(* Content-type: application/mathematica *) (*** Wolfram Notebook File ***) (* http://www.wolfram.com/nb *) (* CreatedBy='Mathematica 6.0' *) (*CacheID: 234*) (* Internal cache information: NotebookFileLineBreakTest NotebookFileLineBreakTest NotebookDataPosition[ 145, 7] NotebookDataLength[ 3514971, 57575] NotebookOptionsPosition[ 3511352, 57457] NotebookOutlinePosition[ 3511756, 57474] CellTagsIndexPosition[ 3511713, 57471] WindowFrame->Normal ContainsDynamic->False*) (* Beginning of Notebook Content *) Notebook[{ Cell[BoxData[ RowBox[{"Clear", "[", RowBox[{"an", ",", " ", "bn", " ", ",", "u"}], "]"}]], "Input", CellChangeTimes->{{3.41228074103125*^9, 3.412280761546875*^9}}], Cell[BoxData[ RowBox[{"(*", RowBox[{ RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"-", " ", "Prob"}]}]}]}]}]}]}], " ", "12.8", RowBox[{ RowBox[{ RowBox[{".5", " ", "--"}], "--"}], "--"}], RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", "--"}]}]}]}]}], "*)"}]], "Input", CellChangeTimes->{{3.412966017705655*^9, 3.4129660236275296`*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"bmn", " ", "=", RowBox[{ SubsuperscriptBox["\[Integral]", "0", "1"], RowBox[{ SubsuperscriptBox["\[Integral]", "0", "1"], RowBox[{"y", " ", RowBox[{"Sin", "[", RowBox[{"m", " ", "\[Pi]", " ", "x"}], "]"}], " ", RowBox[{"Sin", "[", RowBox[{"n", " ", "\[Pi]", " ", "y"}], "]"}], RowBox[{"\[DifferentialD]", "x"}], RowBox[{"\[DifferentialD]", "y"}]}]}]}]}]], "Input", CellChangeTimes->{{3.412278292125*^9, 3.412278337296875*^9}, { 3.412966266799405*^9, 3.412966273143155*^9}, 3.4129663501275296`*^9}], Cell[BoxData[ FractionBox[ RowBox[{ RowBox[{"(", RowBox[{ RowBox[{"-", "1"}], "+", RowBox[{"Cos", "[", RowBox[{"m", " ", "\[Pi]"}], "]"}]}], ")"}], " ", RowBox[{"(", RowBox[{ RowBox[{"n", " ", "\[Pi]", " ", RowBox[{"Cos", "[", RowBox[{"n", " ", "\[Pi]"}], "]"}]}], "-", RowBox[{"Sin", "[", RowBox[{"n", " ", "\[Pi]"}], "]"}]}], ")"}]}], RowBox[{"m", " ", SuperscriptBox["n", "2"], " ", SuperscriptBox["\[Pi]", "3"]}]]], "Output", CellChangeTimes->{3.41227834134375*^9, 3.4129662749087796`*^9, 3.412966350924405*^9}] }, Open ]], Cell[BoxData[ RowBox[{"(*", RowBox[{ RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"-", " ", "Prob"}]}]}]}]}]}]}], " ", "12.8", RowBox[{ RowBox[{ RowBox[{ RowBox[{".11", " ", "--"}], "--"}], "--"}], "--"}], RowBox[{"--", RowBox[{"--", RowBox[{"--", "--"}]}]}]}], "*)"}]], "Input", CellChangeTimes->{{3.412966088205655*^9, 3.412966088705655*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Bmn", " ", "=", " ", RowBox[{ SubsuperscriptBox["\[Integral]", "0", "\[Pi]"], RowBox[{ SubsuperscriptBox["\[Integral]", "0", "\[Pi]"], RowBox[{"k", " ", RowBox[{"Sin", "[", RowBox[{"2", " ", "x"}], "]"}], " ", RowBox[{"Sin", "[", RowBox[{"5", " ", "y"}], "]"}], " ", RowBox[{"Sin", "[", RowBox[{"m", " ", "x"}], "]"}], " ", RowBox[{"Sin", "[", RowBox[{"n", " ", "y"}], "]"}], RowBox[{"\[DifferentialD]", "x"}], RowBox[{"\[DifferentialD]", "y"}]}]}]}]}]], "Input", CellChangeTimes->{{3.412966103455655*^9, 3.4129661955337796`*^9}, { 3.4129662854400296`*^9, 3.412966288705655*^9}, 3.412966345736905*^9}], Cell[BoxData[ RowBox[{"-", FractionBox[ RowBox[{"10", " ", "k", " ", RowBox[{"Sin", "[", RowBox[{"m", " ", "\[Pi]"}], "]"}], " ", RowBox[{"Sin", "[", RowBox[{"n", " ", "\[Pi]"}], "]"}]}], RowBox[{ RowBox[{"(", RowBox[{ RowBox[{"-", "4"}], "+", SuperscriptBox["m", "2"]}], ")"}], " ", RowBox[{"(", RowBox[{ RowBox[{"-", "25"}], "+", SuperscriptBox["n", "2"]}], ")"}]}]]}]], "Output", CellChangeTimes->{{3.412966176518155*^9, 3.4129661965962796`*^9}, 3.4129662894712796`*^9, 3.412966346268155*^9}] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Bmn", " ", "=", " ", RowBox[{ SubsuperscriptBox["\[Integral]", "0", "\[Pi]"], RowBox[{ SubsuperscriptBox["\[Integral]", "0", "\[Pi]"], RowBox[{"k", " ", RowBox[{"Sin", "[", RowBox[{"2", " ", "x"}], "]"}], " ", RowBox[{"Sin", "[", RowBox[{"5", " ", "y"}], "]"}], " ", RowBox[{"Sin", "[", RowBox[{"2", " ", "x"}], "]"}], " ", RowBox[{"Sin", "[", RowBox[{"5", " ", "y"}], "]"}], RowBox[{"\[DifferentialD]", "x"}], RowBox[{"\[DifferentialD]", "y"}]}]}]}]}]], "Input", CellChangeTimes->{{3.412966223986905*^9, 3.4129662305337796`*^9}, 3.412966293799405*^9, 3.412966341330655*^9}], Cell[BoxData[ FractionBox[ RowBox[{"k", " ", SuperscriptBox["\[Pi]", "2"]}], "4"]], "Output", CellChangeTimes->{3.4129662313150296`*^9, 3.4129662945650296`*^9, 3.412966342705655*^9}] }, Open ]], Cell[BoxData[ RowBox[{"(*", RowBox[{ RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"-", " ", "Prob"}]}]}]}]}]}]}], " ", "12.8", RowBox[{ RowBox[{ RowBox[{ RowBox[{ RowBox[{".13", " ", "--"}], "--"}], "--"}], "--"}], "--"}], RowBox[{"--", RowBox[{"--", "--"}]}]}], "*)"}]], "Input", CellChangeTimes->{{3.412966310986905*^9, 3.4129663117525296`*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"bmn", " ", "=", " ", RowBox[{"0.1", " ", "*", RowBox[{"(", RowBox[{ SubsuperscriptBox["\[Integral]", "0", "\[Pi]"], RowBox[{"y", "*", RowBox[{"(", RowBox[{"\[Pi]", " ", "-", " ", "y"}], ")"}], "*", RowBox[{"Sin", "[", RowBox[{"n", " ", "y"}], "]"}], RowBox[{"\[DifferentialD]", "y"}]}]}], ")"}], "*", RowBox[{"(", RowBox[{ SubsuperscriptBox["\[Integral]", "0", "\[Pi]"], RowBox[{"x", " ", "*", RowBox[{"(", RowBox[{"\[Pi]", " ", "-", " ", "x"}], ")"}], "*", RowBox[{"Sin", "[", RowBox[{"m", " ", "x"}], "]"}], RowBox[{"\[DifferentialD]", "x"}]}]}], ")"}]}]}]], "Input", CellChangeTimes->{{3.4129665136900296`*^9, 3.4129665796900296`*^9}, { 3.412966624518155*^9, 3.412966632518155*^9}}], Cell[BoxData[ FractionBox[ RowBox[{"0.1`", " ", RowBox[{"(", RowBox[{"2", "-", RowBox[{"2", " ", RowBox[{"Cos", "[", RowBox[{"m", " ", "\[Pi]"}], "]"}]}], "-", RowBox[{"m", " ", "\[Pi]", " ", RowBox[{"Sin", "[", RowBox[{"m", " ", "\[Pi]"}], "]"}]}]}], ")"}], " ", RowBox[{"(", RowBox[{"2", "-", RowBox[{"2", " ", RowBox[{"Cos", "[", RowBox[{"n", " ", "\[Pi]"}], "]"}]}], "-", RowBox[{"n", " ", "\[Pi]", " ", RowBox[{"Sin", "[", RowBox[{"n", " ", "\[Pi]"}], "]"}]}]}], ")"}]}], RowBox[{ SuperscriptBox["m", "3"], " ", SuperscriptBox["n", "3"]}]]], "Output", CellChangeTimes->{3.412966634611905*^9}] }, Open ]], Cell[BoxData[ RowBox[{"(*", RowBox[{ RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"-", " ", "Prob"}]}]}]}]}]}]}], " ", "12.9", RowBox[{ RowBox[{ RowBox[{ RowBox[{".11", " ", "--"}], "--"}], "--"}], "--"}], RowBox[{"--", RowBox[{"--", RowBox[{"--", "--"}]}]}]}], "*)"}]], "Input", CellChangeTimes->{{3.412966057518155*^9, 3.4129660625337796`*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{ RowBox[{"an", "[", "n_", "]"}], " ", "=", " ", RowBox[{ FractionBox["1", "\[Pi]"], RowBox[{ SubsuperscriptBox["\[Integral]", RowBox[{"-", "\[Pi]"}], "\[Pi]"], RowBox[{ RowBox[{"Abs", "[", "t", "]"}], " ", RowBox[{"Cos", "[", RowBox[{"n", " ", "t"}], "]"}], RowBox[{"\[DifferentialD]", "t"}]}]}]}]}]], "Input", CellChangeTimes->{{3.41227994659375*^9, 3.4122800035*^9}, { 3.412280730015625*^9, 3.412280732609375*^9}}], Cell[BoxData[ FractionBox[ RowBox[{"2", " ", RowBox[{"(", RowBox[{ RowBox[{"-", "1"}], "+", RowBox[{"Cos", "[", RowBox[{"n", " ", "\[Pi]"}], "]"}], "+", RowBox[{"n", " ", "\[Pi]", " ", RowBox[{"Sin", "[", RowBox[{"n", " ", "\[Pi]"}], "]"}]}]}], ")"}]}], RowBox[{ SuperscriptBox["n", "2"], " ", "\[Pi]"}]]], "Output", CellChangeTimes->{3.412280011734375*^9, 3.412280735*^9, 3.412280765203125*^9, 3.41228162540625*^9, 3.4129668529712796`*^9}] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{ RowBox[{"bn", "[", "n_", "]"}], " ", "=", " ", RowBox[{ FractionBox["1", "\[Pi]"], RowBox[{ SubsuperscriptBox["\[Integral]", RowBox[{"-", "\[Pi]"}], "\[Pi]"], RowBox[{ RowBox[{"Abs", "[", "t", "]"}], RowBox[{"Sin", "[", RowBox[{"n", " ", "t"}], "]"}], RowBox[{"\[DifferentialD]", "t"}]}]}]}]}]], "Input", CellChangeTimes->{{3.41228017796875*^9, 3.41228019675*^9}, { 3.412280768265625*^9, 3.4122807698125*^9}}], Cell[BoxData["0"], "Output", CellChangeTimes->{{3.4122801851875*^9, 3.412280198109375*^9}, 3.41228077034375*^9, 3.412966854830655*^9}] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{ RowBox[{"u", "[", RowBox[{"r_", ",", "theta_"}], "]"}], " ", "=", " ", RowBox[{ FractionBox["\[Pi]", "2"], " ", "+", " ", RowBox[{"Sum", "[", RowBox[{ RowBox[{ RowBox[{"an", "[", "n", "]"}], "*", RowBox[{"r", "^", RowBox[{"(", "n", ")"}]}], "*", RowBox[{"Cos", "[", RowBox[{"n", "*", "theta"}], "]"}]}], ",", RowBox[{"{", RowBox[{"n", ",", "1", ",", "20"}], "}"}]}], "]"}]}]}]], "Input", CellChangeTimes->{{3.41228064890625*^9, 3.412280725328125*^9}, { 3.412280773453125*^9, 3.412280842625*^9}}], Cell[BoxData[ RowBox[{ FractionBox["\[Pi]", "2"], "-", FractionBox[ RowBox[{"4", " ", "r", " ", RowBox[{"Cos", "[", "theta", "]"}]}], "\[Pi]"], "-", FractionBox[ RowBox[{"4", " ", SuperscriptBox["r", "3"], " ", RowBox[{"Cos", "[", RowBox[{"3", " ", "theta"}], "]"}]}], RowBox[{"9", " ", "\[Pi]"}]], "-", FractionBox[ RowBox[{"4", " ", SuperscriptBox["r", "5"], " ", RowBox[{"Cos", "[", RowBox[{"5", " ", "theta"}], "]"}]}], RowBox[{"25", " ", "\[Pi]"}]], "-", FractionBox[ RowBox[{"4", " ", SuperscriptBox["r", "7"], " ", RowBox[{"Cos", "[", RowBox[{"7", " ", "theta"}], "]"}]}], RowBox[{"49", " ", "\[Pi]"}]], "-", FractionBox[ RowBox[{"4", " ", SuperscriptBox["r", "9"], " ", RowBox[{"Cos", "[", RowBox[{"9", " ", "theta"}], "]"}]}], RowBox[{"81", " ", "\[Pi]"}]], "-", FractionBox[ RowBox[{"4", " ", SuperscriptBox["r", "11"], " ", RowBox[{"Cos", "[", RowBox[{"11", " ", "theta"}], "]"}]}], RowBox[{"121", " ", "\[Pi]"}]], "-", FractionBox[ RowBox[{"4", " ", SuperscriptBox["r", "13"], " ", RowBox[{"Cos", "[", RowBox[{"13", " ", "theta"}], "]"}]}], RowBox[{"169", " ", "\[Pi]"}]], "-", FractionBox[ RowBox[{"4", " ", SuperscriptBox["r", "15"], " ", RowBox[{"Cos", "[", RowBox[{"15", " ", "theta"}], "]"}]}], RowBox[{"225", " ", "\[Pi]"}]], "-", FractionBox[ RowBox[{"4", " ", SuperscriptBox["r", "17"], " ", RowBox[{"Cos", "[", RowBox[{"17", " ", "theta"}], "]"}]}], RowBox[{"289", " ", "\[Pi]"}]], "-", FractionBox[ RowBox[{"4", " ", SuperscriptBox["r", "19"], " ", RowBox[{"Cos", "[", RowBox[{"19", " ", "theta"}], "]"}]}], RowBox[{"361", " ", "\[Pi]"}]]}]], "Output", CellChangeTimes->{3.412280843046875*^9, 3.412281627421875*^9, 3.412966856736905*^9}] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"ParametricPlot3D", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"r", "*", RowBox[{"Cos", "[", "theta", "]"}]}], ",", RowBox[{"r", "*", RowBox[{"Sin", "[", "theta", "]"}]}], ",", RowBox[{"Evaluate", "[", RowBox[{"u", "[", RowBox[{"r", ",", "theta"}], "]"}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"r", ",", "0", ",", "1"}], "}"}], ",", RowBox[{"{", RowBox[{"theta", ",", RowBox[{"-", "Pi"}], ",", "Pi"}], "}"}], ",", RowBox[{"BoxRatios", "\[Rule]", RowBox[{"{", RowBox[{"1", ",", "1", ",", "1"}], "}"}]}], ",", RowBox[{"AxesLabel", " ", "\[Rule]", " ", RowBox[{"{", RowBox[{ RowBox[{"r", " ", "*", "cos", RowBox[{"(", "theta", ")"}]}], ",", " ", RowBox[{"r", " ", "*", "sin", RowBox[{"(", "theta", ")"}]}], ",", " ", "u"}], "}"}]}]}], "]"}]], "Input", CellChangeTimes->{{3.412280869359375*^9, 3.412280945828125*^9}, { 3.41228098959375*^9, 3.41228099171875*^9}, {3.4122810575625*^9, 3.412281060390625*^9}, {3.412281562234375*^9, 3.412281614484375*^9}, { 3.41228165134375*^9, 3.4122816609375*^9}, {3.412966713111905*^9, 3.412966718424405*^9}, {3.412966780424405*^9, 3.412966843049405*^9}, { 3.412966883268155*^9, 3.412966941299405*^9}}], Cell[BoxData[ Graphics3DBox[GraphicsComplex3DBox[CompressedData[" 1:eJx0fHlUTd/7f3PxzhQiQ0SliDQoSfe5oWg2F6JCSAmlCRUKRSqVEmkyNAiR 5tzdQJNK85zmNNI8D799cq/vb93POv2zV3udte++z3k9r+f1vM4+V+j05YPG bCwsLB84WVjY8Xjn6Nt4FwlL2tLEoXkd/637Ytn5zmxCaAzOSlD8RdQ+IbVe r28t24xoIWfquGN9x+FNW9WMsFo6qgqT2day7Spt05sY9jjeSVgZv0Qm/tJ3 5F7xgru80I6mL8ImePDuFGRnbIgRVitGoewcPc3bbtN2+JUpjbDOAJvEt7xL NeXIfqVCub7TXVr5b2fFNbtYqEo+p9viLtUgXRlzVFboSivyXG7Fys1KtZmc wX/1SFrjZbi2oDst1EPZJq2QlXrsU4GbsFoTuifVnd287TFNsii6PCeYjWp9 7oWAmlcLuvblnlKwvjctxjsldcKWneq9wuzNpZo2ZKQm9Enf6Qmt6b9TG6dO cFCjC3bIeAl3IO2yZFGBSD8a293P54q1OKkFd+akxl3qQjuNjj4vK/SnHX12 7+j6I1zULrlKzZq4HiTe07vAa+Q57dw6/vrFDtxUrq43VTMzf9ASu4fO2oKB tHtH1t6obOCh0opFbl1WvUrLMB7abvvSkDY6vesiEefgFykrHttFow9j6b81 U4LQRrYvtW+ujkOgkKunp10qWmP9sEUj5QP6WVbz9GnaBFwajPHWi8tGn+Or w7fnxyNr+2meBXxTEHjmsoanXSHS+3zZQCMFobFvLbbyZ6aBK59Da9CvFDno sf33oSwD3Qqt7BaKnYFLcs+09eIqUVG55rnt+Vko/NWEUKUTC7UsSHJ/Smkt Wn/ELy3t63dUpi16AjazUgOdm8Q87RqQVUnjKo2UH2hKa1T0dDkr9aDCO/F0 lybUIsa/s7OqCBmeWa/m68BG5fpts3HQrwXNu5Dc8b6sBDmms1pUCbNTE0N3 bRINa0NyYYZ+lkVl6GgGZV1eFjv1ku48Cb24dmTQxqmyPb8CrfBx+a/MmIMq xFsp8eBbJ3IReds/mV2FMrfN138xxUEtSQ3dnFLajT6c3R+c9rUGVVe6KIl4 cFI3DSxpKm8/T3sulXpTY+ISraT45hkizhdinpWp579Bwp0fW1L8opDiVatv vHPH4ejkIX71/Dik5F4xmOyXgkItYveO9Y6DvU6P4YhAGvq8+G1y3tVviEuC v9i/bAJ+BEfHqeVnIg3DzpvJfnlI9uHGtV/jJkGo35I34FYeulK+ZE3ZzyK0 8ORmRU3vKUgMWSk1IlCEkm9+dsy7WoZaVaKocy5Ow2n1qRPBAyWIe/3hhgyO KiTdYPm1TmEG/hv4eU8tvxwdzBmgJvvVouRj1oGNLCzUz89TP/a/qUIF8Tn7 jy1tQHITY+dMDVmoJ/eE1j6/VYsGHwiwlv1sRFf5k8Wkk1moXD1O3CrH65HA KZOP+8ObkcMrt5uDC1mpFbnSAiMCjQikEo3yrraijad8e24asVIlgl6+/36v CRlzzOHbp/gL0cqcLp+LYqU6Wi7ZEzzQjFwr9NIzODpQdguy1OhlpZou79Zn WXSAxq0s72vz0YKmX//pGBHn/aVv3zxX9USK8070ZpV8RFc2O/DRruH4F60X fK4ajFz3/zieVZKGHknN35aYOQYRCX0X2k3CkdWKq18iv+SiHFmHG5LLxmHo R33VM9VoJGUxZ2FWSRFq3mc7z8Z4HHwzVB2V9T6jDbrH0xL2laMmnumrLB/H QS7+nXC7SQJavfOtReSXauTdsS/j+Ng4VEQuyXW/kYIWC02uD5CuR/WtsnO3 USZg548v8c9UUxGn05vOzJJGpNmbvvSk4wTwql2da66Tjm4NaWfA/BakOHPh bkrKBNSmC59U1vuKJs6PPE/Y14ZYM+StjgxPQNTOyg9LjDKRdXXQNSmndrR0 v7XKbolJsI97yNZuko36NPdpRX7pROk6u5sLT02C1lY4kmyRi8xQr8j60W70 cv9ttVZ3zJ+R/WHuN/JQq5T/9HPpP+iS1JmcQDQJLq9+e7AtOkC5NXeZNRFn oetl2kScjdz80QtVT2AriS8i4lyha/Bw+49RaLRZJP9CNRgOLJPYScT51Icd p5TsR8FL/Kh7l0k4CKnc9CDivOO10bwsiVEIvZTfH6AaDXYK5/oycZzzF1Ou Ov4cgeuZlwX36H0Go/3znxNxllnWwDbsNQKH1vCpd5kkgPr5uD1EnE8Jrw5/ rj4CErafrbxupIC0w6nfz3Gc3/YJ66VxjsCdC28LA1RT4ZE6ex4RZ66y6d3+ X4fhj8/Nc1d00oH1aEUwEefMDIU8hfvDcCJNa3K33lewMnprRcT5z/fM0mCt YcjqEfRaZpQJnWaO6kScKXBy6tOyYZBd0buhyyQbTtkeWkPEuSqjXE+kdQiC VdO+0Cxyodhpw+A6HOcbbrLdC2OHYK6l1yGvG3mwx2Mim4izokuFsa7zEIwU lmZUtJ+nSCUlZKtj3ii4958KEefGk61RGvlvIOQqqwLBG4YdjtUdCqOQHhTY g3kDjq/coEbwhlRXsM7UwRFQ32fMNiqQBgO0th0Eb3T1PEjRNx+GGOrEI/X8 TNjeq1CUhHnj/cpXxtKPhmCVwmOBF7fyAHlmxpRi3gh990E5MnoQMp56F2Pe gNPivdPfMW8USgjL9FQNwIjPqeUhAyXAmS6gTvCGWDe8WT53ACQei59Szy+H sOO7nyRh3mBLeSsss6sfDB8Nvhx4UwWv7eR69TBvfEgLfrDGqQ+euKKOgFu1 MKzy/Ukp5g2ZdI3px/m9kHv3gaTq8XrYx2eoSPDGZ4l12vPW9cJMamQS5g3w /znY8B3zxn6DoaxR1j8gAJ4n8+41QVek6729mDe8rmR8PFjeA9JfrFhCBppB 0UZQguANH8lfvrTMblCtzaHhOkixWvxD1gbXwfbjKhQizkI5dkdxHQThN57T 6rgOvo7mzNIpHoGNGqp5uA5CufSxQTVcB5uHObhO3RmGbx91enAdBO05sbLy uA7qPsr0/CU1BFvdJO7jOghSdkqX1XAdVD1ycSVqGAB7+OiH6yA8GGwqfYfr 4O21d0JK3fsht39bOK6DcENiQ78croNeBVm7VXf2wfI3SQm4DsKls6YLUnEd bLLi8PlT/AdiooLO4joIpwI+SKjhOnhBsuzQ2S09cIyryQzXQRDrHBPuwHVw 6Z32eO9HncBiKGyF6yAIcQXEvMN1UC00Yvre4C8ISzxnj+sgCKyj7LLAdXB9 m7NIyoVW0FoccRfXQeCjNBTK4TroozTv3NPeJhg063qE6yD8d/yOwQSug2f5 u7lsHjeAf+ZmX1wHgc1a+DfCdXCh0t649761EKI3q+soLPS/L5erFYk4X9wy q+uAMW88HBms/G4Eotpndd2/+eiY0ldU+WEQTprVdf/mD8nee/CKNggF32Z1 3b/5XemfLs4oD8CDLbO67t/80xsOUgmoD1T9ZnXdv3lDeV3awLZeYJ39r+Hf fLnF3Gu/9vSAwedZXfdvvshUa/gbRyd8uTCr6/7NvzQU1J5+2QYrV8/qun/z Kg5Pw0aXNYNd0ayu+zd/eIu92d6Qn1Bxd1bX/Zvfc727B50rh207ZnXdv/m1 Wg0HbSi58Pj3rK77N3+Lb2Bf3L5gZjxTSPAMJHgGEjwDCZ6BBM9AgmcgwTOQ 4BlI8AwkeAYSPAMJnoEEz0CCZ2DgmYmfKST8DCT8DCT8DCT8DCT8DCT8DCT8 DCT8DCT8DCT8DCT8DCT8DCT8DCT8DAx+ZtIbFBK9ASR6A0j0BpDoDSDRG0Ci N4BEbwCJ3gASvQEkegNI9AaQ6A0g0RtAojeAoTeY9DOFRD8DiX4GEv0MJPoZ SPQzkOhnINHPQKKfgUQ/A4l+BhL9DCT6GUj0M5DoZ2DoZ6Z+kELSDwJJPwgk /SCQ9INA0g8CST8IJP0gkPSDQNIPAkk/CCT9IJD0g0DSDwJJPwiMfpDJ36CQ +BtA4m8Aib8BJP4GkPgbQOJvAIm/AST+BpD4G0DibwCJvwEk/gaQ+BtA4m8A w99g8uuUSPw6ColfRyHx6ygkfh2FxK+jkPh1FBK/jkLi11FI/DoKiV9HIfHr KCR+HYXEr6OQ+HUUhl9380f8HoOlv5HxwU9aG22+IzGFn2pPO7mof5RNbfE8 ZBuHZIji+dKidi/+5CJgmgfGPNM6wFgnN9K+J7skBL0NWVsXpHoLjfxo7POt GIP3PVzniD5fquNyBDuuDyHbF83e31FP8L5U8xutkaGo9859QVM/smVRjwgP 9USyxHuij5U4clrcB/Pff1a6R19qcFO7q+rSv/gFIGfZ5X5a+b7ojlXSfb+Y MQgJbl3IubYdDVmXz5FXaka8ebIbhD3YqQv3t63QTPFA508gFy+7YNQZF7v8 m8UYgLxDWW1mNVojde3r+vwuJCR1bvzaIhbqy9sH2lq3KVPOJHLliaqFom7q /QPEPrtn9/eI4uL9d7+fnPRWEPPhWcv/007xgPzNbFrE+nzyzQ+kikZBx0/M 9mdmNbSyvDYg1ldIur6TV6gfqgzdzWl+AWDtkI808f6/959ebeA5CpK30kPw /kHVWfKwHN7/lQfHCk9oYN3fsZY3pyQEZLKlv77A8Ty83DzWwGwUOtjehbRV d0EAn4HOIfMc1KLzOkt6XyVcWsc7j6gf0jtvzfmC64m+cGNayWApWBjlNhP1 46RHur0njqeh0J62G8b5zOsDY32m64FxPdP+gWT/wNg/U3yAJD7AiA9T/IEk /sCIP9P9BZL7C4z7y4QfIMEPMPDDhGcgwTOFgefkkfyr+L6gCs2DvkfNcyBE 403h4HIuakDzrhrCrwnSYbNIxXrq96b5bw2duJhxDgycM+UFhZEX9fF/cSk+ G6cDtN5Ym/bdtWMwM/HZnPB3Gr58lq3EuoDN9Ph5Yj+sKqyN6Rwd6Kzhm1NY FyOp3OMDNens1M725E/WLw1pz+tX/iTqG62s5hRx/bGb85cS/fbyvZa5BE/X hpzOSxJloT6Z5WU+JYG//TctRWLPYeL6jll+cae87/nLN50yfQLEPJ9SUxzR N05V2AQR6+c5RakR84LmO7JSMe/f2dNuRKzPZmPmfWu4D5KsU9YROia5afAg 7odoyb83KxPXLw5XtCHqcdtylVCiPt970fDs5s1WUBPdcI/QlwOnLlmzYj45 J2Szk7ieaZ7CmGdan0KyPjDWZ9o/hWT/wNg/U3woJPEBRnyY4k8hiT8w4s90 fykk9xcY95cJJxQGTs74/M0fRr+/fyzxdPZtBIbcfSlrFP9AdOgPjijRFNRu LXRzICYNpAUsQvE88li18FSMaApYK25uSebioTLNI8Y80zrAWGdGyTIu7tIf tKL87PkgH8zzO8xCn9/iobKfgfP2eX9g8RnTvJiIFGTo2OUUvjAJ842KJp5H y3Y27E2OSAHV9JwCqwM81M6271OJm7xQQsKWu6xGhqg1oUbivsMY8/WIcT0T TwKDJ5k+Fxify7Q+MNZn2j+Fsf9rZ2ec3s6zpEU1vxJ8K6FMOxR4b5YHSgv8 pMTVvNCv0IIN7ZjPsqJthFY7/s88jTH/8sl6SaJ+FLBIs+tgPjP4vDo8L2cM puuWCNjueox2+c4xPilmi3JVTGqa7Maglc6PjPso8Wph6qfzo+ByTG5e0iYv kIoNoUwZ4vgsO3Xj8rdR4Gq4wqXm1f3v+uXVM1dv9xTB/G8NFwneRG4zfFoE Tz+eMy1+fRRea7mr4s+F3guyJ0+I2ULLRfm8xbmjwPR9KYzvy7R/INk/MPZ/ 2f+FzFIBC5og9/EzqYePUbRldEyJdZj2g0j2gxj78b+heQavQ9nGo7KLdvgY 7bWoghKxDlMcgBGHunviPnj/FJFvPaFv8P6zk1ln+eGhX9Tu7yWPURW/8kyI 6hVUwftCJuvmGHyt0jmN54F15GBbEJ5fsF3nmmTWKPM8MObNvefNf/slCR20 94zoMXmKBjZ1r9LaPQEXZc+lE88zlpxfmBeI++BvvXLbDj4aB36W40EfmiOQ qrBk4y5BL2TfvdI5RXwckszYduJ1wGFqk3MnXmdbScf9CJYReHFlTiPRP+dF r4sJwOt47/155VXcCCiHnNvvpfwW5v/K9rJ5bIvmrLxYvId3lHkdIFkHGOu8 WunZjPcDZvd0TigLegF3T4zQjhWjYDCmqoDXR6Zazyft8foX/pMu+yg/znw9 YlzPtB9g7Kdy0jYv/lIyml4z5VdeaEI76RVeYHNgAl7PlCS+jItDlCCd50p2 zoiba/Fq/r5xaJyZvf4fbn2y6qsc+oehYa5APr4eMuzW7t5u5wyibztcGw6O gDW/3EDe1VgIj9BcNCrwEU1nTfdcujQCyZJONsfiEmAwvTBRPj8M8cul/Tyz cQQUXbqLFnnHQkD/gXpT6UDU7Ky4nnpxBCqLmmVopVHo5A1b74yvz1FWwqvJ 93vHoazq5povpSkob4Tqmv71LaqWP97/+NIE/An/acDCko0iOeP0kn2taQec I7s+jUyCYauT16Ogb2i48vSrxyWf0Q/Rlk8/vCchcsExURaWQmTyp7hXW9CB Fsa7c8d/u6eh7KTak5TSPMQlJ8KR/jUZrfG+L/IwaQrqctNXsbCUIu9umz19 xXdo5zbMEV/kNQMiptx5QxzF6EHOgNTY8TSkfzBvflXjNCy8J7GYhaUSWRjd W5jse49W5PHh84AFC9Vgw0WtR0FliG+01OhxyVf0R+P3gVoOFuouZd85LCy1 6EC5T63z8Qc0xfcnUn+vYaVa0fudrUznE/yb8wqEd1Qhf9G4x+Ka2eiidVQ2 hz8LtYTehwrRn7OX0vvQ0hrZiZmZRsTdoLeDt8+Tdtkrv9boHhuVe0tOe4R8 A4pwsu07pvQD8XYX+6imsVLNE02GZ2aake0Kw7V9xV40/iUcSXN3sVNF3K5H DHE0IYGqqIVjx4vQ4Lba1VGH8Tp+gX0zM63o1+HzXOWffWgNaQ1qRpwc1F2d my4qFzejk1deiKksK0GNh6PaC9rYqCHXSrpnZn4hXQ/z7iRfX9rtTcbHE4o5 qAb76jY+CmpFwdzu1MclpWjJ8eT+Mmt26o6DPO0zMx0oM8eqOMj2KY1PRl7N 4x0n9eYb965Ks1+oJdBBr86jHB3WCv2WwI77XEml5pmZLiTHYZ/gfPwZzddH 8rr7cy6qPwc1SnhHBxKTu3xFXLMSUXbL9Ru7cVAvzbP4OTPTg15TnANNdgbQ QqVRovsbbmrc6T6zK9xdyCzfwMWKpxqd7U4+tmYhJxXNTYwMGXiJKnfzOX/j iEBzL+o/XdIzBu8OWXQFD8Sgvl/yPl85EpHexY8fTeLHYUrIhfVqzxc0eVRG xjsjHbG4Us5suzUBoqMFD4MHMhBLkvqqrxw5aJ9tgmO06iRo1Vf5uvRmI7bV pzmHVH4gGeV0Zb65U3AtsyXkSk8+YkvdOeKVUYw0d20YeJwzBfnlNkclrIqQ 89Vs000tZWjfAv6tF52nwYju/3AynQcY+nLHaIlFObpXWn9YX6QW7ehg+67U MQOuUjznXXor0Zx7pjmDKvWobKWF2Og+Furq14/MJs1r0LfnE4GqMo2o4+e3 tckYb9HLF1tc6alD964pV3llNKGj9zQ3xrexUNep5in2b2tAe7XuL64/1ILe bLaMyZJkpXbPuFMkrDAORfO1NrW0osVRnku/XWOlxiYeUD73uQllT/O52Fz7 hSz2bFY/GMtKZYntDfO84YZubTOWDJT+gE7aJwSYXRyDrR8afD1uBKBVKVoc L6QR0lk0nar7aQz6breYvdV/jVLMr9kOGWehZRGJ04pjY6AepTff40YUMp1J Mw+Q/oHq3RemhVLG4YBpm65C/kfEm33/U4hjCdrz5Grg+jvjYH8rWOytfiw6 4/l+85BxBUp5pSRyPmMcIp4cH1vVnYCS9MrC92nWIEFP95NibBNQRvczFzGd B2A1PK91izMVfb72+IeNWyMSN3tTbmYzAX4Xv25TyE9DDZXCj0Icm9FGr1qE 3k3AZishwX6fDMSrlKD+3QLH596L3RKNE5Dh6MD1Vv8bkg/R4Bky/oUKjDzS aYsm4diDmt9nhLPQGc76b4LHOhDXh4pUX5iEPz7bK1Z1ZyN3EwunfZpd6ETU xAFW00m4G/QElcXkosR8TmUL6EGjo3cWVfhMQgfyPORzww1WeWSNvcBx3hFk x/agCve5vrd2ed8IgMRl0QUBOM5LY7pLAx+PQu+5gM3v9V/DgAxlPxHnTDFu 9yT1UTC9M5rodSMK5uoLKxBxDrnyMf0Q5ygMaG98qZj/ERbu4nxMxJlXy7W2 OG0EovX1Ot7px8KKo7acRJwV/mzX8rg1Apcu3pNc250AIhe77Ig4L6r7wFug PAIb6f78VqbzAIO7+k7e4UyF1TkXPhJxNirY4OyaNwwlajy3FfPTQPhQqCkR ZzaLdG8532H4tH/Nq0GfDBCvqxEh4jxfaeuc3NPD4Kkrl/VO/xtInl/aMIjj XJWb6yQvPQyXT2l1nhPOAtk+7WdEnKXzTBwNOIZBy/jsvLXd2aBww+UwEecH FxzbByuHQMLsxtaqmFwAzvT5RJy74y6sX/NhCKKMVpwPHXgJ05UVPV8xb+Qk v+VpOjoKj16WhIUMxED8nampDMwbnOYFv9zcRkCFf8Uqi54vYOd2P90L80bQ +4gtaRnD4LBn676QgQx4orvwXgbmjes6TnNVp4ag2v7QHdfebPi0zl9tEPOG wclYaovCEGyLt0652pMPv4Y97xG84Vl97f7Z64Owb1RzAvMGWOkfad+IeWP7 Gb9dbmgAhunPm9iZzgO8krqybalFOTze8PPtCcwbkSIJfgnH++FQwe2Drr2V IPQodB7BG4G1PXO4PvUBi6n35SnzGtC1i5EneMOn1H7RrYV98J77tdvVnjoQ jHpygeANZYXq4fvWvbDlYE0p5g1o/Wnj/xPzBjK8npSf/Qfurj3bjHkDohYd z92IecOSU1648vNvqP3d3Yd5A67t2TlhjXljWuSuystPPTD00zwA6weQMdds TMP6Yd2r+LC9kyPA3cztgvUDtI4vqUjF+uGNWsa7s+XDoLGpuwHrBDhWn3bK E+uEjPml7aLRQ8BnXDqF9QCA8tiBVKwH3v/2uGrqOghmOqfmDXMUg/eBp+tG cd13X6DntPr0AOw3K36O6zvcZZNd5Ynr+85X7e1KO/pBxlV1o8iOKrCN+bFU DNdr9iTnoe5FfcBPf35qSj8P0Ex/fmpv5Lc+Ur4BTi3lnqOH6/LvuWGBxXd6 4M/lok5cf0H8zAHWUVx/J3kWXdy5rQuMHP77hOssvFRcM70b11ndlVYSH7vb odhNxQ7XU1i1pGfcA9fTW8EDf3yi2mDPc0dqldkveNKdNFKD6+ZI1BH3OXYt EBeRyC2yowMWfHMZ3IDrYygmqsNHm2BDwkABroPg8uJonyWugzumZXkv720A 3uuXeVlZov/pw86xWwPNNSOgLfufJQtL6r/5XvbJkj6fYfB7O6vT/s1fLqtL 2a05BFcWzeqxf/N/NDXNu1gGYUn+rO76N88m7ejY+rEfElxm9dW/eS8FcVhw qg/098zqqH/zdyYLNwhw9NL//7/zABX08wDFdbO66P8+91x1nbF5J7xOntU/ /+YvGLCYpDv+Ahv/WZ3zb376zSPxCxYtoGYzq2f+zYdP3/j1n1IjrDwyq1v+ zU8mndczfFnDjE8gwSeQ4BNI8Akk+AQSfAIJPoEEn0CCTyDBJ5DgE0jwCST4 BBJ8Agk+gYFPJr4FEr4FEr4FEr4FEr4FEr4FEr4FEr4FEr4FEr4FEr4FEr4F Er4FEr4FEr4FBt8y6Qcg0Q9Aoh+ARD8AiX4AEv0AJPoBSPQDkOgHINEPQKIf gEQ/AIl+ABL9ACT6ARj6gUkPA4keBhI9DCR6GEj0MJDoYSDRw0Cih4FEDwOJ HgYSPQwkehhI9DCQ6GEg0cPA0MNM/R2Q9HdA0t8BSX8HJP0dkPR3QNLfAUl/ ByT9HZD0d0DS3wFJfwck/R2Q9HdA0t8Bo79j8nmAxOcBhs/D5OcAw89h8m2A 4dsw+TPA8GeYfBhg+DBMvgqQ+CrA8FWY/BNg+CdMPgkwfBImPwQYfgiT7wEM 34PJ3wCGv8HkYwDDx2DyK4DhV6jazuo0lJDdG7Jf8BRlnSF3LN+FcXCRntVp qEJe+raOoDll+IhbKceH//HTKAw/jck3ozB8MyZ/jMLwx5h8MArDB2Pyuygk fte/5/tM/hWF4V8x+VQUhk/F5EdRGH4Uk+9EYfhOTP4SheEvMflIFIaPRNW5 a37J8x06eFskq9X+KYpOznaV0BmHtY9vntaQpaHK/c6jmutfo7miihptrhNw cij/asOCLDTfSO7QXe9IpP5n5fWNhZOQev+IINEni5pme/hgPu736q5VXjsN x9RmGsLjS9DNhomnfPmRaJ2VSv8z2xko4SwXO1VVgd5XVgRrOr5Gj6Va2H+Y slB9i/QlEwdrUMK6y9bhgv6obVV3Y9xqVmoFHbeLmd67kfyYYrEzpAHZPLgc GfzoO+pumz78sJuVKiD1ze19QxPqNJoxXWOWi3iq5x4piWWj/uJPjG5a34pk Zeau9NDPRoZFqXO2P2CnKuwb/070yUHKXhs+YD7efcFhcZApB/X0R9b2wZAO JFrQc+iTaRp6T/tqe+okJ3VZu2NYT3EX4jGQbHZakogWXwuFBmMu6pYy+b64 g69RcFv/uHZtGMrfuT1rwcQYOFw1cQ0MjkP8/mMuQXjk3RD5ZP3vcVh3ojxU oTUNzZsrb8w3iRDrfwovq0cnQEt4YAfRD7N1GL7Beg0p32Y/JSswBb20oPS3 OoVobWzpxFORLLSaMpQdoDUNQa68X1UOlqJs/vFdL1xzUMET4eYhnxn4Ffb7 nf/tSlR0fJ2WP/93JHbzlrWODQv1PJ1vWeh+miydbxek3JXjnapA8zoKF1ZU VKMWAconfTkWqp1A+cFv+2rRSWV1r0w8Bn7f4j5WxUIVt+BwvXa+AUkt2jiT dKAORbltFXx6n5VqkAlbiX44crJHwALz7ipXzk9UYKPOufBtmYFsK5KXGPVX XfYTZT/PpImwslPnbzRXOBD7C629em6X/Pc6RNWaYnXNZ6dqiOifiYp/jBbq SFZjtKD9h/1Orbo5Bt2rlLTVMS6bttdUETg9+jjT8+joGExHfLQyOfUJpYpJ GRyQyER+uxawf/YZhwd7mm0R7nu12wSkv2B+nZu7woVNZwImLyGbvccykOUU VUjkdhHKrzlexCMyCV85+mye4zjWxe8+rIrjqv5RxjZ6yRRctWBn75QpRPbx 1Uv6ysqRqmDu/vWrpqGHrhMW0n2zRrpOmOpeGBD8OwO9uf5nd7tGI7JfNaK6 /b9JCLwuumwVxuVnXcMKAqdS3aPHmv9MQvRqNZ6H5YXIQT17u/qhFlRyeL7F yc4pCHu6So/oeynv7IIJfj0pZnhi0dg0UMycFu/eUIU0Gntqbqa1oYITb72N 5rFQR+trNm7Dcbzm+r6RiGsn/1ilZhgLVa7g9MqaK3ehk3W54W63Dyg+JvSR Zdco+PL6XU+IcMN66PZZhzyE7n79+UMf695Qa/+s0ft3QVOppf/IcBaqSFeN yMLXU3oJ3jSnTC/8y6Oiitdnn4ObxFp8Uel7jMpC89f0j5Qgd88d/h7Xx0Dx 4OC2PTjPux5J7iXyPor//q/nA2Mg1Ki4Jzn9E1I/lHgg8VkN6nG2uNX9YBwW 0/WtFN0fe0fXtxmin5sHBRPA9tmz+BZaI6osWn5RwmgECtYqZPB1fgTfyDPn CuqbUXMH67yTuH8fLHGPfpnyEp42uyWsH2lFJ2qipfOujsKIh3ZXEubxIOu/ PDpnQdc6Yv/T98orqYfCUFDPjYP3hzpQeLR67q2OMeCdEVl0Hed534n2XCLv A07PUdiSOQ7iodWrbjiHwvFwnrAlApFIWVZl0tF4FCz11/y8wPURxla87T+5 PBmVmL9tU8keAVO+LaW98vFgV5cbZMD6De0TO2OeoTkCF3Yu2JSG6z21yT2H qP/whm96YHAY6vbyaem/oMHQQ6tzu68Xow27tjxakj4Ml9omD/d9RhB9qZt/ e1g5WntLWdn28zD4UCOrzVkR2Kif6Kz+VY22DJV8uf19GPrpfRk33QfbSO/L YpUvrJ5TVgrb+J32btOvQ9UPJrMMG/thseJlC7Z9ZbDWLWfbjj8NiDKwV7aq vh+GRR8bBOD5isCxUWXlZmQfvc+hgn0ALrp/eeGJ672s6aKDBD5DOt53t6gP gKVZSsC+thJIPLbqnC5nO7pQ4TRv86cBeFFrM97oUAw1fYWQdqkTGchpUJ/J DYKK3lGrctYo4PuKSpSHAtEJSfaxjxyj0B6aIX1qeTK0HFlti+OKbhfU56wb H4auU/rxBV4ZMNlU+TkuMxkNJp8u8OMchpuum4uI/rYhcKaD0K0+Oa1S6RuH INWv/KFhST4YGww7nwnLRYHmFk9cLw3CNU3DcevRQti452YSHpFSyvWrcUUD IDYcYm8QXgxWgqPyGQ2lyLxlQY/j8QFYTPcTbOh+VyvdTyhfOrNxwZ16uBW+ /+eASRGSSbi/lov6GxrrK0/iOEJCXHc/674ytLwwoqFhqhv8Pdg3KvU1whg1 nWODdRU6cOfCao+l3VDq2RVM6NT/FunPELo1JXlzTceDLsi1fOg9fboZDBR1 k2QONaLpYx/VNfS74PSCwMgHec2gwrXEEI/o49j4VX/nLrDsYWsWHPgAxaLb g1RizdB/WxxSzteOwOpv01dxnsOMY23K5wg3JFBs8mGl/zCceJ92QSoiCwbF otaFLglGijGOnV7Hh+DploFDRH8l8lSsxRPXd3TTLf3z+kF4sT0pqlW+BF4J tan5icShMof3O+aP9kM9/1dZjEuYd6Rq5s9nhFRy3W3m1PbBiJXShVM/q0BL y15M1PwbarV/dnNhGZOvtS4xheFr3Q07uzl1tBG0Dx/lHxYJRq8qnt5uvNEJ Xj+LzHGew/CzV2YLOz+iDzoWYlfTf0GMV0OrWXQrHGN1iRO78QWNulTq/pBo hQrnrYNEH3vYrPpcFK7vhY0Lg65UNcH1iMmHdRPtQNu2NsAmNw+Fnzw6ktvT AF7SSblYF8HE4j9zWuyfgoPlopW5gyPwim3RJ1xv4KxkpJTG+tewUqjp6MKk YeBtKX2JdRFcEgwKuOMdCWuHZETzLP8nbsCIW0rn9nGsi2D/GpWhefmRMIf3 /LsT3/thW/wiJcyPULKRyrHX8TVYOez11zPrgxg+SUWsi4AVbmg/F/QHWdW5 DS48vSBAx6EB3ddqoOPQ/9KzN1gXQf4Vr9jAR9+hYPznG1TWDY+Gb9NwvQGR HHOZ1Wa5UI3cQ4KicR+f6fMT6yKssw8HuulnQ2+XSC6vQRtU0+Mm+TdukE2P 282APJ6hkA5YQ+nU+WCaBqNh23nbhH9CTHfDq/iDr0Fp9OxxrH+gYbdYddu+ UVj/KEcG6x7od/T/iXUQrLusxFlyZASac6grd7SmQaZNou6iSQSj7+v7Vmr8 T/4CI3/PmX4ViNIpBF8raS6sf0DW5mj6seEBoB6WEsZ1GjbyDi4McM2B3Gre Vywf+kGMvXPxs9uV+Pvz1/rxfwdrlYe+ukf6YILOhzNpf30qUTofzu94yTJv qgLa9knpl1dUQ7o0B4tSRR+83lawAeseOCR28AvWQVDgOqnM7tkLx1jOjWD9 A39eCfFg/QOv+Wzl3Ux+QzU9fycXzuYvxNDz1/fdfFesf2Bk1+vjKst+Avd/ Bs+OOLVD+FL/CFynQeW8QR2u2yCv0WuffaAVBFNNpd/HPwaFczf8sP6Bhfkp 1OqsUYilLluKdTnE56o+IPB4/FAcZ7DGKJy49Czj4qlPsMl5zgqsf+CaGc/D XR/+p74Ao75cqD7muO9YBtg0XagUvl0Ej44avesRHAZ5vpEIIo72fwQHsa6E kQd3Z1Qkh8CIa+g91j/Q+qT6WW9ZOdQIqK0t2TAIu+j1egvdj4qg1+ubemyv Q39ngIT6RUGsf+DqSt0ltO3DcJA/XkcQ40/P5+VrAo9pWW/G+Q4PQZPVqR1u 5YWQNXhmTA334zaKW2qfHhuE6/T6svVvfYEAen0J9JC+uGdDFUTrKdpj/QNK rJErZMT7YW1Pk4ccjuONYKerRFxvtlAe6A/1wsZvcsYVV+6iXXLXXLD+Af2q a4uc9MYguU9oJhrzYErzDUeCF10rYr75XxwDRMm+1XP/LrIS55rC+gd2JtU1 bcHXM+kfYOifkOG163X6HkM2j/4yrH/A+2Zbw7mcUXBicytWw/m8uX5Amshv HjW5B8f3j0KUTKgTLf0TpIVd2IL1Dxy/e6pjTuII0JjeK6mj60nUnB7XK5iA zllrF2D9AwF7DvXmNI1D8+KF/PMxD15bRLUheNFvDo+qP+6LLyvqHPdPeYm8 35SnYf0DlbscBTYWj8Gwh3vP/6d/gIOuf0T6ty/UOhQGEZW392L9A1wZwVZW x0chjSrx4taSRPA21orB+gcUNwuxZtuPQHuWnt5151D0yN1aeqlAJIhHXnll /XMMzmqv5CPqtK54rQVRt4tXBH6MvjEOX0Vr/P7Ix6ODT2VHsP6BV4Yza2VG /kefA0OfC590X3v8BQ25+PAHY/0De/Z9/NN4ewJy0mIjf+O6UkR7fpCoM2/z L0k7eExAhIhOtCkrQtc+JQjX/KoGFdPRqGu2E3CC3u/MpftLW+n9TtOOo1Se slJEe3+qBesf2Nyxxf/J6RlYJ3XRkqjTsdLtd4m6zc9RuX712RmodXim9BzP v3VZobZLuRlc/1gUCVJnwI+uz3f91eegR9fnF9VZZPa2laAn6twfsf6BFVYB MjmPp2HJXDuzBodixF5ocRfrH3CrLhw/MW8a5I/msGD9g54kOdntHgqEsO8/ I/fAOLg+9vpE6Ei+00J7TLCuvO95orREbQIODuVoY/2DPJ8+r4nPTAZl1i05 pyiTzP0jMPpHRzmRDIOSfGQU5Wp8NiwXmoa6+szKp6B9x9PrhO4pPbRnhw3W QbsyX/NSLabh3X/mDafCixGX6rWvWP8Ai/m5+9Yd01BI78e3MvlI1JsNYfPv 1KNTJe7fB02KwLn+2Kexx6xUM/mkeYSO1Kb19RG6MrNOe/JOEyu1nlMsd2df I6qPH+QTs66C0WdrzvutYqMeo/ePiX/7R1hB7x9HxZYvwvoH2Xrt15Q91Ahm P9kOtKuzUccnXJcSuufGMrEhQgcpFLqkl1LZqFzHbpVh/YOmKnXCD8eaQSbn rS738+Pgf4dDl+hzXvkd2J6C+x5pw97h6kjcr929qY71D9Kfq9X1akkwJEjz Jp7p+B9/Axj+hlXWHCesf9Ach0Q3f5E4cJE9aNCuMQOKGUvG5LEul7VeG9mP dfrT1MRHwzIs1J2yHsuw/kEjJbzvN5h/A/WQdi7LeJb/3y+K+P/9IhfZ7yJY /6Azyy0fTosEQ9vro71sTmzUW1ZDJ4k+p+11vsBS3PeEGzmyGkixU2W3COVi /YOeS3EUbb7xBaw3OJlnlbNT5en+RvpffwN20f0NVfvcI1j/oHXH/d2u5+bB T01OS5c2DupXP6HCzoEe5PZW5OZURySKXLVw+RJPburR4edhZ+O70LaK7z84 h8sRzcnwpYwtJ/XC3XnTeB6aey5s4cDztiHSNYradcDDlleL14EPV4LP/MHr NFwXP2QhmMM8D4x5pnWAsQ7T5wLjc5n2CYx9MuURYuRR3GR1bpxyJ+L9dn9H D2cd2nPWNev6aw6q87lzqx5MNSNRk4HrLqfakP7o+E7udWxUJn5DDH6TUd9w U0q/EW1VtxK/Y9OOvi28u+W8GivV3r7NcmtAIer/Ga5XWdKN2jMTV265MsVc dxCj7uwd3nQ/W+Arel37kmLv3YNM7/6Yrxc/AfYsQ6x5Al9BwTx/OTE/um+n SKDbMLMeQAw9oMXCKSodUAg8CmtXEJ8ranR8RXbJIPSNGcpK6zfCbQ3am9t4 n4fcoz/rnP7DrNMQQ6flNJR+xXEAqbPmLfdxHO7ZTdv8mOkC1g1rtscrY90t vvZDF45b9bDPQdb+RnjdGHKa4K8JS1sZ3M+hye5deUXz6sG1cQUi6sTyteK6 9rhvXrhiqLCioQw0O5s3EM8n/O7x2FbE5KJ9yoFcSutLmfs+YPR9TJ8LjM9l 2icw9snUjwOjH2eKAzDiwBQ3YMSNyScBhk/CdF+AcV+Y7iMw7iOTfwUM/4oJ J8DACROugIErJl8RGL4iE26BgVsmnAMD50x+LzD8Xk8WltVEH269xyatCffl d84E9lCp/+NzAsPn9BIMHroKPUhn/+/26phc2NmSfsv7BRfz+UMK4/whk29P Y/j2aOHs9f/3ewK7dMJz4rKY8QMM/DDhDRh465Ge9bf/rZPw6lXhOZlSeErn +a9/eR4xeP5A4uhP4nwYT4ahuO8N3P+GL33302AcKJeFrIm84nMbEPiA79uo leBZtRPjzH0fYvR9Emd8lxDPLyE51d4Lr1PyWHtsWcsIDK9SvUbgZm+uJrUK 5/2frAlLp4b/6buB0XczrQOMdexPlCUQuJEeaFZ/h/P+HF+q8rv2EWDUNaWq 2bqGGHVtTWuHBsEvU4W2w7X4cyc7/khbnhln7mcRo59lWh8x1mfyDYDhGzB9 L2B8L6bnLzTG8xemvg8x+r63nsZxLXFXaZyiSpcjj52kuWwpnn0f9rTQzpWF LanIRiw21m/qLZp2vXagt3gCFIOmG+V1c9BNV59HUtOfEduBsq3+ElPg6m5Y +qOlECU7aFP9ppLRht0HEl/cnwbr/LR4dsEyNK3gbOfgkIYGzbs3HG6ZgdO8 65/L61ahQNnGg1LTX9GZQ4NDNiEsVG0NZwdTzzpEkaRItNhno+wVyT6xB1ip q7/1R/9oaUB14s85/aa+o2Opzfyf2Nio3mdfhpqwNiN74dGfavY/EHtPeORQ DBt1DsdhH3bBVuThsVHfwaEIWYQNvQo5y051fMlx78WOX6ietypbl1KC2pak 8x1ZzEEd2hVrI6/bgSQf3N8mNV2K+CR0E4HGQTVtMjYpsuxCjtxyoXNp5Whc pE305xlO6sv3a4LX10Ygxc3SX4Xx6F6wV15JfBwK7kg9ilttSjs7ZYni8Xjl wn1jIp7bx6Wy1tUmIsrlPV3r8bhxnOLnJzkBnvM31gsYZ6DeZvmkFXi0fVI+ skJ2EjjWJh9fV5uDlD3zHdbjcZ0F8s7eNgUpy0VNn4gXIrXAj0K+eLyw1+HG Ixkc55Df4QLGJcji2qTTCjyOa/NvVZaYga0b49teBJejZ+p72wLxuO+Feejh BSzUzk+Owutqq1DGWq996/EYxXvXJ82Zhfpacd/pN8vqUPdwbWQYHle/CxDI HWKhSp7m2f9EvAE9aPPm8sVjUMNCar0RK9XtTbe5blYjCjyQKK+Hx2yn2P/c slmpHZ2FjwSMm1FMys8LK/D4Q8li8W1xNqqqZGxUDVsrytrA8awWj5av4nUD ndmoh7+pvX4y9Rzlck+OFLZEo2vDhxx1o8fg+LM+7TCMS4W1KnNaMU7fVj4/ ScSz5sHNJB+MS8f6PRcJnO76FfLxgdI43BfYeEAS43Jl8kO97Rin9cauNdbZ 4xDSs1TFB+PyhIbJ+kKM03fsCtyL909AXcOtgJsYl+KJbis4ME7N1kQ+uFYy AZ251vySGJfDotGLtmOcSn6TNyo/MAkjn808GzEuv/qU8JhhnHo8XrE0MHcS 2INOz/XBuFS7PTFD4DT/oWnOSaUpWOiq56yKcbl1+6MJAqe3nsrKl0RMgbvC BsebGJf8fwRHCJxqrw/e1rxgGp5sWZdyBONy6nV0P4FTDnW1y+6Xp+H5+tVj WzAuW/R3/SZwmqh0cSg/expCli+X48G4/L64tIPA6ZCKSwrfyhnImH2/+gCl ffPf9621V+fN/j7GoXDi/Wojysa/v6ODxEVPz74Hp1JJvF9tQjFK/Pu+teqD xXuI+VUcxPvVVymaf39HB3mwdM/+bszSVcT71VZ4/b/vW1+RHlKYfd9Hlni/ 2o7i5Pv3fetkO7ltxDy3JvH81YGyZoaur2s+byXmWaSJ96tvU+pi/r5vrSFt KUHMT82+X+1E2fT3d3RQ8F0LMWJ+bPb96rsUu1V/37d+Hv5JmJgfnn2/+j4l q/Dv+9ZyO2SFiPn+2ferXSlL/v6ODlrZxSJIzP+Zfb/6IeW0wt/3rWN+a66c /R0A6opQv6nnsMtFI4PAYWQV/5og71G4MaQZ7zv1Fj4a+Wwj8PblZlyTKdco HDbOLNg6/Rl2zdyZQ+Bt/EzJe8cbI9Cp06bsO5UMJgUJvwleVInQsGseGAbq aqdqe4c0kF4dXUnwYoW7TPftK8PwkG+xz9bprzBuGpZO8KKDNIV3bf8QVHC/ 1Gq2z4aMpMAoghcPtlF19OyGYN2UNLfv1HfI5ND4TuCNekHS6ynXEFzqT0/d Z/8DNkapphJ4i304d9X6Z4NQayn+xd6hCNwP7Yol8Pa58sPSxbKDcMe8TwDz IPSPK0USeEvIcik9XzoAG0wSrbdOl4JuqEIQgbeE9yf2it0YgPwzt0vm0Moh WW2bD4G351+C7JrFBuDqKbWtzfaVsLpvq6upZw/K7fafb9fQD2s/lJ/G/AjP JG+wEjxpXGZvkrhiFI4MtrtiHoRpm0diBB96cEezGiwZgUf7ZK5iHgSBqC1i BB8mKa30r1kwDL38FqsxD4J0AH8KwYtrc6cHN88fgkiLyhbMhyCqOhNG8OLm p7kcJgsHoaZqZAfmQZChDPQRvHjC2Xpv7LIB4FVe9hjzIIDcL0WCDxP2R4tr ifQDJVzuF+ZD0NxSc5fgxWF+7Z2WO/rg8oKjSpgH4Zjojx8ELxrvyxU7rdcL +5OTcjAfgoxHoxvBi6p+y19fZvkDHea5g5gPQeFhzUeCF+99WXw2xbgH7qyr XoN5EKj3y8oJXjxR3ynd3tgFK8s71DEPgqrTjwmCF9/vbZxvadUJn1zHrAKD 20DDMWctHtGzHR+v7VjbAQ7ZL+swLiGV/dNLX8yXTzc0UWk5I7AwpFsH4xL6 UlsSnmBeNNF/pM11dRiaTnJLYVwSHfsCjFM04vPq4sllQ3B83qI5mAfh4RqH 3U8wL648q1anlzIAGaaBYxiX8GDmtiLGKRJ8ctAk1KAfJHI3dWJcgs6fPWUE L5bOORjExdoHT8QSqzEuYUk99+UmgheFvsXyK/8Bx90vWzEuobIgl+cJ5sWl