(* 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[ 34319714, 568871] NotebookOptionsPosition[ 34296004, 568220] NotebookOutlinePosition[ 34302836, 568383] CellTagsIndexPosition[ 34301637, 568358] WindowFrame->Normal ContainsDynamic->True *) (* Beginning of Notebook Content *) Notebook[{ Cell["Graphics and Plotting", "Title"], Cell["\<\ Mathematica has a large number of built-in graphics programs for plotting and \ exploring mathematics graphically and for plotting and visualizing data. \ Graphs and plots are effective ways of conveying complex information. It is \ important to learn how to create and manipulate plots and graphics. \ Mathematica is very rich in its graphical functions\[LongDash]we will explore \ just a small subset of all its capabilities. We can get an idea of how many \ plotting routines are available by using a wildcard:\ \>", "Text", CellChangeTimes->{3.3960021210214987`*^9}], Cell[BoxData[ RowBox[{"?", "*Plot*"}]], "Input"], Cell["\<\ While Mathematica has a large number of plotting routines, no one program \ does everything we need. It can be useful to export numbers and graphics \ from Mathematica and operate on them individually or with other specialized \ programs. The number of different creative graphical solutions available \ grows geometrically with the number of different graphical tools that are \ mastered. Here, we will just produce a number of examples of plots and graphics... \ \>", "Text", CellChangeTimes->{3.39600071838099*^9}, CellTags->"mmtag:05:init.m__example_of_using_to_change_default_graphics"], Cell[CellGroupData[{ Cell["Changing the Appearance of Simple Plots", "Subtitle", CellChangeTimes->{{3.396154748175549*^9, 3.3961547533314*^9}, { 3.3961555711734257`*^9, 3.396155608446784*^9}}], Cell["Simple Plot with no options", "Text", CellChangeTimes->{{3.39598621117955*^9, 3.395986232114073*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"Plot", "[", RowBox[{ RowBox[{ RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{ RowBox[{"-", "5"}], " ", "Pi"}], ",", RowBox[{"5", "Pi"}]}], "}"}]}], "]"}]}]], "Input", CellTags->{"mmtag:05:Plot[]", "mmtag:05:Plot__examples_with_options"}], Cell[BoxData[ RowBox[{"Options", "[", "Plot", "]"}]], "Input"], Cell["PlotRange and PlotStyle", "Text", CellChangeTimes->{{3.39598621117955*^9, 3.3959862673511887`*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"Plot", "[", RowBox[{ RowBox[{ RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{ RowBox[{"-", "5"}], "Pi"}], ",", RowBox[{"5", "Pi"}]}], "}"}], ",", StyleBox[ RowBox[{"PlotRange", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"-", "0.25"}], ",", "1.25"}], "}"}]}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]], ",", StyleBox[ RowBox[{"PlotStyle", "\[Rule]", RowBox[{"{", RowBox[{"Red", ",", "Thick"}], "}"}]}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]]}], "]"}]}]], "Input", CellChangeTimes->{{3.3959805397032547`*^9, 3.395980555648281*^9}}], Cell["AxesLabel", "Text", CellChangeTimes->{{3.39598621117955*^9, 3.395986232114073*^9}, { 3.395986280747259*^9, 3.395986283766376*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"Plot", "[", RowBox[{ RowBox[{ RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{ RowBox[{"-", "5"}], "Pi"}], ",", RowBox[{"5", "Pi"}]}], "}"}], ",", RowBox[{"PlotRange", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"-", "0.25"}], ",", "1.25"}], "}"}]}], ",", RowBox[{"PlotStyle", "\[Rule]", RowBox[{"{", RowBox[{"Red", ",", "Thick"}], "}"}]}], ",", StyleBox[ RowBox[{"AxesLabel", "\[Rule]", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\<\!\(\*FractionBox[\(Sin \((x)\)\), \(x\)]\)\>\""}], "}"}]}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]]}], "]"}]}]], "Input", CellChangeTimes->{{3.3959806042337723`*^9, 3.395980615467904*^9}}], Cell["BaseStyle", "Text", CellChangeTimes->{{3.39598621117955*^9, 3.395986232114073*^9}, { 3.3959862994720078`*^9, 3.3959863014320107`*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"Plot", "[", RowBox[{ RowBox[{ RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{ RowBox[{"-", "5"}], "Pi"}], ",", RowBox[{"5", "Pi"}]}], "}"}], ",", RowBox[{"PlotRange", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"-", "0.25"}], ",", "1.25"}], "}"}]}], ",", RowBox[{"PlotStyle", "\[Rule]", RowBox[{"{", RowBox[{"Red", ",", "Thick"}], "}"}]}], ",", RowBox[{"AxesLabel", "\[Rule]", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\<\!\(\*FractionBox[\(Sin \((x)\)\), \(x\)]\)\>\""}], "}"}]}], ",", StyleBox[ RowBox[{"BaseStyle", "\[Rule]", RowBox[{"{", RowBox[{"Large", ",", RowBox[{"FontFamily", "\[Rule]", "\"\\""}], ",", "Italic"}], "}"}]}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]]}], "]"}]}]], "Input", CellChangeTimes->{{3.3959806042337723`*^9, 3.395980615467904*^9}, { 3.395980748889402*^9, 3.395980756285366*^9}, {3.395981210419401*^9, 3.3959812202957897`*^9}}], Cell["TicksStyle", "Text", CellChangeTimes->{{3.395986312175062*^9, 3.395986316820736*^9}}], Cell[BoxData[ RowBox[{ RowBox[{"Plot", "[", RowBox[{ RowBox[{ RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{ RowBox[{"-", "5"}], "Pi"}], ",", RowBox[{"5", "Pi"}]}], "}"}], ",", RowBox[{"PlotRange", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"-", "0.25"}], ",", "1.25"}], "}"}]}], ",", RowBox[{"PlotStyle", "\[Rule]", RowBox[{"{", RowBox[{"Red", ",", "Thick"}], "}"}]}], ",", RowBox[{"AxesLabel", "\[Rule]", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\<\!\(\*FractionBox[\(Sin \((x)\)\), \(x\)]\)\>\""}], "}"}]}], ",", RowBox[{"BaseStyle", "\[Rule]", RowBox[{"{", RowBox[{"Large", ",", RowBox[{"FontFamily", "\[Rule]", "\"\\""}], ",", "Italic"}], "}"}]}], ",", StyleBox[ RowBox[{"TicksStyle", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{"Medium", ",", "Blue"}], "}"}], ",", RowBox[{"{", RowBox[{"Medium", ",", RowBox[{"RGBColor", "[", RowBox[{"0.5", ",", "0.2", ",", "0"}], "]"}]}], "}"}]}], "}"}]}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]]}], "]"}]}]], "Input", CellChangeTimes->{{3.3959806042337723`*^9, 3.395980615467904*^9}, { 3.395980748889402*^9, 3.395980804338718*^9}, {3.395980864747794*^9, 3.395980968832753*^9}}] }, Closed]], Cell[CellGroupData[{ Cell["\<\ Controlling Precision and Size: The Mesh (And an example of Interactive Control over Plot Appearance--Manipulate)\ \>", "Subtitle", CellChangeTimes->{{3.39598621117955*^9, 3.395986232114073*^9}, { 3.395986340430147*^9, 3.39598635659687*^9}, {3.396155789569306*^9, 3.3961558512099133`*^9}, {3.3969684969081583`*^9, 3.3969685273389273`*^9}}], Cell["Mesh and MeshStyle", "Text", CellGroupingRules->{GroupTogetherGrouping, 10000.}, CellChangeTimes->{{3.39598621117955*^9, 3.395986232114073*^9}, { 3.395986366742632*^9, 3.395986381430113*^9}, {3.397040631075893*^9, 3.3970406365562763`*^9}, {3.397041090725046*^9, 3.3970410943953457`*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Plot", "[", RowBox[{ RowBox[{ RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{ RowBox[{"-", "5"}], "Pi"}], ",", RowBox[{"5", "Pi"}]}], "}"}], ",", RowBox[{"PlotRange", "\[Rule]", "All"}], ",", RowBox[{"PlotStyle", "\[Rule]", RowBox[{"{", RowBox[{"Red", ",", "Thick"}], "}"}]}], ",", RowBox[{"AxesLabel", "\[Rule]", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\<\!\(\*FractionBox[\(Sin \((x)\)\), \(x\)]\)\>\""}], "}"}]}], ",", RowBox[{"BaseStyle", "\[Rule]", RowBox[{"{", RowBox[{"Large", ",", RowBox[{"FontFamily", "\[Rule]", "\"\\""}], ",", "Italic"}], "}"}]}], ",", RowBox[{"TicksStyle", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{"Medium", ",", "Blue"}], "}"}], ",", RowBox[{"{", RowBox[{"Medium", ",", RowBox[{"RGBColor", "[", RowBox[{"0.5", ",", "0.2", ",", "0"}], "]"}]}], "}"}]}], "}"}]}], ",", StyleBox[ RowBox[{"Mesh", "\[Rule]", "All"}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]], ",", StyleBox[ RowBox[{"MeshStyle", "\[Rule]", RowBox[{"{", RowBox[{"Black", ",", RowBox[{"PointSize", "[", "0.015", "]"}]}], "}"}]}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]]}], "]"}]], "Input", CellGroupingRules->{GroupTogetherGrouping, 10000.}, CellChangeTimes->{{3.3959810507782373`*^9, 3.3959810538114567`*^9}, { 3.395981163353767*^9, 3.3959811743295116`*^9}, {3.3959812304669533`*^9, 3.395981247409552*^9}, {3.395981304672886*^9, 3.395981345653913*^9}, 3.3959813909222*^9, {3.395981437039406*^9, 3.395981517556518*^9}, { 3.3959815595723343`*^9, 3.395981574570139*^9}, 3.395981617845892*^9, { 3.396001599221014*^9, 3.3960016137083*^9}, 3.397040636556122*^9}], Cell["MaxRecursion and PlotPoints", "Text", CellGroupingRules->{GroupTogetherGrouping, 10000.}, CellChangeTimes->{{3.39598621117955*^9, 3.395986232114073*^9}, { 3.395986366742632*^9, 3.395986381430113*^9}, {3.397040631075893*^9, 3.3970406365562763`*^9}}], Cell[BoxData[ RowBox[{"Plot", "[", RowBox[{ RowBox[{ RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{ RowBox[{"-", "5"}], "Pi"}], ",", RowBox[{"5", "Pi"}]}], "}"}], ",", RowBox[{"PlotRange", "\[Rule]", "All"}], ",", RowBox[{"PlotStyle", "\[Rule]", RowBox[{"{", RowBox[{"Red", ",", "Thick"}], "}"}]}], ",", RowBox[{"AxesLabel", "\[Rule]", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\<\!\(\*FractionBox[\(Sin \((x)\)\), \(x\)]\)\>\""}], "}"}]}], ",", RowBox[{"BaseStyle", "\[Rule]", RowBox[{"{", RowBox[{"Large", ",", RowBox[{"FontFamily", "\[Rule]", "\"\\""}], ",", "Italic"}], "}"}]}], ",", RowBox[{"TicksStyle", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{"Medium", ",", "Blue"}], "}"}], ",", RowBox[{"{", RowBox[{"Medium", ",", RowBox[{"RGBColor", "[", RowBox[{"0.5", ",", "0.2", ",", "0"}], "]"}]}], "}"}]}], "}"}]}], ",", RowBox[{"Mesh", "\[Rule]", "All"}], ",", RowBox[{"MeshStyle", "\[Rule]", RowBox[{"{", RowBox[{"Black", ",", RowBox[{"PointSize", "[", "0.015", "]"}]}], "}"}]}], ",", StyleBox[ RowBox[{"MaxRecursion", "\[Rule]", "2"}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]], ",", StyleBox[ RowBox[{"PlotPoints", "\[Rule]", "8"}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]]}], "]"}]], "Input", CellGroupingRules->{GroupTogetherGrouping, 10000.}, CellChangeTimes->{3.397040636556336*^9}] }, Open ]], Cell["Interactive Graphics: An Example of Manipulate", "Section", CellChangeTimes->{{3.39598621117955*^9, 3.395986232114073*^9}, { 3.395986393736001*^9, 3.395986399746608*^9}, {3.396155892852355*^9, 3.3961559113052053`*^9}}], Cell[BoxData[ RowBox[{ StyleBox["Manipulate", Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]], "[", RowBox[{ RowBox[{"Plot", "[", RowBox[{ RowBox[{ RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{ RowBox[{"-", "5"}], "Pi"}], ",", RowBox[{"5", "Pi"}]}], "}"}], ",", RowBox[{"PlotRange", "\[Rule]", "All"}], ",", RowBox[{"PlotStyle", "\[Rule]", RowBox[{"{", RowBox[{"Red", ",", "Thick"}], "}"}]}], ",", RowBox[{"AxesLabel", "\[Rule]", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\<\!\(\*FractionBox[\(Sin \((x)\)\), \(x\)]\)\>\""}], "}"}]}], ",", RowBox[{"BaseStyle", "\[Rule]", RowBox[{"{", RowBox[{"Large", ",", RowBox[{"FontFamily", "\[Rule]", "\"\\""}], ",", "Italic"}], "}"}]}], ",", RowBox[{"TicksStyle", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{"Medium", ",", "Blue"}], "}"}], ",", RowBox[{"{", RowBox[{"Medium", ",", RowBox[{"RGBColor", "[", RowBox[{"0.5", ",", "0.2", ",", "0"}], "]"}]}], "}"}]}], "}"}]}], ",", RowBox[{"Mesh", "\[Rule]", "All"}], ",", RowBox[{"MeshStyle", "\[Rule]", RowBox[{"{", RowBox[{"Black", ",", RowBox[{"PointSize", "[", "0.015", "]"}]}], "}"}]}], ",", RowBox[{"MaxRecursion", "\[Rule]", StyleBox["recursion", Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]]}], ",", RowBox[{"PlotPoints", "\[Rule]", StyleBox["plotpoints", Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]]}]}], "]"}], ",", StyleBox[ RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{"recursion", ",", "3"}], "}"}], ",", "1", ",", "15", ",", "1"}], "}"}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]], ",", StyleBox[ RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{"plotpoints", ",", "4"}], "}"}], ",", "2", ",", "12", ",", "1"}], "}"}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]]}], "]"}]], "Input", CellGroupingRules->{GroupTogetherGrouping, 10000.}, CellChangeTimes->{{3.395981768035449*^9, 3.395981772536667*^9}, { 3.395981947462491*^9, 3.395982089932794*^9}, {3.395982122594069*^9, 3.395982123946005*^9}, {3.39598216686173*^9, 3.395982231462096*^9}, { 3.395982335362956*^9, 3.395982341082368*^9}, {3.3959824256865807`*^9, 3.3959824515153112`*^9}, {3.3970392812619534`*^9, 3.3970392971196404`*^9}, 3.397040636556572*^9}] }, Closed]], Cell[CellGroupData[{ Cell["Plotting Multiple Curves and Plot Filling", "Subtitle", CellChangeTimes->{{3.395986409205997*^9, 3.3959864135038023`*^9}, { 3.396155963447092*^9, 3.396155977946699*^9}}], Cell["Example of filling below a curve", "Text", CellChangeTimes->{{3.39598621117955*^9, 3.395986232114073*^9}, { 3.395986427019638*^9, 3.3959864361556797`*^9}, {3.3970416334050283`*^9, 3.397041654739422*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Plot", "[", RowBox[{ RowBox[{ RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{ RowBox[{"-", "5"}], "Pi"}], ",", RowBox[{"5", "Pi"}]}], "}"}], ",", RowBox[{"PlotRange", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"-", "0.25"}], ",", "1.25"}], "}"}]}], ",", RowBox[{"PlotStyle", "\[Rule]", RowBox[{"{", RowBox[{"Red", ",", "Thick"}], "}"}]}], ",", RowBox[{"AxesLabel", "\[Rule]", RowBox[{"{", RowBox[{ "\"\\"", ",", "\"\<\!