC3iEg+WsH6ykBdVHAE762 L/wQCPWTzZjf4yfrQmGeHnhz5crPzWcjCJhXBp47yTBpS1kUAfOgmJ/c7vz4 pUosAfN2wJ1sko15feOw7wrmLZld6w8LswioO4S81iRJhWq1qlcE1MkBL3e6 e0vgdSA5T9aA/NnQ5yXJZrD+txvzbOVkveU1cv4Y82kzjiQrxiUQMF8L3EPj odtjySQC5hcxX576Lvr7Jg4B82HAlx2+7L3gUjIBdXuQLzqQvzn9q1IUAXVm wNcJXHi22wv6XX/DPNVesi4R5omBb5HLzEu+kULAvCZw5YxDsV1RqdD/B/nC o/0+ki1pZH1kE+aFFMad92LcSCRgvhn4BrIeD+YXgS/NrmO2zM/E+TDgUkYX X848QK1vhXwC1JXBPB9wUeNev4l5ufAcwPf9ODKfkEzLAwSSeQCouwXuSb7v Q50o8Pvkez3UNQK/Tr6/Qx0ecFPyPR3qmYBrke/XUH8DfDP5Hg31IsBXke/L UN8AfCr5Xsymvf+OI99/Yf4YOD/5ngvPQXjPnUTWicE8KOw/SL7nQp03vJe9 TGx36enIwrpk4C77b1vLyORgHS1wuz7xk5p7crHuE/jlR1E6Ng55WKeI65kU dhJvE/KxDgn4c5s7w16BRVg3A9xNo8xcUbUY6zyAPxCXbs2rK8a6BOD2racP H7tcgvPowG2YzNKBSVyc9wVuYce/43EgF+ut4b3pvj7/DTGXfLLuvx/59e8e p9QyC7CeFbipy8q9Fj8Lsf4S+DJ3I2+uWxHW/QCfWuRycfmvEqxTAT7u+fvW LDcu1lVg3dBpeQODZaVYBwB8cI1F2bfsUpy3Bt4rlLbjgWEZ1jHDe0rCtfsx 3uLFhCT5PAQepV61eHVMMdaJAg+eNc+n8N8SrJsB7iDp/SXt3zKs8wBu0/7F QP9zGdYlALdIUC7vsS3HeXRc53rnpvpd8Qqs94Vx/tJ8d/lVplysTwW+yOOj T65wKdaRAB84G3RE17cC6x6A9677Vt6pUonz9MDbRTbvtC+rJNzJ5xuMe/3E /Xwzk8uIleRzDNfXJsVUfOmtwucYcJN7Y3bddKrG5xU8z5ompOyy3lYLv8t/ jUNgnh64OzmPD+MZ4FefuvetPR9NQB0AfL9TZr3Zn7OS6tcKnM976OQTqXLY H8dFtSaWTcEX6nG8B8dX5/YbHP16A8d7OE+rtvr2G2dnHO8BT1zYVyUpT82j we/v9V9vNM3f3cDxJ/Bthx5dW37HmeqnQ/7e6V5ovRhv7UyQdXV/jbuM9Ip3 fG3m+Wt+83KYXTvLofX/eX+oP4b9VUK8n105/IiAdUf0/XXJul48r6M7uZ6X XxPaZB0q8K0lgdd0VYMIWKcE58VHbDutl3efgPU8wMdbvxd5Ze1O7CLrg4Ev UfY7nSQZQUA9LvApptyN4nZR5O9yE/Le12NmWrbFQN8/nHfzqZnwoX/tKwLW C2HfF/XTdyOEAglY3wJ8cUKO4tnSUPL3MRe55Hpf01C+OPJ9IRfHD7wXi1XH n0wgr+9H5B+DecROFiUSUGcJ3PDrk2+Gszm4PgrrenpuXTh1I5yA9UvAfRdH bc9ujiRgvQ3w24aNEgs0YghYH4Lrbj2m9NyKYhJQ/w184mZvs+fNbGILWe8L /Epi89yh+ckE1NcCP7nf+h+FAynEbLKeErhe34wfevdTCahfBL7rUWijIyeN gDoVGJ+E/bC9pGfEJGD9Es77LI9Qj8uNJ2C9DfCLJh+kZq5IJGB9C9Zl+Ezq N3dnE7CeAbhX2wsjk2EO3IfIrWUL12YapRJQh419CzjH5/W7pxFQN4x1avpD E+flpRNQ5wpc+7vrT+3hDALqGoGruih8sl2RRUAdHnClZemF4UbZBNTlwHjD e9jmiroaG95TkCfP1vUvreDAew3yiNjOR3zjUghYzwPcT9veasWGVHhvQu7a OefEkfNpBKyXAG53N0bzoV86sYas28b11qmf5neIZBFQJw38wOFrkyU2ZMPz B7n6wLRB9fM5BNShAl/3JLjJ0i+XgLpJ4EtWqhYHVOTB+yaOu+YU1iRUihTg +kMYb0SQ9fmwrgD4/uzGRfUdBbguEX7HA2XLglgKubjuDrgHWWcO6xCALzoe Pv3UsmJiG9TNk1x61S/HMTnFuL4Rfn99FuiERL0owPV7wB+nfnnSWFKI682A p5D11QfJ5xhwv+ZzM058LsG6fODPo1l3h2y5xEPyOQbc7aYwr5t4Ka6rxP5n rib7yoWLcd0g8C2G0XlnfIuJPvI5BpxYzrtJYF0JUUM+d4BDHfJF8vkGXMpk 2UxD31JiD/l8Az5L2ereT5UyrGsHPkUgi9e5rAzrsIGLcKdeXmRajs83GA9k z1ikW5JcQq1vhPXfH83zTfS4uB4PeHwEZxNvHxfXjwGPtBnPdHcqxfVOwKG+ F9aNAPdq7Zx5WK+cWE8+94C7MlXu9/eWE7zkcw+4k539GCenCqwjB26vw708 b2El1j3j+jYZyXZWciU+92Ccs8W9RbfAshSfe8DXH19VYDStDJ97wJVW2Wz+ FVJGwLo44EvH5DFdtpXjcw/4gqKZS+Q/lBP7yOce8Fmn34rqTaskdpDPPeCT 1w7c/xpSSSSQzz3gIsLb+By3VRFQHw+cr9zZQvpDFT73gA+8rG9nWlYTAeRz D3jveTnD3dNqCFiPCuOr+OaegiP55QSsnwQeEU2o/jheQcB6P+BBN+/GPeSp xOcbcD/NiiULn1USsJ4KuKfkXD/2yipiNvl8A34/Id6p43g1AesogNvdEeS3 46khoO4f+PV9WlckntXg8w24xbznHVErawmoqwZu2vPZcGd+LQF1wNgHIlmx qvF4HQF1qMDXk3Wno43TYPxE5zC+oXMYT/xV70d+L/6q6yOfL8B/ji39wGl4 hd9b4FlBTTM+TQ/E+xu4864f6mPVQql1slDX9+02Z8aGcPz9g/MIvXjNX/DO c/w9AO6rX+zgf/klPn+B89HWTQNv7b6/RFwmAuPE+r1NM9VCVaIwTuCxj70N GXtiME7gHh8XXS85y8TrB9xWMdL9mEM8js/At6jmh2MRxCsc3wD/+LXnablZ ALXOi+RvXQQLf74KwfMFvt5jvO2DNuq8gJfR1ikDT1yaIHjydAKeF3BfG1Xp wduJeF7AHYrzVZxesPG8gCs/Wrz4YS0H44fzO9TkJbKgNRLjB75ZecG8OL4Y jB/4IocwQl2CiXEC30Nb5ws8U8m8U08vBeMEvvYdc1DWOBXjBB5i/2tshznV Jw3iXS6b22C+KpHqr0jyGRd1fglqsKk+h7Q8G/Y5JHlYmWONLU8m1eeQ5LLX C1vUJ2Th8eHzeZdbHTxCpI6af8P3RpI/NffJDHhFreuEPNK6/+x7xmSF/mff MyZL5j/7njFZrv/Z94zJEv7PvmdM1tX/7HvGZLWTfc/+t78Zk1X6n/3NmKxt /9nfjMmK/8/+ZkzWkv/sb8Zkaf5nfzMmy5HW3wzihfWb/9v3jMlKI/uegU84 j3k5z2LvZ1HrN3F9qtm7tL1l2egT+PjZsiWSDTnoE7h1qvG7lo5c9Inr40+F tIUP5KFPrBuZ9vWHpXABegNeL/h+0qkn1HpM4KJ6tk8KJah+ZcA138rOWeVH 9SsDfpcv089djupXBjxtn8niX2FUvzLgQ0HjIo4oc6m8PBnXRJPwl1Fn8qn6 TpLbTu4Pu2ZZgB6A98WtTdpqX4gecP1HOPuT0A6q/xjwMwJHT58uos4XuPbe L3ZDn6l1kZg/DLw/wfAc1TcMeObQUpfMfmpdJN6P2iVi8tdK8XyBr/U393nI R/VHgs8f5PuYeWYs1e8LuKKunUbJA2o9I3DT4IVlSjOofl/A3/Dk6nl4UvED z3rVP/hoXRnVl5LkY3663+xPodYbAlfRUBHRU6PWmwC/6Fv3kF1IrZ/CPnba net59an1gMAD/R+lGTVQ6wGBfxxYqZ5jTK1/BL6uj/fCvAfUujxcb63m9+PO 9EqMB3iY11abDg+qrxEc75Pvz0iXUGp9HHDJb55rf6yi+o8BD1ed8Jn5gVqP BvyL+1tTCeNqPA78uwNfBeQW8lLx4PjWRfTwzlW1+ByB5+t8Mv8Gf9PzVLA/ 8LNk3T58T4Bv8O7/2lkXhMeB741Rhdbduzsf4X5Y9y5m0ceNeIrxAJ9L1rHD 8YGLrJeMjZSMxvsbeNf9N8Vb1sTi58L9e29LNyNRyB8/F+etmvkufVgbhP8e uOydGUECZ99iPMAnkvXeEA/w/kWp5qa7WRgP8FrLnQ94TybhfQz8w6fW0uyN HKrfMnmfRjwQP/QsKoLqt0xy9/evLOQLoqh1bSS3Xr70cVJzDNVvmeTHbJkh u3njqHWsJIc6anzOktzs7sqnrpxkWr+dbvanlRavD+WnUH2SSb6vlhW5oDqV 6pNM8txbvMldTWl4XnC/P7fizN77KY6+bp19K19NqWUoAc8L+zLO4e62FE2i PJI8QDlUUXAWNe4CPvv9102F85LxfOn1zHC+wFtuCFj06Kbj+QI/ILfjNsso A88XeEGJk/Nts0xaP5ZmNuMq94WGdRY+H4BHzRUNmXkvGz1g/5hVEW3Cd6m+ uNi3oK7/R/ETqi8u8ODbKkIeflRfXOCSS2ymHQun+uLius/yNGmFJGq8B5zf euzS/px09AO8lazvBT/AD1lU7NXspvrfAi+WEj8mNkT1vwW+OdvgfKMIldcA Hnv+1fXgmXnoB7icWOvdi7L5+HwD7pmy5OmG5VSfW3r+CuIHXkHWncL+EO9C 0YV3ZHSoPgn0/BUch15XCccF/iHk9RXFOqoPA+aX/vl5wqatgOojTfIpsRsu qv0opPpI0/JX8LnAP5B1htjnmeTiARNNjgVwqT7PJN/zK7wza2kpxgO+Hccc n2u6iRq/AU/bKxzIzaLy+8CHAgOXrf6XWkdPz19BnMDFyTo99E7yvX4Wuo8v lmGcwB9+F3v3baCMWi9M8pydiUb6tuUYP9wX6b8Kpjz/h4vxAx/WPP90jCs1 7gK++vVUqROzqfXpwM1+Rr/O9aHWp9PzV3Be9Lo4OC/gzi8+bEvZSN0HwHN7 bhbMz6KuE3CB7fP33NWg1psD3+CZVdNZWonnC/c77w/lMfnV1LwO8LW7qh2W HynD8wVu7mM10a2ZGo8BD+2b4/bzDDXOwXlAtWTxw73leL7AH5P1aXC+wPOf 7VDunlCF5wtcsLMtcY8L1X8S+MbND1Tjxah138CvPFmeO8eH6j8JPPILV/Pm Amo+D8Yj68i8DfYlIPnF7ZstDBSo33vgbz0/DaVFUr+7wD932d9etJZaxw1c ZovceCcONe4Crvc0z/nrVmq9Nr3eDPwAF3aLnC9VTa2LB76xdU/ILQOqPhj4 1Q3fV35uoupZgUc7P4vfdYbqGwm8o2ndxogeqm8k8AUq7zJnWFJ9I8GfGzlv i33hSJ4pWfvP1SP6+JwFLj1uvhJH9xaeF/BsWn9C4EuMk4M93/rQ+pzwcl4H KflF616k5ttIPqbO6PUXi7voH7joCt31STJuxP8B2itndA== "], {{ {RGBColor[0.880722, 0.611041, 0.142051], Opacity[0.5], EdgeForm[None], Specularity[ GrayLevel[1], 3], StyleBox[GraphicsGroup3DBox[ TagBox[{Polygon3DBox[CompressedData[" 1:eJw12Xf8VvP/x/Hr+rzeB9+GrHahYWRlay/tIe00tCdpSItEGpSQkbKyUiRS GaUURXZ9K7K3jBAKhR/fx/P2vH5/XL3vn3enT+c657xfr9f7dar0H9nxsqJc LncFfwTjJfwxlfGglMu9wNzb+Nd8LrcBb8X78Hq8Be/Fz+HX8A94LX4T/4zX 4bfwL/hnxm/47OLzNvOfMBYx3s9nOd7BMW/hj3GecROfd/B+5l/G7+ID+BW8 E/+JF+In8XZ8Db4Fr8IL8GP4LTwXP4Bfxjfgu/A6PB8/it/E8/Bi/Dq+Ey/B b+CZeD5+Hl+L5+Kn8X34CbwNT8Sz8DI8Gl+LF+EJ+Ab8OL4eL8Br8Zv4o5y+ fC73Itf5dfiavgef9fhLjlmON+Cv8FM6Dn+NT8MNcX98PD4X98An4PNwT3wq boD74XNwMzwMP4FfwF/g83AL3WdcEzfCA/C5uDkejt/AH+J/8dP4FfwdXobX 4c/x6iKf/494M34P/4Vfxe/jv/Gz+FW8Gz+An8Lv4CV4Nf4IP4rX4I/xM3gz /h6vwi/jb/Ei/Ax+Hz+Cn8Uf4MX4OfwhPh03xgPxLXq28Ca8BX+Kg7G2Pvhi 5mvhWrg3roPr4D64Bq6BL8An4hNxO1wal8Fn4z26J7pHfEoyX5yxLvN1cV3c F5fAxXBtfBQujc/ApXBJ3BAfikvg+oXnZzSeh0/Bp+AOeA1+Hn9auOa6Vp/g FXgF3olX4pX4PTwWj8UL8Bg8Bt9ZuD5n4C74ZHwyvhCfic/C3fBJ+CTcHp+B z8Rd8Vn4bNwd34wX4o24HC6Ha+EKuAKuh4fjS/DN+BJ8Kb4FX4pH4Ln4InwR vho3wefjIbg1bo1H4pa4JR6BL8QdFKfwCHwZvhV3wB3xONwKt8KX4e64O56M y+PyuA4eiofiOViBbyS+DVfEFXEDXB0fh1vharg6bomr4mq4Ba6Cq+Lm+Fhc BTfDlXFl3AT3xf3wdDwSj8K348a4CR6MK+FKuBFuVHiGBxXWvtbLu7ipzkPP HXNl+ZzAfBut5cz3YySx+pzMMW4EPjtz3LkUn4gH4L74BNwf98HlcXtdO1wW t8MX4qNwC9wO18q8lkbhI3Fz3BaXwxfofuAyuC1uj0vjNvgCXCdzPB2D62WO y2PxqXgYHoRPzxxDh+KamePmEHwKHoIH4jMzx/fhuAYeqGuKT8KDcH9cN3NM vxzXzhzTR+Pnktf898Tak5kfjAcwd1bm+H4JPgyfr+cGV8SdcGdcGXfBXXHf zHlrHu6ROd7NxRdlzkm34H6ZY82duD/eiufjIbg43sI5DMWH43dwo8z5bwLH dM+c527GXTLn2jl4MC6G3+b4bpnz4k3MV8KdcRfcM3PMvRX3yZxH78BH4664 Gz4O98EX4+r4YtwbV8O9cS9cFffCPXEV3BP3wMfiHlqr+OLMOex23DtznrgN N8ycj8fjY3A3rT3cIHO+HJe8RhR/OisvJMff7/hep3HMKDw4+fnXGh/LMQ31 POLLcQM9X3hM3s9mN3xlISZofU3L+1nui6/L+9nsg6fiTuG42q/I93YAnpn3 c9oLT8n72b8YX5v3s9wbX6M4xrkdyc87+R1N9VwwP4H5Zrr2eCKup7WCR+Fj 8Om4Ez4a18Qd836OBuEb8r42Q/BsnX/4/BUntCYm4XuZr681hEfnvea64kl5 3/OB+Hq8NTmW/Ru+z4OZn6V8nRzTv2W+Szj+H2Csz3e5l/kr+PvlyXnuS+af So77X+EVybnha/xkcv77Aj+YnLe24/uTc95/8cLkPLcVn8vvv0lxmbllyXHz c+bPYH6Kvh9zx2e+D/q+FXBH3RPmL8TP4+vxquTc8w3/9vHkmPsZXpIcoz/C vTj+9SLXTs3x44xX8/ePJsfTjznmkeS4/wFenJyfPsSLkvPW+3hpchz/FK9M zru78GPJcfwT/EBynt6GH0rO5e/pGMalXNstXPOl+HG8VTmUY7apruOYnTp3 xXDGX1RDqZ5RDaTrx/g7x+/NuZ7YzWd/zrXy9sLPewo1xh8Fl5KLnMsUT7bh Q3HjvOPEUYxfMv6W8//3I599hd/5A588/6as8rXuRfLv3sHcCYoXBZfPu1ap oDohueZ5i/lW4Ty+j7FJOIf+wng+n2H4V8Zm4by/N3y+ewvnvJFz2qFzz/s8 dD7aC9Tg929iPDH5XH8pXJ9S/PvjVUsw3yZcM/zGWCXvPFuVsUyRj2mN14Vr VMXPp8M16iz8TLjuna29TLi2VKxeH65LFcM3hvcsimmVwnlZz56erw/wP4pX 4fr8Ro7ZEN7vKN5uCu9xFG9fwm/kHA8fTq4Xz1MOCtfziuer8FrFAcVk/v4c fJHq8+Saoy5jsfB3VLxUDaFaYnuR41Alft7FeASfo/HXRc4nx+KvGNeGa2bl iNXhvcOLei7C9a3W+LBCPFS9WTpcr2q9Vw7XYIob7cL11e/he7Wv8EyWD8e3 RooN4f1IC9Ue4RioGuD48B6kueoNxR3VRfhc3Dbn2qAe7pRznu0Rjl3KyxXC OUK1aq9wnFQNcF44Hqo+6R6Opcr7XcPxUPXA0eHr2UQ5KLw/Ol+1EL+rKR6a d57X/zser02uO5X3yykPMd8AnxbeN7VRfRLeK6kWqhneH6n+OTa852qKy4bj fEM9b8m1cmPF1HAtp5xWI7zPapn8jB8oxALFQt2LOzifjhzTP+farGk4Nyn/ tgznI+Xl1uE8pXzdHPfMOS8fFq4J6+MO4Tpzf+HeKaZ8U1hbiguf65zCOVQ5 +kDh7zTfPlwP/1FYv4o72ud0DudN1ZANw/lIdUXtcI5WDakcfg1+mO+yM7ne VU4fwDHDc673XkuFmlj5LZyvVZPUCud31ZMbkmt65YU64XpAeb5BOOeqHmsb zu+qYeqH87JqIeUTXcMZnMOfyXsn5ZSq4X2E6o1Hwvv3a5LXhuLwbxz/Kz/f U8iP8zjmvpzrlq2FGJ5U9+iDV3P8Haqz8Bp8q+ov/Cy+HF+O5+edb5fh/+I5 +Ca8At+mugk/l3ePQr2FZ/LeIz+AX8F3hvdZqqnmh/ezqhWPw23wD4x/JOce 5T7lQMWWz7R/DO+JfmQ8uXAN9RzeF+51TOL4hboWeCK+NdwbUX2+IHwOOpeb wz0Q1fC34DtzrqvnhnsaqrfvD/dMrsQP8m8exJs5h7vxPXgDnlrkntJifB2+ Di/B0/A0/Ch+CD+EX8UP44fxa3hBckxTbNP9UkzbpT0p87tVD5H/pzNOZ/6x vPOW8ldFxpeYf0nPf961gvoVP+G78N14PZ6BZ+Cl+Go8BT+EZ+Mb8XJ8I56D n8r7GblXcRXPwrPxk/hKfBW+H1+FJ+sa4kn4SrwQT9a9wg/m3VO6Fj+Cx+Px +J68+3BX4LvwODwO361nI9yzukrXOdzjmoxvCD8/eo6y8P5ddc5B4T2+6qWD w/0E1UUp3N9QXVS8EG+Va0qE9/uqhUqGewKquyLcA1G9dAifU3Ouiw4N9wRU 4x0Z7quonjwi3FdR3Xhqcn9A+5fN4f6h9kQvh/uK2k8tCq+RKck1oHLoHr7v 4nB/71rml4T7hFNV44X3xdofLw/3f2YwvyLcG1GP5An8NL6O+VfCvUrty5aF +0jT8FPhHtRM/GS4pzQd7y9yH0M1bcVCDFc+OlDk/oDq3tHhWl371urhfsVu XQ8+PfDPjGP4TMx5P1s3XOcrjk0M33fdf9XFN+OVfN/rwz1M7bVfDccl1Ykz w8dojz8hHGO1F/4i+XlVXX1muNfxU7gGV+x6id+5OznuqCY/Lblfob3nn0Xu Oaim/bfI/Q3tcWom9zfexWoGqweiWrdF5t6f7lEZfq6Xc51cLdxv0f56argX qv7DX0WFukXPUbjPs0ffm8/1Oe+7rwn3SNWjaJm5R6mYfGo4X7dWrkyOI5UZ p4XXbGk8PRxbyuhZSt63qj6cwmce80epBgv3zargm/AixQQ8OxyjyuGUuX+q vHlQVuix4rHhdV0Cl8y8H1M9Myxz7aXrM6sQJ7XuhhfuqWqqLCv0YTl+RjhW lNVzmLzXVk31N/6P6j/GK8O54zA8qbCW9WzcEd5T6Lv/kJxjdM5/Jce16oy3 h/cglXC3cN75k3FOOH5WYP6KcBwrqeclnLOOxJPDuewIfGk4Jh+MrwrnpsPx +HDOKoXHhWPgofjGcKwuj79OjuP6PQPDsS6PB4XjYZHWdXhPpHNeGY7DWqf7 k/uYVRmLZe5Bq2bTHur/90lrCmtBsV8/a177Ke0ptIfYUeQcobGr9oIcv5H5 aswVZa6zVVdrv6M6egBzl4XzxX+YGxqO+ZnuSea+eZPC/dFe6RzW0b/JfTft m4aEY3jS/QzH5/9j/Cd5T6Kavx8/T8jpIK5X5v6F6uQR4Xx3CH4snMsUx75K zou65n3CueAfxlF8ZuLiqqfCeaoY7hnOEX9rbYX7vX8xDg7nneCY4pl7/apR S2TuU6gOPzgr9P1xPnPPog4ulbnnohr1nnA/+RjFouTekerJIzL3PlQbt8vc r1fMbJa5j698dEHmvr9icvvM74cUYw/P3EPRuj4kc12uOvnb5Dyqdf1Ocm9X 13ZLcg9Q1+Gt5F6fvu/vyXtvrettyb1mPW/bk3vNet7eTe7t6p7uSO4765p8 k5zvFR9+Sq7ntEbaZn7PobwQmd+vaO/ZJPP7BtVLjTO/h1C91DnzOzDtB5tm fp+hvPxzcm2h9bgnuUZUzLk73Ks/Gp+f+b2F6qVOmd+xaX/aMfM7M+1bO2R+ l6Z9YpvM70KUy1plfleknHhXIQ+qTmud+b2R8uPm5P6eavhdybWR1vt7ye8D 9F7vjeSesGLF3uS6Tef2QnIPXbF6XXL/XTllX3J9pudhdfL7EuW7XOY+V23m 1iS//1Bd+nxyj1v156bkXqL6Bq8n95/VjzqQ/N5C6/Refl6lOkSxLfndgPoJ Lyb38dVn2Jjch1Rv4cvkmlIxc33yOwPl3B+Ta2vFpQ+S34VorX2XXM8pX3ye XIcppn2WXKsppr2fXLsrBn6aXM8pZr6Z3HPW+loaricVr35LrlN1zp8k13nK Fx8l121ap98n146K/x8n13lay28n96IVNz5MrvkUi/4Hed+glg== "]], Polygon3DBox[CompressedData[" 1:eJwtmnnAVeMaxc87fFzzWAkhpYlKiJAmpaRJmiWVUCkZGmhAk1AZK3OUCAll SpRGMmeoiIwVCRmv6V7u+t21/9h957ffc/Y5e+/3fZ611q5y3yEdL46lUulM /ZP194FUKi3W30fELcpKpVniReK54lPFD4pfFD8mPk08WB+6Qfx4KJXqiy/S +OXiyzX+ocb6axspnqnxozV+i8YfFt+u8ZPEM8XPih8UNxXfJJ4rniE+UXyr +BHxHeKTxbeJHxXfKW4oHqjjX8PndfxjxDM0Pl98r8ZPEd8lni2eLf45+/N3 i+8S/yCeIp4mnib+XjxZfJv4NvF34mnie8R3i38U3y1+gOsk/kV8mbY7xC8G n8+F4iv5fnFd8RDxTeKnxSeILxXfLn4h+PwW6HhrxM/peO3ET4pfET8rbite KH5VvEjcXvy0+HU+L+4gni9ezfHFZ4iH6vh3iZcGX5/h4pnileJG4ivE94tX i5uILxffKV4SfH3v1/GeEz+k4zUTzxY/L35Y3Fz8hPhl8TPiNuIR+vx94lX6 fGPxJeKbGRc3YD6Ir2O+iI8Vj8m+f28Fz6+5Ot5S5o+O14rfl3y9rhbXE1+Z fLxrou/vs+I3+b3ijuLnxG9xvuKzxIvEb4tfEnfi/JLn55XR8+9o/e3HuWvf gRprlf2afXtpvLf4PPF14hrihuJq4jPESXyKuLq4jTiLW4obi88T7ykel3w9 r9P3HCduofFTxH00vrt4fPL9uT56vZyq8ePFZ2t8V3EDcQXxCeJ/9HpS8v27 Ue8/XuPNte8EcU+N7yY+TdxI3Fe8h7iPuB/HF9cUnyvuK54krs78Ep/DvdG+ fXXsx8RdWDvi3cXniwfyfdpXW+/vIe7J9RdXFs8Td9bretq3m96/UHwuc1+8 v7iduI1eX6J95fT+w7gPrH3t21XjT2v8fHFT8UHiZ8QXiJuJDxb3E1+o11O0 7yh9vpe4t3iC+Ahxd/HZzA/xYeKzOR/xWPHh4p7iXuJx4iric/h94vHiquKn OB5zXfvK6fvO4/v1erL2Hanxvvw+8Q3iWuJrktf3pOj520zj9cU9NL4L61nj 14uviF7vUzW+TLxF452pX9nr9zvx2dSv7PX7g/gc8YDk+nWJPl9HPE3jb4h/ 1Hgv8eTs9fFl8Py+PXt+/yLuI75DvFb8q7gv9S97Pfws7k09zV6v34i7UX+z 68234h7ih/T9S8Tz9f0txY8k//4nxa3FD4tfEj8hPl38TPLve1F8pvj65Hpy c/R6vzG7Hm3T8buKb86uZ9vF3VnP4ofErwXX++nZ6/kn8bniKdnftzl4/d6Q /fu+CF7v48XPiD8Mrndv6fsPKNbLBdy/5H4zIHr+Ntb764rP0vhO4ibZc5E5 ubN4Qnb/2Rhcz65Lrmc3RdfrRhqvI+6o8TLxxOz6+FFwfb42uz9+HFy/J2XX y03B9Xqs+Anx+8HX7xrx4+L3guvdyOx+93pwvR2UPZ/mB9ePq7P72bvB92dU dv98I7gfX5/djz8Pvh/jxE+K1wXfv9HZ/fPN4PpNz34n+Jj08v9o/AudaznW m17fo31zNDZH+34Vf8D90thY7RuosT7aP108TdurGquhbZXGvhZ30bHfze71 3APuxXv0B/Eoaqx4efbaZo03Fa8TzxKPEV8gfp/+JB4tPl+8QjxV3F/cTLwy uzZRo1qKV9FfxReJW9CbxLeIB1Oz6Y30I/Eg8eniS6O1AmuOtXeutl7a1up9 72R/R3eNdY/+7p3FlcSVxI9m18ya4prRtXQNmkLHG6J97end4lvFF4vbJp9j N73uFn3u67XN1vhV2nchvQpNIR4uPif5Gl+m15dFX/v/3wONP1XyvaGetqDW FfV3D21V9bqK9s/PruFVxIdH1/adxAdTW8WPiP/hXlOr9feB7GNwrMrRtb1M fBC1WfxwtsbZoO9bWLL2eQt9IR5GzxK/Jp4hvpQ1hjZB3wSfQ2dqBfooWBN2 Tb7G94hHlHzt64vLB89B5mLWvgPpzeK54lis7wO4b9QK9IreP5R7pLGkraJe V9T4Q9mac67Gx5WsRdF868ULStaCaLw1wRoO7fe5eIF4qng410LbiXp9oo63 SGOVk3tlA/Fz4k3a5un912rfEI19jJ4RTxRfLB4brX3QLGiXj1h/4gniwck9 7li9Pia699VDg4hbiZeIjxGfzlwVLxUfK24tbi1+SbyZ+qPj3ap9ozT2JfVL fIt4ZHJPO0qvj4rudVWSe/NJ4ufFRyb32qbiF8RbqF/Bmne0xvbTVkuva2l8 gca+0rZY49O17yqNbaW+BWvmMck9HO1QL7q3f5LtBdBcaK/PqEfiKeJh4m3U 92ANPiF5jbNWB0WvfWoAa2dwdG1gjbC2MCmsnX3ENcQ1xE9ka/RXgjU+2v2W aG1LT6I37aD/Bte0qeJv6YfiWfR4ccNkfdRRnzuwzDWKWnFRdO2iNlB7+kfX iI3UX31+PL+ZtZesJU7W+GKNfUq91/hk7RuaXAOpTQOja+PX2docDYgWxIOg hdHEeJNv0A/BnmOieFZ0Laem35nsQd4WzyvZm3BO3Jvp0efaJFnPdBEfovM5 Ufuq6/1fYfLKPN+6UjvF+4tPSNZPbcTly1xDugbPUWoL95DaPTL63jZI1ldt xRX0/jdZn3p/BfSTxjtEa7XezLnkNcJaHxG9do4WdxGfJt6vzOfI2psSfe7M CebK5Oi5Uj9Zf54RrSe55qz9odH3gvXZkv4frYdZg9TS4dFrkznLWr02ei4z x1mLE6LnPnOYtTsxem5zT7h3N0TfK9YY93p89Nr7N3M82CPjlVnT1MJh0Wud OU4vGx0992uI24lPidbn1cRtxQ2j/UBNcXtxo2j/UEvcQdw42o/cnqwXZkb7 t9ris8Snivcu85xgbtwf7efuSNYb90X7sSbReps1z9qvq60zvVL799V4HXEn cXPxPsyXZL3cTnxAme8h97K9uGKZayS9a0x07WSO06tHRc99ahC1d1x0bfqL a6bvf0f7FmtsebRWRbM+n7wGqWW3Rq9Nrilz+9Hoax2S/Vd58d/0K363Pr+P to3RHq6JxutG6zk8E1qQnkHv+Fuv/4tW0fhrxTXHi+GZuBfcE7wTHo57xTXv V/gT7gVrhrVzBB5Gxz5E+5pr93Ha968y3zO8H7+Be8k5rtDrFdHnjmfEO+IZ 9072jHhHahi17E/mhV7vpb+z9f7Gyf6js7hSmfUDWqmr+FDxoeIW4vrR/qNR st/rJD5Y/DvrgLWrv/freH9wzuI99XeW+JRkf3uW+CC9/zf93VW8u/7ep/HD NH6a+PhoP8qawmvSA1lr7MOr4kF5717JfugIvT9q7Plor4PnIbvgnPG31aKv xe/6jq0aX849Tr5HXJsK0fduQbR3WlayF6mQfK9qR+vvisn3qk60nkez4pd3 KfQDHhN9f6g4lPka81urR1/79axr8TZtG4pj4A34DMfmmuLt+M1ca34j2mdh 9G//g54YfI/nJf8mvAEeg9/KHMRb4I+Zm7wH7fZU9GeZQ7z3kKIek0fgp+mh 9NK22fVsUHB9pgf3CtYk+xX94OWi36Fn8Bx4DzwHWRIZx8xCb1O78TR4GzwL 2Q0eAa+Ap8LL4aHwUnggsiQ8Dd4GT0MWhefCe+FByV7wuPcW+h7vi8fZVNRD 7vf3yXp3dLCe2ZGsp8cE65mTOWbJeeMy8Q/iHuKrgvXNdm3L9fpeanbyfKLe vsA1FP9Gjy14jvhZNAJeSFwp2WPiNfG4LyV7rveL/omXpUauLvo/tZPM4khq Y3SWgWe8sfAT9G5qLtkZnpBajKdaV+hJ5ieeGm+Nx12aPH/XF3qZuUMGsKWY 79Q7/MeMQh+j9fFMeCc8853ZnhnvjGdfkuz58f54YrIuPPHmYn0sKurp1mI+ Unuo+asK/UMv+K643sOC9d5P2tbq9WPaN11jHyXrvXbBentjsr9pG6yntyfr z4uD9eO3zBnxkGC9s0Pff7heV6aH6O/HxfVsH+wf/p2s5/BkeLNNyfq0Q7Af +TC5FlIT0ffvJfutJsH18APxEeJWwX6lJC6vP+X0vXOy9QdcT+P9dO67sCaD NQ/a5xNxbeZbsH87KnmuNNPnXxT/lqwv8Wx4t1+T9SieEe/4d7J+waPh1f5b 6As8EF6ITIxsDA3VSmN/JesTPA/eh546ILhm02v/TPZCeCS80i/JehMPi5cN 2WuXNYxePI6aTL/T7+2vY/2cPDeZo3hhPDhe/BLOUWM/JutVPDZ+8yfxgJI9 NH729+T34lnxrn8kz0XmJF7u3WS/2Ci4X/BQ4B80gLY+yZny0kK/o1fpUSOD NR29C805KlhjokXRg8w95iBrn8yb7JtMjayfnkatoGbQ6+hhVwZrFHobmmOo +MyStQg964pgzUIvI7NeUuhpnhWQmZCd4D/IYgeQeQR73DrZGR5ZNBkL2d6F 4gaFXqidnSGhH+gp9BYyfbJ9Ml2eXQwUtwz22HWzNdLlwZoN7YQmvixY06GV 0dSXBmtAtDaZLNksPb5bsqYlK0UTonXJPLl33EO8Bxk0WTQ9vktyJkk2icbv kZyJorf7sKaSM0yyTDRDz2SNNzC4p6P9yEDJQnuz5pMzUrJSNF+b5J5D78GT 4hXQ6BcF9yS0OxkrWSseoHVypky2jKbolJxpkW2hQcn2WZPboz0Ca5W8aKvG vtJWMzvDIssio+JZExkYWRgZF88iyCi/LfTEsuQMFX3xmnh5sq5D331YMP4P P4ymRFui0boHa5T/a7cyZ2H4LZ5t8AwC/4XmRHv+qd/0fXF8+g2ZG9kbGpys lMyS7JLMjmdXPJMgTxpbst8nM+RZD/6fLJFMlDwAf44ffZWaXLIGqZVdw04P rnHUNjRu/WL+oX3RVK2DNTBa6wuNLxTfKB6RnBGTFZOhrkrOUMlSyYBXJ2fA ZMFkxi8nZ8Zkx+jvV5KfQeDX8Tx4n3XRev3d4veRKaPX0e9rkjVV86Leo7Ue 13u6iY8T75mcaZNtkxGvFL+vbbNeb9FWXe89j+sZva9adl5CvohnwDtQw5jH vaNr23+S/RWZD9nPX/ikko/BsfbNziLIMPBz/Yv6NkTjG8Q7ZR+b7yBPowcO K+oJfmj37HPnGuBvd872e2RIZEm7ZPtDMhz83b+y/SMZAP5zN22TSs6E8LcH aXuw5MxhR1E/ryg58yL72jt7bjJH8UfsW1vUWN67X7afJ2PBj+6a7V/JmPCz +2ubUXImg589MDvbINMi29onO8shI8Kv0qPp1fRwsgr84NCiXuFvyHOroWGT 8zvmPNpqcfRaoEfTq+npZIn0dHo7moGskMxkRLAnJUvhWNeGIlOh3mTPJeYU foj7OjH4Pbz3neS8sWGwX2FOXy2+Knqu75GdB5Cp4C/3yp77ZHb4TzK6wUW9 Irvjnj8QfAzmwp7Z+QIZFH4cjYnWRJOSrR2cvfapAWQxaNQxRT8ii+uc3Wvo SfQm1gce4rNiPXTKPnd6Er2JTAq/hOfAe5CJkI18gw/XeJfs3kbPpHd2zL4X 3BN6Xbfs3klPpDd2ze6t9FR6a+ts/4mmQFucka0tqPHU+reT81B6Gr2tTXbt p4ZTyztk9yJ6FL3qzOxeRQ+jl7XP7kX0LHoXmgnthGYjC+ccjgvWXJwbmeig oj/gD9H8o4v+T/+omJ21ktGR1ZFZ9A8+B7KMnJ0n8AyAvA9Niva/J1qr8gx/ RfAzUJ7tV8rWrmRgZGFoVrQrmpXsuKfevyP4GduKZH39fnTPofdUyD4+GRt5 Ex6D+TQ12nuUy9Y2aBzyn/LZWRyZ5baifr0XrVGpRTyD/yz4GQzP5g/I9mZ4 NPIMavLH4jeiazUaGi1Nxks2S03+hPkXXatTdn7EMxDy0LXJefhJwf58S3Le yDNX/MpWNFnJzzTJe79M9oo84+X5RFn2WuCZA/npF8lenjnKXN2cnA/jMfGa rEHWIt/5e5EZoAVZo38UGQXaHI1IdoHH2sD5RnsvPBn3Z160V6ucXU/wcOQ5 PMN+KvgZP8+2m+r19pL7ATW9it6zsmSPjV/+jetY8v1bidfI9jp4Hvw4PW6T +M3o3sc14lqxBsg26En01qrRvQoPgZeoWvKzkM+Ss06egfO85PPkXkYGShZa qeBjo73m18n+gWfW5PefJnt3PDzPTzYkHxuNiFZcn6wV0aBo0XXJWpRnOOh5 1hO1gWcgPAs5TNvTJT/z4dnPV8nZHRke+TrPiHn+xvMWnl/xfyTmBD/P4v9O 4GmGB+ttvA4em3rbp2T9Tf5AllVV20nZHg+vhwfjWcq25FrKmmZtx+x8j2d4 5OF4NLwamQ3ZzTfJc5kaTC0+NDvv4JkRz454Rs+zejLc5slrcmPJWRxrFU+M FlkW7ZXxvOvEq6K9MJ56vXh1tNdGU3wkfj1aa6D50H5rorUhehD9Rg3g+Idk e3E8Oc+C0JAfUI+itSU1nFq+NlrroIk+pb5Ea6X/ARYnlE8= "]], Polygon3DBox[CompressedData[" 1:eJwt13ncVdMaAODvO7tjTFIKUWkkUpcGSoNbCqVBEZWKJtGsWaPmNGpGyRCF kqEJpa4m96LMQ+ZwDbnmeyMunve3/PH+9nqf9a7znb3P2mutr0L3ge0G5AoK Cl4QeTGgSEHBHPBcYUHBP8RB+UAxl+2Q361mWlZQcLXoIK7X11Pfi67fy6/R Hquuo7om8kF8HtvJVrDpLMf6snmsP+vFirEx7F42jg1nGevHbmcDWG9WhPVn 89lAdgM7mg1jd7LhcQ+si7hW9NR3g759rh3j+4nu2r3YS65Xya8U12n3YC+4 DhaLtf/l8x70efP0NxMXi076Osf9xH17YOeqKaXmFNdabIhYGs9Dvprfbsy3 4jI2gLVgteTfiRZsIGvJastHGfsAe4dtYCvYFvG69g7+urhDzc1iSXxXdav0 zVVTyG5ic1k/1pP1YaPYWjaDDWbfiEtZf3YZO0/+g+jIxrFOrKm8v7Ez2FZ2 B5vIerNBbCW7X7wVz1aMZGvk09XdrO7IeA5sKRvK+rHO8exED3299e11vVGM 135S3RPigPyIuD+2RD7E2L7GjGT3xP2zdWwp+3+WPufsfPqd4/f+I+6ZzVZ3 o7rr5HljY4IvYINYn/i9WXs2jXVnDVh71o5NZVPE9pgb4ko2Xd5DXUN1p7AF bDNbyGbFexC1bAbryRrFPGNXs5msN7uItRGtRVd93fQ971pGLNR+St0idbP1 F2cT2So2iY1mN7EJbD2by0ayvmwae4YtYbeyUuw2to7NYpNZaTaTPcZmsyms lbg8npu+rvr2uF4ibx5zQbtTvO+uLWOexruk3YXtdj1BTNJe7fMm+7wx+vux 6WwLW8omsJPYLPY4m8OmxnsQ8y/mg75r9e1yLSmmaD+sbqq6cfp7xfxgy9ko 1iN+I9FOdNPXPd5P1+PFWO371I1XN0J/UXYLW8HGsKHsVLaIPc0WsznsGDac 3cVGsIFsKLsj1gb2EJvPRrAV7DX2KFvChrO72atsLVvMjmUj2DI2kg1iJ7P5 bBNbwGayo9jQeJfZMNafHcdGs3vYWDaMlWCT2UMxJ9lY9nuW1rPq5n3XeBbi RHVT2SPqpqkbz4ax5ewV9rL4Ieaj6MBuk/dS11jdUvYyKyI+ZHvY4SythWfm 0xofa/1l6pqwG4ztI4rrq8SeZG/L1xu7Rt1ctov9wt5gW9ksto39yPayTWwB e4H9wfaz59hstp39xPaxzWwO28l+LkzrYKyH89hudpi9yZ79636X5dKeFXtX Q9/vdraH/Rprlbpt6tqyVuxW1oWdzyqyJ9hb7En2SMwz1oZNYt1YPfYf8XfW mzVl1eXz1T3PfmNvs+2sMnuOfc52sGdYOXZfvGexdrK7WFl2F9vOlrNFrDy7 P9YGtpItYzPZs+wH9hLbyC5kVVhHdk3My1hHxIuxmYt3Y89Qt4Ttk2fiA7ab ncbulG8zbhlbyF6O94bVY8eyn7UXq9vrmhPvs11qXom5Kr9QXVH2i/YidS+5 For32E41e+P9kn8iSqo9R83pYqX8n/IH1C1XU4OVl5cTJfTd6HerzkrJTyxM n9GbNWLnaF8fv62xJxvbmNVg3VkjdlKW9pRxubQ/xT51rrFt2OVsgvxadXXU tWTN2Ch2JasRa3Osd2w868zqsotYTdaDNY59PtZN1pzdwq5iNVkTVie+P7uY lYs1NtZUNpp1YH+L+cNq59I7FO/SRnlTUZfdJG+mrry6huwM1pnVZcWz9Azj WZaI3yjeRffWgl2sPZK1V3dOnFPY+awva85OZ1ew1mwi68ouyNJZb3Yu7b2x B9f1eePYI7m0ZsTa0ZxNZ0/H+iD/SLRlNVlZ7dNEyfju+bRGNNUeEecwsSW+ hyjNWsR5I36TIukcMZAtjD1P1DC2GWvABskv9/3O8P0uYCexlqwqK2SXsEbs ZtaanRn7CWvMhrA2rFrsY6whG8xasarsQ1GBNWeVWNHI1T3M9rE1bCWbwbaw 7wrTuXg9ey/2ENYo7pkdIX8n1nd2ATuFZfL9cUZg9VkZVkT+rijDGrBT45wt fzNL8/2zXHqO8Tw/YdXkreVnqSsp/0yczdqy6qyU/Mt4NqwLq8cqyg+IM1kr Vo2VkH8d6wS7jjVgVeRfiXqsK6vPKskPivqsG7uQVZa/HftKLp1vSxfEzRUU HMrSWaFyPp1j4jzzfqwn7CJ1ZZUdKf8lS/vzGfl0to4z9m9ZOnOflU/nwDgP fiwqsUuNrWJsMfmvWfp/olo+ndXjzP5RrNHsEnWV1R0n7xNzRl5BXsG1tuf3 c5bOVVX0tY05n6Vz3RW5NB9jXpbR90GsvaxJrDvGHyX/b5bOIxXz6bwT557/ ZenMUymfzkpxZvopS+f/Cvl0jonzzI9ZOi+dnk//I8T/Crf5u1vZ9/7Gi/7G hr/e/Vq5tF7Hun2U+vqx/rH2MQdijZDfKtbF2smeZauMHcNWx/rKNrN72UT2 GPuUbWOrs/S+lWK1WR3xu/z1LN1n3O9r+qrGuVFs1v6aPa/vcTWj2arYO9gm dk+W3v1n2LfsG3FYPl6sZR/HO67uAXW3sAfZ/ljT2N1sAnuUHWBb2YNsLHso 9hP2FLsvS2vOmlxaW2KNORR7VpbWuP3iGHWHcmnPq5xL60isJznP7w11J8Qz yKV9JPaTz9m58g7yWsaelqXnXDne+1ifRaGxn/Kz1LWRn63uxHg31JVj7eKz 2NHs36I6uyL2MVZa/oU4j10dc4+VlTcwtirrFM+eHc9eE8ezxqwY+1V7qrpN rgfZHvaYmilsI/uK7Wbr2GS2gX3JdrG1bBJbz75gO9mj7FVRjDVkx7HD2nXU HZ1LcyDmQi/3+ycfptlk "]], Polygon3DBox[{{983, 531, 742, 283, 21, 767}}]}, Annotation[#, "Charting`Private`Tag$19247#1"]& ]], Lighting->{{"Ambient", RGBColor[0.30100577, 0.22414668499999998`, 0.090484535]}, { "Directional", RGBColor[0.2642166, 0.18331229999999998`, 0.04261530000000001], ImageScaled[{0, 2, 2}]}, {"Directional", RGBColor[0.2642166, 0.18331229999999998`, 0.04261530000000001], ImageScaled[{2, 2, 2}]}, {"Directional", RGBColor[0.2642166, 0.18331229999999998`, 0.04261530000000001], ImageScaled[{2, 0, 2}]}}]}, {GrayLevel[1], EdgeForm[None], StyleBox[GraphicsGroup3DBox[{Polygon3DBox[CompressedData[" 1:eJwtkcsyA1EQhrtPJplBIS57LKJcK5KFF/AGHsED8D5uD4SNHYVg7FJKlRFZ hISvq3vxT//9n/+cvsza0cnhcRKRHVADefK4rSJ3cDu75VMRP8AbqJMvEDfw DEPXODNegjEowBQHp5nICD7kXg/MoL0SJ3YOpsm7mT8yQX8CBfyF+Ahy+HPy t61eH5zhb6Bd0WwL3kSryC/hD8QO8Tzzea7xjJN79tEuQEF+Y7rdTa5bXMVz QL0BfEn87hd8UbyWzV7GTn5jD73orYo9fIZu3nvwA3+PWRrwPfWZbfY/0FSv q+qz5/Cu+pv92GcWHvN+41kW73+dfAU+r96H1d1S3439u014Up9lVn03dXhb fQe29l31HZbRc039/TniP/GkPWQ= "]], Polygon3DBox[CompressedData[" 1:eJwtkUtOgkEQhIeZ+XnEFyp7YWFiiCFRk/8C3IAjeAA8EMiBwA07jdEY3ahR 43thgPhVuheV7pruma7q6ZyeDYYxhNABGfQqIbSIifhKYQ7u4c/gkvwdbFHb g/eJL/BNv3NFXoADeBO+z4OH5LvkkfhG7SJZr+acZ0PPe76pj/3ODvwLPoJ3 4dvwD/gsWa961PvL2R+8Cj+CT7Lp0IwfYsl5g3wFHuEn8Dr5EjzBVzLP2Rq4 Jf8ED8E8S/8ymx/NX0Tz3NauKrYLeVp3vdI0TZZLs7TfUV/Aa+AmmgeNrLo3 zVe/3jjOprmAX0fzoh0k3ffdlNl2K03SJk8N91S6h67r0dv6ww3fr/asHeuf 69F2X/gfR9+vPMpfM9r7/6MHPhU= "]], Polygon3DBox[{{1078, 528, 323, 31, 765}, {758, 6, 732, 735, 1178}, { 970, 518, 297, 3, 755}, {745, 264, 733, 306, 307}, {734, 737, 257, 32, 764}, {972, 520, 301, 5, 757}, {1073, 731, 303, 6, 758}, {971, 519, 299, 4, 756}, {1073, 262, 251, 729, 1182}, {304, 7, 252, 263, 732}}]}], Lighting->{{"Ambient", GrayLevel[0.8]}}]}, {}, {}, {}}, { {GrayLevel[0], Line3DBox[{246, 1, 242, 227, 754, 16, 765, 31, 294, 271, 752, 260, 272, 257, 737, 267, 256, 1074, 268, 750, 258, 269, 749, 259, 270, 748, 251, 262, 250, 1178, 735, 263, 252, 736, 264, 745, 253, 265, 744, 254, 266, 255, 9, 310, 8, 307, 306, 7, 304, 6, 303, 5, 301, 4, 299, 3, 297, 2, 728, 234, 246}], Line3DBox[CompressedData[" 1:eJwt0jtIV1EcwPGjfwMtH/jo7ytfqYhDLYkgJiKCDjY55qI56WDRpJM05aI4 6RRNOoWTTo21uGrlu3wm+cDBxPfjc8Hhy+d3DhfuOZdb9uZte19CCGFYdYaH XE4MIdOcpWxtWefwsTbNce4xl3naN79ICiHfXKBC/bX3hEXaMRezRNvmUtZ4 voxPdWSvnBWq1K51FR8oJRbCc2fKYwOr+Iq17GALW9Vr7uYA33OIHzjOUU7y M2c4xe+sdoZdnmle/3WgU+/9Ee3zJ8/5ixdc4CUXecUlXvNGy+ZbrjC4wyoS uBYt+Zsx/mES17nAf9E7tKETHWrWGef4ld/4hdP8xAmOcIyD/Mh37GcXO9Vj buZr1rCNlXzJOJ8xmcXRN/UddqJ7K0PH2leTu6SzkWlsYCrr+ej+f7kDvyNH sg== "]]}, {GrayLevel[0.2], Line3DBox[{776, 990, 1194, 775, 989, 1193, 774, 988, 1192, 773, 987, 1191, 772, 986, 1190, 771, 985, 1189, 770, 1279, 1080, 769, 1278, 1079, 1188, 768, 984, 1187, 767, 983, 1386, 1071, 982, 1385, 1070, 981, 1384, 1076}], Line3DBox[{777, 1081, 1280, 1072, 1082, 1281, 778, 544, 779, 1195, 991, 780, 1196, 992, 781, 1197, 993, 782, 1198, 1083, 1282, 783, 1084, 1283, 784, 1085, 1284, 785, 1199, 994, 786, 1200, 995, 787, 1201, 996, 788, 1202, 997, 789, 1203, 998, 790}], Line3DBox[{792, 1086, 1285, 791, 1087, 1286, 793, 1088, 1287, 794, 560, 795, 1204, 999, 796, 1205, 1000, 797, 1206, 1089, 1288, 798, 1090, 1289, 799, 1091, 1290, 800, 1092, 1291, 801, 1207, 1001, 802, 1208, 1002, 803, 1209, 1003, 804, 1210, 1004, 805}], Line3DBox[{807, 1093, 1292, 806, 1094, 1293, 808, 1095, 1294, 809, 1096, 1295, 810, 576, 811, 1211, 1005, 812, 1212, 1097, 1296, 813, 1098, 1297, 814, 1099, 1298, 815, 1100, 1299, 816, 1101, 1300, 817, 1213, 1006, 818, 1214, 1007, 819, 1215, 1008, 820}], Line3DBox[{822, 1102, 1301, 821, 1103, 1302, 823, 1104, 1303, 824, 1105, 1304, 825, 1106, 1305, 826, 592, 827, 1216, 1107, 1306, 828, 1108, 1307, 829, 1109, 1308, 830, 1110, 1309, 831, 1111, 1310, 832, 1112, 1311, 833, 1217, 1009, 834, 1218, 1010, 835}], Line3DBox[{839, 1219, 1011, 837, 1220, 1012, 841, 1221, 1013, 843, 1222, 1014, 845, 1223, 1015, 847, 1224, 1016, 849, 1225, 609, 851, 1226, 1017, 853, 1227, 1018, 855, 1228, 1019, 857, 1229, 1020, 859, 1230, 1021, 861, 1231, 1022, 863, 1233, 1024, 865}], Line3DBox[{864, 1023, 1232, 862, 1324, 1124, 860, 1323, 1123, 858, 1322, 1122, 856, 1321, 1121, 854, 1320, 1120, 852, 1319, 1119, 850, 1318, 608, 848, 1317, 1118, 846, 1316, 1117, 844, 1315, 1116, 842, 1314, 1115, 840, 1313, 1114, 836, 1312, 1113, 838}], Line3DBox[{867, 1125, 1325, 866, 1234, 1025, 868, 1235, 1026, 869, 1236, 1027, 870, 1237, 1028, 871, 1238, 1029, 872, 1239, 1126, 1326, 873, 625, 874, 1240, 1030, 875, 1241, 1031, 876, 1242, 1032, 877, 1243, 1033, 878, 1244, 1034, 879, 1245, 1035, 880}], Line3DBox[{882, 1127, 1327, 881, 1128, 1328, 883, 1246, 1036, 884, 1247, 1037, 885, 1248, 1038, 886, 1249, 1039, 887, 1250, 1129, 1329, 888, 1130, 1330, 889, 641, 890, 1251, 1040, 891, 1252, 1041, 892, 1253, 1042, 893, 1254, 1043, 894, 1255, 1044, 895}], Line3DBox[{897, 1131, 1331, 896, 1132, 1332, 898, 1133, 1333, 899, 1256, 1045, 900, 1257, 1046, 901, 1258, 1047, 902, 1259, 1134, 1334, 903, 1135, 1335, 904, 1136, 1336, 905, 657, 906, 1260, 1048, 907, 1261, 1049, 908, 1262, 1050, 909, 1263, 1051, 910}], Line3DBox[{912, 1137, 1337, 911, 1138, 1338, 913, 1139, 1339, 914, 1140, 1340, 915, 1264, 1052, 916, 1265, 1053, 917, 1266, 1141, 1341, 918, 1142, 1342, 919, 1143, 1343, 920, 1144, 1344, 921, 673, 922, 1267, 1054, 923, 1268, 1055, 924, 1269, 1056, 925}], Line3DBox[{927, 1145, 1345, 926, 1146, 1346, 928, 1147, 1347, 929, 1148, 1348, 930, 1149, 1349, 931, 1270, 1057, 932, 1271, 1150, 1350, 933, 1151, 1351, 934, 1152, 1352, 935, 1153, 1353, 936, 1154, 1354, 937, 689, 938, 1272, 1058, 939, 1273, 1059, 940}], Line3DBox[{942, 1155, 1355, 941, 1156, 1356, 943, 1157, 1357, 944, 1158, 1358, 945, 1159, 1359, 946, 697, 947, 1274, 1160, 1360, 948, 1161, 1361, 949, 1162, 1362, 950, 1163, 1363, 951, 1164, 1364, 952, 1165, 1365, 953, 705, 954, 1275, 1060, 955}], Line3DBox[{969, 1066, 725, 968, 1378, 1176, 967, 1377, 1175, 966, 1376, 1174, 965, 1375, 1173, 964, 1374, 1172, 963, 1373, 1171, 962, 1372, 713, 961, 1371, 1170, 960, 1370, 1169, 959, 1369, 1168, 958, 1368, 1167, 957, 1367, 1166, 956, 1177, 1366, 1064, 1065}], Line3DBox[{1063, 980, 1062, 1379, 763, 979, 1186, 762, 978, 1185, 761, 977, 1184, 760, 976, 1183, 759, 975, 1383, 1069, 974, 1382, 1068, 1276, 1077, 1381, 1067, 973, 1380, 1075}]}, {GrayLevel[0.2], Line3DBox[{313, 524, 1183, 314, 537, 1190, 333, 552, 1199, 348, 1291, 567, 363, 1299, 582, 378, 1309, 597, 393, 1321, 612, 1228, 408, 627, 1241, 423, 642, 1251, 438, 657, 453, 1344, 672, 468, 1353, 687, 483, 1363, 702, 498, 1375, 717, 513}], Line3DBox[{315, 525, 1184, 316, 538, 1191, 334, 553, 1200, 349, 568, 1207, 364, 1300, 583, 379, 1310, 598, 394, 1322, 613, 1229, 409, 628, 1242, 424, 643, 1252, 439, 658, 1260, 454, 673, 469, 1354, 688, 484, 1364, 703, 499, 1376, 718, 514}], Line3DBox[{317, 526, 1185, 318, 539, 1192, 335, 554, 1201, 350, 569, 1208, 365, 584, 1213, 380, 1311, 599, 395, 1323, 614, 1230, 410, 629, 1243, 425, 644, 1253, 440, 659, 1261, 455, 674, 1267, 470, 689, 485, 1365, 704, 500, 1377, 719, 515}], Line3DBox[{319, 527, 1186, 320, 540, 1193, 336, 555, 1202, 351, 570, 1209, 366, 585, 1214, 381, 600, 1217, 396, 1324, 615, 1231, 411, 630, 1244, 426, 645, 1254, 441, 660, 1262, 456, 675, 1268, 471, 690, 1272, 486, 705, 501, 1378, 720, 516}], Line3DBox[{321, 722, 1379, 723, 322, 541, 1194, 337, 556, 1203, 352, 571, 1210, 367, 586, 1215, 382, 601, 1218, 397, 616, 1232, 1233, 412, 631, 1245, 427, 646, 1255, 442, 661, 1263, 457, 676, 1269, 472, 691, 1273, 487, 706, 1275, 502, 725, 726, 727}], Line3DBox[{503, 707, 724, 1366, 488, 692, 1355, 473, 677, 1345, 458, 662, 1337, 443, 647, 1331, 428, 632, 1327, 413, 617, 1325, 398, 1219, 602, 1312, 383, 587, 1301, 368, 572, 1292, 353, 557, 1285, 338, 542, 1280, 743}], Line3DBox[{504, 708, 1367, 489, 693, 1356, 474, 678, 1346, 459, 663, 1338, 444, 648, 1332, 429, 633, 1328, 414, 1234, 618, 399, 1220, 603, 1313, 384, 588, 1302, 369, 573, 1293, 354, 558, 1286, 339, 543, 1281, 324, 751}], Line3DBox[{505, 709, 1368, 490, 694, 1357, 475, 679, 1347, 460, 664, 1339, 445, 649, 1333, 430, 1246, 634, 415, 1235, 619, 400, 1221, 604, 1314, 385, 589, 1303, 370, 574, 1294, 355, 559, 1287, 340, 544, 325, 1384, 529, 740}], Line3DBox[{506, 710, 1369, 491, 695, 1358, 476, 680, 1348, 461, 665, 1340, 446, 1256, 650, 431, 1247, 635, 416, 1236, 620, 401, 1222, 605, 1315, 386, 590, 1304, 371, 575, 1295, 356, 560, 341, 1195, 545, 326, 1385, 530, 741}], Line3DBox[{507, 711, 1370, 492, 696, 1359, 477, 681, 1349, 462, 1264, 666, 447, 1257, 651, 432, 1248, 636, 417, 1237, 621, 402, 1223, 606, 1316, 387, 591, 1305, 372, 576, 357, 1204, 561, 342, 1196, 546, 327, 1386, 531, 742}], Line3DBox[{508, 712, 1371, 493, 697, 478, 1270, 682, 463, 1265, 667, 448, 1258, 652, 433, 1249, 637, 418, 1238, 622, 403, 1224, 607, 1317, 388, 592, 373, 1211, 577, 358, 1205, 562, 343, 1197, 547, 328, 1187, 532, 305, 1380, 747}], Line3DBox[{510, 714, 1372, 495, 699, 1360, 480, 684, 1350, 465, 669, 1341, 450, 654, 1334, 435, 639, 1329, 420, 624, 1326, 405, 609, 1318, 390, 594, 1306, 375, 579, 1296, 360, 564, 1288, 345, 549, 1282, 330, 534, 1278, 309, 521, 1276, 738}], Line3DBox[{511, 715, 1373, 496, 700, 1361, 481, 685, 1351, 466, 670, 1342, 451, 655, 1335, 436, 640, 1330, 421, 625, 406, 1226, 610, 1319, 391, 595, 1307, 376, 580, 1297, 361, 565, 1289, 346, 550, 1283, 331, 535, 1279, 311, 1382, 522, 739}], Line3DBox[{512, 716, 1374, 497, 701, 1362, 482, 686, 1352, 467, 671, 1343, 452, 656, 1336, 437, 641, 422, 1240, 626, 407, 1227, 611, 1320, 392, 596, 1308, 377, 581, 1298, 362, 566, 1290, 347, 551, 1284, 332, 1189, 536, 312, 1383, 523, 730}], Line3DBox[{746, 1381, 308, 533, 1188, 329, 548, 1198, 344, 563, 1206, 359, 578, 1212, 374, 593, 1216, 389, 608, 1225, 404, 623, 1239, 419, 638, 1250, 434, 653, 1259, 449, 668, 1266, 464, 683, 1271, 479, 698, 1274, 494, 713, 509}]}, {}, {}}}, VertexNormals->CompressedData[" 1:eJztfXlUz1v7NioiszQoUyVDocwlFGUKRRkzz4REEUWDZCxFclSGNBiSREop IVODKeKY0kEc81gU8a7vdX1a6z3ftXa/N+u853me33q+f17rXvfn3ve+973v fe3h23q606hZNapVqzZfqVo1hWqi3/t+/+n49VEa5kn2IRk3f+5cndH8eIaC 4+J8w+fv+q17sm6QDB9nQjyzpRPwxQNb95bhE31DgXcZ7Ax8bvDSkTJ8vdFv wPNmLaxUz6s8Z3zXs4S4swO/+6/yQ/MrmrDn66yTq2T2rFi3BPaI8H3q5VNk eG7jE8A/lS2oVF6E35q0Af7x2JMM3MSM/kw/owM/e7+k/IGZS4GfqO8KP8eF JAEf7EN/5gv09Bq+FN+Nmkg9z5cv+SU/j2m1HN8dnLHSQ6bn9TLqmZqnBzu1 m6wCPnz8MuArnDbBHs3L7sALjVyApxVowZ5tAR7Am3u4Voqbt/8JP8/uvQL4 9ndOv6THRWDPJIH99oL2ugr03Jnsiu/2W8vvbl7A77a63shahhvU7+8J+18z Tq5f8oOe0wuIO27keDnqtgTffTvDAvjK647AUzu0gp3nkgcAv3eMfsgT6FHr qQ57TLtSPjZ/UaV4qHcZ/Fy3sB9w3SHzfknPFYE9yQL7jwjae1Wgp3PyYnz3 aXvqUb/I77adrQo/vzJn/M/YzXxyRxoXq+XGRbI0juLlxtEZadytkRt3dwV6 KsZ1mWC8y+MVeeOqIG/8v+q5JbAnXWD/CUF78wV6KvJGjFzeGGSoBj8/dzqA ODdsS/0luhwXK68Sr3GB+J1by/Dd2Av7gTdSoZ5Hfhx3qzQPAXd6w/HyVaBn h4kO7ImeesxNhtsFrgb++LUq8EFZe71kuFEg40fbV2mqDF9eLx7yOQorfknP iOwg2NM+NAHyTaxWAe/Z0QD2GxZRj9dCT+BG7qvQ3glBR4HrbHIHbiPQk5Di ju/ajqWeDC/a83ptA/i5V9Qe2NNsP8dj+Cpf6MmpQTvfW84H7tFpMb77vXQ3 8J8b5wL3LWwOO68OjwA+aSHjbbdAj8gPInx2z6+IZ81lu4AfUJj9S3p2Cuzx Fti/UtDeUIGebwsW4bsfM4iHezn+18//oJ8j8rTh55DejP8++z2AjxSMiy6C cWQqGHd2Aj2i8S7CRXlD5P/J+4xbyXBX7SjgJ7Wd/y3jWeTnqsZzLfU90ONn nLlYhnezCqzUDyK/VdWfIvl/lZ8r6o3ncvXGxxPboMd9/ublMnyxghfj2T6t qwxv5hEA3G75GuBv+w1DvC3tW7hGhrfTmwz8s0BP4j1z+EfPNxB4r/t+wFd1 MASu8/YZ9GQNY79vsU/ZI8MXRtwFfriZ3S/pSVHy5Lx86zFwRdfpwAMsSpvK 8PUhQdCjH72edZqgvakCPd/1Y0djXE/4A/ih8inA28SmAo/fuHelDF/VjvV5 mqTHXU7PBdOV6F/D75R/UkT5q6/bIh6q2UYCt7y8EvhpgZ74ATXQL0Pd9kB+ 82TW+de6WMM/bW1mOaNu2be9Uvmq6vljQwDs+a64D/L5e9yA5wjszxS097FA j+UKN8Szzjni3veZ35ICk+Hny8O53vFLca7UzxXrQSvBelBTbj0l8nPF+m6G 3PruY7kl/DMhX8MVdp7fXKl8VfVUrAfVBOtBefvtBe11FeipWA+aya0HR0Wv Ar6vrT/GhXY/b8pLdbi7XB3eJ6ujE/QkFMBvffwdgAdJ426D3Li7K9CzLuMj /JM1iHnmVFfmmYr1SI7ceqQiP7SRyw9V1fNOymMecnnslZT3XOTynqmgve8F epyX9jaA/6dsAa7z0Rd4tmIi4lklYwf4JccDC/4Szx5ycThfwF8tFfBdpwV6 7Hd9gx9iDodA3r2A80izZ33gz4JkuxWIq30+lcpXVc//b75u5+M0+PNP3RH4 bkc75o2q8kiPO3awkelRGmEE/eYXuH739V6CcfHotjHwx/a0U+X5iF4YvyVe qFtGzfL6i3yBnHyFfkU5/bc3DIee8O4jYb/TktWV2j/Ysz30RC+kf67l0D8e Ea2AX1Zmv9drPa1Se0T6w3quh5/bqc+BfMEO+nnlPNZpN8e/QntTUj0qxUX6 Nwj6UYSX6ptgHC0c8Rb6HQ96V6r/mz7bO+IW7d94k/XP/XFcz5apvYaeOSWr Kh13VY2f/624lpUG6smJ1nPdMS/oL/uvf/4vXLRPcbqM/NgSo12Ydw5e5rzs l01597BRkK+jxvG4foEaea0fp8AfDk3kuC6qWYp8O/Bka9T5GoZzgCu01Ib8 LpMxmMc/3uE87mtO/lMnuA/06D1hnuk1g9990yMQ33XxoZ2XXhDf+rUf8IT+ tCdkJe1/Ff4C9m9tRPs7BY7tL8P1O5B/26dLPMu9N8ZRwvS6qN8UmrIO9Bqx Ebi2djvI1w6mfGDD7Ygrm+1psPNDPNcvxhrkY40vjAA+5TfmgXY6W/rI8MKl +xCHaqXLOe+MdsF8UTioDezXWsH2fj7bAHZOWmsLXDmT7e2frWqGebmM9c/G zoxn02HzrGS4SYwX7DRuSTtPXqH9en0eQD53yNJK47/s6RvoV2i/G/IKqa7/ q8eLaP+oqnoW9VCzlOnZ9o314Z/5zn+p3+T3s/4nPVvl9IjsHFDvNOQvreH4 /R7GeAtclwH89QvqWXKSesqD7S1k+P0Cyn/ryrga2mAM8J+W1O9sS/1xul4D MO6iKD/iJvWX7fIG3liF8uffUb/xga8jZHj6Es7vNreYB1brlAF//Dt58gvv qcdt6OIhMnxBTeq/lM34PxsWM1CGt06m/fEzKp/3+zY5PBT5xIXrhc3RjPPw +DWw83BXjpd5T7mOeNVqHNobupB4UyvGeZedZ+G3dY2Jq8dRPl3a/wqW9r9a SPtf9QZrQL6THnH/bMpbSOumOdK6KURaN9UXyIv0dxbY80LOfjXJ/lCpvXFy 7W3e7Tv8v6o6/TO/iP07Le4A/Hz6EfHR4yh/v91X5I03U7lPlLCM/bhi8xfo 0Y3hvtKXvoznklqe+O6o3ylf0of9OHCFHew0b8x9pcjdxP0/pKFdHZMpH1WT uLq0/9Vb2v86LO1/zdnbBPL5lymvpUc8TNpfqyftr+lJ+2tzBfIi/RskezrJ 2TNAst9Czv7PUnvt5Nq7XOCfU0pR8PNMX8o/TqA/H58ug5/jtjHOPdsxzr2k 8fJUbryUS+Ouidy4GyaN3+pWfx2/wVIeeCOXB0T7XxX5Z7sgj8nvr1XIBwvy lbz+irz0Vs6eoQL7K/KMqlx7Vwv8U5E3dOXzxtrv8POBc9z/GpTA/LDnz2/Q 86gWcf8V/K72TI6j+qYHmU/cOC4c88fCzu9LiZvcJa6am4l2DZ1liPnd/Abn 9/nPWsAPV8riUFcMvc71XdbPxpC/ErSPcdWX8SDiyf/c1wLy/UrIM58rYP3f wJz1T4vO0cifJrbM51ZfzkH+lnUs7OkbwToh030y7D/Uj/z8kPFcr7nU2Yj2 pisR3/WV+r8G1MC6LOAm9wt2l3K/oLdyPPx8NYH2rF9A+f0FxfBzWQl58h7G XF9b9i+Gn43MiLuXkh8+l+6B705dRB7Y/SvlG3UeCTuHHyDedjzrq3H7U9Eu k+HE252tfN+ny5hGkP9jMvE90npfxHt3FciL9NtL9pjK2VNfYH+GoL39Bf5Z dyoCfnZuRvnZC+b/18//oJ8dDBQGy/CxAYzzccaM8zLBuFguGEcXpXEXK427 odK4q/f5Etq14yn1W5+tfH9NlAdEeaO8kOsvpYN7ON/NYHv3DtI1kuEFS/ah vS5jOH/NcLwAPsdxM/d37ucv+Ef8fN67Ovzs6BAPHsn+BtdfzttZT9baF4n8 5puysNJ4lvdzRX4brHIb7dq7IXmZDK8Z4lupH6q6v/bTpUM7GX5wUCTwkBTO R3pba9rK8KMt6YfXWfTDwCfxwJXrE3c9PPcf8XNZDuN56IWR8M91Nfon0vAY /HP8C/lzh1CJ/xwUgjjfup31zDhdxsOHsnd2iDd7zr+5Tdje9Mhb0KP1mXom BlNPzJHe4FcjW8RgHgxfzv3lM9eaw/+bLYvAX/n50Z+i/bV3LzpD/sp+TcSJ /gzylpvGcH9zn90NtHfWUc6DPp8yYI/m5KfQ81ZpFvAo3bROMty7eyrsb+rP +nnTXJ3WiJMF5Oe/Hic/v61aHPR03cp9ojM9ON4fb7DE+sUomvybpj75t3kr BwK32JTqI8OXvpoJ3Hch6w2LJR9QPxzOkvjYbD/0b+Bi7h9NlXjgivq5j1R/ Rkn151ezo4ifF0Hz0N4dhqx73TxVgdd4a4v+9Ysnn/lKtT/i0zp48xLUbyuC gB+V9tGspX00f2kfTYQrf+kF/zvfPb5Uhi8f6Q/cdEg+/JNrbgC/XfPivuTY 3g6w3/MQ21Uvke1SltobJNfezSN+wj/T+kYAn2bPOurapVjE8z5tyltf4r6b ljr9HJ1ZDD8HT6Kfj2qWQk/weXvkjaXL6LeK9eBBufVR/dccd1mfOnPczWGc N2jCcdq4t5a3DC/zIX+1aHdD4I9b084berRz4gAz+FnrsSLyzNP2G4BbSOvB mXLrQRF+aX1X+Pnh2/fQM2jLWuBPFG/Azw3ikhD/ZnOZ/yvWgzsE68FDgvXg SsF68JTcevDSs/3AvW0/0k4z1s8zj1jOwnh8bQ//l3+dCnzp5wU9Zbi/VyfI G6XRP0k2ZzHuFMKi4LeE9xIP/5jx/FtBTfi/jibzVcDoYvhn48rR0L+hiPsC CoFK42R4sdd76C/rwfEu2l974/N9rAy3txkDPbGDZwCvWD+qSOvHNtL6cavp KdgTevA+/GxRyHh7I+U9N7m8N+9mIfzgefAR8kCgwSTiloOA+7fMRrtyDjE+ I+KUMY83zOK+26AI5rHDC+YgnrdEMJ/UbMV8krG4BP3ld/cl7NxzkP45KvEz r+X4GQ19W8TDgsN9EbdhBWxXyOk4tGuz1TPgQeHMh+s61wXu+s4K7Vp8jf6s vqs74nm52nf44eZB5u3R0j7afmkfzUOq30T4S7uOiOdGruz38Qns99V6uYjn 7HZ70I/Ji7lOEfFUIj5KxDtVlcerKi7i99725frX06ge7BmXxjx/5HfiGl4J kK/2G8fdsVLyeLvW1IX8hTdsr+6o0fDD20btgfeQ+O2NCfSDqYoV8LJdlD9f k3lvYN2pwBc6LKrUD70Kp4OX/lPzGNaJ9vc5Tl/dzQCflprTEPH2YzH9GTPH Bjzz7GuJ6EfnOxwXa0c2Q7taLp5HXt2S+SHCjfxAjFcg8FXdlvwl78nzY/eU yI9p7YkEXurI/DN6Avmxhb45wItPE9+Wdwbyw9cwL40P4nc1NbhOHza+Gb6b mU08ZKYP/DYs1AK4jwrxohjyCcpP5gB/G0d/ljwkn9DdjPZbnqP/A4OOww/L iq/Az3af6OdmPYZAT/y6HODBbvRb/kX2V/CEXsCnpVG/5hX275uMR9D/4AP1 298jT2IV6Af8cCfpfHIi/Xy6Zyfanye197g65DO/3oIfMoqX/iW/yfNjE7ur Qt788wvY8+KrFCfTyCc03BgEfLAn7Zx7lPHpZEL7G6wlriZn/0PJ/lPvyds4 JtD+H7Nof7c6rH9iDhkCv9Kb8o4anHdGJtL+tWtof+sF5MdGv/kT8lbH+N0f Hozzbps1Yc8oRcZPajT9rKIxDLi6v8Rvn2c+iYhdxX3V5cSvvUhHu3ocOgJ8 5DxpX/4BecJXnoXAW54j3vYTecWOTo3gT/tQ+k3Ejx150hTyfUZzHyp+Ctsb 3pZ5wFpTC/prhhEfvoV+LiqxBn5+NO0cKNm/T87+HtXYXocc2h+5V9p3NmY+ vPmxgOc0DKR99nHkIdM60H6tdrTfbBj5scvh2fB/p6n0v/py9lertFfAHe7Q zhspHEfOl+ujXRZrKT/xI3k8zwdGwPODiZsfJR/1Zn8+8kxmb+b5+tsZb1dW