o2IvhO27Iaa/ow7jEl7QHoXuxbz4aPS0In9CB7SHbC3HuAQpXTFBjFP0c//x neeG2mDVAZsCjEtY/GOO6VHMiytFl5o93dECB1homRiXMKTaFS+JeZEjlzeu x70R7n7gQBiXUEnL48A4RSztGzJ/9dZBwimNeIxLSJR7f6DJvhKVtkaEDjZV wgfV1z1Y/1CkrWKPhR87STHaFDf7viFTPIEknkASTyCJJ5DEE0jiCSTxBJJ4 Akk8gSSeQBJPIIknMOLJlNfAyGvu8pPHsO6hbHq3dwDrIAqlj2U3EU+mfAeS fAeSfAeSfAeSfAeSfAeSfAeSfAeSfAeSfAeSfAeSfAdGvjPVHWDUHTNtu7MR GJcbzTiLCZzW3upWJ+LJVI+ApB4BST0CknoEJPUISOoRkNQjIKlHQFKPgKQe AUk9ApJ6BIx6xKR/gET/AIn+ARL9AyT6B0j0D5DoHyDRP0Cif4BE/wCJ/gES /QMk+gcY+odJhwNDhzPpbSDR20Cit4FEbwOJ3gYSvQ0kehtI9DaQ6G0g0dtA oreBRG8DQ2+/mbfYshHXlehc41aizlg5GQjZn5kBpj4RGH0iUz8IJP0gkPSD QNIPAkk/CCT9IJD0g0DSDwJJPwgk/SCQ9INA0g8Cox8MtfT//gLrnmov8e+E DnqyaKNtdxUblX/vQDihy/tv3Al+ivlS1/jKme3Xx5n9CiDxK4DErwASvwJI /Aog8SuAxK8AEr8CSPwKIPErgMSvABK/Ahh+RcNt/hOELs93bpnfgnU6rYfq HMDJRdV5mbWH6x1CG95yqdGUIlG1fJl9QdgE3NIR7ejcl41K1ZUq9gh+Rtcv iK08xDoFb88N6kacLESLqSOukauT0c/x+X9E9afB//URxTrfUhT5TE/QZX4a UjVZdullwgzcbYkTXFRYidSfxI7scP+K3ipGfrr1kIW6hX5e1JXpvOir/ZfO ln9pQuJ385wOzfuBEq+xfPvxgo26onf10SvVLagF+WxxUi1C3nXPtgRps1M9 PQr2zh1pQ7JKu5/rc5WgH966dyOm2Klcko4KrxZ3IOekPm65zFIU65fjvSGC g3qzQHITZWsXKpUPvrbgXjlyk90pZa3DSe271LCqUrMHCcdqN7arVKKdAzxy Bn2cVJlclVTdrDRUa8vnqofHp3L6rTIDExBRU65oSMlGkiLhWkZ4bDr5veHD 0CSs6jkffyG2ADkUKfFdxKNJt+9v18EpUHO86b/dtxi100xMFfC4YGFHaeDv abChn+c8zXSeUyo00FPNuR49XPZkUB2Pk4X9Sbp7WalWT2R+tRk0ourhy29/ 4TFoU1zC+Q+s1OKqZVwRU03ot9GTWmL8ZHow8sciNupWwUlh0+ctiC0/aZ4Z HhNcHgqfMWejPjzdsHuzQhtaur2BsgWP21+fGFz/DeeXwwuTgpOJ6ASHrVZi YAGSr5K3f7t6ApZHfH3vvyUVTVyuf+HpUoLObbenpIROgIh3kpjm+wyUW8f2 5GtaBTp/U8aMb/0kRNHPT96in58spp+fjOHbo3IWf//zrMdlWy63oQAdvkeX NKchkRvuKB0tRdoJXZIObu3oSvfE4hXh04AmFRA/fzmSvWy/aXlEJ6Jwj15Z NzUNX/tkJ/+UVSAB0QUbPn3rRseCK9la1GZguWegUbC+JeWZ3TCoeZUixWmT 2d8DWRReoi4QaUORa/I+5iVchcys3OWJ+ZHZc9v3KMH084fc9OfvgyvnGNl8 caH83hhqJ6zWieaGeawh5nvDXpbJtDygKNbP/v4KsmnzWEXMN5OcD1QSEGgw LEgHWrXZfpuYchS31XbGnjoMjvTzeAn083hn6efxRM47jwm9KYNVrMtP9Al1 oj9TKgUXTwyANf1cnDj9XNxO+rm4C/TzZsr082YR9PNmXV5eYTivYYEau1mK UiRIbUlcJxYwDPu4WmS79mXDIuf7JrsFP4O/Z9utl7uGwM1o5gHOa/A/M+9F +Opk4PLYHP7j1wAMIbcbOK/hcYha+735aSClWSN86GE/nBJcYYbzGo4+5r2j 4P4VRmI/ig5J9MFT+nmnevp5px/08075qxoDcV7DK8MjOgfm/QAjyt3Sdws7 gTVvgx/Oa5AVcxu8rVoESrrvl1/R+gVyN8w9cF7DsuBLyie4SuDb8H+vVR+3 wMWNsfdxXsPYMh132cxSGA8t1tFuboSgqglHnNdQ47G1Zt69cpjUCL6+wecn FLvsssV5DV+4+cR+qVSC4WGXlfXOVTDos14V5zPwRcuyE6O5pf+79P3DoHvm dD/Oa5AIXuVHjMpPOCNVtYcgSSok0CS2AFQ8OTYRI626zNtMZxAWsFwRwfkM klTrepzfIGJQ9Ur3yACE0s8pHaGfUyqkn1MqDeixx/kMp9eqchPjF83ttEcX /wD7Ha6LOJ9BnveFGDF27XzzWSu3B55v43+C8xkoPH5axMgTO1LzjtoNsh0i qTivYQ/HYwtiVH93t8GgoBPyArZ14bwGdZaHfsTofHXlQ33LDujTTZIrPJkI KUKjPQmBBcBeN8qlIToCe4R6Sp9tSYU3BgOGOK8h3nxUcUfIMHjw27trvc+A y+871XFew5/5aRwta4fhJ/1cUA79XJAt/VyQ8xVRP2P8/TcHGPxuvtwGW7xv J7qMDIC46e8BylGMn90nmu3d2qHc0GhT7fMB+GEct385fzkMdx6tXBbRCZJe gVklqgNgaejwrq+sAvS8DuZ//NYND1jOSvKN9zPnNZDkNZDkNZDkNZDkNTDy ehP93Isr07mX0OVKDwwK0tFRth1+OK/BwLTc0pZ9Emzo50x86OdMBOnnTOxh 4vLaN2XoOqt/FM5ruDNv1PRh+zR00c97lNDPe+yhn/dgmfx7jsKGfo5CkX6O 4hj9+bsY/bl/Kv35uxn9eX0p/bn/Bfrzeib8Iwb+ma4HxvVM6wNjfab6CIz6 yKQrEENXzO/4GCtW64r4Qr5WieNx50Xe0tIzY3CSai6rebEVud3REtXCo0RY Z8zNZ2xU6XOj96SnnZFE2aPtO3X90bJg8fFLumPgLDscNWZcgYwSNoY/pHSj tpJ2zk/yM3C424dDdtoZ5Obd7VDE12fP94506R4FmuFFK0eHxyAu/DGbU/A1 yv26I+539ih8N9I8OmFcAbfCF+8n1vldXr95D+//4A0x8Na0wMQW7xvk7ect I/af8p9bsVADXr/BL26l8Uu4Dd6X8IhKlwZr2OuPAkvGuzL8vWAv2/y7xPfb bFTxdGz1/+QjYuQjE18hBl8x+VTA8KmY9gOM/TB9LjA+lyk+wIgPUxyAEQem +AMj/pu4L8g7ODxGYpmP5nIJvoY1ZuNd3Df+574A474w1WVg1GUmPAADD1Iv 3IWJOHbfCpgh4upyZJmu3a//wQkwcMKkW4ChW5h0HTB0HVMfgRh9BFO/hhj9 GpPfQmP4LUy+Fo3hazH5tMDwaZn8cGD44UzPsyiM51lMzw0pjOeG9l5GX4ta gtGvdautn009RKUnwsT5CrDeODpyobLlFnrB+8Xm9ZQpCrS46siiNQZCYSzp RD6EbT6Tge8/GhdoCP7v5RjoLeMbw+vACVdNu6dTD0ErNetmi9UoWPeGvcDr wExk1/WXU6bwO8FTbHh4FH5enbOIwEFxRKaKDMZRj+NSrq7gUeb9AMl+gGQ/ wNgP03NnCuO5M9M+Eck+Eck+EWOfTL4ujeHrurW9fHaRNQZ5WdfbadgHoWP7 bm9UfT0OTH0lYvSVF4rSwwge4XMzXXIL5wH3Is1IgTF83206y/A64DxwTUnN Pgiuy6vZRQeOMPvzwPDnU62COvA6YCFrUo7zCTT1AiZq1UeZ5xFjPp324L6v eDRUe3xUxyN6orppkL1qBHTu0mjbcat3ofHU3a3Tr5B9yzFZu9UjzPtBjP2s LLfJDNwRD/dN7LfrUl4iEx5FSfd9I3B1/XI2lTl1qNODr6hnXjYKXZFYH6LI SmXKR8TIR3YelYqUojK06Mnn/C94FP6tNhrfNANfPOctVZ5XhXaYzkjuwqPg 2ZhvOedZqEy8gRi8kfP2Ifsc2huk8ay0sdgyGV1UCPyRxzMOUvbRodObs5Cv hqjb6HgNmvwYL8seOAlw/s2qj+9y0afaV8r8KxrQ1vGUoQWLp0DzQIDvmc0F yN9bTilargm9kNQyars9BbFrid+hO0ZZ8/d35pCY0xJN4r5rpl4QPOlkTMnc byNgXpOJ9r6JUyXm56byyHqN3KAUqUtZ1sTVIY38Hmlinq070P3uuluUuGPn Vb2EG1F3z8Mts+8l2Siw71K7Q+GYL1cSd6kZTSRd3EjMT7CX2kxfdqYcTOcw rIlrRepOD0SJeeWFxr9w3MHcgRKK7wMq904xtjs1CvEWxeceB0ZDdu08kfgF X5HY9NRWluIR0DzZXzX8Ih70rk+OCt7JQ1Tn5Uay+H65zI/wX6ydCffEz+54 212NfFe/khX9OgTF7AqHMvNzQNv2hHC9SD3SUG2b9NUagtVj2bx2Wvnw8Iz4 fdcPjchroMh7c90gyNpIND85Vwh/5orcXI/1RSo6V7rKchCqrw7CZdFiOPxp 7dUv7a3o+gi/o+WCQbh3gqchbNkX+O/KbQs8og7H+OM8JcMgOrkroJbtG6wJ F9PCI6oOXpkl9GMIXHNv72u1+w4KTxc2tth9R6V9lz4cKhiEsBjH/RMypSC3 8woHHtGTZflPbar7oXJF0BvHyxWwS/asNh4Re0pnZmlHH8y9Q5tkf1sNOhJ6 T/GIsie8tBay9oFiR91Bl7Y6OCGs2XS/rQ5Nt+umGAj1gly4w2Guxw0gO38t Px5Res74qSi/3/DjhLtj9pYm2DF3hSIeUelyoxF/th6IHF2guXogDUq2Z3Je /vIO5RjxxDSoDMPN2I2b7xrnwsDEhbhVP2NRzrBi/aLuQdiQuO7+sGkR3Kj5 3XG7LgXZ/786rjysx+yLtwlNBsXYamytpoiSLPM9r7FFtkoM6ltpihaNUIwQ yZJKoaJGkp/SkClMQriV+pakVWgR7dKi9Sttfvf2fV/PM+8896/7PO/zfeq+ 95zP55zzec89wfehLKgDgsYl7JsRXQzeVg/P7GlJRUvNf5L/qN8OX9j7NSvY +zU17P2abS+zfz03rgIUf2bS3jRnIeX3n0KSP7SAw4Q4NTutSijQkbX025mD HvYv/dNHrQnCs9pV+pdWQ6iKqOvn5jw0bXKc00nrBsjbN3/sBVsc70+kr9h/ rwCJdZUFnhF1IKt5ZMTsw/UwaiA62NSjCDXmR5Vq1FRD1sHrlhjvMOlo3qSm EVmgXB/lZx/2iZ/PAJfPMNsDPTHOYZGRkzZZo/V89wts28Et9+8CjHcw1hPu IWtr0i/l2/a28fMu4PIuvyFdVxSexIDhi7n+GO8gUPTK0l7YDaXfjTCWmpkJ 8/orDTDe4XK+rH5HdBdoSEdI372VDVIxLiMx3iG3eqJjnV4XuIl1ku11c8F+ zQ45jHeQkR3WNTKtk493oOAdKHgHCt6Bgneg4B04vD9KDfHdiHn2sM7tj4R3 pZ1qDQ7V4nrkn3tGQZcTUKlbpB3GO4xPumgtduuB0b5XdboikpDHmjrTyd45 YL/1jHpabw/Ey+jLKa0VIbVdVmcw3kFTXTg336sPkpu0Dqe/eIZa3x45jvEO MUVTf7MW90HWqx+7Pda8QO/UzZ5gvIPiivD0LId+cLZReBDskI8yy6sfTCc6 QUyBZ0l+P7hZDBHv1ChEt867J2K8g+N2y2feBgOgYPNmBIk3GU126ST+BFtc v9Hu1ANt3j1yBP/2ywLXxGI+0Dm6aFHLrl5oNvt+oAzjX26dVSPhA+dPuZkv 9/aB7W+RfxD8b+xtjyd8MP33+a+vuvdD9FOb+z0Y/33agZcIH+S8O15+2PEr CFdriw9j/KtJlQ4QPlCojyscpSvFjC9u0yf4X/1KzVYO88HLjvsKe6KkmEKr h24E/+5xvz8lfPC/4BtrTUZLM8v3pL4egvG/bvHbc4QPTjj8PmrUQWnmWlK0 OBPj/7c4mXTCByZjn0RvqJRm/Nh84KwkHwAuH1B1GzMG8wMSRdtNc3t8C/7W cmkaO9AL4pZXpT722Ugtq3HJjxWJ8PrI9eSaTf2w/V7OeswPyO5xtPjY20fQ wgg2Tro7ABu6dA0wPyCzkviXe1tSQRQ/c5n8MCkG2P7zNrb/3ITtP9fZ09pz dlwFOpfreLK0OQvGDplvmbNdmlEs0fq0TasSzXkmsgnYmQOhwoIfSsfLMN77 S973La1GhU+nL2Ca82CHtb5wQrYM0z3udGGobS2ab53i+8e9AnjR+Mzu0gFZ xjVpQbre4XrkW+4qNvMoghVfjT3atOQYo1eiIc/DG6Dd/WTlDMNiZDN7wZea BZVQs7ExMTu8AZVsVrXTMSyGqrcx9YuL/vN74H7P050QpzuVyI4zdwl6jF7r /lpecygWnWufbpRwsBcUEtw/r9cRIZ8XZ5ychXdQ5YRZx1/d6APNCusM56AX aJJPm0PNoftIftfagYaSfpgmH72S6Gt3F2yws8J1+e7V0sE/KXwFPdXwhPU6 r1D0/rJZzsI0FKr4aH2dqhQjYM+5VXLOiDtnXVZ/PsXTnxMXzdNYcqAKFdde 0bKKyEVj3hw0jD0pwyzKul2y0rwGBU1xLPJ/lY+Kb0wxPTFNlnlqrhOwXqcO GeYeVXIWFiKbOa+TLR7JMqvexTBE1yv3DDddWVeEfJ5Pze82l2MKnKZ2WlU0 oKPad4M0XYuRQs3Dv3Q/yDFDYosSPLpTkNlTr1378Opy8+mNhMJeWHWhXeXy FRGa8NBbJRKvdanZM6wS+yDwxGjfDOMc9C7heJYIr3NaNTX3hfTDx3/rCWgJ qycE3LmudzqnCBnmLRvlh9eIwOimplVfwZ3Vn21Z/TmC1Z/Hn60dVqLyDqU/ MtlRitdYJYPPHfOlGSufA9Ye3e+R8iWNyfvw6nLf6uaHEGlmJuO94Mi2KpSx WVPhKF57Fo4zCW2WZng6BuJ0jGDZKc8rsV0/aMWvc8F2nuNn4vREsRe0/33P CHF6i/XWgQWO2K5/BluMN8V29o8fmubX0QszTiXaq2O7xgcHBxE75+pe3svY 9sFNVn/24unPo/+5puqI7eSbXd9J7HZdPqLRhxkAD1a3OS/RbRCn25S/32qs ju10KVtjpxDbzTolaqlyxQBMaCZzSXYLTuRI5pT0rRo+WF8obSNzSTwE30vm yaER8ilG5LniazKX5IAgZIlkTolr6VWDwe+2rE4VydOf92STuSGnBHYbJHNE olvFEp1qcG7IaYGGpM8a3W5dokqeV7H6cydPfz43sf6UkzANqlt1iwg+9IPd 7zitF4PB6GWNOC+BQos6IOcm0xP/ObGq65suncTTpfO2N77QcC2Gmf77Vcg5 7PDfLa6y7wB3VpfW4t3XThElZ2B/A/3Hsz2J38WWZfsO/9IO21m9mmH16pus Xt3N5kvLefeRk6pN4jFvgE7B1MnVh2IhRF28Y3mmGJQ3RSwi9ypnKsaokHuW 6Yby46eEdYHJo+Cp2J9ANCv5r6pD92FXY1a4olMnpI5afozod0LzfMOt+JxS Mq5LPZ/fAZZPU7vwuYBncnsl9i8YGbSpRXtYO38/wO3nAqtvV7D6dgGrb9ct f2ONeQNuyqj2bYnIhWMXcaXo+BEMpvwwAfsfLMw2j8L+CDaqi4OL+uvh6Bfz Qux/MFU5LB37IzjX3HoZEloLeYVn/YhuONSyoh77I2wd6eYy3KgaVOPyluJz h+Zr078jdhCNMm+eW/8etJL/1MN8ASPvJLVi/oBzd+c0LHMTA4o3y8S8AerX pu0mq1XDmG1hZ7rA4tpwIeYLWBga0IH5A3Y57xZ6/d3JtyNQ7AicHWn6dnO8 dgfmDbCJGnqYrK5qp/JUrnwClZBf3mHegLkBwkiyWhtfbVmp1wKLzVrTMW9A 8soHXmSNECVany9o4vsJcH4SuWXjqWpsV4W1BzpwfADPxsmTjOZ95vs/UPwf KP4PnP+/ZfXtLJ6+PdMtwNkJ2wk0U+KJ3SwSa7e6yXby8QIUvACHFx5vAIU3 gMIbQOENoPAGUHgDON7Qptzr5PEtUPgWOL7l8SdQ+BM4/uTFKaDEKeDiFE0P 58X3b3nUava7/CLePYJZbP9DGK8fviBKdOn23hLUl2H86A5e32x5Y7rWQ4rJ u3KCqcL5ymxTh7ckf9myougvx4k90MX2paSxfeBn2L6UlMrpyRE4n3Be5ZtC 8osLx1ObLWf1g//3ZbWbcT7hnh17kOQXB4+Zflgb2A9xRuSehlBQri+5t3Hw 3MNBvXGVPJmT5SBoviGZm7Vs6IjB+mUI20ekyuuj9hqcY3VEYCaZP4p+LPss 6SManGPlLRgnmT+Kii+6aJPnByzIHCsfQdlFyVyrumHKg/WLntTjfsKzYXtn HyXvW6g4rNlf+z/32RF3n52HR8ThsZjtE0vl9S17DEglRGLefBN405+cj+Gs JtewMV0woUuoZIl5c33a0CXkfNpielyu/9PJxyOi4BFxeOTxIaLwIaLwIeL4 8Du2b1DA9gk/YPsGNybvtsT+ASvjL/URfxnYkZ+2eVMbnw8RhQ8RhQ8RhQ8R x4e8OIgocRBR4iCixEFEiYOIi4Pn2X5UJba/N4PtR+XFQUSJg4gSBxElDiJK HESUOIi4OMjbJ3D75NkRKHYEzo48/wfO/3n+DBR/Boo/A+fPPLwDBe9AwTtQ 8A4UvAMF78DhncdvwPEbb34XcPO7eHk7cHk7jw+BwodA4UPg+JCXtwMlbwcu b+fNcwNunhuvngJKPQWUegq4eooXL4ASL4CLF7x6Cij1FFDqKaDUU8DVU7w6 Gih1NFDqaKDU0UCpo4Gro3nx9FufG6+OBkodDZQ6Gih1NFDqaKDU0cDV0b+y 3681ed/Hndjv3UXs93EX9ns37zlwz3l/59t38Ab1Tdsir8QgpU31tlfw6tDj Xmo5rAcKks62njesRVrFWu+D8Xo4PWFiWKAMs6LM/KfqQxdRZtTLbnLfd3eL SC/08hdYvC/JShbvI2bVcm17/H+qRgz9mKH2FQKekXu5awXhf0ju6d6+emAd welOIPd4/QUfR0ru9X6Jkx/s17UwOf2BzEVKTo28RP6+15x6V5vobphiN/Er eZ+YJy8LyXucfL7BRG9yB3xakaSI9w0B804mkfewSzDODFvYDf45JkF43yBK c2XI/j2VHKVOrfzI/z1Qfg/c73n7Acp+gNsP732B8r7AvS/vPIFynsCdJ89e QLEXcPb6P3qjst0= "], {{ {EdgeForm[None], GraphicsGroup3DBox[{Polygon3DBox[CompressedData[" 1:eJw1mgn8V8Maxn/zmzMp2SKyp0WLIlIhknZR2iWiXaQVFSqVlKVSSopKKlvI lr3se8i+5top5Nq7dvf73Gfu59M0z3l/c+bMmfPOuzzvv8bAUd1Hlkul0v6x VOJf6QD+O5TWIZRK9xel0pmpVJrPgEXI+nF9BmMeoB+G/Crk1yA/QeOQP8U9 1yAbAX4SvAg8HHwwYw6jdUb2IGPP4t4F/HY7+DTwdPCt4L7gaeBl4G7gUeDr wd3Bo/Us7j+Hvg1zLgKfDW4NXggeA24FrsX4xTxrAngu8rOQHwFeibwX84zj +j69B3ge+DbwqeCLwfeCh4KvBM/h3mH0h3PvUuRdkJ/J9RLwCeAzwH0Z045+ Z8acDG4LrqL9Ac8BDwD3B3cAVwWfBm4P3gV8HfN0ZR5t/p3ggeCZ4LvBg8Gz wfeAh4Cv0BjuvZT+JO69A3l/5JdwvRrcDzwDPJP3Po3rkxlzF/0g5LOQz0a+ We+J/EBwU9pxzDeQdiy/74r8SvBwcHPwCsb25N6xXB8LbgF+D1ydMWXa04yp yvW7tMfBHRlzNGPe57o9uDn4NfB2tFdpDzGmA/Ijkb+u96e9Q3sMeRX6t2iP gHemf5v2KPhbnrMGfC14C/gefX/w/ax9EHMtBDenP5A57+O3vxjzpPQIeWX6 V2gPglszpiljnpZ+gJuAnwJH2vPaV8aU6Z+j3QEu6F+g3QW+ifEnMX4S1zcz /xT6bshv0R4jnyw5uA/4QvCN4N7g88CTWecROhuMvwH5icjHI7+FeabSd0e+ E/g7+qNoy8Dna7/Bk7jvZO45HtyG/jDuXc9v7cBHgF8Cb0vbQHuAMftwb4l2 H11bxhzOmBd1dpBdQN8ReUT+E60V1731XrTvkR9G34DxdyEfxvhO9LsjHwLu CN4N/BJjLkz+TiXaGzq7wNeQT0P+L67/Cf62tyHfgHxK8jd+BTw1WVdeBk9O /sbf8I7DuX6K8a/TX4z8Q+kU+HLwl+AdaB/THmbMG8inI/9I+gK+BPyZ9AV8 Kfhz6RT4MvAX4H8x/xlc38u979HPRL5J70PbTHsC+TZl6+w94Apl6/jd4FcZ fxHjP+B6utZW+Fy/Tz8L+deyQbxvE9om5L/yrBH89hr4Q/q5jPm39kp7rLMB /oD+CuRbtDbwHPC34B1pn9DW6hMi/4HWUvvJnN/p7IH/Dj5P0u0tyKvTngFv 5PfZzPON9B/ZFukH+E/wN9IDcJn+R9oxmgf5tzqf4D/AX0u3wPPo2zHP8ToT POs6+jFaPvKfaa25PjP4PSohHxq8rorgs4LXuy14VLB+bQceDe4C3gt8Nrgr eG/wSPAJ4D3Bg8BHgrcBDwheVwVwv+D3SPJL4K/oP6UNB3dGvgd4TPC6tgeP CH6/yuBTg9+7kI/gv+OYpD/Xv/O+R0bb6lOC31v+bgfwt7KLtGt05hg/gN8u kX2kPwT50+BrwSPB54F7gmuCLwCfCK4tH8S9Hbn3ZK6vBh8L7gMez5ge9DUY cz64F7gWeAK4N3h/8DPgxeBR4O3A39DvS5sMPgV5PfCl4EHgxuDFzN+Z+Ydy fTnyIfRNkF8GHgw+FHwR+DRwA/BVjG/P+O5cT0Hel74+8qngU8EHgJsx5gDG 3Kn7wXXBt2tecD3wavBLwX57HONfDPb/Y8FfyB6zmUPBv0mnwZ9pzTqntAvA dej3SN7Hdvq+tN1odZHvmfz+9cB7J+vfC8H++RzFJMj3RX69bCxzb5ItkB0G D9D5V4xBX4sxNzGmEbgm+EbtL3j35LikPngf8DKdQea/QfvHvbWRV0uOV1YH 2+/eyG8Pttkn6rsw5s/CursN/dbCvrwC/S+F44BxOQbQt66I7D+Fff8O9H8X PgOV6f8orMeV6H8t7IMb0FdnDcvBu4Bj8refHaxThzHnbcHxSy/wjKxX0s/p wd/2YPCJ7Ekv7j9I/oX+n8L6OitYH5vJzyILybpbRQclWS+3Bf9e2Ac0pN8P +YpsExQTnc3Q5ck+qwLPuV52TnYCfAO4L/dsC16mufUO4GvBXfTO3H8zeCB4 Z+SLwJ20R8hXJPujbZDvRT8y2mdNkO4U1pXz6McXtrm3Mf4fft+dcbeC/wbv Bl4FHsyYXcG3g0+XzoGXgnvqPcFX87zL9B2Z5w7kw6RzWX5p1tWa9FWT461H guMs6fZM+UHFseA1wXHBaeB7g/1/P3ANvV9yrHBfcIzQH/l+8iHJ/rg6eKdk f/9wcOw5mDHrg2Ptc8G7gH+UraKtDY6Rh8i/g5vRdg2O4Toqxi053lb8OCLb E8WMo7Ptmp1ty0PB8fUg8LrgmPH0kuP2Wdm+TQr2A3XB27POvwrb8ar0RbLt SIW/nWzyWMa3QbYf+FzwP+B9Sh7TvbAdU27xu2whuBZjagbbh4MK68bn4PnI +jHmaPA8cJK9BlcrrEuy0fXK9r1vgfcuOxZ4AXwO47fqnIEfA/9adp5yMbib 7IHsj/xi2T56muJY5m8I3rGwbsjm1kZeifaFbA79trQvwXWD/dBmcEvGHso+ PCofiuxx+luQ7xWshzfR/gQ/gXwV+EidRcbfr3cDNwY/Am4Krg++A3wEuCH4 XvmSsuOUV7m3BfJDkK/j+mfmfJj+etm64PUp9hjHmBlaU3D7Wude6yk7nnoe vGfZMdpz4J8Y8xB4Gfgo7juY+dfKp5Yd7zyL/HjkrZLjpFplx2Kv6FyUHVtt 0Jw668k50tLg3KiDfE2wv22pvQ22Dy1oC4L96jEln/HKybnZ1dnPtkJ+CPLa yG/WesAVk/3Z3uDtkvOTW4Pzkp6M3xV5SvZhu4ErJPu8lcF5lWLvKsFxbifa DcE5ZRf5V8bvkJxD7gPePjmHvDE41+yqMfTf0daDlwTnfO1ld2Srkv3xAWXH dO8g/4u+ZrT+1C87Lntbei59phW0/cqOW19C3ljfVd9JdqPsGPZl8HGKAZNj 38XBfr4d8kPpf5Hea6/of9J3BR/LM3vIf2hO+v259xbNJ1tJPxd5w7Jj0vfA DcqOPd8FfykbHK1vByP7UXoAbkT/A20j+GPGzEu+/gQ8P3nc5+Crk9dUjznq RMcGNYLfucjnpkGO4Zpn+Rv5fEmP+Vf6QT4pOG+tQ38g7bd8HuvTPtF7ZZ3X +DYZ62zuEP1sPbdpto0/l2wfhYflZzXO51nr0XneseQ8aHRh/dSzGuXzrzUe ktcpX6c8TbnYB/Qr5T/Ah4N/pz+fNoU5LqIdrXHB69AafqFtLdnuHRZ8Lax4 aTj7tj3rPqWw35St/50xj8lPytYF28r/gJsx7vFs5++mn8CYvuBW+Vm/Zlva X/EWeCOyKtwzQ+ss7HP/AB9T2D/+Bf6aMVUZswB8F7gyuI/ep7B/1Pt9Q7ub Zy1C/hu4mvx8yfvaNO9t82i/LJuj+HlwdByi2HtQtO1VTrcpOt+vk+3/eSXv sfa6Rn7PWtkvKIaUz9Be7Rttu2W3lX9tybmPcrrN0fyD8qBvo22XcsPPwevA b4KPSc6vqtM+pb1Ycs74RTTnUDPvs9aj/PHLaP7haXAz7n2GeyoG64fOtXyA dEi+r0HWJ+mS4pG9g/PNv7M/WJj3/BzajeCAbN/gnFfffUxhu/QnbY/gOFZr qZfXo7Vpv+Qf/2YdfYLzUH3Ts3X2ZM9pVYP5t0Z5nTovUbaG9nrJ56lOnvNM 7htbmCsYQn9uYZ8lXa4WrM/H0LcMPkOtg/VMsbrsWy325+OSz6Wepb1pjKx2 /B818L/v2TzbO+Wpu5f9vcQbHRnMHU1SHEU7iusm0TotfdYZ0BlSzKP7j8o2 ZGo+Xy0znlZ4jHK6r/Sdyj7jsgubsn62zWewZcZ6lx607rT2+Z3a5ffSeiYX XlvT/Jt0+4g8Ruerbd4Tzal5xI/qfZtkPq0r17OY4wpa7+Bv1bTs79UT3Cuf 39n8Piv6fXWmLytb/gT48rL5Uo3VPZ2C+czd0MOFZa+lVV6PxnTOczbOnG2X bOO6ZNvYLPOu3fJ57ZbvrY/s8Mz3dszP0jwvB8fBioG75/3SO3bI+P/71jrv T5O853pWo+h30PobBtu78VnfFGPr+1eTr2Xck8jrgr+ivQmemPVB+iGdVNwu Q79T9Jq0HunRxqxL10bnBdLVSvKZtPvBLbLOSHcUB1UOtkuK8UYWzvEVjygu UX6k2HJUYf5tC237YB9akfn25BlrSvaPC9n//biuwO/bBOu/+Jx/R8dUymEU +yrunSN5YV5DvMoJjKmG/Erwb4U5NeUR4gZPDM7Ne0XHz/ML525ai3InxcGK gTtn/ZE+6KMpflXsOrew39e7in84NTpuX6D9TuYX9Ize+XzdQz+xbB54dtbV k4LzCPXShdO1h2WveabkilVL5jT6yhbre+mesrF0XPHnscG81nfRMadig63R cePDhfN02Zh19HcgnwJeLvshLhq8Fnkd1ryq7FxRPkz+6036pWWP/wx8K3gO eAV4RNm52ObgmHo+eM9g/ybb+LjsZHK8+ynyB+iv0DcNjnmvBD8LXlJ2rrQp ONaeB36Ie/dK/u1J2cnkWP+r4Nj/qpLzTPlF+USNeSraVz4lWxLNVy8H75hc txAPfF50DKl6xPjouE58+zhw25LrAqOj86BVzH0u9/WQzuvblD1GPPP50fH2 E/IvybmB6iZjomNv1Vmujs7vNOaR6DjwMXCj5L14pDCXLv+jnFwxgeKBR+Uf ouMc1V/Ojo7btZ/rovf/R8Y+yBzXaW3IKyXzUHr3scn5z3fBXPtixrwfzDFP z/OPTub03wvmnC7WGQ+OUxTDfBjM/4ufeT04nr0Q/EawjkwGvxucP03LejUq Od59O5i7miqdQb4gOc7+FHxVctz8m+xiYf+4nn5icq3iBfCE5PrBq8F80kTG vBPMgV0Efp4xFyTz7+LBxNkoZ1f+Lo5KnJX4K/FM4kx+CI4jloKf07dLrjFs Deb1l8uGBHP2K0qOIxRPKGZ4RnqSXJ/4PriOsQT5r8F1gJWyacG1D9VKnpWO Jdc2Pg6ujcwqmbsTlyO+7kD5/BwfKi5QrK0Y45Vgzky1sw3B/Jhs7yfB+ets 8EfBeepM8GvBudqkkjnJM6NthWpkw6K5JtXOzormr8Rr9YuuqSl3GxBdb5K9 6pBsa8Rdt4iul6le8E50XUY1iLfBq0vmro+KrqOJyzolmv8U39UnmiMVr3Vy NBcqfkpcgGJR5W5Do+uGyjHPiK4nSoc7JZ+xEM1ryCa/KP+QXPMQB9I/up6o fHNg5ihU73g3upakesd70fUj1RE+jPZNyqF+jI4/PwK3Ts4tD9J3pb1fcm71 U3RuKF39OTofVO3jk+g6Wg29a84Bpdu/ROfj4v+Pjq7lqZ7ycXT9S/r8Wswc RbQPlv/dSb637DhZdZyPomtJOguvR3MX0tUXozkH6fyr0bmJeDf5yDVZ39ZH 8wmqNbSN5vxVb2oXzfmrjtA+2j+q1ql6pHzQdtF8jbga1TQvjeZdVV+bGp2D q742JTpnV912fjR/9SD3XcQaBpZcp1O9Tfm+6sgXR9tM1a+viubWVNudFz1e 3KV8j/xOpej8R7mP6q1zo/k61WHnRHN6qqVeEc31qfa9IJqLWwPeNbnW+xxz zC27bqIa0PfR3JTqs5dEc8iqNU+P5i7ECfeM9uPikI+LrikofmiT7INVr2kZ XYNTPahVdG1O/PPx0XUE1YzaRNdTVPRoHV0fUW19RjRXLM65WzTnL06vR3Rd YBV4l+R6ZKA9W/b5ks15Idq2i6PuHF2nEKfdKbreIT68e3TtQLxx1+g6heKc tsnxweWFc2PF9OKLRkTXN1W3fTjajskfjUn2JeKjHou2h+K+Ho+2h+J2lYvK t6oe+nJ0nU61zg3R9TvVeZ+PrkuqzvtcdC1Sedy45HcTd/dktL8WF/dEtP1U DWJZtE9RneK6aF8j390j2QeLmxZHKb8sPmpUjlvE906LrvWL61sbbecV34mH