\(\*FractionBox[\(Sin \((x)\)\), \(x\)]\)\>\""}], "}"}]}], ",", RowBox[{"BaseStyle", "\[Rule]", RowBox[{"{", RowBox[{"Large", ",", RowBox[{"FontFamily", "\[Rule]", "\"\\""}], ",", "Italic"}], "}"}]}], ",", RowBox[{"TicksStyle", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{"Medium", ",", "Blue"}], "}"}], ",", RowBox[{"{", RowBox[{"Medium", ",", RowBox[{"RGBColor", "[", RowBox[{"0.5", ",", "0.2", ",", "0"}], "]"}]}], "}"}]}], "}"}]}], ",", StyleBox[ RowBox[{"Filling", "\[Rule]", "Automatic"}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]]}], "]"}]], "Input", CellChangeTimes->{{3.3959806042337723`*^9, 3.395980615467904*^9}, { 3.395980748889402*^9, 3.395980804338718*^9}, {3.395980864747794*^9, 3.395980968832753*^9}, {3.39598260562679*^9, 3.3959826153027678`*^9}, { 3.3959826633365793`*^9, 3.395982665859255*^9}, {3.395982703416321*^9, 3.395982724123344*^9}}], Cell[BoxData[ GraphicsBox[GraphicsComplexBox[CompressedData[" 1:eJw0l3c81W/Yx1H2PvaexzrHqFR+UfedkLRRKISSElLJaKisjGRUiKzsss6x 532TfSQjUUZWhXAks8Ljeb2e56/vH/f3r+t1XZ/P+y3ncN3UkYmBgcFzOwPD /35fDXQJ3HHWxE3u5aN4yvHARIyZEdbQwGuKe0pxUhoID6no8+onY6Lb4NWP rBSwf0lWfjiOhNfspU58eEABNW691iEX1DCjS06GRlQmSJRxW87gVMUFFZGi SUEuKPAI25EbHcr4wyGf3+/vvEHv3wT9yfNUwq4BZ/l7VErRNzHTV5pEIubL Ou57U7AUbWeSWbkwrYCrk65HSci+Qf5ynYWML+Qx3CchOXcpHHBU+imYnpXD L0e+fr58qBjY2fkF/ZCSxc9bKSJHJBBQv9ceOfhCCq+6+lL6uBDIVo0NOiwl gQne8o5SixQwYai278V1Uaz8bme2Ek8iwvctOlw6hPB+wxjHv1Z16E3W44+p 5wRwzFLbfNiBNnQGPoyroPBhwmlWnRHTNiQVs/LKxoULm5jEjy11VCNCyIMA bk5W7Br/dYfv71JgVKSr3lXPiD+N3vL+sfQJaPj/vZX8Zg3dcvMemaCPgzcl +uwnl2eRXQZ759Wgn6Bv+ujtF9s/oj7LREfBu3RAGTgq3SveA1ZbOc1HguhA 6Hz+NHvTHFB8fmzBzeQnmEvgHRg+sgYUPk6f/3BgAmQp90zEMDHB1VoF3jbR T0DUZDpe7TArHNO5tyG3txi4BP912baDC/auHJF9Il6Fkhdr7MPq+aCNh9uI p08b+rPzb/xeIAB/DauIuXu3oZIzSb+tCoTgm5ODtWdn6lABu8/Tl+aiMOw4 iZG7MQUl0E6V3W0Xh6XUa/k/pvNBk7Sd/F0fKcjm/flLc2UtGH3gIiG1JgOf +POu3ylDoMCB/lJ8jxx8IH0p6FxVCeA6YXB4d6g8fLNPrGk/exRwwLG6qc0K 8M2zxUovnSxk+ZelK0GGCF+dJPft3ChBviqqnqdvKEEx1c8B0nqlKHHwiINl rjKUpivXPPmUi85bBdFnGVUh9rTpdff1QASbuncfoRqsq9LMU6hMB2umBVme PiTI0is6sUeNAh7yV5Cz2skwbgen/AESBTBY1K2qsGtAO5WEY0zFGUDG8Zvj f3aacHG33qPYKXPwf/cB//8+YAVBPbFdAw8sFTq3qz8HOpEsvK/81fG56p+y XvtzgSOY/fdGh4xfWmV8pclTwfqOu2jXPzUc4fOXUeNMPlBvTs2JLVHFF6s4 u7QzY0CUdlUyp6sKZnHxKXHZnohU7zSnRsgr4wv3/binEqjIysGFNveeiAsF HwwK2JehxfDy1ubHivjZRmBb+zMqaoha6SkECrjjyi5bLrEXqMlVdTpnSQ73 w8jo9NBssDucqVeyUha3m9sqJJdXAs+kyY7eSWl8IubGhSg3DKa7KZzRVpL4 +/jijrrtlaCpzM7OrUkMPxKtLtC7+hJ0j8LtjDIi+MGz4dxoyxJUEn399OPn gvj2nNrRvy+aEMOif6k6CwGvhMh01r6noUuc/y5P/uDBGyqXhe3HG1FcRFVk SRU7dsW4MOBrLCInDVnSL2/HHY0qe3r+0MCQx38/ZOM2kJjw4Qc8oV8B0/UT 98ZNF1EMnu4Q5JsEYWcWR4/9G0fBpxxOVy7NAjzBOMKhcx8FXireM7dJB16K 03qVqhPAc5fyj7iZWVB9adfkjbOLQJfjhdxj7kmQtHTONChrAxh2LQtfvv4V jJQPo5H07VCAufLmx0ttQH9qYZtINTuMDI6eN5iLRb3luqLcAzww9fiVLKuG RtT+zNp3lIEApxf490l10JBlw7FmYy9BOHPx+0QEQzOiFnDWrTGKwIBzOy7r PylFGdMTr0MjxaB8burvqUNRQOt2v8tfeUno3mShbt1bDsxPfpc+ViENbX4v n7vujMGpru5n5i9lYbzBtYni3ipg2/9yXnlEDvoW5e+51/EG7GV1O/hTRQG+ 0onVPxwQiYZsTgYl3VKE5Zz7joj8oaCf/HFpni1EKFgxIpZoV4ae+v0385FH GSpqcDp2Shehf+KTKgoWKnDpzQyXsF4K2jOQZmWfqgoP5+yghuQ9AyyW5SXE ITU4PXhy6Q5LHtDbqT3No0CGrOpKZy8oUwHUriFMOqtD4dhAVWejPMBna6ZJ KdaAQYdMGas0Y4FtykC1laMm9GG+PJr43QC4mdxMCZPQxM+Tmg5u7A0ATwXy 1DQ+q+MxCXsGok428Llk5hwVTMbz2iEO0jQKSBTomA82IeEDzsqcjKGFYCle 1z+SQw17f9mlpX4wFYi8EaRZVqtgIV3e/4bMIlHfqNPth97KOGmlUa5dshA9 C1pzOCGvhLnPG3pnEMrQjBlz0d1Piri3JddiKq4YTRwJc2R7oYDbjTTZSytf o/Tme+/PGMrjxzwn7/T+TQYpafr39rLJYbu50bbCkjKQULDsahotg8dLn3e5 a2PwRBmcKFuRxPJh9iKFc9WgbP7u7y83xPFZFSafqYVsMPBst8zRZhF81z4j UzohF+0LHue9s0MIZ8pOMDPJNaDe94GNToUE/NxCWyHzAg1tV9j89onAhxVs SJXn7rWgL9GfY9gFOfGzKY2d9nuoKPlZvttGOTM+/L0kruD+O/Blj0un+2MG vG3F14MKB4DomqJ33cYykkJOPjv4v4P4wISl42uT6L7w/lbbzzPAeYGWctun ARU//uUmOUQHpwh87YplQyDXRv9A9+AcUDjS6FY1+AsUPLsne6xuCjQZl8RQ V/+Cg2V8iee3jwGDecvuKrNtsN+d3bzneRfIe+n2IeURGyz4wdESSowHKSkJ +mxB3DD8kZS0uWg92mPA7V5qzw/3eVj9rPGloZy/CjvggAC0Dkq5s7DagoqZ znzJsRSGzC5uN2ou1yC1P/mi0QuisCTHtd7e0RddThGMrvKS2NpH/2fbnhQD 7r1pKRfFpCGFY5vAZ1EMUoIbIn+ZyMK+CVFFa5FaEJRoYCgXJgeHLj5xj6qi gNdqVgaRn+VhA5sndaV5vlY24vdIspQi/KHH5MEunY9eB53cx+5BhJElNoss TGUo6MyOHQJ4q09au931fxSj9r9xjTWMKjC8/gFsepeJjMVfpGedVoUCJ2q5 /hPyBU++VOutP1WDPftT9WL35oD4+l8t+h0k2CB8LJ5jigJG5KuSmyXUYVt6 TeJnwUIQfI5DcNZWAz7rdDBa7kkBtX52Ua0OmvCU1gEfovVJQFApqsi/r4Hb C42vr6wkgjEuu9/sGup4d0VWWezTAnBa/HFEwyQJMz6c/nOGgwpsTqk8Hc5T wxszpP21W3nAiew9aqVUMBBUN1N+k47uEpQ7ktqVsOoddquVjGIkc+Drrggf IiYnxYse4i5D/5qvjQj8p4hbmmC3BHchmhT4xLKRIYfbVpXIbI6FoM2zXp3J RRbXyvlG2e6pAabhXzStgDTmazxPRrsxOOKr2OpSJYElWV34H1mUglbNY1Ol nsL49wHjh6G7q5FW4t/o5ysCuF+ybPpLRgtSE/fL+n2eH7tM78/z96Yh3LnG qPCGGyv7u9HvBdWjM08SQ+0vsuG6cxGHju9NBjMTXg+Zs36hqwJ+x89NTIFl k/hXsRtDKNnObdyhbw5If6QtLGbUAwmpWDbucTpoAu0CY15TIPzvkRH5yhlw 79GlPOZlZhgpdIzzEWM96NPx0glf5oA3tEKJEvsoKHBydplNlA8uv9AJb3/a gi6Ov33ClUKAYsNszsY3aYgl/LbNaQEhmE1Wsf+U0oBkB8TV/TXEYU7k3oaT h9PB3yOvDut2SEL8Q6bM+0A1iHdSTdS2koEHDd1IIeYYMIiPxpT9kIWeJyKv HWeuAO3jfgeMvBVgTLnUMhd3CoonvyUltirCZcN+99jjxUg7cYRrQlIJOkW8 rXOXLEMxBQezYmyUYWUo0yHT+UKk+IrKI/FLFY566NW9IiSDh71FGidIJNgW dk/iKEchGE715BzwIsMzuk5LYd8pIMUQBbJVqkNu1n/HyutywHrN2ckpJ034 t0mQ3fSbNmAWkP/CdEgTf7/7b/dHdQ/w35mHOivbNHDhcDfxw98MsM2LJTWg kIz52GQiwjwpwDXAK6ToBgl3qwY8vECggM8BbPNcu9VwsvzIC7HNNPDlUp3d 5rgK7vO7ovvqqz/KF9L56p2mjIvtCboPr+ehQlGs4XtMCS9US/54VliKJkvf ZvWuK+LOAGQBrpSgReIZjWKkgNcslJpdQjLRcw8lRHKVx0FVoxUhZ2NBb/7Y BwNNObyn1ILOyl4KNMrv1/D9kMGfGjfOGAwiMNgVSG81ksLvjBv7nm/lgVY4 +/6oZnEsdtTaPSQ+H4zMFJDdJUQxg6iUhkJYBlr3k7r++4EQjmrvCQtuqke4 kuV9ALMA/i1knXZ2og3lUgAwduDD7AIfc4oftKJ7zydf7sKcWHfj6ubf8jJk yRO7xuzAgg2Sgrsbe2sB31LPhiyREfeEspnHi38GCgf4PAvNV1ETayn7qe3f wGup6w86vH6iS1mft7vtmQFcExTDUwc7ULhsWeBcER0wrKgv/bvSDyZs6Ze6 99GBhS7PzpHkecBAs34THjYNzt0cKzdO/QOESXXfXBXHwTJnzHnVt0zQfrd4 a3xPDxi7QS5xnGCFJptXsr3uvAFBz2l9gQNcMHDRRLloECHnV98mZQn8sGkp sMZJgIZMY3m/64YLwH9Lh3Z9aWlF2rlr3xm3C8PqKpH3CxYYzTA+73mRJgpr 0m/dqvB6jhhKqekS8hJwQB9/WxClguk3j+yvt0rBoOqgr92RCBhf2s+LFWQh +o4d8v7VAnGGeHqinRx0+1YjuL2lCFhUdzSOUeQh/85Bz8HZh6Auy/BpyoIC LIYvXQfa3qB1+Daw+wgRRqOlF3XPSxETyDOjxilBWqZOybeUEqTt8kuAs08Z hgbEHa0ZzkHdFdxtbaqqUNv8r8+eITPwQQIwTDlt8X3WPS9b7izQFnqqfDCN BBOvvytJe0kBWuL7Lu9dJMN1B1NejtxC0NDvyMKprQHrn/5XNng6Dcz9fn33 kb0mZDI5EFRz1BTkzDv8JmZo4A//majkybwE4Sd2MfZYqmNnI0KV00YeGCDv ayrjI+PTO/vVGhSpQL2uS4m9Vw1fZ+Zy28jJBR0+PByOhirYQ6EmMDcpFZka reyNXVHCfuflhxoLi5BeZ8ZmbRoRs9cw1JQfLUOraoReVztF/M9kzJzFjoL6 8IPVnvdymDm2IMumLBcw+Dk84n0mi0NPjBa4sleDiRf2D0SeS+OcVI1HnXYY xKtcc37AIYlFW/siPxqWg47gpuWBNmH89JDFzu4P5WghdvcCt5Egfrn3U2Dp 22YkxLqtgI/Cjz9vcr25UU1DhLk7xcxHeHD0ZpzFxeMNaDk8NzyMlx0vzyYP xoY6gRXVi76L/xaQ8EnCDBvDFPCvkbVsvz+KAjutr0m7zYHVBlqCdjUF0D/2 fr25RgfSO8+rdHR+B0tFSznnz88CjcTUPbeOM8ODrsFKZGIT4OLfLW1qxQF7 La51BIZmofkGTv+IQF7ot5/uVG/YjOJ0A5i9ThGglC+y+FhMQwUq9oTjjYJw /7FPv3wGG9HY2OaPoK9icMeBgKFN+UQQc2HfuQRvSTglokIYy6wEXgOstpBd Bu69dkFB0wWD7CUroSAsC9mjFiYIvpXA7/YqijulAI3WnvT+uRGH9AzX+xOT FGF8vXZu/N4iFGmhZ5m3QIRLBa99w03LEOFlTevuPcoQBJ587ChARXm6JO0D rapw2f/tcMa9l+Cd8J6F/7aToH5GYkBMZj7gdu7943GcDNtf5VulCVPBvN6B Y97R6jBGuYezLeYt0NB82Z16WROqBV6WHrEEYLzrs6RjvjqOuXqJcPXkG0A/ nbIryY6My0WfnMDbqeD9a0VLWwUSFuzWk7jYUQAY8mM5g48r4/v28sy1VynI c3FnrPQqET+8nVDVcbwMzc/b1soVKOKILJ99cllFyDnutYraqCxOuCqncM+o ArBlXZd+vl8Gu5PvpoVewED3/mpuerYknpi//bIpugp4h+cUMowLYk2l5y1L lxvR9Mj2WpPzBEwUCNumlk9DpSr3xWhBvDjJdlDWwrgZRc82X3t/5zuyOGQn n+k2CyIZ21d2XyxBB3XT9/ss00GnsM/pTL9RsCdysljfdQ5U5l7LC9XigSaq i6N3OBoQ44z2ylEKP5RcfykRsbWPDHY69wxUBWG2gQRfO0cLooV6Pjj/XgL2 cmk65NFKgda7hq8WV6XhkCZrYvMJDFZzjxIUbspC1x9x0onsNcDXM3VXsrEi 5H1wTigxphAZtf+eA0lEOL0ZG/DTsAxxuJTwePxQgrH7WJwK+YrRkZf7fPhL 1SBPoouB+J634Nqf6M/ZqyS4+ermt0NbeRdJ0vtscUgdsgdWfnr9Ph/o0J58 g9vU8eM36dkWtwtBM+tHyy5MwuxpAvWWPRQQ/tV3qShIDV/zy0pIa8wG6cNn L2WmKuHn9/5anPQpQUy5olcunCTid9yT+vcyStGLa/JfFg1kccN6uB/v/lqA A8xG4qelsLhbasW2Lwis9gwpn3ORwF3wvVK0bjFwfV23SyJHAJef+H5Gw68V QXXGlE8s/PjFiqaYKwMNuRV5n4Sc3Lj0UWEjYwRG38V/B8cwfkZhQ3IsSjvo ADdSYj+4toPPnBoNndV04HZ8/+aS9Ay46WlUE8M+A6LnzpBNXPlg+9203p7k VqQR1iPwmk6AwnJqozvZaMhOe0N7QEEKOhI2ftfF14Da3yaDKjky8Mj0RYqc IgZrAla+rxYV4YNaL1LLvhL0eSygTvywEmzxcJHWRaVI7/mOaw6mJLhL7nas d1YhKPgsInnwNRleUW+1ao2lgPZjghs7rmrC4/FaTqRviuDUyppn7VlN/Oqi wucNxUuAZ/kqOi+mgcuafz0T6UoHxgx2er4NZPz5yR94WZ8CevXae40DSbho x62Hd49RAG3NTemoiRq28Fd48vV4BtCrj33bvaKCraX4zcz+3UHxmrKCS+XK 2N1/r5/0n7eo1j5NMMZeCV/si/c3u1GKLk9upPrxE/E4k9b+pvoS9E+gksDR q4DjRfh1JK2zEdfRv2XCj+RxOdU+LXjbM+BeTPWh6cthN5YNsrJqCdBLSlko Y5PFC4p2dRp+CGxXVoVmblJYzI3qQImrBS7nO+1dFsTxZIrsxeDMQuAg5lrk ZyiKJUSCUn+yvEa2DyultbKEcHuH+zYbQj3avaP5lICWAH4bcIApPqYNMax9 /ckQyodvBH+MNaK3omNC7gnGwlx4Pas4rOx0JSo5yolCSlmwO2yP7RqoBKSP rMJrtxgxunvNa5W1H2SPMC9lba4iu5UKoz93JkDmlGUDT9kMsoRTfttHfgI3 N0J7UnQXmjcvkPN4SQeWU9XsU3W9IHiXubDURTq4UUx9dpNxHjguZp+6PTMN FFnXWp8trYF3h//QLlPHQcdLbdmRs0zw3ivFtcClj2DdhlOl5QUrfKjSdb2Y Ugh8nl58bRDEBefXV5mOhNSggJbTxLPTfFDjPzEd0/Y2pOQYiP+7LABHeU5n fFBsQ4sMx2bzPgtByYSIcmvFOtQRyEIRuScKDwsNTT36G486MGP+0RVxaOXR 1Mz9vhD0T8wfvJ0qBbuaFW7dJCMg2e1zQplPFtrLHRUKuIDAJUqDgfVROXj0 x3sL/sZisDMwhIUrSR7esT5lRr8bAgjFcxOyQwqwK+Zh6gH2HKQmbUUq0ybC 4ITLWsknShHe9XOCMVAJDn3NSXFcKEFX0qWqKHXKUOh8ysjlC29RDHub9aCQ KjxmZ3an86ctctdjGLM1V4PHRCwdiyYzwNjcZkHOUxK89drMYcqRAvpf+By5 PkKGSiWbOcVzhWAs9tnmS2kNiPd8qaEEpYMgcoP7kJ0mjHlol58ebwYWP+6L HC3XwPoVnxRv58QAB7pk8F43dZy1+XqjQyEPyJY+s6cokrdAgZp0SpkKXvgo 3UqaVMOGK9kV5YF5QKtvwlzHSgU39Hnn6xNS0AG7ry4C3Mo4/BKTuIpaETIR C/n2qZyIO/snQ/zPlyFPa8cP4h6K+K/GgMLEOgWdiDX/VTsqh9HofPentDcg /vFOUkymLKa37r56zrEKqIsTszxrpbHl2+x7ZtcwqL/PU8W2UxLrnnnz+DSp Apwq8b8/tyiMnZvM9zMJlyHzF92pJq6C2MJQyE5ZsRmF3n+3M3mAH0+Vnn17 mkZDVfequL3iePD9sExvP+lG1MyjHZHiyI6doorXvh8PRPfaLdd/Zv1G3FPG 32+FTILHIRyJXDVj6HL847etu+aA5fHYAaeuZBCfwvw0f4MOTN6+3mlw/xvY cfnRq22Zs4CVBP+qrm2HxmLjo+UHW4DyukBUMQcHTKqfkXnTm4rGatOOn9Di hduEXemST5oQ1Wn+YK4KAb45+ed0VRMNBSx/mjFJEoSffh+uTLjRhBou32xk KxeD8x88HmzCWHDROeQi7bgk7CCKEw41VoDLQl4HjEal4b0bi9MBbhjcuxhj PpsrC7Vr/V/s1KgC1geKGOr1FGDKMjFHxf85enI6U1M6RBF2CTM/oSZSUa32 9HrUEBGeOahdkWZbhjrD/54LlFeGIXyHhjReUdHNsB9NJ0tUoW+laEtlQgy4 tHelp2BeDTLp7UkoHMwDih0BCwd1yFBMaq5+SZ4K4srvaxb6qsOiMMUB71u5 oMmpsnndUROqtkzAO0f0QfnNd2mt79QxjZM2kGucA7QH1jpiPcjY2WmpyvIn Bew+75P+ew8Jn9At2xjSLQQzzQ/g9ovK+J/d6cVbTYUoYL/w/T3cStgtX81S ZXcZcpOnlnfUK+KjzPKuRorFiDnpZnfhoiy+0XfuIXpUDkxJu4x+O8lggcm7 6reOY3CpO2FdvVMSB9f+VOU9XA0+hxrZ7ecQwqXH6q8UNTUgO4vGg58DCbjb 5UFf+hMaulBWc1PvEy8e+RM0emuyGcVUUAq5K38ggZeOoZg4C3b+prziIyF0 JuJVZdNPOvgXgc9Lao6ABCaFh7uz5kBe5jbvIwPcMO+1/Liz6DskKZq661EI P5SQaGI1SKOhj+r5Z/WZBGHFshxrYGALinvRGBz2WgLmiSWuuVNLgPT6Lmxz UBp2+jcWS+3FoF08+HSorSw8mLIh5fSiBnzwMwmV2aUIrY/eyLuSX4A8clKf K4YQ4cLPfUKKqmWoxe538rseJWj04iCP74NiNF3x99zj12pwuVtqyUvvDfCz 1e+6PU6CRs++HMzb4kWdrLvVEZrqkLqfPvPfowLA7eLpkiGqjumNg7dz5QoB V5T6YttHEt5W8kzUeYEClmJ7Dh6JV8OXy7xmGj/kgMjVAy/ly5Tw4V91tzcF ShDf0t/jXpeI2FkoKzJ0uBRp3Vjwv2spi4vnLoSl1dYAdnYRtj+C0tiNqjEj JoSBrOoj7/FnEliy0+Oq1MkS0JFsO27RKYA/8Z94MSrSikrS6hQcd/BjM7O1 EoFDNCSiX5FNOceNOY78SWmLrENz1CaCyMMBFO8hqb6PhQ7o7QcMx0KawVu7 txM/uuggvimA3YU2Dfx794lVX5wBT36mRuXo80HDnVc0jaVbkXEZONXXTID6 m58H+fVpSAMcP8C5Jgm/ET51iS5Wg1z1ymqNRzLQJjeBzwFgYCLL1Cv5VREe /Has9FxrMWLBO502dyjBFStmy6yFUjRcvHCs/wAJuldGjipZF4Km/c0CPOFk aM/2iPt3PQVcCtz9O/yKJjy/kttEtdAEtbO5zGGvyDjmTfJO5XQKYG6X3y9t S8Je0uzaj7sKwesPg8aX9yrhbTM/I5y+lyLnQMs8lWlFfDIv6vvc9hI0savy BaVaBvtX/ktNEcSg+N5YEpSRwoG9LzOfhtQAEwOjI8tfCNixl7vnljINWTon R0fs48Ne5w7bCm9vRbo/D/x2sGlFVz/8SbvfRgfZ25NH+PgGgHRs4BcOHjo4 5e6T+/M/fnhUL3i49wQN+ba+5DxQLABT3ltPf7jUiv65Ex5d/SUF/+jcUf3x AwGPZYZOy72ykPglel07ohZ0Xlz/OmtLhM+qKkMjO0uRgcn1eodcJcjWdi+8 7XAJoiqlYt4KEszzCc0/30gBwUl//DZZ1WF2an3/hYuFoDzvyB23Q+p4Nu2s /If2fBCTNqJW+4+EBwV8XKUkqOAymXebxNhWPsi78nprFiONx/ViWU+JmCxi AjN3lCHHe9F9wQ9ksa/QX3pwejVI4E+yKL8qjYM/RVJXt3wgKj5Ov0taEOuc 98y9QG5BKZH6JL8gfiz651LMZAoNPfi1R+DJgREkf8+E8236HIgvpUDegCrw psHLUm+eDtbbbpV3fuGFw4IKKid/NSNfXtHWg94EeD40b/urOBpqMf956lqa JBS4RUrddqcKBKfG3d+3QwaOXL978cFFDH7qmPtJFStCiiDr3+TmIuRw5ym1 hVUJXuTFf27qlSH5ZQ++BhESZNYRAYsXC8Ays9K2bAcyvPkr3dCHiQretBjF pR/b4tlM1eyDIlRw5e1JCss4Ec/KOIrctS5DSD53WVtABseuzuW+csbgtrPB vmotAnZj2p298I6GBmXaM0r3ZCE+N53oHet08B21VAp/5ofmi6fqW9poSD/k zObpKGn4powVft3yP1G64ZHzRUT44Loy0dFyq39jxkcHuMlQteHx3m4FKnBQ S7MdnCXjyB3DTtL1hcDP905NXy4Jl/tezVPIo4DyBjdNtSdKeCgo1CSntwQt Ouz2O7yPiA1lO+UkHUrRH0dTLbcdsrjmiMGkNaUWeDJElutiKaya74e/3UGA K0MxYPiRAKY+GTl4f6IVtZVCSeNBPmwge3zZqbANDfvJbAr5f0LTv1puSVrS gfEFwu3h7E6grPncrj2NDuJ+sTdPx/JBP2e6U6BAGxK84NTnIiIALzwuE5xs aEPPVAtIb09IwY0/NamWO7f2t2Lgr3yXDNyhYJI9yoRBNmuhsiQHEa7P/J2p Ty1Bucx9EnuslWCGVoSuuV8pir/lHjLjSIJpmkqj6jOFIO72FUWPMjJ8WuJd Q97iNW3B32yftnzlQYTtptR3QeA55Wj4yk4T12br8hfLmAOfpmEmHkUNfInv 7t9POulguoGL424HGfcGn1ufJFIA+8vluwIRJMz9+x5h8zIFGGi/PjhtroYT 7XeXrs9ngJl5ptPVjKr422rhmHGSB4rUe65R9E4Zkw1nXbJ13yIjlhes8i5K uOgMttHZ4lGlRyoyVhJEnO/n/bp8pgQxhM1sL/mqgN3cv174B3KQcamjNleY PG5OfcqR/SUS7C+L73h6TA5XGBv9/VdaDE48iKo+KSCLnRSCdE6fQiCu686k iJ8UlkjTmrn4sRaE1u9a/MwqgQm/0M0PJyggrYC2HHZOFDeLoBQboxTEuxns 2VEphKeuftieX1qH3F2yos8ZCuBLIq80+q+1oTeSWvpDiXz4GYMqIUq+DRX3 7pI0O8iFV4/xaNCeVaFLzo2ptBEWbBrgbeP0rRyUv0uVc0xgxLOWule/+PaB n5SHxQpn1lBbjdvZjN0TIPvD++/5Z2cRl8U3jldFP8FrcoFsPK0bjVYLPsah dBDgsF3wgttHICp192Dk7a1+H2UP8bpEB5c5a3W6JH6CkNMBphXJa+DUcSub D6vjoHLE36+KzARZ72dtY3zcCzg+3rH3cWOFwvdXms/cpIKbYQWs6ee5oLL+ n65TZ6pR9PDjd+6f+OCmtDrfhfQ2xHcM55WbCsD9guE38k+2IXPS7Xn/BiF4 9fz137PBdai2GSVbXhGFvgffJcQeTELaRjnU8VFxmO3tnl0oXwg+PFLZ6R0u BXk/dkkaLdUCFnbRuXMssnBYreHQ1ycIcHCcu14F5eCa92my8MESkDz1PVP2 uTyManEus2wKB/v2HeKz71aAOm5BtBL5bFTHpeWrqkaEHWXXfSnKpUhGIzRP 9a4SbBWdj9kvWor8cBEPc5kyvBYXW7NbMhd571BR+sapCtNHhrgLdruguvaR 7pcmatDU4yHxtWkGmEvpI/EFkKC8xGsHniMUkGsmphv2iQzfCBeFI24KuOGl dm9UQAMysbOUmUlngO4W82thW75StTMqXVLfHIg3Z9qieg0sKH3UD7i8AO9R FG3KWx1nsPKnCVBzQf0dqJmvQcYrMakVdCIVtPaeEru6oIY7/pa0bM7lgRHm U3/kLqrgewdP8p54sTU/V7PHXSLK+HyE5L+VcSrqrrnT7/COiPcm6jBHXyhD u5eeHvt1XxGfcmCmfj5CRaFMyLX455av/Aku+xabA66Eij+0KpTFjakgn4uv CpgOsuhm9kjj9+0+a59dMTirYnfxvaEkPtfWvB7+sgJEHR3DK+wi+FdCuzl1 bynaLpi6NvlQEB88kmkxMtSEGsvTPL7Pb/XNsJSgQAcN8TWcr9TEPNh9mynv Hb9GpPVhhfdtJDu+e5NQYnEyCqHEnmqn9d9IWuJFjsTxSRBy/QHKtR5HWtqf 3HWE5oDKxxgFR/9g0LRvYub9Jh2MODXtfdAzAaR+5DR0tc6CxRsRNswftsOH LAX/7pq2Au1b/m2O4+zQdvgkSbovEQ1W0al5zLxwg/09aVO1CaH7SiNNggTo vvMbJ97yKbch/i+toYLwv0Y38ZGKJlScTSo+ki4G68W+slcaPgdtdK0rF3Uk YW2YJ5PQyQpgQ83XOPJeGk7uNnxqvDWfy/Hai7JpsvDwff5oLv8q0PaaL/XT TgV42GKIKT0wGhX3/Tln66sI46+1EUWPU5G5Qt2p7T1EWBui6fjNrgxpBscr 5IkqwynONmvj4a33IsNIy7eq0Pj4xpV9Si9ASXNfw/R3NVggZs4meWvLVx9a u2Wrk2FLMMtLFSUqcPGUkmv3UIfsT7tFNYdzAWH70fq3W76y/fu9H2xxh4DC IZ0fdzvUcYOUI398XTb4lJz56rkvGdv2/4gVHKSAq2VpJrWQhAtCw1frtvhk 7OPvc/Wuyviu/NlLl28WIq4xVvd6ESW8Vl3rJUssQ+pVA7sz2hWx/Su/+ZwL xag75Zyyx4YsDr/T8v6VZDnwnBX8In9fBvP074p/fxCD1XuzGQvjkrhqRNnG 81U1CGUXKh+QEsIGuxIa/D0aUHx0hr9sAgGziH+0i/SioeING5mldV4s1Fxw c3bXlk8kK/XkWU2ikYgmsY3NGcDkGb3iy1qPvvTE2c5P0IHiy5a6fI6vQIX+ Kziifg5kpp0cyi7khmLn9l+Ria9Hqhp9XQm3+eF01OPPztE0VCs4dahuTgDK v9Z/pIpb0Ka4a7hCuATUuzGsNSBbAoTjrxXaqUtDjtRDpA8qGJSeVvpVYy4L qYoxDSl9NWCVLbnkgooiPDNVvtdhMh9xxnn/iPElQoN2s6cjW/6ufD76ys9W JUj6NZxhUFyMdE0Gj9bHqUH+BhV/56oc8JRP/PhgPwnqx5s/HlqhAC5Hify3 RHU4ySR05uunAuCt97PAQkEdDxwSeJ48XQDyz3ypax4m4Sc6p8sNNilAdXH9 h0C6GmbdFXMs99QbEMRcVDRSp4T5PEJv8AwXo7iXs3DbdSI+ovY3ZcdKKVq/ 9aX/gIMs1tsWUFF2twZo0FYTVNWksYp2UNA5pS2+7umWzc6SwApebGblH0vA A2l13eVxAczmJaPV9bUFzQ+nOuYa8eM6o69j1y/QkEuI1RlnP25cPXsiQ5m7 Hi34FlpYoEHUGJBw/Ch9DgSdYn71U6QRTBz/s7r6hQ60/LN5suSmAamLv+ZK xAxgmz5sYKXOBx2ENJ8d6W9BZ9/fnvtVRIDdk9bfHc/T0POGRf20cUmo0PP+ DTGhGqS1/crd4SoDb1Q9PlZpgsHNzLMMNh8VIePdvx/qnhSjxHz2yhvKSvBx Vsu7eratezLs2S+wmwSP7ulmZNcuBN30pAgPPzLUOXv1XFEvBRTKNc3qbvlK 7livTITxTmBHtep5nEnGbecYTpOfUsB/KsfHJ51ImMOMj6ttoRCoenToLhxU wiftLq3ltZciVWk/tc3filiBViNVsLcEsS8nqI52yeBP8xekd2/xlLGy9mHm XVL44HjRX/XuGhD4QCls/zwBSyUIzO9npSGmp/TJayf48Mkuzp1XDrWidCfv V1YfaIgaWNBThOjg4/3v00HVnwFb75XAdUU6sAkqMGFR4oeNhUWlUTtp6Erh x9XqFAGoP5QU2xPbin5zm9xwGZKCpo9lvVlqEbBVT77+RF0WdvmoOB5srgWX TT/utDMnwtl4i+nfRaUozYAnLPS1EhSylygyvl2Cavu99TzzSXCiPPz+w0IK sLaO95DYIEPNHYaVN4MLgbxvbY3sCXWcZCH8VMUpH+hcCV+tZCFjUVXVJx9l qcD6P3+pzzNK2H/bT7rsryJUQirm2vWSiOsefZRaA2Vo54M75GMhsjjpsd5/ MpbVAPc8+PnDVxp/GSwW6LTEQF/MKf76TkF8KbbddmamGX2hybu2JvBjseEC f8NCGnrU93Y3eXgERbRxRgyHzIHWmgNzciml4Ovz+IGzS3Sw3IyktAp5YUxp g8PRxGYURjzhZH2JAFN5+Fk2s2hI80v0mW1PJWHhtEuyIaEKPDzQ6bpfSgZy iIpapF7BQBBl59nkKEL1J8fuDD4sQmtXHJl114nQKMJLcEum0c2gM4yb3CSY PH+q9jNLAWAqX/flsSTDWzsf8wdzU8Gx8N+OqWfJ2G6P/cgwDxXQTx5Mj54l 4vQdQQOOZ8vQxER46CUVGSzZZTSx5IhBYYbivW1GBJz9rnA1pJKGEJtVhvGD QsT7YgfN/A8dLPZuWO5o5IcGF02vcDbS0H9K4XTz+9LwqeiqKHFrXgVDkq/e ZxNhyZ4fjjdOlSE74yob/W1kaMqtV8UpQwXv/4i8frpKxsFDii7xrwqB4iHl sI+lJLztQIO3fB0F5HeNHZmMUcImvFotSdkl6C6r8u0egy1eLttkFA4sRS1X 9gXu0JXFb4PLD/l614KE+hvHrvVKYQWmY9g0F4Fqhd8D914IYDu9E6VWxa2I eUHWNuIXH757p7dQ9EsbGjvBbnC2vg+dG5h9KGtIByr6P2HT1w6g/Nv+O62Q DoTmC3zi/figY92Y1eWBViR3O/H2420CMP/3O+GyH23oT/5ZrUP/ScG5qgN8 NyZrQPNZgRlijQy8WjK3CAQx6Azfbma9qQgDvFwfvbhegvQX89yyTytBGZR8 bjG1FP3cdvqOsjUJvrgb/imrrRCkK8OUL7lkqHWZy8XpAQU8LPTfFrDlK4le Fx/LWMqATN0it0eVZNx9d4eVsQ0F7K2hyHFYKOEk7ohY6ehSZHbnwmn4TwZb 6M7t7C9E4M/Sd552cQGc6Lx+vbm2De0rvO2VZtWJeLvbHTSy6MCLKvFYd4MP lr8u+mr2qw2NHq44fbNECrIQ5EnH7BB4runXbwCIUPFCr9mfm6Xok56K9qGX JOi2x/JI00MK8P31/VmxOBk7tfqQZ7f6/Z1H7IJJPhGP6Z688N28DLFZHhI4 nCONL6wH5f+9jMEp/fF5iyZ+nCnC6ntra19OxFGinxbmgHJGbbXIf3SQcboy LUqPACNX+44IoS3e8QYnDi1JQ21l3qtKbhgoGwm8lZkkQpjs3PTFqgyJSuZ5 DuiT4fcbQm9apKggWvg4Y4IzGTOZmytOrlLAepxi6BsmJWwW1steob/FA1dP U9+ZymAGA4l1GwsMiJLfNqPcCTjlluPIlyQasv9zwEThcCU6tXdKNvkXHfAw XXtxOZEfrlvwXj1BoSFlu38fzp2RhsHjqUGNhzAYqmw7SH1GhAM+z6S7dcqQ Z67zGd45Eoy3fTnrw0sFzu0PlTraSPjN8Chf0zgFhJziOP/Tiogv2T5YP/6u FE0Y7fZo25TCgxHq0f8YMbhzZXRUSpIfm5t96ryqQEOWR7zn+v+2gimGwuNf mulAN5WdWj1AgPx1JwvMlGioJNKvnfRCBm73zbjrvxMD967zguF6SpDtJllV 4Uspqgyjx2bFkqEl2ejRiXwKkFRl0HkaTcafX+BZ73IKECf9PPOFrIQHDW2z qtZLEb7Rz+iXJYMV38qG2hEx4GO/zFrQSMBeGTa/5wxoqNuN2cTlZxOaez5z /uhHOjh07hBP13F+eKSP0VPnCg1t//gl8jKzNDSY31+5jxWD/24rhd+9SoQe BaPLMdOlKNOj1SDnHQlKOFs+1e6ngMXhXTZ1CyR8wrpcOEmACjLHOpUkAog4 XnlKCcluzfNk9btgc2ksq73RZ7w1b8czDlP7bvBjy/qIDPOnNFRqEX1kYxcG 0wwZyQrTdOC+Nqqm/IQAZzbPqFCDaChqu334XkMZeHb3g1aaNQa0sLILZwlK sMJibTxXvQxNm514fNCVDNO0hxJ9liiAbXt8W5Y+GS9USiV+39qnERbb2jv9 RPxE74IN5xb/xtu1OTBvSONf2mpC97Z4ep/mpVUPCQJmP/abZN1GQx7W7Yzl Q/HoYmfmVd4t/v+cEy35b4Yffu4/3tT+noaOzkjxnsyQhmKzhHsrW/nqx3B9 ebKGCEdc0q602JQh4wnOy7dFydCp7bJV3NY9TXo58Kg4b/Fx1/OF9MntIGQs gRzmqIn9/u1N/y1pAPI1Xio6qWrgTv/xq8wzaUBPedzdp4eMvURu2fKLUIBC M+eH1WckPDtwPy/x1laedOl++O+cGhatcG/xOJgJDILLFSgsqpiJdc8VO/cb iONQhy6hVRnbr3AYBg28QaH93IxXbihhB8XbCR26pSjoeI2NgSwR37+RWz3I sOWjTcy+HN8U8H9Pyy8EFuag7z/jF1gi5fEzTe+6mScRIL2cx8f9tByev7kj 2/Z+Meijh6QmiMpiqUabkR17EBjLTNP7EyaFG0ITSpl/1QIxT8eaSIIE1rO9 Y/8plQIa/tyJ43MUxUE3D8SIv09CVw64v05sEMJpT8pDPbb8nDs0dtfGSQH8 