L4Gd+7PYrvIBjOeXpurQozCWekTr3HHbm1M+aRTmqf2TOL980OO+pMvRZ2hv jRH0w8Sc81x36wcjj5X2oZ51VhNg/5j+3WHnQ3vmtwMXfclDZtF+taW0P7wP 66iAsa7wz7ePjPNRB1kvrShRg/05T4k7Hy+Bnxc15H5or2lc3917xfldyykC dnpJ6z5dM/LMZ1N1gXuvZ3/19WE86NUn72ekSb/ZXmP8rMvlfmLXBOIiHrKq vI2ItxTxkCLeZq7Eo36TeNReEo96tN5atLdsAXnLwN/p55zeXBckLTwM+0NM OE9FT46Dnx+vJm/gW5frsv/yY/8MPybibXLl+mu71F/HBf0rz6tXxINWFOfB 8qIYjKPufzj/Jd5aysVbVXn1qvI5/248pIgfW5vK+Ven1n74bZ0G808rnVmw c7zKKRcZPuHuOuBjT11BHa606TD65cMJ5j2VFHV8t4Y+80a7hcRtS7Xhh1GZ 7Pe01e6V+jOkhSH8uX1lNPolVHNJpfL/Kh7yY2f6OfHGEfj5WU/6OTUhAfbs HnAH67XMlzzHNSMlZYIMv3h+P9aVKXW4XuuTw/W4/gM1xPOcXozzuWfuQ4+3 kS34k2XpPDc729II69bC6y5Yl6W1Y7ypOLyfI8PXfFMEviGG61YRPzb0Yk/4 eYYO+c+BZ8i/ua7vCP3JJmqQv2BOv01wO4x1n9qNA7DfJ5v6tz86jXV6bK4G 7K/ryvHyxHo87DfsZ4q4ataIPMPQp5/g57D3TrDTS4k8yaVRQ7CePdlRGbjy d/o/K+ED8rPy9Oawx8iU6+KgndXAN569w3X3oI787rZtU/DdjV7uwF/WJm95 e18RecgNPN8eMoz8g5ZBOtp1aMtx+CE8mvF5avEA+KEoSYk8sP9G4FFv9OG3 uT/T4Yca8dL6WsCD5bYpRb84pV/EeGkk8Q+XwwdD/2zt9+DZIt6TZ9OOyWI8 P2C9l1DI+O8v4PcU9gwxRJ08MRn2LypnvIX/cRR6Rk22A+5ylrxBh267Ec+d 8sg35k3jul7EQ4r4Mb+7rHO8NmajXUoBjFsRDynixyw+Nga+5Vof9FcdN84L uxIs4OcjuZfgH9XXvOdiIeDBtmwmXl2hL3DXVfTzNJtu4BPUVq9EPyrGkuc5 Me4m/HNqguSfU/RPyyPjYX+dzVvQriAPzkct9nI+StW0Z116kPiHdT/gn7bx 6sAjpfHrPZM8pOLoh4iHBSbMh131bOBnq+ItGBdPrDlPTdLoD/6nbip5oc6D yAtpuw5G/95Qmgf/5NnRTm1p3TpUbt061/EQ/Jn8iHG+7gHj/G7UD/inj/Fl +GdhF/pt4wqez++aMwfn88fVYp4R8WOnh32GHrPZnxAnPRypv3Y41zXvtWdz vJ/k/PLBiPspgY0j4P87OdxPib/zCuPRSqET8qpvB64333c6AH/OPsJ9hEvD pHPjVvSzaod+8HP9e8wnxU7VMb+UmBYAVx5C/zf4cQz99XFiHcSb2gfqvyjg PTy/RDP/Nw2GPWo6lN8v8f8+cvz/ge6J8PMCSxXoaXKXegw3KAG/qtsH351i wzgf9+d3+KfmwBvQMzOZ7RLxYNWtFMFb7njOdaLqZOp31TZAPN+9X4L2HvBj 3mt05zi+++TQAOgpHkl5o9VcpyxY3gTyN6IZh6E/UzEfmZkUwc7LD5jPr9qQ p7W080f/PnJm/4p4oZbLeC7L98dqfFe3NuPqbpAz8JY5+bDfQ7qf1eZMKvql W/E8xKFXTfrzjd0KyE+Z0R1xXnSceVikX3t4CvTM7zUI+p0+/9p5PNG51qrq +Vfhz6Rzs4Okc7Oa0rnZR7PZrtu1A9Cu2HVs184N5PH6nytCPGybwjxmu5s8 3q2x3TDubmtx/J5t+wHjy9rvPOQTJnJ8aTxLAq/VbfMN9KP1icrPi4rwNwG0 U7XtMthZdIZ2dkghblcyEXif8r+3XzzcOS7M2pMXWjyn8nOD/274rV3khbrt vIX4fzWA8b+pE+8fpeTdBB77lX5bGsR3CdKaczxqtmZ/LXjEc8UvsvKAp/bl +Nos0PN32S/iaUV4xfxlITd/VVVP3Vc85/wxnfxV0lL6oXg4750VK+cC1wuX 8lIY30/QOZEF/Lx0L6+eQM+iey74rro7vzstXto3DGyKc+C/7VSCP78PYn9t 6Un/Gz/rgTh8NoJ5+7cXvDekaGoC3MqY8gl+vLdS7V1P4HeU2S+fi6Xz9ifI u6pJ919E+Apzzkc207sD33LJ8Zf0HBbYs11gv7+gvXECPfWX8Z6L/mF+d40l v3urMeVb1iTPaTdDOkeh1QR+3rzfA/gq6f5RYibvW9mWuwOffpD5Ld2VduqO 5PxydhP13xbo1/ShH0JziW89srhSfHcu5/eFK1YCV9Fx/CU9NwT2pArsPyZo b55AT9ca9LNVJvGf0nytp8w4b9FoFOJ2bWf2o0tDxvOmYyPJVwfxu4opfOfE Rpl4sCv11HXUhZ2tJ9qR9x7LcaEv0J9TzHsfZbq3Me/k1OE8VauUfHvPTddg 5+mXtN/WvBrWX1eu50HecrXzL+nx8dvM91gmkb/dlME84PiiDez3OUA9pc+p Z0ZPN77rYn8LeKgS27VGoKfIdRnvvzSjnl7fOJ9OXcl8GxBG/urHTNp/1If3 3L+ZEW93if40N6CfM7ZGA68XS/sHP2SeD3pGPsfRn3lpukC/iO8V8YfvjLjO 3bP/EOTPDXD5JT2tl/N+9MhulK+zVuKR7vGe9WjPI8Dd4rgeVGjHe9Y+BuQJ NXPoNx2BHt/ZvGft9oF40hnaI3pXRISL3nMQ4aL3HET4WumdhGvSOwmTpXcS RLjoPZO/652Tv+tdlL/rvZS/630VEe4j8LMIF71fUdV3LUT4d+m9i0/Sexe7 pPcuRHhqq0Do6TOH/GqDIo6XOu21EJ+HlImbDCIedsMddi6afAR4CwOOi8g1 7dFe82NHgXvUk+6NCvT/3NIK9pzsSPnhRh6V4mvvKSBvbLp3GPilSI7fple/ Ochwz0LGickJxkm8Sic9Gd7gGHn1ttK6rKr9WNV+EflZ9H6L5t3G8HODOlFc n85hvXHIm/PvzSnk25WtOf8e78r5OuY49yPmdGQevpcZBv3xOafBdxmu3QTc 8HJH8GDecfshv2cF8+3H5BrgB9KO7gN+U5/tDd7IeuP9/Qjyh5lsl+j8qujc 6b/KzyHlWyE/cWIZeKd638nfNtpKP7eZfRXtOlBd4hUvPuqLOif2M/J84mTG s/6DCaNkePco8tXhnuQ3HMp2sP4prga+q5k2ea3gNjx32v/hF+i5fJzftY/X AH/Vclos9ExqJJ2LfnF9nQzv2CgSuEqXCb+kJ66xN+z5/cJBnoubTj62Q/kz XRk+wJ16zBpST11Be48I9JhNSxwuw8e0In5hBHld+fcuTKV3KmLWz0E85BQZ YP2yeAbrB49BYbhnqpemjvEb3onxP1ktFfpNL5Gv67GM8SD/DkaFfuMtrVl3 /aCex+HUU3HuN1ru3G/L3IeeMvzBZjPoD0+b8Ut6Kt5FPCW9Z7hAes/QcEcg xpfl0mbQcyKJ/PlKQXuvCvS0lt6ZbCe9MxnyuuI+11/f26kh3bvv7Z2C9xx+ 7zoKdWDhao7rBw1XYByNiSY+2EyqG8/pY9y1LyX/vL8F+z1doP+iZnW+79F6 JPfpEllXfy/gvsPKiMvIMz1stlYqX1U9X6f4wx79I3aQNymR3sMR2H9P0N5S gR4Hm+Xo92GO1FNkzHovM4zx37vWOMT5DX3OIwVN5yGezRXJG78Opf6g7KfI n+dP2SGfeKexvwzf3jWW4cVd+0N+wGvOdxcE+m/W5zp61Q/ec98r5bHJijyX m/S0H/JYizzy3ru3N4A92+vRHs9Drr+kp4k3/XP0PfX4tuF65EzcIvB17x+O hh7FYZw3AwTtVRXo+fGE/XW8twX7fTj7K19aP2rLrR8jfZY5or/+6I44tL3M /YuO/Xc3Qx5LXML7Xyk8n3xHoMfi/if4YZZqT+hpksV3qJyNeY534XPery+I p7xy114Yv92HOEP/Xoc1v6QnsjfnnXGKi6Dn2zOp/imMQX1ivI56Dq4nH75X 0N4ogZ6SHhvQj8rlPbmPU4f7OH8Xn9bflHzgndIG5HtPMN+Kzpc+yyNe+1Mi /JC+RVrXm4Vh32r9K/J+TXQorzYrHvf9J34m31j3gXTve/sh7JvMVKV8zVP0 58Goi9gf35NAfOFZxuEMpdaIz+/jbgPvI/EVVn6R0G9zrpj5YQLj8FhUG/D/ L4dchPy769TzzN0I+VmrP/dVf7/J/FBVPrCgZjx47KB35PH8LnK+613cB/Ns tyTKKzfmOHVSfow8rz6U8hOP0Q9Wd5TAn592J26qJL2bOtkUdl61pp7lU6Vz 8iqPgbd2JK9V7Xe2q3cu8XoS/ugO8WKJf/OQ499E5y1Xz7zcT4Y/TieuPZ3y NhOawp97LpBny8pkf9V4YY52Hd9EvLk0HoemNcM+S69Z1KN7lfrdhl4HPmke x+8nia9rJvFXYXL8lehcYlL4UMSbSVviQaH8bv9Xq4bJ8GRv8ngT/FjvralT ju8en0n59tWpR8TniM7jNcjPQN1Snkzexj6W/TLE/Cn8uTCK8q+7V36urOzj ZcRP2AzyDMU3OR9V9f3Sqq73/1Xr6L+r/hedqxGtCzwd+mLeXO/JdavDdM5H 0698wn7WxTlcbxoFcb2pOVwB+ncHct2q3YH7ieo+9RGHL1QpX1Sz8nWraB3q sykE+sO0aOe4RbS/TeIh5DEnPfrHtp1UBz7l/vIyS66zrGuRL0r6dBZ5MuEP 4sfqUU8Dwfklo0snYOexFlw/XutGe4K1fRC3zi0yUI8NbsB9fIfDtTsgD7hz /XhNv/L1Y/bFePizR23a/7iM381a1xP5sP432jPgicRLhN5H3vgQQPt3rGG7 8ub9RJ7ZcYa4y23iuh+6Ir8dDKSeBOOKd1OfA0/rx3VNh1iOIztjxc6oG9cq YL32ZTrP4Szp2Qn1p/ejONRjmaZSPePmj3pA92cJ9DSx4Px77U+vHjI8Y2Mx 8N9usq6r4WoC+zdO5/qofzrXR277JyLe5t7l+nHW71x35H3PxrmFmR+aIk5+ GlHPuZoDYU/Mi5U4L3erbwDwDqdT8A6nwxDeQ/S7wPVIbado+HmTuQbwYBWu 71ZnfEO+Gp7DdUR/6dz1xiFaiJMu3zajrsjyZbvWHTmDPBalzDpZ4THnqdOa RYgH1WLioQuYr1wWs36+HWcO3GiaW6V1iGgf37oZ3yfveorzuL7E258pdub6 VCsb9eohZa6npjxYCXlnux5ob4Al7a+n07ObDL8Ryrro5Wz6R78a6xOLiC48 7y3NX80cWCcXevHcctgbxk+3w5RPrpkLe1zG0Z6oAPLhRbm0s2FzzstJanw3 MinpKN9FP0Y8Zgbr0rE3eS8g+7bTL9VpGg85D6atHwQ924xof3YHfZxbG5lz j+9gbKX+a+V+GI9XP08Hrli/8u/2ymMdq1KT+5Jbtkv3UAxVEScR8axD8hzY roZt6mF8FdUsgv7WF2jP1eBEzLNbdvK9rIhhjLf1irXsZbhXBPfp+j/gOve5 cX3ID1vGOmFmP6e/1Cfy+4PlIcMRP7dvcx6fq0p5S8H8flKqB3rJ1QMT29bB eFTUpbzNn7RnkgAX1SHLBHXL6DdnYGf129y3epRL+5fP74/8cC2OePYG4pfu q0E+/Tnx5S+JFxdloe6qVsj9rOz19H+6cWO0N+sp6w2NEubhyYoq8PPPBsS/ bF1aaT3TMPcZ+nHTXdYn26Rzd6EqxPdKeKKEh58xRl261577Prvesr07ZisC nzCeuHcJ8XM7CtHexLbEoyKl9aOvGcb19W3cV7JVoJ1dQ+JQ/3S8QvkryfTD mox6iEP3z8z/9TtyXhs+uTbi1tEjFnn4aQzzlWj/qOGN95gHD+zgfDG1D8f7 /WsuyG+N11FevwHl1y9Mg56pL4kXSveIH+vtRntVjtKe/FTORycF82+6YL5u K83vi+Tm93VSPRAqVw+I6is1Ae8tki8tqAE/uB0lfnk28ZKDX+B/A0PiPzbw u+Yd/sT8Yq9AOxt/kPiEk114jleL7epzjnWa6Hx+d+daEzG/W8YBHzea88is zS6QX+tDPnxX88rPmX+S6o10uXrjaqg+1sUnfo/h+Tc1xtV73cfQr7v3E/rx +l5+d/VUQ+Tzqfu/YX5x16v8fLWIp12+qw342MLJrAemb5TekRDUFR9O8Hxy Qp0r8FviBsbDpK9+GNejj6vBP7EurDO9Wi3BveZ6zzi/57bkvCY6h6whvTfV S+69qVZy/Ocuif88K9Ub0VK9cVOqN4wmPES9EbTCEvK20rhuMXwm+t1hNs87 GUnnIpIamGG8r8/ludxTroyHPV2bob0XfFk/GCQwn7QL4brySGueT657ULpn ITjfaxrfCX5Ov7QZ9dtkT94juCTxiq5yvOIGqc4xlqtz/IcooA70TvOHnrvq vC/fsIh5b2AH8oHTL0j8lYIh+f99nB+7hkr36ZLm8/9Qcuj/xqfo/5gDO6BH w5V1kUcN1kV9JR7AWI4H6Pw5DHXXCGPyrgkzed9cp5jnxuueTYKdnYdyH0fE 71Wca+ord67pY6wG6vbI1BPQ0yeY7Q2MPIXvHi7ieeyjcexH1YZt4bd9K8n7 DYmhnkMSD7Nbjod52uvwXMwLBj1gf7gl339WL2uvLcMHn9ZC3Oo+Ip+WFb0D +bO1N/X4LKaeCXq8L597IgDjxf8sx508Lxch8XLjBfItnd8iz+zawfOx/v2k e9lzlZBXUzqST6ttyDrZvYPzZNQPZuTlJtVlP/rWNZkvw81rsF0BP8nLic6d VrWu+7vwgeN4X6ltc/JpT1yk84eFvCfb243447ocF0cX8Z7O8L7Eux+mfLdP PM/cvC77pUdc5efiojN5X7JWM+Iz61XOj11S5buCU5WJv33H/OwdzvPnS2cQ f7OO8l0M+I6EX3vi5m2Jn4jn/dAxXzgeLdqxXaXteJ93Rz7rVcMw6tfrRT/4 BLOerN9cuv8r4LtK5Pgxdan+HDiF92rVrIn77av8nnJrwXfzpHvZ2+XuZY+x pv9ntmM9PD2d43Hn+Wi0K7om5YcZUT7QjN8NsGX9uemRU6X1quMr3r/uMZ14 jXLKi/i0L6No53Fn4g/ViLvf4by8ph/r5AJ12plhSzsvNKd81kbq37WP6ymd 0xyP54ayv96q8J5+uh1x4530j4hnM7Aux3efhLC+VXNhPCw+fxDf1XOlfPXn 0ruagvuMIv6t/gnesyixZr3ndZh5+z/lXud/yv1NET6jiPew9u0lL7dzJ+vt wqnr8d0beawnd/7Guqhz3kTYmVGXPJuV9B6a69CLaNehBMpbTSMu4uVE9wpt CvRxX8byIc85KCkzno/fOou6XUmH9fBQvX/mnuC7hhyPPW/xfMiak7Tn09Vp zDPRSbgXM0qT86PWyTzUS5d1eR/tRz7rxkULWwJ/qcA62eG4c6V1tWLf0/Db nmTak7LE8R9pr8GOH1iP9E5dzTzvxPGu9+fvsD9jdQ3UM0px/L8Mv9LuqJfO Lef+lKEtx/UO+zqoW9Ynk5drZs3zDDuNeN+wUN8b+uu7c7zr6zVEfThhJHm/ ui0ZJ05LuN6fc7Y29LdqQb/lh/C+W0AI9TdUpX7V7amoY19O7As9Vz9JPH82 92HfLc1Cf91/w33Mc4FdUOdkzbiCPNbKhnE43+Ud5PO3kffLs+B+n4UD43ms dG5BYxfr24p3X6fJvfv6KYD34z7WWgF5g5fSfWQ9c3y395FE3A/dmcj6P1KP 96Q2Pud++nlpf/nZrkPQn3OB9Xx8c2m/2KM39Pwxyh3t0q/PfjnvVgPja4AN 6+EJmZTXEvBvojqnor41l6tvYwR1SIuoRMTPA5MOnAfdOX/tVYpH3Xvn7lze t/Li/CU6xy6a90U8VcHSUswXw8s4P/5mQzs9pHnTV27eLBXMsxXnvRfJnfeu mMe7y83j8vP+Nmne9xfUCR3nfYOd1koSv6QlnZfO5bs0PkPJRzV8Sj1DBvP9 jWMelG/whPK/pfD9jb1JxNMGsO4SnaPWmqLJ93tTOF+bSv/LI+Kp+gre8fja k/crqyvw/PM5ad923n2+35K2hTzSgJH8rnI/tuvTLZ5z3iC9XyF/b329dG89 34DtamhBvLv0Tu9zN77/s/RnW+A9G7G9ovPMp2y0ID83kHVFinReRfR+hYbg /YGQdnzXLu8u9VhI8+OgZL5r92wP8eBeK/4t65b/lHcnRPyV6NxpVd9JEJ2r 7PlBD3k+OzoKedstifFQ+0QNnn9o/hX6bdZzPlLsOBd1iINdKXATf65nq8pf df/ale+tKfN8YIwt7W9cpy3wpDrkryLuzP9Lfhsi5bedUn573ZLnWtN6cj6K HEk7vzRXBH84rgXfsZztSn+K+Ct5nqrinN5C6f3DQrn3D0X3i3ecuIQ6waGE PNhYLfpTdD89dADzw3ytSOa9VpTXEdzXrur9dBFPJcK7R/ZAPGQaqKPO6fuD vM2olnzvtOTFA7S36x3ylgsb8R7ifjvaubgO6xmduMFo76yS+bBnWgPG+cvM 2WNkeKOzHRH/tdKIz8vpZSrD/ex5XmvqcuaTptL7Pxv1ma+KNaT59Gss2mvw 4zP8qaDK/trzP5xPWy3HX3WRzmGaSPXME+kcpo8a79cfzF+JOC+cyPpn2PcI 8EiLepGnutKTcXhz/AfgbY2Il7cnLuJtsuf4T5PhydqH4Z+G3Wh/g+JGGF+D djdAPARdZz4/pngGdWNk9floV7Y667RuPxLQ3m6xkxAP04+wXZOcysFTGdpk Qb9LKONNxGvt303591pxkFcooPz8MNbncYnH0a6GP6T65EwKvrtsQDrGRW6m 9D99YUOxnuq+qx7sH+7GeeTa5vbTZfi8u+S1ImfzPJt2thXua89NicV3Rwcw b4j2bafU5bq+81gDnvOReKdL1u/Bf3ZOeMv50e/Xzo8pXl8IfvjWcp7jciiQ 3u0pV0H9eSic57jqOFBPx1FlmBfivlyAfMRYyv8fFfiDcw== "]], {RGBColor[1, 0, 0], PointSize[0.05], Point3DBox[{5.989892829488903, -0.8582295059257177, 0.3614668686849979}], Point3DBox[{-0.826912362583955, 1.509426052117006, 1.0473710275962713`}], Point3DBox[{3.2390074858387434`, 0.08224610537568908, 0.15404733374183638`}], Point3DBox[{1.6368918618364654`, -0.6986863248034352, 0.8816919796402783}], Point3DBox[{ 7.773320425783489, -0.30790016751365806`, -0.044092331937571394`}], Point3DBox[{2.9206902159859647`, 0.1751427055739737, 0.7314467971139854}], Point3DBox[{7.201518917942471, 1.221692618459779, 0.3073250852237775}], Point3DBox[{3.0891771951248552`, 0.19496735620058345`, 0.4617759162929146}], Point3DBox[{5.979660391553667, 1.1636446733714698`, 0.6448636513797623}], Point3DBox[{1.4796203932542435`, 0.9440985087628949, -0.357616619254818}], Point3DBox[{7.811671481800942, 1.669801841267314, -0.021201135737239394`}], Point3DBox[{-1.6816539404756075`, 0.016271356956533922`, 0.7881665422873447}], Point3DBox[{2.0041321473525215`, -0.7344388117867335, 1.530470932664914}], Point3DBox[{-1.2406251460926399`, -0.943968284158695, 0.5344843037791005}], Point3DBox[{5.614044221340049, -0.9259946927452559, 0.7000443226772294}], Point3DBox[{0.9948503706783267, -1.6556495885057483`, 0.28203668316121916`}], Point3DBox[{-1.8437129832618204`, -0.6031649226038737, \ -0.24256145425135542`}], Point3DBox[{5.775812142241079, 0.35401220001611555`, -0.2193019474381121}], Point3DBox[{7.763187779373723, 1.0120230284653642`, 0.5651663403799512}], Point3DBox[{-0.5537286389720402, -0.10209758746730686`, \ -0.36927533001188506`}], Point3DBox[{-0.9788071800610192, 0.8483407320602911, 0.6483302672973292}], Point3DBox[{6.7760364113946565`, 1.3165612456382094`, 0.6082917864119136}], Point3DBox[{0.034933703070919364`, 0.4776874931288377, -0.08405071949434959}], Point3DBox[{1.0709170142923825`, 0.8350557107713937, 0.4158308875331567}], Point3DBox[{7.603134383198258, 0.9071548235290242, 0.9207846745701337}], Point3DBox[{-0.3815258119084426, -0.9841533072361334, \ -2.0163386401106727`}], Point3DBox[{3.7427724277472016`, 0.3678496779378933, -0.6491432877372706}], Point3DBox[{4.843717742358376, -0.03849726222703499, 0.3642028447139174}], Point3DBox[{5.864277005848307, -0.30981528834176275`, 0.6588948780264678}]}}, Axes->True, AxesLabel->{None, None, None}, AxesOrigin->{Automatic, Automatic, Automatic}, BoxRatios->{1, 1, 0.4}, DisplayFunction->Identity, FaceGrids->None, FaceGridsStyle->Automatic, Method->{"DefaultBoundaryStyle" -> Directive[ GrayLevel[0.3]], "RotationControl" -> "Globe"}, PlotRange->{{-2.9999995714285714`, 2.9999995714285714`}, {-2.9999995714285714`, 2.9999995714285714`}, {0, 2}}, PlotRangePadding->{ Scaled[0.02], Scaled[0.02], Automatic}, Ticks->{Automatic, Automatic, Automatic}]], "Output", CellChangeTimes->{3.8241812763140593`*^9, 3.824181314626416*^9, 3.824350039213169*^9}, CellLabel->"Out[26]=",ExpressionUUID->"dead5381-591a-4f98-aff3-e9e8a56c28cd"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{ RowBox[{"(*", RowBox[{"regresn\[IAcute]", " ", "p\[RHacek]\[IAcute]mka"}], "*)"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"lm1", "[", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\\"", ",", "\"\\""}], "}"}], "]"}], "\[IndentingNewLine]", RowBox[{"(*", RowBox[{"regresn\[IAcute]", " ", "parabola"}], "*)"}], "\[IndentingNewLine]", RowBox[{"lm2", "[", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\\"", ",", "\"\\""}], "}"}], "]"}], "\[IndentingNewLine]", RowBox[{"(*", RowBox[{ RowBox[{"line\[AAcute]rn\[IAcute]", " ", "regrese"}], "-", RowBox[{"2", " ", "prom\[EHacek]nn\[YAcute]ch"}]}], "*)"}], "\[IndentingNewLine]", RowBox[{"lm3", "[", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\\"", ",", "\"\\""}], "}"}], "]"}]}]}]], "Input", CellChangeTimes->{{3.8241816688850603`*^9, 3.824181762959544*^9}, { 3.8241821904214773`*^9, 3.8241822007343903`*^9}, {3.8241824976367173`*^9, 3.824182499273135*^9}}, CellLabel->"In[27]:=",ExpressionUUID->"80d5272b-9366-48b5-aeb2-c3003a38ac34"], Cell[BoxData[ RowBox[{"{", RowBox[{"0.10071678431451996`", ",", RowBox[{"{", RowBox[{ RowBox[{"-", "1.2655350996162968`"}], ",", "1.6739088151375041`", ",", RowBox[{"-", "0.09431734946435683`"}], ",", RowBox[{"-", "0.7408655579886378`"}], ",", RowBox[{"-", "0.8647982911160952`"}], ",", "0.025279457577675274`", ",", "0.7127567638852929`", ",", "0.03097155047165817`", ",", "0.7571973686751163`", ",", "0.9151110849435722`", ",", "1.1096868606944217`", ",", "0.25244918364169977`", ",", RowBox[{"-", "0.8074218765993266`"}], ",", RowBox[{"-", "0.7447836122574967`"}], ",", RowBox[{"-", "1.3017743953519167`"}], ",", RowBox[{"-", "1.6439748770899596`"}], ",", RowBox[{"-", "0.3533937085247633`"}], ",", RowBox[{"-", "0.03533647090551628`"}], ",", "0.45597482342103857`", ",", "0.03947073572353084`", ",", "1.025564315102922`", ",", "0.8433145352263286`", ",", "0.5698792735359894`", ",", "0.8403500108468104`", ",", "0.3645317737893594`", ",", RowBox[{"-", "0.8570292242330889`"}], ",", "0.1490308086938311`", ",", RowBox[{"-", "0.34966257449433735`"}], ",", RowBox[{"-", "0.7065843237249564`"}]}], "}"}], ",", StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"DF\"\>", "\<\"SS\"\>", "\<\"MS\"\>", \ "\<\"F\[Hyphen]Statistic\"\>", "\<\"P\[Hyphen]Value\"\>"}, {"x", "1", "2.1468962358070023`", "2.1468962358070023`", "3.023911854530948`", "0.09343714449961014`"}, {"\<\"Error\"\>", "27", "19.169275149318285`", "0.7099731536784549`", "", ""}, {"\<\"Total\"\>", "28", "21.31617138512529`", "", "", ""} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{ "ColumnsIndexed" -> {2 -> 1}, "RowsIndexed" -> {2 -> 0.75}}], "Grid"], "DialogStyle", StripOnInput->False]}], "}"}]], "Output", CellChangeTimes->{ 3.8241817658991547`*^9, {3.8241821858062925`*^9, 3.8241822020561423`*^9}, 3.824350039498095*^9}, CellLabel->"Out[27]=",ExpressionUUID->"ee341459-9a1b-4bd7-b9bc-3fc3cf9c6994"], Cell[BoxData[ RowBox[{"{", RowBox[{"0.15138873916419363`", ",", RowBox[{"{", RowBox[{ RowBox[{"-", "1.2080676829793862`"}], ",", "1.548750420448391`", ",", "0.15936116882980503`", ",", RowBox[{"-", "0.5412075719180547`"}], ",", RowBox[{"-", "1.1296794358705244`"}], ",", "0.27808636914770396`", ",", "0.5679454140151244`", ",", "0.2848489964485451`", ",", "0.8160713649239051`", ",", "1.102788911751964`", ",", "0.8361878869586005`", ",", RowBox[{"-", "0.05384352236541316`"}], ",", RowBox[{"-", "0.5844376186239095`"}], ",", RowBox[{"-", "0.9532117690384311`"}], ",", RowBox[{"-", "1.195957847774462`"}], ",", RowBox[{"-", "1.5007351940879028`"}], ",", RowBox[{"-", "0.6980059314328537`"}], ",", "0.050505975953211046`", ",", "0.19335872083764205`", ",", RowBox[{"-", "0.0352310537521832`"}], ",", "0.8707930769012825`", ",", "0.7776084934391615`", ",", "0.5916596698241651`", ",", "0.9913128286479073`", ",", "0.1370365391341083`", ",", RowBox[{"-", "0.9017762369498687`"}], ",", "0.39409496151445345`", ",", RowBox[{"-", "0.16605776769205893`"}], ",", RowBox[{"-", "0.6321991662909207`"}]}], "}"}], ",", StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"DF\"\>", "\<\"SS\"\>", "\<\"MS\"\>", \ "\<\"F\[Hyphen]Statistic\"\>", "\<\"P\[Hyphen]Value\"\>"}, {"x", "1", "2.1468962358070023`", "2.1468962358070023`", "3.0857902941311326`", "0.09075220814599087`"}, { SuperscriptBox["x", "2"], "1", "1.080132073994978`", "1.080132073994978`", "1.5525021725423822`", "0.22387735898836358`"}, {"\<\"Error\"\>", "26", "18.08914307532331`", "0.6957362721278196`", "", ""}, {"\<\"Total\"\>", "28", "21.31617138512529`", "", "", ""} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{ "ColumnsIndexed" -> {2 -> 1}, "RowsIndexed" -> {2 -> 0.75}}], "Grid"], "DialogStyle", StripOnInput->False]}], "}"}]], "Output", CellChangeTimes->{ 3.8241817658991547`*^9, {3.8241821858062925`*^9, 3.8241822020561423`*^9}, 3.824350039498095*^9}, CellLabel->"Out[28]=",ExpressionUUID->"9f894141-1ef1-4907-a19b-74870d120510"], Cell[BoxData[ RowBox[{"{", RowBox[{"0.028835051350479427`", ",", RowBox[{"{", RowBox[{"0.07997704828679159`", ",", "0.7376541638236744`", ",", RowBox[{"-", "0.1377114263789177`"}], ",", "0.6834691550582933`", ",", RowBox[{"-", "0.4058119825608004`"}], ",", "0.43969292680017535`", ",", RowBox[{"-", "0.15645304048087572`"}], ",", "0.16485173428437572`", ",", "0.21215999926116658`", ",", RowBox[{"-", "0.6754433148556971`"}], ",", RowBox[{"-", "0.5318888444746471`"}], ",", "0.6089828883197281`", ",", "1.3268930117707218`", ",", "0.41757527532301475`", ",", "0.43185133222672606`", ",", "0.16953395998224777`", ",", RowBox[{"-", "0.37180470307106295`"}], ",", RowBox[{"-", "0.5869054781701095`"}], ",", "0.10480655324150812`", ",", RowBox[{"-", "0.5642652178635504`"}], ",", "0.39145097658584876`", ",", "0.14671495859644768`", ",", RowBox[{"-", "0.3353425920501145`"}], ",", "0.11511135928637983`", ",", "0.47178045637533084`", ",", RowBox[{"-", "2.1490296016789805`"}], ",", RowBox[{"-", "0.973312912907839`"}], ",", "0.046386589871361905`", ",", "0.339076725398805`"}], "}"}], ",", StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"DF\"\>", "\<\"SS\"\>", "\<\"MS\"\>", \ "\<\"F\[Hyphen]Statistic\"\>", "\<\"P\[Hyphen]Value\"\>"}, {"x", "1", "0.241910366193121`", "0.241910366193121`", "0.5344062737748481`", "0.4712974861308571`"}, {"y", "1", "0.10753880002304328`", "0.10753880002304328`", "0.2375648894708974`", "0.6300549051215281`"}, {"\<\"Error\"\>", "26", "11.769452997984564`", "0.45267126915325245`", "", ""}, {"\<\"Total\"\>", "28", "12.118902164200728`", "", "", ""} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{ "ColumnsIndexed" -> {2 -> 1}, "RowsIndexed" -> {2 -> 0.75}}], "Grid"], "DialogStyle", StripOnInput->False]}], "}"}]], "Output", CellChangeTimes->{ 3.8241817658991547`*^9, {3.8241821858062925`*^9, 3.8241822020561423`*^9}, 3.824350039513729*^9}, CellLabel->"Out[29]=",ExpressionUUID->"b5a1dbeb-516e-4c2c-99b0-7f0445fe1476"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{ RowBox[{"Correlation", "[", "datk", "]"}], " ", "//", "MatrixForm"}]], "Input", CellChangeTimes->{{3.824181359817582*^9, 3.824181409615361*^9}}, CellLabel->"In[30]:=",ExpressionUUID->"1563cf0b-4da2-4f49-a55c-05201c726803"], Cell[BoxData[ TagBox[ RowBox[{"(", "\[NoBreak]", GridBox[{ {"1.0000000000000002`", "0.31735907788264034`"}, {"0.31735907788264034`", "1.0000000000000002`"} }, GridBoxAlignment->{ "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, "RowsIndexed" -> {}}, GridBoxSpacings->{"Columns" -> { Offset[0.27999999999999997`], { Offset[0.7]}, Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> { Offset[0.2], { Offset[0.4]}, Offset[0.2]}, "RowsIndexed" -> {}}], "\[NoBreak]", ")"}], Function[BoxForm`e$, MatrixForm[BoxForm`e$]]]], "Output", CellChangeTimes->{{3.8241813961826115`*^9, 3.824181410473461*^9}, 3.82435003952935*^9}, CellLabel-> "Out[30]//MatrixForm=",ExpressionUUID->"5a991766-a3d8-41b4-8e8a-\ 69f1df40cf60"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{ RowBox[{"Correlation", "[", "datk3", "]"}], " ", "//", "MatrixForm"}]], "Input", CellChangeTimes->{{3.824181415834628*^9, 3.8241814333736916`*^9}}, CellLabel->"In[31]:=",ExpressionUUID->"f0db2e9f-0dea-4aa3-9ee0-1f9cff4791e9"], Cell[BoxData[ TagBox[ RowBox[{"(", "\[NoBreak]", GridBox[{ {"1.0000000000000002`", "0.31735907788264034`", "0.14128485157904483`"}, {"0.31735907788264034`", "1.0000000000000002`", "0.13416841346173272`"}, {"0.14128485157904483`", "0.13416841346173272`", "0.9999999999999998`"} }, GridBoxAlignment->{ "Columns" -> {{Center}}, "ColumnsIndexed" -> {}, "Rows" -> {{Baseline}}, "RowsIndexed" -> {}}, GridBoxSpacings->{"Columns" -> { Offset[0.27999999999999997`], { Offset[0.7]}, Offset[0.27999999999999997`]}, "ColumnsIndexed" -> {}, "Rows" -> { Offset[0.2], { Offset[0.4]}, Offset[0.2]}, "RowsIndexed" -> {}}], "\[NoBreak]", ")"}], Function[BoxForm`e$, MatrixForm[BoxForm`e$]]]], "Output", CellChangeTimes->{{3.8243500298009944`*^9, 3.824350039544918*^9}}, CellLabel-> "Out[31]//MatrixForm=",ExpressionUUID->"2c5e9d34-2ee4-49c4-98a9-\ 9a60082a115f"] }, Open ]], Cell[BoxData[ RowBox[{"(*", RowBox[{ "Testov\[AAcute]n\[IAcute]", " ", "pomoc\[IAcute]", " ", "korela\[CHacek]n\[IAcute]ho", " ", "koeficientu", " ", "Pearsnovo"}], "*)"}]], "Input", CellChangeTimes->{{3.8243500600778*^9, 3.8243500849609437`*^9}}, CellLabel->"In[42]:=",ExpressionUUID->"56e183e0-6aeb-410b-9f79-dcea1798571e"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"PearsonCorrelationTest", "[", RowBox[{"datk1", ",", "datk2", ",", "\"\\""}], "]"}]], "Input", CellChangeTimes->{{3.8243500913104095`*^9, 3.8243501064409037`*^9}, { 3.8243501535247707`*^9, 3.824350157079174*^9}, {3.8243502767280474`*^9, 3.8243502861369963`*^9}, {3.8243503175511684`*^9, 3.8243503785176125`*^9}}, CellLabel->"In[51]:=",ExpressionUUID->"919fe11f-6868-45a7-9fe9-a8665c97641b"], Cell[BoxData[ StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"P\[Hyphen]Value\"\>"}, {"\<\"Pearson Correlation\"\>", "0.09343714449961085`"} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"], "DialogStyle", StripOnInput->False]], "Output", CellChangeTimes->{3.8243502885823803`*^9, 3.824350334583579*^9, 3.82435038103135*^9}, CellLabel->"Out[51]=",ExpressionUUID->"edeec243-14b8-4579-86e3-fbc858d88852"] }, Open ]], Cell[BoxData[ RowBox[{"(*", RowBox[{ RowBox[{"Spearman\[URing]v", " ", "korela\[CHacek]n\[IAcute]", " ", RowBox[{"koeficient", ".", " ", "Pou\[ZHacek]\[IAcute]v\[AAcute]"}], " ", "se", " ", "pro", " ", "po\[RHacek]adov\[AAcute]"}], "-", RowBox[{"ordin\[AAcute]ln\[IAcute]", " ", RowBox[{"data", ".", " ", "Data"}], " ", "lze", " ", "podle", " ", "zadan\[YAcute]ch", " ", "pravidel", " ", RowBox[{"se\[RHacek]adit", "."}]}]}], "*)"}]], "Input", CellChangeTimes->{{3.8243455199325175`*^9, 3.8243456012714386`*^9}, { 3.8243457164816313`*^9, 3.8243457199077897`*^9}}, CellLabel->"In[33]:=",ExpressionUUID->"39979bee-d5a4-40b2-af48-7fde93678217"], Cell[BoxData[{ RowBox[{ RowBox[{"datsp", "=", RowBox[{"Table", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"RandomInteger", "[", RowBox[{"{", RowBox[{"0", ",", "50"}], "}"}], "]"}], ",", RowBox[{"RandomInteger", "[", RowBox[{"{", RowBox[{"0", ",", "50"}], "}"}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"i", ",", "25"}], "}"}]}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"dat1", "=", RowBox[{"Table", "[", RowBox[{ RowBox[{"datsp", "[", RowBox[{"[", RowBox[{"i", ",", "1"}], "]"}], "]"}], ",", RowBox[{"{", RowBox[{"i", ",", "25"}], "}"}]}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"dat2", "=", RowBox[{"Table", "[", RowBox[{ RowBox[{"datsp", "[", RowBox[{"[", RowBox[{"i", ",", "2"}], "]"}], "]"}], ",", RowBox[{"{", RowBox[{"i", ",", "25"}], "}"}]}], "]"}]}], ";"}]}], "Input", CellChangeTimes->{{3.8243456064245787`*^9, 3.824345621905515*^9}, { 3.8243456989249225`*^9, 3.824345753822016*^9}, {3.824345797676423*^9, 3.824345857363023*^9}}, CellLabel->"In[34]:=",ExpressionUUID->"7fcd1981-42be-4cb6-9667-27e8cb65cc7b"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"SpearmanRho", "[", RowBox[{"dat1", ",", "dat2"}], "]"}]], "Input", CellChangeTimes->{{3.824345764678961*^9, 3.8243457793358393`*^9}, { 3.8243458630982895`*^9, 3.8243458800491543`*^9}}, CellLabel->"In[37]:=",ExpressionUUID->"44c2ebce-7c8c-402f-b0e1-528ee8f7fe7e"], Cell[BoxData[ RowBox[{ RowBox[{"-", "36"}], " ", SqrtBox[ FractionBox["3", "561601"]]}]], "Output", CellChangeTimes->{3.824345871091254*^9, 3.8243500396295967`*^9}, CellLabel->"Out[37]=",ExpressionUUID->"165a19c1-7ddb-4fff-a841-039e478ddc08"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"N", "[", "%", "]"}]], "Input", CellChangeTimes->{{3.824345884409935*^9, 3.8243458870548344`*^9}}, CellLabel->"In[38]:=",ExpressionUUID->"d2b32ee8-428a-4468-98e4-8de8decea4f5"], Cell[BoxData[ RowBox[{"-", "0.08320495535533146`"}]], "Output", CellChangeTimes->{3.824345887919731*^9, 3.8243500396452208`*^9}, CellLabel->"Out[38]=",ExpressionUUID->"024efe3a-03c2-47e7-af30-8506b60ab851"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[{ RowBox[{ RowBox[{"a", "=", RowBox[{"RandomSample", "[", RowBox[{ RowBox[{"Range", "[", "20", "]"}], ",", "20"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"b", "=", RowBox[{"RandomSample", "[", RowBox[{ RowBox[{"Range", "[", "20", "]"}], ",", "20"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{"SpearmanRho", "[", RowBox[{"a", ",", "b"}], "]"}]}], "Input", CellChangeTimes->{{3.8243462132103224`*^9, 3.824346284439642*^9}}, CellLabel-> "In[110]:=",ExpressionUUID->"00a89936-1ff8-4b68-a111-a8d9df4d80e7"], Cell[BoxData[ RowBox[{"-", FractionBox["251", "665"]}]], "Output", CellChangeTimes->{{3.8243462854106812`*^9, 3.824346293280781*^9}, 3.824350039676462*^9, 3.8247217261545057`*^9}, CellLabel-> "Out[112]=",ExpressionUUID->"a3eb1138-796e-497c-8cc7-04dcf0c8410e"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[{ RowBox[{"SpearmanRankTest", "[", RowBox[{"a", ",", "b", ",", "\"\\""}], "]"}], "\[IndentingNewLine]", RowBox[{"SpearmanRankTest", "[", RowBox[{"a", ",", "b", ",", "\"\\""}], "]"}]}], "Input", CellChangeTimes->{{3.824350393905511*^9, 3.8243504192572093`*^9}, { 3.824351455369814*^9, 3.8243514787498417`*^9}}, CellLabel->"In[56]:=",ExpressionUUID->"06deafb3-a765-452c-bf61-5566560712b6"], Cell[BoxData["\<\"Do not reject\"\>"], "Output", CellChangeTimes->{3.8243504215796785`*^9, 3.8243514833651776`*^9}, CellLabel->"Out[56]=",ExpressionUUID->"6f28695f-8fa1-4d08-bf70-1f4ab37b24c4"], Cell[BoxData[ StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"Statistic\"\>"}, {"\<\"Spearman Rank\"\>", "0.1548872180451128`"} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"], "DialogStyle", StripOnInput->False]], "Output", CellChangeTimes->{3.8243504215796785`*^9, 3.8243514833651776`*^9}, CellLabel->"Out[57]=",ExpressionUUID->"901b7f1a-fa60-4719-a4e8-55fac6dfca89"] }, Open ]], Cell[BoxData[ RowBox[{"(*", " ", RowBox[{"Dal\[SHacek]\[IAcute]", " ", "korela\[CHacek]n\[IAcute]", " ", RowBox[{"koeficienty", ".", "\[IndentingNewLine]", "Jde"}], " ", "bu\[DHacek]", " ", "o", " ", "v\[IAcute]cen\[AAcute]sobn\[EAcute]", " ", "Pearsonovy", " ", "koeficienty", " ", "nebo", " ", "korela\[CHacek]n\[IAcute]", " ", "koeficienty", " ", RowBox[{"nap\[RHacek]", ".", " ", "pro"}], " ", "kontingen\[CHacek]n\[IAcute]", " ", RowBox[{"tabulky", "."}]}], "*)"}]], "Input", CellChangeTimes->{{3.824350437111133*^9, 3.8243504505273085`*^9}, { 3.8243507208888664`*^9, 3.824350770164209*^9}}, CellLabel->"In[53]:=",ExpressionUUID->"f5c87d51-b7e8-48a7-82ea-7d70a981d842"], Cell[BoxData[ RowBox[{"(*", " ", RowBox[{ RowBox[{"Kendal", " ", RowBox[{"Tau", ".", " ", "\[IndentingNewLine]", RowBox[{"Kendall", "'"}]}], "s", " ", "Tau", " ", "je", " ", "neparametrick\[YAcute]", " ", "zp\[URing]sob", " ", "m\[EHacek]\[RHacek]en\[IAcute]", " ", "vztah\[URing]", " ", "mezi", " ", "sloupci", " ", "se\[RHacek]azen\[YAcute]ch", " ", RowBox[{"dat", ".", "Tau\[URing]v"}], " ", "korela\[CHacek]n\[IAcute]", " ", "koeficient", " ", "vrac\[IAcute]", " ", "hodnotu", " ", "0", " ", "a\[ZHacek]", " ", "1"}], ",", RowBox[{"kde", ":", RowBox[{ "0", " ", "neexistuje", " ", "\[ZHacek]\[AAcute]dn\[YAcute]", " ", "vztah"}]}], ",", RowBox[{"1", " ", "je", " ", "dokonal\[YAcute]", " ", RowBox[{"vztah", ".", "Tento"}], " ", "test", " ", "m\[URing]\[ZHacek]e", " ", "vyj\[IAcute]t", " ", "z\[AAcute]porn\[YAcute]"}], ",", " ", RowBox[{ "v", " ", "tom", " ", "p\[RHacek]\[IAcute]pad\[EHacek]", " ", "jen", " ", "zm\[EHacek]n\[IAcute]me", " ", RowBox[{"znam\[EAcute]nko", ".", " ", "Na"}], " ", "rozd\[IAcute]l", " ", "od", " ", "Pearsonova", " ", "koeficientu", " ", "negativn\[IAcute]", " ", "vztah", " ", "u", " ", "hodnocen\[YAcute]ch", " ", "sloupc\[URing]", " ", "neznamen\[AAcute]", " ", "mnoho", " ", RowBox[{"(", RowBox[{ RowBox[{"krom\[EHacek]", " ", "toho"}], ",", RowBox[{ "\[ZHacek]e", " ", "jste", " ", "sloupce", " ", "mo\[ZHacek]n\[AAcute]", " ", "p\[RHacek]epnuli"}]}], ")"}]}], ",", RowBox[{ RowBox[{ "tak\[ZHacek]e", " ", "p\[RHacek]i", " ", "interpretaci", " ", "Tau", " ", "sta\[CHacek]\[IAcute]", " ", "odstranit", " ", "z\[AAcute]porn\[EAcute]", " ", RowBox[{"znam\[EAcute]nko", ".", "Existuje"}], " ", "n\[EHacek]kolik", " ", "verz\[IAcute]", " ", RowBox[{"Tau", ".", "Tau"}]}], "-", RowBox[{"A", " ", "a", " ", "Tau"}], "-", RowBox[{ "B", " ", "se", " ", "obvykle", " ", "pou\[ZHacek]\[IAcute]vaj\[IAcute]", " ", "pro", " ", "\[CHacek]tvercov\[EAcute]", " ", "tabulky", " ", RowBox[{ RowBox[{"(", RowBox[{ "se", " ", "stejn\[YAcute]mi", " ", "sloupci", " ", "a", " ", "\[RHacek]\[AAcute]dky"}], ")"}], ".", " ", "Tau"}]}], "-", RowBox[{ "B", " ", "se", " ", "uprav\[IAcute]", " ", "podle", " ", "d\[EHacek]len\[YAcute]ch", " ", RowBox[{"\[RHacek]ad", ".", "Tau"}]}], "-", RowBox[{ "C", " ", "se", " ", "obvykle", " ", "pou\[ZHacek]\[IAcute]v\[AAcute]", " ", "pro", " ", "obd\[EAcute]ln\[IAcute]kov\[EAcute]", " ", RowBox[{"tabulky", ".", "U"}], " ", "\[CHacek]tvercov\[YAcute]ch", " ", "tabulek", " ", "jsou", " ", "Tau"}], "-", RowBox[{"B", " ", "a", " ", "Tau"}], "-", RowBox[{"C", " ", "v", " ", "podstat\[EHacek]", " ", RowBox[{"stejn\[EAcute]", ".", "V\[EHacek]t\[SHacek]ina"}], " ", "statistick\[YAcute]ch", " ", "bal\[IAcute]\[CHacek]k\[URing]", " ", "m\[AAcute]", " ", "zabudovan\[YAcute]", " ", "Tau"}], "-", "B"}], ",", RowBox[{ RowBox[{ "ale", " ", "k", " ", "jeho", " ", "ru\[CHacek]n\[IAcute]mu", " ", "v\[YAcute]po\[CHacek]tu", " ", "m\[URing]\[ZHacek]ete", " ", "pou\[ZHacek]\[IAcute]t", " ", "n\[AAcute]sleduj\[IAcute]c\[IAcute]", " ", RowBox[{"vzorec", ":", RowBox[{ RowBox[{"Kendall", "'"}], "s", " ", "Tau"}]}]}], "=", RowBox[{ RowBox[{"(", RowBox[{"C", "-", RowBox[{"D", "/", "C"}], "+", "D"}], ")"}], "\n", "Kde", " ", "C", " ", "je", " ", "po\[CHacek]et", " ", "shodn\[YAcute]ch", " ", "p\[AAcute]r\[URing]", " ", "a", " ", "D", " ", "je", " ", "po\[CHacek]et", " ", "nesouhlasn\[YAcute]ch", " ", "p\[AAcute]r\[URing]", " ", "hodnocen\[YAcute]ch", " ", RowBox[{"dat", "."