kk72KVzPFc8xILkW3zCaE54YrXvihCdE1/fFoSu+UWyj+Eo1SOUR4gkfivan 4nlWR8czqtHcHR23qHZzV3RsI47xnui4SOuZmONBceniDQ/NfuPZ6Nqi6gkn RdcUJH8m2qfIDz8Q7YtVJ1oTHf/IP6zKctWR742OH3aJ5koUP6iOoJqN/L5q NLdF+yPVaG6N9iOqfdwQHQMo7hqRHPPpuQ/mNah2syLa/ypWHJkcC4ozvD3a N6lOtDI6HlAtaXl0DCB+8fRojlG839jo+rv0/5RkO6IaQKWcR4h/+yya9xOH MCOZO1C8vSSZ71asfl0yv6x8TnmgYmx9V+VxiqUbRH8/xcbKuZSnKocaWrg2 LT5AfzvxQbRN1t9OvBld79bfS7wVXRc+q3CtXDm9uNmvo/kQ+ZErk/2Hcijl 28qXD4rOK8VFdUW+OJn77gy+Jpkfl1+blOwD9DceG6Nr4hqvuEhch9avvwdS /ieO9Nzov39Qrqd8VPnIIdE5o+oppxb++xNxEopfVKcRZyQ+RHUacVuqrVwe bfP19wyvRPsR2dLTk22o1qm/Kfqs5Prd0ugYQ3W6JdHxmPZwdXKeJp/4//xM e6C8UvugfbszOefUnuhvX5TrKB+5KZnLqxvNWypnFZcoTk48nWyXvmnX/F43 JnNkyh9V9+qX4+dbkjky7YP+zkm5mjhD1clUw9DZX5mc56g22DG6Pqi6lPi+ m/O5653lNZLrm1qX9HZIPo+6t0O0HdC5uzk6NlONTJyd+Lr/Aif6haw= "]], Polygon3DBox[CompressedData[" 1:eJwtmnfgV9Mfxs8993w0VEQqKU17U1LKLjRIQlFJhRAllJGGzAqlNKwolR3Z Cdl7i6KszJD9s/V7Xt/n/HG/n/Occ+/93vEez/t53+YDh/U8I4YQbtefpN/f 9adrGUI9jQ/WXH+Ny0oIVxUhtNXcZK2fILyj5g/V3BT9DhZ+UOMBWr9KeKDw /cL9ha8WHiT8gPDxwm8K3yW8uX4XCl+h3wHC92i9t/A04ZOFHxUeJPyb/t+h mttE4066nms0Pknrj2h9oOamCp8o/JDwCcKXCx8vfLfwMcL/0/FdNLepxp11 /KUa99P6nVo/SnOXCfcXvkv4aOFvtP/F2joL76n9R2tbzLlY1/aW9j9f+/+t 8W3a/xjhIzmv8K7CLYT/Ff5E42rck/B6ne8yjXfT3ECNF+r4upr/W7i38Fzh 03XMj8IPav424U31e4Xw4fr9S/uM0fHbCDcQ/lPj+Rqv19ZHOGj/yzW3u4an at97hD/U+SLPXOtJ+GqN99L6QuEFwhtzH8LH6rcQvkLrewifILyB8FTh9sIn Jb+v1zAS3rHWK8JTNG6nqcFav124Hvct/JTmd9G4m357aftD692EN9PaIdFj 5s7XWivNjeT56fjrhA8S7ij8ndYHFLbBucJbav194YuEbxJuJPy28BjhG4Qb Cr8pPFr4RuHNhd8SvlD4euEGwm8IXyB8i3AT4feExwvfLNxYeLnwOOFbhZsJ rxS+WPgs4Z7CM4T3F35SeDfh/wnfIrxMeHfh34Xncv/Cewj/ITxPeLHw9sJf C08TnifcVHiF8ATsT/daX/j1wu/jXq1vK/yl8NTga+Maz+Te9fy+0v7NNfeB 1i/RXAetfau5/oVt/FrhU7T+mPCJwtOFhwgvER4sPEP4VOGlwicJzxQ+Tfhx 4ZOFj9e5hgo/ITwkOBYQE84Tbin8jPAdWq+v31lcr+ZraPwTtkQc0biF1j/S /MRsb7fqulcXtudRwr20fr1wJ+GLhY8Tvl34SOG9hdfq//Ut7PN3CW+l9U+F rxS+U7iV8CfCk4UXCW8j/AWxSPgS4b7Cd2B/wncItxT+WHiScA/8TucfK7yt 8BHC/wiPE95OuK/Gt2r/C3TNPwvXZUys0/h8za3UeJzmksb3au494QuFC+G7 hVcIjxUuhRdxPTpfG4130PzB+h9f4df4t+ae1Pr7wmOEo/A9wl8LT8SfhJcJ b6zx+Zo7ROPzNPeOxqM196/OdUewrWKz5+ArWv9c40vxb42Xau5t4QuE/9H+ t3MOXc8F2trhm8IfaH281iva/z7h2hXbPLZ+pua+1PhyzW2i8RPER+FJwpsJ PyW8fel7O0Tn+1L4dJ17pta30vpbwr9o7RrhZsKvCu+K/2g7LP//XzWepvXm Wn9NuF7FOYFccLnmLtf5ZkQf013HfK/fyeQPzT1P/tDvzprrorXTyBcaT9d6 C82/TvwXvla4pfAbwptofJHmjtB4nOZ+13iG5lpp/Kbmuun/zcK/hT9jH+GJ 2nro/L8KH6X9b+J9EyeIz1q7Tvgvnr3wR6Xjb2P9PiRcR+OzNT5A4xHR5z1L 5/o6+PzELmLY6RrP1toXGl9GftD4cfYRvkS4tvAS4bbCe5a+V55HK+KPtsM1 rqmtJ3FY1zRe4+21TxvhnUpfO/cwMTpGE5vJ38sKn+8I/bbRNpRz5Xy/V/5/ vDPeFfvsUfqd8675n9/ofNtoa65x0vakxn/pd4HW/9O2EflKc6N4F8GxmJg8 VONZmj9S4/90vRfpmB2CYzsxfhixW+tHa20O/qG574NjOzH+DI2vi46dxFDy zczo97AVMajw+yDWE/NHaDwnOpYQU8gdtwn30rE3am69xt8GxxZiDLljYXQs I6aRO+YLf6zxRZqrqfHDmvtU+GLhWsKPCn8iPEF4Q+FHgmMPMYjctCD6+fG+ SKfEA3IbOe4scpEmtyb+a2urtR0L2/ey/G66ars0x5M+vAtt+2rfdZo7UeP6 +EP2l9d4f4VzDTnnbHJfdFy7T/P7FI5vx2Z/GKDxWK2NwBY0d63W99Pc88Kt hf/L8YbcRI4iF98dzW/gP6O03kJz7SuOUez7lub3Fn5X+E5iUfR7nKB9dwp+ n7OEZ1dsJ9jHqfi58GTsUvgU4W7Ck3gGwVwFzgJ3OFrn60tc1dxorW8dzFcP rZgvEd/3gQtpbjGxTvt3rDjmEetWRucOcghc4C7hvTTerjT/68kzhPuUzu2v aL0fsU5zF2Y+1o7cXTrXv0pM13wt4V+4dm0naTwwmv/BzwYTq3TMJZkvVtda w9Jc7gFt+2l8oNYHa716ME/8UOPLgvniI8L3R+dX8tk9+ALPOPOXDeGSpbnZ adlO/tPv2mB7qVmxj+Pbp2LDGg+vOD+Tr+F+cEB8sb/WT9S4a8X8Fv4K3+0s PFK4ebDfnI0dB/sPz3JY5lM8U7j7Qdrn2JzPefYdc/4gv8Fd4bAtia3RXBmb wpZ6CdfS+hmluejQ6HfJO62f88++FcdIYuMn0dfGNfJsewrvX3HOYt+vo2sZ bATbOE74eG3TdG0dhdcFczk4HVzt8ehj98/5jPwAt4PjTdf4iWguCCe8Rnip cKeKOTu20TX62fEM8aUThHfK/G2b0v49Uvhcba1z/sQ2sJF9NR6AX+V13t3G wbaHDeIbfbS+qnCt8A/5Mtj2uT9qtWOjuT81QBW3EW4j/ILwDcLPRvs2Pn69 8DPRPL+Gtgd5Nzr3t4W5HrF8ZrBvt8/5iHjXVuNXS3Phl6N9BZ/ZIPMJ1tpm fgFfwlfwmWrRPsm74x02EX5JeMeKbRzbfoDnJfxoaa73oPCucNPS3PgxeJXw /aW58L3RXBvODXdfJLyd8H2lufY9wi1L12dfCNcoHJuIUXVyft1Z4yWlueZD 0bUONQ+5tJ/wHzyrius86rtqFfs4vj1I69WFTy5dSw2O9ucf9P6GaN8GwVzu GHJcYU5HriZnb0E+ja5VqVnPzfEU7gCHWFiYsxCridkLMt6HvKj9BxauscYL 99H6fOEe5Jjsf/hrs+A6c67G3YLrzWfJDdr/O83NDq41TsdGCtcc+C81+Kjs 79wr9zyzMEfsJPyr1kcINw72VXz25sKcmWfBM5lVmAPBLWvn6+f6xgn3hsMK Hx6c++rwP4NzYAXf0m8H4R+CuTqcvZHGh0VzeTj95sLdo9817/yrwj55pnAP 4emFfeo54aej+TN8GFvCpn4Tvjm41sZ/G2rcLdq2sLFvCvv8ucJHwdmEOwdz DfjNmmDOcZ7w0XAUjQ8Otl1s+IfCPoZtYWM/FvbBr7OegsbQT/ggcofmhhe2 iYdzvP8+vx98Ax9ZJ3xdcKwn5s/J9kRsr5nti/+/v/CPOt+phe/pZ40P5Bhy TbRtYqPkmo7CDbRtIVxo/2c095LGI3W+n4VvCq7NqNFK3k90LCGmrC+c47FF bHIDjdvn/EH+m5H5xE9aP4BrJHZHcyvqQ+pfOFZruCTHF9ZQ4IZwRGyrR/S7 IcYOyfcDz0HL+CuY72CL2GRt4QOi/QXOjz40AJvBH/DZ7I88G55RDXwpWvtB AyJf1dXc1prbkvsVflv4FY3P1fG/ZnvBfs6quP4kJvFsecZnFLbRpcJnan2N 8NXB984zGFrYZokH1HjoX+hV6ChrNZ4RrKdQe1KDLipcE2Eb2Egt3i01gsYj tP554foX7QQNRVOhXbQ2gEaAtrdXdG1FjUV9T71/fq4HeXbn5Xh9XvYHYvrz 2V/WZft9WXiU1n8RnpP96ZyK7RN7HCR8s3DS7y7BsYiYhPY3JlqXaggvLKxP /ai1q7VP4xz/RwvPq1hT6BNc65JzyDVvRut9m5GzdOxwza0jVgs3whaDa2lq amqn5dGxjRiHVrcsutaFgywTXhFdq1OzU9u+JzxB400193BhPXFY5oc82zu1 vqB0vfe3xpfm91Em2yc+y/97OlkbIabiO/gQ2sDz0doBGkJV7R9tKzHZ17EZ uBg+j68vjraVItmWsBneNe+cZ/9otO1hg9jiEuE55BKemfYdG1z7owFQi7yh 9Ykaz6+Yo6LvoPfAweHexNzDhGcL/x4c09AKlyT718b52H7J/JZznKnxccm1 xKaFbQMbQct4IdpX8Bm0kBejbQsbgwu8JDxMxzZIrgXq4KMa75xcu/0ZXBt0 T74WagT4UHv9fhXMmahtqf+pjahxT9P4MB1zZWEOhFaLZkut9rr+3xk6fqNk rlqLGKz1Kcn8GJ5MbT9N+LvgGh/bxsbJFU9F5/4eyfwBDjBc42OSc2ndfP/P JcdKfITjn0l+n/gI/rAwOdeRo8nltyXnQnJilTadrF2hUQ/T/7gFPqXfLiFr W8laGRoXuXOB8GHBObRK+07WstHA0dbQ2AYKX6TrP0fjjfif1DfBXGR+cq4g Z7TT+iTh7sLzCmuJDyVrh2iKaIcPJ2uLaIho9Q8knx/NHu3wi+TYUqUhCj+Y rOWjQaI1PpKsPaI5Dixd35f63TtkLT5Zm0eTr+oNJMdGYiT29Hyy/ROD4Spw lnHCN0b7/6vJ/hazvb2Q7B/ENGIxMZn380i0vz2RrE1SA+HvS5PPtzz727Lk 2E2MPU7HRs1N1Lh1sP89lRwfyAFwg3nJ2iYcoVdpfYGEuWO2xxeTex/0EPDP l5LjExpdd/gEMVnjrXL8eznZ/uAsaI1ojmh770bXftSAXN8dOZ69lux/ZY53 byT7WyXHn9eT/RENEy3jzWStCk0D7eKtZH9BwyAW90nWd4nJPTWuJGtX3wRr fWh+5OtmWh/EueBjhWuSE7g34QaFY8ixwheSkwufs7/wJHJS4ZhCPrpOuH5h jXKI8GrhLQtzEq4XDQbtb1W+XjQXYv/qaH+AU9J7ujDHa2ouai00qKH4vuaa Fc7pZ2PLJEeNm2i7W8efnPy/4EGLhE9L3hceAFejB0Y/qKovVMmcXqc4N/pZ UCNQG/BM4IJVnFDro7R+FL4JPykcY44UPgQ+VjgGnSN8SnJubFq4d0YPDb1r cnSvixxI7rsqWqtBsyGeDIvuVcCxiSfDo7kvHJj4QKOP2EiMhLsOidb64Iz4 /ynR8QUNHX+dEG3PVZxXeGS0dl+l4XOt0fGKnhrx4eJo/6WnRny4JDoekGPI LbVL+zMchPhwWXS8omdHPLg0undIDxE9dFJ0b5EeI3rgldHxhh4het7U6PhE zwN9a1p0vKHngZ52TXS8occxUvja6PhFDwS9fDrPT9f2p3D1wjF9DPap7dlg jgLf/bt0b4WeBFoymvJHxJ9obRuN+0Phn4SnCP8kvFJ4XTQ3gaO8J/yt8FXC Pwi/L/xdtFaNZr2afCE8Ai6WrPU0LMyN4EgryB/RWjma+Srhn6O1cDTx5cJr o7VsNO2PiXfRWj0aBtrFV9G9BXoMaOFfRvci6EmglX8R3Xt8PNl30RXQ/ukB oM1/Hq11onm+KPxRtFaNZo22v0a4qcajk58dPA/tmhofbvdx5tf0RNA+0dha a21yaf0erRotF80fbRtNF34OeYUrU8NQr6wvzf2pAdA+0UCr8b54vsn+ibbd u3A98l9pbZQaGT78T+neIj0z+PK/pWtneo5w/79Ka1XUAFzblcnn4hrpPdOD pjaekv8f632DYwL3Q78AfRWddYLG47lG6p/C+i2aD1oPPRP0Wnoy6Ov0RMbk /EuvmXOepfF+ybVAo8L2yfNFa+9APEzuUcB99s2Y/3dc8DWMzfbMvh0Lx4/F ybXQQznfjy1de47O/rcoGdPDh0vOyfHmhuh+5LbJ2h75kdpzi+RanxoUPXWP 5FqIfIj+AMeCW1FPoe9vk8xN6eGiJ7dOrtXpea4qHYOJvU8H18p7a/3G4Jp5 a/hN6eP5ZoFat1Fy7Qt/ofZvk6zfoQG8qH33JP9q37v0s4vGj2nuKo0fju4H 7J6M6TFSW7dLrnWoeajd2yfX6tTwaAFtha8N1gTQm/ZM1gbo8dYQHlKaG5wY Xb/WSc799DjoR2yXrJ/Tg0Z7Olj4sWANin7A9sl6FT3v5TpXB81tFL0P3A0O dyC2obkHSn9PsEnpa0J7aZzMFdFgKATrJutRfCNAr72q5y58drQW10nr9wdr ctSiTZNrTfgWtf0Byc+OGp9nyTPlfTwXrU1tmcwl0ajox7RMruWp6en3tEru f9CDR/skH1M70cNGS+ycrL2hKaLFdEiuPeFr9Dd3TNb36MnT/9k6uX9Djx/9 tWOyPk9PHu3xoGRtEQ0S7fHAZC0S/kO/bavk/g7fDNAf2SFZL6Qnj/5TM1kf poeArWFznxW2EbTrQ5L1ZDRstLENkrU6NDL6Pbsm65X0nNHyqiXr21WantZ3 SdY30fA7l+43/q5zNQnWd2ck9zLoMdCP2i1Zj6TnjXaBhsF6l+jefPXkfgg9 evTE2sn6PT1AuCqcFS55THR8ob9dszTHR9/cLFlf55sO9OJ6yf0DvhlBL980 uV9ATxDtr2GylocGOLz09yvV9LtPcH9mk2T755sStL/Nk+0VDRB9f+NkvZSe CP2G+sncn29O3tB57qy4J4JNovVck6zVEO/R96cna5lomvRK0K9Y75D5zQ3J +jg1IPzmxuRakOuHH92crEWhSeGr+OzswteIXj87uX9AzwO9sVay/ss3AvSm rk/uRdGjojdFj+og4ZOi9cgNk/V2vjGAn81J1h7pqaFFNU/WFoi/8LObkp8d GiW+js/jb+9EfytTI/n98c0MvYiuyb11ehIHZL7xMvEpujdyaHLspEeCtt4l eR2Nndqie86Hh0b3C2Ym9yuwd3pp9NS4v95a3094TenY82l0f2JWsrZDD4v+ wf7J2h89QrTdJsnaNPUs9TQ9c/Y/gvqzcF0N920azBe+0/ZucC+ZWpeaF3tA ++Xe4FRcO/dArTgw11L0EtFi4Phwe3q/6AXoGWgbf0Tz97U5lzQp3ZunR/9c sBaFVjUo2y69IHLPqmx7jUrXbtRw+Ca9rrW5JqAW4B3A5eB0W0RzInwZn64T 3OuHH36i5/FK8DcQfEvFN3DUW/RayI3kSOz5wMwHP0vmWy0yf/wwud5plPnW 8uT6r27mmx8l8yueEXxxdfK1NM58c1VyfbRF5osfJN8/31DcUlhbQFvvGswX VybrY8Q3+N97yXoa34CgvVF/YL9Xw+cKa330znYO1kf+yM/mn8xXP03mh80z /1yRrH/Vy/zz/WT9jW9ipgr/rOM/EP4xmm+vSeanfMPBGvs0jX6mfIvEN0nU 009mvvlOsl5IPuFbGL6JYd/Pou0Jn9kpmqMTa4g5twZ/W/d06e/ZNstz8GG+ yUPPuy8615JzyV/0ZvENfGTLbJ/w47eT9Ta+CaB+uze5HuUbSLTXFsn2iT6C 1ojmSP4cn+ud+5L1Ur6ppB+5T3J/mW/M0IKbJWujaMJwGTjNT4VzMv3JfZOv nW/Q0MNTsv3So+Hens5coV6O3cNzLqA3hN7HN1voIfOi69dbk+tFehrU+18m 1xPEH+IhPftOwidH64NojFzfhqX1AzRd+Ej10vXj3OR4yTdg1CufJ9cjfIND biJHwX35VuH/xupAiw== "]], Polygon3DBox[CompressedData[" 1:eJwt1wf4luMaAPB/X4tClHK0Ix2UQnRQSpNKRRRaWlrSIuuUdjppSXsvoqXS XjRoT21pKNWxMg9HHfzu873X1X19z/1777fve99n/ou17Fy/UyojI2OjyCr6 Z87ImJMlI6MfXJkpI6Ml+04+XFRgbdgzYri6RWwo2yTvpO51Np8NZGuijs1k t7JpbBt7gbVnE1lbNpFVYwPYXNafrWKtWAP5W+JR1p+VDlM3itVnA1gZNoPd wqayrex5NogtYK+ztawNm85uZlPYFtaNXe6hJ7A2bAIbLx6TjxBVWXd5EXUD 3TuPDWCrWWvW2L3vsT7sXfae+Ke6IuwVNlVeU10L+Soxkx1jg1gPdUXZq2wa q8X6sHdZL7aUPc2msBJsQvKeO7O8vveD+I1sM/tETFX3dzaRfSzvou4FVoh1 ZWNZFfZw8rzPsMHsjXg3yf83nC2Xr4jvcW9B1pG9KS/v3sHsBjaIvc+eYs+5 dyWblEr/jvg9b6lbykYm/RHveRRbFv2ZjIPoo5FsCXsz6Y+ubBIrzsaxDew5 VldeR/zGPmTt2WR1N7HxbGMy/gokv2Uy288+jb5k09nzqXTfRh+Pdu9yNopt T8bkGLaCjWY7WHfWWv6AeFv7vyyvml7iHdZT3QesqWvN5E1FTtcWskbsmHZN dlRd9qhl3dg01kX+trp6bCh7n72RPG9H1p0VZt3YOFaV5UnGWt9Uun+in7qo m8JiAs+U11E3LH4DG5K8l3h/LeX3iDHaX7HcahrJnxKXaU9nteM9a49ktd3b k5WI547+EbVYjxjfYoS6xWxYMtZiTD4pf0Lcr/0Wy66mq5jKOqubxerGeGH5 WQc2nN3L2rHrWWv2L3YX68QKsGfZCHYf68eKsd5sNqvPXmFvs5fZfNaQvcxm sZfYPNaAvcRmshfZXPY4681ms9fYEtaMvchmsO5sTowflisZQy+k0nM85nq7 WL9EfvWXxf3qOmhPYu3kk9RUZ7VZdlaDNWPXsoby62I9jTnAMqs5Inazw+qu jXHu2hl2gJ2WF42xyr5kB9kZebEYq+ww28UOyfOIdWwP28J2yXOIZWwDq8TW yf8d84DtZVvZbpYz5j87xHayg/LcsX6yXawa2y7/1b0zWU/vZTv7NDYQkUl8 pu4hdkQ7m1js0j62je2RXxHjl51lh9iX8hvETvaA/28/+0JeRBSO9U1dZbZR +4LvnRR9pG4T+5j9wH4Ua9R9xFayn+RT1C1l69hi9g0bx1rJ14pF7Gs2lu1U V5VtY/9hM1iF5Nn2s6tFrli31H3CtmhnFgvUbWFV2Cb59+6dzE6xT9kJVjDW NradbWZb5Vli/WTH2R52TH59zCV2ku1jx+UF4vnZCbaXfS7PH+ssa8v+xlrJ B/nesmw/q8H2sj/YXHaAPcj2sT/ZPNYm1n/xjvbv7Ho1HeTtxdLYE+N3s5Xi XrZEfkLdENdWs/JsGTvFhrFV7L64l51kQ1lX7+9Dtpx9wU6LX9WdZUVjHosT 6sr7/F2UU3eLT/8ymqhpLB6Ovd19OeC5WId9vshKxF4nxoov+ZU+r0quTfR5 Ixvr/yuTOb2ens+SXmejPZiX0q7HSsf5gH3mOy7GnOMV2Grts2ykax+x+9ka di72tlibPNtq9l4qvcfEXrNQXVk2jx2U91W3mN3NFrDDrD9bzyrGGGTn2Sg2 i5Vk05P9KPaeJewfbCE7ygay+exO9i7bx3qxuez26Eu2h/VkH8T7ZO+zI2wA m8fuYLPZXvYaW8TuYvPZIdYvI/2OS7EZyT4Y73QOKxPvn+1mPViZpH9XpNLz L+bhWnXr2Sr2c5xJ1G1lH7PNLBVrNKvI/hdjS/60umysljybuuqsCcvDqsd4 YJVZZ3Ylq8ZSsS+z59gVrAbLwqqwruwqVpVlYpXYsywnu59dEvewppnS590L 8s/VfctKxntgVVw4wb6Xlxa3xbqg7gz7RbusOK7ue3acfRdjKvo4zsrsGPtG fmuMBfYt+4x9HWNcHGA/spPshxin0cfxvTH4WUV5+xj38RxZ02fv8qxVnDtj 75LnErfFniiPSVMiGZNzUum5FnNuN6/OdrDf5LPiTMPGsxZsNKsUayIbx5qz Uawiq8T+iHnNWsR+Hku87xit7slU+twY58c3k3d1IVmvY92u7L4/Y95ot1Vz uXubxnxV14gNZeXYAraGzWVn2PCY+2xMnE3YEHZ3nFnlWUXhONPGOhJ9qm5y rFnak1kN135hp9nP7E7xOfuJnWI/ym+P/Yk9HusFe0Tezb2FWCN2DWvAXmHF 2WPsSlaPdWEF2aMsJ6vDOrL8rD67gtVlnViBGKdZ0+emmqn030vxd1PHOM+I QuqvS6X/5jqnfZidld8odrFyyf72SbKnxt56Ps4I7Jx28ZiHeBPbyNbLL8W5 JH5fPJe4xErEOsE2qtvAPpJfVDeb/cy+YD+xO8Qx9gjLEeuuvEPsC6wxy80a slfZTewbdpR9xW4W+1kddjl7SN5SXT52mtViJ9lVYnXsq+xirG3yxpn+P9wz vpLX1jjP8okN7Cl2NXtc/rK6G9nTLE/sDawXu4W1YHlZU9aHlYzxEmcy9iBr Hud21pxdy5qw3uxW9mAynp9Ipc+1cb5tqS4fa8b6ykupG5icS04l54A4DxxU t4Md0L5GrFH3F5wtABQ= "]]}]}, {}, {}, {}}, {{}, {}, {}, { Line3DBox[{347, 567, 1258, 348, 581, 1269, 375, 595, 390, 1355, 609, 405, 1361, 623, 420, 1368, 637, 435, 1378, 651, 450, 664, 1303, 463, 677, 1314, 478, 691, 493, 1397, 705, 508, 1403, 719, 523, 1411, 733, 538, 1421, 747, 553}], Line3DBox[{349, 568, 1259, 350, 582, 1270, 376, 596, 1279, 391, 610, 406, 1362, 624, 421, 1369, 638, 436, 1379, 652, 451, 665, 1304, 464, 678, 1315, 479, 692, 1324, 494, 706, 509, 1404, 720, 524, 1412, 734, 539, 1422, 748, 554}], Line3DBox[{351, 569, 1260, 352, 583, 1271, 377, 597, 1280, 392, 611, 1287, 407, 625, 1293, 422, 1370, 639, 437, 1380, 653, 452, 666, 1305, 465, 679, 1316, 480, 693, 1325, 495, 707, 1332, 510, 721, 1338, 525, 1413, 735, 540, 1423, 749, 555}], Line3DBox[{353, 570, 1261, 354, 584, 1272, 378, 598, 1281, 393, 612, 1288, 408, 626, 1294, 423, 640, 1298, 438, 1381, 654, 453, 667, 1306, 466, 680, 1317, 481, 694, 1326, 496, 708, 1333, 511, 722, 1339, 526, 736, 1343, 541, 1424, 750, 556}], Line3DBox[{355, 571, 1262, 357, 585, 1273, 379, 599, 1282, 394, 613, 1289, 409, 627, 1295, 424, 641, 1299, 439, 655, 1301, 454, 668, 1307, 467, 681, 1318, 482, 695, 1327, 497, 709, 1334, 512, 723, 1340, 527, 737, 1344, 542, 751, 1346, 557}], Line3DBox[{359, 573, 1263, 360, 1349, 587, 381, 1352, 601, 396, 1357, 615, 411, 1364, 629, 426, 1372, 643, 441, 1383, 657, 456, 670, 1308, 469, 1391, 683, 484, 1394, 697, 499, 1399, 711, 514, 1406, 725, 529, 1415, 739, 544, 1426, 753, 559}], Line3DBox[{361, 574, 1264, 362, 588, 1274, 382, 1353, 602, 397, 1358, 616, 412, 1365, 630, 427, 1373, 644, 442, 1384, 658, 457, 671, 1309, 470, 684, 1319, 485, 1395, 698, 500, 1400, 712, 515, 1407, 726, 530, 1416, 740, 545, 1427, 754, 560}], Line3DBox[{363, 575, 1265, 364, 589, 1275, 383, 603, 1283, 398, 1359, 617, 413, 1366, 631, 428, 1374, 645, 443, 1385, 659, 458, 672, 1310, 471, 685, 1320, 486, 699, 1328, 501, 1401, 713, 516, 1408, 727, 531, 1417, 741, 546, 1428, 755, 561}], Line3DBox[{365, 576, 1266, 366, 590, 1276, 384, 604, 1284, 399, 618, 1290, 414, 1367, 632, 429, 1375, 646, 444, 1386, 660, 459, 673, 1311, 472, 686, 1321, 487, 700, 1329, 502, 714, 1335, 517, 1409, 728, 532, 1418, 742, 547, 1429, 756, 562}], Line3DBox[{367, 577, 1267, 368, 591, 1277, 385, 605, 1285, 400, 619, 1291, 415, 633, 1296, 430, 1376, 647, 445, 1387, 661, 460, 674, 1312, 473, 687, 1322, 488, 701, 1330, 503, 715, 1336, 518, 729, 1341, 533, 1419, 743, 548, 1430, 757, 563}], Line3DBox[{369, 578, 1268, 370, 592, 1278, 386, 606, 1286, 401, 620, 1292, 416, 634, 1297, 431, 648, 1300, 446, 1388, 781, 782, 808, 806, 807, 1313, 474, 688, 1323, 489, 702, 1331, 504, 716, 1337, 519, 730, 1342, 534, 744, 1345, 549, 1431, 800, 801, 564}], Line3DBox[{371, 758, 1432, 759, 372, 767, 1437, 768, 387, 770, 1439, 771, 402, 773, 1441, 774, 417, 776, 1443, 777, 432, 779, 1445, 780, 447, 760, 1433, 783, 761, 805, 762, 1434, 763, 475, 785, 1447, 786, 490, 788, 1449, 789, 505, 791, 1451, 792, 520, 794, 1453, 795, 535, 797, 1455, 798, 550, 764, 1435, 802, 765, 803}], Line3DBox[{551, 745, 799, 536, 731, 1454, 796, 521, 717, 1452, 793, 506, 703, 1450, 790, 491, 689, 1448, 787, 476, 675, 1446, 784, 461, 662, 817, 816, 823, 822, 448, 649, 814, 813, 821, 820, 433, 635, 1444, 778, 418, 621, 1442, 775, 403, 607, 1440, 772, 388, 593, 1438, 769, 373, 579, 1436, 766, 345, 565, 811, 810, 819, 818, 804}], Line3DBox[{552, 746, 1420, 537, 732, 1410, 522, 718, 1402, 507, 704, 1396, 492, 690, 1392, 477, 676, 462, 1302, 663, 815, 449, 650, 812, 1377, 434, 636, 825, 419, 622, 1360, 404, 608, 1354, 389, 594, 1350, 374, 580, 346, 1257, 566, 809, 824}], Line3DBox[{558, 752, 1425, 543, 738, 1414, 528, 724, 1405, 513, 710, 1398, 498, 696, 1393, 483, 682, 1390, 468, 669, 1389, 455, 656, 1382, 440, 642, 1371, 425, 628, 1363, 410, 614, 1356, 395, 600, 1351, 380, 586, 1348, 358, 572, 1347, 356}]}, { Line3DBox[{826, 1143, 1144, 1142, 1158, 565, 1157, 1156, 1257, 1018, 827, 1258, 1019, 828, 1259, 1020, 829, 1260, 1021, 830, 1261, 1022, 831, 1262, 1167, 1347, 832, 1263, 1023, 833, 1264, 1024, 834, 1265, 1025, 835, 1266, 1026, 836, 1267, 1027, 837, 1268, 1028, 838, 1432, 1100, 1029, 1106}], Line3DBox[{840, 1107, 1168, 1436, 839, 580, 841, 1269, 1030, 842, 1270, 1031, 843, 1271, 1032, 844, 1272, 1033, 845, 1273, 1169, 1348, 846, 1170, 1349, 847, 