caC6yu9MG3qoYelKy+LDdhr8oyK6bWiy5IV1/1kuTP0nrHNgZzWq8pF/NrPE grNaV6RGf5aBB1VuyhIFjPjBDi2Z8/v6wBPxA89HH6whx9gCw27CBMjRZ1v1 zZxFb78m/5NI/Amqw9bbRK70oNbPD3zY/elAXEZFLL6hB9icDcLWvnQQLD1Y AYXoIKQpiVln19b/y63C7R5rwMU0snRQYgJoBbzdlSPCBHmOeR8f/NAL+CN2 bnSdY4VWnBOUveZFgB5yptLMiAvW/3rm21xeheKmXhN82/ng/oHvH45EtKFA ZKO4aiwAi826LptdakMBmH1hrkIIdkRqa7RU1qHSK5IiPraikPF0QXHEt2Q0 ybZerNknDhPCjShf4gqAySmDNz7+UvA/DxHSjf5acFfxR40Hoyx032MREPga AevS9O3XdOXghNN92xu+JeBTgtCKWoQ8vFppYfLfTAQ4cX+WyPheAdpYTfBw 5WchroCErDFFIrwYIa9uIFCKTrz9HLXfUwlKOAofdFUrRZEdvuX5FGW4futm BsUnFzkb9oVOsajCkIUWjr3HbqBpwdNHywzVIPNG1fsClgyw6PPu6jtfEoxj dREZ+48CYnZO7XrZRYaFD8+mFEpSgM6P2/sCeTTg3Lh1pPPVDLAqnHjFwU4T MuafK/38whyobyVZfrMGJjovlpPePwdMKsdm9X3VcbJId5ysdy4QHBKOyd1F xq+VPQViFKlgfNtllxMrarhLQf72HfktXkxkfi98RQVHWetp8b1PRPm3wp9r SSljA6pDAwlTkXDk767sFiIWq+F1SN/Kg+d1CmGDfoo4t/TboMB1KlLRWSQV zMth24YNb1f+HNAR9lRNt0QWV8t27n85UQku1axsPzAsjfMq565e3+qzlPXg soKTkrjT44d4yIcKQI2JcrgnKILXoq+t7GspQdZmwcTyUEF8li1oXbayCTl8 eiYU+pcft/moaB/toKHKH2/5uD7yYBmlgeyTRY3oUoHVKa1MdpzMH53gE/8c 2bFEvSKqLCIpQbauPI1JEDpW0Xkvdxxde/55JIZ5DkS+IzmhjougY3BkcX0r r8hGlpWvfCfApxHX82cHZoGzUBnP74rtcFe2tofnQCvQ1dB1qv3ADrkbDxfq f4tHlpUvHG3meeC+/gqHxJVG1BR8UPMjBwEOHWxYPrSVd+OnCk6xPxKE047u iteGmlDukWCSc7wYnJq9n5DcGA3uUwOcC9QloaRorlcOoQL0P2zLNHknDcc+ PM/jdcFgoGRbw74kWRhfFPMsK7cKMJwBv0bUFaCgus64a2AUahHPcN/wVoRs c3JSEwpUlBJPvlPznghJuyczCfZlyJZ5mrVOQBlWLjqxoA0qMmxeXLTOVIU6 CxYMRs7PwTCv8X62MTU4cI76jLw/D+yxMs49r0KGJ5u2x2xTpoKzZ2bFvlxX h6KUNvyKkAd0TJ8hP0dNOBccHm8KDIDl2wW23h51fLnifoPa/WygwnR/2zN/ Mraw1Hr2oYcC/L+VJ6YZkvAIh7uhsFchsB5QvyJ3Sxk7D6WR2g4XolPFD6+y SSnhitN3RXdIlqEnj909IrsUcbKjtc3Te8Xov9cdXWe2yWFV8aiDF6bKQHAH c3rlYxl8JVB47Izulo+YCv/5OCuJH9kekl5rrAZjxv/G3ygL4fzIl+EzJg1I p/CFYkMGAb+oyHJburblF/x9lZNsfJip5mNIoGULekmwn7ifM4mcvNSmW2dm wB5tzWN34Dtkcy6UoDRKB5VnZpqm7IaBsTjfdM+HOaDweinCMoEbrgoIJuRY 1SOt/xZkc67xw+NS08r0YBrSDg6qZPgmAK8vTyy3DrYg6hCOuO4nAUV/PJ3/ 9KkYRF95rOKgIA3ndq5KssthQHJdwn0nZeFi/1Fax0oN4Dp2hLYprwg3ry8x I/98dJZ3gu+UDxEuq9qHNnGVobP9o8c2G5Qg9XYux/r7YnQp+ljD12dq8NpJ lT/9Pjng+RRzWEQPCb5N3uVVPE8By4d+ZlbIqkP7PBFOU4ZCkJee0VWooo6/ 803lb68pAAzlhSpN4yQMMkf9WJip4JC8gO5athqO0m135Yt8Axi4ZjFoVsLX nh4mHq4vRoPXLu874kHEpoRQnnCmMnTp9gl/WSdZ/Gh4B7C0qgEwd8qxTlsa fzT0PGKsgcFG9l+PUIoEtj014uUlXAr6bQSdGmcFcFrn8wOEdy0o/F8Uy6nT /Fjleuk9BxcaEs7LeWsUw43LLpPsdpnUo8VLxDsrtkNoI3t1l+f4HDCNvnJ4 fvgdeNPzK1v+Kx3ctd8X1dA+BXa9Sjs6kT4DjKbipSjyfHDI0ovhb1ELsu6P 3L+ZQ4DE2ZL3RCcaMn5sbEjvl4S8e+uIRq7VQPolN3HXRRkoMR0v3HMSg6Ap BuH1DkW4/v5tmK9rMZok3h5Xk1eCN5jry38QypBl+KFSLS0SnFO7/c1GphD0 t4S+V75PhsMt1j3WwxTw6TrPT8IVTTjsM0Wfi9kFqIJa+4LeknEmea9npB8F mJ112NPhQsJ6Esci2pgowMXo8G6dw0q4NWZH3kxtKQqeFr46vaqIt+X1Ouw/ VYIk+5789h6UwV2MI6/wPALR/6wTfuhJ4dM6n+KNl2qAfKIwefQPAT/QKv8q s9yG+pJFBM9Z8uFHswIrc/atqJ8o9Muc7T16cndH9HwFHTjv45ivI3wG1fcZ mzi16OBSVNtLAUl++OVQZKnVFm8PKdy8/i9GAN7g+cIRW9iK3AYdp1x7pCA9 /QN3XxYCPcZuIFNFFt60NP99dKwWUFuBtdhJIlyV+3EtL70UddfZXE9KVILP Vb4Wm4WVoAbKpTuqOSS4cjv/gGkGBRjpOruqrpFhXN5RKbf4QmD53furj5k6 Vllpj1TblQ9C2y5eqOAk41wr0wPMClTQB2rUdBaUcEJ+35ldXUVodZ3M4pNE xENeJfokozL08uHcJ/Wnsvhx6vkenh3VoLvYveRBiDSe/4V4OG0wiLc80XRA TxBPStTsCmlvRt5TBB7XTH788yM+UldKQ34m343+qY8ixqGSfsl7c8DuILMh SaMYlIjGUwJW6OBWk2Pn13heKBu0P2nlRjOK1rpaevUcAfpJVndW5dPQ2Kvv Fif9JWG+9jkS21Al+Mc18+2AgAyEg98m453xVh6avVtPU4RkX0OWMOsiZDDS qbG4QoTGTSSd5eNbPN3R6CPJToLfLnR0SvblA7aoqeo6UzLUqA49YU6ggiR6 a3vyeTJG/6LmWDioYKd8ZWL/AhH7vL5u7mxahpYbfc3/7ZTBZ1PLX686YHD8 naBU1ikCHjvre7m8mIZUAqNPgF9UpNMm8SVolQ7+jIhlH6jih4ct73gT62io eDHb6ewtaSgS9eHLGzMM/pgHNwalEaHbjH7Xw6Nl6LJcVsLSOgl6f7dgn5Sg AqaL3e9+rJNxnO21UK2QQuCZsf6ru4qEl4T1Sj3bKEC1X9Li8CslLPZpRAdE laDaz8luYiZELOd+IzPhRSnScM7XFICyOEOAzV70fC3IT3MQ3jYihTmiQspf v0NA8OIX1mPJAvhCVN7dgIRW9JqXf3PnPz4ctJmklD/bhia0fS8v2/ej//gP Mx3SpYNF/xMzbZnvwdFxu5LZUjowpzOZLXjxQYY/mxWcta1I5WF5w/M1AnQf W/wKVttQ3o03OyM0pCD/t2xjQn0N0CdqXlIukoE6dayv7CQxmOjMv/JvTRFm dH597XemBD29JhZnf0wJZnqrgfHCUiR4rG7BwIIEC83C9htWFII3DOTh8Cwy vPHrXnVPGAVkbtAYzl/VhMXOL3XjjeXBSmJI7wNExnrBHXMcpyjgToSaxClr JXyffNplm18pKlLP5nbZJovxcZ3o6ZcIxAn0FVwnCuDKh3wT2962IXPeBjm5 5U60UcN1xz2FDnxr9nwyXuSDu5dTGHd8bUPWwr2tt95KQbX9/G9bjRD4mjnL uPEfEVZ01qnJ2JeiQSHBm8vPSDCozqowdst/PpjV/KHKkDHL080Ai61+ZznM NxNZRMTihkmTQZZlSPw/7aHhImmsvpA7an8Vg9kLPVF/O/lx9L7MV00tNHQ/ +QBMbU8HlMdqumidDnKtexeSdhKgXLgpQe8dDU0bnW8y+LnldzorE8FbfHez xvdj/xgR3k0h/I2wLkPSS3HFT/eT4eCtixeSZLf401vhysvrZDyfTtWyWKAA eC3Rf55VCY9WX+wFemUImujfO28jgzUE+IgpphjU/9ebsvsuAcf6G+2UjKGh Nk/v32IV1ejGJy5q9xwdCHEHTdx6xg8DupTrXr+hodcaosbWR6Wh3P53jpn7 t+5x555r154SYRuKrDm+owzdCzz7rH6SBLvENZfMtu6rSsMivP0DCZtJUuHp nxTQLu9vvuMCEc9rWP0+0FWKlpWVDjhwSGNnyX+jTZwYiAZ1+dUp8WMvtzvv s3fRkGLY/3Rx/uFQZ3scr7CNiGZqJM+aEb5jmK/1o8mPdXUOrkbadiJyGT/a m9Ktq2SVFMmvi2zkxy0l05ralBV3ZvFV4ZxlE/uNlKu48mNzzWpdZkNJkv3e 57nrj3v+ez3nn/M85/P+vD/v88fpvzTQ3Abu/63n62UdGuBZabn8x8ccWFEt KEwW08g+Qv5H2xw+jPZuibBwxeCezwP3rc4CmKv+VU+lrkM4sr8npICEr23E RgP1ShCd81T+1UUSZxuORmVUKUH4wl6pmaMAw+QDl8KnmH7r305vUPFxy9Qd XydTDG4Ldt/07+LgosxoabYTjT6yVcijLNtQBv2xfvojDfDdFx426MWGjvRJ oxEZjc4o3rAOzJvCVVebzhfPI5D+n/w6cSQBVz+Tf6UeqEOVO2pTQ5uY+pk3 jGU9UgJvj1U/oFkRlp2beHJhvQr8UrPN7ItsAv9D6OGTYU2hLPvb58wiePjV Lp1x2TYMVnzpf3bwFBt/9HbZsE4xjbQ2jb/UedMI3sUqGqUTGhCvvZAgTuXA oRdWabN5NNLvTtRxdeNDx+PjZUF7MDDSssg2XC2ATUnhr8I3U+hX8tP7M1Ek bJc07nF+rwTB+2McbkhIPNqgmadNVMCy7ymFBwjsZlC7siicQpUe98hSFh9/ KJtJ8Gbm6d7PAi4ZCzi4y/sdnfmARnpWwbva/RXo4fS/w+AHDRiuuX1Id4QN v8HlhWUPadR61zVzZwkPviOj0vh7MeiI/xdfUU/A3bVBdw7IKPR54+w14VoS Eooaj2OEChi0VugtMvpPW9ap+XOIIThqfLCt2prE4/a/lPUKVCB3fPnQx00E tikNPP08jKnvee5Rg3Yetpsvbe5izics+a7bU83GfnkGWVwmP9TJlE7ndC+A avogP5zJJ/Wxevl3eBwYsi3BvaCd8Z+RgjrJMx7syP7exYTRm25loNX2XgKe mL1yncvkM5vyGPvXjiQs6pgp6mTyXoZ71+YLCSTeN165fmJECdoM844ncgS4 11hi8KUtM8/pW67JieXjekVI+jMJBgtxtS8Sz3NwZEXO8LFUGnVSrxVpnRgZ Xc3wPjWmAeYWDam5yWyYwjt52aGERpdpqUuEMw9K1/oGiuwxwGarmwbSCIgy D+sHmjH14fyJofWgCP7l+mx7xgclCJvWkrX3ifDkhfa/r5lTAuH7HrF9PB9q J6lsgDcGP+tQ+Q3LSZxmETDnwFOB2GC3tROFBOY+3y40d6VQ1VTuxp1xPBxn wZLxAzBwr3J8SOSzsVaDVs7CTRo5fnriojGTq/iWN/e9nNKAdJNNxtLDHFjl Otop/5pG2jE1r92s+HCX3eRdz/0YVL2a609ZIYBW139KG/Ok0PtBtocsjIQr VfentrBUYN7GdFHhR+Kzd3SHJGtVoDKpreKzMQL/dKh4DAdT6IlWKX5oysfl LIuVqQcw4GSJ+yPcOPgPgzX1pYhGt43B22smlaj22l9XjcxrwMSPI7qWj9iw /ETPZQ+mvzYFHY3flcmDBBGU4hSKQeR+Zey6KgIeI+diGgMoFHLkET+PRULx AzW3eqMKkHlrbOu4JHYeO3KEzdTXGQVvTvsWgV0ndaiyncx8cNx/W7Wch+XR QwqzSAxUltPSmnts/KxqJC6I8X9+vuXoqaIq0Ljpi4iNzHnkW68GpG/lwJRw SavkLo2mblk89VjkwdM9FffCojF43lmesn+CgIf6k0+l76YQx+t7F6EPCZ/G sdVxjP7utn57PnKBwCV7/ZIKfRg/ydozJvLh44xcB99KGQZZH2bCJ/dxcG9w 4D+HbtDobZJOGdlDobNi4YJoRgNYs9KtweVsmLvnynUJRaMCrwjjuWICviyt DlQCCsV0n14fOi2CA4c+ceGvUwFFYtib5gkRtv65QLjJUAWMnLy5TlI+VM9k 2z3/EwZ1ZS17b7mTmFu7yi+f8Zsr4tEfxN0EZjnswMOMPrKS+4qjp3m4Z3iz EDL6KWXHBT1ew8HF+m7dhxn9PzmoDh3g5qPd2y+q5Iz+nsjjOybfsOEE9lr3 3/eHLtMVF3dU8+DnhurQKOa+nbK1OuxaCLjFNyA2PYJCnnpmwmZTEt53mbvh xvhts7UJ2++gHRRGltppT85seflKL6/F3Bov+9/KXud+3qjffIkTFTcXEwQb lljUShXZmusuccoLY63HhC78nUsyTp7pM9+wxIUBDdcS+8yX2Ou7/JWLG62X +Pf/c/6Pl/Z/A1rz7kY= "], {{ {Hue[0.67, 0.6, 0.6], Opacity[0.2], EdgeForm[None], GraphicsGroupBox[{ PolygonBox[{{1140, 1139, 141, 91, 880, 613, 410, 271, 182, 41, 840, 573, 370, 231, 142, 910, 643, 440, 301, 92, 881, 614, 411, 272, 971, 704, 501, 183, 934, 667, 464, 325, 998, 731, 528, 42, 841, 574, 371, 1010, 743, 232, 953, 686, 483, 1046, 779, 143, 911, 644, 1083, 441, 1028, 761, 1119, 302, 982, 715, 1103, 512, 1064, 797, 1130, 93, 882, 615, 1074, 412, 1019, 752, 1112, 273, 972, 705, 1094, 502, 1055, 788, 184, 935, 668, 465, 1037, 770, 326, 999, 732, 529, 43, 842, 575, 372, 233, 954, 687, 484, 144, 912, 645, 442, 303, 94, 883, 616, 413, 274, 185, 44, 843, 576, 373, 234, 145, 95, 45, 844, 577, 374}}, VertexColors->None], PolygonBox[{{1138, 1137, 81, 872, 605, 402, 263, 174, 31, 830, 563, 360, 221, 132, 904, 637, 434, 295, 82, 873, 606, 403, 264, 967, 700, 497, 175, 930, 663, 460, 321, 994, 727, 524, 32, 831, 564, 361, 1008, 741, 222, 949, 682, 479, 1044, 777, 133, 905, 638, 1081, 435, 1026, 759, 1118, 296, 980, 713, 1101, 510, 1062, 795, 1128, 83, 874, 607, 1072, 404, 1017, 750, 1110, 265, 968, 701, 1092, 498, 1053, 786, 176, 931, 664, 461, 1035, 768, 322, 995, 728, 525, 33, 832, 565, 362, 223, 950, 683, 480, 134, 906, 639, 436, 297, 84, 875, 608, 405, 266, 177, 34, 833, 566, 363, 224, 135, 85, 35, 834, 567, 364, 225, 136}, { 1134, 1133, 6, 805, 538, 335, 196, 107, 57, 854, 587, 384, 245, 156, 7, 806, 539, 336, 197, 108, 892, 625, 422, 283, 58, 855, 588, 385, 246, 959, 692, 489, 157, 919, 652, 449, 310, 986, 719, 516, 8, 807, 540, 337, 1004, 737, 198, 941, 674, 471, 1040, 773, 109, 893, 626, 1077, 423, 1022, 755, 1114, 284, 976, 709, 1097, 506, 1058, 791, 1124, 59, 856, 589, 1068, 386, 1013, 746, 1106, 247, 960, 693, 1088, 490, 1049, 782, 158, 920, 653, 450, 1031, 764, 311, 987, 720, 517, 9, 808, 541, 338, 199, 942, 675, 472, 110, 894, 627, 424, 285, 60, 857, 590, 387, 248, 159, 10, 809, 542, 339, 200, 111, 61}}, VertexColors->None], PolygonBox[{{1136, 1135, 16, 815, 548, 345, 206, 117, 67, 862, 595, 392, 253, 164, 17, 816, 549, 346, 207, 118, 898, 631, 428, 289, 68, 863, 596, 393, 254, 963, 696, 493, 165, 924, 657, 454, 315, 990, 723, 520, 18, 817, 550, 347, 1006, 739, 208, 945, 678, 475, 1042, 775, 119, 899, 632, 1079, 429, 1024, 757, 1116, 290, 978, 711, 1099, 508, 1060, 793, 1126, 69, 864, 597, 1070, 394, 1015, 748, 1108, 255, 964, 697, 1090, 494, 1051, 784, 166, 925, 658, 455, 1033, 766, 316, 991, 724, 521, 19, 818, 551, 348, 209, 946, 679, 476, 120, 900, 633, 430, 291, 70, 865, 598, 395, 256, 167, 926, 659, 456, 317, 20, 819, 552, 349, 210, 121, 71, 866, 599, 396}}, VertexColors->None]}]}, {Hue[0.67, 0.6, 0.6], Opacity[0.2], EdgeForm[None], GraphicsGroupBox[{ PolygonBox[{{1138, 1139, 230, 369, 572, 839, 40, 90, 140, 229, 368, 571, 838, 39, 181, 270, 409, 612, 879, 89, 300, 439, 642, 909, 139, 482, 685, 952, 228, 367, 570, 837, 38, 527, 730, 997, 324, 769, 1036, 463, 1086, 666, 933, 180, 1122, 787, 1054, 500, 1093, 703, 970, 269, 1111, 751, 1018, 408, 1073, 611, 878, 88, 1129, 796, 1063, 511, 1102, 714, 981, 299, 760, 1027, 438, 1082, 641, 908, 138, 778, 1045, 481, 684, 951, 227, 742, 1009, 366, 569, 836, 37, 526, 729, 996, 323, 462, 665, 932, 179, 499, 702, 969, 268, 407, 610, 877, 87, 298, 437, 640, 907, 137, 226, 365, 568, 835, 36, 178, 267, 406, 609, 876, 86}}, VertexColors->None], PolygonBox[{{1134, 1135, 66, 116, 205, 344, 547, 814, 15, 314, 453, 656, 923, 163, 252, 391, 594, 861, 65, 288, 427, 630, 897, 115, 474, 677, 944, 204, 343, 546, 813, 14, 519, 722, 989, 313, 765, 1032, 452, 655, 922, 162, 783, 1050, 492, 1089, 695, 962, 251, 1107, 747, 1014, 390, 1069, 593, 860, 64, 1125, 792, 1059, 507, 1098, 710, 977, 287, 1115, 756, 1023, 426, 1078, 629, 896, 114, 774, 1041, 473, 676, 943, 203, 738, 1005, 342, 545, 812, 13, 518, 721, 988, 312, 451, 654, 921, 161, 491, 694, 961, 250, 389, 592, 859, 63, 286, 425, 628, 895, 113, 202, 341, 544, 811, 12, 160, 249, 388, 591, 858, 62, 112, 201, 340, 543, 810, 11}}, VertexColors->None], PolygonBox[{{1, 1141, 1133, 56, 106, 195, 334, 537, 804, 5, 309, 448, 651, 918, 155, 244, 383, 586, 853, 55, 282, 421, 624, 891, 105, 470, 673, 940, 194, 333, 536, 803, 4, 515, 718, 985, 308, 763, 1030, 447, 1085, 650, 917, 154, 1121, 781, 1048, 488, 1087, 691, 958, 243, 1105, 745, 1012, 382, 1067, 585, 852, 54, 1123, 790, 1057, 505, 1096, 708, 975, 281, 754, 1021, 420, 1076, 623, 890, 104, 772, 1039, 469, 672, 939, 193, 736, 1003, 332, 535, 802, 3, 514, 717, 984, 307, 446, 649, 916, 153, 487, 690, 957, 242, 381, 584, 851, 53, 280, 419, 622, 889, 103, 192, 331, 534, 801, 2, 152, 241, 380, 583, 850, 52, 102, 191, 330, 533, 800}}, VertexColors->None], PolygonBox[{{1140, 1142, 51, 1132, 799, 1066, 532, 735, 1002, 329, 468, 671, 938, 190, 279, 418, 621, 888, 101, 151, 240, 379, 582, 849, 50, 100, 150, 239, 378, 581, 848, 49, 189, 278, 417, 620, 887, 99, 306, 445, 648, 915, 149, 486, 689, 956, 238, 377, 580, 847, 48, 531, 734, 1001, 328, 771, 1038, 467, 670, 937, 188, 789, 1056, 504, 1095, 707, 974, 277, 1113, 753, 1020, 416, 1075, 619, 886, 98, 1131, 798, 1065, 513, 1104, 716, 983, 305, 1120, 762, 1029, 444, 1084, 647, 914, 148, 780, 1047, 485, 688, 955, 237, 744, 1011, 376, 579, 846, 47, 530, 733, 1000, 327, 466, 669, 936, 187, 503, 706, 973, 276, 415, 618, 885, 97, 304, 443, 646, 913, 147, 236, 375, 578, 845, 46, 186, 275, 414, 617, 884, 96, 146, 235}}, VertexColors->None], PolygonBox[{{1136, 1137, 131, 220, 359, 562, 829, 30, 173, 262, 401, 604, 871, 80, 130, 219, 358, 561, 828, 29, 79, 129, 218, 357, 560, 827, 28, 78, 128, 217, 356, 559, 826, 27, 320, 459, 662, 929, 172, 261, 400, 603, 870, 77, 294, 433, 636, 903, 127, 478, 681, 948, 216, 355, 558, 825, 26, 523, 726, 993, 319, 767, 1034, 458, 661, 928, 171, 785, 1052, 496, 1091, 699, 966, 260, 1109, 749, 1016, 399, 1071, 602, 869, 76, 1127, 794, 1061, 509, 1100, 712, 979, 293, 1117, 758, 1025, 432, 1080, 635, 902, 126, 776, 1043, 477, 680, 947, 215, 740, 1007, 354, 557, 824, 25, 522, 725, 992, 318, 457, 660, 927, 170, 495, 698, 965, 259, 398, 601, 868, 75, 292, 431, 634, 901, 125, 214, 353, 556, 823, 24, 169, 258, 397, 600, 867, 74, 124, 213, 352, 555, 822, 23, 73, 123, 212, 351, 554, 821, 22, 72, 122, 211, 350, 553, 820, 21, 168, 257}}, VertexColors->None]}]}, {}, {}}, {{}, {}, {RGBColor[1, 0, 0], Thickness[Large], LineBox[CompressedData[" 1:eJwl13XcFGUXh/EFUUKUku7ulpDukO7ubqTEJASUBhUQBJQO6W4QMEDA7g5K SsDO93s+7x8/zrmus8vOzs7c9zx5e49oPTxJIpEYkyyRiJrnjkQiY9JE4kFw FPeX+6U135B/nL+JXxCYyMtn0jThj+EB8gg3nFvFZZEKXBuuEfcEvoUP4x34 Il6Mn8fT8RFcXj7BZ3FS0Sby+SezvqnZFf03+lf5V/Qv6z/k0/gOyfBA/lF1 BH8/t9rsH3wLZ9W/rT+pb2T2B86rZuL6qBW9t62+sXlx/KT5z/gyboVvmx/B O3FNfCm+o3oP10tdYr5AP8O8Oj5qfpf6VxyL/lOzc/GdhE7kx1n0zcyO4014 Bf4ID8KP4ZF4Dc4mlbh23IPchDg2/KIs5GZyx+J8y51cAS4r1xyfwIOlsgzz wXepBc2zmbcwP4mHyAPSnm/CT+R/wUsluRTis/Mt+dfwUHmce4hby2WXKlwH rik3Cf+Kj+Jd+DJehhfhWfH74YryGX47zoekMC+Mc8T5Nruq/1b/Or9Zv1L/ MZ/Wd7gTD+OfUEfxFbh1Zv/i27gzzoHfwa/hxvhPnE/NzPVVq3p/R30z8xJ4 cnxn/CNujX8zP4Z341r4R/Os6r3c8rgP1Nlmx/nk/N/6SvrP+Xf0d0pKryuC c8b/afYG3oJX4U/wcPwkHo3X45xSjevENeeewr/jlySVFOVz8W34N/EIqS7D ff7dajHz3OZtzU/hkVJDOvMt+Cn8H/hlSS3F+Tx8O/40fkgmcGO4DVwuqcl1 4VpyU/Gf+FW8B1/BK/BiPAefwJXlC/wuvkvuMS+B8+rbm13Tf6d/i9+qX63/ lE8X12b8nvxEdSxfkdto9h/+GXfBufG7+PVYq+L+wvnVLFw/tZb3d9W3Mi+J p8W1iK/EeYvXmx/He3FtfDXuLzVNXGNmS9S5Zif5FPw/+gf0X/Lv6ZPLvV5X EufTdzA7g7fhNfgzPBpPwuPwKziP1Oa6ca25p/HfeFXcw9w87rW4h2It40px +bmO+Gys0VInfm/Hk1YtbV7AvJP5OTxW6kp3vg3/TKx7eLWkkzJ8wbgvYg3E 42Qy9zC3KdZBqcf14Npy0+NewifwPnwNr4n1AM+PexJXla/w+3HvSnrzsrhQ /E5m1/Xf69/ht+vX6j/n0/sOyeOz+afU8XHfcJtjE1J/wV3VfPg98zdij4n7 CxdQs3L91fpe3lPfzrwUnmH+G74a1z/+z/wk3o/r4OuxTsX5i2MxW6Y+a/YG n5L/V19N/zX/Qdy7ksHryuHCcUxx3eEdeB3+Ao/HU/AjeEtch9KA68W152bG d5J1ynLuOe5NXF3u48pzRbhu8V1j/5SG0pvvwM/iR8b+rK7nM8aebFbUrDv3 fux30kgySQWzYmY9zD6IPUQaS2apaFbcrKfZh7F+y4PSh+/Iz+aTygYui1Ti S/C9uI9irZWp3KPc1vgtpAnXl+vEzcF3xP6AD+Ab+o2xduHn8SlcQ77BH+JU sSfHvoRL6nub3dD/EOs8v1O/Xv8ln8E5SIGf5Kepj/GVuW1mSdRf4xyqBeOc mL8Zzwtx7+KCajZugNrU+/vpO5uXxnNjfcXXYg2MZwj8Oj6I6+KfcA41HfdK rJvqArPTfKq4xuJZQP8t/5H+bskWeykupe8TzzN4F96Av8IT8NP4cbwdF5Jm XH+uCzcv9nDZxK3gFsZaiWvF9ctV4UpzfeOZItZKaS45pKpZGbN+sbfGGiQt JKdUMytr1j/2qLj/paUM4Lvy8+N5RTZzuWJf4cvxA2I9j3s19gffuZU60Kyb 2bOx98kWLnfsNXx5fmCsl3FvyDPcE9wOrrC05gZx3bnnYo2NfREfwjf1W81X 4kX4TKyb8h3+GKeWPOY18f36QWY/6c/HueV36zfqv477y7GmxFP56XHtxDrO 7YzrPPb3uIfUInGvmJ/CzWIdiN9Ezc4NVNt4/2B9D/My+PnYQ/H12M/iM2Iv xodxPXwr9nE1Pbct1nj1BbOz/N3x4Ifr6L9XP4n9UfLStXAF/eBYg/CeuObw N3ganoEn4F24qLTlhnA9uQVxPcp2Lp/U5ivyQ+J+i+tN2kn+2EfMKpkNjes2 fh8Z5bjaq0PNepktjGOVHVyB2Fv4yvyw+C3ifMpMbiK3mysmHbhhXG9uEU4t p/ARfFu/M/YjvBifw3XlB/xp7KdS0LwefkAff5jc1F/Qf8/v1W/Sf8tndKyp 8Ax+ljqJr8LtifVH/R0XjzXO7LS+edynce3FMyE3SO3ovcP1fczL4hfM/8Q3 Yj+PZ3p8Gh/F9fHPOJeaIb6fusv71+iXmNfAb8f3jXWaq6c/r35mlkYKeW19 XEU/Ir4z3oc34+/wTDwbT8Z7cQnpFHs915dbjO+V3VxhacBX5UfG58Q5kM5S JPYOs2pmD5ldwKMd02y1i4w062e2JJ4xZA9XNPYOvjo/iruI50S4p7h9XEnp Gvd+7LvcizitvIWP4V/0e83X4hdjv8f14/Px5zitFIt9CNfQjza7pb+ov8Tv 12+J35nPFM+xeC4/V53CV+X2myWLv9lib1NLxZ5k/hZuEfeUWkTNyQ1Wu8U1 HWs+Xw4v9fq/8E+4Y6zn+Ax+FTeI/QPnVu/j9nnvOnWp2bv8PXxS3CDOj/oF ny6usdg/cU39GLPL+ADein/A8/C8WH/wAVxausdvEusKtwynl/1cCWnC1+LH cj/i+dJDSkpTs9pm45L8/+/1K9yz0lPGxDVttjz2STnAlZJmsc7wD3NX8XPx f3LTuINcGenFjY1zxr0Ua6acxcfxb/qD5uvxMvwebiiX8Jc4feyhsffguvrx Zrf1l/TX+IOx/unP85kdc+p4DojjVp/mq3GHYq+Lv83iuUQtiz82P4Nbxv2k FlVzcUPU3t4/Lnq+PH7Z6//GN3EnnBGfwydww1gLcJ7wsb947wZ1udn7cU/x d+BG8dupX/EZYo2PPTPuY/0jZtfxIbwdX8AL4lziZ/BhXE76cA9zQ7kVcR3L Ya5s7LF8ff5R7gZeGM9MUk5axXVl9ljsY3hRPJ/IeH4YvzLOnRzhNnIvcR/g xnGN4K/xfXF/xd9F8flqea/9H1nmIqA= "]]}}}], AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->True, AxesLabel->{ FormBox["\"x\"", TraditionalForm], FormBox[ "\"\\!