}]}]}]}], "*)"}]], "Input", CellChangeTimes->{{3.8243510158001933`*^9, 3.824351028168142*^9}, { 3.824351209045072*^9, 3.8243513840763435`*^9}},ExpressionUUID->"b7ed263f-fd31-4470-8e23-\ 7e3b96c82cb6"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"KendallTau", "[", RowBox[{"a", ",", "b"}], "]"}]], "Input", CellChangeTimes->{{3.8243513952283134`*^9, 3.8243514064335375`*^9}}, CellLabel->"In[54]:=",ExpressionUUID->"66b2be7d-976a-4340-afdc-93179c8cfec0"], Cell[BoxData[ FractionBox["9", "95"]], "Output", CellChangeTimes->{3.8243514077670827`*^9}, CellLabel->"Out[54]=",ExpressionUUID->"e8d246c9-5263-4725-b1d5-cbb1b99185ca"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"KendallTauTest", "[", RowBox[{"a", ",", "b", ",", "\"\\""}], "]"}]], "Input", CellChangeTimes->{{3.8243514104450808`*^9, 3.824351436500095*^9}}, CellLabel->"In[55]:=",ExpressionUUID->"025910e6-a516-44b1-846f-052dcd3573ea"], Cell[BoxData[ StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"Statistic\"\>"}, {"\<\"Kendall \[Tau]\"\>", "0.09473684210526316`"} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"], "DialogStyle", StripOnInput->False]], "Output", CellChangeTimes->{3.8243514373497496`*^9}, CellLabel->"Out[55]=",ExpressionUUID->"4aa4e978-c29d-4be1-b79f-917ba11d63c9"] }, Open ]], Cell[BoxData[ RowBox[{ RowBox[{"(*", RowBox[{ "Zaj\[IAcute]mav\[YAcute]", " ", "p\[RHacek]\[IAcute]klad", " ", "na", " ", "m\[EHacek]\[RHacek]en\[IAcute]", " ", "line\[AAcute]rn\[IAcute]", " ", "z\[AAcute]visloati"}], "*)"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"data", "=", RowBox[{"BlockRandom", "[", RowBox[{ RowBox[{"SeedRandom", "[", "1", "]"}], ";", RowBox[{"Table", "[", RowBox[{ RowBox[{"RandomVariate", "[", RowBox[{ RowBox[{"BinormalDistribution", "[", "i", "]"}], ",", "1000"}], "]"}], ",", RowBox[{"{", RowBox[{"i", ",", RowBox[{"{", RowBox[{ RowBox[{"-", ".99"}], ",", RowBox[{"-", ".75"}], ",", RowBox[{"-", ".25"}], ",", RowBox[{"-", ".5"}], ",", "0.", ",", ".25", ",", ".5", ",", ".75", ",", ".99"}], "}"}]}], "}"}]}], "]"}]}], "]"}]}], ";"}]}]], "Input", CellChangeTimes->{{3.8243515625492687`*^9, 3.8243515972362022`*^9}}, CellLabel-> "In[109]:=",ExpressionUUID->"1b9609d4-314c-44d9-8905-4cc3bdca2814"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Grid", "[", RowBox[{"Partition", "[", RowBox[{ RowBox[{"Table", "[", RowBox[{ RowBox[{"ListPlot", "[", RowBox[{"i", ",", " ", RowBox[{"PlotStyle", " ", "\[Rule]", " ", RowBox[{"Directive", "[", RowBox[{"PointSize", "[", "Tiny", "]"}], "]"}]}], ",", " ", "\n", " ", RowBox[{"FrameTicks", " ", "\[Rule]", " ", "None"}], ",", " ", RowBox[{"Frame", " ", "\[Rule]", " ", "True"}], ",", " ", RowBox[{"Axes", " ", "\[Rule]", " ", "None"}], ",", RowBox[{"PlotLabel", " ", "\[Rule]", " ", RowBox[{"Row", "[", RowBox[{"{", RowBox[{"\"\<\[Rho] : \>\"", ",", " ", RowBox[{ RowBox[{"KendallTau", "[", "i", "]"}], "\[LeftDoubleBracket]", RowBox[{"1", ",", "2"}], "\[RightDoubleBracket]"}]}], "}"}], "]"}]}]}], "]"}], ",", " ", RowBox[{"{", RowBox[{"i", ",", " ", "data"}], "}"}]}], "]"}], ",", " ", "\n", " ", "3"}], "]"}], "]"}]], "Input", CellLabel->"In[60]:=", CellID->80899249,ExpressionUUID->"45b288b0-9597-4e8d-affb-6b9cd7c14832"], Cell[BoxData[ TagBox[GridBox[{ { GraphicsBox[{{}, {{}, {RGBColor[0.368417, 0.506779, 0.709798], PointSize[Tiny], AbsoluteThickness[1.6], PointBox[CompressedData[" 1:eJwVl3c8Ff4Xh22hgcqIlNXkq0EkdUQUQiGiVEYSJamMlFCIyk5oo4yUHVnn WhnZe13rXlz7uvbF9fP76/Pv5/U657zfzyNuec/gJgsTExOFlYnp/y+1b17h 6vZe6Ew83bx/WxdiroJTUnE9PLygd14uqwztbXP0nbIWQTnn7LHdU/PoVDV/ tyyXALsff3yZczQaXJ7Ujwond2Jhk4g0j10NXNz5J5v7QSDeu7/p85WJGuRx p+0plH4L7crcNBX+MtjdPnpgjuMPpKYpWp1MRXRU3e/Jp9qKV3TeiG8xa4YN 5g5P34l3wkny1hta9hXYk7XyuINjGB6qn8u+bUVCvpmLYdkabdh7dMr8nFAJ UD3C/FKTB+CCAf9CgwAFJbwV5SToM/jlhD1RmjINLhnCfFe6++FcZkxFnVEn 5vT9ow0HdEHC8dFYYu0APlWT7zO+P4NG1fNNnFZLoCIfqlU7NghSmy8vMFwG UWx3uMHew3PomGOYwVU2B905GV0DHn+RyaCL0W12DBs7ez1ETvxE/7AfMbtC S0Ai0PtClMUC7lAyz7hzdRE6Pvyl1IixEqwbeGQOnmJVjZYs/yDDWgMSwlyz v/wK8X5rRJ2oFhWHza4eBeNJIBStUdSmh+AEJ3fqd7VhlPsjsiqmsooq1nwv 7oeuwFknEZWRLiLs7WebVs6tR7sXOsavz09jg3MQaqVMg9u71qpH9osYWsEX vl9oAXb+nQ+9bUVFsYRXbj1HpmCi62FUpHkDDlgoPf5DqoQh0/l8Jw0qyk0x vtLDR2GI/p/eCZNOTHrt1xhj3gchzIM7gwSZVTeubFfJSGbgih+TfoAfBW8d YfZ8fHYUHOKPUE64fsGX7h0SNaP3Ucjl9sNT6cPweEJqWgwm8D1n0sroWjGy RSXt8a/5DRJ3Wb6cXqHCZtudVgF8s+h6yOGoOnsZjJcK97YVxWLbjevRzGP1 0E7w1D7/JRtv5jy8st1zErmr5RcrNMbB7NSGc4rn2VWZN3OwvzzMQdAsPSfw Jn4Mrk1+VTk2RsE4dm8037yE/P+O0FkN5+G2S7uHQcQKKjx/stqWvww8Iiom pcNUaN+zIfqf9AR6/HlJHIuuhMWoDeLE15mw6+YfcsaJCdAfS5drnh/Dqg0Z tXqrZBA7KMHrXNeHNurfTO85jMG9nZaHR24P412diNfVzGTUs8reG3eEBHrc tibhzAtIu26+WyplDu4Yt711et+BYU9GpG6ebgez1hvGSn6DEOlFp0iZDWKJ 2FTmjGo7fnjNLJhJHQIWjh+0KZ5WPKvrQPVMJULVtFqne+cs3A7PK9+8h4YN iXNDQ1ELoF3M3C2vsohFeV5+0xI9cOwxF1fBg0HksblmrrGlH0MnuKiXr/ZB zxbDWrumIYiNGmrNHxzGKPrzy4qHZvF5cPoHs+IF0Hjlkefr0wrVJmwTIe5d 6BDG7qp7n4hpbHNSZ/NIcJ+hHOrFnQ/08V0eb0LL8OKH8v8S439DArt7yXxC FVzPfB5+PH4A3tcTtNlGBlH/45fkAxWd8OveXHTj80ZkOSakPJlNg/RRl/mw P1S0lQ04lvS7AO8a5z7LuZsJxxMkmhMMydiom+JQ3UiB9G5KiXlaP3gd3Smm M9qKNsoHq1bKSXjId1eIvcQAPAoMEJUymMWlEFWr/+zm4KJ4PdG7dRnYtL4c oN+nI8+QQ1prax9GfNTNZzXohxz6332pCjN4UNY9vMtrDMS/6YjnJZDx3T2C xd5dJKi9b3N8YXEal3wmLIYaqLCnffHuJaN8AEMP6zvJZdi1x8Hkg/0g+o6f 2sO42w96VjaXx3nYVG9w5S0P8rEShuZvmvxbHUDHAaPv966SYfvjWWLo4gwY jalWWG6fwWjZNi/Ks1fImR+ypi2DcDw343RJdiw0bvjvtaFGLFp6pDuz76VA fcXQwVvjQ3hzMT3aXH8Qbk+U5C30DWFt9iviCr0CwipJ0048FWh4jB/aMun4 2+jLD66UJShIY+Jaez0AFfLqikK7O/BsTgbX2RwaJLySMPSZoiLRC+9EncvE NCXOzsHJPCx/ENyio8oAPeaQnsluOoopp/mXCYwB/3GrzCgfMt61XnprN0vE wcS6B+dn+4GXzLuVb3AFZsjFlUY/lzFWzyq62mccOtjtnx8/Mo0U4b17gi/k wqbKJqqAVQ5uptpnplxqA96y0LmpXUTUlkt9O6IygaaXJE/ccZsE93evicwW c6D0zE52f+MsCvLE99FKp+HrPTNH9yAaHr/XG5Cxj4ytI0TrMIVRYHJ111fj YCLML0aLlQWtwNzVn+mD6eMgsnTeJ9RoEC/7F9wSSlvG3Tv33tpHWoE7rftP lm6qQOvv+Q1ftv8Ewq6rjDD3NAg3TqCE25VgSgMHw+18ESzeY9ZztKvAnfME 9bePc0CTjSKmsq8IeEKjbzAzZnCDsP4O4ZBZYP7z89X3YQKoJR5TFcxtRPfd 8WaddwrwvAfDlysmG0odL9fuFiMj3w3t65s2t8FPH1mpWv8PSEhL7z+84QvW RO9eMdEcwd12/2UTnMfgYS13gsNrEm66mSW/u2gY3h8W8ervZCPEsN2NufmI Q3XfrfHox+8WwGbeDDieLKHI0V7B7BMDaNYsxHPdux+GW4Xuv1JcgNHMDaHc h2fQ9+bWasmvg2jTuZGDvkyGLneefak1JZDX33BgF99vfCwtOFSaTcKtBN/7 6h2DIMws8hPXe2XX4fOemVpkOGH0eovBVQaYHlMSeWbEwGuxifTe2mnIKLHN YTkwgQP9RbvKrtVDwqdqi9KGMox2rqbpvWhFpkd2atR34XAyq4EQa1aLBKuz SVUXiOB2Y+ldXzsR0mYE7PBkB6YbXDip+HEANTllamIHeyErZGiHzyYmwtbT j/PbXdZg52rXjOrZMSDdOfPYN2gU945ltTHxLaK7rLcIv8wsOIZIO+9xaoae j0kLp0424NmfI2C4MgmhDzWOpV2noeZ0w0pCAR0yQ2jU0mQ6Pt1TMs48PYIs v+mLv+VH4PrrQqWUlHo4K+yvJmPVgW31kUnyN4sgvjhVbhibMXSjtcbO2CH0 22N/yLSQArYvagWGPQgg/qmVNTMwAwcKKIfDcnOhtlX9zfasOtwQxNTE040Y t/PNjlqtX7BJ5cYRmuAYhJNU5M4YTOLW3Rw/P8ZSwdBzaLZOfhzPVyZd47Xt wt8zg1kuUtWQXRrTEiY5jVNL0SqXEsaBR9foKKfdR5Sf8CwPciNgSVGHw6X9 G1R1ePdGBZ3gItidvp52+NQ8dO6tzmneOo9TJmn5nq9aobPqvez+rHa84Rcy Yin5G5X9gwYn6UXQuvG6X3NzBmzVvWpn+rQRyWtvlv/9a4NNYr5B2SWt+Mhf zrY2ggrVthK4ODiJkx+U60KysuHxirvs3Uuf8cZO35dHtWrQjjPVzLER4QVr +ph35RzS3lpKD2xZhO9Ui1z+9Tx9NuN1pEWBBk9/ZEbbm47AbuNoV2rGMHrH 5/Bf52/C8EmbMO7XedAsMseX2DUOAoTD4+rOY7hhbfbETv8u+PbSPODmeBsa BKkf7ThHBfqJco6mfdOYF/98kvxpFmpPtgcg5xyKHXr15PtdCmouZJ78IDwE m7iFOFi+MhN2piY0XgpeA7ZQjXcftrMRtic18zm9YVYdLNuWonFnnXd+PFJz +0CF2C+fnT8dIuETBuwf5u2HndeU2D4akrA7qOR7JdMIFG4vrDuz2IOLp6V8 zur1w6v2i85yWl9AZu3GIyG/DBw+/uLZQDkFjAn71DRkh/G0rff3xfZxzFCN PyfSOA7aw8y+1YR+THnrnJzeQQZdxf6dbwOZVc1e7J89xc9AoZTfliYzuVAp H/7I/kAR9tSuPZ0+E42BBx4meT0g4KxIQJnmuypgC4rVyLxTg7ZhyZwZ72cg Y2u3qI3l+p7cKyom5ZLA8KTF56daJBT7z7BCyD0Ok9oDEna9L0b4cbxalKsJ 8p9zy5UWduAsoazI6Xo2OgpUm9uLuMH14qKq9HUO1jvXailYR8Uj9HNejerD 4HU6aO0Q/zq3FN3oPb6RjPkhZNc7p9rh46VTn5jk26DmnFeEtlAVHvd6GvPE sg3nVKkvP1IG4OufjSmvr16CQ8ZuYao7c8DkkKdg/ZdusPWxOHTbowdTxv9d 2B7/F4Hv7pTp3ywItGHk7jcgAcspGdh1axAzeb83nf2ZAvV2Y9/iNtXjpQN0 DrPKC9jEKsglz9IAfH42x41SKsDx1GvW6yKNmH2JNWGmqR4dvcTEc8d+oPDb lTCDU534Pcgi7OizJjC1HAhs98jHK/tPC4xXloDPkS2D8xfmsL0o7vFo2ywI z8hET2E9zHUpL9bd7UaRbw9ehEoPwYXW5jJKah9m+buMe6uMo+CizV9Z5Sko 3X3B5kkNDVfM5f7E0ydhMlnkh5ROM/i7EXNCEutxILbj3arGHKi19re66dLw tsrPpYvORfB7gv9tCWcVxnGcnN1ycAxOpX72OVpDQpGVO/917ZgD6t53XLbi C0iwD2R8aWNAnl5RsdxLBk41SZBkmctR6PwXjuuXkuEOBTwkDiZjN3++yH7/ JOD/lWc2SCJDwL0LAZSuMXQw7/Rr3rkGgayxO0uOrWCl3pk779X6MFrQXcbt yAjIsZ9+95M2CfE6snv6lyZRU9/gsT/vEIjyO3Lq4CBKqhQVyDzKxINnpJT2 AQHq3jY+XqiYAf4HT9/Wqkyj5NY1BunWHByxrtZ53DeLy/bw3y7xYczLbFOx JXQDytxqNTxYgUnsz0MeQCtwGpqTPLPbQeTBjY4FsU5McYjyzxino3eKyOLX TUsQf1a2eod7PYrpY+X03RYI7btUN8xKRDUZJaGO8A6oO9WSKKDUjBs21e1l /5sI/fUaRGb3QQx1XNkp6jMEL446LuvmTEHDtv+4vPJHMKyYyr5/7yyQJANl TNbnZLzTN8BpZBacDc9M6RZS8QozQbXowAqcem/dO3mKgQ/Pf/FVnFjEH6qH tZgE5kE01am+5tb6fR19QonaPYvCD/a5sPxkIsy5nOqmu63BF+KiyIdcGhQ+ XMic8JxH/9FUjYIXlchEk5Z49CERVLwuV3y9R8LQ+NicrXKDUPU00X1b4iwI FamfOS49g4GRKeSHTWRMKA4u52ogQ3NcjoO29l+Y6mX5xDpSjeyuh05JGddC 63Ro1SipEqVrOqJ5uOagVszzhscUDXlnLW68OziH79/UJhG85iFakW7tzTeK HMZLD3as322l1E+urZeYCKpKeay50syqOjbe2X9npsCALnGt1Hga2+SZrORd J8DnwpYb8bepGHjtwuQ5ehPqjcwffs6RA7b0e3Ef2prhG8dLiXtvCah/o8Va G6cws0DKw417Bngu57y9+osKm+ytDP/20nBtNGtxZZ1Pw08Me290ouC8pZ7r +NgMiO8SNrg+P4OpUgFBv5QXcFUp+FDxm0X49fWQs9OnIVzK3XJo/wcSHAtm XfKsGENWtyuFCZfGwKtdPaA7pRV5d80X0hlhaEFUOpCSvIjC81HsBUxLEKGa LjlPp+LJmR+NGYwpuN1VHX3+TD+qFfxkZzvRC5V6x/e5VC/jw1k5hpjgMsxU Sz0ltDdhwusEx07tr/jy0xFN7TE6llS9KCteXAbSt2hWrQMxUMXZfiyCpRwV 2KaDFEtGwF/Sl1sigow1zUXagz19sPVEj+9dyX706jzM0NHvBccKjvudH0io flaS2yJwnVtIUhxSE0Scexc9s+/mDLYl9j+t4JmF+UPZL0Knl4D72x9lYY0l tCE+anrTuAS3Q/dfmRmi4zblbp/vH/5iyM7UuR8iWZC0eVni7cZhnB48G1Dk SoZjvRQDUtMI7tleYvGFMQTKn07tJorOYM61smb7VRpEASe9d5IGdxWjHNcR B9W0bkl8/lWOjon/9JxFA/EHbTX9yqkupB/bEpi4pwlEH57OVbQthctJ216u UZvR0fSllZbhCGzkst37a514YrTHjJNER7HZnjIsbTsCof6zE7xLzfiStlvw 11InqC+efGluQ4PpMcWN0vE0HFFq2xnxiJVw1EFP+2I7s2pOeoJcWnonbhbu zFfpqYckr3AW+ZdTKFzhs7l/eBqi5/fyqXLOoJDkFu1d/qMQ8YhfRPdLFzjp kL6a7iThbxo4ByvR4LDH+N2V5vV9fekmoJA7jiZ+e8Qvuk+CWlSJhdPvafAt 8Hu6Y3USGXOX9jKtc6B+1tkcffkZDKkWS3N/u4ynv3TEnFVchov19y8RrhHh jOYtylaXdhQX9hdTjJ1Zz/+0/KVwGuSELHy54LMA1CIr6s2JeVRSuevf0dCK y5t46y1PtAN9wvaNT8QoyjrEhJ24NwUDhwuw8EALwElxll/jFfh97+PzTC+p aPVN0t7k4zRYh16/qldZgPm7pD6YjhViTVKE9ZolAz/NqXZpeq6CBuW3VvaR PFg8NU7J3eCNm0dKyD7nRlDXKLo2tHoSaFtttU89WIMzZ3uc9EyZCRP5EnPK ebWQ2F0qFEStw8HNtIjxdW78+cKr9k/jMHzXeNpYkl2HhNRVf9fQFNDS3Lf3 e285+F6SdpsuIeB+WdmwP29n0boCrBbuzkEAH0Vqd848+IkuTaoGz2G4qklN 7sA8cqfa6/6VmAft5pHztfWV6Pmr2Lh+vB5kt2w2zzTvxx0h/+0y5O0G1lha l2sWHVj42V5vlFnBX8fuPFAU7cSxmVdeKobNUP1xj2I01zR87u8NylulYea2 nMNKmX+BU8dKQHWtHJeuv72jMfETD1Rdqfgt/xfi2Vr1Pu4YwHIh/mvpmQPw crJW6Z0MCd3xesAD/0G428YyprCtHzWvL5Dokq3wbonyvK1vAdp3PtGdXpxH lY7HrtscaCB2hcgfpz2N21QNOcQq0kDP8hFl+9e3KBcYlBLYNI3xTksdZ7Kp UBMnrtD1bQwI27le75Ebwjb1pH1ssotAuZj2qTx1Hh0rfAqCpXrB+6eQyIsY EjbrdWuyPKViWOxp5TfhU2CxupP6NWoZvOlmMTGkJaRn9i6qVs8DG8u7T76r s8hqJbiZL3IA9ty6XPCpm4TaU2Q5Gt80Lq0K2QfrjkLSQ01aqeYQbolYFNj7 dhiiP8xsNVJZ98nW/f7+yrOg7K8RE8LHRhDf6fnG+wCLquL5YELbz3kgzQmb GDDNo1/dXvEJfzJyLKpcMsofAXc1T67XkVXo4vtEm3mwHlKsD27yLs1HM/kO j566arjOk3u2aSQWK0w6s/YZ/cL3CuqD9jKTWBWTOhYgPgmmNz+usXC2ocDv u8HJEk0Qv/zP7sfsInhbsYyra9ExaePmzObvw8j82eBalR8FXA5GnaXNIVbX cnWOZ73DEmO/VyVS677xxECqsrwTjb+8FeDIWkIH1rB9IhFLoGaeG+peMgTH x5Nkrf8MosPk0GHb6QmsO3Jmkvv7OEyaaLqVjA+DAJfhvgXvQfwvvfhViiaL 6iz7ZhOvKWZC8H99G6pkFlDAy2HL4YfzkEh6Eu9a2IknP6i0aSS3g/73f/4P 8max5xExyE2GBun3Dyr1ZTIT9N7ROgmnWFQ3npEx/KfSjxCuNGbzuxcaGH0/ nh4cgL/E8mt6zU3YaVr/qdpgCAV2ljx2lOsD2dXJB+das4GXnnNb/EYBloap mHlUVYOekGwUe2QbHjkcGXm3eQY5SmPr9rfNQfTHvLFtkYswc76si0xdxNnr Mhyv4rrxoee//27bdYLdsX6pHGkqXkgsc+domoR3Yew26p+J6GytQo/c0gl7 uUmPE/bmQfrcl509rrnwWDiETf7qej89KRl08p8H2aFZ+yRiM+KIRaRTcSMM 2R3TkTn1Dxet7jzX84wD6WfWnpm6i3hwgU0mJG4RIvjtuKhzw3iX3hzIcnUQ 4n826v8nTYW++latWhMqckby3j3bVwG/swQCvlJLsNx4hY+6MIH6ss2Lj9f7 5doui8YttRPAkkI68dCChkfYe9rKOPrwsGqVXOh/PbDWNvGpJJBFVcx9UXE8 lIXwKNNwrM53AjlL9N2YeKhQvyvyuoZUFz5kY3z4l9cHRRTHy5v+UpCxMrR6 6PsIFLzMD3pg3ondyb3Ou8itkPR+dpvSpX/Y6fz0lTyxD3YzEfdbZtXjWmG7 bgo/EZz2n1o7emAVt7Bvmiv6sAgMjw7WzMRYYHCopmWs5552w98dS0/nsUFh gRi4PAf/SPe0+kRpqCr9GvlLabCoFnNeQLcGfQ2E1P+IFwIrxUaIbkqETTLv L+761YHPJi6+utFOQhq5Z+zY9lG4kBIt9ud9JQY4rURmsCE4+2vtS58aAlvQ oAu5TaFI5ud7XQdmkM/SJrNamAZUcX+jq/k0rBXRuh/jQoW4DUphkqtj4D2h 2Za7YQx97LRXPz9bl0trtrjd4kyEP9kWatvbGtDna3ynqGAX7Ah7LWQq+gP/ fdsx+0n4F+bQmETlZYch9WS0uPHwMEo7Vz0+LfMXuccd+piE6oGPwzC9m6sf 5yMSmbWHiuCm8a8fF6+wEc6GR3gcq2RTzb8erz9zewZeSOTZxx6n4tsZ1Uca CWScF1WSlVqirHM45/VjDQug9OHMD6HrSzh+2yRGpGqDqt+huEg2E06CGP/M nyc5s3DupIr+FZsFvJLw0EJskYJmRwoVP82MQ3yTrNo7iX6Q/USJYBHsQ86f gTW/ZUexwUjizHLpMERYG7hZsvTDm0u1ctcWetHZaZsVJboNbr76unHPShO+ YlbwTqymYofhytdtrBPwozDmh8itFtzkE2UfrdIEp12CM7Lu9OOR432VHeQe iKrwOKhK70FTwfZGYOsDAU2/zGrxUow5UGQbKkSA3fYmVLObg3AgcXbwbfUw rsr7B89iKw6eaKqo/q8NPl7/VKV/ngAhzMF3djwmIKVPUbYgmQyGgWGfY7dQ sFrp/paLPTSIkeQVvv2XhmN2CSrSuxfh2o9725NDFrBHxYiRPNaGmlSediOZ fqjM0ghW+LgCJQfzODxPr+JXu42Pk0z6MM1vWuC9Sz+oi1zwPOJOw0+35BPt jCZBOPp95lelETimq/u5PHMcDy/HkFINq3DbZ5M6vlN/oYZ45Yuc9CI8LD2r u6ZKx2lBusrhmj68tPWar2cLGfJy5ts3bGiDqleJBuwsZGRmLk9q3zqPYl80 GqeYaVAfMvcfPmQl+D+quepLYFHt2nX68zR7Pez9kvggPLIG/6odE8/aQoV5 Usb7osoxlB+2NNjxdAC3+cv4/JntgumY592PZhlQu4v1IEOOgd5t8r6am3Lg qdV4iOn7Fiy6/PT4q+3jWNrkeO2N7jj8LAk1uC3Lotp5UF1wKJGZoKJ+Zv9K ehvIBY+bvnb+i8czWL2Sdg+htvPiqNwTCuh6bOAcZZ7ESVcLKa2YKXBjcL8S EyahY0SJydHsUfjeXxNVlkoF7+yMhMsm0yjEXqO240EdPIxlqhmtrce5KEG7 s+5zyBHq77t1fA44xk/YmL6chjBJ6+StkTNonDUynBBGg+QnlWufb83hmbTr hXmrVRhqVWORqtYA1mbum8yXe2He1+m+TFgLZtJZLKevNaKt9P6zYnJVEPNI XoyHTkah+APb7hf2Q2lSo0vJHXu0zoFOLbHfKDfikrA7ZAT1uBxfsFn2weQH uR3y5RQMnqqfTz0/Aj/prI+TMvqBMNI6yZtGwtdcX+zIzgl41aTd9G7UcySK GPl8u06FpOkR5vNTU5jYK3NIbCsRqo2aJCGMjLp5GRya77thWPCJtajTIAYX SPWNlzaDi74+kRjUjBJXXQgSvLNwu5Z25XfNNJ55VKvkwzWA7rqUrk0TZBh4 4wwK6/kbfmTu8fQ6H4eMXXM3OxMD7Xuzxe2et6Oxy9U9IpnL2MJwY3pwkAFm 76rJUUJxaHCg8p3l0Lrn18tKm73uwlvP72YJhLRDpKXEH6L8BD5WoAfyNIyA plu15YL1LAhwn1Pl3kFFsSO5thvWPfZf8bMNEzaTEMhpgKeCSuDL5MHzTsKJ 6P/gJrmYPojcxw2/T6gPgLdDi/oepQnISemQILuP46OJHq3DDBoebM+MfX5+ Bsz6DDVERCbhmWSVq+C/CWxYoB370dAAxQqXGZNKDXgmUczMu3wUL3t4Qv+h IVg5F2liZdUFZMPQbbSyelzySxNbTmAiiL9OU3n+kUV1SpfP/IV8L4S0dBd/ sxxG/tEZj407JzFBOjFV4uAI3Lf6e2ROOg/Op4T0uIaV4Efrvy6HiO/xPt0h sdcjA60m2P5dFiiF5b5JZqOwctTiaG+XUm1HBfP6vs8fO+GuQuSj64oxYPfM +7+nLR9BmtFhL/QuFialgq/E3f4NEvNrjvzCRRAZLLGj80osVE8rPpaV6cZc yvMi1c0dMM98WjKvMhzfeUdvVxqph2KLLSLK24eBP032yuabw3iSLzJi7fQg /Oc6QlHtHMaKAvZz5PXeptQyNm0+MQfmF1215MPzoZT7176bD/Mx/cWTbu+z VPh7jeHZeomG2Vfs3Lq5q8Bv03y9R2UxrkYfKk8/MI+FajqNmlcW4ErjZ/bV 6G6sbN63KcykC47X+a5ulZnHK5kPXvKs8wb7ZBvL0Qv9QCS37W237UfOG05b Hr1qwsCDwby/91TATZpkeaUlDXbrtB7yZJtBuefXCIE6JEzapPq03GcC7nbX b9+uVw7dRzSbzdRbcN9tGoHFiwQ8jAc7znhScNPzUvPmMhYCr0jg1wU2NtU4 noTCZkEy0jcyyzGxdkNWhNkPulsnPhEUOCZ8uA1UJgbSFMrJWJWjqSRfTgTr NzLMapNklGXxkhzeMQJnDvhnpJgtg0voye+vE5ZRv/Jm1b2d7YBV9AXN3kb0 zEvOb2Ba97bIyeea/0bwnq9L0ha/UZz7fWSzgP44lMoz7Be7prGPi28xaL2/ VepuF3zs30RgEItaJAo2qTa42B38kkfEHBEimzA/CfqqKg84qNPwdHXJB60z M6Ds8LkjXrQItUy9i+N/VYBUs/2hZqUObOEz/soW0ge+keVHTS1zwK6uZnPm 5QbsvtNvrDCzhPnfHTVsCHPwX1UZPUehD3frManVVgxAiqPoaEdYJx7eMKm9 cZAEoivb5m6EUrEtzqd+KJkGtblfI0f2TmLnWmnWmvMYWF1U9vlmMIgqoudX iCoUSMzKGWh6VQr1tpI347bUYeLPC0ocfg24LzTuz1fjvzBRN+55+QMJN510 FT65awLIzlHMntYTKCUs5FZxaxj+frhwTrqwCXR8XAuey1Vij+/U6WP2I5i4 /PXgr5OjkKdla5a81oeuGvuIZ2G9n/jZvWvKhpCpzsFR++4k3HvxvjiGuxra F2Oib95tRtK/DyGtY/O4q3W7Hf/WBXjR+fl3btIMOBM/Sl7bNo+7dx0yePWI Dle0su0n5eh4xdX+4bLRAMqZf9tT0joEnw/7zL17GgdDQw1iMasN4BRX1qC2 IRWl3MReXTifB/tkJ1OH9VhVI3gSL0zfZiEoSdFcPuSTYMWImSxe1Y9hJxN/ W11px95ZMT7TQ52waf9BdrHuVpx8sv07tawd9l5j5bWKLcJOBdec65EVMLTq vkNpYgFcvYlCn7YtoDyfwMnbxCY0c3yk/bKrFpyep1/+yTMBxGdC4l27prGQ Vss6F0QBvbh29RnvKQwyTx5OBAbGioy357xmADH78umyhTlg6k/STJSdx7lo R2t3Rhtkh0WHpgq24aBdi4+I4TJqXrrHxk5dBb6UOPmgyUG4EJN2q+/oIC7e DTJ3qe7H5BDWzWPznaBTKi/YyzQLSmpfS/fYUpHna9ba4d+/oSMiqHwmthbb 7v/YzjU8iInavrEnTCjAhAWHD+d344HuxgtRAj2gXu//5A87CZYHE9fc/Pqw uzM+S9NkDJ0+emSYZo6Ci1Eaz0YCGYfeiu1W9xsFO4f7n9vruQnKDaPDPtt5 VFmWr1tlBExBW5iXqillneNWMx4mXfwLmqcFNzY9LENLbmuZmXkqRFHcRN9s ncbnD51nkW0JTEhNJguuc1hjmPeEINWI0z8/hjd/7YBtKt//sj6cxi1kRuVf VirYXHOXO/3iBSYUFM9SrVPgVkhtKQ/TCoyq3MvlVGIiWDb83Ht1rBLEOKZV LHS6Mes18beX0xDObmwI/b3ex2m9Zhtpb2NQoHyv+j9qI9z428UZvLkOOBLu iydItOGraXU9Fa0xGLrkwea6MoXWH/cJRgc24J75m3XtxpVw3SRH6qLgAhqf MHVdy58D5wBVNu32QZBm65681TSOko7fTlSoL2A9OSlm4sQCvPIYmGT1WkSf 7p8dB9Tn4Llhh6Juax9sLVt4Q9xLxi1+bCtG63k1+3yDlIpQP7y8fejhuRuN YO0hK3jkwj+8pVbD4zVSCTc8bpdTpL+gAtuZYgOuNGRK+Lvm3s0OR0d4wwP1 uzDooGAEa34HcDyK0WlZyMCJE3fizh2oBV5B8UrZHUX4/Y/qBqmibpD1PifY GDyIrRpPZb5UjAHDNbHHNnAMvdt1tntsmYRpzU9iXYVtuDASIO/Y2gnDqCFf 4J2PEd90nzRHdMPqEdUdIpFkFC30LjxnNQzPePNmrvVQkWrrHmVOmoGRmi1f rjososcNDurrkCXwGZ0JHVNtxj2nia2Fef3A+p+aCvlbB8Y9j+qIM2gES9po nYrWCs7tmv9kKrUC+lLq2iqOfXitMMk//tMQiFZzk/S/saia1yhl++xnJ0T3 WQ0vfy6FpiP/7a6+Worh3NMzj842oHKNRM0z7TxgOuPCKktrBtMQg0Gr9434 ynFs1G24BbawrCwk1pVgA0FH5nVFITwoPvuKrNGCIk5TzRG7wjGz/niH8adE EMm79jG+egwGHos8kDElY8CkSrPZhyJ8xPfm4P7jefDkleJ4/3IPPvjrw2Cf 6IfYg1ZygQvzEF3HSNsjsYQ545fb1srZVAN4z79NpLMRfsJAzJIwi+o1h7X+ z0wsBN04F8XA6+2YFfNBy3fzAPgxLe6ZWPf+qj+nihLW+cZ13EaqxPcvfu7Y fvxGWjvYSW60Urw0C79CTMJlz8+jmljf5pbVQlRJ7j0edT8TwuWCg62sO9Fh v5rp+7w6+Cc//ImoOgM9tWu8TOse6rldTuN+4CLodt86t+/TLMbfzUlcW22F Y7cuiLMw92AyaucGmbCo9iUH8hu2MxGINidY4+bX+d1Tp3LzMAtB7fwj0Fe5 j1bBSz8ujJZBOt1r4G94F4o+fPLueNQwZJ8P9lt59QruX8lpjv1cDJzJZjpl S/3Ip7Txhi+VBCly9it/UnvRp1hzr+rWNmAwvCXLv+WjVzxlzEWkCjcdPaK7 9+EVHA6F0MjxDFQ055ISz6RgFBeMxDwdAUmJHYHqrZ/AxU9EsH5PJe5v6VZf qiOB/LkurZ9cvTjHiN+zrz0PgiNv0aXUU/G0fGeb8PVhHB2MdQ4NHoLhysg6 9/IGyGEnjDzjbsWHFdr2opE0OHhJxPD6HRqenN9StuksG6G3MURevZRV1YdL VFZ49xzePMQoLoubgU1qdbud7xZjdfkhPS7vf5Bwbm480rwPmNoT6iULSdgl G3n9zy0a7p+RW8AgKiTXVTsqLYzgAfond1LvAPD8PivezfoXon/UJRX7/MMA GyfTW8ZT8FuGWerFKRrypvB/jIuZhl0sDhoHi6l4Yrsb6QuJhPLV/IuW1uOQ X3b1bHpHI6T3yExomXeg+cuu8IKcFjzcq1LLDS3wTnzDQCKhDkbzpC6NylRg 34MgcnDg+r+2fgr79nQYKrY+0HrtR4X6QznluHMaReSqdj1tr4f6jj+w0l6M 7z26Wuy/tUFRn7P17uJ6tNhcFcVxqwq4LDdN4KkSOHKip+NJ1ShsZ5B3MjeM 4AmLLhIzWxmcmW2u+B5RijvV9DgH9i9AuYlmiWj1At514/I+70HFgW+UJgpt BjhHM0J8tchw0faTnuAJMrrLa3gbsVGQI4Emk5M/BLM5x9O2nOgB+lpzgY9k Hz4/5Ucc3kGGWs4h46syZGQrCrQe2j8EG4XK8ro/9mNL0QSh/v0Q6gi5GD5+ Mw5GBR+r8cYi7Dl+r/Xw5yX8InNLszWnHX/8CtBvuNcBWY2OrSJbV/Dxo6T5 wXWOqIVQrSpmIiqd2pHP+6QPit+NSVwfngc2bdYKtch5JASXiKyajKBtpGrw LZVJiBzPvxIZSsNhQomMXxQVBJ5P/00cJ4FL5/fV7bxDaJqczZ1xgUk1fe+b gIjJVcwasosjjffCo135hRYtvUg+cbz0+z0yfkpszkt+PQqqoQIx71ZPgLX2 cNZ/yem44d+OrVuvMfC3RHPyaMQyzMYYkPZUN2I3r0+ornETcHCz7GosLMPU k+6dm5ta4ZHoyxNNAjPgJ2Rg/X59nsFvD9W0SXTAkzen32nzN+IbaudnvzQ3 SMhou29aV4p5PO+SeHtWIWnE4u4FbmZCwDWJ+wZ/SsDWnbAqsTccWKwd+KcT u0HsJ3vXubp+JJaMHHR6VITdDjfs81izoDVTwno+cwiI0DautLjuo0YHuyaF yUgLMALC/RHwMZXraxDxgqSfvg4be0txQvetuM4kDRjedFlJ2gSe1A8hLMVT IfdeXQHfk1Fs4Y+c+re7H09gmP5SzQDQR7d7hlObkf/KaZJX7hDceHnDuyuz FEIKjcffyPzF4An7aeUvDGwX/Rp2cmQV6uTW92A1BwiVrR1xx1zRtOl5UcRl EowQ7unkVvSjIZH6XuUqFeKZ/ShycjM4yGpz4uTFLmzNuR6/dfcAZOyqygp4 14x80wMvb95pg9HpORnG+5uozy960Uw+E2TLkrhdVilofXhx5iIfBb44cjqk P+tH3Yenczn9WmBOR/K59h8afGeyoTLdpuJ4lfGP+19+o5mb7Z7MLYhqbzor d0wt4bYg3XebHBfgVuDBMyYmo6Bw82ZDec8wTl9RpnGPLuA5t1v7/J4vwGqq ZPBM7AoeOGh9Z7smHQx+9HS37aXBAfrTCIfzs5jac5m4w3UAXXeWF79wHoDt ax/PCYyQQJExmFdcOogpmQnmvR+aAI6cZRU42oSios6quj2doOTSniZU3IoK VE/uvVqL8MRTWW9z2Ar+MqWwJ3yqgRA2x/0f7CpQoPrHmYYFFgLr2K+62GhW VWF4U0rUpALJO3mzwn9UvEnt+UbyKsGiYgUTC8iD3+cevRV9Pgz0b0/8U951 YoDhh3aukGbwEH7xQuJ7LW59pKVDcwoFP39JZ3nHatATzqqzLZgFZfOoEywc NLRf3SPanj4GJ0tu9xg3juFtOi+fvOsILF2RfHnwwwh+Y5l21v04izphV9tl HWmQlxGns9qbh0ymH4XaGo2AHMpK/yNcDOUOt7cJfurAXLKtirvoCD5hvx1l xEkBTSHbb3ZJNMxPnfnku76Hocb3O24RVkDIZ4ux2/4V5KGdFfKJnQQpYbpI 4osxPN6oNqSzYQQEcpOXnUijeG5XQPEhfiKU2X8oHSDVYLfOkNPTmmG4ey36 437NbvRB5aToVCYC3avvMc84s+qlX9fI6xeBujHce2MOjAB10GS6pHoZ9LTo e6t16HhY0KHJv6sPjlBJP8ZDyHiv9qWR3r4+lChWXk3qb4bE839entEagX2M zxeCT48iobt0bjWTjimGzSq5Tiswsk1A5fJ3KoZ7vF2IMx0GRbFIz60zfSDq qq3r0dKNHTvKpKvsFoFsZ2+juHUZvWKCIgW5i0FBaw8x+DUBGacr4qNbmVRb gzNzd9BXsM7jhWgtz0OQTCr21PUqAkkZirZH5ALIhZq13Tdawpfi/Z1jLhOw obdz0+WYcTz8haJhFUqGv91FesqC/bgtvqiu16YC2Dg8Uqxi/8DrW1v0a9fn GuGrwhNtPA1vI/QPPOkugzsjB1T/8ZRh2ocKm7H4ORxSnltk8ZiH8wHeqod4 qdjv5Xs+1nsalkeJe35dSkTXD56Bhu5lwH+O3dJrnAabz7fGGb2ZxUWWliDP F80oHSIWFhbeCCV/KjYzasfxZMHB4wrsE5DEa22ReXcULp/5Ft4gMInPe29l tid34cYTLvwFLESQ51cYZFcgATao9e5/T8II8XKfPSYz+HD0ZQ4UzMF192Ep rbBCTLqYoSYqXQLGMcERo+v+Zl6+0tR2bBDHy55I3eXpgdM9KpL1T/rQYXWP svVlKmTrdDQQcsfRwd1I501bCV41bPr5kNYL99N649vdB+Bt5o+4M639WK+c N58qsISMAIXW2T9LYFo9IbdfZwiPsl7QeJM1APpvbEZe9y5Czo1hnznJGfQ7 ZXmdpjOFihWnrI25KBAQN2/QEOsDoWoxu/o3lUJCg1wzTbAW4un8r6a867Dx VMV//sED8HDs8ZOGPwPoxEFZJbuNQk+sxNDAtUEsM7to9Wh7D3zYsdvzx7lO ZNjTbxaE1SGtMk2AcSUfvmYv/PjjWAaKj9Otb1yqwptv9tH1c8cwqTTU88LO UVimc7yQFlnGXPqXrU5cy9DRHefA70PDKU6xj1TbWTDyYivsuFaIkhzcx59I lYCFpQJztOcytJL12YsaGFjwWY35YQgFd+8dufmmawjSAjdFRsSO4E//5eeH TEdApe6ZetApGkQEN/0+nzKNWib1PjVbZqBS+SwnxW8OfUzEt/46SsDm7x9r b/P3AdvFgC3dIRRYkv7yLEt4GLNGyg2bejqwXMExQ0mZCDkxbM1aHBM4kPFB fkRgFFbry++GfZoCzn3nbkz1TCFn7JI7iWkOBXurD7DvmoEXz8MXhqVagUTJ 4Tl/vBlzcrZx55lPgO435UbvuxM44fuh96D0ECQUtVxJyaHglfurwooDbTDv uPAxU7Idm18e7bJc9xbXojCu/CcMzGsnmy7dHMNnBhc2ZEuPgY2fMlXeYgFy 3aOu1CesI+Lg9KUFygjyB7IOSFwaAFV1+cPpHoNo9Cjz2c7rZBhlPUC82sKk +u+Zkk/v8BoatzQY+qqNYKMnR+6NuBF4FSJIet47jCvxDVflpwaBwkUqnU4Z hvG/orSUwAl067x/OUunDpiKzV5ute3Dj85RpMtsPbASStrepdmFhJYbdeSc WRx3Z35F95uFz9ntFrlNZGSNjov500KGW5fHx6TLGjGLLysoVbwcQpTlP+84 R8W/KW+WWvOnIcnjbkqQSy7ecrVw5DKvxpPnnMjB0tOYcDpL23DrDGzvYIrc ruSKVjsOPlURL8VdBxU2f9tSB7Vnr76+Mf0Xf6lJ+3VylkF17l7qWnwFntS4 4DpaM4cy3gd22abPgTqz6fNB6xnoMMgS/bO2iJXv1N8b9pSizZ0jhl055fDx Fb2+LbgYHI91ym00DAfhV+ytLFuJeK9V5QeTWRdInTDr/vh+Ftnfq/z44zUP Am/bzATEWFQt6oN5JKKYCE3/bHPpagPYpPrkw6P8AbCjbo5yYNDAsizrqQTL HA6/aYIvUqUQPhBRkfOyD9vpGZZq6gvwdWWNqLxxFs3k7udd6G9Gdb5n32jV ZZC962jPK85u3CHkSC3Taocgvt0DsltyYP87CYnSHeX4w2uNfieGAVo5/M1a 2kwEN+Yut6Qt/aAl8QhEijuwVpl9G++mQiQFqKz9tswEjuGGs8KB3XimKGPn 7r4+cBDoYvnOnQncrz0cCEfK0HF1QEjYIBjvHyb6bZMJxZcsPtF9ImtAfmFL YSExcEZa2+UNrRVv/xZM+PejBOQSbhr6GwygRZnxq8T1+7mqs427xmIW/cg1 k0GCs1CiyB2pYzqL7f82fH97dhGybx7f/eRsMyg+bGGwHGnDhO7FXWLvqaht 576FUEUDXWJ246mvX+DV2Eqmx71MEB7r5Q5o7EClNpogMbwV8lRMz3KtzaDR qGDuIZlZqB7q05Fhm4AqsX07fmyhooT7gx0mkRRcNU3Q6ksegjdU1YWeqwww flNOuO6xhvpSZxQyW+dxp8K0hnTRDOy4y3sw23QaVMIOL7VUzOJl35iBUlYy SrELd0/IkuCe1A/3cEoWNn4Vt8x8WwTvWDks5S80g7LsWsP9/ypxjN0i6hbr PCQm/yiNXprDDawqqyr3p1CAeLGhqHsUctkbqi16pyFBKUXxTBYNY6r/ZcWo L2BO8n9vHGJmYSI+WTWJew7rzSn9FZRZoG3jKn3Pv86rEdumvP5Ww5+FKw0/ +svwT92/bCp/MySVRb0NLBiHe/sqvc1Zp7HiwadxWadZXGGVS+AUmgHFjQYR HVCFyckfVu4ZfsXtRzRotAgKcJsc2t0nMoSfDn9WUv65CIxGWx/kmMek7CTj DW6taHIusC7Hvg82f93PJThFxDCV3mrTUiKA/btrEpz16/zg+eALpkPY4Oq9 H+5E+DrHmxbg1oFuNmF7Bm/WYSW30LNIai3wVw8O5c8MwdGc4xMTXn3Y/2tS U1a+B4gy7zm23RvAVR8FXgfRKbxp2VS0ajMJta8kmSSVl/F3S671hO0iqPh5 zSSVT4C83c3P5cUUlOAdfazNF4L8ToMWPx4V4lcbs+KfPb0gHEDcdy+9D530 NT5Oij3DXXwBJzYQUqBbYsRcubwZPZVjeLeHPwPJlZ8X91FZCdPve6cy+lhU 24UDy4sGyoGJ+CRz5G4kpEqbcBertKNBTqDbafluWNh3xdS2eRxOpSWfMZ2c Rve4W9GStwex+Y5vpM3NXkh/fUF9y0IL7N2sz8HgbMMFwq+zAn6NOEv9FH+n IAMmJOd6hbLG4BEf822hzVOYd1zhl7p9G0qEHHaisRPAmN+My+vGABwYaTn3 UrJtna9vafgcmgAHC3LjMw4qxvAqvNInDGCnzvWa0sQREBy93K4euoiyVoSa 617LcD7ZpOj7lXpwM3fxNXJpwuZbO1pEUqswmHnvrXrPDjgc84s4LzmIjExJ +x1dwxC70NchslyHrumsRpG0cHhscPm/LetcEh9kkxSmOIOVn/ly7uwZhm// kuv5Kyh4e4GvKZt1CvfnNXmffzsFoWnSMRlKo/Dn+L/zI7+H8GuFj6OLUQ+Q t4bkPojrRyMt8bWkp8mQ9PbWW5e4Qjzv9VE6LptJde1L1aYdpUyEXz/vFrzJ msMcSfdxA8VFmCUyhIR+LiLH20c+FdYLUOrs/l5zaRx7TpppZZqPQ+WLtHQP 40ZI8LdvNNNdz6vXhss39GuwPC96aTixCVZOT16T1RmGsuz7a+c+DKLN9gep jvvr4feBrad33GvAFJ3jG/QKhlHKRCManEbBjXKtUreNBH5TmseUmwewe9vS u8lrbWg91zKvcqsNts/yOJ/+Nww3TpeJc6xzc0nb05FjWhT0C4sihGcPwM0/ d24cEOuG1sPG+iH6XfguJJt03HgAbKjVOZ6Z4xg7dkmx40YzmmqVRXRTCLCx PFRXoLkJ+bZ8F5RpbYS1HCfjCrNBJARtXFPkHQHXAhOD7ic+8LLmi51ccxba PNvXXvOtF9MjD3weoK37ar/qvbD6Nkg/b2kkm9GL7oygT3WniUjs+0FrXRyA W7O/FHxrSNhQPuWhw9YC0nd2MmkrLYOFsnNX1sgK2hfcY7OMHwfFNu+0BLkJ FE6QjLPtW8EQyYRNZ9KWQCFdwadCn5XQOfPt3vhrVtX3ucunXzjOrPd41bGx 8hmw1f9oJcPVg92JUwFhs0S4HXPhAlP6CuyxPN4cdIGBc2f5eL/HF+LTb9o/ O6kVEL6vKjuGMQ/f1lIj9ofOYRWr6wV9nRIUfXjy5YbJamgbldlwUGQOrVMa 40x9ZmH12fyOUI41uFOkcuHD2xU8kt4uw2k7iHuvXdU7rzIGDN3aTpvnNGBN XzC5pD2NN3oKq/mezSL3xdNJOVVTwBDu1/MraMXXouz343pqIO+AX1eSRTUy rg72XLnUCLI5yON/phUczLsO68kMoMS8c7yx8yw4n3L30tWfQ/I13pJaXzo4 X6zXC6MuosYP/aNs6RS4do5zM3sWBV9/KuK4nT+Jl4u2XfnVOwkKZtbSRnYN yDt+ijY4WwHmfV3OdksN2H6g6vxpqW+gk1bK1hzTB8csGWyuTwYwbvtxu8Rw Csi9mLF4fHUa3yYekCjtnobdifpjUcfG8enuN2dW3VORy7fdRmZjDiqKpp4N ICzi7zvsjDGhBdh3bH8iWWUGbQZ/bZ0LmAVMPK51Y3kOvwmVVGjoLsIRwSCt N99i8PhoyFxBz3dwfUCdqntDAvlUgaCEBTLK9/5erdg1h3zM1rrd9TMgEBSc E+wdgVlscpJX2mrB1u71Fx7dAXBt6N3Ibt+Daxph8Im5CFYnV63NNIrQsXEw Qe/zH3SdZnkk4vwPvo8z50nCMigNn6g3EmKg7uMSk/4DtbhqjzRlj3x4Pal+ 7EFIF7RyyjXJmQygAtFClrVyCOMnbbc6NQ+DzbUzVz0kupARwVOcJ9cDIYOV Y38t6yDmibvwTrsmvFHaThoUZVPtIp95U9jJSvA0upV7L7IJDErvXT+88x+G Hv15TTZuDpaLuPVFgpdQr3+l2k6RiXCBfuV9YBCTamequV2VeA+Oym78dj+2 H9KOyOkxNfQAs5s2u0J1Py5J1X9v7uxExziheozqBOrbpPzF9GaUf1BoV/C9 AXaKmy9IzDeg0rcYW9Z6ImxNe2mptHMZivsufdSJWML/AeKytdQ= "]]}, {}}, {}, {}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{False, False}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{True, True}, {True, True}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{None, None}, {None, None}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotLabel->FormBox[ TemplateBox[{"\"\[Rho] : \"", RowBox[{"-", "0.9098218218218218`"}]}, "RowDefault"], TraditionalForm], PlotRange->{{-3.7351641462245464`, 3.098685520451218}, {-3.154082485680225, 3.7173515987194596`}}, 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], PointSize[Tiny], AbsoluteThickness[1.6], PointBox[CompressedData[" 1:eJwVl3c4Fu4Xxq3KLEVRyorCF1HSMM6bWcrICkkZoRIaSIWUpJQSSqUyM0J2 KM5rRbL33u9r8w57/vz+ev55rnM913nuc+77I2LjYniViYGBYYSZgeH/pyl3 mrKKLwlVLlev5h1fhvg1yVXvGyR4VKQUv0X/JWwXF7PZPzmH679eyeh9mYCn AZvjPr7rRF6mZxd3Sv0FNYP9sqNWM/imSTxRYEcX3GNkPDfxjY5/PN6N2I3M gidDvLZ+YAlsdZX5MHyHCodG2bO9UonY1Hlh126RZmSvSjlQGFEALLseCsy8 omOQS6xufnoDRB2lsRh9WsLoIGuCw2Qc6EsVUbVD6HBQW6NuUaoft6rqHf68 uQEv2K5eiI3rgOwv0Wf3/aHj3dzeiK1HEO4ZZ/n276wDzhc8fjG5i2hW1Po6 ToqFwK9f27j3dyvOab1xWLMtAXcrN6O/lfdgV+W96dO8XejyN4fHkXMRL9jP xESfnwU6d2LAP/oAlLI0uGnyDABd87vMroBp9L5nPSW7iQ7LP8zPHGliIPzL FzpceWAej+btzFkJGcDoq1ZmV5sGMfb71oNipWRcaR2nadLqYXjU8Bo3DwOx UI6TcDZ1BlKrOz/usB3GK6/t7zoyTYL1/NSc+dFmXEsSlI94OwmePGvFPLcb sTAjTlXYoBsiTCwO+OYMYR3PQ7beaz9RXf7Hdk03KnxnDn+dtNaPRYwTD59k dmEzc6haTzMV+KePGP07MAlOT1W3Se3ug1s8wovVAaXguGwV2zT5DJk5HlQc VmsEDXuWjrCkGSTf+LK5cF8/Mh/6ccBCuBbElVTT57M64FyWree9lFKY6O33 mS+aQb/FylZT7S5w9ybIurwuxvsn67+JkVpg8383TQhSjIQjLxUSd6kzEos2 bf8m7T2FlHfHjB3G6OAeMzWSaNgCMS71jpMSI8hz5bLtl7Ih2MqQlBFFGsCz ij+mIirLcMTxo3mHRBws1P16HOY6g9Ulg7TrtBXYflxfk/NtJz7bK1HI0NOD dxUMZJ7/GsGc93qN6Z9WgAGUagcd03Hr2r/StQtTGGseSZ03GMV7HzzV/vOq R07Ol1MOSIe+Z3eM5XfP4GsLvYU9t8MhOTWQUv1+FH6+HWwlNnWBhOhzEaPp DMx4V3Zew7ESNp6yLhA/BBE781U46YPIOd+eEcXcD1qlWo9/ZWzUN6maiL42 Bx6fnZ3itqxikmhwciszDTxU5A7WK3SDGe3F9MlZElqk5e1M29KMYnZ3bKzW huCrX+O38kcreJOUm7dTdBpMXrtrWm8ahIqbTjVLdlQkKewwmmibQPZ021zL Db2NA8N0m90U8n8ov3/SfQGuyUpG/HszBnWH+jx0E1Ih/GjGiZjmRXjrf7JG yHgz8Tn1Ur5kzxRQVX6GsCYOouyB/kSLBDI+8nq6+KzVBxvm2loHpurxU8/n zbUm00DNut0s3zwNbCOqexOe0/HkkFrmb7Z5HAz+opDjPg1zViaax+zrYY2J +6vlBBU1H6x2154dwtu6tefMDzXDj/Jz3eYSVBCaOzZ4vGoQmZSJFz7+mYUr ap26166NYGW2+thuXiraBt33TOZuhUpXP9p5dhLM56bei9eYxwTla+1uL3pR YRPBNtaXjtezPE+18Q/DsH6rgVgnI9Ey9XtHz34qsD8kF9yU60RqS9izcPoo eioaMRGEyMC149q/ovPNwFNy18R2bx88b9lnnGXXjAfXVkwOaPTi7LimFdvH WfQ61xJjGslI2LKk/Py87zRWsD4NXJMbgn2XlMabqtvATC8iiJfQhRZFXQIX 2uYwginsc6IXHSRanh598TkVD1FuqAic7IB//pH2++Xp6CmT+001Zwnm2FdC LgQ3g2M5w6I8XxdQ7n+12zKejaqVm6NrC4ewVWhq/cdbGri9VpOUz+tBp76V D/5/I0Ewiksm+Uo5JrSb9hiVkzDo67QVSWoWJplzeAWSqFgSInzueiYZPhsZ vHsmzEi4cTw/UMWcgr8b/PS7xsagZqfCf/x3hrBDkJs10NcT93Ht84m26EP3 uQub94b1w62LWrqCSUOYx5Tm6bGtBR+NS9xTHMnGoNq70aYV+Xhlv1nlwNFe 2GPmqB2qOga3SRY64hN0jGP3/mJNsIbpnjOws+Yv6qQ3PDFqWcVh3ZdGEfqL IH8jo6TqFxki+e7lvSr9CqV2sp7qNl3AgJnPVw5O4+nZ3M9+mwqx+L6j1CG3 bvD5PHul6PFPGPebCzweOQfvdkw0ssy0w8F3NKb0/AVcJAwVv92chXZ7jSlf t5Xjse49UW6hY/DmclsjIbgVVDoYpbKjNhG8n2g3R75YxcQje5VYDi9C+YhH ilDSInLBd/6Md2PwLvhUQEDVBCp98nO/fKoL5N7G03ruTuKfMxJ2T//rQkMz 77jahTo4MeGVNaEyh0PLs17arXT4lSlVlqk9jcVjrvqngsfhEueB519fTcHP klc7GovGsXhlgi8maQxYRWtOVl1IR40a9cK0OxQM386qO3B+AfRukacGy9Jg Sn51Z61qGx6YbuNRCOoB4hhPZd82MjhquyWpU8jwZjgzeTqnHubvawdfIAwh W9+tZ04Xx6AgsMvAdL4Pu+iKpQwKw8gS/83z1ckFNP14+MTDjAl4PRGToi64 jKwN0UKX+OdhXVfR3VU6E4S33ShxWKSgUI1pyVFNKjiw7JZ8VjuMN2M2VWpR +lHXpSz45IUJ4Ejf8uzG9jFsjzOO0lWZgqyFS50aXwfBK6S55pJ3J4YP8jp9 Su1AA81n7EO3N/Yd4zxtMpCEDLERosH2+tiX55fQptKMM6HBq+/cZmAoeu9N n5OrOMM0zQQu62BL1FhZNCJCwg5D9p/2dZh1NfNlSVkvFp80d98tMIFFArN7 A/8jYcfzYwnbguggWrI+Wr4wBpG0ykpJRjoeFIkZdyOtISVVNp0/rxH0MwJs rxyYRadhqVaHT4MQdkZYX7FmDnc+PG5N+zAGXIo6/xn192L4R+ItBcF0yJKr n5JMqcaZgw/f7/n3DzQSdgRom5FAeeDqHefeaYy/laKc2NgDGtM9TE9JhXjd Pojr1qE6CL78b4Z1oB1pm2QYIWYE9eRf8a3R56Bdf3TmTUku9P2NfWfbX4pL aUzurd1zwJd1+a1CwDy+nX5PFVjqA8UbOZHWm8bxYi7z5n1+v4FBPENmX0IV sGoMaPj/JoNiiaa4hjoF5U4wwi8dOi6dfCavV9sE3Qnpr/6ukqC5bNeLC8yr +KjRM853lAzP36xetpUjYYHMVcKaSgvoiN8mq92dQRGeKXVVfjqq5RT/4/Qb gIM1s2OzPDSsNT7yPsRmBTRqcfLwqX50MumN2DsxDwczs76OvSvBlo7zj0tz o4Giwq7x6X0deLDqqQ+RV7FkkuFj7bcF/H1Z7vrq0ChQM8Mb70UtwD1DkcGt m9fxt3ukFgdTKp61ZNh+yqYKhXf7c4jJDuLydbLBwp4GqCDsnj/9oxnNjvvc UTSIAYJt9etNyqM47vzIN+UsGe6HrfvpHRrFqdqkrRZ6PdAk7mKc2j+A+Y8y aaMVjaA93/fX+voEKB+IcZ1NLQIBA53nEpqMxK7fAiJU21lwabzyUsmwEf3f 3FMuD+jDb9KJF+OzqfiY+8y8WHwjhIkXYnfkJOY9PM6vcbQNBteeGf88xED4 /WZeL2KQkSjzR8Iqb5oCPs0/qQUPVvF5XdyJXUY94FpfZEvDCRR2KZrV5KHg 6aHvv7R3lsCSQ7bpwcNzaJWUyKrutQLahixjTcKjaGJm/oR3ZgAstx9UVVKu xuMNyr+dd/bA0YXC6wnvOsAy7Cu7tAwZmu2DZ5aUWnH7pYieRxfLwXS7Ft8/ 9S3ErKNbE34ycBAMqrm6fvZ1wGHGKAHnLdM4rCAu/UF8EPMs1Wu7c3qBXz4+ 6tsTCn5mGsqt56OCeIp55L+nRFCQ5j685BiLAmJWq+qr45AmxZEvHjaO9VOJ e0xtWQjOYmerbybO45hNATEneBkflSlfXMzdRAjlCM57OdcGf0VvhcgydWFO guSTiPIKpATDTSoDFZSYndw0qinY5f1XxkZ7EbKcw3TtotYhIDTRfuj+Kp69 MlR8mdwJN/BACjf7DJqWmFoska3wReWBJ6Kz/Wjy8hinFHsDJJuycYzJNqGq 3of4yD0VqPeEO4y5tA+6FOXi9p2rBoEnR2lJef9A0mu3qs8nEtalX3ePzciD iYcseuYhNMgs7eA/ZzWCJtXbJRdNijEmZPU519o4Ssgy/Ls71I0a/pwfdJnr sYL2JppEboajiw/K5w4O4lB8W1+ZWB2evn2lKHxyGDlf72excaXDNLHm5W47 OjY8nPP5dHMeJzPUk38lzUFZR+1klX8x6Oe7t3qojaH2mmItR/YEJOwOKj8T lg/bTcvUeg78wQuNUic2i08DnwDR3ltvHazu3Wos3LeM1lLRugf8fsGupPqZ B5f/gnjoFRfvXcO4MKPb2PK0HUp+pZpq8Q6hVIJjl2v0IEz8Ds+iHZqCuG9j EbWKFNTT+D778vAY4hzxwbWAdtC+TFwxCP6Bf7pqBFPrekCneHp56t8SMCnG hps4NuOJejWlI5cm4RitaO3Px2kYLpA+PVlGwxunQkWzxJgIA/8ZjfbYsxDD AxdrNBdYCNPvB9hffF9Ai1AWFav3jIT6dsVNKYLjsJ/b8WOKajdK3uPde7G0 HvZ+etEicjIWsnl992leoqDyfHJUTiUjQf7IY94fFQiy9ALsIhfgxxpRa4pY F45cXhke/fp7Iy9+PKo+T8fOynbBZo5ZyLwkoaFPpKBhzP2iC8/JcNt1ounx ho4GHSUt3xPmkcVIgVn6NQ3PxKvNSmYwEubW50eJ0UMo1CAoQ8xbBpuYAIcd f/7gG85VhuypcfCgTzF9XmkGK/U2v8s9Y8gWedmfmacPKcpbf06Qo2Da3Z2U M9ONJgf6F2c6qCC24wKXa3c0KA+bBNBDKEDyf1oaw1sGyrtzdrvLEeFQxLMP jPcpOKVdz7Wm3w8B0btuDBwnQcZF6yFt6AA7B9Pwlqku/LpweVk0rQt4d0QV jsnUgXe3N/1A3hCEMlw4+EGwFxiIk8dimbZBuKeqdUbsIiRPhSwnKlGx2F7+ ZuITBsIu9zFxoSJGolxOTV7mUD1uOXI2xtywDx0yfZ2ZXKfhYb21/kz4Il6b sFquLm1E5/TRxAr5OnC5UDe17Uk31L+8+KT5Wg+WhiaSEi1mMELG8IKQxhI4 WjEv65k0A0PBO1q6egMGko11/Rl/oHl77JnqIw1gKeuSslLQBiH9+8vP99eD GcfBA0Mqs1BXQiCtMMfiSBlvrKxRP/KyrI37utbjWbcTO0Kfj2NA7LfCrGdd uPsIse7XAhUruKuW2CPqEA4qXj4uT8LrQ1f+dheSIXHTS12jKDL03Y/+/vkB DedDUnfFa46iKbPTCNvtSXA/0B51PbIdRt5Rv96JqoeVlsMReDof+v8csmuP bMOnmzoWyRrLECQvkSZXQ0ZNUcIDz7QWxCt+O+6QaJAqbvKy9HAoFM3M1pym tIKc74NyAeIyeq3lssncmwdp0ZcTCg+pWPrj6MV0o0bc6RlAtxwaAmFntQMf V0cw8iHDUEncDO68qabwI2oA+DRfNd3dTMJXpqZ67763w3OJ6qf8rhQM6JWV rxlah58xDpfLjQfAQq668nbJGCp1EisPilVCREPshW0riyiulXCAOjwMJgsC ZuSaSWSrevZn+z9mwqObngu5IU3QxtwauKn6GyzKuJ64eoGGWbt9IyY2FWCj 1IFS+YwO8N9HCHatHwHikaAtP852oztlaUe1GBE9zn/U88gnI+Oyx6koGTpw feF7onWZhN6COt1JA4OQ9NWl/+rVKrSpGmLnmh2AtbWjb9Vt1/F+3jEJhrZV uDdjo/ehj5F4NPiRv1t4L9zjb7Bbz8sBuZ0OKir8VUhIPHCn7tcTtBzy1/on uoLEPSfWTM/OAQfffsGIqB5U3f2PyL/B/Tw6xor915sxVao19qvcCOyYotjK FzIQvCxdE4ibV7AhtZNeztqIw2piF3S2TkBNq2KPJj8FOwJ6PFxWZqBezzLk cBsdhCK23As7OYKFEV2qzvvJ6C9Hrck5OAkuXh/J2Zr9yMUjoP3XZArKrcyp oU8ncS9X/1+L2jK4YEyK288zAIT5v5su2AwhacSZKevlAC7s/yocoE+GkekM 4m8vClA3bStqFaYhy/vlaUGFEbS3nHpfv74I786/pcfSx2FQiCB25w4Vg7aw HbS1DkazB3G3TB1H4OySVOC6+To6DMxPlw6wEExG1CQY6T3o948uzP23BBeC xFNeCw0Biq/rGtyfxuodHi3n5vox/8ldMb2lMdi+MHTk8olG1Lz1VKxBsR5D cjqhYoMD9s91OnZz9CEpR2vv2F5GIkfmrcfGXht1pkghz95QwdLvycLDnUzE Bozd9IC3DxZevYLgTakoGfejZtEyH139tj40fT6Fnzu8ykN/TyDn3rqP8+p/ 8YcjxyuJvgGs5tzuH9lUBbMKe447FA3iWqbH1W3ZpeC/sD/K2HYWg7fkcNZ7 TsGlnXfFrxNaoXpwIPZL2RQsBtdUEEVzIT+fZMZ7ew6fV30Jz5Km4UVXwd9X SkhguSjBmjk1ASfnTvGNn+5CJh/7ddG9NCg/Z2vrkjeKeZPvCk8wF0Atn3B9 xON+YCclcNb9HkbBF25Ch9looHFNmRDOPwpab7m3JUR0YI1DaXAxLKDPzaJm SucKZJHvm861Izzfdcx20oyKwk4CVOO9FLxuJitcLtGHrzMdPr+dIWPa6dL1 5vtpGJVtTX3btoxn7Lw+PzlBhZhAUvz53Gk0enxu6uPDMbB8HhNZdYsIlrmZ oZf7p/G+1NZHuNF3gdLnU8eMyXBgwO2etV8xprja3pd7Vwe/2rcMfXNvAFe/ d5nXdSZxxMVS2y6PBHU7HoYdNa4BbvZiu7Zrk+jkHRzg60eD7J7TT1p1mAmf lbaVXBZjIu7Uex9cVdyNj/kczjptLwYTk5bALJEZSI6xYmQ6XYrxH/6Feo5v IliIWRnH/WEi3uCJpCvtocLWb77xxO9LaGJi/9VlaAi/3Gd4yaBSB0NLQ+mK nV24y4Iu7BE7BnXjuiO/EsYgId3on9bXSeTaNNg994YCDw9MfP8zP4uLbCWO MTd74Yvy7dr7SWVwy3jNvTeFDjJOs332I6Oo/abo67XTk3BSO+2wRdYkkrha PyTyzUHyaZOENv1ZjD6X0WwSNoaHPRzETJQmUGd883Of5b+QHLFupNBBRfGT Zx4ui3WAN5OkSP7IX3QMjNm0RbMVZEeuL/ZojqFIsOoXu68tKGAptqSzrR7F AzO5pHjGwXLKU7yRNo6ZM8/pOi1UXDljZ73MtAxnu/cb/h7sRoO+J3/42xNQ 43Dvwf8OzUGv/T6VoblVzCKVzXBGjyJDqF5SR8gzWOVUOEg9SsVH9kWndHp/ gVzQN/f3a4yEjidfSK4tDMSQ+vL8VZsm+Hs79SIXdRAuBAjZhR1phOjs0BAt wjjcvyMTm31zEXl7hcKUnDb0+EFYz29lFZ6YfeK0Zp7HwDcXP5YYk5HJ1KMg obQNPto5/X5s24sxzH/feAR3gH6e9MGOsFFoZrm64Kw5hQWO9oFn56goyx7m 5s08Ao1nI2T4Smfxt7i/r0vfLOh/k4lttR6Etqy9e1e3kvB82P3jnKkb/Ovs kyvbZo8Pm7Oz3gZ1oWiq/c71qA5oL7DJ8zrFQFh1bJI3SpjBb1tMfTym6XBi r9Psn6fd2Pg3tTopzw/zzdTC36vWgE2H4hmx7iFsXPkcFJ1NB8um7ycPpyyC A7MSkwT3PKbv1X/We3Me2FT92cdFyHjBRjDoS8AgtjgLaw2/bQVood7Tf0BF aQvf9MTZMnhl90lAS6QG1I5WujAXUWFZ4PCPnp5yLCqN0CtX6IPHB45eSmof RUmWKJV7Mv3wNGtLi8CmOWD0dRvpZ6Di9ajDIV9nOyFh3tRfTegvyohIK2y9 t4KnWc991U5bhvr93fVbBobRMNVvuIyLBEdFedRrLNNAceGd9kdoBeT0UpDQ oOIuBgmp5usNoJ7BU6xt04tPveXLpMvIEJe49DGtPgWjesuukc/3I2trT+V1 tSnkVPzCPanZhbd2mH05bcJEUJ2L/3VLch0/TV7zvWUzhccahMOunluDldWQ OV7rXlwRuyR/ibsPv6SeZz7bNgOKUr23As5MoMXNbXeMzCZQ4L8tlPGbo3A4 PzHvuPks7NnF+POr0wJS+uUyY2Un4WVX+OwB2gTmHo9C3c9tmJTsSb/MOgj3 pE2MlEWo+DKbdeFEzxxMzvwqjH42Cpw2Fy7c86uHo74ueQx6VPQzS5L4erkP rhGUevL312DkvZC9U75EuF1YQpc/Uwuspoqcn6PygNo1doTBax76z894NkbR 0EDtXAvn9iToKPvy/bthK6Q808y4br6JcFfy0Js0JTYi79gnTu72WjQ3Ft+5 zXhjL8Q1n5cJqIMddkt/JIVGsOSw6qOzZ0KwQvaVWsimbPB0/8mi6jUGHDv7 5A5wkDGkyF/CrykPWY0XzT2udyLv+77/LqRWgFPIvqMrqg0oxPJpJdtzGHxe duwy2EHH1sjdx5X6puADr9o/7GzCe/teOPrqbexNn+G0rXqlUDkyEZSyeRbZ t8XZVG6dhxtHBIO0b1OgPvFQgjhPL56clXJieEDBILr4m6xQOnALFgZp7CnG 9c9lryUpdXjuo7F/OR8ReF/wbGJ6uJEny6mJ19ZrQeos+WZvyQCeiUif//xq AEX2VPyLyh4BJs1yzcSzZZDLkXrmSXk0vuYRjEiU8YPmELJ9j+Eg2uxfFtFg +gR5X9NanUqzkLT6cWjQbAVW8vtRM7wDdUhMSkJmPVDLWADxF3qwnsPKS/Nu LzYUftW6dHIYhD0eOPHf7EDFwzcPFRU1osap7eJUBTrE1Adl8c4u4PHKiyyF q72QVcP5sbZ/HDksKl5qkGqQTyPCkuNhN5CdX7RxQjeGn4J4K346fL/JtVQx 2AqrGke/KQ9M4lK+6Xhtwxgk7zG/46nSDnuPh2jFjU2BVPlR/fqP01iWEHfu 3pE5WKt58fWm6zpKyvzrZQsgQYDdAH37yBIS204Glcq+w18CYcWRnWlYfu/p ovCWEiAquN9tt2jGIaoH8RJxBqRDpNUexZChLu6d9sVbNOw41qzDcWIAxh3c m1s314K9wO0kzS1lQFgoYxO0a4QPTv6+Fnd6UHiX4FszyijcH26KMZckQ+3W xz/lr01h61bXrbpuPTC/T93w8T4qNJh88CxiGsLzWyAxvoMCF5Vv+U93juHb Yz9GLTkpmDWcu8dHYwA8gy7m/MgbB++yrQftSqlw4FCK/tIYI0HsMJO1vfA0 /n6c2q1yvgtjvo+UspyqR9kUC+2J/FZsi96/ZueUgKdcr4poW4xCjfu11x3X +lGZffKmRGox9p5qLgqXmQQ/lwdjQtRJNLNvzD2WvaG/OZYG9V8NKPxt9IQQ 6RauSR9W0JQcBC3Pxs2x0hu+rTSxbKQ8BdxZZy1dFQdA0rf4MZXaATSdLk6h 30MQ03qe1ceIBjuMF8Z5decxWtOphV1rHuRTdh84EUBB89Bypy89ybDo63nE R7YCsse1r1RfH0HhXKbikAtToJLCaWWQtwAcE99GJWVm8OW0toVLZwPWebVP uFDaYMs+hs8m+5NxOuuO+7PLdNiuvP660IWJeOaWwkLmGRaChoKt2yGDKSAt epR4UTtRJVFuvnawCvR8ltN25JHB2XFgOtboN373iWmtOzGIN3OZ3ResFrH2 FBMbHloGQoH81B7mQdCotrr5orsVjh9b0/M/MwbHuOT259kOYlarpdQIxxL6 Ptn+9dNgH6xaOfdrpXUjMfQdy9rQ/znzjtRloxmgXGnhun1kE5EpYXf+yr4a LBT5PnfQYgjWfvYOhJ6bwXCLLz9syvMQVh4eEWMn4xvyM3ElnXx8Ju3oIpBF gppecxU7RzoOfO5wz7RdwcmeyMd3ybOQ9q3kiu+dGbyt6fLI3IYEps4fXgSX 0nDPrakac3EGwviRAEe4RUV5nyHWlDtUGO8vCinuG8Jfj8Q52dgHoYCmaNJj TofcQrNS/oQ/mLTJ8XvzhQU894ixKKFmEALPPnrOXD2LghMn1rnmqPB9WrVe ppOZeC06SLWqYg1mdzWYHLozCcbVConjkWOYnTn8UvbyxnzVZ2mJbOlHdjaG DJPGDpAQo5HKGhPw34pM5n0hEhomr5m1v1+FcSfGZg9eEmodfzVSNzOAPS/6 o++OkyGBcmrJZTEX1F1Za2+OzMGzF58y+3jXUC1QuNY8ZxCanm3KCJ3rwza7 oVM7AxdhNo7TcqGWhK0sZgduxC9Aoorildh3dOwZOT7+zigD0w0GtG/WkMFR 2JA692YZsgKZJ/tpDSgfzyVSxDeHDNa5Nz/5+IGitvzrdjkqsCUGvAg4RsHq /peG4W19UPHX/tNungnofE4NZb0yi0deJ9i0fSBB1e4e9p10a8x5OXLF0W0Q 71Jbfn+eGoRzRtuOXpsvBcbTVK6TTaPA7fj5k9ShKGDdrTmdM7fBA2uePcYT g1gjVTK9xMpIuPT4ucur7EE8Z4Fv2p+0Q5rUeR82wWacy5YVtvtvFH2KK12f SE/AfUXTk40eI2AhIPovIr0flFK+W7FxlqLEkJZjrt4/HKROvF280AgNXHtd b9+eRR2tTMnGT5MQ+baUiUtwGHudWT5vbmzG6xSvK26hxXCNyYD7/cAY1oxO mBdxrkLMpIFmSiIVI8P/TGceG4QU4UXD4Mo+nHRWt9/D3rfBQTSlqPvRqDTb oMxUFIPht07ZVViTMPjLydw+t2mQk6RI9ssPoTsteHQcaZif0Tv5X9c7dHJX OS65wZneTPFhFhrNkDFRY3p4awHOnuksbT68CiXNzx/nFC3glxdnrk3upkJu RuyBKu5lXGD0f61En8Jw1rbEdM0C2Igy+U9lFyGCMeYk17MesNRd9JGPHAO7 +Qo176xmDKzsvmr9ngr+TWLZ8+qzqFlge6VtZBBzWEUX9OpbgUGq2LElrhHW pu7YvDk1BP1f+3tsDvai8fMf9cbpGfDqyHcl58nbsNYo85d2OwsuRKfJs/GV Qb6P3dAZ7SmsYBKZe76R53YbCPc6tI6Avsr8veW39Tjzvn3H8pm+Df/+pa27 4RN7qT/iZhl6oHIsjF/0RSbuaSru1NXsgIPiDcf+vK+Cogzl5YLHZBzkVd6P J+dw65r0RKHGEhjxh/klGA3CZS6hjnWhJWTQYr1qemgQDoOk8Kn5ASy5PCny fKIVeFnDN29JGgS+BPqbHxfmUHDxLnj4U6Cn+ov6K19mwsV+29u2Latov/9F l4jwAnzb4h84rLOAJlfvevnojELy9Cw55WMXWl37HMsrPQoSV8IP+1eQcNed +7+dfcnAEDY7c0G9DaPOX9/5vT8MhPQLIYwwD7nh+9t3DNLQW/Z6T9vIMvDS 6LITo5mwt0P6Pz+2EjC8fz9LcfM4JNf5b82+P4DPmIrVQ7c1Q69R9odUSh9e CDU489i4ASnhZoZe7s8hc4h4K1i7CnR9FXYkMbXAs2vHqjPjGQmmde82J3xm In4ocU01tGtBsRcazlbxo7DH9Xj2g7ud4JGZ84R9ZQCZvqfm9+6dQ86fDati W2bgZ5sW1YdaD3/IrB+OSFVC2I53TNMXKfjonH4H5dwXUJmoFyhM+4pH6/vv CLoug9G+J0J6h4oBbJy0jht2QZTpdf60/FW0+H42NrWcAqpF8glztVuIfJ0Z DlwGWwg6/2Sk5BfIMH7PpGVUfBSVK/8r37anE2Q1WR34VYbgyo55xhNyrSjG 8elXb0YFNG/ruVr7Kxb9dF4mMvKXg8fFS0HhQRXom5TgwepHBi+p4lna71kk PCio61EoxPTv0lL/7Z8G4rcMAv+uD/ioqOFO92EGorxVbwtNkJGw3vfMfz9H I54O52QUZewAjcNX3PZwlkLSkf18v1P/4vsrv/mvVM8hlTn3UuWlGRA7pX/C PXkUiEVP4elZMu53+KTA71gMPjuSLWi3KPjO5dXu0mUKMKwExFqYxKJ/jqnb jMIMTv8XTCk1mACVry/O1fnSISLQMPFnLgkfpoa/Yv5BxSyf4G5LmSp4NGtI 2v+sEZUdpDOEmiqhtFD9l7vjMBbd9x3PNR2Hxb4JJ/sCBqJ3/Kgup/4caOll 8HT5T4GZ2Q/To0+qcZdtImmn8VeQE+PgV50ax6fqra55pAVU9zYvyqCtwpVk 9fOXHX7i9xFzFU/GAWR4zFhu4zOGLUXy1gHbR8Bdmsr959EMTCUKzl3ZyLWO XkrB1NcV8Ib9sKNK7TBoF3jHL2jUYuTHPheXc+7YSYtwMDgxAicnmUzNPgyA aOiYovK15/BI+W1UwmAV3pL38x64+hXyUz3OHesYw7/7KJevhKzC9p/XEveK UfDOmc0ax1RGwXzXjYGmviasqDa3Cdn5FZ2KdLtOy/cj1Trz8NZtzISx04LB yUPMxLCmcn2R2QUo5X9mU2s0hMxuv3LeHRuGk3tfXhTsn0bvXAbrnMPNUB54 nCxePglflPi4PD1oULA4reEmOo2GJkc+ham1Q7j5Y62niwVQRJU1p/AtYN2x p2EOf8nAk/lu9yrHNKZdP5pXnZ8Ln1KbNdI9mAlf4h1M3ioyEm9+8U0V2t6H JuIpipQ+GrZlykXuhHFwHfVzUA1PxtWKSwXrna0gxNQjsVNvGJqYhq8VbR4B 7vqW9ZE3RNjS//hQRxMdfCj7e9b1F9Cfg9vgqUsUynN1PFltaMI2Ze+kIql0 UOCe301cLYDXlv3hHadz8ejxKdvCjfmwaZq8GbCzGUsN016Jci/Cix+S6bwz zfBI3T2DMWwMb/0+eEdSaByVhve8enizDwyYaVnbIpuwMOtlkXUoBVAhNSxx dyna8d7QLfivE0b2S7oLTo7hw7LxsBTFdtRtK7AYkqwBibE8M5LWJC6zHyW5 3G7C1Z4LVX69/Xjl/Ge2jrtUfKOXbMjTMAMD/ZJ3bOX6kZJXsslBaRqcFXh1 H7v/QuFfVxY91+vwGY9cakH6OIiN3foY5FAHe3UtqM5iC1ClJfrjTFgr1n9n 0U8mDoPijdITd3+X4aL4vi3/3ZhAMZFymXmlRZjfRgjZHlaEouOxwYxuY7in UU9donwOKm84Dt0UX8UzTWsRyTqD6Jf2xGVm1zzwnMrb5+c5BysGi4PKa0O4 v03RYnKWBN2tFjDXQMVgnhNqAsfn4GCIzxL/dTreb+0UohTP4svbAZlbji/C 58dEGGz9C+8PexsdnexB5eyDowpsLfA6rCXJ+mMd3LCViDKq+IO2h4kX7GyG oFsjP0JGsAlZ+cQUpG178NxX9qzppRGQ1av5s999HIlGXE9Sx0bg0t2LH5Yq 5tDa2379zQaXcQqOO/Ns8GLTtr8uJKseEOqYif4g3YneN2Zdi+QG8Z7XsrfQ zlicoZyNfD1RjvaOYtFeB7tQM+zY13/1ZHTa4af46HkdtFSuijZQplD5d9CX u7E0+PGA4dP5j2MgZ8zk/rd8ANW80248WiqDnnQtHVf9ISx4MHAiaH8FqP3j 0c8zb4b4K6tvQpNpcIY6oVCntYBvm7YVTlKK4U5i8zPj2xNQZCLXxqtWiMan yr6W6v2BwfEJV3vKH2C5XSJs95mEOTxHr+7KqkWFU0YWtjvy8IufXFJq9SwY sBv+vupPQvtLg7RstlSQIp4rKv1eDmd/fPt0rqwTfQMl/wlLjYJz2V/Zps5F CFK0exV3egJz4uMJ/3ENodYrt69mmsMQmffy98OP6eD6LJLXkEJB4jvTx9yZ ZZCB9DvV8U04m3LmoZD8Aqh6af7tPUNF4i4KjvaO4F6aaPoitRK+3/9e3nSe hRAqzTvdS1zDUGmW4CGeNpAtzjlSIliBzfSPUp5Cf/DK/E32wwFlSNmKagtF KfhkVDP24doItI7c+W/LdD5M7VK8tKmFBMWWY5bB1zf+r9RH8D+GadgdsXXM wYMOD4vNP/A+39CTp+MHM44xMOg5amms9BsFug2OBRnWor9S1XTzt17wYdt7 2FU4HJQWPiUct8zBAhdOu6pdo9AzYBJ9TnwAsgaEzrovZsJ+h1UP4uc8YAwJ Xxe2IIGyktjeMrsOjKt6zKuxjYnAp5HQF8OygK5e+5v8uTvQzkduv/2zMtDZ aziw+XMLnnvxu2V0ugBOXhym87F6gpuqgEz9Rv/v9Szp3Q4eQqcs/+3H7s+C n4TSzqclG/tk4NvZ+4sLIEwTX+wqXIaIrB6dfQYUlBrvJDlrbeSXbVUvRdj8 0HnmT4lIMwVGn3Peqt01hH3nTZxFnPvx7lp8bfKNATh21ieV05wG7urMpwLe tqCOlVXij/tV2PS6LNXFOQ4iE84qwM5Z9HgQpTkVMwVjSbxzSsRRfHWmNntP 6gK8OSFvUcC3AKZlDZa7RGh4Uvbrk4aYYJSNr6lPuNSB0gW0L9F7aRCfFC3d fpqKhUpRBWLnx2GF9ltMpXnj/ofy0acUBoI9qVZ0ZLIfd+eMVe2erkBNmmRJ WnEfJjyq91C+SoWqJ47sz4z6MVK2RarhDRVPH+f8XPaEhOWnfOgiOzrhXLFt lUZAI364+pY7SWAeki9PRn9bnMGVA29O0U7NwqJIbUL+rhV08gkYduqg4yX7 tweLO+jgJtIeEC5DQQNP8Z7lliiQiNU2XHOm4fGrKY5bPDog5HOoyM5rjAS/ PXXyF09sJibEX2UMfDqN47Q8ekTYMEgw3/U8t3MFvnnrVJ3fsoIrda+2GUrR sdFL+2WU0xxwNqcrqoSNQ9CjqGe5n6koG6c62rIwAISV7/IOdevo6nOo79vS ArbT921N/E4D2YvJo04PG5Cv6t25XUbTGBB1pz2sphpPtxakmv6dwBHaf9Zi hzpxW5KaSWAaHeSvmYUEBA0DhX/nq+M8NKwZIfzZfmEci3++yvBvnAdOn+pp 24VusDxlvz00shGNj/L+MDv8FxPOHZv0lhpDrbGFbVtlQ4GiU5byPX4Yngc5 fl4f6QPlDhZoonWjwT5zHb5fFSAh/3TwTC0dBp192FgdaaDKofa+kNKIO84s 60QFUEBuc5lQYPcqBtvtimA2acT7naSuSc1B3DHO/qc7vwgLUu46c0R3oMMs F/9gWhBIp9f+jExcBgEdtWpm/WGMPbtLWbepDdOsv7iqMhVju8RA3g2GKVTj yiaem6ZAfqeL2C/WNVxsZxXWMW5GBharWyI4jq8DvC2cc6uBEHe8wI3xKihY Jwy4HmzArRNUsKymQH2g3808/jXYaujl4Cc2jWV2NmeS9ceBM+3ZT9mQSTRo HRY0L6WBJfco48+f9ZhXXTAltcG7W3d8/3Y5uQv+u/XN58AMFXyjjDZLurSh 8PD1dd59P0Gc7RntIK0f+tkSJ6SchnDT1c/7Y7ZOQebkjmCPJ29goHikg2uN BC9fq17ev4+BSGSqfFEgsQRXiEazhNQxfHO0+dIaWyLy7hzYNp20gpI61Au7 BRcg84t6VXE1FR+1MTRbQyGaOXf+OxW6iISmPZoKTY3gaWbjk3mFDNW3b5tl z0xj9z2F9Lbz3Vh8McqPsaITol4/cLIaj0MeggQPe2Qn5PadnzhwZxC/MN2/ 9BuowD4nxpm7UI5ZLaGjekfq0Zc4d1hkcxZEMbrv1dKYBKMX2Td6u6igVjzP E9EzhAG1fdeY3s3ArdNxkkc8ZzE7RFg2jXMETQUd+YQyaPDJ6i/nJbcuWFh+ etX3Xyx25KurNjkvQoJv8K0wUQq+uvy53mZ3K868cAjctt4PE7mFLUcflOFE QcSj4ftTkD33afm4ezxaNVg6L+uWw42EqB8yO/rA70BswrDzCLJ5aHTS/dKh Tvd0/SM2OloKDQtoUeqhtJg8n92IcEby80BuJwk7Q3+bkW6Og5+o7MiVZDr8 x3CK8EF0Dr2qx785PZmE406r8f6//4KBx6sOvqfz0KdTMb/uPox1u5z8pDb8 SzyAJHT8OwWSA4xerTrPg7Tmqmnls1aU0Xs62rxnAnUrpZMEXesg6an3jOGb AJjodVdJFuxDfbFMWNWgo0Q579NXyb3g1WZdeuhxHfgpxjx12pGL8n8UR/N/ D8C9j3d6A4M35vHe3PEp1hb4XlYmoPJmFtsqvpwvXCuGshn2Q0XW+Ri2JFJ8 JmYU3y50c1BOt4DqyM2Z72llWHO9qbXpZR0ei3ztoU8dB+MP31uuvx1E0fgO E23lBpSWktyjqpIDFUIJQ+pPJ4D9AF7k1G9F7rB3x4OlFzF52uTqfZEFaDx3 VS1tfglZFpUFLMLb4Z+oNW2P+DyaDtI7Fjf4hFuXNha2pQCEG9SxZy0EWjMj 2MToIxid7fBCL6QZV1LHPBLHSFCZuzNjy80KnO8gc5O3MhBTu51d4nrooHCf fTSWIxPfpjvcy4r6CUrxSicaI6j4h9PknPLqIFw/+MdcsnEGGL00OVrp81i+ 1VP9dusoKMsfrLlH7MTuYhHV5NURuMJjLNsTPIitV6yGRe+NYbTFmYMhxyfB 2mA+z9PuH7KZFj4zSmsEoipbZK/4LPjU2RfGN9LxtMCUOC2zCI2N/z0+7kjG