1274, 1034, 848, 1275, 1035, 849, 1276, 1036, 850, 1277, 1037, 851, 1278, 1038, 852, 1437, 1108, 1039, 1134}], Line3DBox[{854, 1109, 1171, 1438, 853, 1172, 1350, 855, 595, 856, 1279, 1040, 857, 1280, 1041, 858, 1281, 1042, 859, 1282, 1173, 1351, 860, 1174, 1352, 861, 1175, 1353, 862, 1283, 1043, 863, 1284, 1044, 864, 1285, 1045, 865, 1286, 1046, 866, 1439, 1110, 1047, 1135}], Line3DBox[{271, 238, 1440, 867, 1176, 1354, 868, 1177, 1355, 869, 610, 870, 1287, 1048, 871, 1288, 1049, 872, 1289, 1178, 1356, 873, 1179, 1357, 874, 1180, 1358, 875, 1181, 1359, 876, 1290, 1050, 877, 1291, 1051, 878, 1292, 1052, 879, 1441, 239, 272}], Line3DBox[{893, 1114, 1113, 1443, 892, 1056, 1297, 891, 1055, 1296, 890, 1367, 1189, 889, 1366, 1188, 888, 1365, 1187, 887, 1364, 1186, 886, 1363, 1185, 1295, 885, 1054, 1294, 884, 1053, 1293, 883, 1362, 1184, 882, 1361, 1183, 881, 1360, 1182, 880, 1442, 1112, 1111, 1136}], Line3DBox[{907, 1118, 1117, 1445, 906, 1058, 1300, 905, 1376, 1198, 904, 1375, 1197, 903, 1374, 1196, 902, 1373, 1195, 901, 1372, 1194, 900, 1371, 1193, 1299, 899, 1057, 1298, 898, 1370, 1192, 897, 1369, 1191, 896, 1368, 1190, 895, 825, 1163, 894, 1444, 1116, 1115, 1137}], Line3DBox[{106, 309, 448, 107, 340, 449, 108, 450, 109, 451, 110, 452, 111, 453, 112, 454, 455, 113, 456, 114, 457, 115, 458, 116, 459, 117, 460, 118, 808, 311, 119, 805, 290, 120}], Line3DBox[{921, 1102, 1101, 1433, 920, 1119, 1388, 1253, 919, 1387, 1208, 918, 1386, 1207, 917, 1385, 1206, 916, 1384, 1205, 915, 1383, 1204, 914, 1382, 1203, 1301, 913, 1381, 1202, 912, 1380, 1201, 911, 1379, 1200, 910, 1378, 1199, 909, 1256, 1377, 1164, 1166, 1165, 908, 820, 1162, 1152, 1154, 1153, 1155}], Line3DBox[{922, 1146, 1147, 1145, 1161, 662, 1160, 1159, 1302, 1059, 923, 1303, 1060, 924, 1304, 1061, 925, 1305, 1062, 926, 1306, 1063, 927, 1307, 1209, 1389, 928, 1308, 1064, 929, 1309, 1065, 930, 1310, 1066, 931, 1311, 1067, 932, 1312, 1068, 933, 1255, 1313, 1069, 934, 1434, 1103, 1070, 1120}], Line3DBox[{936, 1121, 1210, 1446, 935, 676, 937, 1314, 1071, 938, 1315, 1072, 939, 1316, 1073, 940, 1317, 1074, 941, 1318, 1211, 1390, 942, 1212, 1391, 943, 1319, 1075, 944, 1320, 1076, 945, 1321, 1077, 946, 1322, 1078, 947, 1323, 1079, 948, 1447, 1122, 1080, 1138}], Line3DBox[{950, 1123, 1213, 1448, 949, 1214, 1392, 951, 691, 952, 1324, 1081, 953, 1325, 1082, 954, 1326, 1083, 955, 1327, 1215, 1393, 956, 1216, 1394, 957, 1217, 1395, 958, 1328, 1084, 959, 1329, 1085, 960, 1330, 1086, 961, 1331, 1087, 962, 1449, 1124, 1088, 1139}], Line3DBox[{283, 254, 1450, 963, 1218, 1396, 964, 1219, 1397, 965, 706, 966, 1332, 1089, 967, 1333, 1090, 968, 1334, 1220, 1398, 969, 1221, 1399, 970, 1222, 1400, 971, 1223, 1401, 972, 1335, 1091, 973, 1336, 1092, 974, 1337, 1093, 975, 1451, 255, 284}], Line3DBox[{989, 1128, 1127, 1453, 988, 1097, 1342, 987, 1096, 1341, 986, 1409, 1231, 985, 1408, 1230, 984, 1407, 1229, 983, 1406, 1228, 982, 1405, 1227, 1340, 981, 1095, 1339, 980, 1094, 1338, 979, 1404, 1226, 978, 1403, 1225, 977, 1402, 1224, 976, 1452, 1126, 1125, 1140}], Line3DBox[{1003, 1132, 1131, 1455, 1002, 1099, 1345, 1001, 1419, 1241, 1000, 1418, 1240, 999, 1417, 1239, 998, 1416, 1238, 997, 1415, 1237, 996, 1414, 1236, 1344, 995, 1098, 1343, 994, 1413, 1235, 993, 1412, 1234, 992, 1411, 1233, 991, 1410, 1232, 990, 1454, 1130, 1129, 1141}], Line3DBox[{1017, 1105, 1104, 1435, 1016, 1133, 1431, 1254, 1015, 1430, 1252, 1014, 1429, 1251, 1013, 1428, 1250, 1012, 1427, 1249, 1011, 1426, 1248, 1010, 1425, 1247, 1346, 1009, 1424, 1246, 1008, 1423, 1245, 1007, 1422, 1244, 1006, 1421, 1243, 1005, 1420, 1242, 1004, 799, 1148, 1150, 1149, 1151}]}}}, VertexNormals->CompressedData[" 1:eJxcvHk0ld/7/48mKpGhUlSGUCpURHG2IUMaTBlCCpmnQhFRypRCKMqQWaYM mVPnLlOGEpmFcAznICk0ou++Tl6f9+/XX62111773p77eZ7XY1/3veI3d9ax ZGJgYMhbwcCwDP97q2ndqRu7aKhJVvqx+PqHpJVDvtqfqyhIoMOX+eleGpIQ kym2eraX5P/80KOHZApqqXpqdeowDa2UvNlmE3aQtNj9qfliLgXV7Ru6n6pF Q/l81rrLS3XJV5m0jjBEUtC6gJ6vLM40xNys/KBp0oRszMUocdGegiwz/Zi3 R9OQburj0RyJ82S2Xxo3r0lTkOcvibXV9TTUZ03qcrhqT/Ylld7R+jqESGMS r3YxjyMJzVcv+A0ukbfzLPyQjhtCO4NiN644NY7MAj4FeQpdJ//hZ9p2VGII GS4I25HzxlF83DEJsbAActOK4JDkjEHk84rFbHjrBLKrJ4fdKLpLNo6zUmGY H0AWd0TnitIn0HRq+4v+4odk2Ze2q/dvGUANhRql6OQk2jk10uVMTSFv+7B/ dG9PH3ofSIT7bPmEPrmstJY2ySczcAmrcEf3oNcxLBy3Vk2hTF57LddzFeSB WSOPBN4O5HZ3C98wPw09iK76wyzsjsLuJek/aaKgNz5Nclv20FDaiQ+sk+La hIVplu2jlxTUfPT3vfoDNFRxk/Xnk9MXCQ/L+VuFJRTkzbX4cp8iDW3dEVwp 1HaTiLyfbn00nYIGxC+r5mjT0OJ7MwGW5RGEl5SS1oMwCvo6MdKxxZKG9Bmb 2Nu+xBFZt/SZVrvic1FyuV5zhYbc2ybzpe+kERJZMeOntSnoeGPb6IoQGsp+ yilv6pFLJC63WVkjRkG/vo1tXoihIaPC3lMsRBGRlcylr7GcgnqYpruOPKKh tkrtyzfsKgj+kbCJz31DaG/z2pLFMBq66XLs0LfUV8RPl/tZPc+H0Bq3t7YT NjRU/KJ6hE2olrigWOYYnjaEXtiP1nQK0dAhLb6bydyNhNKu0XnHh0NoqLdj YEsDFV1qH/E0lG4mFN5uM/ILHkIrP2WykV2pyPjQTvKV862E5eOhdi7ZIaTm 2at7W4eGHL25ORql/AmuBL6w91iHNe0P6sJ20tDFD92en/T1COGZa/v4ayjo SoCew01hGrL7E9r+UfkS8VIuZ6ajjoJCtFIdKrfTkHNKDu1DbSCRNuqd7PSO gg5X+Cfob6Shw+vXcP+Yvkc07+L4frWbgm5xLIgxsdDQjhtjP4aFE4lvIhd8 Xo5R0OOZmwtnZqnowS+WZP++dCLQSYB13W8KYrG2c2DqoiLnpxfehbvkEvzP /OUOcg2jsOVzPCVPqUh/5677MqcLCQEbySuf9g8jspvIloc3qUit/UmuQEEp YRzGeDbDaBitfR7TKqVBRVYXpOrjBJ4TVC3Ll4lBw+j7k86A3SupSM7dXG30 6Eui6kHcan7yMPKbest7qngMtb2+qvvDp5JgKhC5sHNhGF03an7JdHwMXRcM EP/cWE0kyF3L/aM5gpSXR+ZVRo+iH4hT4GbGa8Jt5ZTL+YERxJ3ybq2MEw35 K/Y+PejmRvx52/LN0IGCAu3lkshYz5wPR/0Zp5SIRx1i7WVYz+oXnmc8ttDQ 24MNb5xzzAkUyuq30EFB3aW8q18y05CFg2yMxG03ovR14otLUxR0o1B2VfEU FTnpnHIpKfYlUkTq/+SsG0bsEto6wW/x35XEkyiVFEysfK1ZuOLgMIoUH++/ lUZFbjZfg6/pRBBz3c8eEVbDKNBRs5fbnYq6P/5Y1pIbTRhyNTAwxA+jy4OF mx4rUdFFznGVzQfjifw/XVs+dA2jhesCnfXM+LnrA94zmCURlqVB+md4RlC+ 0u7+rQ1j6EkFc7IOVyoxWBUjG3ZmBKWyvqFdDRxDg4zy334+SCeQ/Brns6kj SNOjYCJLaQxtXV88GBCTQfjWlRvwTY6gZyzXHJwZx5DmQOBV/+4M4uK9E/xK EqOI5bj/2KfOUdRmcHy3xvtkQjzeOqzv3CiSYhW+Ii5CQyWfLYpz3ogTPd3y bTuxnvGNz2NA59yrgheGPymh9UEX+kBnLs+8s6BzYrkEn0uOORIvUvAFnb83 J64BnY/klHrsv+2GmnyeVIDOe77cXw0618Vo/ikr9kVbGtx/g84CW3j0QOfg gRPdMknByNggOQ90PuPY/BF0/kPbvPKGTgSK2rghHnT+eGP3IOhsLbuBvS03 Gh1UFvr1J24YycVe5AWdE0ziNLYejEfmbBs2gM7xDFM9oPN3Za1xJrMkVEK+ qgU6v/ffSAGd35wKCdDjSkVNeTaSoHNtR9Ak6Dxs4/p7/kE66l+k2YDOcZNC n0FntfFvBbdiMtBlVqoW6My2s8UCdO5sWHslqDsD9bDPCYPOpyPGn4POL8g/ jI69T0bfXUbLQefk3MkvdrhO8dgbza+/GIE2TTy988qGgi7e8qiB3FDimPs8 qa+H7HI8pSE3pH9ddITcuFj8baxP+RIS/qTxFXLDVzXZBXLDVEa+sK82EFX0 vIqB3JiVnU+G3ODNvuOMcwPtLH74FXKj3OWZJOTGct/BqBHhRMRMK70MufEs pG+FKc6NjbI/xQL60tHXDxuYIDc0PUIuQ25c3mwtHuGSiwp1bMUhN9JrVEUg N/i+dRyQPV2ILFT8rSA3LJl3iUBuhIYKvhAsKEXPTRKOQW7cl5IagtywGQ99 Ei/wHEU6H86C3JjQEroHueE74/cW5wZSWJ04ux3nBn+yhijkxlg666GfPpVo aIOXPuQG32qrZsgNpcMeQdON1agnwCEIcmP9U5tyyA2+ziaGgIzXiOMF70HI jas/D/KeT6Kil1z7jCSqCoksmvqkk9owup3oIwt18HfJg8xKcW0kum7SEeqg 4fLrEVAHvzl/HEo/fRFlximGQB38LuhWDXWwtK4hF9dBpLBcygLq4OFcaTWo g+7nlkWuWh6BnjGmaUIdfJLv/AHqoIFnQ1XrlzhkqRowz4LrYEO03y2og+W9 m2kH7qQhFq/EAaiD/u92zUEdTP20L+GMRy6qilKbrcZ18FD5w71QBzdoFJQz E0Wof78UCeqguWD6F6iDy8YRN66DaFBJ+g3UQeaMG61QB7VWcjLiOoiGayr9 oQ46ydTfgTq4/TX3FK6D6J6KkzzUwV3y2yahDppH1qXhOoiW3+OohTp4k9bH zYvroJHbL3tcB1Fb69UNUAfVijf5Qh1kN6OOeJxvRZV/pNyhDqa1/OW6rEJB h7UMKiSWJa4TXeK6+CuRwT3MqiTvJa7rWuI66nSEHo1TlTSzxHUh0yXRwHUP umYeE0HyJKvGL4rAdVT/v1w3fsjnjqiiKil8ieu69vxeA1xnJ998t56mSFKS zPUBrvNd18MKXPfp5ZXTbBtIpPvZbsHAdbv3BVYC11neS9nzLm8PiePE1u/A dZWBf7musC1par33bhKz4F+u2/xSwAa4rnNF6g+unl1kO/Gou8B1Tbc6zwLX Hcgu+FpgtpukH6WpBlzHHfKX61aJ3eGIl9lIFqn+y3WHSv9ynUzP9MyolhI5 ifqX6zrcdCKA61qFbr+QmjMmu7CmKAHXfes4tx64zlhEm4s18zQ5rnHaC7ju eVxmr74ZDXmWnw2/ci+VkDSuSndzoSD9or9+9rS9mIX9TLyYnaD72X1aPBr8 nKb4Y7IQc90Xd+5A8PNDhcEq8PMhloBeQcx1vOv/0P08rZOnAX7eO/t612rM dX3TIRrg5yviz3vBz+dlzzYC1xlzuPwCP1NfTN8GP+vNRs5IYa5Ts1PpBT87 CLnOgp8V3GTUsJ8JA+m6OfBz+AE9up+pR/PSsZ+JSethup8Dhhanwc9F6e69 vpjrNG0tmsDPbxSZ28DPnatUtgHXXY5UuQl+Xr4sm+5n9sFwCnDd7wNnSeDn Ll0+up+tY0+lAtcJLj9I9/MdyR66nz2s0l2A6+wvruUGP8+mm9D9nDR7qgv7 mVBzcfcEPzck+UxDPi/vnYnG+Uyou2eFQj7vdnpcDfm8Oe+CPw1zne1z/4OQ zzdNW+0hn52bWaR7MddZqpjNQj6veBxzEfK5L5pvJ85nwjJmcxzkc2iE8mPI 577sitCfmOtsz45MQj6PMu+n5/PAWUF/nM+Ex6ML7pDPReOM9HxuD1Njw/lM /GTUWAb5LLIs1QPyWbTutRvOZ8Lsmd1uyOcKlQfCkM/KROpOnM/ENm9/a8hn SQFdej6vlawgcD4TTxrM6PnsKrtiEPJ5xqstBucz4ZTDkgP5fIsxLgryeeGR 1QBwnYR45zTks8+4jwjkc5ClxAGcz0TiUKEB5PORIpsmyGf5mgBPnM+Eyy+X 25DPK5BYGeQzP0vrD3/MdYfLp2Qgn2sG6zyANzgczknkvxFH3ceK6Lyh3/Dr IfDGBauQpKFPSkSnqnU/8IbIUR06b7TqHx69iLluqKOEzhvGa6zovPFQOt8a 8wZxJeo7nTd4lPtYgDcchMRHMG8QWW9M54E3uBY3agNvMHR6HMe8QdgVRxcB b3imUIaAN8RHTQ9h3iDk9HUfAm94ctX3AW/wSSR1tWKuW1cquwi84TghQ+cN Tgd+NcwbhD46TeeNkA0sdN5IaomkYN4gyKyB2sAbiuajQ8AbZi93+WPeID4U JtJ5wzapdgp440nSzOoFzHXc87ZWwBsMnP6TwBv6Wr6JmDeIW77VusAb17tS 6bwxuuGTO+YNwkJFSAR4Q9F7ks4ba/1XGGPeIPhch+m8IeKruUH2DhXtvnin dt/OQOLlhC3NJmAYaR0piwSdx3eMaQxiruNNNhkFnS98ZjEFnTNz5PgvYK6z Zza8CTrn1GTS+fmh1KYqzM+oe3bqOegck/CCzs9jHIt+mJ+RkqAQnZ95Xwlq gc623X66mJ/R+1VMJaBzj1scnetsbeuiMD+j5tYBOtetMFxN1/k25yQb5mf0 4C31D+icYZK+EXS222AqhfkZ6V/cxAc6F55qaAedY85Y1mF+Rim8PIags9Ce pwOgc32YfBHmZ3TV7Zk06DxFFhkHnYf4S39gfkbz31KdQOc7I+/GQecL1l0f MD+jQ0V5hqCztGKSPehcz0C9jPkZnWqTFQCd2xM2jYDO12/v4MX8jJRrpsJB Z+cpByf5V1QUJR86SX4QQ4QdfPGlSWkYbdlwsxFyw+vJ2+yfmOu29tXuhdxI 2VlkCbnR68U30oW5jlJ/cB5yg038ijPkhtHoZUvgOu7v9Y8gNwTeH6Fznfhv s7fAdZWNNjOQG2dfZe6F3LCOjtcBrjOXbfCE3FjmmTsP98H9VsIB+D6Isr8d Xwe5UZ4T7wi5MbxJ5zu+DyI19reHIDd+PeHeDLkhkqoUje+DiNuVkX4ffK6z iw9yo0xI5B2+D6LBI4vGkBsBmgxtkBt83u7v8H0QSfQ2EJAbo/se+kNuiLn3 yQPXbVvvvxbug89492+B3Ag4lamG74Oo3/ORC+TG+o7eSsgNP2JQHt8HEdsr s2zIDeLG26eQG0/MeqXxfRBJN0s4QW78LnPeBv0NTYeF90zC7sTEsgZd6G+s aVI5TOc6j0/KHzDXcQYn20MdLLwrcx/q4AzJPyUXc11vYTa9v3G9J4ve3yBP Wh0Drqtm57GBOlgy/ofe31CRVrrFgrkuGHnQuU5ZvqoT6mA+SeElroNovcYs A/Q3NN7yXYM6+EYreas05rpTrYuTUAcftY/R+xvXAvepmmKuO7hDgd7fSBtm 3QJ1sEnN/CwL5rrn6YV6UAcFXmh2Qx3siGqJAq4LYtIehzq4THsjvb+hL5It B1zXYWRB72/8eiBnB3XwSLXbWnbMdX5NinZQB48+WFkLdTDIISIWuO516/Vf UAf33Wun9zci7u/3Bq6zfJh4Gurg5Oen9P5GmbrJ8yuY6+IktTugDu5595fr tB615S+cjiL/16/bvsR1i00iBw8zHSQHLXHdpyWuMw99cMr36XFS1xLXFSz1 6zJnd39onNpLerjUr2Nd6te1sT5xOCNqQjqzxHWGS/06u0PmvrsmTUjCS/06 x6V+HYdB9/RzynlS3FK/7tBSv26O3X2ivNuVtGepXyey1K+LTOnhSXrkQ2IT +Mt1Bkv9OqWtolbNqn6k+aV+XfBSv27Uupe2gj+MFLrUryta6tetOBk0ZZkY RWpf6tclFv3luv0LGQy/JpJIi71/ue5m8N9+nWHTLY2vxk9IIxv/9uvikv/2 63ii2Vx7S8pI3vN/+3WMZ0S3GGH/KPJVcsW+aCOuabxLkDUeQOJnl1vC+Fa2 kQk8jpKJSKoMHq+eGbOC8d7+190w/23auQkYDzfN5oZxmVUWR2E+k01ONKzT IVFh4SqG74l7eLUcVwsSdudvHXteiTlZwGE6G4+b7ZvnsB4zIkLea5U54/EG wyrd3WGfULnsr+d1/MVk6TI5M+rNLrRvpK5y1hxzSB03z5WGLuLkKW21ozED SNrt+50X2CdxoRZJnWekCL3GqWcp2Cd965TjI2vHkNzhFCVT6wYi9OO18BXn hhFpwdvtA87DO0qa83LbJAlTu4HUqmoKov1yT9JYN4Z02YeMB/LIRDdxgEPr wwja/pF97DKe76qjMPhRdjNpB/NhsjLOzynnmIlzD0aRGxL59sv0Kum2stpQ V8Yocr/+4zSs37C9WI5vqySSykyvhfV/d3tVwfobestH8frI2VxtQhOv39Pc nwj799ddc6vvrBT63BySBPvP2mQeDvvvOLpc+ax1A3oe9iAY9i8xUW0Fei5u 6Ls9s0YQHdXMVAM93zwrkja4OI4MzL30hG3eIoO2GXFZtwHE5/Wm5+mmcdSl PyFV4NyCKFznD7zXH0BZzAVjoKeKcZmMV0MX8o8VU1XHevJfOUFfX4ulLTN+ jSAhXquoDut7lHZMwvxlew3Y8XwibDH3BMyPNc/zgf1/OKj087SJFDH5TOgt 7D87WPEu7D+cJ1QC7584zm4TAvtvObf5JuhDsqo//xzrXx+sEgH6eH6IqQR9 okdvDID+1ASDSdBn9ZL+wjJ0/ckKS/oPLul/6q/+5IdL+m+/8s4U1md0+bLD HOtfmXL1Jaw/UT+XCuvzqka4gf5PFH6zwvl2mn+Og/1/9jBr88L6xx6NSIf9 C8XHPYL9e6wgDLF/ULe8QCjsX5tRxAz02chekxTBLIgQZ9tJ0KclpvYL+Jl3 xUBywJgRKnp2pwT8LKIQMaqPz+VNxQ1hEXwuI9XmD+FcSozmg+BciK1d8nAu 0Upfi+BcVHdxloPOhdpKltjnaO03IVnwue2Zv78Lao56bg9TIanwxd/fRXJr 22wIfm6gGWGw/fR5Mqfda+8Y/NzT2oJfORlpSOyLgP7W6LtIwGvHsoBv+J61 vjt+W/4Y/jvXRZF66wnpta9DJf2HUf+8d5AVru/n46vUeFbZIEFBFz6+Xgq6 P5aQUT0/iqyXnbxEWnhJPHBAEsd6RlCJsrnrpttUZHpKIjos6Aj5/SqldZG4 /g4pbfnoqDSKUqMqGE1m/Ej3WTI5TyyMIq55C1vSVyranvHreHuoL2G5pnFE fTWu42HJg7B+i0CeHF4fWais+q6B1w89vz3BVJaKfF5Q0qvqigm+xcgi0Yph dPlCmSvsf/m9jVaotx5xFq3Ig/0Hq67OvriMhpbJxj4/su8xcfeE4lgd5hB5 7spMGD8z8spcZd9jtG0TLxXGKec8Xqmfxud+OzPjSXskkXpv3vmoPwWRmbjc YP0MgQZ7vD6xkW9nLqxfsj3QBva/rF8wHO8ftcn1jML+p4+a98P+t5/2kAR9 htHiL9h/a79NnMZdGuKWER14iJTJqwWkj0Qh7NslfVL+6kOOWtLnQeuHW6D/ tzV3wjeusiH8pJ9tAf133qnMhPVDbslcAX0kf/XuBf1lUz/MwvnuCj6gyhd9 l2Bvnvvjj8/XL0Odfr62GzhC8PmiHZ8E7sL+zy/5JOctT7HWPimy3ZJPzE9p 0X1FxAelRPIZkqWW21iAr0SMdnCIPp5A949afIhvfo/kyzTICYI9yC9cVFQE j385V3QoCY9Lt6wST8LjHz++F4DxtLKI83icMB9xF4HxAXVhNlgn8NLYV7wO IXFuzTNY57UGaeOmxk+I5e7aFY82l5GjmvMjnhl1olKal46QNV4nc8PieZN2 dOCyy1tFmW5UndshKYjH5/SsG23wOLvjfS9lPB5tezq4Cv9+b1w9m/bVZ4Zs c8VBPQ7/fi/6PxKD+Se9WefwfCImWt8V5vev/yIFOcl/hckR5yQx5BWyF36P NWV9WvBctTOTzJZ4frrBiUZ47rU122/D+rf4fQV+Bc6QPlk5q8H667T/7v+k dM1MfGIxSb/z7/6N08TKnHH+PBjKKOnWsEGbZebn5HFeqZxyPFiD11Gb+xB+ m3yAvJC8TzgGr8O0NO7leUJBKMGapJLyd7yIafOiKD6vQku/9JwdksQ2gcs/ NuPx9/4hcSV4fkb9U6EbJ9cQpMqZFzl4/Alr6Tc4X9uVWbd4VqqSiJ1mXnC+ d7l3B8D+p8hfnn46NUO6UEM+AftP3NTbzJY/iYw72levskDkTYuGxZuMe5EL 5/cFeG5cu5RkMH5u6sYU+nNXT5+Nhee2CWbmvcLPNat0JeC5W2Nm6H/vka9+ XnUaNgSictD/3l2rmxh24nXIZZx+AsKS6N3eZXOwjnzwbBasc7lfIcjbdg2a jozJhnXIEw1T1/D9bqJgxeykcjxhcP/D3F0aBQ0xDtB1oHhZ9hXskER/Rq58 h3WCpv7u57RLZw7eDzpe/Xc/auHjkZaiOA/P8TlmXzpL5NQ+VHlYS0FxSzrY H/QoxDqQzZZ0CCQu3XXZT0MW0gIsrNmpxPfDZl/zn+B67SsURcbzUwPWHb7C uIyQXjMSlYzn+4wqR8D473jdxIEZJvSmqT0Wxt0034TDePj24wK3vjIRFmJO cTDuzrfu3sI+Guqz8og8F69HfFlhum5LOa4L9hd6VTHHdqTqjgVtViYKmrNL +QkKYqHtzDbcTUOn8vpdz74jEQwuf3qjX2H+VxCkr1N1MWhQK14PpWur0ddJ O23QB+vYn67jidisjIhavxJYh1vsa/RbvM6ooHpR6wphlJG3U3IZXidJMCAS 1inidQ1VwvuR+8XJBuv89Bmg74fI0ki4ivcjmMJH349YX1ce7Gc1urersZlE nBta7ID9CCtcugfrZ6Vkva7+s4O4b5ksBetnPatIhfnMAutq9zaRULS9zAjM dzfvj4T5M433sz/i+YfvmEvDfPGH0yJfsf5eRgOxqvq6pAdvBj1GSino6bxG JEUCcwXfQc/IEhJx+SL/szcVFHR8aX5r1L7dR6zlSZeX5usJd9yF+ckheY8O FZOIwojjL2B+wk/zGzfxcwu72zw3bbJBVt4Dszr4ucWfZOt08fyv/vbSRrYW SPXe+41ezylouXuPTaw4DQ3rFIYLeumhtBiHBYcXFLS5NKzxEV5nd4tRY/Tk MeJOOClNHq8zusdm6iPWc3mYWpLfbgfiuH5pjTjWU7s3lClLHd+/HvXfHpY9 QlZw7Q89EU9Bd2yljkbIYZ3v3mnv1LhG7J/uSLmcQ0Fz3MM/+8/SkMeO093T 2oZko7LQdNI1CpKyvUT1OUpDOpc0/XZP3SaiEhQb52MoaF9i7KZtPjT0aK1Q 3dG4c+QXGSSdRAOsw3cngg3XNdcOh4fH+KKId5EN+d/8KEhn98kf3SmYB1w/ O2QvsyLHsD6xu74Dn2Pjs2JrOxpy+Hoz8r18IjFtYXO71I6CdpwV8UxsoaH0 jWb25eaO5Lyz5dUPxv73fcKef75PyJFuKD12lYY6jbsudWSmE9HFcsLk4/97 z/74n/fsVckH5JI1xtGxw/oWneM+5KdWZ5s65YfQzep72+wf0lAtZZ1Cy7oi 4tNBXU5jFswh/nFm6x+Oo0HLxx5PZ/3I+ymJH0sbBhHX9IlDg/E0NMu0gYPz ZTnB5nhjuhPvM22bu3TZ3Dj++yK+DxiEkLlbCo+xyw8ijmVdmRuiaEi1v0kq WOwlwdp8dPRt/RAyfOmvXWgxgVSPhx+hSN0nN2usYNxxZwAdEqUc8Pamoeto /rD2SBUxZif2+nvBEOqZSN+8cmwC1cbGx6YzJpAr/GtMvfU+IvuXtZ8j8X1T gW/bz9o/r4m1r9a/oyQNoYfze1Orb04iaa33urJbH5MtKmtlM9b0IUbdoP3q bDSk9LmQL8fhDaHKe7YyKGoIvQtjv6Mh+wmFzVb184cWkA+ne1hwcPagDzfu tsq/pCLH+mnR53HNBLmrhofZdwi5koqKnuPf7+U9Glt+TFsQ53aGf/bF9+Ix HYcxdREa+iNmYmKofpGo0s09P/Ea+/xW0o+vAjS0b1V9MEv3DYJ87IvE/BsK Ghjq2MvHS0Pj3J+p8nZ3CSf25tkbbRR0oyCwnY2Dhp4vljZ83P+QMOXbzjTe T0HUGU2zOcxXh74Vqia1JRGOKqwWWZPYPzJM7NRpKuIR0Cg83PyY8Egfcjmy +L/vARz++R7Aocr/7ZVSKgo/FBJ6sv0pseVILttaiWHU0Rwrei+Mis5KzXUY xJYQtrON14S0h9GTzrggpnNUNJ99+JGJxzNi9Zx/YoL7MOpsav1wQ5SK2N5W asUak4nUOfHc9JRhdJxaVb6XOobEfc88Y976ihDoudCxtmMY3R3b4qwXO4Yu rbqIvDiqCNNW50tiHCPo8TDt4qjUGLq2Ub+LIlJD/FQ44OtsPoK0KprGX+F8 4PX5oXHshg7B1MYeJ4fzwW5VgOCxrTgn8zNO254zJbZwah53bKUgs2s/xOvx +co9qv2mZ3CBKLqr2JM9QkGSvBHulb+pKDGXK9ngtxchsYatLBrr86VH1EZr iIqKn1x4zbbOn9hSyH6lkw/vPzojJaqKiqqj5eOlBUKI5QFNpxeVhpGfNde1 6gR8XxjfV82+GEEEJOrIhzn+73uAzn++BxB8w/AUHaWiuf6PZL6AOCLSdf+0 Tcswmngwzqq/kYr4ZK+ee5qXSPSENa/SZBlBcfcNAisGx5DhsWfkXetTiLjz rZ+5j4yg3WFZQ58yxpDDrJ5IlX4aoVBC2HD5jqAr9+wcGx3H0EKq1o/s048J ppC0d2bECEr3d//ltG8MZQ3XZxplZRC/kd5VmYURVIXUsjUx38Zslj+RtymD 4OubvWApPYqexsrXvhGmoeOmhmv98TUraiGF+XEdBV3nDaHrfOtbnDjWGW3f pUrXefoyIQk6s9ykSRgaXED1EgudoHOOHpMn6Nxgq/XI+LcXSnw1WQQ6v1I/ aQ86Kxxddp9jnT/a47rgBjo/EfyVBjpPqbxQOSQQgswmU/VB57pmj+ugc9pF T23OxQjkuZP1MOg8sPQ9gNXS9wAyS98DFCdRikFno8c3UvkD4tBvEb1x0Fms /el60Hl+/aRLUV4iuvSzgxF0bm3oug06p4d66+9Zn4JuHrhIBZ39q66Pgs6N VrK8tfppaOFntBnobFlndwF0vjnxhJZ7+jH6xKFYDzo/yKTRddY6Iex/JisD 1V/O8ACd99nbPQKdlU9tYn+6KQMt91HxAp1PfM92uIzrl1CDo97R1/bIyVZq aymuX+40D3putK31GtRXv4jW+aTQc6Og9+085Aa7muzx1d030MeIh2KQG3yh YfshN9bZRwaR7O6iLyFFU5AbHYy93ZAbozZ1Vwb2P0QnjrjM03BuhCkWWkNu