\\(\\*FractionBox[\\(Sin \\((x)\\)\\), \\(x\\)]\\)\"", TraditionalForm]}, AxesOrigin->{0, 0}, BaseStyle->{Large, FontFamily -> "Helvetica", Italic}, Method->{"AxesInFront" -> True}, PlotRange-> NCache[{{(-5) Pi, 5 Pi}, {-0.25, 1.25}}, {{-15.707963267948966`, 15.707963267948966`}, {-0.25, 1.25}}], PlotRangeClipping->True, PlotRangePadding->{ Scaled[0.02], Automatic}, TicksStyle->{{Medium, RGBColor[0, 0, 1]}, {Medium, RGBColor[0.5, 0.2, 0]}}]], "Output", CellChangeTimes->{3.397041907354347*^9}] }, Open ]], Cell["Combining several curves", "Text", CellChangeTimes->{{3.39598621117955*^9, 3.395986232114073*^9}, { 3.395986427019638*^9, 3.3959864361556797`*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Plot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{ RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", RowBox[{ RowBox[{"Tan", "[", "x", "]"}], "/", "x"}]}], "}"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{ RowBox[{"-", "5"}], "Pi"}], ",", RowBox[{"5", "Pi"}]}], "}"}], ",", RowBox[{"BaseStyle", "\[Rule]", RowBox[{"{", "Thick", "}"}]}]}], "]"}]], "Input", CellChangeTimes->{{3.395984306657468*^9, 3.39598434280956*^9}, { 3.397041928366329*^9, 3.3970419294689007`*^9}}], Cell[BoxData[ GraphicsBox[{{}, {}, {Hue[0.67, 0.6, 0.6], LineBox[CompressedData[" 1:eJwVl3k8lN8Xxy0RhZixlW0sM7YhklKqq4VKqyjabFER0jfZlyKyJDtFlGTN MmOZsd9DlhjJTiWRFmWNCln6ze+f53l9Xufce8/7nPM891552+un7Lk4ODhU 2I//vx+/7yR6O26GJtfyEfhuvyfsUwo1wn4zBC5vfz4nfQC5f7c3fGy9GWpz 9EVK5czQyflF99ozm+HxJcW3q0p2iIeo8I5r/2b46rOs26PhhlyM/3saIbUZ 4tOa9q5uv4sMKggaqW2a8P43zbFNIx5pwKBhYbMmkB1/lau/jkebmrMscb0m iMoeCUROCehXz87okXJN2FfRp3QrNxHlztjOkTM14c0OY5UCuUeIoFJSUein CW20Q9fn51PR50RTI9DUhEWlbQxIy0CFmo+UrqhqQkfQqAPPRAbyahriElLS BDthn6U+vedI6I8DPr9RE5jNP+MkOp+jHadv681zawJtqIv8ZikTPSAWqGm+ 1YBPUjYcZL0cZPFilq+3WwMuV/g1qPnlIMX9et982jWgQcZeJLkuB5X/9zKj 5aUGsNaz3ucfykWjnW+l7Qs1INHBjuBwIg/pRfNueBykAeeqx0keu/MRl8rR yX3+GvBEoushyTMfvcYxrO+eGpC5ViSDWJyPbKelQ7e7aED2v2er7YoFKPK4 Dme3hQY4GhGqrqwWIIuvnh+9TDVAZb4tWk2nECn419aQjmtAmrn4A5Urhai8 4LC3y34NmMw4o/CmrRB9ErCe49fUAN2KbGbSgyJU8Dyzk6aiAV+FvxeuqSlC nrvGi8wVNeD9fmL8kx9FSNDJ3SlTUgOmGwdv5cvTkB7r/hcDbg24l/c8x/wW DXFd6nr5bYUKDy2vhWuF0dDrvxLPHixQIfSDklPyYxqyVcuwHJykQrT20BXZ ehqKDKvo9xigAtll0KFnLR3tUh519eqmgofETUsRCTr60SCwzqedCr2h51bG yHR0iMN6l38DFd7e/2tweR8dzaeG9QZgKuwKbZ9ad5KOsvRLXO5UUqHLR/vs oYt0xO3Bm36XRgVhPrmoCHc6KhbV2hnyggpZ1O3u0YF0ZF18tvteFhVaz3GY UB/QUe1kPk/EYyok5j3Zovycjpwj+tLuJ1EhbMOXK8GFdCStyqH3IJa9fgJM epbTkZedqWNMKBVmtobZyrLoSIXLjzsuiArmFlpxb7rpqO9J1uN4fypYDnxL Eh2ko+DdHbqJXlSwH8+XmBylo63vF9uT3KjgeOV3lcU4HY16Kl59dJ093/Ni LfNZOooVP8aZ4kgFLjMzpbEFOpo2eaqTZk2Fcsn7x2FNMUqbbml7cp4KeDlm inddMToaOWeffoYK1ttshoeEitGSmsy/ZyZUCK/g/3iQWIzyXhk9fH6UHX+W as5eiWJ09rKrdtZBKnypnl5ibSpGfGuSW7P3UWG2Uib1q0wxYqS/vJS7mwpi ZetMYkjFyB5NLufpUeHR2cyPLIViJPpBPDFfhwrPlN2JiUrFqN7bYHOhJhXm E9MrpsnF6Iak46siVSqMa/1IH6AUIxIjzoauRAWUXJx2UrkYvTGt+VssRwXe B//umrO1/8+vcaWbqHClxYs6yfanRglrMMSosH3s+nURtn5P3dnEFKaCyZYB tQb2euGtl6wq1lMh/+ypPTyKxUjvauRCJS8VJFVV7/ew4/3Gw4yp5qRCkKLZ orZsMUrMGFarXVaHQaKXs4xUMTLcu64Bz6vD+cjJrkR2Pn4N6Vysm1WH4xfK xdPY+Xrme/FP/aQ6qH6LVdHZUIxMNt2LahhTB87bP/6eZuebo5ym0jSqDihr JJCXpxgVnn5X1zykDvf1TMoP/KOji3Pc51veqsNUYkuC8CIdCcRo/GrtUQfu sjhJR3Z9qzTNI9veqIOpdLGBCbv+jm23Ke2t6pA3NCLcxO6P5rU9Fp2gDvwZ xHoLdj+5Z6787KpSh9/iuxjurXSktF85oofBnm9Pg6dCHR0F+nvX9OerQ7m/ Q4FiAR3t/k1SGHqoDos2MsffBNCRYvP6Nwtx6jD53q8g9SYd8T/640OMUgfB OV/Cv8t01LurrfdQsDqUaN+87XOU3f93PcJKbqhDl+rd21YEOjI9Y7ut3Ukd dkkdjWrloqMdKsdGx66owzpTYYHWWRriaVPYLWupDh6y/FvvddJQKrF9JtRY HfY4Kq/nDKehoC/lqRmG6jC8ztVQ3IOGHJgZxrUG6lAUHrlQd4mGdM97PZ/b xs6/PnP1gz77//FMycJSUR1Eu3ZJXWovQivaPlhnWQ2ivJY4NU8XolHuy07H 59WgU1HhlrdCIWrpPbnRYVYN2pfKXv2bKkAJXpSbaWNqYDifU1EeXIA06jop /L1qcJ1HwGU1Nx9dPKnyYKhADVYn1HfXtueh/QpE/cUcNYjRb3MWjs5Dqr9W vhGfq8FancSj+Sfz0O+k7r2Hk9XgMtNjovFNLor86P+7JEQNrgVmp2Q05qAa l94LYVZqwOmUm6kZk4Vud+q/2XFODSQrXF+57c1CB7Y+2/vDTA1SbXQZKzOZ iLXoQjlirAbmQYr3Px7LRG/v8s0I6KrBE4XhhI3/MtDvZP2g6HVq4PlOR0tj bzrSaE7PTSpThUtV6zu3ZiWiVDmXP5nrVaGoIloyLcQJHwgtV6TzqgLX2m1X rV1v4IkZLpNqTlX4skD7dCjNDe+qT3rRNa8CF2RETE2XvfE7uzrrf6Mq0B94 Vf/xxyAskSfKsqhWATH9DTs+mEbjmK1VT9Y7qwCvk1eZ05pUrJfK81r8qgrE XNilJfw6FQ/znPwrf0kFfPee2HA8IQ1r9X820zurAg39noX7CE9xu5fQOntD FXBTrAnOT0vH67GNW62MCiBRDVPlvOc4+DDf4RvtyvBmv9fca+88vG5/uz6h RRls5tcZhrzPw9G74jVLXioD1XDSKUf/BU7eTBL9Xa4MrkHbA2X/vsCFYnof PTOUodSGoH/7egHuH7ly67anMqTNN8q3SdPwhfcaV+VvKoPjhwz11oM0/Kln 7ly9szL4KJyxu/wfDU80BxisuaQMy9Ymv2420TBHYdL60GPK4GejwFPrQMeq 3s3pUQrKYOUXKPg9pRgX3oyM15JRhgPFtg3qUIy3Opve65RQhvNR0svzo8V4 j/VHJ6KgMkTacW1SUSvBp4zmtyfNUyDwvMKHRloJ7kc1anqzFEgp7D+t01mC L+wIknk7QYEg7vFp0s8SfJm6gVvqEwVcFJw3eG4uxT4E5fa0NgqoevOfnc8s xRwCk4CaKXDtwUHywfpSHMJTUjJcRwFht/AbQkOlOHphzyMFJgUO/qy79Y9Y hp8PnbHLSqdAvO+S+QmvMqw6IG1+8DEFNvYN66GYMlzY+enwWCIFjDdovUrL KcPlDS6b1e5T4ENIuHFubxl+nRfyt8CdAs53z4h0qzBw+IAg59UbFLBVupXS rs/ARrwJaxWcKFByGi7qHWfgWpsM0UQbClzqTw4yvcHA3lFqUicvUMCPauLE HcjA22vo8uvMKZAmGJUkG8vANEnQ9D9Kgdlq6W9xNAZ2Mjqoq3eQAi2J2gUT tQys6tauP7uXAies7RYL2hj42ZvBQ5e3U4B7YjzqylcGtly5dIK0hQIGAVcf Wc4y8Cb18dPvqBT2KdIyu2qFgeNCFm2PK1BA8LyhZyaBiU+W3nbgk6FAhYmP pLY0Ewt8WutaL0GBxepaDxKZiV9tiHL3JVBgQPKg0E0NJr67W9xvmyC7HoVq Fiq6TGxwLTVoZi0FRqov9aJdTLzyUCk8j4sCphG9/BX7mLiy6UW03QoZUi6Z +MUdYmL3X1uSZBfIcPtWSlX7MSbeolCZOjBLBq9n180cTzHx9Im9z2MnyfBc O+S9/Rkmzvd7lXd0jAwj1x6OwVkmvvriBJ13lAyTcvYSPheYWOltHxM+kEFf qGxtvCUTD/Na1noPkOH+LquL662Z+PHWLw1bu8nAp30Mhtn6rK0Ta+o1GWii AYNEGyYWj57rzHlFho01G2yfs+1dNd4Dti/JsD1VjyfWiokfjHN+lK4lg1rq af/Bi0xsvDHsS185GToGxsKCzjMx70HhiegSMmwyTBsLsWDil25Js8aFZPik f8LqqxkT334mu7gmlww7pniY6SeZeFdH5r/aDDLw13DUlB9h4oUVKq9XGhk+ eJTtUzdi4jL1UgGdR2Sou9Mjs4iY+L+z+sTJODKIDR5RUdjBxJr36jdmPyAD VcLYIEubiX+UHibZhLF5VPYeClZl4qxPHRSpu2RIVv5OwSQmltvzUSfKi+2f liy5X5CJB69d3nnYjQynCOFCkVxM/PDRpAH3dTIcVlt6qj3PwMK/l4552JHB USw7OnyIgdsUgsy0rcgwo3l2bk8nA4edXHd+/CwZ7CwDVo69ZGCufMmrVifI 8FJwbJ9vJrvf3z5x2WhMBnnXG1kpCQzss1b5VvcBMhQy/3GKBzPwL1vdwIM7 yWBI6pCXtmXgLxtPPd5MJoNw9jH//0QZOORYzcUDJDL43civHuRgYModFbmz UuzxgZ7PyifK8OWx1fRAETKMcmntbqovw2OMF9m9K0rQcRebo6tlOPSHuMOP BSXgLui13X2S/X3LBqr9m1MCRVaNTNH2MuwYbFGg8kMJThTEfJ1aU4YnTHlK fPqUoPdVvvn3h6X4/j1Xt+hOJXhif+HiA99SrFH1XjezTQlsHgfO5FqVYheF 4vL2eiU4wqPgbKRUimdmLGvli5QgKttrp3x2Cf4VWd7SfE8J4laDW9viinF8 nWLEYKAS5DO+DBKvF2Pd3w+O/vRTgpO2PMVvDxdj9wv2bza5KcGS5nvFzyt0 vKBG6HW2VoJl409mvNZ0vNx8bZi4QwleNRl0SQnS8BouuXmrH4pQnXY9RoqU hwObePzXfVGEHQ/KrYJpuZgjYmJN2UdFcHH9aLWMcvEysZKwrlcRkiVE9KQv 5OBf5NOapVgRFs0pzU5hWfjz4Qh7vgRFaDPazM+ofIYbYua7aUgR2q/qWAps TMBB8h00zgQFMNgpJT1lF4m+jifP8kYrQNxmz7qJ+1HoEMN+q0CEAjSnP1iX 8y4aCRxZYorfUYDyYpuMUO44FO9GwerOChBSNVIRdiYJPW/2fX3aUAHuCZ3w 7l16gpqcVX/k/paHAYPo2OfhOUhF75d60Yw8WDasejqL5KJwLuxcOi4P+G8o 80tSLjqeZPazdoStR2a6+jLyUD8ELHS/lgeepKLsi8x8NEbs413NlIfWBQqV z56G1lUGKp46Iw+Phj++vby/FD0vF/JyNZGHmf+0cyz9StFuZnL7g6PyUHHI aGmZUYpcS4u9WPvkwYV3laqsWoZ6Cz+9ObBZHrYxzKfX8jPQ04x9vtv55MF6 aqSVVsZEO561d57mlgfVTTF7rb4zUdfTc8puqySI9H71+rF0OeJJ+6+L9osE N/rP3cZ3ypHjw2cqaiMkSHGQV/Q1qkC6kVy90pUkaDOzVHxSXonaIx6o6ZeR oJrUsfvR50p0NXzT7bM0EjSmo0IB4SqUfG+LemIWCaZbdB3O2VchjkDbOxvi SBB+fKTImb8aPbo91afxgAT30s93C2lXoy0B3tSjYSRIu7drh5xFNbL3je0P DSCBv9jSdOjzatTqXq/B5USCWnn/GMttNcju1vEg0hUS3BnSRhZna9DKzXcD e2xJsIv7bgXTpwZp3ZgN8rEgQemUVURGbQ1KuKbw7tcBEjSsRAZu2F2LNB0L NxMNSJBJ5LORPF+LXl3dGaytT4IXoeX7/T1r0V/7U1ou2iSoOXxg7AK9Fllb B4Z8kyFBfAtd4rAURv3TYekpkiSQabw4rL0No+MBMdUniCS4ohiiZ3ISo11p T2eZfCSYVbKu0wzEqEQjR9CJmwRwTC/2xyOMTL2tTAyW5cBcf2rLAA0jzXK/ GuFvctDXuHr6wCBG0v335zwH5aCTc/gxzGDE/ydFdaSTbZ+xktXlAvRZpzKB Xi0HQZXL6U9FAXWdamFtLJaDl7MVxttkAMGNAc7AbDlQekEKtyYDSin643wq Vg5GGfGdrlsBhbbzPK+8JwdXg8U/ndYH5D4p+k7BTw6EBnSSX+8FZCegJBzx nxyUPzt3t/8goFPqOkZzV+SAOOajcfMYIAPjfb7nL8qBJlGY/PQUIA0Hk+KX p+SA44DUykVzQJtCrcfUD8lB8ANt4/zzgPiyr8vG75YDV6pPRrgVoD+N/mbL W+TgTHr5swVbNs/nyHA7FTmQ7jT6/NuezcOdCm0ycpDNp7g28CogrJD/ZytR DpIWpvIfOwLK31tFTeWTg9X0X16GTuxrqXWrLc+qLPzcqibm68zmC3j70HlO FnqHdVUMXNh8aWPtvWOycDzxhlUMW9vVzK/ZMyQLBZVTDtfZ+tQgr35Wtyy8 bvNafMseb7AkdkOoRRY2L6XWd7Dn19hEznavlQWLFzm+ptfYfDu2fhgqkQWN 2fwRGwc2n8V+4sFcWbBaCSlcuszmcz91uChNFtKcPz4j2bH5EmwCJOJlITdd 806HNZuv1LUsIEwWZn5iofUX2fXqDhj/5i8L7wZLiR0WgApnH8ifdJNln7/5 zsuZsesnkmZe7iALoX3RxQvH2XxaBZEkKzavKc/4+cNsvhPVL0PNZIG0dbX/ 0H42T+S7zWeRLAg3nqdiXTZP/nf7uq2y0GPofviQJiBN1kKKqposqGwNCTlH AcTPL8H3V1QWXIo1JzaKseNXpuyxXScLjtLLI03r2fEb6bq1/pOBwSiN2GVO drx3TYeTf8jAJpf0Cu53GBVm2IpzD8vAupiw8mcvMUqpv3H0Wq8MKHIdhVP5 GLlzRJfrgwyoFgbCF2+MNHzbogcTZGDB2Z/eL4DRp6yMXX8jZKAhPIXB87MW Pez0HpMIlAGpDK2JSz21aI2yqoGpiwxsdCm2pT+sRYOdwdMtRjLw8lBjf7xE LYpdvpDybZcMmOj1JR/6XYMOKW89yKMjA3tHS5Y0umpQqe+nNAM5GQjufZT1 IKwG3VdGx5nz0qAQYSNBm6pG+06J/+2ZlIY7lvtlFxur0YLvZObsqDRUDStf dH9cjey6UlY0OqQhtHZcdcPBaqTvt5D/PEcaPs/cetQUW4V+dNHXx56Vhq+j v7Tr1lSipyuhzKIT0tDh9m1T2JsKdEbF+tJrQ2k419q8EvmoAtX7CVXxbZEG /dN590zUK1CyyjXHgHXSINnSH91jWI4O+yu1OFVJgfRaJ5E75gy0mrPkFk6X AsuTwx4e4gxU2t1FysmWAkUPPtPynjJEUr3jORrH9u9wc5A5UYYWuj8on3OS gk6D15RY/VKUo5oUclBGCgieCvYyv+hoo7t9TTRBCnZZetv0pdNReL3Or7dr 2faf+L83x+nI6XyHjdPsJhh7SroUmkVDWpH8u2OaN8HGIxdcw5ILEXPGZ+7d jU1wRoXL6/tsDmpiWlu7NG2EO5LVRbscHqHPhmo7E65LgvLLLTkUoVTc8Nf7 obC9JIT8tydx0+s0nFHE+hNxThKaJfDTi0ZPse1G55JAQ0mQkghJH+d9hocn iqiuUpLAISmjqRiRid/H6codaZYAH5vMLNmUfNw1YrCGU04CAuKG8mMtynBx Yoytr6gELMZem9/5qgzHHPkE8/wS8DOlzax4OwOfLAvym/olDo5NZru5xJm4 PbTpz/tWcXiw33xL15ty3LL56HeGuzjM7Tl0O1y3GoOfebtTuxjsNky0Xzpb h6/ucX2W2iAGGffLw91C6/CGf6Hu7ZVi8N3hzZpCRh22vF0pq5UtBm3trtwX CfV4JVDm+lyAGMS0dUeENtXjnaGjG7y1xSCL9JmHS74Bfzq0PJqnLAaF0Y8i J4wbcDi/WPl7GTE4oJPSEOTWgN+GG1nvXicGjKP1V0uaGrBnZC6NY1QUNlPi X/2+3IjLYq+b3IsXhVtTakeWEprwBdNQcnm4KJzhC1khVTbhNaLpi2O3RWHv 4Szz4Q9N2CyhK93YWRTMDcWslZWa8WyS7qygkSg82t4XzHjRjJMtjjft2SUK Y1I1OmFtzXjfxivJ17eIgl1Sm+XERDOOSX64r1NWFPTOu+dbUV9hrdSl2Ph5 IgxIM3+8y3yFBy6KXmmcJEJGR/wewstXOEBWQ//PKBH4POS0Oj++wu1PLEfN O4jQJ3I8YUSiBTs/q9ORyiVC+fGvpzUDW7DopXdrjz4hglVMgc/dlBZcrTj3 3jeBCNa7jjPOlrZggUylu0N3iFB8f3iv3+cWnJd9ryf9HBESf7fOROxpxYLh STqrJ4jQ8766KvB0K3Z1yo49Z0gEO4nHmgPXWrGudvNJohYRXtzdw5Wc2Iof EvuLrpOJUHlb+DP3i1b89/dXobZNREh1XLneXNuKoZL39V0eIsyJXcg487kV K6SKU0f+EiBAq/yj3J9WHBxAidg9QwCZFOLM7rUsbHzA6PCfdwSw7xXsvqnM wgWUMzmnOggQf8/5RNg2Fhbmv7y2qJEAHpkX56YOsHDv6+DGKzS23XyrYpYV C+vREpQaMgmQUJHt8vsaCyfHZgaRUgjAu6nHOtqDhVfcyj75RhPALi9i+FYg C1ubN+59G0yALqeA/uf3Wbh+R+9TXR8CJAUZbZFOZGGy9Jd/Ma4EeHrTfvhd GguHrv6ynLInwMDZ0z0fs1j4x/CaWuPzBCATI7jVCln42EtRmeyTBPh0xv9y eSkL0zKVfLmNCJDzkrYQVsnChNCt7630CbBrqLQ8FbPwLccDO6u1CODCpZsz +5KFB46aPZKkEKDD8C/rXjML79xst+AmRQD+o3PqF1pZOFXEzbxTmAAPBfS7 XdpYmONXEEODlwDzYXIdta9Z2LYvTix8SQRavVS2Hmln4cbyDLevMyIgOSQj SmRrlZSS7n1fRcAkSihUjO0f7vdyy5P3IvCdceaFCYuFJ626Y5Y6RCB2Z9bj plcsfHLf6Ix5kwhkSaz1v9nIwsVKcydKq0Sgv3DUzbyOhcXWchcJ00Xg7T+B vBvVLOz5nSDknCUC4z1wuI7Bwu9YCs4tKSKwcagoyJDGwrsLt7SRY0SAu5o7 YiWHhZ9G71MPDGHH99cucewpC3PdPBU+5CMCvAscwzwPWdj+tO33nTdEwKI+ KtPsAQurbQrMnjsvAk4/dhcEebJw5HIM70kTEVC5zvBlX/XxzFC6fb6RCNQZ ffx0nd0PZRl1ivbaImBqulhG3M/CkiGdgXUUEfBw8X6do8PC3ldHRmSkRcDM tK/DQZGFDTQ4n/bxikDC/OaNzhws/GyDyL8ty8IQ8i+NUjjZinlmSZZRP4XB x7uXJvmuFbcyDKQPDQrDAdKxP1dorfi0we2HFXRhIJis1Rs+1Ypva1o4s7KF wVpTZERCvxXnSWvt+5AqDHEcqoQYhVbMsfhxnCNcGG6E9iQZTbfgfDpCh2yF gZ/Yk1sa0IL7n0iInrMQhjuTxPkpmxbM9WB67NpxYTjRuX7L1f0t2MLxSWzU TmHwOHfQUnxNC16j+O9LH0EYFC+qV57zfYU3i/RXjvEJA1dNT1iwxStcunpR 7vfKBhBrLvpvUucVtmLW/LerbwMM/w0ZuTnWjBkqfhtZIRsgzXKQZH6oGdut X7489k0IVlUui9uMNuLKby+EBXqEQI7yPudESSMWbjhfuRmEwJX71AbvwEZc 5Vsl6PFQCPwisjwDZRsxYcq7lOewEMT+e2h+6VgDho5FTsU8QVAOcpn2DanH 4gW5L4wSBYF5Wd1ax7geO4WdPe0YKAjVk8czlQXrscS+ihz6OUFYd/jv09bo OuxS4nnCYL0gMO7QGjmjAMskzj++6CQAxsbJn363V+OxsoQLA2cEoHhZXG/P lmpc2qsjbbpXABaOCmmy4qrwUTHXlEPiArCSXRrBNKnEvvFjj3RgPeivOvxb Kmfid7FvE/lF10Pcd80tNtuK8cOoquiyKn5wBqDd/ZiE7YrOntTK4ocnIrEp XsnxWOvN/IYX0fzg8x+hzPxEDG4W2hr11J4frsSULn49Foz/ROZHRmzghz+T TwaTwq+g0/dTw20u8UHduaj9x7Y/QYSwgLuC69eCc/JHbf85BqryUoib+M0L 2S3zMiPjTGTn2JjOGuaFU3c9L175Uo7KjqzHYQxecDVoS+p8X4kshJIWeWx5 4UBaaFdjby16ElfoslrOAwe/lj0s8nuJqGkfLKYvr4H2RpVt3X9ZyKhEX6Oz nhP6Rm56fvvdhwKqXJSlijghQFtL7vzOflT+Ml3ePoUTJi30Hd759yP1nrXi izc5Aftc81hYO4CEf3evksic0B3OZ5a86S16t82pw/UeB3DP+7sVG7xHH9x2 fCM9XMUbxQ8GCIV/RJpBSzef5C3imy6ew5+nR9H9TXviRwIWsX1SkWEX4TMa p98uVTy9iFtrXM5k6n5GOcM8v7P/LWDr+Qqjv96fkeIeYXea2QJuWsvgP7nm C5JcVPKsW/2DZfAVL22Rr4jr+nHf0VO/cCL8aBcVHkPWvDGPySq/sIwoX2eB 5hjCqd3VV1bmsKxUQq7UsTHk22axMp49hwW/H/p6M2wMzate8v+1PIvFTxAm +Di+o4nPHrd5sn9iB2LgsXOfv6O8sn38J/5MYutM/g6HkHGUu49vwT9rEr/4 +GRZKnUc5bx5/bXwzCQWMP+y7nHJOMr6btEgxJzAFgbfA9cMj6NnMtcD2j3G sV322zUu2yZQcnDK72OLY9hPfHeL5dsJ9Ihg89kvdwxf8VD70TIxgR4+oXQX nB3Dw1FNG1f/TaDECjpNsPIbJj6yDwfyJIqdbL722vsrNt9vrZDlMokiTv8a Obo8ikNP2ppU/p5E4Z8qOnzzR/G1+LfDiTxTKOx6AM6/MIq1tva56olNoXth 61IFaj7hy8n3XrToTKGgGpJFm98IDu64cE3WZQoFGn81WtYYwZwfygakfafQ nf4XutShYRzVuj5qKGwKBfzcRry/Zxgr+Bqvf/F8Cv0xTn6ctPoBP7F2GbXt n0K/7Mje85Yf8GrOgo776BSa9aeZm+NB3Hg35diR6Sk0VdxEkLj9Hie7SWvs 5J1GXzfNhSZyvsURH+R5KdrT6PNW/8t/bAbwDpGDXPv1p9Gn4/wHztT343Pv J2+TDKfRUKDcP7GgPvzj56ub0hbTqP/HkVsJa3pwv0WqvajPNKqOWGmVuNqN W94GePEHTaNn1CJSMqsLj1SL3oPwaeTiQmhLi+3EM2ZF8m6PppHZhgZ5+T8d eLVGwNv16TTaSbvlkXG2A2/oarPVzJ5GAp/phif3tuNIEjN4qmQaDZDFfprx vcb3fbRjZyqm0fMrno/PvmHvi8FF3SV4GumP75mzvdiCHd78zfBrnUa8Gs/S rii9wsEsaYG7b6ZRlwuPsdN4E56Knzh/pGcaOc6ynt7yasCl9366SH+YRi9y p1M5Yl7iNFKmgvTwNPofj/aE2g== "]], LineBox[CompressedData[" 1:eJwVmHc41e8bx1F21jEyj3msc4zkW8p4bjMzhbLbRhspNFRWSqKUVcoqlHWO ceznkH2oJKWMJAlZCaWS3/n98/lcr+u5x/u+7+fzua7nUTx02smHg42NTY31 +P97aFDxFd/t5+ihwmMl2ZE55HTHf8f88HP0tPd7vtLHORSzi/PBt40taMzh 969fH+bQXJeJ5ej1NvTswLOxrz1zSCVuIG2oqR21xPRlsnXPITeb0Nn+Px1o kq3U4UPbHGK0UFNenuxC7/m1m1/VzaHFyJ3TnU+6kd3nAxUzlXNI3ewbtH58 gdR+HBxnls4h6/2Es8P5r5Cazt0DXTlziDpgR+yT7kW/OvhdRmLmkLS8ulR6 cy/y3hvD8AqfQ1GH1ovtP/UGScpdME08y8o/Wcc72diHYje7SMgdnkNsP7WW /vr3o7F9c0deb59Dx7bzzTcS3qO6S+yt/Lpz6M2l8amYuveIp88/elVlDuWv fzQiLDyAiCnRH/gE59AugnCXCn0IFXqbmbwenEU1e6ZbJw8MI2tp4anel7NI Ja29sZjvI1Kf+x6b0DSL/iYwPGV1RtB9DuUr/+XNolcSYbufRHxCWxInys1O zqIQlSmjGo0xdG6z2tfU6RlEsXKreRA+ht6OnPTcOzCDRvxat17uHUNyXwua ezpmkO2zbD2LS1/QJt+rD9Y9mUFEPU/1F6/G0VLZUoGn5wxqRV2ioyGTKP6P zYhSzTS6cHD77eauSbT5QY7dWO400o3MF8xTnELkHpF6/4RplN4axXuCOYUi +7ZL1R2eRqccjNeWiNMo6JxVfTLvNBL3LJ7ibWXVddd+4ZTtNxRLHKwG8Tl0 vfUhp8Hmb+jvJ97rIUfmkC9/g0GPzDcUWE5LCmKfRz6L+bvOTk8hV0NBvZFH 84iN6fU0Pm4KKdu0nKod/I5Kki4q2DdOorojmycC9y4iQ757itcEJtDsfaGB YZsVpPxmyvOlyRiqW+6Q6ApeQSecEisHZcbQ9d1RTtWPVtAuB3fvl78+IxXu lY6kpRX0fMdvpi/tM/IIGq2yzvqNJMiNX06qfEat1hXJtF9/kCldOMNz/Sh6 uOThFJP3D1n2LEv4nv6I8tR6x5I5OOBXg7JQp+RbpBv1bHPBRg4QtA91GHzZ h2pGIiNqKRzAfSlvHfu1PvQiTV9hZC8HXHygshK99AYt8yd7ajzjgIP/SXek 9/Yii3m317XO66A/gNel924PGqkaxiO560GUsybozZFOdEycLvijej1sztcP PjfQgRYDE7w5X66HK1wlfy84dSBuMvzRWFkP1lKfP1WZtiPtjKwtZxw4wfRk rCqF1IouXj1SxLnMCYni9vxX2ZuQpO1UuuYObhg1uPhPcWs5EknQ+9fjwQ3u /GPUrS5liO/N+YNhp7hB4tLPtj1BNLTqza/efo8brqj3nC6nlqLRQEqFzxg3 2K7554ecf4qK0k69zLzKAyVf+dpvkNKR2eTCuo11vJAYe2feYjYFG2ob+jW8 5AWBlh2lZl/Ssf6ZyE6fz7ywb9iRTHyXgdVWRW+X8/HBw6Zp+ad9WXiDyH9E J3c+6HM9/iL6Rh5+ZxBiEL/MB4G6N0gy26n4ROyfE+s2bYC+nzYKN6Vr8dz1 PTXOVhug6XtSeFtVLQ6KK+HO9dwAama/e3btqcNhtw5nW8RsgPnVXxw21+tx zF3mu+iBDRC9aKtWNohxZuZ9M54YAYi/Kkd0kWzCytlLCW73BeCXqNj9Avcm /CTHcSi/VACkPIz95dObcNGTdaE2AwJQlK30+Zjkc1xTeLzohq4g2GosfjrP 14z7qgwlBQYEIcvBP8+9uQW71dzz8Z4XhO391Ycyfrbgwdo5WhGnEPzj7Sav abTi0YYch526QrBO4uSc7M1WPN/MH5kQLQQRxnN+TZZt+Eyrz6uP6UKgEGP8 8GdgG15uw3K6pUKQXNl8yC6jDa92nql69UEIhsWU1R2/t+HoiZllHklhWL5n EN91qx1bTabLUZWEYcgthO1PWTvmmdph4a4lDIfEdZJs+tvxzW9ZtwvMhMFS z1/HmtiB78zuodieFIauCzl9vY86sMsch/NCiDCw/V6r5m/owOLzJWHpEcLg 0zjq7jvQgVO/87ZNpQhDxLE5v2jRTvxosf5gXJMweAefGjkX1olTJ7MJ4V3C YDww/tImoRPfGb72POCtMKwRtYT353biqPbdpL1TwqC9TcrAqasTh9dveWu9 