uWyH84GZI7hlfSn4hCoN5O2dkkpODOLd4zTD3RdK8PYjzZKo14vwxd7ZddKW ikm/D2jvCRwCgdr3X0JSpjD/Zc++OSINzZ5K/KGeJUNNM18dYZaOVSoHr0eQ /qHRwYt3TZun4aTRz3+eIYv4cvRXu9K2YWT410NLfhYM9/JfXgs7M4PeAje2 tr+kwa8dEnHcbrNIO/udRS5wHibfmrUNjVRATQxfWcZAEfD0/27RCl5BTouR 2Pw3mwn63zI5yJYshO2sW+vrBDYRK4zvaB+zqoXEgZcN7a+qUdew+2TiyVK8 P6nS4jbeCK7p2w+Nc2ahKudi4HudOFgXVZoTXfBCxxdiKn5KI8Dw65f4gsIg xlwLO3GArw4UdT34Al1okN3POy0cSEWx5XE3Z94xbFgaf7+gxEi4m3C0TfZL FY7PqSzkqudB2YcfxKdlUyjHLZMcx1sOFoyjeQqb+mDE7ePmQb82ZNryolwr 7B82ul3LJiZ04cxgm1udyDCSJ5ILm79QsD8iaFvM0jrY6u6IfOu7jE+JFYoe 3eXo3t8gd8iBBue3s7ymujzCAyURdr9malC/SPV3TfYqPK3U5Gs/Nov9Htzu oi9GoIVoWEGeJuH+w2SLefN+sNRcG6GXj6HT5Mmj9UhFhl1qmWW+M5A90rsr uq8Xun7beOrJp2OmQLLDwuNe1P1UOJETMwlsnCnxZB+EF27Kn/3UZ5D/5+Lg P2kq6ojt8HrAUQ+kaJtfn0e6cEeYXFlBXDe0cMzb1uU0QajhFjUe03w0l2wz TdxFBPL2uwl3/zZj4MnT2mUGY6ija6Am7UcBLzaI/MkyDMEMBH+1hQ6ki90Q OL+FDPNfvf7LDlzGcWrz9EzkCNwR6rrezEzCwfaZ0bOjQ5BVZSyXPNOFksHA orqR2xxYdHYTb1PAyvKlgO2G/zpOMjMpfppAa8m/1tdZFzGJm2tszJyJsGT0 4ubv8/P4ICqMleneIuR8vhVj4zOKdukFwVc3DwInf/LDfUWtyG6u+qbnRxqM SB/0Ew5sw+5+j+3WjBVwu6LdLfvMML5I8k96kdqIUT9NA1krx9CTEBPWpDYL PawabcvpX+CXg+/adGQfHOddNz1SMQYvTy2M7TEk4+EArsN8azOY2dVr0eOz CNKHNh0WTUzDVr7zn7SPN4N3nqde1tZxNGnwr9CTWYX7pqyb0y9RsEmQPzMj sB/U02a7+IkLyKnGsarE2oGW15ZIW7TaYC0R6udCJlBFzoxYG9UL1m/2mj7S KsIc2+KkOpYZeN0c5PVAug/5rl4j6/XPgQH3LU/Goz3YLf+96AO0wszCrXnF 9Vk8X/he3mrXEk6YvLxa3sFEcHsfuMtKhYTJyttTl570Qfv5b7bnzEfReXSP lx1fNewkhX+1mpiG1J+FDzaxUPB3m8KmqxcyUasjbnRlZRRduYJcXSdboXIs RfWaYjvYfXK+I32rEU7bW7KJ+zdimTstX8ykC/hXSFMMwf2w9Hj/ts5PA5jl 4XFktHAU8mNP1e4MnsLThn4cD13noC2Kp472fA165Q1DhhumccdJg9Gsu2UY t/3EY1ePbJhQcre8KDAFD5vY2cC+HG3PfAudPkCDntVMzXGzUXwfk+PDx9YF Ym1G/LLUcVyuHnhxg6sW7wixvZAVHwPNIt24pf0j2OBH3v7n6TAMil7xfXdm EljeP5Ub8V/CLZFiuTfj+7CdpXkz5XY/vqytPiOYPQA5pllN56mLOK5wTcGI cQ2F0h8pErWWwMLL7QWdoxcmFDncE4orcfFOLzu5qAbcvoTpzkpP4iW3OLMz gTR4i0Ya+2rI2DEiH/bWfhqurOrvaSQvoHptSceB7DJ8ZSjtl17cA9Y3rS5z jiWBb8/R4qa6aOB/sZvZKZEEwvoXF4+kx0GUveN5yp5FTNlToB6/wbu7+699 eL2tFXQMm212fRhHOQcGA6bFBphhVokU3F8FEUGb7KbPD8OHQIK3tvEgmHzl qT88VAWnGTjDfb+04pUMi1hlCSrufd9/ecmGBt6xntf/vKXBZPel9T+CFNTP a47YQy4Hv2977eWE6mChkz35Av8A5NvucpGraACmzV+3dFZXwdTdDrKfCBn2 iSi6Waf8RKtICe9huQkQLX+7PZUwCgXNNQfjuMh4ze/q6wXDbhgy6n0mbteE f/jNauaek7FPPK0xLCYD4n6+VBE3aMCgv2/t13Y2wf3+2B/bdUhoURf3ru9o I5yqTWrMFBvHJf4n74XNqiGqMsblxPwEGnrkPf2T2Q+OMs8T4tdHsCVr3Ica TIK3JwailI1nwLtAlzh/rhuNj30w2PNrGFwym+vcT9PRWHyrfuPYJIhrju9q 8ppCV/OmMdc9vWAHtXUi2fPotO/tTsLmdqS92M+V1jACDT+cr2s/XMKfD5hb OL4xEMrld2YGsVHwM8HW+4d4A7yvcBk2SmQkyIRxG8XyLqLYx44IY9IgDMX7 fb9Y3ICPLQ/K2JZdxb1xpEMUk0bgylAxp5BLwbxj/HUA7xK6HtykZtMejSyd sxIaj+pA1Mi7NsB7AMS6//wXTBrHX9KBu5O/tYE6dW+P8tlivBrBYqs33Ix9 /lyusZGLkKvfphUY3YLGbL4PHhT1g7KI+drHq/UQdNGlvnWpH+Q7xbJae6iA BzZJfWrpQY/dShjewUiw92/fd9prHalFJ2VnyaPgfu3pjqg7f/Hy4M9RG6YZ /FDtNXxjaYMTvGdjhdna4GCmAK/AKyqmHZt3rgqnYmguifHbCBOB8+MnmxNC Y7CiNmNx8nUV1nr2XAr4NI+iT0KPnNZdhYRY46mL29Ow4cGXD97KYyg6V2np J9cKp+2ODuZk/kLfxaPZpznG8D+jIjbNuj48Q1ufzhudh+if97mtubuQNnv9 cKVnEUYk38WHlyaQ03YxvSdvFuOzygpuaS5D3O99r12zm0HjWDQLFrfDo9jO lFRKGR7D1uOrV8fB/BR519EBRPWXIelLIsPwzKvNvZm1H29z7m86tGkQqzaF SsnebUKbwqYjDynDYJA2GXblRB9Usem92bzUjJTUIv6s2SZkYb2x1WjvACb5 HkklCFaig6XlZrNvPbAUYMDbzzmD36vKX5RTR+DtNF/YwPZuFDYmil1LKcd9 T45vstQdguKXzux3/mtEFskDRyX65vCmg6jNzuZFuJj21pT7Kgn8dO49Cqqb xk1VE7mVVrl45WLcZ/7OYXgbt9ms+8QYcDW7Rbp9oyHboLKmPks1lBL4jvwY 6UE1869lQdE5iKpmQQRCCYZWpF37r7UBDSKH6fskN/rNUfA6x/0Haiwyitx+ NoEnvPtPvPPqx4cmrUfcGGnI3ScfeulyMa6c7uxSk6CDUwr53v64RMhZ2Uof iOiHuOI9qvm1LETyqZqDB8dp8DPMkd1xmIR82ZdcML4dPIRX7GRiqFDuLNhY qz6MnEsS+7rT2nDk5zv2i3f7IXT3nkvHWAfBXfv7rws8fdiU+9VF93gR3vjU vzOlIwXWlG7cOUMoBFGh/F9O78h4/5tw539Sw3jCsvYjuLaCINdLFeukKbgX yTgYWNsKq802k7sth9FCxTzcp6AERgMyuvfxj+Ab7l8Wfx9lo4HOobyzEQNI PGHw1Ig7A5qtuZ3cNviILfT8op7JFMqcsmZ/9ZeCfedec/T+icBvCwz+bxiG 4fQnt9P3Gftwc53XHTbVLpgiVjxyTpnBNkO3XV+qY3Dn25/lHyIGUSiZTXWz dB/sUtzRtjuzD0SrX1wqkpyEBNuINjWWTFws7h7f86gNCk+y7czVbcZP94Ia NlNb8MBTUmzoaA5gR/tJ22/jwJrSqM2XUYgikQFRfkGhyHfpQ1hvyT+c3mG+ Y+LJRi50meuV+jWM+EYmz+TBCkhe93e+bURF2ppEMWfTEuhwXP7YI0FD2aZt Jl5dbaAcf968qpiKZD3xnFnhJgg3GWo6z4vIE54kd6epERniZH0fK03A/wBK 2pxp "]]}, {}}, {}, {}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{False, False}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{True, True}, {True, True}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{None, None}, {None, None}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotLabel->FormBox[ TemplateBox[{"\"\[Rho] : \"", RowBox[{"-", "0.5315755755755756`"}]}, "RowDefault"], TraditionalForm], PlotRange->{{-2.976544679659269, 2.7399779915460445`}, {-3.1541453613655737`, 3.375350296910904}}, 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], PointSize[Tiny], AbsoluteThickness[1.6], PointBox[CompressedData[" 1:eJwVl2cg1e8bxs2iMlKpRIhKKSGlJLdkVTIblBRFQklDSqlfRiWVzMjeQkZI 1n3svfc+jnOOzXE49vj7v/q+eV58n/t+ruv6XKJmtvrmLExMTEOsTEz//8o5 nEs2MV2GO5leRoSy73D8VBKtSpiG3d63vxBsJsHpVNNOF5Ub4GwY69R9lQja ecJqhcod4GW0NPpsKx0+nOyerZcsw0rv/b2BUatAme478eTuAm5gUufnrx/H J2o/+NUbZkBh+gVts+8svHEn3tNk9EEbmAuZbunB7yvfWQfPUoB73PGUhkMX movJpT2UH4K9L980+wZV4VDYo8BL0i1oypMy9MyhENmPyrbeM+6FsjtDQwmG E9A06bTrG6zCvGKHqlwtE4HxJ3pSP7UNWZNXU09MTgCp7BC/+3Ij3gJR6+gD U3jLUCNmWpND2eV5uqGIch9qdalX/N6VAyunzTptL47At/cVbMTFOSQsX8xf /fQGFmoe8VnsJoLf0kPV13f68ZVbml7QvVr0v3JMSXJ0EWg7Jl+r/SRAgOzy kudaM1CtzvJV8E8Cedji0d77GwhxVzZHnVaZQUvhGj1dnjp827zl0X/H+mC4 zt3xzEUWQs6wG1XHuRM1Hvxl9OaxEthz2QK5s2YgO+kk5wiQQcFhL4uM4TQY vDzBy/uLhIo7Refy6sfhvxM1RAEqG2Heer5uRXcaRq/mVtuLEtHbWsnzxRQB JN9skV5tb4CL36S0I7uHUaCH+/vxChqwH1p0OqbVArU0gYf8KVPQVilW2hHa j3lC5LeBJ0vQWPy+T/DRGXTXoehx7qbCcJbnoBY1G0u5f7Tv818DQRWODTdY y6FfJa3/g9UQnJvUU2QbnMco9eL7P8KagPsL3/R0Qxvk9fZI7pWdxPJ//Ref TtVDvHDTNdd0Cl6XmTTpS61FmSsm9YZ+dKgCURYHoW54USQXwFM9Dl4Cm5Nj 2SdRfIfPTHhWO2hLhM24XV2GJ8FXwcprChU2hd9K803A/ACnrX+GfmN9U3Oe xLZADDvaYm8w3wVbA8arZM8P4xHXwrrOU1SQUlsTkHvVCQ5O1OoLegFgYRbO R3mwikzKHVuVns+DWtD5Y3fqp7HAgbdji/sQ8BwKZE97WA9GzyzviT+ah4ZH e/X4Hi0DTWQf14fvcXg46pB+Kc8UavN31nnodqJd1W65OxLJOKlrq7zpKAUT XyW+LYiKx/4Z9irnTgpMwsOjG2P7oV4ygklMoRP6rwRuWL5QgzYPh+fpgwxo k7Yts/3ZBUH9m/Pa/nZAHFb2WlUOoMh/aeJXz03BH0F+n/wCBtQke7rsPcFC kFDOWAyVI+LNm/UV54No6GV/w3cluBPuWY//bk7sxFe39wiHSLEo5/urzPlW VaL4DzP5zRcomJY+93QLLwOXBT95RJoMwfJNquQqVOGtbaTSS9d6sP+SKHvB 5WnI9TDwVe6ch6z7azaKc1NoR4n7xdm6rvs1c8bnP2Nw+habUd7tRkx5lv1D 1L4D2oNmpY1PFKDqHqWZ2LFmoG+Z8iB9Zlb+L+L5GpmNhgGf7F6+u8RKuF/1 8tUOyQl8olWl2EguQMoL/8Ez83SIcZyzqHCeBJvj73r72Bl4zKEwfCMvHYns oo7zAxNwY3/stVbpBhiKpV49cmwM04uynjZvqUP6GUvRhyI9YDwVaAo5DDjR l6ZeoVGHxea5P20J3Uiw273plhcNBYptyiZuMMAtl/S2i38aHnySVlFZHQGb N7e5HvNEoNt/7w9/bEyF7dvE2DvdiagKewdlMtvA/bFE3fErExBrXneGTX0c 99l+pLVtYGAC/w7DcpUKhIH01e8np3DIL+tFx40B3LKWK8Z9qRnSiha4Czyi YLf/wbxremNIp109KuKxCFTH1+Zb2oewIdfB7sPTZeRoKz5IfV8GojQlm9Pq mcjiJnpVs+IvCGt5cM5uHYDggLxkBSYiNhR8u7vzvzbM2PKnoO7fIgpttbzp 82EMtRRSYxXSC+BABe7aHs6ifIvzc0O7YCsmMKQCEpJHcLsdl9o7bSpa/OOW iMYOcJXr+WTbuohPLZbCBZd78X4W640LTMNY+jViYmf3CP7ZkV3GrzmDZ2sq ry+LL8KG65u2iRZOw2+LBO188hQKlO9VbtrXBz/Pv7kju7SMS9+WZCKa+vDi 9Yef8t9Og8TvhxqKvrkwsNfGKIuQhWyB579eGh6GtQSPGkphBV6RPRP5BZiV rxiGnjk6MI+TG3MYBXYd0P01h8WoeBnlcj0FDfN6YIlJ5XDN6BDu+h6TxqbV gEpc/uIJKTXYdeDis7hWGhTvt5UM2DwAaExKeeQ0jnd4Putc2kyH/tNWLK92 T8FPWbHuLt9R2G1lsVPbiogJZyzqKCzLYCI277p0qgmNZM+nfmgfBRnHk9Uu PXTIaS3Jus1KwwOJkV8vlxXBY9sT6aY/iXiVQBJ6rDkKDe57NXhvjOKtPJ7z 1MfMytX/HaC5qjHgq/RhqynHTmzbWdPDJzIDdufEg9yKuzBGnxRraVuPq1uO SklJNcC1RvnDqmnT4KSffc2hiISXtHuVvJX8gReyRGLvZyH/e1bNzCQaXjT/ dK3FrB2UsPNjTsoqPBw7K3NTg4YrNxNety/EA0HwjFyXw0aCYoxD8o5rw2gT OvK1q5IGR/hImxuOr2Cr8GiJxUkiZLK9546VaID6Hy9UMnL+ALOddtzBQzmg 9eDnhRLCLwzYFmuf/4UEXFV3THevzsA/XZsXuwIpKBPo/TLj7Tg85eg/rryx A1+f2y20UZmEk8Mvj0VadMHy6xNOLe3rur6eK2q5cR4u37BxzsqfgdzFRwVn 1adwoJt6edKJjBlqrvGb9bqx7gP999vfHXC4MZzpVPcM1F4yCVj53Ygn3VzJ +4UY4GPcwfR6tQaYz6cbpLF2gYGV29Yj35vwn77ooLxRHWSWHuOafzkJyRe3 3ru7lokqlMfVWxqpkEX5uTy7sxgPVVfvdBnrQ0V77o+sRSt4z/fipj//upH7 lrnZ18NF+FmiR02Zn4p/it67HNxYCc/ehyby2PbAn+h2fQPBf+g8FyVEDhzA ex1ZqH10I8H6Ot8T5ZQh4LxwKLbjyTQMD7hzNlxfBIPJoLtTPxdQQYq9juAw C8kWLz9WKVJg8ZWtk8x4PbAa/w3v+TkOvIP3m8/mkXEm96nFxhUKMtnvTRe9 k4316apjW5mHkGv3TXm/w0s4ORj89F5QP956rT5j8rgS/557OkLeMo88pMSz C8ajwHK8Yqdj8yQuN4fOW/HRwMeyiGkbhUn5nc1Zvr8eniilx/B/R2KAWYRL SdTdZbS8m7+DiakL869Yub6T60Ve3UdjiZ+moJH0p6uhbhZ8Xkb/665kJtBy VlTNVLYoE11arM/6haEh013tue1zKCQ6NXJdbBqenen0XEY6xsjnGD8Z7UEd ZqcrUaaTWFBAvS4i2w3ET+LvZrZ0g4Cl4RVdjkrQGZ+Q4R34Bw9bn8Syejah WbqX/ZH4SHjid3ea0dEKbv/2nzRfJOGU6eqdmUcLSBc9cT6EVoShEv/K3sj0 Y8j9LvlzRmHr586amr6noqpl9ttAgUY8QK1YFTYug3MVmgPSR+jo02YVMFbT BPn5DgPlmAqrAuW3LnykQXKt4Nnz79bfx/tLznTNHnSpmEkmPytFy3Lx2kVd JuU3jLrnplozuONUhgI7fwOStv4M/ZgyivuHXtyT2EEGHZPcPJdPs+j3t65H j68BHrBfG325hwbReuNF/RZjIDcTEF5oVojPv5BnnQvJEJDy+1XeKgOYKDaP 9hcsoOXPSCr/3DS2KB3euCpTjh+e/e4tim6Hx5OCDBNiEbY+JLD5HBtEHstf N12556BnaaX/2C0WwkOeGNrva9O4tBIW0qLHpJxyWuF7R9YitruHPNodSAUz wStf/TUo0Nl5/uLkx0U0j+QJH/Ijw2Y5YpTeoUkcq+9cZMkYx4rLJ/Y4jkwA KudkhAU14s5gNf479AG4YtOgbMdYQNV9gn2Gfn0wMmp1/JFqHarlB27/6TmB WneTFuSMCuBQH3Ce8U/BINXxk7udRpGrxEuqht4LNy+H5zSaLoGP25t6QgkR BA3PPh7ZW4WxcaZ+iRpD4Mu0g1/taBsElV+hrjkk454jmalN7jSsbqjSYV6Z AE4rXzbb9bw7UWSlVPi2Cw6o+doOa/iAf1iDhZZhC7arfrFv71gFn/067FWH hrFhdUWDf3AUtx94eJxpdxiysgU7z682o53I6XRBTyJG6quNvF3nU5OzRXv6 FvNQ0tzxPu0iA3bF9Yo63Z1Av9djXknjvaA28OX7Zu1h+PWTaXeI2Qh83YVa VQ8nMPbkcdtanAaj0Prk74oLGLQYbpx3qAQizU2NH0yQ0HnhgvX2D1Ogcnba tfcTFUkef68slY3B7V5x3g6NGXS69lLnyc5BHNPhe7zm0waULBMm8dIRFEj8 c+xbNQmc9N7NtHPNwbeP8383vSJDqNszHYLcHJSVne7h/T2LO5+4lr0KbYdZ la8qvqYl+M1YxErXdhKp6Vzy8T3DePdh/xlbg35UTdBOGasdwS/CPuWF42SI dfrZO9k6jxPF2k7fHjZgac8mWqMECeJa69VSEvqR8aW6NLmtBm6ZRdGPqU/i otdZq5PZqUAKnK20+8pEGLXSajM3pUCGoNRTVeNSvP7w/KQhdQi1ncakFIqr YClY+fl3n3zwePtLZk73F6gqOW92tSwHWVGucpZPGUiUvcBWxUKD7VN126lb k+BgYtUtOz4GHH5rTO19ts4v4UGvmSIY4G6n9i13rgVOfN3bdbx4Hkz6/G/z vmpHmRyZLU8bqvBH6u3xueb1fSx7Gw/lp2Ln259bjfZN4j+q8dld7j0wte/p dNxbAn6o6tW3MaBiua+1abD2EnAJbnWoDJyHYPpR8S73QdhVS9l72JmCXFlD KnT6FB50G3s6sLMWNrGonmY36wbqdn+mGzkUHHrVuif5ey/4dJp/8Hw7DxVp CatbBCdAP5Ibg4qGwT1OU8DUuAVDclWIwmxLcNbXio/VOg3Hz2x4vbVsFjey uZy47DUAzaHn5T3b+9FX11uVnb8FvjoIkLk8Sdg64qYTZkBEjl8xhn8iq/Bt 0Hspv/xeGH5IO6kWMgKURoZdSJw/ZF4zXrr+qRzDrEvD2L0HgId28/Z7QQq6 521tqJem4F81m7nngd3gfYf796QfGY/z5jF8ZhkY+umQbVRCK25/oLe4YbUR +Tevlf7V+Im3fMW3VXbEo92UrZLrsVzslG+Wf2Q3CZPh22QO+3XBvJrQeIB8 P/48+v2Za8gSbLrkebpOkga6QkOztZM0vOaq0UYYagWOKi2SlPQgHBaNpLp9 mwC5J2pP2Rmx0D9oXXboDRn7Y9LvzVo0w2t74sBUZh1KLlq/Hnyz3gO2bY4V Zi2GnVcX1eJSGChrovt02mUU+msj9/UGElBc5JA9652PKMGXN6rxpB27bsUm p/yhrM9PNW6j0Bh2r6PWF8UlJF3OaPnwYRQsDTc3+8tQUOMitZkiMQo9RP73 lwMYqHBTS5JTmIaPKSn2z+w7cKLlg2+z1AQcKNs/MGmyro/yj0zTpyh4sL6L zT2NCh3xlq7MEgxMzLDbosxEhHwmPtkdgitIVDpDZ6kZg0Dvk2P7bg6gVudF lV/7xmFkM7NjbdgYuG/iC/0vuh3PtNbw/nd8DFWYww9LFJGh6FMv8q9m40Cy zEmePzMgUWm05vrdD3JvXxF385jEjZ6PLTdu6ASOJM7xZPtxNMqrtN5Gm8Hx yEtHf2o04DR3g8DD/2pAhvNGrBG5H1Ij6Od4ykcwLuBiy0jNMgzfUTpcz05D Ptnl7aEPKKgo9TLbbLQKgnoYzsoCfSh06lCV8+cWTMjMnA416sXAM67jGiy5 cLiUXWZBi4pcXVz3GtYaoPfZVt2lziQom73+9m8Kk/KTBjiudbYVt42cGeAO 70Dn3XF+XhYshISbB067vxiCvjcnr/cID+Bzvj8tsWs1+PEbeR+v6QBKNy7e LREegMoAg44YsxjUZJ4m52U2w+1N/C977xWDytSA77d1Py1/stvcWG4FnhOZ vbKuUoD+LppffsM0irve7DipQcKrj67cmhgdxWcOw0fM1wqAP4PwgFJMwq2u nzdzfieiZT/bUGjND1ST041Kuj6GzLIMc7b1HF7Iv2NmRJ9Hf39XjgjTGXRU W8uOGZrFJ10GPwT+LcCVMy0DsYMd4GelfsVKoxXebpCd/SGdg9fDyx+ea62H wCKhw+JeFbCc6LI57jQFhymnt98iTGDQQqep+c8GHPvIcuX7q3rQKQi6f9Zq Go/GLqtZZ/Yjk8gB9YsXF+BrcPrFm40rIHu+isg6MIN+VpHd5ZfG0L32pqij 2AjseDqb8M53Ai84Dp64kECCwf1Ocps+DaNUc/9Hw+k+ENqV1nnNqwwUz24J OUeqxyeKt1/EredW2KPKOyrMiF9HSsk6kQU4LkKRJUrOI/vXvqjxNDqGHRGW LvmvB5Ijky85RsVDi8fld0+dh/HE0peA+vZpXLCxf5dkNgMZnc5FZJkSkLqO DdItRLgyMl/j+JQKa8KbM3mPDuK4cMKJSNUp2Pny9VJARjtw7bpT0pQxDWwv o4btVdvQRiDNzsNhGoe8B8su7apf5+dBufmhaZiP+2NreG0M7LKE/m6/uoAp 1kFKxlxj8P6d4viFbSuwPL61wLymBXuVewP8WRmQIpAsmhyeCb9djD+lnhnA iXcUFedTa+D+1+9b1Y9yVOBJt3Y4Mw9/W8PFadxD4PNZ3M8DiJg4+0LdJZOC 3N2GE0EJk2BLKE+I4ZqHjDktD5IfEQfbXrh9mOzFKL23CYpZa7jxwpE+HrNB LMzbGcPr3onBe8pX5bgG8O7WQ6bfTy7AlyAaV7YpHb2mTgjyRw+hbf17N7eE BtgsvzRkdICI+9VKDEUfkJG/x8wi710LnMtUVay6PQ1vuJxL3w00obxemblc UhXybxKb+HavD3zzjB9dN55C7qOvTbunWuH5aOhIg+YUPPLzPnmcSIFCoQcu HA3TqLUYI1YzUAnJuhty509RcYg8cyl4/zjIbj5nrVA8ile5a8bokUTIbiiW aG2Zgm7/xpdUi3i0mXpp+zN9Hg9cQc1xpxW43mUYMSQVh69WXupyK+bg95oH 5bwfm8GGfF+u5isJS90/3RSLGkQV7umrbwcImPx2SG1jxDR0PdLVCG/tBv2x XRxSfqkYEiLgutJbCn+8f0S23u+HUev4nCjSIlZmWQZLNeSjHO1ozEemQZx5 vFqZZTQHVr3c7w0HV1DnKDF47FgUhJ2I2FFMpIJuEEdOajQdZHVlNTTHRqB9 /7xUgmMGiHP5K7MfYiHs2unwW4lYDWpZr6OEQpiUPd0tLcpCx7H1hLKM/8cO vHh2p0Dr73kIkuxayvaio8vIWzaaZyQWZvxqUE7tgKU7mobR671dhEy6U8Gz /p96rJ2bVUbgRt/slr51nx/5VBHBETuBI6Wftf/5d8H1+8Uc0oRhDLx0rV2f MgMvWu03/bo/DofSih6sBDATBsVbc+WKB3CGtTQ4rX4E61vY/sBwCaz80pt5 8YWI+0JPBCnbMPDIOc78yph2XFR2UHE2rgCz2xEzdrMjYNd5e0Hk6jD8Fy9r mMSyANu1apQEh+rhlJrTns/7WkCxVDQh/BsDvA+wV1fvGEL/O0p2evMl+Pcl T4QfTwO4cB/z7Ur+jdk8Ly5eoI3C+5iANC87f5TdqZem5DMDvB7kXj76KjAV mkc0dDMRNk9nqo4bDOCD02e4splowBCSXw3JzEDKkyPX6/wGYOi46JzoLX8Y Zk0g7DlZgvRy+xRW3UKQFegumlYrwbv0xqNEXhpqxsj/c1mMA+fX/urCMmT8 +Wtm7rjwEDT8y7t6ooiJsFehjHNr9gxwpZXX3jv3B8aey9bt/FmOmcbJiSv6 I9BKbT4yrF+K7d6q9CoFEoblpAv3fEtA1xaFINmbaWByxHUS6kbQ2cClIK+E igTZYy4D1zuQayp7KEZkCLk5py8NH6JD2+OYqKcj3WC4h/41e2wW9Y6WXIk4 PINf/em+d/6Woc/5fTxsnSyEj4W6VzvrSRgk8udlMH0CQ+2b2NaExqC0dkdA 2iMaOIn8JzGFRdjgKqLZYjiMCSXdand6ZlBeWoNHiDoKf0TiHpnfpSNJ/rl/ MlcP/nJlCSFbdEGsRLRag7M+elBrOMbaukE85T6v4zEq3LkoVp3s9QYK9xar lE/MgtV4+c2hsHVfKjxmf9WrBN/an0+UPjUMDtpbjhD8lyB5MUfkI70J317c 2JL8YRwlLuDP6sMsyn9nj4UdlETkCy4hp8uSsKghPl+gahb33NvfFqTeDJwb m83uvS+H3ZnakeLNqzi+6bLp5itTmKv3g+6VMwAs6XeKwnVIaO0pGTiUtQDV +z2XOxWYlT0tuJ958fZg7edWwehtPeDmZ73RSmY9p/998he6OAS3GqW1nz8i 4/2oMUG+C2twJG93kgRrOqiJfe1sCBrFCG2XyXdPadD7u7F8G9so3hWzWAs6 3QjG7wyH065MQ3GkDYdLWCeIcy6nxbxYgtW91+cWzxXhgVSbf1qPSXhfeWNA nH4Dps/JuY6fK8b9KLbN/9sS6PqxkCfXfUkvF7e8MJtAN1k7cb8YGipPCVnt FMpGg71als+Jc0hbLviRrzKF8Y5atuqpLbBru8hISToF2bKibjDzNEGuvt1B Z7F+/Lox7iur0RT4njq1g3SJiq2iRxs/CPfDbwXfUO4bM1h5g/aMr2YaNbsY XU4OizBy/IPp7vQI5NIIOmPCQcCOvDUv38Fa2Ovzp2/p/gKy3m8uzImOgLNa gf02npX44BYpmS0wGrT5C6eLUpfx1Ekt809LI6hvR1Whqk5Cfrb8t9HuRji5 36Lk2etSFP1kWPE4jQYDk1pPJK+tYVv0SvmrkWLYTzz9vvtoOx44oERy8S2D PKJfwuvfNPhvKSmVaa0ZWof9ZmRz13mPbdKCIbmBoLHJR2B5zxBMd+/ax1tP wVWx6FdxZ/qQX27exDahFVxZxhMusCUix6280FLXVth3NfeCB3kBFVaDth4K msJBzpRvv4aIqLPZO/76wTnwuXDHWLh2FFJ6o/nOVpSisixF7KVtJ7Ay3X1P 0JmFtAMvjSRC6ci4r7RrsGwevQ6JNOxV78eEvbLeVc0UUP1dfuTJfQrWJpzj MVykomRL0zN9n3nQm2Eb1aUUYhk7bb7+biuc7n29w3JtAHQeFGiPppRheHuB vOP7EtQXjy/JdSFiyx69GKEEOr6Lvc7rdt4M+vYNy596Ww1sp5+tbewtQEp4 bNU8RywGZYe+iK3qxHyle8n32YcxX7hYnIc4DB+lXl5aYOvA7AdVgtmkboiV /nNLgLceBT5aWLKIDeFViO46+jMPvw38bPGRIiFv/DOdnIIxxCsPFHsG6TDT /8Hpl+UoSLYEilqepyNhH+/vrF1uoPqzrndWrxfEdTR4b74ZQL/AwGe1JpOw y+x5wDdTFmXeQvU95RcjcHwnsJzL7gezivD7qaEZAPUNkYNvyLA7gsq8X3AI +fdQuzyk6WiXyHANTx5EqpfmrZduA0CrORR4fHIEqwlv4zdsmoDSk0hgf9AI +SrdVea3F0DgY/idmhcreHzyp3xxmidE3RZdHqNE4P6aUImI/cVY5KKzTVi3 EslVcw5b1lqA9ZdIW8f4GvJdGpI9ZDkM41xqfM4ZDHhnz5Haz0YHb74G5oxN q/gv9l6utaoHSJCmusCIVbnKvIFnbHIUjYQ9JL6vFKGmJJfJEyEqMiWSG0P3 JaBu4WalhPY/8EpggJK5vxOriWfZJgrGoVKzfuTGbgaw6YcJ+OSv51q2c8+Z qnG8Jzxlnh3XiPPOg5u2xs/AnfpzIt35Meh1YLdxUAgZv77R5RYKomH1nqgm qhcdvhyy2Di2bwpQvqvwVMMcvqCpdpJn2jCw7uX57Sml+OHaVsu3l4igxz7b YP2xH+98Fkr08urFN4LxcekSVJifarXKfEEHsW1vUjrXc7v5dYrESZZyiOuJ Y9ORGcFO2cdhV0gUPNKn13t/yyi2iRgILuwaBOH4orR+i1V8a7R79S4nFS+d +kO2LS9A/9BJPtXYQfyhfizrUksLvjSTJsUSgsA9KVPgb3gnvrr//kycxzyO RRZUPXg/DQJiWx9fyOnGU8LFRVk8tXDXHtmkxZsw+UP4/id6LSgWn/R4PnQS H7KaXjxvXY3mDVq/Km73g1KOc63NhxzI4LvtskeMiTD0uefFGLUZcymL4cOh 88Bg4vT+85uJoPtywaPrzBCEMwbdJw3Gcatm5PiRkQF0N7TYwdO7AMdiXuhl jsUBT8dgj/mDKbT0GqAdIhDRKAyOfpcYhw9jyTbzD5oQVXS+BGi2wqHQ8N3n /q4Ak+cm5Tn/cRRTURQ/7NUO1069yY6Oi4IzFEpFp8AcvJeZPuSeTMaD1dH1 fmyz0K7xm+d3UyyaijFbdlS0g1Kn3tWd8TV4hcIx78NORUE2lbcXDcZAXD/+ itXxceD3nn++UD2OO31pXlzLrTDyZuuC27c5fP73sODJByRExbBdxN5JzEur Ne40a0A3eSfFs6zDwJHWnzInNonbY7mcH78qgid6HkRmv1HUzLJ8+HULFa58 PPw0S28GRfLyGqVZmJSVq74JF18mgWe678e24Tk4xnPakZkYiYrJwFEi3YWc waIJm9WnYcUlwl54bmq9l/uayz5bgmo1Z8GHOkP4UjLzUX3NIFz9EX+9umMN +Ie37krhmwb7eGFB3r3dWP0xVG8/iQqUFbW5NTES5M0+IJe7LsM0++XDDWw9 OCySKxz7iQ5MjwOsNL8fhobfcZzCG+uhaLpo0VSICgpjpPNb7AkAb2YJrueb cJ6Pe2LxKw0PKdIVbq7zscmhLc6xjXMg7X/2MzUwEV+5XZ3avZ+MmloJUWsa /1A56oow6+Tien8KetVvFY+u08miO9OH0GjwYtFbt1Hk+2Y+/k2WVTkiYNna 7fMCjlbsua66PRrfK9zVP1bJRHi+J/z02woK+Pu4Rb54V45+shtMzNVbUd15 j83bC/m4kjdwntVvClVWGNT51wNwMJ4lCV1K8UDcDtZk9xa4q873ICM1G+S3 l1FPN8/iYPXmgvAxGmhe+Op2d7YEOo+MpSnaUnHHk6e9xo+KIdondneT1RrG PR+MTQ2rgo/u3OLEz50w84jZ76DuADi1cH1PsRyHKHndooaQbAzqWdqY/aQO L7UJBibHTGH6LvNQu5EMTPMTPMH+bxANLm757hHKgN4x916zuBHMO13JRxIa gqy6JBaj6my0zDfmLW9vxOWkb8NZL0vBR2zTgEpKBhYLb77zrbMeppiqsh4e JWPAB80NVco0WDESDHhXQ8OZXh4WtMtDHWeOtg2hdGDlbZ7qjC/AvyEsX8j9 maCke531mgwVD5vpBS3br8AP3ZqjL4zS0buMyPz+CxnDHAcKLLALGljsz8x8 mMPmxxUBireIGMG8ppmg3oNbWni8RM04lC0rLyabJPxFEZW9Df3CTISUQ+N8 je/+APmyW2aVYxP+N1n7W1V4Anh57Zi+ek/g062uvS3sLWjPeltE1JMO2SEB ++khHTjSmVHpocCkXGR49ll2xQw+cGXtDNMmgka4Oc2otB7sdhq3zRyl4Jq2 pmcLcRCULMPZhBhEiEr3e1NhwQBlhaslQJrBHv9cZpMXPfCIU9s2RHEVglFY pbp0FgVIZZ1nrvSCyMOxmAOPB8GD3dHW7RYNb0Y/TiB0U2Bfk+rpdhcSLt73 /M+CYxDTZa7ub2Pth/nnCYUa1c0gF1CozOLJwKgfFaP7LGaQu0g/drfGDJDl o//V9/fCNiXSbYZeIxbd20389ysFurg73IRf9ePIda/4cqdhoOX3WXCYdOBU VVW3Ul0u0lXnOhm5s3Cg6JA8bd8wPk7wPr//4hiyFrhz93KXgXq17bf0ODL8 sAu+ackzhIk1L44EsA/hjWLRQzqX6yFvMiMsOXgAbxx7fv5f+hjOjxQZlCTV QcwZuXHZbUXA8N+mVT+fgDJ5zldyXZmUIwfWFtSamQheD2xdA/iGQC6wkvSB vwkoLjLRoieawCoii9vHnoZyg9OfJpXmcELCb+NF9yWofWZSkOU7CaV/JRyM g8fhTFUVV3L4Kh64P2L44UQpPt6vX/bHdQ2K6H3SjqqjmHDae8+lY7m4VSXC h0+7COXY+J0TAyioQG7mJLjRkeWgrntZWiEq+h3Jqd0+hG5/4yJ7whaQx11r KPcVq3Jw5857yyHDkEkpWmz1boPwP7PQYNmGN5V4z1InySB3zC3/LGcPxD2w 6fxb3oJ/gq2tl7tzoCoqeB/Zph5jDpa3ZV95hvE6taW2PdUwErRR9K/DEErI vfnu7D0BCueEjo4cpIOQe3b/ZvZBmKhjjM+NDcD6krvPrjIr27YRk/C/db0c qkq5caUPyj5rFbubVGJSXTPTiFYP6vk/DWFxJAHH3roLyxbzeM4tcJG3ohhb pqyaAhkLMDvNJciWWA55VPGS2TsUuK7JFNrZ1wbvKv5pxNo0gduj8dSE//Pp crDuNYn13hdlc3B0qgkcWvR3z6/zzDfn/Tpl69zY9u6f5vIrIiR/nn23XacB ORMHJJMvTcLX6SCWzg4G2vG5yFambFQekTyodCq0G0uJhy02sU3hUKI/ff4g C0HDs2O/+vlVMH3tYbhh8wjmCnzzLr/Tgpn/dvzSd5uCKON73Qef0HG5fahE 6zIRpbzZuB47jMGjfI8dOTfqUXfo/hEtjy4o7ebPzn1dgLeP/Wi06yGC3eZX 5dOzrTD1+uCOJ7NTKPFAXXLv2Xl0fmO/WZrRjxFMhxMdOX5BePCGl6kqTIRU i678/aF9EJ/98M7F4kVUDdCzDDg6C0cUc4YnGfmQW1q8syKGitxNLw7f+zEL Onl7Zf00xyDRo7diUjcXX5k/unyraxY676WyjItQkb3mxsNLjBYw61EaLzCk 4J/ZH9r7FIj4StRosfrGCPRl/CI1mIyCe0bIjHROIQrTZZ/SHRrxuGAzs/kg EcuYKiMsHBYwm633i4nuCN51cLFwImSjX4vse6vCGJyMNXgv898YtiktXFpU 6wehtcFnvs0NEOpMD0genAPvkUib0iQyPEkcfsKon4LsPOGjgtXDOMI0hU+9 B1Bq6x+XkfV5C/RPDpBnaLi519wi70QtvIwe2PNcfBSEjKM6Q1YGgfmowtWI umq4w06z5LCgoLT25JFM90Y8pbeLal07AXZsIqlxkwzYYpVorxTXi80Tcoys 48MYeDbwUil7J35vd7152WUWBFL9pgurB/BhyIGx++MZsPwkx9tovV/+MLub Jx2xiN/fKzVFrTCw3DHf7N2mQZCylJJL/PcXFCfamX/9YiJcO86uRBqtwy6Z 3DtNcojNF8eEzXh64OuD5YrBHVXwn8Zpt7q0RRC8/JSH7UgflmeWulTz0vFa zLKjlS4FSsz7OCSjyXBuA7lfcmEYyh3+xBXMpMKso3Gqtx0ZXlcMmbu9qARm Sa7Vsdgx9JT1avJXn8ISgf+ebZqZB/PQTuU2UjO2+u7vfLpERya3U7orD2mo tJ8iQGCMYC+Qdd/UsisXfhc5cie4Gf8uXj1zODcehf5rVj1p3Y9aK3aH3m3t gyv8gt5tLKPILCbjy8bcgcN4/VX24wGw7npSmd5AgwxWIUEn7U2E378iV4tE pzD/879Nd48OYO2G7m5d7zlo8qMbK1YyKScm3bb9rNwBmrSgH/fUa7EhtMV7 uqMTeQS0jcR2/8G7zK8Z1hX9kC89tvOgVyS+5PvSbFc+BZPXGzWX/ctx9Vy6 T05WF6YHjB3I7W7C755RHjb9dCQt+N84w5YDUbot3XV3Z/Fe/WUOWXI9iqFC Z7z2DCROnBH6cLMH47rMvIS+UpEYkasXcywLQ33eZ2ha52Di2zdcwp8mITap pbWHMg3b5Qdon/0KgfvGFsIjGxJOUlmnx093wKeZpmD3pmF4zLL3pFnuCLz/ 7fGx0aYHCxssAzSG2lAyQ//tosgsRs1r1bpxTwD/Z74f/ZoN6GX8jN7jsIjb usTDrq6G4fG7vxxFqBTc/MPq0oOFWaD82CZ/PpyORUyBZ2aP08BngBU3yA4h j5lK0qeoZjC4/yxoPjAT2BmC5DOf/oKWDNeqp/wQuNUdsxAxb8TL/U+WJD2H kcPCOvClYAMK7t/yX217DuoFVz0TEB7DuD+Rqz/X/sI2DrYCtz0kUI/kvBwy 2ID79Ztljx1ewzbzCjvvgjlUdjCPJvixEMaKfni8Dp+DmwMTySpxc/j093Cm +I1VPCETnZ1a9Bd2NjhI3s2Zxwg1kTPS9/rAcb8N/8bvRAh5qXpTwJ6Z0Os9 /66cg1X5tJb7pSSzFrxQFjPMGt0NTz4wvhcZ/sXtupMK1znbUNA8a6WCGAed Rs97vPUHsFrG6bRkdRs4yAg5YbEvBJA+Rok+moM3PoZtMo874W6ZpocDnYFl WpKBjUwdOPttiSI4Pon3hpJiJIX7YGJjWZHBOzJEZxrFddm0wmnb+4pvzpFh 8bKM2NRhElzSTztcspiJm3d1SuvGZUJ9+C1z6cOInoqyh4ueDsN3pcv235Rr cepd8LgCTxtuWTJ9UzkzA5MFZ224useREuXENCfXjAKWXW42dxvhccsHm9+J g5jMvVQV1j+DojY7PnDdLYHKQtPMtqtRaL/wjDL9kYbP9qr5pbl1gYXiSEiB AQXDPeJei1zuQPhv+1jcqwVwV1DfuCduAZ0tUyW0+BlgayR97cGBfgxeWrjb GcNA8edyRc2kVmhw9PezVW3CucXrnoQJMhb9M9t6W4xVeXs64Xyf+wqSZhJV svgK4RY7T3dGcQZ0+U/HBPn0I133y8szPKloOzAuu2rWBQoyorLkvdHo0nps x6L3ADD1dW2PU54Fe+4++RfZRGRj7zxrw96GCoZZSpFnBlG7SfCMdhYJSRFO Cf+t63lTqJel/nqfF9/R3PXs8TrfSVKJgj7zeEZEgrdRioGdxTs2BXTQQf8A Y+/I0y4o69api08qhUlrraxtOjMo9mv6ea8vG4EJ2d0urw2hadC7uLOps8CV kh168uJg/tVc7ksGsasglVRcncndizuKG7ezUaqA/NzmgXjsug+yVJ/aPlgL 5pf3cJV0j0Jp4RFdWwYdusniTwVjFlFGf4cJ560+eMLytoB6YQJffPzIOMk2 jcaLF+wUt09DzhmvEqf0dT+8RBaIlutA7tFXU98C+sHbl/65qaQfgCvBzmYX Hc9/kJ7ka5+BFrX5mBHHASxQsOHRGZ5CZafO1fdu9hA9WXBH4zIdIPblJfO3 a0jjaHoYLEeDbMbThkzNWrx8xSrmdnA7eAe71Iz8GoBc0wiBs1/6IWK0mZDr No1XP5qfqdCj4NWpV3ssWKfhCNNua8nZ9vW+nXXs9L9peBpYVitKXEV9e2ri hZ0kUNr23GfbwRaUEtZ82hU2jrb58/J+aU3APCqp7/CdhFT5EKlyeTJ4ferZ oHVoHuIOdzb7KnxHj4s8a13c41jyuSnNkKMPf1ruOP5oRxvu+HAHrm2bwv5f tvrnpkvAbi7c5WFzBTK/bvYdtWIn3Ok0UDiQ0g+G7gFG1S/JsLLE68T6dGB9 3vk3sr51wz0oM1AwGMb/+BffXhqkgNRtq1eNUmSQTlA4tWe2Hx4sNETZ8LRj 5N9PaoNKkzAt4/pM3yIIfnUQh0y6aLC4y432yrkP3glpjnu43ge/XbdChR7Q cNnzRcfhs9NwLO/0YXcjArbbOe71S5yDuLr2vMQf0/DhtwBBmjSNhNscV7cn DsI83DeaLi4Ay4oEliNSC0CdUhOO2TWLTyt/dx/QYSfwbDxl4OfUD2OxBhUp B4pQKzL9RAUwKbN/Ib/7HcJM6DjSxRJypR7yz/N8tds1BLMni1wu5xFBvNPm leIoEflCd0R2BPYi6ViTfdKVJZQ+eJRp59YU+DVoJ/mzeHTdP9oFBoeIUDmx 7x4xjQQSTK0ab9TH4cfnCf8XFCo00zaJFD4gwaHDCxfSdhDRY/ItpDO3IUlU 7pedfRmmSys0W+oQUYmZr/QgWyzKn85LsuQbhrnJsyqEoXo40pUoUTI4ipbN fZEHY5iUmUZ5ZYMXFzHWTCHsTkg6Wo3ZPM79TME38lzmB1z6sDZosIpl1zge 3fJZ4+96fgbnbtsWdWEGI7l2ndEPzIE3ZqzaxC39aPMFs8RvDoFhaSPp3/FC 8Bl7P1F18jfYe3/ZVuw0ioXBT9ir05dAsI5z7qLnMkaf35m04z2LskS0zwup zwxUczVi3yBMg/qZBAXf+L/Q8KHoZoFyD2zqF8/XFqNh9d5bq5yKdHCT/iF0 SGMa68zZpXKn3kAiU35YdAoRhm8dLijzmcK499NNhe4jkO/Hcpe0rR9NJjfp d7BMwJFZ9RwJnkXI+utZOveSjLFEWrLf6hya3uQM2Ke5AEMQTHLTbFv355MK 6apDqDlc3MNylgRNf+3csg4wsO+ckJZ1IwmHwsS3nQikgco+7qg3bAygCTsF 769swQ38ov+sA+egd3RuWW/PND4y5q9a5p6Bk2u0fGn2duzavCnZjr0KronK NLCUsCsv3CtNZnqyDOrzR/hldUaRh4Up0t2uF5djhYzG9gUDCktKCWhNwZTA Ue8LpeyEw7cuGstGNyNny0srwU8VuIOhy6n/pAM6MzJsByymwXFGzP2zXh8e 0iAwtbRTYXfGal/VFiZlr9/k3IcWE8iZ4QX+kZNok8GXetKzG6LPjf9nNsdG uD7saMnNTsQter8eaGtRUPYkJAsYTaNZfe/OV9en0aKkI4dHswNYLC8PF5V1 gEnbnMKzfUTo8MkNu/+2G4YeNX6umFsE31DhpZvr3ELPf9GmxTeAEY+ss398 p2Eafdsal+gc7nt/vDEpYAHuUCc36GQlgn+gtuOeahKGcafoHmILxa/Rm/Sz LyFM/PheEnOmE5PfBd08/20YRXT0LNlUnkE+yeSp6uY5/Nhx3N/nXB02q494 Py4sQQ+7BK/rF2cw877tdDtvB1yrrJXLT1+GVzaM6zqkPvzVdzNrjj4MHqZi BRXX6MiqM+VZqzONnJc9hvskCkC9lUbeHtqM/5aPUrJPjIDZ9j2fnUUKsGPS X8opvAy9ii5W3ftXs76ntdSNBdP4Q9Lodt3BeXw8QRs9ojGPWiIhZgShAaDe +l6yiZMOOvLmgvZAR22+x9YSBhWoXvqRe9u/KUjYuVNMkpACpbW2zKrmJPQ4 m2DWuYsBP1iSckR+JuLjpeytGfMdGKH+of25WiPsjr3pcO1UO269O3Qg9OEk HmETynG93QAR1oXFJ2NjkMIXREnypWMkc5jjzx0LYC5m/fOvNhFTR5PmZB5R MZO/8OLiZQaUfkzet3SwHsLOGHw+HfYPf7SKkH/40PHh8ecXDbpbIFjkddXY 1gakc5MoDp1MhGEpGV/9OjJIXbm8D6SW8B1L7eJ7rULU1whoFjaZwtxDU8Wc SjTIUXnlPiTXihpy1Zfnw8fRVPCn58GDg2C/kdo9GtGBNQtCKfEt/+CKfUi9 4jUSZBjv+vauKB1G00z3iWuuYojneFQt5yjG5AlsMPAZRs+X4l/16V3IzuPf Flk1Bu/JapGGnv1wkXH9/YDJJAQSWk41PEmC7NucpxToq2CurjAnuXkGO/6V jVFrGjD+PGdfy6c5LN3moCzJtYY3vemd5u2WoMHyQdxYqBETLtg2XgjvAdVz myR8tWgoojL+W3aOgcf7xUsPDhZBjvIntwWOdvx8Py+VkDyIrvPd+y320sDP tVx+g9kwLKjcv5Ikl4oJLdYVpwuIoG5eEPNGlYyJO8JrDvmP4tnuNNnvy/2g /eEyy5IzCUKmTa9eLaIBxzt1g+uVg6gVv/S2ek8T5BaPv0+rakSZTz3BLyl0 kPAnXJGwSYdxK5nrn9gLQPzEByeGNR0EZOWb5cnDoEo71/Lwaz7EGmk/vK2c hFXlhjUSt8n4TZY/cuYEBdau3i2JHiZifuGekQuMZtxwICx6S9Aaer86XOqS 34wVrIpDE50Z0PNgo79Jagv4lJhV33uThTNuu2ZuJJPhmZnLt9reZkx5yLz/ xzQFjTODJJafzCNd+0CH7/5WOG9VnMfYMYxjEVvCLN27kenxo7xXmmeRxy3M 4Nm6zuOELtXHM4/BI1lrr/KmGfQpf36im4sGOn+9Fz0721DV7rZLRfU40jd0 Xks60goflau/dgeV4MPbyx/cBodxdMTxqtymajzRFrbn059ZMLb49+v6jUFU 8+ev4dqfAf/tqHEs+dKN1/eelG1saILMgWMxT08OY+rat3rHnlzo0DW4d+P5 AKr8S0AxuyaQCzF64KYzA7yhtib7NEjIZGVZ9DopEEwmEge2UjYqv2t2NHDh /YwTnuIXNqv2A19V/nxX3no/U9r0+dKdRZxMHmwusBiAnPcfmZ6J9aCSW/92 X1sqDrmlbtGPGsCPQSL7XW6F4oOjnH3O2A/LbDrNh0JC8NToEZ/S/0rAxCDy 4o9TrVg0H1jXPNiBZLs92z+9m4Zp8vHTxT+G8bT4cd1Ezn4YNLdN0cydwt4v DfGpmQQsvLtn6vvtaeAQnRGMeN4GZx0IhF1mFTBz6viOvVvK8dzpmKL4KAoc DBoOYuGvg4XZrZAr3wWFvg7I20pEsYK795JeMfBrgbxBtPMwbmAkFqvPsioX ryXv+rHeR08HCR2kOU+hfrXsnfHfo6BuIiZ1w6ECH3DFmQ91reer0rmbe7o6 wOaWFXUW6UBnzzCa5exCJru7lW9yFrDAa0atjmMQWixz2Vesx3AvIeria+Zu 0PRritIczUDsEvlq8n4Ba0MtfbZL9YB0VKf0TM04cFDoiqeVqbBq4diy8zkZ VwfGNbWG2+F0A9/jZDkmgq9/Ly0F+zE3WHH2j3gPkNV5hHVUBkDq3WKcjuo4 XGMO4zntVQ5GLdnxP9JncX4mj3hj9yjUERy/6MvNAymv3Oqj1BI88F+/z3wM 3ip+t5jmxEY47FDxMfBAJ3hcvhqyYd1fIpv2uuxqHwDBoc/HtH6uwZ+I4+rT SovA5znMIW1QB2+T5Eb/6LErE/Zt41VJLYfQN7aaLzLW9bH1xuFb9S0YIl3s 367dgMpHP49Z+niheoMlL8/YOKiPiF6dtC2DvMN99+95LMCBt/yvx/InMHDT O+dT57rwZcUhu97eSfSKcLGoGOnDDCeqaGsQHU5I8TCXPmZWbs9Sm3Fa9//E kVOXi/gmUcX+yM+6qXk4scswp3f7CBCeXcp4IlUPiXfNT7CP90Ht9b15dVJN SLUuT3GkpyHrZKyn9tk1TJAu75WMaQH1BJfXnRIDyMVXnxP9tRq3bun/Kao7 BYPXTBvZmbrA1kon4w8LEUz5jBrH99LwceCHvXJDk2hy10xu3iAFnDgcDeq0 EYKfNvYbL82Akte/zy1PqCAZT7NbvLUC8tInN1enzwPOze1VbKBhwN/Io9wW MzhlG3cnc7YdDm78VE7et4gUJecHq5oMyFKMi94g2w8cb7izA8sZaBHG9cW0 rwEVLu41vDbQCqkBQ/fLfg9DVmCdR/z9CuBe3VBYTKJB74/ndls+NaL0vuVb LVL9sK3x0b8j++iwV1vYJGdtAAzySKbM8TGg+puvNleVAoXiYptIzMugyC30 V76DCNQvkjMin0bBrYonQXTdB1nnkz7mnZrCDdK7i6acmZSTP8iFaB2LwMBJ U/Rn64D9rXrtLRuWgdumRoW+fQmbzvedsy7KwErr7pQvG8dQteVvw+f5afi9 Q63xpMEE7vBTeP3fo0bYJV/dSb81AOXTx76IpJXCysie8Wf+U+BlHqzjcHgY ijNT/8SPshAy7laZiNM6oOSB8L0vV2fA9uO90MqP7SjaeOOT5aVm+PfVXPxy 6DSwDb/ZJcFTiyJj/FX3luioGPEm/fJGIuQG7Np9qrQdTYaKq+xlR5DEMuag R6lAy937qsLvVWCaUf9G9Ts0LP4vcQzUelBNY8t7n/8oGMHuUi4OLZjjlzp4 6dc4enGFtnZwkMDrudCGoaBhDCwTVuS+TYKXkalT13go8JKz1Md450bC9nGy 5z3lb7CZRAi8xces/OPIjef87MMg1UR9ffXPCH7VWm57+IkC2oHXK5tfz0Au pX3zIaYJqKZ9cd7HUgWCK052vXYkEDck133xCkcx4WxiidYiai7Q2y5Zz6Kw yljLG9V6fPVw+9bzPxYgLFPs9GIrGaXyJF/sfkqCyF1icUf3DOLkBXs2mbMM vO4YesNEaQJT/y5lnzWdQrHLkapiW6ahimqcNk+Zwr8tzw1cbvXjLtdLmxNu /oCrfmcGPrIOIXJuc9uTRMQrDVYvBN71QHIUW7Br9SxcCK841PaIiM85KBMa aWMQc25riFNMJxxxShoeLKPgylE6i8efKVQ30Qz59okE+9nfKAnfcwHtUsUn fTWzaEgq5A2ZLMRNxtGKFkfHwJNw6m2X+DQI6Be0XLrTj8J/U7vjRIbgjsH1 7XWUVpT8dWHA9NgIWLX0n1P+M4QlC9Elz9aIqPrEb/jKMRr+D4mZwNE= "]]}, {}}, {}, {}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{False, False}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{True, True}, {True, True}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{None, None}, {None, None}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotLabel->FormBox[ TemplateBox[{"\"\[Rho] : \"", RowBox[{"-", "0.14661061061061062`"}]}, "RowDefault"], TraditionalForm], PlotRange->{{-2.8971228578840726`, 3.0356209745905702`}, {-3.2883264728884236`, 3.5324139966901313`}}, 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], PointSize[Tiny], AbsoluteThickness[1.6], PointBox[CompressedData[" 1:eJwVmmc4Fe4bx83SjyTJiDJKSGRlJfehkkoZRRSRiFKRzEI0jBSFyoysJKGB yriPkZW99z72OMc59vr7v3pePC+e576v+/l+P9/reoQt7Q2sGejo6EYZ6ej+ v+5K3zlKDqUiRXIi9qMgCRVGuLy94vOxrznsYPl2H+T5Gezmd6UYHHPijxc8 LAbzq1d5vpKLoLx9WMfeaxk4olPV3p8bxjOMGEfuaIdLa6D8/Hk7PPDxv/5Q YRZ/y3Q+6SF9gzeBWpqwkwQnY/sfrf8YQf0+ff88Dyryf/7dl+Vbge9IpwOj FL/D+w04sZq3hOK2xCPTjxZwbrpQ3ni+CG8Eh5QvF1Gxb9aj3WtlHkpK6nNr ebuAxMvWuFN3EIdsUjgJ7wsxw7JyODSyBVQMWiiOOa3ov8x+ev7AL6wKJlas GXchS3KH4aFREjLs0HyjGVwCu9KtH4RLTKL2+NmJO+ZjUP0vk55NbBp/2hge ZjSbAbaa4+SM6Rkw+Oa4evZoOT6KFrZqnZ0AmWRmKcFXrUj2GzOM9ZtCQkyH 8LGCaSCbruhKjH/HJpfA18+vLIGqqQ1P2ZMBSC9+VyO0vQ+8So/UZZV3Y8xf 8zXTlzWQkPBcl8OnDwNUd7ZrWFLwvkKoG3vBIlzRuRyZO7aAx8giy/SjJLj8 2+dUYlE3ioatBEbcp6BR6qibo+A/EGX0OfewbgMOuJgaTR6rBHU170npd8Nw M9Ly0G/rPhj6dno/bw0DocPtmvPk1Ql86sBdtOrdDdJlDyvyAhmJA95Us392 veB02V/9zqsRWKHZao9+ZCJYLAQ7E3ZvoMmtg14a6U1whnSthVNuHl6JLyZF DA7jXvG2n8caV2Hi/Z12fvFpvPi04NSz2lZ0CnOqaPDsgqrrPfT2wyWw5ZCO mOCnFFCWunLk0blGVAl3zuqILAVlmtCn4zb92CyI0/a5n4C1xF2WrrIbTXLU G9TV1yBv5kgvnxQ9sfm9UINH8ixK/1d2/BYTDY5UTE0HnR5ESwkBR/lTs9A1 Rld2U6YBDsf3dV3eOgxBr3ZJrR5pQOLXWy9Dmoaw9UZlRFRZLeYr3HF9HFsD Fxf9DynGteED73zO8g0q6lt6TKZEDYGhidlKI6UBRzpdsplDJuAKT8n5eYMZ ZFwdvNwYNYN0gt06yfuDwGH27Xi6Ig17ThF1/DyGcH0X52XO5GZ0ijtw+up8 KwTfdGfP/9mGAwOG6/UfJ7H4W/p9cu4CWA1qrf83MoOmpqJcM9cYiHROgu3j bzvgaMCAbLz4DDw/p/6d5cMQTphTp++ll6DC1StZPT9HITtCt1lsfRjEo53/ JgvlgMmqh3EedRzGj9kLKAW0YxGXIEnz2zymPPW9XcI8CYrTzLUWMWUQbT3+ n2V6PVA7FA3vvFuCGn11IfdTI5jzY+XOjEA3XKrbsU+gOhmFeKYTv7zvRWkc zW5poMErS0U1wchBfPzmQWyB7zqo5gQfTY7sgDzqtWvn7CpA6tSOLqYrrfD7 1YuyV0fJUGAmHJWiNwurqp0eoiZN8EHgbTzDyUkMU0FzhflqDHlaQXKnG8CX Zl2+VlY0cNYT9kenl6jk777H5nU/Vvcxb/cXGsHqP2K+9hH0BM1QQcP4i5ko +l7Gu+13JvQ+LLMaYSnBR39Ev42b5aH5s58Oea//YMfw4uss81KIPu1O7XCc wCAOqvTBfwwE372FjH76TZD3vpAaIkyEHX7bFDmF8iCi8Iye69gQnmUCARfG QXzn/L18hpWKbQnar5beLqP4j6Q3U6rlmHLyR0rKVgrQkbMDn7L3w4MU/kjG 3r84r6jwIYM4DXkRhQrXDw2id5rTPc6qAdhVdfKHt2sQSpj5m96R6oOdf9dY ygYKsIXcoyxe+xcacp7seXamGDhuax9+a98EhJ2esSf3rCL/vCCf7uFpiLkW nW2jWoJXgveJJV+pQUfTwChyQR96x2WUCFneRW0bw1x5q35c5rCWNFIdxMOu y0xm0fPo9ovZv/XwCoo3PbIuCiWjaWajVerlbvj85G4gW0w9KOt56vnd+oeP P/AxT75uxMQs7tnAvClkPxBVzD41CSlBZdcTntZAZLCWvR51DJbfaNpdW9gU 3322vW/PjuBzPpfVlIVZGBAz/BnwdxX85wQj21vy8FfN70879zdh6f3PfM7c 83CjtcLlntNzSPhk8Ix79xjk5CZZqFzJRr7U8sqAU6lof/+VGV1/H9RJOkyy FBeBaEBRVb7nKm7oUV06T0+AMI1OlXA5H7+wbN3L2deM1wd35U1UraKI1+SE /LENsNHbFeYQMomUrU+X6+X/wajmiEe4RwJqvTXJ8cVpNL4vHf6CdwXThJ8q K9pRwTE1keLnkI6WqfmCLya/gbDrbiGd/Hr8KBhyl8BfCXmxxM/N4ivwZ2mH KENCw6b4dB/vtvmGLI5+HBWXhtAzrLcjlH0SdjKcyKbtW8HQ3wqOXpfbgSD8 OzXFawIj7lztgT3d6FbqMP7wdT2WVSV6nnvXi6ymp3qr2ykwSE0ZvXh6GFQL TrV73JzGq+bCRlL2feC2YVBvLDsKD4q2H57WnQKhoOoh6dAmfENmiFb6Og45 d0xlCxrbUIz5Xe+8Hw1lSAc9drP/gg/kUZk+zzpQb6rWF4mpQgYBwp0tnPNY ZO//u6ORCn+3n48v5W2Ce0O7notdawW1mZgZN5Us/LFRftXWfAn+0zdOLYhf QhLC5Ws3W2Eug7+OiP9ghwopzmhgCE4RZi8xyndiZRbdTuv4Omw2eSJ9ZNcs pr7QDRuiJ8Mrw2A9Y4ceaDaq0VqbpKJbhEy+Ne8IBnkbSxaKrAO7Yn0dVxQV jSQGHnX2LQHvL1H+2IoBVPbSYNwY+gFSopyEA71f8bzohRsBQ7OQ1rql+ZjZ BDI1mOaJ9ndgwqLW4ZHkMSxYqDq8/cUcjGTIGzbKtmCl0zfN6QMkiPQ6+dPv 7hAsxP1iU32+hdjumHVlPNEXb/BuuWg0vYBqXCovTOWaQfm917dtJlGgWqJj EbdYBL5FkqzEjHi8+plF4llqJWQfPbHSc/AzuH3u28pwqQMCzYZyeiUaoPBQ xa2igHHcJrRPmdTehmYqnV/LHzMQTyrb3/r7tRF9384FcB1cBkXr8gXTw0xE h+M5grwMJDA1iZ5VsZmGXyN11s5t2Zgo+dH1BT0FTtVV3NsuXwXPNuZ2DF0Y w0+XnzG1hk8ix0jH2J3GEgiTs2/X6/SFPYZ6HLYnqTjIo3j1I88YbCfGaPGn d0HRiW3BYhcG4bt/tNipdCouHN7/w/BnFhTNuCkR91Ox22MmavAgFbb8bdf+ k7eMrpn/VWadH8Ho0VjDaWoWSGhySrUtTUO2MEcr3RkKXvUpt97+ZQUejhSf d5AZxV9J7Ix05mRUvaKWYj+yiPSeVMvEt3PoZ3GmN3+OBFweajW1KTNAfn34 JacaCfvIcj9zXGYxspKJGMc/Csmn36/rczIQLpk9ePz98zw2vtP5eUyuF0yO aFx7xDEG/ClLo4GcHIQ3NdafJL0WMd5sI3kbBw2U177oMtRWYbf7Uoi1dwFU vUL/Xxp5kJPqvL7FtRUzVf3uRltR8XSrkfgvLETnu/6KLlsnIOK2wpEyzhUw 3Vto89yoDo/Xpihf3tmJHUJkTVWhSfjO1njp7Vg7Ep1uDQ5FkcE6bwu7ulYn +DN9UOihReC5JcHb29NvAD/hdNGW7/0wckRmV/+mD7zSqIk/bNgIzQc01c52 z+H7mJQvlemDcNDghk/ezkXkz1R+pecyAhHM07JLW+fg+sXOrFAqCWzZlORa cQDlq9h2LOnPwcCXkUT2k3HQKi2oeFm+F9tWqTK6BS3YIs7/UeEVPaHsr+UW ZoYa+FWhx+2jNAGvzcUqSs91geZ2yfttEV0Q7HDz82jjb/SHZi15oWWcvjSg mkA/hB92vW/86UIBjowKo1/vh/C7mrLXXqcBOPbufm/3Uyrsy9X5/UWGgcj1 esCBZ/kLfuIUeDjcOYWqtPNO2hdasJF/X1p9cSac2lZgY9Q2AZrTaYXlJwcx urKJ/ZvoLJS8ndwda0NDK72C4syWSVB4NnZCwmYO+68X7UviCUB7i/+knCXm 4a+Sate2PX1oNZNtLXgnB5Km5gwcf24l3I+d41A8uY5cQj5U99v/sMun+for kxowX/hL3sMyCkyE++d1cinIdCW14aEVCRq8/MyTXbqBYnRl8kj2Ij4Oytb3 SpoDNQbL+Oj9bTCw4eH2O7oTpmz5b10Qpyd6HGbzpuW0QvXxXVbHRmno6wWm uVGteOhb9Wyk2DvYvl7zH39jHybHR9s6rVLRNTGO6xUnGZwPnq0//HIF8s7n u5pFU9FXWmTi2yZfpCvavvlo1IU2Lr7NR8uToFZm2+/XTkP4TE34+eXxChAK dmQdO0eDtJFj/dWvVuHJCzOTysIFtP4rk3Nm6xgUDnPwpggPo3im/1db0xb0 31n4qm1PFq5Gi2ax8dARqrbnLQ2+YyDqyzFONLGP4BfLhBSPV+1431dDNFhq GDkJLy83fx+EqNeZPeuvqtBnjbnzShYdwZepdvmidiM4qktKz+8j4XyHsdcO cibUNgZ9usIyA7++z+fdvDaM72aLGq037/lOXcis9PEiEg/tPSzyhgJ6T0O+ hzQwEat2uVCf7ViGPZnT8TOpRajPdedrmAMNXr9MqLbRXMa4i5EaC6IVeK+n 4jwLXTNO/h3YMtVbjffvaVsEv6XisMk6eYR7EphVBq5UGHShrah5turxNhxv 1EtbtZ4HDoFihUv9LRDoc97h2cow9l3P3uvYToI0yz668WMd6OjW533iyiI8 OmvNdkl3CS7cuJGUY7qA4kGkceM+Epr9+d77nbQCWWWvP387UoOKXuUTQZFk POvin1RmNgSZVfJNVtytsHuvwr+Y9AkwaGOSYxkoRa+oWPnarHrghmvOB5Oq 8N6QJ53jp0bgkF3mEWemI2TtaG05FlwHpa9aX2qc7YBHXU3ExuTvQPYPuHfq xSAuJOvcZuungOmcRc+30lr0/7icnMbXjDk9OQJ51t1geZTeqNe8GcuvJk7P iswDl9K/h0JdBeCX8UH4a8AASne6jur5jsET4ZD7W44OQjOPDPvTUxOQRR8X blaxgTv/W9xLucRAnOV59ePd3BiEDvD59tq24FRJ0DR34ThyfXzPVLZ/FTKN h7jP3utG2Tttx/QPDsBeI65P2Udn8Q0TpZPrCBPBpKMty+L0CB59di4jzm4S 438UrXdd2gD9zwStuM36fv3QeDgmMgHHmBWUnoX2o3Jar/1xSi5Y8FIv7L0/ CwKzoKm4b3NOFsVvnWnrwS11PzLZ1PpB0ermRa+7RTD+iTnFOWMEr8ZYZZ0U bcPzFYQtPS5tcCSGeOHOcSqqVLoTd28bRRGbsREZvgG83aV5nd66FXfU7pC6 9YaR+NywK+Dc0jIIi261KNk8/77tOi2LZQTSUg+11pdu5h/zHa6kU/8g6nL5 fzXb+vC5GO3u64Pd8MHnY+R2iWJ0qNePuxhdAfveKay+uz6FukQbCYWIYbyV MVc5cIsCaWm8uq7VM7jl+27X00+/Y5tWRoaryQiIil25/jsWIaFQv+vS2S7c kmf5xVujEQSk97rMWuTD3HU7033bp+DFPjcD6o4pVOD5HbIoUISj56bSSuZH UErRUseP3IrBjp7FcqWlqOcYcm+0ZhrSNG9/btszhJl7E2hKip1w90WqjfTh QWRN3WMhIlKAF3cXLYYcmYeIo/HxZpoUXLWQqxuLmoWLsgecYj6TQKpjO/vA xwXcRknxSgslgzI9vioIXMFr9t1k9h3DUFL0H/3NvflQbRp6yfF4Hl5teLbX TmAIElJuiZRWjkKFbgq9ivMSOr+nyvK4j0AVv2WRkvM8XhgXlXTO2OSK6bJ1 vNYMq6dnFXs+D6Ob6IL9jGwW2u5s/9wjPg03H9lDXA8VqbFy4s+jyXgnyG+L lWgxzlfeLHlTNgNJO9ncE2jz+EupMS6SawxEzC4l94m04lbf8NMPwxbhs1NS 2WPRIXhz7JTeC55Z9LrfOmGvuskvnDMEh/fjWHtvfWiubB68FClmadsr4Vep pEMlYzRKyhQvp6akAFfyfwrsWv+w96pzknxFDxw3/bGgljaDe4YMqkPMWrGw umfaLbgFd53SjPPR6ISZZ/Hhb46Vw9rM56HmryTYXkzz+5M0iFgyE6coPoCH txETP2aR8LfBkJKeTR5231dr4FsrBt6jn19cXViGh5JjZ82i1vCvmbFb/r84 CF6VORW/UY0JfPe0C9aqQCFwYCF33zQIH3tvsXZmDAT9qbo9iVQ8ePbWwhrj ItZ9cPax7liG/ZHGHKctZjHTW+SWTkIerGRnDmblj6NaVa1nlPMIHHiq1TOx YwiDhIpJxy+SwXtLVtTDHY1wWuXH3YK787g+EiieLZ+JTQVjqgJB4xB4Xr+K PbYXXAd7Kz7PLaINR6X4Ra0a6E8o23XLZwGvhB27lHGPnpDhw8h6/L95vNHN O37zYyukOrPwCXYPYWrLvKngiQoId+OOu1b2CZx5ttbwW67jeBFkK22lJ7i2 cgvefD6HT2eXJB1u0BF71j8M8p3fwMTVw8Gub+gI7HFRjBuSbRCy0fT6lPs4 2lG3N/cKToO0Urgpg+Q8rPKfNBC/RIHGDQXn74ur+OJUDa/n42mk1VGrS76U IdKdYSz4MgWfOuqNzwnX4Glm3ecXj9HQKJHvsSzTHLTWHalUGh6GtCdX9qTP DIC8Ijiuec4gb0VK9un7NPTjLe9RXCahVusv36Q9ZESZ6T/2SSOo+uIQX5xr P+qKf3Q5rEYBBXW3FZFHjTi5bh707mwXuB7blnPvAGLyvPowuZyeKGG0I3Ul gQKjnTax8TErEF4YLp3wkpF4RFYtgLWwH3/4b+nV5+7B6aN3X8hc7EZ5wbUd hZoUmGlJ3xll3wya+1J2hep1YjC/ktBn6xXwrauP2jJNAbeRSr+bis0wr3xj rex8NyT07DJQjJ5GoTgzBgcFKrSqFNkO3xuCuolrvxOpxfi+SvZucv0QrHhW sgjrd8Fvqdv6coVpIP6Kb/uj8nyUD2Z4OvqWBB3EtAuWTIyEk9n2Xy5d6EeH z5rOPvfJ4LSzXJH6goKaxT23VQ7PQ8nVbzI6t2fhxZ8hpdyXNOTjMWrdcr8P ajwoeQ9SxjCCFiGcSF+BS353xG7a0iBhgy7rP9Y6KIk//dHTZQi+b4TeWnw/ B7wLH2LvyY3ix2G5xuLX03AgwCZE/mkLno2R8qc9JoOe9S2T40ndWBesVb9c /xe+DXd3brDQcOH+8sZe7lk0ee9a+zGGgSDTejfY0Os+TPovmNgVVsABSPWR O7CFUOrD6Rb5eAbbxt7EFHi2ooLBbHauQD5KMFvo+ZkNo0EfXbjZUzJcuHtl oOdDJ/w7sPXfLgYSyjk+m60aW0Jiyw8982epeCYpVv0HqQ6OSDnenswYAufy MyXD6yR4fac+QHAtHF4/uQ97w2bxgY2VQBHPMjz5Efwoq6wO38RaVQRvXcUC DxtLnxcLaLbFPtCKQIU41SVW985FbNS9arhaOAxf6MLDRZrn0d+GxYT9zhAU 0p8hmW/uW5z30BBcqwYfj62/H/xNgJNCkp/1yxbRyvLhn5lbZOSmZGufFZkC zZqnFX83+YF9ew3bRyUSDikVWbVED6GCYkPzB6UBmOZdkF8I7oMX8wf0CwT/ wgGF6q7h5G6UW/K80nG6HTqtqW8tZoZR4Nr4k49HScjXJMaxM3kYZKykgwu7 EezeXiensfbhofsX1PIkJsDE7Hn6Db5VOOw8m6tyfB15+xR86efiIc+uePbH bRouztf/UE6j4tkotuzChkm8xxpgGZ1ABoJnWbvm7QAQtuuuybzXD7d7R0qi NPqxsdGn+d3lXqyQObXrE0MbmIbnJGpLVWPU7NDdO5t5/OzvbQG26ST0fv1L 6+S+GOxlDafK7u2DdEKmj6t3B5q37rwn1TmLFpJXmc7bdkOB5+f/qKE0vOeN rK2WwxDOAoe9GVcxz7X1TXBWP752Dpx/xt8PbVv30qVo/MRuLZeY/eG/wH17 90fhyFWUm6FnP8X8DXUM6EM9DrVBr70Nl6bUL9AOc6KEZzbCUdmjNy0sFlHj 9w6XXFYGQpNIQCrPuSI4l+qmJxNXCmpRdAWRKzM44PT3cPq+DtRJtTozFV+I Rx7+syo1oYG5Y7FRTs00enmXvOunK8KXxi3COrxkODTJUCh5ZB7PjHd5aicW 48IIaXFhtR9DLssOm8utoeJDjYczWmuQO/CW/0H+Btzdy87JdmIZTd341EP5 GnFcJ1hnIbING/SYQ04+b0cZarCEmEIyCIbcvF1nNIb85IlbvPT0hF3wwf7B jzY8nPxleUYqF5hveGnodk/CwJ60dXf5Ugz1mPusXjMKA1c0DuzfPoax8qbP xX4N44XoXJrKwjTQ1d/Rf/i0HuOrqw0jd07jmm7hTmLnAGhF83KtlfVDnOHX h2Hnh+Fe0Hnzdc5ZNC6epx9vbMEfh1jS/l7/DZ/qG8/mBNNgnkV0XOvcHDYa Dmgdap6FBrsrIR7bK7Dl4A/NjMIJJNic+9XNmwJ7LYPDTscPYkmQbjHp4zjo XjvuwHO/C88d8z+l5kDEvSdZjaXZZuFGRgPHxdcMRMFO9hyFH0TczRzDo7ZG Q5c64yftVS2gOWllctFmEg4a5tAi2WhIvOlf/pevCf2Mxzuk386i9iGhwcHg YlzENHX2oGEo5dN7P2owh8k6S41a5oxEoQwxZuV9LISzF0q25akuABd94PRB nV74OflsNREaUOb9nPm2GytInOrtPHx2DF5Xsn2g5w3BMAsb4YOb/nXD7lH9 9nOMRGnVWw5Dv6jIyxgKJl6/QOydyt+IwHb8MJlz9WZzGbBxVxYw3iADiVg7 UvmVhZhqPK1a8rsHTIXZj4su9GOt4b14iUcUCB/o54pKyIYyD8FCa58hWJQP bDq6YxEt3YfTfwsnwrzlt6npOx0ws1/K09djFdmXbcd5eweAkzi8/1ZaMRwU cVdj6JiDcpsi35O0VlBmYMmNsf8IFZKNcwNHJkCW5OxVqNwMR50P6N9rbgIu 5mmDotVG/JOYVG+4mwbrDOTh6fgBjBS6kCNRvgSZOrkNI3t+wBMpg1OGdvVI U1pbEQ8fwRHBjj2Zi3n4lGX1NKQ1wESsTVFtyTDY5jIW2gjGIa+N7/Ou3VTs y3lAvuNfiEODd6bTtZYxM2RjvlBzAua4GAIrN3mOO8bw1EP2VQiWzNlPK6Rg ZqrxyaYX88DT3l5bs70V7RIo/ufE80HhhN+hm+lTqGmr7cB9dhrWfM6sza1v IY549FebqtLgvPnPPM6mVXzY2G+a84aB8Fwy4aTSPgoYt/yTvWlfhId+vViI 52qBsbIwExQgIVEleM8HwUw462jmThKpBWjJDxGv6UeZD6zP1+EPlD+J6siV IkLO91duHD9bsXf86RK9yggQKVZ8Gj/bMEKqPfxyUjNIByVcX8kZgK+MjyuO vGiCMvWnlnqHZjGoVJu8j74fiEXpIZqVSyg5+sH/pF4XhgdYxWl86Ue/a771 8jdn8Ytrk7ZQPwkNBNA0+jwV5HlS4vfUDOP66uk37LIT0KN90/YdSyMEMP/q EfXqB6mWkxZfuP5hldi1xskj9ejxYM0xN5UCq2yGe38S8yB7jdavy90MgYqL 2Yyf/23ymQjbo945kBwc3vW6noxCYtpPybPvkctFqFU/vASoL2/Hts3XYthL lQvsdwqxMza+I3RrN94ZDrbkDa1CYwtwP8CRDX3E2eB9R5qQyb72lMD+NYyo N6m4X9cKvIq8Ux/NWyAn6vJ+7pVClLjT8VX6ah9+Z+O0vLipL3KjYtsiZgbh 2daB70zlZCT7M5pzKs3CqbSCEivefqy+xfO2R7geqfTf9Kv6+zHyuzrxjTER 6a5mwKsOKgaKdZmoRCyDd+HwpfXCSUy6xrf7o9ci8NbtPf6jYBSFaVcOf2NZ BJPiFO8i3iosTWiSiLcaw6zSm5nKe+gJCoNdPI8X22C7vu6IHn8n6PAYnuBm 6QFmo18HI4cnQEA57ZV0JxGPn979JvoICUOiQ3l+mNEgw6Vtm44nIzGiQnXC