JG3N/ohzA6frNSPIDQ9a5CbIjX3pPw/KNT9Gjiz3rCE3/vsewPWf7wE031/q gdy4e1ttu2b7UyRqUrqwBueGIs/vA5Abge8q6w1jS9Ck1SMHyI2OBpkoyI1c XZOIMx7P0Eea2W3IjVTNNzTIDQWNLUfjjMmoy2/7A8gNRapbLeSGbEnZeZat r5BIIz8BuUGZzPKC3Ljh/VjpKkcV4qEWGkJu6A5NXYfcSN6w23xEpAaFf71j CLkxe+9IPfDDwvcWY6PJY8hhv0QG8IOXjUVYGNb/95nX06fW2SPezCvLHmD9 rxVd0gBOSJMI52rXuIbyHp5IBk54wXR7HHiAzLV6YtfUbZTfWlwHPKBgmPQK 6v6j77M3NPii0C8hlAt1/yaXUQXU91nNtOW4viOerzf9oL7bW4W8gnrNukqj tS0zHWUuO7IF6nXA0vcASUvfA1QvfQ8gax+9D+rynTGr3OZ1RWjwqei8Ea7L NWxvtKH+ViT7JXO8LEe6yqytUH8/yfjVQJ0d3dD+55bYS5T+2LcK6mzX50N6 UE+lyh8J4nqKdmwviIN62n92Jdc9XDf9/c6sef3nNXLlMoqDumm7YHAG6mN8 K68Ero9ojwUpCOqj4uWnbCRcB5cL3mbAdRD1rLB5vwrXQYMOfU7aHhrq7Sw1 2MWsSqo7dX3wIebY22x5ZSkH8fozvsy1Fkqk3IvuC2KFmD8di5YBp10Mp72T uqFIEmI+HwKcJhP09hfwWFjE1Lv6G0qk+6OmacBjoSfHeYC7NC9xGDgnHiE1 hvprAXeJiWr9Br5qr2Z2FdqnSHr+Kc0K+IpzrsYLOOqwQoal8V45kq/ozUrg qP++B3D553sASrgpnYuskckBv5TdpAffBOhcRNhuOAf8Y5iRZt3BvJksxU0d BP4ZHv5+ADgnofaJQ8GTdaScXWtOAudsvT+tBTyTIocyp2vYSUzS83Sesf30 l1tUzr9YdDGVJPuH/eWWi5Gr6f6clgm31sN8WxrqSfdnqJjCZ+DbL08J8yDM t3orHlUD39470noM/Pl2zvNLF+ZYpUduieBP8gvmSfBn+INynj2YV2vKo2vB n4zGStXgz51uKX7HMZcWP1HOAn9GW848B38OG27LAv4sfDXoC/6UK75dBf58 csaxoB3zpN+x+I3gT8el9/vyS+/3DZfe7xfyqdL9KR6n+gD7k7ihPkP35wov Gbo/t/KJumJ/Er3KnW3gz2KHPLo/bfbzMQMH3n3dVgn+3LTehO7PG0+s9wDv iRr0xYI/x6e/cYI/C6SUl2N/EuscGePBn4bBxnR/ViWZ7wN+a1hkpPsz/Vk2 3Z+jao+XA6c5Dvm1gD/3n6m1h7y9yWvrovbanlA3ObMN8pbxMuso5O2l5nOW epjTorouW0HeOnwJ+Q15+2TbrVTgtNYnsnsgb/US9ktB3r5ZnT6H85b4yBE8 CXl72lu7F/J2xmNm2yDmNMmzgj8hb7X8N9Dz9kibeCNwWrOhvjHk7ZcVm+h5 W5p8WwTnLWEtomQDefvf+/0d/7zf3xm2lZ63MuHNm3HeEu7R0ouQt8d+T9Hz loih1uG8JVZ15dPzNmDtrfuQt7IaCYE4b4njVXZ3IG8f97qMQ94yKKTo4Lwl Cnx2REPeupcXvIa8pVVqO+G8JU5vl3kBectZEOEJeeu6WH0I5y3Rz3rOCPKW xZblGuSt/bKfp3DeEubvHIwhb88dCKoBfrg1yZ/tK4gIkafBLMAPBU820Plh ca1Rig3mNFGHXjo/bKl0p/MD97tvWzA/EEKvDbqAHypeBV0BfpA2zPHC/EBY OPoXAz+cTDS2BX4wW/ioifmBWPXOzh34oS6xgs5p2fZy32Qxp6XK29E5Le8Z +Qbwg+8tdQ/MD0TwU1UZ4If/3u9v+ef9/rmqI3R+cHENjMH8QHyhrp8Aflh1 8ic78IPqPWdHzA9EdmMeE/CDf7UFnR8MKZt0MT8QOVnf6fzQruE/BvywL1lV EPMDEaTncg744dO3Ljo/iLi3T2J+IJ7O19YBP7xSGPkB/NASU+2O+YFgV+jy BH6Yeq9M54cd27ayYX4gor2d6Pwwdla7soGThg7EP07KrTxBeLTk3ywbwHV/ edh20PmP1MoWS8xpCawcWqAzn3GABOjcaCiyXR9z2rhRaDfozBC32QN03kbZ U495GF1PsigFnZlI2dag8+FaixLMw+jmvid0Hvbl3JcMOv8sL7XFPIwiKHHG oHMp8ZrOwx/urW3GPIwM8t3lQOf/3u/f+uf9vunb3QWgc53mcAHmYUSREv8C OufJpq0Fnc8ov9fHPIx2dx9nAZ0XM6yDQOcplhO1mIeRP1vsFOi8eYF3GHSe +ZIriXkYRQ/yWYPO+yW06DzcvyX7O+ZhZPikks7DMwNRP0Hn6vPzKZiH0ecX 6t6gc8wWmSzQ2WjguCrmYbTmB5cL6PxW35w0iX/vsv0JWj+UzIjH6w+sEW3H 9VdVjAK5cYSTa0IXcxo5T9gOckNS/fN3yA2Tr9xiODfQD9VuSciN2LeJkpAb fHdYU4HTYg35v0BumLSgLsgN8ZsHfYHTVn5zX4TceEXisYDcuPGB8SZwWsuu h+fonPbBiQ1yg3nDQAK+36HSmAJXyI1nS+/3h5be76svvd+/L1VHv9+tNRiI wPc75F57nH6/c0oU2QW5cWGw8zO+3yHDIh9vyA32mdhbkBtFLNq5+H6HhqaZ EiA39IWt6Pe7+MNnNPD9DonMtNPvdxV55mWQGxYDv/Lw/Q6ZpoR2QW78sLZ3 gtzQf7LzEL7fIZllNy5DblTVb3GD3BDVuTaG73fopOWQN+QG2Y6b3ueRYxcx DMGcJm/wgd7nST0hRe/zDHeQA2/udkCnqD/pfZ5TFzbS+zkMEneud2JOG7v2 h97P8ZmNoPdtaP2Jebsxp7FlbqT3bRxO8byEOigf6r8F10FU4FOXB3Vw185l JVAHV30syQdO65X/Egx18NSb9BKog1e5Fr/hOoiKr+qIQh1MWHq/f3Xp/b7M 0vv94bIyev8kdn3H0RbMaZ4ZPzmgfxLGn0zvk5AyNu/hxJx2c4f3Z6iDcuIL 9H5ITMBZeVwHkebyvBGog41JElJQByU/h2sBp/1UtaiBOtjUsn4a+htGHm6b gdP83s03Qh1cpvaA3sfIebhLEjit0cLxJdTBO5tC6f2K5Wnlu4DTxILN6f2K 9Ub9HMBpy6+cSlUIlSafnuEZAk57MVLzercMDdWbm2nFpCmRQmqcA64+xXm7 1E+7viC1zF8CkY4s9dMmlvpmPUpW2tuXaZHslvpmu5f6Y680r+R1XTQh1S71 x1SW+mA1XOfqb60/R3q61AfjWep33Vl/peOVvDXp9VK/67/3+1/+eb//cql/ JXSKxXabqjfp1VL/KmKpT3XNhyS2jeUm6fRSnypnqR/VbthtXcR2m6S61I+6 ttR30pjSUeHmiSTtP/a372Qw+ZfT7kZJshRFxZJ2B/7ltHcLf/tI6oX7t96r TyXlVC/1kXYOrnyGfSu823ehiqJOcNqJ7tuCfWsTLXdmZD8NBUYqP1v1yorQ M7xRQC3FPHytqWM9oqGnF04EonoPIkJ0+RerTArabqqRbaNNQ6eFNbhklt8g xmvI097hFFQ2fob3kz0NdfzQnRwt9ieGC+U2VjpRkO99TgPKXczDwwNCoiH+ REaRiPZqEgXldcfPXa2ioW2xPwJ/XPEhtB2Dt7r/Gvq/fuCjf/qB3uwux7dm 09DnxwmTNNGnxDb+olS+n0Po1F29E9atNKRoM/djeVQR0bo/3mZz2RBqcWoo TFg7jgZ1T+Vb8ZYQbCU5YhxmQ+irv174pNk4cuoNnz0rX0K8fTGktWNkEKVy 2TfyD48j9rPb47Rdi4g/p+9ofRMZROY0dfHbGRPI2Vt6q8vpfOLnLf0V5p8+ ojMNIWbwHrmd9WkBm4E24cvwaeZVNQWt37igvluUhljkux5QV1wkhh56bG6s pSAOm/hAHTzeLhb3TJDvBlFMm1qxH4936DOsscPn0pfbjGQ+hBLBJX3eDC8x J49f7C6VxjpfWH7y+9logjU7Sm4oH98j6s6am+Lc8K8YTTOOSCSm5c5rWdyn oLfhswl/LGkoqmqngg3m4Qpnfl5Wu//10+z/6acFUKqTnjZR0aFwo19bO54S nmtYJzw4h5GXwuZYxUYqUk488fDotxKCocdOJnAlztt7h4VWv6Uiv5GFEo3B CkKr0uiS6gTO8x6z3O3NVNR/3eXl4K+XRKnJ4Xpf7KvSI7eeHXmD793dO32q G6uJPyMcLgW3KUiNX8pKs4SKek01s4Ru1xN5SUKs609gzleco/rjOpW+rf6d jb4Cka36PboC16nqkuLQP5gTCKbDDvtyzhF39w95B76noEVe/onPmCsyTb+/ cW92I/Yu8jifxVxBaemzalmF9a+LEDIm+xE6xQpc2z5TUMlTWfk+zA/itzr3 /uKKINS9XWXL5ykoJaie6yquU80CE79N3sUR1p0L07WrhlF961nODSNUJPii rYnbO40459YZHMP2v74Z5Z++2U8eZTSnR0UeTkGPe6MSieSBddYtL4eRFHn8 0u8DVJQzkev4oySdmFn2KstrcBh9c6Ptes9BRe9CK+/76eUS2qp+ew7+wbxR yhR589MY4oktz7WsKCRCBbnPxG8eQX5spw4XV44hVnlnx+t/ygg3r0Nfow+M oLzy8cGk0DH0OaHvzcdBMrGpdoVevOYIcrvgVOuA9Zy2iLXuOi+HdPsWMj5g PXtc1OaAu0aLRdd8Sj2NatwvTwF3FZ85vtiC83mx9crPs0/M0eO5dR1PMXdJ 6yr/HsG6HW+08St5eQZdXl6xvQjX8fM2xmfTMXcJvtwlwKajSLTlPp/j3TqM XtjEKApVU5FY3taJtoRLRMD8h4MuysPIW+RpjH4iFZWX31w8uSOY+L3u1UVm p//1x/T/6Y+JSQZd26FBRUHUJwoKsVFIcdvA8J73w2jtS8vKSB4qalhVNH2n JgKxqvB/U14zgr7m22wOGRlDb3857z6xIwid4nplfVVtBM2VOKbsyR1DvA7B h0Z3nkdNzQKl3f6Ye9NFlKtdx5BNuBxneexN4iLTmYnJaqzbRkaT5INjKDXV WSj6+gOC3UwmVJhpFK3cntKejH/vb358T+Xk1EZVpfrzLDXYn9t+3riP7xGv sowqDIIvIA3vqGXv8T3C3DW/uBP6vTxagdfjrqOp7n0p2ti3C7/aFEjsNGR9 pVf1F2cwstgwS+YfpqAI8d6e+R9UpDL1NlgxPRy5mZOHbRmGkbrW5TZKJxUd jH13stb+PtryxeJkiOgwulnRIuiTQ0XhNZpJbmnRSHn5ueFvJsP/1wdz/KcP 9np4JkMdz1/JmPX8SE4B8v8kpzamOIxayw7VfrlERQPxQUGmMYUojzM73/Tq MJpSXxshJE1FX+YdZrM/FKHWN+zZFZXDiF8ivMVuagwV2SW+jzhVjNRsviee 4RxBGy9NVQkmjiHuC5Z3M+aKkAGfwWFnhxH0+bCFWdDxMdRcpOWukl6I9iQ2 bON/M4JSZ4un4b2bW0tZc4LrcfTg+GDLWZwbVT3FFx9L0NC89969RZaOKHQV +rbsOQWR3C/bHzpIQ7p2RKq+2XVklzfQogL9mewdT3RkaYijw6wpagxz/gml 2gd5FHTzAVno+QEa+rJuq8LNL9GoMpfRTAHPXxtgcfv+Dhp627hp3vt6EjI1 Zz/kVonz6qqX1UecG6HPJOXUWx6jceUT3zwH/9fvSv6n39VOrJ07d5OGlJ3U xcYxR22z8tTtEaaghoB8pRCcw8rziltNbMrRnZTDxZxSFNTKHbc3RZyGvl/j JY3NkdEAN/snXWMK+pYtneA5QEVVtV86yrZVoiSHd6Q7cRREbXzUyuNFRYsM 1e+FTKvR6zcvmdf9wPu/qE86v4KK9iQn8p9ZXot0rvSg57bDiE+Qr5vAvGR2 3uOj2MoNiJWc5dSEeSlM/h1tJ9btQNS2EpN4FWShpin6GuuwfW/Kx8OqNHTW Z09K0EojVF4W9tYukYK4H3CzKBvSUIXEVLVSmyvq7i0L/RlEQYZepYo8DjRk eeGO9jn/AORWr3LvCq7vMg6u1ozXaCh+Silmsfg+6mMVImx1MZdaGby/eoeG vh24c9X4QzJyzdARsDpM+b++FoPC+oP/375WfFStE5P8OArdtaIyyNMH3d9s TKzQHkLvrO8nRF8YRzqzxca1VfcQn2/LtcxlQ2iNStvw6bhxZHl+PsErJhUd 62Fb112OOaoyZz9b8Ti6EvzaiqmkAC0efL6n9+og0rfN2q6XMY7eXqrYqd9V gcqCX0UZGQ/ifAhdBVzE3lwZOIe56Ii+miRw0ckfG0yBi54GTe9eibno+3LH fOCi+aNxXcBFd9wOTMpjLmo8XjEFXDTWcz4XuIj30E77g5iLqiOrJ4GLsq/k bwUu4r2gZDCMuejEejMu4CLO8kcmwEVfPVVfC2AuemC4SwO46EJDxw/gIsa2 tyM0zEUNt4M2Axf919c68E9f6/i652eAi269yxcBLuqQU7oLXKR1YuEscJF0 71pG4KLSMQFd4CKBZu/XwEUKX275W2IuOuJgyg1cdOL6znTgogukqPYzmIsM +MrlgIsOVFoPAhcp8SkWnsBctHu+XAG4KE+J2Rj4Z/M8/8dZfW2il1lhHvhH x6ZeDfin6PyiBgXzD4siBy/wT+ho4G3gn8orCwk7MP9cKelkAP65PqnHDvyz 4UuAqizmHxbP75eBfxj3sPQD/9SluJr8wPwz5m8pDfzjEPvIBvhHVG/PKhPM P8d8GNWBf9xmw7OBfwy7d+VZY/5Z9eYBK/DPf30qoX/6VD9CI3OBf7ykZh22 Yf65EH27G/hnfhUpE/gnabTikAbmn9bS5ULAP0bj7VLAP018YQzHMP9c4Wk7 A/yT3e5ZA/wzxpH8B/gno6c1A/iH0hjbBvzjamvYAvxzu/ryMeCfDUKyAcA/ xbeWb9iB+YdZmPSBHfOPZ7bYGPDPyXNrIsww/5iHyccA/8hLbg4D/pGXTr6+ H/PPq1kzOv+USL2g848/Y5ikB+afQStdJ+Cf/k/ZdsA/p2UqFkww/+i9NmID /hk9nKYI/CMiqBT7G/NPXEbMfuCf5Y7ZPMA/929t8zTF/DMkeW4c+CeLc8tm 4J9knWLjDZh/StlHfYF//utHifzTj3LT61YG/jm1uvpqP+afMz3S54B/Logg L+Cfr4odR35h/rF4FpEM/FOhY7cP+OfS1/cSgZh/7BSE+YF/TuuviQP+Ec98 22uF+eeoluNJ4J8Qs0QV4B/XFxP5vph/7vJXDAD/lCSuowL/MFjK+gxi/rlw yOEI8E+khtgr4J/0Hf42zZh/5gTy8oB/LLlkvwL/lNnnfwL+KbHS+wr8U3DB nM4/DU9G3hhj/pnl+N4O/BMe5fkL+KcvZRPDY8w/6+Mr+IF/xr8L0flnUGRb pRzmn4TwBTr/lG99oAD8o8G87cwHzD8iovMywD9r7mfEA//w9uRePIX5hxcR jsA///WdrvzTd/r54qoX8I+uo66uHOafb3MZ48A/+6QdCeCfMeFtL4Iw/6zl 9fgF/FPxuo8H+IejXWWZMuaf23e4bYF/4tbGpgL/HBsfYCjF/LPHb1kJ8A+T M/kI8E95sMWaGsw/d9R+UYF/vrL6mQL/vHccr47D/PNIjDEY+Gd1/rkPwD8T sk7X+TH/HFFfMQf8c2yFjRfwz5ETawd0Mf8IjCmyAv9sHd5UCPzjIMwtAvxj 23k9HfjnuMZyOv8EbdL6/hPzz9swxpfAP39iZzuBf3YHm4UrYP7pqbtPBf55 7uTWBPwTnFeQWY35x2XLYX3gn6vbwgWAf3y39l90wfyznhowCvzzX3+p95/+ kjzPcBzwz8/tLzcD/4S8ETAE/nmhEPgC+OfQ0/h7ZzD/dJsWkYF/1mopBwL/ XDnIuwz454i3UwXwz/bNovXAP/uct4WGY/6RmUrLA/7xiJB5AfxjvW+Wmo75 h/xY+ijwTwbvRiPgn8i2Ry+VMf+UnKjZA/wTosX+BfjnT22KbxnmH87P9nT+ 0WERll+QpKHrK7vDrAsc0CKH5wOtZxRkPXTACvjHae3my3qYfxpLsrqAf46Z eWcD/6jcqot/gPnHZlaqDvjncBpNAPhnhbVzN/DPOl4xC+CfP2zeAcA/vEzq G3ww/7RmSSkA/zgrZZsA/9jd+kGoYf7J2SC/zGvwf30k73/6SItTzUPAP44j VWXAP06zrrbAP24r9u4B/rnsv8UQ+OfUJc9m4B+/awGbgH9Co53EgX9O7t21 +hTmn102HQHAP94+93OBf1wG2M4B/0hLyj4H/jkxvuIS8E9hmK0Y8I8UNVsE +KfQPcTNBPNPp42kFfDPZ+V3zkOYf5576ScxMy9DX2reGyRj/lmxVf3Ga6wb s9S88ioJSbQyO4Zt8SnO7Uk/Ov/8IV1aH4H5Jy20kM4/gT17VwH/+Jj43TiC +adDY2c48E9P3VEF4B8pQYZiC8w/7udH7gP/jP9G54F/5ChpA38w/3C6MVYB /7ikstQD/7Dn8HSaYP6ZpxrtAf75r1/E4FP5/+sX9Re9cwD+2XSN2ykF88/G mSuvgH8s8ktigX+Oc9TUNGH+ce3huAn8k1L+tgf4J8xp4e11zD+Uuxs3Av9c jeblB/7Z/bT2ygrMP84hSfLAP1NXKUzAPwfXdZScxvwz6FD4BPiHMdkt1T94 Et0TPv1m3WIR8fJWDJl0uRcdKOJ0XITvIqg2aWYmLcRZBVTCgZ+r31qXCeOu Z8pb8DjKfmxiAOPy2vMdsA7ni9ULTItF6F3m0WuwTuK0XTuMa8rNRyzD64/v zvKB8cHXXFmwTmAt93tYv2pVnz6s81J8hQOMX+MIKoL1WXLXF8G47pOrj2Ed gXYVMiteX2VwmL7PlGWHp+B3JLxFbFe863EiK2l1O/yOeC5rla8Lwb/rBPfz EtNNhE1D6qFeJszzsXJj+g5jaOemnfbnD9QSHUZbZv25R1CrZWw/5FuDPS+L MKc2YcBJnYZ8+/ObTbdefgz1GJ4P+OJcRcyJ7Uyedh1B0u8fMgWsGkP97fYK mX/yCY4NVofq+EZRhODJRqg7Gpt4XjJYyhF2pxqSoe60Z9xlfUIdRRl/Lj0z SU0mknx3sHzUHEVq1x+uhHG3g7kvzqUmo4dbvq6F8bRXrn3AA8WpP1aJ6ysg Ppa4dOCB+oGzy+G5Zf0tvll/8hHH7oID8Fx9pRRr2CejXlvMV+cq9Mzg4FXY p5DBnvPAaf1lfx6LG2ijwt1h08Bpio9SP4MOWS9ePbE8UIvOlAe1gw7vtVz7 QbcMmZhQrBvaf8tqJejWcj4w8kIzDaUFTmYQR94godXrn10KHkT9lL0SdyMn EPl+5tqqhBdIb7tmVUbcRyR5VH1n5VcaCufdmuh75D1y3hlezHd6AN06sJcK 57W5gfmcOD6vB/wNvXBekbYK9OeaVPPdg/NaKNxEf+7Ko32fYJ+PGJ48wvsk HhVc74J9bmo6/hHO62ztvVVi+LxmJFfQzyvmwpgl6KC4PzIM60A4aVX4gA5D Csvpuj1w6biGdSOMczZIgW5aM701cF5KR54VtJ+XI9w+l2TCeR3+4U4/lzDh juf4XIgWeW5WOJf5TupaGF9IkyvB54iUDNrp53jd2aobzqtp5/6jUvi81Psr s+G8nAL66D5hl/c7gn2CNvzhoPvELtlDD/ZZEIruYV8hflL1I7qvpsut4bxG Z6N59uPziu1lmYTzkjDdRgMdhtI8vLBvkY/k9DToUFkURfd5rZWZI5xX7aKZ LOi28MvQtgDrfLfs4EGdHxpoJRJlFMY6ayzzNYBzjDjgseYlPscN2z2ZL+Nz 1HswtRCGz7FwZ5BdHT5HoWfiApn4HMOqLDpf4XN0s5y5Cuf4If+s4lZ8jl8j /n5/yGh+/qReYB7JO+vv94cCS3171a/y8ka75cmKS337urWm9PlGPjHZvAzG ZNEkPnOY/3kuURz8k5vOfRT7hyixKXoF/pHasZfut69UpiLsNyLY+3I5+G01 Z0RB3bVJxG+oceQ+oyLZmfvUTvUtfeh2dQ39nrv3rqKncbwKkXbVmH7Pnec/ xBGB97NrfTzfFhZEyFoed2DG9wt+o91vNPH4qiOm+ryKioTu99FmEzw+fZPZ BO59P1uiS+dfWqE/7zYVwr1PUTeTE9YJG67KP82C0JWXl+1gHX+/Q+rBeFwl iZ9rVZwMyjl6zYcDj79a6Uvfj+7gNk0ZvB+ugWL6fp7p7KOv83pz7fO9eD/e N9ns6etcqmiC/Tj8Wbn9It5PvmrCW9iP/CrTTrjX9+5YxZ3+h5vwjxq9APf6 X0mrVeG5z4oChD1jZAjZKi1feC7KZWKC+yw1pcHxJEUdaey2koH7bIi4bT2s n1AoVN2moIhkj11og/VtMzjo6x/pnQoLxOublahehPX7dn5XgfW/O3lEu+H1 y/Nt6etfWfpOprbcVon/0FFS9dJ3Mv2fRhv9sG/HNckzc48voCerSxa58e+x VEy5x1SIhphqU8LFTJxRY55Sd2ojBZ1wvVwUJ0VD1pOBB7+aOBEKq+SKc4rx /Kj9x3Yp05AZEuxPP+1L+IueuT6WQkF5BuIr3fVoSIH6lf1gYBghJqtgKobv U0MfBgKf4Ps16+ez5HHdh0S76FxRiT0FndrhZHDVj4aMgy9qHfyQTLCb3/jN pEpBraen0wfiaahkiFG9KyuLGGpuODm+mYIGDK6uphbheyU1vG77zqfEjkOp OZ0TQ2i/uKn3jRq8zzscp6mMZcRKTc9VM8+G0B5z6fVZDTREttyoTpogE2rm lee4bg8h+3hbnasEDWV+SXtB2FURDwK4kntNh5Ayp7PMmWSsm++zAwH1r4mm iJ7le6WG0IRF4sezXjTkLHopeCT4DXHI7k4+WhxEuZ0xFS67sG+ttCT3nDhF qLPdCmfAOVAsw9pzH48vK7/akPDFGtXXfZ19XUVBnJm9pzbg8cO1gx6njuL7 4Bn33Zp4/lOTWOsRfO/ez+h89kBDALF2rzmxC5/L6VWHihgxt4uv56t8K3WP CLhf1MmF88pa7DCP/Hbsq47gw+vcE4iXaVJyzxsoSN3lGE1wA34u0v4WcSud 2Gvz0eRbMwVVa/aLrF5JQ0m/LOa+ueUSR3bauZf1UNCPJuOVm6eo6AlJc2VZ YSGxX8eshoNGQW+VpfvN8b3YJuxE4/2kMqL45PF34gsUpHUxd+v4Iypqztf/ YjX9gsiMfDVvsGkYXdzb3lxggXlP3kHwW9UrQsUsp//PYXx/NAn9tn8TFW2u bGJMyaomjj34Oi9ih+/1oncXyMVjKEJYWeM0+TVhd01u2v/xMNrbqif7Fuez zoC4/Ez7McJvf86mc/jv9Rb+9EYH+1zCdms6/x5NFGw1OGGAfe7TuYUzYRsN vRu2Cc9/ZE8sY3XjLGihIMGvr8versc8ycY6ty/Hh4j9flymb4iC0oc37uVZ pCK5Zcj9cm0woUs1j+35RUEOad2/DgxT0Y8tCk7dzveI5n0qDtE8w+hQXeKu tioqYlGQTrkdE0eMf/ApmiMNo6KSdvPSOCqSvnHucuT7ZOKh96xXDf67rq8b Mapwwvfo1T4W29MfE1Jvr6uT8T3xvB/3+RFZKuLLHZzZkJZDTA0cKrzSNoz6 amZ47RbHkIqa5Ix2Rz7x8FWni+v6EVS6NdU//Tm+L5cVPms9VkjsJVIyeXVH UJqaS+2M2xhaYXt9g2xUMfFBV+f6wYcjKPqXJwOjyBiaF2VoTbIqJcbq3nOT RkbQBiPLYfj/GYQ32eQLc8uT+y7ns5fje5/2vm+pV7fQUF2tn9TBmwKkqbtO FIZOCroUSn7Sxozv3f2F48tnpUnsAuW7AqYo6IO3Dv9X7BO57EDltTZHSLc8 3gv2rxtGUXINrzibqEjgnV6fRMNREtPavMJLB4fRqlv21+6kU1H4lgpdrh5d krfZRMF962GUlfq7p9KDih7++q4cZW5IkmXa5Wz7aBj1XnoTvVeFipo4f26/ zHWOVCiq4r3qwzASolYx6a+louz6i6jh5TnS/PRgpCfvCNqxfn7/u6YxHMx1 lkWi1qSa529ka8xG0Bf/oyvOhIyhSyFRrRXiNiQVk/WU2kzMV1I+LKFHx1Dm j5q+siArkvt2zWWxX0eQhud7bXPmMXR3y7cy0wlrkkOL6Mc56VHUcmrzAfDh VOybxwPtx9B3N71t4MPCC6Nc4DfRuEvgN6Rbsnc9+G1P++8K8Fv0neMbpXN8 UNpqiQPgt66FK5LgNzLtsK5HbTCyTv8TBX7rHXyxCH77kpo02uN8D21t4rQG v6n6ntgLfmvblBMdEhOHoi0188Bvpx2ibMFvSXyCoffeJ6N32U0u4LfPt/eZ g9/OOLTxCqQ/Rt8v98uD355vWWMPflvlPcvKk5aDKvtIGeA3tplzO8BvYofO SOh25KMFvqOW4Dfz13J3wG9rinaubz9WiNQC3OLBb3WbSW/Bb1klR9MORRUj 54ASF/Db770URvAbh7pjbYpVKeLoWlwDfrsvnX3tzY9RtCtyJt+3twLdvxcS MMswivZ0OpVBTlapcl0QOHEKFWffvw852fKJQw/ysDtDUFH7qBsS9Eb0PKQM f3OAPGS4k10g1RCAPMw9yiAPLVKZSiEP2eWEk3EeorxH+9ogD+1ysrdCHuYW K3GzuSegQt3vByAP99/r+AJ5GEJ5P4HzEI0HbtaBPIxX3rgf8rBVc5r7u1su ijrKaQt5+OvocW7IQ76fJw1wHqLu1Q4FkIfeu1w/QR6+K5v3jkoqQ2NbZ8sg D/v2rJaEPJyV3Hzdehpzdcz0EOShtTCZAnkodl4zGOchivxzuBLycDq1kvkA zsM1LfGlOA+Rk/PcB8hDwdFv3ATOw20ip1WMyK/R/6vrzMOp6t7/T0JU5qEU pUGZI5lZVEhmQhmjUIZMmWkiGkVlKLMKIUpJxm2WCElpQDgH5xhSIUnlu+7z 0fP8fq7r+Xdf51rtvc56ve73Wvs+euMkXQs+XLFGW8hGZASt3fiDZa7+OXIh hzMv2zWESqXEJZ2xD6XsumP3RRuiS9FB+xD2YWH8viKo11cZYj8N25xAhcz8 z6Ber4z1N4R63SJ8MQnXa+TSLRUK9bpp91tavW7b3M0mF3UNVZ4utoV67alv fAXqtZmBmCqu1+jtEZNCqNcX/S7bQ70OWOC+vgvvl/88D/wG9Xo6r+Ex1Otj o7ru3bm56JPvc3Wo1xwLX9ZBvd5mwL0M12vkLTSSAPV64JHxDajXhjFJOSP0 z5CHXcf4N1yvjw38Eod6nU5a76A2VoXC2S9qQr2OvVTqC/W6QC/MHtdrRFVM DoJ6veKckT3U69GEb8Xnm5uQ56fAd5K4Xvu2BOt3C1PRA042FbuoDnRvwCAi gm4QuTC9fq/iR0Gv9PMkX9Z2IarMMCXyzQBaEcA4c86Qil5ed+cU0r1BrHCU r3W4QUKiDU5PYT4V9jEY/8L5x/JrURHMJ8/8dwOYz/nGkJx7OP+42PXT5jPy 1BgLzGfztlNIEecfb939h2A+6S6FXYX5bIxhXID8E3M16gHM55Q84QDzufX2 Pnd5nH/UKM8+w3xa2m+mzae5bQ8/nk+Ce5RfA+aT9LSENp8nMwYmNuD88zLw XCLMZ6h+9nWYT1Nh0WA8n4TUzezPMJ8nSTESMJ+PtqZex/NJhDB6I5hPj+kY 2ny2bJy2gPzT7+cUDPNp/nAjbT6jkwVK8XwSve3/m8/M5avWHMb5h24sMJKM 88/ArFsw5J+TqzpLgOssMZf+DTj/CM7YxgPX+u0S2nZHqehjvst3x803iJEo evKKABLq/MNM473XXFHdDOefeHUtGu/5xatovO9+co4X804o3X9QCry3ZPCU A+9XrwZvaMf5R0vjbhvwzmhzm8Z7vccVVcw7ofjoN413e+9XNN4t6r+suYHz z4VnEybA+w1RXzng/Zzvt52YdwI1SbkA72Wfn/EA7y+ztu+H/ENOPFgEvE9O 2NF4bxEp8sa8EzLtuqXA+ylh2x3Au1aX5lnMOzFYWUkC3lN+nBwC3rUqG+Ig /6xedYkA3pn4dtB4r3X+VAT5pxpN9gDv+udTeYB3UXk7dcw7sW+9Sj3wLpxq uhPqTpFXy/cenH9Ym802Qt2hU1lTE7dAQUYy7ZHf44KR2gu6xrdzuC5zctDq 0cOS+6KFOP+4u2pwQT0KNfal1SO9NrZ7u3D+uTnUR6tHHx7el4V69IbDXCAI 559qHt84qEfrXNh+QT3K+mr6ANcj4ne5nyvUo20ifdJQj54oNmXiekQcdXF4 APXo3X6zY1CPjE4PxON6RFzapH8S6lEsudkB6pEV1Ywb1yPiqauTOtQjG59r rlCPdkw9WYnrESHw/BWtHoW5NG6BelR9qH87rkfEXnZOZ6hHXWfTo6EeFeup bsH1iFCLibwN9YjjnWEL1CNqgEcSrkeE76vZk1CPNLmnaPkn4WxEOa5HhL+9 +GqoR+JNmr2QfyL5zPYedZ2pjHhXtxbyj58S+z3IP4GtRScnjdZXFZANafnn 3osRWv7hjXjv92rLripby/O0/NOzTJGWf0SfvxEqod9TpXxkipZ/9MILqiD/ PFe4VLj5uU4Vm93pEsg/l0kmZyH/GAhEeMYKmlcVdqYVQv5ZrnD3PeQfWTs/ d2kdi6qE5BovyD8e0dto+SfT4m0Dse9wFSMH4ynIP7nVGfSQf34ppOl/+Xi4 itlfIg7yj1Cq2C7IP1d3RKl9uOxcJdsTogj5x0YriQnyz8+b8qlMiceqTEUz ByD//PR8ygz5J2SfAOmNuHPV0RJZRsg/qQ56tPzTcqhsxpX9WFUh6Qkt/7zX /CUD63CvrqsaBeefW4pMm2Ad9ufOcMB6KzDqjs3D+eeBlxwfrDfmSNkyWG9J z33F5XD+WekSKg/rTSjIXxrW2+iC9OoAnH9UOtJuwXo76HyBlrcPWd25hfM2 ynmeSsvbE0nltLytmJ8Xh/M2evrakZa3j2nVHoH11unGexHnbTTP0xgM6y3u ij4tb1v8HLHHeRv5PlTShfVWuY6blrcLn9Iz8eP8s6dmCy1vh97IEYL1pqCl OI/zNkrNbPWC9eZz5SAtb8eU6T7BeRut52XPhfVWGarWAOuNQ75yJc7bSKSk 9SysN+/cNtp6M/Pd2IPzNrqmY0bL27ZW3+0h/8y8FCdD/tm17W4W5B+y4bFK 8CTz88ubZXH+2YpUr4En825NGYEP2V6JeRrh/LPWtlUWfPgw4t5x8OGXS2F2 kH+cDEoqwIcaYa5PwYcre3id23D+kWeppeWfFnafdeBDzojZCTbIP+wblMCH /bnmFPChZ3BnBeQf5a+WduBDhqnG7eDDrpjrtPxjEs/tDz4k652i7Qdvpoaz Qv75eWorbT/oYdbyCXyYuK1xDO8HUVhlcSv4ULZsnrYfVJqRn8X7QWTah2j7 waOFW2n7wcoV7CKQf5IGrT6BD7Ono2ZgP9iuLrmQifOP56jpH/Chry/TAuwH j3lutMD7QTSW/GQCfFhSKCAD+edcd7nSLM4/C6LveSD/xHqk7jDE+YdS0eFS xW2IzOgLR2xx/tmnmkc7r+AwyL03jfOPQsP0E6jXvmvH90O9Pu15Rh7yz0q7 Wtp5hfmW+7T8w7lnvEYB55+UUzG0/PNJ6f4FqNemb+g1x3D+uaNf/xjqdX/Z bguo1zVUpTpcr9GG74m/oV775TJmQ72+L7tq/zucf1yP5NHOK86V3qOdVxBX Atsg/7w5ZE47r3C60UE7r7BWP+tOwfnn074gJjivuJ9sSzuvoOzQ3KOO808C Tz7tvOJjyn4zqNcfC+JfQ/7x2eCcBvXagElZCer1yWyyciTOPym/VBjgvGJ5 sAs75B971RO6kH+6FLXeQv6ZCm73hfzj1Y3MIf8cubnveBTOP1e/6o1ZyuEc JWB+ULbMnUif4AwwLCGhEFv+m6c1qMh7xLv5Ls45N9d3iplnk1B8kqZbtgkV VfZ5PBPDOSeu6QvTuhgSunVl7mamMxWl6Ns/7cA551tDbaWhDwmJiDZN85zC z/viagwHzjlftE2eBBv+2y86v6RflL05xieolIrulTdv76F7Rmwgi0WFtgwi SQkjxcpyKoq4lWHGTqkiTOlULD+kDSLXP45hWfn4e4/m+PXRuY6IaGhodgka RF/entiw7BIVzao8tT1Q00TQr3f8/tVyEEW1uIvus6YiZY/pzNshrUQyfXN4 r8QgknuVs2/FMwqa+GFhxVH5mrBaMaz1qG4APZVTmmrbSkXXr3y47EgXQQSV 8Rnsa4bfzbHnUPE8qzT5vzeWvk7MXH3L1dhKQoMsHj3HcH0ZqnrImlieTEwl 8z4cwp7Uad3w8g8HFUVV5XE8rb9LVLdSNzm/J/3Tz7l3ST9nSd/klr4MCjpD YWSKmS0nYuM2hPJuJCOj68bmR90piJSr7Kd6p5pQZysmv9MgI3O77Xnh2yho Xa1kQLx7HWGlp5F70w17dafP2JPmETRxPlLynlMj8epyTnVmDs4bWyeqtsuO oMnl3driK5uJCCudjM+bcF1IsbWLpqciiY/P5Hf9Cide/6R7yThLQvPuHwVc qRSUTW9gMCARQ3AbVoWs4yGjb4c54/bi+8/yuZQmEZtA2H31agxU+Ld/smlJ /yRDG9uX/i68fyw972+c/oiQPVab16U2hHaFpqt3xI4gNbqf5+0mHhOZ8fm5 QmeG0KPLg9ce6Y+gj1aKjVl5xcSY4x7R/fX4+tiakIfLR1DRm5fRCY6lRFP8 0NFw7NsMxpPnovooyMFDsZel2wFdmzM0ltxMRgrXDSwtyygowK73mirzUdTG K0u9ZITvc7H/UNnjf/2H7Yv9hzUJ436xbiNIkLtAMOOnPaq50vleq20IBUjI U7lFR5Bc4eYGrVxJpDHL2dDLM/xPf+C+Jf2Bf6y2nRrpoSB5i7Lvu4NuoXiF gmxpYfI//Xibl/TjefUIy8YbjaBEPcK9wKQEHbdnsbArG/qnL65tSV/c6sV+ M/nFfjPjxX6znwFd48B1VmzCeQXM9ckEHj/gWnF1ajxwHRMTN3YHc+3vl7YN uH5PyHsC1/mr6gUkMNdz7x7QA9dR9FtvA9dOUdEsrzDXcgvDT4Hr1jijBeC6 r/piKTvmWmlIORu4/tvvFLek38leeC4KuK7mn7T/iLn+s6zfA7hmr+I3A64f iCi2smGuf2yo2AVch9qHpADXe1YwlQDX99DjDOC6iHR4L3CdHPaOF7jm4Kx7 DlxzjWmJ+ChiTotnVqJH7YRynJW81IpBtCV8axFwvZNBpJ8dc51bzfbmIeY6 +2roLHA9FD6mdBRz7RYWowNcS668XQBcfxz/3W2CuR5ebsgKXB9CRwaA68bl IhtuYa4P2h27D1xPhcl2Ade/a8eDgGvS6qtrgeu/fUqZS/qUzl0R3wVc1x3+ GQpch7HmOwHXxetfHgOuv7U7DgDXRzuym4Br2QyBCuBa44bbhgTM9aio3BXg WnxoywJwnc6iKZWFuXarvJkIXL+fvlMOXK/T19guibmOY1c9C1zzGA44ANef HQ3lFTDXjeuDnwPXf6RYBIHrbwzdDwcx1zwFtYHAtY1NyC3g+k+fzVMpzPWc hls1cP23L8hjSV9QzapVP4DrPT6Pyk0w1x8Cb6YC15piO7SAawvH1i57zPXx uYxU4Nr0TkM0cH0P6dnlYK4P6KzbAlwz60RdBK6vrPNdk4i5lrI0MQOu6932 nwWupy5Wj/1+64DY+JpNgOvkTRctgOtNLi5BkpjrJ0I7RoHrlMW+muNj/+ur kVrsq7nObe0PXEeNu5rvxlx3Zp6icV2u4zsBXFcxh/kdzZZEK4rvVAPXf/te pJf0vRSVpQYA10jv3GFNzPWrHI2HwPXfPhO/JX0mf45GiALX7I99YvIx18/k 97oA13Qc/+v32LDY79G12O8hv9hHUb7YR/F2sY9i1+J7//bF9/62i+/9LRff +wctvvfPWXzv/8k78BGs//CHPZ/x+kd7dlNfwfofXHy/f3Xx/X714vv9msX3 +xGL7/eZF9/vp/h468A4gj6azrg+oqufdfZCffT6nOEHuSKBftUenCsIRWZe d8gV5S06Lo3qVHRgk516d78fIermcevNfRJyJNlnXbk8gkZEhn+/T2oi9tKb KzB9IKNbP9onuFSoKJPa5iuTa0ksCIzvqC0goSu5Xw2nV48g1mi/lp/CZYRo /usOvSm8fkK6/HeIUlHt16sVdGXCKInjtlUKzsnFR7jUePB1Bv7vihcM5BFp nfy6Gnxd0IjLGcaRFlh9Y164DJFLO5/AOFVPZC/BetswLCSI1xvK9rxgCuvt jGK2dJgBFe38WLH/U+M5ZD+8qzU8HudtfWOKCM7tui8ZbpAL9qNvgXVxjji3 m39uy4bnGj6zV+xjUhNylvbbCM8lX9hdATwOTp7ehXlEsdKTp4BHudNhNF8l /eL+pf6oHfn4tSiArz5TBD/CfPYe37UW5tPzBc8EnFPt3m8vBPfTfxa962g8 R7TxOpPgfoad1Wnzebl5tQD+dwkfCfvN8O8KTCTGwfy0jny5daJCmCjL9doJ 87PG2MYJ5mHIXC0azwNh9yKnGOaBVeuACB8DFa09sdluONqJeFlk6VQ4Q0Kx r76pw3wuJGmZl+H51B54tQbmc73NERMYR3nOpBd/L2jUZ+IljNN0RDIM5pP+ gWMarsuIns7dEebz+B3LHX3fKehzW4S95N5LRO2On+4TDHi/HGdHhfnsaysa eIfnc7e9+02YT/Fxvhx4Lrfd2zg+4PnccV1ADp6r9YZMDcxnPUnLBucWpL5S LgXm85oqleqN5/P5MiNd7H/sL9YImM/fHr3SsI8wsf68E+8jCLPxND7YR7zd UEDbrync2duP92vEqBlDNuzXVG930c5b2C1vr/0eF0x8MONvgPOWsS10z20+ URBDZ/ohXrkMgqKc3NcpgH2b+UkQxj96r2/FHB7/3r4VK2D8Q/1SYTC+fRRH Oozf7x1yEcZ/xq3gzzNDQaouBfpZCSeJhY6DRziZyehQp+cuqwEKqq2b41qb GEfsqbhzunM9GdnOSiSqiFMR2STZUChEipj+Wm3AAH/P7epo/gG8H+R/UZbl M+mM7s2ta5HF9Us6g61jEs9nRr75ROi1LURAxaHeI/jzO9VLaOPEHuAplsfj vC/koI0TfT9wtY8OFZXXXwv1S75JZF20uSSWTEJaps7tME77B6fjjnicGMkd fTDOfqFrt2AcD8LW82CIFMq79FsPxtHVciqG+8m7KR8uP+lMOJ+5XQ33Q8+X 9A7G8TCwUDC9sQVJv/HphHHC6GrUM3mpSDj2qBpjVCxRL3TtT0APCRW0htPG P8vVVxiFx1fIX6kP43cqmqqqj1FQw8SWK+S6OwRDp7x7GQsZtXV/oN1nhLUK 76VrW9DFjCTa8zZejKl6jetaOB35AqvWXWLX5xmBX6xkxNOye+VNKSra3nDs oK6eKWHzR4OorCIh3iIPaThXT09ItY6INiROml7XgnN167Vv3lfj+1FP38oV +VOB6C5vP3EI+9lG/t4KGMe3P6F1Ex7nwae0WhjneMpq2vm8Pn+Y3B48jkp9 Gu18Xr10XQ+Mw/7ufZHYvAJx2HXYDcax9qfrhuuzGg8svswpoC0PPHzg+uBt 6h5WfF1UemikycEBufMb3FDGz3Vbscv7zw4qEtnsOfpgtwOaeKKkcaechOTW Eg7W+H4+HLMX8zU3Q4d35tUyEiRUltfVNStNRXu/eOuMi9ih6Nd9StMVJDTy u9ZlPI6KmOzEoiJycwmDjCmnmK143xo5+Ql4LJWnv3ukYD/hXB+YDjw+51zz Qw7nh+cBzsxtSvnEAV8JlrVkEroxk98VOkpBzsl9IR9Ni4g+sofBh28ktKEz 3hS8ceaj2o0ThvLE4+sdC9XYG7W21a/g75O3qA39FDloTyS+l1HQ7yChm5Gi 9p+yKOjw8IBjxHQa8XIZA8/kYegXdTnHHEpBulMMIbuv3iXY1auRVgwZaX49 pp+9n4KWdZ47l+Fwn2j9o+kj3kBGQU6KskI4v3UVRT0dGdBDTCsO6PW2k9Dh xOckUS4qusx1/zSLqwXSp5wPrR8kofH7VYxF1/D+q5SPr8bLCbFOd3Ewh5NR M2dyHaM9BdnVWebkizgjx93vwuoqyOhBZevBzu34eYWKq2vkndFuRnJs+zwZ 6SQEz9ybGEGt2SafDXKckPTlS/EyaAita4qIzAcu6uS28FEc0bO9Rx2a4P8/ qr6147wgzrdBTAOCeQEoScvSdlcXCXFOp6kfY6MiY8YHsa4bIxFKvWVaNUxC 1DOtt9+XUtD3B5nLkrdmoM5u9r7JfWQ0YyyTlonvP+RghnHV2D2EAlPbXAPI KGJdT7SyHQU96Q7o0xnNRYNHRbg18slIX3g09PlWClo+uF/3+u9CtOe2Y8rE MH6u3LUnIoZHkGWbddrAuSK0USx61bTIEJot6WiSx+tZJd82gr43CGWs2+ut hNdzxlDGYU58PfzPeIRm9yUUycvPchGvt+VB+bGzeP3cTyiUs/kajzzXvj3J iD/vL9WwZjfOz/ptT+y+1OegGN2qqbYmEvpcQAlhZaWiFJkWvdtJDxG1wclc HefqTXPvlIlJCrq2Orkn1L4Y2axBZuv7SSgtsumqwAsK4guvU92dVIZcDI/2 DeI6VU//rnB1AgVZeQ2qZ66tRqqpTOnz3GSU/TCpyt6cgqIa9lJYGOqQ6/nV gkIqZHSq8LCFLq4Xs67mpyk2J1C47ni0RhEJ8Xv4PPqtTUW27pSYnENn0YeW 5TU/U7HfKmPVL1hREVK7ZqEcdQ25W35enRhBQsoqnEpCPlR0x0ryyQ+zW4iN eRuhdeTf39dMLvl9jV7Zb96ybCrisN1fOJ+bi0iUeKmC1SSkNN4cxlpDRXRl aeU8okXobOeCjvHHQRRUz0HK6MLrJylq1VX6Z8iyp9CaJwvva7aeOve5l4pM WH9cjxytQu1ybmLSXoPombqfV8U7zBfv6rQm1zoUqUMo71UZRMelpn2B92qe K97hmPcxX3FL4N2zu+st8O56I3YvHeb9jNqafOCdL116+S7Mu7zyxgPAe4LM lbk1mPftOXcGgPe7b663Au9GBjyqwLuXeoU18O42UV5YhXn3eyw+Dby/inCj 8Z46d19oO+adgT6Fxjsvf78j8B5ztDYoEvO+zPsxG/AuPLnlIvAeneo7twfz nv9SRR54T8mcNgXef/MWqN7BvP/qDTsGvAu41EoC7w+rgndMYd5bIuaNgXfF QEUy8C7OPf2THvO+Zv5nCPB+dlsejXc3/wCLXMx7If9yTuD9gMKnGuD9YwDD nxjMe0YK3Rngna/7jyXwzi6olpOOeb8hNH0deJcZjafxbivwqUUE88598TqN d54axdPAe+UFNTIn5n2Gp9AVeF/Pc0QKeM+WmGEG3j9ziB4G3nWHG9WAd508 44XjmPfLHMVmwLvBvuMJwHss6hRLwrz7W48MAu/aOTkJwHtoiNZoBea9t237 e+D9Alp/AXhvs+Yd0sK8v+N/IAi8b093Ogm8P1ZXMIjBvLPv35MLvG/xkHMB 3qUV75j0Y94t5ylrgPfbbvOWhyWoqGFQKN//wWG0MuSEW1QN/n5ruGrAA/2r L8f87glCQtQvQeCB0vUqduCBZe6E1m7sgVUBfKvAA8tC5WPAA/vJEmXggX3U y/7ggUuuZmzggZ98fKvAA74nXOjbsQeyNPW9wANP1KQOgwcK+V8eAQ9M7qeK gQeO87+PBA/0RRQcAw9oMfw4BR6If8WXo4k9cKBlYAo8UDtwNRk8sNVabCoD e6BnwrscPMC+TDQXPPBasy8IPDD0SFgVPLClJU6GhOvmNs987npuQ1RtRQ45 hOs4q/aFg+AH51Ny72awH9Z58V4BP3Q6CBeAHyQZOE6BH2zu6jWAH6z8p9TA Dyx0Drzq2A/fNluzgR+iMtN3gR9O1996M4f9wKSpXwd++Nt/zrqk/9zr9QEW 8MM5073PfmE/dPZKq4MfXASy3MEP+m5OabzYD9qi89bgB7dd21+CHwa3nf8B fji/U9cP/MCYxuMCfnCTDnsYhf0gs8ZJF/yg3OVlCH6wpkruf479kEAXZw9+ 2PiZU/R7CL7Pt0a70gtakPlApfMA1yAy8W+encHXvzZpOsD1sweZcuB64dPh 7fD5V32blfF1ovVUBO3zUctPUuHcqflOR/XWMneUfv10EJw7cY+xE447qcgm UVun0f844XXA1ujKMxKquM3500UNr6sbx7PubQgjFjbrvPTOI6EJQ5aDYXpU ZPku0uOx70Vimz6bZHoi5ndq9vCIDRU1vbgfPNBzg/Bm/up+4wwJHfRRKljp TUVSljdCSnuTCffdOTHeeJ7l1K7v54miot9zZ8df/rhD6LpMXPbV/Pf8eXbJ +bPRLwkJ1lIq+jVv3uEiXkIk9/kW7+kYROl7fb+xElQ0Ol/zqW2ygnAsJ6t8 yR5Ehibl6+zKcK6rltfXfFpDRPAymQSdHUQr8qblG+/j/a8q9UC8VgNRx1+7 5rDNINpm49OYdI2KzksO5b8WbCb6dJzn52UH0Y6r86oXsDek2LXeNFifI9iQ 5G5/7I3hPZuoWluoiHms+2tP9zVCnHTwwp4X2J+bWPbWY6+ubJK5VB2YSNgH RDBfbMX5QW3WRgXzVeyz/4/+8QziWX6pfgH2YbVAx5mn2IdqftvizEKzCZGP l3Nlu0j/+fcE6j/Wq666T0FCoT8P2R8vJzQ3dEofxPud6pcSR53DKMh/43fr 1bzVREGhzvHAnWTU8ZNnvFOLggIzd5hcT6wlSF2aB8bNMF8vtaoN/4ygE9a2 7q/UGwh99kKFdafJaOdQgGLHciriNrXTlGELJ7xLlbQXcB256na16MlXChJN Xr3zk1A0wTv0bBcjzu3124bOaH6goEzvU1s8HsYRYxZJ22O2klHdTZPl7FUU 5Jfz6ZaydgrRQv9DvUHrv8+fBe35hRV6R5BLgH0oQ+Aj4rW5/dd5uSEkYZxA v5A5gpw+9IWsf/CYELR9MSlyAu/T32U6Dh2F/3fmwY/otGJi+gD5oF/uEOJa qexxd5CChKMyAqNrrdDhp6KO64TISM8qOlepnoLqfszwJTEdQLlKb8vC95BR xh3G1vfpFMTWcWZbvLsWsiMWtP1O/Hv+LLrk/DlsoxsXy8kR9HA/A+E1bYmO n/NqlmgYQie9LwpbKI2gpn5G6eLedUjQ9WR6HcO/5886S86fs+5vNrLG+9Yz LwR5gloSEEuetHMevk9zjv7rkdXYn/FnONjPpCKBnh5Tw93/nksLL55LWyye S5Me8cnx2YygQwE+l6oqn6I/T9tXOhYO/efvtasdDORL1uB969krgtrZ2cji 16FVzq3/nlfLLjmv/q+8lKVDpXmjyeyQQxP2RslWbUPwhp+/6y/whsSevA/g Dbux3S/AG1/1TluDN34LGz0Gb3j+idkO3ij+ZewE3ti6jJgGbwR7iLmAN2Qy FIrBG3fvdUuBN65VJESBN0ZXbDMHb7z6tYcevOGm++EUeOPv+XbskvNtjid/ NMAbNasml4M3bFqHk8EbfDUlK1dib8wPH0LgDQN+6nrwRnjMWyXwxkvX0t8a 2BvHyT3i4I3h+c5D4I2BT90/47A3KpUuf7bH3ui+Kt4vje8zOvSu5A6rVmIh LUzUi3MQFRnHaoA3uFO8hJuwN0LlL6uBN4Rt5j+DNxLZR8/2YW80ldSeAW/M DXzRBW/4sa2rq8HeoGy8t3ABfy+P7w87gje+sK8MMMDekFr+Yi94QzX380Xw hjjlRRV4g+tqZyp4479+h/vtfIc+eCNRousdeMPTynMteCMqhDsAvEEt4agA b2TFxRmANx7kUv6AN0ynw/vAG+aoaBd4YyEtvRO8Ib1lQaETe0PbnZ4XvMFp 36EC3jgw57lhJ/aGCtuYJnijpuVhMXijor9ybAB7g8vjmgx4g2+HYzh4I1ak r/QE9obHsfVbwRva+zRZwBuXFNamqmJv3DFSUARv/Nf59hn1VaLgjXX13lXL sTdmVmmTwRuaxzaygDfc+BzeCGJvNFWcHwRvdD0TcgJvzGWano/B3ni7h8kY vBGrecAdvPElUjYjAHsj/qrBEfCG3J6UHPDGpsKJpNPYG0wxqpXgjT1vPF6C NyxmraY1sTdO8ZppgTf+nm8fXHK+faWbixu8cXu+Yy8n9kYC/9vn4A0nztpN 4I1QhZ83V7xbh84dl0gDb/w935Zacr5dt8FBF7xxoN0gPgB7o+EY4QHeiDto dw28sWbmm+hq7A2Vlz2W4I2gxXPvk0vOvW915ImDN0rXO9dXYG+M3DNZD974 e+4tuOTc+4mHmQR44ztLRY8W9obbK/214I2/5+HPlpyH/1eO+vs7gtIlvyOo W+yHT1nSD+/fyxNoMk5B+rV9j/QYHhNZp9Tfzk+Q0DfFXT8cMC+7HJ2CUrKP EA8HTofU4f3L3z7wnUv6wL0/iVnI+FIQc16ibWNKFnHj1IR7ciIZvWKyYRTA 61xy9gQXS2AuEd27qUP/BRkNebzoNBCiogrPQcbPAypI/cTpY56vSWhF+y2n N+xUJHuu3fdyuzHyVJG7VDxE+qePurxh697/t4/6fOETqft6FHS7MJjOR1Yb PX5/Xzn4NRl5OesTSQK4Lqcpknk0LNDB0WWhYquG0Oi605++D40gZ2HTNSqa h9Hl+ZTEDzpDyC+Bs9d7ExVdCnM667vpGBJvUu3b2EZCH3k1mLrx99L8gi7c JjAY8ap+suPG87av9YTqtpU4D6cr+J1gi0LFXIcuNYyS/ulbTl/StyyyTZnD 0o+CUuPoPN4aZKM3cyXSenFkpCYmoB68j4J2B1yUtpjOQxVPH3IdrycjCWse Fn4+CppxTRuSNX+IMjtVKr7PklHruU3NUn0jKOXj3F2xvCI0xeX88qX0EDrs 8HQZtzjOw+krQu16zqLqBIcvxXhdjdlXiRF4P5J3ZeU3LrtrSHdeOoobzvGy S7fI433ro+siW+lsE5HwAVXhNzX/9gm3L+kTrqyd+/zmGwU5lEqvqpV+jDYF ivZuw9+Ls1zNoMk7nJcy2xIeXS5BPemPXBOmSCh/zT6toicUxLWpwXK1dgXq VT3Jo8JMRl1vqU8FIynIvbfVsDe7Go1OsK84IUxGkfQVpQb4e0wNndYo1q1D 4momN1ZgD9wdHo9SxnXQlSo9nDNyDKUFXDpejetgKuWXaaQ63j82mXl3mAcj z+NOy7hyScib31tFzYCKHN7yvZXziEIlU0f2RMaT0NbxRJfT9riujYVPbjt9 HdH1pHhcDCOhuyvbs9pOUpHuz2zeiTVJ6DWzdMgWexKaWuzvPbqkv1dsfT5Z 8jEVOV3eH3kt8BEK1mTNff5lECWeO09KrqciFZVht+UWT5HRN+VJ7/pBZFV6 syOunYo8ng04SEyXI51jw0krEwaR9clRrsZXeJ/yp2j7L5Ea9Lxn/UV0fBCN kOpuib+gop6uwhvn79cj2/YO1gWlQTRpZ0Grg0x030VwHUTZfFRaHfzbN2ux pG/2+mL/Z9hi/6fGYv+nvnfVeeDduHbrL+D90KbV9cA7adSAxnt5WIUj8N6a fZjG+9++R/0lfY+6+xhsgffBmLlfTZh3Bg7GI8B7x1HSSuD9C9frMVbM+zMO 0Ubgvb8qqQN4l25nNf+KeReS2uMGvL/Z8oPG++TOMrZwzLuyNHEReP/bN5h8 w+j/6xsUGmqWBN7XZG1Wn5HRRq856lWAd2rwgSrgPdR6SqoTWaDTATvCgHdO xX4a72LTLiZcmPd+LmMa79Ilz7uBd9dxz7YTmPcC91ky8K5BkVsOvIt+ZVS1 xrwv8wtxAN5jVlqpAO88tmNVHpj3FlR7GXj/rz69KRvnFcC7FZNTTRfm/YwI VRl457usqAC8v1jjKnkA8y6S4SUIvGct06YH3j38r7ySwbzf8r72HHjn1FOr Bd7dlikfEMW8Z958+R54n3YQ0PiIuW7RZG5tNvBCdE0sMrTzf56Hv7mwBz51 h5nbYg9MXXz3HTzQc+XbdvCA7VfFGW7sga+z9hfBA0l6s5vAA9sX3l4FD3gm HNoMHli22C/XsaRfLuruw37wgOixuPYa7AER3d+T4AH+ApMu8AB9aeVa8MDt rD+nwANcwR/lwAOZ/gzNq7AHOGd6xMEDU/vP3QEPPEgY+dmDPaClwLoFPCDK GnAPPEAV29X4BHtgp+t4EXigqUbBrwh74J3fgbS1b11Qe6pY8HbsgX0v+kzA A55KzB86sQeMO5oYwAM7rp1SAg9wpak6yGMPsNm90AIPhOKyCh742hYYI4o9 YHJQyhM8kPjiUiZ4YMh64uhn7IFEQfMz4AH/xT63rMU+N7fFPje3F6u7wAMj Qz77YrAHrvu+qAQPyKihdvDAh4c/FRmxByLoNJl9sAdG6GZLwAOTp8/uk8Qe eFKa8ww8cGWz/kwD9kBKqkE+eOBB4K9c8IA711l/8EAyxU4uEnug562pDHig VlbuAXjgx8TZg+CBrEerPcADiovvx2uXvB8/uPh+3G/J+/GhxffgYYvvwWuW vAc/s+Q9uOGOkG59vH5W/7G/IN1pTGw7kpEuU09CR5lfmD/G+SfY3SdA+0ET UfxUhrmtGu/72knGytvxc4U3G9praxPXJb41vmkkoS8/+TeUCY2gwb4v1s+N nhGvGxOPLh/F+zud4C/we+fGhS9z6hJyVS3LWRvg984rRiTkY8eH0VcOprbb 7F7qR6Rid983G0Yp48raMD4x3BEpoa2NhNnOd8H4Z/Jzt8H4MbJOY81Gz5BS YfoBGJ+5hOcD3H/3t7NH9ncao3o7/RS4f/MfhCPcf9MIuqzzoAlx5jaQX+L7 1+5leQWfZ6lhX8GBn3d+6GMOfH6SVd8BPm+7Juc0/jxxqUxjBD6fz/nZCO4n mku73RY/b2O/2HO4H/HdbSJwPyTXiEF8P4RV+kNzuJ9NbzaMwfMelitP6trC WCVW+a6F9ndgBJp2wfO6lTCqbRL0qpJ7Mkd7Xt8cby0Yv1RCZ1IJP6/Rpog3 MH5G0MaNML5J9JwLnk8kb6Z/BMbn617TC/fPm0s1NsLPW2Vw8hbcf/zew5Zw /7zzZyLx94XYrY2Xw/f1f9UNs2I= "]], Axes->True, AxesLabel->{ FormBox[ RowBox[{"cos", " ", "r", " ", "theta"}], TraditionalForm], FormBox[ RowBox[{"r", " ", "sin", " ", "theta"}], TraditionalForm], FormBox["u", TraditionalForm]}, BoxRatios->{1, 1, 1}, PlotRange->{{-0.9999999285713279, 0.9999999285714286}, {-0.9999999285714034, 0.9999999285714034}, {0., 3.1097879046671464`}}, PlotRangePadding->{ Scaled[0.02], Scaled[0.02], Scaled[0.02]}]], "Output", CellChangeTimes->{3.4129669420650296`*^9}] }, Open ]], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Plot", "[", RowBox[{ RowBox[{"u", "[", RowBox[{"1", ",", "theta"}], "]"}], ",", RowBox[{"{", RowBox[{"theta", ",", RowBox[{"-", "\[Pi]"}], ",", "\[Pi]"}], "}"}], ",", RowBox[{"AxesLabel", " ", "\[Rule]", " ", RowBox[{"{", RowBox[{"theta", ",", " ", "u"}], "}"}]}], ",", RowBox[{"PlotLabel", "\[Rule]", "\"\\""}]}], "]"}]], "Input", CellChangeTimes->{{3.41228170340625*^9, 3.41228173115625*^9}, { 3.4129669623150296`*^9, 3.412966995580655*^9}, {3.412967039768155*^9, 3.4129670623150296`*^9}, {3.412967119768155*^9, 3.4129671301587796`*^9}, { 3.4129672829712796`*^9, 3.412967286174405*^9}}], Cell[BoxData[ GraphicsBox[{{}, {}, {Hue[0.67, 0.6, 0.6], LineBox[CompressedData[" 1:eJw12Hk01c//B/DrWu5cCdmSECqfpGyJEma0SilSkhZLttJHishWkkQoobKV y5V9Ddm93/a1QrKHhHT7JEtarN+55/x+f815zJkzd+b1Puee52tkra+esKVS KBRxDgqFPRoc5t+3IEsnV/y3PukZBmhPofcUkKaTvgFDyq3Y22S/PReToJM/ v9hTU7ClQs8c2SRGJ5tL3dZcwub/2/BHVYhO1n4eshHCXrHRSIb8dPLpyac0 5hBAU21JJoa8dNIuLI22HntYW5jjLA+dHPLa6+Y5CFB76p1sByqdLPGIt6/6 CFC1yNRZt2VAlnYKzP4YAOiV7wW6/zwgnW5OqvFgM/9rff34FyCp87H7ufoB ijTbYxM/A8iBGXd9Vi9A92rT1mRNArIiu9equAcgNxVxopQFSDNlUOTUDZAZ mFvXNQJIMsyqPLIToMOuFxs+DwJy96J7A9d7gLSG212n+wCpWitVe74dIMni 7Hd87wGZL2xn1/IGoNWbpHwk3gGSYvnJe7gFoOVHwVu3tAByp46/3VATvp+9 w719NYCEpw3zYuvw/d53qRkTgBxtTHp2pgbfDx4YvlAGyDpXh7PUKoCS1srt 8cwHZPXQ9XjRcoDsG/qncpmA1DYLf3wkD593h8GLynhAnp150uyQDZB+fPGR 1lhAdv7QsXTJAGir+5PkLxGAfEe9zX3iJUCT8sfPSfsDsqug3xBG4fsHVDcE 2wDS3NlzTskL7z+jciPaEpA3L65/fswd738hXi7lHF6v1dtg5YLvr+HtU30S kNF8YsdsHAFaGtu54+9+QD7oDiLHzAHyP5D2wm4zILOl0401dwFEBnsabZAF pC3VOsRyB0CL7UeoPZKADP/0fcRPCSCXC5O2h0UAeS5PZbxgE0DW7ju2b+ME 5BY1Q9qAIEAwraJsephG7m1un34xQUPzfB093nE0Un20apaIoqFrnfNCEcI0 svXFZqu1gIaenjhuHilAIzU4PupocdFQeRsz4ckqGjlziHXfikJDPG+OqkRx 0sjcbwVj5X94UFzdC8PnszxkkH+5MPMrD2p8vTcw5T0PKS+o68fXyoOkox8s lUXwkOG2T8pUw3lQ83mJiVFhHtKf+8ri+fU8aKkyPVdrHTfZesRhlYIYN/r8 avqxMZ2L3Cq15+4jOhfSSODpDF3FSd5J+NmzkZ8Tact1KAX/4SBXJpS9eeY4 kKQXv08Ii0KalJ/ROj5JQW1xqmZ2H1eIoGJNu8juFfjOIf/LzrIlosdlxzXP yiWYrNC+y6higUjtvNWhVLkAVWLanK83/SVcl60OF9T+hbIqOn1iGb8JPTO1 MPO835BVeoCbJ2+OcJvgXxpLn4PrHcus3ENmiQdh9mOCj2fhcrPQy6lr00Rm t/ghHedp6AL5Tl76PUkk1TD2NE1NwuIdb8i5QhYxG5Ix6l/Dgjlr6nPXVowT 1y+qbrqTNg5dtKI5da+OEONB9jv6/Ueg1j0L/YnLA0Sc8PRS/b4B+MNh8dHt wE6CEXDqe2x4J7xbG6sF/zQQw6v4AlXkG+HE290RtsUNhO9ln+2NAw3wWG/3 t+CbDUTxfwnTmyIaoMSk8POeP/WEuJLoKa2Vepi7NmTl2t86Qp9/q736hzr4 8bJ3bdJ8DSGuFfdm0KsG7r0hIdVSWkNEjXo0hqjUwNTbxTemPWsIs/LRoL1j 1dA18qe87kI1MXE7PKPvWDXkrbwS1L1QRVDkZRvNNlZBJ7nSOJF5gvBta7vl nlUBd2v+MrTyJAiZRUlzTakKyHVUbSVrvpJApT6lDaHlMPZGutWhhQqCvPjT 89G1MtjYGCPvuVhGCCKQsfNACZS76pU7tFxEDDMjX/ZtKYTf7xZZbbtdRKDk DVWcmQWwOGpWyGPlNUF5aDzcrVIAj1c73hCiYL832VgE86G36DmtAxwFBBn7 cEe9Sx48tDXq2+M7+UTu8cUT5dx5UAh2xg1y5BOCs1JP66NzYZrD0RV36isC ybiwwsNyYFeZdm06Zy6BiuUii3wzoaSH9eAMXw7BSNhiL9OaAUM8j6iHCWUT MrGv+nUkM6Cjj9Rws1QmYbkkyzXRnAb7bvFoOGzMIMj+u+pxCmnQwPdHMLdC OuG7/t0vk9BUuPVulSZSTyXQm19ha21SYIx/eujH3SkE44hl5cHuZMgbEPHZ EyYTaK2wLHk8GbICbR8VGiQR5H39b+1GL6H5g2NjJ4yYxPCVSe6g3iTYHKy5 Z+pUIkHJvVjYYJ8E0x7Sv2y1YhCkybC50BMmVJMZ8wh784IYjqmY01RnQqGN