KAz/LWeyb/rYiUNoMtcM/wlDVXbZR+fvnfjYgy8TCgQRaF2KrvcTZeIjtzvT RGVF4IN5YqW7MhN7x5TYcqmKQEtpWeVtPSbeFRBW+G2bCNgZxQ737WRiW599 3sPmIqDHPC/x2ZOJzT3MBXscRMDmHfs5A38m3mIhEFB5UAS2B7t/qw9nYt1t CwoFx0XAQW5KbS6WiTW03/XcPysCU7evvT92h4mVlOsibl0WgavE8+mb7jOx rGTW5qvXRUBGppXbIoeJxQVixs4kiUBUj1pj9lMmFuQ4fs83QwRWXYWO7qQy Mc9PRyv3PBG4deBB7g46E7NP6/+0o4qA7GqaTEIdE/8ekco3qRWBHW7nQ0mN TLzY989tU4sIWBx28udvYeKZzs+8Ki9FIC+0L920nYnHcXuNxHsRcFnc1dTe ycQj5UXHeT+LwGNGXlJWFxO/L7gj+3daBN73O7R2dTPx64ch3bPLIjDDMBez e8HEXUle4Z/YCDC1ILJdjsWtsaY6b/gIMGTavGzOsseXVEdaxQgQoPeFn8Fk 4qog/tvVRAJ42IQZ3+lgYprfvGmhOgGeOv7eXdvKxIVefQsP9QigGO9EMHrO xI931+TcNiJA4q93NuKYiR9aPXKJsiLA1X07WnfUMHGqYRRnyC4CyIVj1zfl THxH92jlUQ8CRMjWvaotZuI40k4/ryMEyBIU4VrLY+Io6c2SjqcIULzty4uH mUwcLiTZYRpKAM8bResfpDJxyPrVMP0IAnwcVYv8mcDEASufNNVuEmB6bY86 LYaJD39+dnNDJgGkhnmOWQcxsVd/ovFaAQFIMxXdJD8m3tt9dvZ7GQFeT3iN +7D2izUd7XrXRgCztfeDImZMbFaowt7Zw6q3RDXpsj4TG2bx0uoGCCDS6Fji rMrE2nG9otlzBJBQ1Pykx8PE6leqmu+usPo3uvgR/erEimczzl5bJwrFP55L 0L92YrH9fu9ObBSF/dfoYhPNnfi33p/0rUgUvg+rSwWEduJo7K3yy1oUyp17 fJ2PdGJhe0ZRlZMoGIvFBxY7dmJVn2jGNl9R+CS4+/FLlU7slCI0bhgvCn+X zDd/aO/AQ8pBp/8mi0Kg4Ae+lNIO7F/65lddpiiYDT1M6U3pwOEdafwm5aKQ 2e019fJIBy74o7wJBkTBKybz/MKvdqwfG1PD9kUUTi+PLXcMtuMGsUnzxllR UMo2u6rBaMdvtIr3mnGIQfWyInd0dDtmO2Bw0UJDDPItZIS7+NqxW7N9m3WI GEwfHh9LYGvDn3eV7OK9KgZTPgEqx4da8akhkQ8dN8RgW8sp6ZHqVhy1/Hba 9qEYvP2xo+Z+YCsuUT9IcGgRA2P7t9/DBlswV/xZ792i4pBPUT/4NrMZV+x5 +MO9RJy1/wYb9k434igG78JstTi8SNTXbq9pxC7ks/ORzeJw1PP0j5nYRrzI Zj9T9F4cZO8nVHmpNGL9wpVx9vUSUFe7sXvBlYHLOfZ8KHCTAM4TpwLrfesx rYS/cYV9I0R5bPI1u1mJS3jDbqW5SEKcA5ldoCUTV/rLbgzbJwnsu0vKE748 wg1t+JGbvySEmz6/n2L6EL+I5qJuvCgJO8SHJq/+ScfT7Hd77+VIQn3umTPV IXex5u9iyTsLklBRcLLpoE84fjw1ln0jUQqUCrN+TJrfRoU2seRj6VIwOXPp /qOWO6g8n1xukysFTVIfeWss76Jm36AWniopmH8ZfHkNUtDo6NrXmI9SsMkk amhNKQMpDEhrRWpLQ0Hi1mbHHbnoPnMX/UKXNFTSjhd/nSpGEzyr5TrvpOF+ vBX1Q2oJ0rcqoH3+JA35oQH5pUql6AWDvdjupzS4B7e2CXSXIrZKWq6MkgwM mDG+LEjSkG+m2J3aEBnYURCZtO5mOaINMRJOR8iA5Ndb82/flqM16ZPxyvEy YBQ4rDugUIFS77XExmXLQJFUxkoArQIxb5y77NktA30bdA4VMSuR7tn+E3+U ZCGg1VXLq68KXaJFHSvRkgVZycKQAkI16pzT9T9sIAsNcec4xB2r0eFj1w8z HWThBUmaYN5SjZL3b/e4HyoLkxvVCaNPatDog3FXx0hZKNb3IPMM1SCdD3f2 rLslC6VTJx5ZEmpRu8u3XcdzZEH0DDlr3fla9MfmwQ7DF7LA+CpPDzWpQ9bX rC3n+mVBaGsjyepkHbrbvGiW81kWlHu7n5Lu1yFt5GDCvyILXwhveyQX69AB /X/6A8py4EP496MxvR4VBT7VS9CWA5Ev+daEpnr0u3ivrvk2OZitNREOnKhH SRol5Gc75eDf7/osN70G1Eo8oHQhTA54Qt9/aKtpQLa7LJ6GRcrBtuCN5MD+ BvTyqrpeaLwcCL3pkbVaakD9Y/OmZ7PkoKdN+UwQBSMvib6OM8/kQNNY5FmH FUafdlTvDqqQAy6CEtn+AEZTT68ePN0hBzF1MR9fJ2J0atBn8mSvHMzlvhR4 l4fRDwHbwBNDcuB0TSGUqwGjvwGEq0e/y8Fvg/MaX79idCV7mcf/jxzwPWpI TP2D0fo3HxJ9OYlgMW9cs52bgQS25mQeliIClW+d6HtJBrrjf039kDIRZvV+ yfIqMpBE+vHSA1pE4MsyJ79UZ6B0pqPB/q1EcBS13UPWZSDi6maGtykRXkW2 lMttZaBsbUlrLzsiKBo/93lizEBqB/6+9NhDhNjPWTEt5gyk+7z5o+tRIgzp cGe07WSg8sV8v71niLDx9ssPT50ZaJtq/JzLJSLckvwlSXJjoAbXwBDna0Qg kVyvbvFiILPre9Z23ybCUzo3fNzPQK01267tuk+E3xS/SPnDDGQ3LSfk+JgI UjOEiz99GOiVHEeKQwkRdgqNe/n5M5CL4zjRvpoI3j+WPU4fY6D+K51PbJ8T YfTl3SKhEwzkTSvWtukmwsR/lresTzLQ6Oc7lTveEaH7eqOB9CkG8hUPMbH6 RISLgYtTUSyesvJstfjGymfwcyyWxadC0U7zJSLoqwkdVWXxQoHyW9M1IoT3 Pa31ZsULGeDeB7zysPX4fmUdVr6/G6a/mIjKAwx+mUhn6bli8uqksZw88ElK umax9K4PKF8yVJMHZ53ZGjNfBorNSr20fZM8jJy+cPgyq94NvRc5txnKg965 b1muBxjo9vqD8Vst5WHvf5c7mKx+SWyxFN/iKA/ji9d1Bln9TPfTyNB3lwdT y1Pk6y6s+aUJkDYflgeZqXSJXkcGyun8XrjppDwE1l6zr7FlIPW/ffq6IfKw /hJNE1kyUKFWTZ32VXnwLrwvfAix5rn/oYVWnDyctHy+X3kbA1UkRnSR77Hs wx9fiNRjze+H7aB6gTzYTB2mKqqw5kfSOaJWJg8GjdwPDsgyUNte0WlSvTwc rZhdRGKseVUP/FHqkYdNyrb5nzgY6NPlEzJyK/JwM1Jo9TwdowsqX+uD2RUg YItrVHQ2Rly8krMeXAowrNls/vEmRrKvw3aqCSvAQUU78aj9GFkfMRZiKCsA HmccKvrbgHqtT6En6goQ5Obyw260Ae3TenT6ppYC9ISp+5i2NaDgZbZXblsV gPThzqp+QgPKjG1O/G6rAO/GJFW8NjYg8sklxjtHBVjst2O++FmPKnerfq93 UQCaSnJz5rt61CUdu/vGPgUwzfwn53evHv0qtCMoBynAya+pxAzeerSr53WS S5oCpFscHyvvq0UDFeuatz9kcVlyUl5hLfJN119UyFGAHZdE7myIrEUXDye7 zBQqgH5D5D097VqUv+QuHsNQAN7bC2OE8BrEJv0pmf5VAc7tTDzuwFmNSg7N pUlvUYTLxCMxHrUVyKsyd/1xQ0UY87u0LzC8AvHxeZyuBUVYCd1NkTCtQEeo zRZedopg97XbVaSlHEmzpc9lHFCEU1/qxda3l6GYDAtLxThFGDp8M+B2LRXt 60+bVxtRhPCy4i0XXzxFG3Za7PjvhhI83S7Vasx7G729L/5TM0EJjta42m6b TkCPJsefKNxVgtvtx+hurfFIL/o614aHSnDea5fz3IXryLXuRcsoVQlE9AbP Dc5cQdma7haJ75Wgmecc7WfbfMNW7lOm39SV4YFBitmOqETMtgd9H9FSBjEt g88no2/jzmzhrLd6yrDDdYgjN/oO9jIpY2syUobMZVKBeuRdHHH2F07dpQxW Kzf7fgem4q7PESZWocqQXCW3vEEgEx9ipBhmtSnD06TFmhCDPLzz0gyJvVsZ vN3HBDcU5+Ht282FD75WBoNTMcwKpXxMKJ8dUxhShp7kK1kmvAW4Mc/yVuaC MpRD2smBzqdYIeHHyCM5FfhqxBHMSyzGG+xtmGtKKrB2eokTRxbjXzyPKvar q8CeyaqthyaK8csI2xvym1XAyy6wyL+4BIefy9r8yFoFhC57iGckl+Ihb8eY h2dUoIp/u83G31TcLv044F+oCvDMKsqNKdNw+bvfHvvCVSD9eCdJ0oGGb+5+ okO8rgI9Epw3aRk0bGS52p/xkLXepF+YvrUMq3M4P1/NUQFKuCVXnFcZFsP5 Rd4FKqB10/784JUy/M3AJUKuXAWoYtx/HrWV4XTKM3JGhwosW/YHpDiU45hJ NonVFyqw2v0sLvxkOQ56spfN+40KsF/487LxZjm2VeDok/2oAqZf7Cs9Osrx iqh7+INFFbjcEEJu316Bx14V+/9dUYHHrz5mR+ypwK/i1zt7ralAVMjJq/dO V+B87lI1WT4SrE7/mW7KqsBuf7h67suT4IEj5Z3evwq8Iep+3qgKCQ4nKGlZ iFbixg264RqaJHhBPx1OVavEmkR3Ml2fBLH3fXUf7azEH5/MsP/bRoLqV42a 8gcr8V2diH4LRAKV/X3Ov4Mq8So8i35tQ4I7eOle491KTOtAXlKOJPil+PV4 UW4l9nV6o3fAhQQz6a5TP8oq8avDqx9n9pEgqbbmRuKrShw1fbtS/wgJBN49 vDk+VIm3nVWNv3CUBMEln5aTpypxdozjdt5gEiRWeC9ycdDxXqEx4V1hJFjW OHijdQMd86eGfk0OJ4FFl/OtEQk6ZigINAxFkgBfO7VhjwIdBxdk3VW5ToKF b9vFVTToWF1vy/Hjt0jQiRPrHTbR8VBNpyktiQQDYUnE1wZ0fMd8v+RKKgkm M0r2UBEdW3X9mEUPSTC1lhL1zZKOf7vEtsTkkODUtFnPFTs6LhmSfdCdT4KK LV99AnfR8RFfapBYMQnOUlYC6l3oWHLO0sazjASXT6uRfNzouDvkg3x2FQn2 VrhW+3vScQTb6eWJehKMnMjxb/em4y3X13XrPCeBia1LUNR+Ov4mkppzrp0E YtUjUhkH6DgznXK+vpsE5P8mnhAO0rGLcuOu9b0kaLiu4/OFtc5buEfNrp8E oT8f5IqzuEF/avX2EAn2mOpX5+yj46D68Df9oyS4kEn4k+BFx2pWos/kJ0gA j461fnCn48EXeVd9Z0hwfODyhai9dJzoauRWtECCpZLs8HgnOrYYeaW9+JME 1q1kg2UHOl7x9+E0XCWBVUKIGOvwiIu/rwxc5VAFtdxPkRNmdHzo/C1aO7cq HBZi/A4yomOJdcrXhQRUoeHSvu/7/qNjZhx9/16CKlS7rnwu1KJj/YyRDWOy quCX8KwxQJaOJ0hnP2sqqUIgZ1PVVwIdZxTz1gSqqcK1vPbnTTx0zMXQ81vb pAo/3Tnd8hYqca11m7HVVlW4NT7PTxuvxAE9nmLxRqrAE0TRUP5Qid+PRjVK 71CF9uATRENciW8dl0o9aK8KT0I10efSSmy2WHQqf7cqyONHHotZlbiQ853M Fi9VeKybYOgSUYnD1TXO7Q5UBSmN91FEo0q889n728bnVEHGR8L0pGYllte+ UaRxQRU6JOeTjSUrMWPztzH2aFUY+liQ6bNQgTlQkTMtVRWYTwwqvmRW4NeN 3qcfZqjCXfWP5c5xFTjHQjDuRrYqiB+UKbM+W4EtbE83HSpk6e+8GN+5owLH 7Nm0SZTByt/xOsDsazne2//Jfq1ZFWhnC/lWu8uxmucd/28dqkD+PvzYorwc tx/48eh5rypY3TMVDL9cjvlOVAgGf1WFlO1cfqXC5fhWxLbpN4JqoKLN7/OK WIb3cU5xN4qqQc2iHxf+R8M6senKRZJqMMnf6WU9TGP9b/54RCupwXVh8yHt BzRMSKvv+G+LGqBox2s+ojScXGKal+zN8r/BYe40X4ozBm0OuRWqAXFOrf7m 20Kc+CK8qpiqBqtngh5TwwpxBKNMkJOuBsdTU+r/ky3E/rlytdRGNRD3zBzx 3f8M65/4Lsr/Tg1uRKXa1Q8X4K4/qS317OoQ33QZWp8/wX+lJ9SVXdVh6en0 BgmjTOzpHjM3w64BjHPefQHhwfiY5bsbk1wacH2hnW+rfSAO3aSu+oVfA3JH hgRK/juBk3k7vQbFNcD+gPP5V9/24dfVAp2dGhqg7/InbMuQM7KWvpebt1sD RHc2bNgmHo62DOS4H8zSYJ3/NtGuFyUhy7bFRa8nGmCw4MpmdewucimzTHR7 pgHWDv/8t6veQ0FxX1sdKzQgvEayveZ+MioyJOubdGjAcuSz4ccX05DKA5qg zHcN+BRs1PiA8AgRvBufvwFNaKzVKVKuyUVTYrvt6JaawPmvtruE6zFq7Bp5 nWarCU7BV0jZTo9RgBHb6D4XTbDf6OZTNvEYvZRBbJN+LP+8iyH7BPLQzQ91 Rqu3NKHXOMsoZWsBOnLHvvljkiYcd1T/3R9WgAxtB+2aUjVBpFk98lhtAZqq /uNxLVsTll/LLYUYPUU2advDRCo1QTDjhIX0lmeIy62qgjSkCVODjkvnuYrQ sJC1Mc+oJgx40JIoxkWoou1d89S4JpRIufDInilCR7b+7C2Z1wQOoy33SweL 0HOJLQvb1pPB7HFGVPKTYpT+oiVMlpcMX/a/eCX7rhgFxexhXxMgw6P5XQ3v uUqQ0nKwcPNGMnAabESLh0vQlb4y7Z1kMnTGXZSx4ytFbvHmlbq6ZJjVPPvF W74U6Vj2Gov+Rwa7La/ZefVL0XD5gn2/CRkCahI/qXqVIqO7m44fciLDZsWz KaF5pUjMvnHBwpUMpc5xxpbVpejbut3n1bzIcO9C/Nu8zlKUfibg+rQPGXJ0 VD9pTZeiFaeSvHNhZODqkxzboklFi2HPjz4PJ0Mq94mNo9uoaDbzHVk4igxK MtmHBG2oaHR2raTgFhnOZDsfmvShokFxsaDlJDLENLqXppyhordG6vrmaWQ4 tcXNpvUKFXXe2FU1mEOGjNPPK3LSqKiZeuS8RgEZfp4tNnF6TEUN/aFG54rJ MFYVf+lKKRXRVLMYQtVkKAq7UezZQkWFDhURXg2s+H+EgnheUtGT4A6Lgudk kDnmdku/n4rSm763m70gQ7OEfTrfJBXdneSMS+glw7NHm0PK56nolrC0w2A/ az7pLteGflJR7FZtIY1hMhzN/dkR/Y+KIvaZ9Zz9TAarpA+mRetp6GL03qSm CTL0SOssOfPR0LnCY3uEZsmQvi9tJkyIhgJ6wzd6/SDD0HFtA3kxGjr++877 /F9kWHsQ9MX8//cpinn3l1bJEDruyjshQ0MHrGu9zdZRwEnAqJZfnoY8Tr+U T+ChgH7buHiJIg25JH/+NCBAAY3ma1tfK9PQzvqfOeqiFCBll5ueJdGQ9Ri/ 71lJCvh1+rqnqtKQGb+CepMcBVoMVp4YqtGQkZ7+lKAyBbi1VPfuZ/EWd+tC T3UKOLauT17HYt0rXqfytSjQHsuVps7y18wL0F3So8Dd7sW7L1RoSOVF1IKp AQWk5GablpRoiLiUWn7LmAKDZw7vf6hAQ5KyRecGzCgwHij+tF2OhgjmjQbq 1hR4GywyHixNQwLH+n4HO1Cg60Gxe44EDfHcnqxrdKKAdt2NnS4EGuKoWg0X dKPAGb1rIrECNPR3WMTU05ull9ayYMJDQ8ucquvyD1Eg6HuuZRgHDc1Ttrcs +lGgY0f9ga1/qWjKeec105MUyNEfyghboqLhrHP8AyEU2GPotxQ3TkX97Te6 1S5RYLjdq9drmIpezz1MCI6ggMHeox5lfVTUatwmKhhPgYM8VwV+NFER48hA n8cdCixp6ksMVVFRTdxcSl4KBdwoVld3FlNRyfuNsqbZFPDX6nDvSKGip2yU 4fg8CgR+v1jXG0dFuWqQ+aGQArq+G074Xaai1LP+KsF0CtyqCK2nsL6HKyLV lLwuCqRu4lcyIVNRst7k5rQeCpRe2ZtZKsvaz85ShnFvKfBUoiweC7D03wuz OT1CAdWKtYLy2VKkK73dd+siBVYPOQnxFZYiK8NjJzVWWPGK7OROpZciL6/0 YJl/FNDZZFkTFFuKYh/+jljj1oL8rKb+/YdL0YhS7aM2GS3ozK3PeC9WipbN vz2pVtCCg0Ub+Z3YStEGH5niZyQtmOAQ3/PxbQkyyLtQl6CjBTTjueltV0tQ Itnovau5FvBG17zN7i5GoF9PmDimBRIp0RrHrIrQ3j0zUh9Oa4EktZPxgFCE TpyTU+wKZtnfei2pM1yIUqsu6ZSGa0FZnMpA6JlCNG9kYh96RwuS1Xr5O5Of oUxLHM1TowUC3H/tqxoLEJtr4y91Xm04oH7fnqP8MTL4enZ7tKA2zH72Sjx2 9DEKDNG8+ElUGzh4uejOxMdoNCVpLY2oDYwtH+qpMbmoud+Hi19fG5pubaMP 7s5BsR58YjP7tCHp1SGr5d5MJLzPWYdarg0x5k7stTopSN7ni8+2Azqw+J/R 1ZRJF/RLIsP/EIvZiz0q399zQa/bXY7HsbhW73aurJkLiqE0BwyxOPnKgeLc dGc0+yP7wtWDOsBhaxJTb+eEGiIO3O44pAO7dE3CSF6OaF/mQJ27jw6Ecfp+ yhi3QAZOSTiCxbOx8elOyAIR1ts1PWPx+vGLX3lSzVGrX03bKos12sfgvI0Z 0tZJe53lqwOa0b7EETeEVuv3Tkz66cCfVjFepy/66O1pwW8Efx0YDpucm03e jEoVW2cMWVw42iefYK2HjkT/9yOexZ4/C1tprjqoy17s36ajOuCQrutH/qKC nvxjsnmyuPxYmmG6tRK6Uhq5LorFGSGHr8m7ySN9sR88b1l8OWHfmty4GBJs fcq/xuJIthdzhzyE0ETIIUH1Yyz9PXcXcifWoyYNaZHdLFY/kqGzfnbR5MFA j+h5FrcGVH1iTPqY/A9zuUgS "]]}, {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData[" 1:eJwV0Hk41HkcwPFhcpRIsY6irLQ79Pv+RgdG2LWLkrAV6yhkJ7RaOzFFJOKh 5HGUO1e5EoVy5CHx+eQqiYypEWYVtaLoQI5dads/3s/r//e33GP7vSUZDMa+ r/1vzqBA6dRRNjYE1g3juHdT7Eg2FefNRuPcoyJ9TUsIGve2yvFko6Tx5aUS LUfYO7cQ1OTERhXDlEUhywuklLQHJC3YqMWWazQ0OwE8G35e3Do2PvpuKUsz KBoO7jOtz1Fho6LHFeua9rNg7SLdW76ajXKPd/zUrhYD2j5ZzB4ZNvpNffIo uhcLfZHNPsozNMazwrgOrAtgXr+G5D6iMXpKtTaQpAFBsVXFfRoZItc+ejQN 1t4v9oBmGluLO1tt8tJh5smOi8N1NJIX7ofFapeg9AN3etNVGnsE5gKBRjas YVXXV4TRqPZZ+cWupjz4Qof1QjCNu8Pd7i2y8mHCYNfbnuM0+mxLvjaYmg/t FoMa0740es7Xqv/gXwChh5gRRk40diY4Tdw2LIJX6Q47kaZRlHKMX72yBCro TJ0jujRmSgdWemWVQEj7kKSCDo0f3abtf9MrBYVZXzioTmPR2iWJ1H3XwfjX CM4ck8ZfIvpJKJTBssk2lctLBJ9EpsZocsuhO1ruk+UCQcfheXmRTAV41aRX Jr8jOBbE0ZFxvwmJSuV6dD9BVcs9SerqleByY0r2qZCgkVVcY2FwJWy04LwO 7Sb4XqfNzW6gEur4LYUdLQQ7B5atdi+qgpeCfg3vCoJT5h429k41UOG74V+5 UoJnVtgml3XUQLCEd39VIcE81dwsefPboLDlQxojk+C0uP+gn2EtcC5Kr8qJ IsjMDi0ztK8DSZbt5M/hBNdu8dTgDNVBFyR1jgcTVLn+wK2MXw/c9xrnjXgE LbMnDo2W3gESw/UZ+p1g88WtytvtGmB+fYnl2cME42TNnKVmGyDBfpuE0IWg 4V0j/3DXRnAZDX4e4kDQeJN3iVi5CbTDmxq17AnyDebPU31NUFe++xTPgmDA Bp5oqzHCyErP6eU0wcxx/sBH2WYoL7oquMUiuF6TzyqMbYZg07c3nTcSzN8T UEQptoC8X5DfVTWCyqEmJkn6rfCMedfGVomgRENgMa+zFQqyJXSn5Qm6LUiv pnhtwOmM/9ucSTAwZw1jpqsdJA/3trz+TKGTkXj8XPx96PpHtSBxnsJqB7tL ik4P4FKye4TBNIV/zH6ITNvcAVy9Qg/xJIVHjh9wNlF4CKR5zDRqjMKEUw9O 2395CPOu9Dq9lxTGtnsWWDMeQUJsfd/JZxQWbLglnuB0g+n3L/1DhBTmDPn6 qx56DG9aV64I7aZw7sdRk012PZDJNSw83UHhitdmVkGzPWDN8DQNb6XQxqi9 YaRMAHO5sU/PAIVSzEGd5fxeKDap5kXeoTB0cd748S4hOPaLZaJuU7gzo3gk QP8JME9K50ffolC2wvZmJv0UqpT1d5y7QWGK/hA30EoEnlWuwphiChUsTZvE wX2wam+UX2w+hS+WJdWGdz2DpskyqbgcCvtuHKndsHsA/owTXY7PoDBRKOp+ NzUIGroMTmLy1z/jigcWhX/Bw3ZdwYUECpW1Bvkjc88hxMvhaNJ5Cg2CIu+J DYeBJRnGTImiMNDZVru5aAREV4pzUsMp/MjjX6MdXsFZsx6D9BAK91cMfppx HIXtgwvdGSco3Ls54w6zbQyOF9RcWwygcP2WYINvXN/Af5kknM0= "]], LineBox[CompressedData[" 1:eJwVjns4lPkfhoeyQqUNW5ZWprzvzPsOaVHTou+maBwqpUI5ZNFhV1qLNpRI pchSSNqwzoesjENGDt/POGsY50ZCk3KslpJDOv36/fFczx/Pdd33o/3LqX2e sgwGI+Zr/t+RO08HxGtzIHltJlNTOona7KoWirQ4YDRHzuXo/YeC34zElnzP gUyfTtM95ROIE71C974aBxKjX8h3vh9FTzg/NZSt4MCLvOIFi6phFPHQ3bVc iQOnHY++0Rl6jrjHo+YffMMBGSJX3XfvEBqVK7teKcMBh1OJ0SMLUnQzXUpV f6Sh/fD5f60ynyLzbYp1eI6GbS9cuvkpA+jdoIGz8C0N8/fpQzGSJyjtrPNs zWsaAtz4W86Z9aG934dH143R0LC/6guvtxcxBIWshuc0nIUZh5M3JKjgQJ+w cZCGZeZP/bN+e4Scpxcdbn5MwyrW3aYc1x609Lruu4fdNBj17Dgy8Ws3qtCz j2ppo0Hb+8p3gRFd6NeWEEL8kIYNlubZ0opO1Cjf7dABNLiPW3fp2nSg05mf 3nRW0NCp3Wktym5H67eTkd33aUBJNdGxy9tRl9R2/SM+DRwi2kv0WYwuBAdW SfJpOCXdNH7tbSvaqJlx8HE2Df5Jea4lsy1IWt462ZdGw/0wSytQaEGmM2uZ g7e++kNUfZztH6J1jUpt87E0WB+T/BQe24wUEmeDVKJpMNC3zxU8bkI9Ji09 vEs03Dr249/M0EZUsbzsgnsIDYFmj3IXPWtAqdLUDcFBNEi9NtRzeQ3o5MU/ rxb70CDUPxtxk6pHdgd/2ST2okHyck6/N6MObWHtej52jIZNvz7mJa2vQ3It TNMfXGhoehUWb2VQi5JUxFNXrGgYH018PXxRiMKGBUnp5jRYqEviBEwhOlGW blX9Mw3EjeI7Q7WAjA4HZExvokGkq5wUqgyoNW29g8s6GtyKDOUX/qpCxX7K cgE/0LA8yb5cZq4SJVos8GPVaThUOtbu6l6JPCfalJqVaVCJz2Ra8irQp41B 2OAjBdG9bZIs03L0fNFRr91zFKAp2nxNrQA199iqn3hLwX+hU15XrQUoPoDw TR6jYGOnOAF7lCFdYQeh0EPBJ/nF2V6lpUgltrJrXTsFfiPxYL2nFL33yA7Z KqIgn9oTtP1lCapfcq7PV0jB6lV5d0h2CXK2Zf01+C8Fu01XWWY9KELbmSrG 73O++rP+7tdxL0Lsd59GVTIoULjCkOEsK0IzCV3bLG9T4PPu9YobnnwU9TR4 pvgyBU2G3nb7iEJU5d3jdNWVgkGGz8CZirsopMO4bcshChKWNvm4EXfRDsO0 bRP7KYh90q7Hi81DovfehLUVBcYjub21f+SixxeXTC01oiB4/HLAJYtsNHPb OCxGkYKO1TYnSgzSkW5jam5CKRuaD62DtpQENMVeoskrZIPwcH2NCr6JSq55 /zWfxwaXtF1zB57GI+N9xr6O/7AhILL7bCIzDlkOdJtoRLJBdsfAi4iiGOQ5 Ld+efIQNDFn17Sd6w1CSlvdsphIbzB0XK9yI8sI7rgjW8b9hg14/Q1h+2ge/ mpLdWynDhow/wrn1OX7YpCbhbuccC2wdTCraVIJwn4fwyJfnLKi/HW6gJXcR r8pTFTlUskDQ9domITsGV690nXcvY0Gg6NNamdDr+GhQrs6pIhYsFnMY6Ydv 4Ps2W0Mu5bBgbvkySqgah/dPHjMqimNB5HozYXdCAr5uWJGidJIFWkhNs+R1 MuYmybV+d5wF/ulaHarPUrBUznZB250FCvou/ja//YP1JS/2cx1ZILrlz2d7 pGJxwHJFT3MWqGl/2GnnkY6VsJtf9RoWDPDuDd/LzsZFZH5q82oWaPpyC202 5+BDMbPibhUWNGmc+1DQlIPz3CLZLxVY8KmE3/Z5KhfzFpcOrpoloVlhWfhF x3x8yXKJpY+YBLZtaD2jtRArbhcbr2wmofDg6cYcPT6OMYnTK64l4aB5EFPl Bh/f3rBWdUZAwrhfhLafSxEuUOM+PZNOwpeON+NByiXYQPlzh3oyCUs/+oRb hJZgwZK6uge3SIi6xpzznynBNR/25H2MIsGmun/fieFSLHl2zD/kDAkKBXub K0bKsNMT3ePaviTIKfm9r/YW4KHu6UM1J0nQGtT4UWNBgF81nv95sTsJ58ub rM5qPMCMggSlK7tIGBVkVFdEVeJL2c6fWbyvvL7Z9P1GVVgxdd2bZjMSzow4 jTU9q8KqcfceKXFJyIo8q2JuhTE7sDE1mkmC05qZJ2J9IS7wjYrTX0PCNJ/T K3dHiA1P2oV3rCIBPENlpxRr8NYjT71UlpGQWu8wid/V4FrHTNcSeRLCuH9+ z/y9FvPsftt3QJaECrGh0capWrzPYm5zwhwB9wb4k5Ff6rAEVVHctwR8qzzs ERZdj522hK15/IqAFNaWDyE6DfgoR3mRxtDX3c0r0cyzEb/U6Zmp6Ccg+Z+g ZwvKTfh3rb/HnCQETPr1uWXUNOGglaQ4uYWA8OFvCXOzh5ix9DWgRgL2l0sK 0leI8GW54mKpkIB+l3uJDeMiHDO/NZFZRkCZ6IHdamjFam8XX6vlE+B8KX/h JBbj2y8fBnvkE+Bk8ubcYGsbzhg86JGVSsA02/kPhnIHZvdq2u+8Q8CmQL/5 eH4HLugYshy7ScDvw0ZrjF07sYEox+TqdQIareQS1qt3YUGd9wbqGgFCnZ/u lkq7sGm1IVN0mYC1WSm7rpZ145qyBVWvUAJ2B10MOpfSg1vzLi/8e5oAJZ7r 5OhdCY7oXSZz3IeAgQCl5j3tvdjim3h5phcB9rYZYRtX9GFZQ83l/UcJmF9h Fn7v1BNc7ZauetONgNsXDMSi6X4cGE1p2DoRkO9Zzc1KG8Sbq/jaivYEuLpO BI5tk+J3E1xW3d6vf04sOP5i+wwXrga9YBsCcitrsfDCEPay2GnE3UmAzvgd KUifY7af2PjtNgLc1WKyz/kN45HUA2b5JgQoCiPeB1iP4rS2ft7RzQSYWTyK ZZ0Zxz/uNB1NMSLgh41njNQcJ/D/AMKnnJE= "]], LineBox[CompressedData[" 1:eJwVkXc8lX8fxnWyEg1KkXHf59y3UUbJqX6Kb6kes7T0EElWkpU0NMwoKUSI PKKSsuscJev7sUtWZMZBJXUQWYXi1/PH9br+vF7v603aeRxwZAgICET+zf+7 y4ouflxPQxKRypTrHUGWdq5vv9fRQPX+YYxajCDpyPF3T17TsN5/eiRYdwg1 FV9styun4axMg+CpZ99Q+OCCHrkSGvzd+vR+Rw4gY5nQ/tZ8GqwyA6r8yvuR sMGyoUgODZOky9TOzZ9RuXfcmHE2DfN1eTyjno/I/4HCtOBTGnLk80bqn/Wh bY2p8yUPaaB/RusfSetFv/6oCfsk0bBfRGte27sH5a3jim+Mp8E960fkcE03 8rLcKjUcTcM78QFugEkX0rhWJpMWTsOWF8+KZkY6EZ9rRBwPpWH4p2HBOU4H evyxUWnNVRqmrS0Chm63I0W9no0RPjRc6mZJdUS1oq5TTjpG3jRcPaD3Wzq3 Bd2NH96+0IMG57IM4ezu9+hQtbdB8UkaLGpXmPFk3qNlk7N7zjvQIFi9O5q2 b0a1zKBDG47R8KDKaEw7vwmF7hOzGrSkQdxqX9rXVU2Ikbna+ZgZDYkhZzxs xhtRScd9dxljGiKSbXk+bo3okojy2eZdNGhMdRGvuxvQhB070ECHBsULMx43 xOpRbmTR9QVsGoRMHsU6a9Uh15KdEYWaNHD85CKLHGpRv8yBRE2ahoywB52c /hoUsqf46C6Chm/5b2awXg1SClBRtFxDw4/iueKIpDfI6etcSuDyvz5eqcZW eb5GwnIu9nHiNOTeG5Vw+ViN0sxaqEyRvzyWSMXQshp9fZGR1vKHApuiBcmX zavQdb70Sf4vCnK+897v7qxEqgqBa+fHKVihJrVbw74SuQRbZKnwKdirc2Xq vH8FGjooxLnUSoH2QTGLgE9l6OY1T+/IdxTc8cqYyQsqQ+qFH9iptRTUNxqP xiuVIXfm8/z6MgoKc49TQ2dK0eioTQmZQ4HHKmZKmCqgSKrGb1M6BRO84Npf LzHaYMHeYZJKgYmPNzuEwMgLL67wvkfBJmJwM+N3MZq4lf+m+hoFCV8W2Vxt L0R3SllhXYEU2BerReQfLkTsyXDTH1coQJXDeSFtBeictWODrDcFCu17hK/1 vkK/1kq2uNlSELwnrPa8RD76XX2qV+ofCs5rlJZ7lXJR4mxrioo2BTcilLir j3GRrqa+va4mBeZaRCc1x0G+sau/ONEUcEbt3bdt5yABx8rBV8spOJ3icEGu +RkSZCj+PMZngYDlyRBN82wUWCXkK9bPgrktNkJOqVlIIGxIMK+HBVdmB9w9 f2ai31IFkmItLPDLf8J5mZyBJmhzDS5mQaLBq3JN4afos1GYo2gMC/ZXl/52 WvoIVdz+2ZyLWBBWISzvExKD9A/zjljpsOC/M/s8bRzvIJCt7BNis8C0Yuv+ xl3RqOhh1MiRtSwQjnx0QUroNuLmqS8WWsmCNEm1mJOSoehRh72+JZ8JiklB