eZ0KTHKqsr/jyZhSkEtPfLMETE/U1GyP1sH472u+udtmIbicwS+xewDXj3bk Ve0eB9UkXjXV6wPITOgLUFydgdS3Ln0XjErATEmx1ie4CaWuJXbcv9eHMrE6 7+/IJ6HThEdb/JZGSBT88CXy2hiQZmQXVBRp8Kb7mLlFyxLW+nAtx0hH4All 0T1tTv+wu71F+7tCCWTotNhxctOAsenJ0cLaOexV1b/zUHocRc6pfc9vboeu zwMmOw8M49xC85zBhTHIP7xX7Z4tFdm0K46FXmkFgqGubE1DCHBf0CDfYplC WoRR2tZeRkLp5ViLoHe9oHjrn7sBbRjSk9Z/khL7IOm/kZFRvwHQKTeuc6tf RPKs4aJU/jKkpKVSCpj+YdiBEKvrL2PANjYvtLVqFBlSE94Y35iD14f9S1z1 J3D5SM/WUukZ3Kqc9agicRCdzlrtmmpsg7z7ykwrlYuo0Hu3JHp609+L69q+ DEzA6a7jn2zpe3F/9MSbqXP94Hs+Uz4/bRyN4pXndcVq4Qsjt84X42rQLvgW kJHei/UHcv1+z/Xjz6xTh743VKO66tVrgpwzEFhAsEHnYmRhKqp/W0kB/dZE H/4rtcChfOIj6dgDNKjRj/SqG8S+L63a7HbpcG9a1VTa7iUyeWSoGGe8hPCc pE/v3HthOSLt3i9aOcwJX8t979MHBith3Sp3+uFX/M0Ly+l1aHsgpVPCvQnH cj6nE5/nw70Thx5zyS6B3G7+8MySEuxQc5J1fNcA+5SWLtyx7Yc9IUaP7LqK 8fSTMaNTZ6bA85n47y85C9hZUn7MaSYd6GPNpDSozfCBwYOOYNqDwT99XbmZ 5lGH9ZzowtYeHIni+eXOVggWbSoBgX/WYeA/xRuffJbQUXNhj1vnIHbMsLm8 CuwD+VH/dVunLjC6n15IPLMIH/fl2J6db4P/DoXuvJLThgImzd73SpcgeoeA 5qJaKx7YJjG+fKUcvM/wv3GlLeDgUfVlQ6Nq8HW88aC4cwWb41muc6x9hpvz YQbbLtGQQ/98iVo7FVaP6Nw9aNaL+VO+Lg759XhBWnblVO4ofm2pTHotNori U9PvyxUoEJ8pPuko34izkbW3VN1G4GzSjLHL33WguU70jdZ34ZqfWF/j1xGM H21elJcYhGw9X79/OcNQ5Wc9pRIwiOw+TB8u/SJBuF3dlqtlVVAvyi3h1twK niXF1trqDMTC6EjrLV964E34R4myr8Pg+GOf0h3ZccyU048jNiShNZPg2IL/ DJz38uysrukGd2uDP/VH2yH7WlVNkNU00m+Ze950oReb+E9a+pWuwG9CQta2 9nFceW3EFiLWiy4G3pcypVrQM5lZ9Mj9OZSSDCQNHhyAaitd1Y+HmjBejnS4 w2wdMx21BY7snYXpA4JvYh4UYp9VNNNejlbwGf88TK9MQT8uFUvemhHQlxaJ UBqbxgaWhj0Pd/VASOl3PyOxIQgPqqyrl1uEPnZb4V1V/TgsKXS7s3EEe517 wtL/DmFPcJ/5Q7054DBnM9HoGABfhQx7vffdMG0aJ7RQtKlXVcS1KrEFWPXO gIr8EXhCCLG7fLwPBEZOhn6ypKK3RZFaSdwYuCjX0HmUMhBud/do/DCdw5wx 8V1GrRR4fONU6BgPDanBl1ribctBnq6Hpd2jFQXynTkXuqfwv19rd13LhsDt 8LdrDjAPR3+4FFVyLuHAmtPQ7ZxNHwlUn/eUWsArlU2yPX70BK3K/264Zo+i Wfx47BOjdJC/zlI4aDqOPDfrlWI7mtH2o53qcEwvpL1iqby20o8v7w+Eb+0a wwaZnVqaz/Lwnj8teINxGLx7rcpvF1KAa0vM9/3FXZj8wMLP4i89cerLA11D tnXg2Vv23WjThw+IMHgoPCRDdHK4rqAOI4EQPpwNlBGUO33/512zChS29RZ5 sKcFHj+LSRGNGMOowYeT596uAVsog2tFzxg4/Qix9bT4hY/kDew2YvrwhPx5 mxDshSllwaqa0yOoS/e73+MuEfx6r9BtTe7C49velzdOlYPsU4XYsz10BIqc xtB8GgVVJQ6GfNjkZm/RtvV3f1bA8y61fDGVgkYBnN9QaBGWuXhGP2UOgMuA uyJZhAzSp18mkFKbIXU/68X/MqZw5mAZJe7x3CYvKzzJzCTiuFaS4Ml3VJDb U/Zxu2E31udeU1npGMG79OKPPGvJ8NWbIVH30iZ/2Qp+tiEV4+rpxyP7qrKQ d0RYTHBfN8g0s6ofW3uL5UVKQxKldVDPkxev93YKfFvvXRlpWQIWpz1PBqtI OLahnRETNgd/TFn++IZWw82xxkyJTa5aO9cV+pVEg19HzdTP8tIRIwuvNtg/ nUO6fS8jHis/QQ7zS3+O+VJxVOxRdg9bFaQbcJgpibWBWtuHevGhORByMxDj 9uvF+Jplm5VXRBCPKQqT+zeNJL9QaXdCK1A+s2nHlbeiZ9+Vdi9jMpKGn2yj nh3HvBRJPC/Xh/YuTVoLPQN4+Prn2dxHs2B5h72EIbcV/EZPzJ60WkDGdcGH /oXToLh3PfMffRH+vnhv+qRWLe4PpNIrSzZDSGtZz+f9G1B51vVandkauriJ G+8/14hvWypuTv1pxWhx5Q4r7VFUeMLiEmhZDwlVYZnzubO4Pf6Ak532JIyp K8+rX5uHtHN/9m5VK8XcpBP/ZTd3g6G55Lg1wwLKyLU/qjCf38wRkWuLckXo 9ept4jHffqj/tBvIXkO4J0AoeMNvFQvz050t/szAXZdBFZfqeZgmhGoUikyg aZfMqEU5Ce9E6lBo9iOYGWGA/dy1cNmHLkZCaB5LeDdk9D8sY0pe7JlDNDJY xwTsltqcT7N9F9ke5c6hbMqFw/bKKzDt3rp6xbMdmrltvZ2WF5B9z50ym/J+ EPpe37Ie8BSzxQuCaGaN8Pv2GWm/HUtgUKnlnbI+jnvUPQ5eeDgLetXP1s+9 K4HHHgXv2uvXcO9w884HL+dgl6DFoPLRftRvvhr7+VMXPKn0urm0qx5NXd7o xdGqYZpUSr91tBFe00e/4ImZAMVJ3lAKHxkOuuYv97H2wrrsn9BR7XlokiME SXPTEdtuDw4p+a1jazjrDql2MpQWUTYSYhrx7kurXTLULtDUKhHxkR9Fj4Fw epc+MkQ+41K6FlCAI3aN5KDMXrDV7NdalZ0FfzMxwmnZ3zD0iLmnILYc/yyq L1ilrcIBI6UdAl/pCN3h75XSvCjYkqQg+J80FQoqaDnNG0PQDgKUH/xVWJGd usg+lYeHFj5Yl3T1Y8dcg8mpERKs0fSG/ThGwL7xB/Hj0TlsLz5oROmbRuv8 BGZLhwa87ajPMJQwBoV3P3+T46JgUkR5DyyXohFF5o08SylsDz6UeWhxHpQd /iyujebAsaSJ5O7HIzjjTre9JasbnUZjswsf0NDxydDdR8c74bcRjS7x7jjQ 9cU0FBgzQUxk5c8zXz8Bt+XksGErDf+qxoxLzRhD3eWcrbS7ZKjULX52jjQD P4dOM88sUfCVZCTXa8sVMAr1ncq81gLSsyuNQ1Y96OGzR4wzfhIn33O6zPfW YQu/2vmS1xkQ0h4vOOY+C97KMXVfzN1gR9/++bNuk1BnzhgynFeL6h7vj4da t2Csg/72IDIVe+QZbojE1OKu22mW/LQKrLy+r4DVgwz3vP/wWQV0wJa8jtrV pCnQaIn+NKQ2iu3NcgoZz77iQ8YIw399ZExTfFsop16FWnvLvcRGypCv8MGD bdU1MO1k0Ree3o0E1m0tSVwDaKrziWf73BS83ClXYOo8D7X/8fCdahrBKYkr Ww6SqeDPY2nZ//sPigdYdngBCfIuzXYnpg6ifrha66f+SexL4qEu5H2AMzsm pYb1JnCSQ1fIQWURhpVn4gs0J8F+tMn8RMkEpF82er5g2QtFa1VHJcZGoELR N/JILxnfijMti/pvIUSWOjWbPGEiRmV4/tEzpgFx6/Gvqpt1ciQuk/KvDOLP l0X0C440mPMU5Sb7DOC7qrPhmhWlmH6ESYyolocZrEpfKqOZCCtckCV7hJ74 4mD3bjuROSB51VWoqw5iZML92CNXqKDzny/rqfQykBaWf8Ui0QB0BbKsjkFR qGpubOQl2w7kXzY6OWeq8YNY/mz331nM6GxEh+FRkJjL5HjdSUW5E2d/LrDP QtqtM1/TCdVIUuvtPW9ERdeDJqusgRRcn3J10spagiEjLu6K58Mw7tGk3/5y Ac7HNjZHnxiD+G+vmdreFoHu4sXeqzHz0NPIsjv30RK+0JYLvRU8h7Y1rmTW Ix34calF9OE3BoJCt6GzCSyh17BdS5nbMA4c7bnUvunLw50Hpi4yzmKR+9+c WskREHYZfLx8n4ar7iHWfn5zcPaETpnYMzK0y3305TOdR90Uvt5/LeOgedy+ OEK6HOic3577212K0X8LO8KkKfiEppT9JbIQ9gY2cs7QqHDOwKvkmV4dCpaN TN2QW4AOnbC/3740wvHYrO8m/L3gM5UpZHWNjuAm7Vz5+1ADHMp4tW8liIwN vcr90exMhIph16Dcj0S89p9Fz6uJPvCQMlgrsypA2eIjf6TPD2EMn8HT64Wz uHjw2DF1jVwoaCxUdbIdRdGq/zK01oZBTv6AjbQdBdy+lfI88yFhQ0KPhDnH OFTjE0aNwhmUV36xFPChFRPz7I9/1Nrkv/spj0Qf/AVly3MCdyN88Y2khdlH UUZCeV7hxSWpPsj3H3E/dasZpB+/e7BVeBDdFZ6YdPTmY4zP0iJ9PgXe2H5l WmxJhUM0d4kO/QHo3OoSpDY3hLTju6rJxhMoI3BZz840C1NTI1LSRRbgwtLb 1v2KDRhBX91t+6oD9+5OkRY370Na3oxzhFQB3im5wRb0cwY8mfjazj0bRjHh MYHF3jDcHf097WhYI7TpTjy4P92BD/f38lxvb0HyonuHSNg83ocg5iVDKqiy dhgKa2/ACv++dZolGTlXS4RaDs7jr8/taqFhvzB71+PgJNIg7EmIJug4teOd Cr47DjGzKNxdWm3kRwX6lTaTe44N2Klllm5NooDDD40TZxaYiR4qTvlO1zdz xP1tHiJOC8glLldtrkoDG93hjxsa7eg6q5qt9SEP8rOVffbrD4POlYynvVkT ED83JTxwtR/uSgpdvV3bB+O3tBhiNzn3WZiyXt2vLrgR6WAq4z8H6992uup8 qcLU6x0nghybQfei3pL/YBs+zTCpsNnMI10fW8z/JI7At47Upd0Lc/Cl6iXT wZfjkDAj8PRk/ADKD26JeLTSjmpDC+lZwRQ8GnP78s+EDfglFDhURhzFnktG OguGQzh2zZXKt9mX4caEKj2jMpjjuv/87/I46MWKHK1XGMZtgdkPb+f8w7t7 HfsF5BgJb1MqzxvuX8BF/ddPmG03ILNGSCovohEKEt+yqbBO49hKJjM1oBP6 jqS3i1AoqPTJbdq+KR6CpSIP+vT04VhUamvi4gaEftrKRJihYqKLu8M93w5Q 8NhmzcxKw9N0lzIaLk9guZtipYb9AsgommmCOwnbnoTeYHxVAQsnvsBuC2aC 9jCr9/unnZhOSSelN+SCC4OgXzjTKLaVslet5yyCmHHJ27jNfCDgMNIfebgf D+bl9fSwTYL8E99v3zv8wekD59KA6CTGqrAyMh6bg2QT3C/JvoApvbxbravq 8Z5GV7p9ZBE8PKUzVX2uB8Rs3z7yySLhQ00xreQbw3jSLJ81WqIGNO/SLtKs 23D0QR5L8JMOMPq+epwzYBwTc3XUL3VVYexJwp//bq3DTbOrd91G13BtN6fK K9UcSAtjHXp0bBD0V2+8K06lAut+1ry5+QlwcibN7Vodhp5LMzXMBzd11Yo9 inmJjvhBtmA/bxE9gUWPwWzPg2WsqkikL7s3Am126fxWtG7gjGpW0mkagZDr Udt5D1LAN0r21PNMEnJ4qNjKE5swWEOVrbVqGQ9G5Ty6LjmORtM1Cc/muzGO IL3/68IaJhP5s/2SesDuPT3jh2gyjj9YsSe4VUK42OFQfds+qN/icb49nYha dQl3Oe8sIqEhbTJcPQMfX1jP3vHQB9+/uBCe5tuLfks3P5RmUHAPHzO3QDEF xcRWnh+faYMBiWMhO+LboO5RfqS5HgUbgoQkn9j3Y7vuB38ZgSUU5Z591vKm EcIcUmq9r1djIlNecpl4BVz13SoXEDUKz6XFB/UN6Igt4TsiNj72IfMz4o2a sAkoGt79bcpyDtUu9/6UE6SCxYeh62bONGSaOMF/zYAMF+pNUr8eGcTabZ8u mibWQ7/37jWa3QAsZ5y9aptejpksJ7lLj3eg1qeteT08dXC5w/KWnRoFFXYE PfLe5LO7Aof4ixQqwTFkFweZuIJD+9jy76W3Q602y9+I+kncp3n12yu3fhSq /kTm2CgFq4NPRISe1wIDUSfsdfEs1N7iPFRxYgLVF/rnhh+Vo8Eb4m36vRuQ oj5bcmLPHO6vYWXovtCNrNkNqtOq9IS3nUGBx9mGwSk/8eePW5Pwje1Z2WtC Gfw4QC3mP0ZPzP9s+qV9dyNSbZu25RpMgThBeXLuDz2x47JXq7IiE4He+O+e nQENsLrhm/dTqhlIuqraGoYz4F2T9rKRxQY3agZ/ml1sBtl99f6uwiTwDY3d fvPCCmxdfv9Al3sUJzPM7MK0miCZsH16KKwX4oy+5B7a2g9Vr0MuhWkRkafj 4B46i1ksPyr/5JkMEZKX9347pEhBiRt28Roug2AiNSz7PoMIsWccPV4cX0Rj Tt+SoGetMHS4WT6FoQmoRZn6dxObYCF55tOP8Ao4M9kWub2FBLtbUjo9VOmJ 07sH1Tt6OoDBkEf7ni4NpNqOveXW+ARbhZgpf0IX8Y5j3i5mByaircPa27BN ntyjpsYjeWBT57gFqm0EqqAl1V1f480QyAQl8e7X36TlSk/p7uQ6jFQUK31/ rxCm+pbsYnt74NpE/NuGtU6kVnPLVc52whX3Mou9kzP4wnDfaFVlNdDT3sYT 6odQ8tWB51vsRqBY/YyG7eEaPFbUX23IPIeX5lQYffXpCGfClfuM9SZBLMU5 Tqa8C69bdfz+kjuA1nKf+cIYenC/75CuXvQ8FsxXqtb2LIHtUa9YZ+4FXPj3 3Hnt4ix84mF7eL22CX6Z3Os2+voNCb75EZ0l2VDxzvKGQ/4YFA+9nx0PHYTE +WOmvAEjyOMjsqG2OgZfPdcXlFXH8Y9H/I26TY78kBb2mneUgrWpzUcNWihA d/EkhedpOg49D3wxaPodXL+pLIT9G0Ohg6Z23yKXwD9D8mXyQgvQ19sKXD9P QQ4G1hlyXzxEfZxcY2/YQEuW9Oe1xAHw3BV845NXH5TFuFWcOU/EMB+R5ECD CIz+wiSoltWHrBHb+bPehUOrjIQl8wkm4pEzBWoxvYMoxGyovrA6DhJxt5MV FUfhdq2D8qR1P67rpwUvBdVBYOGhncyTC3C/wiCWL2cNx/OEzFnXl/FnXuUK 558J9JN4/KS2bQWnXiTertzZhjq77QxmXKlgX9CgXa21jaiQ87ddI2cbobmq ajlrLwWYAtK09/eMYp5j+stPDbOgybe1j8G3DifSd0go7ejCD50enS9OtoH+ yT4uQY4uJA+CjE8wBWhk93uefv14bNHxVl4UFUb4Wo6akCfhYeAN+wHzUni4 +zQhln0a2ZdMlfr0WnGXgsnt8xr0hCjPPcentGmoe12DY7GSjjgqJUeaUcqC FL6zpr26c3jigv1Xd+EZCL3rziGR1Yj1bqlfYWkF1zIMohjnxlF3UP7C3pk5 3Lnb8UCa6wp4Xe4I1Faex7k/FXc4alYhdyIsZaCAiajzppPV8WIttu0880ha tx8qKoimNz90YRfb20PMbJ1wMpFJzvj1CJ4Wkad99hkHBVVlM9b//+/V4fVT JA+h1H92ty9t+txBy+f7DmmuQ2nHTVdJ8ybIf9wbucS3AnpSZ4peGM7h7tRn NLuH46C7IZv5dXEZEsYYo74eYCDu89S2j3+ahod14qc+z/Rjz0Js7KukJgih 7eNqZP6Jlxifnoi4l4Hih6zG1elJ8NG1ZtlNewjiakicsWX9EPTKb/2U7zJw 6Par8IilQvP87baNsEn8pZlYnN3TDofW3fepX6+EUk+74EJdMv4x3q81/a8d RdyNLbNVJsHyRVbsz0PfkCHgDLmNtwE5+JnPck+NQ79aSOvdgGlM5+o8VPwm CVTvrk7An0F4Q0t5E39qCRv5VIfknBkJ36up+xOj6nDST/xJ8jIRqnb35n0y SsKSeZHK1aRGuCG6L6OSk55wtnrlv7uGPWji1nVi//0R/InfH/vK5cLf7LBd +0eaQPnlG8YP7eO4Nu35LnbaH6WpMdtrpXuRqKfi7Kg8jrOFE40E2ynQp7tY QG88iiuPcval8U+C2dpcwSO5JZBMGfp87wA9cW/ryY9adM04rbjtr8Mm531T kbsZExkJtv2fSNfOL+A/m9jF+M3c3Ee1sf4+9A32ENdKwrS6cWRV7ZLepzbc 8IhTKTHuhDRvpQL6WwMY29AonhFKQSJfSKcZyxQEPu0S/H5+ANoOuvUfP1EI 2fTyQ4do8xjjoCR9rJ0EKSo8B7MVqBh9VZHeN7oZamjungyEQlj764i3Iskg cJNy99LZGWSquK70ay8JHFIFjnduW4VI3ssdg3tGMT2MT5iVvxmWvyhHkZfG MCVT2Yo7bxp1/h2+VmUyAVwjL2sumzbigJzff0H9U/DeR6a2u+E7sAhziHy6 wECsUAz+5cI0gM0qIWYdJ8hgfzHUzrFsHf1+8mn8ODwJTYtBKjYPV1D2otDT hoFV+PnR52oxJxGfEHjsjh2shydNQqaWzENoV943q11TD3GMY8KB6Yv4WrLH vX18AQix3t2RA0Q8ln6+OeAFCZ5J75peeV4PqhKsTKtfqHhTCQoyE5iJkc/+ 9lqtMBNcc/v5Z6oH4Xee9LTrLjIqbDse2LA4DC7jJ/miW8agYaIhXoN7HlKS joN2eD80XiZfuZY2hKd17xxfMxyGtcMDZ7hJlbB1Mfhs2fwIpq080FeiLOJc fyIHybAFnkT5Sr0Y64EDHorKF14Oom75UAJUkZBpZT4x3XQSR84vyW31/wVn 9W6wn1vMBEt5A8OEAAr4X9F10Qj/AxeMAuvsAqtRae8D+2fJVPBj+W3G+mYa DvxQW71gWbDJJZ77hI9mQ+XJg0O8zzegUJpWb6C3qf8Pe1MPVP3Ed0Xn/rJs b0RNG08urd4+mBrbLhhQTgVkuzU4GzOHY9lyDXTDdIS/7p4l7ybn8AzfHJlf bxSWWXM0pogdmGV4j7ZlpRQFP33ys1AawujW6apI8Wl0OiPkpP5+HE4Zyhz6 klsPwqnxX8/r0ZCyi+Hp5YAFpBOIT2tfGYO25S71hrJFHD0xHBCfnAn0TefF z82+g/vJrc/aNMnYKiqp2L2TjGwP1l7bja0DlB9w0DBCSPYQ8bioloc3eLKe v+q9iBywO0LUJgVIQiGrywYjcO4fd7++9TKeDpV4aRLaiTpHrUpn50fhRFN7 x2lhEvoJoilnzRJ4dwwr2ymV4PbsSw3pHrOg+7jkdWfbKKrpmP6o4ZoCzQOm HzYfJY4ylR92HJqBOA8WHjfdevwb1hfFIv8bmnuLtyycnYGfYjWt2Vt7sVus 34RssQwidUduvKEfxWwl1ugA6jLoMe3lV6QvwzP3+8YLHdsh2XWm4M1SE+xS j93GvlqF0rJNtNVtZHwoSpqy3uTiJ3E3+1jU2lF6bPfN1wETKBxnsdVgbhpu yzpb97JOYbRs2QWm0/9Qcq2pt/7wHMpM5X4oUaLC67jhE7+4Z5Fud7DYYeNi 5AiSiPANbkXDdzNyAz+HIfKDvA23ySo8DBh7IO6+igHvqqYPe8+AJSGFopVT BpFGrfmSr0hYdzHDgKt0AH5fY1MSJXdCssh4xfGEOqDIGs+3vmtDyaKGq2NB RXiTz7OhKrQePL7bROySJOPSn/4JJ7Z2vJCzHBtzswz+sUeo5U+OgV7di5j+ twsgwBQvfbN2GT0GdheWDjEQSjPrZpUD1uG+aLUXUXwBw5K+jIxIjOK0gLMv XywFhOgaSyrV6lE46S+BLrUOtdxShk/LNuG1nUbs45JD6K3u4kZ3ZQQcDSYW fvhOAL3jDo+9THWwQeXilxf4B38WIsoHfXvhjpjj9b7N3NWZPmx8h68aE3gd 2oyMl+HQJLdAaGod1K609CuKdQFRyVA7JKwMnG5YPDo2soUosE0/7avpBDYu jf3mD6LgUsGYwWjABBgHptuU3J1ARW+DE/GcEzBKe10md6YRdYzk5r+H/kTn BicPl+VhPGB9uPGM3AI+0IlVL35KwRCSzd0r/N8giJGNTeVGHZ4o7Ez51tgL 23Zddas9NIiGwW1z9gdIWBUg7Pg8bwA+kGn8V6M2+z66I11kph7lx7n7z9ze wBMxNwK/+W3qzou6Gw5VDfh1S+6wKq0EKIMnXabPfsJYPSO2b4oUKD0yprla vI4ySvQGdcyN8D8V0ZfE "]]}, {}}, {}, {}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{False, False}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{True, True}, {True, True}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{None, None}, {None, None}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotLabel->FormBox[ TemplateBox[{"\"\[Rho] : \"", RowBox[{"-", "0.3181061061061061`"}]}, "RowDefault"], TraditionalForm], PlotRange->{{-3.1595712365449837`, 4.018111839521249}, {-3.0848596678043685`, 3.2144810689414047`}}, 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], PointSize[Tiny], AbsoluteThickness[1.6], PointBox[CompressedData[" 1:eJwVl2cgFW4bxq2MUklGW0WFEFlFuVXIKIRkZScRGcU/FMooUtokEhll78z7 2GTvvdexz+HY6/V+ej4/z30/1/X7nTB9pHGPhoqKikhLRfX/c2fn6YbOgyR0 KXSU+K2dhIsVp/RphVthPv0/nRXZeZSd7rwq9KAZqITWnhf+qMX3/g0CxVb1 eNntpTTxTiqOcSoeoMrfxPrnN2t9fSexzeaiyNmoIdxjed7nkv44Kh18yPeF cw5fLlX78e0tw6yBtXiP2XYwzpfnmqbdgM8rVLH1HP2gNmWpdN1+HH2N8q+9 lmvBcwp5OsEL/eApNJGwUDEGqwMTu/KrxtGiNPxxtvE06FztDuLKppf9nrpH aFf+MB6x83Pj/T2AnLQTptLJZByl2J95HTMGaskpqjm2Q6BcReXhpFGIYX9g fVRvCP5z/5R9OH4MfYLr5VYeFiPlr/1CyWYrnBWZa7PS7od1sSfh8m+KkLZx KfLMgzKwaKAEcZ/aAqquN1IxLq1Yaxkqr/qzBUxXO747JzUiV2hDLISsgu+x hkMl7t+ww/HOqyLmMdR/pVd7kqkRNhmtO5nfFMLm36LR3wskYHRtZa9KT8fT T03iW6NWcbrr5x1bVjI88fppZEKVCoe+ixkdON+J7XUcqTKyw3Cv631pBWkY hTo9RKmDZ2BHReUt6awlaCOQTmpcXUVmahZzhRki+vocqFEjRwL3f5nau83b kPat2THzI73QKs99eP9gOvTUSV/8uT6ESw5Z62/9ZoD38vtV29hyMDNKIsc5 5eKnoVJ1Hr0lsBFrr7XOJMOHBxF3a03GQcRhyevg/Az+0Mt6Xl1TBTIjgpNP v5OAl1uk1z20DYLec2uQHxJxr3oQ8ZxUI7g3eGst/ymHxkDRonOjc6j1xS6V hjgG2uvU2RLucxiYHHOilIcAbKHfou7cmEC1O3nf7w534NxkXl6w0izyrYxU BKmW4zm1uc7M9V4oN3k09HKFmuBvoc36OigVfIUF2qmftSNX0cm9WuFVWCc4 Sr1W2QT3mDP5SqXHoT+Qv9TyQT8Wqf3ez9M+Bqy992zrfqXDCWv+niEYwtV+ H0fFzgEokojJUmPOwmd5sjySrSSQyjE70elLgZdPn8UedGlHf74l2YUWMqbX ajtMcLSC+oLP9/KHC8jKH+B4kGkcw3rePX36moIvorqr1DkiwcoyvrlGYh07 D9M5qvL0grnbYsmiYz/e+HP60szdViBmt1+//oECMfvk2kdtosBwv7nCqH0H HGg37ntVMwgxBy+/+Mq+DtVhH1Tj5cn4Nv/0J0WmSSjNuJcqYzgLDoO3+h2O DOEsnZHZ76sk/FXOxTetuYRh+eNlAlL9wHRMkzh+mQK9XPrLvsQFRM2D7LeL 1tDK4ar6qddrKDayxB2XvwIndr4c32tAwlv0+oIjB/rx8PmEayEuhSCi+tdB 3IoCLgMNOTcjUmEj61h/3sAwfFoQWhmbI+LSBX2RRPZmbJg3Nd7VMgZdnez/ JPvHkHxO9qH8hVEoWC3iFUjeArn05YfneBcwwtv+uuijTii5cn0+j7IKlKnl ZIpHL0D1hxQ9x3gMyMo+X/GYgFR5CQTjnk9QMHKP7V1cP5awKlis/TeIfvbq Tf9FksF9xR6ZvzUgq0KFQFTqCoZR2Q6YDOyVleN6zZAYFYX1wvRrKuXFuOfp sXN9ej3oOkOfl2gxBfeu9aS8mKYiHB5YO5h9fRGehnjG8ijMYMfKc1lb11m8 vWa6Sy63DksShRuJ5GkYb5CwP2/UDM6K3MoZCg2oXMF18Fl2F+iFRdiU/0vB v+Uy2pbx02ghX0+eN8mAy5YTdB/Xh3E/uXT3ENs07vT9Z/HnfAXcvlQ+1cq3 AvfUTj/kPDWCC+4xE62DG/Cl78l4k/EvfMt2/+XGni48GF+SPJv0Gzw2TBgj zMbx2MacaKdhB5C0y2ykyhqRX0zx/qXbXTgfUZUYlz+LOfovZAO7KFhd+nwv +81/2Br050AT2wT2hB2MW/k6Cgmml7V9Geew4eAbN6XDA3h3/vGdIPZOyKSd 5f803AUXM5KZOTK3cKt2pLn3RCOcGl1wNslKhK6GLQ+unzPoxED/Xj5kBqVc Y5qOvt7e2242z+mlWRzdsPQ6dnIAH4kVulB3N+JfUztZw+hFyJdQ7C/VjQQV /iVFAdZSFH5u3p6nNg9r1I+3KqbGIVJIqWamfwppyQ8/KP+ag1Q/18Y2ESqC 6DLrNINRPUCVVJXp7T/AFU+bq/SjGQ/T7g5UaxkGG3oWmVBaMnjbkDuKuHbI OlyYuCQTV4SxmaHXTWOGccXhpd6NczMI9Jq2hpfX4RVYnvQQbkMeKX2l/yjU BNWVF/TpsRQwKvAXbpMbQeuUyDuPHMexR+FRk1P5InBKLZYeKRmAjwK2hxWO puO6ZJF9xvtNfNTb7GciOoCyJgWitXUkjLjLO0qVMoZMRYSjbkMLkHCmfdRB ZQQZvB88uXmOjHsE/76n2TmPgfZck/6YCwFdDSfu/iWDCgf/4+vm6/CfR8DL 8rAOROOLa6OMy9DDEB82OTiA7XO1kozb+Z1yO5/564cBZI0JfyNbPQ9ffa52 OEktYpiOJpOO2zo4SEQ/dNreK0NokJuPbwerCRr9q3RUstZ/FJQfiHXhz/0m j0gM0/BvZd9M9V8ycnpxxpxdIeIbpj/1CVP50Hcu2aTEtgP9+ywCOQ6tYd+p ja4Qcgck1rPSydYVQYtYQcapolbYs7Qnmst6AFjOXhu3N06E74be/90ZIUPQ ucNhztJkDN1t0FKXXwy9fh959VTJuOlziebdxUl0X1cNFg6ZQI+y67KpuhtA VlMVE5OaxX9C0eMn9ArBRsJHML2xA7vOqP7KUi8AAxfNV+zWfVD15nkLZ8EM GMYnfH9+Qx579SfzAm+OAZ2/8bTTuQR0zTmu8imlCkyH7Q7uZKjDk4xNxX+q Z7FDTPLo8cl+0IqxWUw6Xgq5RqWF1SfLsF/oub8V/TT8Ge2cedMeCX58LmvU EstgHyDbeaCUiN03bPZn72gE3wq+P+F+UxDFbXclOq8Hoo6I29admsHnkabK WUdn0C39dZ3lwQyIu2j9wLZrADbXYtLneMfR+fvc20znSTgZ9rNj5eMELBUa jDW5j0F1avmg9Vg7SspqyfWYf8XYaVcX8fAh2H1hX0Dq3ibcNIqzH7zcCrsI qX9cRUfhZ8TBHGclElJtcrZ0r8yjSgKp7nnHMB7uUrlp8JOIIVJFB3dWDQOv S4HoWPEmKilJZKuXdkEBZdI42H8Azz5KzX9e3QGLHZ1Ubhx1ELXVxFW23A8h M+JCrWqbkKOudlH26Qw2Cq4bEIKWkKA/2jU9R0NwCCqJaywkomeA45K+9wSM uZgbMfl2YgydgUZb9xqIHHEKnvPcQCt6Ua9o7nn0/dQpsRRKI3tHU/6+7f0h 7B35mLPF1YEPynji8l3qYMlvl9x70zo4avefxfj3ZTzoEv+PxZMEkz7vWt8p rYCRhN9MuslfJGr/KbZhbsG0D4Fqh54wEEbOJBXklkRhjOgupsOPt0Cp6+TP nS+aYdDL8pC80xZMR+aFk6cpoHSUKDd/agV4CkI67v0dxuMzVLtODExi80sX tu7NWXCbuXZacH0Ed66Tt3bol6NrKfHIY54BSPl9u3LxFRlv2F3bV862itnh ak+/p2/iuz0WNtfMmzFhb7renpeLuPO6lNidxmksYN99YPxsF8rtW86tPjEM pUOOkHOsE4dVOokqI/14fISbfj/1HJ4WkZhPvB6Oj2sVnflu12DWkQw30V2j UNuYR8W8bw577u4ycj+zAHeETphaJpPhYkIF96h3LKDkxy/msAENHV90zyn8 Bn1hRbdHbzNRa9bpz6H6TIA/I1T3WIdBQ+M8s+HHfvhibzVTd2IZNNsy7/Ed GMTLzmwT/1qn4RpzXNLYiVJYKmMhxdkv4av74TRxjANwZ5ru0TWpNdC/TXWE ZmsO4qXO7H61NQ/3lY8qGLxbxdH3O4YndpMA6vQ+rQhTIF9L0dnJdB5vuwkn tpkXoozss7ZIpgFMsbZgLwuZBraT32Mb98RAAdH+SJzRPGx9qls5bzuG0axp 2v17m4BbqopLgqMLZNgGRdtTu1GKS4mVRy8P+xL8h/nMJzH6uwjtFScKun8c dGW5vgRvFqy/z14dQ/MyqYf8cmOotMNR6GHsMCLPYT+Vtk50qcq4WEj3D998 FsmheuYP3eEewnvHSJhErJK//pSCrMBirm1QB4vtZ2ZzGhaAp746ZOfNDdQd 97w4dmYJZV6v2k38GAI1x7nsMIY1eJfIrScZSC2r3OIgIFhAgu+SH5k8jk+h 5j9V+Xc0c0DHbpVWZNQFbEfj3zBdjsff88oyvp98kG5LNrFcYxgSxn2197rO YciudN2OXjrZ9dIq10FiA64OXR55Eh0Fx6mdla9kFQHBnMfKLP899B0Yf3V+ aQUc0uT3fmyfQQFdAjFMtxk15+6pZ4bQEZjE1tNKJuZRX7CFedioBQUep09H rA/DbLfUmvhrGtnDXNxPomY2sGvI+fbgHRrCXff1A/Y/GvBXlZIu49ooqo4T 2zqOULDsfGZPQmUfBAuJ2gqVduP59/q7KtnJoJhkfHrSfRRO3v+9d+XTMPZ2 PW5696cZ1BrcXe/ojsMGS+ji97sUmLlbf11Elkp2luJF1vQYxSnuKKNol0l4 UeJuV+dcjPFOx0nUh4jI5OzOH1/aA8H2R8UGvnTD0aE1cc2Yba6hP5Hn5k1C pcTnXPVvhzDcIs/719tFmOAVTHm2fw5/RZqOW1F6cbrkiY/OsyWolo4MsOla wyg6es20a6NI1T6R2NGwhAqV3zf4GMe380kzIZ6rHPUuT1+pvtuKvbf9hVZT I7DqQj7pBMcIGF8+uKn0Yw7GT6tms9jWo8o+IoP2uwU8zEZz/LbRAB4OVKlf jBhBxR+PqiI6yHDG8tihkuVJLDqaqPecVAvU1AXjjKm9MMovE3U2rR8a2xU3 laRJGKY2bxW9/a6fSXdcO//MYZMb0zkqbjL8+0qwHTg0jhPK2mdepi3Aq89U 7jJnx6Fq+lvYldx0FLvkUayuXoWqrYeSMXkSpYfp3bkuPYQIXvtuOhZqWX2W 0NX2unYImvDSr/XvwKMlm5lv2cYR7jrr6mRRIHVx/wWBpm1ODn390+FWP77+ teFPnz6NZi5Nu4dPreCI40/umqkitCq+EAlz2dD6bZn/ed8YrHxy0/EaWQEm WtGgT1UMhE9cz1X1zk+ADsFj5PPvNYzY+K1iUDKE6TrP9pVLLuOO3Lg6ef9J XFla4ckWKERll82F2Ykm7CuhS79U3YSvr5d/Y0V6wkdt5ls7NdtQXPZSqpNm GXypJRyiysiESw6fFSP2DyLJR0s6WYyWULI/6Ck3oQbNdi3LPN8awPKwxIDN Y2MYMDSkWq88jzUZTE0xiovo6TIQ/JeNhFlNJ3ODHKbgxmaGGf3kP5QS15kg kJYgpvi6M1/5FCzY+N64uTqFrf/8xI6GLEGr9xiVt2cWqFzM7ifHULD8xZid shkZRkaXhHsIk6AS0y24+rEWcpdNr1M/HUSdXRzn1+ym8d2xv/KegiOg19hN RzZbhoNnTvzVN6aSfa3O9cclvBs5XevLPCsa4cOjD7Hscl14suQb3+mnRUCW HzchvRqDoyZVDUSFQYyJPSmdEk+C3ur2TzSZE7BZ++XcMZlR5HWx2BcvtAi/ /TqGCwKoCF5Z2X6MQyT0lItW67wZBhsqX/YdsupH639PfjckZANnmP5Fpwtz WDvzaUHfZALBh1ZmMHoJ1QuXSmIPD+L9U/nR/UrL2OXE/qWSuRYV9jc/5Cwq Qa2TLOmaomNYdKnQZd2zHXdKbqkpU7b720P+9rfQUYyrcXKQFmvBZsrWDCPL AtY6l7+yPkJEqi2+75qRs3CIkUa2SX4T/f4wubdQhuFKyfAbts3tXK3t/nBL gwKuD38eHMutxat0jYSpGiIQ3jKMPKOnlX0dmU2UZWlF5pfC452t2zk7Ktj0 KmMejr+dVCp7Q0OgotPzzh9YQ3zgO2NGpsDH970bNffz8TPDtyvKeyjYSNpJ TqnsBuernOe5XBJRbv1zzfDeObxpsGHY3N4DSRea7t1DMghNs+YPUm2iAeOv kJfm216RSFqsFBgAjT7s8WegJhA7tmLv1TfhLe9pWzf5URSX8L3GfG8CUxKH HLh1lyGXp1/fIWEKDY+F04f9I8J3bsm2ftZROBNbqn3v9dT2nIVdK1eW0G7l jLZzwmegEnm5c8gnBTY0deVirUdg633iprBmNc77/hg9Nt8Fmt8axvdvUcmq CVj5iJesgbrh9T2hf36BVkLSlyKJTbBmoOGgfVGNwz28pvbjQyicMLUmcXwQ hZQ8v8u1UxHoKgxDxB9SUP0kKfDkMgWeuebeIbR3YffJT212tqvAxVL7feMK ooKzoXCXLRH4ltwZ/thNQbxixatzUfNQINtpYkWaxKcSc9+FfWfxRYCGfm5Q H95SfK5wkaMCwjOJ/3EYjiBnyCFHeqExVLS1evDDrxC1LhINrvwg4Q6XDgmq 74swmBbY8KWwG3ijHd21vg8Cy8RNC6OgUZjw4bzgcnQeq/ivBI8Z/8T03F8N 0S1E6H/J0iXVvgIVfEpNO/UHYOLoA1HLD3+hW4wc598/jMr8Z8kMjs1wW/kw 6W9BB/5JgqVmtjEYS7avKuD4t80J90QtZPuw4/Uf5bDbjZBkNsF6arQPJE+d Gq3rb8a1pGohmQkKSrNYn+OvLcCWxx5huecK8LRA7JM4nlXMv2i3WLkQi9zG ZQEFWIt1MWd+l6v3Iz/7/TF16w6suOxG/amUllD20r05QnYan52+tHXy4SSO 6eiwDJSugPzJH/EOR0qhfF7rYPGlZfhaEMlqKpiA3IM+7G7Z8fAt9ojiF9zA yIf2QTbdBGgVffuhlJOK8Ippo6hJZQn2eTAKVIfVIP+07tyL4BfgGyr1/b7I GiRHv2Hc6uoFM8faxx8Eh1GH2Xn9770GiJjyEkvmJMH42rD3I45VuHuWhkGd mYTEfW5hzr3p4KvNada+sIBJV6VpnHY3oMqTGyLPTrbDMjGl5efXARCU+d56 gJOGcK/fO/RUSgm83MnsP6W0DjYrX9QtqEZx/33Fel31IRyt6c/ZH7EMTIk9 bJXRkzAwXNrqNzoOhREXD/883IYXKD8PcipTQFbmBtd73kUwSO0QztiiIEHa Z2if5yp+irzh9nDbM+92cYWMaZdAf/AlL2n+HQSHYOtX2j+oZT8c66TLvtuO Ae17zh5QTIXh3faKv281AzdznN+rriUoodN5at+/gmVVhsXVHNModFbihgXT JkgVjKqp3mhActVLy7rGdmBV0zux9q0Jj1iVc0/eJGCSxgMZOelueBnuMMX8 ag6zaOJqogfqIUw70YNxfxq+WhS9IiXcgR0iilujKW3QIH5Ax7KhcNs7GNt6 LFshLEtN8z/qTYyPlrkYyNgCBvemB5mFq8D9W7ms2ZsVvCBfXbzjfDgce69+ WGCuHg4YFJtPic7Dd5d5xfDCQlwbfJ/FJTaKs48PuZ7SGAONlKKoWc953F3N fCrFcBbzfrGwPuYl4bUX/xXEDPVifbDhxxOlwVjyQuqQzX/bXG7quK/5ZSNk KBIljhMo6OoVFfcraxbeKO132XdxDB9p0/mMXRkFmdHhzduJGXib48qHaPp1 YDPVNnlTNQYK3p1nZtVIQNwXraPlGwcZl48nnI7ZAN7H57lHXVZgqufa58X8 cuxlc2dQXRvCYL/oK6tx4TjpGMkbpRwFT2T3RfDLjWA9ywfV9dQ5PC8xMvuw ZRL8fZJ2xvwmgdIr5kgmjkmsDoUsp7lRVGe62flrawRft+/oK2YexxW1D0Tf 2Hlg7Pn3X5lfE/xwp7n2SG4KPp+PyAv+QgZHXU2VNLMm/MuS+PqtTAOyw9s/ s3oLGFMht8uOfQwNRJKmf6sMo7pQ2osN1W1OJE8x0L4nob6dzljZjVFkGz06 61XSgdVP4uYv0NdAtZftzTqmCdRo3HDwsljANK9aE8YoOkKype0zr8Z6KI7t UxvJLQIb0YLPxTuIOHbvTC3hawZocIk8Ptg/i456IvH+/41CXLFXwrVcIpS/ ZQ8jU8hw51jegttCJapMbDK9zZ/Ap0czfx6Kn4LbSotq5qfacYHJWJEzpBuY bRovft3u+8grOzz1qqZALSf8bvDdQXzi51XFb9ePt2gCJ52uUKD1bOLu07K1 eDPpj8H3lg6wkfKk0lEawtecDpXfWyfwZqKXZXtQI4z+IRkuFfWDhGSb2f5r kxj23oos+3cOw2h2eYQYdiH/jhMiTypHsVT+8+mTd4ZQ7BhTZN3JQlTUcL4r 956IRhOnreoJc8ig9Xxvn/wcUPI+Hy5IHwcNoVNGQ4QxdFzi7f3kXAj9TTFb 7NpjYCrm8o5jaRHfmDvMtl5aA77EuxtTxGl4//to3mWPbhiyIRmxC6bClOHp E1a+jXB6t+ZA5rZnfW+rP2+xoxUZQu20qHOWgO9zz+bA5Bzoc+VqWzEkoE/l fzbef/uB1eVN9GrtIv5I3+PZR54DH7hV5CS7CEHlwr9NHMkg6H/NWUmSjCr9 mT9ntvvM9Kn8DULXALKoX7u7Xykf2e6LEmPfdWLs312n1ObqcejUjg5mmlng r8nWGdnev6Xwg1s+iRSYnvKbcGqZ2fYds+lX5g1QrZ1fdmm1BPtouw/w9K1j Z817NjP6UdToA9ZigQkkit+XuCRAQu5It1vxNxtB6X7exlPDMpSd6oxjn1iE t5FmdCFPF5BAnGy0qbWAa+lFl4bT+3AQ9D01rhNw42ATWTezGKQ7vrx44UeE QsqRWFGONtBOmfh17CMN4SVDjcb+ixTMWKSLvn91FPbTGoUFrpXgWwzChIeu sDqbeZepeQq3Mjke6pZ0wQnrQM43p0bxcRaB9fqtdoh4UiSvr9OPqrT3WzJw EpRc2xLqs9bRJcTO4vryJpg2pNQPFZJxI7ExXT1lFM1IR+sz/UKA3imYfZ/E PGp9PMBouG8es3Nd5pzYi9EypjVEW6wQDUYklypyWvBIhjV3YHw61GfTmu61 7IQqz6SB2dvDuP+HkU+ydD2EBO0yeSu/AnqG1ndbmpqxfCQ9rWujCctNdpvr XR1G2v6WCMdCIpYLRvy8n7aEv0gmP2g4B4BX95tXmNsEMLpyn/tj2QHWLwyG 69pJIP35dHOZ1ihUUAcYlNQv4ZPeRWt92kkMn2W96rljDBL/0N+Y2vZGytyG iktNE271Tw5UGYwA8V2OHk99OMqMinuViNZh+QX6C+curGL8aAAz7YltTunY fWS+fRAFVPvLDrlO4MX2LavkMjKKk5YkfwsvQaHUhTdC+ychz6J6D+V7P06F Tx2IfLOIvOlfCf0PxjCC9b8Ci5E1yE3WEWBhopfNdQlU1mnYxDYNJkWF9Eig n5q7875wDmcldwRceUuEd+26qRynEexry7oFJftRrf6hy39+HfDe2XyPbNAY KIX0lNoTJvEwwY38vngCWjPUPwxTmsHAtDaf9uQI3lfy2bg83I8Lul085v4L +MSGe6BbZx1qd7kF36CZArsWQy6jyHGIz38jIsFYAudq/pPTNOzHMruE3Utb Qxg0UZP8emgUmf9xSiupIFSIudHocsSC9KUqY5u0TdzszQ0to1sAxtKRdB+d OaTSCDJnfbSAj3dRnLOu9GOz2b3X2vIUMGLG65LfR1G5yehVJVMhUFUTo0+J rUPfyNCGQDkVYdqaLqjAux/t1J880PSYwR9TSrtKDxfDfNvrkCsPRzHi3UXr +0+GIOiWh7H7lwVQyqiNvlVfhjt5J4TfHaHAnCCj7JnWdbS3eGounDYEKkGB 0ze3/7+GlaDV8kAD5ryFh7Y3Z/DbEPXq0PVyMDr0/WmZcguk6EQ2FQoP4u9S JdkUoxrMuHJU3VaDBGeahU6faajCqxHJFeElXdjTKf1DVbUZApevmVZ1teKJ mTJz8K/BKy+v+zp69mD0Pvq4UNIYng95TiP/aB60TNLCjl7b3vszvuxsuiT4 a+t+6kjPOFCcsu2VJKgIrg/bPoTS0RFcGNrW93K9h6OWQYYOcVXwzPSVM+Ox ReQwzapWeUCEhJ1UoYc4B/FnxVeGC/E/QMKY16AQpyE36vbjVvyGweVdlkfO bIGxxa4qPfdu2DcZbH86lYAlm3T6K6KtGM0xIiLwmErWRaFpkeZFN/Ta0nyz Np3C4mye3T7USxD6hU6RTWQdL9p6jT4SW4UKQ1wgiaxgh/NxmkHtVPQ8UFdK y0cA0zt9G8dX6Am7XhfMkfy3+f62T+STISrCkzKFjjyTDlgMuY3ZN6kIPP2P HztyLmFt6ObvQf4iNLhTK3ijZhAXy3dvfCwcwCfP/pOxXe/B+LtVF64ZdsNR 9tcdJsNNeKNE/GAdWy98esKa//5oO1ia8R8/sjse+qicN81HeqBf6VVLnsEy 7KBU/jQupUB46y+dScF+lMtvbXxN9QOpjgTV1vRtIeUh0/fL1hV4r7P9Z4JI GbRXyzhNxfbA2sb9CO7gQSTQ0KS1UKhkozfOXuec70eTUyd3WbMPQISSQMAD vkkIpXN6zeMxins9HziK7ekGubOhwWcXl2G3gnB9ySMi7gqz/1HSQUIKyY+L /k4PHK+01b3fVQHj5lrG/zRGUax2Ke6BxCC+Mt6yH7PrQRny0gUj8QywbtXi umSZCmZ3/plTgsahJUX9C+0cGWT8NWTOLHXhHE1lypvNDXChPxhEuEyGa+/2 2HwrGUVwypzZIdaBt0IFNGIZ+lBF5cJny8elGBpyjo1OlYjMc0r3e1makLL+ IW3o2Sj8NLZJJkl0QcsXBy4qxSH00zPO8pLJhJZKPtVChWr0Xo+/xma/g8B5 dGvzgNcm6sqlusx7kcHA+itOcncCuXzTTECuE+jP8DTrE6thSqFbwOPRHD5h MhbnjhvEXXJXM9mTFvGSurmkZPYSdGYJ/Xxb0QESvlxCjU3RuGP5giAL1Vdk FTSi97szBiJpLlwau8fhlA1nKO16BhzTlWP25BvHVm6NmciaYYjXaUhRNBiE NgkH3uDkIqDtm9VazaLgr2AO8WX3Mfj8gCXwjv4iiLMO3E4tGEMqC7VLrA0L aDewfFemsQo98kD3vd8WNMhXnjU6PY3lWL90xSMDotTEonSLaGQ5zj+zGD6a A9rueudV+/vwjsqocBdPKXr/EHn/5i4FmGl7eW+njUBlL5fjdadBVFMkSHvz 9CIXrzy0LNajV0IAaYqWgPydPGs9y8soYSnc1FyRhHnyclmxj0gwEuevnavU Be72FA7psgY0YWKY0+msQIVSpnRRUhd8uXlHKaR2Br/evvSz8OE/FH/ygTNO dxaYT8UM5CZQsKVzQpWXmQiDWRVRSz/JwNVsPfadpxDc9r8Y9DtfDuGxJ1LF BBfRnDGhpvnYFHxlUzPVtHuLXnbr8+dp8zGA9YzfcJ875t1HAaJEJ2jpR5dk Kg1gYfF8uOBzAgTtdo0lpHUiDT9rtpFZNzTPybrQvliBs+wvdd4n/sUQFf4u TvkG6Hyn9kKipxhuDcy/WhMeQbjb5/l0egTvvNplnCIxBLMf3lLBYRqCgIuw YOi3VWT3Os1wZRcZbW89oByzmULb8Iu/di0uodBwk1z+GhmyOi/Y6/F3A1GF stPodwMULlk+8VesQXnrqMvNd+uRsENY48D9MeT68fEjPZJg9NbqIcHjdIQf 43cY9HImsNXP87T8viE8nunxSfJqOxxQ9T5ev3MI3ebTavroBmDnSlOQMEMB cLb+eL+g2wTi1W0B77e5debAVa41wjA8cVs/vVWeB/vSXMdsTN7ApdUjDYX9 hTh81qkyNWQeVm/NPyixGcQD19UWcvaT4VvjTaa/n7PgmnyPhP9DGlm2oHMK rMpdGDbopqT+IhA5iofy/hq9Q2/Vc5d/NQ7B29Lai546bdC6VXmU/LUJRDvu X75FNQfcI5RnLE2z8O79Du69vM3IFadFy6e9zdPccTsOXxvBHHpdf62jJPTp /N3Y7F6KD9PGSVq89ZikwrdQN7yEawqmD314ptGbl7Hhgcw8xrE0LH2aoZJ9 2cVt5hKfi7Ne87vVTi/DyF4zrevGvvh0I/QLyWgKKS+qrCJWBzCb6lhf+N4c LHjj7/2PhwJmKnP2CYHtMO+p4pMUtICKUaJB7aIVYLCl2TtS3wzv5GbU9kam QbRZXEhKOAWPdxJ/89V1QrG/8o+wPRuwa2axkpPzD6xYrRKy9nXguYPv0660 JAObhsX0gH8mep0m3rf5l4ex/tmjgneWwbOF7/dS6AJYHll1GLOg4MEtG82x mikY6PrA0nNzCPGc8KW/s5Po5Xy9qcpvDL4GfvsqvW8YIwvafhXd6wDmCvLW wbIBEJhT0RC2WQZj7mFpV7YFuBjntJNgOAw/n9oIV79DfEiTe8EwZn7bwwM/ KwaQoY7zr+MSbQ+oSF4USC/sxtkAwYyrC9m47/Jrhie1o0AdmvhP98YIciy/ cKvyeY82L80wTqsNAjR2irO9/4eZfL7HBNTJqFNjIeceOAt7zw6L/Wc+hNx5 8ZszN8jozb3znsIrCoz4koX3UfeC3sOBJLsjrTCpV94VaDEAAz8zM/1/1mNe 0y58IDMLW2x7m55OLkLGg863L39Not4p+9BP+tX4R3WT9b/d7SjCKO29udYF JfXDrWeTVrCViyIvLFCFUguS+bWX61At9cD7uW+1INqctt/tIhEcSnPeaHZX Qf6jtoxbPN1g0P7FkwwDoG17Ru8Feyfu8D/b+vRYL0C0Q+Bexxz8EmCXq62a iSHZh9Jp1wYgN/aHXZviNAwIlntPSLfjgbwJitmbMVggebvnmyZC1X9Fopu3 qGUVzHaI8pYQQHfrAcfh8n8gOPpW5vqwN9xxTxRKlluBLYm6FtOzSaibkXPo SHwSUCvEyTmrjqFyEphwbnNUl62ug4vOCO5cuyZ/IXYA+M+EFZ51GIC0FW3J eqmfkBO38lzx0iyKR9RcIZu34ml7VXlViwF8Z8r+YMFyHroV9hazsU/CFTFh uVuuIzhf9K+AU24Dqb/ZpvPfIsGWBxcT2WcMNBbHv8XzTYOTqQj3W5VRvHbM a07pQida/3IQX3fvBSeBtkxUbsEVUo7kt/xBqO/zIMVytOCWWXAbmx8RLyw3 2p6K7gG3jUsmwYvTkN/0zrBgqwV5z1qN+3JMg1ija8UttwWo6twrpHpxGBr9 FW/KZ3WD1aDw79VDZNSnVdmpPkgla62Ctxlca0HxyrXGwpU11PIqDTl6nQiG Z/juKwfm4OlQYpPJpUEQHe5WZb5AgQPzSSq3mkogNGBv9+eb08Dq4+g4/4yC doTBkqs5peBIef12RbIYv9av9tCw9CH9XSbR2gVqgs7L4Eu26qOoNiGpcOVQ H5w/Up0tvv2Oxnudzyv/a4LquRreL5fX8U/AwpU7u2kIsZGm0YZRc/jOeyGy bYEMjiI8HXqZgyg1+ySGsDSDYUqTD7pkN8GM+9DChQEqwk0mcZvJYwP4o8w6 0+p6Iu68fnbRQmoQD+d9VXnxbAsZumyjLSKW4ISJzo7Hu8pQ6HcV+soMwO52 pUPHzs3j52PMguJcI+D2OaHEXnoEOMQvtt2z34RprOTym2zG8WtObx9OdAFH 1FNHi/RY0FB5nP45axyDbO54FutSE/S+/Oe+EtyEwRMn3/z4SUG6KO/rv1ha cKri6tWYqHIUTI819CEvY0Uj/Y3p/Fm4S1/GzMVXh6ryKRdkF9rw5ARX54HI Bbh2072KtnEdRtoDrsokduKq+InhPwe2c0hub/DilVUcqVpwsHK1h+XD7Xob LIu4zPOc94sDGVsSAy0Mmca2udpI1ZNYhtVJYfsi1pbQmnj7ylfrIXgS75+w /1w9/tAqVghiqsFdAXfPzOylJmzcu5M9/zkIfsjyl/cGlsDnz4YMu+/TER4p 37Nkf1gMFaYmmQYWXWCo91jvZuVL/OdMZ8ev2gY3fzh3XP1VjATCuvvbtiG8 dcxAStCWAvxSBowtDYPIN+rPSKpeQBf6FLt62laQkNv5LT5tGPhf8r18ZLEC umMROuLEdrxw6NfZhLulcGWan6hd3YMXGxMi5cVrMe/Ayzd6DGtgkG+fTrId AHHtr7Qx7fXIY+fBdrVhFpcGaHbtO5GIhzNfdH/o/4OPKETZ+w2jUCB8xKjL sR/spB59Ov+wCLQzdTgV76/AfNDQfc0TA5DYz8j6jnEMk1N/39MaGwY++/NO ZhyZoOhdclhZtx1zL3lVk0dWoKpK8satXcs405Q4HH2CAuI310IVmabAYG/U uZcJr+Hc7NtojvcI1B/vM3c108tKXTgR1rdKwkQl/v8WJYchZXWjtUMnEz7S jI56/B4A1U1Vc1oyNeH0s+C0hqJ+tL3MKcO3OoL/NF4Y8FD3owWrV/MeUTJY DXzQ23uQgjxc7C1BozmQmdZi5/9uBTxnhGbdr6yA8a8287HtXDus7DfjmNmK H2TjGQr7dhCEo47s60og4y1wHY/7N4Ie5fJ7mWQWcC0/77Va4Tj2r+O43f02 4FZNyt9TPQ80EfyqL9c64ZuNV09hQA8+WFwzt+WrB6kLC8trlSsgV7zr4Ny3 Kbz5x4c7SXsYM68G99aLUMtGsmWFKzpG4409xmHZJ6YBhLiOLT4go3YlFwez eTP6ZHVKN3lOAUt3ynUdyiT+ukrvvHu9AxQLLJjVj0zh4ERN1TG3Lrj9JI2T 7eEcLM3KsuZotaIH+aChxVsytkqycJspNYEat+PwmU5a2bbDhvd2hFfjz/N0 XL5O2x5Fu3+fyGYx7jx70q46cwafLm2Z6FBt83eLSGcd+wzkWBZ/3Dk5DubV Hk38toWQdL/9l2ZyFewnR1nNHR9H9xqj2JYAKgKr+F2aJN8CMNl9ecNnvBIa Vf12N71qhR9VT4vof3xF40dZWsPKlah9q8mSJbEFbjqySnb6dYNkrrFUafUc nDUrV5hkHEZbtqh9rhw0hBsCklaeyfWoW/21zdi9DlMK5hlsY8fw1WLmCXEm Wtl8IxH8eHMOMoq/mmmk1MDMFZ1JJqV5GFFqy03dOYZ0aVq116MmUM0t5p1c 9xCyZGtbyt1bBhYBVlofuknceGd25tn9HrA56zz4/vsg3jhWEiz1ORkUnFIK PIIGQLqA11G3fAbtYswJH9yb8cC4U6nl4TQgnrqyy/bAJPCt/mD2lJiB6CNd 9lE5A6hfOaQ5EdiDkkOPlPTXJmFoenHHK+tmUGOP300SJuHRpHSmscp5+KD+ MSNXKgptOn5cswwnQaVT8vH+yGxQv5wiNDYxiip7r0bGfO3DLIrVgZMdozB8 k29LnHUU9O9XNqaO90K5w219nrx6sGWbMuB6VI8m1+PLL2T8Q6cvr+t+fqFA DFfZhTqzYtz/+u5i26EZkNN48vFFxyb2smjQxRUSQOq0sdJ7PmrCuL2yxswx EubpVZrpCHThtb6wAqJGKT4qa/nRvrmC0yUdsfan5zHloT8zD/saplD9FLvN +gr9k0NEc++toKmXyeEYIzJIpl0pkMwow1ePU3efuFUKtIe/VIhIr+BOA9Ok ZxMTEHPvCcQfn4HdJhNmL572Qz41b6VQ5AyslP1r+R0XgbGMtX+81qZx4dOV PWNr9Vi+szKQbLoCkXW+jhe3+yiHeFSv3ncKpC8eddNRWAOtik90oVsUCEt2 J3GwDgK79RKPz5cO/Ko1XZu/cxLpaxzGn3JWIvNXVhb5k1NIuy9E8eZ/W6h3 07qo6gg9weXYmzZNpmn82+n8ikeGiFtWSsbFSXNIPlv2o39rEg7wu/Zq3VrB yvMentc1aqC9mHGlMCoaPzpNB+duToCY11Wxms8TEHz1mWv34TkQ6HpZn6E4 i0L3F4O6TPsh0zEiL3hwDCICnNxch4h4+bv+a1fRNVgxIu696FuJCXMWBoVp BZAhZp4fM7qF+tk3NFP7u0GP+l9j2dM1iPU++3G1dgiHNEP20dEMQcIy4T1D 3hpGxAYERCSPQsRlupH7ZZtwi6B57tXCCorevj9dETiAly4uviVwr8Kkp66K cskn4N/nVxer0w8SyYE700pHUEfJ/xLl6yLwv51M8+KfwDBxE/4Ujw3cSNnK jpQcw4MKzwssea6h3tLNa0VKgyhKw3YwGqkJXh/o7POfLsObi1q3E6NrUPH2 X3afl0Q4s7TN4g6VECi/g4trxzJkH5lVKK7PhL8uYU+oEn5Dh3WjJ+OTbESB n0f9CFSyCtdcdT9REA8Zld5L3ebmLqvv6or/FpHZSkT6LF8HMlknrjI96kXG hqs2zUx18CTJKaNsg4yGlGt8eJaENGuzOzRHWjDf4JSDgtA8SDEFesvtb8EI oVNCSqwDWG9JI29HmgTD0rZXz2ueYOSviOtq9+fQW43D5DT7M+QRa1sR2qjD f4+FWMP4auHneoGlATkFvz4Y2jNpQcYatjFmtb0taJwaHJTzbwG29n7ZZeTW AupKZXtDnZLh6/PD94ZeT2Byld+TlawyVOW9rLlHsRJ3Fz/wi7ejwHLVcFO3 MhWB8VvxnDh3N1zi8zG8w9EDZ/ZVaBw8t4p8wldEQr8R0f6BUp6lcjsYrT2c DAifhuqblk327N3o+niYM3rPOL5u3GM6rtCAdOaBO68/IuNHKvdvmi0kLGTb vfOn+iTk5gV4nf1QDH5/498qK5Fh/gJbRnxGI0Z8HPyzYj6G4z8k/L3cu9HY 4MbAugEJGQJCnFrvlOMHPY/XxpxLaHae/dPbNSLUEMrq5BPXAKWdXiiwNILw 8pvauJuDUMbVdVvMOBO2iyTnn8AmpLAsR1/dGYctg6eDJCNpCd96Fp7q3BmA HIMVYa2jjcgItblXC4bxgfX4Xf7VOehcOdC1sr8Tfp1i6WcV6wHSJrfHDucm fHn4wT3Rr+NwtbOThnpxATK+SUhKp32Aeq4Qf0HfOnAWudvyeHgczjyJD5MI 3SHL3BstXGvfDV4NMrfUYAzy6NMNMtx6gPEae2na53Esr02UDTszhsvhDqza NhRwKKnQfvZoAXVfthWe/92P7iQu/4u1G9hgRaar6+nAmqhUM4ppCXy05bL9 e7gEZnQ6EqlMO/B3+IbZe+cR8DyVJSP/dBV8qW0K9r7YwKKy5t7a4il4+qHe 9PiNOrSJuts4d49e9qNZc/y8KQE4J2wt6l3boJA14szO1O/4KXZLBev6YWrL 0Zaah0qWbfPLoZpKChZTa+1/m9kDGlWt7aF+9SDvjnepRCaxRKg+4/g+Erbt LDFTMKqGprkk6Sb5XjxH+k8m69M46qXo8gquNCH1ruz1lweoZXeq3uG8S9uP CoUeTsPmg9in/rjVWGYOf7xidXaxRXy9NMT96lEyfvkT/osnZxm6v11eqX5S gg+LJ9VrPMbAzlGKT5lmGUoDIrRjwt9jVFi29VDtDDz4x5V8Sy0N85zauTTt V/FubNAnKeNxiHy+M7Q6ZBAnhQbPHI8gIU8ptarKowq40etN7j0yhC/WYo55 9G3Ad+7Ue5RPnfDO40tHm/YahL09q9qzRUL682aSIX7b/e/mfmR/YCGqend1 Zf0mIendmbhvcivIp6WmzyQxDys9p5RKjOthUVXcK99+AU+dOy03dXcA6gU6 dfvOUCCiSDf9b3sZ0GSNRnCPL0IS+/G5Aqts2HjXciOIbRl7sy7Z8FwbBScj 9NLK6QeVU+D3YLtvRnJvs9R1EfCQjHy740Yn5qWdPql8tRW+UMcavWBYRMUo 37Sx7wvAb/rn90XVDXCp5DvSVBYODr+OPPLWLcFaRTG2hNAxYI29Fp2bkQKu cVZ//7ZOwowm6hw6Rk0ITzpOCXg7BafBN+Hr7CJYkridB5dWoZF4M6fuRRUs 9Ns6fJ5cw19BTzPqZMZRyISR95RZ97YfB7hWdBBBwn2ROYC+E6Tv3ys+QZ6F 52X73piuNqL9zwKTPf9S0GDXL6Lj00IIWzny9RHdADIacctURVHJtjFV0pOT l1DtpOHmnd1DmM9McTBU60SLVx5+R3WX8Py9TyZFm/MY+oZDxVN3HO1CuKrp khrxgOdPTkGbCdS/syFG1TYDju9eLAZ/pZKtmXHfsy+nE9y1jZVjFIlY+/FZ Y6XOINhXv7E1DmwCTSK10iDdLJx6TZ3bEpsAV92e5vtF16Jp9yp74+0ikJd/ /UxNbRhyK0xdfbtHYIMSHJkTPAS27skCGfELcODJlcRXqxXgYz3TX+VYCGdq rw7YuXSDnJdQs4ULCU4/1vsWcmgGR6y7ux8qRaE3L9OMbtYQ0sgqaUXTa+Fx c6myri8jyFpxdX3jez1eljWT+RLeDPEeJ0VpnfPg/dDdvwxXB9G7UuV4nGg9 1GSZCUaMvsFk+lUy3aNx0PTrr2cdb0LlsucXvJ434gfzorqE5mmgY/n+rcV/ DM6/ItNYlpXhVpJVk5LFPJ65Rf3GenEYAz8PrfAJDkPkdbYCVQIFtP+d+Ki+ oxgbzzJH9Men46yZGVEwuwmLYzqklJdbUZ14dbO1fA4DX35ks6HtxrvyrZr1 Hj0gJ9r0s+3bGmjnWOklWpIRlh5+fjGcjLdKzXzVD5Nho7g233xhe/653QW6 T4vwZXCsc8erFbzbcQmmIoogQIbrmvmeAuRgNy8U8B7DJPXRvTK+nRiQXZf1 HOhkE+nWz1rtGMfam0W+8U2LIP7z3ACXbwwYdUxvvAmagT3KSc6ZCZ9QiGr+ 3ruUUfR2Ob4mEd0CJ8/cYuXiaYLWQ4kZ0QNtyClD83bmGi3hD5+f2+Odc7jY WP2t1rwcwsm/iw0jU0GcJTj+x4tqKLstxFNGHsO1fYZBp6nbkDpEzsnXph1s x63aV+h7QMdJSXqTfwvlZfRvPnoRB/x/ffep8q2DNeMwi79RGqotPGpwSZpF EbUO/sTjXUBoLpfGunl8knzcI+5dE+z5JvpLsKkZJioeclKpzWOW6UjOXN8i 3G0XobogOYFpl4SSJ6mHINTzUuSxFipZqYH9ZteI+WByLWJ2LmoBuB5RifiF 98P+0BCPWxdIeEReQaK0kIw6VMvn6+cG4Z33JYavpSQwW3tk8Sf7Cz5vJ12c 9R2E1wHhaQdsaWTlKx9/+mUwhIJ8vEF0c22gxenH3xBGJVu4SLN5gncebs6d Mzm80I2S1Pn/uQwR0Eh1tvDZqzXgWpcurXPrA6PxbzX+WfSySycrM8Y2eoF4 w7/vIy8JT2+2WVk8o5HVJ2o2jnzOBi05z0inPGqCgX/RkTues+j6N8jlL900 SBa7+R8aWgK7BY6Sdq8V8AprFHB7REQ5md+POLUpWOac8ao7bxIT/572VvQZ hv1PpW8otSPwwYyz+Fwl6G152R0ZDARZjU+K9hVNeLT+EnXO7j4Q0TH78s6A hrB8bPJ44DQV4Ti9UjdDZx/wfPiQbHOLihDB+yxNj0JLeHFutnUtbRUzLlbv fso3iNyk3cVZwhWQbjZ+gSdiGqUHvQuKev5iIBEmW9vm4ZyfpKj4yAJeaask ZZW/g2SCYIDQrnVwYopXiMAWMC1ZlKrUmQK3S1PWZk/rcIMpbF9p/STQt4jF Oi2QUW6xhXZsqxUGiw6Pux6dhECP6Pkb136jyZrIlsJ2T77/yXGU2nsUHm4I X8xLmoRZJO4WG5sAfx5N8hHKAPjeqH6pGtiBb/QtA/l75pHh9nlTS59urL53 RUz+Fxmmb0QLu+TPA69dYxvfbRIK9h7paegphl7i59qL9VuoZO9x0zJ4Caqk O4M8y4fA8uVmjLtNL571GJx7fqAQ13r+5p1wXsKJvseNxjeWwPaA0SHFnwuo aj7069fTZTz5Zvzo+YdbqPZ49n5GTz8wtb37rms7AMYC4w88vechJPsN+QbP ABLVn/wTp26HJn/6iWekUZjxIez50ViH+V/YJn+lr2CL7f79qvrTUGydeuXN mVo825r7NusQBfuthx5kfdjmllBCs+oFxIwXqy47E0vQckCmcfrrMCbSn76r ld0PnR/+C5D53ApbN5m/8VVs/+9bM9yuAhOo4Xxrek/7Ijz27qy5FNUK3oU5 vYofyKgofj7oOHkDGGxygowlprFlMX9+oHgN3pkre0sSY8C6Nt++NG1o24f9 DYLDylGWc05Ez70A1ekTqC5VL0JWQ1E0RJfDrr7i2o28NlyP06aStmjDqGrl esuUfgCrBjvbX62wGF511evoPKx7HWxwFpkHnT1kAacXjWh4tD5n6mojkP7T av7wlEY2bEnnwuU8CmhAd/6d8yS0rlj/cr68EWQ9tJXWVQYxzYHRK0qwFU5V 2AfPyU7g93NjY2ztPaC72HT4+C8K5jD+kC/5QcE3zfSuJKVC5FEesXw4mIFi HTwGnjfqQWu3X9OMFBmfXmBNbfzYD3X/RfftrupFWxX7CQb3Drg7UnxL5vEs JB4w2XmejwDfRvxzBU9lQrKelyAv1xp8Lfj3g+ELBVfuqxrLTK/iXq3YPT9F m5EkJFmxnDEIXeUE1bg/s8B/mvBC5HI9DmatlO2uGQTvj/55Xk0bwOwUEMHQ MICqV+0WmLbv94D962ZEMgXt5t4W3W9MRgkpXeFvb9cw+q2OwpGzI/g/nbyT Ow== "]]}, {}}, {}, {}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{False, False}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{True, True}, {True, True}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{None, None}, {None, None}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotLabel->FormBox[ TemplateBox[{"\"\[Rho] : \"", "0.014794794794794794`"}, "RowDefault"], TraditionalForm], PlotRange->{{-2.8716449579032295`, 2.799779551966529}, {-2.9744045153205474`, 3.9850499736495086`}}, 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], PointSize[Tiny], AbsoluteThickness[1.6], PointBox[CompressedData[" 1:eJwVl3c4lf8bx60kqUhaaMj6KqWUnVvDSlJCZok0KKMh0UCispKRSFFIysjK vo+9997OsI51zrH3z++v55/neq7rfj6f+/V+vQ9a2OlasTAxMQ2zMjH9//kd DKe9thdi2venJV2Cc6hr+Wzz9f8GUMb0gd0ptSIY/03Sp+4cgV+hDd71jyZg g8ngvYr7NCi/INh5Q2oOP+bs+pSoTsIidr6cPCFWwpYj98w3tDARjMVvnUhP JGF8hUqsAMcUemj2y/c/Wsa/AidV3VkGIJHxM/280QxQL161OqcZiFUvhHYU Pq2G3I2LQXW9RMg+GWqm7d8ASpc8pn7v6gXze4tR25Qn4LpKt/2F2lnc97ub PSamH7Q3/uTN31ePAzIccnPuvZhQDtM3kmtg+d2FRz0dy+Buu4VorduMnS+X /j3b2QveSyoa+ZqLwOe5/W0hdQVhC80r178fi+OsV/YkzWCYMyvJJnoJMloK pH9iB177PfIuKDAHBEpyosXOdEI9x53OkLZuePfwpSFHzyh+vaMgd3i0C0KU q1kVnRAPhQw+6t9HgcO+S18dHcdRQuJBEIvvLF4a8M7xTWyDXJmwAw4MdkJ0 6ubPjEclOB27T2tlpREjIw5Y7c9/gzanX12gWY7gl0MvvysdZiKcDY11PDs3 Ayk5JziKtedQ+uSRfMohBtjWFUpfOFmN7h3PZFjVB/BoRbFjQ9Yc2nI9qBZZ KsUEHu/HM1kkYNW87VlCHkFTA7X72bENYOe4xHzZfQiH+MvI/O/LYbtC13ho Jw2/01q4FeRSkSARxfL+Rj/qWrBsD8ivwYD+pp9n+oYh5o/opem6QdAtOmor dIGB7goa3DkqM2hmdVxN1DMVBfWzwvd6FGHYMWWWLE0a9tZ48fJ/pKHY/HXT fabzyGE2r63QFgsmBqrlP07NgUh0or7kjzZM+o9RMGg9Alz39dViFPqQ6Zfl pcIgZkLYuZZgYS0mgli/KcveYhIYV/h0pxu2YwPH6g1Rpx64alKUn+pLAXPl DaKx5xgwpVB4y5M8D0bt93mnjD6jX/Z+u2erpWj7zkQu1XQQ9vj4PrmsRsPu g9cfuxwegWRdvkBWtr/QZqX8Wl+UhpuHX4//de8F7akI/kDtFnh8/PEVM8U2 eEX5xWB3XYTmt8+e1TQMI+cLi7C2jW1AbD+8dTx8Gvtr+e+JN5Lh0Ip09EPN OZggWadKkApw3NOM46TNEKRJs7JFO01D4pUvlIzrRZi92CnY9TEDy6ufaMZd GEY+o3dLz3cvov0d8bMTdUmgelb2P3aZMXS/RzThjmhH8r7Z0Qt0EuqypMoa KDTgU83L1wJ6W1BG39ghsJ0O+U7+JF5OIj4UGFttq68D98Sa02K4/v6/L8Fb WCtASPIjiU1hGI/eyHIN/DoIneW8XQ0DFaAmnBQ71dgBQ+cmFQniXfjg7S23 BV46zi8uWHh9S8ebnmuvIZeNsDFAbY9g4DT4Vm+P8LJnQGVj1UnW9CkQKNI9 uqUpEzP2CjlmDQ9g6+k+xf96B/B+wmn5Ax/GUegkGASUzsAtuQND9rG9EEdc 0l6+OoZaH4Unbov2wbRo6YN7Fwbh74G4lrH2GPjvu8750yc6gMJ+IVghoBPb AkuDj6v0Qku8HtVfvAPVtlB+l/uXwZf79zn3qA2Dkmeo+Luvs3BHuI/bbp0H TNOFD9gKvuK7Qo2UpFQ6elZddt6RTsGtZ4U0Xj9agW2Z7s/1zk2CQGLAzS2b GUDa2r96oroeQ0o3JZVsr4b7i12G5pvoKCqn53OMsx+P3CyaEQgkQ3H2QMB9 lkHIsv7w9svDYRCV6Cu09Z/HvBSyWrnvCDBp7GXAyD+4ZKKnSYicR49tn2xm XxDB/bnq6cmjs/A8I/1vclEXnM6absui0MDlWfFRcj8Z6q907FULmIUtRSel OKlUMFs0SOVOrIGXfDvFQrduIHRHPqufGeyE4CpP5fSCetC56kSQCacBk3kQ ReT3PMypasVYfmVTYX3xrTGWl0mFPVZPI3BgHkpZbplWb+yCj1z/KmzOpMKT 9F+tXYaVYNk1bm+WRMGdpYJuShpMhI/H+E/u0m/Ct9/k1446sapkN8aH0XOZ VK7L3TawucoAv9uiRr/aW5Az3od4XHgMIhrVYnwypnBx1K6fviUP/vHjrgRk UtkSIHpBWXD9O7HXfQK/LGCJ/rlPaXXjcDL77iFjQgtk04IzzjvWYbhV/69p 5QU4yzsr4yQ9CDL6LYmeD+Ygsln+rNSuVrTR3/A1fV8R8Mf77f2yqRY/ilx/ dXGZgt06MTzZZCLW7tX4veVFJ5x2czSu5FsFraTwkhcibbiaLhkeTSSAjLLC u7msEfirmrEs6UyBfxvzXwpnVKEQi9QFtR10UJJ1PHxmfzZmOj84k75hGQ07 v5V/2JkHirq6Ols0JyHp4+OtP3YRMfPJfPWR3k7gPCZy009oEXdXmL0wLO5F lmiXo+oSJBRjV9qnx0MDUdMX7IpRQ6iv1vjugvcAKGcM5PCo0sCqX3cgfnIW nxebcl6zmUHybZ/S0SPNKMdlftDuKR3S6mJOqZPm4K5RZfRKXh0a/52TmuCm wPNPB4vPVyHqfO3elqdXA+fcQ65tdKuHk11GFb+TlkA05X7i52YSzA2zdc9z tgGUaG69YEuGE2KTsYGSlch1cc5cehcL4YqseysxbwidrgkVFnYFQvXtKlWx zCBkZww4c7vP44DxcODgvxE0Uvb3uLp/Au3Z7KhOnVwqN0OeZy83TcJkkJUd PYqGf1+H8cRr9wAXadf3lpVF6Lx7w9piggEaJRtnc8iTuJvk5Di+cwwiR2NZ 8ld78XJwQpOMWBsOPD8mbpYwjT8kpfVmz7IRlrq+WZzcMIPNDxVvF7pNwGKr Ot0tcBicb2nkNPrQQGyS+6rzGAE8c2yFfgVR8ZTtog/HhB8O6y29Pq8yC4ul J7ayn/uFhH5Rbx/pSfxaw3ksR7sUB95LO5h+aISWnFsR3P1UZPJD5Rb9Bfwi Z6zvONqH3OQSvR8PCTCp2G+7cn8cbyWb3vTvn0XKRn+dgtQetGx5eMr+XBf0 v/su8tV7AR9Hnzbgd1/FhJAhV2brQjyy9azF7AIFv86xuft6jsPLYKbTL6TJ wOXpfZdCYlHZ0fL7+RucAsfp/8IurM2C970x0XRjKnILM+tdTaXhDkGjbb6/ 6Gjy1F/2gQsDyhxEgvVOd2PA3hxC6MQ639X0D56ST8Vkl51M7lxkOMqrVRRS WIoavh7DJ3qbUGDuodjAlyKwSuBuS93EAPNz/SKeScHwxi3Qyue/ebjB1B7S /GkeuDcXvZEqH0C9RTGWuOlBrLqeyjh6pBeJO93BILQd5piPBU0TCsDk4PYt 45YbVHq+HuLaXEFYvxcbXtT1vsZpNx65fnIjvtw5o94WXY2S7ypOhHNvJHDq 4WVnpxEM0n9JTOIiIdvKEQv72VmI3zuSF8NXgfrGn5pnvkzAXueSZMeZNfxD uhox2EBDOw0z89XYNqhljB/6tVIDgTcTN0YEN4CtVEOVuk8F+O4aF3YvIUFx