RZtbeuIIMsPxknhvIpzZHNTOPRpDkOYxA5V3E2H7lrM+6EcUwTAwqN+pnghz FbcreM0/JXwVvb4FsBJgmNJKZyH3E4KyQjlflpwAnVXbfacEIwjfWd8b/Q4J 0EiduU1R8jFB2j7tnlRJgBZOrNyWYw8JipfMlcVlBpR2fQj0bB8Qlm3Flrzv GXDQQ83ytVcAIZNgIi+dxYDPb3cVKYb7EaiG7qwdyoDFvHPSe419CEYrn9ol FwbUFNN5u+3WDUImuY6RYsGAjvt4F5RMHYnhRimVeWMGbCtQzweWpwlkOhtu bcCAna6Zump5EDKUi0s/6eP93Q98NYq7CBny2t3uhgxolGtep5NwDVJME003 mTFge5KQmImrB/RNvDM25sCAaUdtdxQwfeGwpcrV0tsMyDpY1a8b6g9Jrj3S 8XEMuFVPyr/JLRD6VnGfDyPwefZ4bDtpGQIZk1FdQRMM2BVz+fKPTWFweO6Z e8DaBPjrWVRlwbpwKBNufdX3aAIUe1Iv5MkfCWV4LVWv3U+AmuE/7SDnU+i7 1tXNuDEBmj2SK+P68wwO8z/XXSeQCG+GGAk0/xcNKaOlHcTZRFgckFl0sus5 JPfemffjYcKeu32rJFrioeWauy8e2DChN+LK/THEgKRc245DjUz4XEeNq7Az EaL5xMEsRhJU0j6cvfYdE8q4SifriL6ElVqWZp5NSdD3SXyj4aOXcFDzYSas TIaU1L9B+RHJ0EnjpWlicQoc/r2z96tUClxWL6dw56dCGSuZb1ZZKVBajXWy OSUdkiotJzr6U6HFtoNLJx9nQzShkf/KNQNqRyU//MXIgQzqTLCxRibk8+MU PGqWC8lkMabjUib8+v1iwnf7POhrH1ebFJsNE+s21arcz4cMzlTBIN48KHIj mV5UVwSR5eB43VQBpGaYdtw3LIaCjoH7H7oVwqlhnlizD8VwmOZRJ7NcCN8c td82P1oCGTGcR6yFimDApi3HdbjKIbpHsu4blsDFryebrWRJ6FxZR2GtVMBZ riwlA1sSDru8iIyJqYSsDdwRamkkZBzaPCagQcCeU4VnOVWrYNS0mu09TRIW Vol+T8IpxLnb9sIbF/x/GN0lMGFRC8Ulo4xMZ2vgJ32zU04vGqGgvt282Ggj /JkDc8T3dMIr3k157492wr6X0k7TbQNQ5eeagws5A9DLqUz/VPwIrI4jrKLy R6AZQ/l0XOg4XOWZ3irlOQ7t7jdRh9pYcOTPa3HhIRas8VdUDGmZhMv2zLfu 9ZPwwpqxapEz09BD/d7QPdNpOKvVoPvJbRZ2d0es5/CehTlXV/+1dp6Ddxc6 H1RfmoNct8fvWEf+hsqv9H45xvyGd6I3Hl4b+Rfui7gvmRL2Fx7huq1QG7QA bzG3lywELsDsw//2TKYtwQUXV4mcrCW4K4aoe/tyBR6wnv1nS/wKzLbuQGLj FESf5t/d+ZWC7GROKur95EDoW9LohykO9OozrfDgFBX1hnS5lkxTkYEIt3ww BxdyXZ8IValcyM1AXSOdwo3k+Z94Wi9yoabUmRN189zo3O/Wg5lUHuTgOm+6 gZeGNpTF75lf5kFZZ+8riPDjnKKr1d5ApaGZvSKLQIiG7Lx/vormoSGvNUoJ M+vwqMTZZoDXPcy2+lanQEPqIYFnx6RoqHCi8faVwzTkUgYV+XVpiHr+WWpJ IA1Ndvv+Y+NHQ4f2b/LKDqEhCaqV0IcAGgpRzDNkhtFQu+XnGINgGhKdb54J wblqKvPpyt5IGtrybFnbMpWGzEeuT9ok09Cxdtt2nkYaSjJzsNjfQkOxB9Tn TWgAmfd7LOaL4rx94kLj81UAOZwyzMqRAOihReDTLwI4F1+PnUzeAJCfx4Ca lzhAvxKKVQMUALqc5e+YiEeZoISWv9o4X4p+GJg6AtDr1Wmf9awBUpdbSdcy wjn6zOr8EjuAlJQVPPxP4tyfo9q6CedPucM+ouLnAXorRCvpwPmU12fzMegE 0AkDufhb/gBxPTguGXQdoMaLA4N3AvE+Tz1YHW4AnZtIU3ENAWgm902A3W2A WJ2mKxsjAeobvUGEhgEUfEvEIDERoM7p+NBuPH+89aCIYDL+neWms7LRAOm2 NlEvpeG8Li79pyABIIvqXo++HIDKN+vXL+OcrdNASs+8wvdQux6pnw7Q7N0v MrOFAKUfrVcZwPO886mPc8pwvj8ztby5CKCKkAeqlysBemEn8eYqnrf3u/qY D+f/cF+nS5y1AM3/CBCh1QMUEhqladiI66p35M4FPAbEVHM/a8X1ZNrpxTUD 5Fkglrj1A0DJFbkuTW8Bcq1Czq6476lrKjUobgPI6e1l3UrcR32JXdAN6cDf qT+SD4wAdKpXgO8A7nesJyr7jMcBMtpufW0E73NubiI1lgWQ7TVtNRvcH5lS hd3HJgF61tEt2oz7JyMBnQPKswAZTzp+Ee4DyEDSXtjjN+5DRrTd9HD/tV/h 8afqBYDGDVKfnMD9ma5GWQ4fhY74t6lKHcLn2LVvzMeUi44CyQcT0rjfUzMS OMoAdPR0W2J3L/a287slWHx0lCqY8tYd94fyly9O7FhDR1f/Cr3+gy3jHvra R5SO/qTneJ7D/aWEf5F/wzo6atsft5qJrTyUazKB/Zvv8usk7P1a6XJ0CTpK cgs0S8b+dyqONMCunHsdmIZNnvNbfIPdLNsblYP9ocirZRL7ustWvjxsltCN GIH1dDQ433LzFbZwk/0uY2xfjxWdQmy7nYaundhtX+RvlmJ7hR3cN4fNFfWn sAw77BsUEpOkoy4Zie/l2CUJarmnsUXCjx4isPn4xf/rw6b3/JtRgy17aU3Z AjZTpSK/FlujlveBpBQdHRM+V1iHbeG59M8F7EGTwKQG7FfjIxc/YSv2Rau1 YDfoDahRpemoP9qGm92vD8R94NiInca81c42t0ljvA32vAfj1Ft2/bKrnO5h 6+5OXf0OW4leppOMLbNlpZJtMyKr/wt2g3fM6nZ2/SRS0sEGOpLuHkxn2+8G w0MBW9fgul4HdoZixFpHbF+7APP37PoGhIwHY/Py0D6y3fnpXmEm9vaMLrNO 7OVnN00msYPnrLU/sOs7e01OQAbXL2JDEttbjjlOK2MHyytyd2Frp9mQRtgd mfcs2DbmuvDoGnaNnHI+23YWpy+EY/vd+4fSje1ZarQ9H9u5w+kg249EDRbf Y8vTuAPYTnLe1/IT+6Ysq5LtkhbtGFFZOnLbID3N9lt5jUsa2JdWGJLs95CR O8q7TmN3Etf12P49sIV2k73eIsKCbb5dcl1R2Pofqe5sy0Ssf1mC7b2r6j7b OydFXPuw/ZzfPmb7/95b0P+/t/wPwjMgMA== "]]}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->True, AxesLabel->{ FormBox["theta", TraditionalForm], FormBox["u", TraditionalForm]}, AxesOrigin->{0, 0}, PlotLabel->FormBox["\"BC: u(1,theta) = |theta|\"", TraditionalForm], PlotRange-> NCache[{{-Pi, Pi}, {0., 3.1097880986786772`}}, {{-3.141592653589793, 3.141592653589793}, {0., 3.1097880986786772`}}], PlotRangeClipping->True, PlotRangePadding->{ Scaled[0.02], Scaled[0.02]}]], "Output", CellChangeTimes->{3.4129671315025296`*^9, 3.412967286861905*^9}] }, Open ]], Cell[BoxData[ RowBox[{"(*", RowBox[{ RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"--", RowBox[{"-", " ", "Problem"}]}]}]}]}]}]}], " ", RowBox[{ RowBox[{ RowBox[{ RowBox[{ RowBox[{"3", " ", "--"}], "--"}], "--"}], "--"}], "--"}], RowBox[{"--", RowBox[{"--", "--"}]}]}], "*)"}]], "Input", CellChangeTimes->{{3.412967376424405*^9, 3.4129673784087796`*^9}}], Cell[BoxData[ RowBox[{"Clear", "[", RowBox[{ "alphalist", ",", " ", "alpha", ",", " ", "b", ",", " ", "c", ",", " ", "Cmn", ",", " ", "u"}], "]"}]], "Input", CellChangeTimes->{{3.4129675945337796`*^9, 3.4129676130962796`*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"alphalist", "=", RowBox[{"Table", "[", RowBox[{ RowBox[{"N", "[", RowBox[{"Table", "[", RowBox[{ RowBox[{"BesselJZero", "[", RowBox[{"n", ",", "i"}], "]"}], ",", RowBox[{"{", RowBox[{"i", ",", "10"}], "}"}]}], "]"}], "]"}], ",", RowBox[{"{", RowBox[{"n", ",", "1", ",", "10"}], "}"}]}], "]"}]}], ";"}]], "Input", CellChangeTimes->{{3.412967458268155*^9, 3.4129674619712796`*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"alpha", "[", RowBox[{"m_", ",", "n_"}], "]"}], ":=", " ", RowBox[{ RowBox[{"alphalist", "[", RowBox[{"[", "n", "]"}], "]"}], "[", RowBox[{"[", "m", "]"}], "]"}]}]], "Input"], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"alpha", "[", RowBox[{"1", ",", "1"}], "]"}]], "Input"], Cell[BoxData["3.831705970207512`"], "Output", CellChangeTimes->{3.4129674759400296`*^9, 3.4129676200337796`*^9, 3.412967687424405*^9, 3.412968020611905*^9, 3.412968853893155*^9}] }, Open ]], Cell[BoxData[ RowBox[{"(*", RowBox[{ RowBox[{"Note", " ", "that", " ", "here", " ", "R"}], " ", "=", " ", RowBox[{ "b", " ", "to", " ", "avoid", " ", "confusion", " ", "between", " ", "r", " ", "and", " ", "R"}]}], " ", "*)"}]], "Input", CellChangeTimes->{{3.412967516424405*^9, 3.412967544799405*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"b", " ", "=", " ", "1"}], ";", RowBox[{"c", "=", "1"}], ";"}]], "Input", CellChangeTimes->{{3.412967480549405*^9, 3.4129675110025296`*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"Cmn", "[", RowBox[{"m_", ",", "n_"}], "]"}], ":=", RowBox[{ RowBox[{"(", RowBox[{"4", "/", RowBox[{"(", RowBox[{"Pi", "*", RowBox[{"b", "^", "2"}], "*", RowBox[{ RowBox[{"(", RowBox[{"BesselJ", "[", RowBox[{ RowBox[{"n", "+", "1"}], ",", RowBox[{"alpha", "[", RowBox[{"m", ",", "n"}], "]"}]}], "]"}], ")"}], "^", "2"}]}], ")"}]}], ")"}], "*", RowBox[{"Integrate", "[", RowBox[{ RowBox[{"r", "*", "theta", "*", RowBox[{"(", RowBox[{"Pi", "-", "theta"}], ")"}], "*", RowBox[{"Sin", "[", RowBox[{"Pi", "*", RowBox[{"r", "/", "b"}]}], "]"}], "*", RowBox[{"Sin", "[", RowBox[{"n", "*", "theta"}], "]"}], "*", RowBox[{"BesselJ", "[", RowBox[{"n", ",", RowBox[{ RowBox[{"(", RowBox[{"alpha", "[", RowBox[{"m", ",", "n"}], "]"}], ")"}], "*", RowBox[{"r", "/", "b"}]}]}], "]"}]}], ",", RowBox[{"{", RowBox[{"r", ",", "0", ",", "b"}], "}"}], ",", RowBox[{"{", RowBox[{"theta", ",", "0", ",", "Pi"}], "}"}]}], "]"}]}]}]], "Input", CellChangeTimes->{{3.412967500893155*^9, 3.412967508705655*^9}}], Cell[BoxData[ RowBox[{ RowBox[{ RowBox[{"u", "[", RowBox[{"r_", ",", "theta_", ",", "t_"}], "]"}], " ", "=", " ", RowBox[{"Sum", "[", RowBox[{ RowBox[{ RowBox[{"N", "[", RowBox[{"Cmn", "[", RowBox[{"m", ",", "n"}], "]"}], "]"}], "*", RowBox[{"Sin", "[", RowBox[{"n", "*", "theta"}], "]"}], "*", RowBox[{"BesselJ", "[", RowBox[{"n", ",", RowBox[{ RowBox[{"(", RowBox[{"alpha", "[", RowBox[{"m", ",", "n"}], "]"}], ")"}], "*", RowBox[{"r", "/", "b"}]}]}], "]"}], "*", RowBox[{"Cos", "[", RowBox[{ RowBox[{"(", RowBox[{"alpha", "[", RowBox[{"m", ",", "n"}], "]"}], ")"}], "*", "c", "*", RowBox[{"t", "/", "b"}]}], "]"}]}], ",", RowBox[{"{", RowBox[{"n", ",", "1", ",", "4"}], "}"}], ",", RowBox[{"{", RowBox[{"m", ",", "1", ",", "4"}], "}"}]}], "]"}]}], ";"}]], "Input"], Cell[BoxData[ RowBox[{ RowBox[{"graphs", "=", RowBox[{"Table", "[", RowBox[{ RowBox[{"ParametricPlot3D", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"r", "*", RowBox[{"Cos", "[", "theta", "]"}]}], ",", RowBox[{"r", "*", RowBox[{"Sin", "[", "theta", "]"}]}], ",", " ", RowBox[{"Evaluate", "[", RowBox[{"u", "[", RowBox[{"r", ",", "theta", ",", "t"}], "]"}], "]"}]}], "}"}], ",", RowBox[{"{", RowBox[{"r", ",", "0", ",", "b"}], "}"}], ",", RowBox[{"{", RowBox[{"theta", ",", "0", ",", "Pi"}], "}"}], ",", RowBox[{"BoxRatios", "\[Rule]", " ", RowBox[{"{", RowBox[{"1", ",", "1", ",", "1"}], "}"}]}], ",", RowBox[{"PlotRange", "->", RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{"-", "1"}], ",", "1"}], "}"}], ",", RowBox[{"{", RowBox[{"0", ",", "1"}], "}"}], ",", RowBox[{"{", RowBox[{ RowBox[{"-", "3"}], ",", "3"}], "}"}]}], "}"}]}], ",", RowBox[{"AxesLabel", " ", "\[Rule]", " ", RowBox[{"{", RowBox[{ RowBox[{"r", " ", "*", "cos", RowBox[{"(", "theta", ")"}]}], ",", " ", RowBox[{"r", " ", "*", "sin", RowBox[{"(", "theta", ")"}]}], ",", " ", "u"}], "}"}]}]}], "]"}], ",", RowBox[{"{", RowBox[{"t", ",", "0", ",", "1.4", ",", "0.1"}], "}"}]}], "]"}]}], ";"}]], "Input", CellChangeTimes->{{3.4129679691587796`*^9, 3.412967998424405*^9}, { 3.4129683464712796`*^9, 3.412968346986905*^9}, 3.4129684565650296`*^9, { 3.4129686332525296`*^9, 3.4129687131587796`*^9}, {3.4129687604400296`*^9, 3.412968839174405*^9}, {3.412968891768155*^9, 3.412968897330655*^9}}], Cell[CellGroupData[{ Cell["\<\ Plot of vibrating membrane at different time, starting from t = 0 (the first \ on the upper left) to t = 1.4 (the lower right corner) with time step = 0.1 \ (figure go from left to right, top to bottom) \ \>", "Subsubsection", CellChangeTimes->{{3.4129693968150296`*^9, 3.4129695925025296`*^9}, 3.412980520830655*^9}], Cell[BoxData["."], "Input", CellChangeTimes->{3.4129805246900296`*^9}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Show", "[", RowBox[{"GraphicsGrid", "[", RowBox[{"Partition", "[", RowBox[{"graphs", ",", "3"}], "]"}], "]"}], "]"}]], "Input"], Cell[BoxData[ GraphicsBox[{{}, {{InsetBox[ Graphics3DBox[GraphicsComplex3DBox[CompressedData[" 1:eJxknHc8lf///w8S2hsZFUpCJaWSzvNkhTSpUGS0N6GpkETZRUQD0SCU7PGy Izt77z2y9/hdV9er7+39OT//nNvtup3bdbye1+P1eNyfz+uca53hjWPnWGk0 Gh8XjcZGvPJqBUXZSdyi55V1LeyYv2yvnse3Xzml+/a2S9K91qt+B0kb+/Tm HUfpF5aVPoldY0Xf1F4xK6KaAgl7Nu1o3mFAD9H4dvnsEVe6QcwK6ahr2XA2 wpmjtOAS/Wpn8DzbRi+6erpouIjqb7B9NdHdtMOY3il+gnt+8Ht6u2R6zrWq UtDRlCw9/diMfivkx/48fX/6Yw/D1shrVSC5VB+VFNyle0Y/d35T84G+Zpb8 qwOWPLdPhwQf0sUgVPH0ngB6TXieg4hqI1xOb8xs2mFF3xa9/tFg4Ae6+MU3 vKpuzVAs/GDv+9OP6Uqf8v7US/rT7/JfDbxW1Qp065XfTz9+Qi+QEFE4kPSe /rNAVtpNpAM+1Yds4P3ylO4tfGoRa+xr+oonXEmR17pgGah4lxTY031rmrnv XXCjG+4uV6+K7IEHbxoWu40+p8u925+qdceaHtITWDE7+weaJu/ZHBJ0ot9/ J7XFtkd+r+U8bvPb30zoTz/0OrMuPUp3v7/lW2atJZ21KKrwZ9E30HfwQm+U XSA5+Eob6+YkOMotIfezKBnqby/d+Ub5PZi5G+rt1SiAdUoPnL8k/AJXsRNO XZc+QcpHVc/zOuVwd/f5/oyiQvC9ljvgoxwGm1X7085p1IHBkUXe0SqlcDfj hqCi1g/oGTCz0drWCGoXIhW/JFTC0TXL1LouRQN/p95pNq8m2PZQr9d7Wx1s uvPDzO1+PNR1N3Z1DTSBoxpbTkZRA1hdDCrwUU6CuZoKNcMXmoDlRNl7WNQM PS8fnL95OAUUzB5xhc5pBDODILNolVbQTj44paCVBg9SZITe3a6DzquP1KQe t0NGj6Abt0EGLKtuYwStrgC9OxprviR0wrbVfaJdlzLBd+AybVatEH4/Fh0S GuuGt8rJCYkmvyCs4Froj9PJoOg8mem97Q9w3nLTcLufAzwHBc58z7aiT5fd fndD2Zi+bG9j5G1/ffq9M9d2W5q40EukvXe53g2DXwWfRw7Ev4Nfm7vXX76T DxWRF0Jc7iaBznGTbrX4UHiudbBt1KUOMouskrQiM0Gs4WfvztwoWKMTcoZ2 vg1Ojx285HK3AAJenbigFo/A6BPXHvnxHiiee8pk6FUxLPk4cCOkJBVCVDo4 9hv1w4GVF+9rRZbDIVbZ4J25PyFRtGRwOH4AUoXNbOKLq8FB16o9KS0b9js1 583jGQQB3mRll7v18Cs6U0QtPh/mBJy+f+rlAGi/338gxa4R5syzC+uoKARF s9HrHnv7wV007/DQq2bwjwo6FFJSBDPne4RaV/VCYYim5oaPrSB/Lr/bpLAE Fq43PT3L0g4LZaq0tCLboX7Z4LOduWXgNn1Iu9KxHlQSDHSfpXfCo6RVYlOZ FXBLI+d8p38BWCu2G8QXd4PAddmfSWlVkN4kG+C9xJUuFRudqTZ5jT5aUJxa 1n6BHpe79eA9v1d0X2OW3fGvgqFBtyX4QG4gmHPZZ1Y+JfY5n6hq3Kt4SHn3 tkctNxIS1jhrvLvQCoOJrbI5xumgpnKOdYw3GVy92+O0TftgV9/uwthXORDO mHRUy80A9Czk4uuBIUAuGeHFtYXAv9uV941lDiTPq41k3zcGhmJ9M9nGJZDq +eL3KG8hhIU+brsnNgHsKbxqqXMqYPSlHo/vYBFMaZosuh8+AR91FNxjX1WD hKuYnlpuKey8fKVqzcw4BNyV6dNaWQ/6jkP+g4EVYNJ7cv483jEYUcp2L65t AHd71OFjWQ3cXBppLKzDoLJMf8+RT03w68mzLco6dbCtjUXzZ2ofeNUO1Wcb t8Bs0pfYUd4GeHPwgYK1aBt0fbG33b+nDXjBRTfHthFs2pGDxNEy2HNbUCJ1 TgdsSzCj+Q42gZv+/WS93lf0uMahY2R9Y83jhQ4Q9S6T4Bpb5P+GrszF2EfW 92tIhRNZby9dc+EW4WoIOTRuRdbX4/jsW7LeDZ5zVy2J7AJd9c/fRon6dnWo 3Cfr/WqjZnKx0BAY9R8XIuu7QGyZaBxR7wmdLnqVyThc8mB94UPUd9WPax1k vQ+eeeExfnYaot6UWZH1DdQ4BjlEvdniuPYOJMyCbJ9k7HuivjsHZdzJet8R sJ9zS5bGSJC3GVAl6vvTja+LrPenBSZVxj6zwHCv3ETWV4LXcq02UW+dX1yJ rsrTkNq21Yis79BFk2yy3k+PGjwYsxgHZdmn3kpEfeOjz5qT9b4163JxUmsI zmX0XiLra8N5cl0OUW+nTC4jVtFuCPzDO5esr7qWag5Zb/5E5XeCl6qhlUfJ 7z1R3+Wf9twm660RoMLqv+UN3Xx5/nbSL5SrsxJJ/1hT/uCD53Jf+vpAlxk1 wi/WZd09QfrHY/11x5pE66Fsm/aQKuEXmw4o55D+wcL2hFfY/g8c5orYTvpF +rfDPaR/6JvSL0uGjcC2u3tvqBJ+sdVB4inpHwNsb9UG707B86HG4q+EX1jA t1ekfxT8Yl9vdJHGeCAhOiBD+MWvgR2fSP9QTcjXDY5nYVw/e2Ux6Rc8gbHR pH8ERm7h3SPOyjjjEyqhSvhFePC7s6R/qG/Kei39g4WxsXNchPQL7bmNV0n/ 2JcaeJ3fgMZYN9cn/CvhFzR9ETPSP/rSu7fSH07BaiG6POkXH2POW5D+8Vjx 0Z2zaASW0+sLZAi/OLj88xPSP+a/l5+TYPsHFuhYn5kk/GLoapcj6R/PdTOE jjbUAZu5SC8i/MIrQ9KD9I8W7sD8NKP39CG9a+YsRP6pbBC1JfOQb/wZp+k9 P3pumFC4D5F/b25yNZB5eHMHLVnmZgPwBrze5EPk35UfFgfIPAyy2NyW3NEH uf3+kx1E/tmFmQeSeeigO7RqVmwMGO9OtHoT+adRGkX7SeTh7KWX0oaSM/Ba qSpPnsg/Q83tIWQectmF6aafYmEMdZ2J6iDy7+bvsFNkHkqpp3tZ/WRlHHJr fudC5N+jI5JcPkQerhcZNZiWZ2No+mxP8ybyb3+bZhWZhz8VF+y8lcHKsPpj vusGkX+HNiz/TubhY3VffVfi/CHyMcHyRP6dOFdoR+bhmbih3kDxGahyn1y7 isg/3Q/OZ8g8dNpqw76Weww4Ova6dxD5d7bpoAyZh08FM9YVR/bBdjlLrgQi /64KLVgoTOThXHfxt7t76uGMc4qFC5F/xga/msg83MS9a53mZV966Ve3Fdc2 rNzji/kuOXDLfL4hP3plCIvVa3FNucubKb5rdB7g7CH22Q7lvDIv8bNywZjv bhdpSAod6IfpH3w3zu+7LicSS/Hd+8uucpUfxqDJdftjL3FTuTzMd/x7xFef jZ6B/apVeY9k7so920zxnVdg3uPuTyyMYJr16vP7Hsopv6L4bmLfo01n+NkY nKdXSG8ItJJjoZF/9SB4KDDppg8bIzaqTctL3EbuzA+K70ZSOAb2CbIxri6P e7jgm61cAua79NEVc22DWBhrbjh9eCRjL8cnQPHdi9c6Nft/zEDhL4NfA3HP 5e4WUnzn606762wzBo837Og7t89Jrgzz3dzeT4Mxc/qBb9+c51eNXOR2yFJ8 N5G57/1DegMM9vYIbAh0lXPtpfjOeIY9kQ350vspPSeqYj3zYz1nU3pGzHrm pvSM/uk5GOs5i9Izssd6dsR63kvpGf3TM8tlSs+vKD2jf3qeh/XcR+kZGTPp WZXSM7Jk0vNRSs+IWc8WlJ7RYaxnG6znL5Se0T8962M9l1F6RnpYz85Yz2yU ntE5rGc7rOetlJ7RNaxnDqxnHUrPyIRJz2aUPyf+8+e12J+FKX9GQtifbbA/ l1D+jMSZ/Pkg5c8oA/uzIfbnrZQ/o3/+PIj92Z7yZ/QQ+3Mh9ud7lD+jbOzP atifr1L+jHixP3/E/qxL+TP658+HsD+LUv6MdJj8eS3lz4gF+3M/9mceyp/R P3+2wf68lPJndAj780Lsz/Mof0bDTP7MQvkzes3kz9EUbyTGY96owLyhSPEG CsW84YN5I4jiDeSJeaMZ88YpijdQD+YNL8wb+hRvoEWYN6Ywb5yneAPxYN44 jHkjkuIN9AnzBgfmjV0Ub6DdTLwRR/EGysK8EYR5g07xBpLEvHEa80YSxRto GPOGPeYNBYo3UALmDTPMG0YUbyBbzBsumDc+ULyBDmHeEMS80UzxBlqJeeM4 5g1Jip8TpzA/J2F+fkPxM2rF/Hwf8/NJip9RBubnJMzPfRQ/o4OYn19ift5B 8TOKxvycgvk5geJnJIT5OR3z8xmKn1EG5ucfmJ9ZKX5Gk5ifWY5T/PyB4me0 FfPzHszP/hQ/o/OYn29jfh6i+Bl5Y37mw/ysTPEzKsD8vAPz8yuKnxFrMsXP fpif2yl+RgKYn+0wP++i+BnJYH72wPw8SfWDiby4H3yM+8Fiqh9EFbgfrMD9 YBnVD6JLuB98jfvBDKofRNtxP7gJ94M6VD+IwnE/eBP3g4VUP4h4cT8YgftB VaofRNq4H/yJ+8Ekqh9EXrgfPIz7QX6qH0TluB9cgPvBk1Q/iBbgfvAA7gdf UP0gCsb94IILVD+YR/WDSB33gzy4H5xH9YOoG/eDXrgfVKb6QfQc94P3cD/4 iOoH0SbcD+bifvARNd9I9MHzjSA832Ch5hvIFM83SvB84wg130BDeL5hj+cb a6n5BgrF840GPN+4Q803UASebxzH8w19ar6BXuD5xpxBar6hQs030E0835DG 842t1HwDHcLzjXE833Cg5hvIA883BPF8g0bNN9Acd2q+oYXnG6bUfAPdwvMN PzzfaKfmG6gRzze24vnGaWq+gY7i+UYknm8UUPMNhPB8IwPPN+Sp+QaSwPON zXi+ged1ievdTi4i53VBy/mz/zOvQ0OMvr/zOpk+Odv/zOuQ1ZjL33ndeOPq K/+Z1yH7AjFOcl5ntuHg/P/M65CKpkEPOa/7eT7xv/M6pJ709e+87vTOzSr/ mdehIxITf+d1HOcWufxnXoc0PZU/k/M65UZppf/M65CEtWoWOa87Gxj433kd 2hz95++8LtlZue8/8zq0tdf977wuYrHjf+d1aJuInCg5r7t1k3Xxf+Z1aLtO 4995XVrOSZ7/zOuQjIvdEnJeZ+Af+995HZLJ2PyEnNctPfnx77xuYOuSFROc DTDRcGJxWUQIbDc8EV9GK4ZPY8fibx5qgqatjzvnXfgGFcOWm0c5iuBMkvvZ thctkNmnc3DTrXBoSvFOM9pSCKvsyhfoVbRBSNi2MNVHEdAtLr18S1EO5Bzm iygW7ISXN+ctv/Q8Cjbr3dYfdU+Hx9x6ugfOdsO9rY1mdq9igB4+p8tcLxZ2 171nT/ncC2f6Yso/+sfBsYX2RSIXfWHvtpOc3icaocfn5LuqL1mgJ+qXQY/q gqBYO4uOh81