VpdDXVEQ2Zi7IIYJe72GB4uf3MJfBhPGhCOZsOy6RHJVbwQ2fOGoLR7GhEpx H+UaidtY3GT2pXQAE9jPtmvMmUbjO95KeJ0bE5zYtXmVvDj8qPpynfluJqyz XnnTNycZC0cZLLXazoRxR6+0CNMU7Gwtud92KxPi20uy+vgpWO1H2nuXDUyA 2h0eZ9Y9xHmyzR/85JnAHV+SFVqciqvcVPlPJ0nwvdZNn1yfgVW2TKzLGSWB MWUYs3EgA99gYDfuIAlmduc5y5Iz8d64Qz9K+kjAlstF/7M6G7eB36/mOhK2 zdeMGEblYp0wY52O1yQErC6492MqFyear7zMKyfBNLjI8bv1M2zLT5//+oqE cXYOa5n6c/xVqlV4LpUE2brYBXo9HGzMSzZcmEKCoi3+Vm/GxZlPTt0QTSRB 2mqEL13GxZ66C5ZIRZEgrvBhi0hmHp52Ulup4ktCxl3jWJW4l1isIJB14DAJ pwPc8ls6C/Gj/CU+nvtJsG3tSDd0LcK6LxPqw01JUHefVE0QKMae3Oc+b/VJ OGA0O2KgVYJbsj827NIkgWRubI62Aeye5U7bryVBYGCxuCcXsGjmzMUAmoQ0 qxMX9cRLsc5TSaWSNSTMr+QkCZaV4uSH+pc3i5LQ1qRzv8CwHP/zoP6d+UIS tO/GZD7OLcdNyUeUvecIKMtXuWOypgILJXk15U4QkPyYKt8+XYGTEueUG0YI uLvkwqlW10q85d6NK8N8AmqkSYHcT5XY5e4DlbV9BMydOy/f/KEKC8Zp+Bp2 EXA8btr/7NFq/L+YgmanNgKmBBfPSnyqxo1RTb4P6whwPejUMTnzGrNvMVrk CgiY7/QYN3N4i+vDwtduzSMgS3BqSFe8FjvfkPW3zCVA+ctVM72CWpxwTWtd 7GMCBORkZUdV67F2SIk/N4WALp9g3umhelx31bi1KZGABPufzk9eNGCBQLuA pdEE1DV0Ryg8b8Tx/t9b1cMJUNpx/L4N9Q5r+V1UMw0lgJHOO5p47x12vBzV dt2PAGFG1ERgQhOeu6ignnaRALcXhdmzzGZ81yc9sPIsAbVauuornjfjmnNl 6gzXv/uNfwZ3fnmPHc7uDSJOEHBy0Yxq5M0W/OdMZ7ueHQHLhj2s+VtbcayX k8bRowSkG2y2lZtsxetPjwVdsiAgJ1idLfqqDb/x8O2IP0iACSP8Rcb1dmzn LqaZv5eA+EUii2jHDhxzitk5sYuAHf0Ri94bfcAaLtmaUtsJ0Nyt2Spn3oVf O+sEb9j699+p9javM934+ImqTrNNBAyuP2Ew/5iHZxwPrHffQADbvt5cf6wH 33HgBd9U++u3yPqSZGYvVrd3+ZCuTEDQwQuJIu59uOr41Po3TALWaK8yZez4 iG1tA0MG5AnYJNQp76D8CbeNhKbcW02AUPw0maLzGe/1u11kJkXAij8S8n6u /bhySXzbwiUE+O8I1fUp+4K3JSWPvRQlgFTLe+O+8yvmqD+RcF1IQFuPVfGa X9/wLTmZAQcGAQobLrBXWvLxv921jvg= "]], LineBox[CompressedData[" 1:eJwVjHk81PkfxymFHIn5zmBmvqiE3WwqSpGPEjqoKDkiR7Vqk2MdSUS2Y1bZ ct/kiElFcjbo884Z5RpX7mMkjaQf5bat3x+vx/OP1+P5VHJyM7+wSkBAIHhl /6eE1Lm+hY8kJCs+3sgYnETny2eF9PpJSDxey52kfkXmvWt1MltJKPBPNb26 NI70FwkPyToSnpQm0TRU+UhdXjnL5zUJirujW5VCx5D8Hs2+/nwSzmpFRJ5W +oRErAxkjJ+QcGcmMUu47yOa8TE/nJu80p9+pCvOGUEjUY6BtEgSnnV/UvbM 5yFugXth4N8kpP4d6renehhBa+D4pxskUE8bCBFfhlDO1D9KJ7xIuG8/f9NE eQglbEi2LLlEgs3ddohzHUQsjeehivYkkC5Cacr3B5DP8bJK1ikSxlXZQxqn +pF5aPc2a0RCltyZlpHNvUj/2ecLbzRJ2Kt77oCiWg/67d1cgtovJBwJG790 fV83EhWliSxQSHCRKhMLffgBzahs0XNaR0J7x67zhe870YiRllf9TyZc6hpm t8p0Irh1cjCez4TR34+Gm+J2lJPuRF09uPJbciKIje0oocLD5HI7EwRD7HMf 329DPgIPS3SACQlU5/m3Pq3ovELK1/RCJnSSzoUWP7jIXC9ns/hTJmR79eyJ v8ZF6v7vH/ZGMUHTRMSXE9aChjPTdRfuMYGvm2UgurUFxbb4jdGCmVD8w+xX hfpmJKSipn/SlQlucqGyZVLNiGMm8MX9/EpvYvfrYo8m5O7fGfOPDRNo/7aP jtY2ot6W25N1Rkwwm9wlWnOrAYUv2SZ80mWCjVRKRR//PTqkomm8ZicTBvxC H+RbvEcF/sPJ+gpM+Dj84mCK9jt0XwUdK55lAG9iRtxfvQ4dMKcutE0wwNLb /E/n/Ldozn/i8RSPAYL8uLFrum/ReW7CsnozA3yEFV0DLWuRTsDcsww2A8q9 txLuz6vRt6wmq4pkBqiwgxo+HqpGmdxMocFIBkTwbTtCRquQtKqFLf0mA/gN xk1CqlWIz80TC7dmgOMD4/3ObyrQo2VWce5xBtxXzytYulyBTqs6nGswZAB7 mXdXSbYCVQRIlorsYAB3US292+sNile9/EfgOga0NR7+4acH6PCNzXUupXSg kM/ai9aXoX/Zi14heXTIxF+H0kJKUUErV5GdRYcF+9I7OsKlSFHtpi8vgg53 TKNtdq7hoLnWPhUbFzpYf5f4mCpdgthqMXeMmXQoYv+bt/1iAZLzuVD+UJoO 1xfXXqV/zUchFTu/dwnT4ZVbnou0dz5yOdPs6DIlD9/2VzXN3X6JNEJF94XV yoNgxudW95cvUPG369PdHvKwSbByLMomG9UUOzi41sjBWlfaJtHXcWi30LaY 4lI50EqQl5mWiUXsE8sNAnly4CmjmdpzKRqFfI7TiUiQAwNou65PRKBj9FZq ibsc7DRqsxNvYqH2G4YNgnQ5GK/UFGuuNcMjhr/sjXKTBVcjQs4vKAlXLfjF Sl2QBa/QyK17LFJweu67mXs2spCoy1bNin6EneSu5AcbysI9u/bAZc80PPgl d6s7fcX3uBUfbJiJeyK0FI7W0kBg2TC/62QO5hy6E1BTRgOFkWl/bcdcHL/c 0bP/JQ3YXpPmr7RfYCtn31jtJBqESaWNXzbNwx17Szds8aRBSx2JpUPyMXdI X0hQgQZQkav11rYEv4wOc/Kn0ODGpiHvEoFXOOzoMMyK0iC9Ooi7NusVPlH4 V8DX71ToiJodkFjk4EZWzUxPPRWKTlrSlCrLcc4+moUlUGHq8JSrtf9rHDrl nM8tpMLD7A+3H2tjbGIr6l73iApbHKKW/7QDXLfN5HORDxUOZgsIpn9/g9kj icY7XKjwwr6sWM2+ArPiJh4/d6TCMmd5tPhdBTZa/cApw4QK/1PUidz9tBJX dbT0hG2kQvDP2EXpO9U4497GvRKyVOgyk5wjV9fgv/Q9Y1kSVIjpGPYZDa7B B7IpFoFzBFzb9zpb9l4thgDLRpdGApzLs+W939Thi3ruaUlVBFhSzgreNK3H 63+yfBo5BEQHyxS39dbjs0EcUiOLAPV7nU/717zHy8FMt+lAAgYumW/m3G7E GQa7DDb7EBAapyu2W6MJmwgdp1m4ECDspHXmyEATTrwdhIusCPh9S3vR2sxm vJfFW++3nYCYNcpddju5ePjQEi9bhYC+lvlW42QuDhElSnqYBHD4nmUs8Vbc FWLksG8dAX8MmQpXTrfioKP2mq4CBNib++qQV9qwqrivSMoMBcim0chIfhv2 DX3yQoBHAQfjgxIw1Y4Vj1Xc2t5FgYsbdmnMBnTgWskeK6cmCmQmRp47JtmJ qQ/FBatKKfDcMXFjEvqAC8PdzO5GUsCrON9OdLIb255kKZeEUGCgO/vJlec9 WIiSOj8WRIGfMWZ5Bl69+FQUN/XIFQpISk/GcJj9eMli3Pv6OQrsCrLxKBcc wOlUoSPPrCkQZaG6OP9tAE/FaE1JGFGgMVMtxn5hEMdbHavR06UA1ZZV+PT2 ED4g5xzvtoMCuv3zvCzZYczvCnR9pEqBVzldjQIFwzgsPvZAC0mB8KWG6atW PKx9Jo+6iljxRTX6R9eO4EF6PX+HGAWUXb+tMoARrJG0GB45KwO8E9rEfqtR /MGO4lw9IQOJ7j0ka88nHEiq68zwZGC4VDWN+HUMbxkwXK/SLQPdGUZStb99 xo0pZ3mWzTJgIN7LqTbi42gRczFokgFyu68WYc3H/wHRDR+v "]], LineBox[CompressedData[" 1:eJwVxX880/kfAPBttrUd2z4fMZGThnS04q775qTe6HFOpXv40Y+J8iM/itN9 v+W60yVyTjVnin5wLiMnpWmXCC29X46NTn0RGwrNz/nVWaTyyI/v9/54Pp6r w7/1j6RRKJSw//vnI9NLLR7vSci3LhZYaqeQsroofkRPwkxilNfhvr/R2rx7 7Z4jJIRIE1v+Ov8KiRPrP5W+IEG5rn33Rr9J9Cqk/eKHVhLojmd6PZwnkK/n oH6fioRN/lE/8e3HkekyAzlxl4Qgi/US+Y5R9MOYMTfuBgkBzpKEi/E69LxZ EPc4j4RTNfYlgbIRVHDB0zEljYQ45c/Jwe7DiHbcX9z3Iwlr69LcD/w6hCL3 hI+5/oeE05yWfQ0Lg8jBIqVkJoiEjnRhyG+9Ayhj/iLT148EvjlPIhcNIH1f YaTMi4TlSVJV9PN+VFlUZxPpTELmbGBU/ZQWrUhrS6lbQ0LWV3eCUlO06OTh /v6PLUlIHXp6XGChRe5CaoGGSUIV4yDaXNaHrvPIpU/nCejc3e9VP9uLGNPW BzNfE5DgkDR/7cte9Nd9d0vvHgJ+kbm8j5t7gfa4J+fU3CXg0bnhK7E3ulHy elFccwkBTtPvFs3tu1GppZNn7zUCDrp6XSq53YUocy8nKGICVusF4izciWR3 EfIOJ+Dxr1t9FRwN6pSamewXEWBndc486KYa0SRTo7FfE9D/srZf/KUaiWKk WZmuBDz5Lq5p1dkORLdZGtYYE+D5ifegwLYdbSA7H4yyCGBnbNvt0voMVSwe WDW7wIPrsr1viNPPUEhV7TE3DQ9KaR6NtX1t6P7aRPPmNB6A5sPn5uWtKMJw PmpUxwXhcnrAkv1T9EB3mzDq4EIrX72z/NYTRDQEPdgAXFDgsLXrhE+Q4pSC 830OF7S/G711+KIZGf99soKxnQvxFmX+CYceI2ido9qUciBd+a/LR98o0cdX 3v124BsjyMm1EHKOYjRaeTm4a68RDKXGVGVJH6EK9WeWAR5GcKja03q8rRb5 mP47z5tvBIm7Lvs0ujxEpy6N5n4GhiC6w0jfz6lBz7O6r7BNDMFKYh+jqC9H OZmKC5UKNhAuZ2+p9FdRhDzQ1+kGG6yi017/WHwJObW8492+wAa+fFD8bM9F 1MjdmFkQyQZby11TWt+f0dsMWUY6jw1nzJhhGnE03vPLNXHYIRaskRJU9n4p tpZt3tGziwWFlv62stRCPNnczd7nwoITYRE2eaFFONWQf96Hw4JhJ1PKuF0J rhBLzm6qWgZbGLi4cvwONj6flMoxXAasQ52JqroqrEgQZE/OMuFgrqExdFTj iBhlYbOWCS05NcJ1EzW4cqchPn+fCQnflqY2CR5iEffqHCOcCY4ryK9WhgKm Ln3BGvZhgknswIbp94BLp3r4DZuYQHH4Wj+XXYfnWwUbUzhMWNm7tUfb+ieW Zt85uljNgOFHA13cw0rsneqX2FvEgEW3T36KNVFhffyb9IcSBshffZeXVa/C nntdb52MYIDOCL/LdWjCIytUg295DJDoWe7OVs14XX6vaCqKDvtDTn8z0d2K 1ZLk6P/60eHD65Z4mU8bPp1kc6LMjQ67yLHyuro23BJ6JDvWmA7a8RCG271n +JjN7FNdrQHoBFvdJio78EqTnB7VTQMw6xxQ1G9R4wb65onibANoWGNB3G1S Y/5IMiviiAHU/jH0wn1Ug2tuGm3TmhjA8etd8yq/bhyeK/fDSzTYl/F9ects N/5I7B+aP04DO9/tiJ7/HAfH5iQGAw3yznWcKPjwAlPW21Z3xdJga+CbtHl9 H75l1aiq2kuDc7jsUpniJfbnxaiveNCgaCwtz8xLi4v08undZjRYeih/3b2q H3vd2yxs+5MKWqtx9YX5AZykOGq/Uk4Fj2KRdXr8IK6uL1wdmUeFgHLRjKN+ EDt2LOPPHafCltodC8tnhnBEjyuxLZQK5mU+WHFyGOcPxX2U4UOFpjN2V5uZ I5iYbV+0tqPCMWVAMFuow9sXmHMxJBWGdzYxKhp1OIXhOlOxQAHLsLBJiB7F s6YFOm8NBWzu200Ka8awxjYrRKKkgJXzD5+bBo7j/wEBWhJh "]], LineBox[CompressedData[" 1:eJwVx3s41PkewPG5YMww/H5a0SYrslRWI3G22L4fMzYbuaRI2tFDplq6iLMn DilksnU2m80QUUnFMo9L7aYJ3y5GKJdxGWqsGWFCbjUSi+yeP97P63mvDjvu L6BRKJTwf/q/E5xTvlfrKGDuEOtkvHcU65ZKuJ/LKdAVUV/4XDKC5To/JjKo VKh6qj0XtmMYf7PJ3yxxORV6LRPWh157gwtDN0im11OhMSKNLJ1V4xPVIx/6 A6lgUbI9WFY9hHtG6n8NOkIF61rCydBmCG81KXRoTaKCuV5l5X7RINaPDjla XUoFZWsDzzllAN+x6RgU0WjgL+MZpaX3Y87ZEsdiExr8kJBFX2nejyWqlOSH djSQ+T9Lny9T4ZYrmyxUgTTojg8xspYo8YyeaN/aEhpoaXoitCp78ZnDx35z eUSDkvPZdvcXFJgl3Tbn3UWDVUVZItMdCrwq8aMoeokGzF7K3LrZl9h9Kqj9 4S46HHTsmVWf6cYtOxxWtxymQw06YxYwJsdBxcwo1Sk62Oyvi+Hsk+PIMAlb u4gOXH6ZRzm3C2d0rtzus0AHS020q9ipA6uq+rCqUAs0+1sMD9m14gjj+waa B1rA3G3C3RPUgqdPpPO1W7WA3Ngick5rxoz1ML92TgtiPDwzeJrn2D7vhnOM tzZMbA2+FKJpwAlJ4WLtGW3YkRejMU99inX6XBdM9HTgwVCo4tuBJ/iXLcZe 6yx0oPNN/C4Z7wm+qZEO+3jqwJv2UGqL3mPcJLBZk52vA6PfZ9xiRdZgU8/R nHUeDIh6YP3ZIek9TKZv/CQLZkBV7r+8FtvuYlbnf0PjjjFAfuqMla2yEi/y 9WwbMhngln/tj3e0Cvz6hN3vgkEGDPI1A00vfsPiK8daryfpAovndNdsSw7m jrynm1QzwSpznejOUhZysXc5VNvKhOPZftrmn3LQppiUJsEAE8KCN475zuUh m8Vll+6xWLD2oq2bt+YG0iedzP33smAi2jtA3nYHdX998uufZ1jgam1JX1le gY6kzR+hO+gD2p4Ue965Bk3+FCDZtU0fvrzTG3WbWouiL5QxCvfpw25K0+Pk 5loUd/FAgbtQH6S3EwL6HR8h4eXn3amKf95mJIHT+Rhdv57L1RWyocNij0uP kxRZFXxID8plw4sLfpZLt6To9k3fP4vK2SD43FG0waQeiW/TY7cr2PCOfeD4 wEI9kpRGis9zDGDncodr9t0NqKvKxZStMADQuqBiyF+gIEmmgD9lAES4dFlg SDPqfThZKdY2hMw8K4+24Wb0uvamtw/HEIQ/68vLtFrRVJ1eSnqqIWTtN3fN FbehmHpBmzLHEHrTAjcszLehmWd4FafcEOICiCtjXjK02BRT1fbKELiNptkN UzKUOjw+o2tKQKTbYT+pXwfaNpKzqsKSAKamgjYt7kC6ox7ue78iIL+FjI9k d6L/vb1xqZhLQGFVQqO4oxP5jPlU7fQmYIn1YfHBli5kOD7fN7eHgLa6zboZ hV0oYyLAzvMoAV5vu753S5Kj3ZO0Xe9PEnB5W5jr0Wk5Mp4qi8tJJuBclkxk ENmNst8xn41mEcC4y1WfOtCDrk3XhF54QkA1N1qUeu4Vyh4pMEp8QUBA/ZPk IiMFyug79zRKToCJ+t8bLhco0NmGndaBowTEyu5XaGS9KLHGWf7dNAHaBcp+ dvSf6GTlynMunwj4T9msbKtpH4q4OjRsYURCYlOd99lYJQq/1HRlmRkJ62sr 2/EKFeILyzx1viRBcGSyihOvQn5RcaVvN5NQrRZ+YeTVjzwFIfw+HgmEydgv NpJ+xAvmGci8SXD+YnI83v41cnZnR/0RSkK4W2BGuu0A4mx+b1EcSYL575dX 88oG0Fr7blnujyRwF52iVn8ziCytqpMvnibhK2GuuLF9EJmZ3nBM+okE5aNg 5XjUEDJmCwdjfiXhYO7CowBTNTKgRWYezCOh5l2J/etGNaKObfroVUHCiq6P y1J8h9FfqhVFWx+S8JFybGbJegRNd30KcpCS4OXygX9abxSNNw0w17SS4HtV /aqc+hapcYNk+UsSAnPH3gtZY0h1TxzJHCBBfauo0N12HL0szjBbGCNhrzJh 90X+BGrPP9k8MUPCTorC/rR4Eq2ZyrzvM0tCvsUtSzPVJPobobT1Zw== "]], LineBox[CompressedData[" 1:eJwVj3k01e0exVFoksoZOef3eimRQtEyvdfzpYTKGI4x5CUUkYRCiUKhSHVR 5IjI7KUcyWM4EjKEOKZMoSORUFfpuu4fe+211/rsvdb+89Q5CzchAQGBq2v6 vz8syfSjdUgAsT/oINl2Guf+kt0PAxKg0skZqtrGx2rRNyoFJiTgp5VOW/q2 T7iaxD9UOysBeY7umtoyU9go41hr+H8kIM5df77m0CTu3ldorSdEAgsu+3q6 /wR2qtw2IrSFBI9SPFOCij/i6SP+nvVkEmgbvhClL49jAWeNkMMKJLg7V5V/ L3cM35pJERZWJUGIR0F/ofgYpgT/jm/4iwSFHFAUDBvFexPrMo6YkWC9K9ux xncEvyB2KYrakUBhSxyf8WkY6+VFlTW6koDuO7L09OcHbMM93mgYSILS2CEX RRjC42ZFZhvD1/bfJDZm+Q1in6Ht/U031/rckbSt+QM48nvPzNE0EvRWvNrp qNmPxSM0L27OIcHGaWqB1q0+nCL+cLWlhARfvOSbFsZ5uEjeZYdxAwlORnZo s3J6sVZ5fapY+9re31MUfYlezNWV29XGI8EtzR6hpIge3G/3Wd10hgSCX1eu 7/J/j0XiAhzNJcgwtFX588yNLpxA501uZ5LBJKs4+ha5CzOytXw75chg3Ejy yn7aiQ/g1WsntMhw97wzynr/Dp+cj8mxciGDRr61b5ZlB+aHzuynnCHDepRQ MbjUji9sMn3Zc4EM33K7pFUN2vFNWVIbK5oM0vM73zj8aMXlVmkLtkVkUCk2 qI6JbsGRNRu/zXLIUD3SfLGG34wtFQO+RnDJQCuJlV00acaLAse/FPSRwT1o fu7pziaslr88KbieAkovRT5ILL/G66luE/e3UuDsbBLrW8Br3B3eMa5Ip8C7 XxrMwqUGfIH1dMRKiQLU2E3aJr+5uEzIqj/XhgLSnoZbfPbU40jvGp6OKwW0 DlZGe76sw5Y8xd4ubwrM+R+WjTCpw4sFQt2/r1Egut3+GfdSLVa1LW41L6DA 2LPnf6h2YVxatLl2WZAKiudDvER2V+JrkoE4fgsVlm6vpvWHcrDF9bFXslQq +J3c4CzbW4G/2XEqjfeu8WW9h+vvvMD7RU6XZVhToVm0elKdKMfFDnVPjfKo EBTnXsq5W4yvNu7L/lBOhV2xQbh9YzE2O5D8xL+GCtLJIr5YqAh/FfXNePSe CsDryw7h52OVf5ip86trmRUZH9KTg4s2BscnW9LAbl3sgWFGBn7uwaAGn6RB l+7BcpbOY1zdiNNtPGjAPz0bya5Lw23XRUqoITQQNWnLlmOl4hnBpK57mTSY 4DjoTaQn4T0/C2mJ32igJVbVVukdhrOmP7Jv3qGDzaEulVbHBJRvFK3olUKH 76dlnMWmElFZjmKZ0RM6lDQNfBH1TUJc9/MNGyroMFPQKhwa/gCNja1O3Rim w8qGiL3sJ4+Q9IDkvgglSbBJsz27Y/UJSm0xe3H5rSRQY3jfPaaK0acNv8uU eyVBhpfENrYvQWpHckvHRyXBdkL5jmBHCWqrESw89kMSZhrahgWqSpHA89In UjJS0FBn/iAxvQy5PyYlvgyUAiuzlS8T6RWodKjm9rlrUpDONvnhJMdBq5Le cbJxUqBuV2ERWshB/77XEH2LLQVLlbosfn0larl58Yp9qxTEJx//lCn8CqkE 8M7+kmFAwGIA79BKDQotjfQq2seASUevXSXmtah5TsXDVYMBkTl7bJ/n1CJX rxjXFmMGeFskG76zr0P3nbTsUoMYwBVlU6/w6tHYw0mWaQQDwqxPzQ/8xUXK /YlW6+IZcNIwKS0sk4veWH42O5PJgAULc1fhoAb0y+ihgXYbA2br3fFN3UZk GGWoP8djwA57n21XXjaiJO6iXuY4A45bSdi2aLxBSshYZ/MyA47EZFnK6DSh SyHL2ngdE6oqYnffed2EGjlZmv5bmSCjtqOWcaIZOav9V21AlgnEp4Go8OAW VOD37MBtJSbEFtH8ByXeop+F1iqHNJnw6rTBJYd/3qK7CkWKeSZMMHYJXt28 rg29JpxlLgczoaJIWbw8sAMdNTv8LDiCCZNmwlkPejtQe7j8gaA4JiiYXU2Q 1X6HeB+/6gZkrPF/KGiqbO1EDpT3Tf55TBDJbNfUDutEowYc8/PlTLhst91F eKETTT8LdznXxAQpuneg+kwX8hl043t3rf1pmJV38+tGC2JH/c4OMWFTV0Lp 8Eo3WvHdEe45zwQ/uv5hLN+DrrK/b/D4xYRcep6jUXMPWt/df8ddmADzkftO Phd6kZh65mNXOgGkTXHLqRM8lOgRJX9KloAl1sJ2r8I+REk5U+y8jwArH69s t4h+lNJiquGkTgBF9d0H7DaAiN+qNY66BDj96+Jsp/UgYivRDB2OERDA5Gso 2Ayh3c4r7XZWBFTfvSF048wHpFLPHWZ5EiAcV+nt5DGCyhZzTlv7E+Cl72r/ XmIUacrFzVmGruWjyaW+raOomuUXeCKKANqlvs/iD8aQXozVqnkCAW6bohL5 58fR60rNKLNUAuIHcyIyXD+iYzNMcdMsApRP1bL/PjuBOphCD4yLCDDNFTwn ljCJLE0nieMcAsLkKD8te6YQ72pz9tF6AhK+jvuQ9fjIsbRQyaiVAKN6peWs gWk0Np743KCXgLgqQcIhfwa5kwN1jowScG72z4f6NbNIRanv7cIEAWnSWTKM kTn0P963zUs= "]], LineBox[CompressedData[" 1:eJwVkWk4lWsfxXfyolJmIel59n4eFA3GkNx/U0kdGmRKKnVKI5miQpnCaUDq NYQMkUyRrei0b0SGwmZLhmQsKXMyFHm9H9a1Pv2uda21SCeX/X/zMRiMm4v6 v0vYmXkd4yNAQc1bS8ruGxZYJjNiL0CAtIIMMl/4iiOHzRQMVxDgW1InaBQ8 gOWbfCyURAn4waz7nKbxBWcUPfFbKUWAM3Q2IP7PWD2+I/eHLAF9wjWhkhN9 +JW/cFebAgHk5pkFsdlebHZiu0gpi4ClGuK4S6oX88wuoHRlAiykL70sMu3B jhuTXG5uJMDgiXuJcUg3HhTjJrmpExBg+WUfmdWFPaYYXNutBDg27GB9Of4J L7SrMZA+AUe/W9fMaXTicOy0hTYk4PlfmUYTMh/xw9CKiHFzAhIuMhd2yrZj lfM/Sz9YEuCQORWlpdaGi/Ypjr+yIuBX/T41IZtW/E4udF+4IwGc39yMsKoW bLPw4rrrcQKu2Qp10KItuLdvMN/amYCspIuW3k7v8Uz2bnGWGwHip8IO6pHN ODDyqtGySwT4S1tP2tzk4VVeOW6jVwiQOhckH/inCVNIhPcymADRI62j/FON OI8FS1PCCdAycjG6fLkR6wld1Ai9QwAvj1m/lb8R721sumsVS8D1gM0TmxS5 uIO9tEIvkQDX/jNSsVca8Mk4zUkilYDTISLs8YJ6fPX4favhbAI+nlNtWKlT hwXNqoJ4+QTE8n/wmgh6h6NUZwqLiwhYI9khpdX6Fj/+aScVUkrAsZqfGucj arFGe7jpuUoC4FTKXjxZgzmcl577axf30X17RcmxBjffWNui0EzAWe1lQZtQ NWbI9dx/PkCAvPTvPrbGG/zPH7GqhCECzrgmSqqXVGLpPqPpwHECinWMo8VN KrFqdprN3t+L+Qc/rzp+rALbGjjLDK4iwcbeU9+VU477mLFmDRIkZF/aeHSD Qzm+IFjrzZYh4an9ki3Gc2U4iKvSdp1JgsK3yxKbjMtwntNorJw2CRbhb+em mjB2KErjP7uNhJAq9/xCEuPly+1dXgIJnGnFZm8PDj6RX2HisJuEn9datrvQ r7AcI2404SgJswyWCF9+Ca4+YGk/8jcJToF8vIY1Jdgzg7/S4CwJR8zLXoeH FWOuhUtclycJVXENb+zOv8AhCSam5D8kpO9u7Yk/UIQ1x2fzLkaQUOKUkiTE Y+Mekzy58nsk8NIKvVKt2Fh/SHbM6SEJKje2+Uk7FuIJvdG4NDYJ8cc+WPKF FmDH1tgxpW4ShHBBs/LBXCysannI+/Mif4PXfzM8Bxf787+p/kaC0fXpPu/y bCyp5BJ/+uci/2+C3T3dLFzrabIjazkTapNX6HCMHmMtidH4TVpMkMyz56Tk p2BhC5OdWuFMGEs0aBM2iMQt8VLTG+4wwUegXDCcjMBJg1/SiWgm6OpnK/CE b2P14DAB4UQmWLd5nKYfh2Gbf+sre/OZwPH8tKvj1zWcssHOJKKNCRGDmezp qjGDrYIXDL8rs0A4trUh53kEYhxE490bWbBzvVvbqteRqDZFNLlFnQUqgqZC b+qjkIPBM0a5PgvWqf3VcGEgGgV4zuCYvSwY9f/I010Xi971BRjs8GZB95aG xi/tD5FT6X+3JVexgNdqzBb6nYksfIfpJXUssFGSm+5NeYL09IxFjzWx4ECJ S6DZniwkXjjST3SywKR+o+NsajYqyzC9/XCCBRZ9VTYjznko+0S8N2OGBdUl qPOWyFMUQ447HZ1nQYChuUnR2afINf7BVkKIAgmP24qnlfIRcedHd9JaChTF v9pk5RQg4T273i4wKQhO2aGZLP4MzQglsY8oU1Dn5LtfxOcZaggwD1+nQUF+ eINTlHkh8vNK1kgyo6DirpL7Kr4i1HnYMiTRnYK1bp+23msuRtVyj1z/eFNQ /I3olbQvQYUfftk7+lHwzv2eyMXeEnRzX/pmhTAK1GIqJXbMvUT6pvOtCYkU VMp5aYfYcpAy34HX86kUhI0aRfDNcpAkfpxzOJMC4ITYpiZg9F3HKmBtIQVJ bkGDkpdLUZxqlkpCDQWWwk2y10bKUMggQ3q+noK9W4MOJu8vR27p1ozDzRSI jUrN9BSXI3OC7718FwVo2veQT9RrpN1pg6/2U1Cz5Vy9Jn8FYsblZH4cXORt hkvafCrQrISd34NJCla/PZf94WIl6ufmOs/NUmB48rt58WQl4t7iP+CwQIGF 6L4n96++QY8FnyrJL6dBLeuSb9yDKhRd8R/xqyI0HAh9KOmvVY2uXT801yFJ Q/ttucudzdXI9rdAY/w6GvQ5HmrDyrVIOCg+o5eiQX1eQWBPRy0qE97it34D DU2KKHvq3lu0QcFO5bkmDXY9ua5cxTrUlT685I8uDWy/wiO+f+pQ9OaAVhNE AyNNtsqrpx7NQ1Zw0y4a+lNSo9NPclFBDXKQtaRhT9F2tW1DXHRyf7P6USsa BiwvrK7yaURrOpyXZdjRMPPiz00R0SbEPT7fNexIwwVD5srJvCYUNBRZpHmC hp5q/xo3ex7S9VS8deU0DTo3vMlc0WaUEmKpt8yDhrX1dGL5o/fIWqRfdK8P Dcc9v9xvu9GCVsR4D9z3o6FXYz8bXf2ASomVnM5AGlBq5Bnr4FbkkZkcTYXR oCcT5T38qA0pq2ufPXubhqny1NWHe9pRZ0mtYcFdGspc0r5lbPuIooyPyMzG 0DD2ziYxo7gT7Xj3YwQl0pDu7G5ldqwL/bIKrQxJXfyDyvAYetCN8jrlH9Q9 puFw6JK7+uk96MTJfDfJXBpOrUnvsmvqRTKjprsOPaPBp7tsLFu5H9Vdal+X 8oIGZfZ0Zk/BZxTAcJn6+oqGJG0ddovvANIOW1q3+TUN8Y3Lr6yKH0TfxWJS vappmGj5eeI3cwg9jFO9/KpusY/t5CauziiqXc8QS62nIZF4xJTvHkX/A/5F H7s= "]], LineBox[CompressedData[" 1:eJwVkWk81HsfhgdpU0iWDumcxH+Wv5xUssT5fVNjydAhFcKDSoUHSWSto3Js 0RM6liJblgwhZP0ZI8uUnUxCpSIqMoqY4vS8uD/3q/u6X1xbXbysTolSKJS4 n/l///ZwnJKuRcAWzYtacraTuMakxcBIm4BVwyk6qeET2Lv7uOx1fQJiXE6X mxwbx6p2nyd79xHQvSrJmRn6Dj8fvcpRNCZgfxVDW/D+DY51/yXJmUXAnkGN 8OLIUWz4he2ZZ0nA5Lth7sGjr/F8sCFz+igBdsyvvwiNXuFC8QGlPfYE+LEH 28/eH8FOse6CYGcC9GsjhaeFQ1hOgdLGdSXAflNPq5XfC8xLT0hf60FAJiFt LyI/iENpdD/LcwT4VFY/cevnY4v7z/9n4EdAzamGtWbcAfyrRhSbHkTA+Cb3 w0ean+HPD/Ta5C4TIPS5ObFtqB837PrwVuQaATI/ck8UiPbjGxWplKlIAk58 8/2uptOHnXVZmwdjCfhnVafchqBeLIrYh0uTCFhi/9Uhr9qDezgOXml3CGA2 jPasjOjGWQcko6MyCeAJXWTFv3bhAwe9Gl0KCVAMXh2k09GJZdt/HbEoIUC0 oTn3cX8Hfneoa0GvggAr5bybipPtOPyIpubGBgIiUBNFV+spPsp/zVpuIkDV QTPZwu0Jph6/eeZDGwG3353TqM/j4Van2XRuLwE5N3P2y6M2nPQmq6aYT0DL ywrH54mt+Kyr9UDqMAFtjJdn8mZb8FqPcknfcQK64ngTGY3NeHDqFMPpIwEb 90qXLe9sxvfPyRuxZghItR2id+Q9xix//xBVIQHJNWem/LOacGyY7sc+SSqI UMb+cGlvxI7ik6s4G6lQXqUmfsG5Ef8ekbKNvYkK977HO85/4+Cu60K7aypU iDTYlZKkycEyyXVtWnuo4Hcsab9cFMajSp7vtu6lQlqfZmzoq3pclrZFRBKo EHXeAF3ZW4+tsy/pjJlSQeWTp2X0Ui2+Vbwv95YDFeozB0J8yqqx605BY5gL FS4FrjgRSK/G2uWZI56nqVD2rNq8LrMK86vF5I3PUSHo0lieZ9ojrNj8+Or8 VSroWgV/0KqswHeGTF1sCqmwK1Cp7rJNGb7REfqoqIQKrutVB8w+leKwhjJJ 