uZzw1q9dEJd5e3n0ywhOnd4S3X1kBK61bfUpklxFypxwgawxCyHbk2OTADsD a/J38pYp94P/6LYNvuQWDO/WbpWxoOFqaoDhkaUSYNfuyrQ/QcG9oZ5a3NLL 0Hmn63yRfidiv9754qF2tKQ6vX43xUbYlSXU6Fv1E1LtQ5Xe/JxB7Rdj4i0B c/hcSfWs21Qz/nAJoDzaToTMaXrw02t+sNWk52KTZyzcCzZq8y4ggfT5gzSI p8LFha1CNql/gCI9IT11twldlxwbktJnMcrbZSbKtAJl9v9+xZxYBwqysez9 6mNo7pL77UzIVzRqjZvysK+CyDOEq8nclahxTW4s1b0DhCOysn//7sEw4T+8 XoqTqPvnTIEsdxkaNxbuJhweg9xXdr+GiERYWPU4tTW4C7krXk/Of2qGBYZg YbpAKS78+KPFQSMAfzBwnPUax/0h3dUzvUMw/5In4KDhL9gTcqCu8x4ZfWw2 j8c0jcFD8gmu4ppJiOu/xzRi1I/JK2r+pN5aGKdtuSO08gvLTghFlK57jcpT UZeKdS+OtDj3ZPXpIEyU9OoXPOhAW1GDRbJXD164+2h3s2k7cG565MxXS0SL zmMi3npjcH1P9DGOfwNQW/X2lN6Dalh9rvQKBadQd1/a7CS2Ye9h+U8OwiRg 2/jVQLl/BMS11pL/E0zBTvG/B+WZGXhzdmzCOoeCn7RnYubyKDhyek7JPnUY zVmvefLT0tApRHptZ/cgHlJ1k5QpG4O7idttOlo6sGny0s2ML0TUSMjxNS// hVus1NStucm4W+bMCNozUHPbV7ZA7im4Yya5nfM1BTxrXu52WyzGjT8j1Q6m zYCqy6sjJqcpaBlqrP1GchgONJ8e+rI+T3XCnF/eARKc29Xac3Rl3fdif12Y DpyH6kU5zp1HekHw2vyzq0VLOPgr+ckOj164WuTqctGJmeD6q8U3n9GI3PHs xrkV/ViUMnjCs5EGH31Xb6X1TSCBs/VgdeYY+LUb3etcaUellSiZ3rh6sL6q 4vVs4yA6PHqY5fclGe4/rHc9qUmEIX/ygoPHOMpkaBpRaENY5tstODDeAjIc Z500JEuxU3e3otQsEVVIHCYiYTHwp9OZS2I4CcTcBP92CHeB6M8vAcE1RHC9 GNAu500CJ2J0w3NxGkae4PQeDpnEt+1ciZ1eE+D068nZExoNqHujReJ38QCU WB8I8P63AtE35dk7No6j2d+oym0xvbjUPL+1CyshpzC4gktsCP/pCN41Ms7G Vgfz+rGEHnBJ/HWKfqUJTit/27X9cAuU3pi0kQqcQjXPzHdfZTcQnvDMRCXi NOwXD7o3c2wePl4zaKzRrUKH743TDw9NwhuzwE9pHWRg16f3qIROQmrwu2RS TDXMmulLla2fB5cxc2/NJQr8KrswW/bxL4TXh/lXJwxBue6RhpuPGThp6Xvr 44sq5Htfcj85uQHrSOFRl5wmsUrxpsZ8QCkki7Vf37M0gduF1BUSfQbwDF+2 WfidNVxJXI2tdejAcl4xeasjg/AOKyU/dbeBR+3ecs89I6DIGpglSRwD8yHn 4ETxFpzveZ+u/bAR5jb2nuIKXAbeTRyOKpI1UM7Ma88DK8D7wXtFtGICTmjS /R87z+BUZZ2fUvEAnuvYIFp3lgqXvNhqWO2mIF/Dhezm0IgcX2/21D8YBmLf 35PDuyYgd+FxjajbKOQW7DEPbZ9FV+ULS4NpWcC4aBWuNTcOjuEaHZfoRFT9 13H5n9kABjpFPtN5QQEFGf+n3woaUAX2iR2XSQLz4zyamrenQCGJPYFmNQRO V0I0TEnd2CwXXJIrswyCvavP822ZCGkq7SFFwq3wU5jn/J6PPVipb71JVmYa SgR3CKXH0jFF6mNs/EQTPhA0My+1HcBg1w32B3lGQSz4LdwZXYbEm7Y6uo3z WEEhDo1ZrqDgxlPW2mktuEXfr9/lLxHPHJx5m3CrAhgjVQshsUVwVUvpfedC I16zlX906OwaGm/WKrvrUAuKjs3RQ29qgSettJKa3o3aaj9VLpBG4bGDlt6T vRTgyInK+HC6A0NLd5yxEJmFXZqS065fpiGSSYhm4PYdT3KJvDRUowAhxuqH hCUZllp5uiadSeg6raQgxzID/LpLr+Svj+Hl/45u7yN2Y0Xki9ZFCSooanen R76gwcFbX5+GfyPDtlsWv09pp0FeCurcMlyEdqnZNQWOAXz1+KhmxYNxmAkc +M61ed3/Ll5pJHsOQZA8aeX0gZ+o4rIoEZ4wATEZTKnHvKbAo7zZx2OICua6 6m0ixbWAe8Ob48fbgOvff4uXrUPwCqv5g0fpf9B0x90tXrVzmGd/OeH4iyn8 VxnovNGiDtlDdOclbq97WB0vRxixHIzopwa2DA5Cmb+1Fht9CEJZRr47dc9g ttcH6uKPGTix2fbJiAsRZEek0pznpsA58OYaqRbx1MOaOM/ybqjc+UVRxGwe 2PT2yw6z1mHTTreQDPVadPnKrZ37MBYX5B65XD3dg994ki5yBlBgm6v1ow8D qzjbqxBzqmUGQ7Qvqu5+SsD322pSxDtL8AP3yXrGcDTYb/+09unTMGYIqR8O O9CIDsY/zljnj0HOj1eDi8btKCIxsrWKbx5cwhLu3LlNBPGso53TYesedDu8 Km+cBtuiQxVPMUYwhCb7iSksE8sHYPyfzkaC7HHGQZ5dJORxfaAq8XoNxysO iv8jZoNSmed7LzcSLk7bFaWaTqMttS9PmIuIOxoaifu6hsHsxi99vb1kXB6r +t1Zy8DFKwKH6n7MIpXZ/fq/GgrsbQvOV02sRT7jvNUD5bMwqKiR/+IpDbbP Dnhd4aPicrdT2bXOZPjAJzqj6EkFodq0W/Gqs/Cd5/PZFJklzGelxP1dIOOj SJ7RA2mfMPOC9x/fDncQGOXcVSr9B0un5nKYvTPBbqJjWrCGgbf22ND9jfrw fuz5edcPhUC4fnyXTu0CHGIXUXURZiG4GlrMvflDwpxMxZ73eQz0CVUoN6XN 4L+Fd5zjz/LwRyRhuPRWPwhE3/68j20Jd04eqxYUZyaUOFwT2n++GX5Gz/8b FR2AuL3pcg+q6GB66MUtnfgfoGN4w1LfcQ5sFey3xM+MQ/2N/C1bF6ogU1y/ TUiyF179LrjN6zoB1MoLQYZ12agrNewslzUABwNfRux7ngP1jzZItB4Yx8dX ZvtijWiolkpTzoocwQ1XvNw2hXThnYOS4v1JQ5gcc412/RIJvw2m4bIyET+P 9x4r38jAtIgSE87tDIw26S3JGMqBEu/ZINMIEmQ8vnlpbLwZFVclJMuP/sK7 p3+d1Exbz2dXCeOZt9PYMX7A/eePFqzd9mb+810q6hpiRupoOfRkL3awas9D O+Ga+qzYID5p5LWT51qGHuMcMcmRMWiilCULv1yGz0mnSzw4VuCPTHmH5RgD nFmrbs3KUDHy8H+zLMLDKP6mUYrE1A/VJVW8cjsH0WIsUN9vnXNP3/5XZlz0 BDUzKCp3vHuguba4medrIxaKGVbcWc9d3T+uxtlCdHzoLZwj+WkZtB6hjc46 3xPl0vVksxjot/1VpnrHBJZLhMfTpebAQfuCti8LA1LOf/tgdH8EllX19TJ2 raC47NspjvBaJOuWrqbtZCGYp32f2bhIx5aCT2VXdOjAdchGJ8NuHndmJ1Mq 5Qdg97JTcceLcbhEvpjKZvAR6g23bWgRKcHPHAXSF4lk4GR7v+BAp2Jj+n+C cQPz6NA7z7QqRMSd8rdHciOa8AkhMm7HvgGcmCNoQBkRCaeeXB05OQvXBY75 ttvm4d/sAam6g+Uw7OTJfmWdnzZ36b9PvVoE3ye6Cpe3jeGtER35+NgoZE6M 2v3x9RTUS+eIPksiot4HwnT1MQQPNsuU4xHjIP75r6eg0Aw+ZFzUjBeYANsu tsH6TX/B879onvhTBVg/xya+73Y3XErhZN653IEnpWUdNj+fRCH+DmelFiq6 peR+MUsowHHbkMIDh6qR/YNb+qEAKrjC64CefT0wRrXbIf+cCu+zFwcfmQ+h t7G4vvrBBVhp3DAYzSDDqxurLNWtgzjm/rzsG3kIXqjtP1sl24xCwtq5/htJ aP67nJh/moEx5ed2efSN4/FvF188fLDuQ/Vth+zjhmC343P34sU2PDvuXM26 cxRfXDih8CyambDWvDqglj+PVpamfkUJZPjFmcN+6TIVyw5du6tkS4f2yh3N +7b2w5XVlXc8d5og7EVPIOEBHRSEF8PPbGYlpK1nzDKJjszn3Y0CJ8fxabjF xGDoGhZa9Cy32g2DdWFCRLV2HTpMdh3qjhrD5I0qbgux89hnrHj13vt2LJr5 Eu7xoh4Ul5ZcWa1pWPp2z9qXTaV4/DjLIaWOZSAQ7l8q0J0GwU2M5IjgaVSO 4k2qcRmDoL7tmp2NNDRVjZC8tEKFSmXR+UWtKRj0kBws0JrCkrWlbNJwMlT2 KpccZR5CvlliIPX3RpXKxgj6zz10ENzh+7xbZRRHZ48+SSeT4etv/Hzs/CJG d0T93EFZxazTQWyX301Bxd1r+93sB4FJ9nLQ1UgSzEMR5SpzIOpluBuUfJ5H pksyExtLicj+rHfL14tUqE/167l9fhKqxSed8r/T8Mgh+QOMslk8uSOzeop9 Dsr7Fvc88U5ACVd+cnc3A249u7y5R5kIHnxCKkLWFIiiTthLSbdC0UETlhJb Ks71aqUOl24k3EO/vY3B2Xh74WjNpkYmwpNH4ZRDSQSwX03X9jk6iw0Ztlvk tMkwevC/e8pOi/Anv2ir6vQQ2q/lnHLhb0SSpJfq1af1oPfsT+MX0xh4rqk1 9qdiBkYE7yhdnlkBPbMXsptq4nDz4++lJwwoyLNP7kQJYQwVXFJ6q4Py8aUU iz+37AgKbLxroTFBhMWCKsfS8J/QH9olbNLKrOJ6fmSUsrEPeiTuG72IIGNO R2bSi+nPqDPrHXn0wBSe5LZ/u2FXA44cy2GKeEmDz5e66is3M/CTjH163psu UEpV72t3m4D6vtBWna3lOPnxbBc1fAk3V3akTFisoL8PO0nTkEll3M272wkG gfUQka4+PQnnbX2+Df9YgH/2dLOvV1kJqy7FoWEfejF8502r+A3vYErAp1lk /d781DjL8ZQ8g4wgXp2cUiqGzrZwiVwdx0/HJ16X7BtFnedHxjr7m/BrzuWN AmrNKC8553GuaR4laSeGO9OmUGCsKVoxkATUMdkzF2/2opzrWmNldBP4dZCJ mrkF+O7QdTzzgATpPKb7rlwhQ/2oXnOCBB3N2p9LjfNM4Fsm6pCK8whkGx0X OJxVj/YbI2i3EwehdO+Gq5996HDMkMtu6+tmHPExOT+WRwafA/E9z64lQXxH u/6pzgkYDop/mVZeCXtdrTZmd9CAbh4X2Dg2DPxMYZXG1DkweMaTKmyyClzU 9rjHQfMgf/LYeRPWSYyM97hBTH0Knbf1/tVkbyCMHSnI9iZSUDOB2c5Kho5n 3sQNhO8k4AaP78dk5IfQbJdK0uPKciDnRFU8v8KAKKeTfhmBLZhk6RYZsm8K 55NOqc5VzsCZN1VXAx/X4IjFsQvCqlQQ1EvKFy2IRPxUcsxWcByae6/x3aIN wvOqkzLyx9LR4JJDiEdkO2ocmF88K8BOWNpqSQ3Kn0PumOo3l84ngchUSIps xBRoRQ2kix3uQI5s2y1cNBIoUIY3Tkyvc2226vfIMKvKYk2IMnvGNO6MNdyX 9mUMJDcNZKpxzEBnlGF2wMoSPJ+v4Pz13xrc0L0xmruFlfBQ5veGs9Q5LFw2 cF2+xsBks+/32DcuYnVs2ieHwGl0brxwkvVaE24+92ji8RkicHP+aQt/Hgzi BzFht0k+Dgff1mPm68Uc0Vb2wMo51FA/flhmgIYnoxWqkjjGwFU4Y6vqxy9A 3CUt5rXIADdOlbdEt2n4z1rcS8B4FtINgHzyVSlIienLWiv3o1GYSWv3qw2E eba2EsFqCnSKtTz8zjqBjRbXZkOZFlHVfMHv+M1+7Dn65OMTvglMbdx68UjX +j76ZvdQnyB87+3kVByl49FgxW/budhUPF+Phyo/G4E/M/9x5/+tAlpeQ/tr y26Yyllt4xBhInh8Vy30de1BG3V/9gtSFRD5xMOpvjkXLUcVTmlVtYC9gOD5 MAYFrPqlh/9drsbcms1HJBrooO04r22Sv4JhkbOHFdWpED/cQpo/ToSA3HCh vDN9oHU0PG+Xchz0+oyfNttHgXvjf2LE4obwJE8428UHvTga/r6/hJkGgV3q h7/EzoDV5Z4lTiIDZM4q3DfZPImhD56FLnt3YkaSPNPWskGYDS9M7inLwPZn elYdp/Iw6GNQzIm4LjD7u/AO3bsROP5maFm1wak/pXvjwkgYZFDjSA7rRoPM enehcBJK2ywT35+vwQrnfpHprimUO/+hOqhgBAc/09Kf+xAx3o97If0JDR0j NWzW3vUh78dTOyk2NNCNO11Qc78OWk/d2XgihQr8yTS9d4IdmPb3CscMcw1O hAT47npZDhIQ+TF3qQgrNjk+26owDQ2X+utWFKgQtpYnt0TowRzda9lfCknQ L8AueeXpOLBInvSqPToDPhLU1981F6FcOf7oFZlcuJSz7aJyZRMmPrJ8fq6O hBKNr61TdQpB7WD6J70aCv6+zS8VtbCG9tTZkbaAQWj6E06L3NMIs3ksd1gG y3F5wf+wQRMNKSdWP4+cHYJTsbEXahIGUPXn/aDTQbNAWHhg3ChNRvZtV7yi bBdRkIWQVddGwm16frc0GvPw66FYvvv2LITxqhH5bcRmePsv+Meb7SNIthDO 2b48iGef1Le8f7neOz6EPmtpGIFxr77cH8Z9OOfxnwLj8wDU3rF82SJfj/+6 99HvstDWfbDMqLV+Da6mF0gaBTAT2JOePSFfX8CIJz5srtfZVO4bH6D+1FxE Tn9z77hyMhLUOw75BL1B/21q7QXeDLCvKn21msyqEspEMRC4RYfuW4tXTu3L h+3sKofm+dow++sbwcdS7WDVstxGvUtDs7QO5Z7AAnwbtlxX8u8L9tjPWNyk MhGesW/QifdmoIrzed6fJSP4nszXFfdsFgIV2G6Y8E7CIqbY1oZE4nESk6/A 61loncpKzNlPBpFCun9B4SxY3/2u8sNn3T+MvP/uvtgGVcuNOxySlpFY096m vb4Hdr4Wp5+MzqKZVUCK368lLOsQeLP58iLGmLOUOkevYkxGq+md67koUxmQ SKDmoHfv3+F3VnO4dFFhL21xFptqRV3SpaggNlDa3vCeCqXCat3lYV9A+Zrh h9Py41AW8Kj2oG8b6I6U8JlqLALkBL30+kZHgQqmByP0PBC/+0m0Q3YBl/eI qClltkD0rKKH1esUsL7g7l6RPww1fsMPL0jR0cNuNm9nQTW83CRuKp+dhMyd +zS7W0m4X5dy1vjbPFwWyR4Y+TSPukJWB1qTFlCu69TB3xtTQNrYZp8piYj7 nM1JrpKNMHJRrfG2fCmO7ra5LJ8yjhd/JrMa32mGcvNbWjtsprA2y8j77eZV dD1qQTh/shPvlM6rD21Yght5FVoYS4IZP4G18cZiiD+u/y4orxTIF7r37T/N TFgh2Vj8MSSigZJrn2VMI4bfVLMNOz4OhpSBjz4FEyBHvGun8IQOf6cd81fu jkGxSqGCzudJjCBvGrb5+A9+nH3exOZJh+0XezpFBEi4M+YBr/MHGri57u+Z FCBDLLMSko7QwWRHjtFFl0TQ6uccOchYz0s1s7iZr20w20dv5OeowVnxB7tO 35vA5ip9iT1+bZj1SPLgxTdduF3M3bDKtBwPvKZuOJlSgkM7SkIVaM2gF6xz tWS9359XzSnKTm5GJwaH8daycUiwZH/4RrQIeLmZ1Xes799rnrTvgeMkIJpM ff0rgjgTfnaO5+QiJEiplJxki4DRTW+er82OQLzojQdr/GtAFxH+8FiRjC3S pZ+NFqYwrMO1SPryJFKqpQ8cvTSALvo7V3TvUuH4FkbZ4C8KNjPbbb97qA8l 39vse8kTitdehrVo7uqHYcdHl6rdO3GOaUE9uagYDz+019v1cR5ePzMg2IQx YMtva9OGbesernLDJGCuAFO+N31PaZ2HI3JJn4x6GsCauPLFfGsbcn/nP61k 34YWkTvmNh6fBBVhg0avwDkoPh0dwm3VBNsTdLg/vGmAVsvVvKVbbXjNWCZ1 0fY3Cl3TXcuOGIDKlpQUYs4EEqbFB8LLSWBa3HZ2+4vfyJ3s3BRYR4PRC90m M9uHoH1VDRzW+XH++ztBOXcKZLzmcVNn78dLEmWqfFojGG9kphOpSIRODhvu kcwyeEey/73cy4Avfp0Y2DyI1nez/xCd1z3e9vyS0I51DmvN6XTYMLBTP3zP 1c80COVKUj5uHAtWvxNvbBcfxo9uzc87Jlrwqfqd1x/uMeDiJ4meO4YEqO48 UfH7bTNK2j2hdyYTgdTa2ZkbPQO95Ex2q0e9UPlJQKf5yAgGxB2bcqidAjaR mgI4UAaUR7dSXsZWYOU346bIy0X4Iv5ObYRiJSy6iLiYsjeif+gvra1l+XDn cONz/lwSPpF65n5duwAvcpzY2OS6jFKGgZ+fNE6hoSav3gOLOagWjA4zjKCi uNIbWQ3rGWwxW8lm5p+EUeLBvyJ/BrFhz01tX7UxVLbLCeSOqodSUm88G9c4 7vzttOaiREKN634Z2fKVOLhUfdZBZhY+V0pw0u+cAUOD4x+pnHTszGxVUB+d RpdzeQqyDkRIWrxrrnZxCiIsxJWDtlPAMouV+IM+gkTPqIgypUmMHvnUtKez ARjq8mrXE9fzv0Xeyu5sAxS0X3ll6rCIXrMW1f/cW3FHzSTny74gLHOsmLEf GUSlQvXrY8MkzG6c84zUy8ZvhMwAT8txFL2sdv1PLh1Lpa9tOuNdjBYKK4fC TreC64+2yq3xWdAhnzb2+k8//nl6TN3OaALIKH0nLHsNt3lekvNtnkKx5UPT HI+K0G7w/DGOiSm0OmmRFZTEoqKmG67PxmCANa9VHnPDEhjcWtaM+dkNrCcr OHZnkEHq1LEdZkVLYBT7sLY/PBxkAxNOSbwaAYvgHYbnRalwn6THojKbhspi wcTPU6mwaxdJbvLmEgj3EH/RnjWg0MihSwHJC2BXPjL6zHoM/F8m+n3Rr0Hv rFd75hKbweDPLsX4h5XoszeD+XBJOzon+2o+k6iFV3zLXW2+kXjNRZwlQLoH /9SJmIcXZ+KGokUFng+tGLVm87Dm3hDe+7RUS306BC/dEyuKbIfBz1dWomLP KOgyzWcpcWTgy3zldA6XGuCbX55ztqhDj9SkV++Kc6B8wt02b3EOafdd6/iT KNDeusmsUqELUxw3Tdh3UyHv8eaRx6+YVB4zBRmHbShD16RLZ9+3dGNN+IV7 B1mX0VHlVUH9TANuvjNnZ8E/gFra1PM8AzSgeD1pGrbuX/euexGCb4bg0+7L gooKi2Bd+frDhZUpqI8uYfeWTAbSciRZvrcES2tEFZ4mN+K2CaOXUsbLUGXA xVPs2guD0a+efr3biFlBYTJ/IlbAgmnwJ8e2FYyI+hUebcBEsK79JbkhoBu+ l3ypjGlrRcEpybuLPdNgMJ3w3uZRESSJ7nllyGhBB05XsbO6M2iYoDfx2ZEC SsVuUiLqJMh5Iy8QUtAITtOemwQPUHFIJ0W8hJWOuVcdHmYo9eKpDxpZm84N Yd2ZisUbMTUQdvvmO6N9I3CDqj8Sx1INCeNm16qF/0Gy19tVWQlOwrbE/l83 LYvwPd/UVumHq5irX3hYLbwN5p9uffUx+wtWp5wQs+YfRRmOMeHtESR8MQjX Oy3JcKPLiSfz3BzwP8jUZkkdxOfKuXruCk04Z9J+VfHtEMRL3pv12cnAz2e9 he14GsDRJO2Kgl89eFhohL/NTISthoNWKvM0vH20+mrewRn8b+/sucWPI1gp oOvfvaUVbygauF05RUPrXZc3K8eOoUYlcZtW5QzyF4cOHhStgtvK2fXVm1bR f+/jG1tSppHuKnV8o38H9u2gXw2tpkHtU3+uG+eHwM9nyHpTZS0ebZy8yt04 ijxFINWXV4WNHBGrr6enwauOh5/+sxYnaiPtnLNpuPF8hnxz5zRQE1r3xueW YtVdZJPjHYQ73fINV3mmkbPl67fPHotoMFpcz504gI9TKp8xrdJQIOOkxYJH AQZXV2hVqIzgg+Wgvry6QRRkGFG0NadAVuLeSSqRDpfkz5zJ1G8F4RkPt9QO MuiEeZWGtLeh8OZjeS9yWpC4V8Fm68AssiypuLBdmIR9apr0nlU2ldy1d3Sa fyv6JwhMhLeGIsu14m1vVTPBKFRbVYq7B66LRURdrInCtisajHM6lTgu73Q5 IH4GC+WO31vgK8LlgL/ZDkwMWN6ne8HKsQZuH5UtkjVZ5+jdZ/kGO27CP2bn u9qZzfjad9VSmG8IToYoJQn/ZuCuw7Yf5t+W4KPAVXu54EbwuS65fJ2vDmV6 uUPMHoyCIXH+t6ZOE4jSvM9/ezMDO6ezj4oaZqITswmXXCgF/W/oqTycWYbd zF5G9lYp4PvvTOR180V0P6tbnfCLgXQF4qmndp3IIW6u0uo/Cj/cb639WfcZ ++oooSn1D3CRmVcxqbYFHDqdVF0TezA6dHi7ZX8TEof7aeyeC0inbW1O4RvA O6NvzS9doUAZtdBn2/r535bqd8vtmAal39x5ufd64ERrVmmAxyy6s/kQ6C0E vLurIF/+2TTGcvEGGw0zYCE1l//t0iDSulmDPg/QsVLS1BfqqfBJaNBU9+wg sp3RY98rNI3mQ9FiSq6jSHmYxVMl3gRH9F/QX4gP4HyHcWiJYzey+GfnGTDF wr7Ry1beFqPIN3GMSpQeQbkrRdJ8yQxcs2x0DKifQrYhAUr5g0zoGXMxK/cd R/mhu/0NSkwEprGSktrIVeR8UN/2J7cfBGx3fjsZOIIDp4xtF4/VQ9in3EST W2SQuOs6YHWNBOEH9hz6kLUIua2nNlw7TkMbn2nXB5/qgNvlCpMC+19I1Vej tbKl4GO/F4S2pRk8sRynJfI5A9/fZxP+WDiOR3Z+DzXr6wEmqdyuhItj6OM0 Wb0oVIJLodnhiuGpsLH33QdVjk7oZS5/uzbGwMqrfgG7y9OQMBX1zGtjFpx+ 5iCvXtsFbnPpnbuis0BH7v1z5W2sKmWehnNKMdMQ5x09PmY4hi/jXXRUbrMR TIyvbJ1U3KCylnAk73YvGTW1pCPlnwzCYOzgbcrdftD65F7IxtyOPQ7bbzSt ELHjnUWA+fA4Zt+V2W9iPIliBgYnCX9WUWyg58BLF1bC7gnnuR15c8CiUpP0 n2A73N89dkVNvwXUJu53nusYBDnaSzmmCAawKES+v0fph5Y+5g6P+RmUsg0z Df0+j3I3jLuGjHowlr5RVHQbDVWXWlUZv+uh0ja1/ZvJNPbHBXK85J1GYseN /VUHFlDSxA+SXHvgrB+Da02firSxZCetDw3YrxrbySvShaHpLCLGX2g4PcoI TfnTiUqte9RHXdZz2jRs7P26Z/Ob1Bir7Fnnx1N5K1uxMtByOT6yO3MWr18+ 5++S1IcfYrzOHGWhg0Xjg3dO9UMw/+tB8MOHBdia7OGQVJeL6tZNb7+lkiDX 5EK1qv8idpy9mur4jgCpPxqkA4Pn4Fryhweb+SahyrRg7uYyA125HbUiFwuh lqXU9QF7CTbJyzgE8y2gybGoGz8IC5h/rMiNfLULf1oeZPL0HcVhyxCDaN4R dM3O0GUhrKAXv878sj0R4ox/72zdWwS1+iJl9UdJELraxXztXxfw2k1OE0do eIRHFxWlGXC/IGtaVIuCZze5fz/+qAu8CooOXPzZhNa31my7p6rAe38ck33l Wyz4qqM4ltGPqmzD7HMlaxA3+aTNQykLKBc9Va+KjGO/WfFNcZcc4MFNhPtR zXjWIorTebQPt5AOzRK2jiN3x17LKLl6cHrI+UM3gYEZPrRibTsCLE5FXArc EgUbnypcTk8rhFyljyI79lTgA78U7u/fFoCJ/nxbt/soXGdP5id5UZHswHM+ /CkDZlttLJrk+0GSMOfPy9MOFI+LjEc+03jq1yxLgz8Ni77F0oJVBvGvIjHr 341SWDqWrlMoNAhPrCjvAoCEmTMf5DyufMUH6a69P/b1wYE5I4Lb9kW0uJny UvU/FgL953DwXf8R3Fc1Ktx8dA7iSglumg2dWN7Y/Ehfggj8e+VjAu7T4GTc G22rM5/BwneY01W9EryZDj04fLcBaxbGqs+4NsDJ65tYFCtr4Z3y0iONSAZO f7TxGbFtRhp5jzBH/CSU0jqZXxdM4Q7VE+WjAq0wuZWxt5s6hvvnml5UdJLx r3PS5YsMFpW0ngG+wQFWlcNN9Z7kJjLsyHu6/Qa5DWz+3rkhktAHpWNT8s8l m5FYw3+6hWsYdK33Op5ZHMfILtkcAaZc+BKmUStlxIBN6ZY69lcWcFRr4+uD p3shzWOnLPlpG/h0vXyVVE/FVxyja+TqTDxnoqaSF0PD+eelx8esW1FE5UNc CTMF9347z/WYfxbv7mbfbL19GIP0Zk77TbbBHh67xN0pS1AV8o+feT1/H3ZI Z/H0ELFhb5Mwx+MWTOZ3y+OwooOjh/gWjgVFfE+canc6uAq3L1S3/2X6ij36 L1qeyoygkk216MVj83g0sUfdQIaOd3YpqZ992Ai/F/lVPmoOwX5Vol6sCbvK 4ibeP+T7VXDlv3ecku+HsG1zpr9tdwlEeRjZ6B2Zgun60EheRiFoyfoWLtyb AYprW1/KLmaVG6geejdrAhQdxtO6XcioLV9XoPOlH2/d7ynPLJvGkIBCBXMJ OvbTL9HLvw9i0rHrAWeiWFRkA44kbU8YhdZLXHbMCdP4MSOkTTlqCiv89mwI aRmC4K3mz45aUfDMKcWH7qkNOJxhWdMftICLfv9dO05th+ofm6WJ10bWe+6J x7uHc6Hv1wfHnGgqvFg6tJhQ2YNOOwZv+v0aQcPT4cq5kSR8bin0tyWyD597 aUzahbZA7UzGzvB6Clzurq77Jbb+nzRjBk9l/MALlpylxeNLoB4pZNCuMwJy K+lnBpqWsbznUix1fa47l5NDMsWGQbmnyL7vVT321WfuKnjaBSG+PdfORNbA xOxn8dezZLzItYGSdC8KWXuubRY1G4S3UtfKJAfWkOect2xKQSPu7M5/EaT+ Awdz3+zScJiCsNE/nu8vjUBjaJ/bybg2ZDUX8jPWJ6FU8lOniNEGvM1uoxnz jApBHwf/XUpvxccCscP3fo1CJpV5i/koM0Fjc0DQ0sVGMAp5NLHSGgo3Xv6+ /95rEO3i3//8akXG1YVsU6LSKtbRPRJLXIuh/Yy+n1pKLdp7bB+8KrWK+xq2 auqse+YuFoWEuePNoJnfzRg9OIj/CkYV2WNWwIdJ+p+jSTF0PmGDc1nfQagr KrtfgoA2jZszL/sv4z5Z9roNFwbBXJ/XXLR5DMyzSJ4Ngu34sbvkLs+1HDRw zbqVr9qEU+KCncvzw5D/gk/BJrUF+RUDybsoZWC1enuK+1kzjkt+VqGQVmGT NfNDqe8MOGHr8S/3bClwRlKDHFzmoCaTmUF9SgSa/B6LO6V98PB53NOjexuA LY+XQf+Uj/k95B289xdRWGu+2e53N97Qu3J0lFoHKt3nvvoy+tBzzLbRobsf LQyXSG9TJ1HOy/OJ2h86Xpr7pn2ofhQ36MyZbXkwDR+4Km4Yzg2jtfWlJ/d7 ViDzFd1bOTcVTPk23shU6cBF8du1+nvGMc5b9vFmvn7QPHLl+PJGIt4+FCf0 tGYWLuu97Y5sJYF+EfPxpPMELJhbsyS7klBQwDydfLAfWDw/vI0m9KNU7QFR FfUUtFamvatLHAFHrwZ/JxkatpM3KX/i/wk7mSSP5Pd3YNzSLsb5sTaIUJfI Hv/9F2ssjZPJz8lok/ZYKvt2LjaS+zJId0rX/c3wTmQNA0w3ZxS19w+hVrR1 sIN0Dxx2Hxy6Lj4E2pbHy47SZ+FLVfHdZXMS0NUwX3iKhreMrazTrwxj4ZTi 8bpfxeD6WOLIq0k6htDYZLl30nB5c5GuJdsy6rXbd9q+ywangnOJpTUjWNw0 bNJ6cR7+Y89NXKH1wzsnu3vyj9bgVv8epviX42CyUN8vZJiNusflD3rUN4Hx avzhF3rjaL+wU+r43XncpxziX7RlCHb9rK1IbWsAZd/SfzvZySjnEmcSEbaE cuxjaZlRHaAn3VRc5NoFoK+cx/28B9Jvy3sxrfs52cLv2JHKUlBNb7M8IziM TZy2POFqZLheoJPLcq4dp864SaorD8AI668Q6otx/B4a9CWhfBJf3uTNVrs+ AeXOCWtiJv1w2f1g0pmvJHioa1VA5J6D/GUTFdvKaWRxqFcu4hzE7zFpTtIi g2CyeYoiZUDFRK/cr5dW+rGXcu6S1+k1aLQM7HQVH4P/4j80dvHlwyw9aC1W cAEm2AM/RZ4hIjWzTUVQPRIvLZS8EqXSQUrap6hc6ieIP2WN97Kdh9k/4bzK ZDJUCpXclKlahPzGu+Rh2wUQ+nvCfPNmGqZ/IAc97hzHKz0NzxIN6ThUEhCc eaEFBIJbJGzYeyFoc0eMieQPCJrm/EfbUQKD3YcnYcsyPAyQ/zx0aBE/lCzE hUW34xyTdnKh1l8wunVlskBzBhVs9n7WV5+Cp71ls+qChXDi0sUnondGsUJD 1k/2YA908TQscNsPY6YsF1fim2H4XSqr6cwxjcFHt+22fTSHsxte7xSkjWMx 5I2kSszhG0WLU1feMhO+pgQQbywMokaffFntJgrUDI7e+R7TCyPqpy3qcsvQ 7nR+fW18D2hnMYc5jxTiJp/Z4ynfyWgmfpetbakBgw6AzrH2Umx/8eOY2cX1 HDGyE1DPXB/p/Z3n1RVj6NX5ltX59Ry6tH5T3h5Mhny3R4K5d7uhIf/RTNpq LzonSyZz6ZaD5+HNB7wEWAi9hZzsLvMFWCOTeok7ah5YT9l8PfeoDT0VJiKI DZNYVr+t9K07O+Hr1vNXlWcYkHYoakfLzAJkctmKnjenQLTzITdSUD+EHhVo jD8xhdbBYg57t8+hWUZ+gumOZVQNd2WT3DaFL3cKPJ7MYKBV6Pu9XR+peNBs G/IyxlAgb/W/8zJJsJv8cMvn7QW442hs2jONabBPt3ANTKKj6BWHdvMvBcAh uEjg4RsAma3vB6P952GpMk75+xtWgs/53o7llRWszL/9/Xp2AQS9kqTbaf0A Ka8c5QGBaDj23uG88eliSLBrbS3omwJJQw57icZV6L5Kyn3lSAaDMxaFl/8y 8P4V7z9701shZZtfOe3yFNhZRHoEGQ/gYmVszZ2jdcj7NfuT54UlEJbxP7J5 kUnFxOO6w4Mr2SAYIZahor6APxqCWGTcyAC35PLMfk/CgpmdrlJyBujd7jlT NJGH/3gOvV9KLYb6AT77sn1vYMnycOnQnybkerPzlLF5Awy500L01+dWPdx8 c2yAgQ8D7WVmzdf701sL80q/YXhIkvFKvdoC4ps6D06LsRNe6zgc7bWZRqbf rGefqrAQqBFMx0QfDkNcpW+mb2MHGJVmlRf4EfEi70iI1dN6sC9XZfpkSsH7 ZtvD976fQueVttdr6z7xtL/618JxNsL9f80tZzdUwFaxMMW2/n5gFzHa3yNF wiMNmd8KPUbR9aFpYNWGDSrixcOSPBPzYEp4s0YbcYOfe3Zxbt5LgmdXyIN/ jGZAoqC55IRNC9xh1XM8uUoBxjvrDcf9O0FpUvrduM44+kyYpapndOJafnxO 1u5+6Jm8Y3Y+jQ59CvljrfsZ4Pj7RqVJ8jK4f7eYlBgax7ERcu3zz1moW/W2 IksjD4zUfoiL/hnDN5SF90xuNDCwfz5Z830Cr23iMuTya4YP/O15X9UZGLYU ekPh9Q8Qd9wZxRa/CLYsSftfTsyh6Z90ny2sjSDGKltkbEhFz5pb/Gd4lzBh QNs65yUVvvw8+eu6SB5Q6OYzyTN0MDhsIef8c4NKi4Wul9hYOn529D49/5kA O4qNr9BHx4EgSI+JjApFq9vf+eN+EcH0wI4/bvfWe4Bf7zamC3W458uTtNW/ /biJhe/6V6EhtPAT7ShwTYVjxia8MnvHQSNEXyLTKQw3iyq9i4rJhh1N/OmC KS4oE8bz1NiTWSWNxDo7wjUJYsyqmss7BuGZpc/tBM9yfNCJ9TPhrUjvcBex qkyBl6GSqVPjyeBQ8+dv0s8yJGEKUdiaibCP1rltrYOJwMmv/zmpuRz6LP35 s9MZqHdsUGue1A7KRvPmk1OFOGuIPmHpjfBI/0FeoOwAtDx1qdidnQi95s8W T4VN4x7lh33Bb6dAlFPuUY/3NAyxqJ8mlwyAJcFrlZBKhYatK3YHYgphfJ7U UuRXiW23rE31vJkJFtR40vhAH8bzmGwhKIWDayc3X4pyJ+w+WBcm5DcEWSqH OJivziCTiIZE/pcWSJTNDvZ4O44ZNWXlh5s2EO5DB/V06TTe268arEWJAAnJ y9bjYgt4kEXuY1t9Ady20tbRMZ+C4Gq1y4UrH+DflzNsEbp9eGyDNN/xlinQ bnPVHi1kwNqURPPlXirKsZ4prIJ0lAvz+ZEok4UZz8ozuKUGgFLVzGcbv4jl IppXdS1qQazqRgcloRNgg86i/IFUWDq8cnT/pTIs+xzn63G6CC/zCfBd3dSC Nx9fEzOBAfwHPUsxX5vRXbvJwV+vCKIPHNHeL18Ol0MlXPSsyaCsDXof2Rnw aCgriuQ2inL7hk4dyygFKfZfso4yVOSaEtgq9L0HvF7mzmk/7wYtgyZm31Qq TonddrlKGwIZa5mtMe+mMOWDfsQeHQaaOe1nng1ows5DY8t0mWXs+MIf9jd1 AL5wNFK876/3LbEdzJtaR7C8VkcpSDEMn7zpPiW2oxFSAn/meh0YRj/fqeIS JjrkSo/odnIXrp+neeI/xVRIvjO3853+et+yv5QmGkqB8/IJf2tz+6Beo9NL 3nkVh+0lDZTv9MPjY/xLOE7DB+el9gvepuJZ59sj7IaIm9KLL8esDOH/ACZp uuc= "]]}, {}}, {}, {}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{False, False}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{True, True}, {True, True}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{None, None}, {None, None}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotLabel->FormBox[ TemplateBox[{"\"\[Rho] : \"", "0.18059259259259258`"}, "RowDefault"], TraditionalForm], PlotRange->{{-2.883108517432581, 3.606675941002827}, {-3.270614613095823, 2.7067760853728187`}}, 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], PointSize[Tiny], AbsoluteThickness[1.6], PointBox[CompressedData[" 1:eJwVmHcglm8bhq2ElFVGv4YKKSKKZF1GJA1SRpLRUjQkokhSISmSjLK3yKjI yvXae+/tfe39Dnt+vr+ef+/nuc/rOo/jOXDzsd4dBjo6ulFGOrr/PxW+fhff E9qMF5+5s2jLVqPCyQSaless7nDm3LjPNomqf84TBC9PQ1yszXiHeAO84y7W uH2zDhwVzTs94imQ2rmaspWOBp1JWq5DUTS4u7XQRld0AN+MG23lTKLh75xS e55qGrB40ZuND8/BrtcHt1IqxyFzHx11UawepBsnsi7ykJCeJYH/9+kp/O76 OTmlZAFFe647OKySUJ3LkkcqLRNDOFaMyYyzUJPMk5qU1wBnDbqppKkpZLLs 3b9UvYwUS5UkXt45dL2VePXqrXbor5hMM7iZja9a3wSkFf3C+vzGnYbSeei0 +NP/WcEw6owr6fZ1ktGb16Iz0iMdauKe8W4U1OEpj5dt3aZzqNFE8A7+SMHz mqGLeduaUbfPTp7qt4qpdCqv9DnIaBe+nKU+UQc7Wc7pv5luRZ3ESS9dDgpG uGt+7Lg9h3teBu83jGvEohK+T98mhrCFzBtI3d6MHV/tao4MrQGL7gOvtTAa UAs7J2W66AjeMg9Tjh1awCulNzguC3bBxCUxbR0dBpXUlfLtX1fnoHNb1P3n pb3oxsXGcZ6jBkSMDk+dsGxFEzUJ/7M+E8CUdO9qMWkQGJWu5liqtaDISg+h IGMGo9NZps3jFjHomQr5g/s8rleQaXY8ZHjgXTvjtsagYif+vSLQrAAzTUvs 7y0t4qUdnWVG8mmwW/Yp2/l5KurcXmcZLulFiqrX3voVIjKzRflVHpgAV2Pa rrDXxSDlye/Qen8Bdmf8fPJjfgmS6oj3goyoyNLSkx0VQsETPi/VD3MsAeds XZb7v0H49uqisZFmGlBfBcb0zZYD86FPTA9/zaEznwJDY9o8Uoja9aKMDARd rSU+SblVvHlnz7DBfBkycUfzDLFM4c44gz932qZhh+cXbjofIvIxbtTV1pKx L6tgIO3YCAoq8t+YTurHsp8ibfHBY/jzv/1edu9WgOmH5+rjU8uQwvX+7dHE EnjnP/O5eWMQy0brpdSfE0HBw0r6gRIFCjRPOU4ZtqJ2Cy1+/9NpYKa9kHn3 ahC4C89dWQUypJy8JE/Zx6CSfE3C9iUPDbaomcvzOU/APbNbvoau7fBO6pzS tCsFtmVxNTGmD0Idnh7VekND65O+LBrD/fj8enj5L2Uq+O059IF3ngwMd2qr sIWIUZFy769skEE9PHd1/tEMeqWFCHRnDqMTwXjA6TkZHpfMR/UsD4JAJf/J PTNDwH3zfNFb7mos3pckXzwyja1yB/JOrpMwUo2t3u5UCaaZqB0Ka5vE0beL l1QkFvBzvJAlf8UU9n6V5VrWXgdt5yTZ9wsrMD7y/HZG7SBsk7oYIJk9jfVf 8xcrfBLArRR9ymvGUeHdiw2GE1NgIvDxe8CJXlB0NsqsqWzDTwbDyg8lR0FC zGasspWKvOssLgM7mAkMax6eKzXteDQoeCD86gDyOn+gD91OxKqKRyl8skRo 3xt86ObiEtrlBUQmnmoCc4OL48ElFOC36oUPKhmo4jKmv8MzEJdNy5RLq5th pTsvjLGpE/3t02ot5olwBugNTlDHsbtCfTrOfQgLhJQb9a52oGym6Ljjlkms 9nO9+4arA2B/ruIZeyLcsn40fKW1HbJ+XZ+V+9IMXCO8+5t+L4GNh/WjRLdV MDsc6Sj2ggTHX5AjtlrGg3Kew3KoMxUvv9emVU3MYs7LpYAXh7PhW/bbtCK2 WDzSzTUpf48CZEb67ppVCly2PMXk9WACO7uK9i3KkvBOp4WFqvVzCO4U5BE2 XMSkoPsbba1jYKhzLNz9SjfIHLxwJdFyBvrjy4fX6OdB8vfuROrrNlzbXrX4 U68K5AYGvv/VC4HFkkYR62E6wtbTjU2lSeOwx6t1TUrtN4rejwj2Np3Eqgjr uz0RHcic0MUuyD0C0qers1VsaZAj8aJNiCsKmU4py71o+IGZ4lLf5yvGQXSb U84qFwFi486bn5xJQY1VTidltxxgTpzx2OI9hz+GI6bq3QZRmVOvie5nPepU eg/dbezFmC8tH/ayzQNN4dZC7NwEXK09MxQ5RAH3v+M2XNcpaKB9+OHvinis mQ3pdj4+ip8eRWZy3h7FlDHH3t1STfjbIL3jwLF/wE57rjUT74MHbYfO+5WS sb1mxIMnhAjHWneHSrydRGfCScXT0IDbn//3tXNvLRZL19qeXurEcJ3Hazdy 62Bq2p3o6T8G/aPCIjvnGlBTIGj98+NGNE/9vStZiAZyVdSMBzZbVA7W/qea wtqPS4O+DKc0qTiUq/on/H4a1hm4H2Hav4TdRp/YVqP7gEFwi4TIwBIoNvHf eZE1AbZcl23S2onwdKFP0oY4AsbfWDuTNudCIkXihz1lAwN+T2/5F8NIqO1z d9JtpUEWhehIpzIAIc4fnNbk2uEX54OY0s1cqz4lRRMClsFIuTvdUHsNvjk0 o3j3EBBqhVzMxedwlrYtjushg8qDtOoR4qdFeNhgkjl+eQwIwKmzQvyO8Ukf Ip3WqNj40ElIxmIaTY/+SGE2LYNZaSI6Fddj5Lj3pcXbq8j96o31dz8aEgYl Z5v4N9BH1fnKsdVh5C1IIhWrTWN3G+/z8f+68JNtzYUYzU48+lzYS6xoBt+x knd/LaZTSajVZj5lRoPtmWmRrvv6kU7wQ/VhuV60+zUdKHCQipxDeY0sqfmY Nr+F7eO3SRTcoxZe9f03FH6+qJFrsgRZH37aRfl1osarhzp3RyZB/fs6/9nK LSrsMwbbwq+MA9sDW5WNG6OQeWft9vuWbnyqnpzN/rQVTolpBl/1XUA+l9yg QWkSFN66PdapnIlNdOWppbRspG1nX45v7gbx34vUaekl/NxfvVCd14ec+TKe z6UXkD1zu3PdzxVMvtBs+KSCiWDwfeJq8XkaGlmw2f7oWkGja1MO0hbz0HuS QaApfQyX+pe/+GaSsWfEfq5yloIyDl6Sh1/Wo4OJLOcYezkMho4Q1I5PgNHF vsdVryNggPbujebZcoj967fuN9OIxe/v/lDPC0fjlydtHI5VgEPmsa1OpGww f9zXhvYU3Oflnfqqbhy1VqrvPogtwOWsqMU9j9fxrVy07bwbI6FectcDkeNz qD07F5azsYWQaNgivm5Exq7+vQWR+UTsbd91YydkoPX0K9XBXAoqw5GUG1aN yJm0U/3a2zFUP2AZ0cHaBHF3fRwf9PbhdydkfZ1FxYuTF2vr95Hxlfed8HDH fkjh1GCRyukERe4lletHGVSMfPUovFkrMPbl5CVdzgY8JyJ7XjVnEptc7nNO s1OwPIzTeyG3HkfZf+dbzvXDztTEqaNSXRjAqFix/coAskv8fM8hPguRhOZH 7jvGMKPKonaBjYSPJCT+Hb7SidmdKrK5DbP4aOWTqWkbAfIKPPhlwlNwzmo1 XWuChIdrTPW73m/2o7FU+8eldATm5I0Tks0gGZow8MRkAENcBAk9t0jYSM0b MVQbhyQwr5u52Quf3gu6S8tmYVFkfrmn7wCs+Xdef7l9GTs8A4u/qPZDgXF3 9zd2MpJd+hvOtEXB/LWDpMf0rdBefV/uzYk6NI64mSfK0YJOdoJ69tRaVFIY Fn7/YwzdrqZ3qonRkG81oi4oaBpaLJ6xlX6lwoTo/q4X9ksgY97TNKk5Dm6S fWVPB1ug99n69cJmCpwXu1X00KUL6Zg+VJ9RfAgN+/fvzr8zi+dksvjcuxeR 3+8uf+hkG5A1eO9d0UkBbaPiU+mHxvAKbZfo2alh4ND7L+CSXxYa+OjmtosQ UWR17z/vXT2Q1r3+i5ZaAet5CSHV4kNow3O2iX6ZBIHerW7M8eO47nu2MSRh EqNurkTWO0eB1b2j/uUOJAzsFxqkcY4io0eTyYULsyDIM2Oqkk1F44/ri0si 80j7LvN2d/kUKO3ji9GNJUEb/cwLONoBfnX+jm4aA/g0pSSXytEOkxu/q3kX +9BIdpWnjUDFiB/VNil+K9gqPKfXqT6Gw1tYvQ42raIIU+aCABMVWbfuLIw3 JaObVe7hi51E1KJ8vyWkT8ax8l3qkunzQE5NoUV9GgcBKyfCYmgWCKmSj94P H8Rh1h7Wxw3hmMR23Z69rhd1h2hZnlsYCOaOYzD3Mhod+WDLqdFhuGttWm/U QULZKjGbqloa2gWaJYofGsXej4ESt8e78d+psK2UawtIZc9K5sttgVdro2oB P38DJHUePazVhGxftnx23J+Pq50nGKb8hsFPzC1UKJoGLwTzN6BtHAJ2sTX+ ONoKsdptz0vDpnAbd8WtqeskfMBJbEvPaIBf9jxRNwsKQDWsTplsugBaKZEv uU5NAeHcObKmzCcwfHpG1MwqB9arTFbX5X/hnPpDXduxWcz1PJ4+5NYGbxS2 pwyepaFSke58sc041utwXaifHoE9Atc+NJlHYuWtok8DeXOgx6zKnJndimff d/9TFajBlPIMk0pGKl6vOxN6IHkAU4Nr0p7TjSNBPk/vxfBbaFo8lnY6ahJy /k0DNZkMLtvPeGhJjoHRpK0ST2IB/nCTMGUwp+BDB8XEsaRuPEO3SNRUn0W7 DRvipYB5zC6q4jl4Zgw9BBcrL35vhgd3wph/CU9BCN9Vk/s9ZLgasnWX0uku sKn18lbSqIZI2Q2KkMkQjtor/qpNTMW8G2534RoZE7nl+b5f60IZZ4brVWoT aCB2yrl+aRqVqFWOios5SLcQ/yj+Yzf6mplliGbOoKBXqNuPmADwdja80pC8 2UOvIsTq4wshtIq/93E5PaGstzlhoJaBcP4Ll6lj8iJ4G5qZJv0bgdqxEFYt QQpSb14Vj3MmYZf5QaV4ngrUPvxdk8pBxYePR1JQOw1ZuHp96g/2gP4n4+pW bgomo5MxR88a5lspJfM6jmJMwAnqZ3ImiKvy1FWQ55FOJNAq7D0Tofb19JXx 8HT86dCXYuXfBaoGAqfYno9jb2jZoP7QFFrVXpT7smsMz9rJMztcJ6OFp0zX Xjp6QtfeZoflG6O4NJM7oRNHQiNGBpm/W2Kxtbap8obnGMSoFR7096HCs4N+ +ZL9Deg1yWxQTE+EvTt63QgdExCnI1N/8kY3iK1Ji/Y5LcDQvpnBl+/I8F4g 9YgFJxHyGL0MTvFV45ECswyenlooLjW71iBIxTP7Btd1x8shruzZiQ83R0Am 8dYdwlorsqwP3L4e2ghbqswnr8mt4F7ns0K8OtMwqsknIOPWgIsavodEkilY OxZ6QX56Cqx2EZgaHSngIchtNyHDqBLA0zc45bwBtwXkYmv5R1BzNKIxJnoR F8mFfMOrZBhek5/LFB4COdfPCcQrTIQI1qgMkv86wrhybyLvdyiMUnjVEDAM uhe7M8TSZyDCkvzatT0M73/YULX4LwtspHgrQvVpEGAstS/GchK1eGwTJ+Zb sS14bts2pmmk87WaYxCRhpE4nsriOhJ+Sxh8LykxCg+VG86vDc3CunWJS9Xq Avj55ZTLP1rG2dtftW2aG6Dt/Kys3AcaHtwx9vMARyMKvVWJSDMko2ujmNfx 9E+4VZmuON1wAbaUZF1UJA3geHg8g6poP0rdp2fIfT0KbFMv/jQz1eAUf7bU hevlEBV96HlOSyOwwxaJK0cK0CXjV1p2A2lzT50Il73agnxDMslaexKw5UTX PpPJATS2Vd7BbTSI7+4sMXIIzQD59++c49tIkMDw12Zw8h9mH4rXbL/ainRt AsdjLTf3lbngsJP/Iu6xTsuXjFxAbemm5lqfCfRkTTjK2FMOL6tbHzkkTuDd a9/1lmTIOHP1z82dt4iwy3gr986WTvyS6ZMTU7QK345cH6ffnCOR42/22r/p RCm/OleunkbwDrzwplacjHT7NaTvfV1FJfewTob4DnCt+8/ooUgXVp8Wl//X RQYuhvAin+450H7nLEzLHUADLZMbWYd7UEmlpVhEio6wfOFjz12lNTy930Pa Oa4XLZU6XvYrDQNvxUX69qFeTKta8adfHcJb6iK7tk+PA4lo2hZuUI3u++yu txztAu44guPeQBo4EaZ/B9ygoejTkZELT9tRWSH8tOFXMsppLvV0rhYi91sN /8+vmFQ+hE+tWVxahrM1Y7XuilQQ+zzeN3ScUWXb1ub4G2XZcH/fLcbVjW4c DfMb18paxDMz/oNIV4oV83dneS0zYCDVKcn2TydG9Klce7Q4gCb2QRZZL+qB 4Mn5zHViEor3SQmG66xAca6r+8l9S0B9EnVMtnQW3Jht/t0ZmYZnrwf0X0Qs wpM40nxqAgUW5XjNi8RHIGNfsWz0sTlsV/lnKW5CT3D8AoKtCWQUXLDTZHHd 5JU556nYgXF0/FrPZpM2hEoif50bH5Jgz9MlfTreflDv2s4uoEHEDIqqmMTI HPomXs6NfrOCpe9k7xA/0hMsjE2D9DjbQfqC3r1hqym4fiTLqVKjGfDXJzfi NjJMHZbyOyRSDXrF4YH9YpPQ139Ec9exFYhrNnBaf0CB2eS8EJfYcHTg7fxC +lGD4GleHbLKoAJPPca3SS2Aw9TQ8OE8Cgi+PZDblp8DFTvXmN45U6HN84Pj bso4TvsdM3yx1AfqHF4bO2RpULTf7nb2ShLuvdFY80BjGt8t7AY0JqFpdvD0 A+N/WHn5Z+Kv/BX8I6l3L8NtDr//M4+xrlvAZQt1T3feKVRTt5DmY6xCi0O6 JQy5tRClnZIctn83nsy8lrT9Yy9yKT1SvBVMg9U//cb5vynwwkhcKmGSCFd9 ylXmTdLBm/0A2wu7RSg2zJhQMtmiciWk8aCWNAXyNCpHgHEVvAXfWQfMDaH0 Q09bys9JkHqy/NVsk2+zJoJ9lLQXIUVh5Y70oXosTFTW6CU0YLNw89n3/gtw 89jM6zz+RfC/wRD1YrYCj5IrqV7iTShcNdy+nXkQyRpR0xdb/VDSSu/yxPoc ugZypJenPoVDD5Nni+LaMCsqU07BrR9ZyjmWvlGWwe+ov4TDPBVSTxidp5yn gHyn82uujM17shi9/DKCCHTmbBhHrsVjOvc9WJaIUPPxy5ef05vnXOSdOM6y iK7hC80uYvl4eCpLxut7Bxa+q2aptCfj8shlicZD81j6ctlifnoJr9G6Znrt pyHULKBkd3sPPgm7xKMvNgVd6zFRh4XbcNbxRdnfXy0gbGtVZ369CHIdxniu OpbDUMst6dEDjWDqnzxFFa9B2o13jb9yBlE6PfxzoDYNLux6SuOZWIDUjWs/ 1QQoGGRqNZdzrBy+Fnp0ixTNQGjXk56R/fX41qDyQOLSOBz5T3fax3sJmF97 3hIqXcNnNMdDS4b0BK8o5UnBLnoVobGvRXtWqfAyFZMy1Kdgx+OM5ofbuuCq eOOD9dVZ/BC93ydncAgN/thHieEYBIm2nqTaJ+B9jeJtbSP12JpqZHhWawXf n2BaPmLchdTyL59N2Qdg6qnbtIVZHly1OmmTD5NwmEOm6uzOAbDi1Dl+PrUM 1AfofeQ9/kLuee4bIf81QESTrkaOxTiWHGj/8Em2H+ucXeSHalZgXT7M6uPd dnB3fnwnXnIAbILUX5ZY9cA3cy35uiNknPqlmF10pB+ndZnWbndQsLn4eerh pkk0+3SFZ0qegvedbUZcTEmQ+SZ05rZnA4RdszDprRgBWamwY3Nas+Dyo8ZM +DG9SkSAwuDpTb+wLTtcw3VmCCpzpM1LvpZjv/rburN7l+GiYOcOFr9xHP82 0sCYUwc2/p7e52L6gO7mXda/22vAc3aC9WRNI6SJRV0aeFWIr3jX933d5J4D gdmxMXlUcD8ccOAxXTZeNQ5Vr/mWCtrgws02WYsih83sln7OY9lXx6kTRCr4 Db7U7N7ogKurwYMJD6YgpuDg2aygfFh3MX87crwLPVh2qf6imwWbUwVNdrEV qHTuruPL4nWw0kjpXE2bw+7YnpdRiz1IOGexEXSTimy6k4e/BlVh3Fy2mURK HNJlZpzyvzuO1wrcJbgCRsF7R9mJbNXNnNjLLjI4FMAMP8P96J2DkNT9ltBt PourB/I0ZYIouP/kJIfUVSIEHaLxBdZOQeu1Oy7TTzqhf8P3v58KJLwZl6FA aJkEuR/P6dVFq/F02Ew/5ykqdGT+Mzus2gnKIv671MRLIFj7ZmZf/hKML0ap WLAQYfKC/sF+iwX4Hvvi6FTWCB5yFNAoLe0DmVb39e91/fD5WjohNH0Dh9QT S45LdOLUD9My9ZU1OElvuWBm3Q52HbvrFbZtnn9WqsG8kYC+SoPFAU+HYf8J IaYn/AVYb1w2UaXfB54StXxiH+awKSJyzS94BHfvfMl3ZmMCXROkOi8dtsBQ wUN1puE0ELoxKvFQuxpUL+8a1LanwQcfp3OxP0fgctNOGUvrOLTI0q5HriFI jpWVSX+/hiF/e1tEwtqAZ67zTMGnYTAdV7r/SGkKTu8VMrrmv4ARipwnLWO+ QJ7I48+3aKvYHnw7NyiuCLBn9dHez5ueXJFfY1vbAuEzTOq1H8vQLTX0v5n7 axiZMCfuL9IJuc7KPZg7DRGNX980/51ET3mZivPtrWjcppNcwd+NBo1uOUN5 Tdh1J7fHeXcbrOdfbD+S0IuhWYGqLWQynur58fAq3Rj0zetz7QiZRJU/sa8J Ui9w7jx/yrDMNMpd4w4S1P0BB1L1LeU0iRiSvc3sis0gsr73qM0/NQtbT02Y zB8iQYew/gN2w0Hg+ackw2o0j0enHFZka4oxfKWrc7fPMDi9PzjCUzeHPmqj keerZ6Df1qeoL3gcSfy7RVnfDWMo871SPfdiHHWN0BL9PQWXPr1iinlEAXFy wfVzHe3Y5TKvbabORFC7f2qPiAYzwVmA/1GC5QBq5fwKljpZAOd++iSZ9GXD 0MN/8gJPyZh0POb6ZVofpu/7SL8vewTnnt6RXN1Nghsl6o+NPy2DVVPYnaPC c1ihxScfZTeAHSPPDQ/kjMDCz3KzfJFa2MWkt+a11A/a9xViVSoKUGbA+LrM hTGItM7XbeZZg9k98nJbLWfRpIN364erZCgLe+B/1LECDSdZnt9II8Fpn2vk B/v7kVSZ9pFqUwVvSSOUNjcCUCNlBk7llaHCljbKJfN1FAz8fuxfRCJk73NQ 8IsfAhMWaCg7M4DVt0yF3ud1gdP3b3ecXs5gzdLN9DPVbVjltxq7Z0cbjjLv NzCf8EUjh/6Ewbf18HTtqefBkhX8+03IQHK2A4PVvTnp2DY53+Qh340rFUBM d0rfszKIkmecWPjaeuFemUPdWfF5+LablGawbxBVL6hs3bHyG2dUzmW0lhLx VsMtZf+39cjm/HOPi/Q8HjxvsC7eTUegFlXsqJ2axucc/41KHGIh0C/uVtHf t4zfkq32mz/PQ5mNqe+C0/3ofPvuxh/fTCh/RJk+H5SOXlzLKWYHl0C8jvjf Y4VJUHjV3b5711Ng76w8fOpgO3iHuuv7RZGA0ycvajKvAeDnn6VihVnoFzVq l3JLQrbApP5mzTU0j6iOHkoogQtKWxMWpgbwUlJWYgx5EvVU0zzEfCdAjel4 XEr+AvA+Ishun6bgyEH6tSBHMkZ920oN41vCk/cfXD/2sgvMpRV0L3X24+wf j0rlbSPIdFp+LKd+GS5obZi6C3dg6bBLtT0Swao1Rrn/DBWUxE4/L6F2QhBa hbSqkUHUMSxq41gluBcJR2XQUoHB5ogc88Mu3O86YJnV2Qi7Ip9s3x04gtGl R8n5P6ggx6q31ts6B6yczz7nPVsGnrM5TOQvv7Bnb6PTUFAXzOOWgDbZQFRT yRTOv9cHFpE73B81tYDQOQ2z9Gf5kMT1J0d4oB9V6P/IFN6PxfkLpm/pahYw RvPf48cVTcCQKMW8v7gFeU//Gzp6uxz0zfO4t0eVYNRgGN3HU8MYWdkxW+oy AL4KnEdOiy2AQayLsKJ4CIoffCmudWAI2zsKs/uzFmCy2Cf50M4+9PtTavSr igaz56tftY7NQusF/bohj15oYJ6xqOmnIf+rd08uXc0EQeJHOxOmKrQFU40y 2WZIEG2Jzrqci722Osqv9VtxukT5aNw7KnyrkGaY/DMNioyfBfJfNuGYreHQ 1Ux/fPRQlm8rsR8oa/WRNs/ew8Phm+0TkQ24WuTWeDeHCFVm4r6952g4FSvu KPqrH0Z5R554FuSAl7DXno49nchmff3StMJvDEw58GrKfgehquc2kVmemRDx 1fxPkvgERDV4tj0wrQGz6FmP+6Yk9Gi1ePCKqRU8/u4f8rGgoPtCdtYLbQrm qzXmXNk6i/2ked5ojn/wQkNdvj2EgrNcL5lKzApxjfvQzvQrZDhOyvSz/vAN ApL/s3HS7cbDfs05Xrnt4NuYwbJvWyuWymvos9r3oOrIYahvHwXCsRDKfEgm 9C3+Eez3bgaNTwfzbftGsUfesFshcBbc/WyRpLAE2pPHT1hE0hEsvK0IJVUb 6CBxSNPscBUOn9wdf/shDXZ0Hnv98D0JTUTKW07p/AGPK7LB/wWP4YMra3vu JvzB53nS5SktZEgPFHt9Z6INhhjf1ah49ID53y4x8/dEGKrOb+TiJcPrd9t+ pHbQqYxKJdwJt88HvwN3Pr9j6cBz74iMr/60w6p3g02uPhVNqv2m3i20IP/V 5e3fzs7D8VCicFBGJ7C6K1k1+lWD+zb+VGO7fpjc8+JOxgcSROoVXf54goxn T55f0M7pRYFUjbvRO8bxDPFWrdnxRTzHt/vPf8oktB/PZVTS6YFg/q9Jeb6j +Eot257TpAWNCuIdjnq3wPK+3Jb158PwXG+Jg2TLSGiX1fONCVxD5jlOz4G8 RVR0kjmhbdyPVrq2FOOxQgjLtRZulvz/f9q6x8c/D2Gd12teLC9Az2ojVrPX DIQLfSbKX52GcWFa1zesrQlp78Pk2o4P4sZdu4b03AUI3MEuQedLhvtcIhpN D6pQp73+A/X1Kry+3B/4338V0NNNlflxsRskRdz9bVeoMMJtPvfrBAmnLv09 vEOGAsmfJj5s6S2H2O3B5pNbe8Cz/O2vnq5ubDJMEYo6ScFlwycRBZrz2PNC hC5TbwX33UrbULs7jCvHHS5aaa3hSwHRPMvuSeRndd1dwE6vck+C+MD3/CCc 919RE27b5HQeEZMt9+ZxtKdRtqicjpDHJfbtsuoi3hhjOGZ1bgnd6M6TYkeG sTQotYu/LhOlJFPiuEr7MIHeUoB1ahnVPvTIXkin4frr9/srP02BlPB2Mmsk ESoYpo9JP92cy2/KLLl11dB8X+b7Hbo/yN0TmhHwYNN/U6f2kBVycaiep5eu kgwUvakjDCOz2PjX+yH/8ii6Xc4IP6A9gBufq7cw3xzF/MdsnxV5xkG7cCB0 sIMM9PqcD/d2DSOB/U1r1gcbzApsn77DPoSuB5p0Gff6AOl7565LImSQz0js yqkaRTXOVhYJxzLgfPVOek/nEhSdc6HzujcA7dOtxjGCA8i9zHaPd+8ScFw6 7ag2zqASdHnf6uHEYgjPPc2tHzUBA0opd39m0RGGReXbLHj6UHQx+lBjywgk eHrm9d9qhZ/qh109jnbgC9OnZXynR+CLeOOMxO8qSFapZfjPfxSGX9z5e9lx A4RS61xrBGpBOonbUqHRHl1LqsSNiEJAGjx8x/BwAr6/88D3XCEJSBLl54ie PSiqkhR6j34CrN0D5Ww3e8c8is349vdwXHZo8ct36QC59XVFpuuT6J/27v3E +2psi9y6uzRoEevdQxTTvBsRuJh8WhKWMO/GHwHZkAaIZvgQbbzJPWP8b6PP 3OxDrVsm31SsO7G4T7ozUpmGcketmtrMFzD9WNDiiQv92J7i9fFyVDWszvp7 v+WcRgaV4BhbTRJIFO7Lm3Zfg0MyUxb51WTgcjnV0G3SC8xSN2sPn/wNNxMj p47Zj8LM3WNO5LkqCKGVmPsGTOLdCtch086thABxA/dhk8092OBdNwVjUEcl 72M8HIAqTzPZX8RMw8wPXsoRdwp+C+P8feHRDIo5Sxj49hKBRKfyZJcyEWNJ /MdO/87FI21JDnqnRuHEPuUXPQqlKEq3s7dCsA5Z9e/rEgaLQE6M+5tqJRUH mOsc9s8OQL6IwSFLVRL8XZHj6PnnByOSomEb/b+AUJVtNz82i44iHfH6bdUw Sk1S9GRhIDRXOn90vEfBx84uD+x3MxDCXsnncNkyEI4raZyx+daOvYsyXy6+ JeGl9DeGhw3XkGxdSTwtMIQDS7+0fX8xqnjur+GN/lqJgZOqvO5fVvDCF5/J 27XV+Gnv7YDTb+ZRT2/LrMaWFfRgcFJ9qk/GPLpgw7nbJbBxX0Xka3QXBGxV +nXHtxWUb2cpJ+9fwvI9XB8DFMtAxt2cGLneCnnP5oYfRA1vcpRW+7wkHcFG RcDJUmUayXyP1TK/L8Ahva1nCLazEJ+i/ik5ioLmpCPnokeCQWJf7IcC/gYU 9y7bnTu5yREl0xxpkwS8dydi0VF4Gg59Y9mZKtgOiXt9fdjayPAi0e1bkf8U FOf4Xu/IJ+DnkpYhN9MBdBzTMty7FgO3XgzNycz3wvafv84fPLEKPLt15Eoa J/FRpMNtOYNRTGA+fCVxfg6OH8h9/FMhHxrOLvb1OFGB7XD2sLV8G1Sm3Woa tx4DAxEd14qwFchSKxF6fq0DzO9mveC5OIQv6ZomV9/2we4Bs/1vD64j06Bu XmZjFxxPGFlnKu6AJzk5S7W9ZRjU/4ZAbCfj0Tc/A+T9B2F/H3GodJgGv+/e jncvHkDGnUr5fuab/TjlsrHXeBC3NzZqXuYtRPFHixlJzW2gNrf+5pvwL5jS kWW2vFkP48df9g5eW8SrQnf+Ohltfm9lu1Zlj0wQldRxIO/rhzesDSlpVvPA Jhr8hOcZi4q8kcbvlstbVK6kzZttOzYKlyUEd18ZbcBFa+M2t9w1kH7peLPh 3AJcFgj5eKx4Ad3xocFpLSpaKMeKLPoO4Hht2GuDoWkU/jZ/oOj9DLwVbnBJ FfgLu76am0okxuG25KmYNZc2vLgrs5DVhAyVIyI2mk9b0MfpJ8fbqCVwTLm8 aOK96etax+8F3xyHdwrbHP6cY1Axy17LIlVTwKYwwhzGeyD5BPOzAGIfEK2b GkIGO4FJILZYeX0MRNQVy4fMRvCvj3tF3oFFNDojwudTPoG/fok9Otk4g/2E 7k0RpWEiFzk4XogEKnF2+zwHv4H3bEm6WdYyLtOzWluLdyAxY+K2qTcZhVye 7asrHsUf4WanDflKkPRfAk+jPhEtlm+ePEXugb4qY3YpnX6gWfqunSvMQPnR iQP5swt4MHInzZizF8QVx791/pjezEvGsOVqK/7r1YleolLx0tcB3U5cgLIj 9ZP5vwbgyprYQqX1ArJv9VioVlxBBg3XO6S2ZQjQcnJ1l28GgkqG1HRTOl4U YZRpZenBfxG7Ss9Y2MKZVxLLeUl/cICd/e1OdxJKXdmtc/L+MFL1Y1LpNahg nMdlG3eqGa0VDk57q+bAuO2XFHPecYhQE7vEL9AE/pGCgyKiJGh7LHGD/noX 7np8/5eUcAXsVDzpkcowCnQ5specOW0w0K6ReYsZGThvtOx3E17FhbQrR7fN capwlSVbHPBhUPE36CjOvTmOnLb72UmrzTg5z99GPzsNVO1HiiWWa+Davf5A SX8YjH7vtLshm4hPcxs+XzzVAPzagpWzy5s9V5mm//NsEfibbxXWO0yv8oPl RIxi5QSuS+1wGDoyj+u++QxT5AnIlHfzz3pCRiPrZ+KPzPuxfGQrA4cQCStr g86Sy8YhRJN1Q3muHWepG7/dzpTCQS4BN1rEBKbw/Mv+OZ0LzTkOE+NyY1Dh KaJGkVtEuj/hW+8Z/AW9kt645p2T8GMqxlFUdRCuzB4KDiyj4TaDEE3F0c05 efy6WPvxGj5LXhKu+9q46UtXUwgRU9hqMvMFWcpwxM7/6nHOXDj75tKF4pZh rHxyvsf4yxBEuDPuDJR7A0mmqq5igU245vKTu/zmEMTqPPyvx3MOfAuI7m4m dCrxWqIDNLdh+CHu/uCdZQ4EDzLFbV8YRqm0ljcrcsRNv5yPS1UYA+lU25ez 7EPgvVv2fBw3GVm2MkhtZW+Bk0fYPhUlkIGJUyI/c2ECdrgaPZbhmsXjSidC Ryajgd28SnIHZQEjdMIMHvzuhk/9a2k3neYgISN01vJ9ORZde/t54l0a/vlk q9Pk0QIbtdqv7CQnwOjIVcoxg58YKJaocl1zFXMK4roorNsIBXdcOr6oVuGe R0/aDtaR8DF3hp/Bdgr6PyiVFt82gNad/XejvEbBhnfNUzU8CpS5c/zYGDdA p1FEa/rINHAnPNsoi16ELvYfVc08NPiyO6lO5sI/5LeWWxmfbsGLR312eg+Q kHn3NwJrcDrGuHPNxV8ohEP8pzQfaRajmL5DW69WJhpHEf4d5WgCwTN3vf6z n4IdfN0nxvYNQ5MJIcz4MQVDFgcSAqiICQZb+os0VnGZ6vRhf9U4CkWy6njI t+KfG9oF8VErmM++PrafhwzN93jyBDM2/a9bNzt2vA2MGZ9y6+iTIObxN9qj mgIwUXO7Zv6oBdL27mRu4l7E85fDDFyFRrCDdobyy2QWiTqee1t/jgBHsINF jdImGRAkNKlq0/CpqpvjhdEAsK0pByz0MqoYhcYxmd9cRbKt8IAP4yAK7rP8 vPMpDaJKJLx/5c1D4KcVK5fTZFQ4a7vxs7cVb84QZ6+kt6D5es1vofpBUBPu +abklAjhSQe9zH5O4ifnX/wh3zfQLVeVRp5vwDr3A5IyOwdB9MlAamk8nUri 89lwndgliFytFads5slI2XGM+GkUlsPVtbZqt2B/bIWW3TARW089eTXrNwIn hBiCrGTJkFDZv6NCKgVO3r7Sd32DijegXDhgnITyBQoPdHImYKZMUlPx+uhm bi785HVBvCy2eG/7lklgNNtruz90DI98rfEuiKcC9cx1q6u3JmFAMYTz0uQA tEVkXQxSXATuo98s2ASI4KP8XczSeh67rdZ+K1wtxG4eH1lHu044OuNn+PIz Deh844vH/7UA+Yn484HsJXikm3jgvkMT0vF8DYy9tIgO37auKm5nVNGruvvR bTeTyll5vpXUuwvId/7Ci0flZOz9wXdG+dYwBumsBYyZ0kAud4DOrH4Fb58T dLl6hIAZN896TDwlYr1+/p8huyHE8WRTv2BmFRpjjXuXPJPKD9bq7gODRCh9 Mlq+PruCveQ0v7uZ3eiU8NnzGHM3vvxaNGf5uwa3vv9Djixrg5PGTQFdUvN4 r9BbcPFIP6bb2m1ESc+h7QM7x9HVeXRTjae84yLhTZ+Ps343COijZn2UXWce ZUOi2c0Y+vBB7wjrEZ8AzBV9R+Ix7kQhBy1ijsAM+gpyH5yymELxW9qLHXsH oXCi8dqnhVHYd3xpkKezHuWn7vsKpjWB3J1LLu1OaxBg3R1ALCWi8bP5XjG+ cSja3ceV+IVeRbfI6NVezw1ovbq4pYKyAOkNx5J/7MuHuRY9t/bz/cDHku11 NpmOwHRdhKAp0gT3XO5lPbtYgspcCpUXersg7dpp53ifHjALObpzbZ1JRXv3 Hclrt8bguMmi6Cf2QTCrk1/OEm3GaP2DAWvviqD69lyMo30thBhzlH2dosAK T92iKds8CLb4hdFbM6lYmy14W9WTIXnv/LazNdVgfm9cj6lmDlWOpY39ezEP joHb3jvNTkGdq3rBxP0h4Ew8P289NIi3/XztstLqMczuNP1+kTJYMbRXP8ow uOkxO1io8iTU1d7qKL4SAa/yTh895DKPxS8mQ46JL6CO9EjWPqNREFuutZqN aMfce5QIklonTDLDvePHW3DvF5nCf8WTcMHp+p3L6Qt4ISjlwuXf/fj7e/Jn G8F5vLgxv17StgpQ1hbgr0anQhhpGKgWmIL/UrS/lkcsg9fdsaLwj/VwgcdH U9ywAmPTP907xUcCc67PbJKsNKAUcSlH6veCuo7JH9mmMjDwaXlcd9sfkp4Q Bfb8bcOzeo+KeOk2fdAx7v3nwXW80hv0nXGdCAZPkiXpd86C4B7dB+eL6sA7 /3E740I5Rub0PH190wNd8hR2f6H0gxlN412q/SzKP2L4fsxjAfYa9oz4StDg XmVlO4daIQ6MORV98F2GvZ+LLdhTliGZeCvrUvMM2qivSbatREOaxNUKi8ck vODl0d/xaADnyg58jBdYRxXGar1GzziQ/iv1feRxAcilXH1J4E9A908fzilb 1wLBI1QYt2/yzd7vfL88Nj3SICCKQ2lok1vErOlCZzFNcfDD/SE2AlIOqD4P 7sTCVetzT4M3uU0ABm4dnkErww2r7xXj6GDvd8bTpBn8NvZenibN4FYPzusR UmQsD31zV7ikDG7cTed8FtgDQ42r9RuGY5grYahbFd+B5wvTikIE+nHvAaXs UNUuuKKZdiBJcxIOmftKqod2AeMrDfY/os3wISYp982nSThSS89wZMs4lJWS b69cbEdeufomEcdpuDM0fl9XqANPvLEXfBDeiBxkJfuTWwZxOWJbqHTRKJq9 1FJ4VD8OcdcIjh/zZ+Fa/Kmw4YocILNPKAmUDGJw4Xxz9+1ZFPhRe4Ldrx2D 74uFHP9DxWS+nl1E81Xk6uVc2UL2geP6GRdrbiwC7UF10esuIh5Y+75z/SYJ D0ldNN3+mYacQpK5PLbRGGv1GPyflWLxDsubLpYLwGXoxhT5eRIzOTMbndZm MG/Jc/RbzATcu/H7Drc2Ce5lKqUe+jgCDJ9IeSr3liHwVW+Xk+Iy9gj6TpkL kXFWVKuy6RMBnKLumCvVkJH4UZPwfSoCHoaxvMhK74fHlotp2andmGy7WnVd /w9eUicFc7NR8OShxOIzv2noIcktPck9B2EcmSo0Lwr4Wd+yuR84iN9OyTjB Aj1hr+PWGF/RBmw37x3TuZIDui4JCUbBS1jseKm8uq0bCoxDuK/NUyFUPzhO b88MlNustA7ajuOXwf/W+ozbUG7/n9D2Y1SI+yyzUaa6CuJZUfUJbD+B4nuQ a2VHK1g9KTiT1FQMDXssgiWvDIJPWqP7WNs4xrTF5U0dHcE589c3vbkHUQg6 73Or9sPWn1SdAZl6OBawEPYxlgS8iq68sxedIbTigGq29CBKmbK6uF4dx/1M mlnzxFIM4lo+yJ29eS/W3zMeFvZDkK3xb7pHHZi9Enz7i/c8BhVEsa7FNwOb sQMPZXQWLNpITjTRYRCrvP2J9Q8RKljfOl/p7IRKs48VDf91oZmVyFvRXgru ErQZsj8yBja035oc0dWYJukq+8M5GypFTpX8khhBx2Jjqi5rI6QTZqyOsU/C ufke5vs97Yg71QOvvR3CF12Fv91OVOMFwV+9+lz10Fn+yNNVsxddXvMWRjHP gHPF9/pmgTKMyGdw536bBv/evZ2zoF8GMn2yfdCZOQi/X3hMLHoKovJ5AlVy GFW40F33076tKo/N/pu4cnYzx2i/QyesDeI3ko9eSxhDv9bl5EyhIei4doMx 0JJJpb7rXNEE1zA8vvnoXGb8IHDzBV2ZUxvB08WRXTH/jcIsu0nAyYxpMBcr ubWYuJnH2dxPi64DGLW6hVOc0A79mkOjc7GROCK0kk/a0w88X9mP0MqbcXCg i49bsxt9BKo3ouRnYPXV54wzuW1gErkr5eytPqzPbjzIylSACU8Dhza4iXiW e7ahxIuAhNyDC1pnL8OCj5Ln2qk2tPQYUpJ4Uwi/bM0hu5cEdYYuH2O4O4GN stGofL0NH+4s8b7DSUbP+7tMbVW2EoZJRH7G0xwE4sKRmq7bG2CkZX/aBZbB 32m/7Pe7q1iR/iswMIOMfw/K/c2zXYR7BZ/1nNsKQIye99RoNxlTFCxeN2eN 49/Wt4c8E36Dg8bxwLS/Lfh6QkImaPsYroktNUeuN4HwQKCOwMsRSLnLHmXq szknh8R8Okta0cBOMVxachKuvNz2Ab7RYCm12zUhjYialrYRZoJF0Oo6Dwsb RLjIliL8mkDCwsV/uTv9xlFxWatq3q8SM1frD+iLbiHUeDaejLnVCrcm3v98 bTKP28cP1ElYzqA3+bywS8U0XqeyqgyZVIPeute1DZ76TV5N/MowPINCelFd 0qpTGPIywWjw+RA6akQNfbftRt0B061sH9ex2iTGJ4k6ji2OGUWfZUtwRuBC gZ3GLLIImr98kt6MRuFr4erlg8j4I6ldXngJ98TarJ14toa7vOOH/jYO44Vj