8UoqTP9Sg7ZdLcVnspVrSjhUSAdHm/zKErzbY2ajxAAVKj6GzansfoCfCpMe 14nQYAKRusYfCjD+1K4ku4oGiSYhuy2MC3DpS1Eft3U0kFFkb8/MycdJXI8t Cgo0iGrX8Bo9k4dPRoO/tzoNBNKCiqZV9/B3xfe0bcdocMUdL65JzsDT65Qv BdjToGjW1mF2QwYeXbLs73SmAas9eHxnzF3cOlrzV7AHDYx6dwrWrUnHCQVx g/1/0cC7jj+YtjIVq+tpx0QU0uDwcWmzW87x+Lht+PQnETq8cDo5Uxvhi92Y A1ETK+ngJHbgwFmrc/iiJo14J0GHeMuI6DP6HvjWGp79kBwdqheW/FdPOeKe qvU8Hp0Oi5lvv7YPH0YmionZuZZ0SPDtZlXvCUV7XmTZOmfQoUhQmnXbPAEx W758sb9Hh0NLj7/NKyci6zLmDZv7dLh9a0eF4nQi8okebz5UTofP5YGM8fh/ EHsvufuPtp9808GiH+9TkOrtUkmlGTpQhHrl4WN30a4IsQL5OTo4mNenSNpk IENfa6aMkA4Wl6Wq3XkZyIk1F7RGnAG6caz/tJZkotTvuhPzmxjgGmzFXBeT jWQcONw+YIB+nhunxj8PTcpamlUyGbCv7o5Gzrc8xHn6qif5IAMSIbtANCgf eetTRh2tGWC6dPLZoasFqFMJUSZOM6DkhkNgW0Ehutfb8fcTDwY8PJ/7ZkyH jUKjHaWKzjHAZHWWs6CVjTSEIVvOBzHguxiy3zxdhGIGa/V/xDKAre+lJyh4 gE7eZDW9jGdAX49Q+cniA7T34JBZYxIDyBjsOWVWgiarhHZ/ZzIgEltvMBaU INNkvYANFQzQum831/RnGVpp86hcbZgBNg+4aiEnKtCIlInB6lEGLM8EUE50 VqDyloGmyTEGiN2X4FcaVKKT2vO9xZ8ZQB3JKFJWeYS48nsEuitIsKPkPNy3 vhqldDwO2LyGBFHGS52luGrkE35EZHk9Cc4eRoHa8jVIZc5XukmBhHiFXPfu 7bXocn+ZhgVJQkbIQpdaXD2yub6/YscOEoQiN47v3YXR78xeg41aJGRf6A/5 ewijkYcCFv8PEtK97jh9S29AFR5hfdX7SdC7cveo7Y8GdF1Vxv6OCQmKIVbT iw4cpJ+g6e5iRUK7krs5j96IZFkcwYFjJLCNDl07ndiIPohZBlLtSQhUs9qq Js5FKee9Iz+eIiFGeLdKQcBFPiRlQ6cbCZzF/zLHvZrQwTdxSSVeJNS/GKld P9uEFqyKc/0CSBATOT7xfm0z+hLAPcsNJcExT+7KZXYzmro7QEpfJaFg2Ngk wKYFjU4tF+fH/vzTMHO9yGtFQ3KyPnPxJNz74KdJxrehZ/q03fuTSYiojB1I O81DvKg/Hw1lkVA2+1bbVecpaio5GUjPJ4G5lWntod2O6vkX9f2KSEgu8V/M Me5Aj5ZjlhrLfvoYfPh5xq0TlRIZDVJVJPCMDnnVWHahQvPyMPt6EiQWtuTz F7rQPd+2A/lcEjyrIv8xLO5GKY0zrYYdJAyygmkSpr0oYUI8Oq6XBNdeiw6O Zh+KlVY0H+KTgFgW2Xd29KMIbQ0p+sjPfcJ1fRHTZyjM0bD7wpuf/uZBbc2l ARR87Wh843sSZOS2ZDUM8JFfodsRqSkSZh6Ie5+1HUTevaEK9rMkhE+5iLyU GELuizef530jofvoxGWVhWHkujU39esPElaaT2yXUXiFnExqHAzF1IEv8Sd3 zuE1svPq/DVutTpI8FevKBkaRda33rx+sV4detQ6+ilZb5FF3XwWbaM6pOd4 1/3eMoZM3kq4XtikDt75l7qfn51AhhK/0RqV1WGD1Jfl4tqPyIvdRE3dqg5p v+WobH41jf4F6dZKrA== "]], LineBox[CompressedData[" 1:eJwVz2s4lAkUwHHJE5sopdqQWyrs+75T0RKtjktFDQpRkiSTS6lkRNfFknIp lAYJg0wouZQQjqGGRGoqd7kUM26pTdKNfffDec7z+/Q/R8P9mB1LUkJCwoWe //e4xaXkET8CVNcGrV+8Zxjfn3a3unyCALfyrICukSF8yz0p2xlIQMx8qyFl NRG21Uc2rT5HQI3c/CDrrvcoHE+9wg4lwFTAOzhnph8blxTv5EcQUCLcsTjr aB8K/qpbJB9DQC7XnvtuWS9We3S+cY4n4KeC2IUr7sbyqHEOj0P3fmhOeg91 4v2i2c4TKQTwnLn+67U78F77UhXTDAJWtDutsk5uw1wJ4m0Mj4Djo1ECW4NW zFoN6R13CGg3z17LmXqDqTYO7quLCLARBd141vYaEwO8tNgPCehUDbdJePUK 41PODlZXEGDbkuRzcECI0bWxt+VqCPAOS3AylRVisEIZwWskQK22QZh/6QVe Xzekl/SSgN2vzfrFwma8Y7/MOKqF/j9zu/QY7znWsK3MznUSsJ9Kydka24Rt CaesjvUSkL1tFlslshE/lOTsODBAgM76i+YNV5+hVFu7k/0wAcHKH4378xpw jZLRIYMJAuQzs0pZkk9xi7GPr843ut9dX1FkUo8uLsls5WkC/Nr3X14RXocX U7+HzkiTkFLuabSLFGAq6kZ+mkcCn8/uKot5gvd7nePeKZDw0lBLLvzLY+zV fJRWp0yCvqKWDrTX4qT5SHaZOgk/uFpeWxxqcR5LOT9vJQlTTYIN3a9r0JB3 puIKgwRHx+ZHOwf4aFOfVxuiT8LR0tbn0Ww+egx1NvhvIOGE1fIiBRk+xv6x sd3JnARJhZLRSaNqzGYe6bWyJGG/3TzjJ8WIFb4pImNrEpiiB3V7p6pQfO/n FzUnEkz8y05ZX6tE0K9cKPYhwTMnomW3/CN03DW2rOMYCffG82OlT5XjkZPL NRrZJHD0su8uE5dhYuk5RsF5Epo/O+jGCUvx40YTZlA8CeEvNJzTXpXgHNej 9j4cEswzilXVXUpQ5e9UZ5cUEuLt9K5kiB6gJX/aC7JJWNpj8UVb+gGmb8Zw mXISliz9minFKsaSQ+PR36tIMOXXS1tLFmNjhNq10VoSwKP5Uxm3CKee/p3x oomEnKZ5m+8MFuIOG8DEPvqeycHJ1gsFKOHEn9L+jQLPysJKV607aCgKMAqX p8DRwK5bIyIP/QJ1z/YtoiDBWGlf7mgu9nOuziSpUrDdZPR5Fubg4zbWHFl9 CnZd85C7G8rDi85zFcdcKRi0TRzyPZyJ1cNVu6w8KHBw2ecT8DEDv53259zy pkBHV0dDPjADfW50KbmyKWCr9LpUXuQisytfo/kS7QJdE89TabjA1Z5ReJ+C Gbfd9vHliWj5QdpPrpwCYW7GcMsIB0POVxR5IwVhsjZMkSoH/01d+admAwWj v7M36EYm4Ouerxuv9lCwdcH3NRH+8Zh4IGVbwFwGfA1U2HR07iVUYw2wNrgx IJhI35M77IBTS256udMeGD/8tue6AwrrHQ5H0c4ZEYcsMXfAC8Tj4920RWaJ 6hE37PHD54wzIQcYINhklBrAtMOqULe4p+4M4BpRTLl9tuia3lmxh8UAfJgV 3T9ogYZ2VzGUtvjTSZm4TRa4UGp7TR5t7W2iM6aJ5ijwLK/7Rbt3YgxuW5kh xUgScg8xQBhmK6e0ZxP+qnQUD3ky4FAB6B0c0MeWY/IjC70YEJ10U/HXdT0s 0BCMGdNuDE9PS7Zchx7h6z/H0F5j62vGd2JgI1Nxeq03AwKCvhUyBrQwe/qZ xF7a6q21yjctNTG44J/ZYbRnqRSsWrFbDfUVP8u00K5RM12oNqiI8oJc2Rna 9906Wg86z0dxoLu8tg/df+ppcEsshTU6Sgo7aScl9IDUh4mqlM6Xi07TfhRQ 2lc9xKr6DxYp12M= "]], LineBox[{{-4.704934213297927, -0.8233743709875261}, {-4.704823637894215, 0.9961071659718248}}], LineBox[{{11.003814077359406`, 0.9961071659718248}, { 11.003997488149619`, -0.8233743709875261}}], LineBox[{{14.133998083888605`, 0.9961071659718248}, { 14.134635925211112`, -0.8233743709875261}}], LineBox[{{-11.004599674748953`, -0.8233743709875261}, \ {-11.004471242520308`, 0.9961071659718248}}], LineBox[{{1.5612635862018915`, 0.9961071659718248}, { 1.5612654735285836`, -0.8233743709875261}}], LineBox[{{7.849382822326912, 0.9961071659718248}, { 7.849652275302907, -0.8233743709875261}}], LineBox[{{4.706996096127012, 0.9961071659718248}, { 4.707137759626414, -0.8233743709875261}}], LineBox[{{-14.133185937833868`, -0.8233743709875261}, \ {-14.132688046902109`, 0.9961071659718248}}], LineBox[{{-1.564503968839896, -0.8233743709875261}, {-1.5644547566074356`, 0.9961071659718248}}], LineBox[{{-7.859519138470041, -0.8233743709875261}, {-7.859241366570573, 0.9961071659718248}}]}}, AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948], Axes->True, AxesOrigin->{0, 0}, BaseStyle->{ Thickness[Large]}, PlotRange-> NCache[{{(-5) Pi, 5 Pi}, {-0.8233743709875261, 0.9961071659718248}}, {{-15.707963267948966`, 15.707963267948966`}, {-0.8233743709875261, 0.9961071659718248}}], PlotRangeClipping->True, PlotRangePadding->{ Scaled[0.02], Scaled[0.02]}]], "Output", CellChangeTimes->{{3.3970419077119637`*^9, 3.3970419305097923`*^9}}] }, Open ]], Cell["PlotStyles for each curve", "Text", CellChangeTimes->{{3.39598621117955*^9, 3.395986232114073*^9}, { 3.3959864580368977`*^9, 3.395986468866076*^9}}], Cell[CellGroupData[{ Cell[BoxData[ RowBox[{"Plot", "[", RowBox[{ RowBox[{"{", RowBox[{ RowBox[{ RowBox[{"Sin", "[", "x", "]"}], "/", "x"}], ",", RowBox[{ RowBox[{"Tan", "[", "x", "]"}], "/", "x"}]}], "}"}], ",", RowBox[{"{", RowBox[{"x", ",", RowBox[{ RowBox[{"-", "5"}], "Pi"}], ",", RowBox[{"5", "Pi"}]}], "}"}], ",", StyleBox[ RowBox[{"PlotStyle", "\[Rule]", RowBox[{"{", RowBox[{ RowBox[{"{", RowBox[{"Red", ",", "Thick"}], "}"}], ",", RowBox[{"{", RowBox[{ RowBox[{"Hue", "[", RowBox[{"0.3", ",", "1", ",", ".5"}], "]"}], ",", RowBox[{"Thickness", "[", "0.005", "]"}]}], "}"}]}], "}"}]}], Background->RGBColor[ 0.9014724956130312, 0.9014724956130312, 0.9014724956130312]]}], "]"}]], "Input", CellChangeTimes->{{3.395983012737338*^9, 3.3959831661158037`*^9}, { 3.395984389003924*^9, 3.3959843901079884`*^9}}], Cell[BoxData[ GraphicsBox[{{}, {}, {RGBColor[1, 0, 0], Thickness[Large], LineBox[CompressedData[" 1:eJwVl3k8lN8Xxy0RhZixlW0sM7YhklKqq4VKqyjabFER0jfZlyKyJDtFlGTN MmOZsd9DlhjJTiWRFmWNCln6ze+f53l9Xufce8/7nPM891552+un7Lk4ODhU 2I//vx+/7yR6O26GJtfyEfhuvyfsUwo1wn4zBC5vfz4nfQC5f7c3fGy9GWpz 9EVK5czQyflF99ozm+HxJcW3q0p2iIeo8I5r/2b46rOs26PhhlyM/3saIbUZ 4tOa9q5uv4sMKggaqW2a8P43zbFNIx5pwKBhYbMmkB1/lau/jkebmrMscb0m iMoeCUROCehXz87okXJN2FfRp3QrNxHlztjOkTM14c0OY5UCuUeIoFJSUein CW20Q9fn51PR50RTI9DUhEWlbQxIy0CFmo+UrqhqQkfQqAPPRAbyahriElLS BDthn6U+vedI6I8DPr9RE5jNP+MkOp+jHadv681zawJtqIv8ZikTPSAWqGm+ 1YBPUjYcZL0cZPFilq+3WwMuV/g1qPnlIMX9et982jWgQcZeJLkuB5X/9zKj 5aUGsNaz3ucfykWjnW+l7Qs1INHBjuBwIg/pRfNueBykAeeqx0keu/MRl8rR yX3+GvBEoushyTMfvcYxrO+eGpC5ViSDWJyPbKelQ7e7aED2v2er7YoFKPK4 Dme3hQY4GhGqrqwWIIuvnh+9TDVAZb4tWk2nECn419aQjmtAmrn4A5Urhai8 4LC3y34NmMw4o/CmrRB9ErCe49fUAN2KbGbSgyJU8Dyzk6aiAV+FvxeuqSlC nrvGi8wVNeD9fmL8kx9FSNDJ3SlTUgOmGwdv5cvTkB7r/hcDbg24l/c8x/wW DXFd6nr5bYUKDy2vhWuF0dDrvxLPHixQIfSDklPyYxqyVcuwHJykQrT20BXZ ehqKDKvo9xigAtll0KFnLR3tUh519eqmgofETUsRCTr60SCwzqedCr2h51bG yHR0iMN6l38DFd7e/2tweR8dzaeG9QZgKuwKbZ9ad5KOsvRLXO5UUqHLR/vs oYt0xO3Bm36XRgVhPrmoCHc6KhbV2hnyggpZ1O3u0YF0ZF18tvteFhVaz3GY UB/QUe1kPk/EYyok5j3Zovycjpwj+tLuJ1EhbMOXK8GFdCStyqH3IJa9fgJM epbTkZedqWNMKBVmtobZyrLoSIXLjzsuiArmFlpxb7rpqO9J1uN4fypYDnxL Eh2ko+DdHbqJXlSwH8+XmBylo63vF9uT3KjgeOV3lcU4HY16Kl59dJ093/Ni LfNZOooVP8aZ4kgFLjMzpbEFOpo2eaqTZk2Fcsn7x2FNMUqbbml7cp4KeDlm inddMToaOWeffoYK1ttshoeEitGSmsy/ZyZUCK/g/3iQWIzyXhk9fH6UHX+W as5eiWJ09rKrdtZBKnypnl5ibSpGfGuSW7P3UWG2Uib1q0wxYqS/vJS7mwpi ZetMYkjFyB5NLufpUeHR2cyPLIViJPpBPDFfhwrPlN2JiUrFqN7bYHOhJhXm E9MrpsnF6Iak46siVSqMa/1IH6AUIxIjzoauRAWUXJx2UrkYvTGt+VssRwXe B//umrO1/8+vcaWbqHClxYs6yfanRglrMMSosH3s+nURtn5P3dnEFKaCyZYB tQb2euGtl6wq1lMh/+ypPTyKxUjvauRCJS8VJFVV7/ew4/3Gw4yp5qRCkKLZ orZsMUrMGFarXVaHQaKXs4xUMTLcu64Bz6vD+cjJrkR2Pn4N6Vysm1WH4xfK xdPY+Xrme/FP/aQ6qH6LVdHZUIxMNt2LahhTB87bP/6eZuebo5ym0jSqDihr JJCXpxgVnn5X1zykDvf1TMoP/KOji3Pc51veqsNUYkuC8CIdCcRo/GrtUQfu sjhJR3Z9qzTNI9veqIOpdLGBCbv+jm23Ke2t6pA3NCLcxO6P5rU9Fp2gDvwZ xHoLdj+5Z6787KpSh9/iuxjurXSktF85oofBnm9Pg6dCHR0F+nvX9OerQ7m/ Q4FiAR3t/k1SGHqoDos2MsffBNCRYvP6Nwtx6jD53q8g9SYd8T/640OMUgfB OV/Cv8t01LurrfdQsDqUaN+87XOU3f93PcJKbqhDl+rd21YEOjI9Y7ut3Ukd dkkdjWrloqMdKsdGx66owzpTYYHWWRriaVPYLWupDh6y/FvvddJQKrF9JtRY HfY4Kq/nDKehoC/lqRmG6jC8ztVQ3IOGHJgZxrUG6lAUHrlQd4mGdM97PZ/b xs6/PnP1gz77//FMycJSUR1Eu3ZJXWovQivaPlhnWQ2ivJY4NU8XolHuy07H 59WgU1HhlrdCIWrpPbnRYVYN2pfKXv2bKkAJXpSbaWNqYDifU1EeXIA06jop /L1qcJ1HwGU1Nx9dPKnyYKhADVYn1HfXtueh/QpE/cUcNYjRb3MWjs5Dqr9W vhGfq8FancSj+Sfz0O+k7r2Hk9XgMtNjovFNLor86P+7JEQNrgVmp2Q05qAa l94LYVZqwOmUm6kZk4Vud+q/2XFODSQrXF+57c1CB7Y+2/vDTA1SbXQZKzOZ iLXoQjlirAbmQYr3Px7LRG/v8s0I6KrBE4XhhI3/MtDvZP2g6HVq4PlOR0tj bzrSaE7PTSpThUtV6zu3ZiWiVDmXP5nrVaGoIloyLcQJHwgtV6TzqgLX2m1X rV1v4IkZLpNqTlX4skD7dCjNDe+qT3rRNa8CF2RETE2XvfE7uzrrf6Mq0B94 Vf/xxyAskSfKsqhWATH9DTs+mEbjmK1VT9Y7qwCvk1eZ05pUrJfK81r8qgrE XNilJfw6FQ/znPwrf0kFfPee2HA8IQ1r9X820zurAg39noX7CE9xu5fQOntD FXBTrAnOT0vH67GNW62MCiBRDVPlvOc4+DDf4RvtyvBmv9fca+88vG5/uz6h RRls5tcZhrzPw9G74jVLXioD1XDSKUf/BU7eTBL9Xa4MrkHbA2X/vsCFYnof PTOUodSGoH/7egHuH7ly67anMqTNN8q3SdPwhfcaV+VvKoPjhwz11oM0/Kln 7ly9szL4KJyxu/wfDU80BxisuaQMy9Ymv2420TBHYdL60GPK4GejwFPrQMeq 3s3pUQrKYOUXKPg9pRgX3oyM15JRhgPFtg3qUIy3Opve65RQhvNR0svzo8V4 j/VHJ6KgMkTacW1SUSvBp4zmtyfNUyDwvMKHRloJ7kc1anqzFEgp7D+t01mC L+wIknk7QYEg7vFp0s8SfJm6gVvqEwVcFJw3eG4uxT4E5fa0NgqoevOfnc8s xRwCk4CaKXDtwUHywfpSHMJTUjJcRwFht/AbQkOlOHphzyMFJgUO/qy79Y9Y hp8PnbHLSqdAvO+S+QmvMqw6IG1+8DEFNvYN66GYMlzY+enwWCIFjDdovUrL KcPlDS6b1e5T4ENIuHFubxl+nRfyt8CdAs53z4h0qzBw+IAg59UbFLBVupXS rs/ARrwJaxWcKFByGi7qHWfgWpsM0UQbClzqTw4yvcHA3lFqUicvUMCPauLE HcjA22vo8uvMKZAmGJUkG8vANEnQ9D9Kgdlq6W9xNAZ2Mjqoq3eQAi2J2gUT tQys6tauP7uXAies7RYL2hj42ZvBQ5e3U4B7YjzqylcGtly5dIK0hQIGAVcf Wc4y8Cb18dPvqBT2KdIyu2qFgeNCFm2PK1BA8LyhZyaBiU+W3nbgk6FAhYmP pLY0Ewt8WutaL0GBxepaDxKZiV9tiHL3JVBgQPKg0E0NJr67W9xvmyC7HoVq Fiq6TGxwLTVoZi0FRqov9aJdTLzyUCk8j4sCphG9/BX7mLiy6UW03QoZUi6Z +MUdYmL3X1uSZBfIcPtWSlX7MSbeolCZOjBLBq9n180cTzHx9Im9z2MnyfBc O+S9/Rkmzvd7lXd0jAwj1x6OwVkmvvriBJ13lAyTcvYSPheYWOltHxM+kEFf qGxtvCUTD/Na1noPkOH+LquL662Z+PHWLw1bu8nAp30Mhtn6rK0Ta+o1GWii AYNEGyYWj57rzHlFho01G2yfs+1dNd4Dti/JsD1VjyfWiokfjHN+lK4lg1rq af/Bi0xsvDHsS185GToGxsKCzjMx70HhiegSMmwyTBsLsWDil25Js8aFZPik f8LqqxkT334mu7gmlww7pniY6SeZeFdH5r/aDDLw13DUlB9h4oUVKq9XGhk+ eJTtUzdi4jL1UgGdR2Sou9Mjs4iY+L+z+sTJODKIDR5RUdjBxJr36jdmPyAD VcLYIEubiX+UHibZhLF5VPYeClZl4qxPHRSpu2RIVv5OwSQmltvzUSfKi+2f liy5X5CJB69d3nnYjQynCOFCkVxM/PDRpAH3dTIcVlt6qj3PwMK/l4552JHB USw7OnyIgdsUgsy0rcgwo3l2bk8nA4edXHd+/CwZ7CwDVo69ZGCufMmrVifI 8FJwbJ9vJrvf3z5x2WhMBnnXG1kpCQzss1b5VvcBMhQy/3GKBzPwL1vdwIM7 yWBI6pCXtmXgLxtPPd5MJoNw9jH//0QZOORYzcUDJDL43civHuRgYModFbmz UuzxgZ7PyifK8OWx1fRAETKMcmntbqovw2OMF9m9K0rQcRebo6tlOPSHuMOP BSXgLui13X2S/X3LBqr9m1MCRVaNTNH2MuwYbFGg8kMJThTEfJ1aU4YnTHlK fPqUoPdVvvn3h6X4/j1Xt+hOJXhif+HiA99SrFH1XjezTQlsHgfO5FqVYheF 4vL2eiU4wqPgbKRUimdmLGvli5QgKttrp3x2Cf4VWd7SfE8J4laDW9viinF8 nWLEYKAS5DO+DBKvF2Pd3w+O/vRTgpO2PMVvDxdj9wv2bza5KcGS5nvFzyt0 vKBG6HW2VoJl409mvNZ0vNx8bZi4QwleNRl0SQnS8BouuXmrH4pQnXY9RoqU hwObePzXfVGEHQ/KrYJpuZgjYmJN2UdFcHH9aLWMcvEysZKwrlcRkiVE9KQv 5OBf5NOapVgRFs0pzU5hWfjz4Qh7vgRFaDPazM+ofIYbYua7aUgR2q/qWAps TMBB8h00zgQFMNgpJT1lF4m+jifP8kYrQNxmz7qJ+1HoEMN+q0CEAjSnP1iX 8y4aCRxZYorfUYDyYpuMUO44FO9GwerOChBSNVIRdiYJPW/2fX3aUAHuCZ3w 7l16gpqcVX/k/paHAYPo2OfhOUhF75d60Yw8WDasejqL5KJwLuxcOi4P+G8o 80tSLjqeZPazdoStR2a6+jLyUD8ELHS/lgeepKLsi8x8NEbs413NlIfWBQqV z56G1lUGKp46Iw+Phj++vby/FD0vF/JyNZGHmf+0cyz9StFuZnL7g6PyUHHI aGmZUYpcS4u9WPvkwYV3laqsWoZ6Cz+9ObBZHrYxzKfX8jPQ04x9vtv55MF6 aqSVVsZEO561d57mlgfVTTF7rb4zUdfTc8puqySI9H71+rF0OeJJ+6+L9osE N/rP3cZ3ypHjw2cqaiMkSHGQV/Q1qkC6kVy90pUkaDOzVHxSXonaIx6o6ZeR oJrUsfvR50p0NXzT7bM0EjSmo0IB4SqUfG+LemIWCaZbdB3O2VchjkDbOxvi SBB+fKTImb8aPbo91afxgAT30s93C2lXoy0B3tSjYSRIu7drh5xFNbL3je0P DSCBv9jSdOjzatTqXq/B5USCWnn/GMttNcju1vEg0hUS3BnSRhZna9DKzXcD e2xJsIv7bgXTpwZp3ZgN8rEgQemUVURGbQ1KuKbw7tcBEjSsRAZu2F2LNB0L NxMNSJBJ5LORPF+LXl3dGaytT4IXoeX7/T1r0V/7U1ou2iSoOXxg7AK9Fllb B4Z8kyFBfAtd4rAURv3TYekpkiSQabw4rL0No+MBMdUniCS4ohiiZ3ISo11p T2eZfCSYVbKu0wzEqEQjR9CJmwRwTC/2xyOMTL2tTAyW5cBcf2rLAA0jzXK/ GuFvctDXuHr6wCBG0v335zwH5aCTc/gxzGDE/ydFdaSTbZ+xktXlAvRZpzKB Xi0HQZXL6U9FAXWdamFtLJaDl7MVxttkAMGNAc7AbDlQekEKtyYDSin643wq Vg5GGfGdrlsBhbbzPK+8JwdXg8U/ndYH5D4p+k7BTw6EBnSSX+8FZCegJBzx nxyUPzt3t/8goFPqOkZzV+SAOOajcfMYIAPjfb7nL8qBJlGY/PQUIA0Hk+KX p+SA44DUykVzQJtCrcfUD8lB8ANt4/zzgPiyr8vG75YDV6pPRrgVoD+N/mbL W+TgTHr5swVbNs/nyHA7FTmQ7jT6/NuezcOdCm0ycpDNp7g28CogrJD/ZytR DpIWpvIfOwLK31tFTeWTg9X0X16GTuxrqXWrLc+qLPzcqibm68zmC3j70HlO FnqHdVUMXNh8aWPtvWOycDzxhlUMW9vVzK/ZMyQLBZVTDtfZ+tQgr35Wtyy8 bvNafMseb7AkdkOoRRY2L6XWd7Dn19hEznavlQWLFzm+ptfYfDu2fhgqkQWN 2fwRGwc2n8V+4sFcWbBaCSlcuszmcz91uChNFtKcPz4j2bH5EmwCJOJlITdd 806HNZuv1LUsIEwWZn5iofUX2fXqDhj/5i8L7wZLiR0WgApnH8ifdJNln7/5 zsuZsesnkmZe7iALoX3RxQvH2XxaBZEkKzavKc/4+cNsvhPVL0PNZIG0dbX/ 0H42T+S7zWeRLAg3nqdiXTZP/nf7uq2y0GPofviQJiBN1kKKqposqGwNCTlH AcTPL8H3V1QWXIo1JzaKseNXpuyxXScLjtLLI03r2fEb6bq1/pOBwSiN2GVO drx3TYeTf8jAJpf0Cu53GBVm2IpzD8vAupiw8mcvMUqpv3H0Wq8MKHIdhVP5 GLlzRJfrgwyoFgbCF2+MNHzbogcTZGDB2Z/eL4DRp6yMXX8jZKAhPIXB87MW Pez0HpMIlAGpDK2JSz21aI2yqoGpiwxsdCm2pT+sRYOdwdMtRjLw8lBjf7xE LYpdvpDybZcMmOj1JR/6XYMOKW89yKMjA3tHS5Y0umpQqe+nNAM5GQjufZT1 IKwG3VdGx5nz0qAQYSNBm6pG+06J/+2ZlIY7lvtlFxur0YLvZObsqDRUDStf dH9cjey6UlY0OqQhtHZcdcPBaqTvt5D/PEcaPs/cetQUW4V+dNHXx56Vhq+j v7Tr1lSipyuhzKIT0tDh9m1T2JsKdEbF+tJrQ2k419q8EvmoAtX7CVXxbZEG /dN590zUK1CyyjXHgHXSINnSH91jWI4O+yu1OFVJgfRaJ5E75gy0mrPkFk6X AsuTwx4e4gxU2t1FysmWAkUPPtPynjJEUr3jORrH9u9wc5A5UYYWuj8on3OS gk6D15RY/VKUo5oUclBGCgieCvYyv+hoo7t9TTRBCnZZetv0pdNReL3Or7dr 2faf+L83x+nI6XyHjdPsJhh7SroUmkVDWpH8u2OaN8HGIxdcw5ILEXPGZ+7d jU1wRoXL6/tsDmpiWlu7NG2EO5LVRbscHqHPhmo7E65LgvLLLTkUoVTc8Nf7 obC9JIT8tydx0+s0nFHE+hNxThKaJfDTi0ZPse1G55JAQ0mQkghJH+d9hocn iqiuUpLAISmjqRiRid/H6codaZYAH5vMLNmUfNw1YrCGU04CAuKG8mMtynBx Yoytr6gELMZem9/5qgzHHPkE8/wS8DOlzax4OwOfLAvym/olDo5NZru5xJm4 PbTpz/tWcXiw33xL15ty3LL56HeGuzjM7Tl0O1y3GoOfebtTuxjsNky0Xzpb h6/ucX2W2iAGGffLw91C6/CGf6Hu7ZVi8N3hzZpCRh22vF0pq5UtBm3trtwX CfV4JVDm+lyAGMS0dUeENtXjnaGjG7y1xSCL9JmHS74Bfzq0PJqnLAaF0Y8i J4wbcDi/WPl7GTE4oJPSEOTWgN+GG1nvXicGjKP1V0uaGrBnZC6NY1QUNlPi X/2+3IjLYq+b3IsXhVtTakeWEprwBdNQcnm4KJzhC1khVTbhNaLpi2O3RWHv 4Szz4Q9N2CyhK93YWRTMDcWslZWa8WyS7qygkSg82t4XzHjRjJMtjjft2SUK Y1I1OmFtzXjfxivJ17eIgl1Sm+XERDOOSX64r1NWFPTOu+dbUV9hrdSl2Ph5 IgxIM3+8y3yFBy6KXmmcJEJGR/wewstXOEBWQ//PKBH4POS0Oj++wu1PLEfN O4jQJ3I8YUSiBTs/q9ORyiVC+fGvpzUDW7DopXdrjz4hglVMgc/dlBZcrTj3 3jeBCNa7jjPOlrZggUylu0N3iFB8f3iv3+cWnJd9ryf9HBESf7fOROxpxYLh STqrJ4jQ8766KvB0K3Z1yo49Z0gEO4nHmgPXWrGudvNJohYRXtzdw5Wc2Iof EvuLrpOJUHlb+DP3i1b89/dXobZNREh1XLneXNuKoZL39V0eIsyJXcg487kV K6SKU0f+EiBAq/yj3J9WHBxAidg9QwCZFOLM7rUsbHzA6PCfdwSw7xXsvqnM wgWUMzmnOggQf8/5RNg2Fhbmv7y2qJEAHpkX56YOsHDv6+DGKzS23XyrYpYV C+vREpQaMgmQUJHt8vsaCyfHZgaRUgjAu6nHOtqDhVfcyj75RhPALi9i+FYg C1ubN+59G0yALqeA/uf3Wbh+R+9TXR8CJAUZbZFOZGGy9Jd/Ma4EeHrTfvhd GguHrv6ynLInwMDZ0z0fs1j4x/CaWuPzBCATI7jVCln42EtRmeyTBPh0xv9y eSkL0zKVfLmNCJDzkrYQVsnChNCt7630CbBrqLQ8FbPwLccDO6u1CODCpZsz +5KFB46aPZKkEKDD8C/rXjML79xst+AmRQD+o3PqF1pZOFXEzbxTmAAPBfS7 XdpYmONXEEODlwDzYXIdta9Z2LYvTix8SQRavVS2Hmln4cbyDLevMyIgOSQj SmRrlZSS7n1fRcAkSihUjO0f7vdyy5P3IvCdceaFCYuFJ626Y5Y6RCB2Z9bj plcsfHLf6Ix5kwhkSaz1v9nIwsVKcydKq0Sgv3DUzbyOhcXWchcJ00Xg7T+B vBvVLOz5nSDknCUC4z1wuI7Bwu9YCs4tKSKwcagoyJDGwrsLt7SRY0SAu5o7 YiWHhZ9G71MPDGHH99cucewpC3PdPBU+5CMCvAscwzwPWdj+tO33nTdEwKI+ KtPsAQurbQrMnjsvAk4/dhcEebJw5HIM70kTEVC5zvBlX/XxzFC6fb6RCNQZ ffx0nd0PZRl1ivbaImBqulhG3M/CkiGdgXUUEfBw8X6do8PC3ldHRmSkRcDM tK/DQZGFDTQ4n/bxikDC/OaNzhws/GyDyL8ty8IQ8i+NUjjZinlmSZZRP4XB