NV8NI0chPoWNd9K+B3p/eRc/TKuHht4rGVd76iBOUTnBfCsFR5vup7uFD2O9 HbHOkvEv7mz2vt95bgKCfsYWNftToO0Qs5yJfTe48e6VG/RdwWxlhSqu2RkY v5NYFSZHwo4PU7UE81kgzG817GckQrXiuT1AXECBpJw3BZ3LGFIenpbuNYB/ Qs5QeorG4Ss+3f+riILz55pN5e26YO6uzCtloVFU+RQy8HeT2+k+744ypaWg OT/HoP/TGaB1MSj8MV0CTwuOc/u801F7i+UZl95ViPqvdie7KRm+9Vvs+tY4 iDKi7C7juiS4+Vn5qrpaN4q22XWRhfOhwzN5PYHz36YPR/tuKR8Ga7dnYoU2 ExDLqbO36FIn0s89cqXzZSA4/X3mtbyXnlCyXPX66uKmXykYGfMRa+GCR9LK WU8a5lQ8MDsRQkMf98OXhyZpkMXP5fsqPwNIuc07n+8qRcpFpqW3ZDLqH+eN Pdo4gbXf6T5ovhuCqqyW5uM+m75vNdVyKXoMTYS4D9o+23xvfUcD6B9GygXb EK7fU3CRWeTfEHs97Piwf/04xwyI/DfIPZFDgld/FrI+sgyDRcW98XcaVGDI GpwziewF6dN873qkGuF2661oUd81KJEw2h6hsQx0Eds4PzCuYYpzV2y81xIy +0hLUzOYVU5rFsnnf12C5at6d3+eHMWIFM73id/IWC29p2TCtxXuRp/75A31 wHpN6JGUCAka7+v+9/PIPOwQO8/vrjAAmqU2LVd6KfDf70Cd4Hu98EE3K+ra zCioKobrfnjZC/Ve+6Lb7YvA48G2D/W7Z1D+aFxF6fwYpjV+1H6rQ8ZJY9d9 YV8pSPcmJ1H7YC9E75VsefKeDNtuLBeNSVKh0secZyZrCKwzbuEXwVBI+mP/ +BWBBmyfM9KdJ5rA21Xp9K/CSbAJrucdez6O1dx6fIYFwyCz+8POfUs9oPtu QEO8oxFu/mbrFqd2YFofR7pJGZ3Km4upqVoPKdBp6bPl/JNOdPrwQAYr16A9 QHH4osgKBL77vG/9QxtOKOZeWoFpDI6ingzQWgFueg45u08z4FVnvKCnu4FB TziDiq2Xke9Ywt6m9l58Kzt/XDaqBCsWw6aYYpZguiB/bYZtHI6F039W9qKC d/ANYs7RejB7q3Hh/E4a6CZUf5J70gcVntEPqqfnQWiV83Oz5CiYvAujsfpM wnLMQvz49Ql0NPfoSKyjAF3S7odGjQ347nuFUfTlXjzu6iSAegPwLjAjjk9/ GFi8f1xqFhzDGtUFoYdM3aC88iU1g5eI5ca03r1PBkDx0mhakCAVODUdFsx2 LgI/p4hxWzAByyPUF/clk1BBr+x67nonRk0V85/NH0VTUZmgnqebe+hKgYaC UD827/3m0D5HQa2OqB+P3TKBr1LjfT3LGopwsHFH/KUjSNy7levzqA3rjpgK ah6rx52qIZkBE1PQfnqSS+7zOKjJ6tfPB1NQoYdiLStVBrumG6LZGEaxqPO1 xk27YXzmr1TAmdGGmcpHbn3L6YCEaL6NpKo4dGansRtsCcftV2emS38MgtNG yMMXX4vAS/gSg93qBOr0PTqx5QcVSj8a+R7QpmKP4fRCVsdmHzwCTWlmJkIa g6FFB/M4PusSDr++vxuO7iKaeHylwZOR/zZozIOwTV/G9VB1HUp8ZdHmIkXB k7CKorvJc3DU6ytl6zsqpCjJe986xawyUM/flMK+CNqvVvuMD0xjcUPAu/OM hTA8EVpobzYBEYYTBs8C3UAwucpue/YChkz6eIm9moIHimt/pyv6cOTW2aDH DuNwlShODk6jotZwr+meE50ovHvBLvl8C9x5X+u/rk6CoJUZ61PxpfCF2/Al y+9mWMpc9s3gWMF+MYWMOy/oCJYMBIqz0SSG3M97v7owj9FWHzTdXo2BZoAz /cXMWuzneRtiuG0S5ISbTFeuZWPdxL+cWwEEDI/fPzLEx0zYu7zTviW9DlzT hP9I+M9gG0d6Z8X8AB7gIPm9ZW6Hf4foAmPV2iC1KpshSnoSyivsE7YdnkC9 e7NxAi8bkH/Q4VB70gQ+r6WdPCOwjIqHjRlC7CZQNOm6WjAHEfX3WBWPjVVB bk5Kh9LRdnCj/Gt3yZzGzN2k3buuFWGGeUCCWsQAmsRQzwrn0Kkw8JQ+OVja C1pFkz8ui0RA48RGybnuDmTYw6PHJDkCwazPruVuo+LV412nxN6UgX12m93i lj488/v0YJNqCyx5TDvumO8Djqnz10MVi3A+jDyQ6rAOpsPHGxoKmFVcREVj d+xogfaxkmctWb3wsbvKPORxM/bKTJtYGxFxrkpj6rbhCDz1YZ1RamnH/wGX ZcMs "]]}, {}}, {}, {}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{False, False}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{True, True}, {True, True}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{None, None}, {None, None}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotLabel->FormBox[ TemplateBox[{"\"\[Rho] : \"", "0.3290810810810811`"}, "RowDefault"], TraditionalForm], PlotRange->{{-3.8075818950799873`, 4.239300404890165}, {-3.90283793868399, 2.889919880973942}}, 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], PointSize[Tiny], AbsoluteThickness[1.6], PointBox[CompressedData[" 1:eJwVl3cg1e8Xx22VUqlECVkVIasSOtcsFE00kIwGIalUlJXRt60ySyErlbJX 59p77325rmu7l4tr//z+ev78PJ/znPM+r9fe607nbNlYWFiG2FlY/n86q52Q yrs+Am6102adqz34pNbVJCumBA86DEi3pdWhY0HexHYLEhbZyyxGpOdi1tsG d3GdRrwTui3/vWwpcvm2sOa4juFGq8+PwhwpIFxCYR0wHMOTQcuCOz9MY5XY pYNZAlRY1x0jNy9Hg7iHY+FLFr9xMAv7Fj5TwIJPQLyhuQoOkmy53Rn16HRU 11AlrAsd5zPLAnmzcLZ41LoybQ6KMt8ZizTQwDnTJ/IVowgsGqygb6ILKma+ mjy6NossQvz+ylfjoPCM4FHWvE6ICFl96+/Zihv+07sSwTsNmuzRu8+pD8O2 MacTfUotGByU0C8W2IdPj4seLX00jdqkkbqR86NonsivVPB7AbxuBB7WY07D +WOHf3OE9IKEnYfsk/UT0JapY/tpLxfRPsxh00j6IrKee/bgAbMc9W1h6Hjh ADbdqL+40aQbf3WYziY+IGGcwa77smHsROfdfXNJFlR8VusXdVa9ADJbS68o m/ZhRVqs6OptJkZXEsHVmYUoeXTI8cglDsK0zZ9delnjsOd1iTjfvlYsqXor TSophidqb9qeyc2DgVLdYZ8do9Ch93U9R3Ec7DqnwLn7bBceSo948CpnGNrO t5yKZ6bjUJgdiT23HZin9/5i8HXBVvYAquCdfvhjYCBUsjoMiYtpjqKCNKh8 xqEk9aUfzOTzqw70ZqDZjWKZAoMxXG46rjj53hvmI9li7WTz8ab0eNDncS6i 3M1f743FxjFxc0bo+zYSRLtavH9j1wZDd4p+JXt2wCtz9rLJtyPI5pn5YHPK CDLT8gydn4zgy8Zb6pxvp5FX3vlxmesinnlyOGFL5zAkzP1ZfVLIAIeM2iCx NCbcMYtWp0iMg8gjenmO/Bycyp+/H7S0CD762ttPFNHhob3vBtLhaRh2PcjF q8iA2uVkV6bxPGzmPHaa3EtHUs7ZzEWjBNRgbJIbMyGD36m7b/TFuyBH0rWj ftM46Pcxg7+rLILlpS4ls9EacGr2Y6GGjsEN2f1e1osBaHRF7uOdxhYoy5hR 1z6+hDxBPjxVeQvYMaBcYb/CgIAZtqCAjH7QIGv/TN5ThbGsVxIG9tWv3d/y W2HPEupFNy8Z/FrEk2k6PbPZvXjsq/Q+vmgqLhk0JC4k9kGEgN9fsw1k6OQO 7BTio8Pn2vQamTNT8CfTN/uUdTco/viPpPSLDkaXSVc236fgQamHC1+et8Cd 5hQzo8xSEJk+GKTR340Rv+snPJTm4GXsYrlI9yKIlNKHwj/0oNpYpKjrPxpe yIpcvn6+AWgHA0ptHH+inenWGZZNTHxRryrWUz6Ft1tYuKTONOIXo74zoVfJ +E3LbdCkZAxuFvb+loikQwnVPvGHPA12iW12ae1qxTHFGyVZqvNYwrLFuGl6 Dj843bl7wmcCmuTzFa+pD0BXkoH4lY2tOOtxYTRWfgzrtTcfH+GdxtBnzA3v dScwLmavUtp8P2Tm+73+FN8PbY+Mgv3u0NBK9uJ9q5QptNxSoM7H/ReNE+qW YpN7ceYw345oxigMZcVtyEscgLaMo6pjB+jwxaNLYvAFDZr0uUtGxRngaboj ZdvqT8ywv+ubl9UHtQcXRBuvsBFel7Yv6sT248mhbXXxg99A/OIkxb05E5LZ VybHmofASH3OKFeMCiN33rb7d0wDx/0ZzbtXmHhh4ecBigAFTT9Ea4pajeOt f3dXH7PTMfvghXwbxwaQEdVhSZobxCS9Vc6Y9k6cKNj8+PPEMNCzk6tTU/Jh 4Xhspe9av61qhW92+DcDmTv3Uo2dSPiXa706i88YZF9gD6WaUGFgf6vTlz46 2pE9xRt2jWJb5FvOanUajv9J9Fc8xMRCtfO7SZsHgUNdgadbuwpbe8/cvyE4 gj9lqkf8mVRsf3Y/4dmhcVRzGuvXNJ9FzfDtb7+XDaNTXLCNgxkNv9dLNlye WIKU5z6fW45QYX1Hqd5pSgrc6dP2ts6sw3/CbEldb5aw7KT/yMMjS3immYns N6hQ3Wqp8c6XBCNCvmoed7tBOYGW5t9bABIWK/5bJqfhie5F2zTrKdh+Pwpp eqMQMPX57f3HKThWV226/fQY2nw6xU/Z2INShnn6FBYGnice+eO7YQr1Dp5U qJcfBMPYcxmPf/YB/yh5fPB3Pxw2C6NpeBXA0chn/2nkL4Lf53hzP+lZsH5m /MpSdAjU77M5mlb0IPOgyba7MYNw5Ml96rgpBYwNxGXk701ijO+HHWEpLMTS DTz6B/z7YHMT924/mREIOEfi6dhMwdSNCf+Yr/Kx02dCvHdrFYYOslM30vog 3GNXj4N5PX4oaog93ViHpNXDL78YzMB/g6bbrsbOwe8Vy2Pt1FEgdeR+7DOq BmcpAcEkCRrefjDddGthDtlDVOSeOZHhTBhXn5FyHxreODy9Ln4WW3LtJDr3 TKHtpck+pywSurisYw6+YqD8oyD9p3vZifuN3h/NPsVCFLWotDqwWIWHV4wn aW8GUCjGojlr6DdG3E7PODNGRYm7v0/TNfqgzjO6PyuIBvblj5JD7lYBN3Vh 6ZEvBdyLs9s8nmaBTY77q2C5Qni06vztS2cyGohsvjF1eBo16OojruWT6LHn 5R3mIQpKGClz0u+wEE59J925SViBh4nnufiip+AticfHOiEGLWrTyx//oUH6 t0y7EzZ0aMhle3Yllo4PKgMPb+doAp8e42seAim41/xCh4PKGIjMlnkcjxoB yxOXNaf4x0H0xU6lBxd64XDbcoc5vQUm3ltMrSxwETpO+6rudOEkHEu0vnJw dgCkffAPwb8ZbpYNDKavpwAxx/bjka7HsO4hp7uadQ0mz7ta9vdR8fD3m6yB P1tAVePSAm/IBLDe2Ly136IezG7c7pHGEJDNFXWaMKiHsZCjb7niS/Cf2h+P qdPDOHu6ImPP41U0ZW2UKPxRgn84M/IETOqxbDzw4jeJ9USMO8DX7shJTOXm +Nvvy0oQ0Bz3NIulw8nf9zukDRqAMHyDyjUXBNrJ3/nLnMh4+aTJt+veHSCs IG3Tl1mKLe2HRxJrG1F1X3awpQ4Zk73pvTz6pRCQ1HHoxgYanlrXcUFjvgRu b4vf8nlsCLPleRO6v/fDcrAP960HU9h0epWunVuNhW+CD4w8G8XRTU1q4w5z OM/2xvOm6Bgcf6j8Q49rCOhF7dEKdr0wxuwU8LlWCvpPTGkzamUgqPt9kwtH JUal5nglfH0ITQdyVk/en0CeO9nbKY7fsOnHTe+LrH1AqRZjV9KeBoVIn9un O0bh6OsIw8tsLSgaH9OrcOAHirB5bVJn64eS7T8abISZcPXa0DenQ3Rcf8zC wWdsAp8m30i+ZzcNW5cOpErmcBK2tH8Jd1Zl4gkrnlwlFRLe8PLJct5TDgwr n6oNhxowbUvf7jmzGvDhs4wrTSLDV4HvSPYcQPOP7Wd2XSbBL6eX25YVG+H7 jd/ZZQ3/wG6iLYaxYQD+3bGGpytVmLk7TvyUBRPqorDgUU0HnvZ2bg+wmQNn uZATmnFkGG278kNNi52QVl/5wStlEZiSto3/tGawcTPfz/6UOSwDl3UzkjSM +XNN6Yl8G0pt+FzP5tuBMWrSG37s7ISVQAn5kwlFIPfT2nFbMwlow9VHkjeQ kMA1wPC2eAmnDz7LvZQ8Bus1js2njZFh6FCT0+eJGeQ8zyem+G4Sz1DZiPpH 6Hh5/YP95oJ0PEfQA7p1JfY5v2WdNqoD7x2pJ2cuL4KmWg2fUyYFoggD3XNr c1o22uPy5HcOdvzcW2zuMgWm/vVcEw4k4I8+GydU9AXsdrI9eRdKwu6Dfk6P yxshpJvHeWYzDfjUdGfcTcugT1O9w0hxBmyMR9y5AiuR3amkvHLtv1uYf0ZD TQagpy5j1yhfPtT25jpuMqRgwVHxrP4zU6ir/9QtIIWFcGF1ScRPcA66N7z5 cKiTidLhiYo9i234MfvG15vbmkFC5nhbJ/zFvPby2mWpamjxfMfzzmIIfL4F zFlPNcBAkeEFoh8F7na9krA73IU3oybEQ1+lgWNvffwuug1u9RZoS8+gw7oF DqGE8ww8IrrnhmvDIH6/4zzOLbgCB+tlJdzY6eD61J8/4voYmonzCTo1pODb 0+vUxwVouP/a8QHL5HHcK3/Tj25Xgcx15zRUWetA+saApPn2SuR74KI5caEf itTzBHf31KBUauXRGoUOGM3XoddPsBMKl64qdHUtwOEj+TetBkbwsMHc7dYQ Gt5L5poJjWkBfhOBsI59dJD9nMG+rnsaWZ78Hp34FIW54ZwG5x5T0a3KK+3F oyaIFUjQfilQDvfy3ISwaQIOrFtxZ71CAtf0aOkfV2mQoLVe9uqtcfi1eyzp WjQdrgtphvl5jWArH1+Yi/gkHprPSR3XmATDxCsvPDsm4Sn1nYQdcRScv7ms iUoRzj6w6VdozsFTPact6361Y/vqh2zd1RYY/JHCl0ApgNhtD4KsOfOgzeqK o8nXalSxrJkk4jSc6TxNylFhAEfY3OaA3xSk/fv27zLbIj4LT6DnZrERVtK5 /5AUlkDEpuGcqVo9ftUhjG2si4V7Q0VWuyXS8T91Ma7EoHwkuNtMqLkMQISq K6sC+xTcFi6/pCZFAmXuS3f8vzbDv+rGXsE5OvKFtt4+fL4fx+25uWsGx/D6 pU73GbMJPNK7w8EqegqPdrptWRUYQ02mZeIX7MV/grY1L5zLIF9WvJ82NQ1t xf8NFIWyEopnSZUz492oUSRf94a1B9ND+TaJ3x4A0mPuOK3WfizjCQrqPICY UyfvvtOlH/+q13q07pwACcfn3vzWszBBkxFhvzcIVxvkdJ7NIShMN4fLua3x 83FrdbXZKmT2uxOL1t6ZGXFFd/46CbhSLC7N/lvAIWE/i9CkYXz15Mb5hz/6 8cL2wxvX0Yfh6qJR0OS+OTzD62ClbDGFajyFPgGJ9ejb9qqXBWrw+IYTvs8s 84CTa+NOzpxK0Gn/nic934vK7Xf748b6kOsxG5tO8ABakVnYzORbQSrfPeH2 qW8Q98ZDZFNlH4q7t33ZL8eE464je15eoMIftkHOtqwhbKmN4It7MYM2+4LC lZmFKHo93rTGKxFJcrs/WsQ1I4Ej+dR351dwKqmKSh0swQo2TgYXzwQQV6tU ynbU49W5aDWWlUIIKchqSeH9h6dYPmXRPrfhX/6BoR4bMnwxXefmfWoUbu7S IjTaMoC18fWvz9unYN/Sf7IlN1gIH/gUDoZqzUMDoXxTvggFLsjs1MGgQVCM 7Ny0MkvF1DvcSc6uRfiUzN/Icp0JArPV1po9dXhJ/s3qj9ZJcDj9SdnVawJW bIZ7AtJ7wVTLKfn0ujrobKU8Pr44BvvlvxEK53Pwt0f6tAyxGRfGlXKjh/vQ /KKY8d3rk5BxaI4lNmMUkt0mFFOPz2CwwJX63K109NLz1tK+Ow/bJZMvuxDo cCLvedOrNQ6+qST0/kztNHIrv9LXFWIhclPjuh3v0rB3PusWW2YvOgZHGuo8 pQC1l5hiSR0AOYGYHn6jRuDkX/KOgj7k+ZJroX+ThkeOmyipSDSDQJWAaeJE LtbbvHvHKKNhYtcZoZseTKQ/plk/mllEd2rgtcswg1MZTiGHJIvRPm0542UF olzi0+/H9Rowf8HwsUHqEIZpmx7MV21DgkWBOpdlPeiHcM/wfejAPvWtwQtB RdjWVGKX1knDf+9Ylg22duDIaLHW4eU1P7iqo+LkN4zdJlv/yy+fwS03fRYo yzP4qpW7kMf6L9oIbqncoj2KvAyH4Ecy4xASbnXJ9DQRNu6dLlcJikTqM8L0 UNMSfiO6ij21qAZ7CVv938llEBq1Sd3WlYbDeVKbG2060JOt0fKB7xaCUGig nvAiO2E5e7boQSA7cd1GjfyJ99PIM6yeFz9Rje5nzij8C+7HvbbtpQFGwyhy 8K+u0Uwjdgh72aReGoSALTs51tsMA4vmpr8aK1Q4tPJPcoduKV5/0E/xF8C1 nK+nGm6gYrqsu1VNfya4XbIXuW7xDV8d5y1Vty1F75eOi5npw5Cq/9rK6i3i 0Rt5LMdNyVjBPKe3eqwORZqrt12InIL4zT8Epwv6kFuSQpxpGcXVmN2zSyID sN9AhjZ2fQKcussiY8QYKNY7rv7NdwEJ5UvCLR5DcGiHedDnPdGYeWrlIIvw KGxxU6h4dHcKhPEd9fbvGKhkbviy+10nbpT5sPd88Tcs1+ras+NJB4g+uLH/ NnczXmTq/OAvGEZmedObFzGzOHd6X/NYWB+KBal4frMZwvDihRWvS6NY+q1O PT85Dz+y8D4i/e5DqbCB+Xy/cWSJyQzexhECv5d+fbP5TEHv2ROei3Iz8HXh bfTvdSzERelszdJKGh7g3OMem9MNpxxjTrVk/IG+ZT7Lep0xKPZjyKSfoEKO 0FX3y9yz0DPRu+fqrzFwHeQVafYYAbP42nL+REQX502B6zeyE5Lj+L2Wds9C xRNF0ai0ehwvei+Y2U3G57t25Cu6z+LeN0GLhVLL6Mz2MZtbLhtzM+4pf3lK hzvJEl81qBSQfkNaeG5ChohOlg0Ps8vBKZC0VP67FULqDn6YwQW49kJrp/3U H3S+doLpYl2LbqSPId+2taOB1hGR2EejcPlKkqFuahHoRQRur+Sbwo6rx8+z adGQ+9crVUXLBjhhnW4hReoFcyEnqdx/kzhqEPwr02EZMwOCf98nFMKu8KpJ paODMH2tQUmTOI5jCilWWfWsRO2tePUdMRnMH4qWKsj0g8+9Xc/+BA0B65PK rfe2kEHpXRhZ62EKdseVUvOzyShGd79XeaEZ5KbNv9k5NWJlyMrzoh2dUGfT v1db4A9unRa+eCqMBl9DXqhc5i/HAoK20T8lBkizB4oXAg1M/t4023ejFJ2j unQ7P/fDvg3XfBca/4G6cUWrWUcw8EaYXH1In8CJSyKPl690onSlXMv47Wik d11yZOek4rOp26y3+BjwVSPF4NxyLZSI22Zz9VLgppBD50rcPHg3OSpZ+w7g 2bMvvNykRvCEUfMtctgoJBk7Grwo64MuqYLzgvUkLJCuFyhnn0BS/BXv9NNl 0PvAYaXvOwMKQs4FDv8ahI7kF8tZWdMwpXb/1yHFaUj7uEkypIcG9VG7omzH MnAXu6OwwrZZUK4Iq67LG0Bnm9evzo3SkdXi512L3514b77+7ZJME2hodu4c SJsB/Y2xsY/t6DDicfSRfdosmn2pmbwiQ8ez7j0/54d6QOzDbi1yUTUeeMVy 7f5KBTSlbn/OstoHR+628brYMJGJeRIXLjGxgTtr16mTlZBod/2dzK1GMJ2d LvJOmQZxvpyjn4vpcE+oK4hsS8d8RiTXyGgbBl3YckP2AhWTn42oF0AB4G6Z xK1xndh2/LNtj0I33s/ZGX75zSz05knOSRsxwCtITJsvtBn179meEFGewSWb Iw322sNg3xxuavh3FkCFnTuAlZUoGOSezsu5gOfL0obDj1OxI8G1+bfMWn2R P//i7CD03+VMOnuZDNFzVteKzrSh52L1Jb5CX9jGcOo5Si0BkYuxD7+v64YV 54ygL3v70OJz9lOiXzmc3Z25TbewFx4oKk9iVy0Ifb6YbOzZjzXEXUnbDtRD x1VVPfNT/Xj1xVeRS7kjaBqylHHuVjSE9zUyCTOzcJ/a9lGsbxlzuvidj83P 4JfkhdONg30wsSFDb8agBSK0Tr7R3p8JmQMhFSImg8Cjs6PXvngZpTh9ehO/ zeNJgbSZDtdKKDP+FWUcPYxyBxduvf+zCLxGZUl26TPgO6Vy0TNiEMSNuo99 CB8Ex5GA4E6BQdxifTWH4/wvICocDbhvOgJXXcJHkyqKoGT9+qsZFuW4UdhL TmUHGZlfOj6ZJdXBtMee73SRHgiJO7P0N4qKWl93PN2vMowbgkhn/NW6wYaj JH7ZfgCKnH3rok2ZqJ7qUMIqNIfbK1XbBXbR4OlSJlzunoGbr/cVJFo3w5uo ANHkGRK6bt7ele7UAqea7Y+kbm4F+o76ma/tgxDW1nySdHgIljn33fMzXkK1 r8nfZWWXsHUAD6cVdkNuZfY14+ZB0N6m/owzugwjNihH7jn5FT8Kpe1p9MtC y6JtRv1ynRB3cd9LXgIL8ck6rbDDZgN4qrhvebMEA54nTJ9gSWQnPN308MjK 8Qxw2SEbxU4qAnWRs0oLKXSwEIXzc+0MMPRbr9GgwUo0vyA2mRnASty0qy0g 2LQHeW61TIaHD6LPno+7WhgkKLRoZxzq6QSFpEPMeZs+PH1EYD1pcx0uiP45 kfFkGpXuLg1lXpvFQo1HHxK7arGs7biTavIkfv7vto2rcD3sM77Bt11yHGW2 UoiTBxZR4+GLY6mbGbgUGSM5p9QBhODfSmm/c6Bb84oAp3UPfHFnvH6i0ome RyNol9/lw5TM9pPbm1qxSk8nxzxuCY8IRt8IOEPCq66/+h1FyfChnIu1VawG KTqX9impd8JN6W6c7WmFSXcxK62Hk/CAbeFTsd0UpBs5ZH0TYoDyZ7Wbl1ZX IY7n+9HJh/2oFy7m6yVOQdWcH5ZfdtWDf34P64p7PcZX774/ShvGr/Us14/z 1uOrSvV/zwqmgGglnRaqz4D45jr7ruh5rGEVr2I5RsF2PZeUcM21+SuJzfMJ Wca6wTqruyGL4FA2es9saRRGE/nm/wwMgthNss8ztTHYheO3fvxcBInTK8Vu k+sJseuNNPR1WpF4hyhw9U4MWI3PPtTRGUTPy7qG7ukUvKWjr3hlZO0+819D FQsbcWap7tySdDOEyh3b/CptGC6UPd5ZcoCFKCyiobTr9Cwq87yOCdVYBU6H R7oCJzgIyIy3emc8i45JT4W/TQ7h/E+uqky+GeTbTxApr5nCzPDjS2/Sh7Hy 9AXzkzM0lNnt700hdwHD8its/ZEBFpXT5k1YiqRPsVfbKDTYbv20K1ulGc2j u4RkRxqB/7nuybt5qch6nO2YycAw7tRqZbAMtGNMm3Xb87ARtDYwn/XfXQ/K 57hlzA4Og5EKXtzfPwyv85hXldMZsPs8+cWH5wVoW3qxkNVuGA4fFVsIfUbF xL7OAxTTOZxdsH6pZziHGxm39+/uXfOxCzGtbmv7RORA/bm8ShJEdP/yjlmi YVGNtr0I+xKm9S9A5uIM0OxcMw5aT0Jd5TmqatMgFKlEylan9cPtI2cuLHOP Qo7m3dDAhnZQfuuY/sZzFpPef31iY9uPjM3hW3t8ejHiQK//b8lR7Htk/D2H UYuF9dSO9gtF+KZElZ16vgNJUgER2SaJGMTtQZDJIWFfsrJTBbMMacp13rl1 cxibmRMQvjKEukPXuP03chAavXQTLgYuwj8pvUf+/K1YtP+Xs5tyC3hPFBi+ WV3AyPM/S2r/zaCkX/pMatoIOLCPvb8nsAwGeaxayhysxO3XuIpDV3mIl86/ bKHtY2JVXjDBWJGKu5s692brtACLxmJEYv4ARO61Nf2jz0SW/Dh/45UkaFIY vR/u2ADKWWGdodvy0OXHHyWrVhbC2wOHYzsE50FZ1SM0uHMCfvQsevaItMOv rY03bK3ygVviSGLtVDM4R7t1xcXOY0OroMmNG6xEX4NXxvzNg7jB/NixmLgy ZNKzcr76LmFCjnetbM4KMqkbQ+W01ow96ffc2VMN8FB2WPW1QR8Uf9nMd3Zm EvzHF6Qe8LESC2IGvPq855EtZeXT+do2vGw7EudmPYthyVL7jWYGsUx5csjm xiQWfyp0m9gyjBFHPhkTTCvw3VjxraOH6ZD+NvX8m9xpYI2I4DR9y0Pcl/5N Y76Vmyhtmckr7tILiu/YcpaaWiGtlKaiLb7GQ+7EFUuNMJSUMPT6EpCNFbdH DPNn/mKITH2Q7S0G0CZ2h1VsjIY3wgZRv2MZSORo7S5kfMXjNqfeTV+KBSpP r3hBYT6okleeve2YgH9dmu6i55oh2/CDC1/mCLi6BHhMbWmEXufzxG/b27Gt ISAiEMkYobBiKxfAwKF/wpfrvRbwdTOZ1tTVhBtYH060WdJRGfozup5MgmXd NbtcqRnYc4z1/tugPmDvyv0+JlQH6Xt/7ZqyIeMWThfXEyJB6BFveunMBw6C wlWJa3TdedCv66IY6dVDOMcBH/99+UD1eey+u4cCpJWSob8WU9BEs6TJZFVC 1L3anUO+4+DyqVzornApZvPOPubeTsG42wl7b+eT4eumqY86t/6DGCEBU9Lz USg4Z/mhcOMA3I5at8GtZRY2uPaK9pt1wGIrnZ/CM4gT/WyGVwT7UZbMcSn+ 9Sw8uJYwajS4ACt7n1xwsiwCDl/6bqc1f+JieUwK3ECDmhu9xfWsZBDWVN9z Ys3TJQ8+EbtPJoHn/ObO4Iw8JF1zPWTxlob2udqvHeypuBS3v/6JAQPPKw9z J2t2o/J5eQnvvBHcfMz0b7BsKyiKuE0PtFSgrrxc8WXhZfRcsnQlvl9Cw887 uDtP0iDEnOcKI2EEHGt6CXlmNJBW+c4uvH8CGvkeOz+XaQCzmxdL0u5R4CSl XdKVdY2Pk0ofMtz6IY/TNudRRzLKTxiGpD+uBv7Gj+9gAwMv35OWPiTWCkts W/+8fTsJsSc+ZF8+QAc2h7+vBxoW0aHFreEzGw1bdChEb5tP6Du9Po7jtR/0 +0R1mtwcQR9eajav7DzWvjUei1YYhzb7gOjplLV6OJ6733VsGlRaSTfPJy+C ceavV7Oeo/j4+wFH72tjeEy/+VC1QQOcutli0spSCd/zx4QErtXhv791TSKR LVhNsErnVF7CpaSuBDfJRrwlWiR8iJCBW0MrZYI/jqFE/2WO1rNMVDT3vrb7 bReGtSvVcpYnAJs1SW18BlHsC0W5VS0Sm183e8k3VKDQkyNnGyPIa/vGrDrj wFfwHdER+f6LlSjfaNi53mYRV/mCDXStJ4Agk6Knu3USJJq1xpd+zmKTt/PY HGMIP42cDjYuo8Blfi29z/Er8Jac8Drz+hzqe25i3tg1jquqxp2OZxkY6m1H 7isdRUWSy63ydDqE8tVy/OGaBQn311b3X3ciy8fF42R+EpqL/pAvVqHgL/uk N+wbSaiBX6eDX/Yih+/e7iTf4rWn2SF/Y8tP9AyeeRTNMgyWRG8Pv6czwP81 SG5scBhsf71R45DnJrhM6XpleDOhW8G/4cK+CVB/sW7x03gVqmf0Hmo4VIUv Fh+pHKeXo2oyq+vWiVRUu3c0KnbPLAZ8KUs91TUGDlqZDYek8jH99ZH3bv4r 4M63/DBVlZWQFXc20z8mHx3Uxu1fnqnH3/tb5a7sZ8D4wbGLKRemQM/rprH0 7wl426Dlvu7vDCQ8+R4TwEVGomGRuqBjFpR/hpqU0kaMLRi+zJU6hDe3ujlQ ssnAltY8JV5RCfDeVtN6fQ5UmXxJ2LhYiI7NHLoneehI2H49+STXLJ6l/7n9 iY+Oz8U+K+UvNONuybEmV/UmSE59+8umrhKCKfI8ekntwNLzmW1GNBDPssxI 9qvPonXskPWbd2PomHJU5vGrBuhVP/T51RUS7Hr3ZSuHBQ0bBBJOxLfP4/Jy gta5oVHoV3s/bcg9BoE7PnEvu81DQWGC6LIeDZylQ1f4WXpBlZV+sdKjDzDM euedy2nA3Wypbv18BIQbPnZu4V6r4wGNZ8cai8CKmyMQCvrArlChMId/BBh3 x4TTLNkJjK/U04GcLAQFRnTJhZxlGLtLDKHGLIF8v/+IlNUweqrHex1RSQVT H/36R23jeD95z6H0nw14+KG5yYNTNDSWGX21jU7D5gZNLo7gQgxT1ZHPzZ8H 9oPPHZ36GHgsfpz/xt5+fJNykHo7qQWkDBquOa/5sL2e84J/aSNc19/ZUZHQ BrYnjvW3f0+B9/fKvtXwtkDd4//4PV+X44WswTvXt9SigIFADs/mKTBxeb+/ 4usYZJPSKj2MmKDu2kbcI8lCeDRx84ihWQ/oKA/vS5IdhhB9WcmfgmQ0yf8T uK2IggoLtjEFa5704DYH+60tY2BnOVKtKctCYO60Y493X4GZfRSVh+lj+LTt w76JrTVIrP+u0fO0Gd+afjYM86HiTgEXzg84Aoae7lKeTwbgv4Wh4EC5cdDz jXO7UDQAP2TumDut64fwW4x3zp6DYEGYwtWyGUzcNPD+RXETjodpEey+D0Po DceR+EtLMH/hQ8jwq37UJDPV2pSHYNMll3wJKVZCg146I2WchXBScPsyF2EI 0p9JVfJVshA8FrpbpReZePzsz55G0yEcuhmvpCmaDaGL/C0qq+XYup6+vTAz BlsU85yrjHqRrhima6k9By9YAmejfAbBqqXhWkd7KVL0DlAE/akod0lm7Oj+ 73BstIkRozoK662/KIa49KF7XhzHeH0jrBxgzfW7PQ0hXFssDgj+Re6MN1vd Pn6CNGup/A5yBI5eF/2b8YKBT8tXNQ5ta0Wj+wcclF/UYUn4v4TESyzEUNuW n8efrOWK/PrbjORWfPxoy6LH/AD60vPqDOg9eIIg+kDMsw21UoZiOr5Wgd2J DGqI5iSmX6pV94npRe1h1DWwn8dBDUahhikLUeaGV2N2ZzjGXPebywypgs22 V7qrTrYA0ydrm5dDItYoeMwaKrXhgcZL5SSderTk+psu+LcRdrx81Pt3qRnO zx7T8B+YgpDlfSbsFsXAF9Go6NhCA+8rATmb+0ch6c6vgMhry7B5T9WDpdYZ OGp7ZIuNOhmqUrfzBCm24X/xpw6AbR0SeJR9Np38jISUHr83T9c89a+91aW9 Y+Av6fRA4suaN7nv6TxaVIc7j1VeWic8gPOlJn/E0wbQzuTh7bh7ZBh2t7t+ rrwJOrb+p5u2bhI4Lawo39+PQ1rV1E7hiAEs4DVsZJ6qw47Zvqjxvdn4Zcjp xoz+AHTwE/ZudZ/GoIfb/W0FxzGCS0laeAsNlOMdInPe9gK9SGRLvAsdHPfs LP3ot8YbQQqWN78yQGzw4kFSFAUkiXNfqcx+/G41LnbrxwwKm5nf6b6+1ue9 P98cni/DOIq093nLKrhS99OEuYuGY+fLj6QZ9YCisXrdOxsy8FUdNHi8bxXv ZjWkSJBnseLLFWUf3mBQ+bHumGkmHRipHr+8Btf2f9POUbYfTZhALEs8WUeB /e0xWQ+LB+FlYlRRnH0+nOyO+sf4SwLWc/tuy61xW0/zefPfFWR0u3htZOr8 JJrpJRmNrHFc/JNrGuZiXVCX2WKl390EWyyyBJKWqlDZLqrAfjsZa6dCN+3U 7ETGli3hkhMFuLDOLPxqajQ6l2hIn3OmgCvdG87azOBmn/VfJ9c4gmTzt//e 7z5MJovJUCP/QEDKW+kMnVGICkyIuSS6BP3hf7qa1lOQlP4jUpl97QwVj3q5 UAHfyhtOVHIUwWY3m1j9xjmMerSY9juwHYPGcn9t2DCKTVo7H6t3juD07dnx nHoyrM3amefeg3CZzCnU3jWFsY+/ER40LaLQ6RPwsnoE33dvP1vHQUO+5cTV R0IUVHzuIC681IKnd7pHWd7vhwgP1Y6Ndgi2CoW7Xi0nIJt475d3Xmv1j77K Nn1yGj5Y7a2N/TMHUit78pg3B+C+9IypTFoLmMxnRT/w60eSIu/iKS06Lj7P yjwnPQwKPsn5rLL1cLLo1W7LDV/RY3S8vtinHiMDBI5yZ1Lhvd2XpXOWdLD9 rEBvn5rC21mGLA60BRQajbg/3fIPb627ST7FRcWHemeVZ13b4Y9f8v6Lc+yE D8k+u+7kzsAlwwse31wY0N/lzjOpT8fNfrO7sxhN+J8bn+GZ4imsZFs+dEyZ ga0cI/btWIS2e2SK2I1I+JfbU0vOmALagWT9H650+LLh1WwMZxu+5fiyT+dN NdSelK5ibRtFVXeJkFvTa1wmE8YTOjoHY2Hqw5Fnl0DdO8GUwD0LWqR/7Xs3 MeDmbndtv9JSDCQciTx+sAfEOtMeZ0+R8QGQ5LbkT6KJ3JhsxlgReLnNNRzr pqGtfPuV327NYEExEDuhSIOBX68ybVvykOv7gZ/7lKtAkZ34vd19Ag5nMF0c GpmgVbVyx36wFYgZdw3GDdORVePE5euVk+AXpTs09KYWJgutnAsn5uF6mq8M 4RwFxE7X9s6mDUOE0jhZ32gWJJklb35OkqCWys5G4qqDhwbC9m/qB/G6Kzno /L4hXI46/ZF//TOQ/LCPYuneALdDE+sN/MjouT6q6Sd5BC81mzzyyR9ELCpM OjPTi+S/U7ter9VVZ/Ssz0daIf55NbfOcWsnvJ+VNTs0O4ysrg61gp40VP8W krgpexWrRGrSdY6NotCzZxEG9zuQ8OrFREBmJQrTwv689K8CjxvNVgf39AMv Z1/svvd0cI5vj93PRoJv4m0mHwSaoT17jfk0x3FQ4sNAbgUFee4kOOj+TIJt 8vlVSc6FkErs6PKK78TbOtPsroFk9BZe5VwcHsDgCjPBADY6Xn7Jd+trCg2M VF5U794xCXf3hN579KYLhe8uer4KH8LpwBMJkZvX/PXqg+39Dl1A1/GKXM/S CuwvNKwv76VhyDpWz4sjQ7jQH+f5ILMIqyPvST9gm0PzoGbZUOok+lQqEV/p 9+DRVHm3bKkYyOv2UfvLNQ3J8q/aDFtG4M427iw56QR8Tc4Z3qNJx9dOqi1O WTMgP789WchiDFq1Y5Z6Q2nw3o2P+xXrLNwxC7PcsXMY3lIf8u8VbIXXUxFv lyx60G7Qa4TvFRPzCQHJOvNTsFXUnTvwAwXObmZ/dnVgDgyLuFd14+kwJei+ f+v+IRQ6lLrLproMkg8fSxvc04ib79AfvHzZg6R9rC5/o8lIsHU8LKsViyaM 6Sd113sg/aPtN8fDtcDT8F5bpjEHsuUtn1dY5iDRln7z/kA/uu43k3ooSoZ1 NOdanuoGGJGWsWd3a4FthA0LvAWJWM4jx+dv1Azv8q5OTKw0YJLJ473Kr2vA hJf+zmV1CMN6VraoP59DSXfH8V6ZXnA4jDLMNU6WYv6QKC2mofjRG2D2dARN uER9U8J7gW/ZBeyTGRhFcda9VNyMjf0C10pUR/DdO74Kq4v5yL/Cfu7itkGk 8M2yad3pwx9b5haSe8bwq2Xhv7CqevA9kebx+8Q3pD+7eKwhPBcj7nUUOD0e w5DmiuyQh3WYHDp+b6dfC2ytiH9/PndtL63vM/ViLKKcyDvt4iE6aosYmtkL rfmKlbXT8yM0rPukvTdQeBz502XTKKWjMLKjLOAKpQn6955zXX3YDSmpx1N9 j1CA86J05jPxFVQXvuZLtp9De7vnUwqya/wu8zJS7VwDHF+RKL76cA6e3lHQ HhwYhKf8Zn5aATVwMr3k1JBdAcpcjM46ydsBoplqPDoKc+D4NnWv/eFq4J7b 1wLRheAcKhX5MGsIqoaR9kaQnaAuWvZuYwILIfZq3tzuy/PQfyxHlu3mezSJ r6sIGKyCWqc7HdfDGmHnNQX93U+mgXz3rJfjyQX0Wz8r4XJmCsuVVD4ebl6G jf45NgIRjRAbqLi3tXYczLbFq6UkFWD6015lmbOz0HlmtolXZg4irNdnn7Xu A+kvS/tUkmfgz0dNeVnNGQgem1G1aFkApZ3Ns8VsI+hsmnLF80cWvjc6L1l/ qgSr8u4997/ehFX9YWndf5fgpfykCtGHCp1dVvySVky8zRgUW71Cw6Xz7j8f 7WSCuPnFeZsEGvyq720W5UjDi5lWWR/PNaLy4BnFnaaLaOfoZfVEfRl5lF9T azbQ0P7qp33NPkzM9ic31FmPgTGX2ZESRiuw7XlvxOY0ATNCtya3Eenw6baL aIfrEAgt+k60FXVgbqSStUjHPBStftWcYKx9lyszV82oG/wuXC6JUu4DKXnK LWOxcnDW+O9iGW8bKC066PXOOkHSf1V8H7anIGudWytLYCHGfcgknoqcwjzl R9mcHJWYm2++wcG5HEd17bRLVJpRpuj7Dn+RMpTMNG7IVO3CddTOHIpOP5j1 6ST/NzONxP86/8YoDyGq8hrVD5LQ5QuH5l/dGXTvfN5DenQRdK8FDmj7zkB3 kVqpyvkeNGDIV/EcnkXPlQ9/nVZngcPM+gTn2xmIkX65Xi8oH79IziVlrOVY D219c2zLPEj0Hvzv/vgYcMtd/d18pRdvh7DL1Qr3oRPFdstnzymou8MnR7mW CCPt8RXnJCeQ9KjsuqJiNr6sV002xbX+O7jvBrs8BY6Ai57LehqO4A+J9SIs RMm5zLed7mRUrBytkesbAhXXbqUnbQP4Qiz2tlYnFXOfG9O3fi7DaMWdfkds kjE0Tcpj7yMKsIg/m9zEOQ4S8NFYvj4NR44WH9+gUgOPzk4PX+FPR8tNrMOP M0nI9GFqK//XDJ966Qvha+/PX/WQ+ZXJQtTzyXQuer2EBb7/nnIcWsB4gS8C L9Y4n0FJk7ts2YSXlY0pcgOtqHfqQooadQYKnn86ekhyHCwWZ9Ik3ViILO/i 5P6RF/DMzlsNgl2sxLP1hmXTRSxE/xs5/kziFJ5bHuZi38hEctfS5FBHP4py N81VnQ1FgtggV5RgBw5w8fbtkSuHd7oue5PH6DAU/u9yUOkf4KHbEFbdBoB4 Urgk5V8GFKi98T9K9gXZu9m+gdMkWKenfUrUno0Q8HCZ0PeUlfDvb9xe/qVZ sPssk7LVYgqc0lUprDWrWC7mAsxXbMTvMi0vfm5egqhTU2+eLTDAX/yDHO+r PLCTzudZVa5G3sipYZk9U8D5/lDNKL0byn+Zf2Nj9sF9iktM0NMJaMebpJ4V Mro8ImsdXeOP+4oF+hM2E/iakrs83TqFLuEcOELlIrgZRE4PGHISzrzYc/Xl 8SH4+ufw+w/zv4AlZo+saEYbJk7EsoFxJxyIqmL/LsNKMGetin1AXQGeA9yJ Q9cbQSpfULF3Qz3+fF+0d7QrDf+GPfpr8iULNtSwyv5X3g+h9j9rF9N74VyE Xa3+mRU4kGT+qrh3DPTG7hjYt1BB5/2R/ksCXWDqfd3TqYiJ4/NUd+mkeRT/ lnFi3ce1vHKI58ztZiGeuji7Uo7NKF391GnrpVLIDFc2/z2VBoxrB1P+cNGx 9vBGa10mG/Hyy4IH24fXEfdU3DImTq7lCE06vr1lGVIJN1PVJqfBMWbj6W8L 4zD2ibrNma8W5XwrA71YJ0E18/z2A4aNkP73vEfo1SJYEruwWno9Btg9O6T9 tVqgs7rvcTV5ET+wiz9pLFzAsnl5ySaZZSj7vGsL+R4DVmrVPu5gZ+CY7/hj x9fz2MbrxZf9/BuqF0l7vYxKRN1NZlKtug2wFYNr/3szCiyjhzJnP2cBKeNK 2mbyFP7W3BFh9nQIoluEo+uuzsJGd8/g8iupEMw7WpqsysCGIGdrqUEf2NJ7 69uyEBOHsP0LrZGFcIgutl7BdQmsuLhkK5Z7QCWrw6N+bzHo8WTNMasZMCRU +7nuaiou1HI84d+z1h/BUiODnjSwem5uosj4DLkluR4PrAZQpbv64HTGP1BP XPxUndUMjpuyF+P0piEoXMXsw3c6XPreEe+ybxYbBiO9FIXZiEG2CsFOQgUo XGm4+eSVHLyatbWriDwMn0vVXk4Z0MGv4sitiytrvMjI+5ZbSEI78VmTSNV8 vDqruuXGcAdKW5iELU2QwPivj7ZQegm0rfBfMU0ZA8/uU7NFcd6IwW/S9+jm QtiRpU/brvbj7aKM3W/1V/AKeeN+/YPzGJauqvH9+RhujRSK37KTgkrcHJfz jyXju3FWIY+PdOQ5y6jcUsHEB1KPs2ZCV3BvUyvHO+o4vNcMFB9XqIA9Hsti pbQeUJh0Npc7RoKCGboHnbsJZmFnyZhfL1wxz+MI3ziLbX7NOssL2diz9GOd 3bpxWKrl/ur3qQG9nDQkHAWpGOv1n0zD+ja89agvTtCiFRz1dfUvVxKBZFxZ eKWtGhUvP9ko8qINiwasKkZdo4Hzmlvz7uY21JEcXYlvncWTauWfnJRYiKq/ 3cgGtnTYO6gRntoxDc5PXc+VhbVDzMMc3NFfiYv6AhYG6pyEtk2yn3gej8FJ hxjfoXv9YOOiGHY3Nx/ibsORUPMlTFz/6Qiv4gxeO2pg6XtuENbpc/b/dMuF bcrfnioIf8I7He8sGqsmcb/bAll8/TD4PpNzOsvWj/88Pg1o2A5DxYnfKv8o g+CpZd2oPU1BQ3fep1L2A8j61FQwNbwM9onwndBPGIHHOmJDtg87webvWxXv y7U4XbXOcPeWPvy1HHw7xboO+so3yh8xGoCxH8xPbgr5uNvSPHZW5Dt4hhgc T916ARwLHmmnjM3ghPo1jv+EWIi8u7ZaEB2/g9Gq5MoHji64pPlpMffABDZd 6J5Ylibj9Tk/nqtGC5gox9m/fL0Pf7+l13bkD2Pd0bP9SVYMZAQK3QuJaMcq bZVLq8YkaBlRc+jQ7cckZ4Zd7FAm8Ir+kdMWXQbRvKJez1NL8OzOcf/TgZ0w cc0kYnBzBQ7JXS/cS5rAwfAo82EXNqJvb0UddXYcfsY4h+4eooFvOwGH3Qsx KdFQ9P6zEKzC9+8M5BZxv2aO6tHVWbQN5XoTe2IYQrpHLeZ0RkBZzr6VOjCA mSaP0r2SR3CjuSpFcFcTipl0n3mSNQ5cPyeE2hba8Mzplfsbmlrw9xnH0q61 PCy7bhtL3zEFm1eetrVL9EJuonI5564snDhUf9C9qAod7pYc0suaxOnUEy4b rXuR/56OTi13DU5uFNLzsO7BuxkfZ7qk+7C0/N6rneVk7H0X7tk92I3p9gGq ahoJSPqV26ygNIQXBFr3MX8OorC8Su3Gil4MuqlM3Be9iJq2iVqWkdOo6/G6 KqexF4aFPq++nuhHrofBTrNGg/ic5d7GktOdqLuXFcMPkZHbcz5NKroLy/sf aL8TmcD9lDyJc/7TeEsrtvtsTxsI5RdbhdMroHQyzzd3ba5s7ov+XJKYAlmq FgdJqQNUYzyuXx9uAV5IffNptAIdCvt2RjcM4WJo+rbNDqVowSHU5TzTCpks T6Zp+xoxqvvDw8QrDWD5w++T8V8KKAbplIznd6GsfY7miVgy2J+yjlFLmYUJ qWuleden8NPWs1q132aRf4RB9WcfQZtub32lyAYUtjjz6F3NPAqapGks6DDw 3Zbur3b6g8By79/5l8IesD1KdIURPQGU0smjqXZUKGy13+v+aQOR7XKsVtpB bmLxNq4vqgEk1KPfjdwhvIKvjTN38Go14p7C7lvrpvtBX3ej6BHfBYyozhVW 4GpA29az0cdVKuFSjvv7lj/1oMS9Y7GPUozelnF3p6trYXQoUj1+Ew0CHFJl Lhf+geArNRbHi2ngLJ6/caq7Bv6U6dcICDfCJjLn3rLtLeAuYmNmrl8Duu8P MI8RR8FqZ1/dhigaXvL1Oeu7iYxmD7b7ZEg2g+LhwdUFvTZQGGyV/6VYjTYL 9X9tdKLh8BGycSxXB/AKBv4iZneC/7uA2xdVE7GAvxwjDtPhIW3Ta4XOReia M47fzcVC+Dlt6ij5cRo5vvbNRLxbRGtVo7dVos1A4WDL+7m/HCoU4McMYwYi OcIOkDsG4PV43o6YQ0Og2kH892yECrRjXYKrt1mJF6KzDyj1LmNIjWNU7fdQ 9P46Ll95mIpVIQtv19skwY8dX57VH+tAVcZikFRTNX4yNjQN/pQB0T3fX7vF DYNacXz4HXsGLOaGE6PFKFgVFfbEtvQfer44RolXo8LWgHG9e5rDEPjhQdOH +gIcuis7rMv3EmOX8o+ZSjPRCZ8fq9ccxJHn97mSpAbwwvHTlpFJRfgfMi5Z zjRAALsH1P8qQA/CbKzwLxpoi+44OcA1Ap7ey2e0t85AIWlbV+PbOZh2F7Fw FJ4CGt8Pxz11VBCdOrHw4zI7scpbTqp3dY3rT801ZvKOQkxQitp9o3x8eOLN hR4uGnqaiU++C26AY4zTwqbnGOjfUbYlomoG+d855Dj1zyOhq1t7949fILUp stNWYhG/qj9rvN3HTmwL5DmoFz4PPnv+Oy8Zz4Cgs7vO3zs0jcaZ7Iwz88t4 aoTSYZUzCvK+mW2LO6lYwv1gfMuBeTQs8ZKN75rDPfQ5TA2kQJ2yybnQwzXw n55F+XYmGR7PF0/rmozDpj6bv7TYJri2FBVprDMN9tlR4pI/2vCqYQKB0NoI UXxVdoFaRGxqS2je8QNR+b5Y2FmhbOjPZ3Wv/68N9iyc6KVUIZo9fRCysQVx rlPe2Cq3CEX/mZsW36Lgxtd/Btu/0TF9/+Jb29+j+MVFJmi0Yhr7LtScpaou 4LaadqdsV8oa+0ZNPursxc753M9BbTTs0JmtZRUZxC/s1ypJdxfBxFD/perp Bbiqe0U/uWYB0jleqdnN02FmpCwkzuQHmtE8qc/DqMAVQ/XPZeMg/PHfqC1r vAwWGY8CVmmDQNL31z2YQwbbOx1xKZGsRIv9c0HVVUw8eCep9c3pRVhFxabA ZQYcZl48O6U5gLr3/soGpjfhCD97SmVEK8Tb3jzrJ9iCp2hSOnc3NKFikkin X3UjDogS3nuvecNBV0trAaNVFEyLe8qwq4b9zxfvjxM74H8ivaf0 "]]}, {}}, {}, {}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{False, False}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{True, True}, {True, True}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{None, None}, {None, None}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotLabel->FormBox[ TemplateBox[{"\"\[Rho] : \"", "0.5624184184184184`"}, "RowDefault"], TraditionalForm], PlotRange->{{-3.445478481141891, 4.129357812170042}, {-3.4998050110407437`, 3.241929575751458}}, 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], PointSize[Tiny], AbsoluteThickness[1.6], PointBox[CompressedData[" 1:eJwVl3c8Vf8fx60iRUqkqGRUUohkVN83MkpJIWRE2kqFioyKZEUIRQlJJGVm lPG+9t57X+viWve6rmv7+f11Hudx/jnnfT7v1/P52m/1SO8WCxMT0ygrE9P/ ryUWWpfXUtlUTKpbUjdysqko/lGXqy0sxWuVchdkNDsQRljKY6Wy4Q2P0qTC 03qYtEv+UdE6AOb5IZ/ScodB8lO/tv3YGnInN7LzCjERLk4EPJQ/Q4czcdox V7VnwYBmL/ayPhaVLz2U/MifhtWEGzYMg0Uo4G7zP+67BB8qDhSeVehFYV7G 02ShLvT0jTxQfGYKkiqKLKyiJ+Daaa/IZEYRpFgs8gv8zocNs27m5C0z6Fv6 WNHkKRU3KhHVJk5S4F6clVZ27RS43yW/9dboRMeXN2/EMzqxmRIVcsqyAYup g2GbWluQjcmc7T+hStzakLJD+hkBX51uOLeWzQBbuQq9XZ7zoBD49b61FAlV HtdYZc6N4enFYAVrUhYorrX+bfzpixLmYf/F/e4C+nLPgtJYN1R5S+jpDM7i RubywetZdPxh/O3HB7UO3O/2stfkTjN+HO8yzCxtxbeC8iKP7raji0v8rY1H GEi4qlS+98oMXo7zeWOfQwEtdbtbtCMk0Il8VV6fOIHXTOS4qpLH0OC1ukKr cSOqJPrl0Us6MZN22DSwZhxEGS8f8f2agKu+mZmJYaOoxaxj07c4ios37shM 6vSBhfW2Ly8u98GyfYRf0L8FvOlOCua/tYDJs3QPhtEifgrYH9SUsIT6QVLn zsYVQSz18NbJ1Qo45ce89InBrFITcZV2+BOTSqK7fOUGQWbCJbnXOVFSa+gm EHnxhdr6f3kglNLDNQBRqT13yz0mcPkVuf3Q8gyWcvr/Ut+fCYdxTr/NIRbH kj7EeFeOgHhFCfGsBQlYnRjBEpsoQI9n+9y2NgqaVUN1b53zQNnjyXu9azVQ MlUpWkKbRe6Vb9rSfgx8IpR048C2criX6RvgJFkAyzuPVFto9qFvlGjKdaU+ VCs8rPv2QD+0h0Q99tbtBw/+xMeXDBk48+vov3cLi2h2bwfX7+4mzP6teKEk vhGF+oS6r5nO4d8P/fsyZ+m4OVjS63htP4TEHl/efH8E6stmTe4QpzHjyX9H 1NWm8HDiy72vtWeA0s53LUuSBrzHthbbkAkQmKz1M38oGHunbq2mzOdhcxCb V4h7GDzx9pG7eLkJ7CbW+phDm+H1PPOP+uQ5fFgoIvqmaRbZOZ/RvgbQwZ3E OHn3Lh0GdQfdbC3oEKVrxm+5iQ4rX63c5ktb4aftI8JycBdUKugQOYSp4N+j EYmCU/BRKI3vXXYmVrI9I0gJF8B04EV2/aoZsDsvnnwvfxbcov1uH2rboFLy vchtjo9dRYDNQc3ArQBP7XV75Gn4FT3cSs1TSocxecc9admfo+j1KeeEqHI3 HrK+eEzbdxDnHFgsz5CJoCw2o0yU74Ds7YGm1txDqM8kQzM8N4B/srW/yT+e RorEKOc0MwULfz51TbjVh1vCVds+n6jCwzEtspLb+9GxNumtJmEI73B4leY2 TcKdvijTVIVRaH+2eLCvbgCp+uX7iv504u1t7Kuxxk3IeXhK3FulH+c2E5xK XnWCmNScfce+bth3fbdU6FcGFpaESToMzePu8MKOgM8UVD7s+3vp9AzOJnys tHeOwY/CYR0CXI2omgsNZlp03C2+1e+i3RxK9knFeb3oxxVCk+D5Y6M4tiU3 qsO1Dg0u+pzxHv+JVkLqZ6461mOIpNxvzk3ZqHZbpkxirgUXvx4z/rS3Fj/p 7LTdf5sIGvVUlouDRIjZ2272OJGJMNB28aSsCRPBR7DT2+cqFYrnPi1NF9Fg z3aGzLkvPaD4+5QaX0Yt/P3iEey6vwIIB1Zi5nsR3/kq1I++GgEBbOswFByF /gnWOx3nO7FIR8j8oHMT9jhkg9RiN+q5BRcwh7Tg9/3FvjNyNLhEuFPvtH4O /sveeDJPZhqTp5V9tO1mMFxWNefz9S5Ymz53Md6vHAL5tpnA65/QvPLV5o9R LrJ2HiS8vr4KipYu8uEHmVXsjx35K1k6gnOnNjgKjBLR8fJQErtWA1ouuhJb TxKQYzni0q3Pq8iXJ3GiMn4FN0g81ub9/BmePbZnGhdMgbhvKy/ktYdgyZQU RW8dhoyfNxWcxFkJMhIXWfxymAkZ3na1KS9mkD5kJHBLkoJOq0ek9Ljncfrf tGbYhzk8pB9wP1+rCn6H/Lq+QbwUTPbJCr0rHQX/F9f/ezY8DKq/viremmiG Rb6C3H/adcDuUZ0zMtQIPHf45P0DkpE2Gbnl7YNhNDTapXX9LQlJFrq6CV/J kL2VukPDdBw4b5WWChmMQ8D2Nec6qXH47qM3u1O1DIxqGqlNeSUgYxtei4sz qLTsmLaNh4qy8oMX776bgjPM8i8JIZOQ6dSVPWG1gHtFJT9ucprHjZ92eC3P k0F+F92NMj8N534SLANvk3E1Wi8vTWQYz4/N9KntqgPCHKem6PUPSGh4Gzkd up7HDjUOStsnsTNGp+/rGAVNhvOfmOlQMNWhWqM2dx5Xr9okbw1ioG5tZB1B YA4Nfgn5Ttow0Gr5uKFqLRn6IvxHKbfHIa/F+MjoWSoSS77UtqVS0TXsxGNS ExlSRC5OzKePg8bXxBau9mZ80/Xj++3QdiQyv3r7a/8kKvOKFEnKkjFdRe+b mnwDWgc5fvMq78Gy++a7xAWGkCfc8NmVUyS8ndmY/yqjD3aW1TTkzQ9CguPe vcdk+kB41VK+d2MXHPBLrPm+i4XQffQOh6wNC6GnzXEt/ssIzH/10+HdO7nO jSNbgwOmQGi2/Clr+jQUjOsn3wwaAvp+8/r5sAEwLQtqyYiJQ31Vn013meIx hd4/nhw4iYvmTc7K30eR3/u++BxrB+z8Zy7ye31P5A5IZJyzHYYnur2y041D YI8TLd4XxvDjfORhOx0S5rZcsvFpYiKUCQ29nglnJiSLHn5uUDqIEVyCvI/2 DqIL6ynO/QJU/CfKdDD+8QTOWD4EpndUfPVJPlFi8wze5nHW8qnJhOj66G6d tnR4MBQx/N/1VVT6oyqprsREIGJA23v2IewXUkj6MNWPEh+Mgg6HVuPjs7He r65Uof9wdoFFxCSklA0QXT+MQzhdVcPPi4Yq5WT+/ybpSKbo3fultgwBG3i6 i28sg/um4WhnEg0msz/n0l1n4Xyx5yk26y54spOr/vloK1jd4t+trVuCxE9F y+r+8ShqtKXE+d4MurPcCNbfRV/PuXLLs1m1sMlTpPNVejXsbXi7l6I/C6Yi Os7JXHOwn8luNutsJz6JqjpTTK/Bu4sTAty8RCRn7NHYcmAYo19RvdmFaSid mjuktH0aawPtly1zx4DYetMoNJcMBzhGfR5XjUFLSknrh75RuEg8sVn37gAm aZYknfk2jAnyuZytJQTIjyvy2X2xBnwT1Y0NRIqASYfwgff0HyRyS8p7paSA oYvYhbjET0Ce1xQX4+2ESC1D/h7vCrD2OCPMmrYCbdhiNXWXSaX9RvTb8aZO eHJ90wivbTuUGUT62nzvBA6lHTHhK0RYSHLVreydRR2WQcmDarM4JC3XcSG2 EN58BjMi6x/Yze41JTj/G/3Eo+VU492R+alg96LGDLR+lRIjHluf81By7D55 EkRXFRceOUiCCPP/PLPGCmDX8zdXXJ6kguE4YaUqrxMuO+98fUqzG6T6qZFS TYXoMuUw+GD4AzYKrAXo/asA/ufzaSof/yGHAzGUM34ISOzimYIwAU96P+bP y/TifKDvl4+rRLzwkdb713MNV2/foOiarSAvNIjHLowDUbvhjR7zBNRtGxTp NFkDs/P7hh3slqHq4CPVZucKCKu/8WSrYAmIJJm7l1dNgNDxDfmHSIOQZpDb XMU1hLQ3xNMxXoPYX+KaaUbrBbpY9cXshQ5ISucRzNpNAs9iEZmDDeNQvH+3 KIvnLO78KLvVgTiL33g6j3jbrKL1pfKTxmeXsHRi47H/JgfA8++Sin81EZ6F ue6P+cNKuD1Wp+D9jIXAGSsVVn13DB8YT2oNFo9hp4OT7M5acxzb8bogf0c+ cIWdstH0HwQpHzjyTngArM9/fj+8MoD3rxmYD3zpx3q2MvtcGgNeLvT+YhlZ gM/URxe0OPsxxPSeeIjNCL581Fl36kY7elfvbXflbkKb4onm1BNN+KNw76Kr RCNqb1yRrzhHR06r60r7gmkYNkH6+iSSBgcFS0KmG2iQfiX69a4zVHCaCH9T 92kWBC7nUTeUT+Cp3bEL73aMoOlW/bVPr9fAiKnY0yKMRSXpce/BV6QBvHii pVU5vxeLTA0aC2M64L7JN7fRmAFQOVG566j8HMZe1zh04sEcDtiGl5/WK8N7 YX+tOcrKMXHLMnupBA3PeT4V+LvOsbH/anyPRDSi8uyts/Pr7xszdl9SXmed p+wSp5ViV6Be0PxE0NlmEP4lzfgtmQc9rEWeYlfmkddaNbl2vRfIH3f5YcC7 CtOfJfftXliBM33i5S0RLUAnUFjkZFphT+ypF42PKtH6ZPKdtLYOvFO85eRk WAF+Dqm9m6FTgJqyd9zleJkIBfoKL/1PrufdrfDk0YFBvLi0MlfysRsFHqZd +04YA567Hw8deTkBdxvcFfgVpnH6a97qRdFpNJW6GHX3Zg2wp8Z7x5S2QLRn +lDIVwYM3Fu6oMZHgQPxYovKZ+l4dkDKwmoTDTPlGKxPh+kwkH3Q5TJpFvhE G85H7pjD7l/Dlx8coSFHs3k5iwwdFRU4/qk707BaN6Lubi8VEj8kHz2kOAe6 0sqrSa3zUMY55LkysghFglpc3472wiIwSDdGBuFd0vadYTtm8JHEob8tPLN4 jCnwQ9xEJhj+4blyvRRBw7/+ND/fCGgWuhl0zwxBYCU2NgXPITdYvugapqPu n9LFpdR+ZDV3tr6wl4jMn1T6rN/Q8YVGE/t1DzpKba6eaz88AoWyQoG4nwKS 78+P83IVQWveG7UTOY0gnGvS653FSsg8xPNEl8ZCOEXSz1MrbMFXNoH9WQX5 2PZrRDqFeRocLjDpPDGdhppwWvj7b5W4vc1E6TF/JhY7cE+N6RPR3eKGb91R IkZ7lb03PDsJj7PusDis+/mdAfP3e7e1gCzPo8JnFa1QzfflrFhLJ4w1Pbfi /NYMX24QrlhZMqmcz/GzYnnHpKJ8RtPIcLYR0GO6S3GwCdSpI0832pFx/hvj 2obGSXz7toRhc3saDvsNEL4bTsPf/IBnA5RJnIgdP5LQOYObhwVYtGrTUdtK ofSzcSF+/uJ9hvV6FZDOOHdsjSyFNZ7AiR4HNoJXuDKzd9QGgiL7LvYr9b0o 27yWEKVAQqang3fU1XvAsnRF4euzbjgEGuoqOxaAVrbkBfcXwNJKouv9yXko drzB0268CMnTz+TXGEPAdj2LMrh/BDrEySNpCb1wNP7tLHKRYFDcQ876H8Ij 21vFT+9mAdOGLnb26UV0+Uh19Gycx25dqvupeCoc+PVtR/LIHMTpHLnqt0LG 34dOhiRRp1BxmcdwwH8e9VK/zGnfmsezZeYu2oF0lDtd2suuNIciQRIBJUqz 0LAkqEc8OQvmSQ/C72ZM4o0Vvyt5eaMYeb2qn+dxKzzeznrl8Zk2CFLj/XHB ZX2eCi73HyaNYUjNpoN3C9rQdLeO/CunNtzhvokq3bgCoqIFGrzVaxB4dfH0 890zsPfE8wN+TpMQceam59BUPj41EiKrCDeh2SHFUCdiN7as6ljk9HfhLbfT BScESyFBPMNJcGcK8LNaJQqzUfDhq9c3CM6juPF5VtOe82u44M+VRt24ilfO 1S8UVs9Ct+vo8rg+HajOPGE628dxKZCX5JowhYH2Pm6CfkNwXVp2/MXqACgy Ex5Vbl6AyLtvfpKkF4FfoUEi7fsCLlh7eljkLKHj6be2HySroEKNN/Dfaiao vLl0udNmk4qxb2pmuyW7ivydYKUIbxIsi9WYSspMQuoN3qi3cmnIrxCs1uqf j/qWbafPBwxjP/9F1fiMEdwabKLz6McI5rnb1O7oI2OLtW6KxvV+LOjPGbhg 0IgRxmwlZSEbVMoT/ML82dhUKGL1Qm6eZEyQuyKyP5KMttyXrCkXBlFUmKvk bkg/lhUFXc7flIuHGj9+5q+IwFuhEQ3jXPNQ+vVz7vTMMiwkpn74vPgGDVPr LKV688GWSeYHoagH1FhSNQ83dMHEFVq6fHseeNmK/mmJR8jxac1E7Wk49Yfa /oebCrukNM1PCTFQYU//y0taM3hBXv2YVvp6D8QgJqMDLSjhVLfxlMcg2Omf pTuXjkFAwW8Ve48O1Cjv8bIZb0ZVTVOW8DMUkPAYvt14mwqhPjmWZgqIl1L/ HM2S9sGc87I3xauHcO/nW/yVDqP4NJstyc+nBZ3mYjTdaktx8jW3a+7Zv/jf DSPl5bFCtKXIrs7bV+JD/eezVcU16MdwFTux7v9bJm6e8VCdRJ3jvsLOPGSo usDz5XrtJOwhben8almMZ2Pjf659+Y6xxdLtnmLJoJ7Q15MDcaAYUNf/LnIM +329JwIKJ/Gjl6JGdwMdPeZGpmWMZtc9bcy8d5UE8F8Xa0UiCfR/cIqJyixg rsy0zGFWBr76Lae2epGOV1s1yLT0WQw6eujSDftVnN4o+UI8bBXFROLN+E7M QnmE2QEbVyrQr2+1lIwcRx2OXouRrYNobD+VcdBxFts+vzPsVKdjZ8Nxa2nF YdjhdlVA338U+J8s/VhqWAJFadvb/3WsQPCLy88Djkxg58LO+/Ze48jt8yDg hiAZlakbuMwmSKh6STdNQyEP8kvmxZt/58N/P9k4H0eM4fl+yS8LPSQskCrd 8EJuGc/dvnrwxdUlfPH3jqbR2CDGRGpsTgwawbaYTFp6ZBdazFYdoBl1YGzO +L9+NTZCNbx7ne6ykTBNrGiNteiDH8WyQ9tv9UJFf7nh9qI+PDD5YA5K+zHu 0upx74l2lHHJF22V68OPP6OfRCdPg8X7lfszj2eA26H2l+K+RWzaefQNSXke 78a3Buo6tEPzjsJOFp1uIBGEldoPMxFY89g32/9iJljW1NqdTShHRefps1ke ORi8upfNhk7F0lWXdNoCFZ3edWSKbZwEaeqcWdweCnz0d3DWeJ+Kjns3Ex7I e8LBuCdi7xwn8KGoOEnPiYJMzJKHOjPoKGD3r9JxiYEwso21278cTqg0Nu6R qwJrNq2BvQ5UzOcMO2HwYBpvbitcyukfwg4nkvJr61EcWDHlYn9EBSlhbwvZ 5nEYFhBKoekvYKbI3aAdunOo+Mwgd6aKBA0rJZxP1aeAFpST1/toEqPdGc6x PhTknW4yKpkZgUyqL1ud0ziEJFwIYia3wdTQ7ST+9H54PBA6NKW73jtR74iY +DgkJPT5jYn3gMgMseb+wwEopf3oGREuwcfF1Ew7TQ8klx9ukc+OBY1TYouj m+sxeUl4Y86zfpxP2PawZqQTD5ldeDBLo2BL+4P8q6+paHiKDIyX05jgkMJa aTmDkY+3WvVso8BSupJJYyQFTkzO35rzYlLp7BlwbTZmURl7sZgjuWsAFjaP TPqrkqHJkWH8Vn4Y/R6yS/k7kXFfrGatA08frFX5KK/9a4E9WlNdRd+JWKQb YrHc0YRUyt8mYQYVG5laE9VjKJjya+UindyJP0xpCkee9aLnZIMLGDNw//IP vuztDLTNSXG5uq0cSP7heV0WbbDPRXhAZGka8tV6MFScAvLvjJ/ksVLhGe1b iVAmDXY/4lZIcBvFLSKpFEHlIYTf/dIc8QtYNGr1ae3LAlZY+ZebtFJQ/ASD 5ctRMurnix3b18eAopNFbygH5mHcUHil9ctP+PPAI5TVNgM2q+j6u/QMQNrd JyVbDQdh3JQWk887hOf3yp800BjAt4ISJYJVnegbtsOuNJGE3/7onbhc2Ypu 1WeO9zUUYczjGuMpUxpMCPPLRGevc+5LWfD0JhKqXd7+rSSpF6Wq2/cHuIxg 13xN0lPrQcxrvXLh0aZR3K+WaOdcNIJfPXIjrQ6NYdf1J3cushOx0ZcnW9+0 HYUXq4oPPSKifYyYr+HQEPzHbR1IKCZByYOOR3WDExi4PSNbk28cHUWt59or RoCpojrvlA0JVq38TEYKEfxUUhWuv0yFe0F37ivWfAfvrDOVvTNp2HWwU0p8 8wzoHBsnIT8N/tVLCSXWEeHS7EvrkNddIP56nOT+YB7NK5YtDAIYWLKoHnon NwYf8J+7381ZgvuSFmPfqIzAx6CQzK7aaWhyiShvCxjBBqfPIruzhvGjByVB /vYavg619SYyr+La5zbmDlkaGKd1qJNyKCBeRLhybqQNb8hZRE3UtqC7n95+ riM9qCNXQSVU9GDPtcMt7P3dqCoReyjvQjvmvhJbTd+4ACe409NF1iOnWzPl ygWzKdC+drPQ98skWK9cev+IREaq4euyZ61E9G3SNLsU3osfSso29MTV432S yOsEKgOiTi+Ns7PNQlZt4/6bAt1AaFw9uomtFW4N/dOYfzAGizHMS68HSPDr k6ZjiHQXxLuqTLl+JIKMo5xHrlUcRmzIC6u9lwsPhS81eMeVQz4z+w+vom74 FzrKRZ5YxShrhdI2/lXcJrn0fOkXGey8NNtUhWdAKC6/Jid2Cs+Y5w/kX5lF j11n79BWMxAYYxUCC5VYE+iddbZrGDgspZ/5L44Bn4Yg5eilQchUNFvtu98P Jc9+uw68HIX734P9d94eWvcO+2pe02As1xLMG5zIRuncKV7e7F64d0i1WImt G/x8mP8mH57GlQIbY371aXyeSjK//ZeO1S+v6P8qnMUZRS6NS/sXQdu+SK6U eRHuxyplKGYPYUr6o7Jb636StfWE8KdfP8DUMunwl9sF4Ef2+Z1KHof8VKVT 3kITUGGwleY13IW9pg82ZvH1YMr4mzPP7iSCbZ6DZZVXDXxazPLv15sAHsOJ thIVCrAWyHAOhQ9h0rUzTJ07+/DlhoQfutZ92HDJ+xWHVxdqBBKdDDTn0OVC ULWHHR2dD4rISI12gMnt4yDKVA9/DJRC1jbScYRx9/F+Og2PxyefFA1qQ8fZ jfP+0/UoELB8f4PMCPI/+QMHFwdRxv/bs+2v08GyOcEp6UkdYOtEaaZRGdRH zakksHmiMyn4jIZVFuyc1s69r5+OUbzhp/1XprErtv7j8/W8OHw/rSp6na9+ /Ia77lSv+/MbhrTw+n1llpeANDcZ+WTlweG0K+xokXs55+ODxy69NZQVHIQH N5ttUgWG4Nr1B+M0zzm8ySmpmVYwhy8+ng3+lEREmZ9mSxsy1/dceO3encli KLDIqExaqwPWyd36JxfC0dHVgb73VjGczVMRM8vuR6/Fj9MDgqMYSoladzoy LFI68useD0G676Fj72pyUK10aGOAZDUed9prq6VMRFnd7sUbqyMoolZhda6J AV5n5dltZhhQuck3ta6BhDcz4gJ2XmlFlujbqptfD4PPbP7R2KRuoAYfP+L5 kYrj0XXShvwU/JMymEDLZoB7ctFZC6vFdW/PH+Kc6cOmUF7J+JOdWF0j26JZ P4pUo7ln9KkRvFaiImnv3QQaW25HRG2vBbefr8Kvnh7AI6rCuTquk6ilnPZv w8Y0aNWnKaqQUzHxvZm2Ke8K0O+296hUL8KCuOJ5sbftyNx3uebtvVbU3VM1 59RdB3MVOqeySppgg5eRzWGBOUiUWB0R7JoHZ5HVVOusn5CmcvOaIj0VJEUv b9rhxIDnFNEp61MLME3XUY4LnUOqvBGPxDAVm1vjBJMp8/Ai1Okc0+AS/O4c mW/jX4a30WT66vUVUHG9r+dyjIiB1J0iLqtdaGIQ9wfzeuGDluuhr7/aIeLX +JBMbhcqP3VS2Tvaglw/kjhWCmZB3vml5b09M5BOEVqD0nzUFpiiXz3Si+1q nw9kijZBawtXZk/dem86/Czsh+NPqIiprY/8F4tO18LB5QMBEmi9WqOEAni3 ptakTM7EQ0IPfOf1MtGY9J/J1ewxSLL6p2cSSwYuuvjE6N46tFzQON9MasHh fW6HZXLJaNH430ll62nU/233b3NENCzzP3A5qReHI+9zN7AnUvDRhYBdbtso aL7QIHNzogJSbze4fwmpgwnHocfVH8kIjpr0yD+juEaMyZfqRkjbyXREkL8K /H/IW5u/7ESLB98ZTt9aUKyAyeQVtR21iqyCHagkNM4RP3K8ZBoPS9a6jxpS MVuuvrKbnwx88q1Xg9RHYPftD/NGNcMgGOAWsPvnCCRdMjlGY6ai/Saulc1m FBxVm6zb7NILQ4niXpoNA7DHiH28epyMHdXhTEVnZ1DS9Ni7C451MHCLWrXj UAU0mn6Y3spBh5SBrOGjoVSgqhRD418q3BjlM/WYpkK2s8Hv2NlFqD9x8qKD JQPOWrkS+/5RgOHTlBE1OAHblFM9gxsZuGlIwXXsCQOfui5oko42QeUu3iaF pDKIk3S7ZDTaC3c4u8+PZq/7lna9uNT2Ubiyj4f5WxIZROx4S4at2VR4hVa6 HnazqNRn/DohmFCGX757fCPzFaNwz12T3l3jcPXrJmmddR4WmejqZoSTQVdo We9WGRnyDy+nrFaUw3cn13YbUwTmWbpHX+oQiFneWi1jH4Jd5vN2CyajkHih g15zYwAcJeQMDTKykFttrcjsfSY+IP+8G2qzgj4NjnVNEkyEwnhR2y3xVfi1 4wND6UQHSm1bOjv4pQM/p4W9GHjRjLW8T0Oa9lFwr+jkbPsXKm64/zWXhUrB dDNvs4WDFMyjyP/6Gj8BEdfDXwSbUoDW5/S8j6sbsg73gXhcNwRUy7oxOyzC t6cz5l0RK5D/spq0QagC23NoOS9eteG1DpkI9odEUG5M9zyhNQLPfvBFbzzb Cp8IU49GljvgyrZ341MBM7g7uCPu6xYqHpNasNXV7wU9c5sfdTgARyqOq93+ 3AbH2FU7Y5pbQHowKOyOMuK76z4h80kFkB4T2bHvDANWzpRH2UvRwV12bfWh 1BJMHTqoZjGxClI2UhPf6tMxZlqknrI/CUaDLvnc9i+FSx/zQyI96uHG+529 FSp02CmsR8qlzED0NEZr9TQBRYhD95zTPyjOf+b8Qi0HcVGSQn2QDueM09sE vJrghY2Sj5dIM6wITxEtV9kI+aSlgLi3GwhDx21e9zwiY1W294oVaRSJcg5x HI3D+P5lzBvJ1BFsbGB+vIm8io/N9txp1WUi4LufkaqSNXDBKubLva5O8NAL 7LS4lQJ6nDHf+Me+woWjNy8SlohYvDnBUuNOG04eU+f4eISFUMx44t/4mZWg J7F1ljlmDMfN+4qob8aQyDTscfA3A+d4HAo0N9Bx9aMQVUXzN5w3Z8roKWnA Aafn1z5l08FgXUTaShng7HJ/+qLkPFY6OvIvzNLxmclJ8bX1vnJqKLi99jED JX7xURZGJkBFwS9m99cJWOE14Dfe0IcbA4/3OBcPoWzcJL+FQwuGrbq/O+sw gG1cMfWTTDTk33dMvqhmBs32JvjHFZYiKXdQ9d96btbcERnSItLB75j18W+2 87BKvHqVHNcB8+z18qwFRHhz6jxj1H/dy8LPe3l6N6L0moBfTdkkVMkm2iwe nYQWgjsLTxQTIYOPKHOwhpnwPMzoNTovY7QbjdrcsoiVr/P6L/9Kw4vjr9/z BRKwR5hJec9CO46q/nKjlg/ibXXJyKtfaMiIyMk1OEfD1vEX1k6nS9FPbruy /pYq5E+OaXJ+Qgf5v2l+kaqzcC2/30p7yyA+E4re77N/FCfdr2ooP6pGc98G 