x7uXJvmuFbcyDKQPDQrDAdKxP1dorfi0we2HFXRhIJis1Rs+1Ypva1o4s7KF wVpTZERCvxXnSWvt+5AqDHEcqoQYhVbMsfhxnCNcGG6E9iQZTbfgfDpCh2yF gZ/Yk1sa0IL7n0iInrMQhjuTxPkpmxbM9WB67NpxYTjRuX7L1f0t2MLxSWzU TmHwOHfQUnxNC16j+O9LH0EYFC+qV57zfYU3i/RXjvEJA1dNT1iwxStcunpR 7vfKBhBrLvpvUucVtmLW/LerbwMM/w0ZuTnWjBkqfhtZIRsgzXKQZH6oGdut X7489k0IVlUui9uMNuLKby+EBXqEQI7yPudESSMWbjhfuRmEwJX71AbvwEZc 5Vsl6PFQCPwisjwDZRsxYcq7lOewEMT+e2h+6VgDho5FTsU8QVAOcpn2DanH 4gW5L4wSBYF5Wd1ax7geO4WdPe0YKAjVk8czlQXrscS+ihz6OUFYd/jv09bo OuxS4nnCYL0gMO7QGjmjAMskzj++6CQAxsbJn363V+OxsoQLA2cEoHhZXG/P lmpc2qsjbbpXABaOCmmy4qrwUTHXlEPiArCSXRrBNKnEvvFjj3RgPeivOvxb Kmfid7FvE/lF10Pcd80tNtuK8cOoquiyKn5wBqDd/ZiE7YrOntTK4ocnIrEp XsnxWOvN/IYX0fzg8x+hzPxEDG4W2hr11J4frsSULn49Foz/ROZHRmzghz+T TwaTwq+g0/dTw20u8UHduaj9x7Y/QYSwgLuC69eCc/JHbf85BqryUoib+M0L 2S3zMiPjTGTn2JjOGuaFU3c9L175Uo7KjqzHYQxecDVoS+p8X4kshJIWeWx5 4UBaaFdjby16ElfoslrOAwe/lj0s8nuJqGkfLKYvr4H2RpVt3X9ZyKhEX6Oz nhP6Rm56fvvdhwKqXJSlijghQFtL7vzOflT+Ml3ePoUTJi30Hd759yP1nrXi izc5Aftc81hYO4CEf3evksic0B3OZ5a86S16t82pw/UeB3DP+7sVG7xHH9x2 fCM9XMUbxQ8GCIV/RJpBSzef5C3imy6ew5+nR9H9TXviRwIWsX1SkWEX4TMa p98uVTy9iFtrXM5k6n5GOcM8v7P/LWDr+Qqjv96fkeIeYXea2QJuWsvgP7nm C5JcVPKsW/2DZfAVL22Rr4jr+nHf0VO/cCL8aBcVHkPWvDGPySq/sIwoX2eB 5hjCqd3VV1bmsKxUQq7UsTHk22axMp49hwW/H/p6M2wMzate8v+1PIvFTxAm +Di+o4nPHrd5sn9iB2LgsXOfv6O8sn38J/5MYutM/g6HkHGUu49vwT9rEr/4 +GRZKnUc5bx5/bXwzCQWMP+y7nHJOMr6btEgxJzAFgbfA9cMj6NnMtcD2j3G sV322zUu2yZQcnDK72OLY9hPfHeL5dsJ9Ihg89kvdwxf8VD70TIxgR4+oXQX nB3Dw1FNG1f/TaDECjpNsPIbJj6yDwfyJIqdbL722vsrNt9vrZDlMokiTv8a Obo8ikNP2ppU/p5E4Z8qOnzzR/G1+LfDiTxTKOx6AM6/MIq1tva56olNoXth 61IFaj7hy8n3XrToTKGgGpJFm98IDu64cE3WZQoFGn81WtYYwZwfygakfafQ nf4XutShYRzVuj5qKGwKBfzcRry/Zxgr+Bqvf/F8Cv0xTn6ctPoBP7F2GbXt n0K/7Mje85Yf8GrOgo776BSa9aeZm+NB3Hg35diR6Sk0VdxEkLj9Hie7SWvs 5J1GXzfNhSZyvsURH+R5KdrT6PNW/8t/bAbwDpGDXPv1p9Gn4/wHztT343Pv J2+TDKfRUKDcP7GgPvzj56ub0hbTqP/HkVsJa3pwv0WqvajPNKqOWGmVuNqN W94GePEHTaNn1CJSMqsLj1SL3oPwaeTiQmhLi+3EM2ZF8m6PppHZhgZ5+T8d eLVGwNv16TTaSbvlkXG2A2/oarPVzJ5GAp/phif3tuNIEjN4qmQaDZDFfprx vcb3fbRjZyqm0fMrno/PvmHvi8FF3SV4GumP75mzvdiCHd78zfBrnUa8Gs/S rii9wsEsaYG7b6ZRlwuPsdN4E56Knzh/pGcaOc6ynt7yasCl9366SH+YRi9y p1M5Yl7iNFKmgvTwNPofj/aE2g== "]], LineBox[CompressedData[" 1:eJwVmHc41e8bx1F21jEyj3msc4zkW8p4bjMzhbLbRhspNFRWSqKUVcoqlHWO ceznkH2oJKWMJAlZCaWS3/n98/lcr+u5x/u+7+fzua7nUTx02smHg42NTY31 +P97aFDxFd/t5+ihwmMl2ZE55HTHf8f88HP0tPd7vtLHORSzi/PBt40taMzh 969fH+bQXJeJ5ej1NvTswLOxrz1zSCVuIG2oqR21xPRlsnXPITeb0Nn+Px1o kq3U4UPbHGK0UFNenuxC7/m1m1/VzaHFyJ3TnU+6kd3nAxUzlXNI3ewbtH58 gdR+HBxnls4h6/2Es8P5r5Cazt0DXTlziDpgR+yT7kW/OvhdRmLmkLS8ulR6 cy/y3hvD8AqfQ1GH1ovtP/UGScpdME08y8o/Wcc72diHYje7SMgdnkNsP7WW /vr3o7F9c0deb59Dx7bzzTcS3qO6S+yt/Lpz6M2l8amYuveIp88/elVlDuWv fzQiLDyAiCnRH/gE59AugnCXCn0IFXqbmbwenEU1e6ZbJw8MI2tp4anel7NI Ja29sZjvI1Kf+x6b0DSL/iYwPGV1RtB9DuUr/+XNolcSYbufRHxCWxInys1O zqIQlSmjGo0xdG6z2tfU6RlEsXKreRA+ht6OnPTcOzCDRvxat17uHUNyXwua ezpmkO2zbD2LS1/QJt+rD9Y9mUFEPU/1F6/G0VLZUoGn5wxqRV2ioyGTKP6P zYhSzTS6cHD77eauSbT5QY7dWO400o3MF8xTnELkHpF6/4RplN4axXuCOYUi +7ZL1R2eRqccjNeWiNMo6JxVfTLvNBL3LJ7ibWXVddd+4ZTtNxRLHKwG8Tl0 vfUhp8Hmb+jvJ97rIUfmkC9/g0GPzDcUWE5LCmKfRz6L+bvOTk8hV0NBvZFH 84iN6fU0Pm4KKdu0nKod/I5Kki4q2DdOorojmycC9y4iQ757itcEJtDsfaGB YZsVpPxmyvOlyRiqW+6Q6ApeQSecEisHZcbQ9d1RTtWPVtAuB3fvl78+IxXu lY6kpRX0fMdvpi/tM/IIGq2yzvqNJMiNX06qfEat1hXJtF9/kCldOMNz/Sh6 uOThFJP3D1n2LEv4nv6I8tR6x5I5OOBXg7JQp+RbpBv1bHPBRg4QtA91GHzZ h2pGIiNqKRzAfSlvHfu1PvQiTV9hZC8HXHygshK99AYt8yd7ajzjgIP/SXek 9/Yii3m317XO66A/gNel924PGqkaxiO560GUsybozZFOdEycLvijej1sztcP PjfQgRYDE7w5X66HK1wlfy84dSBuMvzRWFkP1lKfP1WZtiPtjKwtZxw4wfRk rCqF1IouXj1SxLnMCYni9vxX2ZuQpO1UuuYObhg1uPhPcWs5EknQ+9fjwQ3u /GPUrS5liO/N+YNhp7hB4tLPtj1BNLTqza/efo8brqj3nC6nlqLRQEqFzxg3 2K7554ecf4qK0k69zLzKAyVf+dpvkNKR2eTCuo11vJAYe2feYjYFG2ob+jW8 5AWBlh2lZl/Ssf6ZyE6fz7ywb9iRTHyXgdVWRW+X8/HBw6Zp+ad9WXiDyH9E J3c+6HM9/iL6Rh5+ZxBiEL/MB4G6N0gy26n4ROyfE+s2bYC+nzYKN6Vr8dz1 PTXOVhug6XtSeFtVLQ6KK+HO9dwAama/e3btqcNhtw5nW8RsgPnVXxw21+tx zF3mu+iBDRC9aKtWNohxZuZ9M54YAYi/Kkd0kWzCytlLCW73BeCXqNj9Avcm /CTHcSi/VACkPIz95dObcNGTdaE2AwJQlK30+Zjkc1xTeLzohq4g2GosfjrP 14z7qgwlBQYEIcvBP8+9uQW71dzz8Z4XhO391Ycyfrbgwdo5WhGnEPzj7Sav abTi0YYch526QrBO4uSc7M1WPN/MH5kQLQQRxnN+TZZt+Eyrz6uP6UKgEGP8 8GdgG15uw3K6pUKQXNl8yC6jDa92nql69UEIhsWU1R2/t+HoiZllHklhWL5n EN91qx1bTabLUZWEYcgthO1PWTvmmdph4a4lDIfEdZJs+tvxzW9ZtwvMhMFS z1/HmtiB78zuodieFIauCzl9vY86sMsch/NCiDCw/V6r5m/owOLzJWHpEcLg 0zjq7jvQgVO/87ZNpQhDxLE5v2jRTvxosf5gXJMweAefGjkX1olTJ7MJ4V3C YDww/tImoRPfGb72POCtMKwRtYT353biqPbdpL1TwqC9TcrAqasTh9dveWu9 KAz/LWeyb/rYiUNoMtcM/wlDVXbZR+fvnfjYgy8TCgQRaF2KrvcTZeIjtzvT RGVF4IN5YqW7MhN7x5TYcqmKQEtpWeVtPSbeFRBW+G2bCNgZxQ737WRiW599 3sPmIqDHPC/x2ZOJzT3MBXscRMDmHfs5A38m3mIhEFB5UAS2B7t/qw9nYt1t CwoFx0XAQW5KbS6WiTW03/XcPysCU7evvT92h4mVlOsibl0WgavE8+mb7jOx rGTW5qvXRUBGppXbIoeJxQVixs4kiUBUj1pj9lMmFuQ4fs83QwRWXYWO7qQy Mc9PRyv3PBG4deBB7g46E7NP6/+0o4qA7GqaTEIdE/8ekco3qRWBHW7nQ0mN TLzY989tU4sIWBx28udvYeKZzs+8Ki9FIC+0L920nYnHcXuNxHsRcFnc1dTe ycQj5UXHeT+LwGNGXlJWFxO/L7gj+3daBN73O7R2dTPx64ch3bPLIjDDMBez e8HEXUle4Z/YCDC1ILJdjsWtsaY6b/gIMGTavGzOsseXVEdaxQgQoPeFn8Fk 4qog/tvVRAJ42IQZ3+lgYprfvGmhOgGeOv7eXdvKxIVefQsP9QigGO9EMHrO xI931+TcNiJA4q93NuKYiR9aPXKJsiLA1X07WnfUMHGqYRRnyC4CyIVj1zfl THxH92jlUQ8CRMjWvaotZuI40k4/ryMEyBIU4VrLY+Io6c2SjqcIULzty4uH mUwcLiTZYRpKAM8bResfpDJxyPrVMP0IAnwcVYv8mcDEASufNNVuEmB6bY86 LYaJD39+dnNDJgGkhnmOWQcxsVd/ovFaAQFIMxXdJD8m3tt9dvZ7GQFeT3iN +7D2izUd7XrXRgCztfeDImZMbFaowt7Zw6q3RDXpsj4TG2bx0uoGCCDS6Fji rMrE2nG9otlzBJBQ1Pykx8PE6leqmu+usPo3uvgR/erEimczzl5bJwrFP55L 0L92YrH9fu9ObBSF/dfoYhPNnfi33p/0rUgUvg+rSwWEduJo7K3yy1oUyp17 fJ2PdGJhe0ZRlZMoGIvFBxY7dmJVn2jGNl9R+CS4+/FLlU7slCI0bhgvCn+X zDd/aO/AQ8pBp/8mi0Kg4Ae+lNIO7F/65lddpiiYDT1M6U3pwOEdafwm5aKQ 2e019fJIBy74o7wJBkTBKybz/MKvdqwfG1PD9kUUTi+PLXcMtuMGsUnzxllR UMo2u6rBaMdvtIr3mnGIQfWyInd0dDtmO2Bw0UJDDPItZIS7+NqxW7N9m3WI GEwfHh9LYGvDn3eV7OK9KgZTPgEqx4da8akhkQ8dN8RgW8sp6ZHqVhy1/Hba 9qEYvP2xo+Z+YCsuUT9IcGgRA2P7t9/DBlswV/xZ792i4pBPUT/4NrMZV+x5 +MO9RJy1/wYb9k434igG78JstTi8SNTXbq9pxC7ks/ORzeJw1PP0j5nYRrzI Zj9T9F4cZO8nVHmpNGL9wpVx9vUSUFe7sXvBlYHLOfZ8KHCTAM4TpwLrfesx rYS/cYV9I0R5bPI1u1mJS3jDbqW5SEKcA5ldoCUTV/rLbgzbJwnsu0vKE748 wg1t+JGbvySEmz6/n2L6EL+I5qJuvCgJO8SHJq/+ScfT7Hd77+VIQn3umTPV IXex5u9iyTsLklBRcLLpoE84fjw1ln0jUQqUCrN+TJrfRoU2seRj6VIwOXPp /qOWO6g8n1xukysFTVIfeWss76Jm36AWniopmH8ZfHkNUtDo6NrXmI9SsMkk amhNKQMpDEhrRWpLQ0Hi1mbHHbnoPnMX/UKXNFTSjhd/nSpGEzyr5TrvpOF+ vBX1Q2oJ0rcqoH3+JA35oQH5pUql6AWDvdjupzS4B7e2CXSXIrZKWq6MkgwM mDG+LEjSkG+m2J3aEBnYURCZtO5mOaINMRJOR8iA5Ndb82/flqM16ZPxyvEy YBQ4rDugUIFS77XExmXLQJFUxkoArQIxb5y77NktA30bdA4VMSuR7tn+E3+U ZCGg1VXLq68KXaJFHSvRkgVZycKQAkI16pzT9T9sIAsNcec4xB2r0eFj1w8z HWThBUmaYN5SjZL3b/e4HyoLkxvVCaNPatDog3FXx0hZKNb3IPMM1SCdD3f2 rLslC6VTJx5ZEmpRu8u3XcdzZEH0DDlr3fla9MfmwQ7DF7LA+CpPDzWpQ9bX rC3n+mVBaGsjyepkHbrbvGiW81kWlHu7n5Lu1yFt5GDCvyILXwhveyQX69AB /X/6A8py4EP496MxvR4VBT7VS9CWA5Ev+daEpnr0u3ivrvk2OZitNREOnKhH SRol5Gc75eDf7/osN70G1Eo8oHQhTA54Qt9/aKtpQLa7LJ6GRcrBtuCN5MD+ BvTyqrpeaLwcCL3pkbVaakD9Y/OmZ7PkoKdN+UwQBSMvib6OM8/kQNNY5FmH FUafdlTvDqqQAy6CEtn+AEZTT68ePN0hBzF1MR9fJ2J0atBn8mSvHMzlvhR4 l4fRDwHbwBNDcuB0TSGUqwGjvwGEq0e/y8Fvg/MaX79idCV7mcf/jxzwPWpI TP2D0fo3HxJ9OYlgMW9cs52bgQS25mQeliIClW+d6HtJBrrjf039kDIRZvV+ yfIqMpBE+vHSA1pE4MsyJ79UZ6B0pqPB/q1EcBS13UPWZSDi6maGtykRXkW2 lMttZaBsbUlrLzsiKBo/93lizEBqB/6+9NhDhNjPWTEt5gyk+7z5o+tRIgzp cGe07WSg8sV8v71niLDx9ssPT50ZaJtq/JzLJSLckvwlSXJjoAbXwBDna0Qg kVyvbvFiILPre9Z23ybCUzo3fNzPQK01267tuk+E3xS/SPnDDGQ3LSfk+JgI UjOEiz99GOiVHEeKQwkRdgqNe/n5M5CL4zjRvpoI3j+WPU4fY6D+K51PbJ8T YfTl3SKhEwzkTSvWtukmwsR/lresTzLQ6Oc7lTveEaH7eqOB9CkG8hUPMbH6 RISLgYtTUSyesvJstfjGymfwcyyWxadC0U7zJSLoqwkdVWXxQoHyW9M1IoT3 Pa31ZsULGeDeB7zysPX4fmUdVr6/G6a/mIjKAwx+mUhn6bli8uqksZw88ElK umax9K4PKF8yVJMHZ53ZGjNfBorNSr20fZM8jJy+cPgyq94NvRc5txnKg965 b1muBxjo9vqD8Vst5WHvf5c7mKx+SWyxFN/iKA/ji9d1Bln9TPfTyNB3lwdT y1Pk6y6s+aUJkDYflgeZqXSJXkcGyun8XrjppDwE1l6zr7FlIPW/ffq6IfKw /hJNE1kyUKFWTZ32VXnwLrwvfAix5rn/oYVWnDyctHy+X3kbA1UkRnSR77Hs wx9fiNRjze+H7aB6gTzYTB2mKqqw5kfSOaJWJg8GjdwPDsgyUNte0WlSvTwc rZhdRGKseVUP/FHqkYdNyrb5nzgY6NPlEzJyK/JwM1Jo9TwdowsqX+uD2RUg YItrVHQ2Rly8krMeXAowrNls/vEmRrKvw3aqCSvAQUU78aj9GFkfMRZiKCsA HmccKvrbgHqtT6En6goQ5Obyw260Ae3TenT6ppYC9ISp+5i2NaDgZbZXblsV gPThzqp+QgPKjG1O/G6rAO/GJFW8NjYg8sklxjtHBVjst2O++FmPKnerfq93 UQCaSnJz5rt61CUdu/vGPgUwzfwn53evHv0qtCMoBynAya+pxAzeerSr53WS S5oCpFscHyvvq0UDFeuatz9kcVlyUl5hLfJN119UyFGAHZdE7myIrEUXDye7 zBQqgH5D5D097VqUv+QuHsNQAN7bC2OE8BrEJv0pmf5VAc7tTDzuwFmNSg7N pUlvUYTLxCMxHrUVyKsyd/1xQ0UY87u0LzC8AvHxeZyuBUVYCd1NkTCtQEeo zRZedopg97XbVaSlHEmzpc9lHFCEU1/qxda3l6GYDAtLxThFGDp8M+B2LRXt 60+bVxtRhPCy4i0XXzxFG3Za7PjvhhI83S7Vasx7G729L/5TM0EJjta42m6b TkCPJsefKNxVgtvtx+hurfFIL/o614aHSnDea5fz3IXryLXuRcsoVQlE9AbP Dc5cQdma7haJ75Wgmecc7WfbfMNW7lOm39SV4YFBitmOqETMtgd9H9FSBjEt g88no2/jzmzhrLd6yrDDdYgjN/oO9jIpY2syUobMZVKBeuRdHHH2F07dpQxW Kzf7fgem4q7PESZWocqQXCW3vEEgEx9ipBhmtSnD06TFmhCDPLzz0gyJvVsZ vN3HBDcU5+Ht282FD75WBoNTMcwKpXxMKJ8dUxhShp7kK1kmvAW4Mc/yVuaC MpRD2smBzqdYIeHHyCM5FfhqxBHMSyzGG+xtmGtKKrB2eokTRxbjXzyPKvar q8CeyaqthyaK8csI2xvym1XAyy6wyL+4BIefy9r8yFoFhC57iGckl+Ihb8eY h2dUoIp/u83G31TcLv044F+oCvDMKsqNKdNw+bvfHvvCVSD9eCdJ0oGGb+5+ okO8rgI9Epw3aRk0bGS52p/xkLXepF+YvrUMq3M4P1/NUQFKuCVXnFcZFsP5 Rd4FKqB10/784JUy/M3AJUKuXAWoYtx/HrWV4XTKM3JGhwosW/YHpDiU45hJ NonVFyqw2v0sLvxkOQ56spfN+40KsF/487LxZjm2VeDok/2oAqZf7Cs9Osrx iqh7+INFFbjcEEJu316Bx14V+/9dUYHHrz5mR+ypwK/i1zt7ralAVMjJq/dO V+B87lI1WT4SrE7/mW7KqsBuf7h67suT4IEj5Z3evwq8Iep+3qgKCQ4nKGlZ iFbixg264RqaJHhBPx1OVavEmkR3Ml2fBLH3fXUf7azEH5/MsP/bRoLqV42a 8gcr8V2diH4LRAKV/X3Ov4Mq8So8i35tQ4I7eOle491KTOtAXlKOJPil+PV4 UW4l9nV6o3fAhQQz6a5TP8oq8avDqx9n9pEgqbbmRuKrShw1fbtS/wgJBN49 vDk+VIm3nVWNv3CUBMEln5aTpypxdozjdt5gEiRWeC9ycdDxXqEx4V1hJFjW OHijdQMd86eGfk0OJ4FFl/OtEQk6ZigINAxFkgBfO7VhjwIdBxdk3VW5ToKF b9vFVTToWF1vy/Hjt0jQiRPrHTbR8VBNpyktiQQDYUnE1wZ0fMd8v+RKKgkm M0r2UBEdW3X9mEUPSTC1lhL1zZKOf7vEtsTkkODUtFnPFTs6LhmSfdCdT4KK LV99AnfR8RFfapBYMQnOUlYC6l3oWHLO0sazjASXT6uRfNzouDvkg3x2FQn2 VrhW+3vScQTb6eWJehKMnMjxb/em4y3X13XrPCeBia1LUNR+Ov4mkppzrp0E YtUjUhkH6DgznXK+vpsE5P8mnhAO0rGLcuOu9b0kaLiu4/OFtc5buEfNrp8E oT8f5IqzuEF/avX2EAn2mOpX5+yj46D68Df9oyS4kEn4k+BFx2pWos/kJ0gA j461fnCn48EXeVd9Z0hwfODyhai9dJzoauRWtECCpZLs8HgnOrYYeaW9+JME 1q1kg2UHOl7x9+E0XCWBVUKIGOvwiIu/rwxc5VAFtdxPkRNmdHzo/C1aO7cq HBZi/A4yomOJdcrXhQRUoeHSvu/7/qNjZhx9/16CKlS7rnwu1KJj/YyRDWOy quCX8KwxQJaOJ0hnP2sqqUIgZ1PVVwIdZxTz1gSqqcK1vPbnTTx0zMXQ81vb pAo/3Tnd8hYqca11m7HVVlW4NT7PTxuvxAE9nmLxRqrAE0TRUP5Qid+PRjVK 71CF9uATRENciW8dl0o9aK8KT0I10efSSmy2WHQqf7cqyONHHotZlbiQ853M Fi9VeKybYOgSUYnD1TXO7Q5UBSmN91FEo0q889n728bnVEHGR8L0pGYllte+ UaRxQRU6JOeTjSUrMWPztzH2aFUY+liQ6bNQgTlQkTMtVRWYTwwqvmRW4NeN 3qcfZqjCXfWP5c5xFTjHQjDuRrYqiB+UKbM+W4EtbE83HSpk6e+8GN+5owLH 7Nm0SZTByt/xOsDsazne2//Jfq1ZFWhnC/lWu8uxmucd/28dqkD+PvzYorwc tx/48eh5rypY3TMVDL9cjvlOVAgGf1WFlO1cfqXC5fhWxLbpN4JqoKLN7/OK WIb3cU5xN4qqQc2iHxf+R8M6senKRZJqMMnf6WU9TGP9b/54RCupwXVh8yHt BzRMSKvv+G+LGqBox2s+ojScXGKal+zN8r/BYe40X4ozBm0OuRWqAXFOrf7m 20Kc+CK8qpiqBqtngh5TwwpxBKNMkJOuBsdTU+r/ky3E/rlytdRGNRD3zBzx 3f8M65/4Lsr/Tg1uRKXa1Q8X4K4/qS317OoQ33QZWp8/wX+lJ9SVXdVh6en0 BgmjTOzpHjM3w64BjHPefQHhwfiY5bsbk1wacH2hnW+rfSAO3aSu+oVfA3JH hgRK/juBk3k7vQbFNcD+gPP5V9/24dfVAp2dGhqg7/InbMuQM7KWvpebt1sD RHc2bNgmHo62DOS4H8zSYJ3/NtGuFyUhy7bFRa8nGmCw4MpmdewucimzTHR7 pgHWDv/8t6veQ0FxX1sdKzQgvEayveZ+MioyJOubdGjAcuSz4ccX05DKA5qg zHcN+BRs1PiA8AgRvBufvwFNaKzVKVKuyUVTYrvt6JaawPmvtruE6zFq7Bp5 nWarCU7BV0jZTo9RgBHb6D4XTbDf6OZTNvEYvZRBbJN+LP+8iyH7BPLQzQ91 Rqu3NKHXOMsoZWsBOnLHvvljkiYcd1T/3R9WgAxtB+2aUjVBpFk98lhtAZqq /uNxLVsTll/LLYUYPUU2advDRCo1QTDjhIX0lmeIy62qgjSkCVODjkvnuYrQ sJC1Mc+oJgx40JIoxkWoou1d89S4JpRIufDInilCR7b+7C2Z1wQOoy33SweL 0HOJLQvb1pPB7HFGVPKTYpT+oiVMlpcMX/a/eCX7rhgFxexhXxMgw6P5XQ3v uUqQ0nKwcPNGMnAabESLh0vQlb4y7Z1kMnTGXZSx4ytFbvHmlbq6ZJjVPPvF W74U6Vj2Gov+Rwa7La/ZefVL0XD5gn2/CRkCahI/qXqVIqO7m44fciLDZsWz KaF5pUjMvnHBwpUMpc5xxpbVpejbut3n1bzIcO9C/Nu8zlKUfibg+rQPGXJ0 VD9pTZeiFaeSvHNhZODqkxzboklFi2HPjz4PJ0Mq94mNo9uoaDbzHVk4igxK MtmHBG2oaHR2raTgFhnOZDsfmvShokFxsaDlJDLENLqXppyhordG6vrmaWQ4 tcXNpvUKFXXe2FU1mEOGjNPPK3LSqKiZeuS8RgEZfp4tNnF6TEUN/aFG54rJ MFYVf+lKKRXRVLMYQtVkKAq7UezZQkWFDhURXg2s+H+EgnheUtGT4A6Lgudk kDnmdku/n4rSm763m70gQ7OEfTrfJBXdneSMS+glw7NHm0PK56nolrC0w2A/ az7pLteGflJR7FZtIY1hMhzN/dkR/Y+KIvaZ9Zz9TAarpA+mRetp6GL03qSm CTL0SOssOfPR0LnCY3uEZsmQvi9tJkyIhgJ6wzd6/SDD0HFtA3kxGjr++877 /F9kWHsQ9MX8//cpinn3l1bJEDruyjshQ0MHrGu9zdZRwEnAqJZfnoY8Tr+U T+ChgH7buHiJIg25JH/+NCBAAY3ma1tfK9PQzvqfOeqiFCBll5ueJdGQ9Ri/ 71lJCvh1+rqnqtKQGb+CepMcBVoMVp4YqtGQkZ7+lKAyBbi1VPfuZ/EWd+tC T3UKOLauT17HYt0rXqfytSjQHsuVps7y18wL0F3So8Dd7sW7L1RoSOVF1IKp AQWk5GablpRoiLiUWn7LmAKDZw7vf6hAQ5KyRecGzCgwHij+tF2OhgjmjQbq 1hR4GywyHixNQwLH+n4HO1Cg60Gxe44EDfHcnqxrdKKAdt2NnS4EGuKoWg0X dKPAGb1rIrECNPR3WMTU05ull9ayYMJDQ8ucquvyD1Eg6HuuZRgHDc1Ttrcs +lGgY0f9ga1/qWjKeec105MUyNEfyghboqLhrHP8AyEU2GPotxQ3TkX97Te6 1S5RYLjdq9drmIpezz1MCI6ggMHeox5lfVTUatwmKhhPgYM8VwV+NFER48hA n8cdCixp6ksMVVFRTdxcSl4KBdwoVld3FlNRyfuNsqbZFPDX6nDvSKGip2yU 4fg8CgR+v1jXG0dFuWqQ+aGQArq+G074Xaai1LP+KsF0CtyqCK2nsL6HKyLV lLwuCqRu4lcyIVNRst7k5rQeCpRe2ZtZKsvaz85ShnFvKfBUoiweC7D03wuz OT1CAdWKtYLy2VKkK73dd+siBVYPOQnxFZYiK8NjJzVWWPGK7OROpZciL6/0 YJl/FNDZZFkTFFuKYh/+jljj1oL8rKb+/YdL0YhS7aM2GS3ozK3PeC9WipbN vz2pVtCCg0Ub+Z3YStEGH5niZyQtmOAQ3/PxbQkyyLtQl6CjBTTjueltV0tQ Itnovau5FvBG17zN7i5GoF9PmDimBRIp0RrHrIrQ3j0zUh9Oa4EktZPxgFCE TpyTU+wKZtnfei2pM1yIUqsu6ZSGa0FZnMpA6JlCNG9kYh96RwuS1Xr5O5Of oUxLHM1TowUC3H/tqxoLEJtr4y91Xm04oH7fnqP8MTL4enZ7tKA2zH72Sjx2 9DEKDNG8+ElUGzh4uejOxMdoNCVpLY2oDYwtH+qpMbmoud+Hi19fG5pubaMP 7s5BsR58YjP7tCHp1SGr5d5MJLzPWYdarg0x5k7stTopSN7ni8+2Azqw+J/R 1ZRJF/RLIsP/EIvZiz0q399zQa/bXY7HsbhW73aurJkLiqE0BwyxOPnKgeLc dGc0+yP7wtWDOsBhaxJTb+eEGiIO3O44pAO7dE3CSF6OaF/mQJ27jw6Ecfp+ yhi3QAZOSTiCxbOx8elOyAIR1ts1PWPx+vGLX3lSzVGrX03bKos12sfgvI0Z 0tZJe53lqwOa0b7EETeEVuv3Tkz66cCfVjFepy/66O1pwW8Efx0YDpucm03e jEoVW2cMWVw42iefYK2HjkT/9yOexZ4/C1tprjqoy17s36ajOuCQrutH/qKC nvxjsnmyuPxYmmG6tRK6Uhq5LorFGSGHr8m7ySN9sR88b1l8OWHfmty4GBJs fcq/xuJIthdzhzyE0ETIIUH1Yyz9PXcXcifWoyYNaZHdLFY/kqGzfnbR5MFA j+h5FrcGVH1iTPqY/A9zuUgS "]]}, {Hue[0.3, 1, 0.5], Thickness[0.005], LineBox[CompressedData[" 1:eJwV0Hk41HkcwPFhcpRIsY6irLQ79Pv+RgdG2LWLkrAV6yhkJ7RaOzFFJOKh 5HGUO1e5EoVy5CHx+eQqiYypEWYVtaLoQI5dads/3s/r//e33GP7vSUZDMa+ r/1vzqBA6dRRNjYE1g3juHdT7Eg2FefNRuPcoyJ9TUsIGve2yvFko6Tx5aUS LUfYO7cQ1OTERhXDlEUhywuklLQHJC3YqMWWazQ0OwE8G35e3Do2PvpuKUsz KBoO7jOtz1Fho6LHFeua9rNg7SLdW76ajXKPd/zUrhYD2j5ZzB4ZNvpNffIo uhcLfZHNPsozNMazwrgOrAtgXr+G5D6iMXpKtTaQpAFBsVXFfRoZItc+ejQN 1t4v9oBmGluLO1tt8tJh5smOi8N1NJIX7ofFapeg9AN3etNVGnsE5gKBRjas YVXXV4TRqPZZ+cWupjz4Qof1QjCNu8Pd7i2y8mHCYNfbnuM0+mxLvjaYmg/t FoMa0740es7Xqv/gXwChh5gRRk40diY4Tdw2LIJX6Q47kaZRlHKMX72yBCro TJ0jujRmSgdWemWVQEj7kKSCDo0f3abtf9MrBYVZXzioTmPR2iWJ1H3XwfjX CM4ck8ZfIvpJKJTBssk2lctLBJ9EpsZocsuhO1ruk+UCQcfheXmRTAV41aRX Jr8jOBbE0ZFxvwmJSuV6dD9BVcs9SerqleByY0r2qZCgkVVcY2FwJWy04LwO 7Sb4XqfNzW6gEur4LYUdLQQ7B5atdi+qgpeCfg3vCoJT5h429k41UOG74V+5 UoJnVtgml3XUQLCEd39VIcE81dwsefPboLDlQxojk+C0uP+gn2EtcC5Kr8qJ IsjMDi0ztK8DSZbt5M/hBNdu8dTgDNVBFyR1jgcTVLn+wK2MXw/c9xrnjXgE LbMnDo2W3gESw/UZ+p1g88WtytvtGmB+fYnl2cME42TNnKVmGyDBfpuE0IWg 4V0j/3DXRnAZDX4e4kDQeJN3iVi5CbTDmxq17AnyDebPU31NUFe++xTPgmDA Bp5oqzHCyErP6eU0wcxx/sBH2WYoL7oquMUiuF6TzyqMbYZg07c3nTcSzN8T UEQptoC8X5DfVTWCyqEmJkn6rfCMedfGVomgRENgMa+zFQqyJXSn5Qm6LUiv pnhtwOmM/9ucSTAwZw1jpqsdJA/3trz+TKGTkXj8XPx96PpHtSBxnsJqB7tL ik4P4FKye4TBNIV/zH6ITNvcAVy9Qg/xJIVHjh9wNlF4CKR5zDRqjMKEUw9O 2395CPOu9Dq9lxTGtnsWWDMeQUJsfd/JZxQWbLglnuB0g+n3L/1DhBTmDPn6 qx56DG9aV64I7aZw7sdRk012PZDJNSw83UHhitdmVkGzPWDN8DQNb6XQxqi9 YaRMAHO5sU/PAIVSzEGd5fxeKDap5kXeoTB0cd748S4hOPaLZaJuU7gzo3gk QP8JME9K50ffolC2wvZmJv0UqpT1d5y7QWGK/hA30EoEnlWuwphiChUsTZvE wX2wam+UX2w+hS+WJdWGdz2DpskyqbgcCvtuHKndsHsA/owTXY7PoDBRKOp+ NzUIGroMTmLy1z/jigcWhX/Bw3ZdwYUECpW1Bvkjc88hxMvhaNJ5Cg2CIu+J DYeBJRnGTImiMNDZVru5aAREV4pzUsMp/MjjX6MdXsFZsx6D9BAK91cMfppx HIXtgwvdGSco3Ls54w6zbQyOF9RcWwygcP2WYINvXN/Af5kknM0= "]], LineBox[CompressedData[" 1:eJwVjns4lPkfhoeyQqUNW5ZWprzvzPsOaVHTou+maBwqpUI5ZNFhV1qLNpRI pchSSNqwzoesjENGDt/POGsY50ZCk3KslpJDOv36/fFczx/Pdd33o/3LqX2e sgwGI+Zr/t+RO08HxGt