0tGsSvQ9aCvD9n4Oq3eOtBgemse+Nye+0Q814cnJa9ts37Thd+df3kWL0+AX nxOZOTIGdjkzZyerB8FYdOHKo8BuaD/x5USqHxVXpvOkDcKmUF+ycXHD+ncI FNLGeAvpaKa9dkPy7CJyX31xdbfeIiJbvltYkyrILYeNa24gYE358K5wpyk8 fv5CZLjxKDIbFj4xCqeiIzn/Nj1jBsl3lXhU3Nphg86dZ7tL+uHzbc7dteRe CKTesT4oMADvKvzNZF9SkfGtjKBYv96Xg1je3eDIh7MiLw+nzISDtW7X11i+ UQi/W199RmkMBOMbBiZc+6GW+SDbq4VyuMQVzzRxuxndfy889XpVhHdl3F6X faqE1d9pfFYhrUB/o33LPjMGrkmObfIpqAWZUzV2hU5U0E4kpMYjBeLgSUea Bh2e5FRQG7Wo4NvFd+4j+zTOhc0paD0n46GTC4el1Smw9p/s7q0KM7DDQ/7D xJ9OlAn5YBwS04RGasxhdSeH8JLYhKLH9CSKdwWnl64//8Lh/9dHv3E9KILV WEb7IdjFXnPLfRL4ua09c2wbBpsuiuyv661wuq/J2dGSVeW4hixTwnkWFa/W mw6/b/Thb0Hh4x9N+3A5n6nyu1Mv9tv6570j92J1dpZ36O4VpM2/7lUzXUEu LSnB6toZSEv+7/zmXTQw7P336mjnAuon3DtoGLyIZ3ymxMVetkL39u8SNy50 QmrvuX1qhstw0yuRyaRkBW6ujsTHxy8jY//zIyrjqziz9FXv5B8mldcr0Sp7 /zKp2Fydyrw1VACfPxQkP92UCxkxD6p4tavgyf6ULR+3xQGr07Oy/Lp2jC13 u/1SoxFrwfhLnNgqejEG71geX0Nb18QCTvcWXHqdNm61qQ+/WG1dWhnrhu4a t4Wkln7ggcs54buZVGxNrfTumTKpGOY+uRF5n457Skr2nqTRMfeSwLX8Z7Nw lpK6wJFAhS+pYrB9bj1/dDbajlSxEbpUa/880a1EDQGV3+I+5ei+Kc134iId c/zGdqXZz+FiDu+jFs5huBkmytlsPgS354qO3D+Xheqz9okep0IREl6ZtTxj UnFy3f7RaRuzym+v6dlrtgv41/GmRy5lDgVafn3f9HQMrnsK8Th7DsEex2ee D8UG8MmPy77qip2obHeA6eW2buAOlQKt3m5ovfdDo5O5AUs6wi0D7jThiVeL Sw+PdaN3dMiclMkgzvbEGz+1nwE5O8ECbXY6vFb73h0X0o2viu4YaWg34SOp hu6w7mHU/cfFOWs6jjYujXUbUxpAfJ/F6o7OThBdSrWZe7FJRfvfn0tqHptV 9gcS3hbxLMCFJeXWPc8ZYOz5tjX11hjYulzzHjxNgt6LnXMrIavw83jxVrUj zCoPHW84ZHa34cFj20+1RA9h5SvWopYkMtqtHOXySBzH4p+9F8Z8WFTs+ZkS vyezqeT+UTmb8LIDMlmvsLnldEOM4Q1nec5ceKC5BxaiSmFt97Dqjec9UBby 233j1Q7gXyrkJiTOoHFWRqeW/3oPSt4QfGGWBC5GktuJyhMg7PJQdKP/OHyP Ury/w2ACIKb3m5zMIjrd+Tlmw72IUZ42KQ/VKCi+59WFkHMTKDOo9XFuzwqA 5PFf5rAM4v9ZPF4UHgKniEMuEqr9wLEUvFUrehE/96Dkcu0qSqvF78ukdqMI eTo4abwV//wT5tPgmYD6P6xrjtqjoF1w2JDcNAiO2Qo3wyx7YUPPqW2yTf1A 2iEsZcnZAr6DSbEeR8dRUko2JrWHgrJrXE+f1w2glNXvhFB6D1q8UzDQfdoE BWFJLY6JDVDak9BcSerHEuPJpahTRGTenHeqQLEd0u6OHkxqqgamN8SK/M01 8DCYi1ZGawItp/RlmmYvqnMMPB/068ak7IRU1/Q2XDsUusj/vRm3Ooc3rFgH o/j5d+OxF8pR+u5e+vnPDPDtts6dfbEA6uaWzoeiVpAlVidz6vs85iauEIUN yLDT7rnbk3Uv034RsCXpfhC43WxOM8oMBkM7jr3DF0bx+o2X5rfEqAgH/PbZ qvbBfKLf11RiG7ARorVLTjCpLNZ/tRAsYlIJ3+SdcFOnCnNTzbi1lfPQylxu ITq/AULYrpQ+2p0JB4okdugLtMO3Dt4h1/k2CPistPUdUwH+ErF1fuTXiQG9 +2/d2UTEfKM4rvsnK5ErKdTYT3ABHhv/jOo9S4dz159b8PINY8T16ddzDkSs Lus8w6zTjWYmR8NDG7tx/2TZ52kLEmb4MuYUvEh4NNvUeermHBKfnkyW7KHh VFBRua9EDXpLcvrs4+xEestodKcADU8G5U3G1VHRwpCVcV93AYp6FH+F+DLg P9Nid/mid1j+YFCLuT8ABT/4dqs/GQfbHTuOGauSYcM31rocUhcIvGdS27U4 DM3XXmaQODkIMomajZwPOAhah/7dSvBtADfRyU1Brb3AzRn/9JfDDNZj6Rvf J1OobG+40rfjF4ZU7nTkYW8CBuN1ScW/NbhSxZHJTVqD4/OJxJECMhjsqxGI UJgAof+6ThbJj2E5U1+BgCERt1eShr6ql+OTuK3bH/m2oOJvHpYeaxo+NCiQ NvCcwaf7fM0L7FuhxmDX8Rd9tVAmflEnIqoFtthPX9WzHAAz8tFNFUmtaGr8 VN1xqB1fRS+Milwuwn2BT6sfbkrBC4VbzadWioBy1UFanL8NRDSvbW2pawHF hN2nP1UOwunV0l8zCnOwg1KQ/X7TAvDILNPCxakoJkI/MHt1DGNmnG1P3KDg rqgNW/LZqfj66m3dw6s9ONKcVROhM4CHJFUsdO2JMMzYPa1t3wkJ6RvHtpr0 w/NBIaV9Jztg7x+VbPaqDlyI/6ouQ+vC3sXcgJBvzCofuI5f9yMyq4gQgx4N K7AQbgz7mez+yEr4IatjZPG3G17b3jYo8hwEkq6xrTnHFP6VOL79AzsFT0Tc VX9lNwLHs4bEQ86RYUV2okOpuxwNPkk+EtiQjI1qrvgmcgTv0LecVzAbxI6W y9LFhIH1ealvPbxpAEZ/J3sQ8zvwxeH7dYctG5GlUdndfT8ZlUxOW2WvkpE7 Rv7WtVACSvE9OvZirRRT7w0lGRx+hbEbyHoDHD9hm52FzF3iIBKnUvUZHWMo fWKXbmvqDNpK701Wjp/D+oURpaWt80hUTNnB/ZqB445Z73neEEGpAsN949rh CtUnLl1rASJID1gGkAEE1UQP7bZfyG1173nyQAM6HjgcxV8/gWs2kYvMD0Zw 5SkLu/PRWpj8fedTQkUVzJ8dpTa00mBZOjPsnw8FLO0yVaa7ZzApxIRAfE5H m1Vyepv6IA5YqIZV6A0gxyT9+0mTSmCaHxg/1/ALrQ336THeMavMbfuSYCbG pHL25cA5j90z2Pc1bF+A+SyqKEvRGCUMkNh4zP6d6Dyc9c2tvtvQA4KPNxZW tnYDdTpGqjQ0Bh1r0k2i2P5gY0+GnS1PDbpKcrwW9WnG5smEaz8z2pDlirl8 qFIT7j9xtPUDxxrEaSn/3eu4DKeUqzKLf3Tjx5fbV7WfrXNPgvf1deocbk89 fXHzq3nUVP5UukVnHhqfOR/1mZ2H0LxKCs9FKnId38MhmUfGm0ouBwJFqHjA y2UTf9UkZvzqbfSvzIavfHxc0XFtcJDiSFa8Wo+menG/LjJ1YtSQL8dxexq6 d0YY9u5noNjvivFCrVGYfPVpMDW5Fwq/jbxn2zoAdcLTFYVew1CesmPfvZAK qO8+RfBOq4Eu5V7nzRypEPnh7XRsEAG4av5d6l/vUe2zKkWP84YwmChkoJhG QqWyqBs/MwbQYupV2fSPRXyRFXHqhtAqBsYaFLTKrXNk2Xt87SUFf7zOey5y rQXvnbiRCu1lWKy2q7RhcBwTFzwvk6iTuPbftf5zXTPQ0v5I8OsLKnBeyvmT ZjUJFSbTktW807DdeET7jRgZhGNad18UHYcWpgKl8/uCQDz/yORP5Tr4fGli rwjXCH6LGMuOezGKdi1pigrlVGgLfjglQKfBSNFM3rWIbnR+qX3GsbILN7+y jObbOQU5To7bzHJmwHO33BluFwZW7j7a7EVd97AXJ0QCWAZRf62BpcNkDFme n7FS+B0NhO+shPmaXBCUbOyO0JlHh3vbrnKsLqA3XbjBWSoIEifVN4f0ZOEm dqtf/JatQC4ssbY9WQW/dyZw9wsQgfa4r9SOuQe+Uh31fiRUgUX5HRlOcimc +HJwNK2sHBfd6V275nuweR+Zc8fzUci+T34uwjIMMpMC/oYXu1FR2CD00sN2 zO6Zou8a7Ue527cH37qu9yuTDKNHSiRMNmjFLSnDqHSr4puu2Si+vP82+Lrj MB7hHH0RL/EHn40eNbc2/4XyV1Lj92ePwkyqW8KLaiqw/9Bz7euohQME7W0p Hq0gsDdpadCIAZpzIgnB2fOQ2fXTbFc8Hex94uKl2mfBbELid/tXCpaqdWQW PKKgW/NuFpa3JFjzydkjeXcMIlXbs6v9a/GyTyul3L8AF7+y6kd4NmGY7ss/ JmpVeOzMREeS/zRmKhZrFRRTcOYT+bfXiyVs0OwQqB+ZxxZu2tUOoUlMUrYt 2ONBQcsJ1kiJ60Sof3VXoKOnE4Y+slvohK6f7+o9TwdkafjtlCm9RqcWHB2W dwcqZmLfwdMfp8+3I+WH82N9Ri0Kx7foblBgQHNEsajLrTkw2pigJbc6BZwH Jk2n+QbB4s+rqoVXlTBzZNR15OdfIB/0vSVWOAdT/IpsCVyL0H7HTvf5BRbC hyhpoedMrITotVAPvmgyKsqyn8voImFdjunXqyJTKFczJH+RMYFPpc5U2iSQ cLaAO/6d4wi+q3MPSz5xAS4Q/rx26n6FcmUSzGclamD62EHxJ7Zl8EZkG5Pk DAn2zRaTbvuMgJ72P9WWzlqQJEe5m4TWQFmKnz9k9kO2iRPbZv1e+Ogmmril dRSU/vsRIpZOhqHbSfcPGtDRI8D2lX0BA9W0L01FJVKxgjiuu2m9b7Nf13K5 vb7ftVPRm/WX6sD5bYc+1wQVmt+dt+gvoEEXQeKh1P0RHPzC3er0ep3T8rL/ NUaPwb0xOuNz+jAIn5doKGRFHJTUNOa4no2WbGNne8o6UC/6hnbi8z7U043+ aWIxCcdvVl48eXkC2mu8elPNqDjn1qi335aC2aP+EiI/KnFL6OWk8c+pKB7k b/NaagpNdYUb0gbH8O/pWtZPR2Zw9dtEQZMaHa9Ungv7IU+FoD6j2mMdU3Cy yXYo9gERuDJlTayk+0G4GKoOhg9CAWeetP1LErCPD1wWm89Bb9YroXOMLNwV njbWXEKDjTHnpTRVKJDV+urLveVqPMK/a19hfhtGLoWF/7Drh0tfcrgsz/bB 3ocV3LsezYLVan1gkO8s5B2W6lGroaHvZQ11J/kZ9BH+lxlyewSkApT/I5aP QaX7boN9akT4ffSaLyN+ED5doN68+a0KDbODJ4RUK/G/wN+Whl598MOxqO79 lx5wZtWv8cR+mP9Gl7scOgy1L52+32vrA0tdcaM5mzZ4a8F0RDyzDLU637OY x7Sg+t/aWytbhvAkd7jcwbRhbDUizn0P+gsX32yMtOWpBD53H+rIhzTIxVWH efVCUHWpWkKTYWQ6M+Iu+20Yh/96ydgHUmBjVKNaiNMMjBRLnE95TsH6pIQt M2xU7Cw4+viJyAgc5hkO/XtzBCKc/9y7x8eAB9kC40n/5iHcIkqXs2EIY370 ZhU2DyFXxdRIv9wCLGZ+ybxaTYeMVj0+Ddt+kPFxNBHwJEEHNczCxY0BacLW uVf3z4KedN/5790TEHG87knK+SHIrcudmNAYAsUH+7I4ZHsg/a4c9efoCkgt /VKUbVyC/zRDBLk+TUJJ/rbHPkenwK5kW62feQ/8+al78YZAG9iJdn2sfbAC d44WxTjunANPZ1X2KfMx9FUOOclzrh97d8gqONUUQn1oS/chPw8IfPehU/T3 JDI9mzSK20JFW5chuLWDhH3uLcfyWIZRcpUjsmad666KQW6Fom2wx1dyZ3gd BQeUyx17nKaw27JGsMB1EWaFeF9s/LQIThlBIpN7JtGs7MH9bT5DmLlhQ5G8 VgmwSlx+2lhcB8OJldFdBktoLLpoElW6jF6ba+9Efm7EjiSHQ5ZL9fhgjp3+ wXkGvAMnt4Z/ogKJQyjix9dJaHqffomAk8BjepxhQ+hHI4urm05fJOICv+XT kUutyO4SaPE4rwObBScLLCvLcUtFawXrjWKMa734fC69GI0zVuVW+39AzgP/ WBl+ZpXDu12lZ5KZVcbfKvr7M78FgT2uqVTVfLD0PWoa3lEAjtxv/16rW+f7 ib6bcocW4IuPau313iWIqdxfpjkQCzF2d3uI9xowoNu6ucWRCLWb6YqN/v3Q yORxHMRIIMlRoLqpdBQOG6rmdegMwEDRQxKv47pPpNLYuPzosD/LIvfBf3Sg latsSdnIgNQOksOJujl4lMb9IeBlI2xstF6+ulIMy2IZWTerSjBzoEp70aII H/xd1DzuQ0djvsKnO9/TMbXbztGMRIT2oxGtom6DIJUTTJ+dc4cshS31WiPf 4NKbxfYG6ViY2/0vA79UYSlzxs797M0YZCyW6ZTQgj++bT7SzpjCplNlx2/3 TOBjJkUt6vgsXBNRf1/7aQ7kV47tamUdQMGDrMTAU/2YP/+oQFKdup4Xs4JP imfhmP6hTppcPdqVzrvmDqXhH3FnTmd/Cq6FeFPeW1JRVGEmlTxJhPnT914s 8XWBXBb5kosIHTbXjP6mZs+ClE1P6XHtGjjVX1sszaiCY2Efrp/fQ8Rlnfzr u+qHMUNz15UUKSoo6e7M26ZEgW2mPNy2gu1IeJArlbutGX9q+BZqaZOA1/Kl Aat9N9TZ6V1wuj8PQXmWnwST5oB2NtZiZSsZd15W0J96Noq6XmUJ+TajmJx+ nR5RRsIPrXZER+dB4Hr9W8LYfxgsmYXNff7mo/fg7qIQw3D8eEpzLObwIKqz B3vv5h/ES/K9Xj9VhtHeyDY378wQnn82bRaRko7FRKM62+AitJ7XXKlY6ML9 rONGGsJ9eNbwC/YeagETDTHnWqF6+L3F41uwUT24FJ96XylGgKUNrzB0oAv4 ihPlBU63wcOdtXbJ636aK3DCQcaqHnn5lj0r/7XDHqXdWln3++AXb5amevsU ZN4LHWI+SoUT92w6eFcawF6081jg9UaIjHunrKxFBDGqe8JdvmHgSNm5Z1M0 FS9dz2lSY51G9y/Jji/3ZcP2/jz7Oy4lsKN82fvq0CBEp0628u4dgNDzhvF1 DweAdOvC3MZrJChJ3BkmWDOEYVlL/mJr46iQmeE0nUfD6lRCcqkUFW8xsjnI NvWYcmvEL2n+D/J+iPwRR27D5tWmrtWSUuQ+NrXn5lcC5HLHqyqy1UBDacHG d1P1oP05/UGQdAFUbcvt/bmhCImUgs+mxa9gd1/uO2kjJoLYMgdvSx4TgcXI 2YKbOxbflWXrDx2qxZMca38Vjs/BB9YrCb0nGZB+7FrmzAkGWFWe/0n0mYW9 m5oD+NbzwJ3X9wlzZTcmvdv1fLpsAI/kKlROxQ6jYPGbD66/gmCj0O3sltEi tA1gYWtXpUGNZ9rHD4ozMLr2uExGZQFS5gLiMiQW4EmM3oaRVSLMfpHPeX6U CJwhA2bO4jTgKOrTvXluCnS777hJqC7iVKlFv+OfBbQ//4H2+tk0FrgqdH0V msZeU+3u8JNEvC1fyf0osxM96jVCRIOmMUHd/5Ku5xQabMsgp72Zg9628sOr 8wx4d6Gfu4ZCwxIZC92eZSoqyfDqDH5xx/i3iUGnz9YBUejq+E3fOWQr9VKJ +jCLx6hXWFv3TMFx9c9O7c1kCNjygd1nNzOBdtj3SKI1M+FRg5HEp0AyeBz6 Y9zcRYVo6rgjT9EwHKvnvHM0fQjKzrVFJw3Nw5EFxVCiNwNUrsyMeV0egCsz jMXM0BE4bSmceTG0F3l6e5zvKw6hoOWqsU7+ALYLWF0adBhBVGZ5G93LQBgN X+30XMb27oUh99MrWFRkci3k6ArKpfiOrN0jgGf2gaaOyr+w2cDgWaRFC9R/ 87eQJ7WA5oK4PW19vynplokme2fgqqruz4MbBuBAcYuKzbq37EnXZWyqrcHC kOX+xDYCEjSSeiTlB2Fb5IttzEFDcPRE4cpjhWEsTrjpnPGChLEW7Ym1olTs 3rEtRSppGi8LaP3THSAjz3yg3sOpDnQsv7mmSWAiqKhH8Zm+YyI4sCUqLXxY hJ0ekYmGwUswdzlmIfTWHB659jgof703Q7iNoTdzH9wLfrKj6AgRLv2XoCHt Q0UefcG9czoUFJEwLJB5MI6Fx3espRuR0egQ9QeX5wj4tZs+LT4wBBbfzkVV J/WBU8F1patjYyA09SOtPXoEROZK7t8UH4Ko9ErpV3aVqPRlJ+W5ZDtKpg0W q2/sgNCr+OhpRhM42QW53F7vic8q3tdkeq4h82fqJJm5F5Vnc39s6WnB06uT z536KXi04Hwj26EpDLn0FqbOUTHml4LryRYaSj2kmH0/PoAR2w210hR60Ucv /OWp3c3ob6beM2fViPn0p7UH7zOrNCdKug8Osqjkyd9SKji+iH47PzLT7Baw pX7hqv5XOhYca93u2TCDl58GUKMSZ/GrUz5R0nEWD9e3zO1/PwPaNSYPjwbP gO/iv0PGfv/n83meENdhPHR4bNV5cBoXL7xby1WnYDpPyIHjNQzkuhb4lHuC gUTZcy/PXGYloHJMUNBBVoLgcW/Zdqd6rOLb+NftXQP+DwBA+vg= "]]}, {}}, {}, {}, {}, {}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->{False, False}, AxesLabel->{None, None}, AxesOrigin->{0, 0}, DisplayFunction->Identity, Frame->{{True, True}, {True, True}}, FrameLabel->{{None, None}, {None, None}}, FrameTicks->{{None, None}, {None, None}}, GridLines->{None, None}, GridLinesStyle->Directive[ GrayLevel[0.5, 0.4]], ImagePadding->All, Method->{"CoordinatesToolOptions" -> {"DisplayFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& ), "CopiedValueFunction" -> ({ (Identity[#]& )[ Part[#, 1]], (Identity[#]& )[ Part[#, 2]]}& )}}, PlotLabel->FormBox[ TemplateBox[{"\"\[Rho] : \"", "0.9137457457457457`"}, "RowDefault"], TraditionalForm], PlotRange->{{-3.005322854947602, 3.186993462556886}, {-3.0527550151649834`, 3.4395796113160815`}}, PlotRangeClipping->True, PlotRangePadding->{{ Scaled[0.02], Scaled[0.02]}, { Scaled[0.05], Scaled[0.05]}}, Ticks->{Automatic, Automatic}]} }, AutoDelete->False, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"]], "Output", CellChangeTimes->{3.8243516220277815`*^9}, CellLabel->"Out[60]=",ExpressionUUID->"92393489-d976-4626-9f7f-70a6bc7d2037"] }, Open ]], Cell[BoxData[ RowBox[{ RowBox[{"(*", RowBox[{ RowBox[{ RowBox[{ RowBox[{ RowBox[{ RowBox[{"Goodman", " ", "-", " ", RowBox[{"Kruskal", " ", RowBox[{"gama", ".", "\[IndentingNewLine]", "Koeficient"}], " ", "gamma", " ", RowBox[{"(", RowBox[{ RowBox[{ "tak\[EAcute]", " ", "naz\[YAcute]van\[YAcute]", " ", "statistika", " ", "gama"}], ",", RowBox[{ "neboli", " ", "Goodmanova", " ", "a", " ", "Kruskalova", " ", "gama"}]}], ")"}], " ", "n\[AAcute]m", " ", "\[RHacek]\[IAcute]k\[AAcute]"}]}], ",", RowBox[{ "jak", " ", "t\[EHacek]sn\[EHacek]", " ", "se", " ", "dva", " ", "p\[AAcute]ry", " ", "datov\[YAcute]ch", " ", "bod\[URing]", " ", "\:201eshoduj\[IAcute]", RowBox[{"\[OpenCurlyDoubleQuote]", RowBox[{ RowBox[{ RowBox[{".", "Gamma"}], " ", "testy", " ", "pro", " ", "asociaci", " ", "mezi", " ", "body", " ", "n\[AAcute]m", " ", "tak\[EAcute]", " ", "\[RHacek]\[IAcute]kaj\[IAcute]", " ", "s\[IAcute]lu", " ", RowBox[{"asociace", ".", "C\[IAcute]lem"}], " ", "testu", " ", "je", " ", "b\[YAcute]t", " ", "schopen", " ", "p\[RHacek]edpov\[EHacek]d\[EHacek]t"}], ",", RowBox[{ "kam", " ", "se", " ", "nov\[EAcute]", " ", "hodnoty", " ", "budou", " ", RowBox[{"\[RHacek]adit", ".", " ", "Gamma"}], " ", "lze", " ", "vypo\[CHacek]\[IAcute]tat", " ", "pro", " ", "ordin\[AAcute]ln\[IAcute]", " ", "prom\[EHacek]nn\[EAcute]"}], ",", RowBox[{ "kter\[EAcute]", " ", "jsou", " ", "spojit\[YAcute]mi", " ", "prom\[EHacek]nn\[YAcute]mi", " ", RowBox[{"(", RowBox[{ "jako", " ", "je", " ", "v\[YAcute]\[SHacek]ka", " ", "nebo", " ", "hmotnost"}], ")"}], " ", "nebo", " ", "diskr\[EAcute]tn\[IAcute]mi", " ", "prom\[EHacek]nn\[YAcute]mi", " ", RowBox[{"(", RowBox[{"jako", " ", "\:201ehork\[EAcute]", RowBox[{"\[OpenCurlyDoubleQuote]", RowBox[{",", RowBox[{"\:201ehork\[EHacek]j\[SHacek]\[IAcute]", RowBox[{"\[OpenCurlyDoubleQuote]", RowBox[{ "a", " ", "\:201enej\[ZHacek]hav\[EHacek]j\[SHacek]\[IAcute]", "\[OpenCurlyDoubleQuote]"}]}]}]}]}]}]}]}]}]}]}]}], ")"}], ".", "I"}], " ", "kdy\[ZHacek]", " ", "existuj\[IAcute]", " ", "dal\[SHacek]\[IAcute]", " ", "koeficienty"}], ",", RowBox[{ "kter\[EAcute]", " ", "mohou", " ", "vypo\[CHacek]\[IAcute]tat", " ", "vztahy", " ", "pro", " ", "tyto", " ", "typy", " ", "prom\[EHacek]nn\[YAcute]ch"}], ",", RowBox[{ "jako", " ", "Somer\[URing]v", " ", "D", " ", "nebo", " ", "Kendall\[URing]v", " ", "Tau"}], ",", RowBox[{ "gamma", " ", "Goodmana", " ", "a", " ", "Kruskala", " ", "je", " ", "obecn\[EHacek]", " ", "up\[RHacek]ednost\[NHacek]ov\[AAcute]no"}], ",", RowBox[{ "kdy\[ZHacek]", " ", "m\[AAcute]te", " ", "mnoho", " ", "d\[EHacek]len\[YAcute]ch", " ", RowBox[{"\[RHacek]ad", ".", "Je"}], " ", "tak\[EAcute]", " ", "obzvl\[AAcute]\[SHacek]t\[EHacek]", " ", "u\[ZHacek]ite\[CHacek]n\[EAcute]"}], ",", RowBox[{ "kdy\[ZHacek]", " ", "va\[SHacek]e", " ", "data", " ", "maj\[IAcute]", " ", "odlehl\[EAcute]", " ", "hodnoty"}], ",", RowBox[{ "proto\[ZHacek]e", " ", "p\[RHacek]\[IAcute]li\[SHacek]", " ", "neovliv\[NHacek]uj\[IAcute]", " ", RowBox[{"v\[YAcute]sledky", ".", "U"}], " ", "n\[EHacek]kter\[YAcute]ch", " ", "studijn\[IAcute]ch", " ", "obor\[URing]", " ", "to", " ", "m\[URing]\[ZHacek]e", " ", "b\[YAcute]t", " ", "up\[RHacek]ednost\[NHacek]ovan\[AAcute]", " ", "metoda", " ", "pro", " ", "v\[SHacek]echna", " ", "po\[RHacek]adov\[AAcute]", " ", "data", " ", "uspo\[RHacek]\[AAcute]dan\[AAcute]", " ", "v", " ", "dvojrozm\[EHacek]rn\[EAcute]", " ", "tabulce", RowBox[{ RowBox[{"(", "psychologie", ")"}], ".", "Pokud"}], " ", "m\[AAcute]te", " ", "dv\[EHacek]", " ", "dichotomick\[EAcute]", " ", "prom\[EHacek]nn\[EAcute]", " ", RowBox[{"(", RowBox[{ RowBox[{"nap\[RHacek]", ".", "Odpov\[EHacek]di"}], ",", RowBox[{"kter\[EAcute]", " ", "jsou", " ", RowBox[{"ano", "/", "ne"}]}]}], ")"}]}], ",", RowBox[{ RowBox[{ RowBox[{ "pou\[ZHacek]ijte", " ", "m\[IAcute]sto", " ", "toho", " ", "Yule\[URing]v", " ", "koeficient", " ", RowBox[{"Q", ".", "Rozsah"}], " ", "koeficientu", " ", "gama", "\n", "\[IndentingNewLine]", "Koeficient", " ", "gama", " ", "se", " ", "pohybuje", " ", "mezi"}], "-", RowBox[{"1", " ", "a", " ", "1.", "\n", "\[IndentingNewLine]", "1"}]}], "=", RowBox[{"dokonal\[AAcute]", " ", "pozitivn\[IAcute]", " ", RowBox[{"korelace", ":", RowBox[{ "pokud", " ", "jedna", " ", "hodnota", " ", "stoup\[AAcute]"}]}]}]}], ",", RowBox[{ RowBox[{"tak", " ", "i", " ", RowBox[{"druh\[AAcute]", ".", RowBox[{"-", "1"}]}]}], "=", RowBox[{"dokonal\[AAcute]", " ", "inverzn\[IAcute]", " ", RowBox[{"korelace", ":", RowBox[{ "jak", " ", "jedna", " ", "hodnota", " ", "stoup\[AAcute]"}]}]}]}], ",", RowBox[{ RowBox[{"druh\[AAcute]", " ", RowBox[{"kles\[AAcute]", ".", "0"}]}], "=", RowBox[{ "mezi", " ", "prom\[EHacek]nn\[YAcute]mi", " ", "neexistuje", " ", "\[ZHacek]\[AAcute]dn\[AAcute]", " ", "asociace", " ", "mezi", " ", RowBox[{"daty", "."}]}]}]}], "*)"}], "\n"}]], "Input", CellChangeTimes->{{3.8243515206663866`*^9, 3.824351541449732*^9}, { 3.824352068583455*^9, 3.82435218884015*^9}, {3.824352276007661*^9, 3.8243522806212206`*^9}},ExpressionUUID->"e6fd805e-e2b4-44d7-9faa-\ 6408627b8073"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"GoodmanKruskalGamma", "[", RowBox[{"a", ",", "b"}], "]"}]], "Input", CellChangeTimes->{{3.8243522975354347`*^9, 3.8243523063616877`*^9}}, CellLabel->"In[61]:=",ExpressionUUID->"e5118c88-8f6c-4902-84da-e8d356a84723"], Cell[BoxData[ FractionBox["9", "95"]], "Output", CellChangeTimes->{3.8243523076445017`*^9}, CellLabel->"Out[61]=",ExpressionUUID->"ba305789-752e-488d-857b-c6e26cd6705f"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"GoodmanKruskalGammaTest", "[", RowBox[{"a", ",", "b", ",", "\"\\""}], "]"}]], "Input", CellChangeTimes->{{3.824352316610074*^9, 3.8243523364818287`*^9}}, CellLabel->"In[62]:=",ExpressionUUID->"738b87e6-cbf0-423c-a9ce-0af2e6e9845c"], Cell[BoxData[ StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"Statistic\"\>", "\<\"P\[Hyphen]Value\"\>"}, {"\<\"Goodman\[Hyphen]Kruskal \[Gamma]\"\>", "0.09473684210526316`", "0.5812547604118179`"} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"], "DialogStyle", StripOnInput->False]], "Output", CellChangeTimes->{3.824352337601452*^9}, CellLabel->"Out[62]=",ExpressionUUID->"4cba2b0d-4219-4c82-8346-6d3f2aaeddda"] }, Open ]], Cell[BoxData[ RowBox[{"\[IndentingNewLine]", RowBox[{"(*", " ", RowBox[{ RowBox[{ RowBox[{"BlomquistBeta", " ", RowBox[{ "koeficient", ".", "\[IndentingNewLine]", "Blomqvist\[URing]v"}], " ", "koeficient"}], " ", "-", " ", RowBox[{ "Blomqvistova", " ", "beta", " ", "nebo", " ", "medi\[AAcute]ln\[IAcute]", " ", "korelace"}]}], " ", ",", " ", RowBox[{ "je", " ", "medi\[AAcute]nov\[AAcute]", " ", "neparametrick\[AAcute]", " ", "korelace"}], ",", RowBox[{ "kter\[AAcute]", " ", "m\[AAcute]", " ", "n\[EHacek]kter\[EAcute]", " ", "v\[YAcute]hody", " ", "oproti", " ", "n\[EHacek]kter\[YAcute]m", " ", "koeficient\[URing]m", " ", "jako", " ", "je", " ", "Spearman\[URing]v", " ", "nebo", " ", "Kendall\[URing]v", " ", RowBox[{"koeficient", ".", " "}]}]}]}]}]], "Input", CellChangeTimes->{{3.8247210996310797`*^9, 3.8247211204994063`*^9}, { 3.8247213285463133`*^9, 3.824721392386942*^9}},ExpressionUUID->"df98fcaa-887f-40d8-9ed0-\ 4fd4945124d2"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"IndependenceTest", "[", RowBox[{"a", ",", "b", ",", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\\"", ",", "\"\\""}], "}"}]}], "]"}]], "Input", CellChangeTimes->{{3.8247216973944783`*^9, 3.8247217837341995`*^9}, { 3.8247220185913296`*^9, 3.824722029360283*^9}}, CellLabel-> "In[117]:=",ExpressionUUID->"087f2353-dac2-4ef0-8d99-ba425826b045"], Cell[BoxData[ RowBox[{"{", RowBox[{"0.6562817986966594`", ",", "0.10087319118710462`", ",", StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"Statistic\"\>", "\<\"P\[Hyphen]Value\"\>"}, {"\<\"Pearson Correlation\"\>", RowBox[{"-", "0.3774436090225564`"}], "0.10087319118710462`"} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"], "DialogStyle", StripOnInput->False]}], "}"}]], "Output", CellChangeTimes->{{3.824721755324049*^9, 3.8247218077502327`*^9}, 3.8247220313518085`*^9}, CellLabel-> "Out[117]=",ExpressionUUID->"7e168b2b-b796-4f00-bedd-880ec96b9a94"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"IndependenceTest", "[", RowBox[{"a", ",", "b", ",", RowBox[{"{", RowBox[{"\"\\"", ",", "\"\\""}], "}"}]}], "]"}]], "Input", CellChangeTimes->{{3.82472181343792*^9, 3.824721832812945*^9}}, CellLabel-> "In[116]:=",ExpressionUUID->"65e39745-d811-4a23-b736-a3a3ff1f920f"], Cell[BoxData[ RowBox[{"{", RowBox[{"0.6562817986966594`", ",", "0.07977529561741215`"}], "}"}]], "Output", CellChangeTimes->{3.8247218352892065`*^9}, CellLabel-> "Out[116]=",ExpressionUUID->"5080edb8-b6ef-46f1-8da2-17a7613d74c1"] }, Open ]], Cell[BoxData[ RowBox[{"(*", RowBox[{ RowBox[{"Vzhledem", " ", "k", " ", "tomu"}], ",", " ", RowBox[{ RowBox[{ "\[ZHacek]e", " ", "BlomqvistBeta", " ", "nab\[YAcute]v\[AAcute]", " ", "hodnot", " ", "od"}], " ", "-", RowBox[{"1", " ", "do", " ", "1"}]}], ",", " ", RowBox[{ "je", " ", "z", " ", "t\[EHacek]chto", " ", "hodnot", " ", "z\[RHacek]ejm\[EAcute]"}], ",", " ", RowBox[{ "\[ZHacek]e", " ", "sp\[IAcute]\[SHacek]e", " ", "nadce\[NHacek]uje", " ", RowBox[{"vazbu", "."}]}]}], "*)"}]], "Input", CellChangeTimes->{{3.8247219737949986`*^9, 3.82472197677717*^9}, { 3.824722048388829*^9, 3.8247221267329435`*^9}},ExpressionUUID->"01464f42-d92e-4ebb-b0b3-\ fb37024c0896"], Cell[BoxData[ RowBox[{"(*", RowBox[{ "Porovn\[AAcute]n\[IAcute]", " ", "jednotliv\[YAcute]ch", " ", "typ\[URing]", " ", "korela\[CHacek]n\[IAcute]ch", " ", RowBox[{"koeficient\[URing]", "."}]}], "*)"}]], "Input", CellChangeTimes->{{3.8243529141993847`*^9, 3.82435293650233*^9}},ExpressionUUID->"f302b0d8-e1a7-4eae-b5e0-\ 160e0a4f2ca1"], Cell[BoxData[ InterpretationBox[Cell[ "\t", "ExampleDelimiter",ExpressionUUID-> "03dabfd6-5fac-429e-a9d7-429c8e79ca9a"], $Line = 0; Null]], "ExampleDelimiter", CellID->132774385,ExpressionUUID->"1349206d-400b-4f77-9165-c9f00393db46"], Cell["Pearson", "ExampleText", CellChangeTimes->{{3.8243526550734587`*^9, 3.82435268866765*^9}, { 3.824352898350236*^9, 3.824352906138317*^9}}, CellID->46190281,ExpressionUUID->"d94b157f-cd88-4ba3-a909-83e056ce2afa"], Cell[BoxData[{ RowBox[{ RowBox[{"v1", "=", RowBox[{"RandomVariate", "[", RowBox[{ RowBox[{"NormalDistribution", "[", "]"}], ",", "100"}], "]"}]}], ";"}], "\[IndentingNewLine]", RowBox[{ RowBox[{"v2", "=", RowBox[{"RandomVariate", "[", RowBox[{ RowBox[{"NormalDistribution", "[", "]"}], ",", "100"}], "]"}]}], ";"}]}], "Input", CellLabel->"In[104]:=", CellID->333615745,ExpressionUUID->"e1d33e83-5ebe-4313-974e-0d0213dce8a9"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"IndependenceTest", "[", RowBox[{"v1", ",", "v2", ",", "\"\\""}], "]"}]], "Input", CellLabel->"In[67]:=", CellID->118777585,ExpressionUUID->"90627211-d27f-4a8f-91b3-63d983bc6beb"], Cell[BoxData[ StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"Statistic\"\>", "\<\"P\[Hyphen]Value\"\>"}, {"\<\"Pearson Correlation\"\>", RowBox[{"-", "0.09434826792056973`"}], "0.3504557276475417`"} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"], "DialogStyle", StripOnInput->False]], "Output", CellChangeTimes->{3.824352797639573*^9}, ImageSize->{203, 28}, ImageMargins->{{0, 0}, {0, 0}}, ImageRegion->{{0, 1}, {0, 1}}, CellLabel->"Out[67]=",ExpressionUUID->"2fc604bb-ddcc-4b6e-862e-d05d758a2934"] }, Open ]], Cell["Goodman-Kruskal", "ExampleText", CellChangeTimes->{{3.8243526968399343`*^9, 3.824352706540653*^9}}, CellID->99664176,ExpressionUUID->"c14da20a-0089-4699-b7a9-dd36f835b428"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"IndependenceTest", "[", RowBox[{"v1", ",", "v2", ",", RowBox[{"{", RowBox[{"\"\\"", ",", "\"\\""}], "}"}]}], "]"}]], "Input", CellLabel->"In[68]:=", CellID->126542309,ExpressionUUID->"7b4abf49-ef3f-4ee3-8c55-333423184ffd"], Cell[BoxData[ StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"Statistic\"\>", "\<\"P\[Hyphen]Value\"\>"}, {"\<\"Goodman\[Hyphen]Kruskal \[Gamma]\"\>", RowBox[{"-", "0.042828282828282827`"}], "0.5297533052102101`"} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"], "DialogStyle", StripOnInput->False]], "Output", CellChangeTimes->{3.824352801133439*^9}, ImageSize->{212, 28}, ImageMargins->{{0, 0}, {0, 0}}, ImageRegion->{{0, 1}, {0, 1}}, CellLabel->"Out[68]=",ExpressionUUID->"13626e91-f975-45d4-b473-9f088377603e"] }, Open ]], Cell["Kendall", "ExampleText", CellChangeTimes->{{3.8243526968399343`*^9, 3.824352706540653*^9}, { 3.824352829037389*^9, 3.8243528337348013`*^9}}, CellID->208828284,ExpressionUUID->"3de2a5b0-5fdc-4d63-a016-b0daa2475019"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"IndependenceTest", "[", RowBox[{"v1", ",", "v2", ",", RowBox[{"{", RowBox[{"\"\\"", ",", "\"\\""}], "}"}]}], "]"}]], "Input", CellChangeTimes->{{3.824352716402384*^9, 3.8243527836792107`*^9}}, CellLabel->"In[69]:=",ExpressionUUID->"fd8ab1e0-550f-45d1-9adb-d05862b6aa45"], Cell[BoxData[ StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"Statistic\"\>", "\<\"P\[Hyphen]Value\"\>"}, {"\<\"Kendall \[Tau]\"\>", RowBox[{"-", "0.042828282828282827`"}], "0.5278046677400059`"} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"], "DialogStyle", StripOnInput->False]], "Output", CellChangeTimes->{{3.824352785415491*^9, 3.824352804505704*^9}}, CellLabel->"Out[69]=",ExpressionUUID->"a470b15c-efa6-4c4b-b238-20691bb7c470"] }, Open ]], Cell["Spearman", "ExampleText", CellChangeTimes->{{3.8243526968399343`*^9, 3.824352706540653*^9}, { 3.824352829037389*^9, 3.8243528337348013`*^9}, {3.8243528845333233`*^9, 3.8243528902713804`*^9}}, CellID->13840017,ExpressionUUID->"e1448ace-3131-4e5e-88a2-1663470272f9"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"IndependenceTest", "[", RowBox[{"v1", ",", "v2", ",", RowBox[{"{", RowBox[{"\"\\"", ",", "\"\\""}], "}"}]}], "]"}]], "Input", CellChangeTimes->{{3.8243528528178444`*^9, 3.82435286287082*^9}}, CellLabel->"In[70]:=",ExpressionUUID->"1551659d-d1eb-4429-9a48-d2a8c7b49e8c"], Cell[BoxData[ StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"Statistic\"\>", "\<\"P\[Hyphen]Value\"\>"}, {"\<\"Spearman Rank\"\>", RowBox[{"-", "0.06426642664266428`"}], "0.5252708837422001`"} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"], "DialogStyle", StripOnInput->False]], "Output", CellChangeTimes->{3.8243528694225025`*^9}, CellLabel->"Out[70]=",ExpressionUUID->"1bc2b4a6-10fc-43f3-8db1-f01468be04e5"] }, Open ]], Cell["V\[SHacek]echny typy korela\[CHacek]n\[IAcute]ch koeficient\[URing]", \ "ExampleText", CellChangeTimes->{{3.8243526968399343`*^9, 3.824352706540653*^9}, { 3.824352829037389*^9, 3.8243528337348013`*^9}, {3.8243528845333233`*^9, 3.8243528902713804`*^9}, {3.8243529754962664`*^9, 3.824352987279584*^9}}, CellID->76470547,ExpressionUUID->"2965f8b0-c5c9-446f-8585-60abaee98dbd"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"IndependenceTest", "[", RowBox[{"v1", ",", "v2", ",", RowBox[{"{", RowBox[{"\"\\"", ",", "\"\\""}], "}"}]}], "]"}]], "Input", CellChangeTimes->{{3.824353001408311*^9, 3.8243531050692625`*^9}}, CellLabel->"In[74]:=",ExpressionUUID->"5ae442f7-2e1c-4ee9-b54a-90192c669532"], Cell[BoxData[ RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{"\<\"BlomqvistBeta\"\>", ",", "\<\"GoodmanKruskalGamma\"\>", ",", "\<\"HoeffdingD\"\>", ",", "\<\"KendallTau\"\>", ",", "\<\"PearsonCorrelation\"\>", ",", "\<\"PillaiTrace\"\>", ",", "\<\"SpearmanRank\"\>", ",", "\<\"WilksW\"\>"}], "}"}], ",", StyleBox[ TagBox[GridBox[{ {"\<\"\"\>", "\<\"Statistic\"\>"}, {"\<\"Pearson Correlation\"\>", RowBox[{"-", "0.09434826792056973`"}]} }, AutoDelete->False, GridBoxAlignment->{"Columns" -> {{Left}}, "Rows" -> {{Automatic}}}, GridBoxDividers->{ "ColumnsIndexed" -> {2 -> GrayLevel[0.7]}, "RowsIndexed" -> {2 -> GrayLevel[0.7]}}, GridBoxItemSize->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}, GridBoxSpacings->{"Columns" -> {{Automatic}}, "Rows" -> {{Automatic}}}], "Grid"], "DialogStyle", StripOnInput->False]}], "}"}]], "Output", CellChangeTimes->{{3.824353014249628*^9, 3.82435303732591*^9}, { 3.8243530850062456`*^9, 3.824353107344823*^9}}, CellLabel->"Out[74]=",ExpressionUUID->"54a59198-31a5-473d-8a0d-5ee3a56607c0"] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"IndependenceTest", "[", RowBox[{"v1", ",", "v2", ",", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\\"", ",", "\"\\"", ",", "\"\\""}], "}"}]}], "]"}]], "Input", CellChangeTimes->{{3.824720955797305*^9, 3.824721064423862*^9}}, CellLabel-> "In[108]:=",ExpressionUUID->"2eb7cf4b-164f-4875-8fdf-eb3ae44fe771"], Cell[BoxData[ RowBox[{"{", RowBox[{ "0.7909691000383599`", ",", "0.7886758333984693`", ",", "0.8742898680579364`", ",", "0.31734001128568645`"}], "}"}]], "Output", CellChangeTimes->{{3.8247209757429934`*^9, 3.8247209905902987`*^9}, 3.824721067168973*^9}, CellLabel-> "Out[108]=",ExpressionUUID->"afd27ba5-6ccd-48da-afc8-4207a6d616dc"] }, Open ]] }, WindowSize->{1328, 757}, WindowMargins->{{0, Automatic}, {Automatic, 0}}, FrontEndVersion->"11.3 for Microsoft Windows (64-bit) (March 6, 2018)", StyleDefinitions->"Default.nb" ] (* End of Notebook Content *) (* Internal cache information *) (*CellTagsOutline CellTagsIndex->{} *) (*CellTagsIndex CellTagsIndex->{} *) (*NotebookFileOutline Notebook[{ Cell[558, 20, 331, 7, 28, "Input",ExpressionUUID->"86be98dc-7e61-4bb0-9527-0d9647bf8c4b"], Cell[892, 29, 330, 8, 28, "Input",ExpressionUUID->"27cb8892-1923-4345-967d-98d485bd8a05"], Cell[1225, 39, 1189, 37, 67, "Input",ExpressionUUID->"5dbe865b-3a3a-431d-bf76-0cbc5010e283"], Cell[CellGroupData[{ Cell[2439, 80, 387, 8, 28, "Input",ExpressionUUID->"3f038b59-b423-47d2-8dc9-ef1682b48c2a"], Cell[2829, 90, 301, 6, 32, "Output",ExpressionUUID->"55b90cff-f393-48df-9a37-325d9bfa74f6"] }, Open ]], Cell[CellGroupData[{ Cell[3167, 101, 325, 6, 28, "Input",ExpressionUUID->"58a22b92-93fd-420b-95ac-afd9e427e90a"], Cell[3495, 109, 2002, 44, 52, "Output",ExpressionUUID->"3676664f-24f7-45c2-8431-ef10d652fd2d"] }, Open ]], Cell[CellGroupData[{ Cell[5534, 158, 366, 8, 32, "Input",ExpressionUUID->"b7050c0c-f033-4db9-aabf-4dce9f9cb68e"], Cell[5903, 168, 353, 7, 32, "Output",ExpressionUUID->"f7f6850b-f37f-4954-8b9e-e4f147f8bc46"] }, Open ]], Cell[CellGroupData[{ Cell[6293, 180, 365, 8, 32, "Input",ExpressionUUID->"432dec8c-03af-47b2-8d68-14bca8ee99d6"], Cell[6661, 190, 2470, 53, 53, "Output",ExpressionUUID->"81bd7476-2616-4ea9-9b05-944224a11546"] }, Open ]], Cell[CellGroupData[{ Cell[9168, 248, 572, 14, 28, "Input",ExpressionUUID->"7420d16a-a1cb-4ecb-b352-3e2c71d7aefa"], Cell[9743, 264, 9839, 180, 237, "Output",ExpressionUUID->"5f143463-546b-42c7-af06-bbef2790a403"] }, Open ]], Cell[19597, 447, 741, 20, 28, "Input",ExpressionUUID->"c057abd7-a297-47e4-8b50-7638655aa1eb"], Cell[CellGroupData[{ Cell[20363, 471, 405, 9, 28, "Input",ExpressionUUID->"de969488-0423-4709-b2bd-a3f19ac9788b"], Cell[20771, 482, 356, 6, 32, "Output",ExpressionUUID->"466cbae2-3591-4a2c-bd4c-d846e2506aae"] }, Open ]], Cell[CellGroupData[{ Cell[21164, 493, 389, 9, 28, "Input",ExpressionUUID->"cd355dbf-75f2-4bcb-97a6-d7985e97cfa3"], Cell[21556, 504, 2798, 58, 52, "Output",ExpressionUUID->"9ad1cb4b-9d72-484d-9614-ff7befc23b2a"] }, Open ]], Cell[CellGroupData[{ Cell[24391, 567, 940, 25, 28, "Input",ExpressionUUID->"2c9f55fa-3aee-4a71-b1f6-419135967f31", CellID->280137527], Cell[25334, 594, 64077, 1056, 294, "Output",ExpressionUUID->"dead5381-591a-4f98-aff3-e9e8a56c28cd"] }, Open ]], Cell[CellGroupData[{ Cell[89448, 1655, 1237, 32, 124, "Input",ExpressionUUID->"80d5272b-9366-48b5-aeb2-c3003a38ac34"], Cell[90688, 1689, 2355, 47, 140, "Output",ExpressionUUID->"ee341459-9a1b-4bd7-b9bc-3fc3cf9c6994"], Cell[93046, 1738, 2507, 51, 163, "Output",ExpressionUUID->"9f894141-1ef1-4907-a19b-74870d120510"], Cell[95556, 1791, 2442, 47, 159, "Output",ExpressionUUID->"b5a1dbeb-516e-4c2c-99b0-7f0445fe1476"] }, Open ]], Cell[CellGroupData[{ Cell[98035, 1843, 253, 5, 28, "Input",ExpressionUUID->"1563cf0b-4da2-4f49-a55c-05201c726803"], Cell[98291, 1850, 848, 22, 62, "Output",ExpressionUUID->"5a991766-a3d8-41b4-8e8a-69f1df40cf60"] }, Open ]], Cell[CellGroupData[{ Cell[99176, 1877, 256, 5, 28, "Input",ExpressionUUID->"f0db2e9f-0dea-4aa3-9ee0-1f9cff4791e9"], Cell[99435, 1884, 949, 22, 79, "Output",ExpressionUUID->"2c5e9d34-2ee4-49c4-98a9-9a60082a115f"] }, Open ]], Cell[100399, 1909, 340, 7, 28, "Input",ExpressionUUID->"56e183e0-6aeb-410b-9f79-dcea1798571e"], Cell[CellGroupData[{ Cell[100764, 1920, 437, 6, 28, "Input",ExpressionUUID->"919fe11f-6868-45a7-9fe9-a8665c97641b"], Cell[101204, 1928, 755, 17, 49, "Output",ExpressionUUID->"edeec243-14b8-4579-86e3-fbc858d88852"] }, Open ]], Cell[101974, 1948, 681, 12, 28, "Input",ExpressionUUID->"39979bee-d5a4-40b2-af48-7fde93678217"], Cell[102658, 1962, 1247, 38, 67, "Input",ExpressionUUID->"7fcd1981-42be-4cb6-9667-27e8cb65cc7b"], Cell[CellGroupData[{ Cell[103930, 2004, 293, 5, 28, "Input",ExpressionUUID->"44c2ebce-7c8c-402f-b0e1-528ee8f7fe7e"], Cell[104226, 2011, 253, 6, 74, "Output",ExpressionUUID->"165a19c1-7ddb-4fff-a841-039e478ddc08"] }, Open ]], Cell[CellGroupData[{ Cell[104516, 2022, 201, 3, 28, "Input",ExpressionUUID->"d2b32ee8-428a-4468-98e4-8de8decea4f5"], Cell[104720, 2027, 209, 3, 32, "Output",ExpressionUUID->"024efe3a-03c2-47e7-af30-8506b60ab851"] }, Open ]], Cell[CellGroupData[{ Cell[104966, 2035, 586, 17, 67, "Input",ExpressionUUID->"00a89936-1ff8-4b68-a111-a8d9df4d80e7"], Cell[105555, 2054, 271, 6, 55, "Output",ExpressionUUID->"a3eb1138-796e-497c-8cc7-04dcf0c8410e"] }, Open ]], Cell[CellGroupData[{ Cell[105863, 2065, 459, 8, 48, "Input",ExpressionUUID->"06deafb3-a765-452c-bf61-5566560712b6"], Cell[106325, 2075, 195, 2, 32, "Output",ExpressionUUID->"6f28695f-8fa1-4d08-bf70-1f4ab37b24c4"], Cell[106523, 2079, 720, 16, 49, "Output",ExpressionUUID->"901b7f1a-fa60-4719-a4e8-55fac6dfca89"] }, Open ]], Cell[107258, 2098, 710, 12, 48, "Input",ExpressionUUID->"f5c87d51-b7e8-48a7-82ea-7d70a981d842"], Cell[107971, 2112, 4060, 84, 181, "Input",ExpressionUUID->"b7ed263f-fd31-4470-8e23-7e3b96c82cb6"], Cell[CellGroupData[{ Cell[112056, 2200, 235, 4, 28, "Input",ExpressionUUID->"66b2be7d-976a-4340-afdc-93179c8cfec0"], Cell[112294, 2206, 172, 3, 55, "Output",ExpressionUUID->"e8d246c9-5263-4725-b1d5-cbb1b99185ca"] }, Open ]], Cell[CellGroupData[{ Cell[112503, 2214, 272, 4, 28, "Input",ExpressionUUID->"025910e6-a516-44b1-846f-052dcd3573ea"], Cell[112778, 2220, 698, 16, 49, "Output",ExpressionUUID->"4aa4e978-c29d-4be1-b79f-917ba11d63c9"] }, Open ]], Cell[113491, 2239, 1134, 30, 67, "Input",ExpressionUUID->"1b9609d4-314c-44d9-8905-4cc3bdca2814"], Cell[CellGroupData[{ Cell[114650, 2273, 1164, 27, 67, "Input",ExpressionUUID->"45b288b0-9597-4e8d-affb-6b9cd7c14832", CellID->80899249], Cell[115817, 2302, 200795, 3430, 410, "Output",ExpressionUUID->"92393489-d976-4626-9f7f-70a6bc7d2037"] }, Open ]], Cell[316627, 5735, 6193, 135, 295, "Input",ExpressionUUID->"e6fd805e-e2b4-44d7-9faa-6408627b8073"], Cell[CellGroupData[{ Cell[322845, 5874, 244, 4, 28, "Input",ExpressionUUID->"e5118c88-8f6c-4902-84da-e8d356a84723"], Cell[323092, 5880, 172, 3, 55, "Output",ExpressionUUID->"ba305789-752e-488d-857b-c6e26cd6705f"] }, Open ]], Cell[CellGroupData[{ Cell[323301, 5888, 276, 4, 28, "Input",ExpressionUUID->"738b87e6-cbf0-423c-a9ce-0af2e6e9845c"], Cell[323580, 5894, 771, 17, 49, "Output",ExpressionUUID->"4cba2b0d-4219-4c82-8346-6d3f2aaeddda"] }, Open ]], Cell[324366, 5914, 1051, 24, 86, "Input",ExpressionUUID->"df98fcaa-887f-40d8-9ed0-4fd4945124d2"], Cell[CellGroupData[{ Cell[325442, 5942, 435, 10, 28, "Input",ExpressionUUID->"087f2353-dac2-4ef0-8d99-ba425826b045"], Cell[325880, 5954, 953, 21, 49, "Output",ExpressionUUID->"7e168b2b-b796-4f00-bedd-880ec96b9a94"] }, Open ]], Cell[CellGroupData[{ Cell[326870, 5980, 339, 8, 28, "Input",ExpressionUUID->"65e39745-d811-4a23-b736-a3a3ff1f920f"], Cell[327212, 5990, 240, 6, 32, "Output",ExpressionUUID->"5080edb8-b6ef-46f1-8da2-17a7613d74c1"] }, Open ]], Cell[327467, 5999, 730, 18, 28, "Input",ExpressionUUID->"01464f42-d92e-4ebb-b0b3-fb37024c0896"], Cell[328200, 6019, 353, 8, 28, "Input",ExpressionUUID->"f302b0d8-e1a7-4eae-b5e0-160e0a4f2ca1"], Cell[328556, 6029, 242, 5, 22, "ExampleDelimiter",ExpressionUUID->"1349206d-400b-4f77-9165-c9f00393db46", CellID->132774385], Cell[328801, 6036, 220, 3, 23, "ExampleText",ExpressionUUID->"d94b157f-cd88-4ba3-a909-83e056ce2afa", CellID->46190281], Cell[329024, 6041, 467, 14, 48, "Input",ExpressionUUID->"e1d33e83-5ebe-4313-974e-0d0213dce8a9", CellID->333615745], Cell[CellGroupData[{ Cell[329516, 6059, 223, 4, 28, "Input",ExpressionUUID->"90627211-d27f-4a8f-91b3-63d983bc6beb", CellID->118777585], Cell[329742, 6065, 861, 20, 49, "Output",ExpressionUUID->"2fc604bb-ddcc-4b6e-862e-d05d758a2934"] }, Open ]], Cell[330618, 6088, 180, 2, 23, "ExampleText",ExpressionUUID->"c14da20a-0089-4699-b7a9-dd36f835b428", CellID->99664176], Cell[CellGroupData[{ Cell[330823, 6094, 303, 7, 28, "Input",ExpressionUUID->"7b4abf49-ef3f-4ee3-8c55-333423184ffd", CellID->126542309], Cell[331129, 6103, 875, 20, 49, "Output",ExpressionUUID->"13626e91-f975-45d4-b473-9f088377603e"] }, Open ]], Cell[332019, 6126, 224, 3, 23, "ExampleText",ExpressionUUID->"3de2a5b0-5fdc-4d63-a016-b0daa2475019", CellID->208828284], Cell[CellGroupData[{ Cell[332268, 6133, 340, 7, 28, "Input",ExpressionUUID->"fd8ab1e0-550f-45d1-9adb-d05862b6aa45"], Cell[332611, 6142, 793, 17, 49, "Output",ExpressionUUID->"a470b15c-efa6-4c4b-b238-20691bb7c470"] }, Open ]], Cell[333419, 6162, 277, 4, 23, "ExampleText",ExpressionUUID->"e1448ace-3131-4e5e-88a2-1663470272f9", CellID->13840017], Cell[CellGroupData[{ Cell[333721, 6170, 341, 7, 28, "Input",ExpressionUUID->"1551659d-d1eb-4429-9a48-d2a8c7b49e8c"], Cell[334065, 6179, 769, 17, 49, "Output",ExpressionUUID->"1bc2b4a6-10fc-43f3-8db1-f01468be04e5"] }, Open ]], Cell[334849, 6199, 386, 5, 23, "ExampleText",ExpressionUUID->"2965f8b0-c5c9-446f-8585-60abaee98dbd", CellID->76470547], Cell[CellGroupData[{ Cell[335260, 6208, 343, 7, 28, "Input",ExpressionUUID->"5ae442f7-2e1c-4ee9-b54a-90192c669532"], Cell[335606, 6217, 1154, 25, 49, "Output",ExpressionUUID->"54a59198-31a5-473d-8a0d-5ee3a56607c0"] }, Open ]], Cell[CellGroupData[{ Cell[336797, 6247, 418, 10, 28, "Input",ExpressionUUID->"2eb7cf4b-164f-4875-8fdf-eb3ae44fe771"], Cell[337218, 6259, 352, 8, 65, "Output",ExpressionUUID->"afd27ba5-6ccd-48da-afc8-4207a6d616dc"] }, Open